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False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}, 'configuration': '3d_fullres', 'fold': 0, 'dataset_json': {'channel_names': {'0': 'FLAIR'}, 'labels': {'background': 0, 'Lesion': 1}, 'numTraining': 668, 'file_ending': '.nii.gz', 'overwrite_image_reader_writer': 'SimpleITKIO'}, 'unpack_dataset': True, 'device': device(type='cuda')}", + "network": "OptimizedModule", + "num_epochs": "8000", + "num_input_channels": "1", + "num_iterations_per_epoch": "250", + "num_val_iterations_per_epoch": "50", + "optimizer": "SGD (\nParameter Group 0\n dampening: 0\n differentiable: False\n foreach: None\n initial_lr: 0.01\n lr: 0.01\n maximize: False\n momentum: 0.99\n nesterov: True\n weight_decay: 3e-05\n)", + "output_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_0", + "output_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres", + "oversample_foreground_percent": "0.33", + "plans_manager": "{'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 106, 'patch_size': [160, 192], 'median_image_size_in_voxels': [154.0, 185.0], 'spacing': [0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}", + "preprocessed_dataset_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/nnUNetPlans_3d_fullres", + "preprocessed_dataset_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML", + "save_every": "50", + "torch_version": "2.1.2+cu121", + "unpack_dataset": "True", + "was_initialized": "True", + "weight_decay": "3e-05" +} \ No newline at end of file diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_0/progress.png b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_0/progress.png new file mode 100644 index 0000000000000000000000000000000000000000..7aa729be5ba8fe7a701f41515a1b8f90cc65e117 Binary files /dev/null and b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_0/progress.png differ diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_0/training_log_2024_11_21_10_39_24.txt b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_0/training_log_2024_11_21_10_39_24.txt new file mode 100644 index 0000000000000000000000000000000000000000..f4d364e0e2193b8abb15f83033e37b2a1fd2708e --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_0/training_log_2024_11_21_10_39_24.txt @@ -0,0 +1,56423 @@ + +####################################################################### +Please cite the following paper when using nnU-Net: +Isensee, F., Jaeger, P. F., Kohl, S. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 18(2), 203-211. +####################################################################### + +2024-11-21 10:39:24.177667: do_dummy_2d_data_aug: False +2024-11-21 10:39:24.184099: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-21 10:39:24.197235: The split file contains 5 splits. +2024-11-21 10:39:24.197303: Desired fold for training: 0 +2024-11-21 10:39:24.197354: This split has 534 training and 134 validation cases. +2024-11-21 10:39:27.279661: Using torch.compile... + +This is the configuration used by this training: +Configuration name: 3d_fullres + {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False} + +These are the global plan.json settings: + {'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}} + +2024-11-21 10:39:29.865388: unpacking dataset... +2024-11-21 10:39:48.394335: unpacking done... +2024-11-21 10:39:48.418108: Unable to plot network architecture: nnUNet_compile is enabled! +2024-11-21 10:39:48.426230: +2024-11-21 10:39:48.426367: Epoch 0 +2024-11-21 10:39:48.426579: Current learning rate: 0.01 +2024-11-21 10:40:53.812382: train_loss -0.1992 +2024-11-21 10:40:53.813765: val_loss -0.4986 +2024-11-21 10:40:53.813848: Pseudo dice [0.635] +2024-11-21 10:40:53.813951: Epoch time: 65.39 s +2024-11-21 10:40:53.814047: Yayy! New best EMA pseudo Dice: 0.635 +2024-11-21 10:40:54.680061: +2024-11-21 10:40:54.680281: Epoch 1 +2024-11-21 10:40:54.680391: Current learning rate: 0.01 +2024-11-21 10:41:14.034962: train_loss -0.5068 +2024-11-21 10:41:14.035181: val_loss -0.5935 +2024-11-21 10:41:14.035273: Pseudo dice [0.7069] +2024-11-21 10:41:14.035362: Epoch time: 19.36 s +2024-11-21 10:41:14.035436: Yayy! New best EMA pseudo Dice: 0.6422 +2024-11-21 10:41:15.000530: +2024-11-21 10:41:15.000852: Epoch 2 +2024-11-21 10:41:15.000969: Current learning rate: 0.01 +2024-11-21 10:41:33.969466: train_loss -0.5425 +2024-11-21 10:41:33.969761: val_loss -0.62 +2024-11-21 10:41:33.969840: Pseudo dice [0.7268] +2024-11-21 10:41:33.969921: Epoch time: 18.97 s +2024-11-21 10:41:33.969984: Yayy! New best EMA pseudo Dice: 0.6507 +2024-11-21 10:41:35.587134: +2024-11-21 10:41:35.587354: Epoch 3 +2024-11-21 10:41:35.587478: Current learning rate: 0.01 +2024-11-21 10:41:54.344173: train_loss -0.6049 +2024-11-21 10:41:54.344380: val_loss -0.6495 +2024-11-21 10:41:54.344456: Pseudo dice [0.771] +2024-11-21 10:41:54.344532: Epoch time: 18.76 s +2024-11-21 10:41:54.344592: Yayy! New best EMA pseudo Dice: 0.6627 +2024-11-21 10:41:55.293369: +2024-11-21 10:41:55.293571: Epoch 4 +2024-11-21 10:41:55.293685: Current learning rate: 0.01 +2024-11-21 10:42:12.804469: train_loss -0.6195 +2024-11-21 10:42:12.804676: val_loss -0.6222 +2024-11-21 10:42:12.804749: Pseudo dice [0.7663] +2024-11-21 10:42:12.804821: Epoch time: 17.51 s +2024-11-21 10:42:12.804881: Yayy! New best EMA pseudo Dice: 0.6731 +2024-11-21 10:42:13.788967: +2024-11-21 10:42:13.789234: Epoch 5 +2024-11-21 10:42:13.789356: Current learning rate: 0.00999 +2024-11-21 10:42:32.058324: train_loss -0.643 +2024-11-21 10:42:32.058567: val_loss -0.6612 +2024-11-21 10:42:32.058642: Pseudo dice [0.7794] +2024-11-21 10:42:32.058722: Epoch time: 18.27 s +2024-11-21 10:42:32.058784: Yayy! New best EMA pseudo Dice: 0.6837 +2024-11-21 10:42:33.021643: +2024-11-21 10:42:33.021842: Epoch 6 +2024-11-21 10:42:33.021955: Current learning rate: 0.00999 +2024-11-21 10:42:52.291828: train_loss -0.6413 +2024-11-21 10:42:52.293537: val_loss -0.681 +2024-11-21 10:42:52.293638: Pseudo dice [0.8062] +2024-11-21 10:42:52.293713: Epoch time: 19.27 s +2024-11-21 10:42:52.293779: Yayy! New best EMA pseudo Dice: 0.696 +2024-11-21 10:42:53.258624: +2024-11-21 10:42:53.258816: Epoch 7 +2024-11-21 10:42:53.258931: Current learning rate: 0.00999 +2024-11-21 10:43:11.363387: train_loss -0.6568 +2024-11-21 10:43:11.363603: val_loss -0.7322 +2024-11-21 10:43:11.363682: Pseudo dice [0.811] +2024-11-21 10:43:11.363755: Epoch time: 18.11 s +2024-11-21 10:43:11.363816: Yayy! New best EMA pseudo Dice: 0.7075 +2024-11-21 10:43:12.374785: +2024-11-21 10:43:12.374981: Epoch 8 +2024-11-21 10:43:12.375109: Current learning rate: 0.00999 +2024-11-21 10:43:30.124790: train_loss -0.6504 +2024-11-21 10:43:30.125022: val_loss -0.676 +2024-11-21 10:43:30.125097: Pseudo dice [0.7686] +2024-11-21 10:43:30.125170: Epoch time: 17.75 s +2024-11-21 10:43:30.125231: Yayy! New best EMA pseudo Dice: 0.7136 +2024-11-21 10:43:31.099418: +2024-11-21 10:43:31.099625: Epoch 9 +2024-11-21 10:43:31.099735: Current learning rate: 0.00999 +2024-11-21 10:43:49.279574: train_loss -0.6733 +2024-11-21 10:43:49.279802: val_loss -0.7134 +2024-11-21 10:43:49.279907: Pseudo dice [0.8101] +2024-11-21 10:43:49.279995: Epoch time: 18.18 s +2024-11-21 10:43:49.280061: Yayy! New best EMA pseudo Dice: 0.7232 +2024-11-21 10:43:50.234435: +2024-11-21 10:43:50.234636: Epoch 10 +2024-11-21 10:43:50.234748: Current learning rate: 0.00999 +2024-11-21 10:44:08.098053: train_loss -0.6788 +2024-11-21 10:44:08.098277: val_loss -0.6752 +2024-11-21 10:44:08.098348: Pseudo dice [0.7926] +2024-11-21 10:44:08.098420: Epoch time: 17.86 s +2024-11-21 10:44:08.098479: Yayy! New best EMA pseudo Dice: 0.7302 +2024-11-21 10:44:09.061152: +2024-11-21 10:44:09.061366: Epoch 11 +2024-11-21 10:44:09.061481: Current learning rate: 0.00999 +2024-11-21 10:44:27.875690: train_loss -0.6686 +2024-11-21 10:44:27.875895: val_loss -0.674 +2024-11-21 10:44:27.875968: Pseudo dice [0.7914] +2024-11-21 10:44:27.876049: Epoch time: 18.82 s +2024-11-21 10:44:27.876112: Yayy! New best EMA pseudo Dice: 0.7363 +2024-11-21 10:44:28.855842: +2024-11-21 10:44:28.856047: Epoch 12 +2024-11-21 10:44:28.856159: Current learning rate: 0.00999 +2024-11-21 10:44:48.329154: train_loss -0.6659 +2024-11-21 10:44:48.329395: val_loss -0.71 +2024-11-21 10:44:48.329468: Pseudo dice [0.8142] +2024-11-21 10:44:48.329549: Epoch time: 19.47 s +2024-11-21 10:44:48.329614: Yayy! New best EMA pseudo Dice: 0.7441 +2024-11-21 10:44:49.346240: +2024-11-21 10:44:49.346431: Epoch 13 +2024-11-21 10:44:49.346541: Current learning rate: 0.00999 +2024-11-21 10:45:07.190275: train_loss -0.6683 +2024-11-21 10:45:07.190486: val_loss -0.6945 +2024-11-21 10:45:07.190565: Pseudo dice [0.7928] +2024-11-21 10:45:07.190640: Epoch time: 17.84 s +2024-11-21 10:45:07.190701: Yayy! New best EMA pseudo Dice: 0.7489 +2024-11-21 10:45:08.578221: +2024-11-21 10:45:08.578438: Epoch 14 +2024-11-21 10:45:08.578561: Current learning rate: 0.00998 +2024-11-21 10:45:25.924576: train_loss -0.6712 +2024-11-21 10:45:25.924800: val_loss -0.6933 +2024-11-21 10:45:25.924874: Pseudo dice [0.7823] +2024-11-21 10:45:25.924946: Epoch time: 17.35 s +2024-11-21 10:45:25.925013: Yayy! New best EMA pseudo Dice: 0.7523 +2024-11-21 10:45:26.919145: +2024-11-21 10:45:26.919337: Epoch 15 +2024-11-21 10:45:26.919444: Current learning rate: 0.00998 +2024-11-21 10:45:44.985825: train_loss -0.6774 +2024-11-21 10:45:44.986067: val_loss -0.714 +2024-11-21 10:45:44.986143: Pseudo dice [0.8152] +2024-11-21 10:45:44.986223: Epoch time: 18.07 s +2024-11-21 10:45:44.986286: Yayy! New best EMA pseudo Dice: 0.7586 +2024-11-21 10:45:45.956204: +2024-11-21 10:45:45.956412: Epoch 16 +2024-11-21 10:45:45.956534: Current learning rate: 0.00998 +2024-11-21 10:46:03.485296: train_loss -0.6811 +2024-11-21 10:46:03.485493: val_loss -0.682 +2024-11-21 10:46:03.485575: Pseudo dice [0.8074] +2024-11-21 10:46:03.487510: Epoch time: 17.53 s +2024-11-21 10:46:03.487734: Yayy! New best EMA pseudo Dice: 0.7635 +2024-11-21 10:46:04.540410: +2024-11-21 10:46:04.540616: Epoch 17 +2024-11-21 10:46:04.540730: Current learning rate: 0.00998 +2024-11-21 10:46:22.953231: train_loss -0.6798 +2024-11-21 10:46:22.953448: val_loss -0.7091 +2024-11-21 10:46:22.953520: Pseudo dice [0.808] +2024-11-21 10:46:22.953594: Epoch time: 18.41 s +2024-11-21 10:46:22.953655: Yayy! New best EMA pseudo Dice: 0.7679 +2024-11-21 10:46:23.932674: +2024-11-21 10:46:23.932861: Epoch 18 +2024-11-21 10:46:23.932966: Current learning rate: 0.00998 +2024-11-21 10:46:42.495401: train_loss -0.7024 +2024-11-21 10:46:42.495611: val_loss -0.7364 +2024-11-21 10:46:42.495687: Pseudo dice [0.806] +2024-11-21 10:46:42.495762: Epoch time: 18.56 s +2024-11-21 10:46:42.495826: Yayy! New best EMA pseudo Dice: 0.7717 +2024-11-21 10:46:43.464784: +2024-11-21 10:46:43.464979: Epoch 19 +2024-11-21 10:46:43.465092: Current learning rate: 0.00998 +2024-11-21 10:47:01.016868: train_loss -0.6807 +2024-11-21 10:47:01.017113: val_loss -0.7174 +2024-11-21 10:47:01.017190: Pseudo dice [0.8159] +2024-11-21 10:47:01.017272: Epoch time: 17.55 s +2024-11-21 10:47:01.017337: Yayy! New best EMA pseudo Dice: 0.7762 +2024-11-21 10:47:01.993856: +2024-11-21 10:47:01.994043: Epoch 20 +2024-11-21 10:47:01.994156: Current learning rate: 0.00998 +2024-11-21 10:47:19.702212: train_loss -0.7048 +2024-11-21 10:47:19.702427: val_loss -0.7412 +2024-11-21 10:47:19.702498: Pseudo dice [0.8238] +2024-11-21 10:47:19.702572: Epoch time: 17.71 s +2024-11-21 10:47:19.702634: Yayy! New best EMA pseudo Dice: 0.7809 +2024-11-21 10:47:20.689037: +2024-11-21 10:47:20.689217: Epoch 21 +2024-11-21 10:47:20.689325: Current learning rate: 0.00998 +2024-11-21 10:47:38.929436: train_loss -0.6788 +2024-11-21 10:47:38.929677: val_loss -0.6946 +2024-11-21 10:47:38.929752: Pseudo dice [0.7915] +2024-11-21 10:47:38.929825: Epoch time: 18.24 s +2024-11-21 10:47:38.929885: Yayy! New best EMA pseudo Dice: 0.782 +2024-11-21 10:47:39.863872: +2024-11-21 10:47:39.864075: Epoch 22 +2024-11-21 10:47:39.864192: Current learning rate: 0.00998 +2024-11-21 10:47:58.171293: train_loss -0.6944 +2024-11-21 10:47:58.171513: val_loss -0.7388 +2024-11-21 10:47:58.171585: Pseudo dice [0.7977] +2024-11-21 10:47:58.171655: Epoch time: 18.31 s +2024-11-21 10:47:58.171712: Yayy! New best EMA pseudo Dice: 0.7835 +2024-11-21 10:47:59.152120: +2024-11-21 10:47:59.152332: Epoch 23 +2024-11-21 10:47:59.152442: Current learning rate: 0.00997 +2024-11-21 10:48:17.524086: train_loss -0.6997 +2024-11-21 10:48:17.524315: val_loss -0.7455 +2024-11-21 10:48:17.524388: Pseudo dice [0.8145] +2024-11-21 10:48:17.524466: Epoch time: 18.37 s +2024-11-21 10:48:17.524531: Yayy! New best EMA pseudo Dice: 0.7866 +2024-11-21 10:48:18.465724: +2024-11-21 10:48:18.465951: Epoch 24 +2024-11-21 10:48:18.466073: Current learning rate: 0.00997 +2024-11-21 10:48:37.498130: train_loss -0.7121 +2024-11-21 10:48:37.498326: val_loss -0.6715 +2024-11-21 10:48:37.498400: Pseudo dice [0.7924] +2024-11-21 10:48:37.498475: Epoch time: 19.03 s +2024-11-21 10:48:37.498537: Yayy! New best EMA pseudo Dice: 0.7872 +2024-11-21 10:48:38.448064: +2024-11-21 10:48:38.448280: Epoch 25 +2024-11-21 10:48:38.448398: Current learning rate: 0.00997 +2024-11-21 10:48:57.081673: train_loss -0.6934 +2024-11-21 10:48:57.081899: val_loss -0.7374 +2024-11-21 10:48:57.081982: Pseudo dice [0.813] +2024-11-21 10:48:57.082060: Epoch time: 18.63 s +2024-11-21 10:48:57.082124: Yayy! New best EMA pseudo Dice: 0.7898 +2024-11-21 10:48:58.034064: +2024-11-21 10:48:58.034352: Epoch 26 +2024-11-21 10:48:58.034479: Current learning rate: 0.00997 +2024-11-21 10:49:16.552759: train_loss -0.6865 +2024-11-21 10:49:16.553005: val_loss -0.7382 +2024-11-21 10:49:16.553081: Pseudo dice [0.8255] +2024-11-21 10:49:16.553158: Epoch time: 18.52 s +2024-11-21 10:49:16.553219: Yayy! New best EMA pseudo Dice: 0.7934 +2024-11-21 10:49:17.521631: +2024-11-21 10:49:17.521816: Epoch 27 +2024-11-21 10:49:17.521923: Current learning rate: 0.00997 +2024-11-21 10:49:35.681336: train_loss -0.6907 +2024-11-21 10:49:35.681546: val_loss -0.7309 +2024-11-21 10:49:35.681623: Pseudo dice [0.8235] +2024-11-21 10:49:35.681697: Epoch time: 18.16 s +2024-11-21 10:49:35.681760: Yayy! New best EMA pseudo Dice: 0.7964 +2024-11-21 10:49:36.633785: +2024-11-21 10:49:36.633997: Epoch 28 +2024-11-21 10:49:36.634106: Current learning rate: 0.00997 +2024-11-21 10:49:56.169455: train_loss -0.6903 +2024-11-21 10:49:56.169679: val_loss -0.7016 +2024-11-21 10:49:56.169756: Pseudo dice [0.8011] +2024-11-21 10:49:56.169829: Epoch time: 19.54 s +2024-11-21 10:49:56.169896: Yayy! New best EMA pseudo Dice: 0.7969 +2024-11-21 10:49:57.125663: +2024-11-21 10:49:57.125842: Epoch 29 +2024-11-21 10:49:57.125953: Current learning rate: 0.00997 +2024-11-21 10:50:15.498322: train_loss -0.7046 +2024-11-21 10:50:15.498583: val_loss -0.7298 +2024-11-21 10:50:15.498663: Pseudo dice [0.8133] +2024-11-21 10:50:15.498745: Epoch time: 18.37 s +2024-11-21 10:50:15.498808: Yayy! New best EMA pseudo Dice: 0.7985 +2024-11-21 10:50:16.454919: +2024-11-21 10:50:16.455117: Epoch 30 +2024-11-21 10:50:16.455228: Current learning rate: 0.00997 +2024-11-21 10:50:35.258361: train_loss -0.7045 +2024-11-21 10:50:35.258587: val_loss -0.7099 +2024-11-21 10:50:35.258662: Pseudo dice [0.8039] +2024-11-21 10:50:35.258762: Epoch time: 18.8 s +2024-11-21 10:50:35.258824: Yayy! New best EMA pseudo Dice: 0.799 +2024-11-21 10:50:36.226816: +2024-11-21 10:50:36.227032: Epoch 31 +2024-11-21 10:50:36.227143: Current learning rate: 0.00997 +2024-11-21 10:50:54.131814: train_loss -0.6882 +2024-11-21 10:50:54.132027: val_loss -0.7197 +2024-11-21 10:50:54.132101: Pseudo dice [0.8101] +2024-11-21 10:50:54.132174: Epoch time: 17.91 s +2024-11-21 10:50:54.132236: Yayy! New best EMA pseudo Dice: 0.8001 +2024-11-21 10:50:55.118522: +2024-11-21 10:50:55.118733: Epoch 32 +2024-11-21 10:50:55.118849: Current learning rate: 0.00996 +2024-11-21 10:51:15.438877: train_loss -0.7043 +2024-11-21 10:51:15.439090: val_loss -0.6975 +2024-11-21 10:51:15.439166: Pseudo dice [0.7931] +2024-11-21 10:51:15.439239: Epoch time: 20.32 s +2024-11-21 10:51:16.210362: +2024-11-21 10:51:16.210589: Epoch 33 +2024-11-21 10:51:16.210716: Current learning rate: 0.00996 +2024-11-21 10:51:34.589323: train_loss -0.7161 +2024-11-21 10:51:34.589557: val_loss -0.7383 +2024-11-21 10:51:34.589635: Pseudo dice [0.8268] +2024-11-21 10:51:34.589716: Epoch time: 18.38 s +2024-11-21 10:51:34.589782: Yayy! New best EMA pseudo Dice: 0.8022 +2024-11-21 10:51:35.558403: +2024-11-21 10:51:35.558591: Epoch 34 +2024-11-21 10:51:35.558719: Current learning rate: 0.00996 +2024-11-21 10:51:54.867471: train_loss -0.6958 +2024-11-21 10:51:54.867687: val_loss -0.7279 +2024-11-21 10:51:54.867760: Pseudo dice [0.8194] +2024-11-21 10:51:54.867834: Epoch time: 19.31 s +2024-11-21 10:51:54.867896: Yayy! New best EMA pseudo Dice: 0.8039 +2024-11-21 10:51:55.843400: +2024-11-21 10:51:55.843609: Epoch 35 +2024-11-21 10:51:55.843719: Current learning rate: 0.00996 +2024-11-21 10:52:14.245907: train_loss -0.7144 +2024-11-21 10:52:14.246124: val_loss -0.7215 +2024-11-21 10:52:14.246199: Pseudo dice [0.8072] +2024-11-21 10:52:14.246271: Epoch time: 18.4 s +2024-11-21 10:52:14.246333: Yayy! New best EMA pseudo Dice: 0.8042 +2024-11-21 10:52:15.252961: +2024-11-21 10:52:15.253175: Epoch 36 +2024-11-21 10:52:15.253285: Current learning rate: 0.00996 +2024-11-21 10:52:33.917873: train_loss -0.7034 +2024-11-21 10:52:33.918201: val_loss -0.7184 +2024-11-21 10:52:33.918286: Pseudo dice [0.8198] +2024-11-21 10:52:33.918370: Epoch time: 18.67 s +2024-11-21 10:52:33.918434: Yayy! New best EMA pseudo Dice: 0.8058 +2024-11-21 10:52:34.914261: +2024-11-21 10:52:34.914459: Epoch 37 +2024-11-21 10:52:34.914572: Current learning rate: 0.00996 +2024-11-21 10:52:52.852510: train_loss -0.7243 +2024-11-21 10:52:52.852742: val_loss -0.713 +2024-11-21 10:52:52.852816: Pseudo dice [0.8185] +2024-11-21 10:52:52.852893: Epoch time: 17.94 s +2024-11-21 10:52:52.852955: Yayy! New best EMA pseudo Dice: 0.8071 +2024-11-21 10:52:53.862936: +2024-11-21 10:52:53.863137: Epoch 38 +2024-11-21 10:52:53.863250: Current learning rate: 0.00996 +2024-11-21 10:53:12.222163: train_loss -0.7197 +2024-11-21 10:53:12.222372: val_loss -0.7272 +2024-11-21 10:53:12.222448: Pseudo dice [0.8225] +2024-11-21 10:53:12.222524: Epoch time: 18.36 s +2024-11-21 10:53:12.222586: Yayy! New best EMA pseudo Dice: 0.8086 +2024-11-21 10:53:13.224849: +2024-11-21 10:53:13.225055: Epoch 39 +2024-11-21 10:53:13.225168: Current learning rate: 0.00996 +2024-11-21 10:53:30.300570: train_loss -0.7185 +2024-11-21 10:53:30.300814: val_loss -0.7549 +2024-11-21 10:53:30.300891: Pseudo dice [0.8233] +2024-11-21 10:53:30.300968: Epoch time: 17.08 s +2024-11-21 10:53:30.301035: Yayy! New best EMA pseudo Dice: 0.8101 +2024-11-21 10:53:31.520927: +2024-11-21 10:53:31.521279: Epoch 40 +2024-11-21 10:53:31.521396: Current learning rate: 0.00995 +2024-11-21 10:53:49.906613: train_loss -0.7258 +2024-11-21 10:53:49.906858: val_loss -0.7546 +2024-11-21 10:53:49.906938: Pseudo dice [0.822] +2024-11-21 10:53:49.907029: Epoch time: 18.39 s +2024-11-21 10:53:49.912297: Yayy! New best EMA pseudo Dice: 0.8113 +2024-11-21 10:53:50.927046: +2024-11-21 10:53:50.927239: Epoch 41 +2024-11-21 10:53:50.927349: Current learning rate: 0.00995 +2024-11-21 10:54:09.350044: train_loss -0.7182 +2024-11-21 10:54:09.350304: val_loss -0.7492 +2024-11-21 10:54:09.350379: Pseudo dice [0.8218] +2024-11-21 10:54:09.350453: Epoch time: 18.42 s +2024-11-21 10:54:09.350514: Yayy! New best EMA pseudo Dice: 0.8123 +2024-11-21 10:54:10.300957: +2024-11-21 10:54:10.301178: Epoch 42 +2024-11-21 10:54:10.301291: Current learning rate: 0.00995 +2024-11-21 10:54:28.064659: train_loss -0.7119 +2024-11-21 10:54:28.064873: val_loss -0.7499 +2024-11-21 10:54:28.064946: Pseudo dice [0.8265] +2024-11-21 10:54:28.065025: Epoch time: 17.76 s +2024-11-21 10:54:28.065084: Yayy! New best EMA pseudo Dice: 0.8137 +2024-11-21 10:54:29.077229: +2024-11-21 10:54:29.077428: Epoch 43 +2024-11-21 10:54:29.077538: Current learning rate: 0.00995 +2024-11-21 10:54:47.453415: train_loss -0.7152 +2024-11-21 10:54:47.455837: val_loss -0.717 +2024-11-21 10:54:47.455985: Pseudo dice [0.8144] +2024-11-21 10:54:47.456080: Epoch time: 18.38 s +2024-11-21 10:54:47.456156: Yayy! New best EMA pseudo Dice: 0.8138 +2024-11-21 10:54:48.471361: +2024-11-21 10:54:48.471591: Epoch 44 +2024-11-21 10:54:48.471705: Current learning rate: 0.00995 +2024-11-21 10:55:06.200161: train_loss -0.7149 +2024-11-21 10:55:06.200388: val_loss -0.7405 +2024-11-21 10:55:06.200459: Pseudo dice [0.8297] +2024-11-21 10:55:06.200538: Epoch time: 17.73 s +2024-11-21 10:55:06.200600: Yayy! New best EMA pseudo Dice: 0.8154 +2024-11-21 10:55:07.172560: +2024-11-21 10:55:07.172747: Epoch 45 +2024-11-21 10:55:07.172854: Current learning rate: 0.00995 +2024-11-21 10:55:25.758228: train_loss -0.7134 +2024-11-21 10:55:25.758443: val_loss -0.73 +2024-11-21 10:55:25.758579: Pseudo dice [0.811] +2024-11-21 10:55:25.758656: Epoch time: 18.59 s +2024-11-21 10:55:26.515382: +2024-11-21 10:55:26.515596: Epoch 46 +2024-11-21 10:55:26.515707: Current learning rate: 0.00995 +2024-11-21 10:55:44.760506: train_loss -0.7244 +2024-11-21 10:55:44.760718: val_loss -0.7493 +2024-11-21 10:55:44.760792: Pseudo dice [0.8176] +2024-11-21 10:55:44.760867: Epoch time: 18.25 s +2024-11-21 10:55:45.514912: +2024-11-21 10:55:45.515130: Epoch 47 +2024-11-21 10:55:45.515243: Current learning rate: 0.00995 +2024-11-21 10:56:05.563498: train_loss -0.7258 +2024-11-21 10:56:05.563738: val_loss -0.7343 +2024-11-21 10:56:05.563812: Pseudo dice [0.8266] +2024-11-21 10:56:05.563893: Epoch time: 20.05 s +2024-11-21 10:56:05.563954: Yayy! New best EMA pseudo Dice: 0.8164 +2024-11-21 10:56:06.856125: +2024-11-21 10:56:06.856333: Epoch 48 +2024-11-21 10:56:06.856441: Current learning rate: 0.00995 +2024-11-21 10:56:24.266277: train_loss -0.7186 +2024-11-21 10:56:24.266543: val_loss -0.7444 +2024-11-21 10:56:24.266617: Pseudo dice [0.844] +2024-11-21 10:56:24.266689: Epoch time: 17.41 s +2024-11-21 10:56:24.266749: Yayy! New best EMA pseudo Dice: 0.8191 +2024-11-21 10:56:25.238610: +2024-11-21 10:56:25.238803: Epoch 49 +2024-11-21 10:56:25.238916: Current learning rate: 0.00994 +2024-11-21 10:56:44.827910: train_loss -0.7222 +2024-11-21 10:56:44.828139: val_loss -0.7472 +2024-11-21 10:56:44.828212: Pseudo dice [0.8182] +2024-11-21 10:56:44.828285: Epoch time: 19.59 s +2024-11-21 10:56:45.858385: +2024-11-21 10:56:45.858716: Epoch 50 +2024-11-21 10:56:45.858828: Current learning rate: 0.00994 +2024-11-21 10:57:03.617849: train_loss -0.7255 +2024-11-21 10:57:03.618087: val_loss -0.7564 +2024-11-21 10:57:03.618163: Pseudo dice [0.8278] +2024-11-21 10:57:03.618244: Epoch time: 17.76 s +2024-11-21 10:57:03.618308: Yayy! New best EMA pseudo Dice: 0.8199 +2024-11-21 10:57:04.571916: +2024-11-21 10:57:04.572130: Epoch 51 +2024-11-21 10:57:04.572239: Current learning rate: 0.00994 +2024-11-21 10:57:23.300908: train_loss -0.7174 +2024-11-21 10:57:23.301126: val_loss -0.7386 +2024-11-21 10:57:23.301203: Pseudo dice [0.8292] +2024-11-21 10:57:23.301277: Epoch time: 18.73 s +2024-11-21 10:57:23.301338: Yayy! New best EMA pseudo Dice: 0.8208 +2024-11-21 10:57:24.265633: +2024-11-21 10:57:24.265845: Epoch 52 +2024-11-21 10:57:24.265958: Current learning rate: 0.00994 +2024-11-21 10:57:42.124960: train_loss -0.7142 +2024-11-21 10:57:42.125177: val_loss -0.7149 +2024-11-21 10:57:42.125254: Pseudo dice [0.8148] +2024-11-21 10:57:42.125326: Epoch time: 17.86 s +2024-11-21 10:57:42.889972: +2024-11-21 10:57:42.890182: Epoch 53 +2024-11-21 10:57:42.890293: Current learning rate: 0.00994 +2024-11-21 10:58:01.592149: train_loss -0.7266 +2024-11-21 10:58:01.592362: val_loss -0.7337 +2024-11-21 10:58:01.592433: Pseudo dice [0.8154] +2024-11-21 10:58:01.592507: Epoch time: 18.7 s +2024-11-21 10:58:02.516583: +2024-11-21 10:58:02.516815: Epoch 54 +2024-11-21 10:58:02.516937: Current learning rate: 0.00994 +2024-11-21 10:58:20.933472: train_loss -0.7275 +2024-11-21 10:58:20.933725: val_loss -0.7364 +2024-11-21 10:58:20.933802: Pseudo dice [0.8181] +2024-11-21 10:58:20.933897: Epoch time: 18.42 s +2024-11-21 10:58:21.702665: +2024-11-21 10:58:21.702873: Epoch 55 +2024-11-21 10:58:21.702981: Current learning rate: 0.00994 +2024-11-21 10:58:40.611177: train_loss -0.7121 +2024-11-21 10:58:40.611384: val_loss -0.7344 +2024-11-21 10:58:40.611458: Pseudo dice [0.8066] +2024-11-21 10:58:40.611531: Epoch time: 18.91 s +2024-11-21 10:58:41.371903: +2024-11-21 10:58:41.372096: Epoch 56 +2024-11-21 10:58:41.372200: Current learning rate: 0.00994 +2024-11-21 10:58:59.252624: train_loss -0.7302 +2024-11-21 10:58:59.252835: val_loss -0.7017 +2024-11-21 10:58:59.252906: Pseudo dice [0.8324] +2024-11-21 10:58:59.252977: Epoch time: 17.88 s +2024-11-21 10:59:00.009228: +2024-11-21 10:59:00.009440: Epoch 57 +2024-11-21 10:59:00.009551: Current learning rate: 0.00994 +2024-11-21 10:59:17.744261: train_loss -0.7339 +2024-11-21 10:59:17.744472: val_loss -0.7503 +2024-11-21 10:59:17.744550: Pseudo dice [0.8131] +2024-11-21 10:59:17.744627: Epoch time: 17.74 s +2024-11-21 10:59:18.508909: +2024-11-21 10:59:18.509122: Epoch 58 +2024-11-21 10:59:18.509234: Current learning rate: 0.00993 +2024-11-21 10:59:37.151611: train_loss -0.7263 +2024-11-21 10:59:37.151895: val_loss -0.7227 +2024-11-21 10:59:37.151970: Pseudo dice [0.8284] +2024-11-21 10:59:37.152053: Epoch time: 18.64 s +2024-11-21 10:59:38.317569: +2024-11-21 10:59:38.317760: Epoch 59 +2024-11-21 10:59:38.317867: Current learning rate: 0.00993 +2024-11-21 10:59:56.004878: train_loss -0.7256 +2024-11-21 10:59:56.005110: val_loss -0.7347 +2024-11-21 10:59:56.005186: Pseudo dice [0.8367] +2024-11-21 10:59:56.005265: Epoch time: 17.69 s +2024-11-21 10:59:56.005325: Yayy! New best EMA pseudo Dice: 0.8216 +2024-11-21 10:59:56.991907: +2024-11-21 10:59:56.992124: Epoch 60 +2024-11-21 10:59:56.992231: Current learning rate: 0.00993 +2024-11-21 11:00:16.816941: train_loss -0.731 +2024-11-21 11:00:16.817191: val_loss -0.7339 +2024-11-21 11:00:16.817267: Pseudo dice [0.8149] +2024-11-21 11:00:16.817349: Epoch time: 19.83 s +2024-11-21 11:00:17.609449: +2024-11-21 11:00:17.609781: Epoch 61 +2024-11-21 11:00:17.609895: Current learning rate: 0.00993 +2024-11-21 11:00:35.328246: train_loss -0.7365 +2024-11-21 11:00:35.328456: val_loss -0.7486 +2024-11-21 11:00:35.328529: Pseudo dice [0.8304] +2024-11-21 11:00:35.328605: Epoch time: 17.72 s +2024-11-21 11:00:35.328668: Yayy! New best EMA pseudo Dice: 0.8219 +2024-11-21 11:00:36.300347: +2024-11-21 11:00:36.300611: Epoch 62 +2024-11-21 11:00:36.300725: Current learning rate: 0.00993 +2024-11-21 11:00:54.782527: train_loss -0.7308 +2024-11-21 11:00:54.782781: val_loss -0.731 +2024-11-21 11:00:54.782855: Pseudo dice [0.8111] +2024-11-21 11:00:54.782929: Epoch time: 18.48 s +2024-11-21 11:00:55.655290: +2024-11-21 11:00:55.655503: Epoch 63 +2024-11-21 11:00:55.655616: Current learning rate: 0.00993 +2024-11-21 11:01:13.073475: train_loss -0.7219 +2024-11-21 11:01:13.073680: val_loss -0.7483 +2024-11-21 11:01:13.073753: Pseudo dice [0.8279] +2024-11-21 11:01:13.073826: Epoch time: 17.42 s +2024-11-21 11:01:13.839676: +2024-11-21 11:01:13.839902: Epoch 64 +2024-11-21 11:01:13.840021: Current learning rate: 0.00993 +2024-11-21 11:01:32.303661: train_loss -0.7318 +2024-11-21 11:01:32.303942: val_loss -0.7446 +2024-11-21 11:01:32.304028: Pseudo dice [0.8378] +2024-11-21 11:01:32.304114: Epoch time: 18.46 s +2024-11-21 11:01:32.304180: Yayy! New best EMA pseudo Dice: 0.8232 +2024-11-21 11:01:33.312421: +2024-11-21 11:01:33.312623: Epoch 65 +2024-11-21 11:01:33.312731: Current learning rate: 0.00993 +2024-11-21 11:01:51.069846: train_loss -0.7167 +2024-11-21 11:01:51.070053: val_loss -0.7421 +2024-11-21 11:01:51.070128: Pseudo dice [0.8293] +2024-11-21 11:01:51.070219: Epoch time: 17.76 s +2024-11-21 11:01:51.070285: Yayy! New best EMA pseudo Dice: 0.8238 +2024-11-21 11:01:52.081315: +2024-11-21 11:01:52.081626: Epoch 66 +2024-11-21 11:01:52.081738: Current learning rate: 0.00993 +2024-11-21 11:02:09.904957: train_loss -0.7288 +2024-11-21 11:02:09.905233: val_loss -0.7439 +2024-11-21 11:02:09.905310: Pseudo dice [0.8305] +2024-11-21 11:02:09.905384: Epoch time: 17.82 s +2024-11-21 11:02:09.905668: Yayy! New best EMA pseudo Dice: 0.8245 +2024-11-21 11:02:11.028188: +2024-11-21 11:02:11.028368: Epoch 67 +2024-11-21 11:02:11.028499: Current learning rate: 0.00992 +2024-11-21 11:02:30.277299: train_loss -0.7199 +2024-11-21 11:02:30.277577: val_loss -0.7608 +2024-11-21 11:02:30.277652: Pseudo dice [0.8194] +2024-11-21 11:02:30.277726: Epoch time: 19.25 s +2024-11-21 11:02:31.060057: +2024-11-21 11:02:31.060244: Epoch 68 +2024-11-21 11:02:31.060352: Current learning rate: 0.00992 +2024-11-21 11:02:49.862546: train_loss -0.7261 +2024-11-21 11:02:49.862803: val_loss -0.7341 +2024-11-21 11:02:49.862877: Pseudo dice [0.8278] +2024-11-21 11:02:49.862957: Epoch time: 18.8 s +2024-11-21 11:02:50.644059: +2024-11-21 11:02:50.644272: Epoch 69 +2024-11-21 11:02:50.644390: Current learning rate: 0.00992 +2024-11-21 11:03:09.325342: train_loss -0.7268 +2024-11-21 11:03:09.325561: val_loss -0.7611 +2024-11-21 11:03:09.325634: Pseudo dice [0.8308] +2024-11-21 11:03:09.325708: Epoch time: 18.68 s +2024-11-21 11:03:09.325771: Yayy! New best EMA pseudo Dice: 0.825 +2024-11-21 11:03:10.792861: +2024-11-21 11:03:10.793075: Epoch 70 +2024-11-21 11:03:10.793183: Current learning rate: 0.00992 +2024-11-21 11:03:29.063103: train_loss -0.7265 +2024-11-21 11:03:29.063322: val_loss -0.7358 +2024-11-21 11:03:29.063398: Pseudo dice [0.8178] +2024-11-21 11:03:29.063470: Epoch time: 18.27 s +2024-11-21 11:03:29.957048: +2024-11-21 11:03:29.957255: Epoch 71 +2024-11-21 11:03:29.957362: Current learning rate: 0.00992 +2024-11-21 11:03:47.072550: train_loss -0.7217 +2024-11-21 11:03:47.075001: val_loss -0.7196 +2024-11-21 11:03:47.075099: Pseudo dice [0.7992] +2024-11-21 11:03:47.075195: Epoch time: 17.12 s +2024-11-21 11:03:47.952708: +2024-11-21 11:03:47.952921: Epoch 72 +2024-11-21 11:03:47.953033: Current learning rate: 0.00992 +2024-11-21 11:04:06.195681: train_loss -0.7277 +2024-11-21 11:04:06.195949: val_loss -0.7644 +2024-11-21 11:04:06.196031: Pseudo dice [0.8217] +2024-11-21 11:04:06.196105: Epoch time: 18.24 s +2024-11-21 11:04:07.083264: +2024-11-21 11:04:07.083449: Epoch 73 +2024-11-21 11:04:07.083556: Current learning rate: 0.00992 +2024-11-21 11:04:25.744586: train_loss -0.7137 +2024-11-21 11:04:25.744800: val_loss -0.7593 +2024-11-21 11:04:25.744873: Pseudo dice [0.8315] +2024-11-21 11:04:25.744946: Epoch time: 18.66 s +2024-11-21 11:04:26.519651: +2024-11-21 11:04:26.519896: Epoch 74 +2024-11-21 11:04:26.520013: Current learning rate: 0.00992 +2024-11-21 11:04:43.705952: train_loss -0.7294 +2024-11-21 11:04:43.706158: val_loss -0.7593 +2024-11-21 11:04:43.706232: Pseudo dice [0.8434] +2024-11-21 11:04:43.706306: Epoch time: 17.19 s +2024-11-21 11:04:44.469428: +2024-11-21 11:04:44.469635: Epoch 75 +2024-11-21 11:04:44.469742: Current learning rate: 0.00992 +2024-11-21 11:05:04.508473: train_loss -0.7182 +2024-11-21 11:05:04.508710: val_loss -0.7311 +2024-11-21 11:05:04.508859: Pseudo dice [0.8085] +2024-11-21 11:05:04.508942: Epoch time: 20.04 s +2024-11-21 11:05:05.286346: +2024-11-21 11:05:05.286559: Epoch 76 +2024-11-21 11:05:05.286667: Current learning rate: 0.00991 +2024-11-21 11:05:23.182080: train_loss -0.726 +2024-11-21 11:05:23.182289: val_loss -0.7551 +2024-11-21 11:05:23.182364: Pseudo dice [0.8334] +2024-11-21 11:05:23.182437: Epoch time: 17.9 s +2024-11-21 11:05:23.959529: +2024-11-21 11:05:23.959731: Epoch 77 +2024-11-21 11:05:23.959848: Current learning rate: 0.00991 +2024-11-21 11:05:42.606619: train_loss -0.7199 +2024-11-21 11:05:42.608938: val_loss -0.7218 +2024-11-21 11:05:42.609114: Pseudo dice [0.7993] +2024-11-21 11:05:42.609195: Epoch time: 18.65 s +2024-11-21 11:05:43.437591: +2024-11-21 11:05:43.437793: Epoch 78 +2024-11-21 11:05:43.437897: Current learning rate: 0.00991 +2024-11-21 11:06:01.058328: train_loss -0.7231 +2024-11-21 11:06:01.058558: val_loss -0.7518 +2024-11-21 11:06:01.058632: Pseudo dice [0.8366] +2024-11-21 11:06:01.058706: Epoch time: 17.62 s +2024-11-21 11:06:01.846162: +2024-11-21 11:06:01.846352: Epoch 79 +2024-11-21 11:06:01.846455: Current learning rate: 0.00991 +2024-11-21 11:06:19.610814: train_loss -0.7251 +2024-11-21 11:06:19.611047: val_loss -0.7105 +2024-11-21 11:06:19.611119: Pseudo dice [0.8323] +2024-11-21 11:06:19.611195: Epoch time: 17.77 s +2024-11-21 11:06:20.380553: +2024-11-21 11:06:20.382578: Epoch 80 +2024-11-21 11:06:20.382695: Current learning rate: 0.00991 +2024-11-21 11:06:38.642720: train_loss -0.7181 +2024-11-21 11:06:38.642930: val_loss -0.762 +2024-11-21 11:06:38.643011: Pseudo dice [0.8166] +2024-11-21 11:06:38.643120: Epoch time: 18.26 s +2024-11-21 11:06:39.778303: +2024-11-21 11:06:39.778489: Epoch 81 +2024-11-21 11:06:39.778594: Current learning rate: 0.00991 +2024-11-21 11:06:57.352605: train_loss -0.7228 +2024-11-21 11:06:57.352834: val_loss -0.7297 +2024-11-21 11:06:57.352907: Pseudo dice [0.8201] +2024-11-21 11:06:57.352980: Epoch time: 17.58 s +2024-11-21 11:06:58.262727: +2024-11-21 11:06:58.263021: Epoch 82 +2024-11-21 11:06:58.263132: Current learning rate: 0.00991 +2024-11-21 11:07:16.450557: train_loss -0.7351 +2024-11-21 11:07:16.456019: val_loss -0.7359 +2024-11-21 11:07:16.456128: Pseudo dice [0.8271] +2024-11-21 11:07:16.456212: Epoch time: 18.19 s +2024-11-21 11:07:17.288467: +2024-11-21 11:07:17.288663: Epoch 83 +2024-11-21 11:07:17.288774: Current learning rate: 0.00991 +2024-11-21 11:07:35.478532: train_loss -0.7354 +2024-11-21 11:07:35.478734: val_loss -0.7534 +2024-11-21 11:07:35.478808: Pseudo dice [0.8386] +2024-11-21 11:07:35.478884: Epoch time: 18.19 s +2024-11-21 11:07:36.231851: +2024-11-21 11:07:36.232055: Epoch 84 +2024-11-21 11:07:36.232166: Current learning rate: 0.00991 +2024-11-21 11:07:54.407867: train_loss -0.7457 +2024-11-21 11:07:54.408150: val_loss -0.7601 +2024-11-21 11:07:54.408228: Pseudo dice [0.8183] +2024-11-21 11:07:54.408303: Epoch time: 18.18 s +2024-11-21 11:07:55.164594: +2024-11-21 11:07:55.164791: Epoch 85 +2024-11-21 11:07:55.164900: Current learning rate: 0.0099 +2024-11-21 11:08:12.444981: train_loss -0.7399 +2024-11-21 11:08:12.445210: val_loss -0.7591 +2024-11-21 11:08:12.445284: Pseudo dice [0.8122] +2024-11-21 11:08:12.445366: Epoch time: 17.28 s +2024-11-21 11:08:13.205671: +2024-11-21 11:08:13.205875: Epoch 86 +2024-11-21 11:08:13.205983: Current learning rate: 0.0099 +2024-11-21 11:08:32.090754: train_loss -0.7302 +2024-11-21 11:08:32.091020: val_loss -0.7431 +2024-11-21 11:08:32.091101: Pseudo dice [0.8156] +2024-11-21 11:08:32.091178: Epoch time: 18.89 s +2024-11-21 11:08:32.853195: +2024-11-21 11:08:32.853451: Epoch 87 +2024-11-21 11:08:32.853561: Current learning rate: 0.0099 +2024-11-21 11:08:51.229949: train_loss -0.7252 +2024-11-21 11:08:51.230170: val_loss -0.7462 +2024-11-21 11:08:51.230242: Pseudo dice [0.8142] +2024-11-21 11:08:51.235515: Epoch time: 18.38 s +2024-11-21 11:08:52.028741: +2024-11-21 11:08:52.028951: Epoch 88 +2024-11-21 11:08:52.029061: Current learning rate: 0.0099 +2024-11-21 11:09:10.073219: train_loss -0.734 +2024-11-21 11:09:10.073465: val_loss -0.7558 +2024-11-21 11:09:10.073546: Pseudo dice [0.8337] +2024-11-21 11:09:10.073619: Epoch time: 18.05 s +2024-11-21 11:09:10.826668: +2024-11-21 11:09:10.826865: Epoch 89 +2024-11-21 11:09:10.826978: Current learning rate: 0.0099 +2024-11-21 11:09:28.431616: train_loss -0.7347 +2024-11-21 11:09:28.431827: val_loss -0.7548 +2024-11-21 11:09:28.431905: Pseudo dice [0.8211] +2024-11-21 11:09:28.431983: Epoch time: 17.61 s +2024-11-21 11:09:29.181713: +2024-11-21 11:09:29.181915: Epoch 90 +2024-11-21 11:09:29.182033: Current learning rate: 0.0099 +2024-11-21 11:09:48.016389: train_loss -0.7293 +2024-11-21 11:09:48.016632: val_loss -0.7571 +2024-11-21 11:09:48.016710: Pseudo dice [0.8315] +2024-11-21 11:09:48.016786: Epoch time: 18.84 s +2024-11-21 11:09:48.771378: +2024-11-21 11:09:48.771608: Epoch 91 +2024-11-21 11:09:48.771723: Current learning rate: 0.0099 +2024-11-21 11:10:06.992815: train_loss -0.7265 +2024-11-21 11:10:06.993030: val_loss -0.7474 +2024-11-21 11:10:06.993108: Pseudo dice [0.8267] +2024-11-21 11:10:06.993182: Epoch time: 18.22 s +2024-11-21 11:10:07.789937: +2024-11-21 11:10:07.790142: Epoch 92 +2024-11-21 11:10:07.790248: Current learning rate: 0.0099 +2024-11-21 11:10:27.622931: train_loss -0.7376 +2024-11-21 11:10:27.623202: val_loss -0.7379 +2024-11-21 11:10:27.623466: Pseudo dice [0.827] +2024-11-21 11:10:27.623545: Epoch time: 19.83 s +2024-11-21 11:10:28.377270: +2024-11-21 11:10:28.377480: Epoch 93 +2024-11-21 11:10:28.377591: Current learning rate: 0.0099 +2024-11-21 11:10:46.307857: train_loss -0.7191 +2024-11-21 11:10:46.308126: val_loss -0.7555 +2024-11-21 11:10:46.308205: Pseudo dice [0.8413] +2024-11-21 11:10:46.308286: Epoch time: 17.93 s +2024-11-21 11:10:46.308351: Yayy! New best EMA pseudo Dice: 0.8258 +2024-11-21 11:10:47.280350: +2024-11-21 11:10:47.280586: Epoch 94 +2024-11-21 11:10:47.280730: Current learning rate: 0.00989 +2024-11-21 11:11:06.438705: train_loss -0.7298 +2024-11-21 11:11:06.438918: val_loss -0.7083 +2024-11-21 11:11:06.444154: Pseudo dice [0.8278] +2024-11-21 11:11:06.444316: Epoch time: 19.16 s +2024-11-21 11:11:06.444390: Yayy! New best EMA pseudo Dice: 0.826 +2024-11-21 11:11:07.439668: +2024-11-21 11:11:07.440009: Epoch 95 +2024-11-21 11:11:07.440118: Current learning rate: 0.00989 +2024-11-21 11:11:27.119068: train_loss -0.7262 +2024-11-21 11:11:27.119290: val_loss -0.7653 +2024-11-21 11:11:27.119362: Pseudo dice [0.8411] +2024-11-21 11:11:27.119437: Epoch time: 19.68 s +2024-11-21 11:11:27.119499: Yayy! New best EMA pseudo Dice: 0.8275 +2024-11-21 11:11:28.113803: +2024-11-21 11:11:28.114062: Epoch 96 +2024-11-21 11:11:28.114173: Current learning rate: 0.00989 +2024-11-21 11:11:45.723150: train_loss -0.7403 +2024-11-21 11:11:45.723373: val_loss -0.742 +2024-11-21 11:11:45.723454: Pseudo dice [0.8185] +2024-11-21 11:11:45.723533: Epoch time: 17.61 s +2024-11-21 11:11:46.491111: +2024-11-21 11:11:46.491315: Epoch 97 +2024-11-21 11:11:46.491424: Current learning rate: 0.00989 +2024-11-21 11:12:03.919379: train_loss -0.7356 +2024-11-21 11:12:03.919683: val_loss -0.7508 +2024-11-21 11:12:03.919765: Pseudo dice [0.8236] +2024-11-21 11:12:03.919846: Epoch time: 17.43 s +2024-11-21 11:12:04.782780: +2024-11-21 11:12:04.782985: Epoch 98 +2024-11-21 11:12:04.783099: Current learning rate: 0.00989 +2024-11-21 11:12:23.153027: train_loss -0.7328 +2024-11-21 11:12:23.153238: val_loss -0.7552 +2024-11-21 11:12:23.153311: Pseudo dice [0.833] +2024-11-21 11:12:23.153382: Epoch time: 18.37 s +2024-11-21 11:12:23.922598: +2024-11-21 11:12:23.922800: Epoch 99 +2024-11-21 11:12:23.922910: Current learning rate: 0.00989 +2024-11-21 11:12:42.542980: train_loss -0.7431 +2024-11-21 11:12:42.543210: val_loss -0.7453 +2024-11-21 11:12:42.543285: Pseudo dice [0.8266] +2024-11-21 11:12:42.543357: Epoch time: 18.62 s +2024-11-21 11:12:43.522593: +2024-11-21 11:12:43.522797: Epoch 100 +2024-11-21 11:12:43.522911: Current learning rate: 0.00989 +2024-11-21 11:13:02.338041: train_loss -0.7365 +2024-11-21 11:13:02.338268: val_loss -0.741 +2024-11-21 11:13:02.338344: Pseudo dice [0.8217] +2024-11-21 11:13:02.338423: Epoch time: 18.82 s +2024-11-21 11:13:03.235053: +2024-11-21 11:13:03.235248: Epoch 101 +2024-11-21 11:13:03.235356: Current learning rate: 0.00989 +2024-11-21 11:13:21.473068: train_loss -0.7234 +2024-11-21 11:13:21.473306: val_loss -0.7306 +2024-11-21 11:13:21.473381: Pseudo dice [0.8287] +2024-11-21 11:13:21.473458: Epoch time: 18.24 s +2024-11-21 11:13:22.240723: +2024-11-21 11:13:22.240929: Epoch 102 +2024-11-21 11:13:22.241045: Current learning rate: 0.00989 +2024-11-21 11:13:41.316112: train_loss -0.7284 +2024-11-21 11:13:41.316315: val_loss -0.7255 +2024-11-21 11:13:41.316388: Pseudo dice [0.8247] +2024-11-21 11:13:41.316460: Epoch time: 19.08 s +2024-11-21 11:13:42.081949: +2024-11-21 11:13:42.082168: Epoch 103 +2024-11-21 11:13:42.082278: Current learning rate: 0.00988 +2024-11-21 11:14:00.496703: train_loss -0.7275 +2024-11-21 11:14:00.496915: val_loss -0.7434 +2024-11-21 11:14:00.496989: Pseudo dice [0.8224] +2024-11-21 11:14:00.497121: Epoch time: 18.42 s +2024-11-21 11:14:01.370163: +2024-11-21 11:14:01.370385: Epoch 104 +2024-11-21 11:14:01.370496: Current learning rate: 0.00988 +2024-11-21 11:14:20.545682: train_loss -0.7376 +2024-11-21 11:14:20.545945: val_loss -0.7672 +2024-11-21 11:14:20.546025: Pseudo dice [0.8341] +2024-11-21 11:14:20.546103: Epoch time: 19.18 s +2024-11-21 11:14:21.753869: +2024-11-21 11:14:21.754071: Epoch 105 +2024-11-21 11:14:21.754181: Current learning rate: 0.00988 +2024-11-21 11:14:40.968562: train_loss -0.7381 +2024-11-21 11:14:40.968790: val_loss -0.7638 +2024-11-21 11:14:40.968864: Pseudo dice [0.8356] +2024-11-21 11:14:40.968936: Epoch time: 19.22 s +2024-11-21 11:14:40.969005: Yayy! New best EMA pseudo Dice: 0.8277 +2024-11-21 11:14:41.992861: +2024-11-21 11:14:41.993057: Epoch 106 +2024-11-21 11:14:41.993165: Current learning rate: 0.00988 +2024-11-21 11:15:00.101713: train_loss -0.7344 +2024-11-21 11:15:00.101922: val_loss -0.7286 +2024-11-21 11:15:00.102001: Pseudo dice [0.8278] +2024-11-21 11:15:00.102072: Epoch time: 18.11 s +2024-11-21 11:15:00.102132: Yayy! New best EMA pseudo Dice: 0.8277 +2024-11-21 11:15:01.180609: +2024-11-21 11:15:01.180820: Epoch 107 +2024-11-21 11:15:01.180931: Current learning rate: 0.00988 +2024-11-21 11:15:19.238379: train_loss -0.7309 +2024-11-21 11:15:19.238583: val_loss -0.7243 +2024-11-21 11:15:19.238654: Pseudo dice [0.8061] +2024-11-21 11:15:19.238724: Epoch time: 18.06 s +2024-11-21 11:15:20.004973: +2024-11-21 11:15:20.005183: Epoch 108 +2024-11-21 11:15:20.005296: Current learning rate: 0.00988 +2024-11-21 11:15:38.884955: train_loss -0.7284 +2024-11-21 11:15:38.885217: val_loss -0.7502 +2024-11-21 11:15:38.885302: Pseudo dice [0.8129] +2024-11-21 11:15:38.885392: Epoch time: 18.88 s +2024-11-21 11:15:39.822959: +2024-11-21 11:15:39.823142: Epoch 109 +2024-11-21 11:15:39.823251: Current learning rate: 0.00988 +2024-11-21 11:15:58.131531: train_loss -0.7463 +2024-11-21 11:15:58.131753: val_loss -0.737 +2024-11-21 11:15:58.131841: Pseudo dice [0.8235] +2024-11-21 11:15:58.131922: Epoch time: 18.31 s +2024-11-21 11:15:58.909703: +2024-11-21 11:15:58.909926: Epoch 110 +2024-11-21 11:15:58.910043: Current learning rate: 0.00988 +2024-11-21 11:16:16.927486: train_loss -0.7431 +2024-11-21 11:16:16.927701: val_loss -0.7447 +2024-11-21 11:16:16.927773: Pseudo dice [0.8352] +2024-11-21 11:16:16.927846: Epoch time: 18.02 s +2024-11-21 11:16:17.703479: +2024-11-21 11:16:17.703666: Epoch 111 +2024-11-21 11:16:17.703775: Current learning rate: 0.00988 +2024-11-21 11:16:36.599073: train_loss -0.7272 +2024-11-21 11:16:36.599277: val_loss -0.7508 +2024-11-21 11:16:36.599353: Pseudo dice [0.8419] +2024-11-21 11:16:36.599427: Epoch time: 18.9 s +2024-11-21 11:16:37.372603: +2024-11-21 11:16:37.372792: Epoch 112 +2024-11-21 11:16:37.372899: Current learning rate: 0.00987 +2024-11-21 11:16:56.076812: train_loss -0.7237 +2024-11-21 11:16:56.077056: val_loss -0.7109 +2024-11-21 11:16:56.077132: Pseudo dice [0.7983] +2024-11-21 11:16:56.077210: Epoch time: 18.71 s +2024-11-21 11:16:56.847304: +2024-11-21 11:16:56.847519: Epoch 113 +2024-11-21 11:16:56.847637: Current learning rate: 0.00987 +2024-11-21 11:17:14.824636: train_loss -0.7368 +2024-11-21 11:17:14.824839: val_loss -0.7362 +2024-11-21 11:17:14.824912: Pseudo dice [0.8159] +2024-11-21 11:17:14.825029: Epoch time: 17.98 s +2024-11-21 11:17:15.587830: +2024-11-21 11:17:15.588011: Epoch 114 +2024-11-21 11:17:15.588123: Current learning rate: 0.00987 +2024-11-21 11:17:34.206492: train_loss -0.7334 +2024-11-21 11:17:34.206738: val_loss -0.7136 +2024-11-21 11:17:34.206815: Pseudo dice [0.8261] +2024-11-21 11:17:34.206888: Epoch time: 18.62 s +2024-11-21 11:17:34.986012: +2024-11-21 11:17:34.986227: Epoch 115 +2024-11-21 11:17:34.986333: Current learning rate: 0.00987 +2024-11-21 11:17:53.035390: train_loss -0.7348 +2024-11-21 11:17:53.035604: val_loss -0.7462 +2024-11-21 11:17:53.035679: Pseudo dice [0.8412] +2024-11-21 11:17:53.035758: Epoch time: 18.05 s +2024-11-21 11:17:53.812196: +2024-11-21 11:17:53.812432: Epoch 116 +2024-11-21 11:17:53.812549: Current learning rate: 0.00987 +2024-11-21 11:18:11.316427: train_loss -0.733 +2024-11-21 11:18:11.316636: val_loss -0.7702 +2024-11-21 11:18:11.316711: Pseudo dice [0.8515] +2024-11-21 11:18:11.316785: Epoch time: 17.51 s +2024-11-21 11:18:11.316844: Yayy! New best EMA pseudo Dice: 0.8279 +2024-11-21 11:18:12.291321: +2024-11-21 11:18:12.291542: Epoch 117 +2024-11-21 11:18:12.291655: Current learning rate: 0.00987 +2024-11-21 11:18:30.894627: train_loss -0.7281 +2024-11-21 11:18:30.894846: val_loss -0.7419 +2024-11-21 11:18:30.894918: Pseudo dice [0.8219] +2024-11-21 11:18:30.894998: Epoch time: 18.6 s +2024-11-21 11:18:31.675503: +2024-11-21 11:18:31.675744: Epoch 118 +2024-11-21 11:18:31.675869: Current learning rate: 0.00987 +2024-11-21 11:18:49.957320: train_loss -0.742 +2024-11-21 11:18:49.959741: val_loss -0.7699 +2024-11-21 11:18:49.959868: Pseudo dice [0.8338] +2024-11-21 11:18:49.959958: Epoch time: 18.28 s +2024-11-21 11:18:49.960029: Yayy! New best EMA pseudo Dice: 0.828 +2024-11-21 11:18:51.110600: +2024-11-21 11:18:51.110870: Epoch 119 +2024-11-21 11:18:51.110980: Current learning rate: 0.00987 +2024-11-21 11:19:08.888163: train_loss -0.7445 +2024-11-21 11:19:08.888372: val_loss -0.7483 +2024-11-21 11:19:08.888445: Pseudo dice [0.823] +2024-11-21 11:19:08.888515: Epoch time: 17.78 s +2024-11-21 11:19:09.790312: +2024-11-21 11:19:09.790516: Epoch 120 +2024-11-21 11:19:09.790637: Current learning rate: 0.00986 +2024-11-21 11:19:27.525684: train_loss -0.7442 +2024-11-21 11:19:27.525900: val_loss -0.7263 +2024-11-21 11:19:27.525977: Pseudo dice [0.8252] +2024-11-21 11:19:27.526059: Epoch time: 17.74 s +2024-11-21 11:19:28.302913: +2024-11-21 11:19:28.303125: Epoch 121 +2024-11-21 11:19:28.303232: Current learning rate: 0.00986 +2024-11-21 11:19:46.896495: train_loss -0.7431 +2024-11-21 11:19:46.896709: val_loss -0.7484 +2024-11-21 11:19:46.896783: Pseudo dice [0.827] +2024-11-21 11:19:46.896858: Epoch time: 18.59 s +2024-11-21 11:19:47.680881: +2024-11-21 11:19:47.681095: Epoch 122 +2024-11-21 11:19:47.681207: Current learning rate: 0.00986 +2024-11-21 11:20:06.488777: train_loss -0.737 +2024-11-21 11:20:06.489035: val_loss -0.7574 +2024-11-21 11:20:06.489114: Pseudo dice [0.8169] +2024-11-21 11:20:06.489194: Epoch time: 18.81 s +2024-11-21 11:20:07.272911: +2024-11-21 11:20:07.273116: Epoch 123 +2024-11-21 11:20:07.273233: Current learning rate: 0.00986 +2024-11-21 11:20:26.786402: train_loss -0.7341 +2024-11-21 11:20:26.786624: val_loss -0.7432 +2024-11-21 11:20:26.786697: Pseudo dice [0.8303] +2024-11-21 11:20:26.786770: Epoch time: 19.51 s +2024-11-21 11:20:27.802056: +2024-11-21 11:20:27.802373: Epoch 124 +2024-11-21 11:20:27.802482: Current learning rate: 0.00986 +2024-11-21 11:20:46.155534: train_loss -0.7439 +2024-11-21 11:20:46.155766: val_loss -0.7711 +2024-11-21 11:20:46.161025: Pseudo dice [0.8432] +2024-11-21 11:20:46.161180: Epoch time: 18.35 s +2024-11-21 11:20:46.161250: Yayy! New best EMA pseudo Dice: 0.8283 +2024-11-21 11:20:47.205466: +2024-11-21 11:20:47.205726: Epoch 125 +2024-11-21 11:20:47.205841: Current learning rate: 0.00986 +2024-11-21 11:21:06.585275: train_loss -0.7278 +2024-11-21 11:21:06.585542: val_loss -0.7574 +2024-11-21 11:21:06.585628: Pseudo dice [0.828] +2024-11-21 11:21:06.585704: Epoch time: 19.38 s +2024-11-21 11:21:07.364190: +2024-11-21 11:21:07.364391: Epoch 126 +2024-11-21 11:21:07.364504: Current learning rate: 0.00986 +2024-11-21 11:21:25.808268: train_loss -0.7383 +2024-11-21 11:21:25.808525: val_loss -0.747 +2024-11-21 11:21:25.808605: Pseudo dice [0.8285] +2024-11-21 11:21:25.808686: Epoch time: 18.44 s +2024-11-21 11:21:26.588953: +2024-11-21 11:21:26.589166: Epoch 127 +2024-11-21 11:21:26.589284: Current learning rate: 0.00986 +2024-11-21 11:21:44.715084: train_loss -0.7232 +2024-11-21 11:21:44.715297: val_loss -0.7267 +2024-11-21 11:21:44.720518: Pseudo dice [0.8255] +2024-11-21 11:21:44.720657: Epoch time: 18.13 s +2024-11-21 11:21:45.527798: +2024-11-21 11:21:45.528019: Epoch 128 +2024-11-21 11:21:45.528148: Current learning rate: 0.00986 +2024-11-21 11:22:04.320000: train_loss -0.7256 +2024-11-21 11:22:04.320219: val_loss -0.7579 +2024-11-21 11:22:04.320295: Pseudo dice [0.8309] +2024-11-21 11:22:04.320374: Epoch time: 18.79 s +2024-11-21 11:22:04.320434: Yayy! New best EMA pseudo Dice: 0.8283 +2024-11-21 11:22:05.442677: +2024-11-21 11:22:05.442866: Epoch 129 +2024-11-21 11:22:05.442980: Current learning rate: 0.00985 +2024-11-21 11:22:24.171297: train_loss -0.7435 +2024-11-21 11:22:24.171537: val_loss -0.7427 +2024-11-21 11:22:24.171613: Pseudo dice [0.8202] +2024-11-21 11:22:24.171695: Epoch time: 18.73 s +2024-11-21 11:22:24.947812: +2024-11-21 11:22:24.948021: Epoch 130 +2024-11-21 11:22:24.948132: Current learning rate: 0.00985 +2024-11-21 11:22:43.091615: train_loss -0.7417 +2024-11-21 11:22:43.091835: val_loss -0.7388 +2024-11-21 11:22:43.091907: Pseudo dice [0.8347] +2024-11-21 11:22:43.091980: Epoch time: 18.14 s +2024-11-21 11:22:43.866590: +2024-11-21 11:22:43.866806: Epoch 131 +2024-11-21 11:22:43.866919: Current learning rate: 0.00985 +2024-11-21 11:23:01.739105: train_loss -0.7362 +2024-11-21 11:23:01.739399: val_loss -0.7176 +2024-11-21 11:23:01.739476: Pseudo dice [0.7997] +2024-11-21 11:23:01.739549: Epoch time: 17.87 s +2024-11-21 11:23:02.521972: +2024-11-21 11:23:02.522172: Epoch 132 +2024-11-21 11:23:02.522280: Current learning rate: 0.00985 +2024-11-21 11:23:21.441216: train_loss -0.7358 +2024-11-21 11:23:21.441420: val_loss -0.7563 +2024-11-21 11:23:21.441494: Pseudo dice [0.8239] +2024-11-21 11:23:21.441566: Epoch time: 18.92 s +2024-11-21 11:23:22.278188: +2024-11-21 11:23:22.278394: Epoch 133 +2024-11-21 11:23:22.278506: Current learning rate: 0.00985 +2024-11-21 11:23:40.461339: train_loss -0.7359 +2024-11-21 11:23:40.461594: val_loss -0.7476 +2024-11-21 11:23:40.463878: Pseudo dice [0.8262] +2024-11-21 11:23:40.463979: Epoch time: 18.18 s +2024-11-21 11:23:41.262823: +2024-11-21 11:23:41.263068: Epoch 134 +2024-11-21 11:23:41.263173: Current learning rate: 0.00985 +2024-11-21 11:24:00.538098: train_loss -0.7273 +2024-11-21 11:24:00.538322: val_loss -0.7321 +2024-11-21 11:24:00.538399: Pseudo dice [0.8141] +2024-11-21 11:24:00.538473: Epoch time: 19.28 s +2024-11-21 11:24:01.336513: +2024-11-21 11:24:01.336740: Epoch 135 +2024-11-21 11:24:01.336864: Current learning rate: 0.00985 +2024-11-21 11:24:19.364453: train_loss -0.74 +2024-11-21 11:24:19.364668: val_loss -0.7552 +2024-11-21 11:24:19.364743: Pseudo dice [0.8208] +2024-11-21 11:24:19.364818: Epoch time: 18.03 s +2024-11-21 11:24:20.146573: +2024-11-21 11:24:20.146752: Epoch 136 +2024-11-21 11:24:20.146857: Current learning rate: 0.00985 +2024-11-21 11:24:38.131072: train_loss -0.7477 +2024-11-21 11:24:38.131292: val_loss -0.7351 +2024-11-21 11:24:38.131424: Pseudo dice [0.827] +2024-11-21 11:24:38.131502: Epoch time: 17.99 s +2024-11-21 11:24:38.912006: +2024-11-21 11:24:38.912212: Epoch 137 +2024-11-21 11:24:38.912325: Current learning rate: 0.00985 +2024-11-21 11:24:57.973797: train_loss -0.7333 +2024-11-21 11:24:57.974059: val_loss -0.7804 +2024-11-21 11:24:57.974134: Pseudo dice [0.8368] +2024-11-21 11:24:57.974215: Epoch time: 19.06 s +2024-11-21 11:24:59.165960: +2024-11-21 11:24:59.166170: Epoch 138 +2024-11-21 11:24:59.166283: Current learning rate: 0.00984 +2024-11-21 11:25:16.197066: train_loss -0.7311 +2024-11-21 11:25:16.197264: val_loss -0.7198 +2024-11-21 11:25:16.197335: Pseudo dice [0.8281] +2024-11-21 11:25:16.197410: Epoch time: 17.03 s +2024-11-21 11:25:17.007653: +2024-11-21 11:25:17.007869: Epoch 139 +2024-11-21 11:25:17.007977: Current learning rate: 0.00984 +2024-11-21 11:25:34.481985: train_loss -0.7412 +2024-11-21 11:25:34.482201: val_loss -0.7316 +2024-11-21 11:25:34.482274: Pseudo dice [0.8303] +2024-11-21 11:25:34.482345: Epoch time: 17.48 s +2024-11-21 11:25:35.393097: +2024-11-21 11:25:35.393293: Epoch 140 +2024-11-21 11:25:35.393402: Current learning rate: 0.00984 +2024-11-21 11:25:53.333162: train_loss -0.7423 +2024-11-21 11:25:53.333389: val_loss -0.7457 +2024-11-21 11:25:53.333462: Pseudo dice [0.8277] +2024-11-21 11:25:53.333544: Epoch time: 17.94 s +2024-11-21 11:25:54.127255: +2024-11-21 11:25:54.127692: Epoch 141 +2024-11-21 11:25:54.127819: Current learning rate: 0.00984 +2024-11-21 11:26:12.057150: train_loss -0.7403 +2024-11-21 11:26:12.057381: val_loss -0.7339 +2024-11-21 11:26:12.057461: Pseudo dice [0.8297] +2024-11-21 11:26:12.057538: Epoch time: 17.93 s +2024-11-21 11:26:12.850935: +2024-11-21 11:26:12.851153: Epoch 142 +2024-11-21 11:26:12.851273: Current learning rate: 0.00984 +2024-11-21 11:26:30.454300: train_loss -0.7414 +2024-11-21 11:26:30.454566: val_loss -0.7732 +2024-11-21 11:26:30.454646: Pseudo dice [0.8358] +2024-11-21 11:26:30.454958: Epoch time: 17.6 s +2024-11-21 11:26:31.249353: +2024-11-21 11:26:31.249569: Epoch 143 +2024-11-21 11:26:31.249680: Current learning rate: 0.00984 +2024-11-21 11:26:49.533831: train_loss -0.7462 +2024-11-21 11:26:49.534059: val_loss -0.7251 +2024-11-21 11:26:49.534133: Pseudo dice [0.8124] +2024-11-21 11:26:49.534205: Epoch time: 18.29 s +2024-11-21 11:26:50.359020: +2024-11-21 11:26:50.359205: Epoch 144 +2024-11-21 11:26:50.359318: Current learning rate: 0.00984 +2024-11-21 11:27:09.471782: train_loss -0.746 +2024-11-21 11:27:09.472046: val_loss -0.731 +2024-11-21 11:27:09.474388: Pseudo dice [0.8462] +2024-11-21 11:27:09.474501: Epoch time: 19.11 s +2024-11-21 11:27:10.298354: +2024-11-21 11:27:10.298555: Epoch 145 +2024-11-21 11:27:10.298674: Current learning rate: 0.00984 +2024-11-21 11:27:28.129977: train_loss -0.7338 +2024-11-21 11:27:28.130189: val_loss -0.7105 +2024-11-21 11:27:28.130266: Pseudo dice [0.833] +2024-11-21 11:27:28.130340: Epoch time: 17.83 s +2024-11-21 11:27:28.130409: Yayy! New best EMA pseudo Dice: 0.8285 +2024-11-21 11:27:29.122827: +2024-11-21 11:27:29.123038: Epoch 146 +2024-11-21 11:27:29.123147: Current learning rate: 0.00984 +2024-11-21 11:27:46.973384: train_loss -0.7389 +2024-11-21 11:27:46.973586: val_loss -0.7559 +2024-11-21 11:27:46.973661: Pseudo dice [0.8352] +2024-11-21 11:27:46.973734: Epoch time: 17.85 s +2024-11-21 11:27:46.973795: Yayy! New best EMA pseudo Dice: 0.8292 +2024-11-21 11:27:48.071363: +2024-11-21 11:27:48.071573: Epoch 147 +2024-11-21 11:27:48.071685: Current learning rate: 0.00983 +2024-11-21 11:28:06.775435: train_loss -0.7421 +2024-11-21 11:28:06.775654: val_loss -0.7162 +2024-11-21 11:28:06.775730: Pseudo dice [0.8476] +2024-11-21 11:28:06.775807: Epoch time: 18.7 s +2024-11-21 11:28:06.775869: Yayy! New best EMA pseudo Dice: 0.831 +2024-11-21 11:28:07.765518: +2024-11-21 11:28:07.765736: Epoch 148 +2024-11-21 11:28:07.765854: Current learning rate: 0.00983 +2024-11-21 11:28:25.863101: train_loss -0.742 +2024-11-21 11:28:25.863307: val_loss -0.7247 +2024-11-21 11:28:25.863445: Pseudo dice [0.8257] +2024-11-21 11:28:25.863523: Epoch time: 18.1 s +2024-11-21 11:28:26.654307: +2024-11-21 11:28:26.654505: Epoch 149 +2024-11-21 11:28:26.654617: Current learning rate: 0.00983 +2024-11-21 11:28:45.117371: train_loss -0.7465 +2024-11-21 11:28:45.117579: val_loss -0.7627 +2024-11-21 11:28:45.132181: Pseudo dice [0.8327] +2024-11-21 11:28:45.132302: Epoch time: 18.46 s +2024-11-21 11:28:46.457801: +2024-11-21 11:28:46.458216: Epoch 150 +2024-11-21 11:28:46.458325: Current learning rate: 0.00983 +2024-11-21 11:29:04.993914: train_loss -0.7479 +2024-11-21 11:29:04.994122: val_loss -0.7752 +2024-11-21 11:29:04.994196: Pseudo dice [0.8459] +2024-11-21 11:29:04.994272: Epoch time: 18.54 s +2024-11-21 11:29:04.994334: Yayy! New best EMA pseudo Dice: 0.8323 +2024-11-21 11:29:05.991709: +2024-11-21 11:29:05.991927: Epoch 151 +2024-11-21 11:29:05.992039: Current learning rate: 0.00983 +2024-11-21 11:29:24.372686: train_loss -0.734 +2024-11-21 11:29:24.372959: val_loss -0.7681 +2024-11-21 11:29:24.373047: Pseudo dice [0.8423] +2024-11-21 11:29:24.373126: Epoch time: 18.38 s +2024-11-21 11:29:24.373189: Yayy! New best EMA pseudo Dice: 0.8333 +2024-11-21 11:29:25.393006: +2024-11-21 11:29:25.393209: Epoch 152 +2024-11-21 11:29:25.393317: Current learning rate: 0.00983 +2024-11-21 11:29:44.138860: train_loss -0.7326 +2024-11-21 11:29:44.139082: val_loss -0.7146 +2024-11-21 11:29:44.139160: Pseudo dice [0.8299] +2024-11-21 11:29:44.139235: Epoch time: 18.75 s +2024-11-21 11:29:44.940584: +2024-11-21 11:29:44.940796: Epoch 153 +2024-11-21 11:29:44.940911: Current learning rate: 0.00983 +2024-11-21 11:30:03.707001: train_loss -0.7427 +2024-11-21 11:30:03.707217: val_loss -0.7712 +2024-11-21 11:30:03.707290: Pseudo dice [0.8524] +2024-11-21 11:30:03.707365: Epoch time: 18.77 s +2024-11-21 11:30:03.707425: Yayy! New best EMA pseudo Dice: 0.8349 +2024-11-21 11:30:04.788548: +2024-11-21 11:30:04.788792: Epoch 154 +2024-11-21 11:30:04.788904: Current learning rate: 0.00983 +2024-11-21 11:30:23.377681: train_loss -0.7408 +2024-11-21 11:30:23.377881: val_loss -0.7682 +2024-11-21 11:30:23.377951: Pseudo dice [0.8512] +2024-11-21 11:30:23.378102: Epoch time: 18.59 s +2024-11-21 11:30:23.378165: Yayy! New best EMA pseudo Dice: 0.8365 +2024-11-21 11:30:24.410303: +2024-11-21 11:30:24.410515: Epoch 155 +2024-11-21 11:30:24.410625: Current learning rate: 0.00983 +2024-11-21 11:30:42.191944: train_loss -0.7349 +2024-11-21 11:30:42.192186: val_loss -0.7548 +2024-11-21 11:30:42.192262: Pseudo dice [0.8382] +2024-11-21 11:30:42.192345: Epoch time: 17.78 s +2024-11-21 11:30:42.192408: Yayy! New best EMA pseudo Dice: 0.8367 +2024-11-21 11:30:43.198803: +2024-11-21 11:30:43.199016: Epoch 156 +2024-11-21 11:30:43.199127: Current learning rate: 0.00982 +2024-11-21 11:31:01.186205: train_loss -0.7446 +2024-11-21 11:31:01.186418: val_loss -0.7406 +2024-11-21 11:31:01.186490: Pseudo dice [0.8283] +2024-11-21 11:31:01.186562: Epoch time: 17.99 s +2024-11-21 11:31:01.979556: +2024-11-21 11:31:01.979783: Epoch 157 +2024-11-21 11:31:01.979892: Current learning rate: 0.00982 +2024-11-21 11:31:21.015241: train_loss -0.7418 +2024-11-21 11:31:21.015451: val_loss -0.7453 +2024-11-21 11:31:21.015524: Pseudo dice [0.8377] +2024-11-21 11:31:21.015600: Epoch time: 19.04 s +2024-11-21 11:31:21.808228: +2024-11-21 11:31:21.808414: Epoch 158 +2024-11-21 11:31:21.808525: Current learning rate: 0.00982 +2024-11-21 11:31:40.291248: train_loss -0.7351 +2024-11-21 11:31:40.293623: val_loss -0.7546 +2024-11-21 11:31:40.293749: Pseudo dice [0.8293] +2024-11-21 11:31:40.293830: Epoch time: 18.48 s +2024-11-21 11:31:41.197359: +2024-11-21 11:31:41.197538: Epoch 159 +2024-11-21 11:31:41.197664: Current learning rate: 0.00982 +2024-11-21 11:31:59.152972: train_loss -0.7498 +2024-11-21 11:31:59.153218: val_loss -0.7564 +2024-11-21 11:31:59.153293: Pseudo dice [0.8306] +2024-11-21 11:31:59.153374: Epoch time: 17.96 s +2024-11-21 11:32:00.300693: +2024-11-21 11:32:00.300891: Epoch 160 +2024-11-21 11:32:00.301003: Current learning rate: 0.00982 +2024-11-21 11:32:18.267685: train_loss -0.7459 +2024-11-21 11:32:18.267911: val_loss -0.7331 +2024-11-21 11:32:18.267982: Pseudo dice [0.83] +2024-11-21 11:32:18.268060: Epoch time: 17.97 s +2024-11-21 11:32:19.238318: +2024-11-21 11:32:19.238555: Epoch 161 +2024-11-21 11:32:19.238665: Current learning rate: 0.00982 +2024-11-21 11:32:36.218104: train_loss -0.7125 +2024-11-21 11:32:36.218320: val_loss -0.7112 +2024-11-21 11:32:36.218397: Pseudo dice [0.8185] +2024-11-21 11:32:36.218478: Epoch time: 16.98 s +2024-11-21 11:32:37.023100: +2024-11-21 11:32:37.023344: Epoch 162 +2024-11-21 11:32:37.023463: Current learning rate: 0.00982 +2024-11-21 11:32:56.298089: train_loss -0.6991 +2024-11-21 11:32:56.298327: val_loss -0.7562 +2024-11-21 11:32:56.298410: Pseudo dice [0.8272] +2024-11-21 11:32:56.298488: Epoch time: 19.28 s +2024-11-21 11:32:57.097116: +2024-11-21 11:32:57.097306: Epoch 163 +2024-11-21 11:32:57.097414: Current learning rate: 0.00982 +2024-11-21 11:33:14.633249: train_loss -0.7231 +2024-11-21 11:33:14.633461: val_loss -0.7505 +2024-11-21 11:33:14.633541: Pseudo dice [0.8348] +2024-11-21 11:33:14.633615: Epoch time: 17.54 s +2024-11-21 11:33:15.571428: +2024-11-21 11:33:15.571719: Epoch 164 +2024-11-21 11:33:15.571846: Current learning rate: 0.00982 +2024-11-21 11:33:34.871932: train_loss -0.7306 +2024-11-21 11:33:34.872163: val_loss -0.7248 +2024-11-21 11:33:34.872237: Pseudo dice [0.8261] +2024-11-21 11:33:34.872314: Epoch time: 19.3 s +2024-11-21 11:33:35.792445: +2024-11-21 11:33:35.792736: Epoch 165 +2024-11-21 11:33:35.792847: Current learning rate: 0.00981 +2024-11-21 11:33:53.895645: train_loss -0.7436 +2024-11-21 11:33:53.895849: val_loss -0.763 +2024-11-21 11:33:53.895925: Pseudo dice [0.8327] +2024-11-21 11:33:53.896009: Epoch time: 18.1 s +2024-11-21 11:33:54.797408: +2024-11-21 11:33:54.797609: Epoch 166 +2024-11-21 11:33:54.797723: Current learning rate: 0.00981 +2024-11-21 11:34:13.366234: train_loss -0.7407 +2024-11-21 11:34:13.367921: val_loss -0.751 +2024-11-21 11:34:13.368043: Pseudo dice [0.843] +2024-11-21 11:34:13.368122: Epoch time: 18.57 s +2024-11-21 11:34:14.158945: +2024-11-21 11:34:14.159578: Epoch 167 +2024-11-21 11:34:14.159692: Current learning rate: 0.00981 +2024-11-21 11:34:31.869880: train_loss -0.7403 +2024-11-21 11:34:31.870104: val_loss -0.7599 +2024-11-21 11:34:31.870178: Pseudo dice [0.8356] +2024-11-21 11:34:31.870252: Epoch time: 17.71 s +2024-11-21 11:34:32.650360: +2024-11-21 11:34:32.650564: Epoch 168 +2024-11-21 11:34:32.650692: Current learning rate: 0.00981 +2024-11-21 11:34:50.046329: train_loss -0.7474 +2024-11-21 11:34:50.046546: val_loss -0.7561 +2024-11-21 11:34:50.046627: Pseudo dice [0.8325] +2024-11-21 11:34:50.046700: Epoch time: 17.4 s +2024-11-21 11:34:50.943693: +2024-11-21 11:34:50.943967: Epoch 169 +2024-11-21 11:34:50.944080: Current learning rate: 0.00981 +2024-11-21 11:35:09.475827: train_loss -0.7456 +2024-11-21 11:35:09.476076: val_loss -0.7255 +2024-11-21 11:35:09.476151: Pseudo dice [0.8188] +2024-11-21 11:35:09.476232: Epoch time: 18.53 s +2024-11-21 11:35:10.267061: +2024-11-21 11:35:10.267262: Epoch 170 +2024-11-21 11:35:10.267376: Current learning rate: 0.00981 +2024-11-21 11:35:29.110950: train_loss -0.7216 +2024-11-21 11:35:29.111157: val_loss -0.713 +2024-11-21 11:35:29.111232: Pseudo dice [0.8079] +2024-11-21 11:35:29.111305: Epoch time: 18.84 s +2024-11-21 11:35:30.296942: +2024-11-21 11:35:30.297197: Epoch 171 +2024-11-21 11:35:30.297309: Current learning rate: 0.00981 +2024-11-21 11:35:49.216046: train_loss -0.7285 +2024-11-21 11:35:49.216290: val_loss -0.7415 +2024-11-21 11:35:49.216375: Pseudo dice [0.8199] +2024-11-21 11:35:49.216459: Epoch time: 18.92 s +2024-11-21 11:35:50.007962: +2024-11-21 11:35:50.008173: Epoch 172 +2024-11-21 11:35:50.008284: Current learning rate: 0.00981 +2024-11-21 11:36:08.808768: train_loss -0.7329 +2024-11-21 11:36:08.810130: val_loss -0.7425 +2024-11-21 11:36:08.810208: Pseudo dice [0.8185] +2024-11-21 11:36:08.810289: Epoch time: 18.8 s +2024-11-21 11:36:09.600476: +2024-11-21 11:36:09.600749: Epoch 173 +2024-11-21 11:36:09.600860: Current learning rate: 0.00981 +2024-11-21 11:36:27.793203: train_loss -0.7378 +2024-11-21 11:36:27.793406: val_loss -0.7333 +2024-11-21 11:36:27.793480: Pseudo dice [0.8276] +2024-11-21 11:36:27.793556: Epoch time: 18.19 s +2024-11-21 11:36:28.584548: +2024-11-21 11:36:28.584821: Epoch 174 +2024-11-21 11:36:28.584934: Current learning rate: 0.0098 +2024-11-21 11:36:46.402784: train_loss -0.7375 +2024-11-21 11:36:46.403004: val_loss -0.74 +2024-11-21 11:36:46.403086: Pseudo dice [0.8181] +2024-11-21 11:36:46.403161: Epoch time: 17.82 s +2024-11-21 11:36:47.188674: +2024-11-21 11:36:47.188951: Epoch 175 +2024-11-21 11:36:47.189065: Current learning rate: 0.0098 +2024-11-21 11:37:05.840781: train_loss -0.7493 +2024-11-21 11:37:05.841056: val_loss -0.7391 +2024-11-21 11:37:05.841130: Pseudo dice [0.8355] +2024-11-21 11:37:05.841206: Epoch time: 18.65 s +2024-11-21 11:37:06.729460: +2024-11-21 11:37:06.729653: Epoch 176 +2024-11-21 11:37:06.729763: Current learning rate: 0.0098 +2024-11-21 11:37:26.246822: train_loss -0.7498 +2024-11-21 11:37:26.247069: val_loss -0.739 +2024-11-21 11:37:26.247144: Pseudo dice [0.8381] +2024-11-21 11:37:26.247225: Epoch time: 19.52 s +2024-11-21 11:37:27.077844: +2024-11-21 11:37:27.078058: Epoch 177 +2024-11-21 11:37:27.078164: Current learning rate: 0.0098 +2024-11-21 11:37:45.265582: train_loss -0.738 +2024-11-21 11:37:45.265791: val_loss -0.7282 +2024-11-21 11:37:45.265867: Pseudo dice [0.8145] +2024-11-21 11:37:45.265939: Epoch time: 18.19 s +2024-11-21 11:37:46.053135: +2024-11-21 11:37:46.053332: Epoch 178 +2024-11-21 11:37:46.053454: Current learning rate: 0.0098 +2024-11-21 11:38:03.729447: train_loss -0.7577 +2024-11-21 11:38:03.731882: val_loss -0.7638 +2024-11-21 11:38:03.732027: Pseudo dice [0.8432] +2024-11-21 11:38:03.732108: Epoch time: 17.68 s +2024-11-21 11:38:04.525958: +2024-11-21 11:38:04.526163: Epoch 179 +2024-11-21 11:38:04.526272: Current learning rate: 0.0098 +2024-11-21 11:38:22.523790: train_loss -0.7572 +2024-11-21 11:38:22.524012: val_loss -0.7516 +2024-11-21 11:38:22.524086: Pseudo dice [0.8343] +2024-11-21 11:38:22.524163: Epoch time: 18.0 s +2024-11-21 11:38:23.322124: +2024-11-21 11:38:23.322324: Epoch 180 +2024-11-21 11:38:23.322432: Current learning rate: 0.0098 +2024-11-21 11:38:42.503500: train_loss -0.7454 +2024-11-21 11:38:42.503800: val_loss -0.7487 +2024-11-21 11:38:42.503875: Pseudo dice [0.8368] +2024-11-21 11:38:42.503958: Epoch time: 19.18 s +2024-11-21 11:38:43.292096: +2024-11-21 11:38:43.292288: Epoch 181 +2024-11-21 11:38:43.292397: Current learning rate: 0.0098 +2024-11-21 11:39:03.250422: train_loss -0.7395 +2024-11-21 11:39:03.250625: val_loss -0.7591 +2024-11-21 11:39:03.250696: Pseudo dice [0.8347] +2024-11-21 11:39:03.250768: Epoch time: 19.96 s +2024-11-21 11:39:04.408580: +2024-11-21 11:39:04.408777: Epoch 182 +2024-11-21 11:39:04.408887: Current learning rate: 0.0098 +2024-11-21 11:39:24.090375: train_loss -0.7446 +2024-11-21 11:39:24.090604: val_loss -0.7302 +2024-11-21 11:39:24.090677: Pseudo dice [0.8245] +2024-11-21 11:39:24.090752: Epoch time: 19.68 s +2024-11-21 11:39:24.875951: +2024-11-21 11:39:24.876224: Epoch 183 +2024-11-21 11:39:24.876343: Current learning rate: 0.00979 +2024-11-21 11:39:44.482059: train_loss -0.7305 +2024-11-21 11:39:44.482308: val_loss -0.7394 +2024-11-21 11:39:44.482384: Pseudo dice [0.8192] +2024-11-21 11:39:44.482465: Epoch time: 19.61 s +2024-11-21 11:39:45.315982: +2024-11-21 11:39:45.316196: Epoch 184 +2024-11-21 11:39:45.316305: Current learning rate: 0.00979 +2024-11-21 11:40:03.420685: train_loss -0.7476 +2024-11-21 11:40:03.420956: val_loss -0.7676 +2024-11-21 11:40:03.421075: Pseudo dice [0.822] +2024-11-21 11:40:03.421153: Epoch time: 18.11 s +2024-11-21 11:40:04.204545: +2024-11-21 11:40:04.204824: Epoch 185 +2024-11-21 11:40:04.204937: Current learning rate: 0.00979 +2024-11-21 11:40:23.526668: train_loss -0.7486 +2024-11-21 11:40:23.526927: val_loss -0.72 +2024-11-21 11:40:23.527009: Pseudo dice [0.8196] +2024-11-21 11:40:23.527081: Epoch time: 19.32 s +2024-11-21 11:40:24.310291: +2024-11-21 11:40:24.310481: Epoch 186 +2024-11-21 11:40:24.310701: Current learning rate: 0.00979 +2024-11-21 11:40:42.211465: train_loss -0.7412 +2024-11-21 11:40:42.211671: val_loss -0.7378 +2024-11-21 11:40:42.211744: Pseudo dice [0.8363] +2024-11-21 11:40:42.211824: Epoch time: 17.9 s +2024-11-21 11:40:42.999809: +2024-11-21 11:40:43.000035: Epoch 187 +2024-11-21 11:40:43.000150: Current learning rate: 0.00979 +2024-11-21 11:41:02.224408: train_loss -0.7403 +2024-11-21 11:41:02.224646: val_loss -0.7398 +2024-11-21 11:41:02.224721: Pseudo dice [0.8255] +2024-11-21 11:41:02.224799: Epoch time: 19.23 s +2024-11-21 11:41:03.008793: +2024-11-21 11:41:03.008969: Epoch 188 +2024-11-21 11:41:03.009081: Current learning rate: 0.00979 +2024-11-21 11:41:21.618114: train_loss -0.7433 +2024-11-21 11:41:21.618342: val_loss -0.7458 +2024-11-21 11:41:21.618416: Pseudo dice [0.8253] +2024-11-21 11:41:21.618489: Epoch time: 18.61 s +2024-11-21 11:41:22.431363: +2024-11-21 11:41:22.431655: Epoch 189 +2024-11-21 11:41:22.431764: Current learning rate: 0.00979 +2024-11-21 11:41:41.788280: train_loss -0.7481 +2024-11-21 11:41:41.788491: val_loss -0.7518 +2024-11-21 11:41:41.788564: Pseudo dice [0.8224] +2024-11-21 11:41:41.788636: Epoch time: 19.36 s +2024-11-21 11:41:42.571285: +2024-11-21 11:41:42.571475: Epoch 190 +2024-11-21 11:41:42.571584: Current learning rate: 0.00979 +2024-11-21 11:42:01.158019: train_loss -0.7468 +2024-11-21 11:42:01.158230: val_loss -0.767 +2024-11-21 11:42:01.158314: Pseudo dice [0.8387] +2024-11-21 11:42:01.158391: Epoch time: 18.59 s +2024-11-21 11:42:01.942770: +2024-11-21 11:42:01.943003: Epoch 191 +2024-11-21 11:42:01.943115: Current learning rate: 0.00978 +2024-11-21 11:42:19.027135: train_loss -0.7437 +2024-11-21 11:42:19.027423: val_loss -0.7571 +2024-11-21 11:42:19.027501: Pseudo dice [0.84] +2024-11-21 11:42:19.027579: Epoch time: 17.09 s +2024-11-21 11:42:19.883631: +2024-11-21 11:42:19.883820: Epoch 192 +2024-11-21 11:42:19.883926: Current learning rate: 0.00978 +2024-11-21 11:42:37.785328: train_loss -0.7363 +2024-11-21 11:42:37.785527: val_loss -0.7207 +2024-11-21 11:42:37.785598: Pseudo dice [0.8251] +2024-11-21 11:42:37.785671: Epoch time: 17.9 s +2024-11-21 11:42:38.965402: +2024-11-21 11:42:38.965706: Epoch 193 +2024-11-21 11:42:38.965823: Current learning rate: 0.00978 +2024-11-21 11:42:58.421465: train_loss -0.7416 +2024-11-21 11:42:58.421679: val_loss -0.7651 +2024-11-21 11:42:58.421756: Pseudo dice [0.8313] +2024-11-21 11:42:58.421833: Epoch time: 19.46 s +2024-11-21 11:42:59.373839: +2024-11-21 11:42:59.374071: Epoch 194 +2024-11-21 11:42:59.374184: Current learning rate: 0.00978 +2024-11-21 11:43:17.160141: train_loss -0.7423 +2024-11-21 11:43:17.160384: val_loss -0.7204 +2024-11-21 11:43:17.160474: Pseudo dice [0.8049] +2024-11-21 11:43:17.160555: Epoch time: 17.79 s +2024-11-21 11:43:17.958242: +2024-11-21 11:43:17.958449: Epoch 195 +2024-11-21 11:43:17.958559: Current learning rate: 0.00978 +2024-11-21 11:43:36.493379: train_loss -0.7439 +2024-11-21 11:43:36.493634: val_loss -0.7714 +2024-11-21 11:43:36.493707: Pseudo dice [0.8407] +2024-11-21 11:43:36.493783: Epoch time: 18.54 s +2024-11-21 11:43:37.283185: +2024-11-21 11:43:37.283401: Epoch 196 +2024-11-21 11:43:37.283520: Current learning rate: 0.00978 +2024-11-21 11:43:54.449026: train_loss -0.7421 +2024-11-21 11:43:54.449236: val_loss -0.7465 +2024-11-21 11:43:54.449312: Pseudo dice [0.8215] +2024-11-21 11:43:54.449386: Epoch time: 17.17 s +2024-11-21 11:43:55.239923: +2024-11-21 11:43:55.240154: Epoch 197 +2024-11-21 11:43:55.240264: Current learning rate: 0.00978 +2024-11-21 11:44:13.068368: train_loss -0.736 +2024-11-21 11:44:13.068582: val_loss -0.7637 +2024-11-21 11:44:13.068660: Pseudo dice [0.834] +2024-11-21 11:44:13.068738: Epoch time: 17.83 s +2024-11-21 11:44:13.861127: +2024-11-21 11:44:13.861341: Epoch 198 +2024-11-21 11:44:13.861450: Current learning rate: 0.00978 +2024-11-21 11:44:31.792032: train_loss -0.7477 +2024-11-21 11:44:31.792340: val_loss -0.7567 +2024-11-21 11:44:31.792417: Pseudo dice [0.8306] +2024-11-21 11:44:31.792493: Epoch time: 17.93 s +2024-11-21 11:44:32.586273: +2024-11-21 11:44:32.586484: Epoch 199 +2024-11-21 11:44:32.586616: Current learning rate: 0.00978 +2024-11-21 11:44:52.027382: train_loss -0.75 +2024-11-21 11:44:52.027573: val_loss -0.7905 +2024-11-21 11:44:52.027643: Pseudo dice [0.8538] +2024-11-21 11:44:52.027714: Epoch time: 19.44 s +2024-11-21 11:44:53.107239: +2024-11-21 11:44:53.107421: Epoch 200 +2024-11-21 11:44:53.107532: Current learning rate: 0.00977 +2024-11-21 11:45:10.894614: train_loss -0.7489 +2024-11-21 11:45:10.895416: val_loss -0.739 +2024-11-21 11:45:10.895495: Pseudo dice [0.8314] +2024-11-21 11:45:10.895569: Epoch time: 17.79 s +2024-11-21 11:45:11.727288: +2024-11-21 11:45:11.727491: Epoch 201 +2024-11-21 11:45:11.727602: Current learning rate: 0.00977 +2024-11-21 11:45:30.324296: train_loss -0.7465 +2024-11-21 11:45:30.324548: val_loss -0.7201 +2024-11-21 11:45:30.324627: Pseudo dice [0.8207] +2024-11-21 11:45:30.324708: Epoch time: 18.6 s +2024-11-21 11:45:31.157698: +2024-11-21 11:45:31.157900: Epoch 202 +2024-11-21 11:45:31.158011: Current learning rate: 0.00977 +2024-11-21 11:45:49.692103: train_loss -0.7489 +2024-11-21 11:45:49.692309: val_loss -0.726 +2024-11-21 11:45:49.692382: Pseudo dice [0.8262] +2024-11-21 11:45:49.692482: Epoch time: 18.54 s +2024-11-21 11:45:50.483732: +2024-11-21 11:45:50.483953: Epoch 203 +2024-11-21 11:45:50.484093: Current learning rate: 0.00977 +2024-11-21 11:46:07.942623: train_loss -0.7393 +2024-11-21 11:46:07.942843: val_loss -0.7526 +2024-11-21 11:46:07.942920: Pseudo dice [0.8316] +2024-11-21 11:46:07.943025: Epoch time: 17.46 s +2024-11-21 11:46:08.731028: +2024-11-21 11:46:08.731232: Epoch 204 +2024-11-21 11:46:08.731343: Current learning rate: 0.00977 +2024-11-21 11:46:26.348879: train_loss -0.7335 +2024-11-21 11:46:26.349139: val_loss -0.7431 +2024-11-21 11:46:26.349218: Pseudo dice [0.821] +2024-11-21 11:46:26.349303: Epoch time: 17.62 s +2024-11-21 11:46:27.512010: +2024-11-21 11:46:27.512279: Epoch 205 +2024-11-21 11:46:27.512403: Current learning rate: 0.00977 +2024-11-21 11:46:45.561665: train_loss -0.7433 +2024-11-21 11:46:45.561884: val_loss -0.7638 +2024-11-21 11:46:45.561955: Pseudo dice [0.8266] +2024-11-21 11:46:45.562061: Epoch time: 18.05 s +2024-11-21 11:46:46.325675: +2024-11-21 11:46:46.325889: Epoch 206 +2024-11-21 11:46:46.326009: Current learning rate: 0.00977 +2024-11-21 11:47:05.169089: train_loss -0.7464 +2024-11-21 11:47:05.169300: val_loss -0.7668 +2024-11-21 11:47:05.169371: Pseudo dice [0.8314] +2024-11-21 11:47:05.169443: Epoch time: 18.84 s +2024-11-21 11:47:05.931449: +2024-11-21 11:47:05.931680: Epoch 207 +2024-11-21 11:47:05.931791: Current learning rate: 0.00977 +2024-11-21 11:47:25.306033: train_loss -0.737 +2024-11-21 11:47:25.306274: val_loss -0.7634 +2024-11-21 11:47:25.306355: Pseudo dice [0.8461] +2024-11-21 11:47:25.306432: Epoch time: 19.38 s +2024-11-21 11:47:26.096745: +2024-11-21 11:47:26.096986: Epoch 208 +2024-11-21 11:47:26.097101: Current learning rate: 0.00977 +2024-11-21 11:47:44.869396: train_loss -0.7443 +2024-11-21 11:47:44.869629: val_loss -0.7599 +2024-11-21 11:47:44.869700: Pseudo dice [0.8394] +2024-11-21 11:47:44.869773: Epoch time: 18.77 s +2024-11-21 11:47:45.643875: +2024-11-21 11:47:45.644105: Epoch 209 +2024-11-21 11:47:45.644228: Current learning rate: 0.00976 +2024-11-21 11:48:03.475507: train_loss -0.7518 +2024-11-21 11:48:03.475715: val_loss -0.7418 +2024-11-21 11:48:03.475787: Pseudo dice [0.8334] +2024-11-21 11:48:03.475861: Epoch time: 17.83 s +2024-11-21 11:48:04.237730: +2024-11-21 11:48:04.237939: Epoch 210 +2024-11-21 11:48:04.238075: Current learning rate: 0.00976 +2024-11-21 11:48:22.301186: train_loss -0.7411 +2024-11-21 11:48:22.301404: val_loss -0.7553 +2024-11-21 11:48:22.301478: Pseudo dice [0.8367] +2024-11-21 11:48:22.301552: Epoch time: 18.06 s +2024-11-21 11:48:23.065759: +2024-11-21 11:48:23.065970: Epoch 211 +2024-11-21 11:48:23.066087: Current learning rate: 0.00976 +2024-11-21 11:48:41.806606: train_loss -0.7359 +2024-11-21 11:48:41.806818: val_loss -0.7308 +2024-11-21 11:48:41.806934: Pseudo dice [0.8336] +2024-11-21 11:48:41.807016: Epoch time: 18.74 s +2024-11-21 11:48:42.562631: +2024-11-21 11:48:42.562850: Epoch 212 +2024-11-21 11:48:42.562964: Current learning rate: 0.00976 +2024-11-21 11:49:01.247602: train_loss -0.7353 +2024-11-21 11:49:01.247847: val_loss -0.7625 +2024-11-21 11:49:01.247919: Pseudo dice [0.8322] +2024-11-21 11:49:01.248023: Epoch time: 18.69 s +2024-11-21 11:49:02.041232: +2024-11-21 11:49:02.041435: Epoch 213 +2024-11-21 11:49:02.041541: Current learning rate: 0.00976 +2024-11-21 11:49:20.156061: train_loss -0.7418 +2024-11-21 11:49:20.156271: val_loss -0.7456 +2024-11-21 11:49:20.156346: Pseudo dice [0.8288] +2024-11-21 11:49:20.156421: Epoch time: 18.12 s +2024-11-21 11:49:20.922954: +2024-11-21 11:49:20.923205: Epoch 214 +2024-11-21 11:49:20.923313: Current learning rate: 0.00976 +2024-11-21 11:49:39.424570: train_loss -0.7364 +2024-11-21 11:49:39.424797: val_loss -0.7569 +2024-11-21 11:49:39.424952: Pseudo dice [0.8265] +2024-11-21 11:49:39.425040: Epoch time: 18.5 s +2024-11-21 11:49:40.192397: +2024-11-21 11:49:40.192594: Epoch 215 +2024-11-21 11:49:40.192707: Current learning rate: 0.00976 +2024-11-21 11:49:59.457825: train_loss -0.7457 +2024-11-21 11:49:59.458077: val_loss -0.7292 +2024-11-21 11:49:59.458154: Pseudo dice [0.8325] +2024-11-21 11:49:59.458236: Epoch time: 19.27 s +2024-11-21 11:50:00.309804: +2024-11-21 11:50:00.310078: Epoch 216 +2024-11-21 11:50:00.310191: Current learning rate: 0.00976 +2024-11-21 11:50:17.586959: train_loss -0.7451 +2024-11-21 11:50:17.587175: val_loss -0.7247 +2024-11-21 11:50:17.587248: Pseudo dice [0.8286] +2024-11-21 11:50:17.587431: Epoch time: 17.28 s +2024-11-21 11:50:18.734775: +2024-11-21 11:50:18.734996: Epoch 217 +2024-11-21 11:50:18.735103: Current learning rate: 0.00976 +2024-11-21 11:50:36.239563: train_loss -0.7474 +2024-11-21 11:50:36.239793: val_loss -0.7362 +2024-11-21 11:50:36.239868: Pseudo dice [0.8361] +2024-11-21 11:50:36.239942: Epoch time: 17.51 s +2024-11-21 11:50:37.006403: +2024-11-21 11:50:37.006618: Epoch 218 +2024-11-21 11:50:37.006731: Current learning rate: 0.00975 +2024-11-21 11:50:56.084548: train_loss -0.7441 +2024-11-21 11:50:56.084785: val_loss -0.7512 +2024-11-21 11:50:56.084863: Pseudo dice [0.8272] +2024-11-21 11:50:56.084945: Epoch time: 19.08 s +2024-11-21 11:50:56.912337: +2024-11-21 11:50:56.912565: Epoch 219 +2024-11-21 11:50:56.913471: Current learning rate: 0.00975 +2024-11-21 11:51:14.976890: train_loss -0.7364 +2024-11-21 11:51:14.977146: val_loss -0.7525 +2024-11-21 11:51:14.977227: Pseudo dice [0.8171] +2024-11-21 11:51:14.977339: Epoch time: 18.07 s +2024-11-21 11:51:15.737688: +2024-11-21 11:51:15.737907: Epoch 220 +2024-11-21 11:51:15.738021: Current learning rate: 0.00975 +2024-11-21 11:51:34.056015: train_loss -0.7425 +2024-11-21 11:51:34.056252: val_loss -0.7476 +2024-11-21 11:51:34.056334: Pseudo dice [0.8284] +2024-11-21 11:51:34.056419: Epoch time: 18.32 s +2024-11-21 11:51:34.932231: +2024-11-21 11:51:34.932463: Epoch 221 +2024-11-21 11:51:34.932581: Current learning rate: 0.00975 +2024-11-21 11:51:53.208459: train_loss -0.749 +2024-11-21 11:51:53.208736: val_loss -0.7246 +2024-11-21 11:51:53.208817: Pseudo dice [0.8364] +2024-11-21 11:51:53.208894: Epoch time: 18.28 s +2024-11-21 11:51:53.985862: +2024-11-21 11:51:53.986095: Epoch 222 +2024-11-21 11:51:53.986204: Current learning rate: 0.00975 +2024-11-21 11:52:11.442827: train_loss -0.7424 +2024-11-21 11:52:11.443109: val_loss -0.7461 +2024-11-21 11:52:11.443193: Pseudo dice [0.8205] +2024-11-21 11:52:11.443276: Epoch time: 17.46 s +2024-11-21 11:52:12.216078: +2024-11-21 11:52:12.216261: Epoch 223 +2024-11-21 11:52:12.216370: Current learning rate: 0.00975 +2024-11-21 11:52:31.311585: train_loss -0.7508 +2024-11-21 11:52:31.311795: val_loss -0.7283 +2024-11-21 11:52:31.311868: Pseudo dice [0.8198] +2024-11-21 11:52:31.311943: Epoch time: 19.1 s +2024-11-21 11:52:32.105509: +2024-11-21 11:52:32.105706: Epoch 224 +2024-11-21 11:52:32.105816: Current learning rate: 0.00975 +2024-11-21 11:52:51.403398: train_loss -0.7439 +2024-11-21 11:52:51.403622: val_loss -0.7743 +2024-11-21 11:52:51.403697: Pseudo dice [0.8423] +2024-11-21 11:52:51.403770: Epoch time: 19.3 s +2024-11-21 11:52:52.350824: +2024-11-21 11:52:52.351029: Epoch 225 +2024-11-21 11:52:52.351141: Current learning rate: 0.00975 +2024-11-21 11:53:11.073537: train_loss -0.7388 +2024-11-21 11:53:11.073740: val_loss -0.7525 +2024-11-21 11:53:11.073811: Pseudo dice [0.8249] +2024-11-21 11:53:11.073882: Epoch time: 18.72 s +2024-11-21 11:53:11.846126: +2024-11-21 11:53:11.846323: Epoch 226 +2024-11-21 11:53:11.846431: Current learning rate: 0.00975 +2024-11-21 11:53:29.856732: train_loss -0.7518 +2024-11-21 11:53:29.856959: val_loss -0.7578 +2024-11-21 11:53:29.857043: Pseudo dice [0.8313] +2024-11-21 11:53:29.857127: Epoch time: 18.01 s +2024-11-21 11:53:30.618197: +2024-11-21 11:53:30.618523: Epoch 227 +2024-11-21 11:53:30.618637: Current learning rate: 0.00974 +2024-11-21 11:53:49.321533: train_loss -0.753 +2024-11-21 11:53:49.321744: val_loss -0.7553 +2024-11-21 11:53:49.321817: Pseudo dice [0.8299] +2024-11-21 11:53:49.321895: Epoch time: 18.7 s +2024-11-21 11:53:50.090362: +2024-11-21 11:53:50.090574: Epoch 228 +2024-11-21 11:53:50.090681: Current learning rate: 0.00974 +2024-11-21 11:54:08.553398: train_loss -0.7408 +2024-11-21 11:54:08.553602: val_loss -0.7332 +2024-11-21 11:54:08.553679: Pseudo dice [0.8272] +2024-11-21 11:54:08.553755: Epoch time: 18.46 s +2024-11-21 11:54:09.682483: +2024-11-21 11:54:09.682710: Epoch 229 +2024-11-21 11:54:09.682823: Current learning rate: 0.00974 +2024-11-21 11:54:27.530887: train_loss -0.7622 +2024-11-21 11:54:27.531161: val_loss -0.7681 +2024-11-21 11:54:27.531248: Pseudo dice [0.8276] +2024-11-21 11:54:27.531332: Epoch time: 17.85 s +2024-11-21 11:54:28.293428: +2024-11-21 11:54:28.293713: Epoch 230 +2024-11-21 11:54:28.293826: Current learning rate: 0.00974 +2024-11-21 11:54:46.051520: train_loss -0.7529 +2024-11-21 11:54:46.051746: val_loss -0.7505 +2024-11-21 11:54:46.051820: Pseudo dice [0.8488] +2024-11-21 11:54:46.051894: Epoch time: 17.76 s +2024-11-21 11:54:46.919748: +2024-11-21 11:54:46.920026: Epoch 231 +2024-11-21 11:54:46.920141: Current learning rate: 0.00974 +2024-11-21 11:55:05.711638: train_loss -0.7548 +2024-11-21 11:55:05.711845: val_loss -0.7244 +2024-11-21 11:55:05.711918: Pseudo dice [0.8425] +2024-11-21 11:55:05.712001: Epoch time: 18.79 s +2024-11-21 11:55:06.481108: +2024-11-21 11:55:06.481308: Epoch 232 +2024-11-21 11:55:06.481414: Current learning rate: 0.00974 +2024-11-21 11:55:24.067129: train_loss -0.7408 +2024-11-21 11:55:24.067345: val_loss -0.749 +2024-11-21 11:55:24.067420: Pseudo dice [0.8307] +2024-11-21 11:55:24.067497: Epoch time: 17.59 s +2024-11-21 11:55:24.836818: +2024-11-21 11:55:24.837042: Epoch 233 +2024-11-21 11:55:24.837173: Current learning rate: 0.00974 +2024-11-21 11:55:42.964847: train_loss -0.7394 +2024-11-21 11:55:42.965094: val_loss -0.7694 +2024-11-21 11:55:42.965171: Pseudo dice [0.8223] +2024-11-21 11:55:42.965249: Epoch time: 18.13 s +2024-11-21 11:55:43.732066: +2024-11-21 11:55:43.732355: Epoch 234 +2024-11-21 11:55:43.732468: Current learning rate: 0.00974 +2024-11-21 11:56:01.019707: train_loss -0.7396 +2024-11-21 11:56:01.019921: val_loss -0.7665 +2024-11-21 11:56:01.020004: Pseudo dice [0.8216] +2024-11-21 11:56:01.020104: Epoch time: 17.29 s +2024-11-21 11:56:01.786120: +2024-11-21 11:56:01.786327: Epoch 235 +2024-11-21 11:56:01.786433: Current learning rate: 0.00974 +2024-11-21 11:56:20.693600: train_loss -0.7485 +2024-11-21 11:56:20.695950: val_loss -0.7448 +2024-11-21 11:56:20.696105: Pseudo dice [0.8286] +2024-11-21 11:56:20.696240: Epoch time: 18.91 s +2024-11-21 11:56:21.611347: +2024-11-21 11:56:21.611589: Epoch 236 +2024-11-21 11:56:21.611698: Current learning rate: 0.00973 +2024-11-21 11:56:40.308172: train_loss -0.7384 +2024-11-21 11:56:40.308400: val_loss -0.733 +2024-11-21 11:56:40.308479: Pseudo dice [0.8345] +2024-11-21 11:56:40.308559: Epoch time: 18.7 s +2024-11-21 11:56:41.128766: +2024-11-21 11:56:41.128988: Epoch 237 +2024-11-21 11:56:41.129111: Current learning rate: 0.00973 +2024-11-21 11:56:59.270121: train_loss -0.7513 +2024-11-21 11:56:59.270358: val_loss -0.7674 +2024-11-21 11:56:59.270457: Pseudo dice [0.8478] +2024-11-21 11:56:59.270544: Epoch time: 18.14 s +2024-11-21 11:57:00.030752: +2024-11-21 11:57:00.030956: Epoch 238 +2024-11-21 11:57:00.031069: Current learning rate: 0.00973 +2024-11-21 11:57:18.447051: train_loss -0.7486 +2024-11-21 11:57:18.447264: val_loss -0.7753 +2024-11-21 11:57:18.447340: Pseudo dice [0.8474] +2024-11-21 11:57:18.447417: Epoch time: 18.42 s +2024-11-21 11:57:19.210963: +2024-11-21 11:57:19.211180: Epoch 239 +2024-11-21 11:57:19.211289: Current learning rate: 0.00973 +2024-11-21 11:57:37.367532: train_loss -0.7476 +2024-11-21 11:57:37.367737: val_loss -0.7262 +2024-11-21 11:57:37.367809: Pseudo dice [0.8164] +2024-11-21 11:57:37.367882: Epoch time: 18.16 s +2024-11-21 11:57:38.151572: +2024-11-21 11:57:38.151764: Epoch 240 +2024-11-21 11:57:38.151872: Current learning rate: 0.00973 +2024-11-21 11:57:57.450698: train_loss -0.7553 +2024-11-21 11:57:57.450950: val_loss -0.7342 +2024-11-21 11:57:57.451033: Pseudo dice [0.8286] +2024-11-21 11:57:57.451116: Epoch time: 19.3 s +2024-11-21 11:57:58.608083: +2024-11-21 11:57:58.608361: Epoch 241 +2024-11-21 11:57:58.608479: Current learning rate: 0.00973 +2024-11-21 11:58:16.839614: train_loss -0.7504 +2024-11-21 11:58:16.839836: val_loss -0.7543 +2024-11-21 11:58:16.839908: Pseudo dice [0.8337] +2024-11-21 11:58:16.839983: Epoch time: 18.23 s +2024-11-21 11:58:17.749401: +2024-11-21 11:58:17.749634: Epoch 242 +2024-11-21 11:58:17.749763: Current learning rate: 0.00973 +2024-11-21 11:58:35.484665: train_loss -0.7562 +2024-11-21 11:58:35.484880: val_loss -0.761 +2024-11-21 11:58:35.484952: Pseudo dice [0.8369] +2024-11-21 11:58:35.485033: Epoch time: 17.74 s +2024-11-21 11:58:36.251695: +2024-11-21 11:58:36.251907: Epoch 243 +2024-11-21 11:58:36.252025: Current learning rate: 0.00973 +2024-11-21 11:58:54.542355: train_loss -0.7513 +2024-11-21 11:58:54.542585: val_loss -0.7401 +2024-11-21 11:58:54.542659: Pseudo dice [0.8283] +2024-11-21 11:58:54.542739: Epoch time: 18.29 s +2024-11-21 11:58:55.356125: +2024-11-21 11:58:55.356395: Epoch 244 +2024-11-21 11:58:55.356510: Current learning rate: 0.00973 +2024-11-21 11:59:13.851876: train_loss -0.7484 +2024-11-21 11:59:13.852084: val_loss -0.7635 +2024-11-21 11:59:13.852156: Pseudo dice [0.8449] +2024-11-21 11:59:13.852228: Epoch time: 18.5 s +2024-11-21 11:59:14.629469: +2024-11-21 11:59:14.629664: Epoch 245 +2024-11-21 11:59:14.630362: Current learning rate: 0.00972 +2024-11-21 11:59:33.300954: train_loss -0.7516 +2024-11-21 11:59:33.301212: val_loss -0.7634 +2024-11-21 11:59:33.301289: Pseudo dice [0.8399] +2024-11-21 11:59:33.301363: Epoch time: 18.67 s +2024-11-21 11:59:34.140186: +2024-11-21 11:59:34.140393: Epoch 246 +2024-11-21 11:59:34.140508: Current learning rate: 0.00972 +2024-11-21 11:59:52.195261: train_loss -0.7596 +2024-11-21 11:59:52.195503: val_loss -0.7481 +2024-11-21 11:59:52.195585: Pseudo dice [0.8468] +2024-11-21 11:59:52.195682: Epoch time: 18.06 s +2024-11-21 11:59:53.006101: +2024-11-21 11:59:53.006316: Epoch 247 +2024-11-21 11:59:53.006427: Current learning rate: 0.00972 +2024-11-21 12:00:11.586947: train_loss -0.7555 +2024-11-21 12:00:11.587191: val_loss -0.7592 +2024-11-21 12:00:11.587266: Pseudo dice [0.8309] +2024-11-21 12:00:11.587347: Epoch time: 18.58 s +2024-11-21 12:00:12.361336: +2024-11-21 12:00:12.361549: Epoch 248 +2024-11-21 12:00:12.361661: Current learning rate: 0.00972 +2024-11-21 12:00:29.677704: train_loss -0.751 +2024-11-21 12:00:29.677919: val_loss -0.7218 +2024-11-21 12:00:29.678070: Pseudo dice [0.8271] +2024-11-21 12:00:29.678148: Epoch time: 17.32 s +2024-11-21 12:00:30.458278: +2024-11-21 12:00:30.458488: Epoch 249 +2024-11-21 12:00:30.458596: Current learning rate: 0.00972 +2024-11-21 12:00:48.301345: train_loss -0.7383 +2024-11-21 12:00:48.301553: val_loss -0.7555 +2024-11-21 12:00:48.301626: Pseudo dice [0.8315] +2024-11-21 12:00:48.301716: Epoch time: 17.84 s +2024-11-21 12:00:49.294779: +2024-11-21 12:00:49.294983: Epoch 250 +2024-11-21 12:00:49.295099: Current learning rate: 0.00972 +2024-11-21 12:01:08.485567: train_loss -0.7376 +2024-11-21 12:01:08.485785: val_loss -0.7504 +2024-11-21 12:01:08.485867: Pseudo dice [0.8195] +2024-11-21 12:01:08.485942: Epoch time: 19.19 s +2024-11-21 12:01:09.264259: +2024-11-21 12:01:09.264475: Epoch 251 +2024-11-21 12:01:09.264596: Current learning rate: 0.00972 +2024-11-21 12:01:27.374112: train_loss -0.7456 +2024-11-21 12:01:27.374323: val_loss -0.7609 +2024-11-21 12:01:27.374395: Pseudo dice [0.8302] +2024-11-21 12:01:27.374468: Epoch time: 18.11 s +2024-11-21 12:01:28.296692: +2024-11-21 12:01:28.296903: Epoch 252 +2024-11-21 12:01:28.297022: Current learning rate: 0.00972 +2024-11-21 12:01:47.404026: train_loss -0.7447 +2024-11-21 12:01:47.404246: val_loss -0.7173 +2024-11-21 12:01:47.404320: Pseudo dice [0.8047] +2024-11-21 12:01:47.404394: Epoch time: 19.11 s +2024-11-21 12:01:48.569967: +2024-11-21 12:01:48.570203: Epoch 253 +2024-11-21 12:01:48.570319: Current learning rate: 0.00971 +2024-11-21 12:02:06.579195: train_loss -0.7517 +2024-11-21 12:02:06.579494: val_loss -0.7363 +2024-11-21 12:02:06.579577: Pseudo dice [0.839] +2024-11-21 12:02:06.579663: Epoch time: 18.01 s +2024-11-21 12:02:07.355424: +2024-11-21 12:02:07.355648: Epoch 254 +2024-11-21 12:02:07.355767: Current learning rate: 0.00971 +2024-11-21 12:02:26.111886: train_loss -0.7442 +2024-11-21 12:02:26.112097: val_loss -0.7306 +2024-11-21 12:02:26.112169: Pseudo dice [0.8095] +2024-11-21 12:02:26.112241: Epoch time: 18.76 s +2024-11-21 12:02:26.926015: +2024-11-21 12:02:26.926301: Epoch 255 +2024-11-21 12:02:26.926426: Current learning rate: 0.00971 +2024-11-21 12:02:46.029747: train_loss -0.7512 +2024-11-21 12:02:46.029962: val_loss -0.7488 +2024-11-21 12:02:46.030043: Pseudo dice [0.832] +2024-11-21 12:02:46.032321: Epoch time: 19.1 s +2024-11-21 12:02:47.010446: +2024-11-21 12:02:47.010638: Epoch 256 +2024-11-21 12:02:47.010744: Current learning rate: 0.00971 +2024-11-21 12:03:06.015151: train_loss -0.7491 +2024-11-21 12:03:06.015414: val_loss -0.7537 +2024-11-21 12:03:06.015494: Pseudo dice [0.8338] +2024-11-21 12:03:06.015575: Epoch time: 19.01 s +2024-11-21 12:03:06.810488: +2024-11-21 12:03:06.810715: Epoch 257 +2024-11-21 12:03:06.810831: Current learning rate: 0.00971 +2024-11-21 12:03:25.256004: train_loss -0.7429 +2024-11-21 12:03:25.256233: val_loss -0.7357 +2024-11-21 12:03:25.256378: Pseudo dice [0.8413] +2024-11-21 12:03:25.256455: Epoch time: 18.45 s +2024-11-21 12:03:26.122970: +2024-11-21 12:03:26.123237: Epoch 258 +2024-11-21 12:03:26.123343: Current learning rate: 0.00971 +2024-11-21 12:03:44.805929: train_loss -0.7448 +2024-11-21 12:03:44.806154: val_loss -0.7421 +2024-11-21 12:03:44.806227: Pseudo dice [0.8251] +2024-11-21 12:03:44.806302: Epoch time: 18.68 s +2024-11-21 12:03:45.604372: +2024-11-21 12:03:45.604581: Epoch 259 +2024-11-21 12:03:45.604688: Current learning rate: 0.00971 +2024-11-21 12:04:03.572703: train_loss -0.7497 +2024-11-21 12:04:03.572917: val_loss -0.731 +2024-11-21 12:04:03.572998: Pseudo dice [0.8148] +2024-11-21 12:04:03.573074: Epoch time: 17.97 s +2024-11-21 12:04:04.360529: +2024-11-21 12:04:04.360758: Epoch 260 +2024-11-21 12:04:04.360869: Current learning rate: 0.00971 +2024-11-21 12:04:24.267526: train_loss -0.7407 +2024-11-21 12:04:24.267753: val_loss -0.7197 +2024-11-21 12:04:24.267827: Pseudo dice [0.8143] +2024-11-21 12:04:24.267905: Epoch time: 19.91 s +2024-11-21 12:04:25.148673: +2024-11-21 12:04:25.148879: Epoch 261 +2024-11-21 12:04:25.148989: Current learning rate: 0.00971 +2024-11-21 12:04:43.873541: train_loss -0.7386 +2024-11-21 12:04:43.873767: val_loss -0.7422 +2024-11-21 12:04:43.873840: Pseudo dice [0.8384] +2024-11-21 12:04:43.873917: Epoch time: 18.73 s +2024-11-21 12:04:44.651592: +2024-11-21 12:04:44.651789: Epoch 262 +2024-11-21 12:04:44.651899: Current learning rate: 0.0097 +2024-11-21 12:05:03.345187: train_loss -0.736 +2024-11-21 12:05:03.345389: val_loss -0.7544 +2024-11-21 12:05:03.345463: Pseudo dice [0.8301] +2024-11-21 12:05:03.345535: Epoch time: 18.69 s +2024-11-21 12:05:04.139792: +2024-11-21 12:05:04.139961: Epoch 263 +2024-11-21 12:05:04.140074: Current learning rate: 0.0097 +2024-11-21 12:05:23.026612: train_loss -0.7544 +2024-11-21 12:05:23.026826: val_loss -0.7651 +2024-11-21 12:05:23.026901: Pseudo dice [0.8361] +2024-11-21 12:05:23.026981: Epoch time: 18.89 s +2024-11-21 12:05:23.822142: +2024-11-21 12:05:23.822326: Epoch 264 +2024-11-21 12:05:23.822442: Current learning rate: 0.0097 +2024-11-21 12:05:42.711489: train_loss -0.747 +2024-11-21 12:05:42.711750: val_loss -0.7468 +2024-11-21 12:05:42.711827: Pseudo dice [0.8391] +2024-11-21 12:05:42.711909: Epoch time: 18.89 s +2024-11-21 12:05:43.506363: +2024-11-21 12:05:43.506549: Epoch 265 +2024-11-21 12:05:43.506656: Current learning rate: 0.0097 +2024-11-21 12:06:01.627658: train_loss -0.7258 +2024-11-21 12:06:01.627885: val_loss -0.7215 +2024-11-21 12:06:01.627975: Pseudo dice [0.8223] +2024-11-21 12:06:01.628057: Epoch time: 18.12 s +2024-11-21 12:06:02.420838: +2024-11-21 12:06:02.421072: Epoch 266 +2024-11-21 12:06:02.421185: Current learning rate: 0.0097 +2024-11-21 12:06:21.214833: train_loss -0.7342 +2024-11-21 12:06:21.215058: val_loss -0.7278 +2024-11-21 12:06:21.215134: Pseudo dice [0.8321] +2024-11-21 12:06:21.215252: Epoch time: 18.79 s +2024-11-21 12:06:22.009145: +2024-11-21 12:06:22.009374: Epoch 267 +2024-11-21 12:06:22.009487: Current learning rate: 0.0097 +2024-11-21 12:06:39.824732: train_loss -0.7313 +2024-11-21 12:06:39.824979: val_loss -0.7344 +2024-11-21 12:06:39.825060: Pseudo dice [0.8177] +2024-11-21 12:06:39.825143: Epoch time: 17.82 s +2024-11-21 12:06:40.621477: +2024-11-21 12:06:40.621650: Epoch 268 +2024-11-21 12:06:40.621770: Current learning rate: 0.0097 +2024-11-21 12:06:58.909046: train_loss -0.7529 +2024-11-21 12:06:58.909248: val_loss -0.7298 +2024-11-21 12:06:58.909323: Pseudo dice [0.83] +2024-11-21 12:06:58.909395: Epoch time: 18.29 s +2024-11-21 12:06:59.784328: +2024-11-21 12:06:59.784540: Epoch 269 +2024-11-21 12:06:59.784652: Current learning rate: 0.0097 +2024-11-21 12:07:17.762555: train_loss -0.7386 +2024-11-21 12:07:17.762773: val_loss -0.7114 +2024-11-21 12:07:17.762845: Pseudo dice [0.8357] +2024-11-21 12:07:17.762917: Epoch time: 17.98 s +2024-11-21 12:07:18.551184: +2024-11-21 12:07:18.551369: Epoch 270 +2024-11-21 12:07:18.551485: Current learning rate: 0.0097 +2024-11-21 12:07:36.351013: train_loss -0.7424 +2024-11-21 12:07:36.351246: val_loss -0.75 +2024-11-21 12:07:36.351331: Pseudo dice [0.8349] +2024-11-21 12:07:36.351413: Epoch time: 17.8 s +2024-11-21 12:07:37.248310: +2024-11-21 12:07:37.248599: Epoch 271 +2024-11-21 12:07:37.249016: Current learning rate: 0.00969 +2024-11-21 12:07:55.528211: train_loss -0.7304 +2024-11-21 12:07:55.530632: val_loss -0.7271 +2024-11-21 12:07:55.530752: Pseudo dice [0.8017] +2024-11-21 12:07:55.530836: Epoch time: 18.28 s +2024-11-21 12:07:56.351159: +2024-11-21 12:07:56.351423: Epoch 272 +2024-11-21 12:07:56.351541: Current learning rate: 0.00969 +2024-11-21 12:08:14.048926: train_loss -0.74 +2024-11-21 12:08:14.049157: val_loss -0.7393 +2024-11-21 12:08:14.049233: Pseudo dice [0.8044] +2024-11-21 12:08:14.049309: Epoch time: 17.7 s +2024-11-21 12:08:14.826943: +2024-11-21 12:08:14.827139: Epoch 273 +2024-11-21 12:08:14.827245: Current learning rate: 0.00969 +2024-11-21 12:08:31.928006: train_loss -0.7293 +2024-11-21 12:08:31.928210: val_loss -0.7335 +2024-11-21 12:08:31.928286: Pseudo dice [0.8211] +2024-11-21 12:08:31.928360: Epoch time: 17.1 s +2024-11-21 12:08:32.709170: +2024-11-21 12:08:32.709380: Epoch 274 +2024-11-21 12:08:32.709491: Current learning rate: 0.00969 +2024-11-21 12:08:51.760948: train_loss -0.7249 +2024-11-21 12:08:51.761181: val_loss -0.7318 +2024-11-21 12:08:51.761256: Pseudo dice [0.841] +2024-11-21 12:08:51.761339: Epoch time: 19.05 s +2024-11-21 12:08:52.578977: +2024-11-21 12:08:52.579166: Epoch 275 +2024-11-21 12:08:52.579287: Current learning rate: 0.00969 +2024-11-21 12:09:11.081064: train_loss -0.7367 +2024-11-21 12:09:11.081277: val_loss -0.7842 +2024-11-21 12:09:11.081352: Pseudo dice [0.8543] +2024-11-21 12:09:11.081469: Epoch time: 18.5 s +2024-11-21 12:09:12.296587: +2024-11-21 12:09:12.296827: Epoch 276 +2024-11-21 12:09:12.296937: Current learning rate: 0.00969 +2024-11-21 12:09:30.738304: train_loss -0.7555 +2024-11-21 12:09:30.738514: val_loss -0.7724 +2024-11-21 12:09:30.738589: Pseudo dice [0.8346] +2024-11-21 12:09:30.738684: Epoch time: 18.44 s +2024-11-21 12:09:31.512200: +2024-11-21 12:09:31.512425: Epoch 277 +2024-11-21 12:09:31.512533: Current learning rate: 0.00969 +2024-11-21 12:09:49.193565: train_loss -0.7469 +2024-11-21 12:09:49.193806: val_loss -0.7416 +2024-11-21 12:09:49.193883: Pseudo dice [0.8155] +2024-11-21 12:09:49.193965: Epoch time: 17.68 s +2024-11-21 12:09:49.970870: +2024-11-21 12:09:49.971102: Epoch 278 +2024-11-21 12:09:49.971221: Current learning rate: 0.00969 +2024-11-21 12:10:08.571088: train_loss -0.7417 +2024-11-21 12:10:08.571354: val_loss -0.7797 +2024-11-21 12:10:08.571433: Pseudo dice [0.8455] +2024-11-21 12:10:08.571512: Epoch time: 18.6 s +2024-11-21 12:10:09.364477: +2024-11-21 12:10:09.364694: Epoch 279 +2024-11-21 12:10:09.364811: Current learning rate: 0.00969 +2024-11-21 12:10:26.974102: train_loss -0.7529 +2024-11-21 12:10:26.974305: val_loss -0.7854 +2024-11-21 12:10:26.974379: Pseudo dice [0.8428] +2024-11-21 12:10:26.974449: Epoch time: 17.61 s +2024-11-21 12:10:27.752401: +2024-11-21 12:10:27.752638: Epoch 280 +2024-11-21 12:10:27.752750: Current learning rate: 0.00968 +2024-11-21 12:10:45.429896: train_loss -0.7485 +2024-11-21 12:10:45.430104: val_loss -0.7587 +2024-11-21 12:10:45.430177: Pseudo dice [0.836] +2024-11-21 12:10:45.430250: Epoch time: 17.68 s +2024-11-21 12:10:46.424149: +2024-11-21 12:10:46.424365: Epoch 281 +2024-11-21 12:10:46.424480: Current learning rate: 0.00968 +2024-11-21 12:11:05.306377: train_loss -0.7419 +2024-11-21 12:11:05.306633: val_loss -0.7391 +2024-11-21 12:11:05.306710: Pseudo dice [0.8263] +2024-11-21 12:11:05.306793: Epoch time: 18.88 s +2024-11-21 12:11:06.094625: +2024-11-21 12:11:06.094831: Epoch 282 +2024-11-21 12:11:06.094936: Current learning rate: 0.00968 +2024-11-21 12:11:25.025670: train_loss -0.7268 +2024-11-21 12:11:25.025887: val_loss -0.7477 +2024-11-21 12:11:25.025959: Pseudo dice [0.8173] +2024-11-21 12:11:25.026040: Epoch time: 18.93 s +2024-11-21 12:11:26.037868: +2024-11-21 12:11:26.038226: Epoch 283 +2024-11-21 12:11:26.038339: Current learning rate: 0.00968 +2024-11-21 12:11:44.106826: train_loss -0.7373 +2024-11-21 12:11:44.107047: val_loss -0.7218 +2024-11-21 12:11:44.107118: Pseudo dice [0.8313] +2024-11-21 12:11:44.107193: Epoch time: 18.07 s +2024-11-21 12:11:44.904656: +2024-11-21 12:11:44.904865: Epoch 284 +2024-11-21 12:11:44.904980: Current learning rate: 0.00968 +2024-11-21 12:12:02.877293: train_loss -0.7311 +2024-11-21 12:12:02.877502: val_loss -0.7554 +2024-11-21 12:12:02.877579: Pseudo dice [0.8219] +2024-11-21 12:12:02.877654: Epoch time: 17.97 s +2024-11-21 12:12:03.667653: +2024-11-21 12:12:03.667846: Epoch 285 +2024-11-21 12:12:03.667955: Current learning rate: 0.00968 +2024-11-21 12:12:21.844141: train_loss -0.7366 +2024-11-21 12:12:21.844380: val_loss -0.7206 +2024-11-21 12:12:21.844460: Pseudo dice [0.825] +2024-11-21 12:12:21.844538: Epoch time: 18.18 s +2024-11-21 12:12:22.630286: +2024-11-21 12:12:22.630565: Epoch 286 +2024-11-21 12:12:22.630674: Current learning rate: 0.00968 +2024-11-21 12:12:40.478638: train_loss -0.7407 +2024-11-21 12:12:40.478857: val_loss -0.7386 +2024-11-21 12:12:40.478929: Pseudo dice [0.8208] +2024-11-21 12:12:40.479005: Epoch time: 17.85 s +2024-11-21 12:12:41.300283: +2024-11-21 12:12:41.300549: Epoch 287 +2024-11-21 12:12:41.300663: Current learning rate: 0.00968 +2024-11-21 12:13:00.201799: train_loss -0.7478 +2024-11-21 12:13:00.202035: val_loss -0.7497 +2024-11-21 12:13:00.202116: Pseudo dice [0.8279] +2024-11-21 12:13:00.202195: Epoch time: 18.9 s +2024-11-21 12:13:01.004832: +2024-11-21 12:13:01.005032: Epoch 288 +2024-11-21 12:13:01.005138: Current learning rate: 0.00968 +2024-11-21 12:13:19.614102: train_loss -0.7504 +2024-11-21 12:13:19.614327: val_loss -0.7614 +2024-11-21 12:13:19.614398: Pseudo dice [0.8436] +2024-11-21 12:13:19.614474: Epoch time: 18.61 s +2024-11-21 12:13:20.618186: +2024-11-21 12:13:20.618405: Epoch 289 +2024-11-21 12:13:20.618519: Current learning rate: 0.00967 +2024-11-21 12:13:37.721030: train_loss -0.7509 +2024-11-21 12:13:37.721237: val_loss -0.7872 +2024-11-21 12:13:37.721313: Pseudo dice [0.852] +2024-11-21 12:13:37.721389: Epoch time: 17.1 s +2024-11-21 12:13:38.516942: +2024-11-21 12:13:38.517263: Epoch 290 +2024-11-21 12:13:38.517371: Current learning rate: 0.00967 +2024-11-21 12:13:57.412559: train_loss -0.7467 +2024-11-21 12:13:57.412801: val_loss -0.7421 +2024-11-21 12:13:57.412882: Pseudo dice [0.8325] +2024-11-21 12:13:57.412956: Epoch time: 18.9 s +2024-11-21 12:13:58.198140: +2024-11-21 12:13:58.198336: Epoch 291 +2024-11-21 12:13:58.198446: Current learning rate: 0.00967 +2024-11-21 12:14:15.570494: train_loss -0.7557 +2024-11-21 12:14:15.570744: val_loss -0.7633 +2024-11-21 12:14:15.576014: Pseudo dice [0.8289] +2024-11-21 12:14:15.576140: Epoch time: 17.37 s +2024-11-21 12:14:16.470160: +2024-11-21 12:14:16.470352: Epoch 292 +2024-11-21 12:14:16.470463: Current learning rate: 0.00967 +2024-11-21 12:14:35.314924: train_loss -0.7518 +2024-11-21 12:14:35.315155: val_loss -0.7463 +2024-11-21 12:14:35.315275: Pseudo dice [0.8327] +2024-11-21 12:14:35.315348: Epoch time: 18.85 s +2024-11-21 12:14:36.101057: +2024-11-21 12:14:36.101263: Epoch 293 +2024-11-21 12:14:36.101380: Current learning rate: 0.00967 +2024-11-21 12:14:54.224166: train_loss -0.7444 +2024-11-21 12:14:54.224432: val_loss -0.7323 +2024-11-21 12:14:54.224513: Pseudo dice [0.8294] +2024-11-21 12:14:54.224587: Epoch time: 18.12 s +2024-11-21 12:14:55.010335: +2024-11-21 12:14:55.010542: Epoch 294 +2024-11-21 12:14:55.010651: Current learning rate: 0.00967 +2024-11-21 12:15:12.616375: train_loss -0.7568 +2024-11-21 12:15:12.616587: val_loss -0.7685 +2024-11-21 12:15:12.616663: Pseudo dice [0.8466] +2024-11-21 12:15:12.618954: Epoch time: 17.61 s +2024-11-21 12:15:13.506513: +2024-11-21 12:15:13.506716: Epoch 295 +2024-11-21 12:15:13.506832: Current learning rate: 0.00967 +2024-11-21 12:15:31.037237: train_loss -0.7444 +2024-11-21 12:15:31.037477: val_loss -0.7761 +2024-11-21 12:15:31.037553: Pseudo dice [0.8313] +2024-11-21 12:15:31.037632: Epoch time: 17.53 s +2024-11-21 12:15:31.975010: +2024-11-21 12:15:31.975236: Epoch 296 +2024-11-21 12:15:31.975348: Current learning rate: 0.00967 +2024-11-21 12:15:49.996370: train_loss -0.7481 +2024-11-21 12:15:49.996587: val_loss -0.7577 +2024-11-21 12:15:49.996659: Pseudo dice [0.8337] +2024-11-21 12:15:49.996765: Epoch time: 18.02 s +2024-11-21 12:15:50.790118: +2024-11-21 12:15:50.790289: Epoch 297 +2024-11-21 12:15:50.790964: Current learning rate: 0.00967 +2024-11-21 12:16:08.836669: train_loss -0.7363 +2024-11-21 12:16:08.838909: val_loss -0.7598 +2024-11-21 12:16:08.839013: Pseudo dice [0.8427] +2024-11-21 12:16:08.839092: Epoch time: 18.05 s +2024-11-21 12:16:09.644320: +2024-11-21 12:16:09.644516: Epoch 298 +2024-11-21 12:16:09.644623: Current learning rate: 0.00966 +2024-11-21 12:16:28.000305: train_loss -0.7398 +2024-11-21 12:16:28.000547: val_loss -0.7524 +2024-11-21 12:16:28.002853: Pseudo dice [0.832] +2024-11-21 12:16:28.002957: Epoch time: 18.36 s +2024-11-21 12:16:29.209392: +2024-11-21 12:16:29.209608: Epoch 299 +2024-11-21 12:16:29.209714: Current learning rate: 0.00966 +2024-11-21 12:16:47.332640: train_loss -0.7352 +2024-11-21 12:16:47.332879: val_loss -0.7655 +2024-11-21 12:16:47.332950: Pseudo dice [0.8231] +2024-11-21 12:16:47.333029: Epoch time: 18.12 s +2024-11-21 12:16:48.368402: +2024-11-21 12:16:48.368690: Epoch 300 +2024-11-21 12:16:48.368809: Current learning rate: 0.00966 +2024-11-21 12:17:06.522763: train_loss -0.7509 +2024-11-21 12:17:06.522975: val_loss -0.7335 +2024-11-21 12:17:06.523054: Pseudo dice [0.8215] +2024-11-21 12:17:06.523127: Epoch time: 18.16 s +2024-11-21 12:17:07.354191: +2024-11-21 12:17:07.354415: Epoch 301 +2024-11-21 12:17:07.354525: Current learning rate: 0.00966 +2024-11-21 12:17:25.685073: train_loss -0.7412 +2024-11-21 12:17:25.685296: val_loss -0.7484 +2024-11-21 12:17:25.685375: Pseudo dice [0.8184] +2024-11-21 12:17:25.685456: Epoch time: 18.33 s +2024-11-21 12:17:26.495479: +2024-11-21 12:17:26.495718: Epoch 302 +2024-11-21 12:17:26.495866: Current learning rate: 0.00966 +2024-11-21 12:17:45.139300: train_loss -0.7501 +2024-11-21 12:17:45.139522: val_loss -0.7451 +2024-11-21 12:17:45.139596: Pseudo dice [0.8159] +2024-11-21 12:17:45.139674: Epoch time: 18.64 s +2024-11-21 12:17:45.957713: +2024-11-21 12:17:45.957920: Epoch 303 +2024-11-21 12:17:45.958040: Current learning rate: 0.00966 +2024-11-21 12:18:04.822504: train_loss -0.7531 +2024-11-21 12:18:04.822718: val_loss -0.7468 +2024-11-21 12:18:04.822790: Pseudo dice [0.8246] +2024-11-21 12:18:04.822862: Epoch time: 18.87 s +2024-11-21 12:18:05.702295: +2024-11-21 12:18:05.702511: Epoch 304 +2024-11-21 12:18:05.702620: Current learning rate: 0.00966 +2024-11-21 12:18:23.921562: train_loss -0.743 +2024-11-21 12:18:23.921783: val_loss -0.7552 +2024-11-21 12:18:23.921857: Pseudo dice [0.8296] +2024-11-21 12:18:23.921931: Epoch time: 18.22 s +2024-11-21 12:18:24.855839: +2024-11-21 12:18:24.856030: Epoch 305 +2024-11-21 12:18:24.856144: Current learning rate: 0.00966 +2024-11-21 12:18:42.556624: train_loss -0.7588 +2024-11-21 12:18:42.556837: val_loss -0.7638 +2024-11-21 12:18:42.556917: Pseudo dice [0.8284] +2024-11-21 12:18:42.557000: Epoch time: 17.7 s +2024-11-21 12:18:43.342658: +2024-11-21 12:18:43.342863: Epoch 306 +2024-11-21 12:18:43.342977: Current learning rate: 0.00966 +2024-11-21 12:19:00.972940: train_loss -0.7445 +2024-11-21 12:19:00.973178: val_loss -0.7292 +2024-11-21 12:19:00.973254: Pseudo dice [0.8291] +2024-11-21 12:19:00.973334: Epoch time: 17.63 s +2024-11-21 12:19:01.771649: +2024-11-21 12:19:01.771955: Epoch 307 +2024-11-21 12:19:01.772070: Current learning rate: 0.00965 +2024-11-21 12:19:19.826967: train_loss -0.7334 +2024-11-21 12:19:19.827178: val_loss -0.7158 +2024-11-21 12:19:19.827249: Pseudo dice [0.7934] +2024-11-21 12:19:19.827326: Epoch time: 18.06 s +2024-11-21 12:19:20.775549: +2024-11-21 12:19:20.775835: Epoch 308 +2024-11-21 12:19:20.775950: Current learning rate: 0.00965 +2024-11-21 12:19:39.825177: train_loss -0.7387 +2024-11-21 12:19:39.825383: val_loss -0.7503 +2024-11-21 12:19:39.825456: Pseudo dice [0.8191] +2024-11-21 12:19:39.825530: Epoch time: 19.05 s +2024-11-21 12:19:40.612116: +2024-11-21 12:19:40.612301: Epoch 309 +2024-11-21 12:19:40.612414: Current learning rate: 0.00965 +2024-11-21 12:19:59.139779: train_loss -0.7593 +2024-11-21 12:19:59.140026: val_loss -0.7706 +2024-11-21 12:19:59.140103: Pseudo dice [0.844] +2024-11-21 12:19:59.140190: Epoch time: 18.53 s +2024-11-21 12:19:59.959195: +2024-11-21 12:19:59.959384: Epoch 310 +2024-11-21 12:19:59.959493: Current learning rate: 0.00965 +2024-11-21 12:20:17.956536: train_loss -0.7501 +2024-11-21 12:20:17.956750: val_loss -0.7532 +2024-11-21 12:20:17.956840: Pseudo dice [0.836] +2024-11-21 12:20:17.956933: Epoch time: 18.0 s +2024-11-21 12:20:18.754515: +2024-11-21 12:20:18.754720: Epoch 311 +2024-11-21 12:20:18.754828: Current learning rate: 0.00965 +2024-11-21 12:20:37.365451: train_loss -0.753 +2024-11-21 12:20:37.365666: val_loss -0.7138 +2024-11-21 12:20:37.365742: Pseudo dice [0.8471] +2024-11-21 12:20:37.368025: Epoch time: 18.61 s +2024-11-21 12:20:38.189674: +2024-11-21 12:20:38.189906: Epoch 312 +2024-11-21 12:20:38.190020: Current learning rate: 0.00965 +2024-11-21 12:20:56.610704: train_loss -0.755 +2024-11-21 12:20:56.610945: val_loss -0.7757 +2024-11-21 12:20:56.611027: Pseudo dice [0.8326] +2024-11-21 12:20:56.611108: Epoch time: 18.42 s +2024-11-21 12:20:57.406091: +2024-11-21 12:20:57.406321: Epoch 313 +2024-11-21 12:20:57.406430: Current learning rate: 0.00965 +2024-11-21 12:21:15.407775: train_loss -0.7584 +2024-11-21 12:21:15.410146: val_loss -0.7613 +2024-11-21 12:21:15.410236: Pseudo dice [0.832] +2024-11-21 12:21:15.410317: Epoch time: 18.0 s +2024-11-21 12:21:16.289615: +2024-11-21 12:21:16.289816: Epoch 314 +2024-11-21 12:21:16.289922: Current learning rate: 0.00965 +2024-11-21 12:21:34.416876: train_loss -0.7412 +2024-11-21 12:21:34.417117: val_loss -0.7672 +2024-11-21 12:21:34.417198: Pseudo dice [0.8378] +2024-11-21 12:21:34.417276: Epoch time: 18.13 s +2024-11-21 12:21:35.247881: +2024-11-21 12:21:35.248176: Epoch 315 +2024-11-21 12:21:35.248292: Current learning rate: 0.00964 +2024-11-21 12:21:53.351483: train_loss -0.7543 +2024-11-21 12:21:53.351703: val_loss -0.7634 +2024-11-21 12:21:53.351834: Pseudo dice [0.8246] +2024-11-21 12:21:53.351911: Epoch time: 18.1 s +2024-11-21 12:21:54.152663: +2024-11-21 12:21:54.152869: Epoch 316 +2024-11-21 12:21:54.152982: Current learning rate: 0.00964 +2024-11-21 12:22:12.522913: train_loss -0.7416 +2024-11-21 12:22:12.523154: val_loss -0.774 +2024-11-21 12:22:12.523227: Pseudo dice [0.8395] +2024-11-21 12:22:12.523306: Epoch time: 18.37 s +2024-11-21 12:22:13.317558: +2024-11-21 12:22:13.317754: Epoch 317 +2024-11-21 12:22:13.317872: Current learning rate: 0.00964 +2024-11-21 12:22:32.073914: train_loss -0.7448 +2024-11-21 12:22:32.074131: val_loss -0.7529 +2024-11-21 12:22:32.074203: Pseudo dice [0.8402] +2024-11-21 12:22:32.074278: Epoch time: 18.76 s +2024-11-21 12:22:32.869442: +2024-11-21 12:22:32.869642: Epoch 318 +2024-11-21 12:22:32.869771: Current learning rate: 0.00964 +2024-11-21 12:22:51.447242: train_loss -0.7495 +2024-11-21 12:22:51.447450: val_loss -0.7553 +2024-11-21 12:22:51.447521: Pseudo dice [0.8246] +2024-11-21 12:22:51.447595: Epoch time: 18.58 s +2024-11-21 12:22:52.335114: +2024-11-21 12:22:52.335340: Epoch 319 +2024-11-21 12:22:52.335453: Current learning rate: 0.00964 +2024-11-21 12:23:11.596903: train_loss -0.7428 +2024-11-21 12:23:11.597118: val_loss -0.7324 +2024-11-21 12:23:11.597208: Pseudo dice [0.8243] +2024-11-21 12:23:11.597281: Epoch time: 19.26 s +2024-11-21 12:23:12.380945: +2024-11-21 12:23:12.381137: Epoch 320 +2024-11-21 12:23:12.381244: Current learning rate: 0.00964 +2024-11-21 12:23:30.999657: train_loss -0.754 +2024-11-21 12:23:30.999910: val_loss -0.7406 +2024-11-21 12:23:30.999984: Pseudo dice [0.8274] +2024-11-21 12:23:31.000079: Epoch time: 18.62 s +2024-11-21 12:23:31.785607: +2024-11-21 12:23:31.785809: Epoch 321 +2024-11-21 12:23:31.785921: Current learning rate: 0.00964 +2024-11-21 12:23:50.693764: train_loss -0.7505 +2024-11-21 12:23:50.693964: val_loss -0.7625 +2024-11-21 12:23:50.694040: Pseudo dice [0.8213] +2024-11-21 12:23:50.694114: Epoch time: 18.91 s +2024-11-21 12:23:51.865084: +2024-11-21 12:23:51.865410: Epoch 322 +2024-11-21 12:23:51.865523: Current learning rate: 0.00964 +2024-11-21 12:24:10.855278: train_loss -0.7578 +2024-11-21 12:24:10.855499: val_loss -0.7531 +2024-11-21 12:24:10.855581: Pseudo dice [0.8187] +2024-11-21 12:24:10.855658: Epoch time: 18.99 s +2024-11-21 12:24:11.644917: +2024-11-21 12:24:11.645143: Epoch 323 +2024-11-21 12:24:11.645334: Current learning rate: 0.00964 +2024-11-21 12:24:29.022673: train_loss -0.749 +2024-11-21 12:24:29.022904: val_loss -0.7446 +2024-11-21 12:24:29.023025: Pseudo dice [0.813] +2024-11-21 12:24:29.023109: Epoch time: 17.38 s +2024-11-21 12:24:29.830358: +2024-11-21 12:24:29.830614: Epoch 324 +2024-11-21 12:24:29.830730: Current learning rate: 0.00963 +2024-11-21 12:24:48.633495: train_loss -0.7561 +2024-11-21 12:24:48.633696: val_loss -0.7281 +2024-11-21 12:24:48.633766: Pseudo dice [0.8247] +2024-11-21 12:24:48.633842: Epoch time: 18.8 s +2024-11-21 12:24:49.418432: +2024-11-21 12:24:49.418651: Epoch 325 +2024-11-21 12:24:49.418772: Current learning rate: 0.00963 +2024-11-21 12:25:07.454056: train_loss -0.7451 +2024-11-21 12:25:07.454261: val_loss -0.7479 +2024-11-21 12:25:07.454333: Pseudo dice [0.8293] +2024-11-21 12:25:07.454407: Epoch time: 18.04 s +2024-11-21 12:25:08.239888: +2024-11-21 12:25:08.240105: Epoch 326 +2024-11-21 12:25:08.240213: Current learning rate: 0.00963 +2024-11-21 12:25:26.444947: train_loss -0.7569 +2024-11-21 12:25:26.445229: val_loss -0.7503 +2024-11-21 12:25:26.445306: Pseudo dice [0.8317] +2024-11-21 12:25:26.445383: Epoch time: 18.21 s +2024-11-21 12:25:27.235955: +2024-11-21 12:25:27.236169: Epoch 327 +2024-11-21 12:25:27.236277: Current learning rate: 0.00963 +2024-11-21 12:25:44.935141: train_loss -0.7497 +2024-11-21 12:25:44.935375: val_loss -0.7615 +2024-11-21 12:25:44.935452: Pseudo dice [0.8335] +2024-11-21 12:25:44.935532: Epoch time: 17.7 s +2024-11-21 12:25:45.726222: +2024-11-21 12:25:45.726434: Epoch 328 +2024-11-21 12:25:45.726548: Current learning rate: 0.00963 +2024-11-21 12:26:04.587044: train_loss -0.7491 +2024-11-21 12:26:04.587255: val_loss -0.756 +2024-11-21 12:26:04.587328: Pseudo dice [0.8471] +2024-11-21 12:26:04.587403: Epoch time: 18.86 s +2024-11-21 12:26:05.374913: +2024-11-21 12:26:05.375181: Epoch 329 +2024-11-21 12:26:05.375298: Current learning rate: 0.00963 +2024-11-21 12:26:22.568931: train_loss -0.7576 +2024-11-21 12:26:22.569151: val_loss -0.748 +2024-11-21 12:26:22.569225: Pseudo dice [0.8266] +2024-11-21 12:26:22.569298: Epoch time: 17.19 s +2024-11-21 12:26:23.358567: +2024-11-21 12:26:23.358768: Epoch 330 +2024-11-21 12:26:23.358878: Current learning rate: 0.00963 +2024-11-21 12:26:40.938379: train_loss -0.7458 +2024-11-21 12:26:40.940785: val_loss -0.7619 +2024-11-21 12:26:40.940881: Pseudo dice [0.8389] +2024-11-21 12:26:40.940961: Epoch time: 17.58 s +2024-11-21 12:26:41.757935: +2024-11-21 12:26:41.758208: Epoch 331 +2024-11-21 12:26:41.758324: Current learning rate: 0.00963 +2024-11-21 12:27:00.440658: train_loss -0.7474 +2024-11-21 12:27:00.440907: val_loss -0.7444 +2024-11-21 12:27:00.443158: Pseudo dice [0.8418] +2024-11-21 12:27:00.443258: Epoch time: 18.68 s +2024-11-21 12:27:01.303152: +2024-11-21 12:27:01.303362: Epoch 332 +2024-11-21 12:27:01.303471: Current learning rate: 0.00963 +2024-11-21 12:27:19.465776: train_loss -0.7463 +2024-11-21 12:27:19.465999: val_loss -0.763 +2024-11-21 12:27:19.466075: Pseudo dice [0.8417] +2024-11-21 12:27:19.466152: Epoch time: 18.16 s +2024-11-21 12:27:20.639836: +2024-11-21 12:27:20.640072: Epoch 333 +2024-11-21 12:27:20.640181: Current learning rate: 0.00962 +2024-11-21 12:27:40.090810: train_loss -0.7335 +2024-11-21 12:27:40.091030: val_loss -0.7479 +2024-11-21 12:27:40.091110: Pseudo dice [0.8251] +2024-11-21 12:27:40.091182: Epoch time: 19.45 s +2024-11-21 12:27:40.883761: +2024-11-21 12:27:40.883968: Epoch 334 +2024-11-21 12:27:40.884080: Current learning rate: 0.00962 +2024-11-21 12:27:59.215484: train_loss -0.7587 +2024-11-21 12:27:59.215698: val_loss -0.7562 +2024-11-21 12:27:59.215770: Pseudo dice [0.8355] +2024-11-21 12:27:59.215848: Epoch time: 18.33 s +2024-11-21 12:28:00.050255: +2024-11-21 12:28:00.050480: Epoch 335 +2024-11-21 12:28:00.050601: Current learning rate: 0.00962 +2024-11-21 12:28:19.014566: train_loss -0.7449 +2024-11-21 12:28:19.014807: val_loss -0.7429 +2024-11-21 12:28:19.014879: Pseudo dice [0.8282] +2024-11-21 12:28:19.014954: Epoch time: 18.97 s +2024-11-21 12:28:19.809746: +2024-11-21 12:28:19.809955: Epoch 336 +2024-11-21 12:28:19.810070: Current learning rate: 0.00962 +2024-11-21 12:28:37.523610: train_loss -0.7559 +2024-11-21 12:28:37.523815: val_loss -0.7248 +2024-11-21 12:28:37.523893: Pseudo dice [0.8203] +2024-11-21 12:28:37.523968: Epoch time: 17.71 s +2024-11-21 12:28:38.321456: +2024-11-21 12:28:38.321669: Epoch 337 +2024-11-21 12:28:38.321775: Current learning rate: 0.00962 +2024-11-21 12:28:57.215870: train_loss -0.7574 +2024-11-21 12:28:57.216111: val_loss -0.7657 +2024-11-21 12:28:57.216184: Pseudo dice [0.8361] +2024-11-21 12:28:57.216255: Epoch time: 18.9 s +2024-11-21 12:28:58.035118: +2024-11-21 12:28:58.035328: Epoch 338 +2024-11-21 12:28:58.035442: Current learning rate: 0.00962 +2024-11-21 12:29:16.824081: train_loss -0.7576 +2024-11-21 12:29:16.824315: val_loss -0.7221 +2024-11-21 12:29:16.824389: Pseudo dice [0.8405] +2024-11-21 12:29:16.824475: Epoch time: 18.79 s +2024-11-21 12:29:17.704086: +2024-11-21 12:29:17.704320: Epoch 339 +2024-11-21 12:29:17.704430: Current learning rate: 0.00962 +2024-11-21 12:29:36.523282: train_loss -0.7591 +2024-11-21 12:29:36.523495: val_loss -0.7722 +2024-11-21 12:29:36.523574: Pseudo dice [0.8379] +2024-11-21 12:29:36.523649: Epoch time: 18.82 s +2024-11-21 12:29:37.320321: +2024-11-21 12:29:37.320593: Epoch 340 +2024-11-21 12:29:37.320705: Current learning rate: 0.00962 +2024-11-21 12:29:55.931870: train_loss -0.754 +2024-11-21 12:29:55.932091: val_loss -0.7213 +2024-11-21 12:29:55.932169: Pseudo dice [0.8148] +2024-11-21 12:29:55.932247: Epoch time: 18.61 s +2024-11-21 12:29:56.731500: +2024-11-21 12:29:56.731702: Epoch 341 +2024-11-21 12:29:56.731807: Current learning rate: 0.00962 +2024-11-21 12:30:15.830945: train_loss -0.7642 +2024-11-21 12:30:15.831198: val_loss -0.75 +2024-11-21 12:30:15.831278: Pseudo dice [0.8376] +2024-11-21 12:30:15.831355: Epoch time: 19.1 s +2024-11-21 12:30:16.630251: +2024-11-21 12:30:16.630440: Epoch 342 +2024-11-21 12:30:16.630547: Current learning rate: 0.00961 +2024-11-21 12:30:34.252901: train_loss -0.7576 +2024-11-21 12:30:34.254556: val_loss -0.7733 +2024-11-21 12:30:34.254650: Pseudo dice [0.8463] +2024-11-21 12:30:34.254730: Epoch time: 17.62 s +2024-11-21 12:30:35.052253: +2024-11-21 12:30:35.052449: Epoch 343 +2024-11-21 12:30:35.052557: Current learning rate: 0.00961 +2024-11-21 12:30:54.169770: train_loss -0.7496 +2024-11-21 12:30:54.169987: val_loss -0.7641 +2024-11-21 12:30:54.170077: Pseudo dice [0.8512] +2024-11-21 12:30:54.170155: Epoch time: 19.12 s +2024-11-21 12:30:55.020209: +2024-11-21 12:30:55.020446: Epoch 344 +2024-11-21 12:30:55.020563: Current learning rate: 0.00961 +2024-11-21 12:31:13.287604: train_loss -0.7449 +2024-11-21 12:31:13.287884: val_loss -0.7348 +2024-11-21 12:31:13.287970: Pseudo dice [0.8331] +2024-11-21 12:31:13.288056: Epoch time: 18.27 s +2024-11-21 12:31:14.094698: +2024-11-21 12:31:14.094907: Epoch 345 +2024-11-21 12:31:14.095021: Current learning rate: 0.00961 +2024-11-21 12:31:32.751651: train_loss -0.7533 +2024-11-21 12:31:32.751949: val_loss -0.7495 +2024-11-21 12:31:32.752070: Pseudo dice [0.8349] +2024-11-21 12:31:32.752151: Epoch time: 18.66 s +2024-11-21 12:31:33.552379: +2024-11-21 12:31:33.552605: Epoch 346 +2024-11-21 12:31:33.552722: Current learning rate: 0.00961 +2024-11-21 12:31:52.291566: train_loss -0.7504 +2024-11-21 12:31:52.291781: val_loss -0.7561 +2024-11-21 12:31:52.291856: Pseudo dice [0.8137] +2024-11-21 12:31:52.291929: Epoch time: 18.74 s +2024-11-21 12:31:53.225687: +2024-11-21 12:31:53.225927: Epoch 347 +2024-11-21 12:31:53.226047: Current learning rate: 0.00961 +2024-11-21 12:32:11.024367: train_loss -0.741 +2024-11-21 12:32:11.024575: val_loss -0.7603 +2024-11-21 12:32:11.024648: Pseudo dice [0.8504] +2024-11-21 12:32:11.024724: Epoch time: 17.8 s +2024-11-21 12:32:11.820457: +2024-11-21 12:32:11.820688: Epoch 348 +2024-11-21 12:32:11.820808: Current learning rate: 0.00961 +2024-11-21 12:32:31.509029: train_loss -0.7396 +2024-11-21 12:32:31.509275: val_loss -0.7519 +2024-11-21 12:32:31.509352: Pseudo dice [0.8147] +2024-11-21 12:32:31.509434: Epoch time: 19.69 s +2024-11-21 12:32:32.308697: +2024-11-21 12:32:32.308931: Epoch 349 +2024-11-21 12:32:32.309336: Current learning rate: 0.00961 +2024-11-21 12:32:50.451311: train_loss -0.7537 +2024-11-21 12:32:50.451520: val_loss -0.754 +2024-11-21 12:32:50.451602: Pseudo dice [0.8337] +2024-11-21 12:32:50.451675: Epoch time: 18.14 s +2024-11-21 12:32:51.519626: +2024-11-21 12:32:51.519837: Epoch 350 +2024-11-21 12:32:51.519947: Current learning rate: 0.00961 +2024-11-21 12:33:09.825255: train_loss -0.7553 +2024-11-21 12:33:09.825477: val_loss -0.7437 +2024-11-21 12:33:09.827733: Pseudo dice [0.8366] +2024-11-21 12:33:09.827836: Epoch time: 18.31 s +2024-11-21 12:33:10.785649: +2024-11-21 12:33:10.785852: Epoch 351 +2024-11-21 12:33:10.785964: Current learning rate: 0.0096 +2024-11-21 12:33:29.377648: train_loss -0.7523 +2024-11-21 12:33:29.377899: val_loss -0.7477 +2024-11-21 12:33:29.377972: Pseudo dice [0.8432] +2024-11-21 12:33:29.378053: Epoch time: 18.59 s +2024-11-21 12:33:30.177470: +2024-11-21 12:33:30.177677: Epoch 352 +2024-11-21 12:33:30.177801: Current learning rate: 0.0096 +2024-11-21 12:33:48.528643: train_loss -0.7478 +2024-11-21 12:33:48.528880: val_loss -0.7393 +2024-11-21 12:33:48.528956: Pseudo dice [0.8304] +2024-11-21 12:33:48.529047: Epoch time: 18.35 s +2024-11-21 12:33:49.405680: +2024-11-21 12:33:49.405884: Epoch 353 +2024-11-21 12:33:49.406002: Current learning rate: 0.0096 +2024-11-21 12:34:08.258822: train_loss -0.7451 +2024-11-21 12:34:08.259038: val_loss -0.7466 +2024-11-21 12:34:08.259169: Pseudo dice [0.8416] +2024-11-21 12:34:08.259245: Epoch time: 18.85 s +2024-11-21 12:34:09.060362: +2024-11-21 12:34:09.060565: Epoch 354 +2024-11-21 12:34:09.060671: Current learning rate: 0.0096 +2024-11-21 12:34:27.774002: train_loss -0.7491 +2024-11-21 12:34:27.774229: val_loss -0.7451 +2024-11-21 12:34:27.774306: Pseudo dice [0.8408] +2024-11-21 12:34:27.774379: Epoch time: 18.71 s +2024-11-21 12:34:28.960577: +2024-11-21 12:34:28.960799: Epoch 355 +2024-11-21 12:34:28.960909: Current learning rate: 0.0096 +2024-11-21 12:34:46.778839: train_loss -0.7604 +2024-11-21 12:34:46.779175: val_loss -0.7358 +2024-11-21 12:34:46.779257: Pseudo dice [0.8385] +2024-11-21 12:34:46.779341: Epoch time: 17.82 s +2024-11-21 12:34:47.582181: +2024-11-21 12:34:47.582405: Epoch 356 +2024-11-21 12:34:47.582513: Current learning rate: 0.0096 +2024-11-21 12:35:06.248490: train_loss -0.7537 +2024-11-21 12:35:06.248704: val_loss -0.7645 +2024-11-21 12:35:06.248780: Pseudo dice [0.8383] +2024-11-21 12:35:06.248858: Epoch time: 18.67 s +2024-11-21 12:35:07.049594: +2024-11-21 12:35:07.049824: Epoch 357 +2024-11-21 12:35:07.049932: Current learning rate: 0.0096 +2024-11-21 12:35:25.705153: train_loss -0.7444 +2024-11-21 12:35:25.705392: val_loss -0.7509 +2024-11-21 12:35:25.705473: Pseudo dice [0.834] +2024-11-21 12:35:25.705561: Epoch time: 18.66 s +2024-11-21 12:35:26.502666: +2024-11-21 12:35:26.502864: Epoch 358 +2024-11-21 12:35:26.502981: Current learning rate: 0.0096 +2024-11-21 12:35:45.533234: train_loss -0.7458 +2024-11-21 12:35:45.533444: val_loss -0.7227 +2024-11-21 12:35:45.533517: Pseudo dice [0.8386] +2024-11-21 12:35:45.533591: Epoch time: 19.03 s +2024-11-21 12:35:46.386594: +2024-11-21 12:35:46.386800: Epoch 359 +2024-11-21 12:35:46.386910: Current learning rate: 0.0096 +2024-11-21 12:36:04.656045: train_loss -0.7627 +2024-11-21 12:36:04.656288: val_loss -0.7496 +2024-11-21 12:36:04.656364: Pseudo dice [0.8345] +2024-11-21 12:36:04.656444: Epoch time: 18.27 s +2024-11-21 12:36:05.457240: +2024-11-21 12:36:05.457465: Epoch 360 +2024-11-21 12:36:05.457573: Current learning rate: 0.00959 +2024-11-21 12:36:23.457452: train_loss -0.7479 +2024-11-21 12:36:23.457665: val_loss -0.7322 +2024-11-21 12:36:23.462887: Pseudo dice [0.8441] +2024-11-21 12:36:23.463040: Epoch time: 18.0 s +2024-11-21 12:36:24.308253: +2024-11-21 12:36:24.308462: Epoch 361 +2024-11-21 12:36:24.308580: Current learning rate: 0.00959 +2024-11-21 12:36:42.855691: train_loss -0.7563 +2024-11-21 12:36:42.855913: val_loss -0.7555 +2024-11-21 12:36:42.855985: Pseudo dice [0.838] +2024-11-21 12:36:42.856067: Epoch time: 18.55 s +2024-11-21 12:36:42.856128: Yayy! New best EMA pseudo Dice: 0.8367 +2024-11-21 12:36:43.878256: +2024-11-21 12:36:43.878463: Epoch 362 +2024-11-21 12:36:43.878571: Current learning rate: 0.00959 +2024-11-21 12:37:01.862617: train_loss -0.7509 +2024-11-21 12:37:01.862851: val_loss -0.7275 +2024-11-21 12:37:01.862928: Pseudo dice [0.8047] +2024-11-21 12:37:01.863017: Epoch time: 17.99 s +2024-11-21 12:37:02.665684: +2024-11-21 12:37:02.665874: Epoch 363 +2024-11-21 12:37:02.665986: Current learning rate: 0.00959 +2024-11-21 12:37:20.548176: train_loss -0.7542 +2024-11-21 12:37:20.548379: val_loss -0.7371 +2024-11-21 12:37:20.548451: Pseudo dice [0.8426] +2024-11-21 12:37:20.548523: Epoch time: 17.88 s +2024-11-21 12:37:21.442837: +2024-11-21 12:37:21.443031: Epoch 364 +2024-11-21 12:37:21.443138: Current learning rate: 0.00959 +2024-11-21 12:37:38.730441: train_loss -0.7576 +2024-11-21 12:37:38.730657: val_loss -0.7643 +2024-11-21 12:37:38.730730: Pseudo dice [0.8564] +2024-11-21 12:37:38.730805: Epoch time: 17.29 s +2024-11-21 12:37:39.524585: +2024-11-21 12:37:39.524786: Epoch 365 +2024-11-21 12:37:39.524897: Current learning rate: 0.00959 +2024-11-21 12:37:58.978628: train_loss -0.7449 +2024-11-21 12:37:58.978838: val_loss -0.7517 +2024-11-21 12:37:58.978910: Pseudo dice [0.8496] +2024-11-21 12:37:58.978981: Epoch time: 19.45 s +2024-11-21 12:37:58.979050: Yayy! New best EMA pseudo Dice: 0.8379 +2024-11-21 12:38:00.399201: +2024-11-21 12:38:00.399417: Epoch 366 +2024-11-21 12:38:00.399527: Current learning rate: 0.00959 +2024-11-21 12:38:18.223964: train_loss -0.7616 +2024-11-21 12:38:18.225622: val_loss -0.7314 +2024-11-21 12:38:18.225703: Pseudo dice [0.8179] +2024-11-21 12:38:18.225781: Epoch time: 17.83 s +2024-11-21 12:38:19.016042: +2024-11-21 12:38:19.016255: Epoch 367 +2024-11-21 12:38:19.016366: Current learning rate: 0.00959 +2024-11-21 12:38:37.175242: train_loss -0.7546 +2024-11-21 12:38:37.175482: val_loss -0.7556 +2024-11-21 12:38:37.175563: Pseudo dice [0.8215] +2024-11-21 12:38:37.175638: Epoch time: 18.16 s +2024-11-21 12:38:37.972775: +2024-11-21 12:38:37.972974: Epoch 368 +2024-11-21 12:38:37.973084: Current learning rate: 0.00959 +2024-11-21 12:38:56.491984: train_loss -0.7511 +2024-11-21 12:38:56.492197: val_loss -0.7809 +2024-11-21 12:38:56.492270: Pseudo dice [0.8525] +2024-11-21 12:38:56.492345: Epoch time: 18.52 s +2024-11-21 12:38:57.282750: +2024-11-21 12:38:57.282948: Epoch 369 +2024-11-21 12:38:57.283087: Current learning rate: 0.00958 +2024-11-21 12:39:16.328195: train_loss -0.7523 +2024-11-21 12:39:16.328439: val_loss -0.7101 +2024-11-21 12:39:16.328513: Pseudo dice [0.8203] +2024-11-21 12:39:16.328598: Epoch time: 19.05 s +2024-11-21 12:39:17.136172: +2024-11-21 12:39:17.136392: Epoch 370 +2024-11-21 12:39:17.136503: Current learning rate: 0.00958 +2024-11-21 12:39:36.338326: train_loss -0.7528 +2024-11-21 12:39:36.338525: val_loss -0.7647 +2024-11-21 12:39:36.338595: Pseudo dice [0.8304] +2024-11-21 12:39:36.338669: Epoch time: 19.2 s +2024-11-21 12:39:37.139690: +2024-11-21 12:39:37.139908: Epoch 371 +2024-11-21 12:39:37.140032: Current learning rate: 0.00958 +2024-11-21 12:39:55.906922: train_loss -0.7439 +2024-11-21 12:39:55.907145: val_loss -0.7591 +2024-11-21 12:39:55.907222: Pseudo dice [0.8292] +2024-11-21 12:39:55.907300: Epoch time: 18.77 s +2024-11-21 12:39:56.713283: +2024-11-21 12:39:56.713492: Epoch 372 +2024-11-21 12:39:56.713599: Current learning rate: 0.00958 +2024-11-21 12:40:14.225548: train_loss -0.7398 +2024-11-21 12:40:14.225748: val_loss -0.7388 +2024-11-21 12:40:14.225824: Pseudo dice [0.8273] +2024-11-21 12:40:14.225897: Epoch time: 17.51 s +2024-11-21 12:40:15.012417: +2024-11-21 12:40:15.012621: Epoch 373 +2024-11-21 12:40:15.012727: Current learning rate: 0.00958 +2024-11-21 12:40:33.431448: train_loss -0.7485 +2024-11-21 12:40:33.431691: val_loss -0.7693 +2024-11-21 12:40:33.431767: Pseudo dice [0.8485] +2024-11-21 12:40:33.431849: Epoch time: 18.42 s +2024-11-21 12:40:34.240661: +2024-11-21 12:40:34.240872: Epoch 374 +2024-11-21 12:40:34.240989: Current learning rate: 0.00958 +2024-11-21 12:40:52.981168: train_loss -0.7523 +2024-11-21 12:40:52.981419: val_loss -0.7631 +2024-11-21 12:40:52.981494: Pseudo dice [0.8335] +2024-11-21 12:40:52.981802: Epoch time: 18.74 s +2024-11-21 12:40:53.775250: +2024-11-21 12:40:53.775455: Epoch 375 +2024-11-21 12:40:53.775598: Current learning rate: 0.00958 +2024-11-21 12:41:12.497352: train_loss -0.7522 +2024-11-21 12:41:12.497638: val_loss -0.7709 +2024-11-21 12:41:12.497715: Pseudo dice [0.8423] +2024-11-21 12:41:12.497788: Epoch time: 18.72 s +2024-11-21 12:41:13.292333: +2024-11-21 12:41:13.292533: Epoch 376 +2024-11-21 12:41:13.292646: Current learning rate: 0.00958 +2024-11-21 12:41:32.132138: train_loss -0.7504 +2024-11-21 12:41:32.132347: val_loss -0.7605 +2024-11-21 12:41:32.132424: Pseudo dice [0.8358] +2024-11-21 12:41:32.132503: Epoch time: 18.84 s +2024-11-21 12:41:33.340349: +2024-11-21 12:41:33.340574: Epoch 377 +2024-11-21 12:41:33.340685: Current learning rate: 0.00957 +2024-11-21 12:41:52.156885: train_loss -0.7476 +2024-11-21 12:41:52.157611: val_loss -0.7607 +2024-11-21 12:41:52.157691: Pseudo dice [0.842] +2024-11-21 12:41:52.157769: Epoch time: 18.82 s +2024-11-21 12:41:52.961107: +2024-11-21 12:41:52.961329: Epoch 378 +2024-11-21 12:41:52.961442: Current learning rate: 0.00957 +2024-11-21 12:42:10.831576: train_loss -0.742 +2024-11-21 12:42:10.831793: val_loss -0.7419 +2024-11-21 12:42:10.831868: Pseudo dice [0.8256] +2024-11-21 12:42:10.831940: Epoch time: 17.87 s +2024-11-21 12:42:11.626562: +2024-11-21 12:42:11.626851: Epoch 379 +2024-11-21 12:42:11.626972: Current learning rate: 0.00957 +2024-11-21 12:42:30.079788: train_loss -0.7464 +2024-11-21 12:42:30.080002: val_loss -0.7378 +2024-11-21 12:42:30.080130: Pseudo dice [0.8223] +2024-11-21 12:42:30.080209: Epoch time: 18.45 s +2024-11-21 12:42:30.873756: +2024-11-21 12:42:30.873964: Epoch 380 +2024-11-21 12:42:30.874075: Current learning rate: 0.00957 +2024-11-21 12:42:49.560502: train_loss -0.7393 +2024-11-21 12:42:49.560834: val_loss -0.7732 +2024-11-21 12:42:49.560919: Pseudo dice [0.8383] +2024-11-21 12:42:49.561011: Epoch time: 18.69 s +2024-11-21 12:42:50.452134: +2024-11-21 12:42:50.452335: Epoch 381 +2024-11-21 12:42:50.452445: Current learning rate: 0.00957 +2024-11-21 12:43:09.132212: train_loss -0.7448 +2024-11-21 12:43:09.132420: val_loss -0.7144 +2024-11-21 12:43:09.132494: Pseudo dice [0.8079] +2024-11-21 12:43:09.132568: Epoch time: 18.68 s +2024-11-21 12:43:09.955331: +2024-11-21 12:43:09.955532: Epoch 382 +2024-11-21 12:43:09.955645: Current learning rate: 0.00957 +2024-11-21 12:43:28.407829: train_loss -0.7498 +2024-11-21 12:43:28.410216: val_loss -0.7738 +2024-11-21 12:43:28.410338: Pseudo dice [0.8376] +2024-11-21 12:43:28.410431: Epoch time: 18.45 s +2024-11-21 12:43:29.237828: +2024-11-21 12:43:29.238045: Epoch 383 +2024-11-21 12:43:29.238158: Current learning rate: 0.00957 +2024-11-21 12:43:47.361850: train_loss -0.7488 +2024-11-21 12:43:47.362061: val_loss -0.7654 +2024-11-21 12:43:47.362134: Pseudo dice [0.8375] +2024-11-21 12:43:47.362209: Epoch time: 18.12 s +2024-11-21 12:43:48.163533: +2024-11-21 12:43:48.163736: Epoch 384 +2024-11-21 12:43:48.163842: Current learning rate: 0.00957 +2024-11-21 12:44:06.464506: train_loss -0.7565 +2024-11-21 12:44:06.464788: val_loss -0.742 +2024-11-21 12:44:06.464870: Pseudo dice [0.8353] +2024-11-21 12:44:06.464955: Epoch time: 18.3 s +2024-11-21 12:44:07.268731: +2024-11-21 12:44:07.268926: Epoch 385 +2024-11-21 12:44:07.269044: Current learning rate: 0.00957 +2024-11-21 12:44:24.885844: train_loss -0.7496 +2024-11-21 12:44:24.887486: val_loss -0.7522 +2024-11-21 12:44:24.887574: Pseudo dice [0.8195] +2024-11-21 12:44:24.887648: Epoch time: 17.62 s +2024-11-21 12:44:25.744927: +2024-11-21 12:44:25.745145: Epoch 386 +2024-11-21 12:44:25.745256: Current learning rate: 0.00956 +2024-11-21 12:44:44.247688: train_loss -0.7438 +2024-11-21 12:44:44.247897: val_loss -0.7456 +2024-11-21 12:44:44.247971: Pseudo dice [0.8237] +2024-11-21 12:44:44.248054: Epoch time: 18.5 s +2024-11-21 12:44:45.051889: +2024-11-21 12:44:45.052169: Epoch 387 +2024-11-21 12:44:45.052281: Current learning rate: 0.00956 +2024-11-21 12:45:03.949099: train_loss -0.7389 +2024-11-21 12:45:03.949343: val_loss -0.7602 +2024-11-21 12:45:03.949420: Pseudo dice [0.8462] +2024-11-21 12:45:03.949498: Epoch time: 18.9 s +2024-11-21 12:45:04.761189: +2024-11-21 12:45:04.761381: Epoch 388 +2024-11-21 12:45:04.761517: Current learning rate: 0.00956 +2024-11-21 12:45:23.348862: train_loss -0.7403 +2024-11-21 12:45:23.349145: val_loss -0.7175 +2024-11-21 12:45:23.349222: Pseudo dice [0.8205] +2024-11-21 12:45:23.349298: Epoch time: 18.59 s +2024-11-21 12:45:24.537715: +2024-11-21 12:45:24.537932: Epoch 389 +2024-11-21 12:45:24.538049: Current learning rate: 0.00956 +2024-11-21 12:45:42.634821: train_loss -0.7525 +2024-11-21 12:45:42.635117: val_loss -0.7319 +2024-11-21 12:45:42.635196: Pseudo dice [0.8152] +2024-11-21 12:45:42.635274: Epoch time: 18.1 s +2024-11-21 12:45:43.447515: +2024-11-21 12:45:43.447725: Epoch 390 +2024-11-21 12:45:43.447854: Current learning rate: 0.00956 +2024-11-21 12:46:00.977352: train_loss -0.7439 +2024-11-21 12:46:00.977558: val_loss -0.7784 +2024-11-21 12:46:00.977632: Pseudo dice [0.8402] +2024-11-21 12:46:00.977708: Epoch time: 17.53 s +2024-11-21 12:46:01.794265: +2024-11-21 12:46:01.794541: Epoch 391 +2024-11-21 12:46:01.794656: Current learning rate: 0.00956 +2024-11-21 12:46:19.760327: train_loss -0.7508 +2024-11-21 12:46:19.762789: val_loss -0.7585 +2024-11-21 12:46:19.762874: Pseudo dice [0.8597] +2024-11-21 12:46:19.762951: Epoch time: 17.97 s +2024-11-21 12:46:20.564186: +2024-11-21 12:46:20.564390: Epoch 392 +2024-11-21 12:46:20.564503: Current learning rate: 0.00956 +2024-11-21 12:46:39.256059: train_loss -0.7611 +2024-11-21 12:46:39.256279: val_loss -0.7719 +2024-11-21 12:46:39.256357: Pseudo dice [0.8393] +2024-11-21 12:46:39.256435: Epoch time: 18.69 s +2024-11-21 12:46:40.074698: +2024-11-21 12:46:40.074900: Epoch 393 +2024-11-21 12:46:40.075015: Current learning rate: 0.00956 +2024-11-21 12:46:57.708677: train_loss -0.7492 +2024-11-21 12:46:57.708883: val_loss -0.7502 +2024-11-21 12:46:57.708955: Pseudo dice [0.8323] +2024-11-21 12:46:57.709039: Epoch time: 17.63 s +2024-11-21 12:46:58.566044: +2024-11-21 12:46:58.566288: Epoch 394 +2024-11-21 12:46:58.566399: Current learning rate: 0.00956 +2024-11-21 12:47:17.080986: train_loss -0.756 +2024-11-21 12:47:17.081221: val_loss -0.7731 +2024-11-21 12:47:17.081301: Pseudo dice [0.8335] +2024-11-21 12:47:17.081383: Epoch time: 18.52 s +2024-11-21 12:47:17.886791: +2024-11-21 12:47:17.887041: Epoch 395 +2024-11-21 12:47:17.887194: Current learning rate: 0.00955 +2024-11-21 12:47:35.563652: train_loss -0.7666 +2024-11-21 12:47:35.563862: val_loss -0.7561 +2024-11-21 12:47:35.563935: Pseudo dice [0.8324] +2024-11-21 12:47:35.564017: Epoch time: 17.68 s +2024-11-21 12:47:36.367317: +2024-11-21 12:47:36.367568: Epoch 396 +2024-11-21 12:47:36.367679: Current learning rate: 0.00955 +2024-11-21 12:47:54.987007: train_loss -0.749 +2024-11-21 12:47:54.987215: val_loss -0.7646 +2024-11-21 12:47:54.987290: Pseudo dice [0.83] +2024-11-21 12:47:54.987366: Epoch time: 18.62 s +2024-11-21 12:47:55.790428: +2024-11-21 12:47:55.790637: Epoch 397 +2024-11-21 12:47:55.790749: Current learning rate: 0.00955 +2024-11-21 12:48:14.788157: train_loss -0.7494 +2024-11-21 12:48:14.788388: val_loss -0.7617 +2024-11-21 12:48:14.788461: Pseudo dice [0.8331] +2024-11-21 12:48:14.788535: Epoch time: 19.0 s +2024-11-21 12:48:15.620398: +2024-11-21 12:48:15.620601: Epoch 398 +2024-11-21 12:48:15.620712: Current learning rate: 0.00955 +2024-11-21 12:48:33.652130: train_loss -0.7526 +2024-11-21 12:48:33.652357: val_loss -0.7532 +2024-11-21 12:48:33.652434: Pseudo dice [0.8318] +2024-11-21 12:48:33.652517: Epoch time: 18.03 s +2024-11-21 12:48:34.453108: +2024-11-21 12:48:34.453305: Epoch 399 +2024-11-21 12:48:34.453415: Current learning rate: 0.00955 +2024-11-21 12:48:54.095355: train_loss -0.7464 +2024-11-21 12:48:54.095577: val_loss -0.7605 +2024-11-21 12:48:54.095652: Pseudo dice [0.8346] +2024-11-21 12:48:54.095726: Epoch time: 19.64 s +2024-11-21 12:48:55.470558: +2024-11-21 12:48:55.470756: Epoch 400 +2024-11-21 12:48:55.470865: Current learning rate: 0.00955 +2024-11-21 12:49:13.783484: train_loss -0.7445 +2024-11-21 12:49:13.783689: val_loss -0.7581 +2024-11-21 12:49:13.783761: Pseudo dice [0.8542] +2024-11-21 12:49:13.784316: Epoch time: 18.31 s +2024-11-21 12:49:14.720195: +2024-11-21 12:49:14.720422: Epoch 401 +2024-11-21 12:49:14.720535: Current learning rate: 0.00955 +2024-11-21 12:49:32.848403: train_loss -0.7551 +2024-11-21 12:49:32.848642: val_loss -0.7386 +2024-11-21 12:49:32.848716: Pseudo dice [0.8185] +2024-11-21 12:49:32.848799: Epoch time: 18.13 s +2024-11-21 12:49:33.658149: +2024-11-21 12:49:33.658387: Epoch 402 +2024-11-21 12:49:33.658506: Current learning rate: 0.00955 +2024-11-21 12:49:51.722410: train_loss -0.7593 +2024-11-21 12:49:51.722629: val_loss -0.769 +2024-11-21 12:49:51.722702: Pseudo dice [0.8427] +2024-11-21 12:49:51.722776: Epoch time: 18.07 s +2024-11-21 12:49:52.586939: +2024-11-21 12:49:52.587160: Epoch 403 +2024-11-21 12:49:52.587274: Current learning rate: 0.00955 +2024-11-21 12:50:09.862277: train_loss -0.7513 +2024-11-21 12:50:09.862481: val_loss -0.7445 +2024-11-21 12:50:09.862551: Pseudo dice [0.8185] +2024-11-21 12:50:09.862623: Epoch time: 17.28 s +2024-11-21 12:50:10.765758: +2024-11-21 12:50:10.766018: Epoch 404 +2024-11-21 12:50:10.766130: Current learning rate: 0.00954 +2024-11-21 12:50:28.842749: train_loss -0.7293 +2024-11-21 12:50:28.842947: val_loss -0.753 +2024-11-21 12:50:28.843027: Pseudo dice [0.8313] +2024-11-21 12:50:28.843154: Epoch time: 18.08 s +2024-11-21 12:50:29.800970: +2024-11-21 12:50:29.801192: Epoch 405 +2024-11-21 12:50:29.801299: Current learning rate: 0.00954 +2024-11-21 12:50:48.230309: train_loss -0.7434 +2024-11-21 12:50:48.230544: val_loss -0.7523 +2024-11-21 12:50:48.230619: Pseudo dice [0.8333] +2024-11-21 12:50:48.230700: Epoch time: 18.43 s +2024-11-21 12:50:49.086644: +2024-11-21 12:50:49.086933: Epoch 406 +2024-11-21 12:50:49.087048: Current learning rate: 0.00954 +2024-11-21 12:51:07.034961: train_loss -0.7558 +2024-11-21 12:51:07.035188: val_loss -0.7403 +2024-11-21 12:51:07.035265: Pseudo dice [0.8344] +2024-11-21 12:51:07.035342: Epoch time: 17.95 s +2024-11-21 12:51:07.837467: +2024-11-21 12:51:07.837673: Epoch 407 +2024-11-21 12:51:07.837783: Current learning rate: 0.00954 +2024-11-21 12:51:26.827866: train_loss -0.7567 +2024-11-21 12:51:26.828088: val_loss -0.7522 +2024-11-21 12:51:26.828164: Pseudo dice [0.832] +2024-11-21 12:51:26.828257: Epoch time: 18.99 s +2024-11-21 12:51:27.632371: +2024-11-21 12:51:27.632579: Epoch 408 +2024-11-21 12:51:27.632684: Current learning rate: 0.00954 +2024-11-21 12:51:45.867887: train_loss -0.7561 +2024-11-21 12:51:45.868106: val_loss -0.7479 +2024-11-21 12:51:45.868226: Pseudo dice [0.8123] +2024-11-21 12:51:45.868305: Epoch time: 18.24 s +2024-11-21 12:51:46.674437: +2024-11-21 12:51:46.674644: Epoch 409 +2024-11-21 12:51:46.674770: Current learning rate: 0.00954 +2024-11-21 12:52:04.971986: train_loss -0.746 +2024-11-21 12:52:04.972289: val_loss -0.7714 +2024-11-21 12:52:04.972363: Pseudo dice [0.8498] +2024-11-21 12:52:04.972444: Epoch time: 18.3 s +2024-11-21 12:52:05.778822: +2024-11-21 12:52:05.779069: Epoch 410 +2024-11-21 12:52:05.779183: Current learning rate: 0.00954 +2024-11-21 12:52:22.849357: train_loss -0.7507 +2024-11-21 12:52:22.849633: val_loss -0.735 +2024-11-21 12:52:22.849710: Pseudo dice [0.8193] +2024-11-21 12:52:22.849795: Epoch time: 17.07 s +2024-11-21 12:52:23.623123: +2024-11-21 12:52:23.623344: Epoch 411 +2024-11-21 12:52:23.623459: Current learning rate: 0.00954 +2024-11-21 12:52:41.648062: train_loss -0.7464 +2024-11-21 12:52:41.648284: val_loss -0.7584 +2024-11-21 12:52:41.648379: Pseudo dice [0.8148] +2024-11-21 12:52:41.648475: Epoch time: 18.03 s +2024-11-21 12:52:42.473504: +2024-11-21 12:52:42.473703: Epoch 412 +2024-11-21 12:52:42.473809: Current learning rate: 0.00954 +2024-11-21 12:53:01.213607: train_loss -0.7487 +2024-11-21 12:53:01.213858: val_loss -0.7788 +2024-11-21 12:53:01.213940: Pseudo dice [0.8432] +2024-11-21 12:53:01.214023: Epoch time: 18.74 s +2024-11-21 12:53:02.015258: +2024-11-21 12:53:02.015542: Epoch 413 +2024-11-21 12:53:02.015649: Current learning rate: 0.00953 +2024-11-21 12:53:22.080774: train_loss -0.7451 +2024-11-21 12:53:22.080981: val_loss -0.7691 +2024-11-21 12:53:22.081062: Pseudo dice [0.8257] +2024-11-21 12:53:22.081220: Epoch time: 20.07 s +2024-11-21 12:53:22.861082: +2024-11-21 12:53:22.861296: Epoch 414 +2024-11-21 12:53:22.861407: Current learning rate: 0.00953 +2024-11-21 12:53:41.058276: train_loss -0.735 +2024-11-21 12:53:41.063669: val_loss -0.743 +2024-11-21 12:53:41.063748: Pseudo dice [0.8498] +2024-11-21 12:53:41.063823: Epoch time: 18.2 s +2024-11-21 12:53:41.956856: +2024-11-21 12:53:41.957093: Epoch 415 +2024-11-21 12:53:41.957205: Current learning rate: 0.00953 +2024-11-21 12:54:00.275650: train_loss -0.7313 +2024-11-21 12:54:00.275880: val_loss -0.7526 +2024-11-21 12:54:00.275983: Pseudo dice [0.822] +2024-11-21 12:54:00.276082: Epoch time: 18.32 s +2024-11-21 12:54:01.057908: +2024-11-21 12:54:01.058152: Epoch 416 +2024-11-21 12:54:01.058274: Current learning rate: 0.00953 +2024-11-21 12:54:20.228937: train_loss -0.7552 +2024-11-21 12:54:20.230412: val_loss -0.7552 +2024-11-21 12:54:20.230503: Pseudo dice [0.8403] +2024-11-21 12:54:20.230583: Epoch time: 19.17 s +2024-11-21 12:54:21.007675: +2024-11-21 12:54:21.007911: Epoch 417 +2024-11-21 12:54:21.008029: Current learning rate: 0.00953 +2024-11-21 12:54:38.787980: train_loss -0.7606 +2024-11-21 12:54:38.788211: val_loss -0.7317 +2024-11-21 12:54:38.788423: Pseudo dice [0.8378] +2024-11-21 12:54:38.788497: Epoch time: 17.78 s +2024-11-21 12:54:39.566767: +2024-11-21 12:54:39.566983: Epoch 418 +2024-11-21 12:54:39.567103: Current learning rate: 0.00953 +2024-11-21 12:54:58.951063: train_loss -0.7402 +2024-11-21 12:54:58.951270: val_loss -0.7501 +2024-11-21 12:54:58.951348: Pseudo dice [0.8366] +2024-11-21 12:54:58.951429: Epoch time: 19.39 s +2024-11-21 12:54:59.732471: +2024-11-21 12:54:59.732685: Epoch 419 +2024-11-21 12:54:59.732805: Current learning rate: 0.00953 +2024-11-21 12:55:18.157112: train_loss -0.7365 +2024-11-21 12:55:18.157346: val_loss -0.7398 +2024-11-21 12:55:18.157425: Pseudo dice [0.8375] +2024-11-21 12:55:18.157554: Epoch time: 18.43 s +2024-11-21 12:55:18.939226: +2024-11-21 12:55:18.939427: Epoch 420 +2024-11-21 12:55:18.939538: Current learning rate: 0.00953 +2024-11-21 12:55:37.023894: train_loss -0.7357 +2024-11-21 12:55:37.024112: val_loss -0.7527 +2024-11-21 12:55:37.024189: Pseudo dice [0.8329] +2024-11-21 12:55:37.024261: Epoch time: 18.09 s +2024-11-21 12:55:37.798749: +2024-11-21 12:55:37.798952: Epoch 421 +2024-11-21 12:55:37.799069: Current learning rate: 0.00953 +2024-11-21 12:55:55.958689: train_loss -0.7371 +2024-11-21 12:55:55.958889: val_loss -0.7213 +2024-11-21 12:55:55.958960: Pseudo dice [0.8195] +2024-11-21 12:55:55.959040: Epoch time: 18.16 s +2024-11-21 12:55:56.730922: +2024-11-21 12:55:56.731108: Epoch 422 +2024-11-21 12:55:56.731216: Current learning rate: 0.00952 +2024-11-21 12:56:15.331526: train_loss -0.7585 +2024-11-21 12:56:15.331795: val_loss -0.7196 +2024-11-21 12:56:15.331871: Pseudo dice [0.8243] +2024-11-21 12:56:15.331943: Epoch time: 18.6 s +2024-11-21 12:56:16.158024: +2024-11-21 12:56:16.158236: Epoch 423 +2024-11-21 12:56:16.158352: Current learning rate: 0.00952 +2024-11-21 12:56:34.877331: train_loss -0.7467 +2024-11-21 12:56:34.877559: val_loss -0.7457 +2024-11-21 12:56:34.877634: Pseudo dice [0.8444] +2024-11-21 12:56:34.877711: Epoch time: 18.72 s +2024-11-21 12:56:35.662761: +2024-11-21 12:56:35.662977: Epoch 424 +2024-11-21 12:56:35.663105: Current learning rate: 0.00952 +2024-11-21 12:56:54.083793: train_loss -0.7527 +2024-11-21 12:56:54.083999: val_loss -0.75 +2024-11-21 12:56:54.084074: Pseudo dice [0.824] +2024-11-21 12:56:54.084148: Epoch time: 18.42 s +2024-11-21 12:56:54.861794: +2024-11-21 12:56:54.862006: Epoch 425 +2024-11-21 12:56:54.862113: Current learning rate: 0.00952 +2024-11-21 12:57:13.718849: train_loss -0.7531 +2024-11-21 12:57:13.719072: val_loss -0.7453 +2024-11-21 12:57:13.719147: Pseudo dice [0.8231] +2024-11-21 12:57:13.719227: Epoch time: 18.86 s +2024-11-21 12:57:14.539270: +2024-11-21 12:57:14.539541: Epoch 426 +2024-11-21 12:57:14.539648: Current learning rate: 0.00952 +2024-11-21 12:57:32.576192: train_loss -0.7611 +2024-11-21 12:57:32.576421: val_loss -0.7557 +2024-11-21 12:57:32.576494: Pseudo dice [0.8432] +2024-11-21 12:57:32.576886: Epoch time: 18.04 s +2024-11-21 12:57:33.361367: +2024-11-21 12:57:33.361582: Epoch 427 +2024-11-21 12:57:33.361695: Current learning rate: 0.00952 +2024-11-21 12:57:50.961329: train_loss -0.7542 +2024-11-21 12:57:50.961541: val_loss -0.7628 +2024-11-21 12:57:50.961615: Pseudo dice [0.838] +2024-11-21 12:57:50.961689: Epoch time: 17.6 s +2024-11-21 12:57:51.835844: +2024-11-21 12:57:51.836059: Epoch 428 +2024-11-21 12:57:51.836168: Current learning rate: 0.00952 +2024-11-21 12:58:10.087776: train_loss -0.747 +2024-11-21 12:58:10.088032: val_loss -0.7442 +2024-11-21 12:58:10.088115: Pseudo dice [0.8326] +2024-11-21 12:58:10.088188: Epoch time: 18.25 s +2024-11-21 12:58:10.868220: +2024-11-21 12:58:10.868416: Epoch 429 +2024-11-21 12:58:10.868522: Current learning rate: 0.00952 +2024-11-21 12:58:28.845483: train_loss -0.7486 +2024-11-21 12:58:28.845714: val_loss -0.7576 +2024-11-21 12:58:28.845788: Pseudo dice [0.8499] +2024-11-21 12:58:28.845878: Epoch time: 17.98 s +2024-11-21 12:58:29.625767: +2024-11-21 12:58:29.625958: Epoch 430 +2024-11-21 12:58:29.626064: Current learning rate: 0.00951 +2024-11-21 12:58:48.518357: train_loss -0.7521 +2024-11-21 12:58:48.518563: val_loss -0.7617 +2024-11-21 12:58:48.518636: Pseudo dice [0.8487] +2024-11-21 12:58:48.518708: Epoch time: 18.89 s +2024-11-21 12:58:49.295893: +2024-11-21 12:58:49.296263: Epoch 431 +2024-11-21 12:58:49.296377: Current learning rate: 0.00951 +2024-11-21 12:59:07.669865: train_loss -0.7596 +2024-11-21 12:59:07.670090: val_loss -0.7442 +2024-11-21 12:59:07.670176: Pseudo dice [0.8327] +2024-11-21 12:59:07.670255: Epoch time: 18.37 s +2024-11-21 12:59:08.448753: +2024-11-21 12:59:08.448943: Epoch 432 +2024-11-21 12:59:08.449061: Current learning rate: 0.00951 +2024-11-21 12:59:27.212548: train_loss -0.7508 +2024-11-21 12:59:27.212755: val_loss -0.7266 +2024-11-21 12:59:27.212846: Pseudo dice [0.8136] +2024-11-21 12:59:27.212919: Epoch time: 18.76 s +2024-11-21 12:59:27.994920: +2024-11-21 12:59:27.995186: Epoch 433 +2024-11-21 12:59:27.995308: Current learning rate: 0.00951 +2024-11-21 12:59:45.662918: train_loss -0.7465 +2024-11-21 12:59:45.663152: val_loss -0.731 +2024-11-21 12:59:45.663337: Pseudo dice [0.8167] +2024-11-21 12:59:45.663421: Epoch time: 17.67 s +2024-11-21 12:59:46.454645: +2024-11-21 12:59:46.454846: Epoch 434 +2024-11-21 12:59:46.454957: Current learning rate: 0.00951 +2024-11-21 13:00:04.669665: train_loss -0.7585 +2024-11-21 13:00:04.669875: val_loss -0.7643 +2024-11-21 13:00:04.669951: Pseudo dice [0.8361] +2024-11-21 13:00:04.670033: Epoch time: 18.22 s +2024-11-21 13:00:05.456386: +2024-11-21 13:00:05.456578: Epoch 435 +2024-11-21 13:00:05.456688: Current learning rate: 0.00951 +2024-11-21 13:00:24.071785: train_loss -0.7626 +2024-11-21 13:00:24.072005: val_loss -0.746 +2024-11-21 13:00:24.072081: Pseudo dice [0.8545] +2024-11-21 13:00:24.072163: Epoch time: 18.62 s +2024-11-21 13:00:24.854683: +2024-11-21 13:00:24.854901: Epoch 436 +2024-11-21 13:00:24.855031: Current learning rate: 0.00951 +2024-11-21 13:00:44.140046: train_loss -0.7667 +2024-11-21 13:00:44.140282: val_loss -0.7293 +2024-11-21 13:00:44.140357: Pseudo dice [0.8273] +2024-11-21 13:00:44.140435: Epoch time: 19.29 s +2024-11-21 13:00:44.953516: +2024-11-21 13:00:44.953726: Epoch 437 +2024-11-21 13:00:44.953833: Current learning rate: 0.00951 +2024-11-21 13:01:04.145522: train_loss -0.753 +2024-11-21 13:01:04.145730: val_loss -0.7687 +2024-11-21 13:01:04.145803: Pseudo dice [0.8422] +2024-11-21 13:01:04.145951: Epoch time: 19.19 s +2024-11-21 13:01:04.926670: +2024-11-21 13:01:04.926903: Epoch 438 +2024-11-21 13:01:04.927029: Current learning rate: 0.00951 +2024-11-21 13:01:22.952246: train_loss -0.7589 +2024-11-21 13:01:22.955405: val_loss -0.7629 +2024-11-21 13:01:22.955572: Pseudo dice [0.8524] +2024-11-21 13:01:22.955656: Epoch time: 18.03 s +2024-11-21 13:01:23.745705: +2024-11-21 13:01:23.745913: Epoch 439 +2024-11-21 13:01:23.746028: Current learning rate: 0.0095 +2024-11-21 13:01:41.870749: train_loss -0.751 +2024-11-21 13:01:41.870959: val_loss -0.7507 +2024-11-21 13:01:41.871066: Pseudo dice [0.832] +2024-11-21 13:01:41.871145: Epoch time: 18.13 s +2024-11-21 13:01:42.650698: +2024-11-21 13:01:42.650911: Epoch 440 +2024-11-21 13:01:42.651025: Current learning rate: 0.0095 +2024-11-21 13:02:01.338399: train_loss -0.7612 +2024-11-21 13:02:01.338637: val_loss -0.764 +2024-11-21 13:02:01.338713: Pseudo dice [0.842] +2024-11-21 13:02:01.338837: Epoch time: 18.69 s +2024-11-21 13:02:02.126800: +2024-11-21 13:02:02.127031: Epoch 441 +2024-11-21 13:02:02.127143: Current learning rate: 0.0095 +2024-11-21 13:02:20.792037: train_loss -0.7544 +2024-11-21 13:02:20.792252: val_loss -0.7487 +2024-11-21 13:02:20.792324: Pseudo dice [0.8293] +2024-11-21 13:02:20.792397: Epoch time: 18.67 s +2024-11-21 13:02:21.577094: +2024-11-21 13:02:21.577305: Epoch 442 +2024-11-21 13:02:21.577415: Current learning rate: 0.0095 +2024-11-21 13:02:39.220726: train_loss -0.7567 +2024-11-21 13:02:39.220928: val_loss -0.7548 +2024-11-21 13:02:39.221005: Pseudo dice [0.8293] +2024-11-21 13:02:39.221076: Epoch time: 17.64 s +2024-11-21 13:02:40.000047: +2024-11-21 13:02:40.000334: Epoch 443 +2024-11-21 13:02:40.000442: Current learning rate: 0.0095 +2024-11-21 13:02:59.202698: train_loss -0.7509 +2024-11-21 13:02:59.202937: val_loss -0.7255 +2024-11-21 13:02:59.203016: Pseudo dice [0.8275] +2024-11-21 13:02:59.203099: Epoch time: 19.2 s +2024-11-21 13:02:59.988130: +2024-11-21 13:02:59.988337: Epoch 444 +2024-11-21 13:02:59.988453: Current learning rate: 0.0095 +2024-11-21 13:03:18.716951: train_loss -0.7513 +2024-11-21 13:03:18.717163: val_loss -0.7794 +2024-11-21 13:03:18.717237: Pseudo dice [0.8521] +2024-11-21 13:03:18.717315: Epoch time: 18.73 s +2024-11-21 13:03:19.570748: +2024-11-21 13:03:19.570933: Epoch 445 +2024-11-21 13:03:19.571051: Current learning rate: 0.0095 +2024-11-21 13:03:38.010508: train_loss -0.7429 +2024-11-21 13:03:38.010717: val_loss -0.7208 +2024-11-21 13:03:38.010799: Pseudo dice [0.8058] +2024-11-21 13:03:38.010877: Epoch time: 18.44 s +2024-11-21 13:03:38.813036: +2024-11-21 13:03:38.813241: Epoch 446 +2024-11-21 13:03:38.813353: Current learning rate: 0.0095 +2024-11-21 13:03:57.015308: train_loss -0.7464 +2024-11-21 13:03:57.015519: val_loss -0.7438 +2024-11-21 13:03:57.015599: Pseudo dice [0.8189] +2024-11-21 13:03:57.017847: Epoch time: 18.2 s +2024-11-21 13:03:57.954027: +2024-11-21 13:03:57.954225: Epoch 447 +2024-11-21 13:03:57.954335: Current learning rate: 0.0095 +2024-11-21 13:04:16.713355: train_loss -0.7435 +2024-11-21 13:04:16.713581: val_loss -0.7135 +2024-11-21 13:04:16.713655: Pseudo dice [0.8229] +2024-11-21 13:04:16.713739: Epoch time: 18.76 s +2024-11-21 13:04:17.507497: +2024-11-21 13:04:17.507738: Epoch 448 +2024-11-21 13:04:17.507853: Current learning rate: 0.00949 +2024-11-21 13:04:35.554088: train_loss -0.7617 +2024-11-21 13:04:35.554293: val_loss -0.7433 +2024-11-21 13:04:35.554365: Pseudo dice [0.8189] +2024-11-21 13:04:35.554439: Epoch time: 18.05 s +2024-11-21 13:04:36.331430: +2024-11-21 13:04:36.331632: Epoch 449 +2024-11-21 13:04:36.331740: Current learning rate: 0.00949 +2024-11-21 13:04:54.838489: train_loss -0.7495 +2024-11-21 13:04:54.838699: val_loss -0.7546 +2024-11-21 13:04:54.838770: Pseudo dice [0.8436] +2024-11-21 13:04:54.838846: Epoch time: 18.51 s +2024-11-21 13:04:55.836782: +2024-11-21 13:04:55.837010: Epoch 450 +2024-11-21 13:04:55.837117: Current learning rate: 0.00949 +2024-11-21 13:05:14.349800: train_loss -0.7571 +2024-11-21 13:05:14.350039: val_loss -0.7567 +2024-11-21 13:05:14.350118: Pseudo dice [0.8463] +2024-11-21 13:05:14.350200: Epoch time: 18.51 s +2024-11-21 13:05:15.147919: +2024-11-21 13:05:15.148138: Epoch 451 +2024-11-21 13:05:15.148247: Current learning rate: 0.00949 +2024-11-21 13:05:33.709785: train_loss -0.749 +2024-11-21 13:05:33.710006: val_loss -0.7685 +2024-11-21 13:05:33.710086: Pseudo dice [0.8427] +2024-11-21 13:05:33.710162: Epoch time: 18.56 s +2024-11-21 13:05:34.496417: +2024-11-21 13:05:34.496645: Epoch 452 +2024-11-21 13:05:34.496762: Current learning rate: 0.00949 +2024-11-21 13:05:53.419586: train_loss -0.7605 +2024-11-21 13:05:53.419844: val_loss -0.7664 +2024-11-21 13:05:53.419919: Pseudo dice [0.8376] +2024-11-21 13:05:53.420229: Epoch time: 18.92 s +2024-11-21 13:05:54.202615: +2024-11-21 13:05:54.202820: Epoch 453 +2024-11-21 13:05:54.202931: Current learning rate: 0.00949 +2024-11-21 13:06:11.592460: train_loss -0.7612 +2024-11-21 13:06:11.592777: val_loss -0.7754 +2024-11-21 13:06:11.592863: Pseudo dice [0.8419] +2024-11-21 13:06:11.592945: Epoch time: 17.39 s +2024-11-21 13:06:12.380067: +2024-11-21 13:06:12.380322: Epoch 454 +2024-11-21 13:06:12.380432: Current learning rate: 0.00949 +2024-11-21 13:06:30.351730: train_loss -0.7475 +2024-11-21 13:06:30.351933: val_loss -0.757 +2024-11-21 13:06:30.352013: Pseudo dice [0.8234] +2024-11-21 13:06:30.352087: Epoch time: 17.97 s +2024-11-21 13:06:31.183428: +2024-11-21 13:06:31.183632: Epoch 455 +2024-11-21 13:06:31.183738: Current learning rate: 0.00949 +2024-11-21 13:06:49.445112: train_loss -0.7484 +2024-11-21 13:06:49.445335: val_loss -0.7796 +2024-11-21 13:06:49.445441: Pseudo dice [0.8338] +2024-11-21 13:06:49.445517: Epoch time: 18.26 s +2024-11-21 13:06:50.225983: +2024-11-21 13:06:50.226193: Epoch 456 +2024-11-21 13:06:50.226299: Current learning rate: 0.00949 +2024-11-21 13:07:07.871540: train_loss -0.7528 +2024-11-21 13:07:07.871763: val_loss -0.767 +2024-11-21 13:07:07.871837: Pseudo dice [0.8288] +2024-11-21 13:07:07.871918: Epoch time: 17.65 s +2024-11-21 13:07:08.725618: +2024-11-21 13:07:08.725838: Epoch 457 +2024-11-21 13:07:08.725947: Current learning rate: 0.00948 +2024-11-21 13:07:26.932023: train_loss -0.7481 +2024-11-21 13:07:26.932279: val_loss -0.7449 +2024-11-21 13:07:26.932352: Pseudo dice [0.8202] +2024-11-21 13:07:26.932449: Epoch time: 18.21 s +2024-11-21 13:07:27.716655: +2024-11-21 13:07:27.716862: Epoch 458 +2024-11-21 13:07:27.716976: Current learning rate: 0.00948 +2024-11-21 13:07:46.024320: train_loss -0.7597 +2024-11-21 13:07:46.024524: val_loss -0.7525 +2024-11-21 13:07:46.024602: Pseudo dice [0.8427] +2024-11-21 13:07:46.024682: Epoch time: 18.31 s +2024-11-21 13:07:47.168680: +2024-11-21 13:07:47.168936: Epoch 459 +2024-11-21 13:07:47.169054: Current learning rate: 0.00948 +2024-11-21 13:08:04.859210: train_loss -0.7231 +2024-11-21 13:08:04.859447: val_loss -0.7328 +2024-11-21 13:08:04.859522: Pseudo dice [0.8206] +2024-11-21 13:08:04.859595: Epoch time: 17.69 s +2024-11-21 13:08:05.660698: +2024-11-21 13:08:05.660908: Epoch 460 +2024-11-21 13:08:05.661018: Current learning rate: 0.00948 +2024-11-21 13:08:23.428021: train_loss -0.735 +2024-11-21 13:08:23.428259: val_loss -0.7377 +2024-11-21 13:08:23.428330: Pseudo dice [0.8146] +2024-11-21 13:08:23.428413: Epoch time: 17.77 s +2024-11-21 13:08:24.277001: +2024-11-21 13:08:24.277199: Epoch 461 +2024-11-21 13:08:24.277310: Current learning rate: 0.00948 +2024-11-21 13:08:42.805008: train_loss -0.7268 +2024-11-21 13:08:42.805277: val_loss -0.7484 +2024-11-21 13:08:42.805415: Pseudo dice [0.8386] +2024-11-21 13:08:42.805501: Epoch time: 18.53 s +2024-11-21 13:08:43.590286: +2024-11-21 13:08:43.590535: Epoch 462 +2024-11-21 13:08:43.590650: Current learning rate: 0.00948 +2024-11-21 13:09:01.984402: train_loss -0.7521 +2024-11-21 13:09:01.984620: val_loss -0.7723 +2024-11-21 13:09:01.984693: Pseudo dice [0.836] +2024-11-21 13:09:01.984765: Epoch time: 18.39 s +2024-11-21 13:09:02.776970: +2024-11-21 13:09:02.777198: Epoch 463 +2024-11-21 13:09:02.777318: Current learning rate: 0.00948 +2024-11-21 13:09:20.801566: train_loss -0.7563 +2024-11-21 13:09:20.801830: val_loss -0.775 +2024-11-21 13:09:20.801907: Pseudo dice [0.8357] +2024-11-21 13:09:20.801986: Epoch time: 18.03 s +2024-11-21 13:09:21.582134: +2024-11-21 13:09:21.582363: Epoch 464 +2024-11-21 13:09:21.582476: Current learning rate: 0.00948 +2024-11-21 13:09:39.054271: train_loss -0.7553 +2024-11-21 13:09:39.054515: val_loss -0.7677 +2024-11-21 13:09:39.054591: Pseudo dice [0.852] +2024-11-21 13:09:39.054673: Epoch time: 17.47 s +2024-11-21 13:09:39.840936: +2024-11-21 13:09:39.841168: Epoch 465 +2024-11-21 13:09:39.841283: Current learning rate: 0.00948 +2024-11-21 13:09:58.184415: train_loss -0.7566 +2024-11-21 13:09:58.184630: val_loss -0.7586 +2024-11-21 13:09:58.184720: Pseudo dice [0.8423] +2024-11-21 13:09:58.184795: Epoch time: 18.34 s +2024-11-21 13:09:59.128132: +2024-11-21 13:09:59.128335: Epoch 466 +2024-11-21 13:09:59.128447: Current learning rate: 0.00947 +2024-11-21 13:10:17.447241: train_loss -0.7602 +2024-11-21 13:10:17.447518: val_loss -0.7591 +2024-11-21 13:10:17.447597: Pseudo dice [0.8464] +2024-11-21 13:10:17.447676: Epoch time: 18.32 s +2024-11-21 13:10:18.232187: +2024-11-21 13:10:18.232452: Epoch 467 +2024-11-21 13:10:18.232569: Current learning rate: 0.00947 +2024-11-21 13:10:37.123873: train_loss -0.7585 +2024-11-21 13:10:37.126245: val_loss -0.7624 +2024-11-21 13:10:37.126340: Pseudo dice [0.845] +2024-11-21 13:10:37.126417: Epoch time: 18.89 s +2024-11-21 13:10:38.030601: +2024-11-21 13:10:38.030817: Epoch 468 +2024-11-21 13:10:38.030927: Current learning rate: 0.00947 +2024-11-21 13:10:55.291046: train_loss -0.7522 +2024-11-21 13:10:55.291297: val_loss -0.7499 +2024-11-21 13:10:55.291370: Pseudo dice [0.8302] +2024-11-21 13:10:55.291450: Epoch time: 17.26 s +2024-11-21 13:10:56.074839: +2024-11-21 13:10:56.075048: Epoch 469 +2024-11-21 13:10:56.075157: Current learning rate: 0.00947 +2024-11-21 13:11:15.423272: train_loss -0.7513 +2024-11-21 13:11:15.423479: val_loss -0.7536 +2024-11-21 13:11:15.423553: Pseudo dice [0.8413] +2024-11-21 13:11:15.423626: Epoch time: 19.35 s +2024-11-21 13:11:16.308693: +2024-11-21 13:11:16.308905: Epoch 470 +2024-11-21 13:11:16.309021: Current learning rate: 0.00947 +2024-11-21 13:11:34.629951: train_loss -0.7628 +2024-11-21 13:11:34.630178: val_loss -0.7455 +2024-11-21 13:11:34.630253: Pseudo dice [0.8175] +2024-11-21 13:11:34.630331: Epoch time: 18.32 s +2024-11-21 13:11:35.802171: +2024-11-21 13:11:35.802367: Epoch 471 +2024-11-21 13:11:35.802477: Current learning rate: 0.00947 +2024-11-21 13:11:55.235171: train_loss -0.7548 +2024-11-21 13:11:55.235451: val_loss -0.7714 +2024-11-21 13:11:55.235533: Pseudo dice [0.847] +2024-11-21 13:11:55.235613: Epoch time: 19.43 s +2024-11-21 13:11:56.023418: +2024-11-21 13:11:56.023637: Epoch 472 +2024-11-21 13:11:56.023752: Current learning rate: 0.00947 +2024-11-21 13:12:14.408276: train_loss -0.7632 +2024-11-21 13:12:14.408484: val_loss -0.7414 +2024-11-21 13:12:14.408566: Pseudo dice [0.8435] +2024-11-21 13:12:14.408638: Epoch time: 18.39 s +2024-11-21 13:12:15.190087: +2024-11-21 13:12:15.190301: Epoch 473 +2024-11-21 13:12:15.190426: Current learning rate: 0.00947 +2024-11-21 13:12:33.007902: train_loss -0.7615 +2024-11-21 13:12:33.008134: val_loss -0.7614 +2024-11-21 13:12:33.008209: Pseudo dice [0.8428] +2024-11-21 13:12:33.008283: Epoch time: 17.82 s +2024-11-21 13:12:33.791468: +2024-11-21 13:12:33.791713: Epoch 474 +2024-11-21 13:12:33.791824: Current learning rate: 0.00947 +2024-11-21 13:12:51.778155: train_loss -0.7486 +2024-11-21 13:12:51.778391: val_loss -0.7605 +2024-11-21 13:12:51.778468: Pseudo dice [0.8401] +2024-11-21 13:12:51.778551: Epoch time: 17.99 s +2024-11-21 13:12:52.570816: +2024-11-21 13:12:52.571015: Epoch 475 +2024-11-21 13:12:52.571128: Current learning rate: 0.00946 +2024-11-21 13:13:11.446815: train_loss -0.7324 +2024-11-21 13:13:11.447116: val_loss -0.7367 +2024-11-21 13:13:11.447192: Pseudo dice [0.8321] +2024-11-21 13:13:11.447268: Epoch time: 18.88 s +2024-11-21 13:13:12.233258: +2024-11-21 13:13:12.233484: Epoch 476 +2024-11-21 13:13:12.233596: Current learning rate: 0.00946 +2024-11-21 13:13:30.459976: train_loss -0.76 +2024-11-21 13:13:30.462361: val_loss -0.7685 +2024-11-21 13:13:30.462455: Pseudo dice [0.832] +2024-11-21 13:13:30.462528: Epoch time: 18.23 s +2024-11-21 13:13:31.518142: +2024-11-21 13:13:31.518361: Epoch 477 +2024-11-21 13:13:31.518472: Current learning rate: 0.00946 +2024-11-21 13:13:50.624531: train_loss -0.7516 +2024-11-21 13:13:50.624753: val_loss -0.7654 +2024-11-21 13:13:50.624831: Pseudo dice [0.8365] +2024-11-21 13:13:50.624904: Epoch time: 19.11 s +2024-11-21 13:13:51.440471: +2024-11-21 13:13:51.440687: Epoch 478 +2024-11-21 13:13:51.440797: Current learning rate: 0.00946 +2024-11-21 13:14:11.064999: train_loss -0.7475 +2024-11-21 13:14:11.065978: val_loss -0.757 +2024-11-21 13:14:11.066137: Pseudo dice [0.8464] +2024-11-21 13:14:11.066531: Epoch time: 19.63 s +2024-11-21 13:14:11.863814: +2024-11-21 13:14:11.864021: Epoch 479 +2024-11-21 13:14:11.864137: Current learning rate: 0.00946 +2024-11-21 13:14:30.013557: train_loss -0.7612 +2024-11-21 13:14:30.018960: val_loss -0.7485 +2024-11-21 13:14:30.019159: Pseudo dice [0.8265] +2024-11-21 13:14:30.019259: Epoch time: 18.15 s +2024-11-21 13:14:30.814461: +2024-11-21 13:14:30.814667: Epoch 480 +2024-11-21 13:14:30.814791: Current learning rate: 0.00946 +2024-11-21 13:14:48.202400: train_loss -0.7573 +2024-11-21 13:14:48.202605: val_loss -0.7581 +2024-11-21 13:14:48.202680: Pseudo dice [0.8333] +2024-11-21 13:14:48.202753: Epoch time: 17.39 s +2024-11-21 13:14:48.991351: +2024-11-21 13:14:48.991578: Epoch 481 +2024-11-21 13:14:48.991696: Current learning rate: 0.00946 +2024-11-21 13:15:07.260117: train_loss -0.7574 +2024-11-21 13:15:07.260323: val_loss -0.7509 +2024-11-21 13:15:07.260396: Pseudo dice [0.8441] +2024-11-21 13:15:07.260468: Epoch time: 18.27 s +2024-11-21 13:15:08.049251: +2024-11-21 13:15:08.049495: Epoch 482 +2024-11-21 13:15:08.049609: Current learning rate: 0.00946 +2024-11-21 13:15:26.655343: train_loss -0.759 +2024-11-21 13:15:26.655579: val_loss -0.7581 +2024-11-21 13:15:26.655654: Pseudo dice [0.8366] +2024-11-21 13:15:26.655734: Epoch time: 18.61 s +2024-11-21 13:15:27.833162: +2024-11-21 13:15:27.833473: Epoch 483 +2024-11-21 13:15:27.833584: Current learning rate: 0.00945 +2024-11-21 13:15:47.276751: train_loss -0.7626 +2024-11-21 13:15:47.277052: val_loss -0.7742 +2024-11-21 13:15:47.277124: Pseudo dice [0.8416] +2024-11-21 13:15:47.280090: Epoch time: 19.44 s +2024-11-21 13:15:48.135372: +2024-11-21 13:15:48.135595: Epoch 484 +2024-11-21 13:15:48.135705: Current learning rate: 0.00945 +2024-11-21 13:16:06.588612: train_loss -0.7598 +2024-11-21 13:16:06.588823: val_loss -0.7421 +2024-11-21 13:16:06.588901: Pseudo dice [0.8458] +2024-11-21 13:16:06.588975: Epoch time: 18.45 s +2024-11-21 13:16:06.589050: Yayy! New best EMA pseudo Dice: 0.8382 +2024-11-21 13:16:07.633072: +2024-11-21 13:16:07.633256: Epoch 485 +2024-11-21 13:16:07.633366: Current learning rate: 0.00945 +2024-11-21 13:16:26.054781: train_loss -0.7545 +2024-11-21 13:16:26.055055: val_loss -0.7743 +2024-11-21 13:16:26.055135: Pseudo dice [0.8502] +2024-11-21 13:16:26.055222: Epoch time: 18.42 s +2024-11-21 13:16:26.055287: Yayy! New best EMA pseudo Dice: 0.8394 +2024-11-21 13:16:27.087288: +2024-11-21 13:16:27.087479: Epoch 486 +2024-11-21 13:16:27.087587: Current learning rate: 0.00945 +2024-11-21 13:16:45.830860: train_loss -0.7507 +2024-11-21 13:16:45.831132: val_loss -0.7625 +2024-11-21 13:16:45.831209: Pseudo dice [0.853] +2024-11-21 13:16:45.831283: Epoch time: 18.74 s +2024-11-21 13:16:45.831344: Yayy! New best EMA pseudo Dice: 0.8408 +2024-11-21 13:16:46.907327: +2024-11-21 13:16:46.907545: Epoch 487 +2024-11-21 13:16:46.907654: Current learning rate: 0.00945 +2024-11-21 13:17:06.276772: train_loss -0.7559 +2024-11-21 13:17:06.279323: val_loss -0.7812 +2024-11-21 13:17:06.279412: Pseudo dice [0.8482] +2024-11-21 13:17:06.279486: Epoch time: 19.37 s +2024-11-21 13:17:06.279549: Yayy! New best EMA pseudo Dice: 0.8415 +2024-11-21 13:17:07.363085: +2024-11-21 13:17:07.363375: Epoch 488 +2024-11-21 13:17:07.363484: Current learning rate: 0.00945 +2024-11-21 13:17:26.466532: train_loss -0.766 +2024-11-21 13:17:26.466752: val_loss -0.7547 +2024-11-21 13:17:26.466830: Pseudo dice [0.8459] +2024-11-21 13:17:26.466905: Epoch time: 19.1 s +2024-11-21 13:17:26.466969: Yayy! New best EMA pseudo Dice: 0.8419 +2024-11-21 13:17:27.459414: +2024-11-21 13:17:27.459711: Epoch 489 +2024-11-21 13:17:27.459824: Current learning rate: 0.00945 +2024-11-21 13:17:45.154791: train_loss -0.754 +2024-11-21 13:17:45.155038: val_loss -0.7574 +2024-11-21 13:17:45.155112: Pseudo dice [0.8271] +2024-11-21 13:17:45.155191: Epoch time: 17.7 s +2024-11-21 13:17:45.960254: +2024-11-21 13:17:45.960469: Epoch 490 +2024-11-21 13:17:45.960577: Current learning rate: 0.00945 +2024-11-21 13:18:03.668857: train_loss -0.7614 +2024-11-21 13:18:03.669068: val_loss -0.7565 +2024-11-21 13:18:03.669142: Pseudo dice [0.8202] +2024-11-21 13:18:03.669214: Epoch time: 17.71 s +2024-11-21 13:18:04.464119: +2024-11-21 13:18:04.464329: Epoch 491 +2024-11-21 13:18:04.464442: Current learning rate: 0.00945 +2024-11-21 13:18:22.773197: train_loss -0.7586 +2024-11-21 13:18:22.773427: val_loss -0.7534 +2024-11-21 13:18:22.773504: Pseudo dice [0.8372] +2024-11-21 13:18:22.773581: Epoch time: 18.31 s +2024-11-21 13:18:23.564082: +2024-11-21 13:18:23.564266: Epoch 492 +2024-11-21 13:18:23.564374: Current learning rate: 0.00944 +2024-11-21 13:18:42.285401: train_loss -0.7489 +2024-11-21 13:18:42.285650: val_loss -0.7549 +2024-11-21 13:18:42.285728: Pseudo dice [0.8363] +2024-11-21 13:18:42.285811: Epoch time: 18.72 s +2024-11-21 13:18:43.084113: +2024-11-21 13:18:43.084324: Epoch 493 +2024-11-21 13:18:43.084432: Current learning rate: 0.00944 +2024-11-21 13:19:02.073985: train_loss -0.743 +2024-11-21 13:19:02.074205: val_loss -0.7576 +2024-11-21 13:19:02.074279: Pseudo dice [0.8291] +2024-11-21 13:19:02.074351: Epoch time: 18.99 s +2024-11-21 13:19:03.222558: +2024-11-21 13:19:03.222802: Epoch 494 +2024-11-21 13:19:03.222916: Current learning rate: 0.00944 +2024-11-21 13:19:20.776309: train_loss -0.7555 +2024-11-21 13:19:20.776557: val_loss -0.7311 +2024-11-21 13:19:20.776635: Pseudo dice [0.8209] +2024-11-21 13:19:20.776709: Epoch time: 17.55 s +2024-11-21 13:19:21.561988: +2024-11-21 13:19:21.562218: Epoch 495 +2024-11-21 13:19:21.562328: Current learning rate: 0.00944 +2024-11-21 13:19:39.842947: train_loss -0.7496 +2024-11-21 13:19:39.843203: val_loss -0.6982 +2024-11-21 13:19:39.843280: Pseudo dice [0.8164] +2024-11-21 13:19:39.844020: Epoch time: 18.28 s +2024-11-21 13:19:40.676812: +2024-11-21 13:19:40.677035: Epoch 496 +2024-11-21 13:19:40.677154: Current learning rate: 0.00944 +2024-11-21 13:19:58.962494: train_loss -0.7465 +2024-11-21 13:19:58.962696: val_loss -0.7702 +2024-11-21 13:19:58.962768: Pseudo dice [0.8307] +2024-11-21 13:19:58.962862: Epoch time: 18.29 s +2024-11-21 13:19:59.747080: +2024-11-21 13:19:59.747304: Epoch 497 +2024-11-21 13:19:59.747419: Current learning rate: 0.00944 +2024-11-21 13:20:18.191767: train_loss -0.7569 +2024-11-21 13:20:18.191981: val_loss -0.7763 +2024-11-21 13:20:18.192061: Pseudo dice [0.8278] +2024-11-21 13:20:18.192133: Epoch time: 18.45 s +2024-11-21 13:20:19.054868: +2024-11-21 13:20:19.055099: Epoch 498 +2024-11-21 13:20:19.055211: Current learning rate: 0.00944 +2024-11-21 13:20:38.554421: train_loss -0.7588 +2024-11-21 13:20:38.554631: val_loss -0.7607 +2024-11-21 13:20:38.554705: Pseudo dice [0.8384] +2024-11-21 13:20:38.554779: Epoch time: 19.5 s +2024-11-21 13:20:39.497670: +2024-11-21 13:20:39.497904: Epoch 499 +2024-11-21 13:20:39.498017: Current learning rate: 0.00944 +2024-11-21 13:20:58.442750: train_loss -0.7576 +2024-11-21 13:20:58.442980: val_loss -0.7537 +2024-11-21 13:20:58.443062: Pseudo dice [0.8498] +2024-11-21 13:20:58.443144: Epoch time: 18.95 s +2024-11-21 13:20:59.484541: +2024-11-21 13:20:59.484764: Epoch 500 +2024-11-21 13:20:59.484873: Current learning rate: 0.00944 +2024-11-21 13:21:18.505674: train_loss -0.757 +2024-11-21 13:21:18.505892: val_loss -0.7417 +2024-11-21 13:21:18.505967: Pseudo dice [0.8488] +2024-11-21 13:21:18.506051: Epoch time: 19.02 s +2024-11-21 13:21:19.300675: +2024-11-21 13:21:19.300957: Epoch 501 +2024-11-21 13:21:19.301070: Current learning rate: 0.00943 +2024-11-21 13:21:38.024540: train_loss -0.7704 +2024-11-21 13:21:38.024747: val_loss -0.7363 +2024-11-21 13:21:38.024819: Pseudo dice [0.8236] +2024-11-21 13:21:38.024890: Epoch time: 18.72 s +2024-11-21 13:21:39.092767: +2024-11-21 13:21:39.092996: Epoch 502 +2024-11-21 13:21:39.093109: Current learning rate: 0.00943 +2024-11-21 13:21:58.318391: train_loss -0.7613 +2024-11-21 13:21:58.318623: val_loss -0.7716 +2024-11-21 13:21:58.318698: Pseudo dice [0.8261] +2024-11-21 13:21:58.318781: Epoch time: 19.23 s +2024-11-21 13:21:59.109240: +2024-11-21 13:21:59.109521: Epoch 503 +2024-11-21 13:21:59.109632: Current learning rate: 0.00943 +2024-11-21 13:22:17.161830: train_loss -0.7556 +2024-11-21 13:22:17.164291: val_loss -0.7563 +2024-11-21 13:22:17.165087: Pseudo dice [0.8354] +2024-11-21 13:22:17.165219: Epoch time: 18.05 s +2024-11-21 13:22:17.980492: +2024-11-21 13:22:17.980702: Epoch 504 +2024-11-21 13:22:17.980810: Current learning rate: 0.00943 +2024-11-21 13:22:37.013671: train_loss -0.7604 +2024-11-21 13:22:37.013893: val_loss -0.7595 +2024-11-21 13:22:37.013999: Pseudo dice [0.83] +2024-11-21 13:22:37.014081: Epoch time: 19.03 s +2024-11-21 13:22:37.804312: +2024-11-21 13:22:37.804521: Epoch 505 +2024-11-21 13:22:37.804639: Current learning rate: 0.00943 +2024-11-21 13:22:56.404751: train_loss -0.7525 +2024-11-21 13:22:56.404978: val_loss -0.7561 +2024-11-21 13:22:56.405061: Pseudo dice [0.8439] +2024-11-21 13:22:56.405137: Epoch time: 18.6 s +2024-11-21 13:22:57.197504: +2024-11-21 13:22:57.197743: Epoch 506 +2024-11-21 13:22:57.197853: Current learning rate: 0.00943 +2024-11-21 13:23:16.811639: train_loss -0.7595 +2024-11-21 13:23:16.811883: val_loss -0.7496 +2024-11-21 13:23:16.811960: Pseudo dice [0.8517] +2024-11-21 13:23:16.812053: Epoch time: 19.61 s +2024-11-21 13:23:17.602474: +2024-11-21 13:23:17.602700: Epoch 507 +2024-11-21 13:23:17.602811: Current learning rate: 0.00943 +2024-11-21 13:23:36.157299: train_loss -0.7582 +2024-11-21 13:23:36.157519: val_loss -0.7613 +2024-11-21 13:23:36.157595: Pseudo dice [0.8309] +2024-11-21 13:23:36.157672: Epoch time: 18.56 s +2024-11-21 13:23:36.948790: +2024-11-21 13:23:36.949058: Epoch 508 +2024-11-21 13:23:36.949168: Current learning rate: 0.00943 +2024-11-21 13:23:55.314122: train_loss -0.762 +2024-11-21 13:23:55.314337: val_loss -0.7564 +2024-11-21 13:23:55.314414: Pseudo dice [0.8339] +2024-11-21 13:23:55.314490: Epoch time: 18.37 s +2024-11-21 13:23:56.123391: +2024-11-21 13:23:56.123612: Epoch 509 +2024-11-21 13:23:56.123723: Current learning rate: 0.00943 +2024-11-21 13:24:13.978827: train_loss -0.7612 +2024-11-21 13:24:13.979075: val_loss -0.755 +2024-11-21 13:24:13.979153: Pseudo dice [0.8436] +2024-11-21 13:24:13.979236: Epoch time: 17.86 s +2024-11-21 13:24:14.779089: +2024-11-21 13:24:14.779400: Epoch 510 +2024-11-21 13:24:14.779508: Current learning rate: 0.00942 +2024-11-21 13:24:32.840909: train_loss -0.7592 +2024-11-21 13:24:32.841125: val_loss -0.7505 +2024-11-21 13:24:32.841202: Pseudo dice [0.8348] +2024-11-21 13:24:32.841323: Epoch time: 18.06 s +2024-11-21 13:24:33.636968: +2024-11-21 13:24:33.637173: Epoch 511 +2024-11-21 13:24:33.637297: Current learning rate: 0.00942 +2024-11-21 13:24:52.650586: train_loss -0.7454 +2024-11-21 13:24:52.650805: val_loss -0.7724 +2024-11-21 13:24:52.650885: Pseudo dice [0.8337] +2024-11-21 13:24:52.650961: Epoch time: 19.01 s +2024-11-21 13:24:53.445907: +2024-11-21 13:24:53.446118: Epoch 512 +2024-11-21 13:24:53.446226: Current learning rate: 0.00942 +2024-11-21 13:25:11.393557: train_loss -0.7645 +2024-11-21 13:25:11.393760: val_loss -0.7756 +2024-11-21 13:25:11.393836: Pseudo dice [0.8353] +2024-11-21 13:25:11.393911: Epoch time: 17.95 s +2024-11-21 13:25:12.183624: +2024-11-21 13:25:12.183828: Epoch 513 +2024-11-21 13:25:12.183937: Current learning rate: 0.00942 +2024-11-21 13:25:32.028395: train_loss -0.7612 +2024-11-21 13:25:32.030799: val_loss -0.7482 +2024-11-21 13:25:32.030919: Pseudo dice [0.8598] +2024-11-21 13:25:32.031016: Epoch time: 19.85 s +2024-11-21 13:25:32.863640: +2024-11-21 13:25:32.863846: Epoch 514 +2024-11-21 13:25:32.863980: Current learning rate: 0.00942 +2024-11-21 13:25:51.637732: train_loss -0.7587 +2024-11-21 13:25:51.637968: val_loss -0.7414 +2024-11-21 13:25:51.638062: Pseudo dice [0.8319] +2024-11-21 13:25:51.638138: Epoch time: 18.77 s +2024-11-21 13:25:52.494502: +2024-11-21 13:25:52.494713: Epoch 515 +2024-11-21 13:25:52.494821: Current learning rate: 0.00942 +2024-11-21 13:26:09.975610: train_loss -0.7555 +2024-11-21 13:26:09.975809: val_loss -0.7427 +2024-11-21 13:26:09.975882: Pseudo dice [0.8354] +2024-11-21 13:26:09.975955: Epoch time: 17.48 s +2024-11-21 13:26:10.897512: +2024-11-21 13:26:10.897693: Epoch 516 +2024-11-21 13:26:10.897807: Current learning rate: 0.00942 +2024-11-21 13:26:29.718087: train_loss -0.7642 +2024-11-21 13:26:29.718315: val_loss -0.7682 +2024-11-21 13:26:29.718390: Pseudo dice [0.8512] +2024-11-21 13:26:29.718470: Epoch time: 18.82 s +2024-11-21 13:26:30.882200: +2024-11-21 13:26:30.882399: Epoch 517 +2024-11-21 13:26:30.882509: Current learning rate: 0.00942 +2024-11-21 13:26:49.010143: train_loss -0.7434 +2024-11-21 13:26:49.010418: val_loss -0.7576 +2024-11-21 13:26:49.010497: Pseudo dice [0.839] +2024-11-21 13:26:49.010571: Epoch time: 18.13 s +2024-11-21 13:26:49.802124: +2024-11-21 13:26:49.802351: Epoch 518 +2024-11-21 13:26:49.802464: Current learning rate: 0.00942 +2024-11-21 13:27:08.717782: train_loss -0.7562 +2024-11-21 13:27:08.718050: val_loss -0.7605 +2024-11-21 13:27:08.718125: Pseudo dice [0.831] +2024-11-21 13:27:08.718199: Epoch time: 18.92 s +2024-11-21 13:27:09.510192: +2024-11-21 13:27:09.510425: Epoch 519 +2024-11-21 13:27:09.510532: Current learning rate: 0.00941 +2024-11-21 13:27:28.664213: train_loss -0.7573 +2024-11-21 13:27:28.664507: val_loss -0.7774 +2024-11-21 13:27:28.664587: Pseudo dice [0.8407] +2024-11-21 13:27:28.664663: Epoch time: 19.15 s +2024-11-21 13:27:29.510906: +2024-11-21 13:27:29.511128: Epoch 520 +2024-11-21 13:27:29.511240: Current learning rate: 0.00941 +2024-11-21 13:27:48.717071: train_loss -0.7471 +2024-11-21 13:27:48.717303: val_loss -0.7507 +2024-11-21 13:27:48.717379: Pseudo dice [0.831] +2024-11-21 13:27:48.717458: Epoch time: 19.21 s +2024-11-21 13:27:49.514045: +2024-11-21 13:27:49.514255: Epoch 521 +2024-11-21 13:27:49.514365: Current learning rate: 0.00941 +2024-11-21 13:28:07.008970: train_loss -0.7543 +2024-11-21 13:28:07.009195: val_loss -0.7423 +2024-11-21 13:28:07.009274: Pseudo dice [0.8392] +2024-11-21 13:28:07.009351: Epoch time: 17.5 s +2024-11-21 13:28:07.806703: +2024-11-21 13:28:07.806919: Epoch 522 +2024-11-21 13:28:07.807116: Current learning rate: 0.00941 +2024-11-21 13:28:27.019802: train_loss -0.7595 +2024-11-21 13:28:27.020045: val_loss -0.7533 +2024-11-21 13:28:27.020119: Pseudo dice [0.8402] +2024-11-21 13:28:27.020202: Epoch time: 19.21 s +2024-11-21 13:28:28.011932: +2024-11-21 13:28:28.012167: Epoch 523 +2024-11-21 13:28:28.012275: Current learning rate: 0.00941 +2024-11-21 13:28:46.135318: train_loss -0.7532 +2024-11-21 13:28:46.135535: val_loss -0.7607 +2024-11-21 13:28:46.135612: Pseudo dice [0.83] +2024-11-21 13:28:46.135694: Epoch time: 18.12 s +2024-11-21 13:28:46.928230: +2024-11-21 13:28:46.928512: Epoch 524 +2024-11-21 13:28:46.928625: Current learning rate: 0.00941 +2024-11-21 13:29:05.939764: train_loss -0.7624 +2024-11-21 13:29:05.940094: val_loss -0.7399 +2024-11-21 13:29:05.940172: Pseudo dice [0.8176] +2024-11-21 13:29:05.940250: Epoch time: 19.01 s +2024-11-21 13:29:06.732403: +2024-11-21 13:29:06.732631: Epoch 525 +2024-11-21 13:29:06.732754: Current learning rate: 0.00941 +2024-11-21 13:29:24.766803: train_loss -0.7597 +2024-11-21 13:29:24.767017: val_loss -0.7792 +2024-11-21 13:29:24.767091: Pseudo dice [0.8516] +2024-11-21 13:29:24.767167: Epoch time: 18.04 s +2024-11-21 13:29:25.557745: +2024-11-21 13:29:25.557951: Epoch 526 +2024-11-21 13:29:25.558065: Current learning rate: 0.00941 +2024-11-21 13:29:43.688172: train_loss -0.7605 +2024-11-21 13:29:43.688403: val_loss -0.7505 +2024-11-21 13:29:43.688480: Pseudo dice [0.8423] +2024-11-21 13:29:43.688554: Epoch time: 18.13 s +2024-11-21 13:29:44.496641: +2024-11-21 13:29:44.496841: Epoch 527 +2024-11-21 13:29:44.496963: Current learning rate: 0.00941 +2024-11-21 13:30:03.045863: train_loss -0.7659 +2024-11-21 13:30:03.046106: val_loss -0.7714 +2024-11-21 13:30:03.046183: Pseudo dice [0.8421] +2024-11-21 13:30:03.046267: Epoch time: 18.55 s +2024-11-21 13:30:03.841673: +2024-11-21 13:30:03.841840: Epoch 528 +2024-11-21 13:30:03.841951: Current learning rate: 0.0094 +2024-11-21 13:30:21.768642: train_loss -0.7613 +2024-11-21 13:30:21.768860: val_loss -0.7569 +2024-11-21 13:30:21.768933: Pseudo dice [0.841] +2024-11-21 13:30:21.769014: Epoch time: 17.93 s +2024-11-21 13:30:22.560837: +2024-11-21 13:30:22.561046: Epoch 529 +2024-11-21 13:30:22.561155: Current learning rate: 0.0094 +2024-11-21 13:30:42.199406: train_loss -0.7588 +2024-11-21 13:30:42.199623: val_loss -0.7508 +2024-11-21 13:30:42.199698: Pseudo dice [0.8367] +2024-11-21 13:30:42.199862: Epoch time: 19.64 s +2024-11-21 13:30:42.993469: +2024-11-21 13:30:42.993690: Epoch 530 +2024-11-21 13:30:42.993799: Current learning rate: 0.0094 +2024-11-21 13:31:01.474785: train_loss -0.7612 +2024-11-21 13:31:01.477233: val_loss -0.7632 +2024-11-21 13:31:01.477379: Pseudo dice [0.8441] +2024-11-21 13:31:01.477470: Epoch time: 18.48 s +2024-11-21 13:31:02.283161: +2024-11-21 13:31:02.283377: Epoch 531 +2024-11-21 13:31:02.283491: Current learning rate: 0.0094 +2024-11-21 13:31:21.312948: train_loss -0.7539 +2024-11-21 13:31:21.313163: val_loss -0.7627 +2024-11-21 13:31:21.313276: Pseudo dice [0.8357] +2024-11-21 13:31:21.313349: Epoch time: 19.03 s +2024-11-21 13:31:22.104342: +2024-11-21 13:31:22.104553: Epoch 532 +2024-11-21 13:31:22.104662: Current learning rate: 0.0094 +2024-11-21 13:31:40.760505: train_loss -0.7555 +2024-11-21 13:31:40.760714: val_loss -0.7526 +2024-11-21 13:31:40.760788: Pseudo dice [0.8413] +2024-11-21 13:31:40.760864: Epoch time: 18.66 s +2024-11-21 13:31:41.558829: +2024-11-21 13:31:41.559066: Epoch 533 +2024-11-21 13:31:41.559175: Current learning rate: 0.0094 +2024-11-21 13:31:59.775149: train_loss -0.7585 +2024-11-21 13:31:59.775382: val_loss -0.7558 +2024-11-21 13:31:59.775461: Pseudo dice [0.8311] +2024-11-21 13:31:59.775541: Epoch time: 18.22 s +2024-11-21 13:32:00.743743: +2024-11-21 13:32:00.744117: Epoch 534 +2024-11-21 13:32:00.744228: Current learning rate: 0.0094 +2024-11-21 13:32:20.542003: train_loss -0.7536 +2024-11-21 13:32:20.542246: val_loss -0.7311 +2024-11-21 13:32:20.542325: Pseudo dice [0.8177] +2024-11-21 13:32:20.542409: Epoch time: 19.8 s +2024-11-21 13:32:21.513272: +2024-11-21 13:32:21.513496: Epoch 535 +2024-11-21 13:32:21.513619: Current learning rate: 0.0094 +2024-11-21 13:32:39.827736: train_loss -0.748 +2024-11-21 13:32:39.827949: val_loss -0.744 +2024-11-21 13:32:39.830168: Pseudo dice [0.8298] +2024-11-21 13:32:39.830386: Epoch time: 18.32 s +2024-11-21 13:32:40.654441: +2024-11-21 13:32:40.654662: Epoch 536 +2024-11-21 13:32:40.654777: Current learning rate: 0.00939 +2024-11-21 13:32:59.660896: train_loss -0.752 +2024-11-21 13:32:59.661152: val_loss -0.7396 +2024-11-21 13:32:59.661250: Pseudo dice [0.8272] +2024-11-21 13:32:59.661338: Epoch time: 19.01 s +2024-11-21 13:33:00.447407: +2024-11-21 13:33:00.447613: Epoch 537 +2024-11-21 13:33:00.447723: Current learning rate: 0.00939 +2024-11-21 13:33:19.251849: train_loss -0.758 +2024-11-21 13:33:19.252095: val_loss -0.7813 +2024-11-21 13:33:19.252172: Pseudo dice [0.8463] +2024-11-21 13:33:19.252250: Epoch time: 18.81 s +2024-11-21 13:33:20.066896: +2024-11-21 13:33:20.067097: Epoch 538 +2024-11-21 13:33:20.067207: Current learning rate: 0.00939 +2024-11-21 13:33:38.252093: train_loss -0.75 +2024-11-21 13:33:38.252325: val_loss -0.7724 +2024-11-21 13:33:38.252418: Pseudo dice [0.8469] +2024-11-21 13:33:38.252499: Epoch time: 18.19 s +2024-11-21 13:33:39.037695: +2024-11-21 13:33:39.037879: Epoch 539 +2024-11-21 13:33:39.037985: Current learning rate: 0.00939 +2024-11-21 13:33:58.276478: train_loss -0.7557 +2024-11-21 13:33:58.276679: val_loss -0.7478 +2024-11-21 13:33:58.276796: Pseudo dice [0.8145] +2024-11-21 13:33:58.276869: Epoch time: 19.24 s +2024-11-21 13:33:59.450754: +2024-11-21 13:33:59.450965: Epoch 540 +2024-11-21 13:33:59.451078: Current learning rate: 0.00939 +2024-11-21 13:34:17.713639: train_loss -0.7489 +2024-11-21 13:34:17.713864: val_loss -0.7656 +2024-11-21 13:34:17.713936: Pseudo dice [0.8353] +2024-11-21 13:34:17.714014: Epoch time: 18.26 s +2024-11-21 13:34:18.505633: +2024-11-21 13:34:18.505850: Epoch 541 +2024-11-21 13:34:18.505959: Current learning rate: 0.00939 +2024-11-21 13:34:36.157396: train_loss -0.7489 +2024-11-21 13:34:36.157642: val_loss -0.7708 +2024-11-21 13:34:36.157718: Pseudo dice [0.8477] +2024-11-21 13:34:36.157798: Epoch time: 17.65 s +2024-11-21 13:34:36.952009: +2024-11-21 13:34:36.952203: Epoch 542 +2024-11-21 13:34:36.952308: Current learning rate: 0.00939 +2024-11-21 13:34:55.845568: train_loss -0.7617 +2024-11-21 13:34:55.845779: val_loss -0.7557 +2024-11-21 13:34:55.846121: Pseudo dice [0.8326] +2024-11-21 13:34:55.846200: Epoch time: 18.89 s +2024-11-21 13:34:56.645659: +2024-11-21 13:34:56.645884: Epoch 543 +2024-11-21 13:34:56.645998: Current learning rate: 0.00939 +2024-11-21 13:35:14.861082: train_loss -0.7627 +2024-11-21 13:35:14.861288: val_loss -0.739 +2024-11-21 13:35:14.861394: Pseudo dice [0.837] +2024-11-21 13:35:14.861470: Epoch time: 18.22 s +2024-11-21 13:35:15.651402: +2024-11-21 13:35:15.651621: Epoch 544 +2024-11-21 13:35:15.651735: Current learning rate: 0.00939 +2024-11-21 13:35:34.627118: train_loss -0.7607 +2024-11-21 13:35:34.627347: val_loss -0.7488 +2024-11-21 13:35:34.627428: Pseudo dice [0.8399] +2024-11-21 13:35:34.627508: Epoch time: 18.98 s +2024-11-21 13:35:35.426424: +2024-11-21 13:35:35.426618: Epoch 545 +2024-11-21 13:35:35.426729: Current learning rate: 0.00938 +2024-11-21 13:35:54.502148: train_loss -0.7584 +2024-11-21 13:35:54.502382: val_loss -0.7736 +2024-11-21 13:35:54.502454: Pseudo dice [0.8304] +2024-11-21 13:35:54.502532: Epoch time: 19.08 s +2024-11-21 13:35:55.408882: +2024-11-21 13:35:55.409104: Epoch 546 +2024-11-21 13:35:55.409213: Current learning rate: 0.00938 +2024-11-21 13:36:14.630734: train_loss -0.7518 +2024-11-21 13:36:14.630922: val_loss -0.7584 +2024-11-21 13:36:14.630997: Pseudo dice [0.8539] +2024-11-21 13:36:14.631073: Epoch time: 19.22 s +2024-11-21 13:36:15.429085: +2024-11-21 13:36:15.429374: Epoch 547 +2024-11-21 13:36:15.429489: Current learning rate: 0.00938 +2024-11-21 13:36:33.018486: train_loss -0.7542 +2024-11-21 13:36:33.018692: val_loss -0.7814 +2024-11-21 13:36:33.018763: Pseudo dice [0.8375] +2024-11-21 13:36:33.018835: Epoch time: 17.59 s +2024-11-21 13:36:33.804214: +2024-11-21 13:36:33.804479: Epoch 548 +2024-11-21 13:36:33.804588: Current learning rate: 0.00938 +2024-11-21 13:36:51.755850: train_loss -0.7589 +2024-11-21 13:36:51.756060: val_loss -0.7509 +2024-11-21 13:36:51.756135: Pseudo dice [0.8333] +2024-11-21 13:36:51.756209: Epoch time: 17.95 s +2024-11-21 13:36:52.548679: +2024-11-21 13:36:52.548862: Epoch 549 +2024-11-21 13:36:52.548969: Current learning rate: 0.00938 +2024-11-21 13:37:09.715418: train_loss -0.7681 +2024-11-21 13:37:09.715664: val_loss -0.7486 +2024-11-21 13:37:09.715738: Pseudo dice [0.8247] +2024-11-21 13:37:09.715817: Epoch time: 17.17 s +2024-11-21 13:37:10.771653: +2024-11-21 13:37:10.771894: Epoch 550 +2024-11-21 13:37:10.772006: Current learning rate: 0.00938 +2024-11-21 13:37:30.626014: train_loss -0.7496 +2024-11-21 13:37:30.626221: val_loss -0.7609 +2024-11-21 13:37:30.626294: Pseudo dice [0.8159] +2024-11-21 13:37:30.626369: Epoch time: 19.86 s +2024-11-21 13:37:31.412609: +2024-11-21 13:37:31.412816: Epoch 551 +2024-11-21 13:37:31.412923: Current learning rate: 0.00938 +2024-11-21 13:37:49.638763: train_loss -0.7438 +2024-11-21 13:37:49.639984: val_loss -0.7538 +2024-11-21 13:37:49.640099: Pseudo dice [0.8169] +2024-11-21 13:37:49.640178: Epoch time: 18.23 s +2024-11-21 13:37:50.590606: +2024-11-21 13:37:50.590828: Epoch 552 +2024-11-21 13:37:50.590945: Current learning rate: 0.00938 +2024-11-21 13:38:08.899973: train_loss -0.7372 +2024-11-21 13:38:08.900260: val_loss -0.7225 +2024-11-21 13:38:08.900334: Pseudo dice [0.8402] +2024-11-21 13:38:08.900412: Epoch time: 18.31 s +2024-11-21 13:38:09.693478: +2024-11-21 13:38:09.693686: Epoch 553 +2024-11-21 13:38:09.693795: Current learning rate: 0.00938 +2024-11-21 13:38:28.224983: train_loss -0.7387 +2024-11-21 13:38:28.225206: val_loss -0.7337 +2024-11-21 13:38:28.225281: Pseudo dice [0.8395] +2024-11-21 13:38:28.225358: Epoch time: 18.53 s +2024-11-21 13:38:29.175009: +2024-11-21 13:38:29.175209: Epoch 554 +2024-11-21 13:38:29.175319: Current learning rate: 0.00937 +2024-11-21 13:38:47.133029: train_loss -0.747 +2024-11-21 13:38:47.133239: val_loss -0.7587 +2024-11-21 13:38:47.133313: Pseudo dice [0.828] +2024-11-21 13:38:47.133385: Epoch time: 17.96 s +2024-11-21 13:38:47.923652: +2024-11-21 13:38:47.923872: Epoch 555 +2024-11-21 13:38:47.923978: Current learning rate: 0.00937 +2024-11-21 13:39:06.249417: train_loss -0.7429 +2024-11-21 13:39:06.261108: val_loss -0.7654 +2024-11-21 13:39:06.261289: Pseudo dice [0.8299] +2024-11-21 13:39:06.261722: Epoch time: 18.33 s +2024-11-21 13:39:07.261348: +2024-11-21 13:39:07.261575: Epoch 556 +2024-11-21 13:39:07.261684: Current learning rate: 0.00937 +2024-11-21 13:39:25.859025: train_loss -0.752 +2024-11-21 13:39:25.859299: val_loss -0.7593 +2024-11-21 13:39:25.859378: Pseudo dice [0.833] +2024-11-21 13:39:25.859452: Epoch time: 18.6 s +2024-11-21 13:39:26.649923: +2024-11-21 13:39:26.650156: Epoch 557 +2024-11-21 13:39:26.650272: Current learning rate: 0.00937 +2024-11-21 13:39:45.563458: train_loss -0.755 +2024-11-21 13:39:45.568850: val_loss -0.7663 +2024-11-21 13:39:45.568982: Pseudo dice [0.8422] +2024-11-21 13:39:45.569067: Epoch time: 18.91 s +2024-11-21 13:39:46.370217: +2024-11-21 13:39:46.370420: Epoch 558 +2024-11-21 13:39:46.370530: Current learning rate: 0.00937 +2024-11-21 13:40:04.936891: train_loss -0.7521 +2024-11-21 13:40:04.937114: val_loss -0.7454 +2024-11-21 13:40:04.937189: Pseudo dice [0.8235] +2024-11-21 13:40:04.937266: Epoch time: 18.57 s +2024-11-21 13:40:05.741582: +2024-11-21 13:40:05.741794: Epoch 559 +2024-11-21 13:40:05.741902: Current learning rate: 0.00937 +2024-11-21 13:40:23.923828: train_loss -0.7573 +2024-11-21 13:40:23.924067: val_loss -0.7327 +2024-11-21 13:40:23.924143: Pseudo dice [0.8244] +2024-11-21 13:40:23.924225: Epoch time: 18.18 s +2024-11-21 13:40:24.721041: +2024-11-21 13:40:24.721271: Epoch 560 +2024-11-21 13:40:24.721381: Current learning rate: 0.00937 +2024-11-21 13:40:43.438307: train_loss -0.7721 +2024-11-21 13:40:43.438507: val_loss -0.7359 +2024-11-21 13:40:43.438579: Pseudo dice [0.8331] +2024-11-21 13:40:43.438653: Epoch time: 18.72 s +2024-11-21 13:40:44.229427: +2024-11-21 13:40:44.229605: Epoch 561 +2024-11-21 13:40:44.229714: Current learning rate: 0.00937 +2024-11-21 13:41:02.603714: train_loss -0.7642 +2024-11-21 13:41:02.603918: val_loss -0.7653 +2024-11-21 13:41:02.604002: Pseudo dice [0.8404] +2024-11-21 13:41:02.604075: Epoch time: 18.38 s +2024-11-21 13:41:03.392459: +2024-11-21 13:41:03.392779: Epoch 562 +2024-11-21 13:41:03.392892: Current learning rate: 0.00937 +2024-11-21 13:41:23.121744: train_loss -0.7567 +2024-11-21 13:41:23.122010: val_loss -0.7495 +2024-11-21 13:41:23.122094: Pseudo dice [0.8521] +2024-11-21 13:41:23.122180: Epoch time: 19.73 s +2024-11-21 13:41:24.270883: +2024-11-21 13:41:24.271110: Epoch 563 +2024-11-21 13:41:24.271221: Current learning rate: 0.00936 +2024-11-21 13:41:41.837833: train_loss -0.7645 +2024-11-21 13:41:41.838108: val_loss -0.7584 +2024-11-21 13:41:41.838244: Pseudo dice [0.8111] +2024-11-21 13:41:41.838326: Epoch time: 17.57 s +2024-11-21 13:41:42.633034: +2024-11-21 13:41:42.633258: Epoch 564 +2024-11-21 13:41:42.633376: Current learning rate: 0.00936 +2024-11-21 13:42:01.502585: train_loss -0.7544 +2024-11-21 13:42:01.502805: val_loss -0.7584 +2024-11-21 13:42:01.502886: Pseudo dice [0.8416] +2024-11-21 13:42:01.502962: Epoch time: 18.87 s +2024-11-21 13:42:02.297847: +2024-11-21 13:42:02.298090: Epoch 565 +2024-11-21 13:42:02.298204: Current learning rate: 0.00936 +2024-11-21 13:42:21.227704: train_loss -0.7635 +2024-11-21 13:42:21.227941: val_loss -0.7433 +2024-11-21 13:42:21.228020: Pseudo dice [0.8564] +2024-11-21 13:42:21.228093: Epoch time: 18.93 s +2024-11-21 13:42:22.127427: +2024-11-21 13:42:22.127705: Epoch 566 +2024-11-21 13:42:22.127819: Current learning rate: 0.00936 +2024-11-21 13:42:40.551009: train_loss -0.7522 +2024-11-21 13:42:40.551242: val_loss -0.7566 +2024-11-21 13:42:40.551319: Pseudo dice [0.8338] +2024-11-21 13:42:40.551398: Epoch time: 18.42 s +2024-11-21 13:42:41.349859: +2024-11-21 13:42:41.350071: Epoch 567 +2024-11-21 13:42:41.350181: Current learning rate: 0.00936 +2024-11-21 13:42:59.850240: train_loss -0.77 +2024-11-21 13:42:59.850442: val_loss -0.7463 +2024-11-21 13:42:59.850515: Pseudo dice [0.8356] +2024-11-21 13:42:59.850592: Epoch time: 18.5 s +2024-11-21 13:43:00.646676: +2024-11-21 13:43:00.646933: Epoch 568 +2024-11-21 13:43:00.647048: Current learning rate: 0.00936 +2024-11-21 13:43:19.974736: train_loss -0.7707 +2024-11-21 13:43:19.974946: val_loss -0.7652 +2024-11-21 13:43:19.975028: Pseudo dice [0.8436] +2024-11-21 13:43:19.975100: Epoch time: 19.33 s +2024-11-21 13:43:21.065971: +2024-11-21 13:43:21.066202: Epoch 569 +2024-11-21 13:43:21.066311: Current learning rate: 0.00936 +2024-11-21 13:43:39.207174: train_loss -0.7593 +2024-11-21 13:43:39.207386: val_loss -0.7744 +2024-11-21 13:43:39.207460: Pseudo dice [0.8401] +2024-11-21 13:43:39.210038: Epoch time: 18.14 s +2024-11-21 13:43:40.090881: +2024-11-21 13:43:40.091087: Epoch 570 +2024-11-21 13:43:40.091203: Current learning rate: 0.00936 +2024-11-21 13:43:57.919956: train_loss -0.755 +2024-11-21 13:43:57.920208: val_loss -0.7432 +2024-11-21 13:43:57.920284: Pseudo dice [0.8318] +2024-11-21 13:43:57.920363: Epoch time: 17.83 s +2024-11-21 13:43:58.711961: +2024-11-21 13:43:58.712180: Epoch 571 +2024-11-21 13:43:58.712291: Current learning rate: 0.00936 +2024-11-21 13:44:16.557242: train_loss -0.7598 +2024-11-21 13:44:16.557460: val_loss -0.7939 +2024-11-21 13:44:16.557532: Pseudo dice [0.8579] +2024-11-21 13:44:16.557617: Epoch time: 17.85 s +2024-11-21 13:44:17.352339: +2024-11-21 13:44:17.352637: Epoch 572 +2024-11-21 13:44:17.352752: Current learning rate: 0.00935 +2024-11-21 13:44:36.671418: train_loss -0.7663 +2024-11-21 13:44:36.671633: val_loss -0.7195 +2024-11-21 13:44:36.671708: Pseudo dice [0.8266] +2024-11-21 13:44:36.671783: Epoch time: 19.32 s +2024-11-21 13:44:37.470276: +2024-11-21 13:44:37.470502: Epoch 573 +2024-11-21 13:44:37.470611: Current learning rate: 0.00935 +2024-11-21 13:44:55.220713: train_loss -0.7716 +2024-11-21 13:44:55.220942: val_loss -0.7838 +2024-11-21 13:44:55.221023: Pseudo dice [0.8462] +2024-11-21 13:44:55.221104: Epoch time: 17.75 s +2024-11-21 13:44:56.022514: +2024-11-21 13:44:56.022717: Epoch 574 +2024-11-21 13:44:56.022825: Current learning rate: 0.00935 +2024-11-21 13:45:14.178672: train_loss -0.7663 +2024-11-21 13:45:14.178903: val_loss -0.7555 +2024-11-21 13:45:14.178977: Pseudo dice [0.8438] +2024-11-21 13:45:14.179060: Epoch time: 18.16 s +2024-11-21 13:45:14.974765: +2024-11-21 13:45:14.974975: Epoch 575 +2024-11-21 13:45:14.975089: Current learning rate: 0.00935 +2024-11-21 13:45:34.311194: train_loss -0.7613 +2024-11-21 13:45:34.311404: val_loss -0.7435 +2024-11-21 13:45:34.311481: Pseudo dice [0.8353] +2024-11-21 13:45:34.311560: Epoch time: 19.34 s +2024-11-21 13:45:35.112498: +2024-11-21 13:45:35.112698: Epoch 576 +2024-11-21 13:45:35.112809: Current learning rate: 0.00935 +2024-11-21 13:45:54.496349: train_loss -0.7608 +2024-11-21 13:45:54.496616: val_loss -0.759 +2024-11-21 13:45:54.496696: Pseudo dice [0.8272] +2024-11-21 13:45:54.496773: Epoch time: 19.38 s +2024-11-21 13:45:55.298539: +2024-11-21 13:45:55.298733: Epoch 577 +2024-11-21 13:45:55.298842: Current learning rate: 0.00935 +2024-11-21 13:46:14.150832: train_loss -0.7669 +2024-11-21 13:46:14.151098: val_loss -0.7757 +2024-11-21 13:46:14.151177: Pseudo dice [0.8423] +2024-11-21 13:46:14.151287: Epoch time: 18.85 s +2024-11-21 13:46:14.956721: +2024-11-21 13:46:14.956921: Epoch 578 +2024-11-21 13:46:14.957037: Current learning rate: 0.00935 +2024-11-21 13:46:33.496217: train_loss -0.7653 +2024-11-21 13:46:33.496426: val_loss -0.7287 +2024-11-21 13:46:33.496498: Pseudo dice [0.8391] +2024-11-21 13:46:33.496571: Epoch time: 18.54 s +2024-11-21 13:46:34.300842: +2024-11-21 13:46:34.301064: Epoch 579 +2024-11-21 13:46:34.301171: Current learning rate: 0.00935 +2024-11-21 13:46:53.723208: train_loss -0.762 +2024-11-21 13:46:53.723428: val_loss -0.7544 +2024-11-21 13:46:53.723505: Pseudo dice [0.837] +2024-11-21 13:46:53.723579: Epoch time: 19.42 s +2024-11-21 13:46:54.547392: +2024-11-21 13:46:54.547643: Epoch 580 +2024-11-21 13:46:54.547755: Current learning rate: 0.00935 +2024-11-21 13:47:12.716251: train_loss -0.7575 +2024-11-21 13:47:12.716526: val_loss -0.7823 +2024-11-21 13:47:12.716604: Pseudo dice [0.8484] +2024-11-21 13:47:12.716686: Epoch time: 18.17 s +2024-11-21 13:47:13.547703: +2024-11-21 13:47:13.547937: Epoch 581 +2024-11-21 13:47:13.548054: Current learning rate: 0.00934 +2024-11-21 13:47:32.112571: train_loss -0.7479 +2024-11-21 13:47:32.112777: val_loss -0.7275 +2024-11-21 13:47:32.112855: Pseudo dice [0.7932] +2024-11-21 13:47:32.113202: Epoch time: 18.57 s +2024-11-21 13:47:32.910199: +2024-11-21 13:47:32.910407: Epoch 582 +2024-11-21 13:47:32.910516: Current learning rate: 0.00934 +2024-11-21 13:47:51.296570: train_loss -0.7472 +2024-11-21 13:47:51.296797: val_loss -0.758 +2024-11-21 13:47:51.296869: Pseudo dice [0.8452] +2024-11-21 13:47:51.296944: Epoch time: 18.39 s +2024-11-21 13:47:52.099190: +2024-11-21 13:47:52.099373: Epoch 583 +2024-11-21 13:47:52.099479: Current learning rate: 0.00934 +2024-11-21 13:48:10.870275: train_loss -0.7487 +2024-11-21 13:48:10.870486: val_loss -0.7772 +2024-11-21 13:48:10.870559: Pseudo dice [0.8382] +2024-11-21 13:48:10.870633: Epoch time: 18.77 s +2024-11-21 13:48:11.670345: +2024-11-21 13:48:11.670554: Epoch 584 +2024-11-21 13:48:11.670661: Current learning rate: 0.00934 +2024-11-21 13:48:30.274247: train_loss -0.7478 +2024-11-21 13:48:30.274478: val_loss -0.7591 +2024-11-21 13:48:30.281515: Pseudo dice [0.8436] +2024-11-21 13:48:30.281657: Epoch time: 18.6 s +2024-11-21 13:48:31.084814: +2024-11-21 13:48:31.085029: Epoch 585 +2024-11-21 13:48:31.085148: Current learning rate: 0.00934 +2024-11-21 13:48:48.972697: train_loss -0.7426 +2024-11-21 13:48:48.972898: val_loss -0.7545 +2024-11-21 13:48:48.972970: Pseudo dice [0.8349] +2024-11-21 13:48:48.973056: Epoch time: 17.89 s +2024-11-21 13:48:50.186516: +2024-11-21 13:48:50.186724: Epoch 586 +2024-11-21 13:48:50.186833: Current learning rate: 0.00934 +2024-11-21 13:49:08.297409: train_loss -0.7418 +2024-11-21 13:49:08.297951: val_loss -0.7436 +2024-11-21 13:49:08.298042: Pseudo dice [0.819] +2024-11-21 13:49:08.298120: Epoch time: 18.11 s +2024-11-21 13:49:09.094761: +2024-11-21 13:49:09.095013: Epoch 587 +2024-11-21 13:49:09.095132: Current learning rate: 0.00934 +2024-11-21 13:49:28.033715: train_loss -0.7516 +2024-11-21 13:49:28.033956: val_loss -0.751 +2024-11-21 13:49:28.034045: Pseudo dice [0.8157] +2024-11-21 13:49:28.034127: Epoch time: 18.94 s +2024-11-21 13:49:28.841151: +2024-11-21 13:49:28.841416: Epoch 588 +2024-11-21 13:49:28.841529: Current learning rate: 0.00934 +2024-11-21 13:49:47.973546: train_loss -0.7587 +2024-11-21 13:49:47.973754: val_loss -0.7582 +2024-11-21 13:49:47.973825: Pseudo dice [0.8311] +2024-11-21 13:49:47.973897: Epoch time: 19.13 s +2024-11-21 13:49:48.771895: +2024-11-21 13:49:48.772132: Epoch 589 +2024-11-21 13:49:48.772245: Current learning rate: 0.00933 +2024-11-21 13:50:08.610110: train_loss -0.7609 +2024-11-21 13:50:08.610374: val_loss -0.756 +2024-11-21 13:50:08.610452: Pseudo dice [0.8357] +2024-11-21 13:50:08.610526: Epoch time: 19.84 s +2024-11-21 13:50:09.509065: +2024-11-21 13:50:09.509295: Epoch 590 +2024-11-21 13:50:09.509408: Current learning rate: 0.00933 +2024-11-21 13:50:27.457313: train_loss -0.7457 +2024-11-21 13:50:27.457529: val_loss -0.7574 +2024-11-21 13:50:27.457634: Pseudo dice [0.8462] +2024-11-21 13:50:27.457770: Epoch time: 17.95 s +2024-11-21 13:50:28.272410: +2024-11-21 13:50:28.272637: Epoch 591 +2024-11-21 13:50:28.272743: Current learning rate: 0.00933 +2024-11-21 13:50:47.309529: train_loss -0.7423 +2024-11-21 13:50:47.309777: val_loss -0.7462 +2024-11-21 13:50:47.309862: Pseudo dice [0.861] +2024-11-21 13:50:47.309950: Epoch time: 19.04 s +2024-11-21 13:50:48.123225: +2024-11-21 13:50:48.123415: Epoch 592 +2024-11-21 13:50:48.123525: Current learning rate: 0.00933 +2024-11-21 13:51:07.510068: train_loss -0.7513 +2024-11-21 13:51:07.510270: val_loss -0.7393 +2024-11-21 13:51:07.510346: Pseudo dice [0.8397] +2024-11-21 13:51:07.510419: Epoch time: 19.39 s +2024-11-21 13:51:08.319804: +2024-11-21 13:51:08.320012: Epoch 593 +2024-11-21 13:51:08.320122: Current learning rate: 0.00933 +2024-11-21 13:51:27.116635: train_loss -0.7623 +2024-11-21 13:51:27.116840: val_loss -0.7614 +2024-11-21 13:51:27.116914: Pseudo dice [0.8273] +2024-11-21 13:51:27.116989: Epoch time: 18.8 s +2024-11-21 13:51:27.923185: +2024-11-21 13:51:27.923405: Epoch 594 +2024-11-21 13:51:27.923516: Current learning rate: 0.00933 +2024-11-21 13:51:46.919935: train_loss -0.7554 +2024-11-21 13:51:46.920206: val_loss -0.7735 +2024-11-21 13:51:46.920283: Pseudo dice [0.8454] +2024-11-21 13:51:46.920366: Epoch time: 19.0 s +2024-11-21 13:51:47.728138: +2024-11-21 13:51:47.728340: Epoch 595 +2024-11-21 13:51:47.728455: Current learning rate: 0.00933 +2024-11-21 13:52:06.204329: train_loss -0.7586 +2024-11-21 13:52:06.204528: val_loss -0.7802 +2024-11-21 13:52:06.204598: Pseudo dice [0.8365] +2024-11-21 13:52:06.204694: Epoch time: 18.48 s +2024-11-21 13:52:07.006902: +2024-11-21 13:52:07.007120: Epoch 596 +2024-11-21 13:52:07.007232: Current learning rate: 0.00933 +2024-11-21 13:52:25.923771: train_loss -0.7608 +2024-11-21 13:52:25.927608: val_loss -0.7678 +2024-11-21 13:52:25.927695: Pseudo dice [0.8425] +2024-11-21 13:52:25.927770: Epoch time: 18.92 s +2024-11-21 13:52:26.760431: +2024-11-21 13:52:26.760634: Epoch 597 +2024-11-21 13:52:26.760748: Current learning rate: 0.00933 +2024-11-21 13:52:44.456886: train_loss -0.7617 +2024-11-21 13:52:44.457473: val_loss -0.7456 +2024-11-21 13:52:44.457587: Pseudo dice [0.8302] +2024-11-21 13:52:44.457671: Epoch time: 17.7 s +2024-11-21 13:52:45.272779: +2024-11-21 13:52:45.272969: Epoch 598 +2024-11-21 13:52:45.273080: Current learning rate: 0.00932 +2024-11-21 13:53:04.116794: train_loss -0.7544 +2024-11-21 13:53:04.117027: val_loss -0.7425 +2024-11-21 13:53:04.117110: Pseudo dice [0.8278] +2024-11-21 13:53:04.117224: Epoch time: 18.84 s +2024-11-21 13:53:04.955698: +2024-11-21 13:53:04.955998: Epoch 599 +2024-11-21 13:53:04.956113: Current learning rate: 0.00932 +2024-11-21 13:53:23.931220: train_loss -0.755 +2024-11-21 13:53:23.931427: val_loss -0.7527 +2024-11-21 13:53:23.931499: Pseudo dice [0.8246] +2024-11-21 13:53:23.931571: Epoch time: 18.98 s +2024-11-21 13:53:24.957481: +2024-11-21 13:53:24.957693: Epoch 600 +2024-11-21 13:53:24.957801: Current learning rate: 0.00932 +2024-11-21 13:53:44.773661: train_loss -0.7498 +2024-11-21 13:53:44.773879: val_loss -0.7538 +2024-11-21 13:53:44.773955: Pseudo dice [0.834] +2024-11-21 13:53:44.774036: Epoch time: 19.82 s +2024-11-21 13:53:45.618637: +2024-11-21 13:53:45.618852: Epoch 601 +2024-11-21 13:53:45.618964: Current learning rate: 0.00932 +2024-11-21 13:54:02.992879: train_loss -0.7601 +2024-11-21 13:54:02.993178: val_loss -0.7689 +2024-11-21 13:54:02.993262: Pseudo dice [0.8514] +2024-11-21 13:54:02.993341: Epoch time: 17.38 s +2024-11-21 13:54:03.799546: +2024-11-21 13:54:03.799750: Epoch 602 +2024-11-21 13:54:03.799865: Current learning rate: 0.00932 +2024-11-21 13:54:21.542234: train_loss -0.7624 +2024-11-21 13:54:21.543270: val_loss -0.738 +2024-11-21 13:54:21.543346: Pseudo dice [0.8179] +2024-11-21 13:54:21.543420: Epoch time: 17.74 s +2024-11-21 13:54:22.340899: +2024-11-21 13:54:22.341113: Epoch 603 +2024-11-21 13:54:22.341228: Current learning rate: 0.00932 +2024-11-21 13:54:40.144858: train_loss -0.7652 +2024-11-21 13:54:40.145094: val_loss -0.7363 +2024-11-21 13:54:40.145171: Pseudo dice [0.827] +2024-11-21 13:54:40.145248: Epoch time: 17.8 s +2024-11-21 13:54:40.954721: +2024-11-21 13:54:40.954913: Epoch 604 +2024-11-21 13:54:40.955032: Current learning rate: 0.00932 +2024-11-21 13:54:58.354164: train_loss -0.7666 +2024-11-21 13:54:58.354378: val_loss -0.7521 +2024-11-21 13:54:58.354454: Pseudo dice [0.8432] +2024-11-21 13:54:58.354547: Epoch time: 17.4 s +2024-11-21 13:54:59.163077: +2024-11-21 13:54:59.163297: Epoch 605 +2024-11-21 13:54:59.163410: Current learning rate: 0.00932 +2024-11-21 13:55:17.320648: train_loss -0.7465 +2024-11-21 13:55:17.320873: val_loss -0.7672 +2024-11-21 13:55:17.320949: Pseudo dice [0.8389] +2024-11-21 13:55:17.321030: Epoch time: 18.16 s +2024-11-21 13:55:18.126078: +2024-11-21 13:55:18.126301: Epoch 606 +2024-11-21 13:55:18.126417: Current learning rate: 0.00932 +2024-11-21 13:55:37.221820: train_loss -0.7458 +2024-11-21 13:55:37.222046: val_loss -0.7402 +2024-11-21 13:55:37.222123: Pseudo dice [0.8408] +2024-11-21 13:55:37.222197: Epoch time: 19.1 s +2024-11-21 13:55:38.023139: +2024-11-21 13:55:38.023334: Epoch 607 +2024-11-21 13:55:38.023447: Current learning rate: 0.00931 +2024-11-21 13:55:58.127656: train_loss -0.7562 +2024-11-21 13:55:58.127869: val_loss -0.747 +2024-11-21 13:55:58.127945: Pseudo dice [0.8354] +2024-11-21 13:55:58.128434: Epoch time: 20.11 s +2024-11-21 13:55:58.939173: +2024-11-21 13:55:58.939410: Epoch 608 +2024-11-21 13:55:58.939526: Current learning rate: 0.00931 +2024-11-21 13:56:17.406311: train_loss -0.7559 +2024-11-21 13:56:17.406529: val_loss -0.7541 +2024-11-21 13:56:17.406602: Pseudo dice [0.8334] +2024-11-21 13:56:17.411844: Epoch time: 18.47 s +2024-11-21 13:56:18.351843: +2024-11-21 13:56:18.352054: Epoch 609 +2024-11-21 13:56:18.352163: Current learning rate: 0.00931 +2024-11-21 13:56:37.972439: train_loss -0.7467 +2024-11-21 13:56:37.972697: val_loss -0.7495 +2024-11-21 13:56:37.972774: Pseudo dice [0.8403] +2024-11-21 13:56:37.972849: Epoch time: 19.62 s +2024-11-21 13:56:38.775551: +2024-11-21 13:56:38.775770: Epoch 610 +2024-11-21 13:56:38.789137: Current learning rate: 0.00931 +2024-11-21 13:56:56.997071: train_loss -0.7609 +2024-11-21 13:56:56.998378: val_loss -0.7615 +2024-11-21 13:56:56.998468: Pseudo dice [0.8258] +2024-11-21 13:56:56.998545: Epoch time: 18.22 s +2024-11-21 13:56:57.808203: +2024-11-21 13:56:57.808426: Epoch 611 +2024-11-21 13:56:57.808538: Current learning rate: 0.00931 +2024-11-21 13:57:15.225376: train_loss -0.7685 +2024-11-21 13:57:15.225614: val_loss -0.7459 +2024-11-21 13:57:15.225688: Pseudo dice [0.8284] +2024-11-21 13:57:15.225764: Epoch time: 17.42 s +2024-11-21 13:57:16.033071: +2024-11-21 13:57:16.033282: Epoch 612 +2024-11-21 13:57:16.033390: Current learning rate: 0.00931 +2024-11-21 13:57:35.411742: train_loss -0.7582 +2024-11-21 13:57:35.411980: val_loss -0.7457 +2024-11-21 13:57:35.412063: Pseudo dice [0.8339] +2024-11-21 13:57:35.412141: Epoch time: 19.38 s +2024-11-21 13:57:36.219543: +2024-11-21 13:57:36.219823: Epoch 613 +2024-11-21 13:57:36.219934: Current learning rate: 0.00931 +2024-11-21 13:57:54.793865: train_loss -0.7469 +2024-11-21 13:57:54.794075: val_loss -0.739 +2024-11-21 13:57:54.794149: Pseudo dice [0.8394] +2024-11-21 13:57:54.794222: Epoch time: 18.58 s +2024-11-21 13:57:55.592171: +2024-11-21 13:57:55.592379: Epoch 614 +2024-11-21 13:57:55.592488: Current learning rate: 0.00931 +2024-11-21 13:58:13.212439: train_loss -0.7582 +2024-11-21 13:58:13.212643: val_loss -0.7626 +2024-11-21 13:58:13.212722: Pseudo dice [0.8346] +2024-11-21 13:58:13.212798: Epoch time: 17.62 s +2024-11-21 13:58:14.024621: +2024-11-21 13:58:14.024871: Epoch 615 +2024-11-21 13:58:14.024982: Current learning rate: 0.00931 +2024-11-21 13:58:32.378244: train_loss -0.7641 +2024-11-21 13:58:32.378461: val_loss -0.7479 +2024-11-21 13:58:32.378537: Pseudo dice [0.8221] +2024-11-21 13:58:32.378610: Epoch time: 18.35 s +2024-11-21 13:58:33.179322: +2024-11-21 13:58:33.179525: Epoch 616 +2024-11-21 13:58:33.179638: Current learning rate: 0.0093 +2024-11-21 13:58:51.003187: train_loss -0.7572 +2024-11-21 13:58:51.003397: val_loss -0.7586 +2024-11-21 13:58:51.003471: Pseudo dice [0.8381] +2024-11-21 13:58:51.003544: Epoch time: 17.82 s +2024-11-21 13:58:51.807405: +2024-11-21 13:58:51.807620: Epoch 617 +2024-11-21 13:58:51.807729: Current learning rate: 0.0093 +2024-11-21 13:59:10.283859: train_loss -0.7626 +2024-11-21 13:59:10.284081: val_loss -0.756 +2024-11-21 13:59:10.284155: Pseudo dice [0.8319] +2024-11-21 13:59:10.284227: Epoch time: 18.48 s +2024-11-21 13:59:11.139915: +2024-11-21 13:59:11.140131: Epoch 618 +2024-11-21 13:59:11.140252: Current learning rate: 0.0093 +2024-11-21 13:59:29.394903: train_loss -0.7554 +2024-11-21 13:59:29.395161: val_loss -0.7511 +2024-11-21 13:59:29.395245: Pseudo dice [0.8385] +2024-11-21 13:59:29.395328: Epoch time: 18.26 s +2024-11-21 13:59:30.272422: +2024-11-21 13:59:30.272619: Epoch 619 +2024-11-21 13:59:30.272727: Current learning rate: 0.0093 +2024-11-21 13:59:48.467845: train_loss -0.7616 +2024-11-21 13:59:48.468075: val_loss -0.7312 +2024-11-21 13:59:48.468148: Pseudo dice [0.833] +2024-11-21 13:59:48.468223: Epoch time: 18.2 s +2024-11-21 13:59:49.352482: +2024-11-21 13:59:49.352753: Epoch 620 +2024-11-21 13:59:49.352869: Current learning rate: 0.0093 +2024-11-21 14:00:07.195827: train_loss -0.7656 +2024-11-21 14:00:07.196068: val_loss -0.7749 +2024-11-21 14:00:07.196147: Pseudo dice [0.8399] +2024-11-21 14:00:07.196221: Epoch time: 17.84 s +2024-11-21 14:00:07.995272: +2024-11-21 14:00:07.995490: Epoch 621 +2024-11-21 14:00:07.995601: Current learning rate: 0.0093 +2024-11-21 14:00:26.638180: train_loss -0.7538 +2024-11-21 14:00:26.640584: val_loss -0.7655 +2024-11-21 14:00:26.640667: Pseudo dice [0.8312] +2024-11-21 14:00:26.640748: Epoch time: 18.64 s +2024-11-21 14:00:27.604560: +2024-11-21 14:00:27.604796: Epoch 622 +2024-11-21 14:00:27.604906: Current learning rate: 0.0093 +2024-11-21 14:00:45.705494: train_loss -0.7599 +2024-11-21 14:00:45.705694: val_loss -0.7632 +2024-11-21 14:00:45.706453: Pseudo dice [0.8372] +2024-11-21 14:00:45.708055: Epoch time: 18.1 s +2024-11-21 14:00:46.552905: +2024-11-21 14:00:46.553138: Epoch 623 +2024-11-21 14:00:46.553258: Current learning rate: 0.0093 +2024-11-21 14:01:04.769329: train_loss -0.7465 +2024-11-21 14:01:04.769551: val_loss -0.7552 +2024-11-21 14:01:04.769627: Pseudo dice [0.8377] +2024-11-21 14:01:04.769704: Epoch time: 18.22 s +2024-11-21 14:01:05.632422: +2024-11-21 14:01:05.632632: Epoch 624 +2024-11-21 14:01:05.632743: Current learning rate: 0.0093 +2024-11-21 14:01:23.193530: train_loss -0.7628 +2024-11-21 14:01:23.193746: val_loss -0.7747 +2024-11-21 14:01:23.193818: Pseudo dice [0.8423] +2024-11-21 14:01:23.193890: Epoch time: 17.56 s +2024-11-21 14:01:24.001314: +2024-11-21 14:01:24.001495: Epoch 625 +2024-11-21 14:01:24.001608: Current learning rate: 0.00929 +2024-11-21 14:01:42.774637: train_loss -0.7543 +2024-11-21 14:01:42.774887: val_loss -0.7749 +2024-11-21 14:01:42.774962: Pseudo dice [0.8445] +2024-11-21 14:01:42.775052: Epoch time: 18.77 s +2024-11-21 14:01:43.576452: +2024-11-21 14:01:43.576655: Epoch 626 +2024-11-21 14:01:43.576758: Current learning rate: 0.00929 +2024-11-21 14:02:01.600091: train_loss -0.7597 +2024-11-21 14:02:01.602887: val_loss -0.7395 +2024-11-21 14:02:01.602981: Pseudo dice [0.8361] +2024-11-21 14:02:01.603065: Epoch time: 18.02 s +2024-11-21 14:02:02.467157: +2024-11-21 14:02:02.467350: Epoch 627 +2024-11-21 14:02:02.467461: Current learning rate: 0.00929 +2024-11-21 14:02:21.632834: train_loss -0.7587 +2024-11-21 14:02:21.633079: val_loss -0.7551 +2024-11-21 14:02:21.633159: Pseudo dice [0.8462] +2024-11-21 14:02:21.633237: Epoch time: 19.17 s +2024-11-21 14:02:22.460250: +2024-11-21 14:02:22.460458: Epoch 628 +2024-11-21 14:02:22.460574: Current learning rate: 0.00929 +2024-11-21 14:02:40.684215: train_loss -0.7508 +2024-11-21 14:02:40.684434: val_loss -0.7526 +2024-11-21 14:02:40.684509: Pseudo dice [0.8184] +2024-11-21 14:02:40.684588: Epoch time: 18.22 s +2024-11-21 14:02:41.491195: +2024-11-21 14:02:41.491408: Epoch 629 +2024-11-21 14:02:41.491519: Current learning rate: 0.00929 +2024-11-21 14:02:59.687415: train_loss -0.7565 +2024-11-21 14:02:59.687717: val_loss -0.7293 +2024-11-21 14:02:59.687792: Pseudo dice [0.8264] +2024-11-21 14:02:59.687872: Epoch time: 18.2 s +2024-11-21 14:03:00.591424: +2024-11-21 14:03:00.591737: Epoch 630 +2024-11-21 14:03:00.591851: Current learning rate: 0.00929 +2024-11-21 14:03:18.856172: train_loss -0.7603 +2024-11-21 14:03:18.857171: val_loss -0.7735 +2024-11-21 14:03:18.857248: Pseudo dice [0.854] +2024-11-21 14:03:18.857321: Epoch time: 18.27 s +2024-11-21 14:03:20.021389: +2024-11-21 14:03:20.021594: Epoch 631 +2024-11-21 14:03:20.021700: Current learning rate: 0.00929 +2024-11-21 14:03:38.130314: train_loss -0.7681 +2024-11-21 14:03:38.135707: val_loss -0.7748 +2024-11-21 14:03:38.135808: Pseudo dice [0.834] +2024-11-21 14:03:38.135881: Epoch time: 18.11 s +2024-11-21 14:03:39.040710: +2024-11-21 14:03:39.040929: Epoch 632 +2024-11-21 14:03:39.041041: Current learning rate: 0.00929 +2024-11-21 14:03:56.430108: train_loss -0.7731 +2024-11-21 14:03:56.430353: val_loss -0.7773 +2024-11-21 14:03:56.430428: Pseudo dice [0.8457] +2024-11-21 14:03:56.430510: Epoch time: 17.39 s +2024-11-21 14:03:57.240294: +2024-11-21 14:03:57.240523: Epoch 633 +2024-11-21 14:03:57.240635: Current learning rate: 0.00928 +2024-11-21 14:04:14.909003: train_loss -0.745 +2024-11-21 14:04:14.909231: val_loss -0.7699 +2024-11-21 14:04:14.909305: Pseudo dice [0.8244] +2024-11-21 14:04:14.909706: Epoch time: 17.67 s +2024-11-21 14:04:15.711032: +2024-11-21 14:04:15.711238: Epoch 634 +2024-11-21 14:04:15.711348: Current learning rate: 0.00928 +2024-11-21 14:04:33.830814: train_loss -0.7563 +2024-11-21 14:04:33.831036: val_loss -0.7593 +2024-11-21 14:04:33.831114: Pseudo dice [0.8266] +2024-11-21 14:04:33.831192: Epoch time: 18.12 s +2024-11-21 14:04:34.629783: +2024-11-21 14:04:34.630001: Epoch 635 +2024-11-21 14:04:34.630109: Current learning rate: 0.00928 +2024-11-21 14:04:53.081658: train_loss -0.7573 +2024-11-21 14:04:53.081877: val_loss -0.7526 +2024-11-21 14:04:53.082207: Pseudo dice [0.843] +2024-11-21 14:04:53.082284: Epoch time: 18.45 s +2024-11-21 14:04:53.890289: +2024-11-21 14:04:53.890496: Epoch 636 +2024-11-21 14:04:53.890612: Current learning rate: 0.00928 +2024-11-21 14:05:12.343574: train_loss -0.7534 +2024-11-21 14:05:12.343811: val_loss -0.7739 +2024-11-21 14:05:12.343887: Pseudo dice [0.8365] +2024-11-21 14:05:12.343964: Epoch time: 18.45 s +2024-11-21 14:05:13.245868: +2024-11-21 14:05:13.246083: Epoch 637 +2024-11-21 14:05:13.246195: Current learning rate: 0.00928 +2024-11-21 14:05:31.282327: train_loss -0.7498 +2024-11-21 14:05:31.282545: val_loss -0.7215 +2024-11-21 14:05:31.282624: Pseudo dice [0.8165] +2024-11-21 14:05:31.282696: Epoch time: 18.04 s +2024-11-21 14:05:32.079505: +2024-11-21 14:05:32.079756: Epoch 638 +2024-11-21 14:05:32.079915: Current learning rate: 0.00928 +2024-11-21 14:05:50.742917: train_loss -0.7441 +2024-11-21 14:05:50.743190: val_loss -0.7329 +2024-11-21 14:05:50.743269: Pseudo dice [0.832] +2024-11-21 14:05:50.743350: Epoch time: 18.66 s +2024-11-21 14:05:51.546274: +2024-11-21 14:05:51.546549: Epoch 639 +2024-11-21 14:05:51.546658: Current learning rate: 0.00928 +2024-11-21 14:06:10.940567: train_loss -0.7581 +2024-11-21 14:06:10.940802: val_loss -0.7561 +2024-11-21 14:06:10.940879: Pseudo dice [0.8438] +2024-11-21 14:06:10.940958: Epoch time: 19.4 s +2024-11-21 14:06:11.746169: +2024-11-21 14:06:11.746416: Epoch 640 +2024-11-21 14:06:11.746531: Current learning rate: 0.00928 +2024-11-21 14:06:30.087580: train_loss -0.7483 +2024-11-21 14:06:30.087829: val_loss -0.7736 +2024-11-21 14:06:30.087908: Pseudo dice [0.8304] +2024-11-21 14:06:30.088000: Epoch time: 18.34 s +2024-11-21 14:06:30.891184: +2024-11-21 14:06:30.891383: Epoch 641 +2024-11-21 14:06:30.891488: Current learning rate: 0.00928 +2024-11-21 14:06:49.687664: train_loss -0.7569 +2024-11-21 14:06:49.687894: val_loss -0.732 +2024-11-21 14:06:49.687968: Pseudo dice [0.8206] +2024-11-21 14:06:49.688061: Epoch time: 18.8 s +2024-11-21 14:06:50.597322: +2024-11-21 14:06:50.597525: Epoch 642 +2024-11-21 14:06:50.597637: Current learning rate: 0.00927 +2024-11-21 14:07:09.595996: train_loss -0.7613 +2024-11-21 14:07:09.596217: val_loss -0.7556 +2024-11-21 14:07:09.596295: Pseudo dice [0.8357] +2024-11-21 14:07:09.596370: Epoch time: 19.0 s +2024-11-21 14:07:10.404366: +2024-11-21 14:07:10.404617: Epoch 643 +2024-11-21 14:07:10.404725: Current learning rate: 0.00927 +2024-11-21 14:07:29.068630: train_loss -0.7646 +2024-11-21 14:07:29.068864: val_loss -0.7582 +2024-11-21 14:07:29.068936: Pseudo dice [0.8454] +2024-11-21 14:07:29.069043: Epoch time: 18.67 s +2024-11-21 14:07:29.869858: +2024-11-21 14:07:29.870070: Epoch 644 +2024-11-21 14:07:29.870182: Current learning rate: 0.00927 +2024-11-21 14:07:48.427579: train_loss -0.7637 +2024-11-21 14:07:48.427806: val_loss -0.775 +2024-11-21 14:07:48.427879: Pseudo dice [0.8369] +2024-11-21 14:07:48.432514: Epoch time: 18.56 s +2024-11-21 14:07:49.245693: +2024-11-21 14:07:49.245901: Epoch 645 +2024-11-21 14:07:49.246016: Current learning rate: 0.00927 +2024-11-21 14:08:08.280131: train_loss -0.7588 +2024-11-21 14:08:08.280384: val_loss -0.7618 +2024-11-21 14:08:08.280482: Pseudo dice [0.8197] +2024-11-21 14:08:08.280570: Epoch time: 19.04 s +2024-11-21 14:08:09.089423: +2024-11-21 14:08:09.089623: Epoch 646 +2024-11-21 14:08:09.089734: Current learning rate: 0.00927 +2024-11-21 14:08:25.901244: train_loss -0.7571 +2024-11-21 14:08:25.901447: val_loss -0.7482 +2024-11-21 14:08:25.901518: Pseudo dice [0.8479] +2024-11-21 14:08:25.901589: Epoch time: 16.81 s +2024-11-21 14:08:26.705944: +2024-11-21 14:08:26.706161: Epoch 647 +2024-11-21 14:08:26.706270: Current learning rate: 0.00927 +2024-11-21 14:08:45.430627: train_loss -0.7612 +2024-11-21 14:08:45.430836: val_loss -0.7391 +2024-11-21 14:08:45.430912: Pseudo dice [0.8428] +2024-11-21 14:08:45.430985: Epoch time: 18.73 s +2024-11-21 14:08:46.228644: +2024-11-21 14:08:46.228856: Epoch 648 +2024-11-21 14:08:46.228962: Current learning rate: 0.00927 +2024-11-21 14:09:03.813747: train_loss -0.7624 +2024-11-21 14:09:03.821645: val_loss -0.744 +2024-11-21 14:09:03.821745: Pseudo dice [0.8338] +2024-11-21 14:09:03.821831: Epoch time: 17.59 s +2024-11-21 14:09:04.625432: +2024-11-21 14:09:04.625642: Epoch 649 +2024-11-21 14:09:04.625749: Current learning rate: 0.00927 +2024-11-21 14:09:23.162337: train_loss -0.7494 +2024-11-21 14:09:23.162570: val_loss -0.7675 +2024-11-21 14:09:23.162645: Pseudo dice [0.8387] +2024-11-21 14:09:23.162724: Epoch time: 18.54 s +2024-11-21 14:09:24.221790: +2024-11-21 14:09:24.221986: Epoch 650 +2024-11-21 14:09:24.222104: Current learning rate: 0.00927 +2024-11-21 14:09:43.010934: train_loss -0.738 +2024-11-21 14:09:43.011149: val_loss -0.7524 +2024-11-21 14:09:43.011222: Pseudo dice [0.8293] +2024-11-21 14:09:43.011296: Epoch time: 18.79 s +2024-11-21 14:09:43.997988: +2024-11-21 14:09:43.998279: Epoch 651 +2024-11-21 14:09:43.998395: Current learning rate: 0.00926 +2024-11-21 14:10:01.994996: train_loss -0.7458 +2024-11-21 14:10:01.995205: val_loss -0.7581 +2024-11-21 14:10:01.995279: Pseudo dice [0.8365] +2024-11-21 14:10:01.995350: Epoch time: 18.0 s +2024-11-21 14:10:02.797652: +2024-11-21 14:10:02.797861: Epoch 652 +2024-11-21 14:10:02.797973: Current learning rate: 0.00926 +2024-11-21 14:10:20.345394: train_loss -0.7589 +2024-11-21 14:10:20.345690: val_loss -0.7467 +2024-11-21 14:10:20.345769: Pseudo dice [0.842] +2024-11-21 14:10:20.345849: Epoch time: 17.55 s +2024-11-21 14:10:21.209553: +2024-11-21 14:10:21.209755: Epoch 653 +2024-11-21 14:10:21.209864: Current learning rate: 0.00926 +2024-11-21 14:10:40.131499: train_loss -0.7561 +2024-11-21 14:10:40.131719: val_loss -0.7431 +2024-11-21 14:10:40.131798: Pseudo dice [0.8152] +2024-11-21 14:10:40.131903: Epoch time: 18.92 s +2024-11-21 14:10:40.928007: +2024-11-21 14:10:40.928236: Epoch 654 +2024-11-21 14:10:40.928349: Current learning rate: 0.00926 +2024-11-21 14:10:59.303599: train_loss -0.7609 +2024-11-21 14:10:59.303811: val_loss -0.7481 +2024-11-21 14:10:59.303901: Pseudo dice [0.8322] +2024-11-21 14:10:59.303979: Epoch time: 18.38 s +2024-11-21 14:11:00.109126: +2024-11-21 14:11:00.109342: Epoch 655 +2024-11-21 14:11:00.109454: Current learning rate: 0.00926 +2024-11-21 14:11:18.648417: train_loss -0.7565 +2024-11-21 14:11:18.648667: val_loss -0.7561 +2024-11-21 14:11:18.648741: Pseudo dice [0.8359] +2024-11-21 14:11:18.648823: Epoch time: 18.54 s +2024-11-21 14:11:19.459785: +2024-11-21 14:11:19.460093: Epoch 656 +2024-11-21 14:11:19.460211: Current learning rate: 0.00926 +2024-11-21 14:11:38.192534: train_loss -0.7542 +2024-11-21 14:11:38.192784: val_loss -0.75 +2024-11-21 14:11:38.192862: Pseudo dice [0.8288] +2024-11-21 14:11:38.192938: Epoch time: 18.73 s +2024-11-21 14:11:39.000556: +2024-11-21 14:11:39.000756: Epoch 657 +2024-11-21 14:11:39.000861: Current learning rate: 0.00926 +2024-11-21 14:11:57.641663: train_loss -0.7554 +2024-11-21 14:11:57.641876: val_loss -0.7546 +2024-11-21 14:11:57.641950: Pseudo dice [0.8384] +2024-11-21 14:11:57.642032: Epoch time: 18.64 s +2024-11-21 14:11:58.471797: +2024-11-21 14:11:58.472009: Epoch 658 +2024-11-21 14:11:58.472117: Current learning rate: 0.00926 +2024-11-21 14:12:16.954752: train_loss -0.759 +2024-11-21 14:12:16.955006: val_loss -0.7444 +2024-11-21 14:12:16.955079: Pseudo dice [0.8327] +2024-11-21 14:12:16.955155: Epoch time: 18.48 s +2024-11-21 14:12:17.767143: +2024-11-21 14:12:17.767375: Epoch 659 +2024-11-21 14:12:17.767486: Current learning rate: 0.00926 +2024-11-21 14:12:35.755373: train_loss -0.7661 +2024-11-21 14:12:35.755604: val_loss -0.749 +2024-11-21 14:12:35.755682: Pseudo dice [0.8383] +2024-11-21 14:12:35.756009: Epoch time: 17.99 s +2024-11-21 14:12:36.561257: +2024-11-21 14:12:36.561467: Epoch 660 +2024-11-21 14:12:36.561576: Current learning rate: 0.00925 +2024-11-21 14:12:56.083383: train_loss -0.7556 +2024-11-21 14:12:56.083591: val_loss -0.7524 +2024-11-21 14:12:56.083678: Pseudo dice [0.8247] +2024-11-21 14:12:56.083755: Epoch time: 19.52 s +2024-11-21 14:12:56.890778: +2024-11-21 14:12:56.890982: Epoch 661 +2024-11-21 14:12:56.904786: Current learning rate: 0.00925 +2024-11-21 14:13:15.716924: train_loss -0.7628 +2024-11-21 14:13:15.717159: val_loss -0.7669 +2024-11-21 14:13:15.717233: Pseudo dice [0.8306] +2024-11-21 14:13:15.717308: Epoch time: 18.83 s +2024-11-21 14:13:16.531237: +2024-11-21 14:13:16.531443: Epoch 662 +2024-11-21 14:13:16.531549: Current learning rate: 0.00925 +2024-11-21 14:13:33.953525: train_loss -0.7652 +2024-11-21 14:13:33.953796: val_loss -0.738 +2024-11-21 14:13:33.953904: Pseudo dice [0.8321] +2024-11-21 14:13:33.954000: Epoch time: 17.42 s +2024-11-21 14:13:34.766074: +2024-11-21 14:13:34.766251: Epoch 663 +2024-11-21 14:13:34.766362: Current learning rate: 0.00925 +2024-11-21 14:13:53.037374: train_loss -0.7496 +2024-11-21 14:13:53.037581: val_loss -0.7658 +2024-11-21 14:13:53.037657: Pseudo dice [0.8437] +2024-11-21 14:13:53.037729: Epoch time: 18.27 s +2024-11-21 14:13:53.840799: +2024-11-21 14:13:53.840982: Epoch 664 +2024-11-21 14:13:53.841108: Current learning rate: 0.00925 +2024-11-21 14:14:12.734106: train_loss -0.7503 +2024-11-21 14:14:12.734322: val_loss -0.7646 +2024-11-21 14:14:12.734400: Pseudo dice [0.8478] +2024-11-21 14:14:12.734477: Epoch time: 18.89 s +2024-11-21 14:14:13.909698: +2024-11-21 14:14:13.909915: Epoch 665 +2024-11-21 14:14:13.910055: Current learning rate: 0.00925 +2024-11-21 14:14:32.029226: train_loss -0.7532 +2024-11-21 14:14:32.031667: val_loss -0.7672 +2024-11-21 14:14:32.031761: Pseudo dice [0.8491] +2024-11-21 14:14:32.031851: Epoch time: 18.12 s +2024-11-21 14:14:32.853722: +2024-11-21 14:14:32.853937: Epoch 666 +2024-11-21 14:14:32.854051: Current learning rate: 0.00925 +2024-11-21 14:14:50.803097: train_loss -0.759 +2024-11-21 14:14:50.804322: val_loss -0.7555 +2024-11-21 14:14:50.804417: Pseudo dice [0.8586] +2024-11-21 14:14:50.804492: Epoch time: 17.95 s +2024-11-21 14:14:51.606680: +2024-11-21 14:14:51.606934: Epoch 667 +2024-11-21 14:14:51.607050: Current learning rate: 0.00925 +2024-11-21 14:15:08.468477: train_loss -0.7597 +2024-11-21 14:15:08.468687: val_loss -0.7642 +2024-11-21 14:15:08.468760: Pseudo dice [0.8323] +2024-11-21 14:15:08.468835: Epoch time: 16.86 s +2024-11-21 14:15:09.279644: +2024-11-21 14:15:09.279862: Epoch 668 +2024-11-21 14:15:09.279971: Current learning rate: 0.00925 +2024-11-21 14:15:27.057471: train_loss -0.7574 +2024-11-21 14:15:27.057714: val_loss -0.7792 +2024-11-21 14:15:27.057815: Pseudo dice [0.8321] +2024-11-21 14:15:27.057917: Epoch time: 17.78 s +2024-11-21 14:15:27.868563: +2024-11-21 14:15:27.868755: Epoch 669 +2024-11-21 14:15:27.868861: Current learning rate: 0.00924 +2024-11-21 14:15:46.351670: train_loss -0.7614 +2024-11-21 14:15:46.351915: val_loss -0.7514 +2024-11-21 14:15:46.351988: Pseudo dice [0.8324] +2024-11-21 14:15:46.352073: Epoch time: 18.48 s +2024-11-21 14:15:47.162848: +2024-11-21 14:15:47.163055: Epoch 670 +2024-11-21 14:15:47.163165: Current learning rate: 0.00924 +2024-11-21 14:16:05.022014: train_loss -0.764 +2024-11-21 14:16:05.022225: val_loss -0.7648 +2024-11-21 14:16:05.022298: Pseudo dice [0.8386] +2024-11-21 14:16:05.022377: Epoch time: 17.86 s +2024-11-21 14:16:05.829343: +2024-11-21 14:16:05.829544: Epoch 671 +2024-11-21 14:16:05.829654: Current learning rate: 0.00924 +2024-11-21 14:16:24.566086: train_loss -0.7525 +2024-11-21 14:16:24.566377: val_loss -0.7597 +2024-11-21 14:16:24.566453: Pseudo dice [0.839] +2024-11-21 14:16:24.566525: Epoch time: 18.74 s +2024-11-21 14:16:25.471117: +2024-11-21 14:16:25.471299: Epoch 672 +2024-11-21 14:16:25.471407: Current learning rate: 0.00924 +2024-11-21 14:16:44.449638: train_loss -0.7498 +2024-11-21 14:16:44.449870: val_loss -0.7581 +2024-11-21 14:16:44.449944: Pseudo dice [0.8411] +2024-11-21 14:16:44.450030: Epoch time: 18.98 s +2024-11-21 14:16:45.260613: +2024-11-21 14:16:45.260825: Epoch 673 +2024-11-21 14:16:45.260935: Current learning rate: 0.00924 +2024-11-21 14:17:03.719281: train_loss -0.773 +2024-11-21 14:17:03.719498: val_loss -0.7548 +2024-11-21 14:17:03.719570: Pseudo dice [0.8494] +2024-11-21 14:17:03.719646: Epoch time: 18.46 s +2024-11-21 14:17:04.538679: +2024-11-21 14:17:04.538875: Epoch 674 +2024-11-21 14:17:04.538982: Current learning rate: 0.00924 +2024-11-21 14:17:22.277769: train_loss -0.7651 +2024-11-21 14:17:22.277980: val_loss -0.78 +2024-11-21 14:17:22.278061: Pseudo dice [0.8454] +2024-11-21 14:17:22.278135: Epoch time: 17.74 s +2024-11-21 14:17:23.085734: +2024-11-21 14:17:23.085926: Epoch 675 +2024-11-21 14:17:23.086038: Current learning rate: 0.00924 +2024-11-21 14:17:41.870867: train_loss -0.7683 +2024-11-21 14:17:41.871079: val_loss -0.716 +2024-11-21 14:17:41.871149: Pseudo dice [0.8202] +2024-11-21 14:17:41.871225: Epoch time: 18.79 s +2024-11-21 14:17:43.080232: +2024-11-21 14:17:43.080513: Epoch 676 +2024-11-21 14:17:43.080625: Current learning rate: 0.00924 +2024-11-21 14:18:02.197214: train_loss -0.7525 +2024-11-21 14:18:02.197451: val_loss -0.7458 +2024-11-21 14:18:02.197530: Pseudo dice [0.8347] +2024-11-21 14:18:02.197623: Epoch time: 19.12 s +2024-11-21 14:18:03.016793: +2024-11-21 14:18:03.017001: Epoch 677 +2024-11-21 14:18:03.017114: Current learning rate: 0.00924 +2024-11-21 14:18:21.357486: train_loss -0.7565 +2024-11-21 14:18:21.361008: val_loss -0.7695 +2024-11-21 14:18:21.361131: Pseudo dice [0.8359] +2024-11-21 14:18:21.361243: Epoch time: 18.34 s +2024-11-21 14:18:22.194322: +2024-11-21 14:18:22.194545: Epoch 678 +2024-11-21 14:18:22.194657: Current learning rate: 0.00923 +2024-11-21 14:18:40.252205: train_loss -0.7548 +2024-11-21 14:18:40.252421: val_loss -0.7256 +2024-11-21 14:18:40.252495: Pseudo dice [0.8149] +2024-11-21 14:18:40.252566: Epoch time: 18.06 s +2024-11-21 14:18:41.066304: +2024-11-21 14:18:41.066513: Epoch 679 +2024-11-21 14:18:41.066619: Current learning rate: 0.00923 +2024-11-21 14:18:58.835251: train_loss -0.7472 +2024-11-21 14:18:58.835472: val_loss -0.7601 +2024-11-21 14:18:58.835546: Pseudo dice [0.8216] +2024-11-21 14:18:58.835622: Epoch time: 17.77 s +2024-11-21 14:18:59.647219: +2024-11-21 14:18:59.647512: Epoch 680 +2024-11-21 14:18:59.647620: Current learning rate: 0.00923 +2024-11-21 14:19:17.714897: train_loss -0.7487 +2024-11-21 14:19:17.715139: val_loss -0.7287 +2024-11-21 14:19:17.715217: Pseudo dice [0.8171] +2024-11-21 14:19:17.715302: Epoch time: 18.07 s +2024-11-21 14:19:18.535096: +2024-11-21 14:19:18.535300: Epoch 681 +2024-11-21 14:19:18.535414: Current learning rate: 0.00923 +2024-11-21 14:19:36.801480: train_loss -0.7448 +2024-11-21 14:19:36.801735: val_loss -0.774 +2024-11-21 14:19:36.801833: Pseudo dice [0.8424] +2024-11-21 14:19:36.801909: Epoch time: 18.27 s +2024-11-21 14:19:37.633156: +2024-11-21 14:19:37.633359: Epoch 682 +2024-11-21 14:19:37.633473: Current learning rate: 0.00923 +2024-11-21 14:19:55.241755: train_loss -0.7602 +2024-11-21 14:19:55.241982: val_loss -0.762 +2024-11-21 14:19:55.242061: Pseudo dice [0.8274] +2024-11-21 14:19:55.242138: Epoch time: 17.61 s +2024-11-21 14:19:56.070156: +2024-11-21 14:19:56.070364: Epoch 683 +2024-11-21 14:19:56.070479: Current learning rate: 0.00923 +2024-11-21 14:20:14.691236: train_loss -0.755 +2024-11-21 14:20:14.691481: val_loss -0.7514 +2024-11-21 14:20:14.691558: Pseudo dice [0.8355] +2024-11-21 14:20:14.691645: Epoch time: 18.62 s +2024-11-21 14:20:15.515204: +2024-11-21 14:20:15.515412: Epoch 684 +2024-11-21 14:20:15.515522: Current learning rate: 0.00923 +2024-11-21 14:20:34.571843: train_loss -0.7467 +2024-11-21 14:20:34.572061: val_loss -0.7604 +2024-11-21 14:20:34.572133: Pseudo dice [0.8286] +2024-11-21 14:20:34.572205: Epoch time: 19.06 s +2024-11-21 14:20:35.389806: +2024-11-21 14:20:35.390001: Epoch 685 +2024-11-21 14:20:35.390191: Current learning rate: 0.00923 +2024-11-21 14:20:54.188388: train_loss -0.7513 +2024-11-21 14:20:54.190787: val_loss -0.7563 +2024-11-21 14:20:54.190877: Pseudo dice [0.834] +2024-11-21 14:20:54.191160: Epoch time: 18.8 s +2024-11-21 14:20:55.048831: +2024-11-21 14:20:55.049042: Epoch 686 +2024-11-21 14:20:55.049154: Current learning rate: 0.00922 +2024-11-21 14:21:14.399683: train_loss -0.7592 +2024-11-21 14:21:14.399924: val_loss -0.7542 +2024-11-21 14:21:14.406343: Pseudo dice [0.8339] +2024-11-21 14:21:14.406466: Epoch time: 19.35 s +2024-11-21 14:21:15.222522: +2024-11-21 14:21:15.222707: Epoch 687 +2024-11-21 14:21:15.222816: Current learning rate: 0.00922 +2024-11-21 14:21:34.459932: train_loss -0.7512 +2024-11-21 14:21:34.460160: val_loss -0.734 +2024-11-21 14:21:34.460234: Pseudo dice [0.8442] +2024-11-21 14:21:34.460311: Epoch time: 19.24 s +2024-11-21 14:21:35.269701: +2024-11-21 14:21:35.269932: Epoch 688 +2024-11-21 14:21:35.270053: Current learning rate: 0.00922 +2024-11-21 14:21:52.657358: train_loss -0.7522 +2024-11-21 14:21:52.657592: val_loss -0.7499 +2024-11-21 14:21:52.657683: Pseudo dice [0.856] +2024-11-21 14:21:52.657775: Epoch time: 17.39 s +2024-11-21 14:21:53.474849: +2024-11-21 14:21:53.475058: Epoch 689 +2024-11-21 14:21:53.475189: Current learning rate: 0.00922 +2024-11-21 14:22:12.458820: train_loss -0.7479 +2024-11-21 14:22:12.459030: val_loss -0.7349 +2024-11-21 14:22:12.459106: Pseudo dice [0.8272] +2024-11-21 14:22:12.459183: Epoch time: 18.98 s +2024-11-21 14:22:13.293458: +2024-11-21 14:22:13.293644: Epoch 690 +2024-11-21 14:22:13.293753: Current learning rate: 0.00922 +2024-11-21 14:22:31.529438: train_loss -0.7629 +2024-11-21 14:22:31.529737: val_loss -0.7688 +2024-11-21 14:22:31.529816: Pseudo dice [0.8453] +2024-11-21 14:22:31.529899: Epoch time: 18.24 s +2024-11-21 14:22:32.356895: +2024-11-21 14:22:32.357113: Epoch 691 +2024-11-21 14:22:32.357231: Current learning rate: 0.00922 +2024-11-21 14:22:50.067577: train_loss -0.763 +2024-11-21 14:22:50.067802: val_loss -0.7562 +2024-11-21 14:22:50.067876: Pseudo dice [0.838] +2024-11-21 14:22:50.067950: Epoch time: 17.71 s +2024-11-21 14:22:50.881827: +2024-11-21 14:22:50.882104: Epoch 692 +2024-11-21 14:22:50.882213: Current learning rate: 0.00922 +2024-11-21 14:23:09.810738: train_loss -0.7639 +2024-11-21 14:23:09.810946: val_loss -0.7613 +2024-11-21 14:23:09.811033: Pseudo dice [0.8525] +2024-11-21 14:23:09.811106: Epoch time: 18.93 s +2024-11-21 14:23:10.635463: +2024-11-21 14:23:10.635730: Epoch 693 +2024-11-21 14:23:10.635842: Current learning rate: 0.00922 +2024-11-21 14:23:29.362112: train_loss -0.762 +2024-11-21 14:23:29.362398: val_loss -0.7528 +2024-11-21 14:23:29.362479: Pseudo dice [0.8597] +2024-11-21 14:23:29.362564: Epoch time: 18.73 s +2024-11-21 14:23:30.225662: +2024-11-21 14:23:30.225848: Epoch 694 +2024-11-21 14:23:30.225955: Current learning rate: 0.00922 +2024-11-21 14:23:48.274969: train_loss -0.7643 +2024-11-21 14:23:48.275191: val_loss -0.7617 +2024-11-21 14:23:48.275264: Pseudo dice [0.842] +2024-11-21 14:23:48.275340: Epoch time: 18.05 s +2024-11-21 14:23:49.103004: +2024-11-21 14:23:49.103184: Epoch 695 +2024-11-21 14:23:49.103294: Current learning rate: 0.00921 +2024-11-21 14:24:06.539838: train_loss -0.7619 +2024-11-21 14:24:06.540114: val_loss -0.756 +2024-11-21 14:24:06.540193: Pseudo dice [0.8305] +2024-11-21 14:24:06.540293: Epoch time: 17.44 s +2024-11-21 14:24:07.356964: +2024-11-21 14:24:07.357165: Epoch 696 +2024-11-21 14:24:07.357277: Current learning rate: 0.00921 +2024-11-21 14:24:25.867839: train_loss -0.7494 +2024-11-21 14:24:25.868104: val_loss -0.7635 +2024-11-21 14:24:25.868187: Pseudo dice [0.8144] +2024-11-21 14:24:25.868269: Epoch time: 18.51 s +2024-11-21 14:24:26.697782: +2024-11-21 14:24:26.697977: Epoch 697 +2024-11-21 14:24:26.698091: Current learning rate: 0.00921 +2024-11-21 14:24:44.497510: train_loss -0.7671 +2024-11-21 14:24:44.497860: val_loss -0.7518 +2024-11-21 14:24:44.497936: Pseudo dice [0.8245] +2024-11-21 14:24:44.498022: Epoch time: 17.8 s +2024-11-21 14:24:45.357639: +2024-11-21 14:24:45.357848: Epoch 698 +2024-11-21 14:24:45.357958: Current learning rate: 0.00921 +2024-11-21 14:25:03.633789: train_loss -0.7716 +2024-11-21 14:25:03.634030: val_loss -0.7658 +2024-11-21 14:25:03.634106: Pseudo dice [0.8471] +2024-11-21 14:25:03.634187: Epoch time: 18.28 s +2024-11-21 14:25:04.489445: +2024-11-21 14:25:04.489656: Epoch 699 +2024-11-21 14:25:04.489765: Current learning rate: 0.00921 +2024-11-21 14:25:23.299377: train_loss -0.7624 +2024-11-21 14:25:23.299595: val_loss -0.7794 +2024-11-21 14:25:23.299668: Pseudo dice [0.8456] +2024-11-21 14:25:23.299743: Epoch time: 18.81 s +2024-11-21 14:25:24.340524: +2024-11-21 14:25:24.340734: Epoch 700 +2024-11-21 14:25:24.340842: Current learning rate: 0.00921 +2024-11-21 14:25:42.747269: train_loss -0.7611 +2024-11-21 14:25:42.747574: val_loss -0.7463 +2024-11-21 14:25:42.747686: Pseudo dice [0.8407] +2024-11-21 14:25:42.747769: Epoch time: 18.41 s +2024-11-21 14:25:43.566658: +2024-11-21 14:25:43.566879: Epoch 701 +2024-11-21 14:25:43.566988: Current learning rate: 0.00921 +2024-11-21 14:26:01.639625: train_loss -0.7642 +2024-11-21 14:26:01.641282: val_loss -0.7571 +2024-11-21 14:26:01.641394: Pseudo dice [0.8421] +2024-11-21 14:26:01.641468: Epoch time: 18.07 s +2024-11-21 14:26:02.471473: +2024-11-21 14:26:02.471750: Epoch 702 +2024-11-21 14:26:02.471859: Current learning rate: 0.00921 +2024-11-21 14:26:22.396571: train_loss -0.7639 +2024-11-21 14:26:22.396790: val_loss -0.7384 +2024-11-21 14:26:22.396864: Pseudo dice [0.8107] +2024-11-21 14:26:22.396937: Epoch time: 19.93 s +2024-11-21 14:26:23.210809: +2024-11-21 14:26:23.211009: Epoch 703 +2024-11-21 14:26:23.211119: Current learning rate: 0.00921 +2024-11-21 14:26:42.072052: train_loss -0.7568 +2024-11-21 14:26:42.072325: val_loss -0.7412 +2024-11-21 14:26:42.072416: Pseudo dice [0.8263] +2024-11-21 14:26:42.072496: Epoch time: 18.86 s +2024-11-21 14:26:42.893611: +2024-11-21 14:26:42.893829: Epoch 704 +2024-11-21 14:26:42.893942: Current learning rate: 0.0092 +2024-11-21 14:27:01.243866: train_loss -0.7598 +2024-11-21 14:27:01.244107: val_loss -0.7596 +2024-11-21 14:27:01.244180: Pseudo dice [0.8364] +2024-11-21 14:27:01.244258: Epoch time: 18.35 s +2024-11-21 14:27:02.056603: +2024-11-21 14:27:02.056879: Epoch 705 +2024-11-21 14:27:02.056998: Current learning rate: 0.0092 +2024-11-21 14:27:19.812004: train_loss -0.7473 +2024-11-21 14:27:19.812214: val_loss -0.7428 +2024-11-21 14:27:19.812286: Pseudo dice [0.8287] +2024-11-21 14:27:19.812360: Epoch time: 17.76 s +2024-11-21 14:27:20.889736: +2024-11-21 14:27:20.889937: Epoch 706 +2024-11-21 14:27:20.890052: Current learning rate: 0.0092 +2024-11-21 14:27:39.991942: train_loss -0.7378 +2024-11-21 14:27:39.992172: val_loss -0.7375 +2024-11-21 14:27:39.992252: Pseudo dice [0.8458] +2024-11-21 14:27:39.992326: Epoch time: 19.1 s +2024-11-21 14:27:40.803707: +2024-11-21 14:27:40.803909: Epoch 707 +2024-11-21 14:27:40.804019: Current learning rate: 0.0092 +2024-11-21 14:27:59.262265: train_loss -0.7596 +2024-11-21 14:27:59.262492: val_loss -0.7757 +2024-11-21 14:27:59.262569: Pseudo dice [0.8168] +2024-11-21 14:27:59.262652: Epoch time: 18.46 s +2024-11-21 14:28:00.081691: +2024-11-21 14:28:00.081900: Epoch 708 +2024-11-21 14:28:00.082011: Current learning rate: 0.0092 +2024-11-21 14:28:19.376261: train_loss -0.7543 +2024-11-21 14:28:19.378881: val_loss -0.7353 +2024-11-21 14:28:19.379034: Pseudo dice [0.8444] +2024-11-21 14:28:19.379120: Epoch time: 19.3 s +2024-11-21 14:28:20.576717: +2024-11-21 14:28:20.576941: Epoch 709 +2024-11-21 14:28:20.577056: Current learning rate: 0.0092 +2024-11-21 14:28:39.660322: train_loss -0.7661 +2024-11-21 14:28:39.662709: val_loss -0.7293 +2024-11-21 14:28:39.662803: Pseudo dice [0.8362] +2024-11-21 14:28:39.662878: Epoch time: 19.08 s +2024-11-21 14:28:40.600086: +2024-11-21 14:28:40.600292: Epoch 710 +2024-11-21 14:28:40.600401: Current learning rate: 0.0092 +2024-11-21 14:28:58.979823: train_loss -0.7704 +2024-11-21 14:28:58.980046: val_loss -0.7693 +2024-11-21 14:28:58.980119: Pseudo dice [0.8263] +2024-11-21 14:28:58.980261: Epoch time: 18.38 s +2024-11-21 14:28:59.795934: +2024-11-21 14:28:59.796258: Epoch 711 +2024-11-21 14:28:59.796372: Current learning rate: 0.0092 +2024-11-21 14:29:17.497699: train_loss -0.754 +2024-11-21 14:29:17.497911: val_loss -0.7441 +2024-11-21 14:29:17.497985: Pseudo dice [0.8274] +2024-11-21 14:29:17.498463: Epoch time: 17.7 s +2024-11-21 14:29:18.359593: +2024-11-21 14:29:18.359879: Epoch 712 +2024-11-21 14:29:18.360013: Current learning rate: 0.0092 +2024-11-21 14:29:36.769512: train_loss -0.766 +2024-11-21 14:29:36.769734: val_loss -0.7546 +2024-11-21 14:29:36.769808: Pseudo dice [0.8251] +2024-11-21 14:29:36.769883: Epoch time: 18.41 s +2024-11-21 14:29:37.610541: +2024-11-21 14:29:37.610741: Epoch 713 +2024-11-21 14:29:37.610850: Current learning rate: 0.00919 +2024-11-21 14:29:56.812450: train_loss -0.7538 +2024-11-21 14:29:56.814882: val_loss -0.7404 +2024-11-21 14:29:56.814999: Pseudo dice [0.8292] +2024-11-21 14:29:56.815076: Epoch time: 19.2 s +2024-11-21 14:29:57.677289: +2024-11-21 14:29:57.677494: Epoch 714 +2024-11-21 14:29:57.677602: Current learning rate: 0.00919 +2024-11-21 14:30:15.275041: train_loss -0.7604 +2024-11-21 14:30:15.275247: val_loss -0.7663 +2024-11-21 14:30:15.275326: Pseudo dice [0.8332] +2024-11-21 14:30:15.275398: Epoch time: 17.6 s +2024-11-21 14:30:16.087848: +2024-11-21 14:30:16.088065: Epoch 715 +2024-11-21 14:30:16.088178: Current learning rate: 0.00919 +2024-11-21 14:30:34.532369: train_loss -0.7688 +2024-11-21 14:30:34.532668: val_loss -0.7679 +2024-11-21 14:30:34.532745: Pseudo dice [0.8367] +2024-11-21 14:30:34.532824: Epoch time: 18.45 s +2024-11-21 14:30:35.347660: +2024-11-21 14:30:35.347867: Epoch 716 +2024-11-21 14:30:35.347973: Current learning rate: 0.00919 +2024-11-21 14:30:54.366716: train_loss -0.7606 +2024-11-21 14:30:54.366958: val_loss -0.7437 +2024-11-21 14:30:54.367033: Pseudo dice [0.8468] +2024-11-21 14:30:54.367109: Epoch time: 19.02 s +2024-11-21 14:30:55.186288: +2024-11-21 14:30:55.186480: Epoch 717 +2024-11-21 14:30:55.186586: Current learning rate: 0.00919 +2024-11-21 14:31:13.188480: train_loss -0.7533 +2024-11-21 14:31:13.188691: val_loss -0.7611 +2024-11-21 14:31:13.188768: Pseudo dice [0.8303] +2024-11-21 14:31:13.188839: Epoch time: 18.0 s +2024-11-21 14:31:13.996306: +2024-11-21 14:31:13.996485: Epoch 718 +2024-11-21 14:31:13.996594: Current learning rate: 0.00919 +2024-11-21 14:31:32.333588: train_loss -0.7616 +2024-11-21 14:31:32.333802: val_loss -0.737 +2024-11-21 14:31:32.333876: Pseudo dice [0.8315] +2024-11-21 14:31:32.333954: Epoch time: 18.34 s +2024-11-21 14:31:33.141538: +2024-11-21 14:31:33.141737: Epoch 719 +2024-11-21 14:31:33.141852: Current learning rate: 0.00919 +2024-11-21 14:31:51.583098: train_loss -0.746 +2024-11-21 14:31:51.583331: val_loss -0.7275 +2024-11-21 14:31:51.583407: Pseudo dice [0.8224] +2024-11-21 14:31:51.583484: Epoch time: 18.44 s +2024-11-21 14:31:52.888286: +2024-11-21 14:31:52.888506: Epoch 720 +2024-11-21 14:31:52.888616: Current learning rate: 0.00919 +2024-11-21 14:32:10.631752: train_loss -0.7429 +2024-11-21 14:32:10.631962: val_loss -0.7659 +2024-11-21 14:32:10.632047: Pseudo dice [0.833] +2024-11-21 14:32:10.632124: Epoch time: 17.74 s +2024-11-21 14:32:11.443840: +2024-11-21 14:32:11.444067: Epoch 721 +2024-11-21 14:32:11.444180: Current learning rate: 0.00919 +2024-11-21 14:32:29.649362: train_loss -0.7542 +2024-11-21 14:32:29.649584: val_loss -0.7599 +2024-11-21 14:32:29.649660: Pseudo dice [0.833] +2024-11-21 14:32:29.649735: Epoch time: 18.21 s +2024-11-21 14:32:30.636430: +2024-11-21 14:32:30.636674: Epoch 722 +2024-11-21 14:32:30.636786: Current learning rate: 0.00918 +2024-11-21 14:32:48.816454: train_loss -0.7439 +2024-11-21 14:32:48.816682: val_loss -0.7681 +2024-11-21 14:32:48.816754: Pseudo dice [0.8425] +2024-11-21 14:32:48.816830: Epoch time: 18.18 s +2024-11-21 14:32:49.671081: +2024-11-21 14:32:49.671299: Epoch 723 +2024-11-21 14:32:49.671405: Current learning rate: 0.00918 +2024-11-21 14:33:08.290085: train_loss -0.751 +2024-11-21 14:33:08.290330: val_loss -0.761 +2024-11-21 14:33:08.290407: Pseudo dice [0.8429] +2024-11-21 14:33:08.290533: Epoch time: 18.62 s +2024-11-21 14:33:09.104707: +2024-11-21 14:33:09.104953: Epoch 724 +2024-11-21 14:33:09.105073: Current learning rate: 0.00918 +2024-11-21 14:33:26.870136: train_loss -0.7536 +2024-11-21 14:33:26.870358: val_loss -0.7302 +2024-11-21 14:33:26.870430: Pseudo dice [0.8272] +2024-11-21 14:33:26.870504: Epoch time: 17.77 s +2024-11-21 14:33:27.829082: +2024-11-21 14:33:27.829283: Epoch 725 +2024-11-21 14:33:27.829401: Current learning rate: 0.00918 +2024-11-21 14:33:47.149376: train_loss -0.7335 +2024-11-21 14:33:47.149593: val_loss -0.7457 +2024-11-21 14:33:47.149669: Pseudo dice [0.8226] +2024-11-21 14:33:47.149748: Epoch time: 19.32 s +2024-11-21 14:33:47.957502: +2024-11-21 14:33:47.957751: Epoch 726 +2024-11-21 14:33:47.957864: Current learning rate: 0.00918 +2024-11-21 14:34:06.288732: train_loss -0.7483 +2024-11-21 14:34:06.288963: val_loss -0.7518 +2024-11-21 14:34:06.289050: Pseudo dice [0.8255] +2024-11-21 14:34:06.289128: Epoch time: 18.33 s +2024-11-21 14:34:07.097317: +2024-11-21 14:34:07.097599: Epoch 727 +2024-11-21 14:34:07.097716: Current learning rate: 0.00918 +2024-11-21 14:34:25.484962: train_loss -0.7494 +2024-11-21 14:34:25.485189: val_loss -0.7469 +2024-11-21 14:34:25.485261: Pseudo dice [0.8239] +2024-11-21 14:34:25.485333: Epoch time: 18.39 s +2024-11-21 14:34:26.352063: +2024-11-21 14:34:26.352277: Epoch 728 +2024-11-21 14:34:26.352388: Current learning rate: 0.00918 +2024-11-21 14:34:44.561841: train_loss -0.7558 +2024-11-21 14:34:44.562056: val_loss -0.7472 +2024-11-21 14:34:44.562131: Pseudo dice [0.8443] +2024-11-21 14:34:44.562208: Epoch time: 18.21 s +2024-11-21 14:34:45.369302: +2024-11-21 14:34:45.369496: Epoch 729 +2024-11-21 14:34:45.369607: Current learning rate: 0.00918 +2024-11-21 14:35:04.064481: train_loss -0.753 +2024-11-21 14:35:04.064741: val_loss -0.741 +2024-11-21 14:35:04.064822: Pseudo dice [0.8213] +2024-11-21 14:35:04.064930: Epoch time: 18.7 s +2024-11-21 14:35:04.922952: +2024-11-21 14:35:04.923214: Epoch 730 +2024-11-21 14:35:04.923322: Current learning rate: 0.00917 +2024-11-21 14:35:22.698128: train_loss -0.7578 +2024-11-21 14:35:22.698339: val_loss -0.7819 +2024-11-21 14:35:22.698411: Pseudo dice [0.8495] +2024-11-21 14:35:22.698483: Epoch time: 17.78 s +2024-11-21 14:35:23.506890: +2024-11-21 14:35:23.507094: Epoch 731 +2024-11-21 14:35:23.507212: Current learning rate: 0.00917 +2024-11-21 14:35:41.330211: train_loss -0.7589 +2024-11-21 14:35:41.330430: val_loss -0.7426 +2024-11-21 14:35:41.330505: Pseudo dice [0.829] +2024-11-21 14:35:41.330579: Epoch time: 17.82 s +2024-11-21 14:35:42.536256: +2024-11-21 14:35:42.536496: Epoch 732 +2024-11-21 14:35:42.536606: Current learning rate: 0.00917 +2024-11-21 14:36:00.834465: train_loss -0.7611 +2024-11-21 14:36:00.834746: val_loss -0.7529 +2024-11-21 14:36:00.834824: Pseudo dice [0.8151] +2024-11-21 14:36:00.834932: Epoch time: 18.3 s +2024-11-21 14:36:01.646117: +2024-11-21 14:36:01.646342: Epoch 733 +2024-11-21 14:36:01.646451: Current learning rate: 0.00917 +2024-11-21 14:36:19.356064: train_loss -0.7567 +2024-11-21 14:36:19.356272: val_loss -0.7613 +2024-11-21 14:36:19.356345: Pseudo dice [0.8303] +2024-11-21 14:36:19.356419: Epoch time: 17.71 s +2024-11-21 14:36:20.171455: +2024-11-21 14:36:20.171674: Epoch 734 +2024-11-21 14:36:20.171784: Current learning rate: 0.00917 +2024-11-21 14:36:39.160792: train_loss -0.7602 +2024-11-21 14:36:39.161008: val_loss -0.7726 +2024-11-21 14:36:39.161083: Pseudo dice [0.853] +2024-11-21 14:36:39.161155: Epoch time: 18.99 s +2024-11-21 14:36:39.973700: +2024-11-21 14:36:39.973911: Epoch 735 +2024-11-21 14:36:39.974024: Current learning rate: 0.00917 +2024-11-21 14:36:59.250023: train_loss -0.7633 +2024-11-21 14:36:59.250245: val_loss -0.7496 +2024-11-21 14:36:59.250322: Pseudo dice [0.8132] +2024-11-21 14:36:59.250400: Epoch time: 19.28 s +2024-11-21 14:37:00.066974: +2024-11-21 14:37:00.067196: Epoch 736 +2024-11-21 14:37:00.067308: Current learning rate: 0.00917 +2024-11-21 14:37:18.027754: train_loss -0.756 +2024-11-21 14:37:18.027988: val_loss -0.7482 +2024-11-21 14:37:18.028072: Pseudo dice [0.8147] +2024-11-21 14:37:18.028146: Epoch time: 17.96 s +2024-11-21 14:37:18.835706: +2024-11-21 14:37:18.835903: Epoch 737 +2024-11-21 14:37:18.836018: Current learning rate: 0.00917 +2024-11-21 14:37:37.307731: train_loss -0.7668 +2024-11-21 14:37:37.310727: val_loss -0.7442 +2024-11-21 14:37:37.328085: Pseudo dice [0.8083] +2024-11-21 14:37:37.328531: Epoch time: 18.47 s +2024-11-21 14:37:38.136215: +2024-11-21 14:37:38.136422: Epoch 738 +2024-11-21 14:37:38.136532: Current learning rate: 0.00917 +2024-11-21 14:37:56.011590: train_loss -0.7605 +2024-11-21 14:37:56.011804: val_loss -0.7604 +2024-11-21 14:37:56.011876: Pseudo dice [0.8309] +2024-11-21 14:37:56.011949: Epoch time: 17.88 s +2024-11-21 14:37:56.939387: +2024-11-21 14:37:56.939592: Epoch 739 +2024-11-21 14:37:56.939704: Current learning rate: 0.00916 +2024-11-21 14:38:15.217157: train_loss -0.7583 +2024-11-21 14:38:15.217366: val_loss -0.7732 +2024-11-21 14:38:15.217443: Pseudo dice [0.8361] +2024-11-21 14:38:15.217519: Epoch time: 18.28 s +2024-11-21 14:38:16.030841: +2024-11-21 14:38:16.031070: Epoch 740 +2024-11-21 14:38:16.031218: Current learning rate: 0.00916 +2024-11-21 14:38:35.534516: train_loss -0.7604 +2024-11-21 14:38:35.534730: val_loss -0.7535 +2024-11-21 14:38:35.534802: Pseudo dice [0.8449] +2024-11-21 14:38:35.534880: Epoch time: 19.5 s +2024-11-21 14:38:36.363794: +2024-11-21 14:38:36.364014: Epoch 741 +2024-11-21 14:38:36.364130: Current learning rate: 0.00916 +2024-11-21 14:38:55.395943: train_loss -0.7538 +2024-11-21 14:38:55.396164: val_loss -0.7665 +2024-11-21 14:38:55.396239: Pseudo dice [0.8426] +2024-11-21 14:38:55.396311: Epoch time: 19.03 s +2024-11-21 14:38:56.242435: +2024-11-21 14:38:56.242653: Epoch 742 +2024-11-21 14:38:56.242764: Current learning rate: 0.00916 +2024-11-21 14:39:14.381325: train_loss -0.7592 +2024-11-21 14:39:14.381529: val_loss -0.7514 +2024-11-21 14:39:14.381604: Pseudo dice [0.8389] +2024-11-21 14:39:14.381681: Epoch time: 18.14 s +2024-11-21 14:39:15.189353: +2024-11-21 14:39:15.189573: Epoch 743 +2024-11-21 14:39:15.189685: Current learning rate: 0.00916 +2024-11-21 14:39:33.456178: train_loss -0.7622 +2024-11-21 14:39:33.456425: val_loss -0.7646 +2024-11-21 14:39:33.456504: Pseudo dice [0.8415] +2024-11-21 14:39:33.456581: Epoch time: 18.27 s +2024-11-21 14:39:34.369400: +2024-11-21 14:39:34.369600: Epoch 744 +2024-11-21 14:39:34.369712: Current learning rate: 0.00916 +2024-11-21 14:39:52.900094: train_loss -0.7581 +2024-11-21 14:39:52.900329: val_loss -0.7632 +2024-11-21 14:39:52.900407: Pseudo dice [0.8383] +2024-11-21 14:39:52.900483: Epoch time: 18.53 s +2024-11-21 14:39:53.808178: +2024-11-21 14:39:53.808404: Epoch 745 +2024-11-21 14:39:53.808512: Current learning rate: 0.00916 +2024-11-21 14:40:13.649573: train_loss -0.7536 +2024-11-21 14:40:13.649797: val_loss -0.7164 +2024-11-21 14:40:13.649873: Pseudo dice [0.7987] +2024-11-21 14:40:13.649948: Epoch time: 19.84 s +2024-11-21 14:40:14.459918: +2024-11-21 14:40:14.460134: Epoch 746 +2024-11-21 14:40:14.460247: Current learning rate: 0.00916 +2024-11-21 14:40:32.911817: train_loss -0.7547 +2024-11-21 14:40:32.912070: val_loss -0.7673 +2024-11-21 14:40:32.912145: Pseudo dice [0.8225] +2024-11-21 14:40:32.912226: Epoch time: 18.45 s +2024-11-21 14:40:33.722759: +2024-11-21 14:40:33.723040: Epoch 747 +2024-11-21 14:40:33.723148: Current learning rate: 0.00916 +2024-11-21 14:40:51.371092: train_loss -0.7647 +2024-11-21 14:40:51.371296: val_loss -0.7583 +2024-11-21 14:40:51.371371: Pseudo dice [0.8335] +2024-11-21 14:40:51.371447: Epoch time: 17.65 s +2024-11-21 14:40:52.179598: +2024-11-21 14:40:52.179814: Epoch 748 +2024-11-21 14:40:52.179926: Current learning rate: 0.00915 +2024-11-21 14:41:11.424845: train_loss -0.7508 +2024-11-21 14:41:11.425069: val_loss -0.7411 +2024-11-21 14:41:11.425141: Pseudo dice [0.8581] +2024-11-21 14:41:11.425214: Epoch time: 19.25 s +2024-11-21 14:41:12.239772: +2024-11-21 14:41:12.239995: Epoch 749 +2024-11-21 14:41:12.240099: Current learning rate: 0.00915 +2024-11-21 14:41:30.977566: train_loss -0.7609 +2024-11-21 14:41:30.977873: val_loss -0.7582 +2024-11-21 14:41:30.977950: Pseudo dice [0.8472] +2024-11-21 14:41:30.978040: Epoch time: 18.74 s +2024-11-21 14:41:32.018257: +2024-11-21 14:41:32.018465: Epoch 750 +2024-11-21 14:41:32.018586: Current learning rate: 0.00915 +2024-11-21 14:41:51.179758: train_loss -0.7677 +2024-11-21 14:41:51.179989: val_loss -0.7502 +2024-11-21 14:41:51.180069: Pseudo dice [0.8344] +2024-11-21 14:41:51.180147: Epoch time: 19.16 s +2024-11-21 14:41:51.984982: +2024-11-21 14:41:51.985224: Epoch 751 +2024-11-21 14:41:51.985340: Current learning rate: 0.00915 +2024-11-21 14:42:10.836196: train_loss -0.7722 +2024-11-21 14:42:10.836398: val_loss -0.7463 +2024-11-21 14:42:10.836494: Pseudo dice [0.8377] +2024-11-21 14:42:10.836596: Epoch time: 18.85 s +2024-11-21 14:42:11.659347: +2024-11-21 14:42:11.659559: Epoch 752 +2024-11-21 14:42:11.659668: Current learning rate: 0.00915 +2024-11-21 14:42:30.248282: train_loss -0.7585 +2024-11-21 14:42:30.248507: val_loss -0.7647 +2024-11-21 14:42:30.248581: Pseudo dice [0.8248] +2024-11-21 14:42:30.248660: Epoch time: 18.59 s +2024-11-21 14:42:31.045759: +2024-11-21 14:42:31.045957: Epoch 753 +2024-11-21 14:42:31.046068: Current learning rate: 0.00915 +2024-11-21 14:42:50.211068: train_loss -0.7593 +2024-11-21 14:42:50.211296: val_loss -0.7523 +2024-11-21 14:42:50.211374: Pseudo dice [0.8378] +2024-11-21 14:42:50.211454: Epoch time: 19.17 s +2024-11-21 14:42:51.367866: +2024-11-21 14:42:51.368141: Epoch 754 +2024-11-21 14:42:51.368291: Current learning rate: 0.00915 +2024-11-21 14:43:10.811656: train_loss -0.7744 +2024-11-21 14:43:10.811873: val_loss -0.7637 +2024-11-21 14:43:10.811946: Pseudo dice [0.8407] +2024-11-21 14:43:10.812029: Epoch time: 19.44 s +2024-11-21 14:43:11.614930: +2024-11-21 14:43:11.615160: Epoch 755 +2024-11-21 14:43:11.615273: Current learning rate: 0.00915 +2024-11-21 14:43:30.950546: train_loss -0.7539 +2024-11-21 14:43:30.950751: val_loss -0.7625 +2024-11-21 14:43:30.950821: Pseudo dice [0.8444] +2024-11-21 14:43:30.950959: Epoch time: 19.34 s +2024-11-21 14:43:31.758401: +2024-11-21 14:43:31.758636: Epoch 756 +2024-11-21 14:43:31.758750: Current learning rate: 0.00915 +2024-11-21 14:43:49.855731: train_loss -0.7547 +2024-11-21 14:43:49.858033: val_loss -0.7711 +2024-11-21 14:43:49.858235: Pseudo dice [0.8454] +2024-11-21 14:43:49.858322: Epoch time: 18.1 s +2024-11-21 14:43:50.682166: +2024-11-21 14:43:50.682374: Epoch 757 +2024-11-21 14:43:50.682479: Current learning rate: 0.00914 +2024-11-21 14:44:08.013896: train_loss -0.7575 +2024-11-21 14:44:08.014172: val_loss -0.7554 +2024-11-21 14:44:08.014247: Pseudo dice [0.8299] +2024-11-21 14:44:08.014331: Epoch time: 17.33 s +2024-11-21 14:44:08.859588: +2024-11-21 14:44:08.859867: Epoch 758 +2024-11-21 14:44:08.859985: Current learning rate: 0.00914 +2024-11-21 14:44:28.043540: train_loss -0.7491 +2024-11-21 14:44:28.043754: val_loss -0.7521 +2024-11-21 14:44:28.043831: Pseudo dice [0.8185] +2024-11-21 14:44:28.043907: Epoch time: 19.18 s +2024-11-21 14:44:28.863983: +2024-11-21 14:44:28.864192: Epoch 759 +2024-11-21 14:44:28.864307: Current learning rate: 0.00914 +2024-11-21 14:44:46.424642: train_loss -0.7601 +2024-11-21 14:44:46.424870: val_loss -0.782 +2024-11-21 14:44:46.424943: Pseudo dice [0.8446] +2024-11-21 14:44:46.425020: Epoch time: 17.56 s +2024-11-21 14:44:47.356252: +2024-11-21 14:44:47.356467: Epoch 760 +2024-11-21 14:44:47.356580: Current learning rate: 0.00914 +2024-11-21 14:45:05.681444: train_loss -0.7664 +2024-11-21 14:45:05.681694: val_loss -0.7434 +2024-11-21 14:45:05.681767: Pseudo dice [0.843] +2024-11-21 14:45:05.681849: Epoch time: 18.33 s +2024-11-21 14:45:06.508453: +2024-11-21 14:45:06.508677: Epoch 761 +2024-11-21 14:45:06.508790: Current learning rate: 0.00914 +2024-11-21 14:45:25.119698: train_loss -0.7569 +2024-11-21 14:45:25.119934: val_loss -0.7323 +2024-11-21 14:45:25.120017: Pseudo dice [0.8277] +2024-11-21 14:45:25.120095: Epoch time: 18.61 s +2024-11-21 14:45:25.965659: +2024-11-21 14:45:25.965859: Epoch 762 +2024-11-21 14:45:25.965967: Current learning rate: 0.00914 +2024-11-21 14:45:44.112163: train_loss -0.765 +2024-11-21 14:45:44.112378: val_loss -0.7568 +2024-11-21 14:45:44.112451: Pseudo dice [0.8439] +2024-11-21 14:45:44.112523: Epoch time: 18.15 s +2024-11-21 14:45:44.941201: +2024-11-21 14:45:44.941449: Epoch 763 +2024-11-21 14:45:44.953718: Current learning rate: 0.00914 +2024-11-21 14:46:03.486489: train_loss -0.7705 +2024-11-21 14:46:03.486738: val_loss -0.7553 +2024-11-21 14:46:03.486810: Pseudo dice [0.8387] +2024-11-21 14:46:03.487086: Epoch time: 18.55 s +2024-11-21 14:46:04.307693: +2024-11-21 14:46:04.307897: Epoch 764 +2024-11-21 14:46:04.308017: Current learning rate: 0.00914 +2024-11-21 14:46:23.378551: train_loss -0.7527 +2024-11-21 14:46:23.378803: val_loss -0.763 +2024-11-21 14:46:23.378882: Pseudo dice [0.8377] +2024-11-21 14:46:23.378964: Epoch time: 19.07 s +2024-11-21 14:46:24.200267: +2024-11-21 14:46:24.200473: Epoch 765 +2024-11-21 14:46:24.200583: Current learning rate: 0.00914 +2024-11-21 14:46:42.982014: train_loss -0.7566 +2024-11-21 14:46:42.982213: val_loss -0.7645 +2024-11-21 14:46:42.982285: Pseudo dice [0.8425] +2024-11-21 14:46:42.982381: Epoch time: 18.78 s +2024-11-21 14:46:44.160522: +2024-11-21 14:46:44.160750: Epoch 766 +2024-11-21 14:46:44.160864: Current learning rate: 0.00913 +2024-11-21 14:47:02.836188: train_loss -0.7613 +2024-11-21 14:47:02.836415: val_loss -0.746 +2024-11-21 14:47:02.836488: Pseudo dice [0.8389] +2024-11-21 14:47:02.836562: Epoch time: 18.68 s +2024-11-21 14:47:03.661337: +2024-11-21 14:47:03.661571: Epoch 767 +2024-11-21 14:47:03.661723: Current learning rate: 0.00913 +2024-11-21 14:47:21.566327: train_loss -0.7669 +2024-11-21 14:47:21.566592: val_loss -0.7422 +2024-11-21 14:47:21.566704: Pseudo dice [0.8352] +2024-11-21 14:47:21.566791: Epoch time: 17.91 s +2024-11-21 14:47:22.384559: +2024-11-21 14:47:22.384815: Epoch 768 +2024-11-21 14:47:22.384927: Current learning rate: 0.00913 +2024-11-21 14:47:39.934802: train_loss -0.7581 +2024-11-21 14:47:39.935021: val_loss -0.765 +2024-11-21 14:47:39.935095: Pseudo dice [0.8367] +2024-11-21 14:47:39.935170: Epoch time: 17.55 s +2024-11-21 14:47:40.751119: +2024-11-21 14:47:40.751312: Epoch 769 +2024-11-21 14:47:40.751419: Current learning rate: 0.00913 +2024-11-21 14:47:57.672363: train_loss -0.7657 +2024-11-21 14:47:57.672591: val_loss -0.7257 +2024-11-21 14:47:57.672670: Pseudo dice [0.8391] +2024-11-21 14:47:57.672746: Epoch time: 16.92 s +2024-11-21 14:47:58.484828: +2024-11-21 14:47:58.485052: Epoch 770 +2024-11-21 14:47:58.485162: Current learning rate: 0.00913 +2024-11-21 14:48:16.502520: train_loss -0.7617 +2024-11-21 14:48:16.502732: val_loss -0.7972 +2024-11-21 14:48:16.502809: Pseudo dice [0.8563] +2024-11-21 14:48:16.502885: Epoch time: 18.02 s +2024-11-21 14:48:17.320734: +2024-11-21 14:48:17.320966: Epoch 771 +2024-11-21 14:48:17.321091: Current learning rate: 0.00913 +2024-11-21 14:48:35.340246: train_loss -0.7659 +2024-11-21 14:48:35.340471: val_loss -0.7553 +2024-11-21 14:48:35.340549: Pseudo dice [0.8345] +2024-11-21 14:48:35.340627: Epoch time: 18.02 s +2024-11-21 14:48:36.161506: +2024-11-21 14:48:36.161736: Epoch 772 +2024-11-21 14:48:36.161846: Current learning rate: 0.00913 +2024-11-21 14:48:54.243306: train_loss -0.7675 +2024-11-21 14:48:54.243516: val_loss -0.7544 +2024-11-21 14:48:54.243588: Pseudo dice [0.8364] +2024-11-21 14:48:54.243691: Epoch time: 18.08 s +2024-11-21 14:48:55.059247: +2024-11-21 14:48:55.059439: Epoch 773 +2024-11-21 14:48:55.059544: Current learning rate: 0.00913 +2024-11-21 14:49:14.041805: train_loss -0.7498 +2024-11-21 14:49:14.042031: val_loss -0.7423 +2024-11-21 14:49:14.042106: Pseudo dice [0.8343] +2024-11-21 14:49:14.042182: Epoch time: 18.98 s +2024-11-21 14:49:14.855232: +2024-11-21 14:49:14.855413: Epoch 774 +2024-11-21 14:49:14.855519: Current learning rate: 0.00912 +2024-11-21 14:49:32.644176: train_loss -0.7559 +2024-11-21 14:49:32.644387: val_loss -0.7727 +2024-11-21 14:49:32.644464: Pseudo dice [0.8417] +2024-11-21 14:49:32.644541: Epoch time: 17.79 s +2024-11-21 14:49:33.458455: +2024-11-21 14:49:33.458704: Epoch 775 +2024-11-21 14:49:33.458815: Current learning rate: 0.00912 +2024-11-21 14:49:52.468564: train_loss -0.755 +2024-11-21 14:49:52.468783: val_loss -0.7235 +2024-11-21 14:49:52.468858: Pseudo dice [0.8164] +2024-11-21 14:49:52.490790: Epoch time: 19.01 s +2024-11-21 14:49:53.303613: +2024-11-21 14:49:53.303904: Epoch 776 +2024-11-21 14:49:53.304020: Current learning rate: 0.00912 +2024-11-21 14:50:12.767501: train_loss -0.7354 +2024-11-21 14:50:12.767711: val_loss -0.7328 +2024-11-21 14:50:12.767791: Pseudo dice [0.8387] +2024-11-21 14:50:12.767866: Epoch time: 19.46 s +2024-11-21 14:50:13.875019: +2024-11-21 14:50:13.875283: Epoch 777 +2024-11-21 14:50:13.875396: Current learning rate: 0.00912 +2024-11-21 14:50:33.343289: train_loss -0.7527 +2024-11-21 14:50:33.343513: val_loss -0.7822 +2024-11-21 14:50:33.343587: Pseudo dice [0.8437] +2024-11-21 14:50:33.343663: Epoch time: 19.47 s +2024-11-21 14:50:34.155680: +2024-11-21 14:50:34.155912: Epoch 778 +2024-11-21 14:50:34.156030: Current learning rate: 0.00912 +2024-11-21 14:50:51.964582: train_loss -0.7644 +2024-11-21 14:50:51.964841: val_loss -0.7453 +2024-11-21 14:50:51.964924: Pseudo dice [0.8329] +2024-11-21 14:50:51.965021: Epoch time: 17.81 s +2024-11-21 14:50:52.787339: +2024-11-21 14:50:52.787568: Epoch 779 +2024-11-21 14:50:52.787681: Current learning rate: 0.00912 +2024-11-21 14:51:12.436285: train_loss -0.7375 +2024-11-21 14:51:12.436501: val_loss -0.7497 +2024-11-21 14:51:12.436573: Pseudo dice [0.8158] +2024-11-21 14:51:12.436648: Epoch time: 19.65 s +2024-11-21 14:51:13.251026: +2024-11-21 14:51:13.251244: Epoch 780 +2024-11-21 14:51:13.251353: Current learning rate: 0.00912 +2024-11-21 14:51:31.966859: train_loss -0.7347 +2024-11-21 14:51:31.967078: val_loss -0.7614 +2024-11-21 14:51:31.967153: Pseudo dice [0.8291] +2024-11-21 14:51:31.967227: Epoch time: 18.72 s +2024-11-21 14:51:32.834614: +2024-11-21 14:51:32.834817: Epoch 781 +2024-11-21 14:51:32.834948: Current learning rate: 0.00912 +2024-11-21 14:51:51.443511: train_loss -0.7513 +2024-11-21 14:51:51.443725: val_loss -0.7579 +2024-11-21 14:51:51.443801: Pseudo dice [0.8225] +2024-11-21 14:51:51.443878: Epoch time: 18.61 s +2024-11-21 14:51:52.263870: +2024-11-21 14:51:52.264096: Epoch 782 +2024-11-21 14:51:52.264206: Current learning rate: 0.00912 +2024-11-21 14:52:10.728116: train_loss -0.7542 +2024-11-21 14:52:10.728352: val_loss -0.7475 +2024-11-21 14:52:10.728431: Pseudo dice [0.8333] +2024-11-21 14:52:10.728514: Epoch time: 18.47 s +2024-11-21 14:52:11.582095: +2024-11-21 14:52:11.582303: Epoch 783 +2024-11-21 14:52:11.582410: Current learning rate: 0.00911 +2024-11-21 14:52:29.832481: train_loss -0.7591 +2024-11-21 14:52:29.832685: val_loss -0.7736 +2024-11-21 14:52:29.832762: Pseudo dice [0.8478] +2024-11-21 14:52:29.832834: Epoch time: 18.25 s +2024-11-21 14:52:30.665061: +2024-11-21 14:52:30.665267: Epoch 784 +2024-11-21 14:52:30.665376: Current learning rate: 0.00911 +2024-11-21 14:52:49.208319: train_loss -0.7602 +2024-11-21 14:52:49.208528: val_loss -0.7749 +2024-11-21 14:52:49.208619: Pseudo dice [0.836] +2024-11-21 14:52:49.208696: Epoch time: 18.54 s +2024-11-21 14:52:50.029591: +2024-11-21 14:52:50.029799: Epoch 785 +2024-11-21 14:52:50.029907: Current learning rate: 0.00911 +2024-11-21 14:53:08.652217: train_loss -0.7669 +2024-11-21 14:53:08.652433: val_loss -0.7688 +2024-11-21 14:53:08.652509: Pseudo dice [0.8438] +2024-11-21 14:53:08.652587: Epoch time: 18.62 s +2024-11-21 14:53:09.478810: +2024-11-21 14:53:09.479015: Epoch 786 +2024-11-21 14:53:09.479126: Current learning rate: 0.00911 +2024-11-21 14:53:28.476402: train_loss -0.7713 +2024-11-21 14:53:28.476642: val_loss -0.7562 +2024-11-21 14:53:28.476714: Pseudo dice [0.8352] +2024-11-21 14:53:28.476792: Epoch time: 19.0 s +2024-11-21 14:53:29.307254: +2024-11-21 14:53:29.307446: Epoch 787 +2024-11-21 14:53:29.307568: Current learning rate: 0.00911 +2024-11-21 14:53:48.321265: train_loss -0.7638 +2024-11-21 14:53:48.321491: val_loss -0.7634 +2024-11-21 14:53:48.321564: Pseudo dice [0.8302] +2024-11-21 14:53:48.321639: Epoch time: 19.01 s +2024-11-21 14:53:49.510365: +2024-11-21 14:53:49.510556: Epoch 788 +2024-11-21 14:53:49.510663: Current learning rate: 0.00911 +2024-11-21 14:54:08.426172: train_loss -0.7648 +2024-11-21 14:54:08.426397: val_loss -0.7581 +2024-11-21 14:54:08.443682: Pseudo dice [0.835] +2024-11-21 14:54:08.443844: Epoch time: 18.92 s +2024-11-21 14:54:09.365266: +2024-11-21 14:54:09.365474: Epoch 789 +2024-11-21 14:54:09.365582: Current learning rate: 0.00911 +2024-11-21 14:54:27.922385: train_loss -0.757 +2024-11-21 14:54:27.922630: val_loss -0.7769 +2024-11-21 14:54:27.922711: Pseudo dice [0.8442] +2024-11-21 14:54:27.923075: Epoch time: 18.56 s +2024-11-21 14:54:28.737303: +2024-11-21 14:54:28.737520: Epoch 790 +2024-11-21 14:54:28.737648: Current learning rate: 0.00911 +2024-11-21 14:54:46.823050: train_loss -0.7505 +2024-11-21 14:54:46.823326: val_loss -0.7569 +2024-11-21 14:54:46.823401: Pseudo dice [0.8382] +2024-11-21 14:54:46.823476: Epoch time: 18.09 s +2024-11-21 14:54:47.653841: +2024-11-21 14:54:47.654030: Epoch 791 +2024-11-21 14:54:47.654135: Current learning rate: 0.00911 +2024-11-21 14:55:06.679904: train_loss -0.763 +2024-11-21 14:55:06.680137: val_loss -0.7308 +2024-11-21 14:55:06.680213: Pseudo dice [0.8237] +2024-11-21 14:55:06.680285: Epoch time: 19.03 s +2024-11-21 14:55:07.498667: +2024-11-21 14:55:07.498889: Epoch 792 +2024-11-21 14:55:07.499008: Current learning rate: 0.0091 +2024-11-21 14:55:25.673202: train_loss -0.7649 +2024-11-21 14:55:25.673447: val_loss -0.7278 +2024-11-21 14:55:25.673523: Pseudo dice [0.8425] +2024-11-21 14:55:25.673602: Epoch time: 18.18 s +2024-11-21 14:55:26.497013: +2024-11-21 14:55:26.497218: Epoch 793 +2024-11-21 14:55:26.497327: Current learning rate: 0.0091 +2024-11-21 14:55:44.519576: train_loss -0.7756 +2024-11-21 14:55:44.519803: val_loss -0.7598 +2024-11-21 14:55:44.519877: Pseudo dice [0.8433] +2024-11-21 14:55:44.519950: Epoch time: 18.02 s +2024-11-21 14:55:45.333568: +2024-11-21 14:55:45.333852: Epoch 794 +2024-11-21 14:55:45.333966: Current learning rate: 0.0091 +2024-11-21 14:56:04.358585: train_loss -0.7552 +2024-11-21 14:56:04.358805: val_loss -0.7653 +2024-11-21 14:56:04.358880: Pseudo dice [0.8416] +2024-11-21 14:56:04.358956: Epoch time: 19.03 s +2024-11-21 14:56:05.173913: +2024-11-21 14:56:05.174123: Epoch 795 +2024-11-21 14:56:05.174234: Current learning rate: 0.0091 +2024-11-21 14:56:24.475105: train_loss -0.7553 +2024-11-21 14:56:24.475315: val_loss -0.7359 +2024-11-21 14:56:24.475399: Pseudo dice [0.8323] +2024-11-21 14:56:24.475476: Epoch time: 19.3 s +2024-11-21 14:56:25.297173: +2024-11-21 14:56:25.297365: Epoch 796 +2024-11-21 14:56:25.297472: Current learning rate: 0.0091 +2024-11-21 14:56:44.400158: train_loss -0.7431 +2024-11-21 14:56:44.400406: val_loss -0.7461 +2024-11-21 14:56:44.400485: Pseudo dice [0.833] +2024-11-21 14:56:44.400565: Epoch time: 19.1 s +2024-11-21 14:56:45.264706: +2024-11-21 14:56:45.264893: Epoch 797 +2024-11-21 14:56:45.265009: Current learning rate: 0.0091 +2024-11-21 14:57:03.539977: train_loss -0.7429 +2024-11-21 14:57:03.540200: val_loss -0.7474 +2024-11-21 14:57:03.540276: Pseudo dice [0.8343] +2024-11-21 14:57:03.540353: Epoch time: 18.28 s +2024-11-21 14:57:04.358515: +2024-11-21 14:57:04.358729: Epoch 798 +2024-11-21 14:57:04.358840: Current learning rate: 0.0091 +2024-11-21 14:57:23.259691: train_loss -0.7513 +2024-11-21 14:57:23.259910: val_loss -0.7519 +2024-11-21 14:57:23.260000: Pseudo dice [0.8405] +2024-11-21 14:57:23.260077: Epoch time: 18.9 s +2024-11-21 14:57:24.475092: +2024-11-21 14:57:24.475343: Epoch 799 +2024-11-21 14:57:24.475456: Current learning rate: 0.0091 +2024-11-21 14:57:44.367975: train_loss -0.7679 +2024-11-21 14:57:44.368307: val_loss -0.7798 +2024-11-21 14:57:44.368388: Pseudo dice [0.8542] +2024-11-21 14:57:44.368472: Epoch time: 19.89 s +2024-11-21 14:57:45.454869: +2024-11-21 14:57:45.455082: Epoch 800 +2024-11-21 14:57:45.455199: Current learning rate: 0.0091 +2024-11-21 14:58:04.785816: train_loss -0.7651 +2024-11-21 14:58:04.786041: val_loss -0.7704 +2024-11-21 14:58:04.786115: Pseudo dice [0.8283] +2024-11-21 14:58:04.786187: Epoch time: 19.33 s +2024-11-21 14:58:05.601141: +2024-11-21 14:58:05.601352: Epoch 801 +2024-11-21 14:58:05.601461: Current learning rate: 0.00909 +2024-11-21 14:58:23.840925: train_loss -0.7417 +2024-11-21 14:58:23.841188: val_loss -0.7672 +2024-11-21 14:58:23.841261: Pseudo dice [0.8414] +2024-11-21 14:58:23.841335: Epoch time: 18.24 s +2024-11-21 14:58:24.680125: +2024-11-21 14:58:24.680358: Epoch 802 +2024-11-21 14:58:24.680478: Current learning rate: 0.00909 +2024-11-21 14:58:42.078769: train_loss -0.76 +2024-11-21 14:58:42.078984: val_loss -0.7553 +2024-11-21 14:58:42.079083: Pseudo dice [0.854] +2024-11-21 14:58:42.079163: Epoch time: 17.4 s +2024-11-21 14:58:42.900105: +2024-11-21 14:58:42.900352: Epoch 803 +2024-11-21 14:58:42.900476: Current learning rate: 0.00909 +2024-11-21 14:59:01.984247: train_loss -0.7545 +2024-11-21 14:59:01.984485: val_loss -0.7681 +2024-11-21 14:59:01.987349: Pseudo dice [0.8393] +2024-11-21 14:59:01.987577: Epoch time: 19.08 s +2024-11-21 14:59:02.809009: +2024-11-21 14:59:02.809218: Epoch 804 +2024-11-21 14:59:02.809325: Current learning rate: 0.00909 +2024-11-21 14:59:21.816447: train_loss -0.7524 +2024-11-21 14:59:21.816672: val_loss -0.772 +2024-11-21 14:59:21.816745: Pseudo dice [0.8534] +2024-11-21 14:59:21.816820: Epoch time: 19.01 s +2024-11-21 14:59:22.880808: +2024-11-21 14:59:22.881051: Epoch 805 +2024-11-21 14:59:22.881160: Current learning rate: 0.00909 +2024-11-21 14:59:41.641120: train_loss -0.7439 +2024-11-21 14:59:41.641348: val_loss -0.7373 +2024-11-21 14:59:41.641423: Pseudo dice [0.8029] +2024-11-21 14:59:41.641496: Epoch time: 18.76 s +2024-11-21 14:59:42.459065: +2024-11-21 14:59:42.459302: Epoch 806 +2024-11-21 14:59:42.459409: Current learning rate: 0.00909 +2024-11-21 15:00:00.808671: train_loss -0.7519 +2024-11-21 15:00:00.808886: val_loss -0.7495 +2024-11-21 15:00:00.808963: Pseudo dice [0.8343] +2024-11-21 15:00:00.809042: Epoch time: 18.35 s +2024-11-21 15:00:01.623960: +2024-11-21 15:00:01.624232: Epoch 807 +2024-11-21 15:00:01.624346: Current learning rate: 0.00909 +2024-11-21 15:00:20.893684: train_loss -0.7571 +2024-11-21 15:00:20.893895: val_loss -0.7395 +2024-11-21 15:00:20.893967: Pseudo dice [0.8266] +2024-11-21 15:00:20.894047: Epoch time: 19.27 s +2024-11-21 15:00:21.866223: +2024-11-21 15:00:21.866434: Epoch 808 +2024-11-21 15:00:21.866553: Current learning rate: 0.00909 +2024-11-21 15:00:39.969477: train_loss -0.753 +2024-11-21 15:00:39.971847: val_loss -0.7575 +2024-11-21 15:00:39.971936: Pseudo dice [0.8506] +2024-11-21 15:00:39.972021: Epoch time: 18.1 s +2024-11-21 15:00:40.825772: +2024-11-21 15:00:40.825968: Epoch 809 +2024-11-21 15:00:40.826081: Current learning rate: 0.00909 +2024-11-21 15:00:58.909200: train_loss -0.7641 +2024-11-21 15:00:58.909442: val_loss -0.7703 +2024-11-21 15:00:58.909519: Pseudo dice [0.8256] +2024-11-21 15:00:58.909593: Epoch time: 18.08 s +2024-11-21 15:01:00.112521: +2024-11-21 15:01:00.112751: Epoch 810 +2024-11-21 15:01:00.112861: Current learning rate: 0.00908 +2024-11-21 15:01:18.226537: train_loss -0.7547 +2024-11-21 15:01:18.226804: val_loss -0.7491 +2024-11-21 15:01:18.226881: Pseudo dice [0.8216] +2024-11-21 15:01:18.226978: Epoch time: 18.11 s +2024-11-21 15:01:19.043332: +2024-11-21 15:01:19.043524: Epoch 811 +2024-11-21 15:01:19.043634: Current learning rate: 0.00908 +2024-11-21 15:01:37.674461: train_loss -0.7676 +2024-11-21 15:01:37.674675: val_loss -0.7476 +2024-11-21 15:01:37.674749: Pseudo dice [0.8367] +2024-11-21 15:01:37.674823: Epoch time: 18.63 s +2024-11-21 15:01:38.507435: +2024-11-21 15:01:38.507825: Epoch 812 +2024-11-21 15:01:38.507935: Current learning rate: 0.00908 +2024-11-21 15:01:57.467840: train_loss -0.7555 +2024-11-21 15:01:57.468055: val_loss -0.7391 +2024-11-21 15:01:57.468129: Pseudo dice [0.8245] +2024-11-21 15:01:57.468202: Epoch time: 18.96 s +2024-11-21 15:01:58.304041: +2024-11-21 15:01:58.304259: Epoch 813 +2024-11-21 15:01:58.304369: Current learning rate: 0.00908 +2024-11-21 15:02:17.194171: train_loss -0.7668 +2024-11-21 15:02:17.194384: val_loss -0.7517 +2024-11-21 15:02:17.194460: Pseudo dice [0.849] +2024-11-21 15:02:17.194537: Epoch time: 18.89 s +2024-11-21 15:02:18.017853: +2024-11-21 15:02:18.018090: Epoch 814 +2024-11-21 15:02:18.018198: Current learning rate: 0.00908 +2024-11-21 15:02:36.689196: train_loss -0.7636 +2024-11-21 15:02:36.689405: val_loss -0.7698 +2024-11-21 15:02:36.689481: Pseudo dice [0.8609] +2024-11-21 15:02:36.689556: Epoch time: 18.67 s +2024-11-21 15:02:37.503720: +2024-11-21 15:02:37.503944: Epoch 815 +2024-11-21 15:02:37.504061: Current learning rate: 0.00908 +2024-11-21 15:02:55.897869: train_loss -0.7614 +2024-11-21 15:02:55.898098: val_loss -0.7679 +2024-11-21 15:02:55.898174: Pseudo dice [0.8468] +2024-11-21 15:02:55.898556: Epoch time: 18.39 s +2024-11-21 15:02:56.742445: +2024-11-21 15:02:56.742656: Epoch 816 +2024-11-21 15:02:56.742772: Current learning rate: 0.00908 +2024-11-21 15:03:15.376590: train_loss -0.7643 +2024-11-21 15:03:15.376801: val_loss -0.735 +2024-11-21 15:03:15.376873: Pseudo dice [0.8226] +2024-11-21 15:03:15.376944: Epoch time: 18.63 s +2024-11-21 15:03:16.191956: +2024-11-21 15:03:16.192173: Epoch 817 +2024-11-21 15:03:16.192285: Current learning rate: 0.00908 +2024-11-21 15:03:34.279485: train_loss -0.7556 +2024-11-21 15:03:34.279723: val_loss -0.7487 +2024-11-21 15:03:34.279801: Pseudo dice [0.8221] +2024-11-21 15:03:34.279889: Epoch time: 18.09 s +2024-11-21 15:03:35.144465: +2024-11-21 15:03:35.144699: Epoch 818 +2024-11-21 15:03:35.144813: Current learning rate: 0.00907 +2024-11-21 15:03:53.997119: train_loss -0.757 +2024-11-21 15:03:53.997389: val_loss -0.7728 +2024-11-21 15:03:53.997466: Pseudo dice [0.8499] +2024-11-21 15:03:53.997543: Epoch time: 18.85 s +2024-11-21 15:03:54.918643: +2024-11-21 15:03:54.918846: Epoch 819 +2024-11-21 15:03:54.918958: Current learning rate: 0.00907 +2024-11-21 15:04:12.834633: train_loss -0.7642 +2024-11-21 15:04:12.834891: val_loss -0.7548 +2024-11-21 15:04:12.834971: Pseudo dice [0.8237] +2024-11-21 15:04:12.835054: Epoch time: 17.92 s +2024-11-21 15:04:13.625213: +2024-11-21 15:04:13.625432: Epoch 820 +2024-11-21 15:04:13.625539: Current learning rate: 0.00907 +2024-11-21 15:04:32.600767: train_loss -0.7589 +2024-11-21 15:04:32.601011: val_loss -0.7592 +2024-11-21 15:04:32.601092: Pseudo dice [0.8384] +2024-11-21 15:04:32.601171: Epoch time: 18.98 s +2024-11-21 15:04:33.386309: +2024-11-21 15:04:33.386542: Epoch 821 +2024-11-21 15:04:33.386653: Current learning rate: 0.00907 +2024-11-21 15:04:53.124241: train_loss -0.7655 +2024-11-21 15:04:53.124466: val_loss -0.7667 +2024-11-21 15:04:53.124542: Pseudo dice [0.8293] +2024-11-21 15:04:53.124620: Epoch time: 19.74 s +2024-11-21 15:04:53.913961: +2024-11-21 15:04:53.914178: Epoch 822 +2024-11-21 15:04:53.914286: Current learning rate: 0.00907 +2024-11-21 15:05:12.083126: train_loss -0.7678 +2024-11-21 15:05:12.083386: val_loss -0.768 +2024-11-21 15:05:12.083463: Pseudo dice [0.8361] +2024-11-21 15:05:12.083537: Epoch time: 18.17 s +2024-11-21 15:05:12.871024: +2024-11-21 15:05:12.871262: Epoch 823 +2024-11-21 15:05:12.871381: Current learning rate: 0.00907 +2024-11-21 15:05:31.336809: train_loss -0.7734 +2024-11-21 15:05:31.337025: val_loss -0.7529 +2024-11-21 15:05:31.337103: Pseudo dice [0.8461] +2024-11-21 15:05:31.337186: Epoch time: 18.47 s +2024-11-21 15:05:32.137802: +2024-11-21 15:05:32.138034: Epoch 824 +2024-11-21 15:05:32.138147: Current learning rate: 0.00907 +2024-11-21 15:05:50.805856: train_loss -0.7593 +2024-11-21 15:05:50.806077: val_loss -0.7584 +2024-11-21 15:05:50.806154: Pseudo dice [0.8366] +2024-11-21 15:05:50.806232: Epoch time: 18.67 s +2024-11-21 15:05:51.599679: +2024-11-21 15:05:51.599888: Epoch 825 +2024-11-21 15:05:51.600003: Current learning rate: 0.00907 +2024-11-21 15:06:10.433266: train_loss -0.761 +2024-11-21 15:06:10.433474: val_loss -0.7519 +2024-11-21 15:06:10.433550: Pseudo dice [0.844] +2024-11-21 15:06:10.433627: Epoch time: 18.83 s +2024-11-21 15:06:11.226871: +2024-11-21 15:06:11.227099: Epoch 826 +2024-11-21 15:06:11.227220: Current learning rate: 0.00907 +2024-11-21 15:06:30.169609: train_loss -0.7574 +2024-11-21 15:06:30.169813: val_loss -0.7469 +2024-11-21 15:06:30.169888: Pseudo dice [0.8394] +2024-11-21 15:06:30.169961: Epoch time: 18.94 s +2024-11-21 15:06:30.962323: +2024-11-21 15:06:30.962548: Epoch 827 +2024-11-21 15:06:30.962657: Current learning rate: 0.00906 +2024-11-21 15:06:49.792362: train_loss -0.7639 +2024-11-21 15:06:49.792679: val_loss -0.7688 +2024-11-21 15:06:49.792763: Pseudo dice [0.8314] +2024-11-21 15:06:49.792845: Epoch time: 18.83 s +2024-11-21 15:06:50.590447: +2024-11-21 15:06:50.590667: Epoch 828 +2024-11-21 15:06:50.590778: Current learning rate: 0.00906 +2024-11-21 15:07:09.477431: train_loss -0.76 +2024-11-21 15:07:09.477637: val_loss -0.7591 +2024-11-21 15:07:09.477769: Pseudo dice [0.8464] +2024-11-21 15:07:09.477844: Epoch time: 18.89 s +2024-11-21 15:07:10.269600: +2024-11-21 15:07:10.269801: Epoch 829 +2024-11-21 15:07:10.269912: Current learning rate: 0.00906 +2024-11-21 15:07:29.034572: train_loss -0.7658 +2024-11-21 15:07:29.034837: val_loss -0.7515 +2024-11-21 15:07:29.034943: Pseudo dice [0.8368] +2024-11-21 15:07:29.035024: Epoch time: 18.77 s +2024-11-21 15:07:29.844318: +2024-11-21 15:07:29.844557: Epoch 830 +2024-11-21 15:07:29.844677: Current learning rate: 0.00906 +2024-11-21 15:07:47.751988: train_loss -0.7667 +2024-11-21 15:07:47.752214: val_loss -0.7491 +2024-11-21 15:07:47.752290: Pseudo dice [0.8292] +2024-11-21 15:07:47.752369: Epoch time: 17.91 s +2024-11-21 15:07:48.594015: +2024-11-21 15:07:48.594251: Epoch 831 +2024-11-21 15:07:48.594364: Current learning rate: 0.00906 +2024-11-21 15:08:07.737733: train_loss -0.7647 +2024-11-21 15:08:07.737944: val_loss -0.7661 +2024-11-21 15:08:07.738022: Pseudo dice [0.8516] +2024-11-21 15:08:07.738094: Epoch time: 19.14 s +2024-11-21 15:08:08.632797: +2024-11-21 15:08:08.633034: Epoch 832 +2024-11-21 15:08:08.633148: Current learning rate: 0.00906 +2024-11-21 15:08:27.379223: train_loss -0.7642 +2024-11-21 15:08:27.379427: val_loss -0.7527 +2024-11-21 15:08:27.379499: Pseudo dice [0.8392] +2024-11-21 15:08:27.379575: Epoch time: 18.75 s +2024-11-21 15:08:28.165163: +2024-11-21 15:08:28.165385: Epoch 833 +2024-11-21 15:08:28.165495: Current learning rate: 0.00906 +2024-11-21 15:08:47.104537: train_loss -0.755 +2024-11-21 15:08:47.104757: val_loss -0.7539 +2024-11-21 15:08:47.104828: Pseudo dice [0.8378] +2024-11-21 15:08:47.104904: Epoch time: 18.94 s +2024-11-21 15:08:47.899170: +2024-11-21 15:08:47.899413: Epoch 834 +2024-11-21 15:08:47.899526: Current learning rate: 0.00906 +2024-11-21 15:09:06.033123: train_loss -0.7468 +2024-11-21 15:09:06.035514: val_loss -0.766 +2024-11-21 15:09:06.035635: Pseudo dice [0.8477] +2024-11-21 15:09:06.035718: Epoch time: 18.13 s +2024-11-21 15:09:06.883469: +2024-11-21 15:09:06.883705: Epoch 835 +2024-11-21 15:09:06.883819: Current learning rate: 0.00906 +2024-11-21 15:09:25.704313: train_loss -0.7548 +2024-11-21 15:09:25.704514: val_loss -0.7418 +2024-11-21 15:09:25.704589: Pseudo dice [0.8045] +2024-11-21 15:09:25.704664: Epoch time: 18.82 s +2024-11-21 15:09:26.489844: +2024-11-21 15:09:26.490071: Epoch 836 +2024-11-21 15:09:26.490191: Current learning rate: 0.00905 +2024-11-21 15:09:44.510864: train_loss -0.7626 +2024-11-21 15:09:44.511137: val_loss -0.7397 +2024-11-21 15:09:44.511211: Pseudo dice [0.8391] +2024-11-21 15:09:44.511286: Epoch time: 18.02 s +2024-11-21 15:09:45.624124: +2024-11-21 15:09:45.624356: Epoch 837 +2024-11-21 15:09:45.624470: Current learning rate: 0.00905 +2024-11-21 15:10:03.741790: train_loss -0.7497 +2024-11-21 15:10:03.742034: val_loss -0.732 +2024-11-21 15:10:03.742112: Pseudo dice [0.8182] +2024-11-21 15:10:03.742197: Epoch time: 18.12 s +2024-11-21 15:10:04.538615: +2024-11-21 15:10:04.538902: Epoch 838 +2024-11-21 15:10:04.539021: Current learning rate: 0.00905 +2024-11-21 15:10:23.527435: train_loss -0.7445 +2024-11-21 15:10:23.527673: val_loss -0.7647 +2024-11-21 15:10:23.527758: Pseudo dice [0.8258] +2024-11-21 15:10:23.527841: Epoch time: 18.99 s +2024-11-21 15:10:24.319321: +2024-11-21 15:10:24.319526: Epoch 839 +2024-11-21 15:10:24.319630: Current learning rate: 0.00905 +2024-11-21 15:10:42.558784: train_loss -0.7491 +2024-11-21 15:10:42.558986: val_loss -0.762 +2024-11-21 15:10:42.559072: Pseudo dice [0.835] +2024-11-21 15:10:42.559149: Epoch time: 18.24 s +2024-11-21 15:10:43.372962: +2024-11-21 15:10:43.373231: Epoch 840 +2024-11-21 15:10:43.373348: Current learning rate: 0.00905 +2024-11-21 15:11:02.849039: train_loss -0.7466 +2024-11-21 15:11:02.849276: val_loss -0.7602 +2024-11-21 15:11:02.849353: Pseudo dice [0.823] +2024-11-21 15:11:02.849438: Epoch time: 19.48 s +2024-11-21 15:11:03.638827: +2024-11-21 15:11:03.639036: Epoch 841 +2024-11-21 15:11:03.639145: Current learning rate: 0.00905 +2024-11-21 15:11:21.871602: train_loss -0.761 +2024-11-21 15:11:21.871830: val_loss -0.7324 +2024-11-21 15:11:21.871906: Pseudo dice [0.8348] +2024-11-21 15:11:21.872265: Epoch time: 18.23 s +2024-11-21 15:11:22.661896: +2024-11-21 15:11:22.662129: Epoch 842 +2024-11-21 15:11:22.662244: Current learning rate: 0.00905 +2024-11-21 15:11:40.504976: train_loss -0.7709 +2024-11-21 15:11:40.505196: val_loss -0.7568 +2024-11-21 15:11:40.505274: Pseudo dice [0.8245] +2024-11-21 15:11:40.505352: Epoch time: 17.84 s +2024-11-21 15:11:41.298230: +2024-11-21 15:11:41.298450: Epoch 843 +2024-11-21 15:11:41.298561: Current learning rate: 0.00905 +2024-11-21 15:11:59.518403: train_loss -0.7562 +2024-11-21 15:11:59.518620: val_loss -0.7533 +2024-11-21 15:11:59.518704: Pseudo dice [0.8314] +2024-11-21 15:11:59.518784: Epoch time: 18.22 s +2024-11-21 15:12:00.318215: +2024-11-21 15:12:00.318436: Epoch 844 +2024-11-21 15:12:00.318549: Current learning rate: 0.00905 +2024-11-21 15:12:18.329570: train_loss -0.7589 +2024-11-21 15:12:18.332017: val_loss -0.7614 +2024-11-21 15:12:18.332140: Pseudo dice [0.8394] +2024-11-21 15:12:18.332222: Epoch time: 18.01 s +2024-11-21 15:12:19.149677: +2024-11-21 15:12:19.149884: Epoch 845 +2024-11-21 15:12:19.149997: Current learning rate: 0.00904 +2024-11-21 15:12:37.378578: train_loss -0.77 +2024-11-21 15:12:37.378791: val_loss -0.7652 +2024-11-21 15:12:37.378865: Pseudo dice [0.8436] +2024-11-21 15:12:37.378939: Epoch time: 18.23 s +2024-11-21 15:12:38.186357: +2024-11-21 15:12:38.186603: Epoch 846 +2024-11-21 15:12:38.186715: Current learning rate: 0.00904 +2024-11-21 15:12:57.186107: train_loss -0.7601 +2024-11-21 15:12:57.186342: val_loss -0.7711 +2024-11-21 15:12:57.186417: Pseudo dice [0.8401] +2024-11-21 15:12:57.186500: Epoch time: 19.0 s +2024-11-21 15:12:58.068454: +2024-11-21 15:12:58.068711: Epoch 847 +2024-11-21 15:12:58.068825: Current learning rate: 0.00904 +2024-11-21 15:13:16.575790: train_loss -0.7708 +2024-11-21 15:13:16.576025: val_loss -0.7631 +2024-11-21 15:13:16.576104: Pseudo dice [0.8357] +2024-11-21 15:13:16.576185: Epoch time: 18.51 s +2024-11-21 15:13:17.372968: +2024-11-21 15:13:17.373260: Epoch 848 +2024-11-21 15:13:17.373376: Current learning rate: 0.00904 +2024-11-21 15:13:36.790759: train_loss -0.7646 +2024-11-21 15:13:36.790965: val_loss -0.7676 +2024-11-21 15:13:36.791070: Pseudo dice [0.8289] +2024-11-21 15:13:36.791148: Epoch time: 19.42 s +2024-11-21 15:13:37.667974: +2024-11-21 15:13:37.668205: Epoch 849 +2024-11-21 15:13:37.668318: Current learning rate: 0.00904 +2024-11-21 15:13:56.872067: train_loss -0.768 +2024-11-21 15:13:56.872268: val_loss -0.768 +2024-11-21 15:13:56.872354: Pseudo dice [0.8363] +2024-11-21 15:13:56.872429: Epoch time: 19.2 s +2024-11-21 15:13:57.904529: +2024-11-21 15:13:57.904747: Epoch 850 +2024-11-21 15:13:57.904859: Current learning rate: 0.00904 +2024-11-21 15:14:16.305928: train_loss -0.7532 +2024-11-21 15:14:16.306146: val_loss -0.7182 +2024-11-21 15:14:16.306222: Pseudo dice [0.8078] +2024-11-21 15:14:16.306296: Epoch time: 18.4 s +2024-11-21 15:14:17.099312: +2024-11-21 15:14:17.099542: Epoch 851 +2024-11-21 15:14:17.099654: Current learning rate: 0.00904 +2024-11-21 15:14:36.834619: train_loss -0.755 +2024-11-21 15:14:36.834909: val_loss -0.7515 +2024-11-21 15:14:36.834986: Pseudo dice [0.8329] +2024-11-21 15:14:36.835121: Epoch time: 19.74 s +2024-11-21 15:14:37.697846: +2024-11-21 15:14:37.698067: Epoch 852 +2024-11-21 15:14:37.698178: Current learning rate: 0.00904 +2024-11-21 15:14:55.684677: train_loss -0.7656 +2024-11-21 15:14:55.684879: val_loss -0.7303 +2024-11-21 15:14:55.684958: Pseudo dice [0.8186] +2024-11-21 15:14:55.685037: Epoch time: 17.99 s +2024-11-21 15:14:56.479555: +2024-11-21 15:14:56.479771: Epoch 853 +2024-11-21 15:14:56.479883: Current learning rate: 0.00904 +2024-11-21 15:15:14.962849: train_loss -0.7532 +2024-11-21 15:15:14.963072: val_loss -0.7515 +2024-11-21 15:15:14.963152: Pseudo dice [0.8435] +2024-11-21 15:15:14.963231: Epoch time: 18.48 s +2024-11-21 15:15:15.893901: +2024-11-21 15:15:15.894128: Epoch 854 +2024-11-21 15:15:15.894246: Current learning rate: 0.00903 +2024-11-21 15:15:33.672369: train_loss -0.7553 +2024-11-21 15:15:33.672589: val_loss -0.7278 +2024-11-21 15:15:33.677907: Pseudo dice [0.8319] +2024-11-21 15:15:33.678013: Epoch time: 17.78 s +2024-11-21 15:15:34.622632: +2024-11-21 15:15:34.622853: Epoch 855 +2024-11-21 15:15:34.622970: Current learning rate: 0.00903 +2024-11-21 15:15:52.330293: train_loss -0.754 +2024-11-21 15:15:52.330520: val_loss -0.7773 +2024-11-21 15:15:52.330593: Pseudo dice [0.8417] +2024-11-21 15:15:52.330671: Epoch time: 17.71 s +2024-11-21 15:15:53.123792: +2024-11-21 15:15:53.124015: Epoch 856 +2024-11-21 15:15:53.124121: Current learning rate: 0.00903 +2024-11-21 15:16:12.186882: train_loss -0.7447 +2024-11-21 15:16:12.187104: val_loss -0.7543 +2024-11-21 15:16:12.187179: Pseudo dice [0.8396] +2024-11-21 15:16:12.187255: Epoch time: 19.06 s +2024-11-21 15:16:13.433592: +2024-11-21 15:16:13.433823: Epoch 857 +2024-11-21 15:16:13.433937: Current learning rate: 0.00903 +2024-11-21 15:16:31.861779: train_loss -0.7564 +2024-11-21 15:16:31.863685: val_loss -0.7074 +2024-11-21 15:16:31.863783: Pseudo dice [0.8174] +2024-11-21 15:16:31.863858: Epoch time: 18.43 s +2024-11-21 15:16:32.674073: +2024-11-21 15:16:32.674281: Epoch 858 +2024-11-21 15:16:32.674389: Current learning rate: 0.00903 +2024-11-21 15:16:51.400861: train_loss -0.7383 +2024-11-21 15:16:51.401107: val_loss -0.7431 +2024-11-21 15:16:51.401188: Pseudo dice [0.8299] +2024-11-21 15:16:51.401279: Epoch time: 18.73 s +2024-11-21 15:16:52.207277: +2024-11-21 15:16:52.207496: Epoch 859 +2024-11-21 15:16:52.207620: Current learning rate: 0.00903 +2024-11-21 15:17:09.784520: train_loss -0.7549 +2024-11-21 15:17:09.784781: val_loss -0.7498 +2024-11-21 15:17:09.784886: Pseudo dice [0.8376] +2024-11-21 15:17:09.784963: Epoch time: 17.58 s +2024-11-21 15:17:10.581232: +2024-11-21 15:17:10.581415: Epoch 860 +2024-11-21 15:17:10.581528: Current learning rate: 0.00903 +2024-11-21 15:17:29.141887: train_loss -0.7599 +2024-11-21 15:17:29.142100: val_loss -0.7268 +2024-11-21 15:17:29.142175: Pseudo dice [0.8365] +2024-11-21 15:17:29.142250: Epoch time: 18.56 s +2024-11-21 15:17:29.936847: +2024-11-21 15:17:29.937067: Epoch 861 +2024-11-21 15:17:29.937181: Current learning rate: 0.00903 +2024-11-21 15:17:47.789603: train_loss -0.7623 +2024-11-21 15:17:47.789821: val_loss -0.7799 +2024-11-21 15:17:47.789899: Pseudo dice [0.8265] +2024-11-21 15:17:47.792222: Epoch time: 17.85 s +2024-11-21 15:17:48.604540: +2024-11-21 15:17:48.604900: Epoch 862 +2024-11-21 15:17:48.605021: Current learning rate: 0.00902 +2024-11-21 15:18:05.969081: train_loss -0.7609 +2024-11-21 15:18:05.969314: val_loss -0.7707 +2024-11-21 15:18:05.969393: Pseudo dice [0.8391] +2024-11-21 15:18:05.969481: Epoch time: 17.37 s +2024-11-21 15:18:06.991147: +2024-11-21 15:18:06.991367: Epoch 863 +2024-11-21 15:18:06.991480: Current learning rate: 0.00902 +2024-11-21 15:18:25.439042: train_loss -0.7634 +2024-11-21 15:18:25.439250: val_loss -0.7646 +2024-11-21 15:18:25.444130: Pseudo dice [0.8485] +2024-11-21 15:18:25.444355: Epoch time: 18.45 s +2024-11-21 15:18:26.246358: +2024-11-21 15:18:26.246589: Epoch 864 +2024-11-21 15:18:26.246701: Current learning rate: 0.00902 +2024-11-21 15:18:45.062033: train_loss -0.762 +2024-11-21 15:18:45.062277: val_loss -0.7285 +2024-11-21 15:18:45.062355: Pseudo dice [0.8376] +2024-11-21 15:18:45.062429: Epoch time: 18.82 s +2024-11-21 15:18:45.971776: +2024-11-21 15:18:45.972007: Epoch 865 +2024-11-21 15:18:45.972120: Current learning rate: 0.00902 +2024-11-21 15:19:04.270373: train_loss -0.7553 +2024-11-21 15:19:04.270616: val_loss -0.7461 +2024-11-21 15:19:04.270689: Pseudo dice [0.8496] +2024-11-21 15:19:04.270773: Epoch time: 18.3 s +2024-11-21 15:19:05.062699: +2024-11-21 15:19:05.062900: Epoch 866 +2024-11-21 15:19:05.063016: Current learning rate: 0.00902 +2024-11-21 15:19:23.069374: train_loss -0.7628 +2024-11-21 15:19:23.069578: val_loss -0.7788 +2024-11-21 15:19:23.069649: Pseudo dice [0.8474] +2024-11-21 15:19:23.069722: Epoch time: 18.01 s +2024-11-21 15:19:23.861944: +2024-11-21 15:19:23.862151: Epoch 867 +2024-11-21 15:19:23.862258: Current learning rate: 0.00902 +2024-11-21 15:19:42.542185: train_loss -0.7707 +2024-11-21 15:19:42.542408: val_loss -0.7659 +2024-11-21 15:19:42.542484: Pseudo dice [0.8387] +2024-11-21 15:19:42.542789: Epoch time: 18.68 s +2024-11-21 15:19:43.341153: +2024-11-21 15:19:43.341374: Epoch 868 +2024-11-21 15:19:43.341489: Current learning rate: 0.00902 +2024-11-21 15:20:00.953405: train_loss -0.7719 +2024-11-21 15:20:00.953615: val_loss -0.7531 +2024-11-21 15:20:00.953689: Pseudo dice [0.8472] +2024-11-21 15:20:00.953765: Epoch time: 17.61 s +2024-11-21 15:20:02.122178: +2024-11-21 15:20:02.122446: Epoch 869 +2024-11-21 15:20:02.122563: Current learning rate: 0.00902 +2024-11-21 15:20:19.845098: train_loss -0.7675 +2024-11-21 15:20:19.845351: val_loss -0.7431 +2024-11-21 15:20:19.845426: Pseudo dice [0.8251] +2024-11-21 15:20:19.845512: Epoch time: 17.72 s +2024-11-21 15:20:20.647231: +2024-11-21 15:20:20.647523: Epoch 870 +2024-11-21 15:20:20.647632: Current learning rate: 0.00902 +2024-11-21 15:20:38.926136: train_loss -0.7614 +2024-11-21 15:20:38.926369: val_loss -0.7401 +2024-11-21 15:20:38.926454: Pseudo dice [0.8409] +2024-11-21 15:20:38.926528: Epoch time: 18.28 s +2024-11-21 15:20:39.725200: +2024-11-21 15:20:39.725432: Epoch 871 +2024-11-21 15:20:39.725546: Current learning rate: 0.00901 +2024-11-21 15:20:59.960680: train_loss -0.7719 +2024-11-21 15:20:59.960889: val_loss -0.7611 +2024-11-21 15:20:59.960962: Pseudo dice [0.8382] +2024-11-21 15:20:59.961044: Epoch time: 20.24 s +2024-11-21 15:21:00.762131: +2024-11-21 15:21:00.762389: Epoch 872 +2024-11-21 15:21:00.762499: Current learning rate: 0.00901 +2024-11-21 15:21:19.271294: train_loss -0.7636 +2024-11-21 15:21:19.271525: val_loss -0.757 +2024-11-21 15:21:19.271608: Pseudo dice [0.8339] +2024-11-21 15:21:19.271694: Epoch time: 18.51 s +2024-11-21 15:21:20.070672: +2024-11-21 15:21:20.070897: Epoch 873 +2024-11-21 15:21:20.071013: Current learning rate: 0.00901 +2024-11-21 15:21:37.956389: train_loss -0.7539 +2024-11-21 15:21:37.956639: val_loss -0.7716 +2024-11-21 15:21:37.956723: Pseudo dice [0.8383] +2024-11-21 15:21:37.956800: Epoch time: 17.89 s +2024-11-21 15:21:38.749612: +2024-11-21 15:21:38.749840: Epoch 874 +2024-11-21 15:21:38.749949: Current learning rate: 0.00901 +2024-11-21 15:21:58.138900: train_loss -0.7565 +2024-11-21 15:21:58.139108: val_loss -0.7621 +2024-11-21 15:21:58.139182: Pseudo dice [0.849] +2024-11-21 15:21:58.139256: Epoch time: 19.39 s +2024-11-21 15:21:58.938910: +2024-11-21 15:21:58.939146: Epoch 875 +2024-11-21 15:21:58.939258: Current learning rate: 0.00901 +2024-11-21 15:22:17.281011: train_loss -0.7548 +2024-11-21 15:22:17.281227: val_loss -0.7719 +2024-11-21 15:22:17.281299: Pseudo dice [0.8466] +2024-11-21 15:22:17.281372: Epoch time: 18.34 s +2024-11-21 15:22:18.228561: +2024-11-21 15:22:18.228792: Epoch 876 +2024-11-21 15:22:18.228910: Current learning rate: 0.00901 +2024-11-21 15:22:35.725976: train_loss -0.7687 +2024-11-21 15:22:35.726220: val_loss -0.7566 +2024-11-21 15:22:35.726297: Pseudo dice [0.8356] +2024-11-21 15:22:35.726379: Epoch time: 17.5 s +2024-11-21 15:22:36.571683: +2024-11-21 15:22:36.571914: Epoch 877 +2024-11-21 15:22:36.572029: Current learning rate: 0.00901 +2024-11-21 15:22:54.794545: train_loss -0.7547 +2024-11-21 15:22:54.794756: val_loss -0.7618 +2024-11-21 15:22:54.794828: Pseudo dice [0.8137] +2024-11-21 15:22:54.794902: Epoch time: 18.22 s +2024-11-21 15:22:55.610010: +2024-11-21 15:22:55.610306: Epoch 878 +2024-11-21 15:22:55.610420: Current learning rate: 0.00901 +2024-11-21 15:23:14.494198: train_loss -0.7545 +2024-11-21 15:23:14.494430: val_loss -0.7568 +2024-11-21 15:23:14.494505: Pseudo dice [0.8485] +2024-11-21 15:23:14.494592: Epoch time: 18.89 s +2024-11-21 15:23:15.295868: +2024-11-21 15:23:15.296090: Epoch 879 +2024-11-21 15:23:15.296205: Current learning rate: 0.00901 +2024-11-21 15:23:33.377095: train_loss -0.7577 +2024-11-21 15:23:33.377315: val_loss -0.7624 +2024-11-21 15:23:33.377391: Pseudo dice [0.8252] +2024-11-21 15:23:33.377473: Epoch time: 18.08 s +2024-11-21 15:23:34.178273: +2024-11-21 15:23:34.178485: Epoch 880 +2024-11-21 15:23:34.178593: Current learning rate: 0.009 +2024-11-21 15:23:53.281046: train_loss -0.7479 +2024-11-21 15:23:53.281301: val_loss -0.7662 +2024-11-21 15:23:53.281379: Pseudo dice [0.848] +2024-11-21 15:23:53.281458: Epoch time: 19.1 s +2024-11-21 15:23:54.522311: +2024-11-21 15:23:54.522545: Epoch 881 +2024-11-21 15:23:54.522655: Current learning rate: 0.009 +2024-11-21 15:24:12.554628: train_loss -0.7552 +2024-11-21 15:24:12.554845: val_loss -0.7415 +2024-11-21 15:24:12.554923: Pseudo dice [0.8334] +2024-11-21 15:24:12.555008: Epoch time: 18.03 s +2024-11-21 15:24:13.346641: +2024-11-21 15:24:13.346871: Epoch 882 +2024-11-21 15:24:13.346988: Current learning rate: 0.009 +2024-11-21 15:24:33.098557: train_loss -0.7533 +2024-11-21 15:24:33.098762: val_loss -0.727 +2024-11-21 15:24:33.098834: Pseudo dice [0.8374] +2024-11-21 15:24:33.098909: Epoch time: 19.75 s +2024-11-21 15:24:33.895845: +2024-11-21 15:24:33.896060: Epoch 883 +2024-11-21 15:24:33.896167: Current learning rate: 0.009 +2024-11-21 15:24:50.971142: train_loss -0.767 +2024-11-21 15:24:50.971390: val_loss -0.7716 +2024-11-21 15:24:50.971469: Pseudo dice [0.8532] +2024-11-21 15:24:50.971556: Epoch time: 17.08 s +2024-11-21 15:24:51.770730: +2024-11-21 15:24:51.770966: Epoch 884 +2024-11-21 15:24:51.771077: Current learning rate: 0.009 +2024-11-21 15:25:10.535953: train_loss -0.7642 +2024-11-21 15:25:10.536232: val_loss -0.7822 +2024-11-21 15:25:10.536304: Pseudo dice [0.8432] +2024-11-21 15:25:10.536376: Epoch time: 18.77 s +2024-11-21 15:25:11.334115: +2024-11-21 15:25:11.334335: Epoch 885 +2024-11-21 15:25:11.334447: Current learning rate: 0.009 +2024-11-21 15:25:30.684591: train_loss -0.771 +2024-11-21 15:25:30.684869: val_loss -0.7687 +2024-11-21 15:25:30.684951: Pseudo dice [0.8548] +2024-11-21 15:25:30.685034: Epoch time: 19.35 s +2024-11-21 15:25:31.487540: +2024-11-21 15:25:31.487786: Epoch 886 +2024-11-21 15:25:31.487905: Current learning rate: 0.009 +2024-11-21 15:25:49.191587: train_loss -0.7632 +2024-11-21 15:25:49.191840: val_loss -0.7563 +2024-11-21 15:25:49.191918: Pseudo dice [0.8386] +2024-11-21 15:25:49.192006: Epoch time: 17.7 s +2024-11-21 15:25:49.991679: +2024-11-21 15:25:49.991926: Epoch 887 +2024-11-21 15:25:49.992038: Current learning rate: 0.009 +2024-11-21 15:26:09.352928: train_loss -0.7637 +2024-11-21 15:26:09.355346: val_loss -0.7563 +2024-11-21 15:26:09.355438: Pseudo dice [0.8378] +2024-11-21 15:26:09.355518: Epoch time: 19.36 s +2024-11-21 15:26:10.247756: +2024-11-21 15:26:10.248024: Epoch 888 +2024-11-21 15:26:10.248150: Current learning rate: 0.009 +2024-11-21 15:26:28.919814: train_loss -0.7734 +2024-11-21 15:26:28.920028: val_loss -0.7475 +2024-11-21 15:26:28.920105: Pseudo dice [0.8208] +2024-11-21 15:26:28.920210: Epoch time: 18.67 s +2024-11-21 15:26:29.716424: +2024-11-21 15:26:29.716654: Epoch 889 +2024-11-21 15:26:29.716773: Current learning rate: 0.00899 +2024-11-21 15:26:48.006656: train_loss -0.7744 +2024-11-21 15:26:48.009042: val_loss -0.7652 +2024-11-21 15:26:48.009134: Pseudo dice [0.829] +2024-11-21 15:26:48.009212: Epoch time: 18.29 s +2024-11-21 15:26:48.832650: +2024-11-21 15:26:48.832872: Epoch 890 +2024-11-21 15:26:48.832997: Current learning rate: 0.00899 +2024-11-21 15:27:08.170551: train_loss -0.7612 +2024-11-21 15:27:08.170833: val_loss -0.7541 +2024-11-21 15:27:08.174858: Pseudo dice [0.841] +2024-11-21 15:27:08.175050: Epoch time: 19.34 s +2024-11-21 15:27:09.011090: +2024-11-21 15:27:09.011311: Epoch 891 +2024-11-21 15:27:09.011420: Current learning rate: 0.00899 +2024-11-21 15:27:27.920928: train_loss -0.7615 +2024-11-21 15:27:27.921141: val_loss -0.7419 +2024-11-21 15:27:27.921215: Pseudo dice [0.8295] +2024-11-21 15:27:27.921289: Epoch time: 18.91 s +2024-11-21 15:27:28.715477: +2024-11-21 15:27:28.715684: Epoch 892 +2024-11-21 15:27:28.715792: Current learning rate: 0.00899 +2024-11-21 15:27:46.597588: train_loss -0.7659 +2024-11-21 15:27:46.597800: val_loss -0.7463 +2024-11-21 15:27:46.597878: Pseudo dice [0.8308] +2024-11-21 15:27:46.597950: Epoch time: 17.88 s +2024-11-21 15:27:47.767085: +2024-11-21 15:27:47.767307: Epoch 893 +2024-11-21 15:27:47.767419: Current learning rate: 0.00899 +2024-11-21 15:28:06.075878: train_loss -0.7582 +2024-11-21 15:28:06.076143: val_loss -0.7617 +2024-11-21 15:28:06.076223: Pseudo dice [0.8393] +2024-11-21 15:28:06.076632: Epoch time: 18.31 s +2024-11-21 15:28:06.878006: +2024-11-21 15:28:06.878235: Epoch 894 +2024-11-21 15:28:06.878353: Current learning rate: 0.00899 +2024-11-21 15:28:25.768393: train_loss -0.7632 +2024-11-21 15:28:25.768740: val_loss -0.732 +2024-11-21 15:28:25.768820: Pseudo dice [0.8361] +2024-11-21 15:28:25.768900: Epoch time: 18.89 s +2024-11-21 15:28:26.568839: +2024-11-21 15:28:26.569060: Epoch 895 +2024-11-21 15:28:26.569178: Current learning rate: 0.00899 +2024-11-21 15:28:45.061170: train_loss -0.7651 +2024-11-21 15:28:45.061861: val_loss -0.7542 +2024-11-21 15:28:45.061957: Pseudo dice [0.8309] +2024-11-21 15:28:45.062038: Epoch time: 18.49 s +2024-11-21 15:28:45.875803: +2024-11-21 15:28:45.876037: Epoch 896 +2024-11-21 15:28:45.876151: Current learning rate: 0.00899 +2024-11-21 15:29:04.292755: train_loss -0.7471 +2024-11-21 15:29:04.292981: val_loss -0.7513 +2024-11-21 15:29:04.293063: Pseudo dice [0.8388] +2024-11-21 15:29:04.293143: Epoch time: 18.42 s +2024-11-21 15:29:05.091514: +2024-11-21 15:29:05.091737: Epoch 897 +2024-11-21 15:29:05.091856: Current learning rate: 0.00898 +2024-11-21 15:29:23.152474: train_loss -0.7675 +2024-11-21 15:29:23.152719: val_loss -0.7599 +2024-11-21 15:29:23.152809: Pseudo dice [0.8367] +2024-11-21 15:29:23.155079: Epoch time: 18.06 s +2024-11-21 15:29:23.996047: +2024-11-21 15:29:23.996333: Epoch 898 +2024-11-21 15:29:23.996445: Current learning rate: 0.00898 +2024-11-21 15:29:41.935659: train_loss -0.7539 +2024-11-21 15:29:41.935940: val_loss -0.7725 +2024-11-21 15:29:41.936020: Pseudo dice [0.8367] +2024-11-21 15:29:41.936098: Epoch time: 17.94 s +2024-11-21 15:29:42.837611: +2024-11-21 15:29:42.837836: Epoch 899 +2024-11-21 15:29:42.837944: Current learning rate: 0.00898 +2024-11-21 15:30:01.806235: train_loss -0.7526 +2024-11-21 15:30:01.806452: val_loss -0.7552 +2024-11-21 15:30:01.806551: Pseudo dice [0.8335] +2024-11-21 15:30:01.806628: Epoch time: 18.97 s +2024-11-21 15:30:02.838642: +2024-11-21 15:30:02.838866: Epoch 900 +2024-11-21 15:30:02.838978: Current learning rate: 0.00898 +2024-11-21 15:30:22.109479: train_loss -0.7539 +2024-11-21 15:30:22.116155: val_loss -0.7646 +2024-11-21 15:30:22.116255: Pseudo dice [0.8343] +2024-11-21 15:30:22.116346: Epoch time: 19.27 s +2024-11-21 15:30:23.031759: +2024-11-21 15:30:23.032019: Epoch 901 +2024-11-21 15:30:23.032141: Current learning rate: 0.00898 +2024-11-21 15:30:41.199273: train_loss -0.7552 +2024-11-21 15:30:41.199557: val_loss -0.7431 +2024-11-21 15:30:41.199640: Pseudo dice [0.8268] +2024-11-21 15:30:41.199715: Epoch time: 18.17 s +2024-11-21 15:30:42.140264: +2024-11-21 15:30:42.140487: Epoch 902 +2024-11-21 15:30:42.140598: Current learning rate: 0.00898 +2024-11-21 15:31:02.037144: train_loss -0.7573 +2024-11-21 15:31:02.037346: val_loss -0.7604 +2024-11-21 15:31:02.037417: Pseudo dice [0.8482] +2024-11-21 15:31:02.037490: Epoch time: 19.9 s +2024-11-21 15:31:02.977706: +2024-11-21 15:31:02.977942: Epoch 903 +2024-11-21 15:31:02.978067: Current learning rate: 0.00898 +2024-11-21 15:31:21.228373: train_loss -0.7619 +2024-11-21 15:31:21.228586: val_loss -0.735 +2024-11-21 15:31:21.228665: Pseudo dice [0.8416] +2024-11-21 15:31:21.228744: Epoch time: 18.25 s +2024-11-21 15:31:22.022289: +2024-11-21 15:31:22.022494: Epoch 904 +2024-11-21 15:31:22.022605: Current learning rate: 0.00898 +2024-11-21 15:31:39.672863: train_loss -0.7575 +2024-11-21 15:31:39.678289: val_loss -0.7372 +2024-11-21 15:31:39.678410: Pseudo dice [0.8279] +2024-11-21 15:31:39.678501: Epoch time: 17.65 s +2024-11-21 15:31:41.011179: +2024-11-21 15:31:41.011402: Epoch 905 +2024-11-21 15:31:41.011511: Current learning rate: 0.00898 +2024-11-21 15:31:59.997607: train_loss -0.7589 +2024-11-21 15:31:59.997838: val_loss -0.7846 +2024-11-21 15:31:59.997917: Pseudo dice [0.8523] +2024-11-21 15:31:59.998008: Epoch time: 18.99 s +2024-11-21 15:32:00.793925: +2024-11-21 15:32:00.794154: Epoch 906 +2024-11-21 15:32:00.794264: Current learning rate: 0.00897 +2024-11-21 15:32:19.677531: train_loss -0.769 +2024-11-21 15:32:19.677773: val_loss -0.7541 +2024-11-21 15:32:19.677847: Pseudo dice [0.8297] +2024-11-21 15:32:19.677921: Epoch time: 18.88 s +2024-11-21 15:32:20.475588: +2024-11-21 15:32:20.475826: Epoch 907 +2024-11-21 15:32:20.475937: Current learning rate: 0.00897 +2024-11-21 15:32:38.973878: train_loss -0.7582 +2024-11-21 15:32:38.974128: val_loss -0.7642 +2024-11-21 15:32:38.974209: Pseudo dice [0.8505] +2024-11-21 15:32:38.974287: Epoch time: 18.5 s +2024-11-21 15:32:39.768985: +2024-11-21 15:32:39.769223: Epoch 908 +2024-11-21 15:32:39.769342: Current learning rate: 0.00897 +2024-11-21 15:32:58.873287: train_loss -0.7618 +2024-11-21 15:32:58.873502: val_loss -0.7639 +2024-11-21 15:32:58.873582: Pseudo dice [0.8356] +2024-11-21 15:32:58.873659: Epoch time: 19.11 s +2024-11-21 15:32:59.669255: +2024-11-21 15:32:59.669473: Epoch 909 +2024-11-21 15:32:59.669584: Current learning rate: 0.00897 +2024-11-21 15:33:17.668490: train_loss -0.7693 +2024-11-21 15:33:17.668711: val_loss -0.7845 +2024-11-21 15:33:17.668785: Pseudo dice [0.8351] +2024-11-21 15:33:17.668860: Epoch time: 18.0 s +2024-11-21 15:33:18.473001: +2024-11-21 15:33:18.473235: Epoch 910 +2024-11-21 15:33:18.473346: Current learning rate: 0.00897 +2024-11-21 15:33:37.710529: train_loss -0.7719 +2024-11-21 15:33:37.710778: val_loss -0.7507 +2024-11-21 15:33:37.710869: Pseudo dice [0.8421] +2024-11-21 15:33:37.710942: Epoch time: 19.24 s +2024-11-21 15:33:38.509338: +2024-11-21 15:33:38.509570: Epoch 911 +2024-11-21 15:33:38.509678: Current learning rate: 0.00897 +2024-11-21 15:33:57.072302: train_loss -0.7564 +2024-11-21 15:33:57.072533: val_loss -0.7586 +2024-11-21 15:33:57.072607: Pseudo dice [0.7975] +2024-11-21 15:33:57.072685: Epoch time: 18.56 s +2024-11-21 15:33:57.863376: +2024-11-21 15:33:57.863591: Epoch 912 +2024-11-21 15:33:57.863701: Current learning rate: 0.00897 +2024-11-21 15:34:15.628460: train_loss -0.7701 +2024-11-21 15:34:15.628675: val_loss -0.7541 +2024-11-21 15:34:15.628782: Pseudo dice [0.8285] +2024-11-21 15:34:15.628857: Epoch time: 17.77 s +2024-11-21 15:34:16.422307: +2024-11-21 15:34:16.422517: Epoch 913 +2024-11-21 15:34:16.422628: Current learning rate: 0.00897 +2024-11-21 15:34:34.332997: train_loss -0.771 +2024-11-21 15:34:34.333217: val_loss -0.7725 +2024-11-21 15:34:34.333289: Pseudo dice [0.843] +2024-11-21 15:34:34.333468: Epoch time: 17.91 s +2024-11-21 15:34:35.132116: +2024-11-21 15:34:35.132333: Epoch 914 +2024-11-21 15:34:35.132445: Current learning rate: 0.00897 +2024-11-21 15:34:52.551018: train_loss -0.7635 +2024-11-21 15:34:52.551325: val_loss -0.7661 +2024-11-21 15:34:52.551419: Pseudo dice [0.846] +2024-11-21 15:34:52.551502: Epoch time: 17.42 s +2024-11-21 15:34:53.345543: +2024-11-21 15:34:53.345762: Epoch 915 +2024-11-21 15:34:53.345872: Current learning rate: 0.00896 +2024-11-21 15:35:11.748477: train_loss -0.7547 +2024-11-21 15:35:11.748684: val_loss -0.7529 +2024-11-21 15:35:11.748755: Pseudo dice [0.8431] +2024-11-21 15:35:11.750932: Epoch time: 18.4 s +2024-11-21 15:35:12.600095: +2024-11-21 15:35:12.600322: Epoch 916 +2024-11-21 15:35:12.600456: Current learning rate: 0.00896 +2024-11-21 15:35:31.047174: train_loss -0.75 +2024-11-21 15:35:31.047389: val_loss -0.7384 +2024-11-21 15:35:31.047464: Pseudo dice [0.8297] +2024-11-21 15:35:31.047538: Epoch time: 18.45 s +2024-11-21 15:35:32.245985: +2024-11-21 15:35:32.246224: Epoch 917 +2024-11-21 15:35:32.246334: Current learning rate: 0.00896 +2024-11-21 15:35:50.804449: train_loss -0.7618 +2024-11-21 15:35:50.804691: val_loss -0.7475 +2024-11-21 15:35:50.804769: Pseudo dice [0.8435] +2024-11-21 15:35:50.804851: Epoch time: 18.56 s +2024-11-21 15:35:51.601371: +2024-11-21 15:35:51.601621: Epoch 918 +2024-11-21 15:35:51.601743: Current learning rate: 0.00896 +2024-11-21 15:36:10.357608: train_loss -0.7583 +2024-11-21 15:36:10.357859: val_loss -0.7598 +2024-11-21 15:36:10.357976: Pseudo dice [0.8431] +2024-11-21 15:36:10.358059: Epoch time: 18.76 s +2024-11-21 15:36:11.156870: +2024-11-21 15:36:11.157106: Epoch 919 +2024-11-21 15:36:11.157250: Current learning rate: 0.00896 +2024-11-21 15:36:30.220102: train_loss -0.7645 +2024-11-21 15:36:30.220319: val_loss -0.7392 +2024-11-21 15:36:30.220390: Pseudo dice [0.8398] +2024-11-21 15:36:30.220697: Epoch time: 19.06 s +2024-11-21 15:36:31.181878: +2024-11-21 15:36:31.182103: Epoch 920 +2024-11-21 15:36:31.182210: Current learning rate: 0.00896 +2024-11-21 15:36:50.588290: train_loss -0.7641 +2024-11-21 15:36:50.588525: val_loss -0.7643 +2024-11-21 15:36:50.588601: Pseudo dice [0.839] +2024-11-21 15:36:50.588686: Epoch time: 19.41 s +2024-11-21 15:36:51.386906: +2024-11-21 15:36:51.387105: Epoch 921 +2024-11-21 15:36:51.387221: Current learning rate: 0.00896 +2024-11-21 15:37:09.584734: train_loss -0.7644 +2024-11-21 15:37:09.584946: val_loss -0.7479 +2024-11-21 15:37:09.585023: Pseudo dice [0.8472] +2024-11-21 15:37:09.585099: Epoch time: 18.2 s +2024-11-21 15:37:10.386786: +2024-11-21 15:37:10.387022: Epoch 922 +2024-11-21 15:37:10.387138: Current learning rate: 0.00896 +2024-11-21 15:37:28.900083: train_loss -0.7677 +2024-11-21 15:37:28.900292: val_loss -0.7462 +2024-11-21 15:37:28.900366: Pseudo dice [0.816] +2024-11-21 15:37:28.900442: Epoch time: 18.51 s +2024-11-21 15:37:29.704737: +2024-11-21 15:37:29.705037: Epoch 923 +2024-11-21 15:37:29.705152: Current learning rate: 0.00896 +2024-11-21 15:37:48.530736: train_loss -0.7698 +2024-11-21 15:37:48.530966: val_loss -0.7319 +2024-11-21 15:37:48.531045: Pseudo dice [0.8291] +2024-11-21 15:37:48.531118: Epoch time: 18.83 s +2024-11-21 15:37:49.337215: +2024-11-21 15:37:49.337465: Epoch 924 +2024-11-21 15:37:49.337592: Current learning rate: 0.00895 +2024-11-21 15:38:08.347001: train_loss -0.7613 +2024-11-21 15:38:08.347294: val_loss -0.7904 +2024-11-21 15:38:08.347369: Pseudo dice [0.8534] +2024-11-21 15:38:08.347447: Epoch time: 19.01 s +2024-11-21 15:38:09.247557: +2024-11-21 15:38:09.247846: Epoch 925 +2024-11-21 15:38:09.247956: Current learning rate: 0.00895 +2024-11-21 15:38:28.184281: train_loss -0.7633 +2024-11-21 15:38:28.184500: val_loss -0.7621 +2024-11-21 15:38:28.184574: Pseudo dice [0.8416] +2024-11-21 15:38:28.184649: Epoch time: 18.94 s +2024-11-21 15:38:29.026349: +2024-11-21 15:38:29.026563: Epoch 926 +2024-11-21 15:38:29.026674: Current learning rate: 0.00895 +2024-11-21 15:38:48.577209: train_loss -0.7534 +2024-11-21 15:38:48.577426: val_loss -0.7485 +2024-11-21 15:38:48.577503: Pseudo dice [0.8408] +2024-11-21 15:38:48.577588: Epoch time: 19.55 s +2024-11-21 15:38:49.412845: +2024-11-21 15:38:49.413076: Epoch 927 +2024-11-21 15:38:49.413193: Current learning rate: 0.00895 +2024-11-21 15:39:08.443433: train_loss -0.773 +2024-11-21 15:39:08.443757: val_loss -0.7582 +2024-11-21 15:39:08.443844: Pseudo dice [0.8339] +2024-11-21 15:39:08.443944: Epoch time: 19.03 s +2024-11-21 15:39:09.241394: +2024-11-21 15:39:09.241597: Epoch 928 +2024-11-21 15:39:09.241704: Current learning rate: 0.00895 +2024-11-21 15:39:27.761551: train_loss -0.7629 +2024-11-21 15:39:27.761763: val_loss -0.7551 +2024-11-21 15:39:27.761837: Pseudo dice [0.8302] +2024-11-21 15:39:27.761911: Epoch time: 18.52 s +2024-11-21 15:39:28.946134: +2024-11-21 15:39:28.946383: Epoch 929 +2024-11-21 15:39:28.946500: Current learning rate: 0.00895 +2024-11-21 15:39:47.232651: train_loss -0.7648 +2024-11-21 15:39:47.232871: val_loss -0.7525 +2024-11-21 15:39:47.232947: Pseudo dice [0.8301] +2024-11-21 15:39:47.233084: Epoch time: 18.29 s +2024-11-21 15:39:48.086500: +2024-11-21 15:39:48.086731: Epoch 930 +2024-11-21 15:39:48.086853: Current learning rate: 0.00895 +2024-11-21 15:40:06.292602: train_loss -0.7564 +2024-11-21 15:40:06.292845: val_loss -0.7589 +2024-11-21 15:40:06.292940: Pseudo dice [0.8359] +2024-11-21 15:40:06.293033: Epoch time: 18.21 s +2024-11-21 15:40:07.096361: +2024-11-21 15:40:07.096725: Epoch 931 +2024-11-21 15:40:07.096875: Current learning rate: 0.00895 +2024-11-21 15:40:26.489917: train_loss -0.7654 +2024-11-21 15:40:26.490141: val_loss -0.7624 +2024-11-21 15:40:26.490228: Pseudo dice [0.8428] +2024-11-21 15:40:26.490304: Epoch time: 19.39 s +2024-11-21 15:40:27.289981: +2024-11-21 15:40:27.290207: Epoch 932 +2024-11-21 15:40:27.290322: Current learning rate: 0.00895 +2024-11-21 15:40:45.848789: train_loss -0.763 +2024-11-21 15:40:45.849003: val_loss -0.7322 +2024-11-21 15:40:45.849077: Pseudo dice [0.8238] +2024-11-21 15:40:45.849148: Epoch time: 18.56 s +2024-11-21 15:40:46.648634: +2024-11-21 15:40:46.648861: Epoch 933 +2024-11-21 15:40:46.649002: Current learning rate: 0.00894 +2024-11-21 15:41:04.882951: train_loss -0.7679 +2024-11-21 15:41:04.883219: val_loss -0.7768 +2024-11-21 15:41:04.883292: Pseudo dice [0.8427] +2024-11-21 15:41:04.883364: Epoch time: 18.24 s +2024-11-21 15:41:05.684357: +2024-11-21 15:41:05.684576: Epoch 934 +2024-11-21 15:41:05.684686: Current learning rate: 0.00894 +2024-11-21 15:41:23.639529: train_loss -0.7695 +2024-11-21 15:41:23.639778: val_loss -0.7607 +2024-11-21 15:41:23.639855: Pseudo dice [0.8273] +2024-11-21 15:41:23.639951: Epoch time: 17.96 s +2024-11-21 15:41:24.583930: +2024-11-21 15:41:24.584143: Epoch 935 +2024-11-21 15:41:24.584253: Current learning rate: 0.00894 +2024-11-21 15:41:41.858370: train_loss -0.7589 +2024-11-21 15:41:41.858654: val_loss -0.7788 +2024-11-21 15:41:41.858737: Pseudo dice [0.8366] +2024-11-21 15:41:41.858814: Epoch time: 17.28 s +2024-11-21 15:41:42.865326: +2024-11-21 15:41:42.865549: Epoch 936 +2024-11-21 15:41:42.865659: Current learning rate: 0.00894 +2024-11-21 15:42:00.002668: train_loss -0.7486 +2024-11-21 15:42:00.004387: val_loss -0.7572 +2024-11-21 15:42:00.005183: Pseudo dice [0.8516] +2024-11-21 15:42:00.005311: Epoch time: 17.14 s +2024-11-21 15:42:00.808435: +2024-11-21 15:42:00.808639: Epoch 937 +2024-11-21 15:42:00.808747: Current learning rate: 0.00894 +2024-11-21 15:42:18.765861: train_loss -0.7583 +2024-11-21 15:42:18.766101: val_loss -0.7544 +2024-11-21 15:42:18.766181: Pseudo dice [0.8361] +2024-11-21 15:42:18.766257: Epoch time: 17.96 s +2024-11-21 15:42:19.560385: +2024-11-21 15:42:19.560614: Epoch 938 +2024-11-21 15:42:19.560730: Current learning rate: 0.00894 +2024-11-21 15:42:38.272610: train_loss -0.7375 +2024-11-21 15:42:38.272855: val_loss -0.7208 +2024-11-21 15:42:38.272936: Pseudo dice [0.8195] +2024-11-21 15:42:38.273027: Epoch time: 18.71 s +2024-11-21 15:42:39.073973: +2024-11-21 15:42:39.074192: Epoch 939 +2024-11-21 15:42:39.074310: Current learning rate: 0.00894 +2024-11-21 15:42:58.948899: train_loss -0.7395 +2024-11-21 15:42:58.949192: val_loss -0.7601 +2024-11-21 15:42:58.949281: Pseudo dice [0.8298] +2024-11-21 15:42:58.949360: Epoch time: 19.88 s +2024-11-21 15:42:59.764168: +2024-11-21 15:42:59.764435: Epoch 940 +2024-11-21 15:42:59.764546: Current learning rate: 0.00894 +2024-11-21 15:43:17.824123: train_loss -0.7486 +2024-11-21 15:43:17.824333: val_loss -0.7648 +2024-11-21 15:43:17.824404: Pseudo dice [0.8296] +2024-11-21 15:43:17.824476: Epoch time: 18.06 s +2024-11-21 15:43:19.034050: +2024-11-21 15:43:19.034294: Epoch 941 +2024-11-21 15:43:19.034408: Current learning rate: 0.00893 +2024-11-21 15:43:37.360293: train_loss -0.7637 +2024-11-21 15:43:37.360550: val_loss -0.7696 +2024-11-21 15:43:37.360627: Pseudo dice [0.8453] +2024-11-21 15:43:37.360705: Epoch time: 18.33 s +2024-11-21 15:43:38.331147: +2024-11-21 15:43:38.331389: Epoch 942 +2024-11-21 15:43:38.331506: Current learning rate: 0.00893 +2024-11-21 15:43:56.021434: train_loss -0.7621 +2024-11-21 15:43:56.021637: val_loss -0.7483 +2024-11-21 15:43:56.021715: Pseudo dice [0.8398] +2024-11-21 15:43:56.021786: Epoch time: 17.69 s +2024-11-21 15:43:56.831265: +2024-11-21 15:43:56.831496: Epoch 943 +2024-11-21 15:43:56.831611: Current learning rate: 0.00893 +2024-11-21 15:44:14.421672: train_loss -0.7618 +2024-11-21 15:44:14.421882: val_loss -0.7514 +2024-11-21 15:44:14.421979: Pseudo dice [0.851] +2024-11-21 15:44:14.422093: Epoch time: 17.59 s +2024-11-21 15:44:15.216737: +2024-11-21 15:44:15.216959: Epoch 944 +2024-11-21 15:44:15.217083: Current learning rate: 0.00893 +2024-11-21 15:44:33.640584: train_loss -0.7588 +2024-11-21 15:44:33.640800: val_loss -0.7554 +2024-11-21 15:44:33.640874: Pseudo dice [0.8238] +2024-11-21 15:44:33.640952: Epoch time: 18.42 s +2024-11-21 15:44:34.458982: +2024-11-21 15:44:34.459237: Epoch 945 +2024-11-21 15:44:34.459366: Current learning rate: 0.00893 +2024-11-21 15:44:51.948452: train_loss -0.7569 +2024-11-21 15:44:51.948754: val_loss -0.7429 +2024-11-21 15:44:51.948828: Pseudo dice [0.8474] +2024-11-21 15:44:51.949693: Epoch time: 17.49 s +2024-11-21 15:44:52.754208: +2024-11-21 15:44:52.754452: Epoch 946 +2024-11-21 15:44:52.754562: Current learning rate: 0.00893 +2024-11-21 15:45:10.766136: train_loss -0.7594 +2024-11-21 15:45:10.766346: val_loss -0.7489 +2024-11-21 15:45:10.766421: Pseudo dice [0.8312] +2024-11-21 15:45:10.766497: Epoch time: 18.01 s +2024-11-21 15:45:11.565582: +2024-11-21 15:45:11.565809: Epoch 947 +2024-11-21 15:45:11.565924: Current learning rate: 0.00893 +2024-11-21 15:45:29.518959: train_loss -0.7629 +2024-11-21 15:45:29.519166: val_loss -0.7472 +2024-11-21 15:45:29.519242: Pseudo dice [0.8333] +2024-11-21 15:45:29.519316: Epoch time: 17.95 s +2024-11-21 15:45:30.305791: +2024-11-21 15:45:30.306000: Epoch 948 +2024-11-21 15:45:30.306113: Current learning rate: 0.00893 +2024-11-21 15:45:48.644204: train_loss -0.7563 +2024-11-21 15:45:48.644495: val_loss -0.7541 +2024-11-21 15:45:48.644578: Pseudo dice [0.8421] +2024-11-21 15:45:48.644662: Epoch time: 18.34 s +2024-11-21 15:45:49.441766: +2024-11-21 15:45:49.441964: Epoch 949 +2024-11-21 15:45:49.442073: Current learning rate: 0.00893 +2024-11-21 15:46:07.942862: train_loss -0.7684 +2024-11-21 15:46:07.943080: val_loss -0.7643 +2024-11-21 15:46:07.943157: Pseudo dice [0.8378] +2024-11-21 15:46:07.943234: Epoch time: 18.5 s +2024-11-21 15:46:08.972340: +2024-11-21 15:46:08.972631: Epoch 950 +2024-11-21 15:46:08.972748: Current learning rate: 0.00892 +2024-11-21 15:46:27.553580: train_loss -0.7681 +2024-11-21 15:46:27.555912: val_loss -0.7676 +2024-11-21 15:46:27.556141: Pseudo dice [0.8366] +2024-11-21 15:46:27.556225: Epoch time: 18.58 s +2024-11-21 15:46:28.463886: +2024-11-21 15:46:28.464230: Epoch 951 +2024-11-21 15:46:28.464344: Current learning rate: 0.00892 +2024-11-21 15:46:48.329883: train_loss -0.7641 +2024-11-21 15:46:48.332260: val_loss -0.7644 +2024-11-21 15:46:48.332343: Pseudo dice [0.8311] +2024-11-21 15:46:48.332433: Epoch time: 19.87 s +2024-11-21 15:46:49.186850: +2024-11-21 15:46:49.187206: Epoch 952 +2024-11-21 15:46:49.187330: Current learning rate: 0.00892 +2024-11-21 15:47:06.903442: train_loss -0.76 +2024-11-21 15:47:06.903713: val_loss -0.7637 +2024-11-21 15:47:06.903832: Pseudo dice [0.8426] +2024-11-21 15:47:06.903919: Epoch time: 17.72 s +2024-11-21 15:47:08.084594: +2024-11-21 15:47:08.084814: Epoch 953 +2024-11-21 15:47:08.084923: Current learning rate: 0.00892 +2024-11-21 15:47:26.499983: train_loss -0.7689 +2024-11-21 15:47:26.500234: val_loss -0.7362 +2024-11-21 15:47:26.502477: Pseudo dice [0.8516] +2024-11-21 15:47:26.502613: Epoch time: 18.42 s +2024-11-21 15:47:27.394700: +2024-11-21 15:47:27.394984: Epoch 954 +2024-11-21 15:47:27.395100: Current learning rate: 0.00892 +2024-11-21 15:47:44.975007: train_loss -0.7583 +2024-11-21 15:47:44.975217: val_loss -0.7459 +2024-11-21 15:47:44.975292: Pseudo dice [0.8187] +2024-11-21 15:47:44.975368: Epoch time: 17.58 s +2024-11-21 15:47:45.778791: +2024-11-21 15:47:45.779000: Epoch 955 +2024-11-21 15:47:45.779110: Current learning rate: 0.00892 +2024-11-21 15:48:05.054720: train_loss -0.7581 +2024-11-21 15:48:05.054969: val_loss -0.7316 +2024-11-21 15:48:05.055052: Pseudo dice [0.8265] +2024-11-21 15:48:05.055132: Epoch time: 19.28 s +2024-11-21 15:48:05.860351: +2024-11-21 15:48:05.860573: Epoch 956 +2024-11-21 15:48:05.860685: Current learning rate: 0.00892 +2024-11-21 15:48:23.833238: train_loss -0.7571 +2024-11-21 15:48:23.833480: val_loss -0.7394 +2024-11-21 15:48:23.833555: Pseudo dice [0.8306] +2024-11-21 15:48:23.833631: Epoch time: 17.97 s +2024-11-21 15:48:24.639701: +2024-11-21 15:48:24.639909: Epoch 957 +2024-11-21 15:48:24.640039: Current learning rate: 0.00892 +2024-11-21 15:48:43.195032: train_loss -0.7521 +2024-11-21 15:48:43.195245: val_loss -0.7357 +2024-11-21 15:48:43.195323: Pseudo dice [0.8246] +2024-11-21 15:48:43.195396: Epoch time: 18.56 s +2024-11-21 15:48:44.001927: +2024-11-21 15:48:44.002168: Epoch 958 +2024-11-21 15:48:44.002282: Current learning rate: 0.00892 +2024-11-21 15:49:01.851138: train_loss -0.7624 +2024-11-21 15:49:01.851377: val_loss -0.7536 +2024-11-21 15:49:01.851455: Pseudo dice [0.8363] +2024-11-21 15:49:01.851533: Epoch time: 17.85 s +2024-11-21 15:49:02.662548: +2024-11-21 15:49:02.662782: Epoch 959 +2024-11-21 15:49:02.662896: Current learning rate: 0.00891 +2024-11-21 15:49:21.950626: train_loss -0.7572 +2024-11-21 15:49:21.950907: val_loss -0.7839 +2024-11-21 15:49:21.950987: Pseudo dice [0.8409] +2024-11-21 15:49:21.951072: Epoch time: 19.29 s +2024-11-21 15:49:22.757039: +2024-11-21 15:49:22.757244: Epoch 960 +2024-11-21 15:49:22.757351: Current learning rate: 0.00891 +2024-11-21 15:49:41.968032: train_loss -0.7587 +2024-11-21 15:49:41.970442: val_loss -0.7574 +2024-11-21 15:49:41.970530: Pseudo dice [0.8336] +2024-11-21 15:49:41.970603: Epoch time: 19.21 s +2024-11-21 15:49:42.780696: +2024-11-21 15:49:42.780963: Epoch 961 +2024-11-21 15:49:42.781092: Current learning rate: 0.00891 +2024-11-21 15:50:01.755636: train_loss -0.7616 +2024-11-21 15:50:01.755849: val_loss -0.7666 +2024-11-21 15:50:01.755922: Pseudo dice [0.8483] +2024-11-21 15:50:01.756050: Epoch time: 18.98 s +2024-11-21 15:50:02.562904: +2024-11-21 15:50:02.563122: Epoch 962 +2024-11-21 15:50:02.563236: Current learning rate: 0.00891 +2024-11-21 15:50:20.750804: train_loss -0.7697 +2024-11-21 15:50:20.751055: val_loss -0.762 +2024-11-21 15:50:20.751129: Pseudo dice [0.8408] +2024-11-21 15:50:20.751207: Epoch time: 18.19 s +2024-11-21 15:50:21.558170: +2024-11-21 15:50:21.558387: Epoch 963 +2024-11-21 15:50:21.558500: Current learning rate: 0.00891 +2024-11-21 15:50:40.095539: train_loss -0.7653 +2024-11-21 15:50:40.095749: val_loss -0.7585 +2024-11-21 15:50:40.095820: Pseudo dice [0.8577] +2024-11-21 15:50:40.095957: Epoch time: 18.54 s +2024-11-21 15:50:41.004726: +2024-11-21 15:50:41.004917: Epoch 964 +2024-11-21 15:50:41.005028: Current learning rate: 0.00891 +2024-11-21 15:50:59.436622: train_loss -0.7628 +2024-11-21 15:50:59.436837: val_loss -0.7691 +2024-11-21 15:50:59.436907: Pseudo dice [0.8284] +2024-11-21 15:50:59.436980: Epoch time: 18.43 s +2024-11-21 15:51:00.635871: +2024-11-21 15:51:00.636103: Epoch 965 +2024-11-21 15:51:00.636211: Current learning rate: 0.00891 +2024-11-21 15:51:18.813278: train_loss -0.766 +2024-11-21 15:51:18.814156: val_loss -0.7819 +2024-11-21 15:51:18.814243: Pseudo dice [0.8397] +2024-11-21 15:51:18.814327: Epoch time: 18.18 s +2024-11-21 15:51:19.622902: +2024-11-21 15:51:19.623140: Epoch 966 +2024-11-21 15:51:19.623245: Current learning rate: 0.00891 +2024-11-21 15:51:37.519642: train_loss -0.7707 +2024-11-21 15:51:37.519863: val_loss -0.7773 +2024-11-21 15:51:37.519940: Pseudo dice [0.85] +2024-11-21 15:51:37.520031: Epoch time: 17.9 s +2024-11-21 15:51:38.345089: +2024-11-21 15:51:38.345298: Epoch 967 +2024-11-21 15:51:38.345409: Current learning rate: 0.00891 +2024-11-21 15:51:56.042138: train_loss -0.7694 +2024-11-21 15:51:56.042350: val_loss -0.7717 +2024-11-21 15:51:56.042421: Pseudo dice [0.8384] +2024-11-21 15:51:56.042493: Epoch time: 17.7 s +2024-11-21 15:51:56.848226: +2024-11-21 15:51:56.848459: Epoch 968 +2024-11-21 15:51:56.848566: Current learning rate: 0.0089 +2024-11-21 15:52:14.400233: train_loss -0.7756 +2024-11-21 15:52:14.400473: val_loss -0.7708 +2024-11-21 15:52:14.400546: Pseudo dice [0.825] +2024-11-21 15:52:14.400626: Epoch time: 17.55 s +2024-11-21 15:52:15.249605: +2024-11-21 15:52:15.249838: Epoch 969 +2024-11-21 15:52:15.249947: Current learning rate: 0.0089 +2024-11-21 15:52:32.850967: train_loss -0.771 +2024-11-21 15:52:32.851261: val_loss -0.7244 +2024-11-21 15:52:32.851353: Pseudo dice [0.8225] +2024-11-21 15:52:32.851430: Epoch time: 17.6 s +2024-11-21 15:52:33.683514: +2024-11-21 15:52:33.683747: Epoch 970 +2024-11-21 15:52:33.683855: Current learning rate: 0.0089 +2024-11-21 15:52:52.517985: train_loss -0.7581 +2024-11-21 15:52:52.518203: val_loss -0.7536 +2024-11-21 15:52:52.518280: Pseudo dice [0.8274] +2024-11-21 15:52:52.518353: Epoch time: 18.84 s +2024-11-21 15:52:53.329783: +2024-11-21 15:52:53.329988: Epoch 971 +2024-11-21 15:52:53.330114: Current learning rate: 0.0089 +2024-11-21 15:53:10.690796: train_loss -0.7571 +2024-11-21 15:53:10.691016: val_loss -0.763 +2024-11-21 15:53:10.691095: Pseudo dice [0.8187] +2024-11-21 15:53:10.691246: Epoch time: 17.36 s +2024-11-21 15:53:11.613039: +2024-11-21 15:53:11.613238: Epoch 972 +2024-11-21 15:53:11.613363: Current learning rate: 0.0089 +2024-11-21 15:53:31.143391: train_loss -0.7604 +2024-11-21 15:53:31.143655: val_loss -0.7592 +2024-11-21 15:53:31.143732: Pseudo dice [0.8276] +2024-11-21 15:53:31.143813: Epoch time: 19.53 s +2024-11-21 15:53:31.953699: +2024-11-21 15:53:31.953915: Epoch 973 +2024-11-21 15:53:31.954029: Current learning rate: 0.0089 +2024-11-21 15:53:50.435958: train_loss -0.7668 +2024-11-21 15:53:50.436167: val_loss -0.7573 +2024-11-21 15:53:50.436241: Pseudo dice [0.833] +2024-11-21 15:53:50.436317: Epoch time: 18.48 s +2024-11-21 15:53:51.244569: +2024-11-21 15:53:51.244777: Epoch 974 +2024-11-21 15:53:51.244919: Current learning rate: 0.0089 +2024-11-21 15:54:09.256826: train_loss -0.7721 +2024-11-21 15:54:09.257062: val_loss -0.7583 +2024-11-21 15:54:09.257143: Pseudo dice [0.8418] +2024-11-21 15:54:09.257224: Epoch time: 18.01 s +2024-11-21 15:54:10.066939: +2024-11-21 15:54:10.067339: Epoch 975 +2024-11-21 15:54:10.067453: Current learning rate: 0.0089 +2024-11-21 15:54:28.822669: train_loss -0.7681 +2024-11-21 15:54:28.822931: val_loss -0.7444 +2024-11-21 15:54:28.828197: Pseudo dice [0.8398] +2024-11-21 15:54:28.828376: Epoch time: 18.76 s +2024-11-21 15:54:29.822345: +2024-11-21 15:54:29.822556: Epoch 976 +2024-11-21 15:54:29.822664: Current learning rate: 0.00889 +2024-11-21 15:54:48.635096: train_loss -0.7693 +2024-11-21 15:54:48.635300: val_loss -0.7693 +2024-11-21 15:54:48.635373: Pseudo dice [0.8249] +2024-11-21 15:54:48.635449: Epoch time: 18.81 s +2024-11-21 15:54:49.915327: +2024-11-21 15:54:49.915569: Epoch 977 +2024-11-21 15:54:49.915679: Current learning rate: 0.00889 +2024-11-21 15:55:09.083388: train_loss -0.7675 +2024-11-21 15:55:09.084942: val_loss -0.7726 +2024-11-21 15:55:09.085135: Pseudo dice [0.8462] +2024-11-21 15:55:09.085214: Epoch time: 19.17 s +2024-11-21 15:55:09.887476: +2024-11-21 15:55:09.887698: Epoch 978 +2024-11-21 15:55:09.887805: Current learning rate: 0.00889 +2024-11-21 15:55:29.055191: train_loss -0.7707 +2024-11-21 15:55:29.055440: val_loss -0.7781 +2024-11-21 15:55:29.055516: Pseudo dice [0.8411] +2024-11-21 15:55:29.055600: Epoch time: 19.17 s +2024-11-21 15:55:29.863466: +2024-11-21 15:55:29.863715: Epoch 979 +2024-11-21 15:55:29.863828: Current learning rate: 0.00889 +2024-11-21 15:55:47.914189: train_loss -0.7688 +2024-11-21 15:55:47.914391: val_loss -0.7525 +2024-11-21 15:55:47.914463: Pseudo dice [0.847] +2024-11-21 15:55:47.915236: Epoch time: 18.05 s +2024-11-21 15:55:48.723773: +2024-11-21 15:55:48.723995: Epoch 980 +2024-11-21 15:55:48.724105: Current learning rate: 0.00889 +2024-11-21 15:56:06.808467: train_loss -0.765 +2024-11-21 15:56:06.808684: val_loss -0.7551 +2024-11-21 15:56:06.808762: Pseudo dice [0.8176] +2024-11-21 15:56:06.808838: Epoch time: 18.09 s +2024-11-21 15:56:07.621625: +2024-11-21 15:56:07.621842: Epoch 981 +2024-11-21 15:56:07.621951: Current learning rate: 0.00889 +2024-11-21 15:56:25.615575: train_loss -0.7572 +2024-11-21 15:56:25.615783: val_loss -0.7672 +2024-11-21 15:56:25.615859: Pseudo dice [0.8443] +2024-11-21 15:56:25.615934: Epoch time: 17.99 s +2024-11-21 15:56:26.425029: +2024-11-21 15:56:26.425254: Epoch 982 +2024-11-21 15:56:26.425369: Current learning rate: 0.00889 +2024-11-21 15:56:44.383476: train_loss -0.7534 +2024-11-21 15:56:44.385890: val_loss -0.77 +2024-11-21 15:56:44.385989: Pseudo dice [0.842] +2024-11-21 15:56:44.386088: Epoch time: 17.96 s +2024-11-21 15:56:45.352197: +2024-11-21 15:56:45.352399: Epoch 983 +2024-11-21 15:56:45.352510: Current learning rate: 0.00889 +2024-11-21 15:57:04.152098: train_loss -0.7578 +2024-11-21 15:57:04.152312: val_loss -0.7303 +2024-11-21 15:57:04.152387: Pseudo dice [0.8136] +2024-11-21 15:57:04.152462: Epoch time: 18.8 s +2024-11-21 15:57:04.963617: +2024-11-21 15:57:04.963860: Epoch 984 +2024-11-21 15:57:04.963969: Current learning rate: 0.00889 +2024-11-21 15:57:23.338282: train_loss -0.7311 +2024-11-21 15:57:23.338498: val_loss -0.7508 +2024-11-21 15:57:23.338574: Pseudo dice [0.8352] +2024-11-21 15:57:23.338649: Epoch time: 18.38 s +2024-11-21 15:57:24.138880: +2024-11-21 15:57:24.139117: Epoch 985 +2024-11-21 15:57:24.139232: Current learning rate: 0.00888 +2024-11-21 15:57:43.517498: train_loss -0.7483 +2024-11-21 15:57:43.517702: val_loss -0.7518 +2024-11-21 15:57:43.517777: Pseudo dice [0.8439] +2024-11-21 15:57:43.517855: Epoch time: 19.38 s +2024-11-21 15:57:44.322912: +2024-11-21 15:57:44.323137: Epoch 986 +2024-11-21 15:57:44.323250: Current learning rate: 0.00888 +2024-11-21 15:58:01.814376: train_loss -0.7402 +2024-11-21 15:58:01.814611: val_loss -0.7735 +2024-11-21 15:58:01.814688: Pseudo dice [0.8499] +2024-11-21 15:58:01.814768: Epoch time: 17.49 s +2024-11-21 15:58:02.624567: +2024-11-21 15:58:02.624780: Epoch 987 +2024-11-21 15:58:02.624895: Current learning rate: 0.00888 +2024-11-21 15:58:21.463776: train_loss -0.7592 +2024-11-21 15:58:21.463982: val_loss -0.7494 +2024-11-21 15:58:21.464063: Pseudo dice [0.8392] +2024-11-21 15:58:21.464136: Epoch time: 18.84 s +2024-11-21 15:58:22.264617: +2024-11-21 15:58:22.264844: Epoch 988 +2024-11-21 15:58:22.264962: Current learning rate: 0.00888 +2024-11-21 15:58:40.547381: train_loss -0.763 +2024-11-21 15:58:40.547597: val_loss -0.7413 +2024-11-21 15:58:40.547670: Pseudo dice [0.8345] +2024-11-21 15:58:40.547744: Epoch time: 18.28 s +2024-11-21 15:58:41.796695: +2024-11-21 15:58:41.796950: Epoch 989 +2024-11-21 15:58:41.797067: Current learning rate: 0.00888 +2024-11-21 15:58:59.695014: train_loss -0.7644 +2024-11-21 15:58:59.695263: val_loss -0.7558 +2024-11-21 15:58:59.695335: Pseudo dice [0.8377] +2024-11-21 15:58:59.695414: Epoch time: 17.9 s +2024-11-21 15:59:00.500945: +2024-11-21 15:59:00.501150: Epoch 990 +2024-11-21 15:59:00.501260: Current learning rate: 0.00888 +2024-11-21 15:59:18.595357: train_loss -0.7685 +2024-11-21 15:59:18.595559: val_loss -0.7469 +2024-11-21 15:59:18.595631: Pseudo dice [0.8442] +2024-11-21 15:59:18.595704: Epoch time: 18.1 s +2024-11-21 15:59:19.398044: +2024-11-21 15:59:19.398269: Epoch 991 +2024-11-21 15:59:19.398378: Current learning rate: 0.00888 +2024-11-21 15:59:37.928693: train_loss -0.7666 +2024-11-21 15:59:37.928907: val_loss -0.761 +2024-11-21 15:59:37.928985: Pseudo dice [0.8343] +2024-11-21 15:59:37.929069: Epoch time: 18.53 s +2024-11-21 15:59:38.793380: +2024-11-21 15:59:38.793616: Epoch 992 +2024-11-21 15:59:38.793741: Current learning rate: 0.00888 +2024-11-21 15:59:57.915054: train_loss -0.765 +2024-11-21 15:59:57.939044: val_loss -0.7699 +2024-11-21 15:59:57.939160: Pseudo dice [0.8193] +2024-11-21 15:59:57.939245: Epoch time: 19.12 s +2024-11-21 15:59:58.750383: +2024-11-21 15:59:58.750613: Epoch 993 +2024-11-21 15:59:58.750730: Current learning rate: 0.00888 +2024-11-21 16:00:17.385025: train_loss -0.7589 +2024-11-21 16:00:17.385310: val_loss -0.7577 +2024-11-21 16:00:17.385388: Pseudo dice [0.8337] +2024-11-21 16:00:17.385466: Epoch time: 18.64 s +2024-11-21 16:00:18.199087: +2024-11-21 16:00:18.199304: Epoch 994 +2024-11-21 16:00:18.199415: Current learning rate: 0.00887 +2024-11-21 16:00:35.958878: train_loss -0.7563 +2024-11-21 16:00:35.959832: val_loss -0.7418 +2024-11-21 16:00:35.959910: Pseudo dice [0.8211] +2024-11-21 16:00:35.959984: Epoch time: 17.76 s +2024-11-21 16:00:36.767057: +2024-11-21 16:00:36.767279: Epoch 995 +2024-11-21 16:00:36.767395: Current learning rate: 0.00887 +2024-11-21 16:00:56.346308: train_loss -0.753 +2024-11-21 16:00:56.346530: val_loss -0.7601 +2024-11-21 16:00:56.346604: Pseudo dice [0.8404] +2024-11-21 16:00:56.346677: Epoch time: 19.58 s +2024-11-21 16:00:57.162583: +2024-11-21 16:00:57.162838: Epoch 996 +2024-11-21 16:00:57.162963: Current learning rate: 0.00887 +2024-11-21 16:01:15.464076: train_loss -0.7607 +2024-11-21 16:01:15.464318: val_loss -0.7472 +2024-11-21 16:01:15.464391: Pseudo dice [0.8479] +2024-11-21 16:01:15.464471: Epoch time: 18.3 s +2024-11-21 16:01:16.276917: +2024-11-21 16:01:16.277147: Epoch 997 +2024-11-21 16:01:16.277258: Current learning rate: 0.00887 +2024-11-21 16:01:34.377479: train_loss -0.7581 +2024-11-21 16:01:34.377694: val_loss -0.7425 +2024-11-21 16:01:34.377767: Pseudo dice [0.8487] +2024-11-21 16:01:34.377842: Epoch time: 18.1 s +2024-11-21 16:01:35.196515: +2024-11-21 16:01:35.196814: Epoch 998 +2024-11-21 16:01:35.196932: Current learning rate: 0.00887 +2024-11-21 16:01:53.098166: train_loss -0.7672 +2024-11-21 16:01:53.098378: val_loss -0.771 +2024-11-21 16:01:53.098453: Pseudo dice [0.8391] +2024-11-21 16:01:53.098528: Epoch time: 17.9 s +2024-11-21 16:01:53.905767: +2024-11-21 16:01:53.905983: Epoch 999 +2024-11-21 16:01:53.906101: Current learning rate: 0.00887 +2024-11-21 16:02:12.933112: train_loss -0.7666 +2024-11-21 16:02:12.933374: val_loss -0.7479 +2024-11-21 16:02:12.933450: Pseudo dice [0.8333] +2024-11-21 16:02:12.933534: Epoch time: 19.03 s +2024-11-21 16:02:13.971966: +2024-11-21 16:02:13.972203: Epoch 1000 +2024-11-21 16:02:13.972329: Current learning rate: 0.00887 +2024-11-21 16:02:33.108292: train_loss -0.7732 +2024-11-21 16:02:33.108531: val_loss -0.7667 +2024-11-21 16:02:33.108610: Pseudo dice [0.8464] +2024-11-21 16:02:33.108686: Epoch time: 19.14 s +2024-11-21 16:02:33.914091: +2024-11-21 16:02:33.914324: Epoch 1001 +2024-11-21 16:02:33.914432: Current learning rate: 0.00887 +2024-11-21 16:02:52.574376: train_loss -0.7649 +2024-11-21 16:02:52.574603: val_loss -0.734 +2024-11-21 16:02:52.574684: Pseudo dice [0.8309] +2024-11-21 16:02:52.574765: Epoch time: 18.66 s +2024-11-21 16:02:53.459609: +2024-11-21 16:02:53.459834: Epoch 1002 +2024-11-21 16:02:53.459947: Current learning rate: 0.00887 +2024-11-21 16:03:11.592112: train_loss -0.7717 +2024-11-21 16:03:11.592350: val_loss -0.7393 +2024-11-21 16:03:11.592431: Pseudo dice [0.8521] +2024-11-21 16:03:11.592516: Epoch time: 18.13 s +2024-11-21 16:03:12.404475: +2024-11-21 16:03:12.404698: Epoch 1003 +2024-11-21 16:03:12.404811: Current learning rate: 0.00886 +2024-11-21 16:03:30.179388: train_loss -0.7735 +2024-11-21 16:03:30.179604: val_loss -0.7565 +2024-11-21 16:03:30.179704: Pseudo dice [0.832] +2024-11-21 16:03:30.179782: Epoch time: 17.78 s +2024-11-21 16:03:30.993487: +2024-11-21 16:03:30.993706: Epoch 1004 +2024-11-21 16:03:30.993813: Current learning rate: 0.00886 +2024-11-21 16:03:49.455536: train_loss -0.7601 +2024-11-21 16:03:49.455750: val_loss -0.7653 +2024-11-21 16:03:49.455823: Pseudo dice [0.8426] +2024-11-21 16:03:49.455897: Epoch time: 18.46 s +2024-11-21 16:03:50.292426: +2024-11-21 16:03:50.292653: Epoch 1005 +2024-11-21 16:03:50.292763: Current learning rate: 0.00886 +2024-11-21 16:04:08.306908: train_loss -0.7656 +2024-11-21 16:04:08.307122: val_loss -0.7561 +2024-11-21 16:04:08.307197: Pseudo dice [0.8475] +2024-11-21 16:04:08.307272: Epoch time: 18.02 s +2024-11-21 16:04:09.125019: +2024-11-21 16:04:09.125435: Epoch 1006 +2024-11-21 16:04:09.125558: Current learning rate: 0.00886 +2024-11-21 16:04:28.550075: train_loss -0.7527 +2024-11-21 16:04:28.550315: val_loss -0.7624 +2024-11-21 16:04:28.550391: Pseudo dice [0.836] +2024-11-21 16:04:28.550472: Epoch time: 19.43 s +2024-11-21 16:04:29.360100: +2024-11-21 16:04:29.360343: Epoch 1007 +2024-11-21 16:04:29.360456: Current learning rate: 0.00886 +2024-11-21 16:04:48.430327: train_loss -0.7526 +2024-11-21 16:04:48.430548: val_loss -0.7439 +2024-11-21 16:04:48.430624: Pseudo dice [0.8289] +2024-11-21 16:04:48.430700: Epoch time: 19.07 s +2024-11-21 16:04:49.256080: +2024-11-21 16:04:49.256311: Epoch 1008 +2024-11-21 16:04:49.256424: Current learning rate: 0.00886 +2024-11-21 16:05:07.516299: train_loss -0.7581 +2024-11-21 16:05:07.516503: val_loss -0.7457 +2024-11-21 16:05:07.516574: Pseudo dice [0.8292] +2024-11-21 16:05:07.516698: Epoch time: 18.26 s +2024-11-21 16:05:08.322979: +2024-11-21 16:05:08.323245: Epoch 1009 +2024-11-21 16:05:08.323366: Current learning rate: 0.00886 +2024-11-21 16:05:26.277435: train_loss -0.7615 +2024-11-21 16:05:26.277685: val_loss -0.7783 +2024-11-21 16:05:26.277766: Pseudo dice [0.8493] +2024-11-21 16:05:26.277843: Epoch time: 17.96 s +2024-11-21 16:05:27.090624: +2024-11-21 16:05:27.090870: Epoch 1010 +2024-11-21 16:05:27.091003: Current learning rate: 0.00886 +2024-11-21 16:05:45.281356: train_loss -0.7683 +2024-11-21 16:05:45.281579: val_loss -0.7403 +2024-11-21 16:05:45.281653: Pseudo dice [0.8152] +2024-11-21 16:05:45.281730: Epoch time: 18.19 s +2024-11-21 16:05:46.093608: +2024-11-21 16:05:46.093802: Epoch 1011 +2024-11-21 16:05:46.093908: Current learning rate: 0.00886 +2024-11-21 16:06:04.583158: train_loss -0.7643 +2024-11-21 16:06:04.583462: val_loss -0.7573 +2024-11-21 16:06:04.583541: Pseudo dice [0.8287] +2024-11-21 16:06:04.583616: Epoch time: 18.49 s +2024-11-21 16:06:05.828932: +2024-11-21 16:06:05.829191: Epoch 1012 +2024-11-21 16:06:05.829307: Current learning rate: 0.00885 +2024-11-21 16:06:25.163044: train_loss -0.7667 +2024-11-21 16:06:25.163269: val_loss -0.7218 +2024-11-21 16:06:25.163342: Pseudo dice [0.8424] +2024-11-21 16:06:25.163414: Epoch time: 19.33 s +2024-11-21 16:06:26.064424: +2024-11-21 16:06:26.064640: Epoch 1013 +2024-11-21 16:06:26.064757: Current learning rate: 0.00885 +2024-11-21 16:06:44.770293: train_loss -0.7633 +2024-11-21 16:06:44.770547: val_loss -0.7605 +2024-11-21 16:06:44.770629: Pseudo dice [0.8278] +2024-11-21 16:06:44.770713: Epoch time: 18.71 s +2024-11-21 16:06:45.589290: +2024-11-21 16:06:45.589511: Epoch 1014 +2024-11-21 16:06:45.589625: Current learning rate: 0.00885 +2024-11-21 16:07:04.680622: train_loss -0.7699 +2024-11-21 16:07:04.686035: val_loss -0.756 +2024-11-21 16:07:04.686171: Pseudo dice [0.8465] +2024-11-21 16:07:04.686259: Epoch time: 19.09 s +2024-11-21 16:07:05.530745: +2024-11-21 16:07:05.530967: Epoch 1015 +2024-11-21 16:07:05.531085: Current learning rate: 0.00885 +2024-11-21 16:07:24.500618: train_loss -0.7637 +2024-11-21 16:07:24.500830: val_loss -0.7733 +2024-11-21 16:07:24.500902: Pseudo dice [0.8334] +2024-11-21 16:07:24.500975: Epoch time: 18.97 s +2024-11-21 16:07:25.311732: +2024-11-21 16:07:25.311949: Epoch 1016 +2024-11-21 16:07:25.312064: Current learning rate: 0.00885 +2024-11-21 16:07:44.411045: train_loss -0.774 +2024-11-21 16:07:44.411257: val_loss -0.7664 +2024-11-21 16:07:44.411330: Pseudo dice [0.8439] +2024-11-21 16:07:44.411403: Epoch time: 19.1 s +2024-11-21 16:07:45.224058: +2024-11-21 16:07:45.224287: Epoch 1017 +2024-11-21 16:07:45.224402: Current learning rate: 0.00885 +2024-11-21 16:08:04.058596: train_loss -0.7619 +2024-11-21 16:08:04.058909: val_loss -0.7628 +2024-11-21 16:08:04.058995: Pseudo dice [0.8451] +2024-11-21 16:08:04.059077: Epoch time: 18.84 s +2024-11-21 16:08:04.877455: +2024-11-21 16:08:04.877690: Epoch 1018 +2024-11-21 16:08:04.877804: Current learning rate: 0.00885 +2024-11-21 16:08:23.503757: train_loss -0.7642 +2024-11-21 16:08:23.503958: val_loss -0.743 +2024-11-21 16:08:23.504065: Pseudo dice [0.8477] +2024-11-21 16:08:23.504138: Epoch time: 18.63 s +2024-11-21 16:08:24.315130: +2024-11-21 16:08:24.315368: Epoch 1019 +2024-11-21 16:08:24.315479: Current learning rate: 0.00885 +2024-11-21 16:08:42.443519: train_loss -0.7575 +2024-11-21 16:08:42.443732: val_loss -0.7399 +2024-11-21 16:08:42.443803: Pseudo dice [0.8478] +2024-11-21 16:08:42.443876: Epoch time: 18.13 s +2024-11-21 16:08:43.279707: +2024-11-21 16:08:43.279905: Epoch 1020 +2024-11-21 16:08:43.280016: Current learning rate: 0.00884 +2024-11-21 16:09:01.412925: train_loss -0.7639 +2024-11-21 16:09:01.413146: val_loss -0.7515 +2024-11-21 16:09:01.413224: Pseudo dice [0.8341] +2024-11-21 16:09:01.413301: Epoch time: 18.13 s +2024-11-21 16:09:02.224039: +2024-11-21 16:09:02.224261: Epoch 1021 +2024-11-21 16:09:02.224372: Current learning rate: 0.00884 +2024-11-21 16:09:21.543046: train_loss -0.7651 +2024-11-21 16:09:21.543294: val_loss -0.7586 +2024-11-21 16:09:21.548534: Pseudo dice [0.8414] +2024-11-21 16:09:21.548718: Epoch time: 19.32 s +2024-11-21 16:09:22.378270: +2024-11-21 16:09:22.378486: Epoch 1022 +2024-11-21 16:09:22.378599: Current learning rate: 0.00884 +2024-11-21 16:09:40.932321: train_loss -0.7661 +2024-11-21 16:09:40.932528: val_loss -0.7502 +2024-11-21 16:09:40.932599: Pseudo dice [0.8345] +2024-11-21 16:09:40.932670: Epoch time: 18.55 s +2024-11-21 16:09:41.748275: +2024-11-21 16:09:41.748469: Epoch 1023 +2024-11-21 16:09:41.748585: Current learning rate: 0.00884 +2024-11-21 16:09:59.883016: train_loss -0.7559 +2024-11-21 16:09:59.883222: val_loss -0.7577 +2024-11-21 16:09:59.883306: Pseudo dice [0.8412] +2024-11-21 16:09:59.883714: Epoch time: 18.14 s +2024-11-21 16:10:00.709436: +2024-11-21 16:10:00.709664: Epoch 1024 +2024-11-21 16:10:00.709775: Current learning rate: 0.00884 +2024-11-21 16:10:20.115847: train_loss -0.7665 +2024-11-21 16:10:20.116094: val_loss -0.7619 +2024-11-21 16:10:20.116174: Pseudo dice [0.843] +2024-11-21 16:10:20.116255: Epoch time: 19.41 s +2024-11-21 16:10:20.931769: +2024-11-21 16:10:20.932024: Epoch 1025 +2024-11-21 16:10:20.932136: Current learning rate: 0.00884 +2024-11-21 16:10:38.568655: train_loss -0.7592 +2024-11-21 16:10:38.568861: val_loss -0.7573 +2024-11-21 16:10:38.568933: Pseudo dice [0.8354] +2024-11-21 16:10:38.569014: Epoch time: 17.64 s +2024-11-21 16:10:39.375983: +2024-11-21 16:10:39.376228: Epoch 1026 +2024-11-21 16:10:39.376335: Current learning rate: 0.00884 +2024-11-21 16:10:58.317764: train_loss -0.7759 +2024-11-21 16:10:58.318063: val_loss -0.7666 +2024-11-21 16:10:58.318145: Pseudo dice [0.8459] +2024-11-21 16:10:58.318221: Epoch time: 18.94 s +2024-11-21 16:10:59.133064: +2024-11-21 16:10:59.133277: Epoch 1027 +2024-11-21 16:10:59.133387: Current learning rate: 0.00884 +2024-11-21 16:11:17.215513: train_loss -0.7674 +2024-11-21 16:11:17.215764: val_loss -0.7493 +2024-11-21 16:11:17.215844: Pseudo dice [0.85] +2024-11-21 16:11:17.215933: Epoch time: 18.08 s +2024-11-21 16:11:18.173359: +2024-11-21 16:11:18.173600: Epoch 1028 +2024-11-21 16:11:18.173711: Current learning rate: 0.00884 +2024-11-21 16:11:36.980125: train_loss -0.7659 +2024-11-21 16:11:36.980356: val_loss -0.7412 +2024-11-21 16:11:36.980429: Pseudo dice [0.8461] +2024-11-21 16:11:36.980503: Epoch time: 18.81 s +2024-11-21 16:11:37.792742: +2024-11-21 16:11:37.792958: Epoch 1029 +2024-11-21 16:11:37.793071: Current learning rate: 0.00883 +2024-11-21 16:11:55.952341: train_loss -0.7632 +2024-11-21 16:11:55.952549: val_loss -0.7608 +2024-11-21 16:11:55.952627: Pseudo dice [0.8265] +2024-11-21 16:11:55.952707: Epoch time: 18.16 s +2024-11-21 16:11:56.761090: +2024-11-21 16:11:56.761331: Epoch 1030 +2024-11-21 16:11:56.761441: Current learning rate: 0.00883 +2024-11-21 16:12:14.798788: train_loss -0.7659 +2024-11-21 16:12:14.798999: val_loss -0.7556 +2024-11-21 16:12:14.799098: Pseudo dice [0.8248] +2024-11-21 16:12:14.799175: Epoch time: 18.04 s +2024-11-21 16:12:15.609619: +2024-11-21 16:12:15.609838: Epoch 1031 +2024-11-21 16:12:15.609947: Current learning rate: 0.00883 +2024-11-21 16:12:33.589568: train_loss -0.7555 +2024-11-21 16:12:33.589807: val_loss -0.7608 +2024-11-21 16:12:33.589890: Pseudo dice [0.8342] +2024-11-21 16:12:33.589975: Epoch time: 17.98 s +2024-11-21 16:12:34.401742: +2024-11-21 16:12:34.401959: Epoch 1032 +2024-11-21 16:12:34.402068: Current learning rate: 0.00883 +2024-11-21 16:12:53.337878: train_loss -0.7634 +2024-11-21 16:12:53.339559: val_loss -0.7345 +2024-11-21 16:12:53.339643: Pseudo dice [0.834] +2024-11-21 16:12:53.339749: Epoch time: 18.94 s +2024-11-21 16:12:54.156877: +2024-11-21 16:12:54.157089: Epoch 1033 +2024-11-21 16:12:54.157196: Current learning rate: 0.00883 +2024-11-21 16:13:13.142007: train_loss -0.7625 +2024-11-21 16:13:13.142216: val_loss -0.7623 +2024-11-21 16:13:13.142290: Pseudo dice [0.8315] +2024-11-21 16:13:13.142365: Epoch time: 18.99 s +2024-11-21 16:13:13.951760: +2024-11-21 16:13:13.951984: Epoch 1034 +2024-11-21 16:13:13.952102: Current learning rate: 0.00883 +2024-11-21 16:13:32.355936: train_loss -0.757 +2024-11-21 16:13:32.356171: val_loss -0.7428 +2024-11-21 16:13:32.356246: Pseudo dice [0.8456] +2024-11-21 16:13:32.356326: Epoch time: 18.4 s +2024-11-21 16:13:33.423545: +2024-11-21 16:13:33.423719: Epoch 1035 +2024-11-21 16:13:33.423810: Current learning rate: 0.00883 +2024-11-21 16:13:51.520480: train_loss -0.7393 +2024-11-21 16:13:51.520683: val_loss -0.751 +2024-11-21 16:13:51.520777: Pseudo dice [0.8246] +2024-11-21 16:13:51.520915: Epoch time: 18.1 s +2024-11-21 16:13:52.325844: +2024-11-21 16:13:52.326057: Epoch 1036 +2024-11-21 16:13:52.326166: Current learning rate: 0.00883 +2024-11-21 16:14:10.871081: train_loss -0.7459 +2024-11-21 16:14:10.871296: val_loss -0.7268 +2024-11-21 16:14:10.871382: Pseudo dice [0.8296] +2024-11-21 16:14:10.871458: Epoch time: 18.55 s +2024-11-21 16:14:11.692021: +2024-11-21 16:14:11.692325: Epoch 1037 +2024-11-21 16:14:11.692436: Current learning rate: 0.00883 +2024-11-21 16:14:30.952876: train_loss -0.7524 +2024-11-21 16:14:30.953089: val_loss -0.7571 +2024-11-21 16:14:30.953163: Pseudo dice [0.8402] +2024-11-21 16:14:30.953237: Epoch time: 19.26 s +2024-11-21 16:14:31.774346: +2024-11-21 16:14:31.774564: Epoch 1038 +2024-11-21 16:14:31.774684: Current learning rate: 0.00882 +2024-11-21 16:14:49.240150: train_loss -0.7595 +2024-11-21 16:14:49.242567: val_loss -0.7311 +2024-11-21 16:14:49.242690: Pseudo dice [0.8372] +2024-11-21 16:14:49.242779: Epoch time: 17.47 s +2024-11-21 16:14:50.260588: +2024-11-21 16:14:50.260808: Epoch 1039 +2024-11-21 16:14:50.260916: Current learning rate: 0.00882 +2024-11-21 16:15:08.624806: train_loss -0.7449 +2024-11-21 16:15:08.625030: val_loss -0.7468 +2024-11-21 16:15:08.625112: Pseudo dice [0.8314] +2024-11-21 16:15:08.625210: Epoch time: 18.37 s +2024-11-21 16:15:09.437907: +2024-11-21 16:15:09.438148: Epoch 1040 +2024-11-21 16:15:09.438258: Current learning rate: 0.00882 +2024-11-21 16:15:28.570406: train_loss -0.7628 +2024-11-21 16:15:28.570626: val_loss -0.7357 +2024-11-21 16:15:28.570699: Pseudo dice [0.8035] +2024-11-21 16:15:28.570774: Epoch time: 19.13 s +2024-11-21 16:15:29.379949: +2024-11-21 16:15:29.380195: Epoch 1041 +2024-11-21 16:15:29.380315: Current learning rate: 0.00882 +2024-11-21 16:15:46.975256: train_loss -0.7587 +2024-11-21 16:15:46.975473: val_loss -0.7452 +2024-11-21 16:15:46.975551: Pseudo dice [0.8246] +2024-11-21 16:15:46.975635: Epoch time: 17.6 s +2024-11-21 16:15:47.787403: +2024-11-21 16:15:47.787628: Epoch 1042 +2024-11-21 16:15:47.787735: Current learning rate: 0.00882 +2024-11-21 16:16:06.115427: train_loss -0.7619 +2024-11-21 16:16:06.115665: val_loss -0.755 +2024-11-21 16:16:06.115738: Pseudo dice [0.8412] +2024-11-21 16:16:06.115815: Epoch time: 18.33 s +2024-11-21 16:16:06.931915: +2024-11-21 16:16:06.932179: Epoch 1043 +2024-11-21 16:16:06.932297: Current learning rate: 0.00882 +2024-11-21 16:16:24.063270: train_loss -0.7701 +2024-11-21 16:16:24.063479: val_loss -0.7571 +2024-11-21 16:16:24.063558: Pseudo dice [0.8438] +2024-11-21 16:16:24.063701: Epoch time: 17.13 s +2024-11-21 16:16:24.873889: +2024-11-21 16:16:24.874098: Epoch 1044 +2024-11-21 16:16:24.874207: Current learning rate: 0.00882 +2024-11-21 16:16:44.882237: train_loss -0.7557 +2024-11-21 16:16:44.882442: val_loss -0.7631 +2024-11-21 16:16:44.882526: Pseudo dice [0.8306] +2024-11-21 16:16:44.882599: Epoch time: 20.01 s +2024-11-21 16:16:45.691535: +2024-11-21 16:16:45.691763: Epoch 1045 +2024-11-21 16:16:45.691866: Current learning rate: 0.00882 +2024-11-21 16:17:03.607544: train_loss -0.7599 +2024-11-21 16:17:03.607778: val_loss -0.768 +2024-11-21 16:17:03.607867: Pseudo dice [0.8489] +2024-11-21 16:17:03.607947: Epoch time: 17.92 s +2024-11-21 16:17:04.457355: +2024-11-21 16:17:04.457567: Epoch 1046 +2024-11-21 16:17:04.457674: Current learning rate: 0.00882 +2024-11-21 16:17:22.254345: train_loss -0.7553 +2024-11-21 16:17:22.254552: val_loss -0.7554 +2024-11-21 16:17:22.254628: Pseudo dice [0.8374] +2024-11-21 16:17:22.254706: Epoch time: 17.8 s +2024-11-21 16:17:23.483377: +2024-11-21 16:17:23.483592: Epoch 1047 +2024-11-21 16:17:23.483698: Current learning rate: 0.00881 +2024-11-21 16:17:41.380408: train_loss -0.7621 +2024-11-21 16:17:41.380645: val_loss -0.7491 +2024-11-21 16:17:41.380721: Pseudo dice [0.8333] +2024-11-21 16:17:41.380796: Epoch time: 17.9 s +2024-11-21 16:17:42.261032: +2024-11-21 16:17:42.261247: Epoch 1048 +2024-11-21 16:17:42.261355: Current learning rate: 0.00881 +2024-11-21 16:18:00.137733: train_loss -0.7681 +2024-11-21 16:18:00.137989: val_loss -0.7677 +2024-11-21 16:18:00.138075: Pseudo dice [0.8462] +2024-11-21 16:18:00.143332: Epoch time: 17.88 s +2024-11-21 16:18:01.074397: +2024-11-21 16:18:01.074612: Epoch 1049 +2024-11-21 16:18:01.074725: Current learning rate: 0.00881 +2024-11-21 16:18:18.726012: train_loss -0.7746 +2024-11-21 16:18:18.726216: val_loss -0.7697 +2024-11-21 16:18:18.726287: Pseudo dice [0.8352] +2024-11-21 16:18:18.726654: Epoch time: 17.65 s +2024-11-21 16:18:19.839706: +2024-11-21 16:18:19.839929: Epoch 1050 +2024-11-21 16:18:19.840039: Current learning rate: 0.00881 +2024-11-21 16:18:40.267470: train_loss -0.7659 +2024-11-21 16:18:40.267710: val_loss -0.752 +2024-11-21 16:18:40.267784: Pseudo dice [0.8464] +2024-11-21 16:18:40.267860: Epoch time: 20.43 s +2024-11-21 16:18:41.241348: +2024-11-21 16:18:41.241582: Epoch 1051 +2024-11-21 16:18:41.241685: Current learning rate: 0.00881 +2024-11-21 16:18:59.784334: train_loss -0.7743 +2024-11-21 16:18:59.784551: val_loss -0.746 +2024-11-21 16:18:59.784642: Pseudo dice [0.8361] +2024-11-21 16:18:59.784717: Epoch time: 18.54 s +2024-11-21 16:19:00.594772: +2024-11-21 16:19:00.595002: Epoch 1052 +2024-11-21 16:19:00.595110: Current learning rate: 0.00881 +2024-11-21 16:19:18.464427: train_loss -0.7524 +2024-11-21 16:19:18.464687: val_loss -0.7589 +2024-11-21 16:19:18.464770: Pseudo dice [0.8363] +2024-11-21 16:19:18.464853: Epoch time: 17.87 s +2024-11-21 16:19:19.275316: +2024-11-21 16:19:19.275745: Epoch 1053 +2024-11-21 16:19:19.275857: Current learning rate: 0.00881 +2024-11-21 16:19:36.887391: train_loss -0.7738 +2024-11-21 16:19:36.887608: val_loss -0.7629 +2024-11-21 16:19:36.887681: Pseudo dice [0.8404] +2024-11-21 16:19:36.887754: Epoch time: 17.61 s +2024-11-21 16:19:37.704985: +2024-11-21 16:19:37.705227: Epoch 1054 +2024-11-21 16:19:37.705337: Current learning rate: 0.00881 +2024-11-21 16:19:56.336433: train_loss -0.7675 +2024-11-21 16:19:56.336713: val_loss -0.7865 +2024-11-21 16:19:56.336788: Pseudo dice [0.8552] +2024-11-21 16:19:56.336863: Epoch time: 18.63 s +2024-11-21 16:19:57.153619: +2024-11-21 16:19:57.153829: Epoch 1055 +2024-11-21 16:19:57.153943: Current learning rate: 0.0088 +2024-11-21 16:20:15.743976: train_loss -0.7622 +2024-11-21 16:20:15.744196: val_loss -0.7475 +2024-11-21 16:20:15.744273: Pseudo dice [0.8281] +2024-11-21 16:20:15.744356: Epoch time: 18.59 s +2024-11-21 16:20:16.567786: +2024-11-21 16:20:16.568024: Epoch 1056 +2024-11-21 16:20:16.568135: Current learning rate: 0.0088 +2024-11-21 16:20:35.221114: train_loss -0.7612 +2024-11-21 16:20:35.221336: val_loss -0.7517 +2024-11-21 16:20:35.221415: Pseudo dice [0.8279] +2024-11-21 16:20:35.221491: Epoch time: 18.65 s +2024-11-21 16:20:36.034982: +2024-11-21 16:20:36.035225: Epoch 1057 +2024-11-21 16:20:36.035335: Current learning rate: 0.0088 +2024-11-21 16:20:55.213654: train_loss -0.7608 +2024-11-21 16:20:55.213887: val_loss -0.7503 +2024-11-21 16:20:55.215842: Pseudo dice [0.8377] +2024-11-21 16:20:55.215983: Epoch time: 19.18 s +2024-11-21 16:20:56.043702: +2024-11-21 16:20:56.043925: Epoch 1058 +2024-11-21 16:20:56.044045: Current learning rate: 0.0088 +2024-11-21 16:21:15.013348: train_loss -0.7446 +2024-11-21 16:21:15.013580: val_loss -0.7526 +2024-11-21 16:21:15.013657: Pseudo dice [0.8275] +2024-11-21 16:21:15.013734: Epoch time: 18.97 s +2024-11-21 16:21:15.826463: +2024-11-21 16:21:15.826692: Epoch 1059 +2024-11-21 16:21:15.826802: Current learning rate: 0.0088 +2024-11-21 16:21:34.680920: train_loss -0.7364 +2024-11-21 16:21:34.681162: val_loss -0.763 +2024-11-21 16:21:34.681236: Pseudo dice [0.8322] +2024-11-21 16:21:34.681315: Epoch time: 18.86 s +2024-11-21 16:21:35.492399: +2024-11-21 16:21:35.492638: Epoch 1060 +2024-11-21 16:21:35.492751: Current learning rate: 0.0088 +2024-11-21 16:21:54.916734: train_loss -0.7607 +2024-11-21 16:21:54.916933: val_loss -0.7752 +2024-11-21 16:21:54.917013: Pseudo dice [0.8398] +2024-11-21 16:21:54.917086: Epoch time: 19.43 s +2024-11-21 16:21:55.726215: +2024-11-21 16:21:55.726444: Epoch 1061 +2024-11-21 16:21:55.726559: Current learning rate: 0.0088 +2024-11-21 16:22:13.423748: train_loss -0.7608 +2024-11-21 16:22:13.423953: val_loss -0.7418 +2024-11-21 16:22:13.424038: Pseudo dice [0.8387] +2024-11-21 16:22:13.424114: Epoch time: 17.7 s +2024-11-21 16:22:14.235187: +2024-11-21 16:22:14.235407: Epoch 1062 +2024-11-21 16:22:14.235515: Current learning rate: 0.0088 +2024-11-21 16:22:31.734832: train_loss -0.7485 +2024-11-21 16:22:31.735102: val_loss -0.7248 +2024-11-21 16:22:31.735184: Pseudo dice [0.8274] +2024-11-21 16:22:31.735269: Epoch time: 17.5 s +2024-11-21 16:22:32.555987: +2024-11-21 16:22:32.556211: Epoch 1063 +2024-11-21 16:22:32.556321: Current learning rate: 0.0088 +2024-11-21 16:22:50.823138: train_loss -0.7574 +2024-11-21 16:22:50.823357: val_loss -0.7627 +2024-11-21 16:22:50.823429: Pseudo dice [0.8407] +2024-11-21 16:22:50.823502: Epoch time: 18.27 s +2024-11-21 16:22:51.807182: +2024-11-21 16:22:51.807397: Epoch 1064 +2024-11-21 16:22:51.807508: Current learning rate: 0.00879 +2024-11-21 16:23:10.445129: train_loss -0.7522 +2024-11-21 16:23:10.445350: val_loss -0.7844 +2024-11-21 16:23:10.445447: Pseudo dice [0.8548] +2024-11-21 16:23:10.445587: Epoch time: 18.64 s +2024-11-21 16:23:11.263931: +2024-11-21 16:23:11.264249: Epoch 1065 +2024-11-21 16:23:11.264358: Current learning rate: 0.00879 +2024-11-21 16:23:28.768848: train_loss -0.7661 +2024-11-21 16:23:28.769069: val_loss -0.7845 +2024-11-21 16:23:28.769143: Pseudo dice [0.8488] +2024-11-21 16:23:28.769218: Epoch time: 17.51 s +2024-11-21 16:23:29.578463: +2024-11-21 16:23:29.578681: Epoch 1066 +2024-11-21 16:23:29.578791: Current learning rate: 0.00879 +2024-11-21 16:23:48.448479: train_loss -0.748 +2024-11-21 16:23:48.448702: val_loss -0.7471 +2024-11-21 16:23:48.448775: Pseudo dice [0.8148] +2024-11-21 16:23:48.448854: Epoch time: 18.87 s +2024-11-21 16:23:49.262475: +2024-11-21 16:23:49.262704: Epoch 1067 +2024-11-21 16:23:49.262814: Current learning rate: 0.00879 +2024-11-21 16:24:07.432656: train_loss -0.754 +2024-11-21 16:24:07.432869: val_loss -0.7723 +2024-11-21 16:24:07.432943: Pseudo dice [0.8427] +2024-11-21 16:24:07.433025: Epoch time: 18.17 s +2024-11-21 16:24:08.243175: +2024-11-21 16:24:08.243387: Epoch 1068 +2024-11-21 16:24:08.243508: Current learning rate: 0.00879 +2024-11-21 16:24:27.099258: train_loss -0.7733 +2024-11-21 16:24:27.099477: val_loss -0.7567 +2024-11-21 16:24:27.099551: Pseudo dice [0.8391] +2024-11-21 16:24:27.099627: Epoch time: 18.86 s +2024-11-21 16:24:27.912338: +2024-11-21 16:24:27.912551: Epoch 1069 +2024-11-21 16:24:27.912672: Current learning rate: 0.00879 +2024-11-21 16:24:47.223096: train_loss -0.7626 +2024-11-21 16:24:47.223312: val_loss -0.776 +2024-11-21 16:24:47.223439: Pseudo dice [0.8426] +2024-11-21 16:24:47.223526: Epoch time: 19.31 s +2024-11-21 16:24:48.406127: +2024-11-21 16:24:48.408469: Epoch 1070 +2024-11-21 16:24:48.408582: Current learning rate: 0.00879 +2024-11-21 16:25:06.899727: train_loss -0.7593 +2024-11-21 16:25:06.901004: val_loss -0.7428 +2024-11-21 16:25:06.901091: Pseudo dice [0.8305] +2024-11-21 16:25:06.901170: Epoch time: 18.49 s +2024-11-21 16:25:07.756785: +2024-11-21 16:25:07.757081: Epoch 1071 +2024-11-21 16:25:07.757190: Current learning rate: 0.00879 +2024-11-21 16:25:26.366155: train_loss -0.7681 +2024-11-21 16:25:26.366394: val_loss -0.7542 +2024-11-21 16:25:26.366472: Pseudo dice [0.8442] +2024-11-21 16:25:26.366545: Epoch time: 18.61 s +2024-11-21 16:25:27.190002: +2024-11-21 16:25:27.190255: Epoch 1072 +2024-11-21 16:25:27.190365: Current learning rate: 0.00879 +2024-11-21 16:25:45.266370: train_loss -0.7566 +2024-11-21 16:25:45.268765: val_loss -0.7514 +2024-11-21 16:25:45.268856: Pseudo dice [0.8375] +2024-11-21 16:25:45.268949: Epoch time: 18.08 s +2024-11-21 16:25:46.092575: +2024-11-21 16:25:46.092799: Epoch 1073 +2024-11-21 16:25:46.092906: Current learning rate: 0.00878 +2024-11-21 16:26:05.191584: train_loss -0.76 +2024-11-21 16:26:05.191824: val_loss -0.7544 +2024-11-21 16:26:05.191901: Pseudo dice [0.8443] +2024-11-21 16:26:05.191988: Epoch time: 19.1 s +2024-11-21 16:26:06.008137: +2024-11-21 16:26:06.008354: Epoch 1074 +2024-11-21 16:26:06.008457: Current learning rate: 0.00878 +2024-11-21 16:26:24.456636: train_loss -0.7697 +2024-11-21 16:26:24.456845: val_loss -0.7447 +2024-11-21 16:26:24.456918: Pseudo dice [0.8295] +2024-11-21 16:26:24.456995: Epoch time: 18.45 s +2024-11-21 16:26:25.273411: +2024-11-21 16:26:25.273625: Epoch 1075 +2024-11-21 16:26:25.273732: Current learning rate: 0.00878 +2024-11-21 16:26:42.791942: train_loss -0.7601 +2024-11-21 16:26:42.792162: val_loss -0.7397 +2024-11-21 16:26:42.792498: Pseudo dice [0.838] +2024-11-21 16:26:42.792577: Epoch time: 17.52 s +2024-11-21 16:26:43.602448: +2024-11-21 16:26:43.602650: Epoch 1076 +2024-11-21 16:26:43.602761: Current learning rate: 0.00878 +2024-11-21 16:27:02.471068: train_loss -0.7561 +2024-11-21 16:27:02.471282: val_loss -0.7493 +2024-11-21 16:27:02.471415: Pseudo dice [0.8172] +2024-11-21 16:27:02.471496: Epoch time: 18.87 s +2024-11-21 16:27:03.281847: +2024-11-21 16:27:03.282069: Epoch 1077 +2024-11-21 16:27:03.282182: Current learning rate: 0.00878 +2024-11-21 16:27:21.265118: train_loss -0.7528 +2024-11-21 16:27:21.265343: val_loss -0.7607 +2024-11-21 16:27:21.265415: Pseudo dice [0.8479] +2024-11-21 16:27:21.265491: Epoch time: 17.98 s +2024-11-21 16:27:22.079174: +2024-11-21 16:27:22.079404: Epoch 1078 +2024-11-21 16:27:22.079515: Current learning rate: 0.00878 +2024-11-21 16:27:40.503208: train_loss -0.7615 +2024-11-21 16:27:40.503430: val_loss -0.7467 +2024-11-21 16:27:40.503507: Pseudo dice [0.8287] +2024-11-21 16:27:40.503585: Epoch time: 18.42 s +2024-11-21 16:27:41.316312: +2024-11-21 16:27:41.316535: Epoch 1079 +2024-11-21 16:27:41.316647: Current learning rate: 0.00878 +2024-11-21 16:27:58.632416: train_loss -0.7641 +2024-11-21 16:27:58.632628: val_loss -0.7383 +2024-11-21 16:27:58.632701: Pseudo dice [0.8355] +2024-11-21 16:27:58.632775: Epoch time: 17.32 s +2024-11-21 16:27:59.500942: +2024-11-21 16:27:59.501151: Epoch 1080 +2024-11-21 16:27:59.501255: Current learning rate: 0.00878 +2024-11-21 16:28:18.635052: train_loss -0.7662 +2024-11-21 16:28:18.640488: val_loss -0.7704 +2024-11-21 16:28:18.640574: Pseudo dice [0.8364] +2024-11-21 16:28:18.640662: Epoch time: 19.13 s +2024-11-21 16:28:19.571499: +2024-11-21 16:28:19.571732: Epoch 1081 +2024-11-21 16:28:19.571852: Current learning rate: 0.00878 +2024-11-21 16:28:36.981824: train_loss -0.7569 +2024-11-21 16:28:36.982039: val_loss -0.7544 +2024-11-21 16:28:36.982114: Pseudo dice [0.8329] +2024-11-21 16:28:36.982188: Epoch time: 17.41 s +2024-11-21 16:28:38.154106: +2024-11-21 16:28:38.154319: Epoch 1082 +2024-11-21 16:28:38.154434: Current learning rate: 0.00877 +2024-11-21 16:28:55.307317: train_loss -0.7568 +2024-11-21 16:28:55.307534: val_loss -0.7401 +2024-11-21 16:28:55.307609: Pseudo dice [0.84] +2024-11-21 16:28:55.307682: Epoch time: 17.15 s +2024-11-21 16:28:56.116145: +2024-11-21 16:28:56.116447: Epoch 1083 +2024-11-21 16:28:56.116558: Current learning rate: 0.00877 +2024-11-21 16:29:13.480584: train_loss -0.7518 +2024-11-21 16:29:13.480834: val_loss -0.7435 +2024-11-21 16:29:13.480914: Pseudo dice [0.83] +2024-11-21 16:29:13.481009: Epoch time: 17.37 s +2024-11-21 16:29:14.361313: +2024-11-21 16:29:14.361533: Epoch 1084 +2024-11-21 16:29:14.361648: Current learning rate: 0.00877 +2024-11-21 16:29:32.022192: train_loss -0.7582 +2024-11-21 16:29:32.022408: val_loss -0.7332 +2024-11-21 16:29:32.022482: Pseudo dice [0.8497] +2024-11-21 16:29:32.022558: Epoch time: 17.66 s +2024-11-21 16:29:32.842799: +2024-11-21 16:29:32.843064: Epoch 1085 +2024-11-21 16:29:32.843178: Current learning rate: 0.00877 +2024-11-21 16:29:51.264870: train_loss -0.7567 +2024-11-21 16:29:51.267499: val_loss -0.7505 +2024-11-21 16:29:51.267612: Pseudo dice [0.8374] +2024-11-21 16:29:51.267693: Epoch time: 18.42 s +2024-11-21 16:29:52.200581: +2024-11-21 16:29:52.200798: Epoch 1086 +2024-11-21 16:29:52.200907: Current learning rate: 0.00877 +2024-11-21 16:30:10.676781: train_loss -0.7627 +2024-11-21 16:30:10.677063: val_loss -0.7894 +2024-11-21 16:30:10.677140: Pseudo dice [0.8563] +2024-11-21 16:30:10.677213: Epoch time: 18.48 s +2024-11-21 16:30:11.492245: +2024-11-21 16:30:11.492469: Epoch 1087 +2024-11-21 16:30:11.492575: Current learning rate: 0.00877 +2024-11-21 16:30:30.108741: train_loss -0.7672 +2024-11-21 16:30:30.109041: val_loss -0.7579 +2024-11-21 16:30:30.109125: Pseudo dice [0.833] +2024-11-21 16:30:30.109214: Epoch time: 18.62 s +2024-11-21 16:30:30.970361: +2024-11-21 16:30:30.970567: Epoch 1088 +2024-11-21 16:30:30.970674: Current learning rate: 0.00877 +2024-11-21 16:30:48.818362: train_loss -0.7726 +2024-11-21 16:30:48.818622: val_loss -0.7666 +2024-11-21 16:30:48.818698: Pseudo dice [0.8321] +2024-11-21 16:30:48.818791: Epoch time: 17.85 s +2024-11-21 16:30:49.629043: +2024-11-21 16:30:49.629270: Epoch 1089 +2024-11-21 16:30:49.629379: Current learning rate: 0.00877 +2024-11-21 16:31:08.433315: train_loss -0.7573 +2024-11-21 16:31:08.433527: val_loss -0.7664 +2024-11-21 16:31:08.433602: Pseudo dice [0.8333] +2024-11-21 16:31:08.433675: Epoch time: 18.81 s +2024-11-21 16:31:09.246698: +2024-11-21 16:31:09.246902: Epoch 1090 +2024-11-21 16:31:09.247014: Current learning rate: 0.00876 +2024-11-21 16:31:27.073488: train_loss -0.7614 +2024-11-21 16:31:27.073749: val_loss -0.7772 +2024-11-21 16:31:27.073824: Pseudo dice [0.8436] +2024-11-21 16:31:27.073898: Epoch time: 17.83 s +2024-11-21 16:31:27.884191: +2024-11-21 16:31:27.884416: Epoch 1091 +2024-11-21 16:31:27.884524: Current learning rate: 0.00876 +2024-11-21 16:31:45.173600: train_loss -0.7646 +2024-11-21 16:31:45.174898: val_loss -0.7479 +2024-11-21 16:31:45.174989: Pseudo dice [0.8441] +2024-11-21 16:31:45.175080: Epoch time: 17.29 s +2024-11-21 16:31:46.157382: +2024-11-21 16:31:46.157597: Epoch 1092 +2024-11-21 16:31:46.157706: Current learning rate: 0.00876 +2024-11-21 16:32:05.155619: train_loss -0.7629 +2024-11-21 16:32:05.155827: val_loss -0.7599 +2024-11-21 16:32:05.155899: Pseudo dice [0.8362] +2024-11-21 16:32:05.156018: Epoch time: 19.0 s +2024-11-21 16:32:05.973838: +2024-11-21 16:32:05.974044: Epoch 1093 +2024-11-21 16:32:05.974154: Current learning rate: 0.00876 +2024-11-21 16:32:24.014693: train_loss -0.7695 +2024-11-21 16:32:24.014927: val_loss -0.7458 +2024-11-21 16:32:24.015010: Pseudo dice [0.8319] +2024-11-21 16:32:24.015087: Epoch time: 18.04 s +2024-11-21 16:32:24.865080: +2024-11-21 16:32:24.865348: Epoch 1094 +2024-11-21 16:32:24.867765: Current learning rate: 0.00876 +2024-11-21 16:32:43.237324: train_loss -0.765 +2024-11-21 16:32:43.237552: val_loss -0.7745 +2024-11-21 16:32:43.237624: Pseudo dice [0.8469] +2024-11-21 16:32:43.237733: Epoch time: 18.37 s +2024-11-21 16:32:44.089008: +2024-11-21 16:32:44.089298: Epoch 1095 +2024-11-21 16:32:44.089405: Current learning rate: 0.00876 +2024-11-21 16:33:01.642709: train_loss -0.7662 +2024-11-21 16:33:01.642917: val_loss -0.7624 +2024-11-21 16:33:01.643001: Pseudo dice [0.8568] +2024-11-21 16:33:01.643075: Epoch time: 17.55 s +2024-11-21 16:33:02.458599: +2024-11-21 16:33:02.458833: Epoch 1096 +2024-11-21 16:33:02.458952: Current learning rate: 0.00876 +2024-11-21 16:33:20.152430: train_loss -0.7617 +2024-11-21 16:33:20.152644: val_loss -0.7312 +2024-11-21 16:33:20.154936: Pseudo dice [0.8307] +2024-11-21 16:33:20.155038: Epoch time: 17.69 s +2024-11-21 16:33:21.139574: +2024-11-21 16:33:21.139800: Epoch 1097 +2024-11-21 16:33:21.139911: Current learning rate: 0.00876 +2024-11-21 16:33:40.109076: train_loss -0.7678 +2024-11-21 16:33:40.109363: val_loss -0.7779 +2024-11-21 16:33:40.109440: Pseudo dice [0.845] +2024-11-21 16:33:40.109518: Epoch time: 18.97 s +2024-11-21 16:33:41.029072: +2024-11-21 16:33:41.029293: Epoch 1098 +2024-11-21 16:33:41.029406: Current learning rate: 0.00876 +2024-11-21 16:33:58.489256: train_loss -0.7784 +2024-11-21 16:33:58.489493: val_loss -0.7546 +2024-11-21 16:33:58.489576: Pseudo dice [0.8574] +2024-11-21 16:33:58.489655: Epoch time: 17.46 s +2024-11-21 16:33:59.309949: +2024-11-21 16:33:59.310199: Epoch 1099 +2024-11-21 16:33:59.310314: Current learning rate: 0.00875 +2024-11-21 16:34:18.038595: train_loss -0.7623 +2024-11-21 16:34:18.038809: val_loss -0.7568 +2024-11-21 16:34:18.038882: Pseudo dice [0.8336] +2024-11-21 16:34:18.038957: Epoch time: 18.73 s +2024-11-21 16:34:19.116267: +2024-11-21 16:34:19.116473: Epoch 1100 +2024-11-21 16:34:19.116581: Current learning rate: 0.00875 +2024-11-21 16:34:36.748238: train_loss -0.7575 +2024-11-21 16:34:36.748435: val_loss -0.7502 +2024-11-21 16:34:36.748507: Pseudo dice [0.8241] +2024-11-21 16:34:36.748582: Epoch time: 17.63 s +2024-11-21 16:34:37.566332: +2024-11-21 16:34:37.566551: Epoch 1101 +2024-11-21 16:34:37.566664: Current learning rate: 0.00875 +2024-11-21 16:34:54.694010: train_loss -0.7571 +2024-11-21 16:34:54.694248: val_loss -0.7577 +2024-11-21 16:34:54.694639: Pseudo dice [0.8423] +2024-11-21 16:34:54.694728: Epoch time: 17.13 s +2024-11-21 16:34:55.509201: +2024-11-21 16:34:55.509428: Epoch 1102 +2024-11-21 16:34:55.509536: Current learning rate: 0.00875 +2024-11-21 16:35:13.456576: train_loss -0.76 +2024-11-21 16:35:13.456857: val_loss -0.7738 +2024-11-21 16:35:13.456936: Pseudo dice [0.8343] +2024-11-21 16:35:13.457014: Epoch time: 17.95 s +2024-11-21 16:35:14.359502: +2024-11-21 16:35:14.359732: Epoch 1103 +2024-11-21 16:35:14.359857: Current learning rate: 0.00875 +2024-11-21 16:35:32.098468: train_loss -0.7618 +2024-11-21 16:35:32.098698: val_loss -0.7364 +2024-11-21 16:35:32.098773: Pseudo dice [0.8328] +2024-11-21 16:35:32.098846: Epoch time: 17.74 s +2024-11-21 16:35:32.908718: +2024-11-21 16:35:32.908951: Epoch 1104 +2024-11-21 16:35:32.909070: Current learning rate: 0.00875 +2024-11-21 16:35:51.511142: train_loss -0.762 +2024-11-21 16:35:51.511461: val_loss -0.777 +2024-11-21 16:35:51.511543: Pseudo dice [0.8595] +2024-11-21 16:35:51.511672: Epoch time: 18.6 s +2024-11-21 16:35:52.701892: +2024-11-21 16:35:52.702135: Epoch 1105 +2024-11-21 16:35:52.702247: Current learning rate: 0.00875 +2024-11-21 16:36:10.831903: train_loss -0.7803 +2024-11-21 16:36:10.832132: val_loss -0.7539 +2024-11-21 16:36:10.832207: Pseudo dice [0.8361] +2024-11-21 16:36:10.832282: Epoch time: 18.13 s +2024-11-21 16:36:11.643688: +2024-11-21 16:36:11.643972: Epoch 1106 +2024-11-21 16:36:11.644101: Current learning rate: 0.00875 +2024-11-21 16:36:29.583793: train_loss -0.7728 +2024-11-21 16:36:29.584019: val_loss -0.7407 +2024-11-21 16:36:29.584096: Pseudo dice [0.8475] +2024-11-21 16:36:29.584172: Epoch time: 17.94 s +2024-11-21 16:36:30.394693: +2024-11-21 16:36:30.395028: Epoch 1107 +2024-11-21 16:36:30.395139: Current learning rate: 0.00875 +2024-11-21 16:36:48.950332: train_loss -0.7702 +2024-11-21 16:36:48.950577: val_loss -0.774 +2024-11-21 16:36:48.950651: Pseudo dice [0.8548] +2024-11-21 16:36:48.950735: Epoch time: 18.56 s +2024-11-21 16:36:48.950802: Yayy! New best EMA pseudo Dice: 0.8422 +2024-11-21 16:36:49.993221: +2024-11-21 16:36:49.993427: Epoch 1108 +2024-11-21 16:36:49.993536: Current learning rate: 0.00874 +2024-11-21 16:37:08.319921: train_loss -0.763 +2024-11-21 16:37:08.320143: val_loss -0.7777 +2024-11-21 16:37:08.320220: Pseudo dice [0.8397] +2024-11-21 16:37:08.320296: Epoch time: 18.33 s +2024-11-21 16:37:09.129566: +2024-11-21 16:37:09.129792: Epoch 1109 +2024-11-21 16:37:09.129899: Current learning rate: 0.00874 +2024-11-21 16:37:26.867228: train_loss -0.766 +2024-11-21 16:37:26.867447: val_loss -0.7813 +2024-11-21 16:37:26.867563: Pseudo dice [0.8475] +2024-11-21 16:37:26.867642: Epoch time: 17.74 s +2024-11-21 16:37:26.867702: Yayy! New best EMA pseudo Dice: 0.8425 +2024-11-21 16:37:28.036177: +2024-11-21 16:37:28.036403: Epoch 1110 +2024-11-21 16:37:28.036520: Current learning rate: 0.00874 +2024-11-21 16:37:46.588376: train_loss -0.7625 +2024-11-21 16:37:46.588584: val_loss -0.773 +2024-11-21 16:37:46.588663: Pseudo dice [0.8481] +2024-11-21 16:37:46.588735: Epoch time: 18.55 s +2024-11-21 16:37:46.588796: Yayy! New best EMA pseudo Dice: 0.8431 +2024-11-21 16:37:47.661203: +2024-11-21 16:37:47.661435: Epoch 1111 +2024-11-21 16:37:47.661544: Current learning rate: 0.00874 +2024-11-21 16:38:05.594461: train_loss -0.7713 +2024-11-21 16:38:05.594698: val_loss -0.759 +2024-11-21 16:38:05.594771: Pseudo dice [0.8364] +2024-11-21 16:38:05.594850: Epoch time: 17.93 s +2024-11-21 16:38:06.407869: +2024-11-21 16:38:06.408148: Epoch 1112 +2024-11-21 16:38:06.408260: Current learning rate: 0.00874 +2024-11-21 16:38:26.350435: train_loss -0.7578 +2024-11-21 16:38:26.350646: val_loss -0.7325 +2024-11-21 16:38:26.350719: Pseudo dice [0.8476] +2024-11-21 16:38:26.350794: Epoch time: 19.94 s +2024-11-21 16:38:27.188163: +2024-11-21 16:38:27.188385: Epoch 1113 +2024-11-21 16:38:27.188495: Current learning rate: 0.00874 +2024-11-21 16:38:45.600512: train_loss -0.7581 +2024-11-21 16:38:45.600753: val_loss -0.7755 +2024-11-21 16:38:45.600830: Pseudo dice [0.8495] +2024-11-21 16:38:45.600903: Epoch time: 18.41 s +2024-11-21 16:38:45.600963: Yayy! New best EMA pseudo Dice: 0.8436 +2024-11-21 16:38:46.652986: +2024-11-21 16:38:46.653179: Epoch 1114 +2024-11-21 16:38:46.653293: Current learning rate: 0.00874 +2024-11-21 16:39:04.855112: train_loss -0.7689 +2024-11-21 16:39:04.855319: val_loss -0.7598 +2024-11-21 16:39:04.855394: Pseudo dice [0.8404] +2024-11-21 16:39:04.855476: Epoch time: 18.2 s +2024-11-21 16:39:05.672549: +2024-11-21 16:39:05.672816: Epoch 1115 +2024-11-21 16:39:05.672924: Current learning rate: 0.00874 +2024-11-21 16:39:24.256544: train_loss -0.7593 +2024-11-21 16:39:24.256751: val_loss -0.7369 +2024-11-21 16:39:24.256822: Pseudo dice [0.8404] +2024-11-21 16:39:24.256899: Epoch time: 18.58 s +2024-11-21 16:39:25.438115: +2024-11-21 16:39:25.438328: Epoch 1116 +2024-11-21 16:39:25.438435: Current learning rate: 0.00874 +2024-11-21 16:39:44.884563: train_loss -0.7629 +2024-11-21 16:39:44.884805: val_loss -0.7648 +2024-11-21 16:39:44.884883: Pseudo dice [0.839] +2024-11-21 16:39:44.884958: Epoch time: 19.45 s +2024-11-21 16:39:45.691368: +2024-11-21 16:39:45.691599: Epoch 1117 +2024-11-21 16:39:45.691714: Current learning rate: 0.00873 +2024-11-21 16:40:05.062040: train_loss -0.7494 +2024-11-21 16:40:05.062243: val_loss -0.7557 +2024-11-21 16:40:05.062318: Pseudo dice [0.8316] +2024-11-21 16:40:05.062395: Epoch time: 19.37 s +2024-11-21 16:40:05.870297: +2024-11-21 16:40:05.870523: Epoch 1118 +2024-11-21 16:40:05.870628: Current learning rate: 0.00873 +2024-11-21 16:40:23.531243: train_loss -0.7543 +2024-11-21 16:40:23.531489: val_loss -0.7729 +2024-11-21 16:40:23.531564: Pseudo dice [0.8441] +2024-11-21 16:40:23.531640: Epoch time: 17.66 s +2024-11-21 16:40:24.349859: +2024-11-21 16:40:24.350091: Epoch 1119 +2024-11-21 16:40:24.350199: Current learning rate: 0.00873 +2024-11-21 16:40:42.769279: train_loss -0.7649 +2024-11-21 16:40:42.769489: val_loss -0.761 +2024-11-21 16:40:42.769561: Pseudo dice [0.8444] +2024-11-21 16:40:42.769637: Epoch time: 18.42 s +2024-11-21 16:40:43.619808: +2024-11-21 16:40:43.620012: Epoch 1120 +2024-11-21 16:40:43.620130: Current learning rate: 0.00873 +2024-11-21 16:41:01.433532: train_loss -0.7595 +2024-11-21 16:41:01.433738: val_loss -0.7597 +2024-11-21 16:41:01.433810: Pseudo dice [0.8322] +2024-11-21 16:41:01.433884: Epoch time: 17.81 s +2024-11-21 16:41:02.264336: +2024-11-21 16:41:02.264560: Epoch 1121 +2024-11-21 16:41:02.264666: Current learning rate: 0.00873 +2024-11-21 16:41:20.416804: train_loss -0.7664 +2024-11-21 16:41:20.421167: val_loss -0.7538 +2024-11-21 16:41:20.421320: Pseudo dice [0.8247] +2024-11-21 16:41:20.421411: Epoch time: 18.15 s +2024-11-21 16:41:21.400681: +2024-11-21 16:41:21.400903: Epoch 1122 +2024-11-21 16:41:21.401015: Current learning rate: 0.00873 +2024-11-21 16:41:39.249738: train_loss -0.7581 +2024-11-21 16:41:39.249969: val_loss -0.762 +2024-11-21 16:41:39.250049: Pseudo dice [0.8481] +2024-11-21 16:41:39.250121: Epoch time: 17.85 s +2024-11-21 16:41:40.058537: +2024-11-21 16:41:40.058764: Epoch 1123 +2024-11-21 16:41:40.058881: Current learning rate: 0.00873 +2024-11-21 16:41:58.928077: train_loss -0.758 +2024-11-21 16:41:58.928289: val_loss -0.7755 +2024-11-21 16:41:58.928364: Pseudo dice [0.8313] +2024-11-21 16:41:58.928435: Epoch time: 18.87 s +2024-11-21 16:41:59.745842: +2024-11-21 16:41:59.746053: Epoch 1124 +2024-11-21 16:41:59.746159: Current learning rate: 0.00873 +2024-11-21 16:42:17.831020: train_loss -0.7583 +2024-11-21 16:42:17.831235: val_loss -0.7546 +2024-11-21 16:42:17.831308: Pseudo dice [0.8418] +2024-11-21 16:42:17.831392: Epoch time: 18.09 s +2024-11-21 16:42:18.646954: +2024-11-21 16:42:18.647340: Epoch 1125 +2024-11-21 16:42:18.647470: Current learning rate: 0.00872 +2024-11-21 16:42:39.123820: train_loss -0.7754 +2024-11-21 16:42:39.124117: val_loss -0.7403 +2024-11-21 16:42:39.124193: Pseudo dice [0.8304] +2024-11-21 16:42:39.124272: Epoch time: 20.48 s +2024-11-21 16:42:39.941648: +2024-11-21 16:42:39.941844: Epoch 1126 +2024-11-21 16:42:39.941949: Current learning rate: 0.00872 +2024-11-21 16:42:58.830616: train_loss -0.7691 +2024-11-21 16:42:58.830816: val_loss -0.7747 +2024-11-21 16:42:58.831091: Pseudo dice [0.8286] +2024-11-21 16:42:58.831170: Epoch time: 18.89 s +2024-11-21 16:42:59.647549: +2024-11-21 16:42:59.647758: Epoch 1127 +2024-11-21 16:42:59.647869: Current learning rate: 0.00872 +2024-11-21 16:43:17.665567: train_loss -0.7621 +2024-11-21 16:43:17.665777: val_loss -0.747 +2024-11-21 16:43:17.665851: Pseudo dice [0.8425] +2024-11-21 16:43:17.665922: Epoch time: 18.02 s +2024-11-21 16:43:18.878849: +2024-11-21 16:43:18.879083: Epoch 1128 +2024-11-21 16:43:18.879199: Current learning rate: 0.00872 +2024-11-21 16:43:38.204955: train_loss -0.77 +2024-11-21 16:43:38.205204: val_loss -0.7719 +2024-11-21 16:43:38.205281: Pseudo dice [0.8458] +2024-11-21 16:43:38.205355: Epoch time: 19.33 s +2024-11-21 16:43:39.125431: +2024-11-21 16:43:39.125665: Epoch 1129 +2024-11-21 16:43:39.125775: Current learning rate: 0.00872 +2024-11-21 16:43:57.959493: train_loss -0.772 +2024-11-21 16:43:57.959713: val_loss -0.7572 +2024-11-21 16:43:57.959789: Pseudo dice [0.834] +2024-11-21 16:43:57.959868: Epoch time: 18.83 s +2024-11-21 16:43:58.770955: +2024-11-21 16:43:58.771245: Epoch 1130 +2024-11-21 16:43:58.771359: Current learning rate: 0.00872 +2024-11-21 16:44:16.289433: train_loss -0.7649 +2024-11-21 16:44:16.289644: val_loss -0.7399 +2024-11-21 16:44:16.289715: Pseudo dice [0.8379] +2024-11-21 16:44:16.289788: Epoch time: 17.52 s +2024-11-21 16:44:17.107707: +2024-11-21 16:44:17.107997: Epoch 1131 +2024-11-21 16:44:17.108110: Current learning rate: 0.00872 +2024-11-21 16:44:35.901628: train_loss -0.7666 +2024-11-21 16:44:35.901846: val_loss -0.7727 +2024-11-21 16:44:35.901923: Pseudo dice [0.8484] +2024-11-21 16:44:35.902009: Epoch time: 18.79 s +2024-11-21 16:44:36.721775: +2024-11-21 16:44:36.722063: Epoch 1132 +2024-11-21 16:44:36.722188: Current learning rate: 0.00872 +2024-11-21 16:44:54.830689: train_loss -0.7738 +2024-11-21 16:44:54.830888: val_loss -0.738 +2024-11-21 16:44:54.830984: Pseudo dice [0.8171] +2024-11-21 16:44:54.831070: Epoch time: 18.11 s +2024-11-21 16:44:55.641599: +2024-11-21 16:44:55.641796: Epoch 1133 +2024-11-21 16:44:55.641905: Current learning rate: 0.00872 +2024-11-21 16:45:15.221607: train_loss -0.7644 +2024-11-21 16:45:15.221806: val_loss -0.7572 +2024-11-21 16:45:15.221878: Pseudo dice [0.8234] +2024-11-21 16:45:15.221948: Epoch time: 19.58 s +2024-11-21 16:45:16.040185: +2024-11-21 16:45:16.040404: Epoch 1134 +2024-11-21 16:45:16.040516: Current learning rate: 0.00871 +2024-11-21 16:45:34.493774: train_loss -0.7753 +2024-11-21 16:45:34.493997: val_loss -0.779 +2024-11-21 16:45:34.494111: Pseudo dice [0.8425] +2024-11-21 16:45:34.494189: Epoch time: 18.45 s +2024-11-21 16:45:35.308029: +2024-11-21 16:45:35.308249: Epoch 1135 +2024-11-21 16:45:35.308362: Current learning rate: 0.00871 +2024-11-21 16:45:53.252244: train_loss -0.767 +2024-11-21 16:45:53.252488: val_loss -0.7837 +2024-11-21 16:45:53.252620: Pseudo dice [0.8409] +2024-11-21 16:45:53.252704: Epoch time: 17.95 s +2024-11-21 16:45:54.064962: +2024-11-21 16:45:54.065276: Epoch 1136 +2024-11-21 16:45:54.065388: Current learning rate: 0.00871 +2024-11-21 16:46:12.159480: train_loss -0.7628 +2024-11-21 16:46:12.159774: val_loss -0.762 +2024-11-21 16:46:12.159858: Pseudo dice [0.8218] +2024-11-21 16:46:12.159936: Epoch time: 18.1 s +2024-11-21 16:46:12.974973: +2024-11-21 16:46:12.975178: Epoch 1137 +2024-11-21 16:46:12.975341: Current learning rate: 0.00871 +2024-11-21 16:46:32.109798: train_loss -0.7743 +2024-11-21 16:46:32.110051: val_loss -0.7348 +2024-11-21 16:46:32.112322: Pseudo dice [0.8424] +2024-11-21 16:46:32.112412: Epoch time: 19.14 s +2024-11-21 16:46:33.070394: +2024-11-21 16:46:33.070610: Epoch 1138 +2024-11-21 16:46:33.070729: Current learning rate: 0.00871 +2024-11-21 16:46:52.019107: train_loss -0.765 +2024-11-21 16:46:52.020029: val_loss -0.7583 +2024-11-21 16:46:52.020114: Pseudo dice [0.8487] +2024-11-21 16:46:52.020195: Epoch time: 18.95 s +2024-11-21 16:46:52.838246: +2024-11-21 16:46:52.838459: Epoch 1139 +2024-11-21 16:46:52.838567: Current learning rate: 0.00871 +2024-11-21 16:47:10.208289: train_loss -0.7732 +2024-11-21 16:47:10.208566: val_loss -0.7664 +2024-11-21 16:47:10.208647: Pseudo dice [0.8376] +2024-11-21 16:47:10.208724: Epoch time: 17.37 s +2024-11-21 16:47:11.404827: +2024-11-21 16:47:11.405051: Epoch 1140 +2024-11-21 16:47:11.405161: Current learning rate: 0.00871 +2024-11-21 16:47:29.615587: train_loss -0.7678 +2024-11-21 16:47:29.615806: val_loss -0.7667 +2024-11-21 16:47:29.615881: Pseudo dice [0.8441] +2024-11-21 16:47:29.615963: Epoch time: 18.21 s +2024-11-21 16:47:30.578954: +2024-11-21 16:47:30.579181: Epoch 1141 +2024-11-21 16:47:30.579291: Current learning rate: 0.00871 +2024-11-21 16:47:47.839252: train_loss -0.7706 +2024-11-21 16:47:47.839467: val_loss -0.7827 +2024-11-21 16:47:47.839541: Pseudo dice [0.8384] +2024-11-21 16:47:47.839621: Epoch time: 17.26 s +2024-11-21 16:47:48.659519: +2024-11-21 16:47:48.659750: Epoch 1142 +2024-11-21 16:47:48.659866: Current learning rate: 0.00871 +2024-11-21 16:48:06.688236: train_loss -0.7581 +2024-11-21 16:48:06.688472: val_loss -0.7598 +2024-11-21 16:48:06.688548: Pseudo dice [0.8614] +2024-11-21 16:48:06.688627: Epoch time: 18.03 s +2024-11-21 16:48:07.503309: +2024-11-21 16:48:07.503557: Epoch 1143 +2024-11-21 16:48:07.503670: Current learning rate: 0.0087 +2024-11-21 16:48:25.765327: train_loss -0.7641 +2024-11-21 16:48:25.765543: val_loss -0.7645 +2024-11-21 16:48:25.765621: Pseudo dice [0.8474] +2024-11-21 16:48:25.765693: Epoch time: 18.26 s +2024-11-21 16:48:26.603755: +2024-11-21 16:48:26.603989: Epoch 1144 +2024-11-21 16:48:26.604105: Current learning rate: 0.0087 +2024-11-21 16:48:45.384222: train_loss -0.7582 +2024-11-21 16:48:45.384461: val_loss -0.777 +2024-11-21 16:48:45.384542: Pseudo dice [0.8487] +2024-11-21 16:48:45.384623: Epoch time: 18.78 s +2024-11-21 16:48:46.299616: +2024-11-21 16:48:46.299830: Epoch 1145 +2024-11-21 16:48:46.299946: Current learning rate: 0.0087 +2024-11-21 16:49:04.012715: train_loss -0.7629 +2024-11-21 16:49:04.012948: val_loss -0.7539 +2024-11-21 16:49:04.013037: Pseudo dice [0.8212] +2024-11-21 16:49:04.013126: Epoch time: 17.71 s +2024-11-21 16:49:04.827983: +2024-11-21 16:49:04.828182: Epoch 1146 +2024-11-21 16:49:04.828294: Current learning rate: 0.0087 +2024-11-21 16:49:22.990911: train_loss -0.7606 +2024-11-21 16:49:22.991129: val_loss -0.7932 +2024-11-21 16:49:22.991202: Pseudo dice [0.8542] +2024-11-21 16:49:22.991275: Epoch time: 18.16 s +2024-11-21 16:49:23.812208: +2024-11-21 16:49:23.812451: Epoch 1147 +2024-11-21 16:49:23.812557: Current learning rate: 0.0087 +2024-11-21 16:49:42.690208: train_loss -0.7695 +2024-11-21 16:49:42.690414: val_loss -0.7526 +2024-11-21 16:49:42.690485: Pseudo dice [0.8341] +2024-11-21 16:49:42.690556: Epoch time: 18.88 s +2024-11-21 16:49:43.506713: +2024-11-21 16:49:43.506918: Epoch 1148 +2024-11-21 16:49:43.507036: Current learning rate: 0.0087 +2024-11-21 16:50:02.479315: train_loss -0.7762 +2024-11-21 16:50:02.479541: val_loss -0.7721 +2024-11-21 16:50:02.479617: Pseudo dice [0.8393] +2024-11-21 16:50:02.479708: Epoch time: 18.97 s +2024-11-21 16:50:03.356001: +2024-11-21 16:50:03.356217: Epoch 1149 +2024-11-21 16:50:03.356325: Current learning rate: 0.0087 +2024-11-21 16:50:21.899893: train_loss -0.77 +2024-11-21 16:50:21.900141: val_loss -0.775 +2024-11-21 16:50:21.900221: Pseudo dice [0.8507] +2024-11-21 16:50:21.900301: Epoch time: 18.54 s +2024-11-21 16:50:22.987505: +2024-11-21 16:50:22.987727: Epoch 1150 +2024-11-21 16:50:22.987839: Current learning rate: 0.0087 +2024-11-21 16:50:41.702989: train_loss -0.7674 +2024-11-21 16:50:41.703211: val_loss -0.7663 +2024-11-21 16:50:41.703284: Pseudo dice [0.8569] +2024-11-21 16:50:41.703360: Epoch time: 18.72 s +2024-11-21 16:50:42.528896: +2024-11-21 16:50:42.529109: Epoch 1151 +2024-11-21 16:50:42.529217: Current learning rate: 0.0087 +2024-11-21 16:51:01.194123: train_loss -0.7624 +2024-11-21 16:51:01.196859: val_loss -0.7634 +2024-11-21 16:51:01.196966: Pseudo dice [0.8454] +2024-11-21 16:51:01.197049: Epoch time: 18.67 s +2024-11-21 16:51:02.011258: +2024-11-21 16:51:02.011484: Epoch 1152 +2024-11-21 16:51:02.011591: Current learning rate: 0.00869 +2024-11-21 16:51:21.048441: train_loss -0.7611 +2024-11-21 16:51:21.048671: val_loss -0.7584 +2024-11-21 16:51:21.049089: Pseudo dice [0.8453] +2024-11-21 16:51:21.049182: Epoch time: 19.04 s +2024-11-21 16:51:21.897349: +2024-11-21 16:51:21.897580: Epoch 1153 +2024-11-21 16:51:21.897692: Current learning rate: 0.00869 +2024-11-21 16:51:41.066933: train_loss -0.7601 +2024-11-21 16:51:41.067147: val_loss -0.7475 +2024-11-21 16:51:41.067221: Pseudo dice [0.8322] +2024-11-21 16:51:41.067295: Epoch time: 19.17 s +2024-11-21 16:51:41.881078: +2024-11-21 16:51:41.881320: Epoch 1154 +2024-11-21 16:51:41.881432: Current learning rate: 0.00869 +2024-11-21 16:51:59.651383: train_loss -0.7639 +2024-11-21 16:51:59.651592: val_loss -0.7339 +2024-11-21 16:51:59.651664: Pseudo dice [0.8456] +2024-11-21 16:51:59.651735: Epoch time: 17.77 s +2024-11-21 16:52:00.469696: +2024-11-21 16:52:00.469920: Epoch 1155 +2024-11-21 16:52:00.470036: Current learning rate: 0.00869 +2024-11-21 16:52:17.621333: train_loss -0.7683 +2024-11-21 16:52:17.621551: val_loss -0.7626 +2024-11-21 16:52:17.621625: Pseudo dice [0.8437] +2024-11-21 16:52:17.621703: Epoch time: 17.15 s +2024-11-21 16:52:18.439882: +2024-11-21 16:52:18.440142: Epoch 1156 +2024-11-21 16:52:18.440275: Current learning rate: 0.00869 +2024-11-21 16:52:36.380725: train_loss -0.7628 +2024-11-21 16:52:36.380929: val_loss -0.7527 +2024-11-21 16:52:36.381011: Pseudo dice [0.8413] +2024-11-21 16:52:36.381084: Epoch time: 17.94 s +2024-11-21 16:52:37.364181: +2024-11-21 16:52:37.364541: Epoch 1157 +2024-11-21 16:52:37.364657: Current learning rate: 0.00869 +2024-11-21 16:52:54.114442: train_loss -0.7663 +2024-11-21 16:52:54.114640: val_loss -0.7702 +2024-11-21 16:52:54.114723: Pseudo dice [0.8398] +2024-11-21 16:52:54.114798: Epoch time: 16.75 s +2024-11-21 16:52:54.935061: +2024-11-21 16:52:54.935280: Epoch 1158 +2024-11-21 16:52:54.935389: Current learning rate: 0.00869 +2024-11-21 16:53:12.986835: train_loss -0.7584 +2024-11-21 16:53:12.987050: val_loss -0.7572 +2024-11-21 16:53:12.987128: Pseudo dice [0.8257] +2024-11-21 16:53:12.987243: Epoch time: 18.05 s +2024-11-21 16:53:13.808382: +2024-11-21 16:53:13.808605: Epoch 1159 +2024-11-21 16:53:13.808717: Current learning rate: 0.00869 +2024-11-21 16:53:31.721465: train_loss -0.7577 +2024-11-21 16:53:31.721700: val_loss -0.7457 +2024-11-21 16:53:31.721775: Pseudo dice [0.8197] +2024-11-21 16:53:31.721858: Epoch time: 17.91 s +2024-11-21 16:53:32.546188: +2024-11-21 16:53:32.546400: Epoch 1160 +2024-11-21 16:53:32.546511: Current learning rate: 0.00868 +2024-11-21 16:53:51.314438: train_loss -0.7633 +2024-11-21 16:53:51.314642: val_loss -0.7512 +2024-11-21 16:53:51.314717: Pseudo dice [0.8418] +2024-11-21 16:53:51.314790: Epoch time: 18.77 s +2024-11-21 16:53:52.158618: +2024-11-21 16:53:52.158840: Epoch 1161 +2024-11-21 16:53:52.158953: Current learning rate: 0.00868 +2024-11-21 16:54:11.798035: train_loss -0.7519 +2024-11-21 16:54:11.798247: val_loss -0.7593 +2024-11-21 16:54:11.798321: Pseudo dice [0.8001] +2024-11-21 16:54:11.798430: Epoch time: 19.64 s +2024-11-21 16:54:12.614763: +2024-11-21 16:54:12.615113: Epoch 1162 +2024-11-21 16:54:12.615224: Current learning rate: 0.00868 +2024-11-21 16:54:30.868093: train_loss -0.7647 +2024-11-21 16:54:30.868305: val_loss -0.7585 +2024-11-21 16:54:30.868382: Pseudo dice [0.8288] +2024-11-21 16:54:30.868462: Epoch time: 18.25 s +2024-11-21 16:54:32.009696: +2024-11-21 16:54:32.010024: Epoch 1163 +2024-11-21 16:54:32.010132: Current learning rate: 0.00868 +2024-11-21 16:54:51.128461: train_loss -0.7754 +2024-11-21 16:54:51.128695: val_loss -0.7802 +2024-11-21 16:54:51.128768: Pseudo dice [0.8491] +2024-11-21 16:54:51.128847: Epoch time: 19.12 s +2024-11-21 16:54:52.130888: +2024-11-21 16:54:52.131113: Epoch 1164 +2024-11-21 16:54:52.131225: Current learning rate: 0.00868 +2024-11-21 16:55:10.857658: train_loss -0.7748 +2024-11-21 16:55:10.857876: val_loss -0.7688 +2024-11-21 16:55:10.857952: Pseudo dice [0.8374] +2024-11-21 16:55:10.858032: Epoch time: 18.73 s +2024-11-21 16:55:11.674346: +2024-11-21 16:55:11.674550: Epoch 1165 +2024-11-21 16:55:11.674662: Current learning rate: 0.00868 +2024-11-21 16:55:30.416370: train_loss -0.7693 +2024-11-21 16:55:30.416577: val_loss -0.7542 +2024-11-21 16:55:30.416650: Pseudo dice [0.8321] +2024-11-21 16:55:30.416724: Epoch time: 18.74 s +2024-11-21 16:55:31.236248: +2024-11-21 16:55:31.236562: Epoch 1166 +2024-11-21 16:55:31.236676: Current learning rate: 0.00868 +2024-11-21 16:55:50.160633: train_loss -0.7648 +2024-11-21 16:55:50.160875: val_loss -0.7604 +2024-11-21 16:55:50.160951: Pseudo dice [0.8369] +2024-11-21 16:55:50.161043: Epoch time: 18.93 s +2024-11-21 16:55:50.989929: +2024-11-21 16:55:50.990161: Epoch 1167 +2024-11-21 16:55:50.990269: Current learning rate: 0.00868 +2024-11-21 16:56:08.250370: train_loss -0.761 +2024-11-21 16:56:08.250579: val_loss -0.7542 +2024-11-21 16:56:08.250655: Pseudo dice [0.8358] +2024-11-21 16:56:08.250728: Epoch time: 17.26 s +2024-11-21 16:56:09.140788: +2024-11-21 16:56:09.141063: Epoch 1168 +2024-11-21 16:56:09.141173: Current learning rate: 0.00868 +2024-11-21 16:56:28.211533: train_loss -0.7675 +2024-11-21 16:56:28.213928: val_loss -0.7319 +2024-11-21 16:56:28.214069: Pseudo dice [0.8182] +2024-11-21 16:56:28.214148: Epoch time: 19.07 s +2024-11-21 16:56:29.108055: +2024-11-21 16:56:29.108257: Epoch 1169 +2024-11-21 16:56:29.108367: Current learning rate: 0.00867 +2024-11-21 16:56:47.758943: train_loss -0.7591 +2024-11-21 16:56:47.759198: val_loss -0.7651 +2024-11-21 16:56:47.759274: Pseudo dice [0.8443] +2024-11-21 16:56:47.759356: Epoch time: 18.65 s +2024-11-21 16:56:48.592000: +2024-11-21 16:56:48.592213: Epoch 1170 +2024-11-21 16:56:48.592324: Current learning rate: 0.00867 +2024-11-21 16:57:06.643521: train_loss -0.7472 +2024-11-21 16:57:06.643740: val_loss -0.7579 +2024-11-21 16:57:06.643857: Pseudo dice [0.8392] +2024-11-21 16:57:06.643934: Epoch time: 18.05 s +2024-11-21 16:57:07.462164: +2024-11-21 16:57:07.462388: Epoch 1171 +2024-11-21 16:57:07.462506: Current learning rate: 0.00867 +2024-11-21 16:57:26.181866: train_loss -0.7586 +2024-11-21 16:57:26.182085: val_loss -0.7897 +2024-11-21 16:57:26.182164: Pseudo dice [0.8421] +2024-11-21 16:57:26.182236: Epoch time: 18.72 s +2024-11-21 16:57:26.998849: +2024-11-21 16:57:26.999086: Epoch 1172 +2024-11-21 16:57:26.999198: Current learning rate: 0.00867 +2024-11-21 16:57:45.554338: train_loss -0.7574 +2024-11-21 16:57:45.554616: val_loss -0.7426 +2024-11-21 16:57:45.554694: Pseudo dice [0.8259] +2024-11-21 16:57:45.554771: Epoch time: 18.56 s +2024-11-21 16:57:46.379905: +2024-11-21 16:57:46.380122: Epoch 1173 +2024-11-21 16:57:46.380231: Current learning rate: 0.00867 +2024-11-21 16:58:05.714606: train_loss -0.7698 +2024-11-21 16:58:05.714835: val_loss -0.7661 +2024-11-21 16:58:05.714908: Pseudo dice [0.8422] +2024-11-21 16:58:05.714984: Epoch time: 19.34 s +2024-11-21 16:58:06.915296: +2024-11-21 16:58:06.915518: Epoch 1174 +2024-11-21 16:58:06.915626: Current learning rate: 0.00867 +2024-11-21 16:58:26.291494: train_loss -0.7596 +2024-11-21 16:58:26.291728: val_loss -0.7346 +2024-11-21 16:58:26.291802: Pseudo dice [0.8363] +2024-11-21 16:58:26.291873: Epoch time: 19.38 s +2024-11-21 16:58:27.113986: +2024-11-21 16:58:27.114225: Epoch 1175 +2024-11-21 16:58:27.114334: Current learning rate: 0.00867 +2024-11-21 16:58:45.238975: train_loss -0.7573 +2024-11-21 16:58:45.239236: val_loss -0.7649 +2024-11-21 16:58:45.239314: Pseudo dice [0.8399] +2024-11-21 16:58:45.239389: Epoch time: 18.13 s +2024-11-21 16:58:46.061269: +2024-11-21 16:58:46.061515: Epoch 1176 +2024-11-21 16:58:46.061634: Current learning rate: 0.00867 +2024-11-21 16:59:04.125502: train_loss -0.765 +2024-11-21 16:59:04.125736: val_loss -0.7744 +2024-11-21 16:59:04.125810: Pseudo dice [0.8454] +2024-11-21 16:59:04.125885: Epoch time: 18.07 s +2024-11-21 16:59:04.948964: +2024-11-21 16:59:04.949182: Epoch 1177 +2024-11-21 16:59:04.949293: Current learning rate: 0.00867 +2024-11-21 16:59:22.581962: train_loss -0.7545 +2024-11-21 16:59:22.582183: val_loss -0.7553 +2024-11-21 16:59:22.582265: Pseudo dice [0.8188] +2024-11-21 16:59:22.582345: Epoch time: 17.63 s +2024-11-21 16:59:23.454928: +2024-11-21 16:59:23.455199: Epoch 1178 +2024-11-21 16:59:23.455307: Current learning rate: 0.00866 +2024-11-21 16:59:42.004201: train_loss -0.7742 +2024-11-21 16:59:42.004423: val_loss -0.7644 +2024-11-21 16:59:42.004746: Pseudo dice [0.8386] +2024-11-21 16:59:42.004847: Epoch time: 18.55 s +2024-11-21 16:59:42.833060: +2024-11-21 16:59:42.833290: Epoch 1179 +2024-11-21 16:59:42.833400: Current learning rate: 0.00866 +2024-11-21 17:00:01.349887: train_loss -0.7699 +2024-11-21 17:00:01.350152: val_loss -0.7477 +2024-11-21 17:00:01.350231: Pseudo dice [0.8333] +2024-11-21 17:00:01.350316: Epoch time: 18.52 s +2024-11-21 17:00:02.183004: +2024-11-21 17:00:02.183247: Epoch 1180 +2024-11-21 17:00:02.183364: Current learning rate: 0.00866 +2024-11-21 17:00:20.807397: train_loss -0.7768 +2024-11-21 17:00:20.807616: val_loss -0.7604 +2024-11-21 17:00:20.807688: Pseudo dice [0.8371] +2024-11-21 17:00:20.807762: Epoch time: 18.63 s +2024-11-21 17:00:21.635762: +2024-11-21 17:00:21.636006: Epoch 1181 +2024-11-21 17:00:21.636129: Current learning rate: 0.00866 +2024-11-21 17:00:40.364780: train_loss -0.7722 +2024-11-21 17:00:40.365007: val_loss -0.7898 +2024-11-21 17:00:40.365082: Pseudo dice [0.8517] +2024-11-21 17:00:40.365156: Epoch time: 18.73 s +2024-11-21 17:00:41.193781: +2024-11-21 17:00:41.194001: Epoch 1182 +2024-11-21 17:00:41.194110: Current learning rate: 0.00866 +2024-11-21 17:00:58.583081: train_loss -0.7621 +2024-11-21 17:00:58.583340: val_loss -0.7625 +2024-11-21 17:00:58.583419: Pseudo dice [0.8461] +2024-11-21 17:00:58.583496: Epoch time: 17.39 s +2024-11-21 17:00:59.418926: +2024-11-21 17:00:59.419148: Epoch 1183 +2024-11-21 17:00:59.419260: Current learning rate: 0.00866 +2024-11-21 17:01:17.234680: train_loss -0.7674 +2024-11-21 17:01:17.234903: val_loss -0.7426 +2024-11-21 17:01:17.234976: Pseudo dice [0.8313] +2024-11-21 17:01:17.235066: Epoch time: 17.82 s +2024-11-21 17:01:18.057296: +2024-11-21 17:01:18.057495: Epoch 1184 +2024-11-21 17:01:18.057603: Current learning rate: 0.00866 +2024-11-21 17:01:36.989890: train_loss -0.7699 +2024-11-21 17:01:36.990147: val_loss -0.7512 +2024-11-21 17:01:36.990235: Pseudo dice [0.8435] +2024-11-21 17:01:36.990311: Epoch time: 18.93 s +2024-11-21 17:01:37.938784: +2024-11-21 17:01:37.939062: Epoch 1185 +2024-11-21 17:01:37.939169: Current learning rate: 0.00866 +2024-11-21 17:01:56.740961: train_loss -0.7487 +2024-11-21 17:01:56.741232: val_loss -0.7355 +2024-11-21 17:01:56.741336: Pseudo dice [0.8416] +2024-11-21 17:01:56.741415: Epoch time: 18.8 s +2024-11-21 17:01:57.970417: +2024-11-21 17:01:57.970648: Epoch 1186 +2024-11-21 17:01:57.970764: Current learning rate: 0.00866 +2024-11-21 17:02:15.809797: train_loss -0.7471 +2024-11-21 17:02:15.812212: val_loss -0.7702 +2024-11-21 17:02:15.812306: Pseudo dice [0.8433] +2024-11-21 17:02:15.812403: Epoch time: 17.84 s +2024-11-21 17:02:16.813923: +2024-11-21 17:02:16.814151: Epoch 1187 +2024-11-21 17:02:16.814260: Current learning rate: 0.00865 +2024-11-21 17:02:35.597121: train_loss -0.7281 +2024-11-21 17:02:35.597331: val_loss -0.7653 +2024-11-21 17:02:35.597415: Pseudo dice [0.8532] +2024-11-21 17:02:35.597600: Epoch time: 18.78 s +2024-11-21 17:02:36.422839: +2024-11-21 17:02:36.423171: Epoch 1188 +2024-11-21 17:02:36.423284: Current learning rate: 0.00865 +2024-11-21 17:02:55.432071: train_loss -0.7571 +2024-11-21 17:02:55.432297: val_loss -0.7602 +2024-11-21 17:02:55.432371: Pseudo dice [0.8205] +2024-11-21 17:02:55.432446: Epoch time: 19.01 s +2024-11-21 17:02:56.274464: +2024-11-21 17:02:56.274772: Epoch 1189 +2024-11-21 17:02:56.274881: Current learning rate: 0.00865 +2024-11-21 17:03:13.528339: train_loss -0.76 +2024-11-21 17:03:13.528569: val_loss -0.7506 +2024-11-21 17:03:13.528644: Pseudo dice [0.8307] +2024-11-21 17:03:13.528727: Epoch time: 17.25 s +2024-11-21 17:03:14.358961: +2024-11-21 17:03:14.359227: Epoch 1190 +2024-11-21 17:03:14.359354: Current learning rate: 0.00865 +2024-11-21 17:03:33.737425: train_loss -0.762 +2024-11-21 17:03:33.737630: val_loss -0.736 +2024-11-21 17:03:33.737703: Pseudo dice [0.8157] +2024-11-21 17:03:33.737776: Epoch time: 19.38 s +2024-11-21 17:03:34.675407: +2024-11-21 17:03:34.675703: Epoch 1191 +2024-11-21 17:03:34.675813: Current learning rate: 0.00865 +2024-11-21 17:03:53.703713: train_loss -0.7504 +2024-11-21 17:03:53.703919: val_loss -0.7392 +2024-11-21 17:03:53.703998: Pseudo dice [0.8205] +2024-11-21 17:03:53.704073: Epoch time: 19.03 s +2024-11-21 17:03:54.531911: +2024-11-21 17:03:54.532140: Epoch 1192 +2024-11-21 17:03:54.532250: Current learning rate: 0.00865 +2024-11-21 17:04:12.904840: train_loss -0.7692 +2024-11-21 17:04:12.905058: val_loss -0.7435 +2024-11-21 17:04:12.905132: Pseudo dice [0.8438] +2024-11-21 17:04:12.905203: Epoch time: 18.37 s +2024-11-21 17:04:13.730465: +2024-11-21 17:04:13.730684: Epoch 1193 +2024-11-21 17:04:13.730791: Current learning rate: 0.00865 +2024-11-21 17:04:32.663198: train_loss -0.7738 +2024-11-21 17:04:32.663463: val_loss -0.7573 +2024-11-21 17:04:32.663542: Pseudo dice [0.836] +2024-11-21 17:04:32.663627: Epoch time: 18.93 s +2024-11-21 17:04:33.521546: +2024-11-21 17:04:33.521796: Epoch 1194 +2024-11-21 17:04:33.521909: Current learning rate: 0.00865 +2024-11-21 17:04:52.962832: train_loss -0.7791 +2024-11-21 17:04:52.963100: val_loss -0.7749 +2024-11-21 17:04:52.963174: Pseudo dice [0.8412] +2024-11-21 17:04:52.963247: Epoch time: 19.44 s +2024-11-21 17:04:53.872287: +2024-11-21 17:04:53.872495: Epoch 1195 +2024-11-21 17:04:53.872603: Current learning rate: 0.00864 +2024-11-21 17:05:12.728617: train_loss -0.7619 +2024-11-21 17:05:12.728829: val_loss -0.7671 +2024-11-21 17:05:12.728902: Pseudo dice [0.8492] +2024-11-21 17:05:12.728974: Epoch time: 18.86 s +2024-11-21 17:05:13.590911: +2024-11-21 17:05:13.591132: Epoch 1196 +2024-11-21 17:05:13.591245: Current learning rate: 0.00864 +2024-11-21 17:05:32.092841: train_loss -0.7626 +2024-11-21 17:05:32.093066: val_loss -0.7651 +2024-11-21 17:05:32.093145: Pseudo dice [0.8375] +2024-11-21 17:05:32.093222: Epoch time: 18.5 s +2024-11-21 17:05:32.930583: +2024-11-21 17:05:32.930822: Epoch 1197 +2024-11-21 17:05:32.930941: Current learning rate: 0.00864 +2024-11-21 17:05:51.413951: train_loss -0.783 +2024-11-21 17:05:51.414427: val_loss -0.7424 +2024-11-21 17:05:51.414526: Pseudo dice [0.8257] +2024-11-21 17:05:51.414604: Epoch time: 18.48 s +2024-11-21 17:05:52.244096: +2024-11-21 17:05:52.244321: Epoch 1198 +2024-11-21 17:05:52.244432: Current learning rate: 0.00864 +2024-11-21 17:06:11.217539: train_loss -0.772 +2024-11-21 17:06:11.217757: val_loss -0.732 +2024-11-21 17:06:11.217837: Pseudo dice [0.8178] +2024-11-21 17:06:11.217916: Epoch time: 18.97 s +2024-11-21 17:06:12.074855: +2024-11-21 17:06:12.075096: Epoch 1199 +2024-11-21 17:06:12.075207: Current learning rate: 0.00864 +2024-11-21 17:06:30.414061: train_loss -0.7734 +2024-11-21 17:06:30.414271: val_loss -0.7647 +2024-11-21 17:06:30.414346: Pseudo dice [0.8411] +2024-11-21 17:06:30.414421: Epoch time: 18.34 s +2024-11-21 17:06:31.458756: +2024-11-21 17:06:31.458975: Epoch 1200 +2024-11-21 17:06:31.459089: Current learning rate: 0.00864 +2024-11-21 17:06:49.703824: train_loss -0.7643 +2024-11-21 17:06:49.704081: val_loss -0.7717 +2024-11-21 17:06:49.704228: Pseudo dice [0.8247] +2024-11-21 17:06:49.704309: Epoch time: 18.25 s +2024-11-21 17:06:50.528756: +2024-11-21 17:06:50.528963: Epoch 1201 +2024-11-21 17:06:50.529083: Current learning rate: 0.00864 +2024-11-21 17:07:07.723718: train_loss -0.7597 +2024-11-21 17:07:07.723918: val_loss -0.7329 +2024-11-21 17:07:07.723998: Pseudo dice [0.847] +2024-11-21 17:07:07.724070: Epoch time: 17.2 s +2024-11-21 17:07:08.551061: +2024-11-21 17:07:08.551279: Epoch 1202 +2024-11-21 17:07:08.551396: Current learning rate: 0.00864 +2024-11-21 17:07:26.721746: train_loss -0.767 +2024-11-21 17:07:26.721997: val_loss -0.7802 +2024-11-21 17:07:26.722075: Pseudo dice [0.8225] +2024-11-21 17:07:26.722149: Epoch time: 18.17 s +2024-11-21 17:07:27.555762: +2024-11-21 17:07:27.555974: Epoch 1203 +2024-11-21 17:07:27.556091: Current learning rate: 0.00864 +2024-11-21 17:07:46.451466: train_loss -0.7716 +2024-11-21 17:07:46.451675: val_loss -0.7759 +2024-11-21 17:07:46.451757: Pseudo dice [0.8534] +2024-11-21 17:07:46.451839: Epoch time: 18.9 s +2024-11-21 17:07:47.272944: +2024-11-21 17:07:47.273157: Epoch 1204 +2024-11-21 17:07:47.273288: Current learning rate: 0.00863 +2024-11-21 17:08:05.101620: train_loss -0.7602 +2024-11-21 17:08:05.102137: val_loss -0.7702 +2024-11-21 17:08:05.102224: Pseudo dice [0.8428] +2024-11-21 17:08:05.102304: Epoch time: 17.83 s +2024-11-21 17:08:05.932096: +2024-11-21 17:08:05.932310: Epoch 1205 +2024-11-21 17:08:05.932427: Current learning rate: 0.00863 +2024-11-21 17:08:24.854174: train_loss -0.7758 +2024-11-21 17:08:24.854386: val_loss -0.7259 +2024-11-21 17:08:24.854459: Pseudo dice [0.8189] +2024-11-21 17:08:24.854536: Epoch time: 18.92 s +2024-11-21 17:08:25.677739: +2024-11-21 17:08:25.678031: Epoch 1206 +2024-11-21 17:08:25.678153: Current learning rate: 0.00863 +2024-11-21 17:08:44.349730: train_loss -0.7689 +2024-11-21 17:08:44.350008: val_loss -0.7424 +2024-11-21 17:08:44.350085: Pseudo dice [0.8317] +2024-11-21 17:08:44.350159: Epoch time: 18.67 s +2024-11-21 17:08:45.237667: +2024-11-21 17:08:45.237881: Epoch 1207 +2024-11-21 17:08:45.238003: Current learning rate: 0.00863 +2024-11-21 17:09:03.243934: train_loss -0.7617 +2024-11-21 17:09:03.244188: val_loss -0.7619 +2024-11-21 17:09:03.244272: Pseudo dice [0.8307] +2024-11-21 17:09:03.244351: Epoch time: 18.01 s +2024-11-21 17:09:04.075160: +2024-11-21 17:09:04.075409: Epoch 1208 +2024-11-21 17:09:04.075525: Current learning rate: 0.00863 +2024-11-21 17:09:22.066277: train_loss -0.7697 +2024-11-21 17:09:22.066746: val_loss -0.757 +2024-11-21 17:09:22.066842: Pseudo dice [0.8406] +2024-11-21 17:09:22.066924: Epoch time: 17.99 s +2024-11-21 17:09:22.890229: +2024-11-21 17:09:22.890437: Epoch 1209 +2024-11-21 17:09:22.890544: Current learning rate: 0.00863 +2024-11-21 17:09:41.459814: train_loss -0.7681 +2024-11-21 17:09:41.460030: val_loss -0.773 +2024-11-21 17:09:41.460114: Pseudo dice [0.8397] +2024-11-21 17:09:41.460190: Epoch time: 18.57 s +2024-11-21 17:09:42.286468: +2024-11-21 17:09:42.286676: Epoch 1210 +2024-11-21 17:09:42.286788: Current learning rate: 0.00863 +2024-11-21 17:10:00.551775: train_loss -0.7795 +2024-11-21 17:10:00.552696: val_loss -0.7827 +2024-11-21 17:10:00.552779: Pseudo dice [0.8548] +2024-11-21 17:10:00.552859: Epoch time: 18.27 s +2024-11-21 17:10:01.377717: +2024-11-21 17:10:01.377915: Epoch 1211 +2024-11-21 17:10:01.378026: Current learning rate: 0.00863 +2024-11-21 17:10:20.525571: train_loss -0.7764 +2024-11-21 17:10:20.525804: val_loss -0.7627 +2024-11-21 17:10:20.525888: Pseudo dice [0.8148] +2024-11-21 17:10:20.525963: Epoch time: 19.15 s +2024-11-21 17:10:21.359442: +2024-11-21 17:10:21.359663: Epoch 1212 +2024-11-21 17:10:21.359772: Current learning rate: 0.00863 +2024-11-21 17:10:40.143740: train_loss -0.769 +2024-11-21 17:10:40.144040: val_loss -0.7324 +2024-11-21 17:10:40.144126: Pseudo dice [0.8198] +2024-11-21 17:10:40.144205: Epoch time: 18.79 s +2024-11-21 17:10:41.181195: +2024-11-21 17:10:41.181427: Epoch 1213 +2024-11-21 17:10:41.181550: Current learning rate: 0.00862 +2024-11-21 17:11:00.022696: train_loss -0.772 +2024-11-21 17:11:00.022908: val_loss -0.7356 +2024-11-21 17:11:00.023006: Pseudo dice [0.8275] +2024-11-21 17:11:00.023084: Epoch time: 18.84 s +2024-11-21 17:11:00.925001: +2024-11-21 17:11:00.925226: Epoch 1214 +2024-11-21 17:11:00.925338: Current learning rate: 0.00862 +2024-11-21 17:11:20.104913: train_loss -0.763 +2024-11-21 17:11:20.105248: val_loss -0.7535 +2024-11-21 17:11:20.105336: Pseudo dice [0.8354] +2024-11-21 17:11:20.105423: Epoch time: 19.18 s +2024-11-21 17:11:20.942566: +2024-11-21 17:11:20.942944: Epoch 1215 +2024-11-21 17:11:20.943058: Current learning rate: 0.00862 +2024-11-21 17:11:39.650941: train_loss -0.7673 +2024-11-21 17:11:39.651170: val_loss -0.7652 +2024-11-21 17:11:39.651252: Pseudo dice [0.833] +2024-11-21 17:11:39.651330: Epoch time: 18.71 s +2024-11-21 17:11:40.580304: +2024-11-21 17:11:40.580519: Epoch 1216 +2024-11-21 17:11:40.580636: Current learning rate: 0.00862 +2024-11-21 17:11:59.793178: train_loss -0.7611 +2024-11-21 17:11:59.793435: val_loss -0.7529 +2024-11-21 17:11:59.793508: Pseudo dice [0.8366] +2024-11-21 17:11:59.793581: Epoch time: 19.21 s +2024-11-21 17:12:00.613848: +2024-11-21 17:12:00.614054: Epoch 1217 +2024-11-21 17:12:00.614165: Current learning rate: 0.00862 +2024-11-21 17:12:19.680648: train_loss -0.758 +2024-11-21 17:12:19.680942: val_loss -0.7788 +2024-11-21 17:12:19.681025: Pseudo dice [0.8462] +2024-11-21 17:12:19.681103: Epoch time: 19.07 s +2024-11-21 17:12:20.508630: +2024-11-21 17:12:20.508860: Epoch 1218 +2024-11-21 17:12:20.508971: Current learning rate: 0.00862 +2024-11-21 17:12:39.421629: train_loss -0.7623 +2024-11-21 17:12:39.424315: val_loss -0.7374 +2024-11-21 17:12:39.424406: Pseudo dice [0.8454] +2024-11-21 17:12:39.424484: Epoch time: 18.91 s +2024-11-21 17:12:40.312951: +2024-11-21 17:12:40.313201: Epoch 1219 +2024-11-21 17:12:40.313316: Current learning rate: 0.00862 +2024-11-21 17:12:58.131688: train_loss -0.7664 +2024-11-21 17:12:58.131959: val_loss -0.7451 +2024-11-21 17:12:58.132043: Pseudo dice [0.8456] +2024-11-21 17:12:58.132121: Epoch time: 17.82 s +2024-11-21 17:12:59.329524: +2024-11-21 17:12:59.329748: Epoch 1220 +2024-11-21 17:12:59.329859: Current learning rate: 0.00862 +2024-11-21 17:13:17.672849: train_loss -0.7598 +2024-11-21 17:13:17.673099: val_loss -0.7466 +2024-11-21 17:13:17.673175: Pseudo dice [0.829] +2024-11-21 17:13:17.673254: Epoch time: 18.34 s +2024-11-21 17:13:18.497499: +2024-11-21 17:13:18.497725: Epoch 1221 +2024-11-21 17:13:18.497839: Current learning rate: 0.00862 +2024-11-21 17:13:37.456717: train_loss -0.7606 +2024-11-21 17:13:37.457034: val_loss -0.767 +2024-11-21 17:13:37.457113: Pseudo dice [0.8443] +2024-11-21 17:13:37.457198: Epoch time: 18.96 s +2024-11-21 17:13:38.285495: +2024-11-21 17:13:38.285824: Epoch 1222 +2024-11-21 17:13:38.285941: Current learning rate: 0.00861 +2024-11-21 17:13:57.437168: train_loss -0.7504 +2024-11-21 17:13:57.437370: val_loss -0.7616 +2024-11-21 17:13:57.437449: Pseudo dice [0.8274] +2024-11-21 17:13:57.437534: Epoch time: 19.15 s +2024-11-21 17:13:58.414917: +2024-11-21 17:13:58.415164: Epoch 1223 +2024-11-21 17:13:58.415281: Current learning rate: 0.00861 +2024-11-21 17:14:16.927178: train_loss -0.7692 +2024-11-21 17:14:16.932575: val_loss -0.7771 +2024-11-21 17:14:16.932683: Pseudo dice [0.8282] +2024-11-21 17:14:16.932761: Epoch time: 18.51 s +2024-11-21 17:14:17.771149: +2024-11-21 17:14:17.771457: Epoch 1224 +2024-11-21 17:14:17.771574: Current learning rate: 0.00861 +2024-11-21 17:14:36.771285: train_loss -0.7547 +2024-11-21 17:14:36.771495: val_loss -0.7483 +2024-11-21 17:14:36.771568: Pseudo dice [0.8277] +2024-11-21 17:14:36.771639: Epoch time: 19.0 s +2024-11-21 17:14:37.607138: +2024-11-21 17:14:37.607359: Epoch 1225 +2024-11-21 17:14:37.607464: Current learning rate: 0.00861 +2024-11-21 17:14:56.321525: train_loss -0.76 +2024-11-21 17:14:56.321823: val_loss -0.7603 +2024-11-21 17:14:56.321907: Pseudo dice [0.8528] +2024-11-21 17:14:56.322031: Epoch time: 18.72 s +2024-11-21 17:14:57.254679: +2024-11-21 17:14:57.254893: Epoch 1226 +2024-11-21 17:14:57.255003: Current learning rate: 0.00861 +2024-11-21 17:15:16.067505: train_loss -0.7739 +2024-11-21 17:15:16.067714: val_loss -0.7339 +2024-11-21 17:15:16.067788: Pseudo dice [0.8333] +2024-11-21 17:15:16.067862: Epoch time: 18.81 s +2024-11-21 17:15:16.894580: +2024-11-21 17:15:16.894776: Epoch 1227 +2024-11-21 17:15:16.894885: Current learning rate: 0.00861 +2024-11-21 17:15:35.899131: train_loss -0.7698 +2024-11-21 17:15:35.899369: val_loss -0.7738 +2024-11-21 17:15:35.899445: Pseudo dice [0.8498] +2024-11-21 17:15:35.899590: Epoch time: 19.01 s +2024-11-21 17:15:36.750170: +2024-11-21 17:15:36.750396: Epoch 1228 +2024-11-21 17:15:36.750506: Current learning rate: 0.00861 +2024-11-21 17:15:54.866287: train_loss -0.7643 +2024-11-21 17:15:54.866519: val_loss -0.7537 +2024-11-21 17:15:54.866596: Pseudo dice [0.8428] +2024-11-21 17:15:54.866679: Epoch time: 18.12 s +2024-11-21 17:15:55.696434: +2024-11-21 17:15:55.696640: Epoch 1229 +2024-11-21 17:15:55.696753: Current learning rate: 0.00861 +2024-11-21 17:16:14.123338: train_loss -0.7695 +2024-11-21 17:16:14.123576: val_loss -0.7679 +2024-11-21 17:16:14.123651: Pseudo dice [0.8259] +2024-11-21 17:16:14.123759: Epoch time: 18.43 s +2024-11-21 17:16:14.957777: +2024-11-21 17:16:14.957984: Epoch 1230 +2024-11-21 17:16:14.958096: Current learning rate: 0.0086 +2024-11-21 17:16:33.274623: train_loss -0.7724 +2024-11-21 17:16:33.275102: val_loss -0.7714 +2024-11-21 17:16:33.275191: Pseudo dice [0.8464] +2024-11-21 17:16:33.275267: Epoch time: 18.32 s +2024-11-21 17:16:34.485372: +2024-11-21 17:16:34.485615: Epoch 1231 +2024-11-21 17:16:34.485726: Current learning rate: 0.0086 +2024-11-21 17:16:54.033499: train_loss -0.7652 +2024-11-21 17:16:54.033710: val_loss -0.7355 +2024-11-21 17:16:54.033785: Pseudo dice [0.8541] +2024-11-21 17:16:54.033857: Epoch time: 19.55 s +2024-11-21 17:16:54.852570: +2024-11-21 17:16:54.852782: Epoch 1232 +2024-11-21 17:16:54.852891: Current learning rate: 0.0086 +2024-11-21 17:17:14.102144: train_loss -0.7531 +2024-11-21 17:17:14.102384: val_loss -0.7644 +2024-11-21 17:17:14.102460: Pseudo dice [0.8516] +2024-11-21 17:17:14.102540: Epoch time: 19.25 s +2024-11-21 17:17:14.927881: +2024-11-21 17:17:14.928120: Epoch 1233 +2024-11-21 17:17:14.928231: Current learning rate: 0.0086 +2024-11-21 17:17:32.712874: train_loss -0.7531 +2024-11-21 17:17:32.713104: val_loss -0.765 +2024-11-21 17:17:32.713196: Pseudo dice [0.8206] +2024-11-21 17:17:32.713272: Epoch time: 17.79 s +2024-11-21 17:17:33.540032: +2024-11-21 17:17:33.540263: Epoch 1234 +2024-11-21 17:17:33.540375: Current learning rate: 0.0086 +2024-11-21 17:17:52.858498: train_loss -0.7635 +2024-11-21 17:17:52.858703: val_loss -0.7677 +2024-11-21 17:17:52.858779: Pseudo dice [0.8388] +2024-11-21 17:17:52.858854: Epoch time: 19.32 s +2024-11-21 17:17:53.689070: +2024-11-21 17:17:53.689288: Epoch 1235 +2024-11-21 17:17:53.689395: Current learning rate: 0.0086 +2024-11-21 17:18:12.636245: train_loss -0.761 +2024-11-21 17:18:12.636468: val_loss -0.7547 +2024-11-21 17:18:12.636544: Pseudo dice [0.8374] +2024-11-21 17:18:12.636616: Epoch time: 18.95 s +2024-11-21 17:18:13.474464: +2024-11-21 17:18:13.474687: Epoch 1236 +2024-11-21 17:18:13.474809: Current learning rate: 0.0086 +2024-11-21 17:18:31.141934: train_loss -0.763 +2024-11-21 17:18:31.142179: val_loss -0.7833 +2024-11-21 17:18:31.142256: Pseudo dice [0.8508] +2024-11-21 17:18:31.144591: Epoch time: 17.67 s +2024-11-21 17:18:32.162496: +2024-11-21 17:18:32.162887: Epoch 1237 +2024-11-21 17:18:32.163007: Current learning rate: 0.0086 +2024-11-21 17:18:50.557060: train_loss -0.7535 +2024-11-21 17:18:50.557269: val_loss -0.7343 +2024-11-21 17:18:50.557345: Pseudo dice [0.8214] +2024-11-21 17:18:50.557414: Epoch time: 18.4 s +2024-11-21 17:18:51.384571: +2024-11-21 17:18:51.384831: Epoch 1238 +2024-11-21 17:18:51.384939: Current learning rate: 0.0086 +2024-11-21 17:19:09.473397: train_loss -0.7584 +2024-11-21 17:19:09.473612: val_loss -0.7409 +2024-11-21 17:19:09.473682: Pseudo dice [0.8398] +2024-11-21 17:19:09.473752: Epoch time: 18.09 s +2024-11-21 17:19:10.300330: +2024-11-21 17:19:10.300542: Epoch 1239 +2024-11-21 17:19:10.300666: Current learning rate: 0.00859 +2024-11-21 17:19:28.767980: train_loss -0.7637 +2024-11-21 17:19:28.773390: val_loss -0.7458 +2024-11-21 17:19:28.773505: Pseudo dice [0.8488] +2024-11-21 17:19:28.773597: Epoch time: 18.47 s +2024-11-21 17:19:29.610875: +2024-11-21 17:19:29.611096: Epoch 1240 +2024-11-21 17:19:29.611204: Current learning rate: 0.00859 +2024-11-21 17:19:47.641363: train_loss -0.7578 +2024-11-21 17:19:47.641599: val_loss -0.7401 +2024-11-21 17:19:47.641679: Pseudo dice [0.8313] +2024-11-21 17:19:47.641767: Epoch time: 18.03 s +2024-11-21 17:19:48.467995: +2024-11-21 17:19:48.468250: Epoch 1241 +2024-11-21 17:19:48.468362: Current learning rate: 0.00859 +2024-11-21 17:20:06.264734: train_loss -0.7606 +2024-11-21 17:20:06.264950: val_loss -0.7375 +2024-11-21 17:20:06.265033: Pseudo dice [0.8427] +2024-11-21 17:20:06.265105: Epoch time: 17.8 s +2024-11-21 17:20:07.092857: +2024-11-21 17:20:07.093071: Epoch 1242 +2024-11-21 17:20:07.093182: Current learning rate: 0.00859 +2024-11-21 17:20:24.656406: train_loss -0.7747 +2024-11-21 17:20:24.656610: val_loss -0.7358 +2024-11-21 17:20:24.656683: Pseudo dice [0.8401] +2024-11-21 17:20:24.656756: Epoch time: 17.56 s +2024-11-21 17:20:25.860876: +2024-11-21 17:20:25.861136: Epoch 1243 +2024-11-21 17:20:25.861250: Current learning rate: 0.00859 +2024-11-21 17:20:44.180035: train_loss -0.7618 +2024-11-21 17:20:44.180331: val_loss -0.752 +2024-11-21 17:20:44.180412: Pseudo dice [0.828] +2024-11-21 17:20:44.180492: Epoch time: 18.32 s +2024-11-21 17:20:45.011455: +2024-11-21 17:20:45.011697: Epoch 1244 +2024-11-21 17:20:45.011808: Current learning rate: 0.00859 +2024-11-21 17:21:02.344789: train_loss -0.7687 +2024-11-21 17:21:02.345011: val_loss -0.7647 +2024-11-21 17:21:02.345092: Pseudo dice [0.8524] +2024-11-21 17:21:02.345182: Epoch time: 17.33 s +2024-11-21 17:21:03.195460: +2024-11-21 17:21:03.195680: Epoch 1245 +2024-11-21 17:21:03.195794: Current learning rate: 0.00859 +2024-11-21 17:21:21.426906: train_loss -0.7612 +2024-11-21 17:21:21.427158: val_loss -0.7605 +2024-11-21 17:21:21.427232: Pseudo dice [0.8418] +2024-11-21 17:21:21.427304: Epoch time: 18.23 s +2024-11-21 17:21:22.249931: +2024-11-21 17:21:22.250148: Epoch 1246 +2024-11-21 17:21:22.250256: Current learning rate: 0.00859 +2024-11-21 17:21:40.062675: train_loss -0.7654 +2024-11-21 17:21:40.062971: val_loss -0.7512 +2024-11-21 17:21:40.063054: Pseudo dice [0.8346] +2024-11-21 17:21:40.063137: Epoch time: 17.81 s +2024-11-21 17:21:40.902497: +2024-11-21 17:21:40.902860: Epoch 1247 +2024-11-21 17:21:40.902970: Current learning rate: 0.00859 +2024-11-21 17:21:58.751478: train_loss -0.7688 +2024-11-21 17:21:58.751686: val_loss -0.7813 +2024-11-21 17:21:58.751759: Pseudo dice [0.8506] +2024-11-21 17:21:58.751834: Epoch time: 17.85 s +2024-11-21 17:21:59.599402: +2024-11-21 17:21:59.599627: Epoch 1248 +2024-11-21 17:21:59.599739: Current learning rate: 0.00858 +2024-11-21 17:22:16.966396: train_loss -0.7605 +2024-11-21 17:22:16.966604: val_loss -0.7571 +2024-11-21 17:22:16.966679: Pseudo dice [0.8535] +2024-11-21 17:22:16.966753: Epoch time: 17.37 s +2024-11-21 17:22:17.787467: +2024-11-21 17:22:17.787688: Epoch 1249 +2024-11-21 17:22:17.787800: Current learning rate: 0.00858 +2024-11-21 17:22:36.222549: train_loss -0.7532 +2024-11-21 17:22:36.222755: val_loss -0.7709 +2024-11-21 17:22:36.222831: Pseudo dice [0.8449] +2024-11-21 17:22:36.222906: Epoch time: 18.44 s +2024-11-21 17:22:37.291744: +2024-11-21 17:22:37.291945: Epoch 1250 +2024-11-21 17:22:37.292058: Current learning rate: 0.00858 +2024-11-21 17:22:55.413434: train_loss -0.7702 +2024-11-21 17:22:55.413664: val_loss -0.7426 +2024-11-21 17:22:55.413740: Pseudo dice [0.8347] +2024-11-21 17:22:55.413819: Epoch time: 18.12 s +2024-11-21 17:22:56.253139: +2024-11-21 17:22:56.253374: Epoch 1251 +2024-11-21 17:22:56.253484: Current learning rate: 0.00858 +2024-11-21 17:23:14.665708: train_loss -0.7651 +2024-11-21 17:23:14.665998: val_loss -0.7616 +2024-11-21 17:23:14.666075: Pseudo dice [0.8345] +2024-11-21 17:23:14.666149: Epoch time: 18.41 s +2024-11-21 17:23:15.489466: +2024-11-21 17:23:15.489683: Epoch 1252 +2024-11-21 17:23:15.489790: Current learning rate: 0.00858 +2024-11-21 17:23:34.633108: train_loss -0.7576 +2024-11-21 17:23:34.633329: val_loss -0.748 +2024-11-21 17:23:34.633403: Pseudo dice [0.8448] +2024-11-21 17:23:34.633480: Epoch time: 19.14 s +2024-11-21 17:23:35.503593: +2024-11-21 17:23:35.503809: Epoch 1253 +2024-11-21 17:23:35.503926: Current learning rate: 0.00858 +2024-11-21 17:23:54.775365: train_loss -0.7501 +2024-11-21 17:23:54.777793: val_loss -0.734 +2024-11-21 17:23:54.777897: Pseudo dice [0.8201] +2024-11-21 17:23:54.777985: Epoch time: 19.27 s +2024-11-21 17:23:55.791837: +2024-11-21 17:23:55.792069: Epoch 1254 +2024-11-21 17:23:55.792179: Current learning rate: 0.00858 +2024-11-21 17:24:14.768745: train_loss -0.7622 +2024-11-21 17:24:14.769270: val_loss -0.768 +2024-11-21 17:24:14.769372: Pseudo dice [0.8389] +2024-11-21 17:24:14.769449: Epoch time: 18.98 s +2024-11-21 17:24:15.593095: +2024-11-21 17:24:15.593426: Epoch 1255 +2024-11-21 17:24:15.593534: Current learning rate: 0.00858 +2024-11-21 17:24:35.057861: train_loss -0.7742 +2024-11-21 17:24:35.058075: val_loss -0.7779 +2024-11-21 17:24:35.058156: Pseudo dice [0.8388] +2024-11-21 17:24:35.058235: Epoch time: 19.47 s +2024-11-21 17:24:35.884000: +2024-11-21 17:24:35.884228: Epoch 1256 +2024-11-21 17:24:35.884337: Current learning rate: 0.00858 +2024-11-21 17:24:54.449364: train_loss -0.7586 +2024-11-21 17:24:54.449614: val_loss -0.7465 +2024-11-21 17:24:54.449694: Pseudo dice [0.8394] +2024-11-21 17:24:54.449779: Epoch time: 18.57 s +2024-11-21 17:24:55.285888: +2024-11-21 17:24:55.286105: Epoch 1257 +2024-11-21 17:24:55.286223: Current learning rate: 0.00857 +2024-11-21 17:25:13.925595: train_loss -0.7628 +2024-11-21 17:25:13.925806: val_loss -0.7556 +2024-11-21 17:25:13.925879: Pseudo dice [0.8541] +2024-11-21 17:25:13.925951: Epoch time: 18.64 s +2024-11-21 17:25:14.793593: +2024-11-21 17:25:14.793815: Epoch 1258 +2024-11-21 17:25:14.793929: Current learning rate: 0.00857 +2024-11-21 17:25:33.921227: train_loss -0.7641 +2024-11-21 17:25:33.921443: val_loss -0.787 +2024-11-21 17:25:33.921521: Pseudo dice [0.8394] +2024-11-21 17:25:33.921670: Epoch time: 19.13 s +2024-11-21 17:25:34.748784: +2024-11-21 17:25:34.749018: Epoch 1259 +2024-11-21 17:25:34.749131: Current learning rate: 0.00857 +2024-11-21 17:25:53.511418: train_loss -0.771 +2024-11-21 17:25:53.511632: val_loss -0.7191 +2024-11-21 17:25:53.511712: Pseudo dice [0.8423] +2024-11-21 17:25:53.511786: Epoch time: 18.76 s +2024-11-21 17:25:54.335019: +2024-11-21 17:25:54.335247: Epoch 1260 +2024-11-21 17:25:54.335367: Current learning rate: 0.00857 +2024-11-21 17:26:11.725409: train_loss -0.7727 +2024-11-21 17:26:11.725648: val_loss -0.7569 +2024-11-21 17:26:11.725724: Pseudo dice [0.8449] +2024-11-21 17:26:11.725816: Epoch time: 17.39 s +2024-11-21 17:26:12.557864: +2024-11-21 17:26:12.558091: Epoch 1261 +2024-11-21 17:26:12.558209: Current learning rate: 0.00857 +2024-11-21 17:26:31.950700: train_loss -0.7587 +2024-11-21 17:26:31.950904: val_loss -0.7649 +2024-11-21 17:26:31.950976: Pseudo dice [0.8417] +2024-11-21 17:26:31.951055: Epoch time: 19.39 s +2024-11-21 17:26:32.781449: +2024-11-21 17:26:32.781657: Epoch 1262 +2024-11-21 17:26:32.781769: Current learning rate: 0.00857 +2024-11-21 17:26:51.325380: train_loss -0.7557 +2024-11-21 17:26:51.325584: val_loss -0.769 +2024-11-21 17:26:51.325658: Pseudo dice [0.8337] +2024-11-21 17:26:51.325731: Epoch time: 18.54 s +2024-11-21 17:26:52.156257: +2024-11-21 17:26:52.156460: Epoch 1263 +2024-11-21 17:26:52.156568: Current learning rate: 0.00857 +2024-11-21 17:27:10.376143: train_loss -0.765 +2024-11-21 17:27:10.376359: val_loss -0.7642 +2024-11-21 17:27:10.376435: Pseudo dice [0.8261] +2024-11-21 17:27:10.376509: Epoch time: 18.22 s +2024-11-21 17:27:11.213263: +2024-11-21 17:27:11.213474: Epoch 1264 +2024-11-21 17:27:11.213594: Current learning rate: 0.00857 +2024-11-21 17:27:30.110925: train_loss -0.7635 +2024-11-21 17:27:30.111162: val_loss -0.7653 +2024-11-21 17:27:30.111235: Pseudo dice [0.8359] +2024-11-21 17:27:30.111313: Epoch time: 18.9 s +2024-11-21 17:27:30.936678: +2024-11-21 17:27:30.936889: Epoch 1265 +2024-11-21 17:27:30.937003: Current learning rate: 0.00856 +2024-11-21 17:27:49.866675: train_loss -0.7694 +2024-11-21 17:27:49.866972: val_loss -0.7554 +2024-11-21 17:27:49.867062: Pseudo dice [0.8414] +2024-11-21 17:27:49.867136: Epoch time: 18.93 s +2024-11-21 17:27:50.718520: +2024-11-21 17:27:50.718761: Epoch 1266 +2024-11-21 17:27:50.718875: Current learning rate: 0.00856 +2024-11-21 17:28:08.258095: train_loss -0.765 +2024-11-21 17:28:08.258310: val_loss -0.7587 +2024-11-21 17:28:08.258388: Pseudo dice [0.8328] +2024-11-21 17:28:08.258465: Epoch time: 17.54 s +2024-11-21 17:28:09.088336: +2024-11-21 17:28:09.088580: Epoch 1267 +2024-11-21 17:28:09.088690: Current learning rate: 0.00856 +2024-11-21 17:28:27.195565: train_loss -0.7643 +2024-11-21 17:28:27.195825: val_loss -0.7398 +2024-11-21 17:28:27.195900: Pseudo dice [0.8348] +2024-11-21 17:28:27.195983: Epoch time: 18.11 s +2024-11-21 17:28:28.154965: +2024-11-21 17:28:28.155254: Epoch 1268 +2024-11-21 17:28:28.155366: Current learning rate: 0.00856 +2024-11-21 17:28:47.491058: train_loss -0.7783 +2024-11-21 17:28:47.491276: val_loss -0.7652 +2024-11-21 17:28:47.491349: Pseudo dice [0.8359] +2024-11-21 17:28:47.491426: Epoch time: 19.34 s +2024-11-21 17:28:48.323771: +2024-11-21 17:28:48.323982: Epoch 1269 +2024-11-21 17:28:48.324091: Current learning rate: 0.00856 +2024-11-21 17:29:06.588619: train_loss -0.7748 +2024-11-21 17:29:06.588820: val_loss -0.7484 +2024-11-21 17:29:06.588896: Pseudo dice [0.8391] +2024-11-21 17:29:06.588968: Epoch time: 18.27 s +2024-11-21 17:29:07.415552: +2024-11-21 17:29:07.415768: Epoch 1270 +2024-11-21 17:29:07.415878: Current learning rate: 0.00856 +2024-11-21 17:29:25.091890: train_loss -0.769 +2024-11-21 17:29:25.092103: val_loss -0.7472 +2024-11-21 17:29:25.092176: Pseudo dice [0.8571] +2024-11-21 17:29:25.092248: Epoch time: 17.68 s +2024-11-21 17:29:25.913508: +2024-11-21 17:29:25.913742: Epoch 1271 +2024-11-21 17:29:25.913867: Current learning rate: 0.00856 +2024-11-21 17:29:44.851625: train_loss -0.7773 +2024-11-21 17:29:44.851941: val_loss -0.7326 +2024-11-21 17:29:44.852076: Pseudo dice [0.8511] +2024-11-21 17:29:44.852160: Epoch time: 18.94 s +2024-11-21 17:29:45.682320: +2024-11-21 17:29:45.682539: Epoch 1272 +2024-11-21 17:29:45.682652: Current learning rate: 0.00856 +2024-11-21 17:30:04.129550: train_loss -0.7663 +2024-11-21 17:30:04.129765: val_loss -0.7352 +2024-11-21 17:30:04.129841: Pseudo dice [0.823] +2024-11-21 17:30:04.129916: Epoch time: 18.45 s +2024-11-21 17:30:04.955072: +2024-11-21 17:30:04.955283: Epoch 1273 +2024-11-21 17:30:04.955391: Current learning rate: 0.00856 +2024-11-21 17:30:22.421420: train_loss -0.7638 +2024-11-21 17:30:22.421623: val_loss -0.7665 +2024-11-21 17:30:22.421695: Pseudo dice [0.8519] +2024-11-21 17:30:22.421768: Epoch time: 17.47 s +2024-11-21 17:30:23.240273: +2024-11-21 17:30:23.240496: Epoch 1274 +2024-11-21 17:30:23.240604: Current learning rate: 0.00855 +2024-11-21 17:30:41.927897: train_loss -0.7626 +2024-11-21 17:30:41.928190: val_loss -0.7481 +2024-11-21 17:30:41.928269: Pseudo dice [0.8502] +2024-11-21 17:30:41.928345: Epoch time: 18.69 s +2024-11-21 17:30:42.757282: +2024-11-21 17:30:42.757504: Epoch 1275 +2024-11-21 17:30:42.757640: Current learning rate: 0.00855 +2024-11-21 17:31:01.194075: train_loss -0.7778 +2024-11-21 17:31:01.194318: val_loss -0.7481 +2024-11-21 17:31:01.194393: Pseudo dice [0.8404] +2024-11-21 17:31:01.194474: Epoch time: 18.44 s +2024-11-21 17:31:02.022063: +2024-11-21 17:31:02.022293: Epoch 1276 +2024-11-21 17:31:02.022413: Current learning rate: 0.00855 +2024-11-21 17:31:19.609114: train_loss -0.768 +2024-11-21 17:31:19.609321: val_loss -0.7766 +2024-11-21 17:31:19.609395: Pseudo dice [0.8464] +2024-11-21 17:31:19.609468: Epoch time: 17.59 s +2024-11-21 17:31:20.793189: +2024-11-21 17:31:20.793412: Epoch 1277 +2024-11-21 17:31:20.793522: Current learning rate: 0.00855 +2024-11-21 17:31:38.347264: train_loss -0.7727 +2024-11-21 17:31:38.347487: val_loss -0.7642 +2024-11-21 17:31:38.347559: Pseudo dice [0.8446] +2024-11-21 17:31:38.347636: Epoch time: 17.55 s +2024-11-21 17:31:39.181029: +2024-11-21 17:31:39.181243: Epoch 1278 +2024-11-21 17:31:39.181351: Current learning rate: 0.00855 +2024-11-21 17:31:57.134869: train_loss -0.7746 +2024-11-21 17:31:57.135110: val_loss -0.7614 +2024-11-21 17:31:57.135185: Pseudo dice [0.8375] +2024-11-21 17:31:57.135263: Epoch time: 17.95 s +2024-11-21 17:31:57.961762: +2024-11-21 17:31:57.961985: Epoch 1279 +2024-11-21 17:31:57.962094: Current learning rate: 0.00855 +2024-11-21 17:32:16.424008: train_loss -0.7683 +2024-11-21 17:32:16.424230: val_loss -0.7549 +2024-11-21 17:32:16.424365: Pseudo dice [0.8331] +2024-11-21 17:32:16.424444: Epoch time: 18.46 s +2024-11-21 17:32:17.255171: +2024-11-21 17:32:17.255382: Epoch 1280 +2024-11-21 17:32:17.255498: Current learning rate: 0.00855 +2024-11-21 17:32:36.354523: train_loss -0.7726 +2024-11-21 17:32:36.356932: val_loss -0.7629 +2024-11-21 17:32:36.357030: Pseudo dice [0.8336] +2024-11-21 17:32:36.357114: Epoch time: 19.1 s +2024-11-21 17:32:37.293523: +2024-11-21 17:32:37.293715: Epoch 1281 +2024-11-21 17:32:37.293819: Current learning rate: 0.00855 +2024-11-21 17:32:55.276902: train_loss -0.7786 +2024-11-21 17:32:55.277130: val_loss -0.7642 +2024-11-21 17:32:55.277212: Pseudo dice [0.847] +2024-11-21 17:32:55.277295: Epoch time: 17.98 s +2024-11-21 17:32:56.346653: +2024-11-21 17:32:56.347074: Epoch 1282 +2024-11-21 17:32:56.347208: Current learning rate: 0.00855 +2024-11-21 17:33:14.366217: train_loss -0.7762 +2024-11-21 17:33:14.368623: val_loss -0.7619 +2024-11-21 17:33:14.368714: Pseudo dice [0.8309] +2024-11-21 17:33:14.368789: Epoch time: 18.02 s +2024-11-21 17:33:15.279544: +2024-11-21 17:33:15.279768: Epoch 1283 +2024-11-21 17:33:15.279879: Current learning rate: 0.00854 +2024-11-21 17:33:34.923030: train_loss -0.7626 +2024-11-21 17:33:34.923253: val_loss -0.7565 +2024-11-21 17:33:34.923334: Pseudo dice [0.8324] +2024-11-21 17:33:34.923414: Epoch time: 19.64 s +2024-11-21 17:33:35.751971: +2024-11-21 17:33:35.752185: Epoch 1284 +2024-11-21 17:33:35.752297: Current learning rate: 0.00854 +2024-11-21 17:33:54.410158: train_loss -0.7643 +2024-11-21 17:33:54.410380: val_loss -0.7468 +2024-11-21 17:33:54.410459: Pseudo dice [0.8409] +2024-11-21 17:33:54.410534: Epoch time: 18.66 s +2024-11-21 17:33:55.241001: +2024-11-21 17:33:55.241215: Epoch 1285 +2024-11-21 17:33:55.241325: Current learning rate: 0.00854 +2024-11-21 17:34:13.083252: train_loss -0.7748 +2024-11-21 17:34:13.083496: val_loss -0.766 +2024-11-21 17:34:13.083575: Pseudo dice [0.8386] +2024-11-21 17:34:13.083658: Epoch time: 17.84 s +2024-11-21 17:34:13.958625: +2024-11-21 17:34:13.958859: Epoch 1286 +2024-11-21 17:34:13.958971: Current learning rate: 0.00854 +2024-11-21 17:34:32.374453: train_loss -0.7582 +2024-11-21 17:34:32.374669: val_loss -0.7672 +2024-11-21 17:34:32.374764: Pseudo dice [0.8498] +2024-11-21 17:34:32.374851: Epoch time: 18.42 s +2024-11-21 17:34:33.193041: +2024-11-21 17:34:33.193250: Epoch 1287 +2024-11-21 17:34:33.193357: Current learning rate: 0.00854 +2024-11-21 17:34:50.872738: train_loss -0.7586 +2024-11-21 17:34:50.872954: val_loss -0.7707 +2024-11-21 17:34:50.873032: Pseudo dice [0.8493] +2024-11-21 17:34:50.873103: Epoch time: 17.68 s +2024-11-21 17:34:51.719517: +2024-11-21 17:34:51.719730: Epoch 1288 +2024-11-21 17:34:51.719838: Current learning rate: 0.00854 +2024-11-21 17:35:09.978958: train_loss -0.7774 +2024-11-21 17:35:09.979445: val_loss -0.7553 +2024-11-21 17:35:09.979544: Pseudo dice [0.8196] +2024-11-21 17:35:09.979628: Epoch time: 18.26 s +2024-11-21 17:35:10.807955: +2024-11-21 17:35:10.808218: Epoch 1289 +2024-11-21 17:35:10.808365: Current learning rate: 0.00854 +2024-11-21 17:35:28.975216: train_loss -0.7638 +2024-11-21 17:35:28.975441: val_loss -0.7528 +2024-11-21 17:35:28.975521: Pseudo dice [0.844] +2024-11-21 17:35:28.975598: Epoch time: 18.17 s +2024-11-21 17:35:29.809356: +2024-11-21 17:35:29.809577: Epoch 1290 +2024-11-21 17:35:29.809684: Current learning rate: 0.00854 +2024-11-21 17:35:48.327579: train_loss -0.7721 +2024-11-21 17:35:48.327865: val_loss -0.7721 +2024-11-21 17:35:48.327942: Pseudo dice [0.8473] +2024-11-21 17:35:48.328022: Epoch time: 18.52 s +2024-11-21 17:35:49.157902: +2024-11-21 17:35:49.158140: Epoch 1291 +2024-11-21 17:35:49.158265: Current learning rate: 0.00854 +2024-11-21 17:36:07.201330: train_loss -0.7681 +2024-11-21 17:36:07.201541: val_loss -0.7603 +2024-11-21 17:36:07.203840: Pseudo dice [0.843] +2024-11-21 17:36:07.203938: Epoch time: 18.04 s +2024-11-21 17:36:08.143610: +2024-11-21 17:36:08.143837: Epoch 1292 +2024-11-21 17:36:08.143947: Current learning rate: 0.00853 +2024-11-21 17:36:26.675425: train_loss -0.7737 +2024-11-21 17:36:26.675672: val_loss -0.7708 +2024-11-21 17:36:26.675792: Pseudo dice [0.8396] +2024-11-21 17:36:26.675878: Epoch time: 18.53 s +2024-11-21 17:36:27.507795: +2024-11-21 17:36:27.508031: Epoch 1293 +2024-11-21 17:36:27.508136: Current learning rate: 0.00853 +2024-11-21 17:36:46.956878: train_loss -0.7692 +2024-11-21 17:36:46.957128: val_loss -0.7445 +2024-11-21 17:36:46.957204: Pseudo dice [0.8235] +2024-11-21 17:36:46.957279: Epoch time: 19.45 s +2024-11-21 17:36:47.932014: +2024-11-21 17:36:47.932236: Epoch 1294 +2024-11-21 17:36:47.932343: Current learning rate: 0.00853 +2024-11-21 17:37:07.867467: train_loss -0.7789 +2024-11-21 17:37:07.867687: val_loss -0.7445 +2024-11-21 17:37:07.867764: Pseudo dice [0.8187] +2024-11-21 17:37:07.867836: Epoch time: 19.94 s +2024-11-21 17:37:08.694150: +2024-11-21 17:37:08.694337: Epoch 1295 +2024-11-21 17:37:08.694441: Current learning rate: 0.00853 +2024-11-21 17:37:28.580325: train_loss -0.7584 +2024-11-21 17:37:28.580555: val_loss -0.7633 +2024-11-21 17:37:28.580636: Pseudo dice [0.8412] +2024-11-21 17:37:28.580715: Epoch time: 19.89 s +2024-11-21 17:37:29.491185: +2024-11-21 17:37:29.491388: Epoch 1296 +2024-11-21 17:37:29.491498: Current learning rate: 0.00853 +2024-11-21 17:37:47.025095: train_loss -0.7597 +2024-11-21 17:37:47.030527: val_loss -0.7442 +2024-11-21 17:37:47.030674: Pseudo dice [0.8396] +2024-11-21 17:37:47.030766: Epoch time: 17.53 s +2024-11-21 17:37:47.886424: +2024-11-21 17:37:47.886616: Epoch 1297 +2024-11-21 17:37:47.886726: Current learning rate: 0.00853 +2024-11-21 17:38:06.510146: train_loss -0.754 +2024-11-21 17:38:06.510369: val_loss -0.7652 +2024-11-21 17:38:06.510444: Pseudo dice [0.8319] +2024-11-21 17:38:06.510519: Epoch time: 18.62 s +2024-11-21 17:38:07.376409: +2024-11-21 17:38:07.376647: Epoch 1298 +2024-11-21 17:38:07.376758: Current learning rate: 0.00853 +2024-11-21 17:38:26.417066: train_loss -0.7607 +2024-11-21 17:38:26.417276: val_loss -0.7633 +2024-11-21 17:38:26.417351: Pseudo dice [0.8432] +2024-11-21 17:38:26.417426: Epoch time: 19.04 s +2024-11-21 17:38:27.246139: +2024-11-21 17:38:27.246358: Epoch 1299 +2024-11-21 17:38:27.246477: Current learning rate: 0.00853 +2024-11-21 17:38:46.917472: train_loss -0.7616 +2024-11-21 17:38:46.917718: val_loss -0.7412 +2024-11-21 17:38:46.917800: Pseudo dice [0.8401] +2024-11-21 17:38:46.917884: Epoch time: 19.67 s +2024-11-21 17:38:48.305297: +2024-11-21 17:38:48.305524: Epoch 1300 +2024-11-21 17:38:48.305635: Current learning rate: 0.00852 +2024-11-21 17:39:07.117128: train_loss -0.7735 +2024-11-21 17:39:07.117338: val_loss -0.7683 +2024-11-21 17:39:07.117411: Pseudo dice [0.8505] +2024-11-21 17:39:07.117485: Epoch time: 18.81 s +2024-11-21 17:39:07.996015: +2024-11-21 17:39:07.996215: Epoch 1301 +2024-11-21 17:39:07.996324: Current learning rate: 0.00852 +2024-11-21 17:39:27.214106: train_loss -0.7706 +2024-11-21 17:39:27.214321: val_loss -0.7536 +2024-11-21 17:39:27.214398: Pseudo dice [0.8499] +2024-11-21 17:39:27.214471: Epoch time: 19.22 s +2024-11-21 17:39:28.037186: +2024-11-21 17:39:28.037415: Epoch 1302 +2024-11-21 17:39:28.037522: Current learning rate: 0.00852 +2024-11-21 17:39:46.722277: train_loss -0.7564 +2024-11-21 17:39:46.722556: val_loss -0.7354 +2024-11-21 17:39:46.722635: Pseudo dice [0.8121] +2024-11-21 17:39:46.722719: Epoch time: 18.69 s +2024-11-21 17:39:47.566170: +2024-11-21 17:39:47.566468: Epoch 1303 +2024-11-21 17:39:47.566612: Current learning rate: 0.00852 +2024-11-21 17:40:06.184825: train_loss -0.7539 +2024-11-21 17:40:06.185061: val_loss -0.7529 +2024-11-21 17:40:06.185138: Pseudo dice [0.8442] +2024-11-21 17:40:06.185215: Epoch time: 18.62 s +2024-11-21 17:40:07.015111: +2024-11-21 17:40:07.015324: Epoch 1304 +2024-11-21 17:40:07.015434: Current learning rate: 0.00852 +2024-11-21 17:40:25.990589: train_loss -0.7622 +2024-11-21 17:40:25.990807: val_loss -0.7589 +2024-11-21 17:40:25.990948: Pseudo dice [0.8326] +2024-11-21 17:40:25.991027: Epoch time: 18.98 s +2024-11-21 17:40:26.980759: +2024-11-21 17:40:26.981060: Epoch 1305 +2024-11-21 17:40:26.981166: Current learning rate: 0.00852 +2024-11-21 17:40:45.641668: train_loss -0.7654 +2024-11-21 17:40:45.641885: val_loss -0.733 +2024-11-21 17:40:45.641955: Pseudo dice [0.8351] +2024-11-21 17:40:45.642035: Epoch time: 18.66 s +2024-11-21 17:40:46.489913: +2024-11-21 17:40:46.490130: Epoch 1306 +2024-11-21 17:40:46.490251: Current learning rate: 0.00852 +2024-11-21 17:41:04.343276: train_loss -0.7567 +2024-11-21 17:41:04.343498: val_loss -0.7597 +2024-11-21 17:41:04.343593: Pseudo dice [0.8458] +2024-11-21 17:41:04.343680: Epoch time: 17.85 s +2024-11-21 17:41:05.171247: +2024-11-21 17:41:05.171611: Epoch 1307 +2024-11-21 17:41:05.171718: Current learning rate: 0.00852 +2024-11-21 17:41:23.580366: train_loss -0.7427 +2024-11-21 17:41:23.580645: val_loss -0.7497 +2024-11-21 17:41:23.580724: Pseudo dice [0.833] +2024-11-21 17:41:23.580805: Epoch time: 18.41 s +2024-11-21 17:41:24.413657: +2024-11-21 17:41:24.413893: Epoch 1308 +2024-11-21 17:41:24.414550: Current learning rate: 0.00852 +2024-11-21 17:41:44.205252: train_loss -0.7184 +2024-11-21 17:41:44.205455: val_loss -0.7485 +2024-11-21 17:41:44.205527: Pseudo dice [0.8145] +2024-11-21 17:41:44.205599: Epoch time: 19.79 s +2024-11-21 17:41:45.030741: +2024-11-21 17:41:45.030926: Epoch 1309 +2024-11-21 17:41:45.031041: Current learning rate: 0.00851 +2024-11-21 17:42:02.747998: train_loss -0.7187 +2024-11-21 17:42:02.748214: val_loss -0.7247 +2024-11-21 17:42:02.748290: Pseudo dice [0.8187] +2024-11-21 17:42:02.748367: Epoch time: 17.72 s +2024-11-21 17:42:03.625334: +2024-11-21 17:42:03.625609: Epoch 1310 +2024-11-21 17:42:03.625723: Current learning rate: 0.00851 +2024-11-21 17:42:22.538715: train_loss -0.7446 +2024-11-21 17:42:22.538940: val_loss -0.7368 +2024-11-21 17:42:22.539021: Pseudo dice [0.8271] +2024-11-21 17:42:22.539123: Epoch time: 18.91 s +2024-11-21 17:42:23.743222: +2024-11-21 17:42:23.743436: Epoch 1311 +2024-11-21 17:42:23.743549: Current learning rate: 0.00851 +2024-11-21 17:42:42.499136: train_loss -0.7558 +2024-11-21 17:42:42.499346: val_loss -0.7717 +2024-11-21 17:42:42.499419: Pseudo dice [0.8326] +2024-11-21 17:42:42.499491: Epoch time: 18.76 s +2024-11-21 17:42:43.325581: +2024-11-21 17:42:43.325789: Epoch 1312 +2024-11-21 17:42:43.325897: Current learning rate: 0.00851 +2024-11-21 17:43:01.345986: train_loss -0.7542 +2024-11-21 17:43:01.346288: val_loss -0.7483 +2024-11-21 17:43:01.346370: Pseudo dice [0.8373] +2024-11-21 17:43:01.346447: Epoch time: 18.02 s +2024-11-21 17:43:02.338578: +2024-11-21 17:43:02.338814: Epoch 1313 +2024-11-21 17:43:02.338925: Current learning rate: 0.00851 +2024-11-21 17:43:20.968554: train_loss -0.7526 +2024-11-21 17:43:20.968805: val_loss -0.7684 +2024-11-21 17:43:20.968884: Pseudo dice [0.847] +2024-11-21 17:43:20.968972: Epoch time: 18.63 s +2024-11-21 17:43:21.925972: +2024-11-21 17:43:21.926218: Epoch 1314 +2024-11-21 17:43:21.926325: Current learning rate: 0.00851 +2024-11-21 17:43:40.591265: train_loss -0.7507 +2024-11-21 17:43:40.591475: val_loss -0.7698 +2024-11-21 17:43:40.591548: Pseudo dice [0.84] +2024-11-21 17:43:40.591643: Epoch time: 18.67 s +2024-11-21 17:43:41.420389: +2024-11-21 17:43:41.420628: Epoch 1315 +2024-11-21 17:43:41.420747: Current learning rate: 0.00851 +2024-11-21 17:43:59.938998: train_loss -0.7573 +2024-11-21 17:43:59.939223: val_loss -0.7359 +2024-11-21 17:43:59.939296: Pseudo dice [0.8487] +2024-11-21 17:43:59.939370: Epoch time: 18.52 s +2024-11-21 17:44:00.910242: +2024-11-21 17:44:00.910476: Epoch 1316 +2024-11-21 17:44:00.910595: Current learning rate: 0.00851 +2024-11-21 17:44:19.407609: train_loss -0.7688 +2024-11-21 17:44:19.407828: val_loss -0.7674 +2024-11-21 17:44:19.407901: Pseudo dice [0.8522] +2024-11-21 17:44:19.407973: Epoch time: 18.5 s +2024-11-21 17:44:20.238873: +2024-11-21 17:44:20.239099: Epoch 1317 +2024-11-21 17:44:20.239208: Current learning rate: 0.00851 +2024-11-21 17:44:39.418654: train_loss -0.7619 +2024-11-21 17:44:39.419026: val_loss -0.7801 +2024-11-21 17:44:39.419111: Pseudo dice [0.8527] +2024-11-21 17:44:39.419195: Epoch time: 19.18 s +2024-11-21 17:44:40.252452: +2024-11-21 17:44:40.252679: Epoch 1318 +2024-11-21 17:44:40.252792: Current learning rate: 0.0085 +2024-11-21 17:44:59.666383: train_loss -0.7577 +2024-11-21 17:44:59.666590: val_loss -0.744 +2024-11-21 17:44:59.666663: Pseudo dice [0.8222] +2024-11-21 17:44:59.666738: Epoch time: 19.41 s +2024-11-21 17:45:00.493341: +2024-11-21 17:45:00.493551: Epoch 1319 +2024-11-21 17:45:00.493662: Current learning rate: 0.0085 +2024-11-21 17:45:20.000480: train_loss -0.7603 +2024-11-21 17:45:20.000698: val_loss -0.7568 +2024-11-21 17:45:20.000772: Pseudo dice [0.8382] +2024-11-21 17:45:20.000850: Epoch time: 19.51 s +2024-11-21 17:45:20.826033: +2024-11-21 17:45:20.826247: Epoch 1320 +2024-11-21 17:45:20.826357: Current learning rate: 0.0085 +2024-11-21 17:45:39.716455: train_loss -0.7512 +2024-11-21 17:45:39.716679: val_loss -0.7519 +2024-11-21 17:45:39.716767: Pseudo dice [0.834] +2024-11-21 17:45:39.716946: Epoch time: 18.89 s +2024-11-21 17:45:40.591402: +2024-11-21 17:45:40.591632: Epoch 1321 +2024-11-21 17:45:40.591741: Current learning rate: 0.0085 +2024-11-21 17:45:59.510831: train_loss -0.7586 +2024-11-21 17:45:59.511051: val_loss -0.7411 +2024-11-21 17:45:59.511126: Pseudo dice [0.8275] +2024-11-21 17:45:59.511203: Epoch time: 18.92 s +2024-11-21 17:46:00.823451: +2024-11-21 17:46:00.823667: Epoch 1322 +2024-11-21 17:46:00.823777: Current learning rate: 0.0085 +2024-11-21 17:46:20.044391: train_loss -0.7639 +2024-11-21 17:46:20.044596: val_loss -0.7576 +2024-11-21 17:46:20.044669: Pseudo dice [0.8384] +2024-11-21 17:46:20.044742: Epoch time: 19.22 s +2024-11-21 17:46:21.052938: +2024-11-21 17:46:21.053179: Epoch 1323 +2024-11-21 17:46:21.053290: Current learning rate: 0.0085 +2024-11-21 17:46:39.566943: train_loss -0.7655 +2024-11-21 17:46:39.569344: val_loss -0.7693 +2024-11-21 17:46:39.569431: Pseudo dice [0.8245] +2024-11-21 17:46:39.569513: Epoch time: 18.51 s +2024-11-21 17:46:40.509157: +2024-11-21 17:46:40.509366: Epoch 1324 +2024-11-21 17:46:40.509474: Current learning rate: 0.0085 +2024-11-21 17:46:58.610194: train_loss -0.7704 +2024-11-21 17:46:58.610439: val_loss -0.7369 +2024-11-21 17:46:58.610513: Pseudo dice [0.8609] +2024-11-21 17:46:58.610592: Epoch time: 18.1 s +2024-11-21 17:46:59.439435: +2024-11-21 17:46:59.439664: Epoch 1325 +2024-11-21 17:46:59.439783: Current learning rate: 0.0085 +2024-11-21 17:47:17.307308: train_loss -0.7736 +2024-11-21 17:47:17.307528: val_loss -0.7558 +2024-11-21 17:47:17.307604: Pseudo dice [0.8319] +2024-11-21 17:47:17.307679: Epoch time: 17.87 s +2024-11-21 17:47:18.144857: +2024-11-21 17:47:18.145151: Epoch 1326 +2024-11-21 17:47:18.145258: Current learning rate: 0.0085 +2024-11-21 17:47:36.037954: train_loss -0.7562 +2024-11-21 17:47:36.038188: val_loss -0.7641 +2024-11-21 17:47:36.038264: Pseudo dice [0.8369] +2024-11-21 17:47:36.038342: Epoch time: 17.89 s +2024-11-21 17:47:36.975821: +2024-11-21 17:47:36.976115: Epoch 1327 +2024-11-21 17:47:36.976227: Current learning rate: 0.00849 +2024-11-21 17:47:56.466040: train_loss -0.7596 +2024-11-21 17:47:56.466272: val_loss -0.7229 +2024-11-21 17:47:56.466356: Pseudo dice [0.8277] +2024-11-21 17:47:56.466446: Epoch time: 19.49 s +2024-11-21 17:47:57.308151: +2024-11-21 17:47:57.308403: Epoch 1328 +2024-11-21 17:47:57.308547: Current learning rate: 0.00849 +2024-11-21 17:48:16.406436: train_loss -0.7578 +2024-11-21 17:48:16.406712: val_loss -0.7567 +2024-11-21 17:48:16.406794: Pseudo dice [0.8392] +2024-11-21 17:48:16.406912: Epoch time: 19.1 s +2024-11-21 17:48:17.243435: +2024-11-21 17:48:17.243657: Epoch 1329 +2024-11-21 17:48:17.243763: Current learning rate: 0.00849 +2024-11-21 17:48:35.655286: train_loss -0.7581 +2024-11-21 17:48:35.655494: val_loss -0.7625 +2024-11-21 17:48:35.655567: Pseudo dice [0.8332] +2024-11-21 17:48:35.655642: Epoch time: 18.41 s +2024-11-21 17:48:36.486916: +2024-11-21 17:48:36.487201: Epoch 1330 +2024-11-21 17:48:36.487312: Current learning rate: 0.00849 +2024-11-21 17:48:54.292722: train_loss -0.7693 +2024-11-21 17:48:54.292948: val_loss -0.7771 +2024-11-21 17:48:54.293033: Pseudo dice [0.8488] +2024-11-21 17:48:54.293111: Epoch time: 17.81 s +2024-11-21 17:48:55.126024: +2024-11-21 17:48:55.126581: Epoch 1331 +2024-11-21 17:48:55.126732: Current learning rate: 0.00849 +2024-11-21 17:49:13.126607: train_loss -0.762 +2024-11-21 17:49:13.126839: val_loss -0.7322 +2024-11-21 17:49:13.126916: Pseudo dice [0.8507] +2024-11-21 17:49:13.127035: Epoch time: 18.0 s +2024-11-21 17:49:14.054420: +2024-11-21 17:49:14.054625: Epoch 1332 +2024-11-21 17:49:14.054735: Current learning rate: 0.00849 +2024-11-21 17:49:32.954113: train_loss -0.7688 +2024-11-21 17:49:32.956491: val_loss -0.7821 +2024-11-21 17:49:32.956610: Pseudo dice [0.8456] +2024-11-21 17:49:32.956686: Epoch time: 18.9 s +2024-11-21 17:49:33.910004: +2024-11-21 17:49:33.910203: Epoch 1333 +2024-11-21 17:49:33.910307: Current learning rate: 0.00849 +2024-11-21 17:49:52.606376: train_loss -0.7576 +2024-11-21 17:49:52.606580: val_loss -0.7651 +2024-11-21 17:49:52.606653: Pseudo dice [0.8636] +2024-11-21 17:49:52.606728: Epoch time: 18.7 s +2024-11-21 17:49:53.835266: +2024-11-21 17:49:53.836050: Epoch 1334 +2024-11-21 17:49:53.836207: Current learning rate: 0.00849 +2024-11-21 17:50:12.597172: train_loss -0.7476 +2024-11-21 17:50:12.597433: val_loss -0.7401 +2024-11-21 17:50:12.597510: Pseudo dice [0.8295] +2024-11-21 17:50:12.597595: Epoch time: 18.76 s +2024-11-21 17:50:13.446411: +2024-11-21 17:50:13.446668: Epoch 1335 +2024-11-21 17:50:13.446779: Current learning rate: 0.00848 +2024-11-21 17:50:31.827543: train_loss -0.7507 +2024-11-21 17:50:31.827767: val_loss -0.7525 +2024-11-21 17:50:31.827842: Pseudo dice [0.8273] +2024-11-21 17:50:31.827917: Epoch time: 18.38 s +2024-11-21 17:50:32.657533: +2024-11-21 17:50:32.657760: Epoch 1336 +2024-11-21 17:50:32.657880: Current learning rate: 0.00848 +2024-11-21 17:50:51.801134: train_loss -0.7638 +2024-11-21 17:50:51.801393: val_loss -0.7706 +2024-11-21 17:50:51.801509: Pseudo dice [0.8401] +2024-11-21 17:50:51.801599: Epoch time: 19.14 s +2024-11-21 17:50:52.643024: +2024-11-21 17:50:52.643248: Epoch 1337 +2024-11-21 17:50:52.643356: Current learning rate: 0.00848 +2024-11-21 17:51:11.733300: train_loss -0.7627 +2024-11-21 17:51:11.733514: val_loss -0.7693 +2024-11-21 17:51:11.733637: Pseudo dice [0.8348] +2024-11-21 17:51:11.733748: Epoch time: 19.09 s +2024-11-21 17:51:12.577563: +2024-11-21 17:51:12.577792: Epoch 1338 +2024-11-21 17:51:12.577902: Current learning rate: 0.00848 +2024-11-21 17:51:31.668680: train_loss -0.7618 +2024-11-21 17:51:31.668904: val_loss -0.779 +2024-11-21 17:51:31.668978: Pseudo dice [0.8329] +2024-11-21 17:51:31.669061: Epoch time: 19.09 s +2024-11-21 17:51:32.501671: +2024-11-21 17:51:32.501892: Epoch 1339 +2024-11-21 17:51:32.502028: Current learning rate: 0.00848 +2024-11-21 17:51:51.129422: train_loss -0.7643 +2024-11-21 17:51:51.129642: val_loss -0.7595 +2024-11-21 17:51:51.129716: Pseudo dice [0.8326] +2024-11-21 17:51:51.129791: Epoch time: 18.63 s +2024-11-21 17:51:51.962241: +2024-11-21 17:51:51.962457: Epoch 1340 +2024-11-21 17:51:51.962565: Current learning rate: 0.00848 +2024-11-21 17:52:09.708610: train_loss -0.7693 +2024-11-21 17:52:09.708825: val_loss -0.7768 +2024-11-21 17:52:09.708897: Pseudo dice [0.8264] +2024-11-21 17:52:09.708971: Epoch time: 17.75 s +2024-11-21 17:52:10.577268: +2024-11-21 17:52:10.577473: Epoch 1341 +2024-11-21 17:52:10.577588: Current learning rate: 0.00848 +2024-11-21 17:52:28.936887: train_loss -0.768 +2024-11-21 17:52:28.937108: val_loss -0.7792 +2024-11-21 17:52:28.937189: Pseudo dice [0.8529] +2024-11-21 17:52:28.937270: Epoch time: 18.36 s +2024-11-21 17:52:29.859810: +2024-11-21 17:52:29.860023: Epoch 1342 +2024-11-21 17:52:29.860132: Current learning rate: 0.00848 +2024-11-21 17:52:48.674389: train_loss -0.7737 +2024-11-21 17:52:48.674636: val_loss -0.7617 +2024-11-21 17:52:48.674709: Pseudo dice [0.8458] +2024-11-21 17:52:48.674789: Epoch time: 18.82 s +2024-11-21 17:52:49.510699: +2024-11-21 17:52:49.510915: Epoch 1343 +2024-11-21 17:52:49.511032: Current learning rate: 0.00848 +2024-11-21 17:53:08.697885: train_loss -0.7718 +2024-11-21 17:53:08.698125: val_loss -0.7709 +2024-11-21 17:53:08.698214: Pseudo dice [0.841] +2024-11-21 17:53:08.698330: Epoch time: 19.19 s +2024-11-21 17:53:09.535730: +2024-11-21 17:53:09.536155: Epoch 1344 +2024-11-21 17:53:09.536282: Current learning rate: 0.00847 +2024-11-21 17:53:27.472819: train_loss -0.7637 +2024-11-21 17:53:27.473053: val_loss -0.7509 +2024-11-21 17:53:27.473127: Pseudo dice [0.8339] +2024-11-21 17:53:27.473200: Epoch time: 17.94 s +2024-11-21 17:53:28.639015: +2024-11-21 17:53:28.639265: Epoch 1345 +2024-11-21 17:53:28.639392: Current learning rate: 0.00847 +2024-11-21 17:53:47.894197: train_loss -0.7728 +2024-11-21 17:53:47.894433: val_loss -0.7706 +2024-11-21 17:53:47.894510: Pseudo dice [0.8375] +2024-11-21 17:53:47.894599: Epoch time: 19.26 s +2024-11-21 17:53:48.738080: +2024-11-21 17:53:48.738351: Epoch 1346 +2024-11-21 17:53:48.738462: Current learning rate: 0.00847 +2024-11-21 17:54:06.830983: train_loss -0.7704 +2024-11-21 17:54:06.831203: val_loss -0.7691 +2024-11-21 17:54:06.831276: Pseudo dice [0.846] +2024-11-21 17:54:06.831350: Epoch time: 18.09 s +2024-11-21 17:54:07.667281: +2024-11-21 17:54:07.667517: Epoch 1347 +2024-11-21 17:54:07.667624: Current learning rate: 0.00847 +2024-11-21 17:54:25.255601: train_loss -0.7664 +2024-11-21 17:54:25.255812: val_loss -0.7653 +2024-11-21 17:54:25.255890: Pseudo dice [0.8449] +2024-11-21 17:54:25.255974: Epoch time: 17.59 s +2024-11-21 17:54:26.093138: +2024-11-21 17:54:26.093357: Epoch 1348 +2024-11-21 17:54:26.093489: Current learning rate: 0.00847 +2024-11-21 17:54:43.687373: train_loss -0.7606 +2024-11-21 17:54:43.687600: val_loss -0.7606 +2024-11-21 17:54:43.687675: Pseudo dice [0.8421] +2024-11-21 17:54:43.687756: Epoch time: 17.6 s +2024-11-21 17:54:44.535641: +2024-11-21 17:54:44.535866: Epoch 1349 +2024-11-21 17:54:44.535980: Current learning rate: 0.00847 +2024-11-21 17:55:03.540355: train_loss -0.7614 +2024-11-21 17:55:03.541262: val_loss -0.7786 +2024-11-21 17:55:03.541351: Pseudo dice [0.8415] +2024-11-21 17:55:03.541428: Epoch time: 19.01 s +2024-11-21 17:55:04.575706: +2024-11-21 17:55:04.575920: Epoch 1350 +2024-11-21 17:55:04.576032: Current learning rate: 0.00847 +2024-11-21 17:55:23.918291: train_loss -0.759 +2024-11-21 17:55:23.918511: val_loss -0.7556 +2024-11-21 17:55:23.918583: Pseudo dice [0.842] +2024-11-21 17:55:23.918662: Epoch time: 19.34 s +2024-11-21 17:55:24.889918: +2024-11-21 17:55:24.890134: Epoch 1351 +2024-11-21 17:55:24.890246: Current learning rate: 0.00847 +2024-11-21 17:55:43.798977: train_loss -0.7617 +2024-11-21 17:55:43.799192: val_loss -0.7675 +2024-11-21 17:55:43.799267: Pseudo dice [0.8391] +2024-11-21 17:55:43.799341: Epoch time: 18.91 s +2024-11-21 17:55:44.635145: +2024-11-21 17:55:44.635383: Epoch 1352 +2024-11-21 17:55:44.635489: Current learning rate: 0.00847 +2024-11-21 17:56:03.850064: train_loss -0.7782 +2024-11-21 17:56:03.850304: val_loss -0.7685 +2024-11-21 17:56:03.850463: Pseudo dice [0.8311] +2024-11-21 17:56:03.850552: Epoch time: 19.22 s +2024-11-21 17:56:04.798521: +2024-11-21 17:56:04.798742: Epoch 1353 +2024-11-21 17:56:04.798850: Current learning rate: 0.00846 +2024-11-21 17:56:23.214511: train_loss -0.7601 +2024-11-21 17:56:23.214774: val_loss -0.7582 +2024-11-21 17:56:23.214858: Pseudo dice [0.8473] +2024-11-21 17:56:23.214936: Epoch time: 18.42 s +2024-11-21 17:56:24.053815: +2024-11-21 17:56:24.054055: Epoch 1354 +2024-11-21 17:56:24.054178: Current learning rate: 0.00846 +2024-11-21 17:56:42.994354: train_loss -0.7642 +2024-11-21 17:56:42.998960: val_loss -0.7542 +2024-11-21 17:56:42.999072: Pseudo dice [0.8459] +2024-11-21 17:56:42.999146: Epoch time: 18.94 s +2024-11-21 17:56:43.878487: +2024-11-21 17:56:43.878683: Epoch 1355 +2024-11-21 17:56:43.878789: Current learning rate: 0.00846 +2024-11-21 17:57:02.476270: train_loss -0.7696 +2024-11-21 17:57:02.476501: val_loss -0.7572 +2024-11-21 17:57:02.476576: Pseudo dice [0.8467] +2024-11-21 17:57:02.478831: Epoch time: 18.6 s +2024-11-21 17:57:03.810628: +2024-11-21 17:57:03.811062: Epoch 1356 +2024-11-21 17:57:03.811193: Current learning rate: 0.00846 +2024-11-21 17:57:22.514102: train_loss -0.7567 +2024-11-21 17:57:22.514336: val_loss -0.7374 +2024-11-21 17:57:22.514411: Pseudo dice [0.8396] +2024-11-21 17:57:22.514490: Epoch time: 18.7 s +2024-11-21 17:57:23.404901: +2024-11-21 17:57:23.405334: Epoch 1357 +2024-11-21 17:57:23.405459: Current learning rate: 0.00846 +2024-11-21 17:57:41.882807: train_loss -0.7651 +2024-11-21 17:57:41.883058: val_loss -0.7691 +2024-11-21 17:57:41.883137: Pseudo dice [0.8439] +2024-11-21 17:57:41.883214: Epoch time: 18.48 s +2024-11-21 17:57:42.715801: +2024-11-21 17:57:42.716241: Epoch 1358 +2024-11-21 17:57:42.716377: Current learning rate: 0.00846 +2024-11-21 17:58:01.989436: train_loss -0.7599 +2024-11-21 17:58:01.989641: val_loss -0.735 +2024-11-21 17:58:01.989726: Pseudo dice [0.8204] +2024-11-21 17:58:01.989805: Epoch time: 19.27 s +2024-11-21 17:58:02.833395: +2024-11-21 17:58:02.833864: Epoch 1359 +2024-11-21 17:58:02.834008: Current learning rate: 0.00846 +2024-11-21 17:58:21.022589: train_loss -0.7704 +2024-11-21 17:58:21.022801: val_loss -0.7614 +2024-11-21 17:58:21.022878: Pseudo dice [0.8512] +2024-11-21 17:58:21.022955: Epoch time: 18.19 s +2024-11-21 17:58:21.876197: +2024-11-21 17:58:21.876610: Epoch 1360 +2024-11-21 17:58:21.876737: Current learning rate: 0.00846 +2024-11-21 17:58:40.869050: train_loss -0.7742 +2024-11-21 17:58:40.869278: val_loss -0.7573 +2024-11-21 17:58:40.869352: Pseudo dice [0.8291] +2024-11-21 17:58:40.869427: Epoch time: 18.99 s +2024-11-21 17:58:41.712840: +2024-11-21 17:58:41.713309: Epoch 1361 +2024-11-21 17:58:41.713447: Current learning rate: 0.00845 +2024-11-21 17:59:00.820491: train_loss -0.7669 +2024-11-21 17:59:00.820700: val_loss -0.7687 +2024-11-21 17:59:00.820774: Pseudo dice [0.8491] +2024-11-21 17:59:00.820847: Epoch time: 19.11 s +2024-11-21 17:59:01.651462: +2024-11-21 17:59:01.651893: Epoch 1362 +2024-11-21 17:59:01.652048: Current learning rate: 0.00845 +2024-11-21 17:59:19.740448: train_loss -0.78 +2024-11-21 17:59:19.740655: val_loss -0.7705 +2024-11-21 17:59:19.740796: Pseudo dice [0.8483] +2024-11-21 17:59:19.740875: Epoch time: 18.09 s +2024-11-21 17:59:20.577709: +2024-11-21 17:59:20.578119: Epoch 1363 +2024-11-21 17:59:20.578257: Current learning rate: 0.00845 +2024-11-21 17:59:40.077457: train_loss -0.7666 +2024-11-21 17:59:40.090094: val_loss -0.7487 +2024-11-21 17:59:40.090302: Pseudo dice [0.8415] +2024-11-21 17:59:40.090404: Epoch time: 19.5 s +2024-11-21 17:59:40.941244: +2024-11-21 17:59:40.941470: Epoch 1364 +2024-11-21 17:59:40.941580: Current learning rate: 0.00845 +2024-11-21 17:59:58.453397: train_loss -0.7686 +2024-11-21 17:59:58.453602: val_loss -0.7609 +2024-11-21 17:59:58.453675: Pseudo dice [0.8362] +2024-11-21 17:59:58.453748: Epoch time: 17.51 s +2024-11-21 17:59:59.288455: +2024-11-21 17:59:59.288660: Epoch 1365 +2024-11-21 17:59:59.288769: Current learning rate: 0.00845 +2024-11-21 18:00:17.042426: train_loss -0.7764 +2024-11-21 18:00:17.042642: val_loss -0.7604 +2024-11-21 18:00:17.042717: Pseudo dice [0.8052] +2024-11-21 18:00:17.042792: Epoch time: 17.75 s +2024-11-21 18:00:17.926178: +2024-11-21 18:00:17.926389: Epoch 1366 +2024-11-21 18:00:17.926504: Current learning rate: 0.00845 +2024-11-21 18:00:37.246993: train_loss -0.7741 +2024-11-21 18:00:37.247212: val_loss -0.7522 +2024-11-21 18:00:37.247351: Pseudo dice [0.8323] +2024-11-21 18:00:37.247498: Epoch time: 19.32 s +2024-11-21 18:00:38.088394: +2024-11-21 18:00:38.088619: Epoch 1367 +2024-11-21 18:00:38.088738: Current learning rate: 0.00845 +2024-11-21 18:00:56.636421: train_loss -0.7632 +2024-11-21 18:00:56.638235: val_loss -0.7588 +2024-11-21 18:00:56.638346: Pseudo dice [0.8521] +2024-11-21 18:00:56.638427: Epoch time: 18.55 s +2024-11-21 18:00:57.486195: +2024-11-21 18:00:57.486627: Epoch 1368 +2024-11-21 18:00:57.486783: Current learning rate: 0.00845 +2024-11-21 18:01:16.465616: train_loss -0.7724 +2024-11-21 18:01:16.465836: val_loss -0.7557 +2024-11-21 18:01:16.465913: Pseudo dice [0.8363] +2024-11-21 18:01:16.466012: Epoch time: 18.98 s +2024-11-21 18:01:17.299212: +2024-11-21 18:01:17.299631: Epoch 1369 +2024-11-21 18:01:17.299758: Current learning rate: 0.00845 +2024-11-21 18:01:36.142712: train_loss -0.7563 +2024-11-21 18:01:36.142925: val_loss -0.7522 +2024-11-21 18:01:36.143026: Pseudo dice [0.8409] +2024-11-21 18:01:36.145282: Epoch time: 18.84 s +2024-11-21 18:01:36.994254: +2024-11-21 18:01:36.994678: Epoch 1370 +2024-11-21 18:01:36.994814: Current learning rate: 0.00844 +2024-11-21 18:01:55.672699: train_loss -0.7793 +2024-11-21 18:01:55.673013: val_loss -0.7232 +2024-11-21 18:01:55.673093: Pseudo dice [0.8506] +2024-11-21 18:01:55.673176: Epoch time: 18.68 s +2024-11-21 18:01:56.516996: +2024-11-21 18:01:56.517451: Epoch 1371 +2024-11-21 18:01:56.517580: Current learning rate: 0.00844 +2024-11-21 18:02:14.469531: train_loss -0.77 +2024-11-21 18:02:14.469748: val_loss -0.7772 +2024-11-21 18:02:14.472021: Pseudo dice [0.845] +2024-11-21 18:02:14.472111: Epoch time: 17.95 s +2024-11-21 18:02:15.531206: +2024-11-21 18:02:15.531611: Epoch 1372 +2024-11-21 18:02:15.531742: Current learning rate: 0.00844 +2024-11-21 18:02:35.012933: train_loss -0.7545 +2024-11-21 18:02:35.015348: val_loss -0.7718 +2024-11-21 18:02:35.015477: Pseudo dice [0.8519] +2024-11-21 18:02:35.015556: Epoch time: 19.48 s +2024-11-21 18:02:35.851052: +2024-11-21 18:02:35.851572: Epoch 1373 +2024-11-21 18:02:35.851704: Current learning rate: 0.00844 +2024-11-21 18:02:53.833537: train_loss -0.7741 +2024-11-21 18:02:53.833763: val_loss -0.7711 +2024-11-21 18:02:53.833835: Pseudo dice [0.8492] +2024-11-21 18:02:53.833913: Epoch time: 17.98 s +2024-11-21 18:02:54.693169: +2024-11-21 18:02:54.693658: Epoch 1374 +2024-11-21 18:02:54.693790: Current learning rate: 0.00844 +2024-11-21 18:03:12.768761: train_loss -0.763 +2024-11-21 18:03:12.768965: val_loss -0.7499 +2024-11-21 18:03:12.769046: Pseudo dice [0.8391] +2024-11-21 18:03:12.769117: Epoch time: 18.08 s +2024-11-21 18:03:13.611416: +2024-11-21 18:03:13.611832: Epoch 1375 +2024-11-21 18:03:13.611977: Current learning rate: 0.00844 +2024-11-21 18:03:31.875370: train_loss -0.7599 +2024-11-21 18:03:31.875581: val_loss -0.7582 +2024-11-21 18:03:31.875733: Pseudo dice [0.8382] +2024-11-21 18:03:31.875835: Epoch time: 18.26 s +2024-11-21 18:03:32.707490: +2024-11-21 18:03:32.707904: Epoch 1376 +2024-11-21 18:03:32.708140: Current learning rate: 0.00844 +2024-11-21 18:03:50.999491: train_loss -0.762 +2024-11-21 18:03:50.999735: val_loss -0.7553 +2024-11-21 18:03:50.999821: Pseudo dice [0.8519] +2024-11-21 18:03:50.999897: Epoch time: 18.29 s +2024-11-21 18:03:51.848562: +2024-11-21 18:03:51.848969: Epoch 1377 +2024-11-21 18:03:51.849098: Current learning rate: 0.00844 +2024-11-21 18:04:10.620457: train_loss -0.7698 +2024-11-21 18:04:10.620683: val_loss -0.7521 +2024-11-21 18:04:10.620757: Pseudo dice [0.8322] +2024-11-21 18:04:10.620839: Epoch time: 18.77 s +2024-11-21 18:04:11.849772: +2024-11-21 18:04:11.850194: Epoch 1378 +2024-11-21 18:04:11.850322: Current learning rate: 0.00844 +2024-11-21 18:04:29.246632: train_loss -0.7636 +2024-11-21 18:04:29.246878: val_loss -0.7606 +2024-11-21 18:04:29.246957: Pseudo dice [0.8296] +2024-11-21 18:04:29.247043: Epoch time: 17.4 s +2024-11-21 18:04:30.082395: +2024-11-21 18:04:30.082860: Epoch 1379 +2024-11-21 18:04:30.082999: Current learning rate: 0.00843 +2024-11-21 18:04:47.806730: train_loss -0.7618 +2024-11-21 18:04:47.806940: val_loss -0.777 +2024-11-21 18:04:47.807023: Pseudo dice [0.841] +2024-11-21 18:04:47.807097: Epoch time: 17.73 s +2024-11-21 18:04:48.646134: +2024-11-21 18:04:48.646569: Epoch 1380 +2024-11-21 18:04:48.646698: Current learning rate: 0.00843 +2024-11-21 18:05:06.465901: train_loss -0.7785 +2024-11-21 18:05:06.466133: val_loss -0.7746 +2024-11-21 18:05:06.466210: Pseudo dice [0.857] +2024-11-21 18:05:06.466289: Epoch time: 17.82 s +2024-11-21 18:05:07.308001: +2024-11-21 18:05:07.308405: Epoch 1381 +2024-11-21 18:05:07.308534: Current learning rate: 0.00843 +2024-11-21 18:05:26.776815: train_loss -0.7692 +2024-11-21 18:05:26.777048: val_loss -0.7397 +2024-11-21 18:05:26.777123: Pseudo dice [0.8402] +2024-11-21 18:05:26.777201: Epoch time: 19.47 s +2024-11-21 18:05:27.597790: +2024-11-21 18:05:27.598195: Epoch 1382 +2024-11-21 18:05:27.598305: Current learning rate: 0.00843 +2024-11-21 18:05:45.057475: train_loss -0.7603 +2024-11-21 18:05:45.057680: val_loss -0.7365 +2024-11-21 18:05:45.057752: Pseudo dice [0.8398] +2024-11-21 18:05:45.057825: Epoch time: 17.46 s +2024-11-21 18:05:45.905224: +2024-11-21 18:05:45.905687: Epoch 1383 +2024-11-21 18:05:45.905823: Current learning rate: 0.00843 +2024-11-21 18:06:04.069577: train_loss -0.7553 +2024-11-21 18:06:04.069791: val_loss -0.7485 +2024-11-21 18:06:04.069869: Pseudo dice [0.8136] +2024-11-21 18:06:04.069947: Epoch time: 18.17 s +2024-11-21 18:06:04.905695: +2024-11-21 18:06:04.906159: Epoch 1384 +2024-11-21 18:06:04.906293: Current learning rate: 0.00843 +2024-11-21 18:06:23.410041: train_loss -0.7486 +2024-11-21 18:06:23.410275: val_loss -0.765 +2024-11-21 18:06:23.410351: Pseudo dice [0.8413] +2024-11-21 18:06:23.410462: Epoch time: 18.51 s +2024-11-21 18:06:24.252887: +2024-11-21 18:06:24.253310: Epoch 1385 +2024-11-21 18:06:24.253442: Current learning rate: 0.00843 +2024-11-21 18:06:42.872659: train_loss -0.7507 +2024-11-21 18:06:42.872866: val_loss -0.7531 +2024-11-21 18:06:42.872943: Pseudo dice [0.8249] +2024-11-21 18:06:42.873044: Epoch time: 18.62 s +2024-11-21 18:06:43.714281: +2024-11-21 18:06:43.714696: Epoch 1386 +2024-11-21 18:06:43.714837: Current learning rate: 0.00843 +2024-11-21 18:07:01.524202: train_loss -0.7582 +2024-11-21 18:07:01.524437: val_loss -0.7673 +2024-11-21 18:07:01.524558: Pseudo dice [0.8471] +2024-11-21 18:07:01.524644: Epoch time: 17.81 s +2024-11-21 18:07:02.364912: +2024-11-21 18:07:02.365123: Epoch 1387 +2024-11-21 18:07:02.365233: Current learning rate: 0.00843 +2024-11-21 18:07:20.337425: train_loss -0.7678 +2024-11-21 18:07:20.337656: val_loss -0.7573 +2024-11-21 18:07:20.337738: Pseudo dice [0.8427] +2024-11-21 18:07:20.337813: Epoch time: 17.97 s +2024-11-21 18:07:21.182324: +2024-11-21 18:07:21.182537: Epoch 1388 +2024-11-21 18:07:21.182649: Current learning rate: 0.00842 +2024-11-21 18:07:39.371889: train_loss -0.7676 +2024-11-21 18:07:39.372181: val_loss -0.7359 +2024-11-21 18:07:39.372259: Pseudo dice [0.8366] +2024-11-21 18:07:39.372343: Epoch time: 18.19 s +2024-11-21 18:07:40.610538: +2024-11-21 18:07:40.610978: Epoch 1389 +2024-11-21 18:07:40.611119: Current learning rate: 0.00842 +2024-11-21 18:07:59.615284: train_loss -0.7595 +2024-11-21 18:07:59.615516: val_loss -0.7543 +2024-11-21 18:07:59.615594: Pseudo dice [0.8282] +2024-11-21 18:07:59.615674: Epoch time: 19.01 s +2024-11-21 18:08:00.472885: +2024-11-21 18:08:00.473299: Epoch 1390 +2024-11-21 18:08:00.473442: Current learning rate: 0.00842 +2024-11-21 18:08:18.378237: train_loss -0.769 +2024-11-21 18:08:18.378490: val_loss -0.7765 +2024-11-21 18:08:18.378571: Pseudo dice [0.8381] +2024-11-21 18:08:18.378648: Epoch time: 17.91 s +2024-11-21 18:08:19.402557: +2024-11-21 18:08:19.403012: Epoch 1391 +2024-11-21 18:08:19.403150: Current learning rate: 0.00842 +2024-11-21 18:08:38.302853: train_loss -0.7611 +2024-11-21 18:08:38.303109: val_loss -0.7647 +2024-11-21 18:08:38.303185: Pseudo dice [0.8488] +2024-11-21 18:08:38.303265: Epoch time: 18.9 s +2024-11-21 18:08:39.203329: +2024-11-21 18:08:39.203753: Epoch 1392 +2024-11-21 18:08:39.203889: Current learning rate: 0.00842 +2024-11-21 18:08:57.402813: train_loss -0.7643 +2024-11-21 18:08:57.403024: val_loss -0.7573 +2024-11-21 18:08:57.403101: Pseudo dice [0.8517] +2024-11-21 18:08:57.403191: Epoch time: 18.2 s +2024-11-21 18:08:58.244853: +2024-11-21 18:08:58.245363: Epoch 1393 +2024-11-21 18:08:58.245507: Current learning rate: 0.00842 +2024-11-21 18:09:17.646972: train_loss -0.7735 +2024-11-21 18:09:17.647213: val_loss -0.7585 +2024-11-21 18:09:17.647291: Pseudo dice [0.8307] +2024-11-21 18:09:17.647371: Epoch time: 19.4 s +2024-11-21 18:09:18.490956: +2024-11-21 18:09:18.491374: Epoch 1394 +2024-11-21 18:09:18.491506: Current learning rate: 0.00842 +2024-11-21 18:09:38.200605: train_loss -0.7748 +2024-11-21 18:09:38.200822: val_loss -0.7633 +2024-11-21 18:09:38.200904: Pseudo dice [0.8447] +2024-11-21 18:09:38.201003: Epoch time: 19.71 s +2024-11-21 18:09:39.039005: +2024-11-21 18:09:39.039480: Epoch 1395 +2024-11-21 18:09:39.039620: Current learning rate: 0.00842 +2024-11-21 18:09:57.088770: train_loss -0.7772 +2024-11-21 18:09:57.089009: val_loss -0.7718 +2024-11-21 18:09:57.089083: Pseudo dice [0.8524] +2024-11-21 18:09:57.089160: Epoch time: 18.05 s +2024-11-21 18:09:57.922193: +2024-11-21 18:09:57.922410: Epoch 1396 +2024-11-21 18:09:57.922518: Current learning rate: 0.00841 +2024-11-21 18:10:16.267748: train_loss -0.7759 +2024-11-21 18:10:16.267961: val_loss -0.7687 +2024-11-21 18:10:16.268046: Pseudo dice [0.8465] +2024-11-21 18:10:16.268125: Epoch time: 18.35 s +2024-11-21 18:10:17.106776: +2024-11-21 18:10:17.106997: Epoch 1397 +2024-11-21 18:10:17.107112: Current learning rate: 0.00841 +2024-11-21 18:10:34.997948: train_loss -0.767 +2024-11-21 18:10:34.998223: val_loss -0.7676 +2024-11-21 18:10:34.998323: Pseudo dice [0.8224] +2024-11-21 18:10:34.998404: Epoch time: 17.89 s +2024-11-21 18:10:35.834857: +2024-11-21 18:10:35.835072: Epoch 1398 +2024-11-21 18:10:35.837388: Current learning rate: 0.00841 +2024-11-21 18:10:54.136952: train_loss -0.7649 +2024-11-21 18:10:54.137268: val_loss -0.7527 +2024-11-21 18:10:54.137346: Pseudo dice [0.8233] +2024-11-21 18:10:54.137432: Epoch time: 18.3 s +2024-11-21 18:10:55.029989: +2024-11-21 18:10:55.030206: Epoch 1399 +2024-11-21 18:10:55.030314: Current learning rate: 0.00841 +2024-11-21 18:11:15.231007: train_loss -0.7746 +2024-11-21 18:11:15.231272: val_loss -0.7623 +2024-11-21 18:11:15.231349: Pseudo dice [0.8556] +2024-11-21 18:11:15.231426: Epoch time: 20.2 s +2024-11-21 18:11:16.265845: +2024-11-21 18:11:16.266053: Epoch 1400 +2024-11-21 18:11:16.266160: Current learning rate: 0.00841 +2024-11-21 18:11:35.599467: train_loss -0.771 +2024-11-21 18:11:35.600030: val_loss -0.7566 +2024-11-21 18:11:35.600137: Pseudo dice [0.8584] +2024-11-21 18:11:35.600213: Epoch time: 19.33 s +2024-11-21 18:11:36.518107: +2024-11-21 18:11:36.518391: Epoch 1401 +2024-11-21 18:11:36.518508: Current learning rate: 0.00841 +2024-11-21 18:11:54.796569: train_loss -0.7644 +2024-11-21 18:11:54.796834: val_loss -0.7296 +2024-11-21 18:11:54.796911: Pseudo dice [0.8268] +2024-11-21 18:11:54.797004: Epoch time: 18.27 s +2024-11-21 18:11:55.761709: +2024-11-21 18:11:55.761940: Epoch 1402 +2024-11-21 18:11:55.762065: Current learning rate: 0.00841 +2024-11-21 18:12:14.896374: train_loss -0.7554 +2024-11-21 18:12:14.896583: val_loss -0.7488 +2024-11-21 18:12:14.896656: Pseudo dice [0.8363] +2024-11-21 18:12:14.896731: Epoch time: 19.14 s +2024-11-21 18:12:15.808079: +2024-11-21 18:12:15.808295: Epoch 1403 +2024-11-21 18:12:15.808404: Current learning rate: 0.00841 +2024-11-21 18:12:33.940024: train_loss -0.7642 +2024-11-21 18:12:33.940234: val_loss -0.7692 +2024-11-21 18:12:33.940306: Pseudo dice [0.8445] +2024-11-21 18:12:33.940379: Epoch time: 18.13 s +2024-11-21 18:12:34.782020: +2024-11-21 18:12:34.782227: Epoch 1404 +2024-11-21 18:12:34.782333: Current learning rate: 0.00841 +2024-11-21 18:12:53.917016: train_loss -0.7614 +2024-11-21 18:12:53.917234: val_loss -0.7489 +2024-11-21 18:12:53.917307: Pseudo dice [0.8269] +2024-11-21 18:12:53.917385: Epoch time: 19.14 s +2024-11-21 18:12:54.755822: +2024-11-21 18:12:54.756053: Epoch 1405 +2024-11-21 18:12:54.756165: Current learning rate: 0.0084 +2024-11-21 18:13:13.680440: train_loss -0.7658 +2024-11-21 18:13:13.680665: val_loss -0.7359 +2024-11-21 18:13:13.680740: Pseudo dice [0.8377] +2024-11-21 18:13:13.680815: Epoch time: 18.93 s +2024-11-21 18:13:14.523398: +2024-11-21 18:13:14.523606: Epoch 1406 +2024-11-21 18:13:14.523712: Current learning rate: 0.0084 +2024-11-21 18:13:33.194984: train_loss -0.7526 +2024-11-21 18:13:33.195204: val_loss -0.7527 +2024-11-21 18:13:33.195276: Pseudo dice [0.8438] +2024-11-21 18:13:33.195350: Epoch time: 18.67 s +2024-11-21 18:13:34.032053: +2024-11-21 18:13:34.032251: Epoch 1407 +2024-11-21 18:13:34.032359: Current learning rate: 0.0084 +2024-11-21 18:13:51.898339: train_loss -0.7401 +2024-11-21 18:13:51.898539: val_loss -0.7205 +2024-11-21 18:13:51.898610: Pseudo dice [0.8181] +2024-11-21 18:13:51.898682: Epoch time: 17.87 s +2024-11-21 18:13:52.732626: +2024-11-21 18:13:52.732839: Epoch 1408 +2024-11-21 18:13:52.732950: Current learning rate: 0.0084 +2024-11-21 18:14:12.052806: train_loss -0.7455 +2024-11-21 18:14:12.053059: val_loss -0.7407 +2024-11-21 18:14:12.053139: Pseudo dice [0.8315] +2024-11-21 18:14:12.053225: Epoch time: 19.32 s +2024-11-21 18:14:12.893394: +2024-11-21 18:14:12.893652: Epoch 1409 +2024-11-21 18:14:12.893759: Current learning rate: 0.0084 +2024-11-21 18:14:31.257837: train_loss -0.7614 +2024-11-21 18:14:31.258051: val_loss -0.7557 +2024-11-21 18:14:31.258129: Pseudo dice [0.8474] +2024-11-21 18:14:31.258219: Epoch time: 18.37 s +2024-11-21 18:14:32.095120: +2024-11-21 18:14:32.095413: Epoch 1410 +2024-11-21 18:14:32.095523: Current learning rate: 0.0084 +2024-11-21 18:14:51.147873: train_loss -0.7495 +2024-11-21 18:14:51.148087: val_loss -0.7687 +2024-11-21 18:14:51.148159: Pseudo dice [0.8382] +2024-11-21 18:14:51.148234: Epoch time: 19.05 s +2024-11-21 18:14:52.344005: +2024-11-21 18:14:52.344209: Epoch 1411 +2024-11-21 18:14:52.344322: Current learning rate: 0.0084 +2024-11-21 18:15:11.097017: train_loss -0.7639 +2024-11-21 18:15:11.097241: val_loss -0.7603 +2024-11-21 18:15:11.097316: Pseudo dice [0.8358] +2024-11-21 18:15:11.100249: Epoch time: 18.75 s +2024-11-21 18:15:11.961266: +2024-11-21 18:15:11.961488: Epoch 1412 +2024-11-21 18:15:11.961595: Current learning rate: 0.0084 +2024-11-21 18:15:30.716882: train_loss -0.7672 +2024-11-21 18:15:30.717121: val_loss -0.7473 +2024-11-21 18:15:30.717199: Pseudo dice [0.8365] +2024-11-21 18:15:30.717271: Epoch time: 18.76 s +2024-11-21 18:15:31.545344: +2024-11-21 18:15:31.545620: Epoch 1413 +2024-11-21 18:15:31.545734: Current learning rate: 0.0084 +2024-11-21 18:15:49.119320: train_loss -0.7711 +2024-11-21 18:15:49.119596: val_loss -0.7653 +2024-11-21 18:15:49.119678: Pseudo dice [0.8578] +2024-11-21 18:15:49.119756: Epoch time: 17.57 s +2024-11-21 18:15:49.960637: +2024-11-21 18:15:49.961050: Epoch 1414 +2024-11-21 18:15:49.961165: Current learning rate: 0.00839 +2024-11-21 18:16:09.109555: train_loss -0.7679 +2024-11-21 18:16:09.109778: val_loss -0.7768 +2024-11-21 18:16:09.109856: Pseudo dice [0.8428] +2024-11-21 18:16:09.109930: Epoch time: 19.15 s +2024-11-21 18:16:10.040174: +2024-11-21 18:16:10.040398: Epoch 1415 +2024-11-21 18:16:10.040511: Current learning rate: 0.00839 +2024-11-21 18:16:28.067752: train_loss -0.7713 +2024-11-21 18:16:28.067985: val_loss -0.7625 +2024-11-21 18:16:28.068068: Pseudo dice [0.8428] +2024-11-21 18:16:28.068145: Epoch time: 18.03 s +2024-11-21 18:16:28.921691: +2024-11-21 18:16:28.922034: Epoch 1416 +2024-11-21 18:16:28.922146: Current learning rate: 0.00839 +2024-11-21 18:16:47.121095: train_loss -0.7688 +2024-11-21 18:16:47.121305: val_loss -0.7818 +2024-11-21 18:16:47.121381: Pseudo dice [0.8475] +2024-11-21 18:16:47.121463: Epoch time: 18.2 s +2024-11-21 18:16:47.960131: +2024-11-21 18:16:47.960351: Epoch 1417 +2024-11-21 18:16:47.960463: Current learning rate: 0.00839 +2024-11-21 18:17:07.304345: train_loss -0.7773 +2024-11-21 18:17:07.304575: val_loss -0.7698 +2024-11-21 18:17:07.304666: Pseudo dice [0.8439] +2024-11-21 18:17:07.304805: Epoch time: 19.35 s +2024-11-21 18:17:08.148732: +2024-11-21 18:17:08.148943: Epoch 1418 +2024-11-21 18:17:08.149052: Current learning rate: 0.00839 +2024-11-21 18:17:28.033828: train_loss -0.7637 +2024-11-21 18:17:28.034070: val_loss -0.7716 +2024-11-21 18:17:28.034150: Pseudo dice [0.8486] +2024-11-21 18:17:28.034227: Epoch time: 19.89 s +2024-11-21 18:17:28.874478: +2024-11-21 18:17:28.874747: Epoch 1419 +2024-11-21 18:17:28.874856: Current learning rate: 0.00839 +2024-11-21 18:17:46.787512: train_loss -0.7685 +2024-11-21 18:17:46.787742: val_loss -0.7766 +2024-11-21 18:17:46.787819: Pseudo dice [0.847] +2024-11-21 18:17:46.787901: Epoch time: 17.91 s +2024-11-21 18:17:47.667845: +2024-11-21 18:17:47.668062: Epoch 1420 +2024-11-21 18:17:47.668180: Current learning rate: 0.00839 +2024-11-21 18:18:07.462409: train_loss -0.7739 +2024-11-21 18:18:07.462621: val_loss -0.7428 +2024-11-21 18:18:07.462691: Pseudo dice [0.8461] +2024-11-21 18:18:07.467979: Epoch time: 19.8 s +2024-11-21 18:18:08.320301: +2024-11-21 18:18:08.320537: Epoch 1421 +2024-11-21 18:18:08.320652: Current learning rate: 0.00839 +2024-11-21 18:18:28.430450: train_loss -0.7748 +2024-11-21 18:18:28.434928: val_loss -0.7509 +2024-11-21 18:18:28.435032: Pseudo dice [0.8141] +2024-11-21 18:18:28.435112: Epoch time: 20.11 s +2024-11-21 18:18:29.476492: +2024-11-21 18:18:29.476700: Epoch 1422 +2024-11-21 18:18:29.476808: Current learning rate: 0.00839 +2024-11-21 18:18:48.639276: train_loss -0.7546 +2024-11-21 18:18:48.639536: val_loss -0.7835 +2024-11-21 18:18:48.639613: Pseudo dice [0.8482] +2024-11-21 18:18:48.639695: Epoch time: 19.16 s +2024-11-21 18:18:49.476375: +2024-11-21 18:18:49.476598: Epoch 1423 +2024-11-21 18:18:49.476715: Current learning rate: 0.00838 +2024-11-21 18:19:08.928940: train_loss -0.7674 +2024-11-21 18:19:08.929153: val_loss -0.7767 +2024-11-21 18:19:08.929235: Pseudo dice [0.8382] +2024-11-21 18:19:08.929314: Epoch time: 19.45 s +2024-11-21 18:19:09.770511: +2024-11-21 18:19:09.770713: Epoch 1424 +2024-11-21 18:19:09.770821: Current learning rate: 0.00838 +2024-11-21 18:19:27.210077: train_loss -0.7688 +2024-11-21 18:19:27.210290: val_loss -0.7527 +2024-11-21 18:19:27.210362: Pseudo dice [0.8356] +2024-11-21 18:19:27.210437: Epoch time: 17.44 s +2024-11-21 18:19:28.050451: +2024-11-21 18:19:28.050690: Epoch 1425 +2024-11-21 18:19:28.050802: Current learning rate: 0.00838 +2024-11-21 18:19:46.263873: train_loss -0.7712 +2024-11-21 18:19:46.264132: val_loss -0.789 +2024-11-21 18:19:46.264208: Pseudo dice [0.8628] +2024-11-21 18:19:46.264295: Epoch time: 18.21 s +2024-11-21 18:19:47.103309: +2024-11-21 18:19:47.103525: Epoch 1426 +2024-11-21 18:19:47.103633: Current learning rate: 0.00838 +2024-11-21 18:20:04.803369: train_loss -0.7689 +2024-11-21 18:20:04.803576: val_loss -0.7466 +2024-11-21 18:20:04.803674: Pseudo dice [0.8355] +2024-11-21 18:20:04.803751: Epoch time: 17.7 s +2024-11-21 18:20:05.634593: +2024-11-21 18:20:05.634822: Epoch 1427 +2024-11-21 18:20:05.634943: Current learning rate: 0.00838 +2024-11-21 18:20:23.654243: train_loss -0.7711 +2024-11-21 18:20:23.654488: val_loss -0.7664 +2024-11-21 18:20:23.654564: Pseudo dice [0.8377] +2024-11-21 18:20:23.654635: Epoch time: 18.02 s +2024-11-21 18:20:24.497232: +2024-11-21 18:20:24.497434: Epoch 1428 +2024-11-21 18:20:24.497546: Current learning rate: 0.00838 +2024-11-21 18:20:42.234333: train_loss -0.7622 +2024-11-21 18:20:42.234547: val_loss -0.7806 +2024-11-21 18:20:42.234621: Pseudo dice [0.8487] +2024-11-21 18:20:42.234699: Epoch time: 17.74 s +2024-11-21 18:20:43.072396: +2024-11-21 18:20:43.072606: Epoch 1429 +2024-11-21 18:20:43.072715: Current learning rate: 0.00838 +2024-11-21 18:21:00.427132: train_loss -0.7629 +2024-11-21 18:21:00.427394: val_loss -0.7463 +2024-11-21 18:21:00.427470: Pseudo dice [0.826] +2024-11-21 18:21:00.427566: Epoch time: 17.36 s +2024-11-21 18:21:01.271763: +2024-11-21 18:21:01.271986: Epoch 1430 +2024-11-21 18:21:01.272104: Current learning rate: 0.00838 +2024-11-21 18:21:20.010579: train_loss -0.7552 +2024-11-21 18:21:20.010798: val_loss -0.7832 +2024-11-21 18:21:20.010873: Pseudo dice [0.8496] +2024-11-21 18:21:20.010947: Epoch time: 18.74 s +2024-11-21 18:21:20.854306: +2024-11-21 18:21:20.854518: Epoch 1431 +2024-11-21 18:21:20.854626: Current learning rate: 0.00837 +2024-11-21 18:21:38.100108: train_loss -0.7713 +2024-11-21 18:21:38.100377: val_loss -0.7525 +2024-11-21 18:21:38.100455: Pseudo dice [0.8111] +2024-11-21 18:21:38.100530: Epoch time: 17.25 s +2024-11-21 18:21:38.937714: +2024-11-21 18:21:38.937933: Epoch 1432 +2024-11-21 18:21:38.938049: Current learning rate: 0.00837 +2024-11-21 18:21:56.705344: train_loss -0.7654 +2024-11-21 18:21:56.705597: val_loss -0.7672 +2024-11-21 18:21:56.705689: Pseudo dice [0.8392] +2024-11-21 18:21:56.705773: Epoch time: 17.77 s +2024-11-21 18:21:58.232340: +2024-11-21 18:21:58.232577: Epoch 1433 +2024-11-21 18:21:58.232688: Current learning rate: 0.00837 +2024-11-21 18:22:16.594801: train_loss -0.7578 +2024-11-21 18:22:16.600193: val_loss -0.7694 +2024-11-21 18:22:16.600277: Pseudo dice [0.8534] +2024-11-21 18:22:16.600355: Epoch time: 18.36 s +2024-11-21 18:22:17.601528: +2024-11-21 18:22:17.601751: Epoch 1434 +2024-11-21 18:22:17.601863: Current learning rate: 0.00837 +2024-11-21 18:22:35.243327: train_loss -0.7619 +2024-11-21 18:22:35.243533: val_loss -0.7507 +2024-11-21 18:22:35.243607: Pseudo dice [0.8075] +2024-11-21 18:22:35.243680: Epoch time: 17.64 s +2024-11-21 18:22:36.086567: +2024-11-21 18:22:36.086776: Epoch 1435 +2024-11-21 18:22:36.086887: Current learning rate: 0.00837 +2024-11-21 18:22:54.513231: train_loss -0.767 +2024-11-21 18:22:54.513463: val_loss -0.7594 +2024-11-21 18:22:54.513543: Pseudo dice [0.8321] +2024-11-21 18:22:54.513625: Epoch time: 18.43 s +2024-11-21 18:22:55.388163: +2024-11-21 18:22:55.388439: Epoch 1436 +2024-11-21 18:22:55.388570: Current learning rate: 0.00837 +2024-11-21 18:23:14.314528: train_loss -0.771 +2024-11-21 18:23:14.314733: val_loss -0.7621 +2024-11-21 18:23:14.314808: Pseudo dice [0.8376] +2024-11-21 18:23:14.314883: Epoch time: 18.93 s +2024-11-21 18:23:15.151104: +2024-11-21 18:23:15.151305: Epoch 1437 +2024-11-21 18:23:15.151413: Current learning rate: 0.00837 +2024-11-21 18:23:33.836055: train_loss -0.7691 +2024-11-21 18:23:33.836266: val_loss -0.7826 +2024-11-21 18:23:33.836341: Pseudo dice [0.8462] +2024-11-21 18:23:33.836681: Epoch time: 18.69 s +2024-11-21 18:23:34.680403: +2024-11-21 18:23:34.680615: Epoch 1438 +2024-11-21 18:23:34.680727: Current learning rate: 0.00837 +2024-11-21 18:23:53.459563: train_loss -0.77 +2024-11-21 18:23:53.459837: val_loss -0.7565 +2024-11-21 18:23:53.459917: Pseudo dice [0.8405] +2024-11-21 18:23:53.459996: Epoch time: 18.78 s +2024-11-21 18:23:54.297174: +2024-11-21 18:23:54.297397: Epoch 1439 +2024-11-21 18:23:54.297510: Current learning rate: 0.00837 +2024-11-21 18:24:12.414241: train_loss -0.7671 +2024-11-21 18:24:12.414518: val_loss -0.7449 +2024-11-21 18:24:12.414614: Pseudo dice [0.8131] +2024-11-21 18:24:12.414706: Epoch time: 18.12 s +2024-11-21 18:24:13.262449: +2024-11-21 18:24:13.262719: Epoch 1440 +2024-11-21 18:24:13.262829: Current learning rate: 0.00836 +2024-11-21 18:24:31.816572: train_loss -0.7702 +2024-11-21 18:24:31.816840: val_loss -0.7542 +2024-11-21 18:24:31.816913: Pseudo dice [0.8297] +2024-11-21 18:24:31.816985: Epoch time: 18.55 s +2024-11-21 18:24:32.651870: +2024-11-21 18:24:32.652100: Epoch 1441 +2024-11-21 18:24:32.652207: Current learning rate: 0.00836 +2024-11-21 18:24:51.035600: train_loss -0.7654 +2024-11-21 18:24:51.035898: val_loss -0.7357 +2024-11-21 18:24:51.035988: Pseudo dice [0.8217] +2024-11-21 18:24:51.036067: Epoch time: 18.38 s +2024-11-21 18:24:51.867640: +2024-11-21 18:24:51.867863: Epoch 1442 +2024-11-21 18:24:51.867977: Current learning rate: 0.00836 +2024-11-21 18:25:10.438154: train_loss -0.7727 +2024-11-21 18:25:10.438362: val_loss -0.7629 +2024-11-21 18:25:10.438436: Pseudo dice [0.8544] +2024-11-21 18:25:10.438515: Epoch time: 18.57 s +2024-11-21 18:25:11.296704: +2024-11-21 18:25:11.296912: Epoch 1443 +2024-11-21 18:25:11.297027: Current learning rate: 0.00836 +2024-11-21 18:25:29.654719: train_loss -0.7724 +2024-11-21 18:25:29.654948: val_loss -0.757 +2024-11-21 18:25:29.655027: Pseudo dice [0.838] +2024-11-21 18:25:29.655106: Epoch time: 18.36 s +2024-11-21 18:25:30.482890: +2024-11-21 18:25:30.483311: Epoch 1444 +2024-11-21 18:25:30.483442: Current learning rate: 0.00836 +2024-11-21 18:25:48.715248: train_loss -0.7698 +2024-11-21 18:25:48.715457: val_loss -0.7314 +2024-11-21 18:25:48.715531: Pseudo dice [0.8083] +2024-11-21 18:25:48.715602: Epoch time: 18.23 s +2024-11-21 18:25:49.991553: +2024-11-21 18:25:49.991771: Epoch 1445 +2024-11-21 18:25:49.991880: Current learning rate: 0.00836 +2024-11-21 18:26:08.166240: train_loss -0.7765 +2024-11-21 18:26:08.166480: val_loss -0.7544 +2024-11-21 18:26:08.166554: Pseudo dice [0.8257] +2024-11-21 18:26:08.166632: Epoch time: 18.18 s +2024-11-21 18:26:09.079112: +2024-11-21 18:26:09.079354: Epoch 1446 +2024-11-21 18:26:09.079472: Current learning rate: 0.00836 +2024-11-21 18:26:27.532177: train_loss -0.7741 +2024-11-21 18:26:27.537652: val_loss -0.7648 +2024-11-21 18:26:27.537778: Pseudo dice [0.8436] +2024-11-21 18:26:27.537860: Epoch time: 18.45 s +2024-11-21 18:26:28.421031: +2024-11-21 18:26:28.421258: Epoch 1447 +2024-11-21 18:26:28.421368: Current learning rate: 0.00836 +2024-11-21 18:26:47.035248: train_loss -0.7661 +2024-11-21 18:26:47.035465: val_loss -0.7665 +2024-11-21 18:26:47.035625: Pseudo dice [0.8273] +2024-11-21 18:26:47.035702: Epoch time: 18.62 s +2024-11-21 18:26:47.869788: +2024-11-21 18:26:47.870023: Epoch 1448 +2024-11-21 18:26:47.870132: Current learning rate: 0.00836 +2024-11-21 18:27:06.952886: train_loss -0.7674 +2024-11-21 18:27:06.953102: val_loss -0.735 +2024-11-21 18:27:06.953176: Pseudo dice [0.8221] +2024-11-21 18:27:06.953248: Epoch time: 19.08 s +2024-11-21 18:27:07.798981: +2024-11-21 18:27:07.799192: Epoch 1449 +2024-11-21 18:27:07.799299: Current learning rate: 0.00835 +2024-11-21 18:27:27.401928: train_loss -0.766 +2024-11-21 18:27:27.402174: val_loss -0.7404 +2024-11-21 18:27:27.402252: Pseudo dice [0.8517] +2024-11-21 18:27:27.402338: Epoch time: 19.6 s +2024-11-21 18:27:28.434708: +2024-11-21 18:27:28.434937: Epoch 1450 +2024-11-21 18:27:28.435050: Current learning rate: 0.00835 +2024-11-21 18:27:46.395926: train_loss -0.7652 +2024-11-21 18:27:46.396138: val_loss -0.7636 +2024-11-21 18:27:46.396210: Pseudo dice [0.8392] +2024-11-21 18:27:46.396281: Epoch time: 17.96 s +2024-11-21 18:27:47.288136: +2024-11-21 18:27:47.288353: Epoch 1451 +2024-11-21 18:27:47.288462: Current learning rate: 0.00835 +2024-11-21 18:28:05.605652: train_loss -0.7696 +2024-11-21 18:28:05.605865: val_loss -0.7472 +2024-11-21 18:28:05.605936: Pseudo dice [0.8218] +2024-11-21 18:28:05.606015: Epoch time: 18.32 s +2024-11-21 18:28:06.441902: +2024-11-21 18:28:06.442132: Epoch 1452 +2024-11-21 18:28:06.442240: Current learning rate: 0.00835 +2024-11-21 18:28:24.670979: train_loss -0.7617 +2024-11-21 18:28:24.671203: val_loss -0.7382 +2024-11-21 18:28:24.671276: Pseudo dice [0.8429] +2024-11-21 18:28:24.671350: Epoch time: 18.23 s +2024-11-21 18:28:25.608341: +2024-11-21 18:28:25.608554: Epoch 1453 +2024-11-21 18:28:25.608666: Current learning rate: 0.00835 +2024-11-21 18:28:45.059629: train_loss -0.7605 +2024-11-21 18:28:45.059915: val_loss -0.7615 +2024-11-21 18:28:45.060000: Pseudo dice [0.8395] +2024-11-21 18:28:45.060083: Epoch time: 19.45 s +2024-11-21 18:28:45.900376: +2024-11-21 18:28:45.900599: Epoch 1454 +2024-11-21 18:28:45.900709: Current learning rate: 0.00835 +2024-11-21 18:29:05.382946: train_loss -0.7665 +2024-11-21 18:29:05.383157: val_loss -0.7712 +2024-11-21 18:29:05.383229: Pseudo dice [0.8396] +2024-11-21 18:29:05.383301: Epoch time: 19.48 s +2024-11-21 18:29:06.308822: +2024-11-21 18:29:06.309035: Epoch 1455 +2024-11-21 18:29:06.309147: Current learning rate: 0.00835 +2024-11-21 18:29:24.223658: train_loss -0.7686 +2024-11-21 18:29:24.223871: val_loss -0.7542 +2024-11-21 18:29:24.223948: Pseudo dice [0.8328] +2024-11-21 18:29:24.224025: Epoch time: 17.92 s +2024-11-21 18:29:25.428904: +2024-11-21 18:29:25.429327: Epoch 1456 +2024-11-21 18:29:25.429456: Current learning rate: 0.00835 +2024-11-21 18:29:44.745445: train_loss -0.7766 +2024-11-21 18:29:44.745708: val_loss -0.7544 +2024-11-21 18:29:44.745790: Pseudo dice [0.8416] +2024-11-21 18:29:44.745874: Epoch time: 19.32 s +2024-11-21 18:29:45.581107: +2024-11-21 18:29:45.581571: Epoch 1457 +2024-11-21 18:29:45.581696: Current learning rate: 0.00834 +2024-11-21 18:30:03.403518: train_loss -0.7685 +2024-11-21 18:30:03.403750: val_loss -0.782 +2024-11-21 18:30:03.403828: Pseudo dice [0.8514] +2024-11-21 18:30:03.403904: Epoch time: 17.82 s +2024-11-21 18:30:04.344785: +2024-11-21 18:30:04.345324: Epoch 1458 +2024-11-21 18:30:04.345458: Current learning rate: 0.00834 +2024-11-21 18:30:21.916161: train_loss -0.7651 +2024-11-21 18:30:21.916423: val_loss -0.7396 +2024-11-21 18:30:21.916502: Pseudo dice [0.8237] +2024-11-21 18:30:21.916576: Epoch time: 17.57 s +2024-11-21 18:30:22.742642: +2024-11-21 18:30:22.743064: Epoch 1459 +2024-11-21 18:30:22.743192: Current learning rate: 0.00834 +2024-11-21 18:30:41.395226: train_loss -0.7607 +2024-11-21 18:30:41.395436: val_loss -0.7415 +2024-11-21 18:30:41.395513: Pseudo dice [0.8388] +2024-11-21 18:30:41.395593: Epoch time: 18.65 s +2024-11-21 18:30:42.226591: +2024-11-21 18:30:42.227032: Epoch 1460 +2024-11-21 18:30:42.227174: Current learning rate: 0.00834 +2024-11-21 18:31:00.502961: train_loss -0.7656 +2024-11-21 18:31:00.503249: val_loss -0.7513 +2024-11-21 18:31:00.503334: Pseudo dice [0.8022] +2024-11-21 18:31:00.503414: Epoch time: 18.28 s +2024-11-21 18:31:01.349980: +2024-11-21 18:31:01.350420: Epoch 1461 +2024-11-21 18:31:01.350552: Current learning rate: 0.00834 +2024-11-21 18:31:20.450048: train_loss -0.7623 +2024-11-21 18:31:20.450260: val_loss -0.7381 +2024-11-21 18:31:20.452601: Pseudo dice [0.8316] +2024-11-21 18:31:20.452746: Epoch time: 19.1 s +2024-11-21 18:31:21.301797: +2024-11-21 18:31:21.302179: Epoch 1462 +2024-11-21 18:31:21.302307: Current learning rate: 0.00834 +2024-11-21 18:31:39.454516: train_loss -0.7667 +2024-11-21 18:31:39.454731: val_loss -0.7714 +2024-11-21 18:31:39.454803: Pseudo dice [0.8465] +2024-11-21 18:31:39.454874: Epoch time: 18.15 s +2024-11-21 18:31:40.289011: +2024-11-21 18:31:40.289441: Epoch 1463 +2024-11-21 18:31:40.289572: Current learning rate: 0.00834 +2024-11-21 18:31:57.742410: train_loss -0.7759 +2024-11-21 18:31:57.742653: val_loss -0.7513 +2024-11-21 18:31:57.747155: Pseudo dice [0.8317] +2024-11-21 18:31:57.747339: Epoch time: 17.45 s +2024-11-21 18:31:58.600147: +2024-11-21 18:31:58.600608: Epoch 1464 +2024-11-21 18:31:58.600741: Current learning rate: 0.00834 +2024-11-21 18:32:17.441567: train_loss -0.7615 +2024-11-21 18:32:17.441789: val_loss -0.781 +2024-11-21 18:32:17.441865: Pseudo dice [0.8295] +2024-11-21 18:32:17.441940: Epoch time: 18.84 s +2024-11-21 18:32:18.267386: +2024-11-21 18:32:18.267800: Epoch 1465 +2024-11-21 18:32:18.267932: Current learning rate: 0.00834 +2024-11-21 18:32:37.123533: train_loss -0.7748 +2024-11-21 18:32:37.123751: val_loss -0.7814 +2024-11-21 18:32:37.123827: Pseudo dice [0.8419] +2024-11-21 18:32:37.123910: Epoch time: 18.86 s +2024-11-21 18:32:37.955709: +2024-11-21 18:32:37.956141: Epoch 1466 +2024-11-21 18:32:37.956265: Current learning rate: 0.00833 +2024-11-21 18:32:55.701202: train_loss -0.7533 +2024-11-21 18:32:55.701411: val_loss -0.7645 +2024-11-21 18:32:55.701484: Pseudo dice [0.8276] +2024-11-21 18:32:55.701563: Epoch time: 17.75 s +2024-11-21 18:32:56.923348: +2024-11-21 18:32:56.923767: Epoch 1467 +2024-11-21 18:32:56.923894: Current learning rate: 0.00833 +2024-11-21 18:33:14.731122: train_loss -0.7639 +2024-11-21 18:33:14.732117: val_loss -0.7414 +2024-11-21 18:33:14.732198: Pseudo dice [0.8231] +2024-11-21 18:33:14.732279: Epoch time: 17.81 s +2024-11-21 18:33:15.561196: +2024-11-21 18:33:15.561620: Epoch 1468 +2024-11-21 18:33:15.561749: Current learning rate: 0.00833 +2024-11-21 18:33:33.087175: train_loss -0.7642 +2024-11-21 18:33:33.087390: val_loss -0.7325 +2024-11-21 18:33:33.087470: Pseudo dice [0.8194] +2024-11-21 18:33:33.087547: Epoch time: 17.53 s +2024-11-21 18:33:33.938793: +2024-11-21 18:33:33.939268: Epoch 1469 +2024-11-21 18:33:33.939399: Current learning rate: 0.00833 +2024-11-21 18:33:53.463103: train_loss -0.7571 +2024-11-21 18:33:53.463309: val_loss -0.7726 +2024-11-21 18:33:53.463386: Pseudo dice [0.8305] +2024-11-21 18:33:53.463461: Epoch time: 19.53 s +2024-11-21 18:33:54.297209: +2024-11-21 18:33:54.297675: Epoch 1470 +2024-11-21 18:33:54.297802: Current learning rate: 0.00833 +2024-11-21 18:34:14.003290: train_loss -0.7672 +2024-11-21 18:34:14.003517: val_loss -0.7771 +2024-11-21 18:34:14.003592: Pseudo dice [0.8219] +2024-11-21 18:34:14.003671: Epoch time: 19.71 s +2024-11-21 18:34:14.838227: +2024-11-21 18:34:14.838658: Epoch 1471 +2024-11-21 18:34:14.838786: Current learning rate: 0.00833 +2024-11-21 18:34:32.896095: train_loss -0.7632 +2024-11-21 18:34:32.896317: val_loss -0.7541 +2024-11-21 18:34:32.896403: Pseudo dice [0.8241] +2024-11-21 18:34:32.896477: Epoch time: 18.06 s +2024-11-21 18:34:33.750130: +2024-11-21 18:34:33.750566: Epoch 1472 +2024-11-21 18:34:33.750698: Current learning rate: 0.00833 +2024-11-21 18:34:52.347554: train_loss -0.7693 +2024-11-21 18:34:52.347787: val_loss -0.7415 +2024-11-21 18:34:52.347902: Pseudo dice [0.8399] +2024-11-21 18:34:52.347977: Epoch time: 18.6 s +2024-11-21 18:34:53.176914: +2024-11-21 18:34:53.177342: Epoch 1473 +2024-11-21 18:34:53.177480: Current learning rate: 0.00833 +2024-11-21 18:35:11.210689: train_loss -0.7666 +2024-11-21 18:35:11.210973: val_loss -0.7656 +2024-11-21 18:35:11.211060: Pseudo dice [0.8446] +2024-11-21 18:35:11.211141: Epoch time: 18.03 s +2024-11-21 18:35:12.048172: +2024-11-21 18:35:12.048577: Epoch 1474 +2024-11-21 18:35:12.048705: Current learning rate: 0.00833 +2024-11-21 18:35:29.507466: train_loss -0.7616 +2024-11-21 18:35:29.507706: val_loss -0.7616 +2024-11-21 18:35:29.507780: Pseudo dice [0.8359] +2024-11-21 18:35:29.507857: Epoch time: 17.46 s +2024-11-21 18:35:30.343610: +2024-11-21 18:35:30.343831: Epoch 1475 +2024-11-21 18:35:30.343947: Current learning rate: 0.00832 +2024-11-21 18:35:48.041560: train_loss -0.768 +2024-11-21 18:35:48.041775: val_loss -0.7713 +2024-11-21 18:35:48.041876: Pseudo dice [0.8336] +2024-11-21 18:35:48.041957: Epoch time: 17.7 s +2024-11-21 18:35:48.874571: +2024-11-21 18:35:48.874773: Epoch 1476 +2024-11-21 18:35:48.874883: Current learning rate: 0.00832 +2024-11-21 18:36:07.215527: train_loss -0.7589 +2024-11-21 18:36:07.215786: val_loss -0.7564 +2024-11-21 18:36:07.215862: Pseudo dice [0.8312] +2024-11-21 18:36:07.215937: Epoch time: 18.34 s +2024-11-21 18:36:08.045624: +2024-11-21 18:36:08.046099: Epoch 1477 +2024-11-21 18:36:08.046236: Current learning rate: 0.00832 +2024-11-21 18:36:26.817100: train_loss -0.7685 +2024-11-21 18:36:26.819531: val_loss -0.7703 +2024-11-21 18:36:26.819689: Pseudo dice [0.8416] +2024-11-21 18:36:26.819781: Epoch time: 18.77 s +2024-11-21 18:36:27.802977: +2024-11-21 18:36:27.803250: Epoch 1478 +2024-11-21 18:36:27.803376: Current learning rate: 0.00832 +2024-11-21 18:36:46.806247: train_loss -0.7582 +2024-11-21 18:36:46.806466: val_loss -0.7463 +2024-11-21 18:36:46.811723: Pseudo dice [0.8373] +2024-11-21 18:36:46.811934: Epoch time: 19.0 s +2024-11-21 18:36:48.163471: +2024-11-21 18:36:48.163691: Epoch 1479 +2024-11-21 18:36:48.163800: Current learning rate: 0.00832 +2024-11-21 18:37:05.904711: train_loss -0.7636 +2024-11-21 18:37:05.904932: val_loss -0.765 +2024-11-21 18:37:05.905043: Pseudo dice [0.8411] +2024-11-21 18:37:05.905170: Epoch time: 17.74 s +2024-11-21 18:37:06.746070: +2024-11-21 18:37:06.746280: Epoch 1480 +2024-11-21 18:37:06.746390: Current learning rate: 0.00832 +2024-11-21 18:37:25.346501: train_loss -0.7545 +2024-11-21 18:37:25.346724: val_loss -0.7455 +2024-11-21 18:37:25.346800: Pseudo dice [0.8217] +2024-11-21 18:37:25.346879: Epoch time: 18.6 s +2024-11-21 18:37:26.332979: +2024-11-21 18:37:26.333325: Epoch 1481 +2024-11-21 18:37:26.333442: Current learning rate: 0.00832 +2024-11-21 18:37:44.613364: train_loss -0.7604 +2024-11-21 18:37:44.614397: val_loss -0.7699 +2024-11-21 18:37:44.614477: Pseudo dice [0.8376] +2024-11-21 18:37:44.614558: Epoch time: 18.28 s +2024-11-21 18:37:45.453333: +2024-11-21 18:37:45.453549: Epoch 1482 +2024-11-21 18:37:45.453665: Current learning rate: 0.00832 +2024-11-21 18:38:05.051300: train_loss -0.7722 +2024-11-21 18:38:05.056717: val_loss -0.7501 +2024-11-21 18:38:05.056851: Pseudo dice [0.8364] +2024-11-21 18:38:05.056933: Epoch time: 19.6 s +2024-11-21 18:38:05.911253: +2024-11-21 18:38:05.911459: Epoch 1483 +2024-11-21 18:38:05.911578: Current learning rate: 0.00831 +2024-11-21 18:38:23.974009: train_loss -0.7739 +2024-11-21 18:38:23.974218: val_loss -0.7389 +2024-11-21 18:38:23.974288: Pseudo dice [0.8386] +2024-11-21 18:38:23.974361: Epoch time: 18.06 s +2024-11-21 18:38:24.819482: +2024-11-21 18:38:24.819712: Epoch 1484 +2024-11-21 18:38:24.819825: Current learning rate: 0.00831 +2024-11-21 18:38:42.864578: train_loss -0.7658 +2024-11-21 18:38:42.864788: val_loss -0.7417 +2024-11-21 18:38:42.864864: Pseudo dice [0.8265] +2024-11-21 18:38:42.864942: Epoch time: 18.05 s +2024-11-21 18:38:43.699149: +2024-11-21 18:38:43.699366: Epoch 1485 +2024-11-21 18:38:43.699487: Current learning rate: 0.00831 +2024-11-21 18:39:03.055057: train_loss -0.7614 +2024-11-21 18:39:03.056027: val_loss -0.7459 +2024-11-21 18:39:03.056126: Pseudo dice [0.8161] +2024-11-21 18:39:03.056213: Epoch time: 19.36 s +2024-11-21 18:39:03.890852: +2024-11-21 18:39:03.891065: Epoch 1486 +2024-11-21 18:39:03.891172: Current learning rate: 0.00831 +2024-11-21 18:39:22.778199: train_loss -0.767 +2024-11-21 18:39:22.778415: val_loss -0.7509 +2024-11-21 18:39:22.778488: Pseudo dice [0.8447] +2024-11-21 18:39:22.778563: Epoch time: 18.89 s +2024-11-21 18:39:23.672476: +2024-11-21 18:39:23.672691: Epoch 1487 +2024-11-21 18:39:23.672802: Current learning rate: 0.00831 +2024-11-21 18:39:41.356762: train_loss -0.7676 +2024-11-21 18:39:41.356966: val_loss -0.7543 +2024-11-21 18:39:41.357047: Pseudo dice [0.8387] +2024-11-21 18:39:41.357120: Epoch time: 17.69 s +2024-11-21 18:39:42.196853: +2024-11-21 18:39:42.197066: Epoch 1488 +2024-11-21 18:39:42.197183: Current learning rate: 0.00831 +2024-11-21 18:40:00.498194: train_loss -0.7766 +2024-11-21 18:40:00.498483: val_loss -0.74 +2024-11-21 18:40:00.498574: Pseudo dice [0.8508] +2024-11-21 18:40:00.498675: Epoch time: 18.3 s +2024-11-21 18:40:01.340338: +2024-11-21 18:40:01.340621: Epoch 1489 +2024-11-21 18:40:01.340733: Current learning rate: 0.00831 +2024-11-21 18:40:20.696626: train_loss -0.7713 +2024-11-21 18:40:20.696833: val_loss -0.7618 +2024-11-21 18:40:20.702316: Pseudo dice [0.8074] +2024-11-21 18:40:20.702454: Epoch time: 19.36 s +2024-11-21 18:40:22.126109: +2024-11-21 18:40:22.126342: Epoch 1490 +2024-11-21 18:40:22.126456: Current learning rate: 0.00831 +2024-11-21 18:40:40.088935: train_loss -0.764 +2024-11-21 18:40:40.089186: val_loss -0.7756 +2024-11-21 18:40:40.089264: Pseudo dice [0.8323] +2024-11-21 18:40:40.089344: Epoch time: 17.96 s +2024-11-21 18:40:40.932640: +2024-11-21 18:40:40.932924: Epoch 1491 +2024-11-21 18:40:40.933037: Current learning rate: 0.00831 +2024-11-21 18:40:59.257138: train_loss -0.7435 +2024-11-21 18:40:59.257377: val_loss -0.7255 +2024-11-21 18:40:59.257452: Pseudo dice [0.8155] +2024-11-21 18:40:59.257535: Epoch time: 18.33 s +2024-11-21 18:41:00.096615: +2024-11-21 18:41:00.096879: Epoch 1492 +2024-11-21 18:41:00.097004: Current learning rate: 0.0083 +2024-11-21 18:41:19.842108: train_loss -0.7443 +2024-11-21 18:41:19.842324: val_loss -0.7811 +2024-11-21 18:41:19.842396: Pseudo dice [0.8433] +2024-11-21 18:41:19.842469: Epoch time: 19.75 s +2024-11-21 18:41:20.719927: +2024-11-21 18:41:20.720156: Epoch 1493 +2024-11-21 18:41:20.720265: Current learning rate: 0.0083 +2024-11-21 18:41:38.146918: train_loss -0.7694 +2024-11-21 18:41:38.147149: val_loss -0.7448 +2024-11-21 18:41:38.147222: Pseudo dice [0.8217] +2024-11-21 18:41:38.152442: Epoch time: 17.43 s +2024-11-21 18:41:39.041066: +2024-11-21 18:41:39.041306: Epoch 1494 +2024-11-21 18:41:39.041414: Current learning rate: 0.0083 +2024-11-21 18:41:57.658762: train_loss -0.7646 +2024-11-21 18:41:57.658984: val_loss -0.752 +2024-11-21 18:41:57.659069: Pseudo dice [0.8141] +2024-11-21 18:41:57.659150: Epoch time: 18.62 s +2024-11-21 18:41:58.497962: +2024-11-21 18:41:58.498194: Epoch 1495 +2024-11-21 18:41:58.498309: Current learning rate: 0.0083 +2024-11-21 18:42:16.886315: train_loss -0.7631 +2024-11-21 18:42:16.891756: val_loss -0.7492 +2024-11-21 18:42:16.891865: Pseudo dice [0.8267] +2024-11-21 18:42:16.891948: Epoch time: 18.39 s +2024-11-21 18:42:17.997184: +2024-11-21 18:42:17.997406: Epoch 1496 +2024-11-21 18:42:17.997515: Current learning rate: 0.0083 +2024-11-21 18:42:35.778468: train_loss -0.7716 +2024-11-21 18:42:35.778689: val_loss -0.7459 +2024-11-21 18:42:35.778763: Pseudo dice [0.8497] +2024-11-21 18:42:35.778836: Epoch time: 17.78 s +2024-11-21 18:42:36.714200: +2024-11-21 18:42:36.714427: Epoch 1497 +2024-11-21 18:42:36.714542: Current learning rate: 0.0083 +2024-11-21 18:42:55.249777: train_loss -0.7756 +2024-11-21 18:42:55.250006: val_loss -0.78 +2024-11-21 18:42:55.250095: Pseudo dice [0.857] +2024-11-21 18:42:55.250175: Epoch time: 18.54 s +2024-11-21 18:42:56.187532: +2024-11-21 18:42:56.187730: Epoch 1498 +2024-11-21 18:42:56.187838: Current learning rate: 0.0083 +2024-11-21 18:43:14.980421: train_loss -0.7699 +2024-11-21 18:43:14.980672: val_loss -0.7633 +2024-11-21 18:43:14.980750: Pseudo dice [0.8557] +2024-11-21 18:43:14.980836: Epoch time: 18.79 s +2024-11-21 18:43:15.823671: +2024-11-21 18:43:15.823882: Epoch 1499 +2024-11-21 18:43:15.824003: Current learning rate: 0.0083 +2024-11-21 18:43:34.445487: train_loss -0.7651 +2024-11-21 18:43:34.445746: val_loss -0.7495 +2024-11-21 18:43:34.445824: Pseudo dice [0.8359] +2024-11-21 18:43:34.458952: Epoch time: 18.62 s +2024-11-21 18:43:35.503977: +2024-11-21 18:43:35.504198: Epoch 1500 +2024-11-21 18:43:35.504306: Current learning rate: 0.0083 +2024-11-21 18:43:53.128861: train_loss -0.7657 +2024-11-21 18:43:53.129105: val_loss -0.7538 +2024-11-21 18:43:53.129182: Pseudo dice [0.8447] +2024-11-21 18:43:53.129259: Epoch time: 17.63 s +2024-11-21 18:43:54.349348: +2024-11-21 18:43:54.349553: Epoch 1501 +2024-11-21 18:43:54.349662: Current learning rate: 0.00829 +2024-11-21 18:44:11.805046: train_loss -0.7763 +2024-11-21 18:44:11.805305: val_loss -0.7645 +2024-11-21 18:44:11.805385: Pseudo dice [0.8354] +2024-11-21 18:44:11.805467: Epoch time: 17.46 s +2024-11-21 18:44:12.641066: +2024-11-21 18:44:12.641320: Epoch 1502 +2024-11-21 18:44:12.641441: Current learning rate: 0.00829 +2024-11-21 18:44:30.295774: train_loss -0.7777 +2024-11-21 18:44:30.296014: val_loss -0.7774 +2024-11-21 18:44:30.296091: Pseudo dice [0.8449] +2024-11-21 18:44:30.296165: Epoch time: 17.66 s +2024-11-21 18:44:31.181890: +2024-11-21 18:44:31.182135: Epoch 1503 +2024-11-21 18:44:31.182244: Current learning rate: 0.00829 +2024-11-21 18:44:49.307269: train_loss -0.7739 +2024-11-21 18:44:49.307557: val_loss -0.7734 +2024-11-21 18:44:49.307634: Pseudo dice [0.846] +2024-11-21 18:44:49.307710: Epoch time: 18.13 s +2024-11-21 18:44:50.151076: +2024-11-21 18:44:50.151303: Epoch 1504 +2024-11-21 18:44:50.151410: Current learning rate: 0.00829 +2024-11-21 18:45:08.557969: train_loss -0.7705 +2024-11-21 18:45:08.558200: val_loss -0.7515 +2024-11-21 18:45:08.558277: Pseudo dice [0.84] +2024-11-21 18:45:08.558363: Epoch time: 18.41 s +2024-11-21 18:45:09.410231: +2024-11-21 18:45:09.410464: Epoch 1505 +2024-11-21 18:45:09.410574: Current learning rate: 0.00829 +2024-11-21 18:45:28.153105: train_loss -0.7716 +2024-11-21 18:45:28.153329: val_loss -0.7725 +2024-11-21 18:45:28.153400: Pseudo dice [0.8384] +2024-11-21 18:45:28.153474: Epoch time: 18.74 s +2024-11-21 18:45:28.995236: +2024-11-21 18:45:28.995465: Epoch 1506 +2024-11-21 18:45:28.995574: Current learning rate: 0.00829 +2024-11-21 18:45:46.917424: train_loss -0.7629 +2024-11-21 18:45:46.917638: val_loss -0.7645 +2024-11-21 18:45:46.917717: Pseudo dice [0.8397] +2024-11-21 18:45:46.917791: Epoch time: 17.92 s +2024-11-21 18:45:47.769098: +2024-11-21 18:45:47.769326: Epoch 1507 +2024-11-21 18:45:47.769453: Current learning rate: 0.00829 +2024-11-21 18:46:05.818481: train_loss -0.7701 +2024-11-21 18:46:05.818698: val_loss -0.7315 +2024-11-21 18:46:05.818776: Pseudo dice [0.8386] +2024-11-21 18:46:05.818855: Epoch time: 18.05 s +2024-11-21 18:46:06.653621: +2024-11-21 18:46:06.653837: Epoch 1508 +2024-11-21 18:46:06.653949: Current learning rate: 0.00829 +2024-11-21 18:46:25.619016: train_loss -0.7516 +2024-11-21 18:46:25.619229: val_loss -0.7542 +2024-11-21 18:46:25.619303: Pseudo dice [0.8242] +2024-11-21 18:46:25.619451: Epoch time: 18.97 s +2024-11-21 18:46:26.518075: +2024-11-21 18:46:26.518284: Epoch 1509 +2024-11-21 18:46:26.518403: Current learning rate: 0.00829 +2024-11-21 18:46:45.631158: train_loss -0.7478 +2024-11-21 18:46:45.631389: val_loss -0.7404 +2024-11-21 18:46:45.631461: Pseudo dice [0.8309] +2024-11-21 18:46:45.631543: Epoch time: 19.11 s +2024-11-21 18:46:46.517342: +2024-11-21 18:46:46.517549: Epoch 1510 +2024-11-21 18:46:46.517658: Current learning rate: 0.00828 +2024-11-21 18:47:05.034555: train_loss -0.7541 +2024-11-21 18:47:05.034830: val_loss -0.7775 +2024-11-21 18:47:05.034907: Pseudo dice [0.8472] +2024-11-21 18:47:05.034983: Epoch time: 18.52 s +2024-11-21 18:47:05.874238: +2024-11-21 18:47:05.874423: Epoch 1511 +2024-11-21 18:47:05.874534: Current learning rate: 0.00828 +2024-11-21 18:47:23.573396: train_loss -0.7698 +2024-11-21 18:47:23.573622: val_loss -0.7592 +2024-11-21 18:47:23.573754: Pseudo dice [0.8451] +2024-11-21 18:47:23.573830: Epoch time: 17.7 s +2024-11-21 18:47:24.892358: +2024-11-21 18:47:24.892592: Epoch 1512 +2024-11-21 18:47:24.892705: Current learning rate: 0.00828 +2024-11-21 18:47:42.657867: train_loss -0.7654 +2024-11-21 18:47:42.658141: val_loss -0.762 +2024-11-21 18:47:42.658218: Pseudo dice [0.8405] +2024-11-21 18:47:42.658301: Epoch time: 17.77 s +2024-11-21 18:47:43.498605: +2024-11-21 18:47:43.498832: Epoch 1513 +2024-11-21 18:47:43.498937: Current learning rate: 0.00828 +2024-11-21 18:48:01.161099: train_loss -0.7587 +2024-11-21 18:48:01.161362: val_loss -0.7666 +2024-11-21 18:48:01.161463: Pseudo dice [0.8468] +2024-11-21 18:48:01.161537: Epoch time: 17.66 s +2024-11-21 18:48:01.997989: +2024-11-21 18:48:01.998232: Epoch 1514 +2024-11-21 18:48:01.998341: Current learning rate: 0.00828 +2024-11-21 18:48:22.038283: train_loss -0.7659 +2024-11-21 18:48:22.038489: val_loss -0.7604 +2024-11-21 18:48:22.038562: Pseudo dice [0.8215] +2024-11-21 18:48:22.038646: Epoch time: 20.04 s +2024-11-21 18:48:22.877145: +2024-11-21 18:48:22.877465: Epoch 1515 +2024-11-21 18:48:22.877574: Current learning rate: 0.00828 +2024-11-21 18:48:41.524323: train_loss -0.7612 +2024-11-21 18:48:41.524936: val_loss -0.7534 +2024-11-21 18:48:41.525031: Pseudo dice [0.8376] +2024-11-21 18:48:41.525120: Epoch time: 18.65 s +2024-11-21 18:48:42.365250: +2024-11-21 18:48:42.365485: Epoch 1516 +2024-11-21 18:48:42.365596: Current learning rate: 0.00828 +2024-11-21 18:49:01.340425: train_loss -0.7701 +2024-11-21 18:49:01.340628: val_loss -0.7573 +2024-11-21 18:49:01.340703: Pseudo dice [0.8259] +2024-11-21 18:49:01.340777: Epoch time: 18.98 s +2024-11-21 18:49:02.176144: +2024-11-21 18:49:02.176385: Epoch 1517 +2024-11-21 18:49:02.176495: Current learning rate: 0.00828 +2024-11-21 18:49:21.113803: train_loss -0.764 +2024-11-21 18:49:21.114026: val_loss -0.7365 +2024-11-21 18:49:21.114103: Pseudo dice [0.8008] +2024-11-21 18:49:21.114179: Epoch time: 18.94 s +2024-11-21 18:49:21.950723: +2024-11-21 18:49:21.950925: Epoch 1518 +2024-11-21 18:49:21.951037: Current learning rate: 0.00827 +2024-11-21 18:49:40.657752: train_loss -0.7691 +2024-11-21 18:49:40.657958: val_loss -0.7658 +2024-11-21 18:49:40.658068: Pseudo dice [0.847] +2024-11-21 18:49:40.658142: Epoch time: 18.71 s +2024-11-21 18:49:41.498792: +2024-11-21 18:49:41.499021: Epoch 1519 +2024-11-21 18:49:41.499129: Current learning rate: 0.00827 +2024-11-21 18:50:01.710389: train_loss -0.7645 +2024-11-21 18:50:01.710621: val_loss -0.7439 +2024-11-21 18:50:01.710699: Pseudo dice [0.8116] +2024-11-21 18:50:01.710865: Epoch time: 20.21 s +2024-11-21 18:50:02.556712: +2024-11-21 18:50:02.556928: Epoch 1520 +2024-11-21 18:50:02.557056: Current learning rate: 0.00827 +2024-11-21 18:50:21.264035: train_loss -0.7646 +2024-11-21 18:50:21.264236: val_loss -0.7525 +2024-11-21 18:50:21.264313: Pseudo dice [0.8276] +2024-11-21 18:50:21.264388: Epoch time: 18.71 s +2024-11-21 18:50:22.102804: +2024-11-21 18:50:22.103019: Epoch 1521 +2024-11-21 18:50:22.103135: Current learning rate: 0.00827 +2024-11-21 18:50:40.893503: train_loss -0.7744 +2024-11-21 18:50:40.894323: val_loss -0.7537 +2024-11-21 18:50:40.894401: Pseudo dice [0.8241] +2024-11-21 18:50:40.894475: Epoch time: 18.79 s +2024-11-21 18:50:41.727693: +2024-11-21 18:50:41.727902: Epoch 1522 +2024-11-21 18:50:41.728020: Current learning rate: 0.00827 +2024-11-21 18:50:59.902076: train_loss -0.7694 +2024-11-21 18:50:59.902290: val_loss -0.7725 +2024-11-21 18:50:59.902366: Pseudo dice [0.8393] +2024-11-21 18:50:59.902439: Epoch time: 18.18 s +2024-11-21 18:51:00.744146: +2024-11-21 18:51:00.744496: Epoch 1523 +2024-11-21 18:51:00.744605: Current learning rate: 0.00827 +2024-11-21 18:51:18.966832: train_loss -0.7777 +2024-11-21 18:51:18.967108: val_loss -0.7486 +2024-11-21 18:51:18.967211: Pseudo dice [0.8354] +2024-11-21 18:51:18.967290: Epoch time: 18.22 s +2024-11-21 18:51:20.235444: +2024-11-21 18:51:20.235743: Epoch 1524 +2024-11-21 18:51:20.235859: Current learning rate: 0.00827 +2024-11-21 18:51:38.688668: train_loss -0.7741 +2024-11-21 18:51:38.688890: val_loss -0.7597 +2024-11-21 18:51:38.688965: Pseudo dice [0.8302] +2024-11-21 18:51:38.689048: Epoch time: 18.45 s +2024-11-21 18:51:39.529953: +2024-11-21 18:51:39.530194: Epoch 1525 +2024-11-21 18:51:39.530301: Current learning rate: 0.00827 +2024-11-21 18:51:57.778579: train_loss -0.7764 +2024-11-21 18:51:57.778868: val_loss -0.7532 +2024-11-21 18:51:57.778948: Pseudo dice [0.8459] +2024-11-21 18:51:57.779040: Epoch time: 18.25 s +2024-11-21 18:51:58.659689: +2024-11-21 18:51:58.659935: Epoch 1526 +2024-11-21 18:51:58.660050: Current learning rate: 0.00827 +2024-11-21 18:52:16.370226: train_loss -0.7704 +2024-11-21 18:52:16.370465: val_loss -0.7751 +2024-11-21 18:52:16.370540: Pseudo dice [0.8325] +2024-11-21 18:52:16.370619: Epoch time: 17.71 s +2024-11-21 18:52:17.215435: +2024-11-21 18:52:17.215662: Epoch 1527 +2024-11-21 18:52:17.215776: Current learning rate: 0.00826 +2024-11-21 18:52:35.761905: train_loss -0.7657 +2024-11-21 18:52:35.762193: val_loss -0.7593 +2024-11-21 18:52:35.762271: Pseudo dice [0.8446] +2024-11-21 18:52:35.762344: Epoch time: 18.55 s +2024-11-21 18:52:36.656714: +2024-11-21 18:52:36.657016: Epoch 1528 +2024-11-21 18:52:36.657130: Current learning rate: 0.00826 +2024-11-21 18:52:54.711309: train_loss -0.762 +2024-11-21 18:52:54.711517: val_loss -0.7755 +2024-11-21 18:52:54.711589: Pseudo dice [0.8376] +2024-11-21 18:52:54.711662: Epoch time: 18.06 s +2024-11-21 18:52:55.554697: +2024-11-21 18:52:55.554927: Epoch 1529 +2024-11-21 18:52:55.555054: Current learning rate: 0.00826 +2024-11-21 18:53:13.340743: train_loss -0.7634 +2024-11-21 18:53:13.340983: val_loss -0.7632 +2024-11-21 18:53:13.341072: Pseudo dice [0.83] +2024-11-21 18:53:13.341154: Epoch time: 17.79 s +2024-11-21 18:53:14.323724: +2024-11-21 18:53:14.323943: Epoch 1530 +2024-11-21 18:53:14.324058: Current learning rate: 0.00826 +2024-11-21 18:53:33.060572: train_loss -0.7606 +2024-11-21 18:53:33.060780: val_loss -0.7601 +2024-11-21 18:53:33.060853: Pseudo dice [0.8199] +2024-11-21 18:53:33.060934: Epoch time: 18.74 s +2024-11-21 18:53:33.902033: +2024-11-21 18:53:33.902295: Epoch 1531 +2024-11-21 18:53:33.902411: Current learning rate: 0.00826 +2024-11-21 18:53:51.658391: train_loss -0.7752 +2024-11-21 18:53:51.658602: val_loss -0.7376 +2024-11-21 18:53:51.658679: Pseudo dice [0.8337] +2024-11-21 18:53:51.658752: Epoch time: 17.76 s +2024-11-21 18:53:52.498614: +2024-11-21 18:53:52.498833: Epoch 1532 +2024-11-21 18:53:52.498946: Current learning rate: 0.00826 +2024-11-21 18:54:09.988477: train_loss -0.776 +2024-11-21 18:54:09.993913: val_loss -0.7657 +2024-11-21 18:54:09.994010: Pseudo dice [0.8434] +2024-11-21 18:54:09.994093: Epoch time: 17.49 s +2024-11-21 18:54:10.926485: +2024-11-21 18:54:10.926728: Epoch 1533 +2024-11-21 18:54:10.926839: Current learning rate: 0.00826 +2024-11-21 18:54:29.213037: train_loss -0.7621 +2024-11-21 18:54:29.213266: val_loss -0.7731 +2024-11-21 18:54:29.213337: Pseudo dice [0.8362] +2024-11-21 18:54:29.213415: Epoch time: 18.29 s +2024-11-21 18:54:30.057543: +2024-11-21 18:54:30.057758: Epoch 1534 +2024-11-21 18:54:30.057865: Current learning rate: 0.00826 +2024-11-21 18:54:49.805806: train_loss -0.7712 +2024-11-21 18:54:49.806090: val_loss -0.7466 +2024-11-21 18:54:49.806170: Pseudo dice [0.8346] +2024-11-21 18:54:49.806248: Epoch time: 19.75 s +2024-11-21 18:54:51.038365: +2024-11-21 18:54:51.038600: Epoch 1535 +2024-11-21 18:54:51.038705: Current learning rate: 0.00826 +2024-11-21 18:55:09.460800: train_loss -0.7666 +2024-11-21 18:55:09.461126: val_loss -0.7563 +2024-11-21 18:55:09.461204: Pseudo dice [0.8343] +2024-11-21 18:55:09.461280: Epoch time: 18.42 s +2024-11-21 18:55:10.305251: +2024-11-21 18:55:10.305485: Epoch 1536 +2024-11-21 18:55:10.305592: Current learning rate: 0.00825 +2024-11-21 18:55:28.432205: train_loss -0.7661 +2024-11-21 18:55:28.432444: val_loss -0.7696 +2024-11-21 18:55:28.432520: Pseudo dice [0.8343] +2024-11-21 18:55:28.432602: Epoch time: 18.13 s +2024-11-21 18:55:29.288547: +2024-11-21 18:55:29.288783: Epoch 1537 +2024-11-21 18:55:29.288894: Current learning rate: 0.00825 +2024-11-21 18:55:47.212948: train_loss -0.7691 +2024-11-21 18:55:47.213163: val_loss -0.7692 +2024-11-21 18:55:47.213237: Pseudo dice [0.853] +2024-11-21 18:55:47.213312: Epoch time: 17.93 s +2024-11-21 18:55:48.055020: +2024-11-21 18:55:48.055243: Epoch 1538 +2024-11-21 18:55:48.055350: Current learning rate: 0.00825 +2024-11-21 18:56:06.222804: train_loss -0.7632 +2024-11-21 18:56:06.223020: val_loss -0.7452 +2024-11-21 18:56:06.223098: Pseudo dice [0.8378] +2024-11-21 18:56:06.223171: Epoch time: 18.17 s +2024-11-21 18:56:07.062034: +2024-11-21 18:56:07.062239: Epoch 1539 +2024-11-21 18:56:07.062347: Current learning rate: 0.00825 +2024-11-21 18:56:25.414494: train_loss -0.774 +2024-11-21 18:56:25.414697: val_loss -0.7609 +2024-11-21 18:56:25.414769: Pseudo dice [0.837] +2024-11-21 18:56:25.414841: Epoch time: 18.35 s +2024-11-21 18:56:26.260644: +2024-11-21 18:56:26.260884: Epoch 1540 +2024-11-21 18:56:26.261011: Current learning rate: 0.00825 +2024-11-21 18:56:44.919772: train_loss -0.7761 +2024-11-21 18:56:44.920016: val_loss -0.7302 +2024-11-21 18:56:44.920091: Pseudo dice [0.8395] +2024-11-21 18:56:44.920171: Epoch time: 18.66 s +2024-11-21 18:56:45.765634: +2024-11-21 18:56:45.765861: Epoch 1541 +2024-11-21 18:56:45.765972: Current learning rate: 0.00825 +2024-11-21 18:57:04.205389: train_loss -0.7596 +2024-11-21 18:57:04.205860: val_loss -0.7657 +2024-11-21 18:57:04.205948: Pseudo dice [0.8471] +2024-11-21 18:57:04.206030: Epoch time: 18.44 s +2024-11-21 18:57:05.045856: +2024-11-21 18:57:05.046082: Epoch 1542 +2024-11-21 18:57:05.046196: Current learning rate: 0.00825 +2024-11-21 18:57:23.551061: train_loss -0.7609 +2024-11-21 18:57:23.551296: val_loss -0.7618 +2024-11-21 18:57:23.551370: Pseudo dice [0.8375] +2024-11-21 18:57:23.551444: Epoch time: 18.51 s +2024-11-21 18:57:24.394451: +2024-11-21 18:57:24.394669: Epoch 1543 +2024-11-21 18:57:24.394779: Current learning rate: 0.00825 +2024-11-21 18:57:42.413870: train_loss -0.7622 +2024-11-21 18:57:42.414096: val_loss -0.7812 +2024-11-21 18:57:42.414175: Pseudo dice [0.8555] +2024-11-21 18:57:42.414255: Epoch time: 18.02 s +2024-11-21 18:57:43.287782: +2024-11-21 18:57:43.288029: Epoch 1544 +2024-11-21 18:57:43.288144: Current learning rate: 0.00824 +2024-11-21 18:58:01.090470: train_loss -0.7677 +2024-11-21 18:58:01.090707: val_loss -0.7685 +2024-11-21 18:58:01.090781: Pseudo dice [0.8523] +2024-11-21 18:58:01.090865: Epoch time: 17.8 s +2024-11-21 18:58:01.934491: +2024-11-21 18:58:01.934810: Epoch 1545 +2024-11-21 18:58:01.934927: Current learning rate: 0.00824 +2024-11-21 18:58:20.943248: train_loss -0.7678 +2024-11-21 18:58:20.943463: val_loss -0.7501 +2024-11-21 18:58:20.943535: Pseudo dice [0.8172] +2024-11-21 18:58:20.943610: Epoch time: 19.01 s +2024-11-21 18:58:22.189105: +2024-11-21 18:58:22.189338: Epoch 1546 +2024-11-21 18:58:22.189461: Current learning rate: 0.00824 +2024-11-21 18:58:40.720295: train_loss -0.7586 +2024-11-21 18:58:40.720514: val_loss -0.7612 +2024-11-21 18:58:40.720588: Pseudo dice [0.8491] +2024-11-21 18:58:40.720662: Epoch time: 18.53 s +2024-11-21 18:58:41.566182: +2024-11-21 18:58:41.566421: Epoch 1547 +2024-11-21 18:58:41.566539: Current learning rate: 0.00824 +2024-11-21 18:58:59.517457: train_loss -0.7629 +2024-11-21 18:58:59.517701: val_loss -0.7238 +2024-11-21 18:58:59.517775: Pseudo dice [0.8031] +2024-11-21 18:58:59.517906: Epoch time: 17.95 s +2024-11-21 18:59:00.365220: +2024-11-21 18:59:00.365466: Epoch 1548 +2024-11-21 18:59:00.365587: Current learning rate: 0.00824 +2024-11-21 18:59:18.362781: train_loss -0.7666 +2024-11-21 18:59:18.363001: val_loss -0.7256 +2024-11-21 18:59:18.363075: Pseudo dice [0.8249] +2024-11-21 18:59:18.363146: Epoch time: 18.0 s +2024-11-21 18:59:19.341095: +2024-11-21 18:59:19.341335: Epoch 1549 +2024-11-21 18:59:19.341456: Current learning rate: 0.00824 +2024-11-21 18:59:39.187167: train_loss -0.7589 +2024-11-21 18:59:39.187376: val_loss -0.7327 +2024-11-21 18:59:39.187451: Pseudo dice [0.8305] +2024-11-21 18:59:39.187522: Epoch time: 19.85 s +2024-11-21 18:59:40.220670: +2024-11-21 18:59:40.220891: Epoch 1550 +2024-11-21 18:59:40.221013: Current learning rate: 0.00824 +2024-11-21 18:59:59.142491: train_loss -0.7618 +2024-11-21 18:59:59.142716: val_loss -0.7589 +2024-11-21 18:59:59.142791: Pseudo dice [0.8377] +2024-11-21 18:59:59.142867: Epoch time: 18.92 s +2024-11-21 19:00:00.010085: +2024-11-21 19:00:00.010298: Epoch 1551 +2024-11-21 19:00:00.010418: Current learning rate: 0.00824 +2024-11-21 19:00:17.745693: train_loss -0.7606 +2024-11-21 19:00:17.745944: val_loss -0.7614 +2024-11-21 19:00:17.746025: Pseudo dice [0.8546] +2024-11-21 19:00:17.746105: Epoch time: 17.74 s +2024-11-21 19:00:18.589016: +2024-11-21 19:00:18.589224: Epoch 1552 +2024-11-21 19:00:18.589333: Current learning rate: 0.00824 +2024-11-21 19:00:36.260945: train_loss -0.7661 +2024-11-21 19:00:36.261161: val_loss -0.7611 +2024-11-21 19:00:36.261233: Pseudo dice [0.8215] +2024-11-21 19:00:36.261307: Epoch time: 17.67 s +2024-11-21 19:00:37.091640: +2024-11-21 19:00:37.091852: Epoch 1553 +2024-11-21 19:00:37.091965: Current learning rate: 0.00823 +2024-11-21 19:00:55.900569: train_loss -0.7621 +2024-11-21 19:00:55.900801: val_loss -0.7333 +2024-11-21 19:00:55.900892: Pseudo dice [0.8427] +2024-11-21 19:00:55.900984: Epoch time: 18.81 s +2024-11-21 19:00:56.748295: +2024-11-21 19:00:56.748513: Epoch 1554 +2024-11-21 19:00:56.748628: Current learning rate: 0.00823 +2024-11-21 19:01:15.461442: train_loss -0.7633 +2024-11-21 19:01:15.461724: val_loss -0.756 +2024-11-21 19:01:15.461799: Pseudo dice [0.825] +2024-11-21 19:01:15.461898: Epoch time: 18.71 s +2024-11-21 19:01:16.315043: +2024-11-21 19:01:16.315273: Epoch 1555 +2024-11-21 19:01:16.315393: Current learning rate: 0.00823 +2024-11-21 19:01:35.388298: train_loss -0.762 +2024-11-21 19:01:35.388508: val_loss -0.7576 +2024-11-21 19:01:35.388585: Pseudo dice [0.8279] +2024-11-21 19:01:35.388659: Epoch time: 19.07 s +2024-11-21 19:01:36.256584: +2024-11-21 19:01:36.256773: Epoch 1556 +2024-11-21 19:01:36.256875: Current learning rate: 0.00823 +2024-11-21 19:01:55.294783: train_loss -0.7601 +2024-11-21 19:01:55.295004: val_loss -0.7709 +2024-11-21 19:01:55.295082: Pseudo dice [0.8485] +2024-11-21 19:01:55.295160: Epoch time: 19.04 s +2024-11-21 19:01:56.526546: +2024-11-21 19:01:56.526763: Epoch 1557 +2024-11-21 19:01:56.526871: Current learning rate: 0.00823 +2024-11-21 19:02:15.802857: train_loss -0.7637 +2024-11-21 19:02:15.803100: val_loss -0.7368 +2024-11-21 19:02:15.803183: Pseudo dice [0.8394] +2024-11-21 19:02:15.803261: Epoch time: 19.28 s +2024-11-21 19:02:16.653400: +2024-11-21 19:02:16.653628: Epoch 1558 +2024-11-21 19:02:16.653744: Current learning rate: 0.00823 +2024-11-21 19:02:35.695113: train_loss -0.777 +2024-11-21 19:02:35.695353: val_loss -0.7434 +2024-11-21 19:02:35.695440: Pseudo dice [0.8511] +2024-11-21 19:02:35.695518: Epoch time: 19.04 s +2024-11-21 19:02:36.534081: +2024-11-21 19:02:36.534316: Epoch 1559 +2024-11-21 19:02:36.534423: Current learning rate: 0.00823 +2024-11-21 19:02:54.558655: train_loss -0.7782 +2024-11-21 19:02:54.558870: val_loss -0.741 +2024-11-21 19:02:54.558944: Pseudo dice [0.832] +2024-11-21 19:02:54.559027: Epoch time: 18.03 s +2024-11-21 19:02:55.402772: +2024-11-21 19:02:55.403001: Epoch 1560 +2024-11-21 19:02:55.403106: Current learning rate: 0.00823 +2024-11-21 19:03:13.544783: train_loss -0.7681 +2024-11-21 19:03:13.545006: val_loss -0.7533 +2024-11-21 19:03:13.545080: Pseudo dice [0.8211] +2024-11-21 19:03:13.545155: Epoch time: 18.14 s +2024-11-21 19:03:14.391288: +2024-11-21 19:03:14.391534: Epoch 1561 +2024-11-21 19:03:14.391651: Current learning rate: 0.00823 +2024-11-21 19:03:31.737110: train_loss -0.7704 +2024-11-21 19:03:31.737340: val_loss -0.7085 +2024-11-21 19:03:31.737413: Pseudo dice [0.7721] +2024-11-21 19:03:31.737496: Epoch time: 17.35 s +2024-11-21 19:03:32.623523: +2024-11-21 19:03:32.623740: Epoch 1562 +2024-11-21 19:03:32.623846: Current learning rate: 0.00822 +2024-11-21 19:03:50.839592: train_loss -0.7418 +2024-11-21 19:03:50.839875: val_loss -0.7545 +2024-11-21 19:03:50.839956: Pseudo dice [0.824] +2024-11-21 19:03:50.840038: Epoch time: 18.22 s +2024-11-21 19:03:51.685695: +2024-11-21 19:03:51.686100: Epoch 1563 +2024-11-21 19:03:51.686237: Current learning rate: 0.00822 +2024-11-21 19:04:09.474071: train_loss -0.7427 +2024-11-21 19:04:09.474286: val_loss -0.7543 +2024-11-21 19:04:09.474359: Pseudo dice [0.828] +2024-11-21 19:04:09.474433: Epoch time: 17.79 s +2024-11-21 19:04:10.347288: +2024-11-21 19:04:10.347508: Epoch 1564 +2024-11-21 19:04:10.347622: Current learning rate: 0.00822 +2024-11-21 19:04:28.054843: train_loss -0.734 +2024-11-21 19:04:28.055073: val_loss -0.7242 +2024-11-21 19:04:28.055151: Pseudo dice [0.8221] +2024-11-21 19:04:28.055230: Epoch time: 17.71 s +2024-11-21 19:04:28.899759: +2024-11-21 19:04:28.899965: Epoch 1565 +2024-11-21 19:04:28.900078: Current learning rate: 0.00822 +2024-11-21 19:04:47.382302: train_loss -0.7476 +2024-11-21 19:04:47.382549: val_loss -0.7694 +2024-11-21 19:04:47.382624: Pseudo dice [0.8344] +2024-11-21 19:04:47.382701: Epoch time: 18.48 s +2024-11-21 19:04:48.221747: +2024-11-21 19:04:48.222011: Epoch 1566 +2024-11-21 19:04:48.222122: Current learning rate: 0.00822 +2024-11-21 19:05:05.354295: train_loss -0.7476 +2024-11-21 19:05:05.354583: val_loss -0.7477 +2024-11-21 19:05:05.354673: Pseudo dice [0.8365] +2024-11-21 19:05:05.354754: Epoch time: 17.13 s +2024-11-21 19:05:06.201552: +2024-11-21 19:05:06.201788: Epoch 1567 +2024-11-21 19:05:06.201904: Current learning rate: 0.00822 +2024-11-21 19:05:25.360225: train_loss -0.749 +2024-11-21 19:05:25.360454: val_loss -0.7461 +2024-11-21 19:05:25.360539: Pseudo dice [0.8266] +2024-11-21 19:05:25.360615: Epoch time: 19.16 s +2024-11-21 19:05:26.511312: +2024-11-21 19:05:26.511548: Epoch 1568 +2024-11-21 19:05:26.511661: Current learning rate: 0.00822 +2024-11-21 19:05:44.584352: train_loss -0.7615 +2024-11-21 19:05:44.584653: val_loss -0.7387 +2024-11-21 19:05:44.584729: Pseudo dice [0.8159] +2024-11-21 19:05:44.584813: Epoch time: 18.07 s +2024-11-21 19:05:45.438519: +2024-11-21 19:05:45.438768: Epoch 1569 +2024-11-21 19:05:45.438881: Current learning rate: 0.00822 +2024-11-21 19:06:03.957842: train_loss -0.7281 +2024-11-21 19:06:03.958059: val_loss -0.7299 +2024-11-21 19:06:03.958133: Pseudo dice [0.8177] +2024-11-21 19:06:03.958207: Epoch time: 18.52 s +2024-11-21 19:06:04.801412: +2024-11-21 19:06:04.801633: Epoch 1570 +2024-11-21 19:06:04.801739: Current learning rate: 0.00822 +2024-11-21 19:06:23.051138: train_loss -0.7283 +2024-11-21 19:06:23.051363: val_loss -0.7449 +2024-11-21 19:06:23.051438: Pseudo dice [0.8302] +2024-11-21 19:06:23.051512: Epoch time: 18.25 s +2024-11-21 19:06:23.898682: +2024-11-21 19:06:23.898959: Epoch 1571 +2024-11-21 19:06:23.899073: Current learning rate: 0.00821 +2024-11-21 19:06:42.390716: train_loss -0.7527 +2024-11-21 19:06:42.390945: val_loss -0.7523 +2024-11-21 19:06:42.391029: Pseudo dice [0.8308] +2024-11-21 19:06:42.391106: Epoch time: 18.49 s +2024-11-21 19:06:43.237425: +2024-11-21 19:06:43.237649: Epoch 1572 +2024-11-21 19:06:43.237761: Current learning rate: 0.00821 +2024-11-21 19:07:01.686949: train_loss -0.7584 +2024-11-21 19:07:01.687183: val_loss -0.7716 +2024-11-21 19:07:01.687256: Pseudo dice [0.8427] +2024-11-21 19:07:01.687331: Epoch time: 18.45 s +2024-11-21 19:07:02.526354: +2024-11-21 19:07:02.526580: Epoch 1573 +2024-11-21 19:07:02.526696: Current learning rate: 0.00821 +2024-11-21 19:07:19.768279: train_loss -0.7667 +2024-11-21 19:07:19.768491: val_loss -0.7531 +2024-11-21 19:07:19.768567: Pseudo dice [0.8374] +2024-11-21 19:07:19.768671: Epoch time: 17.24 s +2024-11-21 19:07:20.605978: +2024-11-21 19:07:20.606215: Epoch 1574 +2024-11-21 19:07:20.606326: Current learning rate: 0.00821 +2024-11-21 19:07:39.371916: train_loss -0.762 +2024-11-21 19:07:39.372166: val_loss -0.7607 +2024-11-21 19:07:39.372246: Pseudo dice [0.8358] +2024-11-21 19:07:39.372321: Epoch time: 18.77 s +2024-11-21 19:07:40.221241: +2024-11-21 19:07:40.221437: Epoch 1575 +2024-11-21 19:07:40.221552: Current learning rate: 0.00821 +2024-11-21 19:07:58.819291: train_loss -0.76 +2024-11-21 19:07:58.819548: val_loss -0.7745 +2024-11-21 19:07:58.819624: Pseudo dice [0.8331] +2024-11-21 19:07:58.819708: Epoch time: 18.6 s +2024-11-21 19:07:59.746099: +2024-11-21 19:07:59.746291: Epoch 1576 +2024-11-21 19:07:59.746402: Current learning rate: 0.00821 +2024-11-21 19:08:17.274168: train_loss -0.7679 +2024-11-21 19:08:17.274375: val_loss -0.7304 +2024-11-21 19:08:17.274449: Pseudo dice [0.8286] +2024-11-21 19:08:17.274528: Epoch time: 17.53 s +2024-11-21 19:08:18.117954: +2024-11-21 19:08:18.118185: Epoch 1577 +2024-11-21 19:08:18.118307: Current learning rate: 0.00821 +2024-11-21 19:08:36.431950: train_loss -0.7555 +2024-11-21 19:08:36.432211: val_loss -0.7359 +2024-11-21 19:08:36.432295: Pseudo dice [0.8315] +2024-11-21 19:08:36.432381: Epoch time: 18.31 s +2024-11-21 19:08:37.449052: +2024-11-21 19:08:37.449274: Epoch 1578 +2024-11-21 19:08:37.449380: Current learning rate: 0.00821 +2024-11-21 19:08:55.969500: train_loss -0.767 +2024-11-21 19:08:55.969791: val_loss -0.7709 +2024-11-21 19:08:55.969870: Pseudo dice [0.8341] +2024-11-21 19:08:55.969955: Epoch time: 18.52 s +2024-11-21 19:08:57.205872: +2024-11-21 19:08:57.206112: Epoch 1579 +2024-11-21 19:08:57.206222: Current learning rate: 0.0082 +2024-11-21 19:09:15.124275: train_loss -0.7759 +2024-11-21 19:09:15.124496: val_loss -0.7704 +2024-11-21 19:09:15.124573: Pseudo dice [0.8417] +2024-11-21 19:09:15.124647: Epoch time: 17.92 s +2024-11-21 19:09:15.965829: +2024-11-21 19:09:15.966072: Epoch 1580 +2024-11-21 19:09:15.966189: Current learning rate: 0.0082 +2024-11-21 19:09:34.488238: train_loss -0.77 +2024-11-21 19:09:34.488458: val_loss -0.7345 +2024-11-21 19:09:34.488534: Pseudo dice [0.8447] +2024-11-21 19:09:34.488609: Epoch time: 18.52 s +2024-11-21 19:09:35.331573: +2024-11-21 19:09:35.331805: Epoch 1581 +2024-11-21 19:09:35.331913: Current learning rate: 0.0082 +2024-11-21 19:09:52.751104: train_loss -0.7714 +2024-11-21 19:09:52.751345: val_loss -0.7602 +2024-11-21 19:09:52.751421: Pseudo dice [0.8399] +2024-11-21 19:09:52.751504: Epoch time: 17.42 s +2024-11-21 19:09:53.600630: +2024-11-21 19:09:53.600855: Epoch 1582 +2024-11-21 19:09:53.600963: Current learning rate: 0.0082 +2024-11-21 19:10:12.513896: train_loss -0.758 +2024-11-21 19:10:12.514112: val_loss -0.7826 +2024-11-21 19:10:12.514199: Pseudo dice [0.8484] +2024-11-21 19:10:12.514274: Epoch time: 18.91 s +2024-11-21 19:10:13.353899: +2024-11-21 19:10:13.354147: Epoch 1583 +2024-11-21 19:10:13.354259: Current learning rate: 0.0082 +2024-11-21 19:10:31.481290: train_loss -0.7718 +2024-11-21 19:10:31.481577: val_loss -0.7748 +2024-11-21 19:10:31.481652: Pseudo dice [0.849] +2024-11-21 19:10:31.481726: Epoch time: 18.13 s +2024-11-21 19:10:32.334142: +2024-11-21 19:10:32.334361: Epoch 1584 +2024-11-21 19:10:32.334469: Current learning rate: 0.0082 +2024-11-21 19:10:49.997273: train_loss -0.777 +2024-11-21 19:10:49.997470: val_loss -0.7519 +2024-11-21 19:10:49.997543: Pseudo dice [0.8446] +2024-11-21 19:10:49.997613: Epoch time: 17.66 s +2024-11-21 19:10:50.842403: +2024-11-21 19:10:50.842615: Epoch 1585 +2024-11-21 19:10:50.842723: Current learning rate: 0.0082 +2024-11-21 19:11:08.148397: train_loss -0.7784 +2024-11-21 19:11:08.148670: val_loss -0.766 +2024-11-21 19:11:08.148746: Pseudo dice [0.8458] +2024-11-21 19:11:08.148829: Epoch time: 17.31 s +2024-11-21 19:11:08.997105: +2024-11-21 19:11:08.997333: Epoch 1586 +2024-11-21 19:11:08.997456: Current learning rate: 0.0082 +2024-11-21 19:11:27.567646: train_loss -0.772 +2024-11-21 19:11:27.567852: val_loss -0.7862 +2024-11-21 19:11:27.567924: Pseudo dice [0.8415] +2024-11-21 19:11:27.568010: Epoch time: 18.57 s +2024-11-21 19:11:28.408470: +2024-11-21 19:11:28.408689: Epoch 1587 +2024-11-21 19:11:28.408804: Current learning rate: 0.0082 +2024-11-21 19:11:45.900177: train_loss -0.7728 +2024-11-21 19:11:45.900393: val_loss -0.7443 +2024-11-21 19:11:45.900466: Pseudo dice [0.841] +2024-11-21 19:11:45.900542: Epoch time: 17.49 s +2024-11-21 19:11:46.763149: +2024-11-21 19:11:46.763362: Epoch 1588 +2024-11-21 19:11:46.763474: Current learning rate: 0.00819 +2024-11-21 19:12:04.680654: train_loss -0.7666 +2024-11-21 19:12:04.680868: val_loss -0.7576 +2024-11-21 19:12:04.680946: Pseudo dice [0.8439] +2024-11-21 19:12:04.681083: Epoch time: 17.92 s +2024-11-21 19:12:05.529930: +2024-11-21 19:12:05.530166: Epoch 1589 +2024-11-21 19:12:05.530277: Current learning rate: 0.00819 +2024-11-21 19:12:23.214496: train_loss -0.7622 +2024-11-21 19:12:23.214706: val_loss -0.7526 +2024-11-21 19:12:23.214783: Pseudo dice [0.8424] +2024-11-21 19:12:23.214860: Epoch time: 17.69 s +2024-11-21 19:12:24.424173: +2024-11-21 19:12:24.424371: Epoch 1590 +2024-11-21 19:12:24.424478: Current learning rate: 0.00819 +2024-11-21 19:12:43.142572: train_loss -0.7597 +2024-11-21 19:12:43.147963: val_loss -0.7414 +2024-11-21 19:12:43.148078: Pseudo dice [0.8399] +2024-11-21 19:12:43.148159: Epoch time: 18.72 s +2024-11-21 19:12:44.025427: +2024-11-21 19:12:44.025666: Epoch 1591 +2024-11-21 19:12:44.025769: Current learning rate: 0.00819 +2024-11-21 19:13:02.432500: train_loss -0.7559 +2024-11-21 19:13:02.432734: val_loss -0.7641 +2024-11-21 19:13:02.432811: Pseudo dice [0.8412] +2024-11-21 19:13:02.432940: Epoch time: 18.41 s +2024-11-21 19:13:03.378402: +2024-11-21 19:13:03.378631: Epoch 1592 +2024-11-21 19:13:03.378737: Current learning rate: 0.00819 +2024-11-21 19:13:22.597503: train_loss -0.7719 +2024-11-21 19:13:22.597737: val_loss -0.755 +2024-11-21 19:13:22.597810: Pseudo dice [0.8376] +2024-11-21 19:13:22.597887: Epoch time: 19.22 s +2024-11-21 19:13:23.445973: +2024-11-21 19:13:23.446253: Epoch 1593 +2024-11-21 19:13:23.446362: Current learning rate: 0.00819 +2024-11-21 19:13:42.130538: train_loss -0.7756 +2024-11-21 19:13:42.130805: val_loss -0.7508 +2024-11-21 19:13:42.130902: Pseudo dice [0.832] +2024-11-21 19:13:42.130978: Epoch time: 18.69 s +2024-11-21 19:13:42.981746: +2024-11-21 19:13:42.982013: Epoch 1594 +2024-11-21 19:13:42.982138: Current learning rate: 0.00819 +2024-11-21 19:14:01.318556: train_loss -0.7663 +2024-11-21 19:14:01.318782: val_loss -0.7424 +2024-11-21 19:14:01.318861: Pseudo dice [0.8483] +2024-11-21 19:14:01.318938: Epoch time: 18.34 s +2024-11-21 19:14:02.165119: +2024-11-21 19:14:02.165344: Epoch 1595 +2024-11-21 19:14:02.165454: Current learning rate: 0.00819 +2024-11-21 19:14:20.434957: train_loss -0.7659 +2024-11-21 19:14:20.435208: val_loss -0.7736 +2024-11-21 19:14:20.435282: Pseudo dice [0.8265] +2024-11-21 19:14:20.435363: Epoch time: 18.27 s +2024-11-21 19:14:21.282660: +2024-11-21 19:14:21.282877: Epoch 1596 +2024-11-21 19:14:21.282985: Current learning rate: 0.00819 +2024-11-21 19:14:39.625398: train_loss -0.7695 +2024-11-21 19:14:39.628066: val_loss -0.7502 +2024-11-21 19:14:39.628163: Pseudo dice [0.8425] +2024-11-21 19:14:39.628251: Epoch time: 18.34 s +2024-11-21 19:14:40.545830: +2024-11-21 19:14:40.546045: Epoch 1597 +2024-11-21 19:14:40.546160: Current learning rate: 0.00818 +2024-11-21 19:14:58.689672: train_loss -0.7623 +2024-11-21 19:14:58.689889: val_loss -0.7544 +2024-11-21 19:14:58.689989: Pseudo dice [0.8324] +2024-11-21 19:14:58.690082: Epoch time: 18.14 s +2024-11-21 19:14:59.556310: +2024-11-21 19:14:59.556658: Epoch 1598 +2024-11-21 19:14:59.556774: Current learning rate: 0.00818 +2024-11-21 19:15:17.877017: train_loss -0.7745 +2024-11-21 19:15:17.877250: val_loss -0.7527 +2024-11-21 19:15:17.877330: Pseudo dice [0.8165] +2024-11-21 19:15:17.877412: Epoch time: 18.32 s +2024-11-21 19:15:18.721208: +2024-11-21 19:15:18.721414: Epoch 1599 +2024-11-21 19:15:18.721523: Current learning rate: 0.00818 +2024-11-21 19:15:37.411730: train_loss -0.7751 +2024-11-21 19:15:37.411948: val_loss -0.7542 +2024-11-21 19:15:37.412028: Pseudo dice [0.8384] +2024-11-21 19:15:37.412104: Epoch time: 18.69 s +2024-11-21 19:15:38.443110: +2024-11-21 19:15:38.443305: Epoch 1600 +2024-11-21 19:15:38.443417: Current learning rate: 0.00818 +2024-11-21 19:15:56.535300: train_loss -0.7575 +2024-11-21 19:15:56.535513: val_loss -0.7457 +2024-11-21 19:15:56.535586: Pseudo dice [0.8294] +2024-11-21 19:15:56.535662: Epoch time: 18.09 s +2024-11-21 19:15:57.790369: +2024-11-21 19:15:57.790609: Epoch 1601 +2024-11-21 19:15:57.790722: Current learning rate: 0.00818 +2024-11-21 19:16:17.234634: train_loss -0.7692 +2024-11-21 19:16:17.234876: val_loss -0.7793 +2024-11-21 19:16:17.234957: Pseudo dice [0.8462] +2024-11-21 19:16:17.235049: Epoch time: 19.45 s +2024-11-21 19:16:18.211551: +2024-11-21 19:16:18.211833: Epoch 1602 +2024-11-21 19:16:18.211998: Current learning rate: 0.00818 +2024-11-21 19:16:36.774972: train_loss -0.7684 +2024-11-21 19:16:36.775216: val_loss -0.7674 +2024-11-21 19:16:36.775293: Pseudo dice [0.8576] +2024-11-21 19:16:36.775375: Epoch time: 18.56 s +2024-11-21 19:16:37.638085: +2024-11-21 19:16:37.638312: Epoch 1603 +2024-11-21 19:16:37.638422: Current learning rate: 0.00818 +2024-11-21 19:16:56.943237: train_loss -0.771 +2024-11-21 19:16:56.943453: val_loss -0.777 +2024-11-21 19:16:56.943530: Pseudo dice [0.8364] +2024-11-21 19:16:56.948787: Epoch time: 19.31 s +2024-11-21 19:16:57.793816: +2024-11-21 19:16:57.794041: Epoch 1604 +2024-11-21 19:16:57.794147: Current learning rate: 0.00818 +2024-11-21 19:17:16.568060: train_loss -0.7668 +2024-11-21 19:17:16.568273: val_loss -0.7519 +2024-11-21 19:17:16.568346: Pseudo dice [0.8173] +2024-11-21 19:17:16.568421: Epoch time: 18.78 s +2024-11-21 19:17:17.486259: +2024-11-21 19:17:17.486493: Epoch 1605 +2024-11-21 19:17:17.486609: Current learning rate: 0.00817 +2024-11-21 19:17:36.254485: train_loss -0.7627 +2024-11-21 19:17:36.259917: val_loss -0.7538 +2024-11-21 19:17:36.260007: Pseudo dice [0.8257] +2024-11-21 19:17:36.260097: Epoch time: 18.77 s +2024-11-21 19:17:37.207733: +2024-11-21 19:17:37.207984: Epoch 1606 +2024-11-21 19:17:37.208103: Current learning rate: 0.00817 +2024-11-21 19:17:55.553530: train_loss -0.7637 +2024-11-21 19:17:55.553752: val_loss -0.766 +2024-11-21 19:17:55.553827: Pseudo dice [0.8484] +2024-11-21 19:17:55.553906: Epoch time: 18.35 s +2024-11-21 19:17:56.403822: +2024-11-21 19:17:56.404032: Epoch 1607 +2024-11-21 19:17:56.404142: Current learning rate: 0.00817 +2024-11-21 19:18:14.573313: train_loss -0.7744 +2024-11-21 19:18:14.577068: val_loss -0.7764 +2024-11-21 19:18:14.577168: Pseudo dice [0.8373] +2024-11-21 19:18:14.577251: Epoch time: 18.17 s +2024-11-21 19:18:15.579776: +2024-11-21 19:18:15.580007: Epoch 1608 +2024-11-21 19:18:15.580126: Current learning rate: 0.00817 +2024-11-21 19:18:33.261729: train_loss -0.7609 +2024-11-21 19:18:33.261967: val_loss -0.7328 +2024-11-21 19:18:33.262057: Pseudo dice [0.8296] +2024-11-21 19:18:33.262141: Epoch time: 17.68 s +2024-11-21 19:18:34.208137: +2024-11-21 19:18:34.208354: Epoch 1609 +2024-11-21 19:18:34.208464: Current learning rate: 0.00817 +2024-11-21 19:18:53.675594: train_loss -0.7552 +2024-11-21 19:18:53.675838: val_loss -0.7511 +2024-11-21 19:18:53.675910: Pseudo dice [0.8387] +2024-11-21 19:18:53.675995: Epoch time: 19.47 s +2024-11-21 19:18:54.563257: +2024-11-21 19:18:54.563463: Epoch 1610 +2024-11-21 19:18:54.563580: Current learning rate: 0.00817 +2024-11-21 19:19:12.904397: train_loss -0.7514 +2024-11-21 19:19:12.904616: val_loss -0.7529 +2024-11-21 19:19:12.904691: Pseudo dice [0.8497] +2024-11-21 19:19:12.904769: Epoch time: 18.34 s +2024-11-21 19:19:13.750160: +2024-11-21 19:19:13.750386: Epoch 1611 +2024-11-21 19:19:13.750496: Current learning rate: 0.00817 +2024-11-21 19:19:32.688232: train_loss -0.751 +2024-11-21 19:19:32.689257: val_loss -0.7568 +2024-11-21 19:19:32.689331: Pseudo dice [0.8251] +2024-11-21 19:19:32.689405: Epoch time: 18.94 s +2024-11-21 19:19:33.912882: +2024-11-21 19:19:33.913121: Epoch 1612 +2024-11-21 19:19:33.913232: Current learning rate: 0.00817 +2024-11-21 19:19:53.275468: train_loss -0.7632 +2024-11-21 19:19:53.276064: val_loss -0.7685 +2024-11-21 19:19:53.276186: Pseudo dice [0.8399] +2024-11-21 19:19:53.276270: Epoch time: 19.36 s +2024-11-21 19:19:54.126726: +2024-11-21 19:19:54.127178: Epoch 1613 +2024-11-21 19:19:54.127308: Current learning rate: 0.00817 +2024-11-21 19:20:12.695876: train_loss -0.7689 +2024-11-21 19:20:12.696097: val_loss -0.7578 +2024-11-21 19:20:12.696176: Pseudo dice [0.841] +2024-11-21 19:20:12.696255: Epoch time: 18.57 s +2024-11-21 19:20:13.539226: +2024-11-21 19:20:13.539658: Epoch 1614 +2024-11-21 19:20:13.539790: Current learning rate: 0.00816 +2024-11-21 19:20:31.868910: train_loss -0.7639 +2024-11-21 19:20:31.869139: val_loss -0.7507 +2024-11-21 19:20:31.869236: Pseudo dice [0.8405] +2024-11-21 19:20:31.869314: Epoch time: 18.33 s +2024-11-21 19:20:32.822679: +2024-11-21 19:20:32.823128: Epoch 1615 +2024-11-21 19:20:32.823258: Current learning rate: 0.00816 +2024-11-21 19:20:50.255570: train_loss -0.7599 +2024-11-21 19:20:50.255827: val_loss -0.7578 +2024-11-21 19:20:50.255906: Pseudo dice [0.8567] +2024-11-21 19:20:50.255988: Epoch time: 17.43 s +2024-11-21 19:20:51.108359: +2024-11-21 19:20:51.108789: Epoch 1616 +2024-11-21 19:20:51.108914: Current learning rate: 0.00816 +2024-11-21 19:21:10.298025: train_loss -0.7667 +2024-11-21 19:21:10.298243: val_loss -0.7659 +2024-11-21 19:21:10.298317: Pseudo dice [0.8544] +2024-11-21 19:21:10.298392: Epoch time: 19.19 s +2024-11-21 19:21:11.197510: +2024-11-21 19:21:11.197954: Epoch 1617 +2024-11-21 19:21:11.198101: Current learning rate: 0.00816 +2024-11-21 19:21:30.554778: train_loss -0.7617 +2024-11-21 19:21:30.555009: val_loss -0.7605 +2024-11-21 19:21:30.555085: Pseudo dice [0.8444] +2024-11-21 19:21:30.555161: Epoch time: 19.36 s +2024-11-21 19:21:31.401304: +2024-11-21 19:21:31.401728: Epoch 1618 +2024-11-21 19:21:31.401877: Current learning rate: 0.00816 +2024-11-21 19:21:49.499282: train_loss -0.7765 +2024-11-21 19:21:49.499493: val_loss -0.7871 +2024-11-21 19:21:49.499578: Pseudo dice [0.8562] +2024-11-21 19:21:49.499657: Epoch time: 18.1 s +2024-11-21 19:21:50.341635: +2024-11-21 19:21:50.342070: Epoch 1619 +2024-11-21 19:21:50.342202: Current learning rate: 0.00816 +2024-11-21 19:22:09.250029: train_loss -0.7711 +2024-11-21 19:22:09.250276: val_loss -0.7626 +2024-11-21 19:22:09.250352: Pseudo dice [0.8366] +2024-11-21 19:22:09.250434: Epoch time: 18.91 s +2024-11-21 19:22:10.099160: +2024-11-21 19:22:10.099388: Epoch 1620 +2024-11-21 19:22:10.099523: Current learning rate: 0.00816 +2024-11-21 19:22:28.807824: train_loss -0.7735 +2024-11-21 19:22:28.808056: val_loss -0.7573 +2024-11-21 19:22:28.808140: Pseudo dice [0.8357] +2024-11-21 19:22:28.808241: Epoch time: 18.71 s +2024-11-21 19:22:29.653788: +2024-11-21 19:22:29.654006: Epoch 1621 +2024-11-21 19:22:29.654114: Current learning rate: 0.00816 +2024-11-21 19:22:48.427892: train_loss -0.7673 +2024-11-21 19:22:48.428466: val_loss -0.762 +2024-11-21 19:22:48.428549: Pseudo dice [0.8529] +2024-11-21 19:22:48.428631: Epoch time: 18.77 s +2024-11-21 19:22:49.271768: +2024-11-21 19:22:49.271973: Epoch 1622 +2024-11-21 19:22:49.272088: Current learning rate: 0.00816 +2024-11-21 19:23:08.211883: train_loss -0.7733 +2024-11-21 19:23:08.212116: val_loss -0.7679 +2024-11-21 19:23:08.212194: Pseudo dice [0.8369] +2024-11-21 19:23:08.212272: Epoch time: 18.94 s +2024-11-21 19:23:09.437988: +2024-11-21 19:23:09.438460: Epoch 1623 +2024-11-21 19:23:09.438602: Current learning rate: 0.00815 +2024-11-21 19:23:28.572491: train_loss -0.775 +2024-11-21 19:23:28.572757: val_loss -0.757 +2024-11-21 19:23:28.572840: Pseudo dice [0.8419] +2024-11-21 19:23:28.572924: Epoch time: 19.14 s +2024-11-21 19:23:29.428429: +2024-11-21 19:23:29.428850: Epoch 1624 +2024-11-21 19:23:29.428976: Current learning rate: 0.00815 +2024-11-21 19:23:48.854066: train_loss -0.764 +2024-11-21 19:23:48.854282: val_loss -0.7759 +2024-11-21 19:23:48.854356: Pseudo dice [0.8583] +2024-11-21 19:23:48.854431: Epoch time: 19.43 s +2024-11-21 19:23:48.854492: Yayy! New best EMA pseudo Dice: 0.8437 +2024-11-21 19:23:49.892696: +2024-11-21 19:23:49.893220: Epoch 1625 +2024-11-21 19:23:49.893370: Current learning rate: 0.00815 +2024-11-21 19:24:08.073347: train_loss -0.7739 +2024-11-21 19:24:08.073878: val_loss -0.779 +2024-11-21 19:24:08.073958: Pseudo dice [0.8406] +2024-11-21 19:24:08.074041: Epoch time: 18.18 s +2024-11-21 19:24:08.915928: +2024-11-21 19:24:08.916363: Epoch 1626 +2024-11-21 19:24:08.916495: Current learning rate: 0.00815 +2024-11-21 19:24:28.236530: train_loss -0.7598 +2024-11-21 19:24:28.242053: val_loss -0.7452 +2024-11-21 19:24:28.242204: Pseudo dice [0.8488] +2024-11-21 19:24:28.242309: Epoch time: 19.32 s +2024-11-21 19:24:28.242378: Yayy! New best EMA pseudo Dice: 0.8439 +2024-11-21 19:24:29.299101: +2024-11-21 19:24:29.299506: Epoch 1627 +2024-11-21 19:24:29.299637: Current learning rate: 0.00815 +2024-11-21 19:24:47.587237: train_loss -0.7699 +2024-11-21 19:24:47.587449: val_loss -0.767 +2024-11-21 19:24:47.587526: Pseudo dice [0.848] +2024-11-21 19:24:47.587600: Epoch time: 18.29 s +2024-11-21 19:24:47.587661: Yayy! New best EMA pseudo Dice: 0.8443 +2024-11-21 19:24:48.624467: +2024-11-21 19:24:48.624940: Epoch 1628 +2024-11-21 19:24:48.625085: Current learning rate: 0.00815 +2024-11-21 19:25:07.311326: train_loss -0.7614 +2024-11-21 19:25:07.311544: val_loss -0.75 +2024-11-21 19:25:07.311616: Pseudo dice [0.825] +2024-11-21 19:25:07.311692: Epoch time: 18.69 s +2024-11-21 19:25:08.155427: +2024-11-21 19:25:08.155817: Epoch 1629 +2024-11-21 19:25:08.155949: Current learning rate: 0.00815 +2024-11-21 19:25:25.750586: train_loss -0.767 +2024-11-21 19:25:25.750799: val_loss -0.7641 +2024-11-21 19:25:25.750877: Pseudo dice [0.8476] +2024-11-21 19:25:25.750970: Epoch time: 17.6 s +2024-11-21 19:25:26.594585: +2024-11-21 19:25:26.594823: Epoch 1630 +2024-11-21 19:25:26.594929: Current learning rate: 0.00815 +2024-11-21 19:25:46.054508: train_loss -0.7603 +2024-11-21 19:25:46.054747: val_loss -0.7746 +2024-11-21 19:25:46.054825: Pseudo dice [0.8504] +2024-11-21 19:25:46.054904: Epoch time: 19.46 s +2024-11-21 19:25:46.904560: +2024-11-21 19:25:46.904790: Epoch 1631 +2024-11-21 19:25:46.904903: Current learning rate: 0.00814 +2024-11-21 19:26:04.924431: train_loss -0.7778 +2024-11-21 19:26:04.924640: val_loss -0.7691 +2024-11-21 19:26:04.924715: Pseudo dice [0.8457] +2024-11-21 19:26:04.924790: Epoch time: 18.02 s +2024-11-21 19:26:05.823783: +2024-11-21 19:26:05.823998: Epoch 1632 +2024-11-21 19:26:05.824116: Current learning rate: 0.00814 +2024-11-21 19:26:24.280923: train_loss -0.7687 +2024-11-21 19:26:24.281167: val_loss -0.774 +2024-11-21 19:26:24.281245: Pseudo dice [0.8522] +2024-11-21 19:26:24.281321: Epoch time: 18.46 s +2024-11-21 19:26:24.281383: Yayy! New best EMA pseudo Dice: 0.8447 +2024-11-21 19:26:25.777585: +2024-11-21 19:26:25.778018: Epoch 1633 +2024-11-21 19:26:25.778147: Current learning rate: 0.00814 +2024-11-21 19:26:43.930729: train_loss -0.7722 +2024-11-21 19:26:43.930989: val_loss -0.7587 +2024-11-21 19:26:43.931075: Pseudo dice [0.8286] +2024-11-21 19:26:43.931157: Epoch time: 18.15 s +2024-11-21 19:26:44.775815: +2024-11-21 19:26:44.776253: Epoch 1634 +2024-11-21 19:26:44.776386: Current learning rate: 0.00814 +2024-11-21 19:27:03.461730: train_loss -0.7799 +2024-11-21 19:27:03.461937: val_loss -0.75 +2024-11-21 19:27:03.462013: Pseudo dice [0.8402] +2024-11-21 19:27:03.462088: Epoch time: 18.69 s +2024-11-21 19:27:04.306473: +2024-11-21 19:27:04.306920: Epoch 1635 +2024-11-21 19:27:04.307057: Current learning rate: 0.00814 +2024-11-21 19:27:22.117196: train_loss -0.7701 +2024-11-21 19:27:22.117413: val_loss -0.7449 +2024-11-21 19:27:22.117558: Pseudo dice [0.8246] +2024-11-21 19:27:22.117636: Epoch time: 17.81 s +2024-11-21 19:27:22.963578: +2024-11-21 19:27:22.964077: Epoch 1636 +2024-11-21 19:27:22.964214: Current learning rate: 0.00814 +2024-11-21 19:27:41.523188: train_loss -0.7594 +2024-11-21 19:27:41.523464: val_loss -0.7524 +2024-11-21 19:27:41.523547: Pseudo dice [0.8157] +2024-11-21 19:27:41.523625: Epoch time: 18.56 s +2024-11-21 19:27:42.370480: +2024-11-21 19:27:42.370899: Epoch 1637 +2024-11-21 19:27:42.371038: Current learning rate: 0.00814 +2024-11-21 19:28:02.192930: train_loss -0.747 +2024-11-21 19:28:02.193174: val_loss -0.7608 +2024-11-21 19:28:02.193248: Pseudo dice [0.8308] +2024-11-21 19:28:02.193326: Epoch time: 19.82 s +2024-11-21 19:28:03.025672: +2024-11-21 19:28:03.026116: Epoch 1638 +2024-11-21 19:28:03.026249: Current learning rate: 0.00814 +2024-11-21 19:28:21.425857: train_loss -0.7742 +2024-11-21 19:28:21.426086: val_loss -0.765 +2024-11-21 19:28:21.426430: Pseudo dice [0.8566] +2024-11-21 19:28:21.426507: Epoch time: 18.4 s +2024-11-21 19:28:22.260926: +2024-11-21 19:28:22.261352: Epoch 1639 +2024-11-21 19:28:22.261490: Current learning rate: 0.00814 +2024-11-21 19:28:40.650411: train_loss -0.7586 +2024-11-21 19:28:40.650632: val_loss -0.7921 +2024-11-21 19:28:40.650708: Pseudo dice [0.8534] +2024-11-21 19:28:40.650784: Epoch time: 18.39 s +2024-11-21 19:28:41.481573: +2024-11-21 19:28:41.481988: Epoch 1640 +2024-11-21 19:28:41.482135: Current learning rate: 0.00813 +2024-11-21 19:29:00.719164: train_loss -0.7652 +2024-11-21 19:29:00.719407: val_loss -0.7423 +2024-11-21 19:29:00.719482: Pseudo dice [0.8258] +2024-11-21 19:29:00.719563: Epoch time: 19.24 s +2024-11-21 19:29:01.575489: +2024-11-21 19:29:01.575745: Epoch 1641 +2024-11-21 19:29:01.575856: Current learning rate: 0.00813 +2024-11-21 19:29:20.103979: train_loss -0.7673 +2024-11-21 19:29:20.104199: val_loss -0.7725 +2024-11-21 19:29:20.104272: Pseudo dice [0.8389] +2024-11-21 19:29:20.104388: Epoch time: 18.53 s +2024-11-21 19:29:21.033762: +2024-11-21 19:29:21.033964: Epoch 1642 +2024-11-21 19:29:21.034084: Current learning rate: 0.00813 +2024-11-21 19:29:40.007009: train_loss -0.7595 +2024-11-21 19:29:40.007265: val_loss -0.7583 +2024-11-21 19:29:40.007341: Pseudo dice [0.8516] +2024-11-21 19:29:40.007444: Epoch time: 18.97 s +2024-11-21 19:29:40.843290: +2024-11-21 19:29:40.843485: Epoch 1643 +2024-11-21 19:29:40.843595: Current learning rate: 0.00813 +2024-11-21 19:29:59.431046: train_loss -0.774 +2024-11-21 19:29:59.436333: val_loss -0.7642 +2024-11-21 19:29:59.436581: Pseudo dice [0.8448] +2024-11-21 19:29:59.436670: Epoch time: 18.59 s +2024-11-21 19:30:00.685919: +2024-11-21 19:30:00.686128: Epoch 1644 +2024-11-21 19:30:00.686246: Current learning rate: 0.00813 +2024-11-21 19:30:18.886168: train_loss -0.7621 +2024-11-21 19:30:18.886426: val_loss -0.7753 +2024-11-21 19:30:18.886502: Pseudo dice [0.8497] +2024-11-21 19:30:18.886578: Epoch time: 18.2 s +2024-11-21 19:30:19.718592: +2024-11-21 19:30:19.718816: Epoch 1645 +2024-11-21 19:30:19.718937: Current learning rate: 0.00813 +2024-11-21 19:30:38.174519: train_loss -0.766 +2024-11-21 19:30:38.174745: val_loss -0.7799 +2024-11-21 19:30:38.174818: Pseudo dice [0.8367] +2024-11-21 19:30:38.174894: Epoch time: 18.46 s +2024-11-21 19:30:39.004336: +2024-11-21 19:30:39.004553: Epoch 1646 +2024-11-21 19:30:39.004659: Current learning rate: 0.00813 +2024-11-21 19:30:57.647303: train_loss -0.767 +2024-11-21 19:30:57.647531: val_loss -0.7612 +2024-11-21 19:30:57.647604: Pseudo dice [0.8335] +2024-11-21 19:30:57.647676: Epoch time: 18.64 s +2024-11-21 19:30:58.557220: +2024-11-21 19:30:58.557444: Epoch 1647 +2024-11-21 19:30:58.557546: Current learning rate: 0.00813 +2024-11-21 19:31:16.865193: train_loss -0.7674 +2024-11-21 19:31:16.865448: val_loss -0.7399 +2024-11-21 19:31:16.865525: Pseudo dice [0.818] +2024-11-21 19:31:16.865666: Epoch time: 18.31 s +2024-11-21 19:31:17.707748: +2024-11-21 19:31:17.708022: Epoch 1648 +2024-11-21 19:31:17.708139: Current learning rate: 0.00813 +2024-11-21 19:31:36.628498: train_loss -0.7657 +2024-11-21 19:31:36.628714: val_loss -0.7647 +2024-11-21 19:31:36.628792: Pseudo dice [0.8401] +2024-11-21 19:31:36.628870: Epoch time: 18.92 s +2024-11-21 19:31:37.525871: +2024-11-21 19:31:37.526083: Epoch 1649 +2024-11-21 19:31:37.526197: Current learning rate: 0.00812 +2024-11-21 19:31:56.410457: train_loss -0.7784 +2024-11-21 19:31:56.410676: val_loss -0.7619 +2024-11-21 19:31:56.410749: Pseudo dice [0.8488] +2024-11-21 19:31:56.410823: Epoch time: 18.89 s +2024-11-21 19:31:57.549219: +2024-11-21 19:31:57.549445: Epoch 1650 +2024-11-21 19:31:57.549555: Current learning rate: 0.00812 +2024-11-21 19:32:15.802220: train_loss -0.7754 +2024-11-21 19:32:15.802436: val_loss -0.7564 +2024-11-21 19:32:15.802512: Pseudo dice [0.8374] +2024-11-21 19:32:15.802589: Epoch time: 18.25 s +2024-11-21 19:32:16.633432: +2024-11-21 19:32:16.633665: Epoch 1651 +2024-11-21 19:32:16.633778: Current learning rate: 0.00812 +2024-11-21 19:32:35.473499: train_loss -0.7669 +2024-11-21 19:32:35.473757: val_loss -0.7802 +2024-11-21 19:32:35.473832: Pseudo dice [0.8432] +2024-11-21 19:32:35.473914: Epoch time: 18.84 s +2024-11-21 19:32:36.320357: +2024-11-21 19:32:36.320565: Epoch 1652 +2024-11-21 19:32:36.320675: Current learning rate: 0.00812 +2024-11-21 19:32:53.824331: train_loss -0.7788 +2024-11-21 19:32:53.824553: val_loss -0.7812 +2024-11-21 19:32:53.824626: Pseudo dice [0.8558] +2024-11-21 19:32:53.824702: Epoch time: 17.5 s +2024-11-21 19:32:54.760118: +2024-11-21 19:32:54.760335: Epoch 1653 +2024-11-21 19:32:54.760450: Current learning rate: 0.00812 +2024-11-21 19:33:13.736306: train_loss -0.777 +2024-11-21 19:33:13.736526: val_loss -0.7663 +2024-11-21 19:33:13.736604: Pseudo dice [0.8458] +2024-11-21 19:33:13.736682: Epoch time: 18.98 s +2024-11-21 19:33:14.568951: +2024-11-21 19:33:14.569170: Epoch 1654 +2024-11-21 19:33:14.569285: Current learning rate: 0.00812 +2024-11-21 19:33:33.100031: train_loss -0.7685 +2024-11-21 19:33:33.100278: val_loss -0.7421 +2024-11-21 19:33:33.100356: Pseudo dice [0.8278] +2024-11-21 19:33:33.100438: Epoch time: 18.53 s +2024-11-21 19:33:33.952289: +2024-11-21 19:33:33.952549: Epoch 1655 +2024-11-21 19:33:33.952657: Current learning rate: 0.00812 +2024-11-21 19:33:51.685693: train_loss -0.7701 +2024-11-21 19:33:51.685904: val_loss -0.7407 +2024-11-21 19:33:51.685979: Pseudo dice [0.8463] +2024-11-21 19:33:51.686062: Epoch time: 17.73 s +2024-11-21 19:33:52.923633: +2024-11-21 19:33:52.923917: Epoch 1656 +2024-11-21 19:33:52.924036: Current learning rate: 0.00812 +2024-11-21 19:34:11.564137: train_loss -0.7719 +2024-11-21 19:34:11.564352: val_loss -0.7696 +2024-11-21 19:34:11.564488: Pseudo dice [0.8374] +2024-11-21 19:34:11.564565: Epoch time: 18.64 s +2024-11-21 19:34:12.396158: +2024-11-21 19:34:12.396402: Epoch 1657 +2024-11-21 19:34:12.396514: Current learning rate: 0.00811 +2024-11-21 19:34:31.231524: train_loss -0.7776 +2024-11-21 19:34:31.231749: val_loss -0.7486 +2024-11-21 19:34:31.231830: Pseudo dice [0.8288] +2024-11-21 19:34:31.231912: Epoch time: 18.84 s +2024-11-21 19:34:32.059925: +2024-11-21 19:34:32.060158: Epoch 1658 +2024-11-21 19:34:32.060277: Current learning rate: 0.00811 +2024-11-21 19:34:50.610378: train_loss -0.7688 +2024-11-21 19:34:50.610627: val_loss -0.7621 +2024-11-21 19:34:50.610702: Pseudo dice [0.8304] +2024-11-21 19:34:50.610782: Epoch time: 18.55 s +2024-11-21 19:34:51.554651: +2024-11-21 19:34:51.554879: Epoch 1659 +2024-11-21 19:34:51.555006: Current learning rate: 0.00811 +2024-11-21 19:35:09.769678: train_loss -0.7793 +2024-11-21 19:35:09.771471: val_loss -0.7396 +2024-11-21 19:35:09.771695: Pseudo dice [0.8481] +2024-11-21 19:35:09.771780: Epoch time: 18.22 s +2024-11-21 19:35:10.695997: +2024-11-21 19:35:10.696349: Epoch 1660 +2024-11-21 19:35:10.696464: Current learning rate: 0.00811 +2024-11-21 19:35:29.020657: train_loss -0.7667 +2024-11-21 19:35:29.020890: val_loss -0.7717 +2024-11-21 19:35:29.020966: Pseudo dice [0.8529] +2024-11-21 19:35:29.021045: Epoch time: 18.33 s +2024-11-21 19:35:29.859837: +2024-11-21 19:35:29.860089: Epoch 1661 +2024-11-21 19:35:29.860201: Current learning rate: 0.00811 +2024-11-21 19:35:48.471473: train_loss -0.767 +2024-11-21 19:35:48.471699: val_loss -0.781 +2024-11-21 19:35:48.471774: Pseudo dice [0.8374] +2024-11-21 19:35:48.471853: Epoch time: 18.61 s +2024-11-21 19:35:49.311396: +2024-11-21 19:35:49.311600: Epoch 1662 +2024-11-21 19:35:49.311706: Current learning rate: 0.00811 +2024-11-21 19:36:08.632893: train_loss -0.7699 +2024-11-21 19:36:08.633129: val_loss -0.765 +2024-11-21 19:36:08.633205: Pseudo dice [0.8405] +2024-11-21 19:36:08.633288: Epoch time: 19.32 s +2024-11-21 19:36:09.586017: +2024-11-21 19:36:09.586210: Epoch 1663 +2024-11-21 19:36:09.586316: Current learning rate: 0.00811 +2024-11-21 19:36:28.528365: train_loss -0.7653 +2024-11-21 19:36:28.528575: val_loss -0.7495 +2024-11-21 19:36:28.528651: Pseudo dice [0.8333] +2024-11-21 19:36:28.528728: Epoch time: 18.94 s +2024-11-21 19:36:29.363394: +2024-11-21 19:36:29.363626: Epoch 1664 +2024-11-21 19:36:29.363733: Current learning rate: 0.00811 +2024-11-21 19:36:48.017966: train_loss -0.7632 +2024-11-21 19:36:48.021092: val_loss -0.7597 +2024-11-21 19:36:48.021271: Pseudo dice [0.848] +2024-11-21 19:36:48.021352: Epoch time: 18.66 s +2024-11-21 19:36:48.861322: +2024-11-21 19:36:48.861529: Epoch 1665 +2024-11-21 19:36:48.861636: Current learning rate: 0.00811 +2024-11-21 19:37:06.983781: train_loss -0.7679 +2024-11-21 19:37:06.984039: val_loss -0.7755 +2024-11-21 19:37:06.984128: Pseudo dice [0.8377] +2024-11-21 19:37:06.984219: Epoch time: 18.12 s +2024-11-21 19:37:07.820119: +2024-11-21 19:37:07.820349: Epoch 1666 +2024-11-21 19:37:07.820460: Current learning rate: 0.0081 +2024-11-21 19:37:26.296263: train_loss -0.7726 +2024-11-21 19:37:26.296500: val_loss -0.758 +2024-11-21 19:37:26.296577: Pseudo dice [0.8487] +2024-11-21 19:37:26.296650: Epoch time: 18.48 s +2024-11-21 19:37:27.129733: +2024-11-21 19:37:27.129941: Epoch 1667 +2024-11-21 19:37:27.130057: Current learning rate: 0.0081 +2024-11-21 19:37:46.422465: train_loss -0.7668 +2024-11-21 19:37:46.422967: val_loss -0.7676 +2024-11-21 19:37:46.423071: Pseudo dice [0.8399] +2024-11-21 19:37:46.423147: Epoch time: 19.29 s +2024-11-21 19:37:47.260836: +2024-11-21 19:37:47.261068: Epoch 1668 +2024-11-21 19:37:47.261176: Current learning rate: 0.0081 +2024-11-21 19:38:06.202296: train_loss -0.7775 +2024-11-21 19:38:06.202534: val_loss -0.7497 +2024-11-21 19:38:06.202608: Pseudo dice [0.843] +2024-11-21 19:38:06.202723: Epoch time: 18.94 s +2024-11-21 19:38:07.044582: +2024-11-21 19:38:07.044818: Epoch 1669 +2024-11-21 19:38:07.044946: Current learning rate: 0.0081 +2024-11-21 19:38:25.591909: train_loss -0.769 +2024-11-21 19:38:25.592129: val_loss -0.7381 +2024-11-21 19:38:25.592202: Pseudo dice [0.8308] +2024-11-21 19:38:25.592280: Epoch time: 18.55 s +2024-11-21 19:38:26.609046: +2024-11-21 19:38:26.609283: Epoch 1670 +2024-11-21 19:38:26.609400: Current learning rate: 0.0081 +2024-11-21 19:38:45.679895: train_loss -0.7516 +2024-11-21 19:38:45.680197: val_loss -0.7559 +2024-11-21 19:38:45.680293: Pseudo dice [0.8236] +2024-11-21 19:38:45.680368: Epoch time: 19.07 s +2024-11-21 19:38:46.562813: +2024-11-21 19:38:46.563043: Epoch 1671 +2024-11-21 19:38:46.563155: Current learning rate: 0.0081 +2024-11-21 19:39:05.320831: train_loss -0.7685 +2024-11-21 19:39:05.321043: val_loss -0.7717 +2024-11-21 19:39:05.321118: Pseudo dice [0.8436] +2024-11-21 19:39:05.321196: Epoch time: 18.76 s +2024-11-21 19:39:06.299810: +2024-11-21 19:39:06.300011: Epoch 1672 +2024-11-21 19:39:06.300118: Current learning rate: 0.0081 +2024-11-21 19:39:24.597332: train_loss -0.7787 +2024-11-21 19:39:24.597571: val_loss -0.7813 +2024-11-21 19:39:24.597645: Pseudo dice [0.8425] +2024-11-21 19:39:24.597722: Epoch time: 18.3 s +2024-11-21 19:39:25.500619: +2024-11-21 19:39:25.500847: Epoch 1673 +2024-11-21 19:39:25.500956: Current learning rate: 0.0081 +2024-11-21 19:39:43.323276: train_loss -0.7554 +2024-11-21 19:39:43.323494: val_loss -0.7571 +2024-11-21 19:39:43.323568: Pseudo dice [0.8399] +2024-11-21 19:39:43.323642: Epoch time: 17.82 s +2024-11-21 19:39:44.157918: +2024-11-21 19:39:44.158153: Epoch 1674 +2024-11-21 19:39:44.158266: Current learning rate: 0.0081 +2024-11-21 19:40:02.102482: train_loss -0.7512 +2024-11-21 19:40:02.103043: val_loss -0.7568 +2024-11-21 19:40:02.103125: Pseudo dice [0.8296] +2024-11-21 19:40:02.103202: Epoch time: 17.95 s +2024-11-21 19:40:02.939321: +2024-11-21 19:40:02.939585: Epoch 1675 +2024-11-21 19:40:02.939701: Current learning rate: 0.00809 +2024-11-21 19:40:21.068831: train_loss -0.7629 +2024-11-21 19:40:21.069090: val_loss -0.758 +2024-11-21 19:40:21.071337: Pseudo dice [0.8427] +2024-11-21 19:40:21.071470: Epoch time: 18.13 s +2024-11-21 19:40:21.980130: +2024-11-21 19:40:21.980336: Epoch 1676 +2024-11-21 19:40:21.980448: Current learning rate: 0.00809 +2024-11-21 19:40:40.092722: train_loss -0.7685 +2024-11-21 19:40:40.092928: val_loss -0.7563 +2024-11-21 19:40:40.093096: Pseudo dice [0.8257] +2024-11-21 19:40:40.093438: Epoch time: 18.11 s +2024-11-21 19:40:40.933520: +2024-11-21 19:40:40.933752: Epoch 1677 +2024-11-21 19:40:40.933863: Current learning rate: 0.00809 +2024-11-21 19:40:59.452672: train_loss -0.7794 +2024-11-21 19:40:59.452982: val_loss -0.7474 +2024-11-21 19:40:59.453070: Pseudo dice [0.8387] +2024-11-21 19:40:59.453145: Epoch time: 18.52 s +2024-11-21 19:41:00.380835: +2024-11-21 19:41:00.381047: Epoch 1678 +2024-11-21 19:41:00.381163: Current learning rate: 0.00809 +2024-11-21 19:41:17.663062: train_loss -0.7623 +2024-11-21 19:41:17.663295: val_loss -0.7508 +2024-11-21 19:41:17.663406: Pseudo dice [0.827] +2024-11-21 19:41:17.663538: Epoch time: 17.28 s +2024-11-21 19:41:18.616709: +2024-11-21 19:41:18.616953: Epoch 1679 +2024-11-21 19:41:18.617072: Current learning rate: 0.00809 +2024-11-21 19:41:37.002951: train_loss -0.7776 +2024-11-21 19:41:37.003191: val_loss -0.7615 +2024-11-21 19:41:37.003285: Pseudo dice [0.8433] +2024-11-21 19:41:37.003383: Epoch time: 18.39 s +2024-11-21 19:41:37.845842: +2024-11-21 19:41:37.846081: Epoch 1680 +2024-11-21 19:41:37.846196: Current learning rate: 0.00809 +2024-11-21 19:41:55.680609: train_loss -0.7659 +2024-11-21 19:41:55.680826: val_loss -0.7671 +2024-11-21 19:41:55.680902: Pseudo dice [0.8297] +2024-11-21 19:41:55.680975: Epoch time: 17.84 s +2024-11-21 19:41:56.521858: +2024-11-21 19:41:56.522080: Epoch 1681 +2024-11-21 19:41:56.522193: Current learning rate: 0.00809 +2024-11-21 19:42:14.949442: train_loss -0.7607 +2024-11-21 19:42:14.949695: val_loss -0.7697 +2024-11-21 19:42:14.949773: Pseudo dice [0.8529] +2024-11-21 19:42:14.949858: Epoch time: 18.43 s +2024-11-21 19:42:15.931424: +2024-11-21 19:42:15.931639: Epoch 1682 +2024-11-21 19:42:15.931751: Current learning rate: 0.00809 +2024-11-21 19:42:33.375491: train_loss -0.7538 +2024-11-21 19:42:33.375719: val_loss -0.7542 +2024-11-21 19:42:33.375794: Pseudo dice [0.8215] +2024-11-21 19:42:33.375867: Epoch time: 17.44 s +2024-11-21 19:42:34.217950: +2024-11-21 19:42:34.218244: Epoch 1683 +2024-11-21 19:42:34.218356: Current learning rate: 0.00808 +2024-11-21 19:42:52.492912: train_loss -0.745 +2024-11-21 19:42:52.493136: val_loss -0.7045 +2024-11-21 19:42:52.493209: Pseudo dice [0.8152] +2024-11-21 19:42:52.493283: Epoch time: 18.28 s +2024-11-21 19:42:53.439870: +2024-11-21 19:42:53.440090: Epoch 1684 +2024-11-21 19:42:53.440199: Current learning rate: 0.00808 +2024-11-21 19:43:12.009650: train_loss -0.7511 +2024-11-21 19:43:12.009860: val_loss -0.7713 +2024-11-21 19:43:12.009933: Pseudo dice [0.8369] +2024-11-21 19:43:12.010016: Epoch time: 18.57 s +2024-11-21 19:43:12.848147: +2024-11-21 19:43:12.848365: Epoch 1685 +2024-11-21 19:43:12.848475: Current learning rate: 0.00808 +2024-11-21 19:43:31.913419: train_loss -0.7414 +2024-11-21 19:43:31.913676: val_loss -0.7831 +2024-11-21 19:43:31.913752: Pseudo dice [0.8551] +2024-11-21 19:43:31.913840: Epoch time: 19.07 s +2024-11-21 19:43:32.763394: +2024-11-21 19:43:32.763596: Epoch 1686 +2024-11-21 19:43:32.763702: Current learning rate: 0.00808 +2024-11-21 19:43:51.449631: train_loss -0.7645 +2024-11-21 19:43:51.449856: val_loss -0.751 +2024-11-21 19:43:51.449955: Pseudo dice [0.8245] +2024-11-21 19:43:51.450069: Epoch time: 18.69 s +2024-11-21 19:43:52.294202: +2024-11-21 19:43:52.294425: Epoch 1687 +2024-11-21 19:43:52.294537: Current learning rate: 0.00808 +2024-11-21 19:44:10.583442: train_loss -0.7424 +2024-11-21 19:44:10.583658: val_loss -0.7279 +2024-11-21 19:44:10.583735: Pseudo dice [0.8263] +2024-11-21 19:44:10.583811: Epoch time: 18.29 s +2024-11-21 19:44:11.422268: +2024-11-21 19:44:11.422502: Epoch 1688 +2024-11-21 19:44:11.422626: Current learning rate: 0.00808 +2024-11-21 19:44:30.094547: train_loss -0.7449 +2024-11-21 19:44:30.094759: val_loss -0.7714 +2024-11-21 19:44:30.094831: Pseudo dice [0.8286] +2024-11-21 19:44:30.094912: Epoch time: 18.67 s +2024-11-21 19:44:30.942594: +2024-11-21 19:44:30.942809: Epoch 1689 +2024-11-21 19:44:30.942928: Current learning rate: 0.00808 +2024-11-21 19:44:48.219246: train_loss -0.7618 +2024-11-21 19:44:48.237328: val_loss -0.7677 +2024-11-21 19:44:48.237442: Pseudo dice [0.8358] +2024-11-21 19:44:48.237529: Epoch time: 17.28 s +2024-11-21 19:44:49.072469: +2024-11-21 19:44:49.072721: Epoch 1690 +2024-11-21 19:44:49.072832: Current learning rate: 0.00808 +2024-11-21 19:45:07.721506: train_loss -0.7675 +2024-11-21 19:45:07.721740: val_loss -0.7295 +2024-11-21 19:45:07.721823: Pseudo dice [0.8399] +2024-11-21 19:45:07.721903: Epoch time: 18.65 s +2024-11-21 19:45:08.560983: +2024-11-21 19:45:08.561239: Epoch 1691 +2024-11-21 19:45:08.561353: Current learning rate: 0.00808 +2024-11-21 19:45:27.801609: train_loss -0.7659 +2024-11-21 19:45:27.803687: val_loss -0.7647 +2024-11-21 19:45:27.803800: Pseudo dice [0.8434] +2024-11-21 19:45:27.803917: Epoch time: 19.24 s +2024-11-21 19:45:28.710057: +2024-11-21 19:45:28.710286: Epoch 1692 +2024-11-21 19:45:28.710401: Current learning rate: 0.00807 +2024-11-21 19:45:47.775166: train_loss -0.7611 +2024-11-21 19:45:47.775396: val_loss -0.7347 +2024-11-21 19:45:47.775470: Pseudo dice [0.8235] +2024-11-21 19:45:47.775549: Epoch time: 19.07 s +2024-11-21 19:45:48.665871: +2024-11-21 19:45:48.666143: Epoch 1693 +2024-11-21 19:45:48.666256: Current learning rate: 0.00807 +2024-11-21 19:46:07.686494: train_loss -0.7421 +2024-11-21 19:46:07.686702: val_loss -0.7492 +2024-11-21 19:46:07.686774: Pseudo dice [0.8477] +2024-11-21 19:46:07.686850: Epoch time: 19.02 s +2024-11-21 19:46:08.546095: +2024-11-21 19:46:08.546324: Epoch 1694 +2024-11-21 19:46:08.546433: Current learning rate: 0.00807 +2024-11-21 19:46:26.981866: train_loss -0.7605 +2024-11-21 19:46:26.982157: val_loss -0.7667 +2024-11-21 19:46:26.982242: Pseudo dice [0.8568] +2024-11-21 19:46:26.982320: Epoch time: 18.44 s +2024-11-21 19:46:27.831497: +2024-11-21 19:46:27.831730: Epoch 1695 +2024-11-21 19:46:27.831846: Current learning rate: 0.00807 +2024-11-21 19:46:46.268263: train_loss -0.7699 +2024-11-21 19:46:46.270931: val_loss -0.7613 +2024-11-21 19:46:46.271053: Pseudo dice [0.8523] +2024-11-21 19:46:46.271130: Epoch time: 18.44 s +2024-11-21 19:46:47.129510: +2024-11-21 19:46:47.129710: Epoch 1696 +2024-11-21 19:46:47.129997: Current learning rate: 0.00807 +2024-11-21 19:47:06.033263: train_loss -0.7702 +2024-11-21 19:47:06.033514: val_loss -0.785 +2024-11-21 19:47:06.033589: Pseudo dice [0.8491] +2024-11-21 19:47:06.033671: Epoch time: 18.9 s +2024-11-21 19:47:06.884655: +2024-11-21 19:47:06.884843: Epoch 1697 +2024-11-21 19:47:06.884949: Current learning rate: 0.00807 +2024-11-21 19:47:25.021604: train_loss -0.7699 +2024-11-21 19:47:25.021886: val_loss -0.764 +2024-11-21 19:47:25.021968: Pseudo dice [0.8262] +2024-11-21 19:47:25.022051: Epoch time: 18.14 s +2024-11-21 19:47:25.949610: +2024-11-21 19:47:25.949832: Epoch 1698 +2024-11-21 19:47:25.949950: Current learning rate: 0.00807 +2024-11-21 19:47:43.462740: train_loss -0.7656 +2024-11-21 19:47:43.462962: val_loss -0.7624 +2024-11-21 19:47:43.463044: Pseudo dice [0.8174] +2024-11-21 19:47:43.463122: Epoch time: 17.51 s +2024-11-21 19:47:44.302573: +2024-11-21 19:47:44.302769: Epoch 1699 +2024-11-21 19:47:44.302878: Current learning rate: 0.00807 +2024-11-21 19:48:04.338617: train_loss -0.7668 +2024-11-21 19:48:04.338836: val_loss -0.7533 +2024-11-21 19:48:04.338910: Pseudo dice [0.8236] +2024-11-21 19:48:04.338985: Epoch time: 20.04 s +2024-11-21 19:48:05.869277: +2024-11-21 19:48:05.869501: Epoch 1700 +2024-11-21 19:48:05.869612: Current learning rate: 0.00807 +2024-11-21 19:48:24.020869: train_loss -0.7649 +2024-11-21 19:48:24.021179: val_loss -0.7577 +2024-11-21 19:48:24.021259: Pseudo dice [0.849] +2024-11-21 19:48:24.021341: Epoch time: 18.15 s +2024-11-21 19:48:24.862239: +2024-11-21 19:48:24.862481: Epoch 1701 +2024-11-21 19:48:24.862605: Current learning rate: 0.00806 +2024-11-21 19:48:43.373814: train_loss -0.772 +2024-11-21 19:48:43.374032: val_loss -0.7639 +2024-11-21 19:48:43.374106: Pseudo dice [0.8485] +2024-11-21 19:48:43.374181: Epoch time: 18.51 s +2024-11-21 19:48:44.225652: +2024-11-21 19:48:44.225889: Epoch 1702 +2024-11-21 19:48:44.257064: Current learning rate: 0.00806 +2024-11-21 19:49:03.247986: train_loss -0.772 +2024-11-21 19:49:03.250372: val_loss -0.7663 +2024-11-21 19:49:03.250464: Pseudo dice [0.8288] +2024-11-21 19:49:03.250539: Epoch time: 19.02 s +2024-11-21 19:49:04.137227: +2024-11-21 19:49:04.137445: Epoch 1703 +2024-11-21 19:49:04.137557: Current learning rate: 0.00806 +2024-11-21 19:49:21.557287: train_loss -0.7699 +2024-11-21 19:49:21.557537: val_loss -0.7634 +2024-11-21 19:49:21.557611: Pseudo dice [0.8466] +2024-11-21 19:49:21.557695: Epoch time: 17.42 s +2024-11-21 19:49:22.412981: +2024-11-21 19:49:22.413218: Epoch 1704 +2024-11-21 19:49:22.413329: Current learning rate: 0.00806 +2024-11-21 19:49:40.959552: train_loss -0.7763 +2024-11-21 19:49:40.959773: val_loss -0.7657 +2024-11-21 19:49:40.959848: Pseudo dice [0.8456] +2024-11-21 19:49:40.959924: Epoch time: 18.55 s +2024-11-21 19:49:41.811968: +2024-11-21 19:49:41.812198: Epoch 1705 +2024-11-21 19:49:41.812313: Current learning rate: 0.00806 +2024-11-21 19:49:59.319244: train_loss -0.7649 +2024-11-21 19:49:59.319471: val_loss -0.7557 +2024-11-21 19:49:59.319546: Pseudo dice [0.8521] +2024-11-21 19:49:59.319623: Epoch time: 17.51 s +2024-11-21 19:50:00.255924: +2024-11-21 19:50:00.256202: Epoch 1706 +2024-11-21 19:50:00.256313: Current learning rate: 0.00806 +2024-11-21 19:50:17.765749: train_loss -0.7595 +2024-11-21 19:50:17.765974: val_loss -0.7498 +2024-11-21 19:50:17.766176: Pseudo dice [0.8307] +2024-11-21 19:50:17.766266: Epoch time: 17.51 s +2024-11-21 19:50:18.612648: +2024-11-21 19:50:18.612852: Epoch 1707 +2024-11-21 19:50:18.612965: Current learning rate: 0.00806 +2024-11-21 19:50:37.182084: train_loss -0.7764 +2024-11-21 19:50:37.182330: val_loss -0.7616 +2024-11-21 19:50:37.182404: Pseudo dice [0.8299] +2024-11-21 19:50:37.182485: Epoch time: 18.57 s +2024-11-21 19:50:38.027696: +2024-11-21 19:50:38.027916: Epoch 1708 +2024-11-21 19:50:38.028028: Current learning rate: 0.00806 +2024-11-21 19:50:55.380985: train_loss -0.7626 +2024-11-21 19:50:55.381227: val_loss -0.7424 +2024-11-21 19:50:55.381300: Pseudo dice [0.8373] +2024-11-21 19:50:55.381377: Epoch time: 17.35 s +2024-11-21 19:50:56.398701: +2024-11-21 19:50:56.398916: Epoch 1709 +2024-11-21 19:50:56.399033: Current learning rate: 0.00806 +2024-11-21 19:51:14.925308: train_loss -0.7753 +2024-11-21 19:51:14.925552: val_loss -0.7496 +2024-11-21 19:51:14.925687: Pseudo dice [0.8372] +2024-11-21 19:51:14.925766: Epoch time: 18.53 s +2024-11-21 19:51:15.773556: +2024-11-21 19:51:15.773776: Epoch 1710 +2024-11-21 19:51:15.773882: Current learning rate: 0.00805 +2024-11-21 19:51:34.137592: train_loss -0.7738 +2024-11-21 19:51:34.137844: val_loss -0.7846 +2024-11-21 19:51:34.137922: Pseudo dice [0.8655] +2024-11-21 19:51:34.138017: Epoch time: 18.36 s +2024-11-21 19:51:35.339433: +2024-11-21 19:51:35.339657: Epoch 1711 +2024-11-21 19:51:35.339768: Current learning rate: 0.00805 +2024-11-21 19:51:54.879637: train_loss -0.7793 +2024-11-21 19:51:54.879848: val_loss -0.7615 +2024-11-21 19:51:54.879921: Pseudo dice [0.835] +2024-11-21 19:51:54.880000: Epoch time: 19.54 s +2024-11-21 19:51:55.723115: +2024-11-21 19:51:55.723324: Epoch 1712 +2024-11-21 19:51:55.723430: Current learning rate: 0.00805 +2024-11-21 19:52:14.600743: train_loss -0.7715 +2024-11-21 19:52:14.601039: val_loss -0.7787 +2024-11-21 19:52:14.601117: Pseudo dice [0.8387] +2024-11-21 19:52:14.601194: Epoch time: 18.88 s +2024-11-21 19:52:15.443080: +2024-11-21 19:52:15.443291: Epoch 1713 +2024-11-21 19:52:15.443402: Current learning rate: 0.00805 +2024-11-21 19:52:32.742960: train_loss -0.7822 +2024-11-21 19:52:32.743275: val_loss -0.7625 +2024-11-21 19:52:32.743358: Pseudo dice [0.8491] +2024-11-21 19:52:32.743439: Epoch time: 17.3 s +2024-11-21 19:52:33.586712: +2024-11-21 19:52:33.586939: Epoch 1714 +2024-11-21 19:52:33.587061: Current learning rate: 0.00805 +2024-11-21 19:52:51.851093: train_loss -0.7736 +2024-11-21 19:52:51.853409: val_loss -0.7768 +2024-11-21 19:52:51.853542: Pseudo dice [0.8491] +2024-11-21 19:52:51.853626: Epoch time: 18.27 s +2024-11-21 19:52:52.717112: +2024-11-21 19:52:52.717328: Epoch 1715 +2024-11-21 19:52:52.717435: Current learning rate: 0.00805 +2024-11-21 19:53:10.416842: train_loss -0.7731 +2024-11-21 19:53:10.417059: val_loss -0.8 +2024-11-21 19:53:10.417134: Pseudo dice [0.8561] +2024-11-21 19:53:10.417210: Epoch time: 17.7 s +2024-11-21 19:53:11.372447: +2024-11-21 19:53:11.372668: Epoch 1716 +2024-11-21 19:53:11.372783: Current learning rate: 0.00805 +2024-11-21 19:53:29.609754: train_loss -0.7816 +2024-11-21 19:53:29.609981: val_loss -0.7851 +2024-11-21 19:53:29.610061: Pseudo dice [0.8527] +2024-11-21 19:53:29.610135: Epoch time: 18.24 s +2024-11-21 19:53:30.452718: +2024-11-21 19:53:30.452988: Epoch 1717 +2024-11-21 19:53:30.453102: Current learning rate: 0.00805 +2024-11-21 19:53:48.307509: train_loss -0.7786 +2024-11-21 19:53:48.307772: val_loss -0.7404 +2024-11-21 19:53:48.307849: Pseudo dice [0.8498] +2024-11-21 19:53:48.307932: Epoch time: 17.86 s +2024-11-21 19:53:48.308003: Yayy! New best EMA pseudo Dice: 0.8447 +2024-11-21 19:53:49.356636: +2024-11-21 19:53:49.356839: Epoch 1718 +2024-11-21 19:53:49.356949: Current learning rate: 0.00804 +2024-11-21 19:54:08.418005: train_loss -0.7682 +2024-11-21 19:54:08.418300: val_loss -0.7454 +2024-11-21 19:54:08.418379: Pseudo dice [0.8164] +2024-11-21 19:54:08.418454: Epoch time: 19.06 s +2024-11-21 19:54:09.286193: +2024-11-21 19:54:09.286398: Epoch 1719 +2024-11-21 19:54:09.286507: Current learning rate: 0.00804 +2024-11-21 19:54:27.383314: train_loss -0.7605 +2024-11-21 19:54:27.384679: val_loss -0.7676 +2024-11-21 19:54:27.384831: Pseudo dice [0.832] +2024-11-21 19:54:27.384909: Epoch time: 18.1 s +2024-11-21 19:54:28.238606: +2024-11-21 19:54:28.238839: Epoch 1720 +2024-11-21 19:54:28.238950: Current learning rate: 0.00804 +2024-11-21 19:54:46.500176: train_loss -0.7617 +2024-11-21 19:54:46.500391: val_loss -0.7662 +2024-11-21 19:54:46.500467: Pseudo dice [0.8359] +2024-11-21 19:54:46.500545: Epoch time: 18.26 s +2024-11-21 19:54:47.344505: +2024-11-21 19:54:47.344779: Epoch 1721 +2024-11-21 19:54:47.344891: Current learning rate: 0.00804 +2024-11-21 19:55:04.848348: train_loss -0.7586 +2024-11-21 19:55:04.848594: val_loss -0.7503 +2024-11-21 19:55:04.848670: Pseudo dice [0.8459] +2024-11-21 19:55:04.848980: Epoch time: 17.5 s +2024-11-21 19:55:06.039790: +2024-11-21 19:55:06.040004: Epoch 1722 +2024-11-21 19:55:06.040117: Current learning rate: 0.00804 +2024-11-21 19:55:24.845212: train_loss -0.7669 +2024-11-21 19:55:24.845976: val_loss -0.7537 +2024-11-21 19:55:24.846063: Pseudo dice [0.8268] +2024-11-21 19:55:24.846175: Epoch time: 18.81 s +2024-11-21 19:55:25.687537: +2024-11-21 19:55:25.687766: Epoch 1723 +2024-11-21 19:55:25.687875: Current learning rate: 0.00804 +2024-11-21 19:55:43.610482: train_loss -0.7713 +2024-11-21 19:55:43.610695: val_loss -0.7638 +2024-11-21 19:55:43.610770: Pseudo dice [0.8495] +2024-11-21 19:55:43.610847: Epoch time: 17.92 s +2024-11-21 19:55:44.455119: +2024-11-21 19:55:44.455341: Epoch 1724 +2024-11-21 19:55:44.455463: Current learning rate: 0.00804 +2024-11-21 19:56:02.665667: train_loss -0.776 +2024-11-21 19:56:02.665919: val_loss -0.7458 +2024-11-21 19:56:02.666001: Pseudo dice [0.8459] +2024-11-21 19:56:02.666084: Epoch time: 18.21 s +2024-11-21 19:56:03.512002: +2024-11-21 19:56:03.512215: Epoch 1725 +2024-11-21 19:56:03.512321: Current learning rate: 0.00804 +2024-11-21 19:56:22.287779: train_loss -0.7742 +2024-11-21 19:56:22.297079: val_loss -0.7633 +2024-11-21 19:56:22.297179: Pseudo dice [0.8318] +2024-11-21 19:56:22.297257: Epoch time: 18.78 s +2024-11-21 19:56:23.193620: +2024-11-21 19:56:23.193856: Epoch 1726 +2024-11-21 19:56:23.193967: Current learning rate: 0.00804 +2024-11-21 19:56:41.760275: train_loss -0.7636 +2024-11-21 19:56:41.760497: val_loss -0.767 +2024-11-21 19:56:41.760573: Pseudo dice [0.843] +2024-11-21 19:56:41.760650: Epoch time: 18.57 s +2024-11-21 19:56:42.606757: +2024-11-21 19:56:42.606976: Epoch 1727 +2024-11-21 19:56:42.607109: Current learning rate: 0.00803 +2024-11-21 19:57:01.480421: train_loss -0.7706 +2024-11-21 19:57:01.480646: val_loss -0.7748 +2024-11-21 19:57:01.480719: Pseudo dice [0.8428] +2024-11-21 19:57:01.480796: Epoch time: 18.87 s +2024-11-21 19:57:02.343302: +2024-11-21 19:57:02.343527: Epoch 1728 +2024-11-21 19:57:02.343640: Current learning rate: 0.00803 +2024-11-21 19:57:21.004479: train_loss -0.7625 +2024-11-21 19:57:21.004723: val_loss -0.7764 +2024-11-21 19:57:21.004800: Pseudo dice [0.8375] +2024-11-21 19:57:21.004888: Epoch time: 18.66 s +2024-11-21 19:57:21.879602: +2024-11-21 19:57:21.879810: Epoch 1729 +2024-11-21 19:57:21.879920: Current learning rate: 0.00803 +2024-11-21 19:57:41.152090: train_loss -0.7665 +2024-11-21 19:57:41.152302: val_loss -0.7661 +2024-11-21 19:57:41.152378: Pseudo dice [0.8389] +2024-11-21 19:57:41.152454: Epoch time: 19.27 s +2024-11-21 19:57:41.992239: +2024-11-21 19:57:41.992439: Epoch 1730 +2024-11-21 19:57:41.992546: Current learning rate: 0.00803 +2024-11-21 19:58:01.545450: train_loss -0.778 +2024-11-21 19:58:01.545667: val_loss -0.7706 +2024-11-21 19:58:01.547846: Pseudo dice [0.8357] +2024-11-21 19:58:01.548041: Epoch time: 19.55 s +2024-11-21 19:58:02.507192: +2024-11-21 19:58:02.507402: Epoch 1731 +2024-11-21 19:58:02.507511: Current learning rate: 0.00803 +2024-11-21 19:58:22.379245: train_loss -0.7738 +2024-11-21 19:58:22.379476: val_loss -0.7475 +2024-11-21 19:58:22.379555: Pseudo dice [0.8378] +2024-11-21 19:58:22.379640: Epoch time: 19.87 s +2024-11-21 19:58:23.288405: +2024-11-21 19:58:23.288606: Epoch 1732 +2024-11-21 19:58:23.288716: Current learning rate: 0.00803 +2024-11-21 19:58:42.022322: train_loss -0.7778 +2024-11-21 19:58:42.022565: val_loss -0.7489 +2024-11-21 19:58:42.022641: Pseudo dice [0.8284] +2024-11-21 19:58:42.022720: Epoch time: 18.73 s +2024-11-21 19:58:42.874472: +2024-11-21 19:58:42.874692: Epoch 1733 +2024-11-21 19:58:42.874805: Current learning rate: 0.00803 +2024-11-21 19:59:00.451597: train_loss -0.7705 +2024-11-21 19:59:00.457230: val_loss -0.7701 +2024-11-21 19:59:00.457343: Pseudo dice [0.8447] +2024-11-21 19:59:00.457422: Epoch time: 17.58 s +2024-11-21 19:59:01.403449: +2024-11-21 19:59:01.403679: Epoch 1734 +2024-11-21 19:59:01.403789: Current learning rate: 0.00803 +2024-11-21 19:59:19.630976: train_loss -0.7716 +2024-11-21 19:59:19.631271: val_loss -0.7607 +2024-11-21 19:59:19.631349: Pseudo dice [0.8406] +2024-11-21 19:59:19.631428: Epoch time: 18.23 s +2024-11-21 19:59:20.472276: +2024-11-21 19:59:20.472496: Epoch 1735 +2024-11-21 19:59:20.472609: Current learning rate: 0.00803 +2024-11-21 19:59:38.619637: train_loss -0.7615 +2024-11-21 19:59:38.619873: val_loss -0.7523 +2024-11-21 19:59:38.619950: Pseudo dice [0.8389] +2024-11-21 19:59:38.620037: Epoch time: 18.15 s +2024-11-21 19:59:39.532898: +2024-11-21 19:59:39.533127: Epoch 1736 +2024-11-21 19:59:39.533234: Current learning rate: 0.00802 +2024-11-21 19:59:58.080199: train_loss -0.7748 +2024-11-21 19:59:58.080426: val_loss -0.7569 +2024-11-21 19:59:58.084858: Pseudo dice [0.8338] +2024-11-21 19:59:58.085003: Epoch time: 18.55 s +2024-11-21 19:59:58.930984: +2024-11-21 19:59:58.931190: Epoch 1737 +2024-11-21 19:59:58.931307: Current learning rate: 0.00802 +2024-11-21 20:00:16.268118: train_loss -0.7682 +2024-11-21 20:00:16.268326: val_loss -0.742 +2024-11-21 20:00:16.268398: Pseudo dice [0.8258] +2024-11-21 20:00:16.268472: Epoch time: 17.34 s +2024-11-21 20:00:17.113690: +2024-11-21 20:00:17.113955: Epoch 1738 +2024-11-21 20:00:17.114070: Current learning rate: 0.00802 +2024-11-21 20:00:35.787967: train_loss -0.7723 +2024-11-21 20:00:35.788195: val_loss -0.7368 +2024-11-21 20:00:35.788270: Pseudo dice [0.8293] +2024-11-21 20:00:35.788348: Epoch time: 18.68 s +2024-11-21 20:00:36.635266: +2024-11-21 20:00:36.635499: Epoch 1739 +2024-11-21 20:00:36.635612: Current learning rate: 0.00802 +2024-11-21 20:00:54.738174: train_loss -0.7755 +2024-11-21 20:00:54.738433: val_loss -0.7659 +2024-11-21 20:00:54.738510: Pseudo dice [0.8453] +2024-11-21 20:00:54.738590: Epoch time: 18.1 s +2024-11-21 20:00:55.583609: +2024-11-21 20:00:55.583805: Epoch 1740 +2024-11-21 20:00:55.583916: Current learning rate: 0.00802 +2024-11-21 20:01:14.472272: train_loss -0.7669 +2024-11-21 20:01:14.472480: val_loss -0.7582 +2024-11-21 20:01:14.472553: Pseudo dice [0.8345] +2024-11-21 20:01:14.472627: Epoch time: 18.89 s +2024-11-21 20:01:15.312046: +2024-11-21 20:01:15.312253: Epoch 1741 +2024-11-21 20:01:15.312362: Current learning rate: 0.00802 +2024-11-21 20:01:33.525267: train_loss -0.7751 +2024-11-21 20:01:33.525529: val_loss -0.7526 +2024-11-21 20:01:33.525604: Pseudo dice [0.8236] +2024-11-21 20:01:33.525679: Epoch time: 18.21 s +2024-11-21 20:01:34.372787: +2024-11-21 20:01:34.373089: Epoch 1742 +2024-11-21 20:01:34.373224: Current learning rate: 0.00802 +2024-11-21 20:01:51.572205: train_loss -0.7741 +2024-11-21 20:01:51.572466: val_loss -0.7638 +2024-11-21 20:01:51.572543: Pseudo dice [0.8498] +2024-11-21 20:01:51.572628: Epoch time: 17.2 s +2024-11-21 20:01:52.438310: +2024-11-21 20:01:52.438514: Epoch 1743 +2024-11-21 20:01:52.438627: Current learning rate: 0.00802 +2024-11-21 20:02:11.276196: train_loss -0.7747 +2024-11-21 20:02:11.276431: val_loss -0.7593 +2024-11-21 20:02:11.276510: Pseudo dice [0.8312] +2024-11-21 20:02:11.276585: Epoch time: 18.84 s +2024-11-21 20:02:12.118047: +2024-11-21 20:02:12.118242: Epoch 1744 +2024-11-21 20:02:12.118356: Current learning rate: 0.00801 +2024-11-21 20:02:30.852071: train_loss -0.7673 +2024-11-21 20:02:30.852294: val_loss -0.7691 +2024-11-21 20:02:30.852371: Pseudo dice [0.8488] +2024-11-21 20:02:30.852445: Epoch time: 18.73 s +2024-11-21 20:02:31.693647: +2024-11-21 20:02:31.693876: Epoch 1745 +2024-11-21 20:02:31.693989: Current learning rate: 0.00801 +2024-11-21 20:02:51.012263: train_loss -0.7668 +2024-11-21 20:02:51.012510: val_loss -0.7389 +2024-11-21 20:02:51.012586: Pseudo dice [0.8033] +2024-11-21 20:02:51.012670: Epoch time: 19.32 s +2024-11-21 20:02:51.856976: +2024-11-21 20:02:51.857204: Epoch 1746 +2024-11-21 20:02:51.857314: Current learning rate: 0.00801 +2024-11-21 20:03:11.083147: train_loss -0.7583 +2024-11-21 20:03:11.083369: val_loss -0.7645 +2024-11-21 20:03:11.083446: Pseudo dice [0.8423] +2024-11-21 20:03:11.083524: Epoch time: 19.23 s +2024-11-21 20:03:11.930701: +2024-11-21 20:03:11.930917: Epoch 1747 +2024-11-21 20:03:11.931034: Current learning rate: 0.00801 +2024-11-21 20:03:29.792667: train_loss -0.7632 +2024-11-21 20:03:29.792887: val_loss -0.7576 +2024-11-21 20:03:29.792960: Pseudo dice [0.8364] +2024-11-21 20:03:29.793872: Epoch time: 17.86 s +2024-11-21 20:03:30.635180: +2024-11-21 20:03:30.635617: Epoch 1748 +2024-11-21 20:03:30.635751: Current learning rate: 0.00801 +2024-11-21 20:03:49.067275: train_loss -0.77 +2024-11-21 20:03:49.067491: val_loss -0.761 +2024-11-21 20:03:49.067567: Pseudo dice [0.8452] +2024-11-21 20:03:49.067646: Epoch time: 18.43 s +2024-11-21 20:03:49.971000: +2024-11-21 20:03:49.971431: Epoch 1749 +2024-11-21 20:03:49.971564: Current learning rate: 0.00801 +2024-11-21 20:04:08.537185: train_loss -0.7593 +2024-11-21 20:04:08.537441: val_loss -0.7697 +2024-11-21 20:04:08.537516: Pseudo dice [0.849] +2024-11-21 20:04:08.539806: Epoch time: 18.57 s +2024-11-21 20:04:09.675676: +2024-11-21 20:04:09.676109: Epoch 1750 +2024-11-21 20:04:09.676245: Current learning rate: 0.00801 +2024-11-21 20:04:27.792126: train_loss -0.7662 +2024-11-21 20:04:27.792380: val_loss -0.7852 +2024-11-21 20:04:27.792454: Pseudo dice [0.8492] +2024-11-21 20:04:27.792526: Epoch time: 18.12 s +2024-11-21 20:04:28.640090: +2024-11-21 20:04:28.640549: Epoch 1751 +2024-11-21 20:04:28.640686: Current learning rate: 0.00801 +2024-11-21 20:04:46.965717: train_loss -0.7656 +2024-11-21 20:04:46.965952: val_loss -0.7702 +2024-11-21 20:04:46.966034: Pseudo dice [0.8493] +2024-11-21 20:04:46.966178: Epoch time: 18.33 s +2024-11-21 20:04:47.827860: +2024-11-21 20:04:47.828288: Epoch 1752 +2024-11-21 20:04:47.828415: Current learning rate: 0.00801 +2024-11-21 20:05:05.758128: train_loss -0.7698 +2024-11-21 20:05:05.758343: val_loss -0.7634 +2024-11-21 20:05:05.758420: Pseudo dice [0.8545] +2024-11-21 20:05:05.758496: Epoch time: 17.93 s +2024-11-21 20:05:06.599303: +2024-11-21 20:05:06.599707: Epoch 1753 +2024-11-21 20:05:06.599836: Current learning rate: 0.008 +2024-11-21 20:05:24.941380: train_loss -0.7676 +2024-11-21 20:05:24.941622: val_loss -0.7655 +2024-11-21 20:05:24.941699: Pseudo dice [0.8435] +2024-11-21 20:05:24.941781: Epoch time: 18.34 s +2024-11-21 20:05:25.786071: +2024-11-21 20:05:25.786485: Epoch 1754 +2024-11-21 20:05:25.786616: Current learning rate: 0.008 +2024-11-21 20:05:43.624025: train_loss -0.7694 +2024-11-21 20:05:43.624244: val_loss -0.7395 +2024-11-21 20:05:43.624317: Pseudo dice [0.8305] +2024-11-21 20:05:43.624391: Epoch time: 17.84 s +2024-11-21 20:05:44.461917: +2024-11-21 20:05:44.462135: Epoch 1755 +2024-11-21 20:05:44.462244: Current learning rate: 0.008 +2024-11-21 20:06:03.094514: train_loss -0.7553 +2024-11-21 20:06:03.100152: val_loss -0.7287 +2024-11-21 20:06:03.100263: Pseudo dice [0.8268] +2024-11-21 20:06:03.100342: Epoch time: 18.63 s +2024-11-21 20:06:04.068492: +2024-11-21 20:06:04.068946: Epoch 1756 +2024-11-21 20:06:04.069085: Current learning rate: 0.008 +2024-11-21 20:06:22.740650: train_loss -0.7712 +2024-11-21 20:06:22.740891: val_loss -0.748 +2024-11-21 20:06:22.740965: Pseudo dice [0.8504] +2024-11-21 20:06:22.741050: Epoch time: 18.67 s +2024-11-21 20:06:23.603299: +2024-11-21 20:06:23.603528: Epoch 1757 +2024-11-21 20:06:23.603640: Current learning rate: 0.008 +2024-11-21 20:06:41.749589: train_loss -0.7669 +2024-11-21 20:06:41.749861: val_loss -0.769 +2024-11-21 20:06:41.749939: Pseudo dice [0.8412] +2024-11-21 20:06:41.750026: Epoch time: 18.15 s +2024-11-21 20:06:42.587206: +2024-11-21 20:06:42.587512: Epoch 1758 +2024-11-21 20:06:42.587626: Current learning rate: 0.008 +2024-11-21 20:07:01.848073: train_loss -0.7711 +2024-11-21 20:07:01.848281: val_loss -0.7654 +2024-11-21 20:07:01.848355: Pseudo dice [0.828] +2024-11-21 20:07:01.848430: Epoch time: 19.26 s +2024-11-21 20:07:02.697430: +2024-11-21 20:07:02.697681: Epoch 1759 +2024-11-21 20:07:02.697790: Current learning rate: 0.008 +2024-11-21 20:07:22.026692: train_loss -0.7715 +2024-11-21 20:07:22.026966: val_loss -0.747 +2024-11-21 20:07:22.027065: Pseudo dice [0.8395] +2024-11-21 20:07:22.027147: Epoch time: 19.33 s +2024-11-21 20:07:22.881527: +2024-11-21 20:07:22.881741: Epoch 1760 +2024-11-21 20:07:22.881851: Current learning rate: 0.008 +2024-11-21 20:07:41.293101: train_loss -0.7397 +2024-11-21 20:07:41.293349: val_loss -0.7405 +2024-11-21 20:07:41.298632: Pseudo dice [0.82] +2024-11-21 20:07:41.298763: Epoch time: 18.41 s +2024-11-21 20:07:42.228129: +2024-11-21 20:07:42.228354: Epoch 1761 +2024-11-21 20:07:42.228466: Current learning rate: 0.008 +2024-11-21 20:08:01.554115: train_loss -0.7561 +2024-11-21 20:08:01.554340: val_loss -0.7535 +2024-11-21 20:08:01.554415: Pseudo dice [0.8352] +2024-11-21 20:08:01.554491: Epoch time: 19.33 s +2024-11-21 20:08:02.405539: +2024-11-21 20:08:02.405746: Epoch 1762 +2024-11-21 20:08:02.405852: Current learning rate: 0.00799 +2024-11-21 20:08:21.312929: train_loss -0.7686 +2024-11-21 20:08:21.313157: val_loss -0.7564 +2024-11-21 20:08:21.313259: Pseudo dice [0.8368] +2024-11-21 20:08:21.313336: Epoch time: 18.91 s +2024-11-21 20:08:22.154634: +2024-11-21 20:08:22.154849: Epoch 1763 +2024-11-21 20:08:22.154967: Current learning rate: 0.00799 +2024-11-21 20:08:40.061902: train_loss -0.7655 +2024-11-21 20:08:40.064296: val_loss -0.7558 +2024-11-21 20:08:40.064398: Pseudo dice [0.8606] +2024-11-21 20:08:40.064481: Epoch time: 17.91 s +2024-11-21 20:08:41.093628: +2024-11-21 20:08:41.093887: Epoch 1764 +2024-11-21 20:08:41.094040: Current learning rate: 0.00799 +2024-11-21 20:08:59.625854: train_loss -0.7609 +2024-11-21 20:08:59.626128: val_loss -0.7802 +2024-11-21 20:08:59.626202: Pseudo dice [0.8437] +2024-11-21 20:08:59.626278: Epoch time: 18.53 s +2024-11-21 20:09:00.470064: +2024-11-21 20:09:00.470302: Epoch 1765 +2024-11-21 20:09:00.470421: Current learning rate: 0.00799 +2024-11-21 20:09:19.154422: train_loss -0.7621 +2024-11-21 20:09:19.154644: val_loss -0.7378 +2024-11-21 20:09:19.154779: Pseudo dice [0.8189] +2024-11-21 20:09:19.154859: Epoch time: 18.69 s +2024-11-21 20:09:20.331495: +2024-11-21 20:09:20.331732: Epoch 1766 +2024-11-21 20:09:20.331843: Current learning rate: 0.00799 +2024-11-21 20:09:37.899481: train_loss -0.7588 +2024-11-21 20:09:37.899747: val_loss -0.7813 +2024-11-21 20:09:37.899824: Pseudo dice [0.8382] +2024-11-21 20:09:37.899924: Epoch time: 17.57 s +2024-11-21 20:09:38.739194: +2024-11-21 20:09:38.739490: Epoch 1767 +2024-11-21 20:09:38.739605: Current learning rate: 0.00799 +2024-11-21 20:09:56.087977: train_loss -0.7722 +2024-11-21 20:09:56.088206: val_loss -0.7668 +2024-11-21 20:09:56.088299: Pseudo dice [0.8415] +2024-11-21 20:09:56.088379: Epoch time: 17.35 s +2024-11-21 20:09:56.927778: +2024-11-21 20:09:56.927998: Epoch 1768 +2024-11-21 20:09:56.928106: Current learning rate: 0.00799 +2024-11-21 20:10:15.465206: train_loss -0.7621 +2024-11-21 20:10:15.465430: val_loss -0.7749 +2024-11-21 20:10:15.465505: Pseudo dice [0.8348] +2024-11-21 20:10:15.465580: Epoch time: 18.54 s +2024-11-21 20:10:16.300009: +2024-11-21 20:10:16.300237: Epoch 1769 +2024-11-21 20:10:16.300342: Current learning rate: 0.00799 +2024-11-21 20:10:35.398116: train_loss -0.7747 +2024-11-21 20:10:35.398335: val_loss -0.7736 +2024-11-21 20:10:35.398408: Pseudo dice [0.8245] +2024-11-21 20:10:35.398483: Epoch time: 19.1 s +2024-11-21 20:10:36.248639: +2024-11-21 20:10:36.248888: Epoch 1770 +2024-11-21 20:10:36.249043: Current learning rate: 0.00798 +2024-11-21 20:10:55.723181: train_loss -0.771 +2024-11-21 20:10:55.724170: val_loss -0.7819 +2024-11-21 20:10:55.724247: Pseudo dice [0.8567] +2024-11-21 20:10:55.724325: Epoch time: 19.48 s +2024-11-21 20:10:56.570795: +2024-11-21 20:10:56.571025: Epoch 1771 +2024-11-21 20:10:56.571135: Current learning rate: 0.00798 +2024-11-21 20:11:15.482639: train_loss -0.7811 +2024-11-21 20:11:15.482924: val_loss -0.7631 +2024-11-21 20:11:15.483020: Pseudo dice [0.8374] +2024-11-21 20:11:15.483094: Epoch time: 18.91 s +2024-11-21 20:11:16.326242: +2024-11-21 20:11:16.326464: Epoch 1772 +2024-11-21 20:11:16.326581: Current learning rate: 0.00798 +2024-11-21 20:11:35.397803: train_loss -0.7641 +2024-11-21 20:11:35.398031: val_loss -0.7658 +2024-11-21 20:11:35.398109: Pseudo dice [0.8625] +2024-11-21 20:11:35.398192: Epoch time: 19.07 s +2024-11-21 20:11:36.242458: +2024-11-21 20:11:36.242685: Epoch 1773 +2024-11-21 20:11:36.242803: Current learning rate: 0.00798 +2024-11-21 20:11:55.018952: train_loss -0.78 +2024-11-21 20:11:55.024395: val_loss -0.7888 +2024-11-21 20:11:55.024556: Pseudo dice [0.8486] +2024-11-21 20:11:55.024920: Epoch time: 18.78 s +2024-11-21 20:11:55.991646: +2024-11-21 20:11:55.991864: Epoch 1774 +2024-11-21 20:11:55.991972: Current learning rate: 0.00798 +2024-11-21 20:12:13.735835: train_loss -0.781 +2024-11-21 20:12:13.736080: val_loss -0.7475 +2024-11-21 20:12:13.736155: Pseudo dice [0.8271] +2024-11-21 20:12:13.736233: Epoch time: 17.75 s +2024-11-21 20:12:14.584984: +2024-11-21 20:12:14.585202: Epoch 1775 +2024-11-21 20:12:14.585309: Current learning rate: 0.00798 +2024-11-21 20:12:32.810499: train_loss -0.7783 +2024-11-21 20:12:32.810718: val_loss -0.7591 +2024-11-21 20:12:32.810792: Pseudo dice [0.8415] +2024-11-21 20:12:32.810865: Epoch time: 18.23 s +2024-11-21 20:12:33.704306: +2024-11-21 20:12:33.704526: Epoch 1776 +2024-11-21 20:12:33.704644: Current learning rate: 0.00798 +2024-11-21 20:12:52.901963: train_loss -0.769 +2024-11-21 20:12:52.902220: val_loss -0.756 +2024-11-21 20:12:52.902300: Pseudo dice [0.8452] +2024-11-21 20:12:52.902443: Epoch time: 19.2 s +2024-11-21 20:12:53.761222: +2024-11-21 20:12:53.761439: Epoch 1777 +2024-11-21 20:12:53.761550: Current learning rate: 0.00798 +2024-11-21 20:13:12.873188: train_loss -0.7784 +2024-11-21 20:13:12.873680: val_loss -0.7692 +2024-11-21 20:13:12.873781: Pseudo dice [0.8427] +2024-11-21 20:13:12.873863: Epoch time: 19.11 s +2024-11-21 20:13:13.708787: +2024-11-21 20:13:13.709061: Epoch 1778 +2024-11-21 20:13:13.709171: Current learning rate: 0.00798 +2024-11-21 20:13:32.918868: train_loss -0.7619 +2024-11-21 20:13:32.919088: val_loss -0.767 +2024-11-21 20:13:32.919163: Pseudo dice [0.8482] +2024-11-21 20:13:32.919241: Epoch time: 19.21 s +2024-11-21 20:13:33.850915: +2024-11-21 20:13:33.851140: Epoch 1779 +2024-11-21 20:13:33.851247: Current learning rate: 0.00797 +2024-11-21 20:13:52.189874: train_loss -0.7566 +2024-11-21 20:13:52.192307: val_loss -0.777 +2024-11-21 20:13:52.192404: Pseudo dice [0.8326] +2024-11-21 20:13:52.192483: Epoch time: 18.34 s +2024-11-21 20:13:53.058269: +2024-11-21 20:13:53.058511: Epoch 1780 +2024-11-21 20:13:53.058620: Current learning rate: 0.00797 +2024-11-21 20:14:11.234467: train_loss -0.7608 +2024-11-21 20:14:11.234727: val_loss -0.7736 +2024-11-21 20:14:11.234805: Pseudo dice [0.8451] +2024-11-21 20:14:11.234907: Epoch time: 18.18 s +2024-11-21 20:14:12.104047: +2024-11-21 20:14:12.104282: Epoch 1781 +2024-11-21 20:14:12.104393: Current learning rate: 0.00797 +2024-11-21 20:14:29.231257: train_loss -0.7702 +2024-11-21 20:14:29.231500: val_loss -0.7353 +2024-11-21 20:14:29.231579: Pseudo dice [0.8181] +2024-11-21 20:14:29.231657: Epoch time: 17.13 s +2024-11-21 20:14:30.236253: +2024-11-21 20:14:30.236555: Epoch 1782 +2024-11-21 20:14:30.236667: Current learning rate: 0.00797 +2024-11-21 20:14:48.546636: train_loss -0.767 +2024-11-21 20:14:48.546849: val_loss -0.7282 +2024-11-21 20:14:48.546926: Pseudo dice [0.817] +2024-11-21 20:14:48.547013: Epoch time: 18.31 s +2024-11-21 20:14:49.416614: +2024-11-21 20:14:49.416834: Epoch 1783 +2024-11-21 20:14:49.416944: Current learning rate: 0.00797 +2024-11-21 20:15:08.622782: train_loss -0.7709 +2024-11-21 20:15:08.623019: val_loss -0.7702 +2024-11-21 20:15:08.623098: Pseudo dice [0.848] +2024-11-21 20:15:08.623178: Epoch time: 19.21 s +2024-11-21 20:15:09.468706: +2024-11-21 20:15:09.468963: Epoch 1784 +2024-11-21 20:15:09.469073: Current learning rate: 0.00797 +2024-11-21 20:15:27.584001: train_loss -0.7761 +2024-11-21 20:15:27.584586: val_loss -0.7615 +2024-11-21 20:15:27.584702: Pseudo dice [0.8426] +2024-11-21 20:15:27.584797: Epoch time: 18.11 s +2024-11-21 20:15:28.469874: +2024-11-21 20:15:28.470080: Epoch 1785 +2024-11-21 20:15:28.470189: Current learning rate: 0.00797 +2024-11-21 20:15:46.434810: train_loss -0.7817 +2024-11-21 20:15:46.435046: val_loss -0.7639 +2024-11-21 20:15:46.435129: Pseudo dice [0.8515] +2024-11-21 20:15:46.435216: Epoch time: 17.97 s +2024-11-21 20:15:47.503159: +2024-11-21 20:15:47.503358: Epoch 1786 +2024-11-21 20:15:47.503465: Current learning rate: 0.00797 +2024-11-21 20:16:06.247412: train_loss -0.7696 +2024-11-21 20:16:06.249795: val_loss -0.7553 +2024-11-21 20:16:06.249880: Pseudo dice [0.8348] +2024-11-21 20:16:06.249957: Epoch time: 18.75 s +2024-11-21 20:16:07.226836: +2024-11-21 20:16:07.227048: Epoch 1787 +2024-11-21 20:16:07.227169: Current learning rate: 0.00797 +2024-11-21 20:16:26.458062: train_loss -0.7775 +2024-11-21 20:16:26.458293: val_loss -0.7771 +2024-11-21 20:16:26.458392: Pseudo dice [0.8435] +2024-11-21 20:16:26.458467: Epoch time: 19.23 s +2024-11-21 20:16:27.830680: +2024-11-21 20:16:27.830906: Epoch 1788 +2024-11-21 20:16:27.831025: Current learning rate: 0.00796 +2024-11-21 20:16:46.737587: train_loss -0.7677 +2024-11-21 20:16:46.737833: val_loss -0.7473 +2024-11-21 20:16:46.737909: Pseudo dice [0.823] +2024-11-21 20:16:46.738016: Epoch time: 18.91 s +2024-11-21 20:16:47.588938: +2024-11-21 20:16:47.589179: Epoch 1789 +2024-11-21 20:16:47.589290: Current learning rate: 0.00796 +2024-11-21 20:17:05.126581: train_loss -0.7727 +2024-11-21 20:17:05.126789: val_loss -0.7607 +2024-11-21 20:17:05.129084: Pseudo dice [0.8281] +2024-11-21 20:17:05.129197: Epoch time: 17.54 s +2024-11-21 20:17:06.128364: +2024-11-21 20:17:06.128649: Epoch 1790 +2024-11-21 20:17:06.128762: Current learning rate: 0.00796 +2024-11-21 20:17:24.718102: train_loss -0.7715 +2024-11-21 20:17:24.718325: val_loss -0.7584 +2024-11-21 20:17:24.718399: Pseudo dice [0.834] +2024-11-21 20:17:24.718473: Epoch time: 18.59 s +2024-11-21 20:17:25.563946: +2024-11-21 20:17:25.564166: Epoch 1791 +2024-11-21 20:17:25.564281: Current learning rate: 0.00796 +2024-11-21 20:17:43.495973: train_loss -0.7784 +2024-11-21 20:17:43.496208: val_loss -0.7362 +2024-11-21 20:17:43.496284: Pseudo dice [0.8218] +2024-11-21 20:17:43.496362: Epoch time: 17.93 s +2024-11-21 20:17:44.363691: +2024-11-21 20:17:44.363921: Epoch 1792 +2024-11-21 20:17:44.364035: Current learning rate: 0.00796 +2024-11-21 20:18:02.652921: train_loss -0.7581 +2024-11-21 20:18:02.653234: val_loss -0.7622 +2024-11-21 20:18:02.653314: Pseudo dice [0.8358] +2024-11-21 20:18:02.653394: Epoch time: 18.29 s +2024-11-21 20:18:03.526652: +2024-11-21 20:18:03.526849: Epoch 1793 +2024-11-21 20:18:03.526956: Current learning rate: 0.00796 +2024-11-21 20:18:21.673777: train_loss -0.7669 +2024-11-21 20:18:21.674014: val_loss -0.7802 +2024-11-21 20:18:21.674097: Pseudo dice [0.837] +2024-11-21 20:18:21.674175: Epoch time: 18.15 s +2024-11-21 20:18:22.546133: +2024-11-21 20:18:22.546355: Epoch 1794 +2024-11-21 20:18:22.546465: Current learning rate: 0.00796 +2024-11-21 20:18:40.461030: train_loss -0.7682 +2024-11-21 20:18:40.461247: val_loss -0.7795 +2024-11-21 20:18:40.461321: Pseudo dice [0.8452] +2024-11-21 20:18:40.461399: Epoch time: 17.92 s +2024-11-21 20:18:41.307026: +2024-11-21 20:18:41.307245: Epoch 1795 +2024-11-21 20:18:41.307357: Current learning rate: 0.00796 +2024-11-21 20:18:59.949617: train_loss -0.7697 +2024-11-21 20:18:59.949865: val_loss -0.7768 +2024-11-21 20:18:59.949939: Pseudo dice [0.8551] +2024-11-21 20:18:59.950029: Epoch time: 18.64 s +2024-11-21 20:19:00.797882: +2024-11-21 20:19:00.798129: Epoch 1796 +2024-11-21 20:19:00.798251: Current learning rate: 0.00795 +2024-11-21 20:19:18.748272: train_loss -0.7647 +2024-11-21 20:19:18.748494: val_loss -0.7497 +2024-11-21 20:19:18.748569: Pseudo dice [0.8273] +2024-11-21 20:19:18.748646: Epoch time: 17.95 s +2024-11-21 20:19:19.588459: +2024-11-21 20:19:19.588675: Epoch 1797 +2024-11-21 20:19:19.588787: Current learning rate: 0.00795 +2024-11-21 20:19:38.076840: train_loss -0.7589 +2024-11-21 20:19:38.077061: val_loss -0.7389 +2024-11-21 20:19:38.077133: Pseudo dice [0.8228] +2024-11-21 20:19:38.079458: Epoch time: 18.49 s +2024-11-21 20:19:38.921242: +2024-11-21 20:19:38.921515: Epoch 1798 +2024-11-21 20:19:38.921625: Current learning rate: 0.00795 +2024-11-21 20:19:57.378564: train_loss -0.7695 +2024-11-21 20:19:57.382915: val_loss -0.7585 +2024-11-21 20:19:57.383074: Pseudo dice [0.8381] +2024-11-21 20:19:57.383156: Epoch time: 18.46 s +2024-11-21 20:19:58.247522: +2024-11-21 20:19:58.247750: Epoch 1799 +2024-11-21 20:19:58.247863: Current learning rate: 0.00795 +2024-11-21 20:20:16.363915: train_loss -0.7712 +2024-11-21 20:20:16.364386: val_loss -0.7876 +2024-11-21 20:20:16.364490: Pseudo dice [0.8509] +2024-11-21 20:20:16.364655: Epoch time: 18.12 s +2024-11-21 20:20:17.401543: +2024-11-21 20:20:17.401805: Epoch 1800 +2024-11-21 20:20:17.401915: Current learning rate: 0.00795 +2024-11-21 20:20:35.951758: train_loss -0.7756 +2024-11-21 20:20:35.951980: val_loss -0.7492 +2024-11-21 20:20:35.952067: Pseudo dice [0.8274] +2024-11-21 20:20:35.952143: Epoch time: 18.55 s +2024-11-21 20:20:36.790706: +2024-11-21 20:20:36.790938: Epoch 1801 +2024-11-21 20:20:36.791059: Current learning rate: 0.00795 +2024-11-21 20:20:54.702032: train_loss -0.7737 +2024-11-21 20:20:54.702251: val_loss -0.7731 +2024-11-21 20:20:54.702340: Pseudo dice [0.8295] +2024-11-21 20:20:54.702427: Epoch time: 17.91 s +2024-11-21 20:20:55.539279: +2024-11-21 20:20:55.539517: Epoch 1802 +2024-11-21 20:20:55.539628: Current learning rate: 0.00795 +2024-11-21 20:21:14.544737: train_loss -0.7638 +2024-11-21 20:21:14.544986: val_loss -0.7615 +2024-11-21 20:21:14.545069: Pseudo dice [0.8348] +2024-11-21 20:21:14.545148: Epoch time: 19.01 s +2024-11-21 20:21:15.425374: +2024-11-21 20:21:15.425661: Epoch 1803 +2024-11-21 20:21:15.425774: Current learning rate: 0.00795 +2024-11-21 20:21:33.349074: train_loss -0.7757 +2024-11-21 20:21:33.351459: val_loss -0.7504 +2024-11-21 20:21:33.351587: Pseudo dice [0.8621] +2024-11-21 20:21:33.351664: Epoch time: 17.92 s +2024-11-21 20:21:34.259861: +2024-11-21 20:21:34.260114: Epoch 1804 +2024-11-21 20:21:34.260222: Current learning rate: 0.00795 +2024-11-21 20:21:52.004382: train_loss -0.766 +2024-11-21 20:21:52.004598: val_loss -0.7609 +2024-11-21 20:21:52.004674: Pseudo dice [0.8429] +2024-11-21 20:21:52.004752: Epoch time: 17.75 s +2024-11-21 20:21:52.853967: +2024-11-21 20:21:52.854197: Epoch 1805 +2024-11-21 20:21:52.854309: Current learning rate: 0.00794 +2024-11-21 20:22:11.993714: train_loss -0.7566 +2024-11-21 20:22:11.994033: val_loss -0.7451 +2024-11-21 20:22:11.994116: Pseudo dice [0.8204] +2024-11-21 20:22:11.994195: Epoch time: 19.14 s +2024-11-21 20:22:12.845786: +2024-11-21 20:22:12.846028: Epoch 1806 +2024-11-21 20:22:12.846137: Current learning rate: 0.00794 +2024-11-21 20:22:30.660877: train_loss -0.7653 +2024-11-21 20:22:30.661120: val_loss -0.7439 +2024-11-21 20:22:30.661197: Pseudo dice [0.8305] +2024-11-21 20:22:30.661274: Epoch time: 17.82 s +2024-11-21 20:22:31.500092: +2024-11-21 20:22:31.500309: Epoch 1807 +2024-11-21 20:22:31.500417: Current learning rate: 0.00794 +2024-11-21 20:22:50.307185: train_loss -0.7698 +2024-11-21 20:22:50.307406: val_loss -0.7557 +2024-11-21 20:22:50.307492: Pseudo dice [0.8292] +2024-11-21 20:22:50.307567: Epoch time: 18.81 s +2024-11-21 20:22:51.152972: +2024-11-21 20:22:51.153189: Epoch 1808 +2024-11-21 20:22:51.153301: Current learning rate: 0.00794 +2024-11-21 20:23:09.639577: train_loss -0.7653 +2024-11-21 20:23:09.639788: val_loss -0.7624 +2024-11-21 20:23:09.639860: Pseudo dice [0.8498] +2024-11-21 20:23:09.639936: Epoch time: 18.49 s +2024-11-21 20:23:10.475947: +2024-11-21 20:23:10.476170: Epoch 1809 +2024-11-21 20:23:10.476290: Current learning rate: 0.00794 +2024-11-21 20:23:29.887518: train_loss -0.7699 +2024-11-21 20:23:29.887768: val_loss -0.7607 +2024-11-21 20:23:29.887845: Pseudo dice [0.8392] +2024-11-21 20:23:29.887950: Epoch time: 19.41 s +2024-11-21 20:23:30.726972: +2024-11-21 20:23:30.727191: Epoch 1810 +2024-11-21 20:23:30.727302: Current learning rate: 0.00794 +2024-11-21 20:23:49.486653: train_loss -0.7658 +2024-11-21 20:23:49.486931: val_loss -0.752 +2024-11-21 20:23:49.487013: Pseudo dice [0.8444] +2024-11-21 20:23:49.487090: Epoch time: 18.76 s +2024-11-21 20:23:50.329982: +2024-11-21 20:23:50.330216: Epoch 1811 +2024-11-21 20:23:50.330329: Current learning rate: 0.00794 +2024-11-21 20:24:08.610144: train_loss -0.7786 +2024-11-21 20:24:08.610390: val_loss -0.7858 +2024-11-21 20:24:08.610466: Pseudo dice [0.8668] +2024-11-21 20:24:08.610541: Epoch time: 18.28 s +2024-11-21 20:24:09.455454: +2024-11-21 20:24:09.455669: Epoch 1812 +2024-11-21 20:24:09.455781: Current learning rate: 0.00794 +2024-11-21 20:24:27.616058: train_loss -0.7628 +2024-11-21 20:24:27.616319: val_loss -0.7758 +2024-11-21 20:24:27.616395: Pseudo dice [0.8424] +2024-11-21 20:24:27.616478: Epoch time: 18.16 s +2024-11-21 20:24:28.489189: +2024-11-21 20:24:28.489419: Epoch 1813 +2024-11-21 20:24:28.489534: Current learning rate: 0.00794 +2024-11-21 20:24:46.514279: train_loss -0.7639 +2024-11-21 20:24:46.514495: val_loss -0.7594 +2024-11-21 20:24:46.514570: Pseudo dice [0.8229] +2024-11-21 20:24:46.514644: Epoch time: 18.03 s +2024-11-21 20:24:47.393281: +2024-11-21 20:24:47.393502: Epoch 1814 +2024-11-21 20:24:47.393613: Current learning rate: 0.00793 +2024-11-21 20:25:05.802282: train_loss -0.7537 +2024-11-21 20:25:05.802495: val_loss -0.7383 +2024-11-21 20:25:05.802570: Pseudo dice [0.8072] +2024-11-21 20:25:05.802643: Epoch time: 18.41 s +2024-11-21 20:25:06.717987: +2024-11-21 20:25:06.718208: Epoch 1815 +2024-11-21 20:25:06.718324: Current learning rate: 0.00793 +2024-11-21 20:25:25.425582: train_loss -0.7603 +2024-11-21 20:25:25.425809: val_loss -0.7568 +2024-11-21 20:25:25.425884: Pseudo dice [0.8468] +2024-11-21 20:25:25.425958: Epoch time: 18.71 s +2024-11-21 20:25:26.266120: +2024-11-21 20:25:26.266337: Epoch 1816 +2024-11-21 20:25:26.266457: Current learning rate: 0.00793 +2024-11-21 20:25:45.926667: train_loss -0.7697 +2024-11-21 20:25:45.926924: val_loss -0.7605 +2024-11-21 20:25:45.927014: Pseudo dice [0.8445] +2024-11-21 20:25:45.927100: Epoch time: 19.66 s +2024-11-21 20:25:46.772340: +2024-11-21 20:25:46.772554: Epoch 1817 +2024-11-21 20:25:46.772665: Current learning rate: 0.00793 +2024-11-21 20:26:05.122046: train_loss -0.7612 +2024-11-21 20:26:05.122257: val_loss -0.7363 +2024-11-21 20:26:05.122331: Pseudo dice [0.8446] +2024-11-21 20:26:05.122404: Epoch time: 18.35 s +2024-11-21 20:26:05.960844: +2024-11-21 20:26:05.961038: Epoch 1818 +2024-11-21 20:26:05.961152: Current learning rate: 0.00793 +2024-11-21 20:26:24.134211: train_loss -0.7419 +2024-11-21 20:26:24.134488: val_loss -0.7454 +2024-11-21 20:26:24.134567: Pseudo dice [0.8138] +2024-11-21 20:26:24.134646: Epoch time: 18.17 s +2024-11-21 20:26:24.976306: +2024-11-21 20:26:24.976584: Epoch 1819 +2024-11-21 20:26:24.976695: Current learning rate: 0.00793 +2024-11-21 20:26:43.432443: train_loss -0.7666 +2024-11-21 20:26:43.432674: val_loss -0.7713 +2024-11-21 20:26:43.432749: Pseudo dice [0.837] +2024-11-21 20:26:43.432825: Epoch time: 18.46 s +2024-11-21 20:26:44.366803: +2024-11-21 20:26:44.367033: Epoch 1820 +2024-11-21 20:26:44.367145: Current learning rate: 0.00793 +2024-11-21 20:27:02.184206: train_loss -0.7678 +2024-11-21 20:27:02.184457: val_loss -0.749 +2024-11-21 20:27:02.184534: Pseudo dice [0.823] +2024-11-21 20:27:02.184618: Epoch time: 17.82 s +2024-11-21 20:27:03.031760: +2024-11-21 20:27:03.031981: Epoch 1821 +2024-11-21 20:27:03.032098: Current learning rate: 0.00793 +2024-11-21 20:27:22.203670: train_loss -0.7679 +2024-11-21 20:27:22.203886: val_loss -0.7587 +2024-11-21 20:27:22.203962: Pseudo dice [0.8375] +2024-11-21 20:27:22.204042: Epoch time: 19.17 s +2024-11-21 20:27:23.442577: +2024-11-21 20:27:23.442803: Epoch 1822 +2024-11-21 20:27:23.442919: Current learning rate: 0.00792 +2024-11-21 20:27:42.270386: train_loss -0.7649 +2024-11-21 20:27:42.270629: val_loss -0.7486 +2024-11-21 20:27:42.270730: Pseudo dice [0.8516] +2024-11-21 20:27:42.270844: Epoch time: 18.83 s +2024-11-21 20:27:43.109946: +2024-11-21 20:27:43.110303: Epoch 1823 +2024-11-21 20:27:43.110424: Current learning rate: 0.00792 +2024-11-21 20:28:01.452452: train_loss -0.7666 +2024-11-21 20:28:01.452729: val_loss -0.7733 +2024-11-21 20:28:01.452807: Pseudo dice [0.8459] +2024-11-21 20:28:01.452890: Epoch time: 18.34 s +2024-11-21 20:28:02.297161: +2024-11-21 20:28:02.297392: Epoch 1824 +2024-11-21 20:28:02.297512: Current learning rate: 0.00792 +2024-11-21 20:28:21.005182: train_loss -0.7714 +2024-11-21 20:28:21.005461: val_loss -0.7419 +2024-11-21 20:28:21.005535: Pseudo dice [0.8438] +2024-11-21 20:28:21.005609: Epoch time: 18.71 s +2024-11-21 20:28:21.864011: +2024-11-21 20:28:21.864243: Epoch 1825 +2024-11-21 20:28:21.864361: Current learning rate: 0.00792 +2024-11-21 20:28:40.152117: train_loss -0.7726 +2024-11-21 20:28:40.152353: val_loss -0.7663 +2024-11-21 20:28:40.152682: Pseudo dice [0.8167] +2024-11-21 20:28:40.152773: Epoch time: 18.29 s +2024-11-21 20:28:41.093746: +2024-11-21 20:28:41.093966: Epoch 1826 +2024-11-21 20:28:41.094085: Current learning rate: 0.00792 +2024-11-21 20:28:59.306121: train_loss -0.7813 +2024-11-21 20:28:59.306341: val_loss -0.7701 +2024-11-21 20:28:59.306415: Pseudo dice [0.8416] +2024-11-21 20:28:59.306489: Epoch time: 18.21 s +2024-11-21 20:29:00.139061: +2024-11-21 20:29:00.139291: Epoch 1827 +2024-11-21 20:29:00.139406: Current learning rate: 0.00792 +2024-11-21 20:29:18.110565: train_loss -0.7764 +2024-11-21 20:29:18.110820: val_loss -0.7643 +2024-11-21 20:29:18.110894: Pseudo dice [0.8418] +2024-11-21 20:29:18.110976: Epoch time: 17.97 s +2024-11-21 20:29:18.954020: +2024-11-21 20:29:18.954234: Epoch 1828 +2024-11-21 20:29:18.954342: Current learning rate: 0.00792 +2024-11-21 20:29:37.356361: train_loss -0.7712 +2024-11-21 20:29:37.356590: val_loss -0.7678 +2024-11-21 20:29:37.356663: Pseudo dice [0.8394] +2024-11-21 20:29:37.356739: Epoch time: 18.4 s +2024-11-21 20:29:38.206441: +2024-11-21 20:29:38.206661: Epoch 1829 +2024-11-21 20:29:38.206781: Current learning rate: 0.00792 +2024-11-21 20:29:55.561749: train_loss -0.7784 +2024-11-21 20:29:55.561967: val_loss -0.7664 +2024-11-21 20:29:55.562080: Pseudo dice [0.8433] +2024-11-21 20:29:55.562158: Epoch time: 17.36 s +2024-11-21 20:29:56.401518: +2024-11-21 20:29:56.401771: Epoch 1830 +2024-11-21 20:29:56.401882: Current learning rate: 0.00792 +2024-11-21 20:30:14.796139: train_loss -0.7666 +2024-11-21 20:30:14.796365: val_loss -0.7758 +2024-11-21 20:30:14.796445: Pseudo dice [0.8617] +2024-11-21 20:30:14.796525: Epoch time: 18.4 s +2024-11-21 20:30:15.799774: +2024-11-21 20:30:15.799962: Epoch 1831 +2024-11-21 20:30:15.800077: Current learning rate: 0.00791 +2024-11-21 20:30:33.988003: train_loss -0.7638 +2024-11-21 20:30:33.988261: val_loss -0.7557 +2024-11-21 20:30:33.988341: Pseudo dice [0.8355] +2024-11-21 20:30:33.988423: Epoch time: 18.19 s +2024-11-21 20:30:34.830189: +2024-11-21 20:30:34.830454: Epoch 1832 +2024-11-21 20:30:34.830564: Current learning rate: 0.00791 +2024-11-21 20:30:53.611800: train_loss -0.7632 +2024-11-21 20:30:53.612023: val_loss -0.7534 +2024-11-21 20:30:53.612104: Pseudo dice [0.8528] +2024-11-21 20:30:53.612180: Epoch time: 18.78 s +2024-11-21 20:30:54.451543: +2024-11-21 20:30:54.451738: Epoch 1833 +2024-11-21 20:30:54.451851: Current learning rate: 0.00791 +2024-11-21 20:31:12.271073: train_loss -0.7734 +2024-11-21 20:31:12.271510: val_loss -0.7558 +2024-11-21 20:31:12.271609: Pseudo dice [0.852] +2024-11-21 20:31:12.271693: Epoch time: 17.82 s +2024-11-21 20:31:13.112766: +2024-11-21 20:31:13.113020: Epoch 1834 +2024-11-21 20:31:13.113148: Current learning rate: 0.00791 +2024-11-21 20:31:31.058070: train_loss -0.7711 +2024-11-21 20:31:31.058304: val_loss -0.7458 +2024-11-21 20:31:31.058380: Pseudo dice [0.8204] +2024-11-21 20:31:31.058457: Epoch time: 17.95 s +2024-11-21 20:31:31.933062: +2024-11-21 20:31:31.933300: Epoch 1835 +2024-11-21 20:31:31.933409: Current learning rate: 0.00791 +2024-11-21 20:31:50.393541: train_loss -0.7731 +2024-11-21 20:31:50.393769: val_loss -0.7688 +2024-11-21 20:31:50.393847: Pseudo dice [0.8432] +2024-11-21 20:31:50.393926: Epoch time: 18.46 s +2024-11-21 20:31:51.233995: +2024-11-21 20:31:51.234265: Epoch 1836 +2024-11-21 20:31:51.234374: Current learning rate: 0.00791 +2024-11-21 20:32:09.443221: train_loss -0.7696 +2024-11-21 20:32:09.443469: val_loss -0.7415 +2024-11-21 20:32:09.443544: Pseudo dice [0.8162] +2024-11-21 20:32:09.443626: Epoch time: 18.21 s +2024-11-21 20:32:10.283028: +2024-11-21 20:32:10.283250: Epoch 1837 +2024-11-21 20:32:10.283359: Current learning rate: 0.00791 +2024-11-21 20:32:28.051629: train_loss -0.7712 +2024-11-21 20:32:28.051862: val_loss -0.7524 +2024-11-21 20:32:28.051956: Pseudo dice [0.8457] +2024-11-21 20:32:28.052100: Epoch time: 17.77 s +2024-11-21 20:32:28.893091: +2024-11-21 20:32:28.893324: Epoch 1838 +2024-11-21 20:32:28.893435: Current learning rate: 0.00791 +2024-11-21 20:32:47.139832: train_loss -0.7612 +2024-11-21 20:32:47.140050: val_loss -0.7593 +2024-11-21 20:32:47.140131: Pseudo dice [0.8228] +2024-11-21 20:32:47.140208: Epoch time: 18.25 s +2024-11-21 20:32:47.976988: +2024-11-21 20:32:47.977218: Epoch 1839 +2024-11-21 20:32:47.977340: Current learning rate: 0.00791 +2024-11-21 20:33:06.993004: train_loss -0.7682 +2024-11-21 20:33:06.993218: val_loss -0.7881 +2024-11-21 20:33:06.993292: Pseudo dice [0.8361] +2024-11-21 20:33:06.993365: Epoch time: 19.02 s +2024-11-21 20:33:07.835810: +2024-11-21 20:33:07.836026: Epoch 1840 +2024-11-21 20:33:07.836134: Current learning rate: 0.0079 +2024-11-21 20:33:26.541161: train_loss -0.7631 +2024-11-21 20:33:26.541399: val_loss -0.7383 +2024-11-21 20:33:26.541472: Pseudo dice [0.8271] +2024-11-21 20:33:26.541556: Epoch time: 18.71 s +2024-11-21 20:33:27.496009: +2024-11-21 20:33:27.496221: Epoch 1841 +2024-11-21 20:33:27.496336: Current learning rate: 0.0079 +2024-11-21 20:33:45.648220: train_loss -0.7724 +2024-11-21 20:33:45.648444: val_loss -0.7276 +2024-11-21 20:33:45.648520: Pseudo dice [0.8241] +2024-11-21 20:33:45.648593: Epoch time: 18.15 s +2024-11-21 20:33:46.486629: +2024-11-21 20:33:46.486867: Epoch 1842 +2024-11-21 20:33:46.486978: Current learning rate: 0.0079 +2024-11-21 20:34:03.788970: train_loss -0.7666 +2024-11-21 20:34:03.789193: val_loss -0.7521 +2024-11-21 20:34:03.789268: Pseudo dice [0.8379] +2024-11-21 20:34:03.789359: Epoch time: 17.3 s +2024-11-21 20:34:04.629093: +2024-11-21 20:34:04.629333: Epoch 1843 +2024-11-21 20:34:04.629447: Current learning rate: 0.0079 +2024-11-21 20:34:23.076101: train_loss -0.774 +2024-11-21 20:34:23.076321: val_loss -0.7824 +2024-11-21 20:34:23.076399: Pseudo dice [0.8457] +2024-11-21 20:34:23.076475: Epoch time: 18.45 s +2024-11-21 20:34:23.914865: +2024-11-21 20:34:23.915080: Epoch 1844 +2024-11-21 20:34:23.915189: Current learning rate: 0.0079 +2024-11-21 20:34:42.255219: train_loss -0.7733 +2024-11-21 20:34:42.255454: val_loss -0.783 +2024-11-21 20:34:42.255529: Pseudo dice [0.8555] +2024-11-21 20:34:42.255610: Epoch time: 18.34 s +2024-11-21 20:34:43.484084: +2024-11-21 20:34:43.484308: Epoch 1845 +2024-11-21 20:34:43.484430: Current learning rate: 0.0079 +2024-11-21 20:35:01.090118: train_loss -0.7723 +2024-11-21 20:35:01.090342: val_loss -0.7368 +2024-11-21 20:35:01.090420: Pseudo dice [0.8138] +2024-11-21 20:35:01.090492: Epoch time: 17.61 s +2024-11-21 20:35:01.929596: +2024-11-21 20:35:01.929823: Epoch 1846 +2024-11-21 20:35:01.929938: Current learning rate: 0.0079 +2024-11-21 20:35:20.196055: train_loss -0.778 +2024-11-21 20:35:20.196281: val_loss -0.7277 +2024-11-21 20:35:20.196357: Pseudo dice [0.8348] +2024-11-21 20:35:20.196432: Epoch time: 18.27 s +2024-11-21 20:35:21.049280: +2024-11-21 20:35:21.049523: Epoch 1847 +2024-11-21 20:35:21.049636: Current learning rate: 0.0079 +2024-11-21 20:35:39.691305: train_loss -0.7738 +2024-11-21 20:35:39.691548: val_loss -0.7525 +2024-11-21 20:35:39.691623: Pseudo dice [0.8395] +2024-11-21 20:35:39.691703: Epoch time: 18.64 s +2024-11-21 20:35:40.638832: +2024-11-21 20:35:40.639072: Epoch 1848 +2024-11-21 20:35:40.639181: Current learning rate: 0.00789 +2024-11-21 20:35:59.904156: train_loss -0.7761 +2024-11-21 20:35:59.904397: val_loss -0.7779 +2024-11-21 20:35:59.904477: Pseudo dice [0.8331] +2024-11-21 20:35:59.904552: Epoch time: 19.27 s +2024-11-21 20:36:00.746793: +2024-11-21 20:36:00.747034: Epoch 1849 +2024-11-21 20:36:00.747144: Current learning rate: 0.00789 +2024-11-21 20:36:19.503805: train_loss -0.7678 +2024-11-21 20:36:19.506162: val_loss -0.7592 +2024-11-21 20:36:19.506296: Pseudo dice [0.8228] +2024-11-21 20:36:19.506377: Epoch time: 18.76 s +2024-11-21 20:36:20.563418: +2024-11-21 20:36:20.563629: Epoch 1850 +2024-11-21 20:36:20.563737: Current learning rate: 0.00789 +2024-11-21 20:36:38.669952: train_loss -0.7789 +2024-11-21 20:36:38.670173: val_loss -0.7533 +2024-11-21 20:36:38.670246: Pseudo dice [0.8382] +2024-11-21 20:36:38.670393: Epoch time: 18.11 s +2024-11-21 20:36:39.508755: +2024-11-21 20:36:39.508959: Epoch 1851 +2024-11-21 20:36:39.509081: Current learning rate: 0.00789 +2024-11-21 20:36:57.394159: train_loss -0.7691 +2024-11-21 20:36:57.394686: val_loss -0.7721 +2024-11-21 20:36:57.394775: Pseudo dice [0.83] +2024-11-21 20:36:57.394856: Epoch time: 17.89 s +2024-11-21 20:36:58.238958: +2024-11-21 20:36:58.239178: Epoch 1852 +2024-11-21 20:36:58.239284: Current learning rate: 0.00789 +2024-11-21 20:37:16.620986: train_loss -0.7631 +2024-11-21 20:37:16.621198: val_loss -0.7561 +2024-11-21 20:37:16.621270: Pseudo dice [0.851] +2024-11-21 20:37:16.621343: Epoch time: 18.38 s +2024-11-21 20:37:17.615402: +2024-11-21 20:37:17.615622: Epoch 1853 +2024-11-21 20:37:17.615731: Current learning rate: 0.00789 +2024-11-21 20:37:35.469630: train_loss -0.7746 +2024-11-21 20:37:35.469906: val_loss -0.7672 +2024-11-21 20:37:35.469984: Pseudo dice [0.8298] +2024-11-21 20:37:35.470066: Epoch time: 17.86 s +2024-11-21 20:37:36.311139: +2024-11-21 20:37:36.311346: Epoch 1854 +2024-11-21 20:37:36.311454: Current learning rate: 0.00789 +2024-11-21 20:37:55.987033: train_loss -0.7607 +2024-11-21 20:37:55.987283: val_loss -0.7449 +2024-11-21 20:37:55.987369: Pseudo dice [0.8237] +2024-11-21 20:37:55.987458: Epoch time: 19.68 s +2024-11-21 20:37:56.820804: +2024-11-21 20:37:56.821034: Epoch 1855 +2024-11-21 20:37:56.821164: Current learning rate: 0.00789 +2024-11-21 20:38:15.285054: train_loss -0.7615 +2024-11-21 20:38:15.285273: val_loss -0.7664 +2024-11-21 20:38:15.285347: Pseudo dice [0.8449] +2024-11-21 20:38:15.285425: Epoch time: 18.47 s +2024-11-21 20:38:16.532411: +2024-11-21 20:38:16.532658: Epoch 1856 +2024-11-21 20:38:16.532768: Current learning rate: 0.00789 +2024-11-21 20:38:34.765369: train_loss -0.7665 +2024-11-21 20:38:34.765589: val_loss -0.7543 +2024-11-21 20:38:34.765665: Pseudo dice [0.8308] +2024-11-21 20:38:34.765740: Epoch time: 18.23 s +2024-11-21 20:38:35.786233: +2024-11-21 20:38:35.786462: Epoch 1857 +2024-11-21 20:38:35.786576: Current learning rate: 0.00788 +2024-11-21 20:38:54.083287: train_loss -0.769 +2024-11-21 20:38:54.083497: val_loss -0.7594 +2024-11-21 20:38:54.083570: Pseudo dice [0.8523] +2024-11-21 20:38:54.083672: Epoch time: 18.3 s +2024-11-21 20:38:55.031731: +2024-11-21 20:38:55.032003: Epoch 1858 +2024-11-21 20:38:55.032155: Current learning rate: 0.00788 +2024-11-21 20:39:14.767258: train_loss -0.7617 +2024-11-21 20:39:14.767475: val_loss -0.7721 +2024-11-21 20:39:14.767553: Pseudo dice [0.8419] +2024-11-21 20:39:14.767632: Epoch time: 19.74 s +2024-11-21 20:39:15.642906: +2024-11-21 20:39:15.643150: Epoch 1859 +2024-11-21 20:39:15.643266: Current learning rate: 0.00788 +2024-11-21 20:39:34.404201: train_loss -0.7683 +2024-11-21 20:39:34.404466: val_loss -0.7679 +2024-11-21 20:39:34.404544: Pseudo dice [0.8314] +2024-11-21 20:39:34.404618: Epoch time: 18.76 s +2024-11-21 20:39:35.249876: +2024-11-21 20:39:35.250113: Epoch 1860 +2024-11-21 20:39:35.250231: Current learning rate: 0.00788 +2024-11-21 20:39:54.135083: train_loss -0.7741 +2024-11-21 20:39:54.135295: val_loss -0.7806 +2024-11-21 20:39:54.135367: Pseudo dice [0.8393] +2024-11-21 20:39:54.135443: Epoch time: 18.89 s +2024-11-21 20:39:55.057733: +2024-11-21 20:39:55.058009: Epoch 1861 +2024-11-21 20:39:55.058123: Current learning rate: 0.00788 +2024-11-21 20:40:13.612624: train_loss -0.7748 +2024-11-21 20:40:13.614852: val_loss -0.7635 +2024-11-21 20:40:13.614972: Pseudo dice [0.842] +2024-11-21 20:40:13.615062: Epoch time: 18.56 s +2024-11-21 20:40:14.461439: +2024-11-21 20:40:14.461669: Epoch 1862 +2024-11-21 20:40:14.461778: Current learning rate: 0.00788 +2024-11-21 20:40:33.899026: train_loss -0.773 +2024-11-21 20:40:33.899282: val_loss -0.7803 +2024-11-21 20:40:33.899368: Pseudo dice [0.853] +2024-11-21 20:40:33.899464: Epoch time: 19.44 s +2024-11-21 20:40:34.811689: +2024-11-21 20:40:34.811918: Epoch 1863 +2024-11-21 20:40:34.812035: Current learning rate: 0.00788 +2024-11-21 20:40:52.942022: train_loss -0.777 +2024-11-21 20:40:52.942247: val_loss -0.7642 +2024-11-21 20:40:52.942327: Pseudo dice [0.8393] +2024-11-21 20:40:52.942461: Epoch time: 18.13 s +2024-11-21 20:40:53.781390: +2024-11-21 20:40:53.781602: Epoch 1864 +2024-11-21 20:40:53.781740: Current learning rate: 0.00788 +2024-11-21 20:41:12.379925: train_loss -0.7779 +2024-11-21 20:41:12.380148: val_loss -0.7753 +2024-11-21 20:41:12.380223: Pseudo dice [0.8526] +2024-11-21 20:41:12.380299: Epoch time: 18.6 s +2024-11-21 20:41:13.217391: +2024-11-21 20:41:13.217612: Epoch 1865 +2024-11-21 20:41:13.217722: Current learning rate: 0.00788 +2024-11-21 20:41:31.401779: train_loss -0.7671 +2024-11-21 20:41:31.402043: val_loss -0.7527 +2024-11-21 20:41:31.402121: Pseudo dice [0.8419] +2024-11-21 20:41:31.402203: Epoch time: 18.19 s +2024-11-21 20:41:32.242967: +2024-11-21 20:41:32.243193: Epoch 1866 +2024-11-21 20:41:32.243301: Current learning rate: 0.00787 +2024-11-21 20:41:52.303897: train_loss -0.7747 +2024-11-21 20:41:52.304117: val_loss -0.7763 +2024-11-21 20:41:52.304191: Pseudo dice [0.8418] +2024-11-21 20:41:52.304270: Epoch time: 20.06 s +2024-11-21 20:41:53.154863: +2024-11-21 20:41:53.155389: Epoch 1867 +2024-11-21 20:41:53.155504: Current learning rate: 0.00787 +2024-11-21 20:42:12.076165: train_loss -0.774 +2024-11-21 20:42:12.076372: val_loss -0.7501 +2024-11-21 20:42:12.076446: Pseudo dice [0.8201] +2024-11-21 20:42:12.076517: Epoch time: 18.92 s +2024-11-21 20:42:13.448333: +2024-11-21 20:42:13.448753: Epoch 1868 +2024-11-21 20:42:13.448885: Current learning rate: 0.00787 +2024-11-21 20:42:31.407917: train_loss -0.7649 +2024-11-21 20:42:31.408169: val_loss -0.7707 +2024-11-21 20:42:31.408247: Pseudo dice [0.8477] +2024-11-21 20:42:31.408329: Epoch time: 17.96 s +2024-11-21 20:42:32.244961: +2024-11-21 20:42:32.245422: Epoch 1869 +2024-11-21 20:42:32.245559: Current learning rate: 0.00787 +2024-11-21 20:42:49.961927: train_loss -0.7701 +2024-11-21 20:42:49.962149: val_loss -0.7454 +2024-11-21 20:42:49.962225: Pseudo dice [0.8341] +2024-11-21 20:42:49.962299: Epoch time: 17.72 s +2024-11-21 20:42:50.797277: +2024-11-21 20:42:50.797703: Epoch 1870 +2024-11-21 20:42:50.797834: Current learning rate: 0.00787 +2024-11-21 20:43:08.988028: train_loss -0.778 +2024-11-21 20:43:08.988283: val_loss -0.7394 +2024-11-21 20:43:08.988358: Pseudo dice [0.8362] +2024-11-21 20:43:08.988434: Epoch time: 18.19 s +2024-11-21 20:43:09.940436: +2024-11-21 20:43:09.940897: Epoch 1871 +2024-11-21 20:43:09.941041: Current learning rate: 0.00787 +2024-11-21 20:43:28.072478: train_loss -0.7709 +2024-11-21 20:43:28.072701: val_loss -0.7364 +2024-11-21 20:43:28.072777: Pseudo dice [0.8413] +2024-11-21 20:43:28.072858: Epoch time: 18.13 s +2024-11-21 20:43:28.921690: +2024-11-21 20:43:28.922109: Epoch 1872 +2024-11-21 20:43:28.922235: Current learning rate: 0.00787 +2024-11-21 20:43:47.945626: train_loss -0.7778 +2024-11-21 20:43:47.945850: val_loss -0.788 +2024-11-21 20:43:47.945925: Pseudo dice [0.8608] +2024-11-21 20:43:47.946010: Epoch time: 19.02 s +2024-11-21 20:43:48.786260: +2024-11-21 20:43:48.786697: Epoch 1873 +2024-11-21 20:43:48.786827: Current learning rate: 0.00787 +2024-11-21 20:44:08.225318: train_loss -0.7786 +2024-11-21 20:44:08.225541: val_loss -0.7366 +2024-11-21 20:44:08.225618: Pseudo dice [0.8271] +2024-11-21 20:44:08.225701: Epoch time: 19.44 s +2024-11-21 20:44:09.063341: +2024-11-21 20:44:09.063950: Epoch 1874 +2024-11-21 20:44:09.064091: Current learning rate: 0.00786 +2024-11-21 20:44:28.669086: train_loss -0.7661 +2024-11-21 20:44:28.669304: val_loss -0.778 +2024-11-21 20:44:28.669378: Pseudo dice [0.8407] +2024-11-21 20:44:28.669451: Epoch time: 19.61 s +2024-11-21 20:44:29.637783: +2024-11-21 20:44:29.638205: Epoch 1875 +2024-11-21 20:44:29.638336: Current learning rate: 0.00786 +2024-11-21 20:44:48.090456: train_loss -0.7652 +2024-11-21 20:44:48.090700: val_loss -0.763 +2024-11-21 20:44:48.090776: Pseudo dice [0.8489] +2024-11-21 20:44:48.090855: Epoch time: 18.45 s +2024-11-21 20:44:48.946257: +2024-11-21 20:44:48.946669: Epoch 1876 +2024-11-21 20:44:48.946797: Current learning rate: 0.00786 +2024-11-21 20:45:07.256771: train_loss -0.7714 +2024-11-21 20:45:07.257024: val_loss -0.7623 +2024-11-21 20:45:07.259313: Pseudo dice [0.8571] +2024-11-21 20:45:07.259421: Epoch time: 18.31 s +2024-11-21 20:45:08.262191: +2024-11-21 20:45:08.262619: Epoch 1877 +2024-11-21 20:45:08.262754: Current learning rate: 0.00786 +2024-11-21 20:45:26.482543: train_loss -0.7748 +2024-11-21 20:45:26.483019: val_loss -0.7425 +2024-11-21 20:45:26.483109: Pseudo dice [0.827] +2024-11-21 20:45:26.483185: Epoch time: 18.22 s +2024-11-21 20:45:27.319934: +2024-11-21 20:45:27.320366: Epoch 1878 +2024-11-21 20:45:27.320495: Current learning rate: 0.00786 +2024-11-21 20:45:44.565954: train_loss -0.78 +2024-11-21 20:45:44.566197: val_loss -0.7654 +2024-11-21 20:45:44.566271: Pseudo dice [0.8326] +2024-11-21 20:45:44.566347: Epoch time: 17.25 s +2024-11-21 20:45:45.405683: +2024-11-21 20:45:45.405896: Epoch 1879 +2024-11-21 20:45:45.406014: Current learning rate: 0.00786 +2024-11-21 20:46:04.974920: train_loss -0.7622 +2024-11-21 20:46:04.975449: val_loss -0.7805 +2024-11-21 20:46:04.975548: Pseudo dice [0.8488] +2024-11-21 20:46:04.975900: Epoch time: 19.57 s +2024-11-21 20:46:05.813595: +2024-11-21 20:46:05.813801: Epoch 1880 +2024-11-21 20:46:05.813910: Current learning rate: 0.00786 +2024-11-21 20:46:24.176093: train_loss -0.7686 +2024-11-21 20:46:24.176325: val_loss -0.759 +2024-11-21 20:46:24.176399: Pseudo dice [0.8326] +2024-11-21 20:46:24.176491: Epoch time: 18.36 s +2024-11-21 20:46:25.018236: +2024-11-21 20:46:25.018541: Epoch 1881 +2024-11-21 20:46:25.018654: Current learning rate: 0.00786 +2024-11-21 20:46:43.469500: train_loss -0.7582 +2024-11-21 20:46:43.470911: val_loss -0.7443 +2024-11-21 20:46:43.471116: Pseudo dice [0.8175] +2024-11-21 20:46:43.471208: Epoch time: 18.45 s +2024-11-21 20:46:44.316378: +2024-11-21 20:46:44.316607: Epoch 1882 +2024-11-21 20:46:44.316717: Current learning rate: 0.00786 +2024-11-21 20:47:02.706247: train_loss -0.7583 +2024-11-21 20:47:02.706493: val_loss -0.7659 +2024-11-21 20:47:02.706568: Pseudo dice [0.8434] +2024-11-21 20:47:02.706647: Epoch time: 18.39 s +2024-11-21 20:47:03.656919: +2024-11-21 20:47:03.657132: Epoch 1883 +2024-11-21 20:47:03.657241: Current learning rate: 0.00785 +2024-11-21 20:47:21.066968: train_loss -0.763 +2024-11-21 20:47:21.067183: val_loss -0.7641 +2024-11-21 20:47:21.067255: Pseudo dice [0.8396] +2024-11-21 20:47:21.067363: Epoch time: 17.41 s +2024-11-21 20:47:21.923879: +2024-11-21 20:47:21.924100: Epoch 1884 +2024-11-21 20:47:21.924225: Current learning rate: 0.00785 +2024-11-21 20:47:40.273288: train_loss -0.7756 +2024-11-21 20:47:40.273504: val_loss -0.7446 +2024-11-21 20:47:40.273580: Pseudo dice [0.8346] +2024-11-21 20:47:40.273657: Epoch time: 18.35 s +2024-11-21 20:47:41.115271: +2024-11-21 20:47:41.115546: Epoch 1885 +2024-11-21 20:47:41.115659: Current learning rate: 0.00785 +2024-11-21 20:47:58.707481: train_loss -0.7666 +2024-11-21 20:47:58.707748: val_loss -0.7669 +2024-11-21 20:47:58.707822: Pseudo dice [0.8341] +2024-11-21 20:47:58.707897: Epoch time: 17.59 s +2024-11-21 20:47:59.553585: +2024-11-21 20:47:59.553817: Epoch 1886 +2024-11-21 20:47:59.553937: Current learning rate: 0.00785 +2024-11-21 20:48:18.080696: train_loss -0.7598 +2024-11-21 20:48:18.080949: val_loss -0.7633 +2024-11-21 20:48:18.081032: Pseudo dice [0.8264] +2024-11-21 20:48:18.081112: Epoch time: 18.53 s +2024-11-21 20:48:18.922198: +2024-11-21 20:48:18.922406: Epoch 1887 +2024-11-21 20:48:18.922514: Current learning rate: 0.00785 +2024-11-21 20:48:37.653203: train_loss -0.7386 +2024-11-21 20:48:37.653419: val_loss -0.7173 +2024-11-21 20:48:37.653502: Pseudo dice [0.8236] +2024-11-21 20:48:37.653575: Epoch time: 18.73 s +2024-11-21 20:48:38.496331: +2024-11-21 20:48:38.496532: Epoch 1888 +2024-11-21 20:48:38.496646: Current learning rate: 0.00785 +2024-11-21 20:48:58.260901: train_loss -0.7473 +2024-11-21 20:48:58.261135: val_loss -0.7498 +2024-11-21 20:48:58.261212: Pseudo dice [0.8383] +2024-11-21 20:48:58.261297: Epoch time: 19.77 s +2024-11-21 20:48:59.119234: +2024-11-21 20:48:59.119450: Epoch 1889 +2024-11-21 20:48:59.119562: Current learning rate: 0.00785 +2024-11-21 20:49:18.705376: train_loss -0.7503 +2024-11-21 20:49:18.705624: val_loss -0.7495 +2024-11-21 20:49:18.705707: Pseudo dice [0.833] +2024-11-21 20:49:18.705795: Epoch time: 19.59 s +2024-11-21 20:49:19.579419: +2024-11-21 20:49:19.579631: Epoch 1890 +2024-11-21 20:49:19.579739: Current learning rate: 0.00785 +2024-11-21 20:49:37.576117: train_loss -0.7641 +2024-11-21 20:49:37.576330: val_loss -0.7637 +2024-11-21 20:49:37.576406: Pseudo dice [0.8388] +2024-11-21 20:49:37.578713: Epoch time: 18.0 s +2024-11-21 20:49:38.608114: +2024-11-21 20:49:38.608363: Epoch 1891 +2024-11-21 20:49:38.608493: Current learning rate: 0.00784 +2024-11-21 20:49:56.758767: train_loss -0.7609 +2024-11-21 20:49:56.759046: val_loss -0.7692 +2024-11-21 20:49:56.759123: Pseudo dice [0.829] +2024-11-21 20:49:56.759196: Epoch time: 18.15 s +2024-11-21 20:49:57.600329: +2024-11-21 20:49:57.600581: Epoch 1892 +2024-11-21 20:49:57.600689: Current learning rate: 0.00784 +2024-11-21 20:50:15.313314: train_loss -0.7634 +2024-11-21 20:50:15.328273: val_loss -0.7493 +2024-11-21 20:50:15.328427: Pseudo dice [0.8413] +2024-11-21 20:50:15.328524: Epoch time: 17.71 s +2024-11-21 20:50:16.168288: +2024-11-21 20:50:16.168483: Epoch 1893 +2024-11-21 20:50:16.168591: Current learning rate: 0.00784 +2024-11-21 20:50:35.300304: train_loss -0.7605 +2024-11-21 20:50:35.300522: val_loss -0.7724 +2024-11-21 20:50:35.300596: Pseudo dice [0.8519] +2024-11-21 20:50:35.300672: Epoch time: 19.13 s +2024-11-21 20:50:36.142466: +2024-11-21 20:50:36.142712: Epoch 1894 +2024-11-21 20:50:36.142842: Current learning rate: 0.00784 +2024-11-21 20:50:53.400425: train_loss -0.7778 +2024-11-21 20:50:53.400647: val_loss -0.7528 +2024-11-21 20:50:53.400721: Pseudo dice [0.8347] +2024-11-21 20:50:53.400851: Epoch time: 17.26 s +2024-11-21 20:50:54.251591: +2024-11-21 20:50:54.251832: Epoch 1895 +2024-11-21 20:50:54.251949: Current learning rate: 0.00784 +2024-11-21 20:51:12.698818: train_loss -0.7785 +2024-11-21 20:51:12.699044: val_loss -0.7407 +2024-11-21 20:51:12.699120: Pseudo dice [0.8357] +2024-11-21 20:51:12.699195: Epoch time: 18.45 s +2024-11-21 20:51:13.541466: +2024-11-21 20:51:13.541707: Epoch 1896 +2024-11-21 20:51:13.541817: Current learning rate: 0.00784 +2024-11-21 20:51:32.332573: train_loss -0.7665 +2024-11-21 20:51:32.332883: val_loss -0.7878 +2024-11-21 20:51:32.332960: Pseudo dice [0.8482] +2024-11-21 20:51:32.333048: Epoch time: 18.79 s +2024-11-21 20:51:33.178609: +2024-11-21 20:51:33.178823: Epoch 1897 +2024-11-21 20:51:33.178930: Current learning rate: 0.00784 +2024-11-21 20:51:50.667821: train_loss -0.768 +2024-11-21 20:51:50.668041: val_loss -0.764 +2024-11-21 20:51:50.668118: Pseudo dice [0.838] +2024-11-21 20:51:50.668190: Epoch time: 17.49 s +2024-11-21 20:51:51.500714: +2024-11-21 20:51:51.500924: Epoch 1898 +2024-11-21 20:51:51.501032: Current learning rate: 0.00784 +2024-11-21 20:52:10.177259: train_loss -0.7665 +2024-11-21 20:52:10.177474: val_loss -0.7649 +2024-11-21 20:52:10.177552: Pseudo dice [0.8328] +2024-11-21 20:52:10.177629: Epoch time: 18.68 s +2024-11-21 20:52:11.032075: +2024-11-21 20:52:11.032287: Epoch 1899 +2024-11-21 20:52:11.032396: Current learning rate: 0.00784 +2024-11-21 20:52:29.364557: train_loss -0.7654 +2024-11-21 20:52:29.364776: val_loss -0.7711 +2024-11-21 20:52:29.364851: Pseudo dice [0.8253] +2024-11-21 20:52:29.364930: Epoch time: 18.33 s +2024-11-21 20:52:30.436492: +2024-11-21 20:52:30.436724: Epoch 1900 +2024-11-21 20:52:30.436832: Current learning rate: 0.00783 +2024-11-21 20:52:49.073982: train_loss -0.7653 +2024-11-21 20:52:49.074239: val_loss -0.7718 +2024-11-21 20:52:49.074319: Pseudo dice [0.8274] +2024-11-21 20:52:49.074399: Epoch time: 18.64 s +2024-11-21 20:52:49.896809: +2024-11-21 20:52:49.896987: Epoch 1901 +2024-11-21 20:52:49.897081: Current learning rate: 0.00783 +2024-11-21 20:53:08.528776: train_loss -0.7473 +2024-11-21 20:53:08.528983: val_loss -0.7511 +2024-11-21 20:53:08.529067: Pseudo dice [0.83] +2024-11-21 20:53:08.529141: Epoch time: 18.63 s +2024-11-21 20:53:09.372241: +2024-11-21 20:53:09.372455: Epoch 1902 +2024-11-21 20:53:09.372560: Current learning rate: 0.00783 +2024-11-21 20:53:28.410141: train_loss -0.7712 +2024-11-21 20:53:28.410353: val_loss -0.7385 +2024-11-21 20:53:28.410429: Pseudo dice [0.8385] +2024-11-21 20:53:28.410506: Epoch time: 19.04 s +2024-11-21 20:53:29.249930: +2024-11-21 20:53:29.250200: Epoch 1903 +2024-11-21 20:53:29.250307: Current learning rate: 0.00783 +2024-11-21 20:53:47.525049: train_loss -0.7767 +2024-11-21 20:53:47.525604: val_loss -0.7346 +2024-11-21 20:53:47.525692: Pseudo dice [0.8461] +2024-11-21 20:53:47.525773: Epoch time: 18.28 s +2024-11-21 20:53:48.376609: +2024-11-21 20:53:48.376847: Epoch 1904 +2024-11-21 20:53:48.376958: Current learning rate: 0.00783 +2024-11-21 20:54:08.025043: train_loss -0.784 +2024-11-21 20:54:08.025245: val_loss -0.7762 +2024-11-21 20:54:08.025316: Pseudo dice [0.8498] +2024-11-21 20:54:08.025388: Epoch time: 19.65 s +2024-11-21 20:54:08.890872: +2024-11-21 20:54:08.891098: Epoch 1905 +2024-11-21 20:54:08.906708: Current learning rate: 0.00783 +2024-11-21 20:54:28.045853: train_loss -0.7688 +2024-11-21 20:54:28.046079: val_loss -0.763 +2024-11-21 20:54:28.046154: Pseudo dice [0.836] +2024-11-21 20:54:28.046231: Epoch time: 19.16 s +2024-11-21 20:54:28.894365: +2024-11-21 20:54:28.894562: Epoch 1906 +2024-11-21 20:54:28.894670: Current learning rate: 0.00783 +2024-11-21 20:54:47.826984: train_loss -0.7728 +2024-11-21 20:54:47.827206: val_loss -0.7677 +2024-11-21 20:54:47.827283: Pseudo dice [0.8501] +2024-11-21 20:54:47.827358: Epoch time: 18.93 s +2024-11-21 20:54:48.672641: +2024-11-21 20:54:48.672839: Epoch 1907 +2024-11-21 20:54:48.672949: Current learning rate: 0.00783 +2024-11-21 20:55:06.461795: train_loss -0.7654 +2024-11-21 20:55:06.467261: val_loss -0.7801 +2024-11-21 20:55:06.467382: Pseudo dice [0.8612] +2024-11-21 20:55:06.467475: Epoch time: 17.79 s +2024-11-21 20:55:07.490307: +2024-11-21 20:55:07.490638: Epoch 1908 +2024-11-21 20:55:07.490753: Current learning rate: 0.00783 +2024-11-21 20:55:27.232444: train_loss -0.7782 +2024-11-21 20:55:27.232659: val_loss -0.7801 +2024-11-21 20:55:27.232736: Pseudo dice [0.8485] +2024-11-21 20:55:27.232814: Epoch time: 19.74 s +2024-11-21 20:55:28.154655: +2024-11-21 20:55:28.154858: Epoch 1909 +2024-11-21 20:55:28.154965: Current learning rate: 0.00782 +2024-11-21 20:55:45.950111: train_loss -0.7809 +2024-11-21 20:55:45.950337: val_loss -0.7715 +2024-11-21 20:55:45.950411: Pseudo dice [0.8495] +2024-11-21 20:55:45.950487: Epoch time: 17.8 s +2024-11-21 20:55:46.799888: +2024-11-21 20:55:46.800108: Epoch 1910 +2024-11-21 20:55:46.800224: Current learning rate: 0.00782 +2024-11-21 20:56:05.450749: train_loss -0.7825 +2024-11-21 20:56:05.450975: val_loss -0.7695 +2024-11-21 20:56:05.451062: Pseudo dice [0.8485] +2024-11-21 20:56:05.451142: Epoch time: 18.65 s +2024-11-21 20:56:06.297944: +2024-11-21 20:56:06.298162: Epoch 1911 +2024-11-21 20:56:06.298270: Current learning rate: 0.00782 +2024-11-21 20:56:25.486544: train_loss -0.7695 +2024-11-21 20:56:25.486789: val_loss -0.7576 +2024-11-21 20:56:25.486871: Pseudo dice [0.8458] +2024-11-21 20:56:25.486954: Epoch time: 19.19 s +2024-11-21 20:56:26.377263: +2024-11-21 20:56:26.377479: Epoch 1912 +2024-11-21 20:56:26.377591: Current learning rate: 0.00782 +2024-11-21 20:56:43.893152: train_loss -0.7751 +2024-11-21 20:56:43.893384: val_loss -0.7838 +2024-11-21 20:56:43.893460: Pseudo dice [0.8604] +2024-11-21 20:56:43.893531: Epoch time: 17.52 s +2024-11-21 20:56:43.893590: Yayy! New best EMA pseudo Dice: 0.8451 +2024-11-21 20:56:44.940965: +2024-11-21 20:56:44.941192: Epoch 1913 +2024-11-21 20:56:44.941301: Current learning rate: 0.00782 +2024-11-21 20:57:03.653730: train_loss -0.7729 +2024-11-21 20:57:03.653961: val_loss -0.765 +2024-11-21 20:57:03.654049: Pseudo dice [0.8375] +2024-11-21 20:57:03.654130: Epoch time: 18.71 s +2024-11-21 20:57:04.511773: +2024-11-21 20:57:04.512016: Epoch 1914 +2024-11-21 20:57:04.512144: Current learning rate: 0.00782 +2024-11-21 20:57:22.954737: train_loss -0.7739 +2024-11-21 20:57:22.954983: val_loss -0.7691 +2024-11-21 20:57:22.955063: Pseudo dice [0.8413] +2024-11-21 20:57:22.955144: Epoch time: 18.44 s +2024-11-21 20:57:23.811083: +2024-11-21 20:57:23.811309: Epoch 1915 +2024-11-21 20:57:23.811425: Current learning rate: 0.00782 +2024-11-21 20:57:43.286582: train_loss -0.7791 +2024-11-21 20:57:43.287932: val_loss -0.7574 +2024-11-21 20:57:43.288035: Pseudo dice [0.8291] +2024-11-21 20:57:43.288111: Epoch time: 19.48 s +2024-11-21 20:57:44.182275: +2024-11-21 20:57:44.182512: Epoch 1916 +2024-11-21 20:57:44.182623: Current learning rate: 0.00782 +2024-11-21 20:58:03.177931: train_loss -0.7779 +2024-11-21 20:58:03.178149: val_loss -0.7646 +2024-11-21 20:58:03.178221: Pseudo dice [0.8275] +2024-11-21 20:58:03.178291: Epoch time: 19.0 s +2024-11-21 20:58:04.050238: +2024-11-21 20:58:04.050470: Epoch 1917 +2024-11-21 20:58:04.050581: Current learning rate: 0.00781 +2024-11-21 20:58:22.743021: train_loss -0.7721 +2024-11-21 20:58:22.743255: val_loss -0.7452 +2024-11-21 20:58:22.743330: Pseudo dice [0.8292] +2024-11-21 20:58:22.743407: Epoch time: 18.69 s +2024-11-21 20:58:23.604315: +2024-11-21 20:58:23.604548: Epoch 1918 +2024-11-21 20:58:23.604656: Current learning rate: 0.00781 +2024-11-21 20:58:42.046829: train_loss -0.7624 +2024-11-21 20:58:42.047081: val_loss -0.7844 +2024-11-21 20:58:42.047164: Pseudo dice [0.8519] +2024-11-21 20:58:42.047263: Epoch time: 18.44 s +2024-11-21 20:58:42.897033: +2024-11-21 20:58:42.897242: Epoch 1919 +2024-11-21 20:58:42.897352: Current learning rate: 0.00781 +2024-11-21 20:59:01.344165: train_loss -0.7701 +2024-11-21 20:59:01.344382: val_loss -0.7554 +2024-11-21 20:59:01.344455: Pseudo dice [0.8303] +2024-11-21 20:59:01.344530: Epoch time: 18.45 s +2024-11-21 20:59:02.190883: +2024-11-21 20:59:02.191145: Epoch 1920 +2024-11-21 20:59:02.191266: Current learning rate: 0.00781 +2024-11-21 20:59:19.899827: train_loss -0.7528 +2024-11-21 20:59:19.900054: val_loss -0.7508 +2024-11-21 20:59:19.900129: Pseudo dice [0.8204] +2024-11-21 20:59:19.900203: Epoch time: 17.71 s +2024-11-21 20:59:20.764420: +2024-11-21 20:59:20.764620: Epoch 1921 +2024-11-21 20:59:20.764728: Current learning rate: 0.00781 +2024-11-21 20:59:38.133282: train_loss -0.7542 +2024-11-21 20:59:38.133505: val_loss -0.7322 +2024-11-21 20:59:38.133582: Pseudo dice [0.8123] +2024-11-21 20:59:38.133663: Epoch time: 17.37 s +2024-11-21 20:59:38.986896: +2024-11-21 20:59:38.987126: Epoch 1922 +2024-11-21 20:59:38.987231: Current learning rate: 0.00781 +2024-11-21 20:59:57.667625: train_loss -0.762 +2024-11-21 20:59:57.668151: val_loss -0.7392 +2024-11-21 20:59:57.668229: Pseudo dice [0.8264] +2024-11-21 20:59:57.668305: Epoch time: 18.68 s +2024-11-21 20:59:58.516311: +2024-11-21 20:59:58.516525: Epoch 1923 +2024-11-21 20:59:58.516637: Current learning rate: 0.00781 +2024-11-21 21:00:16.740081: train_loss -0.771 +2024-11-21 21:00:16.745738: val_loss -0.7617 +2024-11-21 21:00:16.745852: Pseudo dice [0.8319] +2024-11-21 21:00:16.745936: Epoch time: 18.22 s +2024-11-21 21:00:17.818967: +2024-11-21 21:00:17.819271: Epoch 1924 +2024-11-21 21:00:17.819382: Current learning rate: 0.00781 +2024-11-21 21:00:36.049671: train_loss -0.7561 +2024-11-21 21:00:36.049919: val_loss -0.7669 +2024-11-21 21:00:36.050015: Pseudo dice [0.8517] +2024-11-21 21:00:36.050101: Epoch time: 18.23 s +2024-11-21 21:00:37.035065: +2024-11-21 21:00:37.035299: Epoch 1925 +2024-11-21 21:00:37.035411: Current learning rate: 0.00781 +2024-11-21 21:00:55.624288: train_loss -0.7638 +2024-11-21 21:00:55.629118: val_loss -0.7643 +2024-11-21 21:00:55.629217: Pseudo dice [0.8427] +2024-11-21 21:00:55.629300: Epoch time: 18.59 s +2024-11-21 21:00:56.486045: +2024-11-21 21:00:56.486282: Epoch 1926 +2024-11-21 21:00:56.486392: Current learning rate: 0.0078 +2024-11-21 21:01:14.100922: train_loss -0.7727 +2024-11-21 21:01:14.101217: val_loss -0.7619 +2024-11-21 21:01:14.101295: Pseudo dice [0.8486] +2024-11-21 21:01:14.101369: Epoch time: 17.62 s +2024-11-21 21:01:14.966248: +2024-11-21 21:01:14.966479: Epoch 1927 +2024-11-21 21:01:14.966596: Current learning rate: 0.0078 +2024-11-21 21:01:34.364421: train_loss -0.7757 +2024-11-21 21:01:34.364637: val_loss -0.7658 +2024-11-21 21:01:34.364740: Pseudo dice [0.8446] +2024-11-21 21:01:34.364820: Epoch time: 19.4 s +2024-11-21 21:01:35.222657: +2024-11-21 21:01:35.222881: Epoch 1928 +2024-11-21 21:01:35.222987: Current learning rate: 0.0078 +2024-11-21 21:01:52.993005: train_loss -0.7671 +2024-11-21 21:01:52.993216: val_loss -0.7554 +2024-11-21 21:01:52.993291: Pseudo dice [0.8481] +2024-11-21 21:01:52.993369: Epoch time: 17.77 s +2024-11-21 21:01:53.835451: +2024-11-21 21:01:53.835660: Epoch 1929 +2024-11-21 21:01:53.836009: Current learning rate: 0.0078 +2024-11-21 21:02:12.223757: train_loss -0.7621 +2024-11-21 21:02:12.224002: val_loss -0.7272 +2024-11-21 21:02:12.224076: Pseudo dice [0.8008] +2024-11-21 21:02:12.224155: Epoch time: 18.39 s +2024-11-21 21:02:13.085952: +2024-11-21 21:02:13.086153: Epoch 1930 +2024-11-21 21:02:13.086264: Current learning rate: 0.0078 +2024-11-21 21:02:31.994799: train_loss -0.766 +2024-11-21 21:02:31.995020: val_loss -0.7413 +2024-11-21 21:02:31.995094: Pseudo dice [0.8192] +2024-11-21 21:02:31.995168: Epoch time: 18.91 s +2024-11-21 21:02:32.842459: +2024-11-21 21:02:32.842730: Epoch 1931 +2024-11-21 21:02:32.842853: Current learning rate: 0.0078 +2024-11-21 21:02:51.057149: train_loss -0.7674 +2024-11-21 21:02:51.062586: val_loss -0.7411 +2024-11-21 21:02:51.062728: Pseudo dice [0.8305] +2024-11-21 21:02:51.062825: Epoch time: 18.22 s +2024-11-21 21:02:52.060004: +2024-11-21 21:02:52.060225: Epoch 1932 +2024-11-21 21:02:52.060344: Current learning rate: 0.0078 +2024-11-21 21:03:10.368165: train_loss -0.7667 +2024-11-21 21:03:10.368384: val_loss -0.7605 +2024-11-21 21:03:10.368457: Pseudo dice [0.8265] +2024-11-21 21:03:10.368535: Epoch time: 18.31 s +2024-11-21 21:03:11.217045: +2024-11-21 21:03:11.217268: Epoch 1933 +2024-11-21 21:03:11.217376: Current learning rate: 0.0078 +2024-11-21 21:03:28.798357: train_loss -0.7624 +2024-11-21 21:03:28.798591: val_loss -0.7449 +2024-11-21 21:03:28.798665: Pseudo dice [0.8494] +2024-11-21 21:03:28.798739: Epoch time: 17.58 s +2024-11-21 21:03:30.027054: +2024-11-21 21:03:30.027262: Epoch 1934 +2024-11-21 21:03:30.027370: Current learning rate: 0.0078 +2024-11-21 21:03:48.341585: train_loss -0.7756 +2024-11-21 21:03:48.341810: val_loss -0.749 +2024-11-21 21:03:48.341887: Pseudo dice [0.8478] +2024-11-21 21:03:48.341961: Epoch time: 18.32 s +2024-11-21 21:03:49.189283: +2024-11-21 21:03:49.189501: Epoch 1935 +2024-11-21 21:03:49.189612: Current learning rate: 0.00779 +2024-11-21 21:04:07.981412: train_loss -0.7684 +2024-11-21 21:04:07.981652: val_loss -0.7424 +2024-11-21 21:04:07.981726: Pseudo dice [0.8187] +2024-11-21 21:04:07.981815: Epoch time: 18.79 s +2024-11-21 21:04:08.828227: +2024-11-21 21:04:08.828426: Epoch 1936 +2024-11-21 21:04:08.828532: Current learning rate: 0.00779 +2024-11-21 21:04:26.972824: train_loss -0.7709 +2024-11-21 21:04:26.973045: val_loss -0.7459 +2024-11-21 21:04:26.973121: Pseudo dice [0.8381] +2024-11-21 21:04:26.973194: Epoch time: 18.15 s +2024-11-21 21:04:27.847909: +2024-11-21 21:04:27.848144: Epoch 1937 +2024-11-21 21:04:27.848260: Current learning rate: 0.00779 +2024-11-21 21:04:46.309717: train_loss -0.7638 +2024-11-21 21:04:46.313348: val_loss -0.7569 +2024-11-21 21:04:46.313427: Pseudo dice [0.8295] +2024-11-21 21:04:46.313500: Epoch time: 18.46 s +2024-11-21 21:04:47.229505: +2024-11-21 21:04:47.229733: Epoch 1938 +2024-11-21 21:04:47.229846: Current learning rate: 0.00779 +2024-11-21 21:05:05.748608: train_loss -0.7743 +2024-11-21 21:05:05.748819: val_loss -0.7129 +2024-11-21 21:05:05.748892: Pseudo dice [0.8269] +2024-11-21 21:05:05.748967: Epoch time: 18.52 s +2024-11-21 21:05:06.666137: +2024-11-21 21:05:06.666362: Epoch 1939 +2024-11-21 21:05:06.666477: Current learning rate: 0.00779 +2024-11-21 21:05:24.254845: train_loss -0.7739 +2024-11-21 21:05:24.255072: val_loss -0.771 +2024-11-21 21:05:24.255187: Pseudo dice [0.8315] +2024-11-21 21:05:24.255269: Epoch time: 17.59 s +2024-11-21 21:05:25.097052: +2024-11-21 21:05:25.097270: Epoch 1940 +2024-11-21 21:05:25.097378: Current learning rate: 0.00779 +2024-11-21 21:05:44.342601: train_loss -0.7739 +2024-11-21 21:05:44.342886: val_loss -0.7645 +2024-11-21 21:05:44.342971: Pseudo dice [0.8357] +2024-11-21 21:05:44.343064: Epoch time: 19.25 s +2024-11-21 21:05:45.242697: +2024-11-21 21:05:45.242901: Epoch 1941 +2024-11-21 21:05:45.243014: Current learning rate: 0.00779 +2024-11-21 21:06:03.311122: train_loss -0.762 +2024-11-21 21:06:03.311341: val_loss -0.7571 +2024-11-21 21:06:03.311416: Pseudo dice [0.8372] +2024-11-21 21:06:03.311494: Epoch time: 18.07 s +2024-11-21 21:06:04.165298: +2024-11-21 21:06:04.165609: Epoch 1942 +2024-11-21 21:06:04.165727: Current learning rate: 0.00779 +2024-11-21 21:06:23.173529: train_loss -0.7772 +2024-11-21 21:06:23.173751: val_loss -0.7666 +2024-11-21 21:06:23.173829: Pseudo dice [0.86] +2024-11-21 21:06:23.173907: Epoch time: 19.01 s +2024-11-21 21:06:24.061226: +2024-11-21 21:06:24.061647: Epoch 1943 +2024-11-21 21:06:24.061761: Current learning rate: 0.00778 +2024-11-21 21:06:42.821801: train_loss -0.7674 +2024-11-21 21:06:42.822096: val_loss -0.7794 +2024-11-21 21:06:42.822218: Pseudo dice [0.8374] +2024-11-21 21:06:42.822309: Epoch time: 18.76 s +2024-11-21 21:06:43.679564: +2024-11-21 21:06:43.679770: Epoch 1944 +2024-11-21 21:06:43.679878: Current learning rate: 0.00778 +2024-11-21 21:07:01.579141: train_loss -0.7816 +2024-11-21 21:07:01.579367: val_loss -0.7254 +2024-11-21 21:07:01.579442: Pseudo dice [0.8314] +2024-11-21 21:07:01.579516: Epoch time: 17.9 s +2024-11-21 21:07:02.430763: +2024-11-21 21:07:02.430972: Epoch 1945 +2024-11-21 21:07:02.431086: Current learning rate: 0.00778 +2024-11-21 21:07:19.854126: train_loss -0.78 +2024-11-21 21:07:19.854407: val_loss -0.7601 +2024-11-21 21:07:19.854486: Pseudo dice [0.8497] +2024-11-21 21:07:19.854562: Epoch time: 17.42 s +2024-11-21 21:07:21.112731: +2024-11-21 21:07:21.112959: Epoch 1946 +2024-11-21 21:07:21.113079: Current learning rate: 0.00778 +2024-11-21 21:07:40.150670: train_loss -0.7696 +2024-11-21 21:07:40.150931: val_loss -0.7666 +2024-11-21 21:07:40.151016: Pseudo dice [0.8372] +2024-11-21 21:07:40.151105: Epoch time: 19.04 s +2024-11-21 21:07:41.010472: +2024-11-21 21:07:41.010701: Epoch 1947 +2024-11-21 21:07:41.010815: Current learning rate: 0.00778 +2024-11-21 21:07:58.694469: train_loss -0.7751 +2024-11-21 21:07:58.694683: val_loss -0.7485 +2024-11-21 21:07:58.694755: Pseudo dice [0.8468] +2024-11-21 21:07:58.694829: Epoch time: 17.68 s +2024-11-21 21:07:59.700711: +2024-11-21 21:07:59.701094: Epoch 1948 +2024-11-21 21:07:59.701207: Current learning rate: 0.00778 +2024-11-21 21:08:17.788864: train_loss -0.7765 +2024-11-21 21:08:17.789113: val_loss -0.7633 +2024-11-21 21:08:17.789190: Pseudo dice [0.8369] +2024-11-21 21:08:17.789268: Epoch time: 18.09 s +2024-11-21 21:08:18.645409: +2024-11-21 21:08:18.645615: Epoch 1949 +2024-11-21 21:08:18.645720: Current learning rate: 0.00778 +2024-11-21 21:08:37.209555: train_loss -0.7679 +2024-11-21 21:08:37.209837: val_loss -0.7441 +2024-11-21 21:08:37.209937: Pseudo dice [0.8535] +2024-11-21 21:08:37.210028: Epoch time: 18.56 s +2024-11-21 21:08:38.265996: +2024-11-21 21:08:38.266219: Epoch 1950 +2024-11-21 21:08:38.266330: Current learning rate: 0.00778 +2024-11-21 21:08:55.594869: train_loss -0.7635 +2024-11-21 21:08:55.595131: val_loss -0.7686 +2024-11-21 21:08:55.595215: Pseudo dice [0.8368] +2024-11-21 21:08:55.595292: Epoch time: 17.33 s +2024-11-21 21:08:56.446197: +2024-11-21 21:08:56.446401: Epoch 1951 +2024-11-21 21:08:56.446511: Current learning rate: 0.00778 +2024-11-21 21:09:15.265756: train_loss -0.7725 +2024-11-21 21:09:15.266010: val_loss -0.7542 +2024-11-21 21:09:15.266090: Pseudo dice [0.8391] +2024-11-21 21:09:15.266171: Epoch time: 18.82 s +2024-11-21 21:09:16.134190: +2024-11-21 21:09:16.134407: Epoch 1952 +2024-11-21 21:09:16.134516: Current learning rate: 0.00777 +2024-11-21 21:09:33.976415: train_loss -0.7698 +2024-11-21 21:09:33.976635: val_loss -0.7535 +2024-11-21 21:09:33.976707: Pseudo dice [0.8153] +2024-11-21 21:09:33.976779: Epoch time: 17.84 s +2024-11-21 21:09:35.009097: +2024-11-21 21:09:35.009298: Epoch 1953 +2024-11-21 21:09:35.009409: Current learning rate: 0.00777 +2024-11-21 21:09:53.483608: train_loss -0.7542 +2024-11-21 21:09:53.483851: val_loss -0.759 +2024-11-21 21:09:53.483926: Pseudo dice [0.8346] +2024-11-21 21:09:53.484011: Epoch time: 18.48 s +2024-11-21 21:09:54.326823: +2024-11-21 21:09:54.327049: Epoch 1954 +2024-11-21 21:09:54.327163: Current learning rate: 0.00777 +2024-11-21 21:10:13.188469: train_loss -0.7607 +2024-11-21 21:10:13.188759: val_loss -0.7658 +2024-11-21 21:10:13.188862: Pseudo dice [0.856] +2024-11-21 21:10:13.188936: Epoch time: 18.86 s +2024-11-21 21:10:14.037853: +2024-11-21 21:10:14.038274: Epoch 1955 +2024-11-21 21:10:14.038393: Current learning rate: 0.00777 +2024-11-21 21:10:32.264266: train_loss -0.7657 +2024-11-21 21:10:32.264497: val_loss -0.7609 +2024-11-21 21:10:32.264578: Pseudo dice [0.8249] +2024-11-21 21:10:32.265724: Epoch time: 18.23 s +2024-11-21 21:10:33.119556: +2024-11-21 21:10:33.119767: Epoch 1956 +2024-11-21 21:10:33.119880: Current learning rate: 0.00777 +2024-11-21 21:10:51.418713: train_loss -0.7788 +2024-11-21 21:10:51.418930: val_loss -0.7636 +2024-11-21 21:10:51.419013: Pseudo dice [0.8233] +2024-11-21 21:10:51.419091: Epoch time: 18.3 s +2024-11-21 21:10:52.642842: +2024-11-21 21:10:52.643067: Epoch 1957 +2024-11-21 21:10:52.643177: Current learning rate: 0.00777 +2024-11-21 21:11:11.331060: train_loss -0.7766 +2024-11-21 21:11:11.331352: val_loss -0.7372 +2024-11-21 21:11:11.331430: Pseudo dice [0.8326] +2024-11-21 21:11:11.331526: Epoch time: 18.69 s +2024-11-21 21:11:12.176344: +2024-11-21 21:11:12.176647: Epoch 1958 +2024-11-21 21:11:12.176761: Current learning rate: 0.00777 +2024-11-21 21:11:30.452385: train_loss -0.7747 +2024-11-21 21:11:30.452606: val_loss -0.7435 +2024-11-21 21:11:30.452682: Pseudo dice [0.8455] +2024-11-21 21:11:30.452765: Epoch time: 18.28 s +2024-11-21 21:11:31.306268: +2024-11-21 21:11:31.306508: Epoch 1959 +2024-11-21 21:11:31.306620: Current learning rate: 0.00777 +2024-11-21 21:11:50.284928: train_loss -0.7759 +2024-11-21 21:11:50.285152: val_loss -0.7467 +2024-11-21 21:11:50.285224: Pseudo dice [0.8401] +2024-11-21 21:11:50.285297: Epoch time: 18.98 s +2024-11-21 21:11:51.139263: +2024-11-21 21:11:51.139469: Epoch 1960 +2024-11-21 21:11:51.139578: Current learning rate: 0.00777 +2024-11-21 21:12:09.296517: train_loss -0.7707 +2024-11-21 21:12:09.296763: val_loss -0.7722 +2024-11-21 21:12:09.296838: Pseudo dice [0.8362] +2024-11-21 21:12:09.296918: Epoch time: 18.16 s +2024-11-21 21:12:10.146928: +2024-11-21 21:12:10.147142: Epoch 1961 +2024-11-21 21:12:10.147248: Current learning rate: 0.00776 +2024-11-21 21:12:28.789053: train_loss -0.7751 +2024-11-21 21:12:28.789282: val_loss -0.7667 +2024-11-21 21:12:28.789357: Pseudo dice [0.8416] +2024-11-21 21:12:28.789435: Epoch time: 18.64 s +2024-11-21 21:12:29.779028: +2024-11-21 21:12:29.779264: Epoch 1962 +2024-11-21 21:12:29.779375: Current learning rate: 0.00776 +2024-11-21 21:12:48.081264: train_loss -0.7802 +2024-11-21 21:12:48.081483: val_loss -0.7449 +2024-11-21 21:12:48.081556: Pseudo dice [0.8338] +2024-11-21 21:12:48.081634: Epoch time: 18.3 s +2024-11-21 21:12:48.940721: +2024-11-21 21:12:48.940928: Epoch 1963 +2024-11-21 21:12:48.941044: Current learning rate: 0.00776 +2024-11-21 21:13:07.117452: train_loss -0.7815 +2024-11-21 21:13:07.117668: val_loss -0.7738 +2024-11-21 21:13:07.117749: Pseudo dice [0.8267] +2024-11-21 21:13:07.122982: Epoch time: 18.18 s +2024-11-21 21:13:07.997571: +2024-11-21 21:13:07.997785: Epoch 1964 +2024-11-21 21:13:07.997898: Current learning rate: 0.00776 +2024-11-21 21:13:26.840505: train_loss -0.7599 +2024-11-21 21:13:26.840769: val_loss -0.7802 +2024-11-21 21:13:26.840846: Pseudo dice [0.8595] +2024-11-21 21:13:26.840924: Epoch time: 18.84 s +2024-11-21 21:13:27.692755: +2024-11-21 21:13:27.692938: Epoch 1965 +2024-11-21 21:13:27.693050: Current learning rate: 0.00776 +2024-11-21 21:13:46.675859: train_loss -0.7646 +2024-11-21 21:13:46.676081: val_loss -0.7545 +2024-11-21 21:13:46.676157: Pseudo dice [0.8373] +2024-11-21 21:13:46.676233: Epoch time: 18.98 s +2024-11-21 21:13:47.550355: +2024-11-21 21:13:47.550633: Epoch 1966 +2024-11-21 21:13:47.550741: Current learning rate: 0.00776 +2024-11-21 21:14:05.808876: train_loss -0.7593 +2024-11-21 21:14:05.809105: val_loss -0.7594 +2024-11-21 21:14:05.809182: Pseudo dice [0.8339] +2024-11-21 21:14:05.809258: Epoch time: 18.26 s +2024-11-21 21:14:06.813771: +2024-11-21 21:14:06.813997: Epoch 1967 +2024-11-21 21:14:06.814104: Current learning rate: 0.00776 +2024-11-21 21:14:25.552246: train_loss -0.7639 +2024-11-21 21:14:25.552497: val_loss -0.7572 +2024-11-21 21:14:25.552571: Pseudo dice [0.8301] +2024-11-21 21:14:25.552650: Epoch time: 18.74 s +2024-11-21 21:14:26.810305: +2024-11-21 21:14:26.810550: Epoch 1968 +2024-11-21 21:14:26.810660: Current learning rate: 0.00776 +2024-11-21 21:14:45.261097: train_loss -0.7681 +2024-11-21 21:14:45.261536: val_loss -0.7902 +2024-11-21 21:14:45.261611: Pseudo dice [0.8356] +2024-11-21 21:14:45.261684: Epoch time: 18.45 s +2024-11-21 21:14:46.110127: +2024-11-21 21:14:46.110340: Epoch 1969 +2024-11-21 21:14:46.110452: Current learning rate: 0.00775 +2024-11-21 21:15:04.290523: train_loss -0.7786 +2024-11-21 21:15:04.290751: val_loss -0.7629 +2024-11-21 21:15:04.290830: Pseudo dice [0.8319] +2024-11-21 21:15:04.290904: Epoch time: 18.18 s +2024-11-21 21:15:05.248181: +2024-11-21 21:15:05.248406: Epoch 1970 +2024-11-21 21:15:05.248518: Current learning rate: 0.00775 +2024-11-21 21:15:23.070817: train_loss -0.7748 +2024-11-21 21:15:23.071072: val_loss -0.7686 +2024-11-21 21:15:23.071147: Pseudo dice [0.8368] +2024-11-21 21:15:23.071229: Epoch time: 17.82 s +2024-11-21 21:15:23.934878: +2024-11-21 21:15:23.935104: Epoch 1971 +2024-11-21 21:15:23.935228: Current learning rate: 0.00775 +2024-11-21 21:15:43.179643: train_loss -0.7799 +2024-11-21 21:15:43.179893: val_loss -0.7757 +2024-11-21 21:15:43.179972: Pseudo dice [0.8495] +2024-11-21 21:15:43.180054: Epoch time: 19.25 s +2024-11-21 21:15:44.035070: +2024-11-21 21:15:44.035312: Epoch 1972 +2024-11-21 21:15:44.035421: Current learning rate: 0.00775 +2024-11-21 21:16:02.278365: train_loss -0.7719 +2024-11-21 21:16:02.278578: val_loss -0.7778 +2024-11-21 21:16:02.278662: Pseudo dice [0.8424] +2024-11-21 21:16:02.278739: Epoch time: 18.24 s +2024-11-21 21:16:03.128557: +2024-11-21 21:16:03.128783: Epoch 1973 +2024-11-21 21:16:03.128907: Current learning rate: 0.00775 +2024-11-21 21:16:21.249381: train_loss -0.7519 +2024-11-21 21:16:21.254772: val_loss -0.766 +2024-11-21 21:16:21.254886: Pseudo dice [0.8428] +2024-11-21 21:16:21.254962: Epoch time: 18.12 s +2024-11-21 21:16:22.336531: +2024-11-21 21:16:22.336767: Epoch 1974 +2024-11-21 21:16:22.336894: Current learning rate: 0.00775 +2024-11-21 21:16:40.436375: train_loss -0.7612 +2024-11-21 21:16:40.436625: val_loss -0.7558 +2024-11-21 21:16:40.436710: Pseudo dice [0.8447] +2024-11-21 21:16:40.436801: Epoch time: 18.1 s +2024-11-21 21:16:41.366527: +2024-11-21 21:16:41.366749: Epoch 1975 +2024-11-21 21:16:41.366861: Current learning rate: 0.00775 +2024-11-21 21:16:59.957709: train_loss -0.7673 +2024-11-21 21:16:59.957915: val_loss -0.7452 +2024-11-21 21:16:59.957987: Pseudo dice [0.8359] +2024-11-21 21:16:59.958068: Epoch time: 18.59 s +2024-11-21 21:17:00.804667: +2024-11-21 21:17:00.804879: Epoch 1976 +2024-11-21 21:17:00.804995: Current learning rate: 0.00775 +2024-11-21 21:17:19.876530: train_loss -0.7749 +2024-11-21 21:17:19.876741: val_loss -0.7439 +2024-11-21 21:17:19.876818: Pseudo dice [0.8298] +2024-11-21 21:17:19.876893: Epoch time: 19.07 s +2024-11-21 21:17:20.724118: +2024-11-21 21:17:20.724328: Epoch 1977 +2024-11-21 21:17:20.724440: Current learning rate: 0.00775 +2024-11-21 21:17:39.681540: train_loss -0.7717 +2024-11-21 21:17:39.681768: val_loss -0.7555 +2024-11-21 21:17:39.681843: Pseudo dice [0.8409] +2024-11-21 21:17:39.681920: Epoch time: 18.96 s +2024-11-21 21:17:40.530426: +2024-11-21 21:17:40.530695: Epoch 1978 +2024-11-21 21:17:40.530806: Current learning rate: 0.00774 +2024-11-21 21:17:58.553464: train_loss -0.7671 +2024-11-21 21:17:58.553719: val_loss -0.7787 +2024-11-21 21:17:58.553798: Pseudo dice [0.8481] +2024-11-21 21:17:58.553885: Epoch time: 18.02 s +2024-11-21 21:17:59.774874: +2024-11-21 21:17:59.775119: Epoch 1979 +2024-11-21 21:17:59.775228: Current learning rate: 0.00774 +2024-11-21 21:18:17.523218: train_loss -0.7718 +2024-11-21 21:18:17.523453: val_loss -0.7416 +2024-11-21 21:18:17.523535: Pseudo dice [0.846] +2024-11-21 21:18:17.523619: Epoch time: 17.75 s +2024-11-21 21:18:18.376867: +2024-11-21 21:18:18.377100: Epoch 1980 +2024-11-21 21:18:18.377217: Current learning rate: 0.00774 +2024-11-21 21:18:37.302229: train_loss -0.7684 +2024-11-21 21:18:37.302447: val_loss -0.76 +2024-11-21 21:18:37.302525: Pseudo dice [0.8361] +2024-11-21 21:18:37.302604: Epoch time: 18.93 s +2024-11-21 21:18:38.151043: +2024-11-21 21:18:38.151260: Epoch 1981 +2024-11-21 21:18:38.151562: Current learning rate: 0.00774 +2024-11-21 21:18:56.649727: train_loss -0.7735 +2024-11-21 21:18:56.649964: val_loss -0.7448 +2024-11-21 21:18:56.650049: Pseudo dice [0.8393] +2024-11-21 21:18:56.650131: Epoch time: 18.5 s +2024-11-21 21:18:57.502444: +2024-11-21 21:18:57.502674: Epoch 1982 +2024-11-21 21:18:57.502786: Current learning rate: 0.00774 +2024-11-21 21:19:16.105491: train_loss -0.7772 +2024-11-21 21:19:16.105698: val_loss -0.7441 +2024-11-21 21:19:16.105775: Pseudo dice [0.8393] +2024-11-21 21:19:16.105850: Epoch time: 18.6 s +2024-11-21 21:19:16.954062: +2024-11-21 21:19:16.954272: Epoch 1983 +2024-11-21 21:19:16.954380: Current learning rate: 0.00774 +2024-11-21 21:19:36.219142: train_loss -0.7636 +2024-11-21 21:19:36.219362: val_loss -0.7315 +2024-11-21 21:19:36.219441: Pseudo dice [0.8362] +2024-11-21 21:19:36.219519: Epoch time: 19.27 s +2024-11-21 21:19:37.072239: +2024-11-21 21:19:37.072452: Epoch 1984 +2024-11-21 21:19:37.072563: Current learning rate: 0.00774 +2024-11-21 21:19:56.393460: train_loss -0.7813 +2024-11-21 21:19:56.393679: val_loss -0.7491 +2024-11-21 21:19:56.393750: Pseudo dice [0.8473] +2024-11-21 21:19:56.393826: Epoch time: 19.32 s +2024-11-21 21:19:57.247739: +2024-11-21 21:19:57.247946: Epoch 1985 +2024-11-21 21:19:57.248062: Current learning rate: 0.00774 +2024-11-21 21:20:16.433585: train_loss -0.7686 +2024-11-21 21:20:16.433843: val_loss -0.7532 +2024-11-21 21:20:16.433920: Pseudo dice [0.825] +2024-11-21 21:20:16.434009: Epoch time: 19.19 s +2024-11-21 21:20:17.283513: +2024-11-21 21:20:17.283727: Epoch 1986 +2024-11-21 21:20:17.283837: Current learning rate: 0.00774 +2024-11-21 21:20:35.194481: train_loss -0.7782 +2024-11-21 21:20:35.194685: val_loss -0.7763 +2024-11-21 21:20:35.194767: Pseudo dice [0.8422] +2024-11-21 21:20:35.194857: Epoch time: 17.91 s +2024-11-21 21:20:36.034713: +2024-11-21 21:20:36.034912: Epoch 1987 +2024-11-21 21:20:36.035030: Current learning rate: 0.00773 +2024-11-21 21:20:54.435965: train_loss -0.7724 +2024-11-21 21:20:54.436188: val_loss -0.7396 +2024-11-21 21:20:54.438435: Pseudo dice [0.8508] +2024-11-21 21:20:54.438525: Epoch time: 18.4 s +2024-11-21 21:20:55.370748: +2024-11-21 21:20:55.371117: Epoch 1988 +2024-11-21 21:20:55.371225: Current learning rate: 0.00773 +2024-11-21 21:21:13.361461: train_loss -0.7632 +2024-11-21 21:21:13.361703: val_loss -0.7685 +2024-11-21 21:21:13.361783: Pseudo dice [0.8498] +2024-11-21 21:21:13.361869: Epoch time: 17.99 s +2024-11-21 21:21:14.217988: +2024-11-21 21:21:14.218199: Epoch 1989 +2024-11-21 21:21:14.218323: Current learning rate: 0.00773 +2024-11-21 21:21:32.605086: train_loss -0.7681 +2024-11-21 21:21:32.605345: val_loss -0.7793 +2024-11-21 21:21:32.605427: Pseudo dice [0.8312] +2024-11-21 21:21:32.605506: Epoch time: 18.39 s +2024-11-21 21:21:33.834754: +2024-11-21 21:21:33.834999: Epoch 1990 +2024-11-21 21:21:33.835114: Current learning rate: 0.00773 +2024-11-21 21:21:51.315606: train_loss -0.7759 +2024-11-21 21:21:51.315826: val_loss -0.7624 +2024-11-21 21:21:51.315897: Pseudo dice [0.8255] +2024-11-21 21:21:51.315969: Epoch time: 17.48 s +2024-11-21 21:21:52.162460: +2024-11-21 21:21:52.162712: Epoch 1991 +2024-11-21 21:21:52.162822: Current learning rate: 0.00773 +2024-11-21 21:22:10.015654: train_loss -0.7824 +2024-11-21 21:22:10.015879: val_loss -0.7621 +2024-11-21 21:22:10.015957: Pseudo dice [0.8365] +2024-11-21 21:22:10.016091: Epoch time: 17.85 s +2024-11-21 21:22:10.872377: +2024-11-21 21:22:10.872689: Epoch 1992 +2024-11-21 21:22:10.872800: Current learning rate: 0.00773 +2024-11-21 21:22:29.163246: train_loss -0.7807 +2024-11-21 21:22:29.163477: val_loss -0.7653 +2024-11-21 21:22:29.163552: Pseudo dice [0.8438] +2024-11-21 21:22:29.163633: Epoch time: 18.29 s +2024-11-21 21:22:30.032571: +2024-11-21 21:22:30.032796: Epoch 1993 +2024-11-21 21:22:30.032914: Current learning rate: 0.00773 +2024-11-21 21:22:48.663877: train_loss -0.7869 +2024-11-21 21:22:48.664133: val_loss -0.75 +2024-11-21 21:22:48.664211: Pseudo dice [0.8257] +2024-11-21 21:22:48.676352: Epoch time: 18.63 s +2024-11-21 21:22:49.550646: +2024-11-21 21:22:49.550865: Epoch 1994 +2024-11-21 21:22:49.550976: Current learning rate: 0.00773 +2024-11-21 21:23:08.584873: train_loss -0.7725 +2024-11-21 21:23:08.585172: val_loss -0.7637 +2024-11-21 21:23:08.585251: Pseudo dice [0.847] +2024-11-21 21:23:08.585325: Epoch time: 19.04 s +2024-11-21 21:23:09.452662: +2024-11-21 21:23:09.452884: Epoch 1995 +2024-11-21 21:23:09.453000: Current learning rate: 0.00772 +2024-11-21 21:23:28.615331: train_loss -0.7699 +2024-11-21 21:23:28.615597: val_loss -0.7786 +2024-11-21 21:23:28.615673: Pseudo dice [0.8392] +2024-11-21 21:23:28.615743: Epoch time: 19.16 s +2024-11-21 21:23:29.467475: +2024-11-21 21:23:29.467689: Epoch 1996 +2024-11-21 21:23:29.467795: Current learning rate: 0.00772 +2024-11-21 21:23:48.191114: train_loss -0.7687 +2024-11-21 21:23:48.191361: val_loss -0.7633 +2024-11-21 21:23:48.193666: Pseudo dice [0.8403] +2024-11-21 21:23:48.193778: Epoch time: 18.72 s +2024-11-21 21:23:49.095091: +2024-11-21 21:23:49.095291: Epoch 1997 +2024-11-21 21:23:49.095396: Current learning rate: 0.00772 +2024-11-21 21:24:07.125792: train_loss -0.7734 +2024-11-21 21:24:07.126047: val_loss -0.7621 +2024-11-21 21:24:07.126123: Pseudo dice [0.8335] +2024-11-21 21:24:07.126198: Epoch time: 18.03 s +2024-11-21 21:24:07.975600: +2024-11-21 21:24:07.975837: Epoch 1998 +2024-11-21 21:24:07.975946: Current learning rate: 0.00772 +2024-11-21 21:24:25.643666: train_loss -0.7659 +2024-11-21 21:24:25.643916: val_loss -0.7578 +2024-11-21 21:24:25.644004: Pseudo dice [0.8352] +2024-11-21 21:24:25.644085: Epoch time: 17.67 s +2024-11-21 21:24:26.493571: +2024-11-21 21:24:26.493798: Epoch 1999 +2024-11-21 21:24:26.493925: Current learning rate: 0.00772 +2024-11-21 21:24:45.962448: train_loss -0.7721 +2024-11-21 21:24:45.962677: val_loss -0.7568 +2024-11-21 21:24:45.962754: Pseudo dice [0.8609] +2024-11-21 21:24:45.962831: Epoch time: 19.47 s +2024-11-21 21:24:47.045894: +2024-11-21 21:24:47.046123: Epoch 2000 +2024-11-21 21:24:47.046235: Current learning rate: 0.00772 +2024-11-21 21:25:07.570496: train_loss -0.7733 +2024-11-21 21:25:07.570744: val_loss -0.7765 +2024-11-21 21:25:07.573056: Pseudo dice [0.8599] +2024-11-21 21:25:07.573180: Epoch time: 20.53 s +2024-11-21 21:25:08.825693: +2024-11-21 21:25:08.825910: Epoch 2001 +2024-11-21 21:25:08.826024: Current learning rate: 0.00772 +2024-11-21 21:25:26.823407: train_loss -0.7729 +2024-11-21 21:25:26.823722: val_loss -0.7687 +2024-11-21 21:25:26.823802: Pseudo dice [0.8407] +2024-11-21 21:25:26.823876: Epoch time: 18.0 s +2024-11-21 21:25:27.673193: +2024-11-21 21:25:27.673414: Epoch 2002 +2024-11-21 21:25:27.673524: Current learning rate: 0.00772 +2024-11-21 21:25:46.101494: train_loss -0.7674 +2024-11-21 21:25:46.101716: val_loss -0.7763 +2024-11-21 21:25:46.101792: Pseudo dice [0.8285] +2024-11-21 21:25:46.101870: Epoch time: 18.43 s +2024-11-21 21:25:46.952750: +2024-11-21 21:25:46.952975: Epoch 2003 +2024-11-21 21:25:46.953087: Current learning rate: 0.00772 +2024-11-21 21:26:05.023326: train_loss -0.77 +2024-11-21 21:26:05.023572: val_loss -0.7353 +2024-11-21 21:26:05.023646: Pseudo dice [0.8281] +2024-11-21 21:26:05.023722: Epoch time: 18.07 s +2024-11-21 21:26:05.872486: +2024-11-21 21:26:05.872715: Epoch 2004 +2024-11-21 21:26:05.872826: Current learning rate: 0.00771 +2024-11-21 21:26:25.351681: train_loss -0.7679 +2024-11-21 21:26:25.351919: val_loss -0.7675 +2024-11-21 21:26:25.352000: Pseudo dice [0.8379] +2024-11-21 21:26:25.352085: Epoch time: 19.48 s +2024-11-21 21:26:26.208215: +2024-11-21 21:26:26.208437: Epoch 2005 +2024-11-21 21:26:26.208542: Current learning rate: 0.00771 +2024-11-21 21:26:44.422865: train_loss -0.7795 +2024-11-21 21:26:44.423095: val_loss -0.7819 +2024-11-21 21:26:44.423184: Pseudo dice [0.8528] +2024-11-21 21:26:44.423261: Epoch time: 18.22 s +2024-11-21 21:26:45.272003: +2024-11-21 21:26:45.272223: Epoch 2006 +2024-11-21 21:26:45.272332: Current learning rate: 0.00771 +2024-11-21 21:27:02.480675: train_loss -0.7715 +2024-11-21 21:27:02.503928: val_loss -0.7497 +2024-11-21 21:27:02.504131: Pseudo dice [0.8368] +2024-11-21 21:27:02.504217: Epoch time: 17.21 s +2024-11-21 21:27:03.385602: +2024-11-21 21:27:03.385812: Epoch 2007 +2024-11-21 21:27:03.385922: Current learning rate: 0.00771 +2024-11-21 21:27:21.505128: train_loss -0.7795 +2024-11-21 21:27:21.510537: val_loss -0.7661 +2024-11-21 21:27:21.510653: Pseudo dice [0.841] +2024-11-21 21:27:21.510743: Epoch time: 18.12 s +2024-11-21 21:27:22.447268: +2024-11-21 21:27:22.447522: Epoch 2008 +2024-11-21 21:27:22.447631: Current learning rate: 0.00771 +2024-11-21 21:27:39.873379: train_loss -0.7702 +2024-11-21 21:27:39.873594: val_loss -0.7517 +2024-11-21 21:27:39.873674: Pseudo dice [0.8321] +2024-11-21 21:27:39.873750: Epoch time: 17.43 s +2024-11-21 21:27:40.715590: +2024-11-21 21:27:40.715816: Epoch 2009 +2024-11-21 21:27:40.715932: Current learning rate: 0.00771 +2024-11-21 21:27:59.179503: train_loss -0.7728 +2024-11-21 21:27:59.179799: val_loss -0.7572 +2024-11-21 21:27:59.179878: Pseudo dice [0.8474] +2024-11-21 21:27:59.179955: Epoch time: 18.46 s +2024-11-21 21:28:00.029745: +2024-11-21 21:28:00.029963: Epoch 2010 +2024-11-21 21:28:00.030081: Current learning rate: 0.00771 +2024-11-21 21:28:17.466850: train_loss -0.7708 +2024-11-21 21:28:17.467199: val_loss -0.7747 +2024-11-21 21:28:17.467283: Pseudo dice [0.8379] +2024-11-21 21:28:17.467373: Epoch time: 17.44 s +2024-11-21 21:28:18.328661: +2024-11-21 21:28:18.328852: Epoch 2011 +2024-11-21 21:28:18.328959: Current learning rate: 0.00771 +2024-11-21 21:28:38.021160: train_loss -0.7706 +2024-11-21 21:28:38.021381: val_loss -0.7786 +2024-11-21 21:28:38.021459: Pseudo dice [0.836] +2024-11-21 21:28:38.021531: Epoch time: 19.69 s +2024-11-21 21:28:38.881150: +2024-11-21 21:28:38.881589: Epoch 2012 +2024-11-21 21:28:38.881723: Current learning rate: 0.0077 +2024-11-21 21:28:57.884969: train_loss -0.7725 +2024-11-21 21:28:57.885487: val_loss -0.7421 +2024-11-21 21:28:57.885587: Pseudo dice [0.8205] +2024-11-21 21:28:57.885663: Epoch time: 19.0 s +2024-11-21 21:28:58.735384: +2024-11-21 21:28:58.735636: Epoch 2013 +2024-11-21 21:28:58.735747: Current learning rate: 0.0077 +2024-11-21 21:29:19.018265: train_loss -0.7676 +2024-11-21 21:29:19.018503: val_loss -0.768 +2024-11-21 21:29:19.018589: Pseudo dice [0.8475] +2024-11-21 21:29:19.018695: Epoch time: 20.28 s +2024-11-21 21:29:19.865944: +2024-11-21 21:29:19.866250: Epoch 2014 +2024-11-21 21:29:19.866361: Current learning rate: 0.0077 +2024-11-21 21:29:38.661036: train_loss -0.7686 +2024-11-21 21:29:38.661326: val_loss -0.7594 +2024-11-21 21:29:38.661404: Pseudo dice [0.8344] +2024-11-21 21:29:38.661484: Epoch time: 18.8 s +2024-11-21 21:29:39.631222: +2024-11-21 21:29:39.631438: Epoch 2015 +2024-11-21 21:29:39.631547: Current learning rate: 0.0077 +2024-11-21 21:29:59.807782: train_loss -0.7624 +2024-11-21 21:29:59.807999: val_loss -0.7395 +2024-11-21 21:29:59.808073: Pseudo dice [0.8132] +2024-11-21 21:29:59.808147: Epoch time: 20.18 s +2024-11-21 21:30:00.660061: +2024-11-21 21:30:00.660341: Epoch 2016 +2024-11-21 21:30:00.660451: Current learning rate: 0.0077 +2024-11-21 21:30:20.019188: train_loss -0.7719 +2024-11-21 21:30:20.019403: val_loss -0.7415 +2024-11-21 21:30:20.019482: Pseudo dice [0.8372] +2024-11-21 21:30:20.019558: Epoch time: 19.36 s +2024-11-21 21:30:20.869109: +2024-11-21 21:30:20.869321: Epoch 2017 +2024-11-21 21:30:20.869428: Current learning rate: 0.0077 +2024-11-21 21:30:38.786206: train_loss -0.7486 +2024-11-21 21:30:38.788636: val_loss -0.7445 +2024-11-21 21:30:38.788731: Pseudo dice [0.8434] +2024-11-21 21:30:38.788815: Epoch time: 17.92 s +2024-11-21 21:30:39.736326: +2024-11-21 21:30:39.736540: Epoch 2018 +2024-11-21 21:30:39.736648: Current learning rate: 0.0077 +2024-11-21 21:30:58.960512: train_loss -0.7672 +2024-11-21 21:30:58.960812: val_loss -0.7273 +2024-11-21 21:30:58.960891: Pseudo dice [0.8368] +2024-11-21 21:30:58.960968: Epoch time: 19.23 s +2024-11-21 21:30:59.815551: +2024-11-21 21:30:59.815773: Epoch 2019 +2024-11-21 21:30:59.815883: Current learning rate: 0.0077 +2024-11-21 21:31:18.201795: train_loss -0.762 +2024-11-21 21:31:18.202017: val_loss -0.7558 +2024-11-21 21:31:18.202108: Pseudo dice [0.8495] +2024-11-21 21:31:18.202240: Epoch time: 18.39 s +2024-11-21 21:31:19.055720: +2024-11-21 21:31:19.055939: Epoch 2020 +2024-11-21 21:31:19.056058: Current learning rate: 0.0077 +2024-11-21 21:31:37.473128: train_loss -0.7755 +2024-11-21 21:31:37.473350: val_loss -0.7352 +2024-11-21 21:31:37.473424: Pseudo dice [0.8025] +2024-11-21 21:31:37.473501: Epoch time: 18.42 s +2024-11-21 21:31:38.324425: +2024-11-21 21:31:38.324644: Epoch 2021 +2024-11-21 21:31:38.324755: Current learning rate: 0.00769 +2024-11-21 21:31:56.551278: train_loss -0.7671 +2024-11-21 21:31:56.551535: val_loss -0.7554 +2024-11-21 21:31:56.551612: Pseudo dice [0.8518] +2024-11-21 21:31:56.551694: Epoch time: 18.23 s +2024-11-21 21:31:57.399949: +2024-11-21 21:31:57.400168: Epoch 2022 +2024-11-21 21:31:57.400279: Current learning rate: 0.00769 +2024-11-21 21:32:15.339383: train_loss -0.7768 +2024-11-21 21:32:15.339599: val_loss -0.7703 +2024-11-21 21:32:15.339675: Pseudo dice [0.8394] +2024-11-21 21:32:15.339751: Epoch time: 17.94 s +2024-11-21 21:32:16.532755: +2024-11-21 21:32:16.532967: Epoch 2023 +2024-11-21 21:32:16.533080: Current learning rate: 0.00769 +2024-11-21 21:32:34.037875: train_loss -0.7738 +2024-11-21 21:32:34.038100: val_loss -0.7342 +2024-11-21 21:32:34.038177: Pseudo dice [0.8307] +2024-11-21 21:32:34.038254: Epoch time: 17.51 s +2024-11-21 21:32:34.881231: +2024-11-21 21:32:34.881561: Epoch 2024 +2024-11-21 21:32:34.881670: Current learning rate: 0.00769 +2024-11-21 21:32:54.078099: train_loss -0.7746 +2024-11-21 21:32:54.078349: val_loss -0.7606 +2024-11-21 21:32:54.078429: Pseudo dice [0.8331] +2024-11-21 21:32:54.078511: Epoch time: 19.2 s +2024-11-21 21:32:54.934684: +2024-11-21 21:32:54.934916: Epoch 2025 +2024-11-21 21:32:54.935032: Current learning rate: 0.00769 +2024-11-21 21:33:13.007449: train_loss -0.7793 +2024-11-21 21:33:13.007662: val_loss -0.7494 +2024-11-21 21:33:13.007735: Pseudo dice [0.8391] +2024-11-21 21:33:13.007809: Epoch time: 18.07 s +2024-11-21 21:33:13.852882: +2024-11-21 21:33:13.853114: Epoch 2026 +2024-11-21 21:33:13.853224: Current learning rate: 0.00769 +2024-11-21 21:33:32.077054: train_loss -0.7827 +2024-11-21 21:33:32.077282: val_loss -0.7733 +2024-11-21 21:33:32.077365: Pseudo dice [0.8492] +2024-11-21 21:33:32.077442: Epoch time: 18.22 s +2024-11-21 21:33:32.936906: +2024-11-21 21:33:32.937192: Epoch 2027 +2024-11-21 21:33:32.937302: Current learning rate: 0.00769 +2024-11-21 21:33:51.169326: train_loss -0.7828 +2024-11-21 21:33:51.169559: val_loss -0.7492 +2024-11-21 21:33:51.169639: Pseudo dice [0.836] +2024-11-21 21:33:51.169713: Epoch time: 18.23 s +2024-11-21 21:33:52.021374: +2024-11-21 21:33:52.021596: Epoch 2028 +2024-11-21 21:33:52.021711: Current learning rate: 0.00769 +2024-11-21 21:34:10.509601: train_loss -0.7785 +2024-11-21 21:34:10.509912: val_loss -0.7723 +2024-11-21 21:34:10.510002: Pseudo dice [0.8371] +2024-11-21 21:34:10.510088: Epoch time: 18.49 s +2024-11-21 21:34:11.365737: +2024-11-21 21:34:11.365947: Epoch 2029 +2024-11-21 21:34:11.366056: Current learning rate: 0.00769 +2024-11-21 21:34:29.085064: train_loss -0.7754 +2024-11-21 21:34:29.087501: val_loss -0.7959 +2024-11-21 21:34:29.087607: Pseudo dice [0.8495] +2024-11-21 21:34:29.087684: Epoch time: 17.72 s +2024-11-21 21:34:29.992231: +2024-11-21 21:34:29.992446: Epoch 2030 +2024-11-21 21:34:29.992556: Current learning rate: 0.00768 +2024-11-21 21:34:48.119280: train_loss -0.7734 +2024-11-21 21:34:48.119509: val_loss -0.7446 +2024-11-21 21:34:48.119584: Pseudo dice [0.8448] +2024-11-21 21:34:48.119658: Epoch time: 18.13 s +2024-11-21 21:34:48.969392: +2024-11-21 21:34:48.969604: Epoch 2031 +2024-11-21 21:34:48.969717: Current learning rate: 0.00768 +2024-11-21 21:35:07.266694: train_loss -0.7626 +2024-11-21 21:35:07.266950: val_loss -0.7514 +2024-11-21 21:35:07.267094: Pseudo dice [0.8324] +2024-11-21 21:35:07.267173: Epoch time: 18.3 s +2024-11-21 21:35:08.203035: +2024-11-21 21:35:08.203407: Epoch 2032 +2024-11-21 21:35:08.203519: Current learning rate: 0.00768 +2024-11-21 21:35:26.229703: train_loss -0.7748 +2024-11-21 21:35:26.235145: val_loss -0.7908 +2024-11-21 21:35:26.235293: Pseudo dice [0.8399] +2024-11-21 21:35:26.235599: Epoch time: 18.03 s +2024-11-21 21:35:27.364046: +2024-11-21 21:35:27.364239: Epoch 2033 +2024-11-21 21:35:27.364347: Current learning rate: 0.00768 +2024-11-21 21:35:46.360933: train_loss -0.7689 +2024-11-21 21:35:46.361214: val_loss -0.7678 +2024-11-21 21:35:46.361291: Pseudo dice [0.8496] +2024-11-21 21:35:46.361366: Epoch time: 19.0 s +2024-11-21 21:35:47.208555: +2024-11-21 21:35:47.208770: Epoch 2034 +2024-11-21 21:35:47.208891: Current learning rate: 0.00768 +2024-11-21 21:36:06.189024: train_loss -0.7821 +2024-11-21 21:36:06.189244: val_loss -0.7502 +2024-11-21 21:36:06.189322: Pseudo dice [0.845] +2024-11-21 21:36:06.189398: Epoch time: 18.98 s +2024-11-21 21:36:07.427141: +2024-11-21 21:36:07.427346: Epoch 2035 +2024-11-21 21:36:07.427476: Current learning rate: 0.00768 +2024-11-21 21:36:25.243401: train_loss -0.7741 +2024-11-21 21:36:25.243649: val_loss -0.7648 +2024-11-21 21:36:25.243728: Pseudo dice [0.8442] +2024-11-21 21:36:25.243819: Epoch time: 17.82 s +2024-11-21 21:36:26.217116: +2024-11-21 21:36:26.217408: Epoch 2036 +2024-11-21 21:36:26.217519: Current learning rate: 0.00768 +2024-11-21 21:36:44.425774: train_loss -0.7741 +2024-11-21 21:36:44.428185: val_loss -0.7632 +2024-11-21 21:36:44.428271: Pseudo dice [0.8526] +2024-11-21 21:36:44.428349: Epoch time: 18.21 s +2024-11-21 21:36:45.424214: +2024-11-21 21:36:45.424426: Epoch 2037 +2024-11-21 21:36:45.424537: Current learning rate: 0.00768 +2024-11-21 21:37:03.617347: train_loss -0.7663 +2024-11-21 21:37:03.617587: val_loss -0.7854 +2024-11-21 21:37:03.617664: Pseudo dice [0.8384] +2024-11-21 21:37:03.617739: Epoch time: 18.19 s +2024-11-21 21:37:04.465377: +2024-11-21 21:37:04.465605: Epoch 2038 +2024-11-21 21:37:04.465707: Current learning rate: 0.00767 +2024-11-21 21:37:22.854923: train_loss -0.7706 +2024-11-21 21:37:22.855175: val_loss -0.7485 +2024-11-21 21:37:22.855253: Pseudo dice [0.8478] +2024-11-21 21:37:22.855339: Epoch time: 18.39 s +2024-11-21 21:37:23.707197: +2024-11-21 21:37:23.707395: Epoch 2039 +2024-11-21 21:37:23.707502: Current learning rate: 0.00767 +2024-11-21 21:37:42.369841: train_loss -0.7734 +2024-11-21 21:37:42.370099: val_loss -0.7471 +2024-11-21 21:37:42.370181: Pseudo dice [0.8494] +2024-11-21 21:37:42.370261: Epoch time: 18.66 s +2024-11-21 21:37:43.222842: +2024-11-21 21:37:43.223057: Epoch 2040 +2024-11-21 21:37:43.223167: Current learning rate: 0.00767 +2024-11-21 21:38:01.618929: train_loss -0.7657 +2024-11-21 21:38:01.619148: val_loss -0.7664 +2024-11-21 21:38:01.619223: Pseudo dice [0.8254] +2024-11-21 21:38:01.619296: Epoch time: 18.4 s +2024-11-21 21:38:02.473284: +2024-11-21 21:38:02.473595: Epoch 2041 +2024-11-21 21:38:02.473710: Current learning rate: 0.00767 +2024-11-21 21:38:22.012105: train_loss -0.776 +2024-11-21 21:38:22.012327: val_loss -0.7612 +2024-11-21 21:38:22.012401: Pseudo dice [0.8588] +2024-11-21 21:38:22.017689: Epoch time: 19.54 s +2024-11-21 21:38:22.995301: +2024-11-21 21:38:22.995500: Epoch 2042 +2024-11-21 21:38:22.995609: Current learning rate: 0.00767 +2024-11-21 21:38:40.983939: train_loss -0.7718 +2024-11-21 21:38:40.984171: val_loss -0.7705 +2024-11-21 21:38:40.984248: Pseudo dice [0.8484] +2024-11-21 21:38:40.984324: Epoch time: 17.99 s +2024-11-21 21:38:41.843117: +2024-11-21 21:38:41.843328: Epoch 2043 +2024-11-21 21:38:41.843437: Current learning rate: 0.00767 +2024-11-21 21:39:00.312874: train_loss -0.7612 +2024-11-21 21:39:00.313113: val_loss -0.7617 +2024-11-21 21:39:00.313192: Pseudo dice [0.8413] +2024-11-21 21:39:00.313267: Epoch time: 18.47 s +2024-11-21 21:39:01.167950: +2024-11-21 21:39:01.168173: Epoch 2044 +2024-11-21 21:39:01.168288: Current learning rate: 0.00767 +2024-11-21 21:39:19.676253: train_loss -0.7675 +2024-11-21 21:39:19.676471: val_loss -0.7466 +2024-11-21 21:39:19.676548: Pseudo dice [0.8263] +2024-11-21 21:39:19.676622: Epoch time: 18.51 s +2024-11-21 21:39:20.675882: +2024-11-21 21:39:20.676150: Epoch 2045 +2024-11-21 21:39:20.676261: Current learning rate: 0.00767 +2024-11-21 21:39:38.375852: train_loss -0.7635 +2024-11-21 21:39:38.376098: val_loss -0.7317 +2024-11-21 21:39:38.376182: Pseudo dice [0.8178] +2024-11-21 21:39:38.376266: Epoch time: 17.7 s +2024-11-21 21:39:39.685712: +2024-11-21 21:39:39.685928: Epoch 2046 +2024-11-21 21:39:39.686045: Current learning rate: 0.00767 +2024-11-21 21:39:57.392973: train_loss -0.7705 +2024-11-21 21:39:57.393248: val_loss -0.7823 +2024-11-21 21:39:57.393322: Pseudo dice [0.8476] +2024-11-21 21:39:57.393399: Epoch time: 17.71 s +2024-11-21 21:39:58.212099: +2024-11-21 21:39:58.212424: Epoch 2047 +2024-11-21 21:39:58.212536: Current learning rate: 0.00766 +2024-11-21 21:40:16.485082: train_loss -0.7762 +2024-11-21 21:40:16.485289: val_loss -0.7702 +2024-11-21 21:40:16.485363: Pseudo dice [0.8397] +2024-11-21 21:40:16.485438: Epoch time: 18.27 s +2024-11-21 21:40:17.302035: +2024-11-21 21:40:17.302282: Epoch 2048 +2024-11-21 21:40:17.302392: Current learning rate: 0.00766 +2024-11-21 21:40:34.619040: train_loss -0.7794 +2024-11-21 21:40:34.619269: val_loss -0.7653 +2024-11-21 21:40:34.619344: Pseudo dice [0.8447] +2024-11-21 21:40:34.619421: Epoch time: 17.32 s +2024-11-21 21:40:35.569924: +2024-11-21 21:40:35.570180: Epoch 2049 +2024-11-21 21:40:35.570324: Current learning rate: 0.00766 +2024-11-21 21:40:54.747538: train_loss -0.7722 +2024-11-21 21:40:54.747793: val_loss -0.7502 +2024-11-21 21:40:54.747871: Pseudo dice [0.8356] +2024-11-21 21:40:54.747953: Epoch time: 19.18 s +2024-11-21 21:40:55.783110: +2024-11-21 21:40:55.783332: Epoch 2050 +2024-11-21 21:40:55.783442: Current learning rate: 0.00766 +2024-11-21 21:41:14.919476: train_loss -0.7678 +2024-11-21 21:41:14.919825: val_loss -0.7512 +2024-11-21 21:41:14.919908: Pseudo dice [0.8441] +2024-11-21 21:41:14.919982: Epoch time: 19.14 s +2024-11-21 21:41:15.746635: +2024-11-21 21:41:15.746857: Epoch 2051 +2024-11-21 21:41:15.746966: Current learning rate: 0.00766 +2024-11-21 21:41:33.423627: train_loss -0.7579 +2024-11-21 21:41:33.423855: val_loss -0.7373 +2024-11-21 21:41:33.423933: Pseudo dice [0.8413] +2024-11-21 21:41:33.424020: Epoch time: 17.68 s +2024-11-21 21:41:34.261514: +2024-11-21 21:41:34.261849: Epoch 2052 +2024-11-21 21:41:34.261958: Current learning rate: 0.00766 +2024-11-21 21:41:51.132691: train_loss -0.7639 +2024-11-21 21:41:51.132919: val_loss -0.7668 +2024-11-21 21:41:51.133013: Pseudo dice [0.8574] +2024-11-21 21:41:51.133091: Epoch time: 16.87 s +2024-11-21 21:41:51.954983: +2024-11-21 21:41:51.955262: Epoch 2053 +2024-11-21 21:41:51.955372: Current learning rate: 0.00766 +2024-11-21 21:42:10.127274: train_loss -0.7731 +2024-11-21 21:42:10.127532: val_loss -0.7755 +2024-11-21 21:42:10.127608: Pseudo dice [0.856] +2024-11-21 21:42:10.127696: Epoch time: 18.17 s +2024-11-21 21:42:11.076644: +2024-11-21 21:42:11.076901: Epoch 2054 +2024-11-21 21:42:11.077028: Current learning rate: 0.00766 +2024-11-21 21:42:29.150277: train_loss -0.766 +2024-11-21 21:42:29.153968: val_loss -0.7791 +2024-11-21 21:42:29.154127: Pseudo dice [0.8591] +2024-11-21 21:42:29.154215: Epoch time: 18.07 s +2024-11-21 21:42:29.154279: Yayy! New best EMA pseudo Dice: 0.8451 +2024-11-21 21:42:30.184599: +2024-11-21 21:42:30.184815: Epoch 2055 +2024-11-21 21:42:30.184930: Current learning rate: 0.00766 +2024-11-21 21:42:47.844325: train_loss -0.7701 +2024-11-21 21:42:47.844553: val_loss -0.7461 +2024-11-21 21:42:47.844710: Pseudo dice [0.8405] +2024-11-21 21:42:47.844789: Epoch time: 17.66 s +2024-11-21 21:42:48.667574: +2024-11-21 21:42:48.667804: Epoch 2056 +2024-11-21 21:42:48.667928: Current learning rate: 0.00765 +2024-11-21 21:43:08.374816: train_loss -0.7695 +2024-11-21 21:43:08.375136: val_loss -0.7352 +2024-11-21 21:43:08.375236: Pseudo dice [0.8298] +2024-11-21 21:43:08.375322: Epoch time: 19.71 s +2024-11-21 21:43:09.204392: +2024-11-21 21:43:09.204579: Epoch 2057 +2024-11-21 21:43:09.204917: Current learning rate: 0.00765 +2024-11-21 21:43:27.301412: train_loss -0.7666 +2024-11-21 21:43:27.301974: val_loss -0.7695 +2024-11-21 21:43:27.302114: Pseudo dice [0.8341] +2024-11-21 21:43:27.302191: Epoch time: 18.1 s +2024-11-21 21:43:28.119766: +2024-11-21 21:43:28.120020: Epoch 2058 +2024-11-21 21:43:28.120131: Current learning rate: 0.00765 +2024-11-21 21:43:45.907201: train_loss -0.7792 +2024-11-21 21:43:45.907421: val_loss -0.7474 +2024-11-21 21:43:45.907832: Pseudo dice [0.8374] +2024-11-21 21:43:45.907925: Epoch time: 17.79 s +2024-11-21 21:43:46.733958: +2024-11-21 21:43:46.734187: Epoch 2059 +2024-11-21 21:43:46.734300: Current learning rate: 0.00765 +2024-11-21 21:44:04.540316: train_loss -0.7711 +2024-11-21 21:44:04.540589: val_loss -0.7469 +2024-11-21 21:44:04.540667: Pseudo dice [0.8384] +2024-11-21 21:44:04.540746: Epoch time: 17.81 s +2024-11-21 21:44:05.375945: +2024-11-21 21:44:05.376177: Epoch 2060 +2024-11-21 21:44:05.376286: Current learning rate: 0.00765 +2024-11-21 21:44:23.091834: train_loss -0.7893 +2024-11-21 21:44:23.092066: val_loss -0.7766 +2024-11-21 21:44:23.092139: Pseudo dice [0.8459] +2024-11-21 21:44:23.092213: Epoch time: 17.72 s +2024-11-21 21:44:23.916285: +2024-11-21 21:44:23.916516: Epoch 2061 +2024-11-21 21:44:23.916625: Current learning rate: 0.00765 +2024-11-21 21:44:42.567714: train_loss -0.7758 +2024-11-21 21:44:42.567929: val_loss -0.758 +2024-11-21 21:44:42.568008: Pseudo dice [0.8415] +2024-11-21 21:44:42.568086: Epoch time: 18.65 s +2024-11-21 21:44:43.442302: +2024-11-21 21:44:43.442530: Epoch 2062 +2024-11-21 21:44:43.442645: Current learning rate: 0.00765 +2024-11-21 21:45:01.838167: train_loss -0.7818 +2024-11-21 21:45:01.838470: val_loss -0.8008 +2024-11-21 21:45:01.838552: Pseudo dice [0.8531] +2024-11-21 21:45:01.838630: Epoch time: 18.4 s +2024-11-21 21:45:02.738890: +2024-11-21 21:45:02.739095: Epoch 2063 +2024-11-21 21:45:02.739205: Current learning rate: 0.00765 +2024-11-21 21:45:20.635453: train_loss -0.7748 +2024-11-21 21:45:20.635686: val_loss -0.7864 +2024-11-21 21:45:20.635763: Pseudo dice [0.8503] +2024-11-21 21:45:20.635840: Epoch time: 17.9 s +2024-11-21 21:45:21.459960: +2024-11-21 21:45:21.460189: Epoch 2064 +2024-11-21 21:45:21.460300: Current learning rate: 0.00764 +2024-11-21 21:45:39.541447: train_loss -0.7808 +2024-11-21 21:45:39.541663: val_loss -0.768 +2024-11-21 21:45:39.541737: Pseudo dice [0.8543] +2024-11-21 21:45:39.541810: Epoch time: 18.08 s +2024-11-21 21:45:40.365227: +2024-11-21 21:45:40.365455: Epoch 2065 +2024-11-21 21:45:40.365569: Current learning rate: 0.00764 +2024-11-21 21:45:58.742550: train_loss -0.7684 +2024-11-21 21:45:58.742768: val_loss -0.7336 +2024-11-21 21:45:58.742843: Pseudo dice [0.8335] +2024-11-21 21:45:58.742919: Epoch time: 18.38 s +2024-11-21 21:45:59.569997: +2024-11-21 21:45:59.570201: Epoch 2066 +2024-11-21 21:45:59.570310: Current learning rate: 0.00764 +2024-11-21 21:46:17.352503: train_loss -0.7845 +2024-11-21 21:46:17.352712: val_loss -0.7737 +2024-11-21 21:46:17.352787: Pseudo dice [0.8472] +2024-11-21 21:46:17.352865: Epoch time: 17.78 s +2024-11-21 21:46:18.224274: +2024-11-21 21:46:18.224555: Epoch 2067 +2024-11-21 21:46:18.224669: Current learning rate: 0.00764 +2024-11-21 21:46:36.750036: train_loss -0.7616 +2024-11-21 21:46:36.750251: val_loss -0.7374 +2024-11-21 21:46:36.750324: Pseudo dice [0.8306] +2024-11-21 21:46:36.750400: Epoch time: 18.53 s +2024-11-21 21:46:37.573530: +2024-11-21 21:46:37.573736: Epoch 2068 +2024-11-21 21:46:37.573845: Current learning rate: 0.00764 +2024-11-21 21:46:56.346818: train_loss -0.7572 +2024-11-21 21:46:56.349242: val_loss -0.7592 +2024-11-21 21:46:56.349338: Pseudo dice [0.8214] +2024-11-21 21:46:56.349420: Epoch time: 18.77 s +2024-11-21 21:46:57.466041: +2024-11-21 21:46:57.466388: Epoch 2069 +2024-11-21 21:46:57.466502: Current learning rate: 0.00764 +2024-11-21 21:47:15.794366: train_loss -0.7611 +2024-11-21 21:47:15.794941: val_loss -0.7648 +2024-11-21 21:47:15.795060: Pseudo dice [0.8412] +2024-11-21 21:47:15.795415: Epoch time: 18.33 s +2024-11-21 21:47:16.622742: +2024-11-21 21:47:16.622948: Epoch 2070 +2024-11-21 21:47:16.623080: Current learning rate: 0.00764 +2024-11-21 21:47:34.755155: train_loss -0.7564 +2024-11-21 21:47:34.755408: val_loss -0.755 +2024-11-21 21:47:34.755484: Pseudo dice [0.8321] +2024-11-21 21:47:34.755564: Epoch time: 18.13 s +2024-11-21 21:47:35.584637: +2024-11-21 21:47:35.584855: Epoch 2071 +2024-11-21 21:47:35.584963: Current learning rate: 0.00764 +2024-11-21 21:47:53.654843: train_loss -0.7662 +2024-11-21 21:47:53.655057: val_loss -0.7347 +2024-11-21 21:47:53.655133: Pseudo dice [0.8303] +2024-11-21 21:47:53.655210: Epoch time: 18.07 s +2024-11-21 21:47:54.482273: +2024-11-21 21:47:54.482498: Epoch 2072 +2024-11-21 21:47:54.482617: Current learning rate: 0.00764 +2024-11-21 21:48:12.184111: train_loss -0.7619 +2024-11-21 21:48:12.184325: val_loss -0.7533 +2024-11-21 21:48:12.184459: Pseudo dice [0.8405] +2024-11-21 21:48:12.184540: Epoch time: 17.7 s +2024-11-21 21:48:13.012024: +2024-11-21 21:48:13.012242: Epoch 2073 +2024-11-21 21:48:13.012353: Current learning rate: 0.00763 +2024-11-21 21:48:31.841346: train_loss -0.7615 +2024-11-21 21:48:31.841582: val_loss -0.7629 +2024-11-21 21:48:31.841666: Pseudo dice [0.8293] +2024-11-21 21:48:31.843915: Epoch time: 18.83 s +2024-11-21 21:48:32.788475: +2024-11-21 21:48:32.788681: Epoch 2074 +2024-11-21 21:48:32.788797: Current learning rate: 0.00763 +2024-11-21 21:48:50.502369: train_loss -0.7687 +2024-11-21 21:48:50.502574: val_loss -0.7555 +2024-11-21 21:48:50.502656: Pseudo dice [0.8451] +2024-11-21 21:48:50.502729: Epoch time: 17.71 s +2024-11-21 21:48:51.324804: +2024-11-21 21:48:51.325027: Epoch 2075 +2024-11-21 21:48:51.325135: Current learning rate: 0.00763 +2024-11-21 21:49:09.979780: train_loss -0.7726 +2024-11-21 21:49:09.980898: val_loss -0.7425 +2024-11-21 21:49:09.980987: Pseudo dice [0.8138] +2024-11-21 21:49:09.981074: Epoch time: 18.66 s +2024-11-21 21:49:10.815712: +2024-11-21 21:49:10.815937: Epoch 2076 +2024-11-21 21:49:10.816053: Current learning rate: 0.00763 +2024-11-21 21:49:28.199890: train_loss -0.7739 +2024-11-21 21:49:28.200128: val_loss -0.7721 +2024-11-21 21:49:28.200205: Pseudo dice [0.8492] +2024-11-21 21:49:28.200285: Epoch time: 17.38 s +2024-11-21 21:49:29.026371: +2024-11-21 21:49:29.026614: Epoch 2077 +2024-11-21 21:49:29.026723: Current learning rate: 0.00763 +2024-11-21 21:49:46.461874: train_loss -0.7784 +2024-11-21 21:49:46.462142: val_loss -0.7712 +2024-11-21 21:49:46.462238: Pseudo dice [0.8575] +2024-11-21 21:49:46.462348: Epoch time: 17.44 s +2024-11-21 21:49:47.285936: +2024-11-21 21:49:47.286174: Epoch 2078 +2024-11-21 21:49:47.286283: Current learning rate: 0.00763 +2024-11-21 21:50:06.935778: train_loss -0.7784 +2024-11-21 21:50:06.936020: val_loss -0.7783 +2024-11-21 21:50:06.936100: Pseudo dice [0.844] +2024-11-21 21:50:06.936174: Epoch time: 19.65 s +2024-11-21 21:50:07.894005: +2024-11-21 21:50:07.894229: Epoch 2079 +2024-11-21 21:50:07.894341: Current learning rate: 0.00763 +2024-11-21 21:50:26.034553: train_loss -0.7745 +2024-11-21 21:50:26.034770: val_loss -0.7717 +2024-11-21 21:50:26.034843: Pseudo dice [0.8527] +2024-11-21 21:50:26.034916: Epoch time: 18.14 s +2024-11-21 21:50:26.859765: +2024-11-21 21:50:26.859982: Epoch 2080 +2024-11-21 21:50:26.860101: Current learning rate: 0.00763 +2024-11-21 21:50:45.702971: train_loss -0.7763 +2024-11-21 21:50:45.703216: val_loss -0.774 +2024-11-21 21:50:45.703367: Pseudo dice [0.8473] +2024-11-21 21:50:45.703452: Epoch time: 18.84 s +2024-11-21 21:50:46.526441: +2024-11-21 21:50:46.526654: Epoch 2081 +2024-11-21 21:50:46.526760: Current learning rate: 0.00763 +2024-11-21 21:51:05.047730: train_loss -0.7782 +2024-11-21 21:51:05.048207: val_loss -0.7716 +2024-11-21 21:51:05.048302: Pseudo dice [0.8404] +2024-11-21 21:51:05.048379: Epoch time: 18.52 s +2024-11-21 21:51:05.870111: +2024-11-21 21:51:05.870334: Epoch 2082 +2024-11-21 21:51:05.870440: Current learning rate: 0.00762 +2024-11-21 21:51:24.680818: train_loss -0.7847 +2024-11-21 21:51:24.692555: val_loss -0.7731 +2024-11-21 21:51:24.692665: Pseudo dice [0.854] +2024-11-21 21:51:24.692743: Epoch time: 18.81 s +2024-11-21 21:51:25.515830: +2024-11-21 21:51:25.516078: Epoch 2083 +2024-11-21 21:51:25.516193: Current learning rate: 0.00762 +2024-11-21 21:51:43.826451: train_loss -0.7819 +2024-11-21 21:51:43.828206: val_loss -0.7618 +2024-11-21 21:51:43.828308: Pseudo dice [0.8473] +2024-11-21 21:51:43.828394: Epoch time: 18.31 s +2024-11-21 21:51:44.726398: +2024-11-21 21:51:44.726614: Epoch 2084 +2024-11-21 21:51:44.726722: Current learning rate: 0.00762 +2024-11-21 21:52:03.182278: train_loss -0.7684 +2024-11-21 21:52:03.182896: val_loss -0.7486 +2024-11-21 21:52:03.183002: Pseudo dice [0.8119] +2024-11-21 21:52:03.183079: Epoch time: 18.46 s +2024-11-21 21:52:04.129816: +2024-11-21 21:52:04.130056: Epoch 2085 +2024-11-21 21:52:04.130167: Current learning rate: 0.00762 +2024-11-21 21:52:22.938394: train_loss -0.7722 +2024-11-21 21:52:22.938617: val_loss -0.7573 +2024-11-21 21:52:22.938692: Pseudo dice [0.8397] +2024-11-21 21:52:22.938766: Epoch time: 18.81 s +2024-11-21 21:52:23.765580: +2024-11-21 21:52:23.765805: Epoch 2086 +2024-11-21 21:52:23.765913: Current learning rate: 0.00762 +2024-11-21 21:52:42.021149: train_loss -0.7698 +2024-11-21 21:52:42.021375: val_loss -0.7603 +2024-11-21 21:52:42.023628: Pseudo dice [0.8341] +2024-11-21 21:52:42.023768: Epoch time: 18.26 s +2024-11-21 21:52:42.865359: +2024-11-21 21:52:42.865554: Epoch 2087 +2024-11-21 21:52:42.865657: Current learning rate: 0.00762 +2024-11-21 21:53:00.389202: train_loss -0.7583 +2024-11-21 21:53:00.389441: val_loss -0.7755 +2024-11-21 21:53:00.389520: Pseudo dice [0.8432] +2024-11-21 21:53:00.389602: Epoch time: 17.52 s +2024-11-21 21:53:01.223665: +2024-11-21 21:53:01.223944: Epoch 2088 +2024-11-21 21:53:01.224063: Current learning rate: 0.00762 +2024-11-21 21:53:20.190798: train_loss -0.7506 +2024-11-21 21:53:20.192333: val_loss -0.7723 +2024-11-21 21:53:20.192410: Pseudo dice [0.8519] +2024-11-21 21:53:20.192486: Epoch time: 18.97 s +2024-11-21 21:53:21.017434: +2024-11-21 21:53:21.017684: Epoch 2089 +2024-11-21 21:53:21.017806: Current learning rate: 0.00762 +2024-11-21 21:53:39.401216: train_loss -0.769 +2024-11-21 21:53:39.401436: val_loss -0.7424 +2024-11-21 21:53:39.401508: Pseudo dice [0.8308] +2024-11-21 21:53:39.401581: Epoch time: 18.38 s +2024-11-21 21:53:40.331705: +2024-11-21 21:53:40.331921: Epoch 2090 +2024-11-21 21:53:40.332032: Current learning rate: 0.00761 +2024-11-21 21:53:58.851416: train_loss -0.7634 +2024-11-21 21:53:58.851645: val_loss -0.7473 +2024-11-21 21:53:58.851721: Pseudo dice [0.8281] +2024-11-21 21:53:58.851809: Epoch time: 18.52 s +2024-11-21 21:53:59.818786: +2024-11-21 21:53:59.819063: Epoch 2091 +2024-11-21 21:53:59.819202: Current learning rate: 0.00761 +2024-11-21 21:54:18.214880: train_loss -0.7821 +2024-11-21 21:54:18.215133: val_loss -0.7681 +2024-11-21 21:54:18.215211: Pseudo dice [0.8445] +2024-11-21 21:54:18.215293: Epoch time: 18.4 s +2024-11-21 21:54:19.047612: +2024-11-21 21:54:19.047814: Epoch 2092 +2024-11-21 21:54:19.047923: Current learning rate: 0.00761 +2024-11-21 21:54:36.847283: train_loss -0.7701 +2024-11-21 21:54:36.847507: val_loss -0.7499 +2024-11-21 21:54:36.847583: Pseudo dice [0.8351] +2024-11-21 21:54:36.847656: Epoch time: 17.8 s +2024-11-21 21:54:37.676972: +2024-11-21 21:54:37.677168: Epoch 2093 +2024-11-21 21:54:37.677280: Current learning rate: 0.00761 +2024-11-21 21:54:55.562745: train_loss -0.772 +2024-11-21 21:54:55.563256: val_loss -0.7533 +2024-11-21 21:54:55.563360: Pseudo dice [0.8289] +2024-11-21 21:54:55.563443: Epoch time: 17.89 s +2024-11-21 21:54:56.395864: +2024-11-21 21:54:56.396098: Epoch 2094 +2024-11-21 21:54:56.396202: Current learning rate: 0.00761 +2024-11-21 21:55:16.549590: train_loss -0.7686 +2024-11-21 21:55:16.550144: val_loss -0.7684 +2024-11-21 21:55:16.550245: Pseudo dice [0.8477] +2024-11-21 21:55:16.550328: Epoch time: 20.15 s +2024-11-21 21:55:17.375712: +2024-11-21 21:55:17.375944: Epoch 2095 +2024-11-21 21:55:17.391448: Current learning rate: 0.00761 +2024-11-21 21:55:35.621961: train_loss -0.7738 +2024-11-21 21:55:35.622285: val_loss -0.7602 +2024-11-21 21:55:35.622363: Pseudo dice [0.8508] +2024-11-21 21:55:35.622437: Epoch time: 18.25 s +2024-11-21 21:55:36.467169: +2024-11-21 21:55:36.467383: Epoch 2096 +2024-11-21 21:55:36.467493: Current learning rate: 0.00761 +2024-11-21 21:55:57.026612: train_loss -0.7694 +2024-11-21 21:55:57.026843: val_loss -0.7409 +2024-11-21 21:55:57.026920: Pseudo dice [0.8348] +2024-11-21 21:55:57.027005: Epoch time: 20.56 s +2024-11-21 21:55:57.859820: +2024-11-21 21:55:57.860033: Epoch 2097 +2024-11-21 21:55:57.860160: Current learning rate: 0.00761 +2024-11-21 21:56:15.805860: train_loss -0.7769 +2024-11-21 21:56:15.806099: val_loss -0.7274 +2024-11-21 21:56:15.806184: Pseudo dice [0.824] +2024-11-21 21:56:15.806276: Epoch time: 17.95 s +2024-11-21 21:56:16.735633: +2024-11-21 21:56:16.735873: Epoch 2098 +2024-11-21 21:56:16.735989: Current learning rate: 0.00761 +2024-11-21 21:56:35.084583: train_loss -0.7693 +2024-11-21 21:56:35.087005: val_loss -0.7661 +2024-11-21 21:56:35.087094: Pseudo dice [0.8388] +2024-11-21 21:56:35.087174: Epoch time: 18.35 s +2024-11-21 21:56:36.233268: +2024-11-21 21:56:36.233490: Epoch 2099 +2024-11-21 21:56:36.233603: Current learning rate: 0.0076 +2024-11-21 21:56:54.123113: train_loss -0.7652 +2024-11-21 21:56:54.123324: val_loss -0.7446 +2024-11-21 21:56:54.123396: Pseudo dice [0.8355] +2024-11-21 21:56:54.123472: Epoch time: 17.89 s +2024-11-21 21:56:55.150422: +2024-11-21 21:56:55.150652: Epoch 2100 +2024-11-21 21:56:55.150760: Current learning rate: 0.0076 +2024-11-21 21:57:13.331137: train_loss -0.7733 +2024-11-21 21:57:13.331350: val_loss -0.7665 +2024-11-21 21:57:13.331424: Pseudo dice [0.8386] +2024-11-21 21:57:13.331496: Epoch time: 18.18 s +2024-11-21 21:57:14.159947: +2024-11-21 21:57:14.160186: Epoch 2101 +2024-11-21 21:57:14.160300: Current learning rate: 0.0076 +2024-11-21 21:57:32.705685: train_loss -0.7748 +2024-11-21 21:57:32.705927: val_loss -0.7561 +2024-11-21 21:57:32.706009: Pseudo dice [0.8277] +2024-11-21 21:57:32.706093: Epoch time: 18.55 s +2024-11-21 21:57:33.570431: +2024-11-21 21:57:33.570686: Epoch 2102 +2024-11-21 21:57:33.570802: Current learning rate: 0.0076 +2024-11-21 21:57:53.223318: train_loss -0.7746 +2024-11-21 21:57:53.223548: val_loss -0.7444 +2024-11-21 21:57:53.223683: Pseudo dice [0.8286] +2024-11-21 21:57:53.223763: Epoch time: 19.65 s +2024-11-21 21:57:54.046148: +2024-11-21 21:57:54.046370: Epoch 2103 +2024-11-21 21:57:54.046482: Current learning rate: 0.0076 +2024-11-21 21:58:13.662868: train_loss -0.7577 +2024-11-21 21:58:13.668264: val_loss -0.7614 +2024-11-21 21:58:13.668380: Pseudo dice [0.8536] +2024-11-21 21:58:13.668468: Epoch time: 19.62 s +2024-11-21 21:58:14.659917: +2024-11-21 21:58:14.660248: Epoch 2104 +2024-11-21 21:58:14.660364: Current learning rate: 0.0076 +2024-11-21 21:58:32.902109: train_loss -0.7626 +2024-11-21 21:58:32.902341: val_loss -0.7458 +2024-11-21 21:58:32.902419: Pseudo dice [0.8317] +2024-11-21 21:58:32.902498: Epoch time: 18.24 s +2024-11-21 21:58:34.076763: +2024-11-21 21:58:34.076988: Epoch 2105 +2024-11-21 21:58:34.077102: Current learning rate: 0.0076 +2024-11-21 21:58:52.411381: train_loss -0.761 +2024-11-21 21:58:52.411637: val_loss -0.758 +2024-11-21 21:58:52.411709: Pseudo dice [0.852] +2024-11-21 21:58:52.411787: Epoch time: 18.34 s +2024-11-21 21:58:53.238981: +2024-11-21 21:58:53.239350: Epoch 2106 +2024-11-21 21:58:53.239467: Current learning rate: 0.0076 +2024-11-21 21:59:10.394618: train_loss -0.7651 +2024-11-21 21:59:10.394848: val_loss -0.761 +2024-11-21 21:59:10.394933: Pseudo dice [0.831] +2024-11-21 21:59:10.395027: Epoch time: 17.16 s +2024-11-21 21:59:11.221017: +2024-11-21 21:59:11.221283: Epoch 2107 +2024-11-21 21:59:11.221396: Current learning rate: 0.00759 +2024-11-21 21:59:29.071279: train_loss -0.77 +2024-11-21 21:59:29.071558: val_loss -0.7331 +2024-11-21 21:59:29.071665: Pseudo dice [0.8487] +2024-11-21 21:59:29.071742: Epoch time: 17.85 s +2024-11-21 21:59:29.927278: +2024-11-21 21:59:29.927505: Epoch 2108 +2024-11-21 21:59:29.927617: Current learning rate: 0.00759 +2024-11-21 21:59:47.924176: train_loss -0.7719 +2024-11-21 21:59:47.924434: val_loss -0.7384 +2024-11-21 21:59:47.924511: Pseudo dice [0.8407] +2024-11-21 21:59:47.924594: Epoch time: 18.0 s +2024-11-21 21:59:48.754609: +2024-11-21 21:59:48.754814: Epoch 2109 +2024-11-21 21:59:48.754922: Current learning rate: 0.00759 +2024-11-21 22:00:06.137745: train_loss -0.7698 +2024-11-21 22:00:06.137966: val_loss -0.7292 +2024-11-21 22:00:06.138047: Pseudo dice [0.8398] +2024-11-21 22:00:06.138123: Epoch time: 17.38 s +2024-11-21 22:00:07.070526: +2024-11-21 22:00:07.070740: Epoch 2110 +2024-11-21 22:00:07.070852: Current learning rate: 0.00759 +2024-11-21 22:00:25.546150: train_loss -0.7777 +2024-11-21 22:00:25.546615: val_loss -0.761 +2024-11-21 22:00:25.546697: Pseudo dice [0.8345] +2024-11-21 22:00:25.546772: Epoch time: 18.48 s +2024-11-21 22:00:26.371584: +2024-11-21 22:00:26.371802: Epoch 2111 +2024-11-21 22:00:26.371917: Current learning rate: 0.00759 +2024-11-21 22:00:45.201372: train_loss -0.7731 +2024-11-21 22:00:45.201677: val_loss -0.751 +2024-11-21 22:00:45.201757: Pseudo dice [0.8477] +2024-11-21 22:00:45.201832: Epoch time: 18.83 s +2024-11-21 22:00:46.165159: +2024-11-21 22:00:46.165384: Epoch 2112 +2024-11-21 22:00:46.165494: Current learning rate: 0.00759 +2024-11-21 22:01:05.201466: train_loss -0.7687 +2024-11-21 22:01:05.201723: val_loss -0.7733 +2024-11-21 22:01:05.201998: Pseudo dice [0.8439] +2024-11-21 22:01:05.202132: Epoch time: 19.04 s +2024-11-21 22:01:06.030453: +2024-11-21 22:01:06.030651: Epoch 2113 +2024-11-21 22:01:06.030758: Current learning rate: 0.00759 +2024-11-21 22:01:23.658910: train_loss -0.7692 +2024-11-21 22:01:23.659132: val_loss -0.7651 +2024-11-21 22:01:23.659206: Pseudo dice [0.8288] +2024-11-21 22:01:23.659281: Epoch time: 17.63 s +2024-11-21 22:01:24.484394: +2024-11-21 22:01:24.484614: Epoch 2114 +2024-11-21 22:01:24.484725: Current learning rate: 0.00759 +2024-11-21 22:01:42.748934: train_loss -0.7646 +2024-11-21 22:01:42.749173: val_loss -0.7692 +2024-11-21 22:01:42.749249: Pseudo dice [0.8246] +2024-11-21 22:01:42.749345: Epoch time: 18.27 s +2024-11-21 22:01:43.579892: +2024-11-21 22:01:43.580112: Epoch 2115 +2024-11-21 22:01:43.580223: Current learning rate: 0.00759 +2024-11-21 22:02:02.419258: train_loss -0.7712 +2024-11-21 22:02:02.419491: val_loss -0.7687 +2024-11-21 22:02:02.419565: Pseudo dice [0.8545] +2024-11-21 22:02:02.419647: Epoch time: 18.84 s +2024-11-21 22:02:03.341062: +2024-11-21 22:02:03.341279: Epoch 2116 +2024-11-21 22:02:03.341398: Current learning rate: 0.00758 +2024-11-21 22:02:21.089074: train_loss -0.7779 +2024-11-21 22:02:21.089353: val_loss -0.7843 +2024-11-21 22:02:21.089428: Pseudo dice [0.848] +2024-11-21 22:02:21.089505: Epoch time: 17.75 s +2024-11-21 22:02:22.284410: +2024-11-21 22:02:22.284693: Epoch 2117 +2024-11-21 22:02:22.284808: Current learning rate: 0.00758 +2024-11-21 22:02:40.628347: train_loss -0.7716 +2024-11-21 22:02:40.628572: val_loss -0.7478 +2024-11-21 22:02:40.628660: Pseudo dice [0.8437] +2024-11-21 22:02:40.628736: Epoch time: 18.34 s +2024-11-21 22:02:41.459020: +2024-11-21 22:02:41.459259: Epoch 2118 +2024-11-21 22:02:41.459367: Current learning rate: 0.00758 +2024-11-21 22:02:59.093932: train_loss -0.7712 +2024-11-21 22:02:59.094177: val_loss -0.7721 +2024-11-21 22:02:59.094253: Pseudo dice [0.8467] +2024-11-21 22:02:59.094334: Epoch time: 17.64 s +2024-11-21 22:02:59.920522: +2024-11-21 22:02:59.920747: Epoch 2119 +2024-11-21 22:02:59.920856: Current learning rate: 0.00758 +2024-11-21 22:03:18.469883: train_loss -0.7686 +2024-11-21 22:03:18.470176: val_loss -0.7822 +2024-11-21 22:03:18.470252: Pseudo dice [0.839] +2024-11-21 22:03:18.470327: Epoch time: 18.55 s +2024-11-21 22:03:19.296056: +2024-11-21 22:03:19.296275: Epoch 2120 +2024-11-21 22:03:19.296385: Current learning rate: 0.00758 +2024-11-21 22:03:38.593122: train_loss -0.7732 +2024-11-21 22:03:38.593336: val_loss -0.78 +2024-11-21 22:03:38.593409: Pseudo dice [0.8423] +2024-11-21 22:03:38.593486: Epoch time: 19.3 s +2024-11-21 22:03:39.422494: +2024-11-21 22:03:39.422724: Epoch 2121 +2024-11-21 22:03:39.422842: Current learning rate: 0.00758 +2024-11-21 22:03:56.838128: train_loss -0.7757 +2024-11-21 22:03:56.838347: val_loss -0.7811 +2024-11-21 22:03:56.838423: Pseudo dice [0.8362] +2024-11-21 22:03:56.838500: Epoch time: 17.42 s +2024-11-21 22:03:57.705306: +2024-11-21 22:03:57.705499: Epoch 2122 +2024-11-21 22:03:57.705608: Current learning rate: 0.00758 +2024-11-21 22:04:15.783787: train_loss -0.7733 +2024-11-21 22:04:15.784045: val_loss -0.7683 +2024-11-21 22:04:15.784120: Pseudo dice [0.8464] +2024-11-21 22:04:15.784200: Epoch time: 18.08 s +2024-11-21 22:04:16.611186: +2024-11-21 22:04:16.611401: Epoch 2123 +2024-11-21 22:04:16.611512: Current learning rate: 0.00758 +2024-11-21 22:04:34.381824: train_loss -0.7705 +2024-11-21 22:04:34.382102: val_loss -0.7635 +2024-11-21 22:04:34.382175: Pseudo dice [0.8404] +2024-11-21 22:04:34.382251: Epoch time: 17.77 s +2024-11-21 22:04:35.204908: +2024-11-21 22:04:35.205141: Epoch 2124 +2024-11-21 22:04:35.205252: Current learning rate: 0.00758 +2024-11-21 22:04:52.827364: train_loss -0.7698 +2024-11-21 22:04:52.831626: val_loss -0.7812 +2024-11-21 22:04:52.831710: Pseudo dice [0.8379] +2024-11-21 22:04:52.831792: Epoch time: 17.62 s +2024-11-21 22:04:53.657973: +2024-11-21 22:04:53.658196: Epoch 2125 +2024-11-21 22:04:53.658308: Current learning rate: 0.00757 +2024-11-21 22:05:11.311264: train_loss -0.7638 +2024-11-21 22:05:11.311501: val_loss -0.7567 +2024-11-21 22:05:11.311583: Pseudo dice [0.8384] +2024-11-21 22:05:11.311681: Epoch time: 17.65 s +2024-11-21 22:05:12.142022: +2024-11-21 22:05:12.142237: Epoch 2126 +2024-11-21 22:05:12.142349: Current learning rate: 0.00757 +2024-11-21 22:05:30.118321: train_loss -0.7784 +2024-11-21 22:05:30.118544: val_loss -0.7836 +2024-11-21 22:05:30.118616: Pseudo dice [0.8571] +2024-11-21 22:05:30.118689: Epoch time: 17.98 s +2024-11-21 22:05:30.950074: +2024-11-21 22:05:30.950329: Epoch 2127 +2024-11-21 22:05:30.950445: Current learning rate: 0.00757 +2024-11-21 22:05:49.205133: train_loss -0.7707 +2024-11-21 22:05:49.205341: val_loss -0.7444 +2024-11-21 22:05:49.205418: Pseudo dice [0.8392] +2024-11-21 22:05:49.205497: Epoch time: 18.26 s +2024-11-21 22:05:50.029139: +2024-11-21 22:05:50.029346: Epoch 2128 +2024-11-21 22:05:50.029457: Current learning rate: 0.00757 +2024-11-21 22:06:08.360915: train_loss -0.7639 +2024-11-21 22:06:08.361137: val_loss -0.7709 +2024-11-21 22:06:08.361214: Pseudo dice [0.8307] +2024-11-21 22:06:08.361287: Epoch time: 18.33 s +2024-11-21 22:06:09.616194: +2024-11-21 22:06:09.616427: Epoch 2129 +2024-11-21 22:06:09.616538: Current learning rate: 0.00757 +2024-11-21 22:06:28.493092: train_loss -0.7595 +2024-11-21 22:06:28.493384: val_loss -0.7564 +2024-11-21 22:06:28.493463: Pseudo dice [0.8332] +2024-11-21 22:06:28.493543: Epoch time: 18.88 s +2024-11-21 22:06:29.323762: +2024-11-21 22:06:29.323980: Epoch 2130 +2024-11-21 22:06:29.324096: Current learning rate: 0.00757 +2024-11-21 22:06:48.705717: train_loss -0.7675 +2024-11-21 22:06:48.705944: val_loss -0.7467 +2024-11-21 22:06:48.711227: Pseudo dice [0.8486] +2024-11-21 22:06:48.711345: Epoch time: 19.38 s +2024-11-21 22:06:49.789043: +2024-11-21 22:06:49.789276: Epoch 2131 +2024-11-21 22:06:49.789385: Current learning rate: 0.00757 +2024-11-21 22:07:08.654950: train_loss -0.7539 +2024-11-21 22:07:08.655237: val_loss -0.7496 +2024-11-21 22:07:08.655315: Pseudo dice [0.8322] +2024-11-21 22:07:08.655425: Epoch time: 18.87 s +2024-11-21 22:07:09.481436: +2024-11-21 22:07:09.481676: Epoch 2132 +2024-11-21 22:07:09.481795: Current learning rate: 0.00757 +2024-11-21 22:07:28.851541: train_loss -0.7725 +2024-11-21 22:07:28.851784: val_loss -0.7541 +2024-11-21 22:07:28.851917: Pseudo dice [0.8418] +2024-11-21 22:07:28.852008: Epoch time: 19.37 s +2024-11-21 22:07:29.682582: +2024-11-21 22:07:29.682814: Epoch 2133 +2024-11-21 22:07:29.682941: Current learning rate: 0.00756 +2024-11-21 22:07:47.785625: train_loss -0.7714 +2024-11-21 22:07:47.785878: val_loss -0.7687 +2024-11-21 22:07:47.785954: Pseudo dice [0.8368] +2024-11-21 22:07:47.786048: Epoch time: 18.1 s +2024-11-21 22:07:48.631450: +2024-11-21 22:07:48.631675: Epoch 2134 +2024-11-21 22:07:48.631784: Current learning rate: 0.00756 +2024-11-21 22:08:07.899544: train_loss -0.7739 +2024-11-21 22:08:07.901964: val_loss -0.77 +2024-11-21 22:08:07.902055: Pseudo dice [0.8485] +2024-11-21 22:08:07.902131: Epoch time: 19.27 s +2024-11-21 22:08:08.868554: +2024-11-21 22:08:08.868876: Epoch 2135 +2024-11-21 22:08:08.868986: Current learning rate: 0.00756 +2024-11-21 22:08:26.259479: train_loss -0.7779 +2024-11-21 22:08:26.259690: val_loss -0.7514 +2024-11-21 22:08:26.259798: Pseudo dice [0.8354] +2024-11-21 22:08:26.259881: Epoch time: 17.39 s +2024-11-21 22:08:27.088248: +2024-11-21 22:08:27.088451: Epoch 2136 +2024-11-21 22:08:27.088560: Current learning rate: 0.00756 +2024-11-21 22:08:45.253932: train_loss -0.7828 +2024-11-21 22:08:45.254195: val_loss -0.7705 +2024-11-21 22:08:45.254315: Pseudo dice [0.8466] +2024-11-21 22:08:45.254431: Epoch time: 18.17 s +2024-11-21 22:08:46.101576: +2024-11-21 22:08:46.101813: Epoch 2137 +2024-11-21 22:08:46.101932: Current learning rate: 0.00756 +2024-11-21 22:09:03.946556: train_loss -0.7741 +2024-11-21 22:09:03.946773: val_loss -0.7615 +2024-11-21 22:09:03.946862: Pseudo dice [0.8449] +2024-11-21 22:09:03.946940: Epoch time: 17.85 s +2024-11-21 22:09:04.776799: +2024-11-21 22:09:04.777018: Epoch 2138 +2024-11-21 22:09:04.777130: Current learning rate: 0.00756 +2024-11-21 22:09:23.947759: train_loss -0.7827 +2024-11-21 22:09:23.947963: val_loss -0.7586 +2024-11-21 22:09:23.948133: Pseudo dice [0.8409] +2024-11-21 22:09:23.948209: Epoch time: 19.17 s +2024-11-21 22:09:24.828456: +2024-11-21 22:09:24.828657: Epoch 2139 +2024-11-21 22:09:24.828766: Current learning rate: 0.00756 +2024-11-21 22:09:43.962749: train_loss -0.7819 +2024-11-21 22:09:43.962951: val_loss -0.7663 +2024-11-21 22:09:43.963031: Pseudo dice [0.8336] +2024-11-21 22:09:43.963109: Epoch time: 19.14 s +2024-11-21 22:09:44.836073: +2024-11-21 22:09:44.836285: Epoch 2140 +2024-11-21 22:09:44.836400: Current learning rate: 0.00756 +2024-11-21 22:10:02.707343: train_loss -0.7752 +2024-11-21 22:10:02.707660: val_loss -0.7426 +2024-11-21 22:10:02.707736: Pseudo dice [0.8395] +2024-11-21 22:10:02.707818: Epoch time: 17.87 s +2024-11-21 22:10:03.954629: +2024-11-21 22:10:03.954834: Epoch 2141 +2024-11-21 22:10:03.954943: Current learning rate: 0.00756 +2024-11-21 22:10:22.867955: train_loss -0.7725 +2024-11-21 22:10:22.868198: val_loss -0.7727 +2024-11-21 22:10:22.868274: Pseudo dice [0.8482] +2024-11-21 22:10:22.868347: Epoch time: 18.91 s +2024-11-21 22:10:23.698540: +2024-11-21 22:10:23.698756: Epoch 2142 +2024-11-21 22:10:23.698869: Current learning rate: 0.00755 +2024-11-21 22:10:41.998519: train_loss -0.7759 +2024-11-21 22:10:41.998739: val_loss -0.7734 +2024-11-21 22:10:41.998814: Pseudo dice [0.8445] +2024-11-21 22:10:41.998892: Epoch time: 18.3 s +2024-11-21 22:10:42.916252: +2024-11-21 22:10:42.916562: Epoch 2143 +2024-11-21 22:10:42.916696: Current learning rate: 0.00755 +2024-11-21 22:11:00.898576: train_loss -0.7773 +2024-11-21 22:11:00.898842: val_loss -0.7568 +2024-11-21 22:11:00.898921: Pseudo dice [0.8274] +2024-11-21 22:11:00.899010: Epoch time: 17.98 s +2024-11-21 22:11:01.730119: +2024-11-21 22:11:01.730343: Epoch 2144 +2024-11-21 22:11:01.730459: Current learning rate: 0.00755 +2024-11-21 22:11:20.867649: train_loss -0.78 +2024-11-21 22:11:20.867924: val_loss -0.765 +2024-11-21 22:11:20.868003: Pseudo dice [0.8364] +2024-11-21 22:11:20.868080: Epoch time: 19.14 s +2024-11-21 22:11:21.709438: +2024-11-21 22:11:21.709636: Epoch 2145 +2024-11-21 22:11:21.709754: Current learning rate: 0.00755 +2024-11-21 22:11:38.984981: train_loss -0.774 +2024-11-21 22:11:38.985201: val_loss -0.7575 +2024-11-21 22:11:38.985288: Pseudo dice [0.8423] +2024-11-21 22:11:38.985364: Epoch time: 17.28 s +2024-11-21 22:11:39.819988: +2024-11-21 22:11:39.820241: Epoch 2146 +2024-11-21 22:11:39.820351: Current learning rate: 0.00755 +2024-11-21 22:11:58.695554: train_loss -0.7764 +2024-11-21 22:11:58.695765: val_loss -0.7767 +2024-11-21 22:11:58.695846: Pseudo dice [0.8454] +2024-11-21 22:11:58.695923: Epoch time: 18.88 s +2024-11-21 22:11:59.529058: +2024-11-21 22:11:59.529271: Epoch 2147 +2024-11-21 22:11:59.529381: Current learning rate: 0.00755 +2024-11-21 22:12:17.444593: train_loss -0.7665 +2024-11-21 22:12:17.444830: val_loss -0.7476 +2024-11-21 22:12:17.444908: Pseudo dice [0.8427] +2024-11-21 22:12:17.445055: Epoch time: 17.92 s +2024-11-21 22:12:18.280022: +2024-11-21 22:12:18.280250: Epoch 2148 +2024-11-21 22:12:18.280360: Current learning rate: 0.00755 +2024-11-21 22:12:37.374610: train_loss -0.7764 +2024-11-21 22:12:37.374836: val_loss -0.7509 +2024-11-21 22:12:37.374915: Pseudo dice [0.8168] +2024-11-21 22:12:37.374989: Epoch time: 19.1 s +2024-11-21 22:12:38.232505: +2024-11-21 22:12:38.232723: Epoch 2149 +2024-11-21 22:12:38.232838: Current learning rate: 0.00755 +2024-11-21 22:12:56.306461: train_loss -0.7756 +2024-11-21 22:12:56.308902: val_loss -0.7594 +2024-11-21 22:12:56.309014: Pseudo dice [0.8431] +2024-11-21 22:12:56.309095: Epoch time: 18.07 s +2024-11-21 22:12:57.352743: +2024-11-21 22:12:57.352948: Epoch 2150 +2024-11-21 22:12:57.353061: Current learning rate: 0.00755 +2024-11-21 22:13:16.197670: train_loss -0.7762 +2024-11-21 22:13:16.197907: val_loss -0.7524 +2024-11-21 22:13:16.197981: Pseudo dice [0.8287] +2024-11-21 22:13:16.198068: Epoch time: 18.85 s +2024-11-21 22:13:17.030545: +2024-11-21 22:13:17.030757: Epoch 2151 +2024-11-21 22:13:17.030865: Current learning rate: 0.00754 +2024-11-21 22:13:36.326527: train_loss -0.7726 +2024-11-21 22:13:36.326737: val_loss -0.7586 +2024-11-21 22:13:36.326814: Pseudo dice [0.8425] +2024-11-21 22:13:36.326890: Epoch time: 19.3 s +2024-11-21 22:13:37.179717: +2024-11-21 22:13:37.180145: Epoch 2152 +2024-11-21 22:13:37.180275: Current learning rate: 0.00754 +2024-11-21 22:13:55.675093: train_loss -0.7737 +2024-11-21 22:13:55.675311: val_loss -0.7734 +2024-11-21 22:13:55.675386: Pseudo dice [0.8507] +2024-11-21 22:13:55.675463: Epoch time: 18.5 s +2024-11-21 22:13:56.924182: +2024-11-21 22:13:56.924472: Epoch 2153 +2024-11-21 22:13:56.924584: Current learning rate: 0.00754 +2024-11-21 22:14:15.583943: train_loss -0.7627 +2024-11-21 22:14:15.584202: val_loss -0.7677 +2024-11-21 22:14:15.584290: Pseudo dice [0.8298] +2024-11-21 22:14:15.584384: Epoch time: 18.66 s +2024-11-21 22:14:16.411063: +2024-11-21 22:14:16.411285: Epoch 2154 +2024-11-21 22:14:16.411391: Current learning rate: 0.00754 +2024-11-21 22:14:34.318011: train_loss -0.7731 +2024-11-21 22:14:34.318233: val_loss -0.775 +2024-11-21 22:14:34.318305: Pseudo dice [0.8543] +2024-11-21 22:14:34.318379: Epoch time: 17.91 s +2024-11-21 22:14:35.147955: +2024-11-21 22:14:35.148182: Epoch 2155 +2024-11-21 22:14:35.148292: Current learning rate: 0.00754 +2024-11-21 22:14:52.470016: train_loss -0.7728 +2024-11-21 22:14:52.470249: val_loss -0.7588 +2024-11-21 22:14:52.470323: Pseudo dice [0.8537] +2024-11-21 22:14:52.470400: Epoch time: 17.32 s +2024-11-21 22:14:53.298090: +2024-11-21 22:14:53.298336: Epoch 2156 +2024-11-21 22:14:53.298459: Current learning rate: 0.00754 +2024-11-21 22:15:13.179390: train_loss -0.7734 +2024-11-21 22:15:13.179610: val_loss -0.7377 +2024-11-21 22:15:13.179699: Pseudo dice [0.8277] +2024-11-21 22:15:13.183029: Epoch time: 19.88 s +2024-11-21 22:15:14.084055: +2024-11-21 22:15:14.084273: Epoch 2157 +2024-11-21 22:15:14.084394: Current learning rate: 0.00754 +2024-11-21 22:15:31.995090: train_loss -0.7757 +2024-11-21 22:15:31.995363: val_loss -0.7565 +2024-11-21 22:15:31.995444: Pseudo dice [0.8387] +2024-11-21 22:15:31.995594: Epoch time: 17.91 s +2024-11-21 22:15:32.836478: +2024-11-21 22:15:32.836679: Epoch 2158 +2024-11-21 22:15:32.836787: Current learning rate: 0.00754 +2024-11-21 22:15:51.020001: train_loss -0.7775 +2024-11-21 22:15:51.025399: val_loss -0.7614 +2024-11-21 22:15:51.025513: Pseudo dice [0.8421] +2024-11-21 22:15:51.025591: Epoch time: 18.18 s +2024-11-21 22:15:52.004138: +2024-11-21 22:15:52.004363: Epoch 2159 +2024-11-21 22:15:52.004474: Current learning rate: 0.00753 +2024-11-21 22:16:10.003651: train_loss -0.7643 +2024-11-21 22:16:10.003877: val_loss -0.757 +2024-11-21 22:16:10.003956: Pseudo dice [0.8289] +2024-11-21 22:16:10.004052: Epoch time: 18.0 s +2024-11-21 22:16:10.852907: +2024-11-21 22:16:10.853126: Epoch 2160 +2024-11-21 22:16:10.853234: Current learning rate: 0.00753 +2024-11-21 22:16:28.979819: train_loss -0.779 +2024-11-21 22:16:28.980049: val_loss -0.7722 +2024-11-21 22:16:28.980129: Pseudo dice [0.8223] +2024-11-21 22:16:28.980207: Epoch time: 18.13 s +2024-11-21 22:16:29.792108: +2024-11-21 22:16:29.792282: Epoch 2161 +2024-11-21 22:16:29.792372: Current learning rate: 0.00753 +2024-11-21 22:16:47.879164: train_loss -0.7818 +2024-11-21 22:16:47.879437: val_loss -0.752 +2024-11-21 22:16:47.879516: Pseudo dice [0.8256] +2024-11-21 22:16:47.879595: Epoch time: 18.09 s +2024-11-21 22:16:48.709298: +2024-11-21 22:16:48.709506: Epoch 2162 +2024-11-21 22:16:48.709612: Current learning rate: 0.00753 +2024-11-21 22:17:07.294701: train_loss -0.7698 +2024-11-21 22:17:07.294923: val_loss -0.7753 +2024-11-21 22:17:07.295008: Pseudo dice [0.8522] +2024-11-21 22:17:07.295086: Epoch time: 18.59 s +2024-11-21 22:17:08.129663: +2024-11-21 22:17:08.129894: Epoch 2163 +2024-11-21 22:17:08.130014: Current learning rate: 0.00753 +2024-11-21 22:17:27.006370: train_loss -0.7722 +2024-11-21 22:17:27.006587: val_loss -0.7867 +2024-11-21 22:17:27.006660: Pseudo dice [0.8536] +2024-11-21 22:17:27.006732: Epoch time: 18.88 s +2024-11-21 22:17:27.947361: +2024-11-21 22:17:27.947590: Epoch 2164 +2024-11-21 22:17:27.947719: Current learning rate: 0.00753 +2024-11-21 22:17:45.892224: train_loss -0.7728 +2024-11-21 22:17:45.892519: val_loss -0.767 +2024-11-21 22:17:45.892631: Pseudo dice [0.8564] +2024-11-21 22:17:45.892771: Epoch time: 17.95 s +2024-11-21 22:17:47.189296: +2024-11-21 22:17:47.189524: Epoch 2165 +2024-11-21 22:17:47.189630: Current learning rate: 0.00753 +2024-11-21 22:18:05.436608: train_loss -0.7819 +2024-11-21 22:18:05.436851: val_loss -0.7769 +2024-11-21 22:18:05.436924: Pseudo dice [0.8383] +2024-11-21 22:18:05.437005: Epoch time: 18.25 s +2024-11-21 22:18:06.272218: +2024-11-21 22:18:06.272609: Epoch 2166 +2024-11-21 22:18:06.272726: Current learning rate: 0.00753 +2024-11-21 22:18:24.938887: train_loss -0.7766 +2024-11-21 22:18:24.939102: val_loss -0.7395 +2024-11-21 22:18:24.939183: Pseudo dice [0.823] +2024-11-21 22:18:24.939257: Epoch time: 18.67 s +2024-11-21 22:18:25.764885: +2024-11-21 22:18:25.765121: Epoch 2167 +2024-11-21 22:18:25.765238: Current learning rate: 0.00753 +2024-11-21 22:18:44.938706: train_loss -0.7854 +2024-11-21 22:18:44.938971: val_loss -0.7899 +2024-11-21 22:18:44.939060: Pseudo dice [0.8508] +2024-11-21 22:18:44.939147: Epoch time: 19.17 s +2024-11-21 22:18:45.817644: +2024-11-21 22:18:45.817854: Epoch 2168 +2024-11-21 22:18:45.817964: Current learning rate: 0.00752 +2024-11-21 22:19:04.021043: train_loss -0.7722 +2024-11-21 22:19:04.021269: val_loss -0.7775 +2024-11-21 22:19:04.021344: Pseudo dice [0.8538] +2024-11-21 22:19:04.021421: Epoch time: 18.2 s +2024-11-21 22:19:04.852347: +2024-11-21 22:19:04.852798: Epoch 2169 +2024-11-21 22:19:04.852911: Current learning rate: 0.00752 +2024-11-21 22:19:23.210040: train_loss -0.7782 +2024-11-21 22:19:23.210268: val_loss -0.7458 +2024-11-21 22:19:23.210343: Pseudo dice [0.8378] +2024-11-21 22:19:23.210420: Epoch time: 18.36 s +2024-11-21 22:19:24.038642: +2024-11-21 22:19:24.038962: Epoch 2170 +2024-11-21 22:19:24.039077: Current learning rate: 0.00752 +2024-11-21 22:19:42.721738: train_loss -0.7736 +2024-11-21 22:19:42.721969: val_loss -0.7507 +2024-11-21 22:19:42.722051: Pseudo dice [0.8256] +2024-11-21 22:19:42.722128: Epoch time: 18.68 s +2024-11-21 22:19:43.552585: +2024-11-21 22:19:43.552791: Epoch 2171 +2024-11-21 22:19:43.552897: Current learning rate: 0.00752 +2024-11-21 22:20:02.914976: train_loss -0.7597 +2024-11-21 22:20:02.915226: val_loss -0.7577 +2024-11-21 22:20:02.915303: Pseudo dice [0.8388] +2024-11-21 22:20:02.915385: Epoch time: 19.36 s +2024-11-21 22:20:03.751417: +2024-11-21 22:20:03.751689: Epoch 2172 +2024-11-21 22:20:03.751801: Current learning rate: 0.00752 +2024-11-21 22:20:21.620521: train_loss -0.7634 +2024-11-21 22:20:21.620732: val_loss -0.7533 +2024-11-21 22:20:21.620806: Pseudo dice [0.8244] +2024-11-21 22:20:21.620879: Epoch time: 17.87 s +2024-11-21 22:20:22.451556: +2024-11-21 22:20:22.451852: Epoch 2173 +2024-11-21 22:20:22.451962: Current learning rate: 0.00752 +2024-11-21 22:20:42.359284: train_loss -0.7647 +2024-11-21 22:20:42.359499: val_loss -0.7467 +2024-11-21 22:20:42.359577: Pseudo dice [0.8369] +2024-11-21 22:20:42.359657: Epoch time: 19.91 s +2024-11-21 22:20:43.249244: +2024-11-21 22:20:43.249464: Epoch 2174 +2024-11-21 22:20:43.249572: Current learning rate: 0.00752 +2024-11-21 22:21:02.435407: train_loss -0.768 +2024-11-21 22:21:02.435630: val_loss -0.7331 +2024-11-21 22:21:02.435709: Pseudo dice [0.8248] +2024-11-21 22:21:02.435792: Epoch time: 19.19 s +2024-11-21 22:21:03.263186: +2024-11-21 22:21:03.263492: Epoch 2175 +2024-11-21 22:21:03.263614: Current learning rate: 0.00752 +2024-11-21 22:21:22.035332: train_loss -0.7751 +2024-11-21 22:21:22.035584: val_loss -0.7594 +2024-11-21 22:21:22.037853: Pseudo dice [0.8341] +2024-11-21 22:21:22.037957: Epoch time: 18.77 s +2024-11-21 22:21:22.988999: +2024-11-21 22:21:22.989218: Epoch 2176 +2024-11-21 22:21:22.989328: Current learning rate: 0.00751 +2024-11-21 22:21:40.978087: train_loss -0.7715 +2024-11-21 22:21:40.978311: val_loss -0.7545 +2024-11-21 22:21:40.978385: Pseudo dice [0.8322] +2024-11-21 22:21:40.978505: Epoch time: 17.99 s +2024-11-21 22:21:42.337374: +2024-11-21 22:21:42.337617: Epoch 2177 +2024-11-21 22:21:42.337727: Current learning rate: 0.00751 +2024-11-21 22:22:00.609740: train_loss -0.7651 +2024-11-21 22:22:00.609959: val_loss -0.7579 +2024-11-21 22:22:00.610045: Pseudo dice [0.8246] +2024-11-21 22:22:00.610136: Epoch time: 18.27 s +2024-11-21 22:22:01.443040: +2024-11-21 22:22:01.443344: Epoch 2178 +2024-11-21 22:22:01.443454: Current learning rate: 0.00751 +2024-11-21 22:22:20.328143: train_loss -0.759 +2024-11-21 22:22:20.333569: val_loss -0.7715 +2024-11-21 22:22:20.333680: Pseudo dice [0.8414] +2024-11-21 22:22:20.333766: Epoch time: 18.89 s +2024-11-21 22:22:21.376979: +2024-11-21 22:22:21.377211: Epoch 2179 +2024-11-21 22:22:21.377332: Current learning rate: 0.00751 +2024-11-21 22:22:39.487850: train_loss -0.7607 +2024-11-21 22:22:39.488068: val_loss -0.7866 +2024-11-21 22:22:39.488145: Pseudo dice [0.8346] +2024-11-21 22:22:39.488220: Epoch time: 18.11 s +2024-11-21 22:22:40.309344: +2024-11-21 22:22:40.309573: Epoch 2180 +2024-11-21 22:22:40.309684: Current learning rate: 0.00751 +2024-11-21 22:22:59.619017: train_loss -0.7688 +2024-11-21 22:22:59.619237: val_loss -0.7339 +2024-11-21 22:22:59.619311: Pseudo dice [0.8099] +2024-11-21 22:22:59.619387: Epoch time: 19.31 s +2024-11-21 22:23:00.627111: +2024-11-21 22:23:00.627330: Epoch 2181 +2024-11-21 22:23:00.627451: Current learning rate: 0.00751 +2024-11-21 22:23:18.339272: train_loss -0.7639 +2024-11-21 22:23:18.339538: val_loss -0.7383 +2024-11-21 22:23:18.339621: Pseudo dice [0.8324] +2024-11-21 22:23:18.339714: Epoch time: 17.71 s +2024-11-21 22:23:19.289956: +2024-11-21 22:23:19.290223: Epoch 2182 +2024-11-21 22:23:19.290349: Current learning rate: 0.00751 +2024-11-21 22:23:38.381944: train_loss -0.751 +2024-11-21 22:23:38.382170: val_loss -0.7615 +2024-11-21 22:23:38.382245: Pseudo dice [0.8262] +2024-11-21 22:23:38.382320: Epoch time: 19.09 s +2024-11-21 22:23:39.235579: +2024-11-21 22:23:39.235883: Epoch 2183 +2024-11-21 22:23:39.236005: Current learning rate: 0.00751 +2024-11-21 22:23:57.934504: train_loss -0.7806 +2024-11-21 22:23:57.934716: val_loss -0.7567 +2024-11-21 22:23:57.934793: Pseudo dice [0.8509] +2024-11-21 22:23:57.934866: Epoch time: 18.7 s +2024-11-21 22:23:58.784498: +2024-11-21 22:23:58.784705: Epoch 2184 +2024-11-21 22:23:58.784814: Current learning rate: 0.00751 +2024-11-21 22:24:17.339789: train_loss -0.7822 +2024-11-21 22:24:17.340030: val_loss -0.7636 +2024-11-21 22:24:17.340111: Pseudo dice [0.8198] +2024-11-21 22:24:17.340191: Epoch time: 18.56 s +2024-11-21 22:24:18.367167: +2024-11-21 22:24:18.367366: Epoch 2185 +2024-11-21 22:24:18.367475: Current learning rate: 0.0075 +2024-11-21 22:24:36.024347: train_loss -0.7742 +2024-11-21 22:24:36.026778: val_loss -0.7745 +2024-11-21 22:24:36.026909: Pseudo dice [0.8544] +2024-11-21 22:24:36.027000: Epoch time: 17.66 s +2024-11-21 22:24:36.901908: +2024-11-21 22:24:36.902181: Epoch 2186 +2024-11-21 22:24:36.902294: Current learning rate: 0.0075 +2024-11-21 22:24:55.281689: train_loss -0.7868 +2024-11-21 22:24:55.281892: val_loss -0.7715 +2024-11-21 22:24:55.281965: Pseudo dice [0.8417] +2024-11-21 22:24:55.282078: Epoch time: 18.38 s +2024-11-21 22:24:56.107907: +2024-11-21 22:24:56.108132: Epoch 2187 +2024-11-21 22:24:56.108239: Current learning rate: 0.0075 +2024-11-21 22:25:14.298067: train_loss -0.7733 +2024-11-21 22:25:14.298280: val_loss -0.7505 +2024-11-21 22:25:14.298355: Pseudo dice [0.8421] +2024-11-21 22:25:14.298432: Epoch time: 18.19 s +2024-11-21 22:25:15.148815: +2024-11-21 22:25:15.149041: Epoch 2188 +2024-11-21 22:25:15.149338: Current learning rate: 0.0075 +2024-11-21 22:25:34.184956: train_loss -0.78 +2024-11-21 22:25:34.186244: val_loss -0.7408 +2024-11-21 22:25:34.186335: Pseudo dice [0.8468] +2024-11-21 22:25:34.186418: Epoch time: 19.04 s +2024-11-21 22:25:35.430827: +2024-11-21 22:25:35.431069: Epoch 2189 +2024-11-21 22:25:35.431186: Current learning rate: 0.0075 +2024-11-21 22:25:54.347946: train_loss -0.7693 +2024-11-21 22:25:54.348235: val_loss -0.7642 +2024-11-21 22:25:54.348319: Pseudo dice [0.8477] +2024-11-21 22:25:54.348401: Epoch time: 18.92 s +2024-11-21 22:25:55.175606: +2024-11-21 22:25:55.175836: Epoch 2190 +2024-11-21 22:25:55.175946: Current learning rate: 0.0075 +2024-11-21 22:26:12.591191: train_loss -0.7587 +2024-11-21 22:26:12.591434: val_loss -0.7483 +2024-11-21 22:26:12.591511: Pseudo dice [0.8333] +2024-11-21 22:26:12.591589: Epoch time: 17.42 s +2024-11-21 22:26:13.530885: +2024-11-21 22:26:13.531174: Epoch 2191 +2024-11-21 22:26:13.531285: Current learning rate: 0.0075 +2024-11-21 22:26:30.829839: train_loss -0.7655 +2024-11-21 22:26:30.830103: val_loss -0.7792 +2024-11-21 22:26:30.830178: Pseudo dice [0.8498] +2024-11-21 22:26:30.830262: Epoch time: 17.3 s +2024-11-21 22:26:31.673649: +2024-11-21 22:26:31.673953: Epoch 2192 +2024-11-21 22:26:31.674092: Current learning rate: 0.0075 +2024-11-21 22:26:50.235106: train_loss -0.7455 +2024-11-21 22:26:50.235314: val_loss -0.7193 +2024-11-21 22:26:50.235389: Pseudo dice [0.819] +2024-11-21 22:26:50.235464: Epoch time: 18.56 s +2024-11-21 22:26:51.065137: +2024-11-21 22:26:51.065376: Epoch 2193 +2024-11-21 22:26:51.065490: Current learning rate: 0.0075 +2024-11-21 22:27:10.058898: train_loss -0.7415 +2024-11-21 22:27:10.060277: val_loss -0.7385 +2024-11-21 22:27:10.060374: Pseudo dice [0.8169] +2024-11-21 22:27:10.060461: Epoch time: 18.99 s +2024-11-21 22:27:10.888718: +2024-11-21 22:27:10.889017: Epoch 2194 +2024-11-21 22:27:10.889130: Current learning rate: 0.00749 +2024-11-21 22:27:30.169704: train_loss -0.7481 +2024-11-21 22:27:30.174274: val_loss -0.7666 +2024-11-21 22:27:30.174397: Pseudo dice [0.8263] +2024-11-21 22:27:30.174477: Epoch time: 19.28 s +2024-11-21 22:27:31.056344: +2024-11-21 22:27:31.056575: Epoch 2195 +2024-11-21 22:27:31.056687: Current learning rate: 0.00749 +2024-11-21 22:27:48.457247: train_loss -0.7554 +2024-11-21 22:27:48.457498: val_loss -0.7495 +2024-11-21 22:27:48.457599: Pseudo dice [0.8158] +2024-11-21 22:27:48.457690: Epoch time: 17.4 s +2024-11-21 22:27:49.297160: +2024-11-21 22:27:49.297386: Epoch 2196 +2024-11-21 22:27:49.297499: Current learning rate: 0.00749 +2024-11-21 22:28:07.272302: train_loss -0.7658 +2024-11-21 22:28:07.272516: val_loss -0.7555 +2024-11-21 22:28:07.272590: Pseudo dice [0.8433] +2024-11-21 22:28:07.284156: Epoch time: 17.98 s +2024-11-21 22:28:08.112103: +2024-11-21 22:28:08.112333: Epoch 2197 +2024-11-21 22:28:08.112454: Current learning rate: 0.00749 +2024-11-21 22:28:25.952027: train_loss -0.756 +2024-11-21 22:28:25.952237: val_loss -0.7633 +2024-11-21 22:28:25.952312: Pseudo dice [0.8412] +2024-11-21 22:28:25.952385: Epoch time: 17.84 s +2024-11-21 22:28:26.773509: +2024-11-21 22:28:26.773811: Epoch 2198 +2024-11-21 22:28:26.773923: Current learning rate: 0.00749 +2024-11-21 22:28:45.091251: train_loss -0.7558 +2024-11-21 22:28:45.091484: val_loss -0.7658 +2024-11-21 22:28:45.091558: Pseudo dice [0.8289] +2024-11-21 22:28:45.091632: Epoch time: 18.32 s +2024-11-21 22:28:45.922560: +2024-11-21 22:28:45.922789: Epoch 2199 +2024-11-21 22:28:45.922895: Current learning rate: 0.00749 +2024-11-21 22:29:05.135167: train_loss -0.7639 +2024-11-21 22:29:05.137582: val_loss -0.7813 +2024-11-21 22:29:05.137723: Pseudo dice [0.8228] +2024-11-21 22:29:05.137823: Epoch time: 19.21 s +2024-11-21 22:29:06.182806: +2024-11-21 22:29:06.183043: Epoch 2200 +2024-11-21 22:29:06.183155: Current learning rate: 0.00749 +2024-11-21 22:29:24.085230: train_loss -0.7673 +2024-11-21 22:29:24.086075: val_loss -0.7597 +2024-11-21 22:29:24.086156: Pseudo dice [0.8473] +2024-11-21 22:29:24.086231: Epoch time: 17.9 s +2024-11-21 22:29:25.315254: +2024-11-21 22:29:25.315480: Epoch 2201 +2024-11-21 22:29:25.315595: Current learning rate: 0.00749 +2024-11-21 22:29:43.379862: train_loss -0.7813 +2024-11-21 22:29:43.380137: val_loss -0.7429 +2024-11-21 22:29:43.380231: Pseudo dice [0.8368] +2024-11-21 22:29:43.380305: Epoch time: 18.07 s +2024-11-21 22:29:44.210769: +2024-11-21 22:29:44.211018: Epoch 2202 +2024-11-21 22:29:44.211128: Current learning rate: 0.00748 +2024-11-21 22:30:03.456820: train_loss -0.768 +2024-11-21 22:30:03.457077: val_loss -0.7507 +2024-11-21 22:30:03.457160: Pseudo dice [0.8425] +2024-11-21 22:30:03.457269: Epoch time: 19.25 s +2024-11-21 22:30:04.288173: +2024-11-21 22:30:04.288477: Epoch 2203 +2024-11-21 22:30:04.288591: Current learning rate: 0.00748 +2024-11-21 22:30:22.606954: train_loss -0.7772 +2024-11-21 22:30:22.607191: val_loss -0.7644 +2024-11-21 22:30:22.607269: Pseudo dice [0.8338] +2024-11-21 22:30:22.607347: Epoch time: 18.32 s +2024-11-21 22:30:23.441315: +2024-11-21 22:30:23.441542: Epoch 2204 +2024-11-21 22:30:23.441658: Current learning rate: 0.00748 +2024-11-21 22:30:41.872567: train_loss -0.7672 +2024-11-21 22:30:41.872793: val_loss -0.7729 +2024-11-21 22:30:41.872869: Pseudo dice [0.8379] +2024-11-21 22:30:41.872945: Epoch time: 18.43 s +2024-11-21 22:30:42.702532: +2024-11-21 22:30:42.702849: Epoch 2205 +2024-11-21 22:30:42.702959: Current learning rate: 0.00748 +2024-11-21 22:31:00.806132: train_loss -0.7837 +2024-11-21 22:31:00.806363: val_loss -0.7845 +2024-11-21 22:31:00.806438: Pseudo dice [0.8493] +2024-11-21 22:31:00.806516: Epoch time: 18.1 s +2024-11-21 22:31:01.898955: +2024-11-21 22:31:01.899184: Epoch 2206 +2024-11-21 22:31:01.899302: Current learning rate: 0.00748 +2024-11-21 22:31:20.294211: train_loss -0.7783 +2024-11-21 22:31:20.294987: val_loss -0.7541 +2024-11-21 22:31:20.295070: Pseudo dice [0.8325] +2024-11-21 22:31:20.295146: Epoch time: 18.4 s +2024-11-21 22:31:21.118740: +2024-11-21 22:31:21.118945: Epoch 2207 +2024-11-21 22:31:21.119060: Current learning rate: 0.00748 +2024-11-21 22:31:38.760317: train_loss -0.7767 +2024-11-21 22:31:38.760546: val_loss -0.7492 +2024-11-21 22:31:38.760620: Pseudo dice [0.8344] +2024-11-21 22:31:38.760694: Epoch time: 17.64 s +2024-11-21 22:31:39.622810: +2024-11-21 22:31:39.623040: Epoch 2208 +2024-11-21 22:31:39.623158: Current learning rate: 0.00748 +2024-11-21 22:31:58.189389: train_loss -0.7716 +2024-11-21 22:31:58.189608: val_loss -0.7572 +2024-11-21 22:31:58.189681: Pseudo dice [0.835] +2024-11-21 22:31:58.189779: Epoch time: 18.57 s +2024-11-21 22:31:59.022420: +2024-11-21 22:31:59.022639: Epoch 2209 +2024-11-21 22:31:59.022747: Current learning rate: 0.00748 +2024-11-21 22:32:17.106759: train_loss -0.7777 +2024-11-21 22:32:17.123137: val_loss -0.7754 +2024-11-21 22:32:17.123243: Pseudo dice [0.8584] +2024-11-21 22:32:17.123330: Epoch time: 18.09 s +2024-11-21 22:32:17.955505: +2024-11-21 22:32:17.955697: Epoch 2210 +2024-11-21 22:32:17.955805: Current learning rate: 0.00748 +2024-11-21 22:32:36.872611: train_loss -0.776 +2024-11-21 22:32:36.872877: val_loss -0.7659 +2024-11-21 22:32:36.872952: Pseudo dice [0.8235] +2024-11-21 22:32:36.873033: Epoch time: 18.92 s +2024-11-21 22:32:37.698580: +2024-11-21 22:32:37.698821: Epoch 2211 +2024-11-21 22:32:37.698932: Current learning rate: 0.00747 +2024-11-21 22:32:55.832559: train_loss -0.7654 +2024-11-21 22:32:55.832783: val_loss -0.7743 +2024-11-21 22:32:55.832862: Pseudo dice [0.8416] +2024-11-21 22:32:55.832937: Epoch time: 18.13 s +2024-11-21 22:32:56.660868: +2024-11-21 22:32:56.661091: Epoch 2212 +2024-11-21 22:32:56.661201: Current learning rate: 0.00747 +2024-11-21 22:33:15.705614: train_loss -0.7791 +2024-11-21 22:33:15.705839: val_loss -0.7648 +2024-11-21 22:33:15.705973: Pseudo dice [0.843] +2024-11-21 22:33:15.706063: Epoch time: 19.05 s +2024-11-21 22:33:16.916342: +2024-11-21 22:33:16.916581: Epoch 2213 +2024-11-21 22:33:16.916702: Current learning rate: 0.00747 +2024-11-21 22:33:35.414689: train_loss -0.7838 +2024-11-21 22:33:35.414986: val_loss -0.7655 +2024-11-21 22:33:35.415081: Pseudo dice [0.8463] +2024-11-21 22:33:35.415161: Epoch time: 18.5 s +2024-11-21 22:33:36.246532: +2024-11-21 22:33:36.246855: Epoch 2214 +2024-11-21 22:33:36.246974: Current learning rate: 0.00747 +2024-11-21 22:33:54.458793: train_loss -0.782 +2024-11-21 22:33:54.459017: val_loss -0.7414 +2024-11-21 22:33:54.459090: Pseudo dice [0.8377] +2024-11-21 22:33:54.459165: Epoch time: 18.21 s +2024-11-21 22:33:55.285499: +2024-11-21 22:33:55.285738: Epoch 2215 +2024-11-21 22:33:55.285848: Current learning rate: 0.00747 +2024-11-21 22:34:13.629632: train_loss -0.7678 +2024-11-21 22:34:13.630184: val_loss -0.7652 +2024-11-21 22:34:13.630261: Pseudo dice [0.8412] +2024-11-21 22:34:13.630335: Epoch time: 18.34 s +2024-11-21 22:34:14.455557: +2024-11-21 22:34:14.455893: Epoch 2216 +2024-11-21 22:34:14.456006: Current learning rate: 0.00747 +2024-11-21 22:34:34.150648: train_loss -0.7664 +2024-11-21 22:34:34.150884: val_loss -0.7735 +2024-11-21 22:34:34.150961: Pseudo dice [0.8447] +2024-11-21 22:34:34.151053: Epoch time: 19.7 s +2024-11-21 22:34:34.980159: +2024-11-21 22:34:34.980374: Epoch 2217 +2024-11-21 22:34:34.980483: Current learning rate: 0.00747 +2024-11-21 22:34:54.330295: train_loss -0.7665 +2024-11-21 22:34:54.335704: val_loss -0.7802 +2024-11-21 22:34:54.335833: Pseudo dice [0.837] +2024-11-21 22:34:54.335916: Epoch time: 19.35 s +2024-11-21 22:34:55.177578: +2024-11-21 22:34:55.177865: Epoch 2218 +2024-11-21 22:34:55.177973: Current learning rate: 0.00747 +2024-11-21 22:35:13.978845: train_loss -0.772 +2024-11-21 22:35:13.979099: val_loss -0.7865 +2024-11-21 22:35:13.979177: Pseudo dice [0.8559] +2024-11-21 22:35:13.979254: Epoch time: 18.8 s +2024-11-21 22:35:14.815551: +2024-11-21 22:35:14.815807: Epoch 2219 +2024-11-21 22:35:14.815914: Current learning rate: 0.00746 +2024-11-21 22:35:33.539545: train_loss -0.7825 +2024-11-21 22:35:33.539811: val_loss -0.7726 +2024-11-21 22:35:33.539888: Pseudo dice [0.8515] +2024-11-21 22:35:33.539966: Epoch time: 18.72 s +2024-11-21 22:35:34.371177: +2024-11-21 22:35:34.371489: Epoch 2220 +2024-11-21 22:35:34.371600: Current learning rate: 0.00746 +2024-11-21 22:35:52.220424: train_loss -0.7777 +2024-11-21 22:35:52.220674: val_loss -0.7837 +2024-11-21 22:35:52.220760: Pseudo dice [0.851] +2024-11-21 22:35:52.220852: Epoch time: 17.85 s +2024-11-21 22:35:53.052724: +2024-11-21 22:35:53.052938: Epoch 2221 +2024-11-21 22:35:53.053050: Current learning rate: 0.00746 +2024-11-21 22:36:11.941820: train_loss -0.7694 +2024-11-21 22:36:11.942040: val_loss -0.7371 +2024-11-21 22:36:11.944316: Pseudo dice [0.8373] +2024-11-21 22:36:11.944418: Epoch time: 18.89 s +2024-11-21 22:36:12.930628: +2024-11-21 22:36:12.930827: Epoch 2222 +2024-11-21 22:36:12.930932: Current learning rate: 0.00746 +2024-11-21 22:36:31.810125: train_loss -0.7737 +2024-11-21 22:36:31.810346: val_loss -0.7753 +2024-11-21 22:36:31.810424: Pseudo dice [0.8423] +2024-11-21 22:36:31.810498: Epoch time: 18.88 s +2024-11-21 22:36:32.644101: +2024-11-21 22:36:32.644327: Epoch 2223 +2024-11-21 22:36:32.644438: Current learning rate: 0.00746 +2024-11-21 22:36:52.494813: train_loss -0.7798 +2024-11-21 22:36:52.495113: val_loss -0.7618 +2024-11-21 22:36:52.495192: Pseudo dice [0.8395] +2024-11-21 22:36:52.495269: Epoch time: 19.85 s +2024-11-21 22:36:53.335891: +2024-11-21 22:36:53.336099: Epoch 2224 +2024-11-21 22:36:53.336207: Current learning rate: 0.00746 +2024-11-21 22:37:12.023840: train_loss -0.7738 +2024-11-21 22:37:12.024094: val_loss -0.7587 +2024-11-21 22:37:12.024170: Pseudo dice [0.8438] +2024-11-21 22:37:12.024248: Epoch time: 18.69 s +2024-11-21 22:37:13.294132: +2024-11-21 22:37:13.294357: Epoch 2225 +2024-11-21 22:37:13.294470: Current learning rate: 0.00746 +2024-11-21 22:37:31.762161: train_loss -0.7668 +2024-11-21 22:37:31.762389: val_loss -0.7537 +2024-11-21 22:37:31.762460: Pseudo dice [0.8163] +2024-11-21 22:37:31.762550: Epoch time: 18.47 s +2024-11-21 22:37:32.608302: +2024-11-21 22:37:32.608525: Epoch 2226 +2024-11-21 22:37:32.608634: Current learning rate: 0.00746 +2024-11-21 22:37:50.635718: train_loss -0.7556 +2024-11-21 22:37:50.635920: val_loss -0.7529 +2024-11-21 22:37:50.637599: Pseudo dice [0.8387] +2024-11-21 22:37:50.637697: Epoch time: 18.03 s +2024-11-21 22:37:51.511243: +2024-11-21 22:37:51.511466: Epoch 2227 +2024-11-21 22:37:51.511574: Current learning rate: 0.00746 +2024-11-21 22:38:09.775692: train_loss -0.7499 +2024-11-21 22:38:09.775939: val_loss -0.7577 +2024-11-21 22:38:09.776025: Pseudo dice [0.8239] +2024-11-21 22:38:09.776108: Epoch time: 18.27 s +2024-11-21 22:38:10.603191: +2024-11-21 22:38:10.603426: Epoch 2228 +2024-11-21 22:38:10.603541: Current learning rate: 0.00745 +2024-11-21 22:38:30.116009: train_loss -0.7553 +2024-11-21 22:38:30.116237: val_loss -0.7906 +2024-11-21 22:38:30.116316: Pseudo dice [0.8522] +2024-11-21 22:38:30.116392: Epoch time: 19.51 s +2024-11-21 22:38:30.947989: +2024-11-21 22:38:30.948213: Epoch 2229 +2024-11-21 22:38:30.948324: Current learning rate: 0.00745 +2024-11-21 22:38:49.346686: train_loss -0.7736 +2024-11-21 22:38:49.346900: val_loss -0.7472 +2024-11-21 22:38:49.346974: Pseudo dice [0.8483] +2024-11-21 22:38:49.347058: Epoch time: 18.4 s +2024-11-21 22:38:50.180067: +2024-11-21 22:38:50.180272: Epoch 2230 +2024-11-21 22:38:50.180382: Current learning rate: 0.00745 +2024-11-21 22:39:07.934972: train_loss -0.7448 +2024-11-21 22:39:07.935223: val_loss -0.7417 +2024-11-21 22:39:07.935309: Pseudo dice [0.833] +2024-11-21 22:39:07.935387: Epoch time: 17.76 s +2024-11-21 22:39:08.764514: +2024-11-21 22:39:08.764720: Epoch 2231 +2024-11-21 22:39:08.764831: Current learning rate: 0.00745 +2024-11-21 22:39:27.694715: train_loss -0.7436 +2024-11-21 22:39:27.694963: val_loss -0.7591 +2024-11-21 22:39:27.695045: Pseudo dice [0.8337] +2024-11-21 22:39:27.695126: Epoch time: 18.93 s +2024-11-21 22:39:28.544788: +2024-11-21 22:39:28.545030: Epoch 2232 +2024-11-21 22:39:28.545151: Current learning rate: 0.00745 +2024-11-21 22:39:47.807552: train_loss -0.7666 +2024-11-21 22:39:47.807786: val_loss -0.738 +2024-11-21 22:39:47.807865: Pseudo dice [0.8035] +2024-11-21 22:39:47.807940: Epoch time: 19.26 s +2024-11-21 22:39:48.688711: +2024-11-21 22:39:48.688927: Epoch 2233 +2024-11-21 22:39:48.689041: Current learning rate: 0.00745 +2024-11-21 22:40:07.104344: train_loss -0.7677 +2024-11-21 22:40:07.104629: val_loss -0.7776 +2024-11-21 22:40:07.104707: Pseudo dice [0.8468] +2024-11-21 22:40:07.104786: Epoch time: 18.42 s +2024-11-21 22:40:07.930920: +2024-11-21 22:40:07.931144: Epoch 2234 +2024-11-21 22:40:07.931257: Current learning rate: 0.00745 +2024-11-21 22:40:25.271951: train_loss -0.7799 +2024-11-21 22:40:25.272237: val_loss -0.7682 +2024-11-21 22:40:25.272328: Pseudo dice [0.8394] +2024-11-21 22:40:25.272413: Epoch time: 17.34 s +2024-11-21 22:40:26.135747: +2024-11-21 22:40:26.135971: Epoch 2235 +2024-11-21 22:40:26.136087: Current learning rate: 0.00745 +2024-11-21 22:40:43.904450: train_loss -0.7726 +2024-11-21 22:40:43.904666: val_loss -0.7554 +2024-11-21 22:40:43.904744: Pseudo dice [0.8363] +2024-11-21 22:40:43.904817: Epoch time: 17.77 s +2024-11-21 22:40:44.738111: +2024-11-21 22:40:44.738330: Epoch 2236 +2024-11-21 22:40:44.738438: Current learning rate: 0.00745 +2024-11-21 22:41:02.447978: train_loss -0.7649 +2024-11-21 22:41:02.448220: val_loss -0.7566 +2024-11-21 22:41:02.448296: Pseudo dice [0.8416] +2024-11-21 22:41:02.448373: Epoch time: 17.71 s +2024-11-21 22:41:03.646961: +2024-11-21 22:41:03.647168: Epoch 2237 +2024-11-21 22:41:03.647275: Current learning rate: 0.00744 +2024-11-21 22:41:22.457899: train_loss -0.7576 +2024-11-21 22:41:22.458236: val_loss -0.735 +2024-11-21 22:41:22.458313: Pseudo dice [0.841] +2024-11-21 22:41:22.458400: Epoch time: 18.81 s +2024-11-21 22:41:23.388135: +2024-11-21 22:41:23.388337: Epoch 2238 +2024-11-21 22:41:23.388447: Current learning rate: 0.00744 +2024-11-21 22:41:40.405787: train_loss -0.777 +2024-11-21 22:41:40.406060: val_loss -0.7707 +2024-11-21 22:41:40.406132: Pseudo dice [0.8417] +2024-11-21 22:41:40.406204: Epoch time: 17.02 s +2024-11-21 22:41:41.230269: +2024-11-21 22:41:41.230510: Epoch 2239 +2024-11-21 22:41:41.230626: Current learning rate: 0.00744 +2024-11-21 22:42:00.028794: train_loss -0.7677 +2024-11-21 22:42:00.029013: val_loss -0.783 +2024-11-21 22:42:00.029116: Pseudo dice [0.8579] +2024-11-21 22:42:00.029195: Epoch time: 18.8 s +2024-11-21 22:42:00.873577: +2024-11-21 22:42:00.873808: Epoch 2240 +2024-11-21 22:42:00.873930: Current learning rate: 0.00744 +2024-11-21 22:42:19.237765: train_loss -0.7669 +2024-11-21 22:42:19.238018: val_loss -0.7636 +2024-11-21 22:42:19.238093: Pseudo dice [0.8313] +2024-11-21 22:42:19.238174: Epoch time: 18.36 s +2024-11-21 22:42:20.068109: +2024-11-21 22:42:20.068322: Epoch 2241 +2024-11-21 22:42:20.068434: Current learning rate: 0.00744 +2024-11-21 22:42:39.431861: train_loss -0.7742 +2024-11-21 22:42:39.432088: val_loss -0.7752 +2024-11-21 22:42:39.432169: Pseudo dice [0.8506] +2024-11-21 22:42:39.434325: Epoch time: 19.36 s +2024-11-21 22:42:40.280098: +2024-11-21 22:42:40.280306: Epoch 2242 +2024-11-21 22:42:40.280416: Current learning rate: 0.00744 +2024-11-21 22:42:59.393196: train_loss -0.7721 +2024-11-21 22:42:59.393414: val_loss -0.7801 +2024-11-21 22:42:59.393527: Pseudo dice [0.8439] +2024-11-21 22:42:59.393611: Epoch time: 19.11 s +2024-11-21 22:43:00.227279: +2024-11-21 22:43:00.227521: Epoch 2243 +2024-11-21 22:43:00.227631: Current learning rate: 0.00744 +2024-11-21 22:43:18.626399: train_loss -0.763 +2024-11-21 22:43:18.626623: val_loss -0.7687 +2024-11-21 22:43:18.626698: Pseudo dice [0.831] +2024-11-21 22:43:18.626772: Epoch time: 18.4 s +2024-11-21 22:43:19.454097: +2024-11-21 22:43:19.454356: Epoch 2244 +2024-11-21 22:43:19.454467: Current learning rate: 0.00744 +2024-11-21 22:43:37.541915: train_loss -0.7759 +2024-11-21 22:43:37.542166: val_loss -0.7661 +2024-11-21 22:43:37.542248: Pseudo dice [0.8402] +2024-11-21 22:43:37.542397: Epoch time: 18.09 s +2024-11-21 22:43:38.369726: +2024-11-21 22:43:38.369935: Epoch 2245 +2024-11-21 22:43:38.370048: Current learning rate: 0.00743 +2024-11-21 22:43:56.842139: train_loss -0.7778 +2024-11-21 22:43:56.842408: val_loss -0.7562 +2024-11-21 22:43:56.842482: Pseudo dice [0.8408] +2024-11-21 22:43:56.842557: Epoch time: 18.47 s +2024-11-21 22:43:57.727762: +2024-11-21 22:43:57.728071: Epoch 2246 +2024-11-21 22:43:57.728183: Current learning rate: 0.00743 +2024-11-21 22:44:15.406589: train_loss -0.7761 +2024-11-21 22:44:15.419820: val_loss -0.7384 +2024-11-21 22:44:15.419919: Pseudo dice [0.8348] +2024-11-21 22:44:15.420005: Epoch time: 17.68 s +2024-11-21 22:44:16.250191: +2024-11-21 22:44:16.250442: Epoch 2247 +2024-11-21 22:44:16.250555: Current learning rate: 0.00743 +2024-11-21 22:44:36.007678: train_loss -0.7689 +2024-11-21 22:44:36.007878: val_loss -0.7694 +2024-11-21 22:44:36.011832: Pseudo dice [0.8507] +2024-11-21 22:44:36.011966: Epoch time: 19.76 s +2024-11-21 22:44:36.862324: +2024-11-21 22:44:36.862536: Epoch 2248 +2024-11-21 22:44:36.862655: Current learning rate: 0.00743 +2024-11-21 22:44:54.560401: train_loss -0.7759 +2024-11-21 22:44:54.560641: val_loss -0.743 +2024-11-21 22:44:54.560715: Pseudo dice [0.8335] +2024-11-21 22:44:54.560794: Epoch time: 17.7 s +2024-11-21 22:44:55.899868: +2024-11-21 22:44:55.900091: Epoch 2249 +2024-11-21 22:44:55.900202: Current learning rate: 0.00743 +2024-11-21 22:45:14.774640: train_loss -0.7762 +2024-11-21 22:45:14.774881: val_loss -0.7532 +2024-11-21 22:45:14.774956: Pseudo dice [0.8293] +2024-11-21 22:45:14.775035: Epoch time: 18.88 s +2024-11-21 22:45:15.843023: +2024-11-21 22:45:15.843246: Epoch 2250 +2024-11-21 22:45:15.843354: Current learning rate: 0.00743 +2024-11-21 22:45:34.420053: train_loss -0.7608 +2024-11-21 22:45:34.420275: val_loss -0.7585 +2024-11-21 22:45:34.420354: Pseudo dice [0.8393] +2024-11-21 22:45:34.420432: Epoch time: 18.58 s +2024-11-21 22:45:35.259708: +2024-11-21 22:45:35.259941: Epoch 2251 +2024-11-21 22:45:35.260058: Current learning rate: 0.00743 +2024-11-21 22:45:53.715639: train_loss -0.7803 +2024-11-21 22:45:53.715895: val_loss -0.7724 +2024-11-21 22:45:53.715970: Pseudo dice [0.8451] +2024-11-21 22:45:53.716061: Epoch time: 18.46 s +2024-11-21 22:45:54.548821: +2024-11-21 22:45:54.549039: Epoch 2252 +2024-11-21 22:45:54.549147: Current learning rate: 0.00743 +2024-11-21 22:46:13.736355: train_loss -0.7744 +2024-11-21 22:46:13.736567: val_loss -0.7512 +2024-11-21 22:46:13.736642: Pseudo dice [0.8286] +2024-11-21 22:46:13.736715: Epoch time: 19.19 s +2024-11-21 22:46:14.623449: +2024-11-21 22:46:14.623671: Epoch 2253 +2024-11-21 22:46:14.623780: Current learning rate: 0.00743 +2024-11-21 22:46:33.305578: train_loss -0.7829 +2024-11-21 22:46:33.305833: val_loss -0.7859 +2024-11-21 22:46:33.305912: Pseudo dice [0.844] +2024-11-21 22:46:33.306000: Epoch time: 18.68 s +2024-11-21 22:46:34.137470: +2024-11-21 22:46:34.137709: Epoch 2254 +2024-11-21 22:46:34.137817: Current learning rate: 0.00742 +2024-11-21 22:46:54.237607: train_loss -0.7611 +2024-11-21 22:46:54.237855: val_loss -0.7634 +2024-11-21 22:46:54.237930: Pseudo dice [0.8264] +2024-11-21 22:46:54.238024: Epoch time: 20.1 s +2024-11-21 22:46:55.070760: +2024-11-21 22:46:55.071028: Epoch 2255 +2024-11-21 22:46:55.071151: Current learning rate: 0.00742 +2024-11-21 22:47:13.107837: train_loss -0.7497 +2024-11-21 22:47:13.108094: val_loss -0.7567 +2024-11-21 22:47:13.108171: Pseudo dice [0.8336] +2024-11-21 22:47:13.108256: Epoch time: 18.04 s +2024-11-21 22:47:13.977487: +2024-11-21 22:47:13.977706: Epoch 2256 +2024-11-21 22:47:13.977836: Current learning rate: 0.00742 +2024-11-21 22:47:32.604329: train_loss -0.7591 +2024-11-21 22:47:32.604551: val_loss -0.7653 +2024-11-21 22:47:32.604630: Pseudo dice [0.8449] +2024-11-21 22:47:32.604716: Epoch time: 18.63 s +2024-11-21 22:47:33.510072: +2024-11-21 22:47:33.510292: Epoch 2257 +2024-11-21 22:47:33.510402: Current learning rate: 0.00742 +2024-11-21 22:47:51.160712: train_loss -0.7745 +2024-11-21 22:47:51.160936: val_loss -0.792 +2024-11-21 22:47:51.161057: Pseudo dice [0.8542] +2024-11-21 22:47:51.161138: Epoch time: 17.65 s +2024-11-21 22:47:51.990791: +2024-11-21 22:47:51.991023: Epoch 2258 +2024-11-21 22:47:51.991138: Current learning rate: 0.00742 +2024-11-21 22:48:10.423551: train_loss -0.7806 +2024-11-21 22:48:10.423778: val_loss -0.7558 +2024-11-21 22:48:10.423854: Pseudo dice [0.8312] +2024-11-21 22:48:10.423935: Epoch time: 18.43 s +2024-11-21 22:48:11.260053: +2024-11-21 22:48:11.260256: Epoch 2259 +2024-11-21 22:48:11.260365: Current learning rate: 0.00742 +2024-11-21 22:48:30.275461: train_loss -0.7702 +2024-11-21 22:48:30.275694: val_loss -0.7572 +2024-11-21 22:48:30.275766: Pseudo dice [0.8472] +2024-11-21 22:48:30.275843: Epoch time: 19.02 s +2024-11-21 22:48:31.228840: +2024-11-21 22:48:31.229083: Epoch 2260 +2024-11-21 22:48:31.229196: Current learning rate: 0.00742 +2024-11-21 22:48:50.248475: train_loss -0.7754 +2024-11-21 22:48:50.248722: val_loss -0.7688 +2024-11-21 22:48:50.248855: Pseudo dice [0.8505] +2024-11-21 22:48:50.248934: Epoch time: 19.02 s +2024-11-21 22:48:51.509697: +2024-11-21 22:48:51.509905: Epoch 2261 +2024-11-21 22:48:51.510022: Current learning rate: 0.00742 +2024-11-21 22:49:09.905187: train_loss -0.7714 +2024-11-21 22:49:09.907611: val_loss -0.752 +2024-11-21 22:49:09.907748: Pseudo dice [0.8234] +2024-11-21 22:49:09.907836: Epoch time: 18.4 s +2024-11-21 22:49:10.745974: +2024-11-21 22:49:10.746243: Epoch 2262 +2024-11-21 22:49:10.746400: Current learning rate: 0.00741 +2024-11-21 22:49:28.739661: train_loss -0.7788 +2024-11-21 22:49:28.739898: val_loss -0.7637 +2024-11-21 22:49:28.739988: Pseudo dice [0.8434] +2024-11-21 22:49:28.740077: Epoch time: 17.99 s +2024-11-21 22:49:29.572616: +2024-11-21 22:49:29.572843: Epoch 2263 +2024-11-21 22:49:29.572959: Current learning rate: 0.00741 +2024-11-21 22:49:48.298123: train_loss -0.7821 +2024-11-21 22:49:48.298336: val_loss -0.7705 +2024-11-21 22:49:48.298410: Pseudo dice [0.8471] +2024-11-21 22:49:48.298486: Epoch time: 18.73 s +2024-11-21 22:49:49.126838: +2024-11-21 22:49:49.127082: Epoch 2264 +2024-11-21 22:49:49.127192: Current learning rate: 0.00741 +2024-11-21 22:50:07.863934: train_loss -0.7798 +2024-11-21 22:50:07.864208: val_loss -0.7418 +2024-11-21 22:50:07.864285: Pseudo dice [0.8366] +2024-11-21 22:50:07.864362: Epoch time: 18.74 s +2024-11-21 22:50:08.698279: +2024-11-21 22:50:08.698508: Epoch 2265 +2024-11-21 22:50:08.698618: Current learning rate: 0.00741 +2024-11-21 22:50:26.944885: train_loss -0.7682 +2024-11-21 22:50:26.945133: val_loss -0.7648 +2024-11-21 22:50:26.945210: Pseudo dice [0.8521] +2024-11-21 22:50:26.945296: Epoch time: 18.25 s +2024-11-21 22:50:27.880105: +2024-11-21 22:50:27.880327: Epoch 2266 +2024-11-21 22:50:27.880438: Current learning rate: 0.00741 +2024-11-21 22:50:46.311901: train_loss -0.7666 +2024-11-21 22:50:46.312155: val_loss -0.774 +2024-11-21 22:50:46.312234: Pseudo dice [0.851] +2024-11-21 22:50:46.312323: Epoch time: 18.43 s +2024-11-21 22:50:47.145424: +2024-11-21 22:50:47.145625: Epoch 2267 +2024-11-21 22:50:47.145756: Current learning rate: 0.00741 +2024-11-21 22:51:05.175428: train_loss -0.7745 +2024-11-21 22:51:05.175659: val_loss -0.7448 +2024-11-21 22:51:05.175741: Pseudo dice [0.8329] +2024-11-21 22:51:05.175858: Epoch time: 18.03 s +2024-11-21 22:51:06.011501: +2024-11-21 22:51:06.011720: Epoch 2268 +2024-11-21 22:51:06.011848: Current learning rate: 0.00741 +2024-11-21 22:51:24.546204: train_loss -0.7577 +2024-11-21 22:51:24.546436: val_loss -0.7463 +2024-11-21 22:51:24.546515: Pseudo dice [0.8282] +2024-11-21 22:51:24.546594: Epoch time: 18.54 s +2024-11-21 22:51:25.378636: +2024-11-21 22:51:25.378884: Epoch 2269 +2024-11-21 22:51:25.379008: Current learning rate: 0.00741 +2024-11-21 22:51:42.604964: train_loss -0.7733 +2024-11-21 22:51:42.605216: val_loss -0.7577 +2024-11-21 22:51:42.605297: Pseudo dice [0.8501] +2024-11-21 22:51:42.607611: Epoch time: 17.23 s +2024-11-21 22:51:43.569849: +2024-11-21 22:51:43.570071: Epoch 2270 +2024-11-21 22:51:43.570180: Current learning rate: 0.00741 +2024-11-21 22:52:01.674651: train_loss -0.7746 +2024-11-21 22:52:01.674871: val_loss -0.7589 +2024-11-21 22:52:01.674951: Pseudo dice [0.8229] +2024-11-21 22:52:01.675034: Epoch time: 18.11 s +2024-11-21 22:52:02.506052: +2024-11-21 22:52:02.506268: Epoch 2271 +2024-11-21 22:52:02.506373: Current learning rate: 0.0074 +2024-11-21 22:52:19.500549: train_loss -0.7724 +2024-11-21 22:52:19.500776: val_loss -0.757 +2024-11-21 22:52:19.500850: Pseudo dice [0.8521] +2024-11-21 22:52:19.500945: Epoch time: 17.0 s +2024-11-21 22:52:20.417923: +2024-11-21 22:52:20.418151: Epoch 2272 +2024-11-21 22:52:20.418267: Current learning rate: 0.0074 +2024-11-21 22:52:38.893330: train_loss -0.7689 +2024-11-21 22:52:38.893573: val_loss -0.7659 +2024-11-21 22:52:38.893647: Pseudo dice [0.8392] +2024-11-21 22:52:38.893729: Epoch time: 18.48 s +2024-11-21 22:52:40.110953: +2024-11-21 22:52:40.111846: Epoch 2273 +2024-11-21 22:52:40.111964: Current learning rate: 0.0074 +2024-11-21 22:52:58.750786: train_loss -0.7755 +2024-11-21 22:52:58.751015: val_loss -0.7474 +2024-11-21 22:52:58.751093: Pseudo dice [0.8364] +2024-11-21 22:52:58.751169: Epoch time: 18.64 s +2024-11-21 22:52:59.580879: +2024-11-21 22:52:59.581125: Epoch 2274 +2024-11-21 22:52:59.581235: Current learning rate: 0.0074 +2024-11-21 22:53:17.155645: train_loss -0.767 +2024-11-21 22:53:17.155885: val_loss -0.7618 +2024-11-21 22:53:17.155959: Pseudo dice [0.8465] +2024-11-21 22:53:17.156039: Epoch time: 17.58 s +2024-11-21 22:53:18.125049: +2024-11-21 22:53:18.125253: Epoch 2275 +2024-11-21 22:53:18.125363: Current learning rate: 0.0074 +2024-11-21 22:53:36.854730: train_loss -0.7724 +2024-11-21 22:53:36.854977: val_loss -0.745 +2024-11-21 22:53:36.855061: Pseudo dice [0.8237] +2024-11-21 22:53:36.855145: Epoch time: 18.73 s +2024-11-21 22:53:37.683293: +2024-11-21 22:53:37.683490: Epoch 2276 +2024-11-21 22:53:37.683597: Current learning rate: 0.0074 +2024-11-21 22:53:55.888640: train_loss -0.7642 +2024-11-21 22:53:55.888851: val_loss -0.7476 +2024-11-21 22:53:55.888925: Pseudo dice [0.8369] +2024-11-21 22:53:55.889008: Epoch time: 18.21 s +2024-11-21 22:53:56.716116: +2024-11-21 22:53:56.716330: Epoch 2277 +2024-11-21 22:53:56.716442: Current learning rate: 0.0074 +2024-11-21 22:54:15.294129: train_loss -0.7645 +2024-11-21 22:54:15.294345: val_loss -0.7521 +2024-11-21 22:54:15.294427: Pseudo dice [0.853] +2024-11-21 22:54:15.294503: Epoch time: 18.58 s +2024-11-21 22:54:16.130169: +2024-11-21 22:54:16.130357: Epoch 2278 +2024-11-21 22:54:16.130462: Current learning rate: 0.0074 +2024-11-21 22:54:34.519892: train_loss -0.7708 +2024-11-21 22:54:34.520146: val_loss -0.7794 +2024-11-21 22:54:34.520228: Pseudo dice [0.858] +2024-11-21 22:54:34.520304: Epoch time: 18.39 s +2024-11-21 22:54:35.351483: +2024-11-21 22:54:35.351808: Epoch 2279 +2024-11-21 22:54:35.351923: Current learning rate: 0.0074 +2024-11-21 22:54:53.920240: train_loss -0.7734 +2024-11-21 22:54:53.920490: val_loss -0.7353 +2024-11-21 22:54:53.920576: Pseudo dice [0.8267] +2024-11-21 22:54:53.920660: Epoch time: 18.57 s +2024-11-21 22:54:54.753914: +2024-11-21 22:54:54.754130: Epoch 2280 +2024-11-21 22:54:54.754240: Current learning rate: 0.00739 +2024-11-21 22:55:12.386303: train_loss -0.7769 +2024-11-21 22:55:12.386546: val_loss -0.7716 +2024-11-21 22:55:12.386619: Pseudo dice [0.8648] +2024-11-21 22:55:12.386697: Epoch time: 17.63 s +2024-11-21 22:55:13.218670: +2024-11-21 22:55:13.218910: Epoch 2281 +2024-11-21 22:55:13.219031: Current learning rate: 0.00739 +2024-11-21 22:55:31.633147: train_loss -0.7768 +2024-11-21 22:55:31.633357: val_loss -0.7789 +2024-11-21 22:55:31.633435: Pseudo dice [0.8533] +2024-11-21 22:55:31.633512: Epoch time: 18.42 s +2024-11-21 22:55:32.462182: +2024-11-21 22:55:32.462395: Epoch 2282 +2024-11-21 22:55:32.462505: Current learning rate: 0.00739 +2024-11-21 22:55:50.901416: train_loss -0.7707 +2024-11-21 22:55:50.901632: val_loss -0.7594 +2024-11-21 22:55:50.901710: Pseudo dice [0.8518] +2024-11-21 22:55:50.901785: Epoch time: 18.44 s +2024-11-21 22:55:51.726803: +2024-11-21 22:55:51.727019: Epoch 2283 +2024-11-21 22:55:51.727131: Current learning rate: 0.00739 +2024-11-21 22:56:10.542274: train_loss -0.7739 +2024-11-21 22:56:10.542527: val_loss -0.7888 +2024-11-21 22:56:10.542604: Pseudo dice [0.8608] +2024-11-21 22:56:10.542686: Epoch time: 18.82 s +2024-11-21 22:56:10.542752: Yayy! New best EMA pseudo Dice: 0.8463 +2024-11-21 22:56:11.644173: +2024-11-21 22:56:11.644403: Epoch 2284 +2024-11-21 22:56:11.644515: Current learning rate: 0.00739 +2024-11-21 22:56:30.560605: train_loss -0.7827 +2024-11-21 22:56:30.560820: val_loss -0.7543 +2024-11-21 22:56:30.560896: Pseudo dice [0.8315] +2024-11-21 22:56:30.560978: Epoch time: 18.92 s +2024-11-21 22:56:31.793648: +2024-11-21 22:56:31.793882: Epoch 2285 +2024-11-21 22:56:31.794001: Current learning rate: 0.00739 +2024-11-21 22:56:49.686374: train_loss -0.7818 +2024-11-21 22:56:49.690751: val_loss -0.7751 +2024-11-21 22:56:49.690895: Pseudo dice [0.8468] +2024-11-21 22:56:49.690983: Epoch time: 17.89 s +2024-11-21 22:56:50.526199: +2024-11-21 22:56:50.526428: Epoch 2286 +2024-11-21 22:56:50.526536: Current learning rate: 0.00739 +2024-11-21 22:57:09.372076: train_loss -0.7777 +2024-11-21 22:57:09.372323: val_loss -0.7544 +2024-11-21 22:57:09.372401: Pseudo dice [0.8448] +2024-11-21 22:57:09.372483: Epoch time: 18.85 s +2024-11-21 22:57:10.209557: +2024-11-21 22:57:10.209781: Epoch 2287 +2024-11-21 22:57:10.209890: Current learning rate: 0.00739 +2024-11-21 22:57:28.886528: train_loss -0.7728 +2024-11-21 22:57:28.886743: val_loss -0.7611 +2024-11-21 22:57:28.886821: Pseudo dice [0.8416] +2024-11-21 22:57:28.886900: Epoch time: 18.68 s +2024-11-21 22:57:29.714114: +2024-11-21 22:57:29.714329: Epoch 2288 +2024-11-21 22:57:29.714437: Current learning rate: 0.00738 +2024-11-21 22:57:48.472419: train_loss -0.779 +2024-11-21 22:57:48.472627: val_loss -0.7405 +2024-11-21 22:57:48.472706: Pseudo dice [0.838] +2024-11-21 22:57:48.472783: Epoch time: 18.76 s +2024-11-21 22:57:49.298751: +2024-11-21 22:57:49.298981: Epoch 2289 +2024-11-21 22:57:49.299095: Current learning rate: 0.00738 +2024-11-21 22:58:07.335556: train_loss -0.7625 +2024-11-21 22:58:07.335802: val_loss -0.7676 +2024-11-21 22:58:07.335881: Pseudo dice [0.8263] +2024-11-21 22:58:07.335966: Epoch time: 18.04 s +2024-11-21 22:58:08.217439: +2024-11-21 22:58:08.217684: Epoch 2290 +2024-11-21 22:58:08.217808: Current learning rate: 0.00738 +2024-11-21 22:58:26.832396: train_loss -0.7707 +2024-11-21 22:58:26.832614: val_loss -0.7544 +2024-11-21 22:58:26.832688: Pseudo dice [0.8459] +2024-11-21 22:58:26.832764: Epoch time: 18.62 s +2024-11-21 22:58:27.664655: +2024-11-21 22:58:27.664857: Epoch 2291 +2024-11-21 22:58:27.664968: Current learning rate: 0.00738 +2024-11-21 22:58:45.308240: train_loss -0.7774 +2024-11-21 22:58:45.308448: val_loss -0.7516 +2024-11-21 22:58:45.313636: Pseudo dice [0.8475] +2024-11-21 22:58:45.313809: Epoch time: 17.64 s +2024-11-21 22:58:46.159393: +2024-11-21 22:58:46.159669: Epoch 2292 +2024-11-21 22:58:46.159778: Current learning rate: 0.00738 +2024-11-21 22:59:05.197889: train_loss -0.7782 +2024-11-21 22:59:05.198122: val_loss -0.7421 +2024-11-21 22:59:05.198195: Pseudo dice [0.8287] +2024-11-21 22:59:05.198271: Epoch time: 19.04 s +2024-11-21 22:59:06.045937: +2024-11-21 22:59:06.046168: Epoch 2293 +2024-11-21 22:59:06.046280: Current learning rate: 0.00738 +2024-11-21 22:59:25.113626: train_loss -0.7753 +2024-11-21 22:59:25.113882: val_loss -0.7389 +2024-11-21 22:59:25.113959: Pseudo dice [0.8157] +2024-11-21 22:59:25.116269: Epoch time: 19.07 s +2024-11-21 22:59:26.008224: +2024-11-21 22:59:26.008440: Epoch 2294 +2024-11-21 22:59:26.008553: Current learning rate: 0.00738 +2024-11-21 22:59:44.908072: train_loss -0.7686 +2024-11-21 22:59:44.908290: val_loss -0.7648 +2024-11-21 22:59:44.908364: Pseudo dice [0.839] +2024-11-21 22:59:44.908439: Epoch time: 18.9 s +2024-11-21 22:59:45.846852: +2024-11-21 22:59:45.847088: Epoch 2295 +2024-11-21 22:59:45.847204: Current learning rate: 0.00738 +2024-11-21 23:00:04.712334: train_loss -0.7706 +2024-11-21 23:00:04.712549: val_loss -0.769 +2024-11-21 23:00:04.712624: Pseudo dice [0.8513] +2024-11-21 23:00:04.712696: Epoch time: 18.87 s +2024-11-21 23:00:05.540313: +2024-11-21 23:00:05.540522: Epoch 2296 +2024-11-21 23:00:05.540630: Current learning rate: 0.00738 +2024-11-21 23:00:22.919612: train_loss -0.7813 +2024-11-21 23:00:22.919909: val_loss -0.7446 +2024-11-21 23:00:22.919988: Pseudo dice [0.8363] +2024-11-21 23:00:22.920076: Epoch time: 17.38 s +2024-11-21 23:00:24.153416: +2024-11-21 23:00:24.153752: Epoch 2297 +2024-11-21 23:00:24.153867: Current learning rate: 0.00737 +2024-11-21 23:00:43.465693: train_loss -0.78 +2024-11-21 23:00:43.465946: val_loss -0.7425 +2024-11-21 23:00:43.466038: Pseudo dice [0.8362] +2024-11-21 23:00:43.466117: Epoch time: 19.31 s +2024-11-21 23:00:44.289457: +2024-11-21 23:00:44.289734: Epoch 2298 +2024-11-21 23:00:44.289847: Current learning rate: 0.00737 +2024-11-21 23:01:02.038178: train_loss -0.7802 +2024-11-21 23:01:02.038406: val_loss -0.7665 +2024-11-21 23:01:02.038486: Pseudo dice [0.8332] +2024-11-21 23:01:02.038562: Epoch time: 17.75 s +2024-11-21 23:01:02.868090: +2024-11-21 23:01:02.868305: Epoch 2299 +2024-11-21 23:01:02.868414: Current learning rate: 0.00737 +2024-11-21 23:01:21.512121: train_loss -0.775 +2024-11-21 23:01:21.512340: val_loss -0.7511 +2024-11-21 23:01:21.512426: Pseudo dice [0.8413] +2024-11-21 23:01:21.512506: Epoch time: 18.64 s +2024-11-21 23:01:22.562870: +2024-11-21 23:01:22.563088: Epoch 2300 +2024-11-21 23:01:22.563200: Current learning rate: 0.00737 +2024-11-21 23:01:42.438740: train_loss -0.7719 +2024-11-21 23:01:42.438998: val_loss -0.7484 +2024-11-21 23:01:42.439079: Pseudo dice [0.841] +2024-11-21 23:01:42.439163: Epoch time: 19.88 s +2024-11-21 23:01:43.311708: +2024-11-21 23:01:43.311936: Epoch 2301 +2024-11-21 23:01:43.312053: Current learning rate: 0.00737 +2024-11-21 23:02:02.694186: train_loss -0.7683 +2024-11-21 23:02:02.694398: val_loss -0.7608 +2024-11-21 23:02:02.694473: Pseudo dice [0.8309] +2024-11-21 23:02:02.694546: Epoch time: 19.38 s +2024-11-21 23:02:03.695880: +2024-11-21 23:02:03.696126: Epoch 2302 +2024-11-21 23:02:03.696236: Current learning rate: 0.00737 +2024-11-21 23:02:21.385598: train_loss -0.7613 +2024-11-21 23:02:21.385828: val_loss -0.7624 +2024-11-21 23:02:21.385907: Pseudo dice [0.8382] +2024-11-21 23:02:21.385982: Epoch time: 17.69 s +2024-11-21 23:02:22.212533: +2024-11-21 23:02:22.212744: Epoch 2303 +2024-11-21 23:02:22.212861: Current learning rate: 0.00737 +2024-11-21 23:02:41.169378: train_loss -0.7811 +2024-11-21 23:02:41.169663: val_loss -0.7811 +2024-11-21 23:02:41.169742: Pseudo dice [0.8534] +2024-11-21 23:02:41.169822: Epoch time: 18.96 s +2024-11-21 23:02:42.011225: +2024-11-21 23:02:42.011470: Epoch 2304 +2024-11-21 23:02:42.011580: Current learning rate: 0.00737 +2024-11-21 23:03:02.329056: train_loss -0.7827 +2024-11-21 23:03:02.329325: val_loss -0.7808 +2024-11-21 23:03:02.329407: Pseudo dice [0.838] +2024-11-21 23:03:02.329488: Epoch time: 20.32 s +2024-11-21 23:03:03.174041: +2024-11-21 23:03:03.174277: Epoch 2305 +2024-11-21 23:03:03.174400: Current learning rate: 0.00736 +2024-11-21 23:03:21.969406: train_loss -0.7723 +2024-11-21 23:03:21.969625: val_loss -0.747 +2024-11-21 23:03:21.969700: Pseudo dice [0.8329] +2024-11-21 23:03:21.969776: Epoch time: 18.8 s +2024-11-21 23:03:22.840388: +2024-11-21 23:03:22.840674: Epoch 2306 +2024-11-21 23:03:22.840786: Current learning rate: 0.00736 +2024-11-21 23:03:41.446045: train_loss -0.7708 +2024-11-21 23:03:41.446331: val_loss -0.7774 +2024-11-21 23:03:41.446406: Pseudo dice [0.8445] +2024-11-21 23:03:41.446481: Epoch time: 18.61 s +2024-11-21 23:03:42.277923: +2024-11-21 23:03:42.278161: Epoch 2307 +2024-11-21 23:03:42.278270: Current learning rate: 0.00736 +2024-11-21 23:04:00.334184: train_loss -0.765 +2024-11-21 23:04:00.334423: val_loss -0.7605 +2024-11-21 23:04:00.334497: Pseudo dice [0.8437] +2024-11-21 23:04:00.334583: Epoch time: 18.06 s +2024-11-21 23:04:01.201716: +2024-11-21 23:04:01.202049: Epoch 2308 +2024-11-21 23:04:01.202159: Current learning rate: 0.00736 +2024-11-21 23:04:19.195824: train_loss -0.7664 +2024-11-21 23:04:19.196068: val_loss -0.7573 +2024-11-21 23:04:19.196147: Pseudo dice [0.828] +2024-11-21 23:04:19.196224: Epoch time: 17.99 s +2024-11-21 23:04:20.396644: +2024-11-21 23:04:20.396864: Epoch 2309 +2024-11-21 23:04:20.396975: Current learning rate: 0.00736 +2024-11-21 23:04:38.611570: train_loss -0.772 +2024-11-21 23:04:38.611783: val_loss -0.7517 +2024-11-21 23:04:38.611856: Pseudo dice [0.8432] +2024-11-21 23:04:38.611928: Epoch time: 18.22 s +2024-11-21 23:04:39.429236: +2024-11-21 23:04:39.429481: Epoch 2310 +2024-11-21 23:04:39.429593: Current learning rate: 0.00736 +2024-11-21 23:04:57.577963: train_loss -0.7753 +2024-11-21 23:04:57.578203: val_loss -0.7806 +2024-11-21 23:04:57.578278: Pseudo dice [0.8395] +2024-11-21 23:04:57.578357: Epoch time: 18.15 s +2024-11-21 23:04:58.434100: +2024-11-21 23:04:58.434438: Epoch 2311 +2024-11-21 23:04:58.434554: Current learning rate: 0.00736 +2024-11-21 23:05:17.227879: train_loss -0.7824 +2024-11-21 23:05:17.228105: val_loss -0.7972 +2024-11-21 23:05:17.228181: Pseudo dice [0.8575] +2024-11-21 23:05:17.228253: Epoch time: 18.79 s +2024-11-21 23:05:18.055778: +2024-11-21 23:05:18.055997: Epoch 2312 +2024-11-21 23:05:18.056108: Current learning rate: 0.00736 +2024-11-21 23:05:35.959608: train_loss -0.7797 +2024-11-21 23:05:35.959820: val_loss -0.7638 +2024-11-21 23:05:35.959895: Pseudo dice [0.8497] +2024-11-21 23:05:35.959968: Epoch time: 17.9 s +2024-11-21 23:05:36.789452: +2024-11-21 23:05:36.789668: Epoch 2313 +2024-11-21 23:05:36.789780: Current learning rate: 0.00736 +2024-11-21 23:05:54.916943: train_loss -0.7699 +2024-11-21 23:05:54.917155: val_loss -0.7897 +2024-11-21 23:05:54.917230: Pseudo dice [0.8552] +2024-11-21 23:05:54.917305: Epoch time: 18.13 s +2024-11-21 23:05:55.754094: +2024-11-21 23:05:55.754356: Epoch 2314 +2024-11-21 23:05:55.754488: Current learning rate: 0.00735 +2024-11-21 23:06:13.439537: train_loss -0.7819 +2024-11-21 23:06:13.444986: val_loss -0.7551 +2024-11-21 23:06:13.445125: Pseudo dice [0.842] +2024-11-21 23:06:13.445215: Epoch time: 17.69 s +2024-11-21 23:06:14.344938: +2024-11-21 23:06:14.345169: Epoch 2315 +2024-11-21 23:06:14.345276: Current learning rate: 0.00735 +2024-11-21 23:06:32.235960: train_loss -0.7738 +2024-11-21 23:06:32.236179: val_loss -0.775 +2024-11-21 23:06:32.236254: Pseudo dice [0.8438] +2024-11-21 23:06:32.236328: Epoch time: 17.89 s +2024-11-21 23:06:33.068877: +2024-11-21 23:06:33.069098: Epoch 2316 +2024-11-21 23:06:33.069211: Current learning rate: 0.00735 +2024-11-21 23:06:51.835514: train_loss -0.7811 +2024-11-21 23:06:51.835754: val_loss -0.7522 +2024-11-21 23:06:51.835829: Pseudo dice [0.8524] +2024-11-21 23:06:51.835903: Epoch time: 18.77 s +2024-11-21 23:06:52.666647: +2024-11-21 23:06:52.666872: Epoch 2317 +2024-11-21 23:06:52.666989: Current learning rate: 0.00735 +2024-11-21 23:07:11.383184: train_loss -0.7771 +2024-11-21 23:07:11.383719: val_loss -0.7312 +2024-11-21 23:07:11.383806: Pseudo dice [0.8357] +2024-11-21 23:07:11.383889: Epoch time: 18.72 s +2024-11-21 23:07:12.219899: +2024-11-21 23:07:12.220123: Epoch 2318 +2024-11-21 23:07:12.220233: Current learning rate: 0.00735 +2024-11-21 23:07:31.229258: train_loss -0.785 +2024-11-21 23:07:31.229526: val_loss -0.7843 +2024-11-21 23:07:31.229602: Pseudo dice [0.851] +2024-11-21 23:07:31.229676: Epoch time: 19.01 s +2024-11-21 23:07:32.071122: +2024-11-21 23:07:32.071355: Epoch 2319 +2024-11-21 23:07:32.071465: Current learning rate: 0.00735 +2024-11-21 23:07:49.825936: train_loss -0.7728 +2024-11-21 23:07:49.826164: val_loss -0.7464 +2024-11-21 23:07:49.826238: Pseudo dice [0.8502] +2024-11-21 23:07:49.826313: Epoch time: 17.76 s +2024-11-21 23:07:50.666672: +2024-11-21 23:07:50.666889: Epoch 2320 +2024-11-21 23:07:50.667000: Current learning rate: 0.00735 +2024-11-21 23:08:09.072970: train_loss -0.7791 +2024-11-21 23:08:09.073223: val_loss -0.7487 +2024-11-21 23:08:09.073307: Pseudo dice [0.8467] +2024-11-21 23:08:09.073385: Epoch time: 18.41 s +2024-11-21 23:08:10.270202: +2024-11-21 23:08:10.270464: Epoch 2321 +2024-11-21 23:08:10.270611: Current learning rate: 0.00735 +2024-11-21 23:08:27.661785: train_loss -0.7836 +2024-11-21 23:08:27.662058: val_loss -0.7597 +2024-11-21 23:08:27.662133: Pseudo dice [0.8435] +2024-11-21 23:08:27.662210: Epoch time: 17.39 s +2024-11-21 23:08:28.490668: +2024-11-21 23:08:28.490897: Epoch 2322 +2024-11-21 23:08:28.491016: Current learning rate: 0.00735 +2024-11-21 23:08:46.893497: train_loss -0.7747 +2024-11-21 23:08:46.893712: val_loss -0.7697 +2024-11-21 23:08:46.893791: Pseudo dice [0.8474] +2024-11-21 23:08:46.893865: Epoch time: 18.4 s +2024-11-21 23:08:47.727283: +2024-11-21 23:08:47.727525: Epoch 2323 +2024-11-21 23:08:47.727635: Current learning rate: 0.00734 +2024-11-21 23:09:05.877008: train_loss -0.7723 +2024-11-21 23:09:05.877218: val_loss -0.7564 +2024-11-21 23:09:05.877294: Pseudo dice [0.8419] +2024-11-21 23:09:05.877371: Epoch time: 18.15 s +2024-11-21 23:09:06.707169: +2024-11-21 23:09:06.707373: Epoch 2324 +2024-11-21 23:09:06.707482: Current learning rate: 0.00734 +2024-11-21 23:09:24.287053: train_loss -0.7791 +2024-11-21 23:09:24.287356: val_loss -0.7747 +2024-11-21 23:09:24.287435: Pseudo dice [0.8368] +2024-11-21 23:09:24.287519: Epoch time: 17.58 s +2024-11-21 23:09:25.127506: +2024-11-21 23:09:25.127804: Epoch 2325 +2024-11-21 23:09:25.127920: Current learning rate: 0.00734 +2024-11-21 23:09:43.292323: train_loss -0.7671 +2024-11-21 23:09:43.292552: val_loss -0.7465 +2024-11-21 23:09:43.292633: Pseudo dice [0.8401] +2024-11-21 23:09:43.292709: Epoch time: 18.17 s +2024-11-21 23:09:44.123121: +2024-11-21 23:09:44.123416: Epoch 2326 +2024-11-21 23:09:44.123530: Current learning rate: 0.00734 +2024-11-21 23:10:03.462376: train_loss -0.7528 +2024-11-21 23:10:03.464833: val_loss -0.7222 +2024-11-21 23:10:03.464964: Pseudo dice [0.8198] +2024-11-21 23:10:03.465053: Epoch time: 19.34 s +2024-11-21 23:10:04.306772: +2024-11-21 23:10:04.306975: Epoch 2327 +2024-11-21 23:10:04.307087: Current learning rate: 0.00734 +2024-11-21 23:10:23.165842: train_loss -0.7684 +2024-11-21 23:10:23.166060: val_loss -0.7628 +2024-11-21 23:10:23.166137: Pseudo dice [0.8404] +2024-11-21 23:10:23.166215: Epoch time: 18.86 s +2024-11-21 23:10:23.993884: +2024-11-21 23:10:23.994111: Epoch 2328 +2024-11-21 23:10:23.994226: Current learning rate: 0.00734 +2024-11-21 23:10:43.653768: train_loss -0.7683 +2024-11-21 23:10:43.654017: val_loss -0.756 +2024-11-21 23:10:43.654093: Pseudo dice [0.8352] +2024-11-21 23:10:43.654174: Epoch time: 19.66 s +2024-11-21 23:10:44.487414: +2024-11-21 23:10:44.487645: Epoch 2329 +2024-11-21 23:10:44.487752: Current learning rate: 0.00734 +2024-11-21 23:11:02.889380: train_loss -0.7782 +2024-11-21 23:11:02.889594: val_loss -0.8024 +2024-11-21 23:11:02.889667: Pseudo dice [0.8498] +2024-11-21 23:11:02.889743: Epoch time: 18.4 s +2024-11-21 23:11:03.717541: +2024-11-21 23:11:03.717761: Epoch 2330 +2024-11-21 23:11:03.717876: Current learning rate: 0.00734 +2024-11-21 23:11:23.012923: train_loss -0.7782 +2024-11-21 23:11:23.013191: val_loss -0.7524 +2024-11-21 23:11:23.013273: Pseudo dice [0.842] +2024-11-21 23:11:23.013370: Epoch time: 19.3 s +2024-11-21 23:11:23.844536: +2024-11-21 23:11:23.844774: Epoch 2331 +2024-11-21 23:11:23.844890: Current learning rate: 0.00733 +2024-11-21 23:11:42.167454: train_loss -0.7798 +2024-11-21 23:11:42.167705: val_loss -0.784 +2024-11-21 23:11:42.167784: Pseudo dice [0.8397] +2024-11-21 23:11:42.167871: Epoch time: 18.32 s +2024-11-21 23:11:43.001062: +2024-11-21 23:11:43.001274: Epoch 2332 +2024-11-21 23:11:43.001390: Current learning rate: 0.00733 +2024-11-21 23:12:01.759753: train_loss -0.7765 +2024-11-21 23:12:01.759971: val_loss -0.7545 +2024-11-21 23:12:01.760056: Pseudo dice [0.8279] +2024-11-21 23:12:01.760133: Epoch time: 18.76 s +2024-11-21 23:12:02.978511: +2024-11-21 23:12:02.978751: Epoch 2333 +2024-11-21 23:12:02.978868: Current learning rate: 0.00733 +2024-11-21 23:12:20.602563: train_loss -0.7805 +2024-11-21 23:12:20.602807: val_loss -0.7425 +2024-11-21 23:12:20.602882: Pseudo dice [0.836] +2024-11-21 23:12:20.602960: Epoch time: 17.62 s +2024-11-21 23:12:21.433544: +2024-11-21 23:12:21.433773: Epoch 2334 +2024-11-21 23:12:21.433891: Current learning rate: 0.00733 +2024-11-21 23:12:38.123719: train_loss -0.7825 +2024-11-21 23:12:38.126147: val_loss -0.7585 +2024-11-21 23:12:38.126291: Pseudo dice [0.835] +2024-11-21 23:12:38.126382: Epoch time: 16.69 s +2024-11-21 23:12:38.955907: +2024-11-21 23:12:38.956137: Epoch 2335 +2024-11-21 23:12:38.956245: Current learning rate: 0.00733 +2024-11-21 23:12:57.365973: train_loss -0.7733 +2024-11-21 23:12:57.366185: val_loss -0.7741 +2024-11-21 23:12:57.366258: Pseudo dice [0.8487] +2024-11-21 23:12:57.366331: Epoch time: 18.41 s +2024-11-21 23:12:58.200973: +2024-11-21 23:12:58.201197: Epoch 2336 +2024-11-21 23:12:58.201319: Current learning rate: 0.00733 +2024-11-21 23:13:16.245428: train_loss -0.7738 +2024-11-21 23:13:16.245666: val_loss -0.772 +2024-11-21 23:13:16.245744: Pseudo dice [0.8597] +2024-11-21 23:13:16.245823: Epoch time: 18.05 s +2024-11-21 23:13:17.078377: +2024-11-21 23:13:17.078614: Epoch 2337 +2024-11-21 23:13:17.078725: Current learning rate: 0.00733 +2024-11-21 23:13:35.770572: train_loss -0.7843 +2024-11-21 23:13:35.770831: val_loss -0.7704 +2024-11-21 23:13:35.770908: Pseudo dice [0.855] +2024-11-21 23:13:35.770999: Epoch time: 18.69 s +2024-11-21 23:13:36.676732: +2024-11-21 23:13:36.676929: Epoch 2338 +2024-11-21 23:13:36.677043: Current learning rate: 0.00733 +2024-11-21 23:13:55.517934: train_loss -0.7682 +2024-11-21 23:13:55.518187: val_loss -0.7636 +2024-11-21 23:13:55.518260: Pseudo dice [0.8501] +2024-11-21 23:13:55.518337: Epoch time: 18.84 s +2024-11-21 23:13:56.359415: +2024-11-21 23:13:56.359639: Epoch 2339 +2024-11-21 23:13:56.359752: Current learning rate: 0.00733 +2024-11-21 23:14:14.024364: train_loss -0.7813 +2024-11-21 23:14:14.024626: val_loss -0.7398 +2024-11-21 23:14:14.024705: Pseudo dice [0.8423] +2024-11-21 23:14:14.024782: Epoch time: 17.67 s +2024-11-21 23:14:14.857305: +2024-11-21 23:14:14.857521: Epoch 2340 +2024-11-21 23:14:14.857625: Current learning rate: 0.00732 +2024-11-21 23:14:33.249502: train_loss -0.775 +2024-11-21 23:14:33.249717: val_loss -0.7447 +2024-11-21 23:14:33.249791: Pseudo dice [0.8324] +2024-11-21 23:14:33.249863: Epoch time: 18.39 s +2024-11-21 23:14:34.177895: +2024-11-21 23:14:34.178120: Epoch 2341 +2024-11-21 23:14:34.178228: Current learning rate: 0.00732 +2024-11-21 23:14:52.381304: train_loss -0.7732 +2024-11-21 23:14:52.381552: val_loss -0.7544 +2024-11-21 23:14:52.381630: Pseudo dice [0.8607] +2024-11-21 23:14:52.381714: Epoch time: 18.2 s +2024-11-21 23:14:53.214714: +2024-11-21 23:14:53.214945: Epoch 2342 +2024-11-21 23:14:53.215067: Current learning rate: 0.00732 +2024-11-21 23:15:13.409954: train_loss -0.7744 +2024-11-21 23:15:13.410178: val_loss -0.7352 +2024-11-21 23:15:13.410273: Pseudo dice [0.8422] +2024-11-21 23:15:13.410358: Epoch time: 20.2 s +2024-11-21 23:15:14.252230: +2024-11-21 23:15:14.252461: Epoch 2343 +2024-11-21 23:15:14.252575: Current learning rate: 0.00732 +2024-11-21 23:15:31.803259: train_loss -0.7815 +2024-11-21 23:15:31.803700: val_loss -0.7732 +2024-11-21 23:15:31.803784: Pseudo dice [0.8508] +2024-11-21 23:15:31.803859: Epoch time: 17.55 s +2024-11-21 23:15:32.633213: +2024-11-21 23:15:32.633439: Epoch 2344 +2024-11-21 23:15:32.633555: Current learning rate: 0.00732 +2024-11-21 23:15:51.429354: train_loss -0.7819 +2024-11-21 23:15:51.429573: val_loss -0.7632 +2024-11-21 23:15:51.429648: Pseudo dice [0.8374] +2024-11-21 23:15:51.429729: Epoch time: 18.8 s +2024-11-21 23:15:52.663439: +2024-11-21 23:15:52.663780: Epoch 2345 +2024-11-21 23:15:52.663901: Current learning rate: 0.00732 +2024-11-21 23:16:10.755159: train_loss -0.7777 +2024-11-21 23:16:10.755403: val_loss -0.7438 +2024-11-21 23:16:10.755476: Pseudo dice [0.8354] +2024-11-21 23:16:10.755554: Epoch time: 18.09 s +2024-11-21 23:16:11.584536: +2024-11-21 23:16:11.584780: Epoch 2346 +2024-11-21 23:16:11.584895: Current learning rate: 0.00732 +2024-11-21 23:16:30.003810: train_loss -0.7781 +2024-11-21 23:16:30.004043: val_loss -0.7663 +2024-11-21 23:16:30.004120: Pseudo dice [0.8433] +2024-11-21 23:16:30.004201: Epoch time: 18.42 s +2024-11-21 23:16:30.834652: +2024-11-21 23:16:30.834871: Epoch 2347 +2024-11-21 23:16:30.834984: Current learning rate: 0.00732 +2024-11-21 23:16:50.080720: train_loss -0.7822 +2024-11-21 23:16:50.080928: val_loss -0.7652 +2024-11-21 23:16:50.081008: Pseudo dice [0.8339] +2024-11-21 23:16:50.081081: Epoch time: 19.25 s +2024-11-21 23:16:50.905716: +2024-11-21 23:16:50.905936: Epoch 2348 +2024-11-21 23:16:50.906057: Current learning rate: 0.00731 +2024-11-21 23:17:09.102331: train_loss -0.771 +2024-11-21 23:17:09.102574: val_loss -0.7416 +2024-11-21 23:17:09.102652: Pseudo dice [0.8416] +2024-11-21 23:17:09.102738: Epoch time: 18.2 s +2024-11-21 23:17:09.933270: +2024-11-21 23:17:09.933521: Epoch 2349 +2024-11-21 23:17:09.933633: Current learning rate: 0.00731 +2024-11-21 23:17:28.606214: train_loss -0.7787 +2024-11-21 23:17:28.606480: val_loss -0.7656 +2024-11-21 23:17:28.606553: Pseudo dice [0.8228] +2024-11-21 23:17:28.606626: Epoch time: 18.67 s +2024-11-21 23:17:29.790948: +2024-11-21 23:17:29.791168: Epoch 2350 +2024-11-21 23:17:29.791292: Current learning rate: 0.00731 +2024-11-21 23:17:47.606153: train_loss -0.7637 +2024-11-21 23:17:47.606383: val_loss -0.7505 +2024-11-21 23:17:47.606459: Pseudo dice [0.84] +2024-11-21 23:17:47.606566: Epoch time: 17.82 s +2024-11-21 23:17:48.439087: +2024-11-21 23:17:48.439368: Epoch 2351 +2024-11-21 23:17:48.439489: Current learning rate: 0.00731 +2024-11-21 23:18:06.185543: train_loss -0.7684 +2024-11-21 23:18:06.185778: val_loss -0.744 +2024-11-21 23:18:06.185855: Pseudo dice [0.8155] +2024-11-21 23:18:06.185935: Epoch time: 17.75 s +2024-11-21 23:18:07.023436: +2024-11-21 23:18:07.023658: Epoch 2352 +2024-11-21 23:18:07.023767: Current learning rate: 0.00731 +2024-11-21 23:18:24.985385: train_loss -0.7844 +2024-11-21 23:18:24.985627: val_loss -0.7556 +2024-11-21 23:18:24.985702: Pseudo dice [0.8363] +2024-11-21 23:18:24.985784: Epoch time: 17.96 s +2024-11-21 23:18:25.816632: +2024-11-21 23:18:25.816854: Epoch 2353 +2024-11-21 23:18:25.816968: Current learning rate: 0.00731 +2024-11-21 23:18:44.741200: train_loss -0.7658 +2024-11-21 23:18:44.741412: val_loss -0.7528 +2024-11-21 23:18:44.741493: Pseudo dice [0.8188] +2024-11-21 23:18:44.741568: Epoch time: 18.93 s +2024-11-21 23:18:45.568782: +2024-11-21 23:18:45.569052: Epoch 2354 +2024-11-21 23:18:45.569156: Current learning rate: 0.00731 +2024-11-21 23:19:04.151005: train_loss -0.7749 +2024-11-21 23:19:04.151217: val_loss -0.7681 +2024-11-21 23:19:04.151291: Pseudo dice [0.8463] +2024-11-21 23:19:04.151363: Epoch time: 18.58 s +2024-11-21 23:19:04.975468: +2024-11-21 23:19:04.975688: Epoch 2355 +2024-11-21 23:19:04.975805: Current learning rate: 0.00731 +2024-11-21 23:19:23.579360: train_loss -0.7769 +2024-11-21 23:19:23.579661: val_loss -0.7623 +2024-11-21 23:19:23.579746: Pseudo dice [0.8409] +2024-11-21 23:19:23.579847: Epoch time: 18.6 s +2024-11-21 23:19:24.458830: +2024-11-21 23:19:24.459052: Epoch 2356 +2024-11-21 23:19:24.459167: Current learning rate: 0.00731 +2024-11-21 23:19:42.184403: train_loss -0.7694 +2024-11-21 23:19:42.184633: val_loss -0.7721 +2024-11-21 23:19:42.184711: Pseudo dice [0.8344] +2024-11-21 23:19:42.184786: Epoch time: 17.73 s +2024-11-21 23:19:43.403345: +2024-11-21 23:19:43.403572: Epoch 2357 +2024-11-21 23:19:43.403681: Current learning rate: 0.0073 +2024-11-21 23:20:01.459525: train_loss -0.7893 +2024-11-21 23:20:01.459752: val_loss -0.7497 +2024-11-21 23:20:01.459826: Pseudo dice [0.8351] +2024-11-21 23:20:01.459899: Epoch time: 18.06 s +2024-11-21 23:20:02.290793: +2024-11-21 23:20:02.291020: Epoch 2358 +2024-11-21 23:20:02.291130: Current learning rate: 0.0073 +2024-11-21 23:20:20.690149: train_loss -0.7882 +2024-11-21 23:20:20.690368: val_loss -0.7767 +2024-11-21 23:20:20.690443: Pseudo dice [0.8311] +2024-11-21 23:20:20.690546: Epoch time: 18.4 s +2024-11-21 23:20:21.529834: +2024-11-21 23:20:21.530141: Epoch 2359 +2024-11-21 23:20:21.530258: Current learning rate: 0.0073 +2024-11-21 23:20:40.027451: train_loss -0.7664 +2024-11-21 23:20:40.027675: val_loss -0.7616 +2024-11-21 23:20:40.027750: Pseudo dice [0.8485] +2024-11-21 23:20:40.027832: Epoch time: 18.5 s +2024-11-21 23:20:40.864371: +2024-11-21 23:20:40.864578: Epoch 2360 +2024-11-21 23:20:40.864693: Current learning rate: 0.0073 +2024-11-21 23:20:59.642887: train_loss -0.7747 +2024-11-21 23:20:59.643115: val_loss -0.7697 +2024-11-21 23:20:59.643190: Pseudo dice [0.8317] +2024-11-21 23:20:59.643265: Epoch time: 18.78 s +2024-11-21 23:21:00.474837: +2024-11-21 23:21:00.475069: Epoch 2361 +2024-11-21 23:21:00.475188: Current learning rate: 0.0073 +2024-11-21 23:21:18.689888: train_loss -0.7742 +2024-11-21 23:21:18.690114: val_loss -0.7454 +2024-11-21 23:21:18.690188: Pseudo dice [0.8396] +2024-11-21 23:21:18.690262: Epoch time: 18.22 s +2024-11-21 23:21:19.523544: +2024-11-21 23:21:19.523758: Epoch 2362 +2024-11-21 23:21:19.523869: Current learning rate: 0.0073 +2024-11-21 23:21:37.889555: train_loss -0.78 +2024-11-21 23:21:37.889810: val_loss -0.7949 +2024-11-21 23:21:37.889888: Pseudo dice [0.8491] +2024-11-21 23:21:37.889971: Epoch time: 18.37 s +2024-11-21 23:21:38.724131: +2024-11-21 23:21:38.724337: Epoch 2363 +2024-11-21 23:21:38.724452: Current learning rate: 0.0073 +2024-11-21 23:21:57.393918: train_loss -0.7758 +2024-11-21 23:21:57.394146: val_loss -0.7746 +2024-11-21 23:21:57.394220: Pseudo dice [0.8461] +2024-11-21 23:21:57.394293: Epoch time: 18.67 s +2024-11-21 23:21:58.220827: +2024-11-21 23:21:58.221044: Epoch 2364 +2024-11-21 23:21:58.221152: Current learning rate: 0.0073 +2024-11-21 23:22:17.248029: train_loss -0.7774 +2024-11-21 23:22:17.248250: val_loss -0.7728 +2024-11-21 23:22:17.248336: Pseudo dice [0.8288] +2024-11-21 23:22:17.248414: Epoch time: 19.03 s +2024-11-21 23:22:18.080269: +2024-11-21 23:22:18.080468: Epoch 2365 +2024-11-21 23:22:18.080578: Current learning rate: 0.00729 +2024-11-21 23:22:37.083901: train_loss -0.7747 +2024-11-21 23:22:37.084127: val_loss -0.779 +2024-11-21 23:22:37.084205: Pseudo dice [0.8506] +2024-11-21 23:22:37.084289: Epoch time: 19.0 s +2024-11-21 23:22:37.910955: +2024-11-21 23:22:37.911170: Epoch 2366 +2024-11-21 23:22:37.911276: Current learning rate: 0.00729 +2024-11-21 23:22:55.739224: train_loss -0.7736 +2024-11-21 23:22:55.739461: val_loss -0.7476 +2024-11-21 23:22:55.739536: Pseudo dice [0.8232] +2024-11-21 23:22:55.739612: Epoch time: 17.83 s +2024-11-21 23:22:56.568220: +2024-11-21 23:22:56.568437: Epoch 2367 +2024-11-21 23:22:56.568545: Current learning rate: 0.00729 +2024-11-21 23:23:14.323581: train_loss -0.7723 +2024-11-21 23:23:14.323814: val_loss -0.7675 +2024-11-21 23:23:14.323892: Pseudo dice [0.8455] +2024-11-21 23:23:14.323974: Epoch time: 17.76 s +2024-11-21 23:23:15.152843: +2024-11-21 23:23:15.153264: Epoch 2368 +2024-11-21 23:23:15.153396: Current learning rate: 0.00729 +2024-11-21 23:23:32.656204: train_loss -0.7841 +2024-11-21 23:23:32.656421: val_loss -0.7536 +2024-11-21 23:23:32.656495: Pseudo dice [0.8359] +2024-11-21 23:23:32.656572: Epoch time: 17.5 s +2024-11-21 23:23:33.979740: +2024-11-21 23:23:33.980141: Epoch 2369 +2024-11-21 23:23:33.980253: Current learning rate: 0.00729 +2024-11-21 23:23:52.011085: train_loss -0.7788 +2024-11-21 23:23:52.011666: val_loss -0.7486 +2024-11-21 23:23:52.011757: Pseudo dice [0.8439] +2024-11-21 23:23:52.011845: Epoch time: 18.03 s +2024-11-21 23:23:52.847064: +2024-11-21 23:23:52.847290: Epoch 2370 +2024-11-21 23:23:52.847401: Current learning rate: 0.00729 +2024-11-21 23:24:11.266363: train_loss -0.7891 +2024-11-21 23:24:11.266614: val_loss -0.7639 +2024-11-21 23:24:11.266695: Pseudo dice [0.8509] +2024-11-21 23:24:11.266773: Epoch time: 18.42 s +2024-11-21 23:24:12.101020: +2024-11-21 23:24:12.101259: Epoch 2371 +2024-11-21 23:24:12.101374: Current learning rate: 0.00729 +2024-11-21 23:24:30.067804: train_loss -0.7852 +2024-11-21 23:24:30.068036: val_loss -0.7833 +2024-11-21 23:24:30.068120: Pseudo dice [0.8519] +2024-11-21 23:24:30.068193: Epoch time: 17.97 s +2024-11-21 23:24:31.052335: +2024-11-21 23:24:31.052581: Epoch 2372 +2024-11-21 23:24:31.052696: Current learning rate: 0.00729 +2024-11-21 23:24:50.784306: train_loss -0.7806 +2024-11-21 23:24:50.784592: val_loss -0.7602 +2024-11-21 23:24:50.784679: Pseudo dice [0.8374] +2024-11-21 23:24:50.784767: Epoch time: 19.73 s +2024-11-21 23:24:51.623022: +2024-11-21 23:24:51.623247: Epoch 2373 +2024-11-21 23:24:51.623361: Current learning rate: 0.00729 +2024-11-21 23:25:11.037841: train_loss -0.7706 +2024-11-21 23:25:11.038067: val_loss -0.738 +2024-11-21 23:25:11.043296: Pseudo dice [0.8388] +2024-11-21 23:25:11.043455: Epoch time: 19.42 s +2024-11-21 23:25:12.035758: +2024-11-21 23:25:12.035961: Epoch 2374 +2024-11-21 23:25:12.036076: Current learning rate: 0.00728 +2024-11-21 23:25:30.123078: train_loss -0.7734 +2024-11-21 23:25:30.123289: val_loss -0.7418 +2024-11-21 23:25:30.123360: Pseudo dice [0.8136] +2024-11-21 23:25:30.123435: Epoch time: 18.09 s +2024-11-21 23:25:30.954372: +2024-11-21 23:25:30.954598: Epoch 2375 +2024-11-21 23:25:30.954714: Current learning rate: 0.00728 +2024-11-21 23:25:48.466165: train_loss -0.7624 +2024-11-21 23:25:48.466431: val_loss -0.7561 +2024-11-21 23:25:48.466511: Pseudo dice [0.8262] +2024-11-21 23:25:48.466584: Epoch time: 17.51 s +2024-11-21 23:25:49.304938: +2024-11-21 23:25:49.305152: Epoch 2376 +2024-11-21 23:25:49.305260: Current learning rate: 0.00728 +2024-11-21 23:26:07.844050: train_loss -0.7826 +2024-11-21 23:26:07.844280: val_loss -0.7867 +2024-11-21 23:26:07.844356: Pseudo dice [0.8652] +2024-11-21 23:26:07.844432: Epoch time: 18.54 s +2024-11-21 23:26:08.676754: +2024-11-21 23:26:08.676957: Epoch 2377 +2024-11-21 23:26:08.677078: Current learning rate: 0.00728 +2024-11-21 23:26:27.189924: train_loss -0.777 +2024-11-21 23:26:27.190188: val_loss -0.7246 +2024-11-21 23:26:27.190269: Pseudo dice [0.8404] +2024-11-21 23:26:27.190374: Epoch time: 18.51 s +2024-11-21 23:26:28.074912: +2024-11-21 23:26:28.075126: Epoch 2378 +2024-11-21 23:26:28.075235: Current learning rate: 0.00728 +2024-11-21 23:26:47.366493: train_loss -0.7864 +2024-11-21 23:26:47.366721: val_loss -0.7612 +2024-11-21 23:26:47.366793: Pseudo dice [0.8387] +2024-11-21 23:26:47.366867: Epoch time: 19.29 s +2024-11-21 23:26:48.236176: +2024-11-21 23:26:48.236399: Epoch 2379 +2024-11-21 23:26:48.236514: Current learning rate: 0.00728 +2024-11-21 23:27:06.761948: train_loss -0.7742 +2024-11-21 23:27:06.762238: val_loss -0.7919 +2024-11-21 23:27:06.762325: Pseudo dice [0.8596] +2024-11-21 23:27:06.762405: Epoch time: 18.53 s +2024-11-21 23:27:07.596375: +2024-11-21 23:27:07.596599: Epoch 2380 +2024-11-21 23:27:07.596711: Current learning rate: 0.00728 +2024-11-21 23:27:26.078618: train_loss -0.7786 +2024-11-21 23:27:26.078857: val_loss -0.7529 +2024-11-21 23:27:26.078935: Pseudo dice [0.835] +2024-11-21 23:27:26.079027: Epoch time: 18.48 s +2024-11-21 23:27:27.302465: +2024-11-21 23:27:27.302676: Epoch 2381 +2024-11-21 23:27:27.302786: Current learning rate: 0.00728 +2024-11-21 23:27:45.489143: train_loss -0.7744 +2024-11-21 23:27:45.489366: val_loss -0.7618 +2024-11-21 23:27:45.489440: Pseudo dice [0.8459] +2024-11-21 23:27:45.489515: Epoch time: 18.19 s +2024-11-21 23:27:46.323941: +2024-11-21 23:27:46.324167: Epoch 2382 +2024-11-21 23:27:46.324280: Current learning rate: 0.00728 +2024-11-21 23:28:04.836468: train_loss -0.7746 +2024-11-21 23:28:04.836688: val_loss -0.7782 +2024-11-21 23:28:04.836766: Pseudo dice [0.8411] +2024-11-21 23:28:04.836845: Epoch time: 18.51 s +2024-11-21 23:28:05.685799: +2024-11-21 23:28:05.686023: Epoch 2383 +2024-11-21 23:28:05.686136: Current learning rate: 0.00727 +2024-11-21 23:28:23.793827: train_loss -0.7686 +2024-11-21 23:28:23.794075: val_loss -0.7796 +2024-11-21 23:28:23.794204: Pseudo dice [0.8459] +2024-11-21 23:28:23.794290: Epoch time: 18.11 s +2024-11-21 23:28:24.739373: +2024-11-21 23:28:24.739596: Epoch 2384 +2024-11-21 23:28:24.739707: Current learning rate: 0.00727 +2024-11-21 23:28:43.876938: train_loss -0.7831 +2024-11-21 23:28:43.877209: val_loss -0.7509 +2024-11-21 23:28:43.877286: Pseudo dice [0.8289] +2024-11-21 23:28:43.877359: Epoch time: 19.14 s +2024-11-21 23:28:44.730616: +2024-11-21 23:28:44.730839: Epoch 2385 +2024-11-21 23:28:44.730951: Current learning rate: 0.00727 +2024-11-21 23:29:02.120081: train_loss -0.7735 +2024-11-21 23:29:02.120286: val_loss -0.7708 +2024-11-21 23:29:02.120358: Pseudo dice [0.8404] +2024-11-21 23:29:02.120431: Epoch time: 17.39 s +2024-11-21 23:29:02.960227: +2024-11-21 23:29:02.960459: Epoch 2386 +2024-11-21 23:29:02.960572: Current learning rate: 0.00727 +2024-11-21 23:29:21.766007: train_loss -0.7745 +2024-11-21 23:29:21.766225: val_loss -0.7632 +2024-11-21 23:29:21.766297: Pseudo dice [0.8475] +2024-11-21 23:29:21.766373: Epoch time: 18.81 s +2024-11-21 23:29:22.709644: +2024-11-21 23:29:22.709852: Epoch 2387 +2024-11-21 23:29:22.709962: Current learning rate: 0.00727 +2024-11-21 23:29:41.451548: train_loss -0.7776 +2024-11-21 23:29:41.451801: val_loss -0.7506 +2024-11-21 23:29:41.451875: Pseudo dice [0.8421] +2024-11-21 23:29:41.452024: Epoch time: 18.74 s +2024-11-21 23:29:42.294376: +2024-11-21 23:29:42.294584: Epoch 2388 +2024-11-21 23:29:42.294696: Current learning rate: 0.00727 +2024-11-21 23:30:01.907507: train_loss -0.7825 +2024-11-21 23:30:01.907732: val_loss -0.7511 +2024-11-21 23:30:01.907804: Pseudo dice [0.8352] +2024-11-21 23:30:01.907877: Epoch time: 19.61 s +2024-11-21 23:30:02.756011: +2024-11-21 23:30:02.756314: Epoch 2389 +2024-11-21 23:30:02.756425: Current learning rate: 0.00727 +2024-11-21 23:30:21.567246: train_loss -0.7676 +2024-11-21 23:30:21.567480: val_loss -0.7621 +2024-11-21 23:30:21.567556: Pseudo dice [0.8224] +2024-11-21 23:30:21.567648: Epoch time: 18.81 s +2024-11-21 23:30:22.423951: +2024-11-21 23:30:22.424184: Epoch 2390 +2024-11-21 23:30:22.424293: Current learning rate: 0.00727 +2024-11-21 23:30:40.741024: train_loss -0.7724 +2024-11-21 23:30:40.741251: val_loss -0.7575 +2024-11-21 23:30:40.741324: Pseudo dice [0.8228] +2024-11-21 23:30:40.741397: Epoch time: 18.32 s +2024-11-21 23:30:41.603507: +2024-11-21 23:30:41.603748: Epoch 2391 +2024-11-21 23:30:41.603875: Current learning rate: 0.00726 +2024-11-21 23:30:58.536340: train_loss -0.7762 +2024-11-21 23:30:58.537201: val_loss -0.7638 +2024-11-21 23:30:58.537282: Pseudo dice [0.8433] +2024-11-21 23:30:58.537365: Epoch time: 16.93 s +2024-11-21 23:30:59.368587: +2024-11-21 23:30:59.368805: Epoch 2392 +2024-11-21 23:30:59.368920: Current learning rate: 0.00726 +2024-11-21 23:31:17.501392: train_loss -0.7755 +2024-11-21 23:31:17.501614: val_loss -0.7492 +2024-11-21 23:31:17.501688: Pseudo dice [0.8532] +2024-11-21 23:31:17.501764: Epoch time: 18.13 s +2024-11-21 23:31:18.945190: +2024-11-21 23:31:18.945396: Epoch 2393 +2024-11-21 23:31:18.945502: Current learning rate: 0.00726 +2024-11-21 23:31:36.990160: train_loss -0.7681 +2024-11-21 23:31:36.990381: val_loss -0.7733 +2024-11-21 23:31:36.990460: Pseudo dice [0.8514] +2024-11-21 23:31:36.990542: Epoch time: 18.05 s +2024-11-21 23:31:37.828810: +2024-11-21 23:31:37.829028: Epoch 2394 +2024-11-21 23:31:37.829135: Current learning rate: 0.00726 +2024-11-21 23:31:56.754197: train_loss -0.7606 +2024-11-21 23:31:56.754436: val_loss -0.7318 +2024-11-21 23:31:56.754517: Pseudo dice [0.8072] +2024-11-21 23:31:56.754597: Epoch time: 18.93 s +2024-11-21 23:31:57.593968: +2024-11-21 23:31:57.594297: Epoch 2395 +2024-11-21 23:31:57.594405: Current learning rate: 0.00726 +2024-11-21 23:32:17.195493: train_loss -0.7558 +2024-11-21 23:32:17.195720: val_loss -0.762 +2024-11-21 23:32:17.195799: Pseudo dice [0.8468] +2024-11-21 23:32:17.195875: Epoch time: 19.6 s +2024-11-21 23:32:18.052801: +2024-11-21 23:32:18.053021: Epoch 2396 +2024-11-21 23:32:18.053138: Current learning rate: 0.00726 +2024-11-21 23:32:35.907650: train_loss -0.7546 +2024-11-21 23:32:35.909546: val_loss -0.7477 +2024-11-21 23:32:35.909689: Pseudo dice [0.8248] +2024-11-21 23:32:35.909773: Epoch time: 17.86 s +2024-11-21 23:32:36.749884: +2024-11-21 23:32:36.750116: Epoch 2397 +2024-11-21 23:32:36.750237: Current learning rate: 0.00726 +2024-11-21 23:32:55.609601: train_loss -0.7536 +2024-11-21 23:32:55.609848: val_loss -0.7392 +2024-11-21 23:32:55.609924: Pseudo dice [0.8256] +2024-11-21 23:32:55.610013: Epoch time: 18.86 s +2024-11-21 23:32:56.449042: +2024-11-21 23:32:56.449260: Epoch 2398 +2024-11-21 23:32:56.449374: Current learning rate: 0.00726 +2024-11-21 23:33:15.075684: train_loss -0.7612 +2024-11-21 23:33:15.075902: val_loss -0.783 +2024-11-21 23:33:15.075978: Pseudo dice [0.8503] +2024-11-21 23:33:15.076058: Epoch time: 18.63 s +2024-11-21 23:33:15.932705: +2024-11-21 23:33:15.932925: Epoch 2399 +2024-11-21 23:33:15.933047: Current learning rate: 0.00726 +2024-11-21 23:33:34.152837: train_loss -0.7773 +2024-11-21 23:33:34.153054: val_loss -0.7698 +2024-11-21 23:33:34.153130: Pseudo dice [0.8461] +2024-11-21 23:33:34.153203: Epoch time: 18.22 s +2024-11-21 23:33:35.226449: +2024-11-21 23:33:35.226645: Epoch 2400 +2024-11-21 23:33:35.226757: Current learning rate: 0.00725 +2024-11-21 23:33:53.133810: train_loss -0.7844 +2024-11-21 23:33:53.134070: val_loss -0.784 +2024-11-21 23:33:53.134148: Pseudo dice [0.8527] +2024-11-21 23:33:53.134234: Epoch time: 17.91 s +2024-11-21 23:33:54.023717: +2024-11-21 23:33:54.023940: Epoch 2401 +2024-11-21 23:33:54.024064: Current learning rate: 0.00725 +2024-11-21 23:34:12.021196: train_loss -0.7723 +2024-11-21 23:34:12.021457: val_loss -0.7517 +2024-11-21 23:34:12.021533: Pseudo dice [0.8339] +2024-11-21 23:34:12.021605: Epoch time: 18.0 s +2024-11-21 23:34:13.002981: +2024-11-21 23:34:13.003201: Epoch 2402 +2024-11-21 23:34:13.003314: Current learning rate: 0.00725 +2024-11-21 23:34:30.660647: train_loss -0.7744 +2024-11-21 23:34:30.660870: val_loss -0.7461 +2024-11-21 23:34:30.660953: Pseudo dice [0.8326] +2024-11-21 23:34:30.661657: Epoch time: 17.66 s +2024-11-21 23:34:31.611132: +2024-11-21 23:34:31.611334: Epoch 2403 +2024-11-21 23:34:31.611443: Current learning rate: 0.00725 +2024-11-21 23:34:50.373313: train_loss -0.7736 +2024-11-21 23:34:50.373580: val_loss -0.7858 +2024-11-21 23:34:50.373657: Pseudo dice [0.851] +2024-11-21 23:34:50.373732: Epoch time: 18.76 s +2024-11-21 23:34:51.210138: +2024-11-21 23:34:51.210348: Epoch 2404 +2024-11-21 23:34:51.210457: Current learning rate: 0.00725 +2024-11-21 23:35:10.244183: train_loss -0.7771 +2024-11-21 23:35:10.249840: val_loss -0.7769 +2024-11-21 23:35:10.249953: Pseudo dice [0.8458] +2024-11-21 23:35:10.250040: Epoch time: 19.03 s +2024-11-21 23:35:11.095119: +2024-11-21 23:35:11.095349: Epoch 2405 +2024-11-21 23:35:11.095466: Current learning rate: 0.00725 +2024-11-21 23:35:29.297668: train_loss -0.7798 +2024-11-21 23:35:29.297921: val_loss -0.7833 +2024-11-21 23:35:29.298004: Pseudo dice [0.8664] +2024-11-21 23:35:29.298080: Epoch time: 18.2 s +2024-11-21 23:35:30.135767: +2024-11-21 23:35:30.135973: Epoch 2406 +2024-11-21 23:35:30.136084: Current learning rate: 0.00725 +2024-11-21 23:35:49.035980: train_loss -0.7772 +2024-11-21 23:35:49.036209: val_loss -0.7614 +2024-11-21 23:35:49.036284: Pseudo dice [0.83] +2024-11-21 23:35:49.036359: Epoch time: 18.9 s +2024-11-21 23:35:49.873676: +2024-11-21 23:35:49.873904: Epoch 2407 +2024-11-21 23:35:49.874023: Current learning rate: 0.00725 +2024-11-21 23:36:08.469458: train_loss -0.7698 +2024-11-21 23:36:08.469718: val_loss -0.7644 +2024-11-21 23:36:08.469801: Pseudo dice [0.8536] +2024-11-21 23:36:08.469892: Epoch time: 18.6 s +2024-11-21 23:36:09.308188: +2024-11-21 23:36:09.308496: Epoch 2408 +2024-11-21 23:36:09.308605: Current learning rate: 0.00724 +2024-11-21 23:36:27.759840: train_loss -0.766 +2024-11-21 23:36:27.760109: val_loss -0.7593 +2024-11-21 23:36:27.760184: Pseudo dice [0.8392] +2024-11-21 23:36:27.760264: Epoch time: 18.45 s +2024-11-21 23:36:28.602988: +2024-11-21 23:36:28.603220: Epoch 2409 +2024-11-21 23:36:28.603335: Current learning rate: 0.00724 +2024-11-21 23:36:47.866658: train_loss -0.7654 +2024-11-21 23:36:47.866878: val_loss -0.776 +2024-11-21 23:36:47.867945: Pseudo dice [0.8526] +2024-11-21 23:36:47.868075: Epoch time: 19.26 s +2024-11-21 23:36:48.715098: +2024-11-21 23:36:48.715312: Epoch 2410 +2024-11-21 23:36:48.715424: Current learning rate: 0.00724 +2024-11-21 23:37:07.311527: train_loss -0.7613 +2024-11-21 23:37:07.311746: val_loss -0.7872 +2024-11-21 23:37:07.311822: Pseudo dice [0.8605] +2024-11-21 23:37:07.311896: Epoch time: 18.6 s +2024-11-21 23:37:08.160767: +2024-11-21 23:37:08.161057: Epoch 2411 +2024-11-21 23:37:08.161168: Current learning rate: 0.00724 +2024-11-21 23:37:27.111964: train_loss -0.7752 +2024-11-21 23:37:27.112274: val_loss -0.7775 +2024-11-21 23:37:27.112352: Pseudo dice [0.8499] +2024-11-21 23:37:27.112438: Epoch time: 18.95 s +2024-11-21 23:37:27.960361: +2024-11-21 23:37:27.960574: Epoch 2412 +2024-11-21 23:37:27.960688: Current learning rate: 0.00724 +2024-11-21 23:37:46.664917: train_loss -0.7743 +2024-11-21 23:37:46.665137: val_loss -0.7389 +2024-11-21 23:37:46.691841: Pseudo dice [0.8304] +2024-11-21 23:37:46.692013: Epoch time: 18.71 s +2024-11-21 23:37:47.530918: +2024-11-21 23:37:47.531136: Epoch 2413 +2024-11-21 23:37:47.531245: Current learning rate: 0.00724 +2024-11-21 23:38:05.014153: train_loss -0.7803 +2024-11-21 23:38:05.014373: val_loss -0.7454 +2024-11-21 23:38:05.014451: Pseudo dice [0.8429] +2024-11-21 23:38:05.014529: Epoch time: 17.48 s +2024-11-21 23:38:05.850865: +2024-11-21 23:38:05.851113: Epoch 2414 +2024-11-21 23:38:05.851222: Current learning rate: 0.00724 +2024-11-21 23:38:24.273484: train_loss -0.7735 +2024-11-21 23:38:24.273705: val_loss -0.7728 +2024-11-21 23:38:24.273779: Pseudo dice [0.8587] +2024-11-21 23:38:24.273854: Epoch time: 18.42 s +2024-11-21 23:38:25.113220: +2024-11-21 23:38:25.113426: Epoch 2415 +2024-11-21 23:38:25.113535: Current learning rate: 0.00724 +2024-11-21 23:38:43.528613: train_loss -0.7809 +2024-11-21 23:38:43.528854: val_loss -0.761 +2024-11-21 23:38:43.528930: Pseudo dice [0.8423] +2024-11-21 23:38:43.529018: Epoch time: 18.42 s +2024-11-21 23:38:44.744415: +2024-11-21 23:38:44.744635: Epoch 2416 +2024-11-21 23:38:44.744745: Current learning rate: 0.00724 +2024-11-21 23:39:03.458251: train_loss -0.7791 +2024-11-21 23:39:03.458471: val_loss -0.7543 +2024-11-21 23:39:03.458549: Pseudo dice [0.8343] +2024-11-21 23:39:03.458621: Epoch time: 18.71 s +2024-11-21 23:39:04.301809: +2024-11-21 23:39:04.302047: Epoch 2417 +2024-11-21 23:39:04.302161: Current learning rate: 0.00723 +2024-11-21 23:39:22.906823: train_loss -0.7765 +2024-11-21 23:39:22.907058: val_loss -0.7622 +2024-11-21 23:39:22.907142: Pseudo dice [0.8316] +2024-11-21 23:39:22.907223: Epoch time: 18.61 s +2024-11-21 23:39:23.740381: +2024-11-21 23:39:23.740602: Epoch 2418 +2024-11-21 23:39:23.740714: Current learning rate: 0.00723 +2024-11-21 23:39:42.495910: train_loss -0.7687 +2024-11-21 23:39:42.496191: val_loss -0.7681 +2024-11-21 23:39:42.496272: Pseudo dice [0.8417] +2024-11-21 23:39:42.496356: Epoch time: 18.76 s +2024-11-21 23:39:43.341497: +2024-11-21 23:39:43.341685: Epoch 2419 +2024-11-21 23:39:43.341790: Current learning rate: 0.00723 +2024-11-21 23:40:01.226924: train_loss -0.7819 +2024-11-21 23:40:01.244354: val_loss -0.7513 +2024-11-21 23:40:01.244470: Pseudo dice [0.8396] +2024-11-21 23:40:01.244559: Epoch time: 17.89 s +2024-11-21 23:40:02.103051: +2024-11-21 23:40:02.103258: Epoch 2420 +2024-11-21 23:40:02.103378: Current learning rate: 0.00723 +2024-11-21 23:40:19.643829: train_loss -0.7682 +2024-11-21 23:40:19.644074: val_loss -0.718 +2024-11-21 23:40:19.644155: Pseudo dice [0.8211] +2024-11-21 23:40:19.644233: Epoch time: 17.54 s +2024-11-21 23:40:20.485759: +2024-11-21 23:40:20.485974: Epoch 2421 +2024-11-21 23:40:20.486089: Current learning rate: 0.00723 +2024-11-21 23:40:38.344261: train_loss -0.7672 +2024-11-21 23:40:38.344475: val_loss -0.7256 +2024-11-21 23:40:38.344549: Pseudo dice [0.8335] +2024-11-21 23:40:38.344623: Epoch time: 17.86 s +2024-11-21 23:40:39.183802: +2024-11-21 23:40:39.184013: Epoch 2422 +2024-11-21 23:40:39.184133: Current learning rate: 0.00723 +2024-11-21 23:40:56.526287: train_loss -0.7614 +2024-11-21 23:40:56.526536: val_loss -0.7666 +2024-11-21 23:40:56.526626: Pseudo dice [0.8389] +2024-11-21 23:40:56.526772: Epoch time: 17.34 s +2024-11-21 23:40:57.378175: +2024-11-21 23:40:57.378368: Epoch 2423 +2024-11-21 23:40:57.378475: Current learning rate: 0.00723 +2024-11-21 23:41:15.330049: train_loss -0.7593 +2024-11-21 23:41:15.330276: val_loss -0.7727 +2024-11-21 23:41:15.330350: Pseudo dice [0.8441] +2024-11-21 23:41:15.330422: Epoch time: 17.95 s +2024-11-21 23:41:16.167694: +2024-11-21 23:41:16.167910: Epoch 2424 +2024-11-21 23:41:16.168025: Current learning rate: 0.00723 +2024-11-21 23:41:34.032705: train_loss -0.7722 +2024-11-21 23:41:34.033578: val_loss -0.7606 +2024-11-21 23:41:34.033665: Pseudo dice [0.8407] +2024-11-21 23:41:34.033749: Epoch time: 17.87 s +2024-11-21 23:41:34.992256: +2024-11-21 23:41:34.992469: Epoch 2425 +2024-11-21 23:41:34.992576: Current learning rate: 0.00723 +2024-11-21 23:41:52.208016: train_loss -0.7828 +2024-11-21 23:41:52.208235: val_loss -0.7537 +2024-11-21 23:41:52.208311: Pseudo dice [0.8384] +2024-11-21 23:41:52.208386: Epoch time: 17.22 s +2024-11-21 23:41:53.050472: +2024-11-21 23:41:53.050707: Epoch 2426 +2024-11-21 23:41:53.050825: Current learning rate: 0.00722 +2024-11-21 23:42:11.388773: train_loss -0.7792 +2024-11-21 23:42:11.389014: val_loss -0.7678 +2024-11-21 23:42:11.389091: Pseudo dice [0.836] +2024-11-21 23:42:11.389169: Epoch time: 18.34 s +2024-11-21 23:42:12.222551: +2024-11-21 23:42:12.222771: Epoch 2427 +2024-11-21 23:42:12.222885: Current learning rate: 0.00722 +2024-11-21 23:42:30.478984: train_loss -0.7767 +2024-11-21 23:42:30.479289: val_loss -0.7907 +2024-11-21 23:42:30.479372: Pseudo dice [0.842] +2024-11-21 23:42:30.479448: Epoch time: 18.26 s +2024-11-21 23:42:31.741070: +2024-11-21 23:42:31.741302: Epoch 2428 +2024-11-21 23:42:31.741408: Current learning rate: 0.00722 +2024-11-21 23:42:49.546657: train_loss -0.7813 +2024-11-21 23:42:49.546925: val_loss -0.7718 +2024-11-21 23:42:49.547062: Pseudo dice [0.8475] +2024-11-21 23:42:49.547194: Epoch time: 17.81 s +2024-11-21 23:42:50.393648: +2024-11-21 23:42:50.393870: Epoch 2429 +2024-11-21 23:42:50.393982: Current learning rate: 0.00722 +2024-11-21 23:43:09.277888: train_loss -0.7771 +2024-11-21 23:43:09.278099: val_loss -0.7795 +2024-11-21 23:43:09.278174: Pseudo dice [0.8444] +2024-11-21 23:43:09.278247: Epoch time: 18.89 s +2024-11-21 23:43:10.285884: +2024-11-21 23:43:10.286153: Epoch 2430 +2024-11-21 23:43:10.286272: Current learning rate: 0.00722 +2024-11-21 23:43:28.133621: train_loss -0.7769 +2024-11-21 23:43:28.133837: val_loss -0.7531 +2024-11-21 23:43:28.133915: Pseudo dice [0.8512] +2024-11-21 23:43:28.133998: Epoch time: 17.85 s +2024-11-21 23:43:28.975274: +2024-11-21 23:43:28.975490: Epoch 2431 +2024-11-21 23:43:28.975601: Current learning rate: 0.00722 +2024-11-21 23:43:47.123603: train_loss -0.7805 +2024-11-21 23:43:47.123857: val_loss -0.7674 +2024-11-21 23:43:47.123935: Pseudo dice [0.8582] +2024-11-21 23:43:47.124024: Epoch time: 18.15 s +2024-11-21 23:43:47.968753: +2024-11-21 23:43:47.968955: Epoch 2432 +2024-11-21 23:43:47.969073: Current learning rate: 0.00722 +2024-11-21 23:44:05.607413: train_loss -0.771 +2024-11-21 23:44:05.607633: val_loss -0.7815 +2024-11-21 23:44:05.607708: Pseudo dice [0.843] +2024-11-21 23:44:05.607789: Epoch time: 17.64 s +2024-11-21 23:44:06.456770: +2024-11-21 23:44:06.456996: Epoch 2433 +2024-11-21 23:44:06.457104: Current learning rate: 0.00722 +2024-11-21 23:44:25.937721: train_loss -0.7845 +2024-11-21 23:44:25.937945: val_loss -0.7745 +2024-11-21 23:44:25.938168: Pseudo dice [0.8428] +2024-11-21 23:44:25.938257: Epoch time: 19.48 s +2024-11-21 23:44:26.778944: +2024-11-21 23:44:26.779168: Epoch 2434 +2024-11-21 23:44:26.779277: Current learning rate: 0.00721 +2024-11-21 23:44:45.371307: train_loss -0.7847 +2024-11-21 23:44:45.371520: val_loss -0.7781 +2024-11-21 23:44:45.371650: Pseudo dice [0.8494] +2024-11-21 23:44:45.371726: Epoch time: 18.59 s +2024-11-21 23:44:46.212830: +2024-11-21 23:44:46.213045: Epoch 2435 +2024-11-21 23:44:46.213155: Current learning rate: 0.00721 +2024-11-21 23:45:03.903005: train_loss -0.7856 +2024-11-21 23:45:03.903252: val_loss -0.7591 +2024-11-21 23:45:03.903331: Pseudo dice [0.8604] +2024-11-21 23:45:03.903415: Epoch time: 17.69 s +2024-11-21 23:45:04.746290: +2024-11-21 23:45:04.746503: Epoch 2436 +2024-11-21 23:45:04.746619: Current learning rate: 0.00721 +2024-11-21 23:45:22.798926: train_loss -0.771 +2024-11-21 23:45:22.799157: val_loss -0.7248 +2024-11-21 23:45:22.799236: Pseudo dice [0.8381] +2024-11-21 23:45:22.799312: Epoch time: 18.05 s +2024-11-21 23:45:23.639207: +2024-11-21 23:45:23.639420: Epoch 2437 +2024-11-21 23:45:23.639532: Current learning rate: 0.00721 +2024-11-21 23:45:41.714138: train_loss -0.7733 +2024-11-21 23:45:41.714407: val_loss -0.751 +2024-11-21 23:45:41.714503: Pseudo dice [0.8448] +2024-11-21 23:45:41.714795: Epoch time: 18.08 s +2024-11-21 23:45:42.563555: +2024-11-21 23:45:42.563780: Epoch 2438 +2024-11-21 23:45:42.563897: Current learning rate: 0.00721 +2024-11-21 23:46:00.722411: train_loss -0.7633 +2024-11-21 23:46:00.722674: val_loss -0.7761 +2024-11-21 23:46:00.722754: Pseudo dice [0.8407] +2024-11-21 23:46:00.722842: Epoch time: 18.16 s +2024-11-21 23:46:01.564384: +2024-11-21 23:46:01.564617: Epoch 2439 +2024-11-21 23:46:01.564727: Current learning rate: 0.00721 +2024-11-21 23:46:19.602836: train_loss -0.7676 +2024-11-21 23:46:19.603058: val_loss -0.7734 +2024-11-21 23:46:19.603136: Pseudo dice [0.8397] +2024-11-21 23:46:19.603208: Epoch time: 18.04 s +2024-11-21 23:46:20.812851: +2024-11-21 23:46:20.813064: Epoch 2440 +2024-11-21 23:46:20.813173: Current learning rate: 0.00721 +2024-11-21 23:46:38.890683: train_loss -0.7755 +2024-11-21 23:46:38.890906: val_loss -0.7481 +2024-11-21 23:46:38.890981: Pseudo dice [0.8422] +2024-11-21 23:46:38.891059: Epoch time: 18.08 s +2024-11-21 23:46:40.034815: +2024-11-21 23:46:40.035043: Epoch 2441 +2024-11-21 23:46:40.035152: Current learning rate: 0.00721 +2024-11-21 23:46:58.546031: train_loss -0.7799 +2024-11-21 23:46:58.546284: val_loss -0.7622 +2024-11-21 23:46:58.546364: Pseudo dice [0.8473] +2024-11-21 23:46:58.546451: Epoch time: 18.51 s +2024-11-21 23:46:59.391344: +2024-11-21 23:46:59.391568: Epoch 2442 +2024-11-21 23:46:59.391683: Current learning rate: 0.00721 +2024-11-21 23:47:17.652013: train_loss -0.7687 +2024-11-21 23:47:17.652225: val_loss -0.7796 +2024-11-21 23:47:17.652295: Pseudo dice [0.8467] +2024-11-21 23:47:17.652368: Epoch time: 18.26 s +2024-11-21 23:47:18.523571: +2024-11-21 23:47:18.523810: Epoch 2443 +2024-11-21 23:47:18.523921: Current learning rate: 0.0072 +2024-11-21 23:47:36.437580: train_loss -0.7789 +2024-11-21 23:47:36.437806: val_loss -0.7731 +2024-11-21 23:47:36.437884: Pseudo dice [0.8371] +2024-11-21 23:47:36.437963: Epoch time: 17.91 s +2024-11-21 23:47:37.477269: +2024-11-21 23:47:37.477451: Epoch 2444 +2024-11-21 23:47:37.477560: Current learning rate: 0.0072 +2024-11-21 23:47:56.259475: train_loss -0.77 +2024-11-21 23:47:56.259705: val_loss -0.7524 +2024-11-21 23:47:56.259783: Pseudo dice [0.8467] +2024-11-21 23:47:56.259861: Epoch time: 18.78 s +2024-11-21 23:47:57.211861: +2024-11-21 23:47:57.212115: Epoch 2445 +2024-11-21 23:47:57.212227: Current learning rate: 0.0072 +2024-11-21 23:48:15.654353: train_loss -0.7814 +2024-11-21 23:48:15.654580: val_loss -0.7492 +2024-11-21 23:48:15.654659: Pseudo dice [0.8298] +2024-11-21 23:48:15.654738: Epoch time: 18.44 s +2024-11-21 23:48:16.498914: +2024-11-21 23:48:16.499130: Epoch 2446 +2024-11-21 23:48:16.499251: Current learning rate: 0.0072 +2024-11-21 23:48:34.153759: train_loss -0.7608 +2024-11-21 23:48:34.154045: val_loss -0.7339 +2024-11-21 23:48:34.154166: Pseudo dice [0.8347] +2024-11-21 23:48:34.154251: Epoch time: 17.66 s +2024-11-21 23:48:35.089707: +2024-11-21 23:48:35.089911: Epoch 2447 +2024-11-21 23:48:35.090267: Current learning rate: 0.0072 +2024-11-21 23:48:53.670177: train_loss -0.7572 +2024-11-21 23:48:53.670391: val_loss -0.7536 +2024-11-21 23:48:53.670464: Pseudo dice [0.841] +2024-11-21 23:48:53.670539: Epoch time: 18.58 s +2024-11-21 23:48:54.638432: +2024-11-21 23:48:54.638650: Epoch 2448 +2024-11-21 23:48:54.638762: Current learning rate: 0.0072 +2024-11-21 23:49:13.003482: train_loss -0.7572 +2024-11-21 23:49:13.003701: val_loss -0.7441 +2024-11-21 23:49:13.003774: Pseudo dice [0.8557] +2024-11-21 23:49:13.003849: Epoch time: 18.37 s +2024-11-21 23:49:13.841793: +2024-11-21 23:49:13.842003: Epoch 2449 +2024-11-21 23:49:13.842112: Current learning rate: 0.0072 +2024-11-21 23:49:31.847689: train_loss -0.758 +2024-11-21 23:49:31.850132: val_loss -0.7588 +2024-11-21 23:49:31.850226: Pseudo dice [0.8391] +2024-11-21 23:49:31.850312: Epoch time: 18.01 s +2024-11-21 23:49:32.973771: +2024-11-21 23:49:32.973970: Epoch 2450 +2024-11-21 23:49:32.974085: Current learning rate: 0.0072 +2024-11-21 23:49:51.240468: train_loss -0.7617 +2024-11-21 23:49:51.240701: val_loss -0.7641 +2024-11-21 23:49:51.240777: Pseudo dice [0.8408] +2024-11-21 23:49:51.240859: Epoch time: 18.27 s +2024-11-21 23:49:52.145361: +2024-11-21 23:49:52.145602: Epoch 2451 +2024-11-21 23:49:52.145711: Current learning rate: 0.00719 +2024-11-21 23:50:10.726064: train_loss -0.7755 +2024-11-21 23:50:10.726525: val_loss -0.7433 +2024-11-21 23:50:10.726627: Pseudo dice [0.808] +2024-11-21 23:50:10.726700: Epoch time: 18.58 s +2024-11-21 23:50:11.566474: +2024-11-21 23:50:11.566711: Epoch 2452 +2024-11-21 23:50:11.566832: Current learning rate: 0.00719 +2024-11-21 23:50:29.422293: train_loss -0.7421 +2024-11-21 23:50:29.422541: val_loss -0.7324 +2024-11-21 23:50:29.422615: Pseudo dice [0.8231] +2024-11-21 23:50:29.422695: Epoch time: 17.86 s +2024-11-21 23:50:30.307256: +2024-11-21 23:50:30.307456: Epoch 2453 +2024-11-21 23:50:30.307564: Current learning rate: 0.00719 +2024-11-21 23:50:48.680285: train_loss -0.757 +2024-11-21 23:50:48.680509: val_loss -0.7469 +2024-11-21 23:50:48.680584: Pseudo dice [0.8119] +2024-11-21 23:50:48.680660: Epoch time: 18.37 s +2024-11-21 23:50:49.619607: +2024-11-21 23:50:49.619836: Epoch 2454 +2024-11-21 23:50:49.619963: Current learning rate: 0.00719 +2024-11-21 23:51:07.680369: train_loss -0.7665 +2024-11-21 23:51:07.680587: val_loss -0.7694 +2024-11-21 23:51:07.680661: Pseudo dice [0.8403] +2024-11-21 23:51:07.680733: Epoch time: 18.06 s +2024-11-21 23:51:08.520053: +2024-11-21 23:51:08.520270: Epoch 2455 +2024-11-21 23:51:08.520379: Current learning rate: 0.00719 +2024-11-21 23:51:26.437785: train_loss -0.7729 +2024-11-21 23:51:26.438049: val_loss -0.7785 +2024-11-21 23:51:26.438128: Pseudo dice [0.8371] +2024-11-21 23:51:26.438292: Epoch time: 17.92 s +2024-11-21 23:51:27.290828: +2024-11-21 23:51:27.291036: Epoch 2456 +2024-11-21 23:51:27.291190: Current learning rate: 0.00719 +2024-11-21 23:51:45.746983: train_loss -0.762 +2024-11-21 23:51:45.747196: val_loss -0.7667 +2024-11-21 23:51:45.747269: Pseudo dice [0.8421] +2024-11-21 23:51:45.747341: Epoch time: 18.46 s +2024-11-21 23:51:46.621259: +2024-11-21 23:51:46.621484: Epoch 2457 +2024-11-21 23:51:46.621595: Current learning rate: 0.00719 +2024-11-21 23:52:04.776578: train_loss -0.7718 +2024-11-21 23:52:04.782010: val_loss -0.758 +2024-11-21 23:52:04.782155: Pseudo dice [0.8265] +2024-11-21 23:52:04.782242: Epoch time: 18.16 s +2024-11-21 23:52:05.632826: +2024-11-21 23:52:05.633047: Epoch 2458 +2024-11-21 23:52:05.633160: Current learning rate: 0.00719 +2024-11-21 23:52:23.556919: train_loss -0.7642 +2024-11-21 23:52:23.557151: val_loss -0.7731 +2024-11-21 23:52:23.557229: Pseudo dice [0.8346] +2024-11-21 23:52:23.557305: Epoch time: 17.92 s +2024-11-21 23:52:24.398371: +2024-11-21 23:52:24.398725: Epoch 2459 +2024-11-21 23:52:24.398838: Current learning rate: 0.00719 +2024-11-21 23:52:43.080653: train_loss -0.7608 +2024-11-21 23:52:43.080944: val_loss -0.7623 +2024-11-21 23:52:43.081038: Pseudo dice [0.8256] +2024-11-21 23:52:43.081121: Epoch time: 18.68 s +2024-11-21 23:52:43.947395: +2024-11-21 23:52:43.947603: Epoch 2460 +2024-11-21 23:52:43.947711: Current learning rate: 0.00718 +2024-11-21 23:53:02.547366: train_loss -0.7761 +2024-11-21 23:53:02.547584: val_loss -0.7584 +2024-11-21 23:53:02.547660: Pseudo dice [0.8278] +2024-11-21 23:53:02.547734: Epoch time: 18.6 s +2024-11-21 23:53:03.482723: +2024-11-21 23:53:03.482920: Epoch 2461 +2024-11-21 23:53:03.483028: Current learning rate: 0.00718 +2024-11-21 23:53:21.843570: train_loss -0.7769 +2024-11-21 23:53:21.843795: val_loss -0.7899 +2024-11-21 23:53:21.843873: Pseudo dice [0.8421] +2024-11-21 23:53:21.843946: Epoch time: 18.36 s +2024-11-21 23:53:22.804282: +2024-11-21 23:53:22.804559: Epoch 2462 +2024-11-21 23:53:22.804665: Current learning rate: 0.00718 +2024-11-21 23:53:40.137388: train_loss -0.7798 +2024-11-21 23:53:40.137620: val_loss -0.7743 +2024-11-21 23:53:40.137699: Pseudo dice [0.8295] +2024-11-21 23:53:40.137774: Epoch time: 17.33 s +2024-11-21 23:53:41.353434: +2024-11-21 23:53:41.353662: Epoch 2463 +2024-11-21 23:53:41.353807: Current learning rate: 0.00718 +2024-11-21 23:53:59.642637: train_loss -0.7765 +2024-11-21 23:53:59.642868: val_loss -0.7791 +2024-11-21 23:53:59.642945: Pseudo dice [0.8481] +2024-11-21 23:53:59.643028: Epoch time: 18.29 s +2024-11-21 23:54:00.478910: +2024-11-21 23:54:00.479142: Epoch 2464 +2024-11-21 23:54:00.479272: Current learning rate: 0.00718 +2024-11-21 23:54:18.755045: train_loss -0.775 +2024-11-21 23:54:18.755281: val_loss -0.7657 +2024-11-21 23:54:18.757170: Pseudo dice [0.8565] +2024-11-21 23:54:18.757265: Epoch time: 18.28 s +2024-11-21 23:54:19.604970: +2024-11-21 23:54:19.605198: Epoch 2465 +2024-11-21 23:54:19.605342: Current learning rate: 0.00718 +2024-11-21 23:54:37.798650: train_loss -0.7793 +2024-11-21 23:54:37.798884: val_loss -0.7658 +2024-11-21 23:54:37.798961: Pseudo dice [0.8438] +2024-11-21 23:54:37.799051: Epoch time: 18.19 s +2024-11-21 23:54:38.640001: +2024-11-21 23:54:38.640206: Epoch 2466 +2024-11-21 23:54:38.640317: Current learning rate: 0.00718 +2024-11-21 23:54:57.801481: train_loss -0.782 +2024-11-21 23:54:57.801690: val_loss -0.7632 +2024-11-21 23:54:57.801767: Pseudo dice [0.8262] +2024-11-21 23:54:57.801842: Epoch time: 19.16 s +2024-11-21 23:54:58.645256: +2024-11-21 23:54:58.645476: Epoch 2467 +2024-11-21 23:54:58.645593: Current learning rate: 0.00718 +2024-11-21 23:55:17.140579: train_loss -0.7624 +2024-11-21 23:55:17.143018: val_loss -0.7273 +2024-11-21 23:55:17.143158: Pseudo dice [0.8409] +2024-11-21 23:55:17.143241: Epoch time: 18.5 s +2024-11-21 23:55:18.000823: +2024-11-21 23:55:18.001025: Epoch 2468 +2024-11-21 23:55:18.001136: Current learning rate: 0.00717 +2024-11-21 23:55:36.829264: train_loss -0.78 +2024-11-21 23:55:36.829497: val_loss -0.7539 +2024-11-21 23:55:36.829633: Pseudo dice [0.844] +2024-11-21 23:55:36.829710: Epoch time: 18.83 s +2024-11-21 23:55:37.673421: +2024-11-21 23:55:37.673687: Epoch 2469 +2024-11-21 23:55:37.673800: Current learning rate: 0.00717 +2024-11-21 23:55:56.227595: train_loss -0.769 +2024-11-21 23:55:56.227851: val_loss -0.7647 +2024-11-21 23:55:56.227931: Pseudo dice [0.8368] +2024-11-21 23:55:56.228024: Epoch time: 18.56 s +2024-11-21 23:55:57.069590: +2024-11-21 23:55:57.069802: Epoch 2470 +2024-11-21 23:55:57.069913: Current learning rate: 0.00717 +2024-11-21 23:56:15.350960: train_loss -0.7755 +2024-11-21 23:56:15.351177: val_loss -0.7612 +2024-11-21 23:56:15.351255: Pseudo dice [0.8324] +2024-11-21 23:56:15.351336: Epoch time: 18.28 s +2024-11-21 23:56:16.185649: +2024-11-21 23:56:16.185850: Epoch 2471 +2024-11-21 23:56:16.185961: Current learning rate: 0.00717 +2024-11-21 23:56:35.127091: train_loss -0.7769 +2024-11-21 23:56:35.127326: val_loss -0.7648 +2024-11-21 23:56:35.127402: Pseudo dice [0.8469] +2024-11-21 23:56:35.127479: Epoch time: 18.94 s +2024-11-21 23:56:35.966839: +2024-11-21 23:56:35.967047: Epoch 2472 +2024-11-21 23:56:35.967154: Current learning rate: 0.00717 +2024-11-21 23:56:54.112487: train_loss -0.7715 +2024-11-21 23:56:54.112725: val_loss -0.7583 +2024-11-21 23:56:54.112807: Pseudo dice [0.8505] +2024-11-21 23:56:54.112882: Epoch time: 18.15 s +2024-11-21 23:56:54.952334: +2024-11-21 23:56:54.952658: Epoch 2473 +2024-11-21 23:56:54.952947: Current learning rate: 0.00717 +2024-11-21 23:57:14.162428: train_loss -0.7708 +2024-11-21 23:57:14.162690: val_loss -0.7627 +2024-11-21 23:57:14.162783: Pseudo dice [0.8511] +2024-11-21 23:57:14.162924: Epoch time: 19.21 s +2024-11-21 23:57:15.004122: +2024-11-21 23:57:15.004343: Epoch 2474 +2024-11-21 23:57:15.004452: Current learning rate: 0.00717 +2024-11-21 23:57:33.225513: train_loss -0.7569 +2024-11-21 23:57:33.225737: val_loss -0.772 +2024-11-21 23:57:33.225812: Pseudo dice [0.8392] +2024-11-21 23:57:33.225916: Epoch time: 18.22 s +2024-11-21 23:57:34.465334: +2024-11-21 23:57:34.465539: Epoch 2475 +2024-11-21 23:57:34.465656: Current learning rate: 0.00717 +2024-11-21 23:57:53.443876: train_loss -0.7615 +2024-11-21 23:57:53.444108: val_loss -0.7653 +2024-11-21 23:57:53.444191: Pseudo dice [0.8395] +2024-11-21 23:57:53.444267: Epoch time: 18.98 s +2024-11-21 23:57:54.280324: +2024-11-21 23:57:54.280542: Epoch 2476 +2024-11-21 23:57:54.280652: Current learning rate: 0.00717 +2024-11-21 23:58:11.840869: train_loss -0.7724 +2024-11-21 23:58:11.841124: val_loss -0.7512 +2024-11-21 23:58:11.841203: Pseudo dice [0.8355] +2024-11-21 23:58:11.841292: Epoch time: 17.56 s +2024-11-21 23:58:12.684207: +2024-11-21 23:58:12.684434: Epoch 2477 +2024-11-21 23:58:12.684543: Current learning rate: 0.00716 +2024-11-21 23:58:31.582433: train_loss -0.7659 +2024-11-21 23:58:31.582644: val_loss -0.7517 +2024-11-21 23:58:31.582720: Pseudo dice [0.8366] +2024-11-21 23:58:31.582794: Epoch time: 18.9 s +2024-11-21 23:58:32.422549: +2024-11-21 23:58:32.422864: Epoch 2478 +2024-11-21 23:58:32.422985: Current learning rate: 0.00716 +2024-11-21 23:58:50.673774: train_loss -0.7661 +2024-11-21 23:58:50.673985: val_loss -0.7667 +2024-11-21 23:58:50.674066: Pseudo dice [0.844] +2024-11-21 23:58:50.674141: Epoch time: 18.25 s +2024-11-21 23:58:51.514049: +2024-11-21 23:58:51.514264: Epoch 2479 +2024-11-21 23:58:51.514373: Current learning rate: 0.00716 +2024-11-21 23:59:10.495987: train_loss -0.7657 +2024-11-21 23:59:10.496305: val_loss -0.7863 +2024-11-21 23:59:10.496404: Pseudo dice [0.8485] +2024-11-21 23:59:10.496491: Epoch time: 18.98 s +2024-11-21 23:59:11.444111: +2024-11-21 23:59:11.444396: Epoch 2480 +2024-11-21 23:59:11.444508: Current learning rate: 0.00716 +2024-11-21 23:59:29.851732: train_loss -0.7572 +2024-11-21 23:59:29.851966: val_loss -0.7712 +2024-11-21 23:59:29.852051: Pseudo dice [0.8499] +2024-11-21 23:59:29.852132: Epoch time: 18.41 s +2024-11-21 23:59:30.689060: +2024-11-21 23:59:30.689294: Epoch 2481 +2024-11-21 23:59:30.689409: Current learning rate: 0.00716 +2024-11-21 23:59:49.530584: train_loss -0.7575 +2024-11-21 23:59:49.530793: val_loss -0.7849 +2024-11-21 23:59:49.530864: Pseudo dice [0.8481] +2024-11-21 23:59:49.530936: Epoch time: 18.84 s +2024-11-21 23:59:50.386894: +2024-11-21 23:59:50.387121: Epoch 2482 +2024-11-21 23:59:50.387230: Current learning rate: 0.00716 +2024-11-22 00:00:09.060605: train_loss -0.7783 +2024-11-22 00:00:09.060821: val_loss -0.7563 +2024-11-22 00:00:09.060894: Pseudo dice [0.841] +2024-11-22 00:00:09.060967: Epoch time: 18.67 s +2024-11-22 00:00:09.895146: +2024-11-22 00:00:09.895365: Epoch 2483 +2024-11-22 00:00:09.895474: Current learning rate: 0.00716 +2024-11-22 00:00:28.937938: train_loss -0.7684 +2024-11-22 00:00:28.938220: val_loss -0.7586 +2024-11-22 00:00:28.938298: Pseudo dice [0.8413] +2024-11-22 00:00:28.938384: Epoch time: 19.04 s +2024-11-22 00:00:29.850688: +2024-11-22 00:00:29.850902: Epoch 2484 +2024-11-22 00:00:29.851018: Current learning rate: 0.00716 +2024-11-22 00:00:48.914946: train_loss -0.7806 +2024-11-22 00:00:48.915169: val_loss -0.7713 +2024-11-22 00:00:48.915243: Pseudo dice [0.8478] +2024-11-22 00:00:48.915316: Epoch time: 19.07 s +2024-11-22 00:00:49.749503: +2024-11-22 00:00:49.749713: Epoch 2485 +2024-11-22 00:00:49.749821: Current learning rate: 0.00716 +2024-11-22 00:01:07.997159: train_loss -0.7742 +2024-11-22 00:01:07.997385: val_loss -0.7586 +2024-11-22 00:01:07.997460: Pseudo dice [0.8403] +2024-11-22 00:01:07.997535: Epoch time: 18.25 s +2024-11-22 00:01:08.992749: +2024-11-22 00:01:08.992957: Epoch 2486 +2024-11-22 00:01:08.993078: Current learning rate: 0.00715 +2024-11-22 00:01:28.164888: train_loss -0.7755 +2024-11-22 00:01:28.165103: val_loss -0.7464 +2024-11-22 00:01:28.165184: Pseudo dice [0.8294] +2024-11-22 00:01:28.165265: Epoch time: 19.17 s +2024-11-22 00:01:29.430656: +2024-11-22 00:01:29.430887: Epoch 2487 +2024-11-22 00:01:29.431005: Current learning rate: 0.00715 +2024-11-22 00:01:48.041937: train_loss -0.777 +2024-11-22 00:01:48.042210: val_loss -0.7151 +2024-11-22 00:01:48.042289: Pseudo dice [0.8274] +2024-11-22 00:01:48.042371: Epoch time: 18.61 s +2024-11-22 00:01:48.884231: +2024-11-22 00:01:48.884477: Epoch 2488 +2024-11-22 00:01:48.884598: Current learning rate: 0.00715 +2024-11-22 00:02:08.082855: train_loss -0.7706 +2024-11-22 00:02:08.083084: val_loss -0.7571 +2024-11-22 00:02:08.083160: Pseudo dice [0.8404] +2024-11-22 00:02:08.083235: Epoch time: 19.2 s +2024-11-22 00:02:09.105722: +2024-11-22 00:02:09.105952: Epoch 2489 +2024-11-22 00:02:09.106066: Current learning rate: 0.00715 +2024-11-22 00:02:27.788025: train_loss -0.7818 +2024-11-22 00:02:27.788241: val_loss -0.7718 +2024-11-22 00:02:27.788316: Pseudo dice [0.8403] +2024-11-22 00:02:27.788390: Epoch time: 18.68 s +2024-11-22 00:02:28.627491: +2024-11-22 00:02:28.627705: Epoch 2490 +2024-11-22 00:02:28.627816: Current learning rate: 0.00715 +2024-11-22 00:02:46.915536: train_loss -0.7851 +2024-11-22 00:02:46.915788: val_loss -0.7783 +2024-11-22 00:02:46.915866: Pseudo dice [0.8315] +2024-11-22 00:02:46.915948: Epoch time: 18.29 s +2024-11-22 00:02:47.756643: +2024-11-22 00:02:47.756845: Epoch 2491 +2024-11-22 00:02:47.756961: Current learning rate: 0.00715 +2024-11-22 00:03:05.904860: train_loss -0.7834 +2024-11-22 00:03:05.905132: val_loss -0.7818 +2024-11-22 00:03:05.905208: Pseudo dice [0.8419] +2024-11-22 00:03:05.905288: Epoch time: 18.15 s +2024-11-22 00:03:06.821653: +2024-11-22 00:03:06.821884: Epoch 2492 +2024-11-22 00:03:06.822002: Current learning rate: 0.00715 +2024-11-22 00:03:25.439975: train_loss -0.7745 +2024-11-22 00:03:25.442050: val_loss -0.7506 +2024-11-22 00:03:25.442191: Pseudo dice [0.8439] +2024-11-22 00:03:25.442269: Epoch time: 18.62 s +2024-11-22 00:03:26.285894: +2024-11-22 00:03:26.286111: Epoch 2493 +2024-11-22 00:03:26.286224: Current learning rate: 0.00715 +2024-11-22 00:03:44.495374: train_loss -0.7831 +2024-11-22 00:03:44.495588: val_loss -0.7499 +2024-11-22 00:03:44.495662: Pseudo dice [0.8381] +2024-11-22 00:03:44.495736: Epoch time: 18.21 s +2024-11-22 00:03:45.438048: +2024-11-22 00:03:45.438264: Epoch 2494 +2024-11-22 00:03:45.438373: Current learning rate: 0.00714 +2024-11-22 00:04:04.003585: train_loss -0.7803 +2024-11-22 00:04:04.003894: val_loss -0.7826 +2024-11-22 00:04:04.003970: Pseudo dice [0.8451] +2024-11-22 00:04:04.004061: Epoch time: 18.57 s +2024-11-22 00:04:04.850807: +2024-11-22 00:04:04.851039: Epoch 2495 +2024-11-22 00:04:04.851150: Current learning rate: 0.00714 +2024-11-22 00:04:23.824150: train_loss -0.7743 +2024-11-22 00:04:23.824446: val_loss -0.7788 +2024-11-22 00:04:23.824526: Pseudo dice [0.8581] +2024-11-22 00:04:23.824600: Epoch time: 18.97 s +2024-11-22 00:04:24.664225: +2024-11-22 00:04:24.664504: Epoch 2496 +2024-11-22 00:04:24.664612: Current learning rate: 0.00714 +2024-11-22 00:04:43.457436: train_loss -0.7767 +2024-11-22 00:04:43.457643: val_loss -0.7714 +2024-11-22 00:04:43.457715: Pseudo dice [0.8415] +2024-11-22 00:04:43.457788: Epoch time: 18.79 s +2024-11-22 00:04:44.295969: +2024-11-22 00:04:44.296163: Epoch 2497 +2024-11-22 00:04:44.296272: Current learning rate: 0.00714 +2024-11-22 00:05:01.990574: train_loss -0.7831 +2024-11-22 00:05:01.990795: val_loss -0.7754 +2024-11-22 00:05:01.990870: Pseudo dice [0.8462] +2024-11-22 00:05:01.990949: Epoch time: 17.7 s +2024-11-22 00:05:02.837321: +2024-11-22 00:05:02.837558: Epoch 2498 +2024-11-22 00:05:02.837708: Current learning rate: 0.00714 +2024-11-22 00:05:21.159519: train_loss -0.7767 +2024-11-22 00:05:21.159743: val_loss -0.7477 +2024-11-22 00:05:21.159817: Pseudo dice [0.8542] +2024-11-22 00:05:21.159902: Epoch time: 18.32 s +2024-11-22 00:05:22.387350: +2024-11-22 00:05:22.387657: Epoch 2499 +2024-11-22 00:05:22.387778: Current learning rate: 0.00714 +2024-11-22 00:05:41.417688: train_loss -0.7697 +2024-11-22 00:05:41.417944: val_loss -0.7573 +2024-11-22 00:05:41.418025: Pseudo dice [0.8351] +2024-11-22 00:05:41.418099: Epoch time: 19.03 s +2024-11-22 00:05:42.552791: +2024-11-22 00:05:42.553066: Epoch 2500 +2024-11-22 00:05:42.553180: Current learning rate: 0.00714 +2024-11-22 00:06:01.362825: train_loss -0.7674 +2024-11-22 00:06:01.363086: val_loss -0.7687 +2024-11-22 00:06:01.363168: Pseudo dice [0.8404] +2024-11-22 00:06:01.363258: Epoch time: 18.81 s +2024-11-22 00:06:02.218463: +2024-11-22 00:06:02.218678: Epoch 2501 +2024-11-22 00:06:02.218786: Current learning rate: 0.00714 +2024-11-22 00:06:20.560197: train_loss -0.7807 +2024-11-22 00:06:20.568283: val_loss -0.786 +2024-11-22 00:06:20.568378: Pseudo dice [0.8448] +2024-11-22 00:06:20.568460: Epoch time: 18.34 s +2024-11-22 00:06:21.409382: +2024-11-22 00:06:21.409613: Epoch 2502 +2024-11-22 00:06:21.409728: Current learning rate: 0.00714 +2024-11-22 00:06:39.833602: train_loss -0.7754 +2024-11-22 00:06:39.833852: val_loss -0.7744 +2024-11-22 00:06:39.833934: Pseudo dice [0.8384] +2024-11-22 00:06:39.834021: Epoch time: 18.43 s +2024-11-22 00:06:40.679780: +2024-11-22 00:06:40.680009: Epoch 2503 +2024-11-22 00:06:40.680116: Current learning rate: 0.00713 +2024-11-22 00:06:59.009118: train_loss -0.7804 +2024-11-22 00:06:59.009364: val_loss -0.7684 +2024-11-22 00:06:59.009448: Pseudo dice [0.8458] +2024-11-22 00:06:59.009530: Epoch time: 18.33 s +2024-11-22 00:06:59.848757: +2024-11-22 00:06:59.848966: Epoch 2504 +2024-11-22 00:06:59.849083: Current learning rate: 0.00713 +2024-11-22 00:07:18.658200: train_loss -0.7888 +2024-11-22 00:07:18.658449: val_loss -0.7646 +2024-11-22 00:07:18.658522: Pseudo dice [0.84] +2024-11-22 00:07:18.658599: Epoch time: 18.81 s +2024-11-22 00:07:19.673957: +2024-11-22 00:07:19.674150: Epoch 2505 +2024-11-22 00:07:19.674259: Current learning rate: 0.00713 +2024-11-22 00:07:37.977275: train_loss -0.7821 +2024-11-22 00:07:37.977497: val_loss -0.7624 +2024-11-22 00:07:37.977574: Pseudo dice [0.8499] +2024-11-22 00:07:37.977659: Epoch time: 18.3 s +2024-11-22 00:07:38.815934: +2024-11-22 00:07:38.816137: Epoch 2506 +2024-11-22 00:07:38.816245: Current learning rate: 0.00713 +2024-11-22 00:07:57.693538: train_loss -0.7761 +2024-11-22 00:07:57.693763: val_loss -0.7611 +2024-11-22 00:07:57.693835: Pseudo dice [0.8427] +2024-11-22 00:07:57.693906: Epoch time: 18.88 s +2024-11-22 00:07:58.569773: +2024-11-22 00:07:58.569968: Epoch 2507 +2024-11-22 00:07:58.570083: Current learning rate: 0.00713 +2024-11-22 00:08:16.284714: train_loss -0.7815 +2024-11-22 00:08:16.284953: val_loss -0.7535 +2024-11-22 00:08:16.287228: Pseudo dice [0.8412] +2024-11-22 00:08:16.287325: Epoch time: 17.72 s +2024-11-22 00:08:17.149062: +2024-11-22 00:08:17.149257: Epoch 2508 +2024-11-22 00:08:17.149364: Current learning rate: 0.00713 +2024-11-22 00:08:35.699021: train_loss -0.7801 +2024-11-22 00:08:35.699244: val_loss -0.7525 +2024-11-22 00:08:35.699320: Pseudo dice [0.8469] +2024-11-22 00:08:35.699395: Epoch time: 18.55 s +2024-11-22 00:08:36.569896: +2024-11-22 00:08:36.570099: Epoch 2509 +2024-11-22 00:08:36.570205: Current learning rate: 0.00713 +2024-11-22 00:08:54.497942: train_loss -0.7818 +2024-11-22 00:08:54.498166: val_loss -0.7629 +2024-11-22 00:08:54.498243: Pseudo dice [0.8401] +2024-11-22 00:08:54.498318: Epoch time: 17.93 s +2024-11-22 00:08:55.327956: +2024-11-22 00:08:55.328142: Epoch 2510 +2024-11-22 00:08:55.328247: Current learning rate: 0.00713 +2024-11-22 00:09:14.007984: train_loss -0.7842 +2024-11-22 00:09:14.008436: val_loss -0.7709 +2024-11-22 00:09:14.008555: Pseudo dice [0.8358] +2024-11-22 00:09:14.008631: Epoch time: 18.68 s +2024-11-22 00:09:14.846259: +2024-11-22 00:09:14.846501: Epoch 2511 +2024-11-22 00:09:14.846640: Current learning rate: 0.00712 +2024-11-22 00:09:33.094771: train_loss -0.7775 +2024-11-22 00:09:33.095009: val_loss -0.7814 +2024-11-22 00:09:33.095085: Pseudo dice [0.8533] +2024-11-22 00:09:33.095163: Epoch time: 18.25 s +2024-11-22 00:09:33.935289: +2024-11-22 00:09:33.935529: Epoch 2512 +2024-11-22 00:09:33.935644: Current learning rate: 0.00712 +2024-11-22 00:09:52.122887: train_loss -0.7766 +2024-11-22 00:09:52.123109: val_loss -0.7486 +2024-11-22 00:09:52.123192: Pseudo dice [0.8366] +2024-11-22 00:09:52.123266: Epoch time: 18.19 s +2024-11-22 00:09:52.971255: +2024-11-22 00:09:52.971472: Epoch 2513 +2024-11-22 00:09:52.971587: Current learning rate: 0.00712 +2024-11-22 00:10:12.512123: train_loss -0.7634 +2024-11-22 00:10:12.512353: val_loss -0.7506 +2024-11-22 00:10:12.512431: Pseudo dice [0.8037] +2024-11-22 00:10:12.512506: Epoch time: 19.54 s +2024-11-22 00:10:13.355339: +2024-11-22 00:10:13.355664: Epoch 2514 +2024-11-22 00:10:13.378443: Current learning rate: 0.00712 +2024-11-22 00:10:32.032712: train_loss -0.7659 +2024-11-22 00:10:32.033051: val_loss -0.7864 +2024-11-22 00:10:32.033134: Pseudo dice [0.8487] +2024-11-22 00:10:32.033218: Epoch time: 18.68 s +2024-11-22 00:10:32.899503: +2024-11-22 00:10:32.899731: Epoch 2515 +2024-11-22 00:10:32.899842: Current learning rate: 0.00712 +2024-11-22 00:10:50.491919: train_loss -0.7767 +2024-11-22 00:10:50.492138: val_loss -0.733 +2024-11-22 00:10:50.492215: Pseudo dice [0.8162] +2024-11-22 00:10:50.492292: Epoch time: 17.59 s +2024-11-22 00:10:51.337752: +2024-11-22 00:10:51.337957: Epoch 2516 +2024-11-22 00:10:51.338077: Current learning rate: 0.00712 +2024-11-22 00:11:10.179879: train_loss -0.771 +2024-11-22 00:11:10.180104: val_loss -0.7543 +2024-11-22 00:11:10.180180: Pseudo dice [0.8067] +2024-11-22 00:11:10.180255: Epoch time: 18.84 s +2024-11-22 00:11:11.020797: +2024-11-22 00:11:11.021010: Epoch 2517 +2024-11-22 00:11:11.021128: Current learning rate: 0.00712 +2024-11-22 00:11:28.079214: train_loss -0.7601 +2024-11-22 00:11:28.079435: val_loss -0.7625 +2024-11-22 00:11:28.079511: Pseudo dice [0.8442] +2024-11-22 00:11:28.079589: Epoch time: 17.06 s +2024-11-22 00:11:28.925184: +2024-11-22 00:11:28.925410: Epoch 2518 +2024-11-22 00:11:28.925531: Current learning rate: 0.00712 +2024-11-22 00:11:46.892372: train_loss -0.7667 +2024-11-22 00:11:46.894391: val_loss -0.7829 +2024-11-22 00:11:46.894487: Pseudo dice [0.8591] +2024-11-22 00:11:46.894572: Epoch time: 17.97 s +2024-11-22 00:11:47.782034: +2024-11-22 00:11:47.782269: Epoch 2519 +2024-11-22 00:11:47.782384: Current learning rate: 0.00712 +2024-11-22 00:12:06.250942: train_loss -0.782 +2024-11-22 00:12:06.251172: val_loss -0.7765 +2024-11-22 00:12:06.251266: Pseudo dice [0.8425] +2024-11-22 00:12:06.251350: Epoch time: 18.47 s +2024-11-22 00:12:07.198008: +2024-11-22 00:12:07.198247: Epoch 2520 +2024-11-22 00:12:07.198361: Current learning rate: 0.00711 +2024-11-22 00:12:25.440620: train_loss -0.7748 +2024-11-22 00:12:25.440869: val_loss -0.7603 +2024-11-22 00:12:25.440944: Pseudo dice [0.8224] +2024-11-22 00:12:25.441027: Epoch time: 18.24 s +2024-11-22 00:12:26.289057: +2024-11-22 00:12:26.289256: Epoch 2521 +2024-11-22 00:12:26.289392: Current learning rate: 0.00711 +2024-11-22 00:12:46.299415: train_loss -0.7696 +2024-11-22 00:12:46.299680: val_loss -0.7698 +2024-11-22 00:12:46.299760: Pseudo dice [0.8465] +2024-11-22 00:12:46.299846: Epoch time: 20.01 s +2024-11-22 00:12:47.600509: +2024-11-22 00:12:47.600748: Epoch 2522 +2024-11-22 00:12:47.600861: Current learning rate: 0.00711 +2024-11-22 00:13:05.567900: train_loss -0.7764 +2024-11-22 00:13:05.570292: val_loss -0.7528 +2024-11-22 00:13:05.570389: Pseudo dice [0.8362] +2024-11-22 00:13:05.570465: Epoch time: 17.97 s +2024-11-22 00:13:06.433100: +2024-11-22 00:13:06.433471: Epoch 2523 +2024-11-22 00:13:06.433583: Current learning rate: 0.00711 +2024-11-22 00:13:25.038932: train_loss -0.7805 +2024-11-22 00:13:25.039159: val_loss -0.743 +2024-11-22 00:13:25.039229: Pseudo dice [0.8249] +2024-11-22 00:13:25.041423: Epoch time: 18.61 s +2024-11-22 00:13:25.949349: +2024-11-22 00:13:25.949811: Epoch 2524 +2024-11-22 00:13:25.949924: Current learning rate: 0.00711 +2024-11-22 00:13:43.861461: train_loss -0.7738 +2024-11-22 00:13:43.861686: val_loss -0.7537 +2024-11-22 00:13:43.861763: Pseudo dice [0.8388] +2024-11-22 00:13:43.861846: Epoch time: 17.91 s +2024-11-22 00:13:44.734664: +2024-11-22 00:13:44.734898: Epoch 2525 +2024-11-22 00:13:44.735021: Current learning rate: 0.00711 +2024-11-22 00:14:02.936834: train_loss -0.7822 +2024-11-22 00:14:02.937076: val_loss -0.7627 +2024-11-22 00:14:02.937152: Pseudo dice [0.8375] +2024-11-22 00:14:02.937231: Epoch time: 18.2 s +2024-11-22 00:14:03.778667: +2024-11-22 00:14:03.778875: Epoch 2526 +2024-11-22 00:14:03.778988: Current learning rate: 0.00711 +2024-11-22 00:14:21.426948: train_loss -0.7734 +2024-11-22 00:14:21.427171: val_loss -0.7564 +2024-11-22 00:14:21.427245: Pseudo dice [0.8322] +2024-11-22 00:14:21.427321: Epoch time: 17.65 s +2024-11-22 00:14:22.266124: +2024-11-22 00:14:22.266324: Epoch 2527 +2024-11-22 00:14:22.266440: Current learning rate: 0.00711 +2024-11-22 00:14:40.536463: train_loss -0.7704 +2024-11-22 00:14:40.545453: val_loss -0.7858 +2024-11-22 00:14:40.545564: Pseudo dice [0.8442] +2024-11-22 00:14:40.545645: Epoch time: 18.27 s +2024-11-22 00:14:41.590861: +2024-11-22 00:14:41.591083: Epoch 2528 +2024-11-22 00:14:41.591191: Current learning rate: 0.0071 +2024-11-22 00:14:59.516684: train_loss -0.7841 +2024-11-22 00:14:59.516923: val_loss -0.7594 +2024-11-22 00:14:59.517020: Pseudo dice [0.8413] +2024-11-22 00:14:59.517107: Epoch time: 17.93 s +2024-11-22 00:15:00.369748: +2024-11-22 00:15:00.369961: Epoch 2529 +2024-11-22 00:15:00.370076: Current learning rate: 0.0071 +2024-11-22 00:15:19.194237: train_loss -0.7718 +2024-11-22 00:15:19.194454: val_loss -0.7679 +2024-11-22 00:15:19.194528: Pseudo dice [0.8573] +2024-11-22 00:15:19.194603: Epoch time: 18.83 s +2024-11-22 00:15:20.041873: +2024-11-22 00:15:20.042081: Epoch 2530 +2024-11-22 00:15:20.042190: Current learning rate: 0.0071 +2024-11-22 00:15:39.312275: train_loss -0.7823 +2024-11-22 00:15:39.312493: val_loss -0.7653 +2024-11-22 00:15:39.312576: Pseudo dice [0.8554] +2024-11-22 00:15:39.312655: Epoch time: 19.27 s +2024-11-22 00:15:40.150625: +2024-11-22 00:15:40.150847: Epoch 2531 +2024-11-22 00:15:40.150956: Current learning rate: 0.0071 +2024-11-22 00:15:57.903268: train_loss -0.7791 +2024-11-22 00:15:57.903485: val_loss -0.7466 +2024-11-22 00:15:57.903558: Pseudo dice [0.8377] +2024-11-22 00:15:57.903635: Epoch time: 17.75 s +2024-11-22 00:15:58.779251: +2024-11-22 00:15:58.779543: Epoch 2532 +2024-11-22 00:15:58.779666: Current learning rate: 0.0071 +2024-11-22 00:16:17.370223: train_loss -0.7918 +2024-11-22 00:16:17.370466: val_loss -0.7811 +2024-11-22 00:16:17.372657: Pseudo dice [0.8509] +2024-11-22 00:16:17.372895: Epoch time: 18.59 s +2024-11-22 00:16:18.237505: +2024-11-22 00:16:18.237966: Epoch 2533 +2024-11-22 00:16:18.238106: Current learning rate: 0.0071 +2024-11-22 00:16:37.489262: train_loss -0.7562 +2024-11-22 00:16:37.491198: val_loss -0.7498 +2024-11-22 00:16:37.491289: Pseudo dice [0.8153] +2024-11-22 00:16:37.491365: Epoch time: 19.25 s +2024-11-22 00:16:38.751411: +2024-11-22 00:16:38.751632: Epoch 2534 +2024-11-22 00:16:38.751749: Current learning rate: 0.0071 +2024-11-22 00:16:57.247134: train_loss -0.7663 +2024-11-22 00:16:57.247379: val_loss -0.7542 +2024-11-22 00:16:57.247457: Pseudo dice [0.8159] +2024-11-22 00:16:57.247534: Epoch time: 18.5 s +2024-11-22 00:16:58.095679: +2024-11-22 00:16:58.095901: Epoch 2535 +2024-11-22 00:16:58.096022: Current learning rate: 0.0071 +2024-11-22 00:17:16.798682: train_loss -0.7601 +2024-11-22 00:17:16.798920: val_loss -0.7755 +2024-11-22 00:17:16.798999: Pseudo dice [0.8528] +2024-11-22 00:17:16.799074: Epoch time: 18.7 s +2024-11-22 00:17:17.643209: +2024-11-22 00:17:17.643438: Epoch 2536 +2024-11-22 00:17:17.643546: Current learning rate: 0.0071 +2024-11-22 00:17:35.802070: train_loss -0.7649 +2024-11-22 00:17:35.802286: val_loss -0.7784 +2024-11-22 00:17:35.802362: Pseudo dice [0.8466] +2024-11-22 00:17:35.802450: Epoch time: 18.16 s +2024-11-22 00:17:36.645299: +2024-11-22 00:17:36.645508: Epoch 2537 +2024-11-22 00:17:36.645614: Current learning rate: 0.00709 +2024-11-22 00:17:55.004142: train_loss -0.7822 +2024-11-22 00:17:55.004417: val_loss -0.758 +2024-11-22 00:17:55.004503: Pseudo dice [0.8425] +2024-11-22 00:17:55.004581: Epoch time: 18.36 s +2024-11-22 00:17:55.853511: +2024-11-22 00:17:55.853731: Epoch 2538 +2024-11-22 00:17:55.853846: Current learning rate: 0.00709 +2024-11-22 00:18:13.783149: train_loss -0.7808 +2024-11-22 00:18:13.783374: val_loss -0.7938 +2024-11-22 00:18:13.783450: Pseudo dice [0.8412] +2024-11-22 00:18:13.783525: Epoch time: 17.93 s +2024-11-22 00:18:14.657226: +2024-11-22 00:18:14.657446: Epoch 2539 +2024-11-22 00:18:14.657561: Current learning rate: 0.00709 +2024-11-22 00:18:32.914972: train_loss -0.7726 +2024-11-22 00:18:32.915225: val_loss -0.7566 +2024-11-22 00:18:32.915303: Pseudo dice [0.8346] +2024-11-22 00:18:32.915383: Epoch time: 18.26 s +2024-11-22 00:18:33.760332: +2024-11-22 00:18:33.760557: Epoch 2540 +2024-11-22 00:18:33.760667: Current learning rate: 0.00709 +2024-11-22 00:18:52.275563: train_loss -0.7713 +2024-11-22 00:18:52.275771: val_loss -0.7656 +2024-11-22 00:18:52.278104: Pseudo dice [0.8297] +2024-11-22 00:18:52.278213: Epoch time: 18.52 s +2024-11-22 00:18:53.135700: +2024-11-22 00:18:53.135994: Epoch 2541 +2024-11-22 00:18:53.136104: Current learning rate: 0.00709 +2024-11-22 00:19:11.494821: train_loss -0.7794 +2024-11-22 00:19:11.497563: val_loss -0.7617 +2024-11-22 00:19:11.497685: Pseudo dice [0.844] +2024-11-22 00:19:11.497762: Epoch time: 18.36 s +2024-11-22 00:19:12.518580: +2024-11-22 00:19:12.518830: Epoch 2542 +2024-11-22 00:19:12.518947: Current learning rate: 0.00709 +2024-11-22 00:19:30.658310: train_loss -0.7649 +2024-11-22 00:19:30.658551: val_loss -0.7778 +2024-11-22 00:19:30.658630: Pseudo dice [0.8486] +2024-11-22 00:19:30.658718: Epoch time: 18.14 s +2024-11-22 00:19:31.503056: +2024-11-22 00:19:31.503258: Epoch 2543 +2024-11-22 00:19:31.503370: Current learning rate: 0.00709 +2024-11-22 00:19:49.849740: train_loss -0.7734 +2024-11-22 00:19:49.851411: val_loss -0.7719 +2024-11-22 00:19:49.851500: Pseudo dice [0.8479] +2024-11-22 00:19:49.851577: Epoch time: 18.35 s +2024-11-22 00:19:50.721955: +2024-11-22 00:19:50.722190: Epoch 2544 +2024-11-22 00:19:50.722306: Current learning rate: 0.00709 +2024-11-22 00:20:08.533736: train_loss -0.7709 +2024-11-22 00:20:08.533952: val_loss -0.7468 +2024-11-22 00:20:08.536244: Pseudo dice [0.8386] +2024-11-22 00:20:08.536349: Epoch time: 17.81 s +2024-11-22 00:20:09.440050: +2024-11-22 00:20:09.440260: Epoch 2545 +2024-11-22 00:20:09.440382: Current learning rate: 0.00708 +2024-11-22 00:20:27.161855: train_loss -0.7839 +2024-11-22 00:20:27.162137: val_loss -0.745 +2024-11-22 00:20:27.162219: Pseudo dice [0.8302] +2024-11-22 00:20:27.162307: Epoch time: 17.72 s +2024-11-22 00:20:28.429393: +2024-11-22 00:20:28.429611: Epoch 2546 +2024-11-22 00:20:28.429721: Current learning rate: 0.00708 +2024-11-22 00:20:47.011007: train_loss -0.7709 +2024-11-22 00:20:47.011231: val_loss -0.7412 +2024-11-22 00:20:47.011307: Pseudo dice [0.8375] +2024-11-22 00:20:47.011382: Epoch time: 18.58 s +2024-11-22 00:20:47.846900: +2024-11-22 00:20:47.847120: Epoch 2547 +2024-11-22 00:20:47.847225: Current learning rate: 0.00708 +2024-11-22 00:21:05.936203: train_loss -0.7808 +2024-11-22 00:21:05.936421: val_loss -0.7437 +2024-11-22 00:21:05.936498: Pseudo dice [0.8248] +2024-11-22 00:21:05.936574: Epoch time: 18.09 s +2024-11-22 00:21:06.943843: +2024-11-22 00:21:06.944076: Epoch 2548 +2024-11-22 00:21:06.944188: Current learning rate: 0.00708 +2024-11-22 00:21:25.310898: train_loss -0.7593 +2024-11-22 00:21:25.311118: val_loss -0.7251 +2024-11-22 00:21:25.311193: Pseudo dice [0.8181] +2024-11-22 00:21:25.311265: Epoch time: 18.37 s +2024-11-22 00:21:26.162582: +2024-11-22 00:21:26.162872: Epoch 2549 +2024-11-22 00:21:26.162999: Current learning rate: 0.00708 +2024-11-22 00:21:44.842196: train_loss -0.7621 +2024-11-22 00:21:44.842440: val_loss -0.7635 +2024-11-22 00:21:44.844667: Pseudo dice [0.8368] +2024-11-22 00:21:44.844791: Epoch time: 18.68 s +2024-11-22 00:21:46.237998: +2024-11-22 00:21:46.238230: Epoch 2550 +2024-11-22 00:21:46.238342: Current learning rate: 0.00708 +2024-11-22 00:22:04.888081: train_loss -0.7623 +2024-11-22 00:22:04.888345: val_loss -0.754 +2024-11-22 00:22:04.888421: Pseudo dice [0.8417] +2024-11-22 00:22:04.888496: Epoch time: 18.65 s +2024-11-22 00:22:05.736269: +2024-11-22 00:22:05.736505: Epoch 2551 +2024-11-22 00:22:05.736619: Current learning rate: 0.00708 +2024-11-22 00:22:24.467444: train_loss -0.7652 +2024-11-22 00:22:24.467662: val_loss -0.7313 +2024-11-22 00:22:24.467736: Pseudo dice [0.8294] +2024-11-22 00:22:24.467809: Epoch time: 18.73 s +2024-11-22 00:22:25.522305: +2024-11-22 00:22:25.522532: Epoch 2552 +2024-11-22 00:22:25.522646: Current learning rate: 0.00708 +2024-11-22 00:22:44.059429: train_loss -0.7708 +2024-11-22 00:22:44.059643: val_loss -0.7637 +2024-11-22 00:22:44.059723: Pseudo dice [0.8445] +2024-11-22 00:22:44.059803: Epoch time: 18.54 s +2024-11-22 00:22:44.903329: +2024-11-22 00:22:44.903571: Epoch 2553 +2024-11-22 00:22:44.903692: Current learning rate: 0.00708 +2024-11-22 00:23:02.556594: train_loss -0.7635 +2024-11-22 00:23:02.556841: val_loss -0.7491 +2024-11-22 00:23:02.556917: Pseudo dice [0.8476] +2024-11-22 00:23:02.557005: Epoch time: 17.65 s +2024-11-22 00:23:03.408683: +2024-11-22 00:23:03.408872: Epoch 2554 +2024-11-22 00:23:03.408983: Current learning rate: 0.00707 +2024-11-22 00:23:21.635629: train_loss -0.7607 +2024-11-22 00:23:21.635850: val_loss -0.7637 +2024-11-22 00:23:21.635926: Pseudo dice [0.8418] +2024-11-22 00:23:21.636011: Epoch time: 18.23 s +2024-11-22 00:23:22.474435: +2024-11-22 00:23:22.474650: Epoch 2555 +2024-11-22 00:23:22.474762: Current learning rate: 0.00707 +2024-11-22 00:23:41.609216: train_loss -0.7567 +2024-11-22 00:23:41.609437: val_loss -0.7653 +2024-11-22 00:23:41.609511: Pseudo dice [0.8204] +2024-11-22 00:23:41.609583: Epoch time: 19.14 s +2024-11-22 00:23:42.453980: +2024-11-22 00:23:42.454232: Epoch 2556 +2024-11-22 00:23:42.454342: Current learning rate: 0.00707 +2024-11-22 00:24:01.691470: train_loss -0.7681 +2024-11-22 00:24:01.691708: val_loss -0.747 +2024-11-22 00:24:01.691782: Pseudo dice [0.824] +2024-11-22 00:24:01.691863: Epoch time: 19.24 s +2024-11-22 00:24:02.555295: +2024-11-22 00:24:02.555509: Epoch 2557 +2024-11-22 00:24:02.555620: Current learning rate: 0.00707 +2024-11-22 00:24:21.303352: train_loss -0.7741 +2024-11-22 00:24:21.303567: val_loss -0.7541 +2024-11-22 00:24:21.303644: Pseudo dice [0.8177] +2024-11-22 00:24:21.303720: Epoch time: 18.75 s +2024-11-22 00:24:22.146424: +2024-11-22 00:24:22.146671: Epoch 2558 +2024-11-22 00:24:22.146781: Current learning rate: 0.00707 +2024-11-22 00:24:39.567339: train_loss -0.7807 +2024-11-22 00:24:39.567820: val_loss -0.7691 +2024-11-22 00:24:39.567923: Pseudo dice [0.8396] +2024-11-22 00:24:39.568005: Epoch time: 17.42 s +2024-11-22 00:24:40.464365: +2024-11-22 00:24:40.464607: Epoch 2559 +2024-11-22 00:24:40.464722: Current learning rate: 0.00707 +2024-11-22 00:24:58.463501: train_loss -0.7614 +2024-11-22 00:24:58.463739: val_loss -0.7766 +2024-11-22 00:24:58.463817: Pseudo dice [0.8599] +2024-11-22 00:24:58.463896: Epoch time: 18.0 s +2024-11-22 00:24:59.321201: +2024-11-22 00:24:59.321423: Epoch 2560 +2024-11-22 00:24:59.321537: Current learning rate: 0.00707 +2024-11-22 00:25:16.814854: train_loss -0.7712 +2024-11-22 00:25:16.815073: val_loss -0.7761 +2024-11-22 00:25:16.815151: Pseudo dice [0.8282] +2024-11-22 00:25:16.815228: Epoch time: 17.49 s +2024-11-22 00:25:17.657089: +2024-11-22 00:25:17.657323: Epoch 2561 +2024-11-22 00:25:17.657438: Current learning rate: 0.00707 +2024-11-22 00:25:36.486103: train_loss -0.7698 +2024-11-22 00:25:36.486313: val_loss -0.7582 +2024-11-22 00:25:36.486387: Pseudo dice [0.8466] +2024-11-22 00:25:36.486461: Epoch time: 18.83 s +2024-11-22 00:25:37.326483: +2024-11-22 00:25:37.326709: Epoch 2562 +2024-11-22 00:25:37.326822: Current learning rate: 0.00707 +2024-11-22 00:25:54.715891: train_loss -0.7801 +2024-11-22 00:25:54.716224: val_loss -0.7435 +2024-11-22 00:25:54.716310: Pseudo dice [0.8343] +2024-11-22 00:25:54.716393: Epoch time: 17.39 s +2024-11-22 00:25:55.564709: +2024-11-22 00:25:55.564908: Epoch 2563 +2024-11-22 00:25:55.565027: Current learning rate: 0.00706 +2024-11-22 00:26:14.638923: train_loss -0.78 +2024-11-22 00:26:14.644370: val_loss -0.7885 +2024-11-22 00:26:14.644495: Pseudo dice [0.8548] +2024-11-22 00:26:14.644584: Epoch time: 19.08 s +2024-11-22 00:26:15.525305: +2024-11-22 00:26:15.525496: Epoch 2564 +2024-11-22 00:26:15.525603: Current learning rate: 0.00706 +2024-11-22 00:26:34.436449: train_loss -0.7859 +2024-11-22 00:26:34.436655: val_loss -0.7614 +2024-11-22 00:26:34.436728: Pseudo dice [0.8371] +2024-11-22 00:26:34.436800: Epoch time: 18.91 s +2024-11-22 00:26:35.293947: +2024-11-22 00:26:35.294199: Epoch 2565 +2024-11-22 00:26:35.294344: Current learning rate: 0.00706 +2024-11-22 00:26:53.969934: train_loss -0.7818 +2024-11-22 00:26:53.970155: val_loss -0.7651 +2024-11-22 00:26:53.970228: Pseudo dice [0.8572] +2024-11-22 00:26:53.970302: Epoch time: 18.68 s +2024-11-22 00:26:54.816961: +2024-11-22 00:26:54.817184: Epoch 2566 +2024-11-22 00:26:54.817302: Current learning rate: 0.00706 +2024-11-22 00:27:13.217313: train_loss -0.7743 +2024-11-22 00:27:13.217658: val_loss -0.7817 +2024-11-22 00:27:13.217744: Pseudo dice [0.8343] +2024-11-22 00:27:13.217826: Epoch time: 18.4 s +2024-11-22 00:27:14.072461: +2024-11-22 00:27:14.072735: Epoch 2567 +2024-11-22 00:27:14.072850: Current learning rate: 0.00706 +2024-11-22 00:27:34.126111: train_loss -0.7794 +2024-11-22 00:27:34.126332: val_loss -0.7602 +2024-11-22 00:27:34.126415: Pseudo dice [0.8608] +2024-11-22 00:27:34.126492: Epoch time: 20.05 s +2024-11-22 00:27:34.981119: +2024-11-22 00:27:34.981322: Epoch 2568 +2024-11-22 00:27:34.981430: Current learning rate: 0.00706 +2024-11-22 00:27:53.472407: train_loss -0.769 +2024-11-22 00:27:53.472612: val_loss -0.7677 +2024-11-22 00:27:53.472685: Pseudo dice [0.8361] +2024-11-22 00:27:53.472763: Epoch time: 18.49 s +2024-11-22 00:27:54.705765: +2024-11-22 00:27:54.705983: Epoch 2569 +2024-11-22 00:27:54.706098: Current learning rate: 0.00706 +2024-11-22 00:28:12.172114: train_loss -0.7838 +2024-11-22 00:28:12.172375: val_loss -0.7881 +2024-11-22 00:28:12.172456: Pseudo dice [0.8501] +2024-11-22 00:28:12.172539: Epoch time: 17.47 s +2024-11-22 00:28:13.017102: +2024-11-22 00:28:13.017308: Epoch 2570 +2024-11-22 00:28:13.017414: Current learning rate: 0.00706 +2024-11-22 00:28:32.393974: train_loss -0.7794 +2024-11-22 00:28:32.394197: val_loss -0.7397 +2024-11-22 00:28:32.394283: Pseudo dice [0.8244] +2024-11-22 00:28:32.394361: Epoch time: 19.38 s +2024-11-22 00:28:33.283171: +2024-11-22 00:28:33.283396: Epoch 2571 +2024-11-22 00:28:33.283514: Current learning rate: 0.00705 +2024-11-22 00:28:51.844856: train_loss -0.7654 +2024-11-22 00:28:51.845353: val_loss -0.749 +2024-11-22 00:28:51.845439: Pseudo dice [0.8406] +2024-11-22 00:28:51.845513: Epoch time: 18.56 s +2024-11-22 00:28:52.707704: +2024-11-22 00:28:52.707941: Epoch 2572 +2024-11-22 00:28:52.708068: Current learning rate: 0.00705 +2024-11-22 00:29:11.049711: train_loss -0.771 +2024-11-22 00:29:11.049947: val_loss -0.7769 +2024-11-22 00:29:11.050031: Pseudo dice [0.8486] +2024-11-22 00:29:11.050114: Epoch time: 18.34 s +2024-11-22 00:29:12.049298: +2024-11-22 00:29:12.049542: Epoch 2573 +2024-11-22 00:29:12.049668: Current learning rate: 0.00705 +2024-11-22 00:29:29.861423: train_loss -0.7804 +2024-11-22 00:29:29.861645: val_loss -0.7378 +2024-11-22 00:29:29.861722: Pseudo dice [0.8245] +2024-11-22 00:29:29.861798: Epoch time: 17.81 s +2024-11-22 00:29:30.725845: +2024-11-22 00:29:30.726069: Epoch 2574 +2024-11-22 00:29:30.726181: Current learning rate: 0.00705 +2024-11-22 00:29:49.004613: train_loss -0.7764 +2024-11-22 00:29:49.004836: val_loss -0.7353 +2024-11-22 00:29:49.009195: Pseudo dice [0.8465] +2024-11-22 00:29:49.009297: Epoch time: 18.28 s +2024-11-22 00:29:49.887159: +2024-11-22 00:29:49.887418: Epoch 2575 +2024-11-22 00:29:49.887528: Current learning rate: 0.00705 +2024-11-22 00:30:08.264541: train_loss -0.7764 +2024-11-22 00:30:08.264758: val_loss -0.7684 +2024-11-22 00:30:08.264830: Pseudo dice [0.8518] +2024-11-22 00:30:08.264904: Epoch time: 18.38 s +2024-11-22 00:30:09.107880: +2024-11-22 00:30:09.108107: Epoch 2576 +2024-11-22 00:30:09.108237: Current learning rate: 0.00705 +2024-11-22 00:30:28.504643: train_loss -0.7686 +2024-11-22 00:30:28.504899: val_loss -0.7968 +2024-11-22 00:30:28.504972: Pseudo dice [0.8537] +2024-11-22 00:30:28.505408: Epoch time: 19.4 s +2024-11-22 00:30:29.353033: +2024-11-22 00:30:29.353232: Epoch 2577 +2024-11-22 00:30:29.353340: Current learning rate: 0.00705 +2024-11-22 00:30:47.406970: train_loss -0.7753 +2024-11-22 00:30:47.407267: val_loss -0.777 +2024-11-22 00:30:47.410429: Pseudo dice [0.8362] +2024-11-22 00:30:47.410570: Epoch time: 18.05 s +2024-11-22 00:30:48.249980: +2024-11-22 00:30:48.250203: Epoch 2578 +2024-11-22 00:30:48.250314: Current learning rate: 0.00705 +2024-11-22 00:31:05.977740: train_loss -0.7831 +2024-11-22 00:31:05.977957: val_loss -0.7567 +2024-11-22 00:31:05.978043: Pseudo dice [0.836] +2024-11-22 00:31:05.978120: Epoch time: 17.73 s +2024-11-22 00:31:06.825673: +2024-11-22 00:31:06.825904: Epoch 2579 +2024-11-22 00:31:06.826014: Current learning rate: 0.00705 +2024-11-22 00:31:25.341778: train_loss -0.7658 +2024-11-22 00:31:25.342011: val_loss -0.7704 +2024-11-22 00:31:25.342089: Pseudo dice [0.8319] +2024-11-22 00:31:25.342165: Epoch time: 18.52 s +2024-11-22 00:31:26.187644: +2024-11-22 00:31:26.187858: Epoch 2580 +2024-11-22 00:31:26.187968: Current learning rate: 0.00704 +2024-11-22 00:31:44.338908: train_loss -0.7682 +2024-11-22 00:31:44.339466: val_loss -0.7576 +2024-11-22 00:31:44.339571: Pseudo dice [0.8385] +2024-11-22 00:31:44.339653: Epoch time: 18.15 s +2024-11-22 00:31:45.189771: +2024-11-22 00:31:45.190001: Epoch 2581 +2024-11-22 00:31:45.190112: Current learning rate: 0.00704 +2024-11-22 00:32:04.529459: train_loss -0.7707 +2024-11-22 00:32:04.529687: val_loss -0.7635 +2024-11-22 00:32:04.529763: Pseudo dice [0.8431] +2024-11-22 00:32:04.532043: Epoch time: 19.34 s +2024-11-22 00:32:05.424853: +2024-11-22 00:32:05.425097: Epoch 2582 +2024-11-22 00:32:05.425213: Current learning rate: 0.00704 +2024-11-22 00:32:24.554316: train_loss -0.7768 +2024-11-22 00:32:24.554535: val_loss -0.7579 +2024-11-22 00:32:24.554611: Pseudo dice [0.8308] +2024-11-22 00:32:24.554695: Epoch time: 19.13 s +2024-11-22 00:32:25.397026: +2024-11-22 00:32:25.397243: Epoch 2583 +2024-11-22 00:32:25.397352: Current learning rate: 0.00704 +2024-11-22 00:32:44.643200: train_loss -0.7774 +2024-11-22 00:32:44.643444: val_loss -0.7668 +2024-11-22 00:32:44.643530: Pseudo dice [0.8187] +2024-11-22 00:32:44.643619: Epoch time: 19.25 s +2024-11-22 00:32:45.594787: +2024-11-22 00:32:45.594996: Epoch 2584 +2024-11-22 00:32:45.595105: Current learning rate: 0.00704 +2024-11-22 00:33:03.437886: train_loss -0.7746 +2024-11-22 00:33:03.438122: val_loss -0.7523 +2024-11-22 00:33:03.438198: Pseudo dice [0.8313] +2024-11-22 00:33:03.438280: Epoch time: 17.84 s +2024-11-22 00:33:04.282461: +2024-11-22 00:33:04.282694: Epoch 2585 +2024-11-22 00:33:04.282816: Current learning rate: 0.00704 +2024-11-22 00:33:22.034791: train_loss -0.768 +2024-11-22 00:33:22.035018: val_loss -0.7701 +2024-11-22 00:33:22.035095: Pseudo dice [0.8467] +2024-11-22 00:33:22.035171: Epoch time: 17.75 s +2024-11-22 00:33:23.061229: +2024-11-22 00:33:23.061472: Epoch 2586 +2024-11-22 00:33:23.061585: Current learning rate: 0.00704 +2024-11-22 00:33:39.965764: train_loss -0.7661 +2024-11-22 00:33:39.966010: val_loss -0.7717 +2024-11-22 00:33:39.966086: Pseudo dice [0.8281] +2024-11-22 00:33:39.966167: Epoch time: 16.91 s +2024-11-22 00:33:40.895607: +2024-11-22 00:33:40.895831: Epoch 2587 +2024-11-22 00:33:40.895942: Current learning rate: 0.00704 +2024-11-22 00:33:58.361693: train_loss -0.7784 +2024-11-22 00:33:58.361946: val_loss -0.7526 +2024-11-22 00:33:58.362116: Pseudo dice [0.8333] +2024-11-22 00:33:58.362197: Epoch time: 17.47 s +2024-11-22 00:33:59.205479: +2024-11-22 00:33:59.205725: Epoch 2588 +2024-11-22 00:33:59.205848: Current learning rate: 0.00703 +2024-11-22 00:34:17.170886: train_loss -0.7818 +2024-11-22 00:34:17.171100: val_loss -0.7818 +2024-11-22 00:34:17.171175: Pseudo dice [0.8478] +2024-11-22 00:34:17.171247: Epoch time: 17.97 s +2024-11-22 00:34:18.010656: +2024-11-22 00:34:18.010859: Epoch 2589 +2024-11-22 00:34:18.010968: Current learning rate: 0.00703 +2024-11-22 00:34:36.776932: train_loss -0.7857 +2024-11-22 00:34:36.777158: val_loss -0.7608 +2024-11-22 00:34:36.777231: Pseudo dice [0.8464] +2024-11-22 00:34:36.777361: Epoch time: 18.77 s +2024-11-22 00:34:37.624950: +2024-11-22 00:34:37.625166: Epoch 2590 +2024-11-22 00:34:37.625274: Current learning rate: 0.00703 +2024-11-22 00:34:55.505249: train_loss -0.7667 +2024-11-22 00:34:55.505509: val_loss -0.7685 +2024-11-22 00:34:55.505585: Pseudo dice [0.8352] +2024-11-22 00:34:55.505668: Epoch time: 17.88 s +2024-11-22 00:34:56.418164: +2024-11-22 00:34:56.418366: Epoch 2591 +2024-11-22 00:34:56.418481: Current learning rate: 0.00703 +2024-11-22 00:35:15.249012: train_loss -0.7767 +2024-11-22 00:35:15.250057: val_loss -0.7708 +2024-11-22 00:35:15.250134: Pseudo dice [0.8453] +2024-11-22 00:35:15.250210: Epoch time: 18.83 s +2024-11-22 00:35:16.492234: +2024-11-22 00:35:16.492477: Epoch 2592 +2024-11-22 00:35:16.492593: Current learning rate: 0.00703 +2024-11-22 00:35:35.391900: train_loss -0.7704 +2024-11-22 00:35:35.394321: val_loss -0.7501 +2024-11-22 00:35:35.394463: Pseudo dice [0.8277] +2024-11-22 00:35:35.394543: Epoch time: 18.9 s +2024-11-22 00:35:36.300191: +2024-11-22 00:35:36.300414: Epoch 2593 +2024-11-22 00:35:36.300526: Current learning rate: 0.00703 +2024-11-22 00:35:54.676047: train_loss -0.7717 +2024-11-22 00:35:54.676294: val_loss -0.7686 +2024-11-22 00:35:54.676399: Pseudo dice [0.8406] +2024-11-22 00:35:54.676482: Epoch time: 18.38 s +2024-11-22 00:35:55.525421: +2024-11-22 00:35:55.525645: Epoch 2594 +2024-11-22 00:35:55.525753: Current learning rate: 0.00703 +2024-11-22 00:36:14.003471: train_loss -0.7721 +2024-11-22 00:36:14.003684: val_loss -0.7664 +2024-11-22 00:36:14.003760: Pseudo dice [0.8375] +2024-11-22 00:36:14.003834: Epoch time: 18.48 s +2024-11-22 00:36:14.875748: +2024-11-22 00:36:14.875940: Epoch 2595 +2024-11-22 00:36:14.876045: Current learning rate: 0.00703 +2024-11-22 00:36:33.413051: train_loss -0.7568 +2024-11-22 00:36:33.413275: val_loss -0.7412 +2024-11-22 00:36:33.415539: Pseudo dice [0.8266] +2024-11-22 00:36:33.415627: Epoch time: 18.54 s +2024-11-22 00:36:34.277230: +2024-11-22 00:36:34.277433: Epoch 2596 +2024-11-22 00:36:34.277543: Current learning rate: 0.00703 +2024-11-22 00:36:52.262530: train_loss -0.7615 +2024-11-22 00:36:52.264572: val_loss -0.7716 +2024-11-22 00:36:52.264734: Pseudo dice [0.8488] +2024-11-22 00:36:52.264816: Epoch time: 17.99 s +2024-11-22 00:36:53.149997: +2024-11-22 00:36:53.150227: Epoch 2597 +2024-11-22 00:36:53.150343: Current learning rate: 0.00702 +2024-11-22 00:37:11.625957: train_loss -0.7623 +2024-11-22 00:37:11.626229: val_loss -0.7667 +2024-11-22 00:37:11.626306: Pseudo dice [0.8497] +2024-11-22 00:37:11.626385: Epoch time: 18.48 s +2024-11-22 00:37:12.476679: +2024-11-22 00:37:12.476899: Epoch 2598 +2024-11-22 00:37:12.477025: Current learning rate: 0.00702 +2024-11-22 00:37:32.052450: train_loss -0.78 +2024-11-22 00:37:32.052757: val_loss -0.7639 +2024-11-22 00:37:32.052837: Pseudo dice [0.8357] +2024-11-22 00:37:32.052916: Epoch time: 19.58 s +2024-11-22 00:37:32.931257: +2024-11-22 00:37:32.931467: Epoch 2599 +2024-11-22 00:37:32.931576: Current learning rate: 0.00702 +2024-11-22 00:37:51.917943: train_loss -0.7709 +2024-11-22 00:37:51.918181: val_loss -0.7792 +2024-11-22 00:37:51.918256: Pseudo dice [0.84] +2024-11-22 00:37:51.918350: Epoch time: 18.99 s +2024-11-22 00:37:52.989617: +2024-11-22 00:37:52.989849: Epoch 2600 +2024-11-22 00:37:52.989960: Current learning rate: 0.00702 +2024-11-22 00:38:11.996765: train_loss -0.7843 +2024-11-22 00:38:11.997060: val_loss -0.7736 +2024-11-22 00:38:11.997137: Pseudo dice [0.8517] +2024-11-22 00:38:11.997215: Epoch time: 19.01 s +2024-11-22 00:38:12.847995: +2024-11-22 00:38:12.848217: Epoch 2601 +2024-11-22 00:38:12.848339: Current learning rate: 0.00702 +2024-11-22 00:38:32.069348: train_loss -0.7788 +2024-11-22 00:38:32.069563: val_loss -0.7452 +2024-11-22 00:38:32.069656: Pseudo dice [0.8273] +2024-11-22 00:38:32.069740: Epoch time: 19.22 s +2024-11-22 00:38:32.908753: +2024-11-22 00:38:32.908951: Epoch 2602 +2024-11-22 00:38:32.909065: Current learning rate: 0.00702 +2024-11-22 00:38:51.828090: train_loss -0.7855 +2024-11-22 00:38:51.828296: val_loss -0.7699 +2024-11-22 00:38:51.828370: Pseudo dice [0.8388] +2024-11-22 00:38:51.828603: Epoch time: 18.92 s +2024-11-22 00:38:52.670908: +2024-11-22 00:38:52.671918: Epoch 2603 +2024-11-22 00:38:52.672056: Current learning rate: 0.00702 +2024-11-22 00:39:11.653740: train_loss -0.7766 +2024-11-22 00:39:11.654308: val_loss -0.772 +2024-11-22 00:39:11.654467: Pseudo dice [0.849] +2024-11-22 00:39:11.654554: Epoch time: 18.98 s +2024-11-22 00:39:12.503229: +2024-11-22 00:39:12.503445: Epoch 2604 +2024-11-22 00:39:12.503552: Current learning rate: 0.00702 +2024-11-22 00:39:31.819652: train_loss -0.7714 +2024-11-22 00:39:31.819896: val_loss -0.7566 +2024-11-22 00:39:31.819973: Pseudo dice [0.8376] +2024-11-22 00:39:31.820052: Epoch time: 19.32 s +2024-11-22 00:39:32.663354: +2024-11-22 00:39:32.663573: Epoch 2605 +2024-11-22 00:39:32.663683: Current learning rate: 0.00701 +2024-11-22 00:39:51.245590: train_loss -0.7762 +2024-11-22 00:39:51.245811: val_loss -0.7518 +2024-11-22 00:39:51.245919: Pseudo dice [0.856] +2024-11-22 00:39:51.246006: Epoch time: 18.58 s +2024-11-22 00:39:52.091663: +2024-11-22 00:39:52.091888: Epoch 2606 +2024-11-22 00:39:52.092009: Current learning rate: 0.00701 +2024-11-22 00:40:10.999303: train_loss -0.7836 +2024-11-22 00:40:10.999621: val_loss -0.7482 +2024-11-22 00:40:10.999704: Pseudo dice [0.8288] +2024-11-22 00:40:10.999787: Epoch time: 18.91 s +2024-11-22 00:40:11.858613: +2024-11-22 00:40:11.858821: Epoch 2607 +2024-11-22 00:40:11.858930: Current learning rate: 0.00701 +2024-11-22 00:40:29.585002: train_loss -0.7802 +2024-11-22 00:40:29.585259: val_loss -0.768 +2024-11-22 00:40:29.585338: Pseudo dice [0.8333] +2024-11-22 00:40:29.585411: Epoch time: 17.73 s +2024-11-22 00:40:30.435388: +2024-11-22 00:40:30.435609: Epoch 2608 +2024-11-22 00:40:30.435719: Current learning rate: 0.00701 +2024-11-22 00:40:49.329504: train_loss -0.7706 +2024-11-22 00:40:49.329717: val_loss -0.7592 +2024-11-22 00:40:49.329793: Pseudo dice [0.8384] +2024-11-22 00:40:49.329865: Epoch time: 18.89 s +2024-11-22 00:40:50.315556: +2024-11-22 00:40:50.315788: Epoch 2609 +2024-11-22 00:40:50.315897: Current learning rate: 0.00701 +2024-11-22 00:41:10.034528: train_loss -0.7763 +2024-11-22 00:41:10.034754: val_loss -0.7792 +2024-11-22 00:41:10.034938: Pseudo dice [0.8551] +2024-11-22 00:41:10.035020: Epoch time: 19.72 s +2024-11-22 00:41:10.883754: +2024-11-22 00:41:10.883964: Epoch 2610 +2024-11-22 00:41:10.884075: Current learning rate: 0.00701 +2024-11-22 00:41:28.182340: train_loss -0.782 +2024-11-22 00:41:28.182569: val_loss -0.7859 +2024-11-22 00:41:28.182649: Pseudo dice [0.8493] +2024-11-22 00:41:28.182731: Epoch time: 17.3 s +2024-11-22 00:41:29.027438: +2024-11-22 00:41:29.027657: Epoch 2611 +2024-11-22 00:41:29.027770: Current learning rate: 0.00701 +2024-11-22 00:41:48.572021: train_loss -0.7821 +2024-11-22 00:41:48.572243: val_loss -0.7452 +2024-11-22 00:41:48.572316: Pseudo dice [0.8471] +2024-11-22 00:41:48.572394: Epoch time: 19.55 s +2024-11-22 00:41:49.417845: +2024-11-22 00:41:49.418058: Epoch 2612 +2024-11-22 00:41:49.418174: Current learning rate: 0.00701 +2024-11-22 00:42:07.351941: train_loss -0.7749 +2024-11-22 00:42:07.354843: val_loss -0.7613 +2024-11-22 00:42:07.354957: Pseudo dice [0.8361] +2024-11-22 00:42:07.355038: Epoch time: 17.93 s +2024-11-22 00:42:08.210228: +2024-11-22 00:42:08.210438: Epoch 2613 +2024-11-22 00:42:08.210551: Current learning rate: 0.00701 +2024-11-22 00:42:26.178435: train_loss -0.7616 +2024-11-22 00:42:26.178657: val_loss -0.7701 +2024-11-22 00:42:26.178733: Pseudo dice [0.8435] +2024-11-22 00:42:26.178809: Epoch time: 17.97 s +2024-11-22 00:42:27.145712: +2024-11-22 00:42:27.145932: Epoch 2614 +2024-11-22 00:42:27.146042: Current learning rate: 0.007 +2024-11-22 00:42:45.118742: train_loss -0.773 +2024-11-22 00:42:45.119041: val_loss -0.7617 +2024-11-22 00:42:45.119121: Pseudo dice [0.848] +2024-11-22 00:42:45.119202: Epoch time: 17.97 s +2024-11-22 00:42:46.374947: +2024-11-22 00:42:46.375187: Epoch 2615 +2024-11-22 00:42:46.375296: Current learning rate: 0.007 +2024-11-22 00:43:03.823423: train_loss -0.7666 +2024-11-22 00:43:03.823660: val_loss -0.7433 +2024-11-22 00:43:03.823821: Pseudo dice [0.8427] +2024-11-22 00:43:03.838471: Epoch time: 17.45 s +2024-11-22 00:43:04.683846: +2024-11-22 00:43:04.684053: Epoch 2616 +2024-11-22 00:43:04.684162: Current learning rate: 0.007 +2024-11-22 00:43:23.628850: train_loss -0.7734 +2024-11-22 00:43:23.631374: val_loss -0.758 +2024-11-22 00:43:23.631530: Pseudo dice [0.8375] +2024-11-22 00:43:23.631608: Epoch time: 18.95 s +2024-11-22 00:43:24.502750: +2024-11-22 00:43:24.502952: Epoch 2617 +2024-11-22 00:43:24.503063: Current learning rate: 0.007 +2024-11-22 00:43:43.249386: train_loss -0.776 +2024-11-22 00:43:43.249648: val_loss -0.7501 +2024-11-22 00:43:43.249733: Pseudo dice [0.8349] +2024-11-22 00:43:43.249817: Epoch time: 18.75 s +2024-11-22 00:43:44.099814: +2024-11-22 00:43:44.100016: Epoch 2618 +2024-11-22 00:43:44.100123: Current learning rate: 0.007 +2024-11-22 00:44:02.217196: train_loss -0.7881 +2024-11-22 00:44:02.217410: val_loss -0.7338 +2024-11-22 00:44:02.217483: Pseudo dice [0.825] +2024-11-22 00:44:02.217556: Epoch time: 18.12 s +2024-11-22 00:44:03.065511: +2024-11-22 00:44:03.065727: Epoch 2619 +2024-11-22 00:44:03.065837: Current learning rate: 0.007 +2024-11-22 00:44:21.319014: train_loss -0.7807 +2024-11-22 00:44:21.319231: val_loss -0.7676 +2024-11-22 00:44:21.319306: Pseudo dice [0.8563] +2024-11-22 00:44:21.319382: Epoch time: 18.25 s +2024-11-22 00:44:22.172697: +2024-11-22 00:44:22.172906: Epoch 2620 +2024-11-22 00:44:22.173023: Current learning rate: 0.007 +2024-11-22 00:44:40.948828: train_loss -0.7801 +2024-11-22 00:44:40.951250: val_loss -0.7449 +2024-11-22 00:44:40.951339: Pseudo dice [0.8284] +2024-11-22 00:44:40.951413: Epoch time: 18.78 s +2024-11-22 00:44:41.986801: +2024-11-22 00:44:41.987014: Epoch 2621 +2024-11-22 00:44:41.987129: Current learning rate: 0.007 +2024-11-22 00:45:00.851964: train_loss -0.7736 +2024-11-22 00:45:00.857396: val_loss -0.7668 +2024-11-22 00:45:00.857545: Pseudo dice [0.8366] +2024-11-22 00:45:00.857637: Epoch time: 18.87 s +2024-11-22 00:45:01.744333: +2024-11-22 00:45:01.744560: Epoch 2622 +2024-11-22 00:45:01.744671: Current learning rate: 0.00699 +2024-11-22 00:45:19.647657: train_loss -0.7825 +2024-11-22 00:45:19.647871: val_loss -0.7581 +2024-11-22 00:45:19.647949: Pseudo dice [0.8427] +2024-11-22 00:45:19.648029: Epoch time: 17.9 s +2024-11-22 00:45:20.492081: +2024-11-22 00:45:20.492283: Epoch 2623 +2024-11-22 00:45:20.492394: Current learning rate: 0.00699 +2024-11-22 00:45:38.855471: train_loss -0.7793 +2024-11-22 00:45:38.855723: val_loss -0.78 +2024-11-22 00:45:38.855798: Pseudo dice [0.8288] +2024-11-22 00:45:38.855870: Epoch time: 18.36 s +2024-11-22 00:45:39.699877: +2024-11-22 00:45:39.700109: Epoch 2624 +2024-11-22 00:45:39.700215: Current learning rate: 0.00699 +2024-11-22 00:45:59.252129: train_loss -0.7773 +2024-11-22 00:45:59.252348: val_loss -0.7336 +2024-11-22 00:45:59.252422: Pseudo dice [0.8345] +2024-11-22 00:45:59.252498: Epoch time: 19.55 s +2024-11-22 00:46:00.097578: +2024-11-22 00:46:00.097979: Epoch 2625 +2024-11-22 00:46:00.098116: Current learning rate: 0.00699 +2024-11-22 00:46:18.836399: train_loss -0.7772 +2024-11-22 00:46:18.836669: val_loss -0.755 +2024-11-22 00:46:18.836750: Pseudo dice [0.8438] +2024-11-22 00:46:18.836881: Epoch time: 18.74 s +2024-11-22 00:46:19.689032: +2024-11-22 00:46:19.689242: Epoch 2626 +2024-11-22 00:46:19.689352: Current learning rate: 0.00699 +2024-11-22 00:46:38.150795: train_loss -0.7811 +2024-11-22 00:46:38.151024: val_loss -0.7699 +2024-11-22 00:46:38.153335: Pseudo dice [0.8435] +2024-11-22 00:46:38.153489: Epoch time: 18.46 s +2024-11-22 00:46:39.564176: +2024-11-22 00:46:39.564405: Epoch 2627 +2024-11-22 00:46:39.564519: Current learning rate: 0.00699 +2024-11-22 00:46:57.326621: train_loss -0.7712 +2024-11-22 00:46:57.326862: val_loss -0.7522 +2024-11-22 00:46:57.326943: Pseudo dice [0.8379] +2024-11-22 00:46:57.327027: Epoch time: 17.76 s +2024-11-22 00:46:58.263915: +2024-11-22 00:46:58.264167: Epoch 2628 +2024-11-22 00:46:58.264327: Current learning rate: 0.00699 +2024-11-22 00:47:15.740288: train_loss -0.7776 +2024-11-22 00:47:15.741908: val_loss -0.7698 +2024-11-22 00:47:15.742040: Pseudo dice [0.8435] +2024-11-22 00:47:15.742404: Epoch time: 17.48 s +2024-11-22 00:47:16.600798: +2024-11-22 00:47:16.601020: Epoch 2629 +2024-11-22 00:47:16.601127: Current learning rate: 0.00699 +2024-11-22 00:47:35.119673: train_loss -0.7722 +2024-11-22 00:47:35.119950: val_loss -0.7368 +2024-11-22 00:47:35.120034: Pseudo dice [0.8353] +2024-11-22 00:47:35.120108: Epoch time: 18.52 s +2024-11-22 00:47:36.056870: +2024-11-22 00:47:36.057086: Epoch 2630 +2024-11-22 00:47:36.057207: Current learning rate: 0.00699 +2024-11-22 00:47:54.573730: train_loss -0.7508 +2024-11-22 00:47:54.573964: val_loss -0.7582 +2024-11-22 00:47:54.574047: Pseudo dice [0.8248] +2024-11-22 00:47:54.574131: Epoch time: 18.52 s +2024-11-22 00:47:55.426080: +2024-11-22 00:47:55.426350: Epoch 2631 +2024-11-22 00:47:55.426502: Current learning rate: 0.00698 +2024-11-22 00:48:13.284623: train_loss -0.7667 +2024-11-22 00:48:13.284862: val_loss -0.759 +2024-11-22 00:48:13.284941: Pseudo dice [0.8241] +2024-11-22 00:48:13.285025: Epoch time: 17.86 s +2024-11-22 00:48:14.134424: +2024-11-22 00:48:14.134637: Epoch 2632 +2024-11-22 00:48:14.134747: Current learning rate: 0.00698 +2024-11-22 00:48:31.958271: train_loss -0.7606 +2024-11-22 00:48:31.958493: val_loss -0.7257 +2024-11-22 00:48:31.958569: Pseudo dice [0.8191] +2024-11-22 00:48:31.958677: Epoch time: 17.82 s +2024-11-22 00:48:32.799445: +2024-11-22 00:48:32.799669: Epoch 2633 +2024-11-22 00:48:32.799781: Current learning rate: 0.00698 +2024-11-22 00:48:51.774599: train_loss -0.7704 +2024-11-22 00:48:51.774828: val_loss -0.782 +2024-11-22 00:48:51.774902: Pseudo dice [0.8375] +2024-11-22 00:48:51.774979: Epoch time: 18.98 s +2024-11-22 00:48:52.700476: +2024-11-22 00:48:52.700695: Epoch 2634 +2024-11-22 00:48:52.700803: Current learning rate: 0.00698 +2024-11-22 00:49:12.265245: train_loss -0.7732 +2024-11-22 00:49:12.265500: val_loss -0.772 +2024-11-22 00:49:12.265584: Pseudo dice [0.8426] +2024-11-22 00:49:12.265668: Epoch time: 19.57 s +2024-11-22 00:49:13.113516: +2024-11-22 00:49:13.113863: Epoch 2635 +2024-11-22 00:49:13.113971: Current learning rate: 0.00698 +2024-11-22 00:49:31.643803: train_loss -0.7736 +2024-11-22 00:49:31.644024: val_loss -0.7713 +2024-11-22 00:49:31.644104: Pseudo dice [0.8521] +2024-11-22 00:49:31.644187: Epoch time: 18.53 s +2024-11-22 00:49:32.481919: +2024-11-22 00:49:32.482170: Epoch 2636 +2024-11-22 00:49:32.482292: Current learning rate: 0.00698 +2024-11-22 00:49:51.183731: train_loss -0.7737 +2024-11-22 00:49:51.183944: val_loss -0.7772 +2024-11-22 00:49:51.184029: Pseudo dice [0.8512] +2024-11-22 00:49:51.184103: Epoch time: 18.7 s +2024-11-22 00:49:52.021308: +2024-11-22 00:49:52.021712: Epoch 2637 +2024-11-22 00:49:52.021848: Current learning rate: 0.00698 +2024-11-22 00:50:10.589278: train_loss -0.7795 +2024-11-22 00:50:10.589505: val_loss -0.7683 +2024-11-22 00:50:10.589587: Pseudo dice [0.8336] +2024-11-22 00:50:10.589671: Epoch time: 18.57 s +2024-11-22 00:50:11.441307: +2024-11-22 00:50:11.441509: Epoch 2638 +2024-11-22 00:50:11.441619: Current learning rate: 0.00698 +2024-11-22 00:50:29.636019: train_loss -0.7763 +2024-11-22 00:50:29.636261: val_loss -0.7607 +2024-11-22 00:50:29.636335: Pseudo dice [0.8539] +2024-11-22 00:50:29.636413: Epoch time: 18.2 s +2024-11-22 00:50:30.929365: +2024-11-22 00:50:30.929590: Epoch 2639 +2024-11-22 00:50:30.929702: Current learning rate: 0.00697 +2024-11-22 00:50:49.075290: train_loss -0.7753 +2024-11-22 00:50:49.075515: val_loss -0.7749 +2024-11-22 00:50:49.075587: Pseudo dice [0.8511] +2024-11-22 00:50:49.075659: Epoch time: 18.15 s +2024-11-22 00:50:49.921525: +2024-11-22 00:50:49.921748: Epoch 2640 +2024-11-22 00:50:49.921871: Current learning rate: 0.00697 +2024-11-22 00:51:07.963180: train_loss -0.7746 +2024-11-22 00:51:07.965139: val_loss -0.7636 +2024-11-22 00:51:07.965238: Pseudo dice [0.8377] +2024-11-22 00:51:07.965316: Epoch time: 18.04 s +2024-11-22 00:51:08.821618: +2024-11-22 00:51:08.821882: Epoch 2641 +2024-11-22 00:51:08.822229: Current learning rate: 0.00697 +2024-11-22 00:51:28.641237: train_loss -0.7594 +2024-11-22 00:51:28.641482: val_loss -0.7569 +2024-11-22 00:51:28.641556: Pseudo dice [0.8387] +2024-11-22 00:51:28.641639: Epoch time: 19.82 s +2024-11-22 00:51:29.490903: +2024-11-22 00:51:29.491131: Epoch 2642 +2024-11-22 00:51:29.491248: Current learning rate: 0.00697 +2024-11-22 00:51:48.641092: train_loss -0.7605 +2024-11-22 00:51:48.641307: val_loss -0.7609 +2024-11-22 00:51:48.641386: Pseudo dice [0.8434] +2024-11-22 00:51:48.641466: Epoch time: 19.15 s +2024-11-22 00:51:49.487897: +2024-11-22 00:51:49.488161: Epoch 2643 +2024-11-22 00:51:49.488277: Current learning rate: 0.00697 +2024-11-22 00:52:07.774580: train_loss -0.7604 +2024-11-22 00:52:07.774799: val_loss -0.7593 +2024-11-22 00:52:07.774873: Pseudo dice [0.8406] +2024-11-22 00:52:07.774950: Epoch time: 18.29 s +2024-11-22 00:52:08.628332: +2024-11-22 00:52:08.628552: Epoch 2644 +2024-11-22 00:52:08.628663: Current learning rate: 0.00697 +2024-11-22 00:52:27.669888: train_loss -0.771 +2024-11-22 00:52:27.672537: val_loss -0.7473 +2024-11-22 00:52:27.672644: Pseudo dice [0.8299] +2024-11-22 00:52:27.672723: Epoch time: 19.04 s +2024-11-22 00:52:28.525656: +2024-11-22 00:52:28.525883: Epoch 2645 +2024-11-22 00:52:28.526016: Current learning rate: 0.00697 +2024-11-22 00:52:45.717929: train_loss -0.7753 +2024-11-22 00:52:45.718182: val_loss -0.7654 +2024-11-22 00:52:45.718284: Pseudo dice [0.8479] +2024-11-22 00:52:45.718369: Epoch time: 17.19 s +2024-11-22 00:52:46.561095: +2024-11-22 00:52:46.561298: Epoch 2646 +2024-11-22 00:52:46.561408: Current learning rate: 0.00697 +2024-11-22 00:53:05.863130: train_loss -0.7783 +2024-11-22 00:53:05.863407: val_loss -0.7691 +2024-11-22 00:53:05.863487: Pseudo dice [0.8531] +2024-11-22 00:53:05.863563: Epoch time: 19.3 s +2024-11-22 00:53:06.712696: +2024-11-22 00:53:06.712901: Epoch 2647 +2024-11-22 00:53:06.713022: Current learning rate: 0.00697 +2024-11-22 00:53:25.982746: train_loss -0.7702 +2024-11-22 00:53:25.982961: val_loss -0.7532 +2024-11-22 00:53:25.983043: Pseudo dice [0.848] +2024-11-22 00:53:25.983118: Epoch time: 19.27 s +2024-11-22 00:53:26.824964: +2024-11-22 00:53:26.825176: Epoch 2648 +2024-11-22 00:53:26.825284: Current learning rate: 0.00696 +2024-11-22 00:53:45.378630: train_loss -0.7685 +2024-11-22 00:53:45.378859: val_loss -0.7681 +2024-11-22 00:53:45.378933: Pseudo dice [0.8527] +2024-11-22 00:53:45.379014: Epoch time: 18.55 s +2024-11-22 00:53:46.228409: +2024-11-22 00:53:46.228824: Epoch 2649 +2024-11-22 00:53:46.228957: Current learning rate: 0.00696 +2024-11-22 00:54:04.737269: train_loss -0.7729 +2024-11-22 00:54:04.737517: val_loss -0.7664 +2024-11-22 00:54:04.737594: Pseudo dice [0.8381] +2024-11-22 00:54:04.737672: Epoch time: 18.51 s +2024-11-22 00:54:06.235178: +2024-11-22 00:54:06.235489: Epoch 2650 +2024-11-22 00:54:06.235612: Current learning rate: 0.00696 +2024-11-22 00:54:24.596327: train_loss -0.7763 +2024-11-22 00:54:24.596554: val_loss -0.7677 +2024-11-22 00:54:24.596627: Pseudo dice [0.8193] +2024-11-22 00:54:24.596775: Epoch time: 18.36 s +2024-11-22 00:54:25.444955: +2024-11-22 00:54:25.445177: Epoch 2651 +2024-11-22 00:54:25.445295: Current learning rate: 0.00696 +2024-11-22 00:54:43.145861: train_loss -0.7727 +2024-11-22 00:54:43.146096: val_loss -0.7776 +2024-11-22 00:54:43.146175: Pseudo dice [0.8419] +2024-11-22 00:54:43.146319: Epoch time: 17.7 s +2024-11-22 00:54:44.001265: +2024-11-22 00:54:44.001521: Epoch 2652 +2024-11-22 00:54:44.001633: Current learning rate: 0.00696 +2024-11-22 00:55:01.252977: train_loss -0.7799 +2024-11-22 00:55:01.253210: val_loss -0.7603 +2024-11-22 00:55:01.253286: Pseudo dice [0.8271] +2024-11-22 00:55:01.253362: Epoch time: 17.25 s +2024-11-22 00:55:02.097591: +2024-11-22 00:55:02.097814: Epoch 2653 +2024-11-22 00:55:02.097923: Current learning rate: 0.00696 +2024-11-22 00:55:20.646130: train_loss -0.7752 +2024-11-22 00:55:20.646348: val_loss -0.7616 +2024-11-22 00:55:20.646424: Pseudo dice [0.8371] +2024-11-22 00:55:20.646498: Epoch time: 18.55 s +2024-11-22 00:55:21.488753: +2024-11-22 00:55:21.488988: Epoch 2654 +2024-11-22 00:55:21.489105: Current learning rate: 0.00696 +2024-11-22 00:55:39.219710: train_loss -0.7807 +2024-11-22 00:55:39.219943: val_loss -0.786 +2024-11-22 00:55:39.220292: Pseudo dice [0.8513] +2024-11-22 00:55:39.220374: Epoch time: 17.73 s +2024-11-22 00:55:40.065511: +2024-11-22 00:55:40.065704: Epoch 2655 +2024-11-22 00:55:40.065814: Current learning rate: 0.00696 +2024-11-22 00:55:58.815836: train_loss -0.7841 +2024-11-22 00:55:58.816069: val_loss -0.7782 +2024-11-22 00:55:58.816148: Pseudo dice [0.8527] +2024-11-22 00:55:58.816229: Epoch time: 18.75 s +2024-11-22 00:55:59.660758: +2024-11-22 00:55:59.660968: Epoch 2656 +2024-11-22 00:55:59.661086: Current learning rate: 0.00696 +2024-11-22 00:56:17.072425: train_loss -0.7884 +2024-11-22 00:56:17.072678: val_loss -0.7393 +2024-11-22 00:56:17.072757: Pseudo dice [0.8394] +2024-11-22 00:56:17.072838: Epoch time: 17.41 s +2024-11-22 00:56:17.914098: +2024-11-22 00:56:17.914306: Epoch 2657 +2024-11-22 00:56:17.914418: Current learning rate: 0.00695 +2024-11-22 00:56:35.733562: train_loss -0.7681 +2024-11-22 00:56:35.733786: val_loss -0.7793 +2024-11-22 00:56:35.733863: Pseudo dice [0.8483] +2024-11-22 00:56:35.733945: Epoch time: 17.82 s +2024-11-22 00:56:36.706694: +2024-11-22 00:56:36.706913: Epoch 2658 +2024-11-22 00:56:36.707030: Current learning rate: 0.00695 +2024-11-22 00:56:54.706451: train_loss -0.7732 +2024-11-22 00:56:54.706672: val_loss -0.7749 +2024-11-22 00:56:54.706746: Pseudo dice [0.8249] +2024-11-22 00:56:54.706820: Epoch time: 18.0 s +2024-11-22 00:56:55.544050: +2024-11-22 00:56:55.544255: Epoch 2659 +2024-11-22 00:56:55.544364: Current learning rate: 0.00695 +2024-11-22 00:57:13.548209: train_loss -0.7782 +2024-11-22 00:57:13.548447: val_loss -0.7632 +2024-11-22 00:57:13.548525: Pseudo dice [0.8458] +2024-11-22 00:57:13.548605: Epoch time: 18.0 s +2024-11-22 00:57:14.402824: +2024-11-22 00:57:14.403251: Epoch 2660 +2024-11-22 00:57:14.403377: Current learning rate: 0.00695 +2024-11-22 00:57:32.388167: train_loss -0.7791 +2024-11-22 00:57:32.388386: val_loss -0.7551 +2024-11-22 00:57:32.388459: Pseudo dice [0.8369] +2024-11-22 00:57:32.388534: Epoch time: 17.99 s +2024-11-22 00:57:33.231932: +2024-11-22 00:57:33.232133: Epoch 2661 +2024-11-22 00:57:33.232244: Current learning rate: 0.00695 +2024-11-22 00:57:51.945143: train_loss -0.7734 +2024-11-22 00:57:51.945392: val_loss -0.779 +2024-11-22 00:57:51.945466: Pseudo dice [0.8469] +2024-11-22 00:57:51.945539: Epoch time: 18.71 s +2024-11-22 00:57:53.155967: +2024-11-22 00:57:53.156197: Epoch 2662 +2024-11-22 00:57:53.156307: Current learning rate: 0.00695 +2024-11-22 00:58:11.464252: train_loss -0.7747 +2024-11-22 00:58:11.464510: val_loss -0.7692 +2024-11-22 00:58:11.464586: Pseudo dice [0.8331] +2024-11-22 00:58:11.464665: Epoch time: 18.31 s +2024-11-22 00:58:12.377016: +2024-11-22 00:58:12.377243: Epoch 2663 +2024-11-22 00:58:12.377349: Current learning rate: 0.00695 +2024-11-22 00:58:31.867620: train_loss -0.7765 +2024-11-22 00:58:31.867832: val_loss -0.7557 +2024-11-22 00:58:31.867910: Pseudo dice [0.8406] +2024-11-22 00:58:31.867984: Epoch time: 19.49 s +2024-11-22 00:58:32.760508: +2024-11-22 00:58:32.760710: Epoch 2664 +2024-11-22 00:58:32.760818: Current learning rate: 0.00695 +2024-11-22 00:58:51.339609: train_loss -0.7883 +2024-11-22 00:58:51.339835: val_loss -0.7648 +2024-11-22 00:58:51.339908: Pseudo dice [0.8423] +2024-11-22 00:58:51.339984: Epoch time: 18.58 s +2024-11-22 00:58:52.186005: +2024-11-22 00:58:52.186235: Epoch 2665 +2024-11-22 00:58:52.186347: Current learning rate: 0.00694 +2024-11-22 00:59:10.848486: train_loss -0.7775 +2024-11-22 00:59:10.848715: val_loss -0.7647 +2024-11-22 00:59:10.848797: Pseudo dice [0.8393] +2024-11-22 00:59:10.848878: Epoch time: 18.66 s +2024-11-22 00:59:11.721181: +2024-11-22 00:59:11.721421: Epoch 2666 +2024-11-22 00:59:11.721549: Current learning rate: 0.00694 +2024-11-22 00:59:29.269449: train_loss -0.7774 +2024-11-22 00:59:29.269685: val_loss -0.7781 +2024-11-22 00:59:29.270865: Pseudo dice [0.863] +2024-11-22 00:59:29.271045: Epoch time: 17.55 s +2024-11-22 00:59:30.121064: +2024-11-22 00:59:30.121283: Epoch 2667 +2024-11-22 00:59:30.121414: Current learning rate: 0.00694 +2024-11-22 00:59:48.684218: train_loss -0.7704 +2024-11-22 00:59:48.684456: val_loss -0.7834 +2024-11-22 00:59:48.684532: Pseudo dice [0.85] +2024-11-22 00:59:48.684605: Epoch time: 18.56 s +2024-11-22 00:59:49.531624: +2024-11-22 00:59:49.531847: Epoch 2668 +2024-11-22 00:59:49.531962: Current learning rate: 0.00694 +2024-11-22 01:00:07.323222: train_loss -0.7709 +2024-11-22 01:00:07.323433: val_loss -0.7801 +2024-11-22 01:00:07.323508: Pseudo dice [0.8228] +2024-11-22 01:00:07.323581: Epoch time: 17.79 s +2024-11-22 01:00:08.167230: +2024-11-22 01:00:08.167441: Epoch 2669 +2024-11-22 01:00:08.167547: Current learning rate: 0.00694 +2024-11-22 01:00:27.447752: train_loss -0.7694 +2024-11-22 01:00:27.448004: val_loss -0.7611 +2024-11-22 01:00:27.448083: Pseudo dice [0.8234] +2024-11-22 01:00:27.448167: Epoch time: 19.28 s +2024-11-22 01:00:28.292584: +2024-11-22 01:00:28.292797: Epoch 2670 +2024-11-22 01:00:28.292907: Current learning rate: 0.00694 +2024-11-22 01:00:47.199876: train_loss -0.7779 +2024-11-22 01:00:47.200091: val_loss -0.7786 +2024-11-22 01:00:47.200164: Pseudo dice [0.8366] +2024-11-22 01:00:47.200241: Epoch time: 18.91 s +2024-11-22 01:00:48.051888: +2024-11-22 01:00:48.052357: Epoch 2671 +2024-11-22 01:00:48.052486: Current learning rate: 0.00694 +2024-11-22 01:01:06.143614: train_loss -0.7741 +2024-11-22 01:01:06.143836: val_loss -0.7772 +2024-11-22 01:01:06.143996: Pseudo dice [0.859] +2024-11-22 01:01:06.144074: Epoch time: 18.09 s +2024-11-22 01:01:07.027362: +2024-11-22 01:01:07.027583: Epoch 2672 +2024-11-22 01:01:07.027704: Current learning rate: 0.00694 +2024-11-22 01:01:25.848735: train_loss -0.78 +2024-11-22 01:01:25.848962: val_loss -0.756 +2024-11-22 01:01:25.849051: Pseudo dice [0.8428] +2024-11-22 01:01:25.849129: Epoch time: 18.82 s +2024-11-22 01:01:26.701996: +2024-11-22 01:01:26.702224: Epoch 2673 +2024-11-22 01:01:26.702331: Current learning rate: 0.00694 +2024-11-22 01:01:45.765499: train_loss -0.7799 +2024-11-22 01:01:45.765734: val_loss -0.7437 +2024-11-22 01:01:45.765809: Pseudo dice [0.8259] +2024-11-22 01:01:45.765887: Epoch time: 19.06 s +2024-11-22 01:01:46.959836: +2024-11-22 01:01:46.960062: Epoch 2674 +2024-11-22 01:01:46.960171: Current learning rate: 0.00693 +2024-11-22 01:02:05.953107: train_loss -0.7807 +2024-11-22 01:02:05.953349: val_loss -0.755 +2024-11-22 01:02:05.953428: Pseudo dice [0.8379] +2024-11-22 01:02:05.953502: Epoch time: 18.99 s +2024-11-22 01:02:06.813766: +2024-11-22 01:02:06.814062: Epoch 2675 +2024-11-22 01:02:06.814178: Current learning rate: 0.00693 +2024-11-22 01:02:25.905814: train_loss -0.7694 +2024-11-22 01:02:25.906040: val_loss -0.7638 +2024-11-22 01:02:25.906117: Pseudo dice [0.8356] +2024-11-22 01:02:25.906191: Epoch time: 19.09 s +2024-11-22 01:02:26.835706: +2024-11-22 01:02:26.835926: Epoch 2676 +2024-11-22 01:02:26.836048: Current learning rate: 0.00693 +2024-11-22 01:02:45.082044: train_loss -0.78 +2024-11-22 01:02:45.082297: val_loss -0.7843 +2024-11-22 01:02:45.082374: Pseudo dice [0.8578] +2024-11-22 01:02:45.082453: Epoch time: 18.25 s +2024-11-22 01:02:45.938114: +2024-11-22 01:02:45.938349: Epoch 2677 +2024-11-22 01:02:45.938459: Current learning rate: 0.00693 +2024-11-22 01:03:04.244248: train_loss -0.7828 +2024-11-22 01:03:04.244458: val_loss -0.777 +2024-11-22 01:03:04.244534: Pseudo dice [0.8411] +2024-11-22 01:03:04.244608: Epoch time: 18.31 s +2024-11-22 01:03:05.089261: +2024-11-22 01:03:05.089472: Epoch 2678 +2024-11-22 01:03:05.089581: Current learning rate: 0.00693 +2024-11-22 01:03:21.863658: train_loss -0.7689 +2024-11-22 01:03:21.863896: val_loss -0.7646 +2024-11-22 01:03:21.863974: Pseudo dice [0.8381] +2024-11-22 01:03:21.864060: Epoch time: 16.78 s +2024-11-22 01:03:22.712901: +2024-11-22 01:03:22.713088: Epoch 2679 +2024-11-22 01:03:22.713224: Current learning rate: 0.00693 +2024-11-22 01:03:41.280162: train_loss -0.7852 +2024-11-22 01:03:41.280372: val_loss -0.7308 +2024-11-22 01:03:41.280447: Pseudo dice [0.8219] +2024-11-22 01:03:41.280522: Epoch time: 18.57 s +2024-11-22 01:03:42.175643: +2024-11-22 01:03:42.175853: Epoch 2680 +2024-11-22 01:03:42.175959: Current learning rate: 0.00693 +2024-11-22 01:04:00.199007: train_loss -0.7798 +2024-11-22 01:04:00.199321: val_loss -0.7794 +2024-11-22 01:04:00.199692: Pseudo dice [0.8408] +2024-11-22 01:04:00.199782: Epoch time: 18.02 s +2024-11-22 01:04:01.055782: +2024-11-22 01:04:01.056216: Epoch 2681 +2024-11-22 01:04:01.056328: Current learning rate: 0.00693 +2024-11-22 01:04:20.200439: train_loss -0.7831 +2024-11-22 01:04:20.200647: val_loss -0.7463 +2024-11-22 01:04:20.200723: Pseudo dice [0.8296] +2024-11-22 01:04:20.200819: Epoch time: 19.15 s +2024-11-22 01:04:21.067029: +2024-11-22 01:04:21.067256: Epoch 2682 +2024-11-22 01:04:21.067369: Current learning rate: 0.00692 +2024-11-22 01:04:39.910550: train_loss -0.7751 +2024-11-22 01:04:39.910762: val_loss -0.7688 +2024-11-22 01:04:39.910838: Pseudo dice [0.8388] +2024-11-22 01:04:39.910917: Epoch time: 18.84 s +2024-11-22 01:04:40.755162: +2024-11-22 01:04:40.755362: Epoch 2683 +2024-11-22 01:04:40.755474: Current learning rate: 0.00692 +2024-11-22 01:04:58.909158: train_loss -0.7802 +2024-11-22 01:04:58.909416: val_loss -0.7898 +2024-11-22 01:04:58.909499: Pseudo dice [0.8409] +2024-11-22 01:04:58.909590: Epoch time: 18.15 s +2024-11-22 01:04:59.865561: +2024-11-22 01:04:59.866024: Epoch 2684 +2024-11-22 01:04:59.866163: Current learning rate: 0.00692 +2024-11-22 01:05:17.905977: train_loss -0.7744 +2024-11-22 01:05:17.906229: val_loss -0.7486 +2024-11-22 01:05:17.906311: Pseudo dice [0.8558] +2024-11-22 01:05:17.906388: Epoch time: 18.04 s +2024-11-22 01:05:18.749074: +2024-11-22 01:05:18.749294: Epoch 2685 +2024-11-22 01:05:18.749401: Current learning rate: 0.00692 +2024-11-22 01:05:36.903930: train_loss -0.7862 +2024-11-22 01:05:36.904444: val_loss -0.7677 +2024-11-22 01:05:36.904542: Pseudo dice [0.8518] +2024-11-22 01:05:36.904620: Epoch time: 18.16 s +2024-11-22 01:05:37.744939: +2024-11-22 01:05:37.745153: Epoch 2686 +2024-11-22 01:05:37.745262: Current learning rate: 0.00692 +2024-11-22 01:05:56.115680: train_loss -0.7838 +2024-11-22 01:05:56.115974: val_loss -0.7854 +2024-11-22 01:05:56.116062: Pseudo dice [0.8511] +2024-11-22 01:05:56.116143: Epoch time: 18.37 s +2024-11-22 01:05:56.963281: +2024-11-22 01:05:56.963492: Epoch 2687 +2024-11-22 01:05:56.963603: Current learning rate: 0.00692 +2024-11-22 01:06:15.488619: train_loss -0.7738 +2024-11-22 01:06:15.488869: val_loss -0.7489 +2024-11-22 01:06:15.488944: Pseudo dice [0.8226] +2024-11-22 01:06:15.489030: Epoch time: 18.53 s +2024-11-22 01:06:16.525439: +2024-11-22 01:06:16.525657: Epoch 2688 +2024-11-22 01:06:16.525769: Current learning rate: 0.00692 +2024-11-22 01:06:34.056971: train_loss -0.7882 +2024-11-22 01:06:34.057200: val_loss -0.779 +2024-11-22 01:06:34.057279: Pseudo dice [0.8523] +2024-11-22 01:06:34.057354: Epoch time: 17.53 s +2024-11-22 01:06:34.908558: +2024-11-22 01:06:34.908791: Epoch 2689 +2024-11-22 01:06:34.908912: Current learning rate: 0.00692 +2024-11-22 01:06:53.611367: train_loss -0.7775 +2024-11-22 01:06:53.611595: val_loss -0.7709 +2024-11-22 01:06:53.611673: Pseudo dice [0.8511] +2024-11-22 01:06:53.611808: Epoch time: 18.7 s +2024-11-22 01:06:54.460927: +2024-11-22 01:06:54.461138: Epoch 2690 +2024-11-22 01:06:54.461244: Current learning rate: 0.00692 +2024-11-22 01:07:12.875770: train_loss -0.7821 +2024-11-22 01:07:12.878176: val_loss -0.7785 +2024-11-22 01:07:12.878299: Pseudo dice [0.8511] +2024-11-22 01:07:12.878382: Epoch time: 18.42 s +2024-11-22 01:07:13.896024: +2024-11-22 01:07:13.896228: Epoch 2691 +2024-11-22 01:07:13.896345: Current learning rate: 0.00691 +2024-11-22 01:07:32.488609: train_loss -0.7735 +2024-11-22 01:07:32.488861: val_loss -0.7744 +2024-11-22 01:07:32.488941: Pseudo dice [0.8374] +2024-11-22 01:07:32.489037: Epoch time: 18.59 s +2024-11-22 01:07:33.334088: +2024-11-22 01:07:33.334302: Epoch 2692 +2024-11-22 01:07:33.334417: Current learning rate: 0.00691 +2024-11-22 01:07:51.651342: train_loss -0.7827 +2024-11-22 01:07:51.651556: val_loss -0.7676 +2024-11-22 01:07:51.651632: Pseudo dice [0.8597] +2024-11-22 01:07:51.651707: Epoch time: 18.32 s +2024-11-22 01:07:52.502522: +2024-11-22 01:07:52.502737: Epoch 2693 +2024-11-22 01:07:52.502849: Current learning rate: 0.00691 +2024-11-22 01:08:10.704651: train_loss -0.7791 +2024-11-22 01:08:10.704877: val_loss -0.7693 +2024-11-22 01:08:10.704952: Pseudo dice [0.8472] +2024-11-22 01:08:10.705034: Epoch time: 18.2 s +2024-11-22 01:08:11.560291: +2024-11-22 01:08:11.560484: Epoch 2694 +2024-11-22 01:08:11.560592: Current learning rate: 0.00691 +2024-11-22 01:08:30.265194: train_loss -0.7977 +2024-11-22 01:08:30.265435: val_loss -0.7466 +2024-11-22 01:08:30.265575: Pseudo dice [0.8532] +2024-11-22 01:08:30.265662: Epoch time: 18.71 s +2024-11-22 01:08:31.213724: +2024-11-22 01:08:31.213937: Epoch 2695 +2024-11-22 01:08:31.214050: Current learning rate: 0.00691 +2024-11-22 01:08:49.868705: train_loss -0.7883 +2024-11-22 01:08:49.868933: val_loss -0.789 +2024-11-22 01:08:49.869016: Pseudo dice [0.8388] +2024-11-22 01:08:49.869093: Epoch time: 18.66 s +2024-11-22 01:08:50.812920: +2024-11-22 01:08:50.813151: Epoch 2696 +2024-11-22 01:08:50.813259: Current learning rate: 0.00691 +2024-11-22 01:09:09.849888: train_loss -0.78 +2024-11-22 01:09:09.850132: val_loss -0.754 +2024-11-22 01:09:09.850230: Pseudo dice [0.8449] +2024-11-22 01:09:09.850310: Epoch time: 19.04 s +2024-11-22 01:09:11.080439: +2024-11-22 01:09:11.080708: Epoch 2697 +2024-11-22 01:09:11.080820: Current learning rate: 0.00691 +2024-11-22 01:09:28.854821: train_loss -0.7801 +2024-11-22 01:09:28.855079: val_loss -0.7707 +2024-11-22 01:09:28.855183: Pseudo dice [0.837] +2024-11-22 01:09:28.855273: Epoch time: 17.78 s +2024-11-22 01:09:29.707710: +2024-11-22 01:09:29.707936: Epoch 2698 +2024-11-22 01:09:29.708051: Current learning rate: 0.00691 +2024-11-22 01:09:48.481387: train_loss -0.7433 +2024-11-22 01:09:48.481627: val_loss -0.7394 +2024-11-22 01:09:48.481708: Pseudo dice [0.814] +2024-11-22 01:09:48.481798: Epoch time: 18.77 s +2024-11-22 01:09:49.327095: +2024-11-22 01:09:49.327324: Epoch 2699 +2024-11-22 01:09:49.327451: Current learning rate: 0.0069 +2024-11-22 01:10:08.278893: train_loss -0.7575 +2024-11-22 01:10:08.279191: val_loss -0.7526 +2024-11-22 01:10:08.279269: Pseudo dice [0.82] +2024-11-22 01:10:08.279345: Epoch time: 18.95 s +2024-11-22 01:10:09.361814: +2024-11-22 01:10:09.362027: Epoch 2700 +2024-11-22 01:10:09.362139: Current learning rate: 0.0069 +2024-11-22 01:10:28.057455: train_loss -0.754 +2024-11-22 01:10:28.057684: val_loss -0.7748 +2024-11-22 01:10:28.057762: Pseudo dice [0.8523] +2024-11-22 01:10:28.057842: Epoch time: 18.7 s +2024-11-22 01:10:28.902828: +2024-11-22 01:10:28.903063: Epoch 2701 +2024-11-22 01:10:28.903172: Current learning rate: 0.0069 +2024-11-22 01:10:47.513475: train_loss -0.7736 +2024-11-22 01:10:47.513719: val_loss -0.7612 +2024-11-22 01:10:47.513798: Pseudo dice [0.825] +2024-11-22 01:10:47.513876: Epoch time: 18.61 s +2024-11-22 01:10:48.361631: +2024-11-22 01:10:48.361855: Epoch 2702 +2024-11-22 01:10:48.361966: Current learning rate: 0.0069 +2024-11-22 01:11:06.116038: train_loss -0.7693 +2024-11-22 01:11:06.116262: val_loss -0.7649 +2024-11-22 01:11:06.116334: Pseudo dice [0.8387] +2024-11-22 01:11:06.118637: Epoch time: 17.76 s +2024-11-22 01:11:07.080107: +2024-11-22 01:11:07.080296: Epoch 2703 +2024-11-22 01:11:07.080402: Current learning rate: 0.0069 +2024-11-22 01:11:25.718478: train_loss -0.7635 +2024-11-22 01:11:25.718704: val_loss -0.7529 +2024-11-22 01:11:25.718779: Pseudo dice [0.828] +2024-11-22 01:11:25.718854: Epoch time: 18.64 s +2024-11-22 01:11:26.563814: +2024-11-22 01:11:26.564027: Epoch 2704 +2024-11-22 01:11:26.564133: Current learning rate: 0.0069 +2024-11-22 01:11:45.126199: train_loss -0.7662 +2024-11-22 01:11:45.126443: val_loss -0.7542 +2024-11-22 01:11:45.126520: Pseudo dice [0.8485] +2024-11-22 01:11:45.127680: Epoch time: 18.56 s +2024-11-22 01:11:46.037096: +2024-11-22 01:11:46.037309: Epoch 2705 +2024-11-22 01:11:46.037420: Current learning rate: 0.0069 +2024-11-22 01:12:05.363875: train_loss -0.7628 +2024-11-22 01:12:05.364148: val_loss -0.7422 +2024-11-22 01:12:05.364226: Pseudo dice [0.836] +2024-11-22 01:12:05.364310: Epoch time: 19.33 s +2024-11-22 01:12:06.211785: +2024-11-22 01:12:06.212012: Epoch 2706 +2024-11-22 01:12:06.212123: Current learning rate: 0.0069 +2024-11-22 01:12:25.012805: train_loss -0.7683 +2024-11-22 01:12:25.013250: val_loss -0.767 +2024-11-22 01:12:25.013405: Pseudo dice [0.849] +2024-11-22 01:12:25.013484: Epoch time: 18.8 s +2024-11-22 01:12:25.858407: +2024-11-22 01:12:25.858624: Epoch 2707 +2024-11-22 01:12:25.858735: Current learning rate: 0.0069 +2024-11-22 01:12:43.692605: train_loss -0.7688 +2024-11-22 01:12:43.692864: val_loss -0.7674 +2024-11-22 01:12:43.692940: Pseudo dice [0.8506] +2024-11-22 01:12:43.693031: Epoch time: 17.83 s +2024-11-22 01:12:44.534781: +2024-11-22 01:12:44.534972: Epoch 2708 +2024-11-22 01:12:44.535086: Current learning rate: 0.00689 +2024-11-22 01:13:02.577225: train_loss -0.7599 +2024-11-22 01:13:02.577697: val_loss -0.7463 +2024-11-22 01:13:02.577795: Pseudo dice [0.8291] +2024-11-22 01:13:02.577869: Epoch time: 18.04 s +2024-11-22 01:13:03.458032: +2024-11-22 01:13:03.458251: Epoch 2709 +2024-11-22 01:13:03.458366: Current learning rate: 0.00689 +2024-11-22 01:13:22.398968: train_loss -0.7546 +2024-11-22 01:13:22.399460: val_loss -0.7795 +2024-11-22 01:13:22.399557: Pseudo dice [0.8523] +2024-11-22 01:13:22.399710: Epoch time: 18.94 s +2024-11-22 01:13:23.278204: +2024-11-22 01:13:23.278427: Epoch 2710 +2024-11-22 01:13:23.278533: Current learning rate: 0.00689 +2024-11-22 01:13:41.712217: train_loss -0.7735 +2024-11-22 01:13:41.712463: val_loss -0.7439 +2024-11-22 01:13:41.712539: Pseudo dice [0.8199] +2024-11-22 01:13:41.712623: Epoch time: 18.43 s +2024-11-22 01:13:42.559651: +2024-11-22 01:13:42.559859: Epoch 2711 +2024-11-22 01:13:42.559972: Current learning rate: 0.00689 +2024-11-22 01:13:59.791471: train_loss -0.7719 +2024-11-22 01:13:59.796859: val_loss -0.7544 +2024-11-22 01:13:59.797028: Pseudo dice [0.8562] +2024-11-22 01:13:59.797112: Epoch time: 17.23 s +2024-11-22 01:14:00.675538: +2024-11-22 01:14:00.675742: Epoch 2712 +2024-11-22 01:14:00.675852: Current learning rate: 0.00689 +2024-11-22 01:14:18.970400: train_loss -0.7694 +2024-11-22 01:14:18.970618: val_loss -0.7581 +2024-11-22 01:14:18.970693: Pseudo dice [0.8234] +2024-11-22 01:14:18.970766: Epoch time: 18.3 s +2024-11-22 01:14:19.821462: +2024-11-22 01:14:19.821656: Epoch 2713 +2024-11-22 01:14:19.821770: Current learning rate: 0.00689 +2024-11-22 01:14:39.231400: train_loss -0.7631 +2024-11-22 01:14:39.231643: val_loss -0.7685 +2024-11-22 01:14:39.231731: Pseudo dice [0.8471] +2024-11-22 01:14:39.231862: Epoch time: 19.41 s +2024-11-22 01:14:40.131764: +2024-11-22 01:14:40.131995: Epoch 2714 +2024-11-22 01:14:40.132107: Current learning rate: 0.00689 +2024-11-22 01:14:59.430838: train_loss -0.77 +2024-11-22 01:14:59.431086: val_loss -0.7812 +2024-11-22 01:14:59.431163: Pseudo dice [0.8472] +2024-11-22 01:14:59.431242: Epoch time: 19.3 s +2024-11-22 01:15:00.281722: +2024-11-22 01:15:00.281917: Epoch 2715 +2024-11-22 01:15:00.282032: Current learning rate: 0.00689 +2024-11-22 01:15:19.251862: train_loss -0.7739 +2024-11-22 01:15:19.252096: val_loss -0.7761 +2024-11-22 01:15:19.252175: Pseudo dice [0.8488] +2024-11-22 01:15:19.252250: Epoch time: 18.97 s +2024-11-22 01:15:20.106561: +2024-11-22 01:15:20.106772: Epoch 2716 +2024-11-22 01:15:20.106880: Current learning rate: 0.00688 +2024-11-22 01:15:38.860885: train_loss -0.7669 +2024-11-22 01:15:38.861107: val_loss -0.7753 +2024-11-22 01:15:38.861180: Pseudo dice [0.8349] +2024-11-22 01:15:38.861253: Epoch time: 18.76 s +2024-11-22 01:15:39.707567: +2024-11-22 01:15:39.707778: Epoch 2717 +2024-11-22 01:15:39.707886: Current learning rate: 0.00688 +2024-11-22 01:15:57.861131: train_loss -0.7778 +2024-11-22 01:15:57.905632: val_loss -0.7532 +2024-11-22 01:15:57.905840: Pseudo dice [0.8447] +2024-11-22 01:15:57.905948: Epoch time: 18.15 s +2024-11-22 01:15:58.755502: +2024-11-22 01:15:58.755680: Epoch 2718 +2024-11-22 01:15:58.755787: Current learning rate: 0.00688 +2024-11-22 01:16:16.993622: train_loss -0.7745 +2024-11-22 01:16:16.994812: val_loss -0.7392 +2024-11-22 01:16:16.994896: Pseudo dice [0.8312] +2024-11-22 01:16:16.994971: Epoch time: 18.24 s +2024-11-22 01:16:17.862690: +2024-11-22 01:16:17.862917: Epoch 2719 +2024-11-22 01:16:17.863042: Current learning rate: 0.00688 +2024-11-22 01:16:36.156596: train_loss -0.7815 +2024-11-22 01:16:36.156819: val_loss -0.7706 +2024-11-22 01:16:36.156892: Pseudo dice [0.859] +2024-11-22 01:16:36.156963: Epoch time: 18.29 s +2024-11-22 01:16:37.380768: +2024-11-22 01:16:37.380971: Epoch 2720 +2024-11-22 01:16:37.381084: Current learning rate: 0.00688 +2024-11-22 01:16:55.670455: train_loss -0.7856 +2024-11-22 01:16:55.670732: val_loss -0.7627 +2024-11-22 01:16:55.670808: Pseudo dice [0.8355] +2024-11-22 01:16:55.670890: Epoch time: 18.29 s +2024-11-22 01:16:56.533086: +2024-11-22 01:16:56.533314: Epoch 2721 +2024-11-22 01:16:56.533431: Current learning rate: 0.00688 +2024-11-22 01:17:14.180566: train_loss -0.7875 +2024-11-22 01:17:14.180815: val_loss -0.7893 +2024-11-22 01:17:14.180895: Pseudo dice [0.8509] +2024-11-22 01:17:14.180974: Epoch time: 17.65 s +2024-11-22 01:17:15.025106: +2024-11-22 01:17:15.025321: Epoch 2722 +2024-11-22 01:17:15.025429: Current learning rate: 0.00688 +2024-11-22 01:17:33.269410: train_loss -0.7835 +2024-11-22 01:17:33.271807: val_loss -0.7729 +2024-11-22 01:17:33.271914: Pseudo dice [0.8342] +2024-11-22 01:17:33.272018: Epoch time: 18.25 s +2024-11-22 01:17:34.334960: +2024-11-22 01:17:34.335180: Epoch 2723 +2024-11-22 01:17:34.335289: Current learning rate: 0.00688 +2024-11-22 01:17:53.311695: train_loss -0.7831 +2024-11-22 01:17:53.311936: val_loss -0.7621 +2024-11-22 01:17:53.312016: Pseudo dice [0.842] +2024-11-22 01:17:53.312099: Epoch time: 18.98 s +2024-11-22 01:17:54.170573: +2024-11-22 01:17:54.170762: Epoch 2724 +2024-11-22 01:17:54.170870: Current learning rate: 0.00688 +2024-11-22 01:18:12.983506: train_loss -0.7853 +2024-11-22 01:18:12.983727: val_loss -0.7691 +2024-11-22 01:18:12.983804: Pseudo dice [0.8452] +2024-11-22 01:18:12.983879: Epoch time: 18.81 s +2024-11-22 01:18:13.837821: +2024-11-22 01:18:13.838042: Epoch 2725 +2024-11-22 01:18:13.838154: Current learning rate: 0.00687 +2024-11-22 01:18:32.072562: train_loss -0.7802 +2024-11-22 01:18:32.072788: val_loss -0.7755 +2024-11-22 01:18:32.072864: Pseudo dice [0.8556] +2024-11-22 01:18:32.072940: Epoch time: 18.24 s +2024-11-22 01:18:32.923575: +2024-11-22 01:18:32.923769: Epoch 2726 +2024-11-22 01:18:32.923879: Current learning rate: 0.00687 +2024-11-22 01:18:51.398101: train_loss -0.7881 +2024-11-22 01:18:51.398328: val_loss -0.7627 +2024-11-22 01:18:51.398400: Pseudo dice [0.8529] +2024-11-22 01:18:51.398474: Epoch time: 18.48 s +2024-11-22 01:18:52.247170: +2024-11-22 01:18:52.247372: Epoch 2727 +2024-11-22 01:18:52.247487: Current learning rate: 0.00687 +2024-11-22 01:19:10.720652: train_loss -0.7844 +2024-11-22 01:19:10.720886: val_loss -0.7549 +2024-11-22 01:19:10.720962: Pseudo dice [0.8426] +2024-11-22 01:19:10.721052: Epoch time: 18.47 s +2024-11-22 01:19:11.624400: +2024-11-22 01:19:11.624612: Epoch 2728 +2024-11-22 01:19:11.624722: Current learning rate: 0.00687 +2024-11-22 01:19:29.096954: train_loss -0.7717 +2024-11-22 01:19:29.097208: val_loss -0.762 +2024-11-22 01:19:29.097286: Pseudo dice [0.8455] +2024-11-22 01:19:29.097368: Epoch time: 17.47 s +2024-11-22 01:19:29.942848: +2024-11-22 01:19:29.943075: Epoch 2729 +2024-11-22 01:19:29.943188: Current learning rate: 0.00687 +2024-11-22 01:19:48.441369: train_loss -0.7755 +2024-11-22 01:19:48.441589: val_loss -0.7767 +2024-11-22 01:19:48.446824: Pseudo dice [0.855] +2024-11-22 01:19:48.447003: Epoch time: 18.5 s +2024-11-22 01:19:49.341634: +2024-11-22 01:19:49.341814: Epoch 2730 +2024-11-22 01:19:49.341920: Current learning rate: 0.00687 +2024-11-22 01:20:07.947690: train_loss -0.7741 +2024-11-22 01:20:07.947905: val_loss -0.7788 +2024-11-22 01:20:07.947987: Pseudo dice [0.8479] +2024-11-22 01:20:07.948072: Epoch time: 18.61 s +2024-11-22 01:20:08.791824: +2024-11-22 01:20:08.792061: Epoch 2731 +2024-11-22 01:20:08.792173: Current learning rate: 0.00687 +2024-11-22 01:20:27.745795: train_loss -0.773 +2024-11-22 01:20:27.747557: val_loss -0.7401 +2024-11-22 01:20:27.747658: Pseudo dice [0.8273] +2024-11-22 01:20:27.747733: Epoch time: 18.95 s +2024-11-22 01:20:28.601474: +2024-11-22 01:20:28.601695: Epoch 2732 +2024-11-22 01:20:28.601824: Current learning rate: 0.00687 +2024-11-22 01:20:47.422055: train_loss -0.7706 +2024-11-22 01:20:47.422863: val_loss -0.7697 +2024-11-22 01:20:47.423040: Pseudo dice [0.8515] +2024-11-22 01:20:47.423126: Epoch time: 18.82 s +2024-11-22 01:20:48.264974: +2024-11-22 01:20:48.265206: Epoch 2733 +2024-11-22 01:20:48.265322: Current learning rate: 0.00686 +2024-11-22 01:21:06.458185: train_loss -0.7685 +2024-11-22 01:21:06.458404: val_loss -0.7661 +2024-11-22 01:21:06.458479: Pseudo dice [0.836] +2024-11-22 01:21:06.458552: Epoch time: 18.19 s +2024-11-22 01:21:07.309833: +2024-11-22 01:21:07.310066: Epoch 2734 +2024-11-22 01:21:07.310174: Current learning rate: 0.00686 +2024-11-22 01:21:25.785191: train_loss -0.7789 +2024-11-22 01:21:25.785442: val_loss -0.7852 +2024-11-22 01:21:25.785516: Pseudo dice [0.8557] +2024-11-22 01:21:25.785596: Epoch time: 18.48 s +2024-11-22 01:21:26.633554: +2024-11-22 01:21:26.633767: Epoch 2735 +2024-11-22 01:21:26.633878: Current learning rate: 0.00686 +2024-11-22 01:21:45.830116: train_loss -0.7747 +2024-11-22 01:21:45.830325: val_loss -0.7463 +2024-11-22 01:21:45.830400: Pseudo dice [0.8339] +2024-11-22 01:21:45.830473: Epoch time: 19.2 s +2024-11-22 01:21:46.679742: +2024-11-22 01:21:46.679955: Epoch 2736 +2024-11-22 01:21:46.680069: Current learning rate: 0.00686 +2024-11-22 01:22:05.140455: train_loss -0.7757 +2024-11-22 01:22:05.140681: val_loss -0.7728 +2024-11-22 01:22:05.140761: Pseudo dice [0.8512] +2024-11-22 01:22:05.140841: Epoch time: 18.46 s +2024-11-22 01:22:06.070384: +2024-11-22 01:22:06.070608: Epoch 2737 +2024-11-22 01:22:06.070719: Current learning rate: 0.00686 +2024-11-22 01:22:25.068076: train_loss -0.7803 +2024-11-22 01:22:25.070467: val_loss -0.772 +2024-11-22 01:22:25.070594: Pseudo dice [0.8312] +2024-11-22 01:22:25.070668: Epoch time: 19.0 s +2024-11-22 01:22:25.957357: +2024-11-22 01:22:25.957546: Epoch 2738 +2024-11-22 01:22:25.957652: Current learning rate: 0.00686 +2024-11-22 01:22:44.027974: train_loss -0.7774 +2024-11-22 01:22:44.028237: val_loss -0.775 +2024-11-22 01:22:44.028319: Pseudo dice [0.8444] +2024-11-22 01:22:44.028408: Epoch time: 18.07 s +2024-11-22 01:22:44.875879: +2024-11-22 01:22:44.876095: Epoch 2739 +2024-11-22 01:22:44.876203: Current learning rate: 0.00686 +2024-11-22 01:23:04.512806: train_loss -0.7832 +2024-11-22 01:23:04.513041: val_loss -0.7799 +2024-11-22 01:23:04.513117: Pseudo dice [0.8567] +2024-11-22 01:23:04.513190: Epoch time: 19.64 s +2024-11-22 01:23:05.360716: +2024-11-22 01:23:05.360932: Epoch 2740 +2024-11-22 01:23:05.361050: Current learning rate: 0.00686 +2024-11-22 01:23:23.359483: train_loss -0.7741 +2024-11-22 01:23:23.359699: val_loss -0.7465 +2024-11-22 01:23:23.359774: Pseudo dice [0.8457] +2024-11-22 01:23:23.359846: Epoch time: 18.0 s +2024-11-22 01:23:24.205305: +2024-11-22 01:23:24.205513: Epoch 2741 +2024-11-22 01:23:24.205633: Current learning rate: 0.00686 +2024-11-22 01:23:42.980553: train_loss -0.7965 +2024-11-22 01:23:42.980767: val_loss -0.7558 +2024-11-22 01:23:42.980845: Pseudo dice [0.8537] +2024-11-22 01:23:42.980928: Epoch time: 18.78 s +2024-11-22 01:23:43.824108: +2024-11-22 01:23:43.824318: Epoch 2742 +2024-11-22 01:23:43.824435: Current learning rate: 0.00685 +2024-11-22 01:24:02.302835: train_loss -0.7817 +2024-11-22 01:24:02.303096: val_loss -0.765 +2024-11-22 01:24:02.303172: Pseudo dice [0.8312] +2024-11-22 01:24:02.303253: Epoch time: 18.48 s +2024-11-22 01:24:03.543146: +2024-11-22 01:24:03.543378: Epoch 2743 +2024-11-22 01:24:03.543486: Current learning rate: 0.00685 +2024-11-22 01:24:21.509216: train_loss -0.7766 +2024-11-22 01:24:21.509446: val_loss -0.7544 +2024-11-22 01:24:21.509527: Pseudo dice [0.8365] +2024-11-22 01:24:21.509604: Epoch time: 17.97 s +2024-11-22 01:24:22.355115: +2024-11-22 01:24:22.355360: Epoch 2744 +2024-11-22 01:24:22.355473: Current learning rate: 0.00685 +2024-11-22 01:24:40.622595: train_loss -0.7838 +2024-11-22 01:24:40.622842: val_loss -0.7356 +2024-11-22 01:24:40.622930: Pseudo dice [0.8389] +2024-11-22 01:24:40.623019: Epoch time: 18.27 s +2024-11-22 01:24:41.474374: +2024-11-22 01:24:41.474592: Epoch 2745 +2024-11-22 01:24:41.474699: Current learning rate: 0.00685 +2024-11-22 01:24:59.502478: train_loss -0.782 +2024-11-22 01:24:59.502740: val_loss -0.7828 +2024-11-22 01:24:59.502813: Pseudo dice [0.8308] +2024-11-22 01:24:59.502897: Epoch time: 18.03 s +2024-11-22 01:25:00.393815: +2024-11-22 01:25:00.394035: Epoch 2746 +2024-11-22 01:25:00.394144: Current learning rate: 0.00685 +2024-11-22 01:25:19.441175: train_loss -0.7808 +2024-11-22 01:25:19.441394: val_loss -0.7606 +2024-11-22 01:25:19.441472: Pseudo dice [0.8507] +2024-11-22 01:25:19.441548: Epoch time: 19.05 s +2024-11-22 01:25:20.295194: +2024-11-22 01:25:20.295427: Epoch 2747 +2024-11-22 01:25:20.295533: Current learning rate: 0.00685 +2024-11-22 01:25:39.391832: train_loss -0.7823 +2024-11-22 01:25:39.392944: val_loss -0.7639 +2024-11-22 01:25:39.393041: Pseudo dice [0.8359] +2024-11-22 01:25:39.393120: Epoch time: 19.1 s +2024-11-22 01:25:40.305777: +2024-11-22 01:25:40.305982: Epoch 2748 +2024-11-22 01:25:40.306091: Current learning rate: 0.00685 +2024-11-22 01:25:57.889038: train_loss -0.79 +2024-11-22 01:25:57.889272: val_loss -0.7555 +2024-11-22 01:25:57.889351: Pseudo dice [0.8357] +2024-11-22 01:25:57.889452: Epoch time: 17.58 s +2024-11-22 01:25:58.830019: +2024-11-22 01:25:58.830231: Epoch 2749 +2024-11-22 01:25:58.830339: Current learning rate: 0.00685 +2024-11-22 01:26:17.860905: train_loss -0.7707 +2024-11-22 01:26:17.861225: val_loss -0.7796 +2024-11-22 01:26:17.861320: Pseudo dice [0.8549] +2024-11-22 01:26:17.861410: Epoch time: 19.03 s +2024-11-22 01:26:18.939736: +2024-11-22 01:26:18.939944: Epoch 2750 +2024-11-22 01:26:18.940056: Current learning rate: 0.00684 +2024-11-22 01:26:37.270926: train_loss -0.7856 +2024-11-22 01:26:37.271140: val_loss -0.7522 +2024-11-22 01:26:37.271215: Pseudo dice [0.8516] +2024-11-22 01:26:37.271293: Epoch time: 18.33 s +2024-11-22 01:26:38.115880: +2024-11-22 01:26:38.116140: Epoch 2751 +2024-11-22 01:26:38.116250: Current learning rate: 0.00684 +2024-11-22 01:26:55.907112: train_loss -0.7797 +2024-11-22 01:26:55.907326: val_loss -0.7549 +2024-11-22 01:26:55.907398: Pseudo dice [0.8476] +2024-11-22 01:26:55.907470: Epoch time: 17.79 s +2024-11-22 01:26:56.761624: +2024-11-22 01:26:56.761855: Epoch 2752 +2024-11-22 01:26:56.761976: Current learning rate: 0.00684 +2024-11-22 01:27:14.882110: train_loss -0.7825 +2024-11-22 01:27:14.882365: val_loss -0.7444 +2024-11-22 01:27:14.882442: Pseudo dice [0.8235] +2024-11-22 01:27:14.882525: Epoch time: 18.12 s +2024-11-22 01:27:15.732719: +2024-11-22 01:27:15.732960: Epoch 2753 +2024-11-22 01:27:15.733081: Current learning rate: 0.00684 +2024-11-22 01:27:34.024132: train_loss -0.7796 +2024-11-22 01:27:34.024354: val_loss -0.7607 +2024-11-22 01:27:34.024427: Pseudo dice [0.8614] +2024-11-22 01:27:34.024500: Epoch time: 18.29 s +2024-11-22 01:27:34.872624: +2024-11-22 01:27:34.872854: Epoch 2754 +2024-11-22 01:27:34.872964: Current learning rate: 0.00684 +2024-11-22 01:27:53.293962: train_loss -0.7758 +2024-11-22 01:27:53.294560: val_loss -0.766 +2024-11-22 01:27:53.294658: Pseudo dice [0.8379] +2024-11-22 01:27:53.294736: Epoch time: 18.42 s +2024-11-22 01:27:54.136592: +2024-11-22 01:27:54.136816: Epoch 2755 +2024-11-22 01:27:54.136924: Current learning rate: 0.00684 +2024-11-22 01:28:13.195051: train_loss -0.7807 +2024-11-22 01:28:13.195273: val_loss -0.783 +2024-11-22 01:28:13.195350: Pseudo dice [0.8511] +2024-11-22 01:28:13.195425: Epoch time: 19.06 s +2024-11-22 01:28:14.042689: +2024-11-22 01:28:14.042918: Epoch 2756 +2024-11-22 01:28:14.043034: Current learning rate: 0.00684 +2024-11-22 01:28:31.544053: train_loss -0.7855 +2024-11-22 01:28:31.544296: val_loss -0.748 +2024-11-22 01:28:31.544369: Pseudo dice [0.8391] +2024-11-22 01:28:31.544447: Epoch time: 17.5 s +2024-11-22 01:28:32.393179: +2024-11-22 01:28:32.393408: Epoch 2757 +2024-11-22 01:28:32.393514: Current learning rate: 0.00684 +2024-11-22 01:28:49.649168: train_loss -0.7835 +2024-11-22 01:28:49.649394: val_loss -0.7849 +2024-11-22 01:28:49.649472: Pseudo dice [0.8555] +2024-11-22 01:28:49.649570: Epoch time: 17.26 s +2024-11-22 01:28:50.499133: +2024-11-22 01:28:50.499378: Epoch 2758 +2024-11-22 01:28:50.499493: Current learning rate: 0.00684 +2024-11-22 01:29:09.114863: train_loss -0.7793 +2024-11-22 01:29:09.115332: val_loss -0.7836 +2024-11-22 01:29:09.115415: Pseudo dice [0.8671] +2024-11-22 01:29:09.115489: Epoch time: 18.62 s +2024-11-22 01:29:09.115551: Yayy! New best EMA pseudo Dice: 0.847 +2024-11-22 01:29:10.185339: +2024-11-22 01:29:10.185565: Epoch 2759 +2024-11-22 01:29:10.185677: Current learning rate: 0.00683 +2024-11-22 01:29:29.055459: train_loss -0.7716 +2024-11-22 01:29:29.055753: val_loss -0.7447 +2024-11-22 01:29:29.055829: Pseudo dice [0.8024] +2024-11-22 01:29:29.055913: Epoch time: 18.87 s +2024-11-22 01:29:29.908134: +2024-11-22 01:29:29.908363: Epoch 2760 +2024-11-22 01:29:29.908482: Current learning rate: 0.00683 +2024-11-22 01:29:48.156229: train_loss -0.7754 +2024-11-22 01:29:48.156703: val_loss -0.7455 +2024-11-22 01:29:48.156808: Pseudo dice [0.8236] +2024-11-22 01:29:48.156890: Epoch time: 18.25 s +2024-11-22 01:29:49.002199: +2024-11-22 01:29:49.002658: Epoch 2761 +2024-11-22 01:29:49.002795: Current learning rate: 0.00683 +2024-11-22 01:30:07.145986: train_loss -0.771 +2024-11-22 01:30:07.146274: val_loss -0.7582 +2024-11-22 01:30:07.146353: Pseudo dice [0.8493] +2024-11-22 01:30:07.146429: Epoch time: 18.14 s +2024-11-22 01:30:07.993007: +2024-11-22 01:30:07.993462: Epoch 2762 +2024-11-22 01:30:07.993602: Current learning rate: 0.00683 +2024-11-22 01:30:25.644015: train_loss -0.7805 +2024-11-22 01:30:25.644241: val_loss -0.7751 +2024-11-22 01:30:25.644317: Pseudo dice [0.8589] +2024-11-22 01:30:25.644393: Epoch time: 17.65 s +2024-11-22 01:30:26.493118: +2024-11-22 01:30:26.493536: Epoch 2763 +2024-11-22 01:30:26.493668: Current learning rate: 0.00683 +2024-11-22 01:30:45.633220: train_loss -0.7758 +2024-11-22 01:30:45.633467: val_loss -0.7551 +2024-11-22 01:30:45.633545: Pseudo dice [0.8401] +2024-11-22 01:30:45.633629: Epoch time: 19.14 s +2024-11-22 01:30:46.484689: +2024-11-22 01:30:46.485151: Epoch 2764 +2024-11-22 01:30:46.485286: Current learning rate: 0.00683 +2024-11-22 01:31:05.063591: train_loss -0.7631 +2024-11-22 01:31:05.063815: val_loss -0.7434 +2024-11-22 01:31:05.063890: Pseudo dice [0.834] +2024-11-22 01:31:05.063964: Epoch time: 18.58 s +2024-11-22 01:31:05.991877: +2024-11-22 01:31:05.992297: Epoch 2765 +2024-11-22 01:31:05.992422: Current learning rate: 0.00683 +2024-11-22 01:31:24.440388: train_loss -0.7621 +2024-11-22 01:31:24.440607: val_loss -0.7693 +2024-11-22 01:31:24.440685: Pseudo dice [0.8345] +2024-11-22 01:31:24.440758: Epoch time: 18.45 s +2024-11-22 01:31:25.684908: +2024-11-22 01:31:25.685337: Epoch 2766 +2024-11-22 01:31:25.685465: Current learning rate: 0.00683 +2024-11-22 01:31:43.955091: train_loss -0.7595 +2024-11-22 01:31:43.955359: val_loss -0.7577 +2024-11-22 01:31:43.955681: Pseudo dice [0.8399] +2024-11-22 01:31:43.955776: Epoch time: 18.27 s +2024-11-22 01:31:44.909892: +2024-11-22 01:31:44.910310: Epoch 2767 +2024-11-22 01:31:44.910439: Current learning rate: 0.00682 +2024-11-22 01:32:03.208722: train_loss -0.7645 +2024-11-22 01:32:03.208940: val_loss -0.7508 +2024-11-22 01:32:03.209024: Pseudo dice [0.8349] +2024-11-22 01:32:03.209100: Epoch time: 18.3 s +2024-11-22 01:32:04.049605: +2024-11-22 01:32:04.050057: Epoch 2768 +2024-11-22 01:32:04.050209: Current learning rate: 0.00682 +2024-11-22 01:32:23.003224: train_loss -0.7659 +2024-11-22 01:32:23.003495: val_loss -0.7531 +2024-11-22 01:32:23.003574: Pseudo dice [0.8337] +2024-11-22 01:32:23.003649: Epoch time: 18.95 s +2024-11-22 01:32:23.852917: +2024-11-22 01:32:23.853315: Epoch 2769 +2024-11-22 01:32:23.853451: Current learning rate: 0.00682 +2024-11-22 01:32:42.441967: train_loss -0.7715 +2024-11-22 01:32:42.442206: val_loss -0.7538 +2024-11-22 01:32:42.442279: Pseudo dice [0.8263] +2024-11-22 01:32:42.442910: Epoch time: 18.59 s +2024-11-22 01:32:43.416996: +2024-11-22 01:32:43.417397: Epoch 2770 +2024-11-22 01:32:43.417536: Current learning rate: 0.00682 +2024-11-22 01:33:01.553363: train_loss -0.7704 +2024-11-22 01:33:01.553567: val_loss -0.754 +2024-11-22 01:33:01.553643: Pseudo dice [0.838] +2024-11-22 01:33:01.553720: Epoch time: 18.14 s +2024-11-22 01:33:02.432660: +2024-11-22 01:33:02.433076: Epoch 2771 +2024-11-22 01:33:02.433210: Current learning rate: 0.00682 +2024-11-22 01:33:20.934781: train_loss -0.7614 +2024-11-22 01:33:20.940250: val_loss -0.7505 +2024-11-22 01:33:20.940374: Pseudo dice [0.8279] +2024-11-22 01:33:20.940455: Epoch time: 18.5 s +2024-11-22 01:33:21.821205: +2024-11-22 01:33:21.821626: Epoch 2772 +2024-11-22 01:33:21.821760: Current learning rate: 0.00682 +2024-11-22 01:33:41.055985: train_loss -0.7697 +2024-11-22 01:33:41.056271: val_loss -0.7726 +2024-11-22 01:33:41.056349: Pseudo dice [0.8456] +2024-11-22 01:33:41.056422: Epoch time: 19.24 s +2024-11-22 01:33:41.904852: +2024-11-22 01:33:41.905283: Epoch 2773 +2024-11-22 01:33:41.905420: Current learning rate: 0.00682 +2024-11-22 01:34:00.307898: train_loss -0.7712 +2024-11-22 01:34:00.308149: val_loss -0.7635 +2024-11-22 01:34:00.308230: Pseudo dice [0.8496] +2024-11-22 01:34:00.308311: Epoch time: 18.4 s +2024-11-22 01:34:01.174408: +2024-11-22 01:34:01.174804: Epoch 2774 +2024-11-22 01:34:01.174934: Current learning rate: 0.00682 +2024-11-22 01:34:19.665745: train_loss -0.7843 +2024-11-22 01:34:19.665951: val_loss -0.7538 +2024-11-22 01:34:19.666035: Pseudo dice [0.8363] +2024-11-22 01:34:19.666112: Epoch time: 18.49 s +2024-11-22 01:34:20.505403: +2024-11-22 01:34:20.505861: Epoch 2775 +2024-11-22 01:34:20.506007: Current learning rate: 0.00682 +2024-11-22 01:34:39.228937: train_loss -0.7735 +2024-11-22 01:34:39.234240: val_loss -0.7647 +2024-11-22 01:34:39.234534: Pseudo dice [0.8475] +2024-11-22 01:34:39.234636: Epoch time: 18.72 s +2024-11-22 01:34:40.156148: +2024-11-22 01:34:40.156569: Epoch 2776 +2024-11-22 01:34:40.156701: Current learning rate: 0.00681 +2024-11-22 01:34:58.403161: train_loss -0.766 +2024-11-22 01:34:58.403375: val_loss -0.7724 +2024-11-22 01:34:58.403446: Pseudo dice [0.8353] +2024-11-22 01:34:58.403519: Epoch time: 18.25 s +2024-11-22 01:34:59.255044: +2024-11-22 01:34:59.255373: Epoch 2777 +2024-11-22 01:34:59.255500: Current learning rate: 0.00681 +2024-11-22 01:35:17.934451: train_loss -0.7741 +2024-11-22 01:35:17.934694: val_loss -0.7715 +2024-11-22 01:35:17.934767: Pseudo dice [0.8459] +2024-11-22 01:35:17.934848: Epoch time: 18.68 s +2024-11-22 01:35:19.217140: +2024-11-22 01:35:19.217468: Epoch 2778 +2024-11-22 01:35:19.217577: Current learning rate: 0.00681 +2024-11-22 01:35:37.828764: train_loss -0.772 +2024-11-22 01:35:37.828979: val_loss -0.7735 +2024-11-22 01:35:37.829061: Pseudo dice [0.8417] +2024-11-22 01:35:37.829134: Epoch time: 18.61 s +2024-11-22 01:35:38.689917: +2024-11-22 01:35:38.690144: Epoch 2779 +2024-11-22 01:35:38.690253: Current learning rate: 0.00681 +2024-11-22 01:35:58.731676: train_loss -0.7774 +2024-11-22 01:35:58.731891: val_loss -0.7661 +2024-11-22 01:35:58.731965: Pseudo dice [0.8282] +2024-11-22 01:35:58.732045: Epoch time: 20.04 s +2024-11-22 01:35:59.607924: +2024-11-22 01:35:59.608152: Epoch 2780 +2024-11-22 01:35:59.608263: Current learning rate: 0.00681 +2024-11-22 01:36:17.345771: train_loss -0.7696 +2024-11-22 01:36:17.346019: val_loss -0.755 +2024-11-22 01:36:17.346100: Pseudo dice [0.828] +2024-11-22 01:36:17.346181: Epoch time: 17.74 s +2024-11-22 01:36:18.195369: +2024-11-22 01:36:18.195604: Epoch 2781 +2024-11-22 01:36:18.195714: Current learning rate: 0.00681 +2024-11-22 01:36:35.097554: train_loss -0.7726 +2024-11-22 01:36:35.097767: val_loss -0.7754 +2024-11-22 01:36:35.097846: Pseudo dice [0.8503] +2024-11-22 01:36:35.097927: Epoch time: 16.9 s +2024-11-22 01:36:35.937140: +2024-11-22 01:36:35.937369: Epoch 2782 +2024-11-22 01:36:35.937485: Current learning rate: 0.00681 +2024-11-22 01:36:54.080287: train_loss -0.784 +2024-11-22 01:36:54.080517: val_loss -0.7492 +2024-11-22 01:36:54.080597: Pseudo dice [0.8236] +2024-11-22 01:36:54.080676: Epoch time: 18.14 s +2024-11-22 01:36:54.937875: +2024-11-22 01:36:54.938096: Epoch 2783 +2024-11-22 01:36:54.938207: Current learning rate: 0.00681 +2024-11-22 01:37:13.898885: train_loss -0.7769 +2024-11-22 01:37:13.899150: val_loss -0.7714 +2024-11-22 01:37:13.899231: Pseudo dice [0.8414] +2024-11-22 01:37:13.899305: Epoch time: 18.96 s +2024-11-22 01:37:14.746967: +2024-11-22 01:37:14.747241: Epoch 2784 +2024-11-22 01:37:14.747579: Current learning rate: 0.0068 +2024-11-22 01:37:32.983330: train_loss -0.7732 +2024-11-22 01:37:32.983579: val_loss -0.754 +2024-11-22 01:37:32.983656: Pseudo dice [0.8374] +2024-11-22 01:37:32.983739: Epoch time: 18.24 s +2024-11-22 01:37:33.841544: +2024-11-22 01:37:33.841762: Epoch 2785 +2024-11-22 01:37:33.841870: Current learning rate: 0.0068 +2024-11-22 01:37:52.230949: train_loss -0.7745 +2024-11-22 01:37:52.231177: val_loss -0.772 +2024-11-22 01:37:52.231290: Pseudo dice [0.8467] +2024-11-22 01:37:52.231425: Epoch time: 18.39 s +2024-11-22 01:37:53.082180: +2024-11-22 01:37:53.082412: Epoch 2786 +2024-11-22 01:37:53.082529: Current learning rate: 0.0068 +2024-11-22 01:38:11.124719: train_loss -0.7852 +2024-11-22 01:38:11.125872: val_loss -0.7483 +2024-11-22 01:38:11.125958: Pseudo dice [0.835] +2024-11-22 01:38:11.126039: Epoch time: 18.04 s +2024-11-22 01:38:11.976234: +2024-11-22 01:38:11.976454: Epoch 2787 +2024-11-22 01:38:11.976574: Current learning rate: 0.0068 +2024-11-22 01:38:30.569597: train_loss -0.7719 +2024-11-22 01:38:30.569796: val_loss -0.7665 +2024-11-22 01:38:30.570465: Pseudo dice [0.8229] +2024-11-22 01:38:30.570568: Epoch time: 18.59 s +2024-11-22 01:38:31.481326: +2024-11-22 01:38:31.481529: Epoch 2788 +2024-11-22 01:38:31.481635: Current learning rate: 0.0068 +2024-11-22 01:38:50.549852: train_loss -0.777 +2024-11-22 01:38:50.550095: val_loss -0.7647 +2024-11-22 01:38:50.555373: Pseudo dice [0.8397] +2024-11-22 01:38:50.555511: Epoch time: 19.07 s +2024-11-22 01:38:51.413870: +2024-11-22 01:38:51.414070: Epoch 2789 +2024-11-22 01:38:51.414185: Current learning rate: 0.0068 +2024-11-22 01:39:08.624295: train_loss -0.7749 +2024-11-22 01:39:08.625383: val_loss -0.7922 +2024-11-22 01:39:08.625467: Pseudo dice [0.8578] +2024-11-22 01:39:08.625540: Epoch time: 17.21 s +2024-11-22 01:39:09.996100: +2024-11-22 01:39:09.996322: Epoch 2790 +2024-11-22 01:39:09.996436: Current learning rate: 0.0068 +2024-11-22 01:39:28.580101: train_loss -0.7745 +2024-11-22 01:39:28.580357: val_loss -0.7645 +2024-11-22 01:39:28.580434: Pseudo dice [0.8313] +2024-11-22 01:39:28.580524: Epoch time: 18.58 s +2024-11-22 01:39:29.432617: +2024-11-22 01:39:29.432832: Epoch 2791 +2024-11-22 01:39:29.432940: Current learning rate: 0.0068 +2024-11-22 01:39:48.422666: train_loss -0.7707 +2024-11-22 01:39:48.422894: val_loss -0.7807 +2024-11-22 01:39:48.422972: Pseudo dice [0.8305] +2024-11-22 01:39:48.423057: Epoch time: 18.99 s +2024-11-22 01:39:49.272738: +2024-11-22 01:39:49.272949: Epoch 2792 +2024-11-22 01:39:49.273067: Current learning rate: 0.0068 +2024-11-22 01:40:06.830554: train_loss -0.7756 +2024-11-22 01:40:06.830794: val_loss -0.7599 +2024-11-22 01:40:06.830870: Pseudo dice [0.8411] +2024-11-22 01:40:06.830943: Epoch time: 17.56 s +2024-11-22 01:40:07.697175: +2024-11-22 01:40:07.697381: Epoch 2793 +2024-11-22 01:40:07.697490: Current learning rate: 0.00679 +2024-11-22 01:40:25.531026: train_loss -0.7812 +2024-11-22 01:40:25.531286: val_loss -0.7848 +2024-11-22 01:40:25.531366: Pseudo dice [0.8519] +2024-11-22 01:40:25.531473: Epoch time: 17.83 s +2024-11-22 01:40:26.379377: +2024-11-22 01:40:26.379600: Epoch 2794 +2024-11-22 01:40:26.379709: Current learning rate: 0.00679 +2024-11-22 01:40:44.739361: train_loss -0.7774 +2024-11-22 01:40:44.739575: val_loss -0.7513 +2024-11-22 01:40:44.739648: Pseudo dice [0.8438] +2024-11-22 01:40:44.739719: Epoch time: 18.36 s +2024-11-22 01:40:45.618248: +2024-11-22 01:40:45.618473: Epoch 2795 +2024-11-22 01:40:45.618587: Current learning rate: 0.00679 +2024-11-22 01:41:04.095009: train_loss -0.7811 +2024-11-22 01:41:04.095231: val_loss -0.7707 +2024-11-22 01:41:04.095304: Pseudo dice [0.8572] +2024-11-22 01:41:04.095376: Epoch time: 18.48 s +2024-11-22 01:41:04.950469: +2024-11-22 01:41:04.950710: Epoch 2796 +2024-11-22 01:41:04.950831: Current learning rate: 0.00679 +2024-11-22 01:41:22.407758: train_loss -0.7889 +2024-11-22 01:41:22.408003: val_loss -0.7918 +2024-11-22 01:41:22.408079: Pseudo dice [0.8551] +2024-11-22 01:41:22.408155: Epoch time: 17.46 s +2024-11-22 01:41:23.279593: +2024-11-22 01:41:23.279827: Epoch 2797 +2024-11-22 01:41:23.279940: Current learning rate: 0.00679 +2024-11-22 01:41:41.546305: train_loss -0.7811 +2024-11-22 01:41:41.546525: val_loss -0.7556 +2024-11-22 01:41:41.546602: Pseudo dice [0.8334] +2024-11-22 01:41:41.546684: Epoch time: 18.27 s +2024-11-22 01:41:42.398698: +2024-11-22 01:41:42.398971: Epoch 2798 +2024-11-22 01:41:42.399112: Current learning rate: 0.00679 +2024-11-22 01:42:00.146588: train_loss -0.785 +2024-11-22 01:42:00.146800: val_loss -0.7665 +2024-11-22 01:42:00.146874: Pseudo dice [0.8327] +2024-11-22 01:42:00.146952: Epoch time: 17.75 s +2024-11-22 01:42:00.999848: +2024-11-22 01:42:01.000080: Epoch 2799 +2024-11-22 01:42:01.000198: Current learning rate: 0.00679 +2024-11-22 01:42:19.716852: train_loss -0.7868 +2024-11-22 01:42:19.717077: val_loss -0.7829 +2024-11-22 01:42:19.717149: Pseudo dice [0.8479] +2024-11-22 01:42:19.717221: Epoch time: 18.72 s +2024-11-22 01:42:20.882300: +2024-11-22 01:42:20.882507: Epoch 2800 +2024-11-22 01:42:20.882627: Current learning rate: 0.00679 +2024-11-22 01:42:39.459948: train_loss -0.78 +2024-11-22 01:42:39.460244: val_loss -0.7512 +2024-11-22 01:42:39.460325: Pseudo dice [0.8255] +2024-11-22 01:42:39.460405: Epoch time: 18.58 s +2024-11-22 01:42:40.312934: +2024-11-22 01:42:40.313154: Epoch 2801 +2024-11-22 01:42:40.313262: Current learning rate: 0.00678 +2024-11-22 01:42:59.856376: train_loss -0.7814 +2024-11-22 01:42:59.856859: val_loss -0.7907 +2024-11-22 01:42:59.856963: Pseudo dice [0.8575] +2024-11-22 01:42:59.857055: Epoch time: 19.54 s +2024-11-22 01:43:00.700768: +2024-11-22 01:43:00.700967: Epoch 2802 +2024-11-22 01:43:00.701084: Current learning rate: 0.00678 +2024-11-22 01:43:18.936557: train_loss -0.7763 +2024-11-22 01:43:18.936795: val_loss -0.7639 +2024-11-22 01:43:18.936883: Pseudo dice [0.8522] +2024-11-22 01:43:18.936972: Epoch time: 18.24 s +2024-11-22 01:43:19.801291: +2024-11-22 01:43:19.801566: Epoch 2803 +2024-11-22 01:43:19.801677: Current learning rate: 0.00678 +2024-11-22 01:43:38.453917: train_loss -0.779 +2024-11-22 01:43:38.454130: val_loss -0.7454 +2024-11-22 01:43:38.454249: Pseudo dice [0.8345] +2024-11-22 01:43:38.454327: Epoch time: 18.65 s +2024-11-22 01:43:39.306212: +2024-11-22 01:43:39.306442: Epoch 2804 +2024-11-22 01:43:39.306554: Current learning rate: 0.00678 +2024-11-22 01:43:57.638407: train_loss -0.7773 +2024-11-22 01:43:57.638661: val_loss -0.7518 +2024-11-22 01:43:57.638739: Pseudo dice [0.8573] +2024-11-22 01:43:57.638821: Epoch time: 18.33 s +2024-11-22 01:43:58.491484: +2024-11-22 01:43:58.491699: Epoch 2805 +2024-11-22 01:43:58.491822: Current learning rate: 0.00678 +2024-11-22 01:44:16.218348: train_loss -0.7767 +2024-11-22 01:44:16.218567: val_loss -0.7731 +2024-11-22 01:44:16.218641: Pseudo dice [0.8572] +2024-11-22 01:44:16.218715: Epoch time: 17.73 s +2024-11-22 01:44:17.074970: +2024-11-22 01:44:17.075202: Epoch 2806 +2024-11-22 01:44:17.075313: Current learning rate: 0.00678 +2024-11-22 01:44:34.681607: train_loss -0.7808 +2024-11-22 01:44:34.681904: val_loss -0.7551 +2024-11-22 01:44:34.681987: Pseudo dice [0.8394] +2024-11-22 01:44:34.682072: Epoch time: 17.61 s +2024-11-22 01:44:35.542071: +2024-11-22 01:44:35.542295: Epoch 2807 +2024-11-22 01:44:35.542404: Current learning rate: 0.00678 +2024-11-22 01:44:53.589681: train_loss -0.7812 +2024-11-22 01:44:53.589888: val_loss -0.7906 +2024-11-22 01:44:53.589971: Pseudo dice [0.863] +2024-11-22 01:44:53.590052: Epoch time: 18.05 s +2024-11-22 01:44:54.466928: +2024-11-22 01:44:54.467137: Epoch 2808 +2024-11-22 01:44:54.467252: Current learning rate: 0.00678 +2024-11-22 01:45:12.526964: train_loss -0.7759 +2024-11-22 01:45:12.527274: val_loss -0.7883 +2024-11-22 01:45:12.527358: Pseudo dice [0.8574] +2024-11-22 01:45:12.527445: Epoch time: 18.06 s +2024-11-22 01:45:12.527513: Yayy! New best EMA pseudo Dice: 0.8474 +2024-11-22 01:45:13.624963: +2024-11-22 01:45:13.625239: Epoch 2809 +2024-11-22 01:45:13.625349: Current learning rate: 0.00678 +2024-11-22 01:45:31.207166: train_loss -0.7876 +2024-11-22 01:45:31.208280: val_loss -0.7656 +2024-11-22 01:45:31.208364: Pseudo dice [0.8464] +2024-11-22 01:45:31.208441: Epoch time: 17.58 s +2024-11-22 01:45:32.053549: +2024-11-22 01:45:32.053761: Epoch 2810 +2024-11-22 01:45:32.053871: Current learning rate: 0.00677 +2024-11-22 01:45:49.989104: train_loss -0.7851 +2024-11-22 01:45:49.989321: val_loss -0.7631 +2024-11-22 01:45:49.989402: Pseudo dice [0.8261] +2024-11-22 01:45:49.989475: Epoch time: 17.94 s +2024-11-22 01:45:50.837471: +2024-11-22 01:45:50.837695: Epoch 2811 +2024-11-22 01:45:50.837806: Current learning rate: 0.00677 +2024-11-22 01:46:08.774368: train_loss -0.7748 +2024-11-22 01:46:08.774664: val_loss -0.7834 +2024-11-22 01:46:08.774757: Pseudo dice [0.8384] +2024-11-22 01:46:08.774839: Epoch time: 17.94 s +2024-11-22 01:46:09.628938: +2024-11-22 01:46:09.629144: Epoch 2812 +2024-11-22 01:46:09.629260: Current learning rate: 0.00677 +2024-11-22 01:46:28.118016: train_loss -0.7813 +2024-11-22 01:46:28.118255: val_loss -0.7565 +2024-11-22 01:46:28.118331: Pseudo dice [0.8312] +2024-11-22 01:46:28.118410: Epoch time: 18.49 s +2024-11-22 01:46:29.299315: +2024-11-22 01:46:29.299539: Epoch 2813 +2024-11-22 01:46:29.299647: Current learning rate: 0.00677 +2024-11-22 01:46:47.839921: train_loss -0.7807 +2024-11-22 01:46:47.840162: val_loss -0.7848 +2024-11-22 01:46:47.840243: Pseudo dice [0.8589] +2024-11-22 01:46:47.840320: Epoch time: 18.54 s +2024-11-22 01:46:48.691025: +2024-11-22 01:46:48.691233: Epoch 2814 +2024-11-22 01:46:48.691344: Current learning rate: 0.00677 +2024-11-22 01:47:08.228882: train_loss -0.7724 +2024-11-22 01:47:08.229107: val_loss -0.7665 +2024-11-22 01:47:08.229187: Pseudo dice [0.8442] +2024-11-22 01:47:08.229270: Epoch time: 19.54 s +2024-11-22 01:47:09.076844: +2024-11-22 01:47:09.077069: Epoch 2815 +2024-11-22 01:47:09.077179: Current learning rate: 0.00677 +2024-11-22 01:47:28.497484: train_loss -0.7644 +2024-11-22 01:47:28.497758: val_loss -0.7618 +2024-11-22 01:47:28.497835: Pseudo dice [0.8346] +2024-11-22 01:47:28.497920: Epoch time: 19.42 s +2024-11-22 01:47:29.488494: +2024-11-22 01:47:29.488709: Epoch 2816 +2024-11-22 01:47:29.488821: Current learning rate: 0.00677 +2024-11-22 01:47:47.444293: train_loss -0.7724 +2024-11-22 01:47:47.444568: val_loss -0.7703 +2024-11-22 01:47:47.444648: Pseudo dice [0.8554] +2024-11-22 01:47:47.444725: Epoch time: 17.96 s +2024-11-22 01:47:48.298238: +2024-11-22 01:47:48.298449: Epoch 2817 +2024-11-22 01:47:48.298554: Current learning rate: 0.00677 +2024-11-22 01:48:07.089192: train_loss -0.7782 +2024-11-22 01:48:07.089414: val_loss -0.7558 +2024-11-22 01:48:07.089494: Pseudo dice [0.8409] +2024-11-22 01:48:07.089574: Epoch time: 18.79 s +2024-11-22 01:48:07.937978: +2024-11-22 01:48:07.938249: Epoch 2818 +2024-11-22 01:48:07.938370: Current learning rate: 0.00676 +2024-11-22 01:48:26.158867: train_loss -0.7802 +2024-11-22 01:48:26.159095: val_loss -0.7651 +2024-11-22 01:48:26.161524: Pseudo dice [0.8547] +2024-11-22 01:48:26.161685: Epoch time: 18.22 s +2024-11-22 01:48:27.018261: +2024-11-22 01:48:27.018590: Epoch 2819 +2024-11-22 01:48:27.018712: Current learning rate: 0.00676 +2024-11-22 01:48:44.821599: train_loss -0.7697 +2024-11-22 01:48:44.821889: val_loss -0.7502 +2024-11-22 01:48:44.821974: Pseudo dice [0.8292] +2024-11-22 01:48:44.822058: Epoch time: 17.8 s +2024-11-22 01:48:45.667808: +2024-11-22 01:48:45.668035: Epoch 2820 +2024-11-22 01:48:45.668149: Current learning rate: 0.00676 +2024-11-22 01:49:03.773035: train_loss -0.7741 +2024-11-22 01:49:03.778414: val_loss -0.7526 +2024-11-22 01:49:03.778542: Pseudo dice [0.8383] +2024-11-22 01:49:03.778625: Epoch time: 18.11 s +2024-11-22 01:49:04.642852: +2024-11-22 01:49:04.643101: Epoch 2821 +2024-11-22 01:49:04.643217: Current learning rate: 0.00676 +2024-11-22 01:49:23.251642: train_loss -0.7757 +2024-11-22 01:49:23.251852: val_loss -0.7493 +2024-11-22 01:49:23.251924: Pseudo dice [0.8345] +2024-11-22 01:49:23.252006: Epoch time: 18.61 s +2024-11-22 01:49:24.129929: +2024-11-22 01:49:24.130139: Epoch 2822 +2024-11-22 01:49:24.130251: Current learning rate: 0.00676 +2024-11-22 01:49:42.953840: train_loss -0.7695 +2024-11-22 01:49:42.954089: val_loss -0.7728 +2024-11-22 01:49:42.954167: Pseudo dice [0.8313] +2024-11-22 01:49:42.954248: Epoch time: 18.82 s +2024-11-22 01:49:43.904303: +2024-11-22 01:49:43.904568: Epoch 2823 +2024-11-22 01:49:43.904677: Current learning rate: 0.00676 +2024-11-22 01:50:01.978867: train_loss -0.7815 +2024-11-22 01:50:01.979083: val_loss -0.776 +2024-11-22 01:50:01.979159: Pseudo dice [0.85] +2024-11-22 01:50:01.979243: Epoch time: 18.08 s +2024-11-22 01:50:02.824084: +2024-11-22 01:50:02.824497: Epoch 2824 +2024-11-22 01:50:02.824630: Current learning rate: 0.00676 +2024-11-22 01:50:21.364796: train_loss -0.7835 +2024-11-22 01:50:21.365028: val_loss -0.7774 +2024-11-22 01:50:21.365102: Pseudo dice [0.8471] +2024-11-22 01:50:21.365177: Epoch time: 18.54 s +2024-11-22 01:50:22.653106: +2024-11-22 01:50:22.653323: Epoch 2825 +2024-11-22 01:50:22.653436: Current learning rate: 0.00676 +2024-11-22 01:50:41.845027: train_loss -0.7821 +2024-11-22 01:50:41.845298: val_loss -0.7837 +2024-11-22 01:50:41.845506: Pseudo dice [0.8515] +2024-11-22 01:50:41.845601: Epoch time: 19.19 s +2024-11-22 01:50:42.691900: +2024-11-22 01:50:42.692119: Epoch 2826 +2024-11-22 01:50:42.692236: Current learning rate: 0.00676 +2024-11-22 01:51:00.469986: train_loss -0.7725 +2024-11-22 01:51:00.470213: val_loss -0.7697 +2024-11-22 01:51:00.470290: Pseudo dice [0.8306] +2024-11-22 01:51:00.470364: Epoch time: 17.78 s +2024-11-22 01:51:01.316683: +2024-11-22 01:51:01.316914: Epoch 2827 +2024-11-22 01:51:01.317029: Current learning rate: 0.00675 +2024-11-22 01:51:20.700068: train_loss -0.7523 +2024-11-22 01:51:20.700283: val_loss -0.7562 +2024-11-22 01:51:20.700362: Pseudo dice [0.8498] +2024-11-22 01:51:20.700434: Epoch time: 19.38 s +2024-11-22 01:51:21.578382: +2024-11-22 01:51:21.578611: Epoch 2828 +2024-11-22 01:51:21.578729: Current learning rate: 0.00675 +2024-11-22 01:51:40.314080: train_loss -0.7601 +2024-11-22 01:51:40.314329: val_loss -0.7789 +2024-11-22 01:51:40.314410: Pseudo dice [0.8533] +2024-11-22 01:51:40.314493: Epoch time: 18.74 s +2024-11-22 01:51:41.346959: +2024-11-22 01:51:41.347204: Epoch 2829 +2024-11-22 01:51:41.347316: Current learning rate: 0.00675 +2024-11-22 01:51:59.520539: train_loss -0.7771 +2024-11-22 01:51:59.520771: val_loss -0.7612 +2024-11-22 01:51:59.520847: Pseudo dice [0.8503] +2024-11-22 01:51:59.520924: Epoch time: 18.17 s +2024-11-22 01:52:00.495692: +2024-11-22 01:52:00.495909: Epoch 2830 +2024-11-22 01:52:00.496025: Current learning rate: 0.00675 +2024-11-22 01:52:18.384712: train_loss -0.7844 +2024-11-22 01:52:18.384942: val_loss -0.7492 +2024-11-22 01:52:18.390258: Pseudo dice [0.8493] +2024-11-22 01:52:18.390340: Epoch time: 17.89 s +2024-11-22 01:52:19.247354: +2024-11-22 01:52:19.247582: Epoch 2831 +2024-11-22 01:52:19.247692: Current learning rate: 0.00675 +2024-11-22 01:52:37.806174: train_loss -0.7775 +2024-11-22 01:52:37.806390: val_loss -0.7601 +2024-11-22 01:52:37.806466: Pseudo dice [0.8356] +2024-11-22 01:52:37.806540: Epoch time: 18.56 s +2024-11-22 01:52:38.787788: +2024-11-22 01:52:38.788016: Epoch 2832 +2024-11-22 01:52:38.788124: Current learning rate: 0.00675 +2024-11-22 01:52:57.855228: train_loss -0.7678 +2024-11-22 01:52:57.855498: val_loss -0.7699 +2024-11-22 01:52:57.855581: Pseudo dice [0.8461] +2024-11-22 01:52:57.855666: Epoch time: 19.07 s +2024-11-22 01:52:58.708446: +2024-11-22 01:52:58.708679: Epoch 2833 +2024-11-22 01:52:58.708793: Current learning rate: 0.00675 +2024-11-22 01:53:18.397949: train_loss -0.7701 +2024-11-22 01:53:18.398254: val_loss -0.7896 +2024-11-22 01:53:18.398381: Pseudo dice [0.8468] +2024-11-22 01:53:18.398484: Epoch time: 19.69 s +2024-11-22 01:53:19.250924: +2024-11-22 01:53:19.251141: Epoch 2834 +2024-11-22 01:53:19.251252: Current learning rate: 0.00675 +2024-11-22 01:53:37.382478: train_loss -0.7753 +2024-11-22 01:53:37.382704: val_loss -0.769 +2024-11-22 01:53:37.382781: Pseudo dice [0.8498] +2024-11-22 01:53:37.382855: Epoch time: 18.13 s +2024-11-22 01:53:38.236206: +2024-11-22 01:53:38.236393: Epoch 2835 +2024-11-22 01:53:38.236506: Current learning rate: 0.00675 +2024-11-22 01:53:57.116922: train_loss -0.7876 +2024-11-22 01:53:57.117162: val_loss -0.7624 +2024-11-22 01:53:57.117239: Pseudo dice [0.8428] +2024-11-22 01:53:57.117689: Epoch time: 18.88 s +2024-11-22 01:53:57.973478: +2024-11-22 01:53:57.973676: Epoch 2836 +2024-11-22 01:53:57.973786: Current learning rate: 0.00674 +2024-11-22 01:54:17.400893: train_loss -0.7841 +2024-11-22 01:54:17.401152: val_loss -0.7648 +2024-11-22 01:54:17.401229: Pseudo dice [0.8319] +2024-11-22 01:54:17.401309: Epoch time: 19.43 s +2024-11-22 01:54:18.651231: +2024-11-22 01:54:18.651458: Epoch 2837 +2024-11-22 01:54:18.651566: Current learning rate: 0.00674 +2024-11-22 01:54:36.469291: train_loss -0.7878 +2024-11-22 01:54:36.469512: val_loss -0.775 +2024-11-22 01:54:36.469587: Pseudo dice [0.8347] +2024-11-22 01:54:36.469659: Epoch time: 17.82 s +2024-11-22 01:54:37.319183: +2024-11-22 01:54:37.319401: Epoch 2838 +2024-11-22 01:54:37.319508: Current learning rate: 0.00674 +2024-11-22 01:54:56.616550: train_loss -0.7679 +2024-11-22 01:54:56.616767: val_loss -0.7627 +2024-11-22 01:54:56.616847: Pseudo dice [0.8428] +2024-11-22 01:54:56.616925: Epoch time: 19.3 s +2024-11-22 01:54:57.466618: +2024-11-22 01:54:57.466875: Epoch 2839 +2024-11-22 01:54:57.466985: Current learning rate: 0.00674 +2024-11-22 01:55:14.730044: train_loss -0.784 +2024-11-22 01:55:14.730302: val_loss -0.7527 +2024-11-22 01:55:14.730378: Pseudo dice [0.8525] +2024-11-22 01:55:14.730462: Epoch time: 17.26 s +2024-11-22 01:55:15.779024: +2024-11-22 01:55:15.779240: Epoch 2840 +2024-11-22 01:55:15.779356: Current learning rate: 0.00674 +2024-11-22 01:55:33.894623: train_loss -0.7874 +2024-11-22 01:55:33.894842: val_loss -0.7763 +2024-11-22 01:55:33.894916: Pseudo dice [0.8481] +2024-11-22 01:55:33.895029: Epoch time: 18.12 s +2024-11-22 01:55:34.752849: +2024-11-22 01:55:34.753092: Epoch 2841 +2024-11-22 01:55:34.753202: Current learning rate: 0.00674 +2024-11-22 01:55:52.592273: train_loss -0.7944 +2024-11-22 01:55:52.592495: val_loss -0.7732 +2024-11-22 01:55:52.592571: Pseudo dice [0.8428] +2024-11-22 01:55:52.592650: Epoch time: 17.84 s +2024-11-22 01:55:53.441835: +2024-11-22 01:55:53.442061: Epoch 2842 +2024-11-22 01:55:53.442172: Current learning rate: 0.00674 +2024-11-22 01:56:12.385897: train_loss -0.7882 +2024-11-22 01:56:12.386119: val_loss -0.7851 +2024-11-22 01:56:12.386193: Pseudo dice [0.8513] +2024-11-22 01:56:12.386267: Epoch time: 18.94 s +2024-11-22 01:56:13.295024: +2024-11-22 01:56:13.295233: Epoch 2843 +2024-11-22 01:56:13.295347: Current learning rate: 0.00674 +2024-11-22 01:56:30.867673: train_loss -0.7839 +2024-11-22 01:56:30.867918: val_loss -0.7523 +2024-11-22 01:56:30.868004: Pseudo dice [0.8387] +2024-11-22 01:56:30.868089: Epoch time: 17.57 s +2024-11-22 01:56:31.717987: +2024-11-22 01:56:31.718229: Epoch 2844 +2024-11-22 01:56:31.718340: Current learning rate: 0.00673 +2024-11-22 01:56:50.845265: train_loss -0.7806 +2024-11-22 01:56:50.845481: val_loss -0.7566 +2024-11-22 01:56:50.845557: Pseudo dice [0.8387] +2024-11-22 01:56:50.845632: Epoch time: 19.13 s +2024-11-22 01:56:51.706197: +2024-11-22 01:56:51.706402: Epoch 2845 +2024-11-22 01:56:51.706520: Current learning rate: 0.00673 +2024-11-22 01:57:09.986757: train_loss -0.7861 +2024-11-22 01:57:09.987008: val_loss -0.7698 +2024-11-22 01:57:09.987083: Pseudo dice [0.848] +2024-11-22 01:57:09.987162: Epoch time: 18.28 s +2024-11-22 01:57:10.837311: +2024-11-22 01:57:10.837519: Epoch 2846 +2024-11-22 01:57:10.837629: Current learning rate: 0.00673 +2024-11-22 01:57:28.712776: train_loss -0.7837 +2024-11-22 01:57:28.712996: val_loss -0.7749 +2024-11-22 01:57:28.713075: Pseudo dice [0.8406] +2024-11-22 01:57:28.713156: Epoch time: 17.88 s +2024-11-22 01:57:29.680368: +2024-11-22 01:57:29.680585: Epoch 2847 +2024-11-22 01:57:29.680695: Current learning rate: 0.00673 +2024-11-22 01:57:48.293535: train_loss -0.7765 +2024-11-22 01:57:48.293786: val_loss -0.7711 +2024-11-22 01:57:48.293866: Pseudo dice [0.8503] +2024-11-22 01:57:48.293946: Epoch time: 18.61 s +2024-11-22 01:57:49.396476: +2024-11-22 01:57:49.396703: Epoch 2848 +2024-11-22 01:57:49.396812: Current learning rate: 0.00673 +2024-11-22 01:58:07.482019: train_loss -0.7824 +2024-11-22 01:58:07.482244: val_loss -0.7709 +2024-11-22 01:58:07.482319: Pseudo dice [0.8442] +2024-11-22 01:58:07.482396: Epoch time: 18.09 s +2024-11-22 01:58:08.724532: +2024-11-22 01:58:08.724754: Epoch 2849 +2024-11-22 01:58:08.724868: Current learning rate: 0.00673 +2024-11-22 01:58:27.164047: train_loss -0.7837 +2024-11-22 01:58:27.164305: val_loss -0.7697 +2024-11-22 01:58:27.164382: Pseudo dice [0.8397] +2024-11-22 01:58:27.164485: Epoch time: 18.44 s +2024-11-22 01:58:28.250844: +2024-11-22 01:58:28.251068: Epoch 2850 +2024-11-22 01:58:28.251185: Current learning rate: 0.00673 +2024-11-22 01:58:47.312582: train_loss -0.775 +2024-11-22 01:58:47.312811: val_loss -0.7695 +2024-11-22 01:58:47.312886: Pseudo dice [0.8412] +2024-11-22 01:58:47.312959: Epoch time: 19.06 s +2024-11-22 01:58:48.173106: +2024-11-22 01:58:48.173345: Epoch 2851 +2024-11-22 01:58:48.173461: Current learning rate: 0.00673 +2024-11-22 01:59:06.128256: train_loss -0.7789 +2024-11-22 01:59:06.133666: val_loss -0.7742 +2024-11-22 01:59:06.133834: Pseudo dice [0.8455] +2024-11-22 01:59:06.133918: Epoch time: 17.96 s +2024-11-22 01:59:07.014364: +2024-11-22 01:59:07.014571: Epoch 2852 +2024-11-22 01:59:07.014681: Current learning rate: 0.00673 +2024-11-22 01:59:24.877854: train_loss -0.7936 +2024-11-22 01:59:24.878117: val_loss -0.759 +2024-11-22 01:59:24.878193: Pseudo dice [0.8326] +2024-11-22 01:59:24.878279: Epoch time: 17.86 s +2024-11-22 01:59:25.746747: +2024-11-22 01:59:25.746949: Epoch 2853 +2024-11-22 01:59:25.747064: Current learning rate: 0.00672 +2024-11-22 01:59:43.485244: train_loss -0.7859 +2024-11-22 01:59:43.485448: val_loss -0.7804 +2024-11-22 01:59:43.487504: Pseudo dice [0.8427] +2024-11-22 01:59:43.489808: Epoch time: 17.74 s +2024-11-22 01:59:44.353514: +2024-11-22 01:59:44.353734: Epoch 2854 +2024-11-22 01:59:44.353851: Current learning rate: 0.00672 +2024-11-22 02:00:02.429975: train_loss -0.7803 +2024-11-22 02:00:02.430204: val_loss -0.7876 +2024-11-22 02:00:02.430283: Pseudo dice [0.8495] +2024-11-22 02:00:02.430358: Epoch time: 18.08 s +2024-11-22 02:00:03.437958: +2024-11-22 02:00:03.438215: Epoch 2855 +2024-11-22 02:00:03.438348: Current learning rate: 0.00672 +2024-11-22 02:00:21.998655: train_loss -0.7775 +2024-11-22 02:00:21.998930: val_loss -0.7794 +2024-11-22 02:00:21.999018: Pseudo dice [0.8469] +2024-11-22 02:00:21.999091: Epoch time: 18.56 s +2024-11-22 02:00:22.842041: +2024-11-22 02:00:22.842240: Epoch 2856 +2024-11-22 02:00:22.842355: Current learning rate: 0.00672 +2024-11-22 02:00:40.883597: train_loss -0.7866 +2024-11-22 02:00:40.883818: val_loss -0.7554 +2024-11-22 02:00:40.883912: Pseudo dice [0.8286] +2024-11-22 02:00:40.884053: Epoch time: 18.04 s +2024-11-22 02:00:41.735837: +2024-11-22 02:00:41.736040: Epoch 2857 +2024-11-22 02:00:41.736149: Current learning rate: 0.00672 +2024-11-22 02:01:00.639109: train_loss -0.7808 +2024-11-22 02:01:00.639347: val_loss -0.7587 +2024-11-22 02:01:00.639422: Pseudo dice [0.833] +2024-11-22 02:01:00.639496: Epoch time: 18.9 s +2024-11-22 02:01:01.484815: +2024-11-22 02:01:01.485004: Epoch 2858 +2024-11-22 02:01:01.485116: Current learning rate: 0.00672 +2024-11-22 02:01:19.253869: train_loss -0.7781 +2024-11-22 02:01:19.254092: val_loss -0.7546 +2024-11-22 02:01:19.254191: Pseudo dice [0.8362] +2024-11-22 02:01:19.254269: Epoch time: 17.77 s +2024-11-22 02:01:20.117452: +2024-11-22 02:01:20.117676: Epoch 2859 +2024-11-22 02:01:20.117785: Current learning rate: 0.00672 +2024-11-22 02:01:39.018400: train_loss -0.7792 +2024-11-22 02:01:39.018621: val_loss -0.7715 +2024-11-22 02:01:39.018693: Pseudo dice [0.8487] +2024-11-22 02:01:39.018766: Epoch time: 18.9 s +2024-11-22 02:01:40.051975: +2024-11-22 02:01:40.052200: Epoch 2860 +2024-11-22 02:01:40.052316: Current learning rate: 0.00672 +2024-11-22 02:01:58.010294: train_loss -0.7759 +2024-11-22 02:01:58.012981: val_loss -0.7782 +2024-11-22 02:01:58.013096: Pseudo dice [0.8554] +2024-11-22 02:01:58.013177: Epoch time: 17.96 s +2024-11-22 02:01:59.091413: +2024-11-22 02:01:59.091640: Epoch 2861 +2024-11-22 02:01:59.091751: Current learning rate: 0.00671 +2024-11-22 02:02:16.584361: train_loss -0.781 +2024-11-22 02:02:16.584576: val_loss -0.7594 +2024-11-22 02:02:16.584656: Pseudo dice [0.8413] +2024-11-22 02:02:16.584839: Epoch time: 17.49 s +2024-11-22 02:02:17.447652: +2024-11-22 02:02:17.447931: Epoch 2862 +2024-11-22 02:02:17.448055: Current learning rate: 0.00671 +2024-11-22 02:02:35.798548: train_loss -0.7744 +2024-11-22 02:02:35.798789: val_loss -0.7764 +2024-11-22 02:02:35.798865: Pseudo dice [0.8492] +2024-11-22 02:02:35.798939: Epoch time: 18.35 s +2024-11-22 02:02:36.811399: +2024-11-22 02:02:36.811623: Epoch 2863 +2024-11-22 02:02:36.811738: Current learning rate: 0.00671 +2024-11-22 02:02:55.689948: train_loss -0.7874 +2024-11-22 02:02:55.690290: val_loss -0.768 +2024-11-22 02:02:55.690370: Pseudo dice [0.848] +2024-11-22 02:02:55.690455: Epoch time: 18.88 s +2024-11-22 02:02:56.567916: +2024-11-22 02:02:56.568130: Epoch 2864 +2024-11-22 02:02:56.568236: Current learning rate: 0.00671 +2024-11-22 02:03:15.554598: train_loss -0.7841 +2024-11-22 02:03:15.554818: val_loss -0.759 +2024-11-22 02:03:15.554895: Pseudo dice [0.8373] +2024-11-22 02:03:15.555035: Epoch time: 18.99 s +2024-11-22 02:03:16.426059: +2024-11-22 02:03:16.426278: Epoch 2865 +2024-11-22 02:03:16.426386: Current learning rate: 0.00671 +2024-11-22 02:03:36.061390: train_loss -0.7833 +2024-11-22 02:03:36.061605: val_loss -0.7611 +2024-11-22 02:03:36.061681: Pseudo dice [0.8352] +2024-11-22 02:03:36.061755: Epoch time: 19.64 s +2024-11-22 02:03:37.054476: +2024-11-22 02:03:37.054679: Epoch 2866 +2024-11-22 02:03:37.054790: Current learning rate: 0.00671 +2024-11-22 02:03:56.206758: train_loss -0.7873 +2024-11-22 02:03:56.207032: val_loss -0.7667 +2024-11-22 02:03:56.207109: Pseudo dice [0.8335] +2024-11-22 02:03:56.207184: Epoch time: 19.15 s +2024-11-22 02:03:57.067919: +2024-11-22 02:03:57.068151: Epoch 2867 +2024-11-22 02:03:57.068264: Current learning rate: 0.00671 +2024-11-22 02:04:15.248693: train_loss -0.7866 +2024-11-22 02:04:15.248908: val_loss -0.7587 +2024-11-22 02:04:15.248986: Pseudo dice [0.8484] +2024-11-22 02:04:15.249069: Epoch time: 18.18 s +2024-11-22 02:04:16.102149: +2024-11-22 02:04:16.102358: Epoch 2868 +2024-11-22 02:04:16.102465: Current learning rate: 0.00671 +2024-11-22 02:04:34.061885: train_loss -0.7705 +2024-11-22 02:04:34.064310: val_loss -0.7819 +2024-11-22 02:04:34.064437: Pseudo dice [0.8552] +2024-11-22 02:04:34.064523: Epoch time: 17.96 s +2024-11-22 02:04:34.928767: +2024-11-22 02:04:34.929002: Epoch 2869 +2024-11-22 02:04:34.929110: Current learning rate: 0.00671 +2024-11-22 02:04:53.323102: train_loss -0.7711 +2024-11-22 02:04:53.323407: val_loss -0.7639 +2024-11-22 02:04:53.323487: Pseudo dice [0.8407] +2024-11-22 02:04:53.323561: Epoch time: 18.4 s +2024-11-22 02:04:54.177418: +2024-11-22 02:04:54.177608: Epoch 2870 +2024-11-22 02:04:54.177717: Current learning rate: 0.0067 +2024-11-22 02:05:12.099787: train_loss -0.7837 +2024-11-22 02:05:12.100011: val_loss -0.7649 +2024-11-22 02:05:12.100086: Pseudo dice [0.8514] +2024-11-22 02:05:12.100162: Epoch time: 17.92 s +2024-11-22 02:05:12.949754: +2024-11-22 02:05:12.949969: Epoch 2871 +2024-11-22 02:05:12.950085: Current learning rate: 0.0067 +2024-11-22 02:05:32.072548: train_loss -0.7839 +2024-11-22 02:05:32.074018: val_loss -0.7437 +2024-11-22 02:05:32.074114: Pseudo dice [0.8441] +2024-11-22 02:05:32.074199: Epoch time: 19.12 s +2024-11-22 02:05:33.435803: +2024-11-22 02:05:33.436026: Epoch 2872 +2024-11-22 02:05:33.436135: Current learning rate: 0.0067 +2024-11-22 02:05:52.009400: train_loss -0.7884 +2024-11-22 02:05:52.009604: val_loss -0.7605 +2024-11-22 02:05:52.009674: Pseudo dice [0.8533] +2024-11-22 02:05:52.009746: Epoch time: 18.57 s +2024-11-22 02:05:52.869334: +2024-11-22 02:05:52.869569: Epoch 2873 +2024-11-22 02:05:52.869681: Current learning rate: 0.0067 +2024-11-22 02:06:11.918096: train_loss -0.783 +2024-11-22 02:06:11.918307: val_loss -0.7751 +2024-11-22 02:06:11.918383: Pseudo dice [0.8457] +2024-11-22 02:06:11.918459: Epoch time: 19.05 s +2024-11-22 02:06:12.793694: +2024-11-22 02:06:12.794062: Epoch 2874 +2024-11-22 02:06:12.794171: Current learning rate: 0.0067 +2024-11-22 02:06:31.804786: train_loss -0.7827 +2024-11-22 02:06:31.805088: val_loss -0.782 +2024-11-22 02:06:31.806796: Pseudo dice [0.8506] +2024-11-22 02:06:31.806921: Epoch time: 19.01 s +2024-11-22 02:06:32.671179: +2024-11-22 02:06:32.671399: Epoch 2875 +2024-11-22 02:06:32.671520: Current learning rate: 0.0067 +2024-11-22 02:06:50.642808: train_loss -0.7878 +2024-11-22 02:06:50.643034: val_loss -0.7639 +2024-11-22 02:06:50.643121: Pseudo dice [0.8335] +2024-11-22 02:06:50.643198: Epoch time: 17.97 s +2024-11-22 02:06:51.515583: +2024-11-22 02:06:51.515803: Epoch 2876 +2024-11-22 02:06:51.515915: Current learning rate: 0.0067 +2024-11-22 02:07:10.340595: train_loss -0.7745 +2024-11-22 02:07:10.340809: val_loss -0.7812 +2024-11-22 02:07:10.340883: Pseudo dice [0.8577] +2024-11-22 02:07:10.340957: Epoch time: 18.83 s +2024-11-22 02:07:11.195214: +2024-11-22 02:07:11.195428: Epoch 2877 +2024-11-22 02:07:11.195539: Current learning rate: 0.0067 +2024-11-22 02:07:30.020695: train_loss -0.7791 +2024-11-22 02:07:30.022649: val_loss -0.7485 +2024-11-22 02:07:30.022741: Pseudo dice [0.8363] +2024-11-22 02:07:30.022815: Epoch time: 18.83 s +2024-11-22 02:07:30.878059: +2024-11-22 02:07:30.878284: Epoch 2878 +2024-11-22 02:07:30.878406: Current learning rate: 0.00669 +2024-11-22 02:07:49.620934: train_loss -0.7794 +2024-11-22 02:07:49.621223: val_loss -0.7765 +2024-11-22 02:07:49.621306: Pseudo dice [0.8387] +2024-11-22 02:07:49.621399: Epoch time: 18.74 s +2024-11-22 02:07:50.623593: +2024-11-22 02:07:50.623974: Epoch 2879 +2024-11-22 02:07:50.624092: Current learning rate: 0.00669 +2024-11-22 02:08:09.342738: train_loss -0.7794 +2024-11-22 02:08:09.342953: val_loss -0.7744 +2024-11-22 02:08:09.343037: Pseudo dice [0.8542] +2024-11-22 02:08:09.343109: Epoch time: 18.72 s +2024-11-22 02:08:10.208684: +2024-11-22 02:08:10.208896: Epoch 2880 +2024-11-22 02:08:10.209005: Current learning rate: 0.00669 +2024-11-22 02:08:27.616559: train_loss -0.7817 +2024-11-22 02:08:27.618957: val_loss -0.7861 +2024-11-22 02:08:27.619082: Pseudo dice [0.8597] +2024-11-22 02:08:27.619158: Epoch time: 17.41 s +2024-11-22 02:08:28.524125: +2024-11-22 02:08:28.524359: Epoch 2881 +2024-11-22 02:08:28.524478: Current learning rate: 0.00669 +2024-11-22 02:08:46.655032: train_loss -0.776 +2024-11-22 02:08:46.655248: val_loss -0.7739 +2024-11-22 02:08:46.655349: Pseudo dice [0.8501] +2024-11-22 02:08:46.655428: Epoch time: 18.13 s +2024-11-22 02:08:47.510797: +2024-11-22 02:08:47.511206: Epoch 2882 +2024-11-22 02:08:47.511338: Current learning rate: 0.00669 +2024-11-22 02:09:06.475474: train_loss -0.7847 +2024-11-22 02:09:06.475718: val_loss -0.7948 +2024-11-22 02:09:06.475792: Pseudo dice [0.8757] +2024-11-22 02:09:06.475870: Epoch time: 18.97 s +2024-11-22 02:09:06.475932: Yayy! New best EMA pseudo Dice: 0.8499 +2024-11-22 02:09:07.967368: +2024-11-22 02:09:07.967687: Epoch 2883 +2024-11-22 02:09:07.967813: Current learning rate: 0.00669 +2024-11-22 02:09:26.735796: train_loss -0.7817 +2024-11-22 02:09:26.736039: val_loss -0.7674 +2024-11-22 02:09:26.736120: Pseudo dice [0.8301] +2024-11-22 02:09:26.736195: Epoch time: 18.77 s +2024-11-22 02:09:27.584523: +2024-11-22 02:09:27.584723: Epoch 2884 +2024-11-22 02:09:27.584835: Current learning rate: 0.00669 +2024-11-22 02:09:45.331246: train_loss -0.7845 +2024-11-22 02:09:45.331482: val_loss -0.7397 +2024-11-22 02:09:45.331558: Pseudo dice [0.8304] +2024-11-22 02:09:45.331637: Epoch time: 17.75 s +2024-11-22 02:09:46.186474: +2024-11-22 02:09:46.186689: Epoch 2885 +2024-11-22 02:09:46.186796: Current learning rate: 0.00669 +2024-11-22 02:10:05.386252: train_loss -0.7788 +2024-11-22 02:10:05.386577: val_loss -0.759 +2024-11-22 02:10:05.386659: Pseudo dice [0.8667] +2024-11-22 02:10:05.386739: Epoch time: 19.2 s +2024-11-22 02:10:06.246882: +2024-11-22 02:10:06.247116: Epoch 2886 +2024-11-22 02:10:06.247226: Current learning rate: 0.00669 +2024-11-22 02:10:23.964157: train_loss -0.7802 +2024-11-22 02:10:23.964390: val_loss -0.7698 +2024-11-22 02:10:23.964465: Pseudo dice [0.8405] +2024-11-22 02:10:23.964555: Epoch time: 17.72 s +2024-11-22 02:10:24.914036: +2024-11-22 02:10:24.914253: Epoch 2887 +2024-11-22 02:10:24.914371: Current learning rate: 0.00668 +2024-11-22 02:10:43.884300: train_loss -0.7818 +2024-11-22 02:10:43.884815: val_loss -0.7449 +2024-11-22 02:10:43.884901: Pseudo dice [0.8362] +2024-11-22 02:10:43.884977: Epoch time: 18.97 s +2024-11-22 02:10:44.742056: +2024-11-22 02:10:44.742341: Epoch 2888 +2024-11-22 02:10:44.742453: Current learning rate: 0.00668 +2024-11-22 02:11:02.682271: train_loss -0.7919 +2024-11-22 02:11:02.682496: val_loss -0.7671 +2024-11-22 02:11:02.682573: Pseudo dice [0.8415] +2024-11-22 02:11:02.682650: Epoch time: 17.94 s +2024-11-22 02:11:03.538034: +2024-11-22 02:11:03.538224: Epoch 2889 +2024-11-22 02:11:03.538330: Current learning rate: 0.00668 +2024-11-22 02:11:21.745017: train_loss -0.7787 +2024-11-22 02:11:21.747442: val_loss -0.7667 +2024-11-22 02:11:21.747569: Pseudo dice [0.836] +2024-11-22 02:11:21.747658: Epoch time: 18.21 s +2024-11-22 02:11:22.882011: +2024-11-22 02:11:22.882223: Epoch 2890 +2024-11-22 02:11:22.882331: Current learning rate: 0.00668 +2024-11-22 02:11:41.472749: train_loss -0.7683 +2024-11-22 02:11:41.472966: val_loss -0.7526 +2024-11-22 02:11:41.473050: Pseudo dice [0.8303] +2024-11-22 02:11:41.473133: Epoch time: 18.59 s +2024-11-22 02:11:42.321294: +2024-11-22 02:11:42.321506: Epoch 2891 +2024-11-22 02:11:42.321612: Current learning rate: 0.00668 +2024-11-22 02:11:59.759428: train_loss -0.7691 +2024-11-22 02:11:59.759689: val_loss -0.7299 +2024-11-22 02:11:59.759764: Pseudo dice [0.8308] +2024-11-22 02:11:59.759887: Epoch time: 17.44 s +2024-11-22 02:12:00.615421: +2024-11-22 02:12:00.615630: Epoch 2892 +2024-11-22 02:12:00.615739: Current learning rate: 0.00668 +2024-11-22 02:12:18.756639: train_loss -0.7856 +2024-11-22 02:12:18.756892: val_loss -0.781 +2024-11-22 02:12:18.756973: Pseudo dice [0.8428] +2024-11-22 02:12:18.757066: Epoch time: 18.14 s +2024-11-22 02:12:19.633601: +2024-11-22 02:12:19.633857: Epoch 2893 +2024-11-22 02:12:19.633966: Current learning rate: 0.00668 +2024-11-22 02:12:37.772856: train_loss -0.7845 +2024-11-22 02:12:37.773072: val_loss -0.7649 +2024-11-22 02:12:37.773146: Pseudo dice [0.849] +2024-11-22 02:12:37.773219: Epoch time: 18.14 s +2024-11-22 02:12:38.619310: +2024-11-22 02:12:38.619537: Epoch 2894 +2024-11-22 02:12:38.619645: Current learning rate: 0.00668 +2024-11-22 02:12:57.624326: train_loss -0.7728 +2024-11-22 02:12:57.629249: val_loss -0.7635 +2024-11-22 02:12:57.629385: Pseudo dice [0.8294] +2024-11-22 02:12:57.629468: Epoch time: 19.01 s +2024-11-22 02:12:58.912024: +2024-11-22 02:12:58.912314: Epoch 2895 +2024-11-22 02:12:58.912429: Current learning rate: 0.00667 +2024-11-22 02:13:16.453462: train_loss -0.7807 +2024-11-22 02:13:16.453721: val_loss -0.7617 +2024-11-22 02:13:16.453801: Pseudo dice [0.8173] +2024-11-22 02:13:16.453887: Epoch time: 17.54 s +2024-11-22 02:13:17.303421: +2024-11-22 02:13:17.303643: Epoch 2896 +2024-11-22 02:13:17.303759: Current learning rate: 0.00667 +2024-11-22 02:13:35.369514: train_loss -0.7717 +2024-11-22 02:13:35.369748: val_loss -0.771 +2024-11-22 02:13:35.369828: Pseudo dice [0.8381] +2024-11-22 02:13:35.369903: Epoch time: 18.07 s +2024-11-22 02:13:36.226496: +2024-11-22 02:13:36.226736: Epoch 2897 +2024-11-22 02:13:36.226853: Current learning rate: 0.00667 +2024-11-22 02:13:54.479743: train_loss -0.7865 +2024-11-22 02:13:54.480010: val_loss -0.7581 +2024-11-22 02:13:54.480094: Pseudo dice [0.8373] +2024-11-22 02:13:54.480174: Epoch time: 18.25 s +2024-11-22 02:13:55.445981: +2024-11-22 02:13:55.446221: Epoch 2898 +2024-11-22 02:13:55.446332: Current learning rate: 0.00667 +2024-11-22 02:14:13.960638: train_loss -0.7634 +2024-11-22 02:14:13.960874: val_loss -0.7303 +2024-11-22 02:14:13.960950: Pseudo dice [0.8345] +2024-11-22 02:14:13.961036: Epoch time: 18.52 s +2024-11-22 02:14:14.818887: +2024-11-22 02:14:14.819098: Epoch 2899 +2024-11-22 02:14:14.819207: Current learning rate: 0.00667 +2024-11-22 02:14:33.041205: train_loss -0.7707 +2024-11-22 02:14:33.041439: val_loss -0.7725 +2024-11-22 02:14:33.041511: Pseudo dice [0.8319] +2024-11-22 02:14:33.041587: Epoch time: 18.22 s +2024-11-22 02:14:34.124966: +2024-11-22 02:14:34.125201: Epoch 2900 +2024-11-22 02:14:34.125313: Current learning rate: 0.00667 +2024-11-22 02:14:53.264376: train_loss -0.7706 +2024-11-22 02:14:53.264626: val_loss -0.7624 +2024-11-22 02:14:53.264702: Pseudo dice [0.826] +2024-11-22 02:14:53.264779: Epoch time: 19.14 s +2024-11-22 02:14:54.113511: +2024-11-22 02:14:54.113744: Epoch 2901 +2024-11-22 02:14:54.113854: Current learning rate: 0.00667 +2024-11-22 02:15:12.487578: train_loss -0.7843 +2024-11-22 02:15:12.487797: val_loss -0.7421 +2024-11-22 02:15:12.487869: Pseudo dice [0.8345] +2024-11-22 02:15:12.487942: Epoch time: 18.37 s +2024-11-22 02:15:13.368882: +2024-11-22 02:15:13.369101: Epoch 2902 +2024-11-22 02:15:13.369214: Current learning rate: 0.00667 +2024-11-22 02:15:32.067744: train_loss -0.7823 +2024-11-22 02:15:32.067997: val_loss -0.7807 +2024-11-22 02:15:32.068074: Pseudo dice [0.8455] +2024-11-22 02:15:32.068162: Epoch time: 18.7 s +2024-11-22 02:15:33.041152: +2024-11-22 02:15:33.041342: Epoch 2903 +2024-11-22 02:15:33.041455: Current learning rate: 0.00667 +2024-11-22 02:15:51.433489: train_loss -0.7787 +2024-11-22 02:15:51.433705: val_loss -0.7494 +2024-11-22 02:15:51.433783: Pseudo dice [0.8163] +2024-11-22 02:15:51.433859: Epoch time: 18.39 s +2024-11-22 02:15:52.290059: +2024-11-22 02:15:52.290282: Epoch 2904 +2024-11-22 02:15:52.290398: Current learning rate: 0.00666 +2024-11-22 02:16:11.224944: train_loss -0.7839 +2024-11-22 02:16:11.225169: val_loss -0.7671 +2024-11-22 02:16:11.225245: Pseudo dice [0.8581] +2024-11-22 02:16:11.225321: Epoch time: 18.94 s +2024-11-22 02:16:12.080725: +2024-11-22 02:16:12.080940: Epoch 2905 +2024-11-22 02:16:12.081059: Current learning rate: 0.00666 +2024-11-22 02:16:31.440302: train_loss -0.7723 +2024-11-22 02:16:31.445657: val_loss -0.7635 +2024-11-22 02:16:31.445750: Pseudo dice [0.8393] +2024-11-22 02:16:31.445833: Epoch time: 19.36 s +2024-11-22 02:16:32.444277: +2024-11-22 02:16:32.444536: Epoch 2906 +2024-11-22 02:16:32.444661: Current learning rate: 0.00666 +2024-11-22 02:16:51.117358: train_loss -0.7674 +2024-11-22 02:16:51.123029: val_loss -0.7325 +2024-11-22 02:16:51.123147: Pseudo dice [0.8158] +2024-11-22 02:16:51.123230: Epoch time: 18.67 s +2024-11-22 02:16:52.011411: +2024-11-22 02:16:52.011625: Epoch 2907 +2024-11-22 02:16:52.011739: Current learning rate: 0.00666 +2024-11-22 02:17:09.931204: train_loss -0.7595 +2024-11-22 02:17:09.931414: val_loss -0.7618 +2024-11-22 02:17:09.931493: Pseudo dice [0.8177] +2024-11-22 02:17:09.931600: Epoch time: 17.92 s +2024-11-22 02:17:10.783851: +2024-11-22 02:17:10.784074: Epoch 2908 +2024-11-22 02:17:10.784182: Current learning rate: 0.00666 +2024-11-22 02:17:29.242264: train_loss -0.7547 +2024-11-22 02:17:29.242485: val_loss -0.7628 +2024-11-22 02:17:29.242591: Pseudo dice [0.8449] +2024-11-22 02:17:29.242671: Epoch time: 18.46 s +2024-11-22 02:17:30.093256: +2024-11-22 02:17:30.093535: Epoch 2909 +2024-11-22 02:17:30.093647: Current learning rate: 0.00666 +2024-11-22 02:17:48.215928: train_loss -0.7556 +2024-11-22 02:17:48.216205: val_loss -0.732 +2024-11-22 02:17:48.216284: Pseudo dice [0.8224] +2024-11-22 02:17:48.216478: Epoch time: 18.12 s +2024-11-22 02:17:49.252192: +2024-11-22 02:17:49.252414: Epoch 2910 +2024-11-22 02:17:49.252525: Current learning rate: 0.00666 +2024-11-22 02:18:07.820482: train_loss -0.7677 +2024-11-22 02:18:07.820699: val_loss -0.7504 +2024-11-22 02:18:07.820778: Pseudo dice [0.8399] +2024-11-22 02:18:07.820856: Epoch time: 18.57 s +2024-11-22 02:18:08.672291: +2024-11-22 02:18:08.672508: Epoch 2911 +2024-11-22 02:18:08.672622: Current learning rate: 0.00666 +2024-11-22 02:18:25.891952: train_loss -0.7693 +2024-11-22 02:18:25.892177: val_loss -0.748 +2024-11-22 02:18:25.892252: Pseudo dice [0.8296] +2024-11-22 02:18:25.892328: Epoch time: 17.22 s +2024-11-22 02:18:26.753596: +2024-11-22 02:18:26.753955: Epoch 2912 +2024-11-22 02:18:26.754069: Current learning rate: 0.00665 +2024-11-22 02:18:45.424268: train_loss -0.7745 +2024-11-22 02:18:45.424508: val_loss -0.7702 +2024-11-22 02:18:45.424629: Pseudo dice [0.8446] +2024-11-22 02:18:45.424732: Epoch time: 18.67 s +2024-11-22 02:18:46.280502: +2024-11-22 02:18:46.280766: Epoch 2913 +2024-11-22 02:18:46.280881: Current learning rate: 0.00665 +2024-11-22 02:19:04.619584: train_loss -0.7881 +2024-11-22 02:19:04.619841: val_loss -0.7552 +2024-11-22 02:19:04.619925: Pseudo dice [0.8614] +2024-11-22 02:19:04.620011: Epoch time: 18.34 s +2024-11-22 02:19:05.472222: +2024-11-22 02:19:05.472439: Epoch 2914 +2024-11-22 02:19:05.472547: Current learning rate: 0.00665 +2024-11-22 02:19:23.573676: train_loss -0.781 +2024-11-22 02:19:23.573893: val_loss -0.7786 +2024-11-22 02:19:23.573970: Pseudo dice [0.8364] +2024-11-22 02:19:23.574054: Epoch time: 18.1 s +2024-11-22 02:19:24.430888: +2024-11-22 02:19:24.431104: Epoch 2915 +2024-11-22 02:19:24.431214: Current learning rate: 0.00665 +2024-11-22 02:19:42.379014: train_loss -0.7776 +2024-11-22 02:19:42.379238: val_loss -0.7632 +2024-11-22 02:19:42.379314: Pseudo dice [0.8398] +2024-11-22 02:19:42.379389: Epoch time: 17.95 s +2024-11-22 02:19:43.241964: +2024-11-22 02:19:43.242198: Epoch 2916 +2024-11-22 02:19:43.242320: Current learning rate: 0.00665 +2024-11-22 02:20:02.039047: train_loss -0.7616 +2024-11-22 02:20:02.039275: val_loss -0.773 +2024-11-22 02:20:02.039352: Pseudo dice [0.8491] +2024-11-22 02:20:02.039433: Epoch time: 18.8 s +2024-11-22 02:20:02.900494: +2024-11-22 02:20:02.900709: Epoch 2917 +2024-11-22 02:20:02.900881: Current learning rate: 0.00665 +2024-11-22 02:20:21.553660: train_loss -0.7672 +2024-11-22 02:20:21.554876: val_loss -0.7612 +2024-11-22 02:20:21.554959: Pseudo dice [0.8334] +2024-11-22 02:20:21.555043: Epoch time: 18.65 s +2024-11-22 02:20:22.785984: +2024-11-22 02:20:22.786206: Epoch 2918 +2024-11-22 02:20:22.786316: Current learning rate: 0.00665 +2024-11-22 02:20:40.614383: train_loss -0.7753 +2024-11-22 02:20:40.614617: val_loss -0.7677 +2024-11-22 02:20:40.614706: Pseudo dice [0.8462] +2024-11-22 02:20:40.614780: Epoch time: 17.83 s +2024-11-22 02:20:41.548287: +2024-11-22 02:20:41.548532: Epoch 2919 +2024-11-22 02:20:41.548646: Current learning rate: 0.00665 +2024-11-22 02:21:01.017351: train_loss -0.7706 +2024-11-22 02:21:01.017560: val_loss -0.7676 +2024-11-22 02:21:01.017637: Pseudo dice [0.8566] +2024-11-22 02:21:01.017716: Epoch time: 19.47 s +2024-11-22 02:21:01.896202: +2024-11-22 02:21:01.898183: Epoch 2920 +2024-11-22 02:21:01.898306: Current learning rate: 0.00665 +2024-11-22 02:21:19.702101: train_loss -0.7769 +2024-11-22 02:21:19.702351: val_loss -0.7732 +2024-11-22 02:21:19.702466: Pseudo dice [0.847] +2024-11-22 02:21:19.702552: Epoch time: 17.81 s +2024-11-22 02:21:20.558566: +2024-11-22 02:21:20.558774: Epoch 2921 +2024-11-22 02:21:20.558886: Current learning rate: 0.00664 +2024-11-22 02:21:39.762822: train_loss -0.7768 +2024-11-22 02:21:39.763094: val_loss -0.7886 +2024-11-22 02:21:39.763176: Pseudo dice [0.853] +2024-11-22 02:21:39.763266: Epoch time: 19.21 s +2024-11-22 02:21:40.622475: +2024-11-22 02:21:40.622749: Epoch 2922 +2024-11-22 02:21:40.622860: Current learning rate: 0.00664 +2024-11-22 02:21:58.630893: train_loss -0.7711 +2024-11-22 02:21:58.631124: val_loss -0.7571 +2024-11-22 02:21:58.631200: Pseudo dice [0.8151] +2024-11-22 02:21:58.631337: Epoch time: 18.01 s +2024-11-22 02:21:59.492523: +2024-11-22 02:21:59.492820: Epoch 2923 +2024-11-22 02:21:59.492931: Current learning rate: 0.00664 +2024-11-22 02:22:17.529536: train_loss -0.7729 +2024-11-22 02:22:17.529761: val_loss -0.7569 +2024-11-22 02:22:17.529838: Pseudo dice [0.8392] +2024-11-22 02:22:17.529916: Epoch time: 18.04 s +2024-11-22 02:22:18.395918: +2024-11-22 02:22:18.396231: Epoch 2924 +2024-11-22 02:22:18.396341: Current learning rate: 0.00664 +2024-11-22 02:22:35.778678: train_loss -0.7756 +2024-11-22 02:22:35.778927: val_loss -0.7799 +2024-11-22 02:22:35.779013: Pseudo dice [0.8524] +2024-11-22 02:22:35.779098: Epoch time: 17.38 s +2024-11-22 02:22:36.653002: +2024-11-22 02:22:36.653229: Epoch 2925 +2024-11-22 02:22:36.653342: Current learning rate: 0.00664 +2024-11-22 02:22:55.118977: train_loss -0.7816 +2024-11-22 02:22:55.119222: val_loss -0.7451 +2024-11-22 02:22:55.119297: Pseudo dice [0.8288] +2024-11-22 02:22:55.124518: Epoch time: 18.47 s +2024-11-22 02:22:55.987964: +2024-11-22 02:22:55.988188: Epoch 2926 +2024-11-22 02:22:55.988309: Current learning rate: 0.00664 +2024-11-22 02:23:13.448773: train_loss -0.7822 +2024-11-22 02:23:13.448999: val_loss -0.7705 +2024-11-22 02:23:13.449077: Pseudo dice [0.8384] +2024-11-22 02:23:13.449155: Epoch time: 17.46 s +2024-11-22 02:23:14.308902: +2024-11-22 02:23:14.309167: Epoch 2927 +2024-11-22 02:23:14.309284: Current learning rate: 0.00664 +2024-11-22 02:23:32.876428: train_loss -0.7867 +2024-11-22 02:23:32.877006: val_loss -0.7536 +2024-11-22 02:23:32.877091: Pseudo dice [0.8403] +2024-11-22 02:23:32.877179: Epoch time: 18.57 s +2024-11-22 02:23:33.734979: +2024-11-22 02:23:33.735181: Epoch 2928 +2024-11-22 02:23:33.735287: Current learning rate: 0.00664 +2024-11-22 02:23:53.220640: train_loss -0.7771 +2024-11-22 02:23:53.220942: val_loss -0.779 +2024-11-22 02:23:53.221029: Pseudo dice [0.8511] +2024-11-22 02:23:53.221104: Epoch time: 19.48 s +2024-11-22 02:23:54.465276: +2024-11-22 02:23:54.465527: Epoch 2929 +2024-11-22 02:23:54.465639: Current learning rate: 0.00663 +2024-11-22 02:24:12.252023: train_loss -0.7765 +2024-11-22 02:24:12.252242: val_loss -0.7714 +2024-11-22 02:24:12.252325: Pseudo dice [0.828] +2024-11-22 02:24:12.252401: Epoch time: 17.79 s +2024-11-22 02:24:13.106036: +2024-11-22 02:24:13.106260: Epoch 2930 +2024-11-22 02:24:13.106370: Current learning rate: 0.00663 +2024-11-22 02:24:32.033285: train_loss -0.7797 +2024-11-22 02:24:32.033871: val_loss -0.7375 +2024-11-22 02:24:32.033957: Pseudo dice [0.8363] +2024-11-22 02:24:32.034055: Epoch time: 18.93 s +2024-11-22 02:24:32.896453: +2024-11-22 02:24:32.896670: Epoch 2931 +2024-11-22 02:24:32.896780: Current learning rate: 0.00663 +2024-11-22 02:24:51.859511: train_loss -0.7709 +2024-11-22 02:24:51.859729: val_loss -0.7552 +2024-11-22 02:24:51.859801: Pseudo dice [0.8341] +2024-11-22 02:24:51.859873: Epoch time: 18.96 s +2024-11-22 02:24:52.737358: +2024-11-22 02:24:52.737581: Epoch 2932 +2024-11-22 02:24:52.737691: Current learning rate: 0.00663 +2024-11-22 02:25:11.358581: train_loss -0.7623 +2024-11-22 02:25:11.358793: val_loss -0.7449 +2024-11-22 02:25:11.358867: Pseudo dice [0.8267] +2024-11-22 02:25:11.375252: Epoch time: 18.62 s +2024-11-22 02:25:12.235950: +2024-11-22 02:25:12.236192: Epoch 2933 +2024-11-22 02:25:12.236303: Current learning rate: 0.00663 +2024-11-22 02:25:30.437536: train_loss -0.7694 +2024-11-22 02:25:30.437749: val_loss -0.7587 +2024-11-22 02:25:30.437822: Pseudo dice [0.8317] +2024-11-22 02:25:30.437896: Epoch time: 18.2 s +2024-11-22 02:25:31.420806: +2024-11-22 02:25:31.421038: Epoch 2934 +2024-11-22 02:25:31.421144: Current learning rate: 0.00663 +2024-11-22 02:25:49.544084: train_loss -0.7619 +2024-11-22 02:25:49.544306: val_loss -0.7521 +2024-11-22 02:25:49.544383: Pseudo dice [0.8421] +2024-11-22 02:25:49.549127: Epoch time: 18.12 s +2024-11-22 02:25:50.444551: +2024-11-22 02:25:50.444778: Epoch 2935 +2024-11-22 02:25:50.444887: Current learning rate: 0.00663 +2024-11-22 02:26:08.266485: train_loss -0.7724 +2024-11-22 02:26:08.266734: val_loss -0.7346 +2024-11-22 02:26:08.266809: Pseudo dice [0.822] +2024-11-22 02:26:08.266901: Epoch time: 17.82 s +2024-11-22 02:26:09.130704: +2024-11-22 02:26:09.130939: Epoch 2936 +2024-11-22 02:26:09.131053: Current learning rate: 0.00663 +2024-11-22 02:26:27.174477: train_loss -0.7839 +2024-11-22 02:26:27.174706: val_loss -0.7496 +2024-11-22 02:26:27.174779: Pseudo dice [0.8405] +2024-11-22 02:26:27.174852: Epoch time: 18.04 s +2024-11-22 02:26:28.037437: +2024-11-22 02:26:28.037653: Epoch 2937 +2024-11-22 02:26:28.037760: Current learning rate: 0.00663 +2024-11-22 02:26:46.381172: train_loss -0.7692 +2024-11-22 02:26:46.381383: val_loss -0.7668 +2024-11-22 02:26:46.381456: Pseudo dice [0.8193] +2024-11-22 02:26:46.381529: Epoch time: 18.34 s +2024-11-22 02:26:47.409395: +2024-11-22 02:26:47.409645: Epoch 2938 +2024-11-22 02:26:47.409771: Current learning rate: 0.00662 +2024-11-22 02:27:05.983011: train_loss -0.7738 +2024-11-22 02:27:05.983282: val_loss -0.7709 +2024-11-22 02:27:05.983361: Pseudo dice [0.8481] +2024-11-22 02:27:05.983442: Epoch time: 18.57 s +2024-11-22 02:27:06.913141: +2024-11-22 02:27:06.913350: Epoch 2939 +2024-11-22 02:27:06.913461: Current learning rate: 0.00662 +2024-11-22 02:27:25.829663: train_loss -0.7781 +2024-11-22 02:27:25.829894: val_loss -0.7849 +2024-11-22 02:27:25.829967: Pseudo dice [0.856] +2024-11-22 02:27:25.830056: Epoch time: 18.92 s +2024-11-22 02:27:26.850319: +2024-11-22 02:27:26.850534: Epoch 2940 +2024-11-22 02:27:26.850649: Current learning rate: 0.00662 +2024-11-22 02:27:44.309487: train_loss -0.774 +2024-11-22 02:27:44.309756: val_loss -0.7782 +2024-11-22 02:27:44.309848: Pseudo dice [0.8404] +2024-11-22 02:27:44.309924: Epoch time: 17.46 s +2024-11-22 02:27:45.540141: +2024-11-22 02:27:45.540361: Epoch 2941 +2024-11-22 02:27:45.540474: Current learning rate: 0.00662 +2024-11-22 02:28:03.781518: train_loss -0.7813 +2024-11-22 02:28:03.781788: val_loss -0.7735 +2024-11-22 02:28:03.781877: Pseudo dice [0.8477] +2024-11-22 02:28:03.781959: Epoch time: 18.24 s +2024-11-22 02:28:04.644892: +2024-11-22 02:28:04.645109: Epoch 2942 +2024-11-22 02:28:04.645219: Current learning rate: 0.00662 +2024-11-22 02:28:21.569874: train_loss -0.7826 +2024-11-22 02:28:21.570114: val_loss -0.7698 +2024-11-22 02:28:21.570192: Pseudo dice [0.8496] +2024-11-22 02:28:21.570267: Epoch time: 16.93 s +2024-11-22 02:28:22.424628: +2024-11-22 02:28:22.424939: Epoch 2943 +2024-11-22 02:28:22.425055: Current learning rate: 0.00662 +2024-11-22 02:28:40.956671: train_loss -0.7771 +2024-11-22 02:28:40.956878: val_loss -0.7599 +2024-11-22 02:28:40.956953: Pseudo dice [0.8496] +2024-11-22 02:28:40.957031: Epoch time: 18.53 s +2024-11-22 02:28:41.802870: +2024-11-22 02:28:41.803080: Epoch 2944 +2024-11-22 02:28:41.803193: Current learning rate: 0.00662 +2024-11-22 02:29:00.484225: train_loss -0.7837 +2024-11-22 02:29:00.484444: val_loss -0.7771 +2024-11-22 02:29:00.484535: Pseudo dice [0.8494] +2024-11-22 02:29:00.484628: Epoch time: 18.68 s +2024-11-22 02:29:01.348797: +2024-11-22 02:29:01.349025: Epoch 2945 +2024-11-22 02:29:01.349137: Current learning rate: 0.00662 +2024-11-22 02:29:20.817761: train_loss -0.7838 +2024-11-22 02:29:20.818041: val_loss -0.7804 +2024-11-22 02:29:20.818119: Pseudo dice [0.8504] +2024-11-22 02:29:20.818202: Epoch time: 19.47 s +2024-11-22 02:29:21.723622: +2024-11-22 02:29:21.723838: Epoch 2946 +2024-11-22 02:29:21.723948: Current learning rate: 0.00661 +2024-11-22 02:29:39.346833: train_loss -0.7796 +2024-11-22 02:29:39.347052: val_loss -0.7904 +2024-11-22 02:29:39.347127: Pseudo dice [0.8473] +2024-11-22 02:29:39.347210: Epoch time: 17.62 s +2024-11-22 02:29:40.225503: +2024-11-22 02:29:40.225722: Epoch 2947 +2024-11-22 02:29:40.225833: Current learning rate: 0.00661 +2024-11-22 02:29:58.062822: train_loss -0.779 +2024-11-22 02:29:58.063092: val_loss -0.753 +2024-11-22 02:29:58.063184: Pseudo dice [0.8221] +2024-11-22 02:29:58.063270: Epoch time: 17.84 s +2024-11-22 02:29:58.927761: +2024-11-22 02:29:58.927985: Epoch 2948 +2024-11-22 02:29:58.928101: Current learning rate: 0.00661 +2024-11-22 02:30:16.866237: train_loss -0.7857 +2024-11-22 02:30:16.866460: val_loss -0.7615 +2024-11-22 02:30:16.866535: Pseudo dice [0.8354] +2024-11-22 02:30:16.866615: Epoch time: 17.94 s +2024-11-22 02:30:17.724257: +2024-11-22 02:30:17.724490: Epoch 2949 +2024-11-22 02:30:17.724603: Current learning rate: 0.00661 +2024-11-22 02:30:36.244952: train_loss -0.7759 +2024-11-22 02:30:36.245186: val_loss -0.7519 +2024-11-22 02:30:36.245295: Pseudo dice [0.8244] +2024-11-22 02:30:36.245375: Epoch time: 18.52 s +2024-11-22 02:30:37.349117: +2024-11-22 02:30:37.349365: Epoch 2950 +2024-11-22 02:30:37.349481: Current learning rate: 0.00661 +2024-11-22 02:30:55.230583: train_loss -0.7471 +2024-11-22 02:30:55.230803: val_loss -0.7688 +2024-11-22 02:30:55.230880: Pseudo dice [0.8368] +2024-11-22 02:30:55.230951: Epoch time: 17.88 s +2024-11-22 02:30:56.088018: +2024-11-22 02:30:56.088248: Epoch 2951 +2024-11-22 02:30:56.088361: Current learning rate: 0.00661 +2024-11-22 02:31:13.625210: train_loss -0.7592 +2024-11-22 02:31:13.625440: val_loss -0.7618 +2024-11-22 02:31:13.625517: Pseudo dice [0.8448] +2024-11-22 02:31:13.625591: Epoch time: 17.54 s +2024-11-22 02:31:14.502705: +2024-11-22 02:31:14.502935: Epoch 2952 +2024-11-22 02:31:14.503052: Current learning rate: 0.00661 +2024-11-22 02:31:32.367517: train_loss -0.7748 +2024-11-22 02:31:32.367740: val_loss -0.7552 +2024-11-22 02:31:32.367818: Pseudo dice [0.8387] +2024-11-22 02:31:32.367897: Epoch time: 17.87 s +2024-11-22 02:31:33.225402: +2024-11-22 02:31:33.225627: Epoch 2953 +2024-11-22 02:31:33.225743: Current learning rate: 0.00661 +2024-11-22 02:31:52.188960: train_loss -0.7843 +2024-11-22 02:31:52.189183: val_loss -0.7791 +2024-11-22 02:31:52.189258: Pseudo dice [0.8543] +2024-11-22 02:31:52.189339: Epoch time: 18.96 s +2024-11-22 02:31:53.047189: +2024-11-22 02:31:53.047419: Epoch 2954 +2024-11-22 02:31:53.047529: Current learning rate: 0.0066 +2024-11-22 02:32:11.121829: train_loss -0.7816 +2024-11-22 02:32:11.122048: val_loss -0.7663 +2024-11-22 02:32:11.122129: Pseudo dice [0.8444] +2024-11-22 02:32:11.122208: Epoch time: 18.08 s +2024-11-22 02:32:11.982790: +2024-11-22 02:32:11.983011: Epoch 2955 +2024-11-22 02:32:11.983115: Current learning rate: 0.0066 +2024-11-22 02:32:29.992431: train_loss -0.7779 +2024-11-22 02:32:29.992714: val_loss -0.7833 +2024-11-22 02:32:29.992792: Pseudo dice [0.8554] +2024-11-22 02:32:29.992871: Epoch time: 18.01 s +2024-11-22 02:32:30.880902: +2024-11-22 02:32:30.881126: Epoch 2956 +2024-11-22 02:32:30.881235: Current learning rate: 0.0066 +2024-11-22 02:32:47.967919: train_loss -0.776 +2024-11-22 02:32:47.968128: val_loss -0.7779 +2024-11-22 02:32:47.968202: Pseudo dice [0.8385] +2024-11-22 02:32:47.968273: Epoch time: 17.09 s +2024-11-22 02:32:48.880940: +2024-11-22 02:32:48.881156: Epoch 2957 +2024-11-22 02:32:48.881266: Current learning rate: 0.0066 +2024-11-22 02:33:07.452112: train_loss -0.7852 +2024-11-22 02:33:07.452358: val_loss -0.7548 +2024-11-22 02:33:07.452433: Pseudo dice [0.8538] +2024-11-22 02:33:07.457676: Epoch time: 18.57 s +2024-11-22 02:33:08.326387: +2024-11-22 02:33:08.326660: Epoch 2958 +2024-11-22 02:33:08.346206: Current learning rate: 0.0066 +2024-11-22 02:33:25.560322: train_loss -0.7741 +2024-11-22 02:33:25.560549: val_loss -0.7644 +2024-11-22 02:33:25.560625: Pseudo dice [0.8416] +2024-11-22 02:33:25.560722: Epoch time: 17.23 s +2024-11-22 02:33:26.421639: +2024-11-22 02:33:26.421854: Epoch 2959 +2024-11-22 02:33:26.421968: Current learning rate: 0.0066 +2024-11-22 02:33:44.008233: train_loss -0.7683 +2024-11-22 02:33:44.013689: val_loss -0.777 +2024-11-22 02:33:44.013812: Pseudo dice [0.8564] +2024-11-22 02:33:44.013905: Epoch time: 17.59 s +2024-11-22 02:33:44.890667: +2024-11-22 02:33:44.890884: Epoch 2960 +2024-11-22 02:33:44.890989: Current learning rate: 0.0066 +2024-11-22 02:34:03.574662: train_loss -0.7878 +2024-11-22 02:34:03.574875: val_loss -0.7608 +2024-11-22 02:34:03.574949: Pseudo dice [0.8434] +2024-11-22 02:34:03.575028: Epoch time: 18.68 s +2024-11-22 02:34:04.492983: +2024-11-22 02:34:04.493239: Epoch 2961 +2024-11-22 02:34:04.493348: Current learning rate: 0.0066 +2024-11-22 02:34:23.801067: train_loss -0.7799 +2024-11-22 02:34:23.801283: val_loss -0.7836 +2024-11-22 02:34:23.801362: Pseudo dice [0.8435] +2024-11-22 02:34:23.801438: Epoch time: 19.31 s +2024-11-22 02:34:24.700890: +2024-11-22 02:34:24.701110: Epoch 2962 +2024-11-22 02:34:24.701223: Current learning rate: 0.0066 +2024-11-22 02:34:44.156480: train_loss -0.7742 +2024-11-22 02:34:44.156693: val_loss -0.783 +2024-11-22 02:34:44.156768: Pseudo dice [0.8543] +2024-11-22 02:34:44.156845: Epoch time: 19.46 s +2024-11-22 02:34:45.118570: +2024-11-22 02:34:45.118791: Epoch 2963 +2024-11-22 02:34:45.118902: Current learning rate: 0.00659 +2024-11-22 02:35:03.083967: train_loss -0.7733 +2024-11-22 02:35:03.084255: val_loss -0.7754 +2024-11-22 02:35:03.084329: Pseudo dice [0.8374] +2024-11-22 02:35:03.084408: Epoch time: 17.97 s +2024-11-22 02:35:04.336427: +2024-11-22 02:35:04.336660: Epoch 2964 +2024-11-22 02:35:04.336771: Current learning rate: 0.00659 +2024-11-22 02:35:22.289913: train_loss -0.7805 +2024-11-22 02:35:22.290187: val_loss -0.7743 +2024-11-22 02:35:22.290265: Pseudo dice [0.848] +2024-11-22 02:35:22.290344: Epoch time: 17.95 s +2024-11-22 02:35:23.193076: +2024-11-22 02:35:23.193289: Epoch 2965 +2024-11-22 02:35:23.193473: Current learning rate: 0.00659 +2024-11-22 02:35:42.119403: train_loss -0.7764 +2024-11-22 02:35:42.119635: val_loss -0.785 +2024-11-22 02:35:42.119715: Pseudo dice [0.8575] +2024-11-22 02:35:42.119794: Epoch time: 18.93 s +2024-11-22 02:35:42.973140: +2024-11-22 02:35:42.973383: Epoch 2966 +2024-11-22 02:35:42.973494: Current learning rate: 0.00659 +2024-11-22 02:36:01.703310: train_loss -0.7822 +2024-11-22 02:36:01.703547: val_loss -0.7809 +2024-11-22 02:36:01.706550: Pseudo dice [0.8472] +2024-11-22 02:36:01.706655: Epoch time: 18.73 s +2024-11-22 02:36:02.595675: +2024-11-22 02:36:02.595898: Epoch 2967 +2024-11-22 02:36:02.596019: Current learning rate: 0.00659 +2024-11-22 02:36:21.136328: train_loss -0.7707 +2024-11-22 02:36:21.136616: val_loss -0.7741 +2024-11-22 02:36:21.136696: Pseudo dice [0.8462] +2024-11-22 02:36:21.136770: Epoch time: 18.54 s +2024-11-22 02:36:21.998958: +2024-11-22 02:36:21.999176: Epoch 2968 +2024-11-22 02:36:21.999285: Current learning rate: 0.00659 +2024-11-22 02:36:41.661518: train_loss -0.7697 +2024-11-22 02:36:41.661741: val_loss -0.7799 +2024-11-22 02:36:41.661815: Pseudo dice [0.8296] +2024-11-22 02:36:41.661887: Epoch time: 19.66 s +2024-11-22 02:36:42.520820: +2024-11-22 02:36:42.521018: Epoch 2969 +2024-11-22 02:36:42.521125: Current learning rate: 0.00659 +2024-11-22 02:37:01.142500: train_loss -0.7719 +2024-11-22 02:37:01.142718: val_loss -0.7524 +2024-11-22 02:37:01.142793: Pseudo dice [0.8277] +2024-11-22 02:37:01.142868: Epoch time: 18.62 s +2024-11-22 02:37:02.000528: +2024-11-22 02:37:02.000740: Epoch 2970 +2024-11-22 02:37:02.000849: Current learning rate: 0.00659 +2024-11-22 02:37:19.395861: train_loss -0.777 +2024-11-22 02:37:19.396124: val_loss -0.7512 +2024-11-22 02:37:19.401448: Pseudo dice [0.8495] +2024-11-22 02:37:19.401922: Epoch time: 17.4 s +2024-11-22 02:37:20.268839: +2024-11-22 02:37:20.269037: Epoch 2971 +2024-11-22 02:37:20.269150: Current learning rate: 0.00658 +2024-11-22 02:37:38.952173: train_loss -0.7786 +2024-11-22 02:37:38.952392: val_loss -0.7775 +2024-11-22 02:37:38.961180: Pseudo dice [0.8634] +2024-11-22 02:37:38.961289: Epoch time: 18.68 s +2024-11-22 02:37:39.882529: +2024-11-22 02:37:39.882738: Epoch 2972 +2024-11-22 02:37:39.882845: Current learning rate: 0.00658 +2024-11-22 02:37:58.086107: train_loss -0.7778 +2024-11-22 02:37:58.086400: val_loss -0.7764 +2024-11-22 02:37:58.086473: Pseudo dice [0.8459] +2024-11-22 02:37:58.086547: Epoch time: 18.2 s +2024-11-22 02:37:58.981539: +2024-11-22 02:37:58.981768: Epoch 2973 +2024-11-22 02:37:58.981878: Current learning rate: 0.00658 +2024-11-22 02:38:16.343395: train_loss -0.7726 +2024-11-22 02:38:16.344551: val_loss -0.7808 +2024-11-22 02:38:16.344651: Pseudo dice [0.859] +2024-11-22 02:38:16.344730: Epoch time: 17.36 s +2024-11-22 02:38:17.238783: +2024-11-22 02:38:17.239019: Epoch 2974 +2024-11-22 02:38:17.239130: Current learning rate: 0.00658 +2024-11-22 02:38:35.659018: train_loss -0.7661 +2024-11-22 02:38:35.659237: val_loss -0.749 +2024-11-22 02:38:35.659314: Pseudo dice [0.8295] +2024-11-22 02:38:35.659410: Epoch time: 18.42 s +2024-11-22 02:38:36.915349: +2024-11-22 02:38:36.915571: Epoch 2975 +2024-11-22 02:38:36.915679: Current learning rate: 0.00658 +2024-11-22 02:38:56.006738: train_loss -0.7645 +2024-11-22 02:38:56.006960: val_loss -0.7407 +2024-11-22 02:38:56.007045: Pseudo dice [0.8271] +2024-11-22 02:38:56.007128: Epoch time: 19.09 s +2024-11-22 02:38:56.861646: +2024-11-22 02:38:56.861898: Epoch 2976 +2024-11-22 02:38:56.862018: Current learning rate: 0.00658 +2024-11-22 02:39:14.517094: train_loss -0.7777 +2024-11-22 02:39:14.517350: val_loss -0.7682 +2024-11-22 02:39:14.517430: Pseudo dice [0.8379] +2024-11-22 02:39:14.517511: Epoch time: 17.66 s +2024-11-22 02:39:15.440734: +2024-11-22 02:39:15.440957: Epoch 2977 +2024-11-22 02:39:15.441076: Current learning rate: 0.00658 +2024-11-22 02:39:35.364864: train_loss -0.7716 +2024-11-22 02:39:35.365135: val_loss -0.7717 +2024-11-22 02:39:35.365218: Pseudo dice [0.8317] +2024-11-22 02:39:35.365302: Epoch time: 19.92 s +2024-11-22 02:39:36.227957: +2024-11-22 02:39:36.228182: Epoch 2978 +2024-11-22 02:39:36.228290: Current learning rate: 0.00658 +2024-11-22 02:39:53.911689: train_loss -0.7753 +2024-11-22 02:39:53.917110: val_loss -0.759 +2024-11-22 02:39:53.917229: Pseudo dice [0.8261] +2024-11-22 02:39:53.917318: Epoch time: 17.68 s +2024-11-22 02:39:54.847250: +2024-11-22 02:39:54.847476: Epoch 2979 +2024-11-22 02:39:54.847587: Current learning rate: 0.00658 +2024-11-22 02:40:13.681841: train_loss -0.7688 +2024-11-22 02:40:13.682065: val_loss -0.7606 +2024-11-22 02:40:13.682142: Pseudo dice [0.838] +2024-11-22 02:40:13.682219: Epoch time: 18.84 s +2024-11-22 02:40:14.678299: +2024-11-22 02:40:14.678518: Epoch 2980 +2024-11-22 02:40:14.678624: Current learning rate: 0.00657 +2024-11-22 02:40:33.237722: train_loss -0.7759 +2024-11-22 02:40:33.237962: val_loss -0.7743 +2024-11-22 02:40:33.238070: Pseudo dice [0.8424] +2024-11-22 02:40:33.238151: Epoch time: 18.56 s +2024-11-22 02:40:34.100245: +2024-11-22 02:40:34.100540: Epoch 2981 +2024-11-22 02:40:34.100649: Current learning rate: 0.00657 +2024-11-22 02:40:52.662349: train_loss -0.7731 +2024-11-22 02:40:52.662623: val_loss -0.7682 +2024-11-22 02:40:52.662699: Pseudo dice [0.8589] +2024-11-22 02:40:52.662780: Epoch time: 18.56 s +2024-11-22 02:40:53.762669: +2024-11-22 02:40:53.762870: Epoch 2982 +2024-11-22 02:40:53.762978: Current learning rate: 0.00657 +2024-11-22 02:41:12.878571: train_loss -0.7904 +2024-11-22 02:41:12.878785: val_loss -0.7497 +2024-11-22 02:41:12.878860: Pseudo dice [0.8237] +2024-11-22 02:41:12.878936: Epoch time: 19.12 s +2024-11-22 02:41:13.741874: +2024-11-22 02:41:13.742074: Epoch 2983 +2024-11-22 02:41:13.742182: Current learning rate: 0.00657 +2024-11-22 02:41:31.300508: train_loss -0.7813 +2024-11-22 02:41:31.324570: val_loss -0.7705 +2024-11-22 02:41:31.324857: Pseudo dice [0.8175] +2024-11-22 02:41:31.324948: Epoch time: 17.56 s +2024-11-22 02:41:32.180191: +2024-11-22 02:41:32.180405: Epoch 2984 +2024-11-22 02:41:32.180514: Current learning rate: 0.00657 +2024-11-22 02:41:50.679559: train_loss -0.7878 +2024-11-22 02:41:50.686385: val_loss -0.7438 +2024-11-22 02:41:50.686478: Pseudo dice [0.836] +2024-11-22 02:41:50.686566: Epoch time: 18.5 s +2024-11-22 02:41:51.580179: +2024-11-22 02:41:51.580457: Epoch 2985 +2024-11-22 02:41:51.580569: Current learning rate: 0.00657 +2024-11-22 02:42:10.092865: train_loss -0.7754 +2024-11-22 02:42:10.093100: val_loss -0.7514 +2024-11-22 02:42:10.093177: Pseudo dice [0.8367] +2024-11-22 02:42:10.093251: Epoch time: 18.51 s +2024-11-22 02:42:10.949621: +2024-11-22 02:42:10.949822: Epoch 2986 +2024-11-22 02:42:10.949934: Current learning rate: 0.00657 +2024-11-22 02:42:29.528717: train_loss -0.7763 +2024-11-22 02:42:29.528946: val_loss -0.7699 +2024-11-22 02:42:29.529025: Pseudo dice [0.8362] +2024-11-22 02:42:29.529099: Epoch time: 18.58 s +2024-11-22 02:42:30.792828: +2024-11-22 02:42:30.793063: Epoch 2987 +2024-11-22 02:42:30.793178: Current learning rate: 0.00657 +2024-11-22 02:42:49.431278: train_loss -0.7764 +2024-11-22 02:42:49.431531: val_loss -0.7635 +2024-11-22 02:42:49.431608: Pseudo dice [0.8455] +2024-11-22 02:42:49.431734: Epoch time: 18.64 s +2024-11-22 02:42:50.297428: +2024-11-22 02:42:50.297647: Epoch 2988 +2024-11-22 02:42:50.297763: Current learning rate: 0.00656 +2024-11-22 02:43:08.655955: train_loss -0.7777 +2024-11-22 02:43:08.656192: val_loss -0.7581 +2024-11-22 02:43:08.656265: Pseudo dice [0.8434] +2024-11-22 02:43:08.656339: Epoch time: 18.36 s +2024-11-22 02:43:09.520496: +2024-11-22 02:43:09.520715: Epoch 2989 +2024-11-22 02:43:09.520827: Current learning rate: 0.00656 +2024-11-22 02:43:27.315591: train_loss -0.7759 +2024-11-22 02:43:27.315805: val_loss -0.7649 +2024-11-22 02:43:27.315878: Pseudo dice [0.8284] +2024-11-22 02:43:27.315952: Epoch time: 17.8 s +2024-11-22 02:43:28.173442: +2024-11-22 02:43:28.173654: Epoch 2990 +2024-11-22 02:43:28.173770: Current learning rate: 0.00656 +2024-11-22 02:43:45.837551: train_loss -0.7794 +2024-11-22 02:43:45.837841: val_loss -0.7815 +2024-11-22 02:43:45.837925: Pseudo dice [0.8449] +2024-11-22 02:43:45.838068: Epoch time: 17.66 s +2024-11-22 02:43:46.703636: +2024-11-22 02:43:46.703855: Epoch 2991 +2024-11-22 02:43:46.704629: Current learning rate: 0.00656 +2024-11-22 02:44:05.377885: train_loss -0.7736 +2024-11-22 02:44:05.378102: val_loss -0.768 +2024-11-22 02:44:05.378177: Pseudo dice [0.846] +2024-11-22 02:44:05.378249: Epoch time: 18.68 s +2024-11-22 02:44:06.296805: +2024-11-22 02:44:06.297018: Epoch 2992 +2024-11-22 02:44:06.297126: Current learning rate: 0.00656 +2024-11-22 02:44:25.037335: train_loss -0.7698 +2024-11-22 02:44:25.040075: val_loss -0.7727 +2024-11-22 02:44:25.040166: Pseudo dice [0.8316] +2024-11-22 02:44:25.040240: Epoch time: 18.74 s +2024-11-22 02:44:25.995655: +2024-11-22 02:44:25.995867: Epoch 2993 +2024-11-22 02:44:25.995976: Current learning rate: 0.00656 +2024-11-22 02:44:44.238263: train_loss -0.7787 +2024-11-22 02:44:44.238495: val_loss -0.7692 +2024-11-22 02:44:44.238571: Pseudo dice [0.8453] +2024-11-22 02:44:44.238647: Epoch time: 18.24 s +2024-11-22 02:44:45.099256: +2024-11-22 02:44:45.099450: Epoch 2994 +2024-11-22 02:44:45.099558: Current learning rate: 0.00656 +2024-11-22 02:45:03.507925: train_loss -0.7799 +2024-11-22 02:45:03.508171: val_loss -0.7221 +2024-11-22 02:45:03.508247: Pseudo dice [0.8445] +2024-11-22 02:45:03.508327: Epoch time: 18.41 s +2024-11-22 02:45:04.366974: +2024-11-22 02:45:04.367232: Epoch 2995 +2024-11-22 02:45:04.367341: Current learning rate: 0.00656 +2024-11-22 02:45:23.233088: train_loss -0.7741 +2024-11-22 02:45:23.233331: val_loss -0.7795 +2024-11-22 02:45:23.233405: Pseudo dice [0.8506] +2024-11-22 02:45:23.233482: Epoch time: 18.87 s +2024-11-22 02:45:24.090698: +2024-11-22 02:45:24.090886: Epoch 2996 +2024-11-22 02:45:24.107855: Current learning rate: 0.00656 +2024-11-22 02:45:42.214465: train_loss -0.7879 +2024-11-22 02:45:42.216836: val_loss -0.7734 +2024-11-22 02:45:42.216944: Pseudo dice [0.8436] +2024-11-22 02:45:42.217027: Epoch time: 18.12 s +2024-11-22 02:45:43.128702: +2024-11-22 02:45:43.128924: Epoch 2997 +2024-11-22 02:45:43.129041: Current learning rate: 0.00655 +2024-11-22 02:46:01.762354: train_loss -0.7834 +2024-11-22 02:46:01.762573: val_loss -0.7665 +2024-11-22 02:46:01.762651: Pseudo dice [0.843] +2024-11-22 02:46:01.762729: Epoch time: 18.63 s +2024-11-22 02:46:02.618219: +2024-11-22 02:46:02.618444: Epoch 2998 +2024-11-22 02:46:02.618557: Current learning rate: 0.00655 +2024-11-22 02:46:20.747618: train_loss -0.7894 +2024-11-22 02:46:20.747868: val_loss -0.7456 +2024-11-22 02:46:20.747942: Pseudo dice [0.842] +2024-11-22 02:46:20.748029: Epoch time: 18.13 s +2024-11-22 02:46:21.603498: +2024-11-22 02:46:21.603735: Epoch 2999 +2024-11-22 02:46:21.603845: Current learning rate: 0.00655 +2024-11-22 02:46:40.447083: train_loss -0.7857 +2024-11-22 02:46:40.447304: val_loss -0.7595 +2024-11-22 02:46:40.447382: Pseudo dice [0.841] +2024-11-22 02:46:40.447455: Epoch time: 18.84 s +2024-11-22 02:46:41.547404: +2024-11-22 02:46:41.547627: Epoch 3000 +2024-11-22 02:46:41.547738: Current learning rate: 0.00655 +2024-11-22 02:46:59.229688: train_loss -0.787 +2024-11-22 02:46:59.229924: val_loss -0.7564 +2024-11-22 02:46:59.230007: Pseudo dice [0.8393] +2024-11-22 02:46:59.230082: Epoch time: 17.68 s +2024-11-22 02:47:00.115811: +2024-11-22 02:47:00.116026: Epoch 3001 +2024-11-22 02:47:00.116136: Current learning rate: 0.00655 +2024-11-22 02:47:17.986527: train_loss -0.7886 +2024-11-22 02:47:17.986780: val_loss -0.7815 +2024-11-22 02:47:17.986861: Pseudo dice [0.8548] +2024-11-22 02:47:17.986948: Epoch time: 17.87 s +2024-11-22 02:47:18.916405: +2024-11-22 02:47:18.916619: Epoch 3002 +2024-11-22 02:47:18.916728: Current learning rate: 0.00655 +2024-11-22 02:47:37.668037: train_loss -0.7862 +2024-11-22 02:47:37.668258: val_loss -0.7829 +2024-11-22 02:47:37.668336: Pseudo dice [0.8477] +2024-11-22 02:47:37.668414: Epoch time: 18.75 s +2024-11-22 02:47:38.534416: +2024-11-22 02:47:38.534623: Epoch 3003 +2024-11-22 02:47:38.534742: Current learning rate: 0.00655 +2024-11-22 02:47:56.109486: train_loss -0.7824 +2024-11-22 02:47:56.109709: val_loss -0.7855 +2024-11-22 02:47:56.109781: Pseudo dice [0.8482] +2024-11-22 02:47:56.109857: Epoch time: 17.58 s +2024-11-22 02:47:56.970668: +2024-11-22 02:47:56.970883: Epoch 3004 +2024-11-22 02:47:56.970990: Current learning rate: 0.00655 +2024-11-22 02:48:16.150320: train_loss -0.7848 +2024-11-22 02:48:16.150599: val_loss -0.7773 +2024-11-22 02:48:16.150683: Pseudo dice [0.8491] +2024-11-22 02:48:16.150761: Epoch time: 19.18 s +2024-11-22 02:48:17.016708: +2024-11-22 02:48:17.016920: Epoch 3005 +2024-11-22 02:48:17.017038: Current learning rate: 0.00654 +2024-11-22 02:48:35.286733: train_loss -0.7907 +2024-11-22 02:48:35.286972: val_loss -0.7626 +2024-11-22 02:48:35.287054: Pseudo dice [0.8401] +2024-11-22 02:48:35.287134: Epoch time: 18.27 s +2024-11-22 02:48:36.152158: +2024-11-22 02:48:36.152349: Epoch 3006 +2024-11-22 02:48:36.152454: Current learning rate: 0.00654 +2024-11-22 02:48:54.546110: train_loss -0.7847 +2024-11-22 02:48:54.546333: val_loss -0.7757 +2024-11-22 02:48:54.546406: Pseudo dice [0.8366] +2024-11-22 02:48:54.546480: Epoch time: 18.39 s +2024-11-22 02:48:55.418201: +2024-11-22 02:48:55.418437: Epoch 3007 +2024-11-22 02:48:55.418556: Current learning rate: 0.00654 +2024-11-22 02:49:14.668807: train_loss -0.7786 +2024-11-22 02:49:14.669027: val_loss -0.7844 +2024-11-22 02:49:14.669104: Pseudo dice [0.8462] +2024-11-22 02:49:14.669178: Epoch time: 19.25 s +2024-11-22 02:49:15.553154: +2024-11-22 02:49:15.553380: Epoch 3008 +2024-11-22 02:49:15.553489: Current learning rate: 0.00654 +2024-11-22 02:49:33.987614: train_loss -0.7784 +2024-11-22 02:49:33.987857: val_loss -0.7608 +2024-11-22 02:49:33.987939: Pseudo dice [0.8452] +2024-11-22 02:49:33.988028: Epoch time: 18.44 s +2024-11-22 02:49:35.223636: +2024-11-22 02:49:35.223856: Epoch 3009 +2024-11-22 02:49:35.223965: Current learning rate: 0.00654 +2024-11-22 02:49:53.820279: train_loss -0.7786 +2024-11-22 02:49:53.820558: val_loss -0.7693 +2024-11-22 02:49:53.820633: Pseudo dice [0.8444] +2024-11-22 02:49:53.820706: Epoch time: 18.6 s +2024-11-22 02:49:54.714960: +2024-11-22 02:49:54.715194: Epoch 3010 +2024-11-22 02:49:54.715307: Current learning rate: 0.00654 +2024-11-22 02:50:13.551660: train_loss -0.7865 +2024-11-22 02:50:13.551887: val_loss -0.797 +2024-11-22 02:50:13.551962: Pseudo dice [0.8575] +2024-11-22 02:50:13.552040: Epoch time: 18.84 s +2024-11-22 02:50:14.516925: +2024-11-22 02:50:14.517157: Epoch 3011 +2024-11-22 02:50:14.517266: Current learning rate: 0.00654 +2024-11-22 02:50:32.547557: train_loss -0.778 +2024-11-22 02:50:32.547790: val_loss -0.7797 +2024-11-22 02:50:32.547877: Pseudo dice [0.8488] +2024-11-22 02:50:32.547956: Epoch time: 18.03 s +2024-11-22 02:50:33.410781: +2024-11-22 02:50:33.411037: Epoch 3012 +2024-11-22 02:50:33.411177: Current learning rate: 0.00654 +2024-11-22 02:50:52.152855: train_loss -0.7747 +2024-11-22 02:50:52.153080: val_loss -0.7835 +2024-11-22 02:50:52.153160: Pseudo dice [0.8437] +2024-11-22 02:50:52.153258: Epoch time: 18.74 s +2024-11-22 02:50:53.065695: +2024-11-22 02:50:53.065917: Epoch 3013 +2024-11-22 02:50:53.066030: Current learning rate: 0.00654 +2024-11-22 02:51:11.897516: train_loss -0.7816 +2024-11-22 02:51:11.897803: val_loss -0.7993 +2024-11-22 02:51:11.897888: Pseudo dice [0.8636] +2024-11-22 02:51:11.897961: Epoch time: 18.83 s +2024-11-22 02:51:12.859418: +2024-11-22 02:51:12.859619: Epoch 3014 +2024-11-22 02:51:12.859733: Current learning rate: 0.00653 +2024-11-22 02:51:31.005509: train_loss -0.7813 +2024-11-22 02:51:31.005718: val_loss -0.7894 +2024-11-22 02:51:31.005793: Pseudo dice [0.8475] +2024-11-22 02:51:31.005868: Epoch time: 18.15 s +2024-11-22 02:51:31.862631: +2024-11-22 02:51:31.862861: Epoch 3015 +2024-11-22 02:51:31.862976: Current learning rate: 0.00653 +2024-11-22 02:51:50.052515: train_loss -0.7852 +2024-11-22 02:51:50.052763: val_loss -0.7631 +2024-11-22 02:51:50.052840: Pseudo dice [0.8341] +2024-11-22 02:51:50.052925: Epoch time: 18.19 s +2024-11-22 02:51:50.938955: +2024-11-22 02:51:50.939171: Epoch 3016 +2024-11-22 02:51:50.939281: Current learning rate: 0.00653 +2024-11-22 02:52:10.047438: train_loss -0.788 +2024-11-22 02:52:10.047665: val_loss -0.7756 +2024-11-22 02:52:10.047739: Pseudo dice [0.8499] +2024-11-22 02:52:10.047813: Epoch time: 19.11 s +2024-11-22 02:52:10.906087: +2024-11-22 02:52:10.906498: Epoch 3017 +2024-11-22 02:52:10.906619: Current learning rate: 0.00653 +2024-11-22 02:52:30.654935: train_loss -0.7859 +2024-11-22 02:52:30.655174: val_loss -0.7605 +2024-11-22 02:52:30.655250: Pseudo dice [0.8442] +2024-11-22 02:52:30.655324: Epoch time: 19.75 s +2024-11-22 02:52:31.654716: +2024-11-22 02:52:31.654933: Epoch 3018 +2024-11-22 02:52:31.655054: Current learning rate: 0.00653 +2024-11-22 02:52:49.994903: train_loss -0.7866 +2024-11-22 02:52:49.995149: val_loss -0.7759 +2024-11-22 02:52:49.995230: Pseudo dice [0.834] +2024-11-22 02:52:49.995308: Epoch time: 18.34 s +2024-11-22 02:52:50.861070: +2024-11-22 02:52:50.861295: Epoch 3019 +2024-11-22 02:52:50.861403: Current learning rate: 0.00653 +2024-11-22 02:53:09.757356: train_loss -0.7659 +2024-11-22 02:53:09.757605: val_loss -0.7517 +2024-11-22 02:53:09.758193: Pseudo dice [0.8409] +2024-11-22 02:53:09.758287: Epoch time: 18.9 s +2024-11-22 02:53:10.675909: +2024-11-22 02:53:10.676137: Epoch 3020 +2024-11-22 02:53:10.676250: Current learning rate: 0.00653 +2024-11-22 02:53:28.244332: train_loss -0.7761 +2024-11-22 02:53:28.244539: val_loss -0.7665 +2024-11-22 02:53:28.244613: Pseudo dice [0.8269] +2024-11-22 02:53:28.244687: Epoch time: 17.57 s +2024-11-22 02:53:29.552647: +2024-11-22 02:53:29.552872: Epoch 3021 +2024-11-22 02:53:29.552983: Current learning rate: 0.00653 +2024-11-22 02:53:47.548859: train_loss -0.7811 +2024-11-22 02:53:47.549164: val_loss -0.7696 +2024-11-22 02:53:47.571400: Pseudo dice [0.8557] +2024-11-22 02:53:47.571579: Epoch time: 18.0 s +2024-11-22 02:53:48.439455: +2024-11-22 02:53:48.439803: Epoch 3022 +2024-11-22 02:53:48.439932: Current learning rate: 0.00652 +2024-11-22 02:54:06.640332: train_loss -0.7826 +2024-11-22 02:54:06.640553: val_loss -0.7713 +2024-11-22 02:54:06.640630: Pseudo dice [0.8479] +2024-11-22 02:54:06.640706: Epoch time: 18.2 s +2024-11-22 02:54:07.598889: +2024-11-22 02:54:07.599123: Epoch 3023 +2024-11-22 02:54:07.599236: Current learning rate: 0.00652 +2024-11-22 02:54:26.476557: train_loss -0.7892 +2024-11-22 02:54:26.477512: val_loss -0.7644 +2024-11-22 02:54:26.477607: Pseudo dice [0.8291] +2024-11-22 02:54:26.477687: Epoch time: 18.88 s +2024-11-22 02:54:27.375116: +2024-11-22 02:54:27.375337: Epoch 3024 +2024-11-22 02:54:27.375449: Current learning rate: 0.00652 +2024-11-22 02:54:46.819555: train_loss -0.7813 +2024-11-22 02:54:46.819785: val_loss -0.7697 +2024-11-22 02:54:46.819860: Pseudo dice [0.8434] +2024-11-22 02:54:46.819939: Epoch time: 19.45 s +2024-11-22 02:54:47.682447: +2024-11-22 02:54:47.682678: Epoch 3025 +2024-11-22 02:54:47.682797: Current learning rate: 0.00652 +2024-11-22 02:55:07.398677: train_loss -0.7659 +2024-11-22 02:55:07.398919: val_loss -0.7735 +2024-11-22 02:55:07.398999: Pseudo dice [0.8541] +2024-11-22 02:55:07.399075: Epoch time: 19.72 s +2024-11-22 02:55:08.364448: +2024-11-22 02:55:08.364664: Epoch 3026 +2024-11-22 02:55:08.364768: Current learning rate: 0.00652 +2024-11-22 02:55:26.774964: train_loss -0.7696 +2024-11-22 02:55:26.775191: val_loss -0.7443 +2024-11-22 02:55:26.775266: Pseudo dice [0.8361] +2024-11-22 02:55:26.775341: Epoch time: 18.41 s +2024-11-22 02:55:27.636075: +2024-11-22 02:55:27.636272: Epoch 3027 +2024-11-22 02:55:27.636376: Current learning rate: 0.00652 +2024-11-22 02:55:46.019607: train_loss -0.7666 +2024-11-22 02:55:46.019825: val_loss -0.7535 +2024-11-22 02:55:46.019899: Pseudo dice [0.8524] +2024-11-22 02:55:46.019976: Epoch time: 18.38 s +2024-11-22 02:55:46.889562: +2024-11-22 02:55:46.889776: Epoch 3028 +2024-11-22 02:55:46.889882: Current learning rate: 0.00652 +2024-11-22 02:56:05.211093: train_loss -0.7717 +2024-11-22 02:56:05.211328: val_loss -0.7812 +2024-11-22 02:56:05.211401: Pseudo dice [0.8405] +2024-11-22 02:56:05.211488: Epoch time: 18.32 s +2024-11-22 02:56:06.054005: +2024-11-22 02:56:06.054184: Epoch 3029 +2024-11-22 02:56:06.054275: Current learning rate: 0.00652 +2024-11-22 02:56:23.961729: train_loss -0.7756 +2024-11-22 02:56:23.961931: val_loss -0.7687 +2024-11-22 02:56:23.962010: Pseudo dice [0.8315] +2024-11-22 02:56:23.962082: Epoch time: 17.91 s +2024-11-22 02:56:24.820320: +2024-11-22 02:56:24.820527: Epoch 3030 +2024-11-22 02:56:24.820634: Current learning rate: 0.00652 +2024-11-22 02:56:43.886053: train_loss -0.7707 +2024-11-22 02:56:43.886278: val_loss -0.7652 +2024-11-22 02:56:43.886384: Pseudo dice [0.8445] +2024-11-22 02:56:43.886468: Epoch time: 19.07 s +2024-11-22 02:56:44.743785: +2024-11-22 02:56:44.744073: Epoch 3031 +2024-11-22 02:56:44.744189: Current learning rate: 0.00651 +2024-11-22 02:57:02.218076: train_loss -0.7821 +2024-11-22 02:57:02.218293: val_loss -0.7778 +2024-11-22 02:57:02.218369: Pseudo dice [0.837] +2024-11-22 02:57:02.218451: Epoch time: 17.48 s +2024-11-22 02:57:03.073795: +2024-11-22 02:57:03.074007: Epoch 3032 +2024-11-22 02:57:03.074114: Current learning rate: 0.00651 +2024-11-22 02:57:22.167805: train_loss -0.789 +2024-11-22 02:57:22.168036: val_loss -0.7845 +2024-11-22 02:57:22.168109: Pseudo dice [0.8403] +2024-11-22 02:57:22.168184: Epoch time: 19.09 s +2024-11-22 02:57:23.047256: +2024-11-22 02:57:23.047464: Epoch 3033 +2024-11-22 02:57:23.047574: Current learning rate: 0.00651 +2024-11-22 02:57:40.953496: train_loss -0.7799 +2024-11-22 02:57:40.953725: val_loss -0.7493 +2024-11-22 02:57:40.953799: Pseudo dice [0.8408] +2024-11-22 02:57:40.953875: Epoch time: 17.91 s +2024-11-22 02:57:41.813476: +2024-11-22 02:57:41.813707: Epoch 3034 +2024-11-22 02:57:41.813816: Current learning rate: 0.00651 +2024-11-22 02:57:59.038513: train_loss -0.7621 +2024-11-22 02:57:59.038736: val_loss -0.7177 +2024-11-22 02:57:59.038814: Pseudo dice [0.8069] +2024-11-22 02:57:59.038895: Epoch time: 17.23 s +2024-11-22 02:57:59.900276: +2024-11-22 02:57:59.900488: Epoch 3035 +2024-11-22 02:57:59.900595: Current learning rate: 0.00651 +2024-11-22 02:58:18.364335: train_loss -0.7668 +2024-11-22 02:58:18.369787: val_loss -0.765 +2024-11-22 02:58:18.369899: Pseudo dice [0.8443] +2024-11-22 02:58:18.369985: Epoch time: 18.46 s +2024-11-22 02:58:19.394590: +2024-11-22 02:58:19.394793: Epoch 3036 +2024-11-22 02:58:19.394901: Current learning rate: 0.00651 +2024-11-22 02:58:37.480947: train_loss -0.7801 +2024-11-22 02:58:37.481199: val_loss -0.7734 +2024-11-22 02:58:37.481302: Pseudo dice [0.8406] +2024-11-22 02:58:37.481378: Epoch time: 18.09 s +2024-11-22 02:58:38.339387: +2024-11-22 02:58:38.339633: Epoch 3037 +2024-11-22 02:58:38.339747: Current learning rate: 0.00651 +2024-11-22 02:58:56.473736: train_loss -0.7794 +2024-11-22 02:58:56.474035: val_loss -0.7902 +2024-11-22 02:58:56.474115: Pseudo dice [0.857] +2024-11-22 02:58:56.474191: Epoch time: 18.14 s +2024-11-22 02:58:57.333155: +2024-11-22 02:58:57.333371: Epoch 3038 +2024-11-22 02:58:57.333480: Current learning rate: 0.00651 +2024-11-22 02:59:15.676344: train_loss -0.7777 +2024-11-22 02:59:15.676573: val_loss -0.7581 +2024-11-22 02:59:15.676651: Pseudo dice [0.8418] +2024-11-22 02:59:15.676730: Epoch time: 18.34 s +2024-11-22 02:59:16.536739: +2024-11-22 02:59:16.537018: Epoch 3039 +2024-11-22 02:59:16.537131: Current learning rate: 0.0065 +2024-11-22 02:59:34.937446: train_loss -0.7656 +2024-11-22 02:59:34.937690: val_loss -0.7687 +2024-11-22 02:59:34.937762: Pseudo dice [0.8342] +2024-11-22 02:59:34.937840: Epoch time: 18.4 s +2024-11-22 02:59:35.792686: +2024-11-22 02:59:35.792908: Epoch 3040 +2024-11-22 02:59:35.793025: Current learning rate: 0.0065 +2024-11-22 02:59:54.194168: train_loss -0.7765 +2024-11-22 02:59:54.194388: val_loss -0.7879 +2024-11-22 02:59:54.194467: Pseudo dice [0.8462] +2024-11-22 02:59:54.194541: Epoch time: 18.4 s +2024-11-22 02:59:55.054085: +2024-11-22 02:59:55.054296: Epoch 3041 +2024-11-22 02:59:55.054409: Current learning rate: 0.0065 +2024-11-22 03:00:14.050029: train_loss -0.7718 +2024-11-22 03:00:14.050244: val_loss -0.783 +2024-11-22 03:00:14.050317: Pseudo dice [0.8272] +2024-11-22 03:00:14.050388: Epoch time: 19.0 s +2024-11-22 03:00:14.911964: +2024-11-22 03:00:14.912308: Epoch 3042 +2024-11-22 03:00:14.912417: Current learning rate: 0.0065 +2024-11-22 03:00:34.284697: train_loss -0.7808 +2024-11-22 03:00:34.284950: val_loss -0.7712 +2024-11-22 03:00:34.285034: Pseudo dice [0.8336] +2024-11-22 03:00:34.285140: Epoch time: 19.37 s +2024-11-22 03:00:35.145497: +2024-11-22 03:00:35.145688: Epoch 3043 +2024-11-22 03:00:35.145797: Current learning rate: 0.0065 +2024-11-22 03:00:53.862099: train_loss -0.7622 +2024-11-22 03:00:53.862312: val_loss -0.7752 +2024-11-22 03:00:53.862390: Pseudo dice [0.8403] +2024-11-22 03:00:53.862465: Epoch time: 18.72 s +2024-11-22 03:00:55.102319: +2024-11-22 03:00:55.102579: Epoch 3044 +2024-11-22 03:00:55.102718: Current learning rate: 0.0065 +2024-11-22 03:01:12.683526: train_loss -0.7699 +2024-11-22 03:01:12.683763: val_loss -0.7412 +2024-11-22 03:01:12.683841: Pseudo dice [0.8423] +2024-11-22 03:01:12.683920: Epoch time: 17.58 s +2024-11-22 03:01:13.661964: +2024-11-22 03:01:13.662186: Epoch 3045 +2024-11-22 03:01:13.662297: Current learning rate: 0.0065 +2024-11-22 03:01:32.536638: train_loss -0.7693 +2024-11-22 03:01:32.536891: val_loss -0.7604 +2024-11-22 03:01:32.536970: Pseudo dice [0.8181] +2024-11-22 03:01:32.537061: Epoch time: 18.88 s +2024-11-22 03:01:33.566256: +2024-11-22 03:01:33.566483: Epoch 3046 +2024-11-22 03:01:33.566594: Current learning rate: 0.0065 +2024-11-22 03:01:52.185668: train_loss -0.7715 +2024-11-22 03:01:52.186764: val_loss -0.7738 +2024-11-22 03:01:52.186859: Pseudo dice [0.8471] +2024-11-22 03:01:52.186937: Epoch time: 18.62 s +2024-11-22 03:01:53.052875: +2024-11-22 03:01:53.053105: Epoch 3047 +2024-11-22 03:01:53.053216: Current learning rate: 0.0065 +2024-11-22 03:02:10.861389: train_loss -0.7806 +2024-11-22 03:02:10.861597: val_loss -0.7758 +2024-11-22 03:02:10.861671: Pseudo dice [0.8559] +2024-11-22 03:02:10.861759: Epoch time: 17.81 s +2024-11-22 03:02:11.721110: +2024-11-22 03:02:11.721474: Epoch 3048 +2024-11-22 03:02:11.721586: Current learning rate: 0.00649 +2024-11-22 03:02:30.497054: train_loss -0.7818 +2024-11-22 03:02:30.498125: val_loss -0.7532 +2024-11-22 03:02:30.498214: Pseudo dice [0.8475] +2024-11-22 03:02:30.498315: Epoch time: 18.78 s +2024-11-22 03:02:31.359240: +2024-11-22 03:02:31.359448: Epoch 3049 +2024-11-22 03:02:31.359574: Current learning rate: 0.00649 +2024-11-22 03:02:50.293302: train_loss -0.7769 +2024-11-22 03:02:50.293569: val_loss -0.7703 +2024-11-22 03:02:50.293672: Pseudo dice [0.8489] +2024-11-22 03:02:50.293760: Epoch time: 18.93 s +2024-11-22 03:02:51.461679: +2024-11-22 03:02:51.461921: Epoch 3050 +2024-11-22 03:02:51.462048: Current learning rate: 0.00649 +2024-11-22 03:03:10.747624: train_loss -0.7616 +2024-11-22 03:03:10.747848: val_loss -0.7411 +2024-11-22 03:03:10.747921: Pseudo dice [0.8433] +2024-11-22 03:03:10.748002: Epoch time: 19.29 s +2024-11-22 03:03:11.646591: +2024-11-22 03:03:11.646810: Epoch 3051 +2024-11-22 03:03:11.646916: Current learning rate: 0.00649 +2024-11-22 03:03:30.874870: train_loss -0.7813 +2024-11-22 03:03:30.875158: val_loss -0.7779 +2024-11-22 03:03:30.875265: Pseudo dice [0.8408] +2024-11-22 03:03:30.875344: Epoch time: 19.23 s +2024-11-22 03:03:31.733431: +2024-11-22 03:03:31.733637: Epoch 3052 +2024-11-22 03:03:31.733745: Current learning rate: 0.00649 +2024-11-22 03:03:51.508600: train_loss -0.7693 +2024-11-22 03:03:51.508838: val_loss -0.7429 +2024-11-22 03:03:51.508912: Pseudo dice [0.8345] +2024-11-22 03:03:51.508997: Epoch time: 19.78 s +2024-11-22 03:03:52.374695: +2024-11-22 03:03:52.375040: Epoch 3053 +2024-11-22 03:03:52.375152: Current learning rate: 0.00649 +2024-11-22 03:04:11.027464: train_loss -0.7779 +2024-11-22 03:04:11.027756: val_loss -0.7663 +2024-11-22 03:04:11.027839: Pseudo dice [0.8351] +2024-11-22 03:04:11.027917: Epoch time: 18.65 s +2024-11-22 03:04:11.887041: +2024-11-22 03:04:11.887252: Epoch 3054 +2024-11-22 03:04:11.887366: Current learning rate: 0.00649 +2024-11-22 03:04:30.457766: train_loss -0.7845 +2024-11-22 03:04:30.458769: val_loss -0.7728 +2024-11-22 03:04:30.458861: Pseudo dice [0.8462] +2024-11-22 03:04:30.458940: Epoch time: 18.57 s +2024-11-22 03:04:31.395799: +2024-11-22 03:04:31.396030: Epoch 3055 +2024-11-22 03:04:31.396142: Current learning rate: 0.00649 +2024-11-22 03:04:49.013012: train_loss -0.7822 +2024-11-22 03:04:49.013243: val_loss -0.7643 +2024-11-22 03:04:49.013318: Pseudo dice [0.8478] +2024-11-22 03:04:49.014775: Epoch time: 17.62 s +2024-11-22 03:04:49.925386: +2024-11-22 03:04:49.925615: Epoch 3056 +2024-11-22 03:04:49.925731: Current learning rate: 0.00648 +2024-11-22 03:05:09.042997: train_loss -0.7945 +2024-11-22 03:05:09.044454: val_loss -0.7651 +2024-11-22 03:05:09.044633: Pseudo dice [0.8392] +2024-11-22 03:05:09.044722: Epoch time: 19.12 s +2024-11-22 03:05:09.967685: +2024-11-22 03:05:09.967910: Epoch 3057 +2024-11-22 03:05:09.968024: Current learning rate: 0.00648 +2024-11-22 03:05:28.682872: train_loss -0.7857 +2024-11-22 03:05:28.683105: val_loss -0.7485 +2024-11-22 03:05:28.683178: Pseudo dice [0.8442] +2024-11-22 03:05:28.683253: Epoch time: 18.72 s +2024-11-22 03:05:29.544100: +2024-11-22 03:05:29.544323: Epoch 3058 +2024-11-22 03:05:29.544435: Current learning rate: 0.00648 +2024-11-22 03:05:49.331786: train_loss -0.7875 +2024-11-22 03:05:49.332010: val_loss -0.7284 +2024-11-22 03:05:49.332083: Pseudo dice [0.8418] +2024-11-22 03:05:49.332157: Epoch time: 19.79 s +2024-11-22 03:05:50.227790: +2024-11-22 03:05:50.228057: Epoch 3059 +2024-11-22 03:05:50.228170: Current learning rate: 0.00648 +2024-11-22 03:06:09.760677: train_loss -0.7728 +2024-11-22 03:06:09.760927: val_loss -0.7491 +2024-11-22 03:06:09.761013: Pseudo dice [0.8432] +2024-11-22 03:06:09.761100: Epoch time: 19.53 s +2024-11-22 03:06:10.630855: +2024-11-22 03:06:10.631062: Epoch 3060 +2024-11-22 03:06:10.631170: Current learning rate: 0.00648 +2024-11-22 03:06:30.741091: train_loss -0.782 +2024-11-22 03:06:30.743226: val_loss -0.755 +2024-11-22 03:06:30.743329: Pseudo dice [0.833] +2024-11-22 03:06:30.743406: Epoch time: 20.11 s +2024-11-22 03:06:31.604618: +2024-11-22 03:06:31.604834: Epoch 3061 +2024-11-22 03:06:31.604941: Current learning rate: 0.00648 +2024-11-22 03:06:50.235867: train_loss -0.7611 +2024-11-22 03:06:50.236089: val_loss -0.7441 +2024-11-22 03:06:50.236163: Pseudo dice [0.8414] +2024-11-22 03:06:50.236238: Epoch time: 18.63 s +2024-11-22 03:06:51.096329: +2024-11-22 03:06:51.096525: Epoch 3062 +2024-11-22 03:06:51.096632: Current learning rate: 0.00648 +2024-11-22 03:07:09.446537: train_loss -0.7754 +2024-11-22 03:07:09.446784: val_loss -0.7595 +2024-11-22 03:07:09.446865: Pseudo dice [0.8474] +2024-11-22 03:07:09.446945: Epoch time: 18.35 s +2024-11-22 03:07:10.310457: +2024-11-22 03:07:10.310709: Epoch 3063 +2024-11-22 03:07:10.310833: Current learning rate: 0.00648 +2024-11-22 03:07:28.764366: train_loss -0.7781 +2024-11-22 03:07:28.766238: val_loss -0.757 +2024-11-22 03:07:28.766335: Pseudo dice [0.8487] +2024-11-22 03:07:28.766419: Epoch time: 18.45 s +2024-11-22 03:07:29.635472: +2024-11-22 03:07:29.635683: Epoch 3064 +2024-11-22 03:07:29.635790: Current learning rate: 0.00648 +2024-11-22 03:07:47.218820: train_loss -0.7742 +2024-11-22 03:07:47.219051: val_loss -0.7856 +2024-11-22 03:07:47.219127: Pseudo dice [0.8421] +2024-11-22 03:07:47.219207: Epoch time: 17.58 s +2024-11-22 03:07:48.075607: +2024-11-22 03:07:48.075819: Epoch 3065 +2024-11-22 03:07:48.075926: Current learning rate: 0.00647 +2024-11-22 03:08:06.114337: train_loss -0.7801 +2024-11-22 03:08:06.114556: val_loss -0.7706 +2024-11-22 03:08:06.114629: Pseudo dice [0.8448] +2024-11-22 03:08:06.114703: Epoch time: 18.04 s +2024-11-22 03:08:06.969065: +2024-11-22 03:08:06.969289: Epoch 3066 +2024-11-22 03:08:06.969398: Current learning rate: 0.00647 +2024-11-22 03:08:26.552331: train_loss -0.78 +2024-11-22 03:08:26.552577: val_loss -0.7663 +2024-11-22 03:08:26.552653: Pseudo dice [0.8439] +2024-11-22 03:08:26.552774: Epoch time: 19.58 s +2024-11-22 03:08:27.819403: +2024-11-22 03:08:27.819726: Epoch 3067 +2024-11-22 03:08:27.819839: Current learning rate: 0.00647 +2024-11-22 03:08:46.387856: train_loss -0.7854 +2024-11-22 03:08:46.388087: val_loss -0.75 +2024-11-22 03:08:46.388158: Pseudo dice [0.834] +2024-11-22 03:08:46.388232: Epoch time: 18.57 s +2024-11-22 03:08:47.254025: +2024-11-22 03:08:47.254251: Epoch 3068 +2024-11-22 03:08:47.254361: Current learning rate: 0.00647 +2024-11-22 03:09:06.561225: train_loss -0.7758 +2024-11-22 03:09:06.563427: val_loss -0.7769 +2024-11-22 03:09:06.563524: Pseudo dice [0.8278] +2024-11-22 03:09:06.563602: Epoch time: 19.31 s +2024-11-22 03:09:07.440206: +2024-11-22 03:09:07.440434: Epoch 3069 +2024-11-22 03:09:07.440542: Current learning rate: 0.00647 +2024-11-22 03:09:25.518381: train_loss -0.7761 +2024-11-22 03:09:25.518628: val_loss -0.7482 +2024-11-22 03:09:25.518708: Pseudo dice [0.8469] +2024-11-22 03:09:25.518789: Epoch time: 18.08 s +2024-11-22 03:09:26.380097: +2024-11-22 03:09:26.380322: Epoch 3070 +2024-11-22 03:09:26.380433: Current learning rate: 0.00647 +2024-11-22 03:09:44.560278: train_loss -0.7716 +2024-11-22 03:09:44.560491: val_loss -0.763 +2024-11-22 03:09:44.560567: Pseudo dice [0.8385] +2024-11-22 03:09:44.560641: Epoch time: 18.18 s +2024-11-22 03:09:45.421500: +2024-11-22 03:09:45.421726: Epoch 3071 +2024-11-22 03:09:45.421838: Current learning rate: 0.00647 +2024-11-22 03:10:03.960012: train_loss -0.7828 +2024-11-22 03:10:03.960274: val_loss -0.7702 +2024-11-22 03:10:03.960352: Pseudo dice [0.8509] +2024-11-22 03:10:03.960426: Epoch time: 18.54 s +2024-11-22 03:10:04.820891: +2024-11-22 03:10:04.821221: Epoch 3072 +2024-11-22 03:10:04.821336: Current learning rate: 0.00647 +2024-11-22 03:10:23.720769: train_loss -0.7784 +2024-11-22 03:10:23.721043: val_loss -0.7831 +2024-11-22 03:10:23.721125: Pseudo dice [0.8581] +2024-11-22 03:10:23.721202: Epoch time: 18.9 s +2024-11-22 03:10:24.576142: +2024-11-22 03:10:24.576350: Epoch 3073 +2024-11-22 03:10:24.576461: Current learning rate: 0.00646 +2024-11-22 03:10:43.152045: train_loss -0.7874 +2024-11-22 03:10:43.152269: val_loss -0.7628 +2024-11-22 03:10:43.152349: Pseudo dice [0.8479] +2024-11-22 03:10:43.152430: Epoch time: 18.58 s +2024-11-22 03:10:44.017984: +2024-11-22 03:10:44.018276: Epoch 3074 +2024-11-22 03:10:44.018385: Current learning rate: 0.00646 +2024-11-22 03:11:03.221778: train_loss -0.7862 +2024-11-22 03:11:03.222034: val_loss -0.7701 +2024-11-22 03:11:03.222114: Pseudo dice [0.8531] +2024-11-22 03:11:03.222198: Epoch time: 19.2 s +2024-11-22 03:11:04.077575: +2024-11-22 03:11:04.077815: Epoch 3075 +2024-11-22 03:11:04.077930: Current learning rate: 0.00646 +2024-11-22 03:11:23.111443: train_loss -0.7934 +2024-11-22 03:11:23.111670: val_loss -0.7765 +2024-11-22 03:11:23.111745: Pseudo dice [0.8532] +2024-11-22 03:11:23.111822: Epoch time: 19.03 s +2024-11-22 03:11:23.963663: +2024-11-22 03:11:23.963885: Epoch 3076 +2024-11-22 03:11:23.964018: Current learning rate: 0.00646 +2024-11-22 03:11:42.525984: train_loss -0.7882 +2024-11-22 03:11:42.526210: val_loss -0.7819 +2024-11-22 03:11:42.526287: Pseudo dice [0.8409] +2024-11-22 03:11:42.526362: Epoch time: 18.56 s +2024-11-22 03:11:43.395828: +2024-11-22 03:11:43.396118: Epoch 3077 +2024-11-22 03:11:43.396230: Current learning rate: 0.00646 +2024-11-22 03:12:02.600828: train_loss -0.792 +2024-11-22 03:12:02.601079: val_loss -0.7839 +2024-11-22 03:12:02.601156: Pseudo dice [0.8528] +2024-11-22 03:12:02.601236: Epoch time: 19.21 s +2024-11-22 03:12:03.459907: +2024-11-22 03:12:03.460122: Epoch 3078 +2024-11-22 03:12:03.460233: Current learning rate: 0.00646 +2024-11-22 03:12:23.263501: train_loss -0.7815 +2024-11-22 03:12:23.263960: val_loss -0.7626 +2024-11-22 03:12:23.264061: Pseudo dice [0.845] +2024-11-22 03:12:23.264139: Epoch time: 19.8 s +2024-11-22 03:12:24.184511: +2024-11-22 03:12:24.184731: Epoch 3079 +2024-11-22 03:12:24.184841: Current learning rate: 0.00646 +2024-11-22 03:12:43.264288: train_loss -0.7832 +2024-11-22 03:12:43.264520: val_loss -0.7583 +2024-11-22 03:12:43.264593: Pseudo dice [0.837] +2024-11-22 03:12:43.264665: Epoch time: 19.08 s +2024-11-22 03:12:44.146686: +2024-11-22 03:12:44.146913: Epoch 3080 +2024-11-22 03:12:44.147032: Current learning rate: 0.00646 +2024-11-22 03:13:02.908016: train_loss -0.7736 +2024-11-22 03:13:02.908278: val_loss -0.7531 +2024-11-22 03:13:02.908357: Pseudo dice [0.8451] +2024-11-22 03:13:02.908443: Epoch time: 18.76 s +2024-11-22 03:13:03.770963: +2024-11-22 03:13:03.771192: Epoch 3081 +2024-11-22 03:13:03.771299: Current learning rate: 0.00646 +2024-11-22 03:13:23.134203: train_loss -0.7699 +2024-11-22 03:13:23.134410: val_loss -0.7573 +2024-11-22 03:13:23.134486: Pseudo dice [0.8549] +2024-11-22 03:13:23.134561: Epoch time: 19.36 s +2024-11-22 03:13:23.988335: +2024-11-22 03:13:23.988552: Epoch 3082 +2024-11-22 03:13:23.988659: Current learning rate: 0.00645 +2024-11-22 03:13:41.958701: train_loss -0.7851 +2024-11-22 03:13:41.958922: val_loss -0.7696 +2024-11-22 03:13:41.959003: Pseudo dice [0.8453] +2024-11-22 03:13:41.959078: Epoch time: 17.97 s +2024-11-22 03:13:42.965953: +2024-11-22 03:13:42.966176: Epoch 3083 +2024-11-22 03:13:42.966392: Current learning rate: 0.00645 +2024-11-22 03:14:01.060857: train_loss -0.7842 +2024-11-22 03:14:01.061085: val_loss -0.7567 +2024-11-22 03:14:01.061169: Pseudo dice [0.841] +2024-11-22 03:14:01.061249: Epoch time: 18.1 s +2024-11-22 03:14:01.924047: +2024-11-22 03:14:01.924267: Epoch 3084 +2024-11-22 03:14:01.924382: Current learning rate: 0.00645 +2024-11-22 03:14:21.357954: train_loss -0.7734 +2024-11-22 03:14:21.358204: val_loss -0.7673 +2024-11-22 03:14:21.358281: Pseudo dice [0.8502] +2024-11-22 03:14:21.358363: Epoch time: 19.43 s +2024-11-22 03:14:22.213531: +2024-11-22 03:14:22.213750: Epoch 3085 +2024-11-22 03:14:22.213856: Current learning rate: 0.00645 +2024-11-22 03:14:40.181072: train_loss -0.7849 +2024-11-22 03:14:40.181300: val_loss -0.7628 +2024-11-22 03:14:40.181374: Pseudo dice [0.8507] +2024-11-22 03:14:40.181449: Epoch time: 17.97 s +2024-11-22 03:14:41.035571: +2024-11-22 03:14:41.035789: Epoch 3086 +2024-11-22 03:14:41.035899: Current learning rate: 0.00645 +2024-11-22 03:14:59.995672: train_loss -0.7865 +2024-11-22 03:14:59.995893: val_loss -0.7581 +2024-11-22 03:14:59.995969: Pseudo dice [0.8391] +2024-11-22 03:14:59.996049: Epoch time: 18.96 s +2024-11-22 03:15:00.864725: +2024-11-22 03:15:00.864934: Epoch 3087 +2024-11-22 03:15:00.865045: Current learning rate: 0.00645 +2024-11-22 03:15:18.874513: train_loss -0.783 +2024-11-22 03:15:18.874750: val_loss -0.7702 +2024-11-22 03:15:18.874825: Pseudo dice [0.8271] +2024-11-22 03:15:18.874916: Epoch time: 18.01 s +2024-11-22 03:15:19.726587: +2024-11-22 03:15:19.726783: Epoch 3088 +2024-11-22 03:15:19.726895: Current learning rate: 0.00645 +2024-11-22 03:15:37.742045: train_loss -0.7928 +2024-11-22 03:15:37.742268: val_loss -0.7703 +2024-11-22 03:15:37.742405: Pseudo dice [0.8459] +2024-11-22 03:15:37.742485: Epoch time: 18.02 s +2024-11-22 03:15:38.595184: +2024-11-22 03:15:38.595416: Epoch 3089 +2024-11-22 03:15:38.595522: Current learning rate: 0.00645 +2024-11-22 03:15:57.666594: train_loss -0.7943 +2024-11-22 03:15:57.666814: val_loss -0.759 +2024-11-22 03:15:57.666889: Pseudo dice [0.8376] +2024-11-22 03:15:57.666975: Epoch time: 19.07 s +2024-11-22 03:15:58.909349: +2024-11-22 03:15:58.909579: Epoch 3090 +2024-11-22 03:15:58.909692: Current learning rate: 0.00644 +2024-11-22 03:16:17.326875: train_loss -0.7805 +2024-11-22 03:16:17.327161: val_loss -0.7556 +2024-11-22 03:16:17.327245: Pseudo dice [0.8334] +2024-11-22 03:16:17.327335: Epoch time: 18.42 s +2024-11-22 03:16:18.228431: +2024-11-22 03:16:18.228652: Epoch 3091 +2024-11-22 03:16:18.228765: Current learning rate: 0.00644 +2024-11-22 03:16:36.453173: train_loss -0.7917 +2024-11-22 03:16:36.453393: val_loss -0.764 +2024-11-22 03:16:36.453470: Pseudo dice [0.8394] +2024-11-22 03:16:36.453546: Epoch time: 18.23 s +2024-11-22 03:16:37.315248: +2024-11-22 03:16:37.315471: Epoch 3092 +2024-11-22 03:16:37.315583: Current learning rate: 0.00644 +2024-11-22 03:16:55.527508: train_loss -0.7849 +2024-11-22 03:16:55.527731: val_loss -0.7822 +2024-11-22 03:16:55.527810: Pseudo dice [0.8414] +2024-11-22 03:16:55.527884: Epoch time: 18.21 s +2024-11-22 03:16:56.488665: +2024-11-22 03:16:56.488948: Epoch 3093 +2024-11-22 03:16:56.489065: Current learning rate: 0.00644 +2024-11-22 03:17:15.060488: train_loss -0.7877 +2024-11-22 03:17:15.060701: val_loss -0.7654 +2024-11-22 03:17:15.060775: Pseudo dice [0.8381] +2024-11-22 03:17:15.060849: Epoch time: 18.57 s +2024-11-22 03:17:15.922688: +2024-11-22 03:17:15.922889: Epoch 3094 +2024-11-22 03:17:15.923002: Current learning rate: 0.00644 +2024-11-22 03:17:35.110483: train_loss -0.7872 +2024-11-22 03:17:35.110727: val_loss -0.783 +2024-11-22 03:17:35.110803: Pseudo dice [0.8392] +2024-11-22 03:17:35.111206: Epoch time: 19.19 s +2024-11-22 03:17:36.074970: +2024-11-22 03:17:36.075203: Epoch 3095 +2024-11-22 03:17:36.075318: Current learning rate: 0.00644 +2024-11-22 03:17:53.903476: train_loss -0.7878 +2024-11-22 03:17:53.903689: val_loss -0.7618 +2024-11-22 03:17:53.903764: Pseudo dice [0.8339] +2024-11-22 03:17:53.903838: Epoch time: 17.83 s +2024-11-22 03:17:54.757915: +2024-11-22 03:17:54.758140: Epoch 3096 +2024-11-22 03:17:54.758246: Current learning rate: 0.00644 +2024-11-22 03:18:12.881838: train_loss -0.7858 +2024-11-22 03:18:12.882064: val_loss -0.7659 +2024-11-22 03:18:12.882139: Pseudo dice [0.8432] +2024-11-22 03:18:12.882211: Epoch time: 18.12 s +2024-11-22 03:18:13.741854: +2024-11-22 03:18:13.742081: Epoch 3097 +2024-11-22 03:18:13.742204: Current learning rate: 0.00644 +2024-11-22 03:18:32.716229: train_loss -0.7846 +2024-11-22 03:18:32.716437: val_loss -0.7686 +2024-11-22 03:18:32.716511: Pseudo dice [0.8169] +2024-11-22 03:18:32.716584: Epoch time: 18.98 s +2024-11-22 03:18:33.577553: +2024-11-22 03:18:33.577834: Epoch 3098 +2024-11-22 03:18:33.577959: Current learning rate: 0.00644 +2024-11-22 03:18:53.502673: train_loss -0.7817 +2024-11-22 03:18:53.502930: val_loss -0.7723 +2024-11-22 03:18:53.503013: Pseudo dice [0.8472] +2024-11-22 03:18:53.503094: Epoch time: 19.93 s +2024-11-22 03:18:54.365407: +2024-11-22 03:18:54.365627: Epoch 3099 +2024-11-22 03:18:54.365738: Current learning rate: 0.00643 +2024-11-22 03:19:12.755252: train_loss -0.78 +2024-11-22 03:19:12.755468: val_loss -0.7413 +2024-11-22 03:19:12.755544: Pseudo dice [0.8228] +2024-11-22 03:19:12.755621: Epoch time: 18.39 s +2024-11-22 03:19:13.838446: +2024-11-22 03:19:13.838665: Epoch 3100 +2024-11-22 03:19:13.838774: Current learning rate: 0.00643 +2024-11-22 03:19:32.555331: train_loss -0.7778 +2024-11-22 03:19:32.555556: val_loss -0.7696 +2024-11-22 03:19:32.555630: Pseudo dice [0.8459] +2024-11-22 03:19:32.555704: Epoch time: 18.72 s +2024-11-22 03:19:33.841695: +2024-11-22 03:19:33.841943: Epoch 3101 +2024-11-22 03:19:33.842066: Current learning rate: 0.00643 +2024-11-22 03:19:51.821349: train_loss -0.7778 +2024-11-22 03:19:51.821605: val_loss -0.7839 +2024-11-22 03:19:51.821705: Pseudo dice [0.8491] +2024-11-22 03:19:51.821792: Epoch time: 17.98 s +2024-11-22 03:19:52.675138: +2024-11-22 03:19:52.675343: Epoch 3102 +2024-11-22 03:19:52.675452: Current learning rate: 0.00643 +2024-11-22 03:20:11.428025: train_loss -0.775 +2024-11-22 03:20:11.428245: val_loss -0.7758 +2024-11-22 03:20:11.428323: Pseudo dice [0.8461] +2024-11-22 03:20:11.428410: Epoch time: 18.75 s +2024-11-22 03:20:12.281743: +2024-11-22 03:20:12.281984: Epoch 3103 +2024-11-22 03:20:12.282101: Current learning rate: 0.00643 +2024-11-22 03:20:29.864110: train_loss -0.7743 +2024-11-22 03:20:29.864319: val_loss -0.7524 +2024-11-22 03:20:29.864393: Pseudo dice [0.8424] +2024-11-22 03:20:29.864469: Epoch time: 17.58 s +2024-11-22 03:20:30.748654: +2024-11-22 03:20:30.748878: Epoch 3104 +2024-11-22 03:20:30.748999: Current learning rate: 0.00643 +2024-11-22 03:20:49.638727: train_loss -0.7762 +2024-11-22 03:20:49.639022: val_loss -0.7628 +2024-11-22 03:20:49.639100: Pseudo dice [0.8275] +2024-11-22 03:20:49.639182: Epoch time: 18.89 s +2024-11-22 03:20:50.519730: +2024-11-22 03:20:50.519950: Epoch 3105 +2024-11-22 03:20:50.520067: Current learning rate: 0.00643 +2024-11-22 03:21:09.094344: train_loss -0.7718 +2024-11-22 03:21:09.094581: val_loss -0.7378 +2024-11-22 03:21:09.094656: Pseudo dice [0.8476] +2024-11-22 03:21:09.094733: Epoch time: 18.58 s +2024-11-22 03:21:09.961499: +2024-11-22 03:21:09.961715: Epoch 3106 +2024-11-22 03:21:09.961834: Current learning rate: 0.00643 +2024-11-22 03:21:28.662539: train_loss -0.7601 +2024-11-22 03:21:28.662755: val_loss -0.7439 +2024-11-22 03:21:28.662833: Pseudo dice [0.832] +2024-11-22 03:21:28.662907: Epoch time: 18.7 s +2024-11-22 03:21:29.525178: +2024-11-22 03:21:29.525444: Epoch 3107 +2024-11-22 03:21:29.525557: Current learning rate: 0.00642 +2024-11-22 03:21:48.809086: train_loss -0.76 +2024-11-22 03:21:48.809304: val_loss -0.7789 +2024-11-22 03:21:48.809381: Pseudo dice [0.8561] +2024-11-22 03:21:48.809455: Epoch time: 19.28 s +2024-11-22 03:21:49.678358: +2024-11-22 03:21:49.678582: Epoch 3108 +2024-11-22 03:21:49.678698: Current learning rate: 0.00642 +2024-11-22 03:22:07.891934: train_loss -0.7858 +2024-11-22 03:22:07.892231: val_loss -0.7614 +2024-11-22 03:22:07.892308: Pseudo dice [0.8356] +2024-11-22 03:22:07.892386: Epoch time: 18.21 s +2024-11-22 03:22:09.079998: +2024-11-22 03:22:09.080211: Epoch 3109 +2024-11-22 03:22:09.080323: Current learning rate: 0.00642 +2024-11-22 03:22:28.152581: train_loss -0.7754 +2024-11-22 03:22:28.152846: val_loss -0.7561 +2024-11-22 03:22:28.152921: Pseudo dice [0.8245] +2024-11-22 03:22:28.153011: Epoch time: 19.07 s +2024-11-22 03:22:29.053566: +2024-11-22 03:22:29.053790: Epoch 3110 +2024-11-22 03:22:29.053900: Current learning rate: 0.00642 +2024-11-22 03:22:47.632729: train_loss -0.7811 +2024-11-22 03:22:47.632947: val_loss -0.7494 +2024-11-22 03:22:47.633032: Pseudo dice [0.8497] +2024-11-22 03:22:47.633108: Epoch time: 18.58 s +2024-11-22 03:22:48.489692: +2024-11-22 03:22:48.489903: Epoch 3111 +2024-11-22 03:22:48.490016: Current learning rate: 0.00642 +2024-11-22 03:23:06.693074: train_loss -0.7833 +2024-11-22 03:23:06.693289: val_loss -0.7867 +2024-11-22 03:23:06.693366: Pseudo dice [0.8365] +2024-11-22 03:23:06.693457: Epoch time: 18.2 s +2024-11-22 03:23:07.548805: +2024-11-22 03:23:07.549034: Epoch 3112 +2024-11-22 03:23:07.549147: Current learning rate: 0.00642 +2024-11-22 03:23:26.968604: train_loss -0.7785 +2024-11-22 03:23:26.969191: val_loss -0.7541 +2024-11-22 03:23:26.969290: Pseudo dice [0.8244] +2024-11-22 03:23:26.969380: Epoch time: 19.42 s +2024-11-22 03:23:27.826881: +2024-11-22 03:23:27.827126: Epoch 3113 +2024-11-22 03:23:27.827243: Current learning rate: 0.00642 +2024-11-22 03:23:46.201793: train_loss -0.7765 +2024-11-22 03:23:46.202084: val_loss -0.7388 +2024-11-22 03:23:46.202160: Pseudo dice [0.8202] +2024-11-22 03:23:46.202234: Epoch time: 18.38 s +2024-11-22 03:23:47.061666: +2024-11-22 03:23:47.061887: Epoch 3114 +2024-11-22 03:23:47.062000: Current learning rate: 0.00642 +2024-11-22 03:24:05.801213: train_loss -0.7723 +2024-11-22 03:24:05.801426: val_loss -0.7896 +2024-11-22 03:24:05.801500: Pseudo dice [0.8614] +2024-11-22 03:24:05.801572: Epoch time: 18.74 s +2024-11-22 03:24:06.650651: +2024-11-22 03:24:06.650874: Epoch 3115 +2024-11-22 03:24:06.650986: Current learning rate: 0.00642 +2024-11-22 03:24:25.794412: train_loss -0.7719 +2024-11-22 03:24:25.794660: val_loss -0.7742 +2024-11-22 03:24:25.794737: Pseudo dice [0.8446] +2024-11-22 03:24:25.794822: Epoch time: 19.14 s +2024-11-22 03:24:26.661026: +2024-11-22 03:24:26.661225: Epoch 3116 +2024-11-22 03:24:26.661333: Current learning rate: 0.00641 +2024-11-22 03:24:45.222802: train_loss -0.7535 +2024-11-22 03:24:45.223044: val_loss -0.7422 +2024-11-22 03:24:45.223122: Pseudo dice [0.8433] +2024-11-22 03:24:45.223195: Epoch time: 18.56 s +2024-11-22 03:24:46.079920: +2024-11-22 03:24:46.080235: Epoch 3117 +2024-11-22 03:24:46.080356: Current learning rate: 0.00641 +2024-11-22 03:25:04.882136: train_loss -0.7658 +2024-11-22 03:25:04.882365: val_loss -0.7675 +2024-11-22 03:25:04.882441: Pseudo dice [0.8413] +2024-11-22 03:25:04.882516: Epoch time: 18.8 s +2024-11-22 03:25:05.750335: +2024-11-22 03:25:05.750562: Epoch 3118 +2024-11-22 03:25:05.750669: Current learning rate: 0.00641 +2024-11-22 03:25:24.182627: train_loss -0.7852 +2024-11-22 03:25:24.182847: val_loss -0.7588 +2024-11-22 03:25:24.182925: Pseudo dice [0.833] +2024-11-22 03:25:24.183005: Epoch time: 18.43 s +2024-11-22 03:25:25.042902: +2024-11-22 03:25:25.043143: Epoch 3119 +2024-11-22 03:25:25.043255: Current learning rate: 0.00641 +2024-11-22 03:25:43.759804: train_loss -0.7837 +2024-11-22 03:25:43.760050: val_loss -0.7514 +2024-11-22 03:25:43.760141: Pseudo dice [0.8423] +2024-11-22 03:25:43.760283: Epoch time: 18.72 s +2024-11-22 03:25:44.618944: +2024-11-22 03:25:44.619168: Epoch 3120 +2024-11-22 03:25:44.619285: Current learning rate: 0.00641 +2024-11-22 03:26:03.448364: train_loss -0.7812 +2024-11-22 03:26:03.448596: val_loss -0.7682 +2024-11-22 03:26:03.448668: Pseudo dice [0.8528] +2024-11-22 03:26:03.448988: Epoch time: 18.83 s +2024-11-22 03:26:04.433975: +2024-11-22 03:26:04.434197: Epoch 3121 +2024-11-22 03:26:04.434306: Current learning rate: 0.00641 +2024-11-22 03:26:23.355627: train_loss -0.7726 +2024-11-22 03:26:23.355848: val_loss -0.7713 +2024-11-22 03:26:23.355925: Pseudo dice [0.8218] +2024-11-22 03:26:23.356009: Epoch time: 18.92 s +2024-11-22 03:26:24.213689: +2024-11-22 03:26:24.213966: Epoch 3122 +2024-11-22 03:26:24.214079: Current learning rate: 0.00641 +2024-11-22 03:26:42.668954: train_loss -0.7676 +2024-11-22 03:26:42.669187: val_loss -0.7645 +2024-11-22 03:26:42.669263: Pseudo dice [0.8416] +2024-11-22 03:26:42.669341: Epoch time: 18.46 s +2024-11-22 03:26:43.533237: +2024-11-22 03:26:43.533453: Epoch 3123 +2024-11-22 03:26:43.535740: Current learning rate: 0.00641 +2024-11-22 03:27:01.442709: train_loss -0.7807 +2024-11-22 03:27:01.442961: val_loss -0.7724 +2024-11-22 03:27:01.443049: Pseudo dice [0.8525] +2024-11-22 03:27:01.443134: Epoch time: 17.91 s +2024-11-22 03:27:02.668040: +2024-11-22 03:27:02.668263: Epoch 3124 +2024-11-22 03:27:02.668377: Current learning rate: 0.0064 +2024-11-22 03:27:21.241754: train_loss -0.7826 +2024-11-22 03:27:21.241985: val_loss -0.7853 +2024-11-22 03:27:21.242072: Pseudo dice [0.8485] +2024-11-22 03:27:21.242155: Epoch time: 18.57 s +2024-11-22 03:27:22.107255: +2024-11-22 03:27:22.107549: Epoch 3125 +2024-11-22 03:27:22.107660: Current learning rate: 0.0064 +2024-11-22 03:27:40.189254: train_loss -0.7867 +2024-11-22 03:27:40.189483: val_loss -0.7675 +2024-11-22 03:27:40.189564: Pseudo dice [0.8513] +2024-11-22 03:27:40.189644: Epoch time: 18.08 s +2024-11-22 03:27:41.052760: +2024-11-22 03:27:41.053063: Epoch 3126 +2024-11-22 03:27:41.053175: Current learning rate: 0.0064 +2024-11-22 03:27:59.483742: train_loss -0.7911 +2024-11-22 03:27:59.483979: val_loss -0.7861 +2024-11-22 03:27:59.484063: Pseudo dice [0.8475] +2024-11-22 03:27:59.484139: Epoch time: 18.43 s +2024-11-22 03:28:00.349111: +2024-11-22 03:28:00.349357: Epoch 3127 +2024-11-22 03:28:00.349472: Current learning rate: 0.0064 +2024-11-22 03:28:18.173153: train_loss -0.7812 +2024-11-22 03:28:18.173368: val_loss -0.7574 +2024-11-22 03:28:18.173441: Pseudo dice [0.8505] +2024-11-22 03:28:18.173517: Epoch time: 17.82 s +2024-11-22 03:28:19.035806: +2024-11-22 03:28:19.036025: Epoch 3128 +2024-11-22 03:28:19.036137: Current learning rate: 0.0064 +2024-11-22 03:28:36.601430: train_loss -0.7764 +2024-11-22 03:28:36.601653: val_loss -0.7732 +2024-11-22 03:28:36.601728: Pseudo dice [0.8422] +2024-11-22 03:28:36.601803: Epoch time: 17.57 s +2024-11-22 03:28:37.466903: +2024-11-22 03:28:37.467134: Epoch 3129 +2024-11-22 03:28:37.467243: Current learning rate: 0.0064 +2024-11-22 03:28:56.096506: train_loss -0.7613 +2024-11-22 03:28:56.096722: val_loss -0.7588 +2024-11-22 03:28:56.096801: Pseudo dice [0.8257] +2024-11-22 03:28:56.096880: Epoch time: 18.63 s +2024-11-22 03:28:56.954245: +2024-11-22 03:28:56.954509: Epoch 3130 +2024-11-22 03:28:56.954615: Current learning rate: 0.0064 +2024-11-22 03:29:15.129261: train_loss -0.778 +2024-11-22 03:29:15.129532: val_loss -0.7809 +2024-11-22 03:29:15.129608: Pseudo dice [0.8518] +2024-11-22 03:29:15.129691: Epoch time: 18.18 s +2024-11-22 03:29:15.992208: +2024-11-22 03:29:15.992428: Epoch 3131 +2024-11-22 03:29:15.992547: Current learning rate: 0.0064 +2024-11-22 03:29:34.518085: train_loss -0.7676 +2024-11-22 03:29:34.518305: val_loss -0.788 +2024-11-22 03:29:34.518379: Pseudo dice [0.8579] +2024-11-22 03:29:34.518461: Epoch time: 18.53 s +2024-11-22 03:29:35.377702: +2024-11-22 03:29:35.377935: Epoch 3132 +2024-11-22 03:29:35.378053: Current learning rate: 0.00639 +2024-11-22 03:29:53.972998: train_loss -0.766 +2024-11-22 03:29:53.973220: val_loss -0.747 +2024-11-22 03:29:53.973327: Pseudo dice [0.8135] +2024-11-22 03:29:53.973415: Epoch time: 18.6 s +2024-11-22 03:29:54.835257: +2024-11-22 03:29:54.835490: Epoch 3133 +2024-11-22 03:29:54.835601: Current learning rate: 0.00639 +2024-11-22 03:30:14.600511: train_loss -0.7632 +2024-11-22 03:30:14.600850: val_loss -0.7491 +2024-11-22 03:30:14.600956: Pseudo dice [0.8388] +2024-11-22 03:30:14.601048: Epoch time: 19.77 s +2024-11-22 03:30:15.469819: +2024-11-22 03:30:15.470028: Epoch 3134 +2024-11-22 03:30:15.470140: Current learning rate: 0.00639 +2024-11-22 03:30:33.172263: train_loss -0.7713 +2024-11-22 03:30:33.172486: val_loss -0.7935 +2024-11-22 03:30:33.172556: Pseudo dice [0.8522] +2024-11-22 03:30:33.172632: Epoch time: 17.7 s +2024-11-22 03:30:34.550538: +2024-11-22 03:30:34.550759: Epoch 3135 +2024-11-22 03:30:34.550869: Current learning rate: 0.00639 +2024-11-22 03:30:53.033376: train_loss -0.7807 +2024-11-22 03:30:53.033592: val_loss -0.7698 +2024-11-22 03:30:53.033665: Pseudo dice [0.8198] +2024-11-22 03:30:53.033736: Epoch time: 18.48 s +2024-11-22 03:30:53.892013: +2024-11-22 03:30:53.892242: Epoch 3136 +2024-11-22 03:30:53.892349: Current learning rate: 0.00639 +2024-11-22 03:31:11.783798: train_loss -0.7854 +2024-11-22 03:31:11.784069: val_loss -0.7641 +2024-11-22 03:31:11.784159: Pseudo dice [0.843] +2024-11-22 03:31:11.784251: Epoch time: 17.89 s +2024-11-22 03:31:12.648465: +2024-11-22 03:31:12.648690: Epoch 3137 +2024-11-22 03:31:12.648796: Current learning rate: 0.00639 +2024-11-22 03:31:31.660721: train_loss -0.7678 +2024-11-22 03:31:31.660951: val_loss -0.7601 +2024-11-22 03:31:31.661041: Pseudo dice [0.835] +2024-11-22 03:31:31.661139: Epoch time: 19.01 s +2024-11-22 03:31:32.523571: +2024-11-22 03:31:32.523862: Epoch 3138 +2024-11-22 03:31:32.523974: Current learning rate: 0.00639 +2024-11-22 03:31:51.794664: train_loss -0.789 +2024-11-22 03:31:51.794878: val_loss -0.7889 +2024-11-22 03:31:51.794953: Pseudo dice [0.8406] +2024-11-22 03:31:51.795033: Epoch time: 19.27 s +2024-11-22 03:31:52.674225: +2024-11-22 03:31:52.674468: Epoch 3139 +2024-11-22 03:31:52.674586: Current learning rate: 0.00639 +2024-11-22 03:32:10.798368: train_loss -0.7753 +2024-11-22 03:32:10.798589: val_loss -0.7813 +2024-11-22 03:32:10.798663: Pseudo dice [0.8568] +2024-11-22 03:32:10.798740: Epoch time: 18.12 s +2024-11-22 03:32:11.655979: +2024-11-22 03:32:11.656198: Epoch 3140 +2024-11-22 03:32:11.656311: Current learning rate: 0.00639 +2024-11-22 03:32:30.625738: train_loss -0.786 +2024-11-22 03:32:30.625959: val_loss -0.7556 +2024-11-22 03:32:30.626047: Pseudo dice [0.8336] +2024-11-22 03:32:30.626128: Epoch time: 18.97 s +2024-11-22 03:32:31.487772: +2024-11-22 03:32:31.488033: Epoch 3141 +2024-11-22 03:32:31.488141: Current learning rate: 0.00638 +2024-11-22 03:32:49.724458: train_loss -0.7721 +2024-11-22 03:32:49.729905: val_loss -0.7708 +2024-11-22 03:32:49.730039: Pseudo dice [0.8351] +2024-11-22 03:32:49.730133: Epoch time: 18.24 s +2024-11-22 03:32:50.725929: +2024-11-22 03:32:50.726157: Epoch 3142 +2024-11-22 03:32:50.726266: Current learning rate: 0.00638 +2024-11-22 03:33:09.157660: train_loss -0.7664 +2024-11-22 03:33:09.157879: val_loss -0.748 +2024-11-22 03:33:09.157952: Pseudo dice [0.83] +2024-11-22 03:33:09.158032: Epoch time: 18.43 s +2024-11-22 03:33:10.013383: +2024-11-22 03:33:10.013605: Epoch 3143 +2024-11-22 03:33:10.013717: Current learning rate: 0.00638 +2024-11-22 03:33:28.387387: train_loss -0.7746 +2024-11-22 03:33:28.387609: val_loss -0.7798 +2024-11-22 03:33:28.387686: Pseudo dice [0.8391] +2024-11-22 03:33:28.392955: Epoch time: 18.37 s +2024-11-22 03:33:29.491209: +2024-11-22 03:33:29.491420: Epoch 3144 +2024-11-22 03:33:29.491530: Current learning rate: 0.00638 +2024-11-22 03:33:48.922521: train_loss -0.7806 +2024-11-22 03:33:48.922758: val_loss -0.773 +2024-11-22 03:33:48.922897: Pseudo dice [0.8337] +2024-11-22 03:33:48.922986: Epoch time: 19.43 s +2024-11-22 03:33:49.776951: +2024-11-22 03:33:49.777150: Epoch 3145 +2024-11-22 03:33:49.777264: Current learning rate: 0.00638 +2024-11-22 03:34:08.624421: train_loss -0.776 +2024-11-22 03:34:08.624641: val_loss -0.7449 +2024-11-22 03:34:08.624731: Pseudo dice [0.8499] +2024-11-22 03:34:08.624861: Epoch time: 18.85 s +2024-11-22 03:34:09.486430: +2024-11-22 03:34:09.486624: Epoch 3146 +2024-11-22 03:34:09.486739: Current learning rate: 0.00638 +2024-11-22 03:34:28.961212: train_loss -0.7759 +2024-11-22 03:34:28.961434: val_loss -0.7316 +2024-11-22 03:34:28.961739: Pseudo dice [0.8386] +2024-11-22 03:34:28.961885: Epoch time: 19.48 s +2024-11-22 03:34:30.223341: +2024-11-22 03:34:30.223568: Epoch 3147 +2024-11-22 03:34:30.223674: Current learning rate: 0.00638 +2024-11-22 03:34:48.530360: train_loss -0.7715 +2024-11-22 03:34:48.530634: val_loss -0.757 +2024-11-22 03:34:48.530711: Pseudo dice [0.8555] +2024-11-22 03:34:48.533013: Epoch time: 18.31 s +2024-11-22 03:34:49.447680: +2024-11-22 03:34:49.447912: Epoch 3148 +2024-11-22 03:34:49.448030: Current learning rate: 0.00638 +2024-11-22 03:35:08.208169: train_loss -0.7746 +2024-11-22 03:35:08.208386: val_loss -0.7563 +2024-11-22 03:35:08.208463: Pseudo dice [0.8593] +2024-11-22 03:35:08.208539: Epoch time: 18.76 s +2024-11-22 03:35:09.100060: +2024-11-22 03:35:09.100301: Epoch 3149 +2024-11-22 03:35:09.100419: Current learning rate: 0.00637 +2024-11-22 03:35:26.296235: train_loss -0.7694 +2024-11-22 03:35:26.296464: val_loss -0.7573 +2024-11-22 03:35:26.296541: Pseudo dice [0.834] +2024-11-22 03:35:26.296659: Epoch time: 17.2 s +2024-11-22 03:35:27.399705: +2024-11-22 03:35:27.399905: Epoch 3150 +2024-11-22 03:35:27.400019: Current learning rate: 0.00637 +2024-11-22 03:35:46.339840: train_loss -0.7741 +2024-11-22 03:35:46.340143: val_loss -0.7875 +2024-11-22 03:35:46.340224: Pseudo dice [0.8352] +2024-11-22 03:35:46.340304: Epoch time: 18.94 s +2024-11-22 03:35:47.200792: +2024-11-22 03:35:47.201022: Epoch 3151 +2024-11-22 03:35:47.201132: Current learning rate: 0.00637 +2024-11-22 03:36:06.467636: train_loss -0.7828 +2024-11-22 03:36:06.467875: val_loss -0.7523 +2024-11-22 03:36:06.467953: Pseudo dice [0.8481] +2024-11-22 03:36:06.468040: Epoch time: 19.27 s +2024-11-22 03:36:07.334721: +2024-11-22 03:36:07.334918: Epoch 3152 +2024-11-22 03:36:07.335028: Current learning rate: 0.00637 +2024-11-22 03:36:26.469783: train_loss -0.7801 +2024-11-22 03:36:26.470005: val_loss -0.763 +2024-11-22 03:36:26.470085: Pseudo dice [0.8432] +2024-11-22 03:36:26.470160: Epoch time: 19.14 s +2024-11-22 03:36:27.326409: +2024-11-22 03:36:27.326607: Epoch 3153 +2024-11-22 03:36:27.326717: Current learning rate: 0.00637 +2024-11-22 03:36:45.693755: train_loss -0.7836 +2024-11-22 03:36:45.693985: val_loss -0.7621 +2024-11-22 03:36:45.694071: Pseudo dice [0.8447] +2024-11-22 03:36:45.694150: Epoch time: 18.37 s +2024-11-22 03:36:46.580396: +2024-11-22 03:36:46.580631: Epoch 3154 +2024-11-22 03:36:46.580743: Current learning rate: 0.00637 +2024-11-22 03:37:04.938055: train_loss -0.7909 +2024-11-22 03:37:04.938267: val_loss -0.7903 +2024-11-22 03:37:04.938346: Pseudo dice [0.8529] +2024-11-22 03:37:04.938428: Epoch time: 18.36 s +2024-11-22 03:37:05.801262: +2024-11-22 03:37:05.801486: Epoch 3155 +2024-11-22 03:37:05.801596: Current learning rate: 0.00637 +2024-11-22 03:37:24.852674: train_loss -0.7721 +2024-11-22 03:37:24.852897: val_loss -0.7818 +2024-11-22 03:37:24.852971: Pseudo dice [0.8605] +2024-11-22 03:37:24.853058: Epoch time: 19.05 s +2024-11-22 03:37:25.712840: +2024-11-22 03:37:25.713061: Epoch 3156 +2024-11-22 03:37:25.713172: Current learning rate: 0.00637 +2024-11-22 03:37:44.027201: train_loss -0.7852 +2024-11-22 03:37:44.027430: val_loss -0.7414 +2024-11-22 03:37:44.027505: Pseudo dice [0.8217] +2024-11-22 03:37:44.027581: Epoch time: 18.32 s +2024-11-22 03:37:44.888937: +2024-11-22 03:37:44.889166: Epoch 3157 +2024-11-22 03:37:44.889274: Current learning rate: 0.00637 +2024-11-22 03:38:04.392712: train_loss -0.7818 +2024-11-22 03:38:04.392954: val_loss -0.7803 +2024-11-22 03:38:04.393037: Pseudo dice [0.8251] +2024-11-22 03:38:04.394279: Epoch time: 19.5 s +2024-11-22 03:38:05.710831: +2024-11-22 03:38:05.711079: Epoch 3158 +2024-11-22 03:38:05.711207: Current learning rate: 0.00636 +2024-11-22 03:38:24.820264: train_loss -0.7828 +2024-11-22 03:38:24.820518: val_loss -0.7664 +2024-11-22 03:38:24.820600: Pseudo dice [0.8398] +2024-11-22 03:38:24.820679: Epoch time: 19.11 s +2024-11-22 03:38:25.683002: +2024-11-22 03:38:25.683276: Epoch 3159 +2024-11-22 03:38:25.683386: Current learning rate: 0.00636 +2024-11-22 03:38:44.489520: train_loss -0.7789 +2024-11-22 03:38:44.489738: val_loss -0.7517 +2024-11-22 03:38:44.489810: Pseudo dice [0.8292] +2024-11-22 03:38:44.489883: Epoch time: 18.81 s +2024-11-22 03:38:45.408104: +2024-11-22 03:38:45.408324: Epoch 3160 +2024-11-22 03:38:45.408442: Current learning rate: 0.00636 +2024-11-22 03:39:04.407196: train_loss -0.7773 +2024-11-22 03:39:04.407420: val_loss -0.7443 +2024-11-22 03:39:04.407496: Pseudo dice [0.8465] +2024-11-22 03:39:04.407571: Epoch time: 19.0 s +2024-11-22 03:39:05.374785: +2024-11-22 03:39:05.375040: Epoch 3161 +2024-11-22 03:39:05.375150: Current learning rate: 0.00636 +2024-11-22 03:39:23.211247: train_loss -0.7762 +2024-11-22 03:39:23.211472: val_loss -0.7907 +2024-11-22 03:39:23.211546: Pseudo dice [0.8339] +2024-11-22 03:39:23.211624: Epoch time: 17.84 s +2024-11-22 03:39:24.224356: +2024-11-22 03:39:24.224574: Epoch 3162 +2024-11-22 03:39:24.224689: Current learning rate: 0.00636 +2024-11-22 03:39:44.013392: train_loss -0.7798 +2024-11-22 03:39:44.013631: val_loss -0.7649 +2024-11-22 03:39:44.013703: Pseudo dice [0.8524] +2024-11-22 03:39:44.013794: Epoch time: 19.79 s +2024-11-22 03:39:44.882195: +2024-11-22 03:39:44.882442: Epoch 3163 +2024-11-22 03:39:44.882558: Current learning rate: 0.00636 +2024-11-22 03:40:03.667806: train_loss -0.7747 +2024-11-22 03:40:03.668028: val_loss -0.754 +2024-11-22 03:40:03.668104: Pseudo dice [0.8382] +2024-11-22 03:40:03.668178: Epoch time: 18.79 s +2024-11-22 03:40:04.522380: +2024-11-22 03:40:04.522605: Epoch 3164 +2024-11-22 03:40:04.522717: Current learning rate: 0.00636 +2024-11-22 03:40:23.748005: train_loss -0.7834 +2024-11-22 03:40:23.748227: val_loss -0.7515 +2024-11-22 03:40:23.748304: Pseudo dice [0.842] +2024-11-22 03:40:23.748379: Epoch time: 19.23 s +2024-11-22 03:40:24.605689: +2024-11-22 03:40:24.605926: Epoch 3165 +2024-11-22 03:40:24.606040: Current learning rate: 0.00636 +2024-11-22 03:40:42.769800: train_loss -0.7774 +2024-11-22 03:40:42.770060: val_loss -0.7717 +2024-11-22 03:40:42.770136: Pseudo dice [0.8454] +2024-11-22 03:40:42.770218: Epoch time: 18.16 s +2024-11-22 03:40:43.721623: +2024-11-22 03:40:43.721837: Epoch 3166 +2024-11-22 03:40:43.721952: Current learning rate: 0.00635 +2024-11-22 03:41:00.980262: train_loss -0.7817 +2024-11-22 03:41:00.980479: val_loss -0.7925 +2024-11-22 03:41:00.980554: Pseudo dice [0.8616] +2024-11-22 03:41:00.980626: Epoch time: 17.26 s +2024-11-22 03:41:01.837583: +2024-11-22 03:41:01.837808: Epoch 3167 +2024-11-22 03:41:01.837925: Current learning rate: 0.00635 +2024-11-22 03:41:19.975384: train_loss -0.7878 +2024-11-22 03:41:19.975601: val_loss -0.7782 +2024-11-22 03:41:19.975677: Pseudo dice [0.847] +2024-11-22 03:41:19.975750: Epoch time: 18.14 s +2024-11-22 03:41:20.832740: +2024-11-22 03:41:20.832934: Epoch 3168 +2024-11-22 03:41:20.833048: Current learning rate: 0.00635 +2024-11-22 03:41:39.306625: train_loss -0.7956 +2024-11-22 03:41:39.306894: val_loss -0.7551 +2024-11-22 03:41:39.306970: Pseudo dice [0.8233] +2024-11-22 03:41:39.307045: Epoch time: 18.47 s +2024-11-22 03:41:40.175164: +2024-11-22 03:41:40.175394: Epoch 3169 +2024-11-22 03:41:40.175508: Current learning rate: 0.00635 +2024-11-22 03:41:58.362628: train_loss -0.7858 +2024-11-22 03:41:58.362872: val_loss -0.7705 +2024-11-22 03:41:58.362946: Pseudo dice [0.8514] +2024-11-22 03:41:58.363028: Epoch time: 18.19 s +2024-11-22 03:41:59.655951: +2024-11-22 03:41:59.656172: Epoch 3170 +2024-11-22 03:41:59.656277: Current learning rate: 0.00635 +2024-11-22 03:42:17.926960: train_loss -0.7885 +2024-11-22 03:42:17.927201: val_loss -0.7843 +2024-11-22 03:42:17.927281: Pseudo dice [0.8475] +2024-11-22 03:42:17.927358: Epoch time: 18.27 s +2024-11-22 03:42:18.784112: +2024-11-22 03:42:18.784327: Epoch 3171 +2024-11-22 03:42:18.784437: Current learning rate: 0.00635 +2024-11-22 03:42:37.393608: train_loss -0.7932 +2024-11-22 03:42:37.393824: val_loss -0.7523 +2024-11-22 03:42:37.393897: Pseudo dice [0.8418] +2024-11-22 03:42:37.393972: Epoch time: 18.61 s +2024-11-22 03:42:38.249748: +2024-11-22 03:42:38.249980: Epoch 3172 +2024-11-22 03:42:38.250097: Current learning rate: 0.00635 +2024-11-22 03:42:57.345281: train_loss -0.7801 +2024-11-22 03:42:57.345519: val_loss -0.7709 +2024-11-22 03:42:57.346460: Pseudo dice [0.8414] +2024-11-22 03:42:57.346595: Epoch time: 19.1 s +2024-11-22 03:42:58.309650: +2024-11-22 03:42:58.309872: Epoch 3173 +2024-11-22 03:42:58.309984: Current learning rate: 0.00635 +2024-11-22 03:43:17.423946: train_loss -0.7836 +2024-11-22 03:43:17.424191: val_loss -0.7719 +2024-11-22 03:43:17.424267: Pseudo dice [0.8315] +2024-11-22 03:43:17.424344: Epoch time: 19.12 s +2024-11-22 03:43:18.305845: +2024-11-22 03:43:18.306076: Epoch 3174 +2024-11-22 03:43:18.306188: Current learning rate: 0.00635 +2024-11-22 03:43:35.805792: train_loss -0.7786 +2024-11-22 03:43:35.806012: val_loss -0.7582 +2024-11-22 03:43:35.806089: Pseudo dice [0.8412] +2024-11-22 03:43:35.806163: Epoch time: 17.5 s +2024-11-22 03:43:36.665834: +2024-11-22 03:43:36.666065: Epoch 3175 +2024-11-22 03:43:36.666177: Current learning rate: 0.00634 +2024-11-22 03:43:55.986676: train_loss -0.7851 +2024-11-22 03:43:55.986908: val_loss -0.7765 +2024-11-22 03:43:55.987030: Pseudo dice [0.8483] +2024-11-22 03:43:55.987124: Epoch time: 19.32 s +2024-11-22 03:43:56.967422: +2024-11-22 03:43:56.967656: Epoch 3176 +2024-11-22 03:43:56.967773: Current learning rate: 0.00634 +2024-11-22 03:44:15.281358: train_loss -0.7833 +2024-11-22 03:44:15.281629: val_loss -0.7898 +2024-11-22 03:44:15.283898: Pseudo dice [0.8486] +2024-11-22 03:44:15.284003: Epoch time: 18.31 s +2024-11-22 03:44:16.341787: +2024-11-22 03:44:16.342011: Epoch 3177 +2024-11-22 03:44:16.342120: Current learning rate: 0.00634 +2024-11-22 03:44:34.929351: train_loss -0.7826 +2024-11-22 03:44:34.929582: val_loss -0.7901 +2024-11-22 03:44:34.929663: Pseudo dice [0.8455] +2024-11-22 03:44:34.929737: Epoch time: 18.59 s +2024-11-22 03:44:35.790689: +2024-11-22 03:44:35.790916: Epoch 3178 +2024-11-22 03:44:35.791028: Current learning rate: 0.00634 +2024-11-22 03:44:56.060472: train_loss -0.7911 +2024-11-22 03:44:56.060684: val_loss -0.7566 +2024-11-22 03:44:56.060757: Pseudo dice [0.8356] +2024-11-22 03:44:56.060832: Epoch time: 20.27 s +2024-11-22 03:44:56.921356: +2024-11-22 03:44:56.921559: Epoch 3179 +2024-11-22 03:44:56.921666: Current learning rate: 0.00634 +2024-11-22 03:45:14.654689: train_loss -0.7934 +2024-11-22 03:45:14.654998: val_loss -0.7786 +2024-11-22 03:45:14.655143: Pseudo dice [0.838] +2024-11-22 03:45:14.655229: Epoch time: 17.73 s +2024-11-22 03:45:15.515958: +2024-11-22 03:45:15.516163: Epoch 3180 +2024-11-22 03:45:15.516271: Current learning rate: 0.00634 +2024-11-22 03:45:34.593297: train_loss -0.778 +2024-11-22 03:45:34.593513: val_loss -0.7687 +2024-11-22 03:45:34.593589: Pseudo dice [0.842] +2024-11-22 03:45:34.593662: Epoch time: 19.08 s +2024-11-22 03:45:35.453423: +2024-11-22 03:45:35.453717: Epoch 3181 +2024-11-22 03:45:35.453835: Current learning rate: 0.00634 +2024-11-22 03:45:53.066643: train_loss -0.7776 +2024-11-22 03:45:53.068261: val_loss -0.7867 +2024-11-22 03:45:53.068369: Pseudo dice [0.8495] +2024-11-22 03:45:53.068448: Epoch time: 17.61 s +2024-11-22 03:45:53.963550: +2024-11-22 03:45:53.963749: Epoch 3182 +2024-11-22 03:45:53.963857: Current learning rate: 0.00634 +2024-11-22 03:46:11.605105: train_loss -0.7828 +2024-11-22 03:46:11.605316: val_loss -0.7627 +2024-11-22 03:46:11.605395: Pseudo dice [0.8337] +2024-11-22 03:46:11.605476: Epoch time: 17.64 s +2024-11-22 03:46:12.461290: +2024-11-22 03:46:12.461504: Epoch 3183 +2024-11-22 03:46:12.461617: Current learning rate: 0.00633 +2024-11-22 03:46:31.782095: train_loss -0.7692 +2024-11-22 03:46:31.782333: val_loss -0.7648 +2024-11-22 03:46:31.782407: Pseudo dice [0.8191] +2024-11-22 03:46:31.782483: Epoch time: 19.32 s +2024-11-22 03:46:32.794922: +2024-11-22 03:46:32.795124: Epoch 3184 +2024-11-22 03:46:32.795234: Current learning rate: 0.00633 +2024-11-22 03:46:51.049631: train_loss -0.7537 +2024-11-22 03:46:51.049842: val_loss -0.7596 +2024-11-22 03:46:51.049923: Pseudo dice [0.832] +2024-11-22 03:46:51.050004: Epoch time: 18.26 s +2024-11-22 03:46:51.911114: +2024-11-22 03:46:51.911336: Epoch 3185 +2024-11-22 03:46:51.911447: Current learning rate: 0.00633 +2024-11-22 03:47:10.817568: train_loss -0.7646 +2024-11-22 03:47:10.817807: val_loss -0.7507 +2024-11-22 03:47:10.817879: Pseudo dice [0.8519] +2024-11-22 03:47:10.817960: Epoch time: 18.91 s +2024-11-22 03:47:11.680847: +2024-11-22 03:47:11.681073: Epoch 3186 +2024-11-22 03:47:11.681188: Current learning rate: 0.00633 +2024-11-22 03:47:29.553421: train_loss -0.7558 +2024-11-22 03:47:29.553660: val_loss -0.764 +2024-11-22 03:47:29.553733: Pseudo dice [0.8302] +2024-11-22 03:47:29.553816: Epoch time: 17.87 s +2024-11-22 03:47:30.414733: +2024-11-22 03:47:30.414960: Epoch 3187 +2024-11-22 03:47:30.415076: Current learning rate: 0.00633 +2024-11-22 03:47:48.485492: train_loss -0.7606 +2024-11-22 03:47:48.485698: val_loss -0.7524 +2024-11-22 03:47:48.485772: Pseudo dice [0.8316] +2024-11-22 03:47:48.485845: Epoch time: 18.07 s +2024-11-22 03:47:49.339355: +2024-11-22 03:47:49.339572: Epoch 3188 +2024-11-22 03:47:49.339679: Current learning rate: 0.00633 +2024-11-22 03:48:07.586420: train_loss -0.7817 +2024-11-22 03:48:07.586656: val_loss -0.7623 +2024-11-22 03:48:07.586729: Pseudo dice [0.842] +2024-11-22 03:48:07.586804: Epoch time: 18.25 s +2024-11-22 03:48:08.497703: +2024-11-22 03:48:08.497919: Epoch 3189 +2024-11-22 03:48:08.498036: Current learning rate: 0.00633 +2024-11-22 03:48:27.006695: train_loss -0.7785 +2024-11-22 03:48:27.006917: val_loss -0.7602 +2024-11-22 03:48:27.007002: Pseudo dice [0.8291] +2024-11-22 03:48:27.007080: Epoch time: 18.51 s +2024-11-22 03:48:27.867884: +2024-11-22 03:48:27.868079: Epoch 3190 +2024-11-22 03:48:27.868189: Current learning rate: 0.00633 +2024-11-22 03:48:46.837518: train_loss -0.7692 +2024-11-22 03:48:46.837745: val_loss -0.7544 +2024-11-22 03:48:46.837821: Pseudo dice [0.8319] +2024-11-22 03:48:46.841130: Epoch time: 18.97 s +2024-11-22 03:48:47.713822: +2024-11-22 03:48:47.714062: Epoch 3191 +2024-11-22 03:48:47.714172: Current learning rate: 0.00633 +2024-11-22 03:49:06.365880: train_loss -0.7681 +2024-11-22 03:49:06.366099: val_loss -0.7681 +2024-11-22 03:49:06.366176: Pseudo dice [0.8477] +2024-11-22 03:49:06.366251: Epoch time: 18.65 s +2024-11-22 03:49:07.214136: +2024-11-22 03:49:07.214355: Epoch 3192 +2024-11-22 03:49:07.214463: Current learning rate: 0.00632 +2024-11-22 03:49:24.794811: train_loss -0.7522 +2024-11-22 03:49:24.795036: val_loss -0.7545 +2024-11-22 03:49:24.795115: Pseudo dice [0.817] +2024-11-22 03:49:24.795191: Epoch time: 17.58 s +2024-11-22 03:49:26.045243: +2024-11-22 03:49:26.045484: Epoch 3193 +2024-11-22 03:49:26.045593: Current learning rate: 0.00632 +2024-11-22 03:49:44.737710: train_loss -0.7678 +2024-11-22 03:49:44.737977: val_loss -0.7753 +2024-11-22 03:49:44.738059: Pseudo dice [0.8488] +2024-11-22 03:49:44.738140: Epoch time: 18.69 s +2024-11-22 03:49:45.600586: +2024-11-22 03:49:45.600801: Epoch 3194 +2024-11-22 03:49:45.600910: Current learning rate: 0.00632 +2024-11-22 03:50:05.150421: train_loss -0.749 +2024-11-22 03:50:05.150639: val_loss -0.7717 +2024-11-22 03:50:05.150719: Pseudo dice [0.8372] +2024-11-22 03:50:05.150798: Epoch time: 19.55 s +2024-11-22 03:50:06.005772: +2024-11-22 03:50:06.005976: Epoch 3195 +2024-11-22 03:50:06.006089: Current learning rate: 0.00632 +2024-11-22 03:50:24.409375: train_loss -0.7706 +2024-11-22 03:50:24.411765: val_loss -0.7564 +2024-11-22 03:50:24.411894: Pseudo dice [0.8322] +2024-11-22 03:50:24.411970: Epoch time: 18.4 s +2024-11-22 03:50:25.392495: +2024-11-22 03:50:25.392724: Epoch 3196 +2024-11-22 03:50:25.392843: Current learning rate: 0.00632 +2024-11-22 03:50:44.772482: train_loss -0.7799 +2024-11-22 03:50:44.772703: val_loss -0.7761 +2024-11-22 03:50:44.772778: Pseudo dice [0.8399] +2024-11-22 03:50:44.774989: Epoch time: 19.38 s +2024-11-22 03:50:45.639595: +2024-11-22 03:50:45.639817: Epoch 3197 +2024-11-22 03:50:45.639928: Current learning rate: 0.00632 +2024-11-22 03:51:03.436469: train_loss -0.7768 +2024-11-22 03:51:03.436716: val_loss -0.7703 +2024-11-22 03:51:03.436796: Pseudo dice [0.8371] +2024-11-22 03:51:03.436890: Epoch time: 17.8 s +2024-11-22 03:51:04.304927: +2024-11-22 03:51:04.305147: Epoch 3198 +2024-11-22 03:51:04.305260: Current learning rate: 0.00632 +2024-11-22 03:51:23.118392: train_loss -0.778 +2024-11-22 03:51:23.118638: val_loss -0.7729 +2024-11-22 03:51:23.119013: Pseudo dice [0.8598] +2024-11-22 03:51:23.119101: Epoch time: 18.81 s +2024-11-22 03:51:23.991449: +2024-11-22 03:51:23.991661: Epoch 3199 +2024-11-22 03:51:23.991772: Current learning rate: 0.00632 +2024-11-22 03:51:42.761410: train_loss -0.7798 +2024-11-22 03:51:42.761639: val_loss -0.7746 +2024-11-22 03:51:42.761729: Pseudo dice [0.8317] +2024-11-22 03:51:42.761808: Epoch time: 18.77 s +2024-11-22 03:51:44.005519: +2024-11-22 03:51:44.005727: Epoch 3200 +2024-11-22 03:51:44.005833: Current learning rate: 0.00631 +2024-11-22 03:52:03.371153: train_loss -0.7823 +2024-11-22 03:52:03.371377: val_loss -0.7824 +2024-11-22 03:52:03.371510: Pseudo dice [0.8473] +2024-11-22 03:52:03.371588: Epoch time: 19.37 s +2024-11-22 03:52:04.227895: +2024-11-22 03:52:04.228110: Epoch 3201 +2024-11-22 03:52:04.228218: Current learning rate: 0.00631 +2024-11-22 03:52:22.449024: train_loss -0.784 +2024-11-22 03:52:22.449650: val_loss -0.7852 +2024-11-22 03:52:22.449732: Pseudo dice [0.8624] +2024-11-22 03:52:22.449815: Epoch time: 18.22 s +2024-11-22 03:52:23.308408: +2024-11-22 03:52:23.308598: Epoch 3202 +2024-11-22 03:52:23.308708: Current learning rate: 0.00631 +2024-11-22 03:52:41.219512: train_loss -0.7818 +2024-11-22 03:52:41.219744: val_loss -0.7888 +2024-11-22 03:52:41.219819: Pseudo dice [0.8541] +2024-11-22 03:52:41.219895: Epoch time: 17.91 s +2024-11-22 03:52:42.135041: +2024-11-22 03:52:42.135286: Epoch 3203 +2024-11-22 03:52:42.135398: Current learning rate: 0.00631 +2024-11-22 03:53:00.103729: train_loss -0.7714 +2024-11-22 03:53:00.103939: val_loss -0.7649 +2024-11-22 03:53:00.104025: Pseudo dice [0.8518] +2024-11-22 03:53:00.104116: Epoch time: 17.97 s +2024-11-22 03:53:00.958864: +2024-11-22 03:53:00.959076: Epoch 3204 +2024-11-22 03:53:00.959186: Current learning rate: 0.00631 +2024-11-22 03:53:19.042188: train_loss -0.7732 +2024-11-22 03:53:19.042732: val_loss -0.7527 +2024-11-22 03:53:19.042834: Pseudo dice [0.8432] +2024-11-22 03:53:19.042923: Epoch time: 18.08 s +2024-11-22 03:53:19.912167: +2024-11-22 03:53:19.912398: Epoch 3205 +2024-11-22 03:53:19.912509: Current learning rate: 0.00631 +2024-11-22 03:53:39.477206: train_loss -0.7628 +2024-11-22 03:53:39.477440: val_loss -0.755 +2024-11-22 03:53:39.477519: Pseudo dice [0.8327] +2024-11-22 03:53:39.477596: Epoch time: 19.57 s +2024-11-22 03:53:40.337879: +2024-11-22 03:53:40.338113: Epoch 3206 +2024-11-22 03:53:40.338218: Current learning rate: 0.00631 +2024-11-22 03:54:00.443600: train_loss -0.7618 +2024-11-22 03:54:00.443834: val_loss -0.7539 +2024-11-22 03:54:00.443914: Pseudo dice [0.83] +2024-11-22 03:54:00.449137: Epoch time: 20.11 s +2024-11-22 03:54:01.343884: +2024-11-22 03:54:01.344093: Epoch 3207 +2024-11-22 03:54:01.344202: Current learning rate: 0.00631 +2024-11-22 03:54:19.963497: train_loss -0.7762 +2024-11-22 03:54:19.974298: val_loss -0.7618 +2024-11-22 03:54:19.974427: Pseudo dice [0.8418] +2024-11-22 03:54:19.974512: Epoch time: 18.62 s +2024-11-22 03:54:20.871399: +2024-11-22 03:54:20.871610: Epoch 3208 +2024-11-22 03:54:20.871721: Current learning rate: 0.0063 +2024-11-22 03:54:38.939005: train_loss -0.7832 +2024-11-22 03:54:38.939323: val_loss -0.7752 +2024-11-22 03:54:38.939399: Pseudo dice [0.8507] +2024-11-22 03:54:38.939483: Epoch time: 18.07 s +2024-11-22 03:54:39.836003: +2024-11-22 03:54:39.836215: Epoch 3209 +2024-11-22 03:54:39.836322: Current learning rate: 0.0063 +2024-11-22 03:54:58.832351: train_loss -0.7809 +2024-11-22 03:54:58.832574: val_loss -0.7655 +2024-11-22 03:54:58.832687: Pseudo dice [0.8433] +2024-11-22 03:54:58.832786: Epoch time: 19.0 s +2024-11-22 03:54:59.700783: +2024-11-22 03:54:59.701005: Epoch 3210 +2024-11-22 03:54:59.701113: Current learning rate: 0.0063 +2024-11-22 03:55:18.083788: train_loss -0.7781 +2024-11-22 03:55:18.084011: val_loss -0.7492 +2024-11-22 03:55:18.084086: Pseudo dice [0.8079] +2024-11-22 03:55:18.084161: Epoch time: 18.38 s +2024-11-22 03:55:18.962622: +2024-11-22 03:55:18.962854: Epoch 3211 +2024-11-22 03:55:18.962965: Current learning rate: 0.0063 +2024-11-22 03:55:37.474799: train_loss -0.7743 +2024-11-22 03:55:37.475074: val_loss -0.7682 +2024-11-22 03:55:37.475153: Pseudo dice [0.8576] +2024-11-22 03:55:37.475233: Epoch time: 18.51 s +2024-11-22 03:55:38.341422: +2024-11-22 03:55:38.341638: Epoch 3212 +2024-11-22 03:55:38.352809: Current learning rate: 0.0063 +2024-11-22 03:55:57.428883: train_loss -0.766 +2024-11-22 03:55:57.429135: val_loss -0.7603 +2024-11-22 03:55:57.429209: Pseudo dice [0.8356] +2024-11-22 03:55:57.429290: Epoch time: 19.09 s +2024-11-22 03:55:58.297586: +2024-11-22 03:55:58.297799: Epoch 3213 +2024-11-22 03:55:58.297903: Current learning rate: 0.0063 +2024-11-22 03:56:16.694585: train_loss -0.767 +2024-11-22 03:56:16.694794: val_loss -0.7672 +2024-11-22 03:56:16.694869: Pseudo dice [0.827] +2024-11-22 03:56:16.694943: Epoch time: 18.4 s +2024-11-22 03:56:17.558040: +2024-11-22 03:56:17.558352: Epoch 3214 +2024-11-22 03:56:17.558466: Current learning rate: 0.0063 +2024-11-22 03:56:36.982255: train_loss -0.7821 +2024-11-22 03:56:36.987618: val_loss -0.7497 +2024-11-22 03:56:36.987747: Pseudo dice [0.831] +2024-11-22 03:56:36.987828: Epoch time: 19.43 s +2024-11-22 03:56:37.858800: +2024-11-22 03:56:37.859019: Epoch 3215 +2024-11-22 03:56:37.859133: Current learning rate: 0.0063 +2024-11-22 03:56:56.708024: train_loss -0.7798 +2024-11-22 03:56:56.708240: val_loss -0.7817 +2024-11-22 03:56:56.708321: Pseudo dice [0.8423] +2024-11-22 03:56:56.708423: Epoch time: 18.85 s +2024-11-22 03:56:57.960778: +2024-11-22 03:56:57.960998: Epoch 3216 +2024-11-22 03:56:57.961108: Current learning rate: 0.0063 +2024-11-22 03:57:17.402721: train_loss -0.7804 +2024-11-22 03:57:17.402960: val_loss -0.7651 +2024-11-22 03:57:17.403054: Pseudo dice [0.8305] +2024-11-22 03:57:17.403127: Epoch time: 19.44 s +2024-11-22 03:57:18.271272: +2024-11-22 03:57:18.271471: Epoch 3217 +2024-11-22 03:57:18.271586: Current learning rate: 0.00629 +2024-11-22 03:57:36.870850: train_loss -0.7712 +2024-11-22 03:57:36.871065: val_loss -0.7862 +2024-11-22 03:57:36.871138: Pseudo dice [0.8445] +2024-11-22 03:57:36.871211: Epoch time: 18.6 s +2024-11-22 03:57:37.728987: +2024-11-22 03:57:37.729231: Epoch 3218 +2024-11-22 03:57:37.729354: Current learning rate: 0.00629 +2024-11-22 03:57:56.013912: train_loss -0.7723 +2024-11-22 03:57:56.014142: val_loss -0.7812 +2024-11-22 03:57:56.014218: Pseudo dice [0.8454] +2024-11-22 03:57:56.014290: Epoch time: 18.29 s +2024-11-22 03:57:56.879881: +2024-11-22 03:57:56.880115: Epoch 3219 +2024-11-22 03:57:56.880225: Current learning rate: 0.00629 +2024-11-22 03:58:15.499055: train_loss -0.7798 +2024-11-22 03:58:15.499312: val_loss -0.7693 +2024-11-22 03:58:15.499395: Pseudo dice [0.8515] +2024-11-22 03:58:15.499476: Epoch time: 18.62 s +2024-11-22 03:58:16.375828: +2024-11-22 03:58:16.376059: Epoch 3220 +2024-11-22 03:58:16.376174: Current learning rate: 0.00629 +2024-11-22 03:58:36.131389: train_loss -0.7783 +2024-11-22 03:58:36.131609: val_loss -0.7809 +2024-11-22 03:58:36.131689: Pseudo dice [0.8459] +2024-11-22 03:58:36.131764: Epoch time: 19.76 s +2024-11-22 03:58:36.997225: +2024-11-22 03:58:36.997438: Epoch 3221 +2024-11-22 03:58:36.997554: Current learning rate: 0.00629 +2024-11-22 03:58:55.527486: train_loss -0.7858 +2024-11-22 03:58:55.527730: val_loss -0.7865 +2024-11-22 03:58:55.527810: Pseudo dice [0.8606] +2024-11-22 03:58:55.527888: Epoch time: 18.53 s +2024-11-22 03:58:56.390062: +2024-11-22 03:58:56.390276: Epoch 3222 +2024-11-22 03:58:56.390387: Current learning rate: 0.00629 +2024-11-22 03:59:14.881657: train_loss -0.7852 +2024-11-22 03:59:14.881926: val_loss -0.7794 +2024-11-22 03:59:14.882013: Pseudo dice [0.8503] +2024-11-22 03:59:14.882094: Epoch time: 18.49 s +2024-11-22 03:59:15.747182: +2024-11-22 03:59:15.747509: Epoch 3223 +2024-11-22 03:59:15.747618: Current learning rate: 0.00629 +2024-11-22 03:59:34.222565: train_loss -0.7824 +2024-11-22 03:59:34.222803: val_loss -0.759 +2024-11-22 03:59:34.222876: Pseudo dice [0.8473] +2024-11-22 03:59:34.222953: Epoch time: 18.48 s +2024-11-22 03:59:35.084151: +2024-11-22 03:59:35.084358: Epoch 3224 +2024-11-22 03:59:35.084471: Current learning rate: 0.00629 +2024-11-22 03:59:53.310510: train_loss -0.782 +2024-11-22 03:59:53.325001: val_loss -0.7627 +2024-11-22 03:59:53.325213: Pseudo dice [0.8412] +2024-11-22 03:59:53.325296: Epoch time: 18.23 s +2024-11-22 03:59:54.353742: +2024-11-22 03:59:54.353929: Epoch 3225 +2024-11-22 03:59:54.354043: Current learning rate: 0.00628 +2024-11-22 04:00:12.618449: train_loss -0.7814 +2024-11-22 04:00:12.618665: val_loss -0.7584 +2024-11-22 04:00:12.618743: Pseudo dice [0.8429] +2024-11-22 04:00:12.618837: Epoch time: 18.27 s +2024-11-22 04:00:13.476229: +2024-11-22 04:00:13.476439: Epoch 3226 +2024-11-22 04:00:13.476545: Current learning rate: 0.00628 +2024-11-22 04:00:31.978410: train_loss -0.79 +2024-11-22 04:00:31.978660: val_loss -0.7577 +2024-11-22 04:00:31.978740: Pseudo dice [0.8473] +2024-11-22 04:00:31.978824: Epoch time: 18.5 s +2024-11-22 04:00:32.843974: +2024-11-22 04:00:32.844408: Epoch 3227 +2024-11-22 04:00:32.844539: Current learning rate: 0.00628 +2024-11-22 04:00:50.638501: train_loss -0.7823 +2024-11-22 04:00:50.638960: val_loss -0.7799 +2024-11-22 04:00:50.639080: Pseudo dice [0.8507] +2024-11-22 04:00:50.639162: Epoch time: 17.8 s +2024-11-22 04:00:51.493766: +2024-11-22 04:00:51.493998: Epoch 3228 +2024-11-22 04:00:51.494112: Current learning rate: 0.00628 +2024-11-22 04:01:10.013176: train_loss -0.7466 +2024-11-22 04:01:10.013399: val_loss -0.7554 +2024-11-22 04:01:10.013474: Pseudo dice [0.8365] +2024-11-22 04:01:10.013551: Epoch time: 18.52 s +2024-11-22 04:01:10.873530: +2024-11-22 04:01:10.873754: Epoch 3229 +2024-11-22 04:01:10.873868: Current learning rate: 0.00628 +2024-11-22 04:01:27.858145: train_loss -0.7661 +2024-11-22 04:01:27.858388: val_loss -0.7766 +2024-11-22 04:01:27.858463: Pseudo dice [0.8436] +2024-11-22 04:01:27.858544: Epoch time: 16.99 s +2024-11-22 04:01:28.721858: +2024-11-22 04:01:28.722060: Epoch 3230 +2024-11-22 04:01:28.722167: Current learning rate: 0.00628 +2024-11-22 04:01:47.342766: train_loss -0.785 +2024-11-22 04:01:47.342985: val_loss -0.7524 +2024-11-22 04:01:47.343066: Pseudo dice [0.8273] +2024-11-22 04:01:47.343140: Epoch time: 18.62 s +2024-11-22 04:01:48.211632: +2024-11-22 04:01:48.211912: Epoch 3231 +2024-11-22 04:01:48.212025: Current learning rate: 0.00628 +2024-11-22 04:02:06.601953: train_loss -0.7788 +2024-11-22 04:02:06.602180: val_loss -0.7539 +2024-11-22 04:02:06.602252: Pseudo dice [0.8463] +2024-11-22 04:02:06.602328: Epoch time: 18.39 s +2024-11-22 04:02:07.469631: +2024-11-22 04:02:07.469871: Epoch 3232 +2024-11-22 04:02:07.469982: Current learning rate: 0.00628 +2024-11-22 04:02:25.448235: train_loss -0.7709 +2024-11-22 04:02:25.448462: val_loss -0.7405 +2024-11-22 04:02:25.448538: Pseudo dice [0.8025] +2024-11-22 04:02:25.448611: Epoch time: 17.98 s +2024-11-22 04:02:26.323706: +2024-11-22 04:02:26.323928: Epoch 3233 +2024-11-22 04:02:26.324047: Current learning rate: 0.00628 +2024-11-22 04:02:45.448271: train_loss -0.7685 +2024-11-22 04:02:45.448525: val_loss -0.7603 +2024-11-22 04:02:45.448600: Pseudo dice [0.8403] +2024-11-22 04:02:45.448681: Epoch time: 19.13 s +2024-11-22 04:02:46.311455: +2024-11-22 04:02:46.311691: Epoch 3234 +2024-11-22 04:02:46.311803: Current learning rate: 0.00627 +2024-11-22 04:03:05.728371: train_loss -0.7718 +2024-11-22 04:03:05.728598: val_loss -0.7655 +2024-11-22 04:03:05.728674: Pseudo dice [0.8347] +2024-11-22 04:03:05.728750: Epoch time: 19.42 s +2024-11-22 04:03:06.590486: +2024-11-22 04:03:06.590719: Epoch 3235 +2024-11-22 04:03:06.590841: Current learning rate: 0.00627 +2024-11-22 04:03:24.575001: train_loss -0.7797 +2024-11-22 04:03:24.575214: val_loss -0.7741 +2024-11-22 04:03:24.575292: Pseudo dice [0.8331] +2024-11-22 04:03:24.575368: Epoch time: 17.99 s +2024-11-22 04:03:25.442671: +2024-11-22 04:03:25.442938: Epoch 3236 +2024-11-22 04:03:25.443075: Current learning rate: 0.00627 +2024-11-22 04:03:43.837976: train_loss -0.7795 +2024-11-22 04:03:43.838228: val_loss -0.7751 +2024-11-22 04:03:43.838311: Pseudo dice [0.8509] +2024-11-22 04:03:43.838399: Epoch time: 18.4 s +2024-11-22 04:03:44.705421: +2024-11-22 04:03:44.705633: Epoch 3237 +2024-11-22 04:03:44.705738: Current learning rate: 0.00627 +2024-11-22 04:04:02.367126: train_loss -0.7849 +2024-11-22 04:04:02.367408: val_loss -0.7811 +2024-11-22 04:04:02.367485: Pseudo dice [0.8473] +2024-11-22 04:04:02.367558: Epoch time: 17.66 s +2024-11-22 04:04:03.235152: +2024-11-22 04:04:03.235341: Epoch 3238 +2024-11-22 04:04:03.235452: Current learning rate: 0.00627 +2024-11-22 04:04:22.241801: train_loss -0.7886 +2024-11-22 04:04:22.242032: val_loss -0.7536 +2024-11-22 04:04:22.242108: Pseudo dice [0.839] +2024-11-22 04:04:22.242191: Epoch time: 19.01 s +2024-11-22 04:04:23.510403: +2024-11-22 04:04:23.510626: Epoch 3239 +2024-11-22 04:04:23.510736: Current learning rate: 0.00627 +2024-11-22 04:04:42.256641: train_loss -0.7879 +2024-11-22 04:04:42.256979: val_loss -0.7823 +2024-11-22 04:04:42.257064: Pseudo dice [0.8526] +2024-11-22 04:04:42.257149: Epoch time: 18.75 s +2024-11-22 04:04:43.121339: +2024-11-22 04:04:43.121549: Epoch 3240 +2024-11-22 04:04:43.121659: Current learning rate: 0.00627 +2024-11-22 04:05:01.938453: train_loss -0.777 +2024-11-22 04:05:01.938678: val_loss -0.7744 +2024-11-22 04:05:01.938757: Pseudo dice [0.8359] +2024-11-22 04:05:01.938836: Epoch time: 18.82 s +2024-11-22 04:05:02.802936: +2024-11-22 04:05:02.803255: Epoch 3241 +2024-11-22 04:05:02.803365: Current learning rate: 0.00627 +2024-11-22 04:05:20.455213: train_loss -0.7857 +2024-11-22 04:05:20.455446: val_loss -0.7843 +2024-11-22 04:05:20.455525: Pseudo dice [0.8492] +2024-11-22 04:05:20.455604: Epoch time: 17.65 s +2024-11-22 04:05:21.423481: +2024-11-22 04:05:21.423709: Epoch 3242 +2024-11-22 04:05:21.423822: Current learning rate: 0.00626 +2024-11-22 04:05:40.011817: train_loss -0.7837 +2024-11-22 04:05:40.012087: val_loss -0.7679 +2024-11-22 04:05:40.012163: Pseudo dice [0.8467] +2024-11-22 04:05:40.012236: Epoch time: 18.59 s +2024-11-22 04:05:40.873700: +2024-11-22 04:05:40.873917: Epoch 3243 +2024-11-22 04:05:40.874041: Current learning rate: 0.00626 +2024-11-22 04:05:58.832718: train_loss -0.7775 +2024-11-22 04:05:58.832965: val_loss -0.7569 +2024-11-22 04:05:58.833051: Pseudo dice [0.8488] +2024-11-22 04:05:58.833133: Epoch time: 17.96 s +2024-11-22 04:05:59.698493: +2024-11-22 04:05:59.698752: Epoch 3244 +2024-11-22 04:05:59.698863: Current learning rate: 0.00626 +2024-11-22 04:06:17.537147: train_loss -0.7743 +2024-11-22 04:06:17.537374: val_loss -0.7783 +2024-11-22 04:06:17.537448: Pseudo dice [0.8352] +2024-11-22 04:06:17.537522: Epoch time: 17.84 s +2024-11-22 04:06:18.420110: +2024-11-22 04:06:18.420335: Epoch 3245 +2024-11-22 04:06:18.420446: Current learning rate: 0.00626 +2024-11-22 04:06:38.442285: train_loss -0.7901 +2024-11-22 04:06:38.442593: val_loss -0.7737 +2024-11-22 04:06:38.442678: Pseudo dice [0.8272] +2024-11-22 04:06:38.442755: Epoch time: 20.02 s +2024-11-22 04:06:39.304757: +2024-11-22 04:06:39.304971: Epoch 3246 +2024-11-22 04:06:39.305086: Current learning rate: 0.00626 +2024-11-22 04:06:58.116009: train_loss -0.7764 +2024-11-22 04:06:58.116247: val_loss -0.7639 +2024-11-22 04:06:58.116323: Pseudo dice [0.8503] +2024-11-22 04:06:58.116407: Epoch time: 18.81 s +2024-11-22 04:06:58.985627: +2024-11-22 04:06:58.985845: Epoch 3247 +2024-11-22 04:06:58.985967: Current learning rate: 0.00626 +2024-11-22 04:07:17.005548: train_loss -0.7696 +2024-11-22 04:07:17.005796: val_loss -0.7713 +2024-11-22 04:07:17.005871: Pseudo dice [0.8476] +2024-11-22 04:07:17.005951: Epoch time: 18.02 s +2024-11-22 04:07:17.862438: +2024-11-22 04:07:17.862654: Epoch 3248 +2024-11-22 04:07:17.862762: Current learning rate: 0.00626 +2024-11-22 04:07:35.914524: train_loss -0.7831 +2024-11-22 04:07:35.914739: val_loss -0.7813 +2024-11-22 04:07:35.914813: Pseudo dice [0.8395] +2024-11-22 04:07:35.914889: Epoch time: 18.05 s +2024-11-22 04:07:36.875644: +2024-11-22 04:07:36.875911: Epoch 3249 +2024-11-22 04:07:36.876038: Current learning rate: 0.00626 +2024-11-22 04:07:55.609986: train_loss -0.7737 +2024-11-22 04:07:55.610212: val_loss -0.7717 +2024-11-22 04:07:55.610290: Pseudo dice [0.8401] +2024-11-22 04:07:55.613486: Epoch time: 18.74 s +2024-11-22 04:07:57.048560: +2024-11-22 04:07:57.048779: Epoch 3250 +2024-11-22 04:07:57.048889: Current learning rate: 0.00626 +2024-11-22 04:08:16.262346: train_loss -0.7861 +2024-11-22 04:08:16.268069: val_loss -0.7609 +2024-11-22 04:08:16.268201: Pseudo dice [0.8449] +2024-11-22 04:08:16.268292: Epoch time: 19.21 s +2024-11-22 04:08:17.336190: +2024-11-22 04:08:17.336419: Epoch 3251 +2024-11-22 04:08:17.336531: Current learning rate: 0.00625 +2024-11-22 04:08:35.827843: train_loss -0.7793 +2024-11-22 04:08:35.828067: val_loss -0.7911 +2024-11-22 04:08:35.828147: Pseudo dice [0.8587] +2024-11-22 04:08:35.828231: Epoch time: 18.49 s +2024-11-22 04:08:36.690154: +2024-11-22 04:08:36.690360: Epoch 3252 +2024-11-22 04:08:36.690472: Current learning rate: 0.00625 +2024-11-22 04:08:54.108781: train_loss -0.7835 +2024-11-22 04:08:54.109110: val_loss -0.7494 +2024-11-22 04:08:54.109193: Pseudo dice [0.8379] +2024-11-22 04:08:54.109267: Epoch time: 17.42 s +2024-11-22 04:08:54.974078: +2024-11-22 04:08:54.974296: Epoch 3253 +2024-11-22 04:08:54.974408: Current learning rate: 0.00625 +2024-11-22 04:09:13.319830: train_loss -0.7749 +2024-11-22 04:09:13.320061: val_loss -0.7666 +2024-11-22 04:09:13.320143: Pseudo dice [0.8534] +2024-11-22 04:09:13.320231: Epoch time: 18.35 s +2024-11-22 04:09:14.184218: +2024-11-22 04:09:14.184445: Epoch 3254 +2024-11-22 04:09:14.184555: Current learning rate: 0.00625 +2024-11-22 04:09:32.875367: train_loss -0.7734 +2024-11-22 04:09:32.875628: val_loss -0.7704 +2024-11-22 04:09:32.875704: Pseudo dice [0.8413] +2024-11-22 04:09:32.875786: Epoch time: 18.69 s +2024-11-22 04:09:33.846511: +2024-11-22 04:09:33.846745: Epoch 3255 +2024-11-22 04:09:33.846856: Current learning rate: 0.00625 +2024-11-22 04:09:51.301182: train_loss -0.7833 +2024-11-22 04:09:51.301466: val_loss -0.7747 +2024-11-22 04:09:51.301542: Pseudo dice [0.8726] +2024-11-22 04:09:51.301617: Epoch time: 17.46 s +2024-11-22 04:09:52.163000: +2024-11-22 04:09:52.163221: Epoch 3256 +2024-11-22 04:09:52.163339: Current learning rate: 0.00625 +2024-11-22 04:10:10.156760: train_loss -0.7861 +2024-11-22 04:10:10.156981: val_loss -0.8036 +2024-11-22 04:10:10.157058: Pseudo dice [0.8672] +2024-11-22 04:10:10.162269: Epoch time: 17.99 s +2024-11-22 04:10:11.070919: +2024-11-22 04:10:11.071121: Epoch 3257 +2024-11-22 04:10:11.071230: Current learning rate: 0.00625 +2024-11-22 04:10:30.046605: train_loss -0.7797 +2024-11-22 04:10:30.046814: val_loss -0.7696 +2024-11-22 04:10:30.046887: Pseudo dice [0.8418] +2024-11-22 04:10:30.046965: Epoch time: 18.98 s +2024-11-22 04:10:30.913512: +2024-11-22 04:10:30.913728: Epoch 3258 +2024-11-22 04:10:30.913836: Current learning rate: 0.00625 +2024-11-22 04:10:48.874507: train_loss -0.7842 +2024-11-22 04:10:48.874724: val_loss -0.7829 +2024-11-22 04:10:48.874800: Pseudo dice [0.8516] +2024-11-22 04:10:48.874877: Epoch time: 17.96 s +2024-11-22 04:10:49.728488: +2024-11-22 04:10:49.728695: Epoch 3259 +2024-11-22 04:10:49.728801: Current learning rate: 0.00624 +2024-11-22 04:11:08.103872: train_loss -0.7841 +2024-11-22 04:11:08.104091: val_loss -0.7819 +2024-11-22 04:11:08.104165: Pseudo dice [0.8522] +2024-11-22 04:11:08.104236: Epoch time: 18.38 s +2024-11-22 04:11:08.971981: +2024-11-22 04:11:08.972261: Epoch 3260 +2024-11-22 04:11:08.972378: Current learning rate: 0.00624 +2024-11-22 04:11:26.895866: train_loss -0.7748 +2024-11-22 04:11:26.898251: val_loss -0.756 +2024-11-22 04:11:26.898352: Pseudo dice [0.8412] +2024-11-22 04:11:26.898432: Epoch time: 17.92 s +2024-11-22 04:11:27.777967: +2024-11-22 04:11:27.778228: Epoch 3261 +2024-11-22 04:11:27.778347: Current learning rate: 0.00624 +2024-11-22 04:11:45.440853: train_loss -0.7719 +2024-11-22 04:11:45.441099: val_loss -0.7623 +2024-11-22 04:11:45.441175: Pseudo dice [0.8558] +2024-11-22 04:11:45.441259: Epoch time: 17.66 s +2024-11-22 04:11:46.673395: +2024-11-22 04:11:46.673603: Epoch 3262 +2024-11-22 04:11:46.673735: Current learning rate: 0.00624 +2024-11-22 04:12:04.908428: train_loss -0.7802 +2024-11-22 04:12:04.909518: val_loss -0.7609 +2024-11-22 04:12:04.909594: Pseudo dice [0.8403] +2024-11-22 04:12:04.909668: Epoch time: 18.24 s +2024-11-22 04:12:05.767844: +2024-11-22 04:12:05.768121: Epoch 3263 +2024-11-22 04:12:05.768235: Current learning rate: 0.00624 +2024-11-22 04:12:24.298410: train_loss -0.7723 +2024-11-22 04:12:24.298653: val_loss -0.7728 +2024-11-22 04:12:24.298732: Pseudo dice [0.8496] +2024-11-22 04:12:24.298844: Epoch time: 18.53 s +2024-11-22 04:12:25.166136: +2024-11-22 04:12:25.166405: Epoch 3264 +2024-11-22 04:12:25.166515: Current learning rate: 0.00624 +2024-11-22 04:12:43.589134: train_loss -0.784 +2024-11-22 04:12:43.589385: val_loss -0.7843 +2024-11-22 04:12:43.589458: Pseudo dice [0.8484] +2024-11-22 04:12:43.589541: Epoch time: 18.42 s +2024-11-22 04:12:44.454511: +2024-11-22 04:12:44.454721: Epoch 3265 +2024-11-22 04:12:44.454829: Current learning rate: 0.00624 +2024-11-22 04:13:03.260822: train_loss -0.7827 +2024-11-22 04:13:03.261051: val_loss -0.7459 +2024-11-22 04:13:03.261128: Pseudo dice [0.8367] +2024-11-22 04:13:03.261203: Epoch time: 18.81 s +2024-11-22 04:13:04.218925: +2024-11-22 04:13:04.219144: Epoch 3266 +2024-11-22 04:13:04.219256: Current learning rate: 0.00624 +2024-11-22 04:13:23.372063: train_loss -0.7778 +2024-11-22 04:13:23.372292: val_loss -0.7615 +2024-11-22 04:13:23.372369: Pseudo dice [0.8174] +2024-11-22 04:13:23.372452: Epoch time: 19.15 s +2024-11-22 04:13:24.234771: +2024-11-22 04:13:24.235003: Epoch 3267 +2024-11-22 04:13:24.235112: Current learning rate: 0.00624 +2024-11-22 04:13:42.003496: train_loss -0.7807 +2024-11-22 04:13:42.003706: val_loss -0.7515 +2024-11-22 04:13:42.003779: Pseudo dice [0.8499] +2024-11-22 04:13:42.003851: Epoch time: 17.77 s +2024-11-22 04:13:42.870540: +2024-11-22 04:13:42.870749: Epoch 3268 +2024-11-22 04:13:42.870853: Current learning rate: 0.00623 +2024-11-22 04:14:02.060849: train_loss -0.7769 +2024-11-22 04:14:02.066269: val_loss -0.7507 +2024-11-22 04:14:02.066348: Pseudo dice [0.8235] +2024-11-22 04:14:02.066435: Epoch time: 19.19 s +2024-11-22 04:14:03.035331: +2024-11-22 04:14:03.035553: Epoch 3269 +2024-11-22 04:14:03.035662: Current learning rate: 0.00623 +2024-11-22 04:14:20.439168: train_loss -0.7876 +2024-11-22 04:14:20.439384: val_loss -0.7698 +2024-11-22 04:14:20.439462: Pseudo dice [0.8608] +2024-11-22 04:14:20.439539: Epoch time: 17.4 s +2024-11-22 04:14:21.295809: +2024-11-22 04:14:21.296030: Epoch 3270 +2024-11-22 04:14:21.296145: Current learning rate: 0.00623 +2024-11-22 04:14:39.698005: train_loss -0.7896 +2024-11-22 04:14:39.698215: val_loss -0.7585 +2024-11-22 04:14:39.698289: Pseudo dice [0.8437] +2024-11-22 04:14:39.698361: Epoch time: 18.4 s +2024-11-22 04:14:40.578676: +2024-11-22 04:14:40.578902: Epoch 3271 +2024-11-22 04:14:40.579014: Current learning rate: 0.00623 +2024-11-22 04:14:59.156611: train_loss -0.7915 +2024-11-22 04:14:59.156890: val_loss -0.7566 +2024-11-22 04:14:59.156966: Pseudo dice [0.8398] +2024-11-22 04:14:59.157052: Epoch time: 18.58 s +2024-11-22 04:15:00.016824: +2024-11-22 04:15:00.017048: Epoch 3272 +2024-11-22 04:15:00.017167: Current learning rate: 0.00623 +2024-11-22 04:15:18.687071: train_loss -0.7755 +2024-11-22 04:15:18.687307: val_loss -0.7693 +2024-11-22 04:15:18.687382: Pseudo dice [0.8258] +2024-11-22 04:15:18.687460: Epoch time: 18.67 s +2024-11-22 04:15:19.548434: +2024-11-22 04:15:19.548654: Epoch 3273 +2024-11-22 04:15:19.548763: Current learning rate: 0.00623 +2024-11-22 04:15:38.092899: train_loss -0.7844 +2024-11-22 04:15:38.098514: val_loss -0.7511 +2024-11-22 04:15:38.098623: Pseudo dice [0.8405] +2024-11-22 04:15:38.098703: Epoch time: 18.55 s +2024-11-22 04:15:39.001912: +2024-11-22 04:15:39.002225: Epoch 3274 +2024-11-22 04:15:39.002342: Current learning rate: 0.00623 +2024-11-22 04:15:57.127146: train_loss -0.7797 +2024-11-22 04:15:57.127443: val_loss -0.7797 +2024-11-22 04:15:57.127520: Pseudo dice [0.8457] +2024-11-22 04:15:57.127602: Epoch time: 18.13 s +2024-11-22 04:15:58.005055: +2024-11-22 04:15:58.005284: Epoch 3275 +2024-11-22 04:15:58.005392: Current learning rate: 0.00623 +2024-11-22 04:16:16.180704: train_loss -0.7843 +2024-11-22 04:16:16.180965: val_loss -0.7694 +2024-11-22 04:16:16.181056: Pseudo dice [0.8436] +2024-11-22 04:16:16.181135: Epoch time: 18.18 s +2024-11-22 04:16:17.043879: +2024-11-22 04:16:17.044113: Epoch 3276 +2024-11-22 04:16:17.044223: Current learning rate: 0.00622 +2024-11-22 04:16:35.832741: train_loss -0.7833 +2024-11-22 04:16:35.833016: val_loss -0.7592 +2024-11-22 04:16:35.833093: Pseudo dice [0.8301] +2024-11-22 04:16:35.833167: Epoch time: 18.79 s +2024-11-22 04:16:36.693379: +2024-11-22 04:16:36.693599: Epoch 3277 +2024-11-22 04:16:36.693716: Current learning rate: 0.00622 +2024-11-22 04:16:54.399154: train_loss -0.7852 +2024-11-22 04:16:54.399362: val_loss -0.732 +2024-11-22 04:16:54.399437: Pseudo dice [0.8355] +2024-11-22 04:16:54.399509: Epoch time: 17.71 s +2024-11-22 04:16:55.262960: +2024-11-22 04:16:55.263165: Epoch 3278 +2024-11-22 04:16:55.263274: Current learning rate: 0.00622 +2024-11-22 04:17:14.511728: train_loss -0.7754 +2024-11-22 04:17:14.511976: val_loss -0.7679 +2024-11-22 04:17:14.512058: Pseudo dice [0.8443] +2024-11-22 04:17:14.512140: Epoch time: 19.25 s +2024-11-22 04:17:15.378390: +2024-11-22 04:17:15.378612: Epoch 3279 +2024-11-22 04:17:15.378723: Current learning rate: 0.00622 +2024-11-22 04:17:34.395026: train_loss -0.7839 +2024-11-22 04:17:34.395254: val_loss -0.783 +2024-11-22 04:17:34.395335: Pseudo dice [0.8291] +2024-11-22 04:17:34.395420: Epoch time: 19.02 s +2024-11-22 04:17:35.261268: +2024-11-22 04:17:35.261579: Epoch 3280 +2024-11-22 04:17:35.261698: Current learning rate: 0.00622 +2024-11-22 04:17:53.866179: train_loss -0.7854 +2024-11-22 04:17:53.866395: val_loss -0.7806 +2024-11-22 04:17:53.866472: Pseudo dice [0.8553] +2024-11-22 04:17:53.866549: Epoch time: 18.61 s +2024-11-22 04:17:54.757952: +2024-11-22 04:17:54.758154: Epoch 3281 +2024-11-22 04:17:54.758265: Current learning rate: 0.00622 +2024-11-22 04:18:14.143353: train_loss -0.7811 +2024-11-22 04:18:14.143584: val_loss -0.7414 +2024-11-22 04:18:14.143710: Pseudo dice [0.8311] +2024-11-22 04:18:14.143824: Epoch time: 19.39 s +2024-11-22 04:18:15.013148: +2024-11-22 04:18:15.013343: Epoch 3282 +2024-11-22 04:18:15.013459: Current learning rate: 0.00622 +2024-11-22 04:18:33.680729: train_loss -0.775 +2024-11-22 04:18:33.680970: val_loss -0.7849 +2024-11-22 04:18:33.681053: Pseudo dice [0.8514] +2024-11-22 04:18:33.681137: Epoch time: 18.67 s +2024-11-22 04:18:34.539143: +2024-11-22 04:18:34.539461: Epoch 3283 +2024-11-22 04:18:34.539570: Current learning rate: 0.00622 +2024-11-22 04:18:53.359294: train_loss -0.7756 +2024-11-22 04:18:53.359558: val_loss -0.7725 +2024-11-22 04:18:53.359640: Pseudo dice [0.8375] +2024-11-22 04:18:53.359720: Epoch time: 18.82 s +2024-11-22 04:18:54.335148: +2024-11-22 04:18:54.335337: Epoch 3284 +2024-11-22 04:18:54.335448: Current learning rate: 0.00621 +2024-11-22 04:19:12.638855: train_loss -0.7822 +2024-11-22 04:19:12.639073: val_loss -0.7712 +2024-11-22 04:19:12.639150: Pseudo dice [0.8596] +2024-11-22 04:19:12.639227: Epoch time: 18.3 s +2024-11-22 04:19:13.874511: +2024-11-22 04:19:13.874707: Epoch 3285 +2024-11-22 04:19:13.874815: Current learning rate: 0.00621 +2024-11-22 04:19:32.655245: train_loss -0.7872 +2024-11-22 04:19:32.655492: val_loss -0.7597 +2024-11-22 04:19:32.655575: Pseudo dice [0.8424] +2024-11-22 04:19:32.655701: Epoch time: 18.78 s +2024-11-22 04:19:33.517851: +2024-11-22 04:19:33.518066: Epoch 3286 +2024-11-22 04:19:33.518177: Current learning rate: 0.00621 +2024-11-22 04:19:51.390379: train_loss -0.7777 +2024-11-22 04:19:51.390585: val_loss -0.7527 +2024-11-22 04:19:51.390726: Pseudo dice [0.8354] +2024-11-22 04:19:51.390805: Epoch time: 17.87 s +2024-11-22 04:19:52.245548: +2024-11-22 04:19:52.245778: Epoch 3287 +2024-11-22 04:19:52.245890: Current learning rate: 0.00621 +2024-11-22 04:20:10.027343: train_loss -0.7789 +2024-11-22 04:20:10.027561: val_loss -0.7769 +2024-11-22 04:20:10.027637: Pseudo dice [0.859] +2024-11-22 04:20:10.027715: Epoch time: 17.78 s +2024-11-22 04:20:10.882052: +2024-11-22 04:20:10.882289: Epoch 3288 +2024-11-22 04:20:10.882398: Current learning rate: 0.00621 +2024-11-22 04:20:28.719225: train_loss -0.7775 +2024-11-22 04:20:28.719475: val_loss -0.752 +2024-11-22 04:20:28.719559: Pseudo dice [0.8478] +2024-11-22 04:20:28.719640: Epoch time: 17.84 s +2024-11-22 04:20:29.718318: +2024-11-22 04:20:29.718541: Epoch 3289 +2024-11-22 04:20:29.718661: Current learning rate: 0.00621 +2024-11-22 04:20:48.496032: train_loss -0.7875 +2024-11-22 04:20:48.496267: val_loss -0.7598 +2024-11-22 04:20:48.496343: Pseudo dice [0.867] +2024-11-22 04:20:48.496423: Epoch time: 18.78 s +2024-11-22 04:20:49.363019: +2024-11-22 04:20:49.363231: Epoch 3290 +2024-11-22 04:20:49.363338: Current learning rate: 0.00621 +2024-11-22 04:21:08.275254: train_loss -0.7792 +2024-11-22 04:21:08.275466: val_loss -0.7425 +2024-11-22 04:21:08.275540: Pseudo dice [0.8648] +2024-11-22 04:21:08.275614: Epoch time: 18.91 s +2024-11-22 04:21:09.136182: +2024-11-22 04:21:09.136465: Epoch 3291 +2024-11-22 04:21:09.136576: Current learning rate: 0.00621 +2024-11-22 04:21:28.046071: train_loss -0.7883 +2024-11-22 04:21:28.046293: val_loss -0.7831 +2024-11-22 04:21:28.046435: Pseudo dice [0.8603] +2024-11-22 04:21:28.046516: Epoch time: 18.91 s +2024-11-22 04:21:28.920185: +2024-11-22 04:21:28.920386: Epoch 3292 +2024-11-22 04:21:28.920494: Current learning rate: 0.00621 +2024-11-22 04:21:48.517024: train_loss -0.7772 +2024-11-22 04:21:48.517249: val_loss -0.7686 +2024-11-22 04:21:48.517369: Pseudo dice [0.8181] +2024-11-22 04:21:48.517450: Epoch time: 19.6 s +2024-11-22 04:21:49.389317: +2024-11-22 04:21:49.389557: Epoch 3293 +2024-11-22 04:21:49.389668: Current learning rate: 0.0062 +2024-11-22 04:22:07.373875: train_loss -0.7692 +2024-11-22 04:22:07.374118: val_loss -0.7672 +2024-11-22 04:22:07.374194: Pseudo dice [0.8501] +2024-11-22 04:22:07.374275: Epoch time: 17.99 s +2024-11-22 04:22:08.258376: +2024-11-22 04:22:08.258673: Epoch 3294 +2024-11-22 04:22:08.258802: Current learning rate: 0.0062 +2024-11-22 04:22:26.128185: train_loss -0.7737 +2024-11-22 04:22:26.128406: val_loss -0.7701 +2024-11-22 04:22:26.128518: Pseudo dice [0.8426] +2024-11-22 04:22:26.128595: Epoch time: 17.87 s +2024-11-22 04:22:26.988868: +2024-11-22 04:22:26.989082: Epoch 3295 +2024-11-22 04:22:26.989194: Current learning rate: 0.0062 +2024-11-22 04:22:44.552644: train_loss -0.781 +2024-11-22 04:22:44.552878: val_loss -0.7914 +2024-11-22 04:22:44.552959: Pseudo dice [0.8542] +2024-11-22 04:22:44.553043: Epoch time: 17.56 s +2024-11-22 04:22:45.523350: +2024-11-22 04:22:45.523581: Epoch 3296 +2024-11-22 04:22:45.523691: Current learning rate: 0.0062 +2024-11-22 04:23:03.924659: train_loss -0.7805 +2024-11-22 04:23:03.925144: val_loss -0.7711 +2024-11-22 04:23:03.927416: Pseudo dice [0.8414] +2024-11-22 04:23:03.927509: Epoch time: 18.4 s +2024-11-22 04:23:04.941143: +2024-11-22 04:23:04.941369: Epoch 3297 +2024-11-22 04:23:04.941486: Current learning rate: 0.0062 +2024-11-22 04:23:23.238488: train_loss -0.7785 +2024-11-22 04:23:23.238700: val_loss -0.7728 +2024-11-22 04:23:23.238774: Pseudo dice [0.8313] +2024-11-22 04:23:23.238844: Epoch time: 18.3 s +2024-11-22 04:23:24.096744: +2024-11-22 04:23:24.096947: Epoch 3298 +2024-11-22 04:23:24.097059: Current learning rate: 0.0062 +2024-11-22 04:23:42.670246: train_loss -0.7825 +2024-11-22 04:23:42.670529: val_loss -0.7738 +2024-11-22 04:23:42.670608: Pseudo dice [0.842] +2024-11-22 04:23:42.670685: Epoch time: 18.57 s +2024-11-22 04:23:43.532384: +2024-11-22 04:23:43.532644: Epoch 3299 +2024-11-22 04:23:43.532754: Current learning rate: 0.0062 +2024-11-22 04:24:01.848135: train_loss -0.7816 +2024-11-22 04:24:01.848380: val_loss -0.7737 +2024-11-22 04:24:01.848458: Pseudo dice [0.8416] +2024-11-22 04:24:01.848541: Epoch time: 18.32 s +2024-11-22 04:24:02.953246: +2024-11-22 04:24:02.953488: Epoch 3300 +2024-11-22 04:24:02.953606: Current learning rate: 0.0062 +2024-11-22 04:24:21.602741: train_loss -0.7807 +2024-11-22 04:24:21.602968: val_loss -0.7494 +2024-11-22 04:24:21.603054: Pseudo dice [0.8204] +2024-11-22 04:24:21.603135: Epoch time: 18.65 s +2024-11-22 04:24:22.666427: +2024-11-22 04:24:22.666729: Epoch 3301 +2024-11-22 04:24:22.666840: Current learning rate: 0.00619 +2024-11-22 04:24:41.453985: train_loss -0.7885 +2024-11-22 04:24:41.454208: val_loss -0.7718 +2024-11-22 04:24:41.454298: Pseudo dice [0.8566] +2024-11-22 04:24:41.454440: Epoch time: 18.79 s +2024-11-22 04:24:42.423757: +2024-11-22 04:24:42.423973: Epoch 3302 +2024-11-22 04:24:42.424098: Current learning rate: 0.00619 +2024-11-22 04:25:00.851118: train_loss -0.7776 +2024-11-22 04:25:00.851336: val_loss -0.7762 +2024-11-22 04:25:00.851417: Pseudo dice [0.8398] +2024-11-22 04:25:00.851493: Epoch time: 18.43 s +2024-11-22 04:25:01.743704: +2024-11-22 04:25:01.743922: Epoch 3303 +2024-11-22 04:25:01.744039: Current learning rate: 0.00619 +2024-11-22 04:25:18.949387: train_loss -0.7684 +2024-11-22 04:25:18.949637: val_loss -0.7665 +2024-11-22 04:25:18.949712: Pseudo dice [0.8374] +2024-11-22 04:25:18.949795: Epoch time: 17.21 s +2024-11-22 04:25:19.815479: +2024-11-22 04:25:19.815698: Epoch 3304 +2024-11-22 04:25:19.815810: Current learning rate: 0.00619 +2024-11-22 04:25:38.517839: train_loss -0.7872 +2024-11-22 04:25:38.518067: val_loss -0.7666 +2024-11-22 04:25:38.518145: Pseudo dice [0.8345] +2024-11-22 04:25:38.518219: Epoch time: 18.7 s +2024-11-22 04:25:39.405483: +2024-11-22 04:25:39.405689: Epoch 3305 +2024-11-22 04:25:39.405800: Current learning rate: 0.00619 +2024-11-22 04:25:57.089507: train_loss -0.7804 +2024-11-22 04:25:57.089740: val_loss -0.7608 +2024-11-22 04:25:57.089814: Pseudo dice [0.8444] +2024-11-22 04:25:57.089889: Epoch time: 17.68 s +2024-11-22 04:25:58.117500: +2024-11-22 04:25:58.117731: Epoch 3306 +2024-11-22 04:25:58.117838: Current learning rate: 0.00619 +2024-11-22 04:26:16.569106: train_loss -0.7786 +2024-11-22 04:26:16.569330: val_loss -0.7696 +2024-11-22 04:26:16.569407: Pseudo dice [0.8543] +2024-11-22 04:26:16.569486: Epoch time: 18.45 s +2024-11-22 04:26:17.856561: +2024-11-22 04:26:17.856807: Epoch 3307 +2024-11-22 04:26:17.856951: Current learning rate: 0.00619 +2024-11-22 04:26:37.631023: train_loss -0.7636 +2024-11-22 04:26:37.635572: val_loss -0.7624 +2024-11-22 04:26:37.635728: Pseudo dice [0.8386] +2024-11-22 04:26:37.635810: Epoch time: 19.78 s +2024-11-22 04:26:38.549537: +2024-11-22 04:26:38.549758: Epoch 3308 +2024-11-22 04:26:38.549872: Current learning rate: 0.00619 +2024-11-22 04:26:56.426667: train_loss -0.7801 +2024-11-22 04:26:56.427526: val_loss -0.7752 +2024-11-22 04:26:56.427638: Pseudo dice [0.8531] +2024-11-22 04:26:56.427714: Epoch time: 17.88 s +2024-11-22 04:26:57.290828: +2024-11-22 04:26:57.291043: Epoch 3309 +2024-11-22 04:26:57.291152: Current learning rate: 0.00619 +2024-11-22 04:27:15.144597: train_loss -0.7849 +2024-11-22 04:27:15.144810: val_loss -0.7765 +2024-11-22 04:27:15.144884: Pseudo dice [0.8397] +2024-11-22 04:27:15.144959: Epoch time: 17.85 s +2024-11-22 04:27:16.005443: +2024-11-22 04:27:16.005672: Epoch 3310 +2024-11-22 04:27:16.005785: Current learning rate: 0.00618 +2024-11-22 04:27:34.536215: train_loss -0.7784 +2024-11-22 04:27:34.538075: val_loss -0.757 +2024-11-22 04:27:34.538168: Pseudo dice [0.8307] +2024-11-22 04:27:34.538252: Epoch time: 18.53 s +2024-11-22 04:27:35.423410: +2024-11-22 04:27:35.423635: Epoch 3311 +2024-11-22 04:27:35.423746: Current learning rate: 0.00618 +2024-11-22 04:27:53.908929: train_loss -0.7853 +2024-11-22 04:27:53.909169: val_loss -0.7678 +2024-11-22 04:27:53.909244: Pseudo dice [0.8294] +2024-11-22 04:27:53.909317: Epoch time: 18.49 s +2024-11-22 04:27:54.789884: +2024-11-22 04:27:54.790101: Epoch 3312 +2024-11-22 04:27:54.790213: Current learning rate: 0.00618 +2024-11-22 04:28:14.697809: train_loss -0.7818 +2024-11-22 04:28:14.698043: val_loss -0.7716 +2024-11-22 04:28:14.698121: Pseudo dice [0.8539] +2024-11-22 04:28:14.698296: Epoch time: 19.91 s +2024-11-22 04:28:15.566029: +2024-11-22 04:28:15.566260: Epoch 3313 +2024-11-22 04:28:15.566371: Current learning rate: 0.00618 +2024-11-22 04:28:34.483685: train_loss -0.7937 +2024-11-22 04:28:34.483908: val_loss -0.7851 +2024-11-22 04:28:34.483988: Pseudo dice [0.8612] +2024-11-22 04:28:34.498585: Epoch time: 18.92 s +2024-11-22 04:28:35.362703: +2024-11-22 04:28:35.362936: Epoch 3314 +2024-11-22 04:28:35.363057: Current learning rate: 0.00618 +2024-11-22 04:28:54.097754: train_loss -0.7838 +2024-11-22 04:28:54.098005: val_loss -0.7601 +2024-11-22 04:28:54.098083: Pseudo dice [0.8429] +2024-11-22 04:28:54.098168: Epoch time: 18.74 s +2024-11-22 04:28:55.067352: +2024-11-22 04:28:55.067570: Epoch 3315 +2024-11-22 04:28:55.067691: Current learning rate: 0.00618 +2024-11-22 04:29:14.208242: train_loss -0.7853 +2024-11-22 04:29:14.208462: val_loss -0.756 +2024-11-22 04:29:14.208543: Pseudo dice [0.8441] +2024-11-22 04:29:14.208617: Epoch time: 19.14 s +2024-11-22 04:29:15.073219: +2024-11-22 04:29:15.073457: Epoch 3316 +2024-11-22 04:29:15.073571: Current learning rate: 0.00618 +2024-11-22 04:29:33.904364: train_loss -0.7852 +2024-11-22 04:29:33.904573: val_loss -0.7806 +2024-11-22 04:29:33.904648: Pseudo dice [0.8438] +2024-11-22 04:29:33.904723: Epoch time: 18.83 s +2024-11-22 04:29:34.765019: +2024-11-22 04:29:34.765379: Epoch 3317 +2024-11-22 04:29:34.765488: Current learning rate: 0.00618 +2024-11-22 04:29:53.323194: train_loss -0.7909 +2024-11-22 04:29:53.323450: val_loss -0.7545 +2024-11-22 04:29:53.323530: Pseudo dice [0.8246] +2024-11-22 04:29:53.323617: Epoch time: 18.56 s +2024-11-22 04:29:54.198201: +2024-11-22 04:29:54.198425: Epoch 3318 +2024-11-22 04:29:54.198536: Current learning rate: 0.00617 +2024-11-22 04:30:13.161590: train_loss -0.7873 +2024-11-22 04:30:13.161804: val_loss -0.7703 +2024-11-22 04:30:13.161876: Pseudo dice [0.847] +2024-11-22 04:30:13.161950: Epoch time: 18.96 s +2024-11-22 04:30:14.450462: +2024-11-22 04:30:14.450679: Epoch 3319 +2024-11-22 04:30:14.450784: Current learning rate: 0.00617 +2024-11-22 04:30:32.797064: train_loss -0.7858 +2024-11-22 04:30:32.797310: val_loss -0.7796 +2024-11-22 04:30:32.797393: Pseudo dice [0.8486] +2024-11-22 04:30:32.797470: Epoch time: 18.35 s +2024-11-22 04:30:33.681453: +2024-11-22 04:30:33.681677: Epoch 3320 +2024-11-22 04:30:33.681789: Current learning rate: 0.00617 +2024-11-22 04:30:52.191797: train_loss -0.7832 +2024-11-22 04:30:52.192062: val_loss -0.7804 +2024-11-22 04:30:52.192146: Pseudo dice [0.8511] +2024-11-22 04:30:52.192230: Epoch time: 18.51 s +2024-11-22 04:30:53.065863: +2024-11-22 04:30:53.066170: Epoch 3321 +2024-11-22 04:30:53.066276: Current learning rate: 0.00617 +2024-11-22 04:31:11.378120: train_loss -0.7867 +2024-11-22 04:31:11.378342: val_loss -0.771 +2024-11-22 04:31:11.378416: Pseudo dice [0.8361] +2024-11-22 04:31:11.378489: Epoch time: 18.31 s +2024-11-22 04:31:12.244669: +2024-11-22 04:31:12.244898: Epoch 3322 +2024-11-22 04:31:12.245024: Current learning rate: 0.00617 +2024-11-22 04:31:31.079493: train_loss -0.774 +2024-11-22 04:31:31.079703: val_loss -0.7598 +2024-11-22 04:31:31.079776: Pseudo dice [0.8353] +2024-11-22 04:31:31.079847: Epoch time: 18.84 s +2024-11-22 04:31:31.953192: +2024-11-22 04:31:31.953400: Epoch 3323 +2024-11-22 04:31:31.953507: Current learning rate: 0.00617 +2024-11-22 04:31:49.516349: train_loss -0.7766 +2024-11-22 04:31:49.516629: val_loss -0.7741 +2024-11-22 04:31:49.516705: Pseudo dice [0.8495] +2024-11-22 04:31:49.516785: Epoch time: 17.56 s +2024-11-22 04:31:50.396778: +2024-11-22 04:31:50.397006: Epoch 3324 +2024-11-22 04:31:50.397118: Current learning rate: 0.00617 +2024-11-22 04:32:08.554332: train_loss -0.7766 +2024-11-22 04:32:08.554615: val_loss -0.7684 +2024-11-22 04:32:08.554695: Pseudo dice [0.8464] +2024-11-22 04:32:08.554774: Epoch time: 18.16 s +2024-11-22 04:32:09.423747: +2024-11-22 04:32:09.423983: Epoch 3325 +2024-11-22 04:32:09.424132: Current learning rate: 0.00617 +2024-11-22 04:32:27.877395: train_loss -0.786 +2024-11-22 04:32:27.877627: val_loss -0.7392 +2024-11-22 04:32:27.877701: Pseudo dice [0.8369] +2024-11-22 04:32:27.877777: Epoch time: 18.45 s +2024-11-22 04:32:28.750779: +2024-11-22 04:32:28.751123: Epoch 3326 +2024-11-22 04:32:28.751252: Current learning rate: 0.00617 +2024-11-22 04:32:46.773831: train_loss -0.7795 +2024-11-22 04:32:46.797918: val_loss -0.7742 +2024-11-22 04:32:46.798031: Pseudo dice [0.8523] +2024-11-22 04:32:46.798110: Epoch time: 18.02 s +2024-11-22 04:32:47.658926: +2024-11-22 04:32:47.659142: Epoch 3327 +2024-11-22 04:32:47.659250: Current learning rate: 0.00616 +2024-11-22 04:33:06.007623: train_loss -0.7785 +2024-11-22 04:33:06.007852: val_loss -0.7626 +2024-11-22 04:33:06.007931: Pseudo dice [0.8559] +2024-11-22 04:33:06.008014: Epoch time: 18.35 s +2024-11-22 04:33:06.877235: +2024-11-22 04:33:06.877461: Epoch 3328 +2024-11-22 04:33:06.877867: Current learning rate: 0.00616 +2024-11-22 04:33:25.178214: train_loss -0.7842 +2024-11-22 04:33:25.178472: val_loss -0.7594 +2024-11-22 04:33:25.178549: Pseudo dice [0.8454] +2024-11-22 04:33:25.178631: Epoch time: 18.3 s +2024-11-22 04:33:26.043824: +2024-11-22 04:33:26.044047: Epoch 3329 +2024-11-22 04:33:26.044163: Current learning rate: 0.00616 +2024-11-22 04:33:43.698412: train_loss -0.7867 +2024-11-22 04:33:43.698636: val_loss -0.772 +2024-11-22 04:33:43.698716: Pseudo dice [0.8479] +2024-11-22 04:33:43.698790: Epoch time: 17.66 s +2024-11-22 04:33:44.946412: +2024-11-22 04:33:44.946669: Epoch 3330 +2024-11-22 04:33:44.946781: Current learning rate: 0.00616 +2024-11-22 04:34:03.397269: train_loss -0.7878 +2024-11-22 04:34:03.397491: val_loss -0.7774 +2024-11-22 04:34:03.397569: Pseudo dice [0.8521] +2024-11-22 04:34:03.397649: Epoch time: 18.45 s +2024-11-22 04:34:04.261864: +2024-11-22 04:34:04.262100: Epoch 3331 +2024-11-22 04:34:04.262207: Current learning rate: 0.00616 +2024-11-22 04:34:22.549460: train_loss -0.7911 +2024-11-22 04:34:22.551856: val_loss -0.7439 +2024-11-22 04:34:22.551943: Pseudo dice [0.8314] +2024-11-22 04:34:22.552070: Epoch time: 18.29 s +2024-11-22 04:34:23.651140: +2024-11-22 04:34:23.651360: Epoch 3332 +2024-11-22 04:34:23.651465: Current learning rate: 0.00616 +2024-11-22 04:34:43.173442: train_loss -0.777 +2024-11-22 04:34:43.173661: val_loss -0.7774 +2024-11-22 04:34:43.173738: Pseudo dice [0.8495] +2024-11-22 04:34:43.173812: Epoch time: 19.52 s +2024-11-22 04:34:44.138507: +2024-11-22 04:34:44.138716: Epoch 3333 +2024-11-22 04:34:44.138828: Current learning rate: 0.00616 +2024-11-22 04:35:02.455461: train_loss -0.7768 +2024-11-22 04:35:02.455682: val_loss -0.7464 +2024-11-22 04:35:02.455757: Pseudo dice [0.8382] +2024-11-22 04:35:02.455831: Epoch time: 18.32 s +2024-11-22 04:35:03.330012: +2024-11-22 04:35:03.330386: Epoch 3334 +2024-11-22 04:35:03.330499: Current learning rate: 0.00616 +2024-11-22 04:35:21.514745: train_loss -0.7869 +2024-11-22 04:35:21.514989: val_loss -0.7508 +2024-11-22 04:35:21.515076: Pseudo dice [0.8352] +2024-11-22 04:35:21.515165: Epoch time: 18.19 s +2024-11-22 04:35:22.392168: +2024-11-22 04:35:22.392382: Epoch 3335 +2024-11-22 04:35:22.392493: Current learning rate: 0.00615 +2024-11-22 04:35:41.187950: train_loss -0.7759 +2024-11-22 04:35:41.188181: val_loss -0.7691 +2024-11-22 04:35:41.188254: Pseudo dice [0.8489] +2024-11-22 04:35:41.188391: Epoch time: 18.8 s +2024-11-22 04:35:42.060650: +2024-11-22 04:35:42.060887: Epoch 3336 +2024-11-22 04:35:42.061004: Current learning rate: 0.00615 +2024-11-22 04:36:00.373637: train_loss -0.7789 +2024-11-22 04:36:00.373858: val_loss -0.7764 +2024-11-22 04:36:00.373932: Pseudo dice [0.847] +2024-11-22 04:36:00.374011: Epoch time: 18.31 s +2024-11-22 04:36:01.244459: +2024-11-22 04:36:01.244668: Epoch 3337 +2024-11-22 04:36:01.244777: Current learning rate: 0.00615 +2024-11-22 04:36:20.694036: train_loss -0.7805 +2024-11-22 04:36:20.694281: val_loss -0.7721 +2024-11-22 04:36:20.694362: Pseudo dice [0.8389] +2024-11-22 04:36:20.694445: Epoch time: 19.45 s +2024-11-22 04:36:21.568560: +2024-11-22 04:36:21.568752: Epoch 3338 +2024-11-22 04:36:21.568863: Current learning rate: 0.00615 +2024-11-22 04:36:39.749275: train_loss -0.784 +2024-11-22 04:36:39.749495: val_loss -0.7534 +2024-11-22 04:36:39.749570: Pseudo dice [0.8246] +2024-11-22 04:36:39.749646: Epoch time: 18.18 s +2024-11-22 04:36:40.669666: +2024-11-22 04:36:40.669887: Epoch 3339 +2024-11-22 04:36:40.670001: Current learning rate: 0.00615 +2024-11-22 04:36:59.211006: train_loss -0.7867 +2024-11-22 04:36:59.211229: val_loss -0.7922 +2024-11-22 04:36:59.211302: Pseudo dice [0.8595] +2024-11-22 04:36:59.211378: Epoch time: 18.54 s +2024-11-22 04:37:00.079550: +2024-11-22 04:37:00.079761: Epoch 3340 +2024-11-22 04:37:00.079870: Current learning rate: 0.00615 +2024-11-22 04:37:18.802549: train_loss -0.7896 +2024-11-22 04:37:18.802778: val_loss -0.7651 +2024-11-22 04:37:18.802853: Pseudo dice [0.8425] +2024-11-22 04:37:18.802934: Epoch time: 18.72 s +2024-11-22 04:37:19.688965: +2024-11-22 04:37:19.689165: Epoch 3341 +2024-11-22 04:37:19.689273: Current learning rate: 0.00615 +2024-11-22 04:37:38.033830: train_loss -0.7896 +2024-11-22 04:37:38.034107: val_loss -0.7806 +2024-11-22 04:37:38.034185: Pseudo dice [0.8323] +2024-11-22 04:37:38.034265: Epoch time: 18.35 s +2024-11-22 04:37:39.387431: +2024-11-22 04:37:39.387649: Epoch 3342 +2024-11-22 04:37:39.387756: Current learning rate: 0.00615 +2024-11-22 04:37:56.864679: train_loss -0.7833 +2024-11-22 04:37:56.864914: val_loss -0.7626 +2024-11-22 04:37:56.865001: Pseudo dice [0.8461] +2024-11-22 04:37:56.865077: Epoch time: 17.48 s +2024-11-22 04:37:57.737663: +2024-11-22 04:37:57.737883: Epoch 3343 +2024-11-22 04:37:57.737999: Current learning rate: 0.00614 +2024-11-22 04:38:15.955539: train_loss -0.7741 +2024-11-22 04:38:15.955765: val_loss -0.7572 +2024-11-22 04:38:15.955842: Pseudo dice [0.8393] +2024-11-22 04:38:15.955919: Epoch time: 18.22 s +2024-11-22 04:38:16.888050: +2024-11-22 04:38:16.888273: Epoch 3344 +2024-11-22 04:38:16.888386: Current learning rate: 0.00614 +2024-11-22 04:38:35.657855: train_loss -0.7835 +2024-11-22 04:38:35.658138: val_loss -0.7588 +2024-11-22 04:38:35.658214: Pseudo dice [0.8445] +2024-11-22 04:38:35.658295: Epoch time: 18.77 s +2024-11-22 04:38:36.570718: +2024-11-22 04:38:36.570937: Epoch 3345 +2024-11-22 04:38:36.571050: Current learning rate: 0.00614 +2024-11-22 04:38:55.500407: train_loss -0.7771 +2024-11-22 04:38:55.500631: val_loss -0.7602 +2024-11-22 04:38:55.500707: Pseudo dice [0.8544] +2024-11-22 04:38:55.500786: Epoch time: 18.93 s +2024-11-22 04:38:56.372701: +2024-11-22 04:38:56.372927: Epoch 3346 +2024-11-22 04:38:56.373044: Current learning rate: 0.00614 +2024-11-22 04:39:16.297467: train_loss -0.7773 +2024-11-22 04:39:16.297689: val_loss -0.7647 +2024-11-22 04:39:16.297762: Pseudo dice [0.8416] +2024-11-22 04:39:16.297836: Epoch time: 19.93 s +2024-11-22 04:39:17.177798: +2024-11-22 04:39:17.178106: Epoch 3347 +2024-11-22 04:39:17.178213: Current learning rate: 0.00614 +2024-11-22 04:39:36.100181: train_loss -0.7893 +2024-11-22 04:39:36.100410: val_loss -0.8029 +2024-11-22 04:39:36.100483: Pseudo dice [0.8607] +2024-11-22 04:39:36.100557: Epoch time: 18.92 s +2024-11-22 04:39:37.013980: +2024-11-22 04:39:37.014192: Epoch 3348 +2024-11-22 04:39:37.014306: Current learning rate: 0.00614 +2024-11-22 04:39:55.014022: train_loss -0.7778 +2024-11-22 04:39:55.014282: val_loss -0.7714 +2024-11-22 04:39:55.014361: Pseudo dice [0.8355] +2024-11-22 04:39:55.014444: Epoch time: 18.0 s +2024-11-22 04:39:55.891495: +2024-11-22 04:39:55.891713: Epoch 3349 +2024-11-22 04:39:55.891823: Current learning rate: 0.00614 +2024-11-22 04:40:14.016049: train_loss -0.7881 +2024-11-22 04:40:14.016270: val_loss -0.7747 +2024-11-22 04:40:14.016345: Pseudo dice [0.838] +2024-11-22 04:40:14.021677: Epoch time: 18.13 s +2024-11-22 04:40:15.193234: +2024-11-22 04:40:15.193462: Epoch 3350 +2024-11-22 04:40:15.193574: Current learning rate: 0.00614 +2024-11-22 04:40:34.246131: train_loss -0.7828 +2024-11-22 04:40:34.246354: val_loss -0.7411 +2024-11-22 04:40:34.246427: Pseudo dice [0.856] +2024-11-22 04:40:34.246502: Epoch time: 19.05 s +2024-11-22 04:40:35.114011: +2024-11-22 04:40:35.114239: Epoch 3351 +2024-11-22 04:40:35.114357: Current learning rate: 0.00614 +2024-11-22 04:40:53.312606: train_loss -0.784 +2024-11-22 04:40:53.312835: val_loss -0.7614 +2024-11-22 04:40:53.312916: Pseudo dice [0.8422] +2024-11-22 04:40:53.313004: Epoch time: 18.2 s +2024-11-22 04:40:54.185705: +2024-11-22 04:40:54.185947: Epoch 3352 +2024-11-22 04:40:54.186069: Current learning rate: 0.00613 +2024-11-22 04:41:13.717355: train_loss -0.7896 +2024-11-22 04:41:13.717589: val_loss -0.75 +2024-11-22 04:41:13.717739: Pseudo dice [0.8519] +2024-11-22 04:41:13.717819: Epoch time: 19.53 s +2024-11-22 04:41:14.976635: +2024-11-22 04:41:14.976840: Epoch 3353 +2024-11-22 04:41:14.976945: Current learning rate: 0.00613 +2024-11-22 04:41:34.113790: train_loss -0.7856 +2024-11-22 04:41:34.114023: val_loss -0.7671 +2024-11-22 04:41:34.114105: Pseudo dice [0.842] +2024-11-22 04:41:34.114184: Epoch time: 19.14 s +2024-11-22 04:41:34.982219: +2024-11-22 04:41:34.982511: Epoch 3354 +2024-11-22 04:41:34.982628: Current learning rate: 0.00613 +2024-11-22 04:41:53.367712: train_loss -0.7705 +2024-11-22 04:41:53.367928: val_loss -0.7775 +2024-11-22 04:41:53.368011: Pseudo dice [0.8369] +2024-11-22 04:41:53.368088: Epoch time: 18.39 s +2024-11-22 04:41:54.238148: +2024-11-22 04:41:54.238374: Epoch 3355 +2024-11-22 04:41:54.238490: Current learning rate: 0.00613 +2024-11-22 04:42:12.334039: train_loss -0.7727 +2024-11-22 04:42:12.339473: val_loss -0.7729 +2024-11-22 04:42:12.339642: Pseudo dice [0.844] +2024-11-22 04:42:12.339741: Epoch time: 18.1 s +2024-11-22 04:42:13.226168: +2024-11-22 04:42:13.226374: Epoch 3356 +2024-11-22 04:42:13.226485: Current learning rate: 0.00613 +2024-11-22 04:42:32.013149: train_loss -0.775 +2024-11-22 04:42:32.013369: val_loss -0.7693 +2024-11-22 04:42:32.013443: Pseudo dice [0.8533] +2024-11-22 04:42:32.013519: Epoch time: 18.79 s +2024-11-22 04:42:32.887928: +2024-11-22 04:42:32.888161: Epoch 3357 +2024-11-22 04:42:32.888282: Current learning rate: 0.00613 +2024-11-22 04:42:51.521906: train_loss -0.7893 +2024-11-22 04:42:51.522125: val_loss -0.756 +2024-11-22 04:42:51.522197: Pseudo dice [0.8334] +2024-11-22 04:42:51.522272: Epoch time: 18.63 s +2024-11-22 04:42:52.396135: +2024-11-22 04:42:52.396349: Epoch 3358 +2024-11-22 04:42:52.396461: Current learning rate: 0.00613 +2024-11-22 04:43:10.254668: train_loss -0.7861 +2024-11-22 04:43:10.254886: val_loss -0.7639 +2024-11-22 04:43:10.254970: Pseudo dice [0.8446] +2024-11-22 04:43:10.255056: Epoch time: 17.86 s +2024-11-22 04:43:11.124316: +2024-11-22 04:43:11.124531: Epoch 3359 +2024-11-22 04:43:11.124640: Current learning rate: 0.00613 +2024-11-22 04:43:29.216725: train_loss -0.7671 +2024-11-22 04:43:29.216979: val_loss -0.7456 +2024-11-22 04:43:29.217061: Pseudo dice [0.847] +2024-11-22 04:43:29.217144: Epoch time: 18.09 s +2024-11-22 04:43:30.084033: +2024-11-22 04:43:30.084265: Epoch 3360 +2024-11-22 04:43:30.084379: Current learning rate: 0.00612 +2024-11-22 04:43:48.471273: train_loss -0.7849 +2024-11-22 04:43:48.471485: val_loss -0.7335 +2024-11-22 04:43:48.471561: Pseudo dice [0.8625] +2024-11-22 04:43:48.471638: Epoch time: 18.39 s +2024-11-22 04:43:49.578064: +2024-11-22 04:43:49.578283: Epoch 3361 +2024-11-22 04:43:49.578390: Current learning rate: 0.00612 +2024-11-22 04:44:08.286537: train_loss -0.7712 +2024-11-22 04:44:08.286758: val_loss -0.7612 +2024-11-22 04:44:08.286837: Pseudo dice [0.807] +2024-11-22 04:44:08.286915: Epoch time: 18.71 s +2024-11-22 04:44:09.149645: +2024-11-22 04:44:09.149859: Epoch 3362 +2024-11-22 04:44:09.149968: Current learning rate: 0.00612 +2024-11-22 04:44:28.261591: train_loss -0.7783 +2024-11-22 04:44:28.261832: val_loss -0.7671 +2024-11-22 04:44:28.261908: Pseudo dice [0.8307] +2024-11-22 04:44:28.261998: Epoch time: 19.11 s +2024-11-22 04:44:29.133082: +2024-11-22 04:44:29.133297: Epoch 3363 +2024-11-22 04:44:29.133403: Current learning rate: 0.00612 +2024-11-22 04:44:47.832659: train_loss -0.7801 +2024-11-22 04:44:47.832874: val_loss -0.775 +2024-11-22 04:44:47.832947: Pseudo dice [0.8363] +2024-11-22 04:44:47.833029: Epoch time: 18.7 s +2024-11-22 04:44:49.115955: +2024-11-22 04:44:49.116304: Epoch 3364 +2024-11-22 04:44:49.116418: Current learning rate: 0.00612 +2024-11-22 04:45:08.560209: train_loss -0.7862 +2024-11-22 04:45:08.560428: val_loss -0.7522 +2024-11-22 04:45:08.560501: Pseudo dice [0.8517] +2024-11-22 04:45:08.560573: Epoch time: 19.45 s +2024-11-22 04:45:09.434119: +2024-11-22 04:45:09.434358: Epoch 3365 +2024-11-22 04:45:09.434470: Current learning rate: 0.00612 +2024-11-22 04:45:27.901893: train_loss -0.7833 +2024-11-22 04:45:27.902117: val_loss -0.7831 +2024-11-22 04:45:27.902215: Pseudo dice [0.851] +2024-11-22 04:45:27.902296: Epoch time: 18.47 s +2024-11-22 04:45:28.773639: +2024-11-22 04:45:28.773993: Epoch 3366 +2024-11-22 04:45:28.774104: Current learning rate: 0.00612 +2024-11-22 04:45:46.993760: train_loss -0.7914 +2024-11-22 04:45:46.994020: val_loss -0.7695 +2024-11-22 04:45:46.994122: Pseudo dice [0.8447] +2024-11-22 04:45:46.994208: Epoch time: 18.22 s +2024-11-22 04:45:47.869984: +2024-11-22 04:45:47.870210: Epoch 3367 +2024-11-22 04:45:47.870314: Current learning rate: 0.00612 +2024-11-22 04:46:06.597239: train_loss -0.7834 +2024-11-22 04:46:06.597458: val_loss -0.7806 +2024-11-22 04:46:06.597544: Pseudo dice [0.8432] +2024-11-22 04:46:06.597619: Epoch time: 18.73 s +2024-11-22 04:46:07.471550: +2024-11-22 04:46:07.471755: Epoch 3368 +2024-11-22 04:46:07.471865: Current learning rate: 0.00612 +2024-11-22 04:46:26.139540: train_loss -0.7685 +2024-11-22 04:46:26.139815: val_loss -0.7628 +2024-11-22 04:46:26.139891: Pseudo dice [0.8276] +2024-11-22 04:46:26.139970: Epoch time: 18.67 s +2024-11-22 04:46:27.019420: +2024-11-22 04:46:27.019646: Epoch 3369 +2024-11-22 04:46:27.019758: Current learning rate: 0.00611 +2024-11-22 04:46:46.138800: train_loss -0.772 +2024-11-22 04:46:46.139051: val_loss -0.7772 +2024-11-22 04:46:46.139194: Pseudo dice [0.8399] +2024-11-22 04:46:46.139290: Epoch time: 19.12 s +2024-11-22 04:46:47.014341: +2024-11-22 04:46:47.014546: Epoch 3370 +2024-11-22 04:46:47.014656: Current learning rate: 0.00611 +2024-11-22 04:47:05.469442: train_loss -0.7866 +2024-11-22 04:47:05.469711: val_loss -0.7751 +2024-11-22 04:47:05.469794: Pseudo dice [0.8453] +2024-11-22 04:47:05.469872: Epoch time: 18.46 s +2024-11-22 04:47:06.341645: +2024-11-22 04:47:06.341860: Epoch 3371 +2024-11-22 04:47:06.341970: Current learning rate: 0.00611 +2024-11-22 04:47:24.999471: train_loss -0.7834 +2024-11-22 04:47:24.999712: val_loss -0.741 +2024-11-22 04:47:24.999788: Pseudo dice [0.8141] +2024-11-22 04:47:24.999864: Epoch time: 18.66 s +2024-11-22 04:47:25.864731: +2024-11-22 04:47:25.864941: Epoch 3372 +2024-11-22 04:47:25.865086: Current learning rate: 0.00611 +2024-11-22 04:47:43.043788: train_loss -0.7689 +2024-11-22 04:47:43.044010: val_loss -0.7745 +2024-11-22 04:47:43.044091: Pseudo dice [0.8533] +2024-11-22 04:47:43.044166: Epoch time: 17.18 s +2024-11-22 04:47:43.913291: +2024-11-22 04:47:43.913576: Epoch 3373 +2024-11-22 04:47:43.913687: Current learning rate: 0.00611 +2024-11-22 04:48:02.653055: train_loss -0.7722 +2024-11-22 04:48:02.655493: val_loss -0.7774 +2024-11-22 04:48:02.655589: Pseudo dice [0.8437] +2024-11-22 04:48:02.655678: Epoch time: 18.74 s +2024-11-22 04:48:03.563760: +2024-11-22 04:48:03.563954: Epoch 3374 +2024-11-22 04:48:03.564069: Current learning rate: 0.00611 +2024-11-22 04:48:22.282470: train_loss -0.7929 +2024-11-22 04:48:22.282662: val_loss -0.768 +2024-11-22 04:48:22.282734: Pseudo dice [0.8358] +2024-11-22 04:48:22.282807: Epoch time: 18.72 s +2024-11-22 04:48:23.565466: +2024-11-22 04:48:23.565722: Epoch 3375 +2024-11-22 04:48:23.565840: Current learning rate: 0.00611 +2024-11-22 04:48:42.452890: train_loss -0.7645 +2024-11-22 04:48:42.453139: val_loss -0.7585 +2024-11-22 04:48:42.453235: Pseudo dice [0.8455] +2024-11-22 04:48:42.453311: Epoch time: 18.89 s +2024-11-22 04:48:43.322186: +2024-11-22 04:48:43.322471: Epoch 3376 +2024-11-22 04:48:43.322580: Current learning rate: 0.00611 +2024-11-22 04:49:02.850551: train_loss -0.7395 +2024-11-22 04:49:02.850877: val_loss -0.788 +2024-11-22 04:49:02.850961: Pseudo dice [0.8419] +2024-11-22 04:49:02.851052: Epoch time: 19.53 s +2024-11-22 04:49:03.742390: +2024-11-22 04:49:03.742631: Epoch 3377 +2024-11-22 04:49:03.742748: Current learning rate: 0.0061 +2024-11-22 04:49:22.180820: train_loss -0.7532 +2024-11-22 04:49:22.181083: val_loss -0.7693 +2024-11-22 04:49:22.181165: Pseudo dice [0.8353] +2024-11-22 04:49:22.181241: Epoch time: 18.44 s +2024-11-22 04:49:23.060244: +2024-11-22 04:49:23.060465: Epoch 3378 +2024-11-22 04:49:23.060574: Current learning rate: 0.0061 +2024-11-22 04:49:41.574897: train_loss -0.7572 +2024-11-22 04:49:41.575127: val_loss -0.7586 +2024-11-22 04:49:41.575205: Pseudo dice [0.851] +2024-11-22 04:49:41.575282: Epoch time: 18.52 s +2024-11-22 04:49:42.470339: +2024-11-22 04:49:42.470569: Epoch 3379 +2024-11-22 04:49:42.470680: Current learning rate: 0.0061 +2024-11-22 04:50:01.924052: train_loss -0.7623 +2024-11-22 04:50:01.924301: val_loss -0.7698 +2024-11-22 04:50:01.924379: Pseudo dice [0.8412] +2024-11-22 04:50:01.924455: Epoch time: 19.45 s +2024-11-22 04:50:02.844924: +2024-11-22 04:50:02.845150: Epoch 3380 +2024-11-22 04:50:02.845259: Current learning rate: 0.0061 +2024-11-22 04:50:21.905920: train_loss -0.7816 +2024-11-22 04:50:21.906140: val_loss -0.7699 +2024-11-22 04:50:21.906240: Pseudo dice [0.8383] +2024-11-22 04:50:21.906322: Epoch time: 19.06 s +2024-11-22 04:50:22.778133: +2024-11-22 04:50:22.778343: Epoch 3381 +2024-11-22 04:50:22.778453: Current learning rate: 0.0061 +2024-11-22 04:50:40.246288: train_loss -0.7834 +2024-11-22 04:50:40.246532: val_loss -0.7512 +2024-11-22 04:50:40.246609: Pseudo dice [0.8485] +2024-11-22 04:50:40.246690: Epoch time: 17.47 s +2024-11-22 04:50:41.111645: +2024-11-22 04:50:41.111865: Epoch 3382 +2024-11-22 04:50:41.111976: Current learning rate: 0.0061 +2024-11-22 04:51:00.545135: train_loss -0.7848 +2024-11-22 04:51:00.545345: val_loss -0.7568 +2024-11-22 04:51:00.545417: Pseudo dice [0.8467] +2024-11-22 04:51:00.545513: Epoch time: 19.43 s +2024-11-22 04:51:01.411397: +2024-11-22 04:51:01.411598: Epoch 3383 +2024-11-22 04:51:01.411708: Current learning rate: 0.0061 +2024-11-22 04:51:20.146327: train_loss -0.7761 +2024-11-22 04:51:20.146539: val_loss -0.7593 +2024-11-22 04:51:20.146613: Pseudo dice [0.8442] +2024-11-22 04:51:20.146688: Epoch time: 18.74 s +2024-11-22 04:51:21.021751: +2024-11-22 04:51:21.021979: Epoch 3384 +2024-11-22 04:51:21.022098: Current learning rate: 0.0061 +2024-11-22 04:51:40.209110: train_loss -0.7759 +2024-11-22 04:51:40.211495: val_loss -0.7575 +2024-11-22 04:51:40.211572: Pseudo dice [0.8492] +2024-11-22 04:51:40.211652: Epoch time: 19.19 s +2024-11-22 04:51:41.108859: +2024-11-22 04:51:41.109079: Epoch 3385 +2024-11-22 04:51:41.109190: Current learning rate: 0.00609 +2024-11-22 04:51:59.461702: train_loss -0.7836 +2024-11-22 04:51:59.461915: val_loss -0.7685 +2024-11-22 04:51:59.461987: Pseudo dice [0.8266] +2024-11-22 04:51:59.462070: Epoch time: 18.35 s +2024-11-22 04:52:00.817410: +2024-11-22 04:52:00.817679: Epoch 3386 +2024-11-22 04:52:00.817788: Current learning rate: 0.00609 +2024-11-22 04:52:18.963271: train_loss -0.7683 +2024-11-22 04:52:18.963492: val_loss -0.781 +2024-11-22 04:52:18.963569: Pseudo dice [0.8535] +2024-11-22 04:52:18.963645: Epoch time: 18.15 s +2024-11-22 04:52:19.870373: +2024-11-22 04:52:19.870609: Epoch 3387 +2024-11-22 04:52:19.870724: Current learning rate: 0.00609 +2024-11-22 04:52:37.063172: train_loss -0.7824 +2024-11-22 04:52:37.065582: val_loss -0.7544 +2024-11-22 04:52:37.065676: Pseudo dice [0.839] +2024-11-22 04:52:37.065763: Epoch time: 17.19 s +2024-11-22 04:52:37.990640: +2024-11-22 04:52:37.990859: Epoch 3388 +2024-11-22 04:52:37.990970: Current learning rate: 0.00609 +2024-11-22 04:52:56.513075: train_loss -0.7715 +2024-11-22 04:52:56.513295: val_loss -0.7602 +2024-11-22 04:52:56.513368: Pseudo dice [0.8456] +2024-11-22 04:52:56.513442: Epoch time: 18.52 s +2024-11-22 04:52:57.390629: +2024-11-22 04:52:57.390836: Epoch 3389 +2024-11-22 04:52:57.390949: Current learning rate: 0.00609 +2024-11-22 04:53:15.709144: train_loss -0.7829 +2024-11-22 04:53:15.709359: val_loss -0.7749 +2024-11-22 04:53:15.709433: Pseudo dice [0.8316] +2024-11-22 04:53:15.711704: Epoch time: 18.32 s +2024-11-22 04:53:16.602462: +2024-11-22 04:53:16.602670: Epoch 3390 +2024-11-22 04:53:16.602777: Current learning rate: 0.00609 +2024-11-22 04:53:35.882797: train_loss -0.7801 +2024-11-22 04:53:35.883019: val_loss -0.77 +2024-11-22 04:53:35.883099: Pseudo dice [0.8393] +2024-11-22 04:53:35.883177: Epoch time: 19.28 s +2024-11-22 04:53:36.756098: +2024-11-22 04:53:36.756321: Epoch 3391 +2024-11-22 04:53:36.756431: Current learning rate: 0.00609 +2024-11-22 04:53:54.826800: train_loss -0.7833 +2024-11-22 04:53:54.827048: val_loss -0.7756 +2024-11-22 04:53:54.827129: Pseudo dice [0.8603] +2024-11-22 04:53:54.827215: Epoch time: 18.07 s +2024-11-22 04:53:55.710101: +2024-11-22 04:53:55.710339: Epoch 3392 +2024-11-22 04:53:55.710448: Current learning rate: 0.00609 +2024-11-22 04:54:14.974552: train_loss -0.7736 +2024-11-22 04:54:14.980999: val_loss -0.7835 +2024-11-22 04:54:14.981162: Pseudo dice [0.8527] +2024-11-22 04:54:14.981246: Epoch time: 19.27 s +2024-11-22 04:54:16.059464: +2024-11-22 04:54:16.059707: Epoch 3393 +2024-11-22 04:54:16.059816: Current learning rate: 0.00609 +2024-11-22 04:54:34.708514: train_loss -0.7851 +2024-11-22 04:54:34.708746: val_loss -0.7731 +2024-11-22 04:54:34.708825: Pseudo dice [0.8515] +2024-11-22 04:54:34.708904: Epoch time: 18.65 s +2024-11-22 04:54:35.628615: +2024-11-22 04:54:35.628827: Epoch 3394 +2024-11-22 04:54:35.628937: Current learning rate: 0.00608 +2024-11-22 04:54:54.229462: train_loss -0.7832 +2024-11-22 04:54:54.229697: val_loss -0.7813 +2024-11-22 04:54:54.229778: Pseudo dice [0.8501] +2024-11-22 04:54:54.229858: Epoch time: 18.6 s +2024-11-22 04:54:55.108882: +2024-11-22 04:54:55.109082: Epoch 3395 +2024-11-22 04:54:55.109195: Current learning rate: 0.00608 +2024-11-22 04:55:13.987284: train_loss -0.7865 +2024-11-22 04:55:13.987567: val_loss -0.7526 +2024-11-22 04:55:13.987650: Pseudo dice [0.8336] +2024-11-22 04:55:13.987734: Epoch time: 18.88 s +2024-11-22 04:55:14.869514: +2024-11-22 04:55:14.869816: Epoch 3396 +2024-11-22 04:55:14.869930: Current learning rate: 0.00608 +2024-11-22 04:55:34.297442: train_loss -0.7824 +2024-11-22 04:55:34.297660: val_loss -0.7503 +2024-11-22 04:55:34.297740: Pseudo dice [0.8412] +2024-11-22 04:55:34.297814: Epoch time: 19.43 s +2024-11-22 04:55:35.551170: +2024-11-22 04:55:35.551608: Epoch 3397 +2024-11-22 04:55:35.551747: Current learning rate: 0.00608 +2024-11-22 04:55:53.723403: train_loss -0.7744 +2024-11-22 04:55:53.723626: val_loss -0.7726 +2024-11-22 04:55:53.723704: Pseudo dice [0.8438] +2024-11-22 04:55:53.723784: Epoch time: 18.17 s +2024-11-22 04:55:54.754488: +2024-11-22 04:55:54.755028: Epoch 3398 +2024-11-22 04:55:54.755167: Current learning rate: 0.00608 +2024-11-22 04:56:13.704443: train_loss -0.7789 +2024-11-22 04:56:13.704663: val_loss -0.77 +2024-11-22 04:56:13.704737: Pseudo dice [0.8346] +2024-11-22 04:56:13.704814: Epoch time: 18.95 s +2024-11-22 04:56:14.581498: +2024-11-22 04:56:14.581936: Epoch 3399 +2024-11-22 04:56:14.582078: Current learning rate: 0.00608 +2024-11-22 04:56:32.898666: train_loss -0.7878 +2024-11-22 04:56:32.898884: val_loss -0.7766 +2024-11-22 04:56:32.898958: Pseudo dice [0.8438] +2024-11-22 04:56:32.899040: Epoch time: 18.32 s +2024-11-22 04:56:34.181524: +2024-11-22 04:56:34.181964: Epoch 3400 +2024-11-22 04:56:34.182101: Current learning rate: 0.00608 +2024-11-22 04:56:53.033752: train_loss -0.7808 +2024-11-22 04:56:53.033962: val_loss -0.7697 +2024-11-22 04:56:53.034152: Pseudo dice [0.8553] +2024-11-22 04:56:53.034232: Epoch time: 18.85 s +2024-11-22 04:56:53.910260: +2024-11-22 04:56:53.910768: Epoch 3401 +2024-11-22 04:56:53.910904: Current learning rate: 0.00608 +2024-11-22 04:57:11.493729: train_loss -0.7829 +2024-11-22 04:57:11.493980: val_loss -0.7345 +2024-11-22 04:57:11.494064: Pseudo dice [0.8245] +2024-11-22 04:57:11.496056: Epoch time: 17.58 s +2024-11-22 04:57:12.524919: +2024-11-22 04:57:12.525349: Epoch 3402 +2024-11-22 04:57:12.525492: Current learning rate: 0.00607 +2024-11-22 04:57:30.704200: train_loss -0.769 +2024-11-22 04:57:30.704409: val_loss -0.7613 +2024-11-22 04:57:30.704904: Pseudo dice [0.8291] +2024-11-22 04:57:30.705025: Epoch time: 18.18 s +2024-11-22 04:57:31.583796: +2024-11-22 04:57:31.584283: Epoch 3403 +2024-11-22 04:57:31.584416: Current learning rate: 0.00607 +2024-11-22 04:57:49.771748: train_loss -0.7855 +2024-11-22 04:57:49.777164: val_loss -0.7591 +2024-11-22 04:57:49.777255: Pseudo dice [0.8484] +2024-11-22 04:57:49.777336: Epoch time: 18.19 s +2024-11-22 04:57:50.687017: +2024-11-22 04:57:50.687425: Epoch 3404 +2024-11-22 04:57:50.687556: Current learning rate: 0.00607 +2024-11-22 04:58:09.924080: train_loss -0.7859 +2024-11-22 04:58:09.924311: val_loss -0.784 +2024-11-22 04:58:09.924445: Pseudo dice [0.8546] +2024-11-22 04:58:09.924520: Epoch time: 19.24 s +2024-11-22 04:58:10.792396: +2024-11-22 04:58:10.792816: Epoch 3405 +2024-11-22 04:58:10.792958: Current learning rate: 0.00607 +2024-11-22 04:58:30.466936: train_loss -0.7837 +2024-11-22 04:58:30.467201: val_loss -0.7738 +2024-11-22 04:58:30.467279: Pseudo dice [0.8481] +2024-11-22 04:58:30.467365: Epoch time: 19.68 s +2024-11-22 04:58:31.454653: +2024-11-22 04:58:31.454895: Epoch 3406 +2024-11-22 04:58:31.455016: Current learning rate: 0.00607 +2024-11-22 04:58:49.139216: train_loss -0.7866 +2024-11-22 04:58:49.139435: val_loss -0.7771 +2024-11-22 04:58:49.139509: Pseudo dice [0.8562] +2024-11-22 04:58:49.139588: Epoch time: 17.69 s +2024-11-22 04:58:50.014165: +2024-11-22 04:58:50.014441: Epoch 3407 +2024-11-22 04:58:50.014552: Current learning rate: 0.00607 +2024-11-22 04:59:08.447095: train_loss -0.787 +2024-11-22 04:59:08.447312: val_loss -0.7655 +2024-11-22 04:59:08.447387: Pseudo dice [0.8512] +2024-11-22 04:59:08.447461: Epoch time: 18.43 s +2024-11-22 04:59:09.722146: +2024-11-22 04:59:09.722373: Epoch 3408 +2024-11-22 04:59:09.722492: Current learning rate: 0.00607 +2024-11-22 04:59:29.258246: train_loss -0.7797 +2024-11-22 04:59:29.258567: val_loss -0.7685 +2024-11-22 04:59:29.258653: Pseudo dice [0.8407] +2024-11-22 04:59:29.258738: Epoch time: 19.54 s +2024-11-22 04:59:30.130744: +2024-11-22 04:59:30.130948: Epoch 3409 +2024-11-22 04:59:30.131065: Current learning rate: 0.00607 +2024-11-22 04:59:49.305508: train_loss -0.7803 +2024-11-22 04:59:49.305724: val_loss -0.7584 +2024-11-22 04:59:49.305798: Pseudo dice [0.8567] +2024-11-22 04:59:49.305872: Epoch time: 19.18 s +2024-11-22 04:59:50.171672: +2024-11-22 04:59:50.171890: Epoch 3410 +2024-11-22 04:59:50.172009: Current learning rate: 0.00607 +2024-11-22 05:00:08.304523: train_loss -0.7855 +2024-11-22 05:00:08.304732: val_loss -0.7841 +2024-11-22 05:00:08.304804: Pseudo dice [0.8552] +2024-11-22 05:00:08.304875: Epoch time: 18.13 s +2024-11-22 05:00:09.185286: +2024-11-22 05:00:09.185485: Epoch 3411 +2024-11-22 05:00:09.185600: Current learning rate: 0.00606 +2024-11-22 05:00:27.068450: train_loss -0.7913 +2024-11-22 05:00:27.068682: val_loss -0.7594 +2024-11-22 05:00:27.068763: Pseudo dice [0.8521] +2024-11-22 05:00:27.068847: Epoch time: 17.88 s +2024-11-22 05:00:27.949701: +2024-11-22 05:00:27.949922: Epoch 3412 +2024-11-22 05:00:27.950035: Current learning rate: 0.00606 +2024-11-22 05:00:47.164029: train_loss -0.7822 +2024-11-22 05:00:47.164299: val_loss -0.7598 +2024-11-22 05:00:47.164379: Pseudo dice [0.8505] +2024-11-22 05:00:47.164466: Epoch time: 19.22 s +2024-11-22 05:00:48.034962: +2024-11-22 05:00:48.035190: Epoch 3413 +2024-11-22 05:00:48.035304: Current learning rate: 0.00606 +2024-11-22 05:01:06.284920: train_loss -0.7832 +2024-11-22 05:01:06.285140: val_loss -0.7455 +2024-11-22 05:01:06.285214: Pseudo dice [0.8471] +2024-11-22 05:01:06.285286: Epoch time: 18.25 s +2024-11-22 05:01:07.320741: +2024-11-22 05:01:07.320978: Epoch 3414 +2024-11-22 05:01:07.321102: Current learning rate: 0.00606 +2024-11-22 05:01:25.955105: train_loss -0.7642 +2024-11-22 05:01:25.955333: val_loss -0.7636 +2024-11-22 05:01:25.955431: Pseudo dice [0.8388] +2024-11-22 05:01:25.955509: Epoch time: 18.64 s +2024-11-22 05:01:26.833314: +2024-11-22 05:01:26.833528: Epoch 3415 +2024-11-22 05:01:26.833639: Current learning rate: 0.00606 +2024-11-22 05:01:46.090059: train_loss -0.7621 +2024-11-22 05:01:46.090284: val_loss -0.7653 +2024-11-22 05:01:46.090359: Pseudo dice [0.8422] +2024-11-22 05:01:46.090439: Epoch time: 19.26 s +2024-11-22 05:01:46.967605: +2024-11-22 05:01:46.967825: Epoch 3416 +2024-11-22 05:01:46.967931: Current learning rate: 0.00606 +2024-11-22 05:02:06.100537: train_loss -0.7755 +2024-11-22 05:02:06.100785: val_loss -0.7461 +2024-11-22 05:02:06.100859: Pseudo dice [0.8453] +2024-11-22 05:02:06.100936: Epoch time: 19.13 s +2024-11-22 05:02:06.973690: +2024-11-22 05:02:06.973893: Epoch 3417 +2024-11-22 05:02:06.974011: Current learning rate: 0.00606 +2024-11-22 05:02:25.928634: train_loss -0.784 +2024-11-22 05:02:25.928860: val_loss -0.7608 +2024-11-22 05:02:25.928937: Pseudo dice [0.8236] +2024-11-22 05:02:25.929070: Epoch time: 18.96 s +2024-11-22 05:02:26.805663: +2024-11-22 05:02:26.805862: Epoch 3418 +2024-11-22 05:02:26.805971: Current learning rate: 0.00606 +2024-11-22 05:02:45.879839: train_loss -0.7815 +2024-11-22 05:02:45.880060: val_loss -0.7646 +2024-11-22 05:02:45.880133: Pseudo dice [0.8298] +2024-11-22 05:02:45.880207: Epoch time: 19.07 s +2024-11-22 05:02:47.193604: +2024-11-22 05:02:47.193881: Epoch 3419 +2024-11-22 05:02:47.194000: Current learning rate: 0.00605 +2024-11-22 05:03:05.763372: train_loss -0.7725 +2024-11-22 05:03:05.763638: val_loss -0.7625 +2024-11-22 05:03:05.763717: Pseudo dice [0.8421] +2024-11-22 05:03:05.763797: Epoch time: 18.57 s +2024-11-22 05:03:06.636494: +2024-11-22 05:03:06.636735: Epoch 3420 +2024-11-22 05:03:06.636846: Current learning rate: 0.00605 +2024-11-22 05:03:25.011053: train_loss -0.7854 +2024-11-22 05:03:25.011264: val_loss -0.7606 +2024-11-22 05:03:25.011377: Pseudo dice [0.8441] +2024-11-22 05:03:25.011454: Epoch time: 18.38 s +2024-11-22 05:03:25.883082: +2024-11-22 05:03:25.883322: Epoch 3421 +2024-11-22 05:03:25.883465: Current learning rate: 0.00605 +2024-11-22 05:03:44.050698: train_loss -0.7887 +2024-11-22 05:03:44.050924: val_loss -0.7644 +2024-11-22 05:03:44.051009: Pseudo dice [0.8446] +2024-11-22 05:03:44.051088: Epoch time: 18.17 s +2024-11-22 05:03:44.926824: +2024-11-22 05:03:44.927041: Epoch 3422 +2024-11-22 05:03:44.927153: Current learning rate: 0.00605 +2024-11-22 05:04:03.399298: train_loss -0.7881 +2024-11-22 05:04:03.399608: val_loss -0.7463 +2024-11-22 05:04:03.399685: Pseudo dice [0.8514] +2024-11-22 05:04:03.399768: Epoch time: 18.47 s +2024-11-22 05:04:04.279968: +2024-11-22 05:04:04.280215: Epoch 3423 +2024-11-22 05:04:04.280329: Current learning rate: 0.00605 +2024-11-22 05:04:21.805773: train_loss -0.7786 +2024-11-22 05:04:21.806027: val_loss -0.7673 +2024-11-22 05:04:21.806105: Pseudo dice [0.8353] +2024-11-22 05:04:21.806181: Epoch time: 17.53 s +2024-11-22 05:04:22.681745: +2024-11-22 05:04:22.681965: Epoch 3424 +2024-11-22 05:04:22.682087: Current learning rate: 0.00605 +2024-11-22 05:04:41.205162: train_loss -0.7844 +2024-11-22 05:04:41.205388: val_loss -0.7645 +2024-11-22 05:04:41.205465: Pseudo dice [0.8378] +2024-11-22 05:04:41.205537: Epoch time: 18.52 s +2024-11-22 05:04:42.198633: +2024-11-22 05:04:42.198891: Epoch 3425 +2024-11-22 05:04:42.199011: Current learning rate: 0.00605 +2024-11-22 05:05:00.382841: train_loss -0.7839 +2024-11-22 05:05:00.383073: val_loss -0.7703 +2024-11-22 05:05:00.383155: Pseudo dice [0.8333] +2024-11-22 05:05:00.383234: Epoch time: 18.19 s +2024-11-22 05:05:01.330818: +2024-11-22 05:05:01.331056: Epoch 3426 +2024-11-22 05:05:01.331170: Current learning rate: 0.00605 +2024-11-22 05:05:19.608805: train_loss -0.78 +2024-11-22 05:05:19.609063: val_loss -0.7689 +2024-11-22 05:05:19.609140: Pseudo dice [0.8383] +2024-11-22 05:05:19.609221: Epoch time: 18.28 s +2024-11-22 05:05:20.478577: +2024-11-22 05:05:20.478862: Epoch 3427 +2024-11-22 05:05:20.478973: Current learning rate: 0.00605 +2024-11-22 05:05:38.191422: train_loss -0.7821 +2024-11-22 05:05:38.191644: val_loss -0.7815 +2024-11-22 05:05:38.191720: Pseudo dice [0.8569] +2024-11-22 05:05:38.191802: Epoch time: 17.71 s +2024-11-22 05:05:39.062257: +2024-11-22 05:05:39.105957: Epoch 3428 +2024-11-22 05:05:39.106102: Current learning rate: 0.00604 +2024-11-22 05:05:58.111164: train_loss -0.7807 +2024-11-22 05:05:58.111446: val_loss -0.7867 +2024-11-22 05:05:58.111521: Pseudo dice [0.8569] +2024-11-22 05:05:58.111595: Epoch time: 19.05 s +2024-11-22 05:05:58.990550: +2024-11-22 05:05:58.990765: Epoch 3429 +2024-11-22 05:05:58.990880: Current learning rate: 0.00604 +2024-11-22 05:06:17.269750: train_loss -0.7857 +2024-11-22 05:06:17.270009: val_loss -0.7618 +2024-11-22 05:06:17.270088: Pseudo dice [0.8586] +2024-11-22 05:06:17.270179: Epoch time: 18.28 s +2024-11-22 05:06:18.533961: +2024-11-22 05:06:18.534184: Epoch 3430 +2024-11-22 05:06:18.534293: Current learning rate: 0.00604 +2024-11-22 05:06:37.783146: train_loss -0.7775 +2024-11-22 05:06:37.783364: val_loss -0.762 +2024-11-22 05:06:37.783438: Pseudo dice [0.8409] +2024-11-22 05:06:37.783513: Epoch time: 19.25 s +2024-11-22 05:06:38.651731: +2024-11-22 05:06:38.651961: Epoch 3431 +2024-11-22 05:06:38.652087: Current learning rate: 0.00604 +2024-11-22 05:06:57.797256: train_loss -0.7797 +2024-11-22 05:06:57.797486: val_loss -0.7598 +2024-11-22 05:06:57.797559: Pseudo dice [0.8426] +2024-11-22 05:06:57.803016: Epoch time: 19.15 s +2024-11-22 05:06:58.784884: +2024-11-22 05:06:58.785099: Epoch 3432 +2024-11-22 05:06:58.785207: Current learning rate: 0.00604 +2024-11-22 05:07:16.755898: train_loss -0.7842 +2024-11-22 05:07:16.756151: val_loss -0.7527 +2024-11-22 05:07:16.756230: Pseudo dice [0.8339] +2024-11-22 05:07:16.756317: Epoch time: 17.97 s +2024-11-22 05:07:17.630492: +2024-11-22 05:07:17.630706: Epoch 3433 +2024-11-22 05:07:17.630818: Current learning rate: 0.00604 +2024-11-22 05:07:36.776195: train_loss -0.7812 +2024-11-22 05:07:36.776406: val_loss -0.7447 +2024-11-22 05:07:36.776482: Pseudo dice [0.8373] +2024-11-22 05:07:36.776554: Epoch time: 19.15 s +2024-11-22 05:07:37.646621: +2024-11-22 05:07:37.646835: Epoch 3434 +2024-11-22 05:07:37.646950: Current learning rate: 0.00604 +2024-11-22 05:07:56.090590: train_loss -0.7883 +2024-11-22 05:07:56.102221: val_loss -0.744 +2024-11-22 05:07:56.102378: Pseudo dice [0.8395] +2024-11-22 05:07:56.102458: Epoch time: 18.44 s +2024-11-22 05:07:57.003201: +2024-11-22 05:07:57.003432: Epoch 3435 +2024-11-22 05:07:57.003544: Current learning rate: 0.00604 +2024-11-22 05:08:16.213959: train_loss -0.7847 +2024-11-22 05:08:16.214199: val_loss -0.7491 +2024-11-22 05:08:16.214279: Pseudo dice [0.8449] +2024-11-22 05:08:16.214355: Epoch time: 19.21 s +2024-11-22 05:08:17.092620: +2024-11-22 05:08:17.092838: Epoch 3436 +2024-11-22 05:08:17.092947: Current learning rate: 0.00603 +2024-11-22 05:08:35.256387: train_loss -0.7783 +2024-11-22 05:08:35.258774: val_loss -0.7764 +2024-11-22 05:08:35.258863: Pseudo dice [0.8497] +2024-11-22 05:08:35.258947: Epoch time: 18.16 s +2024-11-22 05:08:36.268442: +2024-11-22 05:08:36.268659: Epoch 3437 +2024-11-22 05:08:36.268767: Current learning rate: 0.00603 +2024-11-22 05:08:55.763298: train_loss -0.7835 +2024-11-22 05:08:55.763540: val_loss -0.7632 +2024-11-22 05:08:55.763620: Pseudo dice [0.8439] +2024-11-22 05:08:55.763704: Epoch time: 19.5 s +2024-11-22 05:08:56.757493: +2024-11-22 05:08:56.757708: Epoch 3438 +2024-11-22 05:08:56.757815: Current learning rate: 0.00603 +2024-11-22 05:09:15.738695: train_loss -0.7678 +2024-11-22 05:09:15.738921: val_loss -0.7811 +2024-11-22 05:09:15.739003: Pseudo dice [0.8491] +2024-11-22 05:09:15.739080: Epoch time: 18.98 s +2024-11-22 05:09:16.608952: +2024-11-22 05:09:16.609188: Epoch 3439 +2024-11-22 05:09:16.609298: Current learning rate: 0.00603 +2024-11-22 05:09:35.376702: train_loss -0.7746 +2024-11-22 05:09:35.376963: val_loss -0.7779 +2024-11-22 05:09:35.377072: Pseudo dice [0.8523] +2024-11-22 05:09:35.377173: Epoch time: 18.77 s +2024-11-22 05:09:36.250245: +2024-11-22 05:09:36.250479: Epoch 3440 +2024-11-22 05:09:36.250590: Current learning rate: 0.00603 +2024-11-22 05:09:54.479071: train_loss -0.7776 +2024-11-22 05:09:54.479335: val_loss -0.7597 +2024-11-22 05:09:54.479431: Pseudo dice [0.8481] +2024-11-22 05:09:54.479523: Epoch time: 18.23 s +2024-11-22 05:09:55.768186: +2024-11-22 05:09:55.768400: Epoch 3441 +2024-11-22 05:09:55.768508: Current learning rate: 0.00603 +2024-11-22 05:10:15.398378: train_loss -0.7699 +2024-11-22 05:10:15.398602: val_loss -0.7813 +2024-11-22 05:10:15.398678: Pseudo dice [0.8487] +2024-11-22 05:10:15.398752: Epoch time: 19.63 s +2024-11-22 05:10:16.267410: +2024-11-22 05:10:16.267647: Epoch 3442 +2024-11-22 05:10:16.267756: Current learning rate: 0.00603 +2024-11-22 05:10:34.760412: train_loss -0.7533 +2024-11-22 05:10:34.760625: val_loss -0.7244 +2024-11-22 05:10:34.760701: Pseudo dice [0.7939] +2024-11-22 05:10:34.760871: Epoch time: 18.49 s +2024-11-22 05:10:35.628577: +2024-11-22 05:10:35.628815: Epoch 3443 +2024-11-22 05:10:35.628925: Current learning rate: 0.00603 +2024-11-22 05:10:53.781477: train_loss -0.7627 +2024-11-22 05:10:53.781736: val_loss -0.7661 +2024-11-22 05:10:53.781816: Pseudo dice [0.8498] +2024-11-22 05:10:53.781901: Epoch time: 18.15 s +2024-11-22 05:10:54.744881: +2024-11-22 05:10:54.745260: Epoch 3444 +2024-11-22 05:10:54.745373: Current learning rate: 0.00602 +2024-11-22 05:11:12.282179: train_loss -0.7675 +2024-11-22 05:11:12.282392: val_loss -0.7697 +2024-11-22 05:11:12.282464: Pseudo dice [0.8416] +2024-11-22 05:11:12.282536: Epoch time: 17.54 s +2024-11-22 05:11:13.156737: +2024-11-22 05:11:13.156951: Epoch 3445 +2024-11-22 05:11:13.157069: Current learning rate: 0.00602 +2024-11-22 05:11:31.819543: train_loss -0.7656 +2024-11-22 05:11:31.819758: val_loss -0.7653 +2024-11-22 05:11:31.819829: Pseudo dice [0.8212] +2024-11-22 05:11:31.819903: Epoch time: 18.66 s +2024-11-22 05:11:32.696274: +2024-11-22 05:11:32.696545: Epoch 3446 +2024-11-22 05:11:32.696658: Current learning rate: 0.00602 +2024-11-22 05:11:50.842404: train_loss -0.7741 +2024-11-22 05:11:50.842694: val_loss -0.7939 +2024-11-22 05:11:50.842773: Pseudo dice [0.8475] +2024-11-22 05:11:50.842849: Epoch time: 18.15 s +2024-11-22 05:11:51.724003: +2024-11-22 05:11:51.724295: Epoch 3447 +2024-11-22 05:11:51.724407: Current learning rate: 0.00602 +2024-11-22 05:12:10.841494: train_loss -0.7852 +2024-11-22 05:12:10.841741: val_loss -0.7872 +2024-11-22 05:12:10.841818: Pseudo dice [0.866] +2024-11-22 05:12:10.841902: Epoch time: 19.12 s +2024-11-22 05:12:11.721393: +2024-11-22 05:12:11.721605: Epoch 3448 +2024-11-22 05:12:11.721714: Current learning rate: 0.00602 +2024-11-22 05:12:30.737729: train_loss -0.7814 +2024-11-22 05:12:30.737947: val_loss -0.7854 +2024-11-22 05:12:30.738046: Pseudo dice [0.8422] +2024-11-22 05:12:30.738127: Epoch time: 19.02 s +2024-11-22 05:12:31.606789: +2024-11-22 05:12:31.607014: Epoch 3449 +2024-11-22 05:12:31.607126: Current learning rate: 0.00602 +2024-11-22 05:12:51.030091: train_loss -0.7776 +2024-11-22 05:12:51.030307: val_loss -0.7595 +2024-11-22 05:12:51.030382: Pseudo dice [0.8351] +2024-11-22 05:12:51.030458: Epoch time: 19.42 s +2024-11-22 05:12:52.151839: +2024-11-22 05:12:52.152165: Epoch 3450 +2024-11-22 05:12:52.152280: Current learning rate: 0.00602 +2024-11-22 05:13:10.366151: train_loss -0.774 +2024-11-22 05:13:10.366356: val_loss -0.7802 +2024-11-22 05:13:10.366432: Pseudo dice [0.8556] +2024-11-22 05:13:10.366504: Epoch time: 18.22 s +2024-11-22 05:13:11.233312: +2024-11-22 05:13:11.233597: Epoch 3451 +2024-11-22 05:13:11.233713: Current learning rate: 0.00602 +2024-11-22 05:13:31.010869: train_loss -0.772 +2024-11-22 05:13:31.011121: val_loss -0.7833 +2024-11-22 05:13:31.011198: Pseudo dice [0.8558] +2024-11-22 05:13:31.011280: Epoch time: 19.78 s +2024-11-22 05:13:32.265060: +2024-11-22 05:13:32.265284: Epoch 3452 +2024-11-22 05:13:32.265391: Current learning rate: 0.00602 +2024-11-22 05:13:50.586042: train_loss -0.7931 +2024-11-22 05:13:50.586272: val_loss -0.7881 +2024-11-22 05:13:50.586345: Pseudo dice [0.8381] +2024-11-22 05:13:50.586416: Epoch time: 18.32 s +2024-11-22 05:13:51.464245: +2024-11-22 05:13:51.464466: Epoch 3453 +2024-11-22 05:13:51.464572: Current learning rate: 0.00601 +2024-11-22 05:14:09.495424: train_loss -0.791 +2024-11-22 05:14:09.495643: val_loss -0.7737 +2024-11-22 05:14:09.495720: Pseudo dice [0.8508] +2024-11-22 05:14:09.495797: Epoch time: 18.03 s +2024-11-22 05:14:10.368697: +2024-11-22 05:14:10.368935: Epoch 3454 +2024-11-22 05:14:10.369052: Current learning rate: 0.00601 +2024-11-22 05:14:28.927038: train_loss -0.7849 +2024-11-22 05:14:28.927291: val_loss -0.7797 +2024-11-22 05:14:28.927369: Pseudo dice [0.8469] +2024-11-22 05:14:28.927450: Epoch time: 18.56 s +2024-11-22 05:14:29.802544: +2024-11-22 05:14:29.802735: Epoch 3455 +2024-11-22 05:14:29.802846: Current learning rate: 0.00601 +2024-11-22 05:14:48.249026: train_loss -0.7765 +2024-11-22 05:14:48.249242: val_loss -0.7656 +2024-11-22 05:14:48.249316: Pseudo dice [0.8375] +2024-11-22 05:14:48.249389: Epoch time: 18.45 s +2024-11-22 05:14:49.162409: +2024-11-22 05:14:49.162645: Epoch 3456 +2024-11-22 05:14:49.162760: Current learning rate: 0.00601 +2024-11-22 05:15:07.242312: train_loss -0.7785 +2024-11-22 05:15:07.242562: val_loss -0.7619 +2024-11-22 05:15:07.242640: Pseudo dice [0.8416] +2024-11-22 05:15:07.242716: Epoch time: 18.08 s +2024-11-22 05:15:08.114718: +2024-11-22 05:15:08.114943: Epoch 3457 +2024-11-22 05:15:08.115060: Current learning rate: 0.00601 +2024-11-22 05:15:25.966267: train_loss -0.7921 +2024-11-22 05:15:25.966496: val_loss -0.755 +2024-11-22 05:15:25.966571: Pseudo dice [0.8455] +2024-11-22 05:15:25.972194: Epoch time: 17.85 s +2024-11-22 05:15:26.879592: +2024-11-22 05:15:26.879819: Epoch 3458 +2024-11-22 05:15:26.879932: Current learning rate: 0.00601 +2024-11-22 05:15:44.277056: train_loss -0.7857 +2024-11-22 05:15:44.277300: val_loss -0.7695 +2024-11-22 05:15:44.277375: Pseudo dice [0.8513] +2024-11-22 05:15:44.277452: Epoch time: 17.4 s +2024-11-22 05:15:45.145358: +2024-11-22 05:15:45.145567: Epoch 3459 +2024-11-22 05:15:45.145678: Current learning rate: 0.00601 +2024-11-22 05:16:04.770526: train_loss -0.7766 +2024-11-22 05:16:04.771317: val_loss -0.7839 +2024-11-22 05:16:04.771398: Pseudo dice [0.8364] +2024-11-22 05:16:04.771472: Epoch time: 19.63 s +2024-11-22 05:16:05.636932: +2024-11-22 05:16:05.637155: Epoch 3460 +2024-11-22 05:16:05.637271: Current learning rate: 0.00601 +2024-11-22 05:16:23.625938: train_loss -0.7804 +2024-11-22 05:16:23.626179: val_loss -0.7565 +2024-11-22 05:16:23.626260: Pseudo dice [0.8442] +2024-11-22 05:16:23.626343: Epoch time: 17.99 s +2024-11-22 05:16:24.506606: +2024-11-22 05:16:24.506813: Epoch 3461 +2024-11-22 05:16:24.506921: Current learning rate: 0.006 +2024-11-22 05:16:43.291526: train_loss -0.7845 +2024-11-22 05:16:43.291781: val_loss -0.7623 +2024-11-22 05:16:43.291925: Pseudo dice [0.8397] +2024-11-22 05:16:43.292025: Epoch time: 18.79 s +2024-11-22 05:16:44.175091: +2024-11-22 05:16:44.175320: Epoch 3462 +2024-11-22 05:16:44.175435: Current learning rate: 0.006 +2024-11-22 05:17:04.136024: train_loss -0.7884 +2024-11-22 05:17:04.136246: val_loss -0.7837 +2024-11-22 05:17:04.136338: Pseudo dice [0.8443] +2024-11-22 05:17:04.136415: Epoch time: 19.96 s +2024-11-22 05:17:05.425851: +2024-11-22 05:17:05.426078: Epoch 3463 +2024-11-22 05:17:05.426186: Current learning rate: 0.006 +2024-11-22 05:17:23.159219: train_loss -0.7919 +2024-11-22 05:17:23.161194: val_loss -0.7877 +2024-11-22 05:17:23.161302: Pseudo dice [0.844] +2024-11-22 05:17:23.161383: Epoch time: 17.73 s +2024-11-22 05:17:24.039272: +2024-11-22 05:17:24.039515: Epoch 3464 +2024-11-22 05:17:24.039639: Current learning rate: 0.006 +2024-11-22 05:17:43.327318: train_loss -0.7873 +2024-11-22 05:17:43.327564: val_loss -0.777 +2024-11-22 05:17:43.327645: Pseudo dice [0.8504] +2024-11-22 05:17:43.327733: Epoch time: 19.29 s +2024-11-22 05:17:44.201369: +2024-11-22 05:17:44.201626: Epoch 3465 +2024-11-22 05:17:44.201738: Current learning rate: 0.006 +2024-11-22 05:18:04.024371: train_loss -0.7772 +2024-11-22 05:18:04.024594: val_loss -0.7576 +2024-11-22 05:18:04.024671: Pseudo dice [0.8508] +2024-11-22 05:18:04.024749: Epoch time: 19.82 s +2024-11-22 05:18:04.900463: +2024-11-22 05:18:04.900854: Epoch 3466 +2024-11-22 05:18:04.900964: Current learning rate: 0.006 +2024-11-22 05:18:23.785339: train_loss -0.7763 +2024-11-22 05:18:23.785555: val_loss -0.786 +2024-11-22 05:18:23.785665: Pseudo dice [0.8503] +2024-11-22 05:18:23.785742: Epoch time: 18.89 s +2024-11-22 05:18:24.660610: +2024-11-22 05:18:24.660825: Epoch 3467 +2024-11-22 05:18:24.660940: Current learning rate: 0.006 +2024-11-22 05:18:43.932841: train_loss -0.7867 +2024-11-22 05:18:43.933069: val_loss -0.7437 +2024-11-22 05:18:43.933142: Pseudo dice [0.8391] +2024-11-22 05:18:43.933217: Epoch time: 19.27 s +2024-11-22 05:18:44.923759: +2024-11-22 05:18:44.924003: Epoch 3468 +2024-11-22 05:18:44.924114: Current learning rate: 0.006 +2024-11-22 05:19:02.350809: train_loss -0.7832 +2024-11-22 05:19:02.351037: val_loss -0.7703 +2024-11-22 05:19:02.351116: Pseudo dice [0.8574] +2024-11-22 05:19:02.351198: Epoch time: 17.43 s +2024-11-22 05:19:03.234722: +2024-11-22 05:19:03.235060: Epoch 3469 +2024-11-22 05:19:03.235174: Current learning rate: 0.006 +2024-11-22 05:19:22.989973: train_loss -0.7805 +2024-11-22 05:19:22.990255: val_loss -0.7608 +2024-11-22 05:19:22.990395: Pseudo dice [0.8508] +2024-11-22 05:19:22.990482: Epoch time: 19.76 s +2024-11-22 05:19:23.864904: +2024-11-22 05:19:23.865137: Epoch 3470 +2024-11-22 05:19:23.865246: Current learning rate: 0.00599 +2024-11-22 05:19:42.832747: train_loss -0.7906 +2024-11-22 05:19:42.832970: val_loss -0.7971 +2024-11-22 05:19:42.833051: Pseudo dice [0.8553] +2024-11-22 05:19:42.833126: Epoch time: 18.97 s +2024-11-22 05:19:43.767267: +2024-11-22 05:19:43.767460: Epoch 3471 +2024-11-22 05:19:43.767571: Current learning rate: 0.00599 +2024-11-22 05:20:03.114952: train_loss -0.7854 +2024-11-22 05:20:03.115265: val_loss -0.7545 +2024-11-22 05:20:03.115343: Pseudo dice [0.8331] +2024-11-22 05:20:03.115417: Epoch time: 19.35 s +2024-11-22 05:20:04.005352: +2024-11-22 05:20:04.005638: Epoch 3472 +2024-11-22 05:20:04.005747: Current learning rate: 0.00599 +2024-11-22 05:20:22.676750: train_loss -0.7875 +2024-11-22 05:20:22.677004: val_loss -0.7854 +2024-11-22 05:20:22.677081: Pseudo dice [0.8458] +2024-11-22 05:20:22.677191: Epoch time: 18.67 s +2024-11-22 05:20:23.555268: +2024-11-22 05:20:23.555471: Epoch 3473 +2024-11-22 05:20:23.555576: Current learning rate: 0.00599 +2024-11-22 05:20:42.294467: train_loss -0.7773 +2024-11-22 05:20:42.294684: val_loss -0.7666 +2024-11-22 05:20:42.294779: Pseudo dice [0.857] +2024-11-22 05:20:42.294874: Epoch time: 18.74 s +2024-11-22 05:20:43.167367: +2024-11-22 05:20:43.167600: Epoch 3474 +2024-11-22 05:20:43.167719: Current learning rate: 0.00599 +2024-11-22 05:21:01.018937: train_loss -0.7903 +2024-11-22 05:21:01.024616: val_loss -0.7351 +2024-11-22 05:21:01.024721: Pseudo dice [0.8455] +2024-11-22 05:21:01.024802: Epoch time: 17.85 s +2024-11-22 05:21:02.020119: +2024-11-22 05:21:02.020344: Epoch 3475 +2024-11-22 05:21:02.020455: Current learning rate: 0.00599 +2024-11-22 05:21:20.514906: train_loss -0.775 +2024-11-22 05:21:20.515161: val_loss -0.7616 +2024-11-22 05:21:20.515241: Pseudo dice [0.84] +2024-11-22 05:21:20.515325: Epoch time: 18.5 s +2024-11-22 05:21:21.387674: +2024-11-22 05:21:21.387892: Epoch 3476 +2024-11-22 05:21:21.388005: Current learning rate: 0.00599 +2024-11-22 05:21:39.546786: train_loss -0.7857 +2024-11-22 05:21:39.547008: val_loss -0.7513 +2024-11-22 05:21:39.547095: Pseudo dice [0.8337] +2024-11-22 05:21:39.547173: Epoch time: 18.16 s +2024-11-22 05:21:40.413586: +2024-11-22 05:21:40.413826: Epoch 3477 +2024-11-22 05:21:40.413938: Current learning rate: 0.00599 +2024-11-22 05:21:59.210571: train_loss -0.7357 +2024-11-22 05:21:59.210825: val_loss -0.7306 +2024-11-22 05:21:59.210913: Pseudo dice [0.8175] +2024-11-22 05:21:59.210999: Epoch time: 18.8 s +2024-11-22 05:22:00.085267: +2024-11-22 05:22:00.085486: Epoch 3478 +2024-11-22 05:22:00.085597: Current learning rate: 0.00598 +2024-11-22 05:22:19.312153: train_loss -0.7474 +2024-11-22 05:22:19.312471: val_loss -0.7615 +2024-11-22 05:22:19.312556: Pseudo dice [0.8316] +2024-11-22 05:22:19.312644: Epoch time: 19.23 s +2024-11-22 05:22:20.312694: +2024-11-22 05:22:20.312917: Epoch 3479 +2024-11-22 05:22:20.313032: Current learning rate: 0.00598 +2024-11-22 05:22:39.760170: train_loss -0.7645 +2024-11-22 05:22:39.762641: val_loss -0.7515 +2024-11-22 05:22:39.762743: Pseudo dice [0.8302] +2024-11-22 05:22:39.762824: Epoch time: 19.45 s +2024-11-22 05:22:40.661714: +2024-11-22 05:22:40.662017: Epoch 3480 +2024-11-22 05:22:40.662136: Current learning rate: 0.00598 +2024-11-22 05:22:59.372900: train_loss -0.7854 +2024-11-22 05:22:59.375152: val_loss -0.7766 +2024-11-22 05:22:59.375244: Pseudo dice [0.8412] +2024-11-22 05:22:59.375322: Epoch time: 18.71 s +2024-11-22 05:23:00.369014: +2024-11-22 05:23:00.369232: Epoch 3481 +2024-11-22 05:23:00.369340: Current learning rate: 0.00598 +2024-11-22 05:23:18.557153: train_loss -0.782 +2024-11-22 05:23:18.557371: val_loss -0.7682 +2024-11-22 05:23:18.557447: Pseudo dice [0.8323] +2024-11-22 05:23:18.557525: Epoch time: 18.19 s +2024-11-22 05:23:19.427905: +2024-11-22 05:23:19.428118: Epoch 3482 +2024-11-22 05:23:19.428243: Current learning rate: 0.00598 +2024-11-22 05:23:37.509129: train_loss -0.7793 +2024-11-22 05:23:37.509364: val_loss -0.7736 +2024-11-22 05:23:37.509441: Pseudo dice [0.8635] +2024-11-22 05:23:37.509532: Epoch time: 18.08 s +2024-11-22 05:23:38.384148: +2024-11-22 05:23:38.384382: Epoch 3483 +2024-11-22 05:23:38.384495: Current learning rate: 0.00598 +2024-11-22 05:23:57.272083: train_loss -0.7883 +2024-11-22 05:23:57.272391: val_loss -0.7615 +2024-11-22 05:23:57.272470: Pseudo dice [0.8351] +2024-11-22 05:23:57.272794: Epoch time: 18.89 s +2024-11-22 05:23:58.149293: +2024-11-22 05:23:58.149509: Epoch 3484 +2024-11-22 05:23:58.149627: Current learning rate: 0.00598 +2024-11-22 05:24:16.774849: train_loss -0.7812 +2024-11-22 05:24:16.775081: val_loss -0.7959 +2024-11-22 05:24:16.775157: Pseudo dice [0.841] +2024-11-22 05:24:16.775234: Epoch time: 18.63 s +2024-11-22 05:24:18.021455: +2024-11-22 05:24:18.021683: Epoch 3485 +2024-11-22 05:24:18.021797: Current learning rate: 0.00598 +2024-11-22 05:24:37.306932: train_loss -0.7798 +2024-11-22 05:24:37.307169: val_loss -0.7461 +2024-11-22 05:24:37.307244: Pseudo dice [0.8206] +2024-11-22 05:24:37.307322: Epoch time: 19.29 s +2024-11-22 05:24:38.224156: +2024-11-22 05:24:38.224417: Epoch 3486 +2024-11-22 05:24:38.224531: Current learning rate: 0.00597 +2024-11-22 05:24:57.051249: train_loss -0.7776 +2024-11-22 05:24:57.056699: val_loss -0.7692 +2024-11-22 05:24:57.056818: Pseudo dice [0.8444] +2024-11-22 05:24:57.056903: Epoch time: 18.83 s +2024-11-22 05:24:57.948202: +2024-11-22 05:24:57.948420: Epoch 3487 +2024-11-22 05:24:57.948528: Current learning rate: 0.00597 +2024-11-22 05:25:16.365806: train_loss -0.785 +2024-11-22 05:25:16.368205: val_loss -0.7693 +2024-11-22 05:25:16.368294: Pseudo dice [0.8343] +2024-11-22 05:25:16.368374: Epoch time: 18.42 s +2024-11-22 05:25:17.267701: +2024-11-22 05:25:17.267977: Epoch 3488 +2024-11-22 05:25:17.268092: Current learning rate: 0.00597 +2024-11-22 05:25:35.571600: train_loss -0.7857 +2024-11-22 05:25:35.571891: val_loss -0.7575 +2024-11-22 05:25:35.571971: Pseudo dice [0.8305] +2024-11-22 05:25:35.572053: Epoch time: 18.3 s +2024-11-22 05:25:36.458985: +2024-11-22 05:25:36.459224: Epoch 3489 +2024-11-22 05:25:36.459338: Current learning rate: 0.00597 +2024-11-22 05:25:55.758138: train_loss -0.7856 +2024-11-22 05:25:55.758371: val_loss -0.7713 +2024-11-22 05:25:55.758459: Pseudo dice [0.844] +2024-11-22 05:25:55.758540: Epoch time: 19.3 s +2024-11-22 05:25:56.629542: +2024-11-22 05:25:56.629764: Epoch 3490 +2024-11-22 05:25:56.629875: Current learning rate: 0.00597 +2024-11-22 05:26:14.887845: train_loss -0.7786 +2024-11-22 05:26:14.888086: val_loss -0.7477 +2024-11-22 05:26:14.888164: Pseudo dice [0.8176] +2024-11-22 05:26:14.888240: Epoch time: 18.26 s +2024-11-22 05:26:15.759674: +2024-11-22 05:26:15.760048: Epoch 3491 +2024-11-22 05:26:15.760159: Current learning rate: 0.00597 +2024-11-22 05:26:34.209065: train_loss -0.7683 +2024-11-22 05:26:34.209282: val_loss -0.7591 +2024-11-22 05:26:34.209356: Pseudo dice [0.8462] +2024-11-22 05:26:34.209432: Epoch time: 18.45 s +2024-11-22 05:26:35.080115: +2024-11-22 05:26:35.080335: Epoch 3492 +2024-11-22 05:26:35.080442: Current learning rate: 0.00597 +2024-11-22 05:26:54.054397: train_loss -0.7742 +2024-11-22 05:26:54.054618: val_loss -0.75 +2024-11-22 05:26:54.054693: Pseudo dice [0.8407] +2024-11-22 05:26:54.054769: Epoch time: 18.98 s +2024-11-22 05:26:54.921878: +2024-11-22 05:26:54.922077: Epoch 3493 +2024-11-22 05:26:54.922187: Current learning rate: 0.00597 +2024-11-22 05:27:14.656786: train_loss -0.7506 +2024-11-22 05:27:14.657034: val_loss -0.764 +2024-11-22 05:27:14.657111: Pseudo dice [0.8361] +2024-11-22 05:27:14.657192: Epoch time: 19.74 s +2024-11-22 05:27:15.532824: +2024-11-22 05:27:15.533067: Epoch 3494 +2024-11-22 05:27:15.533179: Current learning rate: 0.00597 +2024-11-22 05:27:33.242786: train_loss -0.7894 +2024-11-22 05:27:33.243038: val_loss -0.778 +2024-11-22 05:27:33.243122: Pseudo dice [0.8574] +2024-11-22 05:27:33.243203: Epoch time: 17.71 s +2024-11-22 05:27:34.112968: +2024-11-22 05:27:34.113185: Epoch 3495 +2024-11-22 05:27:34.113301: Current learning rate: 0.00596 +2024-11-22 05:27:53.332973: train_loss -0.7752 +2024-11-22 05:27:53.333209: val_loss -0.7531 +2024-11-22 05:27:53.333285: Pseudo dice [0.8416] +2024-11-22 05:27:53.333361: Epoch time: 19.22 s +2024-11-22 05:27:54.204570: +2024-11-22 05:27:54.204791: Epoch 3496 +2024-11-22 05:27:54.204902: Current learning rate: 0.00596 +2024-11-22 05:28:12.056433: train_loss -0.7855 +2024-11-22 05:28:12.056886: val_loss -0.7569 +2024-11-22 05:28:12.056985: Pseudo dice [0.8332] +2024-11-22 05:28:12.057071: Epoch time: 17.85 s +2024-11-22 05:28:12.925109: +2024-11-22 05:28:12.925383: Epoch 3497 +2024-11-22 05:28:12.925495: Current learning rate: 0.00596 +2024-11-22 05:28:30.609426: train_loss -0.7783 +2024-11-22 05:28:30.611880: val_loss -0.7714 +2024-11-22 05:28:30.611976: Pseudo dice [0.8436] +2024-11-22 05:28:30.612068: Epoch time: 17.69 s +2024-11-22 05:28:31.492789: +2024-11-22 05:28:31.493031: Epoch 3498 +2024-11-22 05:28:31.493139: Current learning rate: 0.00596 +2024-11-22 05:28:49.165322: train_loss -0.7828 +2024-11-22 05:28:49.165536: val_loss -0.7652 +2024-11-22 05:28:49.165609: Pseudo dice [0.8425] +2024-11-22 05:28:49.165682: Epoch time: 17.67 s +2024-11-22 05:28:50.043899: +2024-11-22 05:28:50.044147: Epoch 3499 +2024-11-22 05:28:50.044265: Current learning rate: 0.00596 +2024-11-22 05:29:07.421525: train_loss -0.7905 +2024-11-22 05:29:07.421743: val_loss -0.7815 +2024-11-22 05:29:07.421822: Pseudo dice [0.8572] +2024-11-22 05:29:07.421899: Epoch time: 17.38 s +2024-11-22 05:29:08.567673: +2024-11-22 05:29:08.567929: Epoch 3500 +2024-11-22 05:29:08.568060: Current learning rate: 0.00596 +2024-11-22 05:29:27.036756: train_loss -0.7818 +2024-11-22 05:29:27.037017: val_loss -0.7943 +2024-11-22 05:29:27.037096: Pseudo dice [0.862] +2024-11-22 05:29:27.037177: Epoch time: 18.47 s +2024-11-22 05:29:27.906897: +2024-11-22 05:29:27.907117: Epoch 3501 +2024-11-22 05:29:27.907231: Current learning rate: 0.00596 +2024-11-22 05:29:46.824780: train_loss -0.7863 +2024-11-22 05:29:46.825043: val_loss -0.7584 +2024-11-22 05:29:46.825124: Pseudo dice [0.8338] +2024-11-22 05:29:46.825203: Epoch time: 18.92 s +2024-11-22 05:29:47.697455: +2024-11-22 05:29:47.697689: Epoch 3502 +2024-11-22 05:29:47.697800: Current learning rate: 0.00596 +2024-11-22 05:30:06.463335: train_loss -0.7898 +2024-11-22 05:30:06.463556: val_loss -0.7701 +2024-11-22 05:30:06.463631: Pseudo dice [0.8419] +2024-11-22 05:30:06.463706: Epoch time: 18.77 s +2024-11-22 05:30:07.337856: +2024-11-22 05:30:07.338076: Epoch 3503 +2024-11-22 05:30:07.338184: Current learning rate: 0.00595 +2024-11-22 05:30:26.221760: train_loss -0.7899 +2024-11-22 05:30:26.221978: val_loss -0.7413 +2024-11-22 05:30:26.222065: Pseudo dice [0.8273] +2024-11-22 05:30:26.222144: Epoch time: 18.88 s +2024-11-22 05:30:27.096649: +2024-11-22 05:30:27.096865: Epoch 3504 +2024-11-22 05:30:27.096976: Current learning rate: 0.00595 +2024-11-22 05:30:45.553376: train_loss -0.786 +2024-11-22 05:30:45.553644: val_loss -0.7676 +2024-11-22 05:30:45.553767: Pseudo dice [0.8372] +2024-11-22 05:30:45.553870: Epoch time: 18.46 s +2024-11-22 05:30:46.426283: +2024-11-22 05:30:46.426480: Epoch 3505 +2024-11-22 05:30:46.426591: Current learning rate: 0.00595 +2024-11-22 05:31:04.896797: train_loss -0.789 +2024-11-22 05:31:04.897020: val_loss -0.7801 +2024-11-22 05:31:04.897094: Pseudo dice [0.8618] +2024-11-22 05:31:04.897198: Epoch time: 18.47 s +2024-11-22 05:31:05.766321: +2024-11-22 05:31:05.766541: Epoch 3506 +2024-11-22 05:31:05.766651: Current learning rate: 0.00595 +2024-11-22 05:31:25.008678: train_loss -0.7863 +2024-11-22 05:31:25.008895: val_loss -0.7671 +2024-11-22 05:31:25.008973: Pseudo dice [0.8458] +2024-11-22 05:31:25.009058: Epoch time: 19.24 s +2024-11-22 05:31:25.875925: +2024-11-22 05:31:25.876139: Epoch 3507 +2024-11-22 05:31:25.876248: Current learning rate: 0.00595 +2024-11-22 05:31:44.626877: train_loss -0.7826 +2024-11-22 05:31:44.627093: val_loss -0.7659 +2024-11-22 05:31:44.627198: Pseudo dice [0.8436] +2024-11-22 05:31:44.627287: Epoch time: 18.75 s +2024-11-22 05:31:45.492973: +2024-11-22 05:31:45.493295: Epoch 3508 +2024-11-22 05:31:45.493438: Current learning rate: 0.00595 +2024-11-22 05:32:05.185923: train_loss -0.7817 +2024-11-22 05:32:05.186158: val_loss -0.7824 +2024-11-22 05:32:05.186232: Pseudo dice [0.836] +2024-11-22 05:32:05.186309: Epoch time: 19.69 s +2024-11-22 05:32:06.079648: +2024-11-22 05:32:06.079880: Epoch 3509 +2024-11-22 05:32:06.080001: Current learning rate: 0.00595 +2024-11-22 05:32:23.612786: train_loss -0.7713 +2024-11-22 05:32:23.616231: val_loss -0.7803 +2024-11-22 05:32:23.616617: Pseudo dice [0.8522] +2024-11-22 05:32:23.616705: Epoch time: 17.53 s +2024-11-22 05:32:24.513686: +2024-11-22 05:32:24.513909: Epoch 3510 +2024-11-22 05:32:24.514023: Current learning rate: 0.00595 +2024-11-22 05:32:43.043634: train_loss -0.7876 +2024-11-22 05:32:43.044679: val_loss -0.7833 +2024-11-22 05:32:43.044787: Pseudo dice [0.8493] +2024-11-22 05:32:43.044863: Epoch time: 18.53 s +2024-11-22 05:32:43.923637: +2024-11-22 05:32:43.923893: Epoch 3511 +2024-11-22 05:32:43.924045: Current learning rate: 0.00595 +2024-11-22 05:33:02.305666: train_loss -0.7877 +2024-11-22 05:33:02.311111: val_loss -0.7695 +2024-11-22 05:33:02.311233: Pseudo dice [0.8348] +2024-11-22 05:33:02.311321: Epoch time: 18.38 s +2024-11-22 05:33:03.208778: +2024-11-22 05:33:03.209016: Epoch 3512 +2024-11-22 05:33:03.209130: Current learning rate: 0.00594 +2024-11-22 05:33:21.196408: train_loss -0.7936 +2024-11-22 05:33:21.196629: val_loss -0.7893 +2024-11-22 05:33:21.196706: Pseudo dice [0.8562] +2024-11-22 05:33:21.196784: Epoch time: 17.99 s +2024-11-22 05:33:22.073614: +2024-11-22 05:33:22.073832: Epoch 3513 +2024-11-22 05:33:22.073946: Current learning rate: 0.00594 +2024-11-22 05:33:40.740055: train_loss -0.7844 +2024-11-22 05:33:40.740274: val_loss -0.7879 +2024-11-22 05:33:40.740350: Pseudo dice [0.8463] +2024-11-22 05:33:40.740422: Epoch time: 18.67 s +2024-11-22 05:33:41.606717: +2024-11-22 05:33:41.606959: Epoch 3514 +2024-11-22 05:33:41.607079: Current learning rate: 0.00594 +2024-11-22 05:34:00.217773: train_loss -0.7914 +2024-11-22 05:34:00.218014: val_loss -0.7838 +2024-11-22 05:34:00.218101: Pseudo dice [0.8506] +2024-11-22 05:34:00.218179: Epoch time: 18.61 s +2024-11-22 05:34:01.095052: +2024-11-22 05:34:01.095263: Epoch 3515 +2024-11-22 05:34:01.095370: Current learning rate: 0.00594 +2024-11-22 05:34:19.898976: train_loss -0.777 +2024-11-22 05:34:19.904415: val_loss -0.7251 +2024-11-22 05:34:19.904541: Pseudo dice [0.8181] +2024-11-22 05:34:19.904629: Epoch time: 18.8 s +2024-11-22 05:34:20.954028: +2024-11-22 05:34:20.954268: Epoch 3516 +2024-11-22 05:34:20.954383: Current learning rate: 0.00594 +2024-11-22 05:34:39.670848: train_loss -0.7847 +2024-11-22 05:34:39.671073: val_loss -0.7739 +2024-11-22 05:34:39.671152: Pseudo dice [0.8586] +2024-11-22 05:34:39.671230: Epoch time: 18.72 s +2024-11-22 05:34:40.637305: +2024-11-22 05:34:40.637547: Epoch 3517 +2024-11-22 05:34:40.637659: Current learning rate: 0.00594 +2024-11-22 05:34:58.665017: train_loss -0.7831 +2024-11-22 05:34:58.665318: val_loss -0.7609 +2024-11-22 05:34:58.665395: Pseudo dice [0.8481] +2024-11-22 05:34:58.665469: Epoch time: 18.03 s +2024-11-22 05:34:59.967775: +2024-11-22 05:34:59.967988: Epoch 3518 +2024-11-22 05:34:59.968101: Current learning rate: 0.00594 +2024-11-22 05:35:17.888645: train_loss -0.7856 +2024-11-22 05:35:17.888956: val_loss -0.7783 +2024-11-22 05:35:17.889046: Pseudo dice [0.8512] +2024-11-22 05:35:17.889131: Epoch time: 17.92 s +2024-11-22 05:35:18.763468: +2024-11-22 05:35:18.763684: Epoch 3519 +2024-11-22 05:35:18.763794: Current learning rate: 0.00594 +2024-11-22 05:35:37.966247: train_loss -0.7892 +2024-11-22 05:35:37.966462: val_loss -0.7596 +2024-11-22 05:35:37.966535: Pseudo dice [0.8462] +2024-11-22 05:35:37.966609: Epoch time: 19.2 s +2024-11-22 05:35:38.859475: +2024-11-22 05:35:38.859705: Epoch 3520 +2024-11-22 05:35:38.859814: Current learning rate: 0.00593 +2024-11-22 05:35:57.077556: train_loss -0.791 +2024-11-22 05:35:57.077833: val_loss -0.7651 +2024-11-22 05:35:57.077907: Pseudo dice [0.8492] +2024-11-22 05:35:57.077980: Epoch time: 18.22 s +2024-11-22 05:35:57.953616: +2024-11-22 05:35:57.953828: Epoch 3521 +2024-11-22 05:35:57.953938: Current learning rate: 0.00593 +2024-11-22 05:36:16.637075: train_loss -0.7876 +2024-11-22 05:36:16.637296: val_loss -0.7669 +2024-11-22 05:36:16.637375: Pseudo dice [0.8521] +2024-11-22 05:36:16.637451: Epoch time: 18.68 s +2024-11-22 05:36:17.510536: +2024-11-22 05:36:17.510757: Epoch 3522 +2024-11-22 05:36:17.510869: Current learning rate: 0.00593 +2024-11-22 05:36:36.498916: train_loss -0.7902 +2024-11-22 05:36:36.499246: val_loss -0.7777 +2024-11-22 05:36:36.499326: Pseudo dice [0.8469] +2024-11-22 05:36:36.499410: Epoch time: 18.99 s +2024-11-22 05:36:37.387751: +2024-11-22 05:36:37.387968: Epoch 3523 +2024-11-22 05:36:37.388081: Current learning rate: 0.00593 +2024-11-22 05:36:55.356351: train_loss -0.7892 +2024-11-22 05:36:55.356575: val_loss -0.7845 +2024-11-22 05:36:55.356653: Pseudo dice [0.8618] +2024-11-22 05:36:55.356803: Epoch time: 17.97 s +2024-11-22 05:36:56.334527: +2024-11-22 05:36:56.334750: Epoch 3524 +2024-11-22 05:36:56.334865: Current learning rate: 0.00593 +2024-11-22 05:37:15.145749: train_loss -0.7922 +2024-11-22 05:37:15.145960: val_loss -0.7781 +2024-11-22 05:37:15.146040: Pseudo dice [0.8353] +2024-11-22 05:37:15.146138: Epoch time: 18.81 s +2024-11-22 05:37:16.021259: +2024-11-22 05:37:16.021474: Epoch 3525 +2024-11-22 05:37:16.021584: Current learning rate: 0.00593 +2024-11-22 05:37:34.797024: train_loss -0.7844 +2024-11-22 05:37:34.797268: val_loss -0.7415 +2024-11-22 05:37:34.797345: Pseudo dice [0.8342] +2024-11-22 05:37:34.797427: Epoch time: 18.78 s +2024-11-22 05:37:35.667355: +2024-11-22 05:37:35.667563: Epoch 3526 +2024-11-22 05:37:35.667674: Current learning rate: 0.00593 +2024-11-22 05:37:54.753504: train_loss -0.7815 +2024-11-22 05:37:54.753747: val_loss -0.7673 +2024-11-22 05:37:54.753822: Pseudo dice [0.8543] +2024-11-22 05:37:54.753905: Epoch time: 19.09 s +2024-11-22 05:37:55.629292: +2024-11-22 05:37:55.629501: Epoch 3527 +2024-11-22 05:37:55.629611: Current learning rate: 0.00593 +2024-11-22 05:38:14.177300: train_loss -0.7825 +2024-11-22 05:38:14.177532: val_loss -0.7819 +2024-11-22 05:38:14.177606: Pseudo dice [0.8453] +2024-11-22 05:38:14.177681: Epoch time: 18.55 s +2024-11-22 05:38:15.132358: +2024-11-22 05:38:15.132574: Epoch 3528 +2024-11-22 05:38:15.132681: Current learning rate: 0.00592 +2024-11-22 05:38:33.737493: train_loss -0.7892 +2024-11-22 05:38:33.737710: val_loss -0.7864 +2024-11-22 05:38:33.737782: Pseudo dice [0.8566] +2024-11-22 05:38:33.737855: Epoch time: 18.61 s +2024-11-22 05:38:34.614609: +2024-11-22 05:38:34.614891: Epoch 3529 +2024-11-22 05:38:34.615010: Current learning rate: 0.00592 +2024-11-22 05:38:52.179087: train_loss -0.7963 +2024-11-22 05:38:52.181747: val_loss -0.7621 +2024-11-22 05:38:52.204843: Pseudo dice [0.8497] +2024-11-22 05:38:52.205007: Epoch time: 17.57 s +2024-11-22 05:38:53.245035: +2024-11-22 05:38:53.245256: Epoch 3530 +2024-11-22 05:38:53.245366: Current learning rate: 0.00592 +2024-11-22 05:39:12.760065: train_loss -0.7778 +2024-11-22 05:39:12.760288: val_loss -0.7645 +2024-11-22 05:39:12.760382: Pseudo dice [0.8412] +2024-11-22 05:39:12.760458: Epoch time: 19.52 s +2024-11-22 05:39:13.636020: +2024-11-22 05:39:13.636235: Epoch 3531 +2024-11-22 05:39:13.636340: Current learning rate: 0.00592 +2024-11-22 05:39:32.755220: train_loss -0.7789 +2024-11-22 05:39:32.755462: val_loss -0.7388 +2024-11-22 05:39:32.755535: Pseudo dice [0.8396] +2024-11-22 05:39:32.755610: Epoch time: 19.12 s +2024-11-22 05:39:33.677299: +2024-11-22 05:39:33.677525: Epoch 3532 +2024-11-22 05:39:33.677634: Current learning rate: 0.00592 +2024-11-22 05:39:53.057444: train_loss -0.7758 +2024-11-22 05:39:53.062883: val_loss -0.7694 +2024-11-22 05:39:53.063008: Pseudo dice [0.8431] +2024-11-22 05:39:53.063097: Epoch time: 19.38 s +2024-11-22 05:39:53.978194: +2024-11-22 05:39:53.978393: Epoch 3533 +2024-11-22 05:39:53.978501: Current learning rate: 0.00592 +2024-11-22 05:40:13.464944: train_loss -0.7794 +2024-11-22 05:40:13.465167: val_loss -0.7599 +2024-11-22 05:40:13.465240: Pseudo dice [0.8396] +2024-11-22 05:40:13.465312: Epoch time: 19.49 s +2024-11-22 05:40:14.371955: +2024-11-22 05:40:14.372171: Epoch 3534 +2024-11-22 05:40:14.372281: Current learning rate: 0.00592 +2024-11-22 05:40:31.771359: train_loss -0.7884 +2024-11-22 05:40:31.771609: val_loss -0.7842 +2024-11-22 05:40:31.771686: Pseudo dice [0.8625] +2024-11-22 05:40:31.771761: Epoch time: 17.4 s +2024-11-22 05:40:32.647691: +2024-11-22 05:40:32.647885: Epoch 3535 +2024-11-22 05:40:32.648000: Current learning rate: 0.00592 +2024-11-22 05:40:50.394752: train_loss -0.7948 +2024-11-22 05:40:50.394975: val_loss -0.7581 +2024-11-22 05:40:50.395271: Pseudo dice [0.825] +2024-11-22 05:40:50.395352: Epoch time: 17.75 s +2024-11-22 05:40:51.265674: +2024-11-22 05:40:51.265941: Epoch 3536 +2024-11-22 05:40:51.266055: Current learning rate: 0.00592 +2024-11-22 05:41:10.267194: train_loss -0.7817 +2024-11-22 05:41:10.267443: val_loss -0.7559 +2024-11-22 05:41:10.267519: Pseudo dice [0.8367] +2024-11-22 05:41:10.267601: Epoch time: 19.0 s +2024-11-22 05:41:11.141935: +2024-11-22 05:41:11.142141: Epoch 3537 +2024-11-22 05:41:11.142251: Current learning rate: 0.00591 +2024-11-22 05:41:29.369787: train_loss -0.7816 +2024-11-22 05:41:29.370006: val_loss -0.7578 +2024-11-22 05:41:29.370079: Pseudo dice [0.8419] +2024-11-22 05:41:29.370152: Epoch time: 18.23 s +2024-11-22 05:41:30.239219: +2024-11-22 05:41:30.239455: Epoch 3538 +2024-11-22 05:41:30.239562: Current learning rate: 0.00591 +2024-11-22 05:41:48.425190: train_loss -0.7829 +2024-11-22 05:41:48.425419: val_loss -0.7588 +2024-11-22 05:41:48.425492: Pseudo dice [0.8498] +2024-11-22 05:41:48.425567: Epoch time: 18.19 s +2024-11-22 05:41:49.299132: +2024-11-22 05:41:49.299357: Epoch 3539 +2024-11-22 05:41:49.299472: Current learning rate: 0.00591 +2024-11-22 05:42:07.837686: train_loss -0.7757 +2024-11-22 05:42:07.837996: val_loss -0.7538 +2024-11-22 05:42:07.838085: Pseudo dice [0.8357] +2024-11-22 05:42:07.838166: Epoch time: 18.54 s +2024-11-22 05:42:09.098658: +2024-11-22 05:42:09.098876: Epoch 3540 +2024-11-22 05:42:09.098985: Current learning rate: 0.00591 +2024-11-22 05:42:27.214165: train_loss -0.7863 +2024-11-22 05:42:27.214415: val_loss -0.782 +2024-11-22 05:42:27.214492: Pseudo dice [0.8632] +2024-11-22 05:42:27.214570: Epoch time: 18.12 s +2024-11-22 05:42:28.081167: +2024-11-22 05:42:28.081384: Epoch 3541 +2024-11-22 05:42:28.081497: Current learning rate: 0.00591 +2024-11-22 05:42:46.944190: train_loss -0.7782 +2024-11-22 05:42:46.944410: val_loss -0.7727 +2024-11-22 05:42:46.944489: Pseudo dice [0.8408] +2024-11-22 05:42:46.944562: Epoch time: 18.86 s +2024-11-22 05:42:47.815710: +2024-11-22 05:42:47.815957: Epoch 3542 +2024-11-22 05:42:47.816073: Current learning rate: 0.00591 +2024-11-22 05:43:06.165747: train_loss -0.7693 +2024-11-22 05:43:06.166001: val_loss -0.7581 +2024-11-22 05:43:06.166076: Pseudo dice [0.8257] +2024-11-22 05:43:06.166150: Epoch time: 18.35 s +2024-11-22 05:43:07.034413: +2024-11-22 05:43:07.034633: Epoch 3543 +2024-11-22 05:43:07.034741: Current learning rate: 0.00591 +2024-11-22 05:43:24.851920: train_loss -0.7804 +2024-11-22 05:43:24.852173: val_loss -0.7517 +2024-11-22 05:43:24.852251: Pseudo dice [0.8459] +2024-11-22 05:43:24.852335: Epoch time: 17.82 s +2024-11-22 05:43:25.746089: +2024-11-22 05:43:25.746301: Epoch 3544 +2024-11-22 05:43:25.746411: Current learning rate: 0.00591 +2024-11-22 05:43:44.097763: train_loss -0.7718 +2024-11-22 05:43:44.097968: val_loss -0.7823 +2024-11-22 05:43:44.098049: Pseudo dice [0.8394] +2024-11-22 05:43:44.098125: Epoch time: 18.35 s +2024-11-22 05:43:44.966074: +2024-11-22 05:43:44.966285: Epoch 3545 +2024-11-22 05:43:44.966398: Current learning rate: 0.0059 +2024-11-22 05:44:03.868221: train_loss -0.7686 +2024-11-22 05:44:03.868454: val_loss -0.755 +2024-11-22 05:44:03.868531: Pseudo dice [0.8451] +2024-11-22 05:44:03.868618: Epoch time: 18.9 s +2024-11-22 05:44:04.737310: +2024-11-22 05:44:04.737526: Epoch 3546 +2024-11-22 05:44:04.737638: Current learning rate: 0.0059 +2024-11-22 05:44:22.584885: train_loss -0.7814 +2024-11-22 05:44:22.590316: val_loss -0.7618 +2024-11-22 05:44:22.590473: Pseudo dice [0.8339] +2024-11-22 05:44:22.590560: Epoch time: 17.85 s +2024-11-22 05:44:23.514022: +2024-11-22 05:44:23.514366: Epoch 3547 +2024-11-22 05:44:23.514493: Current learning rate: 0.0059 +2024-11-22 05:44:42.503877: train_loss -0.7753 +2024-11-22 05:44:42.504133: val_loss -0.7663 +2024-11-22 05:44:42.504206: Pseudo dice [0.8336] +2024-11-22 05:44:42.504285: Epoch time: 18.99 s +2024-11-22 05:44:43.392158: +2024-11-22 05:44:43.392520: Epoch 3548 +2024-11-22 05:44:43.392637: Current learning rate: 0.0059 +2024-11-22 05:45:01.953016: train_loss -0.7895 +2024-11-22 05:45:01.953243: val_loss -0.7502 +2024-11-22 05:45:01.953318: Pseudo dice [0.833] +2024-11-22 05:45:01.953394: Epoch time: 18.56 s +2024-11-22 05:45:02.818072: +2024-11-22 05:45:02.818294: Epoch 3549 +2024-11-22 05:45:02.818405: Current learning rate: 0.0059 +2024-11-22 05:45:20.779974: train_loss -0.7853 +2024-11-22 05:45:20.780297: val_loss -0.7576 +2024-11-22 05:45:20.780376: Pseudo dice [0.8405] +2024-11-22 05:45:20.780452: Epoch time: 17.96 s +2024-11-22 05:45:21.880000: +2024-11-22 05:45:21.880419: Epoch 3550 +2024-11-22 05:45:21.880547: Current learning rate: 0.0059 +2024-11-22 05:45:40.050075: train_loss -0.7913 +2024-11-22 05:45:40.050317: val_loss -0.7464 +2024-11-22 05:45:40.050395: Pseudo dice [0.8437] +2024-11-22 05:45:40.050482: Epoch time: 18.17 s +2024-11-22 05:45:40.920370: +2024-11-22 05:45:40.920591: Epoch 3551 +2024-11-22 05:45:40.920699: Current learning rate: 0.0059 +2024-11-22 05:45:59.605657: train_loss -0.8002 +2024-11-22 05:45:59.605860: val_loss -0.7423 +2024-11-22 05:45:59.605932: Pseudo dice [0.8402] +2024-11-22 05:45:59.606013: Epoch time: 18.69 s +2024-11-22 05:46:00.946452: +2024-11-22 05:46:00.946666: Epoch 3552 +2024-11-22 05:46:00.946773: Current learning rate: 0.0059 +2024-11-22 05:46:19.545503: train_loss -0.7853 +2024-11-22 05:46:19.545768: val_loss -0.7836 +2024-11-22 05:46:19.545847: Pseudo dice [0.8523] +2024-11-22 05:46:19.545923: Epoch time: 18.6 s +2024-11-22 05:46:20.483079: +2024-11-22 05:46:20.483309: Epoch 3553 +2024-11-22 05:46:20.483423: Current learning rate: 0.00589 +2024-11-22 05:46:38.632488: train_loss -0.7838 +2024-11-22 05:46:38.632708: val_loss -0.7986 +2024-11-22 05:46:38.632787: Pseudo dice [0.846] +2024-11-22 05:46:38.632865: Epoch time: 18.15 s +2024-11-22 05:46:39.501829: +2024-11-22 05:46:39.502077: Epoch 3554 +2024-11-22 05:46:39.502189: Current learning rate: 0.00589 +2024-11-22 05:46:58.615480: train_loss -0.7884 +2024-11-22 05:46:58.615713: val_loss -0.7695 +2024-11-22 05:46:58.615787: Pseudo dice [0.8361] +2024-11-22 05:46:58.621033: Epoch time: 19.11 s +2024-11-22 05:46:59.500169: +2024-11-22 05:46:59.500473: Epoch 3555 +2024-11-22 05:46:59.500586: Current learning rate: 0.00589 +2024-11-22 05:47:19.777810: train_loss -0.7754 +2024-11-22 05:47:19.778032: val_loss -0.7641 +2024-11-22 05:47:19.778107: Pseudo dice [0.8394] +2024-11-22 05:47:19.778180: Epoch time: 20.28 s +2024-11-22 05:47:20.650893: +2024-11-22 05:47:20.651095: Epoch 3556 +2024-11-22 05:47:20.651202: Current learning rate: 0.00589 +2024-11-22 05:47:39.076950: train_loss -0.7833 +2024-11-22 05:47:39.077204: val_loss -0.7888 +2024-11-22 05:47:39.077278: Pseudo dice [0.8402] +2024-11-22 05:47:39.077351: Epoch time: 18.43 s +2024-11-22 05:47:39.945451: +2024-11-22 05:47:39.945680: Epoch 3557 +2024-11-22 05:47:39.945791: Current learning rate: 0.00589 +2024-11-22 05:47:58.010720: train_loss -0.7912 +2024-11-22 05:47:58.010958: val_loss -0.7709 +2024-11-22 05:47:58.011045: Pseudo dice [0.8491] +2024-11-22 05:47:58.011121: Epoch time: 18.07 s +2024-11-22 05:47:58.999901: +2024-11-22 05:47:59.000139: Epoch 3558 +2024-11-22 05:47:59.000251: Current learning rate: 0.00589 +2024-11-22 05:48:17.507645: train_loss -0.7861 +2024-11-22 05:48:17.507899: val_loss -0.7717 +2024-11-22 05:48:17.508006: Pseudo dice [0.8469] +2024-11-22 05:48:17.508091: Epoch time: 18.51 s +2024-11-22 05:48:18.388592: +2024-11-22 05:48:18.388799: Epoch 3559 +2024-11-22 05:48:18.388907: Current learning rate: 0.00589 +2024-11-22 05:48:37.876415: train_loss -0.7804 +2024-11-22 05:48:37.876634: val_loss -0.7675 +2024-11-22 05:48:37.876711: Pseudo dice [0.8525] +2024-11-22 05:48:37.876785: Epoch time: 19.49 s +2024-11-22 05:48:38.763052: +2024-11-22 05:48:38.763303: Epoch 3560 +2024-11-22 05:48:38.763424: Current learning rate: 0.00589 +2024-11-22 05:48:57.174322: train_loss -0.7825 +2024-11-22 05:48:57.174531: val_loss -0.7375 +2024-11-22 05:48:57.174607: Pseudo dice [0.851] +2024-11-22 05:48:57.174682: Epoch time: 18.41 s +2024-11-22 05:48:58.033240: +2024-11-22 05:48:58.033644: Epoch 3561 +2024-11-22 05:48:58.033775: Current learning rate: 0.00589 +2024-11-22 05:49:16.266416: train_loss -0.7797 +2024-11-22 05:49:16.266933: val_loss -0.7492 +2024-11-22 05:49:16.267065: Pseudo dice [0.8452] +2024-11-22 05:49:16.267144: Epoch time: 18.23 s +2024-11-22 05:49:17.171910: +2024-11-22 05:49:17.172127: Epoch 3562 +2024-11-22 05:49:17.172235: Current learning rate: 0.00588 +2024-11-22 05:49:35.120414: train_loss -0.7777 +2024-11-22 05:49:35.122846: val_loss -0.759 +2024-11-22 05:49:35.122947: Pseudo dice [0.8361] +2024-11-22 05:49:35.123033: Epoch time: 17.95 s +2024-11-22 05:49:36.028039: +2024-11-22 05:49:36.028274: Epoch 3563 +2024-11-22 05:49:36.028394: Current learning rate: 0.00588 +2024-11-22 05:49:54.072462: train_loss -0.7852 +2024-11-22 05:49:54.072947: val_loss -0.7647 +2024-11-22 05:49:54.073050: Pseudo dice [0.8513] +2024-11-22 05:49:54.073126: Epoch time: 18.05 s +2024-11-22 05:49:54.946357: +2024-11-22 05:49:54.946614: Epoch 3564 +2024-11-22 05:49:54.946728: Current learning rate: 0.00588 +2024-11-22 05:50:13.271666: train_loss -0.7871 +2024-11-22 05:50:13.271935: val_loss -0.7827 +2024-11-22 05:50:13.272022: Pseudo dice [0.8361] +2024-11-22 05:50:13.272099: Epoch time: 18.33 s +2024-11-22 05:50:14.146186: +2024-11-22 05:50:14.146393: Epoch 3565 +2024-11-22 05:50:14.146501: Current learning rate: 0.00588 +2024-11-22 05:50:31.600132: train_loss -0.7857 +2024-11-22 05:50:31.600374: val_loss -0.765 +2024-11-22 05:50:31.600508: Pseudo dice [0.843] +2024-11-22 05:50:31.600597: Epoch time: 17.45 s +2024-11-22 05:50:32.472774: +2024-11-22 05:50:32.473008: Epoch 3566 +2024-11-22 05:50:32.473119: Current learning rate: 0.00588 +2024-11-22 05:50:50.040749: train_loss -0.7803 +2024-11-22 05:50:50.040958: val_loss -0.7619 +2024-11-22 05:50:50.041039: Pseudo dice [0.8344] +2024-11-22 05:50:50.041115: Epoch time: 17.57 s +2024-11-22 05:50:50.907223: +2024-11-22 05:50:50.907439: Epoch 3567 +2024-11-22 05:50:50.907546: Current learning rate: 0.00588 +2024-11-22 05:51:08.915135: train_loss -0.7836 +2024-11-22 05:51:08.915398: val_loss -0.7798 +2024-11-22 05:51:08.915552: Pseudo dice [0.8451] +2024-11-22 05:51:08.915631: Epoch time: 18.01 s +2024-11-22 05:51:09.789792: +2024-11-22 05:51:09.789989: Epoch 3568 +2024-11-22 05:51:09.790119: Current learning rate: 0.00588 +2024-11-22 05:51:27.950046: train_loss -0.7741 +2024-11-22 05:51:27.950343: val_loss -0.7745 +2024-11-22 05:51:27.950431: Pseudo dice [0.8516] +2024-11-22 05:51:27.950511: Epoch time: 18.16 s +2024-11-22 05:51:28.826218: +2024-11-22 05:51:28.826509: Epoch 3569 +2024-11-22 05:51:28.826624: Current learning rate: 0.00588 +2024-11-22 05:51:46.603116: train_loss -0.7878 +2024-11-22 05:51:46.603353: val_loss -0.7735 +2024-11-22 05:51:46.603431: Pseudo dice [0.8485] +2024-11-22 05:51:46.603512: Epoch time: 17.78 s +2024-11-22 05:51:47.474200: +2024-11-22 05:51:47.474421: Epoch 3570 +2024-11-22 05:51:47.474568: Current learning rate: 0.00587 +2024-11-22 05:52:05.377284: train_loss -0.7913 +2024-11-22 05:52:05.377499: val_loss -0.7662 +2024-11-22 05:52:05.377575: Pseudo dice [0.8378] +2024-11-22 05:52:05.377685: Epoch time: 17.9 s +2024-11-22 05:52:06.275463: +2024-11-22 05:52:06.275676: Epoch 3571 +2024-11-22 05:52:06.275784: Current learning rate: 0.00587 +2024-11-22 05:52:24.886298: train_loss -0.7739 +2024-11-22 05:52:24.886502: val_loss -0.7627 +2024-11-22 05:52:24.886575: Pseudo dice [0.8557] +2024-11-22 05:52:24.886650: Epoch time: 18.61 s +2024-11-22 05:52:25.751592: +2024-11-22 05:52:25.751799: Epoch 3572 +2024-11-22 05:52:25.751909: Current learning rate: 0.00587 +2024-11-22 05:52:44.751952: train_loss -0.7798 +2024-11-22 05:52:44.752213: val_loss -0.7511 +2024-11-22 05:52:44.752288: Pseudo dice [0.8455] +2024-11-22 05:52:44.752371: Epoch time: 19.0 s +2024-11-22 05:52:45.826912: +2024-11-22 05:52:45.827192: Epoch 3573 +2024-11-22 05:52:45.827311: Current learning rate: 0.00587 +2024-11-22 05:53:05.035852: train_loss -0.7874 +2024-11-22 05:53:05.038281: val_loss -0.7603 +2024-11-22 05:53:05.038384: Pseudo dice [0.8473] +2024-11-22 05:53:05.038462: Epoch time: 19.21 s +2024-11-22 05:53:06.100478: +2024-11-22 05:53:06.100691: Epoch 3574 +2024-11-22 05:53:06.100800: Current learning rate: 0.00587 +2024-11-22 05:53:24.664032: train_loss -0.7758 +2024-11-22 05:53:24.664256: val_loss -0.7491 +2024-11-22 05:53:24.664332: Pseudo dice [0.8457] +2024-11-22 05:53:24.664406: Epoch time: 18.56 s +2024-11-22 05:53:25.934117: +2024-11-22 05:53:25.934319: Epoch 3575 +2024-11-22 05:53:25.934425: Current learning rate: 0.00587 +2024-11-22 05:53:45.221311: train_loss -0.7681 +2024-11-22 05:53:45.221573: val_loss -0.7484 +2024-11-22 05:53:45.221663: Pseudo dice [0.8194] +2024-11-22 05:53:45.221743: Epoch time: 19.29 s +2024-11-22 05:53:46.166811: +2024-11-22 05:53:46.167041: Epoch 3576 +2024-11-22 05:53:46.167148: Current learning rate: 0.00587 +2024-11-22 05:54:05.325270: train_loss -0.7783 +2024-11-22 05:54:05.325500: val_loss -0.7375 +2024-11-22 05:54:05.327018: Pseudo dice [0.8438] +2024-11-22 05:54:05.327119: Epoch time: 19.16 s +2024-11-22 05:54:06.211102: +2024-11-22 05:54:06.211326: Epoch 3577 +2024-11-22 05:54:06.211438: Current learning rate: 0.00587 +2024-11-22 05:54:25.555582: train_loss -0.7809 +2024-11-22 05:54:25.555802: val_loss -0.7455 +2024-11-22 05:54:25.555874: Pseudo dice [0.847] +2024-11-22 05:54:25.555948: Epoch time: 19.35 s +2024-11-22 05:54:26.421615: +2024-11-22 05:54:26.421842: Epoch 3578 +2024-11-22 05:54:26.421948: Current learning rate: 0.00587 +2024-11-22 05:54:44.811410: train_loss -0.7817 +2024-11-22 05:54:44.811620: val_loss -0.7784 +2024-11-22 05:54:44.811697: Pseudo dice [0.849] +2024-11-22 05:54:44.811771: Epoch time: 18.39 s +2024-11-22 05:54:45.678092: +2024-11-22 05:54:45.678344: Epoch 3579 +2024-11-22 05:54:45.678450: Current learning rate: 0.00586 +2024-11-22 05:55:03.500713: train_loss -0.7888 +2024-11-22 05:55:03.500969: val_loss -0.766 +2024-11-22 05:55:03.501053: Pseudo dice [0.8422] +2024-11-22 05:55:03.501136: Epoch time: 17.82 s +2024-11-22 05:55:04.390637: +2024-11-22 05:55:04.390861: Epoch 3580 +2024-11-22 05:55:04.390976: Current learning rate: 0.00586 +2024-11-22 05:55:21.935730: train_loss -0.7902 +2024-11-22 05:55:21.935948: val_loss -0.7789 +2024-11-22 05:55:21.941253: Pseudo dice [0.8454] +2024-11-22 05:55:21.941380: Epoch time: 17.55 s +2024-11-22 05:55:22.934512: +2024-11-22 05:55:22.934737: Epoch 3581 +2024-11-22 05:55:22.934847: Current learning rate: 0.00586 +2024-11-22 05:55:41.245280: train_loss -0.7891 +2024-11-22 05:55:41.245495: val_loss -0.7795 +2024-11-22 05:55:41.245571: Pseudo dice [0.8385] +2024-11-22 05:55:41.245644: Epoch time: 18.31 s +2024-11-22 05:55:42.115501: +2024-11-22 05:55:42.115720: Epoch 3582 +2024-11-22 05:55:42.115829: Current learning rate: 0.00586 +2024-11-22 05:56:01.024863: train_loss -0.7937 +2024-11-22 05:56:01.025109: val_loss -0.7763 +2024-11-22 05:56:01.025188: Pseudo dice [0.8389] +2024-11-22 05:56:01.025262: Epoch time: 18.91 s +2024-11-22 05:56:01.894025: +2024-11-22 05:56:01.894250: Epoch 3583 +2024-11-22 05:56:01.894371: Current learning rate: 0.00586 +2024-11-22 05:56:19.834984: train_loss -0.7973 +2024-11-22 05:56:19.840408: val_loss -0.7744 +2024-11-22 05:56:19.840489: Pseudo dice [0.8234] +2024-11-22 05:56:19.840580: Epoch time: 17.94 s +2024-11-22 05:56:20.839220: +2024-11-22 05:56:20.839431: Epoch 3584 +2024-11-22 05:56:20.839538: Current learning rate: 0.00586 +2024-11-22 05:56:39.804627: train_loss -0.7934 +2024-11-22 05:56:39.804963: val_loss -0.7417 +2024-11-22 05:56:39.805051: Pseudo dice [0.8363] +2024-11-22 05:56:39.805133: Epoch time: 18.96 s +2024-11-22 05:56:40.840981: +2024-11-22 05:56:40.841251: Epoch 3585 +2024-11-22 05:56:40.841361: Current learning rate: 0.00586 +2024-11-22 05:56:59.632337: train_loss -0.7938 +2024-11-22 05:56:59.632567: val_loss -0.7638 +2024-11-22 05:56:59.632643: Pseudo dice [0.848] +2024-11-22 05:56:59.632716: Epoch time: 18.79 s +2024-11-22 05:57:00.606033: +2024-11-22 05:57:00.606458: Epoch 3586 +2024-11-22 05:57:00.606594: Current learning rate: 0.00586 +2024-11-22 05:57:18.655980: train_loss -0.7944 +2024-11-22 05:57:18.656490: val_loss -0.7838 +2024-11-22 05:57:18.656586: Pseudo dice [0.8549] +2024-11-22 05:57:18.656667: Epoch time: 18.05 s +2024-11-22 05:57:19.517823: +2024-11-22 05:57:19.518046: Epoch 3587 +2024-11-22 05:57:19.518164: Current learning rate: 0.00585 +2024-11-22 05:57:37.912860: train_loss -0.792 +2024-11-22 05:57:37.913197: val_loss -0.7744 +2024-11-22 05:57:37.913297: Pseudo dice [0.8596] +2024-11-22 05:57:37.913377: Epoch time: 18.4 s +2024-11-22 05:57:38.899166: +2024-11-22 05:57:38.899407: Epoch 3588 +2024-11-22 05:57:38.899519: Current learning rate: 0.00585 +2024-11-22 05:57:56.358874: train_loss -0.7976 +2024-11-22 05:57:56.359096: val_loss -0.7542 +2024-11-22 05:57:56.359188: Pseudo dice [0.8358] +2024-11-22 05:57:56.359266: Epoch time: 17.46 s +2024-11-22 05:57:57.217009: +2024-11-22 05:57:57.217226: Epoch 3589 +2024-11-22 05:57:57.217333: Current learning rate: 0.00585 +2024-11-22 05:58:14.880254: train_loss -0.7856 +2024-11-22 05:58:14.880570: val_loss -0.7625 +2024-11-22 05:58:14.880655: Pseudo dice [0.8531] +2024-11-22 05:58:14.880739: Epoch time: 17.66 s +2024-11-22 05:58:15.907472: +2024-11-22 05:58:15.907700: Epoch 3590 +2024-11-22 05:58:15.907810: Current learning rate: 0.00585 +2024-11-22 05:58:35.110814: train_loss -0.7881 +2024-11-22 05:58:35.111065: val_loss -0.751 +2024-11-22 05:58:35.111147: Pseudo dice [0.8427] +2024-11-22 05:58:35.111225: Epoch time: 19.2 s +2024-11-22 05:58:36.110051: +2024-11-22 05:58:36.110275: Epoch 3591 +2024-11-22 05:58:36.110385: Current learning rate: 0.00585 +2024-11-22 05:58:55.674209: train_loss -0.7899 +2024-11-22 05:58:55.674417: val_loss -0.7846 +2024-11-22 05:58:55.674491: Pseudo dice [0.8555] +2024-11-22 05:58:55.674566: Epoch time: 19.56 s +2024-11-22 05:58:56.552677: +2024-11-22 05:58:56.552906: Epoch 3592 +2024-11-22 05:58:56.553025: Current learning rate: 0.00585 +2024-11-22 05:59:14.353597: train_loss -0.7906 +2024-11-22 05:59:14.353827: val_loss -0.7821 +2024-11-22 05:59:14.353898: Pseudo dice [0.8403] +2024-11-22 05:59:14.359208: Epoch time: 17.8 s +2024-11-22 05:59:15.506181: +2024-11-22 05:59:15.506414: Epoch 3593 +2024-11-22 05:59:15.506528: Current learning rate: 0.00585 +2024-11-22 05:59:34.160405: train_loss -0.776 +2024-11-22 05:59:34.160619: val_loss -0.7645 +2024-11-22 05:59:34.160694: Pseudo dice [0.841] +2024-11-22 05:59:34.160768: Epoch time: 18.66 s +2024-11-22 05:59:35.029987: +2024-11-22 05:59:35.030200: Epoch 3594 +2024-11-22 05:59:35.030313: Current learning rate: 0.00585 +2024-11-22 05:59:53.189112: train_loss -0.793 +2024-11-22 05:59:53.189367: val_loss -0.7764 +2024-11-22 05:59:53.189443: Pseudo dice [0.8563] +2024-11-22 05:59:53.189527: Epoch time: 18.16 s +2024-11-22 05:59:54.062720: +2024-11-22 05:59:54.062921: Epoch 3595 +2024-11-22 05:59:54.063043: Current learning rate: 0.00584 +2024-11-22 06:00:13.175716: train_loss -0.7825 +2024-11-22 06:00:13.176029: val_loss -0.7449 +2024-11-22 06:00:13.176108: Pseudo dice [0.8333] +2024-11-22 06:00:13.176185: Epoch time: 19.11 s +2024-11-22 06:00:14.049203: +2024-11-22 06:00:14.049390: Epoch 3596 +2024-11-22 06:00:14.049500: Current learning rate: 0.00584 +2024-11-22 06:00:32.491852: train_loss -0.777 +2024-11-22 06:00:32.492070: val_loss -0.7582 +2024-11-22 06:00:32.492148: Pseudo dice [0.8398] +2024-11-22 06:00:32.492224: Epoch time: 18.44 s +2024-11-22 06:00:33.359705: +2024-11-22 06:00:33.359925: Epoch 3597 +2024-11-22 06:00:33.360039: Current learning rate: 0.00584 +2024-11-22 06:00:51.532613: train_loss -0.7852 +2024-11-22 06:00:51.532872: val_loss -0.7522 +2024-11-22 06:00:51.532946: Pseudo dice [0.8453] +2024-11-22 06:00:51.533039: Epoch time: 18.17 s +2024-11-22 06:00:52.914766: +2024-11-22 06:00:52.914981: Epoch 3598 +2024-11-22 06:00:52.915096: Current learning rate: 0.00584 +2024-11-22 06:01:11.985570: train_loss -0.7651 +2024-11-22 06:01:11.985811: val_loss -0.7373 +2024-11-22 06:01:11.985889: Pseudo dice [0.8327] +2024-11-22 06:01:11.985963: Epoch time: 19.07 s +2024-11-22 06:01:12.851043: +2024-11-22 06:01:12.851272: Epoch 3599 +2024-11-22 06:01:12.851389: Current learning rate: 0.00584 +2024-11-22 06:01:31.458146: train_loss -0.7724 +2024-11-22 06:01:31.458360: val_loss -0.7744 +2024-11-22 06:01:31.458436: Pseudo dice [0.8468] +2024-11-22 06:01:31.458508: Epoch time: 18.61 s +2024-11-22 06:01:32.596976: +2024-11-22 06:01:32.597214: Epoch 3600 +2024-11-22 06:01:32.597324: Current learning rate: 0.00584 +2024-11-22 06:01:51.227117: train_loss -0.7625 +2024-11-22 06:01:51.227421: val_loss -0.7472 +2024-11-22 06:01:51.227507: Pseudo dice [0.8524] +2024-11-22 06:01:51.227591: Epoch time: 18.63 s +2024-11-22 06:01:52.160978: +2024-11-22 06:01:52.161237: Epoch 3601 +2024-11-22 06:01:52.161351: Current learning rate: 0.00584 +2024-11-22 06:02:10.015176: train_loss -0.7797 +2024-11-22 06:02:10.015400: val_loss -0.7678 +2024-11-22 06:02:10.015474: Pseudo dice [0.8454] +2024-11-22 06:02:10.015567: Epoch time: 17.86 s +2024-11-22 06:02:10.883934: +2024-11-22 06:02:10.884154: Epoch 3602 +2024-11-22 06:02:10.884262: Current learning rate: 0.00584 +2024-11-22 06:02:29.444553: train_loss -0.7806 +2024-11-22 06:02:29.444766: val_loss -0.8015 +2024-11-22 06:02:29.444842: Pseudo dice [0.8488] +2024-11-22 06:02:29.444917: Epoch time: 18.56 s +2024-11-22 06:02:30.314768: +2024-11-22 06:02:30.314989: Epoch 3603 +2024-11-22 06:02:30.315100: Current learning rate: 0.00584 +2024-11-22 06:02:49.435743: train_loss -0.7853 +2024-11-22 06:02:49.435976: val_loss -0.7894 +2024-11-22 06:02:49.436064: Pseudo dice [0.8622] +2024-11-22 06:02:49.436143: Epoch time: 19.12 s +2024-11-22 06:02:50.305634: +2024-11-22 06:02:50.305868: Epoch 3604 +2024-11-22 06:02:50.305980: Current learning rate: 0.00583 +2024-11-22 06:03:08.534153: train_loss -0.7712 +2024-11-22 06:03:08.534460: val_loss -0.7806 +2024-11-22 06:03:08.534538: Pseudo dice [0.8348] +2024-11-22 06:03:08.534621: Epoch time: 18.23 s +2024-11-22 06:03:09.413261: +2024-11-22 06:03:09.413485: Epoch 3605 +2024-11-22 06:03:09.413593: Current learning rate: 0.00583 +2024-11-22 06:03:27.661202: train_loss -0.7815 +2024-11-22 06:03:27.661426: val_loss -0.797 +2024-11-22 06:03:27.661506: Pseudo dice [0.8583] +2024-11-22 06:03:27.661588: Epoch time: 18.25 s +2024-11-22 06:03:28.531101: +2024-11-22 06:03:28.531297: Epoch 3606 +2024-11-22 06:03:28.531407: Current learning rate: 0.00583 +2024-11-22 06:03:47.023396: train_loss -0.7698 +2024-11-22 06:03:47.024031: val_loss -0.7638 +2024-11-22 06:03:47.024165: Pseudo dice [0.8598] +2024-11-22 06:03:47.024243: Epoch time: 18.49 s +2024-11-22 06:03:47.896791: +2024-11-22 06:03:47.897002: Epoch 3607 +2024-11-22 06:03:47.897112: Current learning rate: 0.00583 +2024-11-22 06:04:06.436002: train_loss -0.7688 +2024-11-22 06:04:06.436231: val_loss -0.7865 +2024-11-22 06:04:06.436309: Pseudo dice [0.8532] +2024-11-22 06:04:06.436391: Epoch time: 18.54 s +2024-11-22 06:04:07.310767: +2024-11-22 06:04:07.311022: Epoch 3608 +2024-11-22 06:04:07.311132: Current learning rate: 0.00583 +2024-11-22 06:04:24.972589: train_loss -0.784 +2024-11-22 06:04:24.972828: val_loss -0.7898 +2024-11-22 06:04:24.972908: Pseudo dice [0.8505] +2024-11-22 06:04:24.972987: Epoch time: 17.66 s +2024-11-22 06:04:25.841172: +2024-11-22 06:04:25.841393: Epoch 3609 +2024-11-22 06:04:25.841508: Current learning rate: 0.00583 +2024-11-22 06:04:44.186816: train_loss -0.7873 +2024-11-22 06:04:44.187305: val_loss -0.763 +2024-11-22 06:04:44.187408: Pseudo dice [0.8387] +2024-11-22 06:04:44.187488: Epoch time: 18.35 s +2024-11-22 06:04:45.053093: +2024-11-22 06:04:45.053312: Epoch 3610 +2024-11-22 06:04:45.053420: Current learning rate: 0.00583 +2024-11-22 06:05:03.131689: train_loss -0.7763 +2024-11-22 06:05:03.131910: val_loss -0.7626 +2024-11-22 06:05:03.131983: Pseudo dice [0.8542] +2024-11-22 06:05:03.132069: Epoch time: 18.08 s +2024-11-22 06:05:03.999722: +2024-11-22 06:05:03.999984: Epoch 3611 +2024-11-22 06:05:04.000100: Current learning rate: 0.00583 +2024-11-22 06:05:21.519178: train_loss -0.7783 +2024-11-22 06:05:21.519416: val_loss -0.7589 +2024-11-22 06:05:21.519490: Pseudo dice [0.8429] +2024-11-22 06:05:21.519581: Epoch time: 17.52 s +2024-11-22 06:05:22.390197: +2024-11-22 06:05:22.390420: Epoch 3612 +2024-11-22 06:05:22.390528: Current learning rate: 0.00582 +2024-11-22 06:05:41.442702: train_loss -0.7835 +2024-11-22 06:05:41.442939: val_loss -0.7728 +2024-11-22 06:05:41.443027: Pseudo dice [0.846] +2024-11-22 06:05:41.443102: Epoch time: 19.05 s +2024-11-22 06:05:42.311246: +2024-11-22 06:05:42.311477: Epoch 3613 +2024-11-22 06:05:42.311587: Current learning rate: 0.00582 +2024-11-22 06:06:00.321321: train_loss -0.7972 +2024-11-22 06:06:00.321534: val_loss -0.7452 +2024-11-22 06:06:00.321689: Pseudo dice [0.8353] +2024-11-22 06:06:00.321766: Epoch time: 18.01 s +2024-11-22 06:06:01.194649: +2024-11-22 06:06:01.194973: Epoch 3614 +2024-11-22 06:06:01.195091: Current learning rate: 0.00582 +2024-11-22 06:06:19.566873: train_loss -0.7866 +2024-11-22 06:06:19.567117: val_loss -0.7726 +2024-11-22 06:06:19.567196: Pseudo dice [0.839] +2024-11-22 06:06:19.567275: Epoch time: 18.37 s +2024-11-22 06:06:20.443081: +2024-11-22 06:06:20.443280: Epoch 3615 +2024-11-22 06:06:20.443393: Current learning rate: 0.00582 +2024-11-22 06:06:37.913104: train_loss -0.7925 +2024-11-22 06:06:37.913390: val_loss -0.7729 +2024-11-22 06:06:37.913472: Pseudo dice [0.8325] +2024-11-22 06:06:37.913550: Epoch time: 17.47 s +2024-11-22 06:06:38.782702: +2024-11-22 06:06:38.782917: Epoch 3616 +2024-11-22 06:06:38.783037: Current learning rate: 0.00582 +2024-11-22 06:06:56.989603: train_loss -0.7891 +2024-11-22 06:06:56.989824: val_loss -0.795 +2024-11-22 06:06:56.989906: Pseudo dice [0.8643] +2024-11-22 06:06:56.989982: Epoch time: 18.21 s +2024-11-22 06:06:57.861317: +2024-11-22 06:06:57.861547: Epoch 3617 +2024-11-22 06:06:57.861662: Current learning rate: 0.00582 +2024-11-22 06:07:15.924256: train_loss -0.7858 +2024-11-22 06:07:15.924477: val_loss -0.7544 +2024-11-22 06:07:15.924551: Pseudo dice [0.8494] +2024-11-22 06:07:15.924626: Epoch time: 18.06 s +2024-11-22 06:07:16.825493: +2024-11-22 06:07:16.825704: Epoch 3618 +2024-11-22 06:07:16.825811: Current learning rate: 0.00582 +2024-11-22 06:07:35.232760: train_loss -0.7776 +2024-11-22 06:07:35.233024: val_loss -0.7677 +2024-11-22 06:07:35.254405: Pseudo dice [0.8324] +2024-11-22 06:07:35.254599: Epoch time: 18.41 s +2024-11-22 06:07:36.126129: +2024-11-22 06:07:36.126329: Epoch 3619 +2024-11-22 06:07:36.126438: Current learning rate: 0.00582 +2024-11-22 06:07:54.238784: train_loss -0.7897 +2024-11-22 06:07:54.239005: val_loss -0.7673 +2024-11-22 06:07:54.239083: Pseudo dice [0.8413] +2024-11-22 06:07:54.239159: Epoch time: 18.11 s +2024-11-22 06:07:55.114590: +2024-11-22 06:07:55.114801: Epoch 3620 +2024-11-22 06:07:55.114911: Current learning rate: 0.00581 +2024-11-22 06:08:13.932589: train_loss -0.7749 +2024-11-22 06:08:13.932808: val_loss -0.7857 +2024-11-22 06:08:13.932885: Pseudo dice [0.8588] +2024-11-22 06:08:13.932965: Epoch time: 18.82 s +2024-11-22 06:08:15.182379: +2024-11-22 06:08:15.182600: Epoch 3621 +2024-11-22 06:08:15.182716: Current learning rate: 0.00581 +2024-11-22 06:08:34.657139: train_loss -0.7963 +2024-11-22 06:08:34.657405: val_loss -0.7604 +2024-11-22 06:08:34.657555: Pseudo dice [0.8255] +2024-11-22 06:08:34.657645: Epoch time: 19.48 s +2024-11-22 06:08:35.531948: +2024-11-22 06:08:35.532168: Epoch 3622 +2024-11-22 06:08:35.532276: Current learning rate: 0.00581 +2024-11-22 06:08:53.389935: train_loss -0.7872 +2024-11-22 06:08:53.390163: val_loss -0.7733 +2024-11-22 06:08:53.390238: Pseudo dice [0.8413] +2024-11-22 06:08:53.390311: Epoch time: 17.86 s +2024-11-22 06:08:54.250061: +2024-11-22 06:08:54.250313: Epoch 3623 +2024-11-22 06:08:54.250426: Current learning rate: 0.00581 +2024-11-22 06:09:13.337334: train_loss -0.7904 +2024-11-22 06:09:13.337549: val_loss -0.7913 +2024-11-22 06:09:13.337623: Pseudo dice [0.8604] +2024-11-22 06:09:13.337697: Epoch time: 19.09 s +2024-11-22 06:09:14.210356: +2024-11-22 06:09:14.210583: Epoch 3624 +2024-11-22 06:09:14.210690: Current learning rate: 0.00581 +2024-11-22 06:09:33.173454: train_loss -0.7829 +2024-11-22 06:09:33.173725: val_loss -0.764 +2024-11-22 06:09:33.173803: Pseudo dice [0.8578] +2024-11-22 06:09:33.173881: Epoch time: 18.96 s +2024-11-22 06:09:34.051502: +2024-11-22 06:09:34.051716: Epoch 3625 +2024-11-22 06:09:34.051828: Current learning rate: 0.00581 +2024-11-22 06:09:51.289524: train_loss -0.7886 +2024-11-22 06:09:51.289794: val_loss -0.7644 +2024-11-22 06:09:51.289880: Pseudo dice [0.844] +2024-11-22 06:09:51.289961: Epoch time: 17.24 s +2024-11-22 06:09:52.161761: +2024-11-22 06:09:52.161976: Epoch 3626 +2024-11-22 06:09:52.162091: Current learning rate: 0.00581 +2024-11-22 06:10:10.157372: train_loss -0.7854 +2024-11-22 06:10:10.159759: val_loss -0.7506 +2024-11-22 06:10:10.159880: Pseudo dice [0.8453] +2024-11-22 06:10:10.159961: Epoch time: 18.0 s +2024-11-22 06:10:11.203522: +2024-11-22 06:10:11.203748: Epoch 3627 +2024-11-22 06:10:11.203858: Current learning rate: 0.00581 +2024-11-22 06:10:29.727472: train_loss -0.7785 +2024-11-22 06:10:29.727692: val_loss -0.7799 +2024-11-22 06:10:29.727787: Pseudo dice [0.8392] +2024-11-22 06:10:29.727864: Epoch time: 18.52 s +2024-11-22 06:10:30.704882: +2024-11-22 06:10:30.705085: Epoch 3628 +2024-11-22 06:10:30.705193: Current learning rate: 0.00581 +2024-11-22 06:10:48.571753: train_loss -0.7802 +2024-11-22 06:10:48.572064: val_loss -0.7624 +2024-11-22 06:10:48.572146: Pseudo dice [0.8423] +2024-11-22 06:10:48.572226: Epoch time: 17.87 s +2024-11-22 06:10:49.450042: +2024-11-22 06:10:49.450249: Epoch 3629 +2024-11-22 06:10:49.450356: Current learning rate: 0.0058 +2024-11-22 06:11:07.806897: train_loss -0.7851 +2024-11-22 06:11:07.807252: val_loss -0.7803 +2024-11-22 06:11:07.807331: Pseudo dice [0.8378] +2024-11-22 06:11:07.807412: Epoch time: 18.36 s +2024-11-22 06:11:08.705716: +2024-11-22 06:11:08.705927: Epoch 3630 +2024-11-22 06:11:08.706040: Current learning rate: 0.0058 +2024-11-22 06:11:27.592365: train_loss -0.7826 +2024-11-22 06:11:27.592588: val_loss -0.7666 +2024-11-22 06:11:27.592666: Pseudo dice [0.8463] +2024-11-22 06:11:27.592744: Epoch time: 18.89 s +2024-11-22 06:11:28.553678: +2024-11-22 06:11:28.553881: Epoch 3631 +2024-11-22 06:11:28.554005: Current learning rate: 0.0058 +2024-11-22 06:11:46.866854: train_loss -0.7843 +2024-11-22 06:11:46.867077: val_loss -0.7677 +2024-11-22 06:11:46.867155: Pseudo dice [0.8624] +2024-11-22 06:11:46.867229: Epoch time: 18.31 s +2024-11-22 06:11:48.076985: +2024-11-22 06:11:48.077208: Epoch 3632 +2024-11-22 06:11:48.077342: Current learning rate: 0.0058 +2024-11-22 06:12:07.182665: train_loss -0.7821 +2024-11-22 06:12:07.182922: val_loss -0.788 +2024-11-22 06:12:07.183005: Pseudo dice [0.8462] +2024-11-22 06:12:07.183086: Epoch time: 19.11 s +2024-11-22 06:12:08.061918: +2024-11-22 06:12:08.062195: Epoch 3633 +2024-11-22 06:12:08.062303: Current learning rate: 0.0058 +2024-11-22 06:12:26.258176: train_loss -0.7832 +2024-11-22 06:12:26.258396: val_loss -0.7464 +2024-11-22 06:12:26.258469: Pseudo dice [0.8423] +2024-11-22 06:12:26.258542: Epoch time: 18.2 s +2024-11-22 06:12:27.136693: +2024-11-22 06:12:27.136928: Epoch 3634 +2024-11-22 06:12:27.137049: Current learning rate: 0.0058 +2024-11-22 06:12:45.655088: train_loss -0.7818 +2024-11-22 06:12:45.655301: val_loss -0.7654 +2024-11-22 06:12:45.655376: Pseudo dice [0.8518] +2024-11-22 06:12:45.655453: Epoch time: 18.52 s +2024-11-22 06:12:46.518135: +2024-11-22 06:12:46.518348: Epoch 3635 +2024-11-22 06:12:46.518459: Current learning rate: 0.0058 +2024-11-22 06:13:06.232484: train_loss -0.7737 +2024-11-22 06:13:06.232702: val_loss -0.7642 +2024-11-22 06:13:06.232782: Pseudo dice [0.8465] +2024-11-22 06:13:06.232857: Epoch time: 19.72 s +2024-11-22 06:13:07.105599: +2024-11-22 06:13:07.105825: Epoch 3636 +2024-11-22 06:13:07.105936: Current learning rate: 0.0058 +2024-11-22 06:13:25.141535: train_loss -0.7717 +2024-11-22 06:13:25.141781: val_loss -0.7565 +2024-11-22 06:13:25.141855: Pseudo dice [0.836] +2024-11-22 06:13:25.141934: Epoch time: 18.04 s +2024-11-22 06:13:26.020851: +2024-11-22 06:13:26.021080: Epoch 3637 +2024-11-22 06:13:26.021188: Current learning rate: 0.00579 +2024-11-22 06:13:44.830805: train_loss -0.7805 +2024-11-22 06:13:44.831026: val_loss -0.7765 +2024-11-22 06:13:44.831122: Pseudo dice [0.8469] +2024-11-22 06:13:44.831203: Epoch time: 18.81 s +2024-11-22 06:13:45.699111: +2024-11-22 06:13:45.699319: Epoch 3638 +2024-11-22 06:13:45.699429: Current learning rate: 0.00579 +2024-11-22 06:14:04.499634: train_loss -0.7891 +2024-11-22 06:14:04.499855: val_loss -0.7721 +2024-11-22 06:14:04.499934: Pseudo dice [0.8407] +2024-11-22 06:14:04.500018: Epoch time: 18.8 s +2024-11-22 06:14:05.387765: +2024-11-22 06:14:05.387982: Epoch 3639 +2024-11-22 06:14:05.388094: Current learning rate: 0.00579 +2024-11-22 06:14:23.743099: train_loss -0.793 +2024-11-22 06:14:23.743361: val_loss -0.7817 +2024-11-22 06:14:23.743438: Pseudo dice [0.8458] +2024-11-22 06:14:23.743520: Epoch time: 18.36 s +2024-11-22 06:14:24.614907: +2024-11-22 06:14:24.615228: Epoch 3640 +2024-11-22 06:14:24.615343: Current learning rate: 0.00579 +2024-11-22 06:14:42.603611: train_loss -0.7918 +2024-11-22 06:14:42.603829: val_loss -0.7569 +2024-11-22 06:14:42.603904: Pseudo dice [0.8319] +2024-11-22 06:14:42.603998: Epoch time: 17.99 s +2024-11-22 06:14:43.461752: +2024-11-22 06:14:43.461979: Epoch 3641 +2024-11-22 06:14:43.462093: Current learning rate: 0.00579 +2024-11-22 06:15:01.324954: train_loss -0.7911 +2024-11-22 06:15:01.325184: val_loss -0.7568 +2024-11-22 06:15:01.325258: Pseudo dice [0.8452] +2024-11-22 06:15:01.325332: Epoch time: 17.86 s +2024-11-22 06:15:02.233406: +2024-11-22 06:15:02.233617: Epoch 3642 +2024-11-22 06:15:02.233728: Current learning rate: 0.00579 +2024-11-22 06:15:20.383784: train_loss -0.7785 +2024-11-22 06:15:20.384019: val_loss -0.7913 +2024-11-22 06:15:20.384095: Pseudo dice [0.8624] +2024-11-22 06:15:20.384174: Epoch time: 18.15 s +2024-11-22 06:15:21.253700: +2024-11-22 06:15:21.253907: Epoch 3643 +2024-11-22 06:15:21.254022: Current learning rate: 0.00579 +2024-11-22 06:15:40.319044: train_loss -0.7886 +2024-11-22 06:15:40.319287: val_loss -0.7767 +2024-11-22 06:15:40.319408: Pseudo dice [0.86] +2024-11-22 06:15:40.319489: Epoch time: 19.07 s +2024-11-22 06:15:41.604760: +2024-11-22 06:15:41.605207: Epoch 3644 +2024-11-22 06:15:41.605345: Current learning rate: 0.00579 +2024-11-22 06:15:59.530339: train_loss -0.79 +2024-11-22 06:15:59.530566: val_loss -0.7743 +2024-11-22 06:15:59.530642: Pseudo dice [0.8663] +2024-11-22 06:15:59.530714: Epoch time: 17.93 s +2024-11-22 06:16:00.394811: +2024-11-22 06:16:00.395236: Epoch 3645 +2024-11-22 06:16:00.395368: Current learning rate: 0.00579 +2024-11-22 06:16:18.232316: train_loss -0.7923 +2024-11-22 06:16:18.232551: val_loss -0.7545 +2024-11-22 06:16:18.232633: Pseudo dice [0.8444] +2024-11-22 06:16:18.232713: Epoch time: 17.84 s +2024-11-22 06:16:19.100466: +2024-11-22 06:16:19.100964: Epoch 3646 +2024-11-22 06:16:19.101105: Current learning rate: 0.00578 +2024-11-22 06:16:37.524374: train_loss -0.7858 +2024-11-22 06:16:37.524620: val_loss -0.7736 +2024-11-22 06:16:37.524693: Pseudo dice [0.8495] +2024-11-22 06:16:37.524770: Epoch time: 18.42 s +2024-11-22 06:16:38.389612: +2024-11-22 06:16:38.390046: Epoch 3647 +2024-11-22 06:16:38.390182: Current learning rate: 0.00578 +2024-11-22 06:16:56.231523: train_loss -0.7821 +2024-11-22 06:16:56.231734: val_loss -0.7594 +2024-11-22 06:16:56.231810: Pseudo dice [0.8411] +2024-11-22 06:16:56.231884: Epoch time: 17.84 s +2024-11-22 06:16:57.103825: +2024-11-22 06:16:57.104304: Epoch 3648 +2024-11-22 06:16:57.104439: Current learning rate: 0.00578 +2024-11-22 06:17:15.027450: train_loss -0.7747 +2024-11-22 06:17:15.028483: val_loss -0.7669 +2024-11-22 06:17:15.028561: Pseudo dice [0.8565] +2024-11-22 06:17:15.028636: Epoch time: 17.92 s +2024-11-22 06:17:15.907156: +2024-11-22 06:17:15.907559: Epoch 3649 +2024-11-22 06:17:15.907690: Current learning rate: 0.00578 +2024-11-22 06:17:34.535196: train_loss -0.7812 +2024-11-22 06:17:34.535412: val_loss -0.766 +2024-11-22 06:17:34.535487: Pseudo dice [0.8455] +2024-11-22 06:17:34.535560: Epoch time: 18.63 s +2024-11-22 06:17:35.677016: +2024-11-22 06:17:35.677452: Epoch 3650 +2024-11-22 06:17:35.677588: Current learning rate: 0.00578 +2024-11-22 06:17:54.311143: train_loss -0.7918 +2024-11-22 06:17:54.311406: val_loss -0.7683 +2024-11-22 06:17:54.311497: Pseudo dice [0.8301] +2024-11-22 06:17:54.311587: Epoch time: 18.63 s +2024-11-22 06:17:55.187231: +2024-11-22 06:17:55.187639: Epoch 3651 +2024-11-22 06:17:55.187768: Current learning rate: 0.00578 +2024-11-22 06:18:12.842605: train_loss -0.7783 +2024-11-22 06:18:12.842821: val_loss -0.7684 +2024-11-22 06:18:12.842894: Pseudo dice [0.839] +2024-11-22 06:18:12.842966: Epoch time: 17.66 s +2024-11-22 06:18:13.749908: +2024-11-22 06:18:13.750483: Epoch 3652 +2024-11-22 06:18:13.750627: Current learning rate: 0.00578 +2024-11-22 06:18:32.144666: train_loss -0.7821 +2024-11-22 06:18:32.144887: val_loss -0.7746 +2024-11-22 06:18:32.144964: Pseudo dice [0.8642] +2024-11-22 06:18:32.145077: Epoch time: 18.4 s +2024-11-22 06:18:33.014438: +2024-11-22 06:18:33.014841: Epoch 3653 +2024-11-22 06:18:33.014979: Current learning rate: 0.00578 +2024-11-22 06:18:51.713684: train_loss -0.7778 +2024-11-22 06:18:51.713981: val_loss -0.7567 +2024-11-22 06:18:51.714069: Pseudo dice [0.833] +2024-11-22 06:18:51.714154: Epoch time: 18.7 s +2024-11-22 06:18:52.588806: +2024-11-22 06:18:52.589365: Epoch 3654 +2024-11-22 06:18:52.589542: Current learning rate: 0.00577 +2024-11-22 06:19:10.619610: train_loss -0.7688 +2024-11-22 06:19:10.619823: val_loss -0.7678 +2024-11-22 06:19:10.619900: Pseudo dice [0.849] +2024-11-22 06:19:10.619975: Epoch time: 18.03 s +2024-11-22 06:19:11.485927: +2024-11-22 06:19:11.486139: Epoch 3655 +2024-11-22 06:19:11.486247: Current learning rate: 0.00577 +2024-11-22 06:19:29.963549: train_loss -0.7801 +2024-11-22 06:19:29.969265: val_loss -0.7574 +2024-11-22 06:19:29.969380: Pseudo dice [0.8655] +2024-11-22 06:19:29.969457: Epoch time: 18.48 s +2024-11-22 06:19:30.847981: +2024-11-22 06:19:30.848440: Epoch 3656 +2024-11-22 06:19:30.848577: Current learning rate: 0.00577 +2024-11-22 06:19:49.550965: train_loss -0.7841 +2024-11-22 06:19:49.551246: val_loss -0.7601 +2024-11-22 06:19:49.552057: Pseudo dice [0.8403] +2024-11-22 06:19:49.552182: Epoch time: 18.7 s +2024-11-22 06:19:50.447433: +2024-11-22 06:19:50.447940: Epoch 3657 +2024-11-22 06:19:50.448078: Current learning rate: 0.00577 +2024-11-22 06:20:08.378484: train_loss -0.7929 +2024-11-22 06:20:08.378708: val_loss -0.7689 +2024-11-22 06:20:08.378790: Pseudo dice [0.8576] +2024-11-22 06:20:08.378868: Epoch time: 17.93 s +2024-11-22 06:20:09.246230: +2024-11-22 06:20:09.246647: Epoch 3658 +2024-11-22 06:20:09.246779: Current learning rate: 0.00577 +2024-11-22 06:20:27.784506: train_loss -0.7869 +2024-11-22 06:20:27.784723: val_loss -0.764 +2024-11-22 06:20:27.784796: Pseudo dice [0.8393] +2024-11-22 06:20:27.784870: Epoch time: 18.54 s +2024-11-22 06:20:28.757418: +2024-11-22 06:20:28.757885: Epoch 3659 +2024-11-22 06:20:28.758029: Current learning rate: 0.00577 +2024-11-22 06:20:46.459462: train_loss -0.7926 +2024-11-22 06:20:46.459681: val_loss -0.768 +2024-11-22 06:20:46.459755: Pseudo dice [0.8369] +2024-11-22 06:20:46.459830: Epoch time: 17.7 s +2024-11-22 06:20:47.463645: +2024-11-22 06:20:47.464065: Epoch 3660 +2024-11-22 06:20:47.464197: Current learning rate: 0.00577 +2024-11-22 06:21:06.489265: train_loss -0.7716 +2024-11-22 06:21:06.489488: val_loss -0.7739 +2024-11-22 06:21:06.489564: Pseudo dice [0.8419] +2024-11-22 06:21:06.489645: Epoch time: 19.03 s +2024-11-22 06:21:07.364733: +2024-11-22 06:21:07.365157: Epoch 3661 +2024-11-22 06:21:07.365286: Current learning rate: 0.00577 +2024-11-22 06:21:25.887636: train_loss -0.7756 +2024-11-22 06:21:25.887879: val_loss -0.778 +2024-11-22 06:21:25.887970: Pseudo dice [0.8679] +2024-11-22 06:21:25.888055: Epoch time: 18.52 s +2024-11-22 06:21:26.830157: +2024-11-22 06:21:26.830558: Epoch 3662 +2024-11-22 06:21:26.830689: Current learning rate: 0.00576 +2024-11-22 06:21:46.272349: train_loss -0.7767 +2024-11-22 06:21:46.272560: val_loss -0.7629 +2024-11-22 06:21:46.272635: Pseudo dice [0.8363] +2024-11-22 06:21:46.272713: Epoch time: 19.44 s +2024-11-22 06:21:47.131900: +2024-11-22 06:21:47.132308: Epoch 3663 +2024-11-22 06:21:47.132436: Current learning rate: 0.00576 +2024-11-22 06:22:06.016331: train_loss -0.7884 +2024-11-22 06:22:06.016553: val_loss -0.7526 +2024-11-22 06:22:06.016632: Pseudo dice [0.8351] +2024-11-22 06:22:06.016715: Epoch time: 18.89 s +2024-11-22 06:22:06.888382: +2024-11-22 06:22:06.888787: Epoch 3664 +2024-11-22 06:22:06.888916: Current learning rate: 0.00576 +2024-11-22 06:22:25.045897: train_loss -0.7861 +2024-11-22 06:22:25.046154: val_loss -0.76 +2024-11-22 06:22:25.046232: Pseudo dice [0.8558] +2024-11-22 06:22:25.046314: Epoch time: 18.16 s +2024-11-22 06:22:25.924811: +2024-11-22 06:22:25.925258: Epoch 3665 +2024-11-22 06:22:25.925644: Current learning rate: 0.00576 +2024-11-22 06:22:44.319987: train_loss -0.7867 +2024-11-22 06:22:44.320228: val_loss -0.7665 +2024-11-22 06:22:44.320311: Pseudo dice [0.8179] +2024-11-22 06:22:44.320390: Epoch time: 18.4 s +2024-11-22 06:22:45.189672: +2024-11-22 06:22:45.190081: Epoch 3666 +2024-11-22 06:22:45.190211: Current learning rate: 0.00576 +2024-11-22 06:23:03.847387: train_loss -0.7804 +2024-11-22 06:23:03.847628: val_loss -0.784 +2024-11-22 06:23:03.847705: Pseudo dice [0.8505] +2024-11-22 06:23:03.847786: Epoch time: 18.66 s +2024-11-22 06:23:05.115889: +2024-11-22 06:23:05.116346: Epoch 3667 +2024-11-22 06:23:05.116479: Current learning rate: 0.00576 +2024-11-22 06:23:23.014602: train_loss -0.7812 +2024-11-22 06:23:23.014931: val_loss -0.7905 +2024-11-22 06:23:23.015017: Pseudo dice [0.8524] +2024-11-22 06:23:23.015100: Epoch time: 17.9 s +2024-11-22 06:23:23.909409: +2024-11-22 06:23:23.909821: Epoch 3668 +2024-11-22 06:23:23.909954: Current learning rate: 0.00576 +2024-11-22 06:23:43.669851: train_loss -0.7901 +2024-11-22 06:23:43.670121: val_loss -0.7747 +2024-11-22 06:23:43.670202: Pseudo dice [0.8445] +2024-11-22 06:23:43.670277: Epoch time: 19.76 s +2024-11-22 06:23:44.539380: +2024-11-22 06:23:44.539923: Epoch 3669 +2024-11-22 06:23:44.540059: Current learning rate: 0.00576 +2024-11-22 06:24:02.670818: train_loss -0.7932 +2024-11-22 06:24:02.673221: val_loss -0.7492 +2024-11-22 06:24:02.673312: Pseudo dice [0.8311] +2024-11-22 06:24:02.673390: Epoch time: 18.13 s +2024-11-22 06:24:03.667720: +2024-11-22 06:24:03.668146: Epoch 3670 +2024-11-22 06:24:03.668274: Current learning rate: 0.00576 +2024-11-22 06:24:22.574468: train_loss -0.7931 +2024-11-22 06:24:22.574691: val_loss -0.762 +2024-11-22 06:24:22.574767: Pseudo dice [0.8291] +2024-11-22 06:24:22.574840: Epoch time: 18.91 s +2024-11-22 06:24:23.460788: +2024-11-22 06:24:23.461231: Epoch 3671 +2024-11-22 06:24:23.461370: Current learning rate: 0.00575 +2024-11-22 06:24:41.372162: train_loss -0.7908 +2024-11-22 06:24:41.372455: val_loss -0.7929 +2024-11-22 06:24:41.372535: Pseudo dice [0.8507] +2024-11-22 06:24:41.372615: Epoch time: 17.91 s +2024-11-22 06:24:42.244266: +2024-11-22 06:24:42.244682: Epoch 3672 +2024-11-22 06:24:42.244806: Current learning rate: 0.00575 +2024-11-22 06:24:59.221730: train_loss -0.7856 +2024-11-22 06:24:59.221985: val_loss -0.7548 +2024-11-22 06:24:59.222075: Pseudo dice [0.8483] +2024-11-22 06:24:59.222148: Epoch time: 16.98 s +2024-11-22 06:25:00.088239: +2024-11-22 06:25:00.088698: Epoch 3673 +2024-11-22 06:25:00.088838: Current learning rate: 0.00575 +2024-11-22 06:25:18.690410: train_loss -0.7689 +2024-11-22 06:25:18.692817: val_loss -0.7603 +2024-11-22 06:25:18.692922: Pseudo dice [0.8286] +2024-11-22 06:25:18.693006: Epoch time: 18.6 s +2024-11-22 06:25:19.696419: +2024-11-22 06:25:19.696900: Epoch 3674 +2024-11-22 06:25:19.697040: Current learning rate: 0.00575 +2024-11-22 06:25:38.362465: train_loss -0.7871 +2024-11-22 06:25:38.362691: val_loss -0.7704 +2024-11-22 06:25:38.362775: Pseudo dice [0.8441] +2024-11-22 06:25:38.362859: Epoch time: 18.67 s +2024-11-22 06:25:39.231070: +2024-11-22 06:25:39.231516: Epoch 3675 +2024-11-22 06:25:39.231655: Current learning rate: 0.00575 +2024-11-22 06:25:57.534512: train_loss -0.7978 +2024-11-22 06:25:57.534745: val_loss -0.773 +2024-11-22 06:25:57.534822: Pseudo dice [0.8483] +2024-11-22 06:25:57.534897: Epoch time: 18.3 s +2024-11-22 06:25:58.494002: +2024-11-22 06:25:58.494218: Epoch 3676 +2024-11-22 06:25:58.494331: Current learning rate: 0.00575 +2024-11-22 06:26:16.689681: train_loss -0.7885 +2024-11-22 06:26:16.689906: val_loss -0.7718 +2024-11-22 06:26:16.689979: Pseudo dice [0.8376] +2024-11-22 06:26:16.690060: Epoch time: 18.2 s +2024-11-22 06:26:17.561410: +2024-11-22 06:26:17.561639: Epoch 3677 +2024-11-22 06:26:17.561755: Current learning rate: 0.00575 +2024-11-22 06:26:36.721645: train_loss -0.7923 +2024-11-22 06:26:36.721874: val_loss -0.7629 +2024-11-22 06:26:36.721950: Pseudo dice [0.8461] +2024-11-22 06:26:36.722032: Epoch time: 19.16 s +2024-11-22 06:26:37.964632: +2024-11-22 06:26:37.965065: Epoch 3678 +2024-11-22 06:26:37.965195: Current learning rate: 0.00575 +2024-11-22 06:26:56.146848: train_loss -0.7885 +2024-11-22 06:26:56.147124: val_loss -0.7499 +2024-11-22 06:26:56.147204: Pseudo dice [0.8277] +2024-11-22 06:26:56.147299: Epoch time: 18.18 s +2024-11-22 06:26:57.411075: +2024-11-22 06:26:57.411500: Epoch 3679 +2024-11-22 06:26:57.411626: Current learning rate: 0.00574 +2024-11-22 06:27:15.648378: train_loss -0.7953 +2024-11-22 06:27:15.650706: val_loss -0.7898 +2024-11-22 06:27:15.650805: Pseudo dice [0.8572] +2024-11-22 06:27:15.650882: Epoch time: 18.24 s +2024-11-22 06:27:16.571985: +2024-11-22 06:27:16.572407: Epoch 3680 +2024-11-22 06:27:16.572532: Current learning rate: 0.00574 +2024-11-22 06:27:35.249960: train_loss -0.7941 +2024-11-22 06:27:35.250196: val_loss -0.7736 +2024-11-22 06:27:35.250293: Pseudo dice [0.8497] +2024-11-22 06:27:35.250372: Epoch time: 18.68 s +2024-11-22 06:27:36.114631: +2024-11-22 06:27:36.115118: Epoch 3681 +2024-11-22 06:27:36.115250: Current learning rate: 0.00574 +2024-11-22 06:27:54.174810: train_loss -0.7769 +2024-11-22 06:27:54.175049: val_loss -0.77 +2024-11-22 06:27:54.175126: Pseudo dice [0.8475] +2024-11-22 06:27:54.175205: Epoch time: 18.06 s +2024-11-22 06:27:55.051065: +2024-11-22 06:27:55.051496: Epoch 3682 +2024-11-22 06:27:55.051635: Current learning rate: 0.00574 +2024-11-22 06:28:12.925667: train_loss -0.7823 +2024-11-22 06:28:12.925927: val_loss -0.7616 +2024-11-22 06:28:12.926013: Pseudo dice [0.8341] +2024-11-22 06:28:12.926118: Epoch time: 17.88 s +2024-11-22 06:28:13.793593: +2024-11-22 06:28:13.794018: Epoch 3683 +2024-11-22 06:28:13.794149: Current learning rate: 0.00574 +2024-11-22 06:28:32.233107: train_loss -0.7747 +2024-11-22 06:28:32.233386: val_loss -0.7744 +2024-11-22 06:28:32.233466: Pseudo dice [0.8517] +2024-11-22 06:28:32.233541: Epoch time: 18.44 s +2024-11-22 06:28:33.109386: +2024-11-22 06:28:33.109897: Epoch 3684 +2024-11-22 06:28:33.110041: Current learning rate: 0.00574 +2024-11-22 06:28:51.799582: train_loss -0.764 +2024-11-22 06:28:51.799796: val_loss -0.7452 +2024-11-22 06:28:51.799870: Pseudo dice [0.8459] +2024-11-22 06:28:51.799944: Epoch time: 18.69 s +2024-11-22 06:28:52.657860: +2024-11-22 06:28:52.658320: Epoch 3685 +2024-11-22 06:28:52.658460: Current learning rate: 0.00574 +2024-11-22 06:29:12.091187: train_loss -0.7636 +2024-11-22 06:29:12.091501: val_loss -0.7766 +2024-11-22 06:29:12.091581: Pseudo dice [0.8528] +2024-11-22 06:29:12.091666: Epoch time: 19.43 s +2024-11-22 06:29:13.134744: +2024-11-22 06:29:13.135166: Epoch 3686 +2024-11-22 06:29:13.135296: Current learning rate: 0.00574 +2024-11-22 06:29:31.269196: train_loss -0.7697 +2024-11-22 06:29:31.269419: val_loss -0.7348 +2024-11-22 06:29:31.269497: Pseudo dice [0.8139] +2024-11-22 06:29:31.269571: Epoch time: 18.14 s +2024-11-22 06:29:32.133631: +2024-11-22 06:29:32.134072: Epoch 3687 +2024-11-22 06:29:32.134204: Current learning rate: 0.00573 +2024-11-22 06:29:50.286500: train_loss -0.7717 +2024-11-22 06:29:50.286723: val_loss -0.78 +2024-11-22 06:29:50.286799: Pseudo dice [0.8478] +2024-11-22 06:29:50.286875: Epoch time: 18.15 s +2024-11-22 06:29:51.150057: +2024-11-22 06:29:51.150286: Epoch 3688 +2024-11-22 06:29:51.150398: Current learning rate: 0.00573 +2024-11-22 06:30:09.657075: train_loss -0.7797 +2024-11-22 06:30:09.657311: val_loss -0.7824 +2024-11-22 06:30:09.657390: Pseudo dice [0.8498] +2024-11-22 06:30:09.657470: Epoch time: 18.51 s +2024-11-22 06:30:10.524677: +2024-11-22 06:30:10.524906: Epoch 3689 +2024-11-22 06:30:10.525059: Current learning rate: 0.00573 +2024-11-22 06:30:28.907212: train_loss -0.7839 +2024-11-22 06:30:28.907428: val_loss -0.7799 +2024-11-22 06:30:28.907502: Pseudo dice [0.8387] +2024-11-22 06:30:28.907577: Epoch time: 18.38 s +2024-11-22 06:30:30.144601: +2024-11-22 06:30:30.145042: Epoch 3690 +2024-11-22 06:30:30.145171: Current learning rate: 0.00573 +2024-11-22 06:30:47.474554: train_loss -0.7896 +2024-11-22 06:30:47.474780: val_loss -0.7644 +2024-11-22 06:30:47.474860: Pseudo dice [0.8434] +2024-11-22 06:30:47.474934: Epoch time: 17.33 s +2024-11-22 06:30:48.399326: +2024-11-22 06:30:48.399758: Epoch 3691 +2024-11-22 06:30:48.399988: Current learning rate: 0.00573 +2024-11-22 06:31:06.456396: train_loss -0.771 +2024-11-22 06:31:06.456606: val_loss -0.7431 +2024-11-22 06:31:06.456684: Pseudo dice [0.816] +2024-11-22 06:31:06.456762: Epoch time: 18.06 s +2024-11-22 06:31:07.327811: +2024-11-22 06:31:07.328253: Epoch 3692 +2024-11-22 06:31:07.328383: Current learning rate: 0.00573 +2024-11-22 06:31:25.902096: train_loss -0.7709 +2024-11-22 06:31:25.902338: val_loss -0.7932 +2024-11-22 06:31:25.902417: Pseudo dice [0.8466] +2024-11-22 06:31:25.902533: Epoch time: 18.58 s +2024-11-22 06:31:26.777589: +2024-11-22 06:31:26.778048: Epoch 3693 +2024-11-22 06:31:26.778180: Current learning rate: 0.00573 +2024-11-22 06:31:44.563994: train_loss -0.7823 +2024-11-22 06:31:44.564205: val_loss -0.7627 +2024-11-22 06:31:44.564289: Pseudo dice [0.8434] +2024-11-22 06:31:44.564398: Epoch time: 17.79 s +2024-11-22 06:31:45.435166: +2024-11-22 06:31:45.435599: Epoch 3694 +2024-11-22 06:31:45.435727: Current learning rate: 0.00573 +2024-11-22 06:32:04.242055: train_loss -0.7818 +2024-11-22 06:32:04.242299: val_loss -0.7726 +2024-11-22 06:32:04.242376: Pseudo dice [0.8386] +2024-11-22 06:32:04.242448: Epoch time: 18.81 s +2024-11-22 06:32:05.114753: +2024-11-22 06:32:05.115191: Epoch 3695 +2024-11-22 06:32:05.115322: Current learning rate: 0.00573 +2024-11-22 06:32:23.811048: train_loss -0.7772 +2024-11-22 06:32:23.811276: val_loss -0.7669 +2024-11-22 06:32:23.811392: Pseudo dice [0.8221] +2024-11-22 06:32:23.811477: Epoch time: 18.7 s +2024-11-22 06:32:24.688720: +2024-11-22 06:32:24.689138: Epoch 3696 +2024-11-22 06:32:24.689272: Current learning rate: 0.00572 +2024-11-22 06:32:43.575093: train_loss -0.7732 +2024-11-22 06:32:43.575330: val_loss -0.7887 +2024-11-22 06:32:43.575404: Pseudo dice [0.8501] +2024-11-22 06:32:43.575481: Epoch time: 18.89 s +2024-11-22 06:32:44.444094: +2024-11-22 06:32:44.444533: Epoch 3697 +2024-11-22 06:32:44.444672: Current learning rate: 0.00572 +2024-11-22 06:33:03.362636: train_loss -0.7732 +2024-11-22 06:33:03.362870: val_loss -0.7209 +2024-11-22 06:33:03.362943: Pseudo dice [0.8253] +2024-11-22 06:33:03.363022: Epoch time: 18.92 s +2024-11-22 06:33:04.235305: +2024-11-22 06:33:04.235737: Epoch 3698 +2024-11-22 06:33:04.235868: Current learning rate: 0.00572 +2024-11-22 06:33:23.680876: train_loss -0.7702 +2024-11-22 06:33:23.681091: val_loss -0.7706 +2024-11-22 06:33:23.681166: Pseudo dice [0.8476] +2024-11-22 06:33:23.681242: Epoch time: 19.45 s +2024-11-22 06:33:24.546483: +2024-11-22 06:33:24.546690: Epoch 3699 +2024-11-22 06:33:24.546801: Current learning rate: 0.00572 +2024-11-22 06:33:43.286197: train_loss -0.7804 +2024-11-22 06:33:43.286446: val_loss -0.7735 +2024-11-22 06:33:43.286522: Pseudo dice [0.8483] +2024-11-22 06:33:43.286602: Epoch time: 18.74 s +2024-11-22 06:33:44.399055: +2024-11-22 06:33:44.399271: Epoch 3700 +2024-11-22 06:33:44.399384: Current learning rate: 0.00572 +2024-11-22 06:34:02.681571: train_loss -0.7775 +2024-11-22 06:34:02.681800: val_loss -0.7839 +2024-11-22 06:34:02.681884: Pseudo dice [0.8515] +2024-11-22 06:34:02.681983: Epoch time: 18.28 s +2024-11-22 06:34:03.552605: +2024-11-22 06:34:03.552825: Epoch 3701 +2024-11-22 06:34:03.552934: Current learning rate: 0.00572 +2024-11-22 06:34:22.232831: train_loss -0.7946 +2024-11-22 06:34:22.233281: val_loss -0.7698 +2024-11-22 06:34:22.233385: Pseudo dice [0.85] +2024-11-22 06:34:22.233468: Epoch time: 18.68 s +2024-11-22 06:34:23.103758: +2024-11-22 06:34:23.103986: Epoch 3702 +2024-11-22 06:34:23.104102: Current learning rate: 0.00572 +2024-11-22 06:34:41.189013: train_loss -0.7805 +2024-11-22 06:34:41.194417: val_loss -0.7656 +2024-11-22 06:34:41.194588: Pseudo dice [0.859] +2024-11-22 06:34:41.194682: Epoch time: 18.09 s +2024-11-22 06:34:42.196441: +2024-11-22 06:34:42.196672: Epoch 3703 +2024-11-22 06:34:42.196785: Current learning rate: 0.00572 +2024-11-22 06:35:00.260533: train_loss -0.7767 +2024-11-22 06:35:00.261525: val_loss -0.7676 +2024-11-22 06:35:00.261601: Pseudo dice [0.8342] +2024-11-22 06:35:00.261678: Epoch time: 18.06 s +2024-11-22 06:35:01.128909: +2024-11-22 06:35:01.129135: Epoch 3704 +2024-11-22 06:35:01.129244: Current learning rate: 0.00571 +2024-11-22 06:35:20.578889: train_loss -0.7815 +2024-11-22 06:35:20.579110: val_loss -0.7745 +2024-11-22 06:35:20.579193: Pseudo dice [0.8285] +2024-11-22 06:35:20.579282: Epoch time: 19.45 s +2024-11-22 06:35:21.458946: +2024-11-22 06:35:21.459197: Epoch 3705 +2024-11-22 06:35:21.459312: Current learning rate: 0.00571 +2024-11-22 06:35:39.522289: train_loss -0.7876 +2024-11-22 06:35:39.522529: val_loss -0.7497 +2024-11-22 06:35:39.522605: Pseudo dice [0.8328] +2024-11-22 06:35:39.522688: Epoch time: 18.06 s +2024-11-22 06:35:40.394425: +2024-11-22 06:35:40.394632: Epoch 3706 +2024-11-22 06:35:40.394741: Current learning rate: 0.00571 +2024-11-22 06:36:00.069360: train_loss -0.7751 +2024-11-22 06:36:00.069605: val_loss -0.6925 +2024-11-22 06:36:00.069689: Pseudo dice [0.8132] +2024-11-22 06:36:00.069769: Epoch time: 19.68 s +2024-11-22 06:36:01.001350: +2024-11-22 06:36:01.001572: Epoch 3707 +2024-11-22 06:36:01.001678: Current learning rate: 0.00571 +2024-11-22 06:36:18.823441: train_loss -0.7348 +2024-11-22 06:36:18.823691: val_loss -0.764 +2024-11-22 06:36:18.823767: Pseudo dice [0.8447] +2024-11-22 06:36:18.823842: Epoch time: 17.82 s +2024-11-22 06:36:19.945590: +2024-11-22 06:36:19.945808: Epoch 3708 +2024-11-22 06:36:19.945917: Current learning rate: 0.00571 +2024-11-22 06:36:38.487073: train_loss -0.7361 +2024-11-22 06:36:38.489475: val_loss -0.7598 +2024-11-22 06:36:38.489566: Pseudo dice [0.8428] +2024-11-22 06:36:38.489646: Epoch time: 18.54 s +2024-11-22 06:36:39.467940: +2024-11-22 06:36:39.468190: Epoch 3709 +2024-11-22 06:36:39.468310: Current learning rate: 0.00571 +2024-11-22 06:36:58.141340: train_loss -0.7632 +2024-11-22 06:36:58.141558: val_loss -0.7583 +2024-11-22 06:36:58.141635: Pseudo dice [0.8504] +2024-11-22 06:36:58.141715: Epoch time: 18.67 s +2024-11-22 06:36:59.014175: +2024-11-22 06:36:59.014392: Epoch 3710 +2024-11-22 06:36:59.014501: Current learning rate: 0.00571 +2024-11-22 06:37:17.581691: train_loss -0.7812 +2024-11-22 06:37:17.581977: val_loss -0.7549 +2024-11-22 06:37:17.582065: Pseudo dice [0.843] +2024-11-22 06:37:17.582140: Epoch time: 18.57 s +2024-11-22 06:37:18.461124: +2024-11-22 06:37:18.461396: Epoch 3711 +2024-11-22 06:37:18.461509: Current learning rate: 0.00571 +2024-11-22 06:37:37.552418: train_loss -0.7819 +2024-11-22 06:37:37.552647: val_loss -0.7638 +2024-11-22 06:37:37.552729: Pseudo dice [0.8485] +2024-11-22 06:37:37.552809: Epoch time: 19.09 s +2024-11-22 06:37:38.424227: +2024-11-22 06:37:38.424443: Epoch 3712 +2024-11-22 06:37:38.424552: Current learning rate: 0.0057 +2024-11-22 06:37:57.604765: train_loss -0.7786 +2024-11-22 06:37:57.605014: val_loss -0.7594 +2024-11-22 06:37:57.605098: Pseudo dice [0.8432] +2024-11-22 06:37:57.605177: Epoch time: 19.18 s +2024-11-22 06:37:58.833157: +2024-11-22 06:37:58.833375: Epoch 3713 +2024-11-22 06:37:58.833483: Current learning rate: 0.0057 +2024-11-22 06:38:17.253982: train_loss -0.7837 +2024-11-22 06:38:17.254279: val_loss -0.7595 +2024-11-22 06:38:17.254359: Pseudo dice [0.8224] +2024-11-22 06:38:17.254438: Epoch time: 18.42 s +2024-11-22 06:38:18.130987: +2024-11-22 06:38:18.131222: Epoch 3714 +2024-11-22 06:38:18.131330: Current learning rate: 0.0057 +2024-11-22 06:38:36.179345: train_loss -0.7741 +2024-11-22 06:38:36.179564: val_loss -0.7832 +2024-11-22 06:38:36.179640: Pseudo dice [0.8535] +2024-11-22 06:38:36.179723: Epoch time: 18.05 s +2024-11-22 06:38:37.041335: +2024-11-22 06:38:37.041566: Epoch 3715 +2024-11-22 06:38:37.041678: Current learning rate: 0.0057 +2024-11-22 06:38:54.618013: train_loss -0.7841 +2024-11-22 06:38:54.618267: val_loss -0.7611 +2024-11-22 06:38:54.618342: Pseudo dice [0.8573] +2024-11-22 06:38:54.618424: Epoch time: 17.58 s +2024-11-22 06:38:55.489676: +2024-11-22 06:38:55.489936: Epoch 3716 +2024-11-22 06:38:55.490053: Current learning rate: 0.0057 +2024-11-22 06:39:12.918163: train_loss -0.779 +2024-11-22 06:39:12.918394: val_loss -0.7628 +2024-11-22 06:39:12.918470: Pseudo dice [0.8399] +2024-11-22 06:39:12.918546: Epoch time: 17.43 s +2024-11-22 06:39:13.787639: +2024-11-22 06:39:13.788154: Epoch 3717 +2024-11-22 06:39:13.788282: Current learning rate: 0.0057 +2024-11-22 06:39:32.433112: train_loss -0.7686 +2024-11-22 06:39:32.435490: val_loss -0.7738 +2024-11-22 06:39:32.435611: Pseudo dice [0.8438] +2024-11-22 06:39:32.435689: Epoch time: 18.65 s +2024-11-22 06:39:33.357022: +2024-11-22 06:39:33.357235: Epoch 3718 +2024-11-22 06:39:33.357346: Current learning rate: 0.0057 +2024-11-22 06:39:51.393565: train_loss -0.7869 +2024-11-22 06:39:51.393785: val_loss -0.7261 +2024-11-22 06:39:51.393867: Pseudo dice [0.8341] +2024-11-22 06:39:51.393942: Epoch time: 18.04 s +2024-11-22 06:39:52.259665: +2024-11-22 06:39:52.259983: Epoch 3719 +2024-11-22 06:39:52.260101: Current learning rate: 0.0057 +2024-11-22 06:40:10.954036: train_loss -0.772 +2024-11-22 06:40:10.954284: val_loss -0.7502 +2024-11-22 06:40:10.954358: Pseudo dice [0.8415] +2024-11-22 06:40:10.954445: Epoch time: 18.7 s +2024-11-22 06:40:11.855181: +2024-11-22 06:40:11.855373: Epoch 3720 +2024-11-22 06:40:11.855579: Current learning rate: 0.0057 +2024-11-22 06:40:30.171360: train_loss -0.7832 +2024-11-22 06:40:30.171567: val_loss -0.7608 +2024-11-22 06:40:30.171639: Pseudo dice [0.8235] +2024-11-22 06:40:30.171712: Epoch time: 18.32 s +2024-11-22 06:40:31.040503: +2024-11-22 06:40:31.040707: Epoch 3721 +2024-11-22 06:40:31.040815: Current learning rate: 0.00569 +2024-11-22 06:40:49.394124: train_loss -0.7696 +2024-11-22 06:40:49.394338: val_loss -0.7536 +2024-11-22 06:40:49.394413: Pseudo dice [0.8499] +2024-11-22 06:40:49.394487: Epoch time: 18.35 s +2024-11-22 06:40:50.259187: +2024-11-22 06:40:50.259392: Epoch 3722 +2024-11-22 06:40:50.259501: Current learning rate: 0.00569 +2024-11-22 06:41:07.941150: train_loss -0.7758 +2024-11-22 06:41:07.941381: val_loss -0.761 +2024-11-22 06:41:07.941457: Pseudo dice [0.8261] +2024-11-22 06:41:07.941531: Epoch time: 17.68 s +2024-11-22 06:41:08.812921: +2024-11-22 06:41:08.813164: Epoch 3723 +2024-11-22 06:41:08.813284: Current learning rate: 0.00569 +2024-11-22 06:41:27.603273: train_loss -0.7815 +2024-11-22 06:41:27.603506: val_loss -0.7632 +2024-11-22 06:41:27.603581: Pseudo dice [0.8358] +2024-11-22 06:41:27.603658: Epoch time: 18.79 s +2024-11-22 06:41:28.851850: +2024-11-22 06:41:28.852081: Epoch 3724 +2024-11-22 06:41:28.852190: Current learning rate: 0.00569 +2024-11-22 06:41:47.619761: train_loss -0.7793 +2024-11-22 06:41:47.620033: val_loss -0.7481 +2024-11-22 06:41:47.620112: Pseudo dice [0.8347] +2024-11-22 06:41:47.620205: Epoch time: 18.77 s +2024-11-22 06:41:48.493782: +2024-11-22 06:41:48.494015: Epoch 3725 +2024-11-22 06:41:48.494150: Current learning rate: 0.00569 +2024-11-22 06:42:06.333545: train_loss -0.7851 +2024-11-22 06:42:06.333786: val_loss -0.7701 +2024-11-22 06:42:06.333863: Pseudo dice [0.8605] +2024-11-22 06:42:06.333940: Epoch time: 17.84 s +2024-11-22 06:42:07.211503: +2024-11-22 06:42:07.211719: Epoch 3726 +2024-11-22 06:42:07.211844: Current learning rate: 0.00569 +2024-11-22 06:42:25.477087: train_loss -0.7812 +2024-11-22 06:42:25.477329: val_loss -0.746 +2024-11-22 06:42:25.477406: Pseudo dice [0.8435] +2024-11-22 06:42:25.477486: Epoch time: 18.27 s +2024-11-22 06:42:26.343644: +2024-11-22 06:42:26.343863: Epoch 3727 +2024-11-22 06:42:26.343971: Current learning rate: 0.00569 +2024-11-22 06:42:44.521428: train_loss -0.7831 +2024-11-22 06:42:44.521648: val_loss -0.7669 +2024-11-22 06:42:44.521726: Pseudo dice [0.8521] +2024-11-22 06:42:44.521804: Epoch time: 18.18 s +2024-11-22 06:42:45.393627: +2024-11-22 06:42:45.393852: Epoch 3728 +2024-11-22 06:42:45.393959: Current learning rate: 0.00569 +2024-11-22 06:43:04.485318: train_loss -0.7897 +2024-11-22 06:43:04.485546: val_loss -0.7733 +2024-11-22 06:43:04.485618: Pseudo dice [0.8303] +2024-11-22 06:43:04.485694: Epoch time: 19.09 s +2024-11-22 06:43:05.391638: +2024-11-22 06:43:05.391892: Epoch 3729 +2024-11-22 06:43:05.392008: Current learning rate: 0.00568 +2024-11-22 06:43:24.444018: train_loss -0.7858 +2024-11-22 06:43:24.444242: val_loss -0.7669 +2024-11-22 06:43:24.444319: Pseudo dice [0.8332] +2024-11-22 06:43:24.444394: Epoch time: 19.05 s +2024-11-22 06:43:25.315668: +2024-11-22 06:43:25.315901: Epoch 3730 +2024-11-22 06:43:25.316019: Current learning rate: 0.00568 +2024-11-22 06:43:44.183916: train_loss -0.7734 +2024-11-22 06:43:44.184173: val_loss -0.7657 +2024-11-22 06:43:44.184255: Pseudo dice [0.844] +2024-11-22 06:43:44.184345: Epoch time: 18.87 s +2024-11-22 06:43:45.060417: +2024-11-22 06:43:45.060630: Epoch 3731 +2024-11-22 06:43:45.060743: Current learning rate: 0.00568 +2024-11-22 06:44:03.563396: train_loss -0.7782 +2024-11-22 06:44:03.563610: val_loss -0.7876 +2024-11-22 06:44:03.563684: Pseudo dice [0.8462] +2024-11-22 06:44:03.563757: Epoch time: 18.5 s +2024-11-22 06:44:04.432568: +2024-11-22 06:44:04.432796: Epoch 3732 +2024-11-22 06:44:04.432903: Current learning rate: 0.00568 +2024-11-22 06:44:21.907317: train_loss -0.783 +2024-11-22 06:44:21.907534: val_loss -0.7694 +2024-11-22 06:44:21.907626: Pseudo dice [0.8498] +2024-11-22 06:44:21.907773: Epoch time: 17.48 s +2024-11-22 06:44:22.779444: +2024-11-22 06:44:22.779661: Epoch 3733 +2024-11-22 06:44:22.779771: Current learning rate: 0.00568 +2024-11-22 06:44:41.643556: train_loss -0.7768 +2024-11-22 06:44:41.643794: val_loss -0.761 +2024-11-22 06:44:41.643869: Pseudo dice [0.8417] +2024-11-22 06:44:41.643950: Epoch time: 18.86 s +2024-11-22 06:44:42.508600: +2024-11-22 06:44:42.509029: Epoch 3734 +2024-11-22 06:44:42.509160: Current learning rate: 0.00568 +2024-11-22 06:44:59.524630: train_loss -0.7808 +2024-11-22 06:44:59.524849: val_loss -0.7499 +2024-11-22 06:44:59.524925: Pseudo dice [0.8481] +2024-11-22 06:44:59.525008: Epoch time: 17.02 s +2024-11-22 06:45:00.435039: +2024-11-22 06:45:00.435276: Epoch 3735 +2024-11-22 06:45:00.435390: Current learning rate: 0.00568 +2024-11-22 06:45:19.609727: train_loss -0.7894 +2024-11-22 06:45:19.609945: val_loss -0.7438 +2024-11-22 06:45:19.610024: Pseudo dice [0.8319] +2024-11-22 06:45:19.610101: Epoch time: 19.18 s +2024-11-22 06:45:20.839073: +2024-11-22 06:45:20.839326: Epoch 3736 +2024-11-22 06:45:20.839438: Current learning rate: 0.00568 +2024-11-22 06:45:39.869412: train_loss -0.7805 +2024-11-22 06:45:39.869682: val_loss -0.7774 +2024-11-22 06:45:39.869759: Pseudo dice [0.8394] +2024-11-22 06:45:39.869848: Epoch time: 19.03 s +2024-11-22 06:45:40.765636: +2024-11-22 06:45:40.765870: Epoch 3737 +2024-11-22 06:45:40.765979: Current learning rate: 0.00567 +2024-11-22 06:45:58.653027: train_loss -0.7845 +2024-11-22 06:45:58.653306: val_loss -0.7935 +2024-11-22 06:45:58.653413: Pseudo dice [0.8557] +2024-11-22 06:45:58.653487: Epoch time: 17.89 s +2024-11-22 06:45:59.531209: +2024-11-22 06:45:59.531441: Epoch 3738 +2024-11-22 06:45:59.531546: Current learning rate: 0.00567 +2024-11-22 06:46:17.399952: train_loss -0.7807 +2024-11-22 06:46:17.400223: val_loss -0.7543 +2024-11-22 06:46:17.400301: Pseudo dice [0.8335] +2024-11-22 06:46:17.400376: Epoch time: 17.87 s +2024-11-22 06:46:18.277402: +2024-11-22 06:46:18.277615: Epoch 3739 +2024-11-22 06:46:18.277723: Current learning rate: 0.00567 +2024-11-22 06:46:37.614120: train_loss -0.7778 +2024-11-22 06:46:37.614347: val_loss -0.7769 +2024-11-22 06:46:37.614422: Pseudo dice [0.841] +2024-11-22 06:46:37.614496: Epoch time: 19.34 s +2024-11-22 06:46:38.488035: +2024-11-22 06:46:38.488259: Epoch 3740 +2024-11-22 06:46:38.488374: Current learning rate: 0.00567 +2024-11-22 06:46:57.678695: train_loss -0.7833 +2024-11-22 06:46:57.678936: val_loss -0.7646 +2024-11-22 06:46:57.679018: Pseudo dice [0.8487] +2024-11-22 06:46:57.679099: Epoch time: 19.19 s +2024-11-22 06:46:58.549834: +2024-11-22 06:46:58.550082: Epoch 3741 +2024-11-22 06:46:58.550186: Current learning rate: 0.00567 +2024-11-22 06:47:17.096383: train_loss -0.7799 +2024-11-22 06:47:17.096593: val_loss -0.771 +2024-11-22 06:47:17.096665: Pseudo dice [0.8426] +2024-11-22 06:47:17.096812: Epoch time: 18.55 s +2024-11-22 06:47:18.073648: +2024-11-22 06:47:18.073885: Epoch 3742 +2024-11-22 06:47:18.074003: Current learning rate: 0.00567 +2024-11-22 06:47:37.235701: train_loss -0.7767 +2024-11-22 06:47:37.235951: val_loss -0.7771 +2024-11-22 06:47:37.236034: Pseudo dice [0.849] +2024-11-22 06:47:37.236108: Epoch time: 19.16 s +2024-11-22 06:47:38.114400: +2024-11-22 06:47:38.114628: Epoch 3743 +2024-11-22 06:47:38.114739: Current learning rate: 0.00567 +2024-11-22 06:47:55.684309: train_loss -0.7927 +2024-11-22 06:47:55.684525: val_loss -0.788 +2024-11-22 06:47:55.684601: Pseudo dice [0.8462] +2024-11-22 06:47:55.684681: Epoch time: 17.57 s +2024-11-22 06:47:56.551959: +2024-11-22 06:47:56.552169: Epoch 3744 +2024-11-22 06:47:56.552275: Current learning rate: 0.00567 +2024-11-22 06:48:14.514564: train_loss -0.7942 +2024-11-22 06:48:14.514866: val_loss -0.7643 +2024-11-22 06:48:14.514941: Pseudo dice [0.8374] +2024-11-22 06:48:14.515028: Epoch time: 17.96 s +2024-11-22 06:48:15.385607: +2024-11-22 06:48:15.385821: Epoch 3745 +2024-11-22 06:48:15.385930: Current learning rate: 0.00567 +2024-11-22 06:48:33.197740: train_loss -0.7875 +2024-11-22 06:48:33.197959: val_loss -0.7453 +2024-11-22 06:48:33.198037: Pseudo dice [0.837] +2024-11-22 06:48:33.198113: Epoch time: 17.81 s +2024-11-22 06:48:34.066375: +2024-11-22 06:48:34.066572: Epoch 3746 +2024-11-22 06:48:34.066681: Current learning rate: 0.00566 +2024-11-22 06:48:52.796958: train_loss -0.7832 +2024-11-22 06:48:52.797195: val_loss -0.7544 +2024-11-22 06:48:52.797274: Pseudo dice [0.8421] +2024-11-22 06:48:52.797356: Epoch time: 18.73 s +2024-11-22 06:48:54.130728: +2024-11-22 06:48:54.130941: Epoch 3747 +2024-11-22 06:48:54.131060: Current learning rate: 0.00566 +2024-11-22 06:49:12.846603: train_loss -0.7782 +2024-11-22 06:49:12.851695: val_loss -0.7765 +2024-11-22 06:49:12.851805: Pseudo dice [0.8326] +2024-11-22 06:49:12.851891: Epoch time: 18.72 s +2024-11-22 06:49:13.739144: +2024-11-22 06:49:13.739359: Epoch 3748 +2024-11-22 06:49:13.739465: Current learning rate: 0.00566 +2024-11-22 06:49:33.454190: train_loss -0.795 +2024-11-22 06:49:33.454410: val_loss -0.7788 +2024-11-22 06:49:33.454491: Pseudo dice [0.8506] +2024-11-22 06:49:33.454569: Epoch time: 19.72 s +2024-11-22 06:49:34.328577: +2024-11-22 06:49:34.328818: Epoch 3749 +2024-11-22 06:49:34.328929: Current learning rate: 0.00566 +2024-11-22 06:49:53.580259: train_loss -0.7801 +2024-11-22 06:49:53.580485: val_loss -0.7467 +2024-11-22 06:49:53.580560: Pseudo dice [0.8614] +2024-11-22 06:49:53.580637: Epoch time: 19.25 s +2024-11-22 06:49:54.706568: +2024-11-22 06:49:54.706809: Epoch 3750 +2024-11-22 06:49:54.706921: Current learning rate: 0.00566 +2024-11-22 06:50:12.575798: train_loss -0.7889 +2024-11-22 06:50:12.576043: val_loss -0.7636 +2024-11-22 06:50:12.576121: Pseudo dice [0.8491] +2024-11-22 06:50:12.576199: Epoch time: 17.87 s +2024-11-22 06:50:13.455468: +2024-11-22 06:50:13.455687: Epoch 3751 +2024-11-22 06:50:13.455796: Current learning rate: 0.00566 +2024-11-22 06:50:31.927499: train_loss -0.7822 +2024-11-22 06:50:31.927745: val_loss -0.7623 +2024-11-22 06:50:31.927820: Pseudo dice [0.8318] +2024-11-22 06:50:31.927902: Epoch time: 18.47 s +2024-11-22 06:50:32.803589: +2024-11-22 06:50:32.803818: Epoch 3752 +2024-11-22 06:50:32.803930: Current learning rate: 0.00566 +2024-11-22 06:50:51.118701: train_loss -0.7986 +2024-11-22 06:50:51.118920: val_loss -0.7646 +2024-11-22 06:50:51.119037: Pseudo dice [0.8346] +2024-11-22 06:50:51.119112: Epoch time: 18.32 s +2024-11-22 06:50:52.002393: +2024-11-22 06:50:52.002607: Epoch 3753 +2024-11-22 06:50:52.002721: Current learning rate: 0.00566 +2024-11-22 06:51:11.803726: train_loss -0.7773 +2024-11-22 06:51:11.804943: val_loss -0.7468 +2024-11-22 06:51:11.805042: Pseudo dice [0.8338] +2024-11-22 06:51:11.805120: Epoch time: 19.8 s +2024-11-22 06:51:12.755771: +2024-11-22 06:51:12.756009: Epoch 3754 +2024-11-22 06:51:12.756123: Current learning rate: 0.00565 +2024-11-22 06:51:31.387073: train_loss -0.7924 +2024-11-22 06:51:31.387320: val_loss -0.7784 +2024-11-22 06:51:31.387395: Pseudo dice [0.8393] +2024-11-22 06:51:31.387482: Epoch time: 18.63 s +2024-11-22 06:51:32.258375: +2024-11-22 06:51:32.258587: Epoch 3755 +2024-11-22 06:51:32.258696: Current learning rate: 0.00565 +2024-11-22 06:51:50.130831: train_loss -0.7921 +2024-11-22 06:51:50.131060: val_loss -0.7523 +2024-11-22 06:51:50.131139: Pseudo dice [0.8332] +2024-11-22 06:51:50.131215: Epoch time: 17.87 s +2024-11-22 06:51:51.021456: +2024-11-22 06:51:51.021684: Epoch 3756 +2024-11-22 06:51:51.021805: Current learning rate: 0.00565 +2024-11-22 06:52:09.448010: train_loss -0.7831 +2024-11-22 06:52:09.448236: val_loss -0.7697 +2024-11-22 06:52:09.448309: Pseudo dice [0.8513] +2024-11-22 06:52:09.448382: Epoch time: 18.43 s +2024-11-22 06:52:10.324199: +2024-11-22 06:52:10.324414: Epoch 3757 +2024-11-22 06:52:10.324526: Current learning rate: 0.00565 +2024-11-22 06:52:28.214368: train_loss -0.7796 +2024-11-22 06:52:28.216578: val_loss -0.7638 +2024-11-22 06:52:28.216685: Pseudo dice [0.8448] +2024-11-22 06:52:28.216771: Epoch time: 17.89 s +2024-11-22 06:52:29.270481: +2024-11-22 06:52:29.270720: Epoch 3758 +2024-11-22 06:52:29.270832: Current learning rate: 0.00565 +2024-11-22 06:52:48.006114: train_loss -0.7879 +2024-11-22 06:52:48.006431: val_loss -0.7737 +2024-11-22 06:52:48.006509: Pseudo dice [0.8496] +2024-11-22 06:52:48.006587: Epoch time: 18.74 s +2024-11-22 06:52:49.310056: +2024-11-22 06:52:49.310364: Epoch 3759 +2024-11-22 06:52:49.310478: Current learning rate: 0.00565 +2024-11-22 06:53:07.198107: train_loss -0.7861 +2024-11-22 06:53:07.198332: val_loss -0.7811 +2024-11-22 06:53:07.198408: Pseudo dice [0.8595] +2024-11-22 06:53:07.198484: Epoch time: 17.89 s +2024-11-22 06:53:08.071260: +2024-11-22 06:53:08.071493: Epoch 3760 +2024-11-22 06:53:08.071609: Current learning rate: 0.00565 +2024-11-22 06:53:26.923812: train_loss -0.7817 +2024-11-22 06:53:26.924031: val_loss -0.7749 +2024-11-22 06:53:26.924110: Pseudo dice [0.841] +2024-11-22 06:53:26.924191: Epoch time: 18.85 s +2024-11-22 06:53:27.797692: +2024-11-22 06:53:27.797923: Epoch 3761 +2024-11-22 06:53:27.798039: Current learning rate: 0.00565 +2024-11-22 06:53:45.982308: train_loss -0.789 +2024-11-22 06:53:45.982607: val_loss -0.778 +2024-11-22 06:53:45.982690: Pseudo dice [0.8533] +2024-11-22 06:53:45.982773: Epoch time: 18.19 s +2024-11-22 06:53:46.856762: +2024-11-22 06:53:46.856981: Epoch 3762 +2024-11-22 06:53:46.857094: Current learning rate: 0.00564 +2024-11-22 06:54:05.604723: train_loss -0.764 +2024-11-22 06:54:05.604926: val_loss -0.7746 +2024-11-22 06:54:05.605012: Pseudo dice [0.8506] +2024-11-22 06:54:05.605087: Epoch time: 18.75 s +2024-11-22 06:54:06.519187: +2024-11-22 06:54:06.519455: Epoch 3763 +2024-11-22 06:54:06.519577: Current learning rate: 0.00564 +2024-11-22 06:54:24.287393: train_loss -0.7872 +2024-11-22 06:54:24.287648: val_loss -0.7676 +2024-11-22 06:54:24.287724: Pseudo dice [0.8434] +2024-11-22 06:54:24.287798: Epoch time: 17.77 s +2024-11-22 06:54:25.156934: +2024-11-22 06:54:25.157165: Epoch 3764 +2024-11-22 06:54:25.157276: Current learning rate: 0.00564 +2024-11-22 06:54:43.928782: train_loss -0.7728 +2024-11-22 06:54:43.929016: val_loss -0.7772 +2024-11-22 06:54:43.929096: Pseudo dice [0.8575] +2024-11-22 06:54:43.929176: Epoch time: 18.77 s +2024-11-22 06:54:44.802427: +2024-11-22 06:54:44.802650: Epoch 3765 +2024-11-22 06:54:44.802760: Current learning rate: 0.00564 +2024-11-22 06:55:03.523689: train_loss -0.7856 +2024-11-22 06:55:03.524674: val_loss -0.7956 +2024-11-22 06:55:03.524769: Pseudo dice [0.8628] +2024-11-22 06:55:03.524859: Epoch time: 18.72 s +2024-11-22 06:55:04.403488: +2024-11-22 06:55:04.403709: Epoch 3766 +2024-11-22 06:55:04.403823: Current learning rate: 0.00564 +2024-11-22 06:55:22.741353: train_loss -0.7775 +2024-11-22 06:55:22.741589: val_loss -0.7455 +2024-11-22 06:55:22.741669: Pseudo dice [0.8269] +2024-11-22 06:55:22.741750: Epoch time: 18.34 s +2024-11-22 06:55:23.613438: +2024-11-22 06:55:23.613653: Epoch 3767 +2024-11-22 06:55:23.613757: Current learning rate: 0.00564 +2024-11-22 06:55:41.388393: train_loss -0.7759 +2024-11-22 06:55:41.388642: val_loss -0.7651 +2024-11-22 06:55:41.388719: Pseudo dice [0.849] +2024-11-22 06:55:41.388814: Epoch time: 17.78 s +2024-11-22 06:55:42.257928: +2024-11-22 06:55:42.258211: Epoch 3768 +2024-11-22 06:55:42.258325: Current learning rate: 0.00564 +2024-11-22 06:56:01.353060: train_loss -0.7801 +2024-11-22 06:56:01.353273: val_loss -0.7541 +2024-11-22 06:56:01.353353: Pseudo dice [0.8337] +2024-11-22 06:56:01.353432: Epoch time: 19.1 s +2024-11-22 06:56:02.223502: +2024-11-22 06:56:02.223773: Epoch 3769 +2024-11-22 06:56:02.223921: Current learning rate: 0.00564 +2024-11-22 06:56:21.562814: train_loss -0.7809 +2024-11-22 06:56:21.563033: val_loss -0.7656 +2024-11-22 06:56:21.563108: Pseudo dice [0.8617] +2024-11-22 06:56:21.563186: Epoch time: 19.34 s +2024-11-22 06:56:22.832722: +2024-11-22 06:56:22.832932: Epoch 3770 +2024-11-22 06:56:22.833042: Current learning rate: 0.00564 +2024-11-22 06:56:41.084701: train_loss -0.7873 +2024-11-22 06:56:41.084925: val_loss -0.7691 +2024-11-22 06:56:41.085009: Pseudo dice [0.8293] +2024-11-22 06:56:41.085086: Epoch time: 18.25 s +2024-11-22 06:56:41.946771: +2024-11-22 06:56:41.947028: Epoch 3771 +2024-11-22 06:56:41.947159: Current learning rate: 0.00563 +2024-11-22 06:57:00.000089: train_loss -0.7658 +2024-11-22 06:57:00.000311: val_loss -0.7789 +2024-11-22 06:57:00.000397: Pseudo dice [0.8237] +2024-11-22 06:57:00.000493: Epoch time: 18.05 s +2024-11-22 06:57:00.868973: +2024-11-22 06:57:00.869210: Epoch 3772 +2024-11-22 06:57:00.869324: Current learning rate: 0.00563 +2024-11-22 06:57:19.848948: train_loss -0.7692 +2024-11-22 06:57:19.849191: val_loss -0.7753 +2024-11-22 06:57:19.849272: Pseudo dice [0.8325] +2024-11-22 06:57:19.849350: Epoch time: 18.98 s +2024-11-22 06:57:20.717660: +2024-11-22 06:57:20.717906: Epoch 3773 +2024-11-22 06:57:20.718028: Current learning rate: 0.00563 +2024-11-22 06:57:38.832598: train_loss -0.771 +2024-11-22 06:57:38.832824: val_loss -0.7913 +2024-11-22 06:57:38.832900: Pseudo dice [0.8387] +2024-11-22 06:57:38.832983: Epoch time: 18.12 s +2024-11-22 06:57:39.707331: +2024-11-22 06:57:39.707538: Epoch 3774 +2024-11-22 06:57:39.707645: Current learning rate: 0.00563 +2024-11-22 06:57:58.200612: train_loss -0.7858 +2024-11-22 06:57:58.200834: val_loss -0.7495 +2024-11-22 06:57:58.200914: Pseudo dice [0.8467] +2024-11-22 06:57:58.201001: Epoch time: 18.49 s +2024-11-22 06:57:59.086290: +2024-11-22 06:57:59.086508: Epoch 3775 +2024-11-22 06:57:59.086619: Current learning rate: 0.00563 +2024-11-22 06:58:18.018772: train_loss -0.7722 +2024-11-22 06:58:18.018981: val_loss -0.7664 +2024-11-22 06:58:18.019060: Pseudo dice [0.8284] +2024-11-22 06:58:18.019133: Epoch time: 18.93 s +2024-11-22 06:58:18.895389: +2024-11-22 06:58:18.895633: Epoch 3776 +2024-11-22 06:58:18.895768: Current learning rate: 0.00563 +2024-11-22 06:58:36.924809: train_loss -0.7852 +2024-11-22 06:58:36.925059: val_loss -0.7649 +2024-11-22 06:58:36.925137: Pseudo dice [0.8422] +2024-11-22 06:58:36.925218: Epoch time: 18.03 s +2024-11-22 06:58:37.789429: +2024-11-22 06:58:37.789636: Epoch 3777 +2024-11-22 06:58:37.789752: Current learning rate: 0.00563 +2024-11-22 06:58:56.979271: train_loss -0.7812 +2024-11-22 06:58:56.981670: val_loss -0.7808 +2024-11-22 06:58:56.981767: Pseudo dice [0.8562] +2024-11-22 06:58:56.981846: Epoch time: 19.19 s +2024-11-22 06:58:57.962331: +2024-11-22 06:58:57.962571: Epoch 3778 +2024-11-22 06:58:57.962679: Current learning rate: 0.00563 +2024-11-22 06:59:16.118374: train_loss -0.7994 +2024-11-22 06:59:16.118644: val_loss -0.7709 +2024-11-22 06:59:16.118725: Pseudo dice [0.8378] +2024-11-22 06:59:16.118799: Epoch time: 18.16 s +2024-11-22 06:59:16.988095: +2024-11-22 06:59:16.988322: Epoch 3779 +2024-11-22 06:59:16.988434: Current learning rate: 0.00562 +2024-11-22 06:59:35.192265: train_loss -0.782 +2024-11-22 06:59:35.192520: val_loss -0.7618 +2024-11-22 06:59:35.192597: Pseudo dice [0.8457] +2024-11-22 06:59:35.192683: Epoch time: 18.2 s +2024-11-22 06:59:36.065342: +2024-11-22 06:59:36.065565: Epoch 3780 +2024-11-22 06:59:36.065675: Current learning rate: 0.00562 +2024-11-22 06:59:54.255352: train_loss -0.7832 +2024-11-22 06:59:54.255636: val_loss -0.7637 +2024-11-22 06:59:54.255717: Pseudo dice [0.8462] +2024-11-22 06:59:54.255796: Epoch time: 18.19 s +2024-11-22 06:59:55.125989: +2024-11-22 06:59:55.126191: Epoch 3781 +2024-11-22 06:59:55.126299: Current learning rate: 0.00562 +2024-11-22 07:00:14.790627: train_loss -0.7898 +2024-11-22 07:00:14.790857: val_loss -0.7595 +2024-11-22 07:00:14.790931: Pseudo dice [0.8451] +2024-11-22 07:00:14.796170: Epoch time: 19.67 s +2024-11-22 07:00:16.123176: +2024-11-22 07:00:16.123408: Epoch 3782 +2024-11-22 07:00:16.123521: Current learning rate: 0.00562 +2024-11-22 07:00:33.974964: train_loss -0.7839 +2024-11-22 07:00:33.975230: val_loss -0.7751 +2024-11-22 07:00:33.975311: Pseudo dice [0.8371] +2024-11-22 07:00:33.975396: Epoch time: 17.85 s +2024-11-22 07:00:34.933114: +2024-11-22 07:00:34.933340: Epoch 3783 +2024-11-22 07:00:34.933451: Current learning rate: 0.00562 +2024-11-22 07:00:54.026964: train_loss -0.7928 +2024-11-22 07:00:54.027185: val_loss -0.7658 +2024-11-22 07:00:54.027263: Pseudo dice [0.8508] +2024-11-22 07:00:54.027345: Epoch time: 19.09 s +2024-11-22 07:00:54.890278: +2024-11-22 07:00:54.890507: Epoch 3784 +2024-11-22 07:00:54.890617: Current learning rate: 0.00562 +2024-11-22 07:01:12.599714: train_loss -0.7789 +2024-11-22 07:01:12.599988: val_loss -0.7448 +2024-11-22 07:01:12.600071: Pseudo dice [0.8256] +2024-11-22 07:01:12.600147: Epoch time: 17.71 s +2024-11-22 07:01:13.473888: +2024-11-22 07:01:13.474121: Epoch 3785 +2024-11-22 07:01:13.474232: Current learning rate: 0.00562 +2024-11-22 07:01:31.350100: train_loss -0.7923 +2024-11-22 07:01:31.350325: val_loss -0.7795 +2024-11-22 07:01:31.350403: Pseudo dice [0.8549] +2024-11-22 07:01:31.350478: Epoch time: 17.88 s +2024-11-22 07:01:32.256046: +2024-11-22 07:01:32.256253: Epoch 3786 +2024-11-22 07:01:32.256364: Current learning rate: 0.00562 +2024-11-22 07:01:50.828900: train_loss -0.797 +2024-11-22 07:01:50.829158: val_loss -0.7821 +2024-11-22 07:01:50.829237: Pseudo dice [0.8476] +2024-11-22 07:01:50.829318: Epoch time: 18.57 s +2024-11-22 07:01:51.838964: +2024-11-22 07:01:51.839222: Epoch 3787 +2024-11-22 07:01:51.839334: Current learning rate: 0.00562 +2024-11-22 07:02:10.037767: train_loss -0.7978 +2024-11-22 07:02:10.038008: val_loss -0.7532 +2024-11-22 07:02:10.038099: Pseudo dice [0.8585] +2024-11-22 07:02:10.038177: Epoch time: 18.2 s +2024-11-22 07:02:10.913253: +2024-11-22 07:02:10.913486: Epoch 3788 +2024-11-22 07:02:10.913613: Current learning rate: 0.00561 +2024-11-22 07:02:28.601668: train_loss -0.7923 +2024-11-22 07:02:28.601908: val_loss -0.7711 +2024-11-22 07:02:28.601989: Pseudo dice [0.8498] +2024-11-22 07:02:28.602074: Epoch time: 17.69 s +2024-11-22 07:02:29.474329: +2024-11-22 07:02:29.474537: Epoch 3789 +2024-11-22 07:02:29.474643: Current learning rate: 0.00561 +2024-11-22 07:02:47.102599: train_loss -0.7856 +2024-11-22 07:02:47.102862: val_loss -0.7464 +2024-11-22 07:02:47.102937: Pseudo dice [0.843] +2024-11-22 07:02:47.103027: Epoch time: 17.63 s +2024-11-22 07:02:48.180903: +2024-11-22 07:02:48.181125: Epoch 3790 +2024-11-22 07:02:48.181232: Current learning rate: 0.00561 +2024-11-22 07:03:05.867806: train_loss -0.7736 +2024-11-22 07:03:05.868029: val_loss -0.7721 +2024-11-22 07:03:05.868102: Pseudo dice [0.8451] +2024-11-22 07:03:05.868177: Epoch time: 17.69 s +2024-11-22 07:03:06.869648: +2024-11-22 07:03:06.869909: Epoch 3791 +2024-11-22 07:03:06.870025: Current learning rate: 0.00561 +2024-11-22 07:03:25.130987: train_loss -0.7858 +2024-11-22 07:03:25.131217: val_loss -0.7931 +2024-11-22 07:03:25.131292: Pseudo dice [0.8607] +2024-11-22 07:03:25.131367: Epoch time: 18.26 s +2024-11-22 07:03:26.004437: +2024-11-22 07:03:26.004634: Epoch 3792 +2024-11-22 07:03:26.004741: Current learning rate: 0.00561 +2024-11-22 07:03:43.820704: train_loss -0.7922 +2024-11-22 07:03:43.820923: val_loss -0.7864 +2024-11-22 07:03:43.821003: Pseudo dice [0.8494] +2024-11-22 07:03:43.821081: Epoch time: 17.82 s +2024-11-22 07:03:44.701845: +2024-11-22 07:03:44.702075: Epoch 3793 +2024-11-22 07:03:44.702185: Current learning rate: 0.00561 +2024-11-22 07:04:03.336595: train_loss -0.7878 +2024-11-22 07:04:03.337093: val_loss -0.7901 +2024-11-22 07:04:03.337189: Pseudo dice [0.8672] +2024-11-22 07:04:03.337267: Epoch time: 18.64 s +2024-11-22 07:04:04.203797: +2024-11-22 07:04:04.204093: Epoch 3794 +2024-11-22 07:04:04.204206: Current learning rate: 0.00561 +2024-11-22 07:04:23.206110: train_loss -0.7854 +2024-11-22 07:04:23.206324: val_loss -0.7828 +2024-11-22 07:04:23.206397: Pseudo dice [0.8406] +2024-11-22 07:04:23.206551: Epoch time: 19.0 s +2024-11-22 07:04:24.081212: +2024-11-22 07:04:24.081423: Epoch 3795 +2024-11-22 07:04:24.081532: Current learning rate: 0.00561 +2024-11-22 07:04:43.115125: train_loss -0.7881 +2024-11-22 07:04:43.115332: val_loss -0.7745 +2024-11-22 07:04:43.115408: Pseudo dice [0.8507] +2024-11-22 07:04:43.115485: Epoch time: 19.03 s +2024-11-22 07:04:44.022847: +2024-11-22 07:04:44.023062: Epoch 3796 +2024-11-22 07:04:44.023172: Current learning rate: 0.0056 +2024-11-22 07:05:02.189976: train_loss -0.7877 +2024-11-22 07:05:02.191682: val_loss -0.7659 +2024-11-22 07:05:02.191767: Pseudo dice [0.8565] +2024-11-22 07:05:02.191848: Epoch time: 18.17 s +2024-11-22 07:05:03.072687: +2024-11-22 07:05:03.072923: Epoch 3797 +2024-11-22 07:05:03.073039: Current learning rate: 0.0056 +2024-11-22 07:05:21.139408: train_loss -0.7915 +2024-11-22 07:05:21.139632: val_loss -0.787 +2024-11-22 07:05:21.139755: Pseudo dice [0.8355] +2024-11-22 07:05:21.139832: Epoch time: 18.07 s +2024-11-22 07:05:22.014172: +2024-11-22 07:05:22.014662: Epoch 3798 +2024-11-22 07:05:22.014774: Current learning rate: 0.0056 +2024-11-22 07:05:41.085518: train_loss -0.7864 +2024-11-22 07:05:41.085736: val_loss -0.7733 +2024-11-22 07:05:41.085808: Pseudo dice [0.8517] +2024-11-22 07:05:41.085883: Epoch time: 19.07 s +2024-11-22 07:05:41.966788: +2024-11-22 07:05:41.967016: Epoch 3799 +2024-11-22 07:05:41.967126: Current learning rate: 0.0056 +2024-11-22 07:06:00.509457: train_loss -0.7776 +2024-11-22 07:06:00.509684: val_loss -0.7856 +2024-11-22 07:06:00.509761: Pseudo dice [0.8579] +2024-11-22 07:06:00.509840: Epoch time: 18.54 s +2024-11-22 07:06:01.872097: +2024-11-22 07:06:01.872338: Epoch 3800 +2024-11-22 07:06:01.872460: Current learning rate: 0.0056 +2024-11-22 07:06:19.346772: train_loss -0.7859 +2024-11-22 07:06:19.347028: val_loss -0.7668 +2024-11-22 07:06:19.347116: Pseudo dice [0.8465] +2024-11-22 07:06:19.347205: Epoch time: 17.48 s +2024-11-22 07:06:20.228025: +2024-11-22 07:06:20.228291: Epoch 3801 +2024-11-22 07:06:20.228404: Current learning rate: 0.0056 +2024-11-22 07:06:39.822706: train_loss -0.7832 +2024-11-22 07:06:39.822954: val_loss -0.7783 +2024-11-22 07:06:39.823077: Pseudo dice [0.8394] +2024-11-22 07:06:39.823153: Epoch time: 19.6 s +2024-11-22 07:06:40.692089: +2024-11-22 07:06:40.692300: Epoch 3802 +2024-11-22 07:06:40.692415: Current learning rate: 0.0056 +2024-11-22 07:06:59.199544: train_loss -0.792 +2024-11-22 07:06:59.199773: val_loss -0.7541 +2024-11-22 07:06:59.199861: Pseudo dice [0.8556] +2024-11-22 07:06:59.199939: Epoch time: 18.51 s +2024-11-22 07:07:00.075798: +2024-11-22 07:07:00.076024: Epoch 3803 +2024-11-22 07:07:00.076140: Current learning rate: 0.0056 +2024-11-22 07:07:18.334187: train_loss -0.7839 +2024-11-22 07:07:18.334527: val_loss -0.7681 +2024-11-22 07:07:18.334610: Pseudo dice [0.8456] +2024-11-22 07:07:18.334703: Epoch time: 18.26 s +2024-11-22 07:07:19.399293: +2024-11-22 07:07:19.399765: Epoch 3804 +2024-11-22 07:07:19.399899: Current learning rate: 0.00559 +2024-11-22 07:07:37.227457: train_loss -0.7816 +2024-11-22 07:07:37.227971: val_loss -0.7653 +2024-11-22 07:07:37.228084: Pseudo dice [0.8454] +2024-11-22 07:07:37.228172: Epoch time: 17.83 s +2024-11-22 07:07:38.103907: +2024-11-22 07:07:38.104136: Epoch 3805 +2024-11-22 07:07:38.104248: Current learning rate: 0.00559 +2024-11-22 07:07:56.963984: train_loss -0.789 +2024-11-22 07:07:56.964236: val_loss -0.7804 +2024-11-22 07:07:56.964313: Pseudo dice [0.8445] +2024-11-22 07:07:56.964388: Epoch time: 18.86 s +2024-11-22 07:07:57.846315: +2024-11-22 07:07:57.846561: Epoch 3806 +2024-11-22 07:07:57.846676: Current learning rate: 0.00559 +2024-11-22 07:08:16.399062: train_loss -0.7835 +2024-11-22 07:08:16.404518: val_loss -0.7686 +2024-11-22 07:08:16.404635: Pseudo dice [0.8373] +2024-11-22 07:08:16.404729: Epoch time: 18.55 s +2024-11-22 07:08:17.546623: +2024-11-22 07:08:17.546866: Epoch 3807 +2024-11-22 07:08:17.546978: Current learning rate: 0.00559 +2024-11-22 07:08:36.293917: train_loss -0.7849 +2024-11-22 07:08:36.294133: val_loss -0.7515 +2024-11-22 07:08:36.294204: Pseudo dice [0.8332] +2024-11-22 07:08:36.294277: Epoch time: 18.75 s +2024-11-22 07:08:37.167945: +2024-11-22 07:08:37.168172: Epoch 3808 +2024-11-22 07:08:37.168282: Current learning rate: 0.00559 +2024-11-22 07:08:55.538538: train_loss -0.7887 +2024-11-22 07:08:55.538763: val_loss -0.7542 +2024-11-22 07:08:55.538836: Pseudo dice [0.8578] +2024-11-22 07:08:55.538912: Epoch time: 18.37 s +2024-11-22 07:08:56.412462: +2024-11-22 07:08:56.412763: Epoch 3809 +2024-11-22 07:08:56.412873: Current learning rate: 0.00559 +2024-11-22 07:09:13.554957: train_loss -0.7915 +2024-11-22 07:09:13.556090: val_loss -0.7465 +2024-11-22 07:09:13.556220: Pseudo dice [0.8567] +2024-11-22 07:09:13.556297: Epoch time: 17.14 s +2024-11-22 07:09:14.428889: +2024-11-22 07:09:14.429114: Epoch 3810 +2024-11-22 07:09:14.429221: Current learning rate: 0.00559 +2024-11-22 07:09:33.494037: train_loss -0.7831 +2024-11-22 07:09:33.494253: val_loss -0.7783 +2024-11-22 07:09:33.494335: Pseudo dice [0.8426] +2024-11-22 07:09:33.494438: Epoch time: 19.07 s +2024-11-22 07:09:34.381672: +2024-11-22 07:09:34.381908: Epoch 3811 +2024-11-22 07:09:34.382021: Current learning rate: 0.00559 +2024-11-22 07:09:52.387924: train_loss -0.778 +2024-11-22 07:09:52.388167: val_loss -0.7931 +2024-11-22 07:09:52.388245: Pseudo dice [0.8479] +2024-11-22 07:09:52.388321: Epoch time: 18.01 s +2024-11-22 07:09:53.281742: +2024-11-22 07:09:53.281962: Epoch 3812 +2024-11-22 07:09:53.282080: Current learning rate: 0.00559 +2024-11-22 07:10:10.621844: train_loss -0.7844 +2024-11-22 07:10:10.622082: val_loss -0.7619 +2024-11-22 07:10:10.622157: Pseudo dice [0.8436] +2024-11-22 07:10:10.622242: Epoch time: 17.34 s +2024-11-22 07:10:11.506934: +2024-11-22 07:10:11.507213: Epoch 3813 +2024-11-22 07:10:11.507323: Current learning rate: 0.00558 +2024-11-22 07:10:30.596313: train_loss -0.7749 +2024-11-22 07:10:30.596540: val_loss -0.7542 +2024-11-22 07:10:30.596623: Pseudo dice [0.8221] +2024-11-22 07:10:30.596705: Epoch time: 19.09 s +2024-11-22 07:10:31.471035: +2024-11-22 07:10:31.471251: Epoch 3814 +2024-11-22 07:10:31.471364: Current learning rate: 0.00558 +2024-11-22 07:10:50.628565: train_loss -0.7865 +2024-11-22 07:10:50.628805: val_loss -0.7739 +2024-11-22 07:10:50.628885: Pseudo dice [0.8426] +2024-11-22 07:10:50.628968: Epoch time: 19.16 s +2024-11-22 07:10:51.504235: +2024-11-22 07:10:51.504654: Epoch 3815 +2024-11-22 07:10:51.504781: Current learning rate: 0.00558 +2024-11-22 07:11:09.187086: train_loss -0.7907 +2024-11-22 07:11:09.187541: val_loss -0.7559 +2024-11-22 07:11:09.187635: Pseudo dice [0.8401] +2024-11-22 07:11:09.187710: Epoch time: 17.68 s +2024-11-22 07:11:10.066770: +2024-11-22 07:11:10.067030: Epoch 3816 +2024-11-22 07:11:10.067161: Current learning rate: 0.00558 +2024-11-22 07:11:28.724455: train_loss -0.7786 +2024-11-22 07:11:28.724663: val_loss -0.7694 +2024-11-22 07:11:28.724765: Pseudo dice [0.8583] +2024-11-22 07:11:28.724842: Epoch time: 18.66 s +2024-11-22 07:11:29.619759: +2024-11-22 07:11:29.619980: Epoch 3817 +2024-11-22 07:11:29.620093: Current learning rate: 0.00558 +2024-11-22 07:11:48.177814: train_loss -0.7838 +2024-11-22 07:11:48.178156: val_loss -0.7468 +2024-11-22 07:11:48.178234: Pseudo dice [0.8453] +2024-11-22 07:11:48.178318: Epoch time: 18.56 s +2024-11-22 07:11:49.063249: +2024-11-22 07:11:49.063619: Epoch 3818 +2024-11-22 07:11:49.063769: Current learning rate: 0.00558 +2024-11-22 07:12:08.079348: train_loss -0.7855 +2024-11-22 07:12:08.079604: val_loss -0.7983 +2024-11-22 07:12:08.079679: Pseudo dice [0.8553] +2024-11-22 07:12:08.079753: Epoch time: 19.02 s +2024-11-22 07:12:08.964097: +2024-11-22 07:12:08.964318: Epoch 3819 +2024-11-22 07:12:08.964428: Current learning rate: 0.00558 +2024-11-22 07:12:27.878510: train_loss -0.7854 +2024-11-22 07:12:27.883927: val_loss -0.7831 +2024-11-22 07:12:27.884060: Pseudo dice [0.8527] +2024-11-22 07:12:27.884147: Epoch time: 18.92 s +2024-11-22 07:12:28.875337: +2024-11-22 07:12:28.875571: Epoch 3820 +2024-11-22 07:12:28.875684: Current learning rate: 0.00558 +2024-11-22 07:12:46.857199: train_loss -0.793 +2024-11-22 07:12:46.857509: val_loss -0.7645 +2024-11-22 07:12:46.857584: Pseudo dice [0.8418] +2024-11-22 07:12:46.857886: Epoch time: 17.98 s +2024-11-22 07:12:47.749673: +2024-11-22 07:12:47.749879: Epoch 3821 +2024-11-22 07:12:47.750000: Current learning rate: 0.00557 +2024-11-22 07:13:06.624026: train_loss -0.7844 +2024-11-22 07:13:06.624263: val_loss -0.7847 +2024-11-22 07:13:06.624342: Pseudo dice [0.8496] +2024-11-22 07:13:06.624424: Epoch time: 18.88 s +2024-11-22 07:13:07.502145: +2024-11-22 07:13:07.502357: Epoch 3822 +2024-11-22 07:13:07.502471: Current learning rate: 0.00557 +2024-11-22 07:13:25.221802: train_loss -0.7815 +2024-11-22 07:13:25.222056: val_loss -0.7701 +2024-11-22 07:13:25.222136: Pseudo dice [0.8368] +2024-11-22 07:13:25.222214: Epoch time: 17.72 s +2024-11-22 07:13:26.107457: +2024-11-22 07:13:26.107679: Epoch 3823 +2024-11-22 07:13:26.107787: Current learning rate: 0.00557 +2024-11-22 07:13:43.235542: train_loss -0.7831 +2024-11-22 07:13:43.235765: val_loss -0.7663 +2024-11-22 07:13:43.235841: Pseudo dice [0.8553] +2024-11-22 07:13:43.235915: Epoch time: 17.13 s +2024-11-22 07:13:44.114491: +2024-11-22 07:13:44.114697: Epoch 3824 +2024-11-22 07:13:44.114807: Current learning rate: 0.00557 +2024-11-22 07:14:02.883202: train_loss -0.7893 +2024-11-22 07:14:02.883435: val_loss -0.7739 +2024-11-22 07:14:02.883515: Pseudo dice [0.8373] +2024-11-22 07:14:02.883593: Epoch time: 18.77 s +2024-11-22 07:14:03.766894: +2024-11-22 07:14:03.767120: Epoch 3825 +2024-11-22 07:14:03.767231: Current learning rate: 0.00557 +2024-11-22 07:14:23.537907: train_loss -0.7829 +2024-11-22 07:14:23.538160: val_loss -0.7743 +2024-11-22 07:14:23.538235: Pseudo dice [0.8403] +2024-11-22 07:14:23.538318: Epoch time: 19.77 s +2024-11-22 07:14:24.792851: +2024-11-22 07:14:24.793070: Epoch 3826 +2024-11-22 07:14:24.793180: Current learning rate: 0.00557 +2024-11-22 07:14:44.243462: train_loss -0.7828 +2024-11-22 07:14:44.243693: val_loss -0.7686 +2024-11-22 07:14:44.243776: Pseudo dice [0.8425] +2024-11-22 07:14:44.243854: Epoch time: 19.45 s +2024-11-22 07:14:45.133556: +2024-11-22 07:14:45.133799: Epoch 3827 +2024-11-22 07:14:45.133917: Current learning rate: 0.00557 +2024-11-22 07:15:04.237069: train_loss -0.7768 +2024-11-22 07:15:04.237307: val_loss -0.7611 +2024-11-22 07:15:04.237386: Pseudo dice [0.8539] +2024-11-22 07:15:04.237460: Epoch time: 19.1 s +2024-11-22 07:15:05.112877: +2024-11-22 07:15:05.113114: Epoch 3828 +2024-11-22 07:15:05.113223: Current learning rate: 0.00557 +2024-11-22 07:15:23.266564: train_loss -0.7903 +2024-11-22 07:15:23.266783: val_loss -0.7698 +2024-11-22 07:15:23.266860: Pseudo dice [0.8318] +2024-11-22 07:15:23.266937: Epoch time: 18.15 s +2024-11-22 07:15:24.229090: +2024-11-22 07:15:24.229342: Epoch 3829 +2024-11-22 07:15:24.229468: Current learning rate: 0.00556 +2024-11-22 07:15:42.675112: train_loss -0.7903 +2024-11-22 07:15:42.675333: val_loss -0.7958 +2024-11-22 07:15:42.675404: Pseudo dice [0.851] +2024-11-22 07:15:42.677662: Epoch time: 18.45 s +2024-11-22 07:15:43.597866: +2024-11-22 07:15:43.598109: Epoch 3830 +2024-11-22 07:15:43.598220: Current learning rate: 0.00556 +2024-11-22 07:16:02.472200: train_loss -0.7897 +2024-11-22 07:16:02.472415: val_loss -0.7454 +2024-11-22 07:16:02.472489: Pseudo dice [0.8405] +2024-11-22 07:16:02.472564: Epoch time: 18.88 s +2024-11-22 07:16:03.347883: +2024-11-22 07:16:03.348101: Epoch 3831 +2024-11-22 07:16:03.348207: Current learning rate: 0.00556 +2024-11-22 07:16:21.732328: train_loss -0.7895 +2024-11-22 07:16:21.732543: val_loss -0.7872 +2024-11-22 07:16:21.732622: Pseudo dice [0.8321] +2024-11-22 07:16:21.732710: Epoch time: 18.39 s +2024-11-22 07:16:22.610598: +2024-11-22 07:16:22.610825: Epoch 3832 +2024-11-22 07:16:22.610934: Current learning rate: 0.00556 +2024-11-22 07:16:40.904812: train_loss -0.7874 +2024-11-22 07:16:40.905096: val_loss -0.7686 +2024-11-22 07:16:40.905179: Pseudo dice [0.8243] +2024-11-22 07:16:40.905279: Epoch time: 18.3 s +2024-11-22 07:16:41.897521: +2024-11-22 07:16:41.897743: Epoch 3833 +2024-11-22 07:16:41.897854: Current learning rate: 0.00556 +2024-11-22 07:17:00.049335: train_loss -0.7835 +2024-11-22 07:17:00.049549: val_loss -0.7853 +2024-11-22 07:17:00.049624: Pseudo dice [0.8479] +2024-11-22 07:17:00.049696: Epoch time: 18.15 s +2024-11-22 07:17:00.920728: +2024-11-22 07:17:00.920951: Epoch 3834 +2024-11-22 07:17:00.921071: Current learning rate: 0.00556 +2024-11-22 07:17:19.121743: train_loss -0.7911 +2024-11-22 07:17:19.125586: val_loss -0.7705 +2024-11-22 07:17:19.125728: Pseudo dice [0.847] +2024-11-22 07:17:19.125813: Epoch time: 18.2 s +2024-11-22 07:17:20.024269: +2024-11-22 07:17:20.024515: Epoch 3835 +2024-11-22 07:17:20.024625: Current learning rate: 0.00556 +2024-11-22 07:17:37.751652: train_loss -0.7859 +2024-11-22 07:17:37.751888: val_loss -0.7577 +2024-11-22 07:17:37.751965: Pseudo dice [0.8362] +2024-11-22 07:17:37.752049: Epoch time: 17.73 s +2024-11-22 07:17:38.626329: +2024-11-22 07:17:38.626738: Epoch 3836 +2024-11-22 07:17:38.626870: Current learning rate: 0.00556 +2024-11-22 07:17:56.260858: train_loss -0.7813 +2024-11-22 07:17:56.261105: val_loss -0.7974 +2024-11-22 07:17:56.261182: Pseudo dice [0.8421] +2024-11-22 07:17:56.261261: Epoch time: 17.64 s +2024-11-22 07:17:57.146476: +2024-11-22 07:17:57.146690: Epoch 3837 +2024-11-22 07:17:57.146826: Current learning rate: 0.00556 +2024-11-22 07:18:14.895628: train_loss -0.7879 +2024-11-22 07:18:14.895839: val_loss -0.7854 +2024-11-22 07:18:14.895912: Pseudo dice [0.8594] +2024-11-22 07:18:14.895985: Epoch time: 17.75 s +2024-11-22 07:18:16.146613: +2024-11-22 07:18:16.146824: Epoch 3838 +2024-11-22 07:18:16.146933: Current learning rate: 0.00555 +2024-11-22 07:18:34.679287: train_loss -0.7872 +2024-11-22 07:18:34.679594: val_loss -0.7521 +2024-11-22 07:18:34.679681: Pseudo dice [0.8326] +2024-11-22 07:18:34.679768: Epoch time: 18.53 s +2024-11-22 07:18:35.764785: +2024-11-22 07:18:35.765033: Epoch 3839 +2024-11-22 07:18:35.765148: Current learning rate: 0.00555 +2024-11-22 07:18:53.899653: train_loss -0.7888 +2024-11-22 07:18:53.899882: val_loss -0.7924 +2024-11-22 07:18:53.899966: Pseudo dice [0.8561] +2024-11-22 07:18:53.900051: Epoch time: 18.14 s +2024-11-22 07:18:54.782987: +2024-11-22 07:18:54.783227: Epoch 3840 +2024-11-22 07:18:54.783343: Current learning rate: 0.00555 +2024-11-22 07:19:12.359915: train_loss -0.7874 +2024-11-22 07:19:12.360155: val_loss -0.7718 +2024-11-22 07:19:12.360232: Pseudo dice [0.8515] +2024-11-22 07:19:12.360307: Epoch time: 17.58 s +2024-11-22 07:19:13.238685: +2024-11-22 07:19:13.238942: Epoch 3841 +2024-11-22 07:19:13.239059: Current learning rate: 0.00555 +2024-11-22 07:19:30.872043: train_loss -0.7922 +2024-11-22 07:19:30.872329: val_loss -0.7482 +2024-11-22 07:19:30.872407: Pseudo dice [0.8149] +2024-11-22 07:19:30.872483: Epoch time: 17.63 s +2024-11-22 07:19:31.756702: +2024-11-22 07:19:31.756959: Epoch 3842 +2024-11-22 07:19:31.757097: Current learning rate: 0.00555 +2024-11-22 07:19:50.440044: train_loss -0.793 +2024-11-22 07:19:50.440300: val_loss -0.7727 +2024-11-22 07:19:50.440384: Pseudo dice [0.8398] +2024-11-22 07:19:50.440464: Epoch time: 18.68 s +2024-11-22 07:19:51.328283: +2024-11-22 07:19:51.328527: Epoch 3843 +2024-11-22 07:19:51.328636: Current learning rate: 0.00555 +2024-11-22 07:20:10.327350: train_loss -0.7829 +2024-11-22 07:20:10.327585: val_loss -0.7638 +2024-11-22 07:20:10.327663: Pseudo dice [0.836] +2024-11-22 07:20:10.327737: Epoch time: 19.0 s +2024-11-22 07:20:11.205670: +2024-11-22 07:20:11.205898: Epoch 3844 +2024-11-22 07:20:11.206014: Current learning rate: 0.00555 +2024-11-22 07:20:29.925039: train_loss -0.7859 +2024-11-22 07:20:29.925253: val_loss -0.7589 +2024-11-22 07:20:29.925328: Pseudo dice [0.8469] +2024-11-22 07:20:29.925400: Epoch time: 18.72 s +2024-11-22 07:20:30.804060: +2024-11-22 07:20:30.804286: Epoch 3845 +2024-11-22 07:20:30.804395: Current learning rate: 0.00555 +2024-11-22 07:20:49.142494: train_loss -0.7745 +2024-11-22 07:20:49.142715: val_loss -0.7705 +2024-11-22 07:20:49.142788: Pseudo dice [0.8459] +2024-11-22 07:20:49.142864: Epoch time: 18.34 s +2024-11-22 07:20:50.024104: +2024-11-22 07:20:50.024339: Epoch 3846 +2024-11-22 07:20:50.024462: Current learning rate: 0.00554 +2024-11-22 07:21:08.188090: train_loss -0.7763 +2024-11-22 07:21:08.188301: val_loss -0.7825 +2024-11-22 07:21:08.188599: Pseudo dice [0.8407] +2024-11-22 07:21:08.188696: Epoch time: 18.16 s +2024-11-22 07:21:09.060076: +2024-11-22 07:21:09.060314: Epoch 3847 +2024-11-22 07:21:09.060427: Current learning rate: 0.00554 +2024-11-22 07:21:27.991926: train_loss -0.7842 +2024-11-22 07:21:27.992146: val_loss -0.773 +2024-11-22 07:21:27.992225: Pseudo dice [0.8408] +2024-11-22 07:21:27.992301: Epoch time: 18.93 s +2024-11-22 07:21:28.871766: +2024-11-22 07:21:28.871984: Epoch 3848 +2024-11-22 07:21:28.872101: Current learning rate: 0.00554 +2024-11-22 07:21:47.450971: train_loss -0.7883 +2024-11-22 07:21:47.451218: val_loss -0.7608 +2024-11-22 07:21:47.451300: Pseudo dice [0.8364] +2024-11-22 07:21:47.451375: Epoch time: 18.58 s +2024-11-22 07:21:48.748135: +2024-11-22 07:21:48.748369: Epoch 3849 +2024-11-22 07:21:48.748482: Current learning rate: 0.00554 +2024-11-22 07:22:08.316215: train_loss -0.772 +2024-11-22 07:22:08.316477: val_loss -0.7491 +2024-11-22 07:22:08.316552: Pseudo dice [0.8508] +2024-11-22 07:22:08.316634: Epoch time: 19.57 s +2024-11-22 07:22:09.580659: +2024-11-22 07:22:09.580870: Epoch 3850 +2024-11-22 07:22:09.580978: Current learning rate: 0.00554 +2024-11-22 07:22:28.860086: train_loss -0.7841 +2024-11-22 07:22:28.860307: val_loss -0.7367 +2024-11-22 07:22:28.860380: Pseudo dice [0.8147] +2024-11-22 07:22:28.860452: Epoch time: 19.28 s +2024-11-22 07:22:29.741402: +2024-11-22 07:22:29.741626: Epoch 3851 +2024-11-22 07:22:29.741735: Current learning rate: 0.00554 +2024-11-22 07:22:48.683199: train_loss -0.7838 +2024-11-22 07:22:48.683428: val_loss -0.7521 +2024-11-22 07:22:48.683507: Pseudo dice [0.8354] +2024-11-22 07:22:48.683616: Epoch time: 18.94 s +2024-11-22 07:22:49.564891: +2024-11-22 07:22:49.565130: Epoch 3852 +2024-11-22 07:22:49.565246: Current learning rate: 0.00554 +2024-11-22 07:23:07.903732: train_loss -0.7919 +2024-11-22 07:23:07.903985: val_loss -0.7592 +2024-11-22 07:23:07.904076: Pseudo dice [0.8384] +2024-11-22 07:23:07.904161: Epoch time: 18.34 s +2024-11-22 07:23:08.787935: +2024-11-22 07:23:08.788223: Epoch 3853 +2024-11-22 07:23:08.788333: Current learning rate: 0.00554 +2024-11-22 07:23:27.284678: train_loss -0.7973 +2024-11-22 07:23:27.284900: val_loss -0.7427 +2024-11-22 07:23:27.284977: Pseudo dice [0.8448] +2024-11-22 07:23:27.285060: Epoch time: 18.5 s +2024-11-22 07:23:28.159900: +2024-11-22 07:23:28.160121: Epoch 3854 +2024-11-22 07:23:28.160228: Current learning rate: 0.00553 +2024-11-22 07:23:47.242577: train_loss -0.7905 +2024-11-22 07:23:47.242838: val_loss -0.787 +2024-11-22 07:23:47.242918: Pseudo dice [0.8389] +2024-11-22 07:23:47.243001: Epoch time: 19.08 s +2024-11-22 07:23:48.125690: +2024-11-22 07:23:48.125926: Epoch 3855 +2024-11-22 07:23:48.126041: Current learning rate: 0.00553 +2024-11-22 07:24:06.805096: train_loss -0.787 +2024-11-22 07:24:06.805311: val_loss -0.7516 +2024-11-22 07:24:06.805391: Pseudo dice [0.8362] +2024-11-22 07:24:06.805465: Epoch time: 18.68 s +2024-11-22 07:24:07.701140: +2024-11-22 07:24:07.701376: Epoch 3856 +2024-11-22 07:24:07.701499: Current learning rate: 0.00553 +2024-11-22 07:24:26.399707: train_loss -0.7811 +2024-11-22 07:24:26.399943: val_loss -0.7637 +2024-11-22 07:24:26.400029: Pseudo dice [0.8369] +2024-11-22 07:24:26.400108: Epoch time: 18.7 s +2024-11-22 07:24:27.278341: +2024-11-22 07:24:27.278562: Epoch 3857 +2024-11-22 07:24:27.278677: Current learning rate: 0.00553 +2024-11-22 07:24:45.766608: train_loss -0.7791 +2024-11-22 07:24:45.766824: val_loss -0.7529 +2024-11-22 07:24:45.766898: Pseudo dice [0.8295] +2024-11-22 07:24:45.766972: Epoch time: 18.49 s +2024-11-22 07:24:46.647107: +2024-11-22 07:24:46.647333: Epoch 3858 +2024-11-22 07:24:46.647446: Current learning rate: 0.00553 +2024-11-22 07:25:05.336888: train_loss -0.7761 +2024-11-22 07:25:05.339474: val_loss -0.7551 +2024-11-22 07:25:05.339569: Pseudo dice [0.8457] +2024-11-22 07:25:05.339647: Epoch time: 18.69 s +2024-11-22 07:25:06.226109: +2024-11-22 07:25:06.226319: Epoch 3859 +2024-11-22 07:25:06.226447: Current learning rate: 0.00553 +2024-11-22 07:25:25.508260: train_loss -0.782 +2024-11-22 07:25:25.508517: val_loss -0.7913 +2024-11-22 07:25:25.513761: Pseudo dice [0.8644] +2024-11-22 07:25:25.513956: Epoch time: 19.28 s +2024-11-22 07:25:26.524466: +2024-11-22 07:25:26.524679: Epoch 3860 +2024-11-22 07:25:26.524789: Current learning rate: 0.00553 +2024-11-22 07:25:44.810167: train_loss -0.7728 +2024-11-22 07:25:44.812813: val_loss -0.7527 +2024-11-22 07:25:44.812922: Pseudo dice [0.8404] +2024-11-22 07:25:44.813006: Epoch time: 18.29 s +2024-11-22 07:25:45.766232: +2024-11-22 07:25:45.766499: Epoch 3861 +2024-11-22 07:25:45.766610: Current learning rate: 0.00553 +2024-11-22 07:26:04.239036: train_loss -0.7736 +2024-11-22 07:26:04.239259: val_loss -0.7431 +2024-11-22 07:26:04.239334: Pseudo dice [0.8379] +2024-11-22 07:26:04.239409: Epoch time: 18.47 s +2024-11-22 07:26:05.119026: +2024-11-22 07:26:05.119390: Epoch 3862 +2024-11-22 07:26:05.119500: Current learning rate: 0.00552 +2024-11-22 07:26:25.546617: train_loss -0.7805 +2024-11-22 07:26:25.547502: val_loss -0.7868 +2024-11-22 07:26:25.547583: Pseudo dice [0.8461] +2024-11-22 07:26:25.547665: Epoch time: 20.43 s +2024-11-22 07:26:26.432854: +2024-11-22 07:26:26.433092: Epoch 3863 +2024-11-22 07:26:26.433201: Current learning rate: 0.00552 +2024-11-22 07:26:45.840016: train_loss -0.7809 +2024-11-22 07:26:45.840242: val_loss -0.7731 +2024-11-22 07:26:45.840323: Pseudo dice [0.8513] +2024-11-22 07:26:45.840406: Epoch time: 19.41 s +2024-11-22 07:26:46.715839: +2024-11-22 07:26:46.716081: Epoch 3864 +2024-11-22 07:26:46.716203: Current learning rate: 0.00552 +2024-11-22 07:27:05.831714: train_loss -0.7773 +2024-11-22 07:27:05.831924: val_loss -0.745 +2024-11-22 07:27:05.832010: Pseudo dice [0.8058] +2024-11-22 07:27:05.832085: Epoch time: 19.12 s +2024-11-22 07:27:06.706728: +2024-11-22 07:27:06.706944: Epoch 3865 +2024-11-22 07:27:06.707060: Current learning rate: 0.00552 +2024-11-22 07:27:25.623815: train_loss -0.7727 +2024-11-22 07:27:25.624044: val_loss -0.7711 +2024-11-22 07:27:25.624131: Pseudo dice [0.8391] +2024-11-22 07:27:25.624208: Epoch time: 18.92 s +2024-11-22 07:27:26.507270: +2024-11-22 07:27:26.507473: Epoch 3866 +2024-11-22 07:27:26.507580: Current learning rate: 0.00552 +2024-11-22 07:27:45.224686: train_loss -0.769 +2024-11-22 07:27:45.224916: val_loss -0.7852 +2024-11-22 07:27:45.225002: Pseudo dice [0.8509] +2024-11-22 07:27:45.225109: Epoch time: 18.72 s +2024-11-22 07:27:46.103630: +2024-11-22 07:27:46.103842: Epoch 3867 +2024-11-22 07:27:46.103946: Current learning rate: 0.00552 +2024-11-22 07:28:05.122765: train_loss -0.7739 +2024-11-22 07:28:05.123015: val_loss -0.7647 +2024-11-22 07:28:05.123091: Pseudo dice [0.8261] +2024-11-22 07:28:05.123173: Epoch time: 19.02 s +2024-11-22 07:28:06.000564: +2024-11-22 07:28:06.000779: Epoch 3868 +2024-11-22 07:28:06.000884: Current learning rate: 0.00552 +2024-11-22 07:28:24.741530: train_loss -0.7914 +2024-11-22 07:28:24.741759: val_loss -0.7703 +2024-11-22 07:28:24.741834: Pseudo dice [0.8416] +2024-11-22 07:28:24.741961: Epoch time: 18.74 s +2024-11-22 07:28:25.615351: +2024-11-22 07:28:25.615571: Epoch 3869 +2024-11-22 07:28:25.615713: Current learning rate: 0.00552 +2024-11-22 07:28:43.883001: train_loss -0.7916 +2024-11-22 07:28:43.883603: val_loss -0.761 +2024-11-22 07:28:43.883686: Pseudo dice [0.8531] +2024-11-22 07:28:43.883762: Epoch time: 18.27 s +2024-11-22 07:28:44.802956: +2024-11-22 07:28:44.803224: Epoch 3870 +2024-11-22 07:28:44.803335: Current learning rate: 0.00552 +2024-11-22 07:29:03.360982: train_loss -0.7881 +2024-11-22 07:29:03.361229: val_loss -0.7963 +2024-11-22 07:29:03.361325: Pseudo dice [0.8582] +2024-11-22 07:29:03.361409: Epoch time: 18.56 s +2024-11-22 07:29:04.620553: +2024-11-22 07:29:04.620774: Epoch 3871 +2024-11-22 07:29:04.620880: Current learning rate: 0.00551 +2024-11-22 07:29:22.304270: train_loss -0.7812 +2024-11-22 07:29:22.304492: val_loss -0.7533 +2024-11-22 07:29:22.306795: Pseudo dice [0.8647] +2024-11-22 07:29:22.306893: Epoch time: 17.68 s +2024-11-22 07:29:23.367126: +2024-11-22 07:29:23.367377: Epoch 3872 +2024-11-22 07:29:23.367492: Current learning rate: 0.00551 +2024-11-22 07:29:40.829498: train_loss -0.7882 +2024-11-22 07:29:40.829718: val_loss -0.7569 +2024-11-22 07:29:40.829901: Pseudo dice [0.8303] +2024-11-22 07:29:40.829984: Epoch time: 17.46 s +2024-11-22 07:29:41.710119: +2024-11-22 07:29:41.710337: Epoch 3873 +2024-11-22 07:29:41.710450: Current learning rate: 0.00551 +2024-11-22 07:29:59.812907: train_loss -0.7832 +2024-11-22 07:29:59.813129: val_loss -0.7466 +2024-11-22 07:29:59.813205: Pseudo dice [0.8543] +2024-11-22 07:29:59.814987: Epoch time: 18.1 s +2024-11-22 07:30:00.855717: +2024-11-22 07:30:00.856037: Epoch 3874 +2024-11-22 07:30:00.856149: Current learning rate: 0.00551 +2024-11-22 07:30:19.529386: train_loss -0.7824 +2024-11-22 07:30:19.529628: val_loss -0.7445 +2024-11-22 07:30:19.529723: Pseudo dice [0.8376] +2024-11-22 07:30:19.529802: Epoch time: 18.67 s +2024-11-22 07:30:20.406556: +2024-11-22 07:30:20.406772: Epoch 3875 +2024-11-22 07:30:20.406881: Current learning rate: 0.00551 +2024-11-22 07:30:39.641556: train_loss -0.7814 +2024-11-22 07:30:39.641778: val_loss -0.7617 +2024-11-22 07:30:39.641856: Pseudo dice [0.8402] +2024-11-22 07:30:39.641931: Epoch time: 19.24 s +2024-11-22 07:30:40.522746: +2024-11-22 07:30:40.522997: Epoch 3876 +2024-11-22 07:30:40.523108: Current learning rate: 0.00551 +2024-11-22 07:30:59.635260: train_loss -0.7751 +2024-11-22 07:30:59.635486: val_loss -0.7677 +2024-11-22 07:30:59.635566: Pseudo dice [0.851] +2024-11-22 07:30:59.635642: Epoch time: 19.11 s +2024-11-22 07:31:00.521337: +2024-11-22 07:31:00.521544: Epoch 3877 +2024-11-22 07:31:00.521650: Current learning rate: 0.00551 +2024-11-22 07:31:19.173236: train_loss -0.7723 +2024-11-22 07:31:19.173457: val_loss -0.7604 +2024-11-22 07:31:19.173537: Pseudo dice [0.849] +2024-11-22 07:31:19.173620: Epoch time: 18.65 s +2024-11-22 07:31:20.055167: +2024-11-22 07:31:20.055392: Epoch 3878 +2024-11-22 07:31:20.055509: Current learning rate: 0.00551 +2024-11-22 07:31:38.603018: train_loss -0.7813 +2024-11-22 07:31:38.603295: val_loss -0.7619 +2024-11-22 07:31:38.603375: Pseudo dice [0.8401] +2024-11-22 07:31:38.603457: Epoch time: 18.55 s +2024-11-22 07:31:39.501189: +2024-11-22 07:31:39.501409: Epoch 3879 +2024-11-22 07:31:39.501526: Current learning rate: 0.0055 +2024-11-22 07:31:57.916119: train_loss -0.7778 +2024-11-22 07:31:57.916341: val_loss -0.7657 +2024-11-22 07:31:57.916416: Pseudo dice [0.8367] +2024-11-22 07:31:57.916493: Epoch time: 18.42 s +2024-11-22 07:31:58.797878: +2024-11-22 07:31:58.798090: Epoch 3880 +2024-11-22 07:31:58.798198: Current learning rate: 0.0055 +2024-11-22 07:32:16.874190: train_loss -0.7835 +2024-11-22 07:32:16.874405: val_loss -0.7336 +2024-11-22 07:32:16.874478: Pseudo dice [0.8445] +2024-11-22 07:32:16.874630: Epoch time: 18.08 s +2024-11-22 07:32:17.771107: +2024-11-22 07:32:17.771382: Epoch 3881 +2024-11-22 07:32:17.771492: Current learning rate: 0.0055 +2024-11-22 07:32:35.647866: train_loss -0.7859 +2024-11-22 07:32:35.648126: val_loss -0.7809 +2024-11-22 07:32:35.648202: Pseudo dice [0.8482] +2024-11-22 07:32:35.648288: Epoch time: 17.88 s +2024-11-22 07:32:36.744287: +2024-11-22 07:32:36.744498: Epoch 3882 +2024-11-22 07:32:36.744611: Current learning rate: 0.0055 +2024-11-22 07:32:56.079268: train_loss -0.7748 +2024-11-22 07:32:56.079471: val_loss -0.7621 +2024-11-22 07:32:56.079545: Pseudo dice [0.8404] +2024-11-22 07:32:56.079618: Epoch time: 19.34 s +2024-11-22 07:32:57.353584: +2024-11-22 07:32:57.353808: Epoch 3883 +2024-11-22 07:32:57.353921: Current learning rate: 0.0055 +2024-11-22 07:33:15.670125: train_loss -0.7824 +2024-11-22 07:33:15.670339: val_loss -0.7726 +2024-11-22 07:33:15.670412: Pseudo dice [0.8545] +2024-11-22 07:33:15.670483: Epoch time: 18.32 s +2024-11-22 07:33:16.553317: +2024-11-22 07:33:16.553650: Epoch 3884 +2024-11-22 07:33:16.553758: Current learning rate: 0.0055 +2024-11-22 07:33:36.349310: train_loss -0.7843 +2024-11-22 07:33:36.349579: val_loss -0.7628 +2024-11-22 07:33:36.349661: Pseudo dice [0.8521] +2024-11-22 07:33:36.349743: Epoch time: 19.8 s +2024-11-22 07:33:37.229271: +2024-11-22 07:33:37.229503: Epoch 3885 +2024-11-22 07:33:37.229618: Current learning rate: 0.0055 +2024-11-22 07:33:56.045222: train_loss -0.7874 +2024-11-22 07:33:56.045439: val_loss -0.7916 +2024-11-22 07:33:56.045586: Pseudo dice [0.8497] +2024-11-22 07:33:56.045662: Epoch time: 18.82 s +2024-11-22 07:33:57.031750: +2024-11-22 07:33:57.032040: Epoch 3886 +2024-11-22 07:33:57.032157: Current learning rate: 0.0055 +2024-11-22 07:34:16.279656: train_loss -0.7812 +2024-11-22 07:34:16.279872: val_loss -0.794 +2024-11-22 07:34:16.279948: Pseudo dice [0.8617] +2024-11-22 07:34:16.280035: Epoch time: 19.25 s +2024-11-22 07:34:17.166358: +2024-11-22 07:34:17.166586: Epoch 3887 +2024-11-22 07:34:17.166695: Current learning rate: 0.00549 +2024-11-22 07:34:35.913565: train_loss -0.7795 +2024-11-22 07:34:35.913776: val_loss -0.7603 +2024-11-22 07:34:35.913849: Pseudo dice [0.8386] +2024-11-22 07:34:35.913921: Epoch time: 18.75 s +2024-11-22 07:34:36.794707: +2024-11-22 07:34:36.794911: Epoch 3888 +2024-11-22 07:34:36.795022: Current learning rate: 0.00549 +2024-11-22 07:34:55.508107: train_loss -0.7822 +2024-11-22 07:34:55.508354: val_loss -0.7778 +2024-11-22 07:34:55.508430: Pseudo dice [0.8448] +2024-11-22 07:34:55.508511: Epoch time: 18.71 s +2024-11-22 07:34:56.420300: +2024-11-22 07:34:56.420509: Epoch 3889 +2024-11-22 07:34:56.420618: Current learning rate: 0.00549 +2024-11-22 07:35:15.790631: train_loss -0.7804 +2024-11-22 07:35:15.790871: val_loss -0.7695 +2024-11-22 07:35:15.790948: Pseudo dice [0.8451] +2024-11-22 07:35:15.791032: Epoch time: 19.37 s +2024-11-22 07:35:16.691753: +2024-11-22 07:35:16.692112: Epoch 3890 +2024-11-22 07:35:16.692222: Current learning rate: 0.00549 +2024-11-22 07:35:34.504432: train_loss -0.7764 +2024-11-22 07:35:34.504678: val_loss -0.785 +2024-11-22 07:35:34.504754: Pseudo dice [0.84] +2024-11-22 07:35:34.504830: Epoch time: 17.81 s +2024-11-22 07:35:35.382028: +2024-11-22 07:35:35.382229: Epoch 3891 +2024-11-22 07:35:35.382335: Current learning rate: 0.00549 +2024-11-22 07:35:54.065317: train_loss -0.7903 +2024-11-22 07:35:54.065534: val_loss -0.7773 +2024-11-22 07:35:54.065607: Pseudo dice [0.85] +2024-11-22 07:35:54.065684: Epoch time: 18.68 s +2024-11-22 07:35:54.946697: +2024-11-22 07:35:54.947080: Epoch 3892 +2024-11-22 07:35:54.947198: Current learning rate: 0.00549 +2024-11-22 07:36:13.481046: train_loss -0.7962 +2024-11-22 07:36:13.481278: val_loss -0.7772 +2024-11-22 07:36:13.481352: Pseudo dice [0.8589] +2024-11-22 07:36:13.481431: Epoch time: 18.54 s +2024-11-22 07:36:14.619363: +2024-11-22 07:36:14.619551: Epoch 3893 +2024-11-22 07:36:14.619661: Current learning rate: 0.00549 +2024-11-22 07:36:33.190773: train_loss -0.7858 +2024-11-22 07:36:33.191011: val_loss -0.7741 +2024-11-22 07:36:33.191092: Pseudo dice [0.8529] +2024-11-22 07:36:33.191171: Epoch time: 18.57 s +2024-11-22 07:36:34.480722: +2024-11-22 07:36:34.480953: Epoch 3894 +2024-11-22 07:36:34.481071: Current learning rate: 0.00549 +2024-11-22 07:36:52.716553: train_loss -0.7829 +2024-11-22 07:36:52.716861: val_loss -0.7787 +2024-11-22 07:36:52.716939: Pseudo dice [0.8464] +2024-11-22 07:36:52.717022: Epoch time: 18.24 s +2024-11-22 07:36:53.605365: +2024-11-22 07:36:53.605719: Epoch 3895 +2024-11-22 07:36:53.605878: Current learning rate: 0.00549 +2024-11-22 07:37:11.644258: train_loss -0.7776 +2024-11-22 07:37:11.644487: val_loss -0.7503 +2024-11-22 07:37:11.644561: Pseudo dice [0.8257] +2024-11-22 07:37:11.644637: Epoch time: 18.04 s +2024-11-22 07:37:12.525621: +2024-11-22 07:37:12.525846: Epoch 3896 +2024-11-22 07:37:12.525959: Current learning rate: 0.00548 +2024-11-22 07:37:30.858585: train_loss -0.7519 +2024-11-22 07:37:30.858788: val_loss -0.7534 +2024-11-22 07:37:30.858863: Pseudo dice [0.8061] +2024-11-22 07:37:30.858939: Epoch time: 18.33 s +2024-11-22 07:37:31.739596: +2024-11-22 07:37:31.739870: Epoch 3897 +2024-11-22 07:37:31.739979: Current learning rate: 0.00548 +2024-11-22 07:37:50.650361: train_loss -0.7682 +2024-11-22 07:37:50.650578: val_loss -0.7617 +2024-11-22 07:37:50.650652: Pseudo dice [0.8456] +2024-11-22 07:37:50.650729: Epoch time: 18.91 s +2024-11-22 07:37:51.558118: +2024-11-22 07:37:51.558355: Epoch 3898 +2024-11-22 07:37:51.558467: Current learning rate: 0.00548 +2024-11-22 07:38:10.098983: train_loss -0.7776 +2024-11-22 07:38:10.099554: val_loss -0.7628 +2024-11-22 07:38:10.099640: Pseudo dice [0.8545] +2024-11-22 07:38:10.099720: Epoch time: 18.54 s +2024-11-22 07:38:10.982346: +2024-11-22 07:38:10.982559: Epoch 3899 +2024-11-22 07:38:10.982669: Current learning rate: 0.00548 +2024-11-22 07:38:29.215778: train_loss -0.7662 +2024-11-22 07:38:29.216003: val_loss -0.7653 +2024-11-22 07:38:29.216083: Pseudo dice [0.8499] +2024-11-22 07:38:29.216160: Epoch time: 18.23 s +2024-11-22 07:38:30.342925: +2024-11-22 07:38:30.343150: Epoch 3900 +2024-11-22 07:38:30.343265: Current learning rate: 0.00548 +2024-11-22 07:38:47.599854: train_loss -0.7814 +2024-11-22 07:38:47.600091: val_loss -0.7903 +2024-11-22 07:38:47.600167: Pseudo dice [0.8549] +2024-11-22 07:38:47.600278: Epoch time: 17.26 s +2024-11-22 07:38:48.481354: +2024-11-22 07:38:48.481594: Epoch 3901 +2024-11-22 07:38:48.481705: Current learning rate: 0.00548 +2024-11-22 07:39:06.521198: train_loss -0.7854 +2024-11-22 07:39:06.521435: val_loss -0.7899 +2024-11-22 07:39:06.521519: Pseudo dice [0.8458] +2024-11-22 07:39:06.521595: Epoch time: 18.04 s +2024-11-22 07:39:07.403039: +2024-11-22 07:39:07.403274: Epoch 3902 +2024-11-22 07:39:07.403385: Current learning rate: 0.00548 +2024-11-22 07:39:26.772784: train_loss -0.7846 +2024-11-22 07:39:26.773035: val_loss -0.7695 +2024-11-22 07:39:26.773110: Pseudo dice [0.8507] +2024-11-22 07:39:26.773191: Epoch time: 19.37 s +2024-11-22 07:39:27.653315: +2024-11-22 07:39:27.653533: Epoch 3903 +2024-11-22 07:39:27.653639: Current learning rate: 0.00548 +2024-11-22 07:39:44.861467: train_loss -0.7853 +2024-11-22 07:39:44.861686: val_loss -0.7731 +2024-11-22 07:39:44.861761: Pseudo dice [0.8391] +2024-11-22 07:39:44.861841: Epoch time: 17.21 s +2024-11-22 07:39:45.737827: +2024-11-22 07:39:45.738071: Epoch 3904 +2024-11-22 07:39:45.738185: Current learning rate: 0.00547 +2024-11-22 07:40:03.088481: train_loss -0.7884 +2024-11-22 07:40:03.088702: val_loss -0.742 +2024-11-22 07:40:03.088782: Pseudo dice [0.8374] +2024-11-22 07:40:03.088856: Epoch time: 17.35 s +2024-11-22 07:40:04.351439: +2024-11-22 07:40:04.351678: Epoch 3905 +2024-11-22 07:40:04.351789: Current learning rate: 0.00547 +2024-11-22 07:40:21.988577: train_loss -0.7916 +2024-11-22 07:40:21.988855: val_loss -0.7852 +2024-11-22 07:40:21.988930: Pseudo dice [0.8464] +2024-11-22 07:40:21.989015: Epoch time: 17.64 s +2024-11-22 07:40:22.870326: +2024-11-22 07:40:22.870545: Epoch 3906 +2024-11-22 07:40:22.870662: Current learning rate: 0.00547 +2024-11-22 07:40:41.216252: train_loss -0.7915 +2024-11-22 07:40:41.216463: val_loss -0.7869 +2024-11-22 07:40:41.216537: Pseudo dice [0.8597] +2024-11-22 07:40:41.216610: Epoch time: 18.35 s +2024-11-22 07:40:42.097786: +2024-11-22 07:40:42.098047: Epoch 3907 +2024-11-22 07:40:42.098161: Current learning rate: 0.00547 +2024-11-22 07:41:00.118718: train_loss -0.7998 +2024-11-22 07:41:00.118963: val_loss -0.7704 +2024-11-22 07:41:00.119048: Pseudo dice [0.8495] +2024-11-22 07:41:00.119124: Epoch time: 18.02 s +2024-11-22 07:41:01.066593: +2024-11-22 07:41:01.066817: Epoch 3908 +2024-11-22 07:41:01.066924: Current learning rate: 0.00547 +2024-11-22 07:41:20.002742: train_loss -0.7848 +2024-11-22 07:41:20.002948: val_loss -0.761 +2024-11-22 07:41:20.003032: Pseudo dice [0.833] +2024-11-22 07:41:20.003109: Epoch time: 18.94 s +2024-11-22 07:41:20.883913: +2024-11-22 07:41:20.884137: Epoch 3909 +2024-11-22 07:41:20.884242: Current learning rate: 0.00547 +2024-11-22 07:41:39.673493: train_loss -0.79 +2024-11-22 07:41:39.673753: val_loss -0.7801 +2024-11-22 07:41:39.673830: Pseudo dice [0.8443] +2024-11-22 07:41:39.673918: Epoch time: 18.79 s +2024-11-22 07:41:40.562562: +2024-11-22 07:41:40.562779: Epoch 3910 +2024-11-22 07:41:40.562889: Current learning rate: 0.00547 +2024-11-22 07:41:59.409848: train_loss -0.7852 +2024-11-22 07:41:59.410070: val_loss -0.7949 +2024-11-22 07:41:59.410146: Pseudo dice [0.8479] +2024-11-22 07:41:59.410218: Epoch time: 18.85 s +2024-11-22 07:42:00.293430: +2024-11-22 07:42:00.293650: Epoch 3911 +2024-11-22 07:42:00.293764: Current learning rate: 0.00547 +2024-11-22 07:42:18.864282: train_loss -0.7878 +2024-11-22 07:42:18.864496: val_loss -0.767 +2024-11-22 07:42:18.864568: Pseudo dice [0.8578] +2024-11-22 07:42:18.864642: Epoch time: 18.57 s +2024-11-22 07:42:19.797959: +2024-11-22 07:42:19.798321: Epoch 3912 +2024-11-22 07:42:19.798438: Current learning rate: 0.00546 +2024-11-22 07:42:39.328697: train_loss -0.7815 +2024-11-22 07:42:39.328940: val_loss -0.7475 +2024-11-22 07:42:39.329026: Pseudo dice [0.8311] +2024-11-22 07:42:39.329106: Epoch time: 19.53 s +2024-11-22 07:42:40.382634: +2024-11-22 07:42:40.382846: Epoch 3913 +2024-11-22 07:42:40.382960: Current learning rate: 0.00546 +2024-11-22 07:42:59.069887: train_loss -0.7894 +2024-11-22 07:42:59.070192: val_loss -0.777 +2024-11-22 07:42:59.070271: Pseudo dice [0.8524] +2024-11-22 07:42:59.070353: Epoch time: 18.69 s +2024-11-22 07:42:59.997562: +2024-11-22 07:42:59.997798: Epoch 3914 +2024-11-22 07:42:59.997913: Current learning rate: 0.00546 +2024-11-22 07:43:19.945227: train_loss -0.7879 +2024-11-22 07:43:19.945454: val_loss -0.7515 +2024-11-22 07:43:19.945529: Pseudo dice [0.8332] +2024-11-22 07:43:19.949920: Epoch time: 19.95 s +2024-11-22 07:43:21.001810: +2024-11-22 07:43:21.002022: Epoch 3915 +2024-11-22 07:43:21.002133: Current learning rate: 0.00546 +2024-11-22 07:43:38.605338: train_loss -0.7871 +2024-11-22 07:43:38.605570: val_loss -0.7531 +2024-11-22 07:43:38.605658: Pseudo dice [0.8433] +2024-11-22 07:43:38.605736: Epoch time: 17.6 s +2024-11-22 07:43:39.872878: +2024-11-22 07:43:39.873183: Epoch 3916 +2024-11-22 07:43:39.873294: Current learning rate: 0.00546 +2024-11-22 07:43:56.971276: train_loss -0.7912 +2024-11-22 07:43:56.971586: val_loss -0.746 +2024-11-22 07:43:56.971665: Pseudo dice [0.8429] +2024-11-22 07:43:56.971741: Epoch time: 17.1 s +2024-11-22 07:43:58.109290: +2024-11-22 07:43:58.109516: Epoch 3917 +2024-11-22 07:43:58.109625: Current learning rate: 0.00546 +2024-11-22 07:44:15.443280: train_loss -0.7789 +2024-11-22 07:44:15.444428: val_loss -0.7716 +2024-11-22 07:44:15.444508: Pseudo dice [0.8477] +2024-11-22 07:44:15.444583: Epoch time: 17.33 s +2024-11-22 07:44:16.325734: +2024-11-22 07:44:16.325970: Epoch 3918 +2024-11-22 07:44:16.326086: Current learning rate: 0.00546 +2024-11-22 07:44:34.415144: train_loss -0.7794 +2024-11-22 07:44:34.415366: val_loss -0.7369 +2024-11-22 07:44:34.415446: Pseudo dice [0.8271] +2024-11-22 07:44:34.415569: Epoch time: 18.09 s +2024-11-22 07:44:35.295489: +2024-11-22 07:44:35.295699: Epoch 3919 +2024-11-22 07:44:35.295811: Current learning rate: 0.00546 +2024-11-22 07:44:53.804473: train_loss -0.7897 +2024-11-22 07:44:53.804710: val_loss -0.7737 +2024-11-22 07:44:53.804798: Pseudo dice [0.8671] +2024-11-22 07:44:53.804891: Epoch time: 18.51 s +2024-11-22 07:44:54.696009: +2024-11-22 07:44:54.696238: Epoch 3920 +2024-11-22 07:44:54.696350: Current learning rate: 0.00546 +2024-11-22 07:45:12.772431: train_loss -0.7809 +2024-11-22 07:45:12.773152: val_loss -0.7558 +2024-11-22 07:45:12.773230: Pseudo dice [0.8379] +2024-11-22 07:45:12.773313: Epoch time: 18.08 s +2024-11-22 07:45:13.657507: +2024-11-22 07:45:13.657784: Epoch 3921 +2024-11-22 07:45:13.657892: Current learning rate: 0.00545 +2024-11-22 07:45:32.667947: train_loss -0.7807 +2024-11-22 07:45:32.668189: val_loss -0.7511 +2024-11-22 07:45:32.668326: Pseudo dice [0.8569] +2024-11-22 07:45:32.668408: Epoch time: 19.01 s +2024-11-22 07:45:33.551436: +2024-11-22 07:45:33.551665: Epoch 3922 +2024-11-22 07:45:33.551779: Current learning rate: 0.00545 +2024-11-22 07:45:51.902104: train_loss -0.7814 +2024-11-22 07:45:51.902320: val_loss -0.7438 +2024-11-22 07:45:51.902395: Pseudo dice [0.8356] +2024-11-22 07:45:51.902471: Epoch time: 18.35 s +2024-11-22 07:45:52.799384: +2024-11-22 07:45:52.799611: Epoch 3923 +2024-11-22 07:45:52.799730: Current learning rate: 0.00545 +2024-11-22 07:46:11.240901: train_loss -0.7842 +2024-11-22 07:46:11.241163: val_loss -0.7622 +2024-11-22 07:46:11.241241: Pseudo dice [0.8341] +2024-11-22 07:46:11.241326: Epoch time: 18.44 s +2024-11-22 07:46:12.126737: +2024-11-22 07:46:12.126940: Epoch 3924 +2024-11-22 07:46:12.127064: Current learning rate: 0.00545 +2024-11-22 07:46:30.321613: train_loss -0.7888 +2024-11-22 07:46:30.322065: val_loss -0.7744 +2024-11-22 07:46:30.322155: Pseudo dice [0.8624] +2024-11-22 07:46:30.322229: Epoch time: 18.2 s +2024-11-22 07:46:31.254797: +2024-11-22 07:46:31.255019: Epoch 3925 +2024-11-22 07:46:31.255127: Current learning rate: 0.00545 +2024-11-22 07:46:49.177850: train_loss -0.7947 +2024-11-22 07:46:49.178109: val_loss -0.7771 +2024-11-22 07:46:49.178187: Pseudo dice [0.8455] +2024-11-22 07:46:49.178261: Epoch time: 17.92 s +2024-11-22 07:46:50.052047: +2024-11-22 07:46:50.052276: Epoch 3926 +2024-11-22 07:46:50.052393: Current learning rate: 0.00545 +2024-11-22 07:47:08.635372: train_loss -0.7854 +2024-11-22 07:47:08.635588: val_loss -0.7641 +2024-11-22 07:47:08.635664: Pseudo dice [0.8254] +2024-11-22 07:47:08.635741: Epoch time: 18.58 s +2024-11-22 07:47:09.517885: +2024-11-22 07:47:09.518142: Epoch 3927 +2024-11-22 07:47:09.518290: Current learning rate: 0.00545 +2024-11-22 07:47:27.678495: train_loss -0.782 +2024-11-22 07:47:27.678719: val_loss -0.7539 +2024-11-22 07:47:27.678854: Pseudo dice [0.8356] +2024-11-22 07:47:27.678935: Epoch time: 18.16 s +2024-11-22 07:47:28.944090: +2024-11-22 07:47:28.944312: Epoch 3928 +2024-11-22 07:47:28.944421: Current learning rate: 0.00545 +2024-11-22 07:47:46.738580: train_loss -0.7846 +2024-11-22 07:47:46.738813: val_loss -0.7679 +2024-11-22 07:47:46.738890: Pseudo dice [0.8297] +2024-11-22 07:47:46.738970: Epoch time: 17.8 s +2024-11-22 07:47:47.621978: +2024-11-22 07:47:47.622295: Epoch 3929 +2024-11-22 07:47:47.622405: Current learning rate: 0.00544 +2024-11-22 07:48:06.451923: train_loss -0.7796 +2024-11-22 07:48:06.452162: val_loss -0.7465 +2024-11-22 07:48:06.452238: Pseudo dice [0.8247] +2024-11-22 07:48:06.452315: Epoch time: 18.83 s +2024-11-22 07:48:07.335624: +2024-11-22 07:48:07.335854: Epoch 3930 +2024-11-22 07:48:07.335964: Current learning rate: 0.00544 +2024-11-22 07:48:25.873683: train_loss -0.7832 +2024-11-22 07:48:25.873945: val_loss -0.7881 +2024-11-22 07:48:25.874032: Pseudo dice [0.8481] +2024-11-22 07:48:25.874116: Epoch time: 18.54 s +2024-11-22 07:48:26.761693: +2024-11-22 07:48:26.761918: Epoch 3931 +2024-11-22 07:48:26.762038: Current learning rate: 0.00544 +2024-11-22 07:48:45.069828: train_loss -0.7698 +2024-11-22 07:48:45.070056: val_loss -0.7782 +2024-11-22 07:48:45.070130: Pseudo dice [0.8406] +2024-11-22 07:48:45.070204: Epoch time: 18.31 s +2024-11-22 07:48:46.061496: +2024-11-22 07:48:46.061740: Epoch 3932 +2024-11-22 07:48:46.061848: Current learning rate: 0.00544 +2024-11-22 07:49:04.042077: train_loss -0.7898 +2024-11-22 07:49:04.042305: val_loss -0.7892 +2024-11-22 07:49:04.047539: Pseudo dice [0.8631] +2024-11-22 07:49:04.047717: Epoch time: 17.98 s +2024-11-22 07:49:04.965436: +2024-11-22 07:49:04.965660: Epoch 3933 +2024-11-22 07:49:04.965773: Current learning rate: 0.00544 +2024-11-22 07:49:23.315009: train_loss -0.7881 +2024-11-22 07:49:23.315241: val_loss -0.7784 +2024-11-22 07:49:23.315319: Pseudo dice [0.8591] +2024-11-22 07:49:23.315399: Epoch time: 18.35 s +2024-11-22 07:49:24.195523: +2024-11-22 07:49:24.195768: Epoch 3934 +2024-11-22 07:49:24.195885: Current learning rate: 0.00544 +2024-11-22 07:49:42.377408: train_loss -0.7898 +2024-11-22 07:49:42.377672: val_loss -0.7703 +2024-11-22 07:49:42.377746: Pseudo dice [0.8521] +2024-11-22 07:49:42.377826: Epoch time: 18.18 s +2024-11-22 07:49:43.263537: +2024-11-22 07:49:43.263753: Epoch 3935 +2024-11-22 07:49:43.263867: Current learning rate: 0.00544 +2024-11-22 07:50:02.068532: train_loss -0.7816 +2024-11-22 07:50:02.068757: val_loss -0.8095 +2024-11-22 07:50:02.068831: Pseudo dice [0.8559] +2024-11-22 07:50:02.068906: Epoch time: 18.81 s +2024-11-22 07:50:02.950386: +2024-11-22 07:50:02.952034: Epoch 3936 +2024-11-22 07:50:02.952166: Current learning rate: 0.00544 +2024-11-22 07:50:22.005605: train_loss -0.7906 +2024-11-22 07:50:22.005822: val_loss -0.7843 +2024-11-22 07:50:22.005897: Pseudo dice [0.853] +2024-11-22 07:50:22.005971: Epoch time: 19.06 s +2024-11-22 07:50:22.886868: +2024-11-22 07:50:22.887092: Epoch 3937 +2024-11-22 07:50:22.887200: Current learning rate: 0.00543 +2024-11-22 07:50:40.607567: train_loss -0.789 +2024-11-22 07:50:40.607818: val_loss -0.7668 +2024-11-22 07:50:40.607896: Pseudo dice [0.8448] +2024-11-22 07:50:40.607980: Epoch time: 17.72 s +2024-11-22 07:50:41.487499: +2024-11-22 07:50:41.487707: Epoch 3938 +2024-11-22 07:50:41.487812: Current learning rate: 0.00543 +2024-11-22 07:50:59.465783: train_loss -0.7997 +2024-11-22 07:50:59.466009: val_loss -0.7395 +2024-11-22 07:50:59.466085: Pseudo dice [0.8561] +2024-11-22 07:50:59.466199: Epoch time: 17.98 s +2024-11-22 07:51:00.740011: +2024-11-22 07:51:00.740469: Epoch 3939 +2024-11-22 07:51:00.740608: Current learning rate: 0.00543 +2024-11-22 07:51:19.473152: train_loss -0.7877 +2024-11-22 07:51:19.473379: val_loss -0.7477 +2024-11-22 07:51:19.473453: Pseudo dice [0.8434] +2024-11-22 07:51:19.473528: Epoch time: 18.73 s +2024-11-22 07:51:20.351691: +2024-11-22 07:51:20.352175: Epoch 3940 +2024-11-22 07:51:20.352310: Current learning rate: 0.00543 +2024-11-22 07:51:38.824326: train_loss -0.781 +2024-11-22 07:51:38.824617: val_loss -0.7754 +2024-11-22 07:51:38.824696: Pseudo dice [0.8514] +2024-11-22 07:51:38.824780: Epoch time: 18.47 s +2024-11-22 07:51:39.710364: +2024-11-22 07:51:39.710842: Epoch 3941 +2024-11-22 07:51:39.710975: Current learning rate: 0.00543 +2024-11-22 07:51:58.429236: train_loss -0.7912 +2024-11-22 07:51:58.429467: val_loss -0.7778 +2024-11-22 07:51:58.429540: Pseudo dice [0.8589] +2024-11-22 07:51:58.429615: Epoch time: 18.72 s +2024-11-22 07:51:59.475053: +2024-11-22 07:51:59.475502: Epoch 3942 +2024-11-22 07:51:59.475635: Current learning rate: 0.00543 +2024-11-22 07:52:18.971676: train_loss -0.7896 +2024-11-22 07:52:18.971898: val_loss -0.764 +2024-11-22 07:52:18.971972: Pseudo dice [0.8561] +2024-11-22 07:52:18.972055: Epoch time: 19.5 s +2024-11-22 07:52:19.851566: +2024-11-22 07:52:19.851995: Epoch 3943 +2024-11-22 07:52:19.852130: Current learning rate: 0.00543 +2024-11-22 07:52:38.406533: train_loss -0.7944 +2024-11-22 07:52:38.406763: val_loss -0.7798 +2024-11-22 07:52:38.406837: Pseudo dice [0.8316] +2024-11-22 07:52:38.406909: Epoch time: 18.56 s +2024-11-22 07:52:39.290515: +2024-11-22 07:52:39.290957: Epoch 3944 +2024-11-22 07:52:39.291100: Current learning rate: 0.00543 +2024-11-22 07:52:56.636142: train_loss -0.7983 +2024-11-22 07:52:56.636742: val_loss -0.7722 +2024-11-22 07:52:56.636849: Pseudo dice [0.846] +2024-11-22 07:52:56.636936: Epoch time: 17.35 s +2024-11-22 07:52:57.557179: +2024-11-22 07:52:57.557686: Epoch 3945 +2024-11-22 07:52:57.557818: Current learning rate: 0.00543 +2024-11-22 07:53:16.441267: train_loss -0.7828 +2024-11-22 07:53:16.441546: val_loss -0.7762 +2024-11-22 07:53:16.441625: Pseudo dice [0.8428] +2024-11-22 07:53:16.441701: Epoch time: 18.88 s +2024-11-22 07:53:17.324170: +2024-11-22 07:53:17.324616: Epoch 3946 +2024-11-22 07:53:17.324745: Current learning rate: 0.00542 +2024-11-22 07:53:36.434189: train_loss -0.7862 +2024-11-22 07:53:36.434404: val_loss -0.7641 +2024-11-22 07:53:36.434479: Pseudo dice [0.8429] +2024-11-22 07:53:36.434553: Epoch time: 19.11 s +2024-11-22 07:53:37.316410: +2024-11-22 07:53:37.316872: Epoch 3947 +2024-11-22 07:53:37.317016: Current learning rate: 0.00542 +2024-11-22 07:53:55.412682: train_loss -0.785 +2024-11-22 07:53:55.412902: val_loss -0.7567 +2024-11-22 07:53:55.412975: Pseudo dice [0.8505] +2024-11-22 07:53:55.413056: Epoch time: 18.1 s +2024-11-22 07:53:56.293807: +2024-11-22 07:53:56.294266: Epoch 3948 +2024-11-22 07:53:56.294410: Current learning rate: 0.00542 +2024-11-22 07:54:14.896338: train_loss -0.7941 +2024-11-22 07:54:14.896617: val_loss -0.7801 +2024-11-22 07:54:14.896693: Pseudo dice [0.8548] +2024-11-22 07:54:14.896771: Epoch time: 18.6 s +2024-11-22 07:54:15.802593: +2024-11-22 07:54:15.802805: Epoch 3949 +2024-11-22 07:54:15.802912: Current learning rate: 0.00542 +2024-11-22 07:54:34.482919: train_loss -0.7912 +2024-11-22 07:54:34.483146: val_loss -0.7742 +2024-11-22 07:54:34.483223: Pseudo dice [0.8472] +2024-11-22 07:54:34.483298: Epoch time: 18.68 s +2024-11-22 07:54:35.730552: +2024-11-22 07:54:35.730768: Epoch 3950 +2024-11-22 07:54:35.730873: Current learning rate: 0.00542 +2024-11-22 07:54:55.351367: train_loss -0.7878 +2024-11-22 07:54:55.351831: val_loss -0.7578 +2024-11-22 07:54:55.351932: Pseudo dice [0.8306] +2024-11-22 07:54:55.352017: Epoch time: 19.62 s +2024-11-22 07:54:56.241770: +2024-11-22 07:54:56.242014: Epoch 3951 +2024-11-22 07:54:56.242139: Current learning rate: 0.00542 +2024-11-22 07:55:14.082017: train_loss -0.7846 +2024-11-22 07:55:14.082335: val_loss -0.7737 +2024-11-22 07:55:14.082413: Pseudo dice [0.8558] +2024-11-22 07:55:14.082495: Epoch time: 17.84 s +2024-11-22 07:55:14.973238: +2024-11-22 07:55:14.973480: Epoch 3952 +2024-11-22 07:55:14.973588: Current learning rate: 0.00542 +2024-11-22 07:55:33.784638: train_loss -0.7973 +2024-11-22 07:55:33.784856: val_loss -0.7644 +2024-11-22 07:55:33.784936: Pseudo dice [0.8373] +2024-11-22 07:55:33.785019: Epoch time: 18.81 s +2024-11-22 07:55:34.666961: +2024-11-22 07:55:34.667234: Epoch 3953 +2024-11-22 07:55:34.667347: Current learning rate: 0.00542 +2024-11-22 07:55:52.763928: train_loss -0.7903 +2024-11-22 07:55:52.764159: val_loss -0.777 +2024-11-22 07:55:52.764237: Pseudo dice [0.8539] +2024-11-22 07:55:52.764313: Epoch time: 18.1 s +2024-11-22 07:55:53.653726: +2024-11-22 07:55:53.653957: Epoch 3954 +2024-11-22 07:55:53.654081: Current learning rate: 0.00541 +2024-11-22 07:56:12.454057: train_loss -0.7919 +2024-11-22 07:56:12.454300: val_loss -0.769 +2024-11-22 07:56:12.454379: Pseudo dice [0.8325] +2024-11-22 07:56:12.454457: Epoch time: 18.8 s +2024-11-22 07:56:13.355951: +2024-11-22 07:56:13.356302: Epoch 3955 +2024-11-22 07:56:13.356422: Current learning rate: 0.00541 +2024-11-22 07:56:32.332258: train_loss -0.7861 +2024-11-22 07:56:32.332470: val_loss -0.7657 +2024-11-22 07:56:32.332543: Pseudo dice [0.8469] +2024-11-22 07:56:32.332615: Epoch time: 18.98 s +2024-11-22 07:56:33.209375: +2024-11-22 07:56:33.209590: Epoch 3956 +2024-11-22 07:56:33.209697: Current learning rate: 0.00541 +2024-11-22 07:56:51.646910: train_loss -0.7842 +2024-11-22 07:56:51.647156: val_loss -0.7858 +2024-11-22 07:56:51.647231: Pseudo dice [0.8553] +2024-11-22 07:56:51.647313: Epoch time: 18.44 s +2024-11-22 07:56:52.525719: +2024-11-22 07:56:52.525994: Epoch 3957 +2024-11-22 07:56:52.526101: Current learning rate: 0.00541 +2024-11-22 07:57:10.817839: train_loss -0.7934 +2024-11-22 07:57:10.818075: val_loss -0.7726 +2024-11-22 07:57:10.818159: Pseudo dice [0.8545] +2024-11-22 07:57:10.818237: Epoch time: 18.29 s +2024-11-22 07:57:11.700899: +2024-11-22 07:57:11.701126: Epoch 3958 +2024-11-22 07:57:11.701238: Current learning rate: 0.00541 +2024-11-22 07:57:30.459479: train_loss -0.7926 +2024-11-22 07:57:30.459726: val_loss -0.8061 +2024-11-22 07:57:30.459802: Pseudo dice [0.8659] +2024-11-22 07:57:30.459881: Epoch time: 18.76 s +2024-11-22 07:57:31.341387: +2024-11-22 07:57:31.341599: Epoch 3959 +2024-11-22 07:57:31.341707: Current learning rate: 0.00541 +2024-11-22 07:57:49.465264: train_loss -0.7888 +2024-11-22 07:57:49.465485: val_loss -0.7776 +2024-11-22 07:57:49.465558: Pseudo dice [0.8562] +2024-11-22 07:57:49.465704: Epoch time: 18.12 s +2024-11-22 07:57:49.465766: Yayy! New best EMA pseudo Dice: 0.8499 +2024-11-22 07:57:50.702597: +2024-11-22 07:57:50.702818: Epoch 3960 +2024-11-22 07:57:50.702924: Current learning rate: 0.00541 +2024-11-22 07:58:10.112369: train_loss -0.7894 +2024-11-22 07:58:10.112589: val_loss -0.7982 +2024-11-22 07:58:10.112668: Pseudo dice [0.8534] +2024-11-22 07:58:10.112745: Epoch time: 19.41 s +2024-11-22 07:58:10.112806: Yayy! New best EMA pseudo Dice: 0.8502 +2024-11-22 07:58:11.621287: +2024-11-22 07:58:11.621607: Epoch 3961 +2024-11-22 07:58:11.621722: Current learning rate: 0.00541 +2024-11-22 07:58:29.810783: train_loss -0.7865 +2024-11-22 07:58:29.811144: val_loss -0.7818 +2024-11-22 07:58:29.811231: Pseudo dice [0.8545] +2024-11-22 07:58:29.811323: Epoch time: 18.19 s +2024-11-22 07:58:29.811388: Yayy! New best EMA pseudo Dice: 0.8507 +2024-11-22 07:58:30.951649: +2024-11-22 07:58:30.951870: Epoch 3962 +2024-11-22 07:58:30.951988: Current learning rate: 0.0054 +2024-11-22 07:58:49.210412: train_loss -0.784 +2024-11-22 07:58:49.210625: val_loss -0.7827 +2024-11-22 07:58:49.210700: Pseudo dice [0.8346] +2024-11-22 07:58:49.210775: Epoch time: 18.26 s +2024-11-22 07:58:50.090897: +2024-11-22 07:58:50.091141: Epoch 3963 +2024-11-22 07:58:50.091260: Current learning rate: 0.0054 +2024-11-22 07:59:09.108573: train_loss -0.7819 +2024-11-22 07:59:09.108793: val_loss -0.7656 +2024-11-22 07:59:09.108869: Pseudo dice [0.8359] +2024-11-22 07:59:09.108942: Epoch time: 19.02 s +2024-11-22 07:59:09.992347: +2024-11-22 07:59:09.992575: Epoch 3964 +2024-11-22 07:59:09.992690: Current learning rate: 0.0054 +2024-11-22 07:59:28.983958: train_loss -0.792 +2024-11-22 07:59:28.984191: val_loss -0.7594 +2024-11-22 07:59:28.984270: Pseudo dice [0.8576] +2024-11-22 07:59:28.984349: Epoch time: 18.99 s +2024-11-22 07:59:29.856766: +2024-11-22 07:59:29.857094: Epoch 3965 +2024-11-22 07:59:29.857205: Current learning rate: 0.0054 +2024-11-22 07:59:49.623882: train_loss -0.7876 +2024-11-22 07:59:49.624132: val_loss -0.7438 +2024-11-22 07:59:49.624207: Pseudo dice [0.8328] +2024-11-22 07:59:49.624289: Epoch time: 19.77 s +2024-11-22 07:59:50.507259: +2024-11-22 07:59:50.507471: Epoch 3966 +2024-11-22 07:59:50.507581: Current learning rate: 0.0054 +2024-11-22 08:00:09.373610: train_loss -0.767 +2024-11-22 08:00:09.373841: val_loss -0.7505 +2024-11-22 08:00:09.373916: Pseudo dice [0.8511] +2024-11-22 08:00:09.373996: Epoch time: 18.87 s +2024-11-22 08:00:10.327207: +2024-11-22 08:00:10.327436: Epoch 3967 +2024-11-22 08:00:10.327543: Current learning rate: 0.0054 +2024-11-22 08:00:29.130178: train_loss -0.774 +2024-11-22 08:00:29.130405: val_loss -0.7472 +2024-11-22 08:00:29.135703: Pseudo dice [0.8418] +2024-11-22 08:00:29.135842: Epoch time: 18.8 s +2024-11-22 08:00:30.034136: +2024-11-22 08:00:30.034366: Epoch 3968 +2024-11-22 08:00:30.034480: Current learning rate: 0.0054 +2024-11-22 08:00:48.855878: train_loss -0.7892 +2024-11-22 08:00:48.858316: val_loss -0.769 +2024-11-22 08:00:48.858412: Pseudo dice [0.8519] +2024-11-22 08:00:48.858491: Epoch time: 18.82 s +2024-11-22 08:00:49.886720: +2024-11-22 08:00:49.886940: Epoch 3969 +2024-11-22 08:00:49.887062: Current learning rate: 0.0054 +2024-11-22 08:01:09.002565: train_loss -0.7928 +2024-11-22 08:01:09.002809: val_loss -0.7645 +2024-11-22 08:01:09.002883: Pseudo dice [0.8369] +2024-11-22 08:01:09.002966: Epoch time: 19.12 s +2024-11-22 08:01:09.894762: +2024-11-22 08:01:09.894974: Epoch 3970 +2024-11-22 08:01:09.895089: Current learning rate: 0.0054 +2024-11-22 08:01:28.940497: train_loss -0.7821 +2024-11-22 08:01:28.940731: val_loss -0.7566 +2024-11-22 08:01:28.940810: Pseudo dice [0.8227] +2024-11-22 08:01:28.940883: Epoch time: 19.05 s +2024-11-22 08:01:29.818089: +2024-11-22 08:01:29.818302: Epoch 3971 +2024-11-22 08:01:29.818409: Current learning rate: 0.00539 +2024-11-22 08:01:48.109315: train_loss -0.7786 +2024-11-22 08:01:48.109541: val_loss -0.7726 +2024-11-22 08:01:48.109616: Pseudo dice [0.8409] +2024-11-22 08:01:48.109690: Epoch time: 18.29 s +2024-11-22 08:01:49.427178: +2024-11-22 08:01:49.427407: Epoch 3972 +2024-11-22 08:01:49.427516: Current learning rate: 0.00539 +2024-11-22 08:02:08.452703: train_loss -0.78 +2024-11-22 08:02:08.452965: val_loss -0.7471 +2024-11-22 08:02:08.453048: Pseudo dice [0.8461] +2024-11-22 08:02:08.453127: Epoch time: 19.03 s +2024-11-22 08:02:09.340269: +2024-11-22 08:02:09.340482: Epoch 3973 +2024-11-22 08:02:09.340588: Current learning rate: 0.00539 +2024-11-22 08:02:28.456843: train_loss -0.7896 +2024-11-22 08:02:28.457109: val_loss -0.7754 +2024-11-22 08:02:28.457193: Pseudo dice [0.8564] +2024-11-22 08:02:28.457273: Epoch time: 19.12 s +2024-11-22 08:02:29.335120: +2024-11-22 08:02:29.335336: Epoch 3974 +2024-11-22 08:02:29.335444: Current learning rate: 0.00539 +2024-11-22 08:02:48.593760: train_loss -0.783 +2024-11-22 08:02:48.593968: val_loss -0.7582 +2024-11-22 08:02:48.594072: Pseudo dice [0.8425] +2024-11-22 08:02:48.594156: Epoch time: 19.26 s +2024-11-22 08:02:49.474333: +2024-11-22 08:02:49.474567: Epoch 3975 +2024-11-22 08:02:49.474683: Current learning rate: 0.00539 +2024-11-22 08:03:07.464158: train_loss -0.788 +2024-11-22 08:03:07.464418: val_loss -0.767 +2024-11-22 08:03:07.464818: Pseudo dice [0.8396] +2024-11-22 08:03:07.464904: Epoch time: 17.99 s +2024-11-22 08:03:08.355036: +2024-11-22 08:03:08.355325: Epoch 3976 +2024-11-22 08:03:08.355440: Current learning rate: 0.00539 +2024-11-22 08:03:26.197328: train_loss -0.7827 +2024-11-22 08:03:26.197556: val_loss -0.7616 +2024-11-22 08:03:26.197629: Pseudo dice [0.8324] +2024-11-22 08:03:26.197711: Epoch time: 17.84 s +2024-11-22 08:03:27.079888: +2024-11-22 08:03:27.080159: Epoch 3977 +2024-11-22 08:03:27.080270: Current learning rate: 0.00539 +2024-11-22 08:03:45.358629: train_loss -0.7741 +2024-11-22 08:03:45.358862: val_loss -0.7883 +2024-11-22 08:03:45.364096: Pseudo dice [0.8408] +2024-11-22 08:03:45.364293: Epoch time: 18.28 s +2024-11-22 08:03:46.376364: +2024-11-22 08:03:46.376677: Epoch 3978 +2024-11-22 08:03:46.376791: Current learning rate: 0.00539 +2024-11-22 08:04:05.576469: train_loss -0.7782 +2024-11-22 08:04:05.576727: val_loss -0.7588 +2024-11-22 08:04:05.576804: Pseudo dice [0.8309] +2024-11-22 08:04:05.576880: Epoch time: 19.2 s +2024-11-22 08:04:06.552450: +2024-11-22 08:04:06.552684: Epoch 3979 +2024-11-22 08:04:06.552797: Current learning rate: 0.00538 +2024-11-22 08:04:26.037838: train_loss -0.7796 +2024-11-22 08:04:26.038083: val_loss -0.7737 +2024-11-22 08:04:26.038162: Pseudo dice [0.8319] +2024-11-22 08:04:26.038238: Epoch time: 19.49 s +2024-11-22 08:04:26.928856: +2024-11-22 08:04:26.929126: Epoch 3980 +2024-11-22 08:04:26.929234: Current learning rate: 0.00538 +2024-11-22 08:04:45.535094: train_loss -0.7838 +2024-11-22 08:04:45.535323: val_loss -0.785 +2024-11-22 08:04:45.535401: Pseudo dice [0.8561] +2024-11-22 08:04:45.535479: Epoch time: 18.61 s +2024-11-22 08:04:46.438021: +2024-11-22 08:04:46.438222: Epoch 3981 +2024-11-22 08:04:46.438330: Current learning rate: 0.00538 +2024-11-22 08:05:04.413745: train_loss -0.7897 +2024-11-22 08:05:04.413973: val_loss -0.7885 +2024-11-22 08:05:04.414073: Pseudo dice [0.8434] +2024-11-22 08:05:04.414151: Epoch time: 17.98 s +2024-11-22 08:05:05.298873: +2024-11-22 08:05:05.299101: Epoch 3982 +2024-11-22 08:05:05.299215: Current learning rate: 0.00538 +2024-11-22 08:05:23.129261: train_loss -0.7984 +2024-11-22 08:05:23.129488: val_loss -0.7419 +2024-11-22 08:05:23.129566: Pseudo dice [0.8359] +2024-11-22 08:05:23.129649: Epoch time: 17.83 s +2024-11-22 08:05:24.340808: +2024-11-22 08:05:24.341059: Epoch 3983 +2024-11-22 08:05:24.341185: Current learning rate: 0.00538 +2024-11-22 08:05:42.236677: train_loss -0.7935 +2024-11-22 08:05:42.236924: val_loss -0.7669 +2024-11-22 08:05:42.237032: Pseudo dice [0.8545] +2024-11-22 08:05:42.237111: Epoch time: 17.9 s +2024-11-22 08:05:43.124759: +2024-11-22 08:05:43.125154: Epoch 3984 +2024-11-22 08:05:43.125268: Current learning rate: 0.00538 +2024-11-22 08:06:01.975528: train_loss -0.789 +2024-11-22 08:06:01.975747: val_loss -0.7715 +2024-11-22 08:06:01.975824: Pseudo dice [0.8557] +2024-11-22 08:06:01.975901: Epoch time: 18.85 s +2024-11-22 08:06:02.877742: +2024-11-22 08:06:02.878037: Epoch 3985 +2024-11-22 08:06:02.878144: Current learning rate: 0.00538 +2024-11-22 08:06:21.350083: train_loss -0.7935 +2024-11-22 08:06:21.350318: val_loss -0.7569 +2024-11-22 08:06:21.350393: Pseudo dice [0.8514] +2024-11-22 08:06:21.350469: Epoch time: 18.47 s +2024-11-22 08:06:22.241004: +2024-11-22 08:06:22.241218: Epoch 3986 +2024-11-22 08:06:22.241322: Current learning rate: 0.00538 +2024-11-22 08:06:40.426069: train_loss -0.787 +2024-11-22 08:06:40.426337: val_loss -0.7595 +2024-11-22 08:06:40.426417: Pseudo dice [0.8342] +2024-11-22 08:06:40.426505: Epoch time: 18.19 s +2024-11-22 08:06:41.317047: +2024-11-22 08:06:41.317278: Epoch 3987 +2024-11-22 08:06:41.317401: Current learning rate: 0.00537 +2024-11-22 08:07:00.131397: train_loss -0.7735 +2024-11-22 08:07:00.131609: val_loss -0.7473 +2024-11-22 08:07:00.131692: Pseudo dice [0.8314] +2024-11-22 08:07:00.131797: Epoch time: 18.82 s +2024-11-22 08:07:01.017262: +2024-11-22 08:07:01.017562: Epoch 3988 +2024-11-22 08:07:01.017674: Current learning rate: 0.00537 +2024-11-22 08:07:20.182851: train_loss -0.7837 +2024-11-22 08:07:20.183080: val_loss -0.7723 +2024-11-22 08:07:20.183155: Pseudo dice [0.8473] +2024-11-22 08:07:20.183230: Epoch time: 19.17 s +2024-11-22 08:07:21.068717: +2024-11-22 08:07:21.068954: Epoch 3989 +2024-11-22 08:07:21.069072: Current learning rate: 0.00537 +2024-11-22 08:07:39.956058: train_loss -0.7939 +2024-11-22 08:07:39.956282: val_loss -0.7615 +2024-11-22 08:07:39.956360: Pseudo dice [0.847] +2024-11-22 08:07:39.956439: Epoch time: 18.89 s +2024-11-22 08:07:40.838306: +2024-11-22 08:07:40.838513: Epoch 3990 +2024-11-22 08:07:40.838621: Current learning rate: 0.00537 +2024-11-22 08:07:59.261410: train_loss -0.7879 +2024-11-22 08:07:59.261641: val_loss -0.7925 +2024-11-22 08:07:59.261715: Pseudo dice [0.8708] +2024-11-22 08:07:59.261792: Epoch time: 18.42 s +2024-11-22 08:08:00.142307: +2024-11-22 08:08:00.142542: Epoch 3991 +2024-11-22 08:08:00.142653: Current learning rate: 0.00537 +2024-11-22 08:08:18.981650: train_loss -0.7849 +2024-11-22 08:08:18.981866: val_loss -0.7818 +2024-11-22 08:08:18.981939: Pseudo dice [0.8553] +2024-11-22 08:08:18.982133: Epoch time: 18.84 s +2024-11-22 08:08:19.859154: +2024-11-22 08:08:19.859365: Epoch 3992 +2024-11-22 08:08:19.859478: Current learning rate: 0.00537 +2024-11-22 08:08:38.189477: train_loss -0.7944 +2024-11-22 08:08:38.189693: val_loss -0.7905 +2024-11-22 08:08:38.189768: Pseudo dice [0.8454] +2024-11-22 08:08:38.189838: Epoch time: 18.33 s +2024-11-22 08:08:39.068824: +2024-11-22 08:08:39.069032: Epoch 3993 +2024-11-22 08:08:39.069153: Current learning rate: 0.00537 +2024-11-22 08:08:58.382021: train_loss -0.789 +2024-11-22 08:08:58.382279: val_loss -0.768 +2024-11-22 08:08:58.382353: Pseudo dice [0.8457] +2024-11-22 08:08:58.382443: Epoch time: 19.31 s +2024-11-22 08:08:59.263819: +2024-11-22 08:08:59.264061: Epoch 3994 +2024-11-22 08:08:59.264183: Current learning rate: 0.00537 +2024-11-22 08:09:17.734008: train_loss -0.7665 +2024-11-22 08:09:17.734211: val_loss -0.7348 +2024-11-22 08:09:17.734285: Pseudo dice [0.8363] +2024-11-22 08:09:17.734358: Epoch time: 18.47 s +2024-11-22 08:09:19.019406: +2024-11-22 08:09:19.019822: Epoch 3995 +2024-11-22 08:09:19.019955: Current learning rate: 0.00536 +2024-11-22 08:09:38.017903: train_loss -0.7589 +2024-11-22 08:09:38.018129: val_loss -0.7795 +2024-11-22 08:09:38.018204: Pseudo dice [0.8302] +2024-11-22 08:09:38.018276: Epoch time: 19.0 s +2024-11-22 08:09:38.901973: +2024-11-22 08:09:38.902420: Epoch 3996 +2024-11-22 08:09:38.902552: Current learning rate: 0.00536 +2024-11-22 08:09:56.672776: train_loss -0.7837 +2024-11-22 08:09:56.673002: val_loss -0.7631 +2024-11-22 08:09:56.673135: Pseudo dice [0.8506] +2024-11-22 08:09:56.673221: Epoch time: 17.77 s +2024-11-22 08:09:57.553440: +2024-11-22 08:09:57.553908: Epoch 3997 +2024-11-22 08:09:57.554083: Current learning rate: 0.00536 +2024-11-22 08:10:15.780930: train_loss -0.7825 +2024-11-22 08:10:15.781173: val_loss -0.7409 +2024-11-22 08:10:15.781247: Pseudo dice [0.8249] +2024-11-22 08:10:15.781325: Epoch time: 18.23 s +2024-11-22 08:10:16.805043: +2024-11-22 08:10:16.805457: Epoch 3998 +2024-11-22 08:10:16.805587: Current learning rate: 0.00536 +2024-11-22 08:10:35.647863: train_loss -0.7834 +2024-11-22 08:10:35.648090: val_loss -0.763 +2024-11-22 08:10:35.648167: Pseudo dice [0.8343] +2024-11-22 08:10:35.648243: Epoch time: 18.84 s +2024-11-22 08:10:36.531717: +2024-11-22 08:10:36.532223: Epoch 3999 +2024-11-22 08:10:36.532349: Current learning rate: 0.00536 +2024-11-22 08:10:54.839927: train_loss -0.7786 +2024-11-22 08:10:54.840178: val_loss -0.7686 +2024-11-22 08:10:54.840257: Pseudo dice [0.8442] +2024-11-22 08:10:54.840340: Epoch time: 18.31 s +2024-11-22 08:10:56.141948: +2024-11-22 08:10:56.142399: Epoch 4000 +2024-11-22 08:10:56.142531: Current learning rate: 0.00536 +2024-11-22 08:11:14.765783: train_loss -0.7785 +2024-11-22 08:11:14.766017: val_loss -0.785 +2024-11-22 08:11:14.766097: Pseudo dice [0.8425] +2024-11-22 08:11:14.766197: Epoch time: 18.62 s +2024-11-22 08:11:15.647156: +2024-11-22 08:11:15.647587: Epoch 4001 +2024-11-22 08:11:15.647719: Current learning rate: 0.00536 +2024-11-22 08:11:34.702744: train_loss -0.7781 +2024-11-22 08:11:34.702984: val_loss -0.7613 +2024-11-22 08:11:34.703417: Pseudo dice [0.8344] +2024-11-22 08:11:34.703511: Epoch time: 19.06 s +2024-11-22 08:11:35.579931: +2024-11-22 08:11:35.580419: Epoch 4002 +2024-11-22 08:11:35.580555: Current learning rate: 0.00536 +2024-11-22 08:11:53.314443: train_loss -0.7884 +2024-11-22 08:11:53.314666: val_loss -0.7447 +2024-11-22 08:11:53.316849: Pseudo dice [0.8219] +2024-11-22 08:11:53.317082: Epoch time: 17.74 s +2024-11-22 08:11:54.230042: +2024-11-22 08:11:54.230519: Epoch 4003 +2024-11-22 08:11:54.230661: Current learning rate: 0.00536 +2024-11-22 08:12:12.903629: train_loss -0.7683 +2024-11-22 08:12:12.903843: val_loss -0.7455 +2024-11-22 08:12:12.903916: Pseudo dice [0.8451] +2024-11-22 08:12:12.903996: Epoch time: 18.67 s +2024-11-22 08:12:13.846600: +2024-11-22 08:12:13.847101: Epoch 4004 +2024-11-22 08:12:13.847240: Current learning rate: 0.00535 +2024-11-22 08:12:32.861322: train_loss -0.7795 +2024-11-22 08:12:32.861634: val_loss -0.7741 +2024-11-22 08:12:32.861719: Pseudo dice [0.8455] +2024-11-22 08:12:32.861811: Epoch time: 19.02 s +2024-11-22 08:12:33.746576: +2024-11-22 08:12:33.747054: Epoch 4005 +2024-11-22 08:12:33.747187: Current learning rate: 0.00535 +2024-11-22 08:12:51.023056: train_loss -0.7862 +2024-11-22 08:12:51.023271: val_loss -0.7751 +2024-11-22 08:12:51.023343: Pseudo dice [0.8419] +2024-11-22 08:12:51.023416: Epoch time: 17.28 s +2024-11-22 08:12:52.324294: +2024-11-22 08:12:52.324505: Epoch 4006 +2024-11-22 08:12:52.324613: Current learning rate: 0.00535 +2024-11-22 08:13:11.287048: train_loss -0.7847 +2024-11-22 08:13:11.287289: val_loss -0.7804 +2024-11-22 08:13:11.287376: Pseudo dice [0.8369] +2024-11-22 08:13:11.287454: Epoch time: 18.96 s +2024-11-22 08:13:12.169399: +2024-11-22 08:13:12.169615: Epoch 4007 +2024-11-22 08:13:12.169721: Current learning rate: 0.00535 +2024-11-22 08:13:30.992139: train_loss -0.7868 +2024-11-22 08:13:30.992393: val_loss -0.7373 +2024-11-22 08:13:30.992481: Pseudo dice [0.848] +2024-11-22 08:13:30.992562: Epoch time: 18.82 s +2024-11-22 08:13:31.895415: +2024-11-22 08:13:31.895627: Epoch 4008 +2024-11-22 08:13:31.895745: Current learning rate: 0.00535 +2024-11-22 08:13:49.876590: train_loss -0.7843 +2024-11-22 08:13:49.882000: val_loss -0.7734 +2024-11-22 08:13:49.882106: Pseudo dice [0.8571] +2024-11-22 08:13:49.882184: Epoch time: 17.98 s +2024-11-22 08:13:50.774398: +2024-11-22 08:13:50.774621: Epoch 4009 +2024-11-22 08:13:50.774733: Current learning rate: 0.00535 +2024-11-22 08:14:08.642262: train_loss -0.7798 +2024-11-22 08:14:08.642468: val_loss -0.7516 +2024-11-22 08:14:08.642542: Pseudo dice [0.8385] +2024-11-22 08:14:08.642615: Epoch time: 17.87 s +2024-11-22 08:14:09.524042: +2024-11-22 08:14:09.524279: Epoch 4010 +2024-11-22 08:14:09.524391: Current learning rate: 0.00535 +2024-11-22 08:14:28.354466: train_loss -0.7691 +2024-11-22 08:14:28.354687: val_loss -0.7763 +2024-11-22 08:14:28.354766: Pseudo dice [0.8451] +2024-11-22 08:14:28.354844: Epoch time: 18.83 s +2024-11-22 08:14:29.236970: +2024-11-22 08:14:29.237204: Epoch 4011 +2024-11-22 08:14:29.237318: Current learning rate: 0.00535 +2024-11-22 08:14:47.457437: train_loss -0.7698 +2024-11-22 08:14:47.459837: val_loss -0.7659 +2024-11-22 08:14:47.459923: Pseudo dice [0.8578] +2024-11-22 08:14:47.460010: Epoch time: 18.22 s +2024-11-22 08:14:48.473273: +2024-11-22 08:14:48.473486: Epoch 4012 +2024-11-22 08:14:48.473595: Current learning rate: 0.00534 +2024-11-22 08:15:07.694573: train_loss -0.777 +2024-11-22 08:15:07.694797: val_loss -0.7611 +2024-11-22 08:15:07.694873: Pseudo dice [0.8359] +2024-11-22 08:15:07.694947: Epoch time: 19.22 s +2024-11-22 08:15:08.585712: +2024-11-22 08:15:08.586001: Epoch 4013 +2024-11-22 08:15:08.586124: Current learning rate: 0.00534 +2024-11-22 08:15:28.417808: train_loss -0.782 +2024-11-22 08:15:28.418104: val_loss -0.7665 +2024-11-22 08:15:28.418185: Pseudo dice [0.8393] +2024-11-22 08:15:28.418263: Epoch time: 19.83 s +2024-11-22 08:15:29.298833: +2024-11-22 08:15:29.299047: Epoch 4014 +2024-11-22 08:15:29.299159: Current learning rate: 0.00534 +2024-11-22 08:15:47.816843: train_loss -0.7802 +2024-11-22 08:15:47.817061: val_loss -0.7554 +2024-11-22 08:15:47.817136: Pseudo dice [0.833] +2024-11-22 08:15:47.817211: Epoch time: 18.52 s +2024-11-22 08:15:48.695681: +2024-11-22 08:15:48.695940: Epoch 4015 +2024-11-22 08:15:48.696065: Current learning rate: 0.00534 +2024-11-22 08:16:07.295034: train_loss -0.7799 +2024-11-22 08:16:07.295278: val_loss -0.7727 +2024-11-22 08:16:07.295355: Pseudo dice [0.8389] +2024-11-22 08:16:07.295440: Epoch time: 18.6 s +2024-11-22 08:16:08.178321: +2024-11-22 08:16:08.178563: Epoch 4016 +2024-11-22 08:16:08.178676: Current learning rate: 0.00534 +2024-11-22 08:16:26.024839: train_loss -0.7862 +2024-11-22 08:16:26.025057: val_loss -0.7573 +2024-11-22 08:16:26.025132: Pseudo dice [0.8465] +2024-11-22 08:16:26.025208: Epoch time: 17.85 s +2024-11-22 08:16:27.274732: +2024-11-22 08:16:27.274963: Epoch 4017 +2024-11-22 08:16:27.275088: Current learning rate: 0.00534 +2024-11-22 08:16:45.387744: train_loss -0.7842 +2024-11-22 08:16:45.389005: val_loss -0.7806 +2024-11-22 08:16:45.389091: Pseudo dice [0.8513] +2024-11-22 08:16:45.389165: Epoch time: 18.11 s +2024-11-22 08:16:46.266293: +2024-11-22 08:16:46.266522: Epoch 4018 +2024-11-22 08:16:46.266631: Current learning rate: 0.00534 +2024-11-22 08:17:05.050463: train_loss -0.782 +2024-11-22 08:17:05.050707: val_loss -0.7655 +2024-11-22 08:17:05.050781: Pseudo dice [0.8501] +2024-11-22 08:17:05.050863: Epoch time: 18.78 s +2024-11-22 08:17:05.943606: +2024-11-22 08:17:05.943827: Epoch 4019 +2024-11-22 08:17:05.943946: Current learning rate: 0.00534 +2024-11-22 08:17:24.518524: train_loss -0.7864 +2024-11-22 08:17:24.518745: val_loss -0.7879 +2024-11-22 08:17:24.518819: Pseudo dice [0.8463] +2024-11-22 08:17:24.518910: Epoch time: 18.58 s +2024-11-22 08:17:25.507685: +2024-11-22 08:17:25.507888: Epoch 4020 +2024-11-22 08:17:25.508011: Current learning rate: 0.00533 +2024-11-22 08:17:43.744034: train_loss -0.7982 +2024-11-22 08:17:43.745089: val_loss -0.7951 +2024-11-22 08:17:43.745167: Pseudo dice [0.8552] +2024-11-22 08:17:43.745242: Epoch time: 18.24 s +2024-11-22 08:17:44.627498: +2024-11-22 08:17:44.627767: Epoch 4021 +2024-11-22 08:17:44.627880: Current learning rate: 0.00533 +2024-11-22 08:18:02.995425: train_loss -0.7849 +2024-11-22 08:18:02.995656: val_loss -0.764 +2024-11-22 08:18:02.995730: Pseudo dice [0.8551] +2024-11-22 08:18:02.995803: Epoch time: 18.37 s +2024-11-22 08:18:03.875674: +2024-11-22 08:18:03.875898: Epoch 4022 +2024-11-22 08:18:03.876013: Current learning rate: 0.00533 +2024-11-22 08:18:21.949901: train_loss -0.7987 +2024-11-22 08:18:21.950154: val_loss -0.7545 +2024-11-22 08:18:21.950229: Pseudo dice [0.8389] +2024-11-22 08:18:21.950313: Epoch time: 18.08 s +2024-11-22 08:18:22.830950: +2024-11-22 08:18:22.831216: Epoch 4023 +2024-11-22 08:18:22.831324: Current learning rate: 0.00533 +2024-11-22 08:18:40.886085: train_loss -0.7951 +2024-11-22 08:18:40.886296: val_loss -0.7385 +2024-11-22 08:18:40.886369: Pseudo dice [0.8489] +2024-11-22 08:18:40.886444: Epoch time: 18.06 s +2024-11-22 08:18:41.767334: +2024-11-22 08:18:41.767560: Epoch 4024 +2024-11-22 08:18:41.767668: Current learning rate: 0.00533 +2024-11-22 08:19:00.371819: train_loss -0.7959 +2024-11-22 08:19:00.372040: val_loss -0.7808 +2024-11-22 08:19:00.372117: Pseudo dice [0.8447] +2024-11-22 08:19:00.372192: Epoch time: 18.61 s +2024-11-22 08:19:01.259359: +2024-11-22 08:19:01.259582: Epoch 4025 +2024-11-22 08:19:01.259689: Current learning rate: 0.00533 +2024-11-22 08:19:19.842240: train_loss -0.791 +2024-11-22 08:19:19.842561: val_loss -0.7575 +2024-11-22 08:19:19.842681: Pseudo dice [0.8454] +2024-11-22 08:19:19.842765: Epoch time: 18.58 s +2024-11-22 08:19:20.727702: +2024-11-22 08:19:20.727947: Epoch 4026 +2024-11-22 08:19:20.728057: Current learning rate: 0.00533 +2024-11-22 08:19:40.057912: train_loss -0.789 +2024-11-22 08:19:40.058166: val_loss -0.758 +2024-11-22 08:19:40.058243: Pseudo dice [0.8158] +2024-11-22 08:19:40.058321: Epoch time: 19.33 s +2024-11-22 08:19:40.972870: +2024-11-22 08:19:40.973137: Epoch 4027 +2024-11-22 08:19:40.973253: Current learning rate: 0.00533 +2024-11-22 08:19:59.048714: train_loss -0.7848 +2024-11-22 08:19:59.049132: val_loss -0.7697 +2024-11-22 08:19:59.049222: Pseudo dice [0.8516] +2024-11-22 08:19:59.049298: Epoch time: 18.08 s +2024-11-22 08:19:59.928941: +2024-11-22 08:19:59.929152: Epoch 4028 +2024-11-22 08:19:59.929260: Current learning rate: 0.00533 +2024-11-22 08:20:18.799313: train_loss -0.7791 +2024-11-22 08:20:18.799525: val_loss -0.7829 +2024-11-22 08:20:18.799601: Pseudo dice [0.845] +2024-11-22 08:20:18.799676: Epoch time: 18.87 s +2024-11-22 08:20:20.076626: +2024-11-22 08:20:20.076854: Epoch 4029 +2024-11-22 08:20:20.076969: Current learning rate: 0.00532 +2024-11-22 08:20:38.479225: train_loss -0.7976 +2024-11-22 08:20:38.479472: val_loss -0.7595 +2024-11-22 08:20:38.484716: Pseudo dice [0.8414] +2024-11-22 08:20:38.484872: Epoch time: 18.4 s +2024-11-22 08:20:39.501330: +2024-11-22 08:20:39.501562: Epoch 4030 +2024-11-22 08:20:39.501674: Current learning rate: 0.00532 +2024-11-22 08:20:58.328315: train_loss -0.7917 +2024-11-22 08:20:58.330989: val_loss -0.771 +2024-11-22 08:20:58.331089: Pseudo dice [0.8573] +2024-11-22 08:20:58.331163: Epoch time: 18.83 s +2024-11-22 08:20:59.214884: +2024-11-22 08:20:59.215127: Epoch 4031 +2024-11-22 08:20:59.215238: Current learning rate: 0.00532 +2024-11-22 08:21:17.480585: train_loss -0.7898 +2024-11-22 08:21:17.480850: val_loss -0.7829 +2024-11-22 08:21:17.480963: Pseudo dice [0.8478] +2024-11-22 08:21:17.481051: Epoch time: 18.27 s +2024-11-22 08:21:18.370244: +2024-11-22 08:21:18.370451: Epoch 4032 +2024-11-22 08:21:18.370560: Current learning rate: 0.00532 +2024-11-22 08:21:36.846794: train_loss -0.7854 +2024-11-22 08:21:36.847044: val_loss -0.7726 +2024-11-22 08:21:36.847124: Pseudo dice [0.8419] +2024-11-22 08:21:36.847203: Epoch time: 18.48 s +2024-11-22 08:21:37.992010: +2024-11-22 08:21:37.992213: Epoch 4033 +2024-11-22 08:21:37.992324: Current learning rate: 0.00532 +2024-11-22 08:21:57.223072: train_loss -0.7831 +2024-11-22 08:21:57.223311: val_loss -0.7548 +2024-11-22 08:21:57.223386: Pseudo dice [0.8416] +2024-11-22 08:21:57.223462: Epoch time: 19.23 s +2024-11-22 08:21:58.103434: +2024-11-22 08:21:58.103788: Epoch 4034 +2024-11-22 08:21:58.103910: Current learning rate: 0.00532 +2024-11-22 08:22:16.542868: train_loss -0.7873 +2024-11-22 08:22:16.543109: val_loss -0.7305 +2024-11-22 08:22:16.543184: Pseudo dice [0.8172] +2024-11-22 08:22:16.543256: Epoch time: 18.44 s +2024-11-22 08:22:17.421922: +2024-11-22 08:22:17.422149: Epoch 4035 +2024-11-22 08:22:17.422262: Current learning rate: 0.00532 +2024-11-22 08:22:35.575770: train_loss -0.7931 +2024-11-22 08:22:35.576048: val_loss -0.7599 +2024-11-22 08:22:35.576127: Pseudo dice [0.8431] +2024-11-22 08:22:35.576200: Epoch time: 18.15 s +2024-11-22 08:22:36.453878: +2024-11-22 08:22:36.454130: Epoch 4036 +2024-11-22 08:22:36.454244: Current learning rate: 0.00532 +2024-11-22 08:22:54.448780: train_loss -0.7923 +2024-11-22 08:22:54.449051: val_loss -0.7831 +2024-11-22 08:22:54.449138: Pseudo dice [0.859] +2024-11-22 08:22:54.449219: Epoch time: 18.0 s +2024-11-22 08:22:55.335889: +2024-11-22 08:22:55.337575: Epoch 4037 +2024-11-22 08:22:55.337691: Current learning rate: 0.00531 +2024-11-22 08:23:14.563255: train_loss -0.7855 +2024-11-22 08:23:14.563476: val_loss -0.7588 +2024-11-22 08:23:14.563550: Pseudo dice [0.8444] +2024-11-22 08:23:14.565781: Epoch time: 19.23 s +2024-11-22 08:23:15.489473: +2024-11-22 08:23:15.489769: Epoch 4038 +2024-11-22 08:23:15.489880: Current learning rate: 0.00531 +2024-11-22 08:23:33.950306: train_loss -0.7868 +2024-11-22 08:23:33.950523: val_loss -0.7773 +2024-11-22 08:23:33.950597: Pseudo dice [0.8467] +2024-11-22 08:23:33.950670: Epoch time: 18.46 s +2024-11-22 08:23:34.828109: +2024-11-22 08:23:34.828337: Epoch 4039 +2024-11-22 08:23:34.828465: Current learning rate: 0.00531 +2024-11-22 08:23:53.857398: train_loss -0.7771 +2024-11-22 08:23:53.857617: val_loss -0.7666 +2024-11-22 08:23:53.857697: Pseudo dice [0.8374] +2024-11-22 08:23:53.857772: Epoch time: 19.03 s +2024-11-22 08:23:55.174870: +2024-11-22 08:23:55.175115: Epoch 4040 +2024-11-22 08:23:55.175234: Current learning rate: 0.00531 +2024-11-22 08:24:13.981009: train_loss -0.7899 +2024-11-22 08:24:13.981243: val_loss -0.7603 +2024-11-22 08:24:13.981332: Pseudo dice [0.8258] +2024-11-22 08:24:13.986035: Epoch time: 18.81 s +2024-11-22 08:24:14.876267: +2024-11-22 08:24:14.876646: Epoch 4041 +2024-11-22 08:24:14.876799: Current learning rate: 0.00531 +2024-11-22 08:24:32.559449: train_loss -0.7951 +2024-11-22 08:24:32.559666: val_loss -0.7746 +2024-11-22 08:24:32.559746: Pseudo dice [0.8276] +2024-11-22 08:24:32.559843: Epoch time: 17.68 s +2024-11-22 08:24:33.437307: +2024-11-22 08:24:33.437546: Epoch 4042 +2024-11-22 08:24:33.437657: Current learning rate: 0.00531 +2024-11-22 08:24:51.914339: train_loss -0.7915 +2024-11-22 08:24:51.914549: val_loss -0.7467 +2024-11-22 08:24:51.914624: Pseudo dice [0.8347] +2024-11-22 08:24:51.914703: Epoch time: 18.48 s +2024-11-22 08:24:52.800395: +2024-11-22 08:24:52.800611: Epoch 4043 +2024-11-22 08:24:52.800720: Current learning rate: 0.00531 +2024-11-22 08:25:11.299882: train_loss -0.7822 +2024-11-22 08:25:11.300119: val_loss -0.7623 +2024-11-22 08:25:11.300192: Pseudo dice [0.8429] +2024-11-22 08:25:11.300270: Epoch time: 18.5 s +2024-11-22 08:25:12.179944: +2024-11-22 08:25:12.180175: Epoch 4044 +2024-11-22 08:25:12.180288: Current learning rate: 0.00531 +2024-11-22 08:25:29.970569: train_loss -0.793 +2024-11-22 08:25:29.970803: val_loss -0.7784 +2024-11-22 08:25:29.970879: Pseudo dice [0.8386] +2024-11-22 08:25:29.970958: Epoch time: 17.79 s +2024-11-22 08:25:30.856647: +2024-11-22 08:25:30.856875: Epoch 4045 +2024-11-22 08:25:30.856986: Current learning rate: 0.0053 +2024-11-22 08:25:48.629012: train_loss -0.7938 +2024-11-22 08:25:48.629292: val_loss -0.7867 +2024-11-22 08:25:48.629371: Pseudo dice [0.8518] +2024-11-22 08:25:48.629447: Epoch time: 17.77 s +2024-11-22 08:25:49.516927: +2024-11-22 08:25:49.517167: Epoch 4046 +2024-11-22 08:25:49.517276: Current learning rate: 0.0053 +2024-11-22 08:26:08.964382: train_loss -0.7884 +2024-11-22 08:26:08.964615: val_loss -0.7941 +2024-11-22 08:26:08.964694: Pseudo dice [0.8563] +2024-11-22 08:26:08.964774: Epoch time: 19.45 s +2024-11-22 08:26:09.851359: +2024-11-22 08:26:09.851574: Epoch 4047 +2024-11-22 08:26:09.851685: Current learning rate: 0.0053 +2024-11-22 08:26:27.731817: train_loss -0.7935 +2024-11-22 08:26:27.732092: val_loss -0.7705 +2024-11-22 08:26:27.732174: Pseudo dice [0.849] +2024-11-22 08:26:27.732259: Epoch time: 17.88 s +2024-11-22 08:26:28.780398: +2024-11-22 08:26:28.780612: Epoch 4048 +2024-11-22 08:26:28.780728: Current learning rate: 0.0053 +2024-11-22 08:26:47.049699: train_loss -0.791 +2024-11-22 08:26:47.049968: val_loss -0.7384 +2024-11-22 08:26:47.050050: Pseudo dice [0.8421] +2024-11-22 08:26:47.050122: Epoch time: 18.27 s +2024-11-22 08:26:47.931553: +2024-11-22 08:26:47.931785: Epoch 4049 +2024-11-22 08:26:47.931894: Current learning rate: 0.0053 +2024-11-22 08:27:06.308938: train_loss -0.7929 +2024-11-22 08:27:06.309158: val_loss -0.7764 +2024-11-22 08:27:06.309236: Pseudo dice [0.8436] +2024-11-22 08:27:06.309313: Epoch time: 18.38 s +2024-11-22 08:27:07.644671: +2024-11-22 08:27:07.644890: Epoch 4050 +2024-11-22 08:27:07.645007: Current learning rate: 0.0053 +2024-11-22 08:27:26.145026: train_loss -0.7881 +2024-11-22 08:27:26.145243: val_loss -0.7688 +2024-11-22 08:27:26.145331: Pseudo dice [0.8511] +2024-11-22 08:27:26.145464: Epoch time: 18.5 s +2024-11-22 08:27:27.025175: +2024-11-22 08:27:27.025602: Epoch 4051 +2024-11-22 08:27:27.025733: Current learning rate: 0.0053 +2024-11-22 08:27:46.147489: train_loss -0.781 +2024-11-22 08:27:46.147941: val_loss -0.7579 +2024-11-22 08:27:46.148048: Pseudo dice [0.8292] +2024-11-22 08:27:46.148123: Epoch time: 19.12 s +2024-11-22 08:27:47.020625: +2024-11-22 08:27:47.020843: Epoch 4052 +2024-11-22 08:27:47.020951: Current learning rate: 0.0053 +2024-11-22 08:28:05.563680: train_loss -0.7827 +2024-11-22 08:28:05.563900: val_loss -0.7555 +2024-11-22 08:28:05.563979: Pseudo dice [0.839] +2024-11-22 08:28:05.564075: Epoch time: 18.54 s +2024-11-22 08:28:06.440019: +2024-11-22 08:28:06.440256: Epoch 4053 +2024-11-22 08:28:06.440366: Current learning rate: 0.00529 +2024-11-22 08:28:24.959327: train_loss -0.7645 +2024-11-22 08:28:24.959834: val_loss -0.7562 +2024-11-22 08:28:24.959924: Pseudo dice [0.8405] +2024-11-22 08:28:24.960007: Epoch time: 18.52 s +2024-11-22 08:28:25.935560: +2024-11-22 08:28:25.935810: Epoch 4054 +2024-11-22 08:28:25.935918: Current learning rate: 0.00529 +2024-11-22 08:28:44.217888: train_loss -0.7823 +2024-11-22 08:28:44.218113: val_loss -0.7626 +2024-11-22 08:28:44.218190: Pseudo dice [0.8285] +2024-11-22 08:28:44.218266: Epoch time: 18.28 s +2024-11-22 08:28:45.110262: +2024-11-22 08:28:45.110552: Epoch 4055 +2024-11-22 08:28:45.110661: Current learning rate: 0.00529 +2024-11-22 08:29:03.195051: train_loss -0.7799 +2024-11-22 08:29:03.195276: val_loss -0.7556 +2024-11-22 08:29:03.195353: Pseudo dice [0.8481] +2024-11-22 08:29:03.195428: Epoch time: 18.09 s +2024-11-22 08:29:04.085966: +2024-11-22 08:29:04.086317: Epoch 4056 +2024-11-22 08:29:04.086432: Current learning rate: 0.00529 +2024-11-22 08:29:22.304556: train_loss -0.7838 +2024-11-22 08:29:22.304769: val_loss -0.7715 +2024-11-22 08:29:22.304845: Pseudo dice [0.8399] +2024-11-22 08:29:22.304917: Epoch time: 18.22 s +2024-11-22 08:29:23.186800: +2024-11-22 08:29:23.187015: Epoch 4057 +2024-11-22 08:29:23.187123: Current learning rate: 0.00529 +2024-11-22 08:29:42.003253: train_loss -0.7853 +2024-11-22 08:29:42.003466: val_loss -0.7701 +2024-11-22 08:29:42.003546: Pseudo dice [0.8294] +2024-11-22 08:29:42.003625: Epoch time: 18.82 s +2024-11-22 08:29:42.885877: +2024-11-22 08:29:42.886096: Epoch 4058 +2024-11-22 08:29:42.886209: Current learning rate: 0.00529 +2024-11-22 08:30:02.003597: train_loss -0.7829 +2024-11-22 08:30:02.003851: val_loss -0.7454 +2024-11-22 08:30:02.003933: Pseudo dice [0.8281] +2024-11-22 08:30:02.004022: Epoch time: 19.12 s +2024-11-22 08:30:02.885341: +2024-11-22 08:30:02.885555: Epoch 4059 +2024-11-22 08:30:02.885668: Current learning rate: 0.00529 +2024-11-22 08:30:21.933100: train_loss -0.773 +2024-11-22 08:30:21.933322: val_loss -0.7715 +2024-11-22 08:30:21.933407: Pseudo dice [0.8386] +2024-11-22 08:30:21.933482: Epoch time: 19.05 s +2024-11-22 08:30:22.812798: +2024-11-22 08:30:22.813026: Epoch 4060 +2024-11-22 08:30:22.813146: Current learning rate: 0.00529 +2024-11-22 08:30:41.440398: train_loss -0.7867 +2024-11-22 08:30:41.440629: val_loss -0.7574 +2024-11-22 08:30:41.440714: Pseudo dice [0.8378] +2024-11-22 08:30:41.440795: Epoch time: 18.63 s +2024-11-22 08:30:42.338748: +2024-11-22 08:30:42.338974: Epoch 4061 +2024-11-22 08:30:42.339088: Current learning rate: 0.00529 +2024-11-22 08:31:00.427217: train_loss -0.7855 +2024-11-22 08:31:00.427485: val_loss -0.7763 +2024-11-22 08:31:00.427562: Pseudo dice [0.844] +2024-11-22 08:31:00.427645: Epoch time: 18.09 s +2024-11-22 08:31:01.721656: +2024-11-22 08:31:01.721872: Epoch 4062 +2024-11-22 08:31:01.721980: Current learning rate: 0.00528 +2024-11-22 08:31:19.537185: train_loss -0.7841 +2024-11-22 08:31:19.537424: val_loss -0.7488 +2024-11-22 08:31:19.537507: Pseudo dice [0.8195] +2024-11-22 08:31:19.537591: Epoch time: 17.82 s +2024-11-22 08:31:20.605434: +2024-11-22 08:31:20.605658: Epoch 4063 +2024-11-22 08:31:20.605767: Current learning rate: 0.00528 +2024-11-22 08:31:38.327652: train_loss -0.7759 +2024-11-22 08:31:38.327870: val_loss -0.78 +2024-11-22 08:31:38.327963: Pseudo dice [0.8431] +2024-11-22 08:31:38.328057: Epoch time: 17.72 s +2024-11-22 08:31:39.202530: +2024-11-22 08:31:39.202765: Epoch 4064 +2024-11-22 08:31:39.202883: Current learning rate: 0.00528 +2024-11-22 08:31:57.900931: train_loss -0.7821 +2024-11-22 08:31:57.901173: val_loss -0.7684 +2024-11-22 08:31:57.901247: Pseudo dice [0.8252] +2024-11-22 08:31:57.901327: Epoch time: 18.7 s +2024-11-22 08:31:58.789368: +2024-11-22 08:31:58.789593: Epoch 4065 +2024-11-22 08:31:58.789705: Current learning rate: 0.00528 +2024-11-22 08:32:18.414209: train_loss -0.7839 +2024-11-22 08:32:18.414438: val_loss -0.7469 +2024-11-22 08:32:18.414515: Pseudo dice [0.8455] +2024-11-22 08:32:18.414592: Epoch time: 19.63 s +2024-11-22 08:32:19.353126: +2024-11-22 08:32:19.353363: Epoch 4066 +2024-11-22 08:32:19.353475: Current learning rate: 0.00528 +2024-11-22 08:32:38.494272: train_loss -0.7721 +2024-11-22 08:32:38.494483: val_loss -0.7739 +2024-11-22 08:32:38.494598: Pseudo dice [0.8558] +2024-11-22 08:32:38.494675: Epoch time: 19.14 s +2024-11-22 08:32:39.385844: +2024-11-22 08:32:39.386064: Epoch 4067 +2024-11-22 08:32:39.386173: Current learning rate: 0.00528 +2024-11-22 08:32:57.769322: train_loss -0.7816 +2024-11-22 08:32:57.769539: val_loss -0.7554 +2024-11-22 08:32:57.769612: Pseudo dice [0.8461] +2024-11-22 08:32:57.769685: Epoch time: 18.38 s +2024-11-22 08:32:58.651214: +2024-11-22 08:32:58.651428: Epoch 4068 +2024-11-22 08:32:58.651543: Current learning rate: 0.00528 +2024-11-22 08:33:17.603512: train_loss -0.7865 +2024-11-22 08:33:17.603748: val_loss -0.77 +2024-11-22 08:33:17.606095: Pseudo dice [0.8516] +2024-11-22 08:33:17.606203: Epoch time: 18.95 s +2024-11-22 08:33:18.513811: +2024-11-22 08:33:18.514049: Epoch 4069 +2024-11-22 08:33:18.514189: Current learning rate: 0.00528 +2024-11-22 08:33:38.585538: train_loss -0.7817 +2024-11-22 08:33:38.585788: val_loss -0.7841 +2024-11-22 08:33:38.585896: Pseudo dice [0.8467] +2024-11-22 08:33:38.585979: Epoch time: 20.07 s +2024-11-22 08:33:39.471437: +2024-11-22 08:33:39.471653: Epoch 4070 +2024-11-22 08:33:39.471767: Current learning rate: 0.00527 +2024-11-22 08:33:57.393344: train_loss -0.7844 +2024-11-22 08:33:57.393566: val_loss -0.7578 +2024-11-22 08:33:57.393641: Pseudo dice [0.8381] +2024-11-22 08:33:57.393719: Epoch time: 17.92 s +2024-11-22 08:33:58.272102: +2024-11-22 08:33:58.272319: Epoch 4071 +2024-11-22 08:33:58.272435: Current learning rate: 0.00527 +2024-11-22 08:34:17.253879: train_loss -0.7879 +2024-11-22 08:34:17.254101: val_loss -0.7807 +2024-11-22 08:34:17.254174: Pseudo dice [0.848] +2024-11-22 08:34:17.254247: Epoch time: 18.98 s +2024-11-22 08:34:18.134651: +2024-11-22 08:34:18.134879: Epoch 4072 +2024-11-22 08:34:18.134986: Current learning rate: 0.00527 +2024-11-22 08:34:35.822831: train_loss -0.788 +2024-11-22 08:34:35.823133: val_loss -0.7452 +2024-11-22 08:34:35.823214: Pseudo dice [0.8268] +2024-11-22 08:34:35.823298: Epoch time: 17.69 s +2024-11-22 08:34:36.704774: +2024-11-22 08:34:36.704989: Epoch 4073 +2024-11-22 08:34:36.705110: Current learning rate: 0.00527 +2024-11-22 08:34:55.928165: train_loss -0.7862 +2024-11-22 08:34:55.928441: val_loss -0.7548 +2024-11-22 08:34:55.928520: Pseudo dice [0.8167] +2024-11-22 08:34:55.928609: Epoch time: 19.22 s +2024-11-22 08:34:57.152198: +2024-11-22 08:34:57.152420: Epoch 4074 +2024-11-22 08:34:57.152533: Current learning rate: 0.00527 +2024-11-22 08:35:16.186666: train_loss -0.7776 +2024-11-22 08:35:16.186900: val_loss -0.7475 +2024-11-22 08:35:16.186981: Pseudo dice [0.8384] +2024-11-22 08:35:16.187069: Epoch time: 19.04 s +2024-11-22 08:35:17.067627: +2024-11-22 08:35:17.067830: Epoch 4075 +2024-11-22 08:35:17.067936: Current learning rate: 0.00527 +2024-11-22 08:35:35.719572: train_loss -0.7801 +2024-11-22 08:35:35.719826: val_loss -0.7611 +2024-11-22 08:35:35.719903: Pseudo dice [0.8344] +2024-11-22 08:35:35.719988: Epoch time: 18.65 s +2024-11-22 08:35:36.608334: +2024-11-22 08:35:36.608560: Epoch 4076 +2024-11-22 08:35:36.608674: Current learning rate: 0.00527 +2024-11-22 08:35:54.980046: train_loss -0.7802 +2024-11-22 08:35:54.980272: val_loss -0.7772 +2024-11-22 08:35:54.980350: Pseudo dice [0.8549] +2024-11-22 08:35:54.980424: Epoch time: 18.37 s +2024-11-22 08:35:56.023327: +2024-11-22 08:35:56.023559: Epoch 4077 +2024-11-22 08:35:56.023665: Current learning rate: 0.00527 +2024-11-22 08:36:14.123617: train_loss -0.7925 +2024-11-22 08:36:14.123829: val_loss -0.7738 +2024-11-22 08:36:14.123900: Pseudo dice [0.845] +2024-11-22 08:36:14.123973: Epoch time: 18.1 s +2024-11-22 08:36:15.018044: +2024-11-22 08:36:15.018267: Epoch 4078 +2024-11-22 08:36:15.018378: Current learning rate: 0.00526 +2024-11-22 08:36:33.312017: train_loss -0.7802 +2024-11-22 08:36:33.312267: val_loss -0.7721 +2024-11-22 08:36:33.312348: Pseudo dice [0.8403] +2024-11-22 08:36:33.312430: Epoch time: 18.29 s +2024-11-22 08:36:34.198778: +2024-11-22 08:36:34.199004: Epoch 4079 +2024-11-22 08:36:34.199115: Current learning rate: 0.00526 +2024-11-22 08:36:51.880333: train_loss -0.7907 +2024-11-22 08:36:51.880582: val_loss -0.7509 +2024-11-22 08:36:51.880714: Pseudo dice [0.8398] +2024-11-22 08:36:51.880793: Epoch time: 17.68 s +2024-11-22 08:36:52.767221: +2024-11-22 08:36:52.767456: Epoch 4080 +2024-11-22 08:36:52.767569: Current learning rate: 0.00526 +2024-11-22 08:37:10.544534: train_loss -0.7911 +2024-11-22 08:37:10.544763: val_loss -0.7828 +2024-11-22 08:37:10.544838: Pseudo dice [0.8515] +2024-11-22 08:37:10.544914: Epoch time: 17.78 s +2024-11-22 08:37:11.445152: +2024-11-22 08:37:11.445357: Epoch 4081 +2024-11-22 08:37:11.445467: Current learning rate: 0.00526 +2024-11-22 08:37:29.891412: train_loss -0.7916 +2024-11-22 08:37:29.891706: val_loss -0.7875 +2024-11-22 08:37:29.891807: Pseudo dice [0.8644] +2024-11-22 08:37:29.891888: Epoch time: 18.45 s +2024-11-22 08:37:30.779786: +2024-11-22 08:37:30.780037: Epoch 4082 +2024-11-22 08:37:30.780144: Current learning rate: 0.00526 +2024-11-22 08:37:48.658784: train_loss -0.7874 +2024-11-22 08:37:48.659006: val_loss -0.7509 +2024-11-22 08:37:48.659085: Pseudo dice [0.8262] +2024-11-22 08:37:48.659165: Epoch time: 17.88 s +2024-11-22 08:37:49.546392: +2024-11-22 08:37:49.546602: Epoch 4083 +2024-11-22 08:37:49.546714: Current learning rate: 0.00526 +2024-11-22 08:38:07.557835: train_loss -0.7829 +2024-11-22 08:38:07.558092: val_loss -0.7572 +2024-11-22 08:38:07.558172: Pseudo dice [0.8295] +2024-11-22 08:38:07.558248: Epoch time: 18.01 s +2024-11-22 08:38:08.589465: +2024-11-22 08:38:08.589679: Epoch 4084 +2024-11-22 08:38:08.589787: Current learning rate: 0.00526 +2024-11-22 08:38:26.786880: train_loss -0.7927 +2024-11-22 08:38:26.787102: val_loss -0.7615 +2024-11-22 08:38:26.787176: Pseudo dice [0.848] +2024-11-22 08:38:26.787251: Epoch time: 18.2 s +2024-11-22 08:38:28.024779: +2024-11-22 08:38:28.025015: Epoch 4085 +2024-11-22 08:38:28.025128: Current learning rate: 0.00526 +2024-11-22 08:38:45.440313: train_loss -0.779 +2024-11-22 08:38:45.440557: val_loss -0.75 +2024-11-22 08:38:45.440639: Pseudo dice [0.8478] +2024-11-22 08:38:45.440719: Epoch time: 17.42 s +2024-11-22 08:38:46.325198: +2024-11-22 08:38:46.325410: Epoch 4086 +2024-11-22 08:38:46.325517: Current learning rate: 0.00526 +2024-11-22 08:39:05.156825: train_loss -0.7838 +2024-11-22 08:39:05.157051: val_loss -0.7597 +2024-11-22 08:39:05.157131: Pseudo dice [0.8232] +2024-11-22 08:39:05.157207: Epoch time: 18.83 s +2024-11-22 08:39:06.040359: +2024-11-22 08:39:06.040584: Epoch 4087 +2024-11-22 08:39:06.040701: Current learning rate: 0.00525 +2024-11-22 08:39:24.135750: train_loss -0.7924 +2024-11-22 08:39:24.136053: val_loss -0.7822 +2024-11-22 08:39:24.136133: Pseudo dice [0.8525] +2024-11-22 08:39:24.136204: Epoch time: 18.1 s +2024-11-22 08:39:25.018389: +2024-11-22 08:39:25.018623: Epoch 4088 +2024-11-22 08:39:25.018728: Current learning rate: 0.00525 +2024-11-22 08:39:43.604259: train_loss -0.7831 +2024-11-22 08:39:43.604494: val_loss -0.7398 +2024-11-22 08:39:43.604596: Pseudo dice [0.8461] +2024-11-22 08:39:43.604679: Epoch time: 18.59 s +2024-11-22 08:39:44.498689: +2024-11-22 08:39:44.498956: Epoch 4089 +2024-11-22 08:39:44.499077: Current learning rate: 0.00525 +2024-11-22 08:40:04.543474: train_loss -0.7851 +2024-11-22 08:40:04.543701: val_loss -0.7708 +2024-11-22 08:40:04.543805: Pseudo dice [0.8424] +2024-11-22 08:40:04.543887: Epoch time: 20.05 s +2024-11-22 08:40:05.449329: +2024-11-22 08:40:05.449572: Epoch 4090 +2024-11-22 08:40:05.449683: Current learning rate: 0.00525 +2024-11-22 08:40:24.127309: train_loss -0.7883 +2024-11-22 08:40:24.127546: val_loss -0.7703 +2024-11-22 08:40:24.127618: Pseudo dice [0.8397] +2024-11-22 08:40:24.127692: Epoch time: 18.68 s +2024-11-22 08:40:25.024822: +2024-11-22 08:40:25.025053: Epoch 4091 +2024-11-22 08:40:25.025165: Current learning rate: 0.00525 +2024-11-22 08:40:44.007004: train_loss -0.7889 +2024-11-22 08:40:44.007221: val_loss -0.7847 +2024-11-22 08:40:44.007294: Pseudo dice [0.8388] +2024-11-22 08:40:44.007369: Epoch time: 18.98 s +2024-11-22 08:40:44.887223: +2024-11-22 08:40:44.887439: Epoch 4092 +2024-11-22 08:40:44.887549: Current learning rate: 0.00525 +2024-11-22 08:41:04.237978: train_loss -0.778 +2024-11-22 08:41:04.238205: val_loss -0.7887 +2024-11-22 08:41:04.238276: Pseudo dice [0.8542] +2024-11-22 08:41:04.238358: Epoch time: 19.35 s +2024-11-22 08:41:05.130538: +2024-11-22 08:41:05.130769: Epoch 4093 +2024-11-22 08:41:05.130885: Current learning rate: 0.00525 +2024-11-22 08:41:23.634351: train_loss -0.7879 +2024-11-22 08:41:23.634590: val_loss -0.763 +2024-11-22 08:41:23.634666: Pseudo dice [0.8392] +2024-11-22 08:41:23.634776: Epoch time: 18.5 s +2024-11-22 08:41:24.489242: +2024-11-22 08:41:24.489610: Epoch 4094 +2024-11-22 08:41:24.489725: Current learning rate: 0.00525 +2024-11-22 08:41:42.864213: train_loss -0.7745 +2024-11-22 08:41:42.864440: val_loss -0.7454 +2024-11-22 08:41:42.864516: Pseudo dice [0.835] +2024-11-22 08:41:42.864591: Epoch time: 18.38 s +2024-11-22 08:41:43.721803: +2024-11-22 08:41:43.722176: Epoch 4095 +2024-11-22 08:41:43.722287: Current learning rate: 0.00524 +2024-11-22 08:42:02.155962: train_loss -0.7837 +2024-11-22 08:42:02.156260: val_loss -0.7761 +2024-11-22 08:42:02.156345: Pseudo dice [0.8484] +2024-11-22 08:42:02.156429: Epoch time: 18.43 s +2024-11-22 08:42:03.060541: +2024-11-22 08:42:03.060748: Epoch 4096 +2024-11-22 08:42:03.060859: Current learning rate: 0.00524 +2024-11-22 08:42:20.817237: train_loss -0.7827 +2024-11-22 08:42:20.817478: val_loss -0.7703 +2024-11-22 08:42:20.817554: Pseudo dice [0.8593] +2024-11-22 08:42:20.817632: Epoch time: 17.76 s +2024-11-22 08:42:22.190695: +2024-11-22 08:42:22.190928: Epoch 4097 +2024-11-22 08:42:22.191048: Current learning rate: 0.00524 +2024-11-22 08:42:39.677680: train_loss -0.7902 +2024-11-22 08:42:39.677910: val_loss -0.7824 +2024-11-22 08:42:39.677983: Pseudo dice [0.8563] +2024-11-22 08:42:39.678058: Epoch time: 17.49 s +2024-11-22 08:42:40.538539: +2024-11-22 08:42:40.538771: Epoch 4098 +2024-11-22 08:42:40.538882: Current learning rate: 0.00524 +2024-11-22 08:42:59.645393: train_loss -0.7854 +2024-11-22 08:42:59.645607: val_loss -0.7755 +2024-11-22 08:42:59.645681: Pseudo dice [0.8692] +2024-11-22 08:42:59.645755: Epoch time: 19.11 s +2024-11-22 08:43:00.556115: +2024-11-22 08:43:00.556346: Epoch 4099 +2024-11-22 08:43:00.556465: Current learning rate: 0.00524 +2024-11-22 08:43:19.677402: train_loss -0.7876 +2024-11-22 08:43:19.677648: val_loss -0.7472 +2024-11-22 08:43:19.677724: Pseudo dice [0.8421] +2024-11-22 08:43:19.677803: Epoch time: 19.12 s +2024-11-22 08:43:20.801149: +2024-11-22 08:43:20.801387: Epoch 4100 +2024-11-22 08:43:20.801494: Current learning rate: 0.00524 +2024-11-22 08:43:38.691905: train_loss -0.7748 +2024-11-22 08:43:38.692137: val_loss -0.7488 +2024-11-22 08:43:38.692215: Pseudo dice [0.8457] +2024-11-22 08:43:38.692291: Epoch time: 17.89 s +2024-11-22 08:43:39.556403: +2024-11-22 08:43:39.556638: Epoch 4101 +2024-11-22 08:43:39.556748: Current learning rate: 0.00524 +2024-11-22 08:43:57.817444: train_loss -0.7791 +2024-11-22 08:43:57.817658: val_loss -0.7679 +2024-11-22 08:43:57.817731: Pseudo dice [0.838] +2024-11-22 08:43:57.817801: Epoch time: 18.26 s +2024-11-22 08:43:58.719938: +2024-11-22 08:43:58.720168: Epoch 4102 +2024-11-22 08:43:58.720281: Current learning rate: 0.00524 +2024-11-22 08:44:16.093662: train_loss -0.7877 +2024-11-22 08:44:16.093887: val_loss -0.7815 +2024-11-22 08:44:16.093966: Pseudo dice [0.8668] +2024-11-22 08:44:16.094052: Epoch time: 17.37 s +2024-11-22 08:44:16.987551: +2024-11-22 08:44:16.987778: Epoch 4103 +2024-11-22 08:44:16.987885: Current learning rate: 0.00523 +2024-11-22 08:44:36.004922: train_loss -0.7922 +2024-11-22 08:44:36.005201: val_loss -0.7722 +2024-11-22 08:44:36.005277: Pseudo dice [0.8492] +2024-11-22 08:44:36.005354: Epoch time: 19.02 s +2024-11-22 08:44:36.873575: +2024-11-22 08:44:36.873812: Epoch 4104 +2024-11-22 08:44:36.873928: Current learning rate: 0.00523 +2024-11-22 08:44:55.185972: train_loss -0.7896 +2024-11-22 08:44:55.186201: val_loss -0.7935 +2024-11-22 08:44:55.186281: Pseudo dice [0.8382] +2024-11-22 08:44:55.186357: Epoch time: 18.31 s +2024-11-22 08:44:56.105824: +2024-11-22 08:44:56.106058: Epoch 4105 +2024-11-22 08:44:56.106167: Current learning rate: 0.00523 +2024-11-22 08:45:14.550404: train_loss -0.7839 +2024-11-22 08:45:14.550616: val_loss -0.7603 +2024-11-22 08:45:14.550694: Pseudo dice [0.8445] +2024-11-22 08:45:14.550768: Epoch time: 18.45 s +2024-11-22 08:45:15.407206: +2024-11-22 08:45:15.407429: Epoch 4106 +2024-11-22 08:45:15.407544: Current learning rate: 0.00523 +2024-11-22 08:45:34.095672: train_loss -0.7749 +2024-11-22 08:45:34.095918: val_loss -0.7768 +2024-11-22 08:45:34.096000: Pseudo dice [0.8448] +2024-11-22 08:45:34.096081: Epoch time: 18.69 s +2024-11-22 08:45:35.022755: +2024-11-22 08:45:35.023048: Epoch 4107 +2024-11-22 08:45:35.023160: Current learning rate: 0.00523 +2024-11-22 08:45:54.098958: train_loss -0.7763 +2024-11-22 08:45:54.099196: val_loss -0.7527 +2024-11-22 08:45:54.099357: Pseudo dice [0.8472] +2024-11-22 08:45:54.099481: Epoch time: 19.08 s +2024-11-22 08:45:54.982905: +2024-11-22 08:45:54.983146: Epoch 4108 +2024-11-22 08:45:54.983259: Current learning rate: 0.00523 +2024-11-22 08:46:13.425308: train_loss -0.789 +2024-11-22 08:46:13.425529: val_loss -0.7963 +2024-11-22 08:46:13.425628: Pseudo dice [0.8664] +2024-11-22 08:46:13.425715: Epoch time: 18.44 s +2024-11-22 08:46:14.658424: +2024-11-22 08:46:14.658685: Epoch 4109 +2024-11-22 08:46:14.658797: Current learning rate: 0.00523 +2024-11-22 08:46:33.686328: train_loss -0.7922 +2024-11-22 08:46:33.686604: val_loss -0.776 +2024-11-22 08:46:33.686684: Pseudo dice [0.8513] +2024-11-22 08:46:33.686767: Epoch time: 19.03 s +2024-11-22 08:46:34.560337: +2024-11-22 08:46:34.560581: Epoch 4110 +2024-11-22 08:46:34.560690: Current learning rate: 0.00523 +2024-11-22 08:46:52.531588: train_loss -0.7885 +2024-11-22 08:46:52.531896: val_loss -0.7699 +2024-11-22 08:46:52.531974: Pseudo dice [0.8213] +2024-11-22 08:46:52.532056: Epoch time: 17.97 s +2024-11-22 08:46:53.396988: +2024-11-22 08:46:53.397231: Epoch 4111 +2024-11-22 08:46:53.397342: Current learning rate: 0.00522 +2024-11-22 08:47:11.249443: train_loss -0.7944 +2024-11-22 08:47:11.249668: val_loss -0.766 +2024-11-22 08:47:11.249744: Pseudo dice [0.8334] +2024-11-22 08:47:11.249817: Epoch time: 17.85 s +2024-11-22 08:47:12.107410: +2024-11-22 08:47:12.107638: Epoch 4112 +2024-11-22 08:47:12.107750: Current learning rate: 0.00522 +2024-11-22 08:47:30.845084: train_loss -0.7925 +2024-11-22 08:47:30.845297: val_loss -0.7916 +2024-11-22 08:47:30.845369: Pseudo dice [0.8531] +2024-11-22 08:47:30.845441: Epoch time: 18.74 s +2024-11-22 08:47:31.743592: +2024-11-22 08:47:31.743814: Epoch 4113 +2024-11-22 08:47:31.743926: Current learning rate: 0.00522 +2024-11-22 08:47:49.224618: train_loss -0.7941 +2024-11-22 08:47:49.224875: val_loss -0.7687 +2024-11-22 08:47:49.224951: Pseudo dice [0.8402] +2024-11-22 08:47:49.225035: Epoch time: 17.48 s +2024-11-22 08:47:50.099509: +2024-11-22 08:47:50.099745: Epoch 4114 +2024-11-22 08:47:50.099856: Current learning rate: 0.00522 +2024-11-22 08:48:08.279677: train_loss -0.7892 +2024-11-22 08:48:08.279903: val_loss -0.7505 +2024-11-22 08:48:08.279977: Pseudo dice [0.8398] +2024-11-22 08:48:08.280058: Epoch time: 18.18 s +2024-11-22 08:48:09.134307: +2024-11-22 08:48:09.134525: Epoch 4115 +2024-11-22 08:48:09.134640: Current learning rate: 0.00522 +2024-11-22 08:48:29.101071: train_loss -0.7868 +2024-11-22 08:48:29.101321: val_loss -0.7738 +2024-11-22 08:48:29.101402: Pseudo dice [0.8512] +2024-11-22 08:48:29.101492: Epoch time: 19.97 s +2024-11-22 08:48:29.961326: +2024-11-22 08:48:29.961539: Epoch 4116 +2024-11-22 08:48:29.961650: Current learning rate: 0.00522 +2024-11-22 08:48:48.932116: train_loss -0.7827 +2024-11-22 08:48:48.932339: val_loss -0.7827 +2024-11-22 08:48:48.932434: Pseudo dice [0.8507] +2024-11-22 08:48:48.932521: Epoch time: 18.97 s +2024-11-22 08:48:49.792841: +2024-11-22 08:48:49.793079: Epoch 4117 +2024-11-22 08:48:49.793191: Current learning rate: 0.00522 +2024-11-22 08:49:08.634938: train_loss -0.7855 +2024-11-22 08:49:08.635188: val_loss -0.7775 +2024-11-22 08:49:08.635291: Pseudo dice [0.8407] +2024-11-22 08:49:08.635443: Epoch time: 18.84 s +2024-11-22 08:49:09.562583: +2024-11-22 08:49:09.562797: Epoch 4118 +2024-11-22 08:49:09.562906: Current learning rate: 0.00522 +2024-11-22 08:49:28.363154: train_loss -0.7848 +2024-11-22 08:49:28.363367: val_loss -0.7832 +2024-11-22 08:49:28.363442: Pseudo dice [0.8546] +2024-11-22 08:49:28.363517: Epoch time: 18.8 s +2024-11-22 08:49:29.221250: +2024-11-22 08:49:29.221474: Epoch 4119 +2024-11-22 08:49:29.221592: Current learning rate: 0.00522 +2024-11-22 08:49:47.563802: train_loss -0.792 +2024-11-22 08:49:47.564028: val_loss -0.7865 +2024-11-22 08:49:47.564102: Pseudo dice [0.8454] +2024-11-22 08:49:47.569411: Epoch time: 18.34 s +2024-11-22 08:49:48.616359: +2024-11-22 08:49:48.616594: Epoch 4120 +2024-11-22 08:49:48.616719: Current learning rate: 0.00521 +2024-11-22 08:50:07.086154: train_loss -0.7932 +2024-11-22 08:50:07.086388: val_loss -0.7787 +2024-11-22 08:50:07.091674: Pseudo dice [0.8586] +2024-11-22 08:50:07.091822: Epoch time: 18.47 s +2024-11-22 08:50:08.583435: +2024-11-22 08:50:08.583668: Epoch 4121 +2024-11-22 08:50:08.583774: Current learning rate: 0.00521 +2024-11-22 08:50:27.280074: train_loss -0.7857 +2024-11-22 08:50:27.285506: val_loss -0.7484 +2024-11-22 08:50:27.285591: Pseudo dice [0.8509] +2024-11-22 08:50:27.285670: Epoch time: 18.7 s +2024-11-22 08:50:28.165968: +2024-11-22 08:50:28.166317: Epoch 4122 +2024-11-22 08:50:28.166426: Current learning rate: 0.00521 +2024-11-22 08:50:46.802045: train_loss -0.7844 +2024-11-22 08:50:46.802262: val_loss -0.7565 +2024-11-22 08:50:46.802339: Pseudo dice [0.8457] +2024-11-22 08:50:46.802413: Epoch time: 18.64 s +2024-11-22 08:50:47.660363: +2024-11-22 08:50:47.660589: Epoch 4123 +2024-11-22 08:50:47.660697: Current learning rate: 0.00521 +2024-11-22 08:51:05.676799: train_loss -0.7708 +2024-11-22 08:51:05.677093: val_loss -0.7816 +2024-11-22 08:51:05.677191: Pseudo dice [0.8479] +2024-11-22 08:51:05.677280: Epoch time: 18.02 s +2024-11-22 08:51:06.539119: +2024-11-22 08:51:06.539347: Epoch 4124 +2024-11-22 08:51:06.539461: Current learning rate: 0.00521 +2024-11-22 08:51:25.294728: train_loss -0.7818 +2024-11-22 08:51:25.294949: val_loss -0.742 +2024-11-22 08:51:25.295049: Pseudo dice [0.8436] +2024-11-22 08:51:25.295125: Epoch time: 18.76 s +2024-11-22 08:51:26.154123: +2024-11-22 08:51:26.154361: Epoch 4125 +2024-11-22 08:51:26.154479: Current learning rate: 0.00521 +2024-11-22 08:51:44.727864: train_loss -0.789 +2024-11-22 08:51:44.728167: val_loss -0.7672 +2024-11-22 08:51:44.728243: Pseudo dice [0.8447] +2024-11-22 08:51:44.728321: Epoch time: 18.57 s +2024-11-22 08:51:45.677613: +2024-11-22 08:51:45.677836: Epoch 4126 +2024-11-22 08:51:45.677957: Current learning rate: 0.00521 +2024-11-22 08:52:04.617451: train_loss -0.7852 +2024-11-22 08:52:04.617675: val_loss -0.7652 +2024-11-22 08:52:04.617750: Pseudo dice [0.8527] +2024-11-22 08:52:04.617825: Epoch time: 18.94 s +2024-11-22 08:52:05.673944: +2024-11-22 08:52:05.674188: Epoch 4127 +2024-11-22 08:52:05.674318: Current learning rate: 0.00521 +2024-11-22 08:52:24.675116: train_loss -0.7638 +2024-11-22 08:52:24.675369: val_loss -0.77 +2024-11-22 08:52:24.675450: Pseudo dice [0.8483] +2024-11-22 08:52:24.675564: Epoch time: 19.0 s +2024-11-22 08:52:25.539581: +2024-11-22 08:52:25.539794: Epoch 4128 +2024-11-22 08:52:25.539901: Current learning rate: 0.0052 +2024-11-22 08:52:45.316311: train_loss -0.78 +2024-11-22 08:52:45.316534: val_loss -0.7669 +2024-11-22 08:52:45.316608: Pseudo dice [0.8358] +2024-11-22 08:52:45.316684: Epoch time: 19.78 s +2024-11-22 08:52:46.175292: +2024-11-22 08:52:46.175508: Epoch 4129 +2024-11-22 08:52:46.175618: Current learning rate: 0.0052 +2024-11-22 08:53:04.847124: train_loss -0.7894 +2024-11-22 08:53:04.847344: val_loss -0.762 +2024-11-22 08:53:04.847418: Pseudo dice [0.8382] +2024-11-22 08:53:04.847493: Epoch time: 18.67 s +2024-11-22 08:53:05.719415: +2024-11-22 08:53:05.719627: Epoch 4130 +2024-11-22 08:53:05.719737: Current learning rate: 0.0052 +2024-11-22 08:53:23.841613: train_loss -0.7886 +2024-11-22 08:53:23.841824: val_loss -0.7781 +2024-11-22 08:53:23.841904: Pseudo dice [0.8433] +2024-11-22 08:53:23.841981: Epoch time: 18.12 s +2024-11-22 08:53:24.696725: +2024-11-22 08:53:24.696972: Epoch 4131 +2024-11-22 08:53:24.697532: Current learning rate: 0.0052 +2024-11-22 08:53:42.994333: train_loss -0.7881 +2024-11-22 08:53:42.994562: val_loss -0.7625 +2024-11-22 08:53:42.994637: Pseudo dice [0.8507] +2024-11-22 08:53:42.994719: Epoch time: 18.3 s +2024-11-22 08:53:43.845514: +2024-11-22 08:53:43.845795: Epoch 4132 +2024-11-22 08:53:43.845904: Current learning rate: 0.0052 +2024-11-22 08:54:02.303125: train_loss -0.7829 +2024-11-22 08:54:02.303341: val_loss -0.787 +2024-11-22 08:54:02.303428: Pseudo dice [0.8429] +2024-11-22 08:54:02.303504: Epoch time: 18.46 s +2024-11-22 08:54:03.560989: +2024-11-22 08:54:03.561223: Epoch 4133 +2024-11-22 08:54:03.561332: Current learning rate: 0.0052 +2024-11-22 08:54:21.120595: train_loss -0.7812 +2024-11-22 08:54:21.120838: val_loss -0.7607 +2024-11-22 08:54:21.120914: Pseudo dice [0.8577] +2024-11-22 08:54:21.121021: Epoch time: 17.56 s +2024-11-22 08:54:21.982120: +2024-11-22 08:54:21.982351: Epoch 4134 +2024-11-22 08:54:21.982461: Current learning rate: 0.0052 +2024-11-22 08:54:40.564990: train_loss -0.7822 +2024-11-22 08:54:40.565241: val_loss -0.758 +2024-11-22 08:54:40.565316: Pseudo dice [0.8502] +2024-11-22 08:54:40.565390: Epoch time: 18.58 s +2024-11-22 08:54:41.426554: +2024-11-22 08:54:41.426779: Epoch 4135 +2024-11-22 08:54:41.426891: Current learning rate: 0.0052 +2024-11-22 08:54:59.900367: train_loss -0.7848 +2024-11-22 08:54:59.900586: val_loss -0.7778 +2024-11-22 08:54:59.900660: Pseudo dice [0.8368] +2024-11-22 08:54:59.900735: Epoch time: 18.47 s +2024-11-22 08:55:00.756521: +2024-11-22 08:55:00.756750: Epoch 4136 +2024-11-22 08:55:00.756860: Current learning rate: 0.00519 +2024-11-22 08:55:19.391419: train_loss -0.7925 +2024-11-22 08:55:19.391652: val_loss -0.7796 +2024-11-22 08:55:19.391726: Pseudo dice [0.8572] +2024-11-22 08:55:19.391801: Epoch time: 18.64 s +2024-11-22 08:55:20.355239: +2024-11-22 08:55:20.355487: Epoch 4137 +2024-11-22 08:55:20.355614: Current learning rate: 0.00519 +2024-11-22 08:55:37.809508: train_loss -0.7971 +2024-11-22 08:55:37.809753: val_loss -0.7872 +2024-11-22 08:55:37.809827: Pseudo dice [0.8471] +2024-11-22 08:55:37.809904: Epoch time: 17.46 s +2024-11-22 08:55:38.684312: +2024-11-22 08:55:38.684537: Epoch 4138 +2024-11-22 08:55:38.684644: Current learning rate: 0.00519 +2024-11-22 08:55:56.265970: train_loss -0.7974 +2024-11-22 08:55:56.266195: val_loss -0.786 +2024-11-22 08:55:56.266270: Pseudo dice [0.851] +2024-11-22 08:55:56.267922: Epoch time: 17.58 s +2024-11-22 08:55:57.132676: +2024-11-22 08:55:57.132895: Epoch 4139 +2024-11-22 08:55:57.133010: Current learning rate: 0.00519 +2024-11-22 08:56:15.358918: train_loss -0.7923 +2024-11-22 08:56:15.359175: val_loss -0.7651 +2024-11-22 08:56:15.359251: Pseudo dice [0.8525] +2024-11-22 08:56:15.359326: Epoch time: 18.23 s +2024-11-22 08:56:16.229577: +2024-11-22 08:56:16.229787: Epoch 4140 +2024-11-22 08:56:16.229901: Current learning rate: 0.00519 +2024-11-22 08:56:34.481271: train_loss -0.7953 +2024-11-22 08:56:34.481519: val_loss -0.7712 +2024-11-22 08:56:34.481595: Pseudo dice [0.8504] +2024-11-22 08:56:34.481678: Epoch time: 18.25 s +2024-11-22 08:56:35.342828: +2024-11-22 08:56:35.343063: Epoch 4141 +2024-11-22 08:56:35.343172: Current learning rate: 0.00519 +2024-11-22 08:56:54.256437: train_loss -0.7889 +2024-11-22 08:56:54.256662: val_loss -0.7565 +2024-11-22 08:56:54.256739: Pseudo dice [0.8311] +2024-11-22 08:56:54.256816: Epoch time: 18.91 s +2024-11-22 08:56:55.299437: +2024-11-22 08:56:55.299798: Epoch 4142 +2024-11-22 08:56:55.299912: Current learning rate: 0.00519 +2024-11-22 08:57:13.681302: train_loss -0.787 +2024-11-22 08:57:13.681532: val_loss -0.7554 +2024-11-22 08:57:13.681606: Pseudo dice [0.83] +2024-11-22 08:57:13.681680: Epoch time: 18.38 s +2024-11-22 08:57:14.534569: +2024-11-22 08:57:14.534771: Epoch 4143 +2024-11-22 08:57:14.534881: Current learning rate: 0.00519 +2024-11-22 08:57:32.302226: train_loss -0.7781 +2024-11-22 08:57:32.302441: val_loss -0.774 +2024-11-22 08:57:32.302516: Pseudo dice [0.8464] +2024-11-22 08:57:32.302593: Epoch time: 17.77 s +2024-11-22 08:57:33.161457: +2024-11-22 08:57:33.161650: Epoch 4144 +2024-11-22 08:57:33.161755: Current learning rate: 0.00518 +2024-11-22 08:57:50.687460: train_loss -0.7886 +2024-11-22 08:57:50.689936: val_loss -0.7788 +2024-11-22 08:57:50.690044: Pseudo dice [0.8377] +2024-11-22 08:57:50.690125: Epoch time: 17.53 s +2024-11-22 08:57:52.027772: +2024-11-22 08:57:52.028036: Epoch 4145 +2024-11-22 08:57:52.028148: Current learning rate: 0.00518 +2024-11-22 08:58:10.483237: train_loss -0.7854 +2024-11-22 08:58:10.483469: val_loss -0.7734 +2024-11-22 08:58:10.483547: Pseudo dice [0.8438] +2024-11-22 08:58:10.483622: Epoch time: 18.46 s +2024-11-22 08:58:11.336169: +2024-11-22 08:58:11.336403: Epoch 4146 +2024-11-22 08:58:11.336511: Current learning rate: 0.00518 +2024-11-22 08:58:30.064570: train_loss -0.7804 +2024-11-22 08:58:30.064793: val_loss -0.7509 +2024-11-22 08:58:30.064871: Pseudo dice [0.8209] +2024-11-22 08:58:30.064947: Epoch time: 18.73 s +2024-11-22 08:58:30.929364: +2024-11-22 08:58:30.929592: Epoch 4147 +2024-11-22 08:58:30.929698: Current learning rate: 0.00518 +2024-11-22 08:58:49.166585: train_loss -0.7882 +2024-11-22 08:58:49.166807: val_loss -0.7493 +2024-11-22 08:58:49.166886: Pseudo dice [0.8332] +2024-11-22 08:58:49.166965: Epoch time: 18.24 s +2024-11-22 08:58:50.072560: +2024-11-22 08:58:50.072854: Epoch 4148 +2024-11-22 08:58:50.072970: Current learning rate: 0.00518 +2024-11-22 08:59:07.393932: train_loss -0.7818 +2024-11-22 08:59:07.394146: val_loss -0.7787 +2024-11-22 08:59:07.394228: Pseudo dice [0.8466] +2024-11-22 08:59:07.394300: Epoch time: 17.32 s +2024-11-22 08:59:08.236086: +2024-11-22 08:59:08.236263: Epoch 4149 +2024-11-22 08:59:08.236354: Current learning rate: 0.00518 +2024-11-22 08:59:26.284463: train_loss -0.7905 +2024-11-22 08:59:26.284686: val_loss -0.7813 +2024-11-22 08:59:26.284761: Pseudo dice [0.836] +2024-11-22 08:59:26.286929: Epoch time: 18.05 s +2024-11-22 08:59:27.508632: +2024-11-22 08:59:27.508832: Epoch 4150 +2024-11-22 08:59:27.508944: Current learning rate: 0.00518 +2024-11-22 08:59:45.317533: train_loss -0.7914 +2024-11-22 08:59:45.317770: val_loss -0.7718 +2024-11-22 08:59:45.317854: Pseudo dice [0.8512] +2024-11-22 08:59:45.317937: Epoch time: 17.81 s +2024-11-22 08:59:46.264347: +2024-11-22 08:59:46.264564: Epoch 4151 +2024-11-22 08:59:46.264672: Current learning rate: 0.00518 +2024-11-22 09:00:05.351818: train_loss -0.7781 +2024-11-22 09:00:05.352071: val_loss -0.7476 +2024-11-22 09:00:05.352147: Pseudo dice [0.832] +2024-11-22 09:00:05.352228: Epoch time: 19.09 s +2024-11-22 09:00:06.205965: +2024-11-22 09:00:06.206204: Epoch 4152 +2024-11-22 09:00:06.206316: Current learning rate: 0.00518 +2024-11-22 09:00:25.357774: train_loss -0.7878 +2024-11-22 09:00:25.358039: val_loss -0.7593 +2024-11-22 09:00:25.358116: Pseudo dice [0.856] +2024-11-22 09:00:25.358193: Epoch time: 19.15 s +2024-11-22 09:00:26.215827: +2024-11-22 09:00:26.216064: Epoch 4153 +2024-11-22 09:00:26.216175: Current learning rate: 0.00517 +2024-11-22 09:00:44.050888: train_loss -0.7828 +2024-11-22 09:00:44.051109: val_loss -0.7611 +2024-11-22 09:00:44.051190: Pseudo dice [0.8499] +2024-11-22 09:00:44.051265: Epoch time: 17.84 s +2024-11-22 09:00:44.908682: +2024-11-22 09:00:44.908905: Epoch 4154 +2024-11-22 09:00:44.909029: Current learning rate: 0.00517 +2024-11-22 09:01:02.069629: train_loss -0.7803 +2024-11-22 09:01:02.069884: val_loss -0.7743 +2024-11-22 09:01:02.069964: Pseudo dice [0.847] +2024-11-22 09:01:02.070052: Epoch time: 17.16 s +2024-11-22 09:01:02.929080: +2024-11-22 09:01:02.929307: Epoch 4155 +2024-11-22 09:01:02.929417: Current learning rate: 0.00517 +2024-11-22 09:01:21.437953: train_loss -0.7829 +2024-11-22 09:01:21.438201: val_loss -0.7606 +2024-11-22 09:01:21.438275: Pseudo dice [0.8211] +2024-11-22 09:01:21.438350: Epoch time: 18.51 s +2024-11-22 09:01:22.453454: +2024-11-22 09:01:22.453678: Epoch 4156 +2024-11-22 09:01:22.453789: Current learning rate: 0.00517 +2024-11-22 09:01:41.154353: train_loss -0.7827 +2024-11-22 09:01:41.154586: val_loss -0.7787 +2024-11-22 09:01:41.154661: Pseudo dice [0.8518] +2024-11-22 09:01:41.154761: Epoch time: 18.7 s +2024-11-22 09:01:42.373350: +2024-11-22 09:01:42.373574: Epoch 4157 +2024-11-22 09:01:42.373758: Current learning rate: 0.00517 +2024-11-22 09:02:00.873451: train_loss -0.7899 +2024-11-22 09:02:00.873712: val_loss -0.767 +2024-11-22 09:02:00.873788: Pseudo dice [0.8413] +2024-11-22 09:02:00.873870: Epoch time: 18.5 s +2024-11-22 09:02:01.737674: +2024-11-22 09:02:01.737892: Epoch 4158 +2024-11-22 09:02:01.738009: Current learning rate: 0.00517 +2024-11-22 09:02:20.101949: train_loss -0.7761 +2024-11-22 09:02:20.102181: val_loss -0.7524 +2024-11-22 09:02:20.102262: Pseudo dice [0.844] +2024-11-22 09:02:20.102336: Epoch time: 18.37 s +2024-11-22 09:02:21.097104: +2024-11-22 09:02:21.097338: Epoch 4159 +2024-11-22 09:02:21.097452: Current learning rate: 0.00517 +2024-11-22 09:02:39.591413: train_loss -0.7795 +2024-11-22 09:02:39.591630: val_loss -0.7813 +2024-11-22 09:02:39.591703: Pseudo dice [0.8409] +2024-11-22 09:02:39.591777: Epoch time: 18.5 s +2024-11-22 09:02:40.447989: +2024-11-22 09:02:40.448272: Epoch 4160 +2024-11-22 09:02:40.448384: Current learning rate: 0.00517 +2024-11-22 09:02:59.326775: train_loss -0.784 +2024-11-22 09:02:59.326988: val_loss -0.7757 +2024-11-22 09:02:59.327070: Pseudo dice [0.8406] +2024-11-22 09:02:59.327142: Epoch time: 18.88 s +2024-11-22 09:03:00.234738: +2024-11-22 09:03:00.234996: Epoch 4161 +2024-11-22 09:03:00.235122: Current learning rate: 0.00516 +2024-11-22 09:03:17.859941: train_loss -0.787 +2024-11-22 09:03:17.860185: val_loss -0.7889 +2024-11-22 09:03:17.860258: Pseudo dice [0.8614] +2024-11-22 09:03:17.860335: Epoch time: 17.63 s +2024-11-22 09:03:18.723797: +2024-11-22 09:03:18.724036: Epoch 4162 +2024-11-22 09:03:18.724145: Current learning rate: 0.00516 +2024-11-22 09:03:36.836771: train_loss -0.7841 +2024-11-22 09:03:36.837003: val_loss -0.759 +2024-11-22 09:03:36.837076: Pseudo dice [0.8466] +2024-11-22 09:03:36.837154: Epoch time: 18.11 s +2024-11-22 09:03:37.697706: +2024-11-22 09:03:37.697940: Epoch 4163 +2024-11-22 09:03:37.698060: Current learning rate: 0.00516 +2024-11-22 09:03:55.815360: train_loss -0.7777 +2024-11-22 09:03:55.815607: val_loss -0.7856 +2024-11-22 09:03:55.815687: Pseudo dice [0.8536] +2024-11-22 09:03:55.815762: Epoch time: 18.12 s +2024-11-22 09:03:56.690342: +2024-11-22 09:03:56.690569: Epoch 4164 +2024-11-22 09:03:56.690685: Current learning rate: 0.00516 +2024-11-22 09:04:16.339760: train_loss -0.7887 +2024-11-22 09:04:16.340007: val_loss -0.7836 +2024-11-22 09:04:16.340083: Pseudo dice [0.8552] +2024-11-22 09:04:16.340163: Epoch time: 19.65 s +2024-11-22 09:04:17.229716: +2024-11-22 09:04:17.229946: Epoch 4165 +2024-11-22 09:04:17.230062: Current learning rate: 0.00516 +2024-11-22 09:04:34.943208: train_loss -0.7843 +2024-11-22 09:04:34.943418: val_loss -0.7804 +2024-11-22 09:04:34.943563: Pseudo dice [0.8399] +2024-11-22 09:04:34.943639: Epoch time: 17.71 s +2024-11-22 09:04:35.799460: +2024-11-22 09:04:35.799677: Epoch 4166 +2024-11-22 09:04:35.799786: Current learning rate: 0.00516 +2024-11-22 09:04:53.961295: train_loss -0.7592 +2024-11-22 09:04:53.961516: val_loss -0.7447 +2024-11-22 09:04:53.961591: Pseudo dice [0.8244] +2024-11-22 09:04:53.961726: Epoch time: 18.16 s +2024-11-22 09:04:54.826279: +2024-11-22 09:04:54.826584: Epoch 4167 +2024-11-22 09:04:54.826691: Current learning rate: 0.00516 +2024-11-22 09:05:12.326519: train_loss -0.7535 +2024-11-22 09:05:12.326726: val_loss -0.7563 +2024-11-22 09:05:12.326824: Pseudo dice [0.8347] +2024-11-22 09:05:12.326902: Epoch time: 17.5 s +2024-11-22 09:05:13.178004: +2024-11-22 09:05:13.178206: Epoch 4168 +2024-11-22 09:05:13.178313: Current learning rate: 0.00516 +2024-11-22 09:05:31.838101: train_loss -0.7767 +2024-11-22 09:05:31.838336: val_loss -0.7767 +2024-11-22 09:05:31.838414: Pseudo dice [0.8433] +2024-11-22 09:05:31.838495: Epoch time: 18.66 s +2024-11-22 09:05:33.095899: +2024-11-22 09:05:33.096313: Epoch 4169 +2024-11-22 09:05:33.096443: Current learning rate: 0.00515 +2024-11-22 09:05:51.144481: train_loss -0.773 +2024-11-22 09:05:51.144744: val_loss -0.7524 +2024-11-22 09:05:51.144823: Pseudo dice [0.8343] +2024-11-22 09:05:51.144897: Epoch time: 18.05 s +2024-11-22 09:05:52.008644: +2024-11-22 09:05:52.009057: Epoch 4170 +2024-11-22 09:05:52.009185: Current learning rate: 0.00515 +2024-11-22 09:06:11.521495: train_loss -0.7758 +2024-11-22 09:06:11.521704: val_loss -0.7605 +2024-11-22 09:06:11.521783: Pseudo dice [0.8384] +2024-11-22 09:06:11.521857: Epoch time: 19.51 s +2024-11-22 09:06:12.386985: +2024-11-22 09:06:12.387437: Epoch 4171 +2024-11-22 09:06:12.387579: Current learning rate: 0.00515 +2024-11-22 09:06:31.269131: train_loss -0.7839 +2024-11-22 09:06:31.269381: val_loss -0.7797 +2024-11-22 09:06:31.269457: Pseudo dice [0.8595] +2024-11-22 09:06:31.269539: Epoch time: 18.88 s +2024-11-22 09:06:32.138130: +2024-11-22 09:06:32.138570: Epoch 4172 +2024-11-22 09:06:32.138710: Current learning rate: 0.00515 +2024-11-22 09:06:50.940019: train_loss -0.7902 +2024-11-22 09:06:50.940281: val_loss -0.764 +2024-11-22 09:06:50.940359: Pseudo dice [0.8453] +2024-11-22 09:06:50.940439: Epoch time: 18.8 s +2024-11-22 09:06:51.804732: +2024-11-22 09:06:51.805158: Epoch 4173 +2024-11-22 09:06:51.805287: Current learning rate: 0.00515 +2024-11-22 09:07:10.005422: train_loss -0.7752 +2024-11-22 09:07:10.005634: val_loss -0.7565 +2024-11-22 09:07:10.005708: Pseudo dice [0.8283] +2024-11-22 09:07:10.005780: Epoch time: 18.2 s +2024-11-22 09:07:10.864099: +2024-11-22 09:07:10.864519: Epoch 4174 +2024-11-22 09:07:10.864650: Current learning rate: 0.00515 +2024-11-22 09:07:28.498476: train_loss -0.7736 +2024-11-22 09:07:28.498694: val_loss -0.7873 +2024-11-22 09:07:28.498774: Pseudo dice [0.8414] +2024-11-22 09:07:28.498852: Epoch time: 17.64 s +2024-11-22 09:07:29.358192: +2024-11-22 09:07:29.358597: Epoch 4175 +2024-11-22 09:07:29.358730: Current learning rate: 0.00515 +2024-11-22 09:07:47.256872: train_loss -0.7774 +2024-11-22 09:07:47.257116: val_loss -0.76 +2024-11-22 09:07:47.257194: Pseudo dice [0.8393] +2024-11-22 09:07:47.257279: Epoch time: 17.9 s +2024-11-22 09:07:48.220958: +2024-11-22 09:07:48.221371: Epoch 4176 +2024-11-22 09:07:48.221545: Current learning rate: 0.00515 +2024-11-22 09:08:07.628480: train_loss -0.7692 +2024-11-22 09:08:07.628702: val_loss -0.7803 +2024-11-22 09:08:07.628780: Pseudo dice [0.857] +2024-11-22 09:08:07.628858: Epoch time: 19.41 s +2024-11-22 09:08:08.490383: +2024-11-22 09:08:08.490818: Epoch 4177 +2024-11-22 09:08:08.490948: Current learning rate: 0.00514 +2024-11-22 09:08:26.959809: train_loss -0.7839 +2024-11-22 09:08:26.960029: val_loss -0.7593 +2024-11-22 09:08:26.960105: Pseudo dice [0.8485] +2024-11-22 09:08:26.960180: Epoch time: 18.47 s +2024-11-22 09:08:28.027967: +2024-11-22 09:08:28.028404: Epoch 4178 +2024-11-22 09:08:28.028534: Current learning rate: 0.00514 +2024-11-22 09:08:46.078063: train_loss -0.7771 +2024-11-22 09:08:46.078282: val_loss -0.7778 +2024-11-22 09:08:46.078358: Pseudo dice [0.8422] +2024-11-22 09:08:46.078435: Epoch time: 18.05 s +2024-11-22 09:08:46.936469: +2024-11-22 09:08:46.936690: Epoch 4179 +2024-11-22 09:08:46.936799: Current learning rate: 0.00514 +2024-11-22 09:09:04.983610: train_loss -0.7952 +2024-11-22 09:09:04.983899: val_loss -0.7897 +2024-11-22 09:09:04.983979: Pseudo dice [0.8467] +2024-11-22 09:09:04.984069: Epoch time: 18.05 s +2024-11-22 09:09:05.847036: +2024-11-22 09:09:05.847249: Epoch 4180 +2024-11-22 09:09:05.847362: Current learning rate: 0.00514 +2024-11-22 09:09:24.261136: train_loss -0.7877 +2024-11-22 09:09:24.269919: val_loss -0.7881 +2024-11-22 09:09:24.270018: Pseudo dice [0.8431] +2024-11-22 09:09:24.270095: Epoch time: 18.41 s +2024-11-22 09:09:25.532323: +2024-11-22 09:09:25.532763: Epoch 4181 +2024-11-22 09:09:25.532890: Current learning rate: 0.00514 +2024-11-22 09:09:44.842744: train_loss -0.7883 +2024-11-22 09:09:44.843013: val_loss -0.7692 +2024-11-22 09:09:44.843093: Pseudo dice [0.8471] +2024-11-22 09:09:44.843241: Epoch time: 19.31 s +2024-11-22 09:09:45.704097: +2024-11-22 09:09:45.704515: Epoch 4182 +2024-11-22 09:09:45.704646: Current learning rate: 0.00514 +2024-11-22 09:10:04.624587: train_loss -0.7943 +2024-11-22 09:10:04.624797: val_loss -0.7614 +2024-11-22 09:10:04.624871: Pseudo dice [0.8588] +2024-11-22 09:10:04.624943: Epoch time: 18.92 s +2024-11-22 09:10:05.484078: +2024-11-22 09:10:05.484795: Epoch 4183 +2024-11-22 09:10:05.484937: Current learning rate: 0.00514 +2024-11-22 09:10:23.502603: train_loss -0.7877 +2024-11-22 09:10:23.502823: val_loss -0.7844 +2024-11-22 09:10:23.502897: Pseudo dice [0.8514] +2024-11-22 09:10:23.502972: Epoch time: 18.02 s +2024-11-22 09:10:24.445240: +2024-11-22 09:10:24.445669: Epoch 4184 +2024-11-22 09:10:24.445800: Current learning rate: 0.00514 +2024-11-22 09:10:42.778177: train_loss -0.7992 +2024-11-22 09:10:42.778430: val_loss -0.7727 +2024-11-22 09:10:42.778507: Pseudo dice [0.8435] +2024-11-22 09:10:42.778587: Epoch time: 18.33 s +2024-11-22 09:10:43.762889: +2024-11-22 09:10:43.763320: Epoch 4185 +2024-11-22 09:10:43.763453: Current learning rate: 0.00514 +2024-11-22 09:11:01.606785: train_loss -0.7887 +2024-11-22 09:11:01.607027: val_loss -0.7736 +2024-11-22 09:11:01.607105: Pseudo dice [0.8488] +2024-11-22 09:11:01.607185: Epoch time: 17.84 s +2024-11-22 09:11:02.471916: +2024-11-22 09:11:02.472335: Epoch 4186 +2024-11-22 09:11:02.472462: Current learning rate: 0.00513 +2024-11-22 09:11:20.389657: train_loss -0.7945 +2024-11-22 09:11:20.389887: val_loss -0.7526 +2024-11-22 09:11:20.389961: Pseudo dice [0.8318] +2024-11-22 09:11:20.390042: Epoch time: 17.92 s +2024-11-22 09:11:21.250331: +2024-11-22 09:11:21.250734: Epoch 4187 +2024-11-22 09:11:21.250868: Current learning rate: 0.00513 +2024-11-22 09:11:39.777231: train_loss -0.7825 +2024-11-22 09:11:39.782596: val_loss -0.7718 +2024-11-22 09:11:39.782772: Pseudo dice [0.8355] +2024-11-22 09:11:39.782861: Epoch time: 18.53 s +2024-11-22 09:11:40.666803: +2024-11-22 09:11:40.667366: Epoch 4188 +2024-11-22 09:11:40.667504: Current learning rate: 0.00513 +2024-11-22 09:11:58.604759: train_loss -0.7852 +2024-11-22 09:11:58.605011: val_loss -0.7609 +2024-11-22 09:11:58.605091: Pseudo dice [0.8416] +2024-11-22 09:11:58.605176: Epoch time: 17.94 s +2024-11-22 09:11:59.467385: +2024-11-22 09:11:59.467927: Epoch 4189 +2024-11-22 09:11:59.468070: Current learning rate: 0.00513 +2024-11-22 09:12:18.257255: train_loss -0.7865 +2024-11-22 09:12:18.257538: val_loss -0.7702 +2024-11-22 09:12:18.257621: Pseudo dice [0.8433] +2024-11-22 09:12:18.257698: Epoch time: 18.79 s +2024-11-22 09:12:19.115323: +2024-11-22 09:12:19.115734: Epoch 4190 +2024-11-22 09:12:19.115863: Current learning rate: 0.00513 +2024-11-22 09:12:37.468560: train_loss -0.7865 +2024-11-22 09:12:37.468783: val_loss -0.7589 +2024-11-22 09:12:37.468861: Pseudo dice [0.8555] +2024-11-22 09:12:37.468935: Epoch time: 18.35 s +2024-11-22 09:12:38.325443: +2024-11-22 09:12:38.325670: Epoch 4191 +2024-11-22 09:12:38.325780: Current learning rate: 0.00513 +2024-11-22 09:12:57.405585: train_loss -0.7884 +2024-11-22 09:12:57.405830: val_loss -0.7818 +2024-11-22 09:12:57.405910: Pseudo dice [0.8377] +2024-11-22 09:12:57.406002: Epoch time: 19.08 s +2024-11-22 09:12:58.268012: +2024-11-22 09:12:58.268275: Epoch 4192 +2024-11-22 09:12:58.268387: Current learning rate: 0.00513 +2024-11-22 09:13:16.590887: train_loss -0.7854 +2024-11-22 09:13:16.591139: val_loss -0.7555 +2024-11-22 09:13:16.591219: Pseudo dice [0.8301] +2024-11-22 09:13:16.591320: Epoch time: 18.32 s +2024-11-22 09:13:17.866954: +2024-11-22 09:13:17.867400: Epoch 4193 +2024-11-22 09:13:17.867526: Current learning rate: 0.00513 +2024-11-22 09:13:36.836173: train_loss -0.7734 +2024-11-22 09:13:36.836408: val_loss -0.7741 +2024-11-22 09:13:36.836518: Pseudo dice [0.8422] +2024-11-22 09:13:36.836594: Epoch time: 18.97 s +2024-11-22 09:13:37.695273: +2024-11-22 09:13:37.695754: Epoch 4194 +2024-11-22 09:13:37.695891: Current learning rate: 0.00512 +2024-11-22 09:13:55.816881: train_loss -0.7855 +2024-11-22 09:13:55.817117: val_loss -0.7786 +2024-11-22 09:13:55.817207: Pseudo dice [0.8486] +2024-11-22 09:13:55.817347: Epoch time: 18.12 s +2024-11-22 09:13:56.677564: +2024-11-22 09:13:56.678002: Epoch 4195 +2024-11-22 09:13:56.678133: Current learning rate: 0.00512 +2024-11-22 09:14:15.030411: train_loss -0.7997 +2024-11-22 09:14:15.030656: val_loss -0.7383 +2024-11-22 09:14:15.030737: Pseudo dice [0.8318] +2024-11-22 09:14:15.030819: Epoch time: 18.35 s +2024-11-22 09:14:15.892881: +2024-11-22 09:14:15.893366: Epoch 4196 +2024-11-22 09:14:15.893508: Current learning rate: 0.00512 +2024-11-22 09:14:34.010205: train_loss -0.7946 +2024-11-22 09:14:34.010442: val_loss -0.7875 +2024-11-22 09:14:34.010516: Pseudo dice [0.8345] +2024-11-22 09:14:34.010590: Epoch time: 18.12 s +2024-11-22 09:14:34.903866: +2024-11-22 09:14:34.904288: Epoch 4197 +2024-11-22 09:14:34.904414: Current learning rate: 0.00512 +2024-11-22 09:14:53.848017: train_loss -0.795 +2024-11-22 09:14:53.848244: val_loss -0.7607 +2024-11-22 09:14:53.848319: Pseudo dice [0.8431] +2024-11-22 09:14:53.848399: Epoch time: 18.94 s +2024-11-22 09:14:54.706906: +2024-11-22 09:14:54.707414: Epoch 4198 +2024-11-22 09:14:54.707556: Current learning rate: 0.00512 +2024-11-22 09:15:13.242496: train_loss -0.791 +2024-11-22 09:15:13.242752: val_loss -0.7705 +2024-11-22 09:15:13.242831: Pseudo dice [0.8293] +2024-11-22 09:15:13.242917: Epoch time: 18.54 s +2024-11-22 09:15:14.109820: +2024-11-22 09:15:14.110260: Epoch 4199 +2024-11-22 09:15:14.110397: Current learning rate: 0.00512 +2024-11-22 09:15:32.838181: train_loss -0.7997 +2024-11-22 09:15:32.838423: val_loss -0.7474 +2024-11-22 09:15:32.838498: Pseudo dice [0.8517] +2024-11-22 09:15:32.840810: Epoch time: 18.73 s +2024-11-22 09:15:33.971268: +2024-11-22 09:15:33.971694: Epoch 4200 +2024-11-22 09:15:33.971823: Current learning rate: 0.00512 +2024-11-22 09:15:52.037976: train_loss -0.7839 +2024-11-22 09:15:52.038229: val_loss -0.7745 +2024-11-22 09:15:52.038309: Pseudo dice [0.8462] +2024-11-22 09:15:52.038383: Epoch time: 18.07 s +2024-11-22 09:15:52.895441: +2024-11-22 09:15:52.895856: Epoch 4201 +2024-11-22 09:15:52.895984: Current learning rate: 0.00512 +2024-11-22 09:16:10.325098: train_loss -0.7811 +2024-11-22 09:16:10.325322: val_loss -0.7492 +2024-11-22 09:16:10.325397: Pseudo dice [0.8506] +2024-11-22 09:16:10.335674: Epoch time: 17.43 s +2024-11-22 09:16:11.286867: +2024-11-22 09:16:11.287296: Epoch 4202 +2024-11-22 09:16:11.287424: Current learning rate: 0.00511 +2024-11-22 09:16:30.054893: train_loss -0.7897 +2024-11-22 09:16:30.055151: val_loss -0.7789 +2024-11-22 09:16:30.055229: Pseudo dice [0.8542] +2024-11-22 09:16:30.055317: Epoch time: 18.77 s +2024-11-22 09:16:30.921636: +2024-11-22 09:16:30.921863: Epoch 4203 +2024-11-22 09:16:30.921971: Current learning rate: 0.00511 +2024-11-22 09:16:50.079190: train_loss -0.7919 +2024-11-22 09:16:50.081420: val_loss -0.7847 +2024-11-22 09:16:50.081538: Pseudo dice [0.8594] +2024-11-22 09:16:50.081614: Epoch time: 19.16 s +2024-11-22 09:16:50.955404: +2024-11-22 09:16:50.955624: Epoch 4204 +2024-11-22 09:16:50.955732: Current learning rate: 0.00511 +2024-11-22 09:17:08.688586: train_loss -0.7902 +2024-11-22 09:17:08.688804: val_loss -0.7738 +2024-11-22 09:17:08.688879: Pseudo dice [0.8547] +2024-11-22 09:17:08.688954: Epoch time: 17.73 s +2024-11-22 09:17:09.945907: +2024-11-22 09:17:09.946360: Epoch 4205 +2024-11-22 09:17:09.946495: Current learning rate: 0.00511 +2024-11-22 09:17:27.583196: train_loss -0.785 +2024-11-22 09:17:27.583455: val_loss -0.7791 +2024-11-22 09:17:27.583537: Pseudo dice [0.8528] +2024-11-22 09:17:27.583631: Epoch time: 17.64 s +2024-11-22 09:17:28.449996: +2024-11-22 09:17:28.450435: Epoch 4206 +2024-11-22 09:17:28.450569: Current learning rate: 0.00511 +2024-11-22 09:17:46.946111: train_loss -0.7834 +2024-11-22 09:17:46.946333: val_loss -0.7608 +2024-11-22 09:17:46.946409: Pseudo dice [0.8344] +2024-11-22 09:17:46.946491: Epoch time: 18.5 s +2024-11-22 09:17:47.803852: +2024-11-22 09:17:47.804294: Epoch 4207 +2024-11-22 09:17:47.804429: Current learning rate: 0.00511 +2024-11-22 09:18:05.413788: train_loss -0.7874 +2024-11-22 09:18:05.414016: val_loss -0.7654 +2024-11-22 09:18:05.414093: Pseudo dice [0.8379] +2024-11-22 09:18:05.414173: Epoch time: 17.61 s +2024-11-22 09:18:06.270495: +2024-11-22 09:18:06.270934: Epoch 4208 +2024-11-22 09:18:06.271073: Current learning rate: 0.00511 +2024-11-22 09:18:24.797559: train_loss -0.7912 +2024-11-22 09:18:24.797815: val_loss -0.7631 +2024-11-22 09:18:24.797890: Pseudo dice [0.8306] +2024-11-22 09:18:24.797971: Epoch time: 18.53 s +2024-11-22 09:18:25.665520: +2024-11-22 09:18:25.665933: Epoch 4209 +2024-11-22 09:18:25.666070: Current learning rate: 0.00511 +2024-11-22 09:18:44.305464: train_loss -0.7988 +2024-11-22 09:18:44.307899: val_loss -0.7679 +2024-11-22 09:18:44.308004: Pseudo dice [0.8306] +2024-11-22 09:18:44.308082: Epoch time: 18.64 s +2024-11-22 09:18:45.284335: +2024-11-22 09:18:45.284821: Epoch 4210 +2024-11-22 09:18:45.284950: Current learning rate: 0.0051 +2024-11-22 09:19:03.411222: train_loss -0.7897 +2024-11-22 09:19:03.411492: val_loss -0.7887 +2024-11-22 09:19:03.411609: Pseudo dice [0.8468] +2024-11-22 09:19:03.411710: Epoch time: 18.13 s +2024-11-22 09:19:04.276679: +2024-11-22 09:19:04.277180: Epoch 4211 +2024-11-22 09:19:04.277314: Current learning rate: 0.0051 +2024-11-22 09:19:23.220569: train_loss -0.7904 +2024-11-22 09:19:23.220789: val_loss -0.7465 +2024-11-22 09:19:23.220872: Pseudo dice [0.8612] +2024-11-22 09:19:23.220948: Epoch time: 18.94 s +2024-11-22 09:19:24.086282: +2024-11-22 09:19:24.086700: Epoch 4212 +2024-11-22 09:19:24.086831: Current learning rate: 0.0051 +2024-11-22 09:19:42.980655: train_loss -0.7978 +2024-11-22 09:19:42.980901: val_loss -0.7795 +2024-11-22 09:19:42.980976: Pseudo dice [0.842] +2024-11-22 09:19:42.981069: Epoch time: 18.9 s +2024-11-22 09:19:43.843776: +2024-11-22 09:19:43.844212: Epoch 4213 +2024-11-22 09:19:43.844342: Current learning rate: 0.0051 +2024-11-22 09:20:01.985702: train_loss -0.7885 +2024-11-22 09:20:01.985921: val_loss -0.7837 +2024-11-22 09:20:01.986007: Pseudo dice [0.851] +2024-11-22 09:20:01.986086: Epoch time: 18.14 s +2024-11-22 09:20:02.842262: +2024-11-22 09:20:02.842484: Epoch 4214 +2024-11-22 09:20:02.842596: Current learning rate: 0.0051 +2024-11-22 09:20:21.849400: train_loss -0.7933 +2024-11-22 09:20:21.849624: val_loss -0.7704 +2024-11-22 09:20:21.849715: Pseudo dice [0.8592] +2024-11-22 09:20:21.849790: Epoch time: 19.01 s +2024-11-22 09:20:22.728733: +2024-11-22 09:20:22.728950: Epoch 4215 +2024-11-22 09:20:22.729060: Current learning rate: 0.0051 +2024-11-22 09:20:40.758193: train_loss -0.7845 +2024-11-22 09:20:40.758418: val_loss -0.7626 +2024-11-22 09:20:40.758495: Pseudo dice [0.8439] +2024-11-22 09:20:40.758580: Epoch time: 18.03 s +2024-11-22 09:20:41.622643: +2024-11-22 09:20:41.622882: Epoch 4216 +2024-11-22 09:20:41.623039: Current learning rate: 0.0051 +2024-11-22 09:20:59.146716: train_loss -0.7818 +2024-11-22 09:20:59.146938: val_loss -0.7753 +2024-11-22 09:20:59.147021: Pseudo dice [0.8362] +2024-11-22 09:20:59.147134: Epoch time: 17.52 s +2024-11-22 09:21:00.401114: +2024-11-22 09:21:00.401539: Epoch 4217 +2024-11-22 09:21:00.401669: Current learning rate: 0.0051 +2024-11-22 09:21:17.976315: train_loss -0.7977 +2024-11-22 09:21:17.976563: val_loss -0.7778 +2024-11-22 09:21:17.976640: Pseudo dice [0.8484] +2024-11-22 09:21:17.976714: Epoch time: 17.58 s +2024-11-22 09:21:18.867428: +2024-11-22 09:21:18.867848: Epoch 4218 +2024-11-22 09:21:18.867976: Current learning rate: 0.0051 +2024-11-22 09:21:37.234697: train_loss -0.7841 +2024-11-22 09:21:37.234927: val_loss -0.745 +2024-11-22 09:21:37.235019: Pseudo dice [0.8343] +2024-11-22 09:21:37.235102: Epoch time: 18.37 s +2024-11-22 09:21:38.094662: +2024-11-22 09:21:38.095120: Epoch 4219 +2024-11-22 09:21:38.095252: Current learning rate: 0.00509 +2024-11-22 09:21:55.956141: train_loss -0.7791 +2024-11-22 09:21:55.956467: val_loss -0.7541 +2024-11-22 09:21:55.956542: Pseudo dice [0.827] +2024-11-22 09:21:55.956623: Epoch time: 17.86 s +2024-11-22 09:21:56.821254: +2024-11-22 09:21:56.821670: Epoch 4220 +2024-11-22 09:21:56.821839: Current learning rate: 0.00509 +2024-11-22 09:22:15.498023: train_loss -0.774 +2024-11-22 09:22:15.499043: val_loss -0.7493 +2024-11-22 09:22:15.499150: Pseudo dice [0.8524] +2024-11-22 09:22:15.499237: Epoch time: 18.68 s +2024-11-22 09:22:16.361858: +2024-11-22 09:22:16.362297: Epoch 4221 +2024-11-22 09:22:16.362429: Current learning rate: 0.00509 +2024-11-22 09:22:34.534375: train_loss -0.7887 +2024-11-22 09:22:34.534603: val_loss -0.7731 +2024-11-22 09:22:34.534677: Pseudo dice [0.8592] +2024-11-22 09:22:34.534753: Epoch time: 18.17 s +2024-11-22 09:22:35.439212: +2024-11-22 09:22:35.439680: Epoch 4222 +2024-11-22 09:22:35.439818: Current learning rate: 0.00509 +2024-11-22 09:22:54.274941: train_loss -0.7826 +2024-11-22 09:22:54.276239: val_loss -0.7979 +2024-11-22 09:22:54.276322: Pseudo dice [0.8558] +2024-11-22 09:22:54.276407: Epoch time: 18.84 s +2024-11-22 09:22:55.171697: +2024-11-22 09:22:55.172148: Epoch 4223 +2024-11-22 09:22:55.172281: Current learning rate: 0.00509 +2024-11-22 09:23:13.746429: train_loss -0.7896 +2024-11-22 09:23:13.746669: val_loss -0.7648 +2024-11-22 09:23:13.746744: Pseudo dice [0.8436] +2024-11-22 09:23:13.746821: Epoch time: 18.58 s +2024-11-22 09:23:14.618436: +2024-11-22 09:23:14.618867: Epoch 4224 +2024-11-22 09:23:14.619005: Current learning rate: 0.00509 +2024-11-22 09:23:33.047379: train_loss -0.7919 +2024-11-22 09:23:33.047601: val_loss -0.7703 +2024-11-22 09:23:33.047679: Pseudo dice [0.8372] +2024-11-22 09:23:33.047756: Epoch time: 18.43 s +2024-11-22 09:23:34.003828: +2024-11-22 09:23:34.004273: Epoch 4225 +2024-11-22 09:23:34.004405: Current learning rate: 0.00509 +2024-11-22 09:23:52.792446: train_loss -0.7924 +2024-11-22 09:23:52.792727: val_loss -0.7792 +2024-11-22 09:23:52.792804: Pseudo dice [0.8532] +2024-11-22 09:23:52.792882: Epoch time: 18.79 s +2024-11-22 09:23:53.676962: +2024-11-22 09:23:53.677173: Epoch 4226 +2024-11-22 09:23:53.677280: Current learning rate: 0.00509 +2024-11-22 09:24:11.818782: train_loss -0.7886 +2024-11-22 09:24:11.819044: val_loss -0.7601 +2024-11-22 09:24:11.821349: Pseudo dice [0.8545] +2024-11-22 09:24:11.821470: Epoch time: 18.14 s +2024-11-22 09:24:12.862787: +2024-11-22 09:24:12.863000: Epoch 4227 +2024-11-22 09:24:12.863108: Current learning rate: 0.00508 +2024-11-22 09:24:32.118338: train_loss -0.7941 +2024-11-22 09:24:32.118560: val_loss -0.7676 +2024-11-22 09:24:32.129673: Pseudo dice [0.8484] +2024-11-22 09:24:32.129768: Epoch time: 19.26 s +2024-11-22 09:24:32.983884: +2024-11-22 09:24:32.984076: Epoch 4228 +2024-11-22 09:24:32.984185: Current learning rate: 0.00508 +2024-11-22 09:24:51.258820: train_loss -0.7949 +2024-11-22 09:24:51.259050: val_loss -0.7576 +2024-11-22 09:24:51.264274: Pseudo dice [0.8466] +2024-11-22 09:24:51.264433: Epoch time: 18.28 s +2024-11-22 09:24:52.617851: +2024-11-22 09:24:52.618078: Epoch 4229 +2024-11-22 09:24:52.618194: Current learning rate: 0.00508 +2024-11-22 09:25:11.075035: train_loss -0.7846 +2024-11-22 09:25:11.075282: val_loss -0.7674 +2024-11-22 09:25:11.075357: Pseudo dice [0.8448] +2024-11-22 09:25:11.075440: Epoch time: 18.46 s +2024-11-22 09:25:11.943357: +2024-11-22 09:25:11.943574: Epoch 4230 +2024-11-22 09:25:11.943685: Current learning rate: 0.00508 +2024-11-22 09:25:30.271552: train_loss -0.7905 +2024-11-22 09:25:30.271800: val_loss -0.746 +2024-11-22 09:25:30.271900: Pseudo dice [0.8496] +2024-11-22 09:25:30.272047: Epoch time: 18.33 s +2024-11-22 09:25:31.144327: +2024-11-22 09:25:31.144540: Epoch 4231 +2024-11-22 09:25:31.144650: Current learning rate: 0.00508 +2024-11-22 09:25:48.839631: train_loss -0.7833 +2024-11-22 09:25:48.839884: val_loss -0.7609 +2024-11-22 09:25:48.839961: Pseudo dice [0.843] +2024-11-22 09:25:48.840042: Epoch time: 17.7 s +2024-11-22 09:25:49.714973: +2024-11-22 09:25:49.715264: Epoch 4232 +2024-11-22 09:25:49.715375: Current learning rate: 0.00508 +2024-11-22 09:26:08.964730: train_loss -0.7652 +2024-11-22 09:26:08.964936: val_loss -0.7539 +2024-11-22 09:26:08.965014: Pseudo dice [0.8199] +2024-11-22 09:26:08.965088: Epoch time: 19.25 s +2024-11-22 09:26:09.825572: +2024-11-22 09:26:09.825814: Epoch 4233 +2024-11-22 09:26:09.825921: Current learning rate: 0.00508 +2024-11-22 09:26:29.474665: train_loss -0.7746 +2024-11-22 09:26:29.474939: val_loss -0.7664 +2024-11-22 09:26:29.475024: Pseudo dice [0.8262] +2024-11-22 09:26:29.475111: Epoch time: 19.65 s +2024-11-22 09:26:30.350282: +2024-11-22 09:26:30.350502: Epoch 4234 +2024-11-22 09:26:30.350616: Current learning rate: 0.00508 +2024-11-22 09:26:49.267725: train_loss -0.7825 +2024-11-22 09:26:49.268009: val_loss -0.773 +2024-11-22 09:26:49.268094: Pseudo dice [0.8437] +2024-11-22 09:26:49.268174: Epoch time: 18.92 s +2024-11-22 09:26:50.138453: +2024-11-22 09:26:50.138668: Epoch 4235 +2024-11-22 09:26:50.138785: Current learning rate: 0.00507 +2024-11-22 09:27:09.215808: train_loss -0.7873 +2024-11-22 09:27:09.216126: val_loss -0.7635 +2024-11-22 09:27:09.216207: Pseudo dice [0.8394] +2024-11-22 09:27:09.216284: Epoch time: 19.08 s +2024-11-22 09:27:10.082341: +2024-11-22 09:27:10.082558: Epoch 4236 +2024-11-22 09:27:10.082667: Current learning rate: 0.00507 +2024-11-22 09:27:27.966816: train_loss -0.7916 +2024-11-22 09:27:27.972240: val_loss -0.779 +2024-11-22 09:27:27.972327: Pseudo dice [0.8582] +2024-11-22 09:27:27.972412: Epoch time: 17.89 s +2024-11-22 09:27:28.952979: +2024-11-22 09:27:28.953221: Epoch 4237 +2024-11-22 09:27:28.953344: Current learning rate: 0.00507 +2024-11-22 09:27:47.151419: train_loss -0.7873 +2024-11-22 09:27:47.151631: val_loss -0.8025 +2024-11-22 09:27:47.151705: Pseudo dice [0.8637] +2024-11-22 09:27:47.151780: Epoch time: 18.2 s +2024-11-22 09:27:48.256507: +2024-11-22 09:27:48.256723: Epoch 4238 +2024-11-22 09:27:48.256828: Current learning rate: 0.00507 +2024-11-22 09:28:07.172815: train_loss -0.7732 +2024-11-22 09:28:07.173045: val_loss -0.7549 +2024-11-22 09:28:07.173125: Pseudo dice [0.846] +2024-11-22 09:28:07.173200: Epoch time: 18.92 s +2024-11-22 09:28:08.054217: +2024-11-22 09:28:08.054426: Epoch 4239 +2024-11-22 09:28:08.054533: Current learning rate: 0.00507 +2024-11-22 09:28:27.253276: train_loss -0.7816 +2024-11-22 09:28:27.253509: val_loss -0.7506 +2024-11-22 09:28:27.253584: Pseudo dice [0.8579] +2024-11-22 09:28:27.253658: Epoch time: 19.2 s +2024-11-22 09:28:28.110338: +2024-11-22 09:28:28.110564: Epoch 4240 +2024-11-22 09:28:28.110675: Current learning rate: 0.00507 +2024-11-22 09:28:46.743566: train_loss -0.7844 +2024-11-22 09:28:46.743819: val_loss -0.7488 +2024-11-22 09:28:46.743902: Pseudo dice [0.84] +2024-11-22 09:28:46.743986: Epoch time: 18.63 s +2024-11-22 09:28:48.019920: +2024-11-22 09:28:48.020169: Epoch 4241 +2024-11-22 09:28:48.020284: Current learning rate: 0.00507 +2024-11-22 09:29:06.724107: train_loss -0.7782 +2024-11-22 09:29:06.724337: val_loss -0.7521 +2024-11-22 09:29:06.724413: Pseudo dice [0.8564] +2024-11-22 09:29:06.724489: Epoch time: 18.71 s +2024-11-22 09:29:07.582046: +2024-11-22 09:29:07.582266: Epoch 4242 +2024-11-22 09:29:07.582378: Current learning rate: 0.00507 +2024-11-22 09:29:25.949121: train_loss -0.7892 +2024-11-22 09:29:25.949330: val_loss -0.7537 +2024-11-22 09:29:25.950878: Pseudo dice [0.8375] +2024-11-22 09:29:25.950977: Epoch time: 18.37 s +2024-11-22 09:29:26.851008: +2024-11-22 09:29:26.851251: Epoch 4243 +2024-11-22 09:29:26.851373: Current learning rate: 0.00506 +2024-11-22 09:29:44.029843: train_loss -0.7926 +2024-11-22 09:29:44.030105: val_loss -0.7695 +2024-11-22 09:29:44.030190: Pseudo dice [0.8349] +2024-11-22 09:29:44.030277: Epoch time: 17.18 s +2024-11-22 09:29:44.962615: +2024-11-22 09:29:44.962828: Epoch 4244 +2024-11-22 09:29:44.962935: Current learning rate: 0.00506 +2024-11-22 09:30:03.614078: train_loss -0.7936 +2024-11-22 09:30:03.614294: val_loss -0.7784 +2024-11-22 09:30:03.614373: Pseudo dice [0.8408] +2024-11-22 09:30:03.614446: Epoch time: 18.65 s +2024-11-22 09:30:04.496500: +2024-11-22 09:30:04.496762: Epoch 4245 +2024-11-22 09:30:04.496868: Current learning rate: 0.00506 +2024-11-22 09:30:22.589773: train_loss -0.7861 +2024-11-22 09:30:22.590048: val_loss -0.7777 +2024-11-22 09:30:22.590128: Pseudo dice [0.8504] +2024-11-22 09:30:22.590202: Epoch time: 18.09 s +2024-11-22 09:30:23.586608: +2024-11-22 09:30:23.586825: Epoch 4246 +2024-11-22 09:30:23.586934: Current learning rate: 0.00506 +2024-11-22 09:30:42.331524: train_loss -0.7926 +2024-11-22 09:30:42.331746: val_loss -0.7569 +2024-11-22 09:30:42.331821: Pseudo dice [0.8415] +2024-11-22 09:30:42.331895: Epoch time: 18.75 s +2024-11-22 09:30:43.194902: +2024-11-22 09:30:43.195134: Epoch 4247 +2024-11-22 09:30:43.195248: Current learning rate: 0.00506 +2024-11-22 09:31:00.789181: train_loss -0.7945 +2024-11-22 09:31:00.789437: val_loss -0.7615 +2024-11-22 09:31:00.794742: Pseudo dice [0.8551] +2024-11-22 09:31:00.794867: Epoch time: 17.6 s +2024-11-22 09:31:01.809080: +2024-11-22 09:31:01.809282: Epoch 4248 +2024-11-22 09:31:01.809393: Current learning rate: 0.00506 +2024-11-22 09:31:18.825004: train_loss -0.7983 +2024-11-22 09:31:18.825223: val_loss -0.7893 +2024-11-22 09:31:18.825299: Pseudo dice [0.846] +2024-11-22 09:31:18.825375: Epoch time: 17.02 s +2024-11-22 09:31:19.689181: +2024-11-22 09:31:19.689392: Epoch 4249 +2024-11-22 09:31:19.689499: Current learning rate: 0.00506 +2024-11-22 09:31:37.256325: train_loss -0.7938 +2024-11-22 09:31:37.256546: val_loss -0.7727 +2024-11-22 09:31:37.256625: Pseudo dice [0.8562] +2024-11-22 09:31:37.256701: Epoch time: 17.57 s +2024-11-22 09:31:38.372757: +2024-11-22 09:31:38.372969: Epoch 4250 +2024-11-22 09:31:38.373087: Current learning rate: 0.00506 +2024-11-22 09:31:56.417246: train_loss -0.7927 +2024-11-22 09:31:56.417496: val_loss -0.7833 +2024-11-22 09:31:56.417571: Pseudo dice [0.8431] +2024-11-22 09:31:56.417652: Epoch time: 18.05 s +2024-11-22 09:31:57.354141: +2024-11-22 09:31:57.354370: Epoch 4251 +2024-11-22 09:31:57.354479: Current learning rate: 0.00506 +2024-11-22 09:32:15.647897: train_loss -0.7986 +2024-11-22 09:32:15.648217: val_loss -0.7752 +2024-11-22 09:32:15.648297: Pseudo dice [0.846] +2024-11-22 09:32:15.648379: Epoch time: 18.29 s +2024-11-22 09:32:16.506294: +2024-11-22 09:32:16.506529: Epoch 4252 +2024-11-22 09:32:16.506648: Current learning rate: 0.00505 +2024-11-22 09:32:35.374433: train_loss -0.786 +2024-11-22 09:32:35.374646: val_loss -0.7688 +2024-11-22 09:32:35.374730: Pseudo dice [0.8577] +2024-11-22 09:32:35.374804: Epoch time: 18.87 s +2024-11-22 09:32:36.571732: +2024-11-22 09:32:36.571963: Epoch 4253 +2024-11-22 09:32:36.572076: Current learning rate: 0.00505 +2024-11-22 09:32:54.514904: train_loss -0.7903 +2024-11-22 09:32:54.515177: val_loss -0.7801 +2024-11-22 09:32:54.515254: Pseudo dice [0.8523] +2024-11-22 09:32:54.515339: Epoch time: 17.94 s +2024-11-22 09:32:55.372292: +2024-11-22 09:32:55.372519: Epoch 4254 +2024-11-22 09:32:55.372629: Current learning rate: 0.00505 +2024-11-22 09:33:14.665250: train_loss -0.7926 +2024-11-22 09:33:14.665467: val_loss -0.724 +2024-11-22 09:33:14.665541: Pseudo dice [0.831] +2024-11-22 09:33:14.667778: Epoch time: 19.29 s +2024-11-22 09:33:15.647168: +2024-11-22 09:33:15.647386: Epoch 4255 +2024-11-22 09:33:15.647492: Current learning rate: 0.00505 +2024-11-22 09:33:32.534146: train_loss -0.7939 +2024-11-22 09:33:32.534370: val_loss -0.7637 +2024-11-22 09:33:32.534446: Pseudo dice [0.8592] +2024-11-22 09:33:32.534521: Epoch time: 16.89 s +2024-11-22 09:33:33.394429: +2024-11-22 09:33:33.394674: Epoch 4256 +2024-11-22 09:33:33.394787: Current learning rate: 0.00505 +2024-11-22 09:33:50.921703: train_loss -0.7955 +2024-11-22 09:33:50.921929: val_loss -0.7766 +2024-11-22 09:33:50.922013: Pseudo dice [0.8579] +2024-11-22 09:33:50.922090: Epoch time: 17.53 s +2024-11-22 09:33:51.808872: +2024-11-22 09:33:51.809122: Epoch 4257 +2024-11-22 09:33:51.809244: Current learning rate: 0.00505 +2024-11-22 09:34:11.199251: train_loss -0.7906 +2024-11-22 09:34:11.199511: val_loss -0.7597 +2024-11-22 09:34:11.199592: Pseudo dice [0.843] +2024-11-22 09:34:11.199674: Epoch time: 19.39 s +2024-11-22 09:34:12.055969: +2024-11-22 09:34:12.056254: Epoch 4258 +2024-11-22 09:34:12.056362: Current learning rate: 0.00505 +2024-11-22 09:34:30.324042: train_loss -0.7884 +2024-11-22 09:34:30.324255: val_loss -0.7725 +2024-11-22 09:34:30.324346: Pseudo dice [0.8466] +2024-11-22 09:34:30.324432: Epoch time: 18.27 s +2024-11-22 09:34:31.200940: +2024-11-22 09:34:31.201175: Epoch 4259 +2024-11-22 09:34:31.201303: Current learning rate: 0.00505 +2024-11-22 09:34:48.717221: train_loss -0.7914 +2024-11-22 09:34:48.717441: val_loss -0.7574 +2024-11-22 09:34:48.717514: Pseudo dice [0.8359] +2024-11-22 09:34:48.717587: Epoch time: 17.52 s +2024-11-22 09:34:49.574415: +2024-11-22 09:34:49.574631: Epoch 4260 +2024-11-22 09:34:49.574744: Current learning rate: 0.00504 +2024-11-22 09:35:07.723601: train_loss -0.7905 +2024-11-22 09:35:07.723846: val_loss -0.791 +2024-11-22 09:35:07.723921: Pseudo dice [0.8469] +2024-11-22 09:35:07.724330: Epoch time: 18.15 s +2024-11-22 09:35:08.593723: +2024-11-22 09:35:08.593961: Epoch 4261 +2024-11-22 09:35:08.594082: Current learning rate: 0.00504 +2024-11-22 09:35:27.333265: train_loss -0.7924 +2024-11-22 09:35:27.333483: val_loss -0.7704 +2024-11-22 09:35:27.333556: Pseudo dice [0.8322] +2024-11-22 09:35:27.333631: Epoch time: 18.74 s +2024-11-22 09:35:28.189608: +2024-11-22 09:35:28.189829: Epoch 4262 +2024-11-22 09:35:28.189940: Current learning rate: 0.00504 +2024-11-22 09:35:47.235785: train_loss -0.793 +2024-11-22 09:35:47.236012: val_loss -0.7701 +2024-11-22 09:35:47.236085: Pseudo dice [0.8414] +2024-11-22 09:35:47.236161: Epoch time: 19.05 s +2024-11-22 09:35:48.097621: +2024-11-22 09:35:48.097986: Epoch 4263 +2024-11-22 09:35:48.098103: Current learning rate: 0.00504 +2024-11-22 09:36:05.996167: train_loss -0.7945 +2024-11-22 09:36:05.996396: val_loss -0.7449 +2024-11-22 09:36:05.996470: Pseudo dice [0.8469] +2024-11-22 09:36:05.996547: Epoch time: 17.9 s +2024-11-22 09:36:06.857682: +2024-11-22 09:36:06.857889: Epoch 4264 +2024-11-22 09:36:06.858005: Current learning rate: 0.00504 +2024-11-22 09:36:25.368908: train_loss -0.7807 +2024-11-22 09:36:25.369168: val_loss -0.7726 +2024-11-22 09:36:25.369251: Pseudo dice [0.8354] +2024-11-22 09:36:25.369337: Epoch time: 18.51 s +2024-11-22 09:36:26.619914: +2024-11-22 09:36:26.620250: Epoch 4265 +2024-11-22 09:36:26.620366: Current learning rate: 0.00504 +2024-11-22 09:36:45.051016: train_loss -0.7737 +2024-11-22 09:36:45.051251: val_loss -0.7652 +2024-11-22 09:36:45.051325: Pseudo dice [0.8512] +2024-11-22 09:36:45.051401: Epoch time: 18.43 s +2024-11-22 09:36:45.993380: +2024-11-22 09:36:45.993688: Epoch 4266 +2024-11-22 09:36:45.993804: Current learning rate: 0.00504 +2024-11-22 09:37:04.983360: train_loss -0.7805 +2024-11-22 09:37:04.983601: val_loss -0.7427 +2024-11-22 09:37:04.983680: Pseudo dice [0.8451] +2024-11-22 09:37:04.983757: Epoch time: 18.99 s +2024-11-22 09:37:05.965815: +2024-11-22 09:37:05.966063: Epoch 4267 +2024-11-22 09:37:05.966180: Current learning rate: 0.00504 +2024-11-22 09:37:24.455313: train_loss -0.7832 +2024-11-22 09:37:24.455565: val_loss -0.7529 +2024-11-22 09:37:24.455641: Pseudo dice [0.8098] +2024-11-22 09:37:24.455727: Epoch time: 18.49 s +2024-11-22 09:37:25.319861: +2024-11-22 09:37:25.320100: Epoch 4268 +2024-11-22 09:37:25.320210: Current learning rate: 0.00503 +2024-11-22 09:37:44.656318: train_loss -0.785 +2024-11-22 09:37:44.656583: val_loss -0.7754 +2024-11-22 09:37:44.656661: Pseudo dice [0.8378] +2024-11-22 09:37:44.656735: Epoch time: 19.34 s +2024-11-22 09:37:45.555142: +2024-11-22 09:37:45.555395: Epoch 4269 +2024-11-22 09:37:45.555502: Current learning rate: 0.00503 +2024-11-22 09:38:04.458861: train_loss -0.7789 +2024-11-22 09:38:04.459114: val_loss -0.7699 +2024-11-22 09:38:04.459191: Pseudo dice [0.8438] +2024-11-22 09:38:04.459266: Epoch time: 18.9 s +2024-11-22 09:38:05.320793: +2024-11-22 09:38:05.321026: Epoch 4270 +2024-11-22 09:38:05.321138: Current learning rate: 0.00503 +2024-11-22 09:38:23.695995: train_loss -0.7873 +2024-11-22 09:38:23.696203: val_loss -0.7845 +2024-11-22 09:38:23.696279: Pseudo dice [0.8491] +2024-11-22 09:38:23.696352: Epoch time: 18.38 s +2024-11-22 09:38:24.566170: +2024-11-22 09:38:24.566431: Epoch 4271 +2024-11-22 09:38:24.566557: Current learning rate: 0.00503 +2024-11-22 09:38:43.695815: train_loss -0.794 +2024-11-22 09:38:43.696080: val_loss -0.7703 +2024-11-22 09:38:43.696161: Pseudo dice [0.8404] +2024-11-22 09:38:43.696239: Epoch time: 19.13 s +2024-11-22 09:38:44.560100: +2024-11-22 09:38:44.560312: Epoch 4272 +2024-11-22 09:38:44.560421: Current learning rate: 0.00503 +2024-11-22 09:39:03.129145: train_loss -0.7957 +2024-11-22 09:39:03.129372: val_loss -0.7531 +2024-11-22 09:39:03.129448: Pseudo dice [0.8398] +2024-11-22 09:39:03.129522: Epoch time: 18.57 s +2024-11-22 09:39:04.030112: +2024-11-22 09:39:04.030341: Epoch 4273 +2024-11-22 09:39:04.030480: Current learning rate: 0.00503 +2024-11-22 09:39:22.194405: train_loss -0.792 +2024-11-22 09:39:22.194625: val_loss -0.7553 +2024-11-22 09:39:22.194700: Pseudo dice [0.8453] +2024-11-22 09:39:22.194775: Epoch time: 18.17 s +2024-11-22 09:39:23.057827: +2024-11-22 09:39:23.058043: Epoch 4274 +2024-11-22 09:39:23.058149: Current learning rate: 0.00503 +2024-11-22 09:39:41.906049: train_loss -0.7992 +2024-11-22 09:39:41.906299: val_loss -0.7898 +2024-11-22 09:39:41.906375: Pseudo dice [0.8526] +2024-11-22 09:39:41.906459: Epoch time: 18.85 s +2024-11-22 09:39:42.767604: +2024-11-22 09:39:42.767862: Epoch 4275 +2024-11-22 09:39:42.767978: Current learning rate: 0.00503 +2024-11-22 09:40:02.647395: train_loss -0.7844 +2024-11-22 09:40:02.647613: val_loss -0.7789 +2024-11-22 09:40:02.647689: Pseudo dice [0.8584] +2024-11-22 09:40:02.647762: Epoch time: 19.88 s +2024-11-22 09:40:03.508186: +2024-11-22 09:40:03.508398: Epoch 4276 +2024-11-22 09:40:03.508508: Current learning rate: 0.00502 +2024-11-22 09:40:22.221870: train_loss -0.7929 +2024-11-22 09:40:22.222110: val_loss -0.7466 +2024-11-22 09:40:22.222183: Pseudo dice [0.8453] +2024-11-22 09:40:22.222261: Epoch time: 18.71 s +2024-11-22 09:40:23.498970: +2024-11-22 09:40:23.499213: Epoch 4277 +2024-11-22 09:40:23.499322: Current learning rate: 0.00502 +2024-11-22 09:40:42.683200: train_loss -0.7923 +2024-11-22 09:40:42.683493: val_loss -0.7583 +2024-11-22 09:40:42.683577: Pseudo dice [0.8532] +2024-11-22 09:40:42.683661: Epoch time: 19.18 s +2024-11-22 09:40:43.547665: +2024-11-22 09:40:43.547893: Epoch 4278 +2024-11-22 09:40:43.548009: Current learning rate: 0.00502 +2024-11-22 09:41:01.665251: train_loss -0.7728 +2024-11-22 09:41:01.665486: val_loss -0.7521 +2024-11-22 09:41:01.665561: Pseudo dice [0.8271] +2024-11-22 09:41:01.665632: Epoch time: 18.12 s +2024-11-22 09:41:02.522307: +2024-11-22 09:41:02.522528: Epoch 4279 +2024-11-22 09:41:02.522645: Current learning rate: 0.00502 +2024-11-22 09:41:20.950232: train_loss -0.7787 +2024-11-22 09:41:20.950449: val_loss -0.7673 +2024-11-22 09:41:20.950523: Pseudo dice [0.8363] +2024-11-22 09:41:20.950598: Epoch time: 18.43 s +2024-11-22 09:41:21.810020: +2024-11-22 09:41:21.810246: Epoch 4280 +2024-11-22 09:41:21.810364: Current learning rate: 0.00502 +2024-11-22 09:41:40.522774: train_loss -0.7669 +2024-11-22 09:41:40.523009: val_loss -0.7758 +2024-11-22 09:41:40.523099: Pseudo dice [0.8409] +2024-11-22 09:41:40.523196: Epoch time: 18.71 s +2024-11-22 09:41:41.391899: +2024-11-22 09:41:41.392288: Epoch 4281 +2024-11-22 09:41:41.392411: Current learning rate: 0.00502 +2024-11-22 09:42:00.381385: train_loss -0.7718 +2024-11-22 09:42:00.381648: val_loss -0.7428 +2024-11-22 09:42:00.381725: Pseudo dice [0.8468] +2024-11-22 09:42:00.381808: Epoch time: 18.99 s +2024-11-22 09:42:01.303970: +2024-11-22 09:42:01.304264: Epoch 4282 +2024-11-22 09:42:01.304377: Current learning rate: 0.00502 +2024-11-22 09:42:19.276989: train_loss -0.7714 +2024-11-22 09:42:19.277220: val_loss -0.7739 +2024-11-22 09:42:19.277298: Pseudo dice [0.8563] +2024-11-22 09:42:19.277464: Epoch time: 17.97 s +2024-11-22 09:42:20.177861: +2024-11-22 09:42:20.178109: Epoch 4283 +2024-11-22 09:42:20.178224: Current learning rate: 0.00502 +2024-11-22 09:42:39.321110: train_loss -0.7785 +2024-11-22 09:42:39.321329: val_loss -0.7779 +2024-11-22 09:42:39.321409: Pseudo dice [0.8495] +2024-11-22 09:42:39.321482: Epoch time: 19.14 s +2024-11-22 09:42:40.178613: +2024-11-22 09:42:40.178822: Epoch 4284 +2024-11-22 09:42:40.178937: Current learning rate: 0.00502 +2024-11-22 09:42:57.300218: train_loss -0.7914 +2024-11-22 09:42:57.300483: val_loss -0.7578 +2024-11-22 09:42:57.300570: Pseudo dice [0.8536] +2024-11-22 09:42:57.300661: Epoch time: 17.12 s +2024-11-22 09:42:58.163579: +2024-11-22 09:42:58.163869: Epoch 4285 +2024-11-22 09:42:58.163984: Current learning rate: 0.00501 +2024-11-22 09:43:16.863613: train_loss -0.7825 +2024-11-22 09:43:16.863829: val_loss -0.7965 +2024-11-22 09:43:16.863902: Pseudo dice [0.8439] +2024-11-22 09:43:16.863974: Epoch time: 18.7 s +2024-11-22 09:43:17.726509: +2024-11-22 09:43:17.726736: Epoch 4286 +2024-11-22 09:43:17.726849: Current learning rate: 0.00501 +2024-11-22 09:43:36.528483: train_loss -0.7868 +2024-11-22 09:43:36.528704: val_loss -0.7551 +2024-11-22 09:43:36.528777: Pseudo dice [0.8543] +2024-11-22 09:43:36.529084: Epoch time: 18.8 s +2024-11-22 09:43:37.396234: +2024-11-22 09:43:37.396458: Epoch 4287 +2024-11-22 09:43:37.396571: Current learning rate: 0.00501 +2024-11-22 09:43:55.949194: train_loss -0.784 +2024-11-22 09:43:55.949471: val_loss -0.7775 +2024-11-22 09:43:55.949549: Pseudo dice [0.8581] +2024-11-22 09:43:55.949638: Epoch time: 18.55 s +2024-11-22 09:43:56.922041: +2024-11-22 09:43:56.922248: Epoch 4288 +2024-11-22 09:43:56.922365: Current learning rate: 0.00501 +2024-11-22 09:44:16.395288: train_loss -0.7853 +2024-11-22 09:44:16.395502: val_loss -0.7794 +2024-11-22 09:44:16.395576: Pseudo dice [0.8524] +2024-11-22 09:44:16.395649: Epoch time: 19.47 s +2024-11-22 09:44:17.651205: +2024-11-22 09:44:17.651457: Epoch 4289 +2024-11-22 09:44:17.651569: Current learning rate: 0.00501 +2024-11-22 09:44:34.949092: train_loss -0.7856 +2024-11-22 09:44:34.949332: val_loss -0.7937 +2024-11-22 09:44:34.949410: Pseudo dice [0.8567] +2024-11-22 09:44:34.949487: Epoch time: 17.3 s +2024-11-22 09:44:35.805725: +2024-11-22 09:44:35.805925: Epoch 4290 +2024-11-22 09:44:35.806037: Current learning rate: 0.00501 +2024-11-22 09:44:54.498667: train_loss -0.7923 +2024-11-22 09:44:54.498905: val_loss -0.7782 +2024-11-22 09:44:54.498997: Pseudo dice [0.8553] +2024-11-22 09:44:54.499079: Epoch time: 18.69 s +2024-11-22 09:44:55.370101: +2024-11-22 09:44:55.370315: Epoch 4291 +2024-11-22 09:44:55.370426: Current learning rate: 0.00501 +2024-11-22 09:45:15.281207: train_loss -0.7875 +2024-11-22 09:45:15.281456: val_loss -0.7592 +2024-11-22 09:45:15.281532: Pseudo dice [0.836] +2024-11-22 09:45:15.281613: Epoch time: 19.91 s +2024-11-22 09:45:16.148237: +2024-11-22 09:45:16.148462: Epoch 4292 +2024-11-22 09:45:16.148571: Current learning rate: 0.00501 +2024-11-22 09:45:34.545665: train_loss -0.7889 +2024-11-22 09:45:34.545871: val_loss -0.7519 +2024-11-22 09:45:34.545945: Pseudo dice [0.844] +2024-11-22 09:45:34.546023: Epoch time: 18.4 s +2024-11-22 09:45:35.407878: +2024-11-22 09:45:35.408123: Epoch 4293 +2024-11-22 09:45:35.408236: Current learning rate: 0.005 +2024-11-22 09:45:52.610463: train_loss -0.7698 +2024-11-22 09:45:52.610676: val_loss -0.7633 +2024-11-22 09:45:52.610757: Pseudo dice [0.843] +2024-11-22 09:45:52.610834: Epoch time: 17.2 s +2024-11-22 09:45:53.473985: +2024-11-22 09:45:53.474216: Epoch 4294 +2024-11-22 09:45:53.474331: Current learning rate: 0.005 +2024-11-22 09:46:11.506822: train_loss -0.7845 +2024-11-22 09:46:11.507048: val_loss -0.7709 +2024-11-22 09:46:11.507128: Pseudo dice [0.832] +2024-11-22 09:46:11.507206: Epoch time: 18.03 s +2024-11-22 09:46:12.376354: +2024-11-22 09:46:12.376612: Epoch 4295 +2024-11-22 09:46:12.376727: Current learning rate: 0.005 +2024-11-22 09:46:30.654634: train_loss -0.7868 +2024-11-22 09:46:30.660103: val_loss -0.7739 +2024-11-22 09:46:30.660197: Pseudo dice [0.85] +2024-11-22 09:46:30.660286: Epoch time: 18.28 s +2024-11-22 09:46:31.531335: +2024-11-22 09:46:31.531550: Epoch 4296 +2024-11-22 09:46:31.531658: Current learning rate: 0.005 +2024-11-22 09:46:49.567650: train_loss -0.7858 +2024-11-22 09:46:49.567872: val_loss -0.7586 +2024-11-22 09:46:49.567948: Pseudo dice [0.8551] +2024-11-22 09:46:49.568031: Epoch time: 18.04 s +2024-11-22 09:46:50.431124: +2024-11-22 09:46:50.431364: Epoch 4297 +2024-11-22 09:46:50.431477: Current learning rate: 0.005 +2024-11-22 09:47:08.875805: train_loss -0.776 +2024-11-22 09:47:08.876028: val_loss -0.7517 +2024-11-22 09:47:08.876103: Pseudo dice [0.8334] +2024-11-22 09:47:08.876177: Epoch time: 18.45 s +2024-11-22 09:47:09.739709: +2024-11-22 09:47:09.739986: Epoch 4298 +2024-11-22 09:47:09.740105: Current learning rate: 0.005 +2024-11-22 09:47:28.866478: train_loss -0.775 +2024-11-22 09:47:28.866733: val_loss -0.762 +2024-11-22 09:47:28.866814: Pseudo dice [0.8444] +2024-11-22 09:47:28.866899: Epoch time: 19.13 s +2024-11-22 09:47:29.729082: +2024-11-22 09:47:29.729303: Epoch 4299 +2024-11-22 09:47:29.729421: Current learning rate: 0.005 +2024-11-22 09:47:48.099224: train_loss -0.7869 +2024-11-22 09:47:48.099440: val_loss -0.7654 +2024-11-22 09:47:48.099515: Pseudo dice [0.8626] +2024-11-22 09:47:48.099590: Epoch time: 18.37 s +2024-11-22 09:47:49.236921: +2024-11-22 09:47:49.237119: Epoch 4300 +2024-11-22 09:47:49.237227: Current learning rate: 0.005 +2024-11-22 09:48:08.396712: train_loss -0.7902 +2024-11-22 09:48:08.396939: val_loss -0.7652 +2024-11-22 09:48:08.397016: Pseudo dice [0.8411] +2024-11-22 09:48:08.397090: Epoch time: 19.16 s +2024-11-22 09:48:09.689817: +2024-11-22 09:48:09.690038: Epoch 4301 +2024-11-22 09:48:09.690146: Current learning rate: 0.00499 +2024-11-22 09:48:28.207307: train_loss -0.7853 +2024-11-22 09:48:28.207592: val_loss -0.7632 +2024-11-22 09:48:28.207672: Pseudo dice [0.8509] +2024-11-22 09:48:28.207753: Epoch time: 18.52 s +2024-11-22 09:48:29.068739: +2024-11-22 09:48:29.068967: Epoch 4302 +2024-11-22 09:48:29.069085: Current learning rate: 0.00499 +2024-11-22 09:48:46.954808: train_loss -0.7756 +2024-11-22 09:48:46.955031: val_loss -0.7577 +2024-11-22 09:48:46.955104: Pseudo dice [0.8361] +2024-11-22 09:48:46.955177: Epoch time: 17.89 s +2024-11-22 09:48:47.924046: +2024-11-22 09:48:47.924270: Epoch 4303 +2024-11-22 09:48:47.924381: Current learning rate: 0.00499 +2024-11-22 09:49:06.600330: train_loss -0.7822 +2024-11-22 09:49:06.600553: val_loss -0.7472 +2024-11-22 09:49:06.600626: Pseudo dice [0.8459] +2024-11-22 09:49:06.600698: Epoch time: 18.68 s +2024-11-22 09:49:07.517975: +2024-11-22 09:49:07.518222: Epoch 4304 +2024-11-22 09:49:07.518353: Current learning rate: 0.00499 +2024-11-22 09:49:25.596843: train_loss -0.7919 +2024-11-22 09:49:25.602233: val_loss -0.7681 +2024-11-22 09:49:25.602384: Pseudo dice [0.8611] +2024-11-22 09:49:25.602475: Epoch time: 18.08 s +2024-11-22 09:49:26.658427: +2024-11-22 09:49:26.658666: Epoch 4305 +2024-11-22 09:49:26.658776: Current learning rate: 0.00499 +2024-11-22 09:49:45.550308: train_loss -0.7853 +2024-11-22 09:49:45.550539: val_loss -0.7549 +2024-11-22 09:49:45.550617: Pseudo dice [0.8383] +2024-11-22 09:49:45.550694: Epoch time: 18.89 s +2024-11-22 09:49:46.499781: +2024-11-22 09:49:46.500021: Epoch 4306 +2024-11-22 09:49:46.500137: Current learning rate: 0.00499 +2024-11-22 09:50:04.477356: train_loss -0.7893 +2024-11-22 09:50:04.477573: val_loss -0.7507 +2024-11-22 09:50:04.477646: Pseudo dice [0.8382] +2024-11-22 09:50:04.477774: Epoch time: 17.98 s +2024-11-22 09:50:05.431509: +2024-11-22 09:50:05.431752: Epoch 4307 +2024-11-22 09:50:05.431862: Current learning rate: 0.00499 +2024-11-22 09:50:24.947173: train_loss -0.7884 +2024-11-22 09:50:24.947449: val_loss -0.7694 +2024-11-22 09:50:24.947524: Pseudo dice [0.8571] +2024-11-22 09:50:24.947600: Epoch time: 19.52 s +2024-11-22 09:50:25.920264: +2024-11-22 09:50:25.920467: Epoch 4308 +2024-11-22 09:50:25.920577: Current learning rate: 0.00499 +2024-11-22 09:50:45.323544: train_loss -0.7865 +2024-11-22 09:50:45.323792: val_loss -0.7605 +2024-11-22 09:50:45.323866: Pseudo dice [0.8324] +2024-11-22 09:50:45.323949: Epoch time: 19.4 s +2024-11-22 09:50:46.189899: +2024-11-22 09:50:46.190139: Epoch 4309 +2024-11-22 09:50:46.190253: Current learning rate: 0.00498 +2024-11-22 09:51:04.588504: train_loss -0.7871 +2024-11-22 09:51:04.588728: val_loss -0.7416 +2024-11-22 09:51:04.588800: Pseudo dice [0.8322] +2024-11-22 09:51:04.591082: Epoch time: 18.4 s +2024-11-22 09:51:05.614660: +2024-11-22 09:51:05.614871: Epoch 4310 +2024-11-22 09:51:05.614985: Current learning rate: 0.00498 +2024-11-22 09:51:23.357169: train_loss -0.7856 +2024-11-22 09:51:23.357387: val_loss -0.7307 +2024-11-22 09:51:23.357462: Pseudo dice [0.8185] +2024-11-22 09:51:23.362749: Epoch time: 17.74 s +2024-11-22 09:51:24.250351: +2024-11-22 09:51:24.250648: Epoch 4311 +2024-11-22 09:51:24.250757: Current learning rate: 0.00498 +2024-11-22 09:51:43.977027: train_loss -0.7837 +2024-11-22 09:51:43.977252: val_loss -0.7363 +2024-11-22 09:51:43.977329: Pseudo dice [0.8548] +2024-11-22 09:51:43.977411: Epoch time: 19.73 s +2024-11-22 09:51:44.838705: +2024-11-22 09:51:44.838929: Epoch 4312 +2024-11-22 09:51:44.839047: Current learning rate: 0.00498 +2024-11-22 09:52:04.440492: train_loss -0.7915 +2024-11-22 09:52:04.440742: val_loss -0.7699 +2024-11-22 09:52:04.440817: Pseudo dice [0.8372] +2024-11-22 09:52:04.441125: Epoch time: 19.6 s +2024-11-22 09:52:05.727619: +2024-11-22 09:52:05.727859: Epoch 4313 +2024-11-22 09:52:05.727968: Current learning rate: 0.00498 +2024-11-22 09:52:23.470283: train_loss -0.7968 +2024-11-22 09:52:23.470517: val_loss -0.7657 +2024-11-22 09:52:23.470611: Pseudo dice [0.8446] +2024-11-22 09:52:23.470690: Epoch time: 17.74 s +2024-11-22 09:52:24.328974: +2024-11-22 09:52:24.329235: Epoch 4314 +2024-11-22 09:52:24.329346: Current learning rate: 0.00498 +2024-11-22 09:52:42.937467: train_loss -0.7827 +2024-11-22 09:52:42.938617: val_loss -0.7526 +2024-11-22 09:52:42.938728: Pseudo dice [0.826] +2024-11-22 09:52:42.938834: Epoch time: 18.61 s +2024-11-22 09:52:43.805956: +2024-11-22 09:52:43.806237: Epoch 4315 +2024-11-22 09:52:43.806346: Current learning rate: 0.00498 +2024-11-22 09:53:02.861460: train_loss -0.7759 +2024-11-22 09:53:02.861701: val_loss -0.767 +2024-11-22 09:53:02.861815: Pseudo dice [0.8341] +2024-11-22 09:53:02.861897: Epoch time: 19.06 s +2024-11-22 09:53:03.722435: +2024-11-22 09:53:03.722665: Epoch 4316 +2024-11-22 09:53:03.722775: Current learning rate: 0.00498 +2024-11-22 09:53:22.353694: train_loss -0.7719 +2024-11-22 09:53:22.355347: val_loss -0.7724 +2024-11-22 09:53:22.357094: Pseudo dice [0.8341] +2024-11-22 09:53:22.357318: Epoch time: 18.63 s +2024-11-22 09:53:23.224903: +2024-11-22 09:53:23.225126: Epoch 4317 +2024-11-22 09:53:23.225236: Current learning rate: 0.00498 +2024-11-22 09:53:41.161761: train_loss -0.7959 +2024-11-22 09:53:41.162005: val_loss -0.7736 +2024-11-22 09:53:41.162081: Pseudo dice [0.8521] +2024-11-22 09:53:41.162159: Epoch time: 17.94 s +2024-11-22 09:53:42.022835: +2024-11-22 09:53:42.023046: Epoch 4318 +2024-11-22 09:53:42.023158: Current learning rate: 0.00497 +2024-11-22 09:54:00.234203: train_loss -0.7963 +2024-11-22 09:54:00.234445: val_loss -0.7718 +2024-11-22 09:54:00.234523: Pseudo dice [0.8496] +2024-11-22 09:54:00.234605: Epoch time: 18.21 s +2024-11-22 09:54:01.196303: +2024-11-22 09:54:01.196546: Epoch 4319 +2024-11-22 09:54:01.196653: Current learning rate: 0.00497 +2024-11-22 09:54:20.135224: train_loss -0.7923 +2024-11-22 09:54:20.135459: val_loss -0.7734 +2024-11-22 09:54:20.135535: Pseudo dice [0.8411] +2024-11-22 09:54:20.135654: Epoch time: 18.94 s +2024-11-22 09:54:21.000604: +2024-11-22 09:54:21.000824: Epoch 4320 +2024-11-22 09:54:21.000935: Current learning rate: 0.00497 +2024-11-22 09:54:40.380493: train_loss -0.7929 +2024-11-22 09:54:40.380725: val_loss -0.7738 +2024-11-22 09:54:40.380801: Pseudo dice [0.8407] +2024-11-22 09:54:40.380873: Epoch time: 19.38 s +2024-11-22 09:54:41.238602: +2024-11-22 09:54:41.238830: Epoch 4321 +2024-11-22 09:54:41.238954: Current learning rate: 0.00497 +2024-11-22 09:54:59.710402: train_loss -0.7918 +2024-11-22 09:54:59.710617: val_loss -0.7665 +2024-11-22 09:54:59.710717: Pseudo dice [0.8497] +2024-11-22 09:54:59.710832: Epoch time: 18.47 s +2024-11-22 09:55:00.667285: +2024-11-22 09:55:00.667483: Epoch 4322 +2024-11-22 09:55:00.667588: Current learning rate: 0.00497 +2024-11-22 09:55:18.449770: train_loss -0.7888 +2024-11-22 09:55:18.450039: val_loss -0.7685 +2024-11-22 09:55:18.450120: Pseudo dice [0.8515] +2024-11-22 09:55:18.450203: Epoch time: 17.78 s +2024-11-22 09:55:19.291262: +2024-11-22 09:55:19.291483: Epoch 4323 +2024-11-22 09:55:19.291587: Current learning rate: 0.00497 +2024-11-22 09:55:37.624759: train_loss -0.7961 +2024-11-22 09:55:37.624976: val_loss -0.7772 +2024-11-22 09:55:37.625060: Pseudo dice [0.8549] +2024-11-22 09:55:37.625136: Epoch time: 18.33 s +2024-11-22 09:55:38.482085: +2024-11-22 09:55:38.482308: Epoch 4324 +2024-11-22 09:55:38.482415: Current learning rate: 0.00497 +2024-11-22 09:55:57.299619: train_loss -0.7926 +2024-11-22 09:55:57.299840: val_loss -0.7887 +2024-11-22 09:55:57.299914: Pseudo dice [0.8501] +2024-11-22 09:55:57.299988: Epoch time: 18.82 s +2024-11-22 09:55:58.573116: +2024-11-22 09:55:58.573348: Epoch 4325 +2024-11-22 09:55:58.573458: Current learning rate: 0.00497 +2024-11-22 09:56:17.193395: train_loss -0.7891 +2024-11-22 09:56:17.193659: val_loss -0.7885 +2024-11-22 09:56:17.193741: Pseudo dice [0.8529] +2024-11-22 09:56:17.193822: Epoch time: 18.62 s +2024-11-22 09:56:18.061803: +2024-11-22 09:56:18.062023: Epoch 4326 +2024-11-22 09:56:18.062142: Current learning rate: 0.00496 +2024-11-22 09:56:36.447215: train_loss -0.7849 +2024-11-22 09:56:36.447438: val_loss -0.7616 +2024-11-22 09:56:36.447511: Pseudo dice [0.8301] +2024-11-22 09:56:36.449147: Epoch time: 18.39 s +2024-11-22 09:56:37.447820: +2024-11-22 09:56:37.448058: Epoch 4327 +2024-11-22 09:56:37.448174: Current learning rate: 0.00496 +2024-11-22 09:56:56.850823: train_loss -0.7824 +2024-11-22 09:56:56.851048: val_loss -0.78 +2024-11-22 09:56:56.851124: Pseudo dice [0.859] +2024-11-22 09:56:56.851197: Epoch time: 19.4 s +2024-11-22 09:56:57.809739: +2024-11-22 09:56:57.809967: Epoch 4328 +2024-11-22 09:56:57.810112: Current learning rate: 0.00496 +2024-11-22 09:57:15.270192: train_loss -0.7932 +2024-11-22 09:57:15.271376: val_loss -0.7635 +2024-11-22 09:57:15.271511: Pseudo dice [0.8341] +2024-11-22 09:57:15.271602: Epoch time: 17.46 s +2024-11-22 09:57:16.154033: +2024-11-22 09:57:16.154267: Epoch 4329 +2024-11-22 09:57:16.154380: Current learning rate: 0.00496 +2024-11-22 09:57:35.662420: train_loss -0.7829 +2024-11-22 09:57:35.662683: val_loss -0.7671 +2024-11-22 09:57:35.662758: Pseudo dice [0.8376] +2024-11-22 09:57:35.662835: Epoch time: 19.51 s +2024-11-22 09:57:36.523464: +2024-11-22 09:57:36.523711: Epoch 4330 +2024-11-22 09:57:36.523830: Current learning rate: 0.00496 +2024-11-22 09:57:55.330406: train_loss -0.775 +2024-11-22 09:57:55.330623: val_loss -0.7684 +2024-11-22 09:57:55.330696: Pseudo dice [0.8299] +2024-11-22 09:57:55.330833: Epoch time: 18.81 s +2024-11-22 09:57:56.192287: +2024-11-22 09:57:56.192500: Epoch 4331 +2024-11-22 09:57:56.192609: Current learning rate: 0.00496 +2024-11-22 09:58:15.536284: train_loss -0.7746 +2024-11-22 09:58:15.536502: val_loss -0.7689 +2024-11-22 09:58:15.536573: Pseudo dice [0.8475] +2024-11-22 09:58:15.536647: Epoch time: 19.34 s +2024-11-22 09:58:16.426044: +2024-11-22 09:58:16.426269: Epoch 4332 +2024-11-22 09:58:16.426376: Current learning rate: 0.00496 +2024-11-22 09:58:35.155889: train_loss -0.7784 +2024-11-22 09:58:35.156143: val_loss -0.7492 +2024-11-22 09:58:35.156220: Pseudo dice [0.8079] +2024-11-22 09:58:35.156303: Epoch time: 18.73 s +2024-11-22 09:58:36.019177: +2024-11-22 09:58:36.019397: Epoch 4333 +2024-11-22 09:58:36.019506: Current learning rate: 0.00496 +2024-11-22 09:58:54.639831: train_loss -0.7693 +2024-11-22 09:58:54.640056: val_loss -0.7571 +2024-11-22 09:58:54.640133: Pseudo dice [0.8429] +2024-11-22 09:58:54.640267: Epoch time: 18.62 s +2024-11-22 09:58:55.500253: +2024-11-22 09:58:55.500486: Epoch 4334 +2024-11-22 09:58:55.500598: Current learning rate: 0.00495 +2024-11-22 09:59:14.604222: train_loss -0.7727 +2024-11-22 09:59:14.604437: val_loss -0.7573 +2024-11-22 09:59:14.604510: Pseudo dice [0.8247] +2024-11-22 09:59:14.604584: Epoch time: 19.1 s +2024-11-22 09:59:15.507119: +2024-11-22 09:59:15.507339: Epoch 4335 +2024-11-22 09:59:15.507452: Current learning rate: 0.00495 +2024-11-22 09:59:34.368694: train_loss -0.7648 +2024-11-22 09:59:34.368952: val_loss -0.746 +2024-11-22 09:59:34.369044: Pseudo dice [0.8369] +2024-11-22 09:59:34.369128: Epoch time: 18.86 s +2024-11-22 09:59:35.231240: +2024-11-22 09:59:35.231447: Epoch 4336 +2024-11-22 09:59:35.231555: Current learning rate: 0.00495 +2024-11-22 09:59:54.021340: train_loss -0.7718 +2024-11-22 09:59:54.021564: val_loss -0.7305 +2024-11-22 09:59:54.021640: Pseudo dice [0.8252] +2024-11-22 09:59:54.021715: Epoch time: 18.79 s +2024-11-22 09:59:55.297097: +2024-11-22 09:59:55.297340: Epoch 4337 +2024-11-22 09:59:55.297448: Current learning rate: 0.00495 +2024-11-22 10:00:13.974802: train_loss -0.7798 +2024-11-22 10:00:13.975042: val_loss -0.7697 +2024-11-22 10:00:13.975122: Pseudo dice [0.84] +2024-11-22 10:00:13.975196: Epoch time: 18.68 s +2024-11-22 10:00:14.834221: +2024-11-22 10:00:14.834550: Epoch 4338 +2024-11-22 10:00:14.834668: Current learning rate: 0.00495 +2024-11-22 10:00:33.809783: train_loss -0.7914 +2024-11-22 10:00:33.810067: val_loss -0.7516 +2024-11-22 10:00:33.810431: Pseudo dice [0.8492] +2024-11-22 10:00:33.810522: Epoch time: 18.98 s +2024-11-22 10:00:34.678318: +2024-11-22 10:00:34.678558: Epoch 4339 +2024-11-22 10:00:34.678670: Current learning rate: 0.00495 +2024-11-22 10:00:53.572706: train_loss -0.7839 +2024-11-22 10:00:53.572930: val_loss -0.7521 +2024-11-22 10:00:53.573012: Pseudo dice [0.8336] +2024-11-22 10:00:53.573089: Epoch time: 18.9 s +2024-11-22 10:00:54.435543: +2024-11-22 10:00:54.435790: Epoch 4340 +2024-11-22 10:00:54.435909: Current learning rate: 0.00495 +2024-11-22 10:01:12.861366: train_loss -0.7928 +2024-11-22 10:01:12.861580: val_loss -0.7722 +2024-11-22 10:01:12.861653: Pseudo dice [0.8388] +2024-11-22 10:01:12.861727: Epoch time: 18.43 s +2024-11-22 10:01:13.724895: +2024-11-22 10:01:13.725118: Epoch 4341 +2024-11-22 10:01:13.725224: Current learning rate: 0.00495 +2024-11-22 10:01:31.258264: train_loss -0.7872 +2024-11-22 10:01:31.258468: val_loss -0.7818 +2024-11-22 10:01:31.258541: Pseudo dice [0.8555] +2024-11-22 10:01:31.258615: Epoch time: 17.53 s +2024-11-22 10:01:32.192142: +2024-11-22 10:01:32.192370: Epoch 4342 +2024-11-22 10:01:32.192487: Current learning rate: 0.00494 +2024-11-22 10:01:50.792824: train_loss -0.7872 +2024-11-22 10:01:50.793140: val_loss -0.761 +2024-11-22 10:01:50.793224: Pseudo dice [0.8468] +2024-11-22 10:01:50.793305: Epoch time: 18.6 s +2024-11-22 10:01:51.701165: +2024-11-22 10:01:51.701389: Epoch 4343 +2024-11-22 10:01:51.701510: Current learning rate: 0.00494 +2024-11-22 10:02:10.001420: train_loss -0.7904 +2024-11-22 10:02:10.001659: val_loss -0.7829 +2024-11-22 10:02:10.001742: Pseudo dice [0.8454] +2024-11-22 10:02:10.001822: Epoch time: 18.3 s +2024-11-22 10:02:10.863064: +2024-11-22 10:02:10.863282: Epoch 4344 +2024-11-22 10:02:10.863392: Current learning rate: 0.00494 +2024-11-22 10:02:29.417248: train_loss -0.7884 +2024-11-22 10:02:29.417483: val_loss -0.798 +2024-11-22 10:02:29.417560: Pseudo dice [0.8596] +2024-11-22 10:02:29.417638: Epoch time: 18.56 s +2024-11-22 10:02:30.285156: +2024-11-22 10:02:30.285372: Epoch 4345 +2024-11-22 10:02:30.285487: Current learning rate: 0.00494 +2024-11-22 10:02:48.123312: train_loss -0.8007 +2024-11-22 10:02:48.123535: val_loss -0.7878 +2024-11-22 10:02:48.123612: Pseudo dice [0.8427] +2024-11-22 10:02:48.123688: Epoch time: 17.84 s +2024-11-22 10:02:48.985011: +2024-11-22 10:02:48.985307: Epoch 4346 +2024-11-22 10:02:48.985418: Current learning rate: 0.00494 +2024-11-22 10:03:06.126156: train_loss -0.7826 +2024-11-22 10:03:06.126408: val_loss -0.756 +2024-11-22 10:03:06.126487: Pseudo dice [0.848] +2024-11-22 10:03:06.126570: Epoch time: 17.14 s +2024-11-22 10:03:06.992672: +2024-11-22 10:03:06.992897: Epoch 4347 +2024-11-22 10:03:06.993028: Current learning rate: 0.00494 +2024-11-22 10:03:25.754179: train_loss -0.7847 +2024-11-22 10:03:25.754396: val_loss -0.7611 +2024-11-22 10:03:25.754557: Pseudo dice [0.831] +2024-11-22 10:03:25.754639: Epoch time: 18.76 s +2024-11-22 10:03:26.712363: +2024-11-22 10:03:26.712583: Epoch 4348 +2024-11-22 10:03:26.712692: Current learning rate: 0.00494 +2024-11-22 10:03:44.168795: train_loss -0.7854 +2024-11-22 10:03:44.172787: val_loss -0.7656 +2024-11-22 10:03:44.172912: Pseudo dice [0.8538] +2024-11-22 10:03:44.172989: Epoch time: 17.46 s +2024-11-22 10:03:45.469914: +2024-11-22 10:03:45.470134: Epoch 4349 +2024-11-22 10:03:45.470244: Current learning rate: 0.00494 +2024-11-22 10:04:03.565854: train_loss -0.7816 +2024-11-22 10:04:03.566144: val_loss -0.7306 +2024-11-22 10:04:03.566220: Pseudo dice [0.8271] +2024-11-22 10:04:03.566303: Epoch time: 18.1 s +2024-11-22 10:04:04.704175: +2024-11-22 10:04:04.704408: Epoch 4350 +2024-11-22 10:04:04.704530: Current learning rate: 0.00493 +2024-11-22 10:04:22.876220: train_loss -0.7866 +2024-11-22 10:04:22.876450: val_loss -0.7697 +2024-11-22 10:04:22.876523: Pseudo dice [0.8394] +2024-11-22 10:04:22.876597: Epoch time: 18.17 s +2024-11-22 10:04:23.742659: +2024-11-22 10:04:23.742886: Epoch 4351 +2024-11-22 10:04:23.743011: Current learning rate: 0.00493 +2024-11-22 10:04:42.217593: train_loss -0.7701 +2024-11-22 10:04:42.217811: val_loss -0.7871 +2024-11-22 10:04:42.217884: Pseudo dice [0.8544] +2024-11-22 10:04:42.217961: Epoch time: 18.48 s +2024-11-22 10:04:43.089776: +2024-11-22 10:04:43.090023: Epoch 4352 +2024-11-22 10:04:43.090132: Current learning rate: 0.00493 +2024-11-22 10:05:00.843009: train_loss -0.7739 +2024-11-22 10:05:00.843253: val_loss -0.7319 +2024-11-22 10:05:00.843336: Pseudo dice [0.8312] +2024-11-22 10:05:00.843419: Epoch time: 17.75 s +2024-11-22 10:05:01.713476: +2024-11-22 10:05:01.713699: Epoch 4353 +2024-11-22 10:05:01.713809: Current learning rate: 0.00493 +2024-11-22 10:05:19.664363: train_loss -0.7732 +2024-11-22 10:05:19.664597: val_loss -0.7971 +2024-11-22 10:05:19.664672: Pseudo dice [0.8569] +2024-11-22 10:05:19.664748: Epoch time: 17.95 s +2024-11-22 10:05:20.518718: +2024-11-22 10:05:20.518941: Epoch 4354 +2024-11-22 10:05:20.519056: Current learning rate: 0.00493 +2024-11-22 10:05:38.109243: train_loss -0.7844 +2024-11-22 10:05:38.109468: val_loss -0.76 +2024-11-22 10:05:38.109544: Pseudo dice [0.8526] +2024-11-22 10:05:38.109622: Epoch time: 17.59 s +2024-11-22 10:05:39.289463: +2024-11-22 10:05:39.289686: Epoch 4355 +2024-11-22 10:05:39.289796: Current learning rate: 0.00493 +2024-11-22 10:05:57.851784: train_loss -0.7875 +2024-11-22 10:05:57.852043: val_loss -0.7445 +2024-11-22 10:05:57.852119: Pseudo dice [0.842] +2024-11-22 10:05:57.852193: Epoch time: 18.56 s +2024-11-22 10:05:58.715268: +2024-11-22 10:05:58.715498: Epoch 4356 +2024-11-22 10:05:58.715607: Current learning rate: 0.00493 +2024-11-22 10:06:16.845000: train_loss -0.7721 +2024-11-22 10:06:16.845254: val_loss -0.7496 +2024-11-22 10:06:16.845334: Pseudo dice [0.8323] +2024-11-22 10:06:16.845418: Epoch time: 18.13 s +2024-11-22 10:06:17.742645: +2024-11-22 10:06:17.742872: Epoch 4357 +2024-11-22 10:06:17.742982: Current learning rate: 0.00493 +2024-11-22 10:06:35.795971: train_loss -0.7677 +2024-11-22 10:06:35.796236: val_loss -0.7772 +2024-11-22 10:06:35.796313: Pseudo dice [0.8618] +2024-11-22 10:06:35.796388: Epoch time: 18.05 s +2024-11-22 10:06:36.657938: +2024-11-22 10:06:36.658174: Epoch 4358 +2024-11-22 10:06:36.658282: Current learning rate: 0.00493 +2024-11-22 10:06:55.280400: train_loss -0.7782 +2024-11-22 10:06:55.280653: val_loss -0.7678 +2024-11-22 10:06:55.280787: Pseudo dice [0.8523] +2024-11-22 10:06:55.280862: Epoch time: 18.62 s +2024-11-22 10:06:56.148649: +2024-11-22 10:06:56.148866: Epoch 4359 +2024-11-22 10:06:56.148976: Current learning rate: 0.00492 +2024-11-22 10:07:14.188725: train_loss -0.7709 +2024-11-22 10:07:14.188948: val_loss -0.7762 +2024-11-22 10:07:14.189034: Pseudo dice [0.8433] +2024-11-22 10:07:14.189114: Epoch time: 18.04 s +2024-11-22 10:07:15.061689: +2024-11-22 10:07:15.061950: Epoch 4360 +2024-11-22 10:07:15.062107: Current learning rate: 0.00492 +2024-11-22 10:07:33.861139: train_loss -0.7834 +2024-11-22 10:07:33.861409: val_loss -0.7786 +2024-11-22 10:07:33.861486: Pseudo dice [0.8475] +2024-11-22 10:07:33.861567: Epoch time: 18.8 s +2024-11-22 10:07:35.111973: +2024-11-22 10:07:35.112289: Epoch 4361 +2024-11-22 10:07:35.112401: Current learning rate: 0.00492 +2024-11-22 10:07:52.885090: train_loss -0.7776 +2024-11-22 10:07:52.885334: val_loss -0.7657 +2024-11-22 10:07:52.885417: Pseudo dice [0.8366] +2024-11-22 10:07:52.885499: Epoch time: 17.77 s +2024-11-22 10:07:53.745701: +2024-11-22 10:07:53.745999: Epoch 4362 +2024-11-22 10:07:53.746118: Current learning rate: 0.00492 +2024-11-22 10:08:11.558681: train_loss -0.7804 +2024-11-22 10:08:11.558917: val_loss -0.7626 +2024-11-22 10:08:11.559056: Pseudo dice [0.845] +2024-11-22 10:08:11.559139: Epoch time: 17.81 s +2024-11-22 10:08:12.426490: +2024-11-22 10:08:12.426766: Epoch 4363 +2024-11-22 10:08:12.426918: Current learning rate: 0.00492 +2024-11-22 10:08:31.192788: train_loss -0.779 +2024-11-22 10:08:31.193009: val_loss -0.757 +2024-11-22 10:08:31.193096: Pseudo dice [0.8154] +2024-11-22 10:08:31.193179: Epoch time: 18.77 s +2024-11-22 10:08:32.056357: +2024-11-22 10:08:32.056666: Epoch 4364 +2024-11-22 10:08:32.056777: Current learning rate: 0.00492 +2024-11-22 10:08:50.841202: train_loss -0.7502 +2024-11-22 10:08:50.841432: val_loss -0.7455 +2024-11-22 10:08:50.841818: Pseudo dice [0.841] +2024-11-22 10:08:50.841901: Epoch time: 18.79 s +2024-11-22 10:08:51.733602: +2024-11-22 10:08:51.733862: Epoch 4365 +2024-11-22 10:08:51.733976: Current learning rate: 0.00492 +2024-11-22 10:09:10.282099: train_loss -0.76 +2024-11-22 10:09:10.282321: val_loss -0.7888 +2024-11-22 10:09:10.282394: Pseudo dice [0.8523] +2024-11-22 10:09:10.282467: Epoch time: 18.55 s +2024-11-22 10:09:11.247503: +2024-11-22 10:09:11.247723: Epoch 4366 +2024-11-22 10:09:11.247831: Current learning rate: 0.00492 +2024-11-22 10:09:29.764712: train_loss -0.7705 +2024-11-22 10:09:29.764935: val_loss -0.7659 +2024-11-22 10:09:29.765018: Pseudo dice [0.8471] +2024-11-22 10:09:29.765114: Epoch time: 18.52 s +2024-11-22 10:09:30.625543: +2024-11-22 10:09:30.625777: Epoch 4367 +2024-11-22 10:09:30.625886: Current learning rate: 0.00491 +2024-11-22 10:09:48.649697: train_loss -0.7658 +2024-11-22 10:09:48.649997: val_loss -0.7362 +2024-11-22 10:09:48.650080: Pseudo dice [0.8142] +2024-11-22 10:09:48.650161: Epoch time: 18.02 s +2024-11-22 10:09:49.510542: +2024-11-22 10:09:49.510784: Epoch 4368 +2024-11-22 10:09:49.510892: Current learning rate: 0.00491 +2024-11-22 10:10:08.752110: train_loss -0.7752 +2024-11-22 10:10:08.752327: val_loss -0.761 +2024-11-22 10:10:08.752403: Pseudo dice [0.8547] +2024-11-22 10:10:08.752476: Epoch time: 19.24 s +2024-11-22 10:10:09.607781: +2024-11-22 10:10:09.608021: Epoch 4369 +2024-11-22 10:10:09.608136: Current learning rate: 0.00491 +2024-11-22 10:10:28.532208: train_loss -0.7831 +2024-11-22 10:10:28.532424: val_loss -0.754 +2024-11-22 10:10:28.532501: Pseudo dice [0.8529] +2024-11-22 10:10:28.532606: Epoch time: 18.93 s +2024-11-22 10:10:29.401837: +2024-11-22 10:10:29.402068: Epoch 4370 +2024-11-22 10:10:29.402176: Current learning rate: 0.00491 +2024-11-22 10:10:47.897712: train_loss -0.7849 +2024-11-22 10:10:47.898039: val_loss -0.7654 +2024-11-22 10:10:47.898121: Pseudo dice [0.8282] +2024-11-22 10:10:47.898209: Epoch time: 18.5 s +2024-11-22 10:10:48.763413: +2024-11-22 10:10:48.763627: Epoch 4371 +2024-11-22 10:10:48.763739: Current learning rate: 0.00491 +2024-11-22 10:11:06.624568: train_loss -0.7899 +2024-11-22 10:11:06.624803: val_loss -0.7592 +2024-11-22 10:11:06.624881: Pseudo dice [0.8272] +2024-11-22 10:11:06.624956: Epoch time: 17.86 s +2024-11-22 10:11:07.600703: +2024-11-22 10:11:07.600913: Epoch 4372 +2024-11-22 10:11:07.601032: Current learning rate: 0.00491 +2024-11-22 10:11:26.285814: train_loss -0.7922 +2024-11-22 10:11:26.286054: val_loss -0.7814 +2024-11-22 10:11:26.286131: Pseudo dice [0.8466] +2024-11-22 10:11:26.286204: Epoch time: 18.69 s +2024-11-22 10:11:27.751931: +2024-11-22 10:11:27.752174: Epoch 4373 +2024-11-22 10:11:27.752285: Current learning rate: 0.00491 +2024-11-22 10:11:45.583202: train_loss -0.7811 +2024-11-22 10:11:45.583457: val_loss -0.7738 +2024-11-22 10:11:45.583536: Pseudo dice [0.8347] +2024-11-22 10:11:45.583621: Epoch time: 17.83 s +2024-11-22 10:11:46.479031: +2024-11-22 10:11:46.479255: Epoch 4374 +2024-11-22 10:11:46.479362: Current learning rate: 0.00491 +2024-11-22 10:12:05.827756: train_loss -0.788 +2024-11-22 10:12:05.827973: val_loss -0.7872 +2024-11-22 10:12:05.828056: Pseudo dice [0.857] +2024-11-22 10:12:05.828136: Epoch time: 19.35 s +2024-11-22 10:12:06.691265: +2024-11-22 10:12:06.691495: Epoch 4375 +2024-11-22 10:12:06.691606: Current learning rate: 0.0049 +2024-11-22 10:12:25.274208: train_loss -0.7885 +2024-11-22 10:12:25.274432: val_loss -0.7754 +2024-11-22 10:12:25.274508: Pseudo dice [0.8592] +2024-11-22 10:12:25.274581: Epoch time: 18.58 s +2024-11-22 10:12:26.143040: +2024-11-22 10:12:26.143292: Epoch 4376 +2024-11-22 10:12:26.143403: Current learning rate: 0.0049 +2024-11-22 10:12:45.046973: train_loss -0.7882 +2024-11-22 10:12:45.047240: val_loss -0.7761 +2024-11-22 10:12:45.047318: Pseudo dice [0.8324] +2024-11-22 10:12:45.047407: Epoch time: 18.9 s +2024-11-22 10:12:45.909281: +2024-11-22 10:12:45.909505: Epoch 4377 +2024-11-22 10:12:45.909615: Current learning rate: 0.0049 +2024-11-22 10:13:03.222517: train_loss -0.7922 +2024-11-22 10:13:03.222732: val_loss -0.7739 +2024-11-22 10:13:03.222806: Pseudo dice [0.8245] +2024-11-22 10:13:03.222881: Epoch time: 17.31 s +2024-11-22 10:13:04.308130: +2024-11-22 10:13:04.308351: Epoch 4378 +2024-11-22 10:13:04.308463: Current learning rate: 0.0049 +2024-11-22 10:13:23.075634: train_loss -0.7942 +2024-11-22 10:13:23.075866: val_loss -0.7884 +2024-11-22 10:13:23.075941: Pseudo dice [0.8298] +2024-11-22 10:13:23.076030: Epoch time: 18.77 s +2024-11-22 10:13:23.935912: +2024-11-22 10:13:23.936136: Epoch 4379 +2024-11-22 10:13:23.936241: Current learning rate: 0.0049 +2024-11-22 10:13:42.721625: train_loss -0.7721 +2024-11-22 10:13:42.721844: val_loss -0.7609 +2024-11-22 10:13:42.721919: Pseudo dice [0.8495] +2024-11-22 10:13:42.722001: Epoch time: 18.79 s +2024-11-22 10:13:43.585138: +2024-11-22 10:13:43.585333: Epoch 4380 +2024-11-22 10:13:43.585441: Current learning rate: 0.0049 +2024-11-22 10:14:00.830812: train_loss -0.7917 +2024-11-22 10:14:00.831102: val_loss -0.7923 +2024-11-22 10:14:00.831181: Pseudo dice [0.8584] +2024-11-22 10:14:00.831266: Epoch time: 17.25 s +2024-11-22 10:14:01.701122: +2024-11-22 10:14:01.701345: Epoch 4381 +2024-11-22 10:14:01.701462: Current learning rate: 0.0049 +2024-11-22 10:14:19.485022: train_loss -0.7905 +2024-11-22 10:14:19.485248: val_loss -0.7935 +2024-11-22 10:14:19.485323: Pseudo dice [0.8604] +2024-11-22 10:14:19.485397: Epoch time: 17.78 s +2024-11-22 10:14:20.366681: +2024-11-22 10:14:20.367018: Epoch 4382 +2024-11-22 10:14:20.367130: Current learning rate: 0.0049 +2024-11-22 10:14:38.629933: train_loss -0.7866 +2024-11-22 10:14:38.641186: val_loss -0.7535 +2024-11-22 10:14:38.641278: Pseudo dice [0.8377] +2024-11-22 10:14:38.641356: Epoch time: 18.26 s +2024-11-22 10:14:39.640570: +2024-11-22 10:14:39.640816: Epoch 4383 +2024-11-22 10:14:39.640936: Current learning rate: 0.00489 +2024-11-22 10:15:00.024734: train_loss -0.781 +2024-11-22 10:15:00.024978: val_loss -0.787 +2024-11-22 10:15:00.025148: Pseudo dice [0.8479] +2024-11-22 10:15:00.025237: Epoch time: 20.38 s +2024-11-22 10:15:00.884964: +2024-11-22 10:15:00.885451: Epoch 4384 +2024-11-22 10:15:00.885570: Current learning rate: 0.00489 +2024-11-22 10:15:20.187628: train_loss -0.7855 +2024-11-22 10:15:20.187841: val_loss -0.7721 +2024-11-22 10:15:20.187917: Pseudo dice [0.8452] +2024-11-22 10:15:20.188010: Epoch time: 19.3 s +2024-11-22 10:15:21.432592: +2024-11-22 10:15:21.432824: Epoch 4385 +2024-11-22 10:15:21.432934: Current learning rate: 0.00489 +2024-11-22 10:15:41.001157: train_loss -0.7712 +2024-11-22 10:15:41.001391: val_loss -0.7792 +2024-11-22 10:15:41.001464: Pseudo dice [0.8357] +2024-11-22 10:15:41.001538: Epoch time: 19.57 s +2024-11-22 10:15:41.873697: +2024-11-22 10:15:41.873938: Epoch 4386 +2024-11-22 10:15:41.874063: Current learning rate: 0.00489 +2024-11-22 10:15:59.734687: train_loss -0.7789 +2024-11-22 10:15:59.734906: val_loss -0.7621 +2024-11-22 10:15:59.734981: Pseudo dice [0.8554] +2024-11-22 10:15:59.735067: Epoch time: 17.86 s +2024-11-22 10:16:00.597446: +2024-11-22 10:16:00.597708: Epoch 4387 +2024-11-22 10:16:00.597866: Current learning rate: 0.00489 +2024-11-22 10:16:19.576535: train_loss -0.7858 +2024-11-22 10:16:19.576757: val_loss -0.7768 +2024-11-22 10:16:19.576832: Pseudo dice [0.8564] +2024-11-22 10:16:19.576908: Epoch time: 18.98 s +2024-11-22 10:16:20.444095: +2024-11-22 10:16:20.444316: Epoch 4388 +2024-11-22 10:16:20.444423: Current learning rate: 0.00489 +2024-11-22 10:16:39.826362: train_loss -0.783 +2024-11-22 10:16:39.826569: val_loss -0.7494 +2024-11-22 10:16:39.826642: Pseudo dice [0.8432] +2024-11-22 10:16:39.826715: Epoch time: 19.38 s +2024-11-22 10:16:40.691613: +2024-11-22 10:16:40.691893: Epoch 4389 +2024-11-22 10:16:40.692015: Current learning rate: 0.00489 +2024-11-22 10:16:59.966281: train_loss -0.7791 +2024-11-22 10:16:59.966504: val_loss -0.7491 +2024-11-22 10:16:59.966584: Pseudo dice [0.8479] +2024-11-22 10:16:59.966691: Epoch time: 19.28 s +2024-11-22 10:17:00.929273: +2024-11-22 10:17:00.929498: Epoch 4390 +2024-11-22 10:17:00.929607: Current learning rate: 0.00489 +2024-11-22 10:17:19.463291: train_loss -0.7898 +2024-11-22 10:17:19.463887: val_loss -0.7542 +2024-11-22 10:17:19.463979: Pseudo dice [0.8445] +2024-11-22 10:17:19.464065: Epoch time: 18.53 s +2024-11-22 10:17:20.393261: +2024-11-22 10:17:20.393495: Epoch 4391 +2024-11-22 10:17:20.393608: Current learning rate: 0.00489 +2024-11-22 10:17:38.185265: train_loss -0.7923 +2024-11-22 10:17:38.185509: val_loss -0.7768 +2024-11-22 10:17:38.185586: Pseudo dice [0.8521] +2024-11-22 10:17:38.185665: Epoch time: 17.79 s +2024-11-22 10:17:39.049669: +2024-11-22 10:17:39.049896: Epoch 4392 +2024-11-22 10:17:39.050009: Current learning rate: 0.00488 +2024-11-22 10:17:57.634481: train_loss -0.7882 +2024-11-22 10:17:57.634693: val_loss -0.7659 +2024-11-22 10:17:57.634764: Pseudo dice [0.8411] +2024-11-22 10:17:57.634835: Epoch time: 18.59 s +2024-11-22 10:17:58.522107: +2024-11-22 10:17:58.522327: Epoch 4393 +2024-11-22 10:17:58.522436: Current learning rate: 0.00488 +2024-11-22 10:18:16.177515: train_loss -0.7861 +2024-11-22 10:18:16.177736: val_loss -0.7961 +2024-11-22 10:18:16.177810: Pseudo dice [0.8454] +2024-11-22 10:18:16.177883: Epoch time: 17.66 s +2024-11-22 10:18:17.041793: +2024-11-22 10:18:17.042014: Epoch 4394 +2024-11-22 10:18:17.042123: Current learning rate: 0.00488 +2024-11-22 10:18:35.270072: train_loss -0.7789 +2024-11-22 10:18:35.270310: val_loss -0.7762 +2024-11-22 10:18:35.270386: Pseudo dice [0.847] +2024-11-22 10:18:35.270481: Epoch time: 18.23 s +2024-11-22 10:18:36.133863: +2024-11-22 10:18:36.134088: Epoch 4395 +2024-11-22 10:18:36.134195: Current learning rate: 0.00488 +2024-11-22 10:18:53.563187: train_loss -0.7871 +2024-11-22 10:18:53.563426: val_loss -0.7764 +2024-11-22 10:18:53.563569: Pseudo dice [0.8458] +2024-11-22 10:18:53.563653: Epoch time: 17.43 s +2024-11-22 10:18:54.433553: +2024-11-22 10:18:54.433796: Epoch 4396 +2024-11-22 10:18:54.433908: Current learning rate: 0.00488 +2024-11-22 10:19:14.245901: train_loss -0.7793 +2024-11-22 10:19:14.246113: val_loss -0.7617 +2024-11-22 10:19:14.246189: Pseudo dice [0.8481] +2024-11-22 10:19:14.246264: Epoch time: 19.81 s +2024-11-22 10:19:15.502272: +2024-11-22 10:19:15.502533: Epoch 4397 +2024-11-22 10:19:15.502649: Current learning rate: 0.00488 +2024-11-22 10:19:33.058260: train_loss -0.7892 +2024-11-22 10:19:33.058523: val_loss -0.7757 +2024-11-22 10:19:33.058605: Pseudo dice [0.8483] +2024-11-22 10:19:33.058683: Epoch time: 17.56 s +2024-11-22 10:19:33.928001: +2024-11-22 10:19:33.928233: Epoch 4398 +2024-11-22 10:19:33.928343: Current learning rate: 0.00488 +2024-11-22 10:19:51.577716: train_loss -0.7923 +2024-11-22 10:19:51.577959: val_loss -0.766 +2024-11-22 10:19:51.578042: Pseudo dice [0.8417] +2024-11-22 10:19:51.578121: Epoch time: 17.65 s +2024-11-22 10:19:52.441171: +2024-11-22 10:19:52.441454: Epoch 4399 +2024-11-22 10:19:52.441562: Current learning rate: 0.00488 +2024-11-22 10:20:11.520874: train_loss -0.7905 +2024-11-22 10:20:11.521122: val_loss -0.7856 +2024-11-22 10:20:11.521214: Pseudo dice [0.8461] +2024-11-22 10:20:11.521302: Epoch time: 19.08 s +2024-11-22 10:20:12.765324: +2024-11-22 10:20:12.765542: Epoch 4400 +2024-11-22 10:20:12.765652: Current learning rate: 0.00487 +2024-11-22 10:20:31.452818: train_loss -0.783 +2024-11-22 10:20:31.458253: val_loss -0.7718 +2024-11-22 10:20:31.458382: Pseudo dice [0.854] +2024-11-22 10:20:31.458477: Epoch time: 18.69 s +2024-11-22 10:20:32.357997: +2024-11-22 10:20:32.358252: Epoch 4401 +2024-11-22 10:20:32.358361: Current learning rate: 0.00487 +2024-11-22 10:20:52.050825: train_loss -0.7879 +2024-11-22 10:20:52.051053: val_loss -0.7812 +2024-11-22 10:20:52.051136: Pseudo dice [0.8518] +2024-11-22 10:20:52.051215: Epoch time: 19.69 s +2024-11-22 10:20:53.078294: +2024-11-22 10:20:53.078503: Epoch 4402 +2024-11-22 10:20:53.078611: Current learning rate: 0.00487 +2024-11-22 10:21:11.854302: train_loss -0.7953 +2024-11-22 10:21:11.854544: val_loss -0.7794 +2024-11-22 10:21:11.856856: Pseudo dice [0.8512] +2024-11-22 10:21:11.856953: Epoch time: 18.78 s +2024-11-22 10:21:12.878129: +2024-11-22 10:21:12.878414: Epoch 4403 +2024-11-22 10:21:12.878523: Current learning rate: 0.00487 +2024-11-22 10:21:30.906092: train_loss -0.7797 +2024-11-22 10:21:30.906301: val_loss -0.7593 +2024-11-22 10:21:30.906427: Pseudo dice [0.8511] +2024-11-22 10:21:30.906548: Epoch time: 18.03 s +2024-11-22 10:21:31.762725: +2024-11-22 10:21:31.762946: Epoch 4404 +2024-11-22 10:21:31.763065: Current learning rate: 0.00487 +2024-11-22 10:21:49.861814: train_loss -0.7864 +2024-11-22 10:21:49.862133: val_loss -0.7497 +2024-11-22 10:21:49.862211: Pseudo dice [0.8305] +2024-11-22 10:21:49.862299: Epoch time: 18.1 s +2024-11-22 10:21:50.727974: +2024-11-22 10:21:50.728207: Epoch 4405 +2024-11-22 10:21:50.728317: Current learning rate: 0.00487 +2024-11-22 10:22:09.234139: train_loss -0.7875 +2024-11-22 10:22:09.234408: val_loss -0.7557 +2024-11-22 10:22:09.234482: Pseudo dice [0.8592] +2024-11-22 10:22:09.234557: Epoch time: 18.51 s +2024-11-22 10:22:10.092762: +2024-11-22 10:22:10.093233: Epoch 4406 +2024-11-22 10:22:10.093375: Current learning rate: 0.00487 +2024-11-22 10:22:28.797986: train_loss -0.788 +2024-11-22 10:22:28.798209: val_loss -0.7659 +2024-11-22 10:22:28.798284: Pseudo dice [0.8448] +2024-11-22 10:22:28.798356: Epoch time: 18.71 s +2024-11-22 10:22:29.659257: +2024-11-22 10:22:29.659476: Epoch 4407 +2024-11-22 10:22:29.659587: Current learning rate: 0.00487 +2024-11-22 10:22:46.705877: train_loss -0.796 +2024-11-22 10:22:46.706119: val_loss -0.7687 +2024-11-22 10:22:46.706259: Pseudo dice [0.8449] +2024-11-22 10:22:46.706339: Epoch time: 17.05 s +2024-11-22 10:22:47.573462: +2024-11-22 10:22:47.573690: Epoch 4408 +2024-11-22 10:22:47.573798: Current learning rate: 0.00486 +2024-11-22 10:23:07.157297: train_loss -0.7886 +2024-11-22 10:23:07.157516: val_loss -0.7585 +2024-11-22 10:23:07.157594: Pseudo dice [0.8353] +2024-11-22 10:23:07.157689: Epoch time: 19.58 s +2024-11-22 10:23:08.377563: +2024-11-22 10:23:08.377811: Epoch 4409 +2024-11-22 10:23:08.377920: Current learning rate: 0.00486 +2024-11-22 10:23:28.067763: train_loss -0.7955 +2024-11-22 10:23:28.068008: val_loss -0.7908 +2024-11-22 10:23:28.068082: Pseudo dice [0.8572] +2024-11-22 10:23:28.068155: Epoch time: 19.69 s +2024-11-22 10:23:28.940848: +2024-11-22 10:23:28.941067: Epoch 4410 +2024-11-22 10:23:28.941177: Current learning rate: 0.00486 +2024-11-22 10:23:46.789019: train_loss -0.8005 +2024-11-22 10:23:46.789239: val_loss -0.7979 +2024-11-22 10:23:46.789315: Pseudo dice [0.8654] +2024-11-22 10:23:46.789389: Epoch time: 17.85 s +2024-11-22 10:23:47.651968: +2024-11-22 10:23:47.652237: Epoch 4411 +2024-11-22 10:23:47.652361: Current learning rate: 0.00486 +2024-11-22 10:24:06.141801: train_loss -0.799 +2024-11-22 10:24:06.142038: val_loss -0.7571 +2024-11-22 10:24:06.142118: Pseudo dice [0.8223] +2024-11-22 10:24:06.142197: Epoch time: 18.49 s +2024-11-22 10:24:07.005823: +2024-11-22 10:24:07.006065: Epoch 4412 +2024-11-22 10:24:07.006181: Current learning rate: 0.00486 +2024-11-22 10:24:26.807330: train_loss -0.7885 +2024-11-22 10:24:26.807897: val_loss -0.7758 +2024-11-22 10:24:26.807976: Pseudo dice [0.8589] +2024-11-22 10:24:26.808060: Epoch time: 19.8 s +2024-11-22 10:24:27.676362: +2024-11-22 10:24:27.676590: Epoch 4413 +2024-11-22 10:24:27.676697: Current learning rate: 0.00486 +2024-11-22 10:24:46.042084: train_loss -0.7971 +2024-11-22 10:24:46.042314: val_loss -0.7886 +2024-11-22 10:24:46.042389: Pseudo dice [0.858] +2024-11-22 10:24:46.042464: Epoch time: 18.37 s +2024-11-22 10:24:46.906037: +2024-11-22 10:24:46.906262: Epoch 4414 +2024-11-22 10:24:46.906372: Current learning rate: 0.00486 +2024-11-22 10:25:05.195608: train_loss -0.7895 +2024-11-22 10:25:05.204305: val_loss -0.7498 +2024-11-22 10:25:05.204401: Pseudo dice [0.8308] +2024-11-22 10:25:05.204484: Epoch time: 18.29 s +2024-11-22 10:25:06.080521: +2024-11-22 10:25:06.080747: Epoch 4415 +2024-11-22 10:25:06.080859: Current learning rate: 0.00486 +2024-11-22 10:25:25.474707: train_loss -0.7937 +2024-11-22 10:25:25.475023: val_loss -0.7582 +2024-11-22 10:25:25.475102: Pseudo dice [0.826] +2024-11-22 10:25:25.475185: Epoch time: 19.4 s +2024-11-22 10:25:26.340996: +2024-11-22 10:25:26.341216: Epoch 4416 +2024-11-22 10:25:26.341332: Current learning rate: 0.00485 +2024-11-22 10:25:44.372979: train_loss -0.7933 +2024-11-22 10:25:44.373494: val_loss -0.741 +2024-11-22 10:25:44.373583: Pseudo dice [0.8423] +2024-11-22 10:25:44.373659: Epoch time: 18.03 s +2024-11-22 10:25:45.236722: +2024-11-22 10:25:45.236942: Epoch 4417 +2024-11-22 10:25:45.237059: Current learning rate: 0.00485 +2024-11-22 10:26:03.956430: train_loss -0.7864 +2024-11-22 10:26:03.959251: val_loss -0.7636 +2024-11-22 10:26:03.959393: Pseudo dice [0.8398] +2024-11-22 10:26:03.959472: Epoch time: 18.72 s +2024-11-22 10:26:04.837188: +2024-11-22 10:26:04.837590: Epoch 4418 +2024-11-22 10:26:04.837950: Current learning rate: 0.00485 +2024-11-22 10:26:22.768416: train_loss -0.7842 +2024-11-22 10:26:22.770823: val_loss -0.7571 +2024-11-22 10:26:22.770940: Pseudo dice [0.8541] +2024-11-22 10:26:22.771035: Epoch time: 17.93 s +2024-11-22 10:26:23.633713: +2024-11-22 10:26:23.633908: Epoch 4419 +2024-11-22 10:26:23.634022: Current learning rate: 0.00485 +2024-11-22 10:26:42.532879: train_loss -0.7937 +2024-11-22 10:26:42.533098: val_loss -0.7547 +2024-11-22 10:26:42.533171: Pseudo dice [0.8565] +2024-11-22 10:26:42.533244: Epoch time: 18.9 s +2024-11-22 10:26:43.513266: +2024-11-22 10:26:43.513481: Epoch 4420 +2024-11-22 10:26:43.513592: Current learning rate: 0.00485 +2024-11-22 10:27:03.120148: train_loss -0.7902 +2024-11-22 10:27:03.120370: val_loss -0.7647 +2024-11-22 10:27:03.120472: Pseudo dice [0.8515] +2024-11-22 10:27:03.120552: Epoch time: 19.61 s +2024-11-22 10:27:04.384297: +2024-11-22 10:27:04.384504: Epoch 4421 +2024-11-22 10:27:04.384613: Current learning rate: 0.00485 +2024-11-22 10:27:22.679480: train_loss -0.7952 +2024-11-22 10:27:22.679744: val_loss -0.7575 +2024-11-22 10:27:22.679820: Pseudo dice [0.845] +2024-11-22 10:27:22.679904: Epoch time: 18.3 s +2024-11-22 10:27:23.545931: +2024-11-22 10:27:23.546182: Epoch 4422 +2024-11-22 10:27:23.546298: Current learning rate: 0.00485 +2024-11-22 10:27:41.576658: train_loss -0.7852 +2024-11-22 10:27:41.576948: val_loss -0.7869 +2024-11-22 10:27:41.577034: Pseudo dice [0.8567] +2024-11-22 10:27:41.577111: Epoch time: 18.03 s +2024-11-22 10:27:42.443989: +2024-11-22 10:27:42.444230: Epoch 4423 +2024-11-22 10:27:42.444344: Current learning rate: 0.00485 +2024-11-22 10:27:59.927783: train_loss -0.7916 +2024-11-22 10:27:59.928036: val_loss -0.7704 +2024-11-22 10:27:59.928114: Pseudo dice [0.8479] +2024-11-22 10:27:59.928191: Epoch time: 17.48 s +2024-11-22 10:28:00.790112: +2024-11-22 10:28:00.790358: Epoch 4424 +2024-11-22 10:28:00.790470: Current learning rate: 0.00484 +2024-11-22 10:28:18.169134: train_loss -0.7994 +2024-11-22 10:28:18.169406: val_loss -0.7414 +2024-11-22 10:28:18.169486: Pseudo dice [0.8441] +2024-11-22 10:28:18.169631: Epoch time: 17.38 s +2024-11-22 10:28:19.041366: +2024-11-22 10:28:19.041605: Epoch 4425 +2024-11-22 10:28:19.041725: Current learning rate: 0.00484 +2024-11-22 10:28:36.867432: train_loss -0.7921 +2024-11-22 10:28:36.867641: val_loss -0.7662 +2024-11-22 10:28:36.872400: Pseudo dice [0.847] +2024-11-22 10:28:36.872497: Epoch time: 17.83 s +2024-11-22 10:28:37.744358: +2024-11-22 10:28:37.744577: Epoch 4426 +2024-11-22 10:28:37.744686: Current learning rate: 0.00484 +2024-11-22 10:28:56.727068: train_loss -0.7981 +2024-11-22 10:28:56.728452: val_loss -0.761 +2024-11-22 10:28:56.728556: Pseudo dice [0.8439] +2024-11-22 10:28:56.728637: Epoch time: 18.98 s +2024-11-22 10:28:57.592218: +2024-11-22 10:28:57.592440: Epoch 4427 +2024-11-22 10:28:57.592554: Current learning rate: 0.00484 +2024-11-22 10:29:16.840071: train_loss -0.7966 +2024-11-22 10:29:16.840285: val_loss -0.7619 +2024-11-22 10:29:16.840357: Pseudo dice [0.8489] +2024-11-22 10:29:16.840441: Epoch time: 19.25 s +2024-11-22 10:29:17.704864: +2024-11-22 10:29:17.705086: Epoch 4428 +2024-11-22 10:29:17.705200: Current learning rate: 0.00484 +2024-11-22 10:29:36.443537: train_loss -0.7828 +2024-11-22 10:29:36.443786: val_loss -0.7628 +2024-11-22 10:29:36.443870: Pseudo dice [0.837] +2024-11-22 10:29:36.443951: Epoch time: 18.74 s +2024-11-22 10:29:37.300904: +2024-11-22 10:29:37.301170: Epoch 4429 +2024-11-22 10:29:37.301276: Current learning rate: 0.00484 +2024-11-22 10:29:56.225787: train_loss -0.7899 +2024-11-22 10:29:56.226003: val_loss -0.7762 +2024-11-22 10:29:56.226081: Pseudo dice [0.865] +2024-11-22 10:29:56.226157: Epoch time: 18.93 s +2024-11-22 10:29:57.080781: +2024-11-22 10:29:57.081021: Epoch 4430 +2024-11-22 10:29:57.081131: Current learning rate: 0.00484 +2024-11-22 10:30:16.322676: train_loss -0.7909 +2024-11-22 10:30:16.322876: val_loss -0.7738 +2024-11-22 10:30:16.322948: Pseudo dice [0.8434] +2024-11-22 10:30:16.323026: Epoch time: 19.24 s +2024-11-22 10:30:17.245906: +2024-11-22 10:30:17.246120: Epoch 4431 +2024-11-22 10:30:17.246228: Current learning rate: 0.00484 +2024-11-22 10:30:36.603815: train_loss -0.7847 +2024-11-22 10:30:36.604040: val_loss -0.7572 +2024-11-22 10:30:36.604116: Pseudo dice [0.8446] +2024-11-22 10:30:36.604219: Epoch time: 19.36 s +2024-11-22 10:30:37.461118: +2024-11-22 10:30:37.461330: Epoch 4432 +2024-11-22 10:30:37.461439: Current learning rate: 0.00484 +2024-11-22 10:30:57.482927: train_loss -0.7884 +2024-11-22 10:30:57.483181: val_loss -0.7673 +2024-11-22 10:30:57.483258: Pseudo dice [0.8544] +2024-11-22 10:30:57.483338: Epoch time: 20.02 s +2024-11-22 10:30:58.762933: +2024-11-22 10:30:58.763169: Epoch 4433 +2024-11-22 10:30:58.763279: Current learning rate: 0.00483 +2024-11-22 10:31:18.416142: train_loss -0.7946 +2024-11-22 10:31:18.416615: val_loss -0.75 +2024-11-22 10:31:18.416710: Pseudo dice [0.8501] +2024-11-22 10:31:18.416788: Epoch time: 19.65 s +2024-11-22 10:31:19.280783: +2024-11-22 10:31:19.281020: Epoch 4434 +2024-11-22 10:31:19.281135: Current learning rate: 0.00483 +2024-11-22 10:31:38.346340: train_loss -0.7912 +2024-11-22 10:31:38.346578: val_loss -0.7883 +2024-11-22 10:31:38.346657: Pseudo dice [0.8725] +2024-11-22 10:31:38.346730: Epoch time: 19.07 s +2024-11-22 10:31:39.247545: +2024-11-22 10:31:39.247779: Epoch 4435 +2024-11-22 10:31:39.247892: Current learning rate: 0.00483 +2024-11-22 10:31:57.637254: train_loss -0.797 +2024-11-22 10:31:57.637483: val_loss -0.7774 +2024-11-22 10:31:57.637567: Pseudo dice [0.8485] +2024-11-22 10:31:57.637655: Epoch time: 18.39 s +2024-11-22 10:31:58.543564: +2024-11-22 10:31:58.543786: Epoch 4436 +2024-11-22 10:31:58.543902: Current learning rate: 0.00483 +2024-11-22 10:32:16.644227: train_loss -0.7951 +2024-11-22 10:32:16.644462: val_loss -0.7833 +2024-11-22 10:32:16.644540: Pseudo dice [0.8571] +2024-11-22 10:32:16.644618: Epoch time: 18.1 s +2024-11-22 10:32:16.644682: Yayy! New best EMA pseudo Dice: 0.851 +2024-11-22 10:32:17.783341: +2024-11-22 10:32:17.783568: Epoch 4437 +2024-11-22 10:32:17.783674: Current learning rate: 0.00483 +2024-11-22 10:32:34.887703: train_loss -0.8013 +2024-11-22 10:32:34.887928: val_loss -0.7745 +2024-11-22 10:32:34.888010: Pseudo dice [0.8591] +2024-11-22 10:32:34.888088: Epoch time: 17.11 s +2024-11-22 10:32:34.888151: Yayy! New best EMA pseudo Dice: 0.8518 +2024-11-22 10:32:36.012934: +2024-11-22 10:32:36.013169: Epoch 4438 +2024-11-22 10:32:36.013282: Current learning rate: 0.00483 +2024-11-22 10:32:54.817519: train_loss -0.7885 +2024-11-22 10:32:54.817749: val_loss -0.7762 +2024-11-22 10:32:54.817819: Pseudo dice [0.8409] +2024-11-22 10:32:54.817893: Epoch time: 18.81 s +2024-11-22 10:32:55.682188: +2024-11-22 10:32:55.682422: Epoch 4439 +2024-11-22 10:32:55.682533: Current learning rate: 0.00483 +2024-11-22 10:33:14.508752: train_loss -0.7877 +2024-11-22 10:33:14.508999: val_loss -0.7719 +2024-11-22 10:33:14.509083: Pseudo dice [0.8512] +2024-11-22 10:33:14.509174: Epoch time: 18.83 s +2024-11-22 10:33:15.377712: +2024-11-22 10:33:15.377911: Epoch 4440 +2024-11-22 10:33:15.378024: Current learning rate: 0.00483 +2024-11-22 10:33:33.356755: train_loss -0.7909 +2024-11-22 10:33:33.356982: val_loss -0.7767 +2024-11-22 10:33:33.357065: Pseudo dice [0.8576] +2024-11-22 10:33:33.357141: Epoch time: 17.98 s +2024-11-22 10:33:34.217084: +2024-11-22 10:33:34.217323: Epoch 4441 +2024-11-22 10:33:34.217436: Current learning rate: 0.00482 +2024-11-22 10:33:52.737515: train_loss -0.7807 +2024-11-22 10:33:52.737734: val_loss -0.746 +2024-11-22 10:33:52.737809: Pseudo dice [0.8477] +2024-11-22 10:33:52.737885: Epoch time: 18.52 s +2024-11-22 10:33:53.702269: +2024-11-22 10:33:53.702911: Epoch 4442 +2024-11-22 10:33:53.703068: Current learning rate: 0.00482 +2024-11-22 10:34:11.994800: train_loss -0.7863 +2024-11-22 10:34:11.995118: val_loss -0.777 +2024-11-22 10:34:11.995196: Pseudo dice [0.8534] +2024-11-22 10:34:11.995284: Epoch time: 18.29 s +2024-11-22 10:34:12.865924: +2024-11-22 10:34:12.866146: Epoch 4443 +2024-11-22 10:34:12.884299: Current learning rate: 0.00482 +2024-11-22 10:34:31.334215: train_loss -0.7884 +2024-11-22 10:34:31.334456: val_loss -0.7534 +2024-11-22 10:34:31.334535: Pseudo dice [0.8375] +2024-11-22 10:34:31.334615: Epoch time: 18.47 s +2024-11-22 10:34:32.192163: +2024-11-22 10:34:32.192361: Epoch 4444 +2024-11-22 10:34:32.192472: Current learning rate: 0.00482 +2024-11-22 10:34:50.917295: train_loss -0.7888 +2024-11-22 10:34:50.917528: val_loss -0.7518 +2024-11-22 10:34:50.917604: Pseudo dice [0.8301] +2024-11-22 10:34:50.917680: Epoch time: 18.73 s +2024-11-22 10:34:51.777329: +2024-11-22 10:34:51.777570: Epoch 4445 +2024-11-22 10:34:51.777684: Current learning rate: 0.00482 +2024-11-22 10:35:10.749384: train_loss -0.7779 +2024-11-22 10:35:10.749607: val_loss -0.7594 +2024-11-22 10:35:10.749686: Pseudo dice [0.8375] +2024-11-22 10:35:10.749771: Epoch time: 18.97 s +2024-11-22 10:35:11.716608: +2024-11-22 10:35:11.716858: Epoch 4446 +2024-11-22 10:35:11.716969: Current learning rate: 0.00482 +2024-11-22 10:35:30.430416: train_loss -0.7853 +2024-11-22 10:35:30.430680: val_loss -0.7618 +2024-11-22 10:35:30.430759: Pseudo dice [0.8469] +2024-11-22 10:35:30.430840: Epoch time: 18.71 s +2024-11-22 10:35:31.480745: +2024-11-22 10:35:31.480975: Epoch 4447 +2024-11-22 10:35:31.481088: Current learning rate: 0.00482 +2024-11-22 10:35:49.641507: train_loss -0.7925 +2024-11-22 10:35:49.641717: val_loss -0.7631 +2024-11-22 10:35:49.641789: Pseudo dice [0.843] +2024-11-22 10:35:49.641862: Epoch time: 18.16 s +2024-11-22 10:35:50.512064: +2024-11-22 10:35:50.512353: Epoch 4448 +2024-11-22 10:35:50.512462: Current learning rate: 0.00482 +2024-11-22 10:36:08.038382: train_loss -0.787 +2024-11-22 10:36:08.038603: val_loss -0.7553 +2024-11-22 10:36:08.038677: Pseudo dice [0.8432] +2024-11-22 10:36:08.038753: Epoch time: 17.53 s +2024-11-22 10:36:08.904349: +2024-11-22 10:36:08.904539: Epoch 4449 +2024-11-22 10:36:08.904646: Current learning rate: 0.00481 +2024-11-22 10:36:27.106466: train_loss -0.7766 +2024-11-22 10:36:27.106681: val_loss -0.772 +2024-11-22 10:36:27.111923: Pseudo dice [0.8362] +2024-11-22 10:36:27.112072: Epoch time: 18.2 s +2024-11-22 10:36:28.284520: +2024-11-22 10:36:28.284761: Epoch 4450 +2024-11-22 10:36:28.284870: Current learning rate: 0.00481 +2024-11-22 10:36:47.521735: train_loss -0.7815 +2024-11-22 10:36:47.521989: val_loss -0.7714 +2024-11-22 10:36:47.522077: Pseudo dice [0.8368] +2024-11-22 10:36:47.522160: Epoch time: 19.24 s +2024-11-22 10:36:48.383701: +2024-11-22 10:36:48.384086: Epoch 4451 +2024-11-22 10:36:48.384201: Current learning rate: 0.00481 +2024-11-22 10:37:07.223881: train_loss -0.7935 +2024-11-22 10:37:07.224174: val_loss -0.7651 +2024-11-22 10:37:07.224254: Pseudo dice [0.8477] +2024-11-22 10:37:07.224332: Epoch time: 18.84 s +2024-11-22 10:37:08.107347: +2024-11-22 10:37:08.107555: Epoch 4452 +2024-11-22 10:37:08.107667: Current learning rate: 0.00481 +2024-11-22 10:37:26.082028: train_loss -0.7873 +2024-11-22 10:37:26.082247: val_loss -0.7786 +2024-11-22 10:37:26.082324: Pseudo dice [0.8532] +2024-11-22 10:37:26.082403: Epoch time: 17.98 s +2024-11-22 10:37:27.039131: +2024-11-22 10:37:27.039335: Epoch 4453 +2024-11-22 10:37:27.039444: Current learning rate: 0.00481 +2024-11-22 10:37:46.511883: train_loss -0.7896 +2024-11-22 10:37:46.512108: val_loss -0.7887 +2024-11-22 10:37:46.512187: Pseudo dice [0.8524] +2024-11-22 10:37:46.512272: Epoch time: 19.47 s +2024-11-22 10:37:47.373405: +2024-11-22 10:37:47.373830: Epoch 4454 +2024-11-22 10:37:47.373955: Current learning rate: 0.00481 +2024-11-22 10:38:05.931055: train_loss -0.8021 +2024-11-22 10:38:05.931313: val_loss -0.772 +2024-11-22 10:38:05.931385: Pseudo dice [0.8466] +2024-11-22 10:38:05.936626: Epoch time: 18.56 s +2024-11-22 10:38:06.947270: +2024-11-22 10:38:06.947469: Epoch 4455 +2024-11-22 10:38:06.947577: Current learning rate: 0.00481 +2024-11-22 10:38:25.904525: train_loss -0.7914 +2024-11-22 10:38:25.904795: val_loss -0.7747 +2024-11-22 10:38:25.904871: Pseudo dice [0.8446] +2024-11-22 10:38:25.904946: Epoch time: 18.96 s +2024-11-22 10:38:27.178813: +2024-11-22 10:38:27.179019: Epoch 4456 +2024-11-22 10:38:27.179124: Current learning rate: 0.00481 +2024-11-22 10:38:45.588391: train_loss -0.7844 +2024-11-22 10:38:45.588646: val_loss -0.7744 +2024-11-22 10:38:45.588723: Pseudo dice [0.8418] +2024-11-22 10:38:45.588807: Epoch time: 18.41 s +2024-11-22 10:38:46.443999: +2024-11-22 10:38:46.444212: Epoch 4457 +2024-11-22 10:38:46.444319: Current learning rate: 0.0048 +2024-11-22 10:39:04.001237: train_loss -0.7855 +2024-11-22 10:39:04.001459: val_loss -0.7676 +2024-11-22 10:39:04.001542: Pseudo dice [0.8349] +2024-11-22 10:39:04.001620: Epoch time: 17.56 s +2024-11-22 10:39:04.864385: +2024-11-22 10:39:04.864618: Epoch 4458 +2024-11-22 10:39:04.864729: Current learning rate: 0.0048 +2024-11-22 10:39:22.393459: train_loss -0.7821 +2024-11-22 10:39:22.393696: val_loss -0.7274 +2024-11-22 10:39:22.393775: Pseudo dice [0.8397] +2024-11-22 10:39:22.393849: Epoch time: 17.53 s +2024-11-22 10:39:23.252020: +2024-11-22 10:39:23.252245: Epoch 4459 +2024-11-22 10:39:23.252353: Current learning rate: 0.0048 +2024-11-22 10:39:40.889035: train_loss -0.7738 +2024-11-22 10:39:40.889264: val_loss -0.7598 +2024-11-22 10:39:40.889343: Pseudo dice [0.8415] +2024-11-22 10:39:40.889416: Epoch time: 17.64 s +2024-11-22 10:39:41.760661: +2024-11-22 10:39:41.760948: Epoch 4460 +2024-11-22 10:39:41.761069: Current learning rate: 0.0048 +2024-11-22 10:39:59.524979: train_loss -0.7824 +2024-11-22 10:39:59.525262: val_loss -0.7527 +2024-11-22 10:39:59.525342: Pseudo dice [0.8495] +2024-11-22 10:39:59.525423: Epoch time: 17.77 s +2024-11-22 10:40:00.394251: +2024-11-22 10:40:00.394465: Epoch 4461 +2024-11-22 10:40:00.394579: Current learning rate: 0.0048 +2024-11-22 10:40:19.142757: train_loss -0.7722 +2024-11-22 10:40:19.148303: val_loss -0.7912 +2024-11-22 10:40:19.148427: Pseudo dice [0.85] +2024-11-22 10:40:19.148517: Epoch time: 18.75 s +2024-11-22 10:40:20.118285: +2024-11-22 10:40:20.118508: Epoch 4462 +2024-11-22 10:40:20.118613: Current learning rate: 0.0048 +2024-11-22 10:40:37.520126: train_loss -0.7724 +2024-11-22 10:40:37.520346: val_loss -0.7785 +2024-11-22 10:40:37.520419: Pseudo dice [0.8455] +2024-11-22 10:40:37.520491: Epoch time: 17.4 s +2024-11-22 10:40:38.408355: +2024-11-22 10:40:38.408549: Epoch 4463 +2024-11-22 10:40:38.408655: Current learning rate: 0.0048 +2024-11-22 10:40:56.996286: train_loss -0.7708 +2024-11-22 10:40:56.997718: val_loss -0.7589 +2024-11-22 10:40:56.997800: Pseudo dice [0.8333] +2024-11-22 10:40:56.997883: Epoch time: 18.59 s +2024-11-22 10:40:57.857432: +2024-11-22 10:40:57.857656: Epoch 4464 +2024-11-22 10:40:57.857765: Current learning rate: 0.0048 +2024-11-22 10:41:16.696135: train_loss -0.7813 +2024-11-22 10:41:16.696351: val_loss -0.7665 +2024-11-22 10:41:16.696425: Pseudo dice [0.8369] +2024-11-22 10:41:16.696500: Epoch time: 18.84 s +2024-11-22 10:41:17.592997: +2024-11-22 10:41:17.593232: Epoch 4465 +2024-11-22 10:41:17.593348: Current learning rate: 0.00479 +2024-11-22 10:41:35.954448: train_loss -0.7884 +2024-11-22 10:41:35.954682: val_loss -0.7629 +2024-11-22 10:41:35.954758: Pseudo dice [0.8432] +2024-11-22 10:41:35.954833: Epoch time: 18.36 s +2024-11-22 10:41:36.814290: +2024-11-22 10:41:36.814529: Epoch 4466 +2024-11-22 10:41:36.814641: Current learning rate: 0.00479 +2024-11-22 10:41:56.136119: train_loss -0.7833 +2024-11-22 10:41:56.136357: val_loss -0.7617 +2024-11-22 10:41:56.136430: Pseudo dice [0.8369] +2024-11-22 10:41:56.136503: Epoch time: 19.32 s +2024-11-22 10:41:57.002085: +2024-11-22 10:41:57.002295: Epoch 4467 +2024-11-22 10:41:57.002403: Current learning rate: 0.00479 +2024-11-22 10:42:15.022315: train_loss -0.787 +2024-11-22 10:42:15.022547: val_loss -0.7708 +2024-11-22 10:42:15.022621: Pseudo dice [0.8224] +2024-11-22 10:42:15.022716: Epoch time: 18.02 s +2024-11-22 10:42:16.237226: +2024-11-22 10:42:16.237435: Epoch 4468 +2024-11-22 10:42:16.237543: Current learning rate: 0.00479 +2024-11-22 10:42:35.660956: train_loss -0.7731 +2024-11-22 10:42:35.661188: val_loss -0.7453 +2024-11-22 10:42:35.661264: Pseudo dice [0.8395] +2024-11-22 10:42:35.661338: Epoch time: 19.42 s +2024-11-22 10:42:36.519980: +2024-11-22 10:42:36.520243: Epoch 4469 +2024-11-22 10:42:36.520357: Current learning rate: 0.00479 +2024-11-22 10:42:54.057456: train_loss -0.7806 +2024-11-22 10:42:54.057665: val_loss -0.7835 +2024-11-22 10:42:54.057738: Pseudo dice [0.8545] +2024-11-22 10:42:54.057811: Epoch time: 17.54 s +2024-11-22 10:42:54.920501: +2024-11-22 10:42:54.920720: Epoch 4470 +2024-11-22 10:42:54.920827: Current learning rate: 0.00479 +2024-11-22 10:43:13.115237: train_loss -0.7899 +2024-11-22 10:43:13.115488: val_loss -0.774 +2024-11-22 10:43:13.115563: Pseudo dice [0.8486] +2024-11-22 10:43:13.115645: Epoch time: 18.2 s +2024-11-22 10:43:13.979615: +2024-11-22 10:43:13.979859: Epoch 4471 +2024-11-22 10:43:13.979982: Current learning rate: 0.00479 +2024-11-22 10:43:32.136669: train_loss -0.7921 +2024-11-22 10:43:32.136886: val_loss -0.7749 +2024-11-22 10:43:32.136960: Pseudo dice [0.8489] +2024-11-22 10:43:32.137044: Epoch time: 18.16 s +2024-11-22 10:43:32.997088: +2024-11-22 10:43:32.997298: Epoch 4472 +2024-11-22 10:43:32.997409: Current learning rate: 0.00479 +2024-11-22 10:43:51.706051: train_loss -0.7911 +2024-11-22 10:43:51.706254: val_loss -0.759 +2024-11-22 10:43:51.706327: Pseudo dice [0.8472] +2024-11-22 10:43:51.706399: Epoch time: 18.71 s +2024-11-22 10:43:52.568596: +2024-11-22 10:43:52.568798: Epoch 4473 +2024-11-22 10:43:52.568907: Current learning rate: 0.00479 +2024-11-22 10:44:10.751564: train_loss -0.7929 +2024-11-22 10:44:10.751791: val_loss -0.7596 +2024-11-22 10:44:10.751865: Pseudo dice [0.8511] +2024-11-22 10:44:10.751953: Epoch time: 18.18 s +2024-11-22 10:44:11.646865: +2024-11-22 10:44:11.647119: Epoch 4474 +2024-11-22 10:44:11.647232: Current learning rate: 0.00478 +2024-11-22 10:44:29.675593: train_loss -0.7863 +2024-11-22 10:44:29.675836: val_loss -0.7888 +2024-11-22 10:44:29.675915: Pseudo dice [0.8587] +2024-11-22 10:44:29.676007: Epoch time: 18.03 s +2024-11-22 10:44:30.542558: +2024-11-22 10:44:30.542755: Epoch 4475 +2024-11-22 10:44:30.542863: Current learning rate: 0.00478 +2024-11-22 10:44:49.110726: train_loss -0.7881 +2024-11-22 10:44:49.110940: val_loss -0.7703 +2024-11-22 10:44:49.111025: Pseudo dice [0.8441] +2024-11-22 10:44:49.111104: Epoch time: 18.57 s +2024-11-22 10:44:49.971239: +2024-11-22 10:44:49.971456: Epoch 4476 +2024-11-22 10:44:49.971565: Current learning rate: 0.00478 +2024-11-22 10:45:08.985446: train_loss -0.7861 +2024-11-22 10:45:08.985667: val_loss -0.7804 +2024-11-22 10:45:08.985743: Pseudo dice [0.8609] +2024-11-22 10:45:08.985817: Epoch time: 19.02 s +2024-11-22 10:45:09.857855: +2024-11-22 10:45:09.858063: Epoch 4477 +2024-11-22 10:45:09.858169: Current learning rate: 0.00478 +2024-11-22 10:45:28.793666: train_loss -0.7915 +2024-11-22 10:45:28.793897: val_loss -0.7601 +2024-11-22 10:45:28.793985: Pseudo dice [0.8421] +2024-11-22 10:45:28.794073: Epoch time: 18.94 s +2024-11-22 10:45:29.664644: +2024-11-22 10:45:29.664856: Epoch 4478 +2024-11-22 10:45:29.664966: Current learning rate: 0.00478 +2024-11-22 10:45:48.136108: train_loss -0.7857 +2024-11-22 10:45:48.138698: val_loss -0.7848 +2024-11-22 10:45:48.138870: Pseudo dice [0.8435] +2024-11-22 10:45:48.138951: Epoch time: 18.47 s +2024-11-22 10:45:49.014544: +2024-11-22 10:45:49.014755: Epoch 4479 +2024-11-22 10:45:49.014865: Current learning rate: 0.00478 +2024-11-22 10:46:07.289047: train_loss -0.7884 +2024-11-22 10:46:07.289267: val_loss -0.7592 +2024-11-22 10:46:07.289366: Pseudo dice [0.8324] +2024-11-22 10:46:07.289444: Epoch time: 18.28 s +2024-11-22 10:46:08.563346: +2024-11-22 10:46:08.563580: Epoch 4480 +2024-11-22 10:46:08.563688: Current learning rate: 0.00478 +2024-11-22 10:46:27.148385: train_loss -0.7974 +2024-11-22 10:46:27.148608: val_loss -0.7823 +2024-11-22 10:46:27.148680: Pseudo dice [0.8246] +2024-11-22 10:46:27.148754: Epoch time: 18.59 s +2024-11-22 10:46:28.021386: +2024-11-22 10:46:28.021630: Epoch 4481 +2024-11-22 10:46:28.021747: Current learning rate: 0.00478 +2024-11-22 10:46:45.690207: train_loss -0.7999 +2024-11-22 10:46:45.690514: val_loss -0.7762 +2024-11-22 10:46:45.690593: Pseudo dice [0.8516] +2024-11-22 10:46:45.690672: Epoch time: 17.67 s +2024-11-22 10:46:46.586394: +2024-11-22 10:46:46.586616: Epoch 4482 +2024-11-22 10:46:46.586723: Current learning rate: 0.00477 +2024-11-22 10:47:05.517272: train_loss -0.7831 +2024-11-22 10:47:05.517483: val_loss -0.7604 +2024-11-22 10:47:05.517556: Pseudo dice [0.8496] +2024-11-22 10:47:05.517628: Epoch time: 18.93 s +2024-11-22 10:47:06.381576: +2024-11-22 10:47:06.381894: Epoch 4483 +2024-11-22 10:47:06.382011: Current learning rate: 0.00477 +2024-11-22 10:47:24.551145: train_loss -0.7883 +2024-11-22 10:47:24.551362: val_loss -0.7779 +2024-11-22 10:47:24.551437: Pseudo dice [0.8358] +2024-11-22 10:47:24.551514: Epoch time: 18.17 s +2024-11-22 10:47:25.413677: +2024-11-22 10:47:25.413902: Epoch 4484 +2024-11-22 10:47:25.414013: Current learning rate: 0.00477 +2024-11-22 10:47:43.877169: train_loss -0.7904 +2024-11-22 10:47:43.877388: val_loss -0.7704 +2024-11-22 10:47:43.877464: Pseudo dice [0.8572] +2024-11-22 10:47:43.877537: Epoch time: 18.46 s +2024-11-22 10:47:44.746006: +2024-11-22 10:47:44.746235: Epoch 4485 +2024-11-22 10:47:44.746348: Current learning rate: 0.00477 +2024-11-22 10:48:03.215731: train_loss -0.7792 +2024-11-22 10:48:03.216024: val_loss -0.7647 +2024-11-22 10:48:03.216123: Pseudo dice [0.8364] +2024-11-22 10:48:03.216210: Epoch time: 18.47 s +2024-11-22 10:48:04.083415: +2024-11-22 10:48:04.083668: Epoch 4486 +2024-11-22 10:48:04.083786: Current learning rate: 0.00477 +2024-11-22 10:48:22.047368: train_loss -0.76 +2024-11-22 10:48:22.047589: val_loss -0.7748 +2024-11-22 10:48:22.049902: Pseudo dice [0.8287] +2024-11-22 10:48:22.050008: Epoch time: 17.96 s +2024-11-22 10:48:22.935674: +2024-11-22 10:48:22.935895: Epoch 4487 +2024-11-22 10:48:22.936014: Current learning rate: 0.00477 +2024-11-22 10:48:41.872679: train_loss -0.7654 +2024-11-22 10:48:41.872900: val_loss -0.7388 +2024-11-22 10:48:41.873010: Pseudo dice [0.8204] +2024-11-22 10:48:41.873092: Epoch time: 18.94 s +2024-11-22 10:48:42.740011: +2024-11-22 10:48:42.740220: Epoch 4488 +2024-11-22 10:48:42.740326: Current learning rate: 0.00477 +2024-11-22 10:49:00.067651: train_loss -0.7846 +2024-11-22 10:49:00.067901: val_loss -0.7493 +2024-11-22 10:49:00.067978: Pseudo dice [0.8398] +2024-11-22 10:49:00.068130: Epoch time: 17.33 s +2024-11-22 10:49:00.932122: +2024-11-22 10:49:00.932341: Epoch 4489 +2024-11-22 10:49:00.932451: Current learning rate: 0.00477 +2024-11-22 10:49:19.109159: train_loss -0.781 +2024-11-22 10:49:19.109374: val_loss -0.7486 +2024-11-22 10:49:19.109446: Pseudo dice [0.8346] +2024-11-22 10:49:19.109517: Epoch time: 18.18 s +2024-11-22 10:49:19.968121: +2024-11-22 10:49:19.968323: Epoch 4490 +2024-11-22 10:49:19.968432: Current learning rate: 0.00476 +2024-11-22 10:49:38.254855: train_loss -0.7799 +2024-11-22 10:49:38.255117: val_loss -0.7696 +2024-11-22 10:49:38.255191: Pseudo dice [0.8538] +2024-11-22 10:49:38.255265: Epoch time: 18.29 s +2024-11-22 10:49:39.143429: +2024-11-22 10:49:39.143655: Epoch 4491 +2024-11-22 10:49:39.143772: Current learning rate: 0.00476 +2024-11-22 10:49:58.229187: train_loss -0.7792 +2024-11-22 10:49:58.229480: val_loss -0.7614 +2024-11-22 10:49:58.229563: Pseudo dice [0.8507] +2024-11-22 10:49:58.229643: Epoch time: 19.09 s +2024-11-22 10:49:59.470246: +2024-11-22 10:49:59.470701: Epoch 4492 +2024-11-22 10:49:59.470832: Current learning rate: 0.00476 +2024-11-22 10:50:18.025314: train_loss -0.7895 +2024-11-22 10:50:18.025614: val_loss -0.7661 +2024-11-22 10:50:18.025693: Pseudo dice [0.8293] +2024-11-22 10:50:18.025771: Epoch time: 18.56 s +2024-11-22 10:50:18.884403: +2024-11-22 10:50:18.884834: Epoch 4493 +2024-11-22 10:50:18.884962: Current learning rate: 0.00476 +2024-11-22 10:50:37.905240: train_loss -0.7896 +2024-11-22 10:50:37.907599: val_loss -0.7719 +2024-11-22 10:50:37.907719: Pseudo dice [0.8323] +2024-11-22 10:50:37.907797: Epoch time: 19.02 s +2024-11-22 10:50:38.963685: +2024-11-22 10:50:38.964109: Epoch 4494 +2024-11-22 10:50:38.964236: Current learning rate: 0.00476 +2024-11-22 10:50:57.869718: train_loss -0.7913 +2024-11-22 10:50:57.869928: val_loss -0.7513 +2024-11-22 10:50:57.870009: Pseudo dice [0.8317] +2024-11-22 10:50:57.870085: Epoch time: 18.91 s +2024-11-22 10:50:58.733816: +2024-11-22 10:50:58.734229: Epoch 4495 +2024-11-22 10:50:58.734363: Current learning rate: 0.00476 +2024-11-22 10:51:17.275916: train_loss -0.7934 +2024-11-22 10:51:17.276174: val_loss -0.763 +2024-11-22 10:51:17.276251: Pseudo dice [0.8492] +2024-11-22 10:51:17.276336: Epoch time: 18.54 s +2024-11-22 10:51:18.161725: +2024-11-22 10:51:18.162166: Epoch 4496 +2024-11-22 10:51:18.162299: Current learning rate: 0.00476 +2024-11-22 10:51:36.168853: train_loss -0.7824 +2024-11-22 10:51:36.169073: val_loss -0.737 +2024-11-22 10:51:36.169151: Pseudo dice [0.8311] +2024-11-22 10:51:36.169225: Epoch time: 18.01 s +2024-11-22 10:51:37.031860: +2024-11-22 10:51:37.032289: Epoch 4497 +2024-11-22 10:51:37.032431: Current learning rate: 0.00476 +2024-11-22 10:51:55.229707: train_loss -0.788 +2024-11-22 10:51:55.229923: val_loss -0.7603 +2024-11-22 10:51:55.230007: Pseudo dice [0.8561] +2024-11-22 10:51:55.230083: Epoch time: 18.2 s +2024-11-22 10:51:56.086294: +2024-11-22 10:51:56.086735: Epoch 4498 +2024-11-22 10:51:56.086891: Current learning rate: 0.00475 +2024-11-22 10:52:15.914488: train_loss -0.7882 +2024-11-22 10:52:15.914788: val_loss -0.7661 +2024-11-22 10:52:15.914867: Pseudo dice [0.8318] +2024-11-22 10:52:15.914944: Epoch time: 19.83 s +2024-11-22 10:52:16.802758: +2024-11-22 10:52:16.803192: Epoch 4499 +2024-11-22 10:52:16.803333: Current learning rate: 0.00475 +2024-11-22 10:52:35.748054: train_loss -0.785 +2024-11-22 10:52:35.750466: val_loss -0.7554 +2024-11-22 10:52:35.750563: Pseudo dice [0.8507] +2024-11-22 10:52:35.750642: Epoch time: 18.95 s +2024-11-22 10:52:36.900604: +2024-11-22 10:52:36.901062: Epoch 4500 +2024-11-22 10:52:36.901209: Current learning rate: 0.00475 +2024-11-22 10:52:54.535985: train_loss -0.7898 +2024-11-22 10:52:54.536209: val_loss -0.7697 +2024-11-22 10:52:54.536283: Pseudo dice [0.8454] +2024-11-22 10:52:54.536365: Epoch time: 17.64 s +2024-11-22 10:52:55.506411: +2024-11-22 10:52:55.506826: Epoch 4501 +2024-11-22 10:52:55.506954: Current learning rate: 0.00475 +2024-11-22 10:53:14.322535: train_loss -0.7941 +2024-11-22 10:53:14.322788: val_loss -0.7619 +2024-11-22 10:53:14.322863: Pseudo dice [0.8493] +2024-11-22 10:53:14.322939: Epoch time: 18.82 s +2024-11-22 10:53:15.186708: +2024-11-22 10:53:15.186931: Epoch 4502 +2024-11-22 10:53:15.187049: Current learning rate: 0.00475 +2024-11-22 10:53:32.865227: train_loss -0.7872 +2024-11-22 10:53:32.865472: val_loss -0.7836 +2024-11-22 10:53:32.865551: Pseudo dice [0.8515] +2024-11-22 10:53:32.865635: Epoch time: 17.68 s +2024-11-22 10:53:33.731776: +2024-11-22 10:53:33.732014: Epoch 4503 +2024-11-22 10:53:33.732127: Current learning rate: 0.00475 +2024-11-22 10:53:51.517081: train_loss -0.788 +2024-11-22 10:53:51.517290: val_loss -0.7684 +2024-11-22 10:53:51.517363: Pseudo dice [0.8481] +2024-11-22 10:53:51.517436: Epoch time: 17.79 s +2024-11-22 10:53:52.769322: +2024-11-22 10:53:52.769768: Epoch 4504 +2024-11-22 10:53:52.769901: Current learning rate: 0.00475 +2024-11-22 10:54:10.757877: train_loss -0.7915 +2024-11-22 10:54:10.758118: val_loss -0.77 +2024-11-22 10:54:10.760379: Pseudo dice [0.8356] +2024-11-22 10:54:10.760466: Epoch time: 17.99 s +2024-11-22 10:54:11.803033: +2024-11-22 10:54:11.803440: Epoch 4505 +2024-11-22 10:54:11.803567: Current learning rate: 0.00475 +2024-11-22 10:54:29.623681: train_loss -0.7994 +2024-11-22 10:54:29.623935: val_loss -0.7782 +2024-11-22 10:54:29.624025: Pseudo dice [0.8358] +2024-11-22 10:54:29.624112: Epoch time: 17.82 s +2024-11-22 10:54:30.498575: +2024-11-22 10:54:30.499008: Epoch 4506 +2024-11-22 10:54:30.499161: Current learning rate: 0.00474 +2024-11-22 10:54:49.337482: train_loss -0.7876 +2024-11-22 10:54:49.337700: val_loss -0.7531 +2024-11-22 10:54:49.353599: Pseudo dice [0.8447] +2024-11-22 10:54:49.353765: Epoch time: 18.84 s +2024-11-22 10:54:50.273920: +2024-11-22 10:54:50.274357: Epoch 4507 +2024-11-22 10:54:50.274485: Current learning rate: 0.00474 +2024-11-22 10:55:08.426094: train_loss -0.7879 +2024-11-22 10:55:08.426308: val_loss -0.7796 +2024-11-22 10:55:08.428616: Pseudo dice [0.8447] +2024-11-22 10:55:08.428743: Epoch time: 18.15 s +2024-11-22 10:55:09.321227: +2024-11-22 10:55:09.321676: Epoch 4508 +2024-11-22 10:55:09.321808: Current learning rate: 0.00474 +2024-11-22 10:55:27.443079: train_loss -0.7861 +2024-11-22 10:55:27.443298: val_loss -0.7762 +2024-11-22 10:55:27.443374: Pseudo dice [0.8445] +2024-11-22 10:55:27.443448: Epoch time: 18.12 s +2024-11-22 10:55:28.300011: +2024-11-22 10:55:28.300458: Epoch 4509 +2024-11-22 10:55:28.300592: Current learning rate: 0.00474 +2024-11-22 10:55:46.165842: train_loss -0.7825 +2024-11-22 10:55:46.166065: val_loss -0.7852 +2024-11-22 10:55:46.166143: Pseudo dice [0.8462] +2024-11-22 10:55:46.166223: Epoch time: 17.87 s +2024-11-22 10:55:47.035534: +2024-11-22 10:55:47.035982: Epoch 4510 +2024-11-22 10:55:47.036161: Current learning rate: 0.00474 +2024-11-22 10:56:04.856331: train_loss -0.7829 +2024-11-22 10:56:04.856541: val_loss -0.747 +2024-11-22 10:56:04.856614: Pseudo dice [0.83] +2024-11-22 10:56:04.856689: Epoch time: 17.82 s +2024-11-22 10:56:05.892648: +2024-11-22 10:56:05.893116: Epoch 4511 +2024-11-22 10:56:05.893265: Current learning rate: 0.00474 +2024-11-22 10:56:24.272512: train_loss -0.789 +2024-11-22 10:56:24.272780: val_loss -0.7507 +2024-11-22 10:56:24.272856: Pseudo dice [0.8356] +2024-11-22 10:56:24.272931: Epoch time: 18.38 s +2024-11-22 10:56:25.147337: +2024-11-22 10:56:25.147751: Epoch 4512 +2024-11-22 10:56:25.147886: Current learning rate: 0.00474 +2024-11-22 10:56:43.788404: train_loss -0.7763 +2024-11-22 10:56:43.788622: val_loss -0.7534 +2024-11-22 10:56:43.788695: Pseudo dice [0.8269] +2024-11-22 10:56:43.788773: Epoch time: 18.64 s +2024-11-22 10:56:44.706188: +2024-11-22 10:56:44.706409: Epoch 4513 +2024-11-22 10:56:44.706516: Current learning rate: 0.00474 +2024-11-22 10:57:02.502241: train_loss -0.7839 +2024-11-22 10:57:02.502478: val_loss -0.7739 +2024-11-22 10:57:02.502568: Pseudo dice [0.8477] +2024-11-22 10:57:02.502657: Epoch time: 17.8 s +2024-11-22 10:57:03.361073: +2024-11-22 10:57:03.361353: Epoch 4514 +2024-11-22 10:57:03.361463: Current learning rate: 0.00473 +2024-11-22 10:57:21.429402: train_loss -0.7864 +2024-11-22 10:57:21.429689: val_loss -0.7812 +2024-11-22 10:57:21.429765: Pseudo dice [0.8457] +2024-11-22 10:57:21.429843: Epoch time: 18.07 s +2024-11-22 10:57:22.295437: +2024-11-22 10:57:22.295658: Epoch 4515 +2024-11-22 10:57:22.295769: Current learning rate: 0.00473 +2024-11-22 10:57:39.894905: train_loss -0.7948 +2024-11-22 10:57:39.895177: val_loss -0.7412 +2024-11-22 10:57:39.895257: Pseudo dice [0.8343] +2024-11-22 10:57:39.895332: Epoch time: 17.6 s +2024-11-22 10:57:41.185621: +2024-11-22 10:57:41.185849: Epoch 4516 +2024-11-22 10:57:41.185955: Current learning rate: 0.00473 +2024-11-22 10:58:00.845727: train_loss -0.7912 +2024-11-22 10:58:00.846004: val_loss -0.7833 +2024-11-22 10:58:00.846082: Pseudo dice [0.8513] +2024-11-22 10:58:00.846164: Epoch time: 19.66 s +2024-11-22 10:58:01.706204: +2024-11-22 10:58:01.706429: Epoch 4517 +2024-11-22 10:58:01.706537: Current learning rate: 0.00473 +2024-11-22 10:58:21.219219: train_loss -0.7887 +2024-11-22 10:58:21.219442: val_loss -0.7626 +2024-11-22 10:58:21.219516: Pseudo dice [0.845] +2024-11-22 10:58:21.219590: Epoch time: 19.51 s +2024-11-22 10:58:22.237128: +2024-11-22 10:58:22.237389: Epoch 4518 +2024-11-22 10:58:22.237508: Current learning rate: 0.00473 +2024-11-22 10:58:40.750941: train_loss -0.7958 +2024-11-22 10:58:40.751226: val_loss -0.7635 +2024-11-22 10:58:40.751303: Pseudo dice [0.8525] +2024-11-22 10:58:40.751377: Epoch time: 18.51 s +2024-11-22 10:58:41.617440: +2024-11-22 10:58:41.617676: Epoch 4519 +2024-11-22 10:58:41.617791: Current learning rate: 0.00473 +2024-11-22 10:58:59.012720: train_loss -0.7965 +2024-11-22 10:58:59.013042: val_loss -0.7788 +2024-11-22 10:58:59.013120: Pseudo dice [0.8482] +2024-11-22 10:58:59.013513: Epoch time: 17.4 s +2024-11-22 10:58:59.963488: +2024-11-22 10:58:59.963696: Epoch 4520 +2024-11-22 10:58:59.963802: Current learning rate: 0.00473 +2024-11-22 10:59:17.847653: train_loss -0.7876 +2024-11-22 10:59:17.847878: val_loss -0.7648 +2024-11-22 10:59:17.847951: Pseudo dice [0.851] +2024-11-22 10:59:17.848031: Epoch time: 17.88 s +2024-11-22 10:59:18.705534: +2024-11-22 10:59:18.705755: Epoch 4521 +2024-11-22 10:59:18.705864: Current learning rate: 0.00473 +2024-11-22 10:59:37.622914: train_loss -0.7882 +2024-11-22 10:59:37.623140: val_loss -0.7902 +2024-11-22 10:59:37.623219: Pseudo dice [0.8626] +2024-11-22 10:59:37.623296: Epoch time: 18.92 s +2024-11-22 10:59:38.487044: +2024-11-22 10:59:38.487266: Epoch 4522 +2024-11-22 10:59:38.487375: Current learning rate: 0.00473 +2024-11-22 10:59:56.364677: train_loss -0.7914 +2024-11-22 10:59:56.364897: val_loss -0.7624 +2024-11-22 10:59:56.364974: Pseudo dice [0.8276] +2024-11-22 10:59:56.365105: Epoch time: 17.88 s +2024-11-22 10:59:57.240305: +2024-11-22 10:59:57.240593: Epoch 4523 +2024-11-22 10:59:57.240706: Current learning rate: 0.00472 +2024-11-22 11:00:15.074084: train_loss -0.7814 +2024-11-22 11:00:15.074322: val_loss -0.7633 +2024-11-22 11:00:15.074400: Pseudo dice [0.8441] +2024-11-22 11:00:15.074481: Epoch time: 17.83 s +2024-11-22 11:00:15.943089: +2024-11-22 11:00:15.943382: Epoch 4524 +2024-11-22 11:00:15.943495: Current learning rate: 0.00472 +2024-11-22 11:00:33.594947: train_loss -0.7835 +2024-11-22 11:00:33.595168: val_loss -0.7573 +2024-11-22 11:00:33.595243: Pseudo dice [0.835] +2024-11-22 11:00:33.595315: Epoch time: 17.65 s +2024-11-22 11:00:34.453054: +2024-11-22 11:00:34.453262: Epoch 4525 +2024-11-22 11:00:34.453369: Current learning rate: 0.00472 +2024-11-22 11:00:52.481140: train_loss -0.7674 +2024-11-22 11:00:52.481356: val_loss -0.7611 +2024-11-22 11:00:52.481432: Pseudo dice [0.8234] +2024-11-22 11:00:52.481509: Epoch time: 18.03 s +2024-11-22 11:00:53.347451: +2024-11-22 11:00:53.347684: Epoch 4526 +2024-11-22 11:00:53.347795: Current learning rate: 0.00472 +2024-11-22 11:01:11.519995: train_loss -0.7679 +2024-11-22 11:01:11.520252: val_loss -0.7529 +2024-11-22 11:01:11.520329: Pseudo dice [0.8501] +2024-11-22 11:01:11.520422: Epoch time: 18.17 s +2024-11-22 11:01:12.384763: +2024-11-22 11:01:12.384981: Epoch 4527 +2024-11-22 11:01:12.385098: Current learning rate: 0.00472 +2024-11-22 11:01:31.326984: train_loss -0.7722 +2024-11-22 11:01:31.327237: val_loss -0.7533 +2024-11-22 11:01:31.327319: Pseudo dice [0.8227] +2024-11-22 11:01:31.327397: Epoch time: 18.94 s +2024-11-22 11:01:32.584450: +2024-11-22 11:01:32.584722: Epoch 4528 +2024-11-22 11:01:32.584842: Current learning rate: 0.00472 +2024-11-22 11:01:50.368931: train_loss -0.7885 +2024-11-22 11:01:50.369189: val_loss -0.7569 +2024-11-22 11:01:50.369267: Pseudo dice [0.8545] +2024-11-22 11:01:50.369343: Epoch time: 17.79 s +2024-11-22 11:01:51.228670: +2024-11-22 11:01:51.228908: Epoch 4529 +2024-11-22 11:01:51.229027: Current learning rate: 0.00472 +2024-11-22 11:02:10.125176: train_loss -0.7899 +2024-11-22 11:02:10.127513: val_loss -0.7486 +2024-11-22 11:02:10.127647: Pseudo dice [0.8315] +2024-11-22 11:02:10.127739: Epoch time: 18.9 s +2024-11-22 11:02:10.995262: +2024-11-22 11:02:10.995488: Epoch 4530 +2024-11-22 11:02:10.995603: Current learning rate: 0.00472 +2024-11-22 11:02:29.672888: train_loss -0.7883 +2024-11-22 11:02:29.673115: val_loss -0.792 +2024-11-22 11:02:29.673192: Pseudo dice [0.8568] +2024-11-22 11:02:29.673267: Epoch time: 18.68 s +2024-11-22 11:02:30.640743: +2024-11-22 11:02:30.640954: Epoch 4531 +2024-11-22 11:02:30.641071: Current learning rate: 0.00471 +2024-11-22 11:02:48.359263: train_loss -0.7906 +2024-11-22 11:02:48.359481: val_loss -0.7612 +2024-11-22 11:02:48.359581: Pseudo dice [0.8348] +2024-11-22 11:02:48.361850: Epoch time: 17.72 s +2024-11-22 11:02:49.239039: +2024-11-22 11:02:49.256737: Epoch 4532 +2024-11-22 11:02:49.256877: Current learning rate: 0.00471 +2024-11-22 11:03:07.010421: train_loss -0.7893 +2024-11-22 11:03:07.010638: val_loss -0.7905 +2024-11-22 11:03:07.010715: Pseudo dice [0.8463] +2024-11-22 11:03:07.010792: Epoch time: 17.77 s +2024-11-22 11:03:07.977936: +2024-11-22 11:03:07.978188: Epoch 4533 +2024-11-22 11:03:07.978304: Current learning rate: 0.00471 +2024-11-22 11:03:26.560777: train_loss -0.784 +2024-11-22 11:03:26.561003: val_loss -0.7795 +2024-11-22 11:03:26.561091: Pseudo dice [0.8561] +2024-11-22 11:03:26.561172: Epoch time: 18.58 s +2024-11-22 11:03:27.422425: +2024-11-22 11:03:27.422647: Epoch 4534 +2024-11-22 11:03:27.422760: Current learning rate: 0.00471 +2024-11-22 11:03:46.282491: train_loss -0.7962 +2024-11-22 11:03:46.282763: val_loss -0.764 +2024-11-22 11:03:46.282841: Pseudo dice [0.8443] +2024-11-22 11:03:46.282924: Epoch time: 18.86 s +2024-11-22 11:03:47.163875: +2024-11-22 11:03:47.164105: Epoch 4535 +2024-11-22 11:03:47.164228: Current learning rate: 0.00471 +2024-11-22 11:04:04.720209: train_loss -0.7885 +2024-11-22 11:04:04.720425: val_loss -0.7681 +2024-11-22 11:04:04.720499: Pseudo dice [0.8461] +2024-11-22 11:04:04.720573: Epoch time: 17.56 s +2024-11-22 11:04:05.634894: +2024-11-22 11:04:05.635104: Epoch 4536 +2024-11-22 11:04:05.635220: Current learning rate: 0.00471 +2024-11-22 11:04:24.541766: train_loss -0.7971 +2024-11-22 11:04:24.542014: val_loss -0.7902 +2024-11-22 11:04:24.542088: Pseudo dice [0.8529] +2024-11-22 11:04:24.542163: Epoch time: 18.91 s +2024-11-22 11:04:25.430642: +2024-11-22 11:04:25.430861: Epoch 4537 +2024-11-22 11:04:25.430979: Current learning rate: 0.00471 +2024-11-22 11:04:44.482733: train_loss -0.7896 +2024-11-22 11:04:44.482979: val_loss -0.7516 +2024-11-22 11:04:44.483076: Pseudo dice [0.8231] +2024-11-22 11:04:44.483216: Epoch time: 19.05 s +2024-11-22 11:04:45.345883: +2024-11-22 11:04:45.346101: Epoch 4538 +2024-11-22 11:04:45.346210: Current learning rate: 0.00471 +2024-11-22 11:05:04.197817: train_loss -0.7864 +2024-11-22 11:05:04.198050: val_loss -0.7789 +2024-11-22 11:05:04.198130: Pseudo dice [0.8541] +2024-11-22 11:05:04.198205: Epoch time: 18.85 s +2024-11-22 11:05:05.050645: +2024-11-22 11:05:05.050877: Epoch 4539 +2024-11-22 11:05:05.050985: Current learning rate: 0.0047 +2024-11-22 11:05:23.465740: train_loss -0.7848 +2024-11-22 11:05:23.465961: val_loss -0.7836 +2024-11-22 11:05:23.466044: Pseudo dice [0.8499] +2024-11-22 11:05:23.466121: Epoch time: 18.42 s +2024-11-22 11:05:24.755820: +2024-11-22 11:05:24.756047: Epoch 4540 +2024-11-22 11:05:24.756156: Current learning rate: 0.0047 +2024-11-22 11:05:42.442498: train_loss -0.7944 +2024-11-22 11:05:42.442749: val_loss -0.7628 +2024-11-22 11:05:42.442824: Pseudo dice [0.8351] +2024-11-22 11:05:42.442906: Epoch time: 17.69 s +2024-11-22 11:05:43.315725: +2024-11-22 11:05:43.316087: Epoch 4541 +2024-11-22 11:05:43.316198: Current learning rate: 0.0047 +2024-11-22 11:06:01.081996: train_loss -0.7928 +2024-11-22 11:06:01.082210: val_loss -0.784 +2024-11-22 11:06:01.082286: Pseudo dice [0.8572] +2024-11-22 11:06:01.082358: Epoch time: 17.77 s +2024-11-22 11:06:02.098720: +2024-11-22 11:06:02.098925: Epoch 4542 +2024-11-22 11:06:02.099037: Current learning rate: 0.0047 +2024-11-22 11:06:20.550123: train_loss -0.7929 +2024-11-22 11:06:20.550346: val_loss -0.7848 +2024-11-22 11:06:20.550432: Pseudo dice [0.8537] +2024-11-22 11:06:20.550578: Epoch time: 18.45 s +2024-11-22 11:06:21.410735: +2024-11-22 11:06:21.410957: Epoch 4543 +2024-11-22 11:06:21.411075: Current learning rate: 0.0047 +2024-11-22 11:06:39.830785: train_loss -0.7952 +2024-11-22 11:06:39.831008: val_loss -0.7773 +2024-11-22 11:06:39.831107: Pseudo dice [0.8549] +2024-11-22 11:06:39.831189: Epoch time: 18.42 s +2024-11-22 11:06:40.782080: +2024-11-22 11:06:40.782293: Epoch 4544 +2024-11-22 11:06:40.782401: Current learning rate: 0.0047 +2024-11-22 11:06:57.872573: train_loss -0.7855 +2024-11-22 11:06:57.872817: val_loss -0.7547 +2024-11-22 11:06:57.872895: Pseudo dice [0.8555] +2024-11-22 11:06:57.890731: Epoch time: 17.09 s +2024-11-22 11:06:58.761945: +2024-11-22 11:06:58.762185: Epoch 4545 +2024-11-22 11:06:58.762294: Current learning rate: 0.0047 +2024-11-22 11:07:16.881411: train_loss -0.7885 +2024-11-22 11:07:16.881632: val_loss -0.7686 +2024-11-22 11:07:16.881703: Pseudo dice [0.8531] +2024-11-22 11:07:16.882054: Epoch time: 18.12 s +2024-11-22 11:07:17.750582: +2024-11-22 11:07:17.750814: Epoch 4546 +2024-11-22 11:07:17.750932: Current learning rate: 0.0047 +2024-11-22 11:07:36.650979: train_loss -0.7926 +2024-11-22 11:07:36.651187: val_loss -0.7678 +2024-11-22 11:07:36.651260: Pseudo dice [0.8408] +2024-11-22 11:07:36.651331: Epoch time: 18.9 s +2024-11-22 11:07:37.518463: +2024-11-22 11:07:37.518715: Epoch 4547 +2024-11-22 11:07:37.518821: Current learning rate: 0.00469 +2024-11-22 11:07:56.485737: train_loss -0.7971 +2024-11-22 11:07:56.486094: val_loss -0.7709 +2024-11-22 11:07:56.486176: Pseudo dice [0.8442] +2024-11-22 11:07:56.486261: Epoch time: 18.97 s +2024-11-22 11:07:57.380861: +2024-11-22 11:07:57.381081: Epoch 4548 +2024-11-22 11:07:57.381195: Current learning rate: 0.00469 +2024-11-22 11:08:15.512160: train_loss -0.773 +2024-11-22 11:08:15.512387: val_loss -0.7518 +2024-11-22 11:08:15.512464: Pseudo dice [0.8471] +2024-11-22 11:08:15.512551: Epoch time: 18.13 s +2024-11-22 11:08:16.400454: +2024-11-22 11:08:16.400687: Epoch 4549 +2024-11-22 11:08:16.400793: Current learning rate: 0.00469 +2024-11-22 11:08:34.376636: train_loss -0.7869 +2024-11-22 11:08:34.376854: val_loss -0.7897 +2024-11-22 11:08:34.376927: Pseudo dice [0.8553] +2024-11-22 11:08:34.377007: Epoch time: 17.98 s +2024-11-22 11:08:35.521422: +2024-11-22 11:08:35.521626: Epoch 4550 +2024-11-22 11:08:35.521741: Current learning rate: 0.00469 +2024-11-22 11:08:53.994327: train_loss -0.7869 +2024-11-22 11:08:53.994550: val_loss -0.7806 +2024-11-22 11:08:53.994629: Pseudo dice [0.8602] +2024-11-22 11:08:53.994730: Epoch time: 18.47 s +2024-11-22 11:08:54.858453: +2024-11-22 11:08:54.858884: Epoch 4551 +2024-11-22 11:08:54.859024: Current learning rate: 0.00469 +2024-11-22 11:09:13.162110: train_loss -0.7821 +2024-11-22 11:09:13.162369: val_loss -0.7561 +2024-11-22 11:09:13.162487: Pseudo dice [0.8501] +2024-11-22 11:09:13.162578: Epoch time: 18.3 s +2024-11-22 11:09:14.382407: +2024-11-22 11:09:14.382711: Epoch 4552 +2024-11-22 11:09:14.382839: Current learning rate: 0.00469 +2024-11-22 11:09:32.440964: train_loss -0.7793 +2024-11-22 11:09:32.441209: val_loss -0.7549 +2024-11-22 11:09:32.441281: Pseudo dice [0.8493] +2024-11-22 11:09:32.441355: Epoch time: 18.06 s +2024-11-22 11:09:33.469740: +2024-11-22 11:09:33.469971: Epoch 4553 +2024-11-22 11:09:33.470090: Current learning rate: 0.00469 +2024-11-22 11:09:51.612374: train_loss -0.7834 +2024-11-22 11:09:51.612586: val_loss -0.7793 +2024-11-22 11:09:51.612662: Pseudo dice [0.8562] +2024-11-22 11:09:51.612738: Epoch time: 18.14 s +2024-11-22 11:09:52.476784: +2024-11-22 11:09:52.476999: Epoch 4554 +2024-11-22 11:09:52.477105: Current learning rate: 0.00469 +2024-11-22 11:10:10.897626: train_loss -0.7805 +2024-11-22 11:10:10.897874: val_loss -0.767 +2024-11-22 11:10:10.897950: Pseudo dice [0.8357] +2024-11-22 11:10:10.898034: Epoch time: 18.42 s +2024-11-22 11:10:11.765904: +2024-11-22 11:10:11.766125: Epoch 4555 +2024-11-22 11:10:11.766232: Current learning rate: 0.00468 +2024-11-22 11:10:29.976045: train_loss -0.7916 +2024-11-22 11:10:29.976267: val_loss -0.7667 +2024-11-22 11:10:29.976341: Pseudo dice [0.8533] +2024-11-22 11:10:29.976416: Epoch time: 18.21 s +2024-11-22 11:10:30.844560: +2024-11-22 11:10:30.844801: Epoch 4556 +2024-11-22 11:10:30.844916: Current learning rate: 0.00468 +2024-11-22 11:10:49.034445: train_loss -0.7989 +2024-11-22 11:10:49.034662: val_loss -0.7508 +2024-11-22 11:10:49.034739: Pseudo dice [0.8458] +2024-11-22 11:10:49.034816: Epoch time: 18.19 s +2024-11-22 11:10:49.895123: +2024-11-22 11:10:49.895344: Epoch 4557 +2024-11-22 11:10:49.895455: Current learning rate: 0.00468 +2024-11-22 11:11:09.132451: train_loss -0.7911 +2024-11-22 11:11:09.132671: val_loss -0.7942 +2024-11-22 11:11:09.132756: Pseudo dice [0.8592] +2024-11-22 11:11:09.132835: Epoch time: 19.24 s +2024-11-22 11:11:09.999647: +2024-11-22 11:11:09.999836: Epoch 4558 +2024-11-22 11:11:09.999945: Current learning rate: 0.00468 +2024-11-22 11:11:29.077402: train_loss -0.7865 +2024-11-22 11:11:29.077640: val_loss -0.7718 +2024-11-22 11:11:29.077714: Pseudo dice [0.8398] +2024-11-22 11:11:29.077790: Epoch time: 19.08 s +2024-11-22 11:11:29.946309: +2024-11-22 11:11:29.946592: Epoch 4559 +2024-11-22 11:11:29.946705: Current learning rate: 0.00468 +2024-11-22 11:11:47.719091: train_loss -0.7933 +2024-11-22 11:11:47.719304: val_loss -0.7927 +2024-11-22 11:11:47.719380: Pseudo dice [0.8487] +2024-11-22 11:11:47.719457: Epoch time: 17.77 s +2024-11-22 11:11:48.580616: +2024-11-22 11:11:48.580815: Epoch 4560 +2024-11-22 11:11:48.580922: Current learning rate: 0.00468 +2024-11-22 11:12:07.563623: train_loss -0.7867 +2024-11-22 11:12:07.563836: val_loss -0.7801 +2024-11-22 11:12:07.563908: Pseudo dice [0.8434] +2024-11-22 11:12:07.563982: Epoch time: 18.98 s +2024-11-22 11:12:08.420593: +2024-11-22 11:12:08.420811: Epoch 4561 +2024-11-22 11:12:08.420920: Current learning rate: 0.00468 +2024-11-22 11:12:26.554340: train_loss -0.7917 +2024-11-22 11:12:26.554591: val_loss -0.7691 +2024-11-22 11:12:26.554667: Pseudo dice [0.8449] +2024-11-22 11:12:26.554749: Epoch time: 18.13 s +2024-11-22 11:12:27.419160: +2024-11-22 11:12:27.419380: Epoch 4562 +2024-11-22 11:12:27.419492: Current learning rate: 0.00468 +2024-11-22 11:12:45.762678: train_loss -0.784 +2024-11-22 11:12:45.762893: val_loss -0.7778 +2024-11-22 11:12:45.762969: Pseudo dice [0.8485] +2024-11-22 11:12:45.763116: Epoch time: 18.34 s +2024-11-22 11:12:46.620835: +2024-11-22 11:12:46.621077: Epoch 4563 +2024-11-22 11:12:46.621189: Current learning rate: 0.00467 +2024-11-22 11:13:04.013338: train_loss -0.7919 +2024-11-22 11:13:04.013556: val_loss -0.7587 +2024-11-22 11:13:04.015864: Pseudo dice [0.8382] +2024-11-22 11:13:04.015980: Epoch time: 17.39 s +2024-11-22 11:13:05.348099: +2024-11-22 11:13:05.348338: Epoch 4564 +2024-11-22 11:13:05.348447: Current learning rate: 0.00467 +2024-11-22 11:13:24.313320: train_loss -0.7995 +2024-11-22 11:13:24.313569: val_loss -0.7599 +2024-11-22 11:13:24.313688: Pseudo dice [0.8392] +2024-11-22 11:13:24.313771: Epoch time: 18.97 s +2024-11-22 11:13:25.178972: +2024-11-22 11:13:25.179271: Epoch 4565 +2024-11-22 11:13:25.179380: Current learning rate: 0.00467 +2024-11-22 11:13:43.768437: train_loss -0.7869 +2024-11-22 11:13:43.768646: val_loss -0.7599 +2024-11-22 11:13:43.768720: Pseudo dice [0.849] +2024-11-22 11:13:43.768803: Epoch time: 18.59 s +2024-11-22 11:13:44.639925: +2024-11-22 11:13:44.640150: Epoch 4566 +2024-11-22 11:13:44.640257: Current learning rate: 0.00467 +2024-11-22 11:14:03.757799: train_loss -0.7804 +2024-11-22 11:14:03.758018: val_loss -0.783 +2024-11-22 11:14:03.758091: Pseudo dice [0.8561] +2024-11-22 11:14:03.758163: Epoch time: 19.12 s +2024-11-22 11:14:04.646157: +2024-11-22 11:14:04.646382: Epoch 4567 +2024-11-22 11:14:04.646492: Current learning rate: 0.00467 +2024-11-22 11:14:23.494789: train_loss -0.7899 +2024-11-22 11:14:23.495015: val_loss -0.7896 +2024-11-22 11:14:23.495092: Pseudo dice [0.8488] +2024-11-22 11:14:23.495172: Epoch time: 18.85 s +2024-11-22 11:14:24.363247: +2024-11-22 11:14:24.363491: Epoch 4568 +2024-11-22 11:14:24.363606: Current learning rate: 0.00467 +2024-11-22 11:14:43.191752: train_loss -0.7902 +2024-11-22 11:14:43.192019: val_loss -0.7759 +2024-11-22 11:14:43.192098: Pseudo dice [0.8567] +2024-11-22 11:14:43.192179: Epoch time: 18.83 s +2024-11-22 11:14:44.061668: +2024-11-22 11:14:44.061863: Epoch 4569 +2024-11-22 11:14:44.061970: Current learning rate: 0.00467 +2024-11-22 11:15:02.594659: train_loss -0.7917 +2024-11-22 11:15:02.594889: val_loss -0.7828 +2024-11-22 11:15:02.594966: Pseudo dice [0.863] +2024-11-22 11:15:02.595046: Epoch time: 18.53 s +2024-11-22 11:15:03.460341: +2024-11-22 11:15:03.460533: Epoch 4570 +2024-11-22 11:15:03.460642: Current learning rate: 0.00467 +2024-11-22 11:15:23.571313: train_loss -0.7854 +2024-11-22 11:15:23.571523: val_loss -0.7635 +2024-11-22 11:15:23.571601: Pseudo dice [0.8411] +2024-11-22 11:15:23.571676: Epoch time: 20.11 s +2024-11-22 11:15:24.434695: +2024-11-22 11:15:24.434913: Epoch 4571 +2024-11-22 11:15:24.435037: Current learning rate: 0.00467 +2024-11-22 11:15:43.587571: train_loss -0.7847 +2024-11-22 11:15:43.587815: val_loss -0.7549 +2024-11-22 11:15:43.587890: Pseudo dice [0.8418] +2024-11-22 11:15:43.588267: Epoch time: 19.15 s +2024-11-22 11:15:44.451245: +2024-11-22 11:15:44.451455: Epoch 4572 +2024-11-22 11:15:44.451566: Current learning rate: 0.00466 +2024-11-22 11:16:03.068776: train_loss -0.7904 +2024-11-22 11:16:03.069006: val_loss -0.7676 +2024-11-22 11:16:03.069087: Pseudo dice [0.8341] +2024-11-22 11:16:03.069165: Epoch time: 18.62 s +2024-11-22 11:16:03.936364: +2024-11-22 11:16:03.936594: Epoch 4573 +2024-11-22 11:16:03.936710: Current learning rate: 0.00466 +2024-11-22 11:16:22.058824: train_loss -0.793 +2024-11-22 11:16:22.059047: val_loss -0.7608 +2024-11-22 11:16:22.059122: Pseudo dice [0.8443] +2024-11-22 11:16:22.059228: Epoch time: 18.12 s +2024-11-22 11:16:22.923146: +2024-11-22 11:16:22.923359: Epoch 4574 +2024-11-22 11:16:22.923468: Current learning rate: 0.00466 +2024-11-22 11:16:40.958590: train_loss -0.7903 +2024-11-22 11:16:40.958803: val_loss -0.7948 +2024-11-22 11:16:40.958880: Pseudo dice [0.8543] +2024-11-22 11:16:40.958958: Epoch time: 18.04 s +2024-11-22 11:16:41.814920: +2024-11-22 11:16:41.815153: Epoch 4575 +2024-11-22 11:16:41.815264: Current learning rate: 0.00466 +2024-11-22 11:17:00.582375: train_loss -0.7924 +2024-11-22 11:17:00.582617: val_loss -0.7745 +2024-11-22 11:17:00.582691: Pseudo dice [0.8495] +2024-11-22 11:17:00.582799: Epoch time: 18.77 s +2024-11-22 11:17:01.833470: +2024-11-22 11:17:01.833706: Epoch 4576 +2024-11-22 11:17:01.833817: Current learning rate: 0.00466 +2024-11-22 11:17:20.229987: train_loss -0.7901 +2024-11-22 11:17:20.230256: val_loss -0.7501 +2024-11-22 11:17:20.230407: Pseudo dice [0.85] +2024-11-22 11:17:20.230489: Epoch time: 18.4 s +2024-11-22 11:17:21.096503: +2024-11-22 11:17:21.096724: Epoch 4577 +2024-11-22 11:17:21.096832: Current learning rate: 0.00466 +2024-11-22 11:17:39.729507: train_loss -0.7929 +2024-11-22 11:17:39.729722: val_loss -0.7618 +2024-11-22 11:17:39.729803: Pseudo dice [0.8571] +2024-11-22 11:17:39.729885: Epoch time: 18.63 s +2024-11-22 11:17:40.698767: +2024-11-22 11:17:40.699102: Epoch 4578 +2024-11-22 11:17:40.699222: Current learning rate: 0.00466 +2024-11-22 11:17:58.600252: train_loss -0.7962 +2024-11-22 11:17:58.600499: val_loss -0.7881 +2024-11-22 11:17:58.600575: Pseudo dice [0.8424] +2024-11-22 11:17:58.600658: Epoch time: 17.9 s +2024-11-22 11:17:59.474071: +2024-11-22 11:17:59.474282: Epoch 4579 +2024-11-22 11:17:59.474390: Current learning rate: 0.00466 +2024-11-22 11:18:17.377984: train_loss -0.797 +2024-11-22 11:18:17.378200: val_loss -0.7372 +2024-11-22 11:18:17.378276: Pseudo dice [0.8701] +2024-11-22 11:18:17.378353: Epoch time: 17.9 s +2024-11-22 11:18:18.262173: +2024-11-22 11:18:18.262383: Epoch 4580 +2024-11-22 11:18:18.262489: Current learning rate: 0.00465 +2024-11-22 11:18:36.240495: train_loss -0.7969 +2024-11-22 11:18:36.240706: val_loss -0.7925 +2024-11-22 11:18:36.240782: Pseudo dice [0.8561] +2024-11-22 11:18:36.240856: Epoch time: 17.98 s +2024-11-22 11:18:37.185302: +2024-11-22 11:18:37.185520: Epoch 4581 +2024-11-22 11:18:37.185635: Current learning rate: 0.00465 +2024-11-22 11:18:55.389349: train_loss -0.7836 +2024-11-22 11:18:55.389563: val_loss -0.7741 +2024-11-22 11:18:55.389636: Pseudo dice [0.8444] +2024-11-22 11:18:55.389712: Epoch time: 18.2 s +2024-11-22 11:18:56.255442: +2024-11-22 11:18:56.255649: Epoch 4582 +2024-11-22 11:18:56.255760: Current learning rate: 0.00465 +2024-11-22 11:19:14.765027: train_loss -0.7983 +2024-11-22 11:19:14.765302: val_loss -0.7755 +2024-11-22 11:19:14.765380: Pseudo dice [0.8528] +2024-11-22 11:19:14.765466: Epoch time: 18.51 s +2024-11-22 11:19:15.632235: +2024-11-22 11:19:15.632464: Epoch 4583 +2024-11-22 11:19:15.632575: Current learning rate: 0.00465 +2024-11-22 11:19:33.170693: train_loss -0.7989 +2024-11-22 11:19:33.170910: val_loss -0.7524 +2024-11-22 11:19:33.170983: Pseudo dice [0.853] +2024-11-22 11:19:33.171065: Epoch time: 17.54 s +2024-11-22 11:19:34.041131: +2024-11-22 11:19:34.041342: Epoch 4584 +2024-11-22 11:19:34.041448: Current learning rate: 0.00465 +2024-11-22 11:19:52.364470: train_loss -0.7912 +2024-11-22 11:19:52.364698: val_loss -0.7649 +2024-11-22 11:19:52.364782: Pseudo dice [0.8476] +2024-11-22 11:19:52.364858: Epoch time: 18.32 s +2024-11-22 11:19:53.326819: +2024-11-22 11:19:53.327046: Epoch 4585 +2024-11-22 11:19:53.327162: Current learning rate: 0.00465 +2024-11-22 11:20:11.791289: train_loss -0.7886 +2024-11-22 11:20:11.791581: val_loss -0.7684 +2024-11-22 11:20:11.791664: Pseudo dice [0.8408] +2024-11-22 11:20:11.791751: Epoch time: 18.47 s +2024-11-22 11:20:12.657917: +2024-11-22 11:20:12.658124: Epoch 4586 +2024-11-22 11:20:12.658233: Current learning rate: 0.00465 +2024-11-22 11:20:30.428141: train_loss -0.7898 +2024-11-22 11:20:30.428362: val_loss -0.7739 +2024-11-22 11:20:30.428443: Pseudo dice [0.8645] +2024-11-22 11:20:30.428515: Epoch time: 17.77 s +2024-11-22 11:20:31.295666: +2024-11-22 11:20:31.295897: Epoch 4587 +2024-11-22 11:20:31.296014: Current learning rate: 0.00465 +2024-11-22 11:20:49.708342: train_loss -0.7955 +2024-11-22 11:20:49.708569: val_loss -0.7506 +2024-11-22 11:20:49.708647: Pseudo dice [0.854] +2024-11-22 11:20:49.708723: Epoch time: 18.41 s +2024-11-22 11:20:51.023102: +2024-11-22 11:20:51.023553: Epoch 4588 +2024-11-22 11:20:51.023687: Current learning rate: 0.00464 +2024-11-22 11:21:08.774636: train_loss -0.796 +2024-11-22 11:21:08.774908: val_loss -0.7689 +2024-11-22 11:21:08.774989: Pseudo dice [0.8449] +2024-11-22 11:21:08.775081: Epoch time: 17.75 s +2024-11-22 11:21:09.642969: +2024-11-22 11:21:09.643443: Epoch 4589 +2024-11-22 11:21:09.643569: Current learning rate: 0.00464 +2024-11-22 11:21:29.389337: train_loss -0.7953 +2024-11-22 11:21:29.391874: val_loss -0.7514 +2024-11-22 11:21:29.391963: Pseudo dice [0.8327] +2024-11-22 11:21:29.392044: Epoch time: 19.75 s +2024-11-22 11:21:30.257226: +2024-11-22 11:21:30.257643: Epoch 4590 +2024-11-22 11:21:30.257792: Current learning rate: 0.00464 +2024-11-22 11:21:48.173121: train_loss -0.7996 +2024-11-22 11:21:48.173335: val_loss -0.7629 +2024-11-22 11:21:48.173409: Pseudo dice [0.8472] +2024-11-22 11:21:48.173484: Epoch time: 17.92 s +2024-11-22 11:21:49.057984: +2024-11-22 11:21:49.058416: Epoch 4591 +2024-11-22 11:21:49.058546: Current learning rate: 0.00464 +2024-11-22 11:22:07.686215: train_loss -0.7857 +2024-11-22 11:22:07.686450: val_loss -0.749 +2024-11-22 11:22:07.686527: Pseudo dice [0.8424] +2024-11-22 11:22:07.686608: Epoch time: 18.63 s +2024-11-22 11:22:08.554574: +2024-11-22 11:22:08.554975: Epoch 4592 +2024-11-22 11:22:08.555111: Current learning rate: 0.00464 +2024-11-22 11:22:26.346965: train_loss -0.7865 +2024-11-22 11:22:26.347217: val_loss -0.778 +2024-11-22 11:22:26.347296: Pseudo dice [0.8529] +2024-11-22 11:22:26.347373: Epoch time: 17.79 s +2024-11-22 11:22:27.198475: +2024-11-22 11:22:27.198913: Epoch 4593 +2024-11-22 11:22:27.199058: Current learning rate: 0.00464 +2024-11-22 11:22:46.198269: train_loss -0.7914 +2024-11-22 11:22:46.198491: val_loss -0.7792 +2024-11-22 11:22:46.198568: Pseudo dice [0.8592] +2024-11-22 11:22:46.198643: Epoch time: 19.0 s +2024-11-22 11:22:47.061996: +2024-11-22 11:22:47.062397: Epoch 4594 +2024-11-22 11:22:47.062530: Current learning rate: 0.00464 +2024-11-22 11:23:05.618829: train_loss -0.7904 +2024-11-22 11:23:05.619087: val_loss -0.7784 +2024-11-22 11:23:05.619228: Pseudo dice [0.8581] +2024-11-22 11:23:05.619305: Epoch time: 18.56 s +2024-11-22 11:23:06.483378: +2024-11-22 11:23:06.483837: Epoch 4595 +2024-11-22 11:23:06.483978: Current learning rate: 0.00464 +2024-11-22 11:23:24.722391: train_loss -0.8004 +2024-11-22 11:23:24.722663: val_loss -0.7556 +2024-11-22 11:23:24.722822: Pseudo dice [0.8284] +2024-11-22 11:23:24.722917: Epoch time: 18.24 s +2024-11-22 11:23:25.585361: +2024-11-22 11:23:25.585770: Epoch 4596 +2024-11-22 11:23:25.585898: Current learning rate: 0.00463 +2024-11-22 11:23:43.583869: train_loss -0.7906 +2024-11-22 11:23:43.584091: val_loss -0.7516 +2024-11-22 11:23:43.584170: Pseudo dice [0.813] +2024-11-22 11:23:43.584246: Epoch time: 18.0 s +2024-11-22 11:23:44.448123: +2024-11-22 11:23:44.448525: Epoch 4597 +2024-11-22 11:23:44.448653: Current learning rate: 0.00463 +2024-11-22 11:24:02.950423: train_loss -0.794 +2024-11-22 11:24:02.950699: val_loss -0.7651 +2024-11-22 11:24:02.950997: Pseudo dice [0.8338] +2024-11-22 11:24:02.951097: Epoch time: 18.5 s +2024-11-22 11:24:03.814508: +2024-11-22 11:24:03.814931: Epoch 4598 +2024-11-22 11:24:03.815069: Current learning rate: 0.00463 +2024-11-22 11:24:21.746484: train_loss -0.7977 +2024-11-22 11:24:21.746737: val_loss -0.7679 +2024-11-22 11:24:21.746814: Pseudo dice [0.8473] +2024-11-22 11:24:21.746909: Epoch time: 17.93 s +2024-11-22 11:24:22.610612: +2024-11-22 11:24:22.610823: Epoch 4599 +2024-11-22 11:24:22.610947: Current learning rate: 0.00463 +2024-11-22 11:24:41.004678: train_loss -0.7995 +2024-11-22 11:24:41.004894: val_loss -0.7673 +2024-11-22 11:24:41.004974: Pseudo dice [0.8497] +2024-11-22 11:24:41.005058: Epoch time: 18.39 s +2024-11-22 11:24:42.513686: +2024-11-22 11:24:42.513922: Epoch 4600 +2024-11-22 11:24:42.514046: Current learning rate: 0.00463 +2024-11-22 11:25:00.557545: train_loss -0.787 +2024-11-22 11:25:00.557950: val_loss -0.7429 +2024-11-22 11:25:00.558103: Pseudo dice [0.8338] +2024-11-22 11:25:00.558191: Epoch time: 18.04 s +2024-11-22 11:25:01.414183: +2024-11-22 11:25:01.414414: Epoch 4601 +2024-11-22 11:25:01.414524: Current learning rate: 0.00463 +2024-11-22 11:25:20.622063: train_loss -0.7873 +2024-11-22 11:25:20.622310: val_loss -0.7815 +2024-11-22 11:25:20.622388: Pseudo dice [0.8622] +2024-11-22 11:25:20.622473: Epoch time: 19.21 s +2024-11-22 11:25:21.485762: +2024-11-22 11:25:21.485981: Epoch 4602 +2024-11-22 11:25:21.486096: Current learning rate: 0.00463 +2024-11-22 11:25:39.731699: train_loss -0.7908 +2024-11-22 11:25:39.731975: val_loss -0.7657 +2024-11-22 11:25:39.732053: Pseudo dice [0.8414] +2024-11-22 11:25:39.732127: Epoch time: 18.25 s +2024-11-22 11:25:40.598181: +2024-11-22 11:25:40.598408: Epoch 4603 +2024-11-22 11:25:40.598518: Current learning rate: 0.00463 +2024-11-22 11:25:58.674399: train_loss -0.7867 +2024-11-22 11:25:58.674620: val_loss -0.7795 +2024-11-22 11:25:58.674695: Pseudo dice [0.8538] +2024-11-22 11:25:58.674770: Epoch time: 18.08 s +2024-11-22 11:25:59.538431: +2024-11-22 11:25:59.538652: Epoch 4604 +2024-11-22 11:25:59.538760: Current learning rate: 0.00462 +2024-11-22 11:26:18.774363: train_loss -0.7869 +2024-11-22 11:26:18.774584: val_loss -0.7324 +2024-11-22 11:26:18.774661: Pseudo dice [0.8423] +2024-11-22 11:26:18.774736: Epoch time: 19.24 s +2024-11-22 11:26:19.637161: +2024-11-22 11:26:19.637386: Epoch 4605 +2024-11-22 11:26:19.637497: Current learning rate: 0.00462 +2024-11-22 11:26:37.605595: train_loss -0.7955 +2024-11-22 11:26:37.605814: val_loss -0.7713 +2024-11-22 11:26:37.605891: Pseudo dice [0.8329] +2024-11-22 11:26:37.605967: Epoch time: 17.97 s +2024-11-22 11:26:38.476671: +2024-11-22 11:26:38.476885: Epoch 4606 +2024-11-22 11:26:38.477001: Current learning rate: 0.00462 +2024-11-22 11:26:56.086846: train_loss -0.7848 +2024-11-22 11:26:56.087100: val_loss -0.784 +2024-11-22 11:26:56.088685: Pseudo dice [0.8608] +2024-11-22 11:26:56.088784: Epoch time: 17.61 s +2024-11-22 11:26:57.175245: +2024-11-22 11:26:57.175476: Epoch 4607 +2024-11-22 11:26:57.175587: Current learning rate: 0.00462 +2024-11-22 11:27:16.086035: train_loss -0.8033 +2024-11-22 11:27:16.086249: val_loss -0.7806 +2024-11-22 11:27:16.086325: Pseudo dice [0.8419] +2024-11-22 11:27:16.086400: Epoch time: 18.91 s +2024-11-22 11:27:16.999079: +2024-11-22 11:27:16.999284: Epoch 4608 +2024-11-22 11:27:16.999392: Current learning rate: 0.00462 +2024-11-22 11:27:35.712384: train_loss -0.796 +2024-11-22 11:27:35.712600: val_loss -0.7906 +2024-11-22 11:27:35.712673: Pseudo dice [0.8251] +2024-11-22 11:27:35.712749: Epoch time: 18.71 s +2024-11-22 11:27:36.575964: +2024-11-22 11:27:36.576159: Epoch 4609 +2024-11-22 11:27:36.576267: Current learning rate: 0.00462 +2024-11-22 11:27:54.193444: train_loss -0.7909 +2024-11-22 11:27:54.193686: val_loss -0.771 +2024-11-22 11:27:54.193764: Pseudo dice [0.8526] +2024-11-22 11:27:54.193846: Epoch time: 17.62 s +2024-11-22 11:27:55.058298: +2024-11-22 11:27:55.058519: Epoch 4610 +2024-11-22 11:27:55.058633: Current learning rate: 0.00462 +2024-11-22 11:28:12.884259: train_loss -0.7846 +2024-11-22 11:28:12.884469: val_loss -0.7796 +2024-11-22 11:28:12.884546: Pseudo dice [0.8511] +2024-11-22 11:28:12.884619: Epoch time: 17.83 s +2024-11-22 11:28:13.745402: +2024-11-22 11:28:13.745620: Epoch 4611 +2024-11-22 11:28:13.745725: Current learning rate: 0.00462 +2024-11-22 11:28:32.314702: train_loss -0.7892 +2024-11-22 11:28:32.314911: val_loss -0.7594 +2024-11-22 11:28:32.314986: Pseudo dice [0.8364] +2024-11-22 11:28:32.315068: Epoch time: 18.57 s +2024-11-22 11:28:33.274412: +2024-11-22 11:28:33.274642: Epoch 4612 +2024-11-22 11:28:33.274755: Current learning rate: 0.00461 +2024-11-22 11:28:53.532613: train_loss -0.7952 +2024-11-22 11:28:53.533169: val_loss -0.7831 +2024-11-22 11:28:53.533272: Pseudo dice [0.8476] +2024-11-22 11:28:53.533358: Epoch time: 20.26 s +2024-11-22 11:28:54.392999: +2024-11-22 11:28:54.393234: Epoch 4613 +2024-11-22 11:28:54.393345: Current learning rate: 0.00461 +2024-11-22 11:29:13.367455: train_loss -0.7956 +2024-11-22 11:29:13.367664: val_loss -0.7708 +2024-11-22 11:29:13.367742: Pseudo dice [0.8374] +2024-11-22 11:29:13.367818: Epoch time: 18.98 s +2024-11-22 11:29:14.247517: +2024-11-22 11:29:14.247726: Epoch 4614 +2024-11-22 11:29:14.247835: Current learning rate: 0.00461 +2024-11-22 11:29:33.436766: train_loss -0.79 +2024-11-22 11:29:33.436989: val_loss -0.7892 +2024-11-22 11:29:33.437083: Pseudo dice [0.8431] +2024-11-22 11:29:33.437158: Epoch time: 19.19 s +2024-11-22 11:29:34.298671: +2024-11-22 11:29:34.298883: Epoch 4615 +2024-11-22 11:29:34.299001: Current learning rate: 0.00461 +2024-11-22 11:29:51.940103: train_loss -0.7956 +2024-11-22 11:29:51.940357: val_loss -0.7763 +2024-11-22 11:29:51.940435: Pseudo dice [0.8506] +2024-11-22 11:29:51.940591: Epoch time: 17.64 s +2024-11-22 11:29:52.811710: +2024-11-22 11:29:52.811934: Epoch 4616 +2024-11-22 11:29:52.812049: Current learning rate: 0.00461 +2024-11-22 11:30:10.909356: train_loss -0.7997 +2024-11-22 11:30:10.909577: val_loss -0.7485 +2024-11-22 11:30:10.909651: Pseudo dice [0.839] +2024-11-22 11:30:10.909725: Epoch time: 18.1 s +2024-11-22 11:30:11.773681: +2024-11-22 11:30:11.773906: Epoch 4617 +2024-11-22 11:30:11.774022: Current learning rate: 0.00461 +2024-11-22 11:30:30.410875: train_loss -0.792 +2024-11-22 11:30:30.411097: val_loss -0.786 +2024-11-22 11:30:30.411170: Pseudo dice [0.854] +2024-11-22 11:30:30.411242: Epoch time: 18.64 s +2024-11-22 11:30:31.271736: +2024-11-22 11:30:31.271960: Epoch 4618 +2024-11-22 11:30:31.272078: Current learning rate: 0.00461 +2024-11-22 11:30:49.453364: train_loss -0.7885 +2024-11-22 11:30:49.453577: val_loss -0.7506 +2024-11-22 11:30:49.453654: Pseudo dice [0.8261] +2024-11-22 11:30:49.453727: Epoch time: 18.18 s +2024-11-22 11:30:50.310869: +2024-11-22 11:30:50.311083: Epoch 4619 +2024-11-22 11:30:50.311194: Current learning rate: 0.00461 +2024-11-22 11:31:09.037773: train_loss -0.784 +2024-11-22 11:31:09.038017: val_loss -0.772 +2024-11-22 11:31:09.038093: Pseudo dice [0.8328] +2024-11-22 11:31:09.038177: Epoch time: 18.73 s +2024-11-22 11:31:09.901929: +2024-11-22 11:31:09.902158: Epoch 4620 +2024-11-22 11:31:09.902269: Current learning rate: 0.00461 +2024-11-22 11:31:28.628266: train_loss -0.7799 +2024-11-22 11:31:28.628482: val_loss -0.7584 +2024-11-22 11:31:28.628620: Pseudo dice [0.8443] +2024-11-22 11:31:28.628703: Epoch time: 18.73 s +2024-11-22 11:31:29.494416: +2024-11-22 11:31:29.494655: Epoch 4621 +2024-11-22 11:31:29.494763: Current learning rate: 0.0046 +2024-11-22 11:31:48.264495: train_loss -0.7876 +2024-11-22 11:31:48.264710: val_loss -0.7327 +2024-11-22 11:31:48.264786: Pseudo dice [0.8312] +2024-11-22 11:31:48.264862: Epoch time: 18.77 s +2024-11-22 11:31:49.128088: +2024-11-22 11:31:49.128400: Epoch 4622 +2024-11-22 11:31:49.128508: Current learning rate: 0.0046 +2024-11-22 11:32:07.770512: train_loss -0.7845 +2024-11-22 11:32:07.770726: val_loss -0.7512 +2024-11-22 11:32:07.773047: Pseudo dice [0.8408] +2024-11-22 11:32:07.773150: Epoch time: 18.64 s +2024-11-22 11:32:08.662004: +2024-11-22 11:32:08.662237: Epoch 4623 +2024-11-22 11:32:08.662349: Current learning rate: 0.0046 +2024-11-22 11:32:26.984659: train_loss -0.7915 +2024-11-22 11:32:26.984895: val_loss -0.7653 +2024-11-22 11:32:26.985234: Pseudo dice [0.8421] +2024-11-22 11:32:26.985325: Epoch time: 18.32 s +2024-11-22 11:32:27.863817: +2024-11-22 11:32:27.864050: Epoch 4624 +2024-11-22 11:32:27.864164: Current learning rate: 0.0046 +2024-11-22 11:32:47.288256: train_loss -0.7862 +2024-11-22 11:32:47.288548: val_loss -0.7628 +2024-11-22 11:32:47.288631: Pseudo dice [0.8438] +2024-11-22 11:32:47.288710: Epoch time: 19.43 s +2024-11-22 11:32:48.151064: +2024-11-22 11:32:48.151305: Epoch 4625 +2024-11-22 11:32:48.151417: Current learning rate: 0.0046 +2024-11-22 11:33:06.830104: train_loss -0.7858 +2024-11-22 11:33:06.830368: val_loss -0.7989 +2024-11-22 11:33:06.830453: Pseudo dice [0.8618] +2024-11-22 11:33:06.830535: Epoch time: 18.68 s +2024-11-22 11:33:07.702147: +2024-11-22 11:33:07.702377: Epoch 4626 +2024-11-22 11:33:07.702483: Current learning rate: 0.0046 +2024-11-22 11:33:26.329345: train_loss -0.7928 +2024-11-22 11:33:26.329649: val_loss -0.772 +2024-11-22 11:33:26.329730: Pseudo dice [0.8451] +2024-11-22 11:33:26.329810: Epoch time: 18.63 s +2024-11-22 11:33:27.208916: +2024-11-22 11:33:27.209152: Epoch 4627 +2024-11-22 11:33:27.209266: Current learning rate: 0.0046 +2024-11-22 11:33:45.527033: train_loss -0.7871 +2024-11-22 11:33:45.527240: val_loss -0.7553 +2024-11-22 11:33:45.527311: Pseudo dice [0.8524] +2024-11-22 11:33:45.527440: Epoch time: 18.32 s +2024-11-22 11:33:46.391979: +2024-11-22 11:33:46.392207: Epoch 4628 +2024-11-22 11:33:46.392346: Current learning rate: 0.0046 +2024-11-22 11:34:05.905749: train_loss -0.7872 +2024-11-22 11:34:05.905983: val_loss -0.7763 +2024-11-22 11:34:05.906072: Pseudo dice [0.8556] +2024-11-22 11:34:05.906149: Epoch time: 19.51 s +2024-11-22 11:34:06.775350: +2024-11-22 11:34:06.775597: Epoch 4629 +2024-11-22 11:34:06.775711: Current learning rate: 0.00459 +2024-11-22 11:34:24.753664: train_loss -0.7872 +2024-11-22 11:34:24.753896: val_loss -0.757 +2024-11-22 11:34:24.753971: Pseudo dice [0.8346] +2024-11-22 11:34:24.754051: Epoch time: 17.98 s +2024-11-22 11:34:25.721633: +2024-11-22 11:34:25.721850: Epoch 4630 +2024-11-22 11:34:25.721962: Current learning rate: 0.00459 +2024-11-22 11:34:44.476516: train_loss -0.7966 +2024-11-22 11:34:44.476764: val_loss -0.7811 +2024-11-22 11:34:44.476842: Pseudo dice [0.8406] +2024-11-22 11:34:44.476924: Epoch time: 18.76 s +2024-11-22 11:34:45.340474: +2024-11-22 11:34:45.340688: Epoch 4631 +2024-11-22 11:34:45.340799: Current learning rate: 0.00459 +2024-11-22 11:35:03.842872: train_loss -0.7893 +2024-11-22 11:35:03.843091: val_loss -0.7614 +2024-11-22 11:35:03.843169: Pseudo dice [0.8428] +2024-11-22 11:35:03.843243: Epoch time: 18.5 s +2024-11-22 11:35:04.710379: +2024-11-22 11:35:04.710628: Epoch 4632 +2024-11-22 11:35:04.710742: Current learning rate: 0.00459 +2024-11-22 11:35:22.790613: train_loss -0.7975 +2024-11-22 11:35:22.790835: val_loss -0.7861 +2024-11-22 11:35:22.790907: Pseudo dice [0.8466] +2024-11-22 11:35:22.790980: Epoch time: 18.08 s +2024-11-22 11:35:23.658367: +2024-11-22 11:35:23.658584: Epoch 4633 +2024-11-22 11:35:23.658698: Current learning rate: 0.00459 +2024-11-22 11:35:41.855083: train_loss -0.7806 +2024-11-22 11:35:41.855356: val_loss -0.759 +2024-11-22 11:35:41.855435: Pseudo dice [0.8333] +2024-11-22 11:35:41.855516: Epoch time: 18.2 s +2024-11-22 11:35:42.804298: +2024-11-22 11:35:42.804507: Epoch 4634 +2024-11-22 11:35:42.804614: Current learning rate: 0.00459 +2024-11-22 11:36:01.502150: train_loss -0.7908 +2024-11-22 11:36:01.502361: val_loss -0.7732 +2024-11-22 11:36:01.502433: Pseudo dice [0.8632] +2024-11-22 11:36:01.502505: Epoch time: 18.7 s +2024-11-22 11:36:02.363875: +2024-11-22 11:36:02.364083: Epoch 4635 +2024-11-22 11:36:02.364189: Current learning rate: 0.00459 +2024-11-22 11:36:20.827918: train_loss -0.7899 +2024-11-22 11:36:20.828141: val_loss -0.7738 +2024-11-22 11:36:20.828250: Pseudo dice [0.8472] +2024-11-22 11:36:20.828327: Epoch time: 18.46 s +2024-11-22 11:36:21.698274: +2024-11-22 11:36:21.698489: Epoch 4636 +2024-11-22 11:36:21.698598: Current learning rate: 0.00459 +2024-11-22 11:36:39.283169: train_loss -0.7882 +2024-11-22 11:36:39.283398: val_loss -0.7724 +2024-11-22 11:36:39.283475: Pseudo dice [0.8502] +2024-11-22 11:36:39.283557: Epoch time: 17.59 s +2024-11-22 11:36:40.168810: +2024-11-22 11:36:40.169024: Epoch 4637 +2024-11-22 11:36:40.169134: Current learning rate: 0.00458 +2024-11-22 11:36:58.149829: train_loss -0.7948 +2024-11-22 11:36:58.150106: val_loss -0.7834 +2024-11-22 11:36:58.150184: Pseudo dice [0.8429] +2024-11-22 11:36:58.150264: Epoch time: 17.98 s +2024-11-22 11:36:59.009079: +2024-11-22 11:36:59.009420: Epoch 4638 +2024-11-22 11:36:59.009532: Current learning rate: 0.00458 +2024-11-22 11:37:17.083051: train_loss -0.7847 +2024-11-22 11:37:17.083299: val_loss -0.7697 +2024-11-22 11:37:17.083381: Pseudo dice [0.8577] +2024-11-22 11:37:17.083454: Epoch time: 18.07 s +2024-11-22 11:37:17.945260: +2024-11-22 11:37:17.945564: Epoch 4639 +2024-11-22 11:37:17.945676: Current learning rate: 0.00458 +2024-11-22 11:37:36.172159: train_loss -0.7999 +2024-11-22 11:37:36.172372: val_loss -0.7619 +2024-11-22 11:37:36.172446: Pseudo dice [0.8262] +2024-11-22 11:37:36.172527: Epoch time: 18.23 s +2024-11-22 11:37:37.035996: +2024-11-22 11:37:37.036216: Epoch 4640 +2024-11-22 11:37:37.036325: Current learning rate: 0.00458 +2024-11-22 11:37:55.327404: train_loss -0.7879 +2024-11-22 11:37:55.327637: val_loss -0.7609 +2024-11-22 11:37:55.327711: Pseudo dice [0.8467] +2024-11-22 11:37:55.327785: Epoch time: 18.29 s +2024-11-22 11:37:56.304972: +2024-11-22 11:37:56.305210: Epoch 4641 +2024-11-22 11:37:56.305316: Current learning rate: 0.00458 +2024-11-22 11:38:14.609545: train_loss -0.7923 +2024-11-22 11:38:14.609763: val_loss -0.771 +2024-11-22 11:38:14.609836: Pseudo dice [0.851] +2024-11-22 11:38:14.609925: Epoch time: 18.31 s +2024-11-22 11:38:15.475307: +2024-11-22 11:38:15.475526: Epoch 4642 +2024-11-22 11:38:15.475635: Current learning rate: 0.00458 +2024-11-22 11:38:33.427500: train_loss -0.7932 +2024-11-22 11:38:33.427735: val_loss -0.7608 +2024-11-22 11:38:33.427811: Pseudo dice [0.8545] +2024-11-22 11:38:33.427888: Epoch time: 17.95 s +2024-11-22 11:38:34.373185: +2024-11-22 11:38:34.373397: Epoch 4643 +2024-11-22 11:38:34.373508: Current learning rate: 0.00458 +2024-11-22 11:38:52.058867: train_loss -0.7976 +2024-11-22 11:38:52.061565: val_loss -0.7811 +2024-11-22 11:38:52.061661: Pseudo dice [0.8548] +2024-11-22 11:38:52.061743: Epoch time: 17.69 s +2024-11-22 11:38:52.925813: +2024-11-22 11:38:52.926015: Epoch 4644 +2024-11-22 11:38:52.926124: Current learning rate: 0.00458 +2024-11-22 11:39:11.858032: train_loss -0.8004 +2024-11-22 11:39:11.858269: val_loss -0.79 +2024-11-22 11:39:11.858342: Pseudo dice [0.8519] +2024-11-22 11:39:11.858419: Epoch time: 18.93 s +2024-11-22 11:39:12.726863: +2024-11-22 11:39:12.727083: Epoch 4645 +2024-11-22 11:39:12.727196: Current learning rate: 0.00457 +2024-11-22 11:39:31.633691: train_loss -0.7904 +2024-11-22 11:39:31.633914: val_loss -0.7846 +2024-11-22 11:39:31.634031: Pseudo dice [0.862] +2024-11-22 11:39:31.634194: Epoch time: 18.91 s +2024-11-22 11:39:32.495730: +2024-11-22 11:39:32.495957: Epoch 4646 +2024-11-22 11:39:32.496075: Current learning rate: 0.00457 +2024-11-22 11:39:51.297411: train_loss -0.794 +2024-11-22 11:39:51.299827: val_loss -0.7547 +2024-11-22 11:39:51.299924: Pseudo dice [0.857] +2024-11-22 11:39:51.300171: Epoch time: 18.8 s +2024-11-22 11:39:52.169710: +2024-11-22 11:39:52.170031: Epoch 4647 +2024-11-22 11:39:52.170146: Current learning rate: 0.00457 +2024-11-22 11:40:10.838533: train_loss -0.7857 +2024-11-22 11:40:10.838782: val_loss -0.7651 +2024-11-22 11:40:10.838860: Pseudo dice [0.8509] +2024-11-22 11:40:10.838943: Epoch time: 18.67 s +2024-11-22 11:40:11.703836: +2024-11-22 11:40:11.704044: Epoch 4648 +2024-11-22 11:40:11.704150: Current learning rate: 0.00457 +2024-11-22 11:40:30.196550: train_loss -0.7961 +2024-11-22 11:40:30.196773: val_loss -0.7687 +2024-11-22 11:40:30.196845: Pseudo dice [0.852] +2024-11-22 11:40:30.196916: Epoch time: 18.49 s +2024-11-22 11:40:31.052910: +2024-11-22 11:40:31.053140: Epoch 4649 +2024-11-22 11:40:31.053248: Current learning rate: 0.00457 +2024-11-22 11:40:48.973513: train_loss -0.7932 +2024-11-22 11:40:48.973747: val_loss -0.7455 +2024-11-22 11:40:48.973907: Pseudo dice [0.8415] +2024-11-22 11:40:48.973990: Epoch time: 17.92 s +2024-11-22 11:40:50.108353: +2024-11-22 11:40:50.108548: Epoch 4650 +2024-11-22 11:40:50.108653: Current learning rate: 0.00457 +2024-11-22 11:41:09.154332: train_loss -0.8008 +2024-11-22 11:41:09.154635: val_loss -0.7769 +2024-11-22 11:41:09.154718: Pseudo dice [0.8418] +2024-11-22 11:41:09.154845: Epoch time: 19.05 s +2024-11-22 11:41:10.049417: +2024-11-22 11:41:10.049633: Epoch 4651 +2024-11-22 11:41:10.049742: Current learning rate: 0.00457 +2024-11-22 11:41:28.158809: train_loss -0.8016 +2024-11-22 11:41:28.159050: val_loss -0.7892 +2024-11-22 11:41:28.159125: Pseudo dice [0.8555] +2024-11-22 11:41:28.159202: Epoch time: 18.11 s +2024-11-22 11:41:29.019047: +2024-11-22 11:41:29.019270: Epoch 4652 +2024-11-22 11:41:29.019381: Current learning rate: 0.00457 +2024-11-22 11:41:48.924294: train_loss -0.795 +2024-11-22 11:41:48.924547: val_loss -0.7524 +2024-11-22 11:41:48.924625: Pseudo dice [0.8478] +2024-11-22 11:41:48.924707: Epoch time: 19.91 s +2024-11-22 11:41:49.799736: +2024-11-22 11:41:49.799946: Epoch 4653 +2024-11-22 11:41:49.800063: Current learning rate: 0.00456 +2024-11-22 11:42:08.615276: train_loss -0.7846 +2024-11-22 11:42:08.615496: val_loss -0.7811 +2024-11-22 11:42:08.615575: Pseudo dice [0.859] +2024-11-22 11:42:08.615649: Epoch time: 18.82 s +2024-11-22 11:42:09.500763: +2024-11-22 11:42:09.500962: Epoch 4654 +2024-11-22 11:42:09.501077: Current learning rate: 0.00456 +2024-11-22 11:42:28.013495: train_loss -0.7876 +2024-11-22 11:42:28.013723: val_loss -0.7684 +2024-11-22 11:42:28.013802: Pseudo dice [0.839] +2024-11-22 11:42:28.013880: Epoch time: 18.51 s +2024-11-22 11:42:28.920484: +2024-11-22 11:42:28.920732: Epoch 4655 +2024-11-22 11:42:28.920850: Current learning rate: 0.00456 +2024-11-22 11:42:47.818784: train_loss -0.797 +2024-11-22 11:42:47.819023: val_loss -0.7528 +2024-11-22 11:42:47.819099: Pseudo dice [0.8312] +2024-11-22 11:42:47.819177: Epoch time: 18.9 s +2024-11-22 11:42:48.690468: +2024-11-22 11:42:48.690696: Epoch 4656 +2024-11-22 11:42:48.690811: Current learning rate: 0.00456 +2024-11-22 11:43:06.720670: train_loss -0.7796 +2024-11-22 11:43:06.720886: val_loss -0.7585 +2024-11-22 11:43:06.720962: Pseudo dice [0.8625] +2024-11-22 11:43:06.721046: Epoch time: 18.03 s +2024-11-22 11:43:07.580360: +2024-11-22 11:43:07.580551: Epoch 4657 +2024-11-22 11:43:07.580661: Current learning rate: 0.00456 +2024-11-22 11:43:25.737445: train_loss -0.7736 +2024-11-22 11:43:25.737670: val_loss -0.7487 +2024-11-22 11:43:25.737746: Pseudo dice [0.8505] +2024-11-22 11:43:25.737825: Epoch time: 18.16 s +2024-11-22 11:43:26.601789: +2024-11-22 11:43:26.602065: Epoch 4658 +2024-11-22 11:43:26.602184: Current learning rate: 0.00456 +2024-11-22 11:43:45.224030: train_loss -0.79 +2024-11-22 11:43:45.224266: val_loss -0.7669 +2024-11-22 11:43:45.224341: Pseudo dice [0.8478] +2024-11-22 11:43:45.224419: Epoch time: 18.62 s +2024-11-22 11:43:46.119951: +2024-11-22 11:43:46.120269: Epoch 4659 +2024-11-22 11:43:46.120381: Current learning rate: 0.00456 +2024-11-22 11:44:04.197449: train_loss -0.7904 +2024-11-22 11:44:04.197664: val_loss -0.8017 +2024-11-22 11:44:04.197738: Pseudo dice [0.8642] +2024-11-22 11:44:04.197810: Epoch time: 18.08 s +2024-11-22 11:44:05.059948: +2024-11-22 11:44:05.060186: Epoch 4660 +2024-11-22 11:44:05.060298: Current learning rate: 0.00456 +2024-11-22 11:44:22.969356: train_loss -0.7951 +2024-11-22 11:44:22.969954: val_loss -0.7833 +2024-11-22 11:44:22.970068: Pseudo dice [0.8541] +2024-11-22 11:44:22.970156: Epoch time: 17.91 s +2024-11-22 11:44:23.889236: +2024-11-22 11:44:23.889466: Epoch 4661 +2024-11-22 11:44:23.889576: Current learning rate: 0.00455 +2024-11-22 11:44:41.462903: train_loss -0.8016 +2024-11-22 11:44:41.463160: val_loss -0.7923 +2024-11-22 11:44:41.463239: Pseudo dice [0.8572] +2024-11-22 11:44:41.463316: Epoch time: 17.57 s +2024-11-22 11:44:42.330795: +2024-11-22 11:44:42.331022: Epoch 4662 +2024-11-22 11:44:42.331136: Current learning rate: 0.00455 +2024-11-22 11:44:59.815039: train_loss -0.7984 +2024-11-22 11:44:59.815279: val_loss -0.7851 +2024-11-22 11:44:59.815355: Pseudo dice [0.8567] +2024-11-22 11:44:59.815429: Epoch time: 17.49 s +2024-11-22 11:44:59.815493: Yayy! New best EMA pseudo Dice: 0.8519 +2024-11-22 11:45:00.987113: +2024-11-22 11:45:00.987320: Epoch 4663 +2024-11-22 11:45:00.987430: Current learning rate: 0.00455 +2024-11-22 11:45:19.876168: train_loss -0.7907 +2024-11-22 11:45:19.876417: val_loss -0.7615 +2024-11-22 11:45:19.876515: Pseudo dice [0.8463] +2024-11-22 11:45:19.876603: Epoch time: 18.89 s +2024-11-22 11:45:20.749268: +2024-11-22 11:45:20.749576: Epoch 4664 +2024-11-22 11:45:20.749693: Current learning rate: 0.00455 +2024-11-22 11:45:38.753541: train_loss -0.7933 +2024-11-22 11:45:38.753778: val_loss -0.7681 +2024-11-22 11:45:38.753856: Pseudo dice [0.8505] +2024-11-22 11:45:38.753940: Epoch time: 18.01 s +2024-11-22 11:45:39.627520: +2024-11-22 11:45:39.627795: Epoch 4665 +2024-11-22 11:45:39.627908: Current learning rate: 0.00455 +2024-11-22 11:45:59.684332: train_loss -0.7893 +2024-11-22 11:45:59.684550: val_loss -0.7434 +2024-11-22 11:45:59.684624: Pseudo dice [0.8211] +2024-11-22 11:45:59.684695: Epoch time: 20.06 s +2024-11-22 11:46:00.554486: +2024-11-22 11:46:00.554707: Epoch 4666 +2024-11-22 11:46:00.554814: Current learning rate: 0.00455 +2024-11-22 11:46:18.813140: train_loss -0.7808 +2024-11-22 11:46:18.813355: val_loss -0.7916 +2024-11-22 11:46:18.813427: Pseudo dice [0.8507] +2024-11-22 11:46:18.813502: Epoch time: 18.26 s +2024-11-22 11:46:19.667089: +2024-11-22 11:46:19.667276: Epoch 4667 +2024-11-22 11:46:19.667373: Current learning rate: 0.00455 +2024-11-22 11:46:37.126124: train_loss -0.791 +2024-11-22 11:46:37.126340: val_loss -0.7696 +2024-11-22 11:46:37.126415: Pseudo dice [0.8528] +2024-11-22 11:46:37.126494: Epoch time: 17.46 s +2024-11-22 11:46:37.997957: +2024-11-22 11:46:37.998155: Epoch 4668 +2024-11-22 11:46:37.998261: Current learning rate: 0.00455 +2024-11-22 11:46:55.419154: train_loss -0.7865 +2024-11-22 11:46:55.419870: val_loss -0.7543 +2024-11-22 11:46:55.419949: Pseudo dice [0.834] +2024-11-22 11:46:55.420036: Epoch time: 17.42 s +2024-11-22 11:46:56.292472: +2024-11-22 11:46:56.292682: Epoch 4669 +2024-11-22 11:46:56.292790: Current learning rate: 0.00455 +2024-11-22 11:47:13.927505: train_loss -0.788 +2024-11-22 11:47:13.927727: val_loss -0.7504 +2024-11-22 11:47:13.927800: Pseudo dice [0.8321] +2024-11-22 11:47:13.927873: Epoch time: 17.64 s +2024-11-22 11:47:14.790150: +2024-11-22 11:47:14.790359: Epoch 4670 +2024-11-22 11:47:14.790465: Current learning rate: 0.00454 +2024-11-22 11:47:32.021592: train_loss -0.787 +2024-11-22 11:47:32.021798: val_loss -0.7768 +2024-11-22 11:47:32.021872: Pseudo dice [0.8613] +2024-11-22 11:47:32.021946: Epoch time: 17.23 s +2024-11-22 11:47:32.882334: +2024-11-22 11:47:32.882529: Epoch 4671 +2024-11-22 11:47:32.882634: Current learning rate: 0.00454 +2024-11-22 11:47:50.936312: train_loss -0.8067 +2024-11-22 11:47:50.936613: val_loss -0.793 +2024-11-22 11:47:50.946553: Pseudo dice [0.8571] +2024-11-22 11:47:50.946708: Epoch time: 18.05 s +2024-11-22 11:47:51.815104: +2024-11-22 11:47:51.815333: Epoch 4672 +2024-11-22 11:47:51.815444: Current learning rate: 0.00454 +2024-11-22 11:48:11.302925: train_loss -0.8007 +2024-11-22 11:48:11.303404: val_loss -0.7784 +2024-11-22 11:48:11.303503: Pseudo dice [0.8539] +2024-11-22 11:48:11.303577: Epoch time: 19.49 s +2024-11-22 11:48:12.408304: +2024-11-22 11:48:12.408532: Epoch 4673 +2024-11-22 11:48:12.408641: Current learning rate: 0.00454 +2024-11-22 11:48:31.863448: train_loss -0.7935 +2024-11-22 11:48:31.863667: val_loss -0.774 +2024-11-22 11:48:31.863738: Pseudo dice [0.8457] +2024-11-22 11:48:31.863812: Epoch time: 19.46 s +2024-11-22 11:48:32.737452: +2024-11-22 11:48:32.737684: Epoch 4674 +2024-11-22 11:48:32.737795: Current learning rate: 0.00454 +2024-11-22 11:48:52.385602: train_loss -0.795 +2024-11-22 11:48:52.390232: val_loss -0.771 +2024-11-22 11:48:52.390372: Pseudo dice [0.8506] +2024-11-22 11:48:52.390471: Epoch time: 19.65 s +2024-11-22 11:48:53.271521: +2024-11-22 11:48:53.271753: Epoch 4675 +2024-11-22 11:48:53.271858: Current learning rate: 0.00454 +2024-11-22 11:49:10.814749: train_loss -0.7853 +2024-11-22 11:49:10.815036: val_loss -0.7835 +2024-11-22 11:49:10.815142: Pseudo dice [0.8369] +2024-11-22 11:49:10.815216: Epoch time: 17.54 s +2024-11-22 11:49:11.682751: +2024-11-22 11:49:11.682977: Epoch 4676 +2024-11-22 11:49:11.683095: Current learning rate: 0.00454 +2024-11-22 11:49:30.707146: train_loss -0.791 +2024-11-22 11:49:30.707362: val_loss -0.7789 +2024-11-22 11:49:30.707434: Pseudo dice [0.8493] +2024-11-22 11:49:30.707509: Epoch time: 19.03 s +2024-11-22 11:49:31.598408: +2024-11-22 11:49:31.598621: Epoch 4677 +2024-11-22 11:49:31.598729: Current learning rate: 0.00454 +2024-11-22 11:49:49.757425: train_loss -0.7817 +2024-11-22 11:49:49.757671: val_loss -0.7507 +2024-11-22 11:49:49.757744: Pseudo dice [0.8421] +2024-11-22 11:49:49.757818: Epoch time: 18.16 s +2024-11-22 11:49:50.624663: +2024-11-22 11:49:50.624955: Epoch 4678 +2024-11-22 11:49:50.625075: Current learning rate: 0.00453 +2024-11-22 11:50:09.299457: train_loss -0.7851 +2024-11-22 11:50:09.299783: val_loss -0.7757 +2024-11-22 11:50:09.299866: Pseudo dice [0.8546] +2024-11-22 11:50:09.299950: Epoch time: 18.68 s +2024-11-22 11:50:10.167618: +2024-11-22 11:50:10.167840: Epoch 4679 +2024-11-22 11:50:10.167953: Current learning rate: 0.00453 +2024-11-22 11:50:29.050858: train_loss -0.7795 +2024-11-22 11:50:29.051085: val_loss -0.7764 +2024-11-22 11:50:29.051165: Pseudo dice [0.8346] +2024-11-22 11:50:29.051240: Epoch time: 18.88 s +2024-11-22 11:50:30.028169: +2024-11-22 11:50:30.028363: Epoch 4680 +2024-11-22 11:50:30.028470: Current learning rate: 0.00453 +2024-11-22 11:50:49.413464: train_loss -0.7659 +2024-11-22 11:50:49.413690: val_loss -0.7756 +2024-11-22 11:50:49.413770: Pseudo dice [0.8418] +2024-11-22 11:50:49.413847: Epoch time: 19.39 s +2024-11-22 11:50:50.285221: +2024-11-22 11:50:50.285428: Epoch 4681 +2024-11-22 11:50:50.285535: Current learning rate: 0.00453 +2024-11-22 11:51:09.618463: train_loss -0.7768 +2024-11-22 11:51:09.618713: val_loss -0.7396 +2024-11-22 11:51:09.618793: Pseudo dice [0.8387] +2024-11-22 11:51:09.618875: Epoch time: 19.33 s +2024-11-22 11:51:10.485899: +2024-11-22 11:51:10.486124: Epoch 4682 +2024-11-22 11:51:10.486259: Current learning rate: 0.00453 +2024-11-22 11:51:28.593231: train_loss -0.7593 +2024-11-22 11:51:28.593467: val_loss -0.7167 +2024-11-22 11:51:28.593548: Pseudo dice [0.8287] +2024-11-22 11:51:28.593628: Epoch time: 18.11 s +2024-11-22 11:51:29.461043: +2024-11-22 11:51:29.461253: Epoch 4683 +2024-11-22 11:51:29.461363: Current learning rate: 0.00453 +2024-11-22 11:51:48.986554: train_loss -0.7798 +2024-11-22 11:51:48.986770: val_loss -0.7727 +2024-11-22 11:51:48.986843: Pseudo dice [0.8504] +2024-11-22 11:51:48.986917: Epoch time: 19.53 s +2024-11-22 11:51:49.854205: +2024-11-22 11:51:49.854419: Epoch 4684 +2024-11-22 11:51:49.854527: Current learning rate: 0.00453 +2024-11-22 11:52:07.204176: train_loss -0.7701 +2024-11-22 11:52:07.204687: val_loss -0.7597 +2024-11-22 11:52:07.204786: Pseudo dice [0.8491] +2024-11-22 11:52:07.204874: Epoch time: 17.35 s +2024-11-22 11:52:08.069545: +2024-11-22 11:52:08.069796: Epoch 4685 +2024-11-22 11:52:08.069937: Current learning rate: 0.00453 +2024-11-22 11:52:27.267267: train_loss -0.7723 +2024-11-22 11:52:27.267485: val_loss -0.7735 +2024-11-22 11:52:27.267558: Pseudo dice [0.8432] +2024-11-22 11:52:27.267653: Epoch time: 19.2 s +2024-11-22 11:52:28.134771: +2024-11-22 11:52:28.135006: Epoch 4686 +2024-11-22 11:52:28.135139: Current learning rate: 0.00452 +2024-11-22 11:52:46.648355: train_loss -0.7854 +2024-11-22 11:52:46.648571: val_loss -0.7742 +2024-11-22 11:52:46.648649: Pseudo dice [0.8375] +2024-11-22 11:52:46.648724: Epoch time: 18.51 s +2024-11-22 11:52:47.513369: +2024-11-22 11:52:47.513599: Epoch 4687 +2024-11-22 11:52:47.513724: Current learning rate: 0.00452 +2024-11-22 11:53:06.127490: train_loss -0.7855 +2024-11-22 11:53:06.127707: val_loss -0.7612 +2024-11-22 11:53:06.127779: Pseudo dice [0.8511] +2024-11-22 11:53:06.127852: Epoch time: 18.61 s +2024-11-22 11:53:06.992258: +2024-11-22 11:53:06.992477: Epoch 4688 +2024-11-22 11:53:06.992589: Current learning rate: 0.00452 +2024-11-22 11:53:24.829197: train_loss -0.7962 +2024-11-22 11:53:24.829435: val_loss -0.7494 +2024-11-22 11:53:24.829509: Pseudo dice [0.842] +2024-11-22 11:53:24.829594: Epoch time: 17.84 s +2024-11-22 11:53:25.700358: +2024-11-22 11:53:25.700583: Epoch 4689 +2024-11-22 11:53:25.700703: Current learning rate: 0.00452 +2024-11-22 11:53:44.552889: train_loss -0.7817 +2024-11-22 11:53:44.553103: val_loss -0.7898 +2024-11-22 11:53:44.553179: Pseudo dice [0.8441] +2024-11-22 11:53:44.553253: Epoch time: 18.85 s +2024-11-22 11:53:45.533985: +2024-11-22 11:53:45.534223: Epoch 4690 +2024-11-22 11:53:45.534344: Current learning rate: 0.00452 +2024-11-22 11:54:03.053448: train_loss -0.7785 +2024-11-22 11:54:03.053689: val_loss -0.7703 +2024-11-22 11:54:03.053777: Pseudo dice [0.8375] +2024-11-22 11:54:03.053891: Epoch time: 17.52 s +2024-11-22 11:54:04.025209: +2024-11-22 11:54:04.025448: Epoch 4691 +2024-11-22 11:54:04.025566: Current learning rate: 0.00452 +2024-11-22 11:54:23.034935: train_loss -0.7922 +2024-11-22 11:54:23.035145: val_loss -0.7784 +2024-11-22 11:54:23.035218: Pseudo dice [0.8391] +2024-11-22 11:54:23.035292: Epoch time: 19.01 s +2024-11-22 11:54:23.903280: +2024-11-22 11:54:23.903528: Epoch 4692 +2024-11-22 11:54:23.903652: Current learning rate: 0.00452 +2024-11-22 11:54:41.982615: train_loss -0.7884 +2024-11-22 11:54:41.982881: val_loss -0.7426 +2024-11-22 11:54:41.982956: Pseudo dice [0.8494] +2024-11-22 11:54:41.983097: Epoch time: 18.08 s +2024-11-22 11:54:42.907478: +2024-11-22 11:54:42.907691: Epoch 4693 +2024-11-22 11:54:42.907797: Current learning rate: 0.00452 +2024-11-22 11:55:01.063835: train_loss -0.7947 +2024-11-22 11:55:01.064061: val_loss -0.7867 +2024-11-22 11:55:01.064142: Pseudo dice [0.8674] +2024-11-22 11:55:01.064219: Epoch time: 18.16 s +2024-11-22 11:55:01.922567: +2024-11-22 11:55:01.922815: Epoch 4694 +2024-11-22 11:55:01.922924: Current learning rate: 0.00451 +2024-11-22 11:55:20.231298: train_loss -0.7897 +2024-11-22 11:55:20.231551: val_loss -0.7353 +2024-11-22 11:55:20.231627: Pseudo dice [0.8454] +2024-11-22 11:55:20.231703: Epoch time: 18.31 s +2024-11-22 11:55:21.110343: +2024-11-22 11:55:21.110580: Epoch 4695 +2024-11-22 11:55:21.110695: Current learning rate: 0.00451 +2024-11-22 11:55:39.302828: train_loss -0.7961 +2024-11-22 11:55:39.303058: val_loss -0.779 +2024-11-22 11:55:39.303132: Pseudo dice [0.8365] +2024-11-22 11:55:39.303211: Epoch time: 18.19 s +2024-11-22 11:55:40.165395: +2024-11-22 11:55:40.165645: Epoch 4696 +2024-11-22 11:55:40.165796: Current learning rate: 0.00451 +2024-11-22 11:55:58.713339: train_loss -0.7967 +2024-11-22 11:55:58.713808: val_loss -0.7789 +2024-11-22 11:55:58.713904: Pseudo dice [0.8518] +2024-11-22 11:55:58.713984: Epoch time: 18.55 s +2024-11-22 11:55:59.579097: +2024-11-22 11:55:59.579518: Epoch 4697 +2024-11-22 11:55:59.579629: Current learning rate: 0.00451 +2024-11-22 11:56:17.923985: train_loss -0.7983 +2024-11-22 11:56:17.924206: val_loss -0.7552 +2024-11-22 11:56:17.924283: Pseudo dice [0.8511] +2024-11-22 11:56:17.924356: Epoch time: 18.35 s +2024-11-22 11:56:18.887014: +2024-11-22 11:56:18.887235: Epoch 4698 +2024-11-22 11:56:18.887341: Current learning rate: 0.00451 +2024-11-22 11:56:37.636118: train_loss -0.8022 +2024-11-22 11:56:37.636338: val_loss -0.7603 +2024-11-22 11:56:37.636413: Pseudo dice [0.8413] +2024-11-22 11:56:37.636492: Epoch time: 18.75 s +2024-11-22 11:56:38.513033: +2024-11-22 11:56:38.513280: Epoch 4699 +2024-11-22 11:56:38.513391: Current learning rate: 0.00451 +2024-11-22 11:56:57.252657: train_loss -0.793 +2024-11-22 11:56:57.254266: val_loss -0.7893 +2024-11-22 11:56:57.254452: Pseudo dice [0.8439] +2024-11-22 11:56:57.254540: Epoch time: 18.74 s +2024-11-22 11:56:58.416667: +2024-11-22 11:56:58.416888: Epoch 4700 +2024-11-22 11:56:58.417004: Current learning rate: 0.00451 +2024-11-22 11:57:16.694156: train_loss -0.7831 +2024-11-22 11:57:16.694376: val_loss -0.736 +2024-11-22 11:57:16.694458: Pseudo dice [0.8323] +2024-11-22 11:57:16.694542: Epoch time: 18.28 s +2024-11-22 11:57:17.582003: +2024-11-22 11:57:17.582225: Epoch 4701 +2024-11-22 11:57:17.582334: Current learning rate: 0.00451 +2024-11-22 11:57:35.927137: train_loss -0.7935 +2024-11-22 11:57:35.927361: val_loss -0.757 +2024-11-22 11:57:35.927437: Pseudo dice [0.8368] +2024-11-22 11:57:35.927584: Epoch time: 18.35 s +2024-11-22 11:57:36.790761: +2024-11-22 11:57:36.791005: Epoch 4702 +2024-11-22 11:57:36.791122: Current learning rate: 0.0045 +2024-11-22 11:57:55.099282: train_loss -0.7835 +2024-11-22 11:57:55.099505: val_loss -0.789 +2024-11-22 11:57:55.099594: Pseudo dice [0.8501] +2024-11-22 11:57:55.099666: Epoch time: 18.31 s +2024-11-22 11:57:55.987977: +2024-11-22 11:57:55.988193: Epoch 4703 +2024-11-22 11:57:55.988318: Current learning rate: 0.0045 +2024-11-22 11:58:15.020947: train_loss -0.7735 +2024-11-22 11:58:15.029415: val_loss -0.7565 +2024-11-22 11:58:15.029522: Pseudo dice [0.8228] +2024-11-22 11:58:15.029608: Epoch time: 19.03 s +2024-11-22 11:58:16.055625: +2024-11-22 11:58:16.055883: Epoch 4704 +2024-11-22 11:58:16.056002: Current learning rate: 0.0045 +2024-11-22 11:58:34.567855: train_loss -0.7871 +2024-11-22 11:58:34.568086: val_loss -0.76 +2024-11-22 11:58:34.568173: Pseudo dice [0.8395] +2024-11-22 11:58:34.568253: Epoch time: 18.51 s +2024-11-22 11:58:35.722331: +2024-11-22 11:58:35.722570: Epoch 4705 +2024-11-22 11:58:35.722686: Current learning rate: 0.0045 +2024-11-22 11:58:55.090845: train_loss -0.788 +2024-11-22 11:58:55.091134: val_loss -0.7498 +2024-11-22 11:58:55.091222: Pseudo dice [0.8335] +2024-11-22 11:58:55.091297: Epoch time: 19.37 s +2024-11-22 11:58:55.956552: +2024-11-22 11:58:55.956752: Epoch 4706 +2024-11-22 11:58:55.956865: Current learning rate: 0.0045 +2024-11-22 11:59:14.732154: train_loss -0.7956 +2024-11-22 11:59:14.732372: val_loss -0.7367 +2024-11-22 11:59:14.732450: Pseudo dice [0.8186] +2024-11-22 11:59:14.732529: Epoch time: 18.78 s +2024-11-22 11:59:15.603011: +2024-11-22 11:59:15.603254: Epoch 4707 +2024-11-22 11:59:15.603367: Current learning rate: 0.0045 +2024-11-22 11:59:35.434663: train_loss -0.7726 +2024-11-22 11:59:35.434881: val_loss -0.7399 +2024-11-22 11:59:35.434954: Pseudo dice [0.8203] +2024-11-22 11:59:35.435040: Epoch time: 19.83 s +2024-11-22 11:59:36.342190: +2024-11-22 11:59:36.342482: Epoch 4708 +2024-11-22 11:59:36.342590: Current learning rate: 0.0045 +2024-11-22 11:59:54.905269: train_loss -0.7782 +2024-11-22 11:59:54.905808: val_loss -0.7849 +2024-11-22 11:59:54.905910: Pseudo dice [0.8478] +2024-11-22 11:59:54.905982: Epoch time: 18.56 s +2024-11-22 11:59:55.766385: +2024-11-22 11:59:55.766607: Epoch 4709 +2024-11-22 11:59:55.766721: Current learning rate: 0.0045 +2024-11-22 12:00:14.833060: train_loss -0.7939 +2024-11-22 12:00:14.833278: val_loss -0.7596 +2024-11-22 12:00:14.833353: Pseudo dice [0.8266] +2024-11-22 12:00:14.850130: Epoch time: 19.07 s +2024-11-22 12:00:15.719514: +2024-11-22 12:00:15.719758: Epoch 4710 +2024-11-22 12:00:15.719869: Current learning rate: 0.00449 +2024-11-22 12:00:34.408133: train_loss -0.7842 +2024-11-22 12:00:34.408369: val_loss -0.7791 +2024-11-22 12:00:34.408445: Pseudo dice [0.8436] +2024-11-22 12:00:34.408523: Epoch time: 18.69 s +2024-11-22 12:00:35.274116: +2024-11-22 12:00:35.274345: Epoch 4711 +2024-11-22 12:00:35.274469: Current learning rate: 0.00449 +2024-11-22 12:00:53.124195: train_loss -0.7936 +2024-11-22 12:00:53.124408: val_loss -0.7507 +2024-11-22 12:00:53.124484: Pseudo dice [0.8432] +2024-11-22 12:00:53.124621: Epoch time: 17.85 s +2024-11-22 12:00:53.995211: +2024-11-22 12:00:53.995438: Epoch 4712 +2024-11-22 12:00:53.995547: Current learning rate: 0.00449 +2024-11-22 12:01:13.109041: train_loss -0.795 +2024-11-22 12:01:13.109308: val_loss -0.7719 +2024-11-22 12:01:13.109386: Pseudo dice [0.8326] +2024-11-22 12:01:13.109462: Epoch time: 19.11 s +2024-11-22 12:01:13.983452: +2024-11-22 12:01:13.983703: Epoch 4713 +2024-11-22 12:01:13.983816: Current learning rate: 0.00449 +2024-11-22 12:01:32.708179: train_loss -0.7931 +2024-11-22 12:01:32.708407: val_loss -0.751 +2024-11-22 12:01:32.708485: Pseudo dice [0.8311] +2024-11-22 12:01:32.708561: Epoch time: 18.73 s +2024-11-22 12:01:33.580850: +2024-11-22 12:01:33.581055: Epoch 4714 +2024-11-22 12:01:33.581162: Current learning rate: 0.00449 +2024-11-22 12:01:51.322454: train_loss -0.7954 +2024-11-22 12:01:51.322739: val_loss -0.7522 +2024-11-22 12:01:51.322828: Pseudo dice [0.8475] +2024-11-22 12:01:51.322952: Epoch time: 17.74 s +2024-11-22 12:01:52.231499: +2024-11-22 12:01:52.231745: Epoch 4715 +2024-11-22 12:01:52.231853: Current learning rate: 0.00449 +2024-11-22 12:02:10.329149: train_loss -0.7885 +2024-11-22 12:02:10.329654: val_loss -0.7766 +2024-11-22 12:02:10.329816: Pseudo dice [0.835] +2024-11-22 12:02:10.329891: Epoch time: 18.1 s +2024-11-22 12:02:11.208528: +2024-11-22 12:02:11.208879: Epoch 4716 +2024-11-22 12:02:11.209009: Current learning rate: 0.00449 +2024-11-22 12:02:30.375832: train_loss -0.8016 +2024-11-22 12:02:30.376055: val_loss -0.7571 +2024-11-22 12:02:30.376136: Pseudo dice [0.8456] +2024-11-22 12:02:30.376215: Epoch time: 19.17 s +2024-11-22 12:02:31.459795: +2024-11-22 12:02:31.460021: Epoch 4717 +2024-11-22 12:02:31.460133: Current learning rate: 0.00449 +2024-11-22 12:02:51.401077: train_loss -0.8001 +2024-11-22 12:02:51.401302: val_loss -0.784 +2024-11-22 12:02:51.401383: Pseudo dice [0.8517] +2024-11-22 12:02:51.401509: Epoch time: 19.94 s +2024-11-22 12:02:52.287269: +2024-11-22 12:02:52.287523: Epoch 4718 +2024-11-22 12:02:52.287676: Current learning rate: 0.00448 +2024-11-22 12:03:10.949211: train_loss -0.7837 +2024-11-22 12:03:10.949445: val_loss -0.8056 +2024-11-22 12:03:10.949525: Pseudo dice [0.8603] +2024-11-22 12:03:10.949604: Epoch time: 18.66 s +2024-11-22 12:03:11.876196: +2024-11-22 12:03:11.876417: Epoch 4719 +2024-11-22 12:03:11.876526: Current learning rate: 0.00448 +2024-11-22 12:03:30.538687: train_loss -0.7991 +2024-11-22 12:03:30.538901: val_loss -0.7723 +2024-11-22 12:03:30.538982: Pseudo dice [0.8355] +2024-11-22 12:03:30.539070: Epoch time: 18.66 s +2024-11-22 12:03:31.414382: +2024-11-22 12:03:31.414593: Epoch 4720 +2024-11-22 12:03:31.414700: Current learning rate: 0.00448 +2024-11-22 12:03:50.191121: train_loss -0.7957 +2024-11-22 12:03:50.191718: val_loss -0.8017 +2024-11-22 12:03:50.191825: Pseudo dice [0.8488] +2024-11-22 12:03:50.191906: Epoch time: 18.78 s +2024-11-22 12:03:51.067221: +2024-11-22 12:03:51.067453: Epoch 4721 +2024-11-22 12:03:51.067562: Current learning rate: 0.00448 +2024-11-22 12:04:09.388390: train_loss -0.7869 +2024-11-22 12:04:09.388627: val_loss -0.79 +2024-11-22 12:04:09.388705: Pseudo dice [0.8505] +2024-11-22 12:04:09.388787: Epoch time: 18.32 s +2024-11-22 12:04:10.261587: +2024-11-22 12:04:10.261811: Epoch 4722 +2024-11-22 12:04:10.261919: Current learning rate: 0.00448 +2024-11-22 12:04:29.071396: train_loss -0.8033 +2024-11-22 12:04:29.074676: val_loss -0.7823 +2024-11-22 12:04:29.074858: Pseudo dice [0.8543] +2024-11-22 12:04:29.074949: Epoch time: 18.81 s +2024-11-22 12:04:30.086237: +2024-11-22 12:04:30.086456: Epoch 4723 +2024-11-22 12:04:30.086566: Current learning rate: 0.00448 +2024-11-22 12:04:48.461097: train_loss -0.7979 +2024-11-22 12:04:48.461313: val_loss -0.7704 +2024-11-22 12:04:48.461390: Pseudo dice [0.8283] +2024-11-22 12:04:48.461467: Epoch time: 18.38 s +2024-11-22 12:04:49.478392: +2024-11-22 12:04:49.478623: Epoch 4724 +2024-11-22 12:04:49.478740: Current learning rate: 0.00448 +2024-11-22 12:05:09.430039: train_loss -0.7881 +2024-11-22 12:05:09.430350: val_loss -0.7757 +2024-11-22 12:05:09.430432: Pseudo dice [0.8341] +2024-11-22 12:05:09.430518: Epoch time: 19.95 s +2024-11-22 12:05:10.306635: +2024-11-22 12:05:10.306834: Epoch 4725 +2024-11-22 12:05:10.306953: Current learning rate: 0.00448 +2024-11-22 12:05:28.823727: train_loss -0.7867 +2024-11-22 12:05:28.823952: val_loss -0.7819 +2024-11-22 12:05:28.824032: Pseudo dice [0.8413] +2024-11-22 12:05:28.824106: Epoch time: 18.52 s +2024-11-22 12:05:29.706471: +2024-11-22 12:05:29.706687: Epoch 4726 +2024-11-22 12:05:29.706797: Current learning rate: 0.00447 +2024-11-22 12:05:48.284546: train_loss -0.7889 +2024-11-22 12:05:48.284779: val_loss -0.7765 +2024-11-22 12:05:48.284861: Pseudo dice [0.8563] +2024-11-22 12:05:48.284938: Epoch time: 18.58 s +2024-11-22 12:05:49.341834: +2024-11-22 12:05:49.342067: Epoch 4727 +2024-11-22 12:05:49.342404: Current learning rate: 0.00447 +2024-11-22 12:06:07.907049: train_loss -0.785 +2024-11-22 12:06:07.907277: val_loss -0.7615 +2024-11-22 12:06:07.907352: Pseudo dice [0.8621] +2024-11-22 12:06:07.907435: Epoch time: 18.57 s +2024-11-22 12:06:08.774069: +2024-11-22 12:06:08.774337: Epoch 4728 +2024-11-22 12:06:08.774450: Current learning rate: 0.00447 +2024-11-22 12:06:26.588255: train_loss -0.7774 +2024-11-22 12:06:26.588504: val_loss -0.7644 +2024-11-22 12:06:26.588587: Pseudo dice [0.8384] +2024-11-22 12:06:26.588671: Epoch time: 17.82 s +2024-11-22 12:06:27.461982: +2024-11-22 12:06:27.462220: Epoch 4729 +2024-11-22 12:06:27.462343: Current learning rate: 0.00447 +2024-11-22 12:06:45.610432: train_loss -0.7839 +2024-11-22 12:06:45.610640: val_loss -0.7707 +2024-11-22 12:06:45.610712: Pseudo dice [0.8541] +2024-11-22 12:06:45.615864: Epoch time: 18.15 s +2024-11-22 12:06:46.497436: +2024-11-22 12:06:46.497648: Epoch 4730 +2024-11-22 12:06:46.497753: Current learning rate: 0.00447 +2024-11-22 12:07:05.150536: train_loss -0.7871 +2024-11-22 12:07:05.150777: val_loss -0.7726 +2024-11-22 12:07:05.150854: Pseudo dice [0.8455] +2024-11-22 12:07:05.150925: Epoch time: 18.65 s +2024-11-22 12:07:06.018640: +2024-11-22 12:07:06.018861: Epoch 4731 +2024-11-22 12:07:06.018973: Current learning rate: 0.00447 +2024-11-22 12:07:25.050095: train_loss -0.7866 +2024-11-22 12:07:25.050348: val_loss -0.7698 +2024-11-22 12:07:25.050425: Pseudo dice [0.829] +2024-11-22 12:07:25.050510: Epoch time: 19.03 s +2024-11-22 12:07:25.926704: +2024-11-22 12:07:25.927049: Epoch 4732 +2024-11-22 12:07:25.927166: Current learning rate: 0.00447 +2024-11-22 12:07:44.775611: train_loss -0.7857 +2024-11-22 12:07:44.777398: val_loss -0.7771 +2024-11-22 12:07:44.777492: Pseudo dice [0.8592] +2024-11-22 12:07:44.777566: Epoch time: 18.85 s +2024-11-22 12:07:45.660503: +2024-11-22 12:07:45.660774: Epoch 4733 +2024-11-22 12:07:45.660884: Current learning rate: 0.00447 +2024-11-22 12:08:04.171776: train_loss -0.7887 +2024-11-22 12:08:04.172072: val_loss -0.7898 +2024-11-22 12:08:04.172152: Pseudo dice [0.8613] +2024-11-22 12:08:04.172227: Epoch time: 18.51 s +2024-11-22 12:08:05.046870: +2024-11-22 12:08:05.047081: Epoch 4734 +2024-11-22 12:08:05.047189: Current learning rate: 0.00447 +2024-11-22 12:08:23.077488: train_loss -0.7997 +2024-11-22 12:08:23.077703: val_loss -0.778 +2024-11-22 12:08:23.077781: Pseudo dice [0.8599] +2024-11-22 12:08:23.077856: Epoch time: 18.03 s +2024-11-22 12:08:23.955904: +2024-11-22 12:08:23.956143: Epoch 4735 +2024-11-22 12:08:23.973986: Current learning rate: 0.00446 +2024-11-22 12:08:42.305287: train_loss -0.7995 +2024-11-22 12:08:42.305540: val_loss -0.7582 +2024-11-22 12:08:42.305615: Pseudo dice [0.8544] +2024-11-22 12:08:42.305696: Epoch time: 18.35 s +2024-11-22 12:08:43.165494: +2024-11-22 12:08:43.165716: Epoch 4736 +2024-11-22 12:08:43.165826: Current learning rate: 0.00446 +2024-11-22 12:09:01.971930: train_loss -0.7866 +2024-11-22 12:09:01.972144: val_loss -0.7679 +2024-11-22 12:09:01.972218: Pseudo dice [0.8449] +2024-11-22 12:09:01.972290: Epoch time: 18.81 s +2024-11-22 12:09:02.842365: +2024-11-22 12:09:02.842609: Epoch 4737 +2024-11-22 12:09:02.842716: Current learning rate: 0.00446 +2024-11-22 12:09:20.854753: train_loss -0.7898 +2024-11-22 12:09:20.854982: val_loss -0.7651 +2024-11-22 12:09:20.855068: Pseudo dice [0.8385] +2024-11-22 12:09:20.855146: Epoch time: 18.01 s +2024-11-22 12:09:22.035582: +2024-11-22 12:09:22.035803: Epoch 4738 +2024-11-22 12:09:22.035912: Current learning rate: 0.00446 +2024-11-22 12:09:40.468156: train_loss -0.7902 +2024-11-22 12:09:40.468385: val_loss -0.7673 +2024-11-22 12:09:40.468462: Pseudo dice [0.8378] +2024-11-22 12:09:40.468538: Epoch time: 18.43 s +2024-11-22 12:09:41.369711: +2024-11-22 12:09:41.370045: Epoch 4739 +2024-11-22 12:09:41.370156: Current learning rate: 0.00446 +2024-11-22 12:09:59.728350: train_loss -0.7756 +2024-11-22 12:09:59.728602: val_loss -0.7778 +2024-11-22 12:09:59.728686: Pseudo dice [0.8567] +2024-11-22 12:09:59.728769: Epoch time: 18.36 s +2024-11-22 12:10:00.602212: +2024-11-22 12:10:00.602411: Epoch 4740 +2024-11-22 12:10:00.602520: Current learning rate: 0.00446 +2024-11-22 12:10:18.166694: train_loss -0.7914 +2024-11-22 12:10:18.166915: val_loss -0.7682 +2024-11-22 12:10:18.167001: Pseudo dice [0.8429] +2024-11-22 12:10:18.167168: Epoch time: 17.57 s +2024-11-22 12:10:19.175744: +2024-11-22 12:10:19.175965: Epoch 4741 +2024-11-22 12:10:19.176083: Current learning rate: 0.00446 +2024-11-22 12:10:38.369489: train_loss -0.7844 +2024-11-22 12:10:38.369721: val_loss -0.78 +2024-11-22 12:10:38.369798: Pseudo dice [0.8478] +2024-11-22 12:10:38.369873: Epoch time: 19.19 s +2024-11-22 12:10:39.247068: +2024-11-22 12:10:39.247280: Epoch 4742 +2024-11-22 12:10:39.247390: Current learning rate: 0.00446 +2024-11-22 12:10:56.529440: train_loss -0.7989 +2024-11-22 12:10:56.529691: val_loss -0.7945 +2024-11-22 12:10:56.529765: Pseudo dice [0.8433] +2024-11-22 12:10:56.530028: Epoch time: 17.28 s +2024-11-22 12:10:57.392201: +2024-11-22 12:10:57.392425: Epoch 4743 +2024-11-22 12:10:57.392538: Current learning rate: 0.00445 +2024-11-22 12:11:15.276102: train_loss -0.7979 +2024-11-22 12:11:15.276327: val_loss -0.7739 +2024-11-22 12:11:15.276402: Pseudo dice [0.8638] +2024-11-22 12:11:15.276476: Epoch time: 17.88 s +2024-11-22 12:11:16.139372: +2024-11-22 12:11:16.139577: Epoch 4744 +2024-11-22 12:11:16.139686: Current learning rate: 0.00445 +2024-11-22 12:11:34.526581: train_loss -0.7821 +2024-11-22 12:11:34.527138: val_loss -0.788 +2024-11-22 12:11:34.527243: Pseudo dice [0.8378] +2024-11-22 12:11:34.527332: Epoch time: 18.39 s +2024-11-22 12:11:35.395144: +2024-11-22 12:11:35.395385: Epoch 4745 +2024-11-22 12:11:35.395501: Current learning rate: 0.00445 +2024-11-22 12:11:54.335947: train_loss -0.796 +2024-11-22 12:11:54.336193: val_loss -0.7626 +2024-11-22 12:11:54.336267: Pseudo dice [0.8304] +2024-11-22 12:11:54.336343: Epoch time: 18.94 s +2024-11-22 12:11:55.204011: +2024-11-22 12:11:55.204256: Epoch 4746 +2024-11-22 12:11:55.204368: Current learning rate: 0.00445 +2024-11-22 12:12:12.416533: train_loss -0.7698 +2024-11-22 12:12:12.417097: val_loss -0.7727 +2024-11-22 12:12:12.417176: Pseudo dice [0.8329] +2024-11-22 12:12:12.417253: Epoch time: 17.21 s +2024-11-22 12:12:13.274293: +2024-11-22 12:12:13.274512: Epoch 4747 +2024-11-22 12:12:13.274621: Current learning rate: 0.00445 +2024-11-22 12:12:32.433705: train_loss -0.7813 +2024-11-22 12:12:32.439118: val_loss -0.773 +2024-11-22 12:12:32.439244: Pseudo dice [0.8501] +2024-11-22 12:12:32.466495: Epoch time: 19.16 s +2024-11-22 12:12:33.359941: +2024-11-22 12:12:33.360151: Epoch 4748 +2024-11-22 12:12:33.360261: Current learning rate: 0.00445 +2024-11-22 12:12:52.145432: train_loss -0.7817 +2024-11-22 12:12:52.145694: val_loss -0.7609 +2024-11-22 12:12:52.145768: Pseudo dice [0.848] +2024-11-22 12:12:52.145850: Epoch time: 18.79 s +2024-11-22 12:12:53.108857: +2024-11-22 12:12:53.109082: Epoch 4749 +2024-11-22 12:12:53.109189: Current learning rate: 0.00445 +2024-11-22 12:13:11.525426: train_loss -0.79 +2024-11-22 12:13:11.525654: val_loss -0.7532 +2024-11-22 12:13:11.525740: Pseudo dice [0.8307] +2024-11-22 12:13:11.525819: Epoch time: 18.42 s +2024-11-22 12:13:12.688299: +2024-11-22 12:13:12.688519: Epoch 4750 +2024-11-22 12:13:12.688635: Current learning rate: 0.00445 +2024-11-22 12:13:30.819518: train_loss -0.7903 +2024-11-22 12:13:30.825988: val_loss -0.7779 +2024-11-22 12:13:30.826133: Pseudo dice [0.845] +2024-11-22 12:13:30.826214: Epoch time: 18.13 s +2024-11-22 12:13:31.694444: +2024-11-22 12:13:31.694671: Epoch 4751 +2024-11-22 12:13:31.694795: Current learning rate: 0.00444 +2024-11-22 12:13:49.230103: train_loss -0.7976 +2024-11-22 12:13:49.230317: val_loss -0.7765 +2024-11-22 12:13:49.230390: Pseudo dice [0.8465] +2024-11-22 12:13:49.230464: Epoch time: 17.54 s +2024-11-22 12:13:50.105152: +2024-11-22 12:13:50.105462: Epoch 4752 +2024-11-22 12:13:50.105572: Current learning rate: 0.00444 +2024-11-22 12:14:08.091743: train_loss -0.7821 +2024-11-22 12:14:08.094172: val_loss -0.7803 +2024-11-22 12:14:08.094276: Pseudo dice [0.8497] +2024-11-22 12:14:08.094361: Epoch time: 17.99 s +2024-11-22 12:14:09.073792: +2024-11-22 12:14:09.074026: Epoch 4753 +2024-11-22 12:14:09.074369: Current learning rate: 0.00444 +2024-11-22 12:14:27.413525: train_loss -0.7777 +2024-11-22 12:14:27.413739: val_loss -0.781 +2024-11-22 12:14:27.413817: Pseudo dice [0.852] +2024-11-22 12:14:27.413890: Epoch time: 18.34 s +2024-11-22 12:14:28.299736: +2024-11-22 12:14:28.299946: Epoch 4754 +2024-11-22 12:14:28.300062: Current learning rate: 0.00444 +2024-11-22 12:14:47.237113: train_loss -0.7871 +2024-11-22 12:14:47.237330: val_loss -0.7799 +2024-11-22 12:14:47.237407: Pseudo dice [0.851] +2024-11-22 12:14:47.237481: Epoch time: 18.94 s +2024-11-22 12:14:48.101197: +2024-11-22 12:14:48.101393: Epoch 4755 +2024-11-22 12:14:48.101511: Current learning rate: 0.00444 +2024-11-22 12:15:06.448444: train_loss -0.7956 +2024-11-22 12:15:06.448694: val_loss -0.7813 +2024-11-22 12:15:06.448774: Pseudo dice [0.843] +2024-11-22 12:15:06.448859: Epoch time: 18.35 s +2024-11-22 12:15:07.736457: +2024-11-22 12:15:07.736668: Epoch 4756 +2024-11-22 12:15:07.736778: Current learning rate: 0.00444 +2024-11-22 12:15:26.511443: train_loss -0.7991 +2024-11-22 12:15:26.511661: val_loss -0.7386 +2024-11-22 12:15:26.511797: Pseudo dice [0.8378] +2024-11-22 12:15:26.511872: Epoch time: 18.78 s +2024-11-22 12:15:27.382453: +2024-11-22 12:15:27.382674: Epoch 4757 +2024-11-22 12:15:27.382787: Current learning rate: 0.00444 +2024-11-22 12:15:45.890999: train_loss -0.795 +2024-11-22 12:15:45.891211: val_loss -0.8077 +2024-11-22 12:15:45.891286: Pseudo dice [0.8579] +2024-11-22 12:15:45.891360: Epoch time: 18.51 s +2024-11-22 12:15:46.763314: +2024-11-22 12:15:46.763551: Epoch 4758 +2024-11-22 12:15:46.763673: Current learning rate: 0.00444 +2024-11-22 12:16:04.442322: train_loss -0.7957 +2024-11-22 12:16:04.442541: val_loss -0.7658 +2024-11-22 12:16:04.442635: Pseudo dice [0.8518] +2024-11-22 12:16:04.442737: Epoch time: 17.68 s +2024-11-22 12:16:05.349526: +2024-11-22 12:16:05.349747: Epoch 4759 +2024-11-22 12:16:05.349854: Current learning rate: 0.00443 +2024-11-22 12:16:23.256479: train_loss -0.8007 +2024-11-22 12:16:23.256794: val_loss -0.7755 +2024-11-22 12:16:23.256873: Pseudo dice [0.849] +2024-11-22 12:16:23.256960: Epoch time: 17.91 s +2024-11-22 12:16:24.168754: +2024-11-22 12:16:24.168979: Epoch 4760 +2024-11-22 12:16:24.169094: Current learning rate: 0.00443 +2024-11-22 12:16:42.004885: train_loss -0.794 +2024-11-22 12:16:42.005461: val_loss -0.761 +2024-11-22 12:16:42.005539: Pseudo dice [0.8391] +2024-11-22 12:16:42.005613: Epoch time: 17.84 s +2024-11-22 12:16:42.880967: +2024-11-22 12:16:42.881191: Epoch 4761 +2024-11-22 12:16:42.881300: Current learning rate: 0.00443 +2024-11-22 12:17:00.735097: train_loss -0.8015 +2024-11-22 12:17:00.735363: val_loss -0.7712 +2024-11-22 12:17:00.735437: Pseudo dice [0.8433] +2024-11-22 12:17:00.735511: Epoch time: 17.85 s +2024-11-22 12:17:01.606745: +2024-11-22 12:17:01.606973: Epoch 4762 +2024-11-22 12:17:01.607095: Current learning rate: 0.00443 +2024-11-22 12:17:19.729614: train_loss -0.7977 +2024-11-22 12:17:19.729831: val_loss -0.7654 +2024-11-22 12:17:19.729908: Pseudo dice [0.8471] +2024-11-22 12:17:19.730003: Epoch time: 18.12 s +2024-11-22 12:17:20.609305: +2024-11-22 12:17:20.609515: Epoch 4763 +2024-11-22 12:17:20.609629: Current learning rate: 0.00443 +2024-11-22 12:17:38.777552: train_loss -0.7889 +2024-11-22 12:17:38.777791: val_loss -0.783 +2024-11-22 12:17:38.777870: Pseudo dice [0.8515] +2024-11-22 12:17:38.777948: Epoch time: 18.17 s +2024-11-22 12:17:39.649419: +2024-11-22 12:17:39.649653: Epoch 4764 +2024-11-22 12:17:39.649760: Current learning rate: 0.00443 +2024-11-22 12:17:57.975545: train_loss -0.7833 +2024-11-22 12:17:57.975776: val_loss -0.7712 +2024-11-22 12:17:57.975860: Pseudo dice [0.8328] +2024-11-22 12:17:57.975938: Epoch time: 18.33 s +2024-11-22 12:17:58.841892: +2024-11-22 12:17:58.842132: Epoch 4765 +2024-11-22 12:17:58.842246: Current learning rate: 0.00443 +2024-11-22 12:18:17.947346: train_loss -0.7984 +2024-11-22 12:18:17.947558: val_loss -0.7794 +2024-11-22 12:18:17.947634: Pseudo dice [0.8433] +2024-11-22 12:18:17.947708: Epoch time: 19.11 s +2024-11-22 12:18:18.817641: +2024-11-22 12:18:18.817898: Epoch 4766 +2024-11-22 12:18:18.818013: Current learning rate: 0.00443 +2024-11-22 12:18:36.524477: train_loss -0.7896 +2024-11-22 12:18:36.524722: val_loss -0.7904 +2024-11-22 12:18:36.524800: Pseudo dice [0.8547] +2024-11-22 12:18:36.524882: Epoch time: 17.71 s +2024-11-22 12:18:37.396682: +2024-11-22 12:18:37.396879: Epoch 4767 +2024-11-22 12:18:37.396986: Current learning rate: 0.00442 +2024-11-22 12:18:56.186598: train_loss -0.7818 +2024-11-22 12:18:56.186814: val_loss -0.7629 +2024-11-22 12:18:56.186891: Pseudo dice [0.847] +2024-11-22 12:18:56.186968: Epoch time: 18.79 s +2024-11-22 12:18:57.504024: +2024-11-22 12:18:57.504264: Epoch 4768 +2024-11-22 12:18:57.504377: Current learning rate: 0.00442 +2024-11-22 12:19:16.038248: train_loss -0.7882 +2024-11-22 12:19:16.038472: val_loss -0.78 +2024-11-22 12:19:16.038550: Pseudo dice [0.8461] +2024-11-22 12:19:16.039302: Epoch time: 18.54 s +2024-11-22 12:19:16.974603: +2024-11-22 12:19:16.974807: Epoch 4769 +2024-11-22 12:19:16.974916: Current learning rate: 0.00442 +2024-11-22 12:19:36.012176: train_loss -0.7791 +2024-11-22 12:19:36.012421: val_loss -0.7603 +2024-11-22 12:19:36.012518: Pseudo dice [0.8445] +2024-11-22 12:19:36.012600: Epoch time: 19.04 s +2024-11-22 12:19:36.889402: +2024-11-22 12:19:36.889618: Epoch 4770 +2024-11-22 12:19:36.889725: Current learning rate: 0.00442 +2024-11-22 12:19:54.288949: train_loss -0.791 +2024-11-22 12:19:54.289206: val_loss -0.7775 +2024-11-22 12:19:54.289286: Pseudo dice [0.8504] +2024-11-22 12:19:54.289360: Epoch time: 17.4 s +2024-11-22 12:19:55.166458: +2024-11-22 12:19:55.166672: Epoch 4771 +2024-11-22 12:19:55.166782: Current learning rate: 0.00442 +2024-11-22 12:20:13.297355: train_loss -0.7999 +2024-11-22 12:20:13.297574: val_loss -0.773 +2024-11-22 12:20:13.297656: Pseudo dice [0.8471] +2024-11-22 12:20:13.297734: Epoch time: 18.13 s +2024-11-22 12:20:14.178529: +2024-11-22 12:20:14.178749: Epoch 4772 +2024-11-22 12:20:14.178859: Current learning rate: 0.00442 +2024-11-22 12:20:33.844661: train_loss -0.7852 +2024-11-22 12:20:33.844876: val_loss -0.7319 +2024-11-22 12:20:33.844949: Pseudo dice [0.8429] +2024-11-22 12:20:33.845037: Epoch time: 19.67 s +2024-11-22 12:20:34.728920: +2024-11-22 12:20:34.729217: Epoch 4773 +2024-11-22 12:20:34.729328: Current learning rate: 0.00442 +2024-11-22 12:20:53.856482: train_loss -0.7766 +2024-11-22 12:20:53.856753: val_loss -0.7568 +2024-11-22 12:20:53.856832: Pseudo dice [0.8474] +2024-11-22 12:20:53.856923: Epoch time: 19.13 s +2024-11-22 12:20:54.743021: +2024-11-22 12:20:54.743233: Epoch 4774 +2024-11-22 12:20:54.743342: Current learning rate: 0.00442 +2024-11-22 12:21:13.726537: train_loss -0.7843 +2024-11-22 12:21:13.726760: val_loss -0.7669 +2024-11-22 12:21:13.726835: Pseudo dice [0.8447] +2024-11-22 12:21:13.726969: Epoch time: 18.98 s +2024-11-22 12:21:14.603763: +2024-11-22 12:21:14.603975: Epoch 4775 +2024-11-22 12:21:14.604090: Current learning rate: 0.00441 +2024-11-22 12:21:33.155250: train_loss -0.7792 +2024-11-22 12:21:33.157661: val_loss -0.7742 +2024-11-22 12:21:33.157761: Pseudo dice [0.8459] +2024-11-22 12:21:33.157839: Epoch time: 18.55 s +2024-11-22 12:21:34.182809: +2024-11-22 12:21:34.183030: Epoch 4776 +2024-11-22 12:21:34.183159: Current learning rate: 0.00441 +2024-11-22 12:21:53.079905: train_loss -0.7795 +2024-11-22 12:21:53.080143: val_loss -0.7788 +2024-11-22 12:21:53.080221: Pseudo dice [0.843] +2024-11-22 12:21:53.080306: Epoch time: 18.9 s +2024-11-22 12:21:53.975764: +2024-11-22 12:21:53.975978: Epoch 4777 +2024-11-22 12:21:53.976093: Current learning rate: 0.00441 +2024-11-22 12:22:12.380583: train_loss -0.7566 +2024-11-22 12:22:12.395285: val_loss -0.7862 +2024-11-22 12:22:12.395380: Pseudo dice [0.8527] +2024-11-22 12:22:12.395464: Epoch time: 18.41 s +2024-11-22 12:22:13.299252: +2024-11-22 12:22:13.299471: Epoch 4778 +2024-11-22 12:22:13.299587: Current learning rate: 0.00441 +2024-11-22 12:22:31.881706: train_loss -0.7895 +2024-11-22 12:22:31.881921: val_loss -0.7886 +2024-11-22 12:22:31.882001: Pseudo dice [0.8383] +2024-11-22 12:22:31.882075: Epoch time: 18.58 s +2024-11-22 12:22:32.763957: +2024-11-22 12:22:32.764416: Epoch 4779 +2024-11-22 12:22:32.764538: Current learning rate: 0.00441 +2024-11-22 12:22:50.788542: train_loss -0.7933 +2024-11-22 12:22:50.788757: val_loss -0.7775 +2024-11-22 12:22:50.788830: Pseudo dice [0.8601] +2024-11-22 12:22:50.788904: Epoch time: 18.03 s +2024-11-22 12:22:52.082977: +2024-11-22 12:22:52.083213: Epoch 4780 +2024-11-22 12:22:52.083324: Current learning rate: 0.00441 +2024-11-22 12:23:10.762121: train_loss -0.7901 +2024-11-22 12:23:10.762379: val_loss -0.7587 +2024-11-22 12:23:10.762458: Pseudo dice [0.8499] +2024-11-22 12:23:10.762543: Epoch time: 18.68 s +2024-11-22 12:23:11.647755: +2024-11-22 12:23:11.647966: Epoch 4781 +2024-11-22 12:23:11.648079: Current learning rate: 0.00441 +2024-11-22 12:23:30.715436: train_loss -0.7932 +2024-11-22 12:23:30.715662: val_loss -0.7684 +2024-11-22 12:23:30.715736: Pseudo dice [0.8516] +2024-11-22 12:23:30.715814: Epoch time: 19.07 s +2024-11-22 12:23:31.621413: +2024-11-22 12:23:31.621638: Epoch 4782 +2024-11-22 12:23:31.621752: Current learning rate: 0.00441 +2024-11-22 12:23:49.226376: train_loss -0.7845 +2024-11-22 12:23:49.226603: val_loss -0.7804 +2024-11-22 12:23:49.226676: Pseudo dice [0.8516] +2024-11-22 12:23:49.226750: Epoch time: 17.61 s +2024-11-22 12:23:50.273323: +2024-11-22 12:23:50.273537: Epoch 4783 +2024-11-22 12:23:50.273647: Current learning rate: 0.0044 +2024-11-22 12:24:08.964346: train_loss -0.7827 +2024-11-22 12:24:08.964580: val_loss -0.7893 +2024-11-22 12:24:08.964678: Pseudo dice [0.8489] +2024-11-22 12:24:08.964759: Epoch time: 18.69 s +2024-11-22 12:24:09.844809: +2024-11-22 12:24:09.845028: Epoch 4784 +2024-11-22 12:24:09.845134: Current learning rate: 0.0044 +2024-11-22 12:24:28.433523: train_loss -0.8015 +2024-11-22 12:24:28.433791: val_loss -0.7722 +2024-11-22 12:24:28.433881: Pseudo dice [0.8623] +2024-11-22 12:24:28.434022: Epoch time: 18.59 s +2024-11-22 12:24:29.324134: +2024-11-22 12:24:29.324344: Epoch 4785 +2024-11-22 12:24:29.324455: Current learning rate: 0.0044 +2024-11-22 12:24:47.913564: train_loss -0.8008 +2024-11-22 12:24:47.913774: val_loss -0.7529 +2024-11-22 12:24:47.913849: Pseudo dice [0.8425] +2024-11-22 12:24:47.913925: Epoch time: 18.59 s +2024-11-22 12:24:48.806211: +2024-11-22 12:24:48.806433: Epoch 4786 +2024-11-22 12:24:48.806551: Current learning rate: 0.0044 +2024-11-22 12:25:08.517441: train_loss -0.7909 +2024-11-22 12:25:08.517655: val_loss -0.7879 +2024-11-22 12:25:08.517730: Pseudo dice [0.8427] +2024-11-22 12:25:08.517853: Epoch time: 19.71 s +2024-11-22 12:25:09.409631: +2024-11-22 12:25:09.409836: Epoch 4787 +2024-11-22 12:25:09.409940: Current learning rate: 0.0044 +2024-11-22 12:25:27.756257: train_loss -0.7704 +2024-11-22 12:25:27.756526: val_loss -0.73 +2024-11-22 12:25:27.756604: Pseudo dice [0.8132] +2024-11-22 12:25:27.756691: Epoch time: 18.35 s +2024-11-22 12:25:28.644749: +2024-11-22 12:25:28.644951: Epoch 4788 +2024-11-22 12:25:28.645067: Current learning rate: 0.0044 +2024-11-22 12:25:47.556323: train_loss -0.7799 +2024-11-22 12:25:47.556539: val_loss -0.7684 +2024-11-22 12:25:47.556615: Pseudo dice [0.8414] +2024-11-22 12:25:47.558870: Epoch time: 18.91 s +2024-11-22 12:25:48.620260: +2024-11-22 12:25:48.620488: Epoch 4789 +2024-11-22 12:25:48.620598: Current learning rate: 0.0044 +2024-11-22 12:26:07.844892: train_loss -0.7899 +2024-11-22 12:26:07.845118: val_loss -0.7678 +2024-11-22 12:26:07.845194: Pseudo dice [0.8387] +2024-11-22 12:26:07.845270: Epoch time: 19.23 s +2024-11-22 12:26:08.737249: +2024-11-22 12:26:08.737469: Epoch 4790 +2024-11-22 12:26:08.737580: Current learning rate: 0.0044 +2024-11-22 12:26:26.749360: train_loss -0.7834 +2024-11-22 12:26:26.749570: val_loss -0.7661 +2024-11-22 12:26:26.749643: Pseudo dice [0.8481] +2024-11-22 12:26:26.749724: Epoch time: 18.01 s +2024-11-22 12:26:27.618631: +2024-11-22 12:26:27.618867: Epoch 4791 +2024-11-22 12:26:27.619023: Current learning rate: 0.00439 +2024-11-22 12:26:46.989186: train_loss -0.7828 +2024-11-22 12:26:46.989406: val_loss -0.7679 +2024-11-22 12:26:46.989478: Pseudo dice [0.8263] +2024-11-22 12:26:46.989556: Epoch time: 19.37 s +2024-11-22 12:26:48.330535: +2024-11-22 12:26:48.330770: Epoch 4792 +2024-11-22 12:26:48.330878: Current learning rate: 0.00439 +2024-11-22 12:27:06.969075: train_loss -0.7676 +2024-11-22 12:27:06.969296: val_loss -0.7275 +2024-11-22 12:27:06.969370: Pseudo dice [0.7975] +2024-11-22 12:27:06.969443: Epoch time: 18.64 s +2024-11-22 12:27:07.896190: +2024-11-22 12:27:07.896453: Epoch 4793 +2024-11-22 12:27:07.896567: Current learning rate: 0.00439 +2024-11-22 12:27:26.408489: train_loss -0.7702 +2024-11-22 12:27:26.408803: val_loss -0.762 +2024-11-22 12:27:26.408880: Pseudo dice [0.8488] +2024-11-22 12:27:26.408962: Epoch time: 18.51 s +2024-11-22 12:27:27.324263: +2024-11-22 12:27:27.324490: Epoch 4794 +2024-11-22 12:27:27.324598: Current learning rate: 0.00439 +2024-11-22 12:27:46.556576: train_loss -0.7642 +2024-11-22 12:27:46.556827: val_loss -0.7654 +2024-11-22 12:27:46.556902: Pseudo dice [0.8275] +2024-11-22 12:27:46.556983: Epoch time: 19.23 s +2024-11-22 12:27:47.442152: +2024-11-22 12:27:47.442385: Epoch 4795 +2024-11-22 12:27:47.442498: Current learning rate: 0.00439 +2024-11-22 12:28:05.665844: train_loss -0.7698 +2024-11-22 12:28:05.666078: val_loss -0.7664 +2024-11-22 12:28:05.666206: Pseudo dice [0.8297] +2024-11-22 12:28:05.666281: Epoch time: 18.22 s +2024-11-22 12:28:06.561831: +2024-11-22 12:28:06.562147: Epoch 4796 +2024-11-22 12:28:06.562256: Current learning rate: 0.00439 +2024-11-22 12:28:25.573422: train_loss -0.7866 +2024-11-22 12:28:25.573636: val_loss -0.7753 +2024-11-22 12:28:25.573736: Pseudo dice [0.8414] +2024-11-22 12:28:25.573811: Epoch time: 19.01 s +2024-11-22 12:28:26.476546: +2024-11-22 12:28:26.476778: Epoch 4797 +2024-11-22 12:28:26.476906: Current learning rate: 0.00439 +2024-11-22 12:28:44.272793: train_loss -0.7863 +2024-11-22 12:28:44.273042: val_loss -0.7666 +2024-11-22 12:28:44.273116: Pseudo dice [0.8321] +2024-11-22 12:28:44.273200: Epoch time: 17.8 s +2024-11-22 12:28:45.191640: +2024-11-22 12:28:45.191871: Epoch 4798 +2024-11-22 12:28:45.191986: Current learning rate: 0.00439 +2024-11-22 12:29:04.110306: train_loss -0.7817 +2024-11-22 12:29:04.110520: val_loss -0.7702 +2024-11-22 12:29:04.110830: Pseudo dice [0.8456] +2024-11-22 12:29:04.110907: Epoch time: 18.92 s +2024-11-22 12:29:05.031142: +2024-11-22 12:29:05.031361: Epoch 4799 +2024-11-22 12:29:05.031477: Current learning rate: 0.00439 +2024-11-22 12:29:24.614248: train_loss -0.7808 +2024-11-22 12:29:24.614460: val_loss -0.7496 +2024-11-22 12:29:24.614542: Pseudo dice [0.8492] +2024-11-22 12:29:24.614617: Epoch time: 19.58 s +2024-11-22 12:29:25.782248: +2024-11-22 12:29:25.782513: Epoch 4800 +2024-11-22 12:29:25.782624: Current learning rate: 0.00438 +2024-11-22 12:29:44.019970: train_loss -0.7979 +2024-11-22 12:29:44.020191: val_loss -0.7719 +2024-11-22 12:29:44.020323: Pseudo dice [0.8422] +2024-11-22 12:29:44.020399: Epoch time: 18.24 s +2024-11-22 12:29:44.891517: +2024-11-22 12:29:44.891768: Epoch 4801 +2024-11-22 12:29:44.891885: Current learning rate: 0.00438 +2024-11-22 12:30:02.926000: train_loss -0.7846 +2024-11-22 12:30:02.926247: val_loss -0.7734 +2024-11-22 12:30:02.926323: Pseudo dice [0.8437] +2024-11-22 12:30:02.926415: Epoch time: 18.04 s +2024-11-22 12:30:03.981706: +2024-11-22 12:30:03.982111: Epoch 4802 +2024-11-22 12:30:03.982238: Current learning rate: 0.00438 +2024-11-22 12:30:21.947650: train_loss -0.794 +2024-11-22 12:30:21.947882: val_loss -0.7592 +2024-11-22 12:30:21.947957: Pseudo dice [0.8334] +2024-11-22 12:30:21.948068: Epoch time: 17.97 s +2024-11-22 12:30:22.826272: +2024-11-22 12:30:22.826659: Epoch 4803 +2024-11-22 12:30:22.826790: Current learning rate: 0.00438 +2024-11-22 12:30:41.146178: train_loss -0.7953 +2024-11-22 12:30:41.146657: val_loss -0.7772 +2024-11-22 12:30:41.146759: Pseudo dice [0.8467] +2024-11-22 12:30:41.146842: Epoch time: 18.32 s +2024-11-22 12:30:42.028908: +2024-11-22 12:30:42.029170: Epoch 4804 +2024-11-22 12:30:42.029316: Current learning rate: 0.00438 +2024-11-22 12:31:00.191602: train_loss -0.7955 +2024-11-22 12:31:00.191833: val_loss -0.7884 +2024-11-22 12:31:00.191910: Pseudo dice [0.8601] +2024-11-22 12:31:00.191987: Epoch time: 18.16 s +2024-11-22 12:31:01.110515: +2024-11-22 12:31:01.110739: Epoch 4805 +2024-11-22 12:31:01.110845: Current learning rate: 0.00438 +2024-11-22 12:31:19.850652: train_loss -0.7898 +2024-11-22 12:31:19.850865: val_loss -0.7843 +2024-11-22 12:31:19.850938: Pseudo dice [0.8513] +2024-11-22 12:31:19.851017: Epoch time: 18.74 s +2024-11-22 12:31:20.736822: +2024-11-22 12:31:20.737033: Epoch 4806 +2024-11-22 12:31:20.737144: Current learning rate: 0.00438 +2024-11-22 12:31:39.528057: train_loss -0.7957 +2024-11-22 12:31:39.528337: val_loss -0.7914 +2024-11-22 12:31:39.528414: Pseudo dice [0.8506] +2024-11-22 12:31:39.528497: Epoch time: 18.79 s +2024-11-22 12:31:40.424225: +2024-11-22 12:31:40.424432: Epoch 4807 +2024-11-22 12:31:40.424539: Current learning rate: 0.00438 +2024-11-22 12:31:59.361507: train_loss -0.7916 +2024-11-22 12:31:59.361771: val_loss -0.7706 +2024-11-22 12:31:59.361849: Pseudo dice [0.8399] +2024-11-22 12:31:59.361932: Epoch time: 18.94 s +2024-11-22 12:32:00.255267: +2024-11-22 12:32:00.255478: Epoch 4808 +2024-11-22 12:32:00.255587: Current learning rate: 0.00437 +2024-11-22 12:32:18.459900: train_loss -0.7947 +2024-11-22 12:32:18.460148: val_loss -0.7777 +2024-11-22 12:32:18.460257: Pseudo dice [0.8484] +2024-11-22 12:32:18.460362: Epoch time: 18.21 s +2024-11-22 12:32:19.335215: +2024-11-22 12:32:19.335438: Epoch 4809 +2024-11-22 12:32:19.335548: Current learning rate: 0.00437 +2024-11-22 12:32:37.634935: train_loss -0.7886 +2024-11-22 12:32:37.635183: val_loss -0.7668 +2024-11-22 12:32:37.635262: Pseudo dice [0.8433] +2024-11-22 12:32:37.635338: Epoch time: 18.3 s +2024-11-22 12:32:38.522553: +2024-11-22 12:32:38.522886: Epoch 4810 +2024-11-22 12:32:38.523007: Current learning rate: 0.00437 +2024-11-22 12:32:56.723440: train_loss -0.7918 +2024-11-22 12:32:56.723660: val_loss -0.766 +2024-11-22 12:32:56.723738: Pseudo dice [0.8544] +2024-11-22 12:32:56.723819: Epoch time: 18.2 s +2024-11-22 12:32:57.763513: +2024-11-22 12:32:57.763733: Epoch 4811 +2024-11-22 12:32:57.763860: Current learning rate: 0.00437 +2024-11-22 12:33:15.664163: train_loss -0.7956 +2024-11-22 12:33:15.664400: val_loss -0.7776 +2024-11-22 12:33:15.664474: Pseudo dice [0.856] +2024-11-22 12:33:15.664555: Epoch time: 17.9 s +2024-11-22 12:33:16.541250: +2024-11-22 12:33:16.541482: Epoch 4812 +2024-11-22 12:33:16.541589: Current learning rate: 0.00437 +2024-11-22 12:33:35.154638: train_loss -0.8009 +2024-11-22 12:33:35.154850: val_loss -0.7726 +2024-11-22 12:33:35.154924: Pseudo dice [0.8497] +2024-11-22 12:33:35.155007: Epoch time: 18.61 s +2024-11-22 12:33:36.072240: +2024-11-22 12:33:36.072457: Epoch 4813 +2024-11-22 12:33:36.072571: Current learning rate: 0.00437 +2024-11-22 12:33:55.346915: train_loss -0.7767 +2024-11-22 12:33:55.347184: val_loss -0.7801 +2024-11-22 12:33:55.347264: Pseudo dice [0.8519] +2024-11-22 12:33:55.347343: Epoch time: 19.28 s +2024-11-22 12:33:56.238718: +2024-11-22 12:33:56.238997: Epoch 4814 +2024-11-22 12:33:56.239106: Current learning rate: 0.00437 +2024-11-22 12:34:15.214423: train_loss -0.7779 +2024-11-22 12:34:15.214669: val_loss -0.7687 +2024-11-22 12:34:15.214749: Pseudo dice [0.8606] +2024-11-22 12:34:15.214847: Epoch time: 18.98 s +2024-11-22 12:34:16.497754: +2024-11-22 12:34:16.497959: Epoch 4815 +2024-11-22 12:34:16.498072: Current learning rate: 0.00437 +2024-11-22 12:34:33.837447: train_loss -0.7787 +2024-11-22 12:34:33.837698: val_loss -0.7709 +2024-11-22 12:34:33.837776: Pseudo dice [0.8434] +2024-11-22 12:34:33.837850: Epoch time: 17.34 s +2024-11-22 12:34:34.717849: +2024-11-22 12:34:34.718080: Epoch 4816 +2024-11-22 12:34:34.718187: Current learning rate: 0.00436 +2024-11-22 12:34:53.081065: train_loss -0.7903 +2024-11-22 12:34:53.081322: val_loss -0.7748 +2024-11-22 12:34:53.081400: Pseudo dice [0.8616] +2024-11-22 12:34:53.081476: Epoch time: 18.36 s +2024-11-22 12:34:53.970683: +2024-11-22 12:34:53.970885: Epoch 4817 +2024-11-22 12:34:53.970996: Current learning rate: 0.00436 +2024-11-22 12:35:12.682111: train_loss -0.7865 +2024-11-22 12:35:12.682364: val_loss -0.7686 +2024-11-22 12:35:12.682451: Pseudo dice [0.8493] +2024-11-22 12:35:12.682539: Epoch time: 18.71 s +2024-11-22 12:35:13.564670: +2024-11-22 12:35:13.564919: Epoch 4818 +2024-11-22 12:35:13.565036: Current learning rate: 0.00436 +2024-11-22 12:35:31.390754: train_loss -0.784 +2024-11-22 12:35:31.390968: val_loss -0.7779 +2024-11-22 12:35:31.391071: Pseudo dice [0.8335] +2024-11-22 12:35:31.391146: Epoch time: 17.83 s +2024-11-22 12:35:32.265698: +2024-11-22 12:35:32.265933: Epoch 4819 +2024-11-22 12:35:32.266047: Current learning rate: 0.00436 +2024-11-22 12:35:51.670902: train_loss -0.7804 +2024-11-22 12:35:51.671120: val_loss -0.7784 +2024-11-22 12:35:51.671198: Pseudo dice [0.8426] +2024-11-22 12:35:51.671270: Epoch time: 19.41 s +2024-11-22 12:35:52.549057: +2024-11-22 12:35:52.549268: Epoch 4820 +2024-11-22 12:35:52.549379: Current learning rate: 0.00436 +2024-11-22 12:36:10.847728: train_loss -0.7895 +2024-11-22 12:36:10.847945: val_loss -0.7578 +2024-11-22 12:36:10.848030: Pseudo dice [0.8277] +2024-11-22 12:36:10.848111: Epoch time: 18.3 s +2024-11-22 12:36:11.771935: +2024-11-22 12:36:11.772144: Epoch 4821 +2024-11-22 12:36:11.772248: Current learning rate: 0.00436 +2024-11-22 12:36:30.083230: train_loss -0.7911 +2024-11-22 12:36:30.083471: val_loss -0.7685 +2024-11-22 12:36:30.083547: Pseudo dice [0.8496] +2024-11-22 12:36:30.083629: Epoch time: 18.31 s +2024-11-22 12:36:30.989106: +2024-11-22 12:36:30.989314: Epoch 4822 +2024-11-22 12:36:30.989423: Current learning rate: 0.00436 +2024-11-22 12:36:48.320701: train_loss -0.789 +2024-11-22 12:36:48.320921: val_loss -0.7762 +2024-11-22 12:36:48.321008: Pseudo dice [0.8291] +2024-11-22 12:36:48.321086: Epoch time: 17.33 s +2024-11-22 12:36:49.192096: +2024-11-22 12:36:49.192286: Epoch 4823 +2024-11-22 12:36:49.192396: Current learning rate: 0.00436 +2024-11-22 12:37:07.318976: train_loss -0.7867 +2024-11-22 12:37:07.319197: val_loss -0.7703 +2024-11-22 12:37:07.319271: Pseudo dice [0.8569] +2024-11-22 12:37:07.319347: Epoch time: 18.13 s +2024-11-22 12:37:08.217922: +2024-11-22 12:37:08.218574: Epoch 4824 +2024-11-22 12:37:08.218693: Current learning rate: 0.00435 +2024-11-22 12:37:27.789953: train_loss -0.79 +2024-11-22 12:37:27.790169: val_loss -0.7777 +2024-11-22 12:37:27.792477: Pseudo dice [0.8582] +2024-11-22 12:37:27.792602: Epoch time: 19.57 s +2024-11-22 12:37:28.795045: +2024-11-22 12:37:28.795259: Epoch 4825 +2024-11-22 12:37:28.795369: Current learning rate: 0.00435 +2024-11-22 12:37:46.967200: train_loss -0.795 +2024-11-22 12:37:46.967435: val_loss -0.7709 +2024-11-22 12:37:46.967553: Pseudo dice [0.8446] +2024-11-22 12:37:46.967636: Epoch time: 18.17 s +2024-11-22 12:37:47.848391: +2024-11-22 12:37:47.848706: Epoch 4826 +2024-11-22 12:37:47.848811: Current learning rate: 0.00435 +2024-11-22 12:38:05.545182: train_loss -0.7971 +2024-11-22 12:38:05.545399: val_loss -0.7798 +2024-11-22 12:38:05.545501: Pseudo dice [0.847] +2024-11-22 12:38:05.545575: Epoch time: 17.7 s +2024-11-22 12:38:06.811766: +2024-11-22 12:38:06.812000: Epoch 4827 +2024-11-22 12:38:06.812112: Current learning rate: 0.00435 +2024-11-22 12:38:24.569678: train_loss -0.7944 +2024-11-22 12:38:24.569936: val_loss -0.7834 +2024-11-22 12:38:24.570025: Pseudo dice [0.8576] +2024-11-22 12:38:24.570113: Epoch time: 17.76 s +2024-11-22 12:38:25.453230: +2024-11-22 12:38:25.453449: Epoch 4828 +2024-11-22 12:38:25.453559: Current learning rate: 0.00435 +2024-11-22 12:38:44.864786: train_loss -0.8015 +2024-11-22 12:38:44.865009: val_loss -0.7586 +2024-11-22 12:38:44.865173: Pseudo dice [0.8511] +2024-11-22 12:38:44.865250: Epoch time: 19.41 s +2024-11-22 12:38:45.742203: +2024-11-22 12:38:45.742423: Epoch 4829 +2024-11-22 12:38:45.742532: Current learning rate: 0.00435 +2024-11-22 12:39:04.150613: train_loss -0.7921 +2024-11-22 12:39:04.151500: val_loss -0.7656 +2024-11-22 12:39:04.151634: Pseudo dice [0.8337] +2024-11-22 12:39:04.151719: Epoch time: 18.41 s +2024-11-22 12:39:05.095091: +2024-11-22 12:39:05.095316: Epoch 4830 +2024-11-22 12:39:05.095424: Current learning rate: 0.00435 +2024-11-22 12:39:22.873284: train_loss -0.799 +2024-11-22 12:39:22.873496: val_loss -0.7681 +2024-11-22 12:39:22.873572: Pseudo dice [0.8464] +2024-11-22 12:39:22.873652: Epoch time: 17.78 s +2024-11-22 12:39:23.753353: +2024-11-22 12:39:23.753609: Epoch 4831 +2024-11-22 12:39:23.753754: Current learning rate: 0.00435 +2024-11-22 12:39:42.850476: train_loss -0.7909 +2024-11-22 12:39:42.850724: val_loss -0.7647 +2024-11-22 12:39:42.854514: Pseudo dice [0.8572] +2024-11-22 12:39:42.854685: Epoch time: 19.1 s +2024-11-22 12:39:43.756357: +2024-11-22 12:39:43.756554: Epoch 4832 +2024-11-22 12:39:43.756664: Current learning rate: 0.00434 +2024-11-22 12:40:01.650056: train_loss -0.7973 +2024-11-22 12:40:01.650277: val_loss -0.7884 +2024-11-22 12:40:01.650354: Pseudo dice [0.8373] +2024-11-22 12:40:01.650431: Epoch time: 17.89 s +2024-11-22 12:40:02.530824: +2024-11-22 12:40:02.531052: Epoch 4833 +2024-11-22 12:40:02.531164: Current learning rate: 0.00434 +2024-11-22 12:40:21.567914: train_loss -0.7947 +2024-11-22 12:40:21.568148: val_loss -0.779 +2024-11-22 12:40:21.568223: Pseudo dice [0.8532] +2024-11-22 12:40:21.568298: Epoch time: 19.04 s +2024-11-22 12:40:22.539101: +2024-11-22 12:40:22.539316: Epoch 4834 +2024-11-22 12:40:22.539425: Current learning rate: 0.00434 +2024-11-22 12:40:41.445657: train_loss -0.7923 +2024-11-22 12:40:41.445961: val_loss -0.7404 +2024-11-22 12:40:41.446047: Pseudo dice [0.8249] +2024-11-22 12:40:41.446135: Epoch time: 18.91 s +2024-11-22 12:40:42.365101: +2024-11-22 12:40:42.365307: Epoch 4835 +2024-11-22 12:40:42.365418: Current learning rate: 0.00434 +2024-11-22 12:41:00.148015: train_loss -0.7844 +2024-11-22 12:41:00.148232: val_loss -0.7753 +2024-11-22 12:41:00.148305: Pseudo dice [0.8604] +2024-11-22 12:41:00.148379: Epoch time: 17.78 s +2024-11-22 12:41:01.034790: +2024-11-22 12:41:01.035021: Epoch 4836 +2024-11-22 12:41:01.035132: Current learning rate: 0.00434 +2024-11-22 12:41:19.998025: train_loss -0.7899 +2024-11-22 12:41:19.998260: val_loss -0.7783 +2024-11-22 12:41:19.998336: Pseudo dice [0.8525] +2024-11-22 12:41:20.021855: Epoch time: 18.96 s +2024-11-22 12:41:20.925634: +2024-11-22 12:41:20.925826: Epoch 4837 +2024-11-22 12:41:20.925938: Current learning rate: 0.00434 +2024-11-22 12:41:39.013320: train_loss -0.7991 +2024-11-22 12:41:39.013531: val_loss -0.7791 +2024-11-22 12:41:39.013605: Pseudo dice [0.8501] +2024-11-22 12:41:39.013683: Epoch time: 18.09 s +2024-11-22 12:41:39.905939: +2024-11-22 12:41:39.906142: Epoch 4838 +2024-11-22 12:41:39.906253: Current learning rate: 0.00434 +2024-11-22 12:41:58.443969: train_loss -0.8015 +2024-11-22 12:41:58.444212: val_loss -0.7605 +2024-11-22 12:41:58.444291: Pseudo dice [0.8437] +2024-11-22 12:41:58.444376: Epoch time: 18.54 s +2024-11-22 12:41:59.737079: +2024-11-22 12:41:59.737310: Epoch 4839 +2024-11-22 12:41:59.737432: Current learning rate: 0.00434 +2024-11-22 12:42:17.835768: train_loss -0.7989 +2024-11-22 12:42:17.835978: val_loss -0.7928 +2024-11-22 12:42:17.836055: Pseudo dice [0.86] +2024-11-22 12:42:17.836130: Epoch time: 18.1 s +2024-11-22 12:42:18.701407: +2024-11-22 12:42:18.701618: Epoch 4840 +2024-11-22 12:42:18.701731: Current learning rate: 0.00433 +2024-11-22 12:42:37.344502: train_loss -0.7681 +2024-11-22 12:42:37.344712: val_loss -0.7619 +2024-11-22 12:42:37.344789: Pseudo dice [0.8354] +2024-11-22 12:42:37.344866: Epoch time: 18.64 s +2024-11-22 12:42:38.233042: +2024-11-22 12:42:38.233259: Epoch 4841 +2024-11-22 12:42:38.233367: Current learning rate: 0.00433 +2024-11-22 12:42:58.232533: train_loss -0.7846 +2024-11-22 12:42:58.232775: val_loss -0.7824 +2024-11-22 12:42:58.232852: Pseudo dice [0.8547] +2024-11-22 12:42:58.232933: Epoch time: 20.0 s +2024-11-22 12:42:59.121005: +2024-11-22 12:42:59.121226: Epoch 4842 +2024-11-22 12:42:59.121338: Current learning rate: 0.00433 +2024-11-22 12:43:18.689952: train_loss -0.7905 +2024-11-22 12:43:18.690174: val_loss -0.7706 +2024-11-22 12:43:18.690272: Pseudo dice [0.834] +2024-11-22 12:43:18.690356: Epoch time: 19.57 s +2024-11-22 12:43:19.569917: +2024-11-22 12:43:19.570137: Epoch 4843 +2024-11-22 12:43:19.570250: Current learning rate: 0.00433 +2024-11-22 12:43:37.677438: train_loss -0.7855 +2024-11-22 12:43:37.677652: val_loss -0.7631 +2024-11-22 12:43:37.677736: Pseudo dice [0.8353] +2024-11-22 12:43:37.677816: Epoch time: 18.11 s +2024-11-22 12:43:38.560302: +2024-11-22 12:43:38.560507: Epoch 4844 +2024-11-22 12:43:38.560616: Current learning rate: 0.00433 +2024-11-22 12:43:58.002697: train_loss -0.7842 +2024-11-22 12:43:58.002912: val_loss -0.7703 +2024-11-22 12:43:58.002987: Pseudo dice [0.8526] +2024-11-22 12:43:58.003107: Epoch time: 19.44 s +2024-11-22 12:43:58.888145: +2024-11-22 12:43:58.888355: Epoch 4845 +2024-11-22 12:43:58.888463: Current learning rate: 0.00433 +2024-11-22 12:44:17.045669: train_loss -0.7823 +2024-11-22 12:44:17.045921: val_loss -0.7792 +2024-11-22 12:44:17.046012: Pseudo dice [0.8549] +2024-11-22 12:44:17.046103: Epoch time: 18.16 s +2024-11-22 12:44:17.931113: +2024-11-22 12:44:17.931316: Epoch 4846 +2024-11-22 12:44:17.931423: Current learning rate: 0.00433 +2024-11-22 12:44:37.322104: train_loss -0.7931 +2024-11-22 12:44:37.324511: val_loss -0.7747 +2024-11-22 12:44:37.324643: Pseudo dice [0.8611] +2024-11-22 12:44:37.324722: Epoch time: 19.39 s +2024-11-22 12:44:38.244014: +2024-11-22 12:44:38.244240: Epoch 4847 +2024-11-22 12:44:38.244345: Current learning rate: 0.00433 +2024-11-22 12:44:57.074886: train_loss -0.7952 +2024-11-22 12:44:57.075108: val_loss -0.7467 +2024-11-22 12:44:57.075182: Pseudo dice [0.8426] +2024-11-22 12:44:57.075255: Epoch time: 18.83 s +2024-11-22 12:44:57.954141: +2024-11-22 12:44:57.954368: Epoch 4848 +2024-11-22 12:44:57.954485: Current learning rate: 0.00432 +2024-11-22 12:45:16.506663: train_loss -0.798 +2024-11-22 12:45:16.506931: val_loss -0.7761 +2024-11-22 12:45:16.507021: Pseudo dice [0.8628] +2024-11-22 12:45:16.507101: Epoch time: 18.55 s +2024-11-22 12:45:17.381996: +2024-11-22 12:45:17.382224: Epoch 4849 +2024-11-22 12:45:17.382337: Current learning rate: 0.00432 +2024-11-22 12:45:34.009915: train_loss -0.8003 +2024-11-22 12:45:34.034374: val_loss -0.7614 +2024-11-22 12:45:34.034503: Pseudo dice [0.8352] +2024-11-22 12:45:34.034590: Epoch time: 16.63 s +2024-11-22 12:45:35.183857: +2024-11-22 12:45:35.184069: Epoch 4850 +2024-11-22 12:45:35.184184: Current learning rate: 0.00432 +2024-11-22 12:45:53.914599: train_loss -0.8044 +2024-11-22 12:45:53.915098: val_loss -0.765 +2024-11-22 12:45:53.915204: Pseudo dice [0.8249] +2024-11-22 12:45:53.915286: Epoch time: 18.73 s +2024-11-22 12:45:54.797174: +2024-11-22 12:45:54.797395: Epoch 4851 +2024-11-22 12:45:54.797506: Current learning rate: 0.00432 +2024-11-22 12:46:12.808132: train_loss -0.7958 +2024-11-22 12:46:12.808357: val_loss -0.7748 +2024-11-22 12:46:12.808434: Pseudo dice [0.8585] +2024-11-22 12:46:12.808513: Epoch time: 18.01 s +2024-11-22 12:46:13.696869: +2024-11-22 12:46:13.697314: Epoch 4852 +2024-11-22 12:46:13.697426: Current learning rate: 0.00432 +2024-11-22 12:46:31.810067: train_loss -0.7924 +2024-11-22 12:46:31.810306: val_loss -0.7914 +2024-11-22 12:46:31.810382: Pseudo dice [0.8654] +2024-11-22 12:46:31.810462: Epoch time: 18.11 s +2024-11-22 12:46:32.693105: +2024-11-22 12:46:32.693323: Epoch 4853 +2024-11-22 12:46:32.693429: Current learning rate: 0.00432 +2024-11-22 12:46:50.946720: train_loss -0.7941 +2024-11-22 12:46:50.946943: val_loss -0.7737 +2024-11-22 12:46:50.947031: Pseudo dice [0.8417] +2024-11-22 12:46:50.947108: Epoch time: 18.25 s +2024-11-22 12:46:51.845960: +2024-11-22 12:46:51.846169: Epoch 4854 +2024-11-22 12:46:51.846282: Current learning rate: 0.00432 +2024-11-22 12:47:10.622218: train_loss -0.8033 +2024-11-22 12:47:10.622439: val_loss -0.7581 +2024-11-22 12:47:10.622515: Pseudo dice [0.8566] +2024-11-22 12:47:10.622592: Epoch time: 18.78 s +2024-11-22 12:47:11.525662: +2024-11-22 12:47:11.525957: Epoch 4855 +2024-11-22 12:47:11.526074: Current learning rate: 0.00432 +2024-11-22 12:47:29.206911: train_loss -0.7952 +2024-11-22 12:47:29.207147: val_loss -0.7732 +2024-11-22 12:47:29.207223: Pseudo dice [0.845] +2024-11-22 12:47:29.207304: Epoch time: 17.68 s +2024-11-22 12:47:30.124119: +2024-11-22 12:47:30.124354: Epoch 4856 +2024-11-22 12:47:30.124496: Current learning rate: 0.00431 +2024-11-22 12:47:48.389414: train_loss -0.7915 +2024-11-22 12:47:48.389670: val_loss -0.7983 +2024-11-22 12:47:48.389743: Pseudo dice [0.864] +2024-11-22 12:47:48.390084: Epoch time: 18.27 s +2024-11-22 12:47:49.273123: +2024-11-22 12:47:49.273339: Epoch 4857 +2024-11-22 12:47:49.273450: Current learning rate: 0.00431 +2024-11-22 12:48:06.970692: train_loss -0.7993 +2024-11-22 12:48:06.970901: val_loss -0.7672 +2024-11-22 12:48:06.970973: Pseudo dice [0.8512] +2024-11-22 12:48:06.971056: Epoch time: 17.7 s +2024-11-22 12:48:07.869177: +2024-11-22 12:48:07.869381: Epoch 4858 +2024-11-22 12:48:07.869490: Current learning rate: 0.00431 +2024-11-22 12:48:25.590229: train_loss -0.7983 +2024-11-22 12:48:25.590456: val_loss -0.7703 +2024-11-22 12:48:25.590537: Pseudo dice [0.8234] +2024-11-22 12:48:25.590619: Epoch time: 17.72 s +2024-11-22 12:48:26.502836: +2024-11-22 12:48:26.503043: Epoch 4859 +2024-11-22 12:48:26.503153: Current learning rate: 0.00431 +2024-11-22 12:48:44.567106: train_loss -0.7917 +2024-11-22 12:48:44.567350: val_loss -0.769 +2024-11-22 12:48:44.567437: Pseudo dice [0.8308] +2024-11-22 12:48:44.567524: Epoch time: 18.07 s +2024-11-22 12:48:45.444147: +2024-11-22 12:48:45.444357: Epoch 4860 +2024-11-22 12:48:45.444460: Current learning rate: 0.00431 +2024-11-22 12:49:04.231958: train_loss -0.7869 +2024-11-22 12:49:04.232174: val_loss -0.7483 +2024-11-22 12:49:04.232248: Pseudo dice [0.8419] +2024-11-22 12:49:04.232321: Epoch time: 18.79 s +2024-11-22 12:49:05.104345: +2024-11-22 12:49:05.104557: Epoch 4861 +2024-11-22 12:49:05.104672: Current learning rate: 0.00431 +2024-11-22 12:49:23.484371: train_loss -0.7894 +2024-11-22 12:49:23.484586: val_loss -0.7785 +2024-11-22 12:49:23.484663: Pseudo dice [0.8582] +2024-11-22 12:49:23.484741: Epoch time: 18.38 s +2024-11-22 12:49:24.740682: +2024-11-22 12:49:24.740890: Epoch 4862 +2024-11-22 12:49:24.741011: Current learning rate: 0.00431 +2024-11-22 12:49:43.340235: train_loss -0.7918 +2024-11-22 12:49:43.340527: val_loss -0.783 +2024-11-22 12:49:43.340609: Pseudo dice [0.857] +2024-11-22 12:49:43.340704: Epoch time: 18.6 s +2024-11-22 12:49:44.231077: +2024-11-22 12:49:44.231320: Epoch 4863 +2024-11-22 12:49:44.231448: Current learning rate: 0.00431 +2024-11-22 12:50:03.589522: train_loss -0.7835 +2024-11-22 12:50:03.589742: val_loss -0.7611 +2024-11-22 12:50:03.589822: Pseudo dice [0.8201] +2024-11-22 12:50:03.589909: Epoch time: 19.36 s +2024-11-22 12:50:04.458714: +2024-11-22 12:50:04.458931: Epoch 4864 +2024-11-22 12:50:04.459042: Current learning rate: 0.0043 +2024-11-22 12:50:22.963171: train_loss -0.7906 +2024-11-22 12:50:22.963401: val_loss -0.7907 +2024-11-22 12:50:22.965663: Pseudo dice [0.845] +2024-11-22 12:50:22.965763: Epoch time: 18.51 s +2024-11-22 12:50:23.876913: +2024-11-22 12:50:23.877153: Epoch 4865 +2024-11-22 12:50:23.877265: Current learning rate: 0.0043 +2024-11-22 12:50:41.421286: train_loss -0.7949 +2024-11-22 12:50:41.421514: val_loss -0.769 +2024-11-22 12:50:41.421592: Pseudo dice [0.8469] +2024-11-22 12:50:41.421674: Epoch time: 17.55 s +2024-11-22 12:50:42.302065: +2024-11-22 12:50:42.302283: Epoch 4866 +2024-11-22 12:50:42.302390: Current learning rate: 0.0043 +2024-11-22 12:51:00.636553: train_loss -0.7786 +2024-11-22 12:51:00.636790: val_loss -0.7518 +2024-11-22 12:51:00.636864: Pseudo dice [0.8294] +2024-11-22 12:51:00.636952: Epoch time: 18.34 s +2024-11-22 12:51:01.508701: +2024-11-22 12:51:01.508911: Epoch 4867 +2024-11-22 12:51:01.509032: Current learning rate: 0.0043 +2024-11-22 12:51:19.477354: train_loss -0.788 +2024-11-22 12:51:19.477569: val_loss -0.7772 +2024-11-22 12:51:19.477644: Pseudo dice [0.8416] +2024-11-22 12:51:19.477717: Epoch time: 17.97 s +2024-11-22 12:51:20.351138: +2024-11-22 12:51:20.351331: Epoch 4868 +2024-11-22 12:51:20.351438: Current learning rate: 0.0043 +2024-11-22 12:51:40.419003: train_loss -0.788 +2024-11-22 12:51:40.424390: val_loss -0.7476 +2024-11-22 12:51:40.424534: Pseudo dice [0.8547] +2024-11-22 12:51:40.424613: Epoch time: 20.07 s +2024-11-22 12:51:41.452070: +2024-11-22 12:51:41.452288: Epoch 4869 +2024-11-22 12:51:41.452395: Current learning rate: 0.0043 +2024-11-22 12:51:59.284737: train_loss -0.7967 +2024-11-22 12:51:59.284990: val_loss -0.7651 +2024-11-22 12:51:59.285081: Pseudo dice [0.8622] +2024-11-22 12:51:59.285176: Epoch time: 17.83 s +2024-11-22 12:52:00.166659: +2024-11-22 12:52:00.166890: Epoch 4870 +2024-11-22 12:52:00.167010: Current learning rate: 0.0043 +2024-11-22 12:52:19.212685: train_loss -0.7975 +2024-11-22 12:52:19.217170: val_loss -0.7652 +2024-11-22 12:52:19.217335: Pseudo dice [0.8357] +2024-11-22 12:52:19.217565: Epoch time: 19.05 s +2024-11-22 12:52:20.112471: +2024-11-22 12:52:20.112680: Epoch 4871 +2024-11-22 12:52:20.112791: Current learning rate: 0.0043 +2024-11-22 12:52:39.291706: train_loss -0.7967 +2024-11-22 12:52:39.291920: val_loss -0.7721 +2024-11-22 12:52:39.292002: Pseudo dice [0.8426] +2024-11-22 12:52:39.292077: Epoch time: 19.18 s +2024-11-22 12:52:40.171438: +2024-11-22 12:52:40.171711: Epoch 4872 +2024-11-22 12:52:40.171820: Current learning rate: 0.00429 +2024-11-22 12:52:58.109806: train_loss -0.7909 +2024-11-22 12:52:58.110084: val_loss -0.7911 +2024-11-22 12:52:58.110170: Pseudo dice [0.8604] +2024-11-22 12:52:58.110245: Epoch time: 17.94 s +2024-11-22 12:52:58.987433: +2024-11-22 12:52:58.987633: Epoch 4873 +2024-11-22 12:52:58.987738: Current learning rate: 0.00429 +2024-11-22 12:53:16.912118: train_loss -0.7978 +2024-11-22 12:53:16.912349: val_loss -0.765 +2024-11-22 12:53:16.912422: Pseudo dice [0.8333] +2024-11-22 12:53:16.912498: Epoch time: 17.93 s +2024-11-22 12:53:18.188903: +2024-11-22 12:53:18.189123: Epoch 4874 +2024-11-22 12:53:18.189239: Current learning rate: 0.00429 +2024-11-22 12:53:37.330254: train_loss -0.7941 +2024-11-22 12:53:37.330503: val_loss -0.7577 +2024-11-22 12:53:37.330580: Pseudo dice [0.8233] +2024-11-22 12:53:37.330653: Epoch time: 19.14 s +2024-11-22 12:53:38.215554: +2024-11-22 12:53:38.215780: Epoch 4875 +2024-11-22 12:53:38.215888: Current learning rate: 0.00429 +2024-11-22 12:53:56.748450: train_loss -0.794 +2024-11-22 12:53:56.748665: val_loss -0.7784 +2024-11-22 12:53:56.748745: Pseudo dice [0.8542] +2024-11-22 12:53:56.748827: Epoch time: 18.53 s +2024-11-22 12:53:57.628737: +2024-11-22 12:53:57.628975: Epoch 4876 +2024-11-22 12:53:57.629090: Current learning rate: 0.00429 +2024-11-22 12:54:15.726359: train_loss -0.7986 +2024-11-22 12:54:15.726608: val_loss -0.7522 +2024-11-22 12:54:15.726690: Pseudo dice [0.8404] +2024-11-22 12:54:15.726771: Epoch time: 18.1 s +2024-11-22 12:54:16.603778: +2024-11-22 12:54:16.604013: Epoch 4877 +2024-11-22 12:54:16.604129: Current learning rate: 0.00429 +2024-11-22 12:54:35.404202: train_loss -0.782 +2024-11-22 12:54:35.406600: val_loss -0.7627 +2024-11-22 12:54:35.406692: Pseudo dice [0.8404] +2024-11-22 12:54:35.406768: Epoch time: 18.8 s +2024-11-22 12:54:36.369119: +2024-11-22 12:54:36.369342: Epoch 4878 +2024-11-22 12:54:36.369449: Current learning rate: 0.00429 +2024-11-22 12:54:54.321834: train_loss -0.7923 +2024-11-22 12:54:54.322141: val_loss -0.7511 +2024-11-22 12:54:54.322217: Pseudo dice [0.8394] +2024-11-22 12:54:54.322290: Epoch time: 17.95 s +2024-11-22 12:54:55.204450: +2024-11-22 12:54:55.204649: Epoch 4879 +2024-11-22 12:54:55.204767: Current learning rate: 0.00429 +2024-11-22 12:55:13.991978: train_loss -0.7966 +2024-11-22 12:55:13.992332: val_loss -0.7685 +2024-11-22 12:55:13.992418: Pseudo dice [0.827] +2024-11-22 12:55:13.992505: Epoch time: 18.79 s +2024-11-22 12:55:14.904938: +2024-11-22 12:55:14.905203: Epoch 4880 +2024-11-22 12:55:14.905312: Current learning rate: 0.00429 +2024-11-22 12:55:33.176890: train_loss -0.7966 +2024-11-22 12:55:33.177159: val_loss -0.7866 +2024-11-22 12:55:33.177237: Pseudo dice [0.8549] +2024-11-22 12:55:33.177318: Epoch time: 18.27 s +2024-11-22 12:55:34.061917: +2024-11-22 12:55:34.062129: Epoch 4881 +2024-11-22 12:55:34.062239: Current learning rate: 0.00428 +2024-11-22 12:55:53.340229: train_loss -0.789 +2024-11-22 12:55:53.340443: val_loss -0.7806 +2024-11-22 12:55:53.340516: Pseudo dice [0.8355] +2024-11-22 12:55:53.340588: Epoch time: 19.28 s +2024-11-22 12:55:54.217103: +2024-11-22 12:55:54.217313: Epoch 4882 +2024-11-22 12:55:54.217425: Current learning rate: 0.00428 +2024-11-22 12:56:13.054176: train_loss -0.7814 +2024-11-22 12:56:13.054389: val_loss -0.7674 +2024-11-22 12:56:13.054466: Pseudo dice [0.8374] +2024-11-22 12:56:13.054759: Epoch time: 18.84 s +2024-11-22 12:56:13.938631: +2024-11-22 12:56:13.938919: Epoch 4883 +2024-11-22 12:56:13.939034: Current learning rate: 0.00428 +2024-11-22 12:56:32.272524: train_loss -0.7958 +2024-11-22 12:56:32.272831: val_loss -0.7454 +2024-11-22 12:56:32.272911: Pseudo dice [0.8456] +2024-11-22 12:56:32.273000: Epoch time: 18.33 s +2024-11-22 12:56:33.164475: +2024-11-22 12:56:33.164746: Epoch 4884 +2024-11-22 12:56:33.164857: Current learning rate: 0.00428 +2024-11-22 12:56:51.991192: train_loss -0.7939 +2024-11-22 12:56:51.991407: val_loss -0.7662 +2024-11-22 12:56:51.991479: Pseudo dice [0.8467] +2024-11-22 12:56:51.991551: Epoch time: 18.83 s +2024-11-22 12:56:52.862572: +2024-11-22 12:56:52.862790: Epoch 4885 +2024-11-22 12:56:52.862900: Current learning rate: 0.00428 +2024-11-22 12:57:11.244791: train_loss -0.7926 +2024-11-22 12:57:11.245043: val_loss -0.7719 +2024-11-22 12:57:11.245121: Pseudo dice [0.8312] +2024-11-22 12:57:11.245198: Epoch time: 18.38 s +2024-11-22 12:57:12.496936: +2024-11-22 12:57:12.497175: Epoch 4886 +2024-11-22 12:57:12.497289: Current learning rate: 0.00428 +2024-11-22 12:57:31.982001: train_loss -0.7906 +2024-11-22 12:57:31.982265: val_loss -0.7784 +2024-11-22 12:57:31.982341: Pseudo dice [0.8565] +2024-11-22 12:57:31.982424: Epoch time: 19.49 s +2024-11-22 12:57:32.867182: +2024-11-22 12:57:32.867411: Epoch 4887 +2024-11-22 12:57:32.867524: Current learning rate: 0.00428 +2024-11-22 12:57:50.505298: train_loss -0.7948 +2024-11-22 12:57:50.507684: val_loss -0.756 +2024-11-22 12:57:50.507810: Pseudo dice [0.8467] +2024-11-22 12:57:50.507891: Epoch time: 17.64 s +2024-11-22 12:57:51.461887: +2024-11-22 12:57:51.462204: Epoch 4888 +2024-11-22 12:57:51.462312: Current learning rate: 0.00428 +2024-11-22 12:58:09.911580: train_loss -0.7931 +2024-11-22 12:58:09.911807: val_loss -0.7435 +2024-11-22 12:58:09.911884: Pseudo dice [0.855] +2024-11-22 12:58:09.911961: Epoch time: 18.45 s +2024-11-22 12:58:10.788416: +2024-11-22 12:58:10.788634: Epoch 4889 +2024-11-22 12:58:10.788749: Current learning rate: 0.00427 +2024-11-22 12:58:28.954521: train_loss -0.7829 +2024-11-22 12:58:28.954742: val_loss -0.7241 +2024-11-22 12:58:28.954820: Pseudo dice [0.8224] +2024-11-22 12:58:28.954901: Epoch time: 18.17 s +2024-11-22 12:58:29.836024: +2024-11-22 12:58:29.836243: Epoch 4890 +2024-11-22 12:58:29.836354: Current learning rate: 0.00427 +2024-11-22 12:58:47.657934: train_loss -0.7857 +2024-11-22 12:58:47.658190: val_loss -0.7461 +2024-11-22 12:58:47.658266: Pseudo dice [0.8434] +2024-11-22 12:58:47.658352: Epoch time: 17.82 s +2024-11-22 12:58:48.543595: +2024-11-22 12:58:48.543821: Epoch 4891 +2024-11-22 12:58:48.544028: Current learning rate: 0.00427 +2024-11-22 12:59:07.610789: train_loss -0.7985 +2024-11-22 12:59:07.611014: val_loss -0.7525 +2024-11-22 12:59:07.611159: Pseudo dice [0.8513] +2024-11-22 12:59:07.611243: Epoch time: 19.07 s +2024-11-22 12:59:08.490725: +2024-11-22 12:59:08.491008: Epoch 4892 +2024-11-22 12:59:08.491118: Current learning rate: 0.00427 +2024-11-22 12:59:26.783705: train_loss -0.774 +2024-11-22 12:59:26.783927: val_loss -0.7866 +2024-11-22 12:59:26.784006: Pseudo dice [0.839] +2024-11-22 12:59:26.784080: Epoch time: 18.29 s +2024-11-22 12:59:27.698638: +2024-11-22 12:59:27.698868: Epoch 4893 +2024-11-22 12:59:27.698977: Current learning rate: 0.00427 +2024-11-22 12:59:46.053294: train_loss -0.7832 +2024-11-22 12:59:46.053553: val_loss -0.7652 +2024-11-22 12:59:46.053673: Pseudo dice [0.8578] +2024-11-22 12:59:46.053767: Epoch time: 18.36 s +2024-11-22 12:59:46.971714: +2024-11-22 12:59:46.971979: Epoch 4894 +2024-11-22 12:59:46.972098: Current learning rate: 0.00427 +2024-11-22 13:00:05.670053: train_loss -0.7911 +2024-11-22 13:00:05.670273: val_loss -0.7767 +2024-11-22 13:00:05.670351: Pseudo dice [0.8331] +2024-11-22 13:00:05.670429: Epoch time: 18.7 s +2024-11-22 13:00:06.547700: +2024-11-22 13:00:06.547915: Epoch 4895 +2024-11-22 13:00:06.548029: Current learning rate: 0.00427 +2024-11-22 13:00:24.640176: train_loss -0.7975 +2024-11-22 13:00:24.640399: val_loss -0.7688 +2024-11-22 13:00:24.640474: Pseudo dice [0.8254] +2024-11-22 13:00:24.640548: Epoch time: 18.09 s +2024-11-22 13:00:25.544931: +2024-11-22 13:00:25.545147: Epoch 4896 +2024-11-22 13:00:25.545265: Current learning rate: 0.00427 +2024-11-22 13:00:43.734256: train_loss -0.7876 +2024-11-22 13:00:43.734481: val_loss -0.7688 +2024-11-22 13:00:43.734557: Pseudo dice [0.8309] +2024-11-22 13:00:43.734638: Epoch time: 18.19 s +2024-11-22 13:00:44.643332: +2024-11-22 13:00:44.643552: Epoch 4897 +2024-11-22 13:00:44.643660: Current learning rate: 0.00426 +2024-11-22 13:01:03.782608: train_loss -0.7918 +2024-11-22 13:01:03.782850: val_loss -0.785 +2024-11-22 13:01:03.782926: Pseudo dice [0.853] +2024-11-22 13:01:03.783017: Epoch time: 19.14 s +2024-11-22 13:01:05.000255: +2024-11-22 13:01:05.000500: Epoch 4898 +2024-11-22 13:01:05.000614: Current learning rate: 0.00426 +2024-11-22 13:01:22.863037: train_loss -0.7931 +2024-11-22 13:01:22.863280: val_loss -0.7569 +2024-11-22 13:01:22.863353: Pseudo dice [0.8528] +2024-11-22 13:01:22.863427: Epoch time: 17.86 s +2024-11-22 13:01:23.962290: +2024-11-22 13:01:23.962528: Epoch 4899 +2024-11-22 13:01:23.962637: Current learning rate: 0.00426 +2024-11-22 13:01:41.788697: train_loss -0.7853 +2024-11-22 13:01:41.788918: val_loss -0.7824 +2024-11-22 13:01:41.789004: Pseudo dice [0.8251] +2024-11-22 13:01:41.789084: Epoch time: 17.83 s +2024-11-22 13:01:42.954128: +2024-11-22 13:01:42.954363: Epoch 4900 +2024-11-22 13:01:42.954477: Current learning rate: 0.00426 +2024-11-22 13:02:01.497950: train_loss -0.7884 +2024-11-22 13:02:01.498176: val_loss -0.7531 +2024-11-22 13:02:01.498251: Pseudo dice [0.8412] +2024-11-22 13:02:01.498327: Epoch time: 18.54 s +2024-11-22 13:02:02.374006: +2024-11-22 13:02:02.374249: Epoch 4901 +2024-11-22 13:02:02.374371: Current learning rate: 0.00426 +2024-11-22 13:02:21.487124: train_loss -0.7843 +2024-11-22 13:02:21.487344: val_loss -0.7686 +2024-11-22 13:02:21.487422: Pseudo dice [0.8493] +2024-11-22 13:02:21.487504: Epoch time: 19.11 s +2024-11-22 13:02:22.366942: +2024-11-22 13:02:22.367183: Epoch 4902 +2024-11-22 13:02:22.367297: Current learning rate: 0.00426 +2024-11-22 13:02:40.982260: train_loss -0.79 +2024-11-22 13:02:40.982482: val_loss -0.7697 +2024-11-22 13:02:40.982562: Pseudo dice [0.8448] +2024-11-22 13:02:40.982637: Epoch time: 18.62 s +2024-11-22 13:02:41.867139: +2024-11-22 13:02:41.867367: Epoch 4903 +2024-11-22 13:02:41.867473: Current learning rate: 0.00426 +2024-11-22 13:03:00.638770: train_loss -0.7973 +2024-11-22 13:03:00.639660: val_loss -0.7716 +2024-11-22 13:03:00.639743: Pseudo dice [0.8654] +2024-11-22 13:03:00.639822: Epoch time: 18.77 s +2024-11-22 13:03:01.513796: +2024-11-22 13:03:01.514017: Epoch 4904 +2024-11-22 13:03:01.514131: Current learning rate: 0.00426 +2024-11-22 13:03:20.082434: train_loss -0.7889 +2024-11-22 13:03:20.082696: val_loss -0.749 +2024-11-22 13:03:20.082773: Pseudo dice [0.8216] +2024-11-22 13:03:20.082853: Epoch time: 18.57 s +2024-11-22 13:03:20.961759: +2024-11-22 13:03:20.962013: Epoch 4905 +2024-11-22 13:03:20.962127: Current learning rate: 0.00425 +2024-11-22 13:03:40.505067: train_loss -0.7923 +2024-11-22 13:03:40.505291: val_loss -0.7795 +2024-11-22 13:03:40.505367: Pseudo dice [0.8508] +2024-11-22 13:03:40.505443: Epoch time: 19.54 s +2024-11-22 13:03:41.395000: +2024-11-22 13:03:41.395208: Epoch 4906 +2024-11-22 13:03:41.395326: Current learning rate: 0.00425 +2024-11-22 13:03:59.303137: train_loss -0.7969 +2024-11-22 13:03:59.303347: val_loss -0.7601 +2024-11-22 13:03:59.303422: Pseudo dice [0.8366] +2024-11-22 13:03:59.303497: Epoch time: 17.91 s +2024-11-22 13:04:00.177555: +2024-11-22 13:04:00.177758: Epoch 4907 +2024-11-22 13:04:00.177867: Current learning rate: 0.00425 +2024-11-22 13:04:18.946372: train_loss -0.7825 +2024-11-22 13:04:18.946634: val_loss -0.7815 +2024-11-22 13:04:18.946714: Pseudo dice [0.8476] +2024-11-22 13:04:18.946878: Epoch time: 18.77 s +2024-11-22 13:04:19.830522: +2024-11-22 13:04:19.830735: Epoch 4908 +2024-11-22 13:04:19.830843: Current learning rate: 0.00425 +2024-11-22 13:04:38.795146: train_loss -0.7911 +2024-11-22 13:04:38.795364: val_loss -0.7837 +2024-11-22 13:04:38.796802: Pseudo dice [0.8568] +2024-11-22 13:04:38.797159: Epoch time: 18.97 s +2024-11-22 13:04:39.684068: +2024-11-22 13:04:39.684284: Epoch 4909 +2024-11-22 13:04:39.684393: Current learning rate: 0.00425 +2024-11-22 13:04:58.683037: train_loss -0.7959 +2024-11-22 13:04:58.683258: val_loss -0.7897 +2024-11-22 13:04:58.683334: Pseudo dice [0.8482] +2024-11-22 13:04:58.683409: Epoch time: 19.0 s +2024-11-22 13:04:59.558142: +2024-11-22 13:04:59.558362: Epoch 4910 +2024-11-22 13:04:59.558472: Current learning rate: 0.00425 +2024-11-22 13:05:17.881333: train_loss -0.8016 +2024-11-22 13:05:17.881621: val_loss -0.7964 +2024-11-22 13:05:17.881700: Pseudo dice [0.8543] +2024-11-22 13:05:17.881785: Epoch time: 18.32 s +2024-11-22 13:05:18.764045: +2024-11-22 13:05:18.764267: Epoch 4911 +2024-11-22 13:05:18.764380: Current learning rate: 0.00425 +2024-11-22 13:05:38.956959: train_loss -0.7999 +2024-11-22 13:05:38.957220: val_loss -0.795 +2024-11-22 13:05:38.957295: Pseudo dice [0.8647] +2024-11-22 13:05:38.957373: Epoch time: 20.19 s +2024-11-22 13:05:39.844761: +2024-11-22 13:05:39.844978: Epoch 4912 +2024-11-22 13:05:39.845092: Current learning rate: 0.00425 +2024-11-22 13:05:58.804444: train_loss -0.7962 +2024-11-22 13:05:58.804669: val_loss -0.7533 +2024-11-22 13:05:58.804746: Pseudo dice [0.8568] +2024-11-22 13:05:58.804822: Epoch time: 18.96 s +2024-11-22 13:05:59.686675: +2024-11-22 13:05:59.686888: Epoch 4913 +2024-11-22 13:05:59.687000: Current learning rate: 0.00424 +2024-11-22 13:06:18.066020: train_loss -0.7955 +2024-11-22 13:06:18.066248: val_loss -0.7823 +2024-11-22 13:06:18.066323: Pseudo dice [0.8588] +2024-11-22 13:06:18.066397: Epoch time: 18.38 s +2024-11-22 13:06:18.983388: +2024-11-22 13:06:18.983613: Epoch 4914 +2024-11-22 13:06:18.983729: Current learning rate: 0.00424 +2024-11-22 13:06:37.513654: train_loss -0.7945 +2024-11-22 13:06:37.513887: val_loss -0.78 +2024-11-22 13:06:37.513966: Pseudo dice [0.8516] +2024-11-22 13:06:37.514051: Epoch time: 18.53 s +2024-11-22 13:06:38.399614: +2024-11-22 13:06:38.399837: Epoch 4915 +2024-11-22 13:06:38.399946: Current learning rate: 0.00424 +2024-11-22 13:06:57.150371: train_loss -0.8013 +2024-11-22 13:06:57.150622: val_loss -0.7764 +2024-11-22 13:06:57.150729: Pseudo dice [0.8673] +2024-11-22 13:06:57.150820: Epoch time: 18.75 s +2024-11-22 13:06:58.034287: +2024-11-22 13:06:58.034508: Epoch 4916 +2024-11-22 13:06:58.034618: Current learning rate: 0.00424 +2024-11-22 13:07:17.361285: train_loss -0.8031 +2024-11-22 13:07:17.362276: val_loss -0.7848 +2024-11-22 13:07:17.362356: Pseudo dice [0.855] +2024-11-22 13:07:17.362432: Epoch time: 19.33 s +2024-11-22 13:07:18.239002: +2024-11-22 13:07:18.239215: Epoch 4917 +2024-11-22 13:07:18.239329: Current learning rate: 0.00424 +2024-11-22 13:07:36.567717: train_loss -0.7968 +2024-11-22 13:07:36.567975: val_loss -0.7885 +2024-11-22 13:07:36.568059: Pseudo dice [0.8477] +2024-11-22 13:07:36.568134: Epoch time: 18.33 s +2024-11-22 13:07:37.447957: +2024-11-22 13:07:37.448167: Epoch 4918 +2024-11-22 13:07:37.448278: Current learning rate: 0.00424 +2024-11-22 13:07:56.002498: train_loss -0.795 +2024-11-22 13:07:56.002750: val_loss -0.7396 +2024-11-22 13:07:56.002830: Pseudo dice [0.8347] +2024-11-22 13:07:56.002911: Epoch time: 18.56 s +2024-11-22 13:07:56.999504: +2024-11-22 13:07:56.999722: Epoch 4919 +2024-11-22 13:07:56.999832: Current learning rate: 0.00424 +2024-11-22 13:08:15.011876: train_loss -0.7833 +2024-11-22 13:08:15.012093: val_loss -0.7682 +2024-11-22 13:08:15.012167: Pseudo dice [0.849] +2024-11-22 13:08:15.012239: Epoch time: 18.01 s +2024-11-22 13:08:16.052508: +2024-11-22 13:08:16.052718: Epoch 4920 +2024-11-22 13:08:16.052827: Current learning rate: 0.00424 +2024-11-22 13:08:34.072001: train_loss -0.795 +2024-11-22 13:08:34.072245: val_loss -0.7622 +2024-11-22 13:08:34.072322: Pseudo dice [0.8431] +2024-11-22 13:08:34.072396: Epoch time: 18.02 s +2024-11-22 13:08:35.325970: +2024-11-22 13:08:35.326195: Epoch 4921 +2024-11-22 13:08:35.326301: Current learning rate: 0.00423 +2024-11-22 13:08:53.733463: train_loss -0.7939 +2024-11-22 13:08:53.733712: val_loss -0.7814 +2024-11-22 13:08:53.733790: Pseudo dice [0.8614] +2024-11-22 13:08:53.733875: Epoch time: 18.41 s +2024-11-22 13:08:54.622020: +2024-11-22 13:08:54.622246: Epoch 4922 +2024-11-22 13:08:54.622365: Current learning rate: 0.00423 +2024-11-22 13:09:13.227081: train_loss -0.7929 +2024-11-22 13:09:13.227290: val_loss -0.7596 +2024-11-22 13:09:13.227363: Pseudo dice [0.8591] +2024-11-22 13:09:13.227443: Epoch time: 18.61 s +2024-11-22 13:09:14.101514: +2024-11-22 13:09:14.101744: Epoch 4923 +2024-11-22 13:09:14.101856: Current learning rate: 0.00423 +2024-11-22 13:09:32.964799: train_loss -0.7894 +2024-11-22 13:09:32.965043: val_loss -0.7562 +2024-11-22 13:09:32.965133: Pseudo dice [0.834] +2024-11-22 13:09:32.965236: Epoch time: 18.86 s +2024-11-22 13:09:33.842658: +2024-11-22 13:09:33.842878: Epoch 4924 +2024-11-22 13:09:33.842985: Current learning rate: 0.00423 +2024-11-22 13:09:52.754375: train_loss -0.7733 +2024-11-22 13:09:52.754583: val_loss -0.7485 +2024-11-22 13:09:52.754656: Pseudo dice [0.8444] +2024-11-22 13:09:52.754730: Epoch time: 18.91 s +2024-11-22 13:09:53.745066: +2024-11-22 13:09:53.745302: Epoch 4925 +2024-11-22 13:09:53.745417: Current learning rate: 0.00423 +2024-11-22 13:10:11.093131: train_loss -0.7863 +2024-11-22 13:10:11.093379: val_loss -0.772 +2024-11-22 13:10:11.093460: Pseudo dice [0.858] +2024-11-22 13:10:11.093540: Epoch time: 17.35 s +2024-11-22 13:10:11.954765: +2024-11-22 13:10:11.954935: Epoch 4926 +2024-11-22 13:10:11.955033: Current learning rate: 0.00423 +2024-11-22 13:10:30.736678: train_loss -0.7996 +2024-11-22 13:10:30.736900: val_loss -0.7909 +2024-11-22 13:10:30.736977: Pseudo dice [0.8619] +2024-11-22 13:10:30.737063: Epoch time: 18.78 s +2024-11-22 13:10:31.664067: +2024-11-22 13:10:31.664338: Epoch 4927 +2024-11-22 13:10:31.664446: Current learning rate: 0.00423 +2024-11-22 13:10:48.888998: train_loss -0.7937 +2024-11-22 13:10:48.889234: val_loss -0.7993 +2024-11-22 13:10:48.889319: Pseudo dice [0.8505] +2024-11-22 13:10:48.889392: Epoch time: 17.23 s +2024-11-22 13:10:49.764134: +2024-11-22 13:10:49.764331: Epoch 4928 +2024-11-22 13:10:49.764446: Current learning rate: 0.00423 +2024-11-22 13:11:08.362891: train_loss -0.7969 +2024-11-22 13:11:08.363141: val_loss -0.7582 +2024-11-22 13:11:08.363219: Pseudo dice [0.8537] +2024-11-22 13:11:08.363304: Epoch time: 18.6 s +2024-11-22 13:11:09.247321: +2024-11-22 13:11:09.247535: Epoch 4929 +2024-11-22 13:11:09.247645: Current learning rate: 0.00422 +2024-11-22 13:11:28.435579: train_loss -0.8007 +2024-11-22 13:11:28.435805: val_loss -0.761 +2024-11-22 13:11:28.435879: Pseudo dice [0.8369] +2024-11-22 13:11:28.435953: Epoch time: 19.19 s +2024-11-22 13:11:29.312560: +2024-11-22 13:11:29.312779: Epoch 4930 +2024-11-22 13:11:29.312893: Current learning rate: 0.00422 +2024-11-22 13:11:48.288883: train_loss -0.7811 +2024-11-22 13:11:48.291299: val_loss -0.7742 +2024-11-22 13:11:48.291384: Pseudo dice [0.8504] +2024-11-22 13:11:48.291460: Epoch time: 18.98 s +2024-11-22 13:11:49.186618: +2024-11-22 13:11:49.186825: Epoch 4931 +2024-11-22 13:11:49.186935: Current learning rate: 0.00422 +2024-11-22 13:12:07.501833: train_loss -0.7883 +2024-11-22 13:12:07.502059: val_loss -0.7791 +2024-11-22 13:12:07.502134: Pseudo dice [0.8529] +2024-11-22 13:12:07.502212: Epoch time: 18.32 s +2024-11-22 13:12:08.379191: +2024-11-22 13:12:08.379699: Epoch 4932 +2024-11-22 13:12:08.379817: Current learning rate: 0.00422 +2024-11-22 13:12:27.232232: train_loss -0.7825 +2024-11-22 13:12:27.232471: val_loss -0.8013 +2024-11-22 13:12:27.232552: Pseudo dice [0.8533] +2024-11-22 13:12:27.232633: Epoch time: 18.85 s +2024-11-22 13:12:28.554284: +2024-11-22 13:12:28.554507: Epoch 4933 +2024-11-22 13:12:28.554613: Current learning rate: 0.00422 +2024-11-22 13:12:46.212506: train_loss -0.799 +2024-11-22 13:12:46.212820: val_loss -0.7584 +2024-11-22 13:12:46.212898: Pseudo dice [0.8401] +2024-11-22 13:12:46.212972: Epoch time: 17.66 s +2024-11-22 13:12:47.093323: +2024-11-22 13:12:47.093559: Epoch 4934 +2024-11-22 13:12:47.093673: Current learning rate: 0.00422 +2024-11-22 13:13:05.101710: train_loss -0.794 +2024-11-22 13:13:05.101957: val_loss -0.758 +2024-11-22 13:13:05.102391: Pseudo dice [0.8555] +2024-11-22 13:13:05.102485: Epoch time: 18.01 s +2024-11-22 13:13:05.980810: +2024-11-22 13:13:05.981037: Epoch 4935 +2024-11-22 13:13:05.981145: Current learning rate: 0.00422 +2024-11-22 13:13:24.191258: train_loss -0.7883 +2024-11-22 13:13:24.191477: val_loss -0.7411 +2024-11-22 13:13:24.191550: Pseudo dice [0.8407] +2024-11-22 13:13:24.191625: Epoch time: 18.21 s +2024-11-22 13:13:25.072147: +2024-11-22 13:13:25.072381: Epoch 4936 +2024-11-22 13:13:25.072490: Current learning rate: 0.00422 +2024-11-22 13:13:43.761875: train_loss -0.7759 +2024-11-22 13:13:43.762105: val_loss -0.7695 +2024-11-22 13:13:43.762179: Pseudo dice [0.8394] +2024-11-22 13:13:43.762254: Epoch time: 18.69 s +2024-11-22 13:13:44.763363: +2024-11-22 13:13:44.763585: Epoch 4937 +2024-11-22 13:13:44.763694: Current learning rate: 0.00421 +2024-11-22 13:14:03.320603: train_loss -0.7799 +2024-11-22 13:14:03.321755: val_loss -0.7532 +2024-11-22 13:14:03.321831: Pseudo dice [0.8402] +2024-11-22 13:14:03.321905: Epoch time: 18.56 s +2024-11-22 13:14:04.206401: +2024-11-22 13:14:04.206622: Epoch 4938 +2024-11-22 13:14:04.206735: Current learning rate: 0.00421 +2024-11-22 13:14:22.192271: train_loss -0.7752 +2024-11-22 13:14:22.192525: val_loss -0.7499 +2024-11-22 13:14:22.192601: Pseudo dice [0.8254] +2024-11-22 13:14:22.192686: Epoch time: 17.99 s +2024-11-22 13:14:23.153786: +2024-11-22 13:14:23.154019: Epoch 4939 +2024-11-22 13:14:23.154138: Current learning rate: 0.00421 +2024-11-22 13:14:41.254865: train_loss -0.7883 +2024-11-22 13:14:41.255079: val_loss -0.7716 +2024-11-22 13:14:41.255224: Pseudo dice [0.8361] +2024-11-22 13:14:41.255305: Epoch time: 18.1 s +2024-11-22 13:14:42.172589: +2024-11-22 13:14:42.172811: Epoch 4940 +2024-11-22 13:14:42.172922: Current learning rate: 0.00421 +2024-11-22 13:15:01.364782: train_loss -0.7929 +2024-11-22 13:15:01.365016: val_loss -0.7733 +2024-11-22 13:15:01.365095: Pseudo dice [0.8577] +2024-11-22 13:15:01.365174: Epoch time: 19.19 s +2024-11-22 13:15:02.248166: +2024-11-22 13:15:02.248389: Epoch 4941 +2024-11-22 13:15:02.248512: Current learning rate: 0.00421 +2024-11-22 13:15:20.973167: train_loss -0.7964 +2024-11-22 13:15:20.973449: val_loss -0.7782 +2024-11-22 13:15:20.973532: Pseudo dice [0.8396] +2024-11-22 13:15:20.973612: Epoch time: 18.73 s +2024-11-22 13:15:21.851344: +2024-11-22 13:15:21.851563: Epoch 4942 +2024-11-22 13:15:21.851671: Current learning rate: 0.00421 +2024-11-22 13:15:40.612263: train_loss -0.7948 +2024-11-22 13:15:40.612515: val_loss -0.7612 +2024-11-22 13:15:40.612592: Pseudo dice [0.8445] +2024-11-22 13:15:40.612670: Epoch time: 18.76 s +2024-11-22 13:15:41.487320: +2024-11-22 13:15:41.487581: Epoch 4943 +2024-11-22 13:15:41.487693: Current learning rate: 0.00421 +2024-11-22 13:16:00.728171: train_loss -0.7768 +2024-11-22 13:16:00.728401: val_loss -0.746 +2024-11-22 13:16:00.728478: Pseudo dice [0.8319] +2024-11-22 13:16:00.728621: Epoch time: 19.24 s +2024-11-22 13:16:01.607140: +2024-11-22 13:16:01.607363: Epoch 4944 +2024-11-22 13:16:01.607501: Current learning rate: 0.00421 +2024-11-22 13:16:18.970693: train_loss -0.7909 +2024-11-22 13:16:18.970904: val_loss -0.7648 +2024-11-22 13:16:18.970977: Pseudo dice [0.8395] +2024-11-22 13:16:18.971067: Epoch time: 17.36 s +2024-11-22 13:16:20.235972: +2024-11-22 13:16:20.236205: Epoch 4945 +2024-11-22 13:16:20.236314: Current learning rate: 0.0042 +2024-11-22 13:16:39.226110: train_loss -0.7951 +2024-11-22 13:16:39.226371: val_loss -0.7659 +2024-11-22 13:16:39.226448: Pseudo dice [0.851] +2024-11-22 13:16:39.226531: Epoch time: 18.99 s +2024-11-22 13:16:40.114829: +2024-11-22 13:16:40.115065: Epoch 4946 +2024-11-22 13:16:40.115174: Current learning rate: 0.0042 +2024-11-22 13:16:57.748817: train_loss -0.796 +2024-11-22 13:16:57.749046: val_loss -0.7684 +2024-11-22 13:16:57.749120: Pseudo dice [0.8535] +2024-11-22 13:16:57.749195: Epoch time: 17.63 s +2024-11-22 13:16:58.663037: +2024-11-22 13:16:58.663250: Epoch 4947 +2024-11-22 13:16:58.663359: Current learning rate: 0.0042 +2024-11-22 13:17:18.149716: train_loss -0.7943 +2024-11-22 13:17:18.149940: val_loss -0.7719 +2024-11-22 13:17:18.150034: Pseudo dice [0.8521] +2024-11-22 13:17:18.150109: Epoch time: 19.49 s +2024-11-22 13:17:19.228477: +2024-11-22 13:17:19.228707: Epoch 4948 +2024-11-22 13:17:19.228821: Current learning rate: 0.0042 +2024-11-22 13:17:37.782314: train_loss -0.7838 +2024-11-22 13:17:37.782573: val_loss -0.7684 +2024-11-22 13:17:37.782651: Pseudo dice [0.839] +2024-11-22 13:17:37.782736: Epoch time: 18.55 s +2024-11-22 13:17:38.663878: +2024-11-22 13:17:38.664116: Epoch 4949 +2024-11-22 13:17:38.664233: Current learning rate: 0.0042 +2024-11-22 13:17:56.891300: train_loss -0.7846 +2024-11-22 13:17:56.891509: val_loss -0.7973 +2024-11-22 13:17:56.891581: Pseudo dice [0.852] +2024-11-22 13:17:56.891653: Epoch time: 18.23 s +2024-11-22 13:17:58.061209: +2024-11-22 13:17:58.061428: Epoch 4950 +2024-11-22 13:17:58.061535: Current learning rate: 0.0042 +2024-11-22 13:18:15.976953: train_loss -0.7901 +2024-11-22 13:18:15.977212: val_loss -0.7365 +2024-11-22 13:18:15.977291: Pseudo dice [0.8478] +2024-11-22 13:18:15.977369: Epoch time: 17.91 s +2024-11-22 13:18:16.898630: +2024-11-22 13:18:16.898852: Epoch 4951 +2024-11-22 13:18:16.900335: Current learning rate: 0.0042 +2024-11-22 13:18:35.069833: train_loss -0.7954 +2024-11-22 13:18:35.070064: val_loss -0.7793 +2024-11-22 13:18:35.070139: Pseudo dice [0.8454] +2024-11-22 13:18:35.070212: Epoch time: 18.17 s +2024-11-22 13:18:35.950658: +2024-11-22 13:18:35.950926: Epoch 4952 +2024-11-22 13:18:35.951057: Current learning rate: 0.0042 +2024-11-22 13:18:55.350556: train_loss -0.7883 +2024-11-22 13:18:55.350813: val_loss -0.7635 +2024-11-22 13:18:55.350891: Pseudo dice [0.8341] +2024-11-22 13:18:55.350973: Epoch time: 19.4 s +2024-11-22 13:18:56.234210: +2024-11-22 13:18:56.234418: Epoch 4953 +2024-11-22 13:18:56.234524: Current learning rate: 0.00419 +2024-11-22 13:19:14.675909: train_loss -0.8014 +2024-11-22 13:19:14.678310: val_loss -0.7512 +2024-11-22 13:19:14.678406: Pseudo dice [0.837] +2024-11-22 13:19:14.678483: Epoch time: 18.44 s +2024-11-22 13:19:15.678631: +2024-11-22 13:19:15.678840: Epoch 4954 +2024-11-22 13:19:15.678950: Current learning rate: 0.00419 +2024-11-22 13:19:34.534118: train_loss -0.7894 +2024-11-22 13:19:34.534337: val_loss -0.7702 +2024-11-22 13:19:34.534412: Pseudo dice [0.8386] +2024-11-22 13:19:34.534487: Epoch time: 18.86 s +2024-11-22 13:19:35.533560: +2024-11-22 13:19:35.533768: Epoch 4955 +2024-11-22 13:19:35.533878: Current learning rate: 0.00419 +2024-11-22 13:19:54.987368: train_loss -0.7951 +2024-11-22 13:19:54.987610: val_loss -0.7765 +2024-11-22 13:19:54.987689: Pseudo dice [0.8674] +2024-11-22 13:19:54.987768: Epoch time: 19.45 s +2024-11-22 13:19:55.967144: +2024-11-22 13:19:55.967349: Epoch 4956 +2024-11-22 13:19:55.967457: Current learning rate: 0.00419 +2024-11-22 13:20:14.901312: train_loss -0.7863 +2024-11-22 13:20:14.901836: val_loss -0.75 +2024-11-22 13:20:14.903228: Pseudo dice [0.8418] +2024-11-22 13:20:14.903345: Epoch time: 18.93 s +2024-11-22 13:20:15.819165: +2024-11-22 13:20:15.819394: Epoch 4957 +2024-11-22 13:20:15.819510: Current learning rate: 0.00419 +2024-11-22 13:20:33.812733: train_loss -0.7907 +2024-11-22 13:20:33.813016: val_loss -0.7876 +2024-11-22 13:20:33.813101: Pseudo dice [0.8677] +2024-11-22 13:20:33.813179: Epoch time: 17.99 s +2024-11-22 13:20:34.694899: +2024-11-22 13:20:34.695133: Epoch 4958 +2024-11-22 13:20:34.695243: Current learning rate: 0.00419 +2024-11-22 13:20:53.790256: train_loss -0.7906 +2024-11-22 13:20:53.790510: val_loss -0.7551 +2024-11-22 13:20:53.790588: Pseudo dice [0.835] +2024-11-22 13:20:53.790672: Epoch time: 19.1 s +2024-11-22 13:20:54.678596: +2024-11-22 13:20:54.678823: Epoch 4959 +2024-11-22 13:20:54.678936: Current learning rate: 0.00419 +2024-11-22 13:21:12.863002: train_loss -0.7865 +2024-11-22 13:21:12.863221: val_loss -0.7604 +2024-11-22 13:21:12.863294: Pseudo dice [0.8362] +2024-11-22 13:21:12.863368: Epoch time: 18.19 s +2024-11-22 13:21:13.800138: +2024-11-22 13:21:13.800347: Epoch 4960 +2024-11-22 13:21:13.800452: Current learning rate: 0.00419 +2024-11-22 13:21:32.753332: train_loss -0.7751 +2024-11-22 13:21:32.753577: val_loss -0.7705 +2024-11-22 13:21:32.753951: Pseudo dice [0.8411] +2024-11-22 13:21:32.754051: Epoch time: 18.95 s +2024-11-22 13:21:33.633482: +2024-11-22 13:21:33.633703: Epoch 4961 +2024-11-22 13:21:33.633814: Current learning rate: 0.00418 +2024-11-22 13:21:51.568305: train_loss -0.785 +2024-11-22 13:21:51.568528: val_loss -0.7551 +2024-11-22 13:21:51.568605: Pseudo dice [0.8244] +2024-11-22 13:21:51.568680: Epoch time: 17.94 s +2024-11-22 13:21:52.555024: +2024-11-22 13:21:52.555218: Epoch 4962 +2024-11-22 13:21:52.555327: Current learning rate: 0.00418 +2024-11-22 13:22:11.393911: train_loss -0.7816 +2024-11-22 13:22:11.394169: val_loss -0.7509 +2024-11-22 13:22:11.394246: Pseudo dice [0.8134] +2024-11-22 13:22:11.394342: Epoch time: 18.84 s +2024-11-22 13:22:12.275037: +2024-11-22 13:22:12.275240: Epoch 4963 +2024-11-22 13:22:12.275352: Current learning rate: 0.00418 +2024-11-22 13:22:30.005062: train_loss -0.7818 +2024-11-22 13:22:30.005278: val_loss -0.7743 +2024-11-22 13:22:30.005354: Pseudo dice [0.8544] +2024-11-22 13:22:30.005430: Epoch time: 17.73 s +2024-11-22 13:22:30.893884: +2024-11-22 13:22:30.894123: Epoch 4964 +2024-11-22 13:22:30.894266: Current learning rate: 0.00418 +2024-11-22 13:22:48.860355: train_loss -0.7634 +2024-11-22 13:22:48.860570: val_loss -0.7521 +2024-11-22 13:22:48.860643: Pseudo dice [0.8306] +2024-11-22 13:22:48.860719: Epoch time: 17.97 s +2024-11-22 13:22:49.740109: +2024-11-22 13:22:49.740431: Epoch 4965 +2024-11-22 13:22:49.740556: Current learning rate: 0.00418 +2024-11-22 13:23:08.083255: train_loss -0.7659 +2024-11-22 13:23:08.083473: val_loss -0.746 +2024-11-22 13:23:08.083549: Pseudo dice [0.8282] +2024-11-22 13:23:08.083626: Epoch time: 18.34 s +2024-11-22 13:23:08.964677: +2024-11-22 13:23:08.964916: Epoch 4966 +2024-11-22 13:23:08.965043: Current learning rate: 0.00418 +2024-11-22 13:23:27.116290: train_loss -0.7773 +2024-11-22 13:23:27.116513: val_loss -0.7738 +2024-11-22 13:23:27.116588: Pseudo dice [0.8676] +2024-11-22 13:23:27.116665: Epoch time: 18.15 s +2024-11-22 13:23:27.998611: +2024-11-22 13:23:27.998831: Epoch 4967 +2024-11-22 13:23:27.998942: Current learning rate: 0.00418 +2024-11-22 13:23:46.237128: train_loss -0.7889 +2024-11-22 13:23:46.237375: val_loss -0.7767 +2024-11-22 13:23:46.237448: Pseudo dice [0.8475] +2024-11-22 13:23:46.237520: Epoch time: 18.24 s +2024-11-22 13:23:47.496694: +2024-11-22 13:23:47.496951: Epoch 4968 +2024-11-22 13:23:47.497075: Current learning rate: 0.00418 +2024-11-22 13:24:06.078092: train_loss -0.7867 +2024-11-22 13:24:06.078351: val_loss -0.7753 +2024-11-22 13:24:06.078426: Pseudo dice [0.8411] +2024-11-22 13:24:06.078508: Epoch time: 18.58 s +2024-11-22 13:24:06.961152: +2024-11-22 13:24:06.961387: Epoch 4969 +2024-11-22 13:24:06.961492: Current learning rate: 0.00417 +2024-11-22 13:24:25.065542: train_loss -0.7806 +2024-11-22 13:24:25.065760: val_loss -0.7893 +2024-11-22 13:24:25.065835: Pseudo dice [0.8428] +2024-11-22 13:24:25.065910: Epoch time: 18.11 s +2024-11-22 13:24:25.953340: +2024-11-22 13:24:25.953570: Epoch 4970 +2024-11-22 13:24:25.953682: Current learning rate: 0.00417 +2024-11-22 13:24:44.059966: train_loss -0.7931 +2024-11-22 13:24:44.060208: val_loss -0.7742 +2024-11-22 13:24:44.060288: Pseudo dice [0.8545] +2024-11-22 13:24:44.060360: Epoch time: 18.11 s +2024-11-22 13:24:45.120988: +2024-11-22 13:24:45.121331: Epoch 4971 +2024-11-22 13:24:45.121453: Current learning rate: 0.00417 +2024-11-22 13:25:02.835262: train_loss -0.7991 +2024-11-22 13:25:02.835553: val_loss -0.7615 +2024-11-22 13:25:02.835644: Pseudo dice [0.8422] +2024-11-22 13:25:02.835737: Epoch time: 17.71 s +2024-11-22 13:25:03.845415: +2024-11-22 13:25:03.845724: Epoch 4972 +2024-11-22 13:25:03.845832: Current learning rate: 0.00417 +2024-11-22 13:25:22.590907: train_loss -0.7899 +2024-11-22 13:25:22.591170: val_loss -0.7659 +2024-11-22 13:25:22.591252: Pseudo dice [0.8426] +2024-11-22 13:25:22.591332: Epoch time: 18.75 s +2024-11-22 13:25:23.683024: +2024-11-22 13:25:23.683248: Epoch 4973 +2024-11-22 13:25:23.683358: Current learning rate: 0.00417 +2024-11-22 13:25:43.259157: train_loss -0.7877 +2024-11-22 13:25:43.259376: val_loss -0.7598 +2024-11-22 13:25:43.259452: Pseudo dice [0.8481] +2024-11-22 13:25:43.259544: Epoch time: 19.57 s +2024-11-22 13:25:44.149855: +2024-11-22 13:25:44.150079: Epoch 4974 +2024-11-22 13:25:44.150193: Current learning rate: 0.00417 +2024-11-22 13:26:02.682663: train_loss -0.7907 +2024-11-22 13:26:02.682890: val_loss -0.754 +2024-11-22 13:26:02.682967: Pseudo dice [0.8415] +2024-11-22 13:26:02.683049: Epoch time: 18.53 s +2024-11-22 13:26:03.563328: +2024-11-22 13:26:03.563616: Epoch 4975 +2024-11-22 13:26:03.563730: Current learning rate: 0.00417 +2024-11-22 13:26:23.117540: train_loss -0.7941 +2024-11-22 13:26:23.117846: val_loss -0.7567 +2024-11-22 13:26:23.117925: Pseudo dice [0.852] +2024-11-22 13:26:23.118011: Epoch time: 19.56 s +2024-11-22 13:26:24.004005: +2024-11-22 13:26:24.004220: Epoch 4976 +2024-11-22 13:26:24.004326: Current learning rate: 0.00417 +2024-11-22 13:26:42.558764: train_loss -0.7736 +2024-11-22 13:26:42.559015: val_loss -0.749 +2024-11-22 13:26:42.559090: Pseudo dice [0.8217] +2024-11-22 13:26:42.559169: Epoch time: 18.56 s +2024-11-22 13:26:43.449027: +2024-11-22 13:26:43.449260: Epoch 4977 +2024-11-22 13:26:43.449376: Current learning rate: 0.00416 +2024-11-22 13:27:01.243474: train_loss -0.7738 +2024-11-22 13:27:01.243701: val_loss -0.7454 +2024-11-22 13:27:01.243780: Pseudo dice [0.8327] +2024-11-22 13:27:01.243885: Epoch time: 17.8 s +2024-11-22 13:27:02.124097: +2024-11-22 13:27:02.124311: Epoch 4978 +2024-11-22 13:27:02.124422: Current learning rate: 0.00416 +2024-11-22 13:27:20.522453: train_loss -0.7797 +2024-11-22 13:27:20.522686: val_loss -0.7901 +2024-11-22 13:27:20.522858: Pseudo dice [0.8523] +2024-11-22 13:27:20.522942: Epoch time: 18.4 s +2024-11-22 13:27:21.402212: +2024-11-22 13:27:21.402431: Epoch 4979 +2024-11-22 13:27:21.402545: Current learning rate: 0.00416 +2024-11-22 13:27:39.187976: train_loss -0.7884 +2024-11-22 13:27:39.188437: val_loss -0.7557 +2024-11-22 13:27:39.188530: Pseudo dice [0.8255] +2024-11-22 13:27:39.188606: Epoch time: 17.79 s +2024-11-22 13:27:40.055581: +2024-11-22 13:27:40.055808: Epoch 4980 +2024-11-22 13:27:40.055916: Current learning rate: 0.00416 +2024-11-22 13:27:58.334650: train_loss -0.7889 +2024-11-22 13:27:58.334882: val_loss -0.7574 +2024-11-22 13:27:58.334962: Pseudo dice [0.8474] +2024-11-22 13:27:58.335043: Epoch time: 18.28 s +2024-11-22 13:27:59.227516: +2024-11-22 13:27:59.227755: Epoch 4981 +2024-11-22 13:27:59.227870: Current learning rate: 0.00416 +2024-11-22 13:28:17.931682: train_loss -0.7832 +2024-11-22 13:28:17.931910: val_loss -0.7746 +2024-11-22 13:28:17.931997: Pseudo dice [0.8475] +2024-11-22 13:28:17.932076: Epoch time: 18.71 s +2024-11-22 13:28:18.818250: +2024-11-22 13:28:18.818478: Epoch 4982 +2024-11-22 13:28:18.818594: Current learning rate: 0.00416 +2024-11-22 13:28:35.790208: train_loss -0.789 +2024-11-22 13:28:35.790453: val_loss -0.7653 +2024-11-22 13:28:35.790531: Pseudo dice [0.8478] +2024-11-22 13:28:35.790615: Epoch time: 16.97 s +2024-11-22 13:28:36.669301: +2024-11-22 13:28:36.669531: Epoch 4983 +2024-11-22 13:28:36.669646: Current learning rate: 0.00416 +2024-11-22 13:28:53.686857: train_loss -0.7977 +2024-11-22 13:28:53.687096: val_loss -0.7416 +2024-11-22 13:28:53.687173: Pseudo dice [0.8432] +2024-11-22 13:28:53.687250: Epoch time: 17.02 s +2024-11-22 13:28:54.672714: +2024-11-22 13:28:54.672943: Epoch 4984 +2024-11-22 13:28:54.673057: Current learning rate: 0.00416 +2024-11-22 13:29:12.548374: train_loss -0.7861 +2024-11-22 13:29:12.548604: val_loss -0.7867 +2024-11-22 13:29:12.548680: Pseudo dice [0.8661] +2024-11-22 13:29:12.548754: Epoch time: 17.88 s +2024-11-22 13:29:13.425908: +2024-11-22 13:29:13.426103: Epoch 4985 +2024-11-22 13:29:13.426212: Current learning rate: 0.00416 +2024-11-22 13:29:31.247103: train_loss -0.7855 +2024-11-22 13:29:31.247345: val_loss -0.7725 +2024-11-22 13:29:31.247427: Pseudo dice [0.8509] +2024-11-22 13:29:31.247509: Epoch time: 17.82 s +2024-11-22 13:29:32.131856: +2024-11-22 13:29:32.132145: Epoch 4986 +2024-11-22 13:29:32.132256: Current learning rate: 0.00415 +2024-11-22 13:29:51.118690: train_loss -0.7839 +2024-11-22 13:29:51.118943: val_loss -0.7655 +2024-11-22 13:29:51.119301: Pseudo dice [0.8494] +2024-11-22 13:29:51.119395: Epoch time: 18.99 s +2024-11-22 13:29:51.998314: +2024-11-22 13:29:51.998530: Epoch 4987 +2024-11-22 13:29:51.998644: Current learning rate: 0.00415 +2024-11-22 13:30:10.290902: train_loss -0.7872 +2024-11-22 13:30:10.291128: val_loss -0.7706 +2024-11-22 13:30:10.291202: Pseudo dice [0.8453] +2024-11-22 13:30:10.291274: Epoch time: 18.29 s +2024-11-22 13:30:11.180681: +2024-11-22 13:30:11.180895: Epoch 4988 +2024-11-22 13:30:11.181011: Current learning rate: 0.00415 +2024-11-22 13:30:30.769454: train_loss -0.7934 +2024-11-22 13:30:30.769742: val_loss -0.7941 +2024-11-22 13:30:30.769815: Pseudo dice [0.8531] +2024-11-22 13:30:30.769892: Epoch time: 19.59 s +2024-11-22 13:30:31.660087: +2024-11-22 13:30:31.660287: Epoch 4989 +2024-11-22 13:30:31.660397: Current learning rate: 0.00415 +2024-11-22 13:30:50.164574: train_loss -0.786 +2024-11-22 13:30:50.164863: val_loss -0.771 +2024-11-22 13:30:50.164942: Pseudo dice [0.8502] +2024-11-22 13:30:50.165036: Epoch time: 18.51 s +2024-11-22 13:30:51.041206: +2024-11-22 13:30:51.041419: Epoch 4990 +2024-11-22 13:30:51.041526: Current learning rate: 0.00415 +2024-11-22 13:31:11.280166: train_loss -0.7951 +2024-11-22 13:31:11.280382: val_loss -0.7846 +2024-11-22 13:31:11.280454: Pseudo dice [0.8525] +2024-11-22 13:31:11.280529: Epoch time: 20.24 s +2024-11-22 13:31:12.559965: +2024-11-22 13:31:12.560190: Epoch 4991 +2024-11-22 13:31:12.560312: Current learning rate: 0.00415 +2024-11-22 13:31:30.778923: train_loss -0.7979 +2024-11-22 13:31:30.779151: val_loss -0.762 +2024-11-22 13:31:30.779253: Pseudo dice [0.8484] +2024-11-22 13:31:30.779330: Epoch time: 18.22 s +2024-11-22 13:31:31.650459: +2024-11-22 13:31:31.650669: Epoch 4992 +2024-11-22 13:31:31.650781: Current learning rate: 0.00415 +2024-11-22 13:31:50.155391: train_loss -0.7871 +2024-11-22 13:31:50.155678: val_loss -0.7755 +2024-11-22 13:31:50.155759: Pseudo dice [0.8664] +2024-11-22 13:31:50.155845: Epoch time: 18.51 s +2024-11-22 13:31:51.067641: +2024-11-22 13:31:51.067869: Epoch 4993 +2024-11-22 13:31:51.067980: Current learning rate: 0.00415 +2024-11-22 13:32:09.855263: train_loss -0.7898 +2024-11-22 13:32:09.855479: val_loss -0.7934 +2024-11-22 13:32:09.855555: Pseudo dice [0.8543] +2024-11-22 13:32:09.855625: Epoch time: 18.79 s +2024-11-22 13:32:10.745393: +2024-11-22 13:32:10.745624: Epoch 4994 +2024-11-22 13:32:10.745736: Current learning rate: 0.00414 +2024-11-22 13:32:29.100289: train_loss -0.8027 +2024-11-22 13:32:29.100509: val_loss -0.7817 +2024-11-22 13:32:29.100585: Pseudo dice [0.8627] +2024-11-22 13:32:29.100660: Epoch time: 18.36 s +2024-11-22 13:32:30.078734: +2024-11-22 13:32:30.078960: Epoch 4995 +2024-11-22 13:32:30.079080: Current learning rate: 0.00414 +2024-11-22 13:32:48.258909: train_loss -0.7932 +2024-11-22 13:32:48.259132: val_loss -0.7783 +2024-11-22 13:32:48.259208: Pseudo dice [0.8483] +2024-11-22 13:32:48.259282: Epoch time: 18.18 s +2024-11-22 13:32:49.138697: +2024-11-22 13:32:49.138919: Epoch 4996 +2024-11-22 13:32:49.139035: Current learning rate: 0.00414 +2024-11-22 13:33:07.230249: train_loss -0.7941 +2024-11-22 13:33:07.230479: val_loss -0.7801 +2024-11-22 13:33:07.230558: Pseudo dice [0.8555] +2024-11-22 13:33:07.230642: Epoch time: 18.09 s +2024-11-22 13:33:08.115749: +2024-11-22 13:33:08.115963: Epoch 4997 +2024-11-22 13:33:08.116081: Current learning rate: 0.00414 +2024-11-22 13:33:26.865215: train_loss -0.7944 +2024-11-22 13:33:26.865449: val_loss -0.754 +2024-11-22 13:33:26.865525: Pseudo dice [0.8465] +2024-11-22 13:33:26.865632: Epoch time: 18.75 s +2024-11-22 13:33:27.849690: +2024-11-22 13:33:27.849910: Epoch 4998 +2024-11-22 13:33:27.850022: Current learning rate: 0.00414 +2024-11-22 13:33:45.890333: train_loss -0.795 +2024-11-22 13:33:45.890549: val_loss -0.7565 +2024-11-22 13:33:45.890621: Pseudo dice [0.8343] +2024-11-22 13:33:45.890695: Epoch time: 18.04 s +2024-11-22 13:33:46.773454: +2024-11-22 13:33:46.773685: Epoch 4999 +2024-11-22 13:33:46.773798: Current learning rate: 0.00414 +2024-11-22 13:34:05.684678: train_loss -0.7827 +2024-11-22 13:34:05.684897: val_loss -0.7575 +2024-11-22 13:34:05.684970: Pseudo dice [0.8468] +2024-11-22 13:34:05.685051: Epoch time: 18.91 s +2024-11-22 13:34:06.831708: +2024-11-22 13:34:06.831918: Epoch 5000 +2024-11-22 13:34:06.832036: Current learning rate: 0.00414 +2024-11-22 13:34:25.060821: train_loss -0.787 +2024-11-22 13:34:25.061069: val_loss -0.7629 +2024-11-22 13:34:25.061145: Pseudo dice [0.8461] +2024-11-22 13:34:25.061229: Epoch time: 18.23 s +2024-11-22 13:34:25.952795: +2024-11-22 13:34:25.953031: Epoch 5001 +2024-11-22 13:34:25.953145: Current learning rate: 0.00414 +2024-11-22 13:34:44.247421: train_loss -0.7967 +2024-11-22 13:34:44.247644: val_loss -0.7789 +2024-11-22 13:34:44.247717: Pseudo dice [0.8589] +2024-11-22 13:34:44.247793: Epoch time: 18.3 s +2024-11-22 13:34:45.129328: +2024-11-22 13:34:45.129568: Epoch 5002 +2024-11-22 13:34:45.129680: Current learning rate: 0.00413 +2024-11-22 13:35:04.662776: train_loss -0.7943 +2024-11-22 13:35:04.663314: val_loss -0.7899 +2024-11-22 13:35:04.663412: Pseudo dice [0.8483] +2024-11-22 13:35:04.663489: Epoch time: 19.53 s +2024-11-22 13:35:05.541385: +2024-11-22 13:35:05.541610: Epoch 5003 +2024-11-22 13:35:05.541721: Current learning rate: 0.00413 +2024-11-22 13:35:24.135214: train_loss -0.7956 +2024-11-22 13:35:24.135427: val_loss -0.7795 +2024-11-22 13:35:24.135503: Pseudo dice [0.8394] +2024-11-22 13:35:24.135583: Epoch time: 18.59 s +2024-11-22 13:35:25.012276: +2024-11-22 13:35:25.012503: Epoch 5004 +2024-11-22 13:35:25.012613: Current learning rate: 0.00413 +2024-11-22 13:35:43.176315: train_loss -0.7999 +2024-11-22 13:35:43.178706: val_loss -0.7796 +2024-11-22 13:35:43.178856: Pseudo dice [0.8448] +2024-11-22 13:35:43.178939: Epoch time: 18.16 s +2024-11-22 13:35:44.118936: +2024-11-22 13:35:44.119265: Epoch 5005 +2024-11-22 13:35:44.119374: Current learning rate: 0.00413 +2024-11-22 13:36:02.131316: train_loss -0.7936 +2024-11-22 13:36:02.131555: val_loss -0.758 +2024-11-22 13:36:02.131636: Pseudo dice [0.843] +2024-11-22 13:36:02.132524: Epoch time: 18.01 s +2024-11-22 13:36:03.012642: +2024-11-22 13:36:03.012845: Epoch 5006 +2024-11-22 13:36:03.012950: Current learning rate: 0.00413 +2024-11-22 13:36:21.403920: train_loss -0.797 +2024-11-22 13:36:21.404145: val_loss -0.7778 +2024-11-22 13:36:21.409341: Pseudo dice [0.8603] +2024-11-22 13:36:21.409429: Epoch time: 18.39 s +2024-11-22 13:36:22.406500: +2024-11-22 13:36:22.406717: Epoch 5007 +2024-11-22 13:36:22.406828: Current learning rate: 0.00413 +2024-11-22 13:36:41.518351: train_loss -0.7907 +2024-11-22 13:36:41.518587: val_loss -0.7493 +2024-11-22 13:36:41.518667: Pseudo dice [0.8411] +2024-11-22 13:36:41.518747: Epoch time: 19.11 s +2024-11-22 13:36:42.408552: +2024-11-22 13:36:42.408743: Epoch 5008 +2024-11-22 13:36:42.408855: Current learning rate: 0.00413 +2024-11-22 13:37:01.827515: train_loss -0.7938 +2024-11-22 13:37:01.829709: val_loss -0.768 +2024-11-22 13:37:01.829802: Pseudo dice [0.8559] +2024-11-22 13:37:01.829889: Epoch time: 19.42 s +2024-11-22 13:37:02.742309: +2024-11-22 13:37:02.742535: Epoch 5009 +2024-11-22 13:37:02.742652: Current learning rate: 0.00413 +2024-11-22 13:37:21.167986: train_loss -0.8033 +2024-11-22 13:37:21.168214: val_loss -0.7925 +2024-11-22 13:37:21.168292: Pseudo dice [0.8589] +2024-11-22 13:37:21.168382: Epoch time: 18.43 s +2024-11-22 13:37:22.044600: +2024-11-22 13:37:22.044815: Epoch 5010 +2024-11-22 13:37:22.044930: Current learning rate: 0.00412 +2024-11-22 13:37:39.703920: train_loss -0.7866 +2024-11-22 13:37:39.704165: val_loss -0.7587 +2024-11-22 13:37:39.704241: Pseudo dice [0.8387] +2024-11-22 13:37:39.704317: Epoch time: 17.66 s +2024-11-22 13:37:40.581521: +2024-11-22 13:37:40.581739: Epoch 5011 +2024-11-22 13:37:40.581849: Current learning rate: 0.00412 +2024-11-22 13:37:59.223243: train_loss -0.7905 +2024-11-22 13:37:59.223507: val_loss -0.7587 +2024-11-22 13:37:59.223630: Pseudo dice [0.8576] +2024-11-22 13:37:59.223722: Epoch time: 18.64 s +2024-11-22 13:38:00.110744: +2024-11-22 13:38:00.110958: Epoch 5012 +2024-11-22 13:38:00.111075: Current learning rate: 0.00412 +2024-11-22 13:38:18.911591: train_loss -0.7937 +2024-11-22 13:38:18.912055: val_loss -0.7831 +2024-11-22 13:38:18.912141: Pseudo dice [0.8607] +2024-11-22 13:38:18.912220: Epoch time: 18.8 s +2024-11-22 13:38:19.792546: +2024-11-22 13:38:19.792750: Epoch 5013 +2024-11-22 13:38:19.792858: Current learning rate: 0.00412 +2024-11-22 13:38:38.063157: train_loss -0.7946 +2024-11-22 13:38:38.064303: val_loss -0.7726 +2024-11-22 13:38:38.064418: Pseudo dice [0.8242] +2024-11-22 13:38:38.064547: Epoch time: 18.27 s +2024-11-22 13:38:39.267863: +2024-11-22 13:38:39.268161: Epoch 5014 +2024-11-22 13:38:39.268288: Current learning rate: 0.00412 +2024-11-22 13:38:57.594352: train_loss -0.7927 +2024-11-22 13:38:57.594612: val_loss -0.7291 +2024-11-22 13:38:57.594696: Pseudo dice [0.8411] +2024-11-22 13:38:57.594781: Epoch time: 18.33 s +2024-11-22 13:38:58.482289: +2024-11-22 13:38:58.482502: Epoch 5015 +2024-11-22 13:38:58.482614: Current learning rate: 0.00412 +2024-11-22 13:39:16.935471: train_loss -0.7989 +2024-11-22 13:39:16.935707: val_loss -0.779 +2024-11-22 13:39:16.935782: Pseudo dice [0.8408] +2024-11-22 13:39:16.935857: Epoch time: 18.45 s +2024-11-22 13:39:17.820248: +2024-11-22 13:39:17.820467: Epoch 5016 +2024-11-22 13:39:17.820579: Current learning rate: 0.00412 +2024-11-22 13:39:36.520956: train_loss -0.7998 +2024-11-22 13:39:36.521208: val_loss -0.7957 +2024-11-22 13:39:36.521285: Pseudo dice [0.8537] +2024-11-22 13:39:36.521362: Epoch time: 18.7 s +2024-11-22 13:39:37.398639: +2024-11-22 13:39:37.398865: Epoch 5017 +2024-11-22 13:39:37.398986: Current learning rate: 0.00412 +2024-11-22 13:39:57.152133: train_loss -0.7932 +2024-11-22 13:39:57.152347: val_loss -0.7709 +2024-11-22 13:39:57.152427: Pseudo dice [0.8339] +2024-11-22 13:39:57.152503: Epoch time: 19.75 s +2024-11-22 13:39:58.106601: +2024-11-22 13:39:58.106860: Epoch 5018 +2024-11-22 13:39:58.106984: Current learning rate: 0.00411 +2024-11-22 13:40:15.970900: train_loss -0.7952 +2024-11-22 13:40:15.971168: val_loss -0.786 +2024-11-22 13:40:15.971294: Pseudo dice [0.8387] +2024-11-22 13:40:15.971378: Epoch time: 17.87 s +2024-11-22 13:40:16.855271: +2024-11-22 13:40:16.855471: Epoch 5019 +2024-11-22 13:40:16.855577: Current learning rate: 0.00411 +2024-11-22 13:40:36.605972: train_loss -0.7992 +2024-11-22 13:40:36.606198: val_loss -0.7652 +2024-11-22 13:40:36.606272: Pseudo dice [0.8405] +2024-11-22 13:40:36.606347: Epoch time: 19.75 s +2024-11-22 13:40:37.488527: +2024-11-22 13:40:37.488743: Epoch 5020 +2024-11-22 13:40:37.488856: Current learning rate: 0.00411 +2024-11-22 13:40:56.324127: train_loss -0.799 +2024-11-22 13:40:56.324358: val_loss -0.7456 +2024-11-22 13:40:56.324431: Pseudo dice [0.854] +2024-11-22 13:40:56.324504: Epoch time: 18.84 s +2024-11-22 13:40:57.208819: +2024-11-22 13:40:57.209031: Epoch 5021 +2024-11-22 13:40:57.209148: Current learning rate: 0.00411 +2024-11-22 13:41:14.516501: train_loss -0.8014 +2024-11-22 13:41:14.516747: val_loss -0.7903 +2024-11-22 13:41:14.516858: Pseudo dice [0.8621] +2024-11-22 13:41:14.516946: Epoch time: 17.31 s +2024-11-22 13:41:15.399609: +2024-11-22 13:41:15.399849: Epoch 5022 +2024-11-22 13:41:15.399960: Current learning rate: 0.00411 +2024-11-22 13:41:34.889429: train_loss -0.7874 +2024-11-22 13:41:34.889685: val_loss -0.7757 +2024-11-22 13:41:34.889760: Pseudo dice [0.8449] +2024-11-22 13:41:34.889833: Epoch time: 19.49 s +2024-11-22 13:41:35.765419: +2024-11-22 13:41:35.765657: Epoch 5023 +2024-11-22 13:41:35.765778: Current learning rate: 0.00411 +2024-11-22 13:41:54.441705: train_loss -0.7969 +2024-11-22 13:41:54.441978: val_loss -0.7776 +2024-11-22 13:41:54.447250: Pseudo dice [0.8645] +2024-11-22 13:41:54.447477: Epoch time: 18.68 s +2024-11-22 13:41:55.444929: +2024-11-22 13:41:55.445150: Epoch 5024 +2024-11-22 13:41:55.445256: Current learning rate: 0.00411 +2024-11-22 13:42:13.845942: train_loss -0.7906 +2024-11-22 13:42:13.846191: val_loss -0.7793 +2024-11-22 13:42:13.846276: Pseudo dice [0.8678] +2024-11-22 13:42:13.846368: Epoch time: 18.4 s +2024-11-22 13:42:14.812410: +2024-11-22 13:42:14.812625: Epoch 5025 +2024-11-22 13:42:14.812734: Current learning rate: 0.00411 +2024-11-22 13:42:33.514345: train_loss -0.8058 +2024-11-22 13:42:33.514552: val_loss -0.7731 +2024-11-22 13:42:33.514624: Pseudo dice [0.8361] +2024-11-22 13:42:33.514699: Epoch time: 18.7 s +2024-11-22 13:42:34.770832: +2024-11-22 13:42:34.771067: Epoch 5026 +2024-11-22 13:42:34.771182: Current learning rate: 0.0041 +2024-11-22 13:42:53.458956: train_loss -0.7979 +2024-11-22 13:42:53.459226: val_loss -0.7677 +2024-11-22 13:42:53.459302: Pseudo dice [0.8456] +2024-11-22 13:42:53.459376: Epoch time: 18.69 s +2024-11-22 13:42:54.340492: +2024-11-22 13:42:54.340715: Epoch 5027 +2024-11-22 13:42:54.340826: Current learning rate: 0.0041 +2024-11-22 13:43:13.013370: train_loss -0.7981 +2024-11-22 13:43:13.013618: val_loss -0.768 +2024-11-22 13:43:13.013697: Pseudo dice [0.8578] +2024-11-22 13:43:13.013782: Epoch time: 18.67 s +2024-11-22 13:43:13.907295: +2024-11-22 13:43:13.907629: Epoch 5028 +2024-11-22 13:43:13.907741: Current learning rate: 0.0041 +2024-11-22 13:43:32.339493: train_loss -0.7958 +2024-11-22 13:43:32.339717: val_loss -0.7663 +2024-11-22 13:43:32.339793: Pseudo dice [0.8452] +2024-11-22 13:43:32.339867: Epoch time: 18.43 s +2024-11-22 13:43:33.226322: +2024-11-22 13:43:33.226563: Epoch 5029 +2024-11-22 13:43:33.226674: Current learning rate: 0.0041 +2024-11-22 13:43:52.360823: train_loss -0.7931 +2024-11-22 13:43:52.361120: val_loss -0.79 +2024-11-22 13:43:52.361197: Pseudo dice [0.8502] +2024-11-22 13:43:52.361272: Epoch time: 19.14 s +2024-11-22 13:43:53.238935: +2024-11-22 13:43:53.239165: Epoch 5030 +2024-11-22 13:43:53.239274: Current learning rate: 0.0041 +2024-11-22 13:44:12.868254: train_loss -0.7916 +2024-11-22 13:44:12.868479: val_loss -0.7698 +2024-11-22 13:44:12.868554: Pseudo dice [0.8467] +2024-11-22 13:44:12.868628: Epoch time: 19.63 s +2024-11-22 13:44:13.762884: +2024-11-22 13:44:13.763122: Epoch 5031 +2024-11-22 13:44:13.763236: Current learning rate: 0.0041 +2024-11-22 13:44:32.077802: train_loss -0.7801 +2024-11-22 13:44:32.078034: val_loss -0.7479 +2024-11-22 13:44:32.078108: Pseudo dice [0.8253] +2024-11-22 13:44:32.078186: Epoch time: 18.32 s +2024-11-22 13:44:33.004285: +2024-11-22 13:44:33.004506: Epoch 5032 +2024-11-22 13:44:33.004623: Current learning rate: 0.0041 +2024-11-22 13:44:52.587824: train_loss -0.7943 +2024-11-22 13:44:52.588068: val_loss -0.7788 +2024-11-22 13:44:52.588161: Pseudo dice [0.8479] +2024-11-22 13:44:52.588243: Epoch time: 19.58 s +2024-11-22 13:44:53.471554: +2024-11-22 13:44:53.471773: Epoch 5033 +2024-11-22 13:44:53.471881: Current learning rate: 0.0041 +2024-11-22 13:45:12.747958: train_loss -0.7933 +2024-11-22 13:45:12.748245: val_loss -0.7467 +2024-11-22 13:45:12.748322: Pseudo dice [0.8073] +2024-11-22 13:45:12.748397: Epoch time: 19.28 s +2024-11-22 13:45:13.898692: +2024-11-22 13:45:13.898921: Epoch 5034 +2024-11-22 13:45:13.899040: Current learning rate: 0.00409 +2024-11-22 13:45:32.877717: train_loss -0.7783 +2024-11-22 13:45:32.877941: val_loss -0.7483 +2024-11-22 13:45:32.878030: Pseudo dice [0.8375] +2024-11-22 13:45:32.878112: Epoch time: 18.98 s +2024-11-22 13:45:33.759657: +2024-11-22 13:45:33.759885: Epoch 5035 +2024-11-22 13:45:33.760005: Current learning rate: 0.00409 +2024-11-22 13:45:52.070509: train_loss -0.7836 +2024-11-22 13:45:52.070735: val_loss -0.7575 +2024-11-22 13:45:52.070844: Pseudo dice [0.8587] +2024-11-22 13:45:52.070928: Epoch time: 18.31 s +2024-11-22 13:45:52.960917: +2024-11-22 13:45:52.961237: Epoch 5036 +2024-11-22 13:45:52.961354: Current learning rate: 0.00409 +2024-11-22 13:46:10.941927: train_loss -0.7954 +2024-11-22 13:46:10.942151: val_loss -0.7841 +2024-11-22 13:46:10.942227: Pseudo dice [0.8506] +2024-11-22 13:46:10.942303: Epoch time: 17.98 s +2024-11-22 13:46:11.816565: +2024-11-22 13:46:11.816775: Epoch 5037 +2024-11-22 13:46:11.816884: Current learning rate: 0.00409 +2024-11-22 13:46:30.421417: train_loss -0.7867 +2024-11-22 13:46:30.421655: val_loss -0.7486 +2024-11-22 13:46:30.421731: Pseudo dice [0.825] +2024-11-22 13:46:30.421815: Epoch time: 18.61 s +2024-11-22 13:46:31.709948: +2024-11-22 13:46:31.710394: Epoch 5038 +2024-11-22 13:46:31.710524: Current learning rate: 0.00409 +2024-11-22 13:46:49.417202: train_loss -0.7982 +2024-11-22 13:46:49.418181: val_loss -0.7643 +2024-11-22 13:46:49.418335: Pseudo dice [0.8379] +2024-11-22 13:46:49.418421: Epoch time: 17.71 s +2024-11-22 13:46:50.301073: +2024-11-22 13:46:50.301526: Epoch 5039 +2024-11-22 13:46:50.301662: Current learning rate: 0.00409 +2024-11-22 13:47:08.354124: train_loss -0.7931 +2024-11-22 13:47:08.355113: val_loss -0.7728 +2024-11-22 13:47:08.355194: Pseudo dice [0.8436] +2024-11-22 13:47:08.355277: Epoch time: 18.05 s +2024-11-22 13:47:09.228481: +2024-11-22 13:47:09.228953: Epoch 5040 +2024-11-22 13:47:09.229092: Current learning rate: 0.00409 +2024-11-22 13:47:26.678292: train_loss -0.7985 +2024-11-22 13:47:26.678512: val_loss -0.7831 +2024-11-22 13:47:26.678593: Pseudo dice [0.8529] +2024-11-22 13:47:26.678689: Epoch time: 17.45 s +2024-11-22 13:47:27.559385: +2024-11-22 13:47:27.559805: Epoch 5041 +2024-11-22 13:47:27.559937: Current learning rate: 0.00409 +2024-11-22 13:47:46.148973: train_loss -0.8033 +2024-11-22 13:47:46.149192: val_loss -0.7788 +2024-11-22 13:47:46.149269: Pseudo dice [0.8422] +2024-11-22 13:47:46.149344: Epoch time: 18.59 s +2024-11-22 13:47:47.043856: +2024-11-22 13:47:47.044285: Epoch 5042 +2024-11-22 13:47:47.044418: Current learning rate: 0.00408 +2024-11-22 13:48:06.442549: train_loss -0.7919 +2024-11-22 13:48:06.443489: val_loss -0.7969 +2024-11-22 13:48:06.443569: Pseudo dice [0.8516] +2024-11-22 13:48:06.443645: Epoch time: 19.4 s +2024-11-22 13:48:07.322323: +2024-11-22 13:48:07.322762: Epoch 5043 +2024-11-22 13:48:07.322891: Current learning rate: 0.00408 +2024-11-22 13:48:26.059761: train_loss -0.7955 +2024-11-22 13:48:26.060024: val_loss -0.7868 +2024-11-22 13:48:26.060100: Pseudo dice [0.8422] +2024-11-22 13:48:26.060184: Epoch time: 18.74 s +2024-11-22 13:48:26.943202: +2024-11-22 13:48:26.943625: Epoch 5044 +2024-11-22 13:48:26.943764: Current learning rate: 0.00408 +2024-11-22 13:48:45.318082: train_loss -0.799 +2024-11-22 13:48:45.318305: val_loss -0.7805 +2024-11-22 13:48:45.318398: Pseudo dice [0.8538] +2024-11-22 13:48:45.318542: Epoch time: 18.38 s +2024-11-22 13:48:46.409911: +2024-11-22 13:48:46.410309: Epoch 5045 +2024-11-22 13:48:46.410444: Current learning rate: 0.00408 +2024-11-22 13:49:05.440406: train_loss -0.8043 +2024-11-22 13:49:05.440624: val_loss -0.7678 +2024-11-22 13:49:05.440698: Pseudo dice [0.8446] +2024-11-22 13:49:05.440781: Epoch time: 19.03 s +2024-11-22 13:49:06.320307: +2024-11-22 13:49:06.320738: Epoch 5046 +2024-11-22 13:49:06.320878: Current learning rate: 0.00408 +2024-11-22 13:49:24.634662: train_loss -0.7871 +2024-11-22 13:49:24.639195: val_loss -0.7703 +2024-11-22 13:49:24.639299: Pseudo dice [0.8334] +2024-11-22 13:49:24.639386: Epoch time: 18.32 s +2024-11-22 13:49:25.635450: +2024-11-22 13:49:25.635853: Epoch 5047 +2024-11-22 13:49:25.635983: Current learning rate: 0.00408 +2024-11-22 13:49:44.385468: train_loss -0.793 +2024-11-22 13:49:44.385706: val_loss -0.7605 +2024-11-22 13:49:44.385781: Pseudo dice [0.8446] +2024-11-22 13:49:44.385910: Epoch time: 18.75 s +2024-11-22 13:49:45.266634: +2024-11-22 13:49:45.266876: Epoch 5048 +2024-11-22 13:49:45.266987: Current learning rate: 0.00408 +2024-11-22 13:50:04.134603: train_loss -0.7858 +2024-11-22 13:50:04.134825: val_loss -0.7688 +2024-11-22 13:50:04.134899: Pseudo dice [0.8409] +2024-11-22 13:50:04.134975: Epoch time: 18.87 s +2024-11-22 13:50:05.067082: +2024-11-22 13:50:05.067308: Epoch 5049 +2024-11-22 13:50:05.067420: Current learning rate: 0.00408 +2024-11-22 13:50:24.249482: train_loss -0.79 +2024-11-22 13:50:24.249738: val_loss -0.7579 +2024-11-22 13:50:24.249816: Pseudo dice [0.8484] +2024-11-22 13:50:24.249890: Epoch time: 19.18 s +2024-11-22 13:50:25.862095: +2024-11-22 13:50:25.862322: Epoch 5050 +2024-11-22 13:50:25.862433: Current learning rate: 0.00407 +2024-11-22 13:50:43.695154: train_loss -0.7961 +2024-11-22 13:50:43.695413: val_loss -0.794 +2024-11-22 13:50:43.695489: Pseudo dice [0.855] +2024-11-22 13:50:43.695571: Epoch time: 17.83 s +2024-11-22 13:50:44.573491: +2024-11-22 13:50:44.573721: Epoch 5051 +2024-11-22 13:50:44.573830: Current learning rate: 0.00407 +2024-11-22 13:51:02.902486: train_loss -0.7903 +2024-11-22 13:51:02.902703: val_loss -0.7841 +2024-11-22 13:51:02.902776: Pseudo dice [0.8552] +2024-11-22 13:51:02.902850: Epoch time: 18.33 s +2024-11-22 13:51:03.800895: +2024-11-22 13:51:03.801122: Epoch 5052 +2024-11-22 13:51:03.801229: Current learning rate: 0.00407 +2024-11-22 13:51:22.076157: train_loss -0.7898 +2024-11-22 13:51:22.076383: val_loss -0.7947 +2024-11-22 13:51:22.076455: Pseudo dice [0.8491] +2024-11-22 13:51:22.081025: Epoch time: 18.28 s +2024-11-22 13:51:23.069248: +2024-11-22 13:51:23.069466: Epoch 5053 +2024-11-22 13:51:23.069578: Current learning rate: 0.00407 +2024-11-22 13:51:41.147180: train_loss -0.797 +2024-11-22 13:51:41.148598: val_loss -0.7849 +2024-11-22 13:51:41.148679: Pseudo dice [0.8311] +2024-11-22 13:51:41.148764: Epoch time: 18.08 s +2024-11-22 13:51:42.031601: +2024-11-22 13:51:42.031824: Epoch 5054 +2024-11-22 13:51:42.031935: Current learning rate: 0.00407 +2024-11-22 13:51:59.689967: train_loss -0.7911 +2024-11-22 13:51:59.690222: val_loss -0.775 +2024-11-22 13:51:59.691492: Pseudo dice [0.8538] +2024-11-22 13:51:59.691629: Epoch time: 17.66 s +2024-11-22 13:52:00.588788: +2024-11-22 13:52:00.589020: Epoch 5055 +2024-11-22 13:52:00.589133: Current learning rate: 0.00407 +2024-11-22 13:52:20.097903: train_loss -0.7936 +2024-11-22 13:52:20.098495: val_loss -0.757 +2024-11-22 13:52:20.098619: Pseudo dice [0.8284] +2024-11-22 13:52:20.098703: Epoch time: 19.51 s +2024-11-22 13:52:20.994149: +2024-11-22 13:52:20.994370: Epoch 5056 +2024-11-22 13:52:20.994478: Current learning rate: 0.00407 +2024-11-22 13:52:40.200057: train_loss -0.7815 +2024-11-22 13:52:40.200289: val_loss -0.7544 +2024-11-22 13:52:40.200366: Pseudo dice [0.8383] +2024-11-22 13:52:40.200440: Epoch time: 19.21 s +2024-11-22 13:52:41.239714: +2024-11-22 13:52:41.239923: Epoch 5057 +2024-11-22 13:52:41.240039: Current learning rate: 0.00407 +2024-11-22 13:52:59.292860: train_loss -0.7932 +2024-11-22 13:52:59.293144: val_loss -0.7818 +2024-11-22 13:52:59.293223: Pseudo dice [0.8598] +2024-11-22 13:52:59.293306: Epoch time: 18.05 s +2024-11-22 13:53:00.177738: +2024-11-22 13:53:00.177956: Epoch 5058 +2024-11-22 13:53:00.178077: Current learning rate: 0.00406 +2024-11-22 13:53:17.622223: train_loss -0.7978 +2024-11-22 13:53:17.622441: val_loss -0.7596 +2024-11-22 13:53:17.622518: Pseudo dice [0.8299] +2024-11-22 13:53:17.622687: Epoch time: 17.45 s +2024-11-22 13:53:18.503408: +2024-11-22 13:53:18.503626: Epoch 5059 +2024-11-22 13:53:18.503739: Current learning rate: 0.00406 +2024-11-22 13:53:36.679744: train_loss -0.7941 +2024-11-22 13:53:36.683694: val_loss -0.7688 +2024-11-22 13:53:36.683791: Pseudo dice [0.8463] +2024-11-22 13:53:36.683869: Epoch time: 18.18 s +2024-11-22 13:53:37.563524: +2024-11-22 13:53:37.563727: Epoch 5060 +2024-11-22 13:53:37.563841: Current learning rate: 0.00406 +2024-11-22 13:53:55.431193: train_loss -0.8083 +2024-11-22 13:53:55.431417: val_loss -0.7685 +2024-11-22 13:53:55.431497: Pseudo dice [0.8403] +2024-11-22 13:53:55.431587: Epoch time: 17.87 s +2024-11-22 13:53:56.703470: +2024-11-22 13:53:56.703722: Epoch 5061 +2024-11-22 13:53:56.703838: Current learning rate: 0.00406 +2024-11-22 13:54:14.767225: train_loss -0.8029 +2024-11-22 13:54:14.767500: val_loss -0.7572 +2024-11-22 13:54:14.767577: Pseudo dice [0.8436] +2024-11-22 13:54:14.767678: Epoch time: 18.06 s +2024-11-22 13:54:15.648406: +2024-11-22 13:54:15.648636: Epoch 5062 +2024-11-22 13:54:15.648744: Current learning rate: 0.00406 +2024-11-22 13:54:33.805473: train_loss -0.799 +2024-11-22 13:54:33.805688: val_loss -0.7907 +2024-11-22 13:54:33.805764: Pseudo dice [0.8636] +2024-11-22 13:54:33.805836: Epoch time: 18.16 s +2024-11-22 13:54:34.681339: +2024-11-22 13:54:34.681559: Epoch 5063 +2024-11-22 13:54:34.681666: Current learning rate: 0.00406 +2024-11-22 13:54:52.754091: train_loss -0.7968 +2024-11-22 13:54:52.754313: val_loss -0.7911 +2024-11-22 13:54:52.754454: Pseudo dice [0.8574] +2024-11-22 13:54:52.754529: Epoch time: 18.07 s +2024-11-22 13:54:53.635092: +2024-11-22 13:54:53.635332: Epoch 5064 +2024-11-22 13:54:53.635489: Current learning rate: 0.00406 +2024-11-22 13:55:11.383809: train_loss -0.7874 +2024-11-22 13:55:11.384074: val_loss -0.7232 +2024-11-22 13:55:11.384151: Pseudo dice [0.8356] +2024-11-22 13:55:11.384239: Epoch time: 17.75 s +2024-11-22 13:55:12.272561: +2024-11-22 13:55:12.272801: Epoch 5065 +2024-11-22 13:55:12.272934: Current learning rate: 0.00406 +2024-11-22 13:55:30.676443: train_loss -0.7834 +2024-11-22 13:55:30.676727: val_loss -0.7679 +2024-11-22 13:55:30.676812: Pseudo dice [0.8502] +2024-11-22 13:55:30.676890: Epoch time: 18.4 s +2024-11-22 13:55:31.557614: +2024-11-22 13:55:31.557876: Epoch 5066 +2024-11-22 13:55:31.557993: Current learning rate: 0.00405 +2024-11-22 13:55:49.860952: train_loss -0.7939 +2024-11-22 13:55:49.861192: val_loss -0.7599 +2024-11-22 13:55:49.861272: Pseudo dice [0.8508] +2024-11-22 13:55:49.861345: Epoch time: 18.3 s +2024-11-22 13:55:50.741186: +2024-11-22 13:55:50.741383: Epoch 5067 +2024-11-22 13:55:50.741489: Current learning rate: 0.00405 +2024-11-22 13:56:09.772804: train_loss -0.7848 +2024-11-22 13:56:09.776747: val_loss -0.7772 +2024-11-22 13:56:09.776878: Pseudo dice [0.8404] +2024-11-22 13:56:09.776961: Epoch time: 19.03 s +2024-11-22 13:56:10.666109: +2024-11-22 13:56:10.666320: Epoch 5068 +2024-11-22 13:56:10.666438: Current learning rate: 0.00405 +2024-11-22 13:56:30.209032: train_loss -0.7789 +2024-11-22 13:56:30.209264: val_loss -0.7733 +2024-11-22 13:56:30.209340: Pseudo dice [0.847] +2024-11-22 13:56:30.211637: Epoch time: 19.54 s +2024-11-22 13:56:31.226025: +2024-11-22 13:56:31.226252: Epoch 5069 +2024-11-22 13:56:31.226368: Current learning rate: 0.00405 +2024-11-22 13:56:49.521408: train_loss -0.7691 +2024-11-22 13:56:49.521626: val_loss -0.7811 +2024-11-22 13:56:49.521700: Pseudo dice [0.8447] +2024-11-22 13:56:49.521773: Epoch time: 18.3 s +2024-11-22 13:56:50.407562: +2024-11-22 13:56:50.407783: Epoch 5070 +2024-11-22 13:56:50.407902: Current learning rate: 0.00405 +2024-11-22 13:57:08.964228: train_loss -0.7824 +2024-11-22 13:57:08.964451: val_loss -0.7572 +2024-11-22 13:57:08.964525: Pseudo dice [0.8468] +2024-11-22 13:57:08.964598: Epoch time: 18.56 s +2024-11-22 13:57:09.840930: +2024-11-22 13:57:09.841151: Epoch 5071 +2024-11-22 13:57:09.841267: Current learning rate: 0.00405 +2024-11-22 13:57:27.949984: train_loss -0.7841 +2024-11-22 13:57:27.950237: val_loss -0.7672 +2024-11-22 13:57:27.950312: Pseudo dice [0.8371] +2024-11-22 13:57:27.950393: Epoch time: 18.11 s +2024-11-22 13:57:28.834134: +2024-11-22 13:57:28.834342: Epoch 5072 +2024-11-22 13:57:28.834468: Current learning rate: 0.00405 +2024-11-22 13:57:47.494507: train_loss -0.7701 +2024-11-22 13:57:47.494723: val_loss -0.7644 +2024-11-22 13:57:47.494801: Pseudo dice [0.8452] +2024-11-22 13:57:47.494876: Epoch time: 18.66 s +2024-11-22 13:57:48.718616: +2024-11-22 13:57:48.718827: Epoch 5073 +2024-11-22 13:57:48.718936: Current learning rate: 0.00405 +2024-11-22 13:58:06.966946: train_loss -0.7904 +2024-11-22 13:58:06.968144: val_loss -0.7541 +2024-11-22 13:58:06.968245: Pseudo dice [0.8586] +2024-11-22 13:58:06.968320: Epoch time: 18.25 s +2024-11-22 13:58:07.850531: +2024-11-22 13:58:07.850755: Epoch 5074 +2024-11-22 13:58:07.850861: Current learning rate: 0.00404 +2024-11-22 13:58:25.658633: train_loss -0.7866 +2024-11-22 13:58:25.658848: val_loss -0.7473 +2024-11-22 13:58:25.658952: Pseudo dice [0.8449] +2024-11-22 13:58:25.659037: Epoch time: 17.81 s +2024-11-22 13:58:26.548946: +2024-11-22 13:58:26.549190: Epoch 5075 +2024-11-22 13:58:26.549301: Current learning rate: 0.00404 +2024-11-22 13:58:46.238664: train_loss -0.7871 +2024-11-22 13:58:46.241069: val_loss -0.7923 +2024-11-22 13:58:46.241205: Pseudo dice [0.8618] +2024-11-22 13:58:46.241336: Epoch time: 19.69 s +2024-11-22 13:58:47.128604: +2024-11-22 13:58:47.128824: Epoch 5076 +2024-11-22 13:58:47.128933: Current learning rate: 0.00404 +2024-11-22 13:59:05.760329: train_loss -0.7893 +2024-11-22 13:59:05.760548: val_loss -0.769 +2024-11-22 13:59:05.760625: Pseudo dice [0.8468] +2024-11-22 13:59:05.760702: Epoch time: 18.63 s +2024-11-22 13:59:06.639280: +2024-11-22 13:59:06.639494: Epoch 5077 +2024-11-22 13:59:06.639604: Current learning rate: 0.00404 +2024-11-22 13:59:25.277458: train_loss -0.799 +2024-11-22 13:59:25.277681: val_loss -0.7847 +2024-11-22 13:59:25.277757: Pseudo dice [0.8419] +2024-11-22 13:59:25.277836: Epoch time: 18.64 s +2024-11-22 13:59:26.168381: +2024-11-22 13:59:26.168596: Epoch 5078 +2024-11-22 13:59:26.168703: Current learning rate: 0.00404 +2024-11-22 13:59:45.256171: train_loss -0.7969 +2024-11-22 13:59:45.256391: val_loss -0.7839 +2024-11-22 13:59:45.256464: Pseudo dice [0.844] +2024-11-22 13:59:45.256546: Epoch time: 19.09 s +2024-11-22 13:59:46.144332: +2024-11-22 13:59:46.144553: Epoch 5079 +2024-11-22 13:59:46.144661: Current learning rate: 0.00404 +2024-11-22 14:00:05.369878: train_loss -0.8024 +2024-11-22 14:00:05.370215: val_loss -0.7488 +2024-11-22 14:00:05.370298: Pseudo dice [0.8345] +2024-11-22 14:00:05.370380: Epoch time: 19.23 s +2024-11-22 14:00:06.258524: +2024-11-22 14:00:06.258733: Epoch 5080 +2024-11-22 14:00:06.258840: Current learning rate: 0.00404 +2024-11-22 14:00:24.887969: train_loss -0.7926 +2024-11-22 14:00:24.888252: val_loss -0.7636 +2024-11-22 14:00:24.888354: Pseudo dice [0.8482] +2024-11-22 14:00:24.888436: Epoch time: 18.63 s +2024-11-22 14:00:25.775262: +2024-11-22 14:00:25.775492: Epoch 5081 +2024-11-22 14:00:25.775601: Current learning rate: 0.00404 +2024-11-22 14:00:43.551694: train_loss -0.788 +2024-11-22 14:00:43.551908: val_loss -0.7863 +2024-11-22 14:00:43.551981: Pseudo dice [0.8388] +2024-11-22 14:00:43.552063: Epoch time: 17.78 s +2024-11-22 14:00:44.441436: +2024-11-22 14:00:44.441760: Epoch 5082 +2024-11-22 14:00:44.441875: Current learning rate: 0.00403 +2024-11-22 14:01:02.018743: train_loss -0.7988 +2024-11-22 14:01:02.018987: val_loss -0.7903 +2024-11-22 14:01:02.019068: Pseudo dice [0.855] +2024-11-22 14:01:02.019151: Epoch time: 17.58 s +2024-11-22 14:01:02.899033: +2024-11-22 14:01:02.899252: Epoch 5083 +2024-11-22 14:01:02.899362: Current learning rate: 0.00403 +2024-11-22 14:01:20.875607: train_loss -0.7962 +2024-11-22 14:01:20.875815: val_loss -0.781 +2024-11-22 14:01:20.875888: Pseudo dice [0.8519] +2024-11-22 14:01:20.875963: Epoch time: 17.98 s +2024-11-22 14:01:21.748352: +2024-11-22 14:01:21.748565: Epoch 5084 +2024-11-22 14:01:21.748673: Current learning rate: 0.00403 +2024-11-22 14:01:40.527985: train_loss -0.7863 +2024-11-22 14:01:40.528215: val_loss -0.7769 +2024-11-22 14:01:40.528315: Pseudo dice [0.8391] +2024-11-22 14:01:40.528395: Epoch time: 18.78 s +2024-11-22 14:01:41.814683: +2024-11-22 14:01:41.814903: Epoch 5085 +2024-11-22 14:01:41.815035: Current learning rate: 0.00403 +2024-11-22 14:02:00.445042: train_loss -0.7979 +2024-11-22 14:02:00.445301: val_loss -0.7521 +2024-11-22 14:02:00.445395: Pseudo dice [0.8485] +2024-11-22 14:02:00.445483: Epoch time: 18.63 s +2024-11-22 14:02:01.338706: +2024-11-22 14:02:01.338935: Epoch 5086 +2024-11-22 14:02:01.339050: Current learning rate: 0.00403 +2024-11-22 14:02:19.726889: train_loss -0.7926 +2024-11-22 14:02:19.727114: val_loss -0.7866 +2024-11-22 14:02:19.727207: Pseudo dice [0.8633] +2024-11-22 14:02:19.727343: Epoch time: 18.39 s +2024-11-22 14:02:20.617913: +2024-11-22 14:02:20.618122: Epoch 5087 +2024-11-22 14:02:20.618231: Current learning rate: 0.00403 +2024-11-22 14:02:38.689590: train_loss -0.7983 +2024-11-22 14:02:38.690652: val_loss -0.765 +2024-11-22 14:02:38.690730: Pseudo dice [0.8558] +2024-11-22 14:02:38.690805: Epoch time: 18.07 s +2024-11-22 14:02:39.567424: +2024-11-22 14:02:39.567640: Epoch 5088 +2024-11-22 14:02:39.567751: Current learning rate: 0.00403 +2024-11-22 14:02:57.579483: train_loss -0.792 +2024-11-22 14:02:57.579717: val_loss -0.7422 +2024-11-22 14:02:57.579803: Pseudo dice [0.8399] +2024-11-22 14:02:57.579887: Epoch time: 18.01 s +2024-11-22 14:02:58.465649: +2024-11-22 14:02:58.465854: Epoch 5089 +2024-11-22 14:02:58.465966: Current learning rate: 0.00403 +2024-11-22 14:03:17.168225: train_loss -0.7947 +2024-11-22 14:03:17.168480: val_loss -0.7751 +2024-11-22 14:03:17.168556: Pseudo dice [0.8463] +2024-11-22 14:03:17.168635: Epoch time: 18.7 s +2024-11-22 14:03:18.053505: +2024-11-22 14:03:18.053735: Epoch 5090 +2024-11-22 14:03:18.053848: Current learning rate: 0.00402 +2024-11-22 14:03:36.341878: train_loss -0.7999 +2024-11-22 14:03:36.342103: val_loss -0.76 +2024-11-22 14:03:36.342176: Pseudo dice [0.8656] +2024-11-22 14:03:36.342252: Epoch time: 18.29 s +2024-11-22 14:03:37.226035: +2024-11-22 14:03:37.226257: Epoch 5091 +2024-11-22 14:03:37.226367: Current learning rate: 0.00402 +2024-11-22 14:03:55.389455: train_loss -0.7853 +2024-11-22 14:03:55.389727: val_loss -0.7325 +2024-11-22 14:03:55.389844: Pseudo dice [0.8302] +2024-11-22 14:03:55.389922: Epoch time: 18.16 s +2024-11-22 14:03:56.272404: +2024-11-22 14:03:56.272609: Epoch 5092 +2024-11-22 14:03:56.272718: Current learning rate: 0.00402 +2024-11-22 14:04:14.780219: train_loss -0.7928 +2024-11-22 14:04:14.780551: val_loss -0.7756 +2024-11-22 14:04:14.780629: Pseudo dice [0.8542] +2024-11-22 14:04:14.780714: Epoch time: 18.51 s +2024-11-22 14:04:15.668311: +2024-11-22 14:04:15.668521: Epoch 5093 +2024-11-22 14:04:15.668629: Current learning rate: 0.00402 +2024-11-22 14:04:34.098260: train_loss -0.7965 +2024-11-22 14:04:34.098478: val_loss -0.7706 +2024-11-22 14:04:34.098553: Pseudo dice [0.8319] +2024-11-22 14:04:34.098629: Epoch time: 18.43 s +2024-11-22 14:04:34.974292: +2024-11-22 14:04:34.974487: Epoch 5094 +2024-11-22 14:04:34.974597: Current learning rate: 0.00402 +2024-11-22 14:04:53.927120: train_loss -0.8003 +2024-11-22 14:04:53.927371: val_loss -0.7514 +2024-11-22 14:04:53.927454: Pseudo dice [0.8512] +2024-11-22 14:04:53.927538: Epoch time: 18.95 s +2024-11-22 14:04:55.031091: +2024-11-22 14:04:55.031315: Epoch 5095 +2024-11-22 14:04:55.031428: Current learning rate: 0.00402 +2024-11-22 14:05:13.193343: train_loss -0.7962 +2024-11-22 14:05:13.193570: val_loss -0.7585 +2024-11-22 14:05:13.193644: Pseudo dice [0.8358] +2024-11-22 14:05:13.193719: Epoch time: 18.16 s +2024-11-22 14:05:14.107535: +2024-11-22 14:05:14.107753: Epoch 5096 +2024-11-22 14:05:14.107873: Current learning rate: 0.00402 +2024-11-22 14:05:33.680327: train_loss -0.7969 +2024-11-22 14:05:33.680571: val_loss -0.7768 +2024-11-22 14:05:33.680648: Pseudo dice [0.8501] +2024-11-22 14:05:33.680728: Epoch time: 19.57 s +2024-11-22 14:05:34.938810: +2024-11-22 14:05:34.939057: Epoch 5097 +2024-11-22 14:05:34.939173: Current learning rate: 0.00402 +2024-11-22 14:05:54.064546: train_loss -0.7852 +2024-11-22 14:05:54.064776: val_loss -0.7682 +2024-11-22 14:05:54.064848: Pseudo dice [0.8505] +2024-11-22 14:05:54.064919: Epoch time: 19.13 s +2024-11-22 14:05:54.939958: +2024-11-22 14:05:54.940166: Epoch 5098 +2024-11-22 14:05:54.940281: Current learning rate: 0.00401 +2024-11-22 14:06:13.041720: train_loss -0.7925 +2024-11-22 14:06:13.041937: val_loss -0.7757 +2024-11-22 14:06:13.042017: Pseudo dice [0.8389] +2024-11-22 14:06:13.042095: Epoch time: 18.1 s +2024-11-22 14:06:13.957758: +2024-11-22 14:06:13.957961: Epoch 5099 +2024-11-22 14:06:13.958072: Current learning rate: 0.00401 +2024-11-22 14:06:32.923228: train_loss -0.7944 +2024-11-22 14:06:32.923532: val_loss -0.8 +2024-11-22 14:06:32.923622: Pseudo dice [0.8655] +2024-11-22 14:06:32.923706: Epoch time: 18.97 s +2024-11-22 14:06:34.108773: +2024-11-22 14:06:34.109046: Epoch 5100 +2024-11-22 14:06:34.109162: Current learning rate: 0.00401 +2024-11-22 14:06:51.882489: train_loss -0.7961 +2024-11-22 14:06:51.882703: val_loss -0.7627 +2024-11-22 14:06:51.882778: Pseudo dice [0.8209] +2024-11-22 14:06:51.882852: Epoch time: 17.77 s +2024-11-22 14:06:52.766250: +2024-11-22 14:06:52.766475: Epoch 5101 +2024-11-22 14:06:52.766582: Current learning rate: 0.00401 +2024-11-22 14:07:11.298129: train_loss -0.7944 +2024-11-22 14:07:11.298333: val_loss -0.7932 +2024-11-22 14:07:11.298405: Pseudo dice [0.8549] +2024-11-22 14:07:11.298479: Epoch time: 18.53 s +2024-11-22 14:07:12.184087: +2024-11-22 14:07:12.184311: Epoch 5102 +2024-11-22 14:07:12.184420: Current learning rate: 0.00401 +2024-11-22 14:07:29.603572: train_loss -0.7907 +2024-11-22 14:07:29.603790: val_loss -0.7566 +2024-11-22 14:07:29.603867: Pseudo dice [0.8566] +2024-11-22 14:07:29.603942: Epoch time: 17.42 s +2024-11-22 14:07:30.492610: +2024-11-22 14:07:30.492853: Epoch 5103 +2024-11-22 14:07:30.492975: Current learning rate: 0.00401 +2024-11-22 14:07:50.443985: train_loss -0.7768 +2024-11-22 14:07:50.444233: val_loss -0.7776 +2024-11-22 14:07:50.444304: Pseudo dice [0.8606] +2024-11-22 14:07:50.444402: Epoch time: 19.95 s +2024-11-22 14:07:51.333878: +2024-11-22 14:07:51.334099: Epoch 5104 +2024-11-22 14:07:51.334212: Current learning rate: 0.00401 +2024-11-22 14:08:09.619272: train_loss -0.7726 +2024-11-22 14:08:09.619483: val_loss -0.7984 +2024-11-22 14:08:09.619556: Pseudo dice [0.8614] +2024-11-22 14:08:09.619632: Epoch time: 18.29 s +2024-11-22 14:08:10.502046: +2024-11-22 14:08:10.502254: Epoch 5105 +2024-11-22 14:08:10.502365: Current learning rate: 0.00401 +2024-11-22 14:08:28.904297: train_loss -0.7812 +2024-11-22 14:08:28.906701: val_loss -0.7614 +2024-11-22 14:08:28.906832: Pseudo dice [0.836] +2024-11-22 14:08:28.906909: Epoch time: 18.4 s +2024-11-22 14:08:29.948576: +2024-11-22 14:08:29.948881: Epoch 5106 +2024-11-22 14:08:29.948995: Current learning rate: 0.004 +2024-11-22 14:08:48.074530: train_loss -0.7778 +2024-11-22 14:08:48.074751: val_loss -0.7648 +2024-11-22 14:08:48.074826: Pseudo dice [0.8355] +2024-11-22 14:08:48.074905: Epoch time: 18.13 s +2024-11-22 14:08:48.966713: +2024-11-22 14:08:48.966961: Epoch 5107 +2024-11-22 14:08:48.967118: Current learning rate: 0.004 +2024-11-22 14:09:08.489748: train_loss -0.7872 +2024-11-22 14:09:08.489966: val_loss -0.7802 +2024-11-22 14:09:08.490047: Pseudo dice [0.8583] +2024-11-22 14:09:08.490124: Epoch time: 19.52 s +2024-11-22 14:09:09.389984: +2024-11-22 14:09:09.390207: Epoch 5108 +2024-11-22 14:09:09.390314: Current learning rate: 0.004 +2024-11-22 14:09:27.680625: train_loss -0.7872 +2024-11-22 14:09:27.681144: val_loss -0.7683 +2024-11-22 14:09:27.681271: Pseudo dice [0.8368] +2024-11-22 14:09:27.681401: Epoch time: 18.29 s +2024-11-22 14:09:28.568524: +2024-11-22 14:09:28.568756: Epoch 5109 +2024-11-22 14:09:28.568869: Current learning rate: 0.004 +2024-11-22 14:09:47.491762: train_loss -0.7912 +2024-11-22 14:09:47.492006: val_loss -0.7864 +2024-11-22 14:09:47.492088: Pseudo dice [0.8478] +2024-11-22 14:09:47.492169: Epoch time: 18.92 s +2024-11-22 14:09:48.377614: +2024-11-22 14:09:48.377844: Epoch 5110 +2024-11-22 14:09:48.377954: Current learning rate: 0.004 +2024-11-22 14:10:07.666798: train_loss -0.7957 +2024-11-22 14:10:07.667053: val_loss -0.7667 +2024-11-22 14:10:07.667128: Pseudo dice [0.8515] +2024-11-22 14:10:07.667206: Epoch time: 19.29 s +2024-11-22 14:10:08.560000: +2024-11-22 14:10:08.560230: Epoch 5111 +2024-11-22 14:10:08.560342: Current learning rate: 0.004 +2024-11-22 14:10:27.130971: train_loss -0.7995 +2024-11-22 14:10:27.131197: val_loss -0.7603 +2024-11-22 14:10:27.131366: Pseudo dice [0.8611] +2024-11-22 14:10:27.131444: Epoch time: 18.57 s +2024-11-22 14:10:28.012650: +2024-11-22 14:10:28.012876: Epoch 5112 +2024-11-22 14:10:28.012987: Current learning rate: 0.004 +2024-11-22 14:10:45.850544: train_loss -0.7869 +2024-11-22 14:10:45.850771: val_loss -0.7587 +2024-11-22 14:10:45.850850: Pseudo dice [0.8103] +2024-11-22 14:10:45.850928: Epoch time: 17.84 s +2024-11-22 14:10:46.747366: +2024-11-22 14:10:46.747673: Epoch 5113 +2024-11-22 14:10:46.747786: Current learning rate: 0.004 +2024-11-22 14:11:06.128968: train_loss -0.7666 +2024-11-22 14:11:06.129192: val_loss -0.7921 +2024-11-22 14:11:06.129268: Pseudo dice [0.8666] +2024-11-22 14:11:06.129342: Epoch time: 19.38 s +2024-11-22 14:11:07.028981: +2024-11-22 14:11:07.029208: Epoch 5114 +2024-11-22 14:11:07.029315: Current learning rate: 0.00399 +2024-11-22 14:11:26.331958: train_loss -0.7777 +2024-11-22 14:11:26.332210: val_loss -0.766 +2024-11-22 14:11:26.332285: Pseudo dice [0.845] +2024-11-22 14:11:26.332371: Epoch time: 19.3 s +2024-11-22 14:11:27.220097: +2024-11-22 14:11:27.220340: Epoch 5115 +2024-11-22 14:11:27.220459: Current learning rate: 0.00399 +2024-11-22 14:11:45.995311: train_loss -0.7849 +2024-11-22 14:11:45.995542: val_loss -0.7695 +2024-11-22 14:11:45.995620: Pseudo dice [0.823] +2024-11-22 14:11:45.995696: Epoch time: 18.78 s +2024-11-22 14:11:46.921289: +2024-11-22 14:11:46.921513: Epoch 5116 +2024-11-22 14:11:46.921622: Current learning rate: 0.00399 +2024-11-22 14:12:05.537267: train_loss -0.7822 +2024-11-22 14:12:05.537485: val_loss -0.7772 +2024-11-22 14:12:05.537559: Pseudo dice [0.839] +2024-11-22 14:12:05.537655: Epoch time: 18.62 s +2024-11-22 14:12:06.412335: +2024-11-22 14:12:06.412567: Epoch 5117 +2024-11-22 14:12:06.412678: Current learning rate: 0.00399 +2024-11-22 14:12:25.404958: train_loss -0.7872 +2024-11-22 14:12:25.405198: val_loss -0.7719 +2024-11-22 14:12:25.405275: Pseudo dice [0.8395] +2024-11-22 14:12:25.405352: Epoch time: 18.99 s +2024-11-22 14:12:26.288530: +2024-11-22 14:12:26.288770: Epoch 5118 +2024-11-22 14:12:26.288892: Current learning rate: 0.00399 +2024-11-22 14:12:44.913169: train_loss -0.793 +2024-11-22 14:12:44.913392: val_loss -0.7736 +2024-11-22 14:12:44.913472: Pseudo dice [0.8588] +2024-11-22 14:12:44.913553: Epoch time: 18.63 s +2024-11-22 14:12:45.793626: +2024-11-22 14:12:45.793857: Epoch 5119 +2024-11-22 14:12:45.793978: Current learning rate: 0.00399 +2024-11-22 14:13:04.541855: train_loss -0.7956 +2024-11-22 14:13:04.542079: val_loss -0.7607 +2024-11-22 14:13:04.542156: Pseudo dice [0.8419] +2024-11-22 14:13:04.542233: Epoch time: 18.75 s +2024-11-22 14:13:05.827098: +2024-11-22 14:13:05.827322: Epoch 5120 +2024-11-22 14:13:05.827431: Current learning rate: 0.00399 +2024-11-22 14:13:23.822690: train_loss -0.788 +2024-11-22 14:13:23.823015: val_loss -0.7785 +2024-11-22 14:13:23.823093: Pseudo dice [0.8534] +2024-11-22 14:13:23.823178: Epoch time: 18.0 s +2024-11-22 14:13:24.710690: +2024-11-22 14:13:24.710913: Epoch 5121 +2024-11-22 14:13:24.711025: Current learning rate: 0.00399 +2024-11-22 14:13:44.426492: train_loss -0.7926 +2024-11-22 14:13:44.426770: val_loss -0.7516 +2024-11-22 14:13:44.426847: Pseudo dice [0.8425] +2024-11-22 14:13:44.426926: Epoch time: 19.72 s +2024-11-22 14:13:45.311239: +2024-11-22 14:13:45.311435: Epoch 5122 +2024-11-22 14:13:45.311547: Current learning rate: 0.00398 +2024-11-22 14:14:04.412084: train_loss -0.7953 +2024-11-22 14:14:04.412300: val_loss -0.7718 +2024-11-22 14:14:04.412376: Pseudo dice [0.8445] +2024-11-22 14:14:04.412451: Epoch time: 19.1 s +2024-11-22 14:14:05.398704: +2024-11-22 14:14:05.398964: Epoch 5123 +2024-11-22 14:14:05.399092: Current learning rate: 0.00398 +2024-11-22 14:14:24.162639: train_loss -0.7987 +2024-11-22 14:14:24.162892: val_loss -0.8012 +2024-11-22 14:14:24.162975: Pseudo dice [0.8648] +2024-11-22 14:14:24.163056: Epoch time: 18.76 s +2024-11-22 14:14:25.097958: +2024-11-22 14:14:25.098189: Epoch 5124 +2024-11-22 14:14:25.098299: Current learning rate: 0.00398 +2024-11-22 14:14:43.019757: train_loss -0.7967 +2024-11-22 14:14:43.020009: val_loss -0.7762 +2024-11-22 14:14:43.020091: Pseudo dice [0.8479] +2024-11-22 14:14:43.020178: Epoch time: 17.92 s +2024-11-22 14:14:43.912071: +2024-11-22 14:14:43.912338: Epoch 5125 +2024-11-22 14:14:43.912449: Current learning rate: 0.00398 +2024-11-22 14:15:01.457004: train_loss -0.7977 +2024-11-22 14:15:01.457246: val_loss -0.7835 +2024-11-22 14:15:01.457318: Pseudo dice [0.8263] +2024-11-22 14:15:01.457391: Epoch time: 17.55 s +2024-11-22 14:15:02.434398: +2024-11-22 14:15:02.434613: Epoch 5126 +2024-11-22 14:15:02.434723: Current learning rate: 0.00398 +2024-11-22 14:15:20.521815: train_loss -0.7744 +2024-11-22 14:15:20.522047: val_loss -0.75 +2024-11-22 14:15:20.522123: Pseudo dice [0.8456] +2024-11-22 14:15:20.522197: Epoch time: 18.09 s +2024-11-22 14:15:21.403015: +2024-11-22 14:15:21.403238: Epoch 5127 +2024-11-22 14:15:21.403348: Current learning rate: 0.00398 +2024-11-22 14:15:40.491072: train_loss -0.7802 +2024-11-22 14:15:40.491292: val_loss -0.78 +2024-11-22 14:15:40.491365: Pseudo dice [0.8425] +2024-11-22 14:15:40.491506: Epoch time: 19.09 s +2024-11-22 14:15:41.409712: +2024-11-22 14:15:41.409927: Epoch 5128 +2024-11-22 14:15:41.410044: Current learning rate: 0.00398 +2024-11-22 14:16:00.587618: train_loss -0.7869 +2024-11-22 14:16:00.587862: val_loss -0.7555 +2024-11-22 14:16:00.587937: Pseudo dice [0.8309] +2024-11-22 14:16:00.588022: Epoch time: 19.18 s +2024-11-22 14:16:01.579446: +2024-11-22 14:16:01.579654: Epoch 5129 +2024-11-22 14:16:01.579764: Current learning rate: 0.00398 +2024-11-22 14:16:19.799478: train_loss -0.7911 +2024-11-22 14:16:19.799688: val_loss -0.7705 +2024-11-22 14:16:19.799766: Pseudo dice [0.8546] +2024-11-22 14:16:19.799842: Epoch time: 18.22 s +2024-11-22 14:16:20.679291: +2024-11-22 14:16:20.679507: Epoch 5130 +2024-11-22 14:16:20.679615: Current learning rate: 0.00397 +2024-11-22 14:16:40.143333: train_loss -0.7927 +2024-11-22 14:16:40.143611: val_loss -0.7785 +2024-11-22 14:16:40.143687: Pseudo dice [0.8634] +2024-11-22 14:16:40.143762: Epoch time: 19.46 s +2024-11-22 14:16:41.026576: +2024-11-22 14:16:41.026864: Epoch 5131 +2024-11-22 14:16:41.026987: Current learning rate: 0.00397 +2024-11-22 14:16:58.551373: train_loss -0.7903 +2024-11-22 14:16:58.551629: val_loss -0.7829 +2024-11-22 14:16:58.551712: Pseudo dice [0.8467] +2024-11-22 14:16:58.551792: Epoch time: 17.53 s +2024-11-22 14:16:59.867121: +2024-11-22 14:16:59.867346: Epoch 5132 +2024-11-22 14:16:59.867453: Current learning rate: 0.00397 +2024-11-22 14:17:17.932441: train_loss -0.7854 +2024-11-22 14:17:17.932671: val_loss -0.7719 +2024-11-22 14:17:17.932745: Pseudo dice [0.8432] +2024-11-22 14:17:17.932819: Epoch time: 18.07 s +2024-11-22 14:17:18.818730: +2024-11-22 14:17:18.818953: Epoch 5133 +2024-11-22 14:17:18.819076: Current learning rate: 0.00397 +2024-11-22 14:17:38.551187: train_loss -0.7893 +2024-11-22 14:17:38.551401: val_loss -0.7804 +2024-11-22 14:17:38.551477: Pseudo dice [0.854] +2024-11-22 14:17:38.551550: Epoch time: 19.73 s +2024-11-22 14:17:39.438901: +2024-11-22 14:17:39.439130: Epoch 5134 +2024-11-22 14:17:39.439238: Current learning rate: 0.00397 +2024-11-22 14:17:57.231512: train_loss -0.8049 +2024-11-22 14:17:57.236956: val_loss -0.7725 +2024-11-22 14:17:57.237150: Pseudo dice [0.846] +2024-11-22 14:17:57.237252: Epoch time: 17.79 s +2024-11-22 14:17:58.151412: +2024-11-22 14:17:58.151630: Epoch 5135 +2024-11-22 14:17:58.151743: Current learning rate: 0.00397 +2024-11-22 14:18:17.206871: train_loss -0.79 +2024-11-22 14:18:17.207146: val_loss -0.7673 +2024-11-22 14:18:17.207229: Pseudo dice [0.8468] +2024-11-22 14:18:17.207310: Epoch time: 19.05 s +2024-11-22 14:18:18.252607: +2024-11-22 14:18:18.252826: Epoch 5136 +2024-11-22 14:18:18.252943: Current learning rate: 0.00397 +2024-11-22 14:18:36.860937: train_loss -0.8037 +2024-11-22 14:18:36.861206: val_loss -0.7737 +2024-11-22 14:18:36.861283: Pseudo dice [0.8519] +2024-11-22 14:18:36.861357: Epoch time: 18.61 s +2024-11-22 14:18:37.752858: +2024-11-22 14:18:37.753197: Epoch 5137 +2024-11-22 14:18:37.753305: Current learning rate: 0.00397 +2024-11-22 14:18:55.883870: train_loss -0.7949 +2024-11-22 14:18:55.889312: val_loss -0.7364 +2024-11-22 14:18:55.889471: Pseudo dice [0.8377] +2024-11-22 14:18:55.889551: Epoch time: 18.13 s +2024-11-22 14:18:56.880370: +2024-11-22 14:18:56.880580: Epoch 5138 +2024-11-22 14:18:56.880686: Current learning rate: 0.00396 +2024-11-22 14:19:16.319692: train_loss -0.7949 +2024-11-22 14:19:16.319910: val_loss -0.765 +2024-11-22 14:19:16.320000: Pseudo dice [0.8482] +2024-11-22 14:19:16.320080: Epoch time: 19.44 s +2024-11-22 14:19:17.199557: +2024-11-22 14:19:17.199795: Epoch 5139 +2024-11-22 14:19:17.199906: Current learning rate: 0.00396 +2024-11-22 14:19:35.643588: train_loss -0.7883 +2024-11-22 14:19:35.643813: val_loss -0.7674 +2024-11-22 14:19:35.643888: Pseudo dice [0.8432] +2024-11-22 14:19:35.643966: Epoch time: 18.44 s +2024-11-22 14:19:36.528301: +2024-11-22 14:19:36.528657: Epoch 5140 +2024-11-22 14:19:36.528816: Current learning rate: 0.00396 +2024-11-22 14:19:55.634947: train_loss -0.7986 +2024-11-22 14:19:55.635167: val_loss -0.7932 +2024-11-22 14:19:55.635241: Pseudo dice [0.8509] +2024-11-22 14:19:55.635316: Epoch time: 19.11 s +2024-11-22 14:19:56.520766: +2024-11-22 14:19:56.521016: Epoch 5141 +2024-11-22 14:19:56.521130: Current learning rate: 0.00396 +2024-11-22 14:20:15.752310: train_loss -0.7865 +2024-11-22 14:20:15.752518: val_loss -0.784 +2024-11-22 14:20:15.752599: Pseudo dice [0.8384] +2024-11-22 14:20:15.752675: Epoch time: 19.23 s +2024-11-22 14:20:16.634707: +2024-11-22 14:20:16.634916: Epoch 5142 +2024-11-22 14:20:16.635224: Current learning rate: 0.00396 +2024-11-22 14:20:36.503759: train_loss -0.7912 +2024-11-22 14:20:36.504008: val_loss -0.7727 +2024-11-22 14:20:36.504104: Pseudo dice [0.8539] +2024-11-22 14:20:36.504191: Epoch time: 19.87 s +2024-11-22 14:20:37.385767: +2024-11-22 14:20:37.385979: Epoch 5143 +2024-11-22 14:20:37.386098: Current learning rate: 0.00396 +2024-11-22 14:20:55.276184: train_loss -0.8021 +2024-11-22 14:20:55.280329: val_loss -0.7531 +2024-11-22 14:20:55.280465: Pseudo dice [0.8288] +2024-11-22 14:20:55.280545: Epoch time: 17.89 s +2024-11-22 14:20:56.612164: +2024-11-22 14:20:56.612430: Epoch 5144 +2024-11-22 14:20:56.612542: Current learning rate: 0.00396 +2024-11-22 14:21:14.761184: train_loss -0.7978 +2024-11-22 14:21:14.761420: val_loss -0.7846 +2024-11-22 14:21:14.761502: Pseudo dice [0.8578] +2024-11-22 14:21:14.761576: Epoch time: 18.15 s +2024-11-22 14:21:15.641261: +2024-11-22 14:21:15.641475: Epoch 5145 +2024-11-22 14:21:15.641588: Current learning rate: 0.00396 +2024-11-22 14:21:33.627616: train_loss -0.8004 +2024-11-22 14:21:33.627865: val_loss -0.7899 +2024-11-22 14:21:33.627940: Pseudo dice [0.8563] +2024-11-22 14:21:33.628028: Epoch time: 17.99 s +2024-11-22 14:21:34.506828: +2024-11-22 14:21:34.507043: Epoch 5146 +2024-11-22 14:21:34.507155: Current learning rate: 0.00395 +2024-11-22 14:21:52.905527: train_loss -0.794 +2024-11-22 14:21:52.905765: val_loss -0.7771 +2024-11-22 14:21:52.905845: Pseudo dice [0.8367] +2024-11-22 14:21:52.905921: Epoch time: 18.4 s +2024-11-22 14:21:53.796434: +2024-11-22 14:21:53.796659: Epoch 5147 +2024-11-22 14:21:53.796766: Current learning rate: 0.00395 +2024-11-22 14:22:11.921595: train_loss -0.8045 +2024-11-22 14:22:11.927890: val_loss -0.7763 +2024-11-22 14:22:11.928045: Pseudo dice [0.8638] +2024-11-22 14:22:11.928129: Epoch time: 18.13 s +2024-11-22 14:22:12.813522: +2024-11-22 14:22:12.813740: Epoch 5148 +2024-11-22 14:22:12.813866: Current learning rate: 0.00395 +2024-11-22 14:22:31.292454: train_loss -0.7991 +2024-11-22 14:22:31.294049: val_loss -0.7675 +2024-11-22 14:22:31.294143: Pseudo dice [0.8449] +2024-11-22 14:22:31.294216: Epoch time: 18.48 s +2024-11-22 14:22:32.176089: +2024-11-22 14:22:32.176301: Epoch 5149 +2024-11-22 14:22:32.176412: Current learning rate: 0.00395 +2024-11-22 14:22:50.293062: train_loss -0.7975 +2024-11-22 14:22:50.298517: val_loss -0.7652 +2024-11-22 14:22:50.298651: Pseudo dice [0.8376] +2024-11-22 14:22:50.298745: Epoch time: 18.12 s +2024-11-22 14:22:51.576703: +2024-11-22 14:22:51.576907: Epoch 5150 +2024-11-22 14:22:51.577024: Current learning rate: 0.00395 +2024-11-22 14:23:10.332194: train_loss -0.8 +2024-11-22 14:23:10.333199: val_loss -0.7813 +2024-11-22 14:23:10.333282: Pseudo dice [0.8424] +2024-11-22 14:23:10.333360: Epoch time: 18.76 s +2024-11-22 14:23:11.239639: +2024-11-22 14:23:11.239854: Epoch 5151 +2024-11-22 14:23:11.239962: Current learning rate: 0.00395 +2024-11-22 14:23:29.177696: train_loss -0.8017 +2024-11-22 14:23:29.177930: val_loss -0.7922 +2024-11-22 14:23:29.178013: Pseudo dice [0.8621] +2024-11-22 14:23:29.178087: Epoch time: 17.94 s +2024-11-22 14:23:30.116801: +2024-11-22 14:23:30.117023: Epoch 5152 +2024-11-22 14:23:30.117134: Current learning rate: 0.00395 +2024-11-22 14:23:48.865421: train_loss -0.7991 +2024-11-22 14:23:48.865662: val_loss -0.769 +2024-11-22 14:23:48.865745: Pseudo dice [0.8507] +2024-11-22 14:23:48.865831: Epoch time: 18.75 s +2024-11-22 14:23:49.766996: +2024-11-22 14:23:49.767207: Epoch 5153 +2024-11-22 14:23:49.767317: Current learning rate: 0.00395 +2024-11-22 14:24:08.842618: train_loss -0.7953 +2024-11-22 14:24:08.842874: val_loss -0.7684 +2024-11-22 14:24:08.842952: Pseudo dice [0.8537] +2024-11-22 14:24:08.843038: Epoch time: 19.08 s +2024-11-22 14:24:09.731099: +2024-11-22 14:24:09.731298: Epoch 5154 +2024-11-22 14:24:09.731406: Current learning rate: 0.00394 +2024-11-22 14:24:28.139216: train_loss -0.7787 +2024-11-22 14:24:28.139434: val_loss -0.773 +2024-11-22 14:24:28.139509: Pseudo dice [0.8389] +2024-11-22 14:24:28.139584: Epoch time: 18.41 s +2024-11-22 14:24:29.022732: +2024-11-22 14:24:29.023185: Epoch 5155 +2024-11-22 14:24:29.023318: Current learning rate: 0.00394 +2024-11-22 14:24:48.742826: train_loss -0.7806 +2024-11-22 14:24:48.743309: val_loss -0.7889 +2024-11-22 14:24:48.743412: Pseudo dice [0.8341] +2024-11-22 14:24:48.743504: Epoch time: 19.72 s +2024-11-22 14:24:49.610962: +2024-11-22 14:24:49.611190: Epoch 5156 +2024-11-22 14:24:49.611300: Current learning rate: 0.00394 +2024-11-22 14:25:08.131417: train_loss -0.7901 +2024-11-22 14:25:08.131666: val_loss -0.7522 +2024-11-22 14:25:08.131782: Pseudo dice [0.838] +2024-11-22 14:25:08.131873: Epoch time: 18.52 s +2024-11-22 14:25:09.022229: +2024-11-22 14:25:09.022518: Epoch 5157 +2024-11-22 14:25:09.022627: Current learning rate: 0.00394 +2024-11-22 14:25:27.715052: train_loss -0.7893 +2024-11-22 14:25:27.715278: val_loss -0.7488 +2024-11-22 14:25:27.715356: Pseudo dice [0.8437] +2024-11-22 14:25:27.717611: Epoch time: 18.69 s +2024-11-22 14:25:28.664773: +2024-11-22 14:25:28.665076: Epoch 5158 +2024-11-22 14:25:28.665181: Current learning rate: 0.00394 +2024-11-22 14:25:46.740657: train_loss -0.7973 +2024-11-22 14:25:46.740877: val_loss -0.7637 +2024-11-22 14:25:46.740954: Pseudo dice [0.8402] +2024-11-22 14:25:46.741034: Epoch time: 18.08 s +2024-11-22 14:25:47.625874: +2024-11-22 14:25:47.626096: Epoch 5159 +2024-11-22 14:25:47.626206: Current learning rate: 0.00394 +2024-11-22 14:26:06.256989: train_loss -0.7908 +2024-11-22 14:26:06.257247: val_loss -0.7753 +2024-11-22 14:26:06.257322: Pseudo dice [0.8633] +2024-11-22 14:26:06.257404: Epoch time: 18.63 s +2024-11-22 14:26:07.222572: +2024-11-22 14:26:07.222801: Epoch 5160 +2024-11-22 14:26:07.222914: Current learning rate: 0.00394 +2024-11-22 14:26:24.258347: train_loss -0.7919 +2024-11-22 14:26:24.258582: val_loss -0.7787 +2024-11-22 14:26:24.258659: Pseudo dice [0.8397] +2024-11-22 14:26:24.258733: Epoch time: 17.04 s +2024-11-22 14:26:25.144646: +2024-11-22 14:26:25.144893: Epoch 5161 +2024-11-22 14:26:25.145009: Current learning rate: 0.00394 +2024-11-22 14:26:44.763667: train_loss -0.7883 +2024-11-22 14:26:44.763886: val_loss -0.7781 +2024-11-22 14:26:44.763961: Pseudo dice [0.8565] +2024-11-22 14:26:44.764044: Epoch time: 19.62 s +2024-11-22 14:26:45.651905: +2024-11-22 14:26:45.652137: Epoch 5162 +2024-11-22 14:26:45.652256: Current learning rate: 0.00393 +2024-11-22 14:27:04.267506: train_loss -0.7883 +2024-11-22 14:27:04.267786: val_loss -0.7571 +2024-11-22 14:27:04.267866: Pseudo dice [0.8423] +2024-11-22 14:27:04.267943: Epoch time: 18.62 s +2024-11-22 14:27:05.143564: +2024-11-22 14:27:05.143759: Epoch 5163 +2024-11-22 14:27:05.143868: Current learning rate: 0.00393 +2024-11-22 14:27:24.246141: train_loss -0.7862 +2024-11-22 14:27:24.246389: val_loss -0.7547 +2024-11-22 14:27:24.246468: Pseudo dice [0.828] +2024-11-22 14:27:24.246552: Epoch time: 19.1 s +2024-11-22 14:27:25.130261: +2024-11-22 14:27:25.130469: Epoch 5164 +2024-11-22 14:27:25.130579: Current learning rate: 0.00393 +2024-11-22 14:27:42.343162: train_loss -0.7889 +2024-11-22 14:27:42.343374: val_loss -0.7855 +2024-11-22 14:27:42.343447: Pseudo dice [0.8501] +2024-11-22 14:27:42.343520: Epoch time: 17.21 s +2024-11-22 14:27:43.223542: +2024-11-22 14:27:43.223739: Epoch 5165 +2024-11-22 14:27:43.223850: Current learning rate: 0.00393 +2024-11-22 14:28:02.309184: train_loss -0.7959 +2024-11-22 14:28:02.309411: val_loss -0.7771 +2024-11-22 14:28:02.309486: Pseudo dice [0.8534] +2024-11-22 14:28:02.309559: Epoch time: 19.09 s +2024-11-22 14:28:03.190957: +2024-11-22 14:28:03.191319: Epoch 5166 +2024-11-22 14:28:03.191430: Current learning rate: 0.00393 +2024-11-22 14:28:21.385053: train_loss -0.803 +2024-11-22 14:28:21.385288: val_loss -0.7957 +2024-11-22 14:28:21.385371: Pseudo dice [0.861] +2024-11-22 14:28:21.385469: Epoch time: 18.19 s +2024-11-22 14:28:22.630829: +2024-11-22 14:28:22.631081: Epoch 5167 +2024-11-22 14:28:22.631191: Current learning rate: 0.00393 +2024-11-22 14:28:41.418988: train_loss -0.7888 +2024-11-22 14:28:41.419230: val_loss -0.7928 +2024-11-22 14:28:41.419305: Pseudo dice [0.8499] +2024-11-22 14:28:41.419379: Epoch time: 18.79 s +2024-11-22 14:28:42.293964: +2024-11-22 14:28:42.294192: Epoch 5168 +2024-11-22 14:28:42.294404: Current learning rate: 0.00393 +2024-11-22 14:29:00.922377: train_loss -0.7892 +2024-11-22 14:29:00.922602: val_loss -0.7842 +2024-11-22 14:29:00.922675: Pseudo dice [0.8468] +2024-11-22 14:29:00.922749: Epoch time: 18.63 s +2024-11-22 14:29:01.799100: +2024-11-22 14:29:01.799346: Epoch 5169 +2024-11-22 14:29:01.799465: Current learning rate: 0.00393 +2024-11-22 14:29:20.298346: train_loss -0.7897 +2024-11-22 14:29:20.300729: val_loss -0.7806 +2024-11-22 14:29:20.300864: Pseudo dice [0.845] +2024-11-22 14:29:20.300947: Epoch time: 18.5 s +2024-11-22 14:29:21.216256: +2024-11-22 14:29:21.216586: Epoch 5170 +2024-11-22 14:29:21.216732: Current learning rate: 0.00392 +2024-11-22 14:29:39.932203: train_loss -0.787 +2024-11-22 14:29:39.932448: val_loss -0.7908 +2024-11-22 14:29:39.932522: Pseudo dice [0.8572] +2024-11-22 14:29:39.932600: Epoch time: 18.72 s +2024-11-22 14:29:40.823350: +2024-11-22 14:29:40.823550: Epoch 5171 +2024-11-22 14:29:40.823657: Current learning rate: 0.00392 +2024-11-22 14:29:58.720964: train_loss -0.7988 +2024-11-22 14:29:58.721201: val_loss -0.7714 +2024-11-22 14:29:58.721280: Pseudo dice [0.8489] +2024-11-22 14:29:58.721354: Epoch time: 17.9 s +2024-11-22 14:29:59.600347: +2024-11-22 14:29:59.600566: Epoch 5172 +2024-11-22 14:29:59.600678: Current learning rate: 0.00392 +2024-11-22 14:30:17.426334: train_loss -0.7956 +2024-11-22 14:30:17.426548: val_loss -0.7729 +2024-11-22 14:30:17.426657: Pseudo dice [0.8442] +2024-11-22 14:30:17.426732: Epoch time: 17.83 s +2024-11-22 14:30:18.311989: +2024-11-22 14:30:18.312195: Epoch 5173 +2024-11-22 14:30:18.312302: Current learning rate: 0.00392 +2024-11-22 14:30:36.675796: train_loss -0.7863 +2024-11-22 14:30:36.676027: val_loss -0.7448 +2024-11-22 14:30:36.676108: Pseudo dice [0.8466] +2024-11-22 14:30:36.676192: Epoch time: 18.36 s +2024-11-22 14:30:37.552442: +2024-11-22 14:30:37.552668: Epoch 5174 +2024-11-22 14:30:37.552775: Current learning rate: 0.00392 +2024-11-22 14:30:56.979712: train_loss -0.793 +2024-11-22 14:30:56.979940: val_loss -0.7624 +2024-11-22 14:30:56.980023: Pseudo dice [0.8472] +2024-11-22 14:30:56.980105: Epoch time: 19.43 s +2024-11-22 14:30:57.928543: +2024-11-22 14:30:57.928784: Epoch 5175 +2024-11-22 14:30:57.928910: Current learning rate: 0.00392 +2024-11-22 14:31:15.941882: train_loss -0.7998 +2024-11-22 14:31:15.942116: val_loss -0.7681 +2024-11-22 14:31:15.942251: Pseudo dice [0.8407] +2024-11-22 14:31:15.942326: Epoch time: 18.01 s +2024-11-22 14:31:16.832821: +2024-11-22 14:31:16.833039: Epoch 5176 +2024-11-22 14:31:16.833148: Current learning rate: 0.00392 +2024-11-22 14:31:35.548690: train_loss -0.8037 +2024-11-22 14:31:35.548965: val_loss -0.785 +2024-11-22 14:31:35.549044: Pseudo dice [0.856] +2024-11-22 14:31:35.549122: Epoch time: 18.72 s +2024-11-22 14:31:36.432804: +2024-11-22 14:31:36.433022: Epoch 5177 +2024-11-22 14:31:36.433155: Current learning rate: 0.00392 +2024-11-22 14:31:54.612221: train_loss -0.7967 +2024-11-22 14:31:54.612471: val_loss -0.7819 +2024-11-22 14:31:54.612550: Pseudo dice [0.8462] +2024-11-22 14:31:54.612634: Epoch time: 18.18 s +2024-11-22 14:31:55.496437: +2024-11-22 14:31:55.496645: Epoch 5178 +2024-11-22 14:31:55.496758: Current learning rate: 0.00391 +2024-11-22 14:32:12.688500: train_loss -0.7999 +2024-11-22 14:32:12.688720: val_loss -0.7705 +2024-11-22 14:32:12.688793: Pseudo dice [0.8378] +2024-11-22 14:32:12.688888: Epoch time: 17.19 s +2024-11-22 14:32:13.949623: +2024-11-22 14:32:13.949841: Epoch 5179 +2024-11-22 14:32:13.949954: Current learning rate: 0.00391 +2024-11-22 14:32:32.295080: train_loss -0.7979 +2024-11-22 14:32:32.299749: val_loss -0.7774 +2024-11-22 14:32:32.299874: Pseudo dice [0.8499] +2024-11-22 14:32:32.319988: Epoch time: 18.35 s +2024-11-22 14:32:33.280567: +2024-11-22 14:32:33.280828: Epoch 5180 +2024-11-22 14:32:33.280938: Current learning rate: 0.00391 +2024-11-22 14:32:51.237485: train_loss -0.7931 +2024-11-22 14:32:51.237759: val_loss -0.7983 +2024-11-22 14:32:51.237837: Pseudo dice [0.8498] +2024-11-22 14:32:51.237920: Epoch time: 17.96 s +2024-11-22 14:32:52.120870: +2024-11-22 14:32:52.121097: Epoch 5181 +2024-11-22 14:32:52.121210: Current learning rate: 0.00391 +2024-11-22 14:33:09.408538: train_loss -0.8009 +2024-11-22 14:33:09.408760: val_loss -0.7502 +2024-11-22 14:33:09.408842: Pseudo dice [0.8417] +2024-11-22 14:33:09.408920: Epoch time: 17.29 s +2024-11-22 14:33:10.293795: +2024-11-22 14:33:10.294037: Epoch 5182 +2024-11-22 14:33:10.294149: Current learning rate: 0.00391 +2024-11-22 14:33:29.380766: train_loss -0.7995 +2024-11-22 14:33:29.380996: val_loss -0.7739 +2024-11-22 14:33:29.381080: Pseudo dice [0.849] +2024-11-22 14:33:29.381156: Epoch time: 19.09 s +2024-11-22 14:33:30.271615: +2024-11-22 14:33:30.271825: Epoch 5183 +2024-11-22 14:33:30.271935: Current learning rate: 0.00391 +2024-11-22 14:33:48.794883: train_loss -0.782 +2024-11-22 14:33:48.795129: val_loss -0.7531 +2024-11-22 14:33:48.795265: Pseudo dice [0.8382] +2024-11-22 14:33:48.795340: Epoch time: 18.52 s +2024-11-22 14:33:49.689921: +2024-11-22 14:33:49.690145: Epoch 5184 +2024-11-22 14:33:49.690280: Current learning rate: 0.00391 +2024-11-22 14:34:08.786987: train_loss -0.7928 +2024-11-22 14:34:08.787296: val_loss -0.7918 +2024-11-22 14:34:08.787379: Pseudo dice [0.8486] +2024-11-22 14:34:08.787463: Epoch time: 19.1 s +2024-11-22 14:34:09.674232: +2024-11-22 14:34:09.674434: Epoch 5185 +2024-11-22 14:34:09.674544: Current learning rate: 0.00391 +2024-11-22 14:34:28.079677: train_loss -0.8009 +2024-11-22 14:34:28.079895: val_loss -0.7807 +2024-11-22 14:34:28.079971: Pseudo dice [0.8522] +2024-11-22 14:34:28.080053: Epoch time: 18.41 s +2024-11-22 14:34:28.960987: +2024-11-22 14:34:28.961198: Epoch 5186 +2024-11-22 14:34:28.961316: Current learning rate: 0.0039 +2024-11-22 14:34:46.909225: train_loss -0.8025 +2024-11-22 14:34:46.909443: val_loss -0.7663 +2024-11-22 14:34:46.909517: Pseudo dice [0.8597] +2024-11-22 14:34:46.909591: Epoch time: 17.95 s +2024-11-22 14:34:47.807671: +2024-11-22 14:34:47.807895: Epoch 5187 +2024-11-22 14:34:47.808012: Current learning rate: 0.0039 +2024-11-22 14:35:06.241115: train_loss -0.7963 +2024-11-22 14:35:06.241349: val_loss -0.7494 +2024-11-22 14:35:06.241427: Pseudo dice [0.8469] +2024-11-22 14:35:06.241507: Epoch time: 18.43 s +2024-11-22 14:35:07.124639: +2024-11-22 14:35:07.124851: Epoch 5188 +2024-11-22 14:35:07.124959: Current learning rate: 0.0039 +2024-11-22 14:35:25.187899: train_loss -0.7853 +2024-11-22 14:35:25.188160: val_loss -0.7624 +2024-11-22 14:35:25.188235: Pseudo dice [0.8523] +2024-11-22 14:35:25.188315: Epoch time: 18.06 s +2024-11-22 14:35:26.073569: +2024-11-22 14:35:26.073785: Epoch 5189 +2024-11-22 14:35:26.073906: Current learning rate: 0.0039 +2024-11-22 14:35:43.941363: train_loss -0.7935 +2024-11-22 14:35:43.941573: val_loss -0.7621 +2024-11-22 14:35:43.941650: Pseudo dice [0.8383] +2024-11-22 14:35:43.941723: Epoch time: 17.87 s +2024-11-22 14:35:44.825697: +2024-11-22 14:35:44.825920: Epoch 5190 +2024-11-22 14:35:44.826037: Current learning rate: 0.0039 +2024-11-22 14:36:04.849360: train_loss -0.7789 +2024-11-22 14:36:04.849575: val_loss -0.7672 +2024-11-22 14:36:04.849649: Pseudo dice [0.8356] +2024-11-22 14:36:04.851825: Epoch time: 20.02 s +2024-11-22 14:36:06.190518: +2024-11-22 14:36:06.190736: Epoch 5191 +2024-11-22 14:36:06.190846: Current learning rate: 0.0039 +2024-11-22 14:36:24.987172: train_loss -0.7873 +2024-11-22 14:36:24.987435: val_loss -0.7724 +2024-11-22 14:36:24.987511: Pseudo dice [0.8515] +2024-11-22 14:36:24.987590: Epoch time: 18.8 s +2024-11-22 14:36:25.878645: +2024-11-22 14:36:25.878850: Epoch 5192 +2024-11-22 14:36:25.878957: Current learning rate: 0.0039 +2024-11-22 14:36:44.738093: train_loss -0.792 +2024-11-22 14:36:44.754575: val_loss -0.7646 +2024-11-22 14:36:44.754674: Pseudo dice [0.8514] +2024-11-22 14:36:44.754797: Epoch time: 18.86 s +2024-11-22 14:36:45.639926: +2024-11-22 14:36:45.640168: Epoch 5193 +2024-11-22 14:36:45.640276: Current learning rate: 0.0039 +2024-11-22 14:37:02.899483: train_loss -0.7969 +2024-11-22 14:37:02.899714: val_loss -0.7713 +2024-11-22 14:37:02.899789: Pseudo dice [0.8576] +2024-11-22 14:37:02.899865: Epoch time: 17.26 s +2024-11-22 14:37:03.776698: +2024-11-22 14:37:03.777158: Epoch 5194 +2024-11-22 14:37:03.777285: Current learning rate: 0.00389 +2024-11-22 14:37:22.639194: train_loss -0.7859 +2024-11-22 14:37:22.644619: val_loss -0.7811 +2024-11-22 14:37:22.644734: Pseudo dice [0.8414] +2024-11-22 14:37:22.644820: Epoch time: 18.86 s +2024-11-22 14:37:23.593093: +2024-11-22 14:37:23.593322: Epoch 5195 +2024-11-22 14:37:23.593437: Current learning rate: 0.00389 +2024-11-22 14:37:40.711933: train_loss -0.7867 +2024-11-22 14:37:40.712163: val_loss -0.7729 +2024-11-22 14:37:40.712240: Pseudo dice [0.8472] +2024-11-22 14:37:40.712361: Epoch time: 17.12 s +2024-11-22 14:37:41.608306: +2024-11-22 14:37:41.608526: Epoch 5196 +2024-11-22 14:37:41.608636: Current learning rate: 0.00389 +2024-11-22 14:38:00.171465: train_loss -0.7959 +2024-11-22 14:38:00.171695: val_loss -0.7729 +2024-11-22 14:38:00.171770: Pseudo dice [0.8424] +2024-11-22 14:38:00.171847: Epoch time: 18.56 s +2024-11-22 14:38:01.060013: +2024-11-22 14:38:01.060216: Epoch 5197 +2024-11-22 14:38:01.060325: Current learning rate: 0.00389 +2024-11-22 14:38:19.855374: train_loss -0.7917 +2024-11-22 14:38:19.855593: val_loss -0.7843 +2024-11-22 14:38:19.855666: Pseudo dice [0.8519] +2024-11-22 14:38:19.860893: Epoch time: 18.8 s +2024-11-22 14:38:20.755433: +2024-11-22 14:38:20.755641: Epoch 5198 +2024-11-22 14:38:20.755750: Current learning rate: 0.00389 +2024-11-22 14:38:39.679226: train_loss -0.7891 +2024-11-22 14:38:39.679530: val_loss -0.7834 +2024-11-22 14:38:39.679605: Pseudo dice [0.844] +2024-11-22 14:38:39.679692: Epoch time: 18.92 s +2024-11-22 14:38:40.596819: +2024-11-22 14:38:40.597024: Epoch 5199 +2024-11-22 14:38:40.597172: Current learning rate: 0.00389 +2024-11-22 14:38:59.711020: train_loss -0.7908 +2024-11-22 14:38:59.711241: val_loss -0.7917 +2024-11-22 14:38:59.711318: Pseudo dice [0.846] +2024-11-22 14:38:59.711393: Epoch time: 19.12 s +2024-11-22 14:39:00.930573: +2024-11-22 14:39:00.930793: Epoch 5200 +2024-11-22 14:39:00.930902: Current learning rate: 0.00389 +2024-11-22 14:39:19.030149: train_loss -0.7822 +2024-11-22 14:39:19.030372: val_loss -0.78 +2024-11-22 14:39:19.030450: Pseudo dice [0.8602] +2024-11-22 14:39:19.030525: Epoch time: 18.1 s +2024-11-22 14:39:19.905334: +2024-11-22 14:39:19.905563: Epoch 5201 +2024-11-22 14:39:19.905670: Current learning rate: 0.00389 +2024-11-22 14:39:37.807126: train_loss -0.7982 +2024-11-22 14:39:37.807341: val_loss -0.7792 +2024-11-22 14:39:37.807417: Pseudo dice [0.8501] +2024-11-22 14:39:37.807495: Epoch time: 17.9 s +2024-11-22 14:39:38.846352: +2024-11-22 14:39:38.846574: Epoch 5202 +2024-11-22 14:39:38.846681: Current learning rate: 0.00388 +2024-11-22 14:39:57.866560: train_loss -0.7938 +2024-11-22 14:39:57.867048: val_loss -0.7819 +2024-11-22 14:39:57.867149: Pseudo dice [0.8519] +2024-11-22 14:39:57.867227: Epoch time: 19.02 s +2024-11-22 14:39:58.772816: +2024-11-22 14:39:58.773075: Epoch 5203 +2024-11-22 14:39:58.773187: Current learning rate: 0.00388 +2024-11-22 14:40:17.053079: train_loss -0.7946 +2024-11-22 14:40:17.053291: val_loss -0.7725 +2024-11-22 14:40:17.053368: Pseudo dice [0.8605] +2024-11-22 14:40:17.053443: Epoch time: 18.28 s +2024-11-22 14:40:17.928759: +2024-11-22 14:40:17.928981: Epoch 5204 +2024-11-22 14:40:17.929097: Current learning rate: 0.00388 +2024-11-22 14:40:37.275505: train_loss -0.7992 +2024-11-22 14:40:37.275746: val_loss -0.7675 +2024-11-22 14:40:37.275822: Pseudo dice [0.8453] +2024-11-22 14:40:37.275903: Epoch time: 19.35 s +2024-11-22 14:40:38.159029: +2024-11-22 14:40:38.159262: Epoch 5205 +2024-11-22 14:40:38.159605: Current learning rate: 0.00388 +2024-11-22 14:40:57.079592: train_loss -0.7992 +2024-11-22 14:40:57.079798: val_loss -0.7704 +2024-11-22 14:40:57.079870: Pseudo dice [0.8561] +2024-11-22 14:40:57.079945: Epoch time: 18.92 s +2024-11-22 14:40:57.958238: +2024-11-22 14:40:57.958568: Epoch 5206 +2024-11-22 14:40:57.958685: Current learning rate: 0.00388 +2024-11-22 14:41:14.841272: train_loss -0.7956 +2024-11-22 14:41:14.841507: val_loss -0.7779 +2024-11-22 14:41:14.841582: Pseudo dice [0.8699] +2024-11-22 14:41:14.841657: Epoch time: 16.88 s +2024-11-22 14:41:14.841719: Yayy! New best EMA pseudo Dice: 0.8522 +2024-11-22 14:41:16.096101: +2024-11-22 14:41:16.096302: Epoch 5207 +2024-11-22 14:41:16.096413: Current learning rate: 0.00388 +2024-11-22 14:41:33.933938: train_loss -0.7991 +2024-11-22 14:41:33.935199: val_loss -0.7575 +2024-11-22 14:41:33.935440: Pseudo dice [0.8413] +2024-11-22 14:41:33.935529: Epoch time: 17.84 s +2024-11-22 14:41:34.828109: +2024-11-22 14:41:34.828323: Epoch 5208 +2024-11-22 14:41:34.828433: Current learning rate: 0.00388 +2024-11-22 14:41:54.668365: train_loss -0.8003 +2024-11-22 14:41:54.668618: val_loss -0.7608 +2024-11-22 14:41:54.668694: Pseudo dice [0.8376] +2024-11-22 14:41:54.668775: Epoch time: 19.84 s +2024-11-22 14:41:55.556781: +2024-11-22 14:41:55.556983: Epoch 5209 +2024-11-22 14:41:55.557102: Current learning rate: 0.00388 +2024-11-22 14:42:14.167043: train_loss -0.7795 +2024-11-22 14:42:14.167258: val_loss -0.7616 +2024-11-22 14:42:14.167329: Pseudo dice [0.849] +2024-11-22 14:42:14.167401: Epoch time: 18.61 s +2024-11-22 14:42:15.044899: +2024-11-22 14:42:15.045231: Epoch 5210 +2024-11-22 14:42:15.045347: Current learning rate: 0.00387 +2024-11-22 14:42:33.274585: train_loss -0.7917 +2024-11-22 14:42:33.274803: val_loss -0.7566 +2024-11-22 14:42:33.274877: Pseudo dice [0.8461] +2024-11-22 14:42:33.274953: Epoch time: 18.23 s +2024-11-22 14:42:34.153750: +2024-11-22 14:42:34.153963: Epoch 5211 +2024-11-22 14:42:34.154078: Current learning rate: 0.00387 +2024-11-22 14:42:52.272955: train_loss -0.7977 +2024-11-22 14:42:52.273182: val_loss -0.7764 +2024-11-22 14:42:52.273265: Pseudo dice [0.848] +2024-11-22 14:42:52.273347: Epoch time: 18.12 s +2024-11-22 14:42:53.152764: +2024-11-22 14:42:53.153024: Epoch 5212 +2024-11-22 14:42:53.153146: Current learning rate: 0.00387 +2024-11-22 14:43:12.332341: train_loss -0.7886 +2024-11-22 14:43:12.334756: val_loss -0.7604 +2024-11-22 14:43:12.334860: Pseudo dice [0.8412] +2024-11-22 14:43:12.334945: Epoch time: 19.18 s +2024-11-22 14:43:13.263006: +2024-11-22 14:43:13.263220: Epoch 5213 +2024-11-22 14:43:13.263330: Current learning rate: 0.00387 +2024-11-22 14:43:31.186394: train_loss -0.7943 +2024-11-22 14:43:31.186605: val_loss -0.7998 +2024-11-22 14:43:31.186685: Pseudo dice [0.8522] +2024-11-22 14:43:31.186761: Epoch time: 17.92 s +2024-11-22 14:43:32.452542: +2024-11-22 14:43:32.452785: Epoch 5214 +2024-11-22 14:43:32.452892: Current learning rate: 0.00387 +2024-11-22 14:43:51.003983: train_loss -0.7937 +2024-11-22 14:43:51.007105: val_loss -0.7452 +2024-11-22 14:43:51.007225: Pseudo dice [0.8405] +2024-11-22 14:43:51.007314: Epoch time: 18.55 s +2024-11-22 14:43:51.909047: +2024-11-22 14:43:51.909295: Epoch 5215 +2024-11-22 14:43:51.909403: Current learning rate: 0.00387 +2024-11-22 14:44:10.136961: train_loss -0.8044 +2024-11-22 14:44:10.137249: val_loss -0.7745 +2024-11-22 14:44:10.137332: Pseudo dice [0.8589] +2024-11-22 14:44:10.137418: Epoch time: 18.23 s +2024-11-22 14:44:11.025838: +2024-11-22 14:44:11.026077: Epoch 5216 +2024-11-22 14:44:11.026184: Current learning rate: 0.00387 +2024-11-22 14:44:29.981932: train_loss -0.7958 +2024-11-22 14:44:29.982188: val_loss -0.7803 +2024-11-22 14:44:29.982266: Pseudo dice [0.8697] +2024-11-22 14:44:29.982340: Epoch time: 18.96 s +2024-11-22 14:44:31.041682: +2024-11-22 14:44:31.041899: Epoch 5217 +2024-11-22 14:44:31.042013: Current learning rate: 0.00387 +2024-11-22 14:44:48.259482: train_loss -0.7977 +2024-11-22 14:44:48.259697: val_loss -0.7905 +2024-11-22 14:44:48.260327: Pseudo dice [0.8625] +2024-11-22 14:44:48.260449: Epoch time: 17.22 s +2024-11-22 14:44:48.260515: Yayy! New best EMA pseudo Dice: 0.8523 +2024-11-22 14:44:49.452680: +2024-11-22 14:44:49.452902: Epoch 5218 +2024-11-22 14:44:49.453014: Current learning rate: 0.00386 +2024-11-22 14:45:07.944434: train_loss -0.8008 +2024-11-22 14:45:07.944685: val_loss -0.7726 +2024-11-22 14:45:07.944760: Pseudo dice [0.8647] +2024-11-22 14:45:07.944842: Epoch time: 18.49 s +2024-11-22 14:45:07.944909: Yayy! New best EMA pseudo Dice: 0.8535 +2024-11-22 14:45:09.250030: +2024-11-22 14:45:09.250246: Epoch 5219 +2024-11-22 14:45:09.250355: Current learning rate: 0.00386 +2024-11-22 14:45:27.040928: train_loss -0.7983 +2024-11-22 14:45:27.041152: val_loss -0.7821 +2024-11-22 14:45:27.041238: Pseudo dice [0.8551] +2024-11-22 14:45:27.041328: Epoch time: 17.79 s +2024-11-22 14:45:27.041472: Yayy! New best EMA pseudo Dice: 0.8537 +2024-11-22 14:45:28.208575: +2024-11-22 14:45:28.208787: Epoch 5220 +2024-11-22 14:45:28.208899: Current learning rate: 0.00386 +2024-11-22 14:45:48.474885: train_loss -0.8096 +2024-11-22 14:45:48.480262: val_loss -0.7675 +2024-11-22 14:45:48.480356: Pseudo dice [0.8574] +2024-11-22 14:45:48.480434: Epoch time: 20.27 s +2024-11-22 14:45:48.480495: Yayy! New best EMA pseudo Dice: 0.854 +2024-11-22 14:45:49.851270: +2024-11-22 14:45:49.851480: Epoch 5221 +2024-11-22 14:45:49.851593: Current learning rate: 0.00386 +2024-11-22 14:46:06.899514: train_loss -0.8025 +2024-11-22 14:46:06.899732: val_loss -0.7777 +2024-11-22 14:46:06.899808: Pseudo dice [0.8134] +2024-11-22 14:46:06.899911: Epoch time: 17.05 s +2024-11-22 14:46:07.785346: +2024-11-22 14:46:07.785583: Epoch 5222 +2024-11-22 14:46:07.785691: Current learning rate: 0.00386 +2024-11-22 14:46:26.061047: train_loss -0.7981 +2024-11-22 14:46:26.061256: val_loss -0.7972 +2024-11-22 14:46:26.061330: Pseudo dice [0.857] +2024-11-22 14:46:26.061405: Epoch time: 18.28 s +2024-11-22 14:46:27.065240: +2024-11-22 14:46:27.065461: Epoch 5223 +2024-11-22 14:46:27.065571: Current learning rate: 0.00386 +2024-11-22 14:46:46.030726: train_loss -0.8024 +2024-11-22 14:46:46.031033: val_loss -0.7498 +2024-11-22 14:46:46.031117: Pseudo dice [0.8398] +2024-11-22 14:46:46.031195: Epoch time: 18.97 s +2024-11-22 14:46:46.916376: +2024-11-22 14:46:46.916589: Epoch 5224 +2024-11-22 14:46:46.916700: Current learning rate: 0.00386 +2024-11-22 14:47:04.981093: train_loss -0.7934 +2024-11-22 14:47:04.981306: val_loss -0.7508 +2024-11-22 14:47:04.981384: Pseudo dice [0.8516] +2024-11-22 14:47:04.981464: Epoch time: 18.07 s +2024-11-22 14:47:06.231947: +2024-11-22 14:47:06.232175: Epoch 5225 +2024-11-22 14:47:06.232290: Current learning rate: 0.00386 +2024-11-22 14:47:25.222737: train_loss -0.7999 +2024-11-22 14:47:25.228184: val_loss -0.751 +2024-11-22 14:47:25.228366: Pseudo dice [0.8642] +2024-11-22 14:47:25.228458: Epoch time: 18.99 s +2024-11-22 14:47:26.270198: +2024-11-22 14:47:26.270431: Epoch 5226 +2024-11-22 14:47:26.270541: Current learning rate: 0.00385 +2024-11-22 14:47:44.594469: train_loss -0.8002 +2024-11-22 14:47:44.594707: val_loss -0.7527 +2024-11-22 14:47:44.594864: Pseudo dice [0.834] +2024-11-22 14:47:44.594944: Epoch time: 18.33 s +2024-11-22 14:47:45.480123: +2024-11-22 14:47:45.480379: Epoch 5227 +2024-11-22 14:47:45.480491: Current learning rate: 0.00385 +2024-11-22 14:48:04.494561: train_loss -0.7956 +2024-11-22 14:48:04.494788: val_loss -0.7644 +2024-11-22 14:48:04.494863: Pseudo dice [0.8548] +2024-11-22 14:48:04.494938: Epoch time: 19.02 s +2024-11-22 14:48:05.483346: +2024-11-22 14:48:05.483546: Epoch 5228 +2024-11-22 14:48:05.483656: Current learning rate: 0.00385 +2024-11-22 14:48:23.526981: train_loss -0.7906 +2024-11-22 14:48:23.527310: val_loss -0.7627 +2024-11-22 14:48:23.527392: Pseudo dice [0.8398] +2024-11-22 14:48:23.527477: Epoch time: 18.04 s +2024-11-22 14:48:24.443807: +2024-11-22 14:48:24.444028: Epoch 5229 +2024-11-22 14:48:24.444138: Current learning rate: 0.00385 +2024-11-22 14:48:42.218988: train_loss -0.7912 +2024-11-22 14:48:42.219457: val_loss -0.7812 +2024-11-22 14:48:42.219540: Pseudo dice [0.8495] +2024-11-22 14:48:42.219614: Epoch time: 17.78 s +2024-11-22 14:48:43.104050: +2024-11-22 14:48:43.104282: Epoch 5230 +2024-11-22 14:48:43.104397: Current learning rate: 0.00385 +2024-11-22 14:49:02.007505: train_loss -0.798 +2024-11-22 14:49:02.007713: val_loss -0.7883 +2024-11-22 14:49:02.007793: Pseudo dice [0.8517] +2024-11-22 14:49:02.007885: Epoch time: 18.9 s +2024-11-22 14:49:03.030296: +2024-11-22 14:49:03.030508: Epoch 5231 +2024-11-22 14:49:03.030617: Current learning rate: 0.00385 +2024-11-22 14:49:21.071672: train_loss -0.7946 +2024-11-22 14:49:21.077067: val_loss -0.78 +2024-11-22 14:49:21.077202: Pseudo dice [0.8497] +2024-11-22 14:49:21.077283: Epoch time: 18.04 s +2024-11-22 14:49:22.170800: +2024-11-22 14:49:22.171105: Epoch 5232 +2024-11-22 14:49:22.171221: Current learning rate: 0.00385 +2024-11-22 14:49:39.950169: train_loss -0.7748 +2024-11-22 14:49:39.950407: val_loss -0.7532 +2024-11-22 14:49:39.950482: Pseudo dice [0.8335] +2024-11-22 14:49:39.950566: Epoch time: 17.78 s +2024-11-22 14:49:40.842957: +2024-11-22 14:49:40.843179: Epoch 5233 +2024-11-22 14:49:40.843287: Current learning rate: 0.00385 +2024-11-22 14:49:59.510483: train_loss -0.7999 +2024-11-22 14:49:59.510694: val_loss -0.7461 +2024-11-22 14:49:59.510768: Pseudo dice [0.8408] +2024-11-22 14:49:59.510839: Epoch time: 18.67 s +2024-11-22 14:50:00.422167: +2024-11-22 14:50:00.422368: Epoch 5234 +2024-11-22 14:50:00.422474: Current learning rate: 0.00384 +2024-11-22 14:50:18.536667: train_loss -0.7923 +2024-11-22 14:50:18.536895: val_loss -0.7617 +2024-11-22 14:50:18.536969: Pseudo dice [0.8309] +2024-11-22 14:50:18.537049: Epoch time: 18.12 s +2024-11-22 14:50:19.439074: +2024-11-22 14:50:19.439382: Epoch 5235 +2024-11-22 14:50:19.439499: Current learning rate: 0.00384 +2024-11-22 14:50:37.468323: train_loss -0.7999 +2024-11-22 14:50:37.468616: val_loss -0.7718 +2024-11-22 14:50:37.468695: Pseudo dice [0.8379] +2024-11-22 14:50:37.468778: Epoch time: 18.03 s +2024-11-22 14:50:38.361855: +2024-11-22 14:50:38.362080: Epoch 5236 +2024-11-22 14:50:38.362193: Current learning rate: 0.00384 +2024-11-22 14:50:57.359607: train_loss -0.7957 +2024-11-22 14:50:57.360154: val_loss -0.7487 +2024-11-22 14:50:57.360270: Pseudo dice [0.8376] +2024-11-22 14:50:57.360347: Epoch time: 19.0 s +2024-11-22 14:50:58.268121: +2024-11-22 14:50:58.268367: Epoch 5237 +2024-11-22 14:50:58.268480: Current learning rate: 0.00384 +2024-11-22 14:51:16.504919: train_loss -0.7969 +2024-11-22 14:51:16.505137: val_loss -0.7675 +2024-11-22 14:51:16.505213: Pseudo dice [0.8623] +2024-11-22 14:51:16.505287: Epoch time: 18.24 s +2024-11-22 14:51:17.432461: +2024-11-22 14:51:17.432701: Epoch 5238 +2024-11-22 14:51:17.432811: Current learning rate: 0.00384 +2024-11-22 14:51:36.288118: train_loss -0.7988 +2024-11-22 14:51:36.288367: val_loss -0.7793 +2024-11-22 14:51:36.288442: Pseudo dice [0.8392] +2024-11-22 14:51:36.288526: Epoch time: 18.86 s +2024-11-22 14:51:37.180825: +2024-11-22 14:51:37.181038: Epoch 5239 +2024-11-22 14:51:37.181153: Current learning rate: 0.00384 +2024-11-22 14:51:55.475219: train_loss -0.8002 +2024-11-22 14:51:55.475439: val_loss -0.7736 +2024-11-22 14:51:55.475518: Pseudo dice [0.8525] +2024-11-22 14:51:55.475592: Epoch time: 18.3 s +2024-11-22 14:51:56.369136: +2024-11-22 14:51:56.369339: Epoch 5240 +2024-11-22 14:51:56.369449: Current learning rate: 0.00384 +2024-11-22 14:52:14.713967: train_loss -0.7925 +2024-11-22 14:52:14.714193: val_loss -0.7674 +2024-11-22 14:52:14.714265: Pseudo dice [0.8453] +2024-11-22 14:52:14.714417: Epoch time: 18.35 s +2024-11-22 14:52:15.630256: +2024-11-22 14:52:15.630489: Epoch 5241 +2024-11-22 14:52:15.630608: Current learning rate: 0.00384 +2024-11-22 14:52:34.058577: train_loss -0.8038 +2024-11-22 14:52:34.058804: val_loss -0.772 +2024-11-22 14:52:34.058879: Pseudo dice [0.8516] +2024-11-22 14:52:34.058953: Epoch time: 18.43 s +2024-11-22 14:52:34.941714: +2024-11-22 14:52:34.941928: Epoch 5242 +2024-11-22 14:52:34.942045: Current learning rate: 0.00383 +2024-11-22 14:52:52.129365: train_loss -0.8049 +2024-11-22 14:52:52.129592: val_loss -0.7685 +2024-11-22 14:52:52.129667: Pseudo dice [0.8439] +2024-11-22 14:52:52.131938: Epoch time: 17.19 s +2024-11-22 14:52:53.228856: +2024-11-22 14:52:53.229071: Epoch 5243 +2024-11-22 14:52:53.229185: Current learning rate: 0.00383 +2024-11-22 14:53:12.142370: train_loss -0.8005 +2024-11-22 14:53:12.142622: val_loss -0.755 +2024-11-22 14:53:12.142698: Pseudo dice [0.8451] +2024-11-22 14:53:12.142777: Epoch time: 18.91 s +2024-11-22 14:53:13.027515: +2024-11-22 14:53:13.027780: Epoch 5244 +2024-11-22 14:53:13.027891: Current learning rate: 0.00383 +2024-11-22 14:53:32.089294: train_loss -0.8042 +2024-11-22 14:53:32.089511: val_loss -0.7802 +2024-11-22 14:53:32.089585: Pseudo dice [0.8527] +2024-11-22 14:53:32.089891: Epoch time: 19.06 s +2024-11-22 14:53:32.970172: +2024-11-22 14:53:32.970399: Epoch 5245 +2024-11-22 14:53:32.970510: Current learning rate: 0.00383 +2024-11-22 14:53:51.086746: train_loss -0.7907 +2024-11-22 14:53:51.086979: val_loss -0.7843 +2024-11-22 14:53:51.087061: Pseudo dice [0.8488] +2024-11-22 14:53:51.087135: Epoch time: 18.12 s +2024-11-22 14:53:51.971659: +2024-11-22 14:53:51.971865: Epoch 5246 +2024-11-22 14:53:51.971977: Current learning rate: 0.00383 +2024-11-22 14:54:11.362409: train_loss -0.7901 +2024-11-22 14:54:11.367841: val_loss -0.7647 +2024-11-22 14:54:11.367953: Pseudo dice [0.83] +2024-11-22 14:54:11.368052: Epoch time: 19.39 s +2024-11-22 14:54:12.388795: +2024-11-22 14:54:12.389017: Epoch 5247 +2024-11-22 14:54:12.389125: Current learning rate: 0.00383 +2024-11-22 14:54:31.803046: train_loss -0.792 +2024-11-22 14:54:31.803263: val_loss -0.7753 +2024-11-22 14:54:31.803343: Pseudo dice [0.8469] +2024-11-22 14:54:31.803418: Epoch time: 19.42 s +2024-11-22 14:54:33.033697: +2024-11-22 14:54:33.033955: Epoch 5248 +2024-11-22 14:54:33.034073: Current learning rate: 0.00383 +2024-11-22 14:54:51.149721: train_loss -0.7992 +2024-11-22 14:54:51.149947: val_loss -0.7848 +2024-11-22 14:54:51.150030: Pseudo dice [0.8432] +2024-11-22 14:54:51.150111: Epoch time: 18.12 s +2024-11-22 14:54:52.188117: +2024-11-22 14:54:52.188337: Epoch 5249 +2024-11-22 14:54:52.188446: Current learning rate: 0.00383 +2024-11-22 14:55:11.027164: train_loss -0.799 +2024-11-22 14:55:11.027410: val_loss -0.7874 +2024-11-22 14:55:11.027486: Pseudo dice [0.8553] +2024-11-22 14:55:11.029823: Epoch time: 18.84 s +2024-11-22 14:55:12.220627: +2024-11-22 14:55:12.220839: Epoch 5250 +2024-11-22 14:55:12.220949: Current learning rate: 0.00382 +2024-11-22 14:55:30.239899: train_loss -0.8074 +2024-11-22 14:55:30.240127: val_loss -0.7902 +2024-11-22 14:55:30.240200: Pseudo dice [0.8531] +2024-11-22 14:55:30.240277: Epoch time: 18.02 s +2024-11-22 14:55:31.120424: +2024-11-22 14:55:31.120642: Epoch 5251 +2024-11-22 14:55:31.120754: Current learning rate: 0.00382 +2024-11-22 14:55:49.734789: train_loss -0.8001 +2024-11-22 14:55:49.735012: val_loss -0.7724 +2024-11-22 14:55:49.735088: Pseudo dice [0.8399] +2024-11-22 14:55:49.735165: Epoch time: 18.62 s +2024-11-22 14:55:50.626827: +2024-11-22 14:55:50.627062: Epoch 5252 +2024-11-22 14:55:50.627175: Current learning rate: 0.00382 +2024-11-22 14:56:09.440873: train_loss -0.7963 +2024-11-22 14:56:09.441171: val_loss -0.7875 +2024-11-22 14:56:09.441256: Pseudo dice [0.8562] +2024-11-22 14:56:09.441333: Epoch time: 18.81 s +2024-11-22 14:56:10.320565: +2024-11-22 14:56:10.320779: Epoch 5253 +2024-11-22 14:56:10.320889: Current learning rate: 0.00382 +2024-11-22 14:56:30.196210: train_loss -0.7995 +2024-11-22 14:56:30.196444: val_loss -0.7549 +2024-11-22 14:56:30.196521: Pseudo dice [0.8428] +2024-11-22 14:56:30.196599: Epoch time: 19.88 s +2024-11-22 14:56:31.081120: +2024-11-22 14:56:31.081352: Epoch 5254 +2024-11-22 14:56:31.081466: Current learning rate: 0.00382 +2024-11-22 14:56:49.090380: train_loss -0.7869 +2024-11-22 14:56:49.090620: val_loss -0.7529 +2024-11-22 14:56:49.090700: Pseudo dice [0.8295] +2024-11-22 14:56:49.090781: Epoch time: 18.01 s +2024-11-22 14:56:50.001789: +2024-11-22 14:56:50.002007: Epoch 5255 +2024-11-22 14:56:50.002119: Current learning rate: 0.00382 +2024-11-22 14:57:07.710896: train_loss -0.7891 +2024-11-22 14:57:07.711114: val_loss -0.7835 +2024-11-22 14:57:07.711185: Pseudo dice [0.8427] +2024-11-22 14:57:07.711260: Epoch time: 17.71 s +2024-11-22 14:57:08.746627: +2024-11-22 14:57:08.746835: Epoch 5256 +2024-11-22 14:57:08.746947: Current learning rate: 0.00382 +2024-11-22 14:57:27.631681: train_loss -0.7964 +2024-11-22 14:57:27.631897: val_loss -0.7731 +2024-11-22 14:57:27.631975: Pseudo dice [0.8568] +2024-11-22 14:57:27.632065: Epoch time: 18.89 s +2024-11-22 14:57:28.513608: +2024-11-22 14:57:28.513804: Epoch 5257 +2024-11-22 14:57:28.513914: Current learning rate: 0.00382 +2024-11-22 14:57:46.899316: train_loss -0.7942 +2024-11-22 14:57:46.899604: val_loss -0.7818 +2024-11-22 14:57:46.899681: Pseudo dice [0.8559] +2024-11-22 14:57:46.899760: Epoch time: 18.39 s +2024-11-22 14:57:47.788350: +2024-11-22 14:57:47.788555: Epoch 5258 +2024-11-22 14:57:47.788662: Current learning rate: 0.00381 +2024-11-22 14:58:06.932239: train_loss -0.7837 +2024-11-22 14:58:06.932442: val_loss -0.7583 +2024-11-22 14:58:06.932515: Pseudo dice [0.8422] +2024-11-22 14:58:06.932589: Epoch time: 19.14 s +2024-11-22 14:58:07.819224: +2024-11-22 14:58:07.819453: Epoch 5259 +2024-11-22 14:58:07.819565: Current learning rate: 0.00381 +2024-11-22 14:58:25.479568: train_loss -0.7817 +2024-11-22 14:58:25.480166: val_loss -0.7756 +2024-11-22 14:58:25.480273: Pseudo dice [0.8487] +2024-11-22 14:58:25.480358: Epoch time: 17.66 s +2024-11-22 14:58:26.377308: +2024-11-22 14:58:26.377604: Epoch 5260 +2024-11-22 14:58:26.377756: Current learning rate: 0.00381 +2024-11-22 14:58:44.660081: train_loss -0.7904 +2024-11-22 14:58:44.660696: val_loss -0.7573 +2024-11-22 14:58:44.660799: Pseudo dice [0.8414] +2024-11-22 14:58:44.660881: Epoch time: 18.28 s +2024-11-22 14:58:45.555197: +2024-11-22 14:58:45.555440: Epoch 5261 +2024-11-22 14:58:45.555553: Current learning rate: 0.00381 +2024-11-22 14:59:03.932801: train_loss -0.7899 +2024-11-22 14:59:03.933045: val_loss -0.7651 +2024-11-22 14:59:03.934839: Pseudo dice [0.834] +2024-11-22 14:59:03.934956: Epoch time: 18.38 s +2024-11-22 14:59:04.833019: +2024-11-22 14:59:04.833245: Epoch 5262 +2024-11-22 14:59:04.833364: Current learning rate: 0.00381 +2024-11-22 14:59:22.762089: train_loss -0.7918 +2024-11-22 14:59:22.762311: val_loss -0.7714 +2024-11-22 14:59:22.762388: Pseudo dice [0.8362] +2024-11-22 14:59:22.762468: Epoch time: 17.93 s +2024-11-22 14:59:23.644012: +2024-11-22 14:59:23.644231: Epoch 5263 +2024-11-22 14:59:23.644342: Current learning rate: 0.00381 +2024-11-22 14:59:40.709493: train_loss -0.792 +2024-11-22 14:59:40.711909: val_loss -0.7406 +2024-11-22 14:59:40.712010: Pseudo dice [0.8417] +2024-11-22 14:59:40.712089: Epoch time: 17.07 s +2024-11-22 14:59:41.715914: +2024-11-22 14:59:41.716156: Epoch 5264 +2024-11-22 14:59:41.716264: Current learning rate: 0.00381 +2024-11-22 15:00:01.532858: train_loss -0.7942 +2024-11-22 15:00:01.533087: val_loss -0.7331 +2024-11-22 15:00:01.533166: Pseudo dice [0.833] +2024-11-22 15:00:01.533244: Epoch time: 19.82 s +2024-11-22 15:00:02.422443: +2024-11-22 15:00:02.422640: Epoch 5265 +2024-11-22 15:00:02.422754: Current learning rate: 0.00381 +2024-11-22 15:00:21.249723: train_loss -0.8032 +2024-11-22 15:00:21.249949: val_loss -0.766 +2024-11-22 15:00:21.250044: Pseudo dice [0.8459] +2024-11-22 15:00:21.250127: Epoch time: 18.83 s +2024-11-22 15:00:22.131084: +2024-11-22 15:00:22.131306: Epoch 5266 +2024-11-22 15:00:22.131450: Current learning rate: 0.0038 +2024-11-22 15:00:41.523734: train_loss -0.7904 +2024-11-22 15:00:41.523963: val_loss -0.8056 +2024-11-22 15:00:41.526132: Pseudo dice [0.8575] +2024-11-22 15:00:41.530317: Epoch time: 19.39 s +2024-11-22 15:00:42.439308: +2024-11-22 15:00:42.439531: Epoch 5267 +2024-11-22 15:00:42.439645: Current learning rate: 0.0038 +2024-11-22 15:01:00.889062: train_loss -0.7908 +2024-11-22 15:01:00.889398: val_loss -0.7913 +2024-11-22 15:01:00.889483: Pseudo dice [0.8576] +2024-11-22 15:01:00.889565: Epoch time: 18.45 s +2024-11-22 15:01:01.888168: +2024-11-22 15:01:01.888414: Epoch 5268 +2024-11-22 15:01:01.888529: Current learning rate: 0.0038 +2024-11-22 15:01:20.602954: train_loss -0.7946 +2024-11-22 15:01:20.603194: val_loss -0.7642 +2024-11-22 15:01:20.603273: Pseudo dice [0.8547] +2024-11-22 15:01:20.603352: Epoch time: 18.72 s +2024-11-22 15:01:21.487300: +2024-11-22 15:01:21.487599: Epoch 5269 +2024-11-22 15:01:21.487707: Current learning rate: 0.0038 +2024-11-22 15:01:40.309349: train_loss -0.791 +2024-11-22 15:01:40.309569: val_loss -0.7785 +2024-11-22 15:01:40.314785: Pseudo dice [0.8543] +2024-11-22 15:01:40.315006: Epoch time: 18.82 s +2024-11-22 15:01:41.193598: +2024-11-22 15:01:41.193814: Epoch 5270 +2024-11-22 15:01:41.193924: Current learning rate: 0.0038 +2024-11-22 15:02:00.070456: train_loss -0.803 +2024-11-22 15:02:00.070709: val_loss -0.7927 +2024-11-22 15:02:00.070784: Pseudo dice [0.859] +2024-11-22 15:02:00.073102: Epoch time: 18.88 s +2024-11-22 15:02:01.347308: +2024-11-22 15:02:01.347531: Epoch 5271 +2024-11-22 15:02:01.347639: Current learning rate: 0.0038 +2024-11-22 15:02:18.410174: train_loss -0.8003 +2024-11-22 15:02:18.411947: val_loss -0.7594 +2024-11-22 15:02:18.412052: Pseudo dice [0.8368] +2024-11-22 15:02:18.412134: Epoch time: 17.06 s +2024-11-22 15:02:19.299877: +2024-11-22 15:02:19.300110: Epoch 5272 +2024-11-22 15:02:19.300218: Current learning rate: 0.0038 +2024-11-22 15:02:37.890881: train_loss -0.7944 +2024-11-22 15:02:37.891098: val_loss -0.7721 +2024-11-22 15:02:37.891172: Pseudo dice [0.8513] +2024-11-22 15:02:37.891247: Epoch time: 18.59 s +2024-11-22 15:02:38.778741: +2024-11-22 15:02:38.778976: Epoch 5273 +2024-11-22 15:02:38.779093: Current learning rate: 0.0038 +2024-11-22 15:02:56.815867: train_loss -0.7931 +2024-11-22 15:02:56.816129: val_loss -0.773 +2024-11-22 15:02:56.816206: Pseudo dice [0.8579] +2024-11-22 15:02:56.816286: Epoch time: 18.04 s +2024-11-22 15:02:57.701780: +2024-11-22 15:02:57.702017: Epoch 5274 +2024-11-22 15:02:57.702127: Current learning rate: 0.00379 +2024-11-22 15:03:16.575541: train_loss -0.7949 +2024-11-22 15:03:16.575760: val_loss -0.7746 +2024-11-22 15:03:16.575848: Pseudo dice [0.8497] +2024-11-22 15:03:16.575943: Epoch time: 18.87 s +2024-11-22 15:03:17.461879: +2024-11-22 15:03:17.462103: Epoch 5275 +2024-11-22 15:03:17.462214: Current learning rate: 0.00379 +2024-11-22 15:03:36.394533: train_loss -0.79 +2024-11-22 15:03:36.394749: val_loss -0.7844 +2024-11-22 15:03:36.394825: Pseudo dice [0.8466] +2024-11-22 15:03:36.394901: Epoch time: 18.93 s +2024-11-22 15:03:37.285669: +2024-11-22 15:03:37.285882: Epoch 5276 +2024-11-22 15:03:37.286000: Current learning rate: 0.00379 +2024-11-22 15:03:54.639339: train_loss -0.8003 +2024-11-22 15:03:54.639571: val_loss -0.7526 +2024-11-22 15:03:54.639645: Pseudo dice [0.8506] +2024-11-22 15:03:54.639721: Epoch time: 17.35 s +2024-11-22 15:03:55.605662: +2024-11-22 15:03:55.605880: Epoch 5277 +2024-11-22 15:03:55.605996: Current learning rate: 0.00379 +2024-11-22 15:04:13.433078: train_loss -0.7748 +2024-11-22 15:04:13.433316: val_loss -0.7835 +2024-11-22 15:04:13.433406: Pseudo dice [0.8575] +2024-11-22 15:04:13.433496: Epoch time: 17.83 s +2024-11-22 15:04:14.322761: +2024-11-22 15:04:14.322973: Epoch 5278 +2024-11-22 15:04:14.323087: Current learning rate: 0.00379 +2024-11-22 15:04:31.864282: train_loss -0.7868 +2024-11-22 15:04:31.864502: val_loss -0.7309 +2024-11-22 15:04:31.864581: Pseudo dice [0.8423] +2024-11-22 15:04:31.864660: Epoch time: 17.54 s +2024-11-22 15:04:32.757779: +2024-11-22 15:04:32.758003: Epoch 5279 +2024-11-22 15:04:32.758117: Current learning rate: 0.00379 +2024-11-22 15:04:51.550955: train_loss -0.7872 +2024-11-22 15:04:51.551207: val_loss -0.7753 +2024-11-22 15:04:51.551280: Pseudo dice [0.8413] +2024-11-22 15:04:51.551359: Epoch time: 18.79 s +2024-11-22 15:04:52.428535: +2024-11-22 15:04:52.428764: Epoch 5280 +2024-11-22 15:04:52.428878: Current learning rate: 0.00379 +2024-11-22 15:05:09.623263: train_loss -0.7952 +2024-11-22 15:05:09.624136: val_loss -0.7558 +2024-11-22 15:05:09.624217: Pseudo dice [0.8383] +2024-11-22 15:05:09.624294: Epoch time: 17.2 s +2024-11-22 15:05:10.501173: +2024-11-22 15:05:10.501405: Epoch 5281 +2024-11-22 15:05:10.501524: Current learning rate: 0.00379 +2024-11-22 15:05:29.291283: train_loss -0.8003 +2024-11-22 15:05:29.291542: val_loss -0.7684 +2024-11-22 15:05:29.291632: Pseudo dice [0.8472] +2024-11-22 15:05:29.293905: Epoch time: 18.79 s +2024-11-22 15:05:30.210824: +2024-11-22 15:05:30.211094: Epoch 5282 +2024-11-22 15:05:30.211206: Current learning rate: 0.00378 +2024-11-22 15:05:48.546072: train_loss -0.7768 +2024-11-22 15:05:48.546285: val_loss -0.769 +2024-11-22 15:05:48.546362: Pseudo dice [0.8178] +2024-11-22 15:05:48.546436: Epoch time: 18.34 s +2024-11-22 15:05:49.835794: +2024-11-22 15:05:49.836107: Epoch 5283 +2024-11-22 15:05:49.836218: Current learning rate: 0.00378 +2024-11-22 15:06:08.472515: train_loss -0.7823 +2024-11-22 15:06:08.472738: val_loss -0.7714 +2024-11-22 15:06:08.472816: Pseudo dice [0.8433] +2024-11-22 15:06:08.472908: Epoch time: 18.64 s +2024-11-22 15:06:09.361581: +2024-11-22 15:06:09.361828: Epoch 5284 +2024-11-22 15:06:09.361948: Current learning rate: 0.00378 +2024-11-22 15:06:27.015652: train_loss -0.7769 +2024-11-22 15:06:27.015912: val_loss -0.7602 +2024-11-22 15:06:27.021222: Pseudo dice [0.8246] +2024-11-22 15:06:27.021368: Epoch time: 17.65 s +2024-11-22 15:06:27.951341: +2024-11-22 15:06:27.951559: Epoch 5285 +2024-11-22 15:06:27.951668: Current learning rate: 0.00378 +2024-11-22 15:06:46.914603: train_loss -0.7768 +2024-11-22 15:06:46.914816: val_loss -0.776 +2024-11-22 15:06:46.914890: Pseudo dice [0.8541] +2024-11-22 15:06:46.914964: Epoch time: 18.96 s +2024-11-22 15:06:47.806298: +2024-11-22 15:06:47.806501: Epoch 5286 +2024-11-22 15:06:47.806611: Current learning rate: 0.00378 +2024-11-22 15:07:05.733277: train_loss -0.7952 +2024-11-22 15:07:05.733490: val_loss -0.7714 +2024-11-22 15:07:05.733597: Pseudo dice [0.8325] +2024-11-22 15:07:05.733674: Epoch time: 17.93 s +2024-11-22 15:07:06.608287: +2024-11-22 15:07:06.608513: Epoch 5287 +2024-11-22 15:07:06.608627: Current learning rate: 0.00378 +2024-11-22 15:07:25.476185: train_loss -0.7895 +2024-11-22 15:07:25.476409: val_loss -0.7709 +2024-11-22 15:07:25.476485: Pseudo dice [0.8476] +2024-11-22 15:07:25.476558: Epoch time: 18.87 s +2024-11-22 15:07:26.458161: +2024-11-22 15:07:26.458377: Epoch 5288 +2024-11-22 15:07:26.458488: Current learning rate: 0.00378 +2024-11-22 15:07:45.112750: train_loss -0.8011 +2024-11-22 15:07:45.113010: val_loss -0.756 +2024-11-22 15:07:45.113088: Pseudo dice [0.8427] +2024-11-22 15:07:45.113174: Epoch time: 18.66 s +2024-11-22 15:07:46.002652: +2024-11-22 15:07:46.002865: Epoch 5289 +2024-11-22 15:07:46.002977: Current learning rate: 0.00378 +2024-11-22 15:08:04.449965: train_loss -0.7907 +2024-11-22 15:08:04.450187: val_loss -0.7646 +2024-11-22 15:08:04.450264: Pseudo dice [0.8349] +2024-11-22 15:08:04.450338: Epoch time: 18.45 s +2024-11-22 15:08:05.341971: +2024-11-22 15:08:05.342189: Epoch 5290 +2024-11-22 15:08:05.342298: Current learning rate: 0.00377 +2024-11-22 15:08:23.604163: train_loss -0.7964 +2024-11-22 15:08:23.604381: val_loss -0.7789 +2024-11-22 15:08:23.604456: Pseudo dice [0.8548] +2024-11-22 15:08:23.604534: Epoch time: 18.26 s +2024-11-22 15:08:24.491495: +2024-11-22 15:08:24.491702: Epoch 5291 +2024-11-22 15:08:24.491817: Current learning rate: 0.00377 +2024-11-22 15:08:43.382605: train_loss -0.7988 +2024-11-22 15:08:43.382826: val_loss -0.7857 +2024-11-22 15:08:43.382905: Pseudo dice [0.8554] +2024-11-22 15:08:43.382986: Epoch time: 18.89 s +2024-11-22 15:08:44.269987: +2024-11-22 15:08:44.270203: Epoch 5292 +2024-11-22 15:08:44.270316: Current learning rate: 0.00377 +2024-11-22 15:09:03.560302: train_loss -0.8001 +2024-11-22 15:09:03.560546: val_loss -0.7731 +2024-11-22 15:09:03.560624: Pseudo dice [0.8499] +2024-11-22 15:09:03.560704: Epoch time: 19.29 s +2024-11-22 15:09:04.440616: +2024-11-22 15:09:04.440827: Epoch 5293 +2024-11-22 15:09:04.440938: Current learning rate: 0.00377 +2024-11-22 15:09:23.127997: train_loss -0.8071 +2024-11-22 15:09:23.128211: val_loss -0.7814 +2024-11-22 15:09:23.128287: Pseudo dice [0.851] +2024-11-22 15:09:23.128363: Epoch time: 18.69 s +2024-11-22 15:09:24.003347: +2024-11-22 15:09:24.003580: Epoch 5294 +2024-11-22 15:09:24.003696: Current learning rate: 0.00377 +2024-11-22 15:09:42.072982: train_loss -0.7965 +2024-11-22 15:09:42.073228: val_loss -0.7581 +2024-11-22 15:09:42.073311: Pseudo dice [0.8506] +2024-11-22 15:09:42.073391: Epoch time: 18.07 s +2024-11-22 15:09:43.517019: +2024-11-22 15:09:43.517291: Epoch 5295 +2024-11-22 15:09:43.517403: Current learning rate: 0.00377 +2024-11-22 15:10:02.144623: train_loss -0.8044 +2024-11-22 15:10:02.144878: val_loss -0.7486 +2024-11-22 15:10:02.144952: Pseudo dice [0.8388] +2024-11-22 15:10:02.157216: Epoch time: 18.63 s +2024-11-22 15:10:03.184682: +2024-11-22 15:10:03.184923: Epoch 5296 +2024-11-22 15:10:03.185044: Current learning rate: 0.00377 +2024-11-22 15:10:21.562031: train_loss -0.8037 +2024-11-22 15:10:21.562263: val_loss -0.7689 +2024-11-22 15:10:21.562342: Pseudo dice [0.8465] +2024-11-22 15:10:21.562700: Epoch time: 18.38 s +2024-11-22 15:10:22.441854: +2024-11-22 15:10:22.442088: Epoch 5297 +2024-11-22 15:10:22.442194: Current learning rate: 0.00377 +2024-11-22 15:10:40.305734: train_loss -0.8083 +2024-11-22 15:10:40.306036: val_loss -0.7813 +2024-11-22 15:10:40.306122: Pseudo dice [0.8501] +2024-11-22 15:10:40.306199: Epoch time: 17.86 s +2024-11-22 15:10:41.193520: +2024-11-22 15:10:41.193732: Epoch 5298 +2024-11-22 15:10:41.193840: Current learning rate: 0.00376 +2024-11-22 15:11:00.019438: train_loss -0.802 +2024-11-22 15:11:00.019662: val_loss -0.7541 +2024-11-22 15:11:00.019744: Pseudo dice [0.8492] +2024-11-22 15:11:00.019825: Epoch time: 18.83 s +2024-11-22 15:11:00.907764: +2024-11-22 15:11:00.907973: Epoch 5299 +2024-11-22 15:11:00.908092: Current learning rate: 0.00376 +2024-11-22 15:11:19.911903: train_loss -0.7857 +2024-11-22 15:11:19.912148: val_loss -0.7748 +2024-11-22 15:11:19.912223: Pseudo dice [0.8391] +2024-11-22 15:11:19.912297: Epoch time: 19.0 s +2024-11-22 15:11:21.224677: +2024-11-22 15:11:21.224911: Epoch 5300 +2024-11-22 15:11:21.225030: Current learning rate: 0.00376 +2024-11-22 15:11:40.492228: train_loss -0.7982 +2024-11-22 15:11:40.492449: val_loss -0.765 +2024-11-22 15:11:40.492527: Pseudo dice [0.8393] +2024-11-22 15:11:40.492602: Epoch time: 19.27 s +2024-11-22 15:11:41.376423: +2024-11-22 15:11:41.376641: Epoch 5301 +2024-11-22 15:11:41.376753: Current learning rate: 0.00376 +2024-11-22 15:12:00.540732: train_loss -0.7925 +2024-11-22 15:12:00.540999: val_loss -0.7783 +2024-11-22 15:12:00.541077: Pseudo dice [0.8486] +2024-11-22 15:12:00.541157: Epoch time: 19.16 s +2024-11-22 15:12:01.450518: +2024-11-22 15:12:01.450720: Epoch 5302 +2024-11-22 15:12:01.450829: Current learning rate: 0.00376 +2024-11-22 15:12:19.935079: train_loss -0.8011 +2024-11-22 15:12:19.935324: val_loss -0.7534 +2024-11-22 15:12:19.935403: Pseudo dice [0.8442] +2024-11-22 15:12:19.935486: Epoch time: 18.49 s +2024-11-22 15:12:20.815717: +2024-11-22 15:12:20.815938: Epoch 5303 +2024-11-22 15:12:20.816051: Current learning rate: 0.00376 +2024-11-22 15:12:39.270773: train_loss -0.8036 +2024-11-22 15:12:39.270986: val_loss -0.7874 +2024-11-22 15:12:39.271070: Pseudo dice [0.8575] +2024-11-22 15:12:39.271147: Epoch time: 18.46 s +2024-11-22 15:12:40.150164: +2024-11-22 15:12:40.150454: Epoch 5304 +2024-11-22 15:12:40.150562: Current learning rate: 0.00376 +2024-11-22 15:12:58.816341: train_loss -0.7987 +2024-11-22 15:12:58.816544: val_loss -0.7813 +2024-11-22 15:12:58.816631: Pseudo dice [0.8467] +2024-11-22 15:12:58.816709: Epoch time: 18.67 s +2024-11-22 15:12:59.696483: +2024-11-22 15:12:59.696783: Epoch 5305 +2024-11-22 15:12:59.696893: Current learning rate: 0.00376 +2024-11-22 15:13:17.312376: train_loss -0.8009 +2024-11-22 15:13:17.312583: val_loss -0.7831 +2024-11-22 15:13:17.312659: Pseudo dice [0.8305] +2024-11-22 15:13:17.312734: Epoch time: 17.62 s +2024-11-22 15:13:18.295941: +2024-11-22 15:13:18.296195: Epoch 5306 +2024-11-22 15:13:18.296320: Current learning rate: 0.00375 +2024-11-22 15:13:36.015637: train_loss -0.8029 +2024-11-22 15:13:36.016169: val_loss -0.772 +2024-11-22 15:13:36.016271: Pseudo dice [0.8495] +2024-11-22 15:13:36.016351: Epoch time: 17.72 s +2024-11-22 15:13:36.947831: +2024-11-22 15:13:36.948073: Epoch 5307 +2024-11-22 15:13:36.948182: Current learning rate: 0.00375 +2024-11-22 15:13:55.796956: train_loss -0.8001 +2024-11-22 15:13:55.797182: val_loss -0.764 +2024-11-22 15:13:55.797257: Pseudo dice [0.8376] +2024-11-22 15:13:55.797337: Epoch time: 18.85 s +2024-11-22 15:13:56.686821: +2024-11-22 15:13:56.687053: Epoch 5308 +2024-11-22 15:13:56.687165: Current learning rate: 0.00375 +2024-11-22 15:14:14.621636: train_loss -0.8011 +2024-11-22 15:14:14.621869: val_loss -0.7916 +2024-11-22 15:14:14.621945: Pseudo dice [0.8488] +2024-11-22 15:14:14.622033: Epoch time: 17.94 s +2024-11-22 15:14:15.502903: +2024-11-22 15:14:15.503139: Epoch 5309 +2024-11-22 15:14:15.503248: Current learning rate: 0.00375 +2024-11-22 15:14:34.636826: train_loss -0.7943 +2024-11-22 15:14:34.637094: val_loss -0.7813 +2024-11-22 15:14:34.637170: Pseudo dice [0.8522] +2024-11-22 15:14:34.637252: Epoch time: 19.13 s +2024-11-22 15:14:35.526094: +2024-11-22 15:14:35.526370: Epoch 5310 +2024-11-22 15:14:35.526478: Current learning rate: 0.00375 +2024-11-22 15:14:53.711141: train_loss -0.7971 +2024-11-22 15:14:53.711352: val_loss -0.7878 +2024-11-22 15:14:53.711424: Pseudo dice [0.8614] +2024-11-22 15:14:53.711496: Epoch time: 18.19 s +2024-11-22 15:14:54.595097: +2024-11-22 15:14:54.595305: Epoch 5311 +2024-11-22 15:14:54.595413: Current learning rate: 0.00375 +2024-11-22 15:15:12.622761: train_loss -0.8052 +2024-11-22 15:15:12.623002: val_loss -0.7741 +2024-11-22 15:15:12.623081: Pseudo dice [0.8335] +2024-11-22 15:15:12.623155: Epoch time: 18.03 s +2024-11-22 15:15:13.510148: +2024-11-22 15:15:13.510365: Epoch 5312 +2024-11-22 15:15:13.510475: Current learning rate: 0.00375 +2024-11-22 15:15:31.616432: train_loss -0.801 +2024-11-22 15:15:31.616655: val_loss -0.787 +2024-11-22 15:15:31.616730: Pseudo dice [0.8545] +2024-11-22 15:15:31.616807: Epoch time: 18.11 s +2024-11-22 15:15:32.497341: +2024-11-22 15:15:32.497551: Epoch 5313 +2024-11-22 15:15:32.497657: Current learning rate: 0.00375 +2024-11-22 15:15:50.755100: train_loss -0.8011 +2024-11-22 15:15:50.755309: val_loss -0.7744 +2024-11-22 15:15:50.755386: Pseudo dice [0.848] +2024-11-22 15:15:50.755465: Epoch time: 18.26 s +2024-11-22 15:15:51.636166: +2024-11-22 15:15:51.636509: Epoch 5314 +2024-11-22 15:15:51.636621: Current learning rate: 0.00374 +2024-11-22 15:16:10.321903: train_loss -0.8029 +2024-11-22 15:16:10.322149: val_loss -0.7924 +2024-11-22 15:16:10.322289: Pseudo dice [0.8645] +2024-11-22 15:16:10.322372: Epoch time: 18.69 s +2024-11-22 15:16:11.207761: +2024-11-22 15:16:11.207963: Epoch 5315 +2024-11-22 15:16:11.208078: Current learning rate: 0.00374 +2024-11-22 15:16:29.712520: train_loss -0.8034 +2024-11-22 15:16:29.712755: val_loss -0.7854 +2024-11-22 15:16:29.712831: Pseudo dice [0.8501] +2024-11-22 15:16:29.712905: Epoch time: 18.51 s +2024-11-22 15:16:30.594791: +2024-11-22 15:16:30.595004: Epoch 5316 +2024-11-22 15:16:30.595119: Current learning rate: 0.00374 +2024-11-22 15:16:48.516597: train_loss -0.8054 +2024-11-22 15:16:48.516822: val_loss -0.8023 +2024-11-22 15:16:48.516894: Pseudo dice [0.8637] +2024-11-22 15:16:48.516967: Epoch time: 17.92 s +2024-11-22 15:16:49.397812: +2024-11-22 15:16:49.398027: Epoch 5317 +2024-11-22 15:16:49.398139: Current learning rate: 0.00374 +2024-11-22 15:17:07.847460: train_loss -0.7978 +2024-11-22 15:17:07.847731: val_loss -0.7528 +2024-11-22 15:17:07.847808: Pseudo dice [0.8491] +2024-11-22 15:17:07.847894: Epoch time: 18.45 s +2024-11-22 15:17:09.149592: +2024-11-22 15:17:09.150003: Epoch 5318 +2024-11-22 15:17:09.150133: Current learning rate: 0.00374 +2024-11-22 15:17:27.241678: train_loss -0.791 +2024-11-22 15:17:27.241892: val_loss -0.7616 +2024-11-22 15:17:27.241966: Pseudo dice [0.8507] +2024-11-22 15:17:27.242046: Epoch time: 18.09 s +2024-11-22 15:17:28.124003: +2024-11-22 15:17:28.124436: Epoch 5319 +2024-11-22 15:17:28.124573: Current learning rate: 0.00374 +2024-11-22 15:17:47.026614: train_loss -0.806 +2024-11-22 15:17:47.026824: val_loss -0.7595 +2024-11-22 15:17:47.026899: Pseudo dice [0.8434] +2024-11-22 15:17:47.026974: Epoch time: 18.9 s +2024-11-22 15:17:47.982577: +2024-11-22 15:17:47.982999: Epoch 5320 +2024-11-22 15:17:47.983132: Current learning rate: 0.00374 +2024-11-22 15:18:05.090090: train_loss -0.8106 +2024-11-22 15:18:05.090303: val_loss -0.79 +2024-11-22 15:18:05.090379: Pseudo dice [0.8588] +2024-11-22 15:18:05.090459: Epoch time: 17.11 s +2024-11-22 15:18:06.026612: +2024-11-22 15:18:06.027097: Epoch 5321 +2024-11-22 15:18:06.027230: Current learning rate: 0.00374 +2024-11-22 15:18:23.349048: train_loss -0.8001 +2024-11-22 15:18:23.349289: val_loss -0.7643 +2024-11-22 15:18:23.349364: Pseudo dice [0.8497] +2024-11-22 15:18:23.349447: Epoch time: 17.32 s +2024-11-22 15:18:24.237469: +2024-11-22 15:18:24.237934: Epoch 5322 +2024-11-22 15:18:24.238078: Current learning rate: 0.00373 +2024-11-22 15:18:42.656871: train_loss -0.8007 +2024-11-22 15:18:42.657106: val_loss -0.7701 +2024-11-22 15:18:42.657474: Pseudo dice [0.85] +2024-11-22 15:18:42.657553: Epoch time: 18.42 s +2024-11-22 15:18:43.539819: +2024-11-22 15:18:43.540253: Epoch 5323 +2024-11-22 15:18:43.540396: Current learning rate: 0.00373 +2024-11-22 15:19:01.973078: train_loss -0.7967 +2024-11-22 15:19:01.973310: val_loss -0.7851 +2024-11-22 15:19:01.973388: Pseudo dice [0.8645] +2024-11-22 15:19:01.973468: Epoch time: 18.43 s +2024-11-22 15:19:02.878964: +2024-11-22 15:19:02.879419: Epoch 5324 +2024-11-22 15:19:02.879556: Current learning rate: 0.00373 +2024-11-22 15:19:21.037266: train_loss -0.7969 +2024-11-22 15:19:21.037491: val_loss -0.7499 +2024-11-22 15:19:21.037572: Pseudo dice [0.85] +2024-11-22 15:19:21.037648: Epoch time: 18.16 s +2024-11-22 15:19:21.923156: +2024-11-22 15:19:21.923593: Epoch 5325 +2024-11-22 15:19:21.923731: Current learning rate: 0.00373 +2024-11-22 15:19:41.103355: train_loss -0.8025 +2024-11-22 15:19:41.103601: val_loss -0.761 +2024-11-22 15:19:41.103681: Pseudo dice [0.838] +2024-11-22 15:19:41.103768: Epoch time: 19.18 s +2024-11-22 15:19:41.984024: +2024-11-22 15:19:41.984613: Epoch 5326 +2024-11-22 15:19:41.984742: Current learning rate: 0.00373 +2024-11-22 15:19:59.380823: train_loss -0.792 +2024-11-22 15:19:59.384813: val_loss -0.7754 +2024-11-22 15:19:59.390517: Pseudo dice [0.8528] +2024-11-22 15:19:59.390620: Epoch time: 17.4 s +2024-11-22 15:20:00.363611: +2024-11-22 15:20:00.364115: Epoch 5327 +2024-11-22 15:20:00.364244: Current learning rate: 0.00373 +2024-11-22 15:20:18.163782: train_loss -0.7952 +2024-11-22 15:20:18.164011: val_loss -0.7845 +2024-11-22 15:20:18.164088: Pseudo dice [0.8423] +2024-11-22 15:20:18.164163: Epoch time: 17.8 s +2024-11-22 15:20:19.051679: +2024-11-22 15:20:19.052135: Epoch 5328 +2024-11-22 15:20:19.052268: Current learning rate: 0.00373 +2024-11-22 15:20:37.670450: train_loss -0.792 +2024-11-22 15:20:37.670673: val_loss -0.7793 +2024-11-22 15:20:37.670755: Pseudo dice [0.833] +2024-11-22 15:20:37.670834: Epoch time: 18.62 s +2024-11-22 15:20:38.553875: +2024-11-22 15:20:38.554104: Epoch 5329 +2024-11-22 15:20:38.554240: Current learning rate: 0.00373 +2024-11-22 15:20:56.658055: train_loss -0.8046 +2024-11-22 15:20:56.658297: val_loss -0.7781 +2024-11-22 15:20:56.658373: Pseudo dice [0.8655] +2024-11-22 15:20:56.658455: Epoch time: 18.1 s +2024-11-22 15:20:57.938886: +2024-11-22 15:20:57.939173: Epoch 5330 +2024-11-22 15:20:57.939281: Current learning rate: 0.00372 +2024-11-22 15:21:15.869983: train_loss -0.7946 +2024-11-22 15:21:15.870217: val_loss -0.7542 +2024-11-22 15:21:15.870292: Pseudo dice [0.8377] +2024-11-22 15:21:15.870375: Epoch time: 17.93 s +2024-11-22 15:21:16.763619: +2024-11-22 15:21:16.763842: Epoch 5331 +2024-11-22 15:21:16.763950: Current learning rate: 0.00372 +2024-11-22 15:21:34.919629: train_loss -0.8003 +2024-11-22 15:21:34.919891: val_loss -0.7482 +2024-11-22 15:21:34.919965: Pseudo dice [0.8318] +2024-11-22 15:21:34.920047: Epoch time: 18.16 s +2024-11-22 15:21:35.825429: +2024-11-22 15:21:35.825659: Epoch 5332 +2024-11-22 15:21:35.825767: Current learning rate: 0.00372 +2024-11-22 15:21:54.512387: train_loss -0.8049 +2024-11-22 15:21:54.512601: val_loss -0.761 +2024-11-22 15:21:54.512678: Pseudo dice [0.8512] +2024-11-22 15:21:54.512752: Epoch time: 18.69 s +2024-11-22 15:21:55.496415: +2024-11-22 15:21:55.496673: Epoch 5333 +2024-11-22 15:21:55.496812: Current learning rate: 0.00372 +2024-11-22 15:22:14.223495: train_loss -0.7924 +2024-11-22 15:22:14.224430: val_loss -0.7804 +2024-11-22 15:22:14.224525: Pseudo dice [0.8502] +2024-11-22 15:22:14.224610: Epoch time: 18.73 s +2024-11-22 15:22:15.254297: +2024-11-22 15:22:15.254508: Epoch 5334 +2024-11-22 15:22:15.254615: Current learning rate: 0.00372 +2024-11-22 15:22:33.550270: train_loss -0.7966 +2024-11-22 15:22:33.550497: val_loss -0.7728 +2024-11-22 15:22:33.550574: Pseudo dice [0.8537] +2024-11-22 15:22:33.550648: Epoch time: 18.3 s +2024-11-22 15:22:34.457634: +2024-11-22 15:22:34.457847: Epoch 5335 +2024-11-22 15:22:34.457954: Current learning rate: 0.00372 +2024-11-22 15:22:53.810056: train_loss -0.7887 +2024-11-22 15:22:53.810276: val_loss -0.7606 +2024-11-22 15:22:53.810351: Pseudo dice [0.8246] +2024-11-22 15:22:53.810426: Epoch time: 19.35 s +2024-11-22 15:22:54.699217: +2024-11-22 15:22:54.699445: Epoch 5336 +2024-11-22 15:22:54.699552: Current learning rate: 0.00372 +2024-11-22 15:23:12.720529: train_loss -0.784 +2024-11-22 15:23:12.721820: val_loss -0.7638 +2024-11-22 15:23:12.721909: Pseudo dice [0.8425] +2024-11-22 15:23:12.721990: Epoch time: 18.02 s +2024-11-22 15:23:13.670686: +2024-11-22 15:23:13.670878: Epoch 5337 +2024-11-22 15:23:13.670987: Current learning rate: 0.00372 +2024-11-22 15:23:32.216308: train_loss -0.7771 +2024-11-22 15:23:32.218703: val_loss -0.7617 +2024-11-22 15:23:32.218800: Pseudo dice [0.834] +2024-11-22 15:23:32.218881: Epoch time: 18.55 s +2024-11-22 15:23:33.224660: +2024-11-22 15:23:33.224859: Epoch 5338 +2024-11-22 15:23:33.224966: Current learning rate: 0.00371 +2024-11-22 15:23:50.723726: train_loss -0.7875 +2024-11-22 15:23:50.723937: val_loss -0.7591 +2024-11-22 15:23:50.724020: Pseudo dice [0.8498] +2024-11-22 15:23:50.724095: Epoch time: 17.5 s +2024-11-22 15:23:51.782707: +2024-11-22 15:23:51.782918: Epoch 5339 +2024-11-22 15:23:51.783132: Current learning rate: 0.00371 +2024-11-22 15:24:09.837204: train_loss -0.7854 +2024-11-22 15:24:09.837428: val_loss -0.7648 +2024-11-22 15:24:09.837528: Pseudo dice [0.8432] +2024-11-22 15:24:09.837605: Epoch time: 18.06 s +2024-11-22 15:24:10.825672: +2024-11-22 15:24:10.825929: Epoch 5340 +2024-11-22 15:24:10.826041: Current learning rate: 0.00371 +2024-11-22 15:24:28.637100: train_loss -0.8015 +2024-11-22 15:24:28.637947: val_loss -0.7645 +2024-11-22 15:24:28.638031: Pseudo dice [0.8608] +2024-11-22 15:24:28.638111: Epoch time: 17.81 s +2024-11-22 15:24:29.525666: +2024-11-22 15:24:29.525930: Epoch 5341 +2024-11-22 15:24:29.526094: Current learning rate: 0.00371 +2024-11-22 15:24:47.745981: train_loss -0.7979 +2024-11-22 15:24:47.746208: val_loss -0.7847 +2024-11-22 15:24:47.746284: Pseudo dice [0.856] +2024-11-22 15:24:47.746362: Epoch time: 18.22 s +2024-11-22 15:24:49.067086: +2024-11-22 15:24:49.067334: Epoch 5342 +2024-11-22 15:24:49.067446: Current learning rate: 0.00371 +2024-11-22 15:25:08.727552: train_loss -0.7929 +2024-11-22 15:25:08.728806: val_loss -0.7527 +2024-11-22 15:25:08.728895: Pseudo dice [0.8375] +2024-11-22 15:25:08.728972: Epoch time: 19.66 s +2024-11-22 15:25:09.767470: +2024-11-22 15:25:09.767687: Epoch 5343 +2024-11-22 15:25:09.767796: Current learning rate: 0.00371 +2024-11-22 15:25:27.723604: train_loss -0.7956 +2024-11-22 15:25:27.723836: val_loss -0.7787 +2024-11-22 15:25:27.723910: Pseudo dice [0.8545] +2024-11-22 15:25:27.723983: Epoch time: 17.96 s +2024-11-22 15:25:28.619238: +2024-11-22 15:25:28.619475: Epoch 5344 +2024-11-22 15:25:28.619595: Current learning rate: 0.00371 +2024-11-22 15:25:47.800773: train_loss -0.796 +2024-11-22 15:25:47.801017: val_loss -0.7839 +2024-11-22 15:25:47.801094: Pseudo dice [0.8566] +2024-11-22 15:25:47.801185: Epoch time: 19.18 s +2024-11-22 15:25:48.691831: +2024-11-22 15:25:48.692071: Epoch 5345 +2024-11-22 15:25:48.692189: Current learning rate: 0.00371 +2024-11-22 15:26:06.089550: train_loss -0.7869 +2024-11-22 15:26:06.089771: val_loss -0.7704 +2024-11-22 15:26:06.089849: Pseudo dice [0.8478] +2024-11-22 15:26:06.089925: Epoch time: 17.4 s +2024-11-22 15:26:06.971320: +2024-11-22 15:26:06.971535: Epoch 5346 +2024-11-22 15:26:06.971643: Current learning rate: 0.0037 +2024-11-22 15:26:24.862608: train_loss -0.7791 +2024-11-22 15:26:24.862839: val_loss -0.7619 +2024-11-22 15:26:24.862913: Pseudo dice [0.8484] +2024-11-22 15:26:24.863012: Epoch time: 17.89 s +2024-11-22 15:26:25.851114: +2024-11-22 15:26:25.851333: Epoch 5347 +2024-11-22 15:26:25.851442: Current learning rate: 0.0037 +2024-11-22 15:26:43.775490: train_loss -0.7857 +2024-11-22 15:26:43.780888: val_loss -0.7622 +2024-11-22 15:26:43.781013: Pseudo dice [0.8434] +2024-11-22 15:26:43.781092: Epoch time: 17.93 s +2024-11-22 15:26:44.677305: +2024-11-22 15:26:44.677508: Epoch 5348 +2024-11-22 15:26:44.677619: Current learning rate: 0.0037 +2024-11-22 15:27:03.011343: train_loss -0.7871 +2024-11-22 15:27:03.011599: val_loss -0.7776 +2024-11-22 15:27:03.014162: Pseudo dice [0.8412] +2024-11-22 15:27:03.014277: Epoch time: 18.33 s +2024-11-22 15:27:04.063794: +2024-11-22 15:27:04.064024: Epoch 5349 +2024-11-22 15:27:04.064145: Current learning rate: 0.0037 +2024-11-22 15:27:23.259861: train_loss -0.7842 +2024-11-22 15:27:23.260097: val_loss -0.7722 +2024-11-22 15:27:23.260173: Pseudo dice [0.8445] +2024-11-22 15:27:23.260247: Epoch time: 19.2 s +2024-11-22 15:27:24.433185: +2024-11-22 15:27:24.433397: Epoch 5350 +2024-11-22 15:27:24.433507: Current learning rate: 0.0037 +2024-11-22 15:27:43.281976: train_loss -0.7939 +2024-11-22 15:27:43.282201: val_loss -0.764 +2024-11-22 15:27:43.282367: Pseudo dice [0.8528] +2024-11-22 15:27:43.282449: Epoch time: 18.85 s +2024-11-22 15:27:44.174099: +2024-11-22 15:27:44.174318: Epoch 5351 +2024-11-22 15:27:44.174428: Current learning rate: 0.0037 +2024-11-22 15:28:02.393076: train_loss -0.7792 +2024-11-22 15:28:02.393629: val_loss -0.762 +2024-11-22 15:28:02.393717: Pseudo dice [0.8515] +2024-11-22 15:28:02.393793: Epoch time: 18.22 s +2024-11-22 15:28:03.275792: +2024-11-22 15:28:03.275995: Epoch 5352 +2024-11-22 15:28:03.276102: Current learning rate: 0.0037 +2024-11-22 15:28:22.477365: train_loss -0.7868 +2024-11-22 15:28:22.477594: val_loss -0.7766 +2024-11-22 15:28:22.477668: Pseudo dice [0.8518] +2024-11-22 15:28:22.477757: Epoch time: 19.2 s +2024-11-22 15:28:23.353279: +2024-11-22 15:28:23.353486: Epoch 5353 +2024-11-22 15:28:23.353596: Current learning rate: 0.0037 +2024-11-22 15:28:42.622332: train_loss -0.7969 +2024-11-22 15:28:42.622820: val_loss -0.7819 +2024-11-22 15:28:42.622921: Pseudo dice [0.8683] +2024-11-22 15:28:42.623012: Epoch time: 19.27 s +2024-11-22 15:28:43.507901: +2024-11-22 15:28:43.508107: Epoch 5354 +2024-11-22 15:28:43.508214: Current learning rate: 0.00369 +2024-11-22 15:29:01.209705: train_loss -0.7928 +2024-11-22 15:29:01.209937: val_loss -0.7503 +2024-11-22 15:29:01.210020: Pseudo dice [0.8392] +2024-11-22 15:29:01.210099: Epoch time: 17.7 s +2024-11-22 15:29:02.103365: +2024-11-22 15:29:02.103584: Epoch 5355 +2024-11-22 15:29:02.103693: Current learning rate: 0.00369 +2024-11-22 15:29:20.398597: train_loss -0.7783 +2024-11-22 15:29:20.398833: val_loss -0.7624 +2024-11-22 15:29:20.398909: Pseudo dice [0.8478] +2024-11-22 15:29:20.398987: Epoch time: 18.3 s +2024-11-22 15:29:21.362103: +2024-11-22 15:29:21.362327: Epoch 5356 +2024-11-22 15:29:21.362441: Current learning rate: 0.00369 +2024-11-22 15:29:39.083902: train_loss -0.7983 +2024-11-22 15:29:39.084131: val_loss -0.7789 +2024-11-22 15:29:39.104780: Pseudo dice [0.8366] +2024-11-22 15:29:39.104955: Epoch time: 17.72 s +2024-11-22 15:29:39.989058: +2024-11-22 15:29:39.989290: Epoch 5357 +2024-11-22 15:29:39.989401: Current learning rate: 0.00369 +2024-11-22 15:29:58.292570: train_loss -0.7975 +2024-11-22 15:29:58.292799: val_loss -0.7693 +2024-11-22 15:29:58.292878: Pseudo dice [0.8583] +2024-11-22 15:29:58.292955: Epoch time: 18.3 s +2024-11-22 15:29:59.184821: +2024-11-22 15:29:59.185040: Epoch 5358 +2024-11-22 15:29:59.185153: Current learning rate: 0.00369 +2024-11-22 15:30:17.150388: train_loss -0.7924 +2024-11-22 15:30:17.150595: val_loss -0.7915 +2024-11-22 15:30:17.150666: Pseudo dice [0.8465] +2024-11-22 15:30:17.150738: Epoch time: 17.97 s +2024-11-22 15:30:18.043900: +2024-11-22 15:30:18.044102: Epoch 5359 +2024-11-22 15:30:18.044206: Current learning rate: 0.00369 +2024-11-22 15:30:36.486882: train_loss -0.7932 +2024-11-22 15:30:36.487138: val_loss -0.774 +2024-11-22 15:30:36.487214: Pseudo dice [0.854] +2024-11-22 15:30:36.487317: Epoch time: 18.44 s +2024-11-22 15:30:37.382316: +2024-11-22 15:30:37.382537: Epoch 5360 +2024-11-22 15:30:37.382651: Current learning rate: 0.00369 +2024-11-22 15:30:55.988278: train_loss -0.794 +2024-11-22 15:30:55.988485: val_loss -0.7665 +2024-11-22 15:30:55.988557: Pseudo dice [0.8372] +2024-11-22 15:30:55.990853: Epoch time: 18.61 s +2024-11-22 15:30:56.914558: +2024-11-22 15:30:56.914783: Epoch 5361 +2024-11-22 15:30:56.914898: Current learning rate: 0.00369 +2024-11-22 15:31:15.231678: train_loss -0.7948 +2024-11-22 15:31:15.231895: val_loss -0.791 +2024-11-22 15:31:15.231970: Pseudo dice [0.844] +2024-11-22 15:31:15.232057: Epoch time: 18.32 s +2024-11-22 15:31:16.117220: +2024-11-22 15:31:16.117452: Epoch 5362 +2024-11-22 15:31:16.117564: Current learning rate: 0.00368 +2024-11-22 15:31:34.039346: train_loss -0.7839 +2024-11-22 15:31:34.039569: val_loss -0.7841 +2024-11-22 15:31:34.039647: Pseudo dice [0.8544] +2024-11-22 15:31:34.039721: Epoch time: 17.92 s +2024-11-22 15:31:34.926785: +2024-11-22 15:31:34.927004: Epoch 5363 +2024-11-22 15:31:34.927114: Current learning rate: 0.00368 +2024-11-22 15:31:53.761925: train_loss -0.7894 +2024-11-22 15:31:53.762190: val_loss -0.7735 +2024-11-22 15:31:53.762269: Pseudo dice [0.8587] +2024-11-22 15:31:53.762351: Epoch time: 18.84 s +2024-11-22 15:31:54.650681: +2024-11-22 15:31:54.651229: Epoch 5364 +2024-11-22 15:31:54.651365: Current learning rate: 0.00368 +2024-11-22 15:32:13.065043: train_loss -0.7971 +2024-11-22 15:32:13.065255: val_loss -0.7663 +2024-11-22 15:32:13.065325: Pseudo dice [0.8338] +2024-11-22 15:32:13.065398: Epoch time: 18.42 s +2024-11-22 15:32:14.368713: +2024-11-22 15:32:14.368950: Epoch 5365 +2024-11-22 15:32:14.369068: Current learning rate: 0.00368 +2024-11-22 15:32:32.585298: train_loss -0.7891 +2024-11-22 15:32:32.585529: val_loss -0.7457 +2024-11-22 15:32:32.585603: Pseudo dice [0.8433] +2024-11-22 15:32:32.585685: Epoch time: 18.22 s +2024-11-22 15:32:33.471072: +2024-11-22 15:32:33.471290: Epoch 5366 +2024-11-22 15:32:33.471402: Current learning rate: 0.00368 +2024-11-22 15:32:51.401304: train_loss -0.803 +2024-11-22 15:32:51.401520: val_loss -0.7903 +2024-11-22 15:32:51.401596: Pseudo dice [0.8405] +2024-11-22 15:32:51.401674: Epoch time: 17.93 s +2024-11-22 15:32:52.292806: +2024-11-22 15:32:52.293290: Epoch 5367 +2024-11-22 15:32:52.293467: Current learning rate: 0.00368 +2024-11-22 15:33:11.530982: train_loss -0.8085 +2024-11-22 15:33:11.531241: val_loss -0.7556 +2024-11-22 15:33:11.531317: Pseudo dice [0.8295] +2024-11-22 15:33:11.531393: Epoch time: 19.24 s +2024-11-22 15:33:12.423029: +2024-11-22 15:33:12.423508: Epoch 5368 +2024-11-22 15:33:12.423650: Current learning rate: 0.00368 +2024-11-22 15:33:31.022753: train_loss -0.8015 +2024-11-22 15:33:31.022968: val_loss -0.7582 +2024-11-22 15:33:31.023048: Pseudo dice [0.8579] +2024-11-22 15:33:31.023124: Epoch time: 18.6 s +2024-11-22 15:33:31.906536: +2024-11-22 15:33:31.906934: Epoch 5369 +2024-11-22 15:33:31.907068: Current learning rate: 0.00368 +2024-11-22 15:33:50.106533: train_loss -0.7999 +2024-11-22 15:33:50.106741: val_loss -0.7743 +2024-11-22 15:33:50.106816: Pseudo dice [0.8559] +2024-11-22 15:33:50.106890: Epoch time: 18.2 s +2024-11-22 15:33:50.998576: +2024-11-22 15:33:50.999021: Epoch 5370 +2024-11-22 15:33:50.999159: Current learning rate: 0.00367 +2024-11-22 15:34:08.647259: train_loss -0.7966 +2024-11-22 15:34:08.647485: val_loss -0.7918 +2024-11-22 15:34:08.647562: Pseudo dice [0.8656] +2024-11-22 15:34:08.647644: Epoch time: 17.65 s +2024-11-22 15:34:09.547380: +2024-11-22 15:34:09.547805: Epoch 5371 +2024-11-22 15:34:09.547939: Current learning rate: 0.00367 +2024-11-22 15:34:27.646341: train_loss -0.7902 +2024-11-22 15:34:27.647574: val_loss -0.7819 +2024-11-22 15:34:27.647659: Pseudo dice [0.8347] +2024-11-22 15:34:27.647738: Epoch time: 18.1 s +2024-11-22 15:34:28.538306: +2024-11-22 15:34:28.538761: Epoch 5372 +2024-11-22 15:34:28.538898: Current learning rate: 0.00367 +2024-11-22 15:34:47.013456: train_loss -0.7878 +2024-11-22 15:34:47.013678: val_loss -0.7521 +2024-11-22 15:34:47.013752: Pseudo dice [0.8521] +2024-11-22 15:34:47.013829: Epoch time: 18.48 s +2024-11-22 15:34:47.912242: +2024-11-22 15:34:47.912663: Epoch 5373 +2024-11-22 15:34:47.912796: Current learning rate: 0.00367 +2024-11-22 15:35:05.182824: train_loss -0.798 +2024-11-22 15:35:05.183058: val_loss -0.7692 +2024-11-22 15:35:05.183136: Pseudo dice [0.8543] +2024-11-22 15:35:05.183215: Epoch time: 17.27 s +2024-11-22 15:35:06.184496: +2024-11-22 15:35:06.184916: Epoch 5374 +2024-11-22 15:35:06.185059: Current learning rate: 0.00367 +2024-11-22 15:35:24.577829: train_loss -0.7955 +2024-11-22 15:35:24.578074: val_loss -0.7546 +2024-11-22 15:35:24.578455: Pseudo dice [0.8507] +2024-11-22 15:35:24.578554: Epoch time: 18.39 s +2024-11-22 15:35:25.464384: +2024-11-22 15:35:25.464887: Epoch 5375 +2024-11-22 15:35:25.465034: Current learning rate: 0.00367 +2024-11-22 15:35:43.726004: train_loss -0.7934 +2024-11-22 15:35:43.726224: val_loss -0.7723 +2024-11-22 15:35:43.726299: Pseudo dice [0.8421] +2024-11-22 15:35:43.726379: Epoch time: 18.26 s +2024-11-22 15:35:44.625786: +2024-11-22 15:35:44.626099: Epoch 5376 +2024-11-22 15:35:44.626229: Current learning rate: 0.00367 +2024-11-22 15:36:02.496232: train_loss -0.81 +2024-11-22 15:36:02.497081: val_loss -0.7675 +2024-11-22 15:36:02.497158: Pseudo dice [0.8567] +2024-11-22 15:36:02.497241: Epoch time: 17.87 s +2024-11-22 15:36:03.763472: +2024-11-22 15:36:03.763700: Epoch 5377 +2024-11-22 15:36:03.763819: Current learning rate: 0.00367 +2024-11-22 15:36:21.559916: train_loss -0.8037 +2024-11-22 15:36:21.560173: val_loss -0.7997 +2024-11-22 15:36:21.560247: Pseudo dice [0.8596] +2024-11-22 15:36:21.560329: Epoch time: 17.8 s +2024-11-22 15:36:22.446938: +2024-11-22 15:36:22.447169: Epoch 5378 +2024-11-22 15:36:22.447276: Current learning rate: 0.00366 +2024-11-22 15:36:41.120481: train_loss -0.8 +2024-11-22 15:36:41.120698: val_loss -0.7701 +2024-11-22 15:36:41.120775: Pseudo dice [0.8408] +2024-11-22 15:36:41.120850: Epoch time: 18.67 s +2024-11-22 15:36:42.011102: +2024-11-22 15:36:42.011390: Epoch 5379 +2024-11-22 15:36:42.011500: Current learning rate: 0.00366 +2024-11-22 15:37:00.493925: train_loss -0.7912 +2024-11-22 15:37:00.494157: val_loss -0.7635 +2024-11-22 15:37:00.494234: Pseudo dice [0.8313] +2024-11-22 15:37:00.494311: Epoch time: 18.48 s +2024-11-22 15:37:01.523529: +2024-11-22 15:37:01.523756: Epoch 5380 +2024-11-22 15:37:01.523864: Current learning rate: 0.00366 +2024-11-22 15:37:20.561923: train_loss -0.795 +2024-11-22 15:37:20.562148: val_loss -0.762 +2024-11-22 15:37:20.562224: Pseudo dice [0.8405] +2024-11-22 15:37:20.562304: Epoch time: 19.04 s +2024-11-22 15:37:21.453184: +2024-11-22 15:37:21.453470: Epoch 5381 +2024-11-22 15:37:21.453579: Current learning rate: 0.00366 +2024-11-22 15:37:40.204466: train_loss -0.8028 +2024-11-22 15:37:40.209889: val_loss -0.7685 +2024-11-22 15:37:40.210003: Pseudo dice [0.8295] +2024-11-22 15:37:40.210088: Epoch time: 18.75 s +2024-11-22 15:37:41.271192: +2024-11-22 15:37:41.271407: Epoch 5382 +2024-11-22 15:37:41.271516: Current learning rate: 0.00366 +2024-11-22 15:37:59.766499: train_loss -0.7989 +2024-11-22 15:37:59.766711: val_loss -0.7813 +2024-11-22 15:37:59.766786: Pseudo dice [0.8614] +2024-11-22 15:37:59.766861: Epoch time: 18.5 s +2024-11-22 15:38:00.643914: +2024-11-22 15:38:00.644118: Epoch 5383 +2024-11-22 15:38:00.644226: Current learning rate: 0.00366 +2024-11-22 15:38:18.311252: train_loss -0.8064 +2024-11-22 15:38:18.313645: val_loss -0.7773 +2024-11-22 15:38:18.313735: Pseudo dice [0.8371] +2024-11-22 15:38:18.313814: Epoch time: 17.67 s +2024-11-22 15:38:19.374187: +2024-11-22 15:38:19.374400: Epoch 5384 +2024-11-22 15:38:19.374509: Current learning rate: 0.00366 +2024-11-22 15:38:37.965098: train_loss -0.8075 +2024-11-22 15:38:37.965350: val_loss -0.777 +2024-11-22 15:38:37.965425: Pseudo dice [0.855] +2024-11-22 15:38:37.965511: Epoch time: 18.59 s +2024-11-22 15:38:38.856805: +2024-11-22 15:38:38.857038: Epoch 5385 +2024-11-22 15:38:38.857165: Current learning rate: 0.00366 +2024-11-22 15:38:57.709532: train_loss -0.8061 +2024-11-22 15:38:57.711917: val_loss -0.7877 +2024-11-22 15:38:57.712044: Pseudo dice [0.8475] +2024-11-22 15:38:57.712123: Epoch time: 18.85 s +2024-11-22 15:38:58.689079: +2024-11-22 15:38:58.689300: Epoch 5386 +2024-11-22 15:38:58.689407: Current learning rate: 0.00365 +2024-11-22 15:39:16.812087: train_loss -0.7927 +2024-11-22 15:39:16.812300: val_loss -0.7782 +2024-11-22 15:39:16.812374: Pseudo dice [0.8568] +2024-11-22 15:39:16.812448: Epoch time: 18.12 s +2024-11-22 15:39:17.732964: +2024-11-22 15:39:17.733207: Epoch 5387 +2024-11-22 15:39:17.733317: Current learning rate: 0.00365 +2024-11-22 15:39:34.780288: train_loss -0.8018 +2024-11-22 15:39:34.780506: val_loss -0.7698 +2024-11-22 15:39:34.780585: Pseudo dice [0.829] +2024-11-22 15:39:34.780664: Epoch time: 17.05 s +2024-11-22 15:39:35.682120: +2024-11-22 15:39:35.682370: Epoch 5388 +2024-11-22 15:39:35.682519: Current learning rate: 0.00365 +2024-11-22 15:39:54.079351: train_loss -0.7883 +2024-11-22 15:39:54.079576: val_loss -0.769 +2024-11-22 15:39:54.079651: Pseudo dice [0.8758] +2024-11-22 15:39:54.079728: Epoch time: 18.4 s +2024-11-22 15:39:55.368979: +2024-11-22 15:39:55.369276: Epoch 5389 +2024-11-22 15:39:55.369392: Current learning rate: 0.00365 +2024-11-22 15:40:13.180243: train_loss -0.7996 +2024-11-22 15:40:13.180475: val_loss -0.786 +2024-11-22 15:40:13.180552: Pseudo dice [0.8487] +2024-11-22 15:40:13.180716: Epoch time: 17.81 s +2024-11-22 15:40:14.058828: +2024-11-22 15:40:14.059064: Epoch 5390 +2024-11-22 15:40:14.059176: Current learning rate: 0.00365 +2024-11-22 15:40:32.121549: train_loss -0.797 +2024-11-22 15:40:32.121767: val_loss -0.7854 +2024-11-22 15:40:32.121845: Pseudo dice [0.8623] +2024-11-22 15:40:32.121921: Epoch time: 18.06 s +2024-11-22 15:40:33.004227: +2024-11-22 15:40:33.004476: Epoch 5391 +2024-11-22 15:40:33.004590: Current learning rate: 0.00365 +2024-11-22 15:40:51.419844: train_loss -0.7988 +2024-11-22 15:40:51.420095: val_loss -0.7656 +2024-11-22 15:40:51.420170: Pseudo dice [0.8515] +2024-11-22 15:40:51.420330: Epoch time: 18.42 s +2024-11-22 15:40:52.316385: +2024-11-22 15:40:52.316609: Epoch 5392 +2024-11-22 15:40:52.316716: Current learning rate: 0.00365 +2024-11-22 15:41:10.262945: train_loss -0.8011 +2024-11-22 15:41:10.263161: val_loss -0.7809 +2024-11-22 15:41:10.263235: Pseudo dice [0.8548] +2024-11-22 15:41:10.263309: Epoch time: 17.95 s +2024-11-22 15:41:11.149387: +2024-11-22 15:41:11.149583: Epoch 5393 +2024-11-22 15:41:11.149690: Current learning rate: 0.00365 +2024-11-22 15:41:30.743206: train_loss -0.7999 +2024-11-22 15:41:30.743452: val_loss -0.7539 +2024-11-22 15:41:30.743530: Pseudo dice [0.8575] +2024-11-22 15:41:30.743605: Epoch time: 19.59 s +2024-11-22 15:41:31.622186: +2024-11-22 15:41:31.622412: Epoch 5394 +2024-11-22 15:41:31.622521: Current learning rate: 0.00364 +2024-11-22 15:41:50.626999: train_loss -0.7971 +2024-11-22 15:41:50.627216: val_loss -0.806 +2024-11-22 15:41:50.627289: Pseudo dice [0.864] +2024-11-22 15:41:50.627364: Epoch time: 19.01 s +2024-11-22 15:41:51.515452: +2024-11-22 15:41:51.515651: Epoch 5395 +2024-11-22 15:41:51.515758: Current learning rate: 0.00364 +2024-11-22 15:42:10.450048: train_loss -0.7928 +2024-11-22 15:42:10.450294: val_loss -0.769 +2024-11-22 15:42:10.450370: Pseudo dice [0.8594] +2024-11-22 15:42:10.450455: Epoch time: 18.94 s +2024-11-22 15:42:11.343642: +2024-11-22 15:42:11.343938: Epoch 5396 +2024-11-22 15:42:11.344058: Current learning rate: 0.00364 +2024-11-22 15:42:30.084406: train_loss -0.8012 +2024-11-22 15:42:30.084662: val_loss -0.7577 +2024-11-22 15:42:30.084738: Pseudo dice [0.8464] +2024-11-22 15:42:30.084811: Epoch time: 18.74 s +2024-11-22 15:42:30.967196: +2024-11-22 15:42:30.967498: Epoch 5397 +2024-11-22 15:42:30.967612: Current learning rate: 0.00364 +2024-11-22 15:42:50.291838: train_loss -0.788 +2024-11-22 15:42:50.292072: val_loss -0.7622 +2024-11-22 15:42:50.292150: Pseudo dice [0.8566] +2024-11-22 15:42:50.292228: Epoch time: 19.33 s +2024-11-22 15:42:51.182034: +2024-11-22 15:42:51.182326: Epoch 5398 +2024-11-22 15:42:51.182439: Current learning rate: 0.00364 +2024-11-22 15:43:09.076847: train_loss -0.7912 +2024-11-22 15:43:09.077078: val_loss -0.7722 +2024-11-22 15:43:09.077155: Pseudo dice [0.8439] +2024-11-22 15:43:09.077231: Epoch time: 17.9 s +2024-11-22 15:43:10.086782: +2024-11-22 15:43:10.086998: Epoch 5399 +2024-11-22 15:43:10.087114: Current learning rate: 0.00364 +2024-11-22 15:43:28.620277: train_loss -0.8004 +2024-11-22 15:43:28.625729: val_loss -0.7821 +2024-11-22 15:43:28.625850: Pseudo dice [0.8444] +2024-11-22 15:43:28.625952: Epoch time: 18.53 s +2024-11-22 15:43:29.845092: +2024-11-22 15:43:29.845319: Epoch 5400 +2024-11-22 15:43:29.845435: Current learning rate: 0.00364 +2024-11-22 15:43:48.453713: train_loss -0.8009 +2024-11-22 15:43:48.454466: val_loss -0.773 +2024-11-22 15:43:48.454582: Pseudo dice [0.8419] +2024-11-22 15:43:48.454663: Epoch time: 18.61 s +2024-11-22 15:43:49.342724: +2024-11-22 15:43:49.342952: Epoch 5401 +2024-11-22 15:43:49.343082: Current learning rate: 0.00364 +2024-11-22 15:44:07.683308: train_loss -0.7933 +2024-11-22 15:44:07.683548: val_loss -0.8031 +2024-11-22 15:44:07.683628: Pseudo dice [0.8595] +2024-11-22 15:44:07.683707: Epoch time: 18.34 s +2024-11-22 15:44:08.560609: +2024-11-22 15:44:08.560827: Epoch 5402 +2024-11-22 15:44:08.560931: Current learning rate: 0.00363 +2024-11-22 15:44:26.621320: train_loss -0.8007 +2024-11-22 15:44:26.621563: val_loss -0.7761 +2024-11-22 15:44:26.621638: Pseudo dice [0.8504] +2024-11-22 15:44:26.621723: Epoch time: 18.06 s +2024-11-22 15:44:27.513698: +2024-11-22 15:44:27.513942: Epoch 5403 +2024-11-22 15:44:27.514056: Current learning rate: 0.00363 +2024-11-22 15:44:45.247256: train_loss -0.8108 +2024-11-22 15:44:45.247478: val_loss -0.7694 +2024-11-22 15:44:45.247553: Pseudo dice [0.8692] +2024-11-22 15:44:45.247626: Epoch time: 17.73 s +2024-11-22 15:44:46.244458: +2024-11-22 15:44:46.244653: Epoch 5404 +2024-11-22 15:44:46.244765: Current learning rate: 0.00363 +2024-11-22 15:45:04.942852: train_loss -0.7987 +2024-11-22 15:45:04.943077: val_loss -0.7632 +2024-11-22 15:45:04.943152: Pseudo dice [0.8558] +2024-11-22 15:45:04.943230: Epoch time: 18.7 s +2024-11-22 15:45:05.834052: +2024-11-22 15:45:05.834339: Epoch 5405 +2024-11-22 15:45:05.834453: Current learning rate: 0.00363 +2024-11-22 15:45:23.447469: train_loss -0.7973 +2024-11-22 15:45:23.447718: val_loss -0.7838 +2024-11-22 15:45:23.447798: Pseudo dice [0.8535] +2024-11-22 15:45:23.447874: Epoch time: 17.61 s +2024-11-22 15:45:24.369735: +2024-11-22 15:45:24.369961: Epoch 5406 +2024-11-22 15:45:24.370086: Current learning rate: 0.00363 +2024-11-22 15:45:43.254857: train_loss -0.7984 +2024-11-22 15:45:43.255156: val_loss -0.7774 +2024-11-22 15:45:43.255251: Pseudo dice [0.8474] +2024-11-22 15:45:43.255338: Epoch time: 18.89 s +2024-11-22 15:45:44.138473: +2024-11-22 15:45:44.138672: Epoch 5407 +2024-11-22 15:45:44.138778: Current learning rate: 0.00363 +2024-11-22 15:46:02.695908: train_loss -0.7967 +2024-11-22 15:46:02.696121: val_loss -0.7644 +2024-11-22 15:46:02.696195: Pseudo dice [0.8541] +2024-11-22 15:46:02.696267: Epoch time: 18.56 s +2024-11-22 15:46:03.575210: +2024-11-22 15:46:03.575432: Epoch 5408 +2024-11-22 15:46:03.575542: Current learning rate: 0.00363 +2024-11-22 15:46:21.697675: train_loss -0.7962 +2024-11-22 15:46:21.697898: val_loss -0.7844 +2024-11-22 15:46:21.697974: Pseudo dice [0.8604] +2024-11-22 15:46:21.698056: Epoch time: 18.12 s +2024-11-22 15:46:22.748023: +2024-11-22 15:46:22.748238: Epoch 5409 +2024-11-22 15:46:22.748350: Current learning rate: 0.00363 +2024-11-22 15:46:41.317294: train_loss -0.7883 +2024-11-22 15:46:41.317514: val_loss -0.7398 +2024-11-22 15:46:41.317594: Pseudo dice [0.8438] +2024-11-22 15:46:41.317671: Epoch time: 18.57 s +2024-11-22 15:46:42.207736: +2024-11-22 15:46:42.207956: Epoch 5410 +2024-11-22 15:46:42.208067: Current learning rate: 0.00362 +2024-11-22 15:47:00.405731: train_loss -0.7888 +2024-11-22 15:47:00.405971: val_loss -0.7612 +2024-11-22 15:47:00.406052: Pseudo dice [0.8439] +2024-11-22 15:47:00.406136: Epoch time: 18.2 s +2024-11-22 15:47:01.304444: +2024-11-22 15:47:01.304681: Epoch 5411 +2024-11-22 15:47:01.304795: Current learning rate: 0.00362 +2024-11-22 15:47:19.132261: train_loss -0.7919 +2024-11-22 15:47:19.132492: val_loss -0.7725 +2024-11-22 15:47:19.132571: Pseudo dice [0.8418] +2024-11-22 15:47:19.132666: Epoch time: 17.83 s +2024-11-22 15:47:20.406537: +2024-11-22 15:47:20.406754: Epoch 5412 +2024-11-22 15:47:20.406861: Current learning rate: 0.00362 +2024-11-22 15:47:38.481745: train_loss -0.8013 +2024-11-22 15:47:38.481980: val_loss -0.7762 +2024-11-22 15:47:38.482078: Pseudo dice [0.8585] +2024-11-22 15:47:38.482226: Epoch time: 18.08 s +2024-11-22 15:47:39.371358: +2024-11-22 15:47:39.371589: Epoch 5413 +2024-11-22 15:47:39.371710: Current learning rate: 0.00362 +2024-11-22 15:47:57.967642: train_loss -0.796 +2024-11-22 15:47:57.967857: val_loss -0.7548 +2024-11-22 15:47:57.967938: Pseudo dice [0.8493] +2024-11-22 15:47:57.968028: Epoch time: 18.6 s +2024-11-22 15:47:58.854174: +2024-11-22 15:47:58.854393: Epoch 5414 +2024-11-22 15:47:58.854501: Current learning rate: 0.00362 +2024-11-22 15:48:16.830101: train_loss -0.7965 +2024-11-22 15:48:16.830344: val_loss -0.7868 +2024-11-22 15:48:16.830422: Pseudo dice [0.853] +2024-11-22 15:48:16.830503: Epoch time: 17.98 s +2024-11-22 15:48:17.717156: +2024-11-22 15:48:17.717383: Epoch 5415 +2024-11-22 15:48:17.717493: Current learning rate: 0.00362 +2024-11-22 15:48:36.818580: train_loss -0.8 +2024-11-22 15:48:36.818792: val_loss -0.7605 +2024-11-22 15:48:36.818868: Pseudo dice [0.8461] +2024-11-22 15:48:36.818944: Epoch time: 19.1 s +2024-11-22 15:48:37.712486: +2024-11-22 15:48:37.712739: Epoch 5416 +2024-11-22 15:48:37.712850: Current learning rate: 0.00362 +2024-11-22 15:48:56.178811: train_loss -0.8049 +2024-11-22 15:48:56.179083: val_loss -0.7694 +2024-11-22 15:48:56.179199: Pseudo dice [0.8484] +2024-11-22 15:48:56.179281: Epoch time: 18.47 s +2024-11-22 15:48:57.167668: +2024-11-22 15:48:57.167942: Epoch 5417 +2024-11-22 15:48:57.168054: Current learning rate: 0.00362 +2024-11-22 15:49:15.404110: train_loss -0.8065 +2024-11-22 15:49:15.404364: val_loss -0.7686 +2024-11-22 15:49:15.404445: Pseudo dice [0.855] +2024-11-22 15:49:15.404522: Epoch time: 18.24 s +2024-11-22 15:49:16.292529: +2024-11-22 15:49:16.292733: Epoch 5418 +2024-11-22 15:49:16.292840: Current learning rate: 0.00361 +2024-11-22 15:49:34.098146: train_loss -0.8036 +2024-11-22 15:49:34.098385: val_loss -0.7608 +2024-11-22 15:49:34.098462: Pseudo dice [0.8424] +2024-11-22 15:49:34.098543: Epoch time: 17.81 s +2024-11-22 15:49:34.984628: +2024-11-22 15:49:34.984912: Epoch 5419 +2024-11-22 15:49:34.985051: Current learning rate: 0.00361 +2024-11-22 15:49:53.622229: train_loss -0.797 +2024-11-22 15:49:53.622450: val_loss -0.7755 +2024-11-22 15:49:53.622529: Pseudo dice [0.8553] +2024-11-22 15:49:53.622606: Epoch time: 18.64 s +2024-11-22 15:49:54.506231: +2024-11-22 15:49:54.506446: Epoch 5420 +2024-11-22 15:49:54.506557: Current learning rate: 0.00361 +2024-11-22 15:50:13.253910: train_loss -0.7989 +2024-11-22 15:50:13.254143: val_loss -0.7552 +2024-11-22 15:50:13.254219: Pseudo dice [0.8494] +2024-11-22 15:50:13.254295: Epoch time: 18.75 s +2024-11-22 15:50:14.195213: +2024-11-22 15:50:14.195426: Epoch 5421 +2024-11-22 15:50:14.195539: Current learning rate: 0.00361 +2024-11-22 15:50:32.834652: train_loss -0.8054 +2024-11-22 15:50:32.834877: val_loss -0.7969 +2024-11-22 15:50:32.834997: Pseudo dice [0.8521] +2024-11-22 15:50:32.835080: Epoch time: 18.64 s +2024-11-22 15:50:33.723240: +2024-11-22 15:50:33.723443: Epoch 5422 +2024-11-22 15:50:33.723557: Current learning rate: 0.00361 +2024-11-22 15:50:52.323881: train_loss -0.7997 +2024-11-22 15:50:52.324130: val_loss -0.7704 +2024-11-22 15:50:52.324234: Pseudo dice [0.8423] +2024-11-22 15:50:52.324369: Epoch time: 18.6 s +2024-11-22 15:50:53.212533: +2024-11-22 15:50:53.212740: Epoch 5423 +2024-11-22 15:50:53.212850: Current learning rate: 0.00361 +2024-11-22 15:51:11.883807: train_loss -0.7936 +2024-11-22 15:51:11.884055: val_loss -0.7602 +2024-11-22 15:51:11.884132: Pseudo dice [0.8379] +2024-11-22 15:51:11.884214: Epoch time: 18.67 s +2024-11-22 15:51:13.128781: +2024-11-22 15:51:13.129086: Epoch 5424 +2024-11-22 15:51:13.129198: Current learning rate: 0.00361 +2024-11-22 15:51:31.735927: train_loss -0.7963 +2024-11-22 15:51:31.736166: val_loss -0.7993 +2024-11-22 15:51:31.736250: Pseudo dice [0.8513] +2024-11-22 15:51:31.736326: Epoch time: 18.61 s +2024-11-22 15:51:32.622186: +2024-11-22 15:51:32.622407: Epoch 5425 +2024-11-22 15:51:32.622523: Current learning rate: 0.00361 +2024-11-22 15:51:50.218040: train_loss -0.8038 +2024-11-22 15:51:50.218287: val_loss -0.7682 +2024-11-22 15:51:50.218493: Pseudo dice [0.8515] +2024-11-22 15:51:50.218586: Epoch time: 17.6 s +2024-11-22 15:51:51.116290: +2024-11-22 15:51:51.116515: Epoch 5426 +2024-11-22 15:51:51.116645: Current learning rate: 0.0036 +2024-11-22 15:52:09.628335: train_loss -0.803 +2024-11-22 15:52:09.628891: val_loss -0.7915 +2024-11-22 15:52:09.628988: Pseudo dice [0.8591] +2024-11-22 15:52:09.629068: Epoch time: 18.51 s +2024-11-22 15:52:10.523481: +2024-11-22 15:52:10.523694: Epoch 5427 +2024-11-22 15:52:10.523810: Current learning rate: 0.0036 +2024-11-22 15:52:28.668527: train_loss -0.7982 +2024-11-22 15:52:28.668847: val_loss -0.7737 +2024-11-22 15:52:28.668933: Pseudo dice [0.8431] +2024-11-22 15:52:28.669019: Epoch time: 18.15 s +2024-11-22 15:52:29.556716: +2024-11-22 15:52:29.556959: Epoch 5428 +2024-11-22 15:52:29.557081: Current learning rate: 0.0036 +2024-11-22 15:52:47.790152: train_loss -0.8053 +2024-11-22 15:52:47.790370: val_loss -0.7842 +2024-11-22 15:52:47.790447: Pseudo dice [0.8652] +2024-11-22 15:52:47.790522: Epoch time: 18.23 s +2024-11-22 15:52:48.672028: +2024-11-22 15:52:48.672256: Epoch 5429 +2024-11-22 15:52:48.672367: Current learning rate: 0.0036 +2024-11-22 15:53:06.795230: train_loss -0.7987 +2024-11-22 15:53:06.795442: val_loss -0.7675 +2024-11-22 15:53:06.795523: Pseudo dice [0.8357] +2024-11-22 15:53:06.795604: Epoch time: 18.12 s +2024-11-22 15:53:07.686482: +2024-11-22 15:53:07.686709: Epoch 5430 +2024-11-22 15:53:07.686815: Current learning rate: 0.0036 +2024-11-22 15:53:26.321067: train_loss -0.7991 +2024-11-22 15:53:26.321276: val_loss -0.7944 +2024-11-22 15:53:26.321350: Pseudo dice [0.8426] +2024-11-22 15:53:26.321424: Epoch time: 18.64 s +2024-11-22 15:53:27.217154: +2024-11-22 15:53:27.217456: Epoch 5431 +2024-11-22 15:53:27.217571: Current learning rate: 0.0036 +2024-11-22 15:53:46.554163: train_loss -0.7816 +2024-11-22 15:53:46.554390: val_loss -0.7442 +2024-11-22 15:53:46.554469: Pseudo dice [0.8315] +2024-11-22 15:53:46.554548: Epoch time: 19.34 s +2024-11-22 15:53:47.441698: +2024-11-22 15:53:47.441993: Epoch 5432 +2024-11-22 15:53:47.442107: Current learning rate: 0.0036 +2024-11-22 15:54:06.935834: train_loss -0.7878 +2024-11-22 15:54:06.936072: val_loss -0.7413 +2024-11-22 15:54:06.936148: Pseudo dice [0.8278] +2024-11-22 15:54:06.936244: Epoch time: 19.49 s +2024-11-22 15:54:07.820959: +2024-11-22 15:54:07.821175: Epoch 5433 +2024-11-22 15:54:07.821297: Current learning rate: 0.0036 +2024-11-22 15:54:27.167749: train_loss -0.7969 +2024-11-22 15:54:27.167959: val_loss -0.7445 +2024-11-22 15:54:27.168042: Pseudo dice [0.832] +2024-11-22 15:54:27.168118: Epoch time: 19.35 s +2024-11-22 15:54:28.052708: +2024-11-22 15:54:28.052918: Epoch 5434 +2024-11-22 15:54:28.053038: Current learning rate: 0.00359 +2024-11-22 15:54:46.707767: train_loss -0.7901 +2024-11-22 15:54:46.708008: val_loss -0.773 +2024-11-22 15:54:46.708086: Pseudo dice [0.8505] +2024-11-22 15:54:46.708167: Epoch time: 18.66 s +2024-11-22 15:54:47.592911: +2024-11-22 15:54:47.593126: Epoch 5435 +2024-11-22 15:54:47.593237: Current learning rate: 0.00359 +2024-11-22 15:55:05.936504: train_loss -0.7986 +2024-11-22 15:55:05.936728: val_loss -0.7702 +2024-11-22 15:55:05.936808: Pseudo dice [0.8508] +2024-11-22 15:55:05.936960: Epoch time: 18.34 s +2024-11-22 15:55:07.230111: +2024-11-22 15:55:07.230381: Epoch 5436 +2024-11-22 15:55:07.230495: Current learning rate: 0.00359 +2024-11-22 15:55:27.036381: train_loss -0.7744 +2024-11-22 15:55:27.036603: val_loss -0.7528 +2024-11-22 15:55:27.036681: Pseudo dice [0.8391] +2024-11-22 15:55:27.036760: Epoch time: 19.81 s +2024-11-22 15:55:27.932746: +2024-11-22 15:55:27.932996: Epoch 5437 +2024-11-22 15:55:27.933120: Current learning rate: 0.00359 +2024-11-22 15:55:46.338247: train_loss -0.7892 +2024-11-22 15:55:46.338467: val_loss -0.74 +2024-11-22 15:55:46.338548: Pseudo dice [0.8435] +2024-11-22 15:55:46.338625: Epoch time: 18.41 s +2024-11-22 15:55:47.257464: +2024-11-22 15:55:47.257689: Epoch 5438 +2024-11-22 15:55:47.257801: Current learning rate: 0.00359 +2024-11-22 15:56:05.904077: train_loss -0.7886 +2024-11-22 15:56:05.904287: val_loss -0.7714 +2024-11-22 15:56:05.904361: Pseudo dice [0.857] +2024-11-22 15:56:05.904432: Epoch time: 18.65 s +2024-11-22 15:56:06.945028: +2024-11-22 15:56:06.945374: Epoch 5439 +2024-11-22 15:56:06.945481: Current learning rate: 0.00359 +2024-11-22 15:56:25.138484: train_loss -0.7943 +2024-11-22 15:56:25.138711: val_loss -0.7824 +2024-11-22 15:56:25.138787: Pseudo dice [0.8509] +2024-11-22 15:56:25.138866: Epoch time: 18.19 s +2024-11-22 15:56:26.028310: +2024-11-22 15:56:26.028520: Epoch 5440 +2024-11-22 15:56:26.028637: Current learning rate: 0.00359 +2024-11-22 15:56:44.525152: train_loss -0.7933 +2024-11-22 15:56:44.525489: val_loss -0.7492 +2024-11-22 15:56:44.525570: Pseudo dice [0.8419] +2024-11-22 15:56:44.525654: Epoch time: 18.5 s +2024-11-22 15:56:45.426624: +2024-11-22 15:56:45.426845: Epoch 5441 +2024-11-22 15:56:45.426951: Current learning rate: 0.00358 +2024-11-22 15:57:04.539750: train_loss -0.7966 +2024-11-22 15:57:04.545176: val_loss -0.7492 +2024-11-22 15:57:04.545262: Pseudo dice [0.8318] +2024-11-22 15:57:04.545363: Epoch time: 19.11 s +2024-11-22 15:57:05.514907: +2024-11-22 15:57:05.515139: Epoch 5442 +2024-11-22 15:57:05.515254: Current learning rate: 0.00358 +2024-11-22 15:57:24.045640: train_loss -0.7941 +2024-11-22 15:57:24.045887: val_loss -0.7749 +2024-11-22 15:57:24.045970: Pseudo dice [0.8515] +2024-11-22 15:57:24.046055: Epoch time: 18.53 s +2024-11-22 15:57:24.933843: +2024-11-22 15:57:24.934098: Epoch 5443 +2024-11-22 15:57:24.934211: Current learning rate: 0.00358 +2024-11-22 15:57:43.767802: train_loss -0.79 +2024-11-22 15:57:43.768033: val_loss -0.7652 +2024-11-22 15:57:43.768109: Pseudo dice [0.8265] +2024-11-22 15:57:43.768190: Epoch time: 18.83 s +2024-11-22 15:57:44.712200: +2024-11-22 15:57:44.712393: Epoch 5444 +2024-11-22 15:57:44.712505: Current learning rate: 0.00358 +2024-11-22 15:58:04.153921: train_loss -0.7961 +2024-11-22 15:58:04.154477: val_loss -0.7613 +2024-11-22 15:58:04.154556: Pseudo dice [0.8517] +2024-11-22 15:58:04.154641: Epoch time: 19.44 s +2024-11-22 15:58:05.041718: +2024-11-22 15:58:05.041920: Epoch 5445 +2024-11-22 15:58:05.042038: Current learning rate: 0.00358 +2024-11-22 15:58:23.996456: train_loss -0.7971 +2024-11-22 15:58:23.996684: val_loss -0.7796 +2024-11-22 15:58:23.996758: Pseudo dice [0.8459] +2024-11-22 15:58:23.996833: Epoch time: 18.96 s +2024-11-22 15:58:24.880330: +2024-11-22 15:58:24.880553: Epoch 5446 +2024-11-22 15:58:24.880666: Current learning rate: 0.00358 +2024-11-22 15:58:42.863925: train_loss -0.8045 +2024-11-22 15:58:42.864146: val_loss -0.7581 +2024-11-22 15:58:42.864222: Pseudo dice [0.8514] +2024-11-22 15:58:42.864304: Epoch time: 17.98 s +2024-11-22 15:58:43.737349: +2024-11-22 15:58:43.737538: Epoch 5447 +2024-11-22 15:58:43.737650: Current learning rate: 0.00358 +2024-11-22 15:59:02.252424: train_loss -0.8 +2024-11-22 15:59:02.252697: val_loss -0.7779 +2024-11-22 15:59:02.252773: Pseudo dice [0.851] +2024-11-22 15:59:02.252850: Epoch time: 18.52 s +2024-11-22 15:59:03.551965: +2024-11-22 15:59:03.552212: Epoch 5448 +2024-11-22 15:59:03.552321: Current learning rate: 0.00358 +2024-11-22 15:59:22.390957: train_loss -0.7961 +2024-11-22 15:59:22.391527: val_loss -0.7642 +2024-11-22 15:59:22.391625: Pseudo dice [0.8484] +2024-11-22 15:59:22.391705: Epoch time: 18.84 s +2024-11-22 15:59:23.279731: +2024-11-22 15:59:23.279932: Epoch 5449 +2024-11-22 15:59:23.280051: Current learning rate: 0.00357 +2024-11-22 15:59:40.609597: train_loss -0.795 +2024-11-22 15:59:40.609869: val_loss -0.7631 +2024-11-22 15:59:40.609944: Pseudo dice [0.8552] +2024-11-22 15:59:40.610024: Epoch time: 17.33 s +2024-11-22 15:59:41.797605: +2024-11-22 15:59:41.797931: Epoch 5450 +2024-11-22 15:59:41.798049: Current learning rate: 0.00357 +2024-11-22 16:00:00.952411: train_loss -0.8 +2024-11-22 16:00:00.952641: val_loss -0.7809 +2024-11-22 16:00:00.952715: Pseudo dice [0.8613] +2024-11-22 16:00:00.952791: Epoch time: 19.16 s +2024-11-22 16:00:01.877789: +2024-11-22 16:00:01.878014: Epoch 5451 +2024-11-22 16:00:01.878120: Current learning rate: 0.00357 +2024-11-22 16:00:20.231822: train_loss -0.7848 +2024-11-22 16:00:20.232117: val_loss -0.772 +2024-11-22 16:00:20.232197: Pseudo dice [0.8416] +2024-11-22 16:00:20.232280: Epoch time: 18.35 s +2024-11-22 16:00:21.124882: +2024-11-22 16:00:21.125100: Epoch 5452 +2024-11-22 16:00:21.125208: Current learning rate: 0.00357 +2024-11-22 16:00:39.384856: train_loss -0.79 +2024-11-22 16:00:39.385392: val_loss -0.7818 +2024-11-22 16:00:39.385476: Pseudo dice [0.844] +2024-11-22 16:00:39.385551: Epoch time: 18.26 s +2024-11-22 16:00:40.279840: +2024-11-22 16:00:40.280066: Epoch 5453 +2024-11-22 16:00:40.280181: Current learning rate: 0.00357 +2024-11-22 16:00:59.046076: train_loss -0.7953 +2024-11-22 16:00:59.046299: val_loss -0.7769 +2024-11-22 16:00:59.046384: Pseudo dice [0.8455] +2024-11-22 16:00:59.046461: Epoch time: 18.77 s +2024-11-22 16:00:59.937564: +2024-11-22 16:00:59.937803: Epoch 5454 +2024-11-22 16:00:59.937915: Current learning rate: 0.00357 +2024-11-22 16:01:19.042425: train_loss -0.7888 +2024-11-22 16:01:19.042656: val_loss -0.7736 +2024-11-22 16:01:19.042732: Pseudo dice [0.8519] +2024-11-22 16:01:19.042807: Epoch time: 19.11 s +2024-11-22 16:01:19.954949: +2024-11-22 16:01:19.955308: Epoch 5455 +2024-11-22 16:01:19.955420: Current learning rate: 0.00357 +2024-11-22 16:01:38.231408: train_loss -0.7979 +2024-11-22 16:01:38.231651: val_loss -0.7553 +2024-11-22 16:01:38.231726: Pseudo dice [0.8451] +2024-11-22 16:01:38.231834: Epoch time: 18.28 s +2024-11-22 16:01:39.114637: +2024-11-22 16:01:39.114861: Epoch 5456 +2024-11-22 16:01:39.114969: Current learning rate: 0.00357 +2024-11-22 16:01:57.769784: train_loss -0.7956 +2024-11-22 16:01:57.770013: val_loss -0.7277 +2024-11-22 16:01:57.770089: Pseudo dice [0.8083] +2024-11-22 16:01:57.770167: Epoch time: 18.66 s +2024-11-22 16:01:58.653355: +2024-11-22 16:01:58.653614: Epoch 5457 +2024-11-22 16:01:58.653726: Current learning rate: 0.00356 +2024-11-22 16:02:16.785200: train_loss -0.7897 +2024-11-22 16:02:16.785429: val_loss -0.7902 +2024-11-22 16:02:16.785506: Pseudo dice [0.8628] +2024-11-22 16:02:16.785583: Epoch time: 18.13 s +2024-11-22 16:02:17.751046: +2024-11-22 16:02:17.751287: Epoch 5458 +2024-11-22 16:02:17.751399: Current learning rate: 0.00356 +2024-11-22 16:02:35.952697: train_loss -0.785 +2024-11-22 16:02:35.955048: val_loss -0.7416 +2024-11-22 16:02:35.955139: Pseudo dice [0.851] +2024-11-22 16:02:35.955224: Epoch time: 18.2 s +2024-11-22 16:02:36.907388: +2024-11-22 16:02:36.907615: Epoch 5459 +2024-11-22 16:02:36.907722: Current learning rate: 0.00356 +2024-11-22 16:02:55.864641: train_loss -0.7908 +2024-11-22 16:02:55.865149: val_loss -0.7721 +2024-11-22 16:02:55.865245: Pseudo dice [0.8647] +2024-11-22 16:02:55.865326: Epoch time: 18.96 s +2024-11-22 16:02:56.751101: +2024-11-22 16:02:56.751327: Epoch 5460 +2024-11-22 16:02:56.751436: Current learning rate: 0.00356 +2024-11-22 16:03:15.264988: train_loss -0.7963 +2024-11-22 16:03:15.270399: val_loss -0.7702 +2024-11-22 16:03:15.270479: Pseudo dice [0.8427] +2024-11-22 16:03:15.270556: Epoch time: 18.51 s +2024-11-22 16:03:16.243964: +2024-11-22 16:03:16.244370: Epoch 5461 +2024-11-22 16:03:16.244486: Current learning rate: 0.00356 +2024-11-22 16:03:34.384458: train_loss -0.7771 +2024-11-22 16:03:34.384676: val_loss -0.7675 +2024-11-22 16:03:34.384755: Pseudo dice [0.8543] +2024-11-22 16:03:34.384831: Epoch time: 18.14 s +2024-11-22 16:03:35.273359: +2024-11-22 16:03:35.273568: Epoch 5462 +2024-11-22 16:03:35.273693: Current learning rate: 0.00356 +2024-11-22 16:03:54.060784: train_loss -0.7759 +2024-11-22 16:03:54.061061: val_loss -0.7565 +2024-11-22 16:03:54.061141: Pseudo dice [0.8387] +2024-11-22 16:03:54.061232: Epoch time: 18.79 s +2024-11-22 16:03:54.951508: +2024-11-22 16:03:54.951729: Epoch 5463 +2024-11-22 16:03:54.951835: Current learning rate: 0.00356 +2024-11-22 16:04:13.399212: train_loss -0.7874 +2024-11-22 16:04:13.399464: val_loss -0.7598 +2024-11-22 16:04:13.399542: Pseudo dice [0.8414] +2024-11-22 16:04:13.399624: Epoch time: 18.45 s +2024-11-22 16:04:14.289887: +2024-11-22 16:04:14.290116: Epoch 5464 +2024-11-22 16:04:14.290230: Current learning rate: 0.00356 +2024-11-22 16:04:33.263612: train_loss -0.7853 +2024-11-22 16:04:33.263894: val_loss -0.7763 +2024-11-22 16:04:33.263996: Pseudo dice [0.8478] +2024-11-22 16:04:33.264072: Epoch time: 18.97 s +2024-11-22 16:04:34.186353: +2024-11-22 16:04:34.186581: Epoch 5465 +2024-11-22 16:04:34.186696: Current learning rate: 0.00355 +2024-11-22 16:04:52.874797: train_loss -0.7869 +2024-11-22 16:04:52.875104: val_loss -0.7672 +2024-11-22 16:04:52.875189: Pseudo dice [0.8381] +2024-11-22 16:04:52.875273: Epoch time: 18.69 s +2024-11-22 16:04:53.764144: +2024-11-22 16:04:53.764366: Epoch 5466 +2024-11-22 16:04:53.764478: Current learning rate: 0.00355 +2024-11-22 16:05:12.879891: train_loss -0.791 +2024-11-22 16:05:12.880123: val_loss -0.7389 +2024-11-22 16:05:12.880202: Pseudo dice [0.836] +2024-11-22 16:05:12.880282: Epoch time: 19.12 s +2024-11-22 16:05:13.865523: +2024-11-22 16:05:13.865736: Epoch 5467 +2024-11-22 16:05:13.865847: Current learning rate: 0.00355 +2024-11-22 16:05:33.354455: train_loss -0.788 +2024-11-22 16:05:33.354737: val_loss -0.7568 +2024-11-22 16:05:33.354820: Pseudo dice [0.8375] +2024-11-22 16:05:33.354909: Epoch time: 19.49 s +2024-11-22 16:05:34.254781: +2024-11-22 16:05:34.255105: Epoch 5468 +2024-11-22 16:05:34.255215: Current learning rate: 0.00355 +2024-11-22 16:05:52.034590: train_loss -0.778 +2024-11-22 16:05:52.034817: val_loss -0.7321 +2024-11-22 16:05:52.034895: Pseudo dice [0.8243] +2024-11-22 16:05:52.034971: Epoch time: 17.78 s +2024-11-22 16:05:52.999608: +2024-11-22 16:05:52.999815: Epoch 5469 +2024-11-22 16:05:52.999924: Current learning rate: 0.00355 +2024-11-22 16:06:10.281001: train_loss -0.7891 +2024-11-22 16:06:10.281212: val_loss -0.7855 +2024-11-22 16:06:10.281286: Pseudo dice [0.8539] +2024-11-22 16:06:10.281365: Epoch time: 17.28 s +2024-11-22 16:06:11.167121: +2024-11-22 16:06:11.167328: Epoch 5470 +2024-11-22 16:06:11.167443: Current learning rate: 0.00355 +2024-11-22 16:06:29.658436: train_loss -0.7986 +2024-11-22 16:06:29.660826: val_loss -0.7481 +2024-11-22 16:06:29.660918: Pseudo dice [0.8456] +2024-11-22 16:06:29.661010: Epoch time: 18.49 s +2024-11-22 16:06:30.972314: +2024-11-22 16:06:30.972528: Epoch 5471 +2024-11-22 16:06:30.972637: Current learning rate: 0.00355 +2024-11-22 16:06:48.568986: train_loss -0.8002 +2024-11-22 16:06:48.569248: val_loss -0.7503 +2024-11-22 16:06:48.569324: Pseudo dice [0.8372] +2024-11-22 16:06:48.569405: Epoch time: 17.6 s +2024-11-22 16:06:49.455185: +2024-11-22 16:06:49.455407: Epoch 5472 +2024-11-22 16:06:49.455526: Current learning rate: 0.00355 +2024-11-22 16:07:08.715855: train_loss -0.7943 +2024-11-22 16:07:08.716074: val_loss -0.7749 +2024-11-22 16:07:08.716149: Pseudo dice [0.8475] +2024-11-22 16:07:08.716224: Epoch time: 19.26 s +2024-11-22 16:07:09.596755: +2024-11-22 16:07:09.596997: Epoch 5473 +2024-11-22 16:07:09.597113: Current learning rate: 0.00354 +2024-11-22 16:07:29.138137: train_loss -0.7981 +2024-11-22 16:07:29.140543: val_loss -0.7545 +2024-11-22 16:07:29.140639: Pseudo dice [0.8486] +2024-11-22 16:07:29.140715: Epoch time: 19.54 s +2024-11-22 16:07:30.094367: +2024-11-22 16:07:30.094583: Epoch 5474 +2024-11-22 16:07:30.094697: Current learning rate: 0.00354 +2024-11-22 16:07:49.364903: train_loss -0.7959 +2024-11-22 16:07:49.365175: val_loss -0.7568 +2024-11-22 16:07:49.365258: Pseudo dice [0.8272] +2024-11-22 16:07:49.365345: Epoch time: 19.27 s +2024-11-22 16:07:50.281177: +2024-11-22 16:07:50.281413: Epoch 5475 +2024-11-22 16:07:50.281533: Current learning rate: 0.00354 +2024-11-22 16:08:07.909894: train_loss -0.7985 +2024-11-22 16:08:07.910137: val_loss -0.7861 +2024-11-22 16:08:07.910211: Pseudo dice [0.86] +2024-11-22 16:08:07.910285: Epoch time: 17.63 s +2024-11-22 16:08:08.826829: +2024-11-22 16:08:08.827061: Epoch 5476 +2024-11-22 16:08:08.827175: Current learning rate: 0.00354 +2024-11-22 16:08:28.106834: train_loss -0.7913 +2024-11-22 16:08:28.107052: val_loss -0.7775 +2024-11-22 16:08:28.107128: Pseudo dice [0.8549] +2024-11-22 16:08:28.107204: Epoch time: 19.28 s +2024-11-22 16:08:28.991076: +2024-11-22 16:08:28.991403: Epoch 5477 +2024-11-22 16:08:28.991516: Current learning rate: 0.00354 +2024-11-22 16:08:47.825989: train_loss -0.7955 +2024-11-22 16:08:47.826230: val_loss -0.7667 +2024-11-22 16:08:47.826305: Pseudo dice [0.8498] +2024-11-22 16:08:47.826380: Epoch time: 18.83 s +2024-11-22 16:08:48.707728: +2024-11-22 16:08:48.707923: Epoch 5478 +2024-11-22 16:08:48.708032: Current learning rate: 0.00354 +2024-11-22 16:09:06.546192: train_loss -0.8009 +2024-11-22 16:09:06.546719: val_loss -0.7838 +2024-11-22 16:09:06.546807: Pseudo dice [0.8559] +2024-11-22 16:09:06.546891: Epoch time: 17.84 s +2024-11-22 16:09:07.431397: +2024-11-22 16:09:07.431661: Epoch 5479 +2024-11-22 16:09:07.431786: Current learning rate: 0.00354 +2024-11-22 16:09:24.287930: train_loss -0.8038 +2024-11-22 16:09:24.288156: val_loss -0.7761 +2024-11-22 16:09:24.288232: Pseudo dice [0.8368] +2024-11-22 16:09:24.288311: Epoch time: 16.86 s +2024-11-22 16:09:25.169181: +2024-11-22 16:09:25.169384: Epoch 5480 +2024-11-22 16:09:25.169497: Current learning rate: 0.00354 +2024-11-22 16:09:44.977800: train_loss -0.7965 +2024-11-22 16:09:44.978038: val_loss -0.7944 +2024-11-22 16:09:44.978112: Pseudo dice [0.8519] +2024-11-22 16:09:44.978188: Epoch time: 19.81 s +2024-11-22 16:09:45.945368: +2024-11-22 16:09:45.945587: Epoch 5481 +2024-11-22 16:09:45.945694: Current learning rate: 0.00353 +2024-11-22 16:10:03.690118: train_loss -0.8009 +2024-11-22 16:10:03.690335: val_loss -0.7766 +2024-11-22 16:10:03.690409: Pseudo dice [0.8352] +2024-11-22 16:10:03.690490: Epoch time: 17.75 s +2024-11-22 16:10:04.575911: +2024-11-22 16:10:04.576134: Epoch 5482 +2024-11-22 16:10:04.576243: Current learning rate: 0.00353 +2024-11-22 16:10:23.906671: train_loss -0.7944 +2024-11-22 16:10:23.906977: val_loss -0.7684 +2024-11-22 16:10:23.907059: Pseudo dice [0.837] +2024-11-22 16:10:23.907140: Epoch time: 19.33 s +2024-11-22 16:10:25.197329: +2024-11-22 16:10:25.197566: Epoch 5483 +2024-11-22 16:10:25.197678: Current learning rate: 0.00353 +2024-11-22 16:10:43.263841: train_loss -0.8004 +2024-11-22 16:10:43.264071: val_loss -0.7706 +2024-11-22 16:10:43.264149: Pseudo dice [0.8288] +2024-11-22 16:10:43.264243: Epoch time: 18.07 s +2024-11-22 16:10:44.139356: +2024-11-22 16:10:44.139575: Epoch 5484 +2024-11-22 16:10:44.139687: Current learning rate: 0.00353 +2024-11-22 16:11:01.916887: train_loss -0.8035 +2024-11-22 16:11:01.917118: val_loss -0.7755 +2024-11-22 16:11:01.917195: Pseudo dice [0.857] +2024-11-22 16:11:01.917269: Epoch time: 17.78 s +2024-11-22 16:11:02.808619: +2024-11-22 16:11:02.808831: Epoch 5485 +2024-11-22 16:11:02.808955: Current learning rate: 0.00353 +2024-11-22 16:11:21.634056: train_loss -0.7982 +2024-11-22 16:11:21.634311: val_loss -0.7916 +2024-11-22 16:11:21.634384: Pseudo dice [0.8661] +2024-11-22 16:11:21.634467: Epoch time: 18.83 s +2024-11-22 16:11:22.528368: +2024-11-22 16:11:22.528570: Epoch 5486 +2024-11-22 16:11:22.528679: Current learning rate: 0.00353 +2024-11-22 16:11:40.949205: train_loss -0.8052 +2024-11-22 16:11:40.949492: val_loss -0.7696 +2024-11-22 16:11:40.949571: Pseudo dice [0.83] +2024-11-22 16:11:40.949648: Epoch time: 18.42 s +2024-11-22 16:11:41.832893: +2024-11-22 16:11:41.833119: Epoch 5487 +2024-11-22 16:11:41.833233: Current learning rate: 0.00353 +2024-11-22 16:12:00.152368: train_loss -0.8028 +2024-11-22 16:12:00.153561: val_loss -0.7862 +2024-11-22 16:12:00.153640: Pseudo dice [0.8564] +2024-11-22 16:12:00.153714: Epoch time: 18.32 s +2024-11-22 16:12:01.031983: +2024-11-22 16:12:01.032198: Epoch 5488 +2024-11-22 16:12:01.032310: Current learning rate: 0.00353 +2024-11-22 16:12:19.759926: train_loss -0.8013 +2024-11-22 16:12:19.760158: val_loss -0.7716 +2024-11-22 16:12:19.760234: Pseudo dice [0.8478] +2024-11-22 16:12:19.760312: Epoch time: 18.73 s +2024-11-22 16:12:20.648333: +2024-11-22 16:12:20.648549: Epoch 5489 +2024-11-22 16:12:20.648674: Current learning rate: 0.00352 +2024-11-22 16:12:40.226668: train_loss -0.805 +2024-11-22 16:12:40.226918: val_loss -0.7608 +2024-11-22 16:12:40.227011: Pseudo dice [0.8363] +2024-11-22 16:12:40.227092: Epoch time: 19.58 s +2024-11-22 16:12:41.177119: +2024-11-22 16:12:41.177393: Epoch 5490 +2024-11-22 16:12:41.177505: Current learning rate: 0.00352 +2024-11-22 16:12:59.222327: train_loss -0.8024 +2024-11-22 16:12:59.222543: val_loss -0.7668 +2024-11-22 16:12:59.222615: Pseudo dice [0.8675] +2024-11-22 16:12:59.222690: Epoch time: 18.05 s +2024-11-22 16:13:00.181278: +2024-11-22 16:13:00.181467: Epoch 5491 +2024-11-22 16:13:00.181576: Current learning rate: 0.00352 +2024-11-22 16:13:18.541694: train_loss -0.8032 +2024-11-22 16:13:18.542041: val_loss -0.7818 +2024-11-22 16:13:18.542122: Pseudo dice [0.8492] +2024-11-22 16:13:18.542201: Epoch time: 18.36 s +2024-11-22 16:13:19.426037: +2024-11-22 16:13:19.426243: Epoch 5492 +2024-11-22 16:13:19.426354: Current learning rate: 0.00352 +2024-11-22 16:13:38.754190: train_loss -0.7965 +2024-11-22 16:13:38.754463: val_loss -0.7877 +2024-11-22 16:13:38.754540: Pseudo dice [0.8373] +2024-11-22 16:13:38.754615: Epoch time: 19.33 s +2024-11-22 16:13:39.740300: +2024-11-22 16:13:39.740518: Epoch 5493 +2024-11-22 16:13:39.740627: Current learning rate: 0.00352 +2024-11-22 16:13:58.841333: train_loss -0.7974 +2024-11-22 16:13:58.841566: val_loss -0.7897 +2024-11-22 16:13:58.841652: Pseudo dice [0.8407] +2024-11-22 16:13:58.841732: Epoch time: 19.1 s +2024-11-22 16:13:59.820755: +2024-11-22 16:13:59.820984: Epoch 5494 +2024-11-22 16:13:59.821103: Current learning rate: 0.00352 +2024-11-22 16:14:19.017976: train_loss -0.7965 +2024-11-22 16:14:19.018457: val_loss -0.7746 +2024-11-22 16:14:19.018559: Pseudo dice [0.84] +2024-11-22 16:14:19.018636: Epoch time: 19.2 s +2024-11-22 16:14:19.902538: +2024-11-22 16:14:19.902781: Epoch 5495 +2024-11-22 16:14:19.902893: Current learning rate: 0.00352 +2024-11-22 16:14:38.489167: train_loss -0.8048 +2024-11-22 16:14:38.490110: val_loss -0.7749 +2024-11-22 16:14:38.490193: Pseudo dice [0.863] +2024-11-22 16:14:38.490269: Epoch time: 18.59 s +2024-11-22 16:14:39.368360: +2024-11-22 16:14:39.368587: Epoch 5496 +2024-11-22 16:14:39.368699: Current learning rate: 0.00352 +2024-11-22 16:14:59.160793: train_loss -0.7979 +2024-11-22 16:14:59.161040: val_loss -0.789 +2024-11-22 16:14:59.161119: Pseudo dice [0.8548] +2024-11-22 16:14:59.161200: Epoch time: 19.79 s +2024-11-22 16:15:00.049518: +2024-11-22 16:15:00.049744: Epoch 5497 +2024-11-22 16:15:00.049855: Current learning rate: 0.00351 +2024-11-22 16:15:18.012711: train_loss -0.8018 +2024-11-22 16:15:18.012922: val_loss -0.7649 +2024-11-22 16:15:18.013004: Pseudo dice [0.8625] +2024-11-22 16:15:18.013077: Epoch time: 17.96 s +2024-11-22 16:15:18.985036: +2024-11-22 16:15:18.985288: Epoch 5498 +2024-11-22 16:15:18.985402: Current learning rate: 0.00351 +2024-11-22 16:15:37.358742: train_loss -0.8048 +2024-11-22 16:15:37.358963: val_loss -0.7753 +2024-11-22 16:15:37.361228: Pseudo dice [0.8176] +2024-11-22 16:15:37.361329: Epoch time: 18.37 s +2024-11-22 16:15:38.282376: +2024-11-22 16:15:38.282758: Epoch 5499 +2024-11-22 16:15:38.282874: Current learning rate: 0.00351 +2024-11-22 16:15:56.825147: train_loss -0.8017 +2024-11-22 16:15:56.825366: val_loss -0.7683 +2024-11-22 16:15:56.825466: Pseudo dice [0.8323] +2024-11-22 16:15:56.825542: Epoch time: 18.54 s +2024-11-22 16:15:58.028054: +2024-11-22 16:15:58.028273: Epoch 5500 +2024-11-22 16:15:58.028387: Current learning rate: 0.00351 +2024-11-22 16:16:16.504985: train_loss -0.8015 +2024-11-22 16:16:16.505209: val_loss -0.7816 +2024-11-22 16:16:16.505292: Pseudo dice [0.852] +2024-11-22 16:16:16.505373: Epoch time: 18.48 s +2024-11-22 16:16:17.402073: +2024-11-22 16:16:17.402299: Epoch 5501 +2024-11-22 16:16:17.402411: Current learning rate: 0.00351 +2024-11-22 16:16:35.935871: train_loss -0.8006 +2024-11-22 16:16:35.936128: val_loss -0.754 +2024-11-22 16:16:35.936210: Pseudo dice [0.8417] +2024-11-22 16:16:35.936291: Epoch time: 18.53 s +2024-11-22 16:16:36.826078: +2024-11-22 16:16:36.826301: Epoch 5502 +2024-11-22 16:16:36.826414: Current learning rate: 0.00351 +2024-11-22 16:16:54.739524: train_loss -0.804 +2024-11-22 16:16:54.739748: val_loss -0.7667 +2024-11-22 16:16:54.739824: Pseudo dice [0.8588] +2024-11-22 16:16:54.739900: Epoch time: 17.91 s +2024-11-22 16:16:55.632817: +2024-11-22 16:16:55.633017: Epoch 5503 +2024-11-22 16:16:55.633147: Current learning rate: 0.00351 +2024-11-22 16:17:14.165880: train_loss -0.8063 +2024-11-22 16:17:14.166115: val_loss -0.7609 +2024-11-22 16:17:14.166201: Pseudo dice [0.8513] +2024-11-22 16:17:14.166285: Epoch time: 18.53 s +2024-11-22 16:17:15.049497: +2024-11-22 16:17:15.049714: Epoch 5504 +2024-11-22 16:17:15.049825: Current learning rate: 0.00351 +2024-11-22 16:17:32.919472: train_loss -0.7883 +2024-11-22 16:17:32.919723: val_loss -0.7855 +2024-11-22 16:17:32.919799: Pseudo dice [0.8516] +2024-11-22 16:17:32.919881: Epoch time: 17.87 s +2024-11-22 16:17:33.805697: +2024-11-22 16:17:33.805905: Epoch 5505 +2024-11-22 16:17:33.806020: Current learning rate: 0.0035 +2024-11-22 16:17:52.211673: train_loss -0.7967 +2024-11-22 16:17:52.214062: val_loss -0.7818 +2024-11-22 16:17:52.214184: Pseudo dice [0.847] +2024-11-22 16:17:52.214265: Epoch time: 18.41 s +2024-11-22 16:17:53.650225: +2024-11-22 16:17:53.650450: Epoch 5506 +2024-11-22 16:17:53.650556: Current learning rate: 0.0035 +2024-11-22 16:18:11.519646: train_loss -0.8003 +2024-11-22 16:18:11.519869: val_loss -0.7785 +2024-11-22 16:18:11.525150: Pseudo dice [0.8507] +2024-11-22 16:18:11.525283: Epoch time: 17.87 s +2024-11-22 16:18:12.479795: +2024-11-22 16:18:12.480039: Epoch 5507 +2024-11-22 16:18:12.480156: Current learning rate: 0.0035 +2024-11-22 16:18:31.871040: train_loss -0.7885 +2024-11-22 16:18:31.871289: val_loss -0.7841 +2024-11-22 16:18:31.871368: Pseudo dice [0.8483] +2024-11-22 16:18:31.871453: Epoch time: 19.39 s +2024-11-22 16:18:32.765389: +2024-11-22 16:18:32.765596: Epoch 5508 +2024-11-22 16:18:32.765704: Current learning rate: 0.0035 +2024-11-22 16:18:50.434293: train_loss -0.7971 +2024-11-22 16:18:50.434546: val_loss -0.7479 +2024-11-22 16:18:50.434646: Pseudo dice [0.8238] +2024-11-22 16:18:50.434723: Epoch time: 17.67 s +2024-11-22 16:18:51.334225: +2024-11-22 16:18:51.334680: Epoch 5509 +2024-11-22 16:18:51.334808: Current learning rate: 0.0035 +2024-11-22 16:19:09.167704: train_loss -0.7865 +2024-11-22 16:19:09.167935: val_loss -0.7457 +2024-11-22 16:19:09.168013: Pseudo dice [0.8444] +2024-11-22 16:19:09.168089: Epoch time: 17.83 s +2024-11-22 16:19:10.094076: +2024-11-22 16:19:10.094293: Epoch 5510 +2024-11-22 16:19:10.094409: Current learning rate: 0.0035 +2024-11-22 16:19:27.585363: train_loss -0.7911 +2024-11-22 16:19:27.585590: val_loss -0.7361 +2024-11-22 16:19:27.585668: Pseudo dice [0.8324] +2024-11-22 16:19:27.585747: Epoch time: 17.49 s +2024-11-22 16:19:28.469266: +2024-11-22 16:19:28.469496: Epoch 5511 +2024-11-22 16:19:28.469616: Current learning rate: 0.0035 +2024-11-22 16:19:45.966691: train_loss -0.7903 +2024-11-22 16:19:45.966916: val_loss -0.7607 +2024-11-22 16:19:45.967003: Pseudo dice [0.8486] +2024-11-22 16:19:45.967082: Epoch time: 17.5 s +2024-11-22 16:19:46.854972: +2024-11-22 16:19:46.855210: Epoch 5512 +2024-11-22 16:19:46.855359: Current learning rate: 0.0035 +2024-11-22 16:20:05.250826: train_loss -0.7954 +2024-11-22 16:20:05.251089: val_loss -0.7591 +2024-11-22 16:20:05.251167: Pseudo dice [0.8698] +2024-11-22 16:20:05.256482: Epoch time: 18.4 s +2024-11-22 16:20:06.160582: +2024-11-22 16:20:06.160789: Epoch 5513 +2024-11-22 16:20:06.160900: Current learning rate: 0.00349 +2024-11-22 16:20:24.417240: train_loss -0.7964 +2024-11-22 16:20:24.417468: val_loss -0.773 +2024-11-22 16:20:24.417541: Pseudo dice [0.8448] +2024-11-22 16:20:24.417614: Epoch time: 18.26 s +2024-11-22 16:20:25.303004: +2024-11-22 16:20:25.303228: Epoch 5514 +2024-11-22 16:20:25.303333: Current learning rate: 0.00349 +2024-11-22 16:20:43.699750: train_loss -0.8004 +2024-11-22 16:20:43.702181: val_loss -0.7845 +2024-11-22 16:20:43.702317: Pseudo dice [0.8541] +2024-11-22 16:20:43.702396: Epoch time: 18.4 s +2024-11-22 16:20:44.696477: +2024-11-22 16:20:44.696690: Epoch 5515 +2024-11-22 16:20:44.696797: Current learning rate: 0.00349 +2024-11-22 16:21:02.248577: train_loss -0.7938 +2024-11-22 16:21:02.248845: val_loss -0.7634 +2024-11-22 16:21:02.248937: Pseudo dice [0.849] +2024-11-22 16:21:02.249037: Epoch time: 17.55 s +2024-11-22 16:21:03.132280: +2024-11-22 16:21:03.132497: Epoch 5516 +2024-11-22 16:21:03.132607: Current learning rate: 0.00349 +2024-11-22 16:21:21.290963: train_loss -0.7913 +2024-11-22 16:21:21.291195: val_loss -0.7648 +2024-11-22 16:21:21.291272: Pseudo dice [0.8594] +2024-11-22 16:21:21.291349: Epoch time: 18.16 s +2024-11-22 16:21:22.177624: +2024-11-22 16:21:22.177837: Epoch 5517 +2024-11-22 16:21:22.177943: Current learning rate: 0.00349 +2024-11-22 16:21:40.767090: train_loss -0.7806 +2024-11-22 16:21:40.767309: val_loss -0.7638 +2024-11-22 16:21:40.767395: Pseudo dice [0.8462] +2024-11-22 16:21:40.767476: Epoch time: 18.59 s +2024-11-22 16:21:42.048267: +2024-11-22 16:21:42.048509: Epoch 5518 +2024-11-22 16:21:42.048618: Current learning rate: 0.00349 +2024-11-22 16:22:00.033816: train_loss -0.7814 +2024-11-22 16:22:00.034064: val_loss -0.78 +2024-11-22 16:22:00.034142: Pseudo dice [0.8425] +2024-11-22 16:22:00.034227: Epoch time: 17.99 s +2024-11-22 16:22:00.924786: +2024-11-22 16:22:00.925024: Epoch 5519 +2024-11-22 16:22:00.925135: Current learning rate: 0.00349 +2024-11-22 16:22:20.316591: train_loss -0.7871 +2024-11-22 16:22:20.316819: val_loss -0.7759 +2024-11-22 16:22:20.316902: Pseudo dice [0.8339] +2024-11-22 16:22:20.316987: Epoch time: 19.39 s +2024-11-22 16:22:21.204802: +2024-11-22 16:22:21.205162: Epoch 5520 +2024-11-22 16:22:21.205273: Current learning rate: 0.00349 +2024-11-22 16:22:39.399414: train_loss -0.7893 +2024-11-22 16:22:39.399634: val_loss -0.7654 +2024-11-22 16:22:39.399707: Pseudo dice [0.8395] +2024-11-22 16:22:39.399787: Epoch time: 18.2 s +2024-11-22 16:22:40.288140: +2024-11-22 16:22:40.288373: Epoch 5521 +2024-11-22 16:22:40.288480: Current learning rate: 0.00348 +2024-11-22 16:22:59.034631: train_loss -0.7897 +2024-11-22 16:22:59.034850: val_loss -0.7718 +2024-11-22 16:22:59.034927: Pseudo dice [0.842] +2024-11-22 16:22:59.035506: Epoch time: 18.75 s +2024-11-22 16:22:59.920044: +2024-11-22 16:22:59.920264: Epoch 5522 +2024-11-22 16:22:59.920370: Current learning rate: 0.00348 +2024-11-22 16:23:19.802111: train_loss -0.7836 +2024-11-22 16:23:19.802358: val_loss -0.7625 +2024-11-22 16:23:19.802442: Pseudo dice [0.8449] +2024-11-22 16:23:19.802526: Epoch time: 19.88 s +2024-11-22 16:23:20.700523: +2024-11-22 16:23:20.700744: Epoch 5523 +2024-11-22 16:23:20.700855: Current learning rate: 0.00348 +2024-11-22 16:23:38.247033: train_loss -0.7943 +2024-11-22 16:23:38.247247: val_loss -0.7702 +2024-11-22 16:23:38.247344: Pseudo dice [0.8431] +2024-11-22 16:23:38.247431: Epoch time: 17.55 s +2024-11-22 16:23:39.146256: +2024-11-22 16:23:39.146466: Epoch 5524 +2024-11-22 16:23:39.146574: Current learning rate: 0.00348 +2024-11-22 16:23:57.877835: train_loss -0.7915 +2024-11-22 16:23:57.878083: val_loss -0.7834 +2024-11-22 16:23:57.878167: Pseudo dice [0.8603] +2024-11-22 16:23:57.878250: Epoch time: 18.73 s +2024-11-22 16:23:58.770782: +2024-11-22 16:23:58.771064: Epoch 5525 +2024-11-22 16:23:58.771179: Current learning rate: 0.00348 +2024-11-22 16:24:18.168535: train_loss -0.7939 +2024-11-22 16:24:18.168812: val_loss -0.7238 +2024-11-22 16:24:18.168890: Pseudo dice [0.8415] +2024-11-22 16:24:18.168972: Epoch time: 19.4 s +2024-11-22 16:24:19.063320: +2024-11-22 16:24:19.063605: Epoch 5526 +2024-11-22 16:24:19.063716: Current learning rate: 0.00348 +2024-11-22 16:24:37.090728: train_loss -0.7891 +2024-11-22 16:24:37.090962: val_loss -0.7587 +2024-11-22 16:24:37.091048: Pseudo dice [0.8581] +2024-11-22 16:24:37.091125: Epoch time: 18.03 s +2024-11-22 16:24:38.026231: +2024-11-22 16:24:38.026431: Epoch 5527 +2024-11-22 16:24:38.026541: Current learning rate: 0.00348 +2024-11-22 16:24:56.699737: train_loss -0.8002 +2024-11-22 16:24:56.699965: val_loss -0.7846 +2024-11-22 16:24:56.700049: Pseudo dice [0.8555] +2024-11-22 16:24:56.700125: Epoch time: 18.67 s +2024-11-22 16:24:57.716262: +2024-11-22 16:24:57.716498: Epoch 5528 +2024-11-22 16:24:57.716609: Current learning rate: 0.00348 +2024-11-22 16:25:16.800321: train_loss -0.8031 +2024-11-22 16:25:16.802173: val_loss -0.7767 +2024-11-22 16:25:16.802274: Pseudo dice [0.8348] +2024-11-22 16:25:16.802363: Epoch time: 19.08 s +2024-11-22 16:25:17.789021: +2024-11-22 16:25:17.789262: Epoch 5529 +2024-11-22 16:25:17.789380: Current learning rate: 0.00347 +2024-11-22 16:25:35.421972: train_loss -0.7992 +2024-11-22 16:25:35.422221: val_loss -0.7884 +2024-11-22 16:25:35.422300: Pseudo dice [0.8451] +2024-11-22 16:25:35.422375: Epoch time: 17.63 s +2024-11-22 16:25:36.709901: +2024-11-22 16:25:36.710126: Epoch 5530 +2024-11-22 16:25:36.710238: Current learning rate: 0.00347 +2024-11-22 16:25:55.459327: train_loss -0.7984 +2024-11-22 16:25:55.459569: val_loss -0.7738 +2024-11-22 16:25:55.459644: Pseudo dice [0.852] +2024-11-22 16:25:55.459721: Epoch time: 18.75 s +2024-11-22 16:25:56.408767: +2024-11-22 16:25:56.409008: Epoch 5531 +2024-11-22 16:25:56.409118: Current learning rate: 0.00347 +2024-11-22 16:26:14.459555: train_loss -0.8002 +2024-11-22 16:26:14.459774: val_loss -0.7717 +2024-11-22 16:26:14.459851: Pseudo dice [0.8597] +2024-11-22 16:26:14.459929: Epoch time: 18.05 s +2024-11-22 16:26:15.344904: +2024-11-22 16:26:15.345271: Epoch 5532 +2024-11-22 16:26:15.345384: Current learning rate: 0.00347 +2024-11-22 16:26:34.164011: train_loss -0.8034 +2024-11-22 16:26:34.164253: val_loss -0.78 +2024-11-22 16:26:34.164327: Pseudo dice [0.8503] +2024-11-22 16:26:34.164409: Epoch time: 18.82 s +2024-11-22 16:26:35.055152: +2024-11-22 16:26:35.055387: Epoch 5533 +2024-11-22 16:26:35.055499: Current learning rate: 0.00347 +2024-11-22 16:26:53.504252: train_loss -0.7952 +2024-11-22 16:26:53.504467: val_loss -0.7546 +2024-11-22 16:26:53.504556: Pseudo dice [0.856] +2024-11-22 16:26:53.504692: Epoch time: 18.45 s +2024-11-22 16:26:54.397960: +2024-11-22 16:26:54.398184: Epoch 5534 +2024-11-22 16:26:54.398297: Current learning rate: 0.00347 +2024-11-22 16:27:13.673722: train_loss -0.7756 +2024-11-22 16:27:13.675622: val_loss -0.7666 +2024-11-22 16:27:13.675749: Pseudo dice [0.8442] +2024-11-22 16:27:13.675827: Epoch time: 19.28 s +2024-11-22 16:27:14.626196: +2024-11-22 16:27:14.626404: Epoch 5535 +2024-11-22 16:27:14.626530: Current learning rate: 0.00347 +2024-11-22 16:27:33.070018: train_loss -0.7789 +2024-11-22 16:27:33.070297: val_loss -0.7733 +2024-11-22 16:27:33.070376: Pseudo dice [0.8524] +2024-11-22 16:27:33.070450: Epoch time: 18.44 s +2024-11-22 16:27:33.961838: +2024-11-22 16:27:33.962032: Epoch 5536 +2024-11-22 16:27:33.962142: Current learning rate: 0.00346 +2024-11-22 16:27:52.090882: train_loss -0.7956 +2024-11-22 16:27:52.091136: val_loss -0.7767 +2024-11-22 16:27:52.091217: Pseudo dice [0.8373] +2024-11-22 16:27:52.091300: Epoch time: 18.13 s +2024-11-22 16:27:52.981746: +2024-11-22 16:27:52.981961: Epoch 5537 +2024-11-22 16:27:52.982078: Current learning rate: 0.00346 +2024-11-22 16:28:11.280621: train_loss -0.7973 +2024-11-22 16:28:11.280831: val_loss -0.7776 +2024-11-22 16:28:11.280903: Pseudo dice [0.8531] +2024-11-22 16:28:11.280977: Epoch time: 18.3 s +2024-11-22 16:28:12.172707: +2024-11-22 16:28:12.172927: Epoch 5538 +2024-11-22 16:28:12.173043: Current learning rate: 0.00346 +2024-11-22 16:28:31.832003: train_loss -0.7903 +2024-11-22 16:28:31.832238: val_loss -0.7691 +2024-11-22 16:28:31.832318: Pseudo dice [0.8401] +2024-11-22 16:28:31.832396: Epoch time: 19.66 s +2024-11-22 16:28:32.738709: +2024-11-22 16:28:32.738988: Epoch 5539 +2024-11-22 16:28:32.739105: Current learning rate: 0.00346 +2024-11-22 16:28:51.548190: train_loss -0.7968 +2024-11-22 16:28:51.548429: val_loss -0.7617 +2024-11-22 16:28:51.548506: Pseudo dice [0.8549] +2024-11-22 16:28:51.548579: Epoch time: 18.81 s +2024-11-22 16:28:52.579015: +2024-11-22 16:28:52.579262: Epoch 5540 +2024-11-22 16:28:52.579386: Current learning rate: 0.00346 +2024-11-22 16:29:11.021733: train_loss -0.7961 +2024-11-22 16:29:11.027192: val_loss -0.8073 +2024-11-22 16:29:11.027316: Pseudo dice [0.8559] +2024-11-22 16:29:11.027406: Epoch time: 18.44 s +2024-11-22 16:29:11.978245: +2024-11-22 16:29:11.978487: Epoch 5541 +2024-11-22 16:29:11.978605: Current learning rate: 0.00346 +2024-11-22 16:29:29.910850: train_loss -0.7943 +2024-11-22 16:29:29.911069: val_loss -0.7652 +2024-11-22 16:29:29.911151: Pseudo dice [0.8512] +2024-11-22 16:29:29.911226: Epoch time: 17.93 s +2024-11-22 16:29:31.203777: +2024-11-22 16:29:31.204019: Epoch 5542 +2024-11-22 16:29:31.204127: Current learning rate: 0.00346 +2024-11-22 16:29:49.214391: train_loss -0.7947 +2024-11-22 16:29:49.214633: val_loss -0.7719 +2024-11-22 16:29:49.214709: Pseudo dice [0.8495] +2024-11-22 16:29:49.214796: Epoch time: 18.01 s +2024-11-22 16:29:50.106162: +2024-11-22 16:29:50.106379: Epoch 5543 +2024-11-22 16:29:50.106493: Current learning rate: 0.00346 +2024-11-22 16:30:08.206669: train_loss -0.7884 +2024-11-22 16:30:08.206926: val_loss -0.7683 +2024-11-22 16:30:08.207011: Pseudo dice [0.8371] +2024-11-22 16:30:08.207096: Epoch time: 18.1 s +2024-11-22 16:30:09.087696: +2024-11-22 16:30:09.087916: Epoch 5544 +2024-11-22 16:30:09.088032: Current learning rate: 0.00345 +2024-11-22 16:30:28.421250: train_loss -0.7937 +2024-11-22 16:30:28.421470: val_loss -0.7831 +2024-11-22 16:30:28.421555: Pseudo dice [0.8634] +2024-11-22 16:30:28.421632: Epoch time: 19.33 s +2024-11-22 16:30:29.312698: +2024-11-22 16:30:29.312917: Epoch 5545 +2024-11-22 16:30:29.313031: Current learning rate: 0.00345 +2024-11-22 16:30:48.112656: train_loss -0.7982 +2024-11-22 16:30:48.112894: val_loss -0.7448 +2024-11-22 16:30:48.112976: Pseudo dice [0.8265] +2024-11-22 16:30:48.113060: Epoch time: 18.8 s +2024-11-22 16:30:49.057409: +2024-11-22 16:30:49.057622: Epoch 5546 +2024-11-22 16:30:49.057732: Current learning rate: 0.00345 +2024-11-22 16:31:06.797336: train_loss -0.793 +2024-11-22 16:31:06.797559: val_loss -0.7661 +2024-11-22 16:31:06.797634: Pseudo dice [0.8388] +2024-11-22 16:31:06.797707: Epoch time: 17.74 s +2024-11-22 16:31:07.683010: +2024-11-22 16:31:07.683257: Epoch 5547 +2024-11-22 16:31:07.701438: Current learning rate: 0.00345 +2024-11-22 16:31:25.110700: train_loss -0.8028 +2024-11-22 16:31:25.110923: val_loss -0.7464 +2024-11-22 16:31:25.111015: Pseudo dice [0.8556] +2024-11-22 16:31:25.111096: Epoch time: 17.43 s +2024-11-22 16:31:25.991360: +2024-11-22 16:31:25.991556: Epoch 5548 +2024-11-22 16:31:25.991664: Current learning rate: 0.00345 +2024-11-22 16:31:45.442160: train_loss -0.7839 +2024-11-22 16:31:45.442415: val_loss -0.7773 +2024-11-22 16:31:45.442490: Pseudo dice [0.8475] +2024-11-22 16:31:45.442569: Epoch time: 19.45 s +2024-11-22 16:31:46.421951: +2024-11-22 16:31:46.422157: Epoch 5549 +2024-11-22 16:31:46.422267: Current learning rate: 0.00345 +2024-11-22 16:32:05.852367: train_loss -0.7883 +2024-11-22 16:32:05.852583: val_loss -0.7579 +2024-11-22 16:32:05.852656: Pseudo dice [0.8374] +2024-11-22 16:32:05.852736: Epoch time: 19.43 s +2024-11-22 16:32:07.011841: +2024-11-22 16:32:07.012073: Epoch 5550 +2024-11-22 16:32:07.012182: Current learning rate: 0.00345 +2024-11-22 16:32:25.890794: train_loss -0.7964 +2024-11-22 16:32:25.891016: val_loss -0.7686 +2024-11-22 16:32:25.891090: Pseudo dice [0.8399] +2024-11-22 16:32:25.891162: Epoch time: 18.88 s +2024-11-22 16:32:26.776734: +2024-11-22 16:32:26.776948: Epoch 5551 +2024-11-22 16:32:26.777055: Current learning rate: 0.00345 +2024-11-22 16:32:43.725758: train_loss -0.8005 +2024-11-22 16:32:43.726010: val_loss -0.788 +2024-11-22 16:32:43.726086: Pseudo dice [0.833] +2024-11-22 16:32:43.726168: Epoch time: 16.95 s +2024-11-22 16:32:44.614525: +2024-11-22 16:32:44.614743: Epoch 5552 +2024-11-22 16:32:44.614857: Current learning rate: 0.00344 +2024-11-22 16:33:02.833285: train_loss -0.803 +2024-11-22 16:33:02.833505: val_loss -0.7677 +2024-11-22 16:33:02.833580: Pseudo dice [0.8488] +2024-11-22 16:33:02.833654: Epoch time: 18.22 s +2024-11-22 16:33:03.717834: +2024-11-22 16:33:03.718055: Epoch 5553 +2024-11-22 16:33:03.718161: Current learning rate: 0.00344 +2024-11-22 16:33:22.791313: train_loss -0.7959 +2024-11-22 16:33:22.791807: val_loss -0.7684 +2024-11-22 16:33:22.791960: Pseudo dice [0.8285] +2024-11-22 16:33:22.792043: Epoch time: 19.07 s +2024-11-22 16:33:23.674443: +2024-11-22 16:33:23.674650: Epoch 5554 +2024-11-22 16:33:23.674758: Current learning rate: 0.00344 +2024-11-22 16:33:42.159111: train_loss -0.7859 +2024-11-22 16:33:42.159359: val_loss -0.7708 +2024-11-22 16:33:42.159434: Pseudo dice [0.8461] +2024-11-22 16:33:42.159518: Epoch time: 18.49 s +2024-11-22 16:33:43.050569: +2024-11-22 16:33:43.050782: Epoch 5555 +2024-11-22 16:33:43.050887: Current learning rate: 0.00344 +2024-11-22 16:34:01.451355: train_loss -0.7964 +2024-11-22 16:34:01.451598: val_loss -0.7986 +2024-11-22 16:34:01.451672: Pseudo dice [0.8581] +2024-11-22 16:34:01.451749: Epoch time: 18.4 s +2024-11-22 16:34:02.443784: +2024-11-22 16:34:02.444010: Epoch 5556 +2024-11-22 16:34:02.444299: Current learning rate: 0.00344 +2024-11-22 16:34:20.913327: train_loss -0.7872 +2024-11-22 16:34:20.913556: val_loss -0.7957 +2024-11-22 16:34:20.913639: Pseudo dice [0.843] +2024-11-22 16:34:20.913717: Epoch time: 18.47 s +2024-11-22 16:34:21.816624: +2024-11-22 16:34:21.816831: Epoch 5557 +2024-11-22 16:34:21.816940: Current learning rate: 0.00344 +2024-11-22 16:34:40.493134: train_loss -0.7956 +2024-11-22 16:34:40.493386: val_loss -0.7555 +2024-11-22 16:34:40.493463: Pseudo dice [0.8666] +2024-11-22 16:34:40.493538: Epoch time: 18.68 s +2024-11-22 16:34:41.463363: +2024-11-22 16:34:41.463593: Epoch 5558 +2024-11-22 16:34:41.463704: Current learning rate: 0.00344 +2024-11-22 16:35:00.311061: train_loss -0.7991 +2024-11-22 16:35:00.311385: val_loss -0.769 +2024-11-22 16:35:00.311462: Pseudo dice [0.8443] +2024-11-22 16:35:00.311543: Epoch time: 18.85 s +2024-11-22 16:35:01.195747: +2024-11-22 16:35:01.195940: Epoch 5559 +2024-11-22 16:35:01.196055: Current learning rate: 0.00344 +2024-11-22 16:35:18.588445: train_loss -0.7981 +2024-11-22 16:35:18.588670: val_loss -0.7493 +2024-11-22 16:35:18.588743: Pseudo dice [0.8497] +2024-11-22 16:35:18.588819: Epoch time: 17.39 s +2024-11-22 16:35:19.567282: +2024-11-22 16:35:19.567499: Epoch 5560 +2024-11-22 16:35:19.567616: Current learning rate: 0.00343 +2024-11-22 16:35:37.997850: train_loss -0.8006 +2024-11-22 16:35:37.998075: val_loss -0.7835 +2024-11-22 16:35:38.002051: Pseudo dice [0.8547] +2024-11-22 16:35:38.002311: Epoch time: 18.43 s +2024-11-22 16:35:38.887502: +2024-11-22 16:35:38.887716: Epoch 5561 +2024-11-22 16:35:38.887834: Current learning rate: 0.00343 +2024-11-22 16:35:57.942661: train_loss -0.7954 +2024-11-22 16:35:57.942941: val_loss -0.7488 +2024-11-22 16:35:57.943029: Pseudo dice [0.8407] +2024-11-22 16:35:57.943129: Epoch time: 19.06 s +2024-11-22 16:35:58.835300: +2024-11-22 16:35:58.835505: Epoch 5562 +2024-11-22 16:35:58.835613: Current learning rate: 0.00343 +2024-11-22 16:36:17.086189: train_loss -0.8012 +2024-11-22 16:36:17.088015: val_loss -0.7833 +2024-11-22 16:36:17.088105: Pseudo dice [0.8607] +2024-11-22 16:36:17.088236: Epoch time: 18.25 s +2024-11-22 16:36:17.981398: +2024-11-22 16:36:17.981620: Epoch 5563 +2024-11-22 16:36:17.981733: Current learning rate: 0.00343 +2024-11-22 16:36:36.364164: train_loss -0.7921 +2024-11-22 16:36:36.364379: val_loss -0.766 +2024-11-22 16:36:36.364453: Pseudo dice [0.8412] +2024-11-22 16:36:36.364528: Epoch time: 18.38 s +2024-11-22 16:36:37.248747: +2024-11-22 16:36:37.248963: Epoch 5564 +2024-11-22 16:36:37.249082: Current learning rate: 0.00343 +2024-11-22 16:36:55.316136: train_loss -0.7929 +2024-11-22 16:36:55.316360: val_loss -0.7749 +2024-11-22 16:36:55.316432: Pseudo dice [0.845] +2024-11-22 16:36:55.316509: Epoch time: 18.07 s +2024-11-22 16:36:56.603397: +2024-11-22 16:36:56.603630: Epoch 5565 +2024-11-22 16:36:56.603740: Current learning rate: 0.00343 +2024-11-22 16:37:15.186936: train_loss -0.8053 +2024-11-22 16:37:15.187187: val_loss -0.7916 +2024-11-22 16:37:15.187266: Pseudo dice [0.8548] +2024-11-22 16:37:15.187338: Epoch time: 18.58 s +2024-11-22 16:37:16.072689: +2024-11-22 16:37:16.072905: Epoch 5566 +2024-11-22 16:37:16.073017: Current learning rate: 0.00343 +2024-11-22 16:37:33.311253: train_loss -0.8034 +2024-11-22 16:37:33.311467: val_loss -0.7954 +2024-11-22 16:37:33.311542: Pseudo dice [0.8463] +2024-11-22 16:37:33.311615: Epoch time: 17.24 s +2024-11-22 16:37:34.299264: +2024-11-22 16:37:34.299497: Epoch 5567 +2024-11-22 16:37:34.299608: Current learning rate: 0.00343 +2024-11-22 16:37:52.488182: train_loss -0.8013 +2024-11-22 16:37:52.488490: val_loss -0.789 +2024-11-22 16:37:52.488569: Pseudo dice [0.8463] +2024-11-22 16:37:52.488643: Epoch time: 18.19 s +2024-11-22 16:37:53.424496: +2024-11-22 16:37:53.424711: Epoch 5568 +2024-11-22 16:37:53.424829: Current learning rate: 0.00342 +2024-11-22 16:38:12.148667: train_loss -0.8074 +2024-11-22 16:38:12.148925: val_loss -0.7733 +2024-11-22 16:38:12.149007: Pseudo dice [0.8402] +2024-11-22 16:38:12.149087: Epoch time: 18.72 s +2024-11-22 16:38:13.053516: +2024-11-22 16:38:13.053723: Epoch 5569 +2024-11-22 16:38:13.053843: Current learning rate: 0.00342 +2024-11-22 16:38:32.640538: train_loss -0.7975 +2024-11-22 16:38:32.640758: val_loss -0.7624 +2024-11-22 16:38:32.640836: Pseudo dice [0.8414] +2024-11-22 16:38:32.640911: Epoch time: 19.59 s +2024-11-22 16:38:33.539471: +2024-11-22 16:38:33.539709: Epoch 5570 +2024-11-22 16:38:33.539824: Current learning rate: 0.00342 +2024-11-22 16:38:53.035218: train_loss -0.8007 +2024-11-22 16:38:53.035470: val_loss -0.7943 +2024-11-22 16:38:53.035547: Pseudo dice [0.8526] +2024-11-22 16:38:53.035622: Epoch time: 19.5 s +2024-11-22 16:38:53.918961: +2024-11-22 16:38:53.919288: Epoch 5571 +2024-11-22 16:38:53.919397: Current learning rate: 0.00342 +2024-11-22 16:39:11.730411: train_loss -0.8009 +2024-11-22 16:39:11.730634: val_loss -0.7469 +2024-11-22 16:39:11.730727: Pseudo dice [0.8432] +2024-11-22 16:39:11.730804: Epoch time: 17.81 s +2024-11-22 16:39:12.742249: +2024-11-22 16:39:12.742441: Epoch 5572 +2024-11-22 16:39:12.742549: Current learning rate: 0.00342 +2024-11-22 16:39:31.200668: train_loss -0.7947 +2024-11-22 16:39:31.200917: val_loss -0.7709 +2024-11-22 16:39:31.201057: Pseudo dice [0.8491] +2024-11-22 16:39:31.201142: Epoch time: 18.46 s +2024-11-22 16:39:32.088144: +2024-11-22 16:39:32.088346: Epoch 5573 +2024-11-22 16:39:32.088468: Current learning rate: 0.00342 +2024-11-22 16:39:49.341982: train_loss -0.8079 +2024-11-22 16:39:49.342190: val_loss -0.7728 +2024-11-22 16:39:49.342263: Pseudo dice [0.8483] +2024-11-22 16:39:49.342335: Epoch time: 17.25 s +2024-11-22 16:39:50.233120: +2024-11-22 16:39:50.233452: Epoch 5574 +2024-11-22 16:39:50.233563: Current learning rate: 0.00342 +2024-11-22 16:40:08.665747: train_loss -0.8064 +2024-11-22 16:40:08.665979: val_loss -0.7855 +2024-11-22 16:40:08.666062: Pseudo dice [0.8519] +2024-11-22 16:40:08.666137: Epoch time: 18.43 s +2024-11-22 16:40:09.546696: +2024-11-22 16:40:09.546961: Epoch 5575 +2024-11-22 16:40:09.547078: Current learning rate: 0.00342 +2024-11-22 16:40:28.910548: train_loss -0.8057 +2024-11-22 16:40:28.910767: val_loss -0.7505 +2024-11-22 16:40:28.910846: Pseudo dice [0.8362] +2024-11-22 16:40:28.910925: Epoch time: 19.36 s +2024-11-22 16:40:29.790902: +2024-11-22 16:40:29.791137: Epoch 5576 +2024-11-22 16:40:29.791251: Current learning rate: 0.00341 +2024-11-22 16:40:47.836058: train_loss -0.7994 +2024-11-22 16:40:47.836297: val_loss -0.7769 +2024-11-22 16:40:47.836369: Pseudo dice [0.8536] +2024-11-22 16:40:47.836445: Epoch time: 18.05 s +2024-11-22 16:40:49.076401: +2024-11-22 16:40:49.076637: Epoch 5577 +2024-11-22 16:40:49.076750: Current learning rate: 0.00341 +2024-11-22 16:41:07.872664: train_loss -0.7963 +2024-11-22 16:41:07.872897: val_loss -0.7611 +2024-11-22 16:41:07.872971: Pseudo dice [0.8232] +2024-11-22 16:41:07.873053: Epoch time: 18.8 s +2024-11-22 16:41:08.754480: +2024-11-22 16:41:08.754704: Epoch 5578 +2024-11-22 16:41:08.754814: Current learning rate: 0.00341 +2024-11-22 16:41:26.827268: train_loss -0.7954 +2024-11-22 16:41:26.827494: val_loss -0.7661 +2024-11-22 16:41:26.827566: Pseudo dice [0.86] +2024-11-22 16:41:26.827639: Epoch time: 18.07 s +2024-11-22 16:41:27.720709: +2024-11-22 16:41:27.720956: Epoch 5579 +2024-11-22 16:41:27.721102: Current learning rate: 0.00341 +2024-11-22 16:41:47.021615: train_loss -0.8045 +2024-11-22 16:41:47.021875: val_loss -0.7534 +2024-11-22 16:41:47.021948: Pseudo dice [0.8443] +2024-11-22 16:41:47.022034: Epoch time: 19.3 s +2024-11-22 16:41:47.911696: +2024-11-22 16:41:47.911963: Epoch 5580 +2024-11-22 16:41:47.912073: Current learning rate: 0.00341 +2024-11-22 16:42:06.716406: train_loss -0.8052 +2024-11-22 16:42:06.716677: val_loss -0.7785 +2024-11-22 16:42:06.716795: Pseudo dice [0.8455] +2024-11-22 16:42:06.716906: Epoch time: 18.81 s +2024-11-22 16:42:07.609033: +2024-11-22 16:42:07.609233: Epoch 5581 +2024-11-22 16:42:07.609343: Current learning rate: 0.00341 +2024-11-22 16:42:25.146384: train_loss -0.8046 +2024-11-22 16:42:25.146606: val_loss -0.7618 +2024-11-22 16:42:25.146685: Pseudo dice [0.8619] +2024-11-22 16:42:25.146761: Epoch time: 17.54 s +2024-11-22 16:42:26.095235: +2024-11-22 16:42:26.095440: Epoch 5582 +2024-11-22 16:42:26.095947: Current learning rate: 0.00341 +2024-11-22 16:42:44.116360: train_loss -0.8009 +2024-11-22 16:42:44.116637: val_loss -0.7761 +2024-11-22 16:42:44.116716: Pseudo dice [0.8436] +2024-11-22 16:42:44.116795: Epoch time: 18.02 s +2024-11-22 16:42:45.002875: +2024-11-22 16:42:45.003092: Epoch 5583 +2024-11-22 16:42:45.003201: Current learning rate: 0.00341 +2024-11-22 16:43:02.767123: train_loss -0.8037 +2024-11-22 16:43:02.767411: val_loss -0.7885 +2024-11-22 16:43:02.767487: Pseudo dice [0.8487] +2024-11-22 16:43:02.767569: Epoch time: 17.77 s +2024-11-22 16:43:03.658179: +2024-11-22 16:43:03.658442: Epoch 5584 +2024-11-22 16:43:03.658552: Current learning rate: 0.0034 +2024-11-22 16:43:21.591819: train_loss -0.7876 +2024-11-22 16:43:21.594213: val_loss -0.7698 +2024-11-22 16:43:21.594301: Pseudo dice [0.8298] +2024-11-22 16:43:21.594378: Epoch time: 17.93 s +2024-11-22 16:43:22.780982: +2024-11-22 16:43:22.781233: Epoch 5585 +2024-11-22 16:43:22.781339: Current learning rate: 0.0034 +2024-11-22 16:43:40.542458: train_loss -0.8048 +2024-11-22 16:43:40.542668: val_loss -0.7716 +2024-11-22 16:43:40.542741: Pseudo dice [0.8444] +2024-11-22 16:43:40.542816: Epoch time: 17.76 s +2024-11-22 16:43:41.457043: +2024-11-22 16:43:41.457340: Epoch 5586 +2024-11-22 16:43:41.457450: Current learning rate: 0.0034 +2024-11-22 16:44:00.411375: train_loss -0.795 +2024-11-22 16:44:00.411652: val_loss -0.7755 +2024-11-22 16:44:00.411728: Pseudo dice [0.8573] +2024-11-22 16:44:00.411815: Epoch time: 18.96 s +2024-11-22 16:44:01.294711: +2024-11-22 16:44:01.294981: Epoch 5587 +2024-11-22 16:44:01.295101: Current learning rate: 0.0034 +2024-11-22 16:44:19.764006: train_loss -0.8019 +2024-11-22 16:44:19.764268: val_loss -0.7792 +2024-11-22 16:44:19.764346: Pseudo dice [0.8576] +2024-11-22 16:44:19.764443: Epoch time: 18.47 s +2024-11-22 16:44:20.645780: +2024-11-22 16:44:20.646002: Epoch 5588 +2024-11-22 16:44:20.646110: Current learning rate: 0.0034 +2024-11-22 16:44:38.608604: train_loss -0.8143 +2024-11-22 16:44:38.608849: val_loss -0.7645 +2024-11-22 16:44:38.608965: Pseudo dice [0.8461] +2024-11-22 16:44:38.609049: Epoch time: 17.96 s +2024-11-22 16:44:39.854310: +2024-11-22 16:44:39.854555: Epoch 5589 +2024-11-22 16:44:39.854666: Current learning rate: 0.0034 +2024-11-22 16:44:57.960607: train_loss -0.7993 +2024-11-22 16:44:57.960855: val_loss -0.7757 +2024-11-22 16:44:57.960933: Pseudo dice [0.8439] +2024-11-22 16:44:57.961031: Epoch time: 18.11 s +2024-11-22 16:44:58.850532: +2024-11-22 16:44:58.850754: Epoch 5590 +2024-11-22 16:44:58.850862: Current learning rate: 0.0034 +2024-11-22 16:45:17.820131: train_loss -0.8056 +2024-11-22 16:45:17.820440: val_loss -0.7556 +2024-11-22 16:45:17.820517: Pseudo dice [0.8484] +2024-11-22 16:45:17.820598: Epoch time: 18.97 s +2024-11-22 16:45:18.707456: +2024-11-22 16:45:18.707694: Epoch 5591 +2024-11-22 16:45:18.707806: Current learning rate: 0.0034 +2024-11-22 16:45:37.586499: train_loss -0.7871 +2024-11-22 16:45:37.586775: val_loss -0.7691 +2024-11-22 16:45:37.586851: Pseudo dice [0.8326] +2024-11-22 16:45:37.586926: Epoch time: 18.88 s +2024-11-22 16:45:38.473990: +2024-11-22 16:45:38.474204: Epoch 5592 +2024-11-22 16:45:38.474315: Current learning rate: 0.00339 +2024-11-22 16:45:55.280025: train_loss -0.7983 +2024-11-22 16:45:55.280233: val_loss -0.7886 +2024-11-22 16:45:55.280308: Pseudo dice [0.8641] +2024-11-22 16:45:55.280382: Epoch time: 16.81 s +2024-11-22 16:45:56.163141: +2024-11-22 16:45:56.163348: Epoch 5593 +2024-11-22 16:45:56.163453: Current learning rate: 0.00339 +2024-11-22 16:46:14.906342: train_loss -0.8045 +2024-11-22 16:46:14.906557: val_loss -0.7806 +2024-11-22 16:46:14.906679: Pseudo dice [0.8399] +2024-11-22 16:46:14.906752: Epoch time: 18.74 s +2024-11-22 16:46:15.789668: +2024-11-22 16:46:15.789896: Epoch 5594 +2024-11-22 16:46:15.790022: Current learning rate: 0.00339 +2024-11-22 16:46:33.639878: train_loss -0.8093 +2024-11-22 16:46:33.640098: val_loss -0.793 +2024-11-22 16:46:33.640172: Pseudo dice [0.8516] +2024-11-22 16:46:33.640248: Epoch time: 17.85 s +2024-11-22 16:46:34.524950: +2024-11-22 16:46:34.525291: Epoch 5595 +2024-11-22 16:46:34.525401: Current learning rate: 0.00339 +2024-11-22 16:46:52.024845: train_loss -0.8043 +2024-11-22 16:46:52.025084: val_loss -0.7799 +2024-11-22 16:46:52.025162: Pseudo dice [0.8581] +2024-11-22 16:46:52.025239: Epoch time: 17.5 s +2024-11-22 16:46:53.011109: +2024-11-22 16:46:53.011324: Epoch 5596 +2024-11-22 16:46:53.011431: Current learning rate: 0.00339 +2024-11-22 16:47:11.498206: train_loss -0.8034 +2024-11-22 16:47:11.498429: val_loss -0.7671 +2024-11-22 16:47:11.498502: Pseudo dice [0.8477] +2024-11-22 16:47:11.498577: Epoch time: 18.49 s +2024-11-22 16:47:12.540617: +2024-11-22 16:47:12.540844: Epoch 5597 +2024-11-22 16:47:12.540947: Current learning rate: 0.00339 +2024-11-22 16:47:30.486354: train_loss -0.805 +2024-11-22 16:47:30.486575: val_loss -0.787 +2024-11-22 16:47:30.486670: Pseudo dice [0.8536] +2024-11-22 16:47:30.486746: Epoch time: 17.95 s +2024-11-22 16:47:31.366617: +2024-11-22 16:47:31.367129: Epoch 5598 +2024-11-22 16:47:31.367255: Current learning rate: 0.00339 +2024-11-22 16:47:49.310520: train_loss -0.807 +2024-11-22 16:47:49.312955: val_loss -0.7816 +2024-11-22 16:47:49.313094: Pseudo dice [0.8574] +2024-11-22 16:47:49.313189: Epoch time: 17.94 s +2024-11-22 16:47:50.207299: +2024-11-22 16:47:50.207558: Epoch 5599 +2024-11-22 16:47:50.207668: Current learning rate: 0.00339 +2024-11-22 16:48:08.216524: train_loss -0.8014 +2024-11-22 16:48:08.216742: val_loss -0.7701 +2024-11-22 16:48:08.216817: Pseudo dice [0.8478] +2024-11-22 16:48:08.216891: Epoch time: 18.01 s +2024-11-22 16:48:09.383699: +2024-11-22 16:48:09.383952: Epoch 5600 +2024-11-22 16:48:09.384070: Current learning rate: 0.00338 +2024-11-22 16:48:29.200414: train_loss -0.7987 +2024-11-22 16:48:29.200650: val_loss -0.7493 +2024-11-22 16:48:29.200724: Pseudo dice [0.8401] +2024-11-22 16:48:29.200798: Epoch time: 19.82 s +2024-11-22 16:48:30.088796: +2024-11-22 16:48:30.089021: Epoch 5601 +2024-11-22 16:48:30.089129: Current learning rate: 0.00338 +2024-11-22 16:48:49.338583: train_loss -0.8013 +2024-11-22 16:48:49.338814: val_loss -0.7756 +2024-11-22 16:48:49.338889: Pseudo dice [0.8599] +2024-11-22 16:48:49.338966: Epoch time: 19.25 s +2024-11-22 16:48:50.413279: +2024-11-22 16:48:50.413502: Epoch 5602 +2024-11-22 16:48:50.413613: Current learning rate: 0.00338 +2024-11-22 16:49:09.392832: train_loss -0.7905 +2024-11-22 16:49:09.393103: val_loss -0.7509 +2024-11-22 16:49:09.393180: Pseudo dice [0.8379] +2024-11-22 16:49:09.393259: Epoch time: 18.98 s +2024-11-22 16:49:10.284721: +2024-11-22 16:49:10.285030: Epoch 5603 +2024-11-22 16:49:10.285141: Current learning rate: 0.00338 +2024-11-22 16:49:29.311526: train_loss -0.7999 +2024-11-22 16:49:29.312626: val_loss -0.8011 +2024-11-22 16:49:29.312767: Pseudo dice [0.8672] +2024-11-22 16:49:29.312847: Epoch time: 19.03 s +2024-11-22 16:49:30.202916: +2024-11-22 16:49:30.203147: Epoch 5604 +2024-11-22 16:49:30.203256: Current learning rate: 0.00338 +2024-11-22 16:49:48.966123: train_loss -0.7954 +2024-11-22 16:49:48.966357: val_loss -0.7928 +2024-11-22 16:49:48.966434: Pseudo dice [0.8567] +2024-11-22 16:49:48.966507: Epoch time: 18.76 s +2024-11-22 16:49:49.851631: +2024-11-22 16:49:49.851853: Epoch 5605 +2024-11-22 16:49:49.851960: Current learning rate: 0.00338 +2024-11-22 16:50:08.110952: train_loss -0.8115 +2024-11-22 16:50:08.111257: val_loss -0.7858 +2024-11-22 16:50:08.111336: Pseudo dice [0.8472] +2024-11-22 16:50:08.111413: Epoch time: 18.26 s +2024-11-22 16:50:08.986629: +2024-11-22 16:50:08.986828: Epoch 5606 +2024-11-22 16:50:08.986938: Current learning rate: 0.00338 +2024-11-22 16:50:27.186546: train_loss -0.8049 +2024-11-22 16:50:27.186799: val_loss -0.7572 +2024-11-22 16:50:27.186876: Pseudo dice [0.8468] +2024-11-22 16:50:27.186957: Epoch time: 18.2 s +2024-11-22 16:50:28.084579: +2024-11-22 16:50:28.084821: Epoch 5607 +2024-11-22 16:50:28.084932: Current learning rate: 0.00337 +2024-11-22 16:50:46.753662: train_loss -0.8065 +2024-11-22 16:50:46.753885: val_loss -0.7713 +2024-11-22 16:50:46.754038: Pseudo dice [0.8424] +2024-11-22 16:50:46.754116: Epoch time: 18.67 s +2024-11-22 16:50:47.636409: +2024-11-22 16:50:47.636791: Epoch 5608 +2024-11-22 16:50:47.636912: Current learning rate: 0.00337 +2024-11-22 16:51:06.345894: train_loss -0.8017 +2024-11-22 16:51:06.348569: val_loss -0.7782 +2024-11-22 16:51:06.348696: Pseudo dice [0.8457] +2024-11-22 16:51:06.348779: Epoch time: 18.71 s +2024-11-22 16:51:07.332771: +2024-11-22 16:51:07.333000: Epoch 5609 +2024-11-22 16:51:07.333127: Current learning rate: 0.00337 +2024-11-22 16:51:25.799569: train_loss -0.7995 +2024-11-22 16:51:25.799793: val_loss -0.777 +2024-11-22 16:51:25.799871: Pseudo dice [0.8489] +2024-11-22 16:51:25.804198: Epoch time: 18.47 s +2024-11-22 16:51:26.849930: +2024-11-22 16:51:26.850143: Epoch 5610 +2024-11-22 16:51:26.850251: Current learning rate: 0.00337 +2024-11-22 16:51:45.081179: train_loss -0.8055 +2024-11-22 16:51:45.081431: val_loss -0.7645 +2024-11-22 16:51:45.081511: Pseudo dice [0.841] +2024-11-22 16:51:45.096698: Epoch time: 18.23 s +2024-11-22 16:51:45.973723: +2024-11-22 16:51:45.973949: Epoch 5611 +2024-11-22 16:51:45.974077: Current learning rate: 0.00337 +2024-11-22 16:52:04.027833: train_loss -0.792 +2024-11-22 16:52:04.028061: val_loss -0.7762 +2024-11-22 16:52:04.028135: Pseudo dice [0.8305] +2024-11-22 16:52:04.028210: Epoch time: 18.05 s +2024-11-22 16:52:05.264322: +2024-11-22 16:52:05.264641: Epoch 5612 +2024-11-22 16:52:05.264754: Current learning rate: 0.00337 +2024-11-22 16:52:23.117411: train_loss -0.7991 +2024-11-22 16:52:23.117662: val_loss -0.7631 +2024-11-22 16:52:23.117739: Pseudo dice [0.8538] +2024-11-22 16:52:23.117815: Epoch time: 17.85 s +2024-11-22 16:52:24.009968: +2024-11-22 16:52:24.010201: Epoch 5613 +2024-11-22 16:52:24.010314: Current learning rate: 0.00337 +2024-11-22 16:52:41.909623: train_loss -0.7973 +2024-11-22 16:52:41.909892: val_loss -0.7839 +2024-11-22 16:52:41.909968: Pseudo dice [0.8521] +2024-11-22 16:52:41.910055: Epoch time: 17.9 s +2024-11-22 16:52:42.795060: +2024-11-22 16:52:42.795289: Epoch 5614 +2024-11-22 16:52:42.795414: Current learning rate: 0.00337 +2024-11-22 16:52:59.911156: train_loss -0.7994 +2024-11-22 16:52:59.911382: val_loss -0.7705 +2024-11-22 16:52:59.911456: Pseudo dice [0.8552] +2024-11-22 16:52:59.911530: Epoch time: 17.12 s +2024-11-22 16:53:00.791295: +2024-11-22 16:53:00.791533: Epoch 5615 +2024-11-22 16:53:00.791646: Current learning rate: 0.00336 +2024-11-22 16:53:20.176894: train_loss -0.7987 +2024-11-22 16:53:20.179281: val_loss -0.7472 +2024-11-22 16:53:20.179408: Pseudo dice [0.8539] +2024-11-22 16:53:20.179486: Epoch time: 19.39 s +2024-11-22 16:53:21.375254: +2024-11-22 16:53:21.375479: Epoch 5616 +2024-11-22 16:53:21.375590: Current learning rate: 0.00336 +2024-11-22 16:53:40.038747: train_loss -0.8058 +2024-11-22 16:53:40.039055: val_loss -0.7976 +2024-11-22 16:53:40.039137: Pseudo dice [0.8595] +2024-11-22 16:53:40.039219: Epoch time: 18.66 s +2024-11-22 16:53:40.919929: +2024-11-22 16:53:40.920154: Epoch 5617 +2024-11-22 16:53:40.920263: Current learning rate: 0.00336 +2024-11-22 16:53:58.957912: train_loss -0.8058 +2024-11-22 16:53:58.958211: val_loss -0.785 +2024-11-22 16:53:58.958287: Pseudo dice [0.8416] +2024-11-22 16:53:58.958365: Epoch time: 18.04 s +2024-11-22 16:53:59.835323: +2024-11-22 16:53:59.835512: Epoch 5618 +2024-11-22 16:53:59.835625: Current learning rate: 0.00336 +2024-11-22 16:54:18.408363: train_loss -0.7968 +2024-11-22 16:54:18.408614: val_loss -0.7928 +2024-11-22 16:54:18.408700: Pseudo dice [0.8565] +2024-11-22 16:54:18.408775: Epoch time: 18.57 s +2024-11-22 16:54:19.316359: +2024-11-22 16:54:19.316599: Epoch 5619 +2024-11-22 16:54:19.316720: Current learning rate: 0.00336 +2024-11-22 16:54:37.151582: train_loss -0.8008 +2024-11-22 16:54:37.151798: val_loss -0.7642 +2024-11-22 16:54:37.151871: Pseudo dice [0.838] +2024-11-22 16:54:37.151944: Epoch time: 17.84 s +2024-11-22 16:54:38.028962: +2024-11-22 16:54:38.029196: Epoch 5620 +2024-11-22 16:54:38.029315: Current learning rate: 0.00336 +2024-11-22 16:54:57.586123: train_loss -0.8027 +2024-11-22 16:54:57.586333: val_loss -0.7983 +2024-11-22 16:54:57.586401: Pseudo dice [0.8581] +2024-11-22 16:54:57.586476: Epoch time: 19.56 s +2024-11-22 16:54:58.537930: +2024-11-22 16:54:58.538236: Epoch 5621 +2024-11-22 16:54:58.538348: Current learning rate: 0.00336 +2024-11-22 16:55:16.390494: train_loss -0.8018 +2024-11-22 16:55:16.390743: val_loss -0.7595 +2024-11-22 16:55:16.390818: Pseudo dice [0.8282] +2024-11-22 16:55:16.390898: Epoch time: 17.85 s +2024-11-22 16:55:17.370109: +2024-11-22 16:55:17.370315: Epoch 5622 +2024-11-22 16:55:17.370419: Current learning rate: 0.00336 +2024-11-22 16:55:35.357142: train_loss -0.7948 +2024-11-22 16:55:35.357359: val_loss -0.7852 +2024-11-22 16:55:35.357438: Pseudo dice [0.8421] +2024-11-22 16:55:35.357515: Epoch time: 17.99 s +2024-11-22 16:55:36.309399: +2024-11-22 16:55:36.309606: Epoch 5623 +2024-11-22 16:55:36.309716: Current learning rate: 0.00335 +2024-11-22 16:55:54.824999: train_loss -0.7852 +2024-11-22 16:55:54.827825: val_loss -0.7647 +2024-11-22 16:55:54.827918: Pseudo dice [0.8474] +2024-11-22 16:55:54.828002: Epoch time: 18.52 s +2024-11-22 16:55:56.098439: +2024-11-22 16:55:56.098748: Epoch 5624 +2024-11-22 16:55:56.098864: Current learning rate: 0.00335 +2024-11-22 16:56:14.148892: train_loss -0.7976 +2024-11-22 16:56:14.149176: val_loss -0.8035 +2024-11-22 16:56:14.149255: Pseudo dice [0.8485] +2024-11-22 16:56:14.149338: Epoch time: 18.05 s +2024-11-22 16:56:15.035517: +2024-11-22 16:56:15.035769: Epoch 5625 +2024-11-22 16:56:15.035881: Current learning rate: 0.00335 +2024-11-22 16:56:32.712952: train_loss -0.794 +2024-11-22 16:56:32.713194: val_loss -0.7497 +2024-11-22 16:56:32.713269: Pseudo dice [0.8523] +2024-11-22 16:56:32.713343: Epoch time: 17.68 s +2024-11-22 16:56:33.728009: +2024-11-22 16:56:33.728258: Epoch 5626 +2024-11-22 16:56:33.728369: Current learning rate: 0.00335 +2024-11-22 16:56:52.756444: train_loss -0.7936 +2024-11-22 16:56:52.756677: val_loss -0.7713 +2024-11-22 16:56:52.756753: Pseudo dice [0.8492] +2024-11-22 16:56:52.756827: Epoch time: 19.03 s +2024-11-22 16:56:53.640256: +2024-11-22 16:56:53.640473: Epoch 5627 +2024-11-22 16:56:53.640582: Current learning rate: 0.00335 +2024-11-22 16:57:11.144237: train_loss -0.8015 +2024-11-22 16:57:11.144469: val_loss -0.7563 +2024-11-22 16:57:11.144542: Pseudo dice [0.8395] +2024-11-22 16:57:11.144621: Epoch time: 17.5 s +2024-11-22 16:57:12.024964: +2024-11-22 16:57:12.025187: Epoch 5628 +2024-11-22 16:57:12.025296: Current learning rate: 0.00335 +2024-11-22 16:57:31.366502: train_loss -0.8013 +2024-11-22 16:57:31.366742: val_loss -0.7649 +2024-11-22 16:57:31.366814: Pseudo dice [0.8522] +2024-11-22 16:57:31.369067: Epoch time: 19.34 s +2024-11-22 16:57:32.416974: +2024-11-22 16:57:32.417186: Epoch 5629 +2024-11-22 16:57:32.417298: Current learning rate: 0.00335 +2024-11-22 16:57:50.615274: train_loss -0.7988 +2024-11-22 16:57:50.615513: val_loss -0.763 +2024-11-22 16:57:50.615593: Pseudo dice [0.8493] +2024-11-22 16:57:50.615669: Epoch time: 18.2 s +2024-11-22 16:57:51.534884: +2024-11-22 16:57:51.535110: Epoch 5630 +2024-11-22 16:57:51.535218: Current learning rate: 0.00335 +2024-11-22 16:58:10.279519: train_loss -0.7984 +2024-11-22 16:58:10.279753: val_loss -0.8002 +2024-11-22 16:58:10.279831: Pseudo dice [0.8322] +2024-11-22 16:58:10.279909: Epoch time: 18.75 s +2024-11-22 16:58:11.166413: +2024-11-22 16:58:11.166640: Epoch 5631 +2024-11-22 16:58:11.166745: Current learning rate: 0.00334 +2024-11-22 16:58:29.477621: train_loss -0.7948 +2024-11-22 16:58:29.477856: val_loss -0.762 +2024-11-22 16:58:29.477941: Pseudo dice [0.8477] +2024-11-22 16:58:29.478030: Epoch time: 18.31 s +2024-11-22 16:58:30.367236: +2024-11-22 16:58:30.367456: Epoch 5632 +2024-11-22 16:58:30.367573: Current learning rate: 0.00334 +2024-11-22 16:58:48.464351: train_loss -0.7853 +2024-11-22 16:58:48.464570: val_loss -0.7954 +2024-11-22 16:58:48.464643: Pseudo dice [0.8672] +2024-11-22 16:58:48.464720: Epoch time: 18.1 s +2024-11-22 16:58:49.496652: +2024-11-22 16:58:49.496844: Epoch 5633 +2024-11-22 16:58:49.496957: Current learning rate: 0.00334 +2024-11-22 16:59:08.039489: train_loss -0.7954 +2024-11-22 16:59:08.039706: val_loss -0.77 +2024-11-22 16:59:08.039777: Pseudo dice [0.8675] +2024-11-22 16:59:08.039851: Epoch time: 18.54 s +2024-11-22 16:59:09.041114: +2024-11-22 16:59:09.041316: Epoch 5634 +2024-11-22 16:59:09.041427: Current learning rate: 0.00334 +2024-11-22 16:59:26.793777: train_loss -0.8043 +2024-11-22 16:59:26.793989: val_loss -0.7587 +2024-11-22 16:59:26.794072: Pseudo dice [0.8523] +2024-11-22 16:59:26.794144: Epoch time: 17.75 s +2024-11-22 16:59:27.671290: +2024-11-22 16:59:27.671521: Epoch 5635 +2024-11-22 16:59:27.671641: Current learning rate: 0.00334 +2024-11-22 16:59:47.299750: train_loss -0.7998 +2024-11-22 16:59:47.302215: val_loss -0.7801 +2024-11-22 16:59:47.302309: Pseudo dice [0.8412] +2024-11-22 16:59:47.302405: Epoch time: 19.63 s +2024-11-22 16:59:48.603055: +2024-11-22 16:59:48.603308: Epoch 5636 +2024-11-22 16:59:48.603636: Current learning rate: 0.00334 +2024-11-22 17:00:06.972681: train_loss -0.8038 +2024-11-22 17:00:06.972944: val_loss -0.7731 +2024-11-22 17:00:06.973029: Pseudo dice [0.8505] +2024-11-22 17:00:06.973109: Epoch time: 18.37 s +2024-11-22 17:00:07.858212: +2024-11-22 17:00:07.858490: Epoch 5637 +2024-11-22 17:00:07.858601: Current learning rate: 0.00334 +2024-11-22 17:00:25.820644: train_loss -0.8012 +2024-11-22 17:00:25.820870: val_loss -0.7645 +2024-11-22 17:00:25.820948: Pseudo dice [0.8455] +2024-11-22 17:00:25.821034: Epoch time: 17.96 s +2024-11-22 17:00:26.714016: +2024-11-22 17:00:26.714229: Epoch 5638 +2024-11-22 17:00:26.714338: Current learning rate: 0.00334 +2024-11-22 17:00:44.825603: train_loss -0.8017 +2024-11-22 17:00:44.825904: val_loss -0.7698 +2024-11-22 17:00:44.825983: Pseudo dice [0.8421] +2024-11-22 17:00:44.826068: Epoch time: 18.11 s +2024-11-22 17:00:45.717930: +2024-11-22 17:00:45.718125: Epoch 5639 +2024-11-22 17:00:45.718236: Current learning rate: 0.00333 +2024-11-22 17:01:03.976915: train_loss -0.8026 +2024-11-22 17:01:03.977170: val_loss -0.7895 +2024-11-22 17:01:03.977245: Pseudo dice [0.8671] +2024-11-22 17:01:03.977323: Epoch time: 18.26 s +2024-11-22 17:01:04.857538: +2024-11-22 17:01:04.857787: Epoch 5640 +2024-11-22 17:01:04.857903: Current learning rate: 0.00333 +2024-11-22 17:01:23.650882: train_loss -0.8004 +2024-11-22 17:01:23.651121: val_loss -0.7938 +2024-11-22 17:01:23.651207: Pseudo dice [0.856] +2024-11-22 17:01:23.651309: Epoch time: 18.79 s +2024-11-22 17:01:24.542537: +2024-11-22 17:01:24.542800: Epoch 5641 +2024-11-22 17:01:24.542916: Current learning rate: 0.00333 +2024-11-22 17:01:42.470178: train_loss -0.802 +2024-11-22 17:01:42.470425: val_loss -0.7792 +2024-11-22 17:01:42.470505: Pseudo dice [0.8542] +2024-11-22 17:01:42.470579: Epoch time: 17.93 s +2024-11-22 17:01:43.504569: +2024-11-22 17:01:43.504760: Epoch 5642 +2024-11-22 17:01:43.504871: Current learning rate: 0.00333 +2024-11-22 17:02:01.500694: train_loss -0.8038 +2024-11-22 17:02:01.500945: val_loss -0.7818 +2024-11-22 17:02:01.501025: Pseudo dice [0.8525] +2024-11-22 17:02:01.501101: Epoch time: 18.0 s +2024-11-22 17:02:02.393447: +2024-11-22 17:02:02.393680: Epoch 5643 +2024-11-22 17:02:02.393793: Current learning rate: 0.00333 +2024-11-22 17:02:20.727497: train_loss -0.7977 +2024-11-22 17:02:20.727710: val_loss -0.7691 +2024-11-22 17:02:20.727784: Pseudo dice [0.8595] +2024-11-22 17:02:20.727858: Epoch time: 18.33 s +2024-11-22 17:02:21.716495: +2024-11-22 17:02:21.716737: Epoch 5644 +2024-11-22 17:02:21.716846: Current learning rate: 0.00333 +2024-11-22 17:02:40.078379: train_loss -0.7932 +2024-11-22 17:02:40.078597: val_loss -0.7472 +2024-11-22 17:02:40.078676: Pseudo dice [0.8332] +2024-11-22 17:02:40.078751: Epoch time: 18.36 s +2024-11-22 17:02:40.954484: +2024-11-22 17:02:40.954699: Epoch 5645 +2024-11-22 17:02:40.954819: Current learning rate: 0.00333 +2024-11-22 17:02:59.525266: train_loss -0.7986 +2024-11-22 17:02:59.525544: val_loss -0.7818 +2024-11-22 17:02:59.525624: Pseudo dice [0.8625] +2024-11-22 17:02:59.525703: Epoch time: 18.57 s +2024-11-22 17:03:00.403183: +2024-11-22 17:03:00.403409: Epoch 5646 +2024-11-22 17:03:00.403519: Current learning rate: 0.00333 +2024-11-22 17:03:19.793232: train_loss -0.806 +2024-11-22 17:03:19.793485: val_loss -0.7786 +2024-11-22 17:03:19.793563: Pseudo dice [0.8539] +2024-11-22 17:03:19.793645: Epoch time: 19.39 s +2024-11-22 17:03:20.681237: +2024-11-22 17:03:20.681446: Epoch 5647 +2024-11-22 17:03:20.681559: Current learning rate: 0.00332 +2024-11-22 17:03:38.669729: train_loss -0.8059 +2024-11-22 17:03:38.670196: val_loss -0.7986 +2024-11-22 17:03:38.670295: Pseudo dice [0.8547] +2024-11-22 17:03:38.670369: Epoch time: 17.99 s +2024-11-22 17:03:39.552087: +2024-11-22 17:03:39.552325: Epoch 5648 +2024-11-22 17:03:39.552432: Current learning rate: 0.00332 +2024-11-22 17:03:57.844073: train_loss -0.8107 +2024-11-22 17:03:57.844290: val_loss -0.7889 +2024-11-22 17:03:57.844364: Pseudo dice [0.8681] +2024-11-22 17:03:57.865923: Epoch time: 18.29 s +2024-11-22 17:03:58.752440: +2024-11-22 17:03:58.752667: Epoch 5649 +2024-11-22 17:03:58.752801: Current learning rate: 0.00332 +2024-11-22 17:04:17.519680: train_loss -0.8008 +2024-11-22 17:04:17.519901: val_loss -0.7659 +2024-11-22 17:04:17.519974: Pseudo dice [0.8676] +2024-11-22 17:04:17.520053: Epoch time: 18.77 s +2024-11-22 17:04:17.824272: Yayy! New best EMA pseudo Dice: 0.8551 +2024-11-22 17:04:18.983996: +2024-11-22 17:04:18.984255: Epoch 5650 +2024-11-22 17:04:18.984363: Current learning rate: 0.00332 +2024-11-22 17:04:36.818905: train_loss -0.7992 +2024-11-22 17:04:36.819161: val_loss -0.7734 +2024-11-22 17:04:36.819239: Pseudo dice [0.85] +2024-11-22 17:04:36.819316: Epoch time: 17.84 s +2024-11-22 17:04:37.707756: +2024-11-22 17:04:37.708001: Epoch 5651 +2024-11-22 17:04:37.708120: Current learning rate: 0.00332 +2024-11-22 17:04:55.970828: train_loss -0.8069 +2024-11-22 17:04:55.971070: val_loss -0.7776 +2024-11-22 17:04:55.971146: Pseudo dice [0.8353] +2024-11-22 17:04:55.971218: Epoch time: 18.26 s +2024-11-22 17:04:56.872278: +2024-11-22 17:04:56.872485: Epoch 5652 +2024-11-22 17:04:56.872596: Current learning rate: 0.00332 +2024-11-22 17:05:14.636315: train_loss -0.7973 +2024-11-22 17:05:14.636531: val_loss -0.7504 +2024-11-22 17:05:14.636606: Pseudo dice [0.8547] +2024-11-22 17:05:14.636686: Epoch time: 17.76 s +2024-11-22 17:05:15.523243: +2024-11-22 17:05:15.523458: Epoch 5653 +2024-11-22 17:05:15.523566: Current learning rate: 0.00332 +2024-11-22 17:05:35.510321: train_loss -0.798 +2024-11-22 17:05:35.510586: val_loss -0.7581 +2024-11-22 17:05:35.510664: Pseudo dice [0.8413] +2024-11-22 17:05:35.510742: Epoch time: 19.99 s +2024-11-22 17:05:36.404750: +2024-11-22 17:05:36.404969: Epoch 5654 +2024-11-22 17:05:36.405088: Current learning rate: 0.00332 +2024-11-22 17:05:54.750086: train_loss -0.8021 +2024-11-22 17:05:54.750330: val_loss -0.775 +2024-11-22 17:05:54.750407: Pseudo dice [0.8606] +2024-11-22 17:05:54.750488: Epoch time: 18.35 s +2024-11-22 17:05:55.738904: +2024-11-22 17:05:55.739124: Epoch 5655 +2024-11-22 17:05:55.739240: Current learning rate: 0.00331 +2024-11-22 17:06:14.432324: train_loss -0.8004 +2024-11-22 17:06:14.432590: val_loss -0.7647 +2024-11-22 17:06:14.432666: Pseudo dice [0.862] +2024-11-22 17:06:14.432736: Epoch time: 18.69 s +2024-11-22 17:06:15.324134: +2024-11-22 17:06:15.324357: Epoch 5656 +2024-11-22 17:06:15.324471: Current learning rate: 0.00331 +2024-11-22 17:06:34.418504: train_loss -0.8022 +2024-11-22 17:06:34.418724: val_loss -0.7447 +2024-11-22 17:06:34.418811: Pseudo dice [0.8518] +2024-11-22 17:06:34.418891: Epoch time: 19.1 s +2024-11-22 17:06:35.306466: +2024-11-22 17:06:35.306688: Epoch 5657 +2024-11-22 17:06:35.306802: Current learning rate: 0.00331 +2024-11-22 17:06:55.081361: train_loss -0.8015 +2024-11-22 17:06:55.081581: val_loss -0.7911 +2024-11-22 17:06:55.081656: Pseudo dice [0.8549] +2024-11-22 17:06:55.081730: Epoch time: 19.78 s +2024-11-22 17:06:55.961874: +2024-11-22 17:06:55.962101: Epoch 5658 +2024-11-22 17:06:55.962219: Current learning rate: 0.00331 +2024-11-22 17:07:14.471957: train_loss -0.8008 +2024-11-22 17:07:14.472479: val_loss -0.791 +2024-11-22 17:07:14.472576: Pseudo dice [0.8574] +2024-11-22 17:07:14.472652: Epoch time: 18.51 s +2024-11-22 17:07:15.358081: +2024-11-22 17:07:15.358315: Epoch 5659 +2024-11-22 17:07:15.358425: Current learning rate: 0.00331 +2024-11-22 17:07:33.027961: train_loss -0.8076 +2024-11-22 17:07:33.028188: val_loss -0.7633 +2024-11-22 17:07:33.028342: Pseudo dice [0.8575] +2024-11-22 17:07:33.028449: Epoch time: 17.67 s +2024-11-22 17:07:33.917779: +2024-11-22 17:07:33.918027: Epoch 5660 +2024-11-22 17:07:33.918136: Current learning rate: 0.00331 +2024-11-22 17:07:51.222356: train_loss -0.8115 +2024-11-22 17:07:51.222579: val_loss -0.7813 +2024-11-22 17:07:51.222655: Pseudo dice [0.8584] +2024-11-22 17:07:51.222729: Epoch time: 17.31 s +2024-11-22 17:07:52.109276: +2024-11-22 17:07:52.109504: Epoch 5661 +2024-11-22 17:07:52.109619: Current learning rate: 0.00331 +2024-11-22 17:08:11.140626: train_loss -0.799 +2024-11-22 17:08:11.141419: val_loss -0.765 +2024-11-22 17:08:11.141515: Pseudo dice [0.8556] +2024-11-22 17:08:11.141604: Epoch time: 19.03 s +2024-11-22 17:08:12.027821: +2024-11-22 17:08:12.028053: Epoch 5662 +2024-11-22 17:08:12.028163: Current learning rate: 0.00331 +2024-11-22 17:08:31.398627: train_loss -0.8051 +2024-11-22 17:08:31.398883: val_loss -0.7613 +2024-11-22 17:08:31.398960: Pseudo dice [0.8548] +2024-11-22 17:08:31.399045: Epoch time: 19.37 s +2024-11-22 17:08:32.287567: +2024-11-22 17:08:32.287781: Epoch 5663 +2024-11-22 17:08:32.287890: Current learning rate: 0.0033 +2024-11-22 17:08:50.015278: train_loss -0.7954 +2024-11-22 17:08:50.015501: val_loss -0.7477 +2024-11-22 17:08:50.015581: Pseudo dice [0.8347] +2024-11-22 17:08:50.015655: Epoch time: 17.73 s +2024-11-22 17:08:50.932677: +2024-11-22 17:08:50.932897: Epoch 5664 +2024-11-22 17:08:50.933012: Current learning rate: 0.0033 +2024-11-22 17:09:09.172427: train_loss -0.8044 +2024-11-22 17:09:09.172659: val_loss -0.8032 +2024-11-22 17:09:09.172733: Pseudo dice [0.8773] +2024-11-22 17:09:09.172809: Epoch time: 18.24 s +2024-11-22 17:09:09.172870: Yayy! New best EMA pseudo Dice: 0.8552 +2024-11-22 17:09:10.466112: +2024-11-22 17:09:10.466326: Epoch 5665 +2024-11-22 17:09:10.466434: Current learning rate: 0.0033 +2024-11-22 17:09:29.372731: train_loss -0.7724 +2024-11-22 17:09:29.372980: val_loss -0.7276 +2024-11-22 17:09:29.373066: Pseudo dice [0.8356] +2024-11-22 17:09:29.378318: Epoch time: 18.91 s +2024-11-22 17:09:30.381641: +2024-11-22 17:09:30.381857: Epoch 5666 +2024-11-22 17:09:30.381968: Current learning rate: 0.0033 +2024-11-22 17:09:48.412685: train_loss -0.7614 +2024-11-22 17:09:48.412909: val_loss -0.7673 +2024-11-22 17:09:48.413003: Pseudo dice [0.8439] +2024-11-22 17:09:48.413097: Epoch time: 18.03 s +2024-11-22 17:09:49.338556: +2024-11-22 17:09:49.338798: Epoch 5667 +2024-11-22 17:09:49.338906: Current learning rate: 0.0033 +2024-11-22 17:10:07.877981: train_loss -0.7949 +2024-11-22 17:10:07.878260: val_loss -0.7758 +2024-11-22 17:10:07.878338: Pseudo dice [0.8399] +2024-11-22 17:10:07.878414: Epoch time: 18.54 s +2024-11-22 17:10:08.762547: +2024-11-22 17:10:08.762743: Epoch 5668 +2024-11-22 17:10:08.762848: Current learning rate: 0.0033 +2024-11-22 17:10:28.235081: train_loss -0.7893 +2024-11-22 17:10:28.235290: val_loss -0.7706 +2024-11-22 17:10:28.235367: Pseudo dice [0.8517] +2024-11-22 17:10:28.235465: Epoch time: 19.47 s +2024-11-22 17:10:29.270165: +2024-11-22 17:10:29.270390: Epoch 5669 +2024-11-22 17:10:29.270507: Current learning rate: 0.0033 +2024-11-22 17:10:47.626473: train_loss -0.7929 +2024-11-22 17:10:47.626710: val_loss -0.7531 +2024-11-22 17:10:47.626783: Pseudo dice [0.8413] +2024-11-22 17:10:47.626908: Epoch time: 18.36 s +2024-11-22 17:10:48.880867: +2024-11-22 17:10:48.881113: Epoch 5670 +2024-11-22 17:10:48.881228: Current learning rate: 0.00329 +2024-11-22 17:11:07.020299: train_loss -0.7842 +2024-11-22 17:11:07.020539: val_loss -0.7604 +2024-11-22 17:11:07.020614: Pseudo dice [0.8259] +2024-11-22 17:11:07.020686: Epoch time: 18.14 s +2024-11-22 17:11:07.913455: +2024-11-22 17:11:07.913702: Epoch 5671 +2024-11-22 17:11:07.913811: Current learning rate: 0.00329 +2024-11-22 17:11:24.768269: train_loss -0.7827 +2024-11-22 17:11:24.768484: val_loss -0.7614 +2024-11-22 17:11:24.768561: Pseudo dice [0.8406] +2024-11-22 17:11:24.768636: Epoch time: 16.86 s +2024-11-22 17:11:25.654285: +2024-11-22 17:11:25.654550: Epoch 5672 +2024-11-22 17:11:25.654661: Current learning rate: 0.00329 +2024-11-22 17:11:44.745264: train_loss -0.7782 +2024-11-22 17:11:44.745512: val_loss -0.7867 +2024-11-22 17:11:44.745655: Pseudo dice [0.8514] +2024-11-22 17:11:44.745738: Epoch time: 19.09 s +2024-11-22 17:11:45.632210: +2024-11-22 17:11:45.632432: Epoch 5673 +2024-11-22 17:11:45.632542: Current learning rate: 0.00329 +2024-11-22 17:12:04.124906: train_loss -0.7871 +2024-11-22 17:12:04.125134: val_loss -0.7854 +2024-11-22 17:12:04.125206: Pseudo dice [0.8639] +2024-11-22 17:12:04.125279: Epoch time: 18.49 s +2024-11-22 17:12:05.012469: +2024-11-22 17:12:05.012731: Epoch 5674 +2024-11-22 17:12:05.012867: Current learning rate: 0.00329 +2024-11-22 17:12:22.895823: train_loss -0.7939 +2024-11-22 17:12:22.896088: val_loss -0.7496 +2024-11-22 17:12:22.896161: Pseudo dice [0.8548] +2024-11-22 17:12:22.896242: Epoch time: 17.88 s +2024-11-22 17:12:23.821899: +2024-11-22 17:12:23.822125: Epoch 5675 +2024-11-22 17:12:23.822235: Current learning rate: 0.00329 +2024-11-22 17:12:42.530899: train_loss -0.7827 +2024-11-22 17:12:42.531135: val_loss -0.7607 +2024-11-22 17:12:42.531212: Pseudo dice [0.8355] +2024-11-22 17:12:42.531288: Epoch time: 18.71 s +2024-11-22 17:12:43.574253: +2024-11-22 17:12:43.574608: Epoch 5676 +2024-11-22 17:12:43.574720: Current learning rate: 0.00329 +2024-11-22 17:13:02.426744: train_loss -0.7885 +2024-11-22 17:13:02.426969: val_loss -0.7923 +2024-11-22 17:13:02.427058: Pseudo dice [0.8604] +2024-11-22 17:13:02.427138: Epoch time: 18.85 s +2024-11-22 17:13:03.481421: +2024-11-22 17:13:03.481642: Epoch 5677 +2024-11-22 17:13:03.481791: Current learning rate: 0.00329 +2024-11-22 17:13:21.384131: train_loss -0.7912 +2024-11-22 17:13:21.384343: val_loss -0.766 +2024-11-22 17:13:21.384418: Pseudo dice [0.8379] +2024-11-22 17:13:21.384495: Epoch time: 17.9 s +2024-11-22 17:13:22.272386: +2024-11-22 17:13:22.272587: Epoch 5678 +2024-11-22 17:13:22.272693: Current learning rate: 0.00328 +2024-11-22 17:13:40.824393: train_loss -0.8017 +2024-11-22 17:13:40.824606: val_loss -0.768 +2024-11-22 17:13:40.824680: Pseudo dice [0.8602] +2024-11-22 17:13:40.824755: Epoch time: 18.55 s +2024-11-22 17:13:41.707999: +2024-11-22 17:13:41.708225: Epoch 5679 +2024-11-22 17:13:41.708339: Current learning rate: 0.00328 +2024-11-22 17:13:59.312374: train_loss -0.8023 +2024-11-22 17:13:59.312585: val_loss -0.7569 +2024-11-22 17:13:59.312659: Pseudo dice [0.8356] +2024-11-22 17:13:59.312731: Epoch time: 17.61 s +2024-11-22 17:14:00.193150: +2024-11-22 17:14:00.193367: Epoch 5680 +2024-11-22 17:14:00.193474: Current learning rate: 0.00328 +2024-11-22 17:14:19.428112: train_loss -0.8096 +2024-11-22 17:14:19.428348: val_loss -0.7587 +2024-11-22 17:14:19.428425: Pseudo dice [0.8318] +2024-11-22 17:14:19.428503: Epoch time: 19.24 s +2024-11-22 17:14:20.306252: +2024-11-22 17:14:20.306464: Epoch 5681 +2024-11-22 17:14:20.306570: Current learning rate: 0.00328 +2024-11-22 17:14:39.149963: train_loss -0.7999 +2024-11-22 17:14:39.150432: val_loss -0.7598 +2024-11-22 17:14:39.150533: Pseudo dice [0.8434] +2024-11-22 17:14:39.150610: Epoch time: 18.84 s +2024-11-22 17:14:40.040289: +2024-11-22 17:14:40.040520: Epoch 5682 +2024-11-22 17:14:40.040639: Current learning rate: 0.00328 +2024-11-22 17:14:59.295225: train_loss -0.7947 +2024-11-22 17:14:59.295506: val_loss -0.7816 +2024-11-22 17:14:59.295581: Pseudo dice [0.8363] +2024-11-22 17:14:59.295655: Epoch time: 19.26 s +2024-11-22 17:15:00.185863: +2024-11-22 17:15:00.186110: Epoch 5683 +2024-11-22 17:15:00.186218: Current learning rate: 0.00328 +2024-11-22 17:15:18.914804: train_loss -0.804 +2024-11-22 17:15:18.915024: val_loss -0.7927 +2024-11-22 17:15:18.915098: Pseudo dice [0.8545] +2024-11-22 17:15:18.915170: Epoch time: 18.73 s +2024-11-22 17:15:19.931679: +2024-11-22 17:15:19.931904: Epoch 5684 +2024-11-22 17:15:19.932022: Current learning rate: 0.00328 +2024-11-22 17:15:37.931232: train_loss -0.803 +2024-11-22 17:15:37.931552: val_loss -0.7413 +2024-11-22 17:15:37.931637: Pseudo dice [0.8562] +2024-11-22 17:15:37.931720: Epoch time: 18.0 s +2024-11-22 17:15:38.928546: +2024-11-22 17:15:38.928767: Epoch 5685 +2024-11-22 17:15:38.928875: Current learning rate: 0.00328 +2024-11-22 17:15:58.022927: train_loss -0.7998 +2024-11-22 17:15:58.023336: val_loss -0.7821 +2024-11-22 17:15:58.023431: Pseudo dice [0.8522] +2024-11-22 17:15:58.023528: Epoch time: 19.1 s +2024-11-22 17:15:58.909175: +2024-11-22 17:15:58.909392: Epoch 5686 +2024-11-22 17:15:58.909503: Current learning rate: 0.00327 +2024-11-22 17:16:17.018379: train_loss -0.8036 +2024-11-22 17:16:17.028836: val_loss -0.7755 +2024-11-22 17:16:17.029027: Pseudo dice [0.8575] +2024-11-22 17:16:17.029110: Epoch time: 18.11 s +2024-11-22 17:16:18.077506: +2024-11-22 17:16:18.077731: Epoch 5687 +2024-11-22 17:16:18.077853: Current learning rate: 0.00327 +2024-11-22 17:16:37.113279: train_loss -0.7977 +2024-11-22 17:16:37.113495: val_loss -0.805 +2024-11-22 17:16:37.113631: Pseudo dice [0.8567] +2024-11-22 17:16:37.113707: Epoch time: 19.04 s +2024-11-22 17:16:37.996073: +2024-11-22 17:16:37.996295: Epoch 5688 +2024-11-22 17:16:37.996406: Current learning rate: 0.00327 +2024-11-22 17:16:57.217738: train_loss -0.8055 +2024-11-22 17:16:57.217979: val_loss -0.7615 +2024-11-22 17:16:57.218063: Pseudo dice [0.8492] +2024-11-22 17:16:57.218140: Epoch time: 19.22 s +2024-11-22 17:16:58.101504: +2024-11-22 17:16:58.101732: Epoch 5689 +2024-11-22 17:16:58.101846: Current learning rate: 0.00327 +2024-11-22 17:17:16.092751: train_loss -0.8026 +2024-11-22 17:17:16.092975: val_loss -0.7984 +2024-11-22 17:17:16.093054: Pseudo dice [0.8557] +2024-11-22 17:17:16.093132: Epoch time: 17.99 s +2024-11-22 17:17:16.981740: +2024-11-22 17:17:16.982002: Epoch 5690 +2024-11-22 17:17:16.982112: Current learning rate: 0.00327 +2024-11-22 17:17:35.830552: train_loss -0.8014 +2024-11-22 17:17:35.830761: val_loss -0.7862 +2024-11-22 17:17:35.830835: Pseudo dice [0.8517] +2024-11-22 17:17:35.830909: Epoch time: 18.85 s +2024-11-22 17:17:36.719052: +2024-11-22 17:17:36.719270: Epoch 5691 +2024-11-22 17:17:36.719378: Current learning rate: 0.00327 +2024-11-22 17:17:54.680052: train_loss -0.7984 +2024-11-22 17:17:54.680275: val_loss -0.7659 +2024-11-22 17:17:54.680360: Pseudo dice [0.8375] +2024-11-22 17:17:54.680446: Epoch time: 17.96 s +2024-11-22 17:17:55.567106: +2024-11-22 17:17:55.567360: Epoch 5692 +2024-11-22 17:17:55.567483: Current learning rate: 0.00327 +2024-11-22 17:18:13.650037: train_loss -0.8056 +2024-11-22 17:18:13.650280: val_loss -0.7772 +2024-11-22 17:18:13.650354: Pseudo dice [0.8477] +2024-11-22 17:18:13.650433: Epoch time: 18.08 s +2024-11-22 17:18:14.893332: +2024-11-22 17:18:14.893569: Epoch 5693 +2024-11-22 17:18:14.893676: Current learning rate: 0.00327 +2024-11-22 17:18:33.792558: train_loss -0.8056 +2024-11-22 17:18:33.795041: val_loss -0.7499 +2024-11-22 17:18:33.795196: Pseudo dice [0.8455] +2024-11-22 17:18:33.795276: Epoch time: 18.9 s +2024-11-22 17:18:34.687399: +2024-11-22 17:18:34.687625: Epoch 5694 +2024-11-22 17:18:34.687734: Current learning rate: 0.00326 +2024-11-22 17:18:52.680240: train_loss -0.7988 +2024-11-22 17:18:52.680533: val_loss -0.7703 +2024-11-22 17:18:52.680613: Pseudo dice [0.8408] +2024-11-22 17:18:52.680689: Epoch time: 17.99 s +2024-11-22 17:18:53.571898: +2024-11-22 17:18:53.572145: Epoch 5695 +2024-11-22 17:18:53.572257: Current learning rate: 0.00326 +2024-11-22 17:19:13.315456: train_loss -0.7962 +2024-11-22 17:19:13.315679: val_loss -0.7575 +2024-11-22 17:19:13.315758: Pseudo dice [0.8346] +2024-11-22 17:19:13.315839: Epoch time: 19.74 s +2024-11-22 17:19:14.298617: +2024-11-22 17:19:14.298857: Epoch 5696 +2024-11-22 17:19:14.298968: Current learning rate: 0.00326 +2024-11-22 17:19:32.647784: train_loss -0.8035 +2024-11-22 17:19:32.648010: val_loss -0.7632 +2024-11-22 17:19:32.648082: Pseudo dice [0.8441] +2024-11-22 17:19:32.648154: Epoch time: 18.35 s +2024-11-22 17:19:33.538327: +2024-11-22 17:19:33.538579: Epoch 5697 +2024-11-22 17:19:33.538698: Current learning rate: 0.00326 +2024-11-22 17:19:52.218865: train_loss -0.8048 +2024-11-22 17:19:52.219092: val_loss -0.7709 +2024-11-22 17:19:52.221369: Pseudo dice [0.8592] +2024-11-22 17:19:52.221486: Epoch time: 18.68 s +2024-11-22 17:19:53.174952: +2024-11-22 17:19:53.175172: Epoch 5698 +2024-11-22 17:19:53.175279: Current learning rate: 0.00326 +2024-11-22 17:20:12.776795: train_loss -0.8026 +2024-11-22 17:20:12.777016: val_loss -0.7705 +2024-11-22 17:20:12.777093: Pseudo dice [0.8382] +2024-11-22 17:20:12.777169: Epoch time: 19.6 s +2024-11-22 17:20:13.657668: +2024-11-22 17:20:13.657871: Epoch 5699 +2024-11-22 17:20:13.657980: Current learning rate: 0.00326 +2024-11-22 17:20:32.202285: train_loss -0.795 +2024-11-22 17:20:32.202532: val_loss -0.7515 +2024-11-22 17:20:32.206908: Pseudo dice [0.8396] +2024-11-22 17:20:32.207078: Epoch time: 18.55 s +2024-11-22 17:20:33.403900: +2024-11-22 17:20:33.404119: Epoch 5700 +2024-11-22 17:20:33.404234: Current learning rate: 0.00326 +2024-11-22 17:20:51.982733: train_loss -0.8081 +2024-11-22 17:20:51.982943: val_loss -0.7834 +2024-11-22 17:20:51.983031: Pseudo dice [0.8495] +2024-11-22 17:20:51.983108: Epoch time: 18.58 s +2024-11-22 17:20:52.866141: +2024-11-22 17:20:52.866371: Epoch 5701 +2024-11-22 17:20:52.866482: Current learning rate: 0.00326 +2024-11-22 17:21:11.517052: train_loss -0.7998 +2024-11-22 17:21:11.519464: val_loss -0.7675 +2024-11-22 17:21:11.519558: Pseudo dice [0.8408] +2024-11-22 17:21:11.519634: Epoch time: 18.65 s +2024-11-22 17:21:12.444269: +2024-11-22 17:21:12.444595: Epoch 5702 +2024-11-22 17:21:12.444707: Current learning rate: 0.00325 +2024-11-22 17:21:30.939973: train_loss -0.8062 +2024-11-22 17:21:30.940183: val_loss -0.7809 +2024-11-22 17:21:30.940261: Pseudo dice [0.8558] +2024-11-22 17:21:30.940338: Epoch time: 18.5 s +2024-11-22 17:21:31.820841: +2024-11-22 17:21:31.821051: Epoch 5703 +2024-11-22 17:21:31.821160: Current learning rate: 0.00325 +2024-11-22 17:21:49.799868: train_loss -0.8006 +2024-11-22 17:21:49.800117: val_loss -0.7961 +2024-11-22 17:21:49.800192: Pseudo dice [0.8611] +2024-11-22 17:21:49.800272: Epoch time: 17.98 s +2024-11-22 17:21:50.687027: +2024-11-22 17:21:50.687223: Epoch 5704 +2024-11-22 17:21:50.687330: Current learning rate: 0.00325 +2024-11-22 17:22:09.727576: train_loss -0.8012 +2024-11-22 17:22:09.728025: val_loss -0.7987 +2024-11-22 17:22:09.728149: Pseudo dice [0.8619] +2024-11-22 17:22:09.728223: Epoch time: 19.04 s +2024-11-22 17:22:10.619605: +2024-11-22 17:22:10.619846: Epoch 5705 +2024-11-22 17:22:10.619960: Current learning rate: 0.00325 +2024-11-22 17:22:30.247262: train_loss -0.8038 +2024-11-22 17:22:30.247519: val_loss -0.7675 +2024-11-22 17:22:30.247595: Pseudo dice [0.8401] +2024-11-22 17:22:30.247721: Epoch time: 19.63 s +2024-11-22 17:22:31.136059: +2024-11-22 17:22:31.136273: Epoch 5706 +2024-11-22 17:22:31.136381: Current learning rate: 0.00325 +2024-11-22 17:22:49.213624: train_loss -0.8093 +2024-11-22 17:22:49.213851: val_loss -0.751 +2024-11-22 17:22:49.213925: Pseudo dice [0.822] +2024-11-22 17:22:49.214006: Epoch time: 18.08 s +2024-11-22 17:22:50.109580: +2024-11-22 17:22:50.109918: Epoch 5707 +2024-11-22 17:22:50.110034: Current learning rate: 0.00325 +2024-11-22 17:23:08.235492: train_loss -0.7999 +2024-11-22 17:23:08.236577: val_loss -0.7758 +2024-11-22 17:23:08.236667: Pseudo dice [0.857] +2024-11-22 17:23:08.236742: Epoch time: 18.13 s +2024-11-22 17:23:09.199878: +2024-11-22 17:23:09.200098: Epoch 5708 +2024-11-22 17:23:09.200204: Current learning rate: 0.00325 +2024-11-22 17:23:28.345932: train_loss -0.7909 +2024-11-22 17:23:28.346156: val_loss -0.7661 +2024-11-22 17:23:28.346230: Pseudo dice [0.8383] +2024-11-22 17:23:28.346304: Epoch time: 19.15 s +2024-11-22 17:23:29.241730: +2024-11-22 17:23:29.241943: Epoch 5709 +2024-11-22 17:23:29.242063: Current learning rate: 0.00325 +2024-11-22 17:23:48.799747: train_loss -0.8046 +2024-11-22 17:23:48.799965: val_loss -0.7827 +2024-11-22 17:23:48.800047: Pseudo dice [0.845] +2024-11-22 17:23:48.800121: Epoch time: 19.56 s +2024-11-22 17:23:49.681076: +2024-11-22 17:23:49.681281: Epoch 5710 +2024-11-22 17:23:49.681391: Current learning rate: 0.00324 +2024-11-22 17:24:08.253108: train_loss -0.8016 +2024-11-22 17:24:08.253319: val_loss -0.7839 +2024-11-22 17:24:08.253400: Pseudo dice [0.8472] +2024-11-22 17:24:08.253473: Epoch time: 18.57 s +2024-11-22 17:24:09.142852: +2024-11-22 17:24:09.143199: Epoch 5711 +2024-11-22 17:24:09.143310: Current learning rate: 0.00324 +2024-11-22 17:24:28.186021: train_loss -0.805 +2024-11-22 17:24:28.186264: val_loss -0.7735 +2024-11-22 17:24:28.186337: Pseudo dice [0.8398] +2024-11-22 17:24:28.186414: Epoch time: 19.04 s +2024-11-22 17:24:29.076534: +2024-11-22 17:24:29.076730: Epoch 5712 +2024-11-22 17:24:29.076839: Current learning rate: 0.00324 +2024-11-22 17:24:45.960427: train_loss -0.7978 +2024-11-22 17:24:45.960640: val_loss -0.797 +2024-11-22 17:24:45.960713: Pseudo dice [0.8428] +2024-11-22 17:24:45.960787: Epoch time: 16.88 s +2024-11-22 17:24:46.852390: +2024-11-22 17:24:46.852701: Epoch 5713 +2024-11-22 17:24:46.852818: Current learning rate: 0.00324 +2024-11-22 17:25:05.658135: train_loss -0.8021 +2024-11-22 17:25:05.658366: val_loss -0.7735 +2024-11-22 17:25:05.658448: Pseudo dice [0.841] +2024-11-22 17:25:05.658520: Epoch time: 18.81 s +2024-11-22 17:25:06.543593: +2024-11-22 17:25:06.543802: Epoch 5714 +2024-11-22 17:25:06.543909: Current learning rate: 0.00324 +2024-11-22 17:25:24.948835: train_loss -0.7986 +2024-11-22 17:25:24.949071: val_loss -0.7853 +2024-11-22 17:25:24.949146: Pseudo dice [0.8327] +2024-11-22 17:25:24.949220: Epoch time: 18.41 s +2024-11-22 17:25:25.833131: +2024-11-22 17:25:25.833368: Epoch 5715 +2024-11-22 17:25:25.833481: Current learning rate: 0.00324 +2024-11-22 17:25:44.492816: train_loss -0.7963 +2024-11-22 17:25:44.493117: val_loss -0.8035 +2024-11-22 17:25:44.493205: Pseudo dice [0.8626] +2024-11-22 17:25:44.493286: Epoch time: 18.66 s +2024-11-22 17:25:45.777799: +2024-11-22 17:25:45.778116: Epoch 5716 +2024-11-22 17:25:45.778225: Current learning rate: 0.00324 +2024-11-22 17:26:05.170822: train_loss -0.8011 +2024-11-22 17:26:05.171056: val_loss -0.7749 +2024-11-22 17:26:05.171134: Pseudo dice [0.8348] +2024-11-22 17:26:05.171240: Epoch time: 19.39 s +2024-11-22 17:26:06.060016: +2024-11-22 17:26:06.060232: Epoch 5717 +2024-11-22 17:26:06.060344: Current learning rate: 0.00324 +2024-11-22 17:26:25.257876: train_loss -0.802 +2024-11-22 17:26:25.258129: val_loss -0.7628 +2024-11-22 17:26:25.258209: Pseudo dice [0.8465] +2024-11-22 17:26:25.258283: Epoch time: 19.2 s +2024-11-22 17:26:26.153878: +2024-11-22 17:26:26.154132: Epoch 5718 +2024-11-22 17:26:26.154249: Current learning rate: 0.00323 +2024-11-22 17:26:44.824478: train_loss -0.7993 +2024-11-22 17:26:44.824720: val_loss -0.7584 +2024-11-22 17:26:44.824795: Pseudo dice [0.8621] +2024-11-22 17:26:44.824877: Epoch time: 18.67 s +2024-11-22 17:26:45.760792: +2024-11-22 17:26:45.761011: Epoch 5719 +2024-11-22 17:26:45.761122: Current learning rate: 0.00323 +2024-11-22 17:27:03.392562: train_loss -0.8007 +2024-11-22 17:27:03.392778: val_loss -0.7595 +2024-11-22 17:27:03.392855: Pseudo dice [0.8465] +2024-11-22 17:27:03.392931: Epoch time: 17.63 s +2024-11-22 17:27:04.290074: +2024-11-22 17:27:04.290276: Epoch 5720 +2024-11-22 17:27:04.290380: Current learning rate: 0.00323 +2024-11-22 17:27:23.148200: train_loss -0.8047 +2024-11-22 17:27:23.148408: val_loss -0.7529 +2024-11-22 17:27:23.148480: Pseudo dice [0.8485] +2024-11-22 17:27:23.148555: Epoch time: 18.86 s +2024-11-22 17:27:24.047254: +2024-11-22 17:27:24.047482: Epoch 5721 +2024-11-22 17:27:24.047613: Current learning rate: 0.00323 +2024-11-22 17:27:42.755648: train_loss -0.7983 +2024-11-22 17:27:42.755879: val_loss -0.7999 +2024-11-22 17:27:42.755958: Pseudo dice [0.8568] +2024-11-22 17:27:42.756037: Epoch time: 18.71 s +2024-11-22 17:27:43.652681: +2024-11-22 17:27:43.652905: Epoch 5722 +2024-11-22 17:27:43.653022: Current learning rate: 0.00323 +2024-11-22 17:28:01.678612: train_loss -0.7971 +2024-11-22 17:28:01.680522: val_loss -0.7755 +2024-11-22 17:28:01.680609: Pseudo dice [0.8513] +2024-11-22 17:28:01.680691: Epoch time: 18.03 s +2024-11-22 17:28:02.598562: +2024-11-22 17:28:02.598772: Epoch 5723 +2024-11-22 17:28:02.598884: Current learning rate: 0.00323 +2024-11-22 17:28:20.876359: train_loss -0.7965 +2024-11-22 17:28:20.876576: val_loss -0.783 +2024-11-22 17:28:20.876649: Pseudo dice [0.8469] +2024-11-22 17:28:20.876722: Epoch time: 18.28 s +2024-11-22 17:28:21.959630: +2024-11-22 17:28:21.959857: Epoch 5724 +2024-11-22 17:28:21.959963: Current learning rate: 0.00323 +2024-11-22 17:28:40.248094: train_loss -0.7941 +2024-11-22 17:28:40.248314: val_loss -0.761 +2024-11-22 17:28:40.248389: Pseudo dice [0.8366] +2024-11-22 17:28:40.248466: Epoch time: 18.29 s +2024-11-22 17:28:41.145727: +2024-11-22 17:28:41.145921: Epoch 5725 +2024-11-22 17:28:41.146036: Current learning rate: 0.00322 +2024-11-22 17:28:59.249878: train_loss -0.7995 +2024-11-22 17:28:59.250099: val_loss -0.7887 +2024-11-22 17:28:59.250173: Pseudo dice [0.8534] +2024-11-22 17:28:59.250263: Epoch time: 18.1 s +2024-11-22 17:29:00.134488: +2024-11-22 17:29:00.134697: Epoch 5726 +2024-11-22 17:29:00.134803: Current learning rate: 0.00322 +2024-11-22 17:29:19.060965: train_loss -0.8006 +2024-11-22 17:29:19.061223: val_loss -0.7675 +2024-11-22 17:29:19.061301: Pseudo dice [0.8205] +2024-11-22 17:29:19.061387: Epoch time: 18.93 s +2024-11-22 17:29:20.334004: +2024-11-22 17:29:20.334226: Epoch 5727 +2024-11-22 17:29:20.334335: Current learning rate: 0.00322 +2024-11-22 17:29:40.209138: train_loss -0.7975 +2024-11-22 17:29:40.209370: val_loss -0.778 +2024-11-22 17:29:40.209447: Pseudo dice [0.83] +2024-11-22 17:29:40.209522: Epoch time: 19.88 s +2024-11-22 17:29:41.131646: +2024-11-22 17:29:41.131872: Epoch 5728 +2024-11-22 17:29:41.131985: Current learning rate: 0.00322 +2024-11-22 17:29:59.629635: train_loss -0.8097 +2024-11-22 17:29:59.629858: val_loss -0.7528 +2024-11-22 17:29:59.629935: Pseudo dice [0.8314] +2024-11-22 17:29:59.630020: Epoch time: 18.5 s +2024-11-22 17:30:00.523880: +2024-11-22 17:30:00.524106: Epoch 5729 +2024-11-22 17:30:00.524214: Current learning rate: 0.00322 +2024-11-22 17:30:19.004721: train_loss -0.7996 +2024-11-22 17:30:19.004936: val_loss -0.7871 +2024-11-22 17:30:19.005063: Pseudo dice [0.8571] +2024-11-22 17:30:19.005193: Epoch time: 18.48 s +2024-11-22 17:30:19.906874: +2024-11-22 17:30:19.907111: Epoch 5730 +2024-11-22 17:30:19.907221: Current learning rate: 0.00322 +2024-11-22 17:30:38.929350: train_loss -0.7933 +2024-11-22 17:30:38.929596: val_loss -0.7551 +2024-11-22 17:30:38.929669: Pseudo dice [0.8521] +2024-11-22 17:30:38.929752: Epoch time: 19.02 s +2024-11-22 17:30:39.826229: +2024-11-22 17:30:39.826453: Epoch 5731 +2024-11-22 17:30:39.826566: Current learning rate: 0.00322 +2024-11-22 17:30:58.423433: train_loss -0.7986 +2024-11-22 17:30:58.423657: val_loss -0.7773 +2024-11-22 17:30:58.423733: Pseudo dice [0.8364] +2024-11-22 17:30:58.423810: Epoch time: 18.6 s +2024-11-22 17:30:59.322345: +2024-11-22 17:30:59.322678: Epoch 5732 +2024-11-22 17:30:59.322790: Current learning rate: 0.00322 +2024-11-22 17:31:17.260674: train_loss -0.8062 +2024-11-22 17:31:17.260886: val_loss -0.8026 +2024-11-22 17:31:17.260961: Pseudo dice [0.8603] +2024-11-22 17:31:17.261044: Epoch time: 17.94 s +2024-11-22 17:31:18.157990: +2024-11-22 17:31:18.158184: Epoch 5733 +2024-11-22 17:31:18.158292: Current learning rate: 0.00321 +2024-11-22 17:31:36.883200: train_loss -0.8023 +2024-11-22 17:31:36.883421: val_loss -0.7643 +2024-11-22 17:31:36.883497: Pseudo dice [0.8506] +2024-11-22 17:31:36.883570: Epoch time: 18.73 s +2024-11-22 17:31:37.774770: +2024-11-22 17:31:37.775059: Epoch 5734 +2024-11-22 17:31:37.775167: Current learning rate: 0.00321 +2024-11-22 17:31:55.396899: train_loss -0.7983 +2024-11-22 17:31:55.397155: val_loss -0.7892 +2024-11-22 17:31:55.397233: Pseudo dice [0.8626] +2024-11-22 17:31:55.397342: Epoch time: 17.62 s +2024-11-22 17:31:56.288171: +2024-11-22 17:31:56.288392: Epoch 5735 +2024-11-22 17:31:56.288500: Current learning rate: 0.00321 +2024-11-22 17:32:14.178385: train_loss -0.8064 +2024-11-22 17:32:14.178658: val_loss -0.7892 +2024-11-22 17:32:14.178733: Pseudo dice [0.8534] +2024-11-22 17:32:14.178808: Epoch time: 17.89 s +2024-11-22 17:32:15.110245: +2024-11-22 17:32:15.110676: Epoch 5736 +2024-11-22 17:32:15.110810: Current learning rate: 0.00321 +2024-11-22 17:32:34.289258: train_loss -0.79 +2024-11-22 17:32:34.289504: val_loss -0.7838 +2024-11-22 17:32:34.289635: Pseudo dice [0.8557] +2024-11-22 17:32:34.289714: Epoch time: 19.18 s +2024-11-22 17:32:35.180511: +2024-11-22 17:32:35.180709: Epoch 5737 +2024-11-22 17:32:35.180818: Current learning rate: 0.00321 +2024-11-22 17:32:54.098714: train_loss -0.8048 +2024-11-22 17:32:54.098966: val_loss -0.781 +2024-11-22 17:32:54.099055: Pseudo dice [0.8571] +2024-11-22 17:32:54.099135: Epoch time: 18.92 s +2024-11-22 17:32:55.059524: +2024-11-22 17:32:55.059734: Epoch 5738 +2024-11-22 17:32:55.059845: Current learning rate: 0.00321 +2024-11-22 17:33:13.711810: train_loss -0.799 +2024-11-22 17:33:13.712123: val_loss -0.7822 +2024-11-22 17:33:13.712200: Pseudo dice [0.8617] +2024-11-22 17:33:13.712280: Epoch time: 18.65 s +2024-11-22 17:33:15.043536: +2024-11-22 17:33:15.043750: Epoch 5739 +2024-11-22 17:33:15.043855: Current learning rate: 0.00321 +2024-11-22 17:33:33.530530: train_loss -0.7842 +2024-11-22 17:33:33.530745: val_loss -0.7769 +2024-11-22 17:33:33.530819: Pseudo dice [0.8419] +2024-11-22 17:33:33.530891: Epoch time: 18.49 s +2024-11-22 17:33:34.423505: +2024-11-22 17:33:34.423732: Epoch 5740 +2024-11-22 17:33:34.423842: Current learning rate: 0.00321 +2024-11-22 17:33:52.770312: train_loss -0.7877 +2024-11-22 17:33:52.770532: val_loss -0.7716 +2024-11-22 17:33:52.770605: Pseudo dice [0.848] +2024-11-22 17:33:52.770680: Epoch time: 18.35 s +2024-11-22 17:33:53.671007: +2024-11-22 17:33:53.671231: Epoch 5741 +2024-11-22 17:33:53.671340: Current learning rate: 0.0032 +2024-11-22 17:34:11.311034: train_loss -0.8054 +2024-11-22 17:34:11.311277: val_loss -0.7608 +2024-11-22 17:34:11.311354: Pseudo dice [0.8512] +2024-11-22 17:34:11.311436: Epoch time: 17.64 s +2024-11-22 17:34:12.213379: +2024-11-22 17:34:12.213740: Epoch 5742 +2024-11-22 17:34:12.213857: Current learning rate: 0.0032 +2024-11-22 17:34:30.969674: train_loss -0.801 +2024-11-22 17:34:30.969894: val_loss -0.7814 +2024-11-22 17:34:30.969975: Pseudo dice [0.8641] +2024-11-22 17:34:30.970059: Epoch time: 18.76 s +2024-11-22 17:34:31.857270: +2024-11-22 17:34:31.857610: Epoch 5743 +2024-11-22 17:34:31.857725: Current learning rate: 0.0032 +2024-11-22 17:34:49.768529: train_loss -0.7951 +2024-11-22 17:34:49.768738: val_loss -0.7618 +2024-11-22 17:34:49.768811: Pseudo dice [0.8294] +2024-11-22 17:34:49.768890: Epoch time: 17.91 s +2024-11-22 17:34:50.659173: +2024-11-22 17:34:50.659402: Epoch 5744 +2024-11-22 17:34:50.659524: Current learning rate: 0.0032 +2024-11-22 17:35:09.241356: train_loss -0.801 +2024-11-22 17:35:09.241609: val_loss -0.7514 +2024-11-22 17:35:09.241738: Pseudo dice [0.853] +2024-11-22 17:35:09.241811: Epoch time: 18.58 s +2024-11-22 17:35:10.138582: +2024-11-22 17:35:10.138863: Epoch 5745 +2024-11-22 17:35:10.138979: Current learning rate: 0.0032 +2024-11-22 17:35:28.998031: train_loss -0.8016 +2024-11-22 17:35:29.005756: val_loss -0.743 +2024-11-22 17:35:29.007941: Pseudo dice [0.835] +2024-11-22 17:35:29.008454: Epoch time: 18.86 s +2024-11-22 17:35:30.078224: +2024-11-22 17:35:30.078474: Epoch 5746 +2024-11-22 17:35:30.078618: Current learning rate: 0.0032 +2024-11-22 17:35:48.750224: train_loss -0.7966 +2024-11-22 17:35:48.750472: val_loss -0.7757 +2024-11-22 17:35:48.750548: Pseudo dice [0.8438] +2024-11-22 17:35:48.750627: Epoch time: 18.67 s +2024-11-22 17:35:49.651188: +2024-11-22 17:35:49.651403: Epoch 5747 +2024-11-22 17:35:49.651513: Current learning rate: 0.0032 +2024-11-22 17:36:07.704094: train_loss -0.7942 +2024-11-22 17:36:07.704312: val_loss -0.7538 +2024-11-22 17:36:07.704391: Pseudo dice [0.8535] +2024-11-22 17:36:07.704469: Epoch time: 18.05 s +2024-11-22 17:36:08.597647: +2024-11-22 17:36:08.597885: Epoch 5748 +2024-11-22 17:36:08.598005: Current learning rate: 0.0032 +2024-11-22 17:36:26.522463: train_loss -0.8009 +2024-11-22 17:36:26.522679: val_loss -0.7775 +2024-11-22 17:36:26.522755: Pseudo dice [0.8625] +2024-11-22 17:36:26.522831: Epoch time: 17.93 s +2024-11-22 17:36:27.416522: +2024-11-22 17:36:27.416742: Epoch 5749 +2024-11-22 17:36:27.416856: Current learning rate: 0.00319 +2024-11-22 17:36:46.033567: train_loss -0.8006 +2024-11-22 17:36:46.033783: val_loss -0.776 +2024-11-22 17:36:46.033854: Pseudo dice [0.8426] +2024-11-22 17:36:46.033931: Epoch time: 18.62 s +2024-11-22 17:36:47.592670: +2024-11-22 17:36:47.606429: Epoch 5750 +2024-11-22 17:36:47.606564: Current learning rate: 0.00319 +2024-11-22 17:37:06.123128: train_loss -0.7981 +2024-11-22 17:37:06.123365: val_loss -0.7942 +2024-11-22 17:37:06.123440: Pseudo dice [0.8496] +2024-11-22 17:37:06.123516: Epoch time: 18.53 s +2024-11-22 17:37:07.011433: +2024-11-22 17:37:07.011666: Epoch 5751 +2024-11-22 17:37:07.011774: Current learning rate: 0.00319 +2024-11-22 17:37:25.954139: train_loss -0.7974 +2024-11-22 17:37:25.954395: val_loss -0.7695 +2024-11-22 17:37:25.954509: Pseudo dice [0.8559] +2024-11-22 17:37:25.954596: Epoch time: 18.94 s +2024-11-22 17:37:26.840317: +2024-11-22 17:37:26.840557: Epoch 5752 +2024-11-22 17:37:26.840669: Current learning rate: 0.00319 +2024-11-22 17:37:45.688167: train_loss -0.802 +2024-11-22 17:37:45.688407: val_loss -0.7803 +2024-11-22 17:37:45.688487: Pseudo dice [0.8472] +2024-11-22 17:37:45.688561: Epoch time: 18.85 s +2024-11-22 17:37:46.582772: +2024-11-22 17:37:46.583001: Epoch 5753 +2024-11-22 17:37:46.583114: Current learning rate: 0.00319 +2024-11-22 17:38:04.527706: train_loss -0.8014 +2024-11-22 17:38:04.527961: val_loss -0.7679 +2024-11-22 17:38:04.528044: Pseudo dice [0.8424] +2024-11-22 17:38:04.528123: Epoch time: 17.95 s +2024-11-22 17:38:05.461036: +2024-11-22 17:38:05.461249: Epoch 5754 +2024-11-22 17:38:05.461358: Current learning rate: 0.00319 +2024-11-22 17:38:23.402095: train_loss -0.8051 +2024-11-22 17:38:23.402316: val_loss -0.75 +2024-11-22 17:38:23.402389: Pseudo dice [0.851] +2024-11-22 17:38:23.402462: Epoch time: 17.94 s +2024-11-22 17:38:24.289901: +2024-11-22 17:38:24.290107: Epoch 5755 +2024-11-22 17:38:24.290216: Current learning rate: 0.00319 +2024-11-22 17:38:42.663411: train_loss -0.7984 +2024-11-22 17:38:42.663661: val_loss -0.7606 +2024-11-22 17:38:42.663738: Pseudo dice [0.8405] +2024-11-22 17:38:42.663811: Epoch time: 18.37 s +2024-11-22 17:38:43.593677: +2024-11-22 17:38:43.593892: Epoch 5756 +2024-11-22 17:38:43.594003: Current learning rate: 0.00319 +2024-11-22 17:39:01.168670: train_loss -0.804 +2024-11-22 17:39:01.168898: val_loss -0.7672 +2024-11-22 17:39:01.168981: Pseudo dice [0.8476] +2024-11-22 17:39:01.169067: Epoch time: 17.58 s +2024-11-22 17:39:02.065666: +2024-11-22 17:39:02.065895: Epoch 5757 +2024-11-22 17:39:02.066007: Current learning rate: 0.00318 +2024-11-22 17:39:20.580456: train_loss -0.8022 +2024-11-22 17:39:20.580693: val_loss -0.7336 +2024-11-22 17:39:20.580769: Pseudo dice [0.85] +2024-11-22 17:39:20.580846: Epoch time: 18.52 s +2024-11-22 17:39:21.475533: +2024-11-22 17:39:21.475738: Epoch 5758 +2024-11-22 17:39:21.475845: Current learning rate: 0.00318 +2024-11-22 17:39:40.174177: train_loss -0.7895 +2024-11-22 17:39:40.174421: val_loss -0.7693 +2024-11-22 17:39:40.174496: Pseudo dice [0.8333] +2024-11-22 17:39:40.174572: Epoch time: 18.7 s +2024-11-22 17:39:41.081930: +2024-11-22 17:39:41.082131: Epoch 5759 +2024-11-22 17:39:41.082241: Current learning rate: 0.00318 +2024-11-22 17:39:59.181748: train_loss -0.7961 +2024-11-22 17:39:59.184787: val_loss -0.7622 +2024-11-22 17:39:59.184890: Pseudo dice [0.8471] +2024-11-22 17:39:59.184968: Epoch time: 18.1 s +2024-11-22 17:40:00.077580: +2024-11-22 17:40:00.077785: Epoch 5760 +2024-11-22 17:40:00.077899: Current learning rate: 0.00318 +2024-11-22 17:40:18.126252: train_loss -0.7925 +2024-11-22 17:40:18.126466: val_loss -0.7809 +2024-11-22 17:40:18.126542: Pseudo dice [0.8454] +2024-11-22 17:40:18.126619: Epoch time: 18.05 s +2024-11-22 17:40:19.034390: +2024-11-22 17:40:19.034642: Epoch 5761 +2024-11-22 17:40:19.034753: Current learning rate: 0.00318 +2024-11-22 17:40:36.958133: train_loss -0.8026 +2024-11-22 17:40:36.958356: val_loss -0.7803 +2024-11-22 17:40:36.958433: Pseudo dice [0.8503] +2024-11-22 17:40:36.958512: Epoch time: 17.92 s +2024-11-22 17:40:38.241969: +2024-11-22 17:40:38.242198: Epoch 5762 +2024-11-22 17:40:38.242310: Current learning rate: 0.00318 +2024-11-22 17:40:57.549412: train_loss -0.803 +2024-11-22 17:40:57.549652: val_loss -0.7636 +2024-11-22 17:40:57.549734: Pseudo dice [0.8503] +2024-11-22 17:40:57.577697: Epoch time: 19.31 s +2024-11-22 17:40:58.473120: +2024-11-22 17:40:58.473336: Epoch 5763 +2024-11-22 17:40:58.473446: Current learning rate: 0.00318 +2024-11-22 17:41:15.961557: train_loss -0.8024 +2024-11-22 17:41:15.961778: val_loss -0.7866 +2024-11-22 17:41:15.961854: Pseudo dice [0.8504] +2024-11-22 17:41:15.961927: Epoch time: 17.49 s +2024-11-22 17:41:16.952216: +2024-11-22 17:41:16.952422: Epoch 5764 +2024-11-22 17:41:16.952532: Current learning rate: 0.00317 +2024-11-22 17:41:36.451118: train_loss -0.795 +2024-11-22 17:41:36.451384: val_loss -0.7417 +2024-11-22 17:41:36.451457: Pseudo dice [0.8288] +2024-11-22 17:41:36.451534: Epoch time: 19.5 s +2024-11-22 17:41:37.350114: +2024-11-22 17:41:37.350333: Epoch 5765 +2024-11-22 17:41:37.350441: Current learning rate: 0.00317 +2024-11-22 17:41:55.562131: train_loss -0.7983 +2024-11-22 17:41:55.562345: val_loss -0.784 +2024-11-22 17:41:55.562426: Pseudo dice [0.8502] +2024-11-22 17:41:55.562502: Epoch time: 18.21 s +2024-11-22 17:41:56.455188: +2024-11-22 17:41:56.455404: Epoch 5766 +2024-11-22 17:41:56.455512: Current learning rate: 0.00317 +2024-11-22 17:42:15.450800: train_loss -0.7927 +2024-11-22 17:42:15.451041: val_loss -0.7817 +2024-11-22 17:42:15.451116: Pseudo dice [0.8387] +2024-11-22 17:42:15.451326: Epoch time: 19.0 s +2024-11-22 17:42:16.358490: +2024-11-22 17:42:16.358694: Epoch 5767 +2024-11-22 17:42:16.358804: Current learning rate: 0.00317 +2024-11-22 17:42:34.608519: train_loss -0.7999 +2024-11-22 17:42:34.608747: val_loss -0.7552 +2024-11-22 17:42:34.608827: Pseudo dice [0.8464] +2024-11-22 17:42:34.608907: Epoch time: 18.25 s +2024-11-22 17:42:35.505517: +2024-11-22 17:42:35.505827: Epoch 5768 +2024-11-22 17:42:35.505937: Current learning rate: 0.00317 +2024-11-22 17:42:54.476243: train_loss -0.7984 +2024-11-22 17:42:54.476487: val_loss -0.7823 +2024-11-22 17:42:54.476559: Pseudo dice [0.8534] +2024-11-22 17:42:54.476639: Epoch time: 18.97 s +2024-11-22 17:42:55.369012: +2024-11-22 17:42:55.369234: Epoch 5769 +2024-11-22 17:42:55.369342: Current learning rate: 0.00317 +2024-11-22 17:43:12.556080: train_loss -0.8011 +2024-11-22 17:43:12.556299: val_loss -0.7658 +2024-11-22 17:43:12.556372: Pseudo dice [0.8429] +2024-11-22 17:43:12.556447: Epoch time: 17.19 s +2024-11-22 17:43:13.559281: +2024-11-22 17:43:13.559489: Epoch 5770 +2024-11-22 17:43:13.559605: Current learning rate: 0.00317 +2024-11-22 17:43:31.817393: train_loss -0.8035 +2024-11-22 17:43:31.817632: val_loss -0.7544 +2024-11-22 17:43:31.817767: Pseudo dice [0.8414] +2024-11-22 17:43:31.817842: Epoch time: 18.26 s +2024-11-22 17:43:32.712289: +2024-11-22 17:43:32.712492: Epoch 5771 +2024-11-22 17:43:32.712604: Current learning rate: 0.00317 +2024-11-22 17:43:51.888856: train_loss -0.8051 +2024-11-22 17:43:51.889104: val_loss -0.7714 +2024-11-22 17:43:51.889187: Pseudo dice [0.8481] +2024-11-22 17:43:51.889266: Epoch time: 19.18 s +2024-11-22 17:43:52.781186: +2024-11-22 17:43:52.781415: Epoch 5772 +2024-11-22 17:43:52.781564: Current learning rate: 0.00316 +2024-11-22 17:44:11.599643: train_loss -0.8078 +2024-11-22 17:44:11.599869: val_loss -0.7587 +2024-11-22 17:44:11.599945: Pseudo dice [0.8476] +2024-11-22 17:44:11.600029: Epoch time: 18.82 s +2024-11-22 17:44:12.493324: +2024-11-22 17:44:12.493556: Epoch 5773 +2024-11-22 17:44:12.493673: Current learning rate: 0.00316 +2024-11-22 17:44:31.424926: train_loss -0.8059 +2024-11-22 17:44:31.425382: val_loss -0.7759 +2024-11-22 17:44:31.425478: Pseudo dice [0.8583] +2024-11-22 17:44:31.425550: Epoch time: 18.93 s +2024-11-22 17:44:32.307554: +2024-11-22 17:44:32.307773: Epoch 5774 +2024-11-22 17:44:32.307887: Current learning rate: 0.00316 +2024-11-22 17:44:50.463549: train_loss -0.8071 +2024-11-22 17:44:50.463771: val_loss -0.7707 +2024-11-22 17:44:50.463846: Pseudo dice [0.8614] +2024-11-22 17:44:50.463921: Epoch time: 18.16 s +2024-11-22 17:44:51.362644: +2024-11-22 17:44:51.362878: Epoch 5775 +2024-11-22 17:44:51.362986: Current learning rate: 0.00316 +2024-11-22 17:45:10.274472: train_loss -0.8029 +2024-11-22 17:45:10.274716: val_loss -0.7502 +2024-11-22 17:45:10.274794: Pseudo dice [0.8519] +2024-11-22 17:45:10.274875: Epoch time: 18.91 s +2024-11-22 17:45:11.186452: +2024-11-22 17:45:11.186674: Epoch 5776 +2024-11-22 17:45:11.186779: Current learning rate: 0.00316 +2024-11-22 17:45:29.607589: train_loss -0.8046 +2024-11-22 17:45:29.607805: val_loss -0.7978 +2024-11-22 17:45:29.607887: Pseudo dice [0.8675] +2024-11-22 17:45:29.607965: Epoch time: 18.42 s +2024-11-22 17:45:30.498430: +2024-11-22 17:45:30.498636: Epoch 5777 +2024-11-22 17:45:30.498752: Current learning rate: 0.00316 +2024-11-22 17:45:48.351319: train_loss -0.8006 +2024-11-22 17:45:48.351536: val_loss -0.771 +2024-11-22 17:45:48.351610: Pseudo dice [0.8582] +2024-11-22 17:45:48.351682: Epoch time: 17.85 s +2024-11-22 17:45:49.244578: +2024-11-22 17:45:49.244812: Epoch 5778 +2024-11-22 17:45:49.244925: Current learning rate: 0.00316 +2024-11-22 17:46:08.016580: train_loss -0.8002 +2024-11-22 17:46:08.016783: val_loss -0.7579 +2024-11-22 17:46:08.016854: Pseudo dice [0.8448] +2024-11-22 17:46:08.016926: Epoch time: 18.77 s +2024-11-22 17:46:08.901353: +2024-11-22 17:46:08.901574: Epoch 5779 +2024-11-22 17:46:08.901684: Current learning rate: 0.00316 +2024-11-22 17:46:27.482247: train_loss -0.8055 +2024-11-22 17:46:27.484656: val_loss -0.7743 +2024-11-22 17:46:27.484748: Pseudo dice [0.8436] +2024-11-22 17:46:27.484832: Epoch time: 18.58 s +2024-11-22 17:46:28.398898: +2024-11-22 17:46:28.399119: Epoch 5780 +2024-11-22 17:46:28.399228: Current learning rate: 0.00315 +2024-11-22 17:46:46.313131: train_loss -0.8067 +2024-11-22 17:46:46.313346: val_loss -0.78 +2024-11-22 17:46:46.313421: Pseudo dice [0.8488] +2024-11-22 17:46:46.313495: Epoch time: 17.92 s +2024-11-22 17:46:47.211102: +2024-11-22 17:46:47.211317: Epoch 5781 +2024-11-22 17:46:47.211429: Current learning rate: 0.00315 +2024-11-22 17:47:06.260038: train_loss -0.8108 +2024-11-22 17:47:06.260323: val_loss -0.7619 +2024-11-22 17:47:06.260399: Pseudo dice [0.8353] +2024-11-22 17:47:06.260475: Epoch time: 19.05 s +2024-11-22 17:47:07.169106: +2024-11-22 17:47:07.169318: Epoch 5782 +2024-11-22 17:47:07.169427: Current learning rate: 0.00315 +2024-11-22 17:47:26.100808: train_loss -0.8083 +2024-11-22 17:47:26.101342: val_loss -0.8007 +2024-11-22 17:47:26.101431: Pseudo dice [0.87] +2024-11-22 17:47:26.101508: Epoch time: 18.93 s +2024-11-22 17:47:27.072772: +2024-11-22 17:47:27.072994: Epoch 5783 +2024-11-22 17:47:27.073108: Current learning rate: 0.00315 +2024-11-22 17:47:46.025711: train_loss -0.806 +2024-11-22 17:47:46.027178: val_loss -0.7778 +2024-11-22 17:47:46.027303: Pseudo dice [0.8498] +2024-11-22 17:47:46.027382: Epoch time: 18.95 s +2024-11-22 17:47:46.929513: +2024-11-22 17:47:46.929744: Epoch 5784 +2024-11-22 17:47:46.929857: Current learning rate: 0.00315 +2024-11-22 17:48:04.410500: train_loss -0.8093 +2024-11-22 17:48:04.410748: val_loss -0.7681 +2024-11-22 17:48:04.410832: Pseudo dice [0.8422] +2024-11-22 17:48:04.410915: Epoch time: 17.48 s +2024-11-22 17:48:05.683230: +2024-11-22 17:48:05.683465: Epoch 5785 +2024-11-22 17:48:05.683578: Current learning rate: 0.00315 +2024-11-22 17:48:23.388236: train_loss -0.8083 +2024-11-22 17:48:23.388471: val_loss -0.7657 +2024-11-22 17:48:23.388551: Pseudo dice [0.8379] +2024-11-22 17:48:23.388640: Epoch time: 17.71 s +2024-11-22 17:48:24.284309: +2024-11-22 17:48:24.284514: Epoch 5786 +2024-11-22 17:48:24.284617: Current learning rate: 0.00315 +2024-11-22 17:48:43.331074: train_loss -0.8058 +2024-11-22 17:48:43.331371: val_loss -0.7906 +2024-11-22 17:48:43.331446: Pseudo dice [0.851] +2024-11-22 17:48:43.331528: Epoch time: 19.05 s +2024-11-22 17:48:44.231320: +2024-11-22 17:48:44.231585: Epoch 5787 +2024-11-22 17:48:44.231695: Current learning rate: 0.00315 +2024-11-22 17:49:02.443953: train_loss -0.7949 +2024-11-22 17:49:02.444891: val_loss -0.7675 +2024-11-22 17:49:02.444967: Pseudo dice [0.8478] +2024-11-22 17:49:02.445105: Epoch time: 18.21 s +2024-11-22 17:49:03.338336: +2024-11-22 17:49:03.338556: Epoch 5788 +2024-11-22 17:49:03.355208: Current learning rate: 0.00314 +2024-11-22 17:49:21.931862: train_loss -0.8086 +2024-11-22 17:49:21.932087: val_loss -0.7856 +2024-11-22 17:49:21.932165: Pseudo dice [0.8545] +2024-11-22 17:49:21.932239: Epoch time: 18.59 s +2024-11-22 17:49:22.811206: +2024-11-22 17:49:22.811397: Epoch 5789 +2024-11-22 17:49:22.811909: Current learning rate: 0.00314 +2024-11-22 17:49:41.497403: train_loss -0.8042 +2024-11-22 17:49:41.497615: val_loss -0.7659 +2024-11-22 17:49:41.497691: Pseudo dice [0.8484] +2024-11-22 17:49:41.497767: Epoch time: 18.69 s +2024-11-22 17:49:42.390900: +2024-11-22 17:49:42.391108: Epoch 5790 +2024-11-22 17:49:42.391215: Current learning rate: 0.00314 +2024-11-22 17:50:01.631895: train_loss -0.8002 +2024-11-22 17:50:01.632151: val_loss -0.7781 +2024-11-22 17:50:01.632227: Pseudo dice [0.8611] +2024-11-22 17:50:01.632312: Epoch time: 19.24 s +2024-11-22 17:50:02.727787: +2024-11-22 17:50:02.727983: Epoch 5791 +2024-11-22 17:50:02.728098: Current learning rate: 0.00314 +2024-11-22 17:50:20.601515: train_loss -0.8031 +2024-11-22 17:50:20.601721: val_loss -0.7951 +2024-11-22 17:50:20.601797: Pseudo dice [0.8624] +2024-11-22 17:50:20.601872: Epoch time: 17.87 s +2024-11-22 17:50:21.497283: +2024-11-22 17:50:21.497494: Epoch 5792 +2024-11-22 17:50:21.497602: Current learning rate: 0.00314 +2024-11-22 17:50:39.851660: train_loss -0.8049 +2024-11-22 17:50:39.851886: val_loss -0.7679 +2024-11-22 17:50:39.851964: Pseudo dice [0.847] +2024-11-22 17:50:39.852047: Epoch time: 18.36 s +2024-11-22 17:50:40.743446: +2024-11-22 17:50:40.743679: Epoch 5793 +2024-11-22 17:50:40.743791: Current learning rate: 0.00314 +2024-11-22 17:50:59.638973: train_loss -0.7947 +2024-11-22 17:50:59.639244: val_loss -0.7344 +2024-11-22 17:50:59.639330: Pseudo dice [0.8192] +2024-11-22 17:50:59.639414: Epoch time: 18.9 s +2024-11-22 17:51:00.529864: +2024-11-22 17:51:00.530092: Epoch 5794 +2024-11-22 17:51:00.530207: Current learning rate: 0.00314 +2024-11-22 17:51:18.671073: train_loss -0.7744 +2024-11-22 17:51:18.671317: val_loss -0.7731 +2024-11-22 17:51:18.671393: Pseudo dice [0.8398] +2024-11-22 17:51:18.671491: Epoch time: 18.14 s +2024-11-22 17:51:19.560646: +2024-11-22 17:51:19.560882: Epoch 5795 +2024-11-22 17:51:19.560995: Current learning rate: 0.00314 +2024-11-22 17:51:38.660446: train_loss -0.8021 +2024-11-22 17:51:38.660655: val_loss -0.7769 +2024-11-22 17:51:38.660728: Pseudo dice [0.8558] +2024-11-22 17:51:38.660833: Epoch time: 19.1 s +2024-11-22 17:51:39.917035: +2024-11-22 17:51:39.917265: Epoch 5796 +2024-11-22 17:51:39.917380: Current learning rate: 0.00313 +2024-11-22 17:51:57.640382: train_loss -0.7948 +2024-11-22 17:51:57.640613: val_loss -0.7848 +2024-11-22 17:51:57.640686: Pseudo dice [0.8515] +2024-11-22 17:51:57.640758: Epoch time: 17.72 s +2024-11-22 17:51:58.537828: +2024-11-22 17:51:58.538111: Epoch 5797 +2024-11-22 17:51:58.538221: Current learning rate: 0.00313 +2024-11-22 17:52:18.410906: train_loss -0.7902 +2024-11-22 17:52:18.412516: val_loss -0.7576 +2024-11-22 17:52:18.412606: Pseudo dice [0.8329] +2024-11-22 17:52:18.412681: Epoch time: 19.87 s +2024-11-22 17:52:19.338703: +2024-11-22 17:52:19.338920: Epoch 5798 +2024-11-22 17:52:19.339033: Current learning rate: 0.00313 +2024-11-22 17:52:37.938263: train_loss -0.7948 +2024-11-22 17:52:37.938522: val_loss -0.7665 +2024-11-22 17:52:37.938599: Pseudo dice [0.8574] +2024-11-22 17:52:37.938680: Epoch time: 18.6 s +2024-11-22 17:52:38.840379: +2024-11-22 17:52:38.840602: Epoch 5799 +2024-11-22 17:52:38.840711: Current learning rate: 0.00313 +2024-11-22 17:52:57.310189: train_loss -0.7934 +2024-11-22 17:52:57.310406: val_loss -0.7844 +2024-11-22 17:52:57.310478: Pseudo dice [0.8609] +2024-11-22 17:52:57.310550: Epoch time: 18.47 s +2024-11-22 17:52:58.523848: +2024-11-22 17:52:58.524074: Epoch 5800 +2024-11-22 17:52:58.524181: Current learning rate: 0.00313 +2024-11-22 17:53:18.217306: train_loss -0.7959 +2024-11-22 17:53:18.217533: val_loss -0.7837 +2024-11-22 17:53:18.217607: Pseudo dice [0.8643] +2024-11-22 17:53:18.250271: Epoch time: 19.69 s +2024-11-22 17:53:19.145233: +2024-11-22 17:53:19.145456: Epoch 5801 +2024-11-22 17:53:19.145570: Current learning rate: 0.00313 +2024-11-22 17:53:38.091607: train_loss -0.7913 +2024-11-22 17:53:38.091832: val_loss -0.7751 +2024-11-22 17:53:38.091908: Pseudo dice [0.8464] +2024-11-22 17:53:38.091988: Epoch time: 18.95 s +2024-11-22 17:53:38.995091: +2024-11-22 17:53:38.995292: Epoch 5802 +2024-11-22 17:53:38.995404: Current learning rate: 0.00313 +2024-11-22 17:53:57.714867: train_loss -0.7905 +2024-11-22 17:53:57.715117: val_loss -0.7711 +2024-11-22 17:53:57.715191: Pseudo dice [0.8508] +2024-11-22 17:53:57.715273: Epoch time: 18.72 s +2024-11-22 17:53:58.618023: +2024-11-22 17:53:58.618253: Epoch 5803 +2024-11-22 17:53:58.618367: Current learning rate: 0.00313 +2024-11-22 17:54:16.870067: train_loss -0.7964 +2024-11-22 17:54:16.870286: val_loss -0.782 +2024-11-22 17:54:16.870361: Pseudo dice [0.8645] +2024-11-22 17:54:16.870440: Epoch time: 18.25 s +2024-11-22 17:54:17.768735: +2024-11-22 17:54:17.768961: Epoch 5804 +2024-11-22 17:54:17.769076: Current learning rate: 0.00312 +2024-11-22 17:54:35.646186: train_loss -0.7997 +2024-11-22 17:54:35.646398: val_loss -0.7841 +2024-11-22 17:54:35.646476: Pseudo dice [0.8504] +2024-11-22 17:54:35.646552: Epoch time: 17.88 s +2024-11-22 17:54:36.643021: +2024-11-22 17:54:36.643275: Epoch 5805 +2024-11-22 17:54:36.643387: Current learning rate: 0.00312 +2024-11-22 17:54:55.092094: train_loss -0.7966 +2024-11-22 17:54:55.092307: val_loss -0.7863 +2024-11-22 17:54:55.092387: Pseudo dice [0.8513] +2024-11-22 17:54:55.092462: Epoch time: 18.45 s +2024-11-22 17:54:55.989210: +2024-11-22 17:54:55.989424: Epoch 5806 +2024-11-22 17:54:55.989542: Current learning rate: 0.00312 +2024-11-22 17:55:16.403849: train_loss -0.8033 +2024-11-22 17:55:16.404099: val_loss -0.7612 +2024-11-22 17:55:16.404174: Pseudo dice [0.8542] +2024-11-22 17:55:16.404253: Epoch time: 20.42 s +2024-11-22 17:55:17.305421: +2024-11-22 17:55:17.305743: Epoch 5807 +2024-11-22 17:55:17.305856: Current learning rate: 0.00312 +2024-11-22 17:55:35.583703: train_loss -0.7996 +2024-11-22 17:55:35.583918: val_loss -0.7714 +2024-11-22 17:55:35.583998: Pseudo dice [0.8513] +2024-11-22 17:55:35.584074: Epoch time: 18.28 s +2024-11-22 17:55:36.861667: +2024-11-22 17:55:36.861907: Epoch 5808 +2024-11-22 17:55:36.862019: Current learning rate: 0.00312 +2024-11-22 17:55:56.044908: train_loss -0.8076 +2024-11-22 17:55:56.045142: val_loss -0.8022 +2024-11-22 17:55:56.045213: Pseudo dice [0.8652] +2024-11-22 17:55:56.045284: Epoch time: 19.18 s +2024-11-22 17:55:56.958818: +2024-11-22 17:55:56.959039: Epoch 5809 +2024-11-22 17:55:56.959147: Current learning rate: 0.00312 +2024-11-22 17:56:15.387260: train_loss -0.8005 +2024-11-22 17:56:15.387504: val_loss -0.7668 +2024-11-22 17:56:15.387577: Pseudo dice [0.8503] +2024-11-22 17:56:15.387655: Epoch time: 18.43 s +2024-11-22 17:56:16.300045: +2024-11-22 17:56:16.300247: Epoch 5810 +2024-11-22 17:56:16.300355: Current learning rate: 0.00312 +2024-11-22 17:56:35.165905: train_loss -0.8039 +2024-11-22 17:56:35.166144: val_loss -0.7903 +2024-11-22 17:56:35.166220: Pseudo dice [0.8449] +2024-11-22 17:56:35.166298: Epoch time: 18.87 s +2024-11-22 17:56:36.070651: +2024-11-22 17:56:36.070874: Epoch 5811 +2024-11-22 17:56:36.070983: Current learning rate: 0.00311 +2024-11-22 17:56:54.685255: train_loss -0.7976 +2024-11-22 17:56:54.685475: val_loss -0.7836 +2024-11-22 17:56:54.685554: Pseudo dice [0.8426] +2024-11-22 17:56:54.685630: Epoch time: 18.62 s +2024-11-22 17:56:55.596353: +2024-11-22 17:56:55.596571: Epoch 5812 +2024-11-22 17:56:55.596689: Current learning rate: 0.00311 +2024-11-22 17:57:13.756150: train_loss -0.8006 +2024-11-22 17:57:13.756408: val_loss -0.7834 +2024-11-22 17:57:13.756482: Pseudo dice [0.8532] +2024-11-22 17:57:13.756555: Epoch time: 18.16 s +2024-11-22 17:57:14.665648: +2024-11-22 17:57:14.665857: Epoch 5813 +2024-11-22 17:57:14.665967: Current learning rate: 0.00311 +2024-11-22 17:57:32.987356: train_loss -0.8051 +2024-11-22 17:57:32.988127: val_loss -0.7606 +2024-11-22 17:57:32.988212: Pseudo dice [0.8534] +2024-11-22 17:57:32.988295: Epoch time: 18.32 s +2024-11-22 17:57:33.887365: +2024-11-22 17:57:33.887577: Epoch 5814 +2024-11-22 17:57:33.887685: Current learning rate: 0.00311 +2024-11-22 17:57:52.702633: train_loss -0.804 +2024-11-22 17:57:52.702878: val_loss -0.7489 +2024-11-22 17:57:52.702959: Pseudo dice [0.8536] +2024-11-22 17:57:52.703060: Epoch time: 18.82 s +2024-11-22 17:57:53.594363: +2024-11-22 17:57:53.594734: Epoch 5815 +2024-11-22 17:57:53.594854: Current learning rate: 0.00311 +2024-11-22 17:58:12.636419: train_loss -0.7961 +2024-11-22 17:58:12.636638: val_loss -0.788 +2024-11-22 17:58:12.636714: Pseudo dice [0.8586] +2024-11-22 17:58:12.636790: Epoch time: 19.04 s +2024-11-22 17:58:13.535099: +2024-11-22 17:58:13.535338: Epoch 5816 +2024-11-22 17:58:13.535451: Current learning rate: 0.00311 +2024-11-22 17:58:32.197866: train_loss -0.7995 +2024-11-22 17:58:32.198164: val_loss -0.7691 +2024-11-22 17:58:32.198246: Pseudo dice [0.8467] +2024-11-22 17:58:32.198321: Epoch time: 18.66 s +2024-11-22 17:58:33.098220: +2024-11-22 17:58:33.098439: Epoch 5817 +2024-11-22 17:58:33.098552: Current learning rate: 0.00311 +2024-11-22 17:58:51.599645: train_loss -0.8018 +2024-11-22 17:58:51.602086: val_loss -0.7717 +2024-11-22 17:58:51.602203: Pseudo dice [0.8509] +2024-11-22 17:58:51.602292: Epoch time: 18.5 s +2024-11-22 17:58:52.509859: +2024-11-22 17:58:52.510076: Epoch 5818 +2024-11-22 17:58:52.510185: Current learning rate: 0.00311 +2024-11-22 17:59:11.292260: train_loss -0.8108 +2024-11-22 17:59:11.294001: val_loss -0.8001 +2024-11-22 17:59:11.294116: Pseudo dice [0.8586] +2024-11-22 17:59:11.294192: Epoch time: 18.78 s +2024-11-22 17:59:12.588582: +2024-11-22 17:59:12.588823: Epoch 5819 +2024-11-22 17:59:12.588935: Current learning rate: 0.0031 +2024-11-22 17:59:30.442774: train_loss -0.8057 +2024-11-22 17:59:30.442988: val_loss -0.7692 +2024-11-22 17:59:30.443075: Pseudo dice [0.841] +2024-11-22 17:59:30.443148: Epoch time: 17.86 s +2024-11-22 17:59:31.336694: +2024-11-22 17:59:31.336923: Epoch 5820 +2024-11-22 17:59:31.337042: Current learning rate: 0.0031 +2024-11-22 17:59:49.753659: train_loss -0.7975 +2024-11-22 17:59:49.753875: val_loss -0.7813 +2024-11-22 17:59:49.753948: Pseudo dice [0.862] +2024-11-22 17:59:49.754031: Epoch time: 18.42 s +2024-11-22 17:59:50.645844: +2024-11-22 17:59:50.646074: Epoch 5821 +2024-11-22 17:59:50.646188: Current learning rate: 0.0031 +2024-11-22 18:00:09.076877: train_loss -0.8027 +2024-11-22 18:00:09.077131: val_loss -0.7789 +2024-11-22 18:00:09.077209: Pseudo dice [0.8549] +2024-11-22 18:00:09.077312: Epoch time: 18.43 s +2024-11-22 18:00:09.977748: +2024-11-22 18:00:09.978027: Epoch 5822 +2024-11-22 18:00:09.978143: Current learning rate: 0.0031 +2024-11-22 18:00:28.499035: train_loss -0.8129 +2024-11-22 18:00:28.499280: val_loss -0.7652 +2024-11-22 18:00:28.499356: Pseudo dice [0.8316] +2024-11-22 18:00:28.499431: Epoch time: 18.52 s +2024-11-22 18:00:29.400875: +2024-11-22 18:00:29.401100: Epoch 5823 +2024-11-22 18:00:29.401213: Current learning rate: 0.0031 +2024-11-22 18:00:47.580266: train_loss -0.8006 +2024-11-22 18:00:47.580484: val_loss -0.7821 +2024-11-22 18:00:47.580578: Pseudo dice [0.844] +2024-11-22 18:00:47.580655: Epoch time: 18.18 s +2024-11-22 18:00:48.479829: +2024-11-22 18:00:48.480055: Epoch 5824 +2024-11-22 18:00:48.480163: Current learning rate: 0.0031 +2024-11-22 18:01:07.775721: train_loss -0.8084 +2024-11-22 18:01:07.775940: val_loss -0.789 +2024-11-22 18:01:07.776043: Pseudo dice [0.8474] +2024-11-22 18:01:07.776121: Epoch time: 19.3 s +2024-11-22 18:01:08.673995: +2024-11-22 18:01:08.674222: Epoch 5825 +2024-11-22 18:01:08.674334: Current learning rate: 0.0031 +2024-11-22 18:01:27.516361: train_loss -0.7957 +2024-11-22 18:01:27.516601: val_loss -0.7814 +2024-11-22 18:01:27.516677: Pseudo dice [0.859] +2024-11-22 18:01:27.516755: Epoch time: 18.84 s +2024-11-22 18:01:28.472961: +2024-11-22 18:01:28.473172: Epoch 5826 +2024-11-22 18:01:28.473283: Current learning rate: 0.0031 +2024-11-22 18:01:46.774935: train_loss -0.7949 +2024-11-22 18:01:46.775161: val_loss -0.7653 +2024-11-22 18:01:46.775251: Pseudo dice [0.8328] +2024-11-22 18:01:46.775325: Epoch time: 18.3 s +2024-11-22 18:01:47.664363: +2024-11-22 18:01:47.664610: Epoch 5827 +2024-11-22 18:01:47.664732: Current learning rate: 0.00309 +2024-11-22 18:02:05.808716: train_loss -0.7781 +2024-11-22 18:02:05.808937: val_loss -0.754 +2024-11-22 18:02:05.809026: Pseudo dice [0.8423] +2024-11-22 18:02:05.809104: Epoch time: 18.15 s +2024-11-22 18:02:06.700695: +2024-11-22 18:02:06.700943: Epoch 5828 +2024-11-22 18:02:06.701057: Current learning rate: 0.00309 +2024-11-22 18:02:24.296397: train_loss -0.7936 +2024-11-22 18:02:24.296615: val_loss -0.7382 +2024-11-22 18:02:24.296690: Pseudo dice [0.8415] +2024-11-22 18:02:24.296767: Epoch time: 17.6 s +2024-11-22 18:02:25.189536: +2024-11-22 18:02:25.189744: Epoch 5829 +2024-11-22 18:02:25.189855: Current learning rate: 0.00309 +2024-11-22 18:02:44.445676: train_loss -0.7905 +2024-11-22 18:02:44.445923: val_loss -0.7858 +2024-11-22 18:02:44.446004: Pseudo dice [0.8619] +2024-11-22 18:02:44.446082: Epoch time: 19.26 s +2024-11-22 18:02:45.348172: +2024-11-22 18:02:45.348388: Epoch 5830 +2024-11-22 18:02:45.348497: Current learning rate: 0.00309 +2024-11-22 18:03:03.928274: train_loss -0.8014 +2024-11-22 18:03:03.928969: val_loss -0.7822 +2024-11-22 18:03:03.929051: Pseudo dice [0.8494] +2024-11-22 18:03:03.929124: Epoch time: 18.58 s +2024-11-22 18:03:05.168291: +2024-11-22 18:03:05.168505: Epoch 5831 +2024-11-22 18:03:05.168617: Current learning rate: 0.00309 +2024-11-22 18:03:23.355662: train_loss -0.805 +2024-11-22 18:03:23.355896: val_loss -0.78 +2024-11-22 18:03:23.355973: Pseudo dice [0.852] +2024-11-22 18:03:23.356051: Epoch time: 18.19 s +2024-11-22 18:03:24.366780: +2024-11-22 18:03:24.367001: Epoch 5832 +2024-11-22 18:03:24.367109: Current learning rate: 0.00309 +2024-11-22 18:03:42.583741: train_loss -0.7883 +2024-11-22 18:03:42.584037: val_loss -0.7742 +2024-11-22 18:03:42.584208: Pseudo dice [0.8445] +2024-11-22 18:03:42.584306: Epoch time: 18.22 s +2024-11-22 18:03:43.481674: +2024-11-22 18:03:43.481900: Epoch 5833 +2024-11-22 18:03:43.482018: Current learning rate: 0.00309 +2024-11-22 18:04:02.352773: train_loss -0.7877 +2024-11-22 18:04:02.353008: val_loss -0.7726 +2024-11-22 18:04:02.353082: Pseudo dice [0.8392] +2024-11-22 18:04:02.353155: Epoch time: 18.87 s +2024-11-22 18:04:03.401269: +2024-11-22 18:04:03.401475: Epoch 5834 +2024-11-22 18:04:03.401587: Current learning rate: 0.00309 +2024-11-22 18:04:22.486382: train_loss -0.782 +2024-11-22 18:04:22.486617: val_loss -0.7679 +2024-11-22 18:04:22.486691: Pseudo dice [0.8572] +2024-11-22 18:04:22.486769: Epoch time: 19.09 s +2024-11-22 18:04:23.382607: +2024-11-22 18:04:23.382833: Epoch 5835 +2024-11-22 18:04:23.382943: Current learning rate: 0.00308 +2024-11-22 18:04:41.046239: train_loss -0.788 +2024-11-22 18:04:41.046468: val_loss -0.7492 +2024-11-22 18:04:41.046546: Pseudo dice [0.8213] +2024-11-22 18:04:41.046624: Epoch time: 17.66 s +2024-11-22 18:04:41.938928: +2024-11-22 18:04:41.939152: Epoch 5836 +2024-11-22 18:04:41.939260: Current learning rate: 0.00308 +2024-11-22 18:05:00.330479: train_loss -0.7828 +2024-11-22 18:05:00.330718: val_loss -0.7845 +2024-11-22 18:05:00.330792: Pseudo dice [0.853] +2024-11-22 18:05:00.330870: Epoch time: 18.39 s +2024-11-22 18:05:01.232250: +2024-11-22 18:05:01.232448: Epoch 5837 +2024-11-22 18:05:01.232558: Current learning rate: 0.00308 +2024-11-22 18:05:20.405025: train_loss -0.7922 +2024-11-22 18:05:20.405258: val_loss -0.7616 +2024-11-22 18:05:20.405335: Pseudo dice [0.849] +2024-11-22 18:05:20.405409: Epoch time: 19.17 s +2024-11-22 18:05:21.304082: +2024-11-22 18:05:21.304338: Epoch 5838 +2024-11-22 18:05:21.304449: Current learning rate: 0.00308 +2024-11-22 18:05:39.043543: train_loss -0.8068 +2024-11-22 18:05:39.043768: val_loss -0.7759 +2024-11-22 18:05:39.043846: Pseudo dice [0.8623] +2024-11-22 18:05:39.043919: Epoch time: 17.74 s +2024-11-22 18:05:39.942491: +2024-11-22 18:05:39.942713: Epoch 5839 +2024-11-22 18:05:39.942844: Current learning rate: 0.00308 +2024-11-22 18:05:57.506231: train_loss -0.7948 +2024-11-22 18:05:57.506457: val_loss -0.7423 +2024-11-22 18:05:57.506537: Pseudo dice [0.8232] +2024-11-22 18:05:57.506616: Epoch time: 17.56 s +2024-11-22 18:05:58.401582: +2024-11-22 18:05:58.401863: Epoch 5840 +2024-11-22 18:05:58.401973: Current learning rate: 0.00308 +2024-11-22 18:06:16.688526: train_loss -0.7861 +2024-11-22 18:06:16.688769: val_loss -0.7813 +2024-11-22 18:06:16.688846: Pseudo dice [0.8396] +2024-11-22 18:06:16.688929: Epoch time: 18.29 s +2024-11-22 18:06:17.581735: +2024-11-22 18:06:17.582116: Epoch 5841 +2024-11-22 18:06:17.582238: Current learning rate: 0.00308 +2024-11-22 18:06:36.370854: train_loss -0.7921 +2024-11-22 18:06:36.371097: val_loss -0.7827 +2024-11-22 18:06:36.371173: Pseudo dice [0.8584] +2024-11-22 18:06:36.371249: Epoch time: 18.79 s +2024-11-22 18:06:37.323910: +2024-11-22 18:06:37.324225: Epoch 5842 +2024-11-22 18:06:37.324336: Current learning rate: 0.00308 +2024-11-22 18:06:55.003654: train_loss -0.8014 +2024-11-22 18:06:55.004115: val_loss -0.795 +2024-11-22 18:06:55.004215: Pseudo dice [0.8541] +2024-11-22 18:06:55.004290: Epoch time: 17.68 s +2024-11-22 18:06:55.922595: +2024-11-22 18:06:55.923084: Epoch 5843 +2024-11-22 18:06:55.923213: Current learning rate: 0.00307 +2024-11-22 18:07:15.282494: train_loss -0.7925 +2024-11-22 18:07:15.282714: val_loss -0.7655 +2024-11-22 18:07:15.282794: Pseudo dice [0.8374] +2024-11-22 18:07:15.282884: Epoch time: 19.36 s +2024-11-22 18:07:16.183715: +2024-11-22 18:07:16.184174: Epoch 5844 +2024-11-22 18:07:16.184346: Current learning rate: 0.00307 +2024-11-22 18:07:33.869687: train_loss -0.7924 +2024-11-22 18:07:33.869918: val_loss -0.7771 +2024-11-22 18:07:33.870021: Pseudo dice [0.8621] +2024-11-22 18:07:33.870102: Epoch time: 17.69 s +2024-11-22 18:07:34.761131: +2024-11-22 18:07:34.761560: Epoch 5845 +2024-11-22 18:07:34.761689: Current learning rate: 0.00307 +2024-11-22 18:07:52.621408: train_loss -0.7958 +2024-11-22 18:07:52.621661: val_loss -0.7839 +2024-11-22 18:07:52.621741: Pseudo dice [0.8572] +2024-11-22 18:07:52.621817: Epoch time: 17.86 s +2024-11-22 18:07:53.512649: +2024-11-22 18:07:53.513073: Epoch 5846 +2024-11-22 18:07:53.513212: Current learning rate: 0.00307 +2024-11-22 18:08:11.048395: train_loss -0.7958 +2024-11-22 18:08:11.048616: val_loss -0.7795 +2024-11-22 18:08:11.048688: Pseudo dice [0.8473] +2024-11-22 18:08:11.048759: Epoch time: 17.54 s +2024-11-22 18:08:11.944219: +2024-11-22 18:08:11.944669: Epoch 5847 +2024-11-22 18:08:11.944803: Current learning rate: 0.00307 +2024-11-22 18:08:30.452887: train_loss -0.7846 +2024-11-22 18:08:30.453187: val_loss -0.7595 +2024-11-22 18:08:30.453265: Pseudo dice [0.8462] +2024-11-22 18:08:30.453342: Epoch time: 18.51 s +2024-11-22 18:08:31.348036: +2024-11-22 18:08:31.348465: Epoch 5848 +2024-11-22 18:08:31.348595: Current learning rate: 0.00307 +2024-11-22 18:08:50.098523: train_loss -0.7955 +2024-11-22 18:08:50.098766: val_loss -0.7858 +2024-11-22 18:08:50.101035: Pseudo dice [0.857] +2024-11-22 18:08:50.101190: Epoch time: 18.75 s +2024-11-22 18:08:51.012037: +2024-11-22 18:08:51.012500: Epoch 5849 +2024-11-22 18:08:51.012630: Current learning rate: 0.00307 +2024-11-22 18:09:09.348757: train_loss -0.7942 +2024-11-22 18:09:09.348972: val_loss -0.7577 +2024-11-22 18:09:09.349055: Pseudo dice [0.8346] +2024-11-22 18:09:09.349131: Epoch time: 18.34 s +2024-11-22 18:09:10.552390: +2024-11-22 18:09:10.552865: Epoch 5850 +2024-11-22 18:09:10.553004: Current learning rate: 0.00306 +2024-11-22 18:09:30.103931: train_loss -0.8054 +2024-11-22 18:09:30.104799: val_loss -0.7935 +2024-11-22 18:09:30.104877: Pseudo dice [0.8523] +2024-11-22 18:09:30.104953: Epoch time: 19.55 s +2024-11-22 18:09:30.997701: +2024-11-22 18:09:30.998125: Epoch 5851 +2024-11-22 18:09:30.998250: Current learning rate: 0.00306 +2024-11-22 18:09:49.511518: train_loss -0.8003 +2024-11-22 18:09:49.516933: val_loss -0.7805 +2024-11-22 18:09:49.530893: Pseudo dice [0.8519] +2024-11-22 18:09:49.531079: Epoch time: 18.51 s +2024-11-22 18:09:50.452711: +2024-11-22 18:09:50.453177: Epoch 5852 +2024-11-22 18:09:50.453307: Current learning rate: 0.00306 +2024-11-22 18:10:08.626109: train_loss -0.7988 +2024-11-22 18:10:08.626319: val_loss -0.7928 +2024-11-22 18:10:08.626393: Pseudo dice [0.8563] +2024-11-22 18:10:08.626490: Epoch time: 18.17 s +2024-11-22 18:10:09.523679: +2024-11-22 18:10:09.524089: Epoch 5853 +2024-11-22 18:10:09.524231: Current learning rate: 0.00306 +2024-11-22 18:10:29.279760: train_loss -0.8024 +2024-11-22 18:10:29.280245: val_loss -0.7847 +2024-11-22 18:10:29.280346: Pseudo dice [0.8622] +2024-11-22 18:10:29.280422: Epoch time: 19.76 s +2024-11-22 18:10:30.168228: +2024-11-22 18:10:30.168551: Epoch 5854 +2024-11-22 18:10:30.168663: Current learning rate: 0.00306 +2024-11-22 18:10:48.535615: train_loss -0.8022 +2024-11-22 18:10:48.535836: val_loss -0.7787 +2024-11-22 18:10:48.535924: Pseudo dice [0.8546] +2024-11-22 18:10:48.536010: Epoch time: 18.37 s +2024-11-22 18:10:49.437119: +2024-11-22 18:10:49.437351: Epoch 5855 +2024-11-22 18:10:49.437468: Current learning rate: 0.00306 +2024-11-22 18:11:07.917220: train_loss -0.7987 +2024-11-22 18:11:07.917478: val_loss -0.7815 +2024-11-22 18:11:07.917560: Pseudo dice [0.8496] +2024-11-22 18:11:07.917639: Epoch time: 18.48 s +2024-11-22 18:11:08.823150: +2024-11-22 18:11:08.823363: Epoch 5856 +2024-11-22 18:11:08.823470: Current learning rate: 0.00306 +2024-11-22 18:11:27.478363: train_loss -0.8013 +2024-11-22 18:11:27.478579: val_loss -0.7958 +2024-11-22 18:11:27.478659: Pseudo dice [0.8541] +2024-11-22 18:11:27.478763: Epoch time: 18.66 s +2024-11-22 18:11:28.374954: +2024-11-22 18:11:28.375171: Epoch 5857 +2024-11-22 18:11:28.375276: Current learning rate: 0.00306 +2024-11-22 18:11:46.388853: train_loss -0.7959 +2024-11-22 18:11:46.389079: val_loss -0.7641 +2024-11-22 18:11:46.389151: Pseudo dice [0.8324] +2024-11-22 18:11:46.389226: Epoch time: 18.01 s +2024-11-22 18:11:47.422536: +2024-11-22 18:11:47.422753: Epoch 5858 +2024-11-22 18:11:47.422859: Current learning rate: 0.00305 +2024-11-22 18:12:06.182174: train_loss -0.8043 +2024-11-22 18:12:06.182386: val_loss -0.7949 +2024-11-22 18:12:06.182461: Pseudo dice [0.8543] +2024-11-22 18:12:06.182535: Epoch time: 18.76 s +2024-11-22 18:12:07.082256: +2024-11-22 18:12:07.082469: Epoch 5859 +2024-11-22 18:12:07.082581: Current learning rate: 0.00305 +2024-11-22 18:12:26.168423: train_loss -0.7979 +2024-11-22 18:12:26.168702: val_loss -0.7757 +2024-11-22 18:12:26.168824: Pseudo dice [0.8554] +2024-11-22 18:12:26.168907: Epoch time: 19.09 s +2024-11-22 18:12:27.071656: +2024-11-22 18:12:27.071862: Epoch 5860 +2024-11-22 18:12:27.071967: Current learning rate: 0.00305 +2024-11-22 18:12:44.797976: train_loss -0.8019 +2024-11-22 18:12:44.798199: val_loss -0.7546 +2024-11-22 18:12:44.798277: Pseudo dice [0.8364] +2024-11-22 18:12:44.798350: Epoch time: 17.73 s +2024-11-22 18:12:45.732260: +2024-11-22 18:12:45.732457: Epoch 5861 +2024-11-22 18:12:45.732561: Current learning rate: 0.00305 +2024-11-22 18:13:04.852104: train_loss -0.805 +2024-11-22 18:13:04.852318: val_loss -0.7832 +2024-11-22 18:13:04.852390: Pseudo dice [0.8586] +2024-11-22 18:13:04.852464: Epoch time: 19.12 s +2024-11-22 18:13:05.744638: +2024-11-22 18:13:05.744822: Epoch 5862 +2024-11-22 18:13:05.744927: Current learning rate: 0.00305 +2024-11-22 18:13:23.912706: train_loss -0.8011 +2024-11-22 18:13:23.912925: val_loss -0.7728 +2024-11-22 18:13:23.915251: Pseudo dice [0.8523] +2024-11-22 18:13:23.915346: Epoch time: 18.17 s +2024-11-22 18:13:24.907240: +2024-11-22 18:13:24.907466: Epoch 5863 +2024-11-22 18:13:24.907579: Current learning rate: 0.00305 +2024-11-22 18:13:44.208315: train_loss -0.8033 +2024-11-22 18:13:44.208573: val_loss -0.7823 +2024-11-22 18:13:44.208655: Pseudo dice [0.8614] +2024-11-22 18:13:44.208742: Epoch time: 19.3 s +2024-11-22 18:13:45.110182: +2024-11-22 18:13:45.110396: Epoch 5864 +2024-11-22 18:13:45.110505: Current learning rate: 0.00305 +2024-11-22 18:14:02.810527: train_loss -0.8033 +2024-11-22 18:14:02.810739: val_loss -0.7845 +2024-11-22 18:14:02.810813: Pseudo dice [0.861] +2024-11-22 18:14:02.810886: Epoch time: 17.7 s +2024-11-22 18:14:04.068629: +2024-11-22 18:14:04.068845: Epoch 5865 +2024-11-22 18:14:04.068954: Current learning rate: 0.00305 +2024-11-22 18:14:22.859692: train_loss -0.8027 +2024-11-22 18:14:22.859925: val_loss -0.7398 +2024-11-22 18:14:22.860012: Pseudo dice [0.835] +2024-11-22 18:14:22.860088: Epoch time: 18.79 s +2024-11-22 18:14:23.759428: +2024-11-22 18:14:23.759642: Epoch 5866 +2024-11-22 18:14:23.759751: Current learning rate: 0.00304 +2024-11-22 18:14:41.539364: train_loss -0.808 +2024-11-22 18:14:41.544798: val_loss -0.7798 +2024-11-22 18:14:41.544914: Pseudo dice [0.8538] +2024-11-22 18:14:41.545016: Epoch time: 17.78 s +2024-11-22 18:14:42.620664: +2024-11-22 18:14:42.620893: Epoch 5867 +2024-11-22 18:14:42.621009: Current learning rate: 0.00304 +2024-11-22 18:15:00.452643: train_loss -0.8067 +2024-11-22 18:15:00.452863: val_loss -0.7712 +2024-11-22 18:15:00.458068: Pseudo dice [0.8589] +2024-11-22 18:15:00.458258: Epoch time: 17.83 s +2024-11-22 18:15:01.399270: +2024-11-22 18:15:01.399475: Epoch 5868 +2024-11-22 18:15:01.399585: Current learning rate: 0.00304 +2024-11-22 18:15:20.144385: train_loss -0.8013 +2024-11-22 18:15:20.144588: val_loss -0.7482 +2024-11-22 18:15:20.144661: Pseudo dice [0.8548] +2024-11-22 18:15:20.144736: Epoch time: 18.75 s +2024-11-22 18:15:21.039197: +2024-11-22 18:15:21.039510: Epoch 5869 +2024-11-22 18:15:21.039621: Current learning rate: 0.00304 +2024-11-22 18:15:39.919369: train_loss -0.7997 +2024-11-22 18:15:39.919590: val_loss -0.7847 +2024-11-22 18:15:39.919679: Pseudo dice [0.8387] +2024-11-22 18:15:39.919751: Epoch time: 18.88 s +2024-11-22 18:15:40.819221: +2024-11-22 18:15:40.819531: Epoch 5870 +2024-11-22 18:15:40.819644: Current learning rate: 0.00304 +2024-11-22 18:15:58.664753: train_loss -0.8062 +2024-11-22 18:15:58.664972: val_loss -0.7743 +2024-11-22 18:15:58.665057: Pseudo dice [0.8573] +2024-11-22 18:15:58.665140: Epoch time: 17.85 s +2024-11-22 18:15:59.561289: +2024-11-22 18:15:59.561500: Epoch 5871 +2024-11-22 18:15:59.561609: Current learning rate: 0.00304 +2024-11-22 18:16:17.989313: train_loss -0.8078 +2024-11-22 18:16:17.989553: val_loss -0.7792 +2024-11-22 18:16:17.989628: Pseudo dice [0.8584] +2024-11-22 18:16:17.989706: Epoch time: 18.43 s +2024-11-22 18:16:18.979752: +2024-11-22 18:16:18.979977: Epoch 5872 +2024-11-22 18:16:18.980095: Current learning rate: 0.00304 +2024-11-22 18:16:36.757592: train_loss -0.805 +2024-11-22 18:16:36.757813: val_loss -0.7705 +2024-11-22 18:16:36.757886: Pseudo dice [0.8609] +2024-11-22 18:16:36.757968: Epoch time: 17.78 s +2024-11-22 18:16:37.765479: +2024-11-22 18:16:37.765692: Epoch 5873 +2024-11-22 18:16:37.765806: Current learning rate: 0.00304 +2024-11-22 18:16:55.998409: train_loss -0.7944 +2024-11-22 18:16:55.998631: val_loss -0.7766 +2024-11-22 18:16:55.998707: Pseudo dice [0.8458] +2024-11-22 18:16:55.998782: Epoch time: 18.23 s +2024-11-22 18:16:56.901486: +2024-11-22 18:16:56.901700: Epoch 5874 +2024-11-22 18:16:56.901808: Current learning rate: 0.00303 +2024-11-22 18:17:14.770206: train_loss -0.7957 +2024-11-22 18:17:14.770668: val_loss -0.7994 +2024-11-22 18:17:14.770753: Pseudo dice [0.8565] +2024-11-22 18:17:14.770832: Epoch time: 17.87 s +2024-11-22 18:17:15.666202: +2024-11-22 18:17:15.666398: Epoch 5875 +2024-11-22 18:17:15.666507: Current learning rate: 0.00303 +2024-11-22 18:17:33.731179: train_loss -0.7982 +2024-11-22 18:17:33.731417: val_loss -0.7683 +2024-11-22 18:17:33.731491: Pseudo dice [0.8476] +2024-11-22 18:17:33.731568: Epoch time: 18.07 s +2024-11-22 18:17:34.963576: +2024-11-22 18:17:34.963776: Epoch 5876 +2024-11-22 18:17:34.963884: Current learning rate: 0.00303 +2024-11-22 18:17:54.073416: train_loss -0.7952 +2024-11-22 18:17:54.073645: val_loss -0.7612 +2024-11-22 18:17:54.073720: Pseudo dice [0.833] +2024-11-22 18:17:54.073795: Epoch time: 19.11 s +2024-11-22 18:17:54.972584: +2024-11-22 18:17:54.972926: Epoch 5877 +2024-11-22 18:17:54.973042: Current learning rate: 0.00303 +2024-11-22 18:18:13.434623: train_loss -0.8086 +2024-11-22 18:18:13.434855: val_loss -0.7808 +2024-11-22 18:18:13.434930: Pseudo dice [0.8463] +2024-11-22 18:18:13.435012: Epoch time: 18.46 s +2024-11-22 18:18:14.333748: +2024-11-22 18:18:14.333987: Epoch 5878 +2024-11-22 18:18:14.334101: Current learning rate: 0.00303 +2024-11-22 18:18:32.405986: train_loss -0.7994 +2024-11-22 18:18:32.408430: val_loss -0.7956 +2024-11-22 18:18:32.408521: Pseudo dice [0.8667] +2024-11-22 18:18:32.408604: Epoch time: 18.07 s +2024-11-22 18:18:33.383485: +2024-11-22 18:18:33.383715: Epoch 5879 +2024-11-22 18:18:33.383826: Current learning rate: 0.00303 +2024-11-22 18:18:51.941840: train_loss -0.7987 +2024-11-22 18:18:51.942060: val_loss -0.7918 +2024-11-22 18:18:51.942131: Pseudo dice [0.8534] +2024-11-22 18:18:51.942206: Epoch time: 18.56 s +2024-11-22 18:18:52.905225: +2024-11-22 18:18:52.905464: Epoch 5880 +2024-11-22 18:18:52.905575: Current learning rate: 0.00303 +2024-11-22 18:19:11.421042: train_loss -0.8061 +2024-11-22 18:19:11.423428: val_loss -0.77 +2024-11-22 18:19:11.423548: Pseudo dice [0.8491] +2024-11-22 18:19:11.423625: Epoch time: 18.52 s +2024-11-22 18:19:12.347689: +2024-11-22 18:19:12.347924: Epoch 5881 +2024-11-22 18:19:12.348048: Current learning rate: 0.00303 +2024-11-22 18:19:29.781038: train_loss -0.809 +2024-11-22 18:19:29.781246: val_loss -0.7906 +2024-11-22 18:19:29.781323: Pseudo dice [0.8632] +2024-11-22 18:19:29.781400: Epoch time: 17.43 s +2024-11-22 18:19:30.822265: +2024-11-22 18:19:30.822675: Epoch 5882 +2024-11-22 18:19:30.822785: Current learning rate: 0.00302 +2024-11-22 18:19:49.817095: train_loss -0.8124 +2024-11-22 18:19:49.817340: val_loss -0.771 +2024-11-22 18:19:49.817416: Pseudo dice [0.8433] +2024-11-22 18:19:49.817496: Epoch time: 19.0 s +2024-11-22 18:19:50.707541: +2024-11-22 18:19:50.707759: Epoch 5883 +2024-11-22 18:19:50.707879: Current learning rate: 0.00302 +2024-11-22 18:20:08.565140: train_loss -0.8067 +2024-11-22 18:20:08.565360: val_loss -0.7455 +2024-11-22 18:20:08.565438: Pseudo dice [0.8341] +2024-11-22 18:20:08.565512: Epoch time: 17.86 s +2024-11-22 18:20:09.458924: +2024-11-22 18:20:09.459160: Epoch 5884 +2024-11-22 18:20:09.459279: Current learning rate: 0.00302 +2024-11-22 18:20:27.805238: train_loss -0.7979 +2024-11-22 18:20:27.805465: val_loss -0.7762 +2024-11-22 18:20:27.805538: Pseudo dice [0.8594] +2024-11-22 18:20:27.805609: Epoch time: 18.35 s +2024-11-22 18:20:28.700344: +2024-11-22 18:20:28.700541: Epoch 5885 +2024-11-22 18:20:28.700646: Current learning rate: 0.00302 +2024-11-22 18:20:47.601963: train_loss -0.7834 +2024-11-22 18:20:47.602189: val_loss -0.768 +2024-11-22 18:20:47.602264: Pseudo dice [0.8331] +2024-11-22 18:20:47.602339: Epoch time: 18.9 s +2024-11-22 18:20:48.506254: +2024-11-22 18:20:48.506465: Epoch 5886 +2024-11-22 18:20:48.506574: Current learning rate: 0.00302 +2024-11-22 18:21:07.451438: train_loss -0.7905 +2024-11-22 18:21:07.453841: val_loss -0.7772 +2024-11-22 18:21:07.453987: Pseudo dice [0.8293] +2024-11-22 18:21:07.454080: Epoch time: 18.95 s +2024-11-22 18:21:08.467661: +2024-11-22 18:21:08.467881: Epoch 5887 +2024-11-22 18:21:08.468003: Current learning rate: 0.00302 +2024-11-22 18:21:27.401067: train_loss -0.7971 +2024-11-22 18:21:27.401269: val_loss -0.7716 +2024-11-22 18:21:27.401356: Pseudo dice [0.8338] +2024-11-22 18:21:27.401428: Epoch time: 18.93 s +2024-11-22 18:21:28.672228: +2024-11-22 18:21:28.672469: Epoch 5888 +2024-11-22 18:21:28.672582: Current learning rate: 0.00302 +2024-11-22 18:21:47.009724: train_loss -0.7935 +2024-11-22 18:21:47.009931: val_loss -0.7635 +2024-11-22 18:21:47.010011: Pseudo dice [0.8514] +2024-11-22 18:21:47.010089: Epoch time: 18.34 s +2024-11-22 18:21:47.924892: +2024-11-22 18:21:47.925110: Epoch 5889 +2024-11-22 18:21:47.925216: Current learning rate: 0.00301 +2024-11-22 18:22:06.475698: train_loss -0.7931 +2024-11-22 18:22:06.479941: val_loss -0.7952 +2024-11-22 18:22:06.480071: Pseudo dice [0.859] +2024-11-22 18:22:06.480152: Epoch time: 18.55 s +2024-11-22 18:22:07.434154: +2024-11-22 18:22:07.434401: Epoch 5890 +2024-11-22 18:22:07.434512: Current learning rate: 0.00301 +2024-11-22 18:22:26.521552: train_loss -0.7903 +2024-11-22 18:22:26.521824: val_loss -0.7645 +2024-11-22 18:22:26.521937: Pseudo dice [0.8307] +2024-11-22 18:22:26.522019: Epoch time: 19.09 s +2024-11-22 18:22:27.428108: +2024-11-22 18:22:27.428336: Epoch 5891 +2024-11-22 18:22:27.428461: Current learning rate: 0.00301 +2024-11-22 18:22:45.647937: train_loss -0.8034 +2024-11-22 18:22:45.648167: val_loss -0.7853 +2024-11-22 18:22:45.648241: Pseudo dice [0.851] +2024-11-22 18:22:45.648347: Epoch time: 18.22 s +2024-11-22 18:22:46.553708: +2024-11-22 18:22:46.553945: Epoch 5892 +2024-11-22 18:22:46.554069: Current learning rate: 0.00301 +2024-11-22 18:23:05.206841: train_loss -0.7944 +2024-11-22 18:23:05.207071: val_loss -0.7694 +2024-11-22 18:23:05.207146: Pseudo dice [0.8468] +2024-11-22 18:23:05.207221: Epoch time: 18.65 s +2024-11-22 18:23:06.099215: +2024-11-22 18:23:06.099524: Epoch 5893 +2024-11-22 18:23:06.099634: Current learning rate: 0.00301 +2024-11-22 18:23:24.776753: train_loss -0.7992 +2024-11-22 18:23:24.776969: val_loss -0.7982 +2024-11-22 18:23:24.777053: Pseudo dice [0.8541] +2024-11-22 18:23:24.777130: Epoch time: 18.68 s +2024-11-22 18:23:25.748644: +2024-11-22 18:23:25.748858: Epoch 5894 +2024-11-22 18:23:25.748967: Current learning rate: 0.00301 +2024-11-22 18:23:44.460821: train_loss -0.8004 +2024-11-22 18:23:44.461060: val_loss -0.7717 +2024-11-22 18:23:44.461135: Pseudo dice [0.851] +2024-11-22 18:23:44.462944: Epoch time: 18.71 s +2024-11-22 18:23:45.570873: +2024-11-22 18:23:45.571186: Epoch 5895 +2024-11-22 18:23:45.571306: Current learning rate: 0.00301 +2024-11-22 18:24:03.835697: train_loss -0.7992 +2024-11-22 18:24:03.835910: val_loss -0.7597 +2024-11-22 18:24:03.835985: Pseudo dice [0.8566] +2024-11-22 18:24:03.836111: Epoch time: 18.27 s +2024-11-22 18:24:04.734939: +2024-11-22 18:24:04.735147: Epoch 5896 +2024-11-22 18:24:04.735254: Current learning rate: 0.00301 +2024-11-22 18:24:23.597929: train_loss -0.813 +2024-11-22 18:24:23.598149: val_loss -0.7929 +2024-11-22 18:24:23.598225: Pseudo dice [0.872] +2024-11-22 18:24:23.598301: Epoch time: 18.86 s +2024-11-22 18:24:24.505721: +2024-11-22 18:24:24.505945: Epoch 5897 +2024-11-22 18:24:24.506062: Current learning rate: 0.003 +2024-11-22 18:24:43.232069: train_loss -0.7979 +2024-11-22 18:24:43.234651: val_loss -0.7647 +2024-11-22 18:24:43.234757: Pseudo dice [0.839] +2024-11-22 18:24:43.234834: Epoch time: 18.73 s +2024-11-22 18:24:44.168268: +2024-11-22 18:24:44.168489: Epoch 5898 +2024-11-22 18:24:44.168601: Current learning rate: 0.003 +2024-11-22 18:25:02.945668: train_loss -0.8077 +2024-11-22 18:25:02.945904: val_loss -0.7855 +2024-11-22 18:25:02.945976: Pseudo dice [0.861] +2024-11-22 18:25:02.946060: Epoch time: 18.78 s +2024-11-22 18:25:03.852787: +2024-11-22 18:25:03.853073: Epoch 5899 +2024-11-22 18:25:03.853191: Current learning rate: 0.003 +2024-11-22 18:25:21.895878: train_loss -0.8059 +2024-11-22 18:25:21.896387: val_loss -0.7596 +2024-11-22 18:25:21.896484: Pseudo dice [0.8481] +2024-11-22 18:25:21.896565: Epoch time: 18.04 s +2024-11-22 18:25:23.095828: +2024-11-22 18:25:23.096046: Epoch 5900 +2024-11-22 18:25:23.096152: Current learning rate: 0.003 +2024-11-22 18:25:42.045628: train_loss -0.7978 +2024-11-22 18:25:42.045858: val_loss -0.7791 +2024-11-22 18:25:42.045933: Pseudo dice [0.8648] +2024-11-22 18:25:42.046017: Epoch time: 18.95 s +2024-11-22 18:25:42.956192: +2024-11-22 18:25:42.956465: Epoch 5901 +2024-11-22 18:25:42.956573: Current learning rate: 0.003 +2024-11-22 18:26:01.475321: train_loss -0.8067 +2024-11-22 18:26:01.475574: val_loss -0.7721 +2024-11-22 18:26:01.475649: Pseudo dice [0.8514] +2024-11-22 18:26:01.475728: Epoch time: 18.52 s +2024-11-22 18:26:02.415654: +2024-11-22 18:26:02.415855: Epoch 5902 +2024-11-22 18:26:02.415962: Current learning rate: 0.003 +2024-11-22 18:26:21.545567: train_loss -0.8075 +2024-11-22 18:26:21.545790: val_loss -0.7943 +2024-11-22 18:26:21.545870: Pseudo dice [0.8492] +2024-11-22 18:26:21.545946: Epoch time: 19.13 s +2024-11-22 18:26:22.555153: +2024-11-22 18:26:22.555386: Epoch 5903 +2024-11-22 18:26:22.555506: Current learning rate: 0.003 +2024-11-22 18:26:40.023679: train_loss -0.8085 +2024-11-22 18:26:40.023890: val_loss -0.7801 +2024-11-22 18:26:40.023965: Pseudo dice [0.8318] +2024-11-22 18:26:40.024050: Epoch time: 17.47 s +2024-11-22 18:26:40.921542: +2024-11-22 18:26:40.921744: Epoch 5904 +2024-11-22 18:26:40.921852: Current learning rate: 0.003 +2024-11-22 18:26:59.591809: train_loss -0.7918 +2024-11-22 18:26:59.592040: val_loss -0.7621 +2024-11-22 18:26:59.592116: Pseudo dice [0.8447] +2024-11-22 18:26:59.592193: Epoch time: 18.67 s +2024-11-22 18:27:00.569432: +2024-11-22 18:27:00.569656: Epoch 5905 +2024-11-22 18:27:00.569767: Current learning rate: 0.00299 +2024-11-22 18:27:18.776289: train_loss -0.8075 +2024-11-22 18:27:18.776543: val_loss -0.7684 +2024-11-22 18:27:18.776622: Pseudo dice [0.8487] +2024-11-22 18:27:18.776701: Epoch time: 18.21 s +2024-11-22 18:27:19.750749: +2024-11-22 18:27:19.750953: Epoch 5906 +2024-11-22 18:27:19.751068: Current learning rate: 0.00299 +2024-11-22 18:27:37.422032: train_loss -0.794 +2024-11-22 18:27:37.422248: val_loss -0.7836 +2024-11-22 18:27:37.422323: Pseudo dice [0.8482] +2024-11-22 18:27:37.422398: Epoch time: 17.67 s +2024-11-22 18:27:38.335488: +2024-11-22 18:27:38.335724: Epoch 5907 +2024-11-22 18:27:38.335829: Current learning rate: 0.00299 +2024-11-22 18:27:57.327654: train_loss -0.8015 +2024-11-22 18:27:57.327884: val_loss -0.7748 +2024-11-22 18:27:57.327962: Pseudo dice [0.8471] +2024-11-22 18:27:57.328044: Epoch time: 18.99 s +2024-11-22 18:27:58.243843: +2024-11-22 18:27:58.244065: Epoch 5908 +2024-11-22 18:27:58.244181: Current learning rate: 0.00299 +2024-11-22 18:28:16.232305: train_loss -0.7964 +2024-11-22 18:28:16.233121: val_loss -0.7738 +2024-11-22 18:28:16.233216: Pseudo dice [0.8555] +2024-11-22 18:28:16.234644: Epoch time: 17.99 s +2024-11-22 18:28:17.137401: +2024-11-22 18:28:17.137623: Epoch 5909 +2024-11-22 18:28:17.137728: Current learning rate: 0.00299 +2024-11-22 18:28:34.899674: train_loss -0.7984 +2024-11-22 18:28:34.900016: val_loss -0.7881 +2024-11-22 18:28:34.900118: Pseudo dice [0.8493] +2024-11-22 18:28:34.900209: Epoch time: 17.76 s +2024-11-22 18:28:36.171691: +2024-11-22 18:28:36.172045: Epoch 5910 +2024-11-22 18:28:36.172156: Current learning rate: 0.00299 +2024-11-22 18:28:53.803931: train_loss -0.7986 +2024-11-22 18:28:53.804147: val_loss -0.7824 +2024-11-22 18:28:53.804222: Pseudo dice [0.8581] +2024-11-22 18:28:53.804296: Epoch time: 17.63 s +2024-11-22 18:28:54.693691: +2024-11-22 18:28:54.693919: Epoch 5911 +2024-11-22 18:28:54.694040: Current learning rate: 0.00299 +2024-11-22 18:29:12.885432: train_loss -0.8056 +2024-11-22 18:29:12.885651: val_loss -0.7629 +2024-11-22 18:29:12.885725: Pseudo dice [0.8493] +2024-11-22 18:29:12.885803: Epoch time: 18.19 s +2024-11-22 18:29:13.850021: +2024-11-22 18:29:13.850244: Epoch 5912 +2024-11-22 18:29:13.850359: Current learning rate: 0.00299 +2024-11-22 18:29:32.431073: train_loss -0.8079 +2024-11-22 18:29:32.431288: val_loss -0.7806 +2024-11-22 18:29:32.431367: Pseudo dice [0.8527] +2024-11-22 18:29:32.431444: Epoch time: 18.58 s +2024-11-22 18:29:33.334436: +2024-11-22 18:29:33.334652: Epoch 5913 +2024-11-22 18:29:33.334764: Current learning rate: 0.00298 +2024-11-22 18:29:51.428220: train_loss -0.8106 +2024-11-22 18:29:51.428467: val_loss -0.7765 +2024-11-22 18:29:51.428553: Pseudo dice [0.8515] +2024-11-22 18:29:51.428660: Epoch time: 18.09 s +2024-11-22 18:29:52.348551: +2024-11-22 18:29:52.348782: Epoch 5914 +2024-11-22 18:29:52.348899: Current learning rate: 0.00298 +2024-11-22 18:30:10.958076: train_loss -0.8065 +2024-11-22 18:30:10.958311: val_loss -0.7878 +2024-11-22 18:30:10.958441: Pseudo dice [0.8386] +2024-11-22 18:30:10.958521: Epoch time: 18.61 s +2024-11-22 18:30:11.907031: +2024-11-22 18:30:11.907253: Epoch 5915 +2024-11-22 18:30:11.907806: Current learning rate: 0.00298 +2024-11-22 18:30:30.334709: train_loss -0.7987 +2024-11-22 18:30:30.334955: val_loss -0.7731 +2024-11-22 18:30:30.335032: Pseudo dice [0.8413] +2024-11-22 18:30:30.335106: Epoch time: 18.43 s +2024-11-22 18:30:31.225083: +2024-11-22 18:30:31.225293: Epoch 5916 +2024-11-22 18:30:31.225400: Current learning rate: 0.00298 +2024-11-22 18:30:48.770775: train_loss -0.8063 +2024-11-22 18:30:48.771000: val_loss -0.7421 +2024-11-22 18:30:48.771073: Pseudo dice [0.837] +2024-11-22 18:30:48.771147: Epoch time: 17.55 s +2024-11-22 18:30:49.669137: +2024-11-22 18:30:49.669328: Epoch 5917 +2024-11-22 18:30:49.669440: Current learning rate: 0.00298 +2024-11-22 18:31:08.267061: train_loss -0.8094 +2024-11-22 18:31:08.267305: val_loss -0.7526 +2024-11-22 18:31:08.267381: Pseudo dice [0.8445] +2024-11-22 18:31:08.267460: Epoch time: 18.6 s +2024-11-22 18:31:09.161252: +2024-11-22 18:31:09.161484: Epoch 5918 +2024-11-22 18:31:09.161604: Current learning rate: 0.00298 +2024-11-22 18:31:27.026776: train_loss -0.8077 +2024-11-22 18:31:27.026994: val_loss -0.7959 +2024-11-22 18:31:27.027067: Pseudo dice [0.843] +2024-11-22 18:31:27.027141: Epoch time: 17.87 s +2024-11-22 18:31:27.929559: +2024-11-22 18:31:27.929765: Epoch 5919 +2024-11-22 18:31:27.929878: Current learning rate: 0.00298 +2024-11-22 18:31:46.226315: train_loss -0.8075 +2024-11-22 18:31:46.226535: val_loss -0.7867 +2024-11-22 18:31:46.226608: Pseudo dice [0.8583] +2024-11-22 18:31:46.226683: Epoch time: 18.3 s +2024-11-22 18:31:47.326954: +2024-11-22 18:31:47.327235: Epoch 5920 +2024-11-22 18:31:47.327343: Current learning rate: 0.00297 +2024-11-22 18:32:05.026485: train_loss -0.8112 +2024-11-22 18:32:05.031143: val_loss -0.7875 +2024-11-22 18:32:05.031245: Pseudo dice [0.8577] +2024-11-22 18:32:05.031331: Epoch time: 17.7 s +2024-11-22 18:32:05.936242: +2024-11-22 18:32:05.936446: Epoch 5921 +2024-11-22 18:32:05.936553: Current learning rate: 0.00297 +2024-11-22 18:32:24.977743: train_loss -0.8068 +2024-11-22 18:32:24.977960: val_loss -0.7742 +2024-11-22 18:32:24.983288: Pseudo dice [0.8514] +2024-11-22 18:32:24.983386: Epoch time: 19.04 s +2024-11-22 18:32:26.304622: +2024-11-22 18:32:26.304843: Epoch 5922 +2024-11-22 18:32:26.304955: Current learning rate: 0.00297 +2024-11-22 18:32:45.473499: train_loss -0.8027 +2024-11-22 18:32:45.473721: val_loss -0.7669 +2024-11-22 18:32:45.473796: Pseudo dice [0.8502] +2024-11-22 18:32:45.473874: Epoch time: 19.17 s +2024-11-22 18:32:46.405355: +2024-11-22 18:32:46.405638: Epoch 5923 +2024-11-22 18:32:46.405754: Current learning rate: 0.00297 +2024-11-22 18:33:05.215282: train_loss -0.8041 +2024-11-22 18:33:05.215508: val_loss -0.7718 +2024-11-22 18:33:05.215601: Pseudo dice [0.8414] +2024-11-22 18:33:05.215677: Epoch time: 18.81 s +2024-11-22 18:33:06.144911: +2024-11-22 18:33:06.145138: Epoch 5924 +2024-11-22 18:33:06.145244: Current learning rate: 0.00297 +2024-11-22 18:33:25.049669: train_loss -0.8028 +2024-11-22 18:33:25.049910: val_loss -0.76 +2024-11-22 18:33:25.050016: Pseudo dice [0.8464] +2024-11-22 18:33:25.050101: Epoch time: 18.91 s +2024-11-22 18:33:25.945290: +2024-11-22 18:33:25.945525: Epoch 5925 +2024-11-22 18:33:25.945638: Current learning rate: 0.00297 +2024-11-22 18:33:44.497046: train_loss -0.8071 +2024-11-22 18:33:44.497264: val_loss -0.7696 +2024-11-22 18:33:44.497338: Pseudo dice [0.8475] +2024-11-22 18:33:44.497414: Epoch time: 18.55 s +2024-11-22 18:33:45.523099: +2024-11-22 18:33:45.523345: Epoch 5926 +2024-11-22 18:33:45.523451: Current learning rate: 0.00297 +2024-11-22 18:34:04.803603: train_loss -0.805 +2024-11-22 18:34:04.803825: val_loss -0.7734 +2024-11-22 18:34:04.803899: Pseudo dice [0.8439] +2024-11-22 18:34:04.803977: Epoch time: 19.28 s +2024-11-22 18:34:06.031159: +2024-11-22 18:34:06.031391: Epoch 5927 +2024-11-22 18:34:06.031501: Current learning rate: 0.00297 +2024-11-22 18:34:24.519204: train_loss -0.8049 +2024-11-22 18:34:24.519415: val_loss -0.7938 +2024-11-22 18:34:24.519526: Pseudo dice [0.8607] +2024-11-22 18:34:24.519602: Epoch time: 18.49 s +2024-11-22 18:34:25.464171: +2024-11-22 18:34:25.464391: Epoch 5928 +2024-11-22 18:34:25.464500: Current learning rate: 0.00296 +2024-11-22 18:34:43.331108: train_loss -0.7903 +2024-11-22 18:34:43.331427: val_loss -0.7856 +2024-11-22 18:34:43.331510: Pseudo dice [0.8494] +2024-11-22 18:34:43.331589: Epoch time: 17.87 s +2024-11-22 18:34:44.230230: +2024-11-22 18:34:44.230433: Epoch 5929 +2024-11-22 18:34:44.230546: Current learning rate: 0.00296 +2024-11-22 18:35:03.405085: train_loss -0.7967 +2024-11-22 18:35:03.405318: val_loss -0.7957 +2024-11-22 18:35:03.405391: Pseudo dice [0.8523] +2024-11-22 18:35:03.405464: Epoch time: 19.18 s +2024-11-22 18:35:04.329617: +2024-11-22 18:35:04.329834: Epoch 5930 +2024-11-22 18:35:04.329951: Current learning rate: 0.00296 +2024-11-22 18:35:21.903356: train_loss -0.801 +2024-11-22 18:35:21.917051: val_loss -0.768 +2024-11-22 18:35:21.917283: Pseudo dice [0.8449] +2024-11-22 18:35:21.917374: Epoch time: 17.57 s +2024-11-22 18:35:23.048552: +2024-11-22 18:35:23.048801: Epoch 5931 +2024-11-22 18:35:23.048913: Current learning rate: 0.00296 +2024-11-22 18:35:41.790054: train_loss -0.8001 +2024-11-22 18:35:41.790266: val_loss -0.7745 +2024-11-22 18:35:41.790339: Pseudo dice [0.8452] +2024-11-22 18:35:41.790411: Epoch time: 18.74 s +2024-11-22 18:35:42.692654: +2024-11-22 18:35:42.692879: Epoch 5932 +2024-11-22 18:35:42.692987: Current learning rate: 0.00296 +2024-11-22 18:36:01.597076: train_loss -0.801 +2024-11-22 18:36:01.597313: val_loss -0.773 +2024-11-22 18:36:01.597389: Pseudo dice [0.8422] +2024-11-22 18:36:01.597471: Epoch time: 18.91 s +2024-11-22 18:36:02.895800: +2024-11-22 18:36:02.896025: Epoch 5933 +2024-11-22 18:36:02.896140: Current learning rate: 0.00296 +2024-11-22 18:36:22.078291: train_loss -0.8005 +2024-11-22 18:36:22.079132: val_loss -0.7516 +2024-11-22 18:36:22.079233: Pseudo dice [0.842] +2024-11-22 18:36:22.079308: Epoch time: 19.18 s +2024-11-22 18:36:22.968468: +2024-11-22 18:36:22.968695: Epoch 5934 +2024-11-22 18:36:22.968808: Current learning rate: 0.00296 +2024-11-22 18:36:41.402060: train_loss -0.7948 +2024-11-22 18:36:41.402285: val_loss -0.7727 +2024-11-22 18:36:41.402359: Pseudo dice [0.8574] +2024-11-22 18:36:41.402438: Epoch time: 18.43 s +2024-11-22 18:36:42.299267: +2024-11-22 18:36:42.299492: Epoch 5935 +2024-11-22 18:36:42.299606: Current learning rate: 0.00296 +2024-11-22 18:37:00.664550: train_loss -0.7996 +2024-11-22 18:37:00.664781: val_loss -0.7679 +2024-11-22 18:37:00.664854: Pseudo dice [0.8457] +2024-11-22 18:37:00.664929: Epoch time: 18.37 s +2024-11-22 18:37:01.578290: +2024-11-22 18:37:01.578502: Epoch 5936 +2024-11-22 18:37:01.578609: Current learning rate: 0.00295 +2024-11-22 18:37:19.832687: train_loss -0.798 +2024-11-22 18:37:19.832927: val_loss -0.7607 +2024-11-22 18:37:19.833007: Pseudo dice [0.8583] +2024-11-22 18:37:19.833084: Epoch time: 18.26 s +2024-11-22 18:37:20.742885: +2024-11-22 18:37:20.743113: Epoch 5937 +2024-11-22 18:37:20.743219: Current learning rate: 0.00295 +2024-11-22 18:37:39.312444: train_loss -0.8009 +2024-11-22 18:37:39.312665: val_loss -0.7693 +2024-11-22 18:37:39.312739: Pseudo dice [0.8189] +2024-11-22 18:37:39.312815: Epoch time: 18.57 s +2024-11-22 18:37:40.227098: +2024-11-22 18:37:40.227287: Epoch 5938 +2024-11-22 18:37:40.227394: Current learning rate: 0.00295 +2024-11-22 18:37:58.812144: train_loss -0.7942 +2024-11-22 18:37:58.812384: val_loss -0.7796 +2024-11-22 18:37:58.812459: Pseudo dice [0.8562] +2024-11-22 18:37:58.812534: Epoch time: 18.59 s +2024-11-22 18:37:59.723594: +2024-11-22 18:37:59.723879: Epoch 5939 +2024-11-22 18:37:59.723995: Current learning rate: 0.00295 +2024-11-22 18:38:17.967514: train_loss -0.799 +2024-11-22 18:38:17.967758: val_loss -0.7709 +2024-11-22 18:38:17.967836: Pseudo dice [0.8508] +2024-11-22 18:38:17.967921: Epoch time: 18.24 s +2024-11-22 18:38:18.870028: +2024-11-22 18:38:18.870234: Epoch 5940 +2024-11-22 18:38:18.870348: Current learning rate: 0.00295 +2024-11-22 18:38:37.277931: train_loss -0.7994 +2024-11-22 18:38:37.278171: val_loss -0.7667 +2024-11-22 18:38:37.302419: Pseudo dice [0.8432] +2024-11-22 18:38:37.302576: Epoch time: 18.41 s +2024-11-22 18:38:38.330914: +2024-11-22 18:38:38.331136: Epoch 5941 +2024-11-22 18:38:38.331244: Current learning rate: 0.00295 +2024-11-22 18:38:55.939320: train_loss -0.8044 +2024-11-22 18:38:55.941725: val_loss -0.774 +2024-11-22 18:38:55.941827: Pseudo dice [0.8579] +2024-11-22 18:38:55.941910: Epoch time: 17.61 s +2024-11-22 18:38:56.943287: +2024-11-22 18:38:56.943511: Epoch 5942 +2024-11-22 18:38:56.943625: Current learning rate: 0.00295 +2024-11-22 18:39:15.707643: train_loss -0.7937 +2024-11-22 18:39:15.707853: val_loss -0.7808 +2024-11-22 18:39:15.707926: Pseudo dice [0.8556] +2024-11-22 18:39:15.708031: Epoch time: 18.77 s +2024-11-22 18:39:16.599967: +2024-11-22 18:39:16.600196: Epoch 5943 +2024-11-22 18:39:16.600306: Current learning rate: 0.00295 +2024-11-22 18:39:35.212181: train_loss -0.7938 +2024-11-22 18:39:35.212425: val_loss -0.8068 +2024-11-22 18:39:35.212505: Pseudo dice [0.868] +2024-11-22 18:39:35.212589: Epoch time: 18.61 s +2024-11-22 18:39:36.106452: +2024-11-22 18:39:36.106685: Epoch 5944 +2024-11-22 18:39:36.106800: Current learning rate: 0.00294 +2024-11-22 18:39:53.715706: train_loss -0.7952 +2024-11-22 18:39:53.715928: val_loss -0.7717 +2024-11-22 18:39:53.716007: Pseudo dice [0.854] +2024-11-22 18:39:53.716225: Epoch time: 17.61 s +2024-11-22 18:39:55.043056: +2024-11-22 18:39:55.043266: Epoch 5945 +2024-11-22 18:39:55.043377: Current learning rate: 0.00294 +2024-11-22 18:40:12.615591: train_loss -0.7961 +2024-11-22 18:40:12.615934: val_loss -0.7902 +2024-11-22 18:40:12.616018: Pseudo dice [0.8451] +2024-11-22 18:40:12.616098: Epoch time: 17.57 s +2024-11-22 18:40:13.522583: +2024-11-22 18:40:13.522837: Epoch 5946 +2024-11-22 18:40:13.522946: Current learning rate: 0.00294 +2024-11-22 18:40:32.455346: train_loss -0.8021 +2024-11-22 18:40:32.455594: val_loss -0.7744 +2024-11-22 18:40:32.455668: Pseudo dice [0.8544] +2024-11-22 18:40:32.455748: Epoch time: 18.93 s +2024-11-22 18:40:33.353478: +2024-11-22 18:40:33.353703: Epoch 5947 +2024-11-22 18:40:33.353812: Current learning rate: 0.00294 +2024-11-22 18:40:52.598130: train_loss -0.808 +2024-11-22 18:40:52.598344: val_loss -0.7507 +2024-11-22 18:40:52.598422: Pseudo dice [0.8461] +2024-11-22 18:40:52.598496: Epoch time: 19.25 s +2024-11-22 18:40:53.485637: +2024-11-22 18:40:53.485849: Epoch 5948 +2024-11-22 18:40:53.485958: Current learning rate: 0.00294 +2024-11-22 18:41:11.892505: train_loss -0.8044 +2024-11-22 18:41:11.892718: val_loss -0.7664 +2024-11-22 18:41:11.892792: Pseudo dice [0.8437] +2024-11-22 18:41:11.892867: Epoch time: 18.41 s +2024-11-22 18:41:12.793501: +2024-11-22 18:41:12.793724: Epoch 5949 +2024-11-22 18:41:12.793840: Current learning rate: 0.00294 +2024-11-22 18:41:31.302845: train_loss -0.799 +2024-11-22 18:41:31.303070: val_loss -0.7678 +2024-11-22 18:41:31.303144: Pseudo dice [0.8328] +2024-11-22 18:41:31.303218: Epoch time: 18.51 s +2024-11-22 18:41:32.509771: +2024-11-22 18:41:32.509986: Epoch 5950 +2024-11-22 18:41:32.510101: Current learning rate: 0.00294 +2024-11-22 18:41:51.102806: train_loss -0.8065 +2024-11-22 18:41:51.103051: val_loss -0.7692 +2024-11-22 18:41:51.103130: Pseudo dice [0.8389] +2024-11-22 18:41:51.103214: Epoch time: 18.59 s +2024-11-22 18:41:52.007700: +2024-11-22 18:41:52.007910: Epoch 5951 +2024-11-22 18:41:52.008026: Current learning rate: 0.00293 +2024-11-22 18:42:10.591795: train_loss -0.8082 +2024-11-22 18:42:10.592014: val_loss -0.7913 +2024-11-22 18:42:10.592107: Pseudo dice [0.8535] +2024-11-22 18:42:10.592199: Epoch time: 18.58 s +2024-11-22 18:42:11.488215: +2024-11-22 18:42:11.488448: Epoch 5952 +2024-11-22 18:42:11.488559: Current learning rate: 0.00293 +2024-11-22 18:42:30.070883: train_loss -0.8062 +2024-11-22 18:42:30.071114: val_loss -0.7765 +2024-11-22 18:42:30.071188: Pseudo dice [0.8521] +2024-11-22 18:42:30.071262: Epoch time: 18.58 s +2024-11-22 18:42:30.975702: +2024-11-22 18:42:30.975930: Epoch 5953 +2024-11-22 18:42:30.976054: Current learning rate: 0.00293 +2024-11-22 18:42:48.697476: train_loss -0.7963 +2024-11-22 18:42:48.697690: val_loss -0.7719 +2024-11-22 18:42:48.697764: Pseudo dice [0.8523] +2024-11-22 18:42:48.697842: Epoch time: 17.72 s +2024-11-22 18:42:49.593359: +2024-11-22 18:42:49.593573: Epoch 5954 +2024-11-22 18:42:49.593683: Current learning rate: 0.00293 +2024-11-22 18:43:07.627946: train_loss -0.8049 +2024-11-22 18:43:07.628196: val_loss -0.7842 +2024-11-22 18:43:07.628277: Pseudo dice [0.8419] +2024-11-22 18:43:07.628361: Epoch time: 18.04 s +2024-11-22 18:43:08.695906: +2024-11-22 18:43:08.696106: Epoch 5955 +2024-11-22 18:43:08.696215: Current learning rate: 0.00293 +2024-11-22 18:43:26.900335: train_loss -0.8066 +2024-11-22 18:43:26.900557: val_loss -0.7382 +2024-11-22 18:43:26.900634: Pseudo dice [0.8309] +2024-11-22 18:43:26.900707: Epoch time: 18.21 s +2024-11-22 18:43:27.900203: +2024-11-22 18:43:27.900416: Epoch 5956 +2024-11-22 18:43:27.900522: Current learning rate: 0.00293 +2024-11-22 18:43:46.579702: train_loss -0.7998 +2024-11-22 18:43:46.580195: val_loss -0.7685 +2024-11-22 18:43:46.580296: Pseudo dice [0.8577] +2024-11-22 18:43:46.580375: Epoch time: 18.68 s +2024-11-22 18:43:47.484391: +2024-11-22 18:43:47.484677: Epoch 5957 +2024-11-22 18:43:47.484787: Current learning rate: 0.00293 +2024-11-22 18:44:05.303371: train_loss -0.8135 +2024-11-22 18:44:05.303607: val_loss -0.7918 +2024-11-22 18:44:05.303688: Pseudo dice [0.8478] +2024-11-22 18:44:05.303769: Epoch time: 17.82 s +2024-11-22 18:44:06.396143: +2024-11-22 18:44:06.396372: Epoch 5958 +2024-11-22 18:44:06.396484: Current learning rate: 0.00293 +2024-11-22 18:44:24.436449: train_loss -0.8081 +2024-11-22 18:44:24.436701: val_loss -0.8075 +2024-11-22 18:44:24.436773: Pseudo dice [0.8608] +2024-11-22 18:44:24.436851: Epoch time: 18.04 s +2024-11-22 18:44:25.331064: +2024-11-22 18:44:25.331298: Epoch 5959 +2024-11-22 18:44:25.331407: Current learning rate: 0.00292 +2024-11-22 18:44:43.183960: train_loss -0.8108 +2024-11-22 18:44:43.184194: val_loss -0.7879 +2024-11-22 18:44:43.184270: Pseudo dice [0.8667] +2024-11-22 18:44:43.184345: Epoch time: 17.85 s +2024-11-22 18:44:44.090067: +2024-11-22 18:44:44.090299: Epoch 5960 +2024-11-22 18:44:44.090409: Current learning rate: 0.00292 +2024-11-22 18:45:03.004498: train_loss -0.8044 +2024-11-22 18:45:03.004709: val_loss -0.7569 +2024-11-22 18:45:03.004783: Pseudo dice [0.847] +2024-11-22 18:45:03.004856: Epoch time: 18.92 s +2024-11-22 18:45:03.931753: +2024-11-22 18:45:03.931956: Epoch 5961 +2024-11-22 18:45:03.932073: Current learning rate: 0.00292 +2024-11-22 18:45:21.938618: train_loss -0.8035 +2024-11-22 18:45:21.938833: val_loss -0.7619 +2024-11-22 18:45:21.938906: Pseudo dice [0.8393] +2024-11-22 18:45:21.938980: Epoch time: 18.01 s +2024-11-22 18:45:22.832585: +2024-11-22 18:45:22.832782: Epoch 5962 +2024-11-22 18:45:22.832891: Current learning rate: 0.00292 +2024-11-22 18:45:41.039680: train_loss -0.8019 +2024-11-22 18:45:41.039920: val_loss -0.7761 +2024-11-22 18:45:41.040027: Pseudo dice [0.8583] +2024-11-22 18:45:41.040107: Epoch time: 18.21 s +2024-11-22 18:45:41.928781: +2024-11-22 18:45:41.928979: Epoch 5963 +2024-11-22 18:45:41.929089: Current learning rate: 0.00292 +2024-11-22 18:46:00.707783: train_loss -0.8026 +2024-11-22 18:46:00.708019: val_loss -0.7928 +2024-11-22 18:46:00.708097: Pseudo dice [0.8541] +2024-11-22 18:46:00.708171: Epoch time: 18.78 s +2024-11-22 18:46:01.613977: +2024-11-22 18:46:01.614216: Epoch 5964 +2024-11-22 18:46:01.614331: Current learning rate: 0.00292 +2024-11-22 18:46:20.718431: train_loss -0.8144 +2024-11-22 18:46:20.718712: val_loss -0.7711 +2024-11-22 18:46:20.718793: Pseudo dice [0.8566] +2024-11-22 18:46:20.718876: Epoch time: 19.11 s +2024-11-22 18:46:21.623977: +2024-11-22 18:46:21.624197: Epoch 5965 +2024-11-22 18:46:21.624311: Current learning rate: 0.00292 +2024-11-22 18:46:40.847155: train_loss -0.8058 +2024-11-22 18:46:40.847379: val_loss -0.7977 +2024-11-22 18:46:40.847452: Pseudo dice [0.865] +2024-11-22 18:46:40.847537: Epoch time: 19.22 s +2024-11-22 18:46:41.775098: +2024-11-22 18:46:41.775351: Epoch 5966 +2024-11-22 18:46:41.775461: Current learning rate: 0.00292 +2024-11-22 18:47:01.382718: train_loss -0.8021 +2024-11-22 18:47:01.382987: val_loss -0.7759 +2024-11-22 18:47:01.383072: Pseudo dice [0.8493] +2024-11-22 18:47:01.383151: Epoch time: 19.61 s +2024-11-22 18:47:02.383584: +2024-11-22 18:47:02.383807: Epoch 5967 +2024-11-22 18:47:02.383914: Current learning rate: 0.00291 +2024-11-22 18:47:20.526824: train_loss -0.8041 +2024-11-22 18:47:20.527061: val_loss -0.7673 +2024-11-22 18:47:20.527138: Pseudo dice [0.8381] +2024-11-22 18:47:20.527213: Epoch time: 18.14 s +2024-11-22 18:47:21.780874: +2024-11-22 18:47:21.781108: Epoch 5968 +2024-11-22 18:47:21.781224: Current learning rate: 0.00291 +2024-11-22 18:47:40.461215: train_loss -0.7996 +2024-11-22 18:47:40.461452: val_loss -0.7807 +2024-11-22 18:47:40.463699: Pseudo dice [0.8382] +2024-11-22 18:47:40.463823: Epoch time: 18.68 s +2024-11-22 18:47:41.377443: +2024-11-22 18:47:41.377683: Epoch 5969 +2024-11-22 18:47:41.377796: Current learning rate: 0.00291 +2024-11-22 18:47:59.463452: train_loss -0.8055 +2024-11-22 18:47:59.463798: val_loss -0.7632 +2024-11-22 18:47:59.463905: Pseudo dice [0.8343] +2024-11-22 18:47:59.464002: Epoch time: 18.09 s +2024-11-22 18:48:00.357721: +2024-11-22 18:48:00.357937: Epoch 5970 +2024-11-22 18:48:00.358048: Current learning rate: 0.00291 +2024-11-22 18:48:19.108258: train_loss -0.797 +2024-11-22 18:48:19.110666: val_loss -0.7853 +2024-11-22 18:48:19.110782: Pseudo dice [0.8558] +2024-11-22 18:48:19.111049: Epoch time: 18.75 s +2024-11-22 18:48:20.031497: +2024-11-22 18:48:20.031719: Epoch 5971 +2024-11-22 18:48:20.031843: Current learning rate: 0.00291 +2024-11-22 18:48:38.260265: train_loss -0.804 +2024-11-22 18:48:38.260475: val_loss -0.7907 +2024-11-22 18:48:38.260550: Pseudo dice [0.8433] +2024-11-22 18:48:38.260623: Epoch time: 18.23 s +2024-11-22 18:48:39.160005: +2024-11-22 18:48:39.160236: Epoch 5972 +2024-11-22 18:48:39.160346: Current learning rate: 0.00291 +2024-11-22 18:48:56.819767: train_loss -0.7985 +2024-11-22 18:48:56.822147: val_loss -0.7795 +2024-11-22 18:48:56.822276: Pseudo dice [0.8553] +2024-11-22 18:48:56.822355: Epoch time: 17.66 s +2024-11-22 18:48:57.747919: +2024-11-22 18:48:57.748135: Epoch 5973 +2024-11-22 18:48:57.748244: Current learning rate: 0.00291 +2024-11-22 18:49:16.114158: train_loss -0.8097 +2024-11-22 18:49:16.114409: val_loss -0.7723 +2024-11-22 18:49:16.114483: Pseudo dice [0.8425] +2024-11-22 18:49:16.114566: Epoch time: 18.37 s +2024-11-22 18:49:17.006739: +2024-11-22 18:49:17.007045: Epoch 5974 +2024-11-22 18:49:17.007163: Current learning rate: 0.00291 +2024-11-22 18:49:35.734436: train_loss -0.8012 +2024-11-22 18:49:35.734649: val_loss -0.7796 +2024-11-22 18:49:35.734729: Pseudo dice [0.8394] +2024-11-22 18:49:35.734808: Epoch time: 18.73 s +2024-11-22 18:49:36.771818: +2024-11-22 18:49:36.772101: Epoch 5975 +2024-11-22 18:49:36.772207: Current learning rate: 0.0029 +2024-11-22 18:49:55.240355: train_loss -0.8034 +2024-11-22 18:49:55.240624: val_loss -0.7908 +2024-11-22 18:49:55.240698: Pseudo dice [0.8498] +2024-11-22 18:49:55.240775: Epoch time: 18.47 s +2024-11-22 18:49:56.133179: +2024-11-22 18:49:56.133384: Epoch 5976 +2024-11-22 18:49:56.133493: Current learning rate: 0.0029 +2024-11-22 18:50:13.861870: train_loss -0.8103 +2024-11-22 18:50:13.862942: val_loss -0.7903 +2024-11-22 18:50:13.863053: Pseudo dice [0.8665] +2024-11-22 18:50:13.863130: Epoch time: 17.73 s +2024-11-22 18:50:14.918184: +2024-11-22 18:50:14.918418: Epoch 5977 +2024-11-22 18:50:14.918533: Current learning rate: 0.0029 +2024-11-22 18:50:32.607935: train_loss -0.8063 +2024-11-22 18:50:32.608167: val_loss -0.7735 +2024-11-22 18:50:32.608238: Pseudo dice [0.8598] +2024-11-22 18:50:32.608317: Epoch time: 17.69 s +2024-11-22 18:50:33.540818: +2024-11-22 18:50:33.541020: Epoch 5978 +2024-11-22 18:50:33.541131: Current learning rate: 0.0029 +2024-11-22 18:50:53.251918: train_loss -0.8052 +2024-11-22 18:50:53.252158: val_loss -0.7813 +2024-11-22 18:50:53.252311: Pseudo dice [0.8522] +2024-11-22 18:50:53.252390: Epoch time: 19.71 s +2024-11-22 18:50:54.484453: +2024-11-22 18:50:54.484663: Epoch 5979 +2024-11-22 18:50:54.484771: Current learning rate: 0.0029 +2024-11-22 18:51:12.919065: train_loss -0.8083 +2024-11-22 18:51:12.919296: val_loss -0.7895 +2024-11-22 18:51:12.919384: Pseudo dice [0.8538] +2024-11-22 18:51:12.919467: Epoch time: 18.44 s +2024-11-22 18:51:13.920868: +2024-11-22 18:51:13.921156: Epoch 5980 +2024-11-22 18:51:13.921266: Current learning rate: 0.0029 +2024-11-22 18:51:31.928493: train_loss -0.8105 +2024-11-22 18:51:31.928748: val_loss -0.7526 +2024-11-22 18:51:31.928824: Pseudo dice [0.8446] +2024-11-22 18:51:31.928912: Epoch time: 18.01 s +2024-11-22 18:51:32.823430: +2024-11-22 18:51:32.823720: Epoch 5981 +2024-11-22 18:51:32.823832: Current learning rate: 0.0029 +2024-11-22 18:51:50.878436: train_loss -0.8075 +2024-11-22 18:51:50.878667: val_loss -0.7854 +2024-11-22 18:51:50.878746: Pseudo dice [0.8425] +2024-11-22 18:51:50.878828: Epoch time: 18.06 s +2024-11-22 18:51:51.776862: +2024-11-22 18:51:51.777081: Epoch 5982 +2024-11-22 18:51:51.777190: Current learning rate: 0.00289 +2024-11-22 18:52:09.959099: train_loss -0.8003 +2024-11-22 18:52:09.959324: val_loss -0.7713 +2024-11-22 18:52:09.959401: Pseudo dice [0.8435] +2024-11-22 18:52:09.959477: Epoch time: 18.18 s +2024-11-22 18:52:10.967041: +2024-11-22 18:52:10.967244: Epoch 5983 +2024-11-22 18:52:10.967353: Current learning rate: 0.00289 +2024-11-22 18:52:28.955786: train_loss -0.8023 +2024-11-22 18:52:28.956014: val_loss -0.7938 +2024-11-22 18:52:28.956089: Pseudo dice [0.8539] +2024-11-22 18:52:28.956164: Epoch time: 17.99 s +2024-11-22 18:52:29.921099: +2024-11-22 18:52:29.921379: Epoch 5984 +2024-11-22 18:52:29.921492: Current learning rate: 0.00289 +2024-11-22 18:52:48.266328: train_loss -0.8065 +2024-11-22 18:52:48.271738: val_loss -0.7761 +2024-11-22 18:52:48.271852: Pseudo dice [0.8436] +2024-11-22 18:52:48.271929: Epoch time: 18.35 s +2024-11-22 18:52:49.385453: +2024-11-22 18:52:49.385664: Epoch 5985 +2024-11-22 18:52:49.385772: Current learning rate: 0.00289 +2024-11-22 18:53:07.648274: train_loss -0.8019 +2024-11-22 18:53:07.648516: val_loss -0.7561 +2024-11-22 18:53:07.648649: Pseudo dice [0.8482] +2024-11-22 18:53:07.648730: Epoch time: 18.26 s +2024-11-22 18:53:08.541323: +2024-11-22 18:53:08.541544: Epoch 5986 +2024-11-22 18:53:08.541664: Current learning rate: 0.00289 +2024-11-22 18:53:26.228247: train_loss -0.8033 +2024-11-22 18:53:26.228467: val_loss -0.7702 +2024-11-22 18:53:26.228541: Pseudo dice [0.8601] +2024-11-22 18:53:26.228624: Epoch time: 17.69 s +2024-11-22 18:53:27.126694: +2024-11-22 18:53:27.126905: Epoch 5987 +2024-11-22 18:53:27.127021: Current learning rate: 0.00289 +2024-11-22 18:53:45.363287: train_loss -0.7961 +2024-11-22 18:53:45.363509: val_loss -0.7664 +2024-11-22 18:53:45.363595: Pseudo dice [0.8566] +2024-11-22 18:53:45.363677: Epoch time: 18.24 s +2024-11-22 18:53:46.258373: +2024-11-22 18:53:46.258581: Epoch 5988 +2024-11-22 18:53:46.258691: Current learning rate: 0.00289 +2024-11-22 18:54:04.164087: train_loss -0.8062 +2024-11-22 18:54:04.164412: val_loss -0.7772 +2024-11-22 18:54:04.164494: Pseudo dice [0.8401] +2024-11-22 18:54:04.164576: Epoch time: 17.91 s +2024-11-22 18:54:05.070551: +2024-11-22 18:54:05.070772: Epoch 5989 +2024-11-22 18:54:05.070879: Current learning rate: 0.00289 +2024-11-22 18:54:23.354114: train_loss -0.8053 +2024-11-22 18:54:23.354327: val_loss -0.7933 +2024-11-22 18:54:23.354405: Pseudo dice [0.853] +2024-11-22 18:54:23.356686: Epoch time: 18.28 s +2024-11-22 18:54:24.276334: +2024-11-22 18:54:24.276600: Epoch 5990 +2024-11-22 18:54:24.276716: Current learning rate: 0.00288 +2024-11-22 18:54:42.528357: train_loss -0.8103 +2024-11-22 18:54:42.528643: val_loss -0.7802 +2024-11-22 18:54:42.528719: Pseudo dice [0.8579] +2024-11-22 18:54:42.528795: Epoch time: 18.25 s +2024-11-22 18:54:43.815698: +2024-11-22 18:54:43.815914: Epoch 5991 +2024-11-22 18:54:43.816031: Current learning rate: 0.00288 +2024-11-22 18:55:02.800318: train_loss -0.8034 +2024-11-22 18:55:02.800547: val_loss -0.7485 +2024-11-22 18:55:02.800621: Pseudo dice [0.8338] +2024-11-22 18:55:02.800696: Epoch time: 18.99 s +2024-11-22 18:55:03.701747: +2024-11-22 18:55:03.701960: Epoch 5992 +2024-11-22 18:55:03.702077: Current learning rate: 0.00288 +2024-11-22 18:55:23.344666: train_loss -0.8076 +2024-11-22 18:55:23.344914: val_loss -0.7709 +2024-11-22 18:55:23.344997: Pseudo dice [0.8412] +2024-11-22 18:55:23.345077: Epoch time: 19.64 s +2024-11-22 18:55:24.253833: +2024-11-22 18:55:24.254060: Epoch 5993 +2024-11-22 18:55:24.254168: Current learning rate: 0.00288 +2024-11-22 18:55:42.713137: train_loss -0.8135 +2024-11-22 18:55:42.713410: val_loss -0.7542 +2024-11-22 18:55:42.713487: Pseudo dice [0.8617] +2024-11-22 18:55:42.713564: Epoch time: 18.46 s +2024-11-22 18:55:43.614711: +2024-11-22 18:55:43.615007: Epoch 5994 +2024-11-22 18:55:43.615121: Current learning rate: 0.00288 +2024-11-22 18:56:01.804795: train_loss -0.8054 +2024-11-22 18:56:01.810187: val_loss -0.7862 +2024-11-22 18:56:01.810307: Pseudo dice [0.8608] +2024-11-22 18:56:01.810390: Epoch time: 18.19 s +2024-11-22 18:56:02.859099: +2024-11-22 18:56:02.859335: Epoch 5995 +2024-11-22 18:56:02.859447: Current learning rate: 0.00288 +2024-11-22 18:56:21.158478: train_loss -0.8069 +2024-11-22 18:56:21.158724: val_loss -0.7837 +2024-11-22 18:56:21.158802: Pseudo dice [0.8483] +2024-11-22 18:56:21.158891: Epoch time: 18.3 s +2024-11-22 18:56:22.056815: +2024-11-22 18:56:22.057016: Epoch 5996 +2024-11-22 18:56:22.057121: Current learning rate: 0.00288 +2024-11-22 18:56:41.894395: train_loss -0.8072 +2024-11-22 18:56:41.894615: val_loss -0.8008 +2024-11-22 18:56:41.894853: Pseudo dice [0.8609] +2024-11-22 18:56:41.894933: Epoch time: 19.84 s +2024-11-22 18:56:42.802067: +2024-11-22 18:56:42.802274: Epoch 5997 +2024-11-22 18:56:42.802382: Current learning rate: 0.00288 +2024-11-22 18:57:01.944418: train_loss -0.8078 +2024-11-22 18:57:01.944671: val_loss -0.7641 +2024-11-22 18:57:01.944748: Pseudo dice [0.8528] +2024-11-22 18:57:01.944824: Epoch time: 19.14 s +2024-11-22 18:57:02.844626: +2024-11-22 18:57:02.845028: Epoch 5998 +2024-11-22 18:57:02.845137: Current learning rate: 0.00287 +2024-11-22 18:57:22.226876: train_loss -0.8129 +2024-11-22 18:57:22.227114: val_loss -0.7659 +2024-11-22 18:57:22.227186: Pseudo dice [0.8262] +2024-11-22 18:57:22.227259: Epoch time: 19.38 s +2024-11-22 18:57:23.149164: +2024-11-22 18:57:23.149392: Epoch 5999 +2024-11-22 18:57:23.149507: Current learning rate: 0.00287 +2024-11-22 18:57:41.918384: train_loss -0.7945 +2024-11-22 18:57:41.918631: val_loss -0.7668 +2024-11-22 18:57:41.920934: Pseudo dice [0.8454] +2024-11-22 18:57:41.921045: Epoch time: 18.77 s +2024-11-22 18:57:43.133407: +2024-11-22 18:57:43.133631: Epoch 6000 +2024-11-22 18:57:43.133747: Current learning rate: 0.00287 +2024-11-22 18:58:01.317084: train_loss -0.7905 +2024-11-22 18:58:01.317295: val_loss -0.7761 +2024-11-22 18:58:01.317366: Pseudo dice [0.8434] +2024-11-22 18:58:01.317439: Epoch time: 18.18 s +2024-11-22 18:58:02.208139: +2024-11-22 18:58:02.208390: Epoch 6001 +2024-11-22 18:58:02.208499: Current learning rate: 0.00287 +2024-11-22 18:58:20.127592: train_loss -0.8015 +2024-11-22 18:58:20.127800: val_loss -0.7814 +2024-11-22 18:58:20.127871: Pseudo dice [0.8518] +2024-11-22 18:58:20.127944: Epoch time: 17.92 s +2024-11-22 18:58:21.150767: +2024-11-22 18:58:21.150952: Epoch 6002 +2024-11-22 18:58:21.151061: Current learning rate: 0.00287 +2024-11-22 18:58:39.982223: train_loss -0.7933 +2024-11-22 18:58:39.982769: val_loss -0.7654 +2024-11-22 18:58:39.982891: Pseudo dice [0.8512] +2024-11-22 18:58:39.982973: Epoch time: 18.83 s +2024-11-22 18:58:40.903618: +2024-11-22 18:58:40.903823: Epoch 6003 +2024-11-22 18:58:40.903932: Current learning rate: 0.00287 +2024-11-22 18:58:59.687936: train_loss -0.7877 +2024-11-22 18:58:59.688186: val_loss -0.7881 +2024-11-22 18:58:59.688260: Pseudo dice [0.8609] +2024-11-22 18:58:59.688336: Epoch time: 18.79 s +2024-11-22 18:59:00.585323: +2024-11-22 18:59:00.585550: Epoch 6004 +2024-11-22 18:59:00.585659: Current learning rate: 0.00287 +2024-11-22 18:59:19.176321: train_loss -0.8024 +2024-11-22 18:59:19.176563: val_loss -0.7438 +2024-11-22 18:59:19.176653: Pseudo dice [0.8393] +2024-11-22 18:59:19.176732: Epoch time: 18.59 s +2024-11-22 18:59:20.118753: +2024-11-22 18:59:20.118973: Epoch 6005 +2024-11-22 18:59:20.119088: Current learning rate: 0.00287 +2024-11-22 18:59:38.769902: train_loss -0.7997 +2024-11-22 18:59:38.770179: val_loss -0.7747 +2024-11-22 18:59:38.770257: Pseudo dice [0.8518] +2024-11-22 18:59:38.770334: Epoch time: 18.65 s +2024-11-22 18:59:39.668306: +2024-11-22 18:59:39.668507: Epoch 6006 +2024-11-22 18:59:39.668612: Current learning rate: 0.00286 +2024-11-22 18:59:59.030855: train_loss -0.7945 +2024-11-22 18:59:59.031110: val_loss -0.7602 +2024-11-22 18:59:59.031186: Pseudo dice [0.8502] +2024-11-22 18:59:59.031266: Epoch time: 19.36 s +2024-11-22 18:59:59.928952: +2024-11-22 18:59:59.929179: Epoch 6007 +2024-11-22 18:59:59.929289: Current learning rate: 0.00286 +2024-11-22 19:00:18.022789: train_loss -0.8056 +2024-11-22 19:00:18.023040: val_loss -0.7484 +2024-11-22 19:00:18.023133: Pseudo dice [0.8522] +2024-11-22 19:00:18.023211: Epoch time: 18.09 s +2024-11-22 19:00:18.913961: +2024-11-22 19:00:18.914161: Epoch 6008 +2024-11-22 19:00:18.914267: Current learning rate: 0.00286 +2024-11-22 19:00:37.903204: train_loss -0.7994 +2024-11-22 19:00:37.903429: val_loss -0.7669 +2024-11-22 19:00:37.903504: Pseudo dice [0.8419] +2024-11-22 19:00:37.903579: Epoch time: 18.99 s +2024-11-22 19:00:38.805127: +2024-11-22 19:00:38.805465: Epoch 6009 +2024-11-22 19:00:38.805580: Current learning rate: 0.00286 +2024-11-22 19:00:57.493766: train_loss -0.8031 +2024-11-22 19:00:57.493977: val_loss -0.7854 +2024-11-22 19:00:57.494071: Pseudo dice [0.8556] +2024-11-22 19:00:57.494154: Epoch time: 18.69 s +2024-11-22 19:00:58.414201: +2024-11-22 19:00:58.414410: Epoch 6010 +2024-11-22 19:00:58.414515: Current learning rate: 0.00286 +2024-11-22 19:01:16.127212: train_loss -0.8091 +2024-11-22 19:01:16.127459: val_loss -0.7714 +2024-11-22 19:01:16.127533: Pseudo dice [0.8581] +2024-11-22 19:01:16.127611: Epoch time: 17.71 s +2024-11-22 19:01:17.041009: +2024-11-22 19:01:17.041197: Epoch 6011 +2024-11-22 19:01:17.041308: Current learning rate: 0.00286 +2024-11-22 19:01:34.955657: train_loss -0.8078 +2024-11-22 19:01:34.955872: val_loss -0.7573 +2024-11-22 19:01:34.955947: Pseudo dice [0.8509] +2024-11-22 19:01:34.956025: Epoch time: 17.92 s +2024-11-22 19:01:35.854507: +2024-11-22 19:01:35.854719: Epoch 6012 +2024-11-22 19:01:35.854827: Current learning rate: 0.00286 +2024-11-22 19:01:55.196604: train_loss -0.8055 +2024-11-22 19:01:55.196820: val_loss -0.7757 +2024-11-22 19:01:55.196897: Pseudo dice [0.8523] +2024-11-22 19:01:55.196973: Epoch time: 19.34 s +2024-11-22 19:01:56.092696: +2024-11-22 19:01:56.092922: Epoch 6013 +2024-11-22 19:01:56.093038: Current learning rate: 0.00285 +2024-11-22 19:02:14.883632: train_loss -0.8108 +2024-11-22 19:02:14.883872: val_loss -0.7761 +2024-11-22 19:02:14.883951: Pseudo dice [0.8514] +2024-11-22 19:02:14.884036: Epoch time: 18.79 s +2024-11-22 19:02:16.174985: +2024-11-22 19:02:16.175222: Epoch 6014 +2024-11-22 19:02:16.175332: Current learning rate: 0.00285 +2024-11-22 19:02:34.447344: train_loss -0.8114 +2024-11-22 19:02:34.447582: val_loss -0.7935 +2024-11-22 19:02:34.447672: Pseudo dice [0.8561] +2024-11-22 19:02:34.447762: Epoch time: 18.27 s +2024-11-22 19:02:35.339596: +2024-11-22 19:02:35.339819: Epoch 6015 +2024-11-22 19:02:35.339930: Current learning rate: 0.00285 +2024-11-22 19:02:53.083228: train_loss -0.7977 +2024-11-22 19:02:53.083443: val_loss -0.743 +2024-11-22 19:02:53.084803: Pseudo dice [0.8226] +2024-11-22 19:02:53.085031: Epoch time: 17.74 s +2024-11-22 19:02:53.994451: +2024-11-22 19:02:53.994673: Epoch 6016 +2024-11-22 19:02:53.994781: Current learning rate: 0.00285 +2024-11-22 19:03:12.094332: train_loss -0.8078 +2024-11-22 19:03:12.094565: val_loss -0.7612 +2024-11-22 19:03:12.094645: Pseudo dice [0.8518] +2024-11-22 19:03:12.094722: Epoch time: 18.1 s +2024-11-22 19:03:13.013789: +2024-11-22 19:03:13.014014: Epoch 6017 +2024-11-22 19:03:13.014122: Current learning rate: 0.00285 +2024-11-22 19:03:32.186742: train_loss -0.8064 +2024-11-22 19:03:32.187645: val_loss -0.7748 +2024-11-22 19:03:32.187722: Pseudo dice [0.8482] +2024-11-22 19:03:32.187799: Epoch time: 19.17 s +2024-11-22 19:03:33.083458: +2024-11-22 19:03:33.083708: Epoch 6018 +2024-11-22 19:03:33.083837: Current learning rate: 0.00285 +2024-11-22 19:03:51.634463: train_loss -0.8048 +2024-11-22 19:03:51.634675: val_loss -0.7489 +2024-11-22 19:03:51.634748: Pseudo dice [0.8362] +2024-11-22 19:03:51.634821: Epoch time: 18.55 s +2024-11-22 19:03:52.532907: +2024-11-22 19:03:52.533123: Epoch 6019 +2024-11-22 19:03:52.533236: Current learning rate: 0.00285 +2024-11-22 19:04:11.239173: train_loss -0.7975 +2024-11-22 19:04:11.239385: val_loss -0.7851 +2024-11-22 19:04:11.239461: Pseudo dice [0.8423] +2024-11-22 19:04:11.239538: Epoch time: 18.71 s +2024-11-22 19:04:12.197329: +2024-11-22 19:04:12.197542: Epoch 6020 +2024-11-22 19:04:12.197651: Current learning rate: 0.00285 +2024-11-22 19:04:31.734912: train_loss -0.8008 +2024-11-22 19:04:31.735126: val_loss -0.7619 +2024-11-22 19:04:31.735208: Pseudo dice [0.847] +2024-11-22 19:04:31.735284: Epoch time: 19.54 s +2024-11-22 19:04:32.632954: +2024-11-22 19:04:32.633153: Epoch 6021 +2024-11-22 19:04:32.633259: Current learning rate: 0.00284 +2024-11-22 19:04:51.751663: train_loss -0.7971 +2024-11-22 19:04:51.751896: val_loss -0.7644 +2024-11-22 19:04:51.751971: Pseudo dice [0.8526] +2024-11-22 19:04:51.752058: Epoch time: 19.12 s +2024-11-22 19:04:52.707669: +2024-11-22 19:04:52.707883: Epoch 6022 +2024-11-22 19:04:52.708000: Current learning rate: 0.00284 +2024-11-22 19:05:10.803101: train_loss -0.7977 +2024-11-22 19:05:10.803318: val_loss -0.7554 +2024-11-22 19:05:10.803564: Pseudo dice [0.8367] +2024-11-22 19:05:10.803647: Epoch time: 18.1 s +2024-11-22 19:05:11.704796: +2024-11-22 19:05:11.705023: Epoch 6023 +2024-11-22 19:05:11.705134: Current learning rate: 0.00284 +2024-11-22 19:05:30.001966: train_loss -0.8073 +2024-11-22 19:05:30.002204: val_loss -0.7854 +2024-11-22 19:05:30.004486: Pseudo dice [0.8485] +2024-11-22 19:05:30.004587: Epoch time: 18.3 s +2024-11-22 19:05:31.015898: +2024-11-22 19:05:31.016114: Epoch 6024 +2024-11-22 19:05:31.016220: Current learning rate: 0.00284 +2024-11-22 19:05:50.193685: train_loss -0.8027 +2024-11-22 19:05:50.193904: val_loss -0.7547 +2024-11-22 19:05:50.193985: Pseudo dice [0.8346] +2024-11-22 19:05:50.194068: Epoch time: 19.18 s +2024-11-22 19:05:51.475267: +2024-11-22 19:05:51.475496: Epoch 6025 +2024-11-22 19:05:51.475599: Current learning rate: 0.00284 +2024-11-22 19:06:11.139891: train_loss -0.8039 +2024-11-22 19:06:11.140147: val_loss -0.7898 +2024-11-22 19:06:11.140221: Pseudo dice [0.8606] +2024-11-22 19:06:11.143013: Epoch time: 19.67 s +2024-11-22 19:06:12.094902: +2024-11-22 19:06:12.095112: Epoch 6026 +2024-11-22 19:06:12.095219: Current learning rate: 0.00284 +2024-11-22 19:06:29.941914: train_loss -0.8206 +2024-11-22 19:06:29.942140: val_loss -0.7554 +2024-11-22 19:06:29.942219: Pseudo dice [0.843] +2024-11-22 19:06:29.942294: Epoch time: 17.85 s +2024-11-22 19:06:30.839199: +2024-11-22 19:06:30.839413: Epoch 6027 +2024-11-22 19:06:30.839523: Current learning rate: 0.00284 +2024-11-22 19:06:50.218110: train_loss -0.8013 +2024-11-22 19:06:50.223526: val_loss -0.7927 +2024-11-22 19:06:50.223647: Pseudo dice [0.8387] +2024-11-22 19:06:50.223728: Epoch time: 19.38 s +2024-11-22 19:06:51.142372: +2024-11-22 19:06:51.142586: Epoch 6028 +2024-11-22 19:06:51.142699: Current learning rate: 0.00284 +2024-11-22 19:07:09.252625: train_loss -0.8056 +2024-11-22 19:07:09.252887: val_loss -0.7787 +2024-11-22 19:07:09.252964: Pseudo dice [0.8435] +2024-11-22 19:07:09.253053: Epoch time: 18.11 s +2024-11-22 19:07:10.158504: +2024-11-22 19:07:10.158707: Epoch 6029 +2024-11-22 19:07:10.158816: Current learning rate: 0.00283 +2024-11-22 19:07:28.139296: train_loss -0.8048 +2024-11-22 19:07:28.139503: val_loss -0.7786 +2024-11-22 19:07:28.139578: Pseudo dice [0.8644] +2024-11-22 19:07:28.139651: Epoch time: 17.98 s +2024-11-22 19:07:29.032319: +2024-11-22 19:07:29.032551: Epoch 6030 +2024-11-22 19:07:29.032660: Current learning rate: 0.00283 +2024-11-22 19:07:47.427115: train_loss -0.8102 +2024-11-22 19:07:47.427330: val_loss -0.7832 +2024-11-22 19:07:47.427405: Pseudo dice [0.8536] +2024-11-22 19:07:47.427483: Epoch time: 18.4 s +2024-11-22 19:07:48.320606: +2024-11-22 19:07:48.320815: Epoch 6031 +2024-11-22 19:07:48.320920: Current learning rate: 0.00283 +2024-11-22 19:08:07.230380: train_loss -0.8103 +2024-11-22 19:08:07.230603: val_loss -0.7416 +2024-11-22 19:08:07.230683: Pseudo dice [0.85] +2024-11-22 19:08:07.230761: Epoch time: 18.91 s +2024-11-22 19:08:08.232585: +2024-11-22 19:08:08.232811: Epoch 6032 +2024-11-22 19:08:08.232925: Current learning rate: 0.00283 +2024-11-22 19:08:26.755996: train_loss -0.8 +2024-11-22 19:08:26.756231: val_loss -0.7607 +2024-11-22 19:08:26.756308: Pseudo dice [0.8587] +2024-11-22 19:08:26.756385: Epoch time: 18.52 s +2024-11-22 19:08:27.654144: +2024-11-22 19:08:27.654365: Epoch 6033 +2024-11-22 19:08:27.654476: Current learning rate: 0.00283 +2024-11-22 19:08:46.628520: train_loss -0.81 +2024-11-22 19:08:46.628737: val_loss -0.7646 +2024-11-22 19:08:46.628811: Pseudo dice [0.8649] +2024-11-22 19:08:46.628885: Epoch time: 18.98 s +2024-11-22 19:08:47.554224: +2024-11-22 19:08:47.554441: Epoch 6034 +2024-11-22 19:08:47.554550: Current learning rate: 0.00283 +2024-11-22 19:09:05.844236: train_loss -0.8033 +2024-11-22 19:09:05.844457: val_loss -0.8013 +2024-11-22 19:09:05.844534: Pseudo dice [0.8616] +2024-11-22 19:09:05.844610: Epoch time: 18.29 s +2024-11-22 19:09:06.899631: +2024-11-22 19:09:06.899822: Epoch 6035 +2024-11-22 19:09:06.899930: Current learning rate: 0.00283 +2024-11-22 19:09:25.836532: train_loss -0.81 +2024-11-22 19:09:25.841944: val_loss -0.7703 +2024-11-22 19:09:25.842072: Pseudo dice [0.8476] +2024-11-22 19:09:25.842153: Epoch time: 18.94 s +2024-11-22 19:09:26.837567: +2024-11-22 19:09:26.837789: Epoch 6036 +2024-11-22 19:09:26.837912: Current learning rate: 0.00283 +2024-11-22 19:09:46.020141: train_loss -0.7934 +2024-11-22 19:09:46.020378: val_loss -0.781 +2024-11-22 19:09:46.020466: Pseudo dice [0.8416] +2024-11-22 19:09:46.020601: Epoch time: 19.18 s +2024-11-22 19:09:47.319297: +2024-11-22 19:09:47.319513: Epoch 6037 +2024-11-22 19:09:47.319623: Current learning rate: 0.00282 +2024-11-22 19:10:05.728441: train_loss -0.8069 +2024-11-22 19:10:05.728749: val_loss -0.7642 +2024-11-22 19:10:05.728832: Pseudo dice [0.8498] +2024-11-22 19:10:05.728909: Epoch time: 18.41 s +2024-11-22 19:10:06.635345: +2024-11-22 19:10:06.635573: Epoch 6038 +2024-11-22 19:10:06.635682: Current learning rate: 0.00282 +2024-11-22 19:10:25.274357: train_loss -0.8055 +2024-11-22 19:10:25.274604: val_loss -0.7864 +2024-11-22 19:10:25.274695: Pseudo dice [0.8541] +2024-11-22 19:10:25.274809: Epoch time: 18.64 s +2024-11-22 19:10:26.176823: +2024-11-22 19:10:26.177036: Epoch 6039 +2024-11-22 19:10:26.177141: Current learning rate: 0.00282 +2024-11-22 19:10:45.089723: train_loss -0.8004 +2024-11-22 19:10:45.089963: val_loss -0.7762 +2024-11-22 19:10:45.090046: Pseudo dice [0.8505] +2024-11-22 19:10:45.090125: Epoch time: 18.91 s +2024-11-22 19:10:45.985733: +2024-11-22 19:10:45.986032: Epoch 6040 +2024-11-22 19:10:45.986158: Current learning rate: 0.00282 +2024-11-22 19:11:05.280452: train_loss -0.8044 +2024-11-22 19:11:05.280660: val_loss -0.7805 +2024-11-22 19:11:05.280734: Pseudo dice [0.8522] +2024-11-22 19:11:05.280807: Epoch time: 19.3 s +2024-11-22 19:11:06.181660: +2024-11-22 19:11:06.181867: Epoch 6041 +2024-11-22 19:11:06.181973: Current learning rate: 0.00282 +2024-11-22 19:11:24.620563: train_loss -0.8063 +2024-11-22 19:11:24.625972: val_loss -0.7878 +2024-11-22 19:11:24.626127: Pseudo dice [0.8561] +2024-11-22 19:11:24.626209: Epoch time: 18.44 s +2024-11-22 19:11:25.674917: +2024-11-22 19:11:25.675212: Epoch 6042 +2024-11-22 19:11:25.675327: Current learning rate: 0.00282 +2024-11-22 19:11:43.702494: train_loss -0.8087 +2024-11-22 19:11:43.702711: val_loss -0.7665 +2024-11-22 19:11:43.702787: Pseudo dice [0.8576] +2024-11-22 19:11:43.702880: Epoch time: 18.03 s +2024-11-22 19:11:44.600798: +2024-11-22 19:11:44.601117: Epoch 6043 +2024-11-22 19:11:44.601236: Current learning rate: 0.00282 +2024-11-22 19:12:03.304280: train_loss -0.8064 +2024-11-22 19:12:03.304546: val_loss -0.7578 +2024-11-22 19:12:03.304620: Pseudo dice [0.8506] +2024-11-22 19:12:03.304700: Epoch time: 18.7 s +2024-11-22 19:12:04.251178: +2024-11-22 19:12:04.251364: Epoch 6044 +2024-11-22 19:12:04.251474: Current learning rate: 0.00281 +2024-11-22 19:12:22.891348: train_loss -0.8071 +2024-11-22 19:12:22.891592: val_loss -0.7722 +2024-11-22 19:12:22.891669: Pseudo dice [0.8452] +2024-11-22 19:12:22.891744: Epoch time: 18.64 s +2024-11-22 19:12:23.782913: +2024-11-22 19:12:23.783142: Epoch 6045 +2024-11-22 19:12:23.783264: Current learning rate: 0.00281 +2024-11-22 19:12:41.651802: train_loss -0.799 +2024-11-22 19:12:41.654214: val_loss -0.7649 +2024-11-22 19:12:41.654346: Pseudo dice [0.8539] +2024-11-22 19:12:41.654425: Epoch time: 17.87 s +2024-11-22 19:12:42.560925: +2024-11-22 19:12:42.561140: Epoch 6046 +2024-11-22 19:12:42.561247: Current learning rate: 0.00281 +2024-11-22 19:13:01.204243: train_loss -0.8009 +2024-11-22 19:13:01.204456: val_loss -0.7735 +2024-11-22 19:13:01.204531: Pseudo dice [0.8595] +2024-11-22 19:13:01.204606: Epoch time: 18.64 s +2024-11-22 19:13:02.250639: +2024-11-22 19:13:02.250854: Epoch 6047 +2024-11-22 19:13:02.250967: Current learning rate: 0.00281 +2024-11-22 19:13:20.628016: train_loss -0.8115 +2024-11-22 19:13:20.628252: val_loss -0.7803 +2024-11-22 19:13:20.628330: Pseudo dice [0.8613] +2024-11-22 19:13:20.628421: Epoch time: 18.38 s +2024-11-22 19:13:21.522272: +2024-11-22 19:13:21.522510: Epoch 6048 +2024-11-22 19:13:21.522620: Current learning rate: 0.00281 +2024-11-22 19:13:40.348573: train_loss -0.8061 +2024-11-22 19:13:40.349143: val_loss -0.7598 +2024-11-22 19:13:40.349257: Pseudo dice [0.8377] +2024-11-22 19:13:40.349334: Epoch time: 18.83 s +2024-11-22 19:13:41.238813: +2024-11-22 19:13:41.239030: Epoch 6049 +2024-11-22 19:13:41.239146: Current learning rate: 0.00281 +2024-11-22 19:13:59.993241: train_loss -0.808 +2024-11-22 19:13:59.993498: val_loss -0.7505 +2024-11-22 19:13:59.993573: Pseudo dice [0.8377] +2024-11-22 19:13:59.993647: Epoch time: 18.76 s +2024-11-22 19:14:01.204040: +2024-11-22 19:14:01.204346: Epoch 6050 +2024-11-22 19:14:01.204456: Current learning rate: 0.00281 +2024-11-22 19:14:20.515289: train_loss -0.8087 +2024-11-22 19:14:20.515505: val_loss -0.7715 +2024-11-22 19:14:20.515583: Pseudo dice [0.8564] +2024-11-22 19:14:20.515722: Epoch time: 19.31 s +2024-11-22 19:14:21.415714: +2024-11-22 19:14:21.415935: Epoch 6051 +2024-11-22 19:14:21.416059: Current learning rate: 0.00281 +2024-11-22 19:14:40.513970: train_loss -0.8077 +2024-11-22 19:14:40.514256: val_loss -0.7935 +2024-11-22 19:14:40.514337: Pseudo dice [0.8549] +2024-11-22 19:14:40.514421: Epoch time: 19.1 s +2024-11-22 19:14:41.422686: +2024-11-22 19:14:41.423025: Epoch 6052 +2024-11-22 19:14:41.423139: Current learning rate: 0.0028 +2024-11-22 19:14:59.857118: train_loss -0.806 +2024-11-22 19:14:59.857326: val_loss -0.769 +2024-11-22 19:14:59.857406: Pseudo dice [0.8506] +2024-11-22 19:14:59.857484: Epoch time: 18.44 s +2024-11-22 19:15:00.753652: +2024-11-22 19:15:00.753862: Epoch 6053 +2024-11-22 19:15:00.753973: Current learning rate: 0.0028 +2024-11-22 19:15:19.950084: train_loss -0.8102 +2024-11-22 19:15:19.952653: val_loss -0.7962 +2024-11-22 19:15:19.952756: Pseudo dice [0.8658] +2024-11-22 19:15:19.952835: Epoch time: 19.2 s +2024-11-22 19:15:20.920455: +2024-11-22 19:15:20.920675: Epoch 6054 +2024-11-22 19:15:20.920783: Current learning rate: 0.0028 +2024-11-22 19:15:39.787433: train_loss -0.8114 +2024-11-22 19:15:39.787657: val_loss -0.7732 +2024-11-22 19:15:39.787731: Pseudo dice [0.8372] +2024-11-22 19:15:39.787808: Epoch time: 18.87 s +2024-11-22 19:15:40.688097: +2024-11-22 19:15:40.688323: Epoch 6055 +2024-11-22 19:15:40.688432: Current learning rate: 0.0028 +2024-11-22 19:15:59.952216: train_loss -0.8001 +2024-11-22 19:15:59.952461: val_loss -0.7703 +2024-11-22 19:15:59.952533: Pseudo dice [0.8499] +2024-11-22 19:15:59.954828: Epoch time: 19.27 s +2024-11-22 19:16:00.888427: +2024-11-22 19:16:00.888650: Epoch 6056 +2024-11-22 19:16:00.888759: Current learning rate: 0.0028 +2024-11-22 19:16:18.824624: train_loss -0.8139 +2024-11-22 19:16:18.824840: val_loss -0.7669 +2024-11-22 19:16:18.824912: Pseudo dice [0.8358] +2024-11-22 19:16:18.824983: Epoch time: 17.94 s +2024-11-22 19:16:19.716452: +2024-11-22 19:16:19.716667: Epoch 6057 +2024-11-22 19:16:19.716777: Current learning rate: 0.0028 +2024-11-22 19:16:38.321654: train_loss -0.8108 +2024-11-22 19:16:38.321868: val_loss -0.7759 +2024-11-22 19:16:38.321948: Pseudo dice [0.8504] +2024-11-22 19:16:38.322035: Epoch time: 18.61 s +2024-11-22 19:16:39.219422: +2024-11-22 19:16:39.219656: Epoch 6058 +2024-11-22 19:16:39.219766: Current learning rate: 0.0028 +2024-11-22 19:16:58.209756: train_loss -0.7947 +2024-11-22 19:16:58.209975: val_loss -0.7747 +2024-11-22 19:16:58.210054: Pseudo dice [0.8514] +2024-11-22 19:16:58.210132: Epoch time: 18.99 s +2024-11-22 19:16:59.111654: +2024-11-22 19:16:59.111860: Epoch 6059 +2024-11-22 19:16:59.111972: Current learning rate: 0.0028 +2024-11-22 19:17:17.602216: train_loss -0.7994 +2024-11-22 19:17:17.602462: val_loss -0.7907 +2024-11-22 19:17:17.602534: Pseudo dice [0.8526] +2024-11-22 19:17:17.602611: Epoch time: 18.49 s +2024-11-22 19:17:18.501064: +2024-11-22 19:17:18.501302: Epoch 6060 +2024-11-22 19:17:18.501416: Current learning rate: 0.00279 +2024-11-22 19:17:37.517210: train_loss -0.7974 +2024-11-22 19:17:37.517425: val_loss -0.7769 +2024-11-22 19:17:37.517503: Pseudo dice [0.8466] +2024-11-22 19:17:37.517579: Epoch time: 19.02 s +2024-11-22 19:17:38.427048: +2024-11-22 19:17:38.427258: Epoch 6061 +2024-11-22 19:17:38.427365: Current learning rate: 0.00279 +2024-11-22 19:17:58.547827: train_loss -0.7892 +2024-11-22 19:17:58.548048: val_loss -0.7352 +2024-11-22 19:17:58.548141: Pseudo dice [0.835] +2024-11-22 19:17:58.548215: Epoch time: 20.12 s +2024-11-22 19:17:59.442303: +2024-11-22 19:17:59.442570: Epoch 6062 +2024-11-22 19:17:59.442682: Current learning rate: 0.00279 +2024-11-22 19:18:18.469598: train_loss -0.7804 +2024-11-22 19:18:18.469835: val_loss -0.7752 +2024-11-22 19:18:18.469907: Pseudo dice [0.8481] +2024-11-22 19:18:18.470353: Epoch time: 19.03 s +2024-11-22 19:18:19.370738: +2024-11-22 19:18:19.370952: Epoch 6063 +2024-11-22 19:18:19.371066: Current learning rate: 0.00279 +2024-11-22 19:18:37.662140: train_loss -0.7949 +2024-11-22 19:18:37.662422: val_loss -0.796 +2024-11-22 19:18:37.662499: Pseudo dice [0.8495] +2024-11-22 19:18:37.662574: Epoch time: 18.29 s +2024-11-22 19:18:38.556830: +2024-11-22 19:18:38.557070: Epoch 6064 +2024-11-22 19:18:38.557183: Current learning rate: 0.00279 +2024-11-22 19:18:57.029525: train_loss -0.8014 +2024-11-22 19:18:57.029728: val_loss -0.7601 +2024-11-22 19:18:57.029801: Pseudo dice [0.8505] +2024-11-22 19:18:57.029900: Epoch time: 18.47 s +2024-11-22 19:18:57.941488: +2024-11-22 19:18:57.941712: Epoch 6065 +2024-11-22 19:18:57.941825: Current learning rate: 0.00279 +2024-11-22 19:19:16.106221: train_loss -0.8001 +2024-11-22 19:19:16.106449: val_loss -0.7737 +2024-11-22 19:19:16.106528: Pseudo dice [0.8408] +2024-11-22 19:19:16.106616: Epoch time: 18.17 s +2024-11-22 19:19:17.003283: +2024-11-22 19:19:17.003504: Epoch 6066 +2024-11-22 19:19:17.003614: Current learning rate: 0.00279 +2024-11-22 19:19:35.921120: train_loss -0.8063 +2024-11-22 19:19:35.921365: val_loss -0.7747 +2024-11-22 19:19:35.921442: Pseudo dice [0.8486] +2024-11-22 19:19:35.921523: Epoch time: 18.92 s +2024-11-22 19:19:36.821048: +2024-11-22 19:19:36.821262: Epoch 6067 +2024-11-22 19:19:36.821384: Current learning rate: 0.00279 +2024-11-22 19:19:54.593646: train_loss -0.7955 +2024-11-22 19:19:54.598150: val_loss -0.7605 +2024-11-22 19:19:54.598290: Pseudo dice [0.8544] +2024-11-22 19:19:54.598372: Epoch time: 17.77 s +2024-11-22 19:19:55.632564: +2024-11-22 19:19:55.632769: Epoch 6068 +2024-11-22 19:19:55.632882: Current learning rate: 0.00278 +2024-11-22 19:20:16.430008: train_loss -0.8009 +2024-11-22 19:20:16.430225: val_loss -0.7684 +2024-11-22 19:20:16.430319: Pseudo dice [0.858] +2024-11-22 19:20:16.430394: Epoch time: 20.8 s +2024-11-22 19:20:17.332670: +2024-11-22 19:20:17.332889: Epoch 6069 +2024-11-22 19:20:17.333012: Current learning rate: 0.00278 +2024-11-22 19:20:36.919570: train_loss -0.8048 +2024-11-22 19:20:36.919823: val_loss -0.783 +2024-11-22 19:20:36.919899: Pseudo dice [0.8595] +2024-11-22 19:20:36.919976: Epoch time: 19.59 s +2024-11-22 19:20:37.815253: +2024-11-22 19:20:37.815459: Epoch 6070 +2024-11-22 19:20:37.815568: Current learning rate: 0.00278 +2024-11-22 19:20:57.543494: train_loss -0.7937 +2024-11-22 19:20:57.543741: val_loss -0.7642 +2024-11-22 19:20:57.543819: Pseudo dice [0.833] +2024-11-22 19:20:57.543909: Epoch time: 19.73 s +2024-11-22 19:20:58.800435: +2024-11-22 19:20:58.800630: Epoch 6071 +2024-11-22 19:20:58.800738: Current learning rate: 0.00278 +2024-11-22 19:21:17.338665: train_loss -0.7871 +2024-11-22 19:21:17.338883: val_loss -0.7666 +2024-11-22 19:21:17.338956: Pseudo dice [0.8595] +2024-11-22 19:21:17.339038: Epoch time: 18.54 s +2024-11-22 19:21:18.414499: +2024-11-22 19:21:18.414718: Epoch 6072 +2024-11-22 19:21:18.414827: Current learning rate: 0.00278 +2024-11-22 19:21:36.790656: train_loss -0.7993 +2024-11-22 19:21:36.790889: val_loss -0.7895 +2024-11-22 19:21:36.790969: Pseudo dice [0.8473] +2024-11-22 19:21:36.791091: Epoch time: 18.38 s +2024-11-22 19:21:37.689000: +2024-11-22 19:21:37.689223: Epoch 6073 +2024-11-22 19:21:37.689329: Current learning rate: 0.00278 +2024-11-22 19:21:55.885775: train_loss -0.792 +2024-11-22 19:21:55.886004: val_loss -0.7845 +2024-11-22 19:21:55.886085: Pseudo dice [0.8543] +2024-11-22 19:21:55.886165: Epoch time: 18.2 s +2024-11-22 19:21:56.787498: +2024-11-22 19:21:56.787711: Epoch 6074 +2024-11-22 19:21:56.787818: Current learning rate: 0.00278 +2024-11-22 19:22:15.446410: train_loss -0.7991 +2024-11-22 19:22:15.446824: val_loss -0.7577 +2024-11-22 19:22:15.446907: Pseudo dice [0.8584] +2024-11-22 19:22:15.446982: Epoch time: 18.66 s +2024-11-22 19:22:16.341845: +2024-11-22 19:22:16.342109: Epoch 6075 +2024-11-22 19:22:16.342219: Current learning rate: 0.00277 +2024-11-22 19:22:34.372053: train_loss -0.8024 +2024-11-22 19:22:34.372263: val_loss -0.7748 +2024-11-22 19:22:34.372352: Pseudo dice [0.8409] +2024-11-22 19:22:34.372433: Epoch time: 18.03 s +2024-11-22 19:22:35.269783: +2024-11-22 19:22:35.270018: Epoch 6076 +2024-11-22 19:22:35.270127: Current learning rate: 0.00277 +2024-11-22 19:22:54.152112: train_loss -0.8041 +2024-11-22 19:22:54.152328: val_loss -0.7804 +2024-11-22 19:22:54.152405: Pseudo dice [0.8628] +2024-11-22 19:22:54.152480: Epoch time: 18.88 s +2024-11-22 19:22:55.050847: +2024-11-22 19:22:55.051061: Epoch 6077 +2024-11-22 19:22:55.051170: Current learning rate: 0.00277 +2024-11-22 19:23:14.089081: train_loss -0.7964 +2024-11-22 19:23:14.089331: val_loss -0.7704 +2024-11-22 19:23:14.089404: Pseudo dice [0.8566] +2024-11-22 19:23:14.089484: Epoch time: 19.04 s +2024-11-22 19:23:14.991895: +2024-11-22 19:23:14.992131: Epoch 6078 +2024-11-22 19:23:14.992248: Current learning rate: 0.00277 +2024-11-22 19:23:33.252381: train_loss -0.8048 +2024-11-22 19:23:33.252593: val_loss -0.7778 +2024-11-22 19:23:33.252665: Pseudo dice [0.8586] +2024-11-22 19:23:33.252739: Epoch time: 18.26 s +2024-11-22 19:23:34.145838: +2024-11-22 19:23:34.146050: Epoch 6079 +2024-11-22 19:23:34.146160: Current learning rate: 0.00277 +2024-11-22 19:23:54.044628: train_loss -0.8 +2024-11-22 19:23:54.044893: val_loss -0.7817 +2024-11-22 19:23:54.044970: Pseudo dice [0.864] +2024-11-22 19:23:54.045050: Epoch time: 19.9 s +2024-11-22 19:23:54.935036: +2024-11-22 19:23:54.935230: Epoch 6080 +2024-11-22 19:23:54.935337: Current learning rate: 0.00277 +2024-11-22 19:24:14.421257: train_loss -0.8072 +2024-11-22 19:24:14.426667: val_loss -0.7841 +2024-11-22 19:24:14.426791: Pseudo dice [0.8455] +2024-11-22 19:24:14.426870: Epoch time: 19.49 s +2024-11-22 19:24:15.325451: +2024-11-22 19:24:15.325675: Epoch 6081 +2024-11-22 19:24:15.325795: Current learning rate: 0.00277 +2024-11-22 19:24:33.874081: train_loss -0.8126 +2024-11-22 19:24:33.874305: val_loss -0.7884 +2024-11-22 19:24:33.874382: Pseudo dice [0.8543] +2024-11-22 19:24:33.874461: Epoch time: 18.55 s +2024-11-22 19:24:35.178594: +2024-11-22 19:24:35.178813: Epoch 6082 +2024-11-22 19:24:35.178919: Current learning rate: 0.00277 +2024-11-22 19:24:52.904854: train_loss -0.8011 +2024-11-22 19:24:52.905106: val_loss -0.7986 +2024-11-22 19:24:52.905224: Pseudo dice [0.8548] +2024-11-22 19:24:52.905338: Epoch time: 17.73 s +2024-11-22 19:24:53.807611: +2024-11-22 19:24:53.807829: Epoch 6083 +2024-11-22 19:24:53.807943: Current learning rate: 0.00276 +2024-11-22 19:25:12.505763: train_loss -0.8102 +2024-11-22 19:25:12.505999: val_loss -0.7886 +2024-11-22 19:25:12.506076: Pseudo dice [0.859] +2024-11-22 19:25:12.506149: Epoch time: 18.7 s +2024-11-22 19:25:13.401257: +2024-11-22 19:25:13.401471: Epoch 6084 +2024-11-22 19:25:13.401576: Current learning rate: 0.00276 +2024-11-22 19:25:32.866966: train_loss -0.801 +2024-11-22 19:25:32.867190: val_loss -0.7873 +2024-11-22 19:25:32.867271: Pseudo dice [0.8596] +2024-11-22 19:25:32.867349: Epoch time: 19.47 s +2024-11-22 19:25:33.760896: +2024-11-22 19:25:33.761092: Epoch 6085 +2024-11-22 19:25:33.761198: Current learning rate: 0.00276 +2024-11-22 19:25:52.271974: train_loss -0.8069 +2024-11-22 19:25:52.272235: val_loss -0.7716 +2024-11-22 19:25:52.272315: Pseudo dice [0.8648] +2024-11-22 19:25:52.272402: Epoch time: 18.51 s +2024-11-22 19:25:52.272467: Yayy! New best EMA pseudo Dice: 0.8553 +2024-11-22 19:25:53.479215: +2024-11-22 19:25:53.479440: Epoch 6086 +2024-11-22 19:25:53.479550: Current learning rate: 0.00276 +2024-11-22 19:26:10.469309: train_loss -0.814 +2024-11-22 19:26:10.471672: val_loss -0.7627 +2024-11-22 19:26:10.471761: Pseudo dice [0.8601] +2024-11-22 19:26:10.471836: Epoch time: 16.99 s +2024-11-22 19:26:10.471899: Yayy! New best EMA pseudo Dice: 0.8558 +2024-11-22 19:26:11.676862: +2024-11-22 19:26:11.677070: Epoch 6087 +2024-11-22 19:26:11.677181: Current learning rate: 0.00276 +2024-11-22 19:26:30.342454: train_loss -0.8088 +2024-11-22 19:26:30.342674: val_loss -0.7671 +2024-11-22 19:26:30.342756: Pseudo dice [0.8287] +2024-11-22 19:26:30.342863: Epoch time: 18.67 s +2024-11-22 19:26:31.240160: +2024-11-22 19:26:31.240423: Epoch 6088 +2024-11-22 19:26:31.240542: Current learning rate: 0.00276 +2024-11-22 19:26:48.911626: train_loss -0.8155 +2024-11-22 19:26:48.911846: val_loss -0.7954 +2024-11-22 19:26:48.911926: Pseudo dice [0.8589] +2024-11-22 19:26:48.912009: Epoch time: 17.67 s +2024-11-22 19:26:49.808974: +2024-11-22 19:26:49.809198: Epoch 6089 +2024-11-22 19:26:49.809306: Current learning rate: 0.00276 +2024-11-22 19:27:07.804060: train_loss -0.7995 +2024-11-22 19:27:07.804312: val_loss -0.7923 +2024-11-22 19:27:07.804385: Pseudo dice [0.8692] +2024-11-22 19:27:07.804470: Epoch time: 18.0 s +2024-11-22 19:27:08.715459: +2024-11-22 19:27:08.715671: Epoch 6090 +2024-11-22 19:27:08.715782: Current learning rate: 0.00276 +2024-11-22 19:27:26.917371: train_loss -0.8104 +2024-11-22 19:27:26.917587: val_loss -0.7761 +2024-11-22 19:27:26.917666: Pseudo dice [0.8315] +2024-11-22 19:27:26.917742: Epoch time: 18.2 s +2024-11-22 19:27:27.815885: +2024-11-22 19:27:27.816167: Epoch 6091 +2024-11-22 19:27:27.816279: Current learning rate: 0.00275 +2024-11-22 19:27:45.625698: train_loss -0.8027 +2024-11-22 19:27:45.625920: val_loss -0.7512 +2024-11-22 19:27:45.626004: Pseudo dice [0.8457] +2024-11-22 19:27:45.626090: Epoch time: 17.81 s +2024-11-22 19:27:46.520710: +2024-11-22 19:27:46.520931: Epoch 6092 +2024-11-22 19:27:46.521051: Current learning rate: 0.00275 +2024-11-22 19:28:05.306492: train_loss -0.8143 +2024-11-22 19:28:05.306743: val_loss -0.7769 +2024-11-22 19:28:05.306817: Pseudo dice [0.8405] +2024-11-22 19:28:05.306905: Epoch time: 18.79 s +2024-11-22 19:28:06.203187: +2024-11-22 19:28:06.203383: Epoch 6093 +2024-11-22 19:28:06.203491: Current learning rate: 0.00275 +2024-11-22 19:28:24.916894: train_loss -0.8114 +2024-11-22 19:28:24.927975: val_loss -0.7926 +2024-11-22 19:28:24.928154: Pseudo dice [0.8532] +2024-11-22 19:28:24.928237: Epoch time: 18.71 s +2024-11-22 19:28:25.821346: +2024-11-22 19:28:25.821610: Epoch 6094 +2024-11-22 19:28:25.821720: Current learning rate: 0.00275 +2024-11-22 19:28:45.013108: train_loss -0.803 +2024-11-22 19:28:45.013334: val_loss -0.7885 +2024-11-22 19:28:45.013408: Pseudo dice [0.8615] +2024-11-22 19:28:45.013486: Epoch time: 19.19 s +2024-11-22 19:28:45.909274: +2024-11-22 19:28:45.909480: Epoch 6095 +2024-11-22 19:28:45.909587: Current learning rate: 0.00275 +2024-11-22 19:29:04.142250: train_loss -0.8047 +2024-11-22 19:29:04.142460: val_loss -0.7576 +2024-11-22 19:29:04.142535: Pseudo dice [0.8454] +2024-11-22 19:29:04.142608: Epoch time: 18.23 s +2024-11-22 19:29:05.044859: +2024-11-22 19:29:05.045169: Epoch 6096 +2024-11-22 19:29:05.045286: Current learning rate: 0.00275 +2024-11-22 19:29:24.612238: train_loss -0.7996 +2024-11-22 19:29:24.618810: val_loss -0.7865 +2024-11-22 19:29:24.618936: Pseudo dice [0.8448] +2024-11-22 19:29:24.619027: Epoch time: 19.57 s +2024-11-22 19:29:25.674335: +2024-11-22 19:29:25.674555: Epoch 6097 +2024-11-22 19:29:25.674662: Current learning rate: 0.00275 +2024-11-22 19:29:43.545135: train_loss -0.8083 +2024-11-22 19:29:43.547662: val_loss -0.7826 +2024-11-22 19:29:43.547755: Pseudo dice [0.8473] +2024-11-22 19:29:43.547832: Epoch time: 17.87 s +2024-11-22 19:29:44.508223: +2024-11-22 19:29:44.508466: Epoch 6098 +2024-11-22 19:29:44.508577: Current learning rate: 0.00274 +2024-11-22 19:30:03.006428: train_loss -0.8086 +2024-11-22 19:30:03.006640: val_loss -0.807 +2024-11-22 19:30:03.006714: Pseudo dice [0.852] +2024-11-22 19:30:03.006790: Epoch time: 18.5 s +2024-11-22 19:30:03.902718: +2024-11-22 19:30:03.902929: Epoch 6099 +2024-11-22 19:30:03.903042: Current learning rate: 0.00274 +2024-11-22 19:30:22.259824: train_loss -0.8119 +2024-11-22 19:30:22.260108: val_loss -0.7675 +2024-11-22 19:30:22.260186: Pseudo dice [0.8514] +2024-11-22 19:30:22.260267: Epoch time: 18.36 s +2024-11-22 19:30:23.465683: +2024-11-22 19:30:23.466022: Epoch 6100 +2024-11-22 19:30:23.466140: Current learning rate: 0.00274 +2024-11-22 19:30:41.203426: train_loss -0.8003 +2024-11-22 19:30:41.205581: val_loss -0.7704 +2024-11-22 19:30:41.205678: Pseudo dice [0.855] +2024-11-22 19:30:41.205764: Epoch time: 17.74 s +2024-11-22 19:30:42.117173: +2024-11-22 19:30:42.117393: Epoch 6101 +2024-11-22 19:30:42.117507: Current learning rate: 0.00274 +2024-11-22 19:30:59.835938: train_loss -0.8054 +2024-11-22 19:30:59.836171: val_loss -0.7447 +2024-11-22 19:30:59.836243: Pseudo dice [0.8399] +2024-11-22 19:30:59.836357: Epoch time: 17.72 s +2024-11-22 19:31:00.747060: +2024-11-22 19:31:00.747322: Epoch 6102 +2024-11-22 19:31:00.747437: Current learning rate: 0.00274 +2024-11-22 19:31:18.511367: train_loss -0.8077 +2024-11-22 19:31:18.511584: val_loss -0.8025 +2024-11-22 19:31:18.511658: Pseudo dice [0.8641] +2024-11-22 19:31:18.511733: Epoch time: 17.77 s +2024-11-22 19:31:19.471128: +2024-11-22 19:31:19.471373: Epoch 6103 +2024-11-22 19:31:19.471480: Current learning rate: 0.00274 +2024-11-22 19:31:37.517897: train_loss -0.809 +2024-11-22 19:31:37.518135: val_loss -0.7826 +2024-11-22 19:31:37.518279: Pseudo dice [0.8402] +2024-11-22 19:31:37.518358: Epoch time: 18.05 s +2024-11-22 19:31:38.412086: +2024-11-22 19:31:38.412304: Epoch 6104 +2024-11-22 19:31:38.412419: Current learning rate: 0.00274 +2024-11-22 19:31:57.619468: train_loss -0.7962 +2024-11-22 19:31:57.619706: val_loss -0.7882 +2024-11-22 19:31:57.619781: Pseudo dice [0.8421] +2024-11-22 19:31:57.619867: Epoch time: 19.21 s +2024-11-22 19:31:58.515055: +2024-11-22 19:31:58.515296: Epoch 6105 +2024-11-22 19:31:58.515405: Current learning rate: 0.00274 +2024-11-22 19:32:16.698295: train_loss -0.8031 +2024-11-22 19:32:16.698505: val_loss -0.7906 +2024-11-22 19:32:16.698577: Pseudo dice [0.859] +2024-11-22 19:32:16.698650: Epoch time: 18.18 s +2024-11-22 19:32:17.597634: +2024-11-22 19:32:17.597831: Epoch 6106 +2024-11-22 19:32:17.597939: Current learning rate: 0.00273 +2024-11-22 19:32:35.772659: train_loss -0.802 +2024-11-22 19:32:35.772881: val_loss -0.7851 +2024-11-22 19:32:35.772958: Pseudo dice [0.8618] +2024-11-22 19:32:35.773041: Epoch time: 18.18 s +2024-11-22 19:32:36.672137: +2024-11-22 19:32:36.672363: Epoch 6107 +2024-11-22 19:32:36.672478: Current learning rate: 0.00273 +2024-11-22 19:32:55.477814: train_loss -0.8092 +2024-11-22 19:32:55.478066: val_loss -0.8007 +2024-11-22 19:32:55.478141: Pseudo dice [0.8539] +2024-11-22 19:32:55.478220: Epoch time: 18.81 s +2024-11-22 19:32:56.378689: +2024-11-22 19:32:56.378914: Epoch 6108 +2024-11-22 19:32:56.379028: Current learning rate: 0.00273 +2024-11-22 19:33:14.003216: train_loss -0.8066 +2024-11-22 19:33:14.004655: val_loss -0.7768 +2024-11-22 19:33:14.004748: Pseudo dice [0.8568] +2024-11-22 19:33:14.004825: Epoch time: 17.63 s +2024-11-22 19:33:14.915421: +2024-11-22 19:33:14.915643: Epoch 6109 +2024-11-22 19:33:14.915755: Current learning rate: 0.00273 +2024-11-22 19:33:34.532903: train_loss -0.8009 +2024-11-22 19:33:34.533145: val_loss -0.7719 +2024-11-22 19:33:34.533243: Pseudo dice [0.8476] +2024-11-22 19:33:34.533324: Epoch time: 19.62 s +2024-11-22 19:33:35.425359: +2024-11-22 19:33:35.425579: Epoch 6110 +2024-11-22 19:33:35.425690: Current learning rate: 0.00273 +2024-11-22 19:33:54.219354: train_loss -0.8016 +2024-11-22 19:33:54.219580: val_loss -0.7674 +2024-11-22 19:33:54.219656: Pseudo dice [0.859] +2024-11-22 19:33:54.219730: Epoch time: 18.79 s +2024-11-22 19:33:55.120867: +2024-11-22 19:33:55.121109: Epoch 6111 +2024-11-22 19:33:55.121221: Current learning rate: 0.00273 +2024-11-22 19:34:14.142822: train_loss -0.8029 +2024-11-22 19:34:14.143084: val_loss -0.7655 +2024-11-22 19:34:14.143164: Pseudo dice [0.8473] +2024-11-22 19:34:14.143249: Epoch time: 19.02 s +2024-11-22 19:34:15.066641: +2024-11-22 19:34:15.066844: Epoch 6112 +2024-11-22 19:34:15.066958: Current learning rate: 0.00273 +2024-11-22 19:34:33.588262: train_loss -0.802 +2024-11-22 19:34:33.588489: val_loss -0.7711 +2024-11-22 19:34:33.588567: Pseudo dice [0.8461] +2024-11-22 19:34:33.588668: Epoch time: 18.52 s +2024-11-22 19:34:34.484325: +2024-11-22 19:34:34.484533: Epoch 6113 +2024-11-22 19:34:34.484638: Current learning rate: 0.00273 +2024-11-22 19:34:53.766848: train_loss -0.8006 +2024-11-22 19:34:53.767075: val_loss -0.7712 +2024-11-22 19:34:53.767150: Pseudo dice [0.8408] +2024-11-22 19:34:53.767227: Epoch time: 19.28 s +2024-11-22 19:34:54.657929: +2024-11-22 19:34:54.658178: Epoch 6114 +2024-11-22 19:34:54.658290: Current learning rate: 0.00272 +2024-11-22 19:35:12.590212: train_loss -0.8115 +2024-11-22 19:35:12.590424: val_loss -0.7828 +2024-11-22 19:35:12.590494: Pseudo dice [0.8379] +2024-11-22 19:35:12.590569: Epoch time: 17.93 s +2024-11-22 19:35:13.483950: +2024-11-22 19:35:13.484170: Epoch 6115 +2024-11-22 19:35:13.484282: Current learning rate: 0.00272 +2024-11-22 19:35:32.074820: train_loss -0.8045 +2024-11-22 19:35:32.075075: val_loss -0.7807 +2024-11-22 19:35:32.075148: Pseudo dice [0.8511] +2024-11-22 19:35:32.075228: Epoch time: 18.59 s +2024-11-22 19:35:33.308998: +2024-11-22 19:35:33.309213: Epoch 6116 +2024-11-22 19:35:33.309323: Current learning rate: 0.00272 +2024-11-22 19:35:52.018566: train_loss -0.7975 +2024-11-22 19:35:52.018788: val_loss -0.7697 +2024-11-22 19:35:52.018861: Pseudo dice [0.8281] +2024-11-22 19:35:52.018935: Epoch time: 18.71 s +2024-11-22 19:35:52.914498: +2024-11-22 19:35:52.914742: Epoch 6117 +2024-11-22 19:35:52.914853: Current learning rate: 0.00272 +2024-11-22 19:36:11.945987: train_loss -0.8037 +2024-11-22 19:36:11.946217: val_loss -0.7796 +2024-11-22 19:36:11.946292: Pseudo dice [0.8485] +2024-11-22 19:36:11.946365: Epoch time: 19.03 s +2024-11-22 19:36:12.856113: +2024-11-22 19:36:12.856343: Epoch 6118 +2024-11-22 19:36:12.856454: Current learning rate: 0.00272 +2024-11-22 19:36:31.316314: train_loss -0.8095 +2024-11-22 19:36:31.316569: val_loss -0.7855 +2024-11-22 19:36:31.316646: Pseudo dice [0.8503] +2024-11-22 19:36:31.316729: Epoch time: 18.46 s +2024-11-22 19:36:32.333192: +2024-11-22 19:36:32.333414: Epoch 6119 +2024-11-22 19:36:32.333531: Current learning rate: 0.00272 +2024-11-22 19:36:50.126208: train_loss -0.8074 +2024-11-22 19:36:50.126427: val_loss -0.7691 +2024-11-22 19:36:50.126499: Pseudo dice [0.8541] +2024-11-22 19:36:50.126573: Epoch time: 17.79 s +2024-11-22 19:36:51.024933: +2024-11-22 19:36:51.025272: Epoch 6120 +2024-11-22 19:36:51.025385: Current learning rate: 0.00272 +2024-11-22 19:37:09.838654: train_loss -0.7936 +2024-11-22 19:37:09.838870: val_loss -0.7776 +2024-11-22 19:37:09.838954: Pseudo dice [0.8573] +2024-11-22 19:37:09.839077: Epoch time: 18.81 s +2024-11-22 19:37:10.743192: +2024-11-22 19:37:10.743392: Epoch 6121 +2024-11-22 19:37:10.743503: Current learning rate: 0.00271 +2024-11-22 19:37:28.982865: train_loss -0.7991 +2024-11-22 19:37:28.983096: val_loss -0.7592 +2024-11-22 19:37:28.983172: Pseudo dice [0.8352] +2024-11-22 19:37:28.983247: Epoch time: 18.24 s +2024-11-22 19:37:29.876683: +2024-11-22 19:37:29.876900: Epoch 6122 +2024-11-22 19:37:29.877015: Current learning rate: 0.00271 +2024-11-22 19:37:47.538492: train_loss -0.8069 +2024-11-22 19:37:47.538747: val_loss -0.7584 +2024-11-22 19:37:47.538824: Pseudo dice [0.8517] +2024-11-22 19:37:47.538902: Epoch time: 17.66 s +2024-11-22 19:37:48.439800: +2024-11-22 19:37:48.440018: Epoch 6123 +2024-11-22 19:37:48.440133: Current learning rate: 0.00271 +2024-11-22 19:38:06.651014: train_loss -0.8049 +2024-11-22 19:38:06.651285: val_loss -0.7818 +2024-11-22 19:38:06.651365: Pseudo dice [0.851] +2024-11-22 19:38:06.651441: Epoch time: 18.21 s +2024-11-22 19:38:07.688218: +2024-11-22 19:38:07.688442: Epoch 6124 +2024-11-22 19:38:07.688557: Current learning rate: 0.00271 +2024-11-22 19:38:26.427637: train_loss -0.8006 +2024-11-22 19:38:26.427857: val_loss -0.7891 +2024-11-22 19:38:26.427932: Pseudo dice [0.8546] +2024-11-22 19:38:26.428013: Epoch time: 18.74 s +2024-11-22 19:38:27.508159: +2024-11-22 19:38:27.508460: Epoch 6125 +2024-11-22 19:38:27.508567: Current learning rate: 0.00271 +2024-11-22 19:38:45.213768: train_loss -0.8099 +2024-11-22 19:38:45.214029: val_loss -0.7632 +2024-11-22 19:38:45.214104: Pseudo dice [0.8332] +2024-11-22 19:38:45.214191: Epoch time: 17.71 s +2024-11-22 19:38:46.126311: +2024-11-22 19:38:46.126524: Epoch 6126 +2024-11-22 19:38:46.126633: Current learning rate: 0.00271 +2024-11-22 19:39:05.036251: train_loss -0.7985 +2024-11-22 19:39:05.036513: val_loss -0.7533 +2024-11-22 19:39:05.036589: Pseudo dice [0.816] +2024-11-22 19:39:05.038855: Epoch time: 18.91 s +2024-11-22 19:39:06.437852: +2024-11-22 19:39:06.438085: Epoch 6127 +2024-11-22 19:39:06.438214: Current learning rate: 0.00271 +2024-11-22 19:39:24.648471: train_loss -0.8037 +2024-11-22 19:39:24.648745: val_loss -0.7695 +2024-11-22 19:39:24.648825: Pseudo dice [0.8543] +2024-11-22 19:39:24.648952: Epoch time: 18.21 s +2024-11-22 19:39:25.549138: +2024-11-22 19:39:25.549341: Epoch 6128 +2024-11-22 19:39:25.549447: Current learning rate: 0.00271 +2024-11-22 19:39:42.850419: train_loss -0.8071 +2024-11-22 19:39:42.850630: val_loss -0.7815 +2024-11-22 19:39:42.850719: Pseudo dice [0.8501] +2024-11-22 19:39:42.850796: Epoch time: 17.3 s +2024-11-22 19:39:43.744618: +2024-11-22 19:39:43.744826: Epoch 6129 +2024-11-22 19:39:43.744935: Current learning rate: 0.0027 +2024-11-22 19:40:02.623653: train_loss -0.7985 +2024-11-22 19:40:02.623971: val_loss -0.7823 +2024-11-22 19:40:02.624053: Pseudo dice [0.8583] +2024-11-22 19:40:02.624139: Epoch time: 18.88 s +2024-11-22 19:40:03.529750: +2024-11-22 19:40:03.530060: Epoch 6130 +2024-11-22 19:40:03.530180: Current learning rate: 0.0027 +2024-11-22 19:40:21.787397: train_loss -0.8103 +2024-11-22 19:40:21.788311: val_loss -0.764 +2024-11-22 19:40:21.788881: Pseudo dice [0.8496] +2024-11-22 19:40:21.788967: Epoch time: 18.26 s +2024-11-22 19:40:22.687000: +2024-11-22 19:40:22.687245: Epoch 6131 +2024-11-22 19:40:22.687360: Current learning rate: 0.0027 +2024-11-22 19:40:40.870498: train_loss -0.8017 +2024-11-22 19:40:40.870725: val_loss -0.7638 +2024-11-22 19:40:40.870797: Pseudo dice [0.8392] +2024-11-22 19:40:40.870874: Epoch time: 18.18 s +2024-11-22 19:40:41.776779: +2024-11-22 19:40:41.777099: Epoch 6132 +2024-11-22 19:40:41.777214: Current learning rate: 0.0027 +2024-11-22 19:41:00.219331: train_loss -0.7993 +2024-11-22 19:41:00.219590: val_loss -0.7528 +2024-11-22 19:41:00.219694: Pseudo dice [0.836] +2024-11-22 19:41:00.219775: Epoch time: 18.44 s +2024-11-22 19:41:01.166854: +2024-11-22 19:41:01.167103: Epoch 6133 +2024-11-22 19:41:01.167210: Current learning rate: 0.0027 +2024-11-22 19:41:18.448343: train_loss -0.8122 +2024-11-22 19:41:18.448577: val_loss -0.7669 +2024-11-22 19:41:18.448652: Pseudo dice [0.8523] +2024-11-22 19:41:18.448734: Epoch time: 17.28 s +2024-11-22 19:41:19.340747: +2024-11-22 19:41:19.340955: Epoch 6134 +2024-11-22 19:41:19.341073: Current learning rate: 0.0027 +2024-11-22 19:41:36.584918: train_loss -0.8037 +2024-11-22 19:41:36.585212: val_loss -0.7964 +2024-11-22 19:41:36.585286: Pseudo dice [0.8489] +2024-11-22 19:41:36.585359: Epoch time: 17.24 s +2024-11-22 19:41:37.532917: +2024-11-22 19:41:37.533122: Epoch 6135 +2024-11-22 19:41:37.533231: Current learning rate: 0.0027 +2024-11-22 19:41:56.366344: train_loss -0.8067 +2024-11-22 19:41:56.366559: val_loss -0.7592 +2024-11-22 19:41:56.366633: Pseudo dice [0.8516] +2024-11-22 19:41:56.366709: Epoch time: 18.83 s +2024-11-22 19:41:57.272665: +2024-11-22 19:41:57.272892: Epoch 6136 +2024-11-22 19:41:57.273014: Current learning rate: 0.0027 +2024-11-22 19:42:15.840173: train_loss -0.8093 +2024-11-22 19:42:15.840384: val_loss -0.7471 +2024-11-22 19:42:15.840458: Pseudo dice [0.8538] +2024-11-22 19:42:15.840532: Epoch time: 18.57 s +2024-11-22 19:42:16.768669: +2024-11-22 19:42:16.768887: Epoch 6137 +2024-11-22 19:42:16.769001: Current learning rate: 0.00269 +2024-11-22 19:42:35.365642: train_loss -0.8009 +2024-11-22 19:42:35.365885: val_loss -0.7733 +2024-11-22 19:42:35.365959: Pseudo dice [0.8375] +2024-11-22 19:42:35.366045: Epoch time: 18.6 s +2024-11-22 19:42:36.277225: +2024-11-22 19:42:36.277444: Epoch 6138 +2024-11-22 19:42:36.277553: Current learning rate: 0.00269 +2024-11-22 19:42:55.710327: train_loss -0.8013 +2024-11-22 19:42:55.710564: val_loss -0.8037 +2024-11-22 19:42:55.710647: Pseudo dice [0.8675] +2024-11-22 19:42:55.710723: Epoch time: 19.43 s +2024-11-22 19:42:57.030587: +2024-11-22 19:42:57.030823: Epoch 6139 +2024-11-22 19:42:57.030932: Current learning rate: 0.00269 +2024-11-22 19:43:15.459886: train_loss -0.8023 +2024-11-22 19:43:15.460172: val_loss -0.8041 +2024-11-22 19:43:15.460247: Pseudo dice [0.8519] +2024-11-22 19:43:15.460320: Epoch time: 18.43 s +2024-11-22 19:43:16.364664: +2024-11-22 19:43:16.364878: Epoch 6140 +2024-11-22 19:43:16.364982: Current learning rate: 0.00269 +2024-11-22 19:43:34.180009: train_loss -0.8056 +2024-11-22 19:43:34.180272: val_loss -0.7962 +2024-11-22 19:43:34.180349: Pseudo dice [0.8522] +2024-11-22 19:43:34.180430: Epoch time: 17.82 s +2024-11-22 19:43:35.077270: +2024-11-22 19:43:35.077493: Epoch 6141 +2024-11-22 19:43:35.077602: Current learning rate: 0.00269 +2024-11-22 19:43:52.084927: train_loss -0.8043 +2024-11-22 19:43:52.085165: val_loss -0.7487 +2024-11-22 19:43:52.085240: Pseudo dice [0.8601] +2024-11-22 19:43:52.085314: Epoch time: 17.01 s +2024-11-22 19:43:52.991589: +2024-11-22 19:43:52.991800: Epoch 6142 +2024-11-22 19:43:52.991908: Current learning rate: 0.00269 +2024-11-22 19:44:10.358973: train_loss -0.8096 +2024-11-22 19:44:10.359197: val_loss -0.7687 +2024-11-22 19:44:10.359271: Pseudo dice [0.8491] +2024-11-22 19:44:10.359346: Epoch time: 17.37 s +2024-11-22 19:44:11.263969: +2024-11-22 19:44:11.264193: Epoch 6143 +2024-11-22 19:44:11.264305: Current learning rate: 0.00269 +2024-11-22 19:44:29.570652: train_loss -0.8128 +2024-11-22 19:44:29.570871: val_loss -0.777 +2024-11-22 19:44:29.570950: Pseudo dice [0.8504] +2024-11-22 19:44:29.571035: Epoch time: 18.31 s +2024-11-22 19:44:30.474478: +2024-11-22 19:44:30.474686: Epoch 6144 +2024-11-22 19:44:30.474796: Current learning rate: 0.00268 +2024-11-22 19:44:47.799090: train_loss -0.8097 +2024-11-22 19:44:47.799334: val_loss -0.7392 +2024-11-22 19:44:47.799406: Pseudo dice [0.8492] +2024-11-22 19:44:47.801665: Epoch time: 17.33 s +2024-11-22 19:44:48.732795: +2024-11-22 19:44:48.733040: Epoch 6145 +2024-11-22 19:44:48.733153: Current learning rate: 0.00268 +2024-11-22 19:45:06.871850: train_loss -0.8047 +2024-11-22 19:45:06.872096: val_loss -0.7622 +2024-11-22 19:45:06.872186: Pseudo dice [0.8442] +2024-11-22 19:45:06.872262: Epoch time: 18.14 s +2024-11-22 19:45:07.763443: +2024-11-22 19:45:07.763663: Epoch 6146 +2024-11-22 19:45:07.763774: Current learning rate: 0.00268 +2024-11-22 19:45:24.744174: train_loss -0.8136 +2024-11-22 19:45:24.744399: val_loss -0.7742 +2024-11-22 19:45:24.744482: Pseudo dice [0.8577] +2024-11-22 19:45:24.744559: Epoch time: 16.98 s +2024-11-22 19:45:25.638920: +2024-11-22 19:45:25.639150: Epoch 6147 +2024-11-22 19:45:25.639266: Current learning rate: 0.00268 +2024-11-22 19:45:44.616690: train_loss -0.8065 +2024-11-22 19:45:44.616916: val_loss -0.7906 +2024-11-22 19:45:44.619088: Pseudo dice [0.8611] +2024-11-22 19:45:44.619281: Epoch time: 18.98 s +2024-11-22 19:45:45.544465: +2024-11-22 19:45:45.544677: Epoch 6148 +2024-11-22 19:45:45.544787: Current learning rate: 0.00268 +2024-11-22 19:46:03.923955: train_loss -0.8044 +2024-11-22 19:46:03.924212: val_loss -0.7685 +2024-11-22 19:46:03.924289: Pseudo dice [0.8523] +2024-11-22 19:46:03.924369: Epoch time: 18.38 s +2024-11-22 19:46:04.818916: +2024-11-22 19:46:04.819148: Epoch 6149 +2024-11-22 19:46:04.819256: Current learning rate: 0.00268 +2024-11-22 19:46:22.717263: train_loss -0.807 +2024-11-22 19:46:22.717484: val_loss -0.7643 +2024-11-22 19:46:22.717557: Pseudo dice [0.8486] +2024-11-22 19:46:22.717630: Epoch time: 17.9 s +2024-11-22 19:46:24.322787: +2024-11-22 19:46:24.323028: Epoch 6150 +2024-11-22 19:46:24.323138: Current learning rate: 0.00268 +2024-11-22 19:46:42.419903: train_loss -0.806 +2024-11-22 19:46:42.420156: val_loss -0.8116 +2024-11-22 19:46:42.420232: Pseudo dice [0.8619] +2024-11-22 19:46:42.420304: Epoch time: 18.1 s +2024-11-22 19:46:43.330678: +2024-11-22 19:46:43.330892: Epoch 6151 +2024-11-22 19:46:43.331002: Current learning rate: 0.00268 +2024-11-22 19:47:01.467809: train_loss -0.8049 +2024-11-22 19:47:01.468072: val_loss -0.7951 +2024-11-22 19:47:01.468150: Pseudo dice [0.8621] +2024-11-22 19:47:01.468232: Epoch time: 18.14 s +2024-11-22 19:47:02.366756: +2024-11-22 19:47:02.366951: Epoch 6152 +2024-11-22 19:47:02.367061: Current learning rate: 0.00267 +2024-11-22 19:47:20.397089: train_loss -0.8039 +2024-11-22 19:47:20.397310: val_loss -0.7815 +2024-11-22 19:47:20.397383: Pseudo dice [0.8519] +2024-11-22 19:47:20.397458: Epoch time: 18.03 s +2024-11-22 19:47:21.301207: +2024-11-22 19:47:21.301412: Epoch 6153 +2024-11-22 19:47:21.301520: Current learning rate: 0.00267 +2024-11-22 19:47:39.775761: train_loss -0.8076 +2024-11-22 19:47:39.775974: val_loss -0.7659 +2024-11-22 19:47:39.776059: Pseudo dice [0.8613] +2024-11-22 19:47:39.776135: Epoch time: 18.48 s +2024-11-22 19:47:40.677619: +2024-11-22 19:47:40.677829: Epoch 6154 +2024-11-22 19:47:40.677938: Current learning rate: 0.00267 +2024-11-22 19:47:59.680876: train_loss -0.814 +2024-11-22 19:47:59.681160: val_loss -0.79 +2024-11-22 19:47:59.681242: Pseudo dice [0.8641] +2024-11-22 19:47:59.681318: Epoch time: 19.0 s +2024-11-22 19:48:00.586663: +2024-11-22 19:48:00.586884: Epoch 6155 +2024-11-22 19:48:00.587000: Current learning rate: 0.00267 +2024-11-22 19:48:18.196936: train_loss -0.8121 +2024-11-22 19:48:18.197185: val_loss -0.7536 +2024-11-22 19:48:18.197261: Pseudo dice [0.8416] +2024-11-22 19:48:18.197341: Epoch time: 17.61 s +2024-11-22 19:48:19.096972: +2024-11-22 19:48:19.113807: Epoch 6156 +2024-11-22 19:48:19.113948: Current learning rate: 0.00267 +2024-11-22 19:48:38.011777: train_loss -0.8113 +2024-11-22 19:48:38.012003: val_loss -0.7471 +2024-11-22 19:48:38.012077: Pseudo dice [0.8481] +2024-11-22 19:48:38.012152: Epoch time: 18.92 s +2024-11-22 19:48:38.919834: +2024-11-22 19:48:38.920060: Epoch 6157 +2024-11-22 19:48:38.920168: Current learning rate: 0.00267 +2024-11-22 19:48:55.897831: train_loss -0.8063 +2024-11-22 19:48:55.898078: val_loss -0.7748 +2024-11-22 19:48:55.898224: Pseudo dice [0.8397] +2024-11-22 19:48:55.898303: Epoch time: 16.98 s +2024-11-22 19:48:56.805254: +2024-11-22 19:48:56.805467: Epoch 6158 +2024-11-22 19:48:56.805573: Current learning rate: 0.00267 +2024-11-22 19:49:15.134596: train_loss -0.8193 +2024-11-22 19:49:15.134821: val_loss -0.7829 +2024-11-22 19:49:15.137120: Pseudo dice [0.8664] +2024-11-22 19:49:15.137228: Epoch time: 18.33 s +2024-11-22 19:49:16.096636: +2024-11-22 19:49:16.096850: Epoch 6159 +2024-11-22 19:49:16.096962: Current learning rate: 0.00267 +2024-11-22 19:49:33.571376: train_loss -0.8193 +2024-11-22 19:49:33.571668: val_loss -0.8048 +2024-11-22 19:49:33.571748: Pseudo dice [0.8562] +2024-11-22 19:49:33.571830: Epoch time: 17.48 s +2024-11-22 19:49:34.473978: +2024-11-22 19:49:34.474202: Epoch 6160 +2024-11-22 19:49:34.474311: Current learning rate: 0.00266 +2024-11-22 19:49:52.398477: train_loss -0.8013 +2024-11-22 19:49:52.398702: val_loss -0.8041 +2024-11-22 19:49:52.398799: Pseudo dice [0.8606] +2024-11-22 19:49:52.398875: Epoch time: 17.93 s +2024-11-22 19:49:53.324408: +2024-11-22 19:49:53.324623: Epoch 6161 +2024-11-22 19:49:53.324736: Current learning rate: 0.00266 +2024-11-22 19:50:11.515676: train_loss -0.8048 +2024-11-22 19:50:11.515890: val_loss -0.8035 +2024-11-22 19:50:11.515962: Pseudo dice [0.8628] +2024-11-22 19:50:11.516043: Epoch time: 18.19 s +2024-11-22 19:50:12.745736: +2024-11-22 19:50:12.745939: Epoch 6162 +2024-11-22 19:50:12.746050: Current learning rate: 0.00266 +2024-11-22 19:50:32.559208: train_loss -0.8065 +2024-11-22 19:50:32.559523: val_loss -0.7778 +2024-11-22 19:50:32.559609: Pseudo dice [0.8319] +2024-11-22 19:50:32.559695: Epoch time: 19.81 s +2024-11-22 19:50:33.469369: +2024-11-22 19:50:33.469606: Epoch 6163 +2024-11-22 19:50:33.469726: Current learning rate: 0.00266 +2024-11-22 19:50:51.654849: train_loss -0.8137 +2024-11-22 19:50:51.655068: val_loss -0.7869 +2024-11-22 19:50:51.655144: Pseudo dice [0.852] +2024-11-22 19:50:51.660373: Epoch time: 18.19 s +2024-11-22 19:50:52.562972: +2024-11-22 19:50:52.563191: Epoch 6164 +2024-11-22 19:50:52.563296: Current learning rate: 0.00266 +2024-11-22 19:51:11.017268: train_loss -0.8017 +2024-11-22 19:51:11.017498: val_loss -0.7645 +2024-11-22 19:51:11.017575: Pseudo dice [0.8502] +2024-11-22 19:51:11.017653: Epoch time: 18.46 s +2024-11-22 19:51:11.926032: +2024-11-22 19:51:11.926264: Epoch 6165 +2024-11-22 19:51:11.926383: Current learning rate: 0.00266 +2024-11-22 19:51:30.787335: train_loss -0.812 +2024-11-22 19:51:30.787579: val_loss -0.784 +2024-11-22 19:51:30.787659: Pseudo dice [0.8618] +2024-11-22 19:51:30.787740: Epoch time: 18.86 s +2024-11-22 19:51:31.882716: +2024-11-22 19:51:31.882932: Epoch 6166 +2024-11-22 19:51:31.883046: Current learning rate: 0.00266 +2024-11-22 19:51:49.913382: train_loss -0.7982 +2024-11-22 19:51:49.914628: val_loss -0.7533 +2024-11-22 19:51:49.914705: Pseudo dice [0.8439] +2024-11-22 19:51:49.914784: Epoch time: 18.03 s +2024-11-22 19:51:50.810708: +2024-11-22 19:51:50.810919: Epoch 6167 +2024-11-22 19:51:50.811034: Current learning rate: 0.00266 +2024-11-22 19:52:08.487897: train_loss -0.8062 +2024-11-22 19:52:08.488142: val_loss -0.7715 +2024-11-22 19:52:08.488219: Pseudo dice [0.8456] +2024-11-22 19:52:08.488294: Epoch time: 17.68 s +2024-11-22 19:52:09.383480: +2024-11-22 19:52:09.383704: Epoch 6168 +2024-11-22 19:52:09.383812: Current learning rate: 0.00265 +2024-11-22 19:52:28.728049: train_loss -0.8123 +2024-11-22 19:52:28.728308: val_loss -0.7942 +2024-11-22 19:52:28.728394: Pseudo dice [0.8614] +2024-11-22 19:52:28.755222: Epoch time: 19.35 s +2024-11-22 19:52:29.723155: +2024-11-22 19:52:29.723388: Epoch 6169 +2024-11-22 19:52:29.723499: Current learning rate: 0.00265 +2024-11-22 19:52:47.917318: train_loss -0.7969 +2024-11-22 19:52:47.917652: val_loss -0.7871 +2024-11-22 19:52:47.917729: Pseudo dice [0.8573] +2024-11-22 19:52:47.917810: Epoch time: 18.19 s +2024-11-22 19:52:48.816836: +2024-11-22 19:52:48.817041: Epoch 6170 +2024-11-22 19:52:48.817151: Current learning rate: 0.00265 +2024-11-22 19:53:05.980546: train_loss -0.8117 +2024-11-22 19:53:05.980770: val_loss -0.7717 +2024-11-22 19:53:05.980846: Pseudo dice [0.854] +2024-11-22 19:53:05.980922: Epoch time: 17.16 s +2024-11-22 19:53:07.021627: +2024-11-22 19:53:07.021838: Epoch 6171 +2024-11-22 19:53:07.021947: Current learning rate: 0.00265 +2024-11-22 19:53:24.837694: train_loss -0.8046 +2024-11-22 19:53:24.837922: val_loss -0.7871 +2024-11-22 19:53:24.838006: Pseudo dice [0.8415] +2024-11-22 19:53:24.838085: Epoch time: 17.82 s +2024-11-22 19:53:25.857855: +2024-11-22 19:53:25.858082: Epoch 6172 +2024-11-22 19:53:25.858193: Current learning rate: 0.00265 +2024-11-22 19:53:43.607246: train_loss -0.8112 +2024-11-22 19:53:43.607460: val_loss -0.7764 +2024-11-22 19:53:43.607536: Pseudo dice [0.8673] +2024-11-22 19:53:43.607612: Epoch time: 17.75 s +2024-11-22 19:53:44.504330: +2024-11-22 19:53:44.504530: Epoch 6173 +2024-11-22 19:53:44.504638: Current learning rate: 0.00265 +2024-11-22 19:54:03.320544: train_loss -0.811 +2024-11-22 19:54:03.321026: val_loss -0.7793 +2024-11-22 19:54:03.321130: Pseudo dice [0.8576] +2024-11-22 19:54:03.321207: Epoch time: 18.82 s +2024-11-22 19:54:04.296239: +2024-11-22 19:54:04.296439: Epoch 6174 +2024-11-22 19:54:04.296547: Current learning rate: 0.00265 +2024-11-22 19:54:23.080462: train_loss -0.8069 +2024-11-22 19:54:23.080680: val_loss -0.7791 +2024-11-22 19:54:23.080758: Pseudo dice [0.8491] +2024-11-22 19:54:23.080834: Epoch time: 18.79 s +2024-11-22 19:54:23.977247: +2024-11-22 19:54:23.977494: Epoch 6175 +2024-11-22 19:54:23.977627: Current learning rate: 0.00264 +2024-11-22 19:54:42.970193: train_loss -0.8028 +2024-11-22 19:54:42.970414: val_loss -0.8063 +2024-11-22 19:54:42.970491: Pseudo dice [0.8552] +2024-11-22 19:54:42.970567: Epoch time: 18.99 s +2024-11-22 19:54:43.931686: +2024-11-22 19:54:43.931942: Epoch 6176 +2024-11-22 19:54:43.932065: Current learning rate: 0.00264 +2024-11-22 19:55:03.197107: train_loss -0.8011 +2024-11-22 19:55:03.197374: val_loss -0.7811 +2024-11-22 19:55:03.197450: Pseudo dice [0.8553] +2024-11-22 19:55:03.197526: Epoch time: 19.27 s +2024-11-22 19:55:04.097298: +2024-11-22 19:55:04.097547: Epoch 6177 +2024-11-22 19:55:04.097662: Current learning rate: 0.00264 +2024-11-22 19:55:22.295413: train_loss -0.8063 +2024-11-22 19:55:22.295696: val_loss -0.7554 +2024-11-22 19:55:22.295775: Pseudo dice [0.8472] +2024-11-22 19:55:22.296182: Epoch time: 18.2 s +2024-11-22 19:55:23.200284: +2024-11-22 19:55:23.200497: Epoch 6178 +2024-11-22 19:55:23.200608: Current learning rate: 0.00264 +2024-11-22 19:55:41.901319: train_loss -0.8148 +2024-11-22 19:55:41.901544: val_loss -0.7628 +2024-11-22 19:55:41.901623: Pseudo dice [0.8673] +2024-11-22 19:55:41.903877: Epoch time: 18.7 s +2024-11-22 19:55:42.883794: +2024-11-22 19:55:42.884020: Epoch 6179 +2024-11-22 19:55:42.884135: Current learning rate: 0.00264 +2024-11-22 19:56:01.827562: train_loss -0.8109 +2024-11-22 19:56:01.827858: val_loss -0.7623 +2024-11-22 19:56:01.827935: Pseudo dice [0.8431] +2024-11-22 19:56:01.828009: Epoch time: 18.94 s +2024-11-22 19:56:02.727358: +2024-11-22 19:56:02.727566: Epoch 6180 +2024-11-22 19:56:02.727679: Current learning rate: 0.00264 +2024-11-22 19:56:21.137882: train_loss -0.8187 +2024-11-22 19:56:21.143327: val_loss -0.7932 +2024-11-22 19:56:21.143436: Pseudo dice [0.8388] +2024-11-22 19:56:21.143521: Epoch time: 18.41 s +2024-11-22 19:56:22.128354: +2024-11-22 19:56:22.128555: Epoch 6181 +2024-11-22 19:56:22.128667: Current learning rate: 0.00264 +2024-11-22 19:56:40.318872: train_loss -0.8175 +2024-11-22 19:56:40.319106: val_loss -0.8007 +2024-11-22 19:56:40.319189: Pseudo dice [0.8455] +2024-11-22 19:56:40.319277: Epoch time: 18.19 s +2024-11-22 19:56:41.222944: +2024-11-22 19:56:41.223166: Epoch 6182 +2024-11-22 19:56:41.223277: Current learning rate: 0.00264 +2024-11-22 19:56:58.304822: train_loss -0.8172 +2024-11-22 19:56:58.305054: val_loss -0.792 +2024-11-22 19:56:58.305128: Pseudo dice [0.8665] +2024-11-22 19:56:58.305206: Epoch time: 17.08 s +2024-11-22 19:56:59.253819: +2024-11-22 19:56:59.254045: Epoch 6183 +2024-11-22 19:56:59.254168: Current learning rate: 0.00263 +2024-11-22 19:57:18.426416: train_loss -0.8099 +2024-11-22 19:57:18.426628: val_loss -0.7532 +2024-11-22 19:57:18.426710: Pseudo dice [0.8451] +2024-11-22 19:57:18.426795: Epoch time: 19.17 s +2024-11-22 19:57:19.325960: +2024-11-22 19:57:19.326173: Epoch 6184 +2024-11-22 19:57:19.326286: Current learning rate: 0.00263 +2024-11-22 19:57:37.954880: train_loss -0.8124 +2024-11-22 19:57:37.955158: val_loss -0.7623 +2024-11-22 19:57:37.955239: Pseudo dice [0.8527] +2024-11-22 19:57:37.955322: Epoch time: 18.63 s +2024-11-22 19:57:39.306620: +2024-11-22 19:57:39.306840: Epoch 6185 +2024-11-22 19:57:39.306945: Current learning rate: 0.00263 +2024-11-22 19:57:57.328445: train_loss -0.8078 +2024-11-22 19:57:57.328684: val_loss -0.7491 +2024-11-22 19:57:57.328764: Pseudo dice [0.8451] +2024-11-22 19:57:57.328842: Epoch time: 18.02 s +2024-11-22 19:57:58.227879: +2024-11-22 19:57:58.228117: Epoch 6186 +2024-11-22 19:57:58.228230: Current learning rate: 0.00263 +2024-11-22 19:58:16.564080: train_loss -0.81 +2024-11-22 19:58:16.564318: val_loss -0.7634 +2024-11-22 19:58:16.564396: Pseudo dice [0.8474] +2024-11-22 19:58:16.564481: Epoch time: 18.34 s +2024-11-22 19:58:17.473093: +2024-11-22 19:58:17.473412: Epoch 6187 +2024-11-22 19:58:17.473523: Current learning rate: 0.00263 +2024-11-22 19:58:35.306144: train_loss -0.8122 +2024-11-22 19:58:35.306398: val_loss -0.7651 +2024-11-22 19:58:35.306479: Pseudo dice [0.8577] +2024-11-22 19:58:35.306557: Epoch time: 17.83 s +2024-11-22 19:58:36.209584: +2024-11-22 19:58:36.209812: Epoch 6188 +2024-11-22 19:58:36.209927: Current learning rate: 0.00263 +2024-11-22 19:58:54.467298: train_loss -0.7995 +2024-11-22 19:58:54.467512: val_loss -0.784 +2024-11-22 19:58:54.467585: Pseudo dice [0.8407] +2024-11-22 19:58:54.467657: Epoch time: 18.26 s +2024-11-22 19:58:55.365577: +2024-11-22 19:58:55.365871: Epoch 6189 +2024-11-22 19:58:55.365980: Current learning rate: 0.00263 +2024-11-22 19:59:12.821733: train_loss -0.8025 +2024-11-22 19:59:12.821951: val_loss -0.7654 +2024-11-22 19:59:12.822034: Pseudo dice [0.8401] +2024-11-22 19:59:12.822115: Epoch time: 17.46 s +2024-11-22 19:59:13.726842: +2024-11-22 19:59:13.727058: Epoch 6190 +2024-11-22 19:59:13.727166: Current learning rate: 0.00263 +2024-11-22 19:59:31.812638: train_loss -0.8006 +2024-11-22 19:59:31.812852: val_loss -0.7904 +2024-11-22 19:59:31.812928: Pseudo dice [0.8604] +2024-11-22 19:59:31.813013: Epoch time: 18.09 s +2024-11-22 19:59:32.712183: +2024-11-22 19:59:32.712396: Epoch 6191 +2024-11-22 19:59:32.712510: Current learning rate: 0.00262 +2024-11-22 19:59:51.166289: train_loss -0.8094 +2024-11-22 19:59:51.166538: val_loss -0.7862 +2024-11-22 19:59:51.166612: Pseudo dice [0.843] +2024-11-22 19:59:51.166694: Epoch time: 18.45 s +2024-11-22 19:59:52.067727: +2024-11-22 19:59:52.067947: Epoch 6192 +2024-11-22 19:59:52.068064: Current learning rate: 0.00262 +2024-11-22 20:00:09.771153: train_loss -0.8092 +2024-11-22 20:00:09.771376: val_loss -0.7478 +2024-11-22 20:00:09.771455: Pseudo dice [0.8409] +2024-11-22 20:00:09.771533: Epoch time: 17.7 s +2024-11-22 20:00:10.832043: +2024-11-22 20:00:10.832234: Epoch 6193 +2024-11-22 20:00:10.832338: Current learning rate: 0.00262 +2024-11-22 20:00:29.480464: train_loss -0.7984 +2024-11-22 20:00:29.480693: val_loss -0.777 +2024-11-22 20:00:29.482868: Pseudo dice [0.8514] +2024-11-22 20:00:29.483085: Epoch time: 18.65 s +2024-11-22 20:00:30.473349: +2024-11-22 20:00:30.473562: Epoch 6194 +2024-11-22 20:00:30.473674: Current learning rate: 0.00262 +2024-11-22 20:00:49.479347: train_loss -0.8024 +2024-11-22 20:00:49.479564: val_loss -0.7883 +2024-11-22 20:00:49.479639: Pseudo dice [0.8503] +2024-11-22 20:00:49.479725: Epoch time: 19.01 s +2024-11-22 20:00:50.518255: +2024-11-22 20:00:50.518473: Epoch 6195 +2024-11-22 20:00:50.518587: Current learning rate: 0.00262 +2024-11-22 20:01:08.901901: train_loss -0.8042 +2024-11-22 20:01:08.902190: val_loss -0.7908 +2024-11-22 20:01:08.902265: Pseudo dice [0.8607] +2024-11-22 20:01:08.902343: Epoch time: 18.38 s +2024-11-22 20:01:09.806092: +2024-11-22 20:01:09.806307: Epoch 6196 +2024-11-22 20:01:09.806416: Current learning rate: 0.00262 +2024-11-22 20:01:27.477574: train_loss -0.8101 +2024-11-22 20:01:27.478109: val_loss -0.7856 +2024-11-22 20:01:27.478211: Pseudo dice [0.8589] +2024-11-22 20:01:27.478288: Epoch time: 17.67 s +2024-11-22 20:01:28.377707: +2024-11-22 20:01:28.377943: Epoch 6197 +2024-11-22 20:01:28.378061: Current learning rate: 0.00262 +2024-11-22 20:01:46.932722: train_loss -0.8092 +2024-11-22 20:01:46.932951: val_loss -0.7627 +2024-11-22 20:01:46.933040: Pseudo dice [0.8354] +2024-11-22 20:01:46.933115: Epoch time: 18.56 s +2024-11-22 20:01:47.836458: +2024-11-22 20:01:47.836679: Epoch 6198 +2024-11-22 20:01:47.836788: Current learning rate: 0.00261 +2024-11-22 20:02:06.492606: train_loss -0.8082 +2024-11-22 20:02:06.492876: val_loss -0.7548 +2024-11-22 20:02:06.492964: Pseudo dice [0.8357] +2024-11-22 20:02:06.493062: Epoch time: 18.66 s +2024-11-22 20:02:07.398689: +2024-11-22 20:02:07.398915: Epoch 6199 +2024-11-22 20:02:07.399026: Current learning rate: 0.00261 +2024-11-22 20:02:25.212265: train_loss -0.8082 +2024-11-22 20:02:25.212489: val_loss -0.7656 +2024-11-22 20:02:25.212563: Pseudo dice [0.8496] +2024-11-22 20:02:25.212637: Epoch time: 17.81 s +2024-11-22 20:02:26.448246: +2024-11-22 20:02:26.448463: Epoch 6200 +2024-11-22 20:02:26.448575: Current learning rate: 0.00261 +2024-11-22 20:02:45.427756: train_loss -0.8004 +2024-11-22 20:02:45.427978: val_loss -0.7756 +2024-11-22 20:02:45.428062: Pseudo dice [0.8571] +2024-11-22 20:02:45.428143: Epoch time: 18.98 s +2024-11-22 20:02:46.328882: +2024-11-22 20:02:46.329129: Epoch 6201 +2024-11-22 20:02:46.329242: Current learning rate: 0.00261 +2024-11-22 20:03:04.504957: train_loss -0.8052 +2024-11-22 20:03:04.505182: val_loss -0.7688 +2024-11-22 20:03:04.505254: Pseudo dice [0.8367] +2024-11-22 20:03:04.505325: Epoch time: 18.18 s +2024-11-22 20:03:05.404010: +2024-11-22 20:03:05.404241: Epoch 6202 +2024-11-22 20:03:05.404349: Current learning rate: 0.00261 +2024-11-22 20:03:23.919545: train_loss -0.8062 +2024-11-22 20:03:23.919757: val_loss -0.7905 +2024-11-22 20:03:23.919828: Pseudo dice [0.844] +2024-11-22 20:03:23.919903: Epoch time: 18.52 s +2024-11-22 20:03:24.826705: +2024-11-22 20:03:24.826957: Epoch 6203 +2024-11-22 20:03:24.827078: Current learning rate: 0.00261 +2024-11-22 20:03:43.282650: train_loss -0.8087 +2024-11-22 20:03:43.282870: val_loss -0.7928 +2024-11-22 20:03:43.282943: Pseudo dice [0.849] +2024-11-22 20:03:43.283201: Epoch time: 18.46 s +2024-11-22 20:03:44.178000: +2024-11-22 20:03:44.178201: Epoch 6204 +2024-11-22 20:03:44.178308: Current learning rate: 0.00261 +2024-11-22 20:04:01.846165: train_loss -0.8091 +2024-11-22 20:04:01.851568: val_loss -0.7588 +2024-11-22 20:04:01.851734: Pseudo dice [0.844] +2024-11-22 20:04:01.851817: Epoch time: 17.67 s +2024-11-22 20:04:02.757540: +2024-11-22 20:04:02.757749: Epoch 6205 +2024-11-22 20:04:02.757855: Current learning rate: 0.00261 +2024-11-22 20:04:20.782260: train_loss -0.8111 +2024-11-22 20:04:20.782489: val_loss -0.7676 +2024-11-22 20:04:20.782563: Pseudo dice [0.8426] +2024-11-22 20:04:20.782636: Epoch time: 18.03 s +2024-11-22 20:04:21.690339: +2024-11-22 20:04:21.690562: Epoch 6206 +2024-11-22 20:04:21.690675: Current learning rate: 0.0026 +2024-11-22 20:04:39.988227: train_loss -0.8101 +2024-11-22 20:04:39.989924: val_loss -0.7777 +2024-11-22 20:04:39.990024: Pseudo dice [0.8544] +2024-11-22 20:04:39.990104: Epoch time: 18.3 s +2024-11-22 20:04:40.892732: +2024-11-22 20:04:40.892959: Epoch 6207 +2024-11-22 20:04:40.893089: Current learning rate: 0.0026 +2024-11-22 20:04:58.664355: train_loss -0.8089 +2024-11-22 20:04:58.666406: val_loss -0.796 +2024-11-22 20:04:58.666509: Pseudo dice [0.868] +2024-11-22 20:04:58.666593: Epoch time: 17.77 s +2024-11-22 20:04:59.560942: +2024-11-22 20:04:59.561172: Epoch 6208 +2024-11-22 20:04:59.561283: Current learning rate: 0.0026 +2024-11-22 20:05:16.797161: train_loss -0.81 +2024-11-22 20:05:16.797376: val_loss -0.7662 +2024-11-22 20:05:16.797447: Pseudo dice [0.8509] +2024-11-22 20:05:16.797522: Epoch time: 17.24 s +2024-11-22 20:05:17.696096: +2024-11-22 20:05:17.696322: Epoch 6209 +2024-11-22 20:05:17.696429: Current learning rate: 0.0026 +2024-11-22 20:05:36.087000: train_loss -0.8102 +2024-11-22 20:05:36.087234: val_loss -0.7983 +2024-11-22 20:05:36.087319: Pseudo dice [0.8485] +2024-11-22 20:05:36.087410: Epoch time: 18.39 s +2024-11-22 20:05:37.090969: +2024-11-22 20:05:37.091174: Epoch 6210 +2024-11-22 20:05:37.091284: Current learning rate: 0.0026 +2024-11-22 20:05:55.087101: train_loss -0.8049 +2024-11-22 20:05:55.087351: val_loss -0.7908 +2024-11-22 20:05:55.087427: Pseudo dice [0.8524] +2024-11-22 20:05:55.087507: Epoch time: 18.0 s +2024-11-22 20:05:55.992422: +2024-11-22 20:05:55.992655: Epoch 6211 +2024-11-22 20:05:55.992765: Current learning rate: 0.0026 +2024-11-22 20:06:14.469659: train_loss -0.8024 +2024-11-22 20:06:14.469899: val_loss -0.7471 +2024-11-22 20:06:14.469976: Pseudo dice [0.8474] +2024-11-22 20:06:14.470055: Epoch time: 18.48 s +2024-11-22 20:06:15.370680: +2024-11-22 20:06:15.370879: Epoch 6212 +2024-11-22 20:06:15.370987: Current learning rate: 0.0026 +2024-11-22 20:06:33.950818: train_loss -0.8056 +2024-11-22 20:06:33.951041: val_loss -0.7759 +2024-11-22 20:06:33.951119: Pseudo dice [0.8553] +2024-11-22 20:06:33.951197: Epoch time: 18.58 s +2024-11-22 20:06:34.851213: +2024-11-22 20:06:34.851416: Epoch 6213 +2024-11-22 20:06:34.851521: Current learning rate: 0.00259 +2024-11-22 20:06:53.535201: train_loss -0.806 +2024-11-22 20:06:53.536517: val_loss -0.7762 +2024-11-22 20:06:53.536608: Pseudo dice [0.86] +2024-11-22 20:06:53.536681: Epoch time: 18.68 s +2024-11-22 20:06:54.443606: +2024-11-22 20:06:54.443809: Epoch 6214 +2024-11-22 20:06:54.443911: Current learning rate: 0.00259 +2024-11-22 20:07:12.632504: train_loss -0.8123 +2024-11-22 20:07:12.633615: val_loss -0.7648 +2024-11-22 20:07:12.633693: Pseudo dice [0.8563] +2024-11-22 20:07:12.633773: Epoch time: 18.19 s +2024-11-22 20:07:13.531723: +2024-11-22 20:07:13.531940: Epoch 6215 +2024-11-22 20:07:13.532054: Current learning rate: 0.00259 +2024-11-22 20:07:33.215047: train_loss -0.8131 +2024-11-22 20:07:33.215266: val_loss -0.7952 +2024-11-22 20:07:33.215342: Pseudo dice [0.8641] +2024-11-22 20:07:33.215414: Epoch time: 19.68 s +2024-11-22 20:07:34.109345: +2024-11-22 20:07:34.109550: Epoch 6216 +2024-11-22 20:07:34.109657: Current learning rate: 0.00259 +2024-11-22 20:07:52.253075: train_loss -0.8154 +2024-11-22 20:07:52.253301: val_loss -0.779 +2024-11-22 20:07:52.253379: Pseudo dice [0.8499] +2024-11-22 20:07:52.253454: Epoch time: 18.14 s +2024-11-22 20:07:53.222493: +2024-11-22 20:07:53.222728: Epoch 6217 +2024-11-22 20:07:53.222851: Current learning rate: 0.00259 +2024-11-22 20:08:11.718435: train_loss -0.8116 +2024-11-22 20:08:11.718657: val_loss -0.8062 +2024-11-22 20:08:11.718732: Pseudo dice [0.8487] +2024-11-22 20:08:11.718807: Epoch time: 18.5 s +2024-11-22 20:08:12.684794: +2024-11-22 20:08:12.685005: Epoch 6218 +2024-11-22 20:08:12.685112: Current learning rate: 0.00259 +2024-11-22 20:08:30.376149: train_loss -0.8166 +2024-11-22 20:08:30.378856: val_loss -0.7676 +2024-11-22 20:08:30.379087: Pseudo dice [0.8544] +2024-11-22 20:08:30.379181: Epoch time: 17.69 s +2024-11-22 20:08:31.667545: +2024-11-22 20:08:31.667862: Epoch 6219 +2024-11-22 20:08:31.667975: Current learning rate: 0.00259 +2024-11-22 20:08:50.256814: train_loss -0.8058 +2024-11-22 20:08:50.257066: val_loss -0.7854 +2024-11-22 20:08:50.257140: Pseudo dice [0.8588] +2024-11-22 20:08:50.257217: Epoch time: 18.59 s +2024-11-22 20:08:51.403153: +2024-11-22 20:08:51.403376: Epoch 6220 +2024-11-22 20:08:51.403485: Current learning rate: 0.00259 +2024-11-22 20:09:08.725634: train_loss -0.8081 +2024-11-22 20:09:08.725866: val_loss -0.7653 +2024-11-22 20:09:08.725941: Pseudo dice [0.8308] +2024-11-22 20:09:08.726022: Epoch time: 17.32 s +2024-11-22 20:09:09.624436: +2024-11-22 20:09:09.624716: Epoch 6221 +2024-11-22 20:09:09.624825: Current learning rate: 0.00258 +2024-11-22 20:09:27.943647: train_loss -0.8011 +2024-11-22 20:09:27.943933: val_loss -0.7649 +2024-11-22 20:09:27.944021: Pseudo dice [0.8299] +2024-11-22 20:09:27.944105: Epoch time: 18.32 s +2024-11-22 20:09:28.842667: +2024-11-22 20:09:28.842884: Epoch 6222 +2024-11-22 20:09:28.842997: Current learning rate: 0.00258 +2024-11-22 20:09:47.016640: train_loss -0.808 +2024-11-22 20:09:47.016861: val_loss -0.7797 +2024-11-22 20:09:47.019133: Pseudo dice [0.8497] +2024-11-22 20:09:47.019219: Epoch time: 18.17 s +2024-11-22 20:09:48.075647: +2024-11-22 20:09:48.075855: Epoch 6223 +2024-11-22 20:09:48.075961: Current learning rate: 0.00258 +2024-11-22 20:10:06.237970: train_loss -0.8108 +2024-11-22 20:10:06.238186: val_loss -0.7932 +2024-11-22 20:10:06.238262: Pseudo dice [0.8482] +2024-11-22 20:10:06.238338: Epoch time: 18.16 s +2024-11-22 20:10:07.140787: +2024-11-22 20:10:07.141019: Epoch 6224 +2024-11-22 20:10:07.141134: Current learning rate: 0.00258 +2024-11-22 20:10:25.785597: train_loss -0.8133 +2024-11-22 20:10:25.785811: val_loss -0.7855 +2024-11-22 20:10:25.785887: Pseudo dice [0.83] +2024-11-22 20:10:25.785961: Epoch time: 18.65 s +2024-11-22 20:10:26.708642: +2024-11-22 20:10:26.708868: Epoch 6225 +2024-11-22 20:10:26.708983: Current learning rate: 0.00258 +2024-11-22 20:10:45.024477: train_loss -0.8106 +2024-11-22 20:10:45.024739: val_loss -0.7862 +2024-11-22 20:10:45.024814: Pseudo dice [0.8559] +2024-11-22 20:10:45.024891: Epoch time: 18.32 s +2024-11-22 20:10:45.924871: +2024-11-22 20:10:45.925097: Epoch 6226 +2024-11-22 20:10:45.925224: Current learning rate: 0.00258 +2024-11-22 20:11:04.839560: train_loss -0.8023 +2024-11-22 20:11:04.839773: val_loss -0.7886 +2024-11-22 20:11:04.839846: Pseudo dice [0.8532] +2024-11-22 20:11:04.839921: Epoch time: 18.92 s +2024-11-22 20:11:05.732659: +2024-11-22 20:11:05.732891: Epoch 6227 +2024-11-22 20:11:05.733009: Current learning rate: 0.00258 +2024-11-22 20:11:24.245267: train_loss -0.8157 +2024-11-22 20:11:24.245484: val_loss -0.7484 +2024-11-22 20:11:24.245558: Pseudo dice [0.8398] +2024-11-22 20:11:24.245635: Epoch time: 18.51 s +2024-11-22 20:11:25.194870: +2024-11-22 20:11:25.195077: Epoch 6228 +2024-11-22 20:11:25.195189: Current learning rate: 0.00258 +2024-11-22 20:11:43.729597: train_loss -0.8141 +2024-11-22 20:11:43.729814: val_loss -0.7666 +2024-11-22 20:11:43.732050: Pseudo dice [0.8476] +2024-11-22 20:11:43.732172: Epoch time: 18.54 s +2024-11-22 20:11:44.911444: +2024-11-22 20:11:44.911689: Epoch 6229 +2024-11-22 20:11:44.911808: Current learning rate: 0.00257 +2024-11-22 20:12:03.475941: train_loss -0.8094 +2024-11-22 20:12:03.476196: val_loss -0.7509 +2024-11-22 20:12:03.476436: Pseudo dice [0.8304] +2024-11-22 20:12:03.476523: Epoch time: 18.57 s +2024-11-22 20:12:04.371030: +2024-11-22 20:12:04.371243: Epoch 6230 +2024-11-22 20:12:04.371351: Current learning rate: 0.00257 +2024-11-22 20:12:23.510473: train_loss -0.8044 +2024-11-22 20:12:23.511082: val_loss -0.7736 +2024-11-22 20:12:23.511190: Pseudo dice [0.8599] +2024-11-22 20:12:23.511268: Epoch time: 19.14 s +2024-11-22 20:12:24.407303: +2024-11-22 20:12:24.407549: Epoch 6231 +2024-11-22 20:12:24.407662: Current learning rate: 0.00257 +2024-11-22 20:12:41.887477: train_loss -0.8074 +2024-11-22 20:12:41.887709: val_loss -0.805 +2024-11-22 20:12:41.887798: Pseudo dice [0.8524] +2024-11-22 20:12:41.887898: Epoch time: 17.48 s +2024-11-22 20:12:42.785004: +2024-11-22 20:12:42.785226: Epoch 6232 +2024-11-22 20:12:42.785333: Current learning rate: 0.00257 +2024-11-22 20:13:01.514185: train_loss -0.8089 +2024-11-22 20:13:01.514434: val_loss -0.7838 +2024-11-22 20:13:01.514511: Pseudo dice [0.843] +2024-11-22 20:13:01.514604: Epoch time: 18.73 s +2024-11-22 20:13:02.413456: +2024-11-22 20:13:02.413694: Epoch 6233 +2024-11-22 20:13:02.413803: Current learning rate: 0.00257 +2024-11-22 20:13:20.796953: train_loss -0.813 +2024-11-22 20:13:20.797187: val_loss -0.7893 +2024-11-22 20:13:20.797260: Pseudo dice [0.8461] +2024-11-22 20:13:20.797334: Epoch time: 18.38 s +2024-11-22 20:13:21.701075: +2024-11-22 20:13:21.701353: Epoch 6234 +2024-11-22 20:13:21.701469: Current learning rate: 0.00257 +2024-11-22 20:13:40.434971: train_loss -0.8063 +2024-11-22 20:13:40.435193: val_loss -0.7888 +2024-11-22 20:13:40.435268: Pseudo dice [0.8487] +2024-11-22 20:13:40.435345: Epoch time: 18.73 s +2024-11-22 20:13:41.336617: +2024-11-22 20:13:41.336829: Epoch 6235 +2024-11-22 20:13:41.336938: Current learning rate: 0.00257 +2024-11-22 20:14:00.075053: train_loss -0.8101 +2024-11-22 20:14:00.075289: val_loss -0.7734 +2024-11-22 20:14:00.075364: Pseudo dice [0.8482] +2024-11-22 20:14:00.075441: Epoch time: 18.74 s +2024-11-22 20:14:01.014815: +2024-11-22 20:14:01.015028: Epoch 6236 +2024-11-22 20:14:01.015137: Current learning rate: 0.00256 +2024-11-22 20:14:18.757087: train_loss -0.8026 +2024-11-22 20:14:18.762506: val_loss -0.7701 +2024-11-22 20:14:18.762618: Pseudo dice [0.8515] +2024-11-22 20:14:18.762702: Epoch time: 17.74 s +2024-11-22 20:14:19.848721: +2024-11-22 20:14:19.849053: Epoch 6237 +2024-11-22 20:14:19.849161: Current learning rate: 0.00256 +2024-11-22 20:14:37.892694: train_loss -0.7993 +2024-11-22 20:14:37.892915: val_loss -0.7893 +2024-11-22 20:14:37.893017: Pseudo dice [0.8324] +2024-11-22 20:14:37.893095: Epoch time: 18.04 s +2024-11-22 20:14:38.786923: +2024-11-22 20:14:38.787150: Epoch 6238 +2024-11-22 20:14:38.787258: Current learning rate: 0.00256 +2024-11-22 20:14:56.816361: train_loss -0.7894 +2024-11-22 20:14:56.816580: val_loss -0.7777 +2024-11-22 20:14:56.816654: Pseudo dice [0.8535] +2024-11-22 20:14:56.816731: Epoch time: 18.03 s +2024-11-22 20:14:57.705129: +2024-11-22 20:14:57.705344: Epoch 6239 +2024-11-22 20:14:57.705453: Current learning rate: 0.00256 +2024-11-22 20:15:15.299460: train_loss -0.8027 +2024-11-22 20:15:15.299689: val_loss -0.7772 +2024-11-22 20:15:15.299763: Pseudo dice [0.8477] +2024-11-22 20:15:15.299839: Epoch time: 17.6 s +2024-11-22 20:15:16.204386: +2024-11-22 20:15:16.204600: Epoch 6240 +2024-11-22 20:15:16.204711: Current learning rate: 0.00256 +2024-11-22 20:15:34.965799: train_loss -0.8005 +2024-11-22 20:15:34.966052: val_loss -0.7724 +2024-11-22 20:15:34.966129: Pseudo dice [0.8353] +2024-11-22 20:15:34.966210: Epoch time: 18.76 s +2024-11-22 20:15:35.868432: +2024-11-22 20:15:35.868652: Epoch 6241 +2024-11-22 20:15:35.868760: Current learning rate: 0.00256 +2024-11-22 20:15:55.096207: train_loss -0.7866 +2024-11-22 20:15:55.096428: val_loss -0.7644 +2024-11-22 20:15:55.096500: Pseudo dice [0.857] +2024-11-22 20:15:55.096572: Epoch time: 19.23 s +2024-11-22 20:15:56.381603: +2024-11-22 20:15:56.381836: Epoch 6242 +2024-11-22 20:15:56.381950: Current learning rate: 0.00256 +2024-11-22 20:16:14.348498: train_loss -0.7956 +2024-11-22 20:16:14.350911: val_loss -0.7805 +2024-11-22 20:16:14.351007: Pseudo dice [0.8395] +2024-11-22 20:16:14.351093: Epoch time: 17.97 s +2024-11-22 20:16:15.373645: +2024-11-22 20:16:15.373852: Epoch 6243 +2024-11-22 20:16:15.373958: Current learning rate: 0.00256 +2024-11-22 20:16:34.139508: train_loss -0.796 +2024-11-22 20:16:34.139748: val_loss -0.7822 +2024-11-22 20:16:34.139827: Pseudo dice [0.8567] +2024-11-22 20:16:34.139899: Epoch time: 18.77 s +2024-11-22 20:16:35.036647: +2024-11-22 20:16:35.036880: Epoch 6244 +2024-11-22 20:16:35.037001: Current learning rate: 0.00255 +2024-11-22 20:16:53.566651: train_loss -0.8017 +2024-11-22 20:16:53.566893: val_loss -0.7957 +2024-11-22 20:16:53.566974: Pseudo dice [0.8564] +2024-11-22 20:16:53.567056: Epoch time: 18.53 s +2024-11-22 20:16:54.607470: +2024-11-22 20:16:54.607708: Epoch 6245 +2024-11-22 20:16:54.607816: Current learning rate: 0.00255 +2024-11-22 20:17:12.004494: train_loss -0.7978 +2024-11-22 20:17:12.004721: val_loss -0.7691 +2024-11-22 20:17:12.004798: Pseudo dice [0.8474] +2024-11-22 20:17:12.004873: Epoch time: 17.4 s +2024-11-22 20:17:12.945763: +2024-11-22 20:17:12.946016: Epoch 6246 +2024-11-22 20:17:12.946131: Current learning rate: 0.00255 +2024-11-22 20:17:32.291353: train_loss -0.7889 +2024-11-22 20:17:32.291641: val_loss -0.7695 +2024-11-22 20:17:32.291718: Pseudo dice [0.8528] +2024-11-22 20:17:32.291794: Epoch time: 19.35 s +2024-11-22 20:17:33.187398: +2024-11-22 20:17:33.187594: Epoch 6247 +2024-11-22 20:17:33.187706: Current learning rate: 0.00255 +2024-11-22 20:17:51.670350: train_loss -0.7864 +2024-11-22 20:17:51.670569: val_loss -0.761 +2024-11-22 20:17:51.672860: Pseudo dice [0.8502] +2024-11-22 20:17:51.672984: Epoch time: 18.48 s +2024-11-22 20:17:52.602542: +2024-11-22 20:17:52.602757: Epoch 6248 +2024-11-22 20:17:52.602866: Current learning rate: 0.00255 +2024-11-22 20:18:09.948499: train_loss -0.7992 +2024-11-22 20:18:09.948741: val_loss -0.7515 +2024-11-22 20:18:09.948817: Pseudo dice [0.838] +2024-11-22 20:18:09.948894: Epoch time: 17.35 s +2024-11-22 20:18:10.842738: +2024-11-22 20:18:10.842967: Epoch 6249 +2024-11-22 20:18:10.843079: Current learning rate: 0.00255 +2024-11-22 20:18:28.424612: train_loss -0.8067 +2024-11-22 20:18:28.424847: val_loss -0.7412 +2024-11-22 20:18:28.424925: Pseudo dice [0.8288] +2024-11-22 20:18:28.425006: Epoch time: 17.58 s +2024-11-22 20:18:29.635760: +2024-11-22 20:18:29.635965: Epoch 6250 +2024-11-22 20:18:29.636081: Current learning rate: 0.00255 +2024-11-22 20:18:48.054072: train_loss -0.7992 +2024-11-22 20:18:48.054301: val_loss -0.7752 +2024-11-22 20:18:48.054375: Pseudo dice [0.8609] +2024-11-22 20:18:48.054448: Epoch time: 18.42 s +2024-11-22 20:18:48.998649: +2024-11-22 20:18:48.998878: Epoch 6251 +2024-11-22 20:18:48.998986: Current learning rate: 0.00255 +2024-11-22 20:19:06.658206: train_loss -0.8085 +2024-11-22 20:19:06.658447: val_loss -0.7868 +2024-11-22 20:19:06.658522: Pseudo dice [0.8568] +2024-11-22 20:19:06.658602: Epoch time: 17.66 s +2024-11-22 20:19:07.559011: +2024-11-22 20:19:07.559238: Epoch 6252 +2024-11-22 20:19:07.559345: Current learning rate: 0.00254 +2024-11-22 20:19:26.429538: train_loss -0.809 +2024-11-22 20:19:26.429750: val_loss -0.7767 +2024-11-22 20:19:26.429822: Pseudo dice [0.8392] +2024-11-22 20:19:26.429891: Epoch time: 18.87 s +2024-11-22 20:19:27.322016: +2024-11-22 20:19:27.322238: Epoch 6253 +2024-11-22 20:19:27.322345: Current learning rate: 0.00254 +2024-11-22 20:19:45.909075: train_loss -0.8074 +2024-11-22 20:19:45.909553: val_loss -0.7932 +2024-11-22 20:19:45.909646: Pseudo dice [0.851] +2024-11-22 20:19:45.911916: Epoch time: 18.59 s +2024-11-22 20:19:46.925504: +2024-11-22 20:19:46.925708: Epoch 6254 +2024-11-22 20:19:46.925816: Current learning rate: 0.00254 +2024-11-22 20:20:05.793442: train_loss -0.8055 +2024-11-22 20:20:05.793670: val_loss -0.7819 +2024-11-22 20:20:05.793746: Pseudo dice [0.8649] +2024-11-22 20:20:05.793823: Epoch time: 18.87 s +2024-11-22 20:20:06.759240: +2024-11-22 20:20:06.759473: Epoch 6255 +2024-11-22 20:20:06.759633: Current learning rate: 0.00254 +2024-11-22 20:20:24.695395: train_loss -0.8099 +2024-11-22 20:20:24.696736: val_loss -0.7733 +2024-11-22 20:20:24.697053: Pseudo dice [0.8486] +2024-11-22 20:20:24.697144: Epoch time: 17.94 s +2024-11-22 20:20:25.642049: +2024-11-22 20:20:25.642287: Epoch 6256 +2024-11-22 20:20:25.642400: Current learning rate: 0.00254 +2024-11-22 20:20:44.252287: train_loss -0.8051 +2024-11-22 20:20:44.252502: val_loss -0.783 +2024-11-22 20:20:44.252579: Pseudo dice [0.8443] +2024-11-22 20:20:44.252654: Epoch time: 18.61 s +2024-11-22 20:20:45.151257: +2024-11-22 20:20:45.151485: Epoch 6257 +2024-11-22 20:20:45.151607: Current learning rate: 0.00254 +2024-11-22 20:21:02.860495: train_loss -0.81 +2024-11-22 20:21:02.860794: val_loss -0.7873 +2024-11-22 20:21:02.860873: Pseudo dice [0.8511] +2024-11-22 20:21:02.860950: Epoch time: 17.71 s +2024-11-22 20:21:03.771113: +2024-11-22 20:21:03.771375: Epoch 6258 +2024-11-22 20:21:03.771485: Current learning rate: 0.00254 +2024-11-22 20:21:21.809412: train_loss -0.8015 +2024-11-22 20:21:21.814778: val_loss -0.7586 +2024-11-22 20:21:21.814977: Pseudo dice [0.8425] +2024-11-22 20:21:21.815090: Epoch time: 18.04 s +2024-11-22 20:21:22.830964: +2024-11-22 20:21:22.831233: Epoch 6259 +2024-11-22 20:21:22.831344: Current learning rate: 0.00253 +2024-11-22 20:21:41.002600: train_loss -0.8027 +2024-11-22 20:21:41.002838: val_loss -0.7651 +2024-11-22 20:21:41.002919: Pseudo dice [0.8504] +2024-11-22 20:21:41.003006: Epoch time: 18.17 s +2024-11-22 20:21:41.905340: +2024-11-22 20:21:41.905548: Epoch 6260 +2024-11-22 20:21:41.905663: Current learning rate: 0.00253 +2024-11-22 20:22:00.238398: train_loss -0.7959 +2024-11-22 20:22:00.238627: val_loss -0.7696 +2024-11-22 20:22:00.238700: Pseudo dice [0.8425] +2024-11-22 20:22:00.238775: Epoch time: 18.33 s +2024-11-22 20:22:01.148024: +2024-11-22 20:22:01.148314: Epoch 6261 +2024-11-22 20:22:01.148419: Current learning rate: 0.00253 +2024-11-22 20:22:19.489425: train_loss -0.7933 +2024-11-22 20:22:19.489639: val_loss -0.7697 +2024-11-22 20:22:19.489710: Pseudo dice [0.8446] +2024-11-22 20:22:19.489780: Epoch time: 18.34 s +2024-11-22 20:22:20.390226: +2024-11-22 20:22:20.390444: Epoch 6262 +2024-11-22 20:22:20.390553: Current learning rate: 0.00253 +2024-11-22 20:22:39.257187: train_loss -0.7974 +2024-11-22 20:22:39.257450: val_loss -0.7814 +2024-11-22 20:22:39.257633: Pseudo dice [0.8472] +2024-11-22 20:22:39.257730: Epoch time: 18.87 s +2024-11-22 20:22:40.157954: +2024-11-22 20:22:40.158271: Epoch 6263 +2024-11-22 20:22:40.158385: Current learning rate: 0.00253 +2024-11-22 20:22:58.556534: train_loss -0.7923 +2024-11-22 20:22:58.556830: val_loss -0.7833 +2024-11-22 20:22:58.556907: Pseudo dice [0.8584] +2024-11-22 20:22:58.556983: Epoch time: 18.4 s +2024-11-22 20:22:59.544737: +2024-11-22 20:22:59.544948: Epoch 6264 +2024-11-22 20:22:59.545064: Current learning rate: 0.00253 +2024-11-22 20:23:18.233933: train_loss -0.7998 +2024-11-22 20:23:18.234153: val_loss -0.7838 +2024-11-22 20:23:18.234226: Pseudo dice [0.843] +2024-11-22 20:23:18.234300: Epoch time: 18.69 s +2024-11-22 20:23:19.513539: +2024-11-22 20:23:19.513737: Epoch 6265 +2024-11-22 20:23:19.513846: Current learning rate: 0.00253 +2024-11-22 20:23:37.778929: train_loss -0.8035 +2024-11-22 20:23:37.779292: val_loss -0.7865 +2024-11-22 20:23:37.779372: Pseudo dice [0.847] +2024-11-22 20:23:37.779451: Epoch time: 18.27 s +2024-11-22 20:23:38.683643: +2024-11-22 20:23:38.683866: Epoch 6266 +2024-11-22 20:23:38.683973: Current learning rate: 0.00253 +2024-11-22 20:23:57.008242: train_loss -0.8042 +2024-11-22 20:23:57.008467: val_loss -0.7829 +2024-11-22 20:23:57.008542: Pseudo dice [0.8611] +2024-11-22 20:23:57.008616: Epoch time: 18.33 s +2024-11-22 20:23:57.907822: +2024-11-22 20:23:57.908058: Epoch 6267 +2024-11-22 20:23:57.908174: Current learning rate: 0.00252 +2024-11-22 20:24:16.886653: train_loss -0.8009 +2024-11-22 20:24:16.886876: val_loss -0.775 +2024-11-22 20:24:16.886950: Pseudo dice [0.8592] +2024-11-22 20:24:16.887031: Epoch time: 18.98 s +2024-11-22 20:24:17.786004: +2024-11-22 20:24:17.786207: Epoch 6268 +2024-11-22 20:24:17.786313: Current learning rate: 0.00252 +2024-11-22 20:24:37.359003: train_loss -0.802 +2024-11-22 20:24:37.359229: val_loss -0.7681 +2024-11-22 20:24:37.359305: Pseudo dice [0.8665] +2024-11-22 20:24:37.359380: Epoch time: 19.57 s +2024-11-22 20:24:38.260730: +2024-11-22 20:24:38.260967: Epoch 6269 +2024-11-22 20:24:38.261085: Current learning rate: 0.00252 +2024-11-22 20:24:56.595115: train_loss -0.8064 +2024-11-22 20:24:56.595369: val_loss -0.7622 +2024-11-22 20:24:56.595448: Pseudo dice [0.8555] +2024-11-22 20:24:56.595529: Epoch time: 18.34 s +2024-11-22 20:24:57.713695: +2024-11-22 20:24:57.713918: Epoch 6270 +2024-11-22 20:24:57.714034: Current learning rate: 0.00252 +2024-11-22 20:25:15.509480: train_loss -0.8075 +2024-11-22 20:25:15.510572: val_loss -0.7876 +2024-11-22 20:25:15.510651: Pseudo dice [0.8647] +2024-11-22 20:25:15.510724: Epoch time: 17.8 s +2024-11-22 20:25:16.407635: +2024-11-22 20:25:16.407856: Epoch 6271 +2024-11-22 20:25:16.407968: Current learning rate: 0.00252 +2024-11-22 20:25:34.398181: train_loss -0.8124 +2024-11-22 20:25:34.398460: val_loss -0.7751 +2024-11-22 20:25:34.398532: Pseudo dice [0.8521] +2024-11-22 20:25:34.398606: Epoch time: 17.99 s +2024-11-22 20:25:35.301435: +2024-11-22 20:25:35.301658: Epoch 6272 +2024-11-22 20:25:35.301773: Current learning rate: 0.00252 +2024-11-22 20:25:53.741316: train_loss -0.811 +2024-11-22 20:25:53.741534: val_loss -0.7641 +2024-11-22 20:25:53.741607: Pseudo dice [0.8373] +2024-11-22 20:25:53.741683: Epoch time: 18.44 s +2024-11-22 20:25:54.672447: +2024-11-22 20:25:54.672838: Epoch 6273 +2024-11-22 20:25:54.672951: Current learning rate: 0.00252 +2024-11-22 20:26:12.889301: train_loss -0.8083 +2024-11-22 20:26:12.894846: val_loss -0.7864 +2024-11-22 20:26:12.894958: Pseudo dice [0.8403] +2024-11-22 20:26:12.895045: Epoch time: 18.22 s +2024-11-22 20:26:13.815425: +2024-11-22 20:26:13.815618: Epoch 6274 +2024-11-22 20:26:13.815728: Current learning rate: 0.00252 +2024-11-22 20:26:33.079198: train_loss -0.8047 +2024-11-22 20:26:33.079449: val_loss -0.7748 +2024-11-22 20:26:33.079529: Pseudo dice [0.8519] +2024-11-22 20:26:33.079606: Epoch time: 19.26 s +2024-11-22 20:26:33.977442: +2024-11-22 20:26:33.977656: Epoch 6275 +2024-11-22 20:26:33.977768: Current learning rate: 0.00251 +2024-11-22 20:26:52.016781: train_loss -0.808 +2024-11-22 20:26:52.016983: val_loss -0.7648 +2024-11-22 20:26:52.017062: Pseudo dice [0.8469] +2024-11-22 20:26:52.017136: Epoch time: 18.04 s +2024-11-22 20:26:52.952416: +2024-11-22 20:26:52.952619: Epoch 6276 +2024-11-22 20:26:52.952726: Current learning rate: 0.00251 +2024-11-22 20:27:12.281896: train_loss -0.8051 +2024-11-22 20:27:12.282422: val_loss -0.7709 +2024-11-22 20:27:12.282521: Pseudo dice [0.8571] +2024-11-22 20:27:12.282603: Epoch time: 19.33 s +2024-11-22 20:27:13.179445: +2024-11-22 20:27:13.179730: Epoch 6277 +2024-11-22 20:27:13.179845: Current learning rate: 0.00251 +2024-11-22 20:27:31.992956: train_loss -0.8055 +2024-11-22 20:27:31.993175: val_loss -0.78 +2024-11-22 20:27:31.993247: Pseudo dice [0.8469] +2024-11-22 20:27:31.993320: Epoch time: 18.81 s +2024-11-22 20:27:32.884426: +2024-11-22 20:27:32.884640: Epoch 6278 +2024-11-22 20:27:32.884749: Current learning rate: 0.00251 +2024-11-22 20:27:50.608486: train_loss -0.8056 +2024-11-22 20:27:50.608705: val_loss -0.7621 +2024-11-22 20:27:50.608778: Pseudo dice [0.8364] +2024-11-22 20:27:50.608853: Epoch time: 17.72 s +2024-11-22 20:27:51.511144: +2024-11-22 20:27:51.511357: Epoch 6279 +2024-11-22 20:27:51.511467: Current learning rate: 0.00251 +2024-11-22 20:28:09.795360: train_loss -0.802 +2024-11-22 20:28:09.795581: val_loss -0.7861 +2024-11-22 20:28:09.795654: Pseudo dice [0.85] +2024-11-22 20:28:09.795730: Epoch time: 18.29 s +2024-11-22 20:28:10.698294: +2024-11-22 20:28:10.698518: Epoch 6280 +2024-11-22 20:28:10.698629: Current learning rate: 0.00251 +2024-11-22 20:28:29.079433: train_loss -0.8091 +2024-11-22 20:28:29.079666: val_loss -0.7727 +2024-11-22 20:28:29.079743: Pseudo dice [0.8452] +2024-11-22 20:28:29.079866: Epoch time: 18.38 s +2024-11-22 20:28:29.978048: +2024-11-22 20:28:29.978260: Epoch 6281 +2024-11-22 20:28:29.978372: Current learning rate: 0.00251 +2024-11-22 20:28:48.214018: train_loss -0.8063 +2024-11-22 20:28:48.216415: val_loss -0.7729 +2024-11-22 20:28:48.216734: Pseudo dice [0.8517] +2024-11-22 20:28:48.216825: Epoch time: 18.24 s +2024-11-22 20:28:49.189058: +2024-11-22 20:28:49.189310: Epoch 6282 +2024-11-22 20:28:49.189421: Current learning rate: 0.0025 +2024-11-22 20:29:07.586097: train_loss -0.8085 +2024-11-22 20:29:07.586307: val_loss -0.7717 +2024-11-22 20:29:07.586381: Pseudo dice [0.8403] +2024-11-22 20:29:07.586458: Epoch time: 18.4 s +2024-11-22 20:29:08.487414: +2024-11-22 20:29:08.487673: Epoch 6283 +2024-11-22 20:29:08.487788: Current learning rate: 0.0025 +2024-11-22 20:29:25.752966: train_loss -0.813 +2024-11-22 20:29:25.753222: val_loss -0.7962 +2024-11-22 20:29:25.753298: Pseudo dice [0.8758] +2024-11-22 20:29:25.753378: Epoch time: 17.27 s +2024-11-22 20:29:26.829215: +2024-11-22 20:29:26.829439: Epoch 6284 +2024-11-22 20:29:26.829556: Current learning rate: 0.0025 +2024-11-22 20:29:45.801050: train_loss -0.7991 +2024-11-22 20:29:45.801269: val_loss -0.786 +2024-11-22 20:29:45.801343: Pseudo dice [0.8538] +2024-11-22 20:29:45.801419: Epoch time: 18.97 s +2024-11-22 20:29:46.718509: +2024-11-22 20:29:46.718770: Epoch 6285 +2024-11-22 20:29:46.718879: Current learning rate: 0.0025 +2024-11-22 20:30:04.757272: train_loss -0.8081 +2024-11-22 20:30:04.757500: val_loss -0.7609 +2024-11-22 20:30:04.757578: Pseudo dice [0.8474] +2024-11-22 20:30:04.757658: Epoch time: 18.04 s +2024-11-22 20:30:05.654243: +2024-11-22 20:30:05.654443: Epoch 6286 +2024-11-22 20:30:05.654556: Current learning rate: 0.0025 +2024-11-22 20:30:24.646966: train_loss -0.8039 +2024-11-22 20:30:24.647183: val_loss -0.7784 +2024-11-22 20:30:24.647258: Pseudo dice [0.8437] +2024-11-22 20:30:24.647331: Epoch time: 18.99 s +2024-11-22 20:30:25.543322: +2024-11-22 20:30:25.543532: Epoch 6287 +2024-11-22 20:30:25.543641: Current learning rate: 0.0025 +2024-11-22 20:30:44.088035: train_loss -0.811 +2024-11-22 20:30:44.088278: val_loss -0.7833 +2024-11-22 20:30:44.088354: Pseudo dice [0.8522] +2024-11-22 20:30:44.088446: Epoch time: 18.55 s +2024-11-22 20:30:45.370799: +2024-11-22 20:30:45.371051: Epoch 6288 +2024-11-22 20:30:45.371166: Current learning rate: 0.0025 +2024-11-22 20:31:04.437919: train_loss -0.8047 +2024-11-22 20:31:04.438184: val_loss -0.7738 +2024-11-22 20:31:04.438260: Pseudo dice [0.8652] +2024-11-22 20:31:04.438337: Epoch time: 19.07 s +2024-11-22 20:31:05.400879: +2024-11-22 20:31:05.401085: Epoch 6289 +2024-11-22 20:31:05.401189: Current learning rate: 0.0025 +2024-11-22 20:31:23.673369: train_loss -0.8084 +2024-11-22 20:31:23.673591: val_loss -0.7638 +2024-11-22 20:31:23.673664: Pseudo dice [0.8374] +2024-11-22 20:31:23.673736: Epoch time: 18.27 s +2024-11-22 20:31:24.572021: +2024-11-22 20:31:24.572247: Epoch 6290 +2024-11-22 20:31:24.572363: Current learning rate: 0.00249 +2024-11-22 20:31:43.304119: train_loss -0.8082 +2024-11-22 20:31:43.304371: val_loss -0.8081 +2024-11-22 20:31:43.304450: Pseudo dice [0.8558] +2024-11-22 20:31:43.304534: Epoch time: 18.73 s +2024-11-22 20:31:44.298548: +2024-11-22 20:31:44.298890: Epoch 6291 +2024-11-22 20:31:44.299007: Current learning rate: 0.00249 +2024-11-22 20:32:03.305816: train_loss -0.8074 +2024-11-22 20:32:03.306060: val_loss -0.7615 +2024-11-22 20:32:03.306134: Pseudo dice [0.8454] +2024-11-22 20:32:03.306211: Epoch time: 19.01 s +2024-11-22 20:32:04.210751: +2024-11-22 20:32:04.210960: Epoch 6292 +2024-11-22 20:32:04.211075: Current learning rate: 0.00249 +2024-11-22 20:32:22.420176: train_loss -0.8084 +2024-11-22 20:32:22.420388: val_loss -0.7605 +2024-11-22 20:32:22.420460: Pseudo dice [0.8562] +2024-11-22 20:32:22.420533: Epoch time: 18.21 s +2024-11-22 20:32:23.373958: +2024-11-22 20:32:23.374181: Epoch 6293 +2024-11-22 20:32:23.374313: Current learning rate: 0.00249 +2024-11-22 20:32:41.705652: train_loss -0.8077 +2024-11-22 20:32:41.705864: val_loss -0.7756 +2024-11-22 20:32:41.705940: Pseudo dice [0.8379] +2024-11-22 20:32:41.706042: Epoch time: 18.33 s +2024-11-22 20:32:42.608460: +2024-11-22 20:32:42.608668: Epoch 6294 +2024-11-22 20:32:42.608778: Current learning rate: 0.00249 +2024-11-22 20:33:00.729235: train_loss -0.812 +2024-11-22 20:33:00.729497: val_loss -0.7825 +2024-11-22 20:33:00.729573: Pseudo dice [0.8502] +2024-11-22 20:33:00.729656: Epoch time: 18.12 s +2024-11-22 20:33:01.634081: +2024-11-22 20:33:01.634359: Epoch 6295 +2024-11-22 20:33:01.634473: Current learning rate: 0.00249 +2024-11-22 20:33:20.198956: train_loss -0.8058 +2024-11-22 20:33:20.199271: val_loss -0.7666 +2024-11-22 20:33:20.199358: Pseudo dice [0.8558] +2024-11-22 20:33:20.199434: Epoch time: 18.57 s +2024-11-22 20:33:21.251704: +2024-11-22 20:33:21.251981: Epoch 6296 +2024-11-22 20:33:21.252099: Current learning rate: 0.00249 +2024-11-22 20:33:39.498358: train_loss -0.8114 +2024-11-22 20:33:39.498574: val_loss -0.7866 +2024-11-22 20:33:39.498649: Pseudo dice [0.8642] +2024-11-22 20:33:39.498724: Epoch time: 18.25 s +2024-11-22 20:33:40.396646: +2024-11-22 20:33:40.396849: Epoch 6297 +2024-11-22 20:33:40.396960: Current learning rate: 0.00248 +2024-11-22 20:33:58.084206: train_loss -0.8143 +2024-11-22 20:33:58.084408: val_loss -0.7694 +2024-11-22 20:33:58.084481: Pseudo dice [0.8693] +2024-11-22 20:33:58.084556: Epoch time: 17.69 s +2024-11-22 20:33:59.091300: +2024-11-22 20:33:59.091520: Epoch 6298 +2024-11-22 20:33:59.091636: Current learning rate: 0.00248 +2024-11-22 20:34:17.598552: train_loss -0.8122 +2024-11-22 20:34:17.598803: val_loss -0.7688 +2024-11-22 20:34:17.598881: Pseudo dice [0.8379] +2024-11-22 20:34:17.598959: Epoch time: 18.51 s +2024-11-22 20:34:18.887932: +2024-11-22 20:34:18.888152: Epoch 6299 +2024-11-22 20:34:18.888266: Current learning rate: 0.00248 +2024-11-22 20:34:35.772144: train_loss -0.8066 +2024-11-22 20:34:35.772372: val_loss -0.7821 +2024-11-22 20:34:35.772446: Pseudo dice [0.8509] +2024-11-22 20:34:35.772522: Epoch time: 16.89 s +2024-11-22 20:34:36.978814: +2024-11-22 20:34:36.979081: Epoch 6300 +2024-11-22 20:34:36.979192: Current learning rate: 0.00248 +2024-11-22 20:34:55.239887: train_loss -0.8176 +2024-11-22 20:34:55.240113: val_loss -0.7775 +2024-11-22 20:34:55.240187: Pseudo dice [0.8504] +2024-11-22 20:34:55.240262: Epoch time: 18.26 s +2024-11-22 20:34:56.141685: +2024-11-22 20:34:56.141919: Epoch 6301 +2024-11-22 20:34:56.142039: Current learning rate: 0.00248 +2024-11-22 20:35:14.720918: train_loss -0.8123 +2024-11-22 20:35:14.722330: val_loss -0.7633 +2024-11-22 20:35:14.722414: Pseudo dice [0.8521] +2024-11-22 20:35:14.722498: Epoch time: 18.58 s +2024-11-22 20:35:15.623780: +2024-11-22 20:35:15.624000: Epoch 6302 +2024-11-22 20:35:15.624114: Current learning rate: 0.00248 +2024-11-22 20:35:33.771169: train_loss -0.8109 +2024-11-22 20:35:33.771435: val_loss -0.7754 +2024-11-22 20:35:33.771511: Pseudo dice [0.8481] +2024-11-22 20:35:33.771586: Epoch time: 18.15 s +2024-11-22 20:35:34.722756: +2024-11-22 20:35:34.722955: Epoch 6303 +2024-11-22 20:35:34.723064: Current learning rate: 0.00248 +2024-11-22 20:35:52.824380: train_loss -0.8085 +2024-11-22 20:35:52.824588: val_loss -0.8072 +2024-11-22 20:35:52.824660: Pseudo dice [0.8617] +2024-11-22 20:35:52.824731: Epoch time: 18.1 s +2024-11-22 20:35:53.720716: +2024-11-22 20:35:53.720938: Epoch 6304 +2024-11-22 20:35:53.721068: Current learning rate: 0.00248 +2024-11-22 20:36:11.070298: train_loss -0.8125 +2024-11-22 20:36:11.070511: val_loss -0.8003 +2024-11-22 20:36:11.070587: Pseudo dice [0.862] +2024-11-22 20:36:11.070662: Epoch time: 17.35 s +2024-11-22 20:36:11.961726: +2024-11-22 20:36:11.961959: Epoch 6305 +2024-11-22 20:36:11.962081: Current learning rate: 0.00247 +2024-11-22 20:36:30.592563: train_loss -0.8113 +2024-11-22 20:36:30.592815: val_loss -0.7516 +2024-11-22 20:36:30.592892: Pseudo dice [0.8505] +2024-11-22 20:36:30.592970: Epoch time: 18.63 s +2024-11-22 20:36:31.527315: +2024-11-22 20:36:31.527541: Epoch 6306 +2024-11-22 20:36:31.527678: Current learning rate: 0.00247 +2024-11-22 20:36:49.854381: train_loss -0.807 +2024-11-22 20:36:49.854611: val_loss -0.7997 +2024-11-22 20:36:49.854688: Pseudo dice [0.858] +2024-11-22 20:36:49.854761: Epoch time: 18.33 s +2024-11-22 20:36:50.749087: +2024-11-22 20:36:50.749308: Epoch 6307 +2024-11-22 20:36:50.749419: Current learning rate: 0.00247 +2024-11-22 20:37:09.159030: train_loss -0.8122 +2024-11-22 20:37:09.159410: val_loss -0.7764 +2024-11-22 20:37:09.159502: Pseudo dice [0.8579] +2024-11-22 20:37:09.159581: Epoch time: 18.41 s +2024-11-22 20:37:10.054739: +2024-11-22 20:37:10.054946: Epoch 6308 +2024-11-22 20:37:10.055064: Current learning rate: 0.00247 +2024-11-22 20:37:27.493585: train_loss -0.8042 +2024-11-22 20:37:27.493849: val_loss -0.7895 +2024-11-22 20:37:27.493922: Pseudo dice [0.8613] +2024-11-22 20:37:27.494001: Epoch time: 17.44 s +2024-11-22 20:37:28.400050: +2024-11-22 20:37:28.400278: Epoch 6309 +2024-11-22 20:37:28.400389: Current learning rate: 0.00247 +2024-11-22 20:37:47.542818: train_loss -0.8105 +2024-11-22 20:37:47.543074: val_loss -0.7745 +2024-11-22 20:37:47.543151: Pseudo dice [0.8564] +2024-11-22 20:37:47.543237: Epoch time: 19.14 s +2024-11-22 20:37:48.447969: +2024-11-22 20:37:48.448184: Epoch 6310 +2024-11-22 20:37:48.448294: Current learning rate: 0.00247 +2024-11-22 20:38:07.580117: train_loss -0.8099 +2024-11-22 20:38:07.580359: val_loss -0.7897 +2024-11-22 20:38:07.580440: Pseudo dice [0.85] +2024-11-22 20:38:07.580516: Epoch time: 19.13 s +2024-11-22 20:38:08.943942: +2024-11-22 20:38:08.944150: Epoch 6311 +2024-11-22 20:38:08.944259: Current learning rate: 0.00247 +2024-11-22 20:38:27.633845: train_loss -0.7961 +2024-11-22 20:38:27.634087: val_loss -0.762 +2024-11-22 20:38:27.634218: Pseudo dice [0.8439] +2024-11-22 20:38:27.634330: Epoch time: 18.69 s +2024-11-22 20:38:28.537285: +2024-11-22 20:38:28.537555: Epoch 6312 +2024-11-22 20:38:28.537666: Current learning rate: 0.00247 +2024-11-22 20:38:46.557458: train_loss -0.7994 +2024-11-22 20:38:46.560919: val_loss -0.7752 +2024-11-22 20:38:46.561147: Pseudo dice [0.8605] +2024-11-22 20:38:46.561237: Epoch time: 18.02 s +2024-11-22 20:38:47.491552: +2024-11-22 20:38:47.491770: Epoch 6313 +2024-11-22 20:38:47.491877: Current learning rate: 0.00246 +2024-11-22 20:39:05.231534: train_loss -0.8074 +2024-11-22 20:39:05.231748: val_loss -0.7761 +2024-11-22 20:39:05.236970: Pseudo dice [0.8515] +2024-11-22 20:39:05.237132: Epoch time: 17.74 s +2024-11-22 20:39:06.379075: +2024-11-22 20:39:06.379293: Epoch 6314 +2024-11-22 20:39:06.379403: Current learning rate: 0.00246 +2024-11-22 20:39:25.072281: train_loss -0.8072 +2024-11-22 20:39:25.072498: val_loss -0.7975 +2024-11-22 20:39:25.072574: Pseudo dice [0.8542] +2024-11-22 20:39:25.072652: Epoch time: 18.69 s +2024-11-22 20:39:25.969840: +2024-11-22 20:39:25.970062: Epoch 6315 +2024-11-22 20:39:25.970176: Current learning rate: 0.00246 +2024-11-22 20:39:45.056580: train_loss -0.8021 +2024-11-22 20:39:45.056794: val_loss -0.7874 +2024-11-22 20:39:45.056870: Pseudo dice [0.8578] +2024-11-22 20:39:45.056948: Epoch time: 19.09 s +2024-11-22 20:39:46.007454: +2024-11-22 20:39:46.007675: Epoch 6316 +2024-11-22 20:39:46.007786: Current learning rate: 0.00246 +2024-11-22 20:40:05.533697: train_loss -0.8066 +2024-11-22 20:40:05.533930: val_loss -0.7643 +2024-11-22 20:40:05.534010: Pseudo dice [0.8473] +2024-11-22 20:40:05.534088: Epoch time: 19.53 s +2024-11-22 20:40:06.560500: +2024-11-22 20:40:06.560720: Epoch 6317 +2024-11-22 20:40:06.560832: Current learning rate: 0.00246 +2024-11-22 20:40:24.786962: train_loss -0.8049 +2024-11-22 20:40:24.787221: val_loss -0.7502 +2024-11-22 20:40:24.787298: Pseudo dice [0.8512] +2024-11-22 20:40:24.787380: Epoch time: 18.23 s +2024-11-22 20:40:25.768974: +2024-11-22 20:40:25.769212: Epoch 6318 +2024-11-22 20:40:25.769320: Current learning rate: 0.00246 +2024-11-22 20:40:44.261266: train_loss -0.8094 +2024-11-22 20:40:44.261484: val_loss -0.7676 +2024-11-22 20:40:44.261557: Pseudo dice [0.842] +2024-11-22 20:40:44.261632: Epoch time: 18.49 s +2024-11-22 20:40:45.260418: +2024-11-22 20:40:45.260635: Epoch 6319 +2024-11-22 20:40:45.260749: Current learning rate: 0.00246 +2024-11-22 20:41:03.696399: train_loss -0.8123 +2024-11-22 20:41:03.696626: val_loss -0.7595 +2024-11-22 20:41:03.696704: Pseudo dice [0.8181] +2024-11-22 20:41:03.696776: Epoch time: 18.44 s +2024-11-22 20:41:04.599155: +2024-11-22 20:41:04.599357: Epoch 6320 +2024-11-22 20:41:04.599463: Current learning rate: 0.00245 +2024-11-22 20:41:23.105377: train_loss -0.8122 +2024-11-22 20:41:23.105636: val_loss -0.7948 +2024-11-22 20:41:23.105717: Pseudo dice [0.846] +2024-11-22 20:41:23.105849: Epoch time: 18.51 s +2024-11-22 20:41:24.010782: +2024-11-22 20:41:24.011004: Epoch 6321 +2024-11-22 20:41:24.011113: Current learning rate: 0.00245 +2024-11-22 20:41:41.954017: train_loss -0.8063 +2024-11-22 20:41:41.954230: val_loss -0.7806 +2024-11-22 20:41:41.954307: Pseudo dice [0.8564] +2024-11-22 20:41:41.954382: Epoch time: 17.94 s +2024-11-22 20:41:43.230983: +2024-11-22 20:41:43.231224: Epoch 6322 +2024-11-22 20:41:43.231349: Current learning rate: 0.00245 +2024-11-22 20:42:00.591306: train_loss -0.8069 +2024-11-22 20:42:00.591528: val_loss -0.757 +2024-11-22 20:42:00.591603: Pseudo dice [0.8425] +2024-11-22 20:42:00.591680: Epoch time: 17.36 s +2024-11-22 20:42:01.487392: +2024-11-22 20:42:01.487589: Epoch 6323 +2024-11-22 20:42:01.487697: Current learning rate: 0.00245 +2024-11-22 20:42:19.134661: train_loss -0.8111 +2024-11-22 20:42:19.134877: val_loss -0.7762 +2024-11-22 20:42:19.134951: Pseudo dice [0.8529] +2024-11-22 20:42:19.135034: Epoch time: 17.65 s +2024-11-22 20:42:20.046845: +2024-11-22 20:42:20.047064: Epoch 6324 +2024-11-22 20:42:20.047169: Current learning rate: 0.00245 +2024-11-22 20:42:39.496414: train_loss -0.8063 +2024-11-22 20:42:39.496659: val_loss -0.7747 +2024-11-22 20:42:39.496734: Pseudo dice [0.8548] +2024-11-22 20:42:39.496815: Epoch time: 19.45 s +2024-11-22 20:42:40.440892: +2024-11-22 20:42:40.441121: Epoch 6325 +2024-11-22 20:42:40.441229: Current learning rate: 0.00245 +2024-11-22 20:42:59.822775: train_loss -0.8102 +2024-11-22 20:42:59.823003: val_loss -0.7702 +2024-11-22 20:42:59.823079: Pseudo dice [0.8504] +2024-11-22 20:42:59.823151: Epoch time: 19.38 s +2024-11-22 20:43:00.783918: +2024-11-22 20:43:00.784154: Epoch 6326 +2024-11-22 20:43:00.784267: Current learning rate: 0.00245 +2024-11-22 20:43:18.339855: train_loss -0.8134 +2024-11-22 20:43:18.340102: val_loss -0.7687 +2024-11-22 20:43:18.342414: Pseudo dice [0.8425] +2024-11-22 20:43:18.342536: Epoch time: 17.56 s +2024-11-22 20:43:19.277697: +2024-11-22 20:43:19.277893: Epoch 6327 +2024-11-22 20:43:19.278005: Current learning rate: 0.00245 +2024-11-22 20:43:37.589056: train_loss -0.8081 +2024-11-22 20:43:37.589278: val_loss -0.7874 +2024-11-22 20:43:37.589356: Pseudo dice [0.8613] +2024-11-22 20:43:37.589432: Epoch time: 18.31 s +2024-11-22 20:43:38.526281: +2024-11-22 20:43:38.526557: Epoch 6328 +2024-11-22 20:43:38.526666: Current learning rate: 0.00244 +2024-11-22 20:43:56.965845: train_loss -0.8029 +2024-11-22 20:43:56.968238: val_loss -0.7925 +2024-11-22 20:43:56.968423: Pseudo dice [0.8591] +2024-11-22 20:43:56.968514: Epoch time: 18.44 s +2024-11-22 20:43:57.883882: +2024-11-22 20:43:57.884103: Epoch 6329 +2024-11-22 20:43:57.884224: Current learning rate: 0.00244 +2024-11-22 20:44:18.251064: train_loss -0.81 +2024-11-22 20:44:18.251315: val_loss -0.7606 +2024-11-22 20:44:18.251421: Pseudo dice [0.8361] +2024-11-22 20:44:18.251498: Epoch time: 20.37 s +2024-11-22 20:44:19.152480: +2024-11-22 20:44:19.152770: Epoch 6330 +2024-11-22 20:44:19.152880: Current learning rate: 0.00244 +2024-11-22 20:44:38.165885: train_loss -0.8103 +2024-11-22 20:44:38.166153: val_loss -0.7908 +2024-11-22 20:44:38.166233: Pseudo dice [0.8541] +2024-11-22 20:44:38.166312: Epoch time: 19.01 s +2024-11-22 20:44:39.058391: +2024-11-22 20:44:39.058607: Epoch 6331 +2024-11-22 20:44:39.058720: Current learning rate: 0.00244 +2024-11-22 20:44:58.063713: train_loss -0.8048 +2024-11-22 20:44:58.063935: val_loss -0.7958 +2024-11-22 20:44:58.064031: Pseudo dice [0.8613] +2024-11-22 20:44:58.064113: Epoch time: 19.01 s +2024-11-22 20:44:58.960260: +2024-11-22 20:44:58.960478: Epoch 6332 +2024-11-22 20:44:58.960589: Current learning rate: 0.00244 +2024-11-22 20:45:16.902843: train_loss -0.8154 +2024-11-22 20:45:16.903085: val_loss -0.7901 +2024-11-22 20:45:16.903158: Pseudo dice [0.8405] +2024-11-22 20:45:16.903243: Epoch time: 17.94 s +2024-11-22 20:45:17.801322: +2024-11-22 20:45:17.801726: Epoch 6333 +2024-11-22 20:45:17.801855: Current learning rate: 0.00244 +2024-11-22 20:45:36.303771: train_loss -0.8167 +2024-11-22 20:45:36.304127: val_loss -0.76 +2024-11-22 20:45:36.304209: Pseudo dice [0.8542] +2024-11-22 20:45:36.304281: Epoch time: 18.5 s +2024-11-22 20:45:37.589842: +2024-11-22 20:45:37.590070: Epoch 6334 +2024-11-22 20:45:37.590181: Current learning rate: 0.00244 +2024-11-22 20:45:55.937319: train_loss -0.8076 +2024-11-22 20:45:55.937563: val_loss -0.7586 +2024-11-22 20:45:55.937639: Pseudo dice [0.8303] +2024-11-22 20:45:55.937712: Epoch time: 18.35 s +2024-11-22 20:45:56.844969: +2024-11-22 20:45:56.845212: Epoch 6335 +2024-11-22 20:45:56.845328: Current learning rate: 0.00243 +2024-11-22 20:46:14.270391: train_loss -0.8089 +2024-11-22 20:46:14.270648: val_loss -0.7816 +2024-11-22 20:46:14.270725: Pseudo dice [0.8436] +2024-11-22 20:46:14.270805: Epoch time: 17.43 s +2024-11-22 20:46:15.168709: +2024-11-22 20:46:15.168926: Epoch 6336 +2024-11-22 20:46:15.169039: Current learning rate: 0.00243 +2024-11-22 20:46:34.006612: train_loss -0.8065 +2024-11-22 20:46:34.006824: val_loss -0.7897 +2024-11-22 20:46:34.006900: Pseudo dice [0.8356] +2024-11-22 20:46:34.006973: Epoch time: 18.84 s +2024-11-22 20:46:34.901214: +2024-11-22 20:46:34.901433: Epoch 6337 +2024-11-22 20:46:34.901547: Current learning rate: 0.00243 +2024-11-22 20:46:53.335553: train_loss -0.8108 +2024-11-22 20:46:53.335789: val_loss -0.7689 +2024-11-22 20:46:53.335864: Pseudo dice [0.8468] +2024-11-22 20:46:53.335943: Epoch time: 18.44 s +2024-11-22 20:46:54.246435: +2024-11-22 20:46:54.246647: Epoch 6338 +2024-11-22 20:46:54.246754: Current learning rate: 0.00243 +2024-11-22 20:47:13.365714: train_loss -0.8111 +2024-11-22 20:47:13.365935: val_loss -0.7747 +2024-11-22 20:47:13.368194: Pseudo dice [0.8486] +2024-11-22 20:47:13.368299: Epoch time: 19.12 s +2024-11-22 20:47:14.290452: +2024-11-22 20:47:14.290648: Epoch 6339 +2024-11-22 20:47:14.290759: Current learning rate: 0.00243 +2024-11-22 20:47:32.830247: train_loss -0.8141 +2024-11-22 20:47:32.830539: val_loss -0.7652 +2024-11-22 20:47:32.830622: Pseudo dice [0.852] +2024-11-22 20:47:32.830704: Epoch time: 18.54 s +2024-11-22 20:47:33.934015: +2024-11-22 20:47:33.934289: Epoch 6340 +2024-11-22 20:47:33.934400: Current learning rate: 0.00243 +2024-11-22 20:47:51.712839: train_loss -0.8133 +2024-11-22 20:47:51.718233: val_loss -0.782 +2024-11-22 20:47:51.718354: Pseudo dice [0.8404] +2024-11-22 20:47:51.718431: Epoch time: 17.78 s +2024-11-22 20:47:52.756282: +2024-11-22 20:47:52.756504: Epoch 6341 +2024-11-22 20:47:52.756611: Current learning rate: 0.00243 +2024-11-22 20:48:12.546728: train_loss -0.8136 +2024-11-22 20:48:12.546958: val_loss -0.7832 +2024-11-22 20:48:12.547037: Pseudo dice [0.8558] +2024-11-22 20:48:12.547113: Epoch time: 19.79 s +2024-11-22 20:48:13.512156: +2024-11-22 20:48:13.512400: Epoch 6342 +2024-11-22 20:48:13.512515: Current learning rate: 0.00243 +2024-11-22 20:48:34.235282: train_loss -0.8114 +2024-11-22 20:48:34.235497: val_loss -0.7639 +2024-11-22 20:48:34.235573: Pseudo dice [0.8505] +2024-11-22 20:48:34.235648: Epoch time: 20.72 s +2024-11-22 20:48:35.134007: +2024-11-22 20:48:35.134235: Epoch 6343 +2024-11-22 20:48:35.134346: Current learning rate: 0.00242 +2024-11-22 20:48:53.896516: train_loss -0.8006 +2024-11-22 20:48:53.896753: val_loss -0.7684 +2024-11-22 20:48:53.896832: Pseudo dice [0.8557] +2024-11-22 20:48:53.896912: Epoch time: 18.76 s +2024-11-22 20:48:54.794793: +2024-11-22 20:48:54.795022: Epoch 6344 +2024-11-22 20:48:54.795135: Current learning rate: 0.00242 +2024-11-22 20:49:12.895101: train_loss -0.8094 +2024-11-22 20:49:12.895314: val_loss -0.7906 +2024-11-22 20:49:12.895386: Pseudo dice [0.863] +2024-11-22 20:49:12.895458: Epoch time: 18.1 s +2024-11-22 20:49:14.241575: +2024-11-22 20:49:14.241802: Epoch 6345 +2024-11-22 20:49:14.241912: Current learning rate: 0.00242 +2024-11-22 20:49:31.864975: train_loss -0.8165 +2024-11-22 20:49:31.865215: val_loss -0.786 +2024-11-22 20:49:31.865289: Pseudo dice [0.8588] +2024-11-22 20:49:31.865363: Epoch time: 17.62 s +2024-11-22 20:49:32.886006: +2024-11-22 20:49:32.886324: Epoch 6346 +2024-11-22 20:49:32.886434: Current learning rate: 0.00242 +2024-11-22 20:49:50.892072: train_loss -0.8075 +2024-11-22 20:49:50.892282: val_loss -0.8002 +2024-11-22 20:49:50.892355: Pseudo dice [0.8505] +2024-11-22 20:49:50.892433: Epoch time: 18.01 s +2024-11-22 20:49:51.789625: +2024-11-22 20:49:51.789834: Epoch 6347 +2024-11-22 20:49:51.789945: Current learning rate: 0.00242 +2024-11-22 20:50:09.554472: train_loss -0.809 +2024-11-22 20:50:09.554725: val_loss -0.7575 +2024-11-22 20:50:09.554803: Pseudo dice [0.8426] +2024-11-22 20:50:09.554886: Epoch time: 17.77 s +2024-11-22 20:50:10.483730: +2024-11-22 20:50:10.483949: Epoch 6348 +2024-11-22 20:50:10.484068: Current learning rate: 0.00242 +2024-11-22 20:50:29.246540: train_loss -0.8071 +2024-11-22 20:50:29.246810: val_loss -0.7635 +2024-11-22 20:50:29.246893: Pseudo dice [0.846] +2024-11-22 20:50:29.246974: Epoch time: 18.76 s +2024-11-22 20:50:30.142482: +2024-11-22 20:50:30.142703: Epoch 6349 +2024-11-22 20:50:30.142809: Current learning rate: 0.00242 +2024-11-22 20:50:48.948364: train_loss -0.794 +2024-11-22 20:50:48.948590: val_loss -0.7605 +2024-11-22 20:50:48.948663: Pseudo dice [0.8403] +2024-11-22 20:50:48.948740: Epoch time: 18.81 s +2024-11-22 20:50:50.161700: +2024-11-22 20:50:50.161925: Epoch 6350 +2024-11-22 20:50:50.162043: Current learning rate: 0.00242 +2024-11-22 20:51:08.308406: train_loss -0.8081 +2024-11-22 20:51:08.308627: val_loss -0.7833 +2024-11-22 20:51:08.308703: Pseudo dice [0.8607] +2024-11-22 20:51:08.308782: Epoch time: 18.15 s +2024-11-22 20:51:09.217426: +2024-11-22 20:51:09.217662: Epoch 6351 +2024-11-22 20:51:09.217771: Current learning rate: 0.00241 +2024-11-22 20:51:28.046712: train_loss -0.8091 +2024-11-22 20:51:28.046952: val_loss -0.7932 +2024-11-22 20:51:28.047032: Pseudo dice [0.856] +2024-11-22 20:51:28.047112: Epoch time: 18.83 s +2024-11-22 20:51:29.091054: +2024-11-22 20:51:29.091285: Epoch 6352 +2024-11-22 20:51:29.091396: Current learning rate: 0.00241 +2024-11-22 20:51:47.917938: train_loss -0.8073 +2024-11-22 20:51:47.918155: val_loss -0.7545 +2024-11-22 20:51:47.918230: Pseudo dice [0.8331] +2024-11-22 20:51:47.918304: Epoch time: 18.83 s +2024-11-22 20:51:48.816679: +2024-11-22 20:51:48.816890: Epoch 6353 +2024-11-22 20:51:48.817003: Current learning rate: 0.00241 +2024-11-22 20:52:06.340515: train_loss -0.8151 +2024-11-22 20:52:06.340751: val_loss -0.7628 +2024-11-22 20:52:06.340829: Pseudo dice [0.8565] +2024-11-22 20:52:06.340905: Epoch time: 17.52 s +2024-11-22 20:52:07.234924: +2024-11-22 20:52:07.235134: Epoch 6354 +2024-11-22 20:52:07.235243: Current learning rate: 0.00241 +2024-11-22 20:52:24.887927: train_loss -0.8089 +2024-11-22 20:52:24.888146: val_loss -0.8003 +2024-11-22 20:52:24.888227: Pseudo dice [0.858] +2024-11-22 20:52:24.888302: Epoch time: 17.65 s +2024-11-22 20:52:25.785787: +2024-11-22 20:52:25.786013: Epoch 6355 +2024-11-22 20:52:25.786128: Current learning rate: 0.00241 +2024-11-22 20:52:45.757619: train_loss -0.8076 +2024-11-22 20:52:45.757858: val_loss -0.7677 +2024-11-22 20:52:45.757931: Pseudo dice [0.8506] +2024-11-22 20:52:45.758014: Epoch time: 19.97 s +2024-11-22 20:52:46.657353: +2024-11-22 20:52:46.657765: Epoch 6356 +2024-11-22 20:52:46.657892: Current learning rate: 0.00241 +2024-11-22 20:53:04.329351: train_loss -0.8127 +2024-11-22 20:53:04.329566: val_loss -0.7875 +2024-11-22 20:53:04.329640: Pseudo dice [0.8466] +2024-11-22 20:53:04.334885: Epoch time: 17.67 s +2024-11-22 20:53:05.687135: +2024-11-22 20:53:05.687385: Epoch 6357 +2024-11-22 20:53:05.687501: Current learning rate: 0.00241 +2024-11-22 20:53:23.822355: train_loss -0.8102 +2024-11-22 20:53:23.822587: val_loss -0.7722 +2024-11-22 20:53:23.822664: Pseudo dice [0.8644] +2024-11-22 20:53:23.822749: Epoch time: 18.14 s +2024-11-22 20:53:24.718612: +2024-11-22 20:53:24.718838: Epoch 6358 +2024-11-22 20:53:24.718947: Current learning rate: 0.0024 +2024-11-22 20:53:43.204000: train_loss -0.8162 +2024-11-22 20:53:43.204238: val_loss -0.7465 +2024-11-22 20:53:43.204311: Pseudo dice [0.847] +2024-11-22 20:53:43.204389: Epoch time: 18.49 s +2024-11-22 20:53:44.116979: +2024-11-22 20:53:44.117206: Epoch 6359 +2024-11-22 20:53:44.117314: Current learning rate: 0.0024 +2024-11-22 20:54:02.995901: train_loss -0.8127 +2024-11-22 20:54:02.998301: val_loss -0.7701 +2024-11-22 20:54:02.998417: Pseudo dice [0.8357] +2024-11-22 20:54:02.998492: Epoch time: 18.88 s +2024-11-22 20:54:03.920227: +2024-11-22 20:54:03.920441: Epoch 6360 +2024-11-22 20:54:03.920549: Current learning rate: 0.0024 +2024-11-22 20:54:22.251627: train_loss -0.8081 +2024-11-22 20:54:22.251835: val_loss -0.7781 +2024-11-22 20:54:22.251914: Pseudo dice [0.8542] +2024-11-22 20:54:22.251997: Epoch time: 18.33 s +2024-11-22 20:54:23.236704: +2024-11-22 20:54:23.236927: Epoch 6361 +2024-11-22 20:54:23.237047: Current learning rate: 0.0024 +2024-11-22 20:54:41.907749: train_loss -0.8133 +2024-11-22 20:54:41.908033: val_loss -0.7806 +2024-11-22 20:54:41.908114: Pseudo dice [0.8478] +2024-11-22 20:54:41.908195: Epoch time: 18.67 s +2024-11-22 20:54:42.824014: +2024-11-22 20:54:42.824241: Epoch 6362 +2024-11-22 20:54:42.824356: Current learning rate: 0.0024 +2024-11-22 20:55:01.899602: train_loss -0.8143 +2024-11-22 20:55:01.899845: val_loss -0.7931 +2024-11-22 20:55:01.899917: Pseudo dice [0.8674] +2024-11-22 20:55:01.900001: Epoch time: 19.08 s +2024-11-22 20:55:02.839644: +2024-11-22 20:55:02.839853: Epoch 6363 +2024-11-22 20:55:02.839960: Current learning rate: 0.0024 +2024-11-22 20:55:21.922389: train_loss -0.8122 +2024-11-22 20:55:21.922624: val_loss -0.7721 +2024-11-22 20:55:21.922703: Pseudo dice [0.8476] +2024-11-22 20:55:21.922776: Epoch time: 19.08 s +2024-11-22 20:55:22.826833: +2024-11-22 20:55:22.827157: Epoch 6364 +2024-11-22 20:55:22.827264: Current learning rate: 0.0024 +2024-11-22 20:55:40.914275: train_loss -0.8033 +2024-11-22 20:55:40.914493: val_loss -0.7811 +2024-11-22 20:55:40.914567: Pseudo dice [0.8543] +2024-11-22 20:55:40.914641: Epoch time: 18.09 s +2024-11-22 20:55:41.982828: +2024-11-22 20:55:41.983046: Epoch 6365 +2024-11-22 20:55:41.983171: Current learning rate: 0.0024 +2024-11-22 20:56:00.724712: train_loss -0.8065 +2024-11-22 20:56:00.725018: val_loss -0.7687 +2024-11-22 20:56:00.725095: Pseudo dice [0.8447] +2024-11-22 20:56:00.725181: Epoch time: 18.74 s +2024-11-22 20:56:01.626359: +2024-11-22 20:56:01.626573: Epoch 6366 +2024-11-22 20:56:01.626683: Current learning rate: 0.00239 +2024-11-22 20:56:19.497956: train_loss -0.8014 +2024-11-22 20:56:19.498186: val_loss -0.7864 +2024-11-22 20:56:19.498263: Pseudo dice [0.8686] +2024-11-22 20:56:19.498338: Epoch time: 17.87 s +2024-11-22 20:56:20.395693: +2024-11-22 20:56:20.395925: Epoch 6367 +2024-11-22 20:56:20.396043: Current learning rate: 0.00239 +2024-11-22 20:56:38.443074: train_loss -0.8019 +2024-11-22 20:56:38.443323: val_loss -0.7635 +2024-11-22 20:56:38.443456: Pseudo dice [0.8606] +2024-11-22 20:56:38.443535: Epoch time: 18.05 s +2024-11-22 20:56:39.716882: +2024-11-22 20:56:39.717323: Epoch 6368 +2024-11-22 20:56:39.717460: Current learning rate: 0.00239 +2024-11-22 20:56:58.646302: train_loss -0.8069 +2024-11-22 20:56:58.646531: val_loss -0.7979 +2024-11-22 20:56:58.646607: Pseudo dice [0.8495] +2024-11-22 20:56:58.646683: Epoch time: 18.93 s +2024-11-22 20:56:59.554629: +2024-11-22 20:56:59.555080: Epoch 6369 +2024-11-22 20:56:59.555218: Current learning rate: 0.00239 +2024-11-22 20:57:18.250154: train_loss -0.802 +2024-11-22 20:57:18.250364: val_loss -0.7839 +2024-11-22 20:57:18.250440: Pseudo dice [0.8551] +2024-11-22 20:57:18.250515: Epoch time: 18.7 s +2024-11-22 20:57:19.147782: +2024-11-22 20:57:19.148204: Epoch 6370 +2024-11-22 20:57:19.148329: Current learning rate: 0.00239 +2024-11-22 20:57:38.281974: train_loss -0.8094 +2024-11-22 20:57:38.282201: val_loss -0.7955 +2024-11-22 20:57:38.282290: Pseudo dice [0.8526] +2024-11-22 20:57:38.282371: Epoch time: 19.13 s +2024-11-22 20:57:39.186430: +2024-11-22 20:57:39.186859: Epoch 6371 +2024-11-22 20:57:39.186990: Current learning rate: 0.00239 +2024-11-22 20:57:57.967392: train_loss -0.806 +2024-11-22 20:57:57.967670: val_loss -0.7938 +2024-11-22 20:57:57.967749: Pseudo dice [0.865] +2024-11-22 20:57:57.967825: Epoch time: 18.78 s +2024-11-22 20:57:58.874622: +2024-11-22 20:57:58.875075: Epoch 6372 +2024-11-22 20:57:58.875213: Current learning rate: 0.00239 +2024-11-22 20:58:17.945568: train_loss -0.8124 +2024-11-22 20:58:17.945839: val_loss -0.7872 +2024-11-22 20:58:17.945920: Pseudo dice [0.8512] +2024-11-22 20:58:17.946011: Epoch time: 19.07 s +2024-11-22 20:58:18.854932: +2024-11-22 20:58:18.855357: Epoch 6373 +2024-11-22 20:58:18.855490: Current learning rate: 0.00238 +2024-11-22 20:58:36.919587: train_loss -0.8199 +2024-11-22 20:58:36.919851: val_loss -0.7828 +2024-11-22 20:58:36.919924: Pseudo dice [0.8328] +2024-11-22 20:58:36.920006: Epoch time: 18.07 s +2024-11-22 20:58:37.853406: +2024-11-22 20:58:37.853814: Epoch 6374 +2024-11-22 20:58:37.853945: Current learning rate: 0.00238 +2024-11-22 20:58:56.213076: train_loss -0.8118 +2024-11-22 20:58:56.213305: val_loss -0.7896 +2024-11-22 20:58:56.213380: Pseudo dice [0.8602] +2024-11-22 20:58:56.213457: Epoch time: 18.36 s +2024-11-22 20:58:57.214301: +2024-11-22 20:58:57.214756: Epoch 6375 +2024-11-22 20:58:57.214890: Current learning rate: 0.00238 +2024-11-22 20:59:15.570643: train_loss -0.8098 +2024-11-22 20:59:15.573038: val_loss -0.7779 +2024-11-22 20:59:15.573124: Pseudo dice [0.8597] +2024-11-22 20:59:15.573201: Epoch time: 18.36 s +2024-11-22 20:59:16.605273: +2024-11-22 20:59:16.605699: Epoch 6376 +2024-11-22 20:59:16.605873: Current learning rate: 0.00238 +2024-11-22 20:59:34.876582: train_loss -0.8126 +2024-11-22 20:59:34.876848: val_loss -0.7699 +2024-11-22 20:59:34.876922: Pseudo dice [0.8438] +2024-11-22 20:59:34.877006: Epoch time: 18.27 s +2024-11-22 20:59:35.774238: +2024-11-22 20:59:35.774666: Epoch 6377 +2024-11-22 20:59:35.774793: Current learning rate: 0.00238 +2024-11-22 20:59:55.577698: train_loss -0.8072 +2024-11-22 20:59:55.577921: val_loss -0.7758 +2024-11-22 20:59:55.578003: Pseudo dice [0.8562] +2024-11-22 20:59:55.578081: Epoch time: 19.8 s +2024-11-22 20:59:56.582286: +2024-11-22 20:59:56.582508: Epoch 6378 +2024-11-22 20:59:56.582624: Current learning rate: 0.00238 +2024-11-22 21:00:15.753883: train_loss -0.8145 +2024-11-22 21:00:15.754100: val_loss -0.7939 +2024-11-22 21:00:15.754174: Pseudo dice [0.8601] +2024-11-22 21:00:15.754247: Epoch time: 19.17 s +2024-11-22 21:00:16.656851: +2024-11-22 21:00:16.657387: Epoch 6379 +2024-11-22 21:00:16.657525: Current learning rate: 0.00238 +2024-11-22 21:00:35.167984: train_loss -0.8147 +2024-11-22 21:00:35.173411: val_loss -0.7745 +2024-11-22 21:00:35.173495: Pseudo dice [0.8516] +2024-11-22 21:00:35.173580: Epoch time: 18.51 s +2024-11-22 21:00:36.539770: +2024-11-22 21:00:36.540023: Epoch 6380 +2024-11-22 21:00:36.540134: Current learning rate: 0.00238 +2024-11-22 21:00:54.989204: train_loss -0.8107 +2024-11-22 21:00:54.989432: val_loss -0.7669 +2024-11-22 21:00:54.989506: Pseudo dice [0.8506] +2024-11-22 21:00:54.989580: Epoch time: 18.45 s +2024-11-22 21:00:55.958496: +2024-11-22 21:00:55.958710: Epoch 6381 +2024-11-22 21:00:55.958823: Current learning rate: 0.00237 +2024-11-22 21:01:14.518552: train_loss -0.815 +2024-11-22 21:01:14.518779: val_loss -0.7815 +2024-11-22 21:01:14.518855: Pseudo dice [0.8699] +2024-11-22 21:01:14.518979: Epoch time: 18.56 s +2024-11-22 21:01:15.417173: +2024-11-22 21:01:15.417432: Epoch 6382 +2024-11-22 21:01:15.417549: Current learning rate: 0.00237 +2024-11-22 21:01:33.810042: train_loss -0.8148 +2024-11-22 21:01:33.810256: val_loss -0.777 +2024-11-22 21:01:33.810332: Pseudo dice [0.8492] +2024-11-22 21:01:33.810406: Epoch time: 18.39 s +2024-11-22 21:01:34.788134: +2024-11-22 21:01:34.788352: Epoch 6383 +2024-11-22 21:01:34.788498: Current learning rate: 0.00237 +2024-11-22 21:01:53.553047: train_loss -0.8135 +2024-11-22 21:01:53.553301: val_loss -0.8051 +2024-11-22 21:01:53.553376: Pseudo dice [0.8543] +2024-11-22 21:01:53.553454: Epoch time: 18.77 s +2024-11-22 21:01:54.462909: +2024-11-22 21:01:54.463125: Epoch 6384 +2024-11-22 21:01:54.463235: Current learning rate: 0.00237 +2024-11-22 21:02:12.524495: train_loss -0.8112 +2024-11-22 21:02:12.524719: val_loss -0.7779 +2024-11-22 21:02:12.524801: Pseudo dice [0.8513] +2024-11-22 21:02:12.524879: Epoch time: 18.06 s +2024-11-22 21:02:13.673988: +2024-11-22 21:02:13.674185: Epoch 6385 +2024-11-22 21:02:13.674296: Current learning rate: 0.00237 +2024-11-22 21:02:31.977147: train_loss -0.8106 +2024-11-22 21:02:31.977361: val_loss -0.7902 +2024-11-22 21:02:31.977434: Pseudo dice [0.8636] +2024-11-22 21:02:31.977507: Epoch time: 18.3 s +2024-11-22 21:02:32.878481: +2024-11-22 21:02:32.878715: Epoch 6386 +2024-11-22 21:02:32.878828: Current learning rate: 0.00237 +2024-11-22 21:02:51.457844: train_loss -0.8103 +2024-11-22 21:02:51.458380: val_loss -0.7593 +2024-11-22 21:02:51.458458: Pseudo dice [0.8543] +2024-11-22 21:02:51.458542: Epoch time: 18.58 s +2024-11-22 21:02:52.355246: +2024-11-22 21:02:52.355454: Epoch 6387 +2024-11-22 21:02:52.355564: Current learning rate: 0.00237 +2024-11-22 21:03:10.394579: train_loss -0.8091 +2024-11-22 21:03:10.396037: val_loss -0.7789 +2024-11-22 21:03:10.396127: Pseudo dice [0.8577] +2024-11-22 21:03:10.396201: Epoch time: 18.04 s +2024-11-22 21:03:11.355174: +2024-11-22 21:03:11.355399: Epoch 6388 +2024-11-22 21:03:11.355511: Current learning rate: 0.00237 +2024-11-22 21:03:29.700022: train_loss -0.8076 +2024-11-22 21:03:29.700252: val_loss -0.7926 +2024-11-22 21:03:29.700329: Pseudo dice [0.8532] +2024-11-22 21:03:29.700405: Epoch time: 18.35 s +2024-11-22 21:03:30.601263: +2024-11-22 21:03:30.601713: Epoch 6389 +2024-11-22 21:03:30.601847: Current learning rate: 0.00236 +2024-11-22 21:03:48.020905: train_loss -0.8084 +2024-11-22 21:03:48.021461: val_loss -0.7892 +2024-11-22 21:03:48.021542: Pseudo dice [0.8607] +2024-11-22 21:03:48.021614: Epoch time: 17.42 s +2024-11-22 21:03:48.933318: +2024-11-22 21:03:48.933537: Epoch 6390 +2024-11-22 21:03:48.933649: Current learning rate: 0.00236 +2024-11-22 21:04:06.592640: train_loss -0.8098 +2024-11-22 21:04:06.592875: val_loss -0.7725 +2024-11-22 21:04:06.592951: Pseudo dice [0.856] +2024-11-22 21:04:06.593034: Epoch time: 17.66 s +2024-11-22 21:04:07.847342: +2024-11-22 21:04:07.847572: Epoch 6391 +2024-11-22 21:04:07.847684: Current learning rate: 0.00236 +2024-11-22 21:04:25.640137: train_loss -0.8127 +2024-11-22 21:04:25.640343: val_loss -0.7938 +2024-11-22 21:04:25.640419: Pseudo dice [0.8529] +2024-11-22 21:04:25.640494: Epoch time: 17.79 s +2024-11-22 21:04:26.540110: +2024-11-22 21:04:26.540331: Epoch 6392 +2024-11-22 21:04:26.540444: Current learning rate: 0.00236 +2024-11-22 21:04:43.785939: train_loss -0.8094 +2024-11-22 21:04:43.788330: val_loss -0.7489 +2024-11-22 21:04:43.788471: Pseudo dice [0.8483] +2024-11-22 21:04:43.788552: Epoch time: 17.25 s +2024-11-22 21:04:44.720129: +2024-11-22 21:04:44.720337: Epoch 6393 +2024-11-22 21:04:44.720453: Current learning rate: 0.00236 +2024-11-22 21:05:02.523111: train_loss -0.8169 +2024-11-22 21:05:02.523334: val_loss -0.7859 +2024-11-22 21:05:02.523407: Pseudo dice [0.8502] +2024-11-22 21:05:02.523498: Epoch time: 17.8 s +2024-11-22 21:05:03.428935: +2024-11-22 21:05:03.429162: Epoch 6394 +2024-11-22 21:05:03.429292: Current learning rate: 0.00236 +2024-11-22 21:05:22.943049: train_loss -0.8199 +2024-11-22 21:05:22.943270: val_loss -0.7729 +2024-11-22 21:05:22.943366: Pseudo dice [0.8501] +2024-11-22 21:05:22.943464: Epoch time: 19.51 s +2024-11-22 21:05:23.854882: +2024-11-22 21:05:23.855108: Epoch 6395 +2024-11-22 21:05:23.855217: Current learning rate: 0.00236 +2024-11-22 21:05:41.840475: train_loss -0.8114 +2024-11-22 21:05:41.840694: val_loss -0.7581 +2024-11-22 21:05:41.842139: Pseudo dice [0.8328] +2024-11-22 21:05:41.842253: Epoch time: 17.99 s +2024-11-22 21:05:43.027982: +2024-11-22 21:05:43.028198: Epoch 6396 +2024-11-22 21:05:43.028306: Current learning rate: 0.00235 +2024-11-22 21:06:01.995297: train_loss -0.8039 +2024-11-22 21:06:01.995511: val_loss -0.7523 +2024-11-22 21:06:01.995585: Pseudo dice [0.8371] +2024-11-22 21:06:02.000816: Epoch time: 18.97 s +2024-11-22 21:06:02.930040: +2024-11-22 21:06:02.930284: Epoch 6397 +2024-11-22 21:06:02.930399: Current learning rate: 0.00235 +2024-11-22 21:06:21.379345: train_loss -0.8067 +2024-11-22 21:06:21.379584: val_loss -0.7818 +2024-11-22 21:06:21.379658: Pseudo dice [0.8614] +2024-11-22 21:06:21.379743: Epoch time: 18.45 s +2024-11-22 21:06:22.283538: +2024-11-22 21:06:22.283770: Epoch 6398 +2024-11-22 21:06:22.283886: Current learning rate: 0.00235 +2024-11-22 21:06:40.356547: train_loss -0.815 +2024-11-22 21:06:40.356769: val_loss -0.7764 +2024-11-22 21:06:40.356849: Pseudo dice [0.8425] +2024-11-22 21:06:40.356928: Epoch time: 18.07 s +2024-11-22 21:06:41.253168: +2024-11-22 21:06:41.253363: Epoch 6399 +2024-11-22 21:06:41.253475: Current learning rate: 0.00235 +2024-11-22 21:06:59.597395: train_loss -0.8128 +2024-11-22 21:06:59.597611: val_loss -0.7588 +2024-11-22 21:06:59.597685: Pseudo dice [0.8396] +2024-11-22 21:06:59.597761: Epoch time: 18.35 s +2024-11-22 21:07:00.803698: +2024-11-22 21:07:00.804199: Epoch 6400 +2024-11-22 21:07:00.804340: Current learning rate: 0.00235 +2024-11-22 21:07:20.090772: train_loss -0.8072 +2024-11-22 21:07:20.091013: val_loss -0.7652 +2024-11-22 21:07:20.091105: Pseudo dice [0.8625] +2024-11-22 21:07:20.091204: Epoch time: 19.29 s +2024-11-22 21:07:20.994458: +2024-11-22 21:07:20.994689: Epoch 6401 +2024-11-22 21:07:20.994799: Current learning rate: 0.00235 +2024-11-22 21:07:38.938044: train_loss -0.8109 +2024-11-22 21:07:38.938284: val_loss -0.7839 +2024-11-22 21:07:38.938390: Pseudo dice [0.8601] +2024-11-22 21:07:38.938523: Epoch time: 17.94 s +2024-11-22 21:07:39.884232: +2024-11-22 21:07:39.884643: Epoch 6402 +2024-11-22 21:07:39.884782: Current learning rate: 0.00235 +2024-11-22 21:07:58.950422: train_loss -0.8065 +2024-11-22 21:07:58.950630: val_loss -0.7834 +2024-11-22 21:07:58.950706: Pseudo dice [0.8395] +2024-11-22 21:07:58.950780: Epoch time: 19.07 s +2024-11-22 21:08:00.234324: +2024-11-22 21:08:00.234605: Epoch 6403 +2024-11-22 21:08:00.234726: Current learning rate: 0.00235 +2024-11-22 21:08:19.622045: train_loss -0.8103 +2024-11-22 21:08:19.622272: val_loss -0.7866 +2024-11-22 21:08:19.622347: Pseudo dice [0.8417] +2024-11-22 21:08:19.622424: Epoch time: 19.39 s +2024-11-22 21:08:20.530403: +2024-11-22 21:08:20.530634: Epoch 6404 +2024-11-22 21:08:20.530745: Current learning rate: 0.00234 +2024-11-22 21:08:39.974646: train_loss -0.8088 +2024-11-22 21:08:39.974862: val_loss -0.7608 +2024-11-22 21:08:39.974937: Pseudo dice [0.8393] +2024-11-22 21:08:39.975019: Epoch time: 19.45 s +2024-11-22 21:08:41.069080: +2024-11-22 21:08:41.069387: Epoch 6405 +2024-11-22 21:08:41.069503: Current learning rate: 0.00234 +2024-11-22 21:09:00.200416: train_loss -0.7971 +2024-11-22 21:09:00.200654: val_loss -0.7664 +2024-11-22 21:09:00.200783: Pseudo dice [0.85] +2024-11-22 21:09:00.200859: Epoch time: 19.13 s +2024-11-22 21:09:01.110425: +2024-11-22 21:09:01.110645: Epoch 6406 +2024-11-22 21:09:01.110756: Current learning rate: 0.00234 +2024-11-22 21:09:19.737498: train_loss -0.8054 +2024-11-22 21:09:19.737720: val_loss -0.7779 +2024-11-22 21:09:19.737792: Pseudo dice [0.8577] +2024-11-22 21:09:19.737867: Epoch time: 18.63 s +2024-11-22 21:09:20.654475: +2024-11-22 21:09:20.654681: Epoch 6407 +2024-11-22 21:09:20.654791: Current learning rate: 0.00234 +2024-11-22 21:09:39.833465: train_loss -0.8127 +2024-11-22 21:09:39.833678: val_loss -0.7659 +2024-11-22 21:09:39.833757: Pseudo dice [0.8499] +2024-11-22 21:09:39.833836: Epoch time: 19.18 s +2024-11-22 21:09:40.734183: +2024-11-22 21:09:40.734415: Epoch 6408 +2024-11-22 21:09:40.734526: Current learning rate: 0.00234 +2024-11-22 21:10:00.634878: train_loss -0.8113 +2024-11-22 21:10:00.635175: val_loss -0.7845 +2024-11-22 21:10:00.635256: Pseudo dice [0.87] +2024-11-22 21:10:00.635332: Epoch time: 19.9 s +2024-11-22 21:10:01.577389: +2024-11-22 21:10:01.577584: Epoch 6409 +2024-11-22 21:10:01.577691: Current learning rate: 0.00234 +2024-11-22 21:10:19.091094: train_loss -0.8088 +2024-11-22 21:10:19.091340: val_loss -0.7794 +2024-11-22 21:10:19.091416: Pseudo dice [0.8491] +2024-11-22 21:10:19.091496: Epoch time: 17.51 s +2024-11-22 21:10:20.004477: +2024-11-22 21:10:20.004894: Epoch 6410 +2024-11-22 21:10:20.005008: Current learning rate: 0.00234 +2024-11-22 21:10:38.866899: train_loss -0.8025 +2024-11-22 21:10:38.869600: val_loss -0.7719 +2024-11-22 21:10:38.869736: Pseudo dice [0.84] +2024-11-22 21:10:38.869813: Epoch time: 18.86 s +2024-11-22 21:10:39.842160: +2024-11-22 21:10:39.842398: Epoch 6411 +2024-11-22 21:10:39.842658: Current learning rate: 0.00233 +2024-11-22 21:10:58.684786: train_loss -0.7917 +2024-11-22 21:10:58.685068: val_loss -0.7626 +2024-11-22 21:10:58.685143: Pseudo dice [0.8572] +2024-11-22 21:10:58.685215: Epoch time: 18.84 s +2024-11-22 21:10:59.583283: +2024-11-22 21:10:59.583482: Epoch 6412 +2024-11-22 21:10:59.583590: Current learning rate: 0.00233 +2024-11-22 21:11:17.853568: train_loss -0.8084 +2024-11-22 21:11:17.853825: val_loss -0.7537 +2024-11-22 21:11:17.853913: Pseudo dice [0.835] +2024-11-22 21:11:17.854020: Epoch time: 18.27 s +2024-11-22 21:11:18.775654: +2024-11-22 21:11:18.775874: Epoch 6413 +2024-11-22 21:11:18.775986: Current learning rate: 0.00233 +2024-11-22 21:11:37.096969: train_loss -0.8075 +2024-11-22 21:11:37.097219: val_loss -0.7602 +2024-11-22 21:11:37.097298: Pseudo dice [0.8475] +2024-11-22 21:11:37.097380: Epoch time: 18.32 s +2024-11-22 21:11:38.376914: +2024-11-22 21:11:38.377199: Epoch 6414 +2024-11-22 21:11:38.377312: Current learning rate: 0.00233 +2024-11-22 21:11:57.591063: train_loss -0.8147 +2024-11-22 21:11:57.591293: val_loss -0.7601 +2024-11-22 21:11:57.591392: Pseudo dice [0.8523] +2024-11-22 21:11:57.591472: Epoch time: 19.21 s +2024-11-22 21:11:58.495610: +2024-11-22 21:11:58.495821: Epoch 6415 +2024-11-22 21:11:58.495925: Current learning rate: 0.00233 +2024-11-22 21:12:16.463834: train_loss -0.8088 +2024-11-22 21:12:16.464082: val_loss -0.7666 +2024-11-22 21:12:16.464159: Pseudo dice [0.8498] +2024-11-22 21:12:16.464239: Epoch time: 17.97 s +2024-11-22 21:12:17.532739: +2024-11-22 21:12:17.532971: Epoch 6416 +2024-11-22 21:12:17.533089: Current learning rate: 0.00233 +2024-11-22 21:12:35.063417: train_loss -0.8048 +2024-11-22 21:12:35.063662: val_loss -0.7811 +2024-11-22 21:12:35.063746: Pseudo dice [0.8496] +2024-11-22 21:12:35.063852: Epoch time: 17.53 s +2024-11-22 21:12:35.967082: +2024-11-22 21:12:35.967468: Epoch 6417 +2024-11-22 21:12:35.967593: Current learning rate: 0.00233 +2024-11-22 21:12:54.765909: train_loss -0.8061 +2024-11-22 21:12:54.766135: val_loss -0.7606 +2024-11-22 21:12:54.766210: Pseudo dice [0.859] +2024-11-22 21:12:54.766286: Epoch time: 18.8 s +2024-11-22 21:12:55.676314: +2024-11-22 21:12:55.676529: Epoch 6418 +2024-11-22 21:12:55.676635: Current learning rate: 0.00233 +2024-11-22 21:13:13.925688: train_loss -0.8065 +2024-11-22 21:13:13.925904: val_loss -0.7495 +2024-11-22 21:13:13.926008: Pseudo dice [0.8452] +2024-11-22 21:13:13.926086: Epoch time: 18.25 s +2024-11-22 21:13:14.825148: +2024-11-22 21:13:14.825374: Epoch 6419 +2024-11-22 21:13:14.825488: Current learning rate: 0.00232 +2024-11-22 21:13:32.952091: train_loss -0.806 +2024-11-22 21:13:32.952315: val_loss -0.762 +2024-11-22 21:13:32.952389: Pseudo dice [0.8397] +2024-11-22 21:13:32.952464: Epoch time: 18.13 s +2024-11-22 21:13:33.859890: +2024-11-22 21:13:33.860112: Epoch 6420 +2024-11-22 21:13:33.860220: Current learning rate: 0.00232 +2024-11-22 21:13:52.560861: train_loss -0.8038 +2024-11-22 21:13:52.561133: val_loss -0.77 +2024-11-22 21:13:52.561211: Pseudo dice [0.855] +2024-11-22 21:13:52.561290: Epoch time: 18.7 s +2024-11-22 21:13:53.473266: +2024-11-22 21:13:53.473496: Epoch 6421 +2024-11-22 21:13:53.473610: Current learning rate: 0.00232 +2024-11-22 21:14:12.418959: train_loss -0.8013 +2024-11-22 21:14:12.419180: val_loss -0.7736 +2024-11-22 21:14:12.419261: Pseudo dice [0.855] +2024-11-22 21:14:12.419337: Epoch time: 18.95 s +2024-11-22 21:14:13.321516: +2024-11-22 21:14:13.321747: Epoch 6422 +2024-11-22 21:14:13.321861: Current learning rate: 0.00232 +2024-11-22 21:14:31.649015: train_loss -0.809 +2024-11-22 21:14:31.649240: val_loss -0.7548 +2024-11-22 21:14:31.649324: Pseudo dice [0.8553] +2024-11-22 21:14:31.649724: Epoch time: 18.33 s +2024-11-22 21:14:32.552168: +2024-11-22 21:14:32.552359: Epoch 6423 +2024-11-22 21:14:32.552464: Current learning rate: 0.00232 +2024-11-22 21:14:50.441553: train_loss -0.8083 +2024-11-22 21:14:50.441820: val_loss -0.773 +2024-11-22 21:14:50.441894: Pseudo dice [0.8582] +2024-11-22 21:14:50.441972: Epoch time: 17.89 s +2024-11-22 21:14:51.350352: +2024-11-22 21:14:51.350757: Epoch 6424 +2024-11-22 21:14:51.350886: Current learning rate: 0.00232 +2024-11-22 21:15:10.220999: train_loss -0.7948 +2024-11-22 21:15:10.221249: val_loss -0.7929 +2024-11-22 21:15:10.221345: Pseudo dice [0.8484] +2024-11-22 21:15:10.221478: Epoch time: 18.87 s +2024-11-22 21:15:11.147935: +2024-11-22 21:15:11.148150: Epoch 6425 +2024-11-22 21:15:11.148265: Current learning rate: 0.00232 +2024-11-22 21:15:29.670749: train_loss -0.8078 +2024-11-22 21:15:29.670968: val_loss -0.7963 +2024-11-22 21:15:29.671049: Pseudo dice [0.868] +2024-11-22 21:15:29.671125: Epoch time: 18.52 s +2024-11-22 21:15:30.968788: +2024-11-22 21:15:30.969016: Epoch 6426 +2024-11-22 21:15:30.969124: Current learning rate: 0.00231 +2024-11-22 21:15:50.654423: train_loss -0.8025 +2024-11-22 21:15:50.654666: val_loss -0.7941 +2024-11-22 21:15:50.654742: Pseudo dice [0.8584] +2024-11-22 21:15:50.654816: Epoch time: 19.69 s +2024-11-22 21:15:51.555103: +2024-11-22 21:15:51.555326: Epoch 6427 +2024-11-22 21:15:51.555432: Current learning rate: 0.00231 +2024-11-22 21:16:10.460562: train_loss -0.81 +2024-11-22 21:16:10.460808: val_loss -0.7626 +2024-11-22 21:16:10.460884: Pseudo dice [0.8411] +2024-11-22 21:16:10.460968: Epoch time: 18.91 s +2024-11-22 21:16:11.372243: +2024-11-22 21:16:11.372473: Epoch 6428 +2024-11-22 21:16:11.372598: Current learning rate: 0.00231 +2024-11-22 21:16:29.893342: train_loss -0.8127 +2024-11-22 21:16:29.893618: val_loss -0.8 +2024-11-22 21:16:29.893697: Pseudo dice [0.8488] +2024-11-22 21:16:29.893774: Epoch time: 18.52 s +2024-11-22 21:16:30.799515: +2024-11-22 21:16:30.799728: Epoch 6429 +2024-11-22 21:16:30.799840: Current learning rate: 0.00231 +2024-11-22 21:16:49.380310: train_loss -0.8055 +2024-11-22 21:16:49.380520: val_loss -0.7747 +2024-11-22 21:16:49.380595: Pseudo dice [0.8433] +2024-11-22 21:16:49.382824: Epoch time: 18.58 s +2024-11-22 21:16:50.441465: +2024-11-22 21:16:50.441680: Epoch 6430 +2024-11-22 21:16:50.441794: Current learning rate: 0.00231 +2024-11-22 21:17:09.603420: train_loss -0.8074 +2024-11-22 21:17:09.603646: val_loss -0.7832 +2024-11-22 21:17:09.603722: Pseudo dice [0.8506] +2024-11-22 21:17:09.603800: Epoch time: 19.16 s +2024-11-22 21:17:10.841977: +2024-11-22 21:17:10.842203: Epoch 6431 +2024-11-22 21:17:10.842311: Current learning rate: 0.00231 +2024-11-22 21:17:30.371812: train_loss -0.8022 +2024-11-22 21:17:30.372031: val_loss -0.7882 +2024-11-22 21:17:30.372109: Pseudo dice [0.837] +2024-11-22 21:17:30.372189: Epoch time: 19.53 s +2024-11-22 21:17:31.280720: +2024-11-22 21:17:31.280982: Epoch 6432 +2024-11-22 21:17:31.281108: Current learning rate: 0.00231 +2024-11-22 21:17:48.889296: train_loss -0.8046 +2024-11-22 21:17:48.889513: val_loss -0.7836 +2024-11-22 21:17:48.889585: Pseudo dice [0.8456] +2024-11-22 21:17:48.889661: Epoch time: 17.61 s +2024-11-22 21:17:49.964524: +2024-11-22 21:17:49.964746: Epoch 6433 +2024-11-22 21:17:49.964856: Current learning rate: 0.00231 +2024-11-22 21:18:07.861758: train_loss -0.8004 +2024-11-22 21:18:07.861972: val_loss -0.773 +2024-11-22 21:18:07.862057: Pseudo dice [0.8377] +2024-11-22 21:18:07.862135: Epoch time: 17.9 s +2024-11-22 21:18:08.762002: +2024-11-22 21:18:08.762236: Epoch 6434 +2024-11-22 21:18:08.762347: Current learning rate: 0.0023 +2024-11-22 21:18:27.102522: train_loss -0.8099 +2024-11-22 21:18:27.102745: val_loss -0.7867 +2024-11-22 21:18:27.102820: Pseudo dice [0.8582] +2024-11-22 21:18:27.102894: Epoch time: 18.34 s +2024-11-22 21:18:28.004106: +2024-11-22 21:18:28.004323: Epoch 6435 +2024-11-22 21:18:28.004446: Current learning rate: 0.0023 +2024-11-22 21:18:46.524870: train_loss -0.7993 +2024-11-22 21:18:46.529204: val_loss -0.7971 +2024-11-22 21:18:46.529318: Pseudo dice [0.8425] +2024-11-22 21:18:46.529405: Epoch time: 18.52 s +2024-11-22 21:18:47.478000: +2024-11-22 21:18:47.478430: Epoch 6436 +2024-11-22 21:18:47.478564: Current learning rate: 0.0023 +2024-11-22 21:19:05.945395: train_loss -0.8022 +2024-11-22 21:19:05.947787: val_loss -0.7519 +2024-11-22 21:19:05.947907: Pseudo dice [0.8513] +2024-11-22 21:19:05.947985: Epoch time: 18.47 s +2024-11-22 21:19:06.877371: +2024-11-22 21:19:06.877728: Epoch 6437 +2024-11-22 21:19:06.877846: Current learning rate: 0.0023 +2024-11-22 21:19:24.633528: train_loss -0.8096 +2024-11-22 21:19:24.634001: val_loss -0.7586 +2024-11-22 21:19:24.634098: Pseudo dice [0.8539] +2024-11-22 21:19:24.634172: Epoch time: 17.76 s +2024-11-22 21:19:25.561339: +2024-11-22 21:19:25.561549: Epoch 6438 +2024-11-22 21:19:25.561655: Current learning rate: 0.0023 +2024-11-22 21:19:44.672807: train_loss -0.8013 +2024-11-22 21:19:44.673040: val_loss -0.7521 +2024-11-22 21:19:44.673120: Pseudo dice [0.815] +2024-11-22 21:19:44.673197: Epoch time: 19.11 s +2024-11-22 21:19:45.578457: +2024-11-22 21:19:45.578714: Epoch 6439 +2024-11-22 21:19:45.578822: Current learning rate: 0.0023 +2024-11-22 21:20:04.695608: train_loss -0.8069 +2024-11-22 21:20:04.696830: val_loss -0.7707 +2024-11-22 21:20:04.696928: Pseudo dice [0.8366] +2024-11-22 21:20:04.697017: Epoch time: 19.12 s +2024-11-22 21:20:05.597219: +2024-11-22 21:20:05.597487: Epoch 6440 +2024-11-22 21:20:05.597602: Current learning rate: 0.0023 +2024-11-22 21:20:23.194164: train_loss -0.8017 +2024-11-22 21:20:23.194375: val_loss -0.7823 +2024-11-22 21:20:23.194448: Pseudo dice [0.8616] +2024-11-22 21:20:23.194522: Epoch time: 17.6 s +2024-11-22 21:20:24.093210: +2024-11-22 21:20:24.093451: Epoch 6441 +2024-11-22 21:20:24.093566: Current learning rate: 0.00229 +2024-11-22 21:20:42.380831: train_loss -0.8168 +2024-11-22 21:20:42.381059: val_loss -0.7681 +2024-11-22 21:20:42.381137: Pseudo dice [0.8575] +2024-11-22 21:20:42.381220: Epoch time: 18.29 s +2024-11-22 21:20:43.287261: +2024-11-22 21:20:43.287511: Epoch 6442 +2024-11-22 21:20:43.287630: Current learning rate: 0.00229 +2024-11-22 21:21:01.886618: train_loss -0.8072 +2024-11-22 21:21:01.886831: val_loss -0.7687 +2024-11-22 21:21:01.886904: Pseudo dice [0.8551] +2024-11-22 21:21:01.886979: Epoch time: 18.6 s +2024-11-22 21:21:02.802645: +2024-11-22 21:21:02.802865: Epoch 6443 +2024-11-22 21:21:02.802975: Current learning rate: 0.00229 +2024-11-22 21:21:21.545050: train_loss -0.7984 +2024-11-22 21:21:21.545849: val_loss -0.7832 +2024-11-22 21:21:21.545924: Pseudo dice [0.8528] +2024-11-22 21:21:21.546009: Epoch time: 18.74 s +2024-11-22 21:21:22.438668: +2024-11-22 21:21:22.438883: Epoch 6444 +2024-11-22 21:21:22.438989: Current learning rate: 0.00229 +2024-11-22 21:21:42.049540: train_loss -0.8098 +2024-11-22 21:21:42.049768: val_loss -0.7825 +2024-11-22 21:21:42.054995: Pseudo dice [0.846] +2024-11-22 21:21:42.055201: Epoch time: 19.61 s +2024-11-22 21:21:43.071697: +2024-11-22 21:21:43.071917: Epoch 6445 +2024-11-22 21:21:43.072029: Current learning rate: 0.00229 +2024-11-22 21:22:02.019768: train_loss -0.8079 +2024-11-22 21:22:02.019986: val_loss -0.7696 +2024-11-22 21:22:02.020068: Pseudo dice [0.848] +2024-11-22 21:22:02.020144: Epoch time: 18.95 s +2024-11-22 21:22:02.927329: +2024-11-22 21:22:02.927529: Epoch 6446 +2024-11-22 21:22:02.927646: Current learning rate: 0.00229 +2024-11-22 21:22:21.601205: train_loss -0.8041 +2024-11-22 21:22:21.601434: val_loss -0.7437 +2024-11-22 21:22:21.601510: Pseudo dice [0.8265] +2024-11-22 21:22:21.601590: Epoch time: 18.67 s +2024-11-22 21:22:22.505841: +2024-11-22 21:22:22.506071: Epoch 6447 +2024-11-22 21:22:22.506183: Current learning rate: 0.00229 +2024-11-22 21:22:41.747048: train_loss -0.8101 +2024-11-22 21:22:41.748752: val_loss -0.8041 +2024-11-22 21:22:41.748851: Pseudo dice [0.8572] +2024-11-22 21:22:41.748929: Epoch time: 19.24 s +2024-11-22 21:22:42.759329: +2024-11-22 21:22:42.759610: Epoch 6448 +2024-11-22 21:22:42.759722: Current learning rate: 0.00229 +2024-11-22 21:23:01.601003: train_loss -0.8073 +2024-11-22 21:23:01.601228: val_loss -0.7688 +2024-11-22 21:23:01.601303: Pseudo dice [0.8551] +2024-11-22 21:23:01.601377: Epoch time: 18.84 s +2024-11-22 21:23:02.932553: +2024-11-22 21:23:02.932816: Epoch 6449 +2024-11-22 21:23:02.932931: Current learning rate: 0.00228 +2024-11-22 21:23:21.233974: train_loss -0.8065 +2024-11-22 21:23:21.234232: val_loss -0.7827 +2024-11-22 21:23:21.234315: Pseudo dice [0.8628] +2024-11-22 21:23:21.234392: Epoch time: 18.3 s +2024-11-22 21:23:22.490205: +2024-11-22 21:23:22.490431: Epoch 6450 +2024-11-22 21:23:22.490548: Current learning rate: 0.00228 +2024-11-22 21:23:41.456424: train_loss -0.8088 +2024-11-22 21:23:41.456686: val_loss -0.7806 +2024-11-22 21:23:41.456763: Pseudo dice [0.8598] +2024-11-22 21:23:41.456866: Epoch time: 18.97 s +2024-11-22 21:23:42.374278: +2024-11-22 21:23:42.374496: Epoch 6451 +2024-11-22 21:23:42.374615: Current learning rate: 0.00228 +2024-11-22 21:24:00.135117: train_loss -0.8099 +2024-11-22 21:24:00.135347: val_loss -0.7782 +2024-11-22 21:24:00.135418: Pseudo dice [0.8539] +2024-11-22 21:24:00.135491: Epoch time: 17.76 s +2024-11-22 21:24:01.038313: +2024-11-22 21:24:01.038533: Epoch 6452 +2024-11-22 21:24:01.038641: Current learning rate: 0.00228 +2024-11-22 21:24:18.561832: train_loss -0.8077 +2024-11-22 21:24:18.562043: val_loss -0.7704 +2024-11-22 21:24:18.562119: Pseudo dice [0.8496] +2024-11-22 21:24:18.562196: Epoch time: 17.52 s +2024-11-22 21:24:19.462067: +2024-11-22 21:24:19.462320: Epoch 6453 +2024-11-22 21:24:19.462428: Current learning rate: 0.00228 +2024-11-22 21:24:38.603610: train_loss -0.8121 +2024-11-22 21:24:38.603838: val_loss -0.7671 +2024-11-22 21:24:38.603912: Pseudo dice [0.8303] +2024-11-22 21:24:38.603987: Epoch time: 19.14 s +2024-11-22 21:24:39.609457: +2024-11-22 21:24:39.609674: Epoch 6454 +2024-11-22 21:24:39.609785: Current learning rate: 0.00228 +2024-11-22 21:24:57.201948: train_loss -0.8137 +2024-11-22 21:24:57.202198: val_loss -0.7701 +2024-11-22 21:24:57.202275: Pseudo dice [0.8515] +2024-11-22 21:24:57.202352: Epoch time: 17.59 s +2024-11-22 21:24:58.116562: +2024-11-22 21:24:58.116778: Epoch 6455 +2024-11-22 21:24:58.116892: Current learning rate: 0.00228 +2024-11-22 21:25:15.595058: train_loss -0.7973 +2024-11-22 21:25:15.595301: val_loss -0.7495 +2024-11-22 21:25:15.595373: Pseudo dice [0.8501] +2024-11-22 21:25:15.597622: Epoch time: 17.48 s +2024-11-22 21:25:16.699553: +2024-11-22 21:25:16.699769: Epoch 6456 +2024-11-22 21:25:16.699886: Current learning rate: 0.00228 +2024-11-22 21:25:34.720912: train_loss -0.8097 +2024-11-22 21:25:34.721148: val_loss -0.7587 +2024-11-22 21:25:34.721220: Pseudo dice [0.849] +2024-11-22 21:25:34.721294: Epoch time: 18.02 s +2024-11-22 21:25:35.629527: +2024-11-22 21:25:35.629737: Epoch 6457 +2024-11-22 21:25:35.629849: Current learning rate: 0.00227 +2024-11-22 21:25:53.870709: train_loss -0.8036 +2024-11-22 21:25:53.870943: val_loss -0.766 +2024-11-22 21:25:53.871027: Pseudo dice [0.8436] +2024-11-22 21:25:53.871103: Epoch time: 18.24 s +2024-11-22 21:25:54.782927: +2024-11-22 21:25:54.783167: Epoch 6458 +2024-11-22 21:25:54.783276: Current learning rate: 0.00227 +2024-11-22 21:26:14.150161: train_loss -0.8052 +2024-11-22 21:26:14.150395: val_loss -0.7579 +2024-11-22 21:26:14.150471: Pseudo dice [0.8439] +2024-11-22 21:26:14.150548: Epoch time: 19.37 s +2024-11-22 21:26:15.143836: +2024-11-22 21:26:15.144068: Epoch 6459 +2024-11-22 21:26:15.144181: Current learning rate: 0.00227 +2024-11-22 21:26:34.283711: train_loss -0.8068 +2024-11-22 21:26:34.283947: val_loss -0.784 +2024-11-22 21:26:34.284026: Pseudo dice [0.8492] +2024-11-22 21:26:34.284103: Epoch time: 19.14 s +2024-11-22 21:26:35.548867: +2024-11-22 21:26:35.549099: Epoch 6460 +2024-11-22 21:26:35.549208: Current learning rate: 0.00227 +2024-11-22 21:26:54.963966: train_loss -0.8054 +2024-11-22 21:26:54.964196: val_loss -0.7961 +2024-11-22 21:26:54.964269: Pseudo dice [0.8437] +2024-11-22 21:26:54.964344: Epoch time: 19.42 s +2024-11-22 21:26:55.885907: +2024-11-22 21:26:55.886163: Epoch 6461 +2024-11-22 21:26:55.886272: Current learning rate: 0.00227 +2024-11-22 21:27:14.870213: train_loss -0.8109 +2024-11-22 21:27:14.870442: val_loss -0.7683 +2024-11-22 21:27:14.872712: Pseudo dice [0.8453] +2024-11-22 21:27:14.872798: Epoch time: 18.99 s +2024-11-22 21:27:15.862786: +2024-11-22 21:27:15.863025: Epoch 6462 +2024-11-22 21:27:15.863131: Current learning rate: 0.00227 +2024-11-22 21:27:34.755066: train_loss -0.8194 +2024-11-22 21:27:34.755356: val_loss -0.7947 +2024-11-22 21:27:34.755432: Pseudo dice [0.8494] +2024-11-22 21:27:34.755507: Epoch time: 18.89 s +2024-11-22 21:27:35.668457: +2024-11-22 21:27:35.668863: Epoch 6463 +2024-11-22 21:27:35.668985: Current learning rate: 0.00227 +2024-11-22 21:27:54.946083: train_loss -0.8123 +2024-11-22 21:27:54.946344: val_loss -0.772 +2024-11-22 21:27:54.946420: Pseudo dice [0.8537] +2024-11-22 21:27:54.946499: Epoch time: 19.28 s +2024-11-22 21:27:55.859180: +2024-11-22 21:27:55.859437: Epoch 6464 +2024-11-22 21:27:55.859551: Current learning rate: 0.00226 +2024-11-22 21:28:13.944439: train_loss -0.8024 +2024-11-22 21:28:13.944715: val_loss -0.7846 +2024-11-22 21:28:13.944791: Pseudo dice [0.8468] +2024-11-22 21:28:13.944866: Epoch time: 18.09 s +2024-11-22 21:28:14.861791: +2024-11-22 21:28:14.861988: Epoch 6465 +2024-11-22 21:28:14.862102: Current learning rate: 0.00226 +2024-11-22 21:28:33.245708: train_loss -0.8083 +2024-11-22 21:28:33.245932: val_loss -0.7484 +2024-11-22 21:28:33.246011: Pseudo dice [0.8307] +2024-11-22 21:28:33.246088: Epoch time: 18.38 s +2024-11-22 21:28:34.153108: +2024-11-22 21:28:34.153340: Epoch 6466 +2024-11-22 21:28:34.153455: Current learning rate: 0.00226 +2024-11-22 21:28:51.954513: train_loss -0.8149 +2024-11-22 21:28:51.954769: val_loss -0.7789 +2024-11-22 21:28:51.954849: Pseudo dice [0.8429] +2024-11-22 21:28:51.954999: Epoch time: 17.8 s +2024-11-22 21:28:52.874697: +2024-11-22 21:28:52.874964: Epoch 6467 +2024-11-22 21:28:52.875083: Current learning rate: 0.00226 +2024-11-22 21:29:10.497395: train_loss -0.8061 +2024-11-22 21:29:10.497611: val_loss -0.7851 +2024-11-22 21:29:10.497685: Pseudo dice [0.8438] +2024-11-22 21:29:10.497760: Epoch time: 17.62 s +2024-11-22 21:29:11.399776: +2024-11-22 21:29:11.400007: Epoch 6468 +2024-11-22 21:29:11.400121: Current learning rate: 0.00226 +2024-11-22 21:29:29.698137: train_loss -0.8085 +2024-11-22 21:29:29.698360: val_loss -0.7617 +2024-11-22 21:29:29.698433: Pseudo dice [0.8376] +2024-11-22 21:29:29.698509: Epoch time: 18.3 s +2024-11-22 21:29:30.607769: +2024-11-22 21:29:30.607976: Epoch 6469 +2024-11-22 21:29:30.608095: Current learning rate: 0.00226 +2024-11-22 21:29:49.890212: train_loss -0.8055 +2024-11-22 21:29:49.890430: val_loss -0.7698 +2024-11-22 21:29:49.890503: Pseudo dice [0.8615] +2024-11-22 21:29:49.890579: Epoch time: 19.28 s +2024-11-22 21:29:50.831985: +2024-11-22 21:29:50.832198: Epoch 6470 +2024-11-22 21:29:50.832302: Current learning rate: 0.00226 +2024-11-22 21:30:09.261303: train_loss -0.8081 +2024-11-22 21:30:09.261539: val_loss -0.7702 +2024-11-22 21:30:09.261614: Pseudo dice [0.8527] +2024-11-22 21:30:09.261691: Epoch time: 18.43 s +2024-11-22 21:30:10.169014: +2024-11-22 21:30:10.169246: Epoch 6471 +2024-11-22 21:30:10.169357: Current learning rate: 0.00226 +2024-11-22 21:30:29.069103: train_loss -0.7958 +2024-11-22 21:30:29.069335: val_loss -0.7622 +2024-11-22 21:30:29.069409: Pseudo dice [0.8442] +2024-11-22 21:30:29.069498: Epoch time: 18.9 s +2024-11-22 21:30:30.376461: +2024-11-22 21:30:30.376688: Epoch 6472 +2024-11-22 21:30:30.376798: Current learning rate: 0.00225 +2024-11-22 21:30:48.445672: train_loss -0.8124 +2024-11-22 21:30:48.445893: val_loss -0.7541 +2024-11-22 21:30:48.445966: Pseudo dice [0.8326] +2024-11-22 21:30:48.446048: Epoch time: 18.07 s +2024-11-22 21:30:49.347967: +2024-11-22 21:30:49.348185: Epoch 6473 +2024-11-22 21:30:49.348296: Current learning rate: 0.00225 +2024-11-22 21:31:08.214979: train_loss -0.8094 +2024-11-22 21:31:08.215238: val_loss -0.7475 +2024-11-22 21:31:08.249019: Pseudo dice [0.851] +2024-11-22 21:31:08.249238: Epoch time: 18.87 s +2024-11-22 21:31:09.256407: +2024-11-22 21:31:09.256639: Epoch 6474 +2024-11-22 21:31:09.256746: Current learning rate: 0.00225 +2024-11-22 21:31:27.155857: train_loss -0.8049 +2024-11-22 21:31:27.156184: val_loss -0.7761 +2024-11-22 21:31:27.156269: Pseudo dice [0.8435] +2024-11-22 21:31:27.156349: Epoch time: 17.9 s +2024-11-22 21:31:28.058147: +2024-11-22 21:31:28.058361: Epoch 6475 +2024-11-22 21:31:28.058472: Current learning rate: 0.00225 +2024-11-22 21:31:46.776445: train_loss -0.806 +2024-11-22 21:31:46.776658: val_loss -0.766 +2024-11-22 21:31:46.776731: Pseudo dice [0.8441] +2024-11-22 21:31:46.779030: Epoch time: 18.72 s +2024-11-22 21:31:47.699727: +2024-11-22 21:31:47.699924: Epoch 6476 +2024-11-22 21:31:47.700033: Current learning rate: 0.00225 +2024-11-22 21:32:06.283602: train_loss -0.8007 +2024-11-22 21:32:06.283819: val_loss -0.7539 +2024-11-22 21:32:06.283893: Pseudo dice [0.8393] +2024-11-22 21:32:06.283967: Epoch time: 18.58 s +2024-11-22 21:32:07.249803: +2024-11-22 21:32:07.250031: Epoch 6477 +2024-11-22 21:32:07.250144: Current learning rate: 0.00225 +2024-11-22 21:32:25.661387: train_loss -0.8006 +2024-11-22 21:32:25.661652: val_loss -0.7801 +2024-11-22 21:32:25.661727: Pseudo dice [0.8465] +2024-11-22 21:32:25.661811: Epoch time: 18.41 s +2024-11-22 21:32:26.573231: +2024-11-22 21:32:26.573445: Epoch 6478 +2024-11-22 21:32:26.573556: Current learning rate: 0.00225 +2024-11-22 21:32:45.352468: train_loss -0.8025 +2024-11-22 21:32:45.352683: val_loss -0.7904 +2024-11-22 21:32:45.352767: Pseudo dice [0.835] +2024-11-22 21:32:45.352842: Epoch time: 18.78 s +2024-11-22 21:32:46.273607: +2024-11-22 21:32:46.273818: Epoch 6479 +2024-11-22 21:32:46.273928: Current learning rate: 0.00224 +2024-11-22 21:33:05.191854: train_loss -0.8028 +2024-11-22 21:33:05.192151: val_loss -0.7621 +2024-11-22 21:33:05.192229: Pseudo dice [0.8434] +2024-11-22 21:33:05.192307: Epoch time: 18.92 s +2024-11-22 21:33:06.096728: +2024-11-22 21:33:06.097019: Epoch 6480 +2024-11-22 21:33:06.097128: Current learning rate: 0.00224 +2024-11-22 21:33:24.602747: train_loss -0.8101 +2024-11-22 21:33:24.603012: val_loss -0.7835 +2024-11-22 21:33:24.603151: Pseudo dice [0.8494] +2024-11-22 21:33:24.603228: Epoch time: 18.51 s +2024-11-22 21:33:25.511707: +2024-11-22 21:33:25.511941: Epoch 6481 +2024-11-22 21:33:25.512060: Current learning rate: 0.00224 +2024-11-22 21:33:44.609251: train_loss -0.7998 +2024-11-22 21:33:44.609464: val_loss -0.8109 +2024-11-22 21:33:44.609557: Pseudo dice [0.8612] +2024-11-22 21:33:44.609634: Epoch time: 19.1 s +2024-11-22 21:33:45.520799: +2024-11-22 21:33:45.521031: Epoch 6482 +2024-11-22 21:33:45.521149: Current learning rate: 0.00224 +2024-11-22 21:34:04.657400: train_loss -0.8134 +2024-11-22 21:34:04.657653: val_loss -0.7912 +2024-11-22 21:34:04.657729: Pseudo dice [0.8516] +2024-11-22 21:34:04.657806: Epoch time: 19.14 s +2024-11-22 21:34:06.006391: +2024-11-22 21:34:06.006623: Epoch 6483 +2024-11-22 21:34:06.006733: Current learning rate: 0.00224 +2024-11-22 21:34:26.304822: train_loss -0.8139 +2024-11-22 21:34:26.305058: val_loss -0.752 +2024-11-22 21:34:26.305137: Pseudo dice [0.8479] +2024-11-22 21:34:26.305217: Epoch time: 20.3 s +2024-11-22 21:34:27.206819: +2024-11-22 21:34:27.207044: Epoch 6484 +2024-11-22 21:34:27.207159: Current learning rate: 0.00224 +2024-11-22 21:34:44.897346: train_loss -0.8156 +2024-11-22 21:34:44.897563: val_loss -0.7828 +2024-11-22 21:34:44.897638: Pseudo dice [0.852] +2024-11-22 21:34:44.897710: Epoch time: 17.69 s +2024-11-22 21:34:45.804762: +2024-11-22 21:34:45.804995: Epoch 6485 +2024-11-22 21:34:45.805106: Current learning rate: 0.00224 +2024-11-22 21:35:05.055323: train_loss -0.8126 +2024-11-22 21:35:05.055575: val_loss -0.767 +2024-11-22 21:35:05.055656: Pseudo dice [0.8673] +2024-11-22 21:35:05.055738: Epoch time: 19.25 s +2024-11-22 21:35:05.986035: +2024-11-22 21:35:05.986246: Epoch 6486 +2024-11-22 21:35:05.986352: Current learning rate: 0.00224 +2024-11-22 21:35:24.899782: train_loss -0.8101 +2024-11-22 21:35:24.900009: val_loss -0.7566 +2024-11-22 21:35:24.900088: Pseudo dice [0.8461] +2024-11-22 21:35:24.900169: Epoch time: 18.91 s +2024-11-22 21:35:25.809821: +2024-11-22 21:35:25.810022: Epoch 6487 +2024-11-22 21:35:25.810133: Current learning rate: 0.00223 +2024-11-22 21:35:43.452909: train_loss -0.8108 +2024-11-22 21:35:43.453135: val_loss -0.7717 +2024-11-22 21:35:43.453212: Pseudo dice [0.8573] +2024-11-22 21:35:43.453291: Epoch time: 17.64 s +2024-11-22 21:35:44.354601: +2024-11-22 21:35:44.354827: Epoch 6488 +2024-11-22 21:35:44.354938: Current learning rate: 0.00223 +2024-11-22 21:36:02.331269: train_loss -0.8072 +2024-11-22 21:36:02.331490: val_loss -0.8015 +2024-11-22 21:36:02.331564: Pseudo dice [0.8546] +2024-11-22 21:36:02.331643: Epoch time: 17.98 s +2024-11-22 21:36:03.242135: +2024-11-22 21:36:03.242365: Epoch 6489 +2024-11-22 21:36:03.242479: Current learning rate: 0.00223 +2024-11-22 21:36:22.000500: train_loss -0.8166 +2024-11-22 21:36:22.000744: val_loss -0.7839 +2024-11-22 21:36:22.000818: Pseudo dice [0.8568] +2024-11-22 21:36:22.000914: Epoch time: 18.76 s +2024-11-22 21:36:22.909433: +2024-11-22 21:36:22.909667: Epoch 6490 +2024-11-22 21:36:22.909776: Current learning rate: 0.00223 +2024-11-22 21:36:41.017147: train_loss -0.8084 +2024-11-22 21:36:41.022557: val_loss -0.7656 +2024-11-22 21:36:41.022642: Pseudo dice [0.8527] +2024-11-22 21:36:41.022718: Epoch time: 18.11 s +2024-11-22 21:36:42.079891: +2024-11-22 21:36:42.080118: Epoch 6491 +2024-11-22 21:36:42.080232: Current learning rate: 0.00223 +2024-11-22 21:37:00.301565: train_loss -0.8092 +2024-11-22 21:37:00.301788: val_loss -0.7658 +2024-11-22 21:37:00.301863: Pseudo dice [0.8502] +2024-11-22 21:37:00.301940: Epoch time: 18.22 s +2024-11-22 21:37:01.199477: +2024-11-22 21:37:01.199696: Epoch 6492 +2024-11-22 21:37:01.199811: Current learning rate: 0.00223 +2024-11-22 21:37:19.754431: train_loss -0.8082 +2024-11-22 21:37:19.754656: val_loss -0.7915 +2024-11-22 21:37:19.754734: Pseudo dice [0.8636] +2024-11-22 21:37:19.754809: Epoch time: 18.56 s +2024-11-22 21:37:20.685891: +2024-11-22 21:37:20.686197: Epoch 6493 +2024-11-22 21:37:20.686309: Current learning rate: 0.00223 +2024-11-22 21:37:39.218003: train_loss -0.8077 +2024-11-22 21:37:39.218249: val_loss -0.798 +2024-11-22 21:37:39.218325: Pseudo dice [0.8595] +2024-11-22 21:37:39.218402: Epoch time: 18.53 s +2024-11-22 21:37:40.124024: +2024-11-22 21:37:40.124282: Epoch 6494 +2024-11-22 21:37:40.124392: Current learning rate: 0.00222 +2024-11-22 21:37:58.530156: train_loss -0.8097 +2024-11-22 21:37:58.530369: val_loss -0.7643 +2024-11-22 21:37:58.530443: Pseudo dice [0.8354] +2024-11-22 21:37:58.530519: Epoch time: 18.41 s +2024-11-22 21:37:59.827724: +2024-11-22 21:37:59.827959: Epoch 6495 +2024-11-22 21:37:59.828071: Current learning rate: 0.00222 +2024-11-22 21:38:18.531914: train_loss -0.7994 +2024-11-22 21:38:18.532157: val_loss -0.7822 +2024-11-22 21:38:18.532234: Pseudo dice [0.8557] +2024-11-22 21:38:18.532311: Epoch time: 18.7 s +2024-11-22 21:38:19.464792: +2024-11-22 21:38:19.465010: Epoch 6496 +2024-11-22 21:38:19.465118: Current learning rate: 0.00222 +2024-11-22 21:38:38.422493: train_loss -0.8017 +2024-11-22 21:38:38.422734: val_loss -0.762 +2024-11-22 21:38:38.422809: Pseudo dice [0.8328] +2024-11-22 21:38:38.422891: Epoch time: 18.96 s +2024-11-22 21:38:39.324684: +2024-11-22 21:38:39.324891: Epoch 6497 +2024-11-22 21:38:39.325003: Current learning rate: 0.00222 +2024-11-22 21:38:58.241052: train_loss -0.8107 +2024-11-22 21:38:58.241267: val_loss -0.7673 +2024-11-22 21:38:58.241343: Pseudo dice [0.8398] +2024-11-22 21:38:58.241416: Epoch time: 18.92 s +2024-11-22 21:38:59.147067: +2024-11-22 21:38:59.147293: Epoch 6498 +2024-11-22 21:38:59.147402: Current learning rate: 0.00222 +2024-11-22 21:39:17.540153: train_loss -0.8057 +2024-11-22 21:39:17.540393: val_loss -0.7744 +2024-11-22 21:39:17.540473: Pseudo dice [0.849] +2024-11-22 21:39:17.540549: Epoch time: 18.39 s +2024-11-22 21:39:18.625345: +2024-11-22 21:39:18.625553: Epoch 6499 +2024-11-22 21:39:18.625665: Current learning rate: 0.00222 +2024-11-22 21:39:37.646635: train_loss -0.804 +2024-11-22 21:39:37.646859: val_loss -0.7531 +2024-11-22 21:39:37.646933: Pseudo dice [0.8531] +2024-11-22 21:39:37.647013: Epoch time: 19.02 s +2024-11-22 21:39:38.865618: +2024-11-22 21:39:38.865877: Epoch 6500 +2024-11-22 21:39:38.865998: Current learning rate: 0.00222 +2024-11-22 21:39:58.556226: train_loss -0.8139 +2024-11-22 21:39:58.556480: val_loss -0.7692 +2024-11-22 21:39:58.556557: Pseudo dice [0.8442] +2024-11-22 21:39:58.556643: Epoch time: 19.69 s +2024-11-22 21:39:59.461629: +2024-11-22 21:39:59.461845: Epoch 6501 +2024-11-22 21:39:59.461954: Current learning rate: 0.00222 +2024-11-22 21:40:18.138600: train_loss -0.8111 +2024-11-22 21:40:18.138845: val_loss -0.7877 +2024-11-22 21:40:18.138924: Pseudo dice [0.8578] +2024-11-22 21:40:18.139006: Epoch time: 18.68 s +2024-11-22 21:40:19.101194: +2024-11-22 21:40:19.101401: Epoch 6502 +2024-11-22 21:40:19.101509: Current learning rate: 0.00221 +2024-11-22 21:40:36.754122: train_loss -0.8254 +2024-11-22 21:40:36.754351: val_loss -0.7589 +2024-11-22 21:40:36.754422: Pseudo dice [0.8597] +2024-11-22 21:40:36.754497: Epoch time: 17.65 s +2024-11-22 21:40:37.668731: +2024-11-22 21:40:37.668961: Epoch 6503 +2024-11-22 21:40:37.669081: Current learning rate: 0.00221 +2024-11-22 21:40:56.633181: train_loss -0.8139 +2024-11-22 21:40:56.633403: val_loss -0.7836 +2024-11-22 21:40:56.633481: Pseudo dice [0.8627] +2024-11-22 21:40:56.633556: Epoch time: 18.97 s +2024-11-22 21:40:57.541791: +2024-11-22 21:40:57.541984: Epoch 6504 +2024-11-22 21:40:57.542095: Current learning rate: 0.00221 +2024-11-22 21:41:15.533108: train_loss -0.8113 +2024-11-22 21:41:15.533359: val_loss -0.7613 +2024-11-22 21:41:15.533431: Pseudo dice [0.8427] +2024-11-22 21:41:15.533513: Epoch time: 17.99 s +2024-11-22 21:41:16.508378: +2024-11-22 21:41:16.508590: Epoch 6505 +2024-11-22 21:41:16.508694: Current learning rate: 0.00221 +2024-11-22 21:41:35.167799: train_loss -0.812 +2024-11-22 21:41:35.168043: val_loss -0.7858 +2024-11-22 21:41:35.168128: Pseudo dice [0.8699] +2024-11-22 21:41:35.168213: Epoch time: 18.66 s +2024-11-22 21:41:36.476462: +2024-11-22 21:41:36.476676: Epoch 6506 +2024-11-22 21:41:36.476786: Current learning rate: 0.00221 +2024-11-22 21:41:55.727642: train_loss -0.8156 +2024-11-22 21:41:55.727880: val_loss -0.7692 +2024-11-22 21:41:55.727959: Pseudo dice [0.8379] +2024-11-22 21:41:55.728051: Epoch time: 19.25 s +2024-11-22 21:41:56.634701: +2024-11-22 21:41:56.634911: Epoch 6507 +2024-11-22 21:41:56.635020: Current learning rate: 0.00221 +2024-11-22 21:42:15.222617: train_loss -0.813 +2024-11-22 21:42:15.222840: val_loss -0.773 +2024-11-22 21:42:15.222917: Pseudo dice [0.8512] +2024-11-22 21:42:15.223009: Epoch time: 18.59 s +2024-11-22 21:42:16.127928: +2024-11-22 21:42:16.128158: Epoch 6508 +2024-11-22 21:42:16.128266: Current learning rate: 0.00221 +2024-11-22 21:42:34.960313: train_loss -0.8021 +2024-11-22 21:42:34.960557: val_loss -0.7797 +2024-11-22 21:42:34.960639: Pseudo dice [0.845] +2024-11-22 21:42:34.960739: Epoch time: 18.83 s +2024-11-22 21:42:35.944899: +2024-11-22 21:42:35.945183: Epoch 6509 +2024-11-22 21:42:35.945299: Current learning rate: 0.0022 +2024-11-22 21:42:53.371291: train_loss -0.8053 +2024-11-22 21:42:53.371515: val_loss -0.7895 +2024-11-22 21:42:53.371588: Pseudo dice [0.8427] +2024-11-22 21:42:53.371662: Epoch time: 17.43 s +2024-11-22 21:42:54.270958: +2024-11-22 21:42:54.271179: Epoch 6510 +2024-11-22 21:42:54.271294: Current learning rate: 0.0022 +2024-11-22 21:43:13.601885: train_loss -0.806 +2024-11-22 21:43:13.602127: val_loss -0.7595 +2024-11-22 21:43:13.602202: Pseudo dice [0.8474] +2024-11-22 21:43:13.602276: Epoch time: 19.33 s +2024-11-22 21:43:14.511876: +2024-11-22 21:43:14.512097: Epoch 6511 +2024-11-22 21:43:14.512210: Current learning rate: 0.0022 +2024-11-22 21:43:33.432125: train_loss -0.8079 +2024-11-22 21:43:33.432340: val_loss -0.7848 +2024-11-22 21:43:33.432416: Pseudo dice [0.8637] +2024-11-22 21:43:33.432491: Epoch time: 18.92 s +2024-11-22 21:43:34.341675: +2024-11-22 21:43:34.341882: Epoch 6512 +2024-11-22 21:43:34.341989: Current learning rate: 0.0022 +2024-11-22 21:43:53.766427: train_loss -0.7952 +2024-11-22 21:43:53.768860: val_loss -0.7696 +2024-11-22 21:43:53.768964: Pseudo dice [0.8548] +2024-11-22 21:43:53.769053: Epoch time: 19.43 s +2024-11-22 21:43:54.683031: +2024-11-22 21:43:54.683324: Epoch 6513 +2024-11-22 21:43:54.683434: Current learning rate: 0.0022 +2024-11-22 21:44:12.461707: train_loss -0.8066 +2024-11-22 21:44:12.461925: val_loss -0.782 +2024-11-22 21:44:12.462008: Pseudo dice [0.8502] +2024-11-22 21:44:12.462084: Epoch time: 17.78 s +2024-11-22 21:44:13.362365: +2024-11-22 21:44:13.362574: Epoch 6514 +2024-11-22 21:44:13.362685: Current learning rate: 0.0022 +2024-11-22 21:44:32.206268: train_loss -0.8083 +2024-11-22 21:44:32.206489: val_loss -0.783 +2024-11-22 21:44:32.206564: Pseudo dice [0.8589] +2024-11-22 21:44:32.206641: Epoch time: 18.84 s +2024-11-22 21:44:33.112589: +2024-11-22 21:44:33.112825: Epoch 6515 +2024-11-22 21:44:33.112937: Current learning rate: 0.0022 +2024-11-22 21:44:51.920597: train_loss -0.8105 +2024-11-22 21:44:51.920810: val_loss -0.7893 +2024-11-22 21:44:51.920884: Pseudo dice [0.8523] +2024-11-22 21:44:51.920956: Epoch time: 18.81 s +2024-11-22 21:44:52.826284: +2024-11-22 21:44:52.826512: Epoch 6516 +2024-11-22 21:44:52.826620: Current learning rate: 0.0022 +2024-11-22 21:45:11.091088: train_loss -0.8088 +2024-11-22 21:45:11.091324: val_loss -0.7336 +2024-11-22 21:45:11.091399: Pseudo dice [0.8387] +2024-11-22 21:45:11.091477: Epoch time: 18.27 s +2024-11-22 21:45:11.994160: +2024-11-22 21:45:11.994370: Epoch 6517 +2024-11-22 21:45:11.994477: Current learning rate: 0.00219 +2024-11-22 21:45:30.576171: train_loss -0.8128 +2024-11-22 21:45:30.578853: val_loss -0.7745 +2024-11-22 21:45:30.578964: Pseudo dice [0.8602] +2024-11-22 21:45:30.579050: Epoch time: 18.58 s +2024-11-22 21:45:31.496698: +2024-11-22 21:45:31.496919: Epoch 6518 +2024-11-22 21:45:31.497038: Current learning rate: 0.00219 +2024-11-22 21:45:50.515440: train_loss -0.8082 +2024-11-22 21:45:50.515668: val_loss -0.7716 +2024-11-22 21:45:50.515742: Pseudo dice [0.8307] +2024-11-22 21:45:50.515828: Epoch time: 19.02 s +2024-11-22 21:45:51.416029: +2024-11-22 21:45:51.416236: Epoch 6519 +2024-11-22 21:45:51.416349: Current learning rate: 0.00219 +2024-11-22 21:46:11.060403: train_loss -0.8096 +2024-11-22 21:46:11.060650: val_loss -0.7814 +2024-11-22 21:46:11.062950: Pseudo dice [0.8454] +2024-11-22 21:46:11.063081: Epoch time: 19.65 s +2024-11-22 21:46:12.061939: +2024-11-22 21:46:12.062265: Epoch 6520 +2024-11-22 21:46:12.062376: Current learning rate: 0.00219 +2024-11-22 21:46:29.708051: train_loss -0.805 +2024-11-22 21:46:29.708270: val_loss -0.787 +2024-11-22 21:46:29.708342: Pseudo dice [0.8457] +2024-11-22 21:46:29.708418: Epoch time: 17.65 s +2024-11-22 21:46:30.617134: +2024-11-22 21:46:30.617359: Epoch 6521 +2024-11-22 21:46:30.617469: Current learning rate: 0.00219 +2024-11-22 21:46:49.196623: train_loss -0.8034 +2024-11-22 21:46:49.196843: val_loss -0.7799 +2024-11-22 21:46:49.196918: Pseudo dice [0.8483] +2024-11-22 21:46:49.197004: Epoch time: 18.58 s +2024-11-22 21:46:50.098390: +2024-11-22 21:46:50.098663: Epoch 6522 +2024-11-22 21:46:50.098773: Current learning rate: 0.00219 +2024-11-22 21:47:09.053187: train_loss -0.8076 +2024-11-22 21:47:09.053404: val_loss -0.7949 +2024-11-22 21:47:09.053564: Pseudo dice [0.8491] +2024-11-22 21:47:09.053641: Epoch time: 18.96 s +2024-11-22 21:47:09.955546: +2024-11-22 21:47:09.955755: Epoch 6523 +2024-11-22 21:47:09.955861: Current learning rate: 0.00219 +2024-11-22 21:47:29.066412: train_loss -0.8164 +2024-11-22 21:47:29.066657: val_loss -0.7873 +2024-11-22 21:47:29.066735: Pseudo dice [0.862] +2024-11-22 21:47:29.066822: Epoch time: 19.11 s +2024-11-22 21:47:29.990942: +2024-11-22 21:47:29.991224: Epoch 6524 +2024-11-22 21:47:29.991338: Current learning rate: 0.00218 +2024-11-22 21:47:48.124055: train_loss -0.8117 +2024-11-22 21:47:48.124278: val_loss -0.7929 +2024-11-22 21:47:48.124352: Pseudo dice [0.86] +2024-11-22 21:47:48.124429: Epoch time: 18.13 s +2024-11-22 21:47:49.056526: +2024-11-22 21:47:49.056764: Epoch 6525 +2024-11-22 21:47:49.056877: Current learning rate: 0.00218 +2024-11-22 21:48:07.177200: train_loss -0.8095 +2024-11-22 21:48:07.177422: val_loss -0.7834 +2024-11-22 21:48:07.177493: Pseudo dice [0.8417] +2024-11-22 21:48:07.177569: Epoch time: 18.12 s +2024-11-22 21:48:08.084651: +2024-11-22 21:48:08.084852: Epoch 6526 +2024-11-22 21:48:08.084959: Current learning rate: 0.00218 +2024-11-22 21:48:26.182470: train_loss -0.8155 +2024-11-22 21:48:26.182711: val_loss -0.7851 +2024-11-22 21:48:26.182789: Pseudo dice [0.8543] +2024-11-22 21:48:26.182864: Epoch time: 18.1 s +2024-11-22 21:48:27.083844: +2024-11-22 21:48:27.084079: Epoch 6527 +2024-11-22 21:48:27.084188: Current learning rate: 0.00218 +2024-11-22 21:48:45.524119: train_loss -0.8101 +2024-11-22 21:48:45.524369: val_loss -0.7714 +2024-11-22 21:48:45.524470: Pseudo dice [0.8528] +2024-11-22 21:48:45.524553: Epoch time: 18.44 s +2024-11-22 21:48:46.431536: +2024-11-22 21:48:46.431741: Epoch 6528 +2024-11-22 21:48:46.431850: Current learning rate: 0.00218 +2024-11-22 21:49:05.173137: train_loss -0.8126 +2024-11-22 21:49:05.173343: val_loss -0.7638 +2024-11-22 21:49:05.173416: Pseudo dice [0.8496] +2024-11-22 21:49:05.173489: Epoch time: 18.74 s +2024-11-22 21:49:06.393623: +2024-11-22 21:49:06.393837: Epoch 6529 +2024-11-22 21:49:06.393955: Current learning rate: 0.00218 +2024-11-22 21:49:25.304668: train_loss -0.8129 +2024-11-22 21:49:25.304893: val_loss -0.7741 +2024-11-22 21:49:25.304968: Pseudo dice [0.8365] +2024-11-22 21:49:25.305050: Epoch time: 18.91 s +2024-11-22 21:49:26.211186: +2024-11-22 21:49:26.211429: Epoch 6530 +2024-11-22 21:49:26.211545: Current learning rate: 0.00218 +2024-11-22 21:49:43.979715: train_loss -0.814 +2024-11-22 21:49:43.979932: val_loss -0.7913 +2024-11-22 21:49:43.980010: Pseudo dice [0.8527] +2024-11-22 21:49:43.980084: Epoch time: 17.77 s +2024-11-22 21:49:44.891510: +2024-11-22 21:49:44.891814: Epoch 6531 +2024-11-22 21:49:44.891926: Current learning rate: 0.00218 +2024-11-22 21:50:03.708661: train_loss -0.8125 +2024-11-22 21:50:03.708905: val_loss -0.7805 +2024-11-22 21:50:03.708984: Pseudo dice [0.8451] +2024-11-22 21:50:03.709139: Epoch time: 18.82 s +2024-11-22 21:50:04.624775: +2024-11-22 21:50:04.625077: Epoch 6532 +2024-11-22 21:50:04.625187: Current learning rate: 0.00217 +2024-11-22 21:50:23.275958: train_loss -0.8054 +2024-11-22 21:50:23.276179: val_loss -0.7742 +2024-11-22 21:50:23.276256: Pseudo dice [0.8336] +2024-11-22 21:50:23.276331: Epoch time: 18.65 s +2024-11-22 21:50:24.180611: +2024-11-22 21:50:24.180853: Epoch 6533 +2024-11-22 21:50:24.180974: Current learning rate: 0.00217 +2024-11-22 21:50:41.560055: train_loss -0.8111 +2024-11-22 21:50:41.560277: val_loss -0.7735 +2024-11-22 21:50:41.560353: Pseudo dice [0.8532] +2024-11-22 21:50:41.560430: Epoch time: 17.38 s +2024-11-22 21:50:42.464350: +2024-11-22 21:50:42.464698: Epoch 6534 +2024-11-22 21:50:42.464805: Current learning rate: 0.00217 +2024-11-22 21:51:00.323794: train_loss -0.8118 +2024-11-22 21:51:00.324019: val_loss -0.7927 +2024-11-22 21:51:00.324098: Pseudo dice [0.8611] +2024-11-22 21:51:00.324177: Epoch time: 17.86 s +2024-11-22 21:51:01.236559: +2024-11-22 21:51:01.236781: Epoch 6535 +2024-11-22 21:51:01.236900: Current learning rate: 0.00217 +2024-11-22 21:51:18.833129: train_loss -0.8141 +2024-11-22 21:51:18.833396: val_loss -0.7983 +2024-11-22 21:51:18.833473: Pseudo dice [0.8688] +2024-11-22 21:51:18.833603: Epoch time: 17.6 s +2024-11-22 21:51:19.740535: +2024-11-22 21:51:19.740726: Epoch 6536 +2024-11-22 21:51:19.740834: Current learning rate: 0.00217 +2024-11-22 21:51:39.279126: train_loss -0.8131 +2024-11-22 21:51:39.279376: val_loss -0.7946 +2024-11-22 21:51:39.279483: Pseudo dice [0.8567] +2024-11-22 21:51:39.279559: Epoch time: 19.54 s +2024-11-22 21:51:40.184947: +2024-11-22 21:51:40.185169: Epoch 6537 +2024-11-22 21:51:40.185280: Current learning rate: 0.00217 +2024-11-22 21:51:59.382580: train_loss -0.7999 +2024-11-22 21:51:59.382806: val_loss -0.7837 +2024-11-22 21:51:59.382912: Pseudo dice [0.8484] +2024-11-22 21:51:59.382996: Epoch time: 19.2 s +2024-11-22 21:52:00.302905: +2024-11-22 21:52:00.303120: Epoch 6538 +2024-11-22 21:52:00.303232: Current learning rate: 0.00217 +2024-11-22 21:52:18.440431: train_loss -0.7985 +2024-11-22 21:52:18.440654: val_loss -0.762 +2024-11-22 21:52:18.440728: Pseudo dice [0.8555] +2024-11-22 21:52:18.440803: Epoch time: 18.14 s +2024-11-22 21:52:19.353682: +2024-11-22 21:52:19.353905: Epoch 6539 +2024-11-22 21:52:19.354017: Current learning rate: 0.00216 +2024-11-22 21:52:38.236203: train_loss -0.7991 +2024-11-22 21:52:38.236451: val_loss -0.7799 +2024-11-22 21:52:38.236528: Pseudo dice [0.8506] +2024-11-22 21:52:38.236607: Epoch time: 18.88 s +2024-11-22 21:52:39.128388: +2024-11-22 21:52:39.128599: Epoch 6540 +2024-11-22 21:52:39.128709: Current learning rate: 0.00216 +2024-11-22 21:52:57.092875: train_loss -0.795 +2024-11-22 21:52:57.093465: val_loss -0.769 +2024-11-22 21:52:57.093564: Pseudo dice [0.8453] +2024-11-22 21:52:57.093722: Epoch time: 17.97 s +2024-11-22 21:52:57.995842: +2024-11-22 21:52:57.996088: Epoch 6541 +2024-11-22 21:52:57.996200: Current learning rate: 0.00216 +2024-11-22 21:53:15.433203: train_loss -0.7984 +2024-11-22 21:53:15.433448: val_loss -0.7779 +2024-11-22 21:53:15.433533: Pseudo dice [0.8492] +2024-11-22 21:53:15.433612: Epoch time: 17.44 s +2024-11-22 21:53:16.333927: +2024-11-22 21:53:16.334159: Epoch 6542 +2024-11-22 21:53:16.334272: Current learning rate: 0.00216 +2024-11-22 21:53:34.488749: train_loss -0.8035 +2024-11-22 21:53:34.489001: val_loss -0.7773 +2024-11-22 21:53:34.489077: Pseudo dice [0.8568] +2024-11-22 21:53:34.489157: Epoch time: 18.16 s +2024-11-22 21:53:35.383791: +2024-11-22 21:53:35.384023: Epoch 6543 +2024-11-22 21:53:35.384134: Current learning rate: 0.00216 +2024-11-22 21:53:53.494150: train_loss -0.8051 +2024-11-22 21:53:53.494373: val_loss -0.7638 +2024-11-22 21:53:53.494446: Pseudo dice [0.8436] +2024-11-22 21:53:53.494519: Epoch time: 18.11 s +2024-11-22 21:53:54.569768: +2024-11-22 21:53:54.569988: Epoch 6544 +2024-11-22 21:53:54.570101: Current learning rate: 0.00216 +2024-11-22 21:54:12.629868: train_loss -0.797 +2024-11-22 21:54:12.630095: val_loss -0.7682 +2024-11-22 21:54:12.630175: Pseudo dice [0.8494] +2024-11-22 21:54:12.630254: Epoch time: 18.06 s +2024-11-22 21:54:13.531929: +2024-11-22 21:54:13.532269: Epoch 6545 +2024-11-22 21:54:13.532380: Current learning rate: 0.00216 +2024-11-22 21:54:31.888454: train_loss -0.8118 +2024-11-22 21:54:31.888709: val_loss -0.7659 +2024-11-22 21:54:31.888790: Pseudo dice [0.8515] +2024-11-22 21:54:31.888868: Epoch time: 18.36 s +2024-11-22 21:54:32.896442: +2024-11-22 21:54:32.896661: Epoch 6546 +2024-11-22 21:54:32.896819: Current learning rate: 0.00216 +2024-11-22 21:54:52.047349: train_loss -0.8129 +2024-11-22 21:54:52.047593: val_loss -0.7871 +2024-11-22 21:54:52.047670: Pseudo dice [0.8639] +2024-11-22 21:54:52.047752: Epoch time: 19.15 s +2024-11-22 21:54:52.956890: +2024-11-22 21:54:52.957112: Epoch 6547 +2024-11-22 21:54:52.957223: Current learning rate: 0.00215 +2024-11-22 21:55:11.622768: train_loss -0.8034 +2024-11-22 21:55:11.622980: val_loss -0.783 +2024-11-22 21:55:11.623060: Pseudo dice [0.862] +2024-11-22 21:55:11.623135: Epoch time: 18.67 s +2024-11-22 21:55:12.523621: +2024-11-22 21:55:12.523883: Epoch 6548 +2024-11-22 21:55:12.524000: Current learning rate: 0.00215 +2024-11-22 21:55:31.789091: train_loss -0.8044 +2024-11-22 21:55:31.789316: val_loss -0.7377 +2024-11-22 21:55:31.789391: Pseudo dice [0.8265] +2024-11-22 21:55:31.789466: Epoch time: 19.27 s +2024-11-22 21:55:32.808458: +2024-11-22 21:55:32.808679: Epoch 6549 +2024-11-22 21:55:32.808793: Current learning rate: 0.00215 +2024-11-22 21:55:51.492386: train_loss -0.8075 +2024-11-22 21:55:51.492593: val_loss -0.7802 +2024-11-22 21:55:51.492667: Pseudo dice [0.8527] +2024-11-22 21:55:51.492760: Epoch time: 18.68 s +2024-11-22 21:55:52.741606: +2024-11-22 21:55:52.741834: Epoch 6550 +2024-11-22 21:55:52.741944: Current learning rate: 0.00215 +2024-11-22 21:56:09.629248: train_loss -0.8066 +2024-11-22 21:56:09.629495: val_loss -0.7633 +2024-11-22 21:56:09.629575: Pseudo dice [0.8441] +2024-11-22 21:56:09.629655: Epoch time: 16.89 s +2024-11-22 21:56:10.538996: +2024-11-22 21:56:10.539195: Epoch 6551 +2024-11-22 21:56:10.539306: Current learning rate: 0.00215 +2024-11-22 21:56:29.606167: train_loss -0.8109 +2024-11-22 21:56:29.606393: val_loss -0.7907 +2024-11-22 21:56:29.606486: Pseudo dice [0.8507] +2024-11-22 21:56:29.606562: Epoch time: 19.07 s +2024-11-22 21:56:30.513063: +2024-11-22 21:56:30.513286: Epoch 6552 +2024-11-22 21:56:30.513394: Current learning rate: 0.00215 +2024-11-22 21:56:48.812715: train_loss -0.8086 +2024-11-22 21:56:48.813445: val_loss -0.7918 +2024-11-22 21:56:48.813522: Pseudo dice [0.8564] +2024-11-22 21:56:48.813597: Epoch time: 18.3 s +2024-11-22 21:56:49.716265: +2024-11-22 21:56:49.716490: Epoch 6553 +2024-11-22 21:56:49.716610: Current learning rate: 0.00215 +2024-11-22 21:57:07.705283: train_loss -0.8106 +2024-11-22 21:57:07.705545: val_loss -0.7817 +2024-11-22 21:57:07.705621: Pseudo dice [0.8457] +2024-11-22 21:57:07.705705: Epoch time: 17.99 s +2024-11-22 21:57:08.616248: +2024-11-22 21:57:08.616458: Epoch 6554 +2024-11-22 21:57:08.616575: Current learning rate: 0.00214 +2024-11-22 21:57:28.121228: train_loss -0.8085 +2024-11-22 21:57:28.121465: val_loss -0.7772 +2024-11-22 21:57:28.121542: Pseudo dice [0.848] +2024-11-22 21:57:28.121669: Epoch time: 19.51 s +2024-11-22 21:57:29.025783: +2024-11-22 21:57:29.026012: Epoch 6555 +2024-11-22 21:57:29.026128: Current learning rate: 0.00214 +2024-11-22 21:57:47.214311: train_loss -0.806 +2024-11-22 21:57:47.214536: val_loss -0.8034 +2024-11-22 21:57:47.214622: Pseudo dice [0.8525] +2024-11-22 21:57:47.214700: Epoch time: 18.19 s +2024-11-22 21:57:48.107758: +2024-11-22 21:57:48.108035: Epoch 6556 +2024-11-22 21:57:48.108147: Current learning rate: 0.00214 +2024-11-22 21:58:06.458515: train_loss -0.8181 +2024-11-22 21:58:06.458743: val_loss -0.7798 +2024-11-22 21:58:06.458862: Pseudo dice [0.8386] +2024-11-22 21:58:06.458938: Epoch time: 18.35 s +2024-11-22 21:58:07.352847: +2024-11-22 21:58:07.353045: Epoch 6557 +2024-11-22 21:58:07.353156: Current learning rate: 0.00214 +2024-11-22 21:58:25.401931: train_loss -0.8073 +2024-11-22 21:58:25.402158: val_loss -0.7983 +2024-11-22 21:58:25.402231: Pseudo dice [0.8655] +2024-11-22 21:58:25.402307: Epoch time: 18.05 s +2024-11-22 21:58:26.305417: +2024-11-22 21:58:26.305633: Epoch 6558 +2024-11-22 21:58:26.305752: Current learning rate: 0.00214 +2024-11-22 21:58:45.234268: train_loss -0.8102 +2024-11-22 21:58:45.234514: val_loss -0.7825 +2024-11-22 21:58:45.234591: Pseudo dice [0.8545] +2024-11-22 21:58:45.234681: Epoch time: 18.93 s +2024-11-22 21:58:46.129543: +2024-11-22 21:58:46.129754: Epoch 6559 +2024-11-22 21:58:46.129863: Current learning rate: 0.00214 +2024-11-22 21:59:05.089148: train_loss -0.813 +2024-11-22 21:59:05.091531: val_loss -0.7966 +2024-11-22 21:59:05.091656: Pseudo dice [0.8432] +2024-11-22 21:59:05.091731: Epoch time: 18.96 s +2024-11-22 21:59:06.025352: +2024-11-22 21:59:06.025569: Epoch 6560 +2024-11-22 21:59:06.025679: Current learning rate: 0.00214 +2024-11-22 21:59:25.201029: train_loss -0.8141 +2024-11-22 21:59:25.201295: val_loss -0.7493 +2024-11-22 21:59:25.201380: Pseudo dice [0.8327] +2024-11-22 21:59:25.201457: Epoch time: 19.17 s +2024-11-22 21:59:26.109179: +2024-11-22 21:59:26.109449: Epoch 6561 +2024-11-22 21:59:26.109560: Current learning rate: 0.00214 +2024-11-22 21:59:44.291262: train_loss -0.8128 +2024-11-22 21:59:44.291483: val_loss -0.7872 +2024-11-22 21:59:44.291555: Pseudo dice [0.8551] +2024-11-22 21:59:44.291633: Epoch time: 18.18 s +2024-11-22 21:59:45.208077: +2024-11-22 21:59:45.208302: Epoch 6562 +2024-11-22 21:59:45.208454: Current learning rate: 0.00213 +2024-11-22 22:00:04.128399: train_loss -0.8094 +2024-11-22 22:00:04.128620: val_loss -0.7725 +2024-11-22 22:00:04.128695: Pseudo dice [0.8646] +2024-11-22 22:00:04.128774: Epoch time: 18.92 s +2024-11-22 22:00:05.437967: +2024-11-22 22:00:05.438467: Epoch 6563 +2024-11-22 22:00:05.438595: Current learning rate: 0.00213 +2024-11-22 22:00:24.091873: train_loss -0.8063 +2024-11-22 22:00:24.092119: val_loss -0.7916 +2024-11-22 22:00:24.092197: Pseudo dice [0.8586] +2024-11-22 22:00:24.092275: Epoch time: 18.65 s +2024-11-22 22:00:25.038906: +2024-11-22 22:00:25.039136: Epoch 6564 +2024-11-22 22:00:25.039243: Current learning rate: 0.00213 +2024-11-22 22:00:43.748193: train_loss -0.807 +2024-11-22 22:00:43.748412: val_loss -0.7683 +2024-11-22 22:00:43.748487: Pseudo dice [0.8445] +2024-11-22 22:00:43.748561: Epoch time: 18.71 s +2024-11-22 22:00:44.650905: +2024-11-22 22:00:44.651209: Epoch 6565 +2024-11-22 22:00:44.651322: Current learning rate: 0.00213 +2024-11-22 22:01:02.870531: train_loss -0.8136 +2024-11-22 22:01:02.870783: val_loss -0.7716 +2024-11-22 22:01:02.870858: Pseudo dice [0.8648] +2024-11-22 22:01:02.870937: Epoch time: 18.22 s +2024-11-22 22:01:03.774168: +2024-11-22 22:01:03.774446: Epoch 6566 +2024-11-22 22:01:03.774557: Current learning rate: 0.00213 +2024-11-22 22:01:21.631818: train_loss -0.8147 +2024-11-22 22:01:21.632104: val_loss -0.7742 +2024-11-22 22:01:21.632180: Pseudo dice [0.857] +2024-11-22 22:01:21.632437: Epoch time: 17.86 s +2024-11-22 22:01:22.536580: +2024-11-22 22:01:22.536815: Epoch 6567 +2024-11-22 22:01:22.536927: Current learning rate: 0.00213 +2024-11-22 22:01:40.228185: train_loss -0.8138 +2024-11-22 22:01:40.228419: val_loss -0.7804 +2024-11-22 22:01:40.228493: Pseudo dice [0.8466] +2024-11-22 22:01:40.228570: Epoch time: 17.69 s +2024-11-22 22:01:41.131837: +2024-11-22 22:01:41.132057: Epoch 6568 +2024-11-22 22:01:41.132171: Current learning rate: 0.00213 +2024-11-22 22:02:00.736307: train_loss -0.8076 +2024-11-22 22:02:00.736532: val_loss -0.7925 +2024-11-22 22:02:00.736611: Pseudo dice [0.858] +2024-11-22 22:02:00.736771: Epoch time: 19.61 s +2024-11-22 22:02:01.641629: +2024-11-22 22:02:01.641832: Epoch 6569 +2024-11-22 22:02:01.641941: Current learning rate: 0.00212 +2024-11-22 22:02:20.184748: train_loss -0.8165 +2024-11-22 22:02:20.184986: val_loss -0.7702 +2024-11-22 22:02:20.185083: Pseudo dice [0.8425] +2024-11-22 22:02:20.185159: Epoch time: 18.54 s +2024-11-22 22:02:21.147976: +2024-11-22 22:02:21.148187: Epoch 6570 +2024-11-22 22:02:21.148294: Current learning rate: 0.00212 +2024-11-22 22:02:39.751154: train_loss -0.8147 +2024-11-22 22:02:39.751377: val_loss -0.771 +2024-11-22 22:02:39.751451: Pseudo dice [0.8515] +2024-11-22 22:02:39.751527: Epoch time: 18.6 s +2024-11-22 22:02:40.665243: +2024-11-22 22:02:40.665441: Epoch 6571 +2024-11-22 22:02:40.665549: Current learning rate: 0.00212 +2024-11-22 22:02:59.140091: train_loss -0.8037 +2024-11-22 22:02:59.140315: val_loss -0.7848 +2024-11-22 22:02:59.140391: Pseudo dice [0.862] +2024-11-22 22:02:59.140467: Epoch time: 18.48 s +2024-11-22 22:03:00.047376: +2024-11-22 22:03:00.047597: Epoch 6572 +2024-11-22 22:03:00.047712: Current learning rate: 0.00212 +2024-11-22 22:03:18.112849: train_loss -0.8162 +2024-11-22 22:03:18.113069: val_loss -0.7832 +2024-11-22 22:03:18.113152: Pseudo dice [0.8504] +2024-11-22 22:03:18.113228: Epoch time: 18.07 s +2024-11-22 22:03:19.008984: +2024-11-22 22:03:19.009200: Epoch 6573 +2024-11-22 22:03:19.009316: Current learning rate: 0.00212 +2024-11-22 22:03:38.242177: train_loss -0.8071 +2024-11-22 22:03:38.242426: val_loss -0.7786 +2024-11-22 22:03:38.242501: Pseudo dice [0.8499] +2024-11-22 22:03:38.242578: Epoch time: 19.23 s +2024-11-22 22:03:39.522854: +2024-11-22 22:03:39.523058: Epoch 6574 +2024-11-22 22:03:39.523165: Current learning rate: 0.00212 +2024-11-22 22:03:57.476114: train_loss -0.8055 +2024-11-22 22:03:57.476335: val_loss -0.7806 +2024-11-22 22:03:57.476413: Pseudo dice [0.8537] +2024-11-22 22:03:57.476486: Epoch time: 17.95 s +2024-11-22 22:03:58.375676: +2024-11-22 22:03:58.375912: Epoch 6575 +2024-11-22 22:03:58.376023: Current learning rate: 0.00212 +2024-11-22 22:04:16.452799: train_loss -0.8121 +2024-11-22 22:04:16.453039: val_loss -0.779 +2024-11-22 22:04:16.453118: Pseudo dice [0.856] +2024-11-22 22:04:16.453198: Epoch time: 18.08 s +2024-11-22 22:04:17.358239: +2024-11-22 22:04:17.358439: Epoch 6576 +2024-11-22 22:04:17.358546: Current learning rate: 0.00212 +2024-11-22 22:04:36.353684: train_loss -0.8174 +2024-11-22 22:04:36.353914: val_loss -0.7774 +2024-11-22 22:04:36.354001: Pseudo dice [0.8613] +2024-11-22 22:04:36.354080: Epoch time: 19.0 s +2024-11-22 22:04:37.282503: +2024-11-22 22:04:37.282757: Epoch 6577 +2024-11-22 22:04:37.282888: Current learning rate: 0.00211 +2024-11-22 22:04:55.365777: train_loss -0.8164 +2024-11-22 22:04:55.365996: val_loss -0.7955 +2024-11-22 22:04:55.366075: Pseudo dice [0.8497] +2024-11-22 22:04:55.366150: Epoch time: 18.08 s +2024-11-22 22:04:56.265826: +2024-11-22 22:04:56.266049: Epoch 6578 +2024-11-22 22:04:56.266160: Current learning rate: 0.00211 +2024-11-22 22:05:14.562049: train_loss -0.802 +2024-11-22 22:05:14.562278: val_loss -0.7859 +2024-11-22 22:05:14.562356: Pseudo dice [0.8666] +2024-11-22 22:05:14.562437: Epoch time: 18.3 s +2024-11-22 22:05:15.460663: +2024-11-22 22:05:15.460893: Epoch 6579 +2024-11-22 22:05:15.461010: Current learning rate: 0.00211 +2024-11-22 22:05:33.833216: train_loss -0.8131 +2024-11-22 22:05:33.833447: val_loss -0.7672 +2024-11-22 22:05:33.833566: Pseudo dice [0.8553] +2024-11-22 22:05:33.833640: Epoch time: 18.37 s +2024-11-22 22:05:34.742705: +2024-11-22 22:05:34.742939: Epoch 6580 +2024-11-22 22:05:34.743075: Current learning rate: 0.00211 +2024-11-22 22:05:53.353579: train_loss -0.811 +2024-11-22 22:05:53.353840: val_loss -0.7988 +2024-11-22 22:05:53.353921: Pseudo dice [0.8507] +2024-11-22 22:05:53.354018: Epoch time: 18.61 s +2024-11-22 22:05:54.256104: +2024-11-22 22:05:54.256330: Epoch 6581 +2024-11-22 22:05:54.256446: Current learning rate: 0.00211 +2024-11-22 22:06:12.014277: train_loss -0.8074 +2024-11-22 22:06:12.014487: val_loss -0.7707 +2024-11-22 22:06:12.014559: Pseudo dice [0.8447] +2024-11-22 22:06:12.014630: Epoch time: 17.76 s +2024-11-22 22:06:12.918507: +2024-11-22 22:06:12.918725: Epoch 6582 +2024-11-22 22:06:12.918836: Current learning rate: 0.00211 +2024-11-22 22:06:30.884365: train_loss -0.8103 +2024-11-22 22:06:30.884628: val_loss -0.7909 +2024-11-22 22:06:30.884703: Pseudo dice [0.8571] +2024-11-22 22:06:30.884778: Epoch time: 17.97 s +2024-11-22 22:06:31.787790: +2024-11-22 22:06:31.788008: Epoch 6583 +2024-11-22 22:06:31.788117: Current learning rate: 0.00211 +2024-11-22 22:06:50.812350: train_loss -0.8082 +2024-11-22 22:06:50.812567: val_loss -0.7794 +2024-11-22 22:06:50.812640: Pseudo dice [0.8587] +2024-11-22 22:06:50.812737: Epoch time: 19.03 s +2024-11-22 22:06:51.719973: +2024-11-22 22:06:51.720335: Epoch 6584 +2024-11-22 22:06:51.720451: Current learning rate: 0.0021 +2024-11-22 22:07:10.259868: train_loss -0.8172 +2024-11-22 22:07:10.260118: val_loss -0.7752 +2024-11-22 22:07:10.260195: Pseudo dice [0.8595] +2024-11-22 22:07:10.260284: Epoch time: 18.54 s +2024-11-22 22:07:11.162753: +2024-11-22 22:07:11.162966: Epoch 6585 +2024-11-22 22:07:11.163087: Current learning rate: 0.0021 +2024-11-22 22:07:29.412330: train_loss -0.8113 +2024-11-22 22:07:29.412555: val_loss -0.7918 +2024-11-22 22:07:29.412629: Pseudo dice [0.8561] +2024-11-22 22:07:29.412703: Epoch time: 18.25 s +2024-11-22 22:07:30.723376: +2024-11-22 22:07:30.723620: Epoch 6586 +2024-11-22 22:07:30.723737: Current learning rate: 0.0021 +2024-11-22 22:07:48.833033: train_loss -0.8163 +2024-11-22 22:07:48.835459: val_loss -0.7791 +2024-11-22 22:07:48.835564: Pseudo dice [0.854] +2024-11-22 22:07:48.835639: Epoch time: 18.11 s +2024-11-22 22:07:49.869259: +2024-11-22 22:07:49.869485: Epoch 6587 +2024-11-22 22:07:49.869601: Current learning rate: 0.0021 +2024-11-22 22:08:08.861547: train_loss -0.8148 +2024-11-22 22:08:08.861791: val_loss -0.7625 +2024-11-22 22:08:08.861903: Pseudo dice [0.8535] +2024-11-22 22:08:08.861988: Epoch time: 18.99 s +2024-11-22 22:08:09.781887: +2024-11-22 22:08:09.782109: Epoch 6588 +2024-11-22 22:08:09.782218: Current learning rate: 0.0021 +2024-11-22 22:08:28.846673: train_loss -0.8162 +2024-11-22 22:08:28.846901: val_loss -0.7751 +2024-11-22 22:08:28.846975: Pseudo dice [0.8502] +2024-11-22 22:08:28.847060: Epoch time: 19.07 s +2024-11-22 22:08:29.762454: +2024-11-22 22:08:29.762684: Epoch 6589 +2024-11-22 22:08:29.762799: Current learning rate: 0.0021 +2024-11-22 22:08:49.076196: train_loss -0.8125 +2024-11-22 22:08:49.076410: val_loss -0.801 +2024-11-22 22:08:49.076484: Pseudo dice [0.8579] +2024-11-22 22:08:49.076561: Epoch time: 19.31 s +2024-11-22 22:08:49.987499: +2024-11-22 22:08:49.987788: Epoch 6590 +2024-11-22 22:08:49.987895: Current learning rate: 0.0021 +2024-11-22 22:09:08.455049: train_loss -0.8122 +2024-11-22 22:09:08.455271: val_loss -0.7846 +2024-11-22 22:09:08.455347: Pseudo dice [0.8366] +2024-11-22 22:09:08.455426: Epoch time: 18.47 s +2024-11-22 22:09:09.381329: +2024-11-22 22:09:09.381605: Epoch 6591 +2024-11-22 22:09:09.381727: Current learning rate: 0.0021 +2024-11-22 22:09:27.378415: train_loss -0.8113 +2024-11-22 22:09:27.378672: val_loss -0.7609 +2024-11-22 22:09:27.378746: Pseudo dice [0.8436] +2024-11-22 22:09:27.378826: Epoch time: 18.0 s +2024-11-22 22:09:28.280914: +2024-11-22 22:09:28.281121: Epoch 6592 +2024-11-22 22:09:28.281230: Current learning rate: 0.00209 +2024-11-22 22:09:46.923228: train_loss -0.8078 +2024-11-22 22:09:46.923524: val_loss -0.7805 +2024-11-22 22:09:46.924069: Pseudo dice [0.8543] +2024-11-22 22:09:46.924165: Epoch time: 18.64 s +2024-11-22 22:09:47.834413: +2024-11-22 22:09:47.834632: Epoch 6593 +2024-11-22 22:09:47.834743: Current learning rate: 0.00209 +2024-11-22 22:10:06.900086: train_loss -0.8135 +2024-11-22 22:10:06.902423: val_loss -0.7584 +2024-11-22 22:10:06.902672: Pseudo dice [0.8244] +2024-11-22 22:10:06.902755: Epoch time: 19.07 s +2024-11-22 22:10:07.877877: +2024-11-22 22:10:07.878117: Epoch 6594 +2024-11-22 22:10:07.878236: Current learning rate: 0.00209 +2024-11-22 22:10:26.320582: train_loss -0.8149 +2024-11-22 22:10:26.320802: val_loss -0.7735 +2024-11-22 22:10:26.320875: Pseudo dice [0.8528] +2024-11-22 22:10:26.320949: Epoch time: 18.44 s +2024-11-22 22:10:27.224705: +2024-11-22 22:10:27.224923: Epoch 6595 +2024-11-22 22:10:27.225040: Current learning rate: 0.00209 +2024-11-22 22:10:46.389694: train_loss -0.8176 +2024-11-22 22:10:46.389937: val_loss -0.772 +2024-11-22 22:10:46.390020: Pseudo dice [0.8563] +2024-11-22 22:10:46.390100: Epoch time: 19.17 s +2024-11-22 22:10:47.338587: +2024-11-22 22:10:47.338800: Epoch 6596 +2024-11-22 22:10:47.338908: Current learning rate: 0.00209 +2024-11-22 22:11:07.280074: train_loss -0.8151 +2024-11-22 22:11:07.280305: val_loss -0.7652 +2024-11-22 22:11:07.280382: Pseudo dice [0.8487] +2024-11-22 22:11:07.280456: Epoch time: 19.94 s +2024-11-22 22:11:08.542820: +2024-11-22 22:11:08.543052: Epoch 6597 +2024-11-22 22:11:08.543165: Current learning rate: 0.00209 +2024-11-22 22:11:27.217901: train_loss -0.8084 +2024-11-22 22:11:27.218152: val_loss -0.7964 +2024-11-22 22:11:27.218228: Pseudo dice [0.86] +2024-11-22 22:11:27.218313: Epoch time: 18.68 s +2024-11-22 22:11:28.119380: +2024-11-22 22:11:28.119606: Epoch 6598 +2024-11-22 22:11:28.119714: Current learning rate: 0.00209 +2024-11-22 22:11:47.051212: train_loss -0.8021 +2024-11-22 22:11:47.051425: val_loss -0.7831 +2024-11-22 22:11:47.051500: Pseudo dice [0.8481] +2024-11-22 22:11:47.051575: Epoch time: 18.93 s +2024-11-22 22:11:47.979091: +2024-11-22 22:11:47.979379: Epoch 6599 +2024-11-22 22:11:47.979540: Current learning rate: 0.00208 +2024-11-22 22:12:06.707057: train_loss -0.81 +2024-11-22 22:12:06.707391: val_loss -0.7637 +2024-11-22 22:12:06.707475: Pseudo dice [0.8393] +2024-11-22 22:12:06.707552: Epoch time: 18.73 s +2024-11-22 22:12:07.946103: +2024-11-22 22:12:07.946326: Epoch 6600 +2024-11-22 22:12:07.946439: Current learning rate: 0.00208 +2024-11-22 22:12:26.388980: train_loss -0.8119 +2024-11-22 22:12:26.389212: val_loss -0.7757 +2024-11-22 22:12:26.389307: Pseudo dice [0.8573] +2024-11-22 22:12:26.389384: Epoch time: 18.44 s +2024-11-22 22:12:27.288379: +2024-11-22 22:12:27.288603: Epoch 6601 +2024-11-22 22:12:27.288711: Current learning rate: 0.00208 +2024-11-22 22:12:46.251745: train_loss -0.8098 +2024-11-22 22:12:46.251966: val_loss -0.7841 +2024-11-22 22:12:46.252049: Pseudo dice [0.8447] +2024-11-22 22:12:46.252127: Epoch time: 18.96 s +2024-11-22 22:12:47.165414: +2024-11-22 22:12:47.165656: Epoch 6602 +2024-11-22 22:12:47.165770: Current learning rate: 0.00208 +2024-11-22 22:13:05.662640: train_loss -0.8148 +2024-11-22 22:13:05.662917: val_loss -0.7665 +2024-11-22 22:13:05.663006: Pseudo dice [0.864] +2024-11-22 22:13:05.663105: Epoch time: 18.49 s +2024-11-22 22:13:06.738810: +2024-11-22 22:13:06.739028: Epoch 6603 +2024-11-22 22:13:06.739135: Current learning rate: 0.00208 +2024-11-22 22:13:25.937562: train_loss -0.8089 +2024-11-22 22:13:25.937808: val_loss -0.7787 +2024-11-22 22:13:25.937882: Pseudo dice [0.8503] +2024-11-22 22:13:25.937959: Epoch time: 19.2 s +2024-11-22 22:13:26.837168: +2024-11-22 22:13:26.837384: Epoch 6604 +2024-11-22 22:13:26.837495: Current learning rate: 0.00208 +2024-11-22 22:13:45.776423: train_loss -0.812 +2024-11-22 22:13:45.776629: val_loss -0.7958 +2024-11-22 22:13:45.776702: Pseudo dice [0.8511] +2024-11-22 22:13:45.776777: Epoch time: 18.94 s +2024-11-22 22:13:46.716799: +2024-11-22 22:13:46.717032: Epoch 6605 +2024-11-22 22:13:46.717149: Current learning rate: 0.00208 +2024-11-22 22:14:05.028286: train_loss -0.8191 +2024-11-22 22:14:05.028523: val_loss -0.766 +2024-11-22 22:14:05.028599: Pseudo dice [0.8493] +2024-11-22 22:14:05.028676: Epoch time: 18.31 s +2024-11-22 22:14:05.939165: +2024-11-22 22:14:05.939444: Epoch 6606 +2024-11-22 22:14:05.939553: Current learning rate: 0.00208 +2024-11-22 22:14:24.069587: train_loss -0.8164 +2024-11-22 22:14:24.069806: val_loss -0.7632 +2024-11-22 22:14:24.069886: Pseudo dice [0.841] +2024-11-22 22:14:24.069964: Epoch time: 18.13 s +2024-11-22 22:14:24.974566: +2024-11-22 22:14:24.974770: Epoch 6607 +2024-11-22 22:14:24.974881: Current learning rate: 0.00207 +2024-11-22 22:14:44.146045: train_loss -0.8135 +2024-11-22 22:14:44.146303: val_loss -0.7839 +2024-11-22 22:14:44.146403: Pseudo dice [0.8426] +2024-11-22 22:14:44.146486: Epoch time: 19.17 s +2024-11-22 22:14:45.053394: +2024-11-22 22:14:45.053608: Epoch 6608 +2024-11-22 22:14:45.053715: Current learning rate: 0.00207 +2024-11-22 22:15:03.108708: train_loss -0.8131 +2024-11-22 22:15:03.111058: val_loss -0.788 +2024-11-22 22:15:03.111262: Pseudo dice [0.8587] +2024-11-22 22:15:03.111342: Epoch time: 18.06 s +2024-11-22 22:15:04.603436: +2024-11-22 22:15:04.603683: Epoch 6609 +2024-11-22 22:15:04.603794: Current learning rate: 0.00207 +2024-11-22 22:15:23.557461: train_loss -0.8119 +2024-11-22 22:15:23.557745: val_loss -0.776 +2024-11-22 22:15:23.557856: Pseudo dice [0.8577] +2024-11-22 22:15:23.557933: Epoch time: 18.95 s +2024-11-22 22:15:24.463384: +2024-11-22 22:15:24.463602: Epoch 6610 +2024-11-22 22:15:24.463709: Current learning rate: 0.00207 +2024-11-22 22:15:42.975632: train_loss -0.8158 +2024-11-22 22:15:42.975900: val_loss -0.7885 +2024-11-22 22:15:42.975985: Pseudo dice [0.8544] +2024-11-22 22:15:42.976068: Epoch time: 18.51 s +2024-11-22 22:15:43.895030: +2024-11-22 22:15:43.895233: Epoch 6611 +2024-11-22 22:15:43.895339: Current learning rate: 0.00207 +2024-11-22 22:16:02.285946: train_loss -0.8112 +2024-11-22 22:16:02.286167: val_loss -0.7707 +2024-11-22 22:16:02.286242: Pseudo dice [0.8617] +2024-11-22 22:16:02.286316: Epoch time: 18.39 s +2024-11-22 22:16:03.191579: +2024-11-22 22:16:03.191817: Epoch 6612 +2024-11-22 22:16:03.191931: Current learning rate: 0.00207 +2024-11-22 22:16:21.977394: train_loss -0.8099 +2024-11-22 22:16:21.977618: val_loss -0.7577 +2024-11-22 22:16:21.977698: Pseudo dice [0.8596] +2024-11-22 22:16:21.977782: Epoch time: 18.79 s +2024-11-22 22:16:22.878772: +2024-11-22 22:16:22.878987: Epoch 6613 +2024-11-22 22:16:22.879097: Current learning rate: 0.00207 +2024-11-22 22:16:41.864937: train_loss -0.8165 +2024-11-22 22:16:41.871049: val_loss -0.7866 +2024-11-22 22:16:41.871147: Pseudo dice [0.8594] +2024-11-22 22:16:41.871230: Epoch time: 18.99 s +2024-11-22 22:16:42.985338: +2024-11-22 22:16:42.985574: Epoch 6614 +2024-11-22 22:16:42.985716: Current learning rate: 0.00206 +2024-11-22 22:17:01.896423: train_loss -0.8126 +2024-11-22 22:17:01.896642: val_loss -0.7912 +2024-11-22 22:17:01.896716: Pseudo dice [0.8591] +2024-11-22 22:17:01.896793: Epoch time: 18.91 s +2024-11-22 22:17:02.800844: +2024-11-22 22:17:02.801048: Epoch 6615 +2024-11-22 22:17:02.801156: Current learning rate: 0.00206 +2024-11-22 22:17:22.100121: train_loss -0.8029 +2024-11-22 22:17:22.100347: val_loss -0.7755 +2024-11-22 22:17:22.100436: Pseudo dice [0.8577] +2024-11-22 22:17:22.100511: Epoch time: 19.3 s +2024-11-22 22:17:23.000452: +2024-11-22 22:17:23.000667: Epoch 6616 +2024-11-22 22:17:23.000774: Current learning rate: 0.00206 +2024-11-22 22:17:40.539850: train_loss -0.8138 +2024-11-22 22:17:40.540076: val_loss -0.7924 +2024-11-22 22:17:40.540153: Pseudo dice [0.8587] +2024-11-22 22:17:40.540232: Epoch time: 17.54 s +2024-11-22 22:17:41.444605: +2024-11-22 22:17:41.444831: Epoch 6617 +2024-11-22 22:17:41.444948: Current learning rate: 0.00206 +2024-11-22 22:17:59.944795: train_loss -0.8125 +2024-11-22 22:17:59.945718: val_loss -0.7672 +2024-11-22 22:17:59.945799: Pseudo dice [0.8629] +2024-11-22 22:17:59.945880: Epoch time: 18.5 s +2024-11-22 22:18:00.851694: +2024-11-22 22:18:00.851918: Epoch 6618 +2024-11-22 22:18:00.852033: Current learning rate: 0.00206 +2024-11-22 22:18:20.312663: train_loss -0.8145 +2024-11-22 22:18:20.312953: val_loss -0.7814 +2024-11-22 22:18:20.313197: Pseudo dice [0.8537] +2024-11-22 22:18:20.313279: Epoch time: 19.46 s +2024-11-22 22:18:21.263337: +2024-11-22 22:18:21.263590: Epoch 6619 +2024-11-22 22:18:21.263702: Current learning rate: 0.00206 +2024-11-22 22:18:39.720726: train_loss -0.8155 +2024-11-22 22:18:39.720952: val_loss -0.7663 +2024-11-22 22:18:39.721031: Pseudo dice [0.8461] +2024-11-22 22:18:39.721108: Epoch time: 18.46 s +2024-11-22 22:18:40.987611: +2024-11-22 22:18:40.987842: Epoch 6620 +2024-11-22 22:18:40.987953: Current learning rate: 0.00206 +2024-11-22 22:18:59.692037: train_loss -0.8073 +2024-11-22 22:18:59.692295: val_loss -0.7816 +2024-11-22 22:18:59.692369: Pseudo dice [0.8581] +2024-11-22 22:18:59.692447: Epoch time: 18.71 s +2024-11-22 22:19:00.605086: +2024-11-22 22:19:00.605304: Epoch 6621 +2024-11-22 22:19:00.605411: Current learning rate: 0.00206 +2024-11-22 22:19:19.249485: train_loss -0.8141 +2024-11-22 22:19:19.251925: val_loss -0.7923 +2024-11-22 22:19:19.252083: Pseudo dice [0.8568] +2024-11-22 22:19:19.252164: Epoch time: 18.65 s +2024-11-22 22:19:20.265973: +2024-11-22 22:19:20.266204: Epoch 6622 +2024-11-22 22:19:20.266311: Current learning rate: 0.00205 +2024-11-22 22:19:38.201972: train_loss -0.8103 +2024-11-22 22:19:38.203873: val_loss -0.776 +2024-11-22 22:19:38.203954: Pseudo dice [0.851] +2024-11-22 22:19:38.204033: Epoch time: 17.94 s +2024-11-22 22:19:39.106310: +2024-11-22 22:19:39.106529: Epoch 6623 +2024-11-22 22:19:39.106643: Current learning rate: 0.00205 +2024-11-22 22:19:57.864954: train_loss -0.812 +2024-11-22 22:19:57.865181: val_loss -0.8043 +2024-11-22 22:19:57.865260: Pseudo dice [0.8677] +2024-11-22 22:19:57.865336: Epoch time: 18.76 s +2024-11-22 22:19:57.865402: Yayy! New best EMA pseudo Dice: 0.856 +2024-11-22 22:19:59.106175: +2024-11-22 22:19:59.106399: Epoch 6624 +2024-11-22 22:19:59.106515: Current learning rate: 0.00205 +2024-11-22 22:20:18.508671: train_loss -0.8203 +2024-11-22 22:20:18.514119: val_loss -0.7886 +2024-11-22 22:20:18.514248: Pseudo dice [0.8623] +2024-11-22 22:20:18.514334: Epoch time: 19.4 s +2024-11-22 22:20:18.514401: Yayy! New best EMA pseudo Dice: 0.8567 +2024-11-22 22:20:19.737939: +2024-11-22 22:20:19.738168: Epoch 6625 +2024-11-22 22:20:19.738284: Current learning rate: 0.00205 +2024-11-22 22:20:37.424469: train_loss -0.8184 +2024-11-22 22:20:37.426913: val_loss -0.775 +2024-11-22 22:20:37.427031: Pseudo dice [0.8462] +2024-11-22 22:20:37.427110: Epoch time: 17.69 s +2024-11-22 22:20:38.337215: +2024-11-22 22:20:38.337453: Epoch 6626 +2024-11-22 22:20:38.337569: Current learning rate: 0.00205 +2024-11-22 22:20:56.732587: train_loss -0.816 +2024-11-22 22:20:56.732835: val_loss -0.785 +2024-11-22 22:20:56.732915: Pseudo dice [0.8544] +2024-11-22 22:20:56.732990: Epoch time: 18.4 s +2024-11-22 22:20:57.635424: +2024-11-22 22:20:57.635627: Epoch 6627 +2024-11-22 22:20:57.635742: Current learning rate: 0.00205 +2024-11-22 22:21:16.431119: train_loss -0.8127 +2024-11-22 22:21:16.431353: val_loss -0.7829 +2024-11-22 22:21:16.431431: Pseudo dice [0.856] +2024-11-22 22:21:16.431508: Epoch time: 18.8 s +2024-11-22 22:21:17.325196: +2024-11-22 22:21:17.325407: Epoch 6628 +2024-11-22 22:21:17.325522: Current learning rate: 0.00205 +2024-11-22 22:21:35.938981: train_loss -0.8139 +2024-11-22 22:21:35.939237: val_loss -0.7436 +2024-11-22 22:21:35.939320: Pseudo dice [0.8529] +2024-11-22 22:21:35.939399: Epoch time: 18.61 s +2024-11-22 22:21:36.867835: +2024-11-22 22:21:36.868057: Epoch 6629 +2024-11-22 22:21:36.868168: Current learning rate: 0.00204 +2024-11-22 22:21:55.738451: train_loss -0.815 +2024-11-22 22:21:55.740887: val_loss -0.759 +2024-11-22 22:21:55.740986: Pseudo dice [0.8378] +2024-11-22 22:21:55.741071: Epoch time: 18.87 s +2024-11-22 22:21:56.767785: +2024-11-22 22:21:56.768006: Epoch 6630 +2024-11-22 22:21:56.768112: Current learning rate: 0.00204 +2024-11-22 22:22:14.548012: train_loss -0.8121 +2024-11-22 22:22:14.548243: val_loss -0.8184 +2024-11-22 22:22:14.548326: Pseudo dice [0.8672] +2024-11-22 22:22:14.548405: Epoch time: 17.78 s +2024-11-22 22:22:15.781133: +2024-11-22 22:22:15.781377: Epoch 6631 +2024-11-22 22:22:15.781489: Current learning rate: 0.00204 +2024-11-22 22:22:34.709005: train_loss -0.8155 +2024-11-22 22:22:34.709256: val_loss -0.7907 +2024-11-22 22:22:34.709332: Pseudo dice [0.872] +2024-11-22 22:22:34.709416: Epoch time: 18.93 s +2024-11-22 22:22:35.614891: +2024-11-22 22:22:35.615112: Epoch 6632 +2024-11-22 22:22:35.615217: Current learning rate: 0.00204 +2024-11-22 22:22:54.353172: train_loss -0.8164 +2024-11-22 22:22:54.353451: val_loss -0.7822 +2024-11-22 22:22:54.353531: Pseudo dice [0.8513] +2024-11-22 22:22:54.353607: Epoch time: 18.74 s +2024-11-22 22:22:55.260591: +2024-11-22 22:22:55.260855: Epoch 6633 +2024-11-22 22:22:55.260969: Current learning rate: 0.00204 +2024-11-22 22:23:13.425303: train_loss -0.8091 +2024-11-22 22:23:13.425528: val_loss -0.7839 +2024-11-22 22:23:13.425606: Pseudo dice [0.8528] +2024-11-22 22:23:13.425682: Epoch time: 18.17 s +2024-11-22 22:23:14.331006: +2024-11-22 22:23:14.331219: Epoch 6634 +2024-11-22 22:23:14.331324: Current learning rate: 0.00204 +2024-11-22 22:23:33.539500: train_loss -0.8151 +2024-11-22 22:23:33.539716: val_loss -0.7737 +2024-11-22 22:23:33.539788: Pseudo dice [0.8535] +2024-11-22 22:23:33.539864: Epoch time: 19.21 s +2024-11-22 22:23:34.444646: +2024-11-22 22:23:34.444871: Epoch 6635 +2024-11-22 22:23:34.444993: Current learning rate: 0.00204 +2024-11-22 22:23:52.744032: train_loss -0.7907 +2024-11-22 22:23:52.744275: val_loss -0.7799 +2024-11-22 22:23:52.744345: Pseudo dice [0.8586] +2024-11-22 22:23:52.746664: Epoch time: 18.3 s +2024-11-22 22:23:53.798781: +2024-11-22 22:23:53.799026: Epoch 6636 +2024-11-22 22:23:53.799146: Current learning rate: 0.00203 +2024-11-22 22:24:12.802090: train_loss -0.8127 +2024-11-22 22:24:12.802303: val_loss -0.7898 +2024-11-22 22:24:12.802380: Pseudo dice [0.857] +2024-11-22 22:24:12.802453: Epoch time: 19.0 s +2024-11-22 22:24:13.705748: +2024-11-22 22:24:13.705966: Epoch 6637 +2024-11-22 22:24:13.706086: Current learning rate: 0.00203 +2024-11-22 22:24:32.428103: train_loss -0.8147 +2024-11-22 22:24:32.430501: val_loss -0.7751 +2024-11-22 22:24:32.430605: Pseudo dice [0.8386] +2024-11-22 22:24:32.430682: Epoch time: 18.72 s +2024-11-22 22:24:33.359519: +2024-11-22 22:24:33.359748: Epoch 6638 +2024-11-22 22:24:33.359856: Current learning rate: 0.00203 +2024-11-22 22:24:51.095166: train_loss -0.8099 +2024-11-22 22:24:51.095403: val_loss -0.793 +2024-11-22 22:24:51.095480: Pseudo dice [0.8652] +2024-11-22 22:24:51.095559: Epoch time: 17.74 s +2024-11-22 22:24:52.000400: +2024-11-22 22:24:52.000629: Epoch 6639 +2024-11-22 22:24:52.000749: Current learning rate: 0.00203 +2024-11-22 22:25:11.258162: train_loss -0.8043 +2024-11-22 22:25:11.258400: val_loss -0.7926 +2024-11-22 22:25:11.258474: Pseudo dice [0.8545] +2024-11-22 22:25:11.258553: Epoch time: 19.26 s +2024-11-22 22:25:12.165997: +2024-11-22 22:25:12.166351: Epoch 6640 +2024-11-22 22:25:12.166460: Current learning rate: 0.00203 +2024-11-22 22:25:31.123869: train_loss -0.8112 +2024-11-22 22:25:31.124110: val_loss -0.766 +2024-11-22 22:25:31.124187: Pseudo dice [0.8456] +2024-11-22 22:25:31.124259: Epoch time: 18.96 s +2024-11-22 22:25:32.023089: +2024-11-22 22:25:32.023317: Epoch 6641 +2024-11-22 22:25:32.023445: Current learning rate: 0.00203 +2024-11-22 22:25:50.110914: train_loss -0.8151 +2024-11-22 22:25:50.111141: val_loss -0.7804 +2024-11-22 22:25:50.111224: Pseudo dice [0.8685] +2024-11-22 22:25:50.111299: Epoch time: 18.09 s +2024-11-22 22:25:51.053364: +2024-11-22 22:25:51.053585: Epoch 6642 +2024-11-22 22:25:51.053702: Current learning rate: 0.00203 +2024-11-22 22:26:08.982744: train_loss -0.814 +2024-11-22 22:26:08.983009: val_loss -0.7759 +2024-11-22 22:26:08.983089: Pseudo dice [0.8497] +2024-11-22 22:26:08.983176: Epoch time: 17.93 s +2024-11-22 22:26:10.295009: +2024-11-22 22:26:10.295246: Epoch 6643 +2024-11-22 22:26:10.295356: Current learning rate: 0.00203 +2024-11-22 22:26:28.881495: train_loss -0.8086 +2024-11-22 22:26:28.881789: val_loss -0.7852 +2024-11-22 22:26:28.881872: Pseudo dice [0.8672] +2024-11-22 22:26:28.881966: Epoch time: 18.59 s +2024-11-22 22:26:29.788116: +2024-11-22 22:26:29.788356: Epoch 6644 +2024-11-22 22:26:29.788938: Current learning rate: 0.00202 +2024-11-22 22:26:47.922190: train_loss -0.8086 +2024-11-22 22:26:47.922451: val_loss -0.7769 +2024-11-22 22:26:47.922526: Pseudo dice [0.8603] +2024-11-22 22:26:47.922604: Epoch time: 18.13 s +2024-11-22 22:26:47.922665: Yayy! New best EMA pseudo Dice: 0.8567 +2024-11-22 22:26:49.152579: +2024-11-22 22:26:49.152780: Epoch 6645 +2024-11-22 22:26:49.152887: Current learning rate: 0.00202 +2024-11-22 22:27:07.393244: train_loss -0.8028 +2024-11-22 22:27:07.393471: val_loss -0.768 +2024-11-22 22:27:07.393548: Pseudo dice [0.849] +2024-11-22 22:27:07.393625: Epoch time: 18.24 s +2024-11-22 22:27:08.310760: +2024-11-22 22:27:08.311061: Epoch 6646 +2024-11-22 22:27:08.311180: Current learning rate: 0.00202 +2024-11-22 22:27:26.821811: train_loss -0.8142 +2024-11-22 22:27:26.822072: val_loss -0.7721 +2024-11-22 22:27:26.822147: Pseudo dice [0.8669] +2024-11-22 22:27:26.822229: Epoch time: 18.51 s +2024-11-22 22:27:26.822292: Yayy! New best EMA pseudo Dice: 0.857 +2024-11-22 22:27:28.053937: +2024-11-22 22:27:28.054175: Epoch 6647 +2024-11-22 22:27:28.054288: Current learning rate: 0.00202 +2024-11-22 22:27:47.094143: train_loss -0.8105 +2024-11-22 22:27:47.094360: val_loss -0.7824 +2024-11-22 22:27:47.094433: Pseudo dice [0.8517] +2024-11-22 22:27:47.094507: Epoch time: 19.04 s +2024-11-22 22:27:47.997959: +2024-11-22 22:27:47.998158: Epoch 6648 +2024-11-22 22:27:47.998265: Current learning rate: 0.00202 +2024-11-22 22:28:06.852779: train_loss -0.8127 +2024-11-22 22:28:06.853024: val_loss -0.7597 +2024-11-22 22:28:06.853102: Pseudo dice [0.8424] +2024-11-22 22:28:06.853175: Epoch time: 18.86 s +2024-11-22 22:28:07.945888: +2024-11-22 22:28:07.946117: Epoch 6649 +2024-11-22 22:28:07.946235: Current learning rate: 0.00202 +2024-11-22 22:28:26.381881: train_loss -0.8114 +2024-11-22 22:28:26.382123: val_loss -0.7796 +2024-11-22 22:28:26.382200: Pseudo dice [0.8594] +2024-11-22 22:28:26.382276: Epoch time: 18.44 s +2024-11-22 22:28:27.838940: +2024-11-22 22:28:27.839159: Epoch 6650 +2024-11-22 22:28:27.839271: Current learning rate: 0.00202 +2024-11-22 22:28:45.592380: train_loss -0.8109 +2024-11-22 22:28:45.592634: val_loss -0.7972 +2024-11-22 22:28:45.592709: Pseudo dice [0.8537] +2024-11-22 22:28:45.592793: Epoch time: 17.75 s +2024-11-22 22:28:46.680676: +2024-11-22 22:28:46.680886: Epoch 6651 +2024-11-22 22:28:46.680999: Current learning rate: 0.00201 +2024-11-22 22:29:03.951875: train_loss -0.8162 +2024-11-22 22:29:03.952148: val_loss -0.7879 +2024-11-22 22:29:03.952227: Pseudo dice [0.8609] +2024-11-22 22:29:03.952305: Epoch time: 17.27 s +2024-11-22 22:29:04.851181: +2024-11-22 22:29:04.851466: Epoch 6652 +2024-11-22 22:29:04.851586: Current learning rate: 0.00201 +2024-11-22 22:29:23.701597: train_loss -0.8167 +2024-11-22 22:29:23.701838: val_loss -0.7817 +2024-11-22 22:29:23.701916: Pseudo dice [0.8552] +2024-11-22 22:29:23.702000: Epoch time: 18.85 s +2024-11-22 22:29:24.647819: +2024-11-22 22:29:24.648059: Epoch 6653 +2024-11-22 22:29:24.648177: Current learning rate: 0.00201 +2024-11-22 22:29:43.252245: train_loss -0.8026 +2024-11-22 22:29:43.252490: val_loss -0.7916 +2024-11-22 22:29:43.252566: Pseudo dice [0.8566] +2024-11-22 22:29:43.252648: Epoch time: 18.61 s +2024-11-22 22:29:44.555075: +2024-11-22 22:29:44.555308: Epoch 6654 +2024-11-22 22:29:44.555420: Current learning rate: 0.00201 +2024-11-22 22:30:02.669965: train_loss -0.8097 +2024-11-22 22:30:02.670229: val_loss -0.7464 +2024-11-22 22:30:02.670306: Pseudo dice [0.8444] +2024-11-22 22:30:02.670383: Epoch time: 18.12 s +2024-11-22 22:30:03.633161: +2024-11-22 22:30:03.633373: Epoch 6655 +2024-11-22 22:30:03.633489: Current learning rate: 0.00201 +2024-11-22 22:30:21.741655: train_loss -0.807 +2024-11-22 22:30:21.741904: val_loss -0.8004 +2024-11-22 22:30:21.741982: Pseudo dice [0.8545] +2024-11-22 22:30:21.742070: Epoch time: 18.11 s +2024-11-22 22:30:22.640310: +2024-11-22 22:30:22.640610: Epoch 6656 +2024-11-22 22:30:22.640716: Current learning rate: 0.00201 +2024-11-22 22:30:41.320043: train_loss -0.811 +2024-11-22 22:30:41.320279: val_loss -0.7582 +2024-11-22 22:30:41.320354: Pseudo dice [0.8338] +2024-11-22 22:30:41.320432: Epoch time: 18.68 s +2024-11-22 22:30:42.226951: +2024-11-22 22:30:42.227177: Epoch 6657 +2024-11-22 22:30:42.227289: Current learning rate: 0.00201 +2024-11-22 22:30:59.848263: train_loss -0.8121 +2024-11-22 22:30:59.848580: val_loss -0.7756 +2024-11-22 22:30:59.848665: Pseudo dice [0.8404] +2024-11-22 22:30:59.848743: Epoch time: 17.62 s +2024-11-22 22:31:00.764165: +2024-11-22 22:31:00.764403: Epoch 6658 +2024-11-22 22:31:00.764512: Current learning rate: 0.00201 +2024-11-22 22:31:18.937268: train_loss -0.8175 +2024-11-22 22:31:18.937502: val_loss -0.7759 +2024-11-22 22:31:18.937578: Pseudo dice [0.8616] +2024-11-22 22:31:18.937655: Epoch time: 18.17 s +2024-11-22 22:31:19.903156: +2024-11-22 22:31:19.903356: Epoch 6659 +2024-11-22 22:31:19.903465: Current learning rate: 0.002 +2024-11-22 22:31:38.645112: train_loss -0.8127 +2024-11-22 22:31:38.645387: val_loss -0.7739 +2024-11-22 22:31:38.645469: Pseudo dice [0.8488] +2024-11-22 22:31:38.645545: Epoch time: 18.74 s +2024-11-22 22:31:39.686214: +2024-11-22 22:31:39.686569: Epoch 6660 +2024-11-22 22:31:39.686682: Current learning rate: 0.002 +2024-11-22 22:31:58.436047: train_loss -0.8138 +2024-11-22 22:31:58.438434: val_loss -0.7801 +2024-11-22 22:31:58.438571: Pseudo dice [0.8656] +2024-11-22 22:31:58.438661: Epoch time: 18.75 s +2024-11-22 22:31:59.377198: +2024-11-22 22:31:59.377414: Epoch 6661 +2024-11-22 22:31:59.377523: Current learning rate: 0.002 +2024-11-22 22:32:18.347034: train_loss -0.7992 +2024-11-22 22:32:18.347344: val_loss -0.781 +2024-11-22 22:32:18.347430: Pseudo dice [0.8473] +2024-11-22 22:32:18.347505: Epoch time: 18.97 s +2024-11-22 22:32:19.253729: +2024-11-22 22:32:19.253932: Epoch 6662 +2024-11-22 22:32:19.254047: Current learning rate: 0.002 +2024-11-22 22:32:37.603241: train_loss -0.8009 +2024-11-22 22:32:37.603459: val_loss -0.7518 +2024-11-22 22:32:37.603532: Pseudo dice [0.8547] +2024-11-22 22:32:37.603606: Epoch time: 18.35 s +2024-11-22 22:32:38.504403: +2024-11-22 22:32:38.504611: Epoch 6663 +2024-11-22 22:32:38.504721: Current learning rate: 0.002 +2024-11-22 22:32:57.205121: train_loss -0.8084 +2024-11-22 22:32:57.205351: val_loss -0.7691 +2024-11-22 22:32:57.205426: Pseudo dice [0.8401] +2024-11-22 22:32:57.205503: Epoch time: 18.7 s +2024-11-22 22:32:58.126835: +2024-11-22 22:32:58.127073: Epoch 6664 +2024-11-22 22:32:58.127184: Current learning rate: 0.002 +2024-11-22 22:33:16.620703: train_loss -0.8034 +2024-11-22 22:33:16.620946: val_loss -0.7869 +2024-11-22 22:33:16.621033: Pseudo dice [0.8549] +2024-11-22 22:33:16.621117: Epoch time: 18.49 s +2024-11-22 22:33:17.517326: +2024-11-22 22:33:17.517544: Epoch 6665 +2024-11-22 22:33:17.517653: Current learning rate: 0.002 +2024-11-22 22:33:36.792973: train_loss -0.8087 +2024-11-22 22:33:36.793225: val_loss -0.7905 +2024-11-22 22:33:36.793303: Pseudo dice [0.8429] +2024-11-22 22:33:36.793433: Epoch time: 19.28 s +2024-11-22 22:33:37.724984: +2024-11-22 22:33:37.725233: Epoch 6666 +2024-11-22 22:33:37.725383: Current learning rate: 0.00199 +2024-11-22 22:33:56.040282: train_loss -0.8037 +2024-11-22 22:33:56.040511: val_loss -0.7915 +2024-11-22 22:33:56.040586: Pseudo dice [0.8644] +2024-11-22 22:33:56.040659: Epoch time: 18.32 s +2024-11-22 22:33:56.933801: +2024-11-22 22:33:56.934022: Epoch 6667 +2024-11-22 22:33:56.934147: Current learning rate: 0.00199 +2024-11-22 22:34:14.678517: train_loss -0.8056 +2024-11-22 22:34:14.678780: val_loss -0.7585 +2024-11-22 22:34:14.678861: Pseudo dice [0.8425] +2024-11-22 22:34:14.678943: Epoch time: 17.75 s +2024-11-22 22:34:15.586740: +2024-11-22 22:34:15.586967: Epoch 6668 +2024-11-22 22:34:15.587088: Current learning rate: 0.00199 +2024-11-22 22:34:33.410920: train_loss -0.8129 +2024-11-22 22:34:33.411165: val_loss -0.7765 +2024-11-22 22:34:33.411238: Pseudo dice [0.8637] +2024-11-22 22:34:33.411311: Epoch time: 17.83 s +2024-11-22 22:34:34.320781: +2024-11-22 22:34:34.320995: Epoch 6669 +2024-11-22 22:34:34.321106: Current learning rate: 0.00199 +2024-11-22 22:34:52.216815: train_loss -0.8098 +2024-11-22 22:34:52.217065: val_loss -0.7469 +2024-11-22 22:34:52.217146: Pseudo dice [0.8385] +2024-11-22 22:34:52.217403: Epoch time: 17.9 s +2024-11-22 22:34:53.118882: +2024-11-22 22:34:53.119123: Epoch 6670 +2024-11-22 22:34:53.119239: Current learning rate: 0.00199 +2024-11-22 22:35:12.907037: train_loss -0.8147 +2024-11-22 22:35:12.907254: val_loss -0.7973 +2024-11-22 22:35:12.907330: Pseudo dice [0.8684] +2024-11-22 22:35:12.907403: Epoch time: 19.79 s +2024-11-22 22:35:13.810994: +2024-11-22 22:35:13.811261: Epoch 6671 +2024-11-22 22:35:13.811372: Current learning rate: 0.00199 +2024-11-22 22:35:32.358932: train_loss -0.8076 +2024-11-22 22:35:32.359220: val_loss -0.7473 +2024-11-22 22:35:32.359305: Pseudo dice [0.8559] +2024-11-22 22:35:32.359384: Epoch time: 18.55 s +2024-11-22 22:35:33.441901: +2024-11-22 22:35:33.442126: Epoch 6672 +2024-11-22 22:35:33.442239: Current learning rate: 0.00199 +2024-11-22 22:35:52.303831: train_loss -0.8131 +2024-11-22 22:35:52.304586: val_loss -0.7864 +2024-11-22 22:35:52.304662: Pseudo dice [0.8505] +2024-11-22 22:35:52.304737: Epoch time: 18.86 s +2024-11-22 22:35:53.211347: +2024-11-22 22:35:53.211558: Epoch 6673 +2024-11-22 22:35:53.211673: Current learning rate: 0.00199 +2024-11-22 22:36:11.006042: train_loss -0.8128 +2024-11-22 22:36:11.006279: val_loss -0.7664 +2024-11-22 22:36:11.006362: Pseudo dice [0.8518] +2024-11-22 22:36:11.006439: Epoch time: 17.8 s +2024-11-22 22:36:11.916629: +2024-11-22 22:36:11.916878: Epoch 6674 +2024-11-22 22:36:11.916989: Current learning rate: 0.00198 +2024-11-22 22:36:31.295580: train_loss -0.8119 +2024-11-22 22:36:31.295801: val_loss -0.7598 +2024-11-22 22:36:31.295874: Pseudo dice [0.8481] +2024-11-22 22:36:31.295949: Epoch time: 19.38 s +2024-11-22 22:36:32.213643: +2024-11-22 22:36:32.213857: Epoch 6675 +2024-11-22 22:36:32.213965: Current learning rate: 0.00198 +2024-11-22 22:36:50.285311: train_loss -0.8106 +2024-11-22 22:36:50.285588: val_loss -0.7664 +2024-11-22 22:36:50.285677: Pseudo dice [0.857] +2024-11-22 22:36:50.285774: Epoch time: 18.07 s +2024-11-22 22:36:51.205563: +2024-11-22 22:36:51.207707: Epoch 6676 +2024-11-22 22:36:51.207824: Current learning rate: 0.00198 +2024-11-22 22:37:09.354096: train_loss -0.8114 +2024-11-22 22:37:09.354329: val_loss -0.7668 +2024-11-22 22:37:09.354402: Pseudo dice [0.8364] +2024-11-22 22:37:09.354475: Epoch time: 18.15 s +2024-11-22 22:37:10.254214: +2024-11-22 22:37:10.254464: Epoch 6677 +2024-11-22 22:37:10.254577: Current learning rate: 0.00198 +2024-11-22 22:37:29.759974: train_loss -0.8117 +2024-11-22 22:37:29.760603: val_loss -0.786 +2024-11-22 22:37:29.760702: Pseudo dice [0.8475] +2024-11-22 22:37:29.760784: Epoch time: 19.51 s +2024-11-22 22:37:30.807451: +2024-11-22 22:37:30.807667: Epoch 6678 +2024-11-22 22:37:30.807777: Current learning rate: 0.00198 +2024-11-22 22:37:49.437134: train_loss -0.8032 +2024-11-22 22:37:49.437367: val_loss -0.7612 +2024-11-22 22:37:49.437514: Pseudo dice [0.8474] +2024-11-22 22:37:49.437594: Epoch time: 18.63 s +2024-11-22 22:37:50.351614: +2024-11-22 22:37:50.351810: Epoch 6679 +2024-11-22 22:37:50.351917: Current learning rate: 0.00198 +2024-11-22 22:38:08.135927: train_loss -0.8158 +2024-11-22 22:38:08.136198: val_loss -0.7945 +2024-11-22 22:38:08.136274: Pseudo dice [0.8602] +2024-11-22 22:38:08.136357: Epoch time: 17.79 s +2024-11-22 22:38:09.052796: +2024-11-22 22:38:09.053097: Epoch 6680 +2024-11-22 22:38:09.053217: Current learning rate: 0.00198 +2024-11-22 22:38:27.235733: train_loss -0.8044 +2024-11-22 22:38:27.236060: val_loss -0.7882 +2024-11-22 22:38:27.236137: Pseudo dice [0.8456] +2024-11-22 22:38:27.236215: Epoch time: 18.18 s +2024-11-22 22:38:28.144607: +2024-11-22 22:38:28.144819: Epoch 6681 +2024-11-22 22:38:28.144932: Current learning rate: 0.00197 +2024-11-22 22:38:47.363829: train_loss -0.8135 +2024-11-22 22:38:47.364062: val_loss -0.7609 +2024-11-22 22:38:47.364139: Pseudo dice [0.8526] +2024-11-22 22:38:47.364213: Epoch time: 19.22 s +2024-11-22 22:38:48.421173: +2024-11-22 22:38:48.421445: Epoch 6682 +2024-11-22 22:38:48.421556: Current learning rate: 0.00197 +2024-11-22 22:39:07.117922: train_loss -0.8105 +2024-11-22 22:39:07.118165: val_loss -0.8004 +2024-11-22 22:39:07.118240: Pseudo dice [0.8678] +2024-11-22 22:39:07.118318: Epoch time: 18.7 s +2024-11-22 22:39:08.167799: +2024-11-22 22:39:08.168134: Epoch 6683 +2024-11-22 22:39:08.168250: Current learning rate: 0.00197 +2024-11-22 22:39:26.582984: train_loss -0.8183 +2024-11-22 22:39:26.583239: val_loss -0.7551 +2024-11-22 22:39:26.583314: Pseudo dice [0.8515] +2024-11-22 22:39:26.583392: Epoch time: 18.42 s +2024-11-22 22:39:27.489675: +2024-11-22 22:39:27.489870: Epoch 6684 +2024-11-22 22:39:27.489974: Current learning rate: 0.00197 +2024-11-22 22:39:47.107330: train_loss -0.8152 +2024-11-22 22:39:47.107601: val_loss -0.7667 +2024-11-22 22:39:47.107677: Pseudo dice [0.8454] +2024-11-22 22:39:47.107751: Epoch time: 19.62 s +2024-11-22 22:39:48.015256: +2024-11-22 22:39:48.015447: Epoch 6685 +2024-11-22 22:39:48.015562: Current learning rate: 0.00197 +2024-11-22 22:40:06.932058: train_loss -0.813 +2024-11-22 22:40:06.937470: val_loss -0.7979 +2024-11-22 22:40:06.937584: Pseudo dice [0.8641] +2024-11-22 22:40:06.937668: Epoch time: 18.92 s +2024-11-22 22:40:07.931075: +2024-11-22 22:40:07.931274: Epoch 6686 +2024-11-22 22:40:07.931383: Current learning rate: 0.00197 +2024-11-22 22:40:26.413883: train_loss -0.8145 +2024-11-22 22:40:26.414110: val_loss -0.795 +2024-11-22 22:40:26.414190: Pseudo dice [0.8533] +2024-11-22 22:40:26.414264: Epoch time: 18.48 s +2024-11-22 22:40:27.685652: +2024-11-22 22:40:27.685884: Epoch 6687 +2024-11-22 22:40:27.686004: Current learning rate: 0.00197 +2024-11-22 22:40:45.262826: train_loss -0.8088 +2024-11-22 22:40:45.263104: val_loss -0.7707 +2024-11-22 22:40:45.263180: Pseudo dice [0.8428] +2024-11-22 22:40:45.263266: Epoch time: 17.58 s +2024-11-22 22:40:46.174408: +2024-11-22 22:40:46.174671: Epoch 6688 +2024-11-22 22:40:46.174777: Current learning rate: 0.00196 +2024-11-22 22:41:04.871441: train_loss -0.8148 +2024-11-22 22:41:04.871697: val_loss -0.7872 +2024-11-22 22:41:04.871785: Pseudo dice [0.8562] +2024-11-22 22:41:04.888030: Epoch time: 18.7 s +2024-11-22 22:41:05.827911: +2024-11-22 22:41:05.828148: Epoch 6689 +2024-11-22 22:41:05.828257: Current learning rate: 0.00196 +2024-11-22 22:41:24.615072: train_loss -0.8151 +2024-11-22 22:41:24.615316: val_loss -0.7657 +2024-11-22 22:41:24.615391: Pseudo dice [0.8614] +2024-11-22 22:41:24.615476: Epoch time: 18.79 s +2024-11-22 22:41:25.523937: +2024-11-22 22:41:25.524197: Epoch 6690 +2024-11-22 22:41:25.524311: Current learning rate: 0.00196 +2024-11-22 22:41:45.301152: train_loss -0.8084 +2024-11-22 22:41:45.301380: val_loss -0.78 +2024-11-22 22:41:45.301455: Pseudo dice [0.8544] +2024-11-22 22:41:45.301530: Epoch time: 19.78 s +2024-11-22 22:41:46.226976: +2024-11-22 22:41:46.227216: Epoch 6691 +2024-11-22 22:41:46.227366: Current learning rate: 0.00196 +2024-11-22 22:42:04.343312: train_loss -0.8183 +2024-11-22 22:42:04.343540: val_loss -0.7888 +2024-11-22 22:42:04.343616: Pseudo dice [0.8648] +2024-11-22 22:42:04.343691: Epoch time: 18.12 s +2024-11-22 22:42:05.250694: +2024-11-22 22:42:05.250899: Epoch 6692 +2024-11-22 22:42:05.251013: Current learning rate: 0.00196 +2024-11-22 22:42:24.592003: train_loss -0.8083 +2024-11-22 22:42:24.592231: val_loss -0.7941 +2024-11-22 22:42:24.592308: Pseudo dice [0.8505] +2024-11-22 22:42:24.592381: Epoch time: 19.34 s +2024-11-22 22:42:25.499923: +2024-11-22 22:42:25.500126: Epoch 6693 +2024-11-22 22:42:25.500232: Current learning rate: 0.00196 +2024-11-22 22:42:44.122765: train_loss -0.8156 +2024-11-22 22:42:44.123026: val_loss -0.7875 +2024-11-22 22:42:44.123107: Pseudo dice [0.8653] +2024-11-22 22:42:44.123209: Epoch time: 18.62 s +2024-11-22 22:42:45.180452: +2024-11-22 22:42:45.180676: Epoch 6694 +2024-11-22 22:42:45.180785: Current learning rate: 0.00196 +2024-11-22 22:43:02.940415: train_loss -0.8086 +2024-11-22 22:43:02.940668: val_loss -0.7652 +2024-11-22 22:43:02.940743: Pseudo dice [0.8346] +2024-11-22 22:43:02.940825: Epoch time: 17.76 s +2024-11-22 22:43:03.854017: +2024-11-22 22:43:03.854273: Epoch 6695 +2024-11-22 22:43:03.854386: Current learning rate: 0.00196 +2024-11-22 22:43:22.837331: train_loss -0.8128 +2024-11-22 22:43:22.837541: val_loss -0.7568 +2024-11-22 22:43:22.837765: Pseudo dice [0.853] +2024-11-22 22:43:22.837845: Epoch time: 18.98 s +2024-11-22 22:43:23.755364: +2024-11-22 22:43:23.755630: Epoch 6696 +2024-11-22 22:43:23.755741: Current learning rate: 0.00195 +2024-11-22 22:43:41.836630: train_loss -0.8145 +2024-11-22 22:43:41.836843: val_loss -0.7702 +2024-11-22 22:43:41.836916: Pseudo dice [0.8485] +2024-11-22 22:43:41.836997: Epoch time: 18.08 s +2024-11-22 22:43:42.745083: +2024-11-22 22:43:42.745300: Epoch 6697 +2024-11-22 22:43:42.745414: Current learning rate: 0.00195 +2024-11-22 22:44:00.978647: train_loss -0.813 +2024-11-22 22:44:00.978887: val_loss -0.7722 +2024-11-22 22:44:00.978962: Pseudo dice [0.851] +2024-11-22 22:44:00.979042: Epoch time: 18.23 s +2024-11-22 22:44:01.890746: +2024-11-22 22:44:01.890960: Epoch 6698 +2024-11-22 22:44:01.891093: Current learning rate: 0.00195 +2024-11-22 22:44:19.798718: train_loss -0.8104 +2024-11-22 22:44:19.801179: val_loss -0.7824 +2024-11-22 22:44:19.801270: Pseudo dice [0.86] +2024-11-22 22:44:19.801358: Epoch time: 17.91 s +2024-11-22 22:44:21.146748: +2024-11-22 22:44:21.146970: Epoch 6699 +2024-11-22 22:44:21.147084: Current learning rate: 0.00195 +2024-11-22 22:44:40.025185: train_loss -0.8112 +2024-11-22 22:44:40.025426: val_loss -0.7826 +2024-11-22 22:44:40.025513: Pseudo dice [0.8362] +2024-11-22 22:44:40.025587: Epoch time: 18.88 s +2024-11-22 22:44:41.282224: +2024-11-22 22:44:41.282437: Epoch 6700 +2024-11-22 22:44:41.282557: Current learning rate: 0.00195 +2024-11-22 22:44:59.358833: train_loss -0.8071 +2024-11-22 22:44:59.359096: val_loss -0.7732 +2024-11-22 22:44:59.359178: Pseudo dice [0.8377] +2024-11-22 22:44:59.359253: Epoch time: 18.08 s +2024-11-22 22:45:00.260445: +2024-11-22 22:45:00.260642: Epoch 6701 +2024-11-22 22:45:00.260751: Current learning rate: 0.00195 +2024-11-22 22:45:18.800834: train_loss -0.8112 +2024-11-22 22:45:18.809862: val_loss -0.7933 +2024-11-22 22:45:18.810061: Pseudo dice [0.8548] +2024-11-22 22:45:18.810166: Epoch time: 18.54 s +2024-11-22 22:45:19.730646: +2024-11-22 22:45:19.730855: Epoch 6702 +2024-11-22 22:45:19.730959: Current learning rate: 0.00195 +2024-11-22 22:45:38.298834: train_loss -0.8159 +2024-11-22 22:45:38.299107: val_loss -0.7655 +2024-11-22 22:45:38.299184: Pseudo dice [0.8506] +2024-11-22 22:45:38.299260: Epoch time: 18.57 s +2024-11-22 22:45:39.216257: +2024-11-22 22:45:39.216491: Epoch 6703 +2024-11-22 22:45:39.216603: Current learning rate: 0.00194 +2024-11-22 22:45:57.598738: train_loss -0.8171 +2024-11-22 22:45:57.598966: val_loss -0.7514 +2024-11-22 22:45:57.599054: Pseudo dice [0.8319] +2024-11-22 22:45:57.599131: Epoch time: 18.38 s +2024-11-22 22:45:58.512882: +2024-11-22 22:45:58.513118: Epoch 6704 +2024-11-22 22:45:58.513226: Current learning rate: 0.00194 +2024-11-22 22:46:15.617637: train_loss -0.822 +2024-11-22 22:46:15.617851: val_loss -0.7888 +2024-11-22 22:46:15.617926: Pseudo dice [0.8632] +2024-11-22 22:46:15.618010: Epoch time: 17.11 s +2024-11-22 22:46:16.524920: +2024-11-22 22:46:16.525150: Epoch 6705 +2024-11-22 22:46:16.525260: Current learning rate: 0.00194 +2024-11-22 22:46:35.458064: train_loss -0.8051 +2024-11-22 22:46:35.458317: val_loss -0.7367 +2024-11-22 22:46:35.458391: Pseudo dice [0.8426] +2024-11-22 22:46:35.458467: Epoch time: 18.93 s +2024-11-22 22:46:36.363810: +2024-11-22 22:46:36.364120: Epoch 6706 +2024-11-22 22:46:36.364237: Current learning rate: 0.00194 +2024-11-22 22:46:54.071559: train_loss -0.7992 +2024-11-22 22:46:54.071777: val_loss -0.7895 +2024-11-22 22:46:54.071848: Pseudo dice [0.8454] +2024-11-22 22:46:54.071922: Epoch time: 17.71 s +2024-11-22 22:46:55.004368: +2024-11-22 22:46:55.004580: Epoch 6707 +2024-11-22 22:46:55.004691: Current learning rate: 0.00194 +2024-11-22 22:47:12.699789: train_loss -0.8228 +2024-11-22 22:47:12.700025: val_loss -0.7911 +2024-11-22 22:47:12.700103: Pseudo dice [0.8495] +2024-11-22 22:47:12.700177: Epoch time: 17.7 s +2024-11-22 22:47:13.619124: +2024-11-22 22:47:13.619350: Epoch 6708 +2024-11-22 22:47:13.619461: Current learning rate: 0.00194 +2024-11-22 22:47:33.130128: train_loss -0.8106 +2024-11-22 22:47:33.130346: val_loss -0.7704 +2024-11-22 22:47:33.130422: Pseudo dice [0.8409] +2024-11-22 22:47:33.130500: Epoch time: 19.51 s +2024-11-22 22:47:34.040185: +2024-11-22 22:47:34.040413: Epoch 6709 +2024-11-22 22:47:34.040525: Current learning rate: 0.00194 +2024-11-22 22:47:51.731358: train_loss -0.8176 +2024-11-22 22:47:51.731623: val_loss -0.7933 +2024-11-22 22:47:51.731698: Pseudo dice [0.8549] +2024-11-22 22:47:51.731778: Epoch time: 17.69 s +2024-11-22 22:47:53.211789: +2024-11-22 22:47:53.212039: Epoch 6710 +2024-11-22 22:47:53.212150: Current learning rate: 0.00194 +2024-11-22 22:48:11.823316: train_loss -0.8064 +2024-11-22 22:48:11.823555: val_loss -0.7859 +2024-11-22 22:48:11.823633: Pseudo dice [0.8351] +2024-11-22 22:48:11.823711: Epoch time: 18.61 s +2024-11-22 22:48:12.732007: +2024-11-22 22:48:12.732238: Epoch 6711 +2024-11-22 22:48:12.732359: Current learning rate: 0.00193 +2024-11-22 22:48:30.737590: train_loss -0.8146 +2024-11-22 22:48:30.742369: val_loss -0.7873 +2024-11-22 22:48:30.742464: Pseudo dice [0.853] +2024-11-22 22:48:30.742540: Epoch time: 18.01 s +2024-11-22 22:48:31.651246: +2024-11-22 22:48:31.651457: Epoch 6712 +2024-11-22 22:48:31.651562: Current learning rate: 0.00193 +2024-11-22 22:48:50.449490: train_loss -0.8105 +2024-11-22 22:48:50.449854: val_loss -0.7896 +2024-11-22 22:48:50.449933: Pseudo dice [0.8627] +2024-11-22 22:48:50.450020: Epoch time: 18.8 s +2024-11-22 22:48:51.380297: +2024-11-22 22:48:51.380522: Epoch 6713 +2024-11-22 22:48:51.380639: Current learning rate: 0.00193 +2024-11-22 22:49:09.888260: train_loss -0.808 +2024-11-22 22:49:09.888547: val_loss -0.7659 +2024-11-22 22:49:09.888626: Pseudo dice [0.8652] +2024-11-22 22:49:09.888700: Epoch time: 18.51 s +2024-11-22 22:49:10.889391: +2024-11-22 22:49:10.889609: Epoch 6714 +2024-11-22 22:49:10.890382: Current learning rate: 0.00193 +2024-11-22 22:49:30.336171: train_loss -0.8077 +2024-11-22 22:49:30.336412: val_loss -0.7699 +2024-11-22 22:49:30.336487: Pseudo dice [0.8654] +2024-11-22 22:49:30.336563: Epoch time: 19.45 s +2024-11-22 22:49:31.287247: +2024-11-22 22:49:31.287465: Epoch 6715 +2024-11-22 22:49:31.287572: Current learning rate: 0.00193 +2024-11-22 22:49:50.092323: train_loss -0.8104 +2024-11-22 22:49:50.092549: val_loss -0.766 +2024-11-22 22:49:50.092620: Pseudo dice [0.8475] +2024-11-22 22:49:50.097004: Epoch time: 18.81 s +2024-11-22 22:49:51.009948: +2024-11-22 22:49:51.010226: Epoch 6716 +2024-11-22 22:49:51.010343: Current learning rate: 0.00193 +2024-11-22 22:50:08.532830: train_loss -0.8111 +2024-11-22 22:50:08.533100: val_loss -0.7954 +2024-11-22 22:50:08.533177: Pseudo dice [0.8472] +2024-11-22 22:50:08.533258: Epoch time: 17.52 s +2024-11-22 22:50:09.435239: +2024-11-22 22:50:09.435559: Epoch 6717 +2024-11-22 22:50:09.435670: Current learning rate: 0.00193 +2024-11-22 22:50:27.940686: train_loss -0.8159 +2024-11-22 22:50:27.940909: val_loss -0.7579 +2024-11-22 22:50:27.940982: Pseudo dice [0.86] +2024-11-22 22:50:27.941060: Epoch time: 18.51 s +2024-11-22 22:50:28.844494: +2024-11-22 22:50:28.844763: Epoch 6718 +2024-11-22 22:50:28.844871: Current learning rate: 0.00192 +2024-11-22 22:50:48.247701: train_loss -0.8115 +2024-11-22 22:50:48.247924: val_loss -0.7735 +2024-11-22 22:50:48.248007: Pseudo dice [0.8475] +2024-11-22 22:50:48.248084: Epoch time: 19.4 s +2024-11-22 22:50:49.217613: +2024-11-22 22:50:49.217844: Epoch 6719 +2024-11-22 22:50:49.217956: Current learning rate: 0.00192 +2024-11-22 22:51:07.760030: train_loss -0.8116 +2024-11-22 22:51:07.765411: val_loss -0.7915 +2024-11-22 22:51:07.765606: Pseudo dice [0.8538] +2024-11-22 22:51:07.765694: Epoch time: 18.54 s +2024-11-22 22:51:08.727225: +2024-11-22 22:51:08.727414: Epoch 6720 +2024-11-22 22:51:08.727523: Current learning rate: 0.00192 +2024-11-22 22:51:26.607941: train_loss -0.8152 +2024-11-22 22:51:26.608191: val_loss -0.7831 +2024-11-22 22:51:26.608269: Pseudo dice [0.8523] +2024-11-22 22:51:26.608355: Epoch time: 17.88 s +2024-11-22 22:51:27.912184: +2024-11-22 22:51:27.912486: Epoch 6721 +2024-11-22 22:51:27.912600: Current learning rate: 0.00192 +2024-11-22 22:51:45.385835: train_loss -0.8194 +2024-11-22 22:51:45.386071: val_loss -0.7734 +2024-11-22 22:51:45.386233: Pseudo dice [0.8528] +2024-11-22 22:51:45.386313: Epoch time: 17.47 s +2024-11-22 22:51:46.287762: +2024-11-22 22:51:46.287995: Epoch 6722 +2024-11-22 22:51:46.288109: Current learning rate: 0.00192 +2024-11-22 22:52:04.714603: train_loss -0.813 +2024-11-22 22:52:04.714854: val_loss -0.7952 +2024-11-22 22:52:04.714931: Pseudo dice [0.8607] +2024-11-22 22:52:04.715014: Epoch time: 18.43 s +2024-11-22 22:52:05.632062: +2024-11-22 22:52:05.632278: Epoch 6723 +2024-11-22 22:52:05.632384: Current learning rate: 0.00192 +2024-11-22 22:52:23.902700: train_loss -0.8109 +2024-11-22 22:52:23.902953: val_loss -0.789 +2024-11-22 22:52:23.905288: Pseudo dice [0.843] +2024-11-22 22:52:23.905407: Epoch time: 18.27 s +2024-11-22 22:52:24.834145: +2024-11-22 22:52:24.834361: Epoch 6724 +2024-11-22 22:52:24.834470: Current learning rate: 0.00192 +2024-11-22 22:52:43.728393: train_loss -0.8099 +2024-11-22 22:52:43.728636: val_loss -0.7909 +2024-11-22 22:52:43.728711: Pseudo dice [0.8538] +2024-11-22 22:52:43.728787: Epoch time: 18.9 s +2024-11-22 22:52:44.637396: +2024-11-22 22:52:44.637628: Epoch 6725 +2024-11-22 22:52:44.637738: Current learning rate: 0.00192 +2024-11-22 22:53:01.270730: train_loss -0.8161 +2024-11-22 22:53:01.270977: val_loss -0.7491 +2024-11-22 22:53:01.271059: Pseudo dice [0.8533] +2024-11-22 22:53:01.271136: Epoch time: 16.63 s +2024-11-22 22:53:02.198229: +2024-11-22 22:53:02.198432: Epoch 6726 +2024-11-22 22:53:02.198540: Current learning rate: 0.00191 +2024-11-22 22:53:21.293494: train_loss -0.8163 +2024-11-22 22:53:21.306373: val_loss -0.7679 +2024-11-22 22:53:21.306466: Pseudo dice [0.8432] +2024-11-22 22:53:21.306546: Epoch time: 19.1 s +2024-11-22 22:53:22.323518: +2024-11-22 22:53:22.323776: Epoch 6727 +2024-11-22 22:53:22.323888: Current learning rate: 0.00191 +2024-11-22 22:53:40.945641: train_loss -0.8169 +2024-11-22 22:53:40.945899: val_loss -0.7569 +2024-11-22 22:53:40.945981: Pseudo dice [0.85] +2024-11-22 22:53:40.946106: Epoch time: 18.62 s +2024-11-22 22:53:41.859113: +2024-11-22 22:53:41.859319: Epoch 6728 +2024-11-22 22:53:41.859427: Current learning rate: 0.00191 +2024-11-22 22:53:59.540684: train_loss -0.8158 +2024-11-22 22:53:59.540938: val_loss -0.7844 +2024-11-22 22:53:59.541018: Pseudo dice [0.8523] +2024-11-22 22:53:59.541092: Epoch time: 17.68 s +2024-11-22 22:54:00.460082: +2024-11-22 22:54:00.460335: Epoch 6729 +2024-11-22 22:54:00.460449: Current learning rate: 0.00191 +2024-11-22 22:54:19.191820: train_loss -0.8103 +2024-11-22 22:54:19.192042: val_loss -0.7621 +2024-11-22 22:54:19.192118: Pseudo dice [0.8455] +2024-11-22 22:54:19.192193: Epoch time: 18.73 s +2024-11-22 22:54:20.101354: +2024-11-22 22:54:20.101563: Epoch 6730 +2024-11-22 22:54:20.101673: Current learning rate: 0.00191 +2024-11-22 22:54:37.914225: train_loss -0.8148 +2024-11-22 22:54:37.914443: val_loss -0.7758 +2024-11-22 22:54:37.914519: Pseudo dice [0.8551] +2024-11-22 22:54:37.914593: Epoch time: 17.81 s +2024-11-22 22:54:38.820666: +2024-11-22 22:54:38.820903: Epoch 6731 +2024-11-22 22:54:38.821019: Current learning rate: 0.00191 +2024-11-22 22:54:57.643237: train_loss -0.8129 +2024-11-22 22:54:57.643508: val_loss -0.7883 +2024-11-22 22:54:57.643588: Pseudo dice [0.8561] +2024-11-22 22:54:57.643670: Epoch time: 18.82 s +2024-11-22 22:54:58.559957: +2024-11-22 22:54:58.560178: Epoch 6732 +2024-11-22 22:54:58.560304: Current learning rate: 0.00191 +2024-11-22 22:55:16.518274: train_loss -0.811 +2024-11-22 22:55:16.518492: val_loss -0.7609 +2024-11-22 22:55:16.518566: Pseudo dice [0.847] +2024-11-22 22:55:16.518639: Epoch time: 17.96 s +2024-11-22 22:55:17.818702: +2024-11-22 22:55:17.818951: Epoch 6733 +2024-11-22 22:55:17.819069: Current learning rate: 0.0019 +2024-11-22 22:55:35.873481: train_loss -0.8151 +2024-11-22 22:55:35.873730: val_loss -0.7856 +2024-11-22 22:55:35.873808: Pseudo dice [0.8528] +2024-11-22 22:55:35.873887: Epoch time: 18.06 s +2024-11-22 22:55:36.860284: +2024-11-22 22:55:36.860473: Epoch 6734 +2024-11-22 22:55:36.860578: Current learning rate: 0.0019 +2024-11-22 22:55:54.747588: train_loss -0.8084 +2024-11-22 22:55:54.747912: val_loss -0.8024 +2024-11-22 22:55:54.748011: Pseudo dice [0.852] +2024-11-22 22:55:54.748092: Epoch time: 17.89 s +2024-11-22 22:55:55.660135: +2024-11-22 22:55:55.660369: Epoch 6735 +2024-11-22 22:55:55.660483: Current learning rate: 0.0019 +2024-11-22 22:56:14.876985: train_loss -0.8128 +2024-11-22 22:56:14.882407: val_loss -0.7924 +2024-11-22 22:56:14.882520: Pseudo dice [0.866] +2024-11-22 22:56:14.882609: Epoch time: 19.22 s +2024-11-22 22:56:15.816282: +2024-11-22 22:56:15.816481: Epoch 6736 +2024-11-22 22:56:15.816598: Current learning rate: 0.0019 +2024-11-22 22:56:33.753276: train_loss -0.8131 +2024-11-22 22:56:33.753501: val_loss -0.7766 +2024-11-22 22:56:33.753577: Pseudo dice [0.846] +2024-11-22 22:56:33.753658: Epoch time: 17.94 s +2024-11-22 22:56:34.742347: +2024-11-22 22:56:34.742565: Epoch 6737 +2024-11-22 22:56:34.742678: Current learning rate: 0.0019 +2024-11-22 22:56:52.786895: train_loss -0.8174 +2024-11-22 22:56:52.787144: val_loss -0.7536 +2024-11-22 22:56:52.787227: Pseudo dice [0.8556] +2024-11-22 22:56:52.787306: Epoch time: 18.05 s +2024-11-22 22:56:53.699123: +2024-11-22 22:56:53.699355: Epoch 6738 +2024-11-22 22:56:53.699462: Current learning rate: 0.0019 +2024-11-22 22:57:12.530820: train_loss -0.8201 +2024-11-22 22:57:12.531080: val_loss -0.7729 +2024-11-22 22:57:12.531158: Pseudo dice [0.8523] +2024-11-22 22:57:12.531235: Epoch time: 18.83 s +2024-11-22 22:57:13.439037: +2024-11-22 22:57:13.439241: Epoch 6739 +2024-11-22 22:57:13.439351: Current learning rate: 0.0019 +2024-11-22 22:57:30.774862: train_loss -0.8143 +2024-11-22 22:57:30.775121: val_loss -0.7734 +2024-11-22 22:57:30.791769: Pseudo dice [0.8649] +2024-11-22 22:57:30.791960: Epoch time: 17.34 s +2024-11-22 22:57:31.815458: +2024-11-22 22:57:31.815664: Epoch 6740 +2024-11-22 22:57:31.815774: Current learning rate: 0.00189 +2024-11-22 22:57:49.904590: train_loss -0.8182 +2024-11-22 22:57:49.904879: val_loss -0.7854 +2024-11-22 22:57:49.904958: Pseudo dice [0.8513] +2024-11-22 22:57:49.905036: Epoch time: 18.09 s +2024-11-22 22:57:50.820839: +2024-11-22 22:57:50.821053: Epoch 6741 +2024-11-22 22:57:50.821182: Current learning rate: 0.00189 +2024-11-22 22:58:09.711329: train_loss -0.8085 +2024-11-22 22:58:09.711609: val_loss -0.7859 +2024-11-22 22:58:09.711687: Pseudo dice [0.8719] +2024-11-22 22:58:09.711800: Epoch time: 18.89 s +2024-11-22 22:58:10.642043: +2024-11-22 22:58:10.642243: Epoch 6742 +2024-11-22 22:58:10.642350: Current learning rate: 0.00189 +2024-11-22 22:58:29.203899: train_loss -0.8059 +2024-11-22 22:58:29.204128: val_loss -0.7817 +2024-11-22 22:58:29.204221: Pseudo dice [0.8575] +2024-11-22 22:58:29.204355: Epoch time: 18.56 s +2024-11-22 22:58:30.122034: +2024-11-22 22:58:30.122232: Epoch 6743 +2024-11-22 22:58:30.122343: Current learning rate: 0.00189 +2024-11-22 22:58:47.735899: train_loss -0.82 +2024-11-22 22:58:47.736158: val_loss -0.7821 +2024-11-22 22:58:47.736237: Pseudo dice [0.8475] +2024-11-22 22:58:47.736318: Epoch time: 17.61 s +2024-11-22 22:58:49.025676: +2024-11-22 22:58:49.025902: Epoch 6744 +2024-11-22 22:58:49.026023: Current learning rate: 0.00189 +2024-11-22 22:59:07.268357: train_loss -0.8233 +2024-11-22 22:59:07.268577: val_loss -0.7837 +2024-11-22 22:59:07.268653: Pseudo dice [0.8396] +2024-11-22 22:59:07.268729: Epoch time: 18.24 s +2024-11-22 22:59:08.188241: +2024-11-22 22:59:08.188469: Epoch 6745 +2024-11-22 22:59:08.188576: Current learning rate: 0.00189 +2024-11-22 22:59:28.233887: train_loss -0.812 +2024-11-22 22:59:28.234116: val_loss -0.7916 +2024-11-22 22:59:28.234197: Pseudo dice [0.8607] +2024-11-22 22:59:28.235142: Epoch time: 20.05 s +2024-11-22 22:59:29.153711: +2024-11-22 22:59:29.153948: Epoch 6746 +2024-11-22 22:59:29.154069: Current learning rate: 0.00189 +2024-11-22 22:59:47.688367: train_loss -0.8131 +2024-11-22 22:59:47.688591: val_loss -0.7856 +2024-11-22 22:59:47.688664: Pseudo dice [0.8685] +2024-11-22 22:59:47.688743: Epoch time: 18.54 s +2024-11-22 22:59:48.596746: +2024-11-22 22:59:48.596975: Epoch 6747 +2024-11-22 22:59:48.597106: Current learning rate: 0.00189 +2024-11-22 23:00:06.814404: train_loss -0.8182 +2024-11-22 23:00:06.814806: val_loss -0.7584 +2024-11-22 23:00:06.814889: Pseudo dice [0.8355] +2024-11-22 23:00:06.814967: Epoch time: 18.22 s +2024-11-22 23:00:07.751972: +2024-11-22 23:00:07.752204: Epoch 6748 +2024-11-22 23:00:07.752317: Current learning rate: 0.00188 +2024-11-22 23:00:26.757226: train_loss -0.8098 +2024-11-22 23:00:26.758320: val_loss -0.7736 +2024-11-22 23:00:26.758396: Pseudo dice [0.8648] +2024-11-22 23:00:26.758472: Epoch time: 19.01 s +2024-11-22 23:00:27.670338: +2024-11-22 23:00:27.670549: Epoch 6749 +2024-11-22 23:00:27.670657: Current learning rate: 0.00188 +2024-11-22 23:00:46.494143: train_loss -0.8235 +2024-11-22 23:00:46.494370: val_loss -0.7583 +2024-11-22 23:00:46.494447: Pseudo dice [0.8467] +2024-11-22 23:00:46.494524: Epoch time: 18.82 s +2024-11-22 23:00:47.726516: +2024-11-22 23:00:47.726753: Epoch 6750 +2024-11-22 23:00:47.726866: Current learning rate: 0.00188 +2024-11-22 23:01:05.710142: train_loss -0.823 +2024-11-22 23:01:05.710391: val_loss -0.7711 +2024-11-22 23:01:05.710464: Pseudo dice [0.8436] +2024-11-22 23:01:05.710547: Epoch time: 17.98 s +2024-11-22 23:01:06.633154: +2024-11-22 23:01:06.633364: Epoch 6751 +2024-11-22 23:01:06.633478: Current learning rate: 0.00188 +2024-11-22 23:01:25.235167: train_loss -0.8172 +2024-11-22 23:01:25.235392: val_loss -0.7747 +2024-11-22 23:01:25.235478: Pseudo dice [0.8556] +2024-11-22 23:01:25.235559: Epoch time: 18.6 s +2024-11-22 23:01:26.242134: +2024-11-22 23:01:26.242352: Epoch 6752 +2024-11-22 23:01:26.242469: Current learning rate: 0.00188 +2024-11-22 23:01:44.244075: train_loss -0.8172 +2024-11-22 23:01:44.244293: val_loss -0.7534 +2024-11-22 23:01:44.244382: Pseudo dice [0.8464] +2024-11-22 23:01:44.244462: Epoch time: 18.0 s +2024-11-22 23:01:45.153281: +2024-11-22 23:01:45.153475: Epoch 6753 +2024-11-22 23:01:45.153583: Current learning rate: 0.00188 +2024-11-22 23:02:03.847988: train_loss -0.8191 +2024-11-22 23:02:03.848275: val_loss -0.7901 +2024-11-22 23:02:03.848355: Pseudo dice [0.8515] +2024-11-22 23:02:03.848428: Epoch time: 18.7 s +2024-11-22 23:02:04.757971: +2024-11-22 23:02:04.758413: Epoch 6754 +2024-11-22 23:02:04.758550: Current learning rate: 0.00188 +2024-11-22 23:02:23.017617: train_loss -0.8093 +2024-11-22 23:02:23.017872: val_loss -0.7792 +2024-11-22 23:02:23.017946: Pseudo dice [0.8439] +2024-11-22 23:02:23.018031: Epoch time: 18.26 s +2024-11-22 23:02:23.928610: +2024-11-22 23:02:23.928812: Epoch 6755 +2024-11-22 23:02:23.928921: Current learning rate: 0.00187 +2024-11-22 23:02:42.861431: train_loss -0.8076 +2024-11-22 23:02:42.861696: val_loss -0.7846 +2024-11-22 23:02:42.861774: Pseudo dice [0.845] +2024-11-22 23:02:42.861849: Epoch time: 18.93 s +2024-11-22 23:02:43.772761: +2024-11-22 23:02:43.773021: Epoch 6756 +2024-11-22 23:02:43.773133: Current learning rate: 0.00187 +2024-11-22 23:03:01.700767: train_loss -0.816 +2024-11-22 23:03:01.701010: val_loss -0.793 +2024-11-22 23:03:01.701088: Pseudo dice [0.8616] +2024-11-22 23:03:01.701165: Epoch time: 17.93 s +2024-11-22 23:03:02.730806: +2024-11-22 23:03:02.731050: Epoch 6757 +2024-11-22 23:03:02.731168: Current learning rate: 0.00187 +2024-11-22 23:03:20.777212: train_loss -0.8169 +2024-11-22 23:03:20.777468: val_loss -0.7772 +2024-11-22 23:03:20.777543: Pseudo dice [0.8384] +2024-11-22 23:03:20.777627: Epoch time: 18.05 s +2024-11-22 23:03:21.686537: +2024-11-22 23:03:21.686770: Epoch 6758 +2024-11-22 23:03:21.686881: Current learning rate: 0.00187 +2024-11-22 23:03:39.600731: train_loss -0.8182 +2024-11-22 23:03:39.600986: val_loss -0.7725 +2024-11-22 23:03:39.601138: Pseudo dice [0.8621] +2024-11-22 23:03:39.601214: Epoch time: 17.92 s +2024-11-22 23:03:40.509604: +2024-11-22 23:03:40.509824: Epoch 6759 +2024-11-22 23:03:40.509931: Current learning rate: 0.00187 +2024-11-22 23:03:58.956547: train_loss -0.8141 +2024-11-22 23:03:58.956844: val_loss -0.7762 +2024-11-22 23:03:58.956934: Pseudo dice [0.8551] +2024-11-22 23:03:58.957015: Epoch time: 18.45 s +2024-11-22 23:03:59.967082: +2024-11-22 23:03:59.967345: Epoch 6760 +2024-11-22 23:03:59.967455: Current learning rate: 0.00187 +2024-11-22 23:04:19.154335: train_loss -0.818 +2024-11-22 23:04:19.154565: val_loss -0.7709 +2024-11-22 23:04:19.154639: Pseudo dice [0.8407] +2024-11-22 23:04:19.154712: Epoch time: 19.19 s +2024-11-22 23:04:20.072430: +2024-11-22 23:04:20.072637: Epoch 6761 +2024-11-22 23:04:20.072836: Current learning rate: 0.00187 +2024-11-22 23:04:38.676807: train_loss -0.8157 +2024-11-22 23:04:38.677087: val_loss -0.7527 +2024-11-22 23:04:38.677168: Pseudo dice [0.8472] +2024-11-22 23:04:38.677249: Epoch time: 18.61 s +2024-11-22 23:04:39.591337: +2024-11-22 23:04:39.591615: Epoch 6762 +2024-11-22 23:04:39.591729: Current learning rate: 0.00186 +2024-11-22 23:04:58.715978: train_loss -0.8155 +2024-11-22 23:04:58.716224: val_loss -0.7873 +2024-11-22 23:04:58.716300: Pseudo dice [0.8513] +2024-11-22 23:04:58.716384: Epoch time: 19.13 s +2024-11-22 23:04:59.629349: +2024-11-22 23:04:59.629574: Epoch 6763 +2024-11-22 23:04:59.629686: Current learning rate: 0.00186 +2024-11-22 23:05:18.346299: train_loss -0.8218 +2024-11-22 23:05:18.346533: val_loss -0.7948 +2024-11-22 23:05:18.346607: Pseudo dice [0.8456] +2024-11-22 23:05:18.346682: Epoch time: 18.72 s +2024-11-22 23:05:19.254404: +2024-11-22 23:05:19.254627: Epoch 6764 +2024-11-22 23:05:19.254742: Current learning rate: 0.00186 +2024-11-22 23:05:38.916916: train_loss -0.8114 +2024-11-22 23:05:38.919294: val_loss -0.7689 +2024-11-22 23:05:38.919417: Pseudo dice [0.8544] +2024-11-22 23:05:38.919497: Epoch time: 19.66 s +2024-11-22 23:05:39.885592: +2024-11-22 23:05:39.885786: Epoch 6765 +2024-11-22 23:05:39.885892: Current learning rate: 0.00186 +2024-11-22 23:05:58.359409: train_loss -0.8165 +2024-11-22 23:05:58.359663: val_loss -0.801 +2024-11-22 23:05:58.359737: Pseudo dice [0.852] +2024-11-22 23:05:58.359820: Epoch time: 18.47 s +2024-11-22 23:05:59.269398: +2024-11-22 23:05:59.269609: Epoch 6766 +2024-11-22 23:05:59.269736: Current learning rate: 0.00186 +2024-11-22 23:06:17.092292: train_loss -0.8178 +2024-11-22 23:06:17.092544: val_loss -0.7821 +2024-11-22 23:06:17.092628: Pseudo dice [0.8631] +2024-11-22 23:06:17.092770: Epoch time: 17.82 s +2024-11-22 23:06:18.001822: +2024-11-22 23:06:18.002064: Epoch 6767 +2024-11-22 23:06:18.002174: Current learning rate: 0.00186 +2024-11-22 23:06:36.102632: train_loss -0.8161 +2024-11-22 23:06:36.102865: val_loss -0.7861 +2024-11-22 23:06:36.102941: Pseudo dice [0.8381] +2024-11-22 23:06:36.103036: Epoch time: 18.1 s +2024-11-22 23:06:37.022562: +2024-11-22 23:06:37.022926: Epoch 6768 +2024-11-22 23:06:37.023046: Current learning rate: 0.00186 +2024-11-22 23:06:54.623315: train_loss -0.8163 +2024-11-22 23:06:54.628770: val_loss -0.7645 +2024-11-22 23:06:54.628935: Pseudo dice [0.8391] +2024-11-22 23:06:54.629039: Epoch time: 17.6 s +2024-11-22 23:06:55.557497: +2024-11-22 23:06:55.557718: Epoch 6769 +2024-11-22 23:06:55.557827: Current learning rate: 0.00186 +2024-11-22 23:07:14.047523: train_loss -0.8157 +2024-11-22 23:07:14.047751: val_loss -0.7885 +2024-11-22 23:07:14.047826: Pseudo dice [0.8564] +2024-11-22 23:07:14.047900: Epoch time: 18.49 s +2024-11-22 23:07:14.999463: +2024-11-22 23:07:14.999665: Epoch 6770 +2024-11-22 23:07:14.999772: Current learning rate: 0.00185 +2024-11-22 23:07:33.234983: train_loss -0.8117 +2024-11-22 23:07:33.235219: val_loss -0.7828 +2024-11-22 23:07:33.235296: Pseudo dice [0.8495] +2024-11-22 23:07:33.235375: Epoch time: 18.24 s +2024-11-22 23:07:34.143568: +2024-11-22 23:07:34.143786: Epoch 6771 +2024-11-22 23:07:34.143897: Current learning rate: 0.00185 +2024-11-22 23:07:52.390925: train_loss -0.8135 +2024-11-22 23:07:52.391165: val_loss -0.7775 +2024-11-22 23:07:52.391243: Pseudo dice [0.8576] +2024-11-22 23:07:52.391320: Epoch time: 18.25 s +2024-11-22 23:07:53.301638: +2024-11-22 23:07:53.301854: Epoch 6772 +2024-11-22 23:07:53.301959: Current learning rate: 0.00185 +2024-11-22 23:08:11.704586: train_loss -0.8142 +2024-11-22 23:08:11.704910: val_loss -0.8015 +2024-11-22 23:08:11.704995: Pseudo dice [0.865] +2024-11-22 23:08:11.705075: Epoch time: 18.4 s +2024-11-22 23:08:12.620694: +2024-11-22 23:08:12.620887: Epoch 6773 +2024-11-22 23:08:12.621010: Current learning rate: 0.00185 +2024-11-22 23:08:31.629743: train_loss -0.8076 +2024-11-22 23:08:31.630263: val_loss -0.7743 +2024-11-22 23:08:31.630360: Pseudo dice [0.8433] +2024-11-22 23:08:31.630441: Epoch time: 19.01 s +2024-11-22 23:08:32.545425: +2024-11-22 23:08:32.545621: Epoch 6774 +2024-11-22 23:08:32.545734: Current learning rate: 0.00185 +2024-11-22 23:08:51.871737: train_loss -0.7977 +2024-11-22 23:08:51.871972: val_loss -0.797 +2024-11-22 23:08:51.872054: Pseudo dice [0.8571] +2024-11-22 23:08:51.872132: Epoch time: 19.33 s +2024-11-22 23:08:52.826976: +2024-11-22 23:08:52.827191: Epoch 6775 +2024-11-22 23:08:52.827373: Current learning rate: 0.00185 +2024-11-22 23:09:11.843585: train_loss -0.8101 +2024-11-22 23:09:11.843806: val_loss -0.7602 +2024-11-22 23:09:11.843884: Pseudo dice [0.8332] +2024-11-22 23:09:11.843962: Epoch time: 19.02 s +2024-11-22 23:09:12.855379: +2024-11-22 23:09:12.855635: Epoch 6776 +2024-11-22 23:09:12.855749: Current learning rate: 0.00185 +2024-11-22 23:09:31.867458: train_loss -0.8064 +2024-11-22 23:09:31.867683: val_loss -0.7888 +2024-11-22 23:09:31.867763: Pseudo dice [0.8535] +2024-11-22 23:09:31.867842: Epoch time: 19.01 s +2024-11-22 23:09:33.150650: +2024-11-22 23:09:33.150888: Epoch 6777 +2024-11-22 23:09:33.151040: Current learning rate: 0.00184 +2024-11-22 23:09:52.199342: train_loss -0.8104 +2024-11-22 23:09:52.199634: val_loss -0.7804 +2024-11-22 23:09:52.199718: Pseudo dice [0.853] +2024-11-22 23:09:52.232539: Epoch time: 19.04 s +2024-11-22 23:09:53.224146: +2024-11-22 23:09:53.224369: Epoch 6778 +2024-11-22 23:09:53.224483: Current learning rate: 0.00184 +2024-11-22 23:10:12.443062: train_loss -0.8067 +2024-11-22 23:10:12.443304: val_loss -0.7832 +2024-11-22 23:10:12.443379: Pseudo dice [0.8584] +2024-11-22 23:10:12.443457: Epoch time: 19.22 s +2024-11-22 23:10:13.357982: +2024-11-22 23:10:13.358278: Epoch 6779 +2024-11-22 23:10:13.358390: Current learning rate: 0.00184 +2024-11-22 23:10:32.334439: train_loss -0.8168 +2024-11-22 23:10:32.334692: val_loss -0.7719 +2024-11-22 23:10:32.334774: Pseudo dice [0.839] +2024-11-22 23:10:32.334852: Epoch time: 18.98 s +2024-11-22 23:10:33.246592: +2024-11-22 23:10:33.246814: Epoch 6780 +2024-11-22 23:10:33.246922: Current learning rate: 0.00184 +2024-11-22 23:10:52.416903: train_loss -0.8184 +2024-11-22 23:10:52.417146: val_loss -0.7935 +2024-11-22 23:10:52.417226: Pseudo dice [0.8444] +2024-11-22 23:10:52.417303: Epoch time: 19.17 s +2024-11-22 23:10:53.326864: +2024-11-22 23:10:53.327128: Epoch 6781 +2024-11-22 23:10:53.327276: Current learning rate: 0.00184 +2024-11-22 23:11:11.794933: train_loss -0.8146 +2024-11-22 23:11:11.795157: val_loss -0.775 +2024-11-22 23:11:11.795229: Pseudo dice [0.8643] +2024-11-22 23:11:11.795325: Epoch time: 18.47 s +2024-11-22 23:11:12.709571: +2024-11-22 23:11:12.709794: Epoch 6782 +2024-11-22 23:11:12.709906: Current learning rate: 0.00184 +2024-11-22 23:11:31.371483: train_loss -0.8166 +2024-11-22 23:11:31.371731: val_loss -0.7797 +2024-11-22 23:11:31.371806: Pseudo dice [0.8512] +2024-11-22 23:11:31.371904: Epoch time: 18.66 s +2024-11-22 23:11:32.279947: +2024-11-22 23:11:32.280174: Epoch 6783 +2024-11-22 23:11:32.280282: Current learning rate: 0.00184 +2024-11-22 23:11:50.711202: train_loss -0.813 +2024-11-22 23:11:50.711429: val_loss -0.7618 +2024-11-22 23:11:50.711504: Pseudo dice [0.8544] +2024-11-22 23:11:50.711581: Epoch time: 18.43 s +2024-11-22 23:11:51.838483: +2024-11-22 23:11:51.838703: Epoch 6784 +2024-11-22 23:11:51.838815: Current learning rate: 0.00184 +2024-11-22 23:12:09.954788: train_loss -0.8216 +2024-11-22 23:12:09.955050: val_loss -0.7959 +2024-11-22 23:12:09.955129: Pseudo dice [0.8564] +2024-11-22 23:12:09.955209: Epoch time: 18.12 s +2024-11-22 23:12:10.868486: +2024-11-22 23:12:10.868706: Epoch 6785 +2024-11-22 23:12:10.868819: Current learning rate: 0.00183 +2024-11-22 23:12:28.660474: train_loss -0.8173 +2024-11-22 23:12:28.660714: val_loss -0.7836 +2024-11-22 23:12:28.660790: Pseudo dice [0.8523] +2024-11-22 23:12:28.660863: Epoch time: 17.79 s +2024-11-22 23:12:29.647115: +2024-11-22 23:12:29.647352: Epoch 6786 +2024-11-22 23:12:29.647487: Current learning rate: 0.00183 +2024-11-22 23:12:48.330680: train_loss -0.8225 +2024-11-22 23:12:48.330905: val_loss -0.7631 +2024-11-22 23:12:48.330979: Pseudo dice [0.854] +2024-11-22 23:12:48.331094: Epoch time: 18.68 s +2024-11-22 23:12:49.241430: +2024-11-22 23:12:49.241657: Epoch 6787 +2024-11-22 23:12:49.241768: Current learning rate: 0.00183 +2024-11-22 23:13:07.255575: train_loss -0.8194 +2024-11-22 23:13:07.255795: val_loss -0.7866 +2024-11-22 23:13:07.255871: Pseudo dice [0.8596] +2024-11-22 23:13:07.255945: Epoch time: 18.01 s +2024-11-22 23:13:08.170557: +2024-11-22 23:13:08.170766: Epoch 6788 +2024-11-22 23:13:08.170873: Current learning rate: 0.00183 +2024-11-22 23:13:26.857565: train_loss -0.8109 +2024-11-22 23:13:26.857806: val_loss -0.7631 +2024-11-22 23:13:26.857883: Pseudo dice [0.8489] +2024-11-22 23:13:26.857964: Epoch time: 18.69 s +2024-11-22 23:13:28.177925: +2024-11-22 23:13:28.178165: Epoch 6789 +2024-11-22 23:13:28.178275: Current learning rate: 0.00183 +2024-11-22 23:13:46.084637: train_loss -0.8177 +2024-11-22 23:13:46.084891: val_loss -0.7851 +2024-11-22 23:13:46.084969: Pseudo dice [0.856] +2024-11-22 23:13:46.085057: Epoch time: 17.91 s +2024-11-22 23:13:47.158790: +2024-11-22 23:13:47.159029: Epoch 6790 +2024-11-22 23:13:47.159138: Current learning rate: 0.00183 +2024-11-22 23:14:05.677008: train_loss -0.8199 +2024-11-22 23:14:05.677251: val_loss -0.758 +2024-11-22 23:14:05.677335: Pseudo dice [0.854] +2024-11-22 23:14:05.677412: Epoch time: 18.52 s +2024-11-22 23:14:06.585844: +2024-11-22 23:14:06.586067: Epoch 6791 +2024-11-22 23:14:06.586185: Current learning rate: 0.00183 +2024-11-22 23:14:25.306858: train_loss -0.8108 +2024-11-22 23:14:25.307132: val_loss -0.775 +2024-11-22 23:14:25.307212: Pseudo dice [0.8614] +2024-11-22 23:14:25.307297: Epoch time: 18.72 s +2024-11-22 23:14:26.221076: +2024-11-22 23:14:26.221300: Epoch 6792 +2024-11-22 23:14:26.221414: Current learning rate: 0.00182 +2024-11-22 23:14:44.646430: train_loss -0.8144 +2024-11-22 23:14:44.646657: val_loss -0.7857 +2024-11-22 23:14:44.646736: Pseudo dice [0.8517] +2024-11-22 23:14:44.646812: Epoch time: 18.43 s +2024-11-22 23:14:45.563952: +2024-11-22 23:14:45.564176: Epoch 6793 +2024-11-22 23:14:45.564284: Current learning rate: 0.00182 +2024-11-22 23:15:03.736776: train_loss -0.8172 +2024-11-22 23:15:03.737032: val_loss -0.7918 +2024-11-22 23:15:03.737106: Pseudo dice [0.8652] +2024-11-22 23:15:03.737180: Epoch time: 18.17 s +2024-11-22 23:15:04.656411: +2024-11-22 23:15:04.656627: Epoch 6794 +2024-11-22 23:15:04.656737: Current learning rate: 0.00182 +2024-11-22 23:15:23.512065: train_loss -0.8115 +2024-11-22 23:15:23.512286: val_loss -0.7461 +2024-11-22 23:15:23.512446: Pseudo dice [0.8533] +2024-11-22 23:15:23.512524: Epoch time: 18.86 s +2024-11-22 23:15:24.426754: +2024-11-22 23:15:24.426982: Epoch 6795 +2024-11-22 23:15:24.427099: Current learning rate: 0.00182 +2024-11-22 23:15:43.339867: train_loss -0.7917 +2024-11-22 23:15:43.340120: val_loss -0.7767 +2024-11-22 23:15:43.340199: Pseudo dice [0.8337] +2024-11-22 23:15:43.340286: Epoch time: 18.91 s +2024-11-22 23:15:44.257293: +2024-11-22 23:15:44.257504: Epoch 6796 +2024-11-22 23:15:44.257623: Current learning rate: 0.00182 +2024-11-22 23:16:02.995922: train_loss -0.8022 +2024-11-22 23:16:02.996153: val_loss -0.7643 +2024-11-22 23:16:02.996231: Pseudo dice [0.8538] +2024-11-22 23:16:02.996305: Epoch time: 18.74 s +2024-11-22 23:16:03.908879: +2024-11-22 23:16:03.909214: Epoch 6797 +2024-11-22 23:16:03.909325: Current learning rate: 0.00182 +2024-11-22 23:16:22.060329: train_loss -0.8045 +2024-11-22 23:16:22.060565: val_loss -0.7648 +2024-11-22 23:16:22.060639: Pseudo dice [0.859] +2024-11-22 23:16:22.060713: Epoch time: 18.15 s +2024-11-22 23:16:22.964360: +2024-11-22 23:16:22.964589: Epoch 6798 +2024-11-22 23:16:22.964712: Current learning rate: 0.00182 +2024-11-22 23:16:41.399175: train_loss -0.8 +2024-11-22 23:16:41.399392: val_loss -0.7884 +2024-11-22 23:16:41.399467: Pseudo dice [0.8464] +2024-11-22 23:16:41.399544: Epoch time: 18.44 s +2024-11-22 23:16:42.304156: +2024-11-22 23:16:42.304379: Epoch 6799 +2024-11-22 23:16:42.304495: Current learning rate: 0.00181 +2024-11-22 23:17:00.483417: train_loss -0.8173 +2024-11-22 23:17:00.489015: val_loss -0.7844 +2024-11-22 23:17:00.489180: Pseudo dice [0.8467] +2024-11-22 23:17:00.489268: Epoch time: 18.18 s +2024-11-22 23:17:02.170381: +2024-11-22 23:17:02.170620: Epoch 6800 +2024-11-22 23:17:02.170730: Current learning rate: 0.00181 +2024-11-22 23:17:20.650220: train_loss -0.8072 +2024-11-22 23:17:20.650465: val_loss -0.7809 +2024-11-22 23:17:20.650542: Pseudo dice [0.8464] +2024-11-22 23:17:20.650617: Epoch time: 18.48 s +2024-11-22 23:17:21.560066: +2024-11-22 23:17:21.560358: Epoch 6801 +2024-11-22 23:17:21.560475: Current learning rate: 0.00181 +2024-11-22 23:17:39.679849: train_loss -0.8195 +2024-11-22 23:17:39.680084: val_loss -0.7657 +2024-11-22 23:17:39.680159: Pseudo dice [0.8445] +2024-11-22 23:17:39.680234: Epoch time: 18.12 s +2024-11-22 23:17:40.647235: +2024-11-22 23:17:40.647433: Epoch 6802 +2024-11-22 23:17:40.647540: Current learning rate: 0.00181 +2024-11-22 23:17:59.006231: train_loss -0.8114 +2024-11-22 23:17:59.006452: val_loss -0.7594 +2024-11-22 23:17:59.006528: Pseudo dice [0.8492] +2024-11-22 23:17:59.006605: Epoch time: 18.36 s +2024-11-22 23:17:59.911994: +2024-11-22 23:17:59.912213: Epoch 6803 +2024-11-22 23:17:59.912326: Current learning rate: 0.00181 +2024-11-22 23:18:17.725563: train_loss -0.8141 +2024-11-22 23:18:17.725805: val_loss -0.7582 +2024-11-22 23:18:17.725878: Pseudo dice [0.8589] +2024-11-22 23:18:17.725967: Epoch time: 17.81 s +2024-11-22 23:18:18.630185: +2024-11-22 23:18:18.630392: Epoch 6804 +2024-11-22 23:18:18.630501: Current learning rate: 0.00181 +2024-11-22 23:18:37.137808: train_loss -0.8226 +2024-11-22 23:18:37.138041: val_loss -0.7789 +2024-11-22 23:18:37.138117: Pseudo dice [0.8643] +2024-11-22 23:18:37.138191: Epoch time: 18.51 s +2024-11-22 23:18:38.083001: +2024-11-22 23:18:38.083201: Epoch 6805 +2024-11-22 23:18:38.083436: Current learning rate: 0.00181 +2024-11-22 23:18:56.685181: train_loss -0.8196 +2024-11-22 23:18:56.685401: val_loss -0.7595 +2024-11-22 23:18:56.685473: Pseudo dice [0.8578] +2024-11-22 23:18:56.685546: Epoch time: 18.6 s +2024-11-22 23:18:57.597954: +2024-11-22 23:18:57.598181: Epoch 6806 +2024-11-22 23:18:57.598294: Current learning rate: 0.00181 +2024-11-22 23:19:15.372896: train_loss -0.8147 +2024-11-22 23:19:15.373156: val_loss -0.7957 +2024-11-22 23:19:15.373230: Pseudo dice [0.8655] +2024-11-22 23:19:15.373309: Epoch time: 17.78 s +2024-11-22 23:19:16.397668: +2024-11-22 23:19:16.397887: Epoch 6807 +2024-11-22 23:19:16.398000: Current learning rate: 0.0018 +2024-11-22 23:19:34.955110: train_loss -0.8164 +2024-11-22 23:19:34.955327: val_loss -0.7961 +2024-11-22 23:19:34.955404: Pseudo dice [0.8602] +2024-11-22 23:19:34.955480: Epoch time: 18.56 s +2024-11-22 23:19:35.861442: +2024-11-22 23:19:35.861649: Epoch 6808 +2024-11-22 23:19:35.861756: Current learning rate: 0.0018 +2024-11-22 23:19:54.899869: train_loss -0.8034 +2024-11-22 23:19:54.900103: val_loss -0.778 +2024-11-22 23:19:54.900179: Pseudo dice [0.8587] +2024-11-22 23:19:54.900256: Epoch time: 19.04 s +2024-11-22 23:19:55.971689: +2024-11-22 23:19:55.971889: Epoch 6809 +2024-11-22 23:19:55.972005: Current learning rate: 0.0018 +2024-11-22 23:20:14.701695: train_loss -0.8172 +2024-11-22 23:20:14.702893: val_loss -0.7783 +2024-11-22 23:20:14.702988: Pseudo dice [0.8533] +2024-11-22 23:20:14.703074: Epoch time: 18.73 s +2024-11-22 23:20:15.621835: +2024-11-22 23:20:15.622062: Epoch 6810 +2024-11-22 23:20:15.622174: Current learning rate: 0.0018 +2024-11-22 23:20:33.703339: train_loss -0.8133 +2024-11-22 23:20:33.703588: val_loss -0.772 +2024-11-22 23:20:33.703662: Pseudo dice [0.8556] +2024-11-22 23:20:33.703740: Epoch time: 18.08 s +2024-11-22 23:20:34.608714: +2024-11-22 23:20:34.608929: Epoch 6811 +2024-11-22 23:20:34.609046: Current learning rate: 0.0018 +2024-11-22 23:20:53.099295: train_loss -0.813 +2024-11-22 23:20:53.099513: val_loss -0.7848 +2024-11-22 23:20:53.099585: Pseudo dice [0.8481] +2024-11-22 23:20:53.099659: Epoch time: 18.49 s +2024-11-22 23:20:54.409471: +2024-11-22 23:20:54.409708: Epoch 6812 +2024-11-22 23:20:54.409815: Current learning rate: 0.0018 +2024-11-22 23:21:13.299835: train_loss -0.8058 +2024-11-22 23:21:13.300148: val_loss -0.7398 +2024-11-22 23:21:13.300227: Pseudo dice [0.8463] +2024-11-22 23:21:13.300305: Epoch time: 18.89 s +2024-11-22 23:21:14.231116: +2024-11-22 23:21:14.231334: Epoch 6813 +2024-11-22 23:21:14.231444: Current learning rate: 0.0018 +2024-11-22 23:21:32.398776: train_loss -0.8103 +2024-11-22 23:21:32.399044: val_loss -0.742 +2024-11-22 23:21:32.399120: Pseudo dice [0.8497] +2024-11-22 23:21:32.399208: Epoch time: 18.17 s +2024-11-22 23:21:33.316763: +2024-11-22 23:21:33.316988: Epoch 6814 +2024-11-22 23:21:33.317102: Current learning rate: 0.00179 +2024-11-22 23:21:50.933018: train_loss -0.822 +2024-11-22 23:21:50.933243: val_loss -0.7711 +2024-11-22 23:21:50.933318: Pseudo dice [0.8595] +2024-11-22 23:21:50.933392: Epoch time: 17.62 s +2024-11-22 23:21:51.839514: +2024-11-22 23:21:51.839731: Epoch 6815 +2024-11-22 23:21:51.839840: Current learning rate: 0.00179 +2024-11-22 23:22:11.107701: train_loss -0.811 +2024-11-22 23:22:11.107938: val_loss -0.773 +2024-11-22 23:22:11.108020: Pseudo dice [0.8287] +2024-11-22 23:22:11.108094: Epoch time: 19.27 s +2024-11-22 23:22:12.012790: +2024-11-22 23:22:12.013070: Epoch 6816 +2024-11-22 23:22:12.013180: Current learning rate: 0.00179 +2024-11-22 23:22:30.126118: train_loss -0.8105 +2024-11-22 23:22:30.128549: val_loss -0.7539 +2024-11-22 23:22:30.128633: Pseudo dice [0.8396] +2024-11-22 23:22:30.128709: Epoch time: 18.11 s +2024-11-22 23:22:31.159164: +2024-11-22 23:22:31.159403: Epoch 6817 +2024-11-22 23:22:31.159515: Current learning rate: 0.00179 +2024-11-22 23:22:49.123565: train_loss -0.8142 +2024-11-22 23:22:49.123823: val_loss -0.7541 +2024-11-22 23:22:49.123907: Pseudo dice [0.836] +2024-11-22 23:22:49.124014: Epoch time: 17.97 s +2024-11-22 23:22:50.034204: +2024-11-22 23:22:50.034413: Epoch 6818 +2024-11-22 23:22:50.034557: Current learning rate: 0.00179 +2024-11-22 23:23:07.812919: train_loss -0.8109 +2024-11-22 23:23:07.813148: val_loss -0.7759 +2024-11-22 23:23:07.813223: Pseudo dice [0.8366] +2024-11-22 23:23:07.813298: Epoch time: 17.78 s +2024-11-22 23:23:08.712446: +2024-11-22 23:23:08.712688: Epoch 6819 +2024-11-22 23:23:08.712796: Current learning rate: 0.00179 +2024-11-22 23:23:26.460194: train_loss -0.8136 +2024-11-22 23:23:26.460413: val_loss -0.7739 +2024-11-22 23:23:26.460485: Pseudo dice [0.8591] +2024-11-22 23:23:26.460565: Epoch time: 17.75 s +2024-11-22 23:23:27.366133: +2024-11-22 23:23:27.366345: Epoch 6820 +2024-11-22 23:23:27.366453: Current learning rate: 0.00179 +2024-11-22 23:23:45.034026: train_loss -0.8197 +2024-11-22 23:23:45.034295: val_loss -0.7647 +2024-11-22 23:23:45.034376: Pseudo dice [0.8436] +2024-11-22 23:23:45.034458: Epoch time: 17.67 s +2024-11-22 23:23:45.984544: +2024-11-22 23:23:45.984757: Epoch 6821 +2024-11-22 23:23:45.984878: Current learning rate: 0.00178 +2024-11-22 23:24:04.130744: train_loss -0.8133 +2024-11-22 23:24:04.130998: val_loss -0.7681 +2024-11-22 23:24:04.131075: Pseudo dice [0.8472] +2024-11-22 23:24:04.131159: Epoch time: 18.15 s +2024-11-22 23:24:05.068985: +2024-11-22 23:24:05.069219: Epoch 6822 +2024-11-22 23:24:05.069328: Current learning rate: 0.00178 +2024-11-22 23:24:22.573781: train_loss -0.8124 +2024-11-22 23:24:22.574005: val_loss -0.8018 +2024-11-22 23:24:22.574089: Pseudo dice [0.8625] +2024-11-22 23:24:22.574165: Epoch time: 17.51 s +2024-11-22 23:24:23.474945: +2024-11-22 23:24:23.475154: Epoch 6823 +2024-11-22 23:24:23.475264: Current learning rate: 0.00178 +2024-11-22 23:24:41.462445: train_loss -0.8184 +2024-11-22 23:24:41.462910: val_loss -0.7754 +2024-11-22 23:24:41.463024: Pseudo dice [0.8599] +2024-11-22 23:24:41.463103: Epoch time: 17.99 s +2024-11-22 23:24:42.366805: +2024-11-22 23:24:42.367022: Epoch 6824 +2024-11-22 23:24:42.367126: Current learning rate: 0.00178 +2024-11-22 23:25:01.275638: train_loss -0.8202 +2024-11-22 23:25:01.275910: val_loss -0.7906 +2024-11-22 23:25:01.275998: Pseudo dice [0.8472] +2024-11-22 23:25:01.276086: Epoch time: 18.91 s +2024-11-22 23:25:02.182498: +2024-11-22 23:25:02.182731: Epoch 6825 +2024-11-22 23:25:02.182846: Current learning rate: 0.00178 +2024-11-22 23:25:21.206291: train_loss -0.8195 +2024-11-22 23:25:21.206522: val_loss -0.7594 +2024-11-22 23:25:21.206596: Pseudo dice [0.8439] +2024-11-22 23:25:21.206671: Epoch time: 19.02 s +2024-11-22 23:25:22.112955: +2024-11-22 23:25:22.113194: Epoch 6826 +2024-11-22 23:25:22.113303: Current learning rate: 0.00178 +2024-11-22 23:25:41.516380: train_loss -0.8109 +2024-11-22 23:25:41.516680: val_loss -0.7666 +2024-11-22 23:25:41.516761: Pseudo dice [0.8564] +2024-11-22 23:25:41.516837: Epoch time: 19.4 s +2024-11-22 23:25:42.422125: +2024-11-22 23:25:42.422333: Epoch 6827 +2024-11-22 23:25:42.422445: Current learning rate: 0.00178 +2024-11-22 23:26:01.089398: train_loss -0.8206 +2024-11-22 23:26:01.089705: val_loss -0.7958 +2024-11-22 23:26:01.089783: Pseudo dice [0.8614] +2024-11-22 23:26:01.089865: Epoch time: 18.67 s +2024-11-22 23:26:01.998017: +2024-11-22 23:26:01.998305: Epoch 6828 +2024-11-22 23:26:01.998411: Current learning rate: 0.00178 +2024-11-22 23:26:20.086990: train_loss -0.8199 +2024-11-22 23:26:20.087259: val_loss -0.725 +2024-11-22 23:26:20.087372: Pseudo dice [0.8494] +2024-11-22 23:26:20.087449: Epoch time: 18.09 s +2024-11-22 23:26:20.989724: +2024-11-22 23:26:20.989968: Epoch 6829 +2024-11-22 23:26:20.990086: Current learning rate: 0.00177 +2024-11-22 23:26:40.560396: train_loss -0.8089 +2024-11-22 23:26:40.560613: val_loss -0.7604 +2024-11-22 23:26:40.560687: Pseudo dice [0.8411] +2024-11-22 23:26:40.560763: Epoch time: 19.57 s +2024-11-22 23:26:41.470031: +2024-11-22 23:26:41.470408: Epoch 6830 +2024-11-22 23:26:41.470520: Current learning rate: 0.00177 +2024-11-22 23:27:00.250173: train_loss -0.8135 +2024-11-22 23:27:00.250399: val_loss -0.7846 +2024-11-22 23:27:00.252651: Pseudo dice [0.859] +2024-11-22 23:27:00.252773: Epoch time: 18.78 s +2024-11-22 23:27:01.191375: +2024-11-22 23:27:01.191610: Epoch 6831 +2024-11-22 23:27:01.191724: Current learning rate: 0.00177 +2024-11-22 23:27:21.072295: train_loss -0.8105 +2024-11-22 23:27:21.074749: val_loss -0.7668 +2024-11-22 23:27:21.074889: Pseudo dice [0.854] +2024-11-22 23:27:21.074979: Epoch time: 19.88 s +2024-11-22 23:27:21.996875: +2024-11-22 23:27:21.997099: Epoch 6832 +2024-11-22 23:27:21.997213: Current learning rate: 0.00177 +2024-11-22 23:27:41.068967: train_loss -0.8155 +2024-11-22 23:27:41.069204: val_loss -0.7903 +2024-11-22 23:27:41.069277: Pseudo dice [0.8438] +2024-11-22 23:27:41.069352: Epoch time: 19.07 s +2024-11-22 23:27:41.976435: +2024-11-22 23:27:41.976651: Epoch 6833 +2024-11-22 23:27:41.976764: Current learning rate: 0.00177 +2024-11-22 23:28:00.085188: train_loss -0.8088 +2024-11-22 23:28:00.085427: val_loss -0.7623 +2024-11-22 23:28:00.085503: Pseudo dice [0.8451] +2024-11-22 23:28:00.085582: Epoch time: 18.11 s +2024-11-22 23:28:01.052877: +2024-11-22 23:28:01.053093: Epoch 6834 +2024-11-22 23:28:01.053201: Current learning rate: 0.00177 +2024-11-22 23:28:19.468069: train_loss -0.8153 +2024-11-22 23:28:19.468305: val_loss -0.7852 +2024-11-22 23:28:19.468381: Pseudo dice [0.8435] +2024-11-22 23:28:19.468460: Epoch time: 18.42 s +2024-11-22 23:28:20.758611: +2024-11-22 23:28:20.758832: Epoch 6835 +2024-11-22 23:28:20.758946: Current learning rate: 0.00177 +2024-11-22 23:28:39.643538: train_loss -0.8225 +2024-11-22 23:28:39.644032: val_loss -0.7846 +2024-11-22 23:28:39.644129: Pseudo dice [0.8518] +2024-11-22 23:28:39.644210: Epoch time: 18.89 s +2024-11-22 23:28:40.555948: +2024-11-22 23:28:40.556198: Epoch 6836 +2024-11-22 23:28:40.556310: Current learning rate: 0.00176 +2024-11-22 23:28:59.203633: train_loss -0.8167 +2024-11-22 23:28:59.203863: val_loss -0.7885 +2024-11-22 23:28:59.203938: Pseudo dice [0.8542] +2024-11-22 23:28:59.204021: Epoch time: 18.65 s +2024-11-22 23:29:00.138472: +2024-11-22 23:29:00.138694: Epoch 6837 +2024-11-22 23:29:00.138800: Current learning rate: 0.00176 +2024-11-22 23:29:19.383804: train_loss -0.813 +2024-11-22 23:29:19.384061: val_loss -0.7806 +2024-11-22 23:29:19.384150: Pseudo dice [0.8583] +2024-11-22 23:29:19.384236: Epoch time: 19.25 s +2024-11-22 23:29:20.284628: +2024-11-22 23:29:20.284852: Epoch 6838 +2024-11-22 23:29:20.284962: Current learning rate: 0.00176 +2024-11-22 23:29:38.840146: train_loss -0.8154 +2024-11-22 23:29:38.840386: val_loss -0.7642 +2024-11-22 23:29:38.840465: Pseudo dice [0.8528] +2024-11-22 23:29:38.840546: Epoch time: 18.56 s +2024-11-22 23:29:39.789875: +2024-11-22 23:29:39.790106: Epoch 6839 +2024-11-22 23:29:39.790231: Current learning rate: 0.00176 +2024-11-22 23:29:58.537926: train_loss -0.8149 +2024-11-22 23:29:58.538490: val_loss -0.792 +2024-11-22 23:29:58.538572: Pseudo dice [0.8451] +2024-11-22 23:29:58.538647: Epoch time: 18.75 s +2024-11-22 23:29:59.480301: +2024-11-22 23:29:59.480528: Epoch 6840 +2024-11-22 23:29:59.480642: Current learning rate: 0.00176 +2024-11-22 23:30:18.123440: train_loss -0.8153 +2024-11-22 23:30:18.123689: val_loss -0.7815 +2024-11-22 23:30:18.123773: Pseudo dice [0.8498] +2024-11-22 23:30:18.123861: Epoch time: 18.64 s +2024-11-22 23:30:19.033748: +2024-11-22 23:30:19.033955: Epoch 6841 +2024-11-22 23:30:19.034072: Current learning rate: 0.00176 +2024-11-22 23:30:38.737365: train_loss -0.8117 +2024-11-22 23:30:38.739808: val_loss -0.7422 +2024-11-22 23:30:38.739896: Pseudo dice [0.839] +2024-11-22 23:30:38.739989: Epoch time: 19.7 s +2024-11-22 23:30:39.672690: +2024-11-22 23:30:39.672911: Epoch 6842 +2024-11-22 23:30:39.673035: Current learning rate: 0.00176 +2024-11-22 23:30:59.034528: train_loss -0.8084 +2024-11-22 23:30:59.034791: val_loss -0.7751 +2024-11-22 23:30:59.034868: Pseudo dice [0.8588] +2024-11-22 23:30:59.034948: Epoch time: 19.36 s +2024-11-22 23:30:59.967472: +2024-11-22 23:30:59.967696: Epoch 6843 +2024-11-22 23:30:59.967804: Current learning rate: 0.00175 +2024-11-22 23:31:17.927117: train_loss -0.8044 +2024-11-22 23:31:17.927334: val_loss -0.7781 +2024-11-22 23:31:17.927413: Pseudo dice [0.8658] +2024-11-22 23:31:17.927486: Epoch time: 17.96 s +2024-11-22 23:31:18.827625: +2024-11-22 23:31:18.827849: Epoch 6844 +2024-11-22 23:31:18.827965: Current learning rate: 0.00175 +2024-11-22 23:31:37.452875: train_loss -0.8139 +2024-11-22 23:31:37.453106: val_loss -0.7768 +2024-11-22 23:31:37.453182: Pseudo dice [0.849] +2024-11-22 23:31:37.453254: Epoch time: 18.63 s +2024-11-22 23:31:38.362683: +2024-11-22 23:31:38.362911: Epoch 6845 +2024-11-22 23:31:38.363035: Current learning rate: 0.00175 +2024-11-22 23:31:57.347909: train_loss -0.8086 +2024-11-22 23:31:57.348158: val_loss -0.7764 +2024-11-22 23:31:57.348238: Pseudo dice [0.8562] +2024-11-22 23:31:57.348319: Epoch time: 18.99 s +2024-11-22 23:31:58.261548: +2024-11-22 23:31:58.261765: Epoch 6846 +2024-11-22 23:31:58.261876: Current learning rate: 0.00175 +2024-11-22 23:32:17.316453: train_loss -0.8115 +2024-11-22 23:32:17.316958: val_loss -0.763 +2024-11-22 23:32:17.317065: Pseudo dice [0.8416] +2024-11-22 23:32:17.317156: Epoch time: 19.06 s +2024-11-22 23:32:18.217641: +2024-11-22 23:32:18.217924: Epoch 6847 +2024-11-22 23:32:18.218039: Current learning rate: 0.00175 +2024-11-22 23:32:36.681155: train_loss -0.8109 +2024-11-22 23:32:36.681376: val_loss -0.7869 +2024-11-22 23:32:36.681465: Pseudo dice [0.8487] +2024-11-22 23:32:36.681541: Epoch time: 18.46 s +2024-11-22 23:32:37.586312: +2024-11-22 23:32:37.586535: Epoch 6848 +2024-11-22 23:32:37.586646: Current learning rate: 0.00175 +2024-11-22 23:32:56.394309: train_loss -0.8114 +2024-11-22 23:32:56.394532: val_loss -0.8024 +2024-11-22 23:32:56.394618: Pseudo dice [0.8547] +2024-11-22 23:32:56.394701: Epoch time: 18.81 s +2024-11-22 23:32:57.296652: +2024-11-22 23:32:57.296883: Epoch 6849 +2024-11-22 23:32:57.297005: Current learning rate: 0.00175 +2024-11-22 23:33:14.959533: train_loss -0.8137 +2024-11-22 23:33:14.959782: val_loss -0.7802 +2024-11-22 23:33:14.959857: Pseudo dice [0.8672] +2024-11-22 23:33:14.959938: Epoch time: 17.66 s +2024-11-22 23:33:16.184515: +2024-11-22 23:33:16.184740: Epoch 6850 +2024-11-22 23:33:16.184850: Current learning rate: 0.00175 +2024-11-22 23:33:35.707972: train_loss -0.8163 +2024-11-22 23:33:35.708196: val_loss -0.7755 +2024-11-22 23:33:35.708273: Pseudo dice [0.8641] +2024-11-22 23:33:35.708347: Epoch time: 19.52 s +2024-11-22 23:33:36.822741: +2024-11-22 23:33:36.822974: Epoch 6851 +2024-11-22 23:33:36.823088: Current learning rate: 0.00174 +2024-11-22 23:33:56.277563: train_loss -0.8074 +2024-11-22 23:33:56.277772: val_loss -0.7479 +2024-11-22 23:33:56.277846: Pseudo dice [0.8462] +2024-11-22 23:33:56.277920: Epoch time: 19.46 s +2024-11-22 23:33:57.215230: +2024-11-22 23:33:57.215463: Epoch 6852 +2024-11-22 23:33:57.215577: Current learning rate: 0.00174 +2024-11-22 23:34:15.776739: train_loss -0.812 +2024-11-22 23:34:15.776986: val_loss -0.7761 +2024-11-22 23:34:15.777072: Pseudo dice [0.8513] +2024-11-22 23:34:15.777150: Epoch time: 18.56 s +2024-11-22 23:34:16.758553: +2024-11-22 23:34:16.758837: Epoch 6853 +2024-11-22 23:34:16.758954: Current learning rate: 0.00174 +2024-11-22 23:34:34.890642: train_loss -0.8155 +2024-11-22 23:34:34.890890: val_loss -0.8062 +2024-11-22 23:34:34.890967: Pseudo dice [0.8692] +2024-11-22 23:34:34.891051: Epoch time: 18.13 s +2024-11-22 23:34:35.795417: +2024-11-22 23:34:35.795629: Epoch 6854 +2024-11-22 23:34:35.795742: Current learning rate: 0.00174 +2024-11-22 23:34:54.415368: train_loss -0.8165 +2024-11-22 23:34:54.415600: val_loss -0.7942 +2024-11-22 23:34:54.415675: Pseudo dice [0.8506] +2024-11-22 23:34:54.417937: Epoch time: 18.62 s +2024-11-22 23:34:55.424348: +2024-11-22 23:34:55.424563: Epoch 6855 +2024-11-22 23:34:55.424688: Current learning rate: 0.00174 +2024-11-22 23:35:13.181763: train_loss -0.8075 +2024-11-22 23:35:13.181977: val_loss -0.7869 +2024-11-22 23:35:13.182058: Pseudo dice [0.8561] +2024-11-22 23:35:13.182135: Epoch time: 17.76 s +2024-11-22 23:35:14.090883: +2024-11-22 23:35:14.091099: Epoch 6856 +2024-11-22 23:35:14.091209: Current learning rate: 0.00174 +2024-11-22 23:35:33.028046: train_loss -0.8222 +2024-11-22 23:35:33.028355: val_loss -0.7897 +2024-11-22 23:35:33.028431: Pseudo dice [0.858] +2024-11-22 23:35:33.028510: Epoch time: 18.94 s +2024-11-22 23:35:33.937512: +2024-11-22 23:35:33.937745: Epoch 6857 +2024-11-22 23:35:33.937856: Current learning rate: 0.00174 +2024-11-22 23:35:51.558558: train_loss -0.8188 +2024-11-22 23:35:51.558813: val_loss -0.7721 +2024-11-22 23:35:51.558892: Pseudo dice [0.8419] +2024-11-22 23:35:51.558976: Epoch time: 17.62 s +2024-11-22 23:35:52.462463: +2024-11-22 23:35:52.462686: Epoch 6858 +2024-11-22 23:35:52.462796: Current learning rate: 0.00173 +2024-11-22 23:36:11.550248: train_loss -0.8149 +2024-11-22 23:36:11.550483: val_loss -0.7815 +2024-11-22 23:36:11.550562: Pseudo dice [0.8419] +2024-11-22 23:36:11.550639: Epoch time: 19.09 s +2024-11-22 23:36:12.458365: +2024-11-22 23:36:12.458579: Epoch 6859 +2024-11-22 23:36:12.458693: Current learning rate: 0.00173 +2024-11-22 23:36:30.854440: train_loss -0.8169 +2024-11-22 23:36:30.854683: val_loss -0.77 +2024-11-22 23:36:30.854761: Pseudo dice [0.8435] +2024-11-22 23:36:30.854837: Epoch time: 18.4 s +2024-11-22 23:36:31.757584: +2024-11-22 23:36:31.757812: Epoch 6860 +2024-11-22 23:36:31.757918: Current learning rate: 0.00173 +2024-11-22 23:36:50.330125: train_loss -0.8164 +2024-11-22 23:36:50.335549: val_loss -0.7585 +2024-11-22 23:36:50.335629: Pseudo dice [0.8524] +2024-11-22 23:36:50.335714: Epoch time: 18.57 s +2024-11-22 23:36:51.241801: +2024-11-22 23:36:51.242021: Epoch 6861 +2024-11-22 23:36:51.242129: Current learning rate: 0.00173 +2024-11-22 23:37:10.054636: train_loss -0.8161 +2024-11-22 23:37:10.054877: val_loss -0.7939 +2024-11-22 23:37:10.054952: Pseudo dice [0.8656] +2024-11-22 23:37:10.055037: Epoch time: 18.81 s +2024-11-22 23:37:10.962002: +2024-11-22 23:37:10.962219: Epoch 6862 +2024-11-22 23:37:10.962325: Current learning rate: 0.00173 +2024-11-22 23:37:29.441751: train_loss -0.8089 +2024-11-22 23:37:29.442005: val_loss -0.762 +2024-11-22 23:37:29.442084: Pseudo dice [0.8694] +2024-11-22 23:37:29.442159: Epoch time: 18.48 s +2024-11-22 23:37:30.390591: +2024-11-22 23:37:30.390814: Epoch 6863 +2024-11-22 23:37:30.390924: Current learning rate: 0.00173 +2024-11-22 23:37:48.487564: train_loss -0.8149 +2024-11-22 23:37:48.487789: val_loss -0.7741 +2024-11-22 23:37:48.487866: Pseudo dice [0.8693] +2024-11-22 23:37:48.487942: Epoch time: 18.1 s +2024-11-22 23:37:49.417325: +2024-11-22 23:37:49.417519: Epoch 6864 +2024-11-22 23:37:49.417624: Current learning rate: 0.00173 +2024-11-22 23:38:08.286281: train_loss -0.8112 +2024-11-22 23:38:08.286528: val_loss -0.78 +2024-11-22 23:38:08.286604: Pseudo dice [0.8606] +2024-11-22 23:38:08.286683: Epoch time: 18.87 s +2024-11-22 23:38:09.190866: +2024-11-22 23:38:09.191135: Epoch 6865 +2024-11-22 23:38:09.191246: Current learning rate: 0.00172 +2024-11-22 23:38:27.683921: train_loss -0.8149 +2024-11-22 23:38:27.684260: val_loss -0.7818 +2024-11-22 23:38:27.684334: Pseudo dice [0.8547] +2024-11-22 23:38:27.684412: Epoch time: 18.49 s +2024-11-22 23:38:28.590175: +2024-11-22 23:38:28.590449: Epoch 6866 +2024-11-22 23:38:28.590562: Current learning rate: 0.00172 +2024-11-22 23:38:47.066014: train_loss -0.8049 +2024-11-22 23:38:47.066241: val_loss -0.7779 +2024-11-22 23:38:47.066322: Pseudo dice [0.8459] +2024-11-22 23:38:47.066401: Epoch time: 18.48 s +2024-11-22 23:38:48.116507: +2024-11-22 23:38:48.116764: Epoch 6867 +2024-11-22 23:38:48.116877: Current learning rate: 0.00172 +2024-11-22 23:39:07.437098: train_loss -0.8045 +2024-11-22 23:39:07.437306: val_loss -0.75 +2024-11-22 23:39:07.437386: Pseudo dice [0.834] +2024-11-22 23:39:07.437471: Epoch time: 19.32 s +2024-11-22 23:39:08.353702: +2024-11-22 23:39:08.353923: Epoch 6868 +2024-11-22 23:39:08.354035: Current learning rate: 0.00172 +2024-11-22 23:39:26.465989: train_loss -0.8121 +2024-11-22 23:39:26.466326: val_loss -0.7932 +2024-11-22 23:39:26.466400: Pseudo dice [0.8449] +2024-11-22 23:39:26.466477: Epoch time: 18.11 s +2024-11-22 23:39:27.773260: +2024-11-22 23:39:27.773491: Epoch 6869 +2024-11-22 23:39:27.773597: Current learning rate: 0.00172 +2024-11-22 23:39:46.922735: train_loss -0.8076 +2024-11-22 23:39:46.923034: val_loss -0.7587 +2024-11-22 23:39:46.923111: Pseudo dice [0.8478] +2024-11-22 23:39:46.923187: Epoch time: 19.15 s +2024-11-22 23:39:47.843211: +2024-11-22 23:39:47.843440: Epoch 6870 +2024-11-22 23:39:47.843555: Current learning rate: 0.00172 +2024-11-22 23:40:06.330843: train_loss -0.8125 +2024-11-22 23:40:06.331078: val_loss -0.7773 +2024-11-22 23:40:06.331176: Pseudo dice [0.8522] +2024-11-22 23:40:06.331252: Epoch time: 18.49 s +2024-11-22 23:40:07.223940: +2024-11-22 23:40:07.224160: Epoch 6871 +2024-11-22 23:40:07.224273: Current learning rate: 0.00172 +2024-11-22 23:40:25.384820: train_loss -0.8162 +2024-11-22 23:40:25.385084: val_loss -0.7856 +2024-11-22 23:40:25.385157: Pseudo dice [0.8507] +2024-11-22 23:40:25.385237: Epoch time: 18.16 s +2024-11-22 23:40:26.289059: +2024-11-22 23:40:26.289278: Epoch 6872 +2024-11-22 23:40:26.289387: Current learning rate: 0.00172 +2024-11-22 23:40:45.039863: train_loss -0.8029 +2024-11-22 23:40:45.040114: val_loss -0.7476 +2024-11-22 23:40:45.040193: Pseudo dice [0.8455] +2024-11-22 23:40:45.040349: Epoch time: 18.75 s +2024-11-22 23:40:45.973090: +2024-11-22 23:40:45.973315: Epoch 6873 +2024-11-22 23:40:45.973428: Current learning rate: 0.00171 +2024-11-22 23:41:05.098472: train_loss -0.8008 +2024-11-22 23:41:05.098708: val_loss -0.7691 +2024-11-22 23:41:05.098785: Pseudo dice [0.8492] +2024-11-22 23:41:05.098860: Epoch time: 19.13 s +2024-11-22 23:41:06.005182: +2024-11-22 23:41:06.005398: Epoch 6874 +2024-11-22 23:41:06.005506: Current learning rate: 0.00171 +2024-11-22 23:41:23.856177: train_loss -0.8039 +2024-11-22 23:41:23.856417: val_loss -0.7833 +2024-11-22 23:41:23.856492: Pseudo dice [0.8571] +2024-11-22 23:41:23.856566: Epoch time: 17.85 s +2024-11-22 23:41:24.795017: +2024-11-22 23:41:24.795227: Epoch 6875 +2024-11-22 23:41:24.795341: Current learning rate: 0.00171 +2024-11-22 23:41:44.095589: train_loss -0.8041 +2024-11-22 23:41:44.095837: val_loss -0.7646 +2024-11-22 23:41:44.095910: Pseudo dice [0.8572] +2024-11-22 23:41:44.096000: Epoch time: 19.3 s +2024-11-22 23:41:45.007720: +2024-11-22 23:41:45.007931: Epoch 6876 +2024-11-22 23:41:45.008042: Current learning rate: 0.00171 +2024-11-22 23:42:03.090047: train_loss -0.8062 +2024-11-22 23:42:03.090272: val_loss -0.7715 +2024-11-22 23:42:03.090354: Pseudo dice [0.8388] +2024-11-22 23:42:03.090431: Epoch time: 18.08 s +2024-11-22 23:42:03.989652: +2024-11-22 23:42:03.989852: Epoch 6877 +2024-11-22 23:42:03.990119: Current learning rate: 0.00171 +2024-11-22 23:42:22.487937: train_loss -0.8185 +2024-11-22 23:42:22.488189: val_loss -0.76 +2024-11-22 23:42:22.490507: Pseudo dice [0.8319] +2024-11-22 23:42:22.490616: Epoch time: 18.5 s +2024-11-22 23:42:23.418899: +2024-11-22 23:42:23.419116: Epoch 6878 +2024-11-22 23:42:23.419228: Current learning rate: 0.00171 +2024-11-22 23:42:41.794788: train_loss -0.8181 +2024-11-22 23:42:41.795036: val_loss -0.767 +2024-11-22 23:42:41.795110: Pseudo dice [0.8661] +2024-11-22 23:42:41.795184: Epoch time: 18.38 s +2024-11-22 23:42:42.793515: +2024-11-22 23:42:42.793714: Epoch 6879 +2024-11-22 23:42:42.793820: Current learning rate: 0.00171 +2024-11-22 23:43:00.955970: train_loss -0.8171 +2024-11-22 23:43:00.956232: val_loss -0.7625 +2024-11-22 23:43:00.956306: Pseudo dice [0.8502] +2024-11-22 23:43:00.956387: Epoch time: 18.16 s +2024-11-22 23:43:01.891131: +2024-11-22 23:43:01.891361: Epoch 6880 +2024-11-22 23:43:01.891471: Current learning rate: 0.0017 +2024-11-22 23:43:21.499848: train_loss -0.8143 +2024-11-22 23:43:21.500330: val_loss -0.7697 +2024-11-22 23:43:21.500431: Pseudo dice [0.846] +2024-11-22 23:43:21.500506: Epoch time: 19.61 s +2024-11-22 23:43:22.405327: +2024-11-22 23:43:22.405557: Epoch 6881 +2024-11-22 23:43:22.405666: Current learning rate: 0.0017 +2024-11-22 23:43:39.646411: train_loss -0.8114 +2024-11-22 23:43:39.646872: val_loss -0.7724 +2024-11-22 23:43:39.646970: Pseudo dice [0.8498] +2024-11-22 23:43:39.647098: Epoch time: 17.24 s +2024-11-22 23:43:40.546081: +2024-11-22 23:43:40.546301: Epoch 6882 +2024-11-22 23:43:40.546417: Current learning rate: 0.0017 +2024-11-22 23:43:58.439462: train_loss -0.816 +2024-11-22 23:43:58.439724: val_loss -0.7883 +2024-11-22 23:43:58.439804: Pseudo dice [0.8534] +2024-11-22 23:43:58.439890: Epoch time: 17.89 s +2024-11-22 23:43:59.528377: +2024-11-22 23:43:59.528605: Epoch 6883 +2024-11-22 23:43:59.528712: Current learning rate: 0.0017 +2024-11-22 23:44:17.627503: train_loss -0.815 +2024-11-22 23:44:17.627714: val_loss -0.7799 +2024-11-22 23:44:17.627788: Pseudo dice [0.8506] +2024-11-22 23:44:17.627864: Epoch time: 18.1 s +2024-11-22 23:44:18.540044: +2024-11-22 23:44:18.540251: Epoch 6884 +2024-11-22 23:44:18.540357: Current learning rate: 0.0017 +2024-11-22 23:44:36.262672: train_loss -0.8134 +2024-11-22 23:44:36.262895: val_loss -0.7845 +2024-11-22 23:44:36.263001: Pseudo dice [0.8706] +2024-11-22 23:44:36.263091: Epoch time: 17.72 s +2024-11-22 23:44:37.178685: +2024-11-22 23:44:37.178898: Epoch 6885 +2024-11-22 23:44:37.179010: Current learning rate: 0.0017 +2024-11-22 23:44:56.017725: train_loss -0.8213 +2024-11-22 23:44:56.017951: val_loss -0.779 +2024-11-22 23:44:56.018032: Pseudo dice [0.8616] +2024-11-22 23:44:56.018108: Epoch time: 18.84 s +2024-11-22 23:44:57.031384: +2024-11-22 23:44:57.031619: Epoch 6886 +2024-11-22 23:44:57.031736: Current learning rate: 0.0017 +2024-11-22 23:45:16.009216: train_loss -0.8066 +2024-11-22 23:45:16.009463: val_loss -0.7753 +2024-11-22 23:45:16.009534: Pseudo dice [0.8507] +2024-11-22 23:45:16.009612: Epoch time: 18.98 s +2024-11-22 23:45:16.921858: +2024-11-22 23:45:16.922078: Epoch 6887 +2024-11-22 23:45:16.922198: Current learning rate: 0.00169 +2024-11-22 23:45:36.644825: train_loss -0.8071 +2024-11-22 23:45:36.645059: val_loss -0.776 +2024-11-22 23:45:36.645180: Pseudo dice [0.854] +2024-11-22 23:45:36.645255: Epoch time: 19.72 s +2024-11-22 23:45:37.551759: +2024-11-22 23:45:37.551953: Epoch 6888 +2024-11-22 23:45:37.552069: Current learning rate: 0.00169 +2024-11-22 23:45:56.523520: train_loss -0.8155 +2024-11-22 23:45:56.523746: val_loss -0.7727 +2024-11-22 23:45:56.523822: Pseudo dice [0.84] +2024-11-22 23:45:56.523901: Epoch time: 18.97 s +2024-11-22 23:45:57.434333: +2024-11-22 23:45:57.434731: Epoch 6889 +2024-11-22 23:45:57.434842: Current learning rate: 0.00169 +2024-11-22 23:46:15.978828: train_loss -0.8101 +2024-11-22 23:46:15.979076: val_loss -0.7787 +2024-11-22 23:46:15.979149: Pseudo dice [0.8479] +2024-11-22 23:46:15.979221: Epoch time: 18.55 s +2024-11-22 23:46:16.895989: +2024-11-22 23:46:16.896220: Epoch 6890 +2024-11-22 23:46:16.896328: Current learning rate: 0.00169 +2024-11-22 23:46:35.321259: train_loss -0.8178 +2024-11-22 23:46:35.321480: val_loss -0.7966 +2024-11-22 23:46:35.321555: Pseudo dice [0.8612] +2024-11-22 23:46:35.321629: Epoch time: 18.43 s +2024-11-22 23:46:36.235414: +2024-11-22 23:46:36.235656: Epoch 6891 +2024-11-22 23:46:36.235811: Current learning rate: 0.00169 +2024-11-22 23:46:54.046320: train_loss -0.8234 +2024-11-22 23:46:54.048728: val_loss -0.7994 +2024-11-22 23:46:54.048855: Pseudo dice [0.8669] +2024-11-22 23:46:54.048937: Epoch time: 17.81 s +2024-11-22 23:46:55.394420: +2024-11-22 23:46:55.394631: Epoch 6892 +2024-11-22 23:46:55.394739: Current learning rate: 0.00169 +2024-11-22 23:47:14.600302: train_loss -0.8105 +2024-11-22 23:47:14.600543: val_loss -0.7869 +2024-11-22 23:47:14.600619: Pseudo dice [0.8597] +2024-11-22 23:47:14.600704: Epoch time: 19.21 s +2024-11-22 23:47:15.509382: +2024-11-22 23:47:15.509603: Epoch 6893 +2024-11-22 23:47:15.509709: Current learning rate: 0.00169 +2024-11-22 23:47:33.586978: train_loss -0.816 +2024-11-22 23:47:33.587228: val_loss -0.7868 +2024-11-22 23:47:33.587307: Pseudo dice [0.8492] +2024-11-22 23:47:33.587384: Epoch time: 18.08 s +2024-11-22 23:47:34.498082: +2024-11-22 23:47:34.498300: Epoch 6894 +2024-11-22 23:47:34.498407: Current learning rate: 0.00168 +2024-11-22 23:47:52.807754: train_loss -0.8198 +2024-11-22 23:47:52.808080: val_loss -0.7752 +2024-11-22 23:47:52.808164: Pseudo dice [0.8559] +2024-11-22 23:47:52.808251: Epoch time: 18.31 s +2024-11-22 23:47:53.722774: +2024-11-22 23:47:53.723001: Epoch 6895 +2024-11-22 23:47:53.723115: Current learning rate: 0.00168 +2024-11-22 23:48:12.171666: train_loss -0.8238 +2024-11-22 23:48:12.171893: val_loss -0.7677 +2024-11-22 23:48:12.171968: Pseudo dice [0.8475] +2024-11-22 23:48:12.172051: Epoch time: 18.45 s +2024-11-22 23:48:13.179814: +2024-11-22 23:48:13.180024: Epoch 6896 +2024-11-22 23:48:13.180140: Current learning rate: 0.00168 +2024-11-22 23:48:31.169130: train_loss -0.8262 +2024-11-22 23:48:31.169346: val_loss -0.799 +2024-11-22 23:48:31.169423: Pseudo dice [0.8655] +2024-11-22 23:48:31.169499: Epoch time: 17.99 s +2024-11-22 23:48:32.074105: +2024-11-22 23:48:32.074339: Epoch 6897 +2024-11-22 23:48:32.074456: Current learning rate: 0.00168 +2024-11-22 23:48:50.053932: train_loss -0.8194 +2024-11-22 23:48:50.054226: val_loss -0.7744 +2024-11-22 23:48:50.054305: Pseudo dice [0.857] +2024-11-22 23:48:50.054390: Epoch time: 17.98 s +2024-11-22 23:48:51.052821: +2024-11-22 23:48:51.053056: Epoch 6898 +2024-11-22 23:48:51.053161: Current learning rate: 0.00168 +2024-11-22 23:49:10.881115: train_loss -0.8148 +2024-11-22 23:49:10.881358: val_loss -0.7915 +2024-11-22 23:49:10.881432: Pseudo dice [0.8651] +2024-11-22 23:49:10.881511: Epoch time: 19.83 s +2024-11-22 23:49:11.795044: +2024-11-22 23:49:11.795264: Epoch 6899 +2024-11-22 23:49:11.795374: Current learning rate: 0.00168 +2024-11-22 23:49:30.685721: train_loss -0.8137 +2024-11-22 23:49:30.685942: val_loss -0.7633 +2024-11-22 23:49:30.686027: Pseudo dice [0.8545] +2024-11-22 23:49:30.686103: Epoch time: 18.89 s +2024-11-22 23:49:31.992694: +2024-11-22 23:49:31.992917: Epoch 6900 +2024-11-22 23:49:31.993032: Current learning rate: 0.00168 +2024-11-22 23:49:49.665637: train_loss -0.8163 +2024-11-22 23:49:49.665899: val_loss -0.7778 +2024-11-22 23:49:49.665976: Pseudo dice [0.8465] +2024-11-22 23:49:49.666063: Epoch time: 17.67 s +2024-11-22 23:49:50.567857: +2024-11-22 23:49:50.568069: Epoch 6901 +2024-11-22 23:49:50.568201: Current learning rate: 0.00168 +2024-11-22 23:50:08.869918: train_loss -0.8172 +2024-11-22 23:50:08.870178: val_loss -0.7885 +2024-11-22 23:50:08.870254: Pseudo dice [0.8525] +2024-11-22 23:50:08.870333: Epoch time: 18.3 s +2024-11-22 23:50:09.773432: +2024-11-22 23:50:09.773649: Epoch 6902 +2024-11-22 23:50:09.773760: Current learning rate: 0.00167 +2024-11-22 23:50:28.615236: train_loss -0.8146 +2024-11-22 23:50:28.615454: val_loss -0.7786 +2024-11-22 23:50:28.615528: Pseudo dice [0.849] +2024-11-22 23:50:28.615602: Epoch time: 18.84 s +2024-11-22 23:50:29.522854: +2024-11-22 23:50:29.523064: Epoch 6903 +2024-11-22 23:50:29.523321: Current learning rate: 0.00167 +2024-11-22 23:50:48.546023: train_loss -0.8163 +2024-11-22 23:50:48.551676: val_loss -0.7912 +2024-11-22 23:50:48.551792: Pseudo dice [0.8574] +2024-11-22 23:50:48.551875: Epoch time: 19.02 s +2024-11-22 23:50:49.520986: +2024-11-22 23:50:49.521246: Epoch 6904 +2024-11-22 23:50:49.521365: Current learning rate: 0.00167 +2024-11-22 23:51:07.197269: train_loss -0.8151 +2024-11-22 23:51:07.202909: val_loss -0.7976 +2024-11-22 23:51:07.203026: Pseudo dice [0.8583] +2024-11-22 23:51:07.203117: Epoch time: 17.68 s +2024-11-22 23:51:08.131859: +2024-11-22 23:51:08.132087: Epoch 6905 +2024-11-22 23:51:08.132195: Current learning rate: 0.00167 +2024-11-22 23:51:27.821478: train_loss -0.8146 +2024-11-22 23:51:27.821732: val_loss -0.7875 +2024-11-22 23:51:27.821809: Pseudo dice [0.8595] +2024-11-22 23:51:27.821889: Epoch time: 19.69 s +2024-11-22 23:51:28.737307: +2024-11-22 23:51:28.737504: Epoch 6906 +2024-11-22 23:51:28.737612: Current learning rate: 0.00167 +2024-11-22 23:51:48.158241: train_loss -0.8221 +2024-11-22 23:51:48.158498: val_loss -0.7632 +2024-11-22 23:51:48.158597: Pseudo dice [0.8371] +2024-11-22 23:51:48.158685: Epoch time: 19.42 s +2024-11-22 23:51:49.074033: +2024-11-22 23:51:49.074296: Epoch 6907 +2024-11-22 23:51:49.074413: Current learning rate: 0.00167 +2024-11-22 23:52:07.546010: train_loss -0.8195 +2024-11-22 23:52:07.546231: val_loss -0.7866 +2024-11-22 23:52:07.546305: Pseudo dice [0.8488] +2024-11-22 23:52:07.546381: Epoch time: 18.47 s +2024-11-22 23:52:08.461012: +2024-11-22 23:52:08.461247: Epoch 6908 +2024-11-22 23:52:08.461356: Current learning rate: 0.00167 +2024-11-22 23:52:26.641851: train_loss -0.8172 +2024-11-22 23:52:26.642074: val_loss -0.806 +2024-11-22 23:52:26.642148: Pseudo dice [0.8577] +2024-11-22 23:52:26.642222: Epoch time: 18.18 s +2024-11-22 23:52:27.548485: +2024-11-22 23:52:27.548693: Epoch 6909 +2024-11-22 23:52:27.548801: Current learning rate: 0.00166 +2024-11-22 23:52:45.454516: train_loss -0.8215 +2024-11-22 23:52:45.454758: val_loss -0.7677 +2024-11-22 23:52:45.454832: Pseudo dice [0.8619] +2024-11-22 23:52:45.454909: Epoch time: 17.91 s +2024-11-22 23:52:46.374784: +2024-11-22 23:52:46.375077: Epoch 6910 +2024-11-22 23:52:46.375186: Current learning rate: 0.00166 +2024-11-22 23:53:04.564404: train_loss -0.8267 +2024-11-22 23:53:04.564694: val_loss -0.7848 +2024-11-22 23:53:04.564777: Pseudo dice [0.84] +2024-11-22 23:53:04.564850: Epoch time: 18.19 s +2024-11-22 23:53:05.468830: +2024-11-22 23:53:05.469031: Epoch 6911 +2024-11-22 23:53:05.469140: Current learning rate: 0.00166 +2024-11-22 23:53:24.250190: train_loss -0.8218 +2024-11-22 23:53:24.250412: val_loss -0.7825 +2024-11-22 23:53:24.250485: Pseudo dice [0.852] +2024-11-22 23:53:24.250560: Epoch time: 18.78 s +2024-11-22 23:53:25.235566: +2024-11-22 23:53:25.235801: Epoch 6912 +2024-11-22 23:53:25.235915: Current learning rate: 0.00166 +2024-11-22 23:53:43.384980: train_loss -0.8233 +2024-11-22 23:53:43.385215: val_loss -0.8071 +2024-11-22 23:53:43.385290: Pseudo dice [0.857] +2024-11-22 23:53:43.385366: Epoch time: 18.15 s +2024-11-22 23:53:44.291131: +2024-11-22 23:53:44.291376: Epoch 6913 +2024-11-22 23:53:44.291519: Current learning rate: 0.00166 +2024-11-22 23:54:02.698385: train_loss -0.8211 +2024-11-22 23:54:02.700826: val_loss -0.7757 +2024-11-22 23:54:02.700966: Pseudo dice [0.8411] +2024-11-22 23:54:02.701060: Epoch time: 18.41 s +2024-11-22 23:54:03.617907: +2024-11-22 23:54:03.618127: Epoch 6914 +2024-11-22 23:54:03.618237: Current learning rate: 0.00166 +2024-11-22 23:54:21.855640: train_loss -0.825 +2024-11-22 23:54:21.855914: val_loss -0.7895 +2024-11-22 23:54:21.856000: Pseudo dice [0.8558] +2024-11-22 23:54:21.856076: Epoch time: 18.24 s +2024-11-22 23:54:23.108923: +2024-11-22 23:54:23.109167: Epoch 6915 +2024-11-22 23:54:23.109289: Current learning rate: 0.00166 +2024-11-22 23:54:42.091878: train_loss -0.8215 +2024-11-22 23:54:42.092117: val_loss -0.7695 +2024-11-22 23:54:42.094375: Pseudo dice [0.8509] +2024-11-22 23:54:42.094463: Epoch time: 18.98 s +2024-11-22 23:54:43.031721: +2024-11-22 23:54:43.031944: Epoch 6916 +2024-11-22 23:54:43.032061: Current learning rate: 0.00165 +2024-11-22 23:55:01.540498: train_loss -0.8165 +2024-11-22 23:55:01.540707: val_loss -0.767 +2024-11-22 23:55:01.540781: Pseudo dice [0.8425] +2024-11-22 23:55:01.540854: Epoch time: 18.51 s +2024-11-22 23:55:02.448661: +2024-11-22 23:55:02.448951: Epoch 6917 +2024-11-22 23:55:02.449116: Current learning rate: 0.00165 +2024-11-22 23:55:21.073756: train_loss -0.8203 +2024-11-22 23:55:21.073978: val_loss -0.7613 +2024-11-22 23:55:21.074059: Pseudo dice [0.8455] +2024-11-22 23:55:21.074157: Epoch time: 18.63 s +2024-11-22 23:55:21.982858: +2024-11-22 23:55:21.983095: Epoch 6918 +2024-11-22 23:55:21.983207: Current learning rate: 0.00165 +2024-11-22 23:55:40.697604: train_loss -0.8139 +2024-11-22 23:55:40.697816: val_loss -0.7762 +2024-11-22 23:55:40.697887: Pseudo dice [0.8422] +2024-11-22 23:55:40.698001: Epoch time: 18.72 s +2024-11-22 23:55:41.613869: +2024-11-22 23:55:41.614115: Epoch 6919 +2024-11-22 23:55:41.614224: Current learning rate: 0.00165 +2024-11-22 23:55:59.634644: train_loss -0.8195 +2024-11-22 23:55:59.634863: val_loss -0.7889 +2024-11-22 23:55:59.634946: Pseudo dice [0.8761] +2024-11-22 23:55:59.635034: Epoch time: 18.02 s +2024-11-22 23:56:00.631532: +2024-11-22 23:56:00.631788: Epoch 6920 +2024-11-22 23:56:00.631916: Current learning rate: 0.00165 +2024-11-22 23:56:19.579026: train_loss -0.8197 +2024-11-22 23:56:19.579244: val_loss -0.7995 +2024-11-22 23:56:19.579326: Pseudo dice [0.8542] +2024-11-22 23:56:19.579400: Epoch time: 18.95 s +2024-11-22 23:56:20.487905: +2024-11-22 23:56:20.488130: Epoch 6921 +2024-11-22 23:56:20.488252: Current learning rate: 0.00165 +2024-11-22 23:56:39.070501: train_loss -0.8191 +2024-11-22 23:56:39.070740: val_loss -0.804 +2024-11-22 23:56:39.072988: Pseudo dice [0.866] +2024-11-22 23:56:39.073123: Epoch time: 18.58 s +2024-11-22 23:56:40.140779: +2024-11-22 23:56:40.140997: Epoch 6922 +2024-11-22 23:56:40.141107: Current learning rate: 0.00165 +2024-11-22 23:56:58.695023: train_loss -0.817 +2024-11-22 23:56:58.695240: val_loss -0.8021 +2024-11-22 23:56:58.695315: Pseudo dice [0.8594] +2024-11-22 23:56:58.695387: Epoch time: 18.56 s +2024-11-22 23:56:59.602746: +2024-11-22 23:56:59.602962: Epoch 6923 +2024-11-22 23:56:59.603077: Current learning rate: 0.00165 +2024-11-22 23:57:18.150149: train_loss -0.8251 +2024-11-22 23:57:18.150383: val_loss -0.7708 +2024-11-22 23:57:18.150457: Pseudo dice [0.8398] +2024-11-22 23:57:18.150532: Epoch time: 18.55 s +2024-11-22 23:57:19.052798: +2024-11-22 23:57:19.053013: Epoch 6924 +2024-11-22 23:57:19.053122: Current learning rate: 0.00164 +2024-11-22 23:57:36.710057: train_loss -0.8258 +2024-11-22 23:57:36.710282: val_loss -0.801 +2024-11-22 23:57:36.710355: Pseudo dice [0.8572] +2024-11-22 23:57:36.710430: Epoch time: 17.66 s +2024-11-22 23:57:37.616588: +2024-11-22 23:57:37.616802: Epoch 6925 +2024-11-22 23:57:37.616918: Current learning rate: 0.00164 +2024-11-22 23:57:56.592397: train_loss -0.8182 +2024-11-22 23:57:56.592702: val_loss -0.7793 +2024-11-22 23:57:56.592782: Pseudo dice [0.8356] +2024-11-22 23:57:56.592865: Epoch time: 18.98 s +2024-11-22 23:57:57.499246: +2024-11-22 23:57:57.499495: Epoch 6926 +2024-11-22 23:57:57.499606: Current learning rate: 0.00164 +2024-11-22 23:58:15.902664: train_loss -0.8241 +2024-11-22 23:58:15.903161: val_loss -0.7746 +2024-11-22 23:58:15.903256: Pseudo dice [0.858] +2024-11-22 23:58:15.903334: Epoch time: 18.4 s +2024-11-22 23:58:16.810739: +2024-11-22 23:58:16.811074: Epoch 6927 +2024-11-22 23:58:16.811190: Current learning rate: 0.00164 +2024-11-22 23:58:34.418506: train_loss -0.8205 +2024-11-22 23:58:34.418723: val_loss -0.7846 +2024-11-22 23:58:34.418797: Pseudo dice [0.8507] +2024-11-22 23:58:34.418873: Epoch time: 17.61 s +2024-11-22 23:58:35.434804: +2024-11-22 23:58:35.435040: Epoch 6928 +2024-11-22 23:58:35.435148: Current learning rate: 0.00164 +2024-11-22 23:58:54.924327: train_loss -0.8163 +2024-11-22 23:58:54.924580: val_loss -0.8066 +2024-11-22 23:58:54.924658: Pseudo dice [0.8727] +2024-11-22 23:58:54.924737: Epoch time: 19.49 s +2024-11-22 23:58:55.841234: +2024-11-22 23:58:55.841447: Epoch 6929 +2024-11-22 23:58:55.841748: Current learning rate: 0.00164 +2024-11-22 23:59:14.373027: train_loss -0.8207 +2024-11-22 23:59:14.373244: val_loss -0.7948 +2024-11-22 23:59:14.375522: Pseudo dice [0.868] +2024-11-22 23:59:14.375665: Epoch time: 18.53 s +2024-11-22 23:59:15.303066: +2024-11-22 23:59:15.303273: Epoch 6930 +2024-11-22 23:59:15.303381: Current learning rate: 0.00164 +2024-11-22 23:59:34.354928: train_loss -0.8106 +2024-11-22 23:59:34.355153: val_loss -0.7804 +2024-11-22 23:59:34.355230: Pseudo dice [0.8415] +2024-11-22 23:59:34.355304: Epoch time: 19.05 s +2024-11-22 23:59:35.291746: +2024-11-22 23:59:35.291951: Epoch 6931 +2024-11-22 23:59:35.292067: Current learning rate: 0.00163 +2024-11-22 23:59:53.514177: train_loss -0.8174 +2024-11-22 23:59:53.514395: val_loss -0.8086 +2024-11-22 23:59:53.514469: Pseudo dice [0.8622] +2024-11-22 23:59:53.514545: Epoch time: 18.22 s +2024-11-22 23:59:54.418293: +2024-11-22 23:59:54.418509: Epoch 6932 +2024-11-22 23:59:54.418638: Current learning rate: 0.00163 +2024-11-23 00:00:14.193097: train_loss -0.8079 +2024-11-23 00:00:14.193384: val_loss -0.7764 +2024-11-23 00:00:14.193471: Pseudo dice [0.8573] +2024-11-23 00:00:14.193562: Epoch time: 19.77 s +2024-11-23 00:00:15.111253: +2024-11-23 00:00:15.111513: Epoch 6933 +2024-11-23 00:00:15.111626: Current learning rate: 0.00163 +2024-11-23 00:00:33.822557: train_loss -0.8133 +2024-11-23 00:00:33.822782: val_loss -0.7784 +2024-11-23 00:00:33.822855: Pseudo dice [0.8727] +2024-11-23 00:00:33.822928: Epoch time: 18.71 s +2024-11-23 00:00:34.730840: +2024-11-23 00:00:34.731048: Epoch 6934 +2024-11-23 00:00:34.731157: Current learning rate: 0.00163 +2024-11-23 00:00:53.515605: train_loss -0.8142 +2024-11-23 00:00:53.515886: val_loss -0.7718 +2024-11-23 00:00:53.515966: Pseudo dice [0.8704] +2024-11-23 00:00:53.516046: Epoch time: 18.79 s +2024-11-23 00:00:53.516107: Yayy! New best EMA pseudo Dice: 0.8583 +2024-11-23 00:00:54.749628: +2024-11-23 00:00:54.749837: Epoch 6935 +2024-11-23 00:00:54.749945: Current learning rate: 0.00163 +2024-11-23 00:01:13.591003: train_loss -0.8087 +2024-11-23 00:01:13.591286: val_loss -0.7758 +2024-11-23 00:01:13.591364: Pseudo dice [0.8334] +2024-11-23 00:01:13.591443: Epoch time: 18.84 s +2024-11-23 00:01:14.512087: +2024-11-23 00:01:14.512315: Epoch 6936 +2024-11-23 00:01:14.512421: Current learning rate: 0.00163 +2024-11-23 00:01:33.136825: train_loss -0.816 +2024-11-23 00:01:33.137087: val_loss -0.775 +2024-11-23 00:01:33.137161: Pseudo dice [0.8405] +2024-11-23 00:01:33.137244: Epoch time: 18.63 s +2024-11-23 00:01:34.050373: +2024-11-23 00:01:34.050598: Epoch 6937 +2024-11-23 00:01:34.050716: Current learning rate: 0.00163 +2024-11-23 00:01:52.112465: train_loss -0.8111 +2024-11-23 00:01:52.115202: val_loss -0.7756 +2024-11-23 00:01:52.115308: Pseudo dice [0.8478] +2024-11-23 00:01:52.115382: Epoch time: 18.06 s +2024-11-23 00:01:53.033170: +2024-11-23 00:01:53.033396: Epoch 6938 +2024-11-23 00:01:53.033505: Current learning rate: 0.00162 +2024-11-23 00:02:11.310806: train_loss -0.8251 +2024-11-23 00:02:11.311394: val_loss -0.7505 +2024-11-23 00:02:11.311520: Pseudo dice [0.8503] +2024-11-23 00:02:11.311607: Epoch time: 18.28 s +2024-11-23 00:02:12.220786: +2024-11-23 00:02:12.221008: Epoch 6939 +2024-11-23 00:02:12.221116: Current learning rate: 0.00162 +2024-11-23 00:02:30.042344: train_loss -0.8196 +2024-11-23 00:02:30.042607: val_loss -0.7767 +2024-11-23 00:02:30.042692: Pseudo dice [0.8564] +2024-11-23 00:02:30.042772: Epoch time: 17.82 s +2024-11-23 00:02:30.958677: +2024-11-23 00:02:30.958937: Epoch 6940 +2024-11-23 00:02:30.959064: Current learning rate: 0.00162 +2024-11-23 00:02:48.927156: train_loss -0.8201 +2024-11-23 00:02:48.927376: val_loss -0.7386 +2024-11-23 00:02:48.927451: Pseudo dice [0.8369] +2024-11-23 00:02:48.927528: Epoch time: 17.97 s +2024-11-23 00:02:49.961547: +2024-11-23 00:02:49.961792: Epoch 6941 +2024-11-23 00:02:49.961900: Current learning rate: 0.00162 +2024-11-23 00:03:08.939776: train_loss -0.8145 +2024-11-23 00:03:08.939988: val_loss -0.7667 +2024-11-23 00:03:08.940066: Pseudo dice [0.8528] +2024-11-23 00:03:08.942268: Epoch time: 18.98 s +2024-11-23 00:03:09.882606: +2024-11-23 00:03:09.882828: Epoch 6942 +2024-11-23 00:03:09.882936: Current learning rate: 0.00162 +2024-11-23 00:03:27.355441: train_loss -0.8146 +2024-11-23 00:03:27.355674: val_loss -0.7664 +2024-11-23 00:03:27.355747: Pseudo dice [0.8462] +2024-11-23 00:03:27.355821: Epoch time: 17.47 s +2024-11-23 00:03:28.263948: +2024-11-23 00:03:28.264184: Epoch 6943 +2024-11-23 00:03:28.264297: Current learning rate: 0.00162 +2024-11-23 00:03:46.758558: train_loss -0.8183 +2024-11-23 00:03:46.758809: val_loss -0.7736 +2024-11-23 00:03:46.758886: Pseudo dice [0.8417] +2024-11-23 00:03:46.758971: Epoch time: 18.5 s +2024-11-23 00:03:47.662235: +2024-11-23 00:03:47.662441: Epoch 6944 +2024-11-23 00:03:47.662546: Current learning rate: 0.00162 +2024-11-23 00:04:06.933786: train_loss -0.8246 +2024-11-23 00:04:06.934043: val_loss -0.7871 +2024-11-23 00:04:06.934118: Pseudo dice [0.8384] +2024-11-23 00:04:06.934194: Epoch time: 19.27 s +2024-11-23 00:04:07.878956: +2024-11-23 00:04:07.879197: Epoch 6945 +2024-11-23 00:04:07.879313: Current learning rate: 0.00161 +2024-11-23 00:04:26.387861: train_loss -0.8162 +2024-11-23 00:04:26.388156: val_loss -0.7856 +2024-11-23 00:04:26.388244: Pseudo dice [0.8631] +2024-11-23 00:04:26.388322: Epoch time: 18.51 s +2024-11-23 00:04:27.297125: +2024-11-23 00:04:27.297339: Epoch 6946 +2024-11-23 00:04:27.297447: Current learning rate: 0.00161 +2024-11-23 00:04:45.742208: train_loss -0.8183 +2024-11-23 00:04:45.742456: val_loss -0.7737 +2024-11-23 00:04:45.742532: Pseudo dice [0.8671] +2024-11-23 00:04:45.742605: Epoch time: 18.45 s +2024-11-23 00:04:46.646952: +2024-11-23 00:04:46.647159: Epoch 6947 +2024-11-23 00:04:46.647268: Current learning rate: 0.00161 +2024-11-23 00:05:05.864283: train_loss -0.8156 +2024-11-23 00:05:05.864589: val_loss -0.7627 +2024-11-23 00:05:05.864697: Pseudo dice [0.846] +2024-11-23 00:05:05.864778: Epoch time: 19.22 s +2024-11-23 00:05:06.778108: +2024-11-23 00:05:06.778310: Epoch 6948 +2024-11-23 00:05:06.778418: Current learning rate: 0.00161 +2024-11-23 00:05:24.959432: train_loss -0.8121 +2024-11-23 00:05:24.959663: val_loss -0.7669 +2024-11-23 00:05:24.959738: Pseudo dice [0.8401] +2024-11-23 00:05:24.959816: Epoch time: 18.18 s +2024-11-23 00:05:26.251024: +2024-11-23 00:05:26.251272: Epoch 6949 +2024-11-23 00:05:26.251384: Current learning rate: 0.00161 +2024-11-23 00:05:44.932592: train_loss -0.8157 +2024-11-23 00:05:44.933706: val_loss -0.7839 +2024-11-23 00:05:44.933789: Pseudo dice [0.8525] +2024-11-23 00:05:44.933864: Epoch time: 18.68 s +2024-11-23 00:05:46.166569: +2024-11-23 00:05:46.166816: Epoch 6950 +2024-11-23 00:05:46.166930: Current learning rate: 0.00161 +2024-11-23 00:06:03.830715: train_loss -0.8177 +2024-11-23 00:06:03.830956: val_loss -0.7824 +2024-11-23 00:06:03.831042: Pseudo dice [0.8507] +2024-11-23 00:06:03.831121: Epoch time: 17.66 s +2024-11-23 00:06:04.738645: +2024-11-23 00:06:04.738861: Epoch 6951 +2024-11-23 00:06:04.738967: Current learning rate: 0.00161 +2024-11-23 00:06:23.432646: train_loss -0.8087 +2024-11-23 00:06:23.432868: val_loss -0.7633 +2024-11-23 00:06:23.432944: Pseudo dice [0.8357] +2024-11-23 00:06:23.433026: Epoch time: 18.69 s +2024-11-23 00:06:24.339750: +2024-11-23 00:06:24.339988: Epoch 6952 +2024-11-23 00:06:24.340104: Current learning rate: 0.00161 +2024-11-23 00:06:41.355351: train_loss -0.8051 +2024-11-23 00:06:41.355572: val_loss -0.786 +2024-11-23 00:06:41.355652: Pseudo dice [0.8692] +2024-11-23 00:06:41.355750: Epoch time: 17.02 s +2024-11-23 00:06:42.367754: +2024-11-23 00:06:42.367984: Epoch 6953 +2024-11-23 00:06:42.368100: Current learning rate: 0.0016 +2024-11-23 00:07:00.257948: train_loss -0.817 +2024-11-23 00:07:00.258230: val_loss -0.7601 +2024-11-23 00:07:00.258308: Pseudo dice [0.8537] +2024-11-23 00:07:00.258385: Epoch time: 17.89 s +2024-11-23 00:07:01.168778: +2024-11-23 00:07:01.169010: Epoch 6954 +2024-11-23 00:07:01.169121: Current learning rate: 0.0016 +2024-11-23 00:07:19.720926: train_loss -0.8149 +2024-11-23 00:07:19.721185: val_loss -0.7679 +2024-11-23 00:07:19.721263: Pseudo dice [0.8494] +2024-11-23 00:07:19.721561: Epoch time: 18.55 s +2024-11-23 00:07:20.633507: +2024-11-23 00:07:20.633736: Epoch 6955 +2024-11-23 00:07:20.633850: Current learning rate: 0.0016 +2024-11-23 00:07:39.203843: train_loss -0.8138 +2024-11-23 00:07:39.204185: val_loss -0.7826 +2024-11-23 00:07:39.204270: Pseudo dice [0.8595] +2024-11-23 00:07:39.204355: Epoch time: 18.57 s +2024-11-23 00:07:40.116217: +2024-11-23 00:07:40.116449: Epoch 6956 +2024-11-23 00:07:40.116566: Current learning rate: 0.0016 +2024-11-23 00:07:58.371363: train_loss -0.8245 +2024-11-23 00:07:58.371582: val_loss -0.7688 +2024-11-23 00:07:58.371671: Pseudo dice [0.8438] +2024-11-23 00:07:58.371753: Epoch time: 18.26 s +2024-11-23 00:07:59.280843: +2024-11-23 00:07:59.281056: Epoch 6957 +2024-11-23 00:07:59.281197: Current learning rate: 0.0016 +2024-11-23 00:08:16.602972: train_loss -0.8154 +2024-11-23 00:08:16.603197: val_loss -0.7678 +2024-11-23 00:08:16.603895: Pseudo dice [0.854] +2024-11-23 00:08:16.603997: Epoch time: 17.32 s +2024-11-23 00:08:17.562581: +2024-11-23 00:08:17.562815: Epoch 6958 +2024-11-23 00:08:17.562925: Current learning rate: 0.0016 +2024-11-23 00:08:35.480543: train_loss -0.8176 +2024-11-23 00:08:35.480782: val_loss -0.77 +2024-11-23 00:08:35.480857: Pseudo dice [0.8644] +2024-11-23 00:08:35.480936: Epoch time: 17.92 s +2024-11-23 00:08:36.395603: +2024-11-23 00:08:36.395801: Epoch 6959 +2024-11-23 00:08:36.395908: Current learning rate: 0.0016 +2024-11-23 00:08:54.856711: train_loss -0.8136 +2024-11-23 00:08:54.856939: val_loss -0.7893 +2024-11-23 00:08:54.857020: Pseudo dice [0.8606] +2024-11-23 00:08:54.857096: Epoch time: 18.46 s +2024-11-23 00:08:55.761137: +2024-11-23 00:08:55.761370: Epoch 6960 +2024-11-23 00:08:55.761488: Current learning rate: 0.00159 +2024-11-23 00:09:15.370639: train_loss -0.8126 +2024-11-23 00:09:15.370869: val_loss -0.7809 +2024-11-23 00:09:15.370942: Pseudo dice [0.8434] +2024-11-23 00:09:15.371023: Epoch time: 19.61 s +2024-11-23 00:09:16.329674: +2024-11-23 00:09:16.329900: Epoch 6961 +2024-11-23 00:09:16.330015: Current learning rate: 0.00159 +2024-11-23 00:09:35.143505: train_loss -0.8193 +2024-11-23 00:09:35.143735: val_loss -0.7533 +2024-11-23 00:09:35.143810: Pseudo dice [0.8304] +2024-11-23 00:09:35.143885: Epoch time: 18.81 s +2024-11-23 00:09:36.160744: +2024-11-23 00:09:36.160966: Epoch 6962 +2024-11-23 00:09:36.161082: Current learning rate: 0.00159 +2024-11-23 00:09:54.872756: train_loss -0.8205 +2024-11-23 00:09:54.873014: val_loss -0.7978 +2024-11-23 00:09:54.873098: Pseudo dice [0.8652] +2024-11-23 00:09:54.873200: Epoch time: 18.71 s +2024-11-23 00:09:55.774860: +2024-11-23 00:09:55.775093: Epoch 6963 +2024-11-23 00:09:55.775213: Current learning rate: 0.00159 +2024-11-23 00:10:14.251685: train_loss -0.8164 +2024-11-23 00:10:14.251903: val_loss -0.7813 +2024-11-23 00:10:14.251977: Pseudo dice [0.8465] +2024-11-23 00:10:14.252055: Epoch time: 18.48 s +2024-11-23 00:10:15.155705: +2024-11-23 00:10:15.155942: Epoch 6964 +2024-11-23 00:10:15.156054: Current learning rate: 0.00159 +2024-11-23 00:10:34.004611: train_loss -0.8035 +2024-11-23 00:10:34.004830: val_loss -0.7838 +2024-11-23 00:10:34.004904: Pseudo dice [0.8472] +2024-11-23 00:10:34.004978: Epoch time: 18.85 s +2024-11-23 00:10:34.914869: +2024-11-23 00:10:34.915094: Epoch 6965 +2024-11-23 00:10:34.915205: Current learning rate: 0.00159 +2024-11-23 00:10:53.676372: train_loss -0.8169 +2024-11-23 00:10:53.676593: val_loss -0.7635 +2024-11-23 00:10:53.676669: Pseudo dice [0.8519] +2024-11-23 00:10:53.676745: Epoch time: 18.76 s +2024-11-23 00:10:54.594513: +2024-11-23 00:10:54.594881: Epoch 6966 +2024-11-23 00:10:54.594997: Current learning rate: 0.00159 +2024-11-23 00:11:12.732107: train_loss -0.8144 +2024-11-23 00:11:12.732363: val_loss -0.7735 +2024-11-23 00:11:12.732441: Pseudo dice [0.8555] +2024-11-23 00:11:12.732519: Epoch time: 18.14 s +2024-11-23 00:11:13.641044: +2024-11-23 00:11:13.641258: Epoch 6967 +2024-11-23 00:11:13.641370: Current learning rate: 0.00158 +2024-11-23 00:11:33.146521: train_loss -0.8153 +2024-11-23 00:11:33.146737: val_loss -0.7513 +2024-11-23 00:11:33.146809: Pseudo dice [0.8413] +2024-11-23 00:11:33.146881: Epoch time: 19.51 s +2024-11-23 00:11:34.073344: +2024-11-23 00:11:34.073565: Epoch 6968 +2024-11-23 00:11:34.073676: Current learning rate: 0.00158 +2024-11-23 00:11:52.478907: train_loss -0.8213 +2024-11-23 00:11:52.479131: val_loss -0.8066 +2024-11-23 00:11:52.479208: Pseudo dice [0.8655] +2024-11-23 00:11:52.479287: Epoch time: 18.41 s +2024-11-23 00:11:53.388485: +2024-11-23 00:11:53.388736: Epoch 6969 +2024-11-23 00:11:53.388844: Current learning rate: 0.00158 +2024-11-23 00:12:11.908149: train_loss -0.818 +2024-11-23 00:12:11.908380: val_loss -0.777 +2024-11-23 00:12:11.908456: Pseudo dice [0.8531] +2024-11-23 00:12:11.908533: Epoch time: 18.52 s +2024-11-23 00:12:12.817534: +2024-11-23 00:12:12.817760: Epoch 6970 +2024-11-23 00:12:12.817874: Current learning rate: 0.00158 +2024-11-23 00:12:30.985547: train_loss -0.8232 +2024-11-23 00:12:30.985838: val_loss -0.7528 +2024-11-23 00:12:30.985915: Pseudo dice [0.8408] +2024-11-23 00:12:30.985996: Epoch time: 18.17 s +2024-11-23 00:12:31.894625: +2024-11-23 00:12:31.894842: Epoch 6971 +2024-11-23 00:12:31.894950: Current learning rate: 0.00158 +2024-11-23 00:12:50.946836: train_loss -0.8184 +2024-11-23 00:12:50.947066: val_loss -0.785 +2024-11-23 00:12:50.947143: Pseudo dice [0.8543] +2024-11-23 00:12:50.952508: Epoch time: 19.05 s +2024-11-23 00:12:52.299518: +2024-11-23 00:12:52.299751: Epoch 6972 +2024-11-23 00:12:52.299870: Current learning rate: 0.00158 +2024-11-23 00:13:10.656557: train_loss -0.8141 +2024-11-23 00:13:10.659420: val_loss -0.7686 +2024-11-23 00:13:10.659515: Pseudo dice [0.8541] +2024-11-23 00:13:10.659594: Epoch time: 18.36 s +2024-11-23 00:13:11.599876: +2024-11-23 00:13:11.600106: Epoch 6973 +2024-11-23 00:13:11.600220: Current learning rate: 0.00158 +2024-11-23 00:13:30.520931: train_loss -0.8149 +2024-11-23 00:13:30.521186: val_loss -0.7461 +2024-11-23 00:13:30.521260: Pseudo dice [0.8401] +2024-11-23 00:13:30.521339: Epoch time: 18.92 s +2024-11-23 00:13:31.432020: +2024-11-23 00:13:31.432236: Epoch 6974 +2024-11-23 00:13:31.432345: Current learning rate: 0.00157 +2024-11-23 00:13:49.499482: train_loss -0.8143 +2024-11-23 00:13:49.499754: val_loss -0.7705 +2024-11-23 00:13:49.499874: Pseudo dice [0.8479] +2024-11-23 00:13:49.499951: Epoch time: 18.07 s +2024-11-23 00:13:50.408979: +2024-11-23 00:13:50.409201: Epoch 6975 +2024-11-23 00:13:50.409308: Current learning rate: 0.00157 +2024-11-23 00:14:08.374588: train_loss -0.8171 +2024-11-23 00:14:08.374838: val_loss -0.7622 +2024-11-23 00:14:08.374918: Pseudo dice [0.85] +2024-11-23 00:14:08.374996: Epoch time: 17.97 s +2024-11-23 00:14:09.278318: +2024-11-23 00:14:09.278548: Epoch 6976 +2024-11-23 00:14:09.278655: Current learning rate: 0.00157 +2024-11-23 00:14:28.164812: train_loss -0.8217 +2024-11-23 00:14:28.165034: val_loss -0.7665 +2024-11-23 00:14:28.165110: Pseudo dice [0.8585] +2024-11-23 00:14:28.165184: Epoch time: 18.89 s +2024-11-23 00:14:29.074091: +2024-11-23 00:14:29.074290: Epoch 6977 +2024-11-23 00:14:29.074399: Current learning rate: 0.00157 +2024-11-23 00:14:48.335155: train_loss -0.8215 +2024-11-23 00:14:48.335426: val_loss -0.7946 +2024-11-23 00:14:48.335502: Pseudo dice [0.8547] +2024-11-23 00:14:48.335604: Epoch time: 19.26 s +2024-11-23 00:14:49.295741: +2024-11-23 00:14:49.295963: Epoch 6978 +2024-11-23 00:14:49.296091: Current learning rate: 0.00157 +2024-11-23 00:15:08.546762: train_loss -0.8158 +2024-11-23 00:15:08.547029: val_loss -0.7861 +2024-11-23 00:15:08.547111: Pseudo dice [0.84] +2024-11-23 00:15:08.547189: Epoch time: 19.25 s +2024-11-23 00:15:09.574083: +2024-11-23 00:15:09.574315: Epoch 6979 +2024-11-23 00:15:09.574427: Current learning rate: 0.00157 +2024-11-23 00:15:28.821682: train_loss -0.8177 +2024-11-23 00:15:28.821899: val_loss -0.7759 +2024-11-23 00:15:28.821975: Pseudo dice [0.8416] +2024-11-23 00:15:28.822060: Epoch time: 19.25 s +2024-11-23 00:15:29.737501: +2024-11-23 00:15:29.737748: Epoch 6980 +2024-11-23 00:15:29.737876: Current learning rate: 0.00157 +2024-11-23 00:15:48.265345: train_loss -0.8213 +2024-11-23 00:15:48.265631: val_loss -0.7967 +2024-11-23 00:15:48.265711: Pseudo dice [0.8635] +2024-11-23 00:15:48.270027: Epoch time: 18.53 s +2024-11-23 00:15:49.233678: +2024-11-23 00:15:49.233894: Epoch 6981 +2024-11-23 00:15:49.234009: Current learning rate: 0.00157 +2024-11-23 00:16:08.426125: train_loss -0.8166 +2024-11-23 00:16:08.426372: val_loss -0.7968 +2024-11-23 00:16:08.426450: Pseudo dice [0.8598] +2024-11-23 00:16:08.426530: Epoch time: 19.19 s +2024-11-23 00:16:09.341495: +2024-11-23 00:16:09.341704: Epoch 6982 +2024-11-23 00:16:09.341814: Current learning rate: 0.00156 +2024-11-23 00:16:27.836570: train_loss -0.8205 +2024-11-23 00:16:27.836783: val_loss -0.7759 +2024-11-23 00:16:27.836860: Pseudo dice [0.8419] +2024-11-23 00:16:27.836934: Epoch time: 18.5 s +2024-11-23 00:16:29.121698: +2024-11-23 00:16:29.121943: Epoch 6983 +2024-11-23 00:16:29.122060: Current learning rate: 0.00156 +2024-11-23 00:16:46.656974: train_loss -0.822 +2024-11-23 00:16:46.657204: val_loss -0.7728 +2024-11-23 00:16:46.657280: Pseudo dice [0.8555] +2024-11-23 00:16:46.657356: Epoch time: 17.54 s +2024-11-23 00:16:47.565931: +2024-11-23 00:16:47.566178: Epoch 6984 +2024-11-23 00:16:47.566289: Current learning rate: 0.00156 +2024-11-23 00:17:05.115798: train_loss -0.8199 +2024-11-23 00:17:05.116025: val_loss -0.7881 +2024-11-23 00:17:05.116103: Pseudo dice [0.8542] +2024-11-23 00:17:05.116175: Epoch time: 17.55 s +2024-11-23 00:17:06.025377: +2024-11-23 00:17:06.025664: Epoch 6985 +2024-11-23 00:17:06.025818: Current learning rate: 0.00156 +2024-11-23 00:17:24.641172: train_loss -0.8112 +2024-11-23 00:17:24.641385: val_loss -0.7776 +2024-11-23 00:17:24.641464: Pseudo dice [0.8686] +2024-11-23 00:17:24.641544: Epoch time: 18.62 s +2024-11-23 00:17:25.664586: +2024-11-23 00:17:25.664814: Epoch 6986 +2024-11-23 00:17:25.664926: Current learning rate: 0.00156 +2024-11-23 00:17:44.084537: train_loss -0.8181 +2024-11-23 00:17:44.084764: val_loss -0.7832 +2024-11-23 00:17:44.084839: Pseudo dice [0.8458] +2024-11-23 00:17:44.084915: Epoch time: 18.42 s +2024-11-23 00:17:45.078201: +2024-11-23 00:17:45.078427: Epoch 6987 +2024-11-23 00:17:45.078534: Current learning rate: 0.00156 +2024-11-23 00:18:02.685604: train_loss -0.8218 +2024-11-23 00:18:02.685818: val_loss -0.7807 +2024-11-23 00:18:02.685989: Pseudo dice [0.862] +2024-11-23 00:18:02.686075: Epoch time: 17.61 s +2024-11-23 00:18:03.592786: +2024-11-23 00:18:03.593027: Epoch 6988 +2024-11-23 00:18:03.593142: Current learning rate: 0.00156 +2024-11-23 00:18:21.383725: train_loss -0.8265 +2024-11-23 00:18:21.383953: val_loss -0.7599 +2024-11-23 00:18:21.384038: Pseudo dice [0.85] +2024-11-23 00:18:21.384114: Epoch time: 17.79 s +2024-11-23 00:18:22.297756: +2024-11-23 00:18:22.297998: Epoch 6989 +2024-11-23 00:18:22.298114: Current learning rate: 0.00155 +2024-11-23 00:18:41.760245: train_loss -0.8117 +2024-11-23 00:18:41.760486: val_loss -0.7648 +2024-11-23 00:18:41.760560: Pseudo dice [0.8384] +2024-11-23 00:18:41.760638: Epoch time: 19.46 s +2024-11-23 00:18:42.680185: +2024-11-23 00:18:42.680411: Epoch 6990 +2024-11-23 00:18:42.680523: Current learning rate: 0.00155 +2024-11-23 00:19:01.994931: train_loss -0.8164 +2024-11-23 00:19:01.995193: val_loss -0.7831 +2024-11-23 00:19:01.995270: Pseudo dice [0.8592] +2024-11-23 00:19:01.995344: Epoch time: 19.32 s +2024-11-23 00:19:02.903968: +2024-11-23 00:19:02.904204: Epoch 6991 +2024-11-23 00:19:02.904314: Current learning rate: 0.00155 +2024-11-23 00:19:21.581460: train_loss -0.824 +2024-11-23 00:19:21.581676: val_loss -0.8015 +2024-11-23 00:19:21.581752: Pseudo dice [0.8592] +2024-11-23 00:19:21.584022: Epoch time: 18.68 s +2024-11-23 00:19:22.603970: +2024-11-23 00:19:22.604213: Epoch 6992 +2024-11-23 00:19:22.604336: Current learning rate: 0.00155 +2024-11-23 00:19:39.500403: train_loss -0.8208 +2024-11-23 00:19:39.500618: val_loss -0.7801 +2024-11-23 00:19:39.500700: Pseudo dice [0.8594] +2024-11-23 00:19:39.500775: Epoch time: 16.9 s +2024-11-23 00:19:40.510821: +2024-11-23 00:19:40.511058: Epoch 6993 +2024-11-23 00:19:40.511170: Current learning rate: 0.00155 +2024-11-23 00:19:58.948298: train_loss -0.8161 +2024-11-23 00:19:58.948537: val_loss -0.7902 +2024-11-23 00:19:58.948612: Pseudo dice [0.8604] +2024-11-23 00:19:58.948690: Epoch time: 18.44 s +2024-11-23 00:19:59.863117: +2024-11-23 00:19:59.863337: Epoch 6994 +2024-11-23 00:19:59.863450: Current learning rate: 0.00155 +2024-11-23 00:20:19.386578: train_loss -0.818 +2024-11-23 00:20:19.386795: val_loss -0.8054 +2024-11-23 00:20:19.386877: Pseudo dice [0.8581] +2024-11-23 00:20:19.386959: Epoch time: 19.52 s +2024-11-23 00:20:20.628227: +2024-11-23 00:20:20.628436: Epoch 6995 +2024-11-23 00:20:20.628545: Current learning rate: 0.00155 +2024-11-23 00:20:39.770635: train_loss -0.8176 +2024-11-23 00:20:39.770928: val_loss -0.7884 +2024-11-23 00:20:39.771011: Pseudo dice [0.8636] +2024-11-23 00:20:39.771086: Epoch time: 19.14 s +2024-11-23 00:20:40.671851: +2024-11-23 00:20:40.672093: Epoch 6996 +2024-11-23 00:20:40.672218: Current learning rate: 0.00154 +2024-11-23 00:20:59.783672: train_loss -0.8191 +2024-11-23 00:20:59.783919: val_loss -0.7685 +2024-11-23 00:20:59.784013: Pseudo dice [0.8487] +2024-11-23 00:20:59.784196: Epoch time: 19.11 s +2024-11-23 00:21:00.766128: +2024-11-23 00:21:00.766366: Epoch 6997 +2024-11-23 00:21:00.766472: Current learning rate: 0.00154 +2024-11-23 00:21:19.271459: train_loss -0.812 +2024-11-23 00:21:19.271671: val_loss -0.7914 +2024-11-23 00:21:19.271751: Pseudo dice [0.872] +2024-11-23 00:21:19.271844: Epoch time: 18.51 s +2024-11-23 00:21:20.177698: +2024-11-23 00:21:20.177918: Epoch 6998 +2024-11-23 00:21:20.178030: Current learning rate: 0.00154 +2024-11-23 00:21:38.215343: train_loss -0.8211 +2024-11-23 00:21:38.215586: val_loss -0.7828 +2024-11-23 00:21:38.215662: Pseudo dice [0.8454] +2024-11-23 00:21:38.215739: Epoch time: 18.04 s +2024-11-23 00:21:39.138569: +2024-11-23 00:21:39.138809: Epoch 6999 +2024-11-23 00:21:39.138922: Current learning rate: 0.00154 +2024-11-23 00:21:56.689800: train_loss -0.8205 +2024-11-23 00:21:56.690498: val_loss -0.7748 +2024-11-23 00:21:56.690576: Pseudo dice [0.8495] +2024-11-23 00:21:56.690654: Epoch time: 17.55 s +2024-11-23 00:21:57.948690: +2024-11-23 00:21:57.948923: Epoch 7000 +2024-11-23 00:21:57.949036: Current learning rate: 0.00154 +2024-11-23 00:22:16.392222: train_loss -0.8194 +2024-11-23 00:22:16.392468: val_loss -0.7874 +2024-11-23 00:22:16.392576: Pseudo dice [0.8567] +2024-11-23 00:22:16.392660: Epoch time: 18.44 s +2024-11-23 00:22:17.302861: +2024-11-23 00:22:17.303121: Epoch 7001 +2024-11-23 00:22:17.303231: Current learning rate: 0.00154 +2024-11-23 00:22:35.661558: train_loss -0.8205 +2024-11-23 00:22:35.661771: val_loss -0.7773 +2024-11-23 00:22:35.661841: Pseudo dice [0.8648] +2024-11-23 00:22:35.667058: Epoch time: 18.36 s +2024-11-23 00:22:36.612108: +2024-11-23 00:22:36.612337: Epoch 7002 +2024-11-23 00:22:36.612449: Current learning rate: 0.00154 +2024-11-23 00:22:54.707224: train_loss -0.8173 +2024-11-23 00:22:54.707443: val_loss -0.7812 +2024-11-23 00:22:54.707517: Pseudo dice [0.8371] +2024-11-23 00:22:54.707592: Epoch time: 18.1 s +2024-11-23 00:22:55.608068: +2024-11-23 00:22:55.608332: Epoch 7003 +2024-11-23 00:22:55.608449: Current learning rate: 0.00153 +2024-11-23 00:23:14.638686: train_loss -0.8244 +2024-11-23 00:23:14.638921: val_loss -0.7901 +2024-11-23 00:23:14.639008: Pseudo dice [0.8457] +2024-11-23 00:23:14.639091: Epoch time: 19.03 s +2024-11-23 00:23:15.646586: +2024-11-23 00:23:15.646816: Epoch 7004 +2024-11-23 00:23:15.646930: Current learning rate: 0.00153 +2024-11-23 00:23:35.515907: train_loss -0.8206 +2024-11-23 00:23:35.516180: val_loss -0.784 +2024-11-23 00:23:35.516258: Pseudo dice [0.8563] +2024-11-23 00:23:35.516343: Epoch time: 19.87 s +2024-11-23 00:23:36.428579: +2024-11-23 00:23:36.428796: Epoch 7005 +2024-11-23 00:23:36.428912: Current learning rate: 0.00153 +2024-11-23 00:23:55.247267: train_loss -0.8192 +2024-11-23 00:23:55.247477: val_loss -0.7921 +2024-11-23 00:23:55.247550: Pseudo dice [0.86] +2024-11-23 00:23:55.247624: Epoch time: 18.82 s +2024-11-23 00:23:56.150531: +2024-11-23 00:23:56.150756: Epoch 7006 +2024-11-23 00:23:56.150866: Current learning rate: 0.00153 +2024-11-23 00:24:14.238038: train_loss -0.8199 +2024-11-23 00:24:14.240461: val_loss -0.789 +2024-11-23 00:24:14.240600: Pseudo dice [0.8575] +2024-11-23 00:24:14.240900: Epoch time: 18.09 s +2024-11-23 00:24:15.164330: +2024-11-23 00:24:15.164547: Epoch 7007 +2024-11-23 00:24:15.164659: Current learning rate: 0.00153 +2024-11-23 00:24:33.775278: train_loss -0.8251 +2024-11-23 00:24:33.775519: val_loss -0.7912 +2024-11-23 00:24:33.775593: Pseudo dice [0.8488] +2024-11-23 00:24:33.775669: Epoch time: 18.61 s +2024-11-23 00:24:34.684348: +2024-11-23 00:24:34.684558: Epoch 7008 +2024-11-23 00:24:34.684670: Current learning rate: 0.00153 +2024-11-23 00:24:53.978010: train_loss -0.8171 +2024-11-23 00:24:53.978234: val_loss -0.7928 +2024-11-23 00:24:53.978309: Pseudo dice [0.8392] +2024-11-23 00:24:53.978384: Epoch time: 19.29 s +2024-11-23 00:24:54.882352: +2024-11-23 00:24:54.882582: Epoch 7009 +2024-11-23 00:24:54.882690: Current learning rate: 0.00153 +2024-11-23 00:25:13.441812: train_loss -0.8143 +2024-11-23 00:25:13.442049: val_loss -0.7863 +2024-11-23 00:25:13.442122: Pseudo dice [0.853] +2024-11-23 00:25:13.442194: Epoch time: 18.56 s +2024-11-23 00:25:14.370169: +2024-11-23 00:25:14.370401: Epoch 7010 +2024-11-23 00:25:14.370512: Current learning rate: 0.00153 +2024-11-23 00:25:34.015073: train_loss -0.8152 +2024-11-23 00:25:34.015361: val_loss -0.7798 +2024-11-23 00:25:34.015438: Pseudo dice [0.8463] +2024-11-23 00:25:34.015516: Epoch time: 19.65 s +2024-11-23 00:25:34.926620: +2024-11-23 00:25:34.926825: Epoch 7011 +2024-11-23 00:25:34.926935: Current learning rate: 0.00152 +2024-11-23 00:25:53.472353: train_loss -0.813 +2024-11-23 00:25:53.472586: val_loss -0.7912 +2024-11-23 00:25:53.472682: Pseudo dice [0.8502] +2024-11-23 00:25:53.472762: Epoch time: 18.55 s +2024-11-23 00:25:54.375449: +2024-11-23 00:25:54.375644: Epoch 7012 +2024-11-23 00:25:54.375751: Current learning rate: 0.00152 +2024-11-23 00:26:13.591338: train_loss -0.8159 +2024-11-23 00:26:13.591612: val_loss -0.7931 +2024-11-23 00:26:13.591686: Pseudo dice [0.8527] +2024-11-23 00:26:13.591763: Epoch time: 19.22 s +2024-11-23 00:26:14.501038: +2024-11-23 00:26:14.501254: Epoch 7013 +2024-11-23 00:26:14.501362: Current learning rate: 0.00152 +2024-11-23 00:26:33.022400: train_loss -0.8113 +2024-11-23 00:26:33.022632: val_loss -0.7907 +2024-11-23 00:26:33.022717: Pseudo dice [0.8638] +2024-11-23 00:26:33.022792: Epoch time: 18.52 s +2024-11-23 00:26:33.934963: +2024-11-23 00:26:33.935182: Epoch 7014 +2024-11-23 00:26:33.935295: Current learning rate: 0.00152 +2024-11-23 00:26:52.285964: train_loss -0.8218 +2024-11-23 00:26:52.286221: val_loss -0.7663 +2024-11-23 00:26:52.286300: Pseudo dice [0.8561] +2024-11-23 00:26:52.286383: Epoch time: 18.35 s +2024-11-23 00:26:53.196798: +2024-11-23 00:26:53.197082: Epoch 7015 +2024-11-23 00:26:53.197199: Current learning rate: 0.00152 +2024-11-23 00:27:12.263579: train_loss -0.8258 +2024-11-23 00:27:12.263783: val_loss -0.7731 +2024-11-23 00:27:12.263856: Pseudo dice [0.8642] +2024-11-23 00:27:12.263932: Epoch time: 19.07 s +2024-11-23 00:27:13.171166: +2024-11-23 00:27:13.171462: Epoch 7016 +2024-11-23 00:27:13.171582: Current learning rate: 0.00152 +2024-11-23 00:27:31.774312: train_loss -0.812 +2024-11-23 00:27:31.774550: val_loss -0.7911 +2024-11-23 00:27:31.774687: Pseudo dice [0.8468] +2024-11-23 00:27:31.774764: Epoch time: 18.6 s +2024-11-23 00:27:32.687117: +2024-11-23 00:27:32.687320: Epoch 7017 +2024-11-23 00:27:32.687430: Current learning rate: 0.00152 +2024-11-23 00:27:50.964452: train_loss -0.8245 +2024-11-23 00:27:50.964685: val_loss -0.7807 +2024-11-23 00:27:50.964765: Pseudo dice [0.8636] +2024-11-23 00:27:50.964839: Epoch time: 18.28 s +2024-11-23 00:27:52.271281: +2024-11-23 00:27:52.271505: Epoch 7018 +2024-11-23 00:27:52.271614: Current learning rate: 0.00151 +2024-11-23 00:28:11.130368: train_loss -0.8156 +2024-11-23 00:28:11.130628: val_loss -0.7792 +2024-11-23 00:28:11.130731: Pseudo dice [0.8576] +2024-11-23 00:28:11.130815: Epoch time: 18.86 s +2024-11-23 00:28:12.034078: +2024-11-23 00:28:12.034296: Epoch 7019 +2024-11-23 00:28:12.034402: Current learning rate: 0.00151 +2024-11-23 00:28:31.060874: train_loss -0.8162 +2024-11-23 00:28:31.061103: val_loss -0.7865 +2024-11-23 00:28:31.063124: Pseudo dice [0.8456] +2024-11-23 00:28:31.063344: Epoch time: 19.03 s +2024-11-23 00:28:32.004017: +2024-11-23 00:28:32.004237: Epoch 7020 +2024-11-23 00:28:32.004344: Current learning rate: 0.00151 +2024-11-23 00:28:49.782805: train_loss -0.8212 +2024-11-23 00:28:49.783031: val_loss -0.8031 +2024-11-23 00:28:49.783107: Pseudo dice [0.8636] +2024-11-23 00:28:49.783178: Epoch time: 17.78 s +2024-11-23 00:28:50.697700: +2024-11-23 00:28:50.697927: Epoch 7021 +2024-11-23 00:28:50.698054: Current learning rate: 0.00151 +2024-11-23 00:29:09.089536: train_loss -0.8175 +2024-11-23 00:29:09.089781: val_loss -0.7857 +2024-11-23 00:29:09.089857: Pseudo dice [0.8373] +2024-11-23 00:29:09.089939: Epoch time: 18.39 s +2024-11-23 00:29:10.001567: +2024-11-23 00:29:10.001842: Epoch 7022 +2024-11-23 00:29:10.001958: Current learning rate: 0.00151 +2024-11-23 00:29:28.701478: train_loss -0.8206 +2024-11-23 00:29:28.701735: val_loss -0.775 +2024-11-23 00:29:28.701819: Pseudo dice [0.8316] +2024-11-23 00:29:28.701899: Epoch time: 18.7 s +2024-11-23 00:29:29.856382: +2024-11-23 00:29:29.856603: Epoch 7023 +2024-11-23 00:29:29.856712: Current learning rate: 0.00151 +2024-11-23 00:29:47.725553: train_loss -0.8184 +2024-11-23 00:29:47.726996: val_loss -0.7911 +2024-11-23 00:29:47.727155: Pseudo dice [0.8683] +2024-11-23 00:29:47.727240: Epoch time: 17.87 s +2024-11-23 00:29:48.696557: +2024-11-23 00:29:48.696769: Epoch 7024 +2024-11-23 00:29:48.696881: Current learning rate: 0.00151 +2024-11-23 00:30:06.137526: train_loss -0.8079 +2024-11-23 00:30:06.137759: val_loss -0.7768 +2024-11-23 00:30:06.137836: Pseudo dice [0.8564] +2024-11-23 00:30:06.137914: Epoch time: 17.44 s +2024-11-23 00:30:07.042232: +2024-11-23 00:30:07.042456: Epoch 7025 +2024-11-23 00:30:07.042570: Current learning rate: 0.0015 +2024-11-23 00:30:25.018879: train_loss -0.816 +2024-11-23 00:30:25.019122: val_loss -0.7609 +2024-11-23 00:30:25.019200: Pseudo dice [0.8543] +2024-11-23 00:30:25.019279: Epoch time: 17.98 s +2024-11-23 00:30:25.927148: +2024-11-23 00:30:25.927368: Epoch 7026 +2024-11-23 00:30:25.927489: Current learning rate: 0.0015 +2024-11-23 00:30:44.456359: train_loss -0.8213 +2024-11-23 00:30:44.461747: val_loss -0.7785 +2024-11-23 00:30:44.461864: Pseudo dice [0.8501] +2024-11-23 00:30:44.461941: Epoch time: 18.53 s +2024-11-23 00:30:45.388868: +2024-11-23 00:30:45.389100: Epoch 7027 +2024-11-23 00:30:45.389214: Current learning rate: 0.0015 +2024-11-23 00:31:03.495374: train_loss -0.8188 +2024-11-23 00:31:03.495600: val_loss -0.7397 +2024-11-23 00:31:03.495682: Pseudo dice [0.8513] +2024-11-23 00:31:03.498004: Epoch time: 18.11 s +2024-11-23 00:31:04.424093: +2024-11-23 00:31:04.424301: Epoch 7028 +2024-11-23 00:31:04.424412: Current learning rate: 0.0015 +2024-11-23 00:31:21.763473: train_loss -0.818 +2024-11-23 00:31:21.763733: val_loss -0.7884 +2024-11-23 00:31:21.763816: Pseudo dice [0.8558] +2024-11-23 00:31:21.763896: Epoch time: 17.34 s +2024-11-23 00:31:22.695130: +2024-11-23 00:31:22.695373: Epoch 7029 +2024-11-23 00:31:22.695483: Current learning rate: 0.0015 +2024-11-23 00:31:42.034175: train_loss -0.8167 +2024-11-23 00:31:42.034628: val_loss -0.7885 +2024-11-23 00:31:42.034722: Pseudo dice [0.8502] +2024-11-23 00:31:42.034797: Epoch time: 19.34 s +2024-11-23 00:31:42.938333: +2024-11-23 00:31:42.938555: Epoch 7030 +2024-11-23 00:31:42.938662: Current learning rate: 0.0015 +2024-11-23 00:32:01.425641: train_loss -0.8131 +2024-11-23 00:32:01.425850: val_loss -0.788 +2024-11-23 00:32:01.425924: Pseudo dice [0.8599] +2024-11-23 00:32:01.426005: Epoch time: 18.49 s +2024-11-23 00:32:02.342918: +2024-11-23 00:32:02.343139: Epoch 7031 +2024-11-23 00:32:02.343247: Current learning rate: 0.0015 +2024-11-23 00:32:20.615627: train_loss -0.8151 +2024-11-23 00:32:20.615861: val_loss -0.7783 +2024-11-23 00:32:20.635565: Pseudo dice [0.8597] +2024-11-23 00:32:20.635740: Epoch time: 18.27 s +2024-11-23 00:32:21.552331: +2024-11-23 00:32:21.552539: Epoch 7032 +2024-11-23 00:32:21.552644: Current learning rate: 0.00149 +2024-11-23 00:32:39.953963: train_loss -0.8172 +2024-11-23 00:32:39.954208: val_loss -0.7926 +2024-11-23 00:32:39.954479: Pseudo dice [0.8605] +2024-11-23 00:32:39.954564: Epoch time: 18.4 s +2024-11-23 00:32:40.861912: +2024-11-23 00:32:40.862118: Epoch 7033 +2024-11-23 00:32:40.862225: Current learning rate: 0.00149 +2024-11-23 00:32:58.992888: train_loss -0.8158 +2024-11-23 00:32:58.993121: val_loss -0.7928 +2024-11-23 00:32:58.993208: Pseudo dice [0.8609] +2024-11-23 00:32:58.993317: Epoch time: 18.13 s +2024-11-23 00:32:59.900447: +2024-11-23 00:32:59.900668: Epoch 7034 +2024-11-23 00:32:59.900787: Current learning rate: 0.00149 +2024-11-23 00:33:18.239003: train_loss -0.8238 +2024-11-23 00:33:18.239241: val_loss -0.7657 +2024-11-23 00:33:18.239319: Pseudo dice [0.837] +2024-11-23 00:33:18.239399: Epoch time: 18.34 s +2024-11-23 00:33:19.149452: +2024-11-23 00:33:19.149699: Epoch 7035 +2024-11-23 00:33:19.149808: Current learning rate: 0.00149 +2024-11-23 00:33:37.523047: train_loss -0.8177 +2024-11-23 00:33:37.523273: val_loss -0.787 +2024-11-23 00:33:37.523359: Pseudo dice [0.8682] +2024-11-23 00:33:37.523439: Epoch time: 18.37 s +2024-11-23 00:33:38.431553: +2024-11-23 00:33:38.431797: Epoch 7036 +2024-11-23 00:33:38.431913: Current learning rate: 0.00149 +2024-11-23 00:33:57.311038: train_loss -0.813 +2024-11-23 00:33:57.311296: val_loss -0.7671 +2024-11-23 00:33:57.311371: Pseudo dice [0.8546] +2024-11-23 00:33:57.311449: Epoch time: 18.88 s +2024-11-23 00:33:58.330271: +2024-11-23 00:33:58.330544: Epoch 7037 +2024-11-23 00:33:58.330654: Current learning rate: 0.00149 +2024-11-23 00:34:16.316621: train_loss -0.8149 +2024-11-23 00:34:16.316861: val_loss -0.7633 +2024-11-23 00:34:16.316935: Pseudo dice [0.8426] +2024-11-23 00:34:16.317016: Epoch time: 17.99 s +2024-11-23 00:34:17.237024: +2024-11-23 00:34:17.237225: Epoch 7038 +2024-11-23 00:34:17.237331: Current learning rate: 0.00149 +2024-11-23 00:34:34.979798: train_loss -0.8138 +2024-11-23 00:34:34.980037: val_loss -0.7842 +2024-11-23 00:34:34.980114: Pseudo dice [0.8443] +2024-11-23 00:34:34.980213: Epoch time: 17.74 s +2024-11-23 00:34:35.891302: +2024-11-23 00:34:35.891526: Epoch 7039 +2024-11-23 00:34:35.891650: Current learning rate: 0.00148 +2024-11-23 00:34:54.688021: train_loss -0.8198 +2024-11-23 00:34:54.688265: val_loss -0.7889 +2024-11-23 00:34:54.688341: Pseudo dice [0.852] +2024-11-23 00:34:54.688426: Epoch time: 18.8 s +2024-11-23 00:34:55.594789: +2024-11-23 00:34:55.595006: Epoch 7040 +2024-11-23 00:34:55.595114: Current learning rate: 0.00148 +2024-11-23 00:35:13.534116: train_loss -0.815 +2024-11-23 00:35:13.534763: val_loss -0.7706 +2024-11-23 00:35:13.534846: Pseudo dice [0.8508] +2024-11-23 00:35:13.534923: Epoch time: 17.94 s +2024-11-23 00:35:14.944063: +2024-11-23 00:35:14.944292: Epoch 7041 +2024-11-23 00:35:14.944404: Current learning rate: 0.00148 +2024-11-23 00:35:33.840758: train_loss -0.8246 +2024-11-23 00:35:33.841272: val_loss -0.7849 +2024-11-23 00:35:33.841373: Pseudo dice [0.8619] +2024-11-23 00:35:33.841449: Epoch time: 18.9 s +2024-11-23 00:35:34.794129: +2024-11-23 00:35:34.794439: Epoch 7042 +2024-11-23 00:35:34.794555: Current learning rate: 0.00148 +2024-11-23 00:35:54.372100: train_loss -0.8183 +2024-11-23 00:35:54.372398: val_loss -0.773 +2024-11-23 00:35:54.372476: Pseudo dice [0.8636] +2024-11-23 00:35:54.372549: Epoch time: 19.58 s +2024-11-23 00:35:55.282485: +2024-11-23 00:35:55.282772: Epoch 7043 +2024-11-23 00:35:55.282881: Current learning rate: 0.00148 +2024-11-23 00:36:13.593452: train_loss -0.8179 +2024-11-23 00:36:13.593764: val_loss -0.7601 +2024-11-23 00:36:13.593843: Pseudo dice [0.8417] +2024-11-23 00:36:13.593924: Epoch time: 18.31 s +2024-11-23 00:36:14.530593: +2024-11-23 00:36:14.530878: Epoch 7044 +2024-11-23 00:36:14.530989: Current learning rate: 0.00148 +2024-11-23 00:36:32.374728: train_loss -0.8244 +2024-11-23 00:36:32.374945: val_loss -0.8031 +2024-11-23 00:36:32.375032: Pseudo dice [0.8574] +2024-11-23 00:36:32.375108: Epoch time: 17.84 s +2024-11-23 00:36:33.282862: +2024-11-23 00:36:33.283089: Epoch 7045 +2024-11-23 00:36:33.283198: Current learning rate: 0.00148 +2024-11-23 00:36:51.723412: train_loss -0.817 +2024-11-23 00:36:51.723645: val_loss -0.7871 +2024-11-23 00:36:51.723724: Pseudo dice [0.8459] +2024-11-23 00:36:51.723803: Epoch time: 18.44 s +2024-11-23 00:36:52.624258: +2024-11-23 00:36:52.624484: Epoch 7046 +2024-11-23 00:36:52.624593: Current learning rate: 0.00148 +2024-11-23 00:37:10.086592: train_loss -0.8236 +2024-11-23 00:37:10.086812: val_loss -0.7891 +2024-11-23 00:37:10.086885: Pseudo dice [0.8622] +2024-11-23 00:37:10.086959: Epoch time: 17.46 s +2024-11-23 00:37:10.992809: +2024-11-23 00:37:10.993044: Epoch 7047 +2024-11-23 00:37:10.993160: Current learning rate: 0.00147 +2024-11-23 00:37:29.781750: train_loss -0.8232 +2024-11-23 00:37:29.782007: val_loss -0.7822 +2024-11-23 00:37:29.782084: Pseudo dice [0.8619] +2024-11-23 00:37:29.782171: Epoch time: 18.79 s +2024-11-23 00:37:30.742559: +2024-11-23 00:37:30.742789: Epoch 7048 +2024-11-23 00:37:30.742905: Current learning rate: 0.00147 +2024-11-23 00:37:49.276519: train_loss -0.8256 +2024-11-23 00:37:49.277119: val_loss -0.8005 +2024-11-23 00:37:49.277202: Pseudo dice [0.8603] +2024-11-23 00:37:49.277278: Epoch time: 18.53 s +2024-11-23 00:37:50.184670: +2024-11-23 00:37:50.184895: Epoch 7049 +2024-11-23 00:37:50.185012: Current learning rate: 0.00147 +2024-11-23 00:38:09.312803: train_loss -0.8232 +2024-11-23 00:38:09.313087: val_loss -0.7735 +2024-11-23 00:38:09.313169: Pseudo dice [0.8435] +2024-11-23 00:38:09.313249: Epoch time: 19.13 s +2024-11-23 00:38:10.546339: +2024-11-23 00:38:10.546579: Epoch 7050 +2024-11-23 00:38:10.546690: Current learning rate: 0.00147 +2024-11-23 00:38:28.088299: train_loss -0.8217 +2024-11-23 00:38:28.088553: val_loss -0.7607 +2024-11-23 00:38:28.088630: Pseudo dice [0.8418] +2024-11-23 00:38:28.088711: Epoch time: 17.54 s +2024-11-23 00:38:28.990959: +2024-11-23 00:38:28.991180: Epoch 7051 +2024-11-23 00:38:28.991290: Current learning rate: 0.00147 +2024-11-23 00:38:47.590263: train_loss -0.8215 +2024-11-23 00:38:47.590476: val_loss -0.7688 +2024-11-23 00:38:47.590548: Pseudo dice [0.8415] +2024-11-23 00:38:47.590624: Epoch time: 18.6 s +2024-11-23 00:38:48.499205: +2024-11-23 00:38:48.499416: Epoch 7052 +2024-11-23 00:38:48.499525: Current learning rate: 0.00147 +2024-11-23 00:39:06.699995: train_loss -0.8221 +2024-11-23 00:39:06.700480: val_loss -0.7978 +2024-11-23 00:39:06.700579: Pseudo dice [0.8598] +2024-11-23 00:39:06.700655: Epoch time: 18.2 s +2024-11-23 00:39:07.612782: +2024-11-23 00:39:07.613010: Epoch 7053 +2024-11-23 00:39:07.613121: Current learning rate: 0.00147 +2024-11-23 00:39:26.287706: train_loss -0.8222 +2024-11-23 00:39:26.293109: val_loss -0.7798 +2024-11-23 00:39:26.293221: Pseudo dice [0.8563] +2024-11-23 00:39:26.293295: Epoch time: 18.68 s +2024-11-23 00:39:27.371125: +2024-11-23 00:39:27.371353: Epoch 7054 +2024-11-23 00:39:27.371462: Current learning rate: 0.00146 +2024-11-23 00:39:45.353555: train_loss -0.8184 +2024-11-23 00:39:45.353790: val_loss -0.7642 +2024-11-23 00:39:45.353866: Pseudo dice [0.8431] +2024-11-23 00:39:45.353945: Epoch time: 17.98 s +2024-11-23 00:39:46.281520: +2024-11-23 00:39:46.281743: Epoch 7055 +2024-11-23 00:39:46.281855: Current learning rate: 0.00146 +2024-11-23 00:40:05.314244: train_loss -0.8244 +2024-11-23 00:40:05.314461: val_loss -0.7813 +2024-11-23 00:40:05.314535: Pseudo dice [0.8575] +2024-11-23 00:40:05.314609: Epoch time: 19.03 s +2024-11-23 00:40:06.218561: +2024-11-23 00:40:06.218770: Epoch 7056 +2024-11-23 00:40:06.218878: Current learning rate: 0.00146 +2024-11-23 00:40:24.294841: train_loss -0.8232 +2024-11-23 00:40:24.295063: val_loss -0.767 +2024-11-23 00:40:24.295137: Pseudo dice [0.8461] +2024-11-23 00:40:24.295211: Epoch time: 18.08 s +2024-11-23 00:40:25.205155: +2024-11-23 00:40:25.205377: Epoch 7057 +2024-11-23 00:40:25.205492: Current learning rate: 0.00146 +2024-11-23 00:40:44.188037: train_loss -0.8172 +2024-11-23 00:40:44.188258: val_loss -0.762 +2024-11-23 00:40:44.188331: Pseudo dice [0.8548] +2024-11-23 00:40:44.188410: Epoch time: 18.98 s +2024-11-23 00:40:45.099633: +2024-11-23 00:40:45.099853: Epoch 7058 +2024-11-23 00:40:45.099963: Current learning rate: 0.00146 +2024-11-23 00:41:04.787663: train_loss -0.8203 +2024-11-23 00:41:04.787921: val_loss -0.7901 +2024-11-23 00:41:04.788215: Pseudo dice [0.8571] +2024-11-23 00:41:04.788301: Epoch time: 19.69 s +2024-11-23 00:41:05.698058: +2024-11-23 00:41:05.698285: Epoch 7059 +2024-11-23 00:41:05.698400: Current learning rate: 0.00146 +2024-11-23 00:41:23.815527: train_loss -0.8277 +2024-11-23 00:41:23.817919: val_loss -0.7864 +2024-11-23 00:41:23.818012: Pseudo dice [0.8483] +2024-11-23 00:41:23.818089: Epoch time: 18.12 s +2024-11-23 00:41:24.734550: +2024-11-23 00:41:24.734761: Epoch 7060 +2024-11-23 00:41:24.734891: Current learning rate: 0.00146 +2024-11-23 00:41:44.441778: train_loss -0.8149 +2024-11-23 00:41:44.442020: val_loss -0.791 +2024-11-23 00:41:44.442095: Pseudo dice [0.8616] +2024-11-23 00:41:44.442171: Epoch time: 19.71 s +2024-11-23 00:41:45.349229: +2024-11-23 00:41:45.349459: Epoch 7061 +2024-11-23 00:41:45.349566: Current learning rate: 0.00145 +2024-11-23 00:42:02.778874: train_loss -0.8323 +2024-11-23 00:42:02.779099: val_loss -0.8008 +2024-11-23 00:42:02.779173: Pseudo dice [0.854] +2024-11-23 00:42:02.779248: Epoch time: 17.43 s +2024-11-23 00:42:03.691472: +2024-11-23 00:42:03.691694: Epoch 7062 +2024-11-23 00:42:03.691805: Current learning rate: 0.00145 +2024-11-23 00:42:21.582546: train_loss -0.8216 +2024-11-23 00:42:21.582782: val_loss -0.7932 +2024-11-23 00:42:21.582875: Pseudo dice [0.8576] +2024-11-23 00:42:21.582968: Epoch time: 17.89 s +2024-11-23 00:42:22.489715: +2024-11-23 00:42:22.489981: Epoch 7063 +2024-11-23 00:42:22.490093: Current learning rate: 0.00145 +2024-11-23 00:42:42.229584: train_loss -0.8217 +2024-11-23 00:42:42.229809: val_loss -0.787 +2024-11-23 00:42:42.229892: Pseudo dice [0.8621] +2024-11-23 00:42:42.229965: Epoch time: 19.74 s +2024-11-23 00:42:43.505886: +2024-11-23 00:42:43.506150: Epoch 7064 +2024-11-23 00:42:43.506259: Current learning rate: 0.00145 +2024-11-23 00:43:02.352496: train_loss -0.8199 +2024-11-23 00:43:02.352721: val_loss -0.7583 +2024-11-23 00:43:02.352796: Pseudo dice [0.839] +2024-11-23 00:43:02.352868: Epoch time: 18.85 s +2024-11-23 00:43:03.266545: +2024-11-23 00:43:03.266755: Epoch 7065 +2024-11-23 00:43:03.266861: Current learning rate: 0.00145 +2024-11-23 00:43:21.926487: train_loss -0.8204 +2024-11-23 00:43:21.926740: val_loss -0.7575 +2024-11-23 00:43:21.926817: Pseudo dice [0.849] +2024-11-23 00:43:21.926901: Epoch time: 18.66 s +2024-11-23 00:43:22.840617: +2024-11-23 00:43:22.840849: Epoch 7066 +2024-11-23 00:43:22.840960: Current learning rate: 0.00145 +2024-11-23 00:43:41.219178: train_loss -0.8144 +2024-11-23 00:43:41.219452: val_loss -0.7822 +2024-11-23 00:43:41.219529: Pseudo dice [0.8507] +2024-11-23 00:43:41.219599: Epoch time: 18.38 s +2024-11-23 00:43:42.131295: +2024-11-23 00:43:42.131513: Epoch 7067 +2024-11-23 00:43:42.131623: Current learning rate: 0.00145 +2024-11-23 00:44:00.644505: train_loss -0.8133 +2024-11-23 00:44:00.644725: val_loss -0.7901 +2024-11-23 00:44:00.644810: Pseudo dice [0.852] +2024-11-23 00:44:00.644889: Epoch time: 18.51 s +2024-11-23 00:44:01.554200: +2024-11-23 00:44:01.554433: Epoch 7068 +2024-11-23 00:44:01.554543: Current learning rate: 0.00144 +2024-11-23 00:44:18.942362: train_loss -0.8262 +2024-11-23 00:44:18.942597: val_loss -0.8028 +2024-11-23 00:44:18.942673: Pseudo dice [0.855] +2024-11-23 00:44:18.942747: Epoch time: 17.39 s +2024-11-23 00:44:19.852094: +2024-11-23 00:44:19.852330: Epoch 7069 +2024-11-23 00:44:19.852443: Current learning rate: 0.00144 +2024-11-23 00:44:39.263516: train_loss -0.8243 +2024-11-23 00:44:39.263737: val_loss -0.7832 +2024-11-23 00:44:39.281301: Pseudo dice [0.863] +2024-11-23 00:44:39.281400: Epoch time: 19.41 s +2024-11-23 00:44:40.197235: +2024-11-23 00:44:40.197463: Epoch 7070 +2024-11-23 00:44:40.197570: Current learning rate: 0.00144 +2024-11-23 00:44:59.230728: train_loss -0.8178 +2024-11-23 00:44:59.230954: val_loss -0.7747 +2024-11-23 00:44:59.231042: Pseudo dice [0.8455] +2024-11-23 00:44:59.231121: Epoch time: 19.03 s +2024-11-23 00:45:00.139229: +2024-11-23 00:45:00.139522: Epoch 7071 +2024-11-23 00:45:00.139631: Current learning rate: 0.00144 +2024-11-23 00:45:18.685668: train_loss -0.8278 +2024-11-23 00:45:18.685891: val_loss -0.7769 +2024-11-23 00:45:18.685966: Pseudo dice [0.8647] +2024-11-23 00:45:18.686054: Epoch time: 18.55 s +2024-11-23 00:45:19.598177: +2024-11-23 00:45:19.598428: Epoch 7072 +2024-11-23 00:45:19.598541: Current learning rate: 0.00144 +2024-11-23 00:45:39.318282: train_loss -0.816 +2024-11-23 00:45:39.318497: val_loss -0.7959 +2024-11-23 00:45:39.318575: Pseudo dice [0.8595] +2024-11-23 00:45:39.318651: Epoch time: 19.72 s +2024-11-23 00:45:40.224751: +2024-11-23 00:45:40.224982: Epoch 7073 +2024-11-23 00:45:40.225100: Current learning rate: 0.00144 +2024-11-23 00:45:59.228518: train_loss -0.8127 +2024-11-23 00:45:59.233956: val_loss -0.7905 +2024-11-23 00:45:59.234054: Pseudo dice [0.8498] +2024-11-23 00:45:59.234143: Epoch time: 19.0 s +2024-11-23 00:46:00.346555: +2024-11-23 00:46:00.346760: Epoch 7074 +2024-11-23 00:46:00.346869: Current learning rate: 0.00144 +2024-11-23 00:46:18.490927: train_loss -0.8191 +2024-11-23 00:46:18.491150: val_loss -0.7849 +2024-11-23 00:46:18.491227: Pseudo dice [0.8612] +2024-11-23 00:46:18.491302: Epoch time: 18.15 s +2024-11-23 00:46:19.748406: +2024-11-23 00:46:19.748630: Epoch 7075 +2024-11-23 00:46:19.748738: Current learning rate: 0.00143 +2024-11-23 00:46:37.104942: train_loss -0.823 +2024-11-23 00:46:37.105183: val_loss -0.7576 +2024-11-23 00:46:37.105257: Pseudo dice [0.8439] +2024-11-23 00:46:37.105329: Epoch time: 17.36 s +2024-11-23 00:46:38.022408: +2024-11-23 00:46:38.022649: Epoch 7076 +2024-11-23 00:46:38.022758: Current learning rate: 0.00143 +2024-11-23 00:46:56.658023: train_loss -0.8164 +2024-11-23 00:46:56.658253: val_loss -0.7722 +2024-11-23 00:46:56.658328: Pseudo dice [0.8499] +2024-11-23 00:46:56.658403: Epoch time: 18.64 s +2024-11-23 00:46:57.567208: +2024-11-23 00:46:57.567409: Epoch 7077 +2024-11-23 00:46:57.567514: Current learning rate: 0.00143 +2024-11-23 00:47:16.103456: train_loss -0.8194 +2024-11-23 00:47:16.103712: val_loss -0.7819 +2024-11-23 00:47:16.103788: Pseudo dice [0.8513] +2024-11-23 00:47:16.103873: Epoch time: 18.54 s +2024-11-23 00:47:17.022443: +2024-11-23 00:47:17.022666: Epoch 7078 +2024-11-23 00:47:17.022774: Current learning rate: 0.00143 +2024-11-23 00:47:35.336570: train_loss -0.8201 +2024-11-23 00:47:35.336822: val_loss -0.7726 +2024-11-23 00:47:35.336902: Pseudo dice [0.8405] +2024-11-23 00:47:35.337007: Epoch time: 18.31 s +2024-11-23 00:47:36.254001: +2024-11-23 00:47:36.254225: Epoch 7079 +2024-11-23 00:47:36.254331: Current learning rate: 0.00143 +2024-11-23 00:47:54.499021: train_loss -0.8189 +2024-11-23 00:47:54.499242: val_loss -0.781 +2024-11-23 00:47:54.499319: Pseudo dice [0.8694] +2024-11-23 00:47:54.499395: Epoch time: 18.25 s +2024-11-23 00:47:55.406128: +2024-11-23 00:47:55.406350: Epoch 7080 +2024-11-23 00:47:55.406461: Current learning rate: 0.00143 +2024-11-23 00:48:13.772777: train_loss -0.8237 +2024-11-23 00:48:13.772989: val_loss -0.7535 +2024-11-23 00:48:13.773073: Pseudo dice [0.8509] +2024-11-23 00:48:13.773152: Epoch time: 18.37 s +2024-11-23 00:48:14.681175: +2024-11-23 00:48:14.681397: Epoch 7081 +2024-11-23 00:48:14.681504: Current learning rate: 0.00143 +2024-11-23 00:48:32.743183: train_loss -0.827 +2024-11-23 00:48:32.743434: val_loss -0.7853 +2024-11-23 00:48:32.745755: Pseudo dice [0.8654] +2024-11-23 00:48:32.745853: Epoch time: 18.06 s +2024-11-23 00:48:33.671571: +2024-11-23 00:48:33.671785: Epoch 7082 +2024-11-23 00:48:33.671891: Current learning rate: 0.00142 +2024-11-23 00:48:52.882412: train_loss -0.8201 +2024-11-23 00:48:52.882650: val_loss -0.7901 +2024-11-23 00:48:52.882732: Pseudo dice [0.867] +2024-11-23 00:48:52.882808: Epoch time: 19.21 s +2024-11-23 00:48:53.798425: +2024-11-23 00:48:53.798662: Epoch 7083 +2024-11-23 00:48:53.798770: Current learning rate: 0.00142 +2024-11-23 00:49:14.011191: train_loss -0.82 +2024-11-23 00:49:14.011419: val_loss -0.7834 +2024-11-23 00:49:14.011496: Pseudo dice [0.8531] +2024-11-23 00:49:14.011579: Epoch time: 20.21 s +2024-11-23 00:49:14.921490: +2024-11-23 00:49:14.921718: Epoch 7084 +2024-11-23 00:49:14.921829: Current learning rate: 0.00142 +2024-11-23 00:49:33.082102: train_loss -0.8181 +2024-11-23 00:49:33.082331: val_loss -0.7751 +2024-11-23 00:49:33.082569: Pseudo dice [0.8527] +2024-11-23 00:49:33.082650: Epoch time: 18.16 s +2024-11-23 00:49:34.048233: +2024-11-23 00:49:34.048480: Epoch 7085 +2024-11-23 00:49:34.048604: Current learning rate: 0.00142 +2024-11-23 00:49:53.294234: train_loss -0.8114 +2024-11-23 00:49:53.294479: val_loss -0.7696 +2024-11-23 00:49:53.294552: Pseudo dice [0.8588] +2024-11-23 00:49:53.294633: Epoch time: 19.25 s +2024-11-23 00:49:54.239622: +2024-11-23 00:49:54.239889: Epoch 7086 +2024-11-23 00:49:54.240005: Current learning rate: 0.00142 +2024-11-23 00:50:12.824023: train_loss -0.8201 +2024-11-23 00:50:12.824239: val_loss -0.7776 +2024-11-23 00:50:12.824313: Pseudo dice [0.8511] +2024-11-23 00:50:12.824386: Epoch time: 18.59 s +2024-11-23 00:50:14.127307: +2024-11-23 00:50:14.127529: Epoch 7087 +2024-11-23 00:50:14.127645: Current learning rate: 0.00142 +2024-11-23 00:50:32.212733: train_loss -0.822 +2024-11-23 00:50:32.212964: val_loss -0.7822 +2024-11-23 00:50:32.213045: Pseudo dice [0.8633] +2024-11-23 00:50:32.213121: Epoch time: 18.09 s +2024-11-23 00:50:33.123400: +2024-11-23 00:50:33.123622: Epoch 7088 +2024-11-23 00:50:33.123733: Current learning rate: 0.00142 +2024-11-23 00:50:51.726547: train_loss -0.8218 +2024-11-23 00:50:51.726801: val_loss -0.7678 +2024-11-23 00:50:51.729129: Pseudo dice [0.841] +2024-11-23 00:50:51.729242: Epoch time: 18.6 s +2024-11-23 00:50:52.676343: +2024-11-23 00:50:52.676589: Epoch 7089 +2024-11-23 00:50:52.676716: Current learning rate: 0.00142 +2024-11-23 00:51:11.280398: train_loss -0.8243 +2024-11-23 00:51:11.280619: val_loss -0.7917 +2024-11-23 00:51:11.280693: Pseudo dice [0.8647] +2024-11-23 00:51:11.280773: Epoch time: 18.6 s +2024-11-23 00:51:12.193912: +2024-11-23 00:51:12.194142: Epoch 7090 +2024-11-23 00:51:12.194248: Current learning rate: 0.00141 +2024-11-23 00:51:30.205495: train_loss -0.826 +2024-11-23 00:51:30.205710: val_loss -0.7677 +2024-11-23 00:51:30.205786: Pseudo dice [0.853] +2024-11-23 00:51:30.205861: Epoch time: 18.01 s +2024-11-23 00:51:31.120344: +2024-11-23 00:51:31.120555: Epoch 7091 +2024-11-23 00:51:31.120666: Current learning rate: 0.00141 +2024-11-23 00:51:49.969587: train_loss -0.8261 +2024-11-23 00:51:49.971984: val_loss -0.8018 +2024-11-23 00:51:49.972113: Pseudo dice [0.8614] +2024-11-23 00:51:49.972189: Epoch time: 18.85 s +2024-11-23 00:51:50.887791: +2024-11-23 00:51:50.888020: Epoch 7092 +2024-11-23 00:51:50.888129: Current learning rate: 0.00141 +2024-11-23 00:52:09.346119: train_loss -0.8295 +2024-11-23 00:52:09.346345: val_loss -0.7689 +2024-11-23 00:52:09.346424: Pseudo dice [0.8704] +2024-11-23 00:52:09.348692: Epoch time: 18.46 s +2024-11-23 00:52:10.381439: +2024-11-23 00:52:10.381686: Epoch 7093 +2024-11-23 00:52:10.381837: Current learning rate: 0.00141 +2024-11-23 00:52:29.669141: train_loss -0.8195 +2024-11-23 00:52:29.669366: val_loss -0.7733 +2024-11-23 00:52:29.669441: Pseudo dice [0.857] +2024-11-23 00:52:29.669534: Epoch time: 19.29 s +2024-11-23 00:52:30.578311: +2024-11-23 00:52:30.578564: Epoch 7094 +2024-11-23 00:52:30.578676: Current learning rate: 0.00141 +2024-11-23 00:52:49.846873: train_loss -0.8188 +2024-11-23 00:52:49.847105: val_loss -0.7672 +2024-11-23 00:52:49.847181: Pseudo dice [0.8587] +2024-11-23 00:52:49.847255: Epoch time: 19.27 s +2024-11-23 00:52:50.755747: +2024-11-23 00:52:50.755959: Epoch 7095 +2024-11-23 00:52:50.756072: Current learning rate: 0.00141 +2024-11-23 00:53:09.967269: train_loss -0.8231 +2024-11-23 00:53:09.967488: val_loss -0.7825 +2024-11-23 00:53:09.967560: Pseudo dice [0.8478] +2024-11-23 00:53:09.967634: Epoch time: 19.21 s +2024-11-23 00:53:10.866893: +2024-11-23 00:53:10.867115: Epoch 7096 +2024-11-23 00:53:10.867223: Current learning rate: 0.00141 +2024-11-23 00:53:28.429669: train_loss -0.8246 +2024-11-23 00:53:28.429913: val_loss -0.7917 +2024-11-23 00:53:28.429988: Pseudo dice [0.8452] +2024-11-23 00:53:28.430073: Epoch time: 17.56 s +2024-11-23 00:53:29.442576: +2024-11-23 00:53:29.442806: Epoch 7097 +2024-11-23 00:53:29.442920: Current learning rate: 0.0014 +2024-11-23 00:53:47.679415: train_loss -0.8219 +2024-11-23 00:53:47.679625: val_loss -0.7904 +2024-11-23 00:53:47.679700: Pseudo dice [0.8497] +2024-11-23 00:53:47.679773: Epoch time: 18.24 s +2024-11-23 00:53:49.090180: +2024-11-23 00:53:49.090440: Epoch 7098 +2024-11-23 00:53:49.090551: Current learning rate: 0.0014 +2024-11-23 00:54:07.408362: train_loss -0.8243 +2024-11-23 00:54:07.408588: val_loss -0.7656 +2024-11-23 00:54:07.408664: Pseudo dice [0.8491] +2024-11-23 00:54:07.408742: Epoch time: 18.32 s +2024-11-23 00:54:08.320565: +2024-11-23 00:54:08.320817: Epoch 7099 +2024-11-23 00:54:08.320930: Current learning rate: 0.0014 +2024-11-23 00:54:27.880211: train_loss -0.8215 +2024-11-23 00:54:27.880420: val_loss -0.7724 +2024-11-23 00:54:27.880496: Pseudo dice [0.8589] +2024-11-23 00:54:27.880570: Epoch time: 19.56 s +2024-11-23 00:54:29.137202: +2024-11-23 00:54:29.137403: Epoch 7100 +2024-11-23 00:54:29.137510: Current learning rate: 0.0014 +2024-11-23 00:54:48.274654: train_loss -0.8243 +2024-11-23 00:54:48.274910: val_loss -0.7858 +2024-11-23 00:54:48.279133: Pseudo dice [0.8656] +2024-11-23 00:54:48.279284: Epoch time: 19.14 s +2024-11-23 00:54:49.259524: +2024-11-23 00:54:49.259767: Epoch 7101 +2024-11-23 00:54:49.259876: Current learning rate: 0.0014 +2024-11-23 00:55:07.658450: train_loss -0.8187 +2024-11-23 00:55:07.658665: val_loss -0.7806 +2024-11-23 00:55:07.658741: Pseudo dice [0.8492] +2024-11-23 00:55:07.658816: Epoch time: 18.4 s +2024-11-23 00:55:08.563074: +2024-11-23 00:55:08.563279: Epoch 7102 +2024-11-23 00:55:08.563387: Current learning rate: 0.0014 +2024-11-23 00:55:26.569307: train_loss -0.8191 +2024-11-23 00:55:26.569539: val_loss -0.7811 +2024-11-23 00:55:26.569613: Pseudo dice [0.8609] +2024-11-23 00:55:26.569686: Epoch time: 18.01 s +2024-11-23 00:55:27.481617: +2024-11-23 00:55:27.481847: Epoch 7103 +2024-11-23 00:55:27.481966: Current learning rate: 0.0014 +2024-11-23 00:55:45.902282: train_loss -0.8277 +2024-11-23 00:55:45.907691: val_loss -0.7581 +2024-11-23 00:55:45.907814: Pseudo dice [0.8555] +2024-11-23 00:55:45.907894: Epoch time: 18.42 s +2024-11-23 00:55:46.830371: +2024-11-23 00:55:46.830607: Epoch 7104 +2024-11-23 00:55:46.830719: Current learning rate: 0.00139 +2024-11-23 00:56:05.023447: train_loss -0.8178 +2024-11-23 00:56:05.023697: val_loss -0.7801 +2024-11-23 00:56:05.023785: Pseudo dice [0.8526] +2024-11-23 00:56:05.023891: Epoch time: 18.19 s +2024-11-23 00:56:05.938363: +2024-11-23 00:56:05.938566: Epoch 7105 +2024-11-23 00:56:05.938674: Current learning rate: 0.00139 +2024-11-23 00:56:24.164926: train_loss -0.8236 +2024-11-23 00:56:24.165146: val_loss -0.7682 +2024-11-23 00:56:24.165221: Pseudo dice [0.843] +2024-11-23 00:56:24.165293: Epoch time: 18.23 s +2024-11-23 00:56:25.070982: +2024-11-23 00:56:25.071197: Epoch 7106 +2024-11-23 00:56:25.071306: Current learning rate: 0.00139 +2024-11-23 00:56:43.309394: train_loss -0.8155 +2024-11-23 00:56:43.309618: val_loss -0.7961 +2024-11-23 00:56:43.309693: Pseudo dice [0.8487] +2024-11-23 00:56:43.309768: Epoch time: 18.24 s +2024-11-23 00:56:44.213011: +2024-11-23 00:56:44.213222: Epoch 7107 +2024-11-23 00:56:44.213335: Current learning rate: 0.00139 +2024-11-23 00:57:03.485037: train_loss -0.8167 +2024-11-23 00:57:03.485251: val_loss -0.7825 +2024-11-23 00:57:03.485366: Pseudo dice [0.8709] +2024-11-23 00:57:03.485440: Epoch time: 19.27 s +2024-11-23 00:57:04.396019: +2024-11-23 00:57:04.396253: Epoch 7108 +2024-11-23 00:57:04.396358: Current learning rate: 0.00139 +2024-11-23 00:57:23.239965: train_loss -0.8205 +2024-11-23 00:57:23.240243: val_loss -0.7807 +2024-11-23 00:57:23.240316: Pseudo dice [0.8561] +2024-11-23 00:57:23.240396: Epoch time: 18.84 s +2024-11-23 00:57:24.259428: +2024-11-23 00:57:24.259660: Epoch 7109 +2024-11-23 00:57:24.259772: Current learning rate: 0.00139 +2024-11-23 00:57:42.913679: train_loss -0.8268 +2024-11-23 00:57:42.919086: val_loss -0.7971 +2024-11-23 00:57:42.919193: Pseudo dice [0.8653] +2024-11-23 00:57:42.919272: Epoch time: 18.66 s +2024-11-23 00:57:44.253048: +2024-11-23 00:57:44.253302: Epoch 7110 +2024-11-23 00:57:44.253414: Current learning rate: 0.00139 +2024-11-23 00:58:03.077178: train_loss -0.8119 +2024-11-23 00:58:03.077489: val_loss -0.7832 +2024-11-23 00:58:03.077590: Pseudo dice [0.8455] +2024-11-23 00:58:03.077667: Epoch time: 18.82 s +2024-11-23 00:58:04.028718: +2024-11-23 00:58:04.028951: Epoch 7111 +2024-11-23 00:58:04.029067: Current learning rate: 0.00138 +2024-11-23 00:58:22.342444: train_loss -0.8219 +2024-11-23 00:58:22.342702: val_loss -0.7835 +2024-11-23 00:58:22.342780: Pseudo dice [0.8424] +2024-11-23 00:58:22.342869: Epoch time: 18.31 s +2024-11-23 00:58:23.261596: +2024-11-23 00:58:23.261820: Epoch 7112 +2024-11-23 00:58:23.261931: Current learning rate: 0.00138 +2024-11-23 00:58:40.966226: train_loss -0.8144 +2024-11-23 00:58:40.966444: val_loss -0.7915 +2024-11-23 00:58:40.966519: Pseudo dice [0.8595] +2024-11-23 00:58:40.966593: Epoch time: 17.71 s +2024-11-23 00:58:41.874981: +2024-11-23 00:58:41.875218: Epoch 7113 +2024-11-23 00:58:41.875339: Current learning rate: 0.00138 +2024-11-23 00:58:59.772800: train_loss -0.818 +2024-11-23 00:58:59.773080: val_loss -0.7648 +2024-11-23 00:58:59.773160: Pseudo dice [0.8339] +2024-11-23 00:58:59.773236: Epoch time: 17.9 s +2024-11-23 00:59:00.684357: +2024-11-23 00:59:00.684597: Epoch 7114 +2024-11-23 00:59:00.684712: Current learning rate: 0.00138 +2024-11-23 00:59:19.279359: train_loss -0.8218 +2024-11-23 00:59:19.279590: val_loss -0.7773 +2024-11-23 00:59:19.279691: Pseudo dice [0.8451] +2024-11-23 00:59:19.279812: Epoch time: 18.6 s +2024-11-23 00:59:20.197487: +2024-11-23 00:59:20.197816: Epoch 7115 +2024-11-23 00:59:20.197927: Current learning rate: 0.00138 +2024-11-23 00:59:38.778761: train_loss -0.8216 +2024-11-23 00:59:38.778985: val_loss -0.775 +2024-11-23 00:59:38.779068: Pseudo dice [0.8471] +2024-11-23 00:59:38.779148: Epoch time: 18.58 s +2024-11-23 00:59:39.689361: +2024-11-23 00:59:39.689559: Epoch 7116 +2024-11-23 00:59:39.689665: Current learning rate: 0.00138 +2024-11-23 00:59:58.146453: train_loss -0.8153 +2024-11-23 00:59:58.146699: val_loss -0.791 +2024-11-23 00:59:58.146775: Pseudo dice [0.8645] +2024-11-23 00:59:58.146852: Epoch time: 18.46 s +2024-11-23 00:59:59.077183: +2024-11-23 00:59:59.077408: Epoch 7117 +2024-11-23 00:59:59.077518: Current learning rate: 0.00138 +2024-11-23 01:00:17.114087: train_loss -0.8268 +2024-11-23 01:00:17.116459: val_loss -0.7809 +2024-11-23 01:00:17.116574: Pseudo dice [0.8622] +2024-11-23 01:00:17.116654: Epoch time: 18.04 s +2024-11-23 01:00:18.230816: +2024-11-23 01:00:18.231082: Epoch 7118 +2024-11-23 01:00:18.231200: Current learning rate: 0.00137 +2024-11-23 01:00:36.424002: train_loss -0.8235 +2024-11-23 01:00:36.424229: val_loss -0.7767 +2024-11-23 01:00:36.424302: Pseudo dice [0.8516] +2024-11-23 01:00:36.424376: Epoch time: 18.19 s +2024-11-23 01:00:37.443665: +2024-11-23 01:00:37.443888: Epoch 7119 +2024-11-23 01:00:37.444002: Current learning rate: 0.00137 +2024-11-23 01:00:55.315302: train_loss -0.8248 +2024-11-23 01:00:55.315533: val_loss -0.7518 +2024-11-23 01:00:55.315612: Pseudo dice [0.8406] +2024-11-23 01:00:55.315688: Epoch time: 17.87 s +2024-11-23 01:00:56.222677: +2024-11-23 01:00:56.222926: Epoch 7120 +2024-11-23 01:00:56.223036: Current learning rate: 0.00137 +2024-11-23 01:01:15.021004: train_loss -0.8221 +2024-11-23 01:01:15.021231: val_loss -0.7766 +2024-11-23 01:01:15.021306: Pseudo dice [0.8616] +2024-11-23 01:01:15.021383: Epoch time: 18.8 s +2024-11-23 01:01:16.297475: +2024-11-23 01:01:16.297712: Epoch 7121 +2024-11-23 01:01:16.297835: Current learning rate: 0.00137 +2024-11-23 01:01:34.633053: train_loss -0.8228 +2024-11-23 01:01:34.633279: val_loss -0.7842 +2024-11-23 01:01:34.633352: Pseudo dice [0.8557] +2024-11-23 01:01:34.633423: Epoch time: 18.34 s +2024-11-23 01:01:35.591424: +2024-11-23 01:01:35.591675: Epoch 7122 +2024-11-23 01:01:35.591789: Current learning rate: 0.00137 +2024-11-23 01:01:55.133789: train_loss -0.8139 +2024-11-23 01:01:55.134035: val_loss -0.7909 +2024-11-23 01:01:55.134111: Pseudo dice [0.8519] +2024-11-23 01:01:55.134184: Epoch time: 19.54 s +2024-11-23 01:01:56.295998: +2024-11-23 01:01:56.296268: Epoch 7123 +2024-11-23 01:01:56.296380: Current learning rate: 0.00137 +2024-11-23 01:02:15.643500: train_loss -0.8228 +2024-11-23 01:02:15.643716: val_loss -0.7826 +2024-11-23 01:02:15.643789: Pseudo dice [0.8458] +2024-11-23 01:02:15.643864: Epoch time: 19.35 s +2024-11-23 01:02:16.556975: +2024-11-23 01:02:16.557245: Epoch 7124 +2024-11-23 01:02:16.557363: Current learning rate: 0.00137 +2024-11-23 01:02:34.823294: train_loss -0.8166 +2024-11-23 01:02:34.824686: val_loss -0.7834 +2024-11-23 01:02:34.824772: Pseudo dice [0.849] +2024-11-23 01:02:34.824845: Epoch time: 18.27 s +2024-11-23 01:02:35.738250: +2024-11-23 01:02:35.738461: Epoch 7125 +2024-11-23 01:02:35.738587: Current learning rate: 0.00136 +2024-11-23 01:02:54.420005: train_loss -0.8197 +2024-11-23 01:02:54.420221: val_loss -0.8065 +2024-11-23 01:02:54.420295: Pseudo dice [0.8637] +2024-11-23 01:02:54.420372: Epoch time: 18.68 s +2024-11-23 01:02:55.334264: +2024-11-23 01:02:55.334499: Epoch 7126 +2024-11-23 01:02:55.334610: Current learning rate: 0.00136 +2024-11-23 01:03:13.424062: train_loss -0.8178 +2024-11-23 01:03:13.424278: val_loss -0.7975 +2024-11-23 01:03:13.424350: Pseudo dice [0.871] +2024-11-23 01:03:13.424423: Epoch time: 18.09 s +2024-11-23 01:03:14.347391: +2024-11-23 01:03:14.347657: Epoch 7127 +2024-11-23 01:03:14.347767: Current learning rate: 0.00136 +2024-11-23 01:03:32.590732: train_loss -0.8171 +2024-11-23 01:03:32.596185: val_loss -0.7848 +2024-11-23 01:03:32.596272: Pseudo dice [0.8456] +2024-11-23 01:03:32.596354: Epoch time: 18.24 s +2024-11-23 01:03:33.659171: +2024-11-23 01:03:33.659404: Epoch 7128 +2024-11-23 01:03:33.659512: Current learning rate: 0.00136 +2024-11-23 01:03:51.822483: train_loss -0.8215 +2024-11-23 01:03:51.822717: val_loss -0.7693 +2024-11-23 01:03:51.822794: Pseudo dice [0.8406] +2024-11-23 01:03:51.822868: Epoch time: 18.16 s +2024-11-23 01:03:52.734011: +2024-11-23 01:03:52.734236: Epoch 7129 +2024-11-23 01:03:52.734353: Current learning rate: 0.00136 +2024-11-23 01:04:10.770087: train_loss -0.8229 +2024-11-23 01:04:10.770366: val_loss -0.7775 +2024-11-23 01:04:10.770441: Pseudo dice [0.8611] +2024-11-23 01:04:10.770514: Epoch time: 18.04 s +2024-11-23 01:04:11.674299: +2024-11-23 01:04:11.674511: Epoch 7130 +2024-11-23 01:04:11.674615: Current learning rate: 0.00136 +2024-11-23 01:04:29.690596: train_loss -0.824 +2024-11-23 01:04:29.690806: val_loss -0.7907 +2024-11-23 01:04:29.690879: Pseudo dice [0.8692] +2024-11-23 01:04:29.690972: Epoch time: 18.02 s +2024-11-23 01:04:30.600228: +2024-11-23 01:04:30.600495: Epoch 7131 +2024-11-23 01:04:30.600626: Current learning rate: 0.00136 +2024-11-23 01:04:48.032680: train_loss -0.8173 +2024-11-23 01:04:48.032936: val_loss -0.7798 +2024-11-23 01:04:48.033018: Pseudo dice [0.8432] +2024-11-23 01:04:48.033099: Epoch time: 17.43 s +2024-11-23 01:04:49.050574: +2024-11-23 01:04:49.050845: Epoch 7132 +2024-11-23 01:04:49.050958: Current learning rate: 0.00135 +2024-11-23 01:05:07.061946: train_loss -0.8153 +2024-11-23 01:05:07.062176: val_loss -0.7924 +2024-11-23 01:05:07.062252: Pseudo dice [0.8567] +2024-11-23 01:05:07.062335: Epoch time: 18.01 s +2024-11-23 01:05:08.352305: +2024-11-23 01:05:08.352556: Epoch 7133 +2024-11-23 01:05:08.352674: Current learning rate: 0.00135 +2024-11-23 01:05:26.980488: train_loss -0.8215 +2024-11-23 01:05:26.980786: val_loss -0.7659 +2024-11-23 01:05:26.980860: Pseudo dice [0.8313] +2024-11-23 01:05:26.980938: Epoch time: 18.63 s +2024-11-23 01:05:27.989031: +2024-11-23 01:05:27.989265: Epoch 7134 +2024-11-23 01:05:27.989374: Current learning rate: 0.00135 +2024-11-23 01:05:46.004810: train_loss -0.8203 +2024-11-23 01:05:46.005082: val_loss -0.7631 +2024-11-23 01:05:46.005162: Pseudo dice [0.8493] +2024-11-23 01:05:46.005244: Epoch time: 18.02 s +2024-11-23 01:05:46.922378: +2024-11-23 01:05:46.922599: Epoch 7135 +2024-11-23 01:05:46.922707: Current learning rate: 0.00135 +2024-11-23 01:06:05.947204: train_loss -0.8163 +2024-11-23 01:06:05.947494: val_loss -0.7817 +2024-11-23 01:06:05.947573: Pseudo dice [0.8652] +2024-11-23 01:06:05.947650: Epoch time: 19.03 s +2024-11-23 01:06:06.861129: +2024-11-23 01:06:06.861354: Epoch 7136 +2024-11-23 01:06:06.861464: Current learning rate: 0.00135 +2024-11-23 01:06:27.085263: train_loss -0.82 +2024-11-23 01:06:27.085935: val_loss -0.7895 +2024-11-23 01:06:27.086054: Pseudo dice [0.8571] +2024-11-23 01:06:27.086134: Epoch time: 20.22 s +2024-11-23 01:06:28.059250: +2024-11-23 01:06:28.059451: Epoch 7137 +2024-11-23 01:06:28.059559: Current learning rate: 0.00135 +2024-11-23 01:06:46.082678: train_loss -0.8183 +2024-11-23 01:06:46.082909: val_loss -0.777 +2024-11-23 01:06:46.082997: Pseudo dice [0.8511] +2024-11-23 01:06:46.083075: Epoch time: 18.02 s +2024-11-23 01:06:46.999166: +2024-11-23 01:06:46.999408: Epoch 7138 +2024-11-23 01:06:46.999518: Current learning rate: 0.00135 +2024-11-23 01:07:05.517371: train_loss -0.82 +2024-11-23 01:07:05.517601: val_loss -0.7861 +2024-11-23 01:07:05.517676: Pseudo dice [0.8616] +2024-11-23 01:07:05.517750: Epoch time: 18.52 s +2024-11-23 01:07:06.531189: +2024-11-23 01:07:06.531435: Epoch 7139 +2024-11-23 01:07:06.531547: Current learning rate: 0.00134 +2024-11-23 01:07:25.351444: train_loss -0.8195 +2024-11-23 01:07:25.353875: val_loss -0.7909 +2024-11-23 01:07:25.353971: Pseudo dice [0.864] +2024-11-23 01:07:25.354058: Epoch time: 18.82 s +2024-11-23 01:07:26.304576: +2024-11-23 01:07:26.304801: Epoch 7140 +2024-11-23 01:07:26.304911: Current learning rate: 0.00134 +2024-11-23 01:07:45.310005: train_loss -0.8064 +2024-11-23 01:07:45.311113: val_loss -0.7846 +2024-11-23 01:07:45.311213: Pseudo dice [0.8484] +2024-11-23 01:07:45.311294: Epoch time: 19.01 s +2024-11-23 01:07:46.299132: +2024-11-23 01:07:46.299364: Epoch 7141 +2024-11-23 01:07:46.299482: Current learning rate: 0.00134 +2024-11-23 01:08:04.567544: train_loss -0.8118 +2024-11-23 01:08:04.567779: val_loss -0.7846 +2024-11-23 01:08:04.567855: Pseudo dice [0.8637] +2024-11-23 01:08:04.567931: Epoch time: 18.27 s +2024-11-23 01:08:05.473897: +2024-11-23 01:08:05.474133: Epoch 7142 +2024-11-23 01:08:05.474254: Current learning rate: 0.00134 +2024-11-23 01:08:23.821640: train_loss -0.8143 +2024-11-23 01:08:23.821862: val_loss -0.7807 +2024-11-23 01:08:23.821935: Pseudo dice [0.8527] +2024-11-23 01:08:23.822015: Epoch time: 18.35 s +2024-11-23 01:08:24.729458: +2024-11-23 01:08:24.729710: Epoch 7143 +2024-11-23 01:08:24.729862: Current learning rate: 0.00134 +2024-11-23 01:08:43.554339: train_loss -0.8227 +2024-11-23 01:08:43.559740: val_loss -0.7622 +2024-11-23 01:08:43.559861: Pseudo dice [0.8505] +2024-11-23 01:08:43.559945: Epoch time: 18.83 s +2024-11-23 01:08:44.971229: +2024-11-23 01:08:44.971443: Epoch 7144 +2024-11-23 01:08:44.971553: Current learning rate: 0.00134 +2024-11-23 01:09:03.891808: train_loss -0.8232 +2024-11-23 01:09:03.892036: val_loss -0.787 +2024-11-23 01:09:03.892113: Pseudo dice [0.852] +2024-11-23 01:09:03.892221: Epoch time: 18.92 s +2024-11-23 01:09:04.803329: +2024-11-23 01:09:04.803532: Epoch 7145 +2024-11-23 01:09:04.803643: Current learning rate: 0.00134 +2024-11-23 01:09:23.457356: train_loss -0.8196 +2024-11-23 01:09:23.457591: val_loss -0.7694 +2024-11-23 01:09:23.457665: Pseudo dice [0.8565] +2024-11-23 01:09:23.457736: Epoch time: 18.65 s +2024-11-23 01:09:24.363343: +2024-11-23 01:09:24.363562: Epoch 7146 +2024-11-23 01:09:24.363672: Current learning rate: 0.00134 +2024-11-23 01:09:42.618567: train_loss -0.8274 +2024-11-23 01:09:42.618817: val_loss -0.7617 +2024-11-23 01:09:42.618890: Pseudo dice [0.8694] +2024-11-23 01:09:42.618972: Epoch time: 18.26 s +2024-11-23 01:09:43.538039: +2024-11-23 01:09:43.538271: Epoch 7147 +2024-11-23 01:09:43.538383: Current learning rate: 0.00133 +2024-11-23 01:10:01.970981: train_loss -0.8098 +2024-11-23 01:10:01.971203: val_loss -0.7825 +2024-11-23 01:10:01.971277: Pseudo dice [0.8552] +2024-11-23 01:10:01.971349: Epoch time: 18.43 s +2024-11-23 01:10:02.908777: +2024-11-23 01:10:02.909076: Epoch 7148 +2024-11-23 01:10:02.909195: Current learning rate: 0.00133 +2024-11-23 01:10:21.882304: train_loss -0.8204 +2024-11-23 01:10:21.882551: val_loss -0.7676 +2024-11-23 01:10:21.882625: Pseudo dice [0.8454] +2024-11-23 01:10:21.882701: Epoch time: 18.97 s +2024-11-23 01:10:22.874379: +2024-11-23 01:10:22.874640: Epoch 7149 +2024-11-23 01:10:22.874764: Current learning rate: 0.00133 +2024-11-23 01:10:41.688167: train_loss -0.814 +2024-11-23 01:10:41.688387: val_loss -0.783 +2024-11-23 01:10:41.688461: Pseudo dice [0.8613] +2024-11-23 01:10:41.688535: Epoch time: 18.81 s +2024-11-23 01:10:42.948969: +2024-11-23 01:10:42.949227: Epoch 7150 +2024-11-23 01:10:42.949339: Current learning rate: 0.00133 +2024-11-23 01:11:00.734179: train_loss -0.8213 +2024-11-23 01:11:00.734426: val_loss -0.7817 +2024-11-23 01:11:00.734503: Pseudo dice [0.8658] +2024-11-23 01:11:00.734583: Epoch time: 17.79 s +2024-11-23 01:11:01.648584: +2024-11-23 01:11:01.648815: Epoch 7151 +2024-11-23 01:11:01.648929: Current learning rate: 0.00133 +2024-11-23 01:11:20.216774: train_loss -0.8229 +2024-11-23 01:11:20.217006: val_loss -0.7976 +2024-11-23 01:11:20.217085: Pseudo dice [0.8553] +2024-11-23 01:11:20.217160: Epoch time: 18.57 s +2024-11-23 01:11:21.130600: +2024-11-23 01:11:21.130799: Epoch 7152 +2024-11-23 01:11:21.130907: Current learning rate: 0.00133 +2024-11-23 01:11:39.833687: train_loss -0.8263 +2024-11-23 01:11:39.833909: val_loss -0.7498 +2024-11-23 01:11:39.833983: Pseudo dice [0.8527] +2024-11-23 01:11:39.834072: Epoch time: 18.7 s +2024-11-23 01:11:40.736830: +2024-11-23 01:11:40.737068: Epoch 7153 +2024-11-23 01:11:40.737176: Current learning rate: 0.00133 +2024-11-23 01:11:58.540621: train_loss -0.8209 +2024-11-23 01:11:58.540931: val_loss -0.7799 +2024-11-23 01:11:58.541013: Pseudo dice [0.8689] +2024-11-23 01:11:58.541096: Epoch time: 17.8 s +2024-11-23 01:11:59.453362: +2024-11-23 01:11:59.453586: Epoch 7154 +2024-11-23 01:11:59.453698: Current learning rate: 0.00132 +2024-11-23 01:12:17.795020: train_loss -0.8274 +2024-11-23 01:12:17.795289: val_loss -0.7889 +2024-11-23 01:12:17.795371: Pseudo dice [0.8556] +2024-11-23 01:12:17.795451: Epoch time: 18.34 s +2024-11-23 01:12:18.709081: +2024-11-23 01:12:18.709340: Epoch 7155 +2024-11-23 01:12:18.709452: Current learning rate: 0.00132 +2024-11-23 01:12:37.617861: train_loss -0.8188 +2024-11-23 01:12:37.618086: val_loss -0.7948 +2024-11-23 01:12:37.618159: Pseudo dice [0.8594] +2024-11-23 01:12:37.618231: Epoch time: 18.91 s +2024-11-23 01:12:38.920284: +2024-11-23 01:12:38.920491: Epoch 7156 +2024-11-23 01:12:38.920609: Current learning rate: 0.00132 +2024-11-23 01:12:57.045069: train_loss -0.8216 +2024-11-23 01:12:57.046081: val_loss -0.7872 +2024-11-23 01:12:57.046157: Pseudo dice [0.849] +2024-11-23 01:12:57.046234: Epoch time: 18.13 s +2024-11-23 01:12:57.954905: +2024-11-23 01:12:57.955138: Epoch 7157 +2024-11-23 01:12:57.955246: Current learning rate: 0.00132 +2024-11-23 01:13:15.640258: train_loss -0.8176 +2024-11-23 01:13:15.645690: val_loss -0.7775 +2024-11-23 01:13:15.645791: Pseudo dice [0.8371] +2024-11-23 01:13:15.645873: Epoch time: 17.69 s +2024-11-23 01:13:16.790751: +2024-11-23 01:13:16.790977: Epoch 7158 +2024-11-23 01:13:16.791095: Current learning rate: 0.00132 +2024-11-23 01:13:36.577016: train_loss -0.8151 +2024-11-23 01:13:36.577239: val_loss -0.7549 +2024-11-23 01:13:36.577312: Pseudo dice [0.846] +2024-11-23 01:13:36.577386: Epoch time: 19.79 s +2024-11-23 01:13:37.491946: +2024-11-23 01:13:37.492188: Epoch 7159 +2024-11-23 01:13:37.492297: Current learning rate: 0.00132 +2024-11-23 01:13:55.799167: train_loss -0.824 +2024-11-23 01:13:55.799383: val_loss -0.7529 +2024-11-23 01:13:55.799458: Pseudo dice [0.8594] +2024-11-23 01:13:55.799532: Epoch time: 18.31 s +2024-11-23 01:13:56.703678: +2024-11-23 01:13:56.703885: Epoch 7160 +2024-11-23 01:13:56.704011: Current learning rate: 0.00132 +2024-11-23 01:14:15.107634: train_loss -0.8209 +2024-11-23 01:14:15.107896: val_loss -0.7937 +2024-11-23 01:14:15.107977: Pseudo dice [0.8495] +2024-11-23 01:14:15.108065: Epoch time: 18.4 s +2024-11-23 01:14:16.024897: +2024-11-23 01:14:16.025113: Epoch 7161 +2024-11-23 01:14:16.025222: Current learning rate: 0.00131 +2024-11-23 01:14:34.430548: train_loss -0.8189 +2024-11-23 01:14:34.430764: val_loss -0.7657 +2024-11-23 01:14:34.430843: Pseudo dice [0.8348] +2024-11-23 01:14:34.430917: Epoch time: 18.41 s +2024-11-23 01:14:35.338206: +2024-11-23 01:14:35.338421: Epoch 7162 +2024-11-23 01:14:35.338529: Current learning rate: 0.00131 +2024-11-23 01:14:53.100689: train_loss -0.8243 +2024-11-23 01:14:53.100904: val_loss -0.789 +2024-11-23 01:14:53.100978: Pseudo dice [0.8693] +2024-11-23 01:14:53.101060: Epoch time: 17.76 s +2024-11-23 01:14:54.027618: +2024-11-23 01:14:54.027864: Epoch 7163 +2024-11-23 01:14:54.027986: Current learning rate: 0.00131 +2024-11-23 01:15:13.432746: train_loss -0.8143 +2024-11-23 01:15:13.432983: val_loss -0.7528 +2024-11-23 01:15:13.433081: Pseudo dice [0.8366] +2024-11-23 01:15:13.433161: Epoch time: 19.41 s +2024-11-23 01:15:14.338356: +2024-11-23 01:15:14.338575: Epoch 7164 +2024-11-23 01:15:14.338688: Current learning rate: 0.00131 +2024-11-23 01:15:32.679288: train_loss -0.818 +2024-11-23 01:15:32.679531: val_loss -0.7891 +2024-11-23 01:15:32.679606: Pseudo dice [0.8628] +2024-11-23 01:15:32.679686: Epoch time: 18.34 s +2024-11-23 01:15:33.586115: +2024-11-23 01:15:33.586326: Epoch 7165 +2024-11-23 01:15:33.586432: Current learning rate: 0.00131 +2024-11-23 01:15:51.877820: train_loss -0.8231 +2024-11-23 01:15:51.878044: val_loss -0.7851 +2024-11-23 01:15:51.878119: Pseudo dice [0.8663] +2024-11-23 01:15:51.878190: Epoch time: 18.29 s +2024-11-23 01:15:52.783876: +2024-11-23 01:15:52.784116: Epoch 7166 +2024-11-23 01:15:52.784222: Current learning rate: 0.00131 +2024-11-23 01:16:10.983274: train_loss -0.8272 +2024-11-23 01:16:10.983490: val_loss -0.7961 +2024-11-23 01:16:10.983565: Pseudo dice [0.86] +2024-11-23 01:16:10.983639: Epoch time: 18.2 s +2024-11-23 01:16:12.008620: +2024-11-23 01:16:12.009074: Epoch 7167 +2024-11-23 01:16:12.009207: Current learning rate: 0.00131 +2024-11-23 01:16:31.026540: train_loss -0.8279 +2024-11-23 01:16:31.026777: val_loss -0.7803 +2024-11-23 01:16:31.026854: Pseudo dice [0.8527] +2024-11-23 01:16:31.026929: Epoch time: 19.02 s +2024-11-23 01:16:32.049998: +2024-11-23 01:16:32.050230: Epoch 7168 +2024-11-23 01:16:32.050343: Current learning rate: 0.0013 +2024-11-23 01:16:51.052452: train_loss -0.8154 +2024-11-23 01:16:51.052709: val_loss -0.7586 +2024-11-23 01:16:51.052785: Pseudo dice [0.8445] +2024-11-23 01:16:51.052870: Epoch time: 19.0 s +2024-11-23 01:16:51.957247: +2024-11-23 01:16:51.957476: Epoch 7169 +2024-11-23 01:16:51.957581: Current learning rate: 0.0013 +2024-11-23 01:17:10.196694: train_loss -0.8208 +2024-11-23 01:17:10.196944: val_loss -0.757 +2024-11-23 01:17:10.197100: Pseudo dice [0.8558] +2024-11-23 01:17:10.197176: Epoch time: 18.24 s +2024-11-23 01:17:11.105528: +2024-11-23 01:17:11.105779: Epoch 7170 +2024-11-23 01:17:11.105888: Current learning rate: 0.0013 +2024-11-23 01:17:29.922786: train_loss -0.8163 +2024-11-23 01:17:29.923032: val_loss -0.7763 +2024-11-23 01:17:29.923112: Pseudo dice [0.8487] +2024-11-23 01:17:29.923188: Epoch time: 18.82 s +2024-11-23 01:17:30.856016: +2024-11-23 01:17:30.856236: Epoch 7171 +2024-11-23 01:17:30.856355: Current learning rate: 0.0013 +2024-11-23 01:17:49.030576: train_loss -0.8173 +2024-11-23 01:17:49.030815: val_loss -0.7912 +2024-11-23 01:17:49.030894: Pseudo dice [0.8576] +2024-11-23 01:17:49.030974: Epoch time: 18.18 s +2024-11-23 01:17:49.957091: +2024-11-23 01:17:49.957367: Epoch 7172 +2024-11-23 01:17:49.957500: Current learning rate: 0.0013 +2024-11-23 01:18:08.479175: train_loss -0.8311 +2024-11-23 01:18:08.479407: val_loss -0.7561 +2024-11-23 01:18:08.479485: Pseudo dice [0.8491] +2024-11-23 01:18:08.479573: Epoch time: 18.52 s +2024-11-23 01:18:09.387580: +2024-11-23 01:18:09.387794: Epoch 7173 +2024-11-23 01:18:09.387906: Current learning rate: 0.0013 +2024-11-23 01:18:27.964286: train_loss -0.8236 +2024-11-23 01:18:27.969704: val_loss -0.7839 +2024-11-23 01:18:27.969830: Pseudo dice [0.8517] +2024-11-23 01:18:27.969911: Epoch time: 18.58 s +2024-11-23 01:18:29.019847: +2024-11-23 01:18:29.020055: Epoch 7174 +2024-11-23 01:18:29.020167: Current learning rate: 0.0013 +2024-11-23 01:18:48.048085: train_loss -0.8241 +2024-11-23 01:18:48.048333: val_loss -0.7679 +2024-11-23 01:18:48.048410: Pseudo dice [0.8415] +2024-11-23 01:18:48.048487: Epoch time: 19.03 s +2024-11-23 01:18:48.957257: +2024-11-23 01:18:48.957477: Epoch 7175 +2024-11-23 01:18:48.957585: Current learning rate: 0.00129 +2024-11-23 01:19:06.813265: train_loss -0.8192 +2024-11-23 01:19:06.813513: val_loss -0.7688 +2024-11-23 01:19:06.813590: Pseudo dice [0.8636] +2024-11-23 01:19:06.813674: Epoch time: 17.86 s +2024-11-23 01:19:07.742942: +2024-11-23 01:19:07.743173: Epoch 7176 +2024-11-23 01:19:07.743288: Current learning rate: 0.00129 +2024-11-23 01:19:25.454850: train_loss -0.8211 +2024-11-23 01:19:25.455088: val_loss -0.7989 +2024-11-23 01:19:25.455168: Pseudo dice [0.8787] +2024-11-23 01:19:25.455248: Epoch time: 17.71 s +2024-11-23 01:19:26.499723: +2024-11-23 01:19:26.499968: Epoch 7177 +2024-11-23 01:19:26.500085: Current learning rate: 0.00129 +2024-11-23 01:19:44.658352: train_loss -0.816 +2024-11-23 01:19:44.658569: val_loss -0.7875 +2024-11-23 01:19:44.658644: Pseudo dice [0.8677] +2024-11-23 01:19:44.658718: Epoch time: 18.16 s +2024-11-23 01:19:45.564686: +2024-11-23 01:19:45.564976: Epoch 7178 +2024-11-23 01:19:45.565090: Current learning rate: 0.00129 +2024-11-23 01:20:04.365227: train_loss -0.8129 +2024-11-23 01:20:04.365474: val_loss -0.7564 +2024-11-23 01:20:04.365546: Pseudo dice [0.8473] +2024-11-23 01:20:04.365625: Epoch time: 18.8 s +2024-11-23 01:20:05.696290: +2024-11-23 01:20:05.696509: Epoch 7179 +2024-11-23 01:20:05.696619: Current learning rate: 0.00129 +2024-11-23 01:20:24.024505: train_loss -0.8165 +2024-11-23 01:20:24.024756: val_loss -0.7779 +2024-11-23 01:20:24.024832: Pseudo dice [0.8349] +2024-11-23 01:20:24.024916: Epoch time: 18.33 s +2024-11-23 01:20:25.003761: +2024-11-23 01:20:25.004002: Epoch 7180 +2024-11-23 01:20:25.004122: Current learning rate: 0.00129 +2024-11-23 01:20:42.871751: train_loss -0.8214 +2024-11-23 01:20:42.872047: val_loss -0.7759 +2024-11-23 01:20:42.872123: Pseudo dice [0.8601] +2024-11-23 01:20:42.872199: Epoch time: 17.87 s +2024-11-23 01:20:43.801804: +2024-11-23 01:20:43.802062: Epoch 7181 +2024-11-23 01:20:43.802170: Current learning rate: 0.00129 +2024-11-23 01:21:01.682438: train_loss -0.8217 +2024-11-23 01:21:01.682773: val_loss -0.7902 +2024-11-23 01:21:01.682859: Pseudo dice [0.849] +2024-11-23 01:21:01.682943: Epoch time: 17.88 s +2024-11-23 01:21:02.595843: +2024-11-23 01:21:02.596132: Epoch 7182 +2024-11-23 01:21:02.596242: Current learning rate: 0.00128 +2024-11-23 01:21:21.107822: train_loss -0.8138 +2024-11-23 01:21:21.108056: val_loss -0.7881 +2024-11-23 01:21:21.108130: Pseudo dice [0.853] +2024-11-23 01:21:21.108206: Epoch time: 18.51 s +2024-11-23 01:21:22.020385: +2024-11-23 01:21:22.020608: Epoch 7183 +2024-11-23 01:21:22.020721: Current learning rate: 0.00128 +2024-11-23 01:21:41.439250: train_loss -0.8254 +2024-11-23 01:21:41.441703: val_loss -0.7783 +2024-11-23 01:21:41.441797: Pseudo dice [0.8658] +2024-11-23 01:21:41.441874: Epoch time: 19.42 s +2024-11-23 01:21:42.368952: +2024-11-23 01:21:42.370510: Epoch 7184 +2024-11-23 01:21:42.370628: Current learning rate: 0.00128 +2024-11-23 01:22:01.306572: train_loss -0.822 +2024-11-23 01:22:01.306800: val_loss -0.7939 +2024-11-23 01:22:01.306879: Pseudo dice [0.8616] +2024-11-23 01:22:01.306956: Epoch time: 18.94 s +2024-11-23 01:22:02.210212: +2024-11-23 01:22:02.210457: Epoch 7185 +2024-11-23 01:22:02.210574: Current learning rate: 0.00128 +2024-11-23 01:22:20.617317: train_loss -0.8196 +2024-11-23 01:22:20.617562: val_loss -0.7691 +2024-11-23 01:22:20.617639: Pseudo dice [0.8555] +2024-11-23 01:22:20.617718: Epoch time: 18.41 s +2024-11-23 01:22:21.532070: +2024-11-23 01:22:21.532289: Epoch 7186 +2024-11-23 01:22:21.532400: Current learning rate: 0.00128 +2024-11-23 01:22:40.499635: train_loss -0.8182 +2024-11-23 01:22:40.499845: val_loss -0.7916 +2024-11-23 01:22:40.499919: Pseudo dice [0.8458] +2024-11-23 01:22:40.500000: Epoch time: 18.97 s +2024-11-23 01:22:41.412317: +2024-11-23 01:22:41.412541: Epoch 7187 +2024-11-23 01:22:41.412652: Current learning rate: 0.00128 +2024-11-23 01:22:59.498303: train_loss -0.8237 +2024-11-23 01:22:59.498520: val_loss -0.7854 +2024-11-23 01:22:59.498595: Pseudo dice [0.8631] +2024-11-23 01:22:59.498672: Epoch time: 18.09 s +2024-11-23 01:23:00.416481: +2024-11-23 01:23:00.416688: Epoch 7188 +2024-11-23 01:23:00.416793: Current learning rate: 0.00128 +2024-11-23 01:23:19.535652: train_loss -0.8218 +2024-11-23 01:23:19.535872: val_loss -0.7859 +2024-11-23 01:23:19.535949: Pseudo dice [0.8486] +2024-11-23 01:23:19.536029: Epoch time: 19.12 s +2024-11-23 01:23:20.436756: +2024-11-23 01:23:20.436960: Epoch 7189 +2024-11-23 01:23:20.437084: Current learning rate: 0.00127 +2024-11-23 01:23:39.780252: train_loss -0.8239 +2024-11-23 01:23:39.780516: val_loss -0.7717 +2024-11-23 01:23:39.780590: Pseudo dice [0.864] +2024-11-23 01:23:39.780670: Epoch time: 19.34 s +2024-11-23 01:23:40.697485: +2024-11-23 01:23:40.697687: Epoch 7190 +2024-11-23 01:23:40.697797: Current learning rate: 0.00127 +2024-11-23 01:23:59.656372: train_loss -0.8232 +2024-11-23 01:23:59.656619: val_loss -0.8034 +2024-11-23 01:23:59.656700: Pseudo dice [0.8631] +2024-11-23 01:23:59.656776: Epoch time: 18.96 s +2024-11-23 01:24:00.560374: +2024-11-23 01:24:00.560585: Epoch 7191 +2024-11-23 01:24:00.560697: Current learning rate: 0.00127 +2024-11-23 01:24:19.690730: train_loss -0.8182 +2024-11-23 01:24:19.693092: val_loss -0.7919 +2024-11-23 01:24:19.693247: Pseudo dice [0.8634] +2024-11-23 01:24:19.693329: Epoch time: 19.13 s +2024-11-23 01:24:20.765405: +2024-11-23 01:24:20.765622: Epoch 7192 +2024-11-23 01:24:20.765733: Current learning rate: 0.00127 +2024-11-23 01:24:40.317639: train_loss -0.8199 +2024-11-23 01:24:40.317864: val_loss -0.7668 +2024-11-23 01:24:40.317940: Pseudo dice [0.8488] +2024-11-23 01:24:40.318024: Epoch time: 19.55 s +2024-11-23 01:24:41.224048: +2024-11-23 01:24:41.224310: Epoch 7193 +2024-11-23 01:24:41.224426: Current learning rate: 0.00127 +2024-11-23 01:25:00.509197: train_loss -0.8275 +2024-11-23 01:25:00.509444: val_loss -0.7889 +2024-11-23 01:25:00.509518: Pseudo dice [0.8628] +2024-11-23 01:25:00.509598: Epoch time: 19.29 s +2024-11-23 01:25:01.421886: +2024-11-23 01:25:01.422102: Epoch 7194 +2024-11-23 01:25:01.422213: Current learning rate: 0.00127 +2024-11-23 01:25:20.034326: train_loss -0.8165 +2024-11-23 01:25:20.034562: val_loss -0.8022 +2024-11-23 01:25:20.034642: Pseudo dice [0.8617] +2024-11-23 01:25:20.034719: Epoch time: 18.61 s +2024-11-23 01:25:21.175912: +2024-11-23 01:25:21.176117: Epoch 7195 +2024-11-23 01:25:21.176227: Current learning rate: 0.00127 +2024-11-23 01:25:39.363053: train_loss -0.8174 +2024-11-23 01:25:39.363299: val_loss -0.7953 +2024-11-23 01:25:39.363373: Pseudo dice [0.8573] +2024-11-23 01:25:39.363446: Epoch time: 18.19 s +2024-11-23 01:25:40.307426: +2024-11-23 01:25:40.307666: Epoch 7196 +2024-11-23 01:25:40.307785: Current learning rate: 0.00126 +2024-11-23 01:25:58.738811: train_loss -0.8126 +2024-11-23 01:25:58.739036: val_loss -0.7858 +2024-11-23 01:25:58.739176: Pseudo dice [0.844] +2024-11-23 01:25:58.739259: Epoch time: 18.43 s +2024-11-23 01:25:59.649891: +2024-11-23 01:25:59.650129: Epoch 7197 +2024-11-23 01:25:59.650247: Current learning rate: 0.00126 +2024-11-23 01:26:18.257473: train_loss -0.8161 +2024-11-23 01:26:18.257716: val_loss -0.7847 +2024-11-23 01:26:18.257802: Pseudo dice [0.8669] +2024-11-23 01:26:18.257950: Epoch time: 18.61 s +2024-11-23 01:26:19.167132: +2024-11-23 01:26:19.167375: Epoch 7198 +2024-11-23 01:26:19.167488: Current learning rate: 0.00126 +2024-11-23 01:26:36.796172: train_loss -0.826 +2024-11-23 01:26:36.796391: val_loss -0.7581 +2024-11-23 01:26:36.796482: Pseudo dice [0.8533] +2024-11-23 01:26:36.796614: Epoch time: 17.63 s +2024-11-23 01:26:37.709666: +2024-11-23 01:26:37.710061: Epoch 7199 +2024-11-23 01:26:37.710175: Current learning rate: 0.00126 +2024-11-23 01:26:55.560357: train_loss -0.8189 +2024-11-23 01:26:55.560575: val_loss -0.802 +2024-11-23 01:26:55.560650: Pseudo dice [0.8637] +2024-11-23 01:26:55.560730: Epoch time: 17.85 s +2024-11-23 01:26:56.784214: +2024-11-23 01:26:56.784443: Epoch 7200 +2024-11-23 01:26:56.784555: Current learning rate: 0.00126 +2024-11-23 01:27:15.591584: train_loss -0.8091 +2024-11-23 01:27:15.591810: val_loss -0.7758 +2024-11-23 01:27:15.591891: Pseudo dice [0.843] +2024-11-23 01:27:15.591970: Epoch time: 18.81 s +2024-11-23 01:27:16.506002: +2024-11-23 01:27:16.506218: Epoch 7201 +2024-11-23 01:27:16.506326: Current learning rate: 0.00126 +2024-11-23 01:27:35.016177: train_loss -0.8127 +2024-11-23 01:27:35.016417: val_loss -0.7875 +2024-11-23 01:27:35.016494: Pseudo dice [0.8582] +2024-11-23 01:27:35.016570: Epoch time: 18.51 s +2024-11-23 01:27:35.931499: +2024-11-23 01:27:35.931732: Epoch 7202 +2024-11-23 01:27:35.931844: Current learning rate: 0.00126 +2024-11-23 01:27:54.194371: train_loss -0.8169 +2024-11-23 01:27:54.194602: val_loss -0.7692 +2024-11-23 01:27:54.194685: Pseudo dice [0.8513] +2024-11-23 01:27:54.194769: Epoch time: 18.26 s +2024-11-23 01:27:55.132474: +2024-11-23 01:27:55.132806: Epoch 7203 +2024-11-23 01:27:55.132917: Current learning rate: 0.00125 +2024-11-23 01:28:13.632685: train_loss -0.8201 +2024-11-23 01:28:13.632917: val_loss -0.7691 +2024-11-23 01:28:13.633002: Pseudo dice [0.8536] +2024-11-23 01:28:13.633080: Epoch time: 18.5 s +2024-11-23 01:28:14.549525: +2024-11-23 01:28:14.549754: Epoch 7204 +2024-11-23 01:28:14.549865: Current learning rate: 0.00125 +2024-11-23 01:28:33.390900: train_loss -0.8107 +2024-11-23 01:28:33.391181: val_loss -0.7534 +2024-11-23 01:28:33.391260: Pseudo dice [0.8439] +2024-11-23 01:28:33.391346: Epoch time: 18.84 s +2024-11-23 01:28:34.308020: +2024-11-23 01:28:34.308257: Epoch 7205 +2024-11-23 01:28:34.308372: Current learning rate: 0.00125 +2024-11-23 01:28:53.553064: train_loss -0.8173 +2024-11-23 01:28:53.553286: val_loss -0.7628 +2024-11-23 01:28:53.553364: Pseudo dice [0.8679] +2024-11-23 01:28:53.553440: Epoch time: 19.25 s +2024-11-23 01:28:54.473805: +2024-11-23 01:28:54.474018: Epoch 7206 +2024-11-23 01:28:54.474136: Current learning rate: 0.00125 +2024-11-23 01:29:13.945518: train_loss -0.8134 +2024-11-23 01:29:13.945740: val_loss -0.7708 +2024-11-23 01:29:13.945814: Pseudo dice [0.8565] +2024-11-23 01:29:13.945888: Epoch time: 19.47 s +2024-11-23 01:29:14.857012: +2024-11-23 01:29:14.857230: Epoch 7207 +2024-11-23 01:29:14.857338: Current learning rate: 0.00125 +2024-11-23 01:29:33.607489: train_loss -0.8179 +2024-11-23 01:29:33.607704: val_loss -0.7715 +2024-11-23 01:29:33.607780: Pseudo dice [0.8591] +2024-11-23 01:29:33.607853: Epoch time: 18.75 s +2024-11-23 01:29:34.520346: +2024-11-23 01:29:34.520555: Epoch 7208 +2024-11-23 01:29:34.520658: Current learning rate: 0.00125 +2024-11-23 01:29:54.678305: train_loss -0.8142 +2024-11-23 01:29:54.678550: val_loss -0.7683 +2024-11-23 01:29:54.678623: Pseudo dice [0.8522] +2024-11-23 01:29:54.678777: Epoch time: 20.16 s +2024-11-23 01:29:55.593596: +2024-11-23 01:29:55.593910: Epoch 7209 +2024-11-23 01:29:55.594022: Current learning rate: 0.00125 +2024-11-23 01:30:12.321048: train_loss -0.826 +2024-11-23 01:30:12.321269: val_loss -0.7811 +2024-11-23 01:30:12.321347: Pseudo dice [0.8588] +2024-11-23 01:30:12.321423: Epoch time: 16.73 s +2024-11-23 01:30:13.241086: +2024-11-23 01:30:13.241301: Epoch 7210 +2024-11-23 01:30:13.241408: Current learning rate: 0.00124 +2024-11-23 01:30:32.683239: train_loss -0.8225 +2024-11-23 01:30:32.683456: val_loss -0.7781 +2024-11-23 01:30:32.683532: Pseudo dice [0.8622] +2024-11-23 01:30:32.685820: Epoch time: 19.44 s +2024-11-23 01:30:33.665627: +2024-11-23 01:30:33.665839: Epoch 7211 +2024-11-23 01:30:33.665949: Current learning rate: 0.00124 +2024-11-23 01:30:51.907777: train_loss -0.8175 +2024-11-23 01:30:51.907981: val_loss -0.7872 +2024-11-23 01:30:51.908064: Pseudo dice [0.8731] +2024-11-23 01:30:51.908138: Epoch time: 18.24 s +2024-11-23 01:30:51.908201: Yayy! New best EMA pseudo Dice: 0.8583 +2024-11-23 01:30:53.159935: +2024-11-23 01:30:53.160167: Epoch 7212 +2024-11-23 01:30:53.160282: Current learning rate: 0.00124 +2024-11-23 01:31:11.680941: train_loss -0.8193 +2024-11-23 01:31:11.681187: val_loss -0.7814 +2024-11-23 01:31:11.681262: Pseudo dice [0.8566] +2024-11-23 01:31:11.681335: Epoch time: 18.52 s +2024-11-23 01:31:12.595549: +2024-11-23 01:31:12.595761: Epoch 7213 +2024-11-23 01:31:12.595870: Current learning rate: 0.00124 +2024-11-23 01:31:30.215120: train_loss -0.8284 +2024-11-23 01:31:30.215351: val_loss -0.7574 +2024-11-23 01:31:30.215429: Pseudo dice [0.8432] +2024-11-23 01:31:30.215502: Epoch time: 17.62 s +2024-11-23 01:31:31.162268: +2024-11-23 01:31:31.162474: Epoch 7214 +2024-11-23 01:31:31.162580: Current learning rate: 0.00124 +2024-11-23 01:31:48.342257: train_loss -0.8223 +2024-11-23 01:31:48.342502: val_loss -0.7831 +2024-11-23 01:31:48.342583: Pseudo dice [0.8616] +2024-11-23 01:31:48.342658: Epoch time: 17.18 s +2024-11-23 01:31:49.253877: +2024-11-23 01:31:49.254102: Epoch 7215 +2024-11-23 01:31:49.254210: Current learning rate: 0.00124 +2024-11-23 01:32:07.770579: train_loss -0.8194 +2024-11-23 01:32:07.770846: val_loss -0.7979 +2024-11-23 01:32:07.770922: Pseudo dice [0.8625] +2024-11-23 01:32:07.771012: Epoch time: 18.52 s +2024-11-23 01:32:08.684577: +2024-11-23 01:32:08.684799: Epoch 7216 +2024-11-23 01:32:08.684920: Current learning rate: 0.00124 +2024-11-23 01:32:27.248325: train_loss -0.8249 +2024-11-23 01:32:27.252334: val_loss -0.7787 +2024-11-23 01:32:27.252461: Pseudo dice [0.8343] +2024-11-23 01:32:27.252535: Epoch time: 18.56 s +2024-11-23 01:32:28.172236: +2024-11-23 01:32:28.172506: Epoch 7217 +2024-11-23 01:32:28.172619: Current learning rate: 0.00123 +2024-11-23 01:32:46.380686: train_loss -0.8145 +2024-11-23 01:32:46.380912: val_loss -0.7627 +2024-11-23 01:32:46.380985: Pseudo dice [0.8474] +2024-11-23 01:32:46.381069: Epoch time: 18.21 s +2024-11-23 01:32:47.285399: +2024-11-23 01:32:47.285590: Epoch 7218 +2024-11-23 01:32:47.285696: Current learning rate: 0.00123 +2024-11-23 01:33:06.742831: train_loss -0.8281 +2024-11-23 01:33:06.743078: val_loss -0.7847 +2024-11-23 01:33:06.743156: Pseudo dice [0.8628] +2024-11-23 01:33:06.743230: Epoch time: 19.46 s +2024-11-23 01:33:07.650534: +2024-11-23 01:33:07.650780: Epoch 7219 +2024-11-23 01:33:07.650901: Current learning rate: 0.00123 +2024-11-23 01:33:26.131500: train_loss -0.8276 +2024-11-23 01:33:26.131746: val_loss -0.7987 +2024-11-23 01:33:26.131827: Pseudo dice [0.8627] +2024-11-23 01:33:26.131909: Epoch time: 18.48 s +2024-11-23 01:33:27.038450: +2024-11-23 01:33:27.038666: Epoch 7220 +2024-11-23 01:33:27.038772: Current learning rate: 0.00123 +2024-11-23 01:33:44.544370: train_loss -0.8169 +2024-11-23 01:33:44.544589: val_loss -0.763 +2024-11-23 01:33:44.544660: Pseudo dice [0.8592] +2024-11-23 01:33:44.544735: Epoch time: 17.51 s +2024-11-23 01:33:45.469792: +2024-11-23 01:33:45.470014: Epoch 7221 +2024-11-23 01:33:45.470119: Current learning rate: 0.00123 +2024-11-23 01:34:03.990949: train_loss -0.8229 +2024-11-23 01:34:03.991169: val_loss -0.798 +2024-11-23 01:34:03.991242: Pseudo dice [0.8581] +2024-11-23 01:34:03.991316: Epoch time: 18.52 s +2024-11-23 01:34:04.896470: +2024-11-23 01:34:04.896686: Epoch 7222 +2024-11-23 01:34:04.896793: Current learning rate: 0.00123 +2024-11-23 01:34:23.352572: train_loss -0.8251 +2024-11-23 01:34:23.352801: val_loss -0.7853 +2024-11-23 01:34:23.352876: Pseudo dice [0.8645] +2024-11-23 01:34:23.352956: Epoch time: 18.46 s +2024-11-23 01:34:24.269042: +2024-11-23 01:34:24.269245: Epoch 7223 +2024-11-23 01:34:24.269358: Current learning rate: 0.00123 +2024-11-23 01:34:43.011777: train_loss -0.8123 +2024-11-23 01:34:43.012038: val_loss -0.7854 +2024-11-23 01:34:43.012115: Pseudo dice [0.8679] +2024-11-23 01:34:43.012195: Epoch time: 18.74 s +2024-11-23 01:34:43.012255: Yayy! New best EMA pseudo Dice: 0.8584 +2024-11-23 01:34:44.651344: +2024-11-23 01:34:44.651592: Epoch 7224 +2024-11-23 01:34:44.651709: Current learning rate: 0.00122 +2024-11-23 01:35:04.188047: train_loss -0.8175 +2024-11-23 01:35:04.188277: val_loss -0.7982 +2024-11-23 01:35:04.188355: Pseudo dice [0.8683] +2024-11-23 01:35:04.188429: Epoch time: 19.54 s +2024-11-23 01:35:04.188492: Yayy! New best EMA pseudo Dice: 0.8594 +2024-11-23 01:35:05.436636: +2024-11-23 01:35:05.436892: Epoch 7225 +2024-11-23 01:35:05.437011: Current learning rate: 0.00122 +2024-11-23 01:35:23.185982: train_loss -0.8199 +2024-11-23 01:35:23.186249: val_loss -0.7753 +2024-11-23 01:35:23.186327: Pseudo dice [0.8534] +2024-11-23 01:35:23.186402: Epoch time: 17.75 s +2024-11-23 01:35:24.097759: +2024-11-23 01:35:24.097996: Epoch 7226 +2024-11-23 01:35:24.098107: Current learning rate: 0.00122 +2024-11-23 01:35:42.165566: train_loss -0.8254 +2024-11-23 01:35:42.165906: val_loss -0.7825 +2024-11-23 01:35:42.165997: Pseudo dice [0.8574] +2024-11-23 01:35:42.166082: Epoch time: 18.07 s +2024-11-23 01:35:43.079611: +2024-11-23 01:35:43.079836: Epoch 7227 +2024-11-23 01:35:43.079948: Current learning rate: 0.00122 +2024-11-23 01:36:00.607085: train_loss -0.8186 +2024-11-23 01:36:00.607299: val_loss -0.7815 +2024-11-23 01:36:00.607374: Pseudo dice [0.8361] +2024-11-23 01:36:00.607448: Epoch time: 17.53 s +2024-11-23 01:36:01.575901: +2024-11-23 01:36:01.576105: Epoch 7228 +2024-11-23 01:36:01.576211: Current learning rate: 0.00122 +2024-11-23 01:36:20.829591: train_loss -0.8191 +2024-11-23 01:36:20.829831: val_loss -0.7744 +2024-11-23 01:36:20.829910: Pseudo dice [0.8522] +2024-11-23 01:36:20.829986: Epoch time: 19.25 s +2024-11-23 01:36:21.847598: +2024-11-23 01:36:21.847836: Epoch 7229 +2024-11-23 01:36:21.847948: Current learning rate: 0.00122 +2024-11-23 01:36:41.505267: train_loss -0.8229 +2024-11-23 01:36:41.505572: val_loss -0.7913 +2024-11-23 01:36:41.505650: Pseudo dice [0.8596] +2024-11-23 01:36:41.505722: Epoch time: 19.66 s +2024-11-23 01:36:42.485356: +2024-11-23 01:36:42.485576: Epoch 7230 +2024-11-23 01:36:42.485688: Current learning rate: 0.00122 +2024-11-23 01:37:01.154937: train_loss -0.8207 +2024-11-23 01:37:01.155199: val_loss -0.766 +2024-11-23 01:37:01.155277: Pseudo dice [0.8662] +2024-11-23 01:37:01.155362: Epoch time: 18.67 s +2024-11-23 01:37:02.059452: +2024-11-23 01:37:02.059654: Epoch 7231 +2024-11-23 01:37:02.059765: Current learning rate: 0.00121 +2024-11-23 01:37:20.067775: train_loss -0.8188 +2024-11-23 01:37:20.068001: val_loss -0.7764 +2024-11-23 01:37:20.068076: Pseudo dice [0.8574] +2024-11-23 01:37:20.068166: Epoch time: 18.01 s +2024-11-23 01:37:20.982112: +2024-11-23 01:37:20.982339: Epoch 7232 +2024-11-23 01:37:20.982453: Current learning rate: 0.00121 +2024-11-23 01:37:39.470546: train_loss -0.8214 +2024-11-23 01:37:39.470779: val_loss -0.7895 +2024-11-23 01:37:39.470854: Pseudo dice [0.8455] +2024-11-23 01:37:39.470929: Epoch time: 18.49 s +2024-11-23 01:37:40.389472: +2024-11-23 01:37:40.389760: Epoch 7233 +2024-11-23 01:37:40.389868: Current learning rate: 0.00121 +2024-11-23 01:37:58.436058: train_loss -0.817 +2024-11-23 01:37:58.436293: val_loss -0.7903 +2024-11-23 01:37:58.436371: Pseudo dice [0.8388] +2024-11-23 01:37:58.436449: Epoch time: 18.05 s +2024-11-23 01:37:59.412764: +2024-11-23 01:37:59.412983: Epoch 7234 +2024-11-23 01:37:59.413346: Current learning rate: 0.00121 +2024-11-23 01:38:18.662483: train_loss -0.8212 +2024-11-23 01:38:18.662724: val_loss -0.7759 +2024-11-23 01:38:18.662801: Pseudo dice [0.8524] +2024-11-23 01:38:18.662879: Epoch time: 19.25 s +2024-11-23 01:38:19.911959: +2024-11-23 01:38:19.912193: Epoch 7235 +2024-11-23 01:38:19.912315: Current learning rate: 0.00121 +2024-11-23 01:38:38.387388: train_loss -0.8225 +2024-11-23 01:38:38.387625: val_loss -0.7944 +2024-11-23 01:38:38.387704: Pseudo dice [0.8547] +2024-11-23 01:38:38.392929: Epoch time: 18.48 s +2024-11-23 01:38:39.565901: +2024-11-23 01:38:39.566139: Epoch 7236 +2024-11-23 01:38:39.566257: Current learning rate: 0.00121 +2024-11-23 01:38:57.523978: train_loss -0.8271 +2024-11-23 01:38:57.524212: val_loss -0.7812 +2024-11-23 01:38:57.524287: Pseudo dice [0.8559] +2024-11-23 01:38:57.524360: Epoch time: 17.96 s +2024-11-23 01:38:58.434249: +2024-11-23 01:38:58.434461: Epoch 7237 +2024-11-23 01:38:58.434564: Current learning rate: 0.00121 +2024-11-23 01:39:16.394738: train_loss -0.8221 +2024-11-23 01:39:16.409159: val_loss -0.7867 +2024-11-23 01:39:16.409304: Pseudo dice [0.8595] +2024-11-23 01:39:16.409394: Epoch time: 17.96 s +2024-11-23 01:39:17.336347: +2024-11-23 01:39:17.336550: Epoch 7238 +2024-11-23 01:39:17.336660: Current learning rate: 0.0012 +2024-11-23 01:39:35.085398: train_loss -0.8254 +2024-11-23 01:39:35.085631: val_loss -0.7721 +2024-11-23 01:39:35.085706: Pseudo dice [0.8361] +2024-11-23 01:39:35.085781: Epoch time: 17.75 s +2024-11-23 01:39:35.995880: +2024-11-23 01:39:35.996110: Epoch 7239 +2024-11-23 01:39:35.996223: Current learning rate: 0.0012 +2024-11-23 01:39:54.228430: train_loss -0.8279 +2024-11-23 01:39:54.228804: val_loss -0.7794 +2024-11-23 01:39:54.228888: Pseudo dice [0.8508] +2024-11-23 01:39:54.228963: Epoch time: 18.23 s +2024-11-23 01:39:55.159095: +2024-11-23 01:39:55.159303: Epoch 7240 +2024-11-23 01:39:55.159414: Current learning rate: 0.0012 +2024-11-23 01:40:13.080925: train_loss -0.8271 +2024-11-23 01:40:13.081177: val_loss -0.8051 +2024-11-23 01:40:13.081257: Pseudo dice [0.8563] +2024-11-23 01:40:13.081337: Epoch time: 17.92 s +2024-11-23 01:40:14.081606: +2024-11-23 01:40:14.081888: Epoch 7241 +2024-11-23 01:40:14.082000: Current learning rate: 0.0012 +2024-11-23 01:40:32.642162: train_loss -0.8222 +2024-11-23 01:40:32.647624: val_loss -0.8012 +2024-11-23 01:40:32.647748: Pseudo dice [0.8454] +2024-11-23 01:40:32.647833: Epoch time: 18.56 s +2024-11-23 01:40:33.581439: +2024-11-23 01:40:33.581645: Epoch 7242 +2024-11-23 01:40:33.581755: Current learning rate: 0.0012 +2024-11-23 01:40:51.808689: train_loss -0.8206 +2024-11-23 01:40:51.808999: val_loss -0.7831 +2024-11-23 01:40:51.809089: Pseudo dice [0.8631] +2024-11-23 01:40:51.809175: Epoch time: 18.23 s +2024-11-23 01:40:52.723117: +2024-11-23 01:40:52.723340: Epoch 7243 +2024-11-23 01:40:52.723453: Current learning rate: 0.0012 +2024-11-23 01:41:11.032373: train_loss -0.8218 +2024-11-23 01:41:11.032595: val_loss -0.7567 +2024-11-23 01:41:11.032669: Pseudo dice [0.8403] +2024-11-23 01:41:11.032746: Epoch time: 18.31 s +2024-11-23 01:41:11.978583: +2024-11-23 01:41:11.978900: Epoch 7244 +2024-11-23 01:41:11.979012: Current learning rate: 0.0012 +2024-11-23 01:41:30.879439: train_loss -0.8239 +2024-11-23 01:41:30.879681: val_loss -0.7861 +2024-11-23 01:41:30.879756: Pseudo dice [0.8494] +2024-11-23 01:41:30.879836: Epoch time: 18.9 s +2024-11-23 01:41:31.783113: +2024-11-23 01:41:31.783298: Epoch 7245 +2024-11-23 01:41:31.783405: Current learning rate: 0.0012 +2024-11-23 01:41:50.924847: train_loss -0.8251 +2024-11-23 01:41:50.925072: val_loss -0.7699 +2024-11-23 01:41:50.925146: Pseudo dice [0.8597] +2024-11-23 01:41:50.925220: Epoch time: 19.14 s +2024-11-23 01:41:51.834540: +2024-11-23 01:41:51.834758: Epoch 7246 +2024-11-23 01:41:51.834873: Current learning rate: 0.00119 +2024-11-23 01:42:11.153653: train_loss -0.8164 +2024-11-23 01:42:11.153892: val_loss -0.7979 +2024-11-23 01:42:11.159069: Pseudo dice [0.8451] +2024-11-23 01:42:11.174411: Epoch time: 19.32 s +2024-11-23 01:42:12.228689: +2024-11-23 01:42:12.228956: Epoch 7247 +2024-11-23 01:42:12.229072: Current learning rate: 0.00119 +2024-11-23 01:42:30.294675: train_loss -0.8225 +2024-11-23 01:42:30.294898: val_loss -0.7627 +2024-11-23 01:42:30.294972: Pseudo dice [0.8379] +2024-11-23 01:42:30.295052: Epoch time: 18.07 s +2024-11-23 01:42:31.198872: +2024-11-23 01:42:31.199104: Epoch 7248 +2024-11-23 01:42:31.199215: Current learning rate: 0.00119 +2024-11-23 01:42:50.279460: train_loss -0.823 +2024-11-23 01:42:50.279738: val_loss -0.7686 +2024-11-23 01:42:50.279815: Pseudo dice [0.843] +2024-11-23 01:42:50.279893: Epoch time: 19.08 s +2024-11-23 01:42:51.206292: +2024-11-23 01:42:51.206510: Epoch 7249 +2024-11-23 01:42:51.206617: Current learning rate: 0.00119 +2024-11-23 01:43:09.833600: train_loss -0.8218 +2024-11-23 01:43:09.835956: val_loss -0.7923 +2024-11-23 01:43:09.836154: Pseudo dice [0.8589] +2024-11-23 01:43:09.836234: Epoch time: 18.63 s +2024-11-23 01:43:11.144715: +2024-11-23 01:43:11.144955: Epoch 7250 +2024-11-23 01:43:11.145082: Current learning rate: 0.00119 +2024-11-23 01:43:29.808730: train_loss -0.8136 +2024-11-23 01:43:29.808957: val_loss -0.771 +2024-11-23 01:43:29.809037: Pseudo dice [0.8498] +2024-11-23 01:43:29.809112: Epoch time: 18.66 s +2024-11-23 01:43:30.723200: +2024-11-23 01:43:30.723428: Epoch 7251 +2024-11-23 01:43:30.723538: Current learning rate: 0.00119 +2024-11-23 01:43:48.510190: train_loss -0.8215 +2024-11-23 01:43:48.510406: val_loss -0.7636 +2024-11-23 01:43:48.510481: Pseudo dice [0.8399] +2024-11-23 01:43:48.510555: Epoch time: 17.79 s +2024-11-23 01:43:49.588590: +2024-11-23 01:43:49.588789: Epoch 7252 +2024-11-23 01:43:49.588899: Current learning rate: 0.00119 +2024-11-23 01:44:08.683883: train_loss -0.8215 +2024-11-23 01:44:08.684989: val_loss -0.7417 +2024-11-23 01:44:08.685094: Pseudo dice [0.8288] +2024-11-23 01:44:08.685178: Epoch time: 19.1 s +2024-11-23 01:44:09.616809: +2024-11-23 01:44:09.617030: Epoch 7253 +2024-11-23 01:44:09.617139: Current learning rate: 0.00118 +2024-11-23 01:44:26.529982: train_loss -0.8305 +2024-11-23 01:44:26.530220: val_loss -0.7938 +2024-11-23 01:44:26.530309: Pseudo dice [0.8653] +2024-11-23 01:44:26.530392: Epoch time: 16.91 s +2024-11-23 01:44:27.433874: +2024-11-23 01:44:27.434103: Epoch 7254 +2024-11-23 01:44:27.434214: Current learning rate: 0.00118 +2024-11-23 01:44:45.521251: train_loss -0.8288 +2024-11-23 01:44:45.521473: val_loss -0.7686 +2024-11-23 01:44:45.521549: Pseudo dice [0.8571] +2024-11-23 01:44:45.521623: Epoch time: 18.09 s +2024-11-23 01:44:46.434626: +2024-11-23 01:44:46.434820: Epoch 7255 +2024-11-23 01:44:46.434957: Current learning rate: 0.00118 +2024-11-23 01:45:04.983951: train_loss -0.8255 +2024-11-23 01:45:04.984176: val_loss -0.7909 +2024-11-23 01:45:04.984252: Pseudo dice [0.8504] +2024-11-23 01:45:04.984326: Epoch time: 18.55 s +2024-11-23 01:45:06.042020: +2024-11-23 01:45:06.042222: Epoch 7256 +2024-11-23 01:45:06.042327: Current learning rate: 0.00118 +2024-11-23 01:45:24.244654: train_loss -0.8266 +2024-11-23 01:45:24.244898: val_loss -0.8116 +2024-11-23 01:45:24.244972: Pseudo dice [0.859] +2024-11-23 01:45:24.245061: Epoch time: 18.2 s +2024-11-23 01:45:25.160517: +2024-11-23 01:45:25.160747: Epoch 7257 +2024-11-23 01:45:25.160858: Current learning rate: 0.00118 +2024-11-23 01:45:43.466042: train_loss -0.8183 +2024-11-23 01:45:43.468475: val_loss -0.7835 +2024-11-23 01:45:43.468562: Pseudo dice [0.8483] +2024-11-23 01:45:43.468645: Epoch time: 18.31 s +2024-11-23 01:45:44.474050: +2024-11-23 01:45:44.474339: Epoch 7258 +2024-11-23 01:45:44.474450: Current learning rate: 0.00118 +2024-11-23 01:46:02.407645: train_loss -0.8207 +2024-11-23 01:46:02.407870: val_loss -0.7839 +2024-11-23 01:46:02.407945: Pseudo dice [0.8648] +2024-11-23 01:46:02.408051: Epoch time: 17.93 s +2024-11-23 01:46:03.312449: +2024-11-23 01:46:03.312668: Epoch 7259 +2024-11-23 01:46:03.312786: Current learning rate: 0.00118 +2024-11-23 01:46:22.071461: train_loss -0.8291 +2024-11-23 01:46:22.092653: val_loss -0.7656 +2024-11-23 01:46:22.092842: Pseudo dice [0.8469] +2024-11-23 01:46:22.092938: Epoch time: 18.76 s +2024-11-23 01:46:23.106322: +2024-11-23 01:46:23.106553: Epoch 7260 +2024-11-23 01:46:23.106667: Current learning rate: 0.00117 +2024-11-23 01:46:42.040221: train_loss -0.8309 +2024-11-23 01:46:42.040447: val_loss -0.7956 +2024-11-23 01:46:42.040520: Pseudo dice [0.8626] +2024-11-23 01:46:42.040593: Epoch time: 18.93 s +2024-11-23 01:46:42.942195: +2024-11-23 01:46:42.942422: Epoch 7261 +2024-11-23 01:46:42.942531: Current learning rate: 0.00117 +2024-11-23 01:47:00.875378: train_loss -0.8238 +2024-11-23 01:47:00.876415: val_loss -0.7994 +2024-11-23 01:47:00.876503: Pseudo dice [0.862] +2024-11-23 01:47:00.876594: Epoch time: 17.93 s +2024-11-23 01:47:01.790792: +2024-11-23 01:47:01.791001: Epoch 7262 +2024-11-23 01:47:01.791113: Current learning rate: 0.00117 +2024-11-23 01:47:20.453406: train_loss -0.8302 +2024-11-23 01:47:20.453642: val_loss -0.7429 +2024-11-23 01:47:20.453721: Pseudo dice [0.8363] +2024-11-23 01:47:20.453794: Epoch time: 18.66 s +2024-11-23 01:47:21.367573: +2024-11-23 01:47:21.367805: Epoch 7263 +2024-11-23 01:47:21.367918: Current learning rate: 0.00117 +2024-11-23 01:47:39.295634: train_loss -0.822 +2024-11-23 01:47:39.295872: val_loss -0.7691 +2024-11-23 01:47:39.295946: Pseudo dice [0.8457] +2024-11-23 01:47:39.296027: Epoch time: 17.93 s +2024-11-23 01:47:40.210473: +2024-11-23 01:47:40.210719: Epoch 7264 +2024-11-23 01:47:40.210834: Current learning rate: 0.00117 +2024-11-23 01:47:59.449246: train_loss -0.8293 +2024-11-23 01:47:59.449492: val_loss -0.7742 +2024-11-23 01:47:59.449570: Pseudo dice [0.858] +2024-11-23 01:47:59.449648: Epoch time: 19.24 s +2024-11-23 01:48:00.423471: +2024-11-23 01:48:00.423686: Epoch 7265 +2024-11-23 01:48:00.423799: Current learning rate: 0.00117 +2024-11-23 01:48:19.805096: train_loss -0.8234 +2024-11-23 01:48:19.805390: val_loss -0.7641 +2024-11-23 01:48:19.805467: Pseudo dice [0.8591] +2024-11-23 01:48:19.805545: Epoch time: 19.38 s +2024-11-23 01:48:20.743613: +2024-11-23 01:48:20.743844: Epoch 7266 +2024-11-23 01:48:20.743963: Current learning rate: 0.00117 +2024-11-23 01:48:40.527918: train_loss -0.8253 +2024-11-23 01:48:40.528163: val_loss -0.7585 +2024-11-23 01:48:40.528238: Pseudo dice [0.8632] +2024-11-23 01:48:40.528311: Epoch time: 19.79 s +2024-11-23 01:48:41.466308: +2024-11-23 01:48:41.466533: Epoch 7267 +2024-11-23 01:48:41.466649: Current learning rate: 0.00116 +2024-11-23 01:49:00.280477: train_loss -0.8212 +2024-11-23 01:49:00.280704: val_loss -0.7863 +2024-11-23 01:49:00.280783: Pseudo dice [0.8678] +2024-11-23 01:49:00.280857: Epoch time: 18.81 s +2024-11-23 01:49:01.185129: +2024-11-23 01:49:01.185378: Epoch 7268 +2024-11-23 01:49:01.185532: Current learning rate: 0.00116 +2024-11-23 01:49:20.512101: train_loss -0.8154 +2024-11-23 01:49:20.512326: val_loss -0.7604 +2024-11-23 01:49:20.512403: Pseudo dice [0.8483] +2024-11-23 01:49:20.512482: Epoch time: 19.33 s +2024-11-23 01:49:21.781039: +2024-11-23 01:49:21.781269: Epoch 7269 +2024-11-23 01:49:21.781377: Current learning rate: 0.00116 +2024-11-23 01:49:39.244493: train_loss -0.8183 +2024-11-23 01:49:39.244762: val_loss -0.781 +2024-11-23 01:49:39.244846: Pseudo dice [0.8486] +2024-11-23 01:49:39.244923: Epoch time: 17.46 s +2024-11-23 01:49:40.154450: +2024-11-23 01:49:40.154671: Epoch 7270 +2024-11-23 01:49:40.154778: Current learning rate: 0.00116 +2024-11-23 01:49:59.435725: train_loss -0.8195 +2024-11-23 01:49:59.435947: val_loss -0.7646 +2024-11-23 01:49:59.438242: Pseudo dice [0.8438] +2024-11-23 01:49:59.438332: Epoch time: 19.28 s +2024-11-23 01:50:00.490913: +2024-11-23 01:50:00.491137: Epoch 7271 +2024-11-23 01:50:00.491249: Current learning rate: 0.00116 +2024-11-23 01:50:19.787753: train_loss -0.8228 +2024-11-23 01:50:19.788025: val_loss -0.7788 +2024-11-23 01:50:19.788106: Pseudo dice [0.8625] +2024-11-23 01:50:19.788183: Epoch time: 19.3 s +2024-11-23 01:50:20.704037: +2024-11-23 01:50:20.704267: Epoch 7272 +2024-11-23 01:50:20.704378: Current learning rate: 0.00116 +2024-11-23 01:50:39.681620: train_loss -0.8257 +2024-11-23 01:50:39.681841: val_loss -0.7943 +2024-11-23 01:50:39.681922: Pseudo dice [0.8518] +2024-11-23 01:50:39.682021: Epoch time: 18.98 s +2024-11-23 01:50:40.587680: +2024-11-23 01:50:40.587916: Epoch 7273 +2024-11-23 01:50:40.588033: Current learning rate: 0.00116 +2024-11-23 01:50:58.094398: train_loss -0.8242 +2024-11-23 01:50:58.099903: val_loss -0.7707 +2024-11-23 01:50:58.100031: Pseudo dice [0.8464] +2024-11-23 01:50:58.100135: Epoch time: 17.51 s +2024-11-23 01:50:59.021046: +2024-11-23 01:50:59.021252: Epoch 7274 +2024-11-23 01:50:59.021358: Current learning rate: 0.00115 +2024-11-23 01:51:17.305067: train_loss -0.8238 +2024-11-23 01:51:17.305301: val_loss -0.7833 +2024-11-23 01:51:17.305377: Pseudo dice [0.8555] +2024-11-23 01:51:17.305479: Epoch time: 18.28 s +2024-11-23 01:51:18.218675: +2024-11-23 01:51:18.218920: Epoch 7275 +2024-11-23 01:51:18.219038: Current learning rate: 0.00115 +2024-11-23 01:51:37.470469: train_loss -0.8221 +2024-11-23 01:51:37.470769: val_loss -0.79 +2024-11-23 01:51:37.470846: Pseudo dice [0.8665] +2024-11-23 01:51:37.470926: Epoch time: 19.25 s +2024-11-23 01:51:38.381529: +2024-11-23 01:51:38.381766: Epoch 7276 +2024-11-23 01:51:38.381873: Current learning rate: 0.00115 +2024-11-23 01:51:56.442489: train_loss -0.8122 +2024-11-23 01:51:56.442735: val_loss -0.77 +2024-11-23 01:51:56.442857: Pseudo dice [0.8449] +2024-11-23 01:51:56.442933: Epoch time: 18.06 s +2024-11-23 01:51:57.350083: +2024-11-23 01:51:57.350324: Epoch 7277 +2024-11-23 01:51:57.350447: Current learning rate: 0.00115 +2024-11-23 01:52:15.202011: train_loss -0.8174 +2024-11-23 01:52:15.202229: val_loss -0.7842 +2024-11-23 01:52:15.202302: Pseudo dice [0.8563] +2024-11-23 01:52:15.202374: Epoch time: 17.85 s +2024-11-23 01:52:16.224534: +2024-11-23 01:52:16.224725: Epoch 7278 +2024-11-23 01:52:16.224858: Current learning rate: 0.00115 +2024-11-23 01:52:36.303523: train_loss -0.8167 +2024-11-23 01:52:36.303828: val_loss -0.7881 +2024-11-23 01:52:36.303906: Pseudo dice [0.8677] +2024-11-23 01:52:36.303984: Epoch time: 20.08 s +2024-11-23 01:52:37.218490: +2024-11-23 01:52:37.218712: Epoch 7279 +2024-11-23 01:52:37.218828: Current learning rate: 0.00115 +2024-11-23 01:52:55.928712: train_loss -0.8255 +2024-11-23 01:52:55.928969: val_loss -0.7762 +2024-11-23 01:52:55.929058: Pseudo dice [0.854] +2024-11-23 01:52:55.929136: Epoch time: 18.71 s +2024-11-23 01:52:57.195782: +2024-11-23 01:52:57.196026: Epoch 7280 +2024-11-23 01:52:57.196137: Current learning rate: 0.00115 +2024-11-23 01:53:15.600515: train_loss -0.8257 +2024-11-23 01:53:15.600741: val_loss -0.7997 +2024-11-23 01:53:15.600881: Pseudo dice [0.8592] +2024-11-23 01:53:15.600960: Epoch time: 18.41 s +2024-11-23 01:53:16.535222: +2024-11-23 01:53:16.535456: Epoch 7281 +2024-11-23 01:53:16.535563: Current learning rate: 0.00114 +2024-11-23 01:53:35.287957: train_loss -0.8271 +2024-11-23 01:53:35.288188: val_loss -0.7788 +2024-11-23 01:53:35.288264: Pseudo dice [0.8604] +2024-11-23 01:53:35.288338: Epoch time: 18.75 s +2024-11-23 01:53:36.198337: +2024-11-23 01:53:36.198566: Epoch 7282 +2024-11-23 01:53:36.198678: Current learning rate: 0.00114 +2024-11-23 01:53:54.843071: train_loss -0.8244 +2024-11-23 01:53:54.843366: val_loss -0.7626 +2024-11-23 01:53:54.843443: Pseudo dice [0.859] +2024-11-23 01:53:54.843521: Epoch time: 18.65 s +2024-11-23 01:53:55.768999: +2024-11-23 01:53:55.769244: Epoch 7283 +2024-11-23 01:53:55.769354: Current learning rate: 0.00114 +2024-11-23 01:54:14.283117: train_loss -0.8285 +2024-11-23 01:54:14.283343: val_loss -0.7668 +2024-11-23 01:54:14.283422: Pseudo dice [0.8486] +2024-11-23 01:54:14.283509: Epoch time: 18.51 s +2024-11-23 01:54:15.197255: +2024-11-23 01:54:15.197478: Epoch 7284 +2024-11-23 01:54:15.197584: Current learning rate: 0.00114 +2024-11-23 01:54:33.281089: train_loss -0.8261 +2024-11-23 01:54:33.281307: val_loss -0.7769 +2024-11-23 01:54:33.281381: Pseudo dice [0.8557] +2024-11-23 01:54:33.281456: Epoch time: 18.08 s +2024-11-23 01:54:34.252267: +2024-11-23 01:54:34.252515: Epoch 7285 +2024-11-23 01:54:34.252628: Current learning rate: 0.00114 +2024-11-23 01:54:52.595147: train_loss -0.8287 +2024-11-23 01:54:52.595355: val_loss -0.7759 +2024-11-23 01:54:52.595427: Pseudo dice [0.8546] +2024-11-23 01:54:52.595499: Epoch time: 18.34 s +2024-11-23 01:54:53.500296: +2024-11-23 01:54:53.500527: Epoch 7286 +2024-11-23 01:54:53.500633: Current learning rate: 0.00114 +2024-11-23 01:55:12.433492: train_loss -0.8287 +2024-11-23 01:55:12.433743: val_loss -0.7768 +2024-11-23 01:55:12.433819: Pseudo dice [0.8594] +2024-11-23 01:55:12.433897: Epoch time: 18.93 s +2024-11-23 01:55:13.357177: +2024-11-23 01:55:13.357421: Epoch 7287 +2024-11-23 01:55:13.357531: Current learning rate: 0.00114 +2024-11-23 01:55:31.920648: train_loss -0.8258 +2024-11-23 01:55:31.920873: val_loss -0.7908 +2024-11-23 01:55:31.920973: Pseudo dice [0.8667] +2024-11-23 01:55:31.921058: Epoch time: 18.56 s +2024-11-23 01:55:32.837141: +2024-11-23 01:55:32.837382: Epoch 7288 +2024-11-23 01:55:32.837497: Current learning rate: 0.00113 +2024-11-23 01:55:51.201756: train_loss -0.8325 +2024-11-23 01:55:51.201987: val_loss -0.7942 +2024-11-23 01:55:51.202065: Pseudo dice [0.8455] +2024-11-23 01:55:51.202143: Epoch time: 18.37 s +2024-11-23 01:55:52.111963: +2024-11-23 01:55:52.112191: Epoch 7289 +2024-11-23 01:55:52.112298: Current learning rate: 0.00113 +2024-11-23 01:56:10.929909: train_loss -0.8299 +2024-11-23 01:56:10.930135: val_loss -0.7897 +2024-11-23 01:56:10.930212: Pseudo dice [0.865] +2024-11-23 01:56:10.930286: Epoch time: 18.82 s +2024-11-23 01:56:11.835618: +2024-11-23 01:56:11.835871: Epoch 7290 +2024-11-23 01:56:11.835988: Current learning rate: 0.00113 +2024-11-23 01:56:30.361284: train_loss -0.829 +2024-11-23 01:56:30.361550: val_loss -0.7738 +2024-11-23 01:56:30.376475: Pseudo dice [0.8619] +2024-11-23 01:56:30.376691: Epoch time: 18.53 s +2024-11-23 01:56:31.291504: +2024-11-23 01:56:31.291711: Epoch 7291 +2024-11-23 01:56:31.291819: Current learning rate: 0.00113 +2024-11-23 01:56:50.687779: train_loss -0.8247 +2024-11-23 01:56:50.687985: val_loss -0.7813 +2024-11-23 01:56:50.688064: Pseudo dice [0.856] +2024-11-23 01:56:50.688137: Epoch time: 19.4 s +2024-11-23 01:56:51.972977: +2024-11-23 01:56:51.973272: Epoch 7292 +2024-11-23 01:56:51.973378: Current learning rate: 0.00113 +2024-11-23 01:57:10.560555: train_loss -0.826 +2024-11-23 01:57:10.560805: val_loss -0.7737 +2024-11-23 01:57:10.560887: Pseudo dice [0.8583] +2024-11-23 01:57:10.560965: Epoch time: 18.59 s +2024-11-23 01:57:11.475186: +2024-11-23 01:57:11.475409: Epoch 7293 +2024-11-23 01:57:11.475522: Current learning rate: 0.00113 +2024-11-23 01:57:29.750965: train_loss -0.8302 +2024-11-23 01:57:29.751227: val_loss -0.7526 +2024-11-23 01:57:29.751303: Pseudo dice [0.855] +2024-11-23 01:57:29.751388: Epoch time: 18.28 s +2024-11-23 01:57:30.662558: +2024-11-23 01:57:30.662779: Epoch 7294 +2024-11-23 01:57:30.662887: Current learning rate: 0.00112 +2024-11-23 01:57:48.500441: train_loss -0.8256 +2024-11-23 01:57:48.500655: val_loss -0.7544 +2024-11-23 01:57:48.500731: Pseudo dice [0.8536] +2024-11-23 01:57:48.500805: Epoch time: 17.84 s +2024-11-23 01:57:49.407056: +2024-11-23 01:57:49.407292: Epoch 7295 +2024-11-23 01:57:49.407406: Current learning rate: 0.00112 +2024-11-23 01:58:07.470625: train_loss -0.8221 +2024-11-23 01:58:07.470841: val_loss -0.7868 +2024-11-23 01:58:07.470921: Pseudo dice [0.8629] +2024-11-23 01:58:07.471005: Epoch time: 18.06 s +2024-11-23 01:58:08.376202: +2024-11-23 01:58:08.376397: Epoch 7296 +2024-11-23 01:58:08.376504: Current learning rate: 0.00112 +2024-11-23 01:58:26.564823: train_loss -0.8249 +2024-11-23 01:58:26.565081: val_loss -0.7861 +2024-11-23 01:58:26.565161: Pseudo dice [0.8531] +2024-11-23 01:58:26.565238: Epoch time: 18.18 s +2024-11-23 01:58:27.500532: +2024-11-23 01:58:27.500730: Epoch 7297 +2024-11-23 01:58:27.500843: Current learning rate: 0.00112 +2024-11-23 01:58:45.837409: train_loss -0.8269 +2024-11-23 01:58:45.837630: val_loss -0.7537 +2024-11-23 01:58:45.837702: Pseudo dice [0.8376] +2024-11-23 01:58:45.837780: Epoch time: 18.34 s +2024-11-23 01:58:46.753759: +2024-11-23 01:58:46.754022: Epoch 7298 +2024-11-23 01:58:46.754173: Current learning rate: 0.00112 +2024-11-23 01:59:04.487623: train_loss -0.8215 +2024-11-23 01:59:04.487852: val_loss -0.7955 +2024-11-23 01:59:04.487927: Pseudo dice [0.8592] +2024-11-23 01:59:04.488012: Epoch time: 17.73 s +2024-11-23 01:59:05.390708: +2024-11-23 01:59:05.390927: Epoch 7299 +2024-11-23 01:59:05.391045: Current learning rate: 0.00112 +2024-11-23 01:59:23.325749: train_loss -0.8279 +2024-11-23 01:59:23.325965: val_loss -0.7776 +2024-11-23 01:59:23.326049: Pseudo dice [0.8692] +2024-11-23 01:59:23.326125: Epoch time: 17.94 s +2024-11-23 01:59:24.570199: +2024-11-23 01:59:24.570559: Epoch 7300 +2024-11-23 01:59:24.570668: Current learning rate: 0.00112 +2024-11-23 01:59:43.654873: train_loss -0.8232 +2024-11-23 01:59:43.655092: val_loss -0.7648 +2024-11-23 01:59:43.655168: Pseudo dice [0.8491] +2024-11-23 01:59:43.655268: Epoch time: 19.09 s +2024-11-23 01:59:44.566549: +2024-11-23 01:59:44.566752: Epoch 7301 +2024-11-23 01:59:44.566858: Current learning rate: 0.00111 +2024-11-23 02:00:03.716305: train_loss -0.829 +2024-11-23 02:00:03.716548: val_loss -0.787 +2024-11-23 02:00:03.716625: Pseudo dice [0.8457] +2024-11-23 02:00:03.716704: Epoch time: 19.15 s +2024-11-23 02:00:04.678849: +2024-11-23 02:00:04.679060: Epoch 7302 +2024-11-23 02:00:04.679198: Current learning rate: 0.00111 +2024-11-23 02:00:23.076057: train_loss -0.8247 +2024-11-23 02:00:23.076525: val_loss -0.7645 +2024-11-23 02:00:23.076605: Pseudo dice [0.8503] +2024-11-23 02:00:23.076684: Epoch time: 18.4 s +2024-11-23 02:00:24.369644: +2024-11-23 02:00:24.369891: Epoch 7303 +2024-11-23 02:00:24.370020: Current learning rate: 0.00111 +2024-11-23 02:00:43.402616: train_loss -0.8281 +2024-11-23 02:00:43.402860: val_loss -0.7816 +2024-11-23 02:00:43.402935: Pseudo dice [0.8567] +2024-11-23 02:00:43.403021: Epoch time: 19.03 s +2024-11-23 02:00:44.317148: +2024-11-23 02:00:44.317380: Epoch 7304 +2024-11-23 02:00:44.317492: Current learning rate: 0.00111 +2024-11-23 02:01:01.988305: train_loss -0.8223 +2024-11-23 02:01:01.988545: val_loss -0.7785 +2024-11-23 02:01:01.988623: Pseudo dice [0.8562] +2024-11-23 02:01:01.988700: Epoch time: 17.67 s +2024-11-23 02:01:02.902809: +2024-11-23 02:01:02.903029: Epoch 7305 +2024-11-23 02:01:02.903158: Current learning rate: 0.00111 +2024-11-23 02:01:20.830810: train_loss -0.829 +2024-11-23 02:01:20.831080: val_loss -0.7817 +2024-11-23 02:01:20.831158: Pseudo dice [0.8655] +2024-11-23 02:01:20.831240: Epoch time: 17.93 s +2024-11-23 02:01:21.769058: +2024-11-23 02:01:21.769368: Epoch 7306 +2024-11-23 02:01:21.769480: Current learning rate: 0.00111 +2024-11-23 02:01:40.390727: train_loss -0.8293 +2024-11-23 02:01:40.390985: val_loss -0.8024 +2024-11-23 02:01:40.391075: Pseudo dice [0.8444] +2024-11-23 02:01:40.391153: Epoch time: 18.62 s +2024-11-23 02:01:41.406277: +2024-11-23 02:01:41.406480: Epoch 7307 +2024-11-23 02:01:41.406592: Current learning rate: 0.00111 +2024-11-23 02:01:59.497252: train_loss -0.8274 +2024-11-23 02:01:59.497494: val_loss -0.7849 +2024-11-23 02:01:59.497577: Pseudo dice [0.8588] +2024-11-23 02:01:59.497655: Epoch time: 18.09 s +2024-11-23 02:02:00.413598: +2024-11-23 02:02:00.413808: Epoch 7308 +2024-11-23 02:02:00.413921: Current learning rate: 0.0011 +2024-11-23 02:02:18.168605: train_loss -0.828 +2024-11-23 02:02:18.168823: val_loss -0.7743 +2024-11-23 02:02:18.168903: Pseudo dice [0.8441] +2024-11-23 02:02:18.169024: Epoch time: 17.76 s +2024-11-23 02:02:19.083783: +2024-11-23 02:02:19.084033: Epoch 7309 +2024-11-23 02:02:19.084138: Current learning rate: 0.0011 +2024-11-23 02:02:36.065777: train_loss -0.8285 +2024-11-23 02:02:36.066023: val_loss -0.7676 +2024-11-23 02:02:36.066097: Pseudo dice [0.8512] +2024-11-23 02:02:36.066178: Epoch time: 16.98 s +2024-11-23 02:02:36.975033: +2024-11-23 02:02:36.975292: Epoch 7310 +2024-11-23 02:02:36.975408: Current learning rate: 0.0011 +2024-11-23 02:02:55.411198: train_loss -0.8182 +2024-11-23 02:02:55.411422: val_loss -0.7725 +2024-11-23 02:02:55.411501: Pseudo dice [0.8471] +2024-11-23 02:02:55.411578: Epoch time: 18.44 s +2024-11-23 02:02:56.378752: +2024-11-23 02:02:56.378984: Epoch 7311 +2024-11-23 02:02:56.379102: Current learning rate: 0.0011 +2024-11-23 02:03:15.735271: train_loss -0.8251 +2024-11-23 02:03:15.735520: val_loss -0.7733 +2024-11-23 02:03:15.735608: Pseudo dice [0.857] +2024-11-23 02:03:15.735739: Epoch time: 19.36 s +2024-11-23 02:03:16.749791: +2024-11-23 02:03:16.750030: Epoch 7312 +2024-11-23 02:03:16.750138: Current learning rate: 0.0011 +2024-11-23 02:03:33.886896: train_loss -0.8301 +2024-11-23 02:03:33.887127: val_loss -0.7837 +2024-11-23 02:03:33.887204: Pseudo dice [0.8484] +2024-11-23 02:03:33.887281: Epoch time: 17.14 s +2024-11-23 02:03:34.794502: +2024-11-23 02:03:34.794722: Epoch 7313 +2024-11-23 02:03:34.794826: Current learning rate: 0.0011 +2024-11-23 02:03:53.351636: train_loss -0.8192 +2024-11-23 02:03:53.354371: val_loss -0.7684 +2024-11-23 02:03:53.354474: Pseudo dice [0.8515] +2024-11-23 02:03:53.354557: Epoch time: 18.56 s +2024-11-23 02:03:54.329250: +2024-11-23 02:03:54.329486: Epoch 7314 +2024-11-23 02:03:54.329599: Current learning rate: 0.0011 +2024-11-23 02:04:13.511726: train_loss -0.8183 +2024-11-23 02:04:13.511952: val_loss -0.7861 +2024-11-23 02:04:13.512033: Pseudo dice [0.8498] +2024-11-23 02:04:13.512110: Epoch time: 19.18 s +2024-11-23 02:04:14.812506: +2024-11-23 02:04:14.812755: Epoch 7315 +2024-11-23 02:04:14.812865: Current learning rate: 0.00109 +2024-11-23 02:04:32.681036: train_loss -0.8236 +2024-11-23 02:04:32.681276: val_loss -0.7709 +2024-11-23 02:04:32.681352: Pseudo dice [0.8493] +2024-11-23 02:04:32.681426: Epoch time: 17.87 s +2024-11-23 02:04:33.598222: +2024-11-23 02:04:33.598451: Epoch 7316 +2024-11-23 02:04:33.598564: Current learning rate: 0.00109 +2024-11-23 02:04:52.585752: train_loss -0.8258 +2024-11-23 02:04:52.585999: val_loss -0.8003 +2024-11-23 02:04:52.586077: Pseudo dice [0.8539] +2024-11-23 02:04:52.586156: Epoch time: 18.99 s +2024-11-23 02:04:53.499635: +2024-11-23 02:04:53.499862: Epoch 7317 +2024-11-23 02:04:53.500180: Current learning rate: 0.00109 +2024-11-23 02:05:11.864764: train_loss -0.8282 +2024-11-23 02:05:11.864989: val_loss -0.7843 +2024-11-23 02:05:11.865070: Pseudo dice [0.8575] +2024-11-23 02:05:11.865144: Epoch time: 18.37 s +2024-11-23 02:05:12.824446: +2024-11-23 02:05:12.824695: Epoch 7318 +2024-11-23 02:05:12.824803: Current learning rate: 0.00109 +2024-11-23 02:05:30.808009: train_loss -0.8217 +2024-11-23 02:05:30.808218: val_loss -0.7809 +2024-11-23 02:05:30.808297: Pseudo dice [0.8572] +2024-11-23 02:05:30.808370: Epoch time: 17.98 s +2024-11-23 02:05:31.724886: +2024-11-23 02:05:31.725095: Epoch 7319 +2024-11-23 02:05:31.725202: Current learning rate: 0.00109 +2024-11-23 02:05:50.313669: train_loss -0.8219 +2024-11-23 02:05:50.313893: val_loss -0.789 +2024-11-23 02:05:50.313973: Pseudo dice [0.8566] +2024-11-23 02:05:50.314058: Epoch time: 18.59 s +2024-11-23 02:05:51.229564: +2024-11-23 02:05:51.229790: Epoch 7320 +2024-11-23 02:05:51.229898: Current learning rate: 0.00109 +2024-11-23 02:06:10.260887: train_loss -0.821 +2024-11-23 02:06:10.261231: val_loss -0.763 +2024-11-23 02:06:10.261312: Pseudo dice [0.8481] +2024-11-23 02:06:10.261392: Epoch time: 19.03 s +2024-11-23 02:06:11.175972: +2024-11-23 02:06:11.176203: Epoch 7321 +2024-11-23 02:06:11.176310: Current learning rate: 0.00109 +2024-11-23 02:06:29.525118: train_loss -0.8246 +2024-11-23 02:06:29.525346: val_loss -0.7995 +2024-11-23 02:06:29.525420: Pseudo dice [0.8551] +2024-11-23 02:06:29.525495: Epoch time: 18.35 s +2024-11-23 02:06:30.446170: +2024-11-23 02:06:30.446394: Epoch 7322 +2024-11-23 02:06:30.446502: Current learning rate: 0.00108 +2024-11-23 02:06:48.287446: train_loss -0.8297 +2024-11-23 02:06:48.287734: val_loss -0.7764 +2024-11-23 02:06:48.287815: Pseudo dice [0.8278] +2024-11-23 02:06:48.287896: Epoch time: 17.84 s +2024-11-23 02:06:49.198056: +2024-11-23 02:06:49.213199: Epoch 7323 +2024-11-23 02:06:49.213334: Current learning rate: 0.00108 +2024-11-23 02:07:07.777168: train_loss -0.8225 +2024-11-23 02:07:07.777405: val_loss -0.7864 +2024-11-23 02:07:07.777484: Pseudo dice [0.8418] +2024-11-23 02:07:07.777559: Epoch time: 18.58 s +2024-11-23 02:07:08.788628: +2024-11-23 02:07:08.788844: Epoch 7324 +2024-11-23 02:07:08.788951: Current learning rate: 0.00108 +2024-11-23 02:07:27.467982: train_loss -0.8273 +2024-11-23 02:07:27.468236: val_loss -0.7711 +2024-11-23 02:07:27.468315: Pseudo dice [0.8555] +2024-11-23 02:07:27.475763: Epoch time: 18.68 s +2024-11-23 02:07:28.401377: +2024-11-23 02:07:28.401633: Epoch 7325 +2024-11-23 02:07:28.401751: Current learning rate: 0.00108 +2024-11-23 02:07:46.811942: train_loss -0.8248 +2024-11-23 02:07:46.812157: val_loss -0.7863 +2024-11-23 02:07:46.812231: Pseudo dice [0.8494] +2024-11-23 02:07:46.812303: Epoch time: 18.41 s +2024-11-23 02:07:47.881128: +2024-11-23 02:07:47.881344: Epoch 7326 +2024-11-23 02:07:47.881455: Current learning rate: 0.00108 +2024-11-23 02:08:06.077290: train_loss -0.8187 +2024-11-23 02:08:06.077757: val_loss -0.7594 +2024-11-23 02:08:06.077854: Pseudo dice [0.8411] +2024-11-23 02:08:06.077929: Epoch time: 18.2 s +2024-11-23 02:08:06.987020: +2024-11-23 02:08:06.987279: Epoch 7327 +2024-11-23 02:08:06.987399: Current learning rate: 0.00108 +2024-11-23 02:08:26.196265: train_loss -0.824 +2024-11-23 02:08:26.196806: val_loss -0.786 +2024-11-23 02:08:26.196907: Pseudo dice [0.8417] +2024-11-23 02:08:26.196984: Epoch time: 19.21 s +2024-11-23 02:08:27.117395: +2024-11-23 02:08:27.117620: Epoch 7328 +2024-11-23 02:08:27.117729: Current learning rate: 0.00108 +2024-11-23 02:08:44.966923: train_loss -0.8271 +2024-11-23 02:08:44.967185: val_loss -0.7773 +2024-11-23 02:08:44.967264: Pseudo dice [0.8507] +2024-11-23 02:08:44.967345: Epoch time: 17.85 s +2024-11-23 02:08:45.880883: +2024-11-23 02:08:45.881096: Epoch 7329 +2024-11-23 02:08:45.881215: Current learning rate: 0.00107 +2024-11-23 02:09:04.374809: train_loss -0.8266 +2024-11-23 02:09:04.375044: val_loss -0.7759 +2024-11-23 02:09:04.375118: Pseudo dice [0.8547] +2024-11-23 02:09:04.375196: Epoch time: 18.49 s +2024-11-23 02:09:05.299522: +2024-11-23 02:09:05.299742: Epoch 7330 +2024-11-23 02:09:05.299851: Current learning rate: 0.00107 +2024-11-23 02:09:24.134738: train_loss -0.8292 +2024-11-23 02:09:24.134954: val_loss -0.7761 +2024-11-23 02:09:24.135077: Pseudo dice [0.8481] +2024-11-23 02:09:24.135154: Epoch time: 18.84 s +2024-11-23 02:09:25.045995: +2024-11-23 02:09:25.046227: Epoch 7331 +2024-11-23 02:09:25.046341: Current learning rate: 0.00107 +2024-11-23 02:09:42.071826: train_loss -0.8277 +2024-11-23 02:09:42.072050: val_loss -0.7763 +2024-11-23 02:09:42.072128: Pseudo dice [0.8652] +2024-11-23 02:09:42.072207: Epoch time: 17.03 s +2024-11-23 02:09:42.984859: +2024-11-23 02:09:42.985086: Epoch 7332 +2024-11-23 02:09:42.985201: Current learning rate: 0.00107 +2024-11-23 02:10:00.771549: train_loss -0.8266 +2024-11-23 02:10:00.771806: val_loss -0.798 +2024-11-23 02:10:00.771886: Pseudo dice [0.8364] +2024-11-23 02:10:00.771969: Epoch time: 17.79 s +2024-11-23 02:10:01.683705: +2024-11-23 02:10:01.683922: Epoch 7333 +2024-11-23 02:10:01.684035: Current learning rate: 0.00107 +2024-11-23 02:10:19.162988: train_loss -0.8315 +2024-11-23 02:10:19.163214: val_loss -0.7887 +2024-11-23 02:10:19.163287: Pseudo dice [0.8444] +2024-11-23 02:10:19.163361: Epoch time: 17.48 s +2024-11-23 02:10:20.074579: +2024-11-23 02:10:20.074795: Epoch 7334 +2024-11-23 02:10:20.074905: Current learning rate: 0.00107 +2024-11-23 02:10:38.310786: train_loss -0.8239 +2024-11-23 02:10:38.311018: val_loss -0.7678 +2024-11-23 02:10:38.311094: Pseudo dice [0.8466] +2024-11-23 02:10:38.311169: Epoch time: 18.24 s +2024-11-23 02:10:39.233723: +2024-11-23 02:10:39.233928: Epoch 7335 +2024-11-23 02:10:39.234045: Current learning rate: 0.00107 +2024-11-23 02:10:56.856026: train_loss -0.8303 +2024-11-23 02:10:56.856277: val_loss -0.8004 +2024-11-23 02:10:56.856351: Pseudo dice [0.8621] +2024-11-23 02:10:56.856706: Epoch time: 17.62 s +2024-11-23 02:10:57.762606: +2024-11-23 02:10:57.762906: Epoch 7336 +2024-11-23 02:10:57.763020: Current learning rate: 0.00106 +2024-11-23 02:11:16.586413: train_loss -0.8226 +2024-11-23 02:11:16.586626: val_loss -0.7967 +2024-11-23 02:11:16.586750: Pseudo dice [0.8634] +2024-11-23 02:11:16.586828: Epoch time: 18.82 s +2024-11-23 02:11:17.604254: +2024-11-23 02:11:17.604563: Epoch 7337 +2024-11-23 02:11:17.604671: Current learning rate: 0.00106 +2024-11-23 02:11:35.025018: train_loss -0.833 +2024-11-23 02:11:35.025260: val_loss -0.778 +2024-11-23 02:11:35.025333: Pseudo dice [0.848] +2024-11-23 02:11:35.025409: Epoch time: 17.42 s +2024-11-23 02:11:36.254295: +2024-11-23 02:11:36.254502: Epoch 7338 +2024-11-23 02:11:36.254612: Current learning rate: 0.00106 +2024-11-23 02:11:53.733914: train_loss -0.8287 +2024-11-23 02:11:53.734134: val_loss -0.7746 +2024-11-23 02:11:53.734209: Pseudo dice [0.8662] +2024-11-23 02:11:53.734283: Epoch time: 17.48 s +2024-11-23 02:11:54.648501: +2024-11-23 02:11:54.648755: Epoch 7339 +2024-11-23 02:11:54.648871: Current learning rate: 0.00106 +2024-11-23 02:12:12.979708: train_loss -0.8269 +2024-11-23 02:12:12.979948: val_loss -0.7818 +2024-11-23 02:12:12.980034: Pseudo dice [0.8464] +2024-11-23 02:12:12.980112: Epoch time: 18.33 s +2024-11-23 02:12:14.027711: +2024-11-23 02:12:14.027939: Epoch 7340 +2024-11-23 02:12:14.028058: Current learning rate: 0.00106 +2024-11-23 02:12:32.913187: train_loss -0.8258 +2024-11-23 02:12:32.913406: val_loss -0.7796 +2024-11-23 02:12:32.913482: Pseudo dice [0.8618] +2024-11-23 02:12:32.913559: Epoch time: 18.89 s +2024-11-23 02:12:33.832778: +2024-11-23 02:12:33.833009: Epoch 7341 +2024-11-23 02:12:33.833119: Current learning rate: 0.00106 +2024-11-23 02:12:52.158857: train_loss -0.8343 +2024-11-23 02:12:52.159087: val_loss -0.7672 +2024-11-23 02:12:52.159162: Pseudo dice [0.8438] +2024-11-23 02:12:52.159235: Epoch time: 18.33 s +2024-11-23 02:12:53.073146: +2024-11-23 02:12:53.073406: Epoch 7342 +2024-11-23 02:12:53.073519: Current learning rate: 0.00106 +2024-11-23 02:13:12.689337: train_loss -0.823 +2024-11-23 02:13:12.689672: val_loss -0.7526 +2024-11-23 02:13:12.689757: Pseudo dice [0.8411] +2024-11-23 02:13:12.689852: Epoch time: 19.62 s +2024-11-23 02:13:13.615094: +2024-11-23 02:13:13.615326: Epoch 7343 +2024-11-23 02:13:13.615601: Current learning rate: 0.00105 +2024-11-23 02:13:33.308851: train_loss -0.8238 +2024-11-23 02:13:33.309128: val_loss -0.7635 +2024-11-23 02:13:33.309201: Pseudo dice [0.8549] +2024-11-23 02:13:33.309275: Epoch time: 19.69 s +2024-11-23 02:13:34.217393: +2024-11-23 02:13:34.217653: Epoch 7344 +2024-11-23 02:13:34.217764: Current learning rate: 0.00105 +2024-11-23 02:13:52.216603: train_loss -0.8277 +2024-11-23 02:13:52.216826: val_loss -0.7708 +2024-11-23 02:13:52.216900: Pseudo dice [0.8539] +2024-11-23 02:13:52.216974: Epoch time: 18.0 s +2024-11-23 02:13:53.144443: +2024-11-23 02:13:53.144668: Epoch 7345 +2024-11-23 02:13:53.144790: Current learning rate: 0.00105 +2024-11-23 02:14:11.083768: train_loss -0.8315 +2024-11-23 02:14:11.084002: val_loss -0.7817 +2024-11-23 02:14:11.084086: Pseudo dice [0.8321] +2024-11-23 02:14:11.084163: Epoch time: 17.94 s +2024-11-23 02:14:11.999288: +2024-11-23 02:14:11.999535: Epoch 7346 +2024-11-23 02:14:11.999647: Current learning rate: 0.00105 +2024-11-23 02:14:29.526333: train_loss -0.8278 +2024-11-23 02:14:29.526574: val_loss -0.7855 +2024-11-23 02:14:29.526646: Pseudo dice [0.843] +2024-11-23 02:14:29.526725: Epoch time: 17.53 s +2024-11-23 02:14:30.434124: +2024-11-23 02:14:30.434322: Epoch 7347 +2024-11-23 02:14:30.434437: Current learning rate: 0.00105 +2024-11-23 02:14:48.423367: train_loss -0.8255 +2024-11-23 02:14:48.423595: val_loss -0.7898 +2024-11-23 02:14:48.423671: Pseudo dice [0.8527] +2024-11-23 02:14:48.423748: Epoch time: 17.99 s +2024-11-23 02:14:49.331571: +2024-11-23 02:14:49.331804: Epoch 7348 +2024-11-23 02:14:49.331915: Current learning rate: 0.00105 +2024-11-23 02:15:07.635912: train_loss -0.8224 +2024-11-23 02:15:07.650193: val_loss -0.7809 +2024-11-23 02:15:07.650357: Pseudo dice [0.8478] +2024-11-23 02:15:07.650444: Epoch time: 18.31 s +2024-11-23 02:15:09.033485: +2024-11-23 02:15:09.033745: Epoch 7349 +2024-11-23 02:15:09.033860: Current learning rate: 0.00105 +2024-11-23 02:15:28.645314: train_loss -0.8248 +2024-11-23 02:15:28.645590: val_loss -0.7681 +2024-11-23 02:15:28.645670: Pseudo dice [0.8568] +2024-11-23 02:15:28.645750: Epoch time: 19.61 s +2024-11-23 02:15:29.940500: +2024-11-23 02:15:29.940731: Epoch 7350 +2024-11-23 02:15:29.940844: Current learning rate: 0.00104 +2024-11-23 02:15:48.400995: train_loss -0.8245 +2024-11-23 02:15:48.401282: val_loss -0.78 +2024-11-23 02:15:48.401365: Pseudo dice [0.8625] +2024-11-23 02:15:48.401441: Epoch time: 18.46 s +2024-11-23 02:15:49.316130: +2024-11-23 02:15:49.316341: Epoch 7351 +2024-11-23 02:15:49.316450: Current learning rate: 0.00104 +2024-11-23 02:16:07.362838: train_loss -0.8237 +2024-11-23 02:16:07.363082: val_loss -0.7749 +2024-11-23 02:16:07.363164: Pseudo dice [0.8477] +2024-11-23 02:16:07.363243: Epoch time: 18.05 s +2024-11-23 02:16:08.270910: +2024-11-23 02:16:08.271189: Epoch 7352 +2024-11-23 02:16:08.271300: Current learning rate: 0.00104 +2024-11-23 02:16:26.780285: train_loss -0.8164 +2024-11-23 02:16:26.780531: val_loss -0.7749 +2024-11-23 02:16:26.780617: Pseudo dice [0.8471] +2024-11-23 02:16:26.780729: Epoch time: 18.51 s +2024-11-23 02:16:27.686001: +2024-11-23 02:16:27.686266: Epoch 7353 +2024-11-23 02:16:27.686376: Current learning rate: 0.00104 +2024-11-23 02:16:46.567547: train_loss -0.8298 +2024-11-23 02:16:46.567795: val_loss -0.8077 +2024-11-23 02:16:46.567870: Pseudo dice [0.8673] +2024-11-23 02:16:46.567951: Epoch time: 18.88 s +2024-11-23 02:16:47.470911: +2024-11-23 02:16:47.471146: Epoch 7354 +2024-11-23 02:16:47.471271: Current learning rate: 0.00104 +2024-11-23 02:17:06.521057: train_loss -0.8199 +2024-11-23 02:17:06.521268: val_loss -0.7885 +2024-11-23 02:17:06.521340: Pseudo dice [0.8361] +2024-11-23 02:17:06.521415: Epoch time: 19.05 s +2024-11-23 02:17:07.581912: +2024-11-23 02:17:07.582109: Epoch 7355 +2024-11-23 02:17:07.582217: Current learning rate: 0.00104 +2024-11-23 02:17:26.179672: train_loss -0.8227 +2024-11-23 02:17:26.179907: val_loss -0.7832 +2024-11-23 02:17:26.179986: Pseudo dice [0.8543] +2024-11-23 02:17:26.180069: Epoch time: 18.6 s +2024-11-23 02:17:27.108093: +2024-11-23 02:17:27.108317: Epoch 7356 +2024-11-23 02:17:27.108428: Current learning rate: 0.00104 +2024-11-23 02:17:46.146024: train_loss -0.8189 +2024-11-23 02:17:46.146279: val_loss -0.7755 +2024-11-23 02:17:46.146356: Pseudo dice [0.863] +2024-11-23 02:17:46.146432: Epoch time: 19.04 s +2024-11-23 02:17:47.165018: +2024-11-23 02:17:47.165252: Epoch 7357 +2024-11-23 02:17:47.165392: Current learning rate: 0.00103 +2024-11-23 02:18:05.757141: train_loss -0.8236 +2024-11-23 02:18:05.757363: val_loss -0.7796 +2024-11-23 02:18:05.757437: Pseudo dice [0.8477] +2024-11-23 02:18:05.757512: Epoch time: 18.59 s +2024-11-23 02:18:06.664507: +2024-11-23 02:18:06.664722: Epoch 7358 +2024-11-23 02:18:06.664828: Current learning rate: 0.00103 +2024-11-23 02:18:25.254907: train_loss -0.8236 +2024-11-23 02:18:25.255146: val_loss -0.7938 +2024-11-23 02:18:25.255226: Pseudo dice [0.8457] +2024-11-23 02:18:25.255321: Epoch time: 18.59 s +2024-11-23 02:18:26.169875: +2024-11-23 02:18:26.170101: Epoch 7359 +2024-11-23 02:18:26.170212: Current learning rate: 0.00103 +2024-11-23 02:18:43.963182: train_loss -0.8243 +2024-11-23 02:18:43.963435: val_loss -0.7988 +2024-11-23 02:18:43.963510: Pseudo dice [0.8595] +2024-11-23 02:18:43.963588: Epoch time: 17.79 s +2024-11-23 02:18:44.898900: +2024-11-23 02:18:44.899120: Epoch 7360 +2024-11-23 02:18:44.899227: Current learning rate: 0.00103 +2024-11-23 02:19:02.931361: train_loss -0.8269 +2024-11-23 02:19:02.931602: val_loss -0.773 +2024-11-23 02:19:02.931685: Pseudo dice [0.8409] +2024-11-23 02:19:02.931768: Epoch time: 18.03 s +2024-11-23 02:19:04.270382: +2024-11-23 02:19:04.270602: Epoch 7361 +2024-11-23 02:19:04.270961: Current learning rate: 0.00103 +2024-11-23 02:19:22.328554: train_loss -0.8242 +2024-11-23 02:19:22.328771: val_loss -0.7408 +2024-11-23 02:19:22.328842: Pseudo dice [0.855] +2024-11-23 02:19:22.328914: Epoch time: 18.06 s +2024-11-23 02:19:23.255621: +2024-11-23 02:19:23.255854: Epoch 7362 +2024-11-23 02:19:23.255969: Current learning rate: 0.00103 +2024-11-23 02:19:42.035812: train_loss -0.8286 +2024-11-23 02:19:42.036089: val_loss -0.7793 +2024-11-23 02:19:42.036165: Pseudo dice [0.8456] +2024-11-23 02:19:42.036244: Epoch time: 18.78 s +2024-11-23 02:19:42.952863: +2024-11-23 02:19:42.953098: Epoch 7363 +2024-11-23 02:19:42.953208: Current learning rate: 0.00103 +2024-11-23 02:20:02.133862: train_loss -0.8134 +2024-11-23 02:20:02.134115: val_loss -0.809 +2024-11-23 02:20:02.134191: Pseudo dice [0.8552] +2024-11-23 02:20:02.134273: Epoch time: 19.18 s +2024-11-23 02:20:03.050364: +2024-11-23 02:20:03.050589: Epoch 7364 +2024-11-23 02:20:03.050707: Current learning rate: 0.00102 +2024-11-23 02:20:20.358192: train_loss -0.825 +2024-11-23 02:20:20.358425: val_loss -0.7823 +2024-11-23 02:20:20.358503: Pseudo dice [0.8429] +2024-11-23 02:20:20.358578: Epoch time: 17.31 s +2024-11-23 02:20:21.283959: +2024-11-23 02:20:21.284238: Epoch 7365 +2024-11-23 02:20:21.284353: Current learning rate: 0.00102 +2024-11-23 02:20:40.472686: train_loss -0.8215 +2024-11-23 02:20:40.472900: val_loss -0.7795 +2024-11-23 02:20:40.472971: Pseudo dice [0.8492] +2024-11-23 02:20:40.473052: Epoch time: 19.19 s +2024-11-23 02:20:41.390198: +2024-11-23 02:20:41.390430: Epoch 7366 +2024-11-23 02:20:41.390539: Current learning rate: 0.00102 +2024-11-23 02:20:59.047080: train_loss -0.825 +2024-11-23 02:20:59.047297: val_loss -0.7669 +2024-11-23 02:20:59.047369: Pseudo dice [0.8424] +2024-11-23 02:20:59.047441: Epoch time: 17.66 s +2024-11-23 02:20:59.952931: +2024-11-23 02:20:59.953140: Epoch 7367 +2024-11-23 02:20:59.953250: Current learning rate: 0.00102 +2024-11-23 02:21:17.184541: train_loss -0.8284 +2024-11-23 02:21:17.184795: val_loss -0.7696 +2024-11-23 02:21:17.184869: Pseudo dice [0.8622] +2024-11-23 02:21:17.184951: Epoch time: 17.23 s +2024-11-23 02:21:18.116843: +2024-11-23 02:21:18.117074: Epoch 7368 +2024-11-23 02:21:18.117185: Current learning rate: 0.00102 +2024-11-23 02:21:36.852126: train_loss -0.8241 +2024-11-23 02:21:36.852360: val_loss -0.7824 +2024-11-23 02:21:36.852437: Pseudo dice [0.8476] +2024-11-23 02:21:36.852512: Epoch time: 18.74 s +2024-11-23 02:21:37.770761: +2024-11-23 02:21:37.771158: Epoch 7369 +2024-11-23 02:21:37.771270: Current learning rate: 0.00102 +2024-11-23 02:21:56.564833: train_loss -0.8246 +2024-11-23 02:21:56.565137: val_loss -0.77 +2024-11-23 02:21:56.565213: Pseudo dice [0.8481] +2024-11-23 02:21:56.565287: Epoch time: 18.79 s +2024-11-23 02:21:57.521457: +2024-11-23 02:21:57.521844: Epoch 7370 +2024-11-23 02:21:57.521957: Current learning rate: 0.00102 +2024-11-23 02:22:15.142024: train_loss -0.8182 +2024-11-23 02:22:15.142295: val_loss -0.777 +2024-11-23 02:22:15.142370: Pseudo dice [0.8643] +2024-11-23 02:22:15.142446: Epoch time: 17.62 s +2024-11-23 02:22:16.053857: +2024-11-23 02:22:16.054072: Epoch 7371 +2024-11-23 02:22:16.054180: Current learning rate: 0.00101 +2024-11-23 02:22:34.981879: train_loss -0.8198 +2024-11-23 02:22:34.982131: val_loss -0.7809 +2024-11-23 02:22:34.982204: Pseudo dice [0.8429] +2024-11-23 02:22:34.982282: Epoch time: 18.93 s +2024-11-23 02:22:36.264847: +2024-11-23 02:22:36.265091: Epoch 7372 +2024-11-23 02:22:36.265203: Current learning rate: 0.00101 +2024-11-23 02:22:54.800468: train_loss -0.821 +2024-11-23 02:22:54.800691: val_loss -0.7525 +2024-11-23 02:22:54.800770: Pseudo dice [0.8321] +2024-11-23 02:22:54.800849: Epoch time: 18.54 s +2024-11-23 02:22:55.717839: +2024-11-23 02:22:55.718055: Epoch 7373 +2024-11-23 02:22:55.718161: Current learning rate: 0.00101 +2024-11-23 02:23:14.019768: train_loss -0.8284 +2024-11-23 02:23:14.019982: val_loss -0.7791 +2024-11-23 02:23:14.020067: Pseudo dice [0.8357] +2024-11-23 02:23:14.040872: Epoch time: 18.3 s +2024-11-23 02:23:15.010807: +2024-11-23 02:23:15.011032: Epoch 7374 +2024-11-23 02:23:15.011143: Current learning rate: 0.00101 +2024-11-23 02:23:33.761781: train_loss -0.8216 +2024-11-23 02:23:33.762041: val_loss -0.7827 +2024-11-23 02:23:33.762114: Pseudo dice [0.8434] +2024-11-23 02:23:33.762192: Epoch time: 18.75 s +2024-11-23 02:23:34.678382: +2024-11-23 02:23:34.678599: Epoch 7375 +2024-11-23 02:23:34.678715: Current learning rate: 0.00101 +2024-11-23 02:23:51.987340: train_loss -0.8221 +2024-11-23 02:23:51.987560: val_loss -0.7741 +2024-11-23 02:23:51.987634: Pseudo dice [0.8524] +2024-11-23 02:23:51.987710: Epoch time: 17.31 s +2024-11-23 02:23:52.900297: +2024-11-23 02:23:52.900516: Epoch 7376 +2024-11-23 02:23:52.900623: Current learning rate: 0.00101 +2024-11-23 02:24:11.402652: train_loss -0.8287 +2024-11-23 02:24:11.402889: val_loss -0.7759 +2024-11-23 02:24:11.402965: Pseudo dice [0.8605] +2024-11-23 02:24:11.403047: Epoch time: 18.5 s +2024-11-23 02:24:12.309925: +2024-11-23 02:24:12.310146: Epoch 7377 +2024-11-23 02:24:12.310258: Current learning rate: 0.00101 +2024-11-23 02:24:30.363794: train_loss -0.8235 +2024-11-23 02:24:30.364042: val_loss -0.7664 +2024-11-23 02:24:30.364117: Pseudo dice [0.8529] +2024-11-23 02:24:30.364190: Epoch time: 18.05 s +2024-11-23 02:24:31.277743: +2024-11-23 02:24:31.278006: Epoch 7378 +2024-11-23 02:24:31.278128: Current learning rate: 0.001 +2024-11-23 02:24:49.707025: train_loss -0.8257 +2024-11-23 02:24:49.707264: val_loss -0.7491 +2024-11-23 02:24:49.707337: Pseudo dice [0.8407] +2024-11-23 02:24:49.707414: Epoch time: 18.43 s +2024-11-23 02:24:50.625514: +2024-11-23 02:24:50.625735: Epoch 7379 +2024-11-23 02:24:50.625844: Current learning rate: 0.001 +2024-11-23 02:25:09.399629: train_loss -0.8301 +2024-11-23 02:25:09.399854: val_loss -0.7743 +2024-11-23 02:25:09.399950: Pseudo dice [0.8593] +2024-11-23 02:25:09.400036: Epoch time: 18.77 s +2024-11-23 02:25:10.317469: +2024-11-23 02:25:10.317715: Epoch 7380 +2024-11-23 02:25:10.317829: Current learning rate: 0.001 +2024-11-23 02:25:30.100391: train_loss -0.8228 +2024-11-23 02:25:30.100616: val_loss -0.7913 +2024-11-23 02:25:30.100692: Pseudo dice [0.8575] +2024-11-23 02:25:30.100770: Epoch time: 19.78 s +2024-11-23 02:25:31.087688: +2024-11-23 02:25:31.087907: Epoch 7381 +2024-11-23 02:25:31.088022: Current learning rate: 0.001 +2024-11-23 02:25:50.342907: train_loss -0.8227 +2024-11-23 02:25:50.343251: val_loss -0.7892 +2024-11-23 02:25:50.343330: Pseudo dice [0.8396] +2024-11-23 02:25:50.343405: Epoch time: 19.26 s +2024-11-23 02:25:51.347872: +2024-11-23 02:25:51.348094: Epoch 7382 +2024-11-23 02:25:51.348204: Current learning rate: 0.001 +2024-11-23 02:26:10.006585: train_loss -0.8202 +2024-11-23 02:26:10.006854: val_loss -0.7874 +2024-11-23 02:26:10.006931: Pseudo dice [0.8563] +2024-11-23 02:26:10.007017: Epoch time: 18.66 s +2024-11-23 02:26:10.919864: +2024-11-23 02:26:10.920300: Epoch 7383 +2024-11-23 02:26:10.920438: Current learning rate: 0.001 +2024-11-23 02:26:28.812845: train_loss -0.8222 +2024-11-23 02:26:28.813071: val_loss -0.7641 +2024-11-23 02:26:28.813145: Pseudo dice [0.867] +2024-11-23 02:26:28.813219: Epoch time: 17.89 s +2024-11-23 02:26:30.167261: +2024-11-23 02:26:30.167495: Epoch 7384 +2024-11-23 02:26:30.167614: Current learning rate: 0.001 +2024-11-23 02:26:49.372385: train_loss -0.8245 +2024-11-23 02:26:49.387185: val_loss -0.7451 +2024-11-23 02:26:49.387307: Pseudo dice [0.8644] +2024-11-23 02:26:49.387386: Epoch time: 19.21 s +2024-11-23 02:26:50.335571: +2024-11-23 02:26:50.335860: Epoch 7385 +2024-11-23 02:26:50.335967: Current learning rate: 0.00099 +2024-11-23 02:27:08.957934: train_loss -0.8218 +2024-11-23 02:27:08.958193: val_loss -0.7916 +2024-11-23 02:27:08.958270: Pseudo dice [0.8416] +2024-11-23 02:27:08.958350: Epoch time: 18.62 s +2024-11-23 02:27:09.878953: +2024-11-23 02:27:09.879170: Epoch 7386 +2024-11-23 02:27:09.879282: Current learning rate: 0.00099 +2024-11-23 02:27:28.514431: train_loss -0.8233 +2024-11-23 02:27:28.516830: val_loss -0.7656 +2024-11-23 02:27:28.538636: Pseudo dice [0.8585] +2024-11-23 02:27:28.538805: Epoch time: 18.64 s +2024-11-23 02:27:29.658681: +2024-11-23 02:27:29.658905: Epoch 7387 +2024-11-23 02:27:29.659022: Current learning rate: 0.00099 +2024-11-23 02:27:47.855324: train_loss -0.8266 +2024-11-23 02:27:47.855910: val_loss -0.771 +2024-11-23 02:27:47.855987: Pseudo dice [0.86] +2024-11-23 02:27:47.856064: Epoch time: 18.2 s +2024-11-23 02:27:48.758283: +2024-11-23 02:27:48.758493: Epoch 7388 +2024-11-23 02:27:48.758598: Current learning rate: 0.00099 +2024-11-23 02:28:07.062656: train_loss -0.8234 +2024-11-23 02:28:07.062886: val_loss -0.7945 +2024-11-23 02:28:07.062970: Pseudo dice [0.8523] +2024-11-23 02:28:07.063053: Epoch time: 18.31 s +2024-11-23 02:28:08.106294: +2024-11-23 02:28:08.106530: Epoch 7389 +2024-11-23 02:28:08.106645: Current learning rate: 0.00099 +2024-11-23 02:28:26.424575: train_loss -0.8297 +2024-11-23 02:28:26.424885: val_loss -0.8023 +2024-11-23 02:28:26.424967: Pseudo dice [0.835] +2024-11-23 02:28:26.425072: Epoch time: 18.32 s +2024-11-23 02:28:27.348920: +2024-11-23 02:28:27.349144: Epoch 7390 +2024-11-23 02:28:27.349251: Current learning rate: 0.00099 +2024-11-23 02:28:46.537040: train_loss -0.8213 +2024-11-23 02:28:46.537243: val_loss -0.7789 +2024-11-23 02:28:46.537319: Pseudo dice [0.8577] +2024-11-23 02:28:46.537394: Epoch time: 19.19 s +2024-11-23 02:28:47.448402: +2024-11-23 02:28:47.448635: Epoch 7391 +2024-11-23 02:28:47.448743: Current learning rate: 0.00098 +2024-11-23 02:29:06.379157: train_loss -0.8225 +2024-11-23 02:29:06.383523: val_loss -0.7761 +2024-11-23 02:29:06.383624: Pseudo dice [0.8483] +2024-11-23 02:29:06.383700: Epoch time: 18.93 s +2024-11-23 02:29:07.332440: +2024-11-23 02:29:07.332656: Epoch 7392 +2024-11-23 02:29:07.332763: Current learning rate: 0.00098 +2024-11-23 02:29:25.600678: train_loss -0.8217 +2024-11-23 02:29:25.600894: val_loss -0.7612 +2024-11-23 02:29:25.600975: Pseudo dice [0.8517] +2024-11-23 02:29:25.601058: Epoch time: 18.27 s +2024-11-23 02:29:26.509163: +2024-11-23 02:29:26.509375: Epoch 7393 +2024-11-23 02:29:26.509485: Current learning rate: 0.00098 +2024-11-23 02:29:44.910547: train_loss -0.8248 +2024-11-23 02:29:44.910797: val_loss -0.7872 +2024-11-23 02:29:44.910879: Pseudo dice [0.8653] +2024-11-23 02:29:44.910959: Epoch time: 18.4 s +2024-11-23 02:29:45.862802: +2024-11-23 02:29:45.863029: Epoch 7394 +2024-11-23 02:29:45.863143: Current learning rate: 0.00098 +2024-11-23 02:30:04.877046: train_loss -0.8302 +2024-11-23 02:30:04.877259: val_loss -0.7828 +2024-11-23 02:30:04.877335: Pseudo dice [0.8469] +2024-11-23 02:30:04.877410: Epoch time: 19.02 s +2024-11-23 02:30:06.227054: +2024-11-23 02:30:06.227350: Epoch 7395 +2024-11-23 02:30:06.227477: Current learning rate: 0.00098 +2024-11-23 02:30:24.551456: train_loss -0.8251 +2024-11-23 02:30:24.551672: val_loss -0.7759 +2024-11-23 02:30:24.551745: Pseudo dice [0.8627] +2024-11-23 02:30:24.554013: Epoch time: 18.33 s +2024-11-23 02:30:25.524913: +2024-11-23 02:30:25.525141: Epoch 7396 +2024-11-23 02:30:25.525253: Current learning rate: 0.00098 +2024-11-23 02:30:43.936828: train_loss -0.8304 +2024-11-23 02:30:43.937088: val_loss -0.7796 +2024-11-23 02:30:43.937168: Pseudo dice [0.8529] +2024-11-23 02:30:43.937248: Epoch time: 18.41 s +2024-11-23 02:30:44.865412: +2024-11-23 02:30:44.865634: Epoch 7397 +2024-11-23 02:30:44.865748: Current learning rate: 0.00098 +2024-11-23 02:31:03.626808: train_loss -0.8223 +2024-11-23 02:31:03.627033: val_loss -0.7799 +2024-11-23 02:31:03.627106: Pseudo dice [0.8655] +2024-11-23 02:31:03.627184: Epoch time: 18.76 s +2024-11-23 02:31:04.543235: +2024-11-23 02:31:04.543451: Epoch 7398 +2024-11-23 02:31:04.543558: Current learning rate: 0.00097 +2024-11-23 02:31:23.360187: train_loss -0.8242 +2024-11-23 02:31:23.360407: val_loss -0.7644 +2024-11-23 02:31:23.360482: Pseudo dice [0.8474] +2024-11-23 02:31:23.360558: Epoch time: 18.82 s +2024-11-23 02:31:24.280452: +2024-11-23 02:31:24.280671: Epoch 7399 +2024-11-23 02:31:24.280778: Current learning rate: 0.00097 +2024-11-23 02:31:42.605734: train_loss -0.8257 +2024-11-23 02:31:42.605958: val_loss -0.7818 +2024-11-23 02:31:42.606039: Pseudo dice [0.862] +2024-11-23 02:31:42.606116: Epoch time: 18.33 s +2024-11-23 02:31:44.091334: +2024-11-23 02:31:44.091563: Epoch 7400 +2024-11-23 02:31:44.091686: Current learning rate: 0.00097 +2024-11-23 02:32:02.158535: train_loss -0.8266 +2024-11-23 02:32:02.158753: val_loss -0.7905 +2024-11-23 02:32:02.158826: Pseudo dice [0.8672] +2024-11-23 02:32:02.158899: Epoch time: 18.07 s +2024-11-23 02:32:03.084082: +2024-11-23 02:32:03.084323: Epoch 7401 +2024-11-23 02:32:03.084435: Current learning rate: 0.00097 +2024-11-23 02:32:21.584158: train_loss -0.8237 +2024-11-23 02:32:21.584404: val_loss -0.7675 +2024-11-23 02:32:21.584481: Pseudo dice [0.8448] +2024-11-23 02:32:21.584561: Epoch time: 18.5 s +2024-11-23 02:32:22.496509: +2024-11-23 02:32:22.496733: Epoch 7402 +2024-11-23 02:32:22.496856: Current learning rate: 0.00097 +2024-11-23 02:32:40.897032: train_loss -0.8273 +2024-11-23 02:32:40.897233: val_loss -0.7763 +2024-11-23 02:32:40.897306: Pseudo dice [0.8488] +2024-11-23 02:32:40.897380: Epoch time: 18.4 s +2024-11-23 02:32:41.854266: +2024-11-23 02:32:41.854467: Epoch 7403 +2024-11-23 02:32:41.854573: Current learning rate: 0.00097 +2024-11-23 02:33:01.486657: train_loss -0.823 +2024-11-23 02:33:01.486872: val_loss -0.7674 +2024-11-23 02:33:01.486946: Pseudo dice [0.863] +2024-11-23 02:33:01.487025: Epoch time: 19.63 s +2024-11-23 02:33:02.393099: +2024-11-23 02:33:02.393337: Epoch 7404 +2024-11-23 02:33:02.393456: Current learning rate: 0.00097 +2024-11-23 02:33:20.102916: train_loss -0.8318 +2024-11-23 02:33:20.103176: val_loss -0.7737 +2024-11-23 02:33:20.103260: Pseudo dice [0.8674] +2024-11-23 02:33:20.103347: Epoch time: 17.71 s +2024-11-23 02:33:21.015512: +2024-11-23 02:33:21.015820: Epoch 7405 +2024-11-23 02:33:21.015929: Current learning rate: 0.00096 +2024-11-23 02:33:40.255181: train_loss -0.8287 +2024-11-23 02:33:40.255465: val_loss -0.7824 +2024-11-23 02:33:40.255545: Pseudo dice [0.8491] +2024-11-23 02:33:40.255619: Epoch time: 19.24 s +2024-11-23 02:33:41.167984: +2024-11-23 02:33:41.168206: Epoch 7406 +2024-11-23 02:33:41.168323: Current learning rate: 0.00096 +2024-11-23 02:33:59.768862: train_loss -0.8269 +2024-11-23 02:33:59.769171: val_loss -0.7776 +2024-11-23 02:33:59.769271: Pseudo dice [0.8625] +2024-11-23 02:33:59.769357: Epoch time: 18.6 s +2024-11-23 02:34:01.088077: +2024-11-23 02:34:01.088324: Epoch 7407 +2024-11-23 02:34:01.088441: Current learning rate: 0.00096 +2024-11-23 02:34:19.605549: train_loss -0.818 +2024-11-23 02:34:19.605788: val_loss -0.7754 +2024-11-23 02:34:19.608099: Pseudo dice [0.8438] +2024-11-23 02:34:19.608242: Epoch time: 18.52 s +2024-11-23 02:34:20.539453: +2024-11-23 02:34:20.539686: Epoch 7408 +2024-11-23 02:34:20.539801: Current learning rate: 0.00096 +2024-11-23 02:34:39.233754: train_loss -0.8247 +2024-11-23 02:34:39.234040: val_loss -0.8004 +2024-11-23 02:34:39.234119: Pseudo dice [0.8649] +2024-11-23 02:34:39.234201: Epoch time: 18.7 s +2024-11-23 02:34:40.319378: +2024-11-23 02:34:40.319580: Epoch 7409 +2024-11-23 02:34:40.319685: Current learning rate: 0.00096 +2024-11-23 02:34:58.105490: train_loss -0.826 +2024-11-23 02:34:58.105713: val_loss -0.7779 +2024-11-23 02:34:58.105788: Pseudo dice [0.859] +2024-11-23 02:34:58.105876: Epoch time: 17.79 s +2024-11-23 02:34:59.012665: +2024-11-23 02:34:59.012882: Epoch 7410 +2024-11-23 02:34:59.013001: Current learning rate: 0.00096 +2024-11-23 02:35:17.829131: train_loss -0.8276 +2024-11-23 02:35:17.829350: val_loss -0.7825 +2024-11-23 02:35:17.829425: Pseudo dice [0.8548] +2024-11-23 02:35:17.829501: Epoch time: 18.82 s +2024-11-23 02:35:18.744365: +2024-11-23 02:35:18.744587: Epoch 7411 +2024-11-23 02:35:18.744701: Current learning rate: 0.00096 +2024-11-23 02:35:37.082049: train_loss -0.83 +2024-11-23 02:35:37.082273: val_loss -0.7714 +2024-11-23 02:35:37.082347: Pseudo dice [0.8488] +2024-11-23 02:35:37.082438: Epoch time: 18.34 s +2024-11-23 02:35:38.012137: +2024-11-23 02:35:38.012362: Epoch 7412 +2024-11-23 02:35:38.012472: Current learning rate: 0.00095 +2024-11-23 02:35:55.412061: train_loss -0.831 +2024-11-23 02:35:55.412311: val_loss -0.7916 +2024-11-23 02:35:55.412386: Pseudo dice [0.8582] +2024-11-23 02:35:55.412464: Epoch time: 17.4 s +2024-11-23 02:35:56.325351: +2024-11-23 02:35:56.325560: Epoch 7413 +2024-11-23 02:35:56.325668: Current learning rate: 0.00095 +2024-11-23 02:36:15.206788: train_loss -0.8298 +2024-11-23 02:36:15.207016: val_loss -0.7567 +2024-11-23 02:36:15.207092: Pseudo dice [0.8598] +2024-11-23 02:36:15.207166: Epoch time: 18.88 s +2024-11-23 02:36:16.117063: +2024-11-23 02:36:16.117289: Epoch 7414 +2024-11-23 02:36:16.117398: Current learning rate: 0.00095 +2024-11-23 02:36:35.827509: train_loss -0.8198 +2024-11-23 02:36:35.827727: val_loss -0.8052 +2024-11-23 02:36:35.827802: Pseudo dice [0.8458] +2024-11-23 02:36:35.827881: Epoch time: 19.71 s +2024-11-23 02:36:36.744235: +2024-11-23 02:36:36.744461: Epoch 7415 +2024-11-23 02:36:36.744577: Current learning rate: 0.00095 +2024-11-23 02:36:55.105102: train_loss -0.8251 +2024-11-23 02:36:55.105319: val_loss -0.764 +2024-11-23 02:36:55.105395: Pseudo dice [0.8377] +2024-11-23 02:36:55.105469: Epoch time: 18.36 s +2024-11-23 02:36:56.019853: +2024-11-23 02:36:56.020073: Epoch 7416 +2024-11-23 02:36:56.020181: Current learning rate: 0.00095 +2024-11-23 02:37:13.827169: train_loss -0.8238 +2024-11-23 02:37:13.827404: val_loss -0.7703 +2024-11-23 02:37:13.827476: Pseudo dice [0.8544] +2024-11-23 02:37:13.827554: Epoch time: 17.81 s +2024-11-23 02:37:14.733188: +2024-11-23 02:37:14.733409: Epoch 7417 +2024-11-23 02:37:14.733519: Current learning rate: 0.00095 +2024-11-23 02:37:32.663254: train_loss -0.8256 +2024-11-23 02:37:32.663487: val_loss -0.792 +2024-11-23 02:37:32.663566: Pseudo dice [0.873] +2024-11-23 02:37:32.663644: Epoch time: 17.93 s +2024-11-23 02:37:33.574913: +2024-11-23 02:37:33.575156: Epoch 7418 +2024-11-23 02:37:33.575266: Current learning rate: 0.00095 +2024-11-23 02:37:52.394240: train_loss -0.8256 +2024-11-23 02:37:52.394499: val_loss -0.7923 +2024-11-23 02:37:52.394576: Pseudo dice [0.8471] +2024-11-23 02:37:52.394649: Epoch time: 18.82 s +2024-11-23 02:37:53.317216: +2024-11-23 02:37:53.317461: Epoch 7419 +2024-11-23 02:37:53.317570: Current learning rate: 0.00094 +2024-11-23 02:38:11.569210: train_loss -0.8239 +2024-11-23 02:38:11.569457: val_loss -0.7799 +2024-11-23 02:38:11.569532: Pseudo dice [0.8563] +2024-11-23 02:38:11.569616: Epoch time: 18.25 s +2024-11-23 02:38:12.479213: +2024-11-23 02:38:12.479468: Epoch 7420 +2024-11-23 02:38:12.479588: Current learning rate: 0.00094 +2024-11-23 02:38:31.298972: train_loss -0.8287 +2024-11-23 02:38:31.299210: val_loss -0.7782 +2024-11-23 02:38:31.299286: Pseudo dice [0.8502] +2024-11-23 02:38:31.299365: Epoch time: 18.82 s +2024-11-23 02:38:32.215615: +2024-11-23 02:38:32.215853: Epoch 7421 +2024-11-23 02:38:32.215969: Current learning rate: 0.00094 +2024-11-23 02:38:51.148424: train_loss -0.8229 +2024-11-23 02:38:51.148652: val_loss -0.7782 +2024-11-23 02:38:51.148728: Pseudo dice [0.8696] +2024-11-23 02:38:51.148803: Epoch time: 18.93 s +2024-11-23 02:38:52.171323: +2024-11-23 02:38:52.171546: Epoch 7422 +2024-11-23 02:38:52.171651: Current learning rate: 0.00094 +2024-11-23 02:39:10.219060: train_loss -0.8274 +2024-11-23 02:39:10.219355: val_loss -0.7607 +2024-11-23 02:39:10.219437: Pseudo dice [0.8493] +2024-11-23 02:39:10.219521: Epoch time: 18.04 s +2024-11-23 02:39:11.307344: +2024-11-23 02:39:11.307636: Epoch 7423 +2024-11-23 02:39:11.307752: Current learning rate: 0.00094 +2024-11-23 02:39:28.905290: train_loss -0.8247 +2024-11-23 02:39:28.905524: val_loss -0.8055 +2024-11-23 02:39:28.905602: Pseudo dice [0.8595] +2024-11-23 02:39:28.905680: Epoch time: 17.6 s +2024-11-23 02:39:29.874645: +2024-11-23 02:39:29.874860: Epoch 7424 +2024-11-23 02:39:29.874973: Current learning rate: 0.00094 +2024-11-23 02:39:48.198574: train_loss -0.8239 +2024-11-23 02:39:48.198792: val_loss -0.7738 +2024-11-23 02:39:48.198868: Pseudo dice [0.8529] +2024-11-23 02:39:48.199591: Epoch time: 18.32 s +2024-11-23 02:39:49.102959: +2024-11-23 02:39:49.103251: Epoch 7425 +2024-11-23 02:39:49.103363: Current learning rate: 0.00094 +2024-11-23 02:40:07.475152: train_loss -0.8294 +2024-11-23 02:40:07.475363: val_loss -0.7858 +2024-11-23 02:40:07.475436: Pseudo dice [0.8552] +2024-11-23 02:40:07.475507: Epoch time: 18.37 s +2024-11-23 02:40:08.390492: +2024-11-23 02:40:08.390706: Epoch 7426 +2024-11-23 02:40:08.390818: Current learning rate: 0.00093 +2024-11-23 02:40:25.754076: train_loss -0.8303 +2024-11-23 02:40:25.754334: val_loss -0.7847 +2024-11-23 02:40:25.754412: Pseudo dice [0.8515] +2024-11-23 02:40:25.754533: Epoch time: 17.36 s +2024-11-23 02:40:26.670696: +2024-11-23 02:40:26.670923: Epoch 7427 +2024-11-23 02:40:26.671041: Current learning rate: 0.00093 +2024-11-23 02:40:45.422102: train_loss -0.8285 +2024-11-23 02:40:45.422335: val_loss -0.7917 +2024-11-23 02:40:45.422416: Pseudo dice [0.8632] +2024-11-23 02:40:45.422496: Epoch time: 18.75 s +2024-11-23 02:40:46.340792: +2024-11-23 02:40:46.341027: Epoch 7428 +2024-11-23 02:40:46.341138: Current learning rate: 0.00093 +2024-11-23 02:41:04.094294: train_loss -0.8314 +2024-11-23 02:41:04.094506: val_loss -0.7817 +2024-11-23 02:41:04.094578: Pseudo dice [0.8598] +2024-11-23 02:41:04.094654: Epoch time: 17.75 s +2024-11-23 02:41:05.008281: +2024-11-23 02:41:05.008492: Epoch 7429 +2024-11-23 02:41:05.008604: Current learning rate: 0.00093 +2024-11-23 02:41:22.828547: train_loss -0.8247 +2024-11-23 02:41:22.828801: val_loss -0.7715 +2024-11-23 02:41:22.828874: Pseudo dice [0.8428] +2024-11-23 02:41:22.828955: Epoch time: 17.82 s +2024-11-23 02:41:24.124895: +2024-11-23 02:41:24.125160: Epoch 7430 +2024-11-23 02:41:24.125289: Current learning rate: 0.00093 +2024-11-23 02:41:41.844037: train_loss -0.8245 +2024-11-23 02:41:41.844284: val_loss -0.7957 +2024-11-23 02:41:41.844417: Pseudo dice [0.8604] +2024-11-23 02:41:41.844492: Epoch time: 17.72 s +2024-11-23 02:41:42.770279: +2024-11-23 02:41:42.770521: Epoch 7431 +2024-11-23 02:41:42.770631: Current learning rate: 0.00093 +2024-11-23 02:42:01.921661: train_loss -0.8241 +2024-11-23 02:42:01.921891: val_loss -0.7797 +2024-11-23 02:42:01.922006: Pseudo dice [0.8755] +2024-11-23 02:42:01.922087: Epoch time: 19.15 s +2024-11-23 02:42:02.834589: +2024-11-23 02:42:02.834816: Epoch 7432 +2024-11-23 02:42:02.834929: Current learning rate: 0.00092 +2024-11-23 02:42:21.490785: train_loss -0.8334 +2024-11-23 02:42:21.491033: val_loss -0.8001 +2024-11-23 02:42:21.491112: Pseudo dice [0.8744] +2024-11-23 02:42:21.491201: Epoch time: 18.66 s +2024-11-23 02:42:22.404397: +2024-11-23 02:42:22.404626: Epoch 7433 +2024-11-23 02:42:22.404742: Current learning rate: 0.00092 +2024-11-23 02:42:40.603351: train_loss -0.8311 +2024-11-23 02:42:40.603600: val_loss -0.7682 +2024-11-23 02:42:40.603678: Pseudo dice [0.8274] +2024-11-23 02:42:40.603757: Epoch time: 18.2 s +2024-11-23 02:42:41.521281: +2024-11-23 02:42:41.521508: Epoch 7434 +2024-11-23 02:42:41.521617: Current learning rate: 0.00092 +2024-11-23 02:43:00.681588: train_loss -0.83 +2024-11-23 02:43:00.681823: val_loss -0.7644 +2024-11-23 02:43:00.681897: Pseudo dice [0.8549] +2024-11-23 02:43:00.681973: Epoch time: 19.16 s +2024-11-23 02:43:01.627100: +2024-11-23 02:43:01.627320: Epoch 7435 +2024-11-23 02:43:01.627430: Current learning rate: 0.00092 +2024-11-23 02:43:20.886678: train_loss -0.8313 +2024-11-23 02:43:20.886883: val_loss -0.7743 +2024-11-23 02:43:20.886955: Pseudo dice [0.8435] +2024-11-23 02:43:20.887035: Epoch time: 19.26 s +2024-11-23 02:43:21.812732: +2024-11-23 02:43:21.812934: Epoch 7436 +2024-11-23 02:43:21.813045: Current learning rate: 0.00092 +2024-11-23 02:43:39.866548: train_loss -0.832 +2024-11-23 02:43:39.866789: val_loss -0.7764 +2024-11-23 02:43:39.866863: Pseudo dice [0.8487] +2024-11-23 02:43:39.866969: Epoch time: 18.05 s +2024-11-23 02:43:40.781943: +2024-11-23 02:43:40.782148: Epoch 7437 +2024-11-23 02:43:40.782257: Current learning rate: 0.00092 +2024-11-23 02:43:59.022205: train_loss -0.8278 +2024-11-23 02:43:59.022421: val_loss -0.7964 +2024-11-23 02:43:59.022497: Pseudo dice [0.8621] +2024-11-23 02:43:59.022572: Epoch time: 18.24 s +2024-11-23 02:43:59.936095: +2024-11-23 02:43:59.936328: Epoch 7438 +2024-11-23 02:43:59.936439: Current learning rate: 0.00092 +2024-11-23 02:44:18.413594: train_loss -0.8201 +2024-11-23 02:44:18.413812: val_loss -0.7973 +2024-11-23 02:44:18.413892: Pseudo dice [0.8686] +2024-11-23 02:44:18.413966: Epoch time: 18.48 s +2024-11-23 02:44:19.329345: +2024-11-23 02:44:19.329567: Epoch 7439 +2024-11-23 02:44:19.329675: Current learning rate: 0.00091 +2024-11-23 02:44:37.844491: train_loss -0.8293 +2024-11-23 02:44:37.844740: val_loss -0.7772 +2024-11-23 02:44:37.844817: Pseudo dice [0.8431] +2024-11-23 02:44:37.844894: Epoch time: 18.51 s +2024-11-23 02:44:38.753589: +2024-11-23 02:44:38.753794: Epoch 7440 +2024-11-23 02:44:38.753903: Current learning rate: 0.00091 +2024-11-23 02:44:56.358274: train_loss -0.8382 +2024-11-23 02:44:56.359517: val_loss -0.7818 +2024-11-23 02:44:56.359605: Pseudo dice [0.8601] +2024-11-23 02:44:56.359693: Epoch time: 17.61 s +2024-11-23 02:44:57.272685: +2024-11-23 02:44:57.272894: Epoch 7441 +2024-11-23 02:44:57.273020: Current learning rate: 0.00091 +2024-11-23 02:45:15.020471: train_loss -0.8248 +2024-11-23 02:45:15.020692: val_loss -0.7923 +2024-11-23 02:45:15.020767: Pseudo dice [0.8534] +2024-11-23 02:45:15.020840: Epoch time: 17.75 s +2024-11-23 02:45:15.936249: +2024-11-23 02:45:15.936462: Epoch 7442 +2024-11-23 02:45:15.936570: Current learning rate: 0.00091 +2024-11-23 02:45:34.323822: train_loss -0.8324 +2024-11-23 02:45:34.324121: val_loss -0.7862 +2024-11-23 02:45:34.324202: Pseudo dice [0.86] +2024-11-23 02:45:34.324278: Epoch time: 18.39 s +2024-11-23 02:45:35.237473: +2024-11-23 02:45:35.237714: Epoch 7443 +2024-11-23 02:45:35.237824: Current learning rate: 0.00091 +2024-11-23 02:45:53.186940: train_loss -0.8293 +2024-11-23 02:45:53.187232: val_loss -0.7862 +2024-11-23 02:45:53.187309: Pseudo dice [0.8551] +2024-11-23 02:45:53.187391: Epoch time: 17.95 s +2024-11-23 02:45:54.207813: +2024-11-23 02:45:54.208045: Epoch 7444 +2024-11-23 02:45:54.208156: Current learning rate: 0.00091 +2024-11-23 02:46:11.594939: train_loss -0.8285 +2024-11-23 02:46:11.595167: val_loss -0.7755 +2024-11-23 02:46:11.597418: Pseudo dice [0.8602] +2024-11-23 02:46:11.597543: Epoch time: 17.39 s +2024-11-23 02:46:12.739061: +2024-11-23 02:46:12.739285: Epoch 7445 +2024-11-23 02:46:12.739394: Current learning rate: 0.00091 +2024-11-23 02:46:30.810822: train_loss -0.8326 +2024-11-23 02:46:30.811037: val_loss -0.7722 +2024-11-23 02:46:30.811111: Pseudo dice [0.8377] +2024-11-23 02:46:30.811183: Epoch time: 18.07 s +2024-11-23 02:46:31.728862: +2024-11-23 02:46:31.729147: Epoch 7446 +2024-11-23 02:46:31.729256: Current learning rate: 0.0009 +2024-11-23 02:46:50.446621: train_loss -0.8289 +2024-11-23 02:46:50.446852: val_loss -0.7612 +2024-11-23 02:46:50.446933: Pseudo dice [0.846] +2024-11-23 02:46:50.447024: Epoch time: 18.72 s +2024-11-23 02:46:51.361285: +2024-11-23 02:46:51.361514: Epoch 7447 +2024-11-23 02:46:51.361625: Current learning rate: 0.0009 +2024-11-23 02:47:09.531016: train_loss -0.8259 +2024-11-23 02:47:09.531270: val_loss -0.7896 +2024-11-23 02:47:09.531347: Pseudo dice [0.8574] +2024-11-23 02:47:09.536671: Epoch time: 18.17 s +2024-11-23 02:47:10.452306: +2024-11-23 02:47:10.452517: Epoch 7448 +2024-11-23 02:47:10.452626: Current learning rate: 0.0009 +2024-11-23 02:47:28.295631: train_loss -0.8303 +2024-11-23 02:47:28.295851: val_loss -0.7702 +2024-11-23 02:47:28.295933: Pseudo dice [0.8314] +2024-11-23 02:47:28.296016: Epoch time: 17.84 s +2024-11-23 02:47:29.338647: +2024-11-23 02:47:29.338878: Epoch 7449 +2024-11-23 02:47:29.338989: Current learning rate: 0.0009 +2024-11-23 02:47:47.612219: train_loss -0.8291 +2024-11-23 02:47:47.612429: val_loss -0.7402 +2024-11-23 02:47:47.612507: Pseudo dice [0.8491] +2024-11-23 02:47:47.612583: Epoch time: 18.27 s +2024-11-23 02:47:48.852437: +2024-11-23 02:47:48.852643: Epoch 7450 +2024-11-23 02:47:48.863370: Current learning rate: 0.0009 +2024-11-23 02:48:07.438363: train_loss -0.8244 +2024-11-23 02:48:07.438589: val_loss -0.7733 +2024-11-23 02:48:07.438667: Pseudo dice [0.8419] +2024-11-23 02:48:07.438743: Epoch time: 18.59 s +2024-11-23 02:48:08.345269: +2024-11-23 02:48:08.345465: Epoch 7451 +2024-11-23 02:48:08.345572: Current learning rate: 0.0009 +2024-11-23 02:48:27.527886: train_loss -0.8261 +2024-11-23 02:48:27.528132: val_loss -0.784 +2024-11-23 02:48:27.528208: Pseudo dice [0.8543] +2024-11-23 02:48:27.528285: Epoch time: 19.18 s +2024-11-23 02:48:28.437129: +2024-11-23 02:48:28.437345: Epoch 7452 +2024-11-23 02:48:28.437455: Current learning rate: 0.0009 +2024-11-23 02:48:47.679956: train_loss -0.8288 +2024-11-23 02:48:47.680464: val_loss -0.7896 +2024-11-23 02:48:47.680567: Pseudo dice [0.8526] +2024-11-23 02:48:47.680643: Epoch time: 19.24 s +2024-11-23 02:48:48.592711: +2024-11-23 02:48:48.592937: Epoch 7453 +2024-11-23 02:48:48.593050: Current learning rate: 0.00089 +2024-11-23 02:49:06.711715: train_loss -0.8279 +2024-11-23 02:49:06.712223: val_loss -0.749 +2024-11-23 02:49:06.712324: Pseudo dice [0.8319] +2024-11-23 02:49:06.712405: Epoch time: 18.12 s +2024-11-23 02:49:07.620864: +2024-11-23 02:49:07.621096: Epoch 7454 +2024-11-23 02:49:07.621206: Current learning rate: 0.00089 +2024-11-23 02:49:24.888523: train_loss -0.8312 +2024-11-23 02:49:24.888829: val_loss -0.7571 +2024-11-23 02:49:24.888902: Pseudo dice [0.8517] +2024-11-23 02:49:24.888981: Epoch time: 17.27 s +2024-11-23 02:49:25.803707: +2024-11-23 02:49:25.803942: Epoch 7455 +2024-11-23 02:49:25.804056: Current learning rate: 0.00089 +2024-11-23 02:49:45.921242: train_loss -0.8315 +2024-11-23 02:49:45.921488: val_loss -0.8084 +2024-11-23 02:49:45.921567: Pseudo dice [0.8515] +2024-11-23 02:49:45.921658: Epoch time: 20.12 s +2024-11-23 02:49:46.832853: +2024-11-23 02:49:46.833089: Epoch 7456 +2024-11-23 02:49:46.833202: Current learning rate: 0.00089 +2024-11-23 02:50:05.404930: train_loss -0.8206 +2024-11-23 02:50:05.405153: val_loss -0.7971 +2024-11-23 02:50:05.405226: Pseudo dice [0.8698] +2024-11-23 02:50:05.405298: Epoch time: 18.57 s +2024-11-23 02:50:06.320280: +2024-11-23 02:50:06.320505: Epoch 7457 +2024-11-23 02:50:06.320621: Current learning rate: 0.00089 +2024-11-23 02:50:25.029412: train_loss -0.8204 +2024-11-23 02:50:25.029616: val_loss -0.7789 +2024-11-23 02:50:25.029686: Pseudo dice [0.8639] +2024-11-23 02:50:25.029757: Epoch time: 18.71 s +2024-11-23 02:50:25.984859: +2024-11-23 02:50:25.985100: Epoch 7458 +2024-11-23 02:50:25.985217: Current learning rate: 0.00089 +2024-11-23 02:50:44.785728: train_loss -0.823 +2024-11-23 02:50:44.786019: val_loss -0.7715 +2024-11-23 02:50:44.786114: Pseudo dice [0.8567] +2024-11-23 02:50:44.786193: Epoch time: 18.8 s +2024-11-23 02:50:45.702394: +2024-11-23 02:50:45.702607: Epoch 7459 +2024-11-23 02:50:45.702716: Current learning rate: 0.00089 +2024-11-23 02:51:04.285932: train_loss -0.8239 +2024-11-23 02:51:04.286189: val_loss -0.785 +2024-11-23 02:51:04.286265: Pseudo dice [0.8415] +2024-11-23 02:51:04.286349: Epoch time: 18.58 s +2024-11-23 02:51:05.202898: +2024-11-23 02:51:05.203182: Epoch 7460 +2024-11-23 02:51:05.203305: Current learning rate: 0.00088 +2024-11-23 02:51:24.591523: train_loss -0.8259 +2024-11-23 02:51:24.591733: val_loss -0.7648 +2024-11-23 02:51:24.591810: Pseudo dice [0.8552] +2024-11-23 02:51:24.591885: Epoch time: 19.39 s +2024-11-23 02:51:25.508121: +2024-11-23 02:51:25.508349: Epoch 7461 +2024-11-23 02:51:25.508461: Current learning rate: 0.00088 +2024-11-23 02:51:44.306187: train_loss -0.8268 +2024-11-23 02:51:44.306401: val_loss -0.7916 +2024-11-23 02:51:44.306476: Pseudo dice [0.8633] +2024-11-23 02:51:44.306548: Epoch time: 18.8 s +2024-11-23 02:51:45.412665: +2024-11-23 02:51:45.412875: Epoch 7462 +2024-11-23 02:51:45.412997: Current learning rate: 0.00088 +2024-11-23 02:52:03.868234: train_loss -0.8236 +2024-11-23 02:52:03.868465: val_loss -0.7878 +2024-11-23 02:52:03.868538: Pseudo dice [0.8586] +2024-11-23 02:52:03.875880: Epoch time: 18.46 s +2024-11-23 02:52:04.852088: +2024-11-23 02:52:04.852473: Epoch 7463 +2024-11-23 02:52:04.852597: Current learning rate: 0.00088 +2024-11-23 02:52:23.570001: train_loss -0.8199 +2024-11-23 02:52:23.570333: val_loss -0.76 +2024-11-23 02:52:23.570411: Pseudo dice [0.8303] +2024-11-23 02:52:23.570489: Epoch time: 18.72 s +2024-11-23 02:52:24.930740: +2024-11-23 02:52:24.930974: Epoch 7464 +2024-11-23 02:52:24.931089: Current learning rate: 0.00088 +2024-11-23 02:52:43.832855: train_loss -0.8265 +2024-11-23 02:52:43.833083: val_loss -0.7846 +2024-11-23 02:52:43.833160: Pseudo dice [0.8524] +2024-11-23 02:52:43.833242: Epoch time: 18.9 s +2024-11-23 02:52:44.750140: +2024-11-23 02:52:44.750513: Epoch 7465 +2024-11-23 02:52:44.750627: Current learning rate: 0.00088 +2024-11-23 02:53:03.045934: train_loss -0.8249 +2024-11-23 02:53:03.046169: val_loss -0.7913 +2024-11-23 02:53:03.046242: Pseudo dice [0.8615] +2024-11-23 02:53:03.046317: Epoch time: 18.3 s +2024-11-23 02:53:03.959249: +2024-11-23 02:53:03.959453: Epoch 7466 +2024-11-23 02:53:03.959559: Current learning rate: 0.00087 +2024-11-23 02:53:22.324802: train_loss -0.8267 +2024-11-23 02:53:22.325075: val_loss -0.7807 +2024-11-23 02:53:22.325156: Pseudo dice [0.8663] +2024-11-23 02:53:22.325244: Epoch time: 18.37 s +2024-11-23 02:53:23.253339: +2024-11-23 02:53:23.253576: Epoch 7467 +2024-11-23 02:53:23.253688: Current learning rate: 0.00087 +2024-11-23 02:53:40.891763: train_loss -0.8288 +2024-11-23 02:53:40.891978: val_loss -0.7859 +2024-11-23 02:53:40.892059: Pseudo dice [0.8577] +2024-11-23 02:53:40.892131: Epoch time: 17.64 s +2024-11-23 02:53:41.803742: +2024-11-23 02:53:41.803968: Epoch 7468 +2024-11-23 02:53:41.804083: Current learning rate: 0.00087 +2024-11-23 02:54:00.734911: train_loss -0.8235 +2024-11-23 02:54:00.735142: val_loss -0.7847 +2024-11-23 02:54:00.735214: Pseudo dice [0.8514] +2024-11-23 02:54:00.735288: Epoch time: 18.93 s +2024-11-23 02:54:01.649852: +2024-11-23 02:54:01.650101: Epoch 7469 +2024-11-23 02:54:01.650221: Current learning rate: 0.00087 +2024-11-23 02:54:20.406572: train_loss -0.8238 +2024-11-23 02:54:20.406785: val_loss -0.7767 +2024-11-23 02:54:20.406861: Pseudo dice [0.8557] +2024-11-23 02:54:20.406935: Epoch time: 18.76 s +2024-11-23 02:54:21.325485: +2024-11-23 02:54:21.325739: Epoch 7470 +2024-11-23 02:54:21.325852: Current learning rate: 0.00087 +2024-11-23 02:54:39.595435: train_loss -0.8291 +2024-11-23 02:54:39.595728: val_loss -0.8031 +2024-11-23 02:54:39.595805: Pseudo dice [0.8613] +2024-11-23 02:54:39.595885: Epoch time: 18.27 s +2024-11-23 02:54:40.513262: +2024-11-23 02:54:40.513513: Epoch 7471 +2024-11-23 02:54:40.513635: Current learning rate: 0.00087 +2024-11-23 02:54:58.182259: train_loss -0.8241 +2024-11-23 02:54:58.182474: val_loss -0.7409 +2024-11-23 02:54:58.182548: Pseudo dice [0.8364] +2024-11-23 02:54:58.182621: Epoch time: 17.67 s +2024-11-23 02:54:59.084018: +2024-11-23 02:54:59.084242: Epoch 7472 +2024-11-23 02:54:59.084350: Current learning rate: 0.00087 +2024-11-23 02:55:17.187762: train_loss -0.8258 +2024-11-23 02:55:17.187999: val_loss -0.7716 +2024-11-23 02:55:17.188073: Pseudo dice [0.8531] +2024-11-23 02:55:17.188309: Epoch time: 18.1 s +2024-11-23 02:55:18.102776: +2024-11-23 02:55:18.102986: Epoch 7473 +2024-11-23 02:55:18.103100: Current learning rate: 0.00086 +2024-11-23 02:55:36.544749: train_loss -0.8236 +2024-11-23 02:55:36.544964: val_loss -0.7825 +2024-11-23 02:55:36.545043: Pseudo dice [0.8559] +2024-11-23 02:55:36.545116: Epoch time: 18.44 s +2024-11-23 02:55:37.451685: +2024-11-23 02:55:37.451880: Epoch 7474 +2024-11-23 02:55:37.451985: Current learning rate: 0.00086 +2024-11-23 02:55:56.459661: train_loss -0.8261 +2024-11-23 02:55:56.459900: val_loss -0.7699 +2024-11-23 02:55:56.459972: Pseudo dice [0.8578] +2024-11-23 02:55:56.462348: Epoch time: 19.01 s +2024-11-23 02:55:57.765706: +2024-11-23 02:55:57.765929: Epoch 7475 +2024-11-23 02:55:57.766043: Current learning rate: 0.00086 +2024-11-23 02:56:15.970021: train_loss -0.8278 +2024-11-23 02:56:15.973620: val_loss -0.7566 +2024-11-23 02:56:15.973762: Pseudo dice [0.8497] +2024-11-23 02:56:15.973848: Epoch time: 18.21 s +2024-11-23 02:56:17.006989: +2024-11-23 02:56:17.007232: Epoch 7476 +2024-11-23 02:56:17.007343: Current learning rate: 0.00086 +2024-11-23 02:56:36.159693: train_loss -0.8236 +2024-11-23 02:56:36.159909: val_loss -0.7791 +2024-11-23 02:56:36.159990: Pseudo dice [0.8481] +2024-11-23 02:56:36.160072: Epoch time: 19.15 s +2024-11-23 02:56:37.066622: +2024-11-23 02:56:37.066861: Epoch 7477 +2024-11-23 02:56:37.066973: Current learning rate: 0.00086 +2024-11-23 02:56:56.230510: train_loss -0.82 +2024-11-23 02:56:56.230735: val_loss -0.7767 +2024-11-23 02:56:56.230835: Pseudo dice [0.8673] +2024-11-23 02:56:56.230919: Epoch time: 19.16 s +2024-11-23 02:56:57.152361: +2024-11-23 02:56:57.152582: Epoch 7478 +2024-11-23 02:56:57.152722: Current learning rate: 0.00086 +2024-11-23 02:57:15.264843: train_loss -0.8174 +2024-11-23 02:57:15.265111: val_loss -0.7858 +2024-11-23 02:57:15.265195: Pseudo dice [0.8429] +2024-11-23 02:57:15.265280: Epoch time: 18.11 s +2024-11-23 02:57:16.181454: +2024-11-23 02:57:16.181690: Epoch 7479 +2024-11-23 02:57:16.181802: Current learning rate: 0.00086 +2024-11-23 02:57:33.860999: train_loss -0.8267 +2024-11-23 02:57:33.861209: val_loss -0.799 +2024-11-23 02:57:33.861285: Pseudo dice [0.8503] +2024-11-23 02:57:33.861360: Epoch time: 17.68 s +2024-11-23 02:57:34.789945: +2024-11-23 02:57:34.790171: Epoch 7480 +2024-11-23 02:57:34.790279: Current learning rate: 0.00085 +2024-11-23 02:57:52.536037: train_loss -0.8266 +2024-11-23 02:57:52.536282: val_loss -0.8011 +2024-11-23 02:57:52.536359: Pseudo dice [0.8599] +2024-11-23 02:57:52.536435: Epoch time: 17.75 s +2024-11-23 02:57:53.463568: +2024-11-23 02:57:53.463791: Epoch 7481 +2024-11-23 02:57:53.463898: Current learning rate: 0.00085 +2024-11-23 02:58:11.791092: train_loss -0.8324 +2024-11-23 02:58:11.791345: val_loss -0.7809 +2024-11-23 02:58:11.791425: Pseudo dice [0.846] +2024-11-23 02:58:11.791542: Epoch time: 18.33 s +2024-11-23 02:58:12.709278: +2024-11-23 02:58:12.709538: Epoch 7482 +2024-11-23 02:58:12.709646: Current learning rate: 0.00085 +2024-11-23 02:58:31.342293: train_loss -0.8292 +2024-11-23 02:58:31.342519: val_loss -0.7844 +2024-11-23 02:58:31.347759: Pseudo dice [0.8555] +2024-11-23 02:58:31.347896: Epoch time: 18.63 s +2024-11-23 02:58:32.425580: +2024-11-23 02:58:32.425800: Epoch 7483 +2024-11-23 02:58:32.425911: Current learning rate: 0.00085 +2024-11-23 02:58:50.578215: train_loss -0.831 +2024-11-23 02:58:50.578419: val_loss -0.7855 +2024-11-23 02:58:50.578492: Pseudo dice [0.8618] +2024-11-23 02:58:50.578565: Epoch time: 18.15 s +2024-11-23 02:58:51.557353: +2024-11-23 02:58:51.557622: Epoch 7484 +2024-11-23 02:58:51.557733: Current learning rate: 0.00085 +2024-11-23 02:59:10.450907: train_loss -0.8333 +2024-11-23 02:59:10.451132: val_loss -0.7883 +2024-11-23 02:59:10.451207: Pseudo dice [0.8679] +2024-11-23 02:59:10.451281: Epoch time: 18.89 s +2024-11-23 02:59:11.353666: +2024-11-23 02:59:11.353888: Epoch 7485 +2024-11-23 02:59:11.354008: Current learning rate: 0.00085 +2024-11-23 02:59:30.030686: train_loss -0.8323 +2024-11-23 02:59:30.030935: val_loss -0.7827 +2024-11-23 02:59:30.031017: Pseudo dice [0.8579] +2024-11-23 02:59:30.031095: Epoch time: 18.68 s +2024-11-23 02:59:30.937316: +2024-11-23 02:59:30.937541: Epoch 7486 +2024-11-23 02:59:30.937651: Current learning rate: 0.00085 +2024-11-23 02:59:49.131040: train_loss -0.8361 +2024-11-23 02:59:49.131316: val_loss -0.8011 +2024-11-23 02:59:49.131395: Pseudo dice [0.8614] +2024-11-23 02:59:49.131469: Epoch time: 18.19 s +2024-11-23 02:59:50.419879: +2024-11-23 02:59:50.420102: Epoch 7487 +2024-11-23 02:59:50.420211: Current learning rate: 0.00084 +2024-11-23 03:00:09.388974: train_loss -0.8376 +2024-11-23 03:00:09.389492: val_loss -0.8015 +2024-11-23 03:00:09.389587: Pseudo dice [0.8555] +2024-11-23 03:00:09.389660: Epoch time: 18.97 s +2024-11-23 03:00:10.296875: +2024-11-23 03:00:10.297121: Epoch 7488 +2024-11-23 03:00:10.348908: Current learning rate: 0.00084 +2024-11-23 03:00:28.531171: train_loss -0.8234 +2024-11-23 03:00:28.531493: val_loss -0.7665 +2024-11-23 03:00:28.531571: Pseudo dice [0.8497] +2024-11-23 03:00:28.531645: Epoch time: 18.24 s +2024-11-23 03:00:29.454590: +2024-11-23 03:00:29.454867: Epoch 7489 +2024-11-23 03:00:29.454985: Current learning rate: 0.00084 +2024-11-23 03:00:48.185845: train_loss -0.828 +2024-11-23 03:00:48.186072: val_loss -0.806 +2024-11-23 03:00:48.186153: Pseudo dice [0.8611] +2024-11-23 03:00:48.186231: Epoch time: 18.73 s +2024-11-23 03:00:49.096719: +2024-11-23 03:00:49.096955: Epoch 7490 +2024-11-23 03:00:49.097073: Current learning rate: 0.00084 +2024-11-23 03:01:07.444049: train_loss -0.8249 +2024-11-23 03:01:07.444307: val_loss -0.7796 +2024-11-23 03:01:07.444389: Pseudo dice [0.8575] +2024-11-23 03:01:07.444466: Epoch time: 18.35 s +2024-11-23 03:01:08.357816: +2024-11-23 03:01:08.358039: Epoch 7491 +2024-11-23 03:01:08.358149: Current learning rate: 0.00084 +2024-11-23 03:01:26.975728: train_loss -0.8327 +2024-11-23 03:01:26.976001: val_loss -0.7905 +2024-11-23 03:01:26.976080: Pseudo dice [0.8751] +2024-11-23 03:01:26.976157: Epoch time: 18.62 s +2024-11-23 03:01:28.042686: +2024-11-23 03:01:28.042955: Epoch 7492 +2024-11-23 03:01:28.043068: Current learning rate: 0.00084 +2024-11-23 03:01:46.975733: train_loss -0.828 +2024-11-23 03:01:46.975974: val_loss -0.7742 +2024-11-23 03:01:46.976061: Pseudo dice [0.8625] +2024-11-23 03:01:46.976136: Epoch time: 18.93 s +2024-11-23 03:01:47.894224: +2024-11-23 03:01:47.894446: Epoch 7493 +2024-11-23 03:01:47.894559: Current learning rate: 0.00084 +2024-11-23 03:02:06.138880: train_loss -0.8289 +2024-11-23 03:02:06.139124: val_loss -0.7784 +2024-11-23 03:02:06.139201: Pseudo dice [0.8481] +2024-11-23 03:02:06.139281: Epoch time: 18.25 s +2024-11-23 03:02:07.041155: +2024-11-23 03:02:07.041395: Epoch 7494 +2024-11-23 03:02:07.041507: Current learning rate: 0.00083 +2024-11-23 03:02:25.392689: train_loss -0.8299 +2024-11-23 03:02:25.392922: val_loss -0.7581 +2024-11-23 03:02:25.393007: Pseudo dice [0.8469] +2024-11-23 03:02:25.393084: Epoch time: 18.35 s +2024-11-23 03:02:26.313593: +2024-11-23 03:02:26.313817: Epoch 7495 +2024-11-23 03:02:26.313930: Current learning rate: 0.00083 +2024-11-23 03:02:45.313792: train_loss -0.8304 +2024-11-23 03:02:45.314029: val_loss -0.7957 +2024-11-23 03:02:45.314105: Pseudo dice [0.8502] +2024-11-23 03:02:45.314180: Epoch time: 19.0 s +2024-11-23 03:02:46.335825: +2024-11-23 03:02:46.336054: Epoch 7496 +2024-11-23 03:02:46.336168: Current learning rate: 0.00083 +2024-11-23 03:03:04.429189: train_loss -0.8307 +2024-11-23 03:03:04.429418: val_loss -0.7588 +2024-11-23 03:03:04.429493: Pseudo dice [0.8521] +2024-11-23 03:03:04.431716: Epoch time: 18.09 s +2024-11-23 03:03:05.417549: +2024-11-23 03:03:05.417774: Epoch 7497 +2024-11-23 03:03:05.417885: Current learning rate: 0.00083 +2024-11-23 03:03:23.412476: train_loss -0.8284 +2024-11-23 03:03:23.412727: val_loss -0.7923 +2024-11-23 03:03:23.412803: Pseudo dice [0.8614] +2024-11-23 03:03:23.412884: Epoch time: 18.0 s +2024-11-23 03:03:24.743689: +2024-11-23 03:03:24.743916: Epoch 7498 +2024-11-23 03:03:24.744033: Current learning rate: 0.00083 +2024-11-23 03:03:43.424218: train_loss -0.8207 +2024-11-23 03:03:43.424437: val_loss -0.7892 +2024-11-23 03:03:43.424512: Pseudo dice [0.8401] +2024-11-23 03:03:43.424668: Epoch time: 18.68 s +2024-11-23 03:03:44.426566: +2024-11-23 03:03:44.426788: Epoch 7499 +2024-11-23 03:03:44.426905: Current learning rate: 0.00083 +2024-11-23 03:04:03.021153: train_loss -0.822 +2024-11-23 03:04:03.021360: val_loss -0.7856 +2024-11-23 03:04:03.021436: Pseudo dice [0.867] +2024-11-23 03:04:03.021508: Epoch time: 18.6 s +2024-11-23 03:04:04.269251: +2024-11-23 03:04:04.269470: Epoch 7500 +2024-11-23 03:04:04.269583: Current learning rate: 0.00082 +2024-11-23 03:04:23.005160: train_loss -0.8305 +2024-11-23 03:04:23.005416: val_loss -0.7486 +2024-11-23 03:04:23.005493: Pseudo dice [0.8416] +2024-11-23 03:04:23.005576: Epoch time: 18.74 s +2024-11-23 03:04:23.991527: +2024-11-23 03:04:23.991759: Epoch 7501 +2024-11-23 03:04:23.991877: Current learning rate: 0.00082 +2024-11-23 03:04:42.062366: train_loss -0.827 +2024-11-23 03:04:42.062590: val_loss -0.7587 +2024-11-23 03:04:42.062666: Pseudo dice [0.8479] +2024-11-23 03:04:42.062741: Epoch time: 18.07 s +2024-11-23 03:04:42.967385: +2024-11-23 03:04:42.967595: Epoch 7502 +2024-11-23 03:04:42.967700: Current learning rate: 0.00082 +2024-11-23 03:05:01.295216: train_loss -0.8296 +2024-11-23 03:05:01.295492: val_loss -0.7922 +2024-11-23 03:05:01.295571: Pseudo dice [0.852] +2024-11-23 03:05:01.295645: Epoch time: 18.33 s +2024-11-23 03:05:02.240238: +2024-11-23 03:05:02.240504: Epoch 7503 +2024-11-23 03:05:02.240619: Current learning rate: 0.00082 +2024-11-23 03:05:20.241198: train_loss -0.8335 +2024-11-23 03:05:20.241438: val_loss -0.7692 +2024-11-23 03:05:20.241522: Pseudo dice [0.8495] +2024-11-23 03:05:20.241601: Epoch time: 18.0 s +2024-11-23 03:05:21.155868: +2024-11-23 03:05:21.156103: Epoch 7504 +2024-11-23 03:05:21.156214: Current learning rate: 0.00082 +2024-11-23 03:05:39.819020: train_loss -0.824 +2024-11-23 03:05:39.819271: val_loss -0.7969 +2024-11-23 03:05:39.819350: Pseudo dice [0.8718] +2024-11-23 03:05:39.819429: Epoch time: 18.66 s +2024-11-23 03:05:40.907536: +2024-11-23 03:05:40.907745: Epoch 7505 +2024-11-23 03:05:40.907855: Current learning rate: 0.00082 +2024-11-23 03:05:59.116689: train_loss -0.8325 +2024-11-23 03:05:59.116912: val_loss -0.7882 +2024-11-23 03:05:59.116999: Pseudo dice [0.8524] +2024-11-23 03:05:59.117078: Epoch time: 18.21 s +2024-11-23 03:06:00.047843: +2024-11-23 03:06:00.048044: Epoch 7506 +2024-11-23 03:06:00.048151: Current learning rate: 0.00082 +2024-11-23 03:06:18.925436: train_loss -0.8242 +2024-11-23 03:06:18.925656: val_loss -0.7759 +2024-11-23 03:06:18.925730: Pseudo dice [0.8491] +2024-11-23 03:06:18.925804: Epoch time: 18.88 s +2024-11-23 03:06:19.838085: +2024-11-23 03:06:19.838308: Epoch 7507 +2024-11-23 03:06:19.838413: Current learning rate: 0.00081 +2024-11-23 03:06:38.469064: train_loss -0.8301 +2024-11-23 03:06:38.469357: val_loss -0.7995 +2024-11-23 03:06:38.469446: Pseudo dice [0.8547] +2024-11-23 03:06:38.469527: Epoch time: 18.63 s +2024-11-23 03:06:39.394656: +2024-11-23 03:06:39.394850: Epoch 7508 +2024-11-23 03:06:39.394955: Current learning rate: 0.00081 +2024-11-23 03:06:58.093654: train_loss -0.8297 +2024-11-23 03:06:58.093906: val_loss -0.779 +2024-11-23 03:06:58.093983: Pseudo dice [0.8515] +2024-11-23 03:06:58.094069: Epoch time: 18.7 s +2024-11-23 03:06:59.005819: +2024-11-23 03:06:59.006042: Epoch 7509 +2024-11-23 03:06:59.006151: Current learning rate: 0.00081 +2024-11-23 03:07:17.664956: train_loss -0.8275 +2024-11-23 03:07:17.665211: val_loss -0.7624 +2024-11-23 03:07:17.665287: Pseudo dice [0.8522] +2024-11-23 03:07:17.665363: Epoch time: 18.66 s +2024-11-23 03:07:18.959486: +2024-11-23 03:07:18.959704: Epoch 7510 +2024-11-23 03:07:18.959821: Current learning rate: 0.00081 +2024-11-23 03:07:38.128187: train_loss -0.8251 +2024-11-23 03:07:38.128417: val_loss -0.7761 +2024-11-23 03:07:38.128501: Pseudo dice [0.845] +2024-11-23 03:07:38.128572: Epoch time: 19.17 s +2024-11-23 03:07:39.031949: +2024-11-23 03:07:39.032162: Epoch 7511 +2024-11-23 03:07:39.032269: Current learning rate: 0.00081 +2024-11-23 03:07:56.740788: train_loss -0.8313 +2024-11-23 03:07:56.741031: val_loss -0.7886 +2024-11-23 03:07:56.741111: Pseudo dice [0.852] +2024-11-23 03:07:56.741191: Epoch time: 17.71 s +2024-11-23 03:07:57.656388: +2024-11-23 03:07:57.656606: Epoch 7512 +2024-11-23 03:07:57.656717: Current learning rate: 0.00081 +2024-11-23 03:08:15.716845: train_loss -0.8277 +2024-11-23 03:08:15.717057: val_loss -0.7807 +2024-11-23 03:08:15.717128: Pseudo dice [0.8622] +2024-11-23 03:08:15.717198: Epoch time: 18.06 s +2024-11-23 03:08:16.639339: +2024-11-23 03:08:16.639575: Epoch 7513 +2024-11-23 03:08:16.639688: Current learning rate: 0.00081 +2024-11-23 03:08:35.906906: train_loss -0.8284 +2024-11-23 03:08:35.907133: val_loss -0.7861 +2024-11-23 03:08:35.907206: Pseudo dice [0.8485] +2024-11-23 03:08:35.907278: Epoch time: 19.27 s +2024-11-23 03:08:36.895674: +2024-11-23 03:08:36.895907: Epoch 7514 +2024-11-23 03:08:36.896022: Current learning rate: 0.0008 +2024-11-23 03:08:54.996540: train_loss -0.8343 +2024-11-23 03:08:54.996762: val_loss -0.7916 +2024-11-23 03:08:54.996840: Pseudo dice [0.8562] +2024-11-23 03:08:54.996919: Epoch time: 18.1 s +2024-11-23 03:08:55.925226: +2024-11-23 03:08:55.925449: Epoch 7515 +2024-11-23 03:08:55.925554: Current learning rate: 0.0008 +2024-11-23 03:09:14.729644: train_loss -0.822 +2024-11-23 03:09:14.729867: val_loss -0.7618 +2024-11-23 03:09:14.729939: Pseudo dice [0.8439] +2024-11-23 03:09:14.730024: Epoch time: 18.81 s +2024-11-23 03:09:15.645852: +2024-11-23 03:09:15.646094: Epoch 7516 +2024-11-23 03:09:15.646205: Current learning rate: 0.0008 +2024-11-23 03:09:33.204872: train_loss -0.8277 +2024-11-23 03:09:33.205091: val_loss -0.7843 +2024-11-23 03:09:33.205163: Pseudo dice [0.868] +2024-11-23 03:09:33.205239: Epoch time: 17.56 s +2024-11-23 03:09:34.132468: +2024-11-23 03:09:34.132676: Epoch 7517 +2024-11-23 03:09:34.132790: Current learning rate: 0.0008 +2024-11-23 03:09:53.281990: train_loss -0.8224 +2024-11-23 03:09:53.282239: val_loss -0.7669 +2024-11-23 03:09:53.282315: Pseudo dice [0.8555] +2024-11-23 03:09:53.282389: Epoch time: 19.15 s +2024-11-23 03:09:54.195661: +2024-11-23 03:09:54.195878: Epoch 7518 +2024-11-23 03:09:54.195986: Current learning rate: 0.0008 +2024-11-23 03:10:12.813508: train_loss -0.8333 +2024-11-23 03:10:12.813729: val_loss -0.7887 +2024-11-23 03:10:12.813804: Pseudo dice [0.8664] +2024-11-23 03:10:12.813904: Epoch time: 18.62 s +2024-11-23 03:10:13.816454: +2024-11-23 03:10:13.816694: Epoch 7519 +2024-11-23 03:10:13.816808: Current learning rate: 0.0008 +2024-11-23 03:10:32.791126: train_loss -0.8309 +2024-11-23 03:10:32.791386: val_loss -0.7728 +2024-11-23 03:10:32.791518: Pseudo dice [0.8619] +2024-11-23 03:10:32.791600: Epoch time: 18.98 s +2024-11-23 03:10:33.705726: +2024-11-23 03:10:33.706018: Epoch 7520 +2024-11-23 03:10:33.706129: Current learning rate: 0.00079 +2024-11-23 03:10:52.703541: train_loss -0.8293 +2024-11-23 03:10:52.703815: val_loss -0.7628 +2024-11-23 03:10:52.703892: Pseudo dice [0.8578] +2024-11-23 03:10:52.703965: Epoch time: 19.0 s +2024-11-23 03:10:53.650803: +2024-11-23 03:10:53.651220: Epoch 7521 +2024-11-23 03:10:53.651352: Current learning rate: 0.00079 +2024-11-23 03:11:13.451470: train_loss -0.8279 +2024-11-23 03:11:13.453810: val_loss -0.7775 +2024-11-23 03:11:13.454044: Pseudo dice [0.8669] +2024-11-23 03:11:13.454127: Epoch time: 19.8 s +2024-11-23 03:11:14.428446: +2024-11-23 03:11:14.428672: Epoch 7522 +2024-11-23 03:11:14.428780: Current learning rate: 0.00079 +2024-11-23 03:11:32.491828: train_loss -0.8232 +2024-11-23 03:11:32.492058: val_loss -0.7698 +2024-11-23 03:11:32.492133: Pseudo dice [0.838] +2024-11-23 03:11:32.492209: Epoch time: 18.06 s +2024-11-23 03:11:33.408573: +2024-11-23 03:11:33.408819: Epoch 7523 +2024-11-23 03:11:33.408938: Current learning rate: 0.00079 +2024-11-23 03:11:51.714454: train_loss -0.8268 +2024-11-23 03:11:51.719885: val_loss -0.7857 +2024-11-23 03:11:51.720001: Pseudo dice [0.8584] +2024-11-23 03:11:51.720088: Epoch time: 18.31 s +2024-11-23 03:11:52.709105: +2024-11-23 03:11:52.709332: Epoch 7524 +2024-11-23 03:11:52.709448: Current learning rate: 0.00079 +2024-11-23 03:12:10.978148: train_loss -0.8322 +2024-11-23 03:12:10.980525: val_loss -0.7875 +2024-11-23 03:12:10.980639: Pseudo dice [0.8515] +2024-11-23 03:12:10.980892: Epoch time: 18.27 s +2024-11-23 03:12:11.897211: +2024-11-23 03:12:11.897417: Epoch 7525 +2024-11-23 03:12:11.897535: Current learning rate: 0.00079 +2024-11-23 03:12:30.738795: train_loss -0.8264 +2024-11-23 03:12:30.739891: val_loss -0.7954 +2024-11-23 03:12:30.740006: Pseudo dice [0.8794] +2024-11-23 03:12:30.740086: Epoch time: 18.84 s +2024-11-23 03:12:31.741776: +2024-11-23 03:12:31.741999: Epoch 7526 +2024-11-23 03:12:31.742112: Current learning rate: 0.00079 +2024-11-23 03:12:50.478192: train_loss -0.8271 +2024-11-23 03:12:50.478464: val_loss -0.7669 +2024-11-23 03:12:50.478541: Pseudo dice [0.8513] +2024-11-23 03:12:50.478615: Epoch time: 18.74 s +2024-11-23 03:12:51.435147: +2024-11-23 03:12:51.435348: Epoch 7527 +2024-11-23 03:12:51.435457: Current learning rate: 0.00078 +2024-11-23 03:13:09.128340: train_loss -0.8309 +2024-11-23 03:13:09.128593: val_loss -0.7639 +2024-11-23 03:13:09.128688: Pseudo dice [0.8586] +2024-11-23 03:13:09.128775: Epoch time: 17.69 s +2024-11-23 03:13:10.043287: +2024-11-23 03:13:10.043571: Epoch 7528 +2024-11-23 03:13:10.043686: Current learning rate: 0.00078 +2024-11-23 03:13:27.982445: train_loss -0.8324 +2024-11-23 03:13:27.982661: val_loss -0.7801 +2024-11-23 03:13:27.982734: Pseudo dice [0.8605] +2024-11-23 03:13:27.982806: Epoch time: 17.94 s +2024-11-23 03:13:28.924126: +2024-11-23 03:13:28.924345: Epoch 7529 +2024-11-23 03:13:28.924453: Current learning rate: 0.00078 +2024-11-23 03:13:46.925916: train_loss -0.8323 +2024-11-23 03:13:46.926143: val_loss -0.7862 +2024-11-23 03:13:46.926214: Pseudo dice [0.8585] +2024-11-23 03:13:46.926290: Epoch time: 18.0 s +2024-11-23 03:13:47.858468: +2024-11-23 03:13:47.858701: Epoch 7530 +2024-11-23 03:13:47.858807: Current learning rate: 0.00078 +2024-11-23 03:14:06.167922: train_loss -0.8378 +2024-11-23 03:14:06.168144: val_loss -0.7848 +2024-11-23 03:14:06.168222: Pseudo dice [0.8663] +2024-11-23 03:14:06.168297: Epoch time: 18.31 s +2024-11-23 03:14:07.078675: +2024-11-23 03:14:07.078886: Epoch 7531 +2024-11-23 03:14:07.079002: Current learning rate: 0.00078 +2024-11-23 03:14:25.463648: train_loss -0.8284 +2024-11-23 03:14:25.463910: val_loss -0.7578 +2024-11-23 03:14:25.464011: Pseudo dice [0.8537] +2024-11-23 03:14:25.464110: Epoch time: 18.39 s +2024-11-23 03:14:26.377988: +2024-11-23 03:14:26.378201: Epoch 7532 +2024-11-23 03:14:26.378309: Current learning rate: 0.00078 +2024-11-23 03:14:44.326167: train_loss -0.8281 +2024-11-23 03:14:44.326401: val_loss -0.7646 +2024-11-23 03:14:44.326477: Pseudo dice [0.8553] +2024-11-23 03:14:44.326551: Epoch time: 17.95 s +2024-11-23 03:14:45.566370: +2024-11-23 03:14:45.566575: Epoch 7533 +2024-11-23 03:14:45.566685: Current learning rate: 0.00078 +2024-11-23 03:15:03.229404: train_loss -0.8307 +2024-11-23 03:15:03.229632: val_loss -0.7856 +2024-11-23 03:15:03.229712: Pseudo dice [0.8493] +2024-11-23 03:15:03.229788: Epoch time: 17.66 s +2024-11-23 03:15:04.138619: +2024-11-23 03:15:04.138839: Epoch 7534 +2024-11-23 03:15:04.138949: Current learning rate: 0.00077 +2024-11-23 03:15:23.076757: train_loss -0.8356 +2024-11-23 03:15:23.077026: val_loss -0.7758 +2024-11-23 03:15:23.077106: Pseudo dice [0.8596] +2024-11-23 03:15:23.077186: Epoch time: 18.94 s +2024-11-23 03:15:24.002987: +2024-11-23 03:15:24.003237: Epoch 7535 +2024-11-23 03:15:24.003350: Current learning rate: 0.00077 +2024-11-23 03:15:43.174317: train_loss -0.827 +2024-11-23 03:15:43.175291: val_loss -0.7985 +2024-11-23 03:15:43.175379: Pseudo dice [0.8669] +2024-11-23 03:15:43.175455: Epoch time: 19.17 s +2024-11-23 03:15:44.104807: +2024-11-23 03:15:44.105026: Epoch 7536 +2024-11-23 03:15:44.105142: Current learning rate: 0.00077 +2024-11-23 03:16:02.312317: train_loss -0.8353 +2024-11-23 03:16:02.312546: val_loss -0.7745 +2024-11-23 03:16:02.312620: Pseudo dice [0.8551] +2024-11-23 03:16:02.312694: Epoch time: 18.21 s +2024-11-23 03:16:03.316016: +2024-11-23 03:16:03.316228: Epoch 7537 +2024-11-23 03:16:03.316336: Current learning rate: 0.00077 +2024-11-23 03:16:21.499490: train_loss -0.8256 +2024-11-23 03:16:21.499722: val_loss -0.7885 +2024-11-23 03:16:21.499798: Pseudo dice [0.8532] +2024-11-23 03:16:21.499872: Epoch time: 18.18 s +2024-11-23 03:16:22.412621: +2024-11-23 03:16:22.412842: Epoch 7538 +2024-11-23 03:16:22.412951: Current learning rate: 0.00077 +2024-11-23 03:16:41.199469: train_loss -0.8294 +2024-11-23 03:16:41.199700: val_loss -0.7689 +2024-11-23 03:16:41.199775: Pseudo dice [0.8552] +2024-11-23 03:16:41.199849: Epoch time: 18.79 s +2024-11-23 03:16:42.119005: +2024-11-23 03:16:42.119227: Epoch 7539 +2024-11-23 03:16:42.119339: Current learning rate: 0.00077 +2024-11-23 03:17:00.406980: train_loss -0.8223 +2024-11-23 03:17:00.407241: val_loss -0.7794 +2024-11-23 03:17:00.407315: Pseudo dice [0.8386] +2024-11-23 03:17:00.407394: Epoch time: 18.29 s +2024-11-23 03:17:01.454326: +2024-11-23 03:17:01.454549: Epoch 7540 +2024-11-23 03:17:01.454664: Current learning rate: 0.00077 +2024-11-23 03:17:19.572277: train_loss -0.8286 +2024-11-23 03:17:19.572568: val_loss -0.7645 +2024-11-23 03:17:19.572646: Pseudo dice [0.8664] +2024-11-23 03:17:19.572718: Epoch time: 18.12 s +2024-11-23 03:17:20.487838: +2024-11-23 03:17:20.488066: Epoch 7541 +2024-11-23 03:17:20.488179: Current learning rate: 0.00076 +2024-11-23 03:17:37.939702: train_loss -0.8329 +2024-11-23 03:17:37.939983: val_loss -0.7956 +2024-11-23 03:17:37.940066: Pseudo dice [0.8679] +2024-11-23 03:17:37.940141: Epoch time: 17.45 s +2024-11-23 03:17:38.918687: +2024-11-23 03:17:38.918967: Epoch 7542 +2024-11-23 03:17:38.919085: Current learning rate: 0.00076 +2024-11-23 03:17:57.967538: train_loss -0.8309 +2024-11-23 03:17:57.969336: val_loss -0.7819 +2024-11-23 03:17:57.969432: Pseudo dice [0.8489] +2024-11-23 03:17:57.969515: Epoch time: 19.05 s +2024-11-23 03:17:58.904215: +2024-11-23 03:17:58.904428: Epoch 7543 +2024-11-23 03:17:58.904534: Current learning rate: 0.00076 +2024-11-23 03:18:17.351315: train_loss -0.8353 +2024-11-23 03:18:17.351551: val_loss -0.7987 +2024-11-23 03:18:17.351625: Pseudo dice [0.8556] +2024-11-23 03:18:17.351698: Epoch time: 18.45 s +2024-11-23 03:18:18.380160: +2024-11-23 03:18:18.380382: Epoch 7544 +2024-11-23 03:18:18.380492: Current learning rate: 0.00076 +2024-11-23 03:18:36.669849: train_loss -0.8303 +2024-11-23 03:18:36.671913: val_loss -0.7941 +2024-11-23 03:18:36.672021: Pseudo dice [0.8589] +2024-11-23 03:18:36.672097: Epoch time: 18.29 s +2024-11-23 03:18:37.613080: +2024-11-23 03:18:37.613295: Epoch 7545 +2024-11-23 03:18:37.613405: Current learning rate: 0.00076 +2024-11-23 03:18:56.326427: train_loss -0.8337 +2024-11-23 03:18:56.326646: val_loss -0.7721 +2024-11-23 03:18:56.326721: Pseudo dice [0.8534] +2024-11-23 03:18:56.326796: Epoch time: 18.71 s +2024-11-23 03:18:57.245687: +2024-11-23 03:18:57.245955: Epoch 7546 +2024-11-23 03:18:57.246073: Current learning rate: 0.00076 +2024-11-23 03:19:14.775284: train_loss -0.8245 +2024-11-23 03:19:14.775556: val_loss -0.7893 +2024-11-23 03:19:14.775637: Pseudo dice [0.8578] +2024-11-23 03:19:14.775714: Epoch time: 17.53 s +2024-11-23 03:19:15.688788: +2024-11-23 03:19:15.688997: Epoch 7547 +2024-11-23 03:19:15.689110: Current learning rate: 0.00075 +2024-11-23 03:19:34.322798: train_loss -0.8339 +2024-11-23 03:19:34.323023: val_loss -0.783 +2024-11-23 03:19:34.323097: Pseudo dice [0.8794] +2024-11-23 03:19:34.323169: Epoch time: 18.63 s +2024-11-23 03:19:35.271464: +2024-11-23 03:19:35.271692: Epoch 7548 +2024-11-23 03:19:35.271812: Current learning rate: 0.00075 +2024-11-23 03:19:54.828543: train_loss -0.8355 +2024-11-23 03:19:54.828766: val_loss -0.7797 +2024-11-23 03:19:54.828841: Pseudo dice [0.8634] +2024-11-23 03:19:54.828915: Epoch time: 19.56 s +2024-11-23 03:19:55.809114: +2024-11-23 03:19:55.809315: Epoch 7549 +2024-11-23 03:19:55.809431: Current learning rate: 0.00075 +2024-11-23 03:20:12.994442: train_loss -0.837 +2024-11-23 03:20:12.994684: val_loss -0.7546 +2024-11-23 03:20:12.994760: Pseudo dice [0.8625] +2024-11-23 03:20:12.994838: Epoch time: 17.19 s +2024-11-23 03:20:13.347060: Yayy! New best EMA pseudo Dice: 0.8597 +2024-11-23 03:20:14.589543: +2024-11-23 03:20:14.589778: Epoch 7550 +2024-11-23 03:20:14.589890: Current learning rate: 0.00075 +2024-11-23 03:20:32.440730: train_loss -0.8305 +2024-11-23 03:20:32.441110: val_loss -0.7643 +2024-11-23 03:20:32.441194: Pseudo dice [0.8401] +2024-11-23 03:20:32.441274: Epoch time: 17.85 s +2024-11-23 03:20:33.374645: +2024-11-23 03:20:33.374885: Epoch 7551 +2024-11-23 03:20:33.375011: Current learning rate: 0.00075 +2024-11-23 03:20:51.781095: train_loss -0.8315 +2024-11-23 03:20:51.781319: val_loss -0.7769 +2024-11-23 03:20:51.781400: Pseudo dice [0.863] +2024-11-23 03:20:51.781474: Epoch time: 18.41 s +2024-11-23 03:20:52.688415: +2024-11-23 03:20:52.688645: Epoch 7552 +2024-11-23 03:20:52.688755: Current learning rate: 0.00075 +2024-11-23 03:21:10.631675: train_loss -0.8319 +2024-11-23 03:21:10.631899: val_loss -0.7749 +2024-11-23 03:21:10.631977: Pseudo dice [0.8458] +2024-11-23 03:21:10.632064: Epoch time: 17.94 s +2024-11-23 03:21:11.547459: +2024-11-23 03:21:11.547676: Epoch 7553 +2024-11-23 03:21:11.547793: Current learning rate: 0.00075 +2024-11-23 03:21:28.892051: train_loss -0.8275 +2024-11-23 03:21:28.892291: val_loss -0.7922 +2024-11-23 03:21:28.892374: Pseudo dice [0.8604] +2024-11-23 03:21:28.892456: Epoch time: 17.35 s +2024-11-23 03:21:30.044738: +2024-11-23 03:21:30.044971: Epoch 7554 +2024-11-23 03:21:30.045085: Current learning rate: 0.00074 +2024-11-23 03:21:46.858109: train_loss -0.8376 +2024-11-23 03:21:46.858325: val_loss -0.7998 +2024-11-23 03:21:46.858401: Pseudo dice [0.8629] +2024-11-23 03:21:46.858480: Epoch time: 16.81 s +2024-11-23 03:21:47.765636: +2024-11-23 03:21:47.765842: Epoch 7555 +2024-11-23 03:21:47.765954: Current learning rate: 0.00074 +2024-11-23 03:22:06.870284: train_loss -0.8297 +2024-11-23 03:22:06.870760: val_loss -0.7788 +2024-11-23 03:22:06.870855: Pseudo dice [0.8625] +2024-11-23 03:22:06.870948: Epoch time: 19.11 s +2024-11-23 03:22:07.784152: +2024-11-23 03:22:07.784369: Epoch 7556 +2024-11-23 03:22:07.784477: Current learning rate: 0.00074 +2024-11-23 03:22:26.738710: train_loss -0.8301 +2024-11-23 03:22:26.738944: val_loss -0.7943 +2024-11-23 03:22:26.739031: Pseudo dice [0.8478] +2024-11-23 03:22:26.744308: Epoch time: 18.96 s +2024-11-23 03:22:27.692432: +2024-11-23 03:22:27.692652: Epoch 7557 +2024-11-23 03:22:27.692769: Current learning rate: 0.00074 +2024-11-23 03:22:47.225033: train_loss -0.8218 +2024-11-23 03:22:47.225276: val_loss -0.8005 +2024-11-23 03:22:47.225358: Pseudo dice [0.8511] +2024-11-23 03:22:47.225440: Epoch time: 19.53 s +2024-11-23 03:22:48.149413: +2024-11-23 03:22:48.149651: Epoch 7558 +2024-11-23 03:22:48.149771: Current learning rate: 0.00074 +2024-11-23 03:23:06.233315: train_loss -0.8349 +2024-11-23 03:23:06.233527: val_loss -0.7771 +2024-11-23 03:23:06.233601: Pseudo dice [0.8471] +2024-11-23 03:23:06.233676: Epoch time: 18.08 s +2024-11-23 03:23:07.143720: +2024-11-23 03:23:07.143958: Epoch 7559 +2024-11-23 03:23:07.144073: Current learning rate: 0.00074 +2024-11-23 03:23:24.720337: train_loss -0.8333 +2024-11-23 03:23:24.720569: val_loss -0.7655 +2024-11-23 03:23:24.720643: Pseudo dice [0.8537] +2024-11-23 03:23:24.720718: Epoch time: 17.58 s +2024-11-23 03:23:25.664790: +2024-11-23 03:23:25.665016: Epoch 7560 +2024-11-23 03:23:25.665122: Current learning rate: 0.00074 +2024-11-23 03:23:43.080653: train_loss -0.8348 +2024-11-23 03:23:43.080871: val_loss -0.7945 +2024-11-23 03:23:43.080946: Pseudo dice [0.8579] +2024-11-23 03:23:43.081027: Epoch time: 17.42 s +2024-11-23 03:23:43.988127: +2024-11-23 03:23:43.992301: Epoch 7561 +2024-11-23 03:23:43.992453: Current learning rate: 0.00073 +2024-11-23 03:24:01.630589: train_loss -0.8375 +2024-11-23 03:24:01.630830: val_loss -0.7972 +2024-11-23 03:24:01.630910: Pseudo dice [0.8585] +2024-11-23 03:24:01.631003: Epoch time: 17.64 s +2024-11-23 03:24:02.545089: +2024-11-23 03:24:02.545296: Epoch 7562 +2024-11-23 03:24:02.545406: Current learning rate: 0.00073 +2024-11-23 03:24:21.129065: train_loss -0.826 +2024-11-23 03:24:21.129279: val_loss -0.7564 +2024-11-23 03:24:21.129354: Pseudo dice [0.8453] +2024-11-23 03:24:21.129427: Epoch time: 18.58 s +2024-11-23 03:24:22.040461: +2024-11-23 03:24:22.040750: Epoch 7563 +2024-11-23 03:24:22.040862: Current learning rate: 0.00073 +2024-11-23 03:24:40.730591: train_loss -0.8322 +2024-11-23 03:24:40.736013: val_loss -0.7689 +2024-11-23 03:24:40.736134: Pseudo dice [0.8338] +2024-11-23 03:24:40.736219: Epoch time: 18.69 s +2024-11-23 03:24:41.914407: +2024-11-23 03:24:41.914679: Epoch 7564 +2024-11-23 03:24:41.914787: Current learning rate: 0.00073 +2024-11-23 03:24:59.368791: train_loss -0.8337 +2024-11-23 03:24:59.369050: val_loss -0.7657 +2024-11-23 03:24:59.369187: Pseudo dice [0.8603] +2024-11-23 03:24:59.369269: Epoch time: 17.46 s +2024-11-23 03:25:00.304620: +2024-11-23 03:25:00.304860: Epoch 7565 +2024-11-23 03:25:00.304976: Current learning rate: 0.00073 +2024-11-23 03:25:18.643273: train_loss -0.8304 +2024-11-23 03:25:18.643516: val_loss -0.7884 +2024-11-23 03:25:18.643594: Pseudo dice [0.8665] +2024-11-23 03:25:18.643669: Epoch time: 18.34 s +2024-11-23 03:25:19.567320: +2024-11-23 03:25:19.567522: Epoch 7566 +2024-11-23 03:25:19.567630: Current learning rate: 0.00073 +2024-11-23 03:25:38.466149: train_loss -0.831 +2024-11-23 03:25:38.466419: val_loss -0.7894 +2024-11-23 03:25:38.466497: Pseudo dice [0.8438] +2024-11-23 03:25:38.466591: Epoch time: 18.9 s +2024-11-23 03:25:39.789852: +2024-11-23 03:25:39.790087: Epoch 7567 +2024-11-23 03:25:39.790199: Current learning rate: 0.00072 +2024-11-23 03:25:58.755434: train_loss -0.8326 +2024-11-23 03:25:58.755694: val_loss -0.7663 +2024-11-23 03:25:58.755773: Pseudo dice [0.8605] +2024-11-23 03:25:58.755853: Epoch time: 18.97 s +2024-11-23 03:25:59.669444: +2024-11-23 03:25:59.669655: Epoch 7568 +2024-11-23 03:25:59.669761: Current learning rate: 0.00072 +2024-11-23 03:26:18.735380: train_loss -0.8314 +2024-11-23 03:26:18.735602: val_loss -0.7801 +2024-11-23 03:26:18.735674: Pseudo dice [0.8683] +2024-11-23 03:26:18.735747: Epoch time: 19.07 s +2024-11-23 03:26:19.645466: +2024-11-23 03:26:19.645676: Epoch 7569 +2024-11-23 03:26:19.645784: Current learning rate: 0.00072 +2024-11-23 03:26:38.183401: train_loss -0.8281 +2024-11-23 03:26:38.183616: val_loss -0.8101 +2024-11-23 03:26:38.183692: Pseudo dice [0.8542] +2024-11-23 03:26:38.183771: Epoch time: 18.54 s +2024-11-23 03:26:39.096941: +2024-11-23 03:26:39.097204: Epoch 7570 +2024-11-23 03:26:39.097314: Current learning rate: 0.00072 +2024-11-23 03:26:57.676570: train_loss -0.8322 +2024-11-23 03:26:57.676791: val_loss -0.7688 +2024-11-23 03:26:57.676867: Pseudo dice [0.8476] +2024-11-23 03:26:57.676942: Epoch time: 18.58 s +2024-11-23 03:26:58.588689: +2024-11-23 03:26:58.588960: Epoch 7571 +2024-11-23 03:26:58.589077: Current learning rate: 0.00072 +2024-11-23 03:27:16.724620: train_loss -0.8381 +2024-11-23 03:27:16.724882: val_loss -0.7876 +2024-11-23 03:27:16.724958: Pseudo dice [0.8586] +2024-11-23 03:27:16.725048: Epoch time: 18.14 s +2024-11-23 03:27:17.676921: +2024-11-23 03:27:17.677151: Epoch 7572 +2024-11-23 03:27:17.677261: Current learning rate: 0.00072 +2024-11-23 03:27:36.025539: train_loss -0.8371 +2024-11-23 03:27:36.025784: val_loss -0.7798 +2024-11-23 03:27:36.025863: Pseudo dice [0.849] +2024-11-23 03:27:36.025939: Epoch time: 18.35 s +2024-11-23 03:27:36.937220: +2024-11-23 03:27:36.937531: Epoch 7573 +2024-11-23 03:27:36.937649: Current learning rate: 0.00072 +2024-11-23 03:27:55.682746: train_loss -0.8318 +2024-11-23 03:27:55.682970: val_loss -0.7825 +2024-11-23 03:27:55.683055: Pseudo dice [0.8463] +2024-11-23 03:27:55.683132: Epoch time: 18.75 s +2024-11-23 03:27:56.592866: +2024-11-23 03:27:56.593088: Epoch 7574 +2024-11-23 03:27:56.593200: Current learning rate: 0.00071 +2024-11-23 03:28:14.648064: train_loss -0.8294 +2024-11-23 03:28:14.648302: val_loss -0.7718 +2024-11-23 03:28:14.648376: Pseudo dice [0.8454] +2024-11-23 03:28:14.653603: Epoch time: 18.06 s +2024-11-23 03:28:15.650574: +2024-11-23 03:28:15.650788: Epoch 7575 +2024-11-23 03:28:15.650902: Current learning rate: 0.00071 +2024-11-23 03:28:34.284426: train_loss -0.8289 +2024-11-23 03:28:34.284692: val_loss -0.7909 +2024-11-23 03:28:34.284772: Pseudo dice [0.8675] +2024-11-23 03:28:34.284848: Epoch time: 18.63 s +2024-11-23 03:28:35.200385: +2024-11-23 03:28:35.200591: Epoch 7576 +2024-11-23 03:28:35.200698: Current learning rate: 0.00071 +2024-11-23 03:28:53.195602: train_loss -0.8296 +2024-11-23 03:28:53.195838: val_loss -0.7782 +2024-11-23 03:28:53.195915: Pseudo dice [0.8619] +2024-11-23 03:28:53.196000: Epoch time: 18.0 s +2024-11-23 03:28:54.109710: +2024-11-23 03:28:54.109908: Epoch 7577 +2024-11-23 03:28:54.110023: Current learning rate: 0.00071 +2024-11-23 03:29:12.401106: train_loss -0.8349 +2024-11-23 03:29:12.401341: val_loss -0.7893 +2024-11-23 03:29:12.401422: Pseudo dice [0.8546] +2024-11-23 03:29:12.401506: Epoch time: 18.29 s +2024-11-23 03:29:13.320235: +2024-11-23 03:29:13.320474: Epoch 7578 +2024-11-23 03:29:13.320591: Current learning rate: 0.00071 +2024-11-23 03:29:32.219443: train_loss -0.8335 +2024-11-23 03:29:32.219678: val_loss -0.7935 +2024-11-23 03:29:32.219769: Pseudo dice [0.8611] +2024-11-23 03:29:32.219850: Epoch time: 18.9 s +2024-11-23 03:29:33.142296: +2024-11-23 03:29:33.142518: Epoch 7579 +2024-11-23 03:29:33.142627: Current learning rate: 0.00071 +2024-11-23 03:29:52.165822: train_loss -0.8291 +2024-11-23 03:29:52.166107: val_loss -0.7965 +2024-11-23 03:29:52.166208: Pseudo dice [0.8601] +2024-11-23 03:29:52.166282: Epoch time: 19.02 s +2024-11-23 03:29:53.079899: +2024-11-23 03:29:53.080111: Epoch 7580 +2024-11-23 03:29:53.080217: Current learning rate: 0.0007 +2024-11-23 03:30:12.027237: train_loss -0.8268 +2024-11-23 03:30:12.027462: val_loss -0.7574 +2024-11-23 03:30:12.027539: Pseudo dice [0.8436] +2024-11-23 03:30:12.027617: Epoch time: 18.95 s +2024-11-23 03:30:13.130528: +2024-11-23 03:30:13.130774: Epoch 7581 +2024-11-23 03:30:13.130887: Current learning rate: 0.0007 +2024-11-23 03:30:32.786078: train_loss -0.8335 +2024-11-23 03:30:32.786328: val_loss -0.7621 +2024-11-23 03:30:32.786403: Pseudo dice [0.8375] +2024-11-23 03:30:32.786489: Epoch time: 19.66 s +2024-11-23 03:30:33.699671: +2024-11-23 03:30:33.699899: Epoch 7582 +2024-11-23 03:30:33.700018: Current learning rate: 0.0007 +2024-11-23 03:30:52.069458: train_loss -0.8309 +2024-11-23 03:30:52.069675: val_loss -0.7936 +2024-11-23 03:30:52.069753: Pseudo dice [0.8667] +2024-11-23 03:30:52.069830: Epoch time: 18.37 s +2024-11-23 03:30:52.993707: +2024-11-23 03:30:52.993984: Epoch 7583 +2024-11-23 03:30:52.994099: Current learning rate: 0.0007 +2024-11-23 03:31:10.036911: train_loss -0.8346 +2024-11-23 03:31:10.037135: val_loss -0.7913 +2024-11-23 03:31:10.037211: Pseudo dice [0.8625] +2024-11-23 03:31:10.037284: Epoch time: 17.04 s +2024-11-23 03:31:11.206038: +2024-11-23 03:31:11.206320: Epoch 7584 +2024-11-23 03:31:11.206432: Current learning rate: 0.0007 +2024-11-23 03:31:30.058517: train_loss -0.8323 +2024-11-23 03:31:30.058789: val_loss -0.7884 +2024-11-23 03:31:30.058870: Pseudo dice [0.8573] +2024-11-23 03:31:30.058950: Epoch time: 18.85 s +2024-11-23 03:31:31.078840: +2024-11-23 03:31:31.079068: Epoch 7585 +2024-11-23 03:31:31.079188: Current learning rate: 0.0007 +2024-11-23 03:31:50.034215: train_loss -0.8339 +2024-11-23 03:31:50.034465: val_loss -0.78 +2024-11-23 03:31:50.034542: Pseudo dice [0.8607] +2024-11-23 03:31:50.034619: Epoch time: 18.96 s +2024-11-23 03:31:50.940702: +2024-11-23 03:31:50.940952: Epoch 7586 +2024-11-23 03:31:50.941069: Current learning rate: 0.0007 +2024-11-23 03:32:09.468245: train_loss -0.8298 +2024-11-23 03:32:09.468457: val_loss -0.7815 +2024-11-23 03:32:09.468541: Pseudo dice [0.8426] +2024-11-23 03:32:09.468616: Epoch time: 18.53 s +2024-11-23 03:32:10.399894: +2024-11-23 03:32:10.400111: Epoch 7587 +2024-11-23 03:32:10.400233: Current learning rate: 0.00069 +2024-11-23 03:32:28.129721: train_loss -0.8351 +2024-11-23 03:32:28.129948: val_loss -0.7992 +2024-11-23 03:32:28.130033: Pseudo dice [0.8614] +2024-11-23 03:32:28.130121: Epoch time: 17.73 s +2024-11-23 03:32:29.050770: +2024-11-23 03:32:29.050990: Epoch 7588 +2024-11-23 03:32:29.051113: Current learning rate: 0.00069 +2024-11-23 03:32:47.285064: train_loss -0.837 +2024-11-23 03:32:47.285326: val_loss -0.7961 +2024-11-23 03:32:47.285405: Pseudo dice [0.8564] +2024-11-23 03:32:47.285480: Epoch time: 18.24 s +2024-11-23 03:32:48.212279: +2024-11-23 03:32:48.212478: Epoch 7589 +2024-11-23 03:32:48.212584: Current learning rate: 0.00069 +2024-11-23 03:33:06.947366: train_loss -0.8296 +2024-11-23 03:33:06.947616: val_loss -0.7917 +2024-11-23 03:33:06.955046: Pseudo dice [0.8679] +2024-11-23 03:33:06.955192: Epoch time: 18.74 s +2024-11-23 03:33:08.270057: +2024-11-23 03:33:08.270299: Epoch 7590 +2024-11-23 03:33:08.270412: Current learning rate: 0.00069 +2024-11-23 03:33:27.457767: train_loss -0.8316 +2024-11-23 03:33:27.458014: val_loss -0.7523 +2024-11-23 03:33:27.458093: Pseudo dice [0.8578] +2024-11-23 03:33:27.458168: Epoch time: 19.19 s +2024-11-23 03:33:28.378690: +2024-11-23 03:33:28.378922: Epoch 7591 +2024-11-23 03:33:28.379036: Current learning rate: 0.00069 +2024-11-23 03:33:47.417689: train_loss -0.8304 +2024-11-23 03:33:47.421356: val_loss -0.7984 +2024-11-23 03:33:47.421481: Pseudo dice [0.8596] +2024-11-23 03:33:47.421563: Epoch time: 19.04 s +2024-11-23 03:33:48.349889: +2024-11-23 03:33:48.350104: Epoch 7592 +2024-11-23 03:33:48.350212: Current learning rate: 0.00069 +2024-11-23 03:34:05.889043: train_loss -0.835 +2024-11-23 03:34:05.889285: val_loss -0.7646 +2024-11-23 03:34:05.889357: Pseudo dice [0.843] +2024-11-23 03:34:05.889432: Epoch time: 17.54 s +2024-11-23 03:34:06.805079: +2024-11-23 03:34:06.805288: Epoch 7593 +2024-11-23 03:34:06.805400: Current learning rate: 0.00069 +2024-11-23 03:34:24.459877: train_loss -0.8307 +2024-11-23 03:34:24.460363: val_loss -0.7753 +2024-11-23 03:34:24.460460: Pseudo dice [0.8572] +2024-11-23 03:34:24.460538: Epoch time: 17.66 s +2024-11-23 03:34:25.461466: +2024-11-23 03:34:25.461698: Epoch 7594 +2024-11-23 03:34:25.461806: Current learning rate: 0.00068 +2024-11-23 03:34:42.820638: train_loss -0.8343 +2024-11-23 03:34:42.820873: val_loss -0.7744 +2024-11-23 03:34:42.820953: Pseudo dice [0.8441] +2024-11-23 03:34:42.821045: Epoch time: 17.36 s +2024-11-23 03:34:43.734587: +2024-11-23 03:34:43.734817: Epoch 7595 +2024-11-23 03:34:43.734931: Current learning rate: 0.00068 +2024-11-23 03:35:02.000747: train_loss -0.8346 +2024-11-23 03:35:02.001053: val_loss -0.754 +2024-11-23 03:35:02.001136: Pseudo dice [0.8438] +2024-11-23 03:35:02.001210: Epoch time: 18.27 s +2024-11-23 03:35:03.020422: +2024-11-23 03:35:03.020659: Epoch 7596 +2024-11-23 03:35:03.020769: Current learning rate: 0.00068 +2024-11-23 03:35:21.091276: train_loss -0.8337 +2024-11-23 03:35:21.091537: val_loss -0.7812 +2024-11-23 03:35:21.091616: Pseudo dice [0.8403] +2024-11-23 03:35:21.091695: Epoch time: 18.07 s +2024-11-23 03:35:21.998808: +2024-11-23 03:35:21.999037: Epoch 7597 +2024-11-23 03:35:21.999148: Current learning rate: 0.00068 +2024-11-23 03:35:40.056504: train_loss -0.8384 +2024-11-23 03:35:40.056735: val_loss -0.7757 +2024-11-23 03:35:40.056812: Pseudo dice [0.8577] +2024-11-23 03:35:40.056886: Epoch time: 18.06 s +2024-11-23 03:35:40.966147: +2024-11-23 03:35:40.966427: Epoch 7598 +2024-11-23 03:35:40.966539: Current learning rate: 0.00068 +2024-11-23 03:35:59.765780: train_loss -0.8344 +2024-11-23 03:35:59.766038: val_loss -0.7588 +2024-11-23 03:35:59.766117: Pseudo dice [0.8499] +2024-11-23 03:35:59.766191: Epoch time: 18.8 s +2024-11-23 03:36:00.729377: +2024-11-23 03:36:00.729580: Epoch 7599 +2024-11-23 03:36:00.729690: Current learning rate: 0.00068 +2024-11-23 03:36:19.615234: train_loss -0.8299 +2024-11-23 03:36:19.615461: val_loss -0.7856 +2024-11-23 03:36:19.615598: Pseudo dice [0.8664] +2024-11-23 03:36:19.615680: Epoch time: 18.89 s +2024-11-23 03:36:20.878349: +2024-11-23 03:36:20.878559: Epoch 7600 +2024-11-23 03:36:20.878666: Current learning rate: 0.00067 +2024-11-23 03:36:39.262513: train_loss -0.8288 +2024-11-23 03:36:39.262749: val_loss -0.7926 +2024-11-23 03:36:39.262826: Pseudo dice [0.8701] +2024-11-23 03:36:39.262906: Epoch time: 18.38 s +2024-11-23 03:36:40.177131: +2024-11-23 03:36:40.177352: Epoch 7601 +2024-11-23 03:36:40.177462: Current learning rate: 0.00067 +2024-11-23 03:37:00.159370: train_loss -0.826 +2024-11-23 03:37:00.159611: val_loss -0.7701 +2024-11-23 03:37:00.159722: Pseudo dice [0.8664] +2024-11-23 03:37:00.159832: Epoch time: 19.98 s +2024-11-23 03:37:01.079342: +2024-11-23 03:37:01.079567: Epoch 7602 +2024-11-23 03:37:01.079679: Current learning rate: 0.00067 +2024-11-23 03:37:20.608687: train_loss -0.8263 +2024-11-23 03:37:20.611120: val_loss -0.784 +2024-11-23 03:37:20.611208: Pseudo dice [0.8667] +2024-11-23 03:37:20.611284: Epoch time: 19.53 s +2024-11-23 03:37:21.553678: +2024-11-23 03:37:21.553900: Epoch 7603 +2024-11-23 03:37:21.554012: Current learning rate: 0.00067 +2024-11-23 03:37:39.868080: train_loss -0.8302 +2024-11-23 03:37:39.868337: val_loss -0.7773 +2024-11-23 03:37:39.868414: Pseudo dice [0.8587] +2024-11-23 03:37:39.868495: Epoch time: 18.32 s +2024-11-23 03:37:40.791915: +2024-11-23 03:37:40.792153: Epoch 7604 +2024-11-23 03:37:40.792262: Current learning rate: 0.00067 +2024-11-23 03:38:00.459157: train_loss -0.8263 +2024-11-23 03:38:00.459389: val_loss -0.7769 +2024-11-23 03:38:00.459462: Pseudo dice [0.8553] +2024-11-23 03:38:00.459535: Epoch time: 19.67 s +2024-11-23 03:38:01.376205: +2024-11-23 03:38:01.376535: Epoch 7605 +2024-11-23 03:38:01.376645: Current learning rate: 0.00067 +2024-11-23 03:38:19.305389: train_loss -0.8332 +2024-11-23 03:38:19.305610: val_loss -0.7742 +2024-11-23 03:38:19.305688: Pseudo dice [0.8593] +2024-11-23 03:38:19.305764: Epoch time: 17.93 s +2024-11-23 03:38:20.218324: +2024-11-23 03:38:20.218568: Epoch 7606 +2024-11-23 03:38:20.218677: Current learning rate: 0.00067 +2024-11-23 03:38:39.551869: train_loss -0.8188 +2024-11-23 03:38:39.552106: val_loss -0.767 +2024-11-23 03:38:39.552181: Pseudo dice [0.8453] +2024-11-23 03:38:39.552255: Epoch time: 19.33 s +2024-11-23 03:38:40.532056: +2024-11-23 03:38:40.532267: Epoch 7607 +2024-11-23 03:38:40.532378: Current learning rate: 0.00066 +2024-11-23 03:38:59.454131: train_loss -0.827 +2024-11-23 03:38:59.454478: val_loss -0.8002 +2024-11-23 03:38:59.454561: Pseudo dice [0.8549] +2024-11-23 03:38:59.454658: Epoch time: 18.92 s +2024-11-23 03:39:00.379734: +2024-11-23 03:39:00.379959: Epoch 7608 +2024-11-23 03:39:00.380076: Current learning rate: 0.00066 +2024-11-23 03:39:18.931646: train_loss -0.828 +2024-11-23 03:39:18.931896: val_loss -0.763 +2024-11-23 03:39:18.931972: Pseudo dice [0.8546] +2024-11-23 03:39:18.932054: Epoch time: 18.55 s +2024-11-23 03:39:19.848951: +2024-11-23 03:39:19.849181: Epoch 7609 +2024-11-23 03:39:19.849292: Current learning rate: 0.00066 +2024-11-23 03:39:38.401166: train_loss -0.827 +2024-11-23 03:39:38.401396: val_loss -0.7988 +2024-11-23 03:39:38.401475: Pseudo dice [0.8651] +2024-11-23 03:39:38.401552: Epoch time: 18.55 s +2024-11-23 03:39:39.325361: +2024-11-23 03:39:39.325598: Epoch 7610 +2024-11-23 03:39:39.325707: Current learning rate: 0.00066 +2024-11-23 03:39:58.321173: train_loss -0.8281 +2024-11-23 03:39:58.321422: val_loss -0.7625 +2024-11-23 03:39:58.321498: Pseudo dice [0.8441] +2024-11-23 03:39:58.321572: Epoch time: 19.0 s +2024-11-23 03:39:59.230506: +2024-11-23 03:39:59.230729: Epoch 7611 +2024-11-23 03:39:59.230840: Current learning rate: 0.00066 +2024-11-23 03:40:17.808537: train_loss -0.8259 +2024-11-23 03:40:17.808790: val_loss -0.763 +2024-11-23 03:40:17.808866: Pseudo dice [0.8452] +2024-11-23 03:40:17.808948: Epoch time: 18.58 s +2024-11-23 03:40:18.783005: +2024-11-23 03:40:18.783216: Epoch 7612 +2024-11-23 03:40:18.783324: Current learning rate: 0.00066 +2024-11-23 03:40:37.938724: train_loss -0.8371 +2024-11-23 03:40:37.938935: val_loss -0.7835 +2024-11-23 03:40:37.939016: Pseudo dice [0.8523] +2024-11-23 03:40:37.939090: Epoch time: 19.16 s +2024-11-23 03:40:39.205780: +2024-11-23 03:40:39.206009: Epoch 7613 +2024-11-23 03:40:39.206121: Current learning rate: 0.00065 +2024-11-23 03:40:56.640074: train_loss -0.827 +2024-11-23 03:40:56.640296: val_loss -0.7701 +2024-11-23 03:40:56.640371: Pseudo dice [0.8601] +2024-11-23 03:40:56.640444: Epoch time: 17.44 s +2024-11-23 03:40:57.551288: +2024-11-23 03:40:57.551505: Epoch 7614 +2024-11-23 03:40:57.551615: Current learning rate: 0.00065 +2024-11-23 03:41:16.436035: train_loss -0.8336 +2024-11-23 03:41:16.436253: val_loss -0.7535 +2024-11-23 03:41:16.436324: Pseudo dice [0.8523] +2024-11-23 03:41:16.436397: Epoch time: 18.89 s +2024-11-23 03:41:17.356306: +2024-11-23 03:41:17.356526: Epoch 7615 +2024-11-23 03:41:17.356642: Current learning rate: 0.00065 +2024-11-23 03:41:35.825235: train_loss -0.8355 +2024-11-23 03:41:35.825546: val_loss -0.7669 +2024-11-23 03:41:35.825626: Pseudo dice [0.8342] +2024-11-23 03:41:35.825708: Epoch time: 18.47 s +2024-11-23 03:41:36.744606: +2024-11-23 03:41:36.744823: Epoch 7616 +2024-11-23 03:41:36.744936: Current learning rate: 0.00065 +2024-11-23 03:41:54.364782: train_loss -0.8337 +2024-11-23 03:41:54.365033: val_loss -0.8058 +2024-11-23 03:41:54.365115: Pseudo dice [0.8621] +2024-11-23 03:41:54.365190: Epoch time: 17.62 s +2024-11-23 03:41:55.288196: +2024-11-23 03:41:55.288420: Epoch 7617 +2024-11-23 03:41:55.288524: Current learning rate: 0.00065 +2024-11-23 03:42:13.541749: train_loss -0.8336 +2024-11-23 03:42:13.541964: val_loss -0.7932 +2024-11-23 03:42:13.542050: Pseudo dice [0.8572] +2024-11-23 03:42:13.542123: Epoch time: 18.25 s +2024-11-23 03:42:14.466784: +2024-11-23 03:42:14.467061: Epoch 7618 +2024-11-23 03:42:14.467168: Current learning rate: 0.00065 +2024-11-23 03:42:32.457043: train_loss -0.8403 +2024-11-23 03:42:32.457264: val_loss -0.7869 +2024-11-23 03:42:32.457344: Pseudo dice [0.8551] +2024-11-23 03:42:32.457415: Epoch time: 17.99 s +2024-11-23 03:42:33.376659: +2024-11-23 03:42:33.376909: Epoch 7619 +2024-11-23 03:42:33.377074: Current learning rate: 0.00065 +2024-11-23 03:42:51.411596: train_loss -0.8324 +2024-11-23 03:42:51.411840: val_loss -0.7917 +2024-11-23 03:42:51.411918: Pseudo dice [0.8464] +2024-11-23 03:42:51.412003: Epoch time: 18.04 s +2024-11-23 03:42:52.325923: +2024-11-23 03:42:52.326148: Epoch 7620 +2024-11-23 03:42:52.326257: Current learning rate: 0.00064 +2024-11-23 03:43:11.142072: train_loss -0.8365 +2024-11-23 03:43:11.142296: val_loss -0.7731 +2024-11-23 03:43:11.142373: Pseudo dice [0.8448] +2024-11-23 03:43:11.142449: Epoch time: 18.82 s +2024-11-23 03:43:12.255232: +2024-11-23 03:43:12.255476: Epoch 7621 +2024-11-23 03:43:12.255587: Current learning rate: 0.00064 +2024-11-23 03:43:30.741312: train_loss -0.8322 +2024-11-23 03:43:30.741529: val_loss -0.7931 +2024-11-23 03:43:30.746748: Pseudo dice [0.8559] +2024-11-23 03:43:30.746940: Epoch time: 18.49 s +2024-11-23 03:43:31.780513: +2024-11-23 03:43:31.780738: Epoch 7622 +2024-11-23 03:43:31.780849: Current learning rate: 0.00064 +2024-11-23 03:43:49.602410: train_loss -0.8348 +2024-11-23 03:43:49.602633: val_loss -0.804 +2024-11-23 03:43:49.602706: Pseudo dice [0.8656] +2024-11-23 03:43:49.602777: Epoch time: 17.82 s +2024-11-23 03:43:50.526433: +2024-11-23 03:43:50.526857: Epoch 7623 +2024-11-23 03:43:50.526988: Current learning rate: 0.00064 +2024-11-23 03:44:09.056366: train_loss -0.8305 +2024-11-23 03:44:09.056601: val_loss -0.7804 +2024-11-23 03:44:09.056674: Pseudo dice [0.8673] +2024-11-23 03:44:09.056751: Epoch time: 18.53 s +2024-11-23 03:44:10.348525: +2024-11-23 03:44:10.348736: Epoch 7624 +2024-11-23 03:44:10.348844: Current learning rate: 0.00064 +2024-11-23 03:44:27.731974: train_loss -0.8322 +2024-11-23 03:44:27.732209: val_loss -0.804 +2024-11-23 03:44:27.732295: Pseudo dice [0.8494] +2024-11-23 03:44:27.732443: Epoch time: 17.38 s +2024-11-23 03:44:28.659903: +2024-11-23 03:44:28.660193: Epoch 7625 +2024-11-23 03:44:28.660306: Current learning rate: 0.00064 +2024-11-23 03:44:46.306336: train_loss -0.837 +2024-11-23 03:44:46.306562: val_loss -0.7932 +2024-11-23 03:44:46.306638: Pseudo dice [0.8656] +2024-11-23 03:44:46.306713: Epoch time: 17.65 s +2024-11-23 03:44:47.227956: +2024-11-23 03:44:47.228299: Epoch 7626 +2024-11-23 03:44:47.228412: Current learning rate: 0.00064 +2024-11-23 03:45:05.584305: train_loss -0.8331 +2024-11-23 03:45:05.584550: val_loss -0.7716 +2024-11-23 03:45:05.584627: Pseudo dice [0.8579] +2024-11-23 03:45:05.584710: Epoch time: 18.36 s +2024-11-23 03:45:06.510367: +2024-11-23 03:45:06.510584: Epoch 7627 +2024-11-23 03:45:06.510693: Current learning rate: 0.00063 +2024-11-23 03:45:25.178272: train_loss -0.8348 +2024-11-23 03:45:25.178576: val_loss -0.7947 +2024-11-23 03:45:25.178660: Pseudo dice [0.8586] +2024-11-23 03:45:25.178738: Epoch time: 18.67 s +2024-11-23 03:45:26.103174: +2024-11-23 03:45:26.103395: Epoch 7628 +2024-11-23 03:45:26.103677: Current learning rate: 0.00063 +2024-11-23 03:45:44.049875: train_loss -0.8337 +2024-11-23 03:45:44.050104: val_loss -0.7702 +2024-11-23 03:45:44.050183: Pseudo dice [0.8578] +2024-11-23 03:45:44.050256: Epoch time: 17.95 s +2024-11-23 03:45:44.973664: +2024-11-23 03:45:44.973892: Epoch 7629 +2024-11-23 03:45:44.974010: Current learning rate: 0.00063 +2024-11-23 03:46:03.529218: train_loss -0.8333 +2024-11-23 03:46:03.529419: val_loss -0.7474 +2024-11-23 03:46:03.529494: Pseudo dice [0.8708] +2024-11-23 03:46:03.529567: Epoch time: 18.56 s +2024-11-23 03:46:04.511252: +2024-11-23 03:46:04.511478: Epoch 7630 +2024-11-23 03:46:04.511599: Current learning rate: 0.00063 +2024-11-23 03:46:23.154430: train_loss -0.8304 +2024-11-23 03:46:23.154685: val_loss -0.767 +2024-11-23 03:46:23.154761: Pseudo dice [0.8532] +2024-11-23 03:46:23.157017: Epoch time: 18.64 s +2024-11-23 03:46:24.111583: +2024-11-23 03:46:24.111805: Epoch 7631 +2024-11-23 03:46:24.111912: Current learning rate: 0.00063 +2024-11-23 03:46:42.701191: train_loss -0.8323 +2024-11-23 03:46:42.704031: val_loss -0.782 +2024-11-23 03:46:42.704126: Pseudo dice [0.86] +2024-11-23 03:46:42.704204: Epoch time: 18.59 s +2024-11-23 03:46:43.666873: +2024-11-23 03:46:43.667123: Epoch 7632 +2024-11-23 03:46:43.667234: Current learning rate: 0.00063 +2024-11-23 03:47:02.137119: train_loss -0.8415 +2024-11-23 03:47:02.137343: val_loss -0.7979 +2024-11-23 03:47:02.137417: Pseudo dice [0.8621] +2024-11-23 03:47:02.137491: Epoch time: 18.47 s +2024-11-23 03:47:03.134326: +2024-11-23 03:47:03.134550: Epoch 7633 +2024-11-23 03:47:03.134657: Current learning rate: 0.00062 +2024-11-23 03:47:21.202736: train_loss -0.8301 +2024-11-23 03:47:21.202950: val_loss -0.7631 +2024-11-23 03:47:21.203130: Pseudo dice [0.8559] +2024-11-23 03:47:21.203212: Epoch time: 18.07 s +2024-11-23 03:47:22.127503: +2024-11-23 03:47:22.127727: Epoch 7634 +2024-11-23 03:47:22.127846: Current learning rate: 0.00062 +2024-11-23 03:47:41.124809: train_loss -0.8354 +2024-11-23 03:47:41.125077: val_loss -0.8179 +2024-11-23 03:47:41.125155: Pseudo dice [0.8701] +2024-11-23 03:47:41.125236: Epoch time: 19.0 s +2024-11-23 03:47:42.152814: +2024-11-23 03:47:42.153069: Epoch 7635 +2024-11-23 03:47:42.153185: Current learning rate: 0.00062 +2024-11-23 03:48:01.392170: train_loss -0.8285 +2024-11-23 03:48:01.392392: val_loss -0.7882 +2024-11-23 03:48:01.392466: Pseudo dice [0.8618] +2024-11-23 03:48:01.392540: Epoch time: 19.24 s +2024-11-23 03:48:02.706266: +2024-11-23 03:48:02.706486: Epoch 7636 +2024-11-23 03:48:02.706618: Current learning rate: 0.00062 +2024-11-23 03:48:20.433773: train_loss -0.8357 +2024-11-23 03:48:20.434017: val_loss -0.7782 +2024-11-23 03:48:20.434093: Pseudo dice [0.8585] +2024-11-23 03:48:20.434171: Epoch time: 17.73 s +2024-11-23 03:48:21.349611: +2024-11-23 03:48:21.349834: Epoch 7637 +2024-11-23 03:48:21.349944: Current learning rate: 0.00062 +2024-11-23 03:48:39.972148: train_loss -0.8207 +2024-11-23 03:48:39.972403: val_loss -0.8023 +2024-11-23 03:48:39.972478: Pseudo dice [0.8518] +2024-11-23 03:48:39.972558: Epoch time: 18.62 s +2024-11-23 03:48:40.888104: +2024-11-23 03:48:40.888318: Epoch 7638 +2024-11-23 03:48:40.888427: Current learning rate: 0.00062 +2024-11-23 03:48:59.371719: train_loss -0.8352 +2024-11-23 03:48:59.371950: val_loss -0.7745 +2024-11-23 03:48:59.372036: Pseudo dice [0.8525] +2024-11-23 03:48:59.372114: Epoch time: 18.48 s +2024-11-23 03:49:00.300858: +2024-11-23 03:49:00.301201: Epoch 7639 +2024-11-23 03:49:00.301312: Current learning rate: 0.00062 +2024-11-23 03:49:18.207799: train_loss -0.8354 +2024-11-23 03:49:18.208031: val_loss -0.8011 +2024-11-23 03:49:18.208164: Pseudo dice [0.846] +2024-11-23 03:49:18.208241: Epoch time: 17.91 s +2024-11-23 03:49:19.128521: +2024-11-23 03:49:19.128748: Epoch 7640 +2024-11-23 03:49:19.128859: Current learning rate: 0.00061 +2024-11-23 03:49:37.522084: train_loss -0.8327 +2024-11-23 03:49:37.522631: val_loss -0.7801 +2024-11-23 03:49:37.522714: Pseudo dice [0.8653] +2024-11-23 03:49:37.522795: Epoch time: 18.39 s +2024-11-23 03:49:38.447718: +2024-11-23 03:49:38.447940: Epoch 7641 +2024-11-23 03:49:38.448061: Current learning rate: 0.00061 +2024-11-23 03:49:57.320287: train_loss -0.8371 +2024-11-23 03:49:57.323937: val_loss -0.7835 +2024-11-23 03:49:57.324063: Pseudo dice [0.8641] +2024-11-23 03:49:57.324139: Epoch time: 18.87 s +2024-11-23 03:49:58.378158: +2024-11-23 03:49:58.378363: Epoch 7642 +2024-11-23 03:49:58.378469: Current learning rate: 0.00061 +2024-11-23 03:50:17.590947: train_loss -0.8361 +2024-11-23 03:50:17.591171: val_loss -0.7909 +2024-11-23 03:50:17.591275: Pseudo dice [0.8537] +2024-11-23 03:50:17.591357: Epoch time: 19.21 s +2024-11-23 03:50:18.515605: +2024-11-23 03:50:18.515835: Epoch 7643 +2024-11-23 03:50:18.515956: Current learning rate: 0.00061 +2024-11-23 03:50:37.481090: train_loss -0.8287 +2024-11-23 03:50:37.481369: val_loss -0.8007 +2024-11-23 03:50:37.481443: Pseudo dice [0.8667] +2024-11-23 03:50:37.481518: Epoch time: 18.97 s +2024-11-23 03:50:38.411890: +2024-11-23 03:50:38.412116: Epoch 7644 +2024-11-23 03:50:38.412229: Current learning rate: 0.00061 +2024-11-23 03:50:56.517833: train_loss -0.8339 +2024-11-23 03:50:56.518082: val_loss -0.7736 +2024-11-23 03:50:56.518160: Pseudo dice [0.8561] +2024-11-23 03:50:56.518240: Epoch time: 18.11 s +2024-11-23 03:50:57.442699: +2024-11-23 03:50:57.442917: Epoch 7645 +2024-11-23 03:50:57.443033: Current learning rate: 0.00061 +2024-11-23 03:51:15.800051: train_loss -0.8328 +2024-11-23 03:51:15.800263: val_loss -0.7688 +2024-11-23 03:51:15.800340: Pseudo dice [0.8471] +2024-11-23 03:51:15.800414: Epoch time: 18.36 s +2024-11-23 03:51:16.728073: +2024-11-23 03:51:16.728420: Epoch 7646 +2024-11-23 03:51:16.728529: Current learning rate: 0.0006 +2024-11-23 03:51:36.764575: train_loss -0.83 +2024-11-23 03:51:36.764808: val_loss -0.8079 +2024-11-23 03:51:36.764902: Pseudo dice [0.8682] +2024-11-23 03:51:36.764987: Epoch time: 20.04 s +2024-11-23 03:51:38.086503: +2024-11-23 03:51:38.086926: Epoch 7647 +2024-11-23 03:51:38.087061: Current learning rate: 0.0006 +2024-11-23 03:51:57.374915: train_loss -0.8287 +2024-11-23 03:51:57.375173: val_loss -0.805 +2024-11-23 03:51:57.375248: Pseudo dice [0.8704] +2024-11-23 03:51:57.375322: Epoch time: 19.29 s +2024-11-23 03:51:58.300129: +2024-11-23 03:51:58.300586: Epoch 7648 +2024-11-23 03:51:58.300721: Current learning rate: 0.0006 +2024-11-23 03:52:16.652076: train_loss -0.8306 +2024-11-23 03:52:16.652297: val_loss -0.7859 +2024-11-23 03:52:16.652373: Pseudo dice [0.8369] +2024-11-23 03:52:16.652449: Epoch time: 18.35 s +2024-11-23 03:52:17.576565: +2024-11-23 03:52:17.577010: Epoch 7649 +2024-11-23 03:52:17.577141: Current learning rate: 0.0006 +2024-11-23 03:52:35.586884: train_loss -0.8305 +2024-11-23 03:52:35.587181: val_loss -0.7781 +2024-11-23 03:52:35.587258: Pseudo dice [0.8689] +2024-11-23 03:52:35.587334: Epoch time: 18.01 s +2024-11-23 03:52:36.874093: +2024-11-23 03:52:36.874508: Epoch 7650 +2024-11-23 03:52:36.874639: Current learning rate: 0.0006 +2024-11-23 03:52:55.095987: train_loss -0.8284 +2024-11-23 03:52:55.096241: val_loss -0.7833 +2024-11-23 03:52:55.096321: Pseudo dice [0.8537] +2024-11-23 03:52:55.096409: Epoch time: 18.22 s +2024-11-23 03:52:56.025776: +2024-11-23 03:52:56.026214: Epoch 7651 +2024-11-23 03:52:56.026345: Current learning rate: 0.0006 +2024-11-23 03:53:14.242851: train_loss -0.8314 +2024-11-23 03:53:14.243141: val_loss -0.7737 +2024-11-23 03:53:14.243216: Pseudo dice [0.8618] +2024-11-23 03:53:14.243296: Epoch time: 18.22 s +2024-11-23 03:53:15.184392: +2024-11-23 03:53:15.184822: Epoch 7652 +2024-11-23 03:53:15.184951: Current learning rate: 0.0006 +2024-11-23 03:53:33.356068: train_loss -0.8323 +2024-11-23 03:53:33.356333: val_loss -0.7736 +2024-11-23 03:53:33.356415: Pseudo dice [0.8485] +2024-11-23 03:53:33.356495: Epoch time: 18.17 s +2024-11-23 03:53:34.401399: +2024-11-23 03:53:34.401813: Epoch 7653 +2024-11-23 03:53:34.425834: Current learning rate: 0.00059 +2024-11-23 03:53:53.779470: train_loss -0.8289 +2024-11-23 03:53:53.779781: val_loss -0.7839 +2024-11-23 03:53:53.779862: Pseudo dice [0.8548] +2024-11-23 03:53:53.779938: Epoch time: 19.38 s +2024-11-23 03:53:54.705153: +2024-11-23 03:53:54.705620: Epoch 7654 +2024-11-23 03:53:54.705909: Current learning rate: 0.00059 +2024-11-23 03:54:12.253064: train_loss -0.8365 +2024-11-23 03:54:12.253372: val_loss -0.7832 +2024-11-23 03:54:12.253459: Pseudo dice [0.8644] +2024-11-23 03:54:12.253570: Epoch time: 17.55 s +2024-11-23 03:54:13.191394: +2024-11-23 03:54:13.191854: Epoch 7655 +2024-11-23 03:54:13.191990: Current learning rate: 0.00059 +2024-11-23 03:54:31.809171: train_loss -0.8336 +2024-11-23 03:54:31.809391: val_loss -0.7735 +2024-11-23 03:54:31.809524: Pseudo dice [0.8564] +2024-11-23 03:54:31.809599: Epoch time: 18.62 s +2024-11-23 03:54:32.733591: +2024-11-23 03:54:32.734023: Epoch 7656 +2024-11-23 03:54:32.734165: Current learning rate: 0.00059 +2024-11-23 03:54:50.462346: train_loss -0.8379 +2024-11-23 03:54:50.462574: val_loss -0.7952 +2024-11-23 03:54:50.462648: Pseudo dice [0.8535] +2024-11-23 03:54:50.462722: Epoch time: 17.73 s +2024-11-23 03:54:51.421339: +2024-11-23 03:54:51.421628: Epoch 7657 +2024-11-23 03:54:51.421740: Current learning rate: 0.00059 +2024-11-23 03:55:09.461174: train_loss -0.8312 +2024-11-23 03:55:09.461394: val_loss -0.8021 +2024-11-23 03:55:09.461470: Pseudo dice [0.8646] +2024-11-23 03:55:09.461543: Epoch time: 18.04 s +2024-11-23 03:55:10.896873: +2024-11-23 03:55:10.897130: Epoch 7658 +2024-11-23 03:55:10.897242: Current learning rate: 0.00059 +2024-11-23 03:55:28.452459: train_loss -0.8315 +2024-11-23 03:55:28.452793: val_loss -0.7642 +2024-11-23 03:55:28.452872: Pseudo dice [0.8521] +2024-11-23 03:55:28.452954: Epoch time: 17.56 s +2024-11-23 03:55:29.377089: +2024-11-23 03:55:29.377326: Epoch 7659 +2024-11-23 03:55:29.377440: Current learning rate: 0.00058 +2024-11-23 03:55:47.890826: train_loss -0.8336 +2024-11-23 03:55:47.891073: val_loss -0.7864 +2024-11-23 03:55:47.891157: Pseudo dice [0.8743] +2024-11-23 03:55:47.891237: Epoch time: 18.51 s +2024-11-23 03:55:48.888812: +2024-11-23 03:55:48.889119: Epoch 7660 +2024-11-23 03:55:48.889245: Current learning rate: 0.00058 +2024-11-23 03:56:08.008415: train_loss -0.83 +2024-11-23 03:56:08.008638: val_loss -0.7824 +2024-11-23 03:56:08.008718: Pseudo dice [0.8601] +2024-11-23 03:56:08.008794: Epoch time: 19.12 s +2024-11-23 03:56:08.928675: +2024-11-23 03:56:08.928903: Epoch 7661 +2024-11-23 03:56:08.929018: Current learning rate: 0.00058 +2024-11-23 03:56:26.706473: train_loss -0.8306 +2024-11-23 03:56:26.706749: val_loss -0.794 +2024-11-23 03:56:26.706834: Pseudo dice [0.8569] +2024-11-23 03:56:26.706915: Epoch time: 17.78 s +2024-11-23 03:56:27.635095: +2024-11-23 03:56:27.635326: Epoch 7662 +2024-11-23 03:56:27.635430: Current learning rate: 0.00058 +2024-11-23 03:56:46.282053: train_loss -0.8368 +2024-11-23 03:56:46.282275: val_loss -0.763 +2024-11-23 03:56:46.282352: Pseudo dice [0.863] +2024-11-23 03:56:46.282426: Epoch time: 18.65 s +2024-11-23 03:56:47.214355: +2024-11-23 03:56:47.214577: Epoch 7663 +2024-11-23 03:56:47.214703: Current learning rate: 0.00058 +2024-11-23 03:57:06.079565: train_loss -0.8334 +2024-11-23 03:57:06.079772: val_loss -0.7864 +2024-11-23 03:57:06.079845: Pseudo dice [0.856] +2024-11-23 03:57:06.079917: Epoch time: 18.87 s +2024-11-23 03:57:06.997262: +2024-11-23 03:57:06.997498: Epoch 7664 +2024-11-23 03:57:06.997612: Current learning rate: 0.00058 +2024-11-23 03:57:25.221681: train_loss -0.8366 +2024-11-23 03:57:25.221916: val_loss -0.7562 +2024-11-23 03:57:25.222000: Pseudo dice [0.8352] +2024-11-23 03:57:25.222075: Epoch time: 18.23 s +2024-11-23 03:57:26.144605: +2024-11-23 03:57:26.144821: Epoch 7665 +2024-11-23 03:57:26.144929: Current learning rate: 0.00058 +2024-11-23 03:57:44.550426: train_loss -0.8335 +2024-11-23 03:57:44.550669: val_loss -0.802 +2024-11-23 03:57:44.550744: Pseudo dice [0.8589] +2024-11-23 03:57:44.569257: Epoch time: 18.41 s +2024-11-23 03:57:45.485152: +2024-11-23 03:57:45.485368: Epoch 7666 +2024-11-23 03:57:45.485483: Current learning rate: 0.00057 +2024-11-23 03:58:04.644444: train_loss -0.8362 +2024-11-23 03:58:04.644665: val_loss -0.78 +2024-11-23 03:58:04.644739: Pseudo dice [0.8696] +2024-11-23 03:58:04.644815: Epoch time: 19.16 s +2024-11-23 03:58:05.566547: +2024-11-23 03:58:05.566768: Epoch 7667 +2024-11-23 03:58:05.566878: Current learning rate: 0.00057 +2024-11-23 03:58:23.855004: train_loss -0.8405 +2024-11-23 03:58:23.855232: val_loss -0.7887 +2024-11-23 03:58:23.855309: Pseudo dice [0.8577] +2024-11-23 03:58:23.855385: Epoch time: 18.29 s +2024-11-23 03:58:24.775613: +2024-11-23 03:58:24.775858: Epoch 7668 +2024-11-23 03:58:24.775990: Current learning rate: 0.00057 +2024-11-23 03:58:42.820294: train_loss -0.8388 +2024-11-23 03:58:42.820517: val_loss -0.7916 +2024-11-23 03:58:42.820595: Pseudo dice [0.8627] +2024-11-23 03:58:42.820671: Epoch time: 18.05 s +2024-11-23 03:58:43.793822: +2024-11-23 03:58:43.794033: Epoch 7669 +2024-11-23 03:58:43.794147: Current learning rate: 0.00057 +2024-11-23 03:59:02.164154: train_loss -0.8274 +2024-11-23 03:59:02.164392: val_loss -0.7839 +2024-11-23 03:59:02.164468: Pseudo dice [0.853] +2024-11-23 03:59:02.164547: Epoch time: 18.37 s +2024-11-23 03:59:03.444163: +2024-11-23 03:59:03.444372: Epoch 7670 +2024-11-23 03:59:03.444478: Current learning rate: 0.00057 +2024-11-23 03:59:22.125669: train_loss -0.8328 +2024-11-23 03:59:22.125904: val_loss -0.81 +2024-11-23 03:59:22.131137: Pseudo dice [0.8606] +2024-11-23 03:59:22.131318: Epoch time: 18.68 s +2024-11-23 03:59:23.130919: +2024-11-23 03:59:23.131166: Epoch 7671 +2024-11-23 03:59:23.131272: Current learning rate: 0.00057 +2024-11-23 03:59:41.332574: train_loss -0.8366 +2024-11-23 03:59:41.332855: val_loss -0.8089 +2024-11-23 03:59:41.332937: Pseudo dice [0.8607] +2024-11-23 03:59:41.333014: Epoch time: 18.2 s +2024-11-23 03:59:42.309500: +2024-11-23 03:59:42.309721: Epoch 7672 +2024-11-23 03:59:42.309832: Current learning rate: 0.00056 +2024-11-23 04:00:01.123510: train_loss -0.84 +2024-11-23 04:00:01.123752: val_loss -0.7756 +2024-11-23 04:00:01.123827: Pseudo dice [0.8507] +2024-11-23 04:00:01.123904: Epoch time: 18.81 s +2024-11-23 04:00:02.114413: +2024-11-23 04:00:02.114639: Epoch 7673 +2024-11-23 04:00:02.114749: Current learning rate: 0.00056 +2024-11-23 04:00:21.781588: train_loss -0.8362 +2024-11-23 04:00:21.781808: val_loss -0.7772 +2024-11-23 04:00:21.781881: Pseudo dice [0.8518] +2024-11-23 04:00:21.781957: Epoch time: 19.67 s +2024-11-23 04:00:22.810731: +2024-11-23 04:00:22.810962: Epoch 7674 +2024-11-23 04:00:22.811071: Current learning rate: 0.00056 +2024-11-23 04:00:42.204237: train_loss -0.8281 +2024-11-23 04:00:42.204479: val_loss -0.7867 +2024-11-23 04:00:42.204558: Pseudo dice [0.8488] +2024-11-23 04:00:42.204632: Epoch time: 19.39 s +2024-11-23 04:00:43.131875: +2024-11-23 04:00:43.132118: Epoch 7675 +2024-11-23 04:00:43.132240: Current learning rate: 0.00056 +2024-11-23 04:01:01.749127: train_loss -0.8299 +2024-11-23 04:01:01.749357: val_loss -0.7957 +2024-11-23 04:01:01.749434: Pseudo dice [0.8662] +2024-11-23 04:01:01.749511: Epoch time: 18.62 s +2024-11-23 04:01:02.673281: +2024-11-23 04:01:02.673519: Epoch 7676 +2024-11-23 04:01:02.673628: Current learning rate: 0.00056 +2024-11-23 04:01:21.954289: train_loss -0.8327 +2024-11-23 04:01:21.954543: val_loss -0.78 +2024-11-23 04:01:21.954619: Pseudo dice [0.8643] +2024-11-23 04:01:21.954704: Epoch time: 19.28 s +2024-11-23 04:01:22.910888: +2024-11-23 04:01:22.911114: Epoch 7677 +2024-11-23 04:01:22.911224: Current learning rate: 0.00056 +2024-11-23 04:01:40.822801: train_loss -0.8367 +2024-11-23 04:01:40.823019: val_loss -0.7699 +2024-11-23 04:01:40.823093: Pseudo dice [0.8565] +2024-11-23 04:01:40.823166: Epoch time: 17.91 s +2024-11-23 04:01:41.735403: +2024-11-23 04:01:41.735671: Epoch 7678 +2024-11-23 04:01:41.735789: Current learning rate: 0.00055 +2024-11-23 04:01:59.452160: train_loss -0.829 +2024-11-23 04:01:59.469983: val_loss -0.7995 +2024-11-23 04:01:59.470171: Pseudo dice [0.8589] +2024-11-23 04:01:59.470260: Epoch time: 17.72 s +2024-11-23 04:02:00.387373: +2024-11-23 04:02:00.387578: Epoch 7679 +2024-11-23 04:02:00.387688: Current learning rate: 0.00055 +2024-11-23 04:02:18.660295: train_loss -0.8288 +2024-11-23 04:02:18.660509: val_loss -0.7873 +2024-11-23 04:02:18.660585: Pseudo dice [0.8668] +2024-11-23 04:02:18.660665: Epoch time: 18.27 s +2024-11-23 04:02:19.573646: +2024-11-23 04:02:19.574020: Epoch 7680 +2024-11-23 04:02:19.574136: Current learning rate: 0.00055 +2024-11-23 04:02:38.206894: train_loss -0.8351 +2024-11-23 04:02:38.207153: val_loss -0.7932 +2024-11-23 04:02:38.207228: Pseudo dice [0.8603] +2024-11-23 04:02:38.207304: Epoch time: 18.63 s +2024-11-23 04:02:39.674481: +2024-11-23 04:02:39.674708: Epoch 7681 +2024-11-23 04:02:39.674817: Current learning rate: 0.00055 +2024-11-23 04:02:59.483811: train_loss -0.8339 +2024-11-23 04:02:59.484030: val_loss -0.7865 +2024-11-23 04:02:59.484107: Pseudo dice [0.8374] +2024-11-23 04:02:59.484182: Epoch time: 19.81 s +2024-11-23 04:03:00.409813: +2024-11-23 04:03:00.410052: Epoch 7682 +2024-11-23 04:03:00.410159: Current learning rate: 0.00055 +2024-11-23 04:03:18.803706: train_loss -0.8317 +2024-11-23 04:03:18.803936: val_loss -0.7846 +2024-11-23 04:03:18.804015: Pseudo dice [0.8627] +2024-11-23 04:03:18.804090: Epoch time: 18.39 s +2024-11-23 04:03:19.766654: +2024-11-23 04:03:19.766891: Epoch 7683 +2024-11-23 04:03:19.767013: Current learning rate: 0.00055 +2024-11-23 04:03:37.772610: train_loss -0.8307 +2024-11-23 04:03:37.772832: val_loss -0.7832 +2024-11-23 04:03:37.772908: Pseudo dice [0.8673] +2024-11-23 04:03:37.772998: Epoch time: 18.01 s +2024-11-23 04:03:38.684291: +2024-11-23 04:03:38.684501: Epoch 7684 +2024-11-23 04:03:38.684612: Current learning rate: 0.00055 +2024-11-23 04:03:56.901064: train_loss -0.8346 +2024-11-23 04:03:56.901360: val_loss -0.7711 +2024-11-23 04:03:56.901436: Pseudo dice [0.8683] +2024-11-23 04:03:56.901509: Epoch time: 18.22 s +2024-11-23 04:03:57.828654: +2024-11-23 04:03:57.828867: Epoch 7685 +2024-11-23 04:03:57.828976: Current learning rate: 0.00054 +2024-11-23 04:04:16.351935: train_loss -0.8372 +2024-11-23 04:04:16.354264: val_loss -0.7826 +2024-11-23 04:04:16.354497: Pseudo dice [0.8435] +2024-11-23 04:04:16.354582: Epoch time: 18.52 s +2024-11-23 04:04:17.288449: +2024-11-23 04:04:17.288673: Epoch 7686 +2024-11-23 04:04:17.288787: Current learning rate: 0.00054 +2024-11-23 04:04:36.577484: train_loss -0.8306 +2024-11-23 04:04:36.577718: val_loss -0.7972 +2024-11-23 04:04:36.577792: Pseudo dice [0.8608] +2024-11-23 04:04:36.577869: Epoch time: 19.29 s +2024-11-23 04:04:37.505247: +2024-11-23 04:04:37.505467: Epoch 7687 +2024-11-23 04:04:37.505574: Current learning rate: 0.00054 +2024-11-23 04:04:55.909970: train_loss -0.8325 +2024-11-23 04:04:55.910253: val_loss -0.8003 +2024-11-23 04:04:55.910329: Pseudo dice [0.8519] +2024-11-23 04:04:55.910430: Epoch time: 18.41 s +2024-11-23 04:04:56.965506: +2024-11-23 04:04:56.965740: Epoch 7688 +2024-11-23 04:04:56.965849: Current learning rate: 0.00054 +2024-11-23 04:05:15.562675: train_loss -0.8388 +2024-11-23 04:05:15.562897: val_loss -0.786 +2024-11-23 04:05:15.562972: Pseudo dice [0.8645] +2024-11-23 04:05:15.563051: Epoch time: 18.6 s +2024-11-23 04:05:16.489426: +2024-11-23 04:05:16.489658: Epoch 7689 +2024-11-23 04:05:16.489784: Current learning rate: 0.00054 +2024-11-23 04:05:36.456573: train_loss -0.8336 +2024-11-23 04:05:36.456803: val_loss -0.8093 +2024-11-23 04:05:36.456877: Pseudo dice [0.8548] +2024-11-23 04:05:36.456951: Epoch time: 19.97 s +2024-11-23 04:05:37.382008: +2024-11-23 04:05:37.382229: Epoch 7690 +2024-11-23 04:05:37.382337: Current learning rate: 0.00054 +2024-11-23 04:05:54.738087: train_loss -0.836 +2024-11-23 04:05:54.738308: val_loss -0.7943 +2024-11-23 04:05:54.738384: Pseudo dice [0.8716] +2024-11-23 04:05:54.738459: Epoch time: 17.36 s +2024-11-23 04:05:55.658535: +2024-11-23 04:05:55.658756: Epoch 7691 +2024-11-23 04:05:55.694496: Current learning rate: 0.00053 +2024-11-23 04:06:15.270552: train_loss -0.8337 +2024-11-23 04:06:15.270793: val_loss -0.7834 +2024-11-23 04:06:15.270870: Pseudo dice [0.8674] +2024-11-23 04:06:15.270960: Epoch time: 19.61 s +2024-11-23 04:06:15.271061: Yayy! New best EMA pseudo Dice: 0.86 +2024-11-23 04:06:16.574374: +2024-11-23 04:06:16.574647: Epoch 7692 +2024-11-23 04:06:16.574757: Current learning rate: 0.00053 +2024-11-23 04:06:34.642494: train_loss -0.835 +2024-11-23 04:06:34.642724: val_loss -0.7772 +2024-11-23 04:06:34.642802: Pseudo dice [0.8476] +2024-11-23 04:06:34.642877: Epoch time: 18.07 s +2024-11-23 04:06:35.568814: +2024-11-23 04:06:35.569057: Epoch 7693 +2024-11-23 04:06:35.569170: Current learning rate: 0.00053 +2024-11-23 04:06:54.705601: train_loss -0.8346 +2024-11-23 04:06:54.705857: val_loss -0.7986 +2024-11-23 04:06:54.705933: Pseudo dice [0.8568] +2024-11-23 04:06:54.706013: Epoch time: 19.14 s +2024-11-23 04:06:55.629374: +2024-11-23 04:06:55.629600: Epoch 7694 +2024-11-23 04:06:55.629708: Current learning rate: 0.00053 +2024-11-23 04:07:14.266295: train_loss -0.8282 +2024-11-23 04:07:14.266538: val_loss -0.784 +2024-11-23 04:07:14.267855: Pseudo dice [0.8625] +2024-11-23 04:07:14.267967: Epoch time: 18.64 s +2024-11-23 04:07:15.266762: +2024-11-23 04:07:15.267000: Epoch 7695 +2024-11-23 04:07:15.267108: Current learning rate: 0.00053 +2024-11-23 04:07:34.477745: train_loss -0.8331 +2024-11-23 04:07:34.477962: val_loss -0.7903 +2024-11-23 04:07:34.478043: Pseudo dice [0.8691] +2024-11-23 04:07:34.478173: Epoch time: 19.21 s +2024-11-23 04:07:35.402365: +2024-11-23 04:07:35.402612: Epoch 7696 +2024-11-23 04:07:35.402729: Current learning rate: 0.00053 +2024-11-23 04:07:53.395982: train_loss -0.833 +2024-11-23 04:07:53.396205: val_loss -0.7823 +2024-11-23 04:07:53.396279: Pseudo dice [0.8414] +2024-11-23 04:07:53.396353: Epoch time: 17.99 s +2024-11-23 04:07:54.422750: +2024-11-23 04:07:54.423012: Epoch 7697 +2024-11-23 04:07:54.423130: Current learning rate: 0.00053 +2024-11-23 04:08:12.225913: train_loss -0.836 +2024-11-23 04:08:12.226136: val_loss -0.7732 +2024-11-23 04:08:12.226214: Pseudo dice [0.8669] +2024-11-23 04:08:12.226288: Epoch time: 17.8 s +2024-11-23 04:08:13.223909: +2024-11-23 04:08:13.224137: Epoch 7698 +2024-11-23 04:08:13.224250: Current learning rate: 0.00052 +2024-11-23 04:08:31.274573: train_loss -0.8381 +2024-11-23 04:08:31.274821: val_loss -0.7785 +2024-11-23 04:08:31.274895: Pseudo dice [0.8572] +2024-11-23 04:08:31.274973: Epoch time: 18.05 s +2024-11-23 04:08:32.193070: +2024-11-23 04:08:32.193477: Epoch 7699 +2024-11-23 04:08:32.193594: Current learning rate: 0.00052 +2024-11-23 04:08:50.441130: train_loss -0.8434 +2024-11-23 04:08:50.441360: val_loss -0.7784 +2024-11-23 04:08:50.441435: Pseudo dice [0.8568] +2024-11-23 04:08:50.441510: Epoch time: 18.25 s +2024-11-23 04:08:51.800367: +2024-11-23 04:08:51.800684: Epoch 7700 +2024-11-23 04:08:51.800797: Current learning rate: 0.00052 +2024-11-23 04:09:08.668203: train_loss -0.8398 +2024-11-23 04:09:08.668436: val_loss -0.7803 +2024-11-23 04:09:08.668509: Pseudo dice [0.863] +2024-11-23 04:09:08.668585: Epoch time: 16.87 s +2024-11-23 04:09:09.593815: +2024-11-23 04:09:09.594040: Epoch 7701 +2024-11-23 04:09:09.594151: Current learning rate: 0.00052 +2024-11-23 04:09:27.054767: train_loss -0.8342 +2024-11-23 04:09:27.055021: val_loss -0.8116 +2024-11-23 04:09:27.055116: Pseudo dice [0.8691] +2024-11-23 04:09:27.055204: Epoch time: 17.46 s +2024-11-23 04:09:27.055283: Yayy! New best EMA pseudo Dice: 0.8601 +2024-11-23 04:09:28.320716: +2024-11-23 04:09:28.320972: Epoch 7702 +2024-11-23 04:09:28.321092: Current learning rate: 0.00052 +2024-11-23 04:09:46.421966: train_loss -0.8438 +2024-11-23 04:09:46.422260: val_loss -0.7735 +2024-11-23 04:09:46.422344: Pseudo dice [0.85] +2024-11-23 04:09:46.422436: Epoch time: 18.1 s +2024-11-23 04:09:47.332961: +2024-11-23 04:09:47.333185: Epoch 7703 +2024-11-23 04:09:47.333292: Current learning rate: 0.00052 +2024-11-23 04:10:04.895768: train_loss -0.8334 +2024-11-23 04:10:04.896255: val_loss -0.8032 +2024-11-23 04:10:04.896356: Pseudo dice [0.8527] +2024-11-23 04:10:04.896432: Epoch time: 17.56 s +2024-11-23 04:10:05.812323: +2024-11-23 04:10:05.812540: Epoch 7704 +2024-11-23 04:10:05.812648: Current learning rate: 0.00051 +2024-11-23 04:10:24.421504: train_loss -0.8285 +2024-11-23 04:10:24.421717: val_loss -0.8002 +2024-11-23 04:10:24.421796: Pseudo dice [0.8638] +2024-11-23 04:10:24.421873: Epoch time: 18.61 s +2024-11-23 04:10:25.344190: +2024-11-23 04:10:25.344402: Epoch 7705 +2024-11-23 04:10:25.344507: Current learning rate: 0.00051 +2024-11-23 04:10:44.734334: train_loss -0.8364 +2024-11-23 04:10:44.734761: val_loss -0.7866 +2024-11-23 04:10:44.734848: Pseudo dice [0.8481] +2024-11-23 04:10:44.734926: Epoch time: 19.39 s +2024-11-23 04:10:45.655011: +2024-11-23 04:10:45.655278: Epoch 7706 +2024-11-23 04:10:45.655393: Current learning rate: 0.00051 +2024-11-23 04:11:03.519978: train_loss -0.8368 +2024-11-23 04:11:03.525371: val_loss -0.7735 +2024-11-23 04:11:03.525456: Pseudo dice [0.858] +2024-11-23 04:11:03.525532: Epoch time: 17.87 s +2024-11-23 04:11:04.577397: +2024-11-23 04:11:04.577638: Epoch 7707 +2024-11-23 04:11:04.577750: Current learning rate: 0.00051 +2024-11-23 04:11:22.964017: train_loss -0.8322 +2024-11-23 04:11:22.964244: val_loss -0.7998 +2024-11-23 04:11:22.964324: Pseudo dice [0.8531] +2024-11-23 04:11:22.964400: Epoch time: 18.39 s +2024-11-23 04:11:23.988001: +2024-11-23 04:11:23.988303: Epoch 7708 +2024-11-23 04:11:23.988422: Current learning rate: 0.00051 +2024-11-23 04:11:42.797929: train_loss -0.8354 +2024-11-23 04:11:42.798151: val_loss -0.7868 +2024-11-23 04:11:42.798226: Pseudo dice [0.8693] +2024-11-23 04:11:42.798297: Epoch time: 18.81 s +2024-11-23 04:11:43.714601: +2024-11-23 04:11:43.714809: Epoch 7709 +2024-11-23 04:11:43.714917: Current learning rate: 0.00051 +2024-11-23 04:12:02.359265: train_loss -0.8315 +2024-11-23 04:12:02.359515: val_loss -0.7977 +2024-11-23 04:12:02.359601: Pseudo dice [0.8542] +2024-11-23 04:12:02.359678: Epoch time: 18.65 s +2024-11-23 04:12:03.288670: +2024-11-23 04:12:03.288874: Epoch 7710 +2024-11-23 04:12:03.288981: Current learning rate: 0.00051 +2024-11-23 04:12:22.896595: train_loss -0.8334 +2024-11-23 04:12:22.896811: val_loss -0.7762 +2024-11-23 04:12:22.896884: Pseudo dice [0.8505] +2024-11-23 04:12:22.896958: Epoch time: 19.61 s +2024-11-23 04:12:23.819447: +2024-11-23 04:12:23.819668: Epoch 7711 +2024-11-23 04:12:23.819776: Current learning rate: 0.0005 +2024-11-23 04:12:42.129854: train_loss -0.8359 +2024-11-23 04:12:42.130076: val_loss -0.7971 +2024-11-23 04:12:42.130152: Pseudo dice [0.856] +2024-11-23 04:12:42.135381: Epoch time: 18.31 s +2024-11-23 04:12:43.140756: +2024-11-23 04:12:43.140954: Epoch 7712 +2024-11-23 04:12:43.141070: Current learning rate: 0.0005 +2024-11-23 04:13:02.154381: train_loss -0.8364 +2024-11-23 04:13:02.154593: val_loss -0.7953 +2024-11-23 04:13:02.154667: Pseudo dice [0.8577] +2024-11-23 04:13:02.154744: Epoch time: 19.01 s +2024-11-23 04:13:03.089845: +2024-11-23 04:13:03.090072: Epoch 7713 +2024-11-23 04:13:03.090181: Current learning rate: 0.0005 +2024-11-23 04:13:21.435723: train_loss -0.839 +2024-11-23 04:13:21.435971: val_loss -0.7984 +2024-11-23 04:13:21.440686: Pseudo dice [0.8543] +2024-11-23 04:13:21.440802: Epoch time: 18.35 s +2024-11-23 04:13:22.761827: +2024-11-23 04:13:22.762048: Epoch 7714 +2024-11-23 04:13:22.762158: Current learning rate: 0.0005 +2024-11-23 04:13:41.196318: train_loss -0.8358 +2024-11-23 04:13:41.196554: val_loss -0.7882 +2024-11-23 04:13:41.196633: Pseudo dice [0.8613] +2024-11-23 04:13:41.196708: Epoch time: 18.44 s +2024-11-23 04:13:42.125412: +2024-11-23 04:13:42.125637: Epoch 7715 +2024-11-23 04:13:42.125742: Current learning rate: 0.0005 +2024-11-23 04:14:00.378679: train_loss -0.8326 +2024-11-23 04:14:00.378908: val_loss -0.7893 +2024-11-23 04:14:00.378983: Pseudo dice [0.8495] +2024-11-23 04:14:00.379068: Epoch time: 18.25 s +2024-11-23 04:14:01.544749: +2024-11-23 04:14:01.544999: Epoch 7716 +2024-11-23 04:14:01.545123: Current learning rate: 0.0005 +2024-11-23 04:14:19.809298: train_loss -0.8347 +2024-11-23 04:14:19.809526: val_loss -0.7772 +2024-11-23 04:14:19.809597: Pseudo dice [0.8483] +2024-11-23 04:14:19.809684: Epoch time: 18.27 s +2024-11-23 04:14:20.787616: +2024-11-23 04:14:20.787820: Epoch 7717 +2024-11-23 04:14:20.787926: Current learning rate: 0.00049 +2024-11-23 04:14:39.243895: train_loss -0.8355 +2024-11-23 04:14:39.244147: val_loss -0.787 +2024-11-23 04:14:39.244235: Pseudo dice [0.8472] +2024-11-23 04:14:39.244323: Epoch time: 18.46 s +2024-11-23 04:14:40.167722: +2024-11-23 04:14:40.167967: Epoch 7718 +2024-11-23 04:14:40.168079: Current learning rate: 0.00049 +2024-11-23 04:14:58.454661: train_loss -0.8357 +2024-11-23 04:14:58.454871: val_loss -0.7724 +2024-11-23 04:14:58.454945: Pseudo dice [0.863] +2024-11-23 04:14:58.455020: Epoch time: 18.29 s +2024-11-23 04:14:59.375417: +2024-11-23 04:14:59.375651: Epoch 7719 +2024-11-23 04:14:59.375762: Current learning rate: 0.00049 +2024-11-23 04:15:17.906699: train_loss -0.8357 +2024-11-23 04:15:17.906928: val_loss -0.789 +2024-11-23 04:15:17.907008: Pseudo dice [0.8662] +2024-11-23 04:15:17.907084: Epoch time: 18.53 s +2024-11-23 04:15:18.880936: +2024-11-23 04:15:18.881168: Epoch 7720 +2024-11-23 04:15:18.881303: Current learning rate: 0.00049 +2024-11-23 04:15:38.696446: train_loss -0.8288 +2024-11-23 04:15:38.696711: val_loss -0.759 +2024-11-23 04:15:38.696821: Pseudo dice [0.8596] +2024-11-23 04:15:38.696919: Epoch time: 19.82 s +2024-11-23 04:15:39.638145: +2024-11-23 04:15:39.638366: Epoch 7721 +2024-11-23 04:15:39.638477: Current learning rate: 0.00049 +2024-11-23 04:15:58.362569: train_loss -0.8292 +2024-11-23 04:15:58.362782: val_loss -0.7762 +2024-11-23 04:15:58.362856: Pseudo dice [0.8521] +2024-11-23 04:15:58.362927: Epoch time: 18.73 s +2024-11-23 04:15:59.285755: +2024-11-23 04:15:59.285969: Epoch 7722 +2024-11-23 04:15:59.286087: Current learning rate: 0.00049 +2024-11-23 04:16:17.255804: train_loss -0.8336 +2024-11-23 04:16:17.256020: val_loss -0.7756 +2024-11-23 04:16:17.256093: Pseudo dice [0.8519] +2024-11-23 04:16:17.256162: Epoch time: 17.97 s +2024-11-23 04:16:18.194247: +2024-11-23 04:16:18.194567: Epoch 7723 +2024-11-23 04:16:18.194683: Current learning rate: 0.00048 +2024-11-23 04:16:35.494674: train_loss -0.8342 +2024-11-23 04:16:35.494884: val_loss -0.7882 +2024-11-23 04:16:35.494960: Pseudo dice [0.8449] +2024-11-23 04:16:35.495067: Epoch time: 17.3 s +2024-11-23 04:16:36.418209: +2024-11-23 04:16:36.418432: Epoch 7724 +2024-11-23 04:16:36.418540: Current learning rate: 0.00048 +2024-11-23 04:16:54.266848: train_loss -0.8364 +2024-11-23 04:16:54.267098: val_loss -0.7876 +2024-11-23 04:16:54.267172: Pseudo dice [0.8551] +2024-11-23 04:16:54.267251: Epoch time: 17.85 s +2024-11-23 04:16:55.191306: +2024-11-23 04:16:55.191506: Epoch 7725 +2024-11-23 04:16:55.191612: Current learning rate: 0.00048 +2024-11-23 04:17:13.462834: train_loss -0.8356 +2024-11-23 04:17:13.463067: val_loss -0.7829 +2024-11-23 04:17:13.463139: Pseudo dice [0.8576] +2024-11-23 04:17:13.463212: Epoch time: 18.27 s +2024-11-23 04:17:14.790344: +2024-11-23 04:17:14.790563: Epoch 7726 +2024-11-23 04:17:14.790682: Current learning rate: 0.00048 +2024-11-23 04:17:33.043355: train_loss -0.8347 +2024-11-23 04:17:33.043577: val_loss -0.7911 +2024-11-23 04:17:33.043653: Pseudo dice [0.865] +2024-11-23 04:17:33.043727: Epoch time: 18.25 s +2024-11-23 04:17:33.966901: +2024-11-23 04:17:33.967125: Epoch 7727 +2024-11-23 04:17:33.967235: Current learning rate: 0.00048 +2024-11-23 04:17:52.885870: train_loss -0.8367 +2024-11-23 04:17:52.886188: val_loss -0.7747 +2024-11-23 04:17:52.886273: Pseudo dice [0.8563] +2024-11-23 04:17:52.886364: Epoch time: 18.92 s +2024-11-23 04:17:53.869921: +2024-11-23 04:17:53.870132: Epoch 7728 +2024-11-23 04:17:53.870240: Current learning rate: 0.00048 +2024-11-23 04:18:12.378316: train_loss -0.8321 +2024-11-23 04:18:12.378533: val_loss -0.8043 +2024-11-23 04:18:12.378606: Pseudo dice [0.87] +2024-11-23 04:18:12.378677: Epoch time: 18.51 s +2024-11-23 04:18:13.298122: +2024-11-23 04:18:13.298349: Epoch 7729 +2024-11-23 04:18:13.298465: Current learning rate: 0.00048 +2024-11-23 04:18:31.509469: train_loss -0.8334 +2024-11-23 04:18:31.509679: val_loss -0.7731 +2024-11-23 04:18:31.509753: Pseudo dice [0.8584] +2024-11-23 04:18:31.509825: Epoch time: 18.21 s +2024-11-23 04:18:32.438423: +2024-11-23 04:18:32.438624: Epoch 7730 +2024-11-23 04:18:32.438733: Current learning rate: 0.00047 +2024-11-23 04:18:50.621626: train_loss -0.8348 +2024-11-23 04:18:50.621852: val_loss -0.7872 +2024-11-23 04:18:50.621930: Pseudo dice [0.8696] +2024-11-23 04:18:50.622026: Epoch time: 18.18 s +2024-11-23 04:18:51.553664: +2024-11-23 04:18:51.553864: Epoch 7731 +2024-11-23 04:18:51.553975: Current learning rate: 0.00047 +2024-11-23 04:19:09.897237: train_loss -0.8363 +2024-11-23 04:19:09.897653: val_loss -0.7884 +2024-11-23 04:19:09.897738: Pseudo dice [0.8457] +2024-11-23 04:19:09.897814: Epoch time: 18.34 s +2024-11-23 04:19:10.825765: +2024-11-23 04:19:10.826016: Epoch 7732 +2024-11-23 04:19:10.826160: Current learning rate: 0.00047 +2024-11-23 04:19:28.765446: train_loss -0.8333 +2024-11-23 04:19:28.765656: val_loss -0.7747 +2024-11-23 04:19:28.765728: Pseudo dice [0.8436] +2024-11-23 04:19:28.765804: Epoch time: 17.94 s +2024-11-23 04:19:29.691590: +2024-11-23 04:19:29.691870: Epoch 7733 +2024-11-23 04:19:29.692009: Current learning rate: 0.00047 +2024-11-23 04:19:47.671555: train_loss -0.8426 +2024-11-23 04:19:47.671772: val_loss -0.7884 +2024-11-23 04:19:47.671846: Pseudo dice [0.8531] +2024-11-23 04:19:47.671917: Epoch time: 17.98 s +2024-11-23 04:19:48.591102: +2024-11-23 04:19:48.591317: Epoch 7734 +2024-11-23 04:19:48.591427: Current learning rate: 0.00047 +2024-11-23 04:20:06.670761: train_loss -0.8345 +2024-11-23 04:20:06.670983: val_loss -0.7936 +2024-11-23 04:20:06.671061: Pseudo dice [0.8607] +2024-11-23 04:20:06.671134: Epoch time: 18.08 s +2024-11-23 04:20:07.619796: +2024-11-23 04:20:07.620212: Epoch 7735 +2024-11-23 04:20:07.620326: Current learning rate: 0.00047 +2024-11-23 04:20:27.264126: train_loss -0.8335 +2024-11-23 04:20:27.264405: val_loss -0.7852 +2024-11-23 04:20:27.264488: Pseudo dice [0.8627] +2024-11-23 04:20:27.264573: Epoch time: 19.65 s +2024-11-23 04:20:28.190739: +2024-11-23 04:20:28.190953: Epoch 7736 +2024-11-23 04:20:28.191068: Current learning rate: 0.00046 +2024-11-23 04:20:47.640052: train_loss -0.8322 +2024-11-23 04:20:47.640273: val_loss -0.7684 +2024-11-23 04:20:47.640352: Pseudo dice [0.862] +2024-11-23 04:20:47.640431: Epoch time: 19.45 s +2024-11-23 04:20:49.070536: +2024-11-23 04:20:49.070762: Epoch 7737 +2024-11-23 04:20:49.070876: Current learning rate: 0.00046 +2024-11-23 04:21:07.941576: train_loss -0.837 +2024-11-23 04:21:07.947012: val_loss -0.7907 +2024-11-23 04:21:07.947138: Pseudo dice [0.8594] +2024-11-23 04:21:07.947218: Epoch time: 18.87 s +2024-11-23 04:21:08.904668: +2024-11-23 04:21:08.904936: Epoch 7738 +2024-11-23 04:21:08.905053: Current learning rate: 0.00046 +2024-11-23 04:21:26.918882: train_loss -0.8318 +2024-11-23 04:21:26.919144: val_loss -0.7849 +2024-11-23 04:21:26.919223: Pseudo dice [0.8453] +2024-11-23 04:21:26.919300: Epoch time: 18.02 s +2024-11-23 04:21:27.846937: +2024-11-23 04:21:27.847182: Epoch 7739 +2024-11-23 04:21:27.847289: Current learning rate: 0.00046 +2024-11-23 04:21:46.873722: train_loss -0.8348 +2024-11-23 04:21:46.873952: val_loss -0.7915 +2024-11-23 04:21:46.874033: Pseudo dice [0.8536] +2024-11-23 04:21:46.874114: Epoch time: 19.03 s +2024-11-23 04:21:47.794604: +2024-11-23 04:21:47.794819: Epoch 7740 +2024-11-23 04:21:47.794934: Current learning rate: 0.00046 +2024-11-23 04:22:06.157129: train_loss -0.8396 +2024-11-23 04:22:06.157354: val_loss -0.7966 +2024-11-23 04:22:06.157428: Pseudo dice [0.8642] +2024-11-23 04:22:06.157503: Epoch time: 18.36 s +2024-11-23 04:22:07.081131: +2024-11-23 04:22:07.081375: Epoch 7741 +2024-11-23 04:22:07.081485: Current learning rate: 0.00046 +2024-11-23 04:22:25.846182: train_loss -0.8423 +2024-11-23 04:22:25.846394: val_loss -0.7791 +2024-11-23 04:22:25.846464: Pseudo dice [0.8553] +2024-11-23 04:22:25.846540: Epoch time: 18.77 s +2024-11-23 04:22:26.809328: +2024-11-23 04:22:26.809554: Epoch 7742 +2024-11-23 04:22:26.809665: Current learning rate: 0.00045 +2024-11-23 04:22:45.359117: train_loss -0.8368 +2024-11-23 04:22:45.359357: val_loss -0.8012 +2024-11-23 04:22:45.359435: Pseudo dice [0.8538] +2024-11-23 04:22:45.359512: Epoch time: 18.55 s +2024-11-23 04:22:46.276998: +2024-11-23 04:22:46.277369: Epoch 7743 +2024-11-23 04:22:46.277479: Current learning rate: 0.00045 +2024-11-23 04:23:04.711334: train_loss -0.8305 +2024-11-23 04:23:04.711567: val_loss -0.7891 +2024-11-23 04:23:04.711643: Pseudo dice [0.8517] +2024-11-23 04:23:04.711726: Epoch time: 18.44 s +2024-11-23 04:23:05.629981: +2024-11-23 04:23:05.630199: Epoch 7744 +2024-11-23 04:23:05.630307: Current learning rate: 0.00045 +2024-11-23 04:23:23.594069: train_loss -0.8285 +2024-11-23 04:23:23.594289: val_loss -0.7867 +2024-11-23 04:23:23.594362: Pseudo dice [0.8613] +2024-11-23 04:23:23.594437: Epoch time: 17.96 s +2024-11-23 04:23:24.623540: +2024-11-23 04:23:24.623747: Epoch 7745 +2024-11-23 04:23:24.623856: Current learning rate: 0.00045 +2024-11-23 04:23:43.002784: train_loss -0.8267 +2024-11-23 04:23:43.003008: val_loss -0.7516 +2024-11-23 04:23:43.003084: Pseudo dice [0.8337] +2024-11-23 04:23:43.003159: Epoch time: 18.38 s +2024-11-23 04:23:43.929794: +2024-11-23 04:23:43.930087: Epoch 7746 +2024-11-23 04:23:43.930195: Current learning rate: 0.00045 +2024-11-23 04:24:03.840951: train_loss -0.8301 +2024-11-23 04:24:03.846363: val_loss -0.7824 +2024-11-23 04:24:03.846478: Pseudo dice [0.8479] +2024-11-23 04:24:03.846556: Epoch time: 19.91 s +2024-11-23 04:24:04.995296: +2024-11-23 04:24:04.995585: Epoch 7747 +2024-11-23 04:24:04.995703: Current learning rate: 0.00045 +2024-11-23 04:24:23.472779: train_loss -0.833 +2024-11-23 04:24:23.473043: val_loss -0.7855 +2024-11-23 04:24:23.473127: Pseudo dice [0.8696] +2024-11-23 04:24:23.473212: Epoch time: 18.48 s +2024-11-23 04:24:24.402661: +2024-11-23 04:24:24.402911: Epoch 7748 +2024-11-23 04:24:24.403027: Current learning rate: 0.00045 +2024-11-23 04:24:42.611843: train_loss -0.8293 +2024-11-23 04:24:42.612092: val_loss -0.7854 +2024-11-23 04:24:42.612172: Pseudo dice [0.8433] +2024-11-23 04:24:42.612249: Epoch time: 18.21 s +2024-11-23 04:24:43.979415: +2024-11-23 04:24:43.979650: Epoch 7749 +2024-11-23 04:24:43.979755: Current learning rate: 0.00044 +2024-11-23 04:25:03.126936: train_loss -0.8338 +2024-11-23 04:25:03.127168: val_loss -0.7687 +2024-11-23 04:25:03.127244: Pseudo dice [0.8468] +2024-11-23 04:25:03.127319: Epoch time: 19.15 s +2024-11-23 04:25:04.406776: +2024-11-23 04:25:04.406993: Epoch 7750 +2024-11-23 04:25:04.407105: Current learning rate: 0.00044 +2024-11-23 04:25:21.943129: train_loss -0.834 +2024-11-23 04:25:21.943389: val_loss -0.7762 +2024-11-23 04:25:21.943463: Pseudo dice [0.8625] +2024-11-23 04:25:21.943544: Epoch time: 17.54 s +2024-11-23 04:25:22.863134: +2024-11-23 04:25:22.863371: Epoch 7751 +2024-11-23 04:25:22.863485: Current learning rate: 0.00044 +2024-11-23 04:25:41.694764: train_loss -0.833 +2024-11-23 04:25:41.697161: val_loss -0.7787 +2024-11-23 04:25:41.697250: Pseudo dice [0.8581] +2024-11-23 04:25:41.697332: Epoch time: 18.83 s +2024-11-23 04:25:42.786961: +2024-11-23 04:25:42.787221: Epoch 7752 +2024-11-23 04:25:42.787329: Current learning rate: 0.00044 +2024-11-23 04:26:00.763998: train_loss -0.8328 +2024-11-23 04:26:00.764241: val_loss -0.794 +2024-11-23 04:26:00.764316: Pseudo dice [0.8591] +2024-11-23 04:26:00.764390: Epoch time: 17.98 s +2024-11-23 04:26:01.685758: +2024-11-23 04:26:01.685984: Epoch 7753 +2024-11-23 04:26:01.686095: Current learning rate: 0.00044 +2024-11-23 04:26:20.346088: train_loss -0.8356 +2024-11-23 04:26:20.346309: val_loss -0.7735 +2024-11-23 04:26:20.346387: Pseudo dice [0.8511] +2024-11-23 04:26:20.346463: Epoch time: 18.66 s +2024-11-23 04:26:21.272985: +2024-11-23 04:26:21.273220: Epoch 7754 +2024-11-23 04:26:21.273335: Current learning rate: 0.00044 +2024-11-23 04:26:40.386621: train_loss -0.8328 +2024-11-23 04:26:40.386869: val_loss -0.7682 +2024-11-23 04:26:40.386943: Pseudo dice [0.8501] +2024-11-23 04:26:40.387034: Epoch time: 19.11 s +2024-11-23 04:26:41.315096: +2024-11-23 04:26:41.315321: Epoch 7755 +2024-11-23 04:26:41.315429: Current learning rate: 0.00043 +2024-11-23 04:27:00.433651: train_loss -0.8316 +2024-11-23 04:27:00.433865: val_loss -0.8008 +2024-11-23 04:27:00.433942: Pseudo dice [0.8642] +2024-11-23 04:27:00.434020: Epoch time: 19.12 s +2024-11-23 04:27:01.358179: +2024-11-23 04:27:01.358418: Epoch 7756 +2024-11-23 04:27:01.358526: Current learning rate: 0.00043 +2024-11-23 04:27:20.534950: train_loss -0.8366 +2024-11-23 04:27:20.537409: val_loss -0.7769 +2024-11-23 04:27:20.537495: Pseudo dice [0.8309] +2024-11-23 04:27:20.537575: Epoch time: 19.18 s +2024-11-23 04:27:21.517147: +2024-11-23 04:27:21.517377: Epoch 7757 +2024-11-23 04:27:21.517489: Current learning rate: 0.00043 +2024-11-23 04:27:37.949973: train_loss -0.834 +2024-11-23 04:27:37.950497: val_loss -0.7726 +2024-11-23 04:27:37.950601: Pseudo dice [0.8473] +2024-11-23 04:27:37.950677: Epoch time: 16.43 s +2024-11-23 04:27:38.992882: +2024-11-23 04:27:38.993115: Epoch 7758 +2024-11-23 04:27:38.993226: Current learning rate: 0.00043 +2024-11-23 04:27:57.592363: train_loss -0.8339 +2024-11-23 04:27:57.592635: val_loss -0.7738 +2024-11-23 04:27:57.592709: Pseudo dice [0.8612] +2024-11-23 04:27:57.592790: Epoch time: 18.6 s +2024-11-23 04:27:58.601503: +2024-11-23 04:27:58.601855: Epoch 7759 +2024-11-23 04:27:58.601963: Current learning rate: 0.00043 +2024-11-23 04:28:17.078862: train_loss -0.8405 +2024-11-23 04:28:17.079085: val_loss -0.7754 +2024-11-23 04:28:17.079180: Pseudo dice [0.8537] +2024-11-23 04:28:17.079256: Epoch time: 18.48 s +2024-11-23 04:28:18.342884: +2024-11-23 04:28:18.343140: Epoch 7760 +2024-11-23 04:28:18.343277: Current learning rate: 0.00043 +2024-11-23 04:28:37.570015: train_loss -0.8381 +2024-11-23 04:28:37.570255: val_loss -0.7721 +2024-11-23 04:28:37.570341: Pseudo dice [0.8532] +2024-11-23 04:28:37.570417: Epoch time: 19.23 s +2024-11-23 04:28:38.491864: +2024-11-23 04:28:38.492102: Epoch 7761 +2024-11-23 04:28:38.492214: Current learning rate: 0.00042 +2024-11-23 04:28:56.950297: train_loss -0.8298 +2024-11-23 04:28:56.950524: val_loss -0.7614 +2024-11-23 04:28:56.950597: Pseudo dice [0.8489] +2024-11-23 04:28:56.950675: Epoch time: 18.46 s +2024-11-23 04:28:57.880103: +2024-11-23 04:28:57.880410: Epoch 7762 +2024-11-23 04:28:57.880563: Current learning rate: 0.00042 +2024-11-23 04:29:15.755298: train_loss -0.8397 +2024-11-23 04:29:15.755564: val_loss -0.7863 +2024-11-23 04:29:15.755659: Pseudo dice [0.8572] +2024-11-23 04:29:15.755738: Epoch time: 17.88 s +2024-11-23 04:29:16.685299: +2024-11-23 04:29:16.685533: Epoch 7763 +2024-11-23 04:29:16.685648: Current learning rate: 0.00042 +2024-11-23 04:29:34.603841: train_loss -0.8343 +2024-11-23 04:29:34.610153: val_loss -0.7701 +2024-11-23 04:29:34.610282: Pseudo dice [0.8508] +2024-11-23 04:29:34.610361: Epoch time: 17.92 s +2024-11-23 04:29:35.532768: +2024-11-23 04:29:35.532971: Epoch 7764 +2024-11-23 04:29:35.533090: Current learning rate: 0.00042 +2024-11-23 04:29:54.503702: train_loss -0.8393 +2024-11-23 04:29:54.503929: val_loss -0.7786 +2024-11-23 04:29:54.504011: Pseudo dice [0.874] +2024-11-23 04:29:54.504098: Epoch time: 18.97 s +2024-11-23 04:29:55.433138: +2024-11-23 04:29:55.433353: Epoch 7765 +2024-11-23 04:29:55.433465: Current learning rate: 0.00042 +2024-11-23 04:30:13.869588: train_loss -0.8371 +2024-11-23 04:30:13.870522: val_loss -0.7587 +2024-11-23 04:30:13.870601: Pseudo dice [0.8381] +2024-11-23 04:30:13.870683: Epoch time: 18.44 s +2024-11-23 04:30:14.795811: +2024-11-23 04:30:14.796067: Epoch 7766 +2024-11-23 04:30:14.796184: Current learning rate: 0.00042 +2024-11-23 04:30:33.036357: train_loss -0.8403 +2024-11-23 04:30:33.036597: val_loss -0.7828 +2024-11-23 04:30:33.036677: Pseudo dice [0.8468] +2024-11-23 04:30:33.036757: Epoch time: 18.24 s +2024-11-23 04:30:33.953566: +2024-11-23 04:30:33.953795: Epoch 7767 +2024-11-23 04:30:33.953900: Current learning rate: 0.00041 +2024-11-23 04:30:53.074611: train_loss -0.8346 +2024-11-23 04:30:53.074827: val_loss -0.7717 +2024-11-23 04:30:53.074900: Pseudo dice [0.86] +2024-11-23 04:30:53.074977: Epoch time: 19.12 s +2024-11-23 04:30:53.999064: +2024-11-23 04:30:53.999284: Epoch 7768 +2024-11-23 04:30:53.999392: Current learning rate: 0.00041 +2024-11-23 04:31:12.505805: train_loss -0.8367 +2024-11-23 04:31:12.506037: val_loss -0.7748 +2024-11-23 04:31:12.506112: Pseudo dice [0.8487] +2024-11-23 04:31:12.506190: Epoch time: 18.51 s +2024-11-23 04:31:13.436158: +2024-11-23 04:31:13.436370: Epoch 7769 +2024-11-23 04:31:13.436479: Current learning rate: 0.00041 +2024-11-23 04:31:31.765023: train_loss -0.8365 +2024-11-23 04:31:31.765240: val_loss -0.7887 +2024-11-23 04:31:31.765332: Pseudo dice [0.8415] +2024-11-23 04:31:31.765414: Epoch time: 18.33 s +2024-11-23 04:31:32.694094: +2024-11-23 04:31:32.694383: Epoch 7770 +2024-11-23 04:31:32.694505: Current learning rate: 0.00041 +2024-11-23 04:31:51.098749: train_loss -0.8375 +2024-11-23 04:31:51.099057: val_loss -0.7833 +2024-11-23 04:31:51.099138: Pseudo dice [0.8424] +2024-11-23 04:31:51.099216: Epoch time: 18.41 s +2024-11-23 04:31:52.459946: +2024-11-23 04:31:52.460166: Epoch 7771 +2024-11-23 04:31:52.460283: Current learning rate: 0.00041 +2024-11-23 04:32:11.288867: train_loss -0.8405 +2024-11-23 04:32:11.289110: val_loss -0.7815 +2024-11-23 04:32:11.289190: Pseudo dice [0.8562] +2024-11-23 04:32:11.289265: Epoch time: 18.83 s +2024-11-23 04:32:12.211041: +2024-11-23 04:32:12.211277: Epoch 7772 +2024-11-23 04:32:12.211389: Current learning rate: 0.00041 +2024-11-23 04:32:31.109937: train_loss -0.8391 +2024-11-23 04:32:31.110222: val_loss -0.7937 +2024-11-23 04:32:31.110302: Pseudo dice [0.8772] +2024-11-23 04:32:31.110377: Epoch time: 18.9 s +2024-11-23 04:32:32.036725: +2024-11-23 04:32:32.036949: Epoch 7773 +2024-11-23 04:32:32.037064: Current learning rate: 0.00041 +2024-11-23 04:32:49.977764: train_loss -0.8436 +2024-11-23 04:32:49.978056: val_loss -0.771 +2024-11-23 04:32:49.978148: Pseudo dice [0.8553] +2024-11-23 04:32:49.978230: Epoch time: 17.94 s +2024-11-23 04:32:50.903421: +2024-11-23 04:32:50.903694: Epoch 7774 +2024-11-23 04:32:50.903810: Current learning rate: 0.0004 +2024-11-23 04:33:10.027525: train_loss -0.839 +2024-11-23 04:33:10.027785: val_loss -0.7962 +2024-11-23 04:33:10.027896: Pseudo dice [0.8658] +2024-11-23 04:33:10.027977: Epoch time: 19.12 s +2024-11-23 04:33:10.953818: +2024-11-23 04:33:10.954057: Epoch 7775 +2024-11-23 04:33:10.954168: Current learning rate: 0.0004 +2024-11-23 04:33:29.946888: train_loss -0.8442 +2024-11-23 04:33:29.947104: val_loss -0.7748 +2024-11-23 04:33:29.947178: Pseudo dice [0.8502] +2024-11-23 04:33:29.947253: Epoch time: 18.99 s +2024-11-23 04:33:30.873888: +2024-11-23 04:33:30.874125: Epoch 7776 +2024-11-23 04:33:30.874236: Current learning rate: 0.0004 +2024-11-23 04:33:50.484342: train_loss -0.8285 +2024-11-23 04:33:50.484556: val_loss -0.8017 +2024-11-23 04:33:50.484632: Pseudo dice [0.8603] +2024-11-23 04:33:50.484705: Epoch time: 19.61 s +2024-11-23 04:33:51.406147: +2024-11-23 04:33:51.406347: Epoch 7777 +2024-11-23 04:33:51.406454: Current learning rate: 0.0004 +2024-11-23 04:34:09.520260: train_loss -0.8384 +2024-11-23 04:34:09.520513: val_loss -0.7554 +2024-11-23 04:34:09.520586: Pseudo dice [0.8312] +2024-11-23 04:34:09.520665: Epoch time: 18.11 s +2024-11-23 04:34:10.630933: +2024-11-23 04:34:10.631169: Epoch 7778 +2024-11-23 04:34:10.631278: Current learning rate: 0.0004 +2024-11-23 04:34:28.906927: train_loss -0.8369 +2024-11-23 04:34:28.907155: val_loss -0.8069 +2024-11-23 04:34:28.907230: Pseudo dice [0.8742] +2024-11-23 04:34:28.907306: Epoch time: 18.28 s +2024-11-23 04:34:29.930483: +2024-11-23 04:34:29.930705: Epoch 7779 +2024-11-23 04:34:29.930812: Current learning rate: 0.0004 +2024-11-23 04:34:48.430295: train_loss -0.8371 +2024-11-23 04:34:48.434766: val_loss -0.793 +2024-11-23 04:34:48.434900: Pseudo dice [0.8679] +2024-11-23 04:34:48.434981: Epoch time: 18.5 s +2024-11-23 04:34:49.469928: +2024-11-23 04:34:49.470138: Epoch 7780 +2024-11-23 04:34:49.470248: Current learning rate: 0.00039 +2024-11-23 04:35:08.908236: train_loss -0.832 +2024-11-23 04:35:08.908453: val_loss -0.7663 +2024-11-23 04:35:08.908533: Pseudo dice [0.8542] +2024-11-23 04:35:08.910854: Epoch time: 19.44 s +2024-11-23 04:35:09.839373: +2024-11-23 04:35:09.839677: Epoch 7781 +2024-11-23 04:35:09.839792: Current learning rate: 0.00039 +2024-11-23 04:35:29.332913: train_loss -0.8426 +2024-11-23 04:35:29.333157: val_loss -0.7865 +2024-11-23 04:35:29.333237: Pseudo dice [0.8519] +2024-11-23 04:35:29.333317: Epoch time: 19.49 s +2024-11-23 04:35:30.256464: +2024-11-23 04:35:30.256693: Epoch 7782 +2024-11-23 04:35:30.256802: Current learning rate: 0.00039 +2024-11-23 04:35:47.293170: train_loss -0.8361 +2024-11-23 04:35:47.293384: val_loss -0.784 +2024-11-23 04:35:47.293463: Pseudo dice [0.8708] +2024-11-23 04:35:47.293539: Epoch time: 17.04 s +2024-11-23 04:35:48.609606: +2024-11-23 04:35:48.609874: Epoch 7783 +2024-11-23 04:35:48.609986: Current learning rate: 0.00039 +2024-11-23 04:36:06.826723: train_loss -0.8353 +2024-11-23 04:36:06.827009: val_loss -0.7978 +2024-11-23 04:36:06.827091: Pseudo dice [0.8609] +2024-11-23 04:36:06.827170: Epoch time: 18.22 s +2024-11-23 04:36:07.745468: +2024-11-23 04:36:07.745691: Epoch 7784 +2024-11-23 04:36:07.745801: Current learning rate: 0.00039 +2024-11-23 04:36:26.579543: train_loss -0.8389 +2024-11-23 04:36:26.579793: val_loss -0.7838 +2024-11-23 04:36:26.579919: Pseudo dice [0.8517] +2024-11-23 04:36:26.580009: Epoch time: 18.83 s +2024-11-23 04:36:27.509114: +2024-11-23 04:36:27.509420: Epoch 7785 +2024-11-23 04:36:27.509540: Current learning rate: 0.00039 +2024-11-23 04:36:45.807654: train_loss -0.8342 +2024-11-23 04:36:45.807956: val_loss -0.7914 +2024-11-23 04:36:45.808040: Pseudo dice [0.8668] +2024-11-23 04:36:45.808114: Epoch time: 18.3 s +2024-11-23 04:36:46.736709: +2024-11-23 04:36:46.737005: Epoch 7786 +2024-11-23 04:36:46.737114: Current learning rate: 0.00038 +2024-11-23 04:37:05.748404: train_loss -0.8356 +2024-11-23 04:37:05.748612: val_loss -0.7694 +2024-11-23 04:37:05.748685: Pseudo dice [0.8502] +2024-11-23 04:37:05.753906: Epoch time: 19.01 s +2024-11-23 04:37:06.809914: +2024-11-23 04:37:06.810153: Epoch 7787 +2024-11-23 04:37:06.810258: Current learning rate: 0.00038 +2024-11-23 04:37:25.091698: train_loss -0.8346 +2024-11-23 04:37:25.091935: val_loss -0.766 +2024-11-23 04:37:25.092093: Pseudo dice [0.8553] +2024-11-23 04:37:25.092171: Epoch time: 18.28 s +2024-11-23 04:37:26.041203: +2024-11-23 04:37:26.041428: Epoch 7788 +2024-11-23 04:37:26.041542: Current learning rate: 0.00038 +2024-11-23 04:37:44.257814: train_loss -0.8341 +2024-11-23 04:37:44.258042: val_loss -0.7835 +2024-11-23 04:37:44.258117: Pseudo dice [0.8467] +2024-11-23 04:37:44.258192: Epoch time: 18.22 s +2024-11-23 04:37:45.213900: +2024-11-23 04:37:45.214153: Epoch 7789 +2024-11-23 04:37:45.214266: Current learning rate: 0.00038 +2024-11-23 04:38:03.608022: train_loss -0.8346 +2024-11-23 04:38:03.608250: val_loss -0.7688 +2024-11-23 04:38:03.610508: Pseudo dice [0.8566] +2024-11-23 04:38:03.610617: Epoch time: 18.39 s +2024-11-23 04:38:04.582198: +2024-11-23 04:38:04.582444: Epoch 7790 +2024-11-23 04:38:04.582557: Current learning rate: 0.00038 +2024-11-23 04:38:23.095353: train_loss -0.837 +2024-11-23 04:38:23.095572: val_loss -0.777 +2024-11-23 04:38:23.095649: Pseudo dice [0.8483] +2024-11-23 04:38:23.095746: Epoch time: 18.51 s +2024-11-23 04:38:24.070276: +2024-11-23 04:38:24.070500: Epoch 7791 +2024-11-23 04:38:24.070621: Current learning rate: 0.00038 +2024-11-23 04:38:42.681962: train_loss -0.8392 +2024-11-23 04:38:42.682199: val_loss -0.7819 +2024-11-23 04:38:42.682277: Pseudo dice [0.842] +2024-11-23 04:38:42.682368: Epoch time: 18.61 s +2024-11-23 04:38:43.609557: +2024-11-23 04:38:43.609786: Epoch 7792 +2024-11-23 04:38:43.609898: Current learning rate: 0.00037 +2024-11-23 04:39:03.924456: train_loss -0.8386 +2024-11-23 04:39:03.929225: val_loss -0.7873 +2024-11-23 04:39:03.929383: Pseudo dice [0.8528] +2024-11-23 04:39:03.929472: Epoch time: 20.32 s +2024-11-23 04:39:04.882841: +2024-11-23 04:39:04.883094: Epoch 7793 +2024-11-23 04:39:04.883216: Current learning rate: 0.00037 +2024-11-23 04:39:23.132129: train_loss -0.8418 +2024-11-23 04:39:23.132358: val_loss -0.7791 +2024-11-23 04:39:23.132436: Pseudo dice [0.8613] +2024-11-23 04:39:23.132516: Epoch time: 18.25 s +2024-11-23 04:39:24.560687: +2024-11-23 04:39:24.560919: Epoch 7794 +2024-11-23 04:39:24.561034: Current learning rate: 0.00037 +2024-11-23 04:39:43.381075: train_loss -0.8374 +2024-11-23 04:39:43.386464: val_loss -0.7739 +2024-11-23 04:39:43.386582: Pseudo dice [0.8426] +2024-11-23 04:39:43.386667: Epoch time: 18.82 s +2024-11-23 04:39:44.330211: +2024-11-23 04:39:44.330452: Epoch 7795 +2024-11-23 04:39:44.330567: Current learning rate: 0.00037 +2024-11-23 04:40:02.658083: train_loss -0.8401 +2024-11-23 04:40:02.658296: val_loss -0.78 +2024-11-23 04:40:02.658370: Pseudo dice [0.843] +2024-11-23 04:40:02.658444: Epoch time: 18.33 s +2024-11-23 04:40:03.584888: +2024-11-23 04:40:03.585199: Epoch 7796 +2024-11-23 04:40:03.585313: Current learning rate: 0.00037 +2024-11-23 04:40:22.534334: train_loss -0.8437 +2024-11-23 04:40:22.534589: val_loss -0.7993 +2024-11-23 04:40:22.534670: Pseudo dice [0.8571] +2024-11-23 04:40:22.534876: Epoch time: 18.95 s +2024-11-23 04:40:23.462823: +2024-11-23 04:40:23.463157: Epoch 7797 +2024-11-23 04:40:23.463272: Current learning rate: 0.00037 +2024-11-23 04:40:41.191760: train_loss -0.8356 +2024-11-23 04:40:41.191977: val_loss -0.7837 +2024-11-23 04:40:41.192055: Pseudo dice [0.8596] +2024-11-23 04:40:41.192127: Epoch time: 17.73 s +2024-11-23 04:40:42.114883: +2024-11-23 04:40:42.115090: Epoch 7798 +2024-11-23 04:40:42.115200: Current learning rate: 0.00036 +2024-11-23 04:41:00.368962: train_loss -0.835 +2024-11-23 04:41:00.369184: val_loss -0.7907 +2024-11-23 04:41:00.369265: Pseudo dice [0.8379] +2024-11-23 04:41:00.369339: Epoch time: 18.25 s +2024-11-23 04:41:01.298597: +2024-11-23 04:41:01.298838: Epoch 7799 +2024-11-23 04:41:01.298950: Current learning rate: 0.00036 +2024-11-23 04:41:20.150225: train_loss -0.8418 +2024-11-23 04:41:20.150441: val_loss -0.7572 +2024-11-23 04:41:20.150514: Pseudo dice [0.8441] +2024-11-23 04:41:20.150586: Epoch time: 18.85 s +2024-11-23 04:41:21.433146: +2024-11-23 04:41:21.433390: Epoch 7800 +2024-11-23 04:41:21.433507: Current learning rate: 0.00036 +2024-11-23 04:41:39.805081: train_loss -0.8358 +2024-11-23 04:41:39.805393: val_loss -0.76 +2024-11-23 04:41:39.805475: Pseudo dice [0.8263] +2024-11-23 04:41:39.805575: Epoch time: 18.37 s +2024-11-23 04:41:40.732967: +2024-11-23 04:41:40.733180: Epoch 7801 +2024-11-23 04:41:40.733289: Current learning rate: 0.00036 +2024-11-23 04:41:59.258018: train_loss -0.8302 +2024-11-23 04:41:59.258250: val_loss -0.7969 +2024-11-23 04:41:59.258337: Pseudo dice [0.8685] +2024-11-23 04:41:59.258417: Epoch time: 18.53 s +2024-11-23 04:42:00.184981: +2024-11-23 04:42:00.185209: Epoch 7802 +2024-11-23 04:42:00.185318: Current learning rate: 0.00036 +2024-11-23 04:42:19.102873: train_loss -0.8422 +2024-11-23 04:42:19.103129: val_loss -0.7528 +2024-11-23 04:42:19.103204: Pseudo dice [0.843] +2024-11-23 04:42:19.103277: Epoch time: 18.92 s +2024-11-23 04:42:20.019814: +2024-11-23 04:42:20.020032: Epoch 7803 +2024-11-23 04:42:20.020145: Current learning rate: 0.00036 +2024-11-23 04:42:40.023485: train_loss -0.8324 +2024-11-23 04:42:40.023709: val_loss -0.7945 +2024-11-23 04:42:40.023787: Pseudo dice [0.8488] +2024-11-23 04:42:40.023864: Epoch time: 20.0 s +2024-11-23 04:42:40.944669: +2024-11-23 04:42:40.944876: Epoch 7804 +2024-11-23 04:42:40.944989: Current learning rate: 0.00036 +2024-11-23 04:42:59.791890: train_loss -0.8375 +2024-11-23 04:42:59.792136: val_loss -0.7944 +2024-11-23 04:42:59.792209: Pseudo dice [0.8512] +2024-11-23 04:42:59.792282: Epoch time: 18.85 s +2024-11-23 04:43:01.255424: +2024-11-23 04:43:01.255682: Epoch 7805 +2024-11-23 04:43:01.255796: Current learning rate: 0.00035 +2024-11-23 04:43:20.056623: train_loss -0.8351 +2024-11-23 04:43:20.056844: val_loss -0.782 +2024-11-23 04:43:20.056927: Pseudo dice [0.8395] +2024-11-23 04:43:20.057022: Epoch time: 18.8 s +2024-11-23 04:43:20.980636: +2024-11-23 04:43:20.980874: Epoch 7806 +2024-11-23 04:43:20.980985: Current learning rate: 0.00035 +2024-11-23 04:43:39.623328: train_loss -0.8388 +2024-11-23 04:43:39.623557: val_loss -0.7887 +2024-11-23 04:43:39.623630: Pseudo dice [0.8546] +2024-11-23 04:43:39.623706: Epoch time: 18.64 s +2024-11-23 04:43:40.733545: +2024-11-23 04:43:40.733757: Epoch 7807 +2024-11-23 04:43:40.733862: Current learning rate: 0.00035 +2024-11-23 04:43:59.592151: train_loss -0.8358 +2024-11-23 04:43:59.592382: val_loss -0.7947 +2024-11-23 04:43:59.592458: Pseudo dice [0.8504] +2024-11-23 04:43:59.592539: Epoch time: 18.86 s +2024-11-23 04:44:00.521973: +2024-11-23 04:44:00.522190: Epoch 7808 +2024-11-23 04:44:00.522296: Current learning rate: 0.00035 +2024-11-23 04:44:19.390822: train_loss -0.8483 +2024-11-23 04:44:19.391071: val_loss -0.8078 +2024-11-23 04:44:19.391150: Pseudo dice [0.8602] +2024-11-23 04:44:19.391227: Epoch time: 18.87 s +2024-11-23 04:44:20.326069: +2024-11-23 04:44:20.326363: Epoch 7809 +2024-11-23 04:44:20.326483: Current learning rate: 0.00035 +2024-11-23 04:44:38.632087: train_loss -0.8423 +2024-11-23 04:44:38.632332: val_loss -0.783 +2024-11-23 04:44:38.632406: Pseudo dice [0.8523] +2024-11-23 04:44:38.632482: Epoch time: 18.31 s +2024-11-23 04:44:39.593399: +2024-11-23 04:44:39.593632: Epoch 7810 +2024-11-23 04:44:39.593743: Current learning rate: 0.00035 +2024-11-23 04:44:58.030966: train_loss -0.8328 +2024-11-23 04:44:58.031192: val_loss -0.7785 +2024-11-23 04:44:58.031265: Pseudo dice [0.8441] +2024-11-23 04:44:58.031341: Epoch time: 18.44 s +2024-11-23 04:44:58.959520: +2024-11-23 04:44:58.959744: Epoch 7811 +2024-11-23 04:44:58.959862: Current learning rate: 0.00034 +2024-11-23 04:45:16.837327: train_loss -0.8371 +2024-11-23 04:45:16.837569: val_loss -0.8013 +2024-11-23 04:45:16.837641: Pseudo dice [0.8603] +2024-11-23 04:45:16.837719: Epoch time: 17.88 s +2024-11-23 04:45:17.761077: +2024-11-23 04:45:17.761309: Epoch 7812 +2024-11-23 04:45:17.761426: Current learning rate: 0.00034 +2024-11-23 04:45:36.873509: train_loss -0.8287 +2024-11-23 04:45:36.873725: val_loss -0.7924 +2024-11-23 04:45:36.873798: Pseudo dice [0.8582] +2024-11-23 04:45:36.873873: Epoch time: 19.11 s +2024-11-23 04:45:37.825188: +2024-11-23 04:45:37.825433: Epoch 7813 +2024-11-23 04:45:37.825553: Current learning rate: 0.00034 +2024-11-23 04:45:56.649253: train_loss -0.8369 +2024-11-23 04:45:56.649501: val_loss -0.7862 +2024-11-23 04:45:56.649608: Pseudo dice [0.8645] +2024-11-23 04:45:56.649689: Epoch time: 18.82 s +2024-11-23 04:45:57.585713: +2024-11-23 04:45:57.585949: Epoch 7814 +2024-11-23 04:45:57.586066: Current learning rate: 0.00034 +2024-11-23 04:46:15.671268: train_loss -0.8386 +2024-11-23 04:46:15.671504: val_loss -0.7998 +2024-11-23 04:46:15.671601: Pseudo dice [0.8571] +2024-11-23 04:46:15.671682: Epoch time: 18.09 s +2024-11-23 04:46:16.596997: +2024-11-23 04:46:16.597212: Epoch 7815 +2024-11-23 04:46:16.597325: Current learning rate: 0.00034 +2024-11-23 04:46:34.825477: train_loss -0.8385 +2024-11-23 04:46:34.825716: val_loss -0.806 +2024-11-23 04:46:34.825789: Pseudo dice [0.8689] +2024-11-23 04:46:34.825881: Epoch time: 18.23 s +2024-11-23 04:46:35.743193: +2024-11-23 04:46:35.743418: Epoch 7816 +2024-11-23 04:46:35.743527: Current learning rate: 0.00034 +2024-11-23 04:46:52.802014: train_loss -0.842 +2024-11-23 04:46:52.802231: val_loss -0.7894 +2024-11-23 04:46:52.802305: Pseudo dice [0.8733] +2024-11-23 04:46:52.802377: Epoch time: 17.06 s +2024-11-23 04:46:54.161644: +2024-11-23 04:46:54.161879: Epoch 7817 +2024-11-23 04:46:54.162007: Current learning rate: 0.00033 +2024-11-23 04:47:13.033906: train_loss -0.8411 +2024-11-23 04:47:13.034159: val_loss -0.8021 +2024-11-23 04:47:13.034242: Pseudo dice [0.8553] +2024-11-23 04:47:13.034324: Epoch time: 18.87 s +2024-11-23 04:47:14.045099: +2024-11-23 04:47:14.045335: Epoch 7818 +2024-11-23 04:47:14.045442: Current learning rate: 0.00033 +2024-11-23 04:47:31.642632: train_loss -0.8421 +2024-11-23 04:47:31.642878: val_loss -0.7676 +2024-11-23 04:47:31.642969: Pseudo dice [0.8524] +2024-11-23 04:47:31.643109: Epoch time: 17.6 s +2024-11-23 04:47:32.566924: +2024-11-23 04:47:32.567185: Epoch 7819 +2024-11-23 04:47:32.567298: Current learning rate: 0.00033 +2024-11-23 04:47:51.767899: train_loss -0.8328 +2024-11-23 04:47:51.773310: val_loss -0.7776 +2024-11-23 04:47:51.773451: Pseudo dice [0.8595] +2024-11-23 04:47:51.773537: Epoch time: 19.2 s +2024-11-23 04:47:52.788983: +2024-11-23 04:47:52.789192: Epoch 7820 +2024-11-23 04:47:52.789296: Current learning rate: 0.00033 +2024-11-23 04:48:11.823364: train_loss -0.8339 +2024-11-23 04:48:11.823585: val_loss -0.7588 +2024-11-23 04:48:11.823661: Pseudo dice [0.8629] +2024-11-23 04:48:11.823734: Epoch time: 19.04 s +2024-11-23 04:48:12.743181: +2024-11-23 04:48:12.743477: Epoch 7821 +2024-11-23 04:48:12.743587: Current learning rate: 0.00033 +2024-11-23 04:48:32.252557: train_loss -0.8353 +2024-11-23 04:48:32.252774: val_loss -0.7685 +2024-11-23 04:48:32.252848: Pseudo dice [0.8492] +2024-11-23 04:48:32.252922: Epoch time: 19.51 s +2024-11-23 04:48:33.175619: +2024-11-23 04:48:33.176038: Epoch 7822 +2024-11-23 04:48:33.176151: Current learning rate: 0.00033 +2024-11-23 04:48:50.675831: train_loss -0.8372 +2024-11-23 04:48:50.681249: val_loss -0.7584 +2024-11-23 04:48:50.681371: Pseudo dice [0.8391] +2024-11-23 04:48:50.681462: Epoch time: 17.5 s +2024-11-23 04:48:51.717383: +2024-11-23 04:48:51.717653: Epoch 7823 +2024-11-23 04:48:51.717767: Current learning rate: 0.00032 +2024-11-23 04:49:09.378280: train_loss -0.8396 +2024-11-23 04:49:09.378507: val_loss -0.7519 +2024-11-23 04:49:09.378580: Pseudo dice [0.8542] +2024-11-23 04:49:09.378654: Epoch time: 17.66 s +2024-11-23 04:49:10.303168: +2024-11-23 04:49:10.303402: Epoch 7824 +2024-11-23 04:49:10.303511: Current learning rate: 0.00032 +2024-11-23 04:49:28.551056: train_loss -0.838 +2024-11-23 04:49:28.551325: val_loss -0.7826 +2024-11-23 04:49:28.551399: Pseudo dice [0.853] +2024-11-23 04:49:28.551472: Epoch time: 18.25 s +2024-11-23 04:49:29.535817: +2024-11-23 04:49:29.536029: Epoch 7825 +2024-11-23 04:49:29.536141: Current learning rate: 0.00032 +2024-11-23 04:49:48.636287: train_loss -0.8412 +2024-11-23 04:49:48.636510: val_loss -0.7953 +2024-11-23 04:49:48.636585: Pseudo dice [0.8712] +2024-11-23 04:49:48.636661: Epoch time: 19.1 s +2024-11-23 04:49:49.570425: +2024-11-23 04:49:49.570645: Epoch 7826 +2024-11-23 04:49:49.570760: Current learning rate: 0.00032 +2024-11-23 04:50:08.053074: train_loss -0.8361 +2024-11-23 04:50:08.053311: val_loss -0.7842 +2024-11-23 04:50:08.053384: Pseudo dice [0.8706] +2024-11-23 04:50:08.053462: Epoch time: 18.48 s +2024-11-23 04:50:08.976851: +2024-11-23 04:50:08.977157: Epoch 7827 +2024-11-23 04:50:08.977267: Current learning rate: 0.00032 +2024-11-23 04:50:28.267199: train_loss -0.8364 +2024-11-23 04:50:28.267417: val_loss -0.8001 +2024-11-23 04:50:28.267491: Pseudo dice [0.8548] +2024-11-23 04:50:28.267564: Epoch time: 19.29 s +2024-11-23 04:50:29.501296: +2024-11-23 04:50:29.501743: Epoch 7828 +2024-11-23 04:50:29.501874: Current learning rate: 0.00032 +2024-11-23 04:50:48.412211: train_loss -0.8404 +2024-11-23 04:50:48.412430: val_loss -0.785 +2024-11-23 04:50:48.412509: Pseudo dice [0.8542] +2024-11-23 04:50:48.412583: Epoch time: 18.91 s +2024-11-23 04:50:49.332285: +2024-11-23 04:50:49.332718: Epoch 7829 +2024-11-23 04:50:49.332846: Current learning rate: 0.00031 +2024-11-23 04:51:08.313924: train_loss -0.8356 +2024-11-23 04:51:08.314163: val_loss -0.7878 +2024-11-23 04:51:08.314248: Pseudo dice [0.8613] +2024-11-23 04:51:08.314325: Epoch time: 18.98 s +2024-11-23 04:51:09.243492: +2024-11-23 04:51:09.243958: Epoch 7830 +2024-11-23 04:51:09.244092: Current learning rate: 0.00031 +2024-11-23 04:51:26.778666: train_loss -0.8423 +2024-11-23 04:51:26.778893: val_loss -0.7655 +2024-11-23 04:51:26.778968: Pseudo dice [0.8548] +2024-11-23 04:51:26.779053: Epoch time: 17.54 s +2024-11-23 04:51:27.731138: +2024-11-23 04:51:27.731579: Epoch 7831 +2024-11-23 04:51:27.731710: Current learning rate: 0.00031 +2024-11-23 04:51:46.432224: train_loss -0.84 +2024-11-23 04:51:46.432484: val_loss -0.7861 +2024-11-23 04:51:46.432568: Pseudo dice [0.86] +2024-11-23 04:51:46.432641: Epoch time: 18.7 s +2024-11-23 04:51:47.357456: +2024-11-23 04:51:47.357885: Epoch 7832 +2024-11-23 04:51:47.358019: Current learning rate: 0.00031 +2024-11-23 04:52:04.463298: train_loss -0.8377 +2024-11-23 04:52:04.463537: val_loss -0.7867 +2024-11-23 04:52:04.463614: Pseudo dice [0.8588] +2024-11-23 04:52:04.463908: Epoch time: 17.11 s +2024-11-23 04:52:05.655153: +2024-11-23 04:52:05.655596: Epoch 7833 +2024-11-23 04:52:05.655729: Current learning rate: 0.00031 +2024-11-23 04:52:23.765480: train_loss -0.8418 +2024-11-23 04:52:23.765694: val_loss -0.8067 +2024-11-23 04:52:23.765768: Pseudo dice [0.8721] +2024-11-23 04:52:23.765846: Epoch time: 18.11 s +2024-11-23 04:52:24.699497: +2024-11-23 04:52:24.699959: Epoch 7834 +2024-11-23 04:52:24.700103: Current learning rate: 0.00031 +2024-11-23 04:52:42.112938: train_loss -0.8389 +2024-11-23 04:52:42.113185: val_loss -0.7901 +2024-11-23 04:52:42.113268: Pseudo dice [0.8545] +2024-11-23 04:52:42.113354: Epoch time: 17.41 s +2024-11-23 04:52:43.037397: +2024-11-23 04:52:43.037853: Epoch 7835 +2024-11-23 04:52:43.038167: Current learning rate: 0.0003 +2024-11-23 04:53:01.800726: train_loss -0.8342 +2024-11-23 04:53:01.800963: val_loss -0.7745 +2024-11-23 04:53:01.801047: Pseudo dice [0.8633] +2024-11-23 04:53:01.801119: Epoch time: 18.76 s +2024-11-23 04:53:02.720877: +2024-11-23 04:53:02.721307: Epoch 7836 +2024-11-23 04:53:02.721446: Current learning rate: 0.0003 +2024-11-23 04:53:20.895863: train_loss -0.8409 +2024-11-23 04:53:20.896089: val_loss -0.7883 +2024-11-23 04:53:20.896167: Pseudo dice [0.8716] +2024-11-23 04:53:20.896247: Epoch time: 18.18 s +2024-11-23 04:53:20.896314: Yayy! New best EMA pseudo Dice: 0.8603 +2024-11-23 04:53:22.193689: +2024-11-23 04:53:22.194041: Epoch 7837 +2024-11-23 04:53:22.194155: Current learning rate: 0.0003 +2024-11-23 04:53:40.886248: train_loss -0.8301 +2024-11-23 04:53:40.886547: val_loss -0.7662 +2024-11-23 04:53:40.886622: Pseudo dice [0.8342] +2024-11-23 04:53:40.886706: Epoch time: 18.69 s +2024-11-23 04:53:41.811904: +2024-11-23 04:53:41.812186: Epoch 7838 +2024-11-23 04:53:41.812296: Current learning rate: 0.0003 +2024-11-23 04:54:01.194942: train_loss -0.832 +2024-11-23 04:54:01.197364: val_loss -0.754 +2024-11-23 04:54:01.197499: Pseudo dice [0.8401] +2024-11-23 04:54:01.197577: Epoch time: 19.38 s +2024-11-23 04:54:02.499783: +2024-11-23 04:54:02.500035: Epoch 7839 +2024-11-23 04:54:02.500145: Current learning rate: 0.0003 +2024-11-23 04:54:21.230947: train_loss -0.8417 +2024-11-23 04:54:21.231179: val_loss -0.8012 +2024-11-23 04:54:21.231257: Pseudo dice [0.8599] +2024-11-23 04:54:21.231411: Epoch time: 18.73 s +2024-11-23 04:54:22.262061: +2024-11-23 04:54:22.262268: Epoch 7840 +2024-11-23 04:54:22.262375: Current learning rate: 0.0003 +2024-11-23 04:54:40.721519: train_loss -0.8392 +2024-11-23 04:54:40.721730: val_loss -0.7803 +2024-11-23 04:54:40.721805: Pseudo dice [0.8591] +2024-11-23 04:54:40.724063: Epoch time: 18.46 s +2024-11-23 04:54:41.797909: +2024-11-23 04:54:41.798218: Epoch 7841 +2024-11-23 04:54:41.798329: Current learning rate: 0.00029 +2024-11-23 04:55:00.764017: train_loss -0.8355 +2024-11-23 04:55:00.764287: val_loss -0.7659 +2024-11-23 04:55:00.764372: Pseudo dice [0.8376] +2024-11-23 04:55:00.764451: Epoch time: 18.97 s +2024-11-23 04:55:01.855462: +2024-11-23 04:55:01.855686: Epoch 7842 +2024-11-23 04:55:01.855795: Current learning rate: 0.00029 +2024-11-23 04:55:20.619581: train_loss -0.8398 +2024-11-23 04:55:20.619791: val_loss -0.7992 +2024-11-23 04:55:20.619865: Pseudo dice [0.8563] +2024-11-23 04:55:20.619936: Epoch time: 18.76 s +2024-11-23 04:55:21.569998: +2024-11-23 04:55:21.570246: Epoch 7843 +2024-11-23 04:55:21.570358: Current learning rate: 0.00029 +2024-11-23 04:55:39.523579: train_loss -0.8402 +2024-11-23 04:55:39.523798: val_loss -0.7831 +2024-11-23 04:55:39.523875: Pseudo dice [0.855] +2024-11-23 04:55:39.523948: Epoch time: 17.95 s +2024-11-23 04:55:40.466470: +2024-11-23 04:55:40.466703: Epoch 7844 +2024-11-23 04:55:40.466816: Current learning rate: 0.00029 +2024-11-23 04:55:58.704841: train_loss -0.831 +2024-11-23 04:55:58.705080: val_loss -0.7712 +2024-11-23 04:55:58.705161: Pseudo dice [0.8471] +2024-11-23 04:55:58.705233: Epoch time: 18.24 s +2024-11-23 04:55:59.635368: +2024-11-23 04:55:59.635586: Epoch 7845 +2024-11-23 04:55:59.635698: Current learning rate: 0.00029 +2024-11-23 04:56:17.426580: train_loss -0.837 +2024-11-23 04:56:17.426831: val_loss -0.7765 +2024-11-23 04:56:17.426906: Pseudo dice [0.8626] +2024-11-23 04:56:17.426987: Epoch time: 17.79 s +2024-11-23 04:56:18.351583: +2024-11-23 04:56:18.351798: Epoch 7846 +2024-11-23 04:56:18.351911: Current learning rate: 0.00029 +2024-11-23 04:56:36.443790: train_loss -0.8425 +2024-11-23 04:56:36.444014: val_loss -0.7581 +2024-11-23 04:56:36.444089: Pseudo dice [0.8548] +2024-11-23 04:56:36.444164: Epoch time: 18.09 s +2024-11-23 04:56:37.446400: +2024-11-23 04:56:37.446641: Epoch 7847 +2024-11-23 04:56:37.446782: Current learning rate: 0.00028 +2024-11-23 04:56:55.398912: train_loss -0.8329 +2024-11-23 04:56:55.399205: val_loss -0.7834 +2024-11-23 04:56:55.399278: Pseudo dice [0.8644] +2024-11-23 04:56:55.399351: Epoch time: 17.95 s +2024-11-23 04:56:56.327904: +2024-11-23 04:56:56.328198: Epoch 7848 +2024-11-23 04:56:56.328309: Current learning rate: 0.00028 +2024-11-23 04:57:14.716285: train_loss -0.8286 +2024-11-23 04:57:14.716510: val_loss -0.7926 +2024-11-23 04:57:14.716585: Pseudo dice [0.8534] +2024-11-23 04:57:14.716680: Epoch time: 18.39 s +2024-11-23 04:57:15.638069: +2024-11-23 04:57:15.638273: Epoch 7849 +2024-11-23 04:57:15.638383: Current learning rate: 0.00028 +2024-11-23 04:57:35.082272: train_loss -0.8411 +2024-11-23 04:57:35.082523: val_loss -0.781 +2024-11-23 04:57:35.082597: Pseudo dice [0.8658] +2024-11-23 04:57:35.082675: Epoch time: 19.45 s +2024-11-23 04:57:36.347410: +2024-11-23 04:57:36.347629: Epoch 7850 +2024-11-23 04:57:36.347739: Current learning rate: 0.00028 +2024-11-23 04:57:54.716574: train_loss -0.8335 +2024-11-23 04:57:54.716878: val_loss -0.7577 +2024-11-23 04:57:54.716958: Pseudo dice [0.861] +2024-11-23 04:57:54.717036: Epoch time: 18.37 s +2024-11-23 04:57:55.747447: +2024-11-23 04:57:55.747681: Epoch 7851 +2024-11-23 04:57:55.747790: Current learning rate: 0.00028 +2024-11-23 04:58:14.057641: train_loss -0.8372 +2024-11-23 04:58:14.057868: val_loss -0.792 +2024-11-23 04:58:14.057942: Pseudo dice [0.8609] +2024-11-23 04:58:14.058021: Epoch time: 18.31 s +2024-11-23 04:58:15.012129: +2024-11-23 04:58:15.012344: Epoch 7852 +2024-11-23 04:58:15.012449: Current learning rate: 0.00028 +2024-11-23 04:58:33.068545: train_loss -0.8385 +2024-11-23 04:58:33.068799: val_loss -0.7809 +2024-11-23 04:58:33.068884: Pseudo dice [0.8737] +2024-11-23 04:58:33.068966: Epoch time: 18.06 s +2024-11-23 04:58:33.996987: +2024-11-23 04:58:33.997216: Epoch 7853 +2024-11-23 04:58:33.997322: Current learning rate: 0.00027 +2024-11-23 04:58:52.591296: train_loss -0.8325 +2024-11-23 04:58:52.591515: val_loss -0.7941 +2024-11-23 04:58:52.591590: Pseudo dice [0.8538] +2024-11-23 04:58:52.591663: Epoch time: 18.6 s +2024-11-23 04:58:53.512073: +2024-11-23 04:58:53.512304: Epoch 7854 +2024-11-23 04:58:53.512426: Current learning rate: 0.00027 +2024-11-23 04:59:11.646767: train_loss -0.8336 +2024-11-23 04:59:11.649160: val_loss -0.7612 +2024-11-23 04:59:11.649243: Pseudo dice [0.8352] +2024-11-23 04:59:11.649320: Epoch time: 18.14 s +2024-11-23 04:59:12.741401: +2024-11-23 04:59:12.741621: Epoch 7855 +2024-11-23 04:59:12.741729: Current learning rate: 0.00027 +2024-11-23 04:59:31.519797: train_loss -0.8359 +2024-11-23 04:59:31.520011: val_loss -0.7905 +2024-11-23 04:59:31.520085: Pseudo dice [0.8733] +2024-11-23 04:59:31.520159: Epoch time: 18.78 s +2024-11-23 04:59:32.424788: +2024-11-23 04:59:32.424984: Epoch 7856 +2024-11-23 04:59:32.425091: Current learning rate: 0.00027 +2024-11-23 04:59:50.870615: train_loss -0.8433 +2024-11-23 04:59:50.870860: val_loss -0.8018 +2024-11-23 04:59:50.870935: Pseudo dice [0.8543] +2024-11-23 04:59:50.871027: Epoch time: 18.45 s +2024-11-23 04:59:51.802835: +2024-11-23 04:59:51.803047: Epoch 7857 +2024-11-23 04:59:51.803162: Current learning rate: 0.00027 +2024-11-23 05:00:09.438725: train_loss -0.8379 +2024-11-23 05:00:09.438943: val_loss -0.7828 +2024-11-23 05:00:09.439025: Pseudo dice [0.8804] +2024-11-23 05:00:09.439100: Epoch time: 17.64 s +2024-11-23 05:00:10.484070: +2024-11-23 05:00:10.484322: Epoch 7858 +2024-11-23 05:00:10.484445: Current learning rate: 0.00027 +2024-11-23 05:00:31.043859: train_loss -0.8346 +2024-11-23 05:00:31.044077: val_loss -0.8027 +2024-11-23 05:00:31.044159: Pseudo dice [0.8586] +2024-11-23 05:00:31.044233: Epoch time: 20.56 s +2024-11-23 05:00:31.977505: +2024-11-23 05:00:31.977731: Epoch 7859 +2024-11-23 05:00:31.977845: Current learning rate: 0.00026 +2024-11-23 05:00:50.746057: train_loss -0.8414 +2024-11-23 05:00:50.746270: val_loss -0.7843 +2024-11-23 05:00:50.746341: Pseudo dice [0.8545] +2024-11-23 05:00:50.746413: Epoch time: 18.77 s +2024-11-23 05:00:51.667339: +2024-11-23 05:00:51.667611: Epoch 7860 +2024-11-23 05:00:51.667724: Current learning rate: 0.00026 +2024-11-23 05:01:10.353753: train_loss -0.8387 +2024-11-23 05:01:10.354016: val_loss -0.8166 +2024-11-23 05:01:10.354092: Pseudo dice [0.8722] +2024-11-23 05:01:10.354176: Epoch time: 18.69 s +2024-11-23 05:01:10.354402: Yayy! New best EMA pseudo Dice: 0.8605 +2024-11-23 05:01:11.635471: +2024-11-23 05:01:11.635684: Epoch 7861 +2024-11-23 05:01:11.635794: Current learning rate: 0.00026 +2024-11-23 05:01:29.842003: train_loss -0.8425 +2024-11-23 05:01:29.842554: val_loss -0.7864 +2024-11-23 05:01:29.842654: Pseudo dice [0.8561] +2024-11-23 05:01:29.842736: Epoch time: 18.21 s +2024-11-23 05:01:30.765052: +2024-11-23 05:01:30.765282: Epoch 7862 +2024-11-23 05:01:30.765391: Current learning rate: 0.00026 +2024-11-23 05:01:48.329601: train_loss -0.84 +2024-11-23 05:01:48.329835: val_loss -0.7941 +2024-11-23 05:01:48.329908: Pseudo dice [0.8682] +2024-11-23 05:01:48.329983: Epoch time: 17.57 s +2024-11-23 05:01:48.330055: Yayy! New best EMA pseudo Dice: 0.8609 +2024-11-23 05:01:49.630677: +2024-11-23 05:01:49.630884: Epoch 7863 +2024-11-23 05:01:49.630999: Current learning rate: 0.00026 +2024-11-23 05:02:07.780224: train_loss -0.8449 +2024-11-23 05:02:07.780483: val_loss -0.8035 +2024-11-23 05:02:07.780559: Pseudo dice [0.8739] +2024-11-23 05:02:07.780640: Epoch time: 18.15 s +2024-11-23 05:02:07.780705: Yayy! New best EMA pseudo Dice: 0.8622 +2024-11-23 05:02:09.058224: +2024-11-23 05:02:09.058455: Epoch 7864 +2024-11-23 05:02:09.058570: Current learning rate: 0.00026 +2024-11-23 05:02:28.466759: train_loss -0.8367 +2024-11-23 05:02:28.466989: val_loss -0.7984 +2024-11-23 05:02:28.467107: Pseudo dice [0.8642] +2024-11-23 05:02:28.467182: Epoch time: 19.41 s +2024-11-23 05:02:28.467243: Yayy! New best EMA pseudo Dice: 0.8624 +2024-11-23 05:02:29.774663: +2024-11-23 05:02:29.774953: Epoch 7865 +2024-11-23 05:02:29.775071: Current learning rate: 0.00025 +2024-11-23 05:02:48.845423: train_loss -0.8403 +2024-11-23 05:02:48.845659: val_loss -0.7871 +2024-11-23 05:02:48.845739: Pseudo dice [0.8615] +2024-11-23 05:02:48.845818: Epoch time: 19.07 s +2024-11-23 05:02:49.770858: +2024-11-23 05:02:49.771080: Epoch 7866 +2024-11-23 05:02:49.771189: Current learning rate: 0.00025 +2024-11-23 05:03:08.345085: train_loss -0.8426 +2024-11-23 05:03:08.345331: val_loss -0.8028 +2024-11-23 05:03:08.345415: Pseudo dice [0.8498] +2024-11-23 05:03:08.345488: Epoch time: 18.58 s +2024-11-23 05:03:09.268866: +2024-11-23 05:03:09.269100: Epoch 7867 +2024-11-23 05:03:09.269215: Current learning rate: 0.00025 +2024-11-23 05:03:27.511276: train_loss -0.8353 +2024-11-23 05:03:27.511515: val_loss -0.7968 +2024-11-23 05:03:27.511595: Pseudo dice [0.8643] +2024-11-23 05:03:27.511669: Epoch time: 18.24 s +2024-11-23 05:03:28.442098: +2024-11-23 05:03:28.442324: Epoch 7868 +2024-11-23 05:03:28.442470: Current learning rate: 0.00025 +2024-11-23 05:03:46.942784: train_loss -0.8336 +2024-11-23 05:03:46.943011: val_loss -0.7649 +2024-11-23 05:03:46.943084: Pseudo dice [0.8431] +2024-11-23 05:03:46.943157: Epoch time: 18.5 s +2024-11-23 05:03:47.953875: +2024-11-23 05:03:47.954096: Epoch 7869 +2024-11-23 05:03:47.954207: Current learning rate: 0.00025 +2024-11-23 05:04:06.102455: train_loss -0.8365 +2024-11-23 05:04:06.103078: val_loss -0.79 +2024-11-23 05:04:06.103161: Pseudo dice [0.8636] +2024-11-23 05:04:06.103265: Epoch time: 18.15 s +2024-11-23 05:04:07.033637: +2024-11-23 05:04:07.033864: Epoch 7870 +2024-11-23 05:04:07.033981: Current learning rate: 0.00025 +2024-11-23 05:04:25.728873: train_loss -0.8388 +2024-11-23 05:04:25.729112: val_loss -0.7844 +2024-11-23 05:04:25.729198: Pseudo dice [0.8715] +2024-11-23 05:04:25.729272: Epoch time: 18.7 s +2024-11-23 05:04:26.649565: +2024-11-23 05:04:26.649762: Epoch 7871 +2024-11-23 05:04:26.649867: Current learning rate: 0.00024 +2024-11-23 05:04:44.700498: train_loss -0.8423 +2024-11-23 05:04:44.700750: val_loss -0.7758 +2024-11-23 05:04:44.700825: Pseudo dice [0.8376] +2024-11-23 05:04:44.700907: Epoch time: 18.05 s +2024-11-23 05:04:46.004707: +2024-11-23 05:04:46.004945: Epoch 7872 +2024-11-23 05:04:46.005065: Current learning rate: 0.00024 +2024-11-23 05:05:04.624358: train_loss -0.838 +2024-11-23 05:05:04.624608: val_loss -0.7902 +2024-11-23 05:05:04.624690: Pseudo dice [0.8597] +2024-11-23 05:05:04.624823: Epoch time: 18.62 s +2024-11-23 05:05:05.640190: +2024-11-23 05:05:05.640395: Epoch 7873 +2024-11-23 05:05:05.640501: Current learning rate: 0.00024 +2024-11-23 05:05:24.718171: train_loss -0.8388 +2024-11-23 05:05:24.718401: val_loss -0.7795 +2024-11-23 05:05:24.718474: Pseudo dice [0.8497] +2024-11-23 05:05:24.718549: Epoch time: 19.08 s +2024-11-23 05:05:25.647458: +2024-11-23 05:05:25.647684: Epoch 7874 +2024-11-23 05:05:25.647801: Current learning rate: 0.00024 +2024-11-23 05:05:44.477363: train_loss -0.8407 +2024-11-23 05:05:44.477585: val_loss -0.7738 +2024-11-23 05:05:44.477659: Pseudo dice [0.8577] +2024-11-23 05:05:44.477734: Epoch time: 18.83 s +2024-11-23 05:05:45.405038: +2024-11-23 05:05:45.405250: Epoch 7875 +2024-11-23 05:05:45.405360: Current learning rate: 0.00024 +2024-11-23 05:06:06.046128: train_loss -0.8349 +2024-11-23 05:06:06.046387: val_loss -0.7844 +2024-11-23 05:06:06.046474: Pseudo dice [0.8496] +2024-11-23 05:06:06.051716: Epoch time: 20.64 s +2024-11-23 05:06:07.058687: +2024-11-23 05:06:07.058911: Epoch 7876 +2024-11-23 05:06:07.059034: Current learning rate: 0.00024 +2024-11-23 05:06:25.493685: train_loss -0.8387 +2024-11-23 05:06:25.493912: val_loss -0.7875 +2024-11-23 05:06:25.493987: Pseudo dice [0.8462] +2024-11-23 05:06:25.494068: Epoch time: 18.44 s +2024-11-23 05:06:26.421675: +2024-11-23 05:06:26.421883: Epoch 7877 +2024-11-23 05:06:26.422003: Current learning rate: 0.00023 +2024-11-23 05:06:44.003167: train_loss -0.8391 +2024-11-23 05:06:44.003399: val_loss -0.7731 +2024-11-23 05:06:44.003474: Pseudo dice [0.8681] +2024-11-23 05:06:44.003546: Epoch time: 17.58 s +2024-11-23 05:06:44.954545: +2024-11-23 05:06:44.954765: Epoch 7878 +2024-11-23 05:06:44.954884: Current learning rate: 0.00023 +2024-11-23 05:07:03.836668: train_loss -0.8384 +2024-11-23 05:07:03.836895: val_loss -0.791 +2024-11-23 05:07:03.836969: Pseudo dice [0.8653] +2024-11-23 05:07:03.837051: Epoch time: 18.88 s +2024-11-23 05:07:04.931778: +2024-11-23 05:07:04.931997: Epoch 7879 +2024-11-23 05:07:04.932104: Current learning rate: 0.00023 +2024-11-23 05:07:23.707957: train_loss -0.8385 +2024-11-23 05:07:23.708212: val_loss -0.7953 +2024-11-23 05:07:23.708287: Pseudo dice [0.8505] +2024-11-23 05:07:23.708366: Epoch time: 18.78 s +2024-11-23 05:07:24.639179: +2024-11-23 05:07:24.639385: Epoch 7880 +2024-11-23 05:07:24.639491: Current learning rate: 0.00023 +2024-11-23 05:07:43.967388: train_loss -0.8382 +2024-11-23 05:07:43.967625: val_loss -0.793 +2024-11-23 05:07:43.967701: Pseudo dice [0.8526] +2024-11-23 05:07:43.967775: Epoch time: 19.33 s +2024-11-23 05:07:44.892594: +2024-11-23 05:07:44.892797: Epoch 7881 +2024-11-23 05:07:44.892910: Current learning rate: 0.00023 +2024-11-23 05:08:02.896941: train_loss -0.8456 +2024-11-23 05:08:02.897164: val_loss -0.7941 +2024-11-23 05:08:02.897242: Pseudo dice [0.8689] +2024-11-23 05:08:02.897318: Epoch time: 18.01 s +2024-11-23 05:08:03.816969: +2024-11-23 05:08:03.817198: Epoch 7882 +2024-11-23 05:08:03.817309: Current learning rate: 0.00022 +2024-11-23 05:08:23.033723: train_loss -0.8451 +2024-11-23 05:08:23.034001: val_loss -0.7454 +2024-11-23 05:08:23.034083: Pseudo dice [0.8451] +2024-11-23 05:08:23.039247: Epoch time: 19.22 s +2024-11-23 05:08:24.522932: +2024-11-23 05:08:24.523169: Epoch 7883 +2024-11-23 05:08:24.523279: Current learning rate: 0.00022 +2024-11-23 05:08:42.304485: train_loss -0.8431 +2024-11-23 05:08:42.304808: val_loss -0.7847 +2024-11-23 05:08:42.304885: Pseudo dice [0.8536] +2024-11-23 05:08:42.304956: Epoch time: 17.78 s +2024-11-23 05:08:43.229642: +2024-11-23 05:08:43.229999: Epoch 7884 +2024-11-23 05:08:43.230109: Current learning rate: 0.00022 +2024-11-23 05:09:01.641818: train_loss -0.8369 +2024-11-23 05:09:01.642101: val_loss -0.7773 +2024-11-23 05:09:01.642210: Pseudo dice [0.8449] +2024-11-23 05:09:01.642288: Epoch time: 18.41 s +2024-11-23 05:09:02.569429: +2024-11-23 05:09:02.569649: Epoch 7885 +2024-11-23 05:09:02.569756: Current learning rate: 0.00022 +2024-11-23 05:09:21.033948: train_loss -0.8385 +2024-11-23 05:09:21.034196: val_loss -0.7801 +2024-11-23 05:09:21.034272: Pseudo dice [0.8609] +2024-11-23 05:09:21.034354: Epoch time: 18.47 s +2024-11-23 05:09:21.974810: +2024-11-23 05:09:21.975240: Epoch 7886 +2024-11-23 05:09:21.975360: Current learning rate: 0.00022 +2024-11-23 05:09:39.980583: train_loss -0.8392 +2024-11-23 05:09:39.980827: val_loss -0.7798 +2024-11-23 05:09:39.980902: Pseudo dice [0.8488] +2024-11-23 05:09:39.980982: Epoch time: 18.01 s +2024-11-23 05:09:40.903265: +2024-11-23 05:09:40.903476: Epoch 7887 +2024-11-23 05:09:40.903588: Current learning rate: 0.00022 +2024-11-23 05:09:59.125969: train_loss -0.8385 +2024-11-23 05:09:59.126225: val_loss -0.784 +2024-11-23 05:09:59.126299: Pseudo dice [0.8638] +2024-11-23 05:09:59.126380: Epoch time: 18.22 s +2024-11-23 05:10:00.051895: +2024-11-23 05:10:00.052135: Epoch 7888 +2024-11-23 05:10:00.052253: Current learning rate: 0.00021 +2024-11-23 05:10:19.141857: train_loss -0.8423 +2024-11-23 05:10:19.142087: val_loss -0.7806 +2024-11-23 05:10:19.142161: Pseudo dice [0.8502] +2024-11-23 05:10:19.142241: Epoch time: 19.09 s +2024-11-23 05:10:20.066330: +2024-11-23 05:10:20.066558: Epoch 7889 +2024-11-23 05:10:20.066667: Current learning rate: 0.00021 +2024-11-23 05:10:38.684898: train_loss -0.8313 +2024-11-23 05:10:38.685171: val_loss -0.7938 +2024-11-23 05:10:38.685246: Pseudo dice [0.8591] +2024-11-23 05:10:38.685330: Epoch time: 18.62 s +2024-11-23 05:10:39.777638: +2024-11-23 05:10:39.777868: Epoch 7890 +2024-11-23 05:10:39.777978: Current learning rate: 0.00021 +2024-11-23 05:10:57.642701: train_loss -0.8393 +2024-11-23 05:10:57.642914: val_loss -0.7288 +2024-11-23 05:10:57.642989: Pseudo dice [0.8564] +2024-11-23 05:10:57.643069: Epoch time: 17.87 s +2024-11-23 05:10:58.596027: +2024-11-23 05:10:58.596261: Epoch 7891 +2024-11-23 05:10:58.596367: Current learning rate: 0.00021 +2024-11-23 05:11:17.858205: train_loss -0.8382 +2024-11-23 05:11:17.858454: val_loss -0.777 +2024-11-23 05:11:17.858532: Pseudo dice [0.8668] +2024-11-23 05:11:17.858612: Epoch time: 19.26 s +2024-11-23 05:11:18.909466: +2024-11-23 05:11:18.909804: Epoch 7892 +2024-11-23 05:11:18.909925: Current learning rate: 0.00021 +2024-11-23 05:11:37.015279: train_loss -0.8486 +2024-11-23 05:11:37.015501: val_loss -0.7798 +2024-11-23 05:11:37.015576: Pseudo dice [0.863] +2024-11-23 05:11:37.015653: Epoch time: 18.11 s +2024-11-23 05:11:37.976614: +2024-11-23 05:11:37.976831: Epoch 7893 +2024-11-23 05:11:37.976944: Current learning rate: 0.00021 +2024-11-23 05:11:55.773244: train_loss -0.8435 +2024-11-23 05:11:55.773498: val_loss -0.781 +2024-11-23 05:11:55.773575: Pseudo dice [0.8497] +2024-11-23 05:11:55.773662: Epoch time: 17.8 s +2024-11-23 05:11:56.737887: +2024-11-23 05:11:56.738145: Epoch 7894 +2024-11-23 05:11:56.738260: Current learning rate: 0.0002 +2024-11-23 05:12:14.642553: train_loss -0.8509 +2024-11-23 05:12:14.642772: val_loss -0.7691 +2024-11-23 05:12:14.642844: Pseudo dice [0.8516] +2024-11-23 05:12:14.648086: Epoch time: 17.91 s +2024-11-23 05:12:15.990509: +2024-11-23 05:12:15.990733: Epoch 7895 +2024-11-23 05:12:15.990854: Current learning rate: 0.0002 +2024-11-23 05:12:35.006553: train_loss -0.8413 +2024-11-23 05:12:35.006788: val_loss -0.7858 +2024-11-23 05:12:35.006864: Pseudo dice [0.8486] +2024-11-23 05:12:35.006938: Epoch time: 19.02 s +2024-11-23 05:12:35.928668: +2024-11-23 05:12:35.928886: Epoch 7896 +2024-11-23 05:12:35.929000: Current learning rate: 0.0002 +2024-11-23 05:12:54.671376: train_loss -0.839 +2024-11-23 05:12:54.671628: val_loss -0.7952 +2024-11-23 05:12:54.671705: Pseudo dice [0.869] +2024-11-23 05:12:54.671786: Epoch time: 18.74 s +2024-11-23 05:12:55.631361: +2024-11-23 05:12:55.631592: Epoch 7897 +2024-11-23 05:12:55.631701: Current learning rate: 0.0002 +2024-11-23 05:13:14.224028: train_loss -0.8405 +2024-11-23 05:13:14.224250: val_loss -0.7456 +2024-11-23 05:13:14.224324: Pseudo dice [0.8428] +2024-11-23 05:13:14.224400: Epoch time: 18.59 s +2024-11-23 05:13:15.254303: +2024-11-23 05:13:15.254519: Epoch 7898 +2024-11-23 05:13:15.254624: Current learning rate: 0.0002 +2024-11-23 05:13:34.253172: train_loss -0.8393 +2024-11-23 05:13:34.253409: val_loss -0.8093 +2024-11-23 05:13:34.253484: Pseudo dice [0.8617] +2024-11-23 05:13:34.253556: Epoch time: 19.0 s +2024-11-23 05:13:35.224708: +2024-11-23 05:13:35.225080: Epoch 7899 +2024-11-23 05:13:35.225188: Current learning rate: 0.0002 +2024-11-23 05:13:53.191845: train_loss -0.8434 +2024-11-23 05:13:53.192083: val_loss -0.7765 +2024-11-23 05:13:53.192237: Pseudo dice [0.8594] +2024-11-23 05:13:53.192313: Epoch time: 17.97 s +2024-11-23 05:13:54.494489: +2024-11-23 05:13:54.494724: Epoch 7900 +2024-11-23 05:13:54.494830: Current learning rate: 0.00019 +2024-11-23 05:14:12.836435: train_loss -0.8404 +2024-11-23 05:14:12.838879: val_loss -0.7776 +2024-11-23 05:14:12.839018: Pseudo dice [0.8461] +2024-11-23 05:14:12.839106: Epoch time: 18.34 s +2024-11-23 05:14:14.006870: +2024-11-23 05:14:14.007125: Epoch 7901 +2024-11-23 05:14:14.007255: Current learning rate: 0.00019 +2024-11-23 05:14:31.411514: train_loss -0.842 +2024-11-23 05:14:31.411740: val_loss -0.7745 +2024-11-23 05:14:31.411815: Pseudo dice [0.8498] +2024-11-23 05:14:31.411892: Epoch time: 17.41 s +2024-11-23 05:14:32.336413: +2024-11-23 05:14:32.336632: Epoch 7902 +2024-11-23 05:14:32.336749: Current learning rate: 0.00019 +2024-11-23 05:14:50.555068: train_loss -0.8454 +2024-11-23 05:14:50.555330: val_loss -0.7785 +2024-11-23 05:14:50.555410: Pseudo dice [0.8467] +2024-11-23 05:14:50.555489: Epoch time: 18.22 s +2024-11-23 05:14:51.481481: +2024-11-23 05:14:51.481754: Epoch 7903 +2024-11-23 05:14:51.481873: Current learning rate: 0.00019 +2024-11-23 05:15:09.876185: train_loss -0.8423 +2024-11-23 05:15:09.876415: val_loss -0.791 +2024-11-23 05:15:09.876489: Pseudo dice [0.8751] +2024-11-23 05:15:09.876564: Epoch time: 18.4 s +2024-11-23 05:15:10.810442: +2024-11-23 05:15:10.810656: Epoch 7904 +2024-11-23 05:15:10.810760: Current learning rate: 0.00019 +2024-11-23 05:15:30.591487: train_loss -0.8371 +2024-11-23 05:15:30.591729: val_loss -0.779 +2024-11-23 05:15:30.591801: Pseudo dice [0.8595] +2024-11-23 05:15:30.591880: Epoch time: 19.78 s +2024-11-23 05:15:31.525765: +2024-11-23 05:15:31.526002: Epoch 7905 +2024-11-23 05:15:31.526112: Current learning rate: 0.00018 +2024-11-23 05:15:50.967898: train_loss -0.846 +2024-11-23 05:15:50.973319: val_loss -0.791 +2024-11-23 05:15:50.973404: Pseudo dice [0.8592] +2024-11-23 05:15:50.973484: Epoch time: 19.44 s +2024-11-23 05:15:52.484527: +2024-11-23 05:15:52.484763: Epoch 7906 +2024-11-23 05:15:52.484878: Current learning rate: 0.00018 +2024-11-23 05:16:10.597696: train_loss -0.8408 +2024-11-23 05:16:10.597999: val_loss -0.7862 +2024-11-23 05:16:10.598075: Pseudo dice [0.8773] +2024-11-23 05:16:10.598152: Epoch time: 18.11 s +2024-11-23 05:16:11.528141: +2024-11-23 05:16:11.528372: Epoch 7907 +2024-11-23 05:16:11.528482: Current learning rate: 0.00018 +2024-11-23 05:16:30.886257: train_loss -0.8432 +2024-11-23 05:16:30.886468: val_loss -0.7781 +2024-11-23 05:16:30.886545: Pseudo dice [0.859] +2024-11-23 05:16:30.886623: Epoch time: 19.36 s +2024-11-23 05:16:31.807781: +2024-11-23 05:16:31.808019: Epoch 7908 +2024-11-23 05:16:31.808127: Current learning rate: 0.00018 +2024-11-23 05:16:50.880163: train_loss -0.8397 +2024-11-23 05:16:50.880474: val_loss -0.7507 +2024-11-23 05:16:50.880558: Pseudo dice [0.854] +2024-11-23 05:16:50.880641: Epoch time: 19.07 s +2024-11-23 05:16:51.808390: +2024-11-23 05:16:51.808614: Epoch 7909 +2024-11-23 05:16:51.808717: Current learning rate: 0.00018 +2024-11-23 05:17:10.997463: train_loss -0.8378 +2024-11-23 05:17:10.997679: val_loss -0.7905 +2024-11-23 05:17:10.997753: Pseudo dice [0.869] +2024-11-23 05:17:10.997826: Epoch time: 19.19 s +2024-11-23 05:17:11.924040: +2024-11-23 05:17:11.924262: Epoch 7910 +2024-11-23 05:17:11.924370: Current learning rate: 0.00018 +2024-11-23 05:17:30.197725: train_loss -0.8482 +2024-11-23 05:17:30.197949: val_loss -0.7664 +2024-11-23 05:17:30.198033: Pseudo dice [0.8554] +2024-11-23 05:17:30.198108: Epoch time: 18.27 s +2024-11-23 05:17:31.118189: +2024-11-23 05:17:31.118413: Epoch 7911 +2024-11-23 05:17:31.118519: Current learning rate: 0.00017 +2024-11-23 05:17:49.589461: train_loss -0.8413 +2024-11-23 05:17:49.591827: val_loss -0.8017 +2024-11-23 05:17:49.591928: Pseudo dice [0.8758] +2024-11-23 05:17:49.592062: Epoch time: 18.47 s +2024-11-23 05:17:50.545964: +2024-11-23 05:17:50.546208: Epoch 7912 +2024-11-23 05:17:50.546319: Current learning rate: 0.00017 +2024-11-23 05:18:08.337656: train_loss -0.8425 +2024-11-23 05:18:08.337901: val_loss -0.7806 +2024-11-23 05:18:08.337975: Pseudo dice [0.863] +2024-11-23 05:18:08.338067: Epoch time: 17.79 s +2024-11-23 05:18:09.255493: +2024-11-23 05:18:09.255717: Epoch 7913 +2024-11-23 05:18:09.255825: Current learning rate: 0.00017 +2024-11-23 05:18:27.119770: train_loss -0.842 +2024-11-23 05:18:27.120008: val_loss -0.7961 +2024-11-23 05:18:27.120085: Pseudo dice [0.8687] +2024-11-23 05:18:27.120158: Epoch time: 17.87 s +2024-11-23 05:18:28.043075: +2024-11-23 05:18:28.043287: Epoch 7914 +2024-11-23 05:18:28.043402: Current learning rate: 0.00017 +2024-11-23 05:18:46.701218: train_loss -0.8421 +2024-11-23 05:18:46.701442: val_loss -0.7945 +2024-11-23 05:18:46.701517: Pseudo dice [0.8453] +2024-11-23 05:18:46.701589: Epoch time: 18.66 s +2024-11-23 05:18:47.628343: +2024-11-23 05:18:47.628594: Epoch 7915 +2024-11-23 05:18:47.628710: Current learning rate: 0.00017 +2024-11-23 05:19:06.230180: train_loss -0.8411 +2024-11-23 05:19:06.230415: val_loss -0.7804 +2024-11-23 05:19:06.230489: Pseudo dice [0.8598] +2024-11-23 05:19:06.230564: Epoch time: 18.6 s +2024-11-23 05:19:07.167305: +2024-11-23 05:19:07.167545: Epoch 7916 +2024-11-23 05:19:07.167659: Current learning rate: 0.00017 +2024-11-23 05:19:24.101122: train_loss -0.8467 +2024-11-23 05:19:24.101367: val_loss -0.7748 +2024-11-23 05:19:24.101442: Pseudo dice [0.8551] +2024-11-23 05:19:24.101523: Epoch time: 16.93 s +2024-11-23 05:19:25.028153: +2024-11-23 05:19:25.028371: Epoch 7917 +2024-11-23 05:19:25.028480: Current learning rate: 0.00016 +2024-11-23 05:19:44.920436: train_loss -0.8407 +2024-11-23 05:19:44.923061: val_loss -0.7846 +2024-11-23 05:19:44.923190: Pseudo dice [0.8643] +2024-11-23 05:19:44.923273: Epoch time: 19.89 s +2024-11-23 05:19:45.924583: +2024-11-23 05:19:45.924813: Epoch 7918 +2024-11-23 05:19:45.924925: Current learning rate: 0.00016 +2024-11-23 05:20:04.039678: train_loss -0.8417 +2024-11-23 05:20:04.039913: val_loss -0.7791 +2024-11-23 05:20:04.039995: Pseudo dice [0.8385] +2024-11-23 05:20:04.040073: Epoch time: 18.12 s +2024-11-23 05:20:04.962698: +2024-11-23 05:20:04.962919: Epoch 7919 +2024-11-23 05:20:04.963028: Current learning rate: 0.00016 +2024-11-23 05:20:23.297129: train_loss -0.8404 +2024-11-23 05:20:23.297379: val_loss -0.7681 +2024-11-23 05:20:23.297452: Pseudo dice [0.8692] +2024-11-23 05:20:23.297532: Epoch time: 18.34 s +2024-11-23 05:20:24.233603: +2024-11-23 05:20:24.233806: Epoch 7920 +2024-11-23 05:20:24.233914: Current learning rate: 0.00016 +2024-11-23 05:20:42.485365: train_loss -0.8448 +2024-11-23 05:20:42.485599: val_loss -0.7906 +2024-11-23 05:20:42.485672: Pseudo dice [0.8575] +2024-11-23 05:20:42.485750: Epoch time: 18.25 s +2024-11-23 05:20:43.518757: +2024-11-23 05:20:43.518988: Epoch 7921 +2024-11-23 05:20:43.519108: Current learning rate: 0.00016 +2024-11-23 05:21:02.608248: train_loss -0.8412 +2024-11-23 05:21:02.608473: val_loss -0.7923 +2024-11-23 05:21:02.608550: Pseudo dice [0.8594] +2024-11-23 05:21:02.608623: Epoch time: 19.09 s +2024-11-23 05:21:03.563201: +2024-11-23 05:21:03.563434: Epoch 7922 +2024-11-23 05:21:03.563543: Current learning rate: 0.00015 +2024-11-23 05:21:22.286563: train_loss -0.8398 +2024-11-23 05:21:22.286793: val_loss -0.7971 +2024-11-23 05:21:22.286870: Pseudo dice [0.8419] +2024-11-23 05:21:22.286944: Epoch time: 18.72 s +2024-11-23 05:21:23.212683: +2024-11-23 05:21:23.212926: Epoch 7923 +2024-11-23 05:21:23.213044: Current learning rate: 0.00015 +2024-11-23 05:21:42.421261: train_loss -0.8443 +2024-11-23 05:21:42.421551: val_loss -0.7744 +2024-11-23 05:21:42.421633: Pseudo dice [0.8586] +2024-11-23 05:21:42.421719: Epoch time: 19.21 s +2024-11-23 05:21:43.351060: +2024-11-23 05:21:43.351261: Epoch 7924 +2024-11-23 05:21:43.351369: Current learning rate: 0.00015 +2024-11-23 05:22:02.066725: train_loss -0.8383 +2024-11-23 05:22:02.066967: val_loss -0.8099 +2024-11-23 05:22:02.067054: Pseudo dice [0.8602] +2024-11-23 05:22:02.067130: Epoch time: 18.72 s +2024-11-23 05:22:03.102329: +2024-11-23 05:22:03.102544: Epoch 7925 +2024-11-23 05:22:03.102647: Current learning rate: 0.00015 +2024-11-23 05:22:22.219385: train_loss -0.8401 +2024-11-23 05:22:22.219612: val_loss -0.7915 +2024-11-23 05:22:22.219688: Pseudo dice [0.8481] +2024-11-23 05:22:22.219761: Epoch time: 19.12 s +2024-11-23 05:22:23.255311: +2024-11-23 05:22:23.255531: Epoch 7926 +2024-11-23 05:22:23.255646: Current learning rate: 0.00015 +2024-11-23 05:22:42.064741: train_loss -0.8425 +2024-11-23 05:22:42.064976: val_loss -0.7745 +2024-11-23 05:22:42.065057: Pseudo dice [0.8554] +2024-11-23 05:22:42.065131: Epoch time: 18.81 s +2024-11-23 05:22:42.985460: +2024-11-23 05:22:42.985692: Epoch 7927 +2024-11-23 05:22:42.985811: Current learning rate: 0.00015 +2024-11-23 05:23:02.092547: train_loss -0.844 +2024-11-23 05:23:02.092796: val_loss -0.7891 +2024-11-23 05:23:02.092871: Pseudo dice [0.8617] +2024-11-23 05:23:02.092955: Epoch time: 19.11 s +2024-11-23 05:23:03.378917: +2024-11-23 05:23:03.379149: Epoch 7928 +2024-11-23 05:23:03.379260: Current learning rate: 0.00014 +2024-11-23 05:23:21.423909: train_loss -0.84 +2024-11-23 05:23:21.424133: val_loss -0.783 +2024-11-23 05:23:21.424206: Pseudo dice [0.8557] +2024-11-23 05:23:21.424281: Epoch time: 18.05 s +2024-11-23 05:23:22.456045: +2024-11-23 05:23:22.456272: Epoch 7929 +2024-11-23 05:23:22.456386: Current learning rate: 0.00014 +2024-11-23 05:23:41.866532: train_loss -0.8415 +2024-11-23 05:23:41.866762: val_loss -0.7963 +2024-11-23 05:23:41.866839: Pseudo dice [0.8633] +2024-11-23 05:23:41.866919: Epoch time: 19.41 s +2024-11-23 05:23:42.825250: +2024-11-23 05:23:42.825476: Epoch 7930 +2024-11-23 05:23:42.825586: Current learning rate: 0.00014 +2024-11-23 05:24:02.017701: train_loss -0.841 +2024-11-23 05:24:02.017934: val_loss -0.7893 +2024-11-23 05:24:02.018020: Pseudo dice [0.8665] +2024-11-23 05:24:02.018096: Epoch time: 19.19 s +2024-11-23 05:24:03.163010: +2024-11-23 05:24:03.163300: Epoch 7931 +2024-11-23 05:24:03.163415: Current learning rate: 0.00014 +2024-11-23 05:24:21.402059: train_loss -0.8408 +2024-11-23 05:24:21.402309: val_loss -0.8041 +2024-11-23 05:24:21.402385: Pseudo dice [0.8603] +2024-11-23 05:24:21.402466: Epoch time: 18.24 s +2024-11-23 05:24:22.332018: +2024-11-23 05:24:22.332252: Epoch 7932 +2024-11-23 05:24:22.332365: Current learning rate: 0.00014 +2024-11-23 05:24:40.141812: train_loss -0.8418 +2024-11-23 05:24:40.142051: val_loss -0.7752 +2024-11-23 05:24:40.142131: Pseudo dice [0.8624] +2024-11-23 05:24:40.142208: Epoch time: 17.81 s +2024-11-23 05:24:41.178798: +2024-11-23 05:24:41.179040: Epoch 7933 +2024-11-23 05:24:41.179151: Current learning rate: 0.00014 +2024-11-23 05:25:00.295002: train_loss -0.8404 +2024-11-23 05:25:00.295345: val_loss -0.786 +2024-11-23 05:25:00.295424: Pseudo dice [0.8569] +2024-11-23 05:25:00.295501: Epoch time: 19.12 s +2024-11-23 05:25:01.234446: +2024-11-23 05:25:01.234683: Epoch 7934 +2024-11-23 05:25:01.234807: Current learning rate: 0.00013 +2024-11-23 05:25:20.879163: train_loss -0.8399 +2024-11-23 05:25:20.879395: val_loss -0.7947 +2024-11-23 05:25:20.879472: Pseudo dice [0.8699] +2024-11-23 05:25:20.879550: Epoch time: 19.65 s +2024-11-23 05:25:21.806041: +2024-11-23 05:25:21.806265: Epoch 7935 +2024-11-23 05:25:21.806374: Current learning rate: 0.00013 +2024-11-23 05:25:41.103459: train_loss -0.8343 +2024-11-23 05:25:41.103690: val_loss -0.7661 +2024-11-23 05:25:41.103765: Pseudo dice [0.8539] +2024-11-23 05:25:41.103842: Epoch time: 19.3 s +2024-11-23 05:25:42.025723: +2024-11-23 05:25:42.025947: Epoch 7936 +2024-11-23 05:25:42.026064: Current learning rate: 0.00013 +2024-11-23 05:26:00.507679: train_loss -0.8368 +2024-11-23 05:26:00.507906: val_loss -0.7843 +2024-11-23 05:26:00.507999: Pseudo dice [0.8693] +2024-11-23 05:26:00.508075: Epoch time: 18.48 s +2024-11-23 05:26:01.433920: +2024-11-23 05:26:01.434148: Epoch 7937 +2024-11-23 05:26:01.434256: Current learning rate: 0.00013 +2024-11-23 05:26:20.170909: train_loss -0.8423 +2024-11-23 05:26:20.171137: val_loss -0.7678 +2024-11-23 05:26:20.171211: Pseudo dice [0.8523] +2024-11-23 05:26:20.171284: Epoch time: 18.74 s +2024-11-23 05:26:21.096664: +2024-11-23 05:26:21.096893: Epoch 7938 +2024-11-23 05:26:21.097011: Current learning rate: 0.00013 +2024-11-23 05:26:39.321166: train_loss -0.8355 +2024-11-23 05:26:39.321420: val_loss -0.8051 +2024-11-23 05:26:39.321496: Pseudo dice [0.8651] +2024-11-23 05:26:39.321581: Epoch time: 18.23 s +2024-11-23 05:26:40.243351: +2024-11-23 05:26:40.243591: Epoch 7939 +2024-11-23 05:26:40.243698: Current learning rate: 0.00012 +2024-11-23 05:26:59.081030: train_loss -0.8349 +2024-11-23 05:26:59.081249: val_loss -0.7965 +2024-11-23 05:26:59.081322: Pseudo dice [0.8486] +2024-11-23 05:26:59.081396: Epoch time: 18.84 s +2024-11-23 05:27:00.359538: +2024-11-23 05:27:00.359759: Epoch 7940 +2024-11-23 05:27:00.359867: Current learning rate: 0.00012 +2024-11-23 05:27:18.360486: train_loss -0.8437 +2024-11-23 05:27:18.360758: val_loss -0.7964 +2024-11-23 05:27:18.360836: Pseudo dice [0.8657] +2024-11-23 05:27:18.360911: Epoch time: 18.0 s +2024-11-23 05:27:19.291656: +2024-11-23 05:27:19.291955: Epoch 7941 +2024-11-23 05:27:19.292070: Current learning rate: 0.00012 +2024-11-23 05:27:36.940367: train_loss -0.846 +2024-11-23 05:27:36.940617: val_loss -0.7674 +2024-11-23 05:27:36.940696: Pseudo dice [0.8396] +2024-11-23 05:27:36.945977: Epoch time: 17.65 s +2024-11-23 05:27:38.062367: +2024-11-23 05:27:38.062649: Epoch 7942 +2024-11-23 05:27:38.062757: Current learning rate: 0.00012 +2024-11-23 05:27:56.722281: train_loss -0.8419 +2024-11-23 05:27:56.722546: val_loss -0.8057 +2024-11-23 05:27:56.722622: Pseudo dice [0.8579] +2024-11-23 05:27:56.722695: Epoch time: 18.66 s +2024-11-23 05:27:57.643948: +2024-11-23 05:27:57.644189: Epoch 7943 +2024-11-23 05:27:57.644300: Current learning rate: 0.00012 +2024-11-23 05:28:16.146297: train_loss -0.8413 +2024-11-23 05:28:16.146517: val_loss -0.791 +2024-11-23 05:28:16.146590: Pseudo dice [0.8595] +2024-11-23 05:28:16.146666: Epoch time: 18.5 s +2024-11-23 05:28:17.081898: +2024-11-23 05:28:17.082144: Epoch 7944 +2024-11-23 05:28:17.082253: Current learning rate: 0.00011 +2024-11-23 05:28:35.986381: train_loss -0.8414 +2024-11-23 05:28:35.986613: val_loss -0.7986 +2024-11-23 05:28:35.986690: Pseudo dice [0.864] +2024-11-23 05:28:35.986793: Epoch time: 18.91 s +2024-11-23 05:28:36.956573: +2024-11-23 05:28:36.956800: Epoch 7945 +2024-11-23 05:28:36.956907: Current learning rate: 0.00011 +2024-11-23 05:28:54.721811: train_loss -0.8467 +2024-11-23 05:28:54.722073: val_loss -0.7798 +2024-11-23 05:28:54.722152: Pseudo dice [0.8562] +2024-11-23 05:28:54.722235: Epoch time: 17.77 s +2024-11-23 05:28:55.654072: +2024-11-23 05:28:55.654312: Epoch 7946 +2024-11-23 05:28:55.654425: Current learning rate: 0.00011 +2024-11-23 05:29:14.203174: train_loss -0.843 +2024-11-23 05:29:14.203404: val_loss -0.7679 +2024-11-23 05:29:14.203486: Pseudo dice [0.8533] +2024-11-23 05:29:14.203560: Epoch time: 18.55 s +2024-11-23 05:29:15.138100: +2024-11-23 05:29:15.138324: Epoch 7947 +2024-11-23 05:29:15.138432: Current learning rate: 0.00011 +2024-11-23 05:29:33.379795: train_loss -0.8445 +2024-11-23 05:29:33.380030: val_loss -0.782 +2024-11-23 05:29:33.380106: Pseudo dice [0.867] +2024-11-23 05:29:33.380179: Epoch time: 18.24 s +2024-11-23 05:29:34.303213: +2024-11-23 05:29:34.303439: Epoch 7948 +2024-11-23 05:29:34.303553: Current learning rate: 0.00011 +2024-11-23 05:29:53.541914: train_loss -0.8434 +2024-11-23 05:29:53.542152: val_loss -0.7968 +2024-11-23 05:29:53.542229: Pseudo dice [0.8673] +2024-11-23 05:29:53.542304: Epoch time: 19.24 s +2024-11-23 05:29:54.469699: +2024-11-23 05:29:54.469934: Epoch 7949 +2024-11-23 05:29:54.470053: Current learning rate: 0.00011 +2024-11-23 05:30:14.050603: train_loss -0.8427 +2024-11-23 05:30:14.050857: val_loss -0.7673 +2024-11-23 05:30:14.050931: Pseudo dice [0.8551] +2024-11-23 05:30:14.051017: Epoch time: 19.58 s +2024-11-23 05:30:15.328484: +2024-11-23 05:30:15.328722: Epoch 7950 +2024-11-23 05:30:15.328833: Current learning rate: 0.0001 +2024-11-23 05:30:33.694257: train_loss -0.839 +2024-11-23 05:30:33.694479: val_loss -0.7896 +2024-11-23 05:30:33.694596: Pseudo dice [0.8539] +2024-11-23 05:30:33.694680: Epoch time: 18.37 s +2024-11-23 05:30:34.995385: +2024-11-23 05:30:34.995599: Epoch 7951 +2024-11-23 05:30:34.995706: Current learning rate: 0.0001 +2024-11-23 05:30:53.969617: train_loss -0.8433 +2024-11-23 05:30:53.975074: val_loss -0.7692 +2024-11-23 05:30:53.975238: Pseudo dice [0.8556] +2024-11-23 05:30:53.975319: Epoch time: 18.98 s +2024-11-23 05:30:54.945072: +2024-11-23 05:30:54.945328: Epoch 7952 +2024-11-23 05:30:54.945436: Current learning rate: 0.0001 +2024-11-23 05:31:13.508514: train_loss -0.845 +2024-11-23 05:31:13.508743: val_loss -0.7838 +2024-11-23 05:31:13.508816: Pseudo dice [0.8575] +2024-11-23 05:31:13.508887: Epoch time: 18.56 s +2024-11-23 05:31:14.737764: +2024-11-23 05:31:14.738050: Epoch 7953 +2024-11-23 05:31:14.738157: Current learning rate: 0.0001 +2024-11-23 05:31:32.830799: train_loss -0.8416 +2024-11-23 05:31:32.831063: val_loss -0.7493 +2024-11-23 05:31:32.831139: Pseudo dice [0.8577] +2024-11-23 05:31:32.831217: Epoch time: 18.09 s +2024-11-23 05:31:33.760306: +2024-11-23 05:31:33.760520: Epoch 7954 +2024-11-23 05:31:33.760634: Current learning rate: 0.0001 +2024-11-23 05:31:52.324777: train_loss -0.8402 +2024-11-23 05:31:52.325012: val_loss -0.807 +2024-11-23 05:31:52.325086: Pseudo dice [0.8691] +2024-11-23 05:31:52.325161: Epoch time: 18.57 s +2024-11-23 05:31:53.258102: +2024-11-23 05:31:53.258334: Epoch 7955 +2024-11-23 05:31:53.258440: Current learning rate: 9e-05 +2024-11-23 05:32:11.553813: train_loss -0.8444 +2024-11-23 05:32:11.554095: val_loss -0.793 +2024-11-23 05:32:11.554176: Pseudo dice [0.8694] +2024-11-23 05:32:11.554254: Epoch time: 18.3 s +2024-11-23 05:32:12.526726: +2024-11-23 05:32:12.526963: Epoch 7956 +2024-11-23 05:32:12.527076: Current learning rate: 9e-05 +2024-11-23 05:32:30.394696: train_loss -0.8445 +2024-11-23 05:32:30.394935: val_loss -0.806 +2024-11-23 05:32:30.395019: Pseudo dice [0.8546] +2024-11-23 05:32:30.395096: Epoch time: 17.87 s +2024-11-23 05:32:31.472847: +2024-11-23 05:32:31.473075: Epoch 7957 +2024-11-23 05:32:31.473193: Current learning rate: 9e-05 +2024-11-23 05:32:50.299555: train_loss -0.842 +2024-11-23 05:32:50.299804: val_loss -0.7885 +2024-11-23 05:32:50.299878: Pseudo dice [0.8532] +2024-11-23 05:32:50.299958: Epoch time: 18.83 s +2024-11-23 05:32:51.230811: +2024-11-23 05:32:51.231024: Epoch 7958 +2024-11-23 05:32:51.231133: Current learning rate: 9e-05 +2024-11-23 05:33:09.048395: train_loss -0.8479 +2024-11-23 05:33:09.048613: val_loss -0.8108 +2024-11-23 05:33:09.048687: Pseudo dice [0.8658] +2024-11-23 05:33:09.048759: Epoch time: 17.82 s +2024-11-23 05:33:09.975065: +2024-11-23 05:33:09.975334: Epoch 7959 +2024-11-23 05:33:09.975445: Current learning rate: 9e-05 +2024-11-23 05:33:28.242768: train_loss -0.8466 +2024-11-23 05:33:28.243003: val_loss -0.8019 +2024-11-23 05:33:28.243081: Pseudo dice [0.8669] +2024-11-23 05:33:28.243156: Epoch time: 18.27 s +2024-11-23 05:33:29.174437: +2024-11-23 05:33:29.174673: Epoch 7960 +2024-11-23 05:33:29.174785: Current learning rate: 8e-05 +2024-11-23 05:33:47.102877: train_loss -0.8481 +2024-11-23 05:33:47.103144: val_loss -0.7802 +2024-11-23 05:33:47.103220: Pseudo dice [0.8666] +2024-11-23 05:33:47.103297: Epoch time: 17.93 s +2024-11-23 05:33:48.041816: +2024-11-23 05:33:48.042025: Epoch 7961 +2024-11-23 05:33:48.042145: Current learning rate: 8e-05 +2024-11-23 05:34:06.422551: train_loss -0.8391 +2024-11-23 05:34:06.422798: val_loss -0.8093 +2024-11-23 05:34:06.422876: Pseudo dice [0.8571] +2024-11-23 05:34:06.422954: Epoch time: 18.38 s +2024-11-23 05:34:07.640710: +2024-11-23 05:34:07.640953: Epoch 7962 +2024-11-23 05:34:07.641078: Current learning rate: 8e-05 +2024-11-23 05:34:25.831406: train_loss -0.8377 +2024-11-23 05:34:25.831630: val_loss -0.7925 +2024-11-23 05:34:25.831707: Pseudo dice [0.8491] +2024-11-23 05:34:25.831781: Epoch time: 18.19 s +2024-11-23 05:34:26.751131: +2024-11-23 05:34:26.751386: Epoch 7963 +2024-11-23 05:34:26.751513: Current learning rate: 8e-05 +2024-11-23 05:34:45.839415: train_loss -0.8449 +2024-11-23 05:34:45.839646: val_loss -0.781 +2024-11-23 05:34:45.839726: Pseudo dice [0.8688] +2024-11-23 05:34:45.839801: Epoch time: 19.09 s +2024-11-23 05:34:46.770236: +2024-11-23 05:34:46.770467: Epoch 7964 +2024-11-23 05:34:46.770574: Current learning rate: 8e-05 +2024-11-23 05:35:05.582957: train_loss -0.8418 +2024-11-23 05:35:05.583216: val_loss -0.8043 +2024-11-23 05:35:05.583292: Pseudo dice [0.8656] +2024-11-23 05:35:05.583375: Epoch time: 18.81 s +2024-11-23 05:35:06.511210: +2024-11-23 05:35:06.511422: Epoch 7965 +2024-11-23 05:35:06.511531: Current learning rate: 8e-05 +2024-11-23 05:35:23.963391: train_loss -0.8508 +2024-11-23 05:35:23.963608: val_loss -0.7954 +2024-11-23 05:35:23.963682: Pseudo dice [0.8595] +2024-11-23 05:35:23.963756: Epoch time: 17.45 s +2024-11-23 05:35:24.899318: +2024-11-23 05:35:24.899555: Epoch 7966 +2024-11-23 05:35:24.899667: Current learning rate: 7e-05 +2024-11-23 05:35:43.602652: train_loss -0.8424 +2024-11-23 05:35:43.602893: val_loss -0.778 +2024-11-23 05:35:43.602982: Pseudo dice [0.8519] +2024-11-23 05:35:43.603074: Epoch time: 18.7 s +2024-11-23 05:35:44.554272: +2024-11-23 05:35:44.554510: Epoch 7967 +2024-11-23 05:35:44.554622: Current learning rate: 7e-05 +2024-11-23 05:36:03.284641: train_loss -0.8415 +2024-11-23 05:36:03.284858: val_loss -0.7847 +2024-11-23 05:36:03.284981: Pseudo dice [0.8634] +2024-11-23 05:36:03.285090: Epoch time: 18.73 s +2024-11-23 05:36:04.212756: +2024-11-23 05:36:04.212961: Epoch 7968 +2024-11-23 05:36:04.213076: Current learning rate: 7e-05 +2024-11-23 05:36:23.616403: train_loss -0.8421 +2024-11-23 05:36:23.616673: val_loss -0.7929 +2024-11-23 05:36:23.616748: Pseudo dice [0.8695] +2024-11-23 05:36:23.616827: Epoch time: 19.4 s +2024-11-23 05:36:24.559358: +2024-11-23 05:36:24.559576: Epoch 7969 +2024-11-23 05:36:24.559694: Current learning rate: 7e-05 +2024-11-23 05:36:42.993377: train_loss -0.8436 +2024-11-23 05:36:42.993599: val_loss -0.7856 +2024-11-23 05:36:42.993674: Pseudo dice [0.8673] +2024-11-23 05:36:42.993748: Epoch time: 18.43 s +2024-11-23 05:36:43.937112: +2024-11-23 05:36:43.937353: Epoch 7970 +2024-11-23 05:36:43.937464: Current learning rate: 7e-05 +2024-11-23 05:37:03.468843: train_loss -0.8461 +2024-11-23 05:37:03.469066: val_loss -0.7996 +2024-11-23 05:37:03.469140: Pseudo dice [0.8681] +2024-11-23 05:37:03.469245: Epoch time: 19.53 s +2024-11-23 05:37:03.469311: Yayy! New best EMA pseudo Dice: 0.8624 +2024-11-23 05:37:04.767633: +2024-11-23 05:37:04.767852: Epoch 7971 +2024-11-23 05:37:04.767962: Current learning rate: 6e-05 +2024-11-23 05:37:23.185477: train_loss -0.842 +2024-11-23 05:37:23.185714: val_loss -0.7861 +2024-11-23 05:37:23.185788: Pseudo dice [0.8614] +2024-11-23 05:37:23.185868: Epoch time: 18.42 s +2024-11-23 05:37:24.107769: +2024-11-23 05:37:24.107978: Epoch 7972 +2024-11-23 05:37:24.108092: Current learning rate: 6e-05 +2024-11-23 05:37:41.515075: train_loss -0.8454 +2024-11-23 05:37:41.515324: val_loss -0.7924 +2024-11-23 05:37:41.515419: Pseudo dice [0.8552] +2024-11-23 05:37:41.515498: Epoch time: 17.41 s +2024-11-23 05:37:42.787418: +2024-11-23 05:37:42.787741: Epoch 7973 +2024-11-23 05:37:42.787850: Current learning rate: 6e-05 +2024-11-23 05:38:01.101887: train_loss -0.8471 +2024-11-23 05:38:01.102118: val_loss -0.7804 +2024-11-23 05:38:01.102196: Pseudo dice [0.8501] +2024-11-23 05:38:01.102272: Epoch time: 18.32 s +2024-11-23 05:38:02.109143: +2024-11-23 05:38:02.109369: Epoch 7974 +2024-11-23 05:38:02.109481: Current learning rate: 6e-05 +2024-11-23 05:38:20.689690: train_loss -0.8432 +2024-11-23 05:38:20.689917: val_loss -0.7942 +2024-11-23 05:38:20.689998: Pseudo dice [0.8541] +2024-11-23 05:38:20.690073: Epoch time: 18.58 s +2024-11-23 05:38:21.624929: +2024-11-23 05:38:21.625154: Epoch 7975 +2024-11-23 05:38:21.625262: Current learning rate: 6e-05 +2024-11-23 05:38:40.941191: train_loss -0.8415 +2024-11-23 05:38:40.942172: val_loss -0.7842 +2024-11-23 05:38:40.942253: Pseudo dice [0.8454] +2024-11-23 05:38:40.942334: Epoch time: 19.32 s +2024-11-23 05:38:41.924529: +2024-11-23 05:38:41.924745: Epoch 7976 +2024-11-23 05:38:41.924862: Current learning rate: 5e-05 +2024-11-23 05:38:59.793163: train_loss -0.8437 +2024-11-23 05:38:59.793390: val_loss -0.7723 +2024-11-23 05:38:59.793464: Pseudo dice [0.8567] +2024-11-23 05:38:59.793540: Epoch time: 17.87 s +2024-11-23 05:39:00.729497: +2024-11-23 05:39:00.729719: Epoch 7977 +2024-11-23 05:39:00.729826: Current learning rate: 5e-05 +2024-11-23 05:39:18.593474: train_loss -0.8384 +2024-11-23 05:39:18.593701: val_loss -0.7922 +2024-11-23 05:39:18.593774: Pseudo dice [0.8626] +2024-11-23 05:39:18.593851: Epoch time: 17.86 s +2024-11-23 05:39:19.532866: +2024-11-23 05:39:19.533118: Epoch 7978 +2024-11-23 05:39:19.533228: Current learning rate: 5e-05 +2024-11-23 05:39:38.096237: train_loss -0.8484 +2024-11-23 05:39:38.096478: val_loss -0.7933 +2024-11-23 05:39:38.096553: Pseudo dice [0.8604] +2024-11-23 05:39:38.096627: Epoch time: 18.56 s +2024-11-23 05:39:39.355174: +2024-11-23 05:39:39.355391: Epoch 7979 +2024-11-23 05:39:39.355506: Current learning rate: 5e-05 +2024-11-23 05:39:57.438451: train_loss -0.8391 +2024-11-23 05:39:57.438700: val_loss -0.7969 +2024-11-23 05:39:57.438873: Pseudo dice [0.8671] +2024-11-23 05:39:57.438967: Epoch time: 18.08 s +2024-11-23 05:39:58.372577: +2024-11-23 05:39:58.372802: Epoch 7980 +2024-11-23 05:39:58.372919: Current learning rate: 5e-05 +2024-11-23 05:40:16.794035: train_loss -0.8418 +2024-11-23 05:40:16.794257: val_loss -0.7717 +2024-11-23 05:40:16.794335: Pseudo dice [0.8457] +2024-11-23 05:40:16.794409: Epoch time: 18.42 s +2024-11-23 05:40:17.714391: +2024-11-23 05:40:17.714621: Epoch 7981 +2024-11-23 05:40:17.714736: Current learning rate: 4e-05 +2024-11-23 05:40:35.292567: train_loss -0.8442 +2024-11-23 05:40:35.292812: val_loss -0.77 +2024-11-23 05:40:35.292889: Pseudo dice [0.8511] +2024-11-23 05:40:35.292966: Epoch time: 17.58 s +2024-11-23 05:40:36.237013: +2024-11-23 05:40:36.237258: Epoch 7982 +2024-11-23 05:40:36.237367: Current learning rate: 4e-05 +2024-11-23 05:40:53.108282: train_loss -0.8479 +2024-11-23 05:40:53.108619: val_loss -0.773 +2024-11-23 05:40:53.108702: Pseudo dice [0.8431] +2024-11-23 05:40:53.108783: Epoch time: 16.87 s +2024-11-23 05:40:54.036699: +2024-11-23 05:40:54.036927: Epoch 7983 +2024-11-23 05:40:54.037040: Current learning rate: 4e-05 +2024-11-23 05:41:13.212159: train_loss -0.8457 +2024-11-23 05:41:13.212397: val_loss -0.7823 +2024-11-23 05:41:13.212474: Pseudo dice [0.8439] +2024-11-23 05:41:13.212552: Epoch time: 19.18 s +2024-11-23 05:41:14.126329: +2024-11-23 05:41:14.126547: Epoch 7984 +2024-11-23 05:41:14.126657: Current learning rate: 4e-05 +2024-11-23 05:41:32.995997: train_loss -0.8444 +2024-11-23 05:41:32.996274: val_loss -0.785 +2024-11-23 05:41:32.996356: Pseudo dice [0.8629] +2024-11-23 05:41:32.996441: Epoch time: 18.87 s +2024-11-23 05:41:34.344681: +2024-11-23 05:41:34.344910: Epoch 7985 +2024-11-23 05:41:34.345026: Current learning rate: 4e-05 +2024-11-23 05:41:52.747902: train_loss -0.8337 +2024-11-23 05:41:52.748185: val_loss -0.787 +2024-11-23 05:41:52.748261: Pseudo dice [0.839] +2024-11-23 05:41:52.748339: Epoch time: 18.4 s +2024-11-23 05:41:53.679449: +2024-11-23 05:41:53.679704: Epoch 7986 +2024-11-23 05:41:53.679817: Current learning rate: 3e-05 +2024-11-23 05:42:11.909685: train_loss -0.8391 +2024-11-23 05:42:11.910028: val_loss -0.7818 +2024-11-23 05:42:11.910112: Pseudo dice [0.8512] +2024-11-23 05:42:11.910193: Epoch time: 18.23 s +2024-11-23 05:42:12.846401: +2024-11-23 05:42:12.846633: Epoch 7987 +2024-11-23 05:42:12.846747: Current learning rate: 3e-05 +2024-11-23 05:42:32.873320: train_loss -0.8443 +2024-11-23 05:42:32.873546: val_loss -0.7817 +2024-11-23 05:42:32.873622: Pseudo dice [0.8613] +2024-11-23 05:42:32.873707: Epoch time: 20.03 s +2024-11-23 05:42:33.877614: +2024-11-23 05:42:33.877846: Epoch 7988 +2024-11-23 05:42:33.877952: Current learning rate: 3e-05 +2024-11-23 05:42:52.617247: train_loss -0.8435 +2024-11-23 05:42:52.617495: val_loss -0.8017 +2024-11-23 05:42:52.617622: Pseudo dice [0.8521] +2024-11-23 05:42:52.617700: Epoch time: 18.74 s +2024-11-23 05:42:53.544685: +2024-11-23 05:42:53.544896: Epoch 7989 +2024-11-23 05:42:53.545013: Current learning rate: 3e-05 +2024-11-23 05:43:12.880230: train_loss -0.8434 +2024-11-23 05:43:12.880457: val_loss -0.771 +2024-11-23 05:43:12.880533: Pseudo dice [0.8566] +2024-11-23 05:43:12.880607: Epoch time: 19.34 s +2024-11-23 05:43:13.807629: +2024-11-23 05:43:13.807871: Epoch 7990 +2024-11-23 05:43:13.807981: Current learning rate: 2e-05 +2024-11-23 05:43:32.507152: train_loss -0.8429 +2024-11-23 05:43:32.507406: val_loss -0.773 +2024-11-23 05:43:32.507488: Pseudo dice [0.853] +2024-11-23 05:43:32.507569: Epoch time: 18.7 s +2024-11-23 05:43:33.441052: +2024-11-23 05:43:33.441254: Epoch 7991 +2024-11-23 05:43:33.441362: Current learning rate: 2e-05 +2024-11-23 05:43:51.908718: train_loss -0.8462 +2024-11-23 05:43:51.908928: val_loss -0.801 +2024-11-23 05:43:51.909006: Pseudo dice [0.8473] +2024-11-23 05:43:51.909078: Epoch time: 18.47 s +2024-11-23 05:43:52.845258: +2024-11-23 05:43:52.845486: Epoch 7992 +2024-11-23 05:43:52.845596: Current learning rate: 2e-05 +2024-11-23 05:44:11.408497: train_loss -0.8372 +2024-11-23 05:44:11.408720: val_loss -0.8106 +2024-11-23 05:44:11.408797: Pseudo dice [0.877] +2024-11-23 05:44:11.408870: Epoch time: 18.56 s +2024-11-23 05:44:12.329436: +2024-11-23 05:44:12.329668: Epoch 7993 +2024-11-23 05:44:12.329782: Current learning rate: 2e-05 +2024-11-23 05:44:30.298932: train_loss -0.8447 +2024-11-23 05:44:30.299169: val_loss -0.7655 +2024-11-23 05:44:30.299247: Pseudo dice [0.8466] +2024-11-23 05:44:30.299325: Epoch time: 17.97 s +2024-11-23 05:44:31.284343: +2024-11-23 05:44:31.284565: Epoch 7994 +2024-11-23 05:44:31.284681: Current learning rate: 2e-05 +2024-11-23 05:44:49.092548: train_loss -0.8389 +2024-11-23 05:44:49.095201: val_loss -0.7876 +2024-11-23 05:44:49.099296: Pseudo dice [0.8601] +2024-11-23 05:44:49.099437: Epoch time: 17.81 s +2024-11-23 05:44:50.197258: +2024-11-23 05:44:50.197483: Epoch 7995 +2024-11-23 05:44:50.197599: Current learning rate: 1e-05 +2024-11-23 05:45:09.420020: train_loss -0.8426 +2024-11-23 05:45:09.420241: val_loss -0.8058 +2024-11-23 05:45:09.420316: Pseudo dice [0.854] +2024-11-23 05:45:09.420394: Epoch time: 19.22 s +2024-11-23 05:45:10.722614: +2024-11-23 05:45:10.722860: Epoch 7996 +2024-11-23 05:45:10.722981: Current learning rate: 1e-05 +2024-11-23 05:45:29.056066: train_loss -0.8461 +2024-11-23 05:45:29.056284: val_loss -0.7839 +2024-11-23 05:45:29.056367: Pseudo dice [0.8605] +2024-11-23 05:45:29.056445: Epoch time: 18.33 s +2024-11-23 05:45:29.978018: +2024-11-23 05:45:29.978302: Epoch 7997 +2024-11-23 05:45:29.978412: Current learning rate: 1e-05 +2024-11-23 05:45:49.276699: train_loss -0.8446 +2024-11-23 05:45:49.276927: val_loss -0.8046 +2024-11-23 05:45:49.277006: Pseudo dice [0.8704] +2024-11-23 05:45:49.277082: Epoch time: 19.3 s +2024-11-23 05:45:50.229036: +2024-11-23 05:45:50.229295: Epoch 7998 +2024-11-23 05:45:50.229445: Current learning rate: 1e-05 +2024-11-23 05:46:08.751787: train_loss -0.8416 +2024-11-23 05:46:08.752025: val_loss -0.7711 +2024-11-23 05:46:08.752104: Pseudo dice [0.8513] +2024-11-23 05:46:08.752179: Epoch time: 18.52 s +2024-11-23 05:46:09.690543: +2024-11-23 05:46:09.690817: Epoch 7999 +2024-11-23 05:46:09.690924: Current learning rate: 0.0 +2024-11-23 05:46:27.685968: train_loss -0.8456 +2024-11-23 05:46:27.686228: val_loss -0.8048 +2024-11-23 05:46:27.686303: Pseudo dice [0.8567] +2024-11-23 05:46:27.686376: Epoch time: 18.0 s +2024-11-23 05:46:29.108761: Training done. +2024-11-23 05:46:29.122181: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-23 05:46:29.137658: The split file contains 5 splits. +2024-11-23 05:46:29.137769: Desired fold for training: 0 +2024-11-23 05:46:29.137824: This split has 534 training and 134 validation cases. +2024-11-23 05:46:29.138766: predicting FLAIR_001 +2024-11-23 05:46:29.146072: FLAIR_001, shape torch.Size([1, 139, 140, 183]), rank 0 +2024-11-23 05:46:36.201022: predicting FLAIR_005 +2024-11-23 05:46:36.212780: FLAIR_005, shape torch.Size([1, 137, 137, 178]), rank 0 +2024-11-23 05:46:36.785566: predicting FLAIR_007 +2024-11-23 05:46:36.798630: FLAIR_007, shape torch.Size([1, 126, 143, 189]), rank 0 +2024-11-23 05:46:37.380216: predicting FLAIR_011 +2024-11-23 05:46:37.394766: FLAIR_011, shape torch.Size([1, 131, 144, 189]), rank 0 +2024-11-23 05:46:37.975082: predicting FLAIR_023 +2024-11-23 05:46:38.011898: FLAIR_023, shape torch.Size([1, 135, 147, 191]), rank 0 +2024-11-23 05:46:38.594471: predicting FLAIR_047 +2024-11-23 05:46:38.603669: FLAIR_047, shape torch.Size([1, 132, 133, 183]), rank 0 +2024-11-23 05:46:39.176362: predicting FLAIR_049 +2024-11-23 05:46:39.185182: FLAIR_049, shape torch.Size([1, 133, 140, 198]), rank 0 +2024-11-23 05:46:39.758642: predicting FLAIR_055 +2024-11-23 05:46:39.767767: FLAIR_055, shape torch.Size([1, 132, 141, 193]), rank 0 +2024-11-23 05:46:40.341085: predicting FLAIR_056 +2024-11-23 05:46:40.349815: FLAIR_056, shape torch.Size([1, 133, 141, 196]), rank 0 +2024-11-23 05:46:40.923843: predicting FLAIR_057 +2024-11-23 05:46:40.938687: FLAIR_057, shape torch.Size([1, 131, 140, 184]), rank 0 +2024-11-23 05:46:59.252196: predicting FLAIR_058 +2024-11-23 05:46:59.262879: FLAIR_058, shape torch.Size([1, 137, 159, 196]), rank 0 +2024-11-23 05:46:59.900012: predicting FLAIR_068 +2024-11-23 05:46:59.929889: FLAIR_068, shape torch.Size([1, 140, 154, 200]), rank 0 +2024-11-23 05:47:00.538054: predicting FLAIR_088 +2024-11-23 05:47:00.545936: FLAIR_088, shape torch.Size([1, 141, 145, 196]), rank 0 +2024-11-23 05:47:01.139568: predicting FLAIR_091 +2024-11-23 05:47:01.176596: FLAIR_091, shape torch.Size([1, 126, 141, 169]), rank 0 +2024-11-23 05:47:01.769948: predicting FLAIR_112 +2024-11-23 05:47:01.780488: FLAIR_112, shape torch.Size([1, 135, 138, 176]), rank 0 +2024-11-23 05:47:02.353635: predicting FLAIR_116 +2024-11-23 05:47:02.363441: FLAIR_116, shape torch.Size([1, 148, 150, 201]), rank 0 +2024-11-23 05:47:02.940655: predicting FLAIR_120 +2024-11-23 05:47:02.965122: FLAIR_120, shape torch.Size([1, 130, 162, 193]), rank 0 +2024-11-23 05:47:03.566605: predicting FLAIR_124 +2024-11-23 05:47:03.613844: FLAIR_124, shape torch.Size([1, 136, 150, 187]), rank 0 +2024-11-23 05:47:04.242910: predicting FLAIR_134 +2024-11-23 05:47:04.266880: FLAIR_134, shape torch.Size([1, 132, 151, 182]), rank 0 +2024-11-23 05:47:04.888070: predicting FLAIR_135 +2024-11-23 05:47:04.898920: FLAIR_135, shape torch.Size([1, 134, 149, 173]), rank 0 +2024-11-23 05:47:05.515087: predicting FLAIR_136 +2024-11-23 05:47:05.538610: FLAIR_136, shape torch.Size([1, 139, 160, 204]), rank 0 +2024-11-23 05:47:06.162067: predicting FLAIR_137 +2024-11-23 05:47:06.185794: FLAIR_137, shape torch.Size([1, 139, 144, 182]), rank 0 +2024-11-23 05:47:06.790046: predicting FLAIR_139 +2024-11-23 05:47:06.796845: FLAIR_139, shape torch.Size([1, 139, 154, 177]), rank 0 +2024-11-23 05:47:07.389916: predicting FLAIR_140 +2024-11-23 05:47:07.407926: FLAIR_140, shape torch.Size([1, 137, 154, 166]), rank 0 +2024-11-23 05:47:08.000719: predicting FLAIR_151 +2024-11-23 05:47:08.016391: FLAIR_151, shape torch.Size([1, 144, 144, 197]), rank 0 +2024-11-23 05:47:08.645115: predicting FLAIR_155 +2024-11-23 05:47:08.660058: FLAIR_155, shape torch.Size([1, 134, 152, 184]), rank 0 +2024-11-23 05:47:09.273863: predicting FLAIR_159 +2024-11-23 05:47:09.295988: FLAIR_159, shape torch.Size([1, 134, 145, 190]), rank 0 +2024-11-23 05:47:09.973072: predicting FLAIR_164 +2024-11-23 05:47:09.997649: FLAIR_164, shape torch.Size([1, 130, 153, 190]), rank 0 +2024-11-23 05:47:10.604798: predicting FLAIR_169 +2024-11-23 05:47:10.638624: FLAIR_169, shape torch.Size([1, 140, 154, 196]), rank 0 +2024-11-23 05:47:11.256056: predicting FLAIR_178 +2024-11-23 05:47:11.283746: FLAIR_178, shape torch.Size([1, 143, 150, 190]), rank 0 +2024-11-23 05:47:11.887767: predicting FLAIR_181 +2024-11-23 05:47:11.904563: FLAIR_181, shape torch.Size([1, 137, 199, 159]), rank 0 +2024-11-23 05:47:12.364474: predicting FLAIR_185 +2024-11-23 05:47:12.377016: FLAIR_185, shape torch.Size([1, 131, 188, 150]), rank 0 +2024-11-23 05:47:12.734101: predicting FLAIR_188 +2024-11-23 05:47:12.754616: FLAIR_188, shape torch.Size([1, 134, 190, 149]), rank 0 +2024-11-23 05:47:13.123046: predicting FLAIR_191 +2024-11-23 05:47:13.143281: FLAIR_191, shape torch.Size([1, 139, 190, 150]), rank 0 +2024-11-23 05:47:13.577080: predicting FLAIR_193 +2024-11-23 05:47:13.601792: FLAIR_193, shape torch.Size([1, 142, 192, 153]), rank 0 +2024-11-23 05:47:14.528118: predicting FLAIR_194 +2024-11-23 05:47:14.556903: FLAIR_194, shape torch.Size([1, 135, 196, 159]), rank 0 +2024-11-23 05:47:15.045089: predicting FLAIR_196 +2024-11-23 05:47:15.058471: FLAIR_196, shape torch.Size([1, 134, 193, 156]), rank 0 +2024-11-23 05:47:15.707058: predicting FLAIR_197 +2024-11-23 05:47:15.736188: FLAIR_197, shape torch.Size([1, 125, 179, 154]), rank 0 +2024-11-23 05:47:16.074089: predicting FLAIR_198 +2024-11-23 05:47:16.083930: FLAIR_198, shape torch.Size([1, 126, 190, 146]), rank 0 +2024-11-23 05:47:16.413081: predicting FLAIR_199 +2024-11-23 05:47:16.432146: FLAIR_199, shape torch.Size([1, 128, 186, 146]), rank 0 +2024-11-23 05:47:16.752227: predicting FLAIR_207 +2024-11-23 05:47:16.759434: FLAIR_207, shape torch.Size([1, 128, 192, 141]), rank 0 +2024-11-23 05:47:17.088077: predicting FLAIR_217 +2024-11-23 05:47:17.095242: FLAIR_217, shape torch.Size([1, 127, 189, 138]), rank 0 +2024-11-23 05:47:17.424081: predicting FLAIR_239 +2024-11-23 05:47:17.431951: FLAIR_239, shape torch.Size([1, 127, 188, 148]), rank 0 +2024-11-23 05:47:17.777043: predicting FLAIR_242 +2024-11-23 05:47:17.807613: FLAIR_242, shape torch.Size([1, 138, 158, 204]), rank 0 +2024-11-23 05:47:18.418221: predicting FLAIR_245 +2024-11-23 05:47:18.426195: FLAIR_245, shape torch.Size([1, 133, 184, 151]), rank 0 +2024-11-23 05:47:18.732849: predicting FLAIR_256 +2024-11-23 05:47:18.748858: FLAIR_256, shape torch.Size([1, 136, 193, 158]), rank 0 +2024-11-23 05:47:19.216151: predicting FLAIR_258 +2024-11-23 05:47:19.246718: FLAIR_258, shape torch.Size([1, 126, 190, 151]), rank 0 +2024-11-23 05:47:19.555862: predicting FLAIR_267 +2024-11-23 05:47:19.564095: FLAIR_267, shape torch.Size([1, 130, 184, 152]), rank 0 +2024-11-23 05:47:19.873067: predicting FLAIR_269 +2024-11-23 05:47:19.891754: FLAIR_269, shape torch.Size([1, 137, 193, 157]), rank 0 +2024-11-23 05:47:20.355115: predicting FLAIR_271 +2024-11-23 05:47:20.370707: FLAIR_271, shape torch.Size([1, 130, 163, 201]), rank 0 +2024-11-23 05:47:20.975718: predicting FLAIR_278 +2024-11-23 05:47:20.994808: FLAIR_278, shape torch.Size([1, 126, 191, 156]), rank 0 +2024-11-23 05:47:21.305666: predicting FLAIR_287 +2024-11-23 05:47:21.315366: FLAIR_287, shape torch.Size([1, 136, 146, 187]), rank 0 +2024-11-23 05:47:21.899983: predicting FLAIR_290 +2024-11-23 05:47:21.911263: FLAIR_290, shape torch.Size([1, 129, 150, 188]), rank 0 +2024-11-23 05:47:22.510251: predicting FLAIR_297 +2024-11-23 05:47:22.531283: FLAIR_297, shape torch.Size([1, 132, 152, 190]), rank 0 +2024-11-23 05:47:23.113315: predicting FLAIR_299 +2024-11-23 05:47:23.133215: FLAIR_299, shape torch.Size([1, 128, 182, 146]), rank 0 +2024-11-23 05:47:23.443586: predicting FLAIR_300 +2024-11-23 05:47:23.478937: FLAIR_300, shape torch.Size([1, 135, 196, 153]), rank 0 +2024-11-23 05:47:23.931892: predicting FLAIR_301 +2024-11-23 05:47:23.954708: FLAIR_301, shape torch.Size([1, 124, 192, 150]), rank 0 +2024-11-23 05:47:24.265209: predicting FLAIR_305 +2024-11-23 05:47:24.272061: FLAIR_305, shape torch.Size([1, 132, 143, 187]), rank 0 +2024-11-23 05:47:24.851718: predicting FLAIR_306 +2024-11-23 05:47:24.866875: FLAIR_306, shape torch.Size([1, 130, 198, 153]), rank 0 +2024-11-23 05:47:25.347097: predicting FLAIR_309 +2024-11-23 05:47:25.372150: FLAIR_309, shape torch.Size([1, 127, 184, 151]), rank 0 +2024-11-23 05:47:25.695905: predicting FLAIR_311 +2024-11-23 05:47:25.703349: FLAIR_311, shape torch.Size([1, 131, 189, 151]), rank 0 +2024-11-23 05:47:26.000598: predicting FLAIR_312 +2024-11-23 05:47:26.012198: FLAIR_312, shape torch.Size([1, 130, 183, 152]), rank 0 +2024-11-23 05:47:26.328089: predicting FLAIR_315 +2024-11-23 05:47:26.335767: FLAIR_315, shape torch.Size([1, 128, 146, 180]), rank 0 +2024-11-23 05:47:26.922967: predicting FLAIR_329 +2024-11-23 05:47:26.972680: FLAIR_329, shape torch.Size([1, 144, 154, 194]), rank 0 +2024-11-23 05:47:27.557503: predicting FLAIR_343 +2024-11-23 05:47:27.566484: FLAIR_343, shape torch.Size([1, 132, 181, 146]), rank 0 +2024-11-23 05:47:27.863044: predicting FLAIR_344 +2024-11-23 05:47:27.871035: FLAIR_344, shape torch.Size([1, 137, 151, 196]), rank 0 +2024-11-23 05:47:28.457564: predicting FLAIR_357 +2024-11-23 05:47:28.481541: FLAIR_357, shape torch.Size([1, 137, 159, 193]), rank 0 +2024-11-23 05:47:29.057090: predicting FLAIR_366 +2024-11-23 05:47:29.066238: FLAIR_366, shape torch.Size([1, 128, 150, 182]), rank 0 +2024-11-23 05:47:29.639996: predicting FLAIR_367 +2024-11-23 05:47:29.650959: FLAIR_367, shape torch.Size([1, 134, 153, 188]), rank 0 +2024-11-23 05:47:30.238077: predicting FLAIR_374 +2024-11-23 05:47:30.272649: FLAIR_374, shape torch.Size([1, 133, 145, 183]), rank 0 +2024-11-23 05:47:30.864996: predicting FLAIR_381 +2024-11-23 05:47:30.873820: FLAIR_381, shape torch.Size([1, 135, 153, 185]), rank 0 +2024-11-23 05:47:31.478112: predicting FLAIR_385 +2024-11-23 05:47:31.494982: FLAIR_385, shape torch.Size([1, 123, 151, 188]), rank 0 +2024-11-23 05:47:32.080639: predicting FLAIR_386 +2024-11-23 05:47:32.088657: FLAIR_386, shape torch.Size([1, 135, 150, 193]), rank 0 +2024-11-23 05:47:32.684110: predicting FLAIR_387 +2024-11-23 05:47:32.704224: FLAIR_387, shape torch.Size([1, 134, 141, 185]), rank 0 +2024-11-23 05:47:33.296369: predicting FLAIR_391 +2024-11-23 05:47:33.303471: FLAIR_391, shape torch.Size([1, 138, 158, 173]), rank 0 +2024-11-23 05:47:33.891117: predicting FLAIR_396 +2024-11-23 05:47:33.912307: FLAIR_396, shape torch.Size([1, 130, 159, 186]), rank 0 +2024-11-23 05:47:34.501409: predicting FLAIR_400 +2024-11-23 05:47:34.511648: FLAIR_400, shape torch.Size([1, 125, 148, 179]), rank 0 +2024-11-23 05:47:35.098319: predicting FLAIR_402 +2024-11-23 05:47:35.128313: FLAIR_402, shape torch.Size([1, 130, 148, 185]), rank 0 +2024-11-23 05:47:35.713320: predicting FLAIR_418 +2024-11-23 05:47:35.720407: FLAIR_418, shape torch.Size([1, 131, 189, 142]), rank 0 +2024-11-23 05:47:36.044858: predicting FLAIR_423 +2024-11-23 05:47:36.066866: FLAIR_423, shape torch.Size([1, 138, 189, 148]), rank 0 +2024-11-23 05:47:36.393187: predicting FLAIR_424 +2024-11-23 05:47:36.414810: FLAIR_424, shape torch.Size([1, 148, 187, 162]), rank 0 +2024-11-23 05:47:37.037113: predicting FLAIR_425 +2024-11-23 05:47:37.054344: FLAIR_425, shape torch.Size([1, 127, 191, 152]), rank 0 +2024-11-23 05:47:37.363971: predicting FLAIR_427 +2024-11-23 05:47:37.373722: FLAIR_427, shape torch.Size([1, 129, 188, 150]), rank 0 +2024-11-23 05:47:37.690090: predicting FLAIR_429 +2024-11-23 05:47:37.707885: FLAIR_429, shape torch.Size([1, 132, 194, 157]), rank 0 +2024-11-23 05:47:38.159025: predicting FLAIR_430 +2024-11-23 05:47:38.174844: FLAIR_430, shape torch.Size([1, 134, 197, 157]), rank 0 +2024-11-23 05:47:38.627128: predicting FLAIR_431 +2024-11-23 05:47:38.643915: FLAIR_431, shape torch.Size([1, 127, 176, 150]), rank 0 +2024-11-23 05:47:38.952520: predicting FLAIR_435 +2024-11-23 05:47:38.959524: FLAIR_435, shape torch.Size([1, 130, 176, 148]), rank 0 +2024-11-23 05:47:39.272095: predicting FLAIR_441 +2024-11-23 05:47:39.308617: FLAIR_441, shape torch.Size([1, 136, 197, 158]), rank 0 +2024-11-23 05:47:39.767433: predicting FLAIR_446 +2024-11-23 05:47:39.795612: FLAIR_446, shape torch.Size([1, 144, 203, 162]), rank 0 +2024-11-23 05:47:40.665866: predicting FLAIR_450 +2024-11-23 05:47:40.673713: FLAIR_450, shape torch.Size([1, 122, 183, 143]), rank 0 +2024-11-23 05:47:40.969189: predicting FLAIR_451 +2024-11-23 05:47:40.977151: FLAIR_451, shape torch.Size([1, 135, 181, 148]), rank 0 +2024-11-23 05:47:41.294127: predicting FLAIR_452 +2024-11-23 05:47:41.317119: FLAIR_452, shape torch.Size([1, 126, 144, 192]), rank 0 +2024-11-23 05:47:41.909436: predicting FLAIR_463 +2024-11-23 05:47:41.929312: FLAIR_463, shape torch.Size([1, 129, 182, 139]), rank 0 +2024-11-23 05:47:42.229612: predicting FLAIR_464 +2024-11-23 05:47:42.238960: FLAIR_464, shape torch.Size([1, 131, 192, 152]), rank 0 +2024-11-23 05:47:42.547110: predicting FLAIR_468 +2024-11-23 05:47:42.555620: FLAIR_468, shape torch.Size([1, 132, 180, 147]), rank 0 +2024-11-23 05:47:42.864718: predicting FLAIR_469 +2024-11-23 05:47:42.872344: FLAIR_469, shape torch.Size([1, 138, 151, 186]), rank 0 +2024-11-23 05:47:43.459763: predicting FLAIR_474 +2024-11-23 05:47:43.476887: FLAIR_474, shape torch.Size([1, 131, 141, 182]), rank 0 +2024-11-23 05:47:44.085122: predicting FLAIR_478 +2024-11-23 05:47:44.103252: FLAIR_478, shape torch.Size([1, 130, 149, 199]), rank 0 +2024-11-23 05:47:44.708318: predicting FLAIR_479 +2024-11-23 05:47:44.745697: FLAIR_479, shape torch.Size([1, 138, 152, 199]), rank 0 +2024-11-23 05:47:45.341105: predicting FLAIR_484 +2024-11-23 05:47:45.354824: FLAIR_484, shape torch.Size([1, 135, 142, 187]), rank 0 +2024-11-23 05:47:45.936702: predicting FLAIR_488 +2024-11-23 05:47:45.948961: FLAIR_488, shape torch.Size([1, 131, 158, 193]), rank 0 +2024-11-23 05:47:46.550224: predicting FLAIR_490 +2024-11-23 05:47:46.582552: FLAIR_490, shape torch.Size([1, 139, 155, 196]), rank 0 +2024-11-23 05:47:47.197353: predicting FLAIR_499 +2024-11-23 05:47:47.220431: FLAIR_499, shape torch.Size([1, 138, 149, 185]), rank 0 +2024-11-23 05:47:47.840011: predicting FLAIR_503 +2024-11-23 05:47:47.864815: FLAIR_503, shape torch.Size([1, 128, 154, 195]), rank 0 +2024-11-23 05:47:48.471375: predicting FLAIR_504 +2024-11-23 05:47:48.488599: FLAIR_504, shape torch.Size([1, 137, 152, 192]), rank 0 +2024-11-23 05:47:49.094397: predicting FLAIR_508 +2024-11-23 05:47:49.167851: FLAIR_508, shape torch.Size([1, 141, 160, 202]), rank 0 +2024-11-23 05:47:49.855079: predicting FLAIR_526 +2024-11-23 05:47:49.863999: FLAIR_526, shape torch.Size([1, 133, 146, 222]), rank 0 +2024-11-23 05:47:50.458671: predicting FLAIR_527 +2024-11-23 05:47:50.478410: FLAIR_527, shape torch.Size([1, 139, 145, 193]), rank 0 +2024-11-23 05:47:51.175479: predicting FLAIR_530 +2024-11-23 05:47:51.194761: FLAIR_530, shape torch.Size([1, 134, 150, 193]), rank 0 +2024-11-23 05:47:53.507045: predicting FLAIR_532 +2024-11-23 05:47:53.532693: FLAIR_532, shape torch.Size([1, 137, 154, 209]), rank 0 +2024-11-23 05:47:55.180136: predicting FLAIR_539 +2024-11-23 05:47:55.188852: FLAIR_539, shape torch.Size([1, 130, 142, 182]), rank 0 +2024-11-23 05:47:55.986774: predicting FLAIR_546 +2024-11-23 05:47:55.993304: FLAIR_546, shape torch.Size([1, 130, 140, 176]), rank 0 +2024-11-23 05:47:56.603817: predicting FLAIR_553 +2024-11-23 05:47:56.625975: FLAIR_553, shape torch.Size([1, 132, 151, 176]), rank 0 +2024-11-23 05:47:57.235892: predicting FLAIR_554 +2024-11-23 05:47:57.260061: FLAIR_554, shape torch.Size([1, 132, 142, 178]), rank 0 +2024-11-23 05:47:57.863816: predicting FLAIR_563 +2024-11-23 05:47:57.885620: FLAIR_563, shape torch.Size([1, 126, 151, 190]), rank 0 +2024-11-23 05:47:59.292002: predicting FLAIR_566 +2024-11-23 05:47:59.299289: FLAIR_566, shape torch.Size([1, 138, 138, 185]), rank 0 +2024-11-23 05:47:59.930125: predicting FLAIR_580 +2024-11-23 05:47:59.955769: FLAIR_580, shape torch.Size([1, 132, 151, 202]), rank 0 +2024-11-23 05:48:02.777809: predicting FLAIR_582 +2024-11-23 05:48:02.790933: FLAIR_582, shape torch.Size([1, 134, 155, 203]), rank 0 +2024-11-23 05:48:03.570998: predicting FLAIR_585 +2024-11-23 05:48:03.595903: FLAIR_585, shape torch.Size([1, 133, 154, 194]), rank 0 +2024-11-23 05:48:04.230121: predicting FLAIR_597 +2024-11-23 05:48:04.252012: FLAIR_597, shape torch.Size([1, 124, 147, 193]), rank 0 +2024-11-23 05:48:04.852771: predicting FLAIR_599 +2024-11-23 05:48:04.878193: FLAIR_599, shape torch.Size([1, 127, 154, 195]), rank 0 +2024-11-23 05:48:05.497140: predicting FLAIR_601 +2024-11-23 05:48:05.529615: FLAIR_601, shape torch.Size([1, 133, 148, 192]), rank 0 +2024-11-23 05:48:06.121967: predicting FLAIR_603 +2024-11-23 05:48:06.139177: FLAIR_603, shape torch.Size([1, 127, 145, 194]), rank 0 +2024-11-23 05:48:06.731005: predicting FLAIR_607 +2024-11-23 05:48:06.752133: FLAIR_607, shape torch.Size([1, 132, 151, 194]), rank 0 +2024-11-23 05:48:07.358126: predicting FLAIR_610 +2024-11-23 05:48:07.375769: FLAIR_610, shape torch.Size([1, 135, 164, 198]), rank 0 +2024-11-23 05:48:10.271550: predicting FLAIR_611 +2024-11-23 05:48:10.284913: FLAIR_611, shape torch.Size([1, 139, 147, 190]), rank 0 +2024-11-23 05:48:11.193723: predicting FLAIR_623 +2024-11-23 05:48:11.202857: FLAIR_623, shape torch.Size([1, 141, 158, 190]), rank 0 +2024-11-23 05:48:11.801972: predicting FLAIR_627 +2024-11-23 05:48:11.824346: FLAIR_627, shape torch.Size([1, 133, 152, 198]), rank 0 +2024-11-23 05:48:12.436924: predicting FLAIR_642 +2024-11-23 05:48:12.465456: FLAIR_642, shape torch.Size([1, 132, 152, 185]), rank 0 +2024-11-23 05:48:13.085922: predicting FLAIR_644 +2024-11-23 05:48:13.113146: FLAIR_644, shape torch.Size([1, 131, 147, 197]), rank 0 +2024-11-23 05:48:13.722191: predicting FLAIR_648 +2024-11-23 05:48:13.750531: FLAIR_648, shape torch.Size([1, 141, 152, 202]), rank 0 +2024-11-23 05:48:14.371440: predicting FLAIR_651 +2024-11-23 05:48:14.405133: FLAIR_651, shape torch.Size([1, 141, 157, 199]), rank 0 +2024-11-23 05:48:16.419908: predicting FLAIR_663 +2024-11-23 05:48:16.428439: FLAIR_663, shape torch.Size([1, 135, 158, 193]), rank 0 +2024-11-23 05:48:17.139372: predicting FLAIR_664 +2024-11-23 05:48:17.159341: FLAIR_664, shape torch.Size([1, 136, 143, 186]), rank 0 +2024-11-23 05:48:49.483734: Validation complete +2024-11-23 05:48:49.484503: Mean Validation Dice: 0.793141733058811 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/checkpoint_best.pth b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/checkpoint_best.pth new file mode 100644 index 0000000000000000000000000000000000000000..4ec9692794f795abab28505641763ed2227fb980 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/checkpoint_best.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:48ba3b2265daf43c721f577a57c7129a0e98f872757d3dcbd0129f6de910074d +size 249223778 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/checkpoint_final.pth b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/checkpoint_final.pth new file mode 100644 index 0000000000000000000000000000000000000000..c8d0c6ab6b30eae744f80f8cb1bd08fbbf317458 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/checkpoint_final.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3966dd256074a0ea3c7d16c3a8e7412a6cb5071220df71b54745aeb50c33c33c +size 249224766 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/debug.json b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/debug.json new file mode 100644 index 0000000000000000000000000000000000000000..06538b5e0de5680ca243356fddde2c4c6a381512 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/debug.json @@ -0,0 +1,53 @@ +{ + "_best_ema": "None", + "batch_size": "2", + "configuration_manager": "{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 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device(type='cuda')}", + "network": "OptimizedModule", + "num_epochs": "8000", + "num_input_channels": "1", + "num_iterations_per_epoch": "250", + "num_val_iterations_per_epoch": "50", + "optimizer": "SGD (\nParameter Group 0\n dampening: 0\n differentiable: False\n foreach: None\n initial_lr: 0.01\n lr: 0.01\n maximize: False\n momentum: 0.99\n nesterov: True\n weight_decay: 3e-05\n)", + "output_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1", + "output_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres", + "oversample_foreground_percent": "0.33", + "plans_manager": "{'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 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'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 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2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}", + "preprocessed_dataset_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/nnUNetPlans_3d_fullres", + "preprocessed_dataset_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML", + "save_every": "50", + "torch_version": "2.1.2+cu121", + "unpack_dataset": "True", + "was_initialized": "True", + "weight_decay": "3e-05" +} \ No newline at end of file diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/progress.png b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/progress.png new file mode 100644 index 0000000000000000000000000000000000000000..f679b2696e9642cff60d528427b5ddb4282d1899 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/progress.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:14e008afc506b1c1b98421e352d93fbfda9c3161c843e641638dc449b6efb087 +size 1005632 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/training_log_2024_11_21_10_39_41.txt b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/training_log_2024_11_21_10_39_41.txt new file mode 100644 index 0000000000000000000000000000000000000000..1e1bc3d57840e3bc44a51d787af5f5c29161a2ce --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_1/training_log_2024_11_21_10_39_41.txt @@ -0,0 +1,56422 @@ + +####################################################################### +Please cite the following paper when using nnU-Net: +Isensee, F., Jaeger, P. F., Kohl, S. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 18(2), 203-211. +####################################################################### + +2024-11-21 10:39:41.631327: do_dummy_2d_data_aug: False +2024-11-21 10:39:41.634357: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-21 10:39:41.635180: The split file contains 5 splits. +2024-11-21 10:39:41.635242: Desired fold for training: 1 +2024-11-21 10:39:41.635289: This split has 534 training and 134 validation cases. +2024-11-21 10:39:44.848532: Using torch.compile... + +This is the configuration used by this training: +Configuration name: 3d_fullres + {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False} + +These are the global plan.json settings: + {'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}} + +2024-11-21 10:39:46.539358: unpacking dataset... +2024-11-21 10:39:56.972226: unpacking done... +2024-11-21 10:39:56.981035: Unable to plot network architecture: nnUNet_compile is enabled! +2024-11-21 10:39:56.989831: +2024-11-21 10:39:56.989925: Epoch 0 +2024-11-21 10:39:56.990083: Current learning rate: 0.01 +2024-11-21 10:40:53.126324: train_loss -0.2722 +2024-11-21 10:40:53.130172: val_loss -0.3921 +2024-11-21 10:40:53.130266: Pseudo dice [0.5975] +2024-11-21 10:40:53.130346: Epoch time: 56.14 s +2024-11-21 10:40:53.130410: Yayy! New best EMA pseudo Dice: 0.5975 +2024-11-21 10:40:54.058857: +2024-11-21 10:40:54.059051: Epoch 1 +2024-11-21 10:40:54.059151: Current learning rate: 0.01 +2024-11-21 10:41:12.536877: train_loss -0.5469 +2024-11-21 10:41:12.543043: val_loss -0.5708 +2024-11-21 10:41:12.543203: Pseudo dice [0.6593] +2024-11-21 10:41:12.544412: Epoch time: 18.48 s +2024-11-21 10:41:12.544537: Yayy! New best EMA pseudo Dice: 0.6037 +2024-11-21 10:41:13.621245: +2024-11-21 10:41:13.621429: Epoch 2 +2024-11-21 10:41:13.621544: Current learning rate: 0.01 +2024-11-21 10:41:33.844633: train_loss -0.5806 +2024-11-21 10:41:33.850034: val_loss -0.5878 +2024-11-21 10:41:33.850114: Pseudo dice [0.6938] +2024-11-21 10:41:33.850194: Epoch time: 20.22 s +2024-11-21 10:41:33.850257: Yayy! New best EMA pseudo Dice: 0.6127 +2024-11-21 10:41:35.023809: +2024-11-21 10:41:35.024033: Epoch 3 +2024-11-21 10:41:35.024148: Current learning rate: 0.01 +2024-11-21 10:41:53.203923: train_loss -0.6164 +2024-11-21 10:41:53.204146: val_loss -0.5894 +2024-11-21 10:41:53.204222: Pseudo dice [0.7311] +2024-11-21 10:41:53.204299: Epoch time: 18.18 s +2024-11-21 10:41:53.204362: Yayy! New best EMA pseudo Dice: 0.6245 +2024-11-21 10:41:54.602783: +2024-11-21 10:41:54.602985: Epoch 4 +2024-11-21 10:41:54.603108: Current learning rate: 0.01 +2024-11-21 10:42:13.013068: train_loss -0.6418 +2024-11-21 10:42:13.013448: val_loss -0.6251 +2024-11-21 10:42:13.013533: Pseudo dice [0.736] +2024-11-21 10:42:13.013626: Epoch time: 18.41 s +2024-11-21 10:42:13.013693: Yayy! New best EMA pseudo Dice: 0.6357 +2024-11-21 10:42:14.101960: +2024-11-21 10:42:14.102140: Epoch 5 +2024-11-21 10:42:14.102253: Current learning rate: 0.00999 +2024-11-21 10:42:32.650297: train_loss -0.6519 +2024-11-21 10:42:32.650514: val_loss -0.6541 +2024-11-21 10:42:32.650593: Pseudo dice [0.7704] +2024-11-21 10:42:32.650673: Epoch time: 18.55 s +2024-11-21 10:42:32.650736: Yayy! New best EMA pseudo Dice: 0.6492 +2024-11-21 10:42:33.627640: +2024-11-21 10:42:33.627831: Epoch 6 +2024-11-21 10:42:33.627944: Current learning rate: 0.00999 +2024-11-21 10:42:52.643487: train_loss -0.6646 +2024-11-21 10:42:52.643710: val_loss -0.6177 +2024-11-21 10:42:52.643787: Pseudo dice [0.7348] +2024-11-21 10:42:52.643863: Epoch time: 19.02 s +2024-11-21 10:42:52.643925: Yayy! New best EMA pseudo Dice: 0.6577 +2024-11-21 10:42:53.618985: +2024-11-21 10:42:53.619186: Epoch 7 +2024-11-21 10:42:53.619303: Current learning rate: 0.00999 +2024-11-21 10:43:13.496414: train_loss -0.6526 +2024-11-21 10:43:13.496621: val_loss -0.6088 +2024-11-21 10:43:13.496695: Pseudo dice [0.7386] +2024-11-21 10:43:13.496772: Epoch time: 19.88 s +2024-11-21 10:43:13.496833: Yayy! New best EMA pseudo Dice: 0.6658 +2024-11-21 10:43:14.531116: +2024-11-21 10:43:14.531305: Epoch 8 +2024-11-21 10:43:14.531453: Current learning rate: 0.00999 +2024-11-21 10:43:32.680409: train_loss -0.669 +2024-11-21 10:43:32.682078: val_loss -0.6504 +2024-11-21 10:43:32.682211: Pseudo dice [0.7711] +2024-11-21 10:43:32.682301: Epoch time: 18.15 s +2024-11-21 10:43:32.682371: Yayy! New best EMA pseudo Dice: 0.6763 +2024-11-21 10:43:33.741922: +2024-11-21 10:43:33.742101: Epoch 9 +2024-11-21 10:43:33.742213: Current learning rate: 0.00999 +2024-11-21 10:43:51.182689: train_loss -0.6839 +2024-11-21 10:43:51.182982: val_loss -0.6862 +2024-11-21 10:43:51.183065: Pseudo dice [0.7915] +2024-11-21 10:43:51.183150: Epoch time: 17.44 s +2024-11-21 10:43:51.183212: Yayy! New best EMA pseudo Dice: 0.6879 +2024-11-21 10:43:52.156848: +2024-11-21 10:43:52.157035: Epoch 10 +2024-11-21 10:43:52.157153: Current learning rate: 0.00999 +2024-11-21 10:44:11.320653: train_loss -0.6787 +2024-11-21 10:44:11.320865: val_loss -0.6564 +2024-11-21 10:44:11.320940: Pseudo dice [0.7399] +2024-11-21 10:44:11.321022: Epoch time: 19.16 s +2024-11-21 10:44:11.321084: Yayy! New best EMA pseudo Dice: 0.6931 +2024-11-21 10:44:12.274817: +2024-11-21 10:44:12.275009: Epoch 11 +2024-11-21 10:44:12.275126: Current learning rate: 0.00999 +2024-11-21 10:44:30.491557: train_loss -0.6729 +2024-11-21 10:44:30.491832: val_loss -0.6279 +2024-11-21 10:44:30.491911: Pseudo dice [0.7679] +2024-11-21 10:44:30.491994: Epoch time: 18.22 s +2024-11-21 10:44:30.492061: Yayy! New best EMA pseudo Dice: 0.7005 +2024-11-21 10:44:31.461984: +2024-11-21 10:44:31.462164: Epoch 12 +2024-11-21 10:44:31.462279: Current learning rate: 0.00999 +2024-11-21 10:44:50.715470: train_loss -0.6669 +2024-11-21 10:44:50.715708: val_loss -0.6294 +2024-11-21 10:44:50.715783: Pseudo dice [0.7732] +2024-11-21 10:44:50.715868: Epoch time: 19.25 s +2024-11-21 10:44:50.715931: Yayy! New best EMA pseudo Dice: 0.7078 +2024-11-21 10:44:51.677123: +2024-11-21 10:44:51.677338: Epoch 13 +2024-11-21 10:44:51.677457: Current learning rate: 0.00999 +2024-11-21 10:45:10.876990: train_loss -0.6704 +2024-11-21 10:45:10.877209: val_loss -0.7009 +2024-11-21 10:45:10.877284: Pseudo dice [0.7886] +2024-11-21 10:45:10.877360: Epoch time: 19.2 s +2024-11-21 10:45:10.882567: Yayy! New best EMA pseudo Dice: 0.7159 +2024-11-21 10:45:11.945439: +2024-11-21 10:45:11.945615: Epoch 14 +2024-11-21 10:45:11.945729: Current learning rate: 0.00998 +2024-11-21 10:45:30.887823: train_loss -0.6856 +2024-11-21 10:45:30.888050: val_loss -0.6686 +2024-11-21 10:45:30.888125: Pseudo dice [0.7716] +2024-11-21 10:45:30.888201: Epoch time: 18.94 s +2024-11-21 10:45:30.888263: Yayy! New best EMA pseudo Dice: 0.7215 +2024-11-21 10:45:32.251647: +2024-11-21 10:45:32.251843: Epoch 15 +2024-11-21 10:45:32.251961: Current learning rate: 0.00998 +2024-11-21 10:45:50.658070: train_loss -0.6806 +2024-11-21 10:45:50.658306: val_loss -0.6748 +2024-11-21 10:45:50.658381: Pseudo dice [0.7918] +2024-11-21 10:45:50.658463: Epoch time: 18.41 s +2024-11-21 10:45:50.658529: Yayy! New best EMA pseudo Dice: 0.7285 +2024-11-21 10:45:51.638506: +2024-11-21 10:45:51.638673: Epoch 16 +2024-11-21 10:45:51.638782: Current learning rate: 0.00998 +2024-11-21 10:46:10.207161: train_loss -0.699 +2024-11-21 10:46:10.214152: val_loss -0.6745 +2024-11-21 10:46:10.214277: Pseudo dice [0.7943] +2024-11-21 10:46:10.214363: Epoch time: 18.57 s +2024-11-21 10:46:10.214432: Yayy! New best EMA pseudo Dice: 0.7351 +2024-11-21 10:46:11.251542: +2024-11-21 10:46:11.251714: Epoch 17 +2024-11-21 10:46:11.251829: Current learning rate: 0.00998 +2024-11-21 10:46:30.860828: train_loss -0.6895 +2024-11-21 10:46:30.861053: val_loss -0.713 +2024-11-21 10:46:30.861131: Pseudo dice [0.8135] +2024-11-21 10:46:30.861211: Epoch time: 19.61 s +2024-11-21 10:46:30.861275: Yayy! New best EMA pseudo Dice: 0.7429 +2024-11-21 10:46:31.847644: +2024-11-21 10:46:31.847838: Epoch 18 +2024-11-21 10:46:31.847952: Current learning rate: 0.00998 +2024-11-21 10:46:51.061799: train_loss -0.7023 +2024-11-21 10:46:51.062022: val_loss -0.6709 +2024-11-21 10:46:51.062101: Pseudo dice [0.7688] +2024-11-21 10:46:51.062181: Epoch time: 19.21 s +2024-11-21 10:46:51.062244: Yayy! New best EMA pseudo Dice: 0.7455 +2024-11-21 10:46:52.028508: +2024-11-21 10:46:52.028769: Epoch 19 +2024-11-21 10:46:52.028909: Current learning rate: 0.00998 +2024-11-21 10:47:10.406912: train_loss -0.7146 +2024-11-21 10:47:10.407161: val_loss -0.691 +2024-11-21 10:47:10.407235: Pseudo dice [0.8062] +2024-11-21 10:47:10.409499: Epoch time: 18.38 s +2024-11-21 10:47:10.409590: Yayy! New best EMA pseudo Dice: 0.7516 +2024-11-21 10:47:11.401283: +2024-11-21 10:47:11.401463: Epoch 20 +2024-11-21 10:47:11.401578: Current learning rate: 0.00998 +2024-11-21 10:47:29.954032: train_loss -0.7064 +2024-11-21 10:47:29.954247: val_loss -0.704 +2024-11-21 10:47:29.954323: Pseudo dice [0.8208] +2024-11-21 10:47:29.954401: Epoch time: 18.55 s +2024-11-21 10:47:29.954501: Yayy! New best EMA pseudo Dice: 0.7585 +2024-11-21 10:47:30.925730: +2024-11-21 10:47:30.925907: Epoch 21 +2024-11-21 10:47:30.926032: Current learning rate: 0.00998 +2024-11-21 10:47:49.244171: train_loss -0.6799 +2024-11-21 10:47:49.244403: val_loss -0.6631 +2024-11-21 10:47:49.244495: Pseudo dice [0.7782] +2024-11-21 10:47:49.244577: Epoch time: 18.32 s +2024-11-21 10:47:49.244639: Yayy! New best EMA pseudo Dice: 0.7605 +2024-11-21 10:47:50.189521: +2024-11-21 10:47:50.189702: Epoch 22 +2024-11-21 10:47:50.189811: Current learning rate: 0.00998 +2024-11-21 10:48:09.545545: train_loss -0.6937 +2024-11-21 10:48:09.545787: val_loss -0.6889 +2024-11-21 10:48:09.545867: Pseudo dice [0.7755] +2024-11-21 10:48:09.545949: Epoch time: 19.36 s +2024-11-21 10:48:09.546274: Yayy! New best EMA pseudo Dice: 0.762 +2024-11-21 10:48:10.508801: +2024-11-21 10:48:10.508978: Epoch 23 +2024-11-21 10:48:10.509098: Current learning rate: 0.00997 +2024-11-21 10:48:28.994918: train_loss -0.6885 +2024-11-21 10:48:28.995128: val_loss -0.6675 +2024-11-21 10:48:28.995200: Pseudo dice [0.7802] +2024-11-21 10:48:28.995277: Epoch time: 18.49 s +2024-11-21 10:48:28.995338: Yayy! New best EMA pseudo Dice: 0.7638 +2024-11-21 10:48:29.958233: +2024-11-21 10:48:29.958412: Epoch 24 +2024-11-21 10:48:29.958525: Current learning rate: 0.00997 +2024-11-21 10:48:48.846291: train_loss -0.7034 +2024-11-21 10:48:48.846509: val_loss -0.714 +2024-11-21 10:48:48.846583: Pseudo dice [0.782] +2024-11-21 10:48:48.846659: Epoch time: 18.89 s +2024-11-21 10:48:48.846720: Yayy! New best EMA pseudo Dice: 0.7656 +2024-11-21 10:48:50.082348: +2024-11-21 10:48:50.082545: Epoch 25 +2024-11-21 10:48:50.082667: Current learning rate: 0.00997 +2024-11-21 10:49:07.958527: train_loss -0.7168 +2024-11-21 10:49:07.963950: val_loss -0.6857 +2024-11-21 10:49:07.964091: Pseudo dice [0.7911] +2024-11-21 10:49:07.964184: Epoch time: 17.88 s +2024-11-21 10:49:07.964257: Yayy! New best EMA pseudo Dice: 0.7682 +2024-11-21 10:49:09.456733: +2024-11-21 10:49:09.456913: Epoch 26 +2024-11-21 10:49:09.457027: Current learning rate: 0.00997 +2024-11-21 10:49:29.394542: train_loss -0.7097 +2024-11-21 10:49:29.394788: val_loss -0.678 +2024-11-21 10:49:29.394866: Pseudo dice [0.7895] +2024-11-21 10:49:29.394950: Epoch time: 19.94 s +2024-11-21 10:49:29.395022: Yayy! New best EMA pseudo Dice: 0.7703 +2024-11-21 10:49:30.374451: +2024-11-21 10:49:30.374630: Epoch 27 +2024-11-21 10:49:30.374745: Current learning rate: 0.00997 +2024-11-21 10:49:49.070515: train_loss -0.7135 +2024-11-21 10:49:49.070747: val_loss -0.6871 +2024-11-21 10:49:49.070825: Pseudo dice [0.7805] +2024-11-21 10:49:49.070904: Epoch time: 18.7 s +2024-11-21 10:49:49.070967: Yayy! New best EMA pseudo Dice: 0.7713 +2024-11-21 10:49:50.013887: +2024-11-21 10:49:50.014086: Epoch 28 +2024-11-21 10:49:50.014199: Current learning rate: 0.00997 +2024-11-21 10:50:08.139690: train_loss -0.7178 +2024-11-21 10:50:08.139907: val_loss -0.7108 +2024-11-21 10:50:08.140007: Pseudo dice [0.8089] +2024-11-21 10:50:08.140143: Epoch time: 18.13 s +2024-11-21 10:50:08.140206: Yayy! New best EMA pseudo Dice: 0.7751 +2024-11-21 10:50:09.097745: +2024-11-21 10:50:09.097915: Epoch 29 +2024-11-21 10:50:09.098027: Current learning rate: 0.00997 +2024-11-21 10:50:28.174210: train_loss -0.7 +2024-11-21 10:50:28.174457: val_loss -0.663 +2024-11-21 10:50:28.174536: Pseudo dice [0.7878] +2024-11-21 10:50:28.174625: Epoch time: 19.08 s +2024-11-21 10:50:28.174688: Yayy! New best EMA pseudo Dice: 0.7763 +2024-11-21 10:50:29.136974: +2024-11-21 10:50:29.137207: Epoch 30 +2024-11-21 10:50:29.137326: Current learning rate: 0.00997 +2024-11-21 10:50:47.953814: train_loss -0.7013 +2024-11-21 10:50:47.954062: val_loss -0.6738 +2024-11-21 10:50:47.954142: Pseudo dice [0.7809] +2024-11-21 10:50:47.954226: Epoch time: 18.82 s +2024-11-21 10:50:47.954289: Yayy! New best EMA pseudo Dice: 0.7768 +2024-11-21 10:50:48.947797: +2024-11-21 10:50:48.947972: Epoch 31 +2024-11-21 10:50:48.948091: Current learning rate: 0.00997 +2024-11-21 10:51:08.004597: train_loss -0.7088 +2024-11-21 10:51:08.004836: val_loss -0.7034 +2024-11-21 10:51:08.004913: Pseudo dice [0.8178] +2024-11-21 10:51:08.004998: Epoch time: 19.06 s +2024-11-21 10:51:08.005075: Yayy! New best EMA pseudo Dice: 0.7809 +2024-11-21 10:51:09.017599: +2024-11-21 10:51:09.017792: Epoch 32 +2024-11-21 10:51:09.017905: Current learning rate: 0.00996 +2024-11-21 10:51:29.053233: train_loss -0.714 +2024-11-21 10:51:29.053440: val_loss -0.6971 +2024-11-21 10:51:29.053514: Pseudo dice [0.8205] +2024-11-21 10:51:29.053592: Epoch time: 20.04 s +2024-11-21 10:51:29.053657: Yayy! New best EMA pseudo Dice: 0.7849 +2024-11-21 10:51:30.025654: +2024-11-21 10:51:30.025833: Epoch 33 +2024-11-21 10:51:30.025943: Current learning rate: 0.00996 +2024-11-21 10:51:48.675361: train_loss -0.7182 +2024-11-21 10:51:48.675627: val_loss -0.6844 +2024-11-21 10:51:48.675702: Pseudo dice [0.7832] +2024-11-21 10:51:48.675789: Epoch time: 18.65 s +2024-11-21 10:51:49.549574: +2024-11-21 10:51:49.549740: Epoch 34 +2024-11-21 10:51:49.549849: Current learning rate: 0.00996 +2024-11-21 10:52:08.346930: train_loss -0.7189 +2024-11-21 10:52:08.347151: val_loss -0.7049 +2024-11-21 10:52:08.347237: Pseudo dice [0.8041] +2024-11-21 10:52:08.347317: Epoch time: 18.8 s +2024-11-21 10:52:08.347377: Yayy! New best EMA pseudo Dice: 0.7866 +2024-11-21 10:52:09.339437: +2024-11-21 10:52:09.339640: Epoch 35 +2024-11-21 10:52:09.339752: Current learning rate: 0.00996 +2024-11-21 10:52:28.099699: train_loss -0.7158 +2024-11-21 10:52:28.100001: val_loss -0.6955 +2024-11-21 10:52:28.100089: Pseudo dice [0.7954] +2024-11-21 10:52:28.100168: Epoch time: 18.76 s +2024-11-21 10:52:28.100229: Yayy! New best EMA pseudo Dice: 0.7875 +2024-11-21 10:52:29.170180: +2024-11-21 10:52:29.170365: Epoch 36 +2024-11-21 10:52:29.170487: Current learning rate: 0.00996 +2024-11-21 10:52:47.415389: train_loss -0.7304 +2024-11-21 10:52:47.415621: val_loss -0.703 +2024-11-21 10:52:47.415702: Pseudo dice [0.8059] +2024-11-21 10:52:47.415786: Epoch time: 18.25 s +2024-11-21 10:52:47.415850: Yayy! New best EMA pseudo Dice: 0.7894 +2024-11-21 10:52:48.441373: +2024-11-21 10:52:48.441564: Epoch 37 +2024-11-21 10:52:48.441679: Current learning rate: 0.00996 +2024-11-21 10:53:07.003164: train_loss -0.7214 +2024-11-21 10:53:07.003401: val_loss -0.7084 +2024-11-21 10:53:07.003475: Pseudo dice [0.7989] +2024-11-21 10:53:07.003558: Epoch time: 18.56 s +2024-11-21 10:53:07.003619: Yayy! New best EMA pseudo Dice: 0.7903 +2024-11-21 10:53:08.372291: +2024-11-21 10:53:08.372509: Epoch 38 +2024-11-21 10:53:08.372624: Current learning rate: 0.00996 +2024-11-21 10:53:26.986030: train_loss -0.7297 +2024-11-21 10:53:26.986254: val_loss -0.7109 +2024-11-21 10:53:26.986330: Pseudo dice [0.806] +2024-11-21 10:53:26.986406: Epoch time: 18.61 s +2024-11-21 10:53:26.986467: Yayy! New best EMA pseudo Dice: 0.7919 +2024-11-21 10:53:27.969347: +2024-11-21 10:53:27.969549: Epoch 39 +2024-11-21 10:53:27.969665: Current learning rate: 0.00996 +2024-11-21 10:53:47.918279: train_loss -0.7309 +2024-11-21 10:53:47.918492: val_loss -0.7007 +2024-11-21 10:53:47.918569: Pseudo dice [0.8013] +2024-11-21 10:53:47.918649: Epoch time: 19.95 s +2024-11-21 10:53:47.918724: Yayy! New best EMA pseudo Dice: 0.7928 +2024-11-21 10:53:48.918558: +2024-11-21 10:53:48.918767: Epoch 40 +2024-11-21 10:53:48.918882: Current learning rate: 0.00995 +2024-11-21 10:54:07.356810: train_loss -0.7235 +2024-11-21 10:54:07.357123: val_loss -0.6868 +2024-11-21 10:54:07.357205: Pseudo dice [0.7537] +2024-11-21 10:54:07.357291: Epoch time: 18.44 s +2024-11-21 10:54:08.237283: +2024-11-21 10:54:08.237456: Epoch 41 +2024-11-21 10:54:08.237569: Current learning rate: 0.00995 +2024-11-21 10:54:26.463853: train_loss -0.7137 +2024-11-21 10:54:26.464077: val_loss -0.6889 +2024-11-21 10:54:26.464152: Pseudo dice [0.7969] +2024-11-21 10:54:26.464228: Epoch time: 18.23 s +2024-11-21 10:54:27.220318: +2024-11-21 10:54:27.220655: Epoch 42 +2024-11-21 10:54:27.220772: Current learning rate: 0.00995 +2024-11-21 10:54:45.967415: train_loss -0.7209 +2024-11-21 10:54:45.967635: val_loss -0.6783 +2024-11-21 10:54:45.967708: Pseudo dice [0.7869] +2024-11-21 10:54:45.972967: Epoch time: 18.75 s +2024-11-21 10:54:46.732623: +2024-11-21 10:54:46.732826: Epoch 43 +2024-11-21 10:54:46.732945: Current learning rate: 0.00995 +2024-11-21 10:55:05.912048: train_loss -0.7192 +2024-11-21 10:55:05.917480: val_loss -0.7176 +2024-11-21 10:55:05.917630: Pseudo dice [0.8083] +2024-11-21 10:55:05.917729: Epoch time: 19.18 s +2024-11-21 10:55:06.666052: +2024-11-21 10:55:06.666289: Epoch 44 +2024-11-21 10:55:06.666401: Current learning rate: 0.00995 +2024-11-21 10:55:25.271350: train_loss -0.7217 +2024-11-21 10:55:25.271648: val_loss -0.7063 +2024-11-21 10:55:25.271729: Pseudo dice [0.8133] +2024-11-21 10:55:25.271810: Epoch time: 18.61 s +2024-11-21 10:55:25.273425: Yayy! New best EMA pseudo Dice: 0.7935 +2024-11-21 10:55:26.274396: +2024-11-21 10:55:26.274668: Epoch 45 +2024-11-21 10:55:26.274787: Current learning rate: 0.00995 +2024-11-21 10:55:44.912247: train_loss -0.7289 +2024-11-21 10:55:44.912460: val_loss -0.7388 +2024-11-21 10:55:44.912537: Pseudo dice [0.8101] +2024-11-21 10:55:44.912614: Epoch time: 18.64 s +2024-11-21 10:55:44.912679: Yayy! New best EMA pseudo Dice: 0.7952 +2024-11-21 10:55:45.859472: +2024-11-21 10:55:45.859662: Epoch 46 +2024-11-21 10:55:45.859779: Current learning rate: 0.00995 +2024-11-21 10:56:04.887145: train_loss -0.7237 +2024-11-21 10:56:04.887424: val_loss -0.7271 +2024-11-21 10:56:04.887503: Pseudo dice [0.8033] +2024-11-21 10:56:04.887582: Epoch time: 19.03 s +2024-11-21 10:56:04.887648: Yayy! New best EMA pseudo Dice: 0.796 +2024-11-21 10:56:05.860974: +2024-11-21 10:56:05.861179: Epoch 47 +2024-11-21 10:56:05.861297: Current learning rate: 0.00995 +2024-11-21 10:56:24.153860: train_loss -0.722 +2024-11-21 10:56:24.154101: val_loss -0.6948 +2024-11-21 10:56:24.154180: Pseudo dice [0.809] +2024-11-21 10:56:24.154267: Epoch time: 18.29 s +2024-11-21 10:56:24.154367: Yayy! New best EMA pseudo Dice: 0.7973 +2024-11-21 10:56:25.091383: +2024-11-21 10:56:25.091564: Epoch 48 +2024-11-21 10:56:25.091686: Current learning rate: 0.00995 +2024-11-21 10:56:44.538559: train_loss -0.6908 +2024-11-21 10:56:44.538815: val_loss -0.6893 +2024-11-21 10:56:44.538893: Pseudo dice [0.7753] +2024-11-21 10:56:44.538971: Epoch time: 19.45 s +2024-11-21 10:56:45.295612: +2024-11-21 10:56:45.295794: Epoch 49 +2024-11-21 10:56:45.295904: Current learning rate: 0.00994 +2024-11-21 10:57:03.420129: train_loss -0.7161 +2024-11-21 10:57:03.420358: val_loss -0.679 +2024-11-21 10:57:03.420437: Pseudo dice [0.7923] +2024-11-21 10:57:03.420526: Epoch time: 18.13 s +2024-11-21 10:57:04.384924: +2024-11-21 10:57:04.385195: Epoch 50 +2024-11-21 10:57:04.385314: Current learning rate: 0.00994 +2024-11-21 10:57:23.039239: train_loss -0.7174 +2024-11-21 10:57:23.039474: val_loss -0.7061 +2024-11-21 10:57:23.039548: Pseudo dice [0.8066] +2024-11-21 10:57:23.039631: Epoch time: 18.66 s +2024-11-21 10:57:23.792230: +2024-11-21 10:57:23.792451: Epoch 51 +2024-11-21 10:57:23.792568: Current learning rate: 0.00994 +2024-11-21 10:57:41.811586: train_loss -0.7136 +2024-11-21 10:57:41.811793: val_loss -0.6687 +2024-11-21 10:57:41.811871: Pseudo dice [0.7903] +2024-11-21 10:57:41.811962: Epoch time: 18.02 s +2024-11-21 10:57:42.660894: +2024-11-21 10:57:42.661077: Epoch 52 +2024-11-21 10:57:42.661188: Current learning rate: 0.00994 +2024-11-21 10:58:01.946546: train_loss -0.7258 +2024-11-21 10:58:01.951932: val_loss -0.7178 +2024-11-21 10:58:01.952121: Pseudo dice [0.807] +2024-11-21 10:58:01.952204: Epoch time: 19.29 s +2024-11-21 10:58:02.711063: +2024-11-21 10:58:02.711259: Epoch 53 +2024-11-21 10:58:02.711374: Current learning rate: 0.00994 +2024-11-21 10:58:21.069746: train_loss -0.7218 +2024-11-21 10:58:21.072186: val_loss -0.7057 +2024-11-21 10:58:21.072278: Pseudo dice [0.8047] +2024-11-21 10:58:21.072371: Epoch time: 18.36 s +2024-11-21 10:58:21.072438: Yayy! New best EMA pseudo Dice: 0.7974 +2024-11-21 10:58:22.106109: +2024-11-21 10:58:22.106389: Epoch 54 +2024-11-21 10:58:22.106502: Current learning rate: 0.00994 +2024-11-21 10:58:41.554221: train_loss -0.7318 +2024-11-21 10:58:41.554442: val_loss -0.7042 +2024-11-21 10:58:41.554518: Pseudo dice [0.7969] +2024-11-21 10:58:41.554595: Epoch time: 19.45 s +2024-11-21 10:58:42.312429: +2024-11-21 10:58:42.312631: Epoch 55 +2024-11-21 10:58:42.312745: Current learning rate: 0.00994 +2024-11-21 10:59:02.330432: train_loss -0.737 +2024-11-21 10:59:02.330654: val_loss -0.7123 +2024-11-21 10:59:02.332936: Pseudo dice [0.8149] +2024-11-21 10:59:02.333033: Epoch time: 20.02 s +2024-11-21 10:59:02.333102: Yayy! New best EMA pseudo Dice: 0.7991 +2024-11-21 10:59:03.424042: +2024-11-21 10:59:03.424244: Epoch 56 +2024-11-21 10:59:03.424358: Current learning rate: 0.00994 +2024-11-21 10:59:21.276167: train_loss -0.7244 +2024-11-21 10:59:21.276376: val_loss -0.7226 +2024-11-21 10:59:21.276450: Pseudo dice [0.8056] +2024-11-21 10:59:21.276525: Epoch time: 17.85 s +2024-11-21 10:59:21.276587: Yayy! New best EMA pseudo Dice: 0.7997 +2024-11-21 10:59:22.253622: +2024-11-21 10:59:22.253824: Epoch 57 +2024-11-21 10:59:22.253938: Current learning rate: 0.00994 +2024-11-21 10:59:40.954216: train_loss -0.7383 +2024-11-21 10:59:40.954459: val_loss -0.7146 +2024-11-21 10:59:40.954538: Pseudo dice [0.7871] +2024-11-21 10:59:40.954627: Epoch time: 18.7 s +2024-11-21 10:59:41.718838: +2024-11-21 10:59:41.719038: Epoch 58 +2024-11-21 10:59:41.719158: Current learning rate: 0.00993 +2024-11-21 10:59:59.563960: train_loss -0.7221 +2024-11-21 10:59:59.564184: val_loss -0.7337 +2024-11-21 10:59:59.564261: Pseudo dice [0.821] +2024-11-21 10:59:59.564338: Epoch time: 17.85 s +2024-11-21 10:59:59.564396: Yayy! New best EMA pseudo Dice: 0.8007 +2024-11-21 11:00:00.518724: +2024-11-21 11:00:00.518973: Epoch 59 +2024-11-21 11:00:00.519093: Current learning rate: 0.00993 +2024-11-21 11:00:18.682586: train_loss -0.7266 +2024-11-21 11:00:18.682803: val_loss -0.7052 +2024-11-21 11:00:18.682875: Pseudo dice [0.8167] +2024-11-21 11:00:18.682953: Epoch time: 18.16 s +2024-11-21 11:00:18.685224: Yayy! New best EMA pseudo Dice: 0.8023 +2024-11-21 11:00:19.764208: +2024-11-21 11:00:19.764472: Epoch 60 +2024-11-21 11:00:19.764591: Current learning rate: 0.00993 +2024-11-21 11:00:38.637711: train_loss -0.7306 +2024-11-21 11:00:38.637930: val_loss -0.705 +2024-11-21 11:00:38.638020: Pseudo dice [0.8161] +2024-11-21 11:00:38.638148: Epoch time: 18.87 s +2024-11-21 11:00:38.638216: Yayy! New best EMA pseudo Dice: 0.8037 +2024-11-21 11:00:40.085443: +2024-11-21 11:00:40.085644: Epoch 61 +2024-11-21 11:00:40.085747: Current learning rate: 0.00993 +2024-11-21 11:00:59.695973: train_loss -0.7292 +2024-11-21 11:00:59.701358: val_loss -0.7168 +2024-11-21 11:00:59.701506: Pseudo dice [0.8107] +2024-11-21 11:00:59.701591: Epoch time: 19.61 s +2024-11-21 11:00:59.701656: Yayy! New best EMA pseudo Dice: 0.8044 +2024-11-21 11:01:00.803580: +2024-11-21 11:01:00.803773: Epoch 62 +2024-11-21 11:01:00.803884: Current learning rate: 0.00993 +2024-11-21 11:01:20.198384: train_loss -0.7145 +2024-11-21 11:01:20.198672: val_loss -0.7018 +2024-11-21 11:01:20.198749: Pseudo dice [0.7895] +2024-11-21 11:01:20.198827: Epoch time: 19.4 s +2024-11-21 11:01:20.964151: +2024-11-21 11:01:20.964369: Epoch 63 +2024-11-21 11:01:20.964487: Current learning rate: 0.00993 +2024-11-21 11:01:40.570221: train_loss -0.7323 +2024-11-21 11:01:40.570432: val_loss -0.7448 +2024-11-21 11:01:40.570505: Pseudo dice [0.8013] +2024-11-21 11:01:40.570583: Epoch time: 19.61 s +2024-11-21 11:01:41.343508: +2024-11-21 11:01:41.343832: Epoch 64 +2024-11-21 11:01:41.343946: Current learning rate: 0.00993 +2024-11-21 11:02:01.134591: train_loss -0.7268 +2024-11-21 11:02:01.134840: val_loss -0.7443 +2024-11-21 11:02:01.134918: Pseudo dice [0.8213] +2024-11-21 11:02:01.135011: Epoch time: 19.79 s +2024-11-21 11:02:01.140277: Yayy! New best EMA pseudo Dice: 0.8046 +2024-11-21 11:02:02.157327: +2024-11-21 11:02:02.157517: Epoch 65 +2024-11-21 11:02:02.157628: Current learning rate: 0.00993 +2024-11-21 11:02:20.247321: train_loss -0.7343 +2024-11-21 11:02:20.247586: val_loss -0.7257 +2024-11-21 11:02:20.247676: Pseudo dice [0.8132] +2024-11-21 11:02:20.247753: Epoch time: 18.09 s +2024-11-21 11:02:20.247814: Yayy! New best EMA pseudo Dice: 0.8055 +2024-11-21 11:02:21.237047: +2024-11-21 11:02:21.237247: Epoch 66 +2024-11-21 11:02:21.237360: Current learning rate: 0.00993 +2024-11-21 11:02:39.340211: train_loss -0.7256 +2024-11-21 11:02:39.340421: val_loss -0.6954 +2024-11-21 11:02:39.340493: Pseudo dice [0.8136] +2024-11-21 11:02:39.340778: Epoch time: 18.1 s +2024-11-21 11:02:39.340844: Yayy! New best EMA pseudo Dice: 0.8063 +2024-11-21 11:02:40.329077: +2024-11-21 11:02:40.329320: Epoch 67 +2024-11-21 11:02:40.329431: Current learning rate: 0.00992 +2024-11-21 11:02:59.349190: train_loss -0.7338 +2024-11-21 11:02:59.354594: val_loss -0.718 +2024-11-21 11:02:59.354700: Pseudo dice [0.8167] +2024-11-21 11:02:59.354789: Epoch time: 19.02 s +2024-11-21 11:02:59.354861: Yayy! New best EMA pseudo Dice: 0.8073 +2024-11-21 11:03:00.328246: +2024-11-21 11:03:00.328439: Epoch 68 +2024-11-21 11:03:00.328557: Current learning rate: 0.00992 +2024-11-21 11:03:18.758376: train_loss -0.7295 +2024-11-21 11:03:18.758607: val_loss -0.7217 +2024-11-21 11:03:18.758692: Pseudo dice [0.8116] +2024-11-21 11:03:18.758773: Epoch time: 18.43 s +2024-11-21 11:03:18.758833: Yayy! New best EMA pseudo Dice: 0.8078 +2024-11-21 11:03:19.784794: +2024-11-21 11:03:19.785074: Epoch 69 +2024-11-21 11:03:19.785192: Current learning rate: 0.00992 +2024-11-21 11:03:38.551708: train_loss -0.7345 +2024-11-21 11:03:38.551923: val_loss -0.6902 +2024-11-21 11:03:38.552007: Pseudo dice [0.7809] +2024-11-21 11:03:38.552084: Epoch time: 18.77 s +2024-11-21 11:03:39.333568: +2024-11-21 11:03:39.333763: Epoch 70 +2024-11-21 11:03:39.333881: Current learning rate: 0.00992 +2024-11-21 11:03:57.117328: train_loss -0.7301 +2024-11-21 11:03:57.117527: val_loss -0.737 +2024-11-21 11:03:57.117599: Pseudo dice [0.8315] +2024-11-21 11:03:57.117673: Epoch time: 17.78 s +2024-11-21 11:03:57.892600: +2024-11-21 11:03:57.892802: Epoch 71 +2024-11-21 11:03:57.892913: Current learning rate: 0.00992 +2024-11-21 11:04:16.794525: train_loss -0.729 +2024-11-21 11:04:16.794752: val_loss -0.704 +2024-11-21 11:04:16.794830: Pseudo dice [0.7975] +2024-11-21 11:04:16.794913: Epoch time: 18.9 s +2024-11-21 11:04:17.677426: +2024-11-21 11:04:17.677628: Epoch 72 +2024-11-21 11:04:17.677747: Current learning rate: 0.00992 +2024-11-21 11:04:35.772269: train_loss -0.7268 +2024-11-21 11:04:35.772512: val_loss -0.711 +2024-11-21 11:04:35.772587: Pseudo dice [0.7987] +2024-11-21 11:04:35.772669: Epoch time: 18.1 s +2024-11-21 11:04:36.958959: +2024-11-21 11:04:36.959139: Epoch 73 +2024-11-21 11:04:36.959250: Current learning rate: 0.00992 +2024-11-21 11:04:54.793247: train_loss -0.7434 +2024-11-21 11:04:54.793473: val_loss -0.7256 +2024-11-21 11:04:54.793568: Pseudo dice [0.8245] +2024-11-21 11:04:54.793653: Epoch time: 17.84 s +2024-11-21 11:04:55.569276: +2024-11-21 11:04:55.569580: Epoch 74 +2024-11-21 11:04:55.569695: Current learning rate: 0.00992 +2024-11-21 11:05:15.529318: train_loss -0.7226 +2024-11-21 11:05:15.529532: val_loss -0.7141 +2024-11-21 11:05:15.529612: Pseudo dice [0.8044] +2024-11-21 11:05:15.529690: Epoch time: 19.96 s +2024-11-21 11:05:16.284627: +2024-11-21 11:05:16.284890: Epoch 75 +2024-11-21 11:05:16.285012: Current learning rate: 0.00992 +2024-11-21 11:05:35.240428: train_loss -0.7324 +2024-11-21 11:05:35.240692: val_loss -0.7046 +2024-11-21 11:05:35.240769: Pseudo dice [0.7974] +2024-11-21 11:05:35.240851: Epoch time: 18.96 s +2024-11-21 11:05:36.006669: +2024-11-21 11:05:36.006924: Epoch 76 +2024-11-21 11:05:36.007043: Current learning rate: 0.00991 +2024-11-21 11:05:55.242184: train_loss -0.7323 +2024-11-21 11:05:55.242399: val_loss -0.7223 +2024-11-21 11:05:55.242472: Pseudo dice [0.8183] +2024-11-21 11:05:55.242548: Epoch time: 19.24 s +2024-11-21 11:05:56.011917: +2024-11-21 11:05:56.012153: Epoch 77 +2024-11-21 11:05:56.012265: Current learning rate: 0.00991 +2024-11-21 11:06:15.581937: train_loss -0.7382 +2024-11-21 11:06:15.582145: val_loss -0.7231 +2024-11-21 11:06:15.582218: Pseudo dice [0.8064] +2024-11-21 11:06:15.582297: Epoch time: 19.57 s +2024-11-21 11:06:16.357241: +2024-11-21 11:06:16.357414: Epoch 78 +2024-11-21 11:06:16.357559: Current learning rate: 0.00991 +2024-11-21 11:06:35.657654: train_loss -0.7288 +2024-11-21 11:06:35.657891: val_loss -0.7234 +2024-11-21 11:06:35.657966: Pseudo dice [0.7991] +2024-11-21 11:06:35.658061: Epoch time: 19.3 s +2024-11-21 11:06:36.467710: +2024-11-21 11:06:36.467903: Epoch 79 +2024-11-21 11:06:36.468033: Current learning rate: 0.00991 +2024-11-21 11:06:55.664608: train_loss -0.7255 +2024-11-21 11:06:55.664818: val_loss -0.6962 +2024-11-21 11:06:55.664893: Pseudo dice [0.8115] +2024-11-21 11:06:55.671288: Epoch time: 19.2 s +2024-11-21 11:06:56.614398: +2024-11-21 11:06:56.614679: Epoch 80 +2024-11-21 11:06:56.614803: Current learning rate: 0.00991 +2024-11-21 11:07:15.955415: train_loss -0.7144 +2024-11-21 11:07:15.955647: val_loss -0.6941 +2024-11-21 11:07:15.955723: Pseudo dice [0.7736] +2024-11-21 11:07:15.955802: Epoch time: 19.34 s +2024-11-21 11:07:16.731045: +2024-11-21 11:07:16.731254: Epoch 81 +2024-11-21 11:07:16.731365: Current learning rate: 0.00991 +2024-11-21 11:07:35.351945: train_loss -0.721 +2024-11-21 11:07:35.354374: val_loss -0.7282 +2024-11-21 11:07:35.354468: Pseudo dice [0.8153] +2024-11-21 11:07:35.354551: Epoch time: 18.62 s +2024-11-21 11:07:36.140865: +2024-11-21 11:07:36.141103: Epoch 82 +2024-11-21 11:07:36.141217: Current learning rate: 0.00991 +2024-11-21 11:07:54.707962: train_loss -0.7468 +2024-11-21 11:07:54.708176: val_loss -0.7231 +2024-11-21 11:07:54.708250: Pseudo dice [0.803] +2024-11-21 11:07:54.708325: Epoch time: 18.57 s +2024-11-21 11:07:55.454727: +2024-11-21 11:07:55.454923: Epoch 83 +2024-11-21 11:07:55.455043: Current learning rate: 0.00991 +2024-11-21 11:08:14.384340: train_loss -0.732 +2024-11-21 11:08:14.384545: val_loss -0.7258 +2024-11-21 11:08:14.384621: Pseudo dice [0.8173] +2024-11-21 11:08:14.384701: Epoch time: 18.93 s +2024-11-21 11:08:15.233227: +2024-11-21 11:08:15.233442: Epoch 84 +2024-11-21 11:08:15.233556: Current learning rate: 0.00991 +2024-11-21 11:08:34.724848: train_loss -0.7446 +2024-11-21 11:08:34.725092: val_loss -0.7246 +2024-11-21 11:08:34.725170: Pseudo dice [0.7859] +2024-11-21 11:08:34.725249: Epoch time: 19.49 s +2024-11-21 11:08:35.541509: +2024-11-21 11:08:35.541699: Epoch 85 +2024-11-21 11:08:35.541811: Current learning rate: 0.0099 +2024-11-21 11:08:54.100963: train_loss -0.743 +2024-11-21 11:08:54.101207: val_loss -0.708 +2024-11-21 11:08:54.101283: Pseudo dice [0.7974] +2024-11-21 11:08:54.101364: Epoch time: 18.56 s +2024-11-21 11:08:54.915499: +2024-11-21 11:08:54.915687: Epoch 86 +2024-11-21 11:08:54.915806: Current learning rate: 0.0099 +2024-11-21 11:09:12.870109: train_loss -0.7345 +2024-11-21 11:09:12.870333: val_loss -0.7022 +2024-11-21 11:09:12.870408: Pseudo dice [0.7929] +2024-11-21 11:09:12.870485: Epoch time: 17.96 s +2024-11-21 11:09:13.802127: +2024-11-21 11:09:13.802363: Epoch 87 +2024-11-21 11:09:13.802480: Current learning rate: 0.0099 +2024-11-21 11:09:33.202515: train_loss -0.7207 +2024-11-21 11:09:33.202721: val_loss -0.7101 +2024-11-21 11:09:33.202800: Pseudo dice [0.8031] +2024-11-21 11:09:33.202878: Epoch time: 19.4 s +2024-11-21 11:09:33.954300: +2024-11-21 11:09:33.954564: Epoch 88 +2024-11-21 11:09:33.954679: Current learning rate: 0.0099 +2024-11-21 11:09:52.461366: train_loss -0.7294 +2024-11-21 11:09:52.461617: val_loss -0.7237 +2024-11-21 11:09:52.461702: Pseudo dice [0.8003] +2024-11-21 11:09:52.461793: Epoch time: 18.51 s +2024-11-21 11:09:53.220665: +2024-11-21 11:09:53.220872: Epoch 89 +2024-11-21 11:09:53.220994: Current learning rate: 0.0099 +2024-11-21 11:10:12.059268: train_loss -0.7325 +2024-11-21 11:10:12.061673: val_loss -0.7237 +2024-11-21 11:10:12.061772: Pseudo dice [0.8131] +2024-11-21 11:10:12.061851: Epoch time: 18.84 s +2024-11-21 11:10:12.846517: +2024-11-21 11:10:12.846721: Epoch 90 +2024-11-21 11:10:12.846835: Current learning rate: 0.0099 +2024-11-21 11:10:31.796842: train_loss -0.7405 +2024-11-21 11:10:31.797070: val_loss -0.7125 +2024-11-21 11:10:31.799397: Pseudo dice [0.8083] +2024-11-21 11:10:31.799491: Epoch time: 18.95 s +2024-11-21 11:10:32.581594: +2024-11-21 11:10:32.581799: Epoch 91 +2024-11-21 11:10:32.581913: Current learning rate: 0.0099 +2024-11-21 11:10:50.956618: train_loss -0.7276 +2024-11-21 11:10:50.956827: val_loss -0.7176 +2024-11-21 11:10:50.956905: Pseudo dice [0.8082] +2024-11-21 11:10:50.956999: Epoch time: 18.38 s +2024-11-21 11:10:51.708943: +2024-11-21 11:10:51.709136: Epoch 92 +2024-11-21 11:10:51.709255: Current learning rate: 0.0099 +2024-11-21 11:11:11.160963: train_loss -0.7421 +2024-11-21 11:11:11.161223: val_loss -0.7035 +2024-11-21 11:11:11.161299: Pseudo dice [0.7979] +2024-11-21 11:11:11.161383: Epoch time: 19.45 s +2024-11-21 11:11:11.959281: +2024-11-21 11:11:11.959584: Epoch 93 +2024-11-21 11:11:11.959699: Current learning rate: 0.0099 +2024-11-21 11:11:31.398394: train_loss -0.7406 +2024-11-21 11:11:31.398610: val_loss -0.6924 +2024-11-21 11:11:31.398692: Pseudo dice [0.8042] +2024-11-21 11:11:31.398772: Epoch time: 19.44 s +2024-11-21 11:11:32.154004: +2024-11-21 11:11:32.154191: Epoch 94 +2024-11-21 11:11:32.154303: Current learning rate: 0.00989 +2024-11-21 11:11:50.615008: train_loss -0.7427 +2024-11-21 11:11:50.615227: val_loss -0.713 +2024-11-21 11:11:50.615307: Pseudo dice [0.7983] +2024-11-21 11:11:50.615384: Epoch time: 18.46 s +2024-11-21 11:11:51.369363: +2024-11-21 11:11:51.369660: Epoch 95 +2024-11-21 11:11:51.369772: Current learning rate: 0.00989 +2024-11-21 11:12:09.770763: train_loss -0.7492 +2024-11-21 11:12:09.770985: val_loss -0.727 +2024-11-21 11:12:09.771076: Pseudo dice [0.8188] +2024-11-21 11:12:09.771152: Epoch time: 18.4 s +2024-11-21 11:12:10.523082: +2024-11-21 11:12:10.523291: Epoch 96 +2024-11-21 11:12:10.523409: Current learning rate: 0.00989 +2024-11-21 11:12:29.370727: train_loss -0.7524 +2024-11-21 11:12:29.370949: val_loss -0.7126 +2024-11-21 11:12:29.371032: Pseudo dice [0.8145] +2024-11-21 11:12:29.371113: Epoch time: 18.85 s +2024-11-21 11:12:30.129516: +2024-11-21 11:12:30.129712: Epoch 97 +2024-11-21 11:12:30.129831: Current learning rate: 0.00989 +2024-11-21 11:12:49.308787: train_loss -0.7382 +2024-11-21 11:12:49.309072: val_loss -0.7247 +2024-11-21 11:12:49.309152: Pseudo dice [0.8199] +2024-11-21 11:12:49.309236: Epoch time: 19.18 s +2024-11-21 11:12:50.072871: +2024-11-21 11:12:50.073128: Epoch 98 +2024-11-21 11:12:50.073244: Current learning rate: 0.00989 +2024-11-21 11:13:08.455781: train_loss -0.7311 +2024-11-21 11:13:08.456005: val_loss -0.721 +2024-11-21 11:13:08.456080: Pseudo dice [0.8097] +2024-11-21 11:13:08.456161: Epoch time: 18.38 s +2024-11-21 11:13:09.221066: +2024-11-21 11:13:09.221313: Epoch 99 +2024-11-21 11:13:09.221428: Current learning rate: 0.00989 +2024-11-21 11:13:27.928618: train_loss -0.7409 +2024-11-21 11:13:27.928859: val_loss -0.6918 +2024-11-21 11:13:27.929027: Pseudo dice [0.769] +2024-11-21 11:13:27.929114: Epoch time: 18.71 s +2024-11-21 11:13:28.927550: +2024-11-21 11:13:28.927854: Epoch 100 +2024-11-21 11:13:28.927971: Current learning rate: 0.00989 +2024-11-21 11:13:46.921938: train_loss -0.7486 +2024-11-21 11:13:46.922156: val_loss -0.7173 +2024-11-21 11:13:46.922236: Pseudo dice [0.8028] +2024-11-21 11:13:46.922314: Epoch time: 18.0 s +2024-11-21 11:13:47.681860: +2024-11-21 11:13:47.682060: Epoch 101 +2024-11-21 11:13:47.682172: Current learning rate: 0.00989 +2024-11-21 11:14:06.444579: train_loss -0.7441 +2024-11-21 11:14:06.444856: val_loss -0.7084 +2024-11-21 11:14:06.444932: Pseudo dice [0.8053] +2024-11-21 11:14:06.445014: Epoch time: 18.76 s +2024-11-21 11:14:07.232419: +2024-11-21 11:14:07.232610: Epoch 102 +2024-11-21 11:14:07.232721: Current learning rate: 0.00989 +2024-11-21 11:14:26.494542: train_loss -0.7379 +2024-11-21 11:14:26.494758: val_loss -0.7175 +2024-11-21 11:14:26.494834: Pseudo dice [0.8152] +2024-11-21 11:14:26.494912: Epoch time: 19.26 s +2024-11-21 11:14:27.260377: +2024-11-21 11:14:27.260587: Epoch 103 +2024-11-21 11:14:27.260702: Current learning rate: 0.00988 +2024-11-21 11:14:45.066814: train_loss -0.7393 +2024-11-21 11:14:45.067085: val_loss -0.7083 +2024-11-21 11:14:45.067168: Pseudo dice [0.7924] +2024-11-21 11:14:45.067249: Epoch time: 17.81 s +2024-11-21 11:14:45.836713: +2024-11-21 11:14:45.836913: Epoch 104 +2024-11-21 11:14:45.837033: Current learning rate: 0.00988 +2024-11-21 11:15:05.328068: train_loss -0.729 +2024-11-21 11:15:05.328272: val_loss -0.718 +2024-11-21 11:15:05.328346: Pseudo dice [0.8151] +2024-11-21 11:15:05.328423: Epoch time: 19.49 s +2024-11-21 11:15:06.089302: +2024-11-21 11:15:06.089482: Epoch 105 +2024-11-21 11:15:06.089595: Current learning rate: 0.00988 +2024-11-21 11:15:25.486686: train_loss -0.74 +2024-11-21 11:15:25.486909: val_loss -0.711 +2024-11-21 11:15:25.486985: Pseudo dice [0.8241] +2024-11-21 11:15:25.487071: Epoch time: 19.4 s +2024-11-21 11:15:26.247207: +2024-11-21 11:15:26.247393: Epoch 106 +2024-11-21 11:15:26.247506: Current learning rate: 0.00988 +2024-11-21 11:15:44.010760: train_loss -0.7494 +2024-11-21 11:15:44.011009: val_loss -0.7434 +2024-11-21 11:15:44.011109: Pseudo dice [0.8292] +2024-11-21 11:15:44.011195: Epoch time: 17.76 s +2024-11-21 11:15:44.011261: Yayy! New best EMA pseudo Dice: 0.8089 +2024-11-21 11:15:45.026912: +2024-11-21 11:15:45.027101: Epoch 107 +2024-11-21 11:15:45.027216: Current learning rate: 0.00988 +2024-11-21 11:16:03.452564: train_loss -0.7336 +2024-11-21 11:16:03.452794: val_loss -0.7116 +2024-11-21 11:16:03.452874: Pseudo dice [0.7916] +2024-11-21 11:16:03.452951: Epoch time: 18.43 s +2024-11-21 11:16:04.216703: +2024-11-21 11:16:04.216891: Epoch 108 +2024-11-21 11:16:04.217007: Current learning rate: 0.00988 +2024-11-21 11:16:22.781315: train_loss -0.7524 +2024-11-21 11:16:22.781535: val_loss -0.6965 +2024-11-21 11:16:22.781610: Pseudo dice [0.7884] +2024-11-21 11:16:22.781688: Epoch time: 18.57 s +2024-11-21 11:16:23.640842: +2024-11-21 11:16:23.641063: Epoch 109 +2024-11-21 11:16:23.641183: Current learning rate: 0.00988 +2024-11-21 11:16:41.438397: train_loss -0.737 +2024-11-21 11:16:41.438613: val_loss -0.7119 +2024-11-21 11:16:41.438696: Pseudo dice [0.8013] +2024-11-21 11:16:41.438780: Epoch time: 17.8 s +2024-11-21 11:16:42.204757: +2024-11-21 11:16:42.204994: Epoch 110 +2024-11-21 11:16:42.205148: Current learning rate: 0.00988 +2024-11-21 11:17:01.715562: train_loss -0.738 +2024-11-21 11:17:01.715780: val_loss -0.7136 +2024-11-21 11:17:01.715856: Pseudo dice [0.8016] +2024-11-21 11:17:01.715933: Epoch time: 19.51 s +2024-11-21 11:17:02.490555: +2024-11-21 11:17:02.490776: Epoch 111 +2024-11-21 11:17:02.490891: Current learning rate: 0.00988 +2024-11-21 11:17:20.796732: train_loss -0.7247 +2024-11-21 11:17:20.796955: val_loss -0.7159 +2024-11-21 11:17:20.797037: Pseudo dice [0.8185] +2024-11-21 11:17:20.797175: Epoch time: 18.31 s +2024-11-21 11:17:21.557033: +2024-11-21 11:17:21.557223: Epoch 112 +2024-11-21 11:17:21.557332: Current learning rate: 0.00987 +2024-11-21 11:17:40.530372: train_loss -0.7401 +2024-11-21 11:17:40.530596: val_loss -0.7131 +2024-11-21 11:17:40.530674: Pseudo dice [0.8114] +2024-11-21 11:17:40.530749: Epoch time: 18.97 s +2024-11-21 11:17:41.313054: +2024-11-21 11:17:41.313234: Epoch 113 +2024-11-21 11:17:41.313346: Current learning rate: 0.00987 +2024-11-21 11:17:59.808747: train_loss -0.7377 +2024-11-21 11:17:59.808987: val_loss -0.7445 +2024-11-21 11:17:59.809075: Pseudo dice [0.8239] +2024-11-21 11:17:59.809849: Epoch time: 18.5 s +2024-11-21 11:18:00.590976: +2024-11-21 11:18:00.591320: Epoch 114 +2024-11-21 11:18:00.591434: Current learning rate: 0.00987 +2024-11-21 11:18:19.612709: train_loss -0.747 +2024-11-21 11:18:19.612922: val_loss -0.7162 +2024-11-21 11:18:19.613006: Pseudo dice [0.8148] +2024-11-21 11:18:19.613083: Epoch time: 19.02 s +2024-11-21 11:18:19.613144: Yayy! New best EMA pseudo Dice: 0.8089 +2024-11-21 11:18:20.717932: +2024-11-21 11:18:20.718136: Epoch 115 +2024-11-21 11:18:20.718253: Current learning rate: 0.00987 +2024-11-21 11:18:39.924049: train_loss -0.7361 +2024-11-21 11:18:39.924262: val_loss -0.7038 +2024-11-21 11:18:39.924335: Pseudo dice [0.8074] +2024-11-21 11:18:39.924410: Epoch time: 19.21 s +2024-11-21 11:18:40.694266: +2024-11-21 11:18:40.694452: Epoch 116 +2024-11-21 11:18:40.694571: Current learning rate: 0.00987 +2024-11-21 11:18:58.102491: train_loss -0.7537 +2024-11-21 11:18:58.102697: val_loss -0.7171 +2024-11-21 11:18:58.102772: Pseudo dice [0.8114] +2024-11-21 11:18:58.102847: Epoch time: 17.41 s +2024-11-21 11:18:58.102906: Yayy! New best EMA pseudo Dice: 0.809 +2024-11-21 11:18:59.101217: +2024-11-21 11:18:59.101452: Epoch 117 +2024-11-21 11:18:59.101567: Current learning rate: 0.00987 +2024-11-21 11:19:17.844671: train_loss -0.7486 +2024-11-21 11:19:17.844923: val_loss -0.753 +2024-11-21 11:19:17.845010: Pseudo dice [0.814] +2024-11-21 11:19:17.845841: Epoch time: 18.74 s +2024-11-21 11:19:17.845959: Yayy! New best EMA pseudo Dice: 0.8095 +2024-11-21 11:19:18.863553: +2024-11-21 11:19:18.863734: Epoch 118 +2024-11-21 11:19:18.863852: Current learning rate: 0.00987 +2024-11-21 11:19:36.781290: train_loss -0.7483 +2024-11-21 11:19:36.781490: val_loss -0.7463 +2024-11-21 11:19:36.781564: Pseudo dice [0.8032] +2024-11-21 11:19:36.781640: Epoch time: 17.92 s +2024-11-21 11:19:37.693383: +2024-11-21 11:19:37.693588: Epoch 119 +2024-11-21 11:19:37.693703: Current learning rate: 0.00987 +2024-11-21 11:19:55.241702: train_loss -0.743 +2024-11-21 11:19:55.241917: val_loss -0.707 +2024-11-21 11:19:55.242042: Pseudo dice [0.8222] +2024-11-21 11:19:55.242121: Epoch time: 17.55 s +2024-11-21 11:19:55.242182: Yayy! New best EMA pseudo Dice: 0.8102 +2024-11-21 11:19:56.524507: +2024-11-21 11:19:56.524713: Epoch 120 +2024-11-21 11:19:56.524832: Current learning rate: 0.00986 +2024-11-21 11:20:14.137108: train_loss -0.7425 +2024-11-21 11:20:14.137349: val_loss -0.695 +2024-11-21 11:20:14.137429: Pseudo dice [0.8106] +2024-11-21 11:20:14.137516: Epoch time: 17.61 s +2024-11-21 11:20:14.137580: Yayy! New best EMA pseudo Dice: 0.8102 +2024-11-21 11:20:15.104508: +2024-11-21 11:20:15.104727: Epoch 121 +2024-11-21 11:20:15.104851: Current learning rate: 0.00986 +2024-11-21 11:20:34.167843: train_loss -0.7271 +2024-11-21 11:20:34.168070: val_loss -0.6803 +2024-11-21 11:20:34.168145: Pseudo dice [0.8078] +2024-11-21 11:20:34.168224: Epoch time: 19.06 s +2024-11-21 11:20:34.944186: +2024-11-21 11:20:34.944441: Epoch 122 +2024-11-21 11:20:34.944563: Current learning rate: 0.00986 +2024-11-21 11:20:54.083486: train_loss -0.7309 +2024-11-21 11:20:54.083718: val_loss -0.7055 +2024-11-21 11:20:54.083797: Pseudo dice [0.8193] +2024-11-21 11:20:54.083876: Epoch time: 19.14 s +2024-11-21 11:20:54.083940: Yayy! New best EMA pseudo Dice: 0.8109 +2024-11-21 11:20:55.108126: +2024-11-21 11:20:55.108375: Epoch 123 +2024-11-21 11:20:55.108496: Current learning rate: 0.00986 +2024-11-21 11:21:14.465492: train_loss -0.7366 +2024-11-21 11:21:14.465692: val_loss -0.7125 +2024-11-21 11:21:14.465765: Pseudo dice [0.8021] +2024-11-21 11:21:14.465842: Epoch time: 19.36 s +2024-11-21 11:21:15.260315: +2024-11-21 11:21:15.260523: Epoch 124 +2024-11-21 11:21:15.260638: Current learning rate: 0.00986 +2024-11-21 11:21:33.806286: train_loss -0.7451 +2024-11-21 11:21:33.806555: val_loss -0.71 +2024-11-21 11:21:33.806671: Pseudo dice [0.7818] +2024-11-21 11:21:33.806796: Epoch time: 18.55 s +2024-11-21 11:21:34.586497: +2024-11-21 11:21:34.586700: Epoch 125 +2024-11-21 11:21:34.586819: Current learning rate: 0.00986 +2024-11-21 11:21:52.975845: train_loss -0.7285 +2024-11-21 11:21:52.976056: val_loss -0.6982 +2024-11-21 11:21:52.976130: Pseudo dice [0.8054] +2024-11-21 11:21:52.976207: Epoch time: 18.39 s +2024-11-21 11:21:53.748725: +2024-11-21 11:21:53.748901: Epoch 126 +2024-11-21 11:21:53.749022: Current learning rate: 0.00986 +2024-11-21 11:22:12.787977: train_loss -0.744 +2024-11-21 11:22:12.793400: val_loss -0.717 +2024-11-21 11:22:12.793489: Pseudo dice [0.825] +2024-11-21 11:22:12.793570: Epoch time: 19.04 s +2024-11-21 11:22:13.744217: +2024-11-21 11:22:13.744394: Epoch 127 +2024-11-21 11:22:13.744507: Current learning rate: 0.00986 +2024-11-21 11:22:32.189010: train_loss -0.7321 +2024-11-21 11:22:32.189233: val_loss -0.726 +2024-11-21 11:22:32.189337: Pseudo dice [0.7947] +2024-11-21 11:22:32.189416: Epoch time: 18.45 s +2024-11-21 11:22:32.960463: +2024-11-21 11:22:32.960636: Epoch 128 +2024-11-21 11:22:32.960747: Current learning rate: 0.00986 +2024-11-21 11:22:52.150559: train_loss -0.7328 +2024-11-21 11:22:52.150823: val_loss -0.717 +2024-11-21 11:22:52.150898: Pseudo dice [0.8023] +2024-11-21 11:22:52.150983: Epoch time: 19.19 s +2024-11-21 11:22:52.919570: +2024-11-21 11:22:52.919761: Epoch 129 +2024-11-21 11:22:52.919873: Current learning rate: 0.00985 +2024-11-21 11:23:11.424537: train_loss -0.7389 +2024-11-21 11:23:11.424750: val_loss -0.7421 +2024-11-21 11:23:11.424820: Pseudo dice [0.8203] +2024-11-21 11:23:11.424894: Epoch time: 18.51 s +2024-11-21 11:23:12.199618: +2024-11-21 11:23:12.199862: Epoch 130 +2024-11-21 11:23:12.199987: Current learning rate: 0.00985 +2024-11-21 11:23:30.504781: train_loss -0.7382 +2024-11-21 11:23:30.504982: val_loss -0.7335 +2024-11-21 11:23:30.505066: Pseudo dice [0.8224] +2024-11-21 11:23:30.505143: Epoch time: 18.31 s +2024-11-21 11:23:31.267485: +2024-11-21 11:23:31.267685: Epoch 131 +2024-11-21 11:23:31.267795: Current learning rate: 0.00985 +2024-11-21 11:23:50.756455: train_loss -0.7433 +2024-11-21 11:23:50.756690: val_loss -0.7392 +2024-11-21 11:23:50.756767: Pseudo dice [0.8101] +2024-11-21 11:23:50.758976: Epoch time: 19.49 s +2024-11-21 11:23:51.907080: +2024-11-21 11:23:51.907288: Epoch 132 +2024-11-21 11:23:51.907401: Current learning rate: 0.00985 +2024-11-21 11:24:10.216152: train_loss -0.7378 +2024-11-21 11:24:10.216369: val_loss -0.7515 +2024-11-21 11:24:10.216448: Pseudo dice [0.8101] +2024-11-21 11:24:10.216526: Epoch time: 18.31 s +2024-11-21 11:24:11.112156: +2024-11-21 11:24:11.112386: Epoch 133 +2024-11-21 11:24:11.112506: Current learning rate: 0.00985 +2024-11-21 11:24:29.623155: train_loss -0.749 +2024-11-21 11:24:29.623357: val_loss -0.6992 +2024-11-21 11:24:29.623430: Pseudo dice [0.8243] +2024-11-21 11:24:29.623505: Epoch time: 18.51 s +2024-11-21 11:24:29.623567: Yayy! New best EMA pseudo Dice: 0.8112 +2024-11-21 11:24:30.643394: +2024-11-21 11:24:30.643576: Epoch 134 +2024-11-21 11:24:30.643687: Current learning rate: 0.00985 +2024-11-21 11:24:50.014119: train_loss -0.7499 +2024-11-21 11:24:50.014391: val_loss -0.731 +2024-11-21 11:24:50.014484: Pseudo dice [0.8028] +2024-11-21 11:24:50.014576: Epoch time: 19.37 s +2024-11-21 11:24:50.843755: +2024-11-21 11:24:50.843960: Epoch 135 +2024-11-21 11:24:50.844075: Current learning rate: 0.00985 +2024-11-21 11:25:10.309127: train_loss -0.7443 +2024-11-21 11:25:10.309342: val_loss -0.741 +2024-11-21 11:25:10.309415: Pseudo dice [0.8047] +2024-11-21 11:25:10.309490: Epoch time: 19.47 s +2024-11-21 11:25:11.150406: +2024-11-21 11:25:11.150581: Epoch 136 +2024-11-21 11:25:11.150684: Current learning rate: 0.00985 +2024-11-21 11:25:28.770143: train_loss -0.7387 +2024-11-21 11:25:28.770364: val_loss -0.7044 +2024-11-21 11:25:28.770440: Pseudo dice [0.7874] +2024-11-21 11:25:28.770516: Epoch time: 17.62 s +2024-11-21 11:25:29.557890: +2024-11-21 11:25:29.558100: Epoch 137 +2024-11-21 11:25:29.558212: Current learning rate: 0.00985 +2024-11-21 11:25:47.529933: train_loss -0.7355 +2024-11-21 11:25:47.530193: val_loss -0.7137 +2024-11-21 11:25:47.530281: Pseudo dice [0.8177] +2024-11-21 11:25:47.530364: Epoch time: 17.97 s +2024-11-21 11:25:48.316547: +2024-11-21 11:25:48.316732: Epoch 138 +2024-11-21 11:25:48.316839: Current learning rate: 0.00984 +2024-11-21 11:26:07.587872: train_loss -0.7369 +2024-11-21 11:26:07.588116: val_loss -0.7236 +2024-11-21 11:26:07.588192: Pseudo dice [0.7884] +2024-11-21 11:26:07.588275: Epoch time: 19.27 s +2024-11-21 11:26:08.406611: +2024-11-21 11:26:08.406797: Epoch 139 +2024-11-21 11:26:08.406910: Current learning rate: 0.00984 +2024-11-21 11:26:27.978915: train_loss -0.7454 +2024-11-21 11:26:27.979124: val_loss -0.7291 +2024-11-21 11:26:27.979196: Pseudo dice [0.8138] +2024-11-21 11:26:27.979271: Epoch time: 19.57 s +2024-11-21 11:26:28.753205: +2024-11-21 11:26:28.753391: Epoch 140 +2024-11-21 11:26:28.753502: Current learning rate: 0.00984 +2024-11-21 11:26:47.685024: train_loss -0.7418 +2024-11-21 11:26:47.685239: val_loss -0.711 +2024-11-21 11:26:47.685313: Pseudo dice [0.8199] +2024-11-21 11:26:47.685389: Epoch time: 18.93 s +2024-11-21 11:26:48.508409: +2024-11-21 11:26:48.508593: Epoch 141 +2024-11-21 11:26:48.508698: Current learning rate: 0.00984 +2024-11-21 11:27:07.500401: train_loss -0.747 +2024-11-21 11:27:07.500614: val_loss -0.7101 +2024-11-21 11:27:07.505847: Pseudo dice [0.8086] +2024-11-21 11:27:07.506007: Epoch time: 18.99 s +2024-11-21 11:27:08.335169: +2024-11-21 11:27:08.335366: Epoch 142 +2024-11-21 11:27:08.335513: Current learning rate: 0.00984 +2024-11-21 11:27:27.130145: train_loss -0.7457 +2024-11-21 11:27:27.130369: val_loss -0.7031 +2024-11-21 11:27:27.135842: Pseudo dice [0.8084] +2024-11-21 11:27:27.136006: Epoch time: 18.8 s +2024-11-21 11:27:28.379088: +2024-11-21 11:27:28.379294: Epoch 143 +2024-11-21 11:27:28.379405: Current learning rate: 0.00984 +2024-11-21 11:27:46.130492: train_loss -0.7405 +2024-11-21 11:27:46.130717: val_loss -0.6907 +2024-11-21 11:27:46.130792: Pseudo dice [0.8028] +2024-11-21 11:27:46.130870: Epoch time: 17.75 s +2024-11-21 11:27:46.979506: +2024-11-21 11:27:46.979719: Epoch 144 +2024-11-21 11:27:46.979835: Current learning rate: 0.00984 +2024-11-21 11:28:05.651399: train_loss -0.7318 +2024-11-21 11:28:05.651619: val_loss -0.715 +2024-11-21 11:28:05.651698: Pseudo dice [0.8228] +2024-11-21 11:28:05.651781: Epoch time: 18.67 s +2024-11-21 11:28:06.435009: +2024-11-21 11:28:06.435215: Epoch 145 +2024-11-21 11:28:06.435328: Current learning rate: 0.00984 +2024-11-21 11:28:24.566423: train_loss -0.7405 +2024-11-21 11:28:24.566662: val_loss -0.728 +2024-11-21 11:28:24.566738: Pseudo dice [0.7895] +2024-11-21 11:28:24.566822: Epoch time: 18.13 s +2024-11-21 11:28:25.355578: +2024-11-21 11:28:25.355778: Epoch 146 +2024-11-21 11:28:25.355888: Current learning rate: 0.00984 +2024-11-21 11:28:43.675607: train_loss -0.7413 +2024-11-21 11:28:43.675837: val_loss -0.7171 +2024-11-21 11:28:43.675920: Pseudo dice [0.8014] +2024-11-21 11:28:43.676004: Epoch time: 18.32 s +2024-11-21 11:28:44.457071: +2024-11-21 11:28:44.457258: Epoch 147 +2024-11-21 11:28:44.457368: Current learning rate: 0.00983 +2024-11-21 11:29:02.303359: train_loss -0.7325 +2024-11-21 11:29:02.303565: val_loss -0.7255 +2024-11-21 11:29:02.303641: Pseudo dice [0.7941] +2024-11-21 11:29:02.303724: Epoch time: 17.85 s +2024-11-21 11:29:03.089319: +2024-11-21 11:29:03.089503: Epoch 148 +2024-11-21 11:29:03.089618: Current learning rate: 0.00983 +2024-11-21 11:29:22.329345: train_loss -0.7229 +2024-11-21 11:29:22.329553: val_loss -0.7107 +2024-11-21 11:29:22.329634: Pseudo dice [0.8227] +2024-11-21 11:29:22.329715: Epoch time: 19.24 s +2024-11-21 11:29:23.114799: +2024-11-21 11:29:23.115106: Epoch 149 +2024-11-21 11:29:23.115217: Current learning rate: 0.00983 +2024-11-21 11:29:40.802964: train_loss -0.7447 +2024-11-21 11:29:40.806506: val_loss -0.7297 +2024-11-21 11:29:40.806625: Pseudo dice [0.8287] +2024-11-21 11:29:40.806709: Epoch time: 17.69 s +2024-11-21 11:29:41.848715: +2024-11-21 11:29:41.848912: Epoch 150 +2024-11-21 11:29:41.849027: Current learning rate: 0.00983 +2024-11-21 11:30:00.288217: train_loss -0.7426 +2024-11-21 11:30:00.288424: val_loss -0.7083 +2024-11-21 11:30:00.288496: Pseudo dice [0.7913] +2024-11-21 11:30:00.288572: Epoch time: 18.44 s +2024-11-21 11:30:01.084182: +2024-11-21 11:30:01.084372: Epoch 151 +2024-11-21 11:30:01.084483: Current learning rate: 0.00983 +2024-11-21 11:30:19.306564: train_loss -0.7393 +2024-11-21 11:30:19.306771: val_loss -0.7306 +2024-11-21 11:30:19.309015: Pseudo dice [0.8182] +2024-11-21 11:30:19.309098: Epoch time: 18.22 s +2024-11-21 11:30:20.109532: +2024-11-21 11:30:20.109712: Epoch 152 +2024-11-21 11:30:20.109825: Current learning rate: 0.00983 +2024-11-21 11:30:39.392726: train_loss -0.7469 +2024-11-21 11:30:39.393022: val_loss -0.704 +2024-11-21 11:30:39.393106: Pseudo dice [0.8161] +2024-11-21 11:30:39.393194: Epoch time: 19.28 s +2024-11-21 11:30:40.247077: +2024-11-21 11:30:40.247276: Epoch 153 +2024-11-21 11:30:40.247393: Current learning rate: 0.00983 +2024-11-21 11:30:58.831442: train_loss -0.7345 +2024-11-21 11:30:58.833821: val_loss -0.7311 +2024-11-21 11:30:58.833929: Pseudo dice [0.8225] +2024-11-21 11:30:58.834012: Epoch time: 18.59 s +2024-11-21 11:30:59.637631: +2024-11-21 11:30:59.637829: Epoch 154 +2024-11-21 11:30:59.637951: Current learning rate: 0.00983 +2024-11-21 11:31:18.231208: train_loss -0.7443 +2024-11-21 11:31:18.231414: val_loss -0.7454 +2024-11-21 11:31:18.231487: Pseudo dice [0.8338] +2024-11-21 11:31:18.231561: Epoch time: 18.59 s +2024-11-21 11:31:18.231622: Yayy! New best EMA pseudo Dice: 0.813 +2024-11-21 11:31:19.630002: +2024-11-21 11:31:19.630198: Epoch 155 +2024-11-21 11:31:19.630310: Current learning rate: 0.00983 +2024-11-21 11:31:38.420149: train_loss -0.748 +2024-11-21 11:31:38.420393: val_loss -0.7142 +2024-11-21 11:31:38.420473: Pseudo dice [0.8158] +2024-11-21 11:31:38.420556: Epoch time: 18.79 s +2024-11-21 11:31:38.420622: Yayy! New best EMA pseudo Dice: 0.8133 +2024-11-21 11:31:39.418674: +2024-11-21 11:31:39.418962: Epoch 156 +2024-11-21 11:31:39.419098: Current learning rate: 0.00982 +2024-11-21 11:31:58.001058: train_loss -0.7432 +2024-11-21 11:31:58.001357: val_loss -0.7031 +2024-11-21 11:31:58.001438: Pseudo dice [0.8108] +2024-11-21 11:31:58.001522: Epoch time: 18.58 s +2024-11-21 11:31:58.794588: +2024-11-21 11:31:58.794803: Epoch 157 +2024-11-21 11:31:58.794920: Current learning rate: 0.00982 +2024-11-21 11:32:17.939525: train_loss -0.7322 +2024-11-21 11:32:17.939749: val_loss -0.7219 +2024-11-21 11:32:17.939824: Pseudo dice [0.7996] +2024-11-21 11:32:17.939900: Epoch time: 19.15 s +2024-11-21 11:32:18.781799: +2024-11-21 11:32:18.781997: Epoch 158 +2024-11-21 11:32:18.782109: Current learning rate: 0.00982 +2024-11-21 11:32:37.759010: train_loss -0.7417 +2024-11-21 11:32:37.759225: val_loss -0.7417 +2024-11-21 11:32:37.759319: Pseudo dice [0.8077] +2024-11-21 11:32:37.759465: Epoch time: 18.98 s +2024-11-21 11:32:38.548362: +2024-11-21 11:32:38.548565: Epoch 159 +2024-11-21 11:32:38.548680: Current learning rate: 0.00982 +2024-11-21 11:32:57.596137: train_loss -0.7451 +2024-11-21 11:32:57.600421: val_loss -0.7529 +2024-11-21 11:32:57.600597: Pseudo dice [0.8261] +2024-11-21 11:32:57.600688: Epoch time: 19.05 s +2024-11-21 11:32:58.413797: +2024-11-21 11:32:58.413984: Epoch 160 +2024-11-21 11:32:58.414104: Current learning rate: 0.00982 +2024-11-21 11:33:16.408050: train_loss -0.7433 +2024-11-21 11:33:16.408245: val_loss -0.7373 +2024-11-21 11:33:16.408316: Pseudo dice [0.8209] +2024-11-21 11:33:16.408389: Epoch time: 18.0 s +2024-11-21 11:33:16.408452: Yayy! New best EMA pseudo Dice: 0.8136 +2024-11-21 11:33:17.434707: +2024-11-21 11:33:17.434898: Epoch 161 +2024-11-21 11:33:17.435015: Current learning rate: 0.00982 +2024-11-21 11:33:36.123492: train_loss -0.7455 +2024-11-21 11:33:36.123776: val_loss -0.7348 +2024-11-21 11:33:36.123852: Pseudo dice [0.8174] +2024-11-21 11:33:36.123928: Epoch time: 18.69 s +2024-11-21 11:33:36.123995: Yayy! New best EMA pseudo Dice: 0.814 +2024-11-21 11:33:37.212168: +2024-11-21 11:33:37.212381: Epoch 162 +2024-11-21 11:33:37.212493: Current learning rate: 0.00982 +2024-11-21 11:33:56.085011: train_loss -0.742 +2024-11-21 11:33:56.085253: val_loss -0.7322 +2024-11-21 11:33:56.085332: Pseudo dice [0.8061] +2024-11-21 11:33:56.085422: Epoch time: 18.87 s +2024-11-21 11:33:56.972846: +2024-11-21 11:33:56.973067: Epoch 163 +2024-11-21 11:33:56.973183: Current learning rate: 0.00982 +2024-11-21 11:34:16.466152: train_loss -0.7434 +2024-11-21 11:34:16.466361: val_loss -0.7097 +2024-11-21 11:34:16.466433: Pseudo dice [0.802] +2024-11-21 11:34:16.466507: Epoch time: 19.49 s +2024-11-21 11:34:17.275423: +2024-11-21 11:34:17.275595: Epoch 164 +2024-11-21 11:34:17.275709: Current learning rate: 0.00982 +2024-11-21 11:34:35.742535: train_loss -0.7588 +2024-11-21 11:34:35.742780: val_loss -0.7108 +2024-11-21 11:34:35.742861: Pseudo dice [0.8085] +2024-11-21 11:34:35.742936: Epoch time: 18.47 s +2024-11-21 11:34:36.519320: +2024-11-21 11:34:36.519516: Epoch 165 +2024-11-21 11:34:36.519625: Current learning rate: 0.00981 +2024-11-21 11:34:54.758884: train_loss -0.7541 +2024-11-21 11:34:54.759104: val_loss -0.716 +2024-11-21 11:34:54.759186: Pseudo dice [0.8112] +2024-11-21 11:34:54.759261: Epoch time: 18.24 s +2024-11-21 11:34:55.526055: +2024-11-21 11:34:55.526274: Epoch 166 +2024-11-21 11:34:55.526387: Current learning rate: 0.00981 +2024-11-21 11:35:14.748595: train_loss -0.7531 +2024-11-21 11:35:14.748807: val_loss -0.7607 +2024-11-21 11:35:14.759789: Pseudo dice [0.8195] +2024-11-21 11:35:14.759931: Epoch time: 19.22 s +2024-11-21 11:35:15.561217: +2024-11-21 11:35:15.561447: Epoch 167 +2024-11-21 11:35:15.561559: Current learning rate: 0.00981 +2024-11-21 11:35:35.360703: train_loss -0.7372 +2024-11-21 11:35:35.360916: val_loss -0.727 +2024-11-21 11:35:35.366237: Pseudo dice [0.7986] +2024-11-21 11:35:35.366324: Epoch time: 19.8 s +2024-11-21 11:35:36.241990: +2024-11-21 11:35:36.242239: Epoch 168 +2024-11-21 11:35:36.242358: Current learning rate: 0.00981 +2024-11-21 11:35:54.850068: train_loss -0.7393 +2024-11-21 11:35:54.850302: val_loss -0.7025 +2024-11-21 11:35:54.850379: Pseudo dice [0.8092] +2024-11-21 11:35:54.850486: Epoch time: 18.61 s +2024-11-21 11:35:55.658572: +2024-11-21 11:35:55.658841: Epoch 169 +2024-11-21 11:35:55.658957: Current learning rate: 0.00981 +2024-11-21 11:36:14.562022: train_loss -0.7526 +2024-11-21 11:36:14.562245: val_loss -0.7244 +2024-11-21 11:36:14.562332: Pseudo dice [0.8151] +2024-11-21 11:36:14.562417: Epoch time: 18.9 s +2024-11-21 11:36:15.447069: +2024-11-21 11:36:15.447282: Epoch 170 +2024-11-21 11:36:15.447404: Current learning rate: 0.00981 +2024-11-21 11:36:33.541333: train_loss -0.7384 +2024-11-21 11:36:33.541569: val_loss -0.7295 +2024-11-21 11:36:33.541653: Pseudo dice [0.832] +2024-11-21 11:36:33.541731: Epoch time: 18.1 s +2024-11-21 11:36:34.340562: +2024-11-21 11:36:34.340770: Epoch 171 +2024-11-21 11:36:34.340881: Current learning rate: 0.00981 +2024-11-21 11:36:53.519198: train_loss -0.7463 +2024-11-21 11:36:53.519799: val_loss -0.7013 +2024-11-21 11:36:53.519880: Pseudo dice [0.7997] +2024-11-21 11:36:53.519957: Epoch time: 19.18 s +2024-11-21 11:36:54.309340: +2024-11-21 11:36:54.309536: Epoch 172 +2024-11-21 11:36:54.309656: Current learning rate: 0.00981 +2024-11-21 11:37:11.873096: train_loss -0.7454 +2024-11-21 11:37:11.873300: val_loss -0.7118 +2024-11-21 11:37:11.873374: Pseudo dice [0.8013] +2024-11-21 11:37:11.873454: Epoch time: 17.56 s +2024-11-21 11:37:12.691145: +2024-11-21 11:37:12.691391: Epoch 173 +2024-11-21 11:37:12.691507: Current learning rate: 0.00981 +2024-11-21 11:37:31.507867: train_loss -0.75 +2024-11-21 11:37:31.508102: val_loss -0.7088 +2024-11-21 11:37:31.508176: Pseudo dice [0.7773] +2024-11-21 11:37:31.508259: Epoch time: 18.82 s +2024-11-21 11:37:32.284551: +2024-11-21 11:37:32.284720: Epoch 174 +2024-11-21 11:37:32.284858: Current learning rate: 0.0098 +2024-11-21 11:37:50.111329: train_loss -0.7569 +2024-11-21 11:37:50.111539: val_loss -0.741 +2024-11-21 11:37:50.111611: Pseudo dice [0.819] +2024-11-21 11:37:50.111687: Epoch time: 17.83 s +2024-11-21 11:37:50.891557: +2024-11-21 11:37:50.891754: Epoch 175 +2024-11-21 11:37:50.891868: Current learning rate: 0.0098 +2024-11-21 11:38:09.258981: train_loss -0.7529 +2024-11-21 11:38:09.259229: val_loss -0.7158 +2024-11-21 11:38:09.259308: Pseudo dice [0.8186] +2024-11-21 11:38:09.259386: Epoch time: 18.37 s +2024-11-21 11:38:10.033700: +2024-11-21 11:38:10.033892: Epoch 176 +2024-11-21 11:38:10.034015: Current learning rate: 0.0098 +2024-11-21 11:38:28.083159: train_loss -0.7488 +2024-11-21 11:38:28.083397: val_loss -0.7476 +2024-11-21 11:38:28.083474: Pseudo dice [0.814] +2024-11-21 11:38:28.083554: Epoch time: 18.05 s +2024-11-21 11:38:28.953154: +2024-11-21 11:38:28.953324: Epoch 177 +2024-11-21 11:38:28.953435: Current learning rate: 0.0098 +2024-11-21 11:38:48.630618: train_loss -0.731 +2024-11-21 11:38:48.631212: val_loss -0.6915 +2024-11-21 11:38:48.631291: Pseudo dice [0.7912] +2024-11-21 11:38:48.631393: Epoch time: 19.68 s +2024-11-21 11:38:49.414307: +2024-11-21 11:38:49.414504: Epoch 178 +2024-11-21 11:38:49.414614: Current learning rate: 0.0098 +2024-11-21 11:39:07.915271: train_loss -0.74 +2024-11-21 11:39:07.915468: val_loss -0.7323 +2024-11-21 11:39:07.915542: Pseudo dice [0.8223] +2024-11-21 11:39:07.915617: Epoch time: 18.5 s +2024-11-21 11:39:08.703878: +2024-11-21 11:39:08.704093: Epoch 179 +2024-11-21 11:39:08.704209: Current learning rate: 0.0098 +2024-11-21 11:39:27.131390: train_loss -0.7423 +2024-11-21 11:39:27.131684: val_loss -0.7317 +2024-11-21 11:39:27.131767: Pseudo dice [0.814] +2024-11-21 11:39:27.131849: Epoch time: 18.43 s +2024-11-21 11:39:27.926327: +2024-11-21 11:39:27.926532: Epoch 180 +2024-11-21 11:39:27.926654: Current learning rate: 0.0098 +2024-11-21 11:39:47.149728: train_loss -0.7467 +2024-11-21 11:39:47.149938: val_loss -0.6846 +2024-11-21 11:39:47.150021: Pseudo dice [0.7796] +2024-11-21 11:39:47.150096: Epoch time: 19.22 s +2024-11-21 11:39:47.935456: +2024-11-21 11:39:47.935681: Epoch 181 +2024-11-21 11:39:47.935791: Current learning rate: 0.0098 +2024-11-21 11:40:06.868920: train_loss -0.7444 +2024-11-21 11:40:06.869159: val_loss -0.7375 +2024-11-21 11:40:06.869234: Pseudo dice [0.8097] +2024-11-21 11:40:06.869313: Epoch time: 18.93 s +2024-11-21 11:40:07.783539: +2024-11-21 11:40:07.783787: Epoch 182 +2024-11-21 11:40:07.783904: Current learning rate: 0.0098 +2024-11-21 11:40:26.697163: train_loss -0.7433 +2024-11-21 11:40:26.697381: val_loss -0.7245 +2024-11-21 11:40:26.697456: Pseudo dice [0.8087] +2024-11-21 11:40:26.702694: Epoch time: 18.91 s +2024-11-21 11:40:27.609418: +2024-11-21 11:40:27.609620: Epoch 183 +2024-11-21 11:40:27.609742: Current learning rate: 0.00979 +2024-11-21 11:40:45.722357: train_loss -0.7464 +2024-11-21 11:40:45.722625: val_loss -0.7415 +2024-11-21 11:40:45.722710: Pseudo dice [0.8133] +2024-11-21 11:40:45.722792: Epoch time: 18.11 s +2024-11-21 11:40:46.503370: +2024-11-21 11:40:46.503603: Epoch 184 +2024-11-21 11:40:46.503721: Current learning rate: 0.00979 +2024-11-21 11:41:06.181498: train_loss -0.7537 +2024-11-21 11:41:06.183219: val_loss -0.7421 +2024-11-21 11:41:06.183316: Pseudo dice [0.8305] +2024-11-21 11:41:06.183393: Epoch time: 19.68 s +2024-11-21 11:41:06.984042: +2024-11-21 11:41:06.984246: Epoch 185 +2024-11-21 11:41:06.984359: Current learning rate: 0.00979 +2024-11-21 11:41:27.345417: train_loss -0.7566 +2024-11-21 11:41:27.345670: val_loss -0.7368 +2024-11-21 11:41:27.345750: Pseudo dice [0.822] +2024-11-21 11:41:27.345825: Epoch time: 20.36 s +2024-11-21 11:41:28.133226: +2024-11-21 11:41:28.133404: Epoch 186 +2024-11-21 11:41:28.133518: Current learning rate: 0.00979 +2024-11-21 11:41:47.032370: train_loss -0.7389 +2024-11-21 11:41:47.032616: val_loss -0.7274 +2024-11-21 11:41:47.032697: Pseudo dice [0.811] +2024-11-21 11:41:47.032777: Epoch time: 18.9 s +2024-11-21 11:41:47.809420: +2024-11-21 11:41:47.809624: Epoch 187 +2024-11-21 11:41:47.809738: Current learning rate: 0.00979 +2024-11-21 11:42:05.958441: train_loss -0.7403 +2024-11-21 11:42:05.958662: val_loss -0.7332 +2024-11-21 11:42:05.958741: Pseudo dice [0.8025] +2024-11-21 11:42:05.958819: Epoch time: 18.15 s +2024-11-21 11:42:06.743214: +2024-11-21 11:42:06.743407: Epoch 188 +2024-11-21 11:42:06.743519: Current learning rate: 0.00979 +2024-11-21 11:42:26.034178: train_loss -0.7382 +2024-11-21 11:42:26.034420: val_loss -0.7268 +2024-11-21 11:42:26.034493: Pseudo dice [0.8149] +2024-11-21 11:42:26.034568: Epoch time: 19.29 s +2024-11-21 11:42:27.180538: +2024-11-21 11:42:27.180805: Epoch 189 +2024-11-21 11:42:27.180920: Current learning rate: 0.00979 +2024-11-21 11:42:46.648052: train_loss -0.7564 +2024-11-21 11:42:46.648281: val_loss -0.7485 +2024-11-21 11:42:46.648362: Pseudo dice [0.8277] +2024-11-21 11:42:46.648443: Epoch time: 19.47 s +2024-11-21 11:42:47.429056: +2024-11-21 11:42:47.429346: Epoch 190 +2024-11-21 11:42:47.429515: Current learning rate: 0.00979 +2024-11-21 11:43:05.793038: train_loss -0.7487 +2024-11-21 11:43:05.793253: val_loss -0.7063 +2024-11-21 11:43:05.793328: Pseudo dice [0.8042] +2024-11-21 11:43:05.793407: Epoch time: 18.36 s +2024-11-21 11:43:06.712904: +2024-11-21 11:43:06.713116: Epoch 191 +2024-11-21 11:43:06.713235: Current learning rate: 0.00978 +2024-11-21 11:43:26.045797: train_loss -0.7542 +2024-11-21 11:43:26.046022: val_loss -0.7087 +2024-11-21 11:43:26.046096: Pseudo dice [0.7923] +2024-11-21 11:43:26.046172: Epoch time: 19.33 s +2024-11-21 11:43:26.897764: +2024-11-21 11:43:26.897980: Epoch 192 +2024-11-21 11:43:26.918554: Current learning rate: 0.00978 +2024-11-21 11:43:47.431103: train_loss -0.7439 +2024-11-21 11:43:47.431821: val_loss -0.7244 +2024-11-21 11:43:47.431926: Pseudo dice [0.8082] +2024-11-21 11:43:47.432018: Epoch time: 20.53 s +2024-11-21 11:43:48.228525: +2024-11-21 11:43:48.228708: Epoch 193 +2024-11-21 11:43:48.228819: Current learning rate: 0.00978 +2024-11-21 11:44:06.995464: train_loss -0.7472 +2024-11-21 11:44:06.995763: val_loss -0.7314 +2024-11-21 11:44:06.995841: Pseudo dice [0.8046] +2024-11-21 11:44:06.995963: Epoch time: 18.77 s +2024-11-21 11:44:07.785259: +2024-11-21 11:44:07.785449: Epoch 194 +2024-11-21 11:44:07.785561: Current learning rate: 0.00978 +2024-11-21 11:44:26.221920: train_loss -0.7442 +2024-11-21 11:44:26.222186: val_loss -0.7154 +2024-11-21 11:44:26.222260: Pseudo dice [0.8272] +2024-11-21 11:44:26.222339: Epoch time: 18.44 s +2024-11-21 11:44:27.008971: +2024-11-21 11:44:27.009161: Epoch 195 +2024-11-21 11:44:27.009277: Current learning rate: 0.00978 +2024-11-21 11:44:46.237798: train_loss -0.752 +2024-11-21 11:44:46.238015: val_loss -0.722 +2024-11-21 11:44:46.238091: Pseudo dice [0.7924] +2024-11-21 11:44:46.238237: Epoch time: 19.23 s +2024-11-21 11:44:47.022292: +2024-11-21 11:44:47.022465: Epoch 196 +2024-11-21 11:44:47.022574: Current learning rate: 0.00978 +2024-11-21 11:45:05.678130: train_loss -0.7519 +2024-11-21 11:45:05.678342: val_loss -0.7307 +2024-11-21 11:45:05.678420: Pseudo dice [0.8225] +2024-11-21 11:45:05.678497: Epoch time: 18.66 s +2024-11-21 11:45:06.466268: +2024-11-21 11:45:06.466469: Epoch 197 +2024-11-21 11:45:06.466587: Current learning rate: 0.00978 +2024-11-21 11:45:23.823501: train_loss -0.7592 +2024-11-21 11:45:23.823745: val_loss -0.698 +2024-11-21 11:45:23.823825: Pseudo dice [0.7995] +2024-11-21 11:45:23.823915: Epoch time: 17.36 s +2024-11-21 11:45:24.636209: +2024-11-21 11:45:24.636384: Epoch 198 +2024-11-21 11:45:24.636498: Current learning rate: 0.00978 +2024-11-21 11:45:43.475158: train_loss -0.7423 +2024-11-21 11:45:43.475369: val_loss -0.7221 +2024-11-21 11:45:43.475449: Pseudo dice [0.816] +2024-11-21 11:45:43.475576: Epoch time: 18.84 s +2024-11-21 11:45:44.262495: +2024-11-21 11:45:44.262680: Epoch 199 +2024-11-21 11:45:44.262795: Current learning rate: 0.00978 +2024-11-21 11:46:03.099761: train_loss -0.7323 +2024-11-21 11:46:03.099978: val_loss -0.7162 +2024-11-21 11:46:03.100060: Pseudo dice [0.8055] +2024-11-21 11:46:03.100138: Epoch time: 18.84 s +2024-11-21 11:46:04.522776: +2024-11-21 11:46:04.522985: Epoch 200 +2024-11-21 11:46:04.523107: Current learning rate: 0.00977 +2024-11-21 11:46:23.072715: train_loss -0.7456 +2024-11-21 11:46:23.073012: val_loss -0.7472 +2024-11-21 11:46:23.073089: Pseudo dice [0.8106] +2024-11-21 11:46:23.073174: Epoch time: 18.55 s +2024-11-21 11:46:23.862015: +2024-11-21 11:46:23.862254: Epoch 201 +2024-11-21 11:46:23.862368: Current learning rate: 0.00977 +2024-11-21 11:46:42.114233: train_loss -0.7556 +2024-11-21 11:46:42.114445: val_loss -0.7135 +2024-11-21 11:46:42.114521: Pseudo dice [0.81] +2024-11-21 11:46:42.114604: Epoch time: 18.25 s +2024-11-21 11:46:43.034166: +2024-11-21 11:46:43.034426: Epoch 202 +2024-11-21 11:46:43.034539: Current learning rate: 0.00977 +2024-11-21 11:47:01.690628: train_loss -0.7534 +2024-11-21 11:47:01.690847: val_loss -0.6869 +2024-11-21 11:47:01.690919: Pseudo dice [0.7784] +2024-11-21 11:47:01.691005: Epoch time: 18.66 s +2024-11-21 11:47:02.530469: +2024-11-21 11:47:02.530659: Epoch 203 +2024-11-21 11:47:02.530773: Current learning rate: 0.00977 +2024-11-21 11:47:21.221989: train_loss -0.7487 +2024-11-21 11:47:21.222204: val_loss -0.725 +2024-11-21 11:47:21.222279: Pseudo dice [0.8229] +2024-11-21 11:47:21.222358: Epoch time: 18.69 s +2024-11-21 11:47:22.005802: +2024-11-21 11:47:22.006002: Epoch 204 +2024-11-21 11:47:22.006115: Current learning rate: 0.00977 +2024-11-21 11:47:40.857023: train_loss -0.7581 +2024-11-21 11:47:40.857262: val_loss -0.7345 +2024-11-21 11:47:40.857335: Pseudo dice [0.8327] +2024-11-21 11:47:40.857722: Epoch time: 18.85 s +2024-11-21 11:47:41.645295: +2024-11-21 11:47:41.645512: Epoch 205 +2024-11-21 11:47:41.645632: Current learning rate: 0.00977 +2024-11-21 11:48:00.777131: train_loss -0.7489 +2024-11-21 11:48:00.777346: val_loss -0.743 +2024-11-21 11:48:00.777420: Pseudo dice [0.8135] +2024-11-21 11:48:00.777501: Epoch time: 19.13 s +2024-11-21 11:48:01.543514: +2024-11-21 11:48:01.543782: Epoch 206 +2024-11-21 11:48:01.543894: Current learning rate: 0.00977 +2024-11-21 11:48:20.246089: train_loss -0.7378 +2024-11-21 11:48:20.246366: val_loss -0.7093 +2024-11-21 11:48:20.246442: Pseudo dice [0.7908] +2024-11-21 11:48:20.246519: Epoch time: 18.7 s +2024-11-21 11:48:21.109197: +2024-11-21 11:48:21.109424: Epoch 207 +2024-11-21 11:48:21.109548: Current learning rate: 0.00977 +2024-11-21 11:48:39.579959: train_loss -0.7505 +2024-11-21 11:48:39.582427: val_loss -0.7391 +2024-11-21 11:48:39.582541: Pseudo dice [0.8224] +2024-11-21 11:48:39.582629: Epoch time: 18.47 s +2024-11-21 11:48:40.427125: +2024-11-21 11:48:40.427330: Epoch 208 +2024-11-21 11:48:40.427441: Current learning rate: 0.00977 +2024-11-21 11:48:57.899026: train_loss -0.7389 +2024-11-21 11:48:57.899232: val_loss -0.7289 +2024-11-21 11:48:57.899305: Pseudo dice [0.8237] +2024-11-21 11:48:57.899381: Epoch time: 17.47 s +2024-11-21 11:48:58.658419: +2024-11-21 11:48:58.658746: Epoch 209 +2024-11-21 11:48:58.658870: Current learning rate: 0.00976 +2024-11-21 11:49:17.629298: train_loss -0.7454 +2024-11-21 11:49:17.629514: val_loss -0.7432 +2024-11-21 11:49:17.629588: Pseudo dice [0.8286] +2024-11-21 11:49:17.629664: Epoch time: 18.97 s +2024-11-21 11:49:18.437251: +2024-11-21 11:49:18.437586: Epoch 210 +2024-11-21 11:49:18.437703: Current learning rate: 0.00976 +2024-11-21 11:49:36.523659: train_loss -0.7436 +2024-11-21 11:49:36.523881: val_loss -0.7084 +2024-11-21 11:49:36.524019: Pseudo dice [0.8046] +2024-11-21 11:49:36.524102: Epoch time: 18.09 s +2024-11-21 11:49:37.316198: +2024-11-21 11:49:37.316378: Epoch 211 +2024-11-21 11:49:37.316486: Current learning rate: 0.00976 +2024-11-21 11:49:56.424285: train_loss -0.749 +2024-11-21 11:49:56.424525: val_loss -0.7246 +2024-11-21 11:49:56.424602: Pseudo dice [0.8268] +2024-11-21 11:49:56.424689: Epoch time: 19.11 s +2024-11-21 11:49:57.606798: +2024-11-21 11:49:57.607013: Epoch 212 +2024-11-21 11:49:57.607129: Current learning rate: 0.00976 +2024-11-21 11:50:17.428334: train_loss -0.7351 +2024-11-21 11:50:17.428560: val_loss -0.7457 +2024-11-21 11:50:17.428654: Pseudo dice [0.8215] +2024-11-21 11:50:17.428732: Epoch time: 19.82 s +2024-11-21 11:50:17.428793: Yayy! New best EMA pseudo Dice: 0.8146 +2024-11-21 11:50:18.413444: +2024-11-21 11:50:18.413666: Epoch 213 +2024-11-21 11:50:18.413779: Current learning rate: 0.00976 +2024-11-21 11:50:37.090865: train_loss -0.7446 +2024-11-21 11:50:37.091156: val_loss -0.7263 +2024-11-21 11:50:37.091233: Pseudo dice [0.8022] +2024-11-21 11:50:37.091310: Epoch time: 18.68 s +2024-11-21 11:50:37.870394: +2024-11-21 11:50:37.870614: Epoch 214 +2024-11-21 11:50:37.870728: Current learning rate: 0.00976 +2024-11-21 11:50:56.591498: train_loss -0.7504 +2024-11-21 11:50:56.591752: val_loss -0.7367 +2024-11-21 11:50:56.591836: Pseudo dice [0.8301] +2024-11-21 11:50:56.591927: Epoch time: 18.72 s +2024-11-21 11:50:56.592021: Yayy! New best EMA pseudo Dice: 0.8151 +2024-11-21 11:50:57.577546: +2024-11-21 11:50:57.577732: Epoch 215 +2024-11-21 11:50:57.577847: Current learning rate: 0.00976 +2024-11-21 11:51:15.275306: train_loss -0.7523 +2024-11-21 11:51:15.275516: val_loss -0.7386 +2024-11-21 11:51:15.275589: Pseudo dice [0.8259] +2024-11-21 11:51:15.275664: Epoch time: 17.7 s +2024-11-21 11:51:15.275725: Yayy! New best EMA pseudo Dice: 0.8161 +2024-11-21 11:51:16.295271: +2024-11-21 11:51:16.295477: Epoch 216 +2024-11-21 11:51:16.295595: Current learning rate: 0.00976 +2024-11-21 11:51:34.253258: train_loss -0.7399 +2024-11-21 11:51:34.253476: val_loss -0.7036 +2024-11-21 11:51:34.253552: Pseudo dice [0.7793] +2024-11-21 11:51:34.255840: Epoch time: 17.96 s +2024-11-21 11:51:35.180561: +2024-11-21 11:51:35.180772: Epoch 217 +2024-11-21 11:51:35.180883: Current learning rate: 0.00976 +2024-11-21 11:51:55.120415: train_loss -0.7301 +2024-11-21 11:51:55.120679: val_loss -0.7216 +2024-11-21 11:51:55.120756: Pseudo dice [0.8116] +2024-11-21 11:51:55.120836: Epoch time: 19.94 s +2024-11-21 11:51:55.889754: +2024-11-21 11:51:55.889987: Epoch 218 +2024-11-21 11:51:55.890105: Current learning rate: 0.00975 +2024-11-21 11:52:14.868790: train_loss -0.7511 +2024-11-21 11:52:14.869040: val_loss -0.6977 +2024-11-21 11:52:14.869115: Pseudo dice [0.7989] +2024-11-21 11:52:14.869198: Epoch time: 18.98 s +2024-11-21 11:52:15.738819: +2024-11-21 11:52:15.739000: Epoch 219 +2024-11-21 11:52:15.739114: Current learning rate: 0.00975 +2024-11-21 11:52:35.022502: train_loss -0.7531 +2024-11-21 11:52:35.022716: val_loss -0.7291 +2024-11-21 11:52:35.022789: Pseudo dice [0.8253] +2024-11-21 11:52:35.022867: Epoch time: 19.28 s +2024-11-21 11:52:35.816942: +2024-11-21 11:52:35.817182: Epoch 220 +2024-11-21 11:52:35.817297: Current learning rate: 0.00975 +2024-11-21 11:52:54.433544: train_loss -0.7688 +2024-11-21 11:52:54.433770: val_loss -0.7361 +2024-11-21 11:52:54.433842: Pseudo dice [0.8193] +2024-11-21 11:52:54.433920: Epoch time: 18.62 s +2024-11-21 11:52:55.201195: +2024-11-21 11:52:55.201464: Epoch 221 +2024-11-21 11:52:55.201579: Current learning rate: 0.00975 +2024-11-21 11:53:14.434097: train_loss -0.7537 +2024-11-21 11:53:14.434371: val_loss -0.7083 +2024-11-21 11:53:14.434453: Pseudo dice [0.8159] +2024-11-21 11:53:14.434537: Epoch time: 19.23 s +2024-11-21 11:53:15.204001: +2024-11-21 11:53:15.204208: Epoch 222 +2024-11-21 11:53:15.204339: Current learning rate: 0.00975 +2024-11-21 11:53:33.886480: train_loss -0.7514 +2024-11-21 11:53:33.886753: val_loss -0.7018 +2024-11-21 11:53:33.886840: Pseudo dice [0.8117] +2024-11-21 11:53:33.886919: Epoch time: 18.68 s +2024-11-21 11:53:34.652035: +2024-11-21 11:53:34.652236: Epoch 223 +2024-11-21 11:53:34.652348: Current learning rate: 0.00975 +2024-11-21 11:53:53.444383: train_loss -0.7497 +2024-11-21 11:53:53.444608: val_loss -0.7185 +2024-11-21 11:53:53.444687: Pseudo dice [0.8076] +2024-11-21 11:53:53.444763: Epoch time: 18.79 s +2024-11-21 11:53:54.646897: +2024-11-21 11:53:54.647133: Epoch 224 +2024-11-21 11:53:54.647247: Current learning rate: 0.00975 +2024-11-21 11:54:13.329643: train_loss -0.7436 +2024-11-21 11:54:13.329896: val_loss -0.7157 +2024-11-21 11:54:13.329973: Pseudo dice [0.8118] +2024-11-21 11:54:13.330065: Epoch time: 18.68 s +2024-11-21 11:54:14.094678: +2024-11-21 11:54:14.094898: Epoch 225 +2024-11-21 11:54:14.095018: Current learning rate: 0.00975 +2024-11-21 11:54:33.281639: train_loss -0.7411 +2024-11-21 11:54:33.281856: val_loss -0.7321 +2024-11-21 11:54:33.281930: Pseudo dice [0.8179] +2024-11-21 11:54:33.282013: Epoch time: 19.19 s +2024-11-21 11:54:34.046452: +2024-11-21 11:54:34.046682: Epoch 226 +2024-11-21 11:54:34.046798: Current learning rate: 0.00975 +2024-11-21 11:54:51.595010: train_loss -0.7543 +2024-11-21 11:54:51.595226: val_loss -0.7344 +2024-11-21 11:54:51.595302: Pseudo dice [0.8352] +2024-11-21 11:54:51.595387: Epoch time: 17.55 s +2024-11-21 11:54:52.361924: +2024-11-21 11:54:52.362150: Epoch 227 +2024-11-21 11:54:52.362270: Current learning rate: 0.00974 +2024-11-21 11:55:11.082619: train_loss -0.749 +2024-11-21 11:55:11.082863: val_loss -0.6917 +2024-11-21 11:55:11.082972: Pseudo dice [0.8008] +2024-11-21 11:55:11.083061: Epoch time: 18.72 s +2024-11-21 11:55:11.850720: +2024-11-21 11:55:11.850940: Epoch 228 +2024-11-21 11:55:11.851061: Current learning rate: 0.00974 +2024-11-21 11:55:30.750609: train_loss -0.7545 +2024-11-21 11:55:30.750847: val_loss -0.7396 +2024-11-21 11:55:30.750927: Pseudo dice [0.8252] +2024-11-21 11:55:30.751029: Epoch time: 18.9 s +2024-11-21 11:55:31.536982: +2024-11-21 11:55:31.537254: Epoch 229 +2024-11-21 11:55:31.537367: Current learning rate: 0.00974 +2024-11-21 11:55:50.014566: train_loss -0.7588 +2024-11-21 11:55:50.014870: val_loss -0.7498 +2024-11-21 11:55:50.016622: Pseudo dice [0.8337] +2024-11-21 11:55:50.016768: Epoch time: 18.48 s +2024-11-21 11:55:50.016840: Yayy! New best EMA pseudo Dice: 0.8169 +2024-11-21 11:55:51.012298: +2024-11-21 11:55:51.012508: Epoch 230 +2024-11-21 11:55:51.012628: Current learning rate: 0.00974 +2024-11-21 11:56:09.268925: train_loss -0.7426 +2024-11-21 11:56:09.269158: val_loss -0.7393 +2024-11-21 11:56:09.269233: Pseudo dice [0.8317] +2024-11-21 11:56:09.269310: Epoch time: 18.26 s +2024-11-21 11:56:09.269372: Yayy! New best EMA pseudo Dice: 0.8184 +2024-11-21 11:56:10.408096: +2024-11-21 11:56:10.408274: Epoch 231 +2024-11-21 11:56:10.408388: Current learning rate: 0.00974 +2024-11-21 11:56:29.256426: train_loss -0.7481 +2024-11-21 11:56:29.256640: val_loss -0.7362 +2024-11-21 11:56:29.256715: Pseudo dice [0.8187] +2024-11-21 11:56:29.256793: Epoch time: 18.85 s +2024-11-21 11:56:29.256855: Yayy! New best EMA pseudo Dice: 0.8184 +2024-11-21 11:56:30.241464: +2024-11-21 11:56:30.241655: Epoch 232 +2024-11-21 11:56:30.241776: Current learning rate: 0.00974 +2024-11-21 11:56:48.774695: train_loss -0.7493 +2024-11-21 11:56:48.774917: val_loss -0.7213 +2024-11-21 11:56:48.774997: Pseudo dice [0.8176] +2024-11-21 11:56:48.775076: Epoch time: 18.53 s +2024-11-21 11:56:49.542718: +2024-11-21 11:56:49.542973: Epoch 233 +2024-11-21 11:56:49.543096: Current learning rate: 0.00974 +2024-11-21 11:57:07.557704: train_loss -0.738 +2024-11-21 11:57:07.557911: val_loss -0.7265 +2024-11-21 11:57:07.557985: Pseudo dice [0.8067] +2024-11-21 11:57:07.558074: Epoch time: 18.02 s +2024-11-21 11:57:08.346474: +2024-11-21 11:57:08.346677: Epoch 234 +2024-11-21 11:57:08.346792: Current learning rate: 0.00974 +2024-11-21 11:57:26.562467: train_loss -0.7475 +2024-11-21 11:57:26.562674: val_loss -0.7236 +2024-11-21 11:57:26.562756: Pseudo dice [0.8112] +2024-11-21 11:57:26.562836: Epoch time: 18.22 s +2024-11-21 11:57:27.430753: +2024-11-21 11:57:27.430954: Epoch 235 +2024-11-21 11:57:27.431070: Current learning rate: 0.00974 +2024-11-21 11:57:45.923159: train_loss -0.7547 +2024-11-21 11:57:45.923411: val_loss -0.7161 +2024-11-21 11:57:45.923488: Pseudo dice [0.7895] +2024-11-21 11:57:45.923571: Epoch time: 18.49 s +2024-11-21 11:57:46.692146: +2024-11-21 11:57:46.692338: Epoch 236 +2024-11-21 11:57:46.692524: Current learning rate: 0.00973 +2024-11-21 11:58:05.761818: train_loss -0.7602 +2024-11-21 11:58:05.762043: val_loss -0.7245 +2024-11-21 11:58:05.762120: Pseudo dice [0.8142] +2024-11-21 11:58:05.762197: Epoch time: 19.07 s +2024-11-21 11:58:06.527856: +2024-11-21 11:58:06.528115: Epoch 237 +2024-11-21 11:58:06.528239: Current learning rate: 0.00973 +2024-11-21 11:58:25.353951: train_loss -0.743 +2024-11-21 11:58:25.354174: val_loss -0.714 +2024-11-21 11:58:25.354248: Pseudo dice [0.8084] +2024-11-21 11:58:25.359486: Epoch time: 18.83 s +2024-11-21 11:58:26.287776: +2024-11-21 11:58:26.287987: Epoch 238 +2024-11-21 11:58:26.288112: Current learning rate: 0.00973 +2024-11-21 11:58:44.857113: train_loss -0.7424 +2024-11-21 11:58:44.857360: val_loss -0.7155 +2024-11-21 11:58:44.857437: Pseudo dice [0.8094] +2024-11-21 11:58:44.857524: Epoch time: 18.57 s +2024-11-21 11:58:45.630110: +2024-11-21 11:58:45.630298: Epoch 239 +2024-11-21 11:58:45.630439: Current learning rate: 0.00973 +2024-11-21 11:59:04.332293: train_loss -0.7436 +2024-11-21 11:59:04.332512: val_loss -0.7319 +2024-11-21 11:59:04.332584: Pseudo dice [0.819] +2024-11-21 11:59:04.332660: Epoch time: 18.7 s +2024-11-21 11:59:05.110464: +2024-11-21 11:59:05.110666: Epoch 240 +2024-11-21 11:59:05.110780: Current learning rate: 0.00973 +2024-11-21 11:59:25.078675: train_loss -0.7406 +2024-11-21 11:59:25.078902: val_loss -0.7611 +2024-11-21 11:59:25.081178: Pseudo dice [0.8183] +2024-11-21 11:59:25.081292: Epoch time: 19.97 s +2024-11-21 11:59:25.885459: +2024-11-21 11:59:25.885646: Epoch 241 +2024-11-21 11:59:25.885756: Current learning rate: 0.00973 +2024-11-21 11:59:45.295765: train_loss -0.7386 +2024-11-21 11:59:45.295983: val_loss -0.7125 +2024-11-21 11:59:45.296104: Pseudo dice [0.7898] +2024-11-21 11:59:45.312823: Epoch time: 19.41 s +2024-11-21 11:59:46.169750: +2024-11-21 11:59:46.170019: Epoch 242 +2024-11-21 11:59:46.170135: Current learning rate: 0.00973 +2024-11-21 12:00:05.059247: train_loss -0.7414 +2024-11-21 12:00:05.061674: val_loss -0.7091 +2024-11-21 12:00:05.061762: Pseudo dice [0.8135] +2024-11-21 12:00:05.061845: Epoch time: 18.89 s +2024-11-21 12:00:05.874290: +2024-11-21 12:00:05.874503: Epoch 243 +2024-11-21 12:00:05.874622: Current learning rate: 0.00973 +2024-11-21 12:00:24.152297: train_loss -0.7539 +2024-11-21 12:00:24.152507: val_loss -0.7486 +2024-11-21 12:00:24.152582: Pseudo dice [0.8334] +2024-11-21 12:00:24.152660: Epoch time: 18.28 s +2024-11-21 12:00:24.926904: +2024-11-21 12:00:24.927122: Epoch 244 +2024-11-21 12:00:24.927235: Current learning rate: 0.00973 +2024-11-21 12:00:45.038901: train_loss -0.7463 +2024-11-21 12:00:45.039194: val_loss -0.7159 +2024-11-21 12:00:45.039476: Pseudo dice [0.8132] +2024-11-21 12:00:45.039561: Epoch time: 20.11 s +2024-11-21 12:00:45.916678: +2024-11-21 12:00:45.916893: Epoch 245 +2024-11-21 12:00:45.917013: Current learning rate: 0.00972 +2024-11-21 12:01:03.796743: train_loss -0.7601 +2024-11-21 12:01:03.796998: val_loss -0.738 +2024-11-21 12:01:03.797134: Pseudo dice [0.8202] +2024-11-21 12:01:03.797212: Epoch time: 17.88 s +2024-11-21 12:01:04.571856: +2024-11-21 12:01:04.572067: Epoch 246 +2024-11-21 12:01:04.572181: Current learning rate: 0.00972 +2024-11-21 12:01:22.212997: train_loss -0.7732 +2024-11-21 12:01:22.213213: val_loss -0.7526 +2024-11-21 12:01:22.213286: Pseudo dice [0.8268] +2024-11-21 12:01:22.213365: Epoch time: 17.64 s +2024-11-21 12:01:22.996161: +2024-11-21 12:01:22.996359: Epoch 247 +2024-11-21 12:01:22.996470: Current learning rate: 0.00972 +2024-11-21 12:01:41.586370: train_loss -0.7594 +2024-11-21 12:01:41.586584: val_loss -0.7277 +2024-11-21 12:01:41.586659: Pseudo dice [0.8159] +2024-11-21 12:01:41.586736: Epoch time: 18.59 s +2024-11-21 12:01:42.424495: +2024-11-21 12:01:42.424726: Epoch 248 +2024-11-21 12:01:42.424841: Current learning rate: 0.00972 +2024-11-21 12:02:00.863626: train_loss -0.7641 +2024-11-21 12:02:00.863851: val_loss -0.7195 +2024-11-21 12:02:00.863931: Pseudo dice [0.8084] +2024-11-21 12:02:00.864013: Epoch time: 18.44 s +2024-11-21 12:02:01.644637: +2024-11-21 12:02:01.644877: Epoch 249 +2024-11-21 12:02:01.645043: Current learning rate: 0.00972 +2024-11-21 12:02:20.626162: train_loss -0.7485 +2024-11-21 12:02:20.626380: val_loss -0.7493 +2024-11-21 12:02:20.626458: Pseudo dice [0.8234] +2024-11-21 12:02:20.626536: Epoch time: 18.98 s +2024-11-21 12:02:21.627583: +2024-11-21 12:02:21.627784: Epoch 250 +2024-11-21 12:02:21.627971: Current learning rate: 0.00972 +2024-11-21 12:02:39.961155: train_loss -0.7561 +2024-11-21 12:02:39.961378: val_loss -0.7318 +2024-11-21 12:02:39.961455: Pseudo dice [0.7964] +2024-11-21 12:02:39.961534: Epoch time: 18.33 s +2024-11-21 12:02:40.732146: +2024-11-21 12:02:40.732359: Epoch 251 +2024-11-21 12:02:40.732477: Current learning rate: 0.00972 +2024-11-21 12:03:00.071021: train_loss -0.7536 +2024-11-21 12:03:00.073473: val_loss -0.715 +2024-11-21 12:03:00.073603: Pseudo dice [0.8216] +2024-11-21 12:03:00.073699: Epoch time: 19.34 s +2024-11-21 12:03:00.876082: +2024-11-21 12:03:00.876311: Epoch 252 +2024-11-21 12:03:00.876422: Current learning rate: 0.00972 +2024-11-21 12:03:19.849032: train_loss -0.7364 +2024-11-21 12:03:19.849257: val_loss -0.721 +2024-11-21 12:03:19.849337: Pseudo dice [0.8179] +2024-11-21 12:03:19.849410: Epoch time: 18.97 s +2024-11-21 12:03:20.896722: +2024-11-21 12:03:20.896921: Epoch 253 +2024-11-21 12:03:20.897034: Current learning rate: 0.00971 +2024-11-21 12:03:39.722739: train_loss -0.7545 +2024-11-21 12:03:39.722953: val_loss -0.7359 +2024-11-21 12:03:39.723035: Pseudo dice [0.8277] +2024-11-21 12:03:39.723115: Epoch time: 18.83 s +2024-11-21 12:03:40.559565: +2024-11-21 12:03:40.559856: Epoch 254 +2024-11-21 12:03:40.559973: Current learning rate: 0.00971 +2024-11-21 12:03:58.943254: train_loss -0.758 +2024-11-21 12:03:58.945729: val_loss -0.7293 +2024-11-21 12:03:58.945850: Pseudo dice [0.8107] +2024-11-21 12:03:58.945929: Epoch time: 18.38 s +2024-11-21 12:03:59.873855: +2024-11-21 12:03:59.874102: Epoch 255 +2024-11-21 12:03:59.874219: Current learning rate: 0.00971 +2024-11-21 12:04:18.730419: train_loss -0.7537 +2024-11-21 12:04:18.730657: val_loss -0.7366 +2024-11-21 12:04:18.730732: Pseudo dice [0.803] +2024-11-21 12:04:18.730816: Epoch time: 18.86 s +2024-11-21 12:04:19.508185: +2024-11-21 12:04:19.508380: Epoch 256 +2024-11-21 12:04:19.508492: Current learning rate: 0.00971 +2024-11-21 12:04:37.969552: train_loss -0.7426 +2024-11-21 12:04:37.969766: val_loss -0.7225 +2024-11-21 12:04:37.969840: Pseudo dice [0.8079] +2024-11-21 12:04:37.969916: Epoch time: 18.46 s +2024-11-21 12:04:38.799025: +2024-11-21 12:04:38.799216: Epoch 257 +2024-11-21 12:04:38.799328: Current learning rate: 0.00971 +2024-11-21 12:04:56.907290: train_loss -0.738 +2024-11-21 12:04:56.907508: val_loss -0.7195 +2024-11-21 12:04:56.907584: Pseudo dice [0.8162] +2024-11-21 12:04:56.907664: Epoch time: 18.11 s +2024-11-21 12:04:57.682098: +2024-11-21 12:04:57.682302: Epoch 258 +2024-11-21 12:04:57.682418: Current learning rate: 0.00971 +2024-11-21 12:05:16.380267: train_loss -0.7398 +2024-11-21 12:05:16.380473: val_loss -0.733 +2024-11-21 12:05:16.380547: Pseudo dice [0.8336] +2024-11-21 12:05:16.380625: Epoch time: 18.7 s +2024-11-21 12:05:17.229259: +2024-11-21 12:05:17.229473: Epoch 259 +2024-11-21 12:05:17.229585: Current learning rate: 0.00971 +2024-11-21 12:05:36.208358: train_loss -0.7405 +2024-11-21 12:05:36.213735: val_loss -0.7422 +2024-11-21 12:05:36.213897: Pseudo dice [0.8336] +2024-11-21 12:05:36.213986: Epoch time: 18.98 s +2024-11-21 12:05:37.116193: +2024-11-21 12:05:37.116375: Epoch 260 +2024-11-21 12:05:37.116486: Current learning rate: 0.00971 +2024-11-21 12:05:56.285057: train_loss -0.7527 +2024-11-21 12:05:56.285288: val_loss -0.7226 +2024-11-21 12:05:56.285366: Pseudo dice [0.8163] +2024-11-21 12:05:56.285443: Epoch time: 19.17 s +2024-11-21 12:05:57.273513: +2024-11-21 12:05:57.273748: Epoch 261 +2024-11-21 12:05:57.273868: Current learning rate: 0.00971 +2024-11-21 12:06:15.054695: train_loss -0.7566 +2024-11-21 12:06:15.054916: val_loss -0.7193 +2024-11-21 12:06:15.055001: Pseudo dice [0.8202] +2024-11-21 12:06:15.055081: Epoch time: 17.78 s +2024-11-21 12:06:15.843428: +2024-11-21 12:06:15.843704: Epoch 262 +2024-11-21 12:06:15.843820: Current learning rate: 0.0097 +2024-11-21 12:06:35.715634: train_loss -0.7534 +2024-11-21 12:06:35.718056: val_loss -0.7245 +2024-11-21 12:06:35.718176: Pseudo dice [0.8068] +2024-11-21 12:06:35.718262: Epoch time: 19.87 s +2024-11-21 12:06:36.671129: +2024-11-21 12:06:36.671409: Epoch 263 +2024-11-21 12:06:36.671521: Current learning rate: 0.0097 +2024-11-21 12:06:54.258584: train_loss -0.7481 +2024-11-21 12:06:54.258854: val_loss -0.7384 +2024-11-21 12:06:54.258929: Pseudo dice [0.7926] +2024-11-21 12:06:54.259009: Epoch time: 17.59 s +2024-11-21 12:06:55.117075: +2024-11-21 12:06:55.117414: Epoch 264 +2024-11-21 12:06:55.117529: Current learning rate: 0.0097 +2024-11-21 12:07:14.431304: train_loss -0.7432 +2024-11-21 12:07:14.431518: val_loss -0.7185 +2024-11-21 12:07:14.431592: Pseudo dice [0.8006] +2024-11-21 12:07:14.431666: Epoch time: 19.32 s +2024-11-21 12:07:15.215904: +2024-11-21 12:07:15.216113: Epoch 265 +2024-11-21 12:07:15.216229: Current learning rate: 0.0097 +2024-11-21 12:07:33.554160: train_loss -0.7597 +2024-11-21 12:07:33.554393: val_loss -0.7137 +2024-11-21 12:07:33.554466: Pseudo dice [0.7999] +2024-11-21 12:07:33.554551: Epoch time: 18.34 s +2024-11-21 12:07:34.382703: +2024-11-21 12:07:34.383042: Epoch 266 +2024-11-21 12:07:34.383161: Current learning rate: 0.0097 +2024-11-21 12:07:52.453989: train_loss -0.7506 +2024-11-21 12:07:52.454216: val_loss -0.7287 +2024-11-21 12:07:52.454355: Pseudo dice [0.809] +2024-11-21 12:07:52.454437: Epoch time: 18.07 s +2024-11-21 12:07:53.241997: +2024-11-21 12:07:53.242256: Epoch 267 +2024-11-21 12:07:53.242368: Current learning rate: 0.0097 +2024-11-21 12:08:12.552067: train_loss -0.7459 +2024-11-21 12:08:12.552336: val_loss -0.7369 +2024-11-21 12:08:12.552412: Pseudo dice [0.8072] +2024-11-21 12:08:12.552494: Epoch time: 19.31 s +2024-11-21 12:08:13.338321: +2024-11-21 12:08:13.338600: Epoch 268 +2024-11-21 12:08:13.338735: Current learning rate: 0.0097 +2024-11-21 12:08:31.909005: train_loss -0.7509 +2024-11-21 12:08:31.909257: val_loss -0.744 +2024-11-21 12:08:31.909347: Pseudo dice [0.8243] +2024-11-21 12:08:31.909432: Epoch time: 18.57 s +2024-11-21 12:08:32.755491: +2024-11-21 12:08:32.755697: Epoch 269 +2024-11-21 12:08:32.755812: Current learning rate: 0.0097 +2024-11-21 12:08:51.488892: train_loss -0.7521 +2024-11-21 12:08:51.489148: val_loss -0.7311 +2024-11-21 12:08:51.489225: Pseudo dice [0.8143] +2024-11-21 12:08:51.490771: Epoch time: 18.73 s +2024-11-21 12:08:52.319609: +2024-11-21 12:08:52.319800: Epoch 270 +2024-11-21 12:08:52.319914: Current learning rate: 0.0097 +2024-11-21 12:09:10.354644: train_loss -0.7399 +2024-11-21 12:09:10.354856: val_loss -0.7444 +2024-11-21 12:09:10.354928: Pseudo dice [0.8235] +2024-11-21 12:09:10.355273: Epoch time: 18.04 s +2024-11-21 12:09:11.140035: +2024-11-21 12:09:11.140218: Epoch 271 +2024-11-21 12:09:11.140334: Current learning rate: 0.00969 +2024-11-21 12:09:30.259968: train_loss -0.7592 +2024-11-21 12:09:30.260190: val_loss -0.7162 +2024-11-21 12:09:30.260267: Pseudo dice [0.8105] +2024-11-21 12:09:30.260343: Epoch time: 19.12 s +2024-11-21 12:09:31.151699: +2024-11-21 12:09:31.151919: Epoch 272 +2024-11-21 12:09:31.152041: Current learning rate: 0.00969 +2024-11-21 12:09:49.693243: train_loss -0.7499 +2024-11-21 12:09:49.693492: val_loss -0.7295 +2024-11-21 12:09:49.693569: Pseudo dice [0.8164] +2024-11-21 12:09:49.693657: Epoch time: 18.54 s +2024-11-21 12:09:50.536328: +2024-11-21 12:09:50.536529: Epoch 273 +2024-11-21 12:09:50.536643: Current learning rate: 0.00969 +2024-11-21 12:10:09.396677: train_loss -0.7475 +2024-11-21 12:10:09.396892: val_loss -0.7118 +2024-11-21 12:10:09.399199: Pseudo dice [0.7987] +2024-11-21 12:10:09.399298: Epoch time: 18.86 s +2024-11-21 12:10:10.257589: +2024-11-21 12:10:10.257784: Epoch 274 +2024-11-21 12:10:10.257900: Current learning rate: 0.00969 +2024-11-21 12:10:29.130172: train_loss -0.744 +2024-11-21 12:10:29.130466: val_loss -0.7417 +2024-11-21 12:10:29.130548: Pseudo dice [0.8324] +2024-11-21 12:10:29.130625: Epoch time: 18.87 s +2024-11-21 12:10:29.910554: +2024-11-21 12:10:29.910818: Epoch 275 +2024-11-21 12:10:29.910939: Current learning rate: 0.00969 +2024-11-21 12:10:48.133841: train_loss -0.7369 +2024-11-21 12:10:48.134089: val_loss -0.7347 +2024-11-21 12:10:48.134165: Pseudo dice [0.7938] +2024-11-21 12:10:48.134252: Epoch time: 18.22 s +2024-11-21 12:10:48.914092: +2024-11-21 12:10:48.914486: Epoch 276 +2024-11-21 12:10:48.914605: Current learning rate: 0.00969 +2024-11-21 12:11:08.038627: train_loss -0.7365 +2024-11-21 12:11:08.038848: val_loss -0.7226 +2024-11-21 12:11:08.038926: Pseudo dice [0.8205] +2024-11-21 12:11:08.039011: Epoch time: 19.13 s +2024-11-21 12:11:08.845423: +2024-11-21 12:11:08.845703: Epoch 277 +2024-11-21 12:11:08.845823: Current learning rate: 0.00969 +2024-11-21 12:11:28.082458: train_loss -0.727 +2024-11-21 12:11:28.082666: val_loss -0.7398 +2024-11-21 12:11:28.082739: Pseudo dice [0.8051] +2024-11-21 12:11:28.082817: Epoch time: 19.24 s +2024-11-21 12:11:28.904022: +2024-11-21 12:11:28.904232: Epoch 278 +2024-11-21 12:11:28.904344: Current learning rate: 0.00969 +2024-11-21 12:11:47.880350: train_loss -0.7469 +2024-11-21 12:11:47.880632: val_loss -0.7251 +2024-11-21 12:11:47.880716: Pseudo dice [0.8022] +2024-11-21 12:11:47.880799: Epoch time: 18.98 s +2024-11-21 12:11:48.785331: +2024-11-21 12:11:48.785515: Epoch 279 +2024-11-21 12:11:48.785652: Current learning rate: 0.00969 +2024-11-21 12:12:08.133266: train_loss -0.7435 +2024-11-21 12:12:08.133501: val_loss -0.7446 +2024-11-21 12:12:08.133584: Pseudo dice [0.8056] +2024-11-21 12:12:08.133677: Epoch time: 19.35 s +2024-11-21 12:12:08.944611: +2024-11-21 12:12:08.944837: Epoch 280 +2024-11-21 12:12:08.944951: Current learning rate: 0.00968 +2024-11-21 12:12:28.389871: train_loss -0.7494 +2024-11-21 12:12:28.390140: val_loss -0.7414 +2024-11-21 12:12:28.390225: Pseudo dice [0.8213] +2024-11-21 12:12:28.390306: Epoch time: 19.45 s +2024-11-21 12:12:29.170110: +2024-11-21 12:12:29.170314: Epoch 281 +2024-11-21 12:12:29.170424: Current learning rate: 0.00968 +2024-11-21 12:12:48.692002: train_loss -0.7459 +2024-11-21 12:12:48.692222: val_loss -0.7498 +2024-11-21 12:12:48.692294: Pseudo dice [0.8263] +2024-11-21 12:12:48.692370: Epoch time: 19.52 s +2024-11-21 12:12:49.495841: +2024-11-21 12:12:49.496032: Epoch 282 +2024-11-21 12:12:49.496144: Current learning rate: 0.00968 +2024-11-21 12:13:07.939320: train_loss -0.757 +2024-11-21 12:13:07.939561: val_loss -0.7262 +2024-11-21 12:13:07.939640: Pseudo dice [0.8086] +2024-11-21 12:13:07.939812: Epoch time: 18.44 s +2024-11-21 12:13:08.772464: +2024-11-21 12:13:08.772750: Epoch 283 +2024-11-21 12:13:08.772871: Current learning rate: 0.00968 +2024-11-21 12:13:28.513893: train_loss -0.752 +2024-11-21 12:13:28.514116: val_loss -0.7289 +2024-11-21 12:13:28.514190: Pseudo dice [0.8312] +2024-11-21 12:13:28.514266: Epoch time: 19.74 s +2024-11-21 12:13:29.311295: +2024-11-21 12:13:29.311533: Epoch 284 +2024-11-21 12:13:29.311650: Current learning rate: 0.00968 +2024-11-21 12:13:48.106071: train_loss -0.7293 +2024-11-21 12:13:48.106285: val_loss -0.714 +2024-11-21 12:13:48.106359: Pseudo dice [0.8201] +2024-11-21 12:13:48.106434: Epoch time: 18.8 s +2024-11-21 12:13:48.888015: +2024-11-21 12:13:48.888227: Epoch 285 +2024-11-21 12:13:48.888344: Current learning rate: 0.00968 +2024-11-21 12:14:08.321683: train_loss -0.7362 +2024-11-21 12:14:08.321927: val_loss -0.7316 +2024-11-21 12:14:08.322008: Pseudo dice [0.8132] +2024-11-21 12:14:08.322094: Epoch time: 19.43 s +2024-11-21 12:14:09.120627: +2024-11-21 12:14:09.120844: Epoch 286 +2024-11-21 12:14:09.120959: Current learning rate: 0.00968 +2024-11-21 12:14:27.629694: train_loss -0.7624 +2024-11-21 12:14:27.629901: val_loss -0.7251 +2024-11-21 12:14:27.629975: Pseudo dice [0.8139] +2024-11-21 12:14:27.630057: Epoch time: 18.51 s +2024-11-21 12:14:28.415892: +2024-11-21 12:14:28.416285: Epoch 287 +2024-11-21 12:14:28.416402: Current learning rate: 0.00968 +2024-11-21 12:14:47.167249: train_loss -0.7554 +2024-11-21 12:14:47.167466: val_loss -0.7499 +2024-11-21 12:14:47.167562: Pseudo dice [0.8355] +2024-11-21 12:14:47.167643: Epoch time: 18.75 s +2024-11-21 12:14:47.959513: +2024-11-21 12:14:47.959731: Epoch 288 +2024-11-21 12:14:47.959851: Current learning rate: 0.00968 +2024-11-21 12:15:05.607758: train_loss -0.7543 +2024-11-21 12:15:05.607981: val_loss -0.7264 +2024-11-21 12:15:05.608067: Pseudo dice [0.8275] +2024-11-21 12:15:05.608153: Epoch time: 17.65 s +2024-11-21 12:15:06.405932: +2024-11-21 12:15:06.406179: Epoch 289 +2024-11-21 12:15:06.406296: Current learning rate: 0.00967 +2024-11-21 12:15:24.647496: train_loss -0.7488 +2024-11-21 12:15:24.647742: val_loss -0.7322 +2024-11-21 12:15:24.647815: Pseudo dice [0.817] +2024-11-21 12:15:24.658129: Epoch time: 18.24 s +2024-11-21 12:15:25.542391: +2024-11-21 12:15:25.542569: Epoch 290 +2024-11-21 12:15:25.542738: Current learning rate: 0.00967 +2024-11-21 12:15:44.620787: train_loss -0.7495 +2024-11-21 12:15:44.623212: val_loss -0.7477 +2024-11-21 12:15:44.623309: Pseudo dice [0.8158] +2024-11-21 12:15:44.623393: Epoch time: 19.08 s +2024-11-21 12:15:45.412397: +2024-11-21 12:15:45.412585: Epoch 291 +2024-11-21 12:15:45.412696: Current learning rate: 0.00967 +2024-11-21 12:16:04.145046: train_loss -0.7332 +2024-11-21 12:16:04.145264: val_loss -0.7205 +2024-11-21 12:16:04.145339: Pseudo dice [0.8078] +2024-11-21 12:16:04.145414: Epoch time: 18.73 s +2024-11-21 12:16:04.930055: +2024-11-21 12:16:04.930237: Epoch 292 +2024-11-21 12:16:04.930346: Current learning rate: 0.00967 +2024-11-21 12:16:23.193418: train_loss -0.7504 +2024-11-21 12:16:23.193662: val_loss -0.7266 +2024-11-21 12:16:23.193740: Pseudo dice [0.8054] +2024-11-21 12:16:23.193824: Epoch time: 18.26 s +2024-11-21 12:16:23.996500: +2024-11-21 12:16:23.996686: Epoch 293 +2024-11-21 12:16:23.996799: Current learning rate: 0.00967 +2024-11-21 12:16:41.842918: train_loss -0.7542 +2024-11-21 12:16:41.843190: val_loss -0.7247 +2024-11-21 12:16:41.843269: Pseudo dice [0.8118] +2024-11-21 12:16:41.843348: Epoch time: 17.85 s +2024-11-21 12:16:42.701927: +2024-11-21 12:16:42.702116: Epoch 294 +2024-11-21 12:16:42.702230: Current learning rate: 0.00967 +2024-11-21 12:17:01.500495: train_loss -0.758 +2024-11-21 12:17:01.500704: val_loss -0.7175 +2024-11-21 12:17:01.500779: Pseudo dice [0.8033] +2024-11-21 12:17:01.500897: Epoch time: 18.8 s +2024-11-21 12:17:02.294056: +2024-11-21 12:17:02.294276: Epoch 295 +2024-11-21 12:17:02.294388: Current learning rate: 0.00967 +2024-11-21 12:17:19.558180: train_loss -0.7516 +2024-11-21 12:17:19.558392: val_loss -0.7217 +2024-11-21 12:17:19.558477: Pseudo dice [0.8029] +2024-11-21 12:17:19.558559: Epoch time: 17.26 s +2024-11-21 12:17:20.752335: +2024-11-21 12:17:20.752616: Epoch 296 +2024-11-21 12:17:20.752733: Current learning rate: 0.00967 +2024-11-21 12:17:39.769377: train_loss -0.7492 +2024-11-21 12:17:39.774803: val_loss -0.7263 +2024-11-21 12:17:39.774891: Pseudo dice [0.8317] +2024-11-21 12:17:39.775071: Epoch time: 19.02 s +2024-11-21 12:17:40.573052: +2024-11-21 12:17:40.573254: Epoch 297 +2024-11-21 12:17:40.573367: Current learning rate: 0.00967 +2024-11-21 12:17:59.003995: train_loss -0.7481 +2024-11-21 12:17:59.004241: val_loss -0.7512 +2024-11-21 12:17:59.004318: Pseudo dice [0.8254] +2024-11-21 12:17:59.004395: Epoch time: 18.43 s +2024-11-21 12:17:59.802709: +2024-11-21 12:17:59.802909: Epoch 298 +2024-11-21 12:17:59.803029: Current learning rate: 0.00966 +2024-11-21 12:18:19.109100: train_loss -0.7581 +2024-11-21 12:18:19.109313: val_loss -0.735 +2024-11-21 12:18:19.109388: Pseudo dice [0.823] +2024-11-21 12:18:19.109463: Epoch time: 19.31 s +2024-11-21 12:18:19.900809: +2024-11-21 12:18:19.901022: Epoch 299 +2024-11-21 12:18:19.901152: Current learning rate: 0.00966 +2024-11-21 12:18:38.128412: train_loss -0.7454 +2024-11-21 12:18:38.128659: val_loss -0.7332 +2024-11-21 12:18:38.128738: Pseudo dice [0.8158] +2024-11-21 12:18:38.128823: Epoch time: 18.23 s +2024-11-21 12:18:39.159464: +2024-11-21 12:18:39.159668: Epoch 300 +2024-11-21 12:18:39.159783: Current learning rate: 0.00966 +2024-11-21 12:18:56.937496: train_loss -0.7577 +2024-11-21 12:18:56.937702: val_loss -0.7524 +2024-11-21 12:18:56.937775: Pseudo dice [0.82] +2024-11-21 12:18:56.937851: Epoch time: 17.78 s +2024-11-21 12:18:57.776252: +2024-11-21 12:18:57.776476: Epoch 301 +2024-11-21 12:18:57.776593: Current learning rate: 0.00966 +2024-11-21 12:19:16.174700: train_loss -0.7426 +2024-11-21 12:19:16.174978: val_loss -0.7519 +2024-11-21 12:19:16.175063: Pseudo dice [0.8329] +2024-11-21 12:19:16.175142: Epoch time: 18.4 s +2024-11-21 12:19:16.175217: Yayy! New best EMA pseudo Dice: 0.8184 +2024-11-21 12:19:17.190862: +2024-11-21 12:19:17.191106: Epoch 302 +2024-11-21 12:19:17.191217: Current learning rate: 0.00966 +2024-11-21 12:19:35.593012: train_loss -0.7646 +2024-11-21 12:19:35.593230: val_loss -0.737 +2024-11-21 12:19:35.593305: Pseudo dice [0.8433] +2024-11-21 12:19:35.593385: Epoch time: 18.4 s +2024-11-21 12:19:35.593447: Yayy! New best EMA pseudo Dice: 0.8209 +2024-11-21 12:19:36.617705: +2024-11-21 12:19:36.618042: Epoch 303 +2024-11-21 12:19:36.618159: Current learning rate: 0.00966 +2024-11-21 12:19:54.779181: train_loss -0.7616 +2024-11-21 12:19:54.779423: val_loss -0.7172 +2024-11-21 12:19:54.779496: Pseudo dice [0.7881] +2024-11-21 12:19:54.779577: Epoch time: 18.16 s +2024-11-21 12:19:55.664669: +2024-11-21 12:19:55.664891: Epoch 304 +2024-11-21 12:19:55.665008: Current learning rate: 0.00966 +2024-11-21 12:20:14.647202: train_loss -0.7517 +2024-11-21 12:20:14.647421: val_loss -0.724 +2024-11-21 12:20:14.647495: Pseudo dice [0.8135] +2024-11-21 12:20:14.647569: Epoch time: 18.98 s +2024-11-21 12:20:15.430333: +2024-11-21 12:20:15.430547: Epoch 305 +2024-11-21 12:20:15.430661: Current learning rate: 0.00966 +2024-11-21 12:20:33.817578: train_loss -0.7509 +2024-11-21 12:20:33.817799: val_loss -0.745 +2024-11-21 12:20:33.817884: Pseudo dice [0.8279] +2024-11-21 12:20:33.817965: Epoch time: 18.39 s +2024-11-21 12:20:34.614628: +2024-11-21 12:20:34.614824: Epoch 306 +2024-11-21 12:20:34.614933: Current learning rate: 0.00966 +2024-11-21 12:20:52.488415: train_loss -0.7447 +2024-11-21 12:20:52.488623: val_loss -0.7315 +2024-11-21 12:20:52.488704: Pseudo dice [0.8217] +2024-11-21 12:20:52.488809: Epoch time: 17.87 s +2024-11-21 12:20:53.300233: +2024-11-21 12:20:53.300444: Epoch 307 +2024-11-21 12:20:53.300563: Current learning rate: 0.00965 +2024-11-21 12:21:11.733433: train_loss -0.7452 +2024-11-21 12:21:11.733647: val_loss -0.7077 +2024-11-21 12:21:11.733720: Pseudo dice [0.8031] +2024-11-21 12:21:11.733798: Epoch time: 18.43 s +2024-11-21 12:21:12.528652: +2024-11-21 12:21:12.528905: Epoch 308 +2024-11-21 12:21:12.529028: Current learning rate: 0.00965 +2024-11-21 12:21:32.314861: train_loss -0.7554 +2024-11-21 12:21:32.320264: val_loss -0.7323 +2024-11-21 12:21:32.320345: Pseudo dice [0.8131] +2024-11-21 12:21:32.320425: Epoch time: 19.79 s +2024-11-21 12:21:33.154970: +2024-11-21 12:21:33.155183: Epoch 309 +2024-11-21 12:21:33.155296: Current learning rate: 0.00965 +2024-11-21 12:21:51.467308: train_loss -0.7566 +2024-11-21 12:21:51.467547: val_loss -0.718 +2024-11-21 12:21:51.467624: Pseudo dice [0.8339] +2024-11-21 12:21:51.467707: Epoch time: 18.31 s +2024-11-21 12:21:52.259275: +2024-11-21 12:21:52.259538: Epoch 310 +2024-11-21 12:21:52.259654: Current learning rate: 0.00965 +2024-11-21 12:22:11.107402: train_loss -0.7624 +2024-11-21 12:22:11.107609: val_loss -0.7207 +2024-11-21 12:22:11.107683: Pseudo dice [0.8028] +2024-11-21 12:22:11.107826: Epoch time: 18.85 s +2024-11-21 12:22:11.906926: +2024-11-21 12:22:11.907147: Epoch 311 +2024-11-21 12:22:11.907263: Current learning rate: 0.00965 +2024-11-21 12:22:30.385780: train_loss -0.7571 +2024-11-21 12:22:30.386072: val_loss -0.7196 +2024-11-21 12:22:30.386156: Pseudo dice [0.8128] +2024-11-21 12:22:30.386236: Epoch time: 18.48 s +2024-11-21 12:22:31.178894: +2024-11-21 12:22:31.179097: Epoch 312 +2024-11-21 12:22:31.179213: Current learning rate: 0.00965 +2024-11-21 12:22:50.198421: train_loss -0.7522 +2024-11-21 12:22:50.198631: val_loss -0.7449 +2024-11-21 12:22:50.198706: Pseudo dice [0.8263] +2024-11-21 12:22:50.198781: Epoch time: 19.02 s +2024-11-21 12:22:50.986750: +2024-11-21 12:22:50.986936: Epoch 313 +2024-11-21 12:22:50.987063: Current learning rate: 0.00965 +2024-11-21 12:23:10.550669: train_loss -0.7532 +2024-11-21 12:23:10.550945: val_loss -0.7323 +2024-11-21 12:23:10.551029: Pseudo dice [0.8206] +2024-11-21 12:23:10.551120: Epoch time: 19.56 s +2024-11-21 12:23:11.392396: +2024-11-21 12:23:11.392595: Epoch 314 +2024-11-21 12:23:11.392709: Current learning rate: 0.00965 +2024-11-21 12:23:29.602072: train_loss -0.7581 +2024-11-21 12:23:29.602283: val_loss -0.7406 +2024-11-21 12:23:29.602360: Pseudo dice [0.8101] +2024-11-21 12:23:29.602437: Epoch time: 18.21 s +2024-11-21 12:23:30.407839: +2024-11-21 12:23:30.408033: Epoch 315 +2024-11-21 12:23:30.408147: Current learning rate: 0.00964 +2024-11-21 12:23:48.737335: train_loss -0.7544 +2024-11-21 12:23:48.737550: val_loss -0.74 +2024-11-21 12:23:48.737627: Pseudo dice [0.8275] +2024-11-21 12:23:48.739891: Epoch time: 18.33 s +2024-11-21 12:23:49.547762: +2024-11-21 12:23:49.547957: Epoch 316 +2024-11-21 12:23:49.548078: Current learning rate: 0.00964 +2024-11-21 12:24:08.436060: train_loss -0.7385 +2024-11-21 12:24:08.436281: val_loss -0.7089 +2024-11-21 12:24:08.436359: Pseudo dice [0.7938] +2024-11-21 12:24:08.436440: Epoch time: 18.89 s +2024-11-21 12:24:09.227408: +2024-11-21 12:24:09.227604: Epoch 317 +2024-11-21 12:24:09.227718: Current learning rate: 0.00964 +2024-11-21 12:24:27.528521: train_loss -0.7499 +2024-11-21 12:24:27.528771: val_loss -0.7275 +2024-11-21 12:24:27.528852: Pseudo dice [0.8191] +2024-11-21 12:24:27.528940: Epoch time: 18.3 s +2024-11-21 12:24:28.361477: +2024-11-21 12:24:28.361683: Epoch 318 +2024-11-21 12:24:28.361797: Current learning rate: 0.00964 +2024-11-21 12:24:46.164621: train_loss -0.756 +2024-11-21 12:24:46.164827: val_loss -0.7131 +2024-11-21 12:24:46.164904: Pseudo dice [0.8159] +2024-11-21 12:24:46.164980: Epoch time: 17.8 s +2024-11-21 12:24:47.368635: +2024-11-21 12:24:47.368855: Epoch 319 +2024-11-21 12:24:47.368972: Current learning rate: 0.00964 +2024-11-21 12:25:06.335893: train_loss -0.7525 +2024-11-21 12:25:06.336142: val_loss -0.7409 +2024-11-21 12:25:06.336218: Pseudo dice [0.8159] +2024-11-21 12:25:06.336298: Epoch time: 18.97 s +2024-11-21 12:25:07.126034: +2024-11-21 12:25:07.126287: Epoch 320 +2024-11-21 12:25:07.126403: Current learning rate: 0.00964 +2024-11-21 12:25:25.722162: train_loss -0.7489 +2024-11-21 12:25:25.724584: val_loss -0.7365 +2024-11-21 12:25:25.724706: Pseudo dice [0.8154] +2024-11-21 12:25:25.724818: Epoch time: 18.6 s +2024-11-21 12:25:26.592726: +2024-11-21 12:25:26.592945: Epoch 321 +2024-11-21 12:25:26.593067: Current learning rate: 0.00964 +2024-11-21 12:25:46.540833: train_loss -0.7552 +2024-11-21 12:25:46.541059: val_loss -0.7239 +2024-11-21 12:25:46.541135: Pseudo dice [0.7904] +2024-11-21 12:25:46.543463: Epoch time: 19.95 s +2024-11-21 12:25:47.349797: +2024-11-21 12:25:47.350008: Epoch 322 +2024-11-21 12:25:47.350127: Current learning rate: 0.00964 +2024-11-21 12:26:06.257973: train_loss -0.7591 +2024-11-21 12:26:06.258196: val_loss -0.7139 +2024-11-21 12:26:06.258269: Pseudo dice [0.7992] +2024-11-21 12:26:06.258345: Epoch time: 18.91 s +2024-11-21 12:26:07.051641: +2024-11-21 12:26:07.051830: Epoch 323 +2024-11-21 12:26:07.051943: Current learning rate: 0.00964 +2024-11-21 12:26:24.469705: train_loss -0.7614 +2024-11-21 12:26:24.469915: val_loss -0.7336 +2024-11-21 12:26:24.470038: Pseudo dice [0.8189] +2024-11-21 12:26:24.470117: Epoch time: 17.42 s +2024-11-21 12:26:25.264421: +2024-11-21 12:26:25.264610: Epoch 324 +2024-11-21 12:26:25.264720: Current learning rate: 0.00963 +2024-11-21 12:26:43.067828: train_loss -0.7575 +2024-11-21 12:26:43.068074: val_loss -0.7221 +2024-11-21 12:26:43.068153: Pseudo dice [0.8128] +2024-11-21 12:26:43.068248: Epoch time: 17.8 s +2024-11-21 12:26:43.863859: +2024-11-21 12:26:43.864048: Epoch 325 +2024-11-21 12:26:43.864161: Current learning rate: 0.00963 +2024-11-21 12:27:01.355502: train_loss -0.7489 +2024-11-21 12:27:01.355711: val_loss -0.7303 +2024-11-21 12:27:01.355786: Pseudo dice [0.8095] +2024-11-21 12:27:01.355860: Epoch time: 17.49 s +2024-11-21 12:27:02.166973: +2024-11-21 12:27:02.167183: Epoch 326 +2024-11-21 12:27:02.167299: Current learning rate: 0.00963 +2024-11-21 12:27:20.302753: train_loss -0.7261 +2024-11-21 12:27:20.302945: val_loss -0.714 +2024-11-21 12:27:20.303030: Pseudo dice [0.8083] +2024-11-21 12:27:20.303104: Epoch time: 18.14 s +2024-11-21 12:27:21.093574: +2024-11-21 12:27:21.093783: Epoch 327 +2024-11-21 12:27:21.093898: Current learning rate: 0.00963 +2024-11-21 12:27:38.910057: train_loss -0.737 +2024-11-21 12:27:38.910276: val_loss -0.7198 +2024-11-21 12:27:38.926013: Pseudo dice [0.8077] +2024-11-21 12:27:38.926149: Epoch time: 17.82 s +2024-11-21 12:27:39.719410: +2024-11-21 12:27:39.719609: Epoch 328 +2024-11-21 12:27:39.719721: Current learning rate: 0.00963 +2024-11-21 12:27:58.397642: train_loss -0.732 +2024-11-21 12:27:58.397887: val_loss -0.7068 +2024-11-21 12:27:58.397966: Pseudo dice [0.8245] +2024-11-21 12:27:58.398058: Epoch time: 18.68 s +2024-11-21 12:27:59.190823: +2024-11-21 12:27:59.191000: Epoch 329 +2024-11-21 12:27:59.191109: Current learning rate: 0.00963 +2024-11-21 12:28:18.535132: train_loss -0.741 +2024-11-21 12:28:18.535347: val_loss -0.7239 +2024-11-21 12:28:18.535423: Pseudo dice [0.7951] +2024-11-21 12:28:18.535500: Epoch time: 19.35 s +2024-11-21 12:28:19.323032: +2024-11-21 12:28:19.323236: Epoch 330 +2024-11-21 12:28:19.323360: Current learning rate: 0.00963 +2024-11-21 12:28:37.941032: train_loss -0.7423 +2024-11-21 12:28:37.941264: val_loss -0.741 +2024-11-21 12:28:37.941341: Pseudo dice [0.8244] +2024-11-21 12:28:37.941417: Epoch time: 18.62 s +2024-11-21 12:28:38.741176: +2024-11-21 12:28:38.741416: Epoch 331 +2024-11-21 12:28:38.741538: Current learning rate: 0.00963 +2024-11-21 12:28:56.693890: train_loss -0.7555 +2024-11-21 12:28:56.694203: val_loss -0.7474 +2024-11-21 12:28:56.694291: Pseudo dice [0.8391] +2024-11-21 12:28:56.694377: Epoch time: 17.95 s +2024-11-21 12:28:57.537504: +2024-11-21 12:28:57.537714: Epoch 332 +2024-11-21 12:28:57.537828: Current learning rate: 0.00963 +2024-11-21 12:29:15.430134: train_loss -0.7521 +2024-11-21 12:29:15.430343: val_loss -0.7079 +2024-11-21 12:29:15.430445: Pseudo dice [0.8013] +2024-11-21 12:29:15.430523: Epoch time: 17.89 s +2024-11-21 12:29:16.220547: +2024-11-21 12:29:16.220837: Epoch 333 +2024-11-21 12:29:16.220958: Current learning rate: 0.00962 +2024-11-21 12:29:35.668089: train_loss -0.7496 +2024-11-21 12:29:35.668295: val_loss -0.7122 +2024-11-21 12:29:35.668368: Pseudo dice [0.7806] +2024-11-21 12:29:35.668444: Epoch time: 19.45 s +2024-11-21 12:29:36.453924: +2024-11-21 12:29:36.454124: Epoch 334 +2024-11-21 12:29:36.454238: Current learning rate: 0.00962 +2024-11-21 12:29:56.105269: train_loss -0.7479 +2024-11-21 12:29:56.105533: val_loss -0.7117 +2024-11-21 12:29:56.105611: Pseudo dice [0.8148] +2024-11-21 12:29:56.105695: Epoch time: 19.65 s +2024-11-21 12:29:56.915443: +2024-11-21 12:29:56.915641: Epoch 335 +2024-11-21 12:29:56.915752: Current learning rate: 0.00962 +2024-11-21 12:30:16.322021: train_loss -0.7491 +2024-11-21 12:30:16.322204: val_loss -0.7039 +2024-11-21 12:30:16.322272: Pseudo dice [0.7916] +2024-11-21 12:30:16.322347: Epoch time: 19.41 s +2024-11-21 12:30:17.150484: +2024-11-21 12:30:17.150678: Epoch 336 +2024-11-21 12:30:17.150790: Current learning rate: 0.00962 +2024-11-21 12:30:36.175613: train_loss -0.7522 +2024-11-21 12:30:36.175911: val_loss -0.7431 +2024-11-21 12:30:36.175997: Pseudo dice [0.8146] +2024-11-21 12:30:36.176074: Epoch time: 19.03 s +2024-11-21 12:30:36.965782: +2024-11-21 12:30:36.965982: Epoch 337 +2024-11-21 12:30:36.966097: Current learning rate: 0.00962 +2024-11-21 12:30:55.469342: train_loss -0.7375 +2024-11-21 12:30:55.469545: val_loss -0.7174 +2024-11-21 12:30:55.469620: Pseudo dice [0.8108] +2024-11-21 12:30:55.471900: Epoch time: 18.5 s +2024-11-21 12:30:56.363141: +2024-11-21 12:30:56.363371: Epoch 338 +2024-11-21 12:30:56.363490: Current learning rate: 0.00962 +2024-11-21 12:31:15.314332: train_loss -0.7537 +2024-11-21 12:31:15.314574: val_loss -0.7295 +2024-11-21 12:31:15.314648: Pseudo dice [0.8072] +2024-11-21 12:31:15.314731: Epoch time: 18.95 s +2024-11-21 12:31:16.239748: +2024-11-21 12:31:16.239940: Epoch 339 +2024-11-21 12:31:16.240058: Current learning rate: 0.00962 +2024-11-21 12:31:34.208892: train_loss -0.7463 +2024-11-21 12:31:34.209093: val_loss -0.7332 +2024-11-21 12:31:34.209168: Pseudo dice [0.8042] +2024-11-21 12:31:34.209242: Epoch time: 17.97 s +2024-11-21 12:31:35.010967: +2024-11-21 12:31:35.011163: Epoch 340 +2024-11-21 12:31:35.011276: Current learning rate: 0.00962 +2024-11-21 12:31:52.864987: train_loss -0.7538 +2024-11-21 12:31:52.870396: val_loss -0.7446 +2024-11-21 12:31:52.870513: Pseudo dice [0.8287] +2024-11-21 12:31:52.870604: Epoch time: 17.85 s +2024-11-21 12:31:53.730545: +2024-11-21 12:31:53.730745: Epoch 341 +2024-11-21 12:31:53.730867: Current learning rate: 0.00962 +2024-11-21 12:32:12.873607: train_loss -0.7616 +2024-11-21 12:32:12.873819: val_loss -0.7416 +2024-11-21 12:32:12.873894: Pseudo dice [0.8309] +2024-11-21 12:32:12.873972: Epoch time: 19.14 s +2024-11-21 12:32:14.020737: +2024-11-21 12:32:14.020936: Epoch 342 +2024-11-21 12:32:14.021053: Current learning rate: 0.00961 +2024-11-21 12:32:32.194601: train_loss -0.7613 +2024-11-21 12:32:32.194844: val_loss -0.7437 +2024-11-21 12:32:32.194918: Pseudo dice [0.837] +2024-11-21 12:32:32.195008: Epoch time: 18.17 s +2024-11-21 12:32:33.146237: +2024-11-21 12:32:33.146440: Epoch 343 +2024-11-21 12:32:33.146559: Current learning rate: 0.00961 +2024-11-21 12:32:51.868385: train_loss -0.75 +2024-11-21 12:32:51.868599: val_loss -0.6939 +2024-11-21 12:32:51.868680: Pseudo dice [0.8029] +2024-11-21 12:32:51.868758: Epoch time: 18.72 s +2024-11-21 12:32:52.665176: +2024-11-21 12:32:52.665384: Epoch 344 +2024-11-21 12:32:52.665498: Current learning rate: 0.00961 +2024-11-21 12:33:11.690135: train_loss -0.7419 +2024-11-21 12:33:11.690336: val_loss -0.7419 +2024-11-21 12:33:11.690417: Pseudo dice [0.8291] +2024-11-21 12:33:11.690492: Epoch time: 19.03 s +2024-11-21 12:33:12.480396: +2024-11-21 12:33:12.480586: Epoch 345 +2024-11-21 12:33:12.480699: Current learning rate: 0.00961 +2024-11-21 12:33:31.709655: train_loss -0.761 +2024-11-21 12:33:31.709902: val_loss -0.7466 +2024-11-21 12:33:31.709978: Pseudo dice [0.8129] +2024-11-21 12:33:31.710105: Epoch time: 19.23 s +2024-11-21 12:33:32.533448: +2024-11-21 12:33:32.533625: Epoch 346 +2024-11-21 12:33:32.533732: Current learning rate: 0.00961 +2024-11-21 12:33:50.858584: train_loss -0.7523 +2024-11-21 12:33:50.858795: val_loss -0.7363 +2024-11-21 12:33:50.858868: Pseudo dice [0.819] +2024-11-21 12:33:50.858944: Epoch time: 18.33 s +2024-11-21 12:33:51.658938: +2024-11-21 12:33:51.659143: Epoch 347 +2024-11-21 12:33:51.659253: Current learning rate: 0.00961 +2024-11-21 12:34:10.896591: train_loss -0.7499 +2024-11-21 12:34:10.896797: val_loss -0.74 +2024-11-21 12:34:10.896877: Pseudo dice [0.8147] +2024-11-21 12:34:10.896954: Epoch time: 19.24 s +2024-11-21 12:34:11.697668: +2024-11-21 12:34:11.697879: Epoch 348 +2024-11-21 12:34:11.697995: Current learning rate: 0.00961 +2024-11-21 12:34:31.452338: train_loss -0.7511 +2024-11-21 12:34:31.452548: val_loss -0.706 +2024-11-21 12:34:31.452620: Pseudo dice [0.7917] +2024-11-21 12:34:31.452696: Epoch time: 19.76 s +2024-11-21 12:34:32.254175: +2024-11-21 12:34:32.254393: Epoch 349 +2024-11-21 12:34:32.254515: Current learning rate: 0.00961 +2024-11-21 12:34:51.533091: train_loss -0.735 +2024-11-21 12:34:51.533327: val_loss -0.7025 +2024-11-21 12:34:51.533402: Pseudo dice [0.7922] +2024-11-21 12:34:51.533485: Epoch time: 19.28 s +2024-11-21 12:34:52.545885: +2024-11-21 12:34:52.546132: Epoch 350 +2024-11-21 12:34:52.546247: Current learning rate: 0.00961 +2024-11-21 12:35:11.342561: train_loss -0.7519 +2024-11-21 12:35:11.342848: val_loss -0.7194 +2024-11-21 12:35:11.342930: Pseudo dice [0.822] +2024-11-21 12:35:11.343017: Epoch time: 18.8 s +2024-11-21 12:35:12.250097: +2024-11-21 12:35:12.250299: Epoch 351 +2024-11-21 12:35:12.250422: Current learning rate: 0.0096 +2024-11-21 12:35:30.417933: train_loss -0.734 +2024-11-21 12:35:30.418139: val_loss -0.7194 +2024-11-21 12:35:30.418216: Pseudo dice [0.7993] +2024-11-21 12:35:30.418293: Epoch time: 18.17 s +2024-11-21 12:35:31.202055: +2024-11-21 12:35:31.202258: Epoch 352 +2024-11-21 12:35:31.202371: Current learning rate: 0.0096 +2024-11-21 12:35:50.157514: train_loss -0.7396 +2024-11-21 12:35:50.157717: val_loss -0.7219 +2024-11-21 12:35:50.157793: Pseudo dice [0.7874] +2024-11-21 12:35:50.157872: Epoch time: 18.96 s +2024-11-21 12:35:51.366205: +2024-11-21 12:35:51.366444: Epoch 353 +2024-11-21 12:35:51.366559: Current learning rate: 0.0096 +2024-11-21 12:36:10.382056: train_loss -0.7334 +2024-11-21 12:36:10.382279: val_loss -0.7421 +2024-11-21 12:36:10.382355: Pseudo dice [0.8325] +2024-11-21 12:36:10.382434: Epoch time: 19.02 s +2024-11-21 12:36:11.184576: +2024-11-21 12:36:11.184871: Epoch 354 +2024-11-21 12:36:11.184986: Current learning rate: 0.0096 +2024-11-21 12:36:30.694831: train_loss -0.7341 +2024-11-21 12:36:30.695044: val_loss -0.7339 +2024-11-21 12:36:30.695168: Pseudo dice [0.8179] +2024-11-21 12:36:30.695278: Epoch time: 19.51 s +2024-11-21 12:36:31.495045: +2024-11-21 12:36:31.495376: Epoch 355 +2024-11-21 12:36:31.495497: Current learning rate: 0.0096 +2024-11-21 12:36:50.543958: train_loss -0.745 +2024-11-21 12:36:50.544170: val_loss -0.7188 +2024-11-21 12:36:50.544245: Pseudo dice [0.7827] +2024-11-21 12:36:50.549503: Epoch time: 19.05 s +2024-11-21 12:36:51.367985: +2024-11-21 12:36:51.368238: Epoch 356 +2024-11-21 12:36:51.368356: Current learning rate: 0.0096 +2024-11-21 12:37:11.003583: train_loss -0.75 +2024-11-21 12:37:11.003821: val_loss -0.7182 +2024-11-21 12:37:11.003899: Pseudo dice [0.8208] +2024-11-21 12:37:11.003986: Epoch time: 19.64 s +2024-11-21 12:37:11.809702: +2024-11-21 12:37:11.809981: Epoch 357 +2024-11-21 12:37:11.810102: Current learning rate: 0.0096 +2024-11-21 12:37:32.075867: train_loss -0.7497 +2024-11-21 12:37:32.076083: val_loss -0.7324 +2024-11-21 12:37:32.076158: Pseudo dice [0.8218] +2024-11-21 12:37:32.076235: Epoch time: 20.27 s +2024-11-21 12:37:32.883844: +2024-11-21 12:37:32.884035: Epoch 358 +2024-11-21 12:37:32.884178: Current learning rate: 0.0096 +2024-11-21 12:37:51.905941: train_loss -0.746 +2024-11-21 12:37:51.906164: val_loss -0.7204 +2024-11-21 12:37:51.906245: Pseudo dice [0.8055] +2024-11-21 12:37:51.906319: Epoch time: 19.02 s +2024-11-21 12:37:52.713895: +2024-11-21 12:37:52.714079: Epoch 359 +2024-11-21 12:37:52.714190: Current learning rate: 0.0096 +2024-11-21 12:38:11.530435: train_loss -0.76 +2024-11-21 12:38:11.530645: val_loss -0.7233 +2024-11-21 12:38:11.530720: Pseudo dice [0.8175] +2024-11-21 12:38:11.530797: Epoch time: 18.82 s +2024-11-21 12:38:12.330295: +2024-11-21 12:38:12.330479: Epoch 360 +2024-11-21 12:38:12.330589: Current learning rate: 0.00959 +2024-11-21 12:38:31.732088: train_loss -0.7573 +2024-11-21 12:38:31.732383: val_loss -0.7274 +2024-11-21 12:38:31.732460: Pseudo dice [0.7917] +2024-11-21 12:38:31.732544: Epoch time: 19.4 s +2024-11-21 12:38:32.545365: +2024-11-21 12:38:32.545543: Epoch 361 +2024-11-21 12:38:32.545655: Current learning rate: 0.00959 +2024-11-21 12:38:50.096001: train_loss -0.7456 +2024-11-21 12:38:50.096212: val_loss -0.6989 +2024-11-21 12:38:50.096288: Pseudo dice [0.8111] +2024-11-21 12:38:50.096368: Epoch time: 17.55 s +2024-11-21 12:38:50.901864: +2024-11-21 12:38:50.902068: Epoch 362 +2024-11-21 12:38:50.902185: Current learning rate: 0.00959 +2024-11-21 12:39:08.568987: train_loss -0.7574 +2024-11-21 12:39:08.569216: val_loss -0.7228 +2024-11-21 12:39:08.569290: Pseudo dice [0.8158] +2024-11-21 12:39:08.569367: Epoch time: 17.67 s +2024-11-21 12:39:09.372819: +2024-11-21 12:39:09.373065: Epoch 363 +2024-11-21 12:39:09.373175: Current learning rate: 0.00959 +2024-11-21 12:39:28.505356: train_loss -0.7508 +2024-11-21 12:39:28.505569: val_loss -0.7313 +2024-11-21 12:39:28.505653: Pseudo dice [0.8192] +2024-11-21 12:39:28.505732: Epoch time: 19.13 s +2024-11-21 12:39:29.355605: +2024-11-21 12:39:29.355791: Epoch 364 +2024-11-21 12:39:29.355908: Current learning rate: 0.00959 +2024-11-21 12:39:47.231724: train_loss -0.7533 +2024-11-21 12:39:47.233584: val_loss -0.7245 +2024-11-21 12:39:47.233664: Pseudo dice [0.8239] +2024-11-21 12:39:47.233743: Epoch time: 17.88 s +2024-11-21 12:39:48.063272: +2024-11-21 12:39:48.063553: Epoch 365 +2024-11-21 12:39:48.063662: Current learning rate: 0.00959 +2024-11-21 12:40:06.474019: train_loss -0.7464 +2024-11-21 12:40:06.474246: val_loss -0.7101 +2024-11-21 12:40:06.474323: Pseudo dice [0.8035] +2024-11-21 12:40:06.474401: Epoch time: 18.41 s +2024-11-21 12:40:07.269671: +2024-11-21 12:40:07.269892: Epoch 366 +2024-11-21 12:40:07.270008: Current learning rate: 0.00959 +2024-11-21 12:40:25.939257: train_loss -0.7394 +2024-11-21 12:40:25.939539: val_loss -0.7319 +2024-11-21 12:40:25.939615: Pseudo dice [0.8222] +2024-11-21 12:40:25.939695: Epoch time: 18.67 s +2024-11-21 12:40:26.831098: +2024-11-21 12:40:26.831314: Epoch 367 +2024-11-21 12:40:26.831428: Current learning rate: 0.00959 +2024-11-21 12:40:46.197232: train_loss -0.7503 +2024-11-21 12:40:46.197546: val_loss -0.7336 +2024-11-21 12:40:46.197624: Pseudo dice [0.8202] +2024-11-21 12:40:46.197707: Epoch time: 19.37 s +2024-11-21 12:40:46.995446: +2024-11-21 12:40:46.995647: Epoch 368 +2024-11-21 12:40:46.995758: Current learning rate: 0.00959 +2024-11-21 12:41:06.016546: train_loss -0.741 +2024-11-21 12:41:06.016752: val_loss -0.7413 +2024-11-21 12:41:06.016826: Pseudo dice [0.8302] +2024-11-21 12:41:06.016902: Epoch time: 19.02 s +2024-11-21 12:41:06.926215: +2024-11-21 12:41:06.926397: Epoch 369 +2024-11-21 12:41:06.926507: Current learning rate: 0.00958 +2024-11-21 12:41:25.420038: train_loss -0.7582 +2024-11-21 12:41:25.420247: val_loss -0.7404 +2024-11-21 12:41:25.420322: Pseudo dice [0.8228] +2024-11-21 12:41:25.420398: Epoch time: 18.49 s +2024-11-21 12:41:26.215213: +2024-11-21 12:41:26.215401: Epoch 370 +2024-11-21 12:41:26.215511: Current learning rate: 0.00958 +2024-11-21 12:41:44.489936: train_loss -0.7612 +2024-11-21 12:41:44.490162: val_loss -0.7162 +2024-11-21 12:41:44.490243: Pseudo dice [0.8142] +2024-11-21 12:41:44.490324: Epoch time: 18.28 s +2024-11-21 12:41:45.289171: +2024-11-21 12:41:45.289404: Epoch 371 +2024-11-21 12:41:45.289518: Current learning rate: 0.00958 +2024-11-21 12:42:03.617604: train_loss -0.7594 +2024-11-21 12:42:03.617822: val_loss -0.7239 +2024-11-21 12:42:03.617896: Pseudo dice [0.802] +2024-11-21 12:42:03.617976: Epoch time: 18.33 s +2024-11-21 12:42:04.422853: +2024-11-21 12:42:04.423045: Epoch 372 +2024-11-21 12:42:04.423159: Current learning rate: 0.00958 +2024-11-21 12:42:23.624197: train_loss -0.7513 +2024-11-21 12:42:23.624425: val_loss -0.7177 +2024-11-21 12:42:23.624510: Pseudo dice [0.8204] +2024-11-21 12:42:23.624586: Epoch time: 19.2 s +2024-11-21 12:42:24.419185: +2024-11-21 12:42:24.419371: Epoch 373 +2024-11-21 12:42:24.419481: Current learning rate: 0.00958 +2024-11-21 12:42:42.428558: train_loss -0.7547 +2024-11-21 12:42:42.428760: val_loss -0.6954 +2024-11-21 12:42:42.428834: Pseudo dice [0.8008] +2024-11-21 12:42:42.428908: Epoch time: 18.01 s +2024-11-21 12:42:43.238797: +2024-11-21 12:42:43.239010: Epoch 374 +2024-11-21 12:42:43.239123: Current learning rate: 0.00958 +2024-11-21 12:43:01.393742: train_loss -0.7544 +2024-11-21 12:43:01.393975: val_loss -0.7079 +2024-11-21 12:43:01.394059: Pseudo dice [0.7983] +2024-11-21 12:43:01.394145: Epoch time: 18.16 s +2024-11-21 12:43:02.213221: +2024-11-21 12:43:02.213437: Epoch 375 +2024-11-21 12:43:02.213555: Current learning rate: 0.00958 +2024-11-21 12:43:21.333591: train_loss -0.7533 +2024-11-21 12:43:21.333804: val_loss -0.7091 +2024-11-21 12:43:21.333880: Pseudo dice [0.8196] +2024-11-21 12:43:21.333956: Epoch time: 19.12 s +2024-11-21 12:43:22.656281: +2024-11-21 12:43:22.656502: Epoch 376 +2024-11-21 12:43:22.656618: Current learning rate: 0.00958 +2024-11-21 12:43:41.857465: train_loss -0.7484 +2024-11-21 12:43:41.857695: val_loss -0.715 +2024-11-21 12:43:41.857770: Pseudo dice [0.8062] +2024-11-21 12:43:41.857848: Epoch time: 19.2 s +2024-11-21 12:43:42.652297: +2024-11-21 12:43:42.652610: Epoch 377 +2024-11-21 12:43:42.652726: Current learning rate: 0.00957 +2024-11-21 12:44:01.821128: train_loss -0.7632 +2024-11-21 12:44:01.821367: val_loss -0.6996 +2024-11-21 12:44:01.821445: Pseudo dice [0.7827] +2024-11-21 12:44:01.821534: Epoch time: 19.17 s +2024-11-21 12:44:02.621037: +2024-11-21 12:44:02.621346: Epoch 378 +2024-11-21 12:44:02.621465: Current learning rate: 0.00957 +2024-11-21 12:44:20.515367: train_loss -0.7463 +2024-11-21 12:44:20.515571: val_loss -0.7279 +2024-11-21 12:44:20.515644: Pseudo dice [0.8056] +2024-11-21 12:44:20.515722: Epoch time: 17.9 s +2024-11-21 12:44:21.313359: +2024-11-21 12:44:21.313550: Epoch 379 +2024-11-21 12:44:21.313660: Current learning rate: 0.00957 +2024-11-21 12:44:40.272403: train_loss -0.7635 +2024-11-21 12:44:40.272616: val_loss -0.7192 +2024-11-21 12:44:40.272693: Pseudo dice [0.8246] +2024-11-21 12:44:40.272770: Epoch time: 18.96 s +2024-11-21 12:44:41.079703: +2024-11-21 12:44:41.079898: Epoch 380 +2024-11-21 12:44:41.080020: Current learning rate: 0.00957 +2024-11-21 12:44:59.026799: train_loss -0.7673 +2024-11-21 12:44:59.027019: val_loss -0.725 +2024-11-21 12:44:59.027094: Pseudo dice [0.8309] +2024-11-21 12:44:59.027172: Epoch time: 17.95 s +2024-11-21 12:44:59.907919: +2024-11-21 12:44:59.908173: Epoch 381 +2024-11-21 12:44:59.908288: Current learning rate: 0.00957 +2024-11-21 12:45:17.551444: train_loss -0.7702 +2024-11-21 12:45:17.553493: val_loss -0.7367 +2024-11-21 12:45:17.553594: Pseudo dice [0.8033] +2024-11-21 12:45:17.553685: Epoch time: 17.64 s +2024-11-21 12:45:18.358074: +2024-11-21 12:45:18.358263: Epoch 382 +2024-11-21 12:45:18.358379: Current learning rate: 0.00957 +2024-11-21 12:45:36.530146: train_loss -0.7542 +2024-11-21 12:45:36.530353: val_loss -0.7356 +2024-11-21 12:45:36.530426: Pseudo dice [0.8235] +2024-11-21 12:45:36.530500: Epoch time: 18.17 s +2024-11-21 12:45:37.339579: +2024-11-21 12:45:37.339819: Epoch 383 +2024-11-21 12:45:37.339935: Current learning rate: 0.00957 +2024-11-21 12:45:56.258271: train_loss -0.7601 +2024-11-21 12:45:56.258487: val_loss -0.7223 +2024-11-21 12:45:56.258562: Pseudo dice [0.8381] +2024-11-21 12:45:56.258650: Epoch time: 18.92 s +2024-11-21 12:45:57.056573: +2024-11-21 12:45:57.056792: Epoch 384 +2024-11-21 12:45:57.056905: Current learning rate: 0.00957 +2024-11-21 12:46:15.755231: train_loss -0.7615 +2024-11-21 12:46:15.755435: val_loss -0.7465 +2024-11-21 12:46:15.755510: Pseudo dice [0.8277] +2024-11-21 12:46:15.755642: Epoch time: 18.7 s +2024-11-21 12:46:16.545998: +2024-11-21 12:46:16.546189: Epoch 385 +2024-11-21 12:46:16.546301: Current learning rate: 0.00957 +2024-11-21 12:46:33.947143: train_loss -0.7539 +2024-11-21 12:46:33.947375: val_loss -0.7388 +2024-11-21 12:46:33.947448: Pseudo dice [0.811] +2024-11-21 12:46:33.947530: Epoch time: 17.4 s +2024-11-21 12:46:34.757878: +2024-11-21 12:46:34.758230: Epoch 386 +2024-11-21 12:46:34.758346: Current learning rate: 0.00956 +2024-11-21 12:46:53.639487: train_loss -0.7549 +2024-11-21 12:46:53.639692: val_loss -0.7209 +2024-11-21 12:46:53.639764: Pseudo dice [0.8218] +2024-11-21 12:46:53.639839: Epoch time: 18.88 s +2024-11-21 12:46:54.864409: +2024-11-21 12:46:54.864596: Epoch 387 +2024-11-21 12:46:54.864692: Current learning rate: 0.00956 +2024-11-21 12:47:13.475327: train_loss -0.7516 +2024-11-21 12:47:13.475560: val_loss -0.7009 +2024-11-21 12:47:13.475637: Pseudo dice [0.7955] +2024-11-21 12:47:13.475719: Epoch time: 18.61 s +2024-11-21 12:47:14.280129: +2024-11-21 12:47:14.280360: Epoch 388 +2024-11-21 12:47:14.280472: Current learning rate: 0.00956 +2024-11-21 12:47:33.482136: train_loss -0.7461 +2024-11-21 12:47:33.482382: val_loss -0.7345 +2024-11-21 12:47:33.482464: Pseudo dice [0.8211] +2024-11-21 12:47:33.482585: Epoch time: 19.2 s +2024-11-21 12:47:34.282548: +2024-11-21 12:47:34.282759: Epoch 389 +2024-11-21 12:47:34.282867: Current learning rate: 0.00956 +2024-11-21 12:47:53.362987: train_loss -0.7623 +2024-11-21 12:47:53.363182: val_loss -0.7046 +2024-11-21 12:47:53.363261: Pseudo dice [0.8149] +2024-11-21 12:47:53.363334: Epoch time: 19.08 s +2024-11-21 12:47:54.166885: +2024-11-21 12:47:54.167148: Epoch 390 +2024-11-21 12:47:54.167263: Current learning rate: 0.00956 +2024-11-21 12:48:12.338222: train_loss -0.76 +2024-11-21 12:48:12.338436: val_loss -0.738 +2024-11-21 12:48:12.338516: Pseudo dice [0.8304] +2024-11-21 12:48:12.338595: Epoch time: 18.17 s +2024-11-21 12:48:13.209538: +2024-11-21 12:48:13.209775: Epoch 391 +2024-11-21 12:48:13.209891: Current learning rate: 0.00956 +2024-11-21 12:48:31.931130: train_loss -0.7551 +2024-11-21 12:48:31.931344: val_loss -0.731 +2024-11-21 12:48:31.931419: Pseudo dice [0.814] +2024-11-21 12:48:31.931500: Epoch time: 18.72 s +2024-11-21 12:48:32.735900: +2024-11-21 12:48:32.736104: Epoch 392 +2024-11-21 12:48:32.736215: Current learning rate: 0.00956 +2024-11-21 12:48:52.291014: train_loss -0.7628 +2024-11-21 12:48:52.291250: val_loss -0.7452 +2024-11-21 12:48:52.291396: Pseudo dice [0.8122] +2024-11-21 12:48:52.291488: Epoch time: 19.56 s +2024-11-21 12:48:53.099433: +2024-11-21 12:48:53.099713: Epoch 393 +2024-11-21 12:48:53.099824: Current learning rate: 0.00956 +2024-11-21 12:49:10.825513: train_loss -0.7484 +2024-11-21 12:49:10.825722: val_loss -0.718 +2024-11-21 12:49:10.825796: Pseudo dice [0.8203] +2024-11-21 12:49:10.825873: Epoch time: 17.73 s +2024-11-21 12:49:11.624347: +2024-11-21 12:49:11.624550: Epoch 394 +2024-11-21 12:49:11.624659: Current learning rate: 0.00956 +2024-11-21 12:49:29.611025: train_loss -0.7526 +2024-11-21 12:49:29.611233: val_loss -0.7291 +2024-11-21 12:49:29.611305: Pseudo dice [0.8102] +2024-11-21 12:49:29.611379: Epoch time: 17.99 s +2024-11-21 12:49:30.560876: +2024-11-21 12:49:30.561071: Epoch 395 +2024-11-21 12:49:30.561185: Current learning rate: 0.00955 +2024-11-21 12:49:48.898884: train_loss -0.75 +2024-11-21 12:49:48.899163: val_loss -0.7372 +2024-11-21 12:49:48.899247: Pseudo dice [0.7836] +2024-11-21 12:49:48.899326: Epoch time: 18.34 s +2024-11-21 12:49:49.703440: +2024-11-21 12:49:49.703617: Epoch 396 +2024-11-21 12:49:49.703732: Current learning rate: 0.00955 +2024-11-21 12:50:08.332845: train_loss -0.7606 +2024-11-21 12:50:08.333110: val_loss -0.7382 +2024-11-21 12:50:08.333245: Pseudo dice [0.8175] +2024-11-21 12:50:08.333330: Epoch time: 18.63 s +2024-11-21 12:50:09.155645: +2024-11-21 12:50:09.155898: Epoch 397 +2024-11-21 12:50:09.156021: Current learning rate: 0.00955 +2024-11-21 12:50:26.986550: train_loss -0.7406 +2024-11-21 12:50:26.986761: val_loss -0.7185 +2024-11-21 12:50:26.986835: Pseudo dice [0.8133] +2024-11-21 12:50:26.986912: Epoch time: 17.83 s +2024-11-21 12:50:27.862977: +2024-11-21 12:50:27.863158: Epoch 398 +2024-11-21 12:50:27.863268: Current learning rate: 0.00955 +2024-11-21 12:50:46.840874: train_loss -0.731 +2024-11-21 12:50:46.841091: val_loss -0.7341 +2024-11-21 12:50:46.841184: Pseudo dice [0.8075] +2024-11-21 12:50:46.841261: Epoch time: 18.98 s +2024-11-21 12:50:48.046615: +2024-11-21 12:50:48.046842: Epoch 399 +2024-11-21 12:50:48.046966: Current learning rate: 0.00955 +2024-11-21 12:51:05.610174: train_loss -0.7585 +2024-11-21 12:51:05.610429: val_loss -0.7125 +2024-11-21 12:51:05.610523: Pseudo dice [0.8066] +2024-11-21 12:51:05.610610: Epoch time: 17.56 s +2024-11-21 12:51:06.828911: +2024-11-21 12:51:06.829113: Epoch 400 +2024-11-21 12:51:06.829223: Current learning rate: 0.00955 +2024-11-21 12:51:25.467519: train_loss -0.7508 +2024-11-21 12:51:25.467721: val_loss -0.7119 +2024-11-21 12:51:25.467795: Pseudo dice [0.8395] +2024-11-21 12:51:25.467871: Epoch time: 18.64 s +2024-11-21 12:51:26.312886: +2024-11-21 12:51:26.313100: Epoch 401 +2024-11-21 12:51:26.313215: Current learning rate: 0.00955 +2024-11-21 12:51:43.984835: train_loss -0.7503 +2024-11-21 12:51:43.990276: val_loss -0.7232 +2024-11-21 12:51:43.990400: Pseudo dice [0.8111] +2024-11-21 12:51:43.990502: Epoch time: 17.67 s +2024-11-21 12:51:44.936857: +2024-11-21 12:51:44.937087: Epoch 402 +2024-11-21 12:51:44.937203: Current learning rate: 0.00955 +2024-11-21 12:52:03.754931: train_loss -0.7655 +2024-11-21 12:52:03.755183: val_loss -0.7188 +2024-11-21 12:52:03.760421: Pseudo dice [0.8055] +2024-11-21 12:52:03.760605: Epoch time: 18.82 s +2024-11-21 12:52:04.590079: +2024-11-21 12:52:04.590271: Epoch 403 +2024-11-21 12:52:04.590383: Current learning rate: 0.00955 +2024-11-21 12:52:23.445900: train_loss -0.7579 +2024-11-21 12:52:23.446108: val_loss -0.74 +2024-11-21 12:52:23.446180: Pseudo dice [0.8242] +2024-11-21 12:52:23.446258: Epoch time: 18.86 s +2024-11-21 12:52:24.256550: +2024-11-21 12:52:24.256778: Epoch 404 +2024-11-21 12:52:24.256895: Current learning rate: 0.00954 +2024-11-21 12:52:42.542162: train_loss -0.7531 +2024-11-21 12:52:42.542379: val_loss -0.7262 +2024-11-21 12:52:42.542456: Pseudo dice [0.8142] +2024-11-21 12:52:42.542533: Epoch time: 18.29 s +2024-11-21 12:52:43.348971: +2024-11-21 12:52:43.349282: Epoch 405 +2024-11-21 12:52:43.349396: Current learning rate: 0.00954 +2024-11-21 12:53:01.843525: train_loss -0.7478 +2024-11-21 12:53:01.843740: val_loss -0.7285 +2024-11-21 12:53:01.843815: Pseudo dice [0.8128] +2024-11-21 12:53:01.843918: Epoch time: 18.5 s +2024-11-21 12:53:02.660788: +2024-11-21 12:53:02.661054: Epoch 406 +2024-11-21 12:53:02.661177: Current learning rate: 0.00954 +2024-11-21 12:53:21.266141: train_loss -0.7559 +2024-11-21 12:53:21.266378: val_loss -0.734 +2024-11-21 12:53:21.266452: Pseudo dice [0.8195] +2024-11-21 12:53:21.266534: Epoch time: 18.61 s +2024-11-21 12:53:22.074650: +2024-11-21 12:53:22.074861: Epoch 407 +2024-11-21 12:53:22.074969: Current learning rate: 0.00954 +2024-11-21 12:53:40.778594: train_loss -0.7462 +2024-11-21 12:53:40.778822: val_loss -0.7334 +2024-11-21 12:53:40.778899: Pseudo dice [0.8235] +2024-11-21 12:53:40.778979: Epoch time: 18.7 s +2024-11-21 12:53:41.591522: +2024-11-21 12:53:41.591697: Epoch 408 +2024-11-21 12:53:41.591815: Current learning rate: 0.00954 +2024-11-21 12:54:01.055707: train_loss -0.7701 +2024-11-21 12:54:01.055920: val_loss -0.7365 +2024-11-21 12:54:01.056067: Pseudo dice [0.8261] +2024-11-21 12:54:01.056176: Epoch time: 19.47 s +2024-11-21 12:54:01.859361: +2024-11-21 12:54:01.859560: Epoch 409 +2024-11-21 12:54:01.859665: Current learning rate: 0.00954 +2024-11-21 12:54:21.028637: train_loss -0.7613 +2024-11-21 12:54:21.028848: val_loss -0.7302 +2024-11-21 12:54:21.028923: Pseudo dice [0.8218] +2024-11-21 12:54:21.029011: Epoch time: 19.17 s +2024-11-21 12:54:22.180948: +2024-11-21 12:54:22.181226: Epoch 410 +2024-11-21 12:54:22.181340: Current learning rate: 0.00954 +2024-11-21 12:54:40.398001: train_loss -0.7451 +2024-11-21 12:54:40.398311: val_loss -0.7389 +2024-11-21 12:54:40.398393: Pseudo dice [0.8201] +2024-11-21 12:54:40.398474: Epoch time: 18.22 s +2024-11-21 12:54:41.167330: +2024-11-21 12:54:41.167538: Epoch 411 +2024-11-21 12:54:41.167653: Current learning rate: 0.00954 +2024-11-21 12:54:59.878331: train_loss -0.7568 +2024-11-21 12:54:59.878570: val_loss -0.7413 +2024-11-21 12:54:59.878645: Pseudo dice [0.816] +2024-11-21 12:54:59.878721: Epoch time: 18.71 s +2024-11-21 12:55:00.654315: +2024-11-21 12:55:00.654518: Epoch 412 +2024-11-21 12:55:00.654631: Current learning rate: 0.00954 +2024-11-21 12:55:19.122699: train_loss -0.7445 +2024-11-21 12:55:19.122909: val_loss -0.747 +2024-11-21 12:55:19.122981: Pseudo dice [0.8215] +2024-11-21 12:55:19.123068: Epoch time: 18.47 s +2024-11-21 12:55:19.961854: +2024-11-21 12:55:19.962074: Epoch 413 +2024-11-21 12:55:19.962189: Current learning rate: 0.00953 +2024-11-21 12:55:38.315339: train_loss -0.7416 +2024-11-21 12:55:38.315547: val_loss -0.7525 +2024-11-21 12:55:38.317793: Pseudo dice [0.7964] +2024-11-21 12:55:38.317979: Epoch time: 18.35 s +2024-11-21 12:55:39.148159: +2024-11-21 12:55:39.148449: Epoch 414 +2024-11-21 12:55:39.148564: Current learning rate: 0.00953 +2024-11-21 12:55:57.187507: train_loss -0.7448 +2024-11-21 12:55:57.187785: val_loss -0.7254 +2024-11-21 12:55:57.187861: Pseudo dice [0.8088] +2024-11-21 12:55:57.187940: Epoch time: 18.04 s +2024-11-21 12:55:57.968264: +2024-11-21 12:55:57.968446: Epoch 415 +2024-11-21 12:55:57.968559: Current learning rate: 0.00953 +2024-11-21 12:56:15.521259: train_loss -0.7417 +2024-11-21 12:56:15.521473: val_loss -0.7373 +2024-11-21 12:56:15.521549: Pseudo dice [0.8313] +2024-11-21 12:56:15.521629: Epoch time: 17.55 s +2024-11-21 12:56:16.303590: +2024-11-21 12:56:16.303794: Epoch 416 +2024-11-21 12:56:16.303909: Current learning rate: 0.00953 +2024-11-21 12:56:34.150890: train_loss -0.7614 +2024-11-21 12:56:34.151104: val_loss -0.7343 +2024-11-21 12:56:34.151182: Pseudo dice [0.8187] +2024-11-21 12:56:34.151319: Epoch time: 17.85 s +2024-11-21 12:56:34.955897: +2024-11-21 12:56:34.956125: Epoch 417 +2024-11-21 12:56:34.956237: Current learning rate: 0.00953 +2024-11-21 12:56:53.892637: train_loss -0.7537 +2024-11-21 12:56:53.892875: val_loss -0.7215 +2024-11-21 12:56:53.892951: Pseudo dice [0.8181] +2024-11-21 12:56:53.893089: Epoch time: 18.94 s +2024-11-21 12:56:54.677231: +2024-11-21 12:56:54.677427: Epoch 418 +2024-11-21 12:56:54.677539: Current learning rate: 0.00953 +2024-11-21 12:57:13.093043: train_loss -0.7411 +2024-11-21 12:57:13.093278: val_loss -0.7341 +2024-11-21 12:57:13.093354: Pseudo dice [0.8096] +2024-11-21 12:57:13.093443: Epoch time: 18.42 s +2024-11-21 12:57:13.905816: +2024-11-21 12:57:13.906042: Epoch 419 +2024-11-21 12:57:13.906152: Current learning rate: 0.00953 +2024-11-21 12:57:31.931508: train_loss -0.7503 +2024-11-21 12:57:31.931736: val_loss -0.7438 +2024-11-21 12:57:31.931831: Pseudo dice [0.8206] +2024-11-21 12:57:31.931916: Epoch time: 18.03 s +2024-11-21 12:57:32.713809: +2024-11-21 12:57:32.714131: Epoch 420 +2024-11-21 12:57:32.714247: Current learning rate: 0.00953 +2024-11-21 12:57:49.655370: train_loss -0.7608 +2024-11-21 12:57:49.655589: val_loss -0.7405 +2024-11-21 12:57:49.655668: Pseudo dice [0.8277] +2024-11-21 12:57:49.655745: Epoch time: 16.94 s +2024-11-21 12:57:50.433430: +2024-11-21 12:57:50.433737: Epoch 421 +2024-11-21 12:57:50.433893: Current learning rate: 0.00953 +2024-11-21 12:58:08.177669: train_loss -0.7512 +2024-11-21 12:58:08.177897: val_loss -0.7489 +2024-11-21 12:58:08.177972: Pseudo dice [0.8198] +2024-11-21 12:58:08.178066: Epoch time: 17.75 s +2024-11-21 12:58:09.004349: +2024-11-21 12:58:09.004567: Epoch 422 +2024-11-21 12:58:09.004686: Current learning rate: 0.00952 +2024-11-21 12:58:27.824776: train_loss -0.7443 +2024-11-21 12:58:27.827720: val_loss -0.7261 +2024-11-21 12:58:27.827853: Pseudo dice [0.8171] +2024-11-21 12:58:27.827936: Epoch time: 18.82 s +2024-11-21 12:58:29.081422: +2024-11-21 12:58:29.081625: Epoch 423 +2024-11-21 12:58:29.081734: Current learning rate: 0.00952 +2024-11-21 12:58:47.817751: train_loss -0.7238 +2024-11-21 12:58:47.818010: val_loss -0.7159 +2024-11-21 12:58:47.818088: Pseudo dice [0.8215] +2024-11-21 12:58:47.818177: Epoch time: 18.74 s +2024-11-21 12:58:48.626267: +2024-11-21 12:58:48.626488: Epoch 424 +2024-11-21 12:58:48.626607: Current learning rate: 0.00952 +2024-11-21 12:59:07.687049: train_loss -0.7454 +2024-11-21 12:59:07.687266: val_loss -0.7522 +2024-11-21 12:59:07.687345: Pseudo dice [0.8172] +2024-11-21 12:59:07.687423: Epoch time: 19.06 s +2024-11-21 12:59:08.490666: +2024-11-21 12:59:08.490862: Epoch 425 +2024-11-21 12:59:08.490981: Current learning rate: 0.00952 +2024-11-21 12:59:27.666237: train_loss -0.7523 +2024-11-21 12:59:27.666459: val_loss -0.7319 +2024-11-21 12:59:27.666541: Pseudo dice [0.827] +2024-11-21 12:59:27.666619: Epoch time: 19.18 s +2024-11-21 12:59:28.452919: +2024-11-21 12:59:28.453157: Epoch 426 +2024-11-21 12:59:28.453282: Current learning rate: 0.00952 +2024-11-21 12:59:48.177028: train_loss -0.7567 +2024-11-21 12:59:48.177263: val_loss -0.7621 +2024-11-21 12:59:48.177341: Pseudo dice [0.8422] +2024-11-21 12:59:48.177463: Epoch time: 19.72 s +2024-11-21 12:59:48.177565: Yayy! New best EMA pseudo Dice: 0.8213 +2024-11-21 12:59:49.190375: +2024-11-21 12:59:49.190564: Epoch 427 +2024-11-21 12:59:49.190676: Current learning rate: 0.00952 +2024-11-21 13:00:07.402390: train_loss -0.7564 +2024-11-21 13:00:07.407805: val_loss -0.7336 +2024-11-21 13:00:07.407922: Pseudo dice [0.811] +2024-11-21 13:00:07.408012: Epoch time: 18.21 s +2024-11-21 13:00:08.335642: +2024-11-21 13:00:08.335867: Epoch 428 +2024-11-21 13:00:08.335979: Current learning rate: 0.00952 +2024-11-21 13:00:26.301955: train_loss -0.7503 +2024-11-21 13:00:26.302177: val_loss -0.7132 +2024-11-21 13:00:26.302258: Pseudo dice [0.8143] +2024-11-21 13:00:26.302335: Epoch time: 17.97 s +2024-11-21 13:00:27.087311: +2024-11-21 13:00:27.087519: Epoch 429 +2024-11-21 13:00:27.087635: Current learning rate: 0.00952 +2024-11-21 13:00:46.457407: train_loss -0.7556 +2024-11-21 13:00:46.457623: val_loss -0.726 +2024-11-21 13:00:46.457697: Pseudo dice [0.8025] +2024-11-21 13:00:46.457773: Epoch time: 19.37 s +2024-11-21 13:00:47.248114: +2024-11-21 13:00:47.248358: Epoch 430 +2024-11-21 13:00:47.248474: Current learning rate: 0.00951 +2024-11-21 13:01:06.803396: train_loss -0.7441 +2024-11-21 13:01:06.806078: val_loss -0.724 +2024-11-21 13:01:06.806205: Pseudo dice [0.8186] +2024-11-21 13:01:06.806293: Epoch time: 19.55 s +2024-11-21 13:01:07.781894: +2024-11-21 13:01:07.782114: Epoch 431 +2024-11-21 13:01:07.782231: Current learning rate: 0.00951 +2024-11-21 13:01:26.725764: train_loss -0.7516 +2024-11-21 13:01:26.725981: val_loss -0.7256 +2024-11-21 13:01:26.726061: Pseudo dice [0.8117] +2024-11-21 13:01:26.726135: Epoch time: 18.94 s +2024-11-21 13:01:27.510340: +2024-11-21 13:01:27.510523: Epoch 432 +2024-11-21 13:01:27.510631: Current learning rate: 0.00951 +2024-11-21 13:01:46.030378: train_loss -0.7463 +2024-11-21 13:01:46.030592: val_loss -0.7295 +2024-11-21 13:01:46.030668: Pseudo dice [0.8166] +2024-11-21 13:01:46.030743: Epoch time: 18.52 s +2024-11-21 13:01:46.811062: +2024-11-21 13:01:46.811310: Epoch 433 +2024-11-21 13:01:46.811421: Current learning rate: 0.00951 +2024-11-21 13:02:06.514653: train_loss -0.7493 +2024-11-21 13:02:06.514865: val_loss -0.7367 +2024-11-21 13:02:06.514941: Pseudo dice [0.8034] +2024-11-21 13:02:06.515028: Epoch time: 19.7 s +2024-11-21 13:02:07.365885: +2024-11-21 13:02:07.366085: Epoch 434 +2024-11-21 13:02:07.366196: Current learning rate: 0.00951 +2024-11-21 13:02:25.912499: train_loss -0.7596 +2024-11-21 13:02:25.912733: val_loss -0.7382 +2024-11-21 13:02:25.912809: Pseudo dice [0.8218] +2024-11-21 13:02:25.912891: Epoch time: 18.55 s +2024-11-21 13:02:27.104023: +2024-11-21 13:02:27.104216: Epoch 435 +2024-11-21 13:02:27.104327: Current learning rate: 0.00951 +2024-11-21 13:02:45.324384: train_loss -0.7518 +2024-11-21 13:02:45.324612: val_loss -0.7384 +2024-11-21 13:02:45.324687: Pseudo dice [0.791] +2024-11-21 13:02:45.324766: Epoch time: 18.22 s +2024-11-21 13:02:46.102594: +2024-11-21 13:02:46.102818: Epoch 436 +2024-11-21 13:02:46.102938: Current learning rate: 0.00951 +2024-11-21 13:03:04.898147: train_loss -0.7447 +2024-11-21 13:03:04.898363: val_loss -0.7149 +2024-11-21 13:03:04.898444: Pseudo dice [0.8113] +2024-11-21 13:03:04.898521: Epoch time: 18.8 s +2024-11-21 13:03:05.678313: +2024-11-21 13:03:05.678512: Epoch 437 +2024-11-21 13:03:05.678630: Current learning rate: 0.00951 +2024-11-21 13:03:24.778476: train_loss -0.7403 +2024-11-21 13:03:24.782319: val_loss -0.712 +2024-11-21 13:03:24.782410: Pseudo dice [0.8075] +2024-11-21 13:03:24.782523: Epoch time: 19.1 s +2024-11-21 13:03:25.627892: +2024-11-21 13:03:25.628113: Epoch 438 +2024-11-21 13:03:25.628227: Current learning rate: 0.00951 +2024-11-21 13:03:44.069049: train_loss -0.7448 +2024-11-21 13:03:44.069269: val_loss -0.7373 +2024-11-21 13:03:44.069346: Pseudo dice [0.8222] +2024-11-21 13:03:44.069426: Epoch time: 18.44 s +2024-11-21 13:03:44.855349: +2024-11-21 13:03:44.855551: Epoch 439 +2024-11-21 13:03:44.855662: Current learning rate: 0.0095 +2024-11-21 13:04:04.046888: train_loss -0.7554 +2024-11-21 13:04:04.047109: val_loss -0.724 +2024-11-21 13:04:04.047185: Pseudo dice [0.7993] +2024-11-21 13:04:04.047262: Epoch time: 19.19 s +2024-11-21 13:04:04.835670: +2024-11-21 13:04:04.835936: Epoch 440 +2024-11-21 13:04:04.836053: Current learning rate: 0.0095 +2024-11-21 13:04:23.022156: train_loss -0.7624 +2024-11-21 13:04:23.022371: val_loss -0.7 +2024-11-21 13:04:23.022448: Pseudo dice [0.787] +2024-11-21 13:04:23.022534: Epoch time: 18.19 s +2024-11-21 13:04:23.813950: +2024-11-21 13:04:23.814177: Epoch 441 +2024-11-21 13:04:23.814330: Current learning rate: 0.0095 +2024-11-21 13:04:41.958175: train_loss -0.7504 +2024-11-21 13:04:41.958398: val_loss -0.7119 +2024-11-21 13:04:41.958472: Pseudo dice [0.7981] +2024-11-21 13:04:41.958551: Epoch time: 18.15 s +2024-11-21 13:04:42.744974: +2024-11-21 13:04:42.745236: Epoch 442 +2024-11-21 13:04:42.745347: Current learning rate: 0.0095 +2024-11-21 13:05:01.279438: train_loss -0.7654 +2024-11-21 13:05:01.279652: val_loss -0.7445 +2024-11-21 13:05:01.279725: Pseudo dice [0.8294] +2024-11-21 13:05:01.279803: Epoch time: 18.54 s +2024-11-21 13:05:02.085232: +2024-11-21 13:05:02.085507: Epoch 443 +2024-11-21 13:05:02.085625: Current learning rate: 0.0095 +2024-11-21 13:05:21.772641: train_loss -0.7469 +2024-11-21 13:05:21.772866: val_loss -0.7422 +2024-11-21 13:05:21.772945: Pseudo dice [0.8118] +2024-11-21 13:05:21.773028: Epoch time: 19.69 s +2024-11-21 13:05:22.550100: +2024-11-21 13:05:22.550280: Epoch 444 +2024-11-21 13:05:22.550390: Current learning rate: 0.0095 +2024-11-21 13:05:41.612320: train_loss -0.7456 +2024-11-21 13:05:41.612642: val_loss -0.7168 +2024-11-21 13:05:41.612722: Pseudo dice [0.7886] +2024-11-21 13:05:41.612812: Epoch time: 19.06 s +2024-11-21 13:05:42.409582: +2024-11-21 13:05:42.419860: Epoch 445 +2024-11-21 13:05:42.419988: Current learning rate: 0.0095 +2024-11-21 13:06:00.202703: train_loss -0.7593 +2024-11-21 13:06:00.202920: val_loss -0.7399 +2024-11-21 13:06:00.203000: Pseudo dice [0.8153] +2024-11-21 13:06:00.203077: Epoch time: 17.79 s +2024-11-21 13:06:00.979593: +2024-11-21 13:06:00.979797: Epoch 446 +2024-11-21 13:06:00.979909: Current learning rate: 0.0095 +2024-11-21 13:06:20.595127: train_loss -0.7598 +2024-11-21 13:06:20.600553: val_loss -0.7052 +2024-11-21 13:06:20.600690: Pseudo dice [0.8078] +2024-11-21 13:06:20.600779: Epoch time: 19.62 s +2024-11-21 13:06:21.977375: +2024-11-21 13:06:21.977587: Epoch 447 +2024-11-21 13:06:21.977704: Current learning rate: 0.0095 +2024-11-21 13:06:41.630079: train_loss -0.7565 +2024-11-21 13:06:41.630336: val_loss -0.7079 +2024-11-21 13:06:41.630411: Pseudo dice [0.8219] +2024-11-21 13:06:41.630493: Epoch time: 19.65 s +2024-11-21 13:06:42.415709: +2024-11-21 13:06:42.415938: Epoch 448 +2024-11-21 13:06:42.416065: Current learning rate: 0.00949 +2024-11-21 13:07:01.235485: train_loss -0.758 +2024-11-21 13:07:01.235694: val_loss -0.745 +2024-11-21 13:07:01.235766: Pseudo dice [0.8146] +2024-11-21 13:07:01.235842: Epoch time: 18.82 s +2024-11-21 13:07:02.088059: +2024-11-21 13:07:02.088269: Epoch 449 +2024-11-21 13:07:02.088383: Current learning rate: 0.00949 +2024-11-21 13:07:20.495899: train_loss -0.7439 +2024-11-21 13:07:20.496150: val_loss -0.7359 +2024-11-21 13:07:20.496267: Pseudo dice [0.8143] +2024-11-21 13:07:20.496382: Epoch time: 18.41 s +2024-11-21 13:07:21.591658: +2024-11-21 13:07:21.591877: Epoch 450 +2024-11-21 13:07:21.591986: Current learning rate: 0.00949 +2024-11-21 13:07:41.053663: train_loss -0.7525 +2024-11-21 13:07:41.053884: val_loss -0.7305 +2024-11-21 13:07:41.053962: Pseudo dice [0.8051] +2024-11-21 13:07:41.054049: Epoch time: 19.46 s +2024-11-21 13:07:41.899024: +2024-11-21 13:07:41.899233: Epoch 451 +2024-11-21 13:07:41.899346: Current learning rate: 0.00949 +2024-11-21 13:08:00.807495: train_loss -0.7537 +2024-11-21 13:08:00.807739: val_loss -0.7093 +2024-11-21 13:08:00.807823: Pseudo dice [0.8231] +2024-11-21 13:08:00.807903: Epoch time: 18.91 s +2024-11-21 13:08:01.744588: +2024-11-21 13:08:01.744828: Epoch 452 +2024-11-21 13:08:01.745138: Current learning rate: 0.00949 +2024-11-21 13:08:20.898518: train_loss -0.7582 +2024-11-21 13:08:20.898735: val_loss -0.7215 +2024-11-21 13:08:20.898811: Pseudo dice [0.8267] +2024-11-21 13:08:20.898890: Epoch time: 19.15 s +2024-11-21 13:08:21.823121: +2024-11-21 13:08:21.823328: Epoch 453 +2024-11-21 13:08:21.823433: Current learning rate: 0.00949 +2024-11-21 13:08:40.407973: train_loss -0.7663 +2024-11-21 13:08:40.408193: val_loss -0.7255 +2024-11-21 13:08:40.408266: Pseudo dice [0.8311] +2024-11-21 13:08:40.408341: Epoch time: 18.59 s +2024-11-21 13:08:41.282372: +2024-11-21 13:08:41.282613: Epoch 454 +2024-11-21 13:08:41.282724: Current learning rate: 0.00949 +2024-11-21 13:09:00.407215: train_loss -0.7611 +2024-11-21 13:09:00.407449: val_loss -0.7384 +2024-11-21 13:09:00.409716: Pseudo dice [0.8105] +2024-11-21 13:09:00.409811: Epoch time: 19.13 s +2024-11-21 13:09:01.341172: +2024-11-21 13:09:01.341363: Epoch 455 +2024-11-21 13:09:01.341474: Current learning rate: 0.00949 +2024-11-21 13:09:19.831417: train_loss -0.7649 +2024-11-21 13:09:19.831714: val_loss -0.716 +2024-11-21 13:09:19.831790: Pseudo dice [0.8118] +2024-11-21 13:09:19.831872: Epoch time: 18.49 s +2024-11-21 13:09:20.613959: +2024-11-21 13:09:20.614158: Epoch 456 +2024-11-21 13:09:20.614272: Current learning rate: 0.00949 +2024-11-21 13:09:38.728341: train_loss -0.7626 +2024-11-21 13:09:38.728551: val_loss -0.7312 +2024-11-21 13:09:38.728625: Pseudo dice [0.832] +2024-11-21 13:09:38.728700: Epoch time: 18.12 s +2024-11-21 13:09:39.513682: +2024-11-21 13:09:39.513914: Epoch 457 +2024-11-21 13:09:39.514036: Current learning rate: 0.00948 +2024-11-21 13:09:58.514261: train_loss -0.7624 +2024-11-21 13:09:58.514478: val_loss -0.7555 +2024-11-21 13:09:58.514561: Pseudo dice [0.8243] +2024-11-21 13:09:58.514874: Epoch time: 19.0 s +2024-11-21 13:09:59.292637: +2024-11-21 13:09:59.292832: Epoch 458 +2024-11-21 13:09:59.292943: Current learning rate: 0.00948 +2024-11-21 13:10:18.230303: train_loss -0.761 +2024-11-21 13:10:18.230554: val_loss -0.7234 +2024-11-21 13:10:18.230690: Pseudo dice [0.8082] +2024-11-21 13:10:18.230776: Epoch time: 18.94 s +2024-11-21 13:10:19.396722: +2024-11-21 13:10:19.396955: Epoch 459 +2024-11-21 13:10:19.397077: Current learning rate: 0.00948 +2024-11-21 13:10:39.273346: train_loss -0.7461 +2024-11-21 13:10:39.273560: val_loss -0.7284 +2024-11-21 13:10:39.273633: Pseudo dice [0.8229] +2024-11-21 13:10:39.273708: Epoch time: 19.88 s +2024-11-21 13:10:40.058511: +2024-11-21 13:10:40.058720: Epoch 460 +2024-11-21 13:10:40.058837: Current learning rate: 0.00948 +2024-11-21 13:10:58.079811: train_loss -0.7592 +2024-11-21 13:10:58.080032: val_loss -0.7245 +2024-11-21 13:10:58.080110: Pseudo dice [0.8059] +2024-11-21 13:10:58.080187: Epoch time: 18.02 s +2024-11-21 13:10:58.859780: +2024-11-21 13:10:58.860061: Epoch 461 +2024-11-21 13:10:58.860175: Current learning rate: 0.00948 +2024-11-21 13:11:17.428710: train_loss -0.7631 +2024-11-21 13:11:17.428974: val_loss -0.7355 +2024-11-21 13:11:17.429060: Pseudo dice [0.8229] +2024-11-21 13:11:17.429147: Epoch time: 18.57 s +2024-11-21 13:11:18.290354: +2024-11-21 13:11:18.290625: Epoch 462 +2024-11-21 13:11:18.290743: Current learning rate: 0.00948 +2024-11-21 13:11:35.844627: train_loss -0.753 +2024-11-21 13:11:35.844855: val_loss -0.7051 +2024-11-21 13:11:35.844928: Pseudo dice [0.8157] +2024-11-21 13:11:35.845012: Epoch time: 17.56 s +2024-11-21 13:11:36.956584: +2024-11-21 13:11:36.956815: Epoch 463 +2024-11-21 13:11:36.956931: Current learning rate: 0.00948 +2024-11-21 13:11:56.875271: train_loss -0.7502 +2024-11-21 13:11:56.875565: val_loss -0.737 +2024-11-21 13:11:56.875651: Pseudo dice [0.8151] +2024-11-21 13:11:56.875730: Epoch time: 19.92 s +2024-11-21 13:11:57.664653: +2024-11-21 13:11:57.664876: Epoch 464 +2024-11-21 13:11:57.664996: Current learning rate: 0.00948 +2024-11-21 13:12:15.717591: train_loss -0.7601 +2024-11-21 13:12:15.717804: val_loss -0.7231 +2024-11-21 13:12:15.717879: Pseudo dice [0.7941] +2024-11-21 13:12:15.717954: Epoch time: 18.05 s +2024-11-21 13:12:16.504408: +2024-11-21 13:12:16.504634: Epoch 465 +2024-11-21 13:12:16.504747: Current learning rate: 0.00948 +2024-11-21 13:12:34.560781: train_loss -0.7661 +2024-11-21 13:12:34.561022: val_loss -0.7386 +2024-11-21 13:12:34.561099: Pseudo dice [0.7986] +2024-11-21 13:12:34.561183: Epoch time: 18.06 s +2024-11-21 13:12:35.445051: +2024-11-21 13:12:35.445246: Epoch 466 +2024-11-21 13:12:35.445362: Current learning rate: 0.00947 +2024-11-21 13:12:55.586893: train_loss -0.7521 +2024-11-21 13:12:55.587111: val_loss -0.7359 +2024-11-21 13:12:55.587188: Pseudo dice [0.8194] +2024-11-21 13:12:55.587265: Epoch time: 20.14 s +2024-11-21 13:12:56.373887: +2024-11-21 13:12:56.374113: Epoch 467 +2024-11-21 13:12:56.374234: Current learning rate: 0.00947 +2024-11-21 13:13:14.049954: train_loss -0.7509 +2024-11-21 13:13:14.050184: val_loss -0.7398 +2024-11-21 13:13:14.050257: Pseudo dice [0.8155] +2024-11-21 13:13:14.050333: Epoch time: 17.68 s +2024-11-21 13:13:14.836901: +2024-11-21 13:13:14.837129: Epoch 468 +2024-11-21 13:13:14.837237: Current learning rate: 0.00947 +2024-11-21 13:13:33.911566: train_loss -0.7596 +2024-11-21 13:13:33.911785: val_loss -0.7524 +2024-11-21 13:13:33.911861: Pseudo dice [0.823] +2024-11-21 13:13:33.911942: Epoch time: 19.08 s +2024-11-21 13:13:34.693133: +2024-11-21 13:13:34.693321: Epoch 469 +2024-11-21 13:13:34.693429: Current learning rate: 0.00947 +2024-11-21 13:13:54.021744: train_loss -0.7673 +2024-11-21 13:13:54.021982: val_loss -0.7261 +2024-11-21 13:13:54.022065: Pseudo dice [0.8125] +2024-11-21 13:13:54.022147: Epoch time: 19.33 s +2024-11-21 13:13:54.906015: +2024-11-21 13:13:54.906215: Epoch 470 +2024-11-21 13:13:54.906327: Current learning rate: 0.00947 +2024-11-21 13:14:14.552954: train_loss -0.762 +2024-11-21 13:14:14.571332: val_loss -0.7351 +2024-11-21 13:14:14.571427: Pseudo dice [0.8241] +2024-11-21 13:14:14.571504: Epoch time: 19.65 s +2024-11-21 13:14:15.345079: +2024-11-21 13:14:15.345253: Epoch 471 +2024-11-21 13:14:15.345361: Current learning rate: 0.00947 +2024-11-21 13:14:35.113196: train_loss -0.7657 +2024-11-21 13:14:35.113407: val_loss -0.7518 +2024-11-21 13:14:35.113481: Pseudo dice [0.8142] +2024-11-21 13:14:35.113555: Epoch time: 19.77 s +2024-11-21 13:14:35.886412: +2024-11-21 13:14:35.886635: Epoch 472 +2024-11-21 13:14:35.886748: Current learning rate: 0.00947 +2024-11-21 13:14:54.384559: train_loss -0.7287 +2024-11-21 13:14:54.384802: val_loss -0.7278 +2024-11-21 13:14:54.384876: Pseudo dice [0.8067] +2024-11-21 13:14:54.384958: Epoch time: 18.5 s +2024-11-21 13:14:55.166240: +2024-11-21 13:14:55.166447: Epoch 473 +2024-11-21 13:14:55.166559: Current learning rate: 0.00947 +2024-11-21 13:15:14.213553: train_loss -0.7022 +2024-11-21 13:15:14.213791: val_loss -0.7131 +2024-11-21 13:15:14.213867: Pseudo dice [0.8277] +2024-11-21 13:15:14.213944: Epoch time: 19.05 s +2024-11-21 13:15:14.994121: +2024-11-21 13:15:14.994302: Epoch 474 +2024-11-21 13:15:14.994411: Current learning rate: 0.00947 +2024-11-21 13:15:32.655294: train_loss -0.7457 +2024-11-21 13:15:32.657746: val_loss -0.7435 +2024-11-21 13:15:32.657867: Pseudo dice [0.8163] +2024-11-21 13:15:32.657958: Epoch time: 17.66 s +2024-11-21 13:15:33.473520: +2024-11-21 13:15:33.473833: Epoch 475 +2024-11-21 13:15:33.473947: Current learning rate: 0.00946 +2024-11-21 13:15:52.502145: train_loss -0.7451 +2024-11-21 13:15:52.502362: val_loss -0.7096 +2024-11-21 13:15:52.502444: Pseudo dice [0.8097] +2024-11-21 13:15:52.502525: Epoch time: 19.03 s +2024-11-21 13:15:53.286361: +2024-11-21 13:15:53.286578: Epoch 476 +2024-11-21 13:15:53.286690: Current learning rate: 0.00946 +2024-11-21 13:16:12.598773: train_loss -0.7531 +2024-11-21 13:16:12.598975: val_loss -0.7307 +2024-11-21 13:16:12.599056: Pseudo dice [0.823] +2024-11-21 13:16:12.599133: Epoch time: 19.31 s +2024-11-21 13:16:13.401764: +2024-11-21 13:16:13.401962: Epoch 477 +2024-11-21 13:16:13.402083: Current learning rate: 0.00946 +2024-11-21 13:16:30.844975: train_loss -0.7546 +2024-11-21 13:16:30.845207: val_loss -0.7282 +2024-11-21 13:16:30.845282: Pseudo dice [0.7919] +2024-11-21 13:16:30.845360: Epoch time: 17.44 s +2024-11-21 13:16:31.755458: +2024-11-21 13:16:31.755640: Epoch 478 +2024-11-21 13:16:31.755949: Current learning rate: 0.00946 +2024-11-21 13:16:51.390031: train_loss -0.7522 +2024-11-21 13:16:51.390285: val_loss -0.7307 +2024-11-21 13:16:51.390361: Pseudo dice [0.8177] +2024-11-21 13:16:51.390448: Epoch time: 19.64 s +2024-11-21 13:16:52.180549: +2024-11-21 13:16:52.180729: Epoch 479 +2024-11-21 13:16:52.180842: Current learning rate: 0.00946 +2024-11-21 13:17:10.527168: train_loss -0.7618 +2024-11-21 13:17:10.527363: val_loss -0.7446 +2024-11-21 13:17:10.527439: Pseudo dice [0.828] +2024-11-21 13:17:10.527516: Epoch time: 18.35 s +2024-11-21 13:17:11.316969: +2024-11-21 13:17:11.317179: Epoch 480 +2024-11-21 13:17:11.317292: Current learning rate: 0.00946 +2024-11-21 13:17:30.325265: train_loss -0.7596 +2024-11-21 13:17:30.325487: val_loss -0.7555 +2024-11-21 13:17:30.327774: Pseudo dice [0.8177] +2024-11-21 13:17:30.327873: Epoch time: 19.01 s +2024-11-21 13:17:31.239955: +2024-11-21 13:17:31.240161: Epoch 481 +2024-11-21 13:17:31.240277: Current learning rate: 0.00946 +2024-11-21 13:17:49.685391: train_loss -0.7506 +2024-11-21 13:17:49.685638: val_loss -0.7423 +2024-11-21 13:17:49.685714: Pseudo dice [0.8252] +2024-11-21 13:17:49.685802: Epoch time: 18.45 s +2024-11-21 13:17:50.472903: +2024-11-21 13:17:50.473167: Epoch 482 +2024-11-21 13:17:50.473285: Current learning rate: 0.00946 +2024-11-21 13:18:08.701820: train_loss -0.7498 +2024-11-21 13:18:08.702069: val_loss -0.7364 +2024-11-21 13:18:08.702152: Pseudo dice [0.786] +2024-11-21 13:18:08.702227: Epoch time: 18.23 s +2024-11-21 13:18:09.494765: +2024-11-21 13:18:09.494975: Epoch 483 +2024-11-21 13:18:09.495093: Current learning rate: 0.00945 +2024-11-21 13:18:27.584327: train_loss -0.7584 +2024-11-21 13:18:27.584550: val_loss -0.7492 +2024-11-21 13:18:27.584707: Pseudo dice [0.8171] +2024-11-21 13:18:27.584786: Epoch time: 18.09 s +2024-11-21 13:18:28.390050: +2024-11-21 13:18:28.390267: Epoch 484 +2024-11-21 13:18:28.390385: Current learning rate: 0.00945 +2024-11-21 13:18:46.920070: train_loss -0.7599 +2024-11-21 13:18:46.920688: val_loss -0.7246 +2024-11-21 13:18:46.920773: Pseudo dice [0.8188] +2024-11-21 13:18:46.920859: Epoch time: 18.53 s +2024-11-21 13:18:47.716254: +2024-11-21 13:18:47.716460: Epoch 485 +2024-11-21 13:18:47.716576: Current learning rate: 0.00945 +2024-11-21 13:19:06.586926: train_loss -0.7676 +2024-11-21 13:19:06.587151: val_loss -0.7369 +2024-11-21 13:19:06.587229: Pseudo dice [0.8222] +2024-11-21 13:19:06.587335: Epoch time: 18.87 s +2024-11-21 13:19:07.379162: +2024-11-21 13:19:07.379412: Epoch 486 +2024-11-21 13:19:07.379524: Current learning rate: 0.00945 +2024-11-21 13:19:26.411729: train_loss -0.7692 +2024-11-21 13:19:26.411939: val_loss -0.7517 +2024-11-21 13:19:26.412030: Pseudo dice [0.8304] +2024-11-21 13:19:26.412110: Epoch time: 19.03 s +2024-11-21 13:19:27.200869: +2024-11-21 13:19:27.201104: Epoch 487 +2024-11-21 13:19:27.201224: Current learning rate: 0.00945 +2024-11-21 13:19:45.466058: train_loss -0.7727 +2024-11-21 13:19:45.466271: val_loss -0.7371 +2024-11-21 13:19:45.466345: Pseudo dice [0.8127] +2024-11-21 13:19:45.466421: Epoch time: 18.27 s +2024-11-21 13:19:46.261495: +2024-11-21 13:19:46.261712: Epoch 488 +2024-11-21 13:19:46.261823: Current learning rate: 0.00945 +2024-11-21 13:20:06.111523: train_loss -0.7671 +2024-11-21 13:20:06.111779: val_loss -0.7326 +2024-11-21 13:20:06.111855: Pseudo dice [0.7995] +2024-11-21 13:20:06.116260: Epoch time: 19.85 s +2024-11-21 13:20:06.947718: +2024-11-21 13:20:06.947918: Epoch 489 +2024-11-21 13:20:06.948036: Current learning rate: 0.00945 +2024-11-21 13:20:27.168600: train_loss -0.757 +2024-11-21 13:20:27.168811: val_loss -0.7364 +2024-11-21 13:20:27.168887: Pseudo dice [0.8147] +2024-11-21 13:20:27.168965: Epoch time: 20.22 s +2024-11-21 13:20:27.965865: +2024-11-21 13:20:27.966066: Epoch 490 +2024-11-21 13:20:27.966178: Current learning rate: 0.00945 +2024-11-21 13:20:47.869806: train_loss -0.7604 +2024-11-21 13:20:47.870025: val_loss -0.7324 +2024-11-21 13:20:47.870098: Pseudo dice [0.8288] +2024-11-21 13:20:47.870178: Epoch time: 19.9 s +2024-11-21 13:20:48.817968: +2024-11-21 13:20:48.818144: Epoch 491 +2024-11-21 13:20:48.818270: Current learning rate: 0.00945 +2024-11-21 13:21:06.689147: train_loss -0.7576 +2024-11-21 13:21:06.689356: val_loss -0.74 +2024-11-21 13:21:06.689438: Pseudo dice [0.808] +2024-11-21 13:21:06.689516: Epoch time: 17.87 s +2024-11-21 13:21:07.480211: +2024-11-21 13:21:07.480412: Epoch 492 +2024-11-21 13:21:07.480521: Current learning rate: 0.00944 +2024-11-21 13:21:27.237793: train_loss -0.763 +2024-11-21 13:21:27.238430: val_loss -0.758 +2024-11-21 13:21:27.238510: Pseudo dice [0.8108] +2024-11-21 13:21:27.238593: Epoch time: 19.76 s +2024-11-21 13:21:28.031398: +2024-11-21 13:21:28.031569: Epoch 493 +2024-11-21 13:21:28.031677: Current learning rate: 0.00944 +2024-11-21 13:21:46.913642: train_loss -0.7636 +2024-11-21 13:21:46.913851: val_loss -0.7285 +2024-11-21 13:21:46.913925: Pseudo dice [0.8372] +2024-11-21 13:21:46.914005: Epoch time: 18.88 s +2024-11-21 13:21:47.705590: +2024-11-21 13:21:47.705791: Epoch 494 +2024-11-21 13:21:47.705904: Current learning rate: 0.00944 +2024-11-21 13:22:06.362453: train_loss -0.765 +2024-11-21 13:22:06.362673: val_loss -0.7351 +2024-11-21 13:22:06.362751: Pseudo dice [0.8137] +2024-11-21 13:22:06.362826: Epoch time: 18.66 s +2024-11-21 13:22:07.152951: +2024-11-21 13:22:07.153155: Epoch 495 +2024-11-21 13:22:07.153271: Current learning rate: 0.00944 +2024-11-21 13:22:25.537601: train_loss -0.7693 +2024-11-21 13:22:25.537855: val_loss -0.7321 +2024-11-21 13:22:25.537935: Pseudo dice [0.8234] +2024-11-21 13:22:25.538028: Epoch time: 18.39 s +2024-11-21 13:22:26.336860: +2024-11-21 13:22:26.345930: Epoch 496 +2024-11-21 13:22:26.346061: Current learning rate: 0.00944 +2024-11-21 13:22:43.799578: train_loss -0.7593 +2024-11-21 13:22:43.799813: val_loss -0.7399 +2024-11-21 13:22:43.805089: Pseudo dice [0.821] +2024-11-21 13:22:43.805192: Epoch time: 17.46 s +2024-11-21 13:22:44.865518: +2024-11-21 13:22:44.865758: Epoch 497 +2024-11-21 13:22:44.865877: Current learning rate: 0.00944 +2024-11-21 13:23:03.037770: train_loss -0.7666 +2024-11-21 13:23:03.037987: val_loss -0.7512 +2024-11-21 13:23:03.038072: Pseudo dice [0.8322] +2024-11-21 13:23:03.038148: Epoch time: 18.17 s +2024-11-21 13:23:03.834083: +2024-11-21 13:23:03.834287: Epoch 498 +2024-11-21 13:23:03.834401: Current learning rate: 0.00944 +2024-11-21 13:23:22.932293: train_loss -0.7667 +2024-11-21 13:23:22.932526: val_loss -0.7285 +2024-11-21 13:23:22.932603: Pseudo dice [0.8214] +2024-11-21 13:23:22.938949: Epoch time: 19.1 s +2024-11-21 13:23:23.748090: +2024-11-21 13:23:23.748277: Epoch 499 +2024-11-21 13:23:23.748388: Current learning rate: 0.00944 +2024-11-21 13:23:41.771073: train_loss -0.7581 +2024-11-21 13:23:41.771288: val_loss -0.661 +2024-11-21 13:23:41.771361: Pseudo dice [0.7725] +2024-11-21 13:23:41.771440: Epoch time: 18.02 s +2024-11-21 13:23:42.828130: +2024-11-21 13:23:42.828342: Epoch 500 +2024-11-21 13:23:42.828455: Current learning rate: 0.00944 +2024-11-21 13:24:02.024513: train_loss -0.7441 +2024-11-21 13:24:02.024726: val_loss -0.7432 +2024-11-21 13:24:02.024825: Pseudo dice [0.8194] +2024-11-21 13:24:02.024906: Epoch time: 19.2 s +2024-11-21 13:24:02.820118: +2024-11-21 13:24:02.820338: Epoch 501 +2024-11-21 13:24:02.820450: Current learning rate: 0.00943 +2024-11-21 13:24:21.306225: train_loss -0.7544 +2024-11-21 13:24:21.306428: val_loss -0.7428 +2024-11-21 13:24:21.306509: Pseudo dice [0.8259] +2024-11-21 13:24:21.306643: Epoch time: 18.49 s +2024-11-21 13:24:22.118823: +2024-11-21 13:24:22.119035: Epoch 502 +2024-11-21 13:24:22.119148: Current learning rate: 0.00943 +2024-11-21 13:24:41.270711: train_loss -0.7566 +2024-11-21 13:24:41.270957: val_loss -0.7461 +2024-11-21 13:24:41.271044: Pseudo dice [0.8285] +2024-11-21 13:24:41.271132: Epoch time: 19.15 s +2024-11-21 13:24:42.066000: +2024-11-21 13:24:42.066203: Epoch 503 +2024-11-21 13:24:42.066313: Current learning rate: 0.00943 +2024-11-21 13:25:00.809736: train_loss -0.7521 +2024-11-21 13:25:00.809950: val_loss -0.7582 +2024-11-21 13:25:00.810031: Pseudo dice [0.8234] +2024-11-21 13:25:00.810111: Epoch time: 18.74 s +2024-11-21 13:25:01.624282: +2024-11-21 13:25:01.624490: Epoch 504 +2024-11-21 13:25:01.624799: Current learning rate: 0.00943 +2024-11-21 13:25:21.137564: train_loss -0.751 +2024-11-21 13:25:21.137771: val_loss -0.7341 +2024-11-21 13:25:21.137843: Pseudo dice [0.8357] +2024-11-21 13:25:21.137918: Epoch time: 19.51 s +2024-11-21 13:25:22.055056: +2024-11-21 13:25:22.055324: Epoch 505 +2024-11-21 13:25:22.055446: Current learning rate: 0.00943 +2024-11-21 13:25:41.418404: train_loss -0.7623 +2024-11-21 13:25:41.418628: val_loss -0.7499 +2024-11-21 13:25:41.418706: Pseudo dice [0.8356] +2024-11-21 13:25:41.418787: Epoch time: 19.36 s +2024-11-21 13:25:41.418851: Yayy! New best EMA pseudo Dice: 0.8214 +2024-11-21 13:25:42.469262: +2024-11-21 13:25:42.469512: Epoch 506 +2024-11-21 13:25:42.469625: Current learning rate: 0.00943 +2024-11-21 13:26:01.735907: train_loss -0.7485 +2024-11-21 13:26:01.736158: val_loss -0.7314 +2024-11-21 13:26:01.736234: Pseudo dice [0.8135] +2024-11-21 13:26:01.736318: Epoch time: 19.27 s +2024-11-21 13:26:02.944488: +2024-11-21 13:26:02.944800: Epoch 507 +2024-11-21 13:26:02.944921: Current learning rate: 0.00943 +2024-11-21 13:26:22.108503: train_loss -0.7553 +2024-11-21 13:26:22.108758: val_loss -0.7251 +2024-11-21 13:26:22.108837: Pseudo dice [0.8252] +2024-11-21 13:26:22.108920: Epoch time: 19.16 s +2024-11-21 13:26:22.904536: +2024-11-21 13:26:22.904765: Epoch 508 +2024-11-21 13:26:22.904881: Current learning rate: 0.00943 +2024-11-21 13:26:41.880832: train_loss -0.7519 +2024-11-21 13:26:41.881306: val_loss -0.7309 +2024-11-21 13:26:41.881384: Pseudo dice [0.8134] +2024-11-21 13:26:41.881462: Epoch time: 18.98 s +2024-11-21 13:26:42.674291: +2024-11-21 13:26:42.674519: Epoch 509 +2024-11-21 13:26:42.674631: Current learning rate: 0.00943 +2024-11-21 13:27:02.317874: train_loss -0.7554 +2024-11-21 13:27:02.318131: val_loss -0.7506 +2024-11-21 13:27:02.318207: Pseudo dice [0.8225] +2024-11-21 13:27:02.318289: Epoch time: 19.64 s +2024-11-21 13:27:03.243390: +2024-11-21 13:27:03.243600: Epoch 510 +2024-11-21 13:27:03.243708: Current learning rate: 0.00942 +2024-11-21 13:27:21.756580: train_loss -0.7481 +2024-11-21 13:27:21.756790: val_loss -0.7232 +2024-11-21 13:27:21.756868: Pseudo dice [0.7876] +2024-11-21 13:27:21.756949: Epoch time: 18.51 s +2024-11-21 13:27:22.552797: +2024-11-21 13:27:22.553011: Epoch 511 +2024-11-21 13:27:22.553130: Current learning rate: 0.00942 +2024-11-21 13:27:41.147300: train_loss -0.7463 +2024-11-21 13:27:41.147512: val_loss -0.7285 +2024-11-21 13:27:41.147594: Pseudo dice [0.8251] +2024-11-21 13:27:41.147680: Epoch time: 18.6 s +2024-11-21 13:27:41.941000: +2024-11-21 13:27:41.941201: Epoch 512 +2024-11-21 13:27:41.941324: Current learning rate: 0.00942 +2024-11-21 13:28:00.847669: train_loss -0.7551 +2024-11-21 13:28:00.847897: val_loss -0.7306 +2024-11-21 13:28:00.847983: Pseudo dice [0.8157] +2024-11-21 13:28:00.848073: Epoch time: 18.91 s +2024-11-21 13:28:01.644047: +2024-11-21 13:28:01.644304: Epoch 513 +2024-11-21 13:28:01.644423: Current learning rate: 0.00942 +2024-11-21 13:28:21.375787: train_loss -0.7484 +2024-11-21 13:28:21.376033: val_loss -0.7273 +2024-11-21 13:28:21.376109: Pseudo dice [0.8065] +2024-11-21 13:28:21.376189: Epoch time: 19.73 s +2024-11-21 13:28:22.324672: +2024-11-21 13:28:22.324859: Epoch 514 +2024-11-21 13:28:22.324973: Current learning rate: 0.00942 +2024-11-21 13:28:41.029551: train_loss -0.7443 +2024-11-21 13:28:41.029766: val_loss -0.687 +2024-11-21 13:28:41.029842: Pseudo dice [0.7478] +2024-11-21 13:28:41.029919: Epoch time: 18.71 s +2024-11-21 13:28:41.822126: +2024-11-21 13:28:41.822298: Epoch 515 +2024-11-21 13:28:41.822411: Current learning rate: 0.00942 +2024-11-21 13:28:59.169940: train_loss -0.7477 +2024-11-21 13:28:59.170154: val_loss -0.7504 +2024-11-21 13:28:59.170230: Pseudo dice [0.8038] +2024-11-21 13:28:59.170311: Epoch time: 17.35 s +2024-11-21 13:28:59.965942: +2024-11-21 13:28:59.966126: Epoch 516 +2024-11-21 13:28:59.966236: Current learning rate: 0.00942 +2024-11-21 13:29:18.926591: train_loss -0.7445 +2024-11-21 13:29:18.926837: val_loss -0.7059 +2024-11-21 13:29:18.926911: Pseudo dice [0.7964] +2024-11-21 13:29:18.926997: Epoch time: 18.96 s +2024-11-21 13:29:19.726757: +2024-11-21 13:29:19.726937: Epoch 517 +2024-11-21 13:29:19.727048: Current learning rate: 0.00942 +2024-11-21 13:29:37.568027: train_loss -0.7413 +2024-11-21 13:29:37.568228: val_loss -0.7352 +2024-11-21 13:29:37.568300: Pseudo dice [0.8147] +2024-11-21 13:29:37.568375: Epoch time: 17.84 s +2024-11-21 13:29:38.537977: +2024-11-21 13:29:38.538192: Epoch 518 +2024-11-21 13:29:38.538306: Current learning rate: 0.00942 +2024-11-21 13:29:57.185010: train_loss -0.7407 +2024-11-21 13:29:57.185230: val_loss -0.7265 +2024-11-21 13:29:57.185306: Pseudo dice [0.8262] +2024-11-21 13:29:57.185381: Epoch time: 18.65 s +2024-11-21 13:29:58.360348: +2024-11-21 13:29:58.360567: Epoch 519 +2024-11-21 13:29:58.360684: Current learning rate: 0.00941 +2024-11-21 13:30:16.449414: train_loss -0.7462 +2024-11-21 13:30:16.449663: val_loss -0.7487 +2024-11-21 13:30:16.449748: Pseudo dice [0.8424] +2024-11-21 13:30:16.449857: Epoch time: 18.09 s +2024-11-21 13:30:17.242396: +2024-11-21 13:30:17.242596: Epoch 520 +2024-11-21 13:30:17.242711: Current learning rate: 0.00941 +2024-11-21 13:30:36.661652: train_loss -0.7544 +2024-11-21 13:30:36.661868: val_loss -0.7343 +2024-11-21 13:30:36.667196: Pseudo dice [0.8135] +2024-11-21 13:30:36.667327: Epoch time: 19.42 s +2024-11-21 13:30:37.579973: +2024-11-21 13:30:37.580206: Epoch 521 +2024-11-21 13:30:37.580323: Current learning rate: 0.00941 +2024-11-21 13:30:56.521228: train_loss -0.7582 +2024-11-21 13:30:56.521435: val_loss -0.722 +2024-11-21 13:30:56.521507: Pseudo dice [0.8358] +2024-11-21 13:30:56.521582: Epoch time: 18.94 s +2024-11-21 13:30:57.423212: +2024-11-21 13:30:57.423427: Epoch 522 +2024-11-21 13:30:57.423544: Current learning rate: 0.00941 +2024-11-21 13:31:16.469157: train_loss -0.7575 +2024-11-21 13:31:16.469366: val_loss -0.7247 +2024-11-21 13:31:16.469440: Pseudo dice [0.8118] +2024-11-21 13:31:16.469524: Epoch time: 19.05 s +2024-11-21 13:31:17.269961: +2024-11-21 13:31:17.270192: Epoch 523 +2024-11-21 13:31:17.270311: Current learning rate: 0.00941 +2024-11-21 13:31:34.927258: train_loss -0.757 +2024-11-21 13:31:34.927468: val_loss -0.7386 +2024-11-21 13:31:34.927544: Pseudo dice [0.8347] +2024-11-21 13:31:34.927625: Epoch time: 17.66 s +2024-11-21 13:31:35.726211: +2024-11-21 13:31:35.726442: Epoch 524 +2024-11-21 13:31:35.726549: Current learning rate: 0.00941 +2024-11-21 13:31:54.502675: train_loss -0.7618 +2024-11-21 13:31:54.502892: val_loss -0.7383 +2024-11-21 13:31:54.505214: Pseudo dice [0.8265] +2024-11-21 13:31:54.505314: Epoch time: 18.78 s +2024-11-21 13:31:55.429758: +2024-11-21 13:31:55.429968: Epoch 525 +2024-11-21 13:31:55.430084: Current learning rate: 0.00941 +2024-11-21 13:32:13.776673: train_loss -0.7546 +2024-11-21 13:32:13.776881: val_loss -0.7404 +2024-11-21 13:32:13.779183: Pseudo dice [0.8302] +2024-11-21 13:32:13.779276: Epoch time: 18.35 s +2024-11-21 13:32:14.773819: +2024-11-21 13:32:14.774085: Epoch 526 +2024-11-21 13:32:14.774198: Current learning rate: 0.00941 +2024-11-21 13:32:33.549074: train_loss -0.7533 +2024-11-21 13:32:33.549342: val_loss -0.6965 +2024-11-21 13:32:33.549421: Pseudo dice [0.8055] +2024-11-21 13:32:33.549512: Epoch time: 18.78 s +2024-11-21 13:32:34.424688: +2024-11-21 13:32:34.424881: Epoch 527 +2024-11-21 13:32:34.425002: Current learning rate: 0.00941 +2024-11-21 13:32:54.424699: train_loss -0.7629 +2024-11-21 13:32:54.424920: val_loss -0.7424 +2024-11-21 13:32:54.425005: Pseudo dice [0.8205] +2024-11-21 13:32:54.425081: Epoch time: 20.0 s +2024-11-21 13:32:55.374033: +2024-11-21 13:32:55.374226: Epoch 528 +2024-11-21 13:32:55.374335: Current learning rate: 0.0094 +2024-11-21 13:33:12.895669: train_loss -0.7514 +2024-11-21 13:33:12.895885: val_loss -0.6908 +2024-11-21 13:33:12.895962: Pseudo dice [0.8039] +2024-11-21 13:33:12.896048: Epoch time: 17.52 s +2024-11-21 13:33:13.693677: +2024-11-21 13:33:13.693852: Epoch 529 +2024-11-21 13:33:13.693963: Current learning rate: 0.0094 +2024-11-21 13:33:33.097201: train_loss -0.7712 +2024-11-21 13:33:33.097432: val_loss -0.7303 +2024-11-21 13:33:33.097508: Pseudo dice [0.8199] +2024-11-21 13:33:33.097595: Epoch time: 19.4 s +2024-11-21 13:33:33.885521: +2024-11-21 13:33:33.885705: Epoch 530 +2024-11-21 13:33:33.885813: Current learning rate: 0.0094 +2024-11-21 13:33:52.953646: train_loss -0.7591 +2024-11-21 13:33:52.953853: val_loss -0.7307 +2024-11-21 13:33:52.954014: Pseudo dice [0.8258] +2024-11-21 13:33:52.954094: Epoch time: 19.07 s +2024-11-21 13:33:54.067477: +2024-11-21 13:33:54.067697: Epoch 531 +2024-11-21 13:33:54.067819: Current learning rate: 0.0094 +2024-11-21 13:34:13.972436: train_loss -0.7616 +2024-11-21 13:34:13.972667: val_loss -0.7467 +2024-11-21 13:34:13.972741: Pseudo dice [0.8402] +2024-11-21 13:34:13.972876: Epoch time: 19.91 s +2024-11-21 13:34:14.810950: +2024-11-21 13:34:14.811166: Epoch 532 +2024-11-21 13:34:14.811286: Current learning rate: 0.0094 +2024-11-21 13:34:33.683478: train_loss -0.7533 +2024-11-21 13:34:33.683688: val_loss -0.7229 +2024-11-21 13:34:33.683763: Pseudo dice [0.7686] +2024-11-21 13:34:33.683852: Epoch time: 18.87 s +2024-11-21 13:34:34.482799: +2024-11-21 13:34:34.483148: Epoch 533 +2024-11-21 13:34:34.483260: Current learning rate: 0.0094 +2024-11-21 13:34:53.739309: train_loss -0.7354 +2024-11-21 13:34:53.739547: val_loss -0.7216 +2024-11-21 13:34:53.739627: Pseudo dice [0.8017] +2024-11-21 13:34:53.739714: Epoch time: 19.26 s +2024-11-21 13:34:54.536306: +2024-11-21 13:34:54.537211: Epoch 534 +2024-11-21 13:34:54.537326: Current learning rate: 0.0094 +2024-11-21 13:35:12.991891: train_loss -0.7423 +2024-11-21 13:35:12.992106: val_loss -0.7367 +2024-11-21 13:35:12.992181: Pseudo dice [0.8139] +2024-11-21 13:35:12.992258: Epoch time: 18.46 s +2024-11-21 13:35:13.792024: +2024-11-21 13:35:13.792228: Epoch 535 +2024-11-21 13:35:13.792340: Current learning rate: 0.0094 +2024-11-21 13:35:32.777746: train_loss -0.7499 +2024-11-21 13:35:32.777959: val_loss -0.7555 +2024-11-21 13:35:32.778037: Pseudo dice [0.8242] +2024-11-21 13:35:32.778115: Epoch time: 18.99 s +2024-11-21 13:35:33.573916: +2024-11-21 13:35:33.574191: Epoch 536 +2024-11-21 13:35:33.574301: Current learning rate: 0.00939 +2024-11-21 13:35:52.168091: train_loss -0.7517 +2024-11-21 13:35:52.168403: val_loss -0.7371 +2024-11-21 13:35:52.168485: Pseudo dice [0.8033] +2024-11-21 13:35:52.168579: Epoch time: 18.59 s +2024-11-21 13:35:52.972279: +2024-11-21 13:35:52.972484: Epoch 537 +2024-11-21 13:35:52.972595: Current learning rate: 0.00939 +2024-11-21 13:36:10.891396: train_loss -0.7474 +2024-11-21 13:36:10.891617: val_loss -0.7123 +2024-11-21 13:36:10.891694: Pseudo dice [0.8015] +2024-11-21 13:36:10.891779: Epoch time: 17.92 s +2024-11-21 13:36:11.696888: +2024-11-21 13:36:11.697107: Epoch 538 +2024-11-21 13:36:11.697219: Current learning rate: 0.00939 +2024-11-21 13:36:31.088016: train_loss -0.7444 +2024-11-21 13:36:31.088227: val_loss -0.7405 +2024-11-21 13:36:31.088304: Pseudo dice [0.8389] +2024-11-21 13:36:31.088382: Epoch time: 19.39 s +2024-11-21 13:36:31.881008: +2024-11-21 13:36:31.881204: Epoch 539 +2024-11-21 13:36:31.881321: Current learning rate: 0.00939 +2024-11-21 13:36:50.372442: train_loss -0.7534 +2024-11-21 13:36:50.372645: val_loss -0.7269 +2024-11-21 13:36:50.372720: Pseudo dice [0.8313] +2024-11-21 13:36:50.372802: Epoch time: 18.49 s +2024-11-21 13:36:51.171454: +2024-11-21 13:36:51.171633: Epoch 540 +2024-11-21 13:36:51.171846: Current learning rate: 0.00939 +2024-11-21 13:37:09.041623: train_loss -0.76 +2024-11-21 13:37:09.041879: val_loss -0.7733 +2024-11-21 13:37:09.041960: Pseudo dice [0.8313] +2024-11-21 13:37:09.042058: Epoch time: 17.87 s +2024-11-21 13:37:09.838761: +2024-11-21 13:37:09.838946: Epoch 541 +2024-11-21 13:37:09.839067: Current learning rate: 0.00939 +2024-11-21 13:37:28.460534: train_loss -0.7443 +2024-11-21 13:37:28.460739: val_loss -0.7227 +2024-11-21 13:37:28.460815: Pseudo dice [0.8088] +2024-11-21 13:37:28.460891: Epoch time: 18.62 s +2024-11-21 13:37:29.249179: +2024-11-21 13:37:29.249371: Epoch 542 +2024-11-21 13:37:29.249485: Current learning rate: 0.00939 +2024-11-21 13:37:47.419881: train_loss -0.756 +2024-11-21 13:37:47.420096: val_loss -0.7154 +2024-11-21 13:37:47.420168: Pseudo dice [0.8276] +2024-11-21 13:37:47.420244: Epoch time: 18.17 s +2024-11-21 13:37:48.615048: +2024-11-21 13:37:48.615318: Epoch 543 +2024-11-21 13:37:48.615428: Current learning rate: 0.00939 +2024-11-21 13:38:07.206168: train_loss -0.7572 +2024-11-21 13:38:07.207289: val_loss -0.7276 +2024-11-21 13:38:07.207380: Pseudo dice [0.8024] +2024-11-21 13:38:07.207467: Epoch time: 18.59 s +2024-11-21 13:38:08.005110: +2024-11-21 13:38:08.005390: Epoch 544 +2024-11-21 13:38:08.005503: Current learning rate: 0.00939 +2024-11-21 13:38:27.633204: train_loss -0.7569 +2024-11-21 13:38:27.633417: val_loss -0.7194 +2024-11-21 13:38:27.633491: Pseudo dice [0.8029] +2024-11-21 13:38:27.633567: Epoch time: 19.63 s +2024-11-21 13:38:28.430032: +2024-11-21 13:38:28.430250: Epoch 545 +2024-11-21 13:38:28.430369: Current learning rate: 0.00938 +2024-11-21 13:38:47.896943: train_loss -0.7391 +2024-11-21 13:38:47.897197: val_loss -0.705 +2024-11-21 13:38:47.897279: Pseudo dice [0.8194] +2024-11-21 13:38:47.897362: Epoch time: 19.47 s +2024-11-21 13:38:48.695535: +2024-11-21 13:38:48.695739: Epoch 546 +2024-11-21 13:38:48.695854: Current learning rate: 0.00938 +2024-11-21 13:39:07.453657: train_loss -0.7376 +2024-11-21 13:39:07.453869: val_loss -0.7202 +2024-11-21 13:39:07.453943: Pseudo dice [0.8142] +2024-11-21 13:39:07.454782: Epoch time: 18.76 s +2024-11-21 13:39:08.249685: +2024-11-21 13:39:08.249877: Epoch 547 +2024-11-21 13:39:08.249987: Current learning rate: 0.00938 +2024-11-21 13:39:26.691905: train_loss -0.7524 +2024-11-21 13:39:26.692207: val_loss -0.7293 +2024-11-21 13:39:26.692283: Pseudo dice [0.8143] +2024-11-21 13:39:26.692366: Epoch time: 18.44 s +2024-11-21 13:39:27.492837: +2024-11-21 13:39:27.493037: Epoch 548 +2024-11-21 13:39:27.493149: Current learning rate: 0.00938 +2024-11-21 13:39:45.992772: train_loss -0.7404 +2024-11-21 13:39:45.992984: val_loss -0.6894 +2024-11-21 13:39:45.993065: Pseudo dice [0.7761] +2024-11-21 13:39:45.993139: Epoch time: 18.5 s +2024-11-21 13:39:46.788336: +2024-11-21 13:39:46.788575: Epoch 549 +2024-11-21 13:39:46.788694: Current learning rate: 0.00938 +2024-11-21 13:40:06.101229: train_loss -0.75 +2024-11-21 13:40:06.101450: val_loss -0.7474 +2024-11-21 13:40:06.101529: Pseudo dice [0.8222] +2024-11-21 13:40:06.101606: Epoch time: 19.31 s +2024-11-21 13:40:07.126910: +2024-11-21 13:40:07.127107: Epoch 550 +2024-11-21 13:40:07.127230: Current learning rate: 0.00938 +2024-11-21 13:40:26.332050: train_loss -0.7574 +2024-11-21 13:40:26.332259: val_loss -0.7209 +2024-11-21 13:40:26.332331: Pseudo dice [0.8171] +2024-11-21 13:40:26.332410: Epoch time: 19.21 s +2024-11-21 13:40:27.135513: +2024-11-21 13:40:27.135859: Epoch 551 +2024-11-21 13:40:27.136016: Current learning rate: 0.00938 +2024-11-21 13:40:46.560694: train_loss -0.7621 +2024-11-21 13:40:46.566122: val_loss -0.7305 +2024-11-21 13:40:46.566261: Pseudo dice [0.8084] +2024-11-21 13:40:46.566351: Epoch time: 19.43 s +2024-11-21 13:40:47.458740: +2024-11-21 13:40:47.459018: Epoch 552 +2024-11-21 13:40:47.459131: Current learning rate: 0.00938 +2024-11-21 13:41:05.769939: train_loss -0.7501 +2024-11-21 13:41:05.770277: val_loss -0.6944 +2024-11-21 13:41:05.770358: Pseudo dice [0.7987] +2024-11-21 13:41:05.770439: Epoch time: 18.31 s +2024-11-21 13:41:06.575976: +2024-11-21 13:41:06.576175: Epoch 553 +2024-11-21 13:41:06.576290: Current learning rate: 0.00938 +2024-11-21 13:41:26.402842: train_loss -0.7484 +2024-11-21 13:41:26.403051: val_loss -0.7528 +2024-11-21 13:41:26.403125: Pseudo dice [0.8105] +2024-11-21 13:41:26.403203: Epoch time: 19.83 s +2024-11-21 13:41:27.203312: +2024-11-21 13:41:27.203510: Epoch 554 +2024-11-21 13:41:27.203620: Current learning rate: 0.00937 +2024-11-21 13:41:45.858423: train_loss -0.7602 +2024-11-21 13:41:45.858668: val_loss -0.7327 +2024-11-21 13:41:45.858742: Pseudo dice [0.8155] +2024-11-21 13:41:45.858824: Epoch time: 18.66 s +2024-11-21 13:41:46.656028: +2024-11-21 13:41:46.656222: Epoch 555 +2024-11-21 13:41:46.656342: Current learning rate: 0.00937 +2024-11-21 13:42:04.956732: train_loss -0.7648 +2024-11-21 13:42:04.956944: val_loss -0.7086 +2024-11-21 13:42:04.957025: Pseudo dice [0.8191] +2024-11-21 13:42:04.957100: Epoch time: 18.3 s +2024-11-21 13:42:05.757687: +2024-11-21 13:42:05.757911: Epoch 556 +2024-11-21 13:42:05.758041: Current learning rate: 0.00937 +2024-11-21 13:42:24.654758: train_loss -0.7533 +2024-11-21 13:42:24.654982: val_loss -0.7255 +2024-11-21 13:42:24.655063: Pseudo dice [0.8265] +2024-11-21 13:42:24.660278: Epoch time: 18.9 s +2024-11-21 13:42:25.565370: +2024-11-21 13:42:25.565647: Epoch 557 +2024-11-21 13:42:25.565760: Current learning rate: 0.00937 +2024-11-21 13:42:45.114799: train_loss -0.7609 +2024-11-21 13:42:45.115048: val_loss -0.7404 +2024-11-21 13:42:45.115124: Pseudo dice [0.8233] +2024-11-21 13:42:45.115208: Epoch time: 19.55 s +2024-11-21 13:42:45.963773: +2024-11-21 13:42:45.963959: Epoch 558 +2024-11-21 13:42:45.964080: Current learning rate: 0.00937 +2024-11-21 13:43:06.462812: train_loss -0.7596 +2024-11-21 13:43:06.463036: val_loss -0.7533 +2024-11-21 13:43:06.463112: Pseudo dice [0.8298] +2024-11-21 13:43:06.463187: Epoch time: 20.5 s +2024-11-21 13:43:07.263835: +2024-11-21 13:43:07.264040: Epoch 559 +2024-11-21 13:43:07.264149: Current learning rate: 0.00937 +2024-11-21 13:43:27.306064: train_loss -0.7534 +2024-11-21 13:43:27.306778: val_loss -0.749 +2024-11-21 13:43:27.306859: Pseudo dice [0.805] +2024-11-21 13:43:27.306935: Epoch time: 20.04 s +2024-11-21 13:43:28.103282: +2024-11-21 13:43:28.103469: Epoch 560 +2024-11-21 13:43:28.103580: Current learning rate: 0.00937 +2024-11-21 13:43:46.974557: train_loss -0.7553 +2024-11-21 13:43:46.976775: val_loss -0.7272 +2024-11-21 13:43:46.976948: Pseudo dice [0.8125] +2024-11-21 13:43:46.977036: Epoch time: 18.87 s +2024-11-21 13:43:47.786783: +2024-11-21 13:43:47.787037: Epoch 561 +2024-11-21 13:43:47.787175: Current learning rate: 0.00937 +2024-11-21 13:44:07.409102: train_loss -0.753 +2024-11-21 13:44:07.409345: val_loss -0.722 +2024-11-21 13:44:07.409421: Pseudo dice [0.8189] +2024-11-21 13:44:07.409504: Epoch time: 19.62 s +2024-11-21 13:44:08.211194: +2024-11-21 13:44:08.211391: Epoch 562 +2024-11-21 13:44:08.211504: Current learning rate: 0.00937 +2024-11-21 13:44:26.953076: train_loss -0.7615 +2024-11-21 13:44:26.955458: val_loss -0.7327 +2024-11-21 13:44:26.955553: Pseudo dice [0.8288] +2024-11-21 13:44:26.955631: Epoch time: 18.74 s +2024-11-21 13:44:27.779940: +2024-11-21 13:44:27.780173: Epoch 563 +2024-11-21 13:44:27.780288: Current learning rate: 0.00936 +2024-11-21 13:44:46.482084: train_loss -0.7675 +2024-11-21 13:44:46.482300: val_loss -0.7049 +2024-11-21 13:44:46.482374: Pseudo dice [0.7992] +2024-11-21 13:44:46.482453: Epoch time: 18.7 s +2024-11-21 13:44:47.279258: +2024-11-21 13:44:47.279498: Epoch 564 +2024-11-21 13:44:47.279612: Current learning rate: 0.00936 +2024-11-21 13:45:05.366198: train_loss -0.7628 +2024-11-21 13:45:05.366444: val_loss -0.7317 +2024-11-21 13:45:05.366518: Pseudo dice [0.8161] +2024-11-21 13:45:05.366606: Epoch time: 18.09 s +2024-11-21 13:45:06.176363: +2024-11-21 13:45:06.176627: Epoch 565 +2024-11-21 13:45:06.176741: Current learning rate: 0.00936 +2024-11-21 13:45:24.214868: train_loss -0.7589 +2024-11-21 13:45:24.215098: val_loss -0.7262 +2024-11-21 13:45:24.215178: Pseudo dice [0.8225] +2024-11-21 13:45:24.215257: Epoch time: 18.04 s +2024-11-21 13:45:25.404197: +2024-11-21 13:45:25.404393: Epoch 566 +2024-11-21 13:45:25.404507: Current learning rate: 0.00936 +2024-11-21 13:45:43.813399: train_loss -0.7642 +2024-11-21 13:45:43.813638: val_loss -0.7301 +2024-11-21 13:45:43.813711: Pseudo dice [0.8253] +2024-11-21 13:45:43.813788: Epoch time: 18.41 s +2024-11-21 13:45:44.655784: +2024-11-21 13:45:44.656150: Epoch 567 +2024-11-21 13:45:44.656267: Current learning rate: 0.00936 +2024-11-21 13:46:04.169434: train_loss -0.7516 +2024-11-21 13:46:04.169647: val_loss -0.7446 +2024-11-21 13:46:04.169725: Pseudo dice [0.8417] +2024-11-21 13:46:04.171985: Epoch time: 19.51 s +2024-11-21 13:46:05.085202: +2024-11-21 13:46:05.085427: Epoch 568 +2024-11-21 13:46:05.085544: Current learning rate: 0.00936 +2024-11-21 13:46:23.165325: train_loss -0.7557 +2024-11-21 13:46:23.166347: val_loss -0.7253 +2024-11-21 13:46:23.166425: Pseudo dice [0.8186] +2024-11-21 13:46:23.166506: Epoch time: 18.08 s +2024-11-21 13:46:23.963299: +2024-11-21 13:46:23.963489: Epoch 569 +2024-11-21 13:46:23.963599: Current learning rate: 0.00936 +2024-11-21 13:46:43.181702: train_loss -0.7557 +2024-11-21 13:46:43.181927: val_loss -0.7468 +2024-11-21 13:46:43.182005: Pseudo dice [0.8301] +2024-11-21 13:46:43.182087: Epoch time: 19.22 s +2024-11-21 13:46:43.983077: +2024-11-21 13:46:43.983296: Epoch 570 +2024-11-21 13:46:43.983414: Current learning rate: 0.00936 +2024-11-21 13:47:03.520398: train_loss -0.7561 +2024-11-21 13:47:03.521262: val_loss -0.6939 +2024-11-21 13:47:03.521343: Pseudo dice [0.7985] +2024-11-21 13:47:03.521420: Epoch time: 19.54 s +2024-11-21 13:47:04.383915: +2024-11-21 13:47:04.384180: Epoch 571 +2024-11-21 13:47:04.384304: Current learning rate: 0.00936 +2024-11-21 13:47:23.370875: train_loss -0.7468 +2024-11-21 13:47:23.371129: val_loss -0.7257 +2024-11-21 13:47:23.371205: Pseudo dice [0.784] +2024-11-21 13:47:23.371294: Epoch time: 18.99 s +2024-11-21 13:47:24.275380: +2024-11-21 13:47:24.275597: Epoch 572 +2024-11-21 13:47:24.275717: Current learning rate: 0.00935 +2024-11-21 13:47:43.594201: train_loss -0.7615 +2024-11-21 13:47:43.594412: val_loss -0.7385 +2024-11-21 13:47:43.594487: Pseudo dice [0.8285] +2024-11-21 13:47:43.594563: Epoch time: 19.32 s +2024-11-21 13:47:44.400367: +2024-11-21 13:47:44.400605: Epoch 573 +2024-11-21 13:47:44.400721: Current learning rate: 0.00935 +2024-11-21 13:48:03.788891: train_loss -0.7602 +2024-11-21 13:48:03.789109: val_loss -0.7123 +2024-11-21 13:48:03.791375: Pseudo dice [0.8133] +2024-11-21 13:48:03.791469: Epoch time: 19.39 s +2024-11-21 13:48:04.720329: +2024-11-21 13:48:04.720517: Epoch 574 +2024-11-21 13:48:04.720636: Current learning rate: 0.00935 +2024-11-21 13:48:24.608922: train_loss -0.7641 +2024-11-21 13:48:24.609133: val_loss -0.7384 +2024-11-21 13:48:24.609230: Pseudo dice [0.8079] +2024-11-21 13:48:24.609307: Epoch time: 19.89 s +2024-11-21 13:48:25.418661: +2024-11-21 13:48:25.418851: Epoch 575 +2024-11-21 13:48:25.418965: Current learning rate: 0.00935 +2024-11-21 13:48:43.955184: train_loss -0.7602 +2024-11-21 13:48:43.955410: val_loss -0.7433 +2024-11-21 13:48:43.955490: Pseudo dice [0.8268] +2024-11-21 13:48:43.955573: Epoch time: 18.54 s +2024-11-21 13:48:44.764512: +2024-11-21 13:48:44.764720: Epoch 576 +2024-11-21 13:48:44.764840: Current learning rate: 0.00935 +2024-11-21 13:49:03.860445: train_loss -0.7552 +2024-11-21 13:49:03.865027: val_loss -0.7337 +2024-11-21 13:49:03.865170: Pseudo dice [0.8083] +2024-11-21 13:49:03.865257: Epoch time: 19.1 s +2024-11-21 13:49:04.676525: +2024-11-21 13:49:04.676737: Epoch 577 +2024-11-21 13:49:04.676857: Current learning rate: 0.00935 +2024-11-21 13:49:22.840207: train_loss -0.7543 +2024-11-21 13:49:22.840422: val_loss -0.731 +2024-11-21 13:49:22.840498: Pseudo dice [0.8085] +2024-11-21 13:49:22.840575: Epoch time: 18.16 s +2024-11-21 13:49:24.028208: +2024-11-21 13:49:24.028435: Epoch 578 +2024-11-21 13:49:24.028549: Current learning rate: 0.00935 +2024-11-21 13:49:43.161767: train_loss -0.7598 +2024-11-21 13:49:43.164924: val_loss -0.7361 +2024-11-21 13:49:43.165059: Pseudo dice [0.8185] +2024-11-21 13:49:43.165157: Epoch time: 19.13 s +2024-11-21 13:49:44.037648: +2024-11-21 13:49:44.037869: Epoch 579 +2024-11-21 13:49:44.037990: Current learning rate: 0.00935 +2024-11-21 13:50:03.105573: train_loss -0.7584 +2024-11-21 13:50:03.105800: val_loss -0.7398 +2024-11-21 13:50:03.105874: Pseudo dice [0.8374] +2024-11-21 13:50:03.105948: Epoch time: 19.07 s +2024-11-21 13:50:03.912443: +2024-11-21 13:50:03.912654: Epoch 580 +2024-11-21 13:50:03.912796: Current learning rate: 0.00935 +2024-11-21 13:50:23.073791: train_loss -0.7568 +2024-11-21 13:50:23.074007: val_loss -0.7383 +2024-11-21 13:50:23.074085: Pseudo dice [0.8352] +2024-11-21 13:50:23.074160: Epoch time: 19.16 s +2024-11-21 13:50:23.879033: +2024-11-21 13:50:23.879214: Epoch 581 +2024-11-21 13:50:23.879336: Current learning rate: 0.00934 +2024-11-21 13:50:44.052666: train_loss -0.7613 +2024-11-21 13:50:44.052901: val_loss -0.7278 +2024-11-21 13:50:44.052976: Pseudo dice [0.8172] +2024-11-21 13:50:44.053066: Epoch time: 20.17 s +2024-11-21 13:50:44.862078: +2024-11-21 13:50:44.862307: Epoch 582 +2024-11-21 13:50:44.862425: Current learning rate: 0.00934 +2024-11-21 13:51:03.653343: train_loss -0.7638 +2024-11-21 13:51:03.653555: val_loss -0.7374 +2024-11-21 13:51:03.653629: Pseudo dice [0.8321] +2024-11-21 13:51:03.653706: Epoch time: 18.79 s +2024-11-21 13:51:04.467079: +2024-11-21 13:51:04.467289: Epoch 583 +2024-11-21 13:51:04.467402: Current learning rate: 0.00934 +2024-11-21 13:51:25.368376: train_loss -0.761 +2024-11-21 13:51:25.368594: val_loss -0.7342 +2024-11-21 13:51:25.368668: Pseudo dice [0.7962] +2024-11-21 13:51:25.368744: Epoch time: 20.9 s +2024-11-21 13:51:26.208482: +2024-11-21 13:51:26.208672: Epoch 584 +2024-11-21 13:51:26.208783: Current learning rate: 0.00934 +2024-11-21 13:51:44.799227: train_loss -0.7595 +2024-11-21 13:51:44.799479: val_loss -0.7329 +2024-11-21 13:51:44.799557: Pseudo dice [0.8165] +2024-11-21 13:51:44.799634: Epoch time: 18.59 s +2024-11-21 13:51:45.632134: +2024-11-21 13:51:45.632330: Epoch 585 +2024-11-21 13:51:45.632444: Current learning rate: 0.00934 +2024-11-21 13:52:02.997861: train_loss -0.754 +2024-11-21 13:52:03.003239: val_loss -0.7199 +2024-11-21 13:52:03.003355: Pseudo dice [0.8274] +2024-11-21 13:52:03.003449: Epoch time: 17.37 s +2024-11-21 13:52:03.991344: +2024-11-21 13:52:03.991544: Epoch 586 +2024-11-21 13:52:03.991653: Current learning rate: 0.00934 +2024-11-21 13:52:22.211069: train_loss -0.7419 +2024-11-21 13:52:22.211283: val_loss -0.7178 +2024-11-21 13:52:22.211356: Pseudo dice [0.8076] +2024-11-21 13:52:22.213662: Epoch time: 18.22 s +2024-11-21 13:52:23.097112: +2024-11-21 13:52:23.097311: Epoch 587 +2024-11-21 13:52:23.097419: Current learning rate: 0.00934 +2024-11-21 13:52:41.795399: train_loss -0.7463 +2024-11-21 13:52:41.795620: val_loss -0.7638 +2024-11-21 13:52:41.795695: Pseudo dice [0.823] +2024-11-21 13:52:41.795775: Epoch time: 18.7 s +2024-11-21 13:52:42.618461: +2024-11-21 13:52:42.618636: Epoch 588 +2024-11-21 13:52:42.618745: Current learning rate: 0.00934 +2024-11-21 13:53:01.958766: train_loss -0.7492 +2024-11-21 13:53:01.959031: val_loss -0.7311 +2024-11-21 13:53:01.959113: Pseudo dice [0.8068] +2024-11-21 13:53:01.959197: Epoch time: 19.34 s +2024-11-21 13:53:02.765543: +2024-11-21 13:53:02.765739: Epoch 589 +2024-11-21 13:53:02.765850: Current learning rate: 0.00933 +2024-11-21 13:53:21.350733: train_loss -0.7524 +2024-11-21 13:53:21.350966: val_loss -0.7343 +2024-11-21 13:53:21.351052: Pseudo dice [0.8197] +2024-11-21 13:53:21.351150: Epoch time: 18.59 s +2024-11-21 13:53:22.152648: +2024-11-21 13:53:22.152899: Epoch 590 +2024-11-21 13:53:22.153014: Current learning rate: 0.00933 +2024-11-21 13:53:40.928379: train_loss -0.7627 +2024-11-21 13:53:40.928605: val_loss -0.7253 +2024-11-21 13:53:40.928754: Pseudo dice [0.815] +2024-11-21 13:53:40.928838: Epoch time: 18.78 s +2024-11-21 13:53:41.729469: +2024-11-21 13:53:41.729677: Epoch 591 +2024-11-21 13:53:41.729791: Current learning rate: 0.00933 +2024-11-21 13:54:01.104646: train_loss -0.7647 +2024-11-21 13:54:01.104864: val_loss -0.7198 +2024-11-21 13:54:01.104939: Pseudo dice [0.8224] +2024-11-21 13:54:01.105029: Epoch time: 19.38 s +2024-11-21 13:54:01.909116: +2024-11-21 13:54:01.909316: Epoch 592 +2024-11-21 13:54:01.909452: Current learning rate: 0.00933 +2024-11-21 13:54:19.934235: train_loss -0.7507 +2024-11-21 13:54:19.934447: val_loss -0.7457 +2024-11-21 13:54:19.934525: Pseudo dice [0.8291] +2024-11-21 13:54:19.934624: Epoch time: 18.03 s +2024-11-21 13:54:20.923635: +2024-11-21 13:54:20.923860: Epoch 593 +2024-11-21 13:54:20.923974: Current learning rate: 0.00933 +2024-11-21 13:54:39.751286: train_loss -0.7555 +2024-11-21 13:54:39.751492: val_loss -0.7486 +2024-11-21 13:54:39.751570: Pseudo dice [0.8189] +2024-11-21 13:54:39.751645: Epoch time: 18.83 s +2024-11-21 13:54:40.559124: +2024-11-21 13:54:40.559346: Epoch 594 +2024-11-21 13:54:40.559457: Current learning rate: 0.00933 +2024-11-21 13:54:59.004719: train_loss -0.7507 +2024-11-21 13:54:59.004931: val_loss -0.7456 +2024-11-21 13:54:59.005010: Pseudo dice [0.8304] +2024-11-21 13:54:59.005085: Epoch time: 18.45 s +2024-11-21 13:54:59.813861: +2024-11-21 13:54:59.814067: Epoch 595 +2024-11-21 13:54:59.814180: Current learning rate: 0.00933 +2024-11-21 13:55:17.988455: train_loss -0.7691 +2024-11-21 13:55:17.988661: val_loss -0.7453 +2024-11-21 13:55:17.988734: Pseudo dice [0.8404] +2024-11-21 13:55:17.988810: Epoch time: 18.18 s +2024-11-21 13:55:17.988872: Yayy! New best EMA pseudo Dice: 0.822 +2024-11-21 13:55:19.017372: +2024-11-21 13:55:19.017572: Epoch 596 +2024-11-21 13:55:19.017684: Current learning rate: 0.00933 +2024-11-21 13:55:37.713688: train_loss -0.7515 +2024-11-21 13:55:37.713915: val_loss -0.712 +2024-11-21 13:55:37.713987: Pseudo dice [0.8404] +2024-11-21 13:55:37.714099: Epoch time: 18.7 s +2024-11-21 13:55:37.714217: Yayy! New best EMA pseudo Dice: 0.8238 +2024-11-21 13:55:38.755132: +2024-11-21 13:55:38.755324: Epoch 597 +2024-11-21 13:55:38.755430: Current learning rate: 0.00933 +2024-11-21 13:55:56.900613: train_loss -0.7539 +2024-11-21 13:55:56.900821: val_loss -0.7577 +2024-11-21 13:55:56.900896: Pseudo dice [0.8334] +2024-11-21 13:55:56.900973: Epoch time: 18.15 s +2024-11-21 13:55:56.901045: Yayy! New best EMA pseudo Dice: 0.8248 +2024-11-21 13:55:57.945438: +2024-11-21 13:55:57.945637: Epoch 598 +2024-11-21 13:55:57.945760: Current learning rate: 0.00932 +2024-11-21 13:56:16.482155: train_loss -0.7611 +2024-11-21 13:56:16.485212: val_loss -0.7538 +2024-11-21 13:56:16.485317: Pseudo dice [0.8249] +2024-11-21 13:56:16.485396: Epoch time: 18.54 s +2024-11-21 13:56:16.485461: Yayy! New best EMA pseudo Dice: 0.8248 +2024-11-21 13:56:17.535502: +2024-11-21 13:56:17.535686: Epoch 599 +2024-11-21 13:56:17.535800: Current learning rate: 0.00932 +2024-11-21 13:56:35.705581: train_loss -0.7539 +2024-11-21 13:56:35.705801: val_loss -0.7326 +2024-11-21 13:56:35.705876: Pseudo dice [0.8181] +2024-11-21 13:56:35.705957: Epoch time: 18.17 s +2024-11-21 13:56:37.303321: +2024-11-21 13:56:37.303526: Epoch 600 +2024-11-21 13:56:37.303640: Current learning rate: 0.00932 +2024-11-21 13:56:55.777412: train_loss -0.763 +2024-11-21 13:56:55.777611: val_loss -0.7539 +2024-11-21 13:56:55.777681: Pseudo dice [0.8146] +2024-11-21 13:56:55.779981: Epoch time: 18.47 s +2024-11-21 13:56:56.691160: +2024-11-21 13:56:56.691361: Epoch 601 +2024-11-21 13:56:56.691475: Current learning rate: 0.00932 +2024-11-21 13:57:14.627485: train_loss -0.7591 +2024-11-21 13:57:14.627698: val_loss -0.7449 +2024-11-21 13:57:14.627771: Pseudo dice [0.824] +2024-11-21 13:57:14.627848: Epoch time: 17.94 s +2024-11-21 13:57:15.424174: +2024-11-21 13:57:15.424381: Epoch 602 +2024-11-21 13:57:15.424494: Current learning rate: 0.00932 +2024-11-21 13:57:34.849746: train_loss -0.767 +2024-11-21 13:57:34.853747: val_loss -0.7407 +2024-11-21 13:57:34.853862: Pseudo dice [0.8287] +2024-11-21 13:57:34.853950: Epoch time: 19.43 s +2024-11-21 13:57:35.653535: +2024-11-21 13:57:35.653711: Epoch 603 +2024-11-21 13:57:35.653817: Current learning rate: 0.00932 +2024-11-21 13:57:54.055845: train_loss -0.7672 +2024-11-21 13:57:54.056086: val_loss -0.7302 +2024-11-21 13:57:54.056159: Pseudo dice [0.8108] +2024-11-21 13:57:54.056236: Epoch time: 18.4 s +2024-11-21 13:57:54.857927: +2024-11-21 13:57:54.858143: Epoch 604 +2024-11-21 13:57:54.858256: Current learning rate: 0.00932 +2024-11-21 13:58:13.773965: train_loss -0.7737 +2024-11-21 13:58:13.774168: val_loss -0.7486 +2024-11-21 13:58:13.774241: Pseudo dice [0.825] +2024-11-21 13:58:13.774314: Epoch time: 18.92 s +2024-11-21 13:58:14.576547: +2024-11-21 13:58:14.576759: Epoch 605 +2024-11-21 13:58:14.576876: Current learning rate: 0.00932 +2024-11-21 13:58:33.440011: train_loss -0.7758 +2024-11-21 13:58:33.440269: val_loss -0.7189 +2024-11-21 13:58:33.440344: Pseudo dice [0.8328] +2024-11-21 13:58:33.440420: Epoch time: 18.86 s +2024-11-21 13:58:34.238373: +2024-11-21 13:58:34.238546: Epoch 606 +2024-11-21 13:58:34.238653: Current learning rate: 0.00932 +2024-11-21 13:58:52.601845: train_loss -0.7455 +2024-11-21 13:58:52.602069: val_loss -0.7444 +2024-11-21 13:58:52.602205: Pseudo dice [0.8266] +2024-11-21 13:58:52.602283: Epoch time: 18.36 s +2024-11-21 13:58:53.509146: +2024-11-21 13:58:53.509446: Epoch 607 +2024-11-21 13:58:53.509564: Current learning rate: 0.00931 +2024-11-21 13:59:10.963817: train_loss -0.7556 +2024-11-21 13:59:10.964059: val_loss -0.7236 +2024-11-21 13:59:10.964136: Pseudo dice [0.797] +2024-11-21 13:59:10.964220: Epoch time: 17.46 s +2024-11-21 13:59:11.801670: +2024-11-21 13:59:11.801873: Epoch 608 +2024-11-21 13:59:11.801989: Current learning rate: 0.00931 +2024-11-21 13:59:30.388564: train_loss -0.7514 +2024-11-21 13:59:30.388768: val_loss -0.746 +2024-11-21 13:59:30.388840: Pseudo dice [0.8224] +2024-11-21 13:59:30.388913: Epoch time: 18.59 s +2024-11-21 13:59:31.198834: +2024-11-21 13:59:31.199012: Epoch 609 +2024-11-21 13:59:31.199151: Current learning rate: 0.00931 +2024-11-21 13:59:49.289758: train_loss -0.7628 +2024-11-21 13:59:49.289956: val_loss -0.7387 +2024-11-21 13:59:49.290041: Pseudo dice [0.8161] +2024-11-21 13:59:49.290120: Epoch time: 18.09 s +2024-11-21 13:59:50.104818: +2024-11-21 13:59:50.105022: Epoch 610 +2024-11-21 13:59:50.105136: Current learning rate: 0.00931 +2024-11-21 14:00:08.485426: train_loss -0.746 +2024-11-21 14:00:08.485660: val_loss -0.7342 +2024-11-21 14:00:08.485731: Pseudo dice [0.8251] +2024-11-21 14:00:08.485812: Epoch time: 18.38 s +2024-11-21 14:00:09.296408: +2024-11-21 14:00:09.296581: Epoch 611 +2024-11-21 14:00:09.296698: Current learning rate: 0.00931 +2024-11-21 14:00:28.861089: train_loss -0.7536 +2024-11-21 14:00:28.861304: val_loss -0.716 +2024-11-21 14:00:28.861381: Pseudo dice [0.7976] +2024-11-21 14:00:28.861459: Epoch time: 19.57 s +2024-11-21 14:00:29.675478: +2024-11-21 14:00:29.675689: Epoch 612 +2024-11-21 14:00:29.675799: Current learning rate: 0.00931 +2024-11-21 14:00:48.419467: train_loss -0.7654 +2024-11-21 14:00:48.419688: val_loss -0.7402 +2024-11-21 14:00:48.419762: Pseudo dice [0.8162] +2024-11-21 14:00:48.419838: Epoch time: 18.74 s +2024-11-21 14:00:49.230932: +2024-11-21 14:00:49.231144: Epoch 613 +2024-11-21 14:00:49.231256: Current learning rate: 0.00931 +2024-11-21 14:01:08.216148: train_loss -0.7674 +2024-11-21 14:01:08.216447: val_loss -0.7365 +2024-11-21 14:01:08.216525: Pseudo dice [0.8197] +2024-11-21 14:01:08.216611: Epoch time: 18.99 s +2024-11-21 14:01:09.089529: +2024-11-21 14:01:09.089726: Epoch 614 +2024-11-21 14:01:09.089838: Current learning rate: 0.00931 +2024-11-21 14:01:27.158041: train_loss -0.7572 +2024-11-21 14:01:27.160434: val_loss -0.7371 +2024-11-21 14:01:27.160562: Pseudo dice [0.8349] +2024-11-21 14:01:27.160642: Epoch time: 18.07 s +2024-11-21 14:01:28.062323: +2024-11-21 14:01:28.062699: Epoch 615 +2024-11-21 14:01:28.062814: Current learning rate: 0.00931 +2024-11-21 14:01:47.342318: train_loss -0.7482 +2024-11-21 14:01:47.342534: val_loss -0.7379 +2024-11-21 14:01:47.346134: Pseudo dice [0.795] +2024-11-21 14:01:47.346274: Epoch time: 19.28 s +2024-11-21 14:01:48.164615: +2024-11-21 14:01:48.164823: Epoch 616 +2024-11-21 14:01:48.164938: Current learning rate: 0.0093 +2024-11-21 14:02:06.757793: train_loss -0.7684 +2024-11-21 14:02:06.758605: val_loss -0.7308 +2024-11-21 14:02:06.758688: Pseudo dice [0.8098] +2024-11-21 14:02:06.758766: Epoch time: 18.59 s +2024-11-21 14:02:07.572077: +2024-11-21 14:02:07.572257: Epoch 617 +2024-11-21 14:02:07.572369: Current learning rate: 0.0093 +2024-11-21 14:02:27.623580: train_loss -0.772 +2024-11-21 14:02:27.623813: val_loss -0.7411 +2024-11-21 14:02:27.623891: Pseudo dice [0.8164] +2024-11-21 14:02:27.623973: Epoch time: 20.05 s +2024-11-21 14:02:28.469061: +2024-11-21 14:02:28.469240: Epoch 618 +2024-11-21 14:02:28.469352: Current learning rate: 0.0093 +2024-11-21 14:02:46.087076: train_loss -0.7639 +2024-11-21 14:02:46.087286: val_loss -0.7517 +2024-11-21 14:02:46.087361: Pseudo dice [0.8352] +2024-11-21 14:02:46.087440: Epoch time: 17.62 s +2024-11-21 14:02:46.938891: +2024-11-21 14:02:46.939112: Epoch 619 +2024-11-21 14:02:46.939231: Current learning rate: 0.0093 +2024-11-21 14:03:05.655631: train_loss -0.7592 +2024-11-21 14:03:05.655844: val_loss -0.7545 +2024-11-21 14:03:05.655918: Pseudo dice [0.8045] +2024-11-21 14:03:05.655998: Epoch time: 18.72 s +2024-11-21 14:03:06.449050: +2024-11-21 14:03:06.449229: Epoch 620 +2024-11-21 14:03:06.449346: Current learning rate: 0.0093 +2024-11-21 14:03:24.496976: train_loss -0.7653 +2024-11-21 14:03:24.497190: val_loss -0.7319 +2024-11-21 14:03:24.497264: Pseudo dice [0.7989] +2024-11-21 14:03:24.497415: Epoch time: 18.05 s +2024-11-21 14:03:25.473925: +2024-11-21 14:03:25.474120: Epoch 621 +2024-11-21 14:03:25.474232: Current learning rate: 0.0093 +2024-11-21 14:03:44.827606: train_loss -0.7648 +2024-11-21 14:03:44.827851: val_loss -0.7153 +2024-11-21 14:03:44.827926: Pseudo dice [0.8136] +2024-11-21 14:03:44.828016: Epoch time: 19.35 s +2024-11-21 14:03:45.635016: +2024-11-21 14:03:45.635197: Epoch 622 +2024-11-21 14:03:45.635308: Current learning rate: 0.0093 +2024-11-21 14:04:05.731507: train_loss -0.7633 +2024-11-21 14:04:05.731711: val_loss -0.7436 +2024-11-21 14:04:05.731784: Pseudo dice [0.8145] +2024-11-21 14:04:05.731860: Epoch time: 20.1 s +2024-11-21 14:04:06.985407: +2024-11-21 14:04:06.985731: Epoch 623 +2024-11-21 14:04:06.985892: Current learning rate: 0.0093 +2024-11-21 14:04:26.394703: train_loss -0.7559 +2024-11-21 14:04:26.394970: val_loss -0.735 +2024-11-21 14:04:26.395048: Pseudo dice [0.7997] +2024-11-21 14:04:26.395124: Epoch time: 19.41 s +2024-11-21 14:04:27.204908: +2024-11-21 14:04:27.205132: Epoch 624 +2024-11-21 14:04:27.205249: Current learning rate: 0.0093 +2024-11-21 14:04:46.948056: train_loss -0.7577 +2024-11-21 14:04:46.948316: val_loss -0.7448 +2024-11-21 14:04:46.948392: Pseudo dice [0.8413] +2024-11-21 14:04:46.948477: Epoch time: 19.74 s +2024-11-21 14:04:47.936739: +2024-11-21 14:04:47.936977: Epoch 625 +2024-11-21 14:04:47.937094: Current learning rate: 0.00929 +2024-11-21 14:05:06.381878: train_loss -0.7646 +2024-11-21 14:05:06.382094: val_loss -0.7447 +2024-11-21 14:05:06.382170: Pseudo dice [0.8131] +2024-11-21 14:05:06.382308: Epoch time: 18.45 s +2024-11-21 14:05:07.259243: +2024-11-21 14:05:07.259454: Epoch 626 +2024-11-21 14:05:07.259596: Current learning rate: 0.00929 +2024-11-21 14:05:25.430927: train_loss -0.7843 +2024-11-21 14:05:25.431256: val_loss -0.7144 +2024-11-21 14:05:25.431338: Pseudo dice [0.8317] +2024-11-21 14:05:25.431418: Epoch time: 18.17 s +2024-11-21 14:05:26.257376: +2024-11-21 14:05:26.257571: Epoch 627 +2024-11-21 14:05:26.257682: Current learning rate: 0.00929 +2024-11-21 14:05:46.280946: train_loss -0.7583 +2024-11-21 14:05:46.281384: val_loss -0.7387 +2024-11-21 14:05:46.281465: Pseudo dice [0.811] +2024-11-21 14:05:46.281543: Epoch time: 20.02 s +2024-11-21 14:05:47.228138: +2024-11-21 14:05:47.228329: Epoch 628 +2024-11-21 14:05:47.228439: Current learning rate: 0.00929 +2024-11-21 14:06:05.901836: train_loss -0.7667 +2024-11-21 14:06:05.902085: val_loss -0.7401 +2024-11-21 14:06:05.902159: Pseudo dice [0.8288] +2024-11-21 14:06:05.902239: Epoch time: 18.67 s +2024-11-21 14:06:06.728065: +2024-11-21 14:06:06.728280: Epoch 629 +2024-11-21 14:06:06.728416: Current learning rate: 0.00929 +2024-11-21 14:06:25.519565: train_loss -0.7689 +2024-11-21 14:06:25.519761: val_loss -0.7439 +2024-11-21 14:06:25.519830: Pseudo dice [0.8187] +2024-11-21 14:06:25.519902: Epoch time: 18.79 s +2024-11-21 14:06:26.355497: +2024-11-21 14:06:26.355695: Epoch 630 +2024-11-21 14:06:26.355808: Current learning rate: 0.00929 +2024-11-21 14:06:44.550158: train_loss -0.7653 +2024-11-21 14:06:44.550369: val_loss -0.7156 +2024-11-21 14:06:44.550442: Pseudo dice [0.8356] +2024-11-21 14:06:44.550516: Epoch time: 18.2 s +2024-11-21 14:06:45.355799: +2024-11-21 14:06:45.356123: Epoch 631 +2024-11-21 14:06:45.356237: Current learning rate: 0.00929 +2024-11-21 14:07:04.811819: train_loss -0.7688 +2024-11-21 14:07:04.812052: val_loss -0.7499 +2024-11-21 14:07:04.812125: Pseudo dice [0.8291] +2024-11-21 14:07:04.812208: Epoch time: 19.46 s +2024-11-21 14:07:05.639249: +2024-11-21 14:07:05.639422: Epoch 632 +2024-11-21 14:07:05.639535: Current learning rate: 0.00929 +2024-11-21 14:07:23.800244: train_loss -0.7476 +2024-11-21 14:07:23.800442: val_loss -0.7343 +2024-11-21 14:07:23.800513: Pseudo dice [0.815] +2024-11-21 14:07:23.800586: Epoch time: 18.16 s +2024-11-21 14:07:24.635097: +2024-11-21 14:07:24.635389: Epoch 633 +2024-11-21 14:07:24.635508: Current learning rate: 0.00928 +2024-11-21 14:07:43.210650: train_loss -0.7622 +2024-11-21 14:07:43.210868: val_loss -0.7368 +2024-11-21 14:07:43.210944: Pseudo dice [0.8278] +2024-11-21 14:07:43.211027: Epoch time: 18.58 s +2024-11-21 14:07:44.078413: +2024-11-21 14:07:44.078619: Epoch 634 +2024-11-21 14:07:44.078731: Current learning rate: 0.00928 +2024-11-21 14:08:02.989402: train_loss -0.7572 +2024-11-21 14:08:02.989654: val_loss -0.7508 +2024-11-21 14:08:02.989734: Pseudo dice [0.8234] +2024-11-21 14:08:02.989822: Epoch time: 18.91 s +2024-11-21 14:08:03.796618: +2024-11-21 14:08:03.796882: Epoch 635 +2024-11-21 14:08:03.797003: Current learning rate: 0.00928 +2024-11-21 14:08:23.122558: train_loss -0.7595 +2024-11-21 14:08:23.122777: val_loss -0.7442 +2024-11-21 14:08:23.122853: Pseudo dice [0.8131] +2024-11-21 14:08:23.122927: Epoch time: 19.33 s +2024-11-21 14:08:24.036166: +2024-11-21 14:08:24.036410: Epoch 636 +2024-11-21 14:08:24.036529: Current learning rate: 0.00928 +2024-11-21 14:08:42.179214: train_loss -0.7661 +2024-11-21 14:08:42.179432: val_loss -0.7482 +2024-11-21 14:08:42.179507: Pseudo dice [0.8275] +2024-11-21 14:08:42.179586: Epoch time: 18.14 s +2024-11-21 14:08:42.986413: +2024-11-21 14:08:42.986616: Epoch 637 +2024-11-21 14:08:42.986736: Current learning rate: 0.00928 +2024-11-21 14:09:00.919267: train_loss -0.7533 +2024-11-21 14:09:00.921043: val_loss -0.7361 +2024-11-21 14:09:00.921136: Pseudo dice [0.8098] +2024-11-21 14:09:00.921214: Epoch time: 17.93 s +2024-11-21 14:09:01.778818: +2024-11-21 14:09:01.779030: Epoch 638 +2024-11-21 14:09:01.779147: Current learning rate: 0.00928 +2024-11-21 14:09:20.547076: train_loss -0.7541 +2024-11-21 14:09:20.549736: val_loss -0.7125 +2024-11-21 14:09:20.549830: Pseudo dice [0.7892] +2024-11-21 14:09:20.549915: Epoch time: 18.77 s +2024-11-21 14:09:21.576720: +2024-11-21 14:09:21.576940: Epoch 639 +2024-11-21 14:09:21.577058: Current learning rate: 0.00928 +2024-11-21 14:09:42.094193: train_loss -0.7651 +2024-11-21 14:09:42.094438: val_loss -0.7427 +2024-11-21 14:09:42.094513: Pseudo dice [0.807] +2024-11-21 14:09:42.094592: Epoch time: 20.52 s +2024-11-21 14:09:42.904346: +2024-11-21 14:09:42.904563: Epoch 640 +2024-11-21 14:09:42.904684: Current learning rate: 0.00928 +2024-11-21 14:10:01.024023: train_loss -0.7575 +2024-11-21 14:10:01.024242: val_loss -0.7637 +2024-11-21 14:10:01.024320: Pseudo dice [0.8289] +2024-11-21 14:10:01.024396: Epoch time: 18.12 s +2024-11-21 14:10:01.952144: +2024-11-21 14:10:01.952399: Epoch 641 +2024-11-21 14:10:01.952520: Current learning rate: 0.00928 +2024-11-21 14:10:21.383329: train_loss -0.7542 +2024-11-21 14:10:21.383541: val_loss -0.7071 +2024-11-21 14:10:21.383618: Pseudo dice [0.8111] +2024-11-21 14:10:21.383699: Epoch time: 19.43 s +2024-11-21 14:10:22.186877: +2024-11-21 14:10:22.187070: Epoch 642 +2024-11-21 14:10:22.187187: Current learning rate: 0.00927 +2024-11-21 14:10:40.258470: train_loss -0.7596 +2024-11-21 14:10:40.258702: val_loss -0.7226 +2024-11-21 14:10:40.258772: Pseudo dice [0.8213] +2024-11-21 14:10:40.258850: Epoch time: 18.07 s +2024-11-21 14:10:41.064312: +2024-11-21 14:10:41.064504: Epoch 643 +2024-11-21 14:10:41.064617: Current learning rate: 0.00927 +2024-11-21 14:11:00.411493: train_loss -0.7591 +2024-11-21 14:11:00.411693: val_loss -0.7402 +2024-11-21 14:11:00.411767: Pseudo dice [0.8235] +2024-11-21 14:11:00.411843: Epoch time: 19.35 s +2024-11-21 14:11:01.251204: +2024-11-21 14:11:01.251490: Epoch 644 +2024-11-21 14:11:01.251599: Current learning rate: 0.00927 +2024-11-21 14:11:20.690486: train_loss -0.758 +2024-11-21 14:11:20.690702: val_loss -0.7364 +2024-11-21 14:11:20.690777: Pseudo dice [0.8184] +2024-11-21 14:11:20.690852: Epoch time: 19.44 s +2024-11-21 14:11:21.496595: +2024-11-21 14:11:21.496800: Epoch 645 +2024-11-21 14:11:21.496915: Current learning rate: 0.00927 +2024-11-21 14:11:40.732619: train_loss -0.7504 +2024-11-21 14:11:40.732858: val_loss -0.7516 +2024-11-21 14:11:40.732941: Pseudo dice [0.8171] +2024-11-21 14:11:40.733031: Epoch time: 19.24 s +2024-11-21 14:11:41.913035: +2024-11-21 14:11:41.913249: Epoch 646 +2024-11-21 14:11:41.913364: Current learning rate: 0.00927 +2024-11-21 14:12:01.310044: train_loss -0.7561 +2024-11-21 14:12:01.310262: val_loss -0.7382 +2024-11-21 14:12:01.310340: Pseudo dice [0.8172] +2024-11-21 14:12:01.310421: Epoch time: 19.4 s +2024-11-21 14:12:02.117265: +2024-11-21 14:12:02.117481: Epoch 647 +2024-11-21 14:12:02.117597: Current learning rate: 0.00927 +2024-11-21 14:12:20.715487: train_loss -0.7512 +2024-11-21 14:12:20.717892: val_loss -0.7186 +2024-11-21 14:12:20.717999: Pseudo dice [0.8089] +2024-11-21 14:12:20.718079: Epoch time: 18.6 s +2024-11-21 14:12:21.632235: +2024-11-21 14:12:21.632504: Epoch 648 +2024-11-21 14:12:21.632617: Current learning rate: 0.00927 +2024-11-21 14:12:40.062097: train_loss -0.7617 +2024-11-21 14:12:40.062336: val_loss -0.7432 +2024-11-21 14:12:40.062416: Pseudo dice [0.8224] +2024-11-21 14:12:40.062503: Epoch time: 18.43 s +2024-11-21 14:12:40.886231: +2024-11-21 14:12:40.886470: Epoch 649 +2024-11-21 14:12:40.886581: Current learning rate: 0.00927 +2024-11-21 14:12:59.165515: train_loss -0.7606 +2024-11-21 14:12:59.165747: val_loss -0.6827 +2024-11-21 14:12:59.167978: Pseudo dice [0.7863] +2024-11-21 14:12:59.168120: Epoch time: 18.28 s +2024-11-21 14:13:00.190950: +2024-11-21 14:13:00.191139: Epoch 650 +2024-11-21 14:13:00.191283: Current learning rate: 0.00927 +2024-11-21 14:13:18.695843: train_loss -0.7521 +2024-11-21 14:13:18.696059: val_loss -0.7311 +2024-11-21 14:13:18.696132: Pseudo dice [0.8259] +2024-11-21 14:13:18.696206: Epoch time: 18.51 s +2024-11-21 14:13:19.509760: +2024-11-21 14:13:19.509968: Epoch 651 +2024-11-21 14:13:19.510088: Current learning rate: 0.00926 +2024-11-21 14:13:38.212733: train_loss -0.7659 +2024-11-21 14:13:38.212947: val_loss -0.7108 +2024-11-21 14:13:38.213027: Pseudo dice [0.8063] +2024-11-21 14:13:38.213105: Epoch time: 18.7 s +2024-11-21 14:13:39.045341: +2024-11-21 14:13:39.045549: Epoch 652 +2024-11-21 14:13:39.045660: Current learning rate: 0.00926 +2024-11-21 14:13:59.296250: train_loss -0.757 +2024-11-21 14:13:59.298640: val_loss -0.7253 +2024-11-21 14:13:59.298734: Pseudo dice [0.8175] +2024-11-21 14:13:59.298820: Epoch time: 20.25 s +2024-11-21 14:14:00.173746: +2024-11-21 14:14:00.173992: Epoch 653 +2024-11-21 14:14:00.174105: Current learning rate: 0.00926 +2024-11-21 14:14:19.436803: train_loss -0.7618 +2024-11-21 14:14:19.442204: val_loss -0.7287 +2024-11-21 14:14:19.442311: Pseudo dice [0.8112] +2024-11-21 14:14:19.442393: Epoch time: 19.26 s +2024-11-21 14:14:20.269899: +2024-11-21 14:14:20.270079: Epoch 654 +2024-11-21 14:14:20.270202: Current learning rate: 0.00926 +2024-11-21 14:14:38.863968: train_loss -0.7622 +2024-11-21 14:14:38.864209: val_loss -0.7431 +2024-11-21 14:14:38.864285: Pseudo dice [0.8326] +2024-11-21 14:14:38.864362: Epoch time: 18.59 s +2024-11-21 14:14:39.671282: +2024-11-21 14:14:39.671455: Epoch 655 +2024-11-21 14:14:39.671568: Current learning rate: 0.00926 +2024-11-21 14:14:58.626969: train_loss -0.7691 +2024-11-21 14:14:58.627196: val_loss -0.7327 +2024-11-21 14:14:58.627282: Pseudo dice [0.8183] +2024-11-21 14:14:58.627370: Epoch time: 18.96 s +2024-11-21 14:14:59.432289: +2024-11-21 14:14:59.432495: Epoch 656 +2024-11-21 14:14:59.432606: Current learning rate: 0.00926 +2024-11-21 14:15:18.775062: train_loss -0.756 +2024-11-21 14:15:18.775305: val_loss -0.7331 +2024-11-21 14:15:18.775377: Pseudo dice [0.8216] +2024-11-21 14:15:18.775462: Epoch time: 19.34 s +2024-11-21 14:15:20.006950: +2024-11-21 14:15:20.007144: Epoch 657 +2024-11-21 14:15:20.007257: Current learning rate: 0.00926 +2024-11-21 14:15:38.189831: train_loss -0.7526 +2024-11-21 14:15:38.190066: val_loss -0.746 +2024-11-21 14:15:38.190143: Pseudo dice [0.8105] +2024-11-21 14:15:38.190277: Epoch time: 18.18 s +2024-11-21 14:15:39.003426: +2024-11-21 14:15:39.003728: Epoch 658 +2024-11-21 14:15:39.003844: Current learning rate: 0.00926 +2024-11-21 14:15:58.112758: train_loss -0.7606 +2024-11-21 14:15:58.112999: val_loss -0.7228 +2024-11-21 14:15:58.113073: Pseudo dice [0.8171] +2024-11-21 14:15:58.113151: Epoch time: 19.11 s +2024-11-21 14:15:59.088692: +2024-11-21 14:15:59.089007: Epoch 659 +2024-11-21 14:15:59.089119: Current learning rate: 0.00926 +2024-11-21 14:16:17.348497: train_loss -0.7505 +2024-11-21 14:16:17.348712: val_loss -0.7466 +2024-11-21 14:16:17.348790: Pseudo dice [0.8228] +2024-11-21 14:16:17.348876: Epoch time: 18.26 s +2024-11-21 14:16:18.284246: +2024-11-21 14:16:18.284430: Epoch 660 +2024-11-21 14:16:18.284552: Current learning rate: 0.00925 +2024-11-21 14:16:37.530805: train_loss -0.745 +2024-11-21 14:16:37.531046: val_loss -0.7153 +2024-11-21 14:16:37.531122: Pseudo dice [0.8119] +2024-11-21 14:16:37.531204: Epoch time: 19.25 s +2024-11-21 14:16:38.348948: +2024-11-21 14:16:38.349137: Epoch 661 +2024-11-21 14:16:38.349243: Current learning rate: 0.00925 +2024-11-21 14:16:57.562263: train_loss -0.7577 +2024-11-21 14:16:57.562477: val_loss -0.7387 +2024-11-21 14:16:57.562550: Pseudo dice [0.8306] +2024-11-21 14:16:57.562626: Epoch time: 19.21 s +2024-11-21 14:16:58.757443: +2024-11-21 14:16:58.757634: Epoch 662 +2024-11-21 14:16:58.757746: Current learning rate: 0.00925 +2024-11-21 14:17:18.177081: train_loss -0.7436 +2024-11-21 14:17:18.177280: val_loss -0.7376 +2024-11-21 14:17:18.177353: Pseudo dice [0.8171] +2024-11-21 14:17:18.177428: Epoch time: 19.42 s +2024-11-21 14:17:18.979738: +2024-11-21 14:17:18.979913: Epoch 663 +2024-11-21 14:17:18.980029: Current learning rate: 0.00925 +2024-11-21 14:17:37.941185: train_loss -0.749 +2024-11-21 14:17:37.941402: val_loss -0.7454 +2024-11-21 14:17:37.941479: Pseudo dice [0.8174] +2024-11-21 14:17:37.941558: Epoch time: 18.96 s +2024-11-21 14:17:38.833164: +2024-11-21 14:17:38.833383: Epoch 664 +2024-11-21 14:17:38.833503: Current learning rate: 0.00925 +2024-11-21 14:17:58.048942: train_loss -0.7555 +2024-11-21 14:17:58.049182: val_loss -0.7459 +2024-11-21 14:17:58.049255: Pseudo dice [0.8248] +2024-11-21 14:17:58.049336: Epoch time: 19.22 s +2024-11-21 14:17:58.854457: +2024-11-21 14:17:58.854636: Epoch 665 +2024-11-21 14:17:58.854746: Current learning rate: 0.00925 +2024-11-21 14:18:16.970081: train_loss -0.7505 +2024-11-21 14:18:16.970282: val_loss -0.714 +2024-11-21 14:18:16.970353: Pseudo dice [0.8069] +2024-11-21 14:18:16.970430: Epoch time: 18.12 s +2024-11-21 14:18:17.780889: +2024-11-21 14:18:17.781122: Epoch 666 +2024-11-21 14:18:17.781245: Current learning rate: 0.00925 +2024-11-21 14:18:36.195487: train_loss -0.7662 +2024-11-21 14:18:36.195704: val_loss -0.7075 +2024-11-21 14:18:36.195781: Pseudo dice [0.8283] +2024-11-21 14:18:36.197164: Epoch time: 18.42 s +2024-11-21 14:18:37.084330: +2024-11-21 14:18:37.084550: Epoch 667 +2024-11-21 14:18:37.084665: Current learning rate: 0.00925 +2024-11-21 14:18:57.358150: train_loss -0.7564 +2024-11-21 14:18:57.358367: val_loss -0.7276 +2024-11-21 14:18:57.358443: Pseudo dice [0.8294] +2024-11-21 14:18:57.358526: Epoch time: 20.27 s +2024-11-21 14:18:58.177284: +2024-11-21 14:18:58.177469: Epoch 668 +2024-11-21 14:18:58.177583: Current learning rate: 0.00925 +2024-11-21 14:19:17.094540: train_loss -0.7684 +2024-11-21 14:19:17.094749: val_loss -0.7232 +2024-11-21 14:19:17.094820: Pseudo dice [0.8061] +2024-11-21 14:19:17.094896: Epoch time: 18.92 s +2024-11-21 14:19:18.307213: +2024-11-21 14:19:18.307404: Epoch 669 +2024-11-21 14:19:18.307516: Current learning rate: 0.00924 +2024-11-21 14:19:36.934644: train_loss -0.7589 +2024-11-21 14:19:36.934906: val_loss -0.7022 +2024-11-21 14:19:36.934982: Pseudo dice [0.8158] +2024-11-21 14:19:36.935069: Epoch time: 18.63 s +2024-11-21 14:19:37.780476: +2024-11-21 14:19:37.780686: Epoch 670 +2024-11-21 14:19:37.780798: Current learning rate: 0.00924 +2024-11-21 14:19:57.345200: train_loss -0.747 +2024-11-21 14:19:57.345461: val_loss -0.7423 +2024-11-21 14:19:57.345537: Pseudo dice [0.831] +2024-11-21 14:19:57.345618: Epoch time: 19.56 s +2024-11-21 14:19:58.195223: +2024-11-21 14:19:58.195432: Epoch 671 +2024-11-21 14:19:58.195550: Current learning rate: 0.00924 +2024-11-21 14:20:18.284979: train_loss -0.749 +2024-11-21 14:20:18.285203: val_loss -0.7151 +2024-11-21 14:20:18.285276: Pseudo dice [0.821] +2024-11-21 14:20:18.285351: Epoch time: 20.09 s +2024-11-21 14:20:19.107097: +2024-11-21 14:20:19.107293: Epoch 672 +2024-11-21 14:20:19.107406: Current learning rate: 0.00924 +2024-11-21 14:20:37.934702: train_loss -0.7582 +2024-11-21 14:20:37.934920: val_loss -0.7319 +2024-11-21 14:20:37.935017: Pseudo dice [0.8181] +2024-11-21 14:20:37.935157: Epoch time: 18.83 s +2024-11-21 14:20:38.776228: +2024-11-21 14:20:38.776497: Epoch 673 +2024-11-21 14:20:38.776604: Current learning rate: 0.00924 +2024-11-21 14:20:57.799203: train_loss -0.7577 +2024-11-21 14:20:57.799431: val_loss -0.7434 +2024-11-21 14:20:57.799507: Pseudo dice [0.8167] +2024-11-21 14:20:57.799589: Epoch time: 19.02 s +2024-11-21 14:20:58.620362: +2024-11-21 14:20:58.620613: Epoch 674 +2024-11-21 14:20:58.620727: Current learning rate: 0.00924 +2024-11-21 14:21:17.763006: train_loss -0.7648 +2024-11-21 14:21:17.763221: val_loss -0.7071 +2024-11-21 14:21:17.763297: Pseudo dice [0.815] +2024-11-21 14:21:17.763375: Epoch time: 19.14 s +2024-11-21 14:21:18.592374: +2024-11-21 14:21:18.592636: Epoch 675 +2024-11-21 14:21:18.592750: Current learning rate: 0.00924 +2024-11-21 14:21:36.963476: train_loss -0.7718 +2024-11-21 14:21:36.963692: val_loss -0.7301 +2024-11-21 14:21:36.963772: Pseudo dice [0.8139] +2024-11-21 14:21:36.968325: Epoch time: 18.37 s +2024-11-21 14:21:37.833591: +2024-11-21 14:21:37.833789: Epoch 676 +2024-11-21 14:21:37.833900: Current learning rate: 0.00924 +2024-11-21 14:21:57.201574: train_loss -0.7512 +2024-11-21 14:21:57.201793: val_loss -0.7448 +2024-11-21 14:21:57.201866: Pseudo dice [0.8194] +2024-11-21 14:21:57.201943: Epoch time: 19.37 s +2024-11-21 14:21:58.024570: +2024-11-21 14:21:58.024782: Epoch 677 +2024-11-21 14:21:58.024898: Current learning rate: 0.00924 +2024-11-21 14:22:16.533708: train_loss -0.7695 +2024-11-21 14:22:16.533939: val_loss -0.72 +2024-11-21 14:22:16.534016: Pseudo dice [0.8091] +2024-11-21 14:22:16.534095: Epoch time: 18.51 s +2024-11-21 14:22:17.370607: +2024-11-21 14:22:17.370939: Epoch 678 +2024-11-21 14:22:17.371065: Current learning rate: 0.00923 +2024-11-21 14:22:36.243491: train_loss -0.755 +2024-11-21 14:22:36.243701: val_loss -0.7529 +2024-11-21 14:22:36.243779: Pseudo dice [0.8303] +2024-11-21 14:22:36.243860: Epoch time: 18.87 s +2024-11-21 14:22:37.063514: +2024-11-21 14:22:37.063696: Epoch 679 +2024-11-21 14:22:37.063812: Current learning rate: 0.00923 +2024-11-21 14:22:55.946564: train_loss -0.755 +2024-11-21 14:22:55.946794: val_loss -0.7322 +2024-11-21 14:22:55.946868: Pseudo dice [0.8217] +2024-11-21 14:22:55.946944: Epoch time: 18.88 s +2024-11-21 14:22:57.395601: +2024-11-21 14:22:57.395859: Epoch 680 +2024-11-21 14:22:57.395986: Current learning rate: 0.00923 +2024-11-21 14:23:16.588033: train_loss -0.7526 +2024-11-21 14:23:16.588268: val_loss -0.7572 +2024-11-21 14:23:16.588339: Pseudo dice [0.8146] +2024-11-21 14:23:16.588420: Epoch time: 19.19 s +2024-11-21 14:23:17.474561: +2024-11-21 14:23:17.474777: Epoch 681 +2024-11-21 14:23:17.474893: Current learning rate: 0.00923 +2024-11-21 14:23:35.936722: train_loss -0.7631 +2024-11-21 14:23:35.936933: val_loss -0.7555 +2024-11-21 14:23:35.937014: Pseudo dice [0.8479] +2024-11-21 14:23:35.937090: Epoch time: 18.46 s +2024-11-21 14:23:36.867234: +2024-11-21 14:23:36.867445: Epoch 682 +2024-11-21 14:23:36.867556: Current learning rate: 0.00923 +2024-11-21 14:23:56.170388: train_loss -0.7601 +2024-11-21 14:23:56.170604: val_loss -0.75 +2024-11-21 14:23:56.170679: Pseudo dice [0.8253] +2024-11-21 14:23:56.170756: Epoch time: 19.3 s +2024-11-21 14:23:56.990531: +2024-11-21 14:23:56.990744: Epoch 683 +2024-11-21 14:23:56.990857: Current learning rate: 0.00923 +2024-11-21 14:24:14.885601: train_loss -0.7763 +2024-11-21 14:24:14.885848: val_loss -0.7402 +2024-11-21 14:24:14.885927: Pseudo dice [0.8149] +2024-11-21 14:24:14.886009: Epoch time: 17.9 s +2024-11-21 14:24:15.711230: +2024-11-21 14:24:15.711452: Epoch 684 +2024-11-21 14:24:15.711568: Current learning rate: 0.00923 +2024-11-21 14:24:33.515178: train_loss -0.7679 +2024-11-21 14:24:33.515414: val_loss -0.7228 +2024-11-21 14:24:33.515488: Pseudo dice [0.8162] +2024-11-21 14:24:33.515569: Epoch time: 17.8 s +2024-11-21 14:24:34.427276: +2024-11-21 14:24:34.427974: Epoch 685 +2024-11-21 14:24:34.428131: Current learning rate: 0.00923 +2024-11-21 14:24:53.676683: train_loss -0.7742 +2024-11-21 14:24:53.676907: val_loss -0.7354 +2024-11-21 14:24:53.676996: Pseudo dice [0.8301] +2024-11-21 14:24:53.677071: Epoch time: 19.25 s +2024-11-21 14:24:54.492754: +2024-11-21 14:24:54.494571: Epoch 686 +2024-11-21 14:24:54.494698: Current learning rate: 0.00922 +2024-11-21 14:25:12.444873: train_loss -0.7605 +2024-11-21 14:25:12.445098: val_loss -0.7485 +2024-11-21 14:25:12.445175: Pseudo dice [0.8073] +2024-11-21 14:25:12.450459: Epoch time: 17.95 s +2024-11-21 14:25:13.310679: +2024-11-21 14:25:13.310887: Epoch 687 +2024-11-21 14:25:13.311010: Current learning rate: 0.00922 +2024-11-21 14:25:31.866680: train_loss -0.7637 +2024-11-21 14:25:31.866908: val_loss -0.7381 +2024-11-21 14:25:31.866983: Pseudo dice [0.8131] +2024-11-21 14:25:31.867071: Epoch time: 18.56 s +2024-11-21 14:25:32.702027: +2024-11-21 14:25:32.702278: Epoch 688 +2024-11-21 14:25:32.702437: Current learning rate: 0.00922 +2024-11-21 14:25:52.512680: train_loss -0.7595 +2024-11-21 14:25:52.512894: val_loss -0.7392 +2024-11-21 14:25:52.512970: Pseudo dice [0.8305] +2024-11-21 14:25:52.513059: Epoch time: 19.81 s +2024-11-21 14:25:53.329545: +2024-11-21 14:25:53.329715: Epoch 689 +2024-11-21 14:25:53.329828: Current learning rate: 0.00922 +2024-11-21 14:26:11.161559: train_loss -0.7643 +2024-11-21 14:26:11.161783: val_loss -0.7275 +2024-11-21 14:26:11.161858: Pseudo dice [0.8142] +2024-11-21 14:26:11.161935: Epoch time: 17.83 s +2024-11-21 14:26:12.149737: +2024-11-21 14:26:12.149924: Epoch 690 +2024-11-21 14:26:12.150039: Current learning rate: 0.00922 +2024-11-21 14:26:29.988486: train_loss -0.7657 +2024-11-21 14:26:29.988683: val_loss -0.7673 +2024-11-21 14:26:29.988756: Pseudo dice [0.8442] +2024-11-21 14:26:29.988829: Epoch time: 17.84 s +2024-11-21 14:26:30.808265: +2024-11-21 14:26:30.808452: Epoch 691 +2024-11-21 14:26:30.808563: Current learning rate: 0.00922 +2024-11-21 14:26:50.081932: train_loss -0.7618 +2024-11-21 14:26:50.082160: val_loss -0.7139 +2024-11-21 14:26:50.082235: Pseudo dice [0.8078] +2024-11-21 14:26:50.082318: Epoch time: 19.27 s +2024-11-21 14:26:51.306876: +2024-11-21 14:26:51.307161: Epoch 692 +2024-11-21 14:26:51.307282: Current learning rate: 0.00922 +2024-11-21 14:27:09.373712: train_loss -0.7435 +2024-11-21 14:27:09.373933: val_loss -0.7231 +2024-11-21 14:27:09.374013: Pseudo dice [0.8031] +2024-11-21 14:27:09.374090: Epoch time: 18.07 s +2024-11-21 14:27:10.204164: +2024-11-21 14:27:10.204449: Epoch 693 +2024-11-21 14:27:10.204563: Current learning rate: 0.00922 +2024-11-21 14:27:29.181100: train_loss -0.7583 +2024-11-21 14:27:29.181339: val_loss -0.7482 +2024-11-21 14:27:29.181419: Pseudo dice [0.8249] +2024-11-21 14:27:29.181498: Epoch time: 18.98 s +2024-11-21 14:27:30.018219: +2024-11-21 14:27:30.018548: Epoch 694 +2024-11-21 14:27:30.018666: Current learning rate: 0.00922 +2024-11-21 14:27:49.038763: train_loss -0.7649 +2024-11-21 14:27:49.041827: val_loss -0.7269 +2024-11-21 14:27:49.041942: Pseudo dice [0.8115] +2024-11-21 14:27:49.042059: Epoch time: 19.02 s +2024-11-21 14:27:49.889703: +2024-11-21 14:27:49.889922: Epoch 695 +2024-11-21 14:27:49.890043: Current learning rate: 0.00921 +2024-11-21 14:28:09.223895: train_loss -0.7607 +2024-11-21 14:28:09.224109: val_loss -0.751 +2024-11-21 14:28:09.224186: Pseudo dice [0.8224] +2024-11-21 14:28:09.224262: Epoch time: 19.34 s +2024-11-21 14:28:10.046652: +2024-11-21 14:28:10.046886: Epoch 696 +2024-11-21 14:28:10.047013: Current learning rate: 0.00921 +2024-11-21 14:28:29.083355: train_loss -0.751 +2024-11-21 14:28:29.083566: val_loss -0.7364 +2024-11-21 14:28:29.083641: Pseudo dice [0.8214] +2024-11-21 14:28:29.083716: Epoch time: 19.04 s +2024-11-21 14:28:29.902281: +2024-11-21 14:28:29.902481: Epoch 697 +2024-11-21 14:28:29.902600: Current learning rate: 0.00921 +2024-11-21 14:28:49.111090: train_loss -0.7564 +2024-11-21 14:28:49.111300: val_loss -0.7643 +2024-11-21 14:28:49.111376: Pseudo dice [0.8316] +2024-11-21 14:28:49.111458: Epoch time: 19.21 s +2024-11-21 14:28:50.047650: +2024-11-21 14:28:50.047852: Epoch 698 +2024-11-21 14:28:50.047963: Current learning rate: 0.00921 +2024-11-21 14:29:09.202300: train_loss -0.7617 +2024-11-21 14:29:09.202540: val_loss -0.7453 +2024-11-21 14:29:09.202618: Pseudo dice [0.8265] +2024-11-21 14:29:09.214192: Epoch time: 19.16 s +2024-11-21 14:29:10.067553: +2024-11-21 14:29:10.067751: Epoch 699 +2024-11-21 14:29:10.067865: Current learning rate: 0.00921 +2024-11-21 14:29:29.006809: train_loss -0.7582 +2024-11-21 14:29:29.007025: val_loss -0.7414 +2024-11-21 14:29:29.007102: Pseudo dice [0.8098] +2024-11-21 14:29:29.007182: Epoch time: 18.94 s +2024-11-21 14:29:30.046882: +2024-11-21 14:29:30.047078: Epoch 700 +2024-11-21 14:29:30.047189: Current learning rate: 0.00921 +2024-11-21 14:29:48.083390: train_loss -0.7651 +2024-11-21 14:29:48.083606: val_loss -0.7385 +2024-11-21 14:29:48.088864: Pseudo dice [0.8299] +2024-11-21 14:29:48.088981: Epoch time: 18.04 s +2024-11-21 14:29:49.074474: +2024-11-21 14:29:49.074739: Epoch 701 +2024-11-21 14:29:49.074857: Current learning rate: 0.00921 +2024-11-21 14:30:07.618203: train_loss -0.7595 +2024-11-21 14:30:07.618450: val_loss -0.7369 +2024-11-21 14:30:07.618526: Pseudo dice [0.8179] +2024-11-21 14:30:07.618618: Epoch time: 18.54 s +2024-11-21 14:30:08.611345: +2024-11-21 14:30:08.611680: Epoch 702 +2024-11-21 14:30:08.611794: Current learning rate: 0.00921 +2024-11-21 14:30:27.950823: train_loss -0.7601 +2024-11-21 14:30:27.951037: val_loss -0.7331 +2024-11-21 14:30:27.951110: Pseudo dice [0.8092] +2024-11-21 14:30:27.951186: Epoch time: 19.34 s +2024-11-21 14:30:29.144539: +2024-11-21 14:30:29.144759: Epoch 703 +2024-11-21 14:30:29.144873: Current learning rate: 0.00921 +2024-11-21 14:30:47.431649: train_loss -0.7639 +2024-11-21 14:30:47.431876: val_loss -0.7336 +2024-11-21 14:30:47.434170: Pseudo dice [0.8216] +2024-11-21 14:30:47.434268: Epoch time: 18.29 s +2024-11-21 14:30:48.428495: +2024-11-21 14:30:48.428781: Epoch 704 +2024-11-21 14:30:48.428893: Current learning rate: 0.0092 +2024-11-21 14:31:06.538525: train_loss -0.7686 +2024-11-21 14:31:06.538735: val_loss -0.7261 +2024-11-21 14:31:06.538808: Pseudo dice [0.8113] +2024-11-21 14:31:06.538886: Epoch time: 18.11 s +2024-11-21 14:31:07.515068: +2024-11-21 14:31:07.515314: Epoch 705 +2024-11-21 14:31:07.515482: Current learning rate: 0.0092 +2024-11-21 14:31:26.701473: train_loss -0.75 +2024-11-21 14:31:26.701985: val_loss -0.734 +2024-11-21 14:31:26.702079: Pseudo dice [0.8109] +2024-11-21 14:31:26.702159: Epoch time: 19.19 s +2024-11-21 14:31:27.524595: +2024-11-21 14:31:27.524865: Epoch 706 +2024-11-21 14:31:27.524976: Current learning rate: 0.0092 +2024-11-21 14:31:45.646579: train_loss -0.7676 +2024-11-21 14:31:45.646790: val_loss -0.7405 +2024-11-21 14:31:45.646864: Pseudo dice [0.8144] +2024-11-21 14:31:45.647029: Epoch time: 18.12 s +2024-11-21 14:31:46.470002: +2024-11-21 14:31:46.470210: Epoch 707 +2024-11-21 14:31:46.470327: Current learning rate: 0.0092 +2024-11-21 14:32:04.882740: train_loss -0.7631 +2024-11-21 14:32:04.882951: val_loss -0.7001 +2024-11-21 14:32:04.883033: Pseudo dice [0.7887] +2024-11-21 14:32:04.883120: Epoch time: 18.41 s +2024-11-21 14:32:05.702509: +2024-11-21 14:32:05.702725: Epoch 708 +2024-11-21 14:32:05.702839: Current learning rate: 0.0092 +2024-11-21 14:32:23.904362: train_loss -0.763 +2024-11-21 14:32:23.904600: val_loss -0.734 +2024-11-21 14:32:23.904677: Pseudo dice [0.8187] +2024-11-21 14:32:23.904760: Epoch time: 18.2 s +2024-11-21 14:32:24.723783: +2024-11-21 14:32:24.723985: Epoch 709 +2024-11-21 14:32:24.724107: Current learning rate: 0.0092 +2024-11-21 14:32:44.296987: train_loss -0.7653 +2024-11-21 14:32:44.297197: val_loss -0.7232 +2024-11-21 14:32:44.297273: Pseudo dice [0.8232] +2024-11-21 14:32:44.297351: Epoch time: 19.57 s +2024-11-21 14:32:45.119687: +2024-11-21 14:32:45.119954: Epoch 710 +2024-11-21 14:32:45.120070: Current learning rate: 0.0092 +2024-11-21 14:33:03.677343: train_loss -0.7707 +2024-11-21 14:33:03.677596: val_loss -0.7499 +2024-11-21 14:33:03.677737: Pseudo dice [0.8388] +2024-11-21 14:33:03.677825: Epoch time: 18.56 s +2024-11-21 14:33:04.496477: +2024-11-21 14:33:04.496850: Epoch 711 +2024-11-21 14:33:04.496970: Current learning rate: 0.0092 +2024-11-21 14:33:22.889799: train_loss -0.7612 +2024-11-21 14:33:22.890019: val_loss -0.7576 +2024-11-21 14:33:22.890431: Pseudo dice [0.8339] +2024-11-21 14:33:22.890516: Epoch time: 18.39 s +2024-11-21 14:33:23.707834: +2024-11-21 14:33:23.708062: Epoch 712 +2024-11-21 14:33:23.708174: Current learning rate: 0.0092 +2024-11-21 14:33:42.621026: train_loss -0.7518 +2024-11-21 14:33:42.621262: val_loss -0.7257 +2024-11-21 14:33:42.621351: Pseudo dice [0.8034] +2024-11-21 14:33:42.621491: Epoch time: 18.91 s +2024-11-21 14:33:43.443957: +2024-11-21 14:33:43.444164: Epoch 713 +2024-11-21 14:33:43.444281: Current learning rate: 0.00919 +2024-11-21 14:34:01.350021: train_loss -0.744 +2024-11-21 14:34:01.350232: val_loss -0.7079 +2024-11-21 14:34:01.350303: Pseudo dice [0.7863] +2024-11-21 14:34:01.350381: Epoch time: 17.91 s +2024-11-21 14:34:02.546667: +2024-11-21 14:34:02.546921: Epoch 714 +2024-11-21 14:34:02.547043: Current learning rate: 0.00919 +2024-11-21 14:34:21.033247: train_loss -0.7511 +2024-11-21 14:34:21.033463: val_loss -0.7469 +2024-11-21 14:34:21.033536: Pseudo dice [0.8181] +2024-11-21 14:34:21.033623: Epoch time: 18.49 s +2024-11-21 14:34:21.858219: +2024-11-21 14:34:21.858430: Epoch 715 +2024-11-21 14:34:21.858543: Current learning rate: 0.00919 +2024-11-21 14:34:40.968859: train_loss -0.7595 +2024-11-21 14:34:40.969105: val_loss -0.741 +2024-11-21 14:34:40.969227: Pseudo dice [0.8291] +2024-11-21 14:34:40.969309: Epoch time: 19.11 s +2024-11-21 14:34:41.790499: +2024-11-21 14:34:41.790848: Epoch 716 +2024-11-21 14:34:41.790965: Current learning rate: 0.00919 +2024-11-21 14:34:59.283403: train_loss -0.7652 +2024-11-21 14:34:59.283606: val_loss -0.7347 +2024-11-21 14:34:59.283679: Pseudo dice [0.8206] +2024-11-21 14:34:59.283753: Epoch time: 17.49 s +2024-11-21 14:35:00.100515: +2024-11-21 14:35:00.100726: Epoch 717 +2024-11-21 14:35:00.100846: Current learning rate: 0.00919 +2024-11-21 14:35:18.886921: train_loss -0.7457 +2024-11-21 14:35:18.887139: val_loss -0.7149 +2024-11-21 14:35:18.887212: Pseudo dice [0.8072] +2024-11-21 14:35:18.887291: Epoch time: 18.79 s +2024-11-21 14:35:19.712435: +2024-11-21 14:35:19.712636: Epoch 718 +2024-11-21 14:35:19.712760: Current learning rate: 0.00919 +2024-11-21 14:35:38.441243: train_loss -0.7471 +2024-11-21 14:35:38.441464: val_loss -0.7491 +2024-11-21 14:35:38.441547: Pseudo dice [0.8275] +2024-11-21 14:35:38.441627: Epoch time: 18.73 s +2024-11-21 14:35:39.368922: +2024-11-21 14:35:39.369132: Epoch 719 +2024-11-21 14:35:39.369248: Current learning rate: 0.00919 +2024-11-21 14:35:59.694183: train_loss -0.7383 +2024-11-21 14:35:59.694442: val_loss -0.7507 +2024-11-21 14:35:59.694516: Pseudo dice [0.8367] +2024-11-21 14:35:59.694593: Epoch time: 20.33 s +2024-11-21 14:36:00.629600: +2024-11-21 14:36:00.629810: Epoch 720 +2024-11-21 14:36:00.629929: Current learning rate: 0.00919 +2024-11-21 14:36:18.242085: train_loss -0.7506 +2024-11-21 14:36:18.242297: val_loss -0.716 +2024-11-21 14:36:18.242372: Pseudo dice [0.8068] +2024-11-21 14:36:18.242449: Epoch time: 17.61 s +2024-11-21 14:36:19.063259: +2024-11-21 14:36:19.063582: Epoch 721 +2024-11-21 14:36:19.063696: Current learning rate: 0.00919 +2024-11-21 14:36:38.051742: train_loss -0.7571 +2024-11-21 14:36:38.051948: val_loss -0.7359 +2024-11-21 14:36:38.052032: Pseudo dice [0.8102] +2024-11-21 14:36:38.052108: Epoch time: 18.99 s +2024-11-21 14:36:38.871506: +2024-11-21 14:36:38.871693: Epoch 722 +2024-11-21 14:36:38.871810: Current learning rate: 0.00918 +2024-11-21 14:36:56.853643: train_loss -0.7449 +2024-11-21 14:36:56.853909: val_loss -0.709 +2024-11-21 14:36:56.854015: Pseudo dice [0.8056] +2024-11-21 14:36:56.854112: Epoch time: 17.98 s +2024-11-21 14:36:57.677756: +2024-11-21 14:36:57.677950: Epoch 723 +2024-11-21 14:36:57.678075: Current learning rate: 0.00918 +2024-11-21 14:37:16.796487: train_loss -0.7631 +2024-11-21 14:37:16.796785: val_loss -0.7409 +2024-11-21 14:37:16.796861: Pseudo dice [0.8241] +2024-11-21 14:37:16.796939: Epoch time: 19.12 s +2024-11-21 14:37:17.699538: +2024-11-21 14:37:17.699797: Epoch 724 +2024-11-21 14:37:17.699911: Current learning rate: 0.00918 +2024-11-21 14:37:38.547789: train_loss -0.7591 +2024-11-21 14:37:38.548080: val_loss -0.77 +2024-11-21 14:37:38.548167: Pseudo dice [0.8274] +2024-11-21 14:37:38.548254: Epoch time: 20.85 s +2024-11-21 14:37:39.775091: +2024-11-21 14:37:39.775332: Epoch 725 +2024-11-21 14:37:39.775452: Current learning rate: 0.00918 +2024-11-21 14:37:57.927187: train_loss -0.7559 +2024-11-21 14:37:57.927451: val_loss -0.7321 +2024-11-21 14:37:57.927524: Pseudo dice [0.8156] +2024-11-21 14:37:57.927610: Epoch time: 18.15 s +2024-11-21 14:37:58.738923: +2024-11-21 14:37:58.739168: Epoch 726 +2024-11-21 14:37:58.739278: Current learning rate: 0.00918 +2024-11-21 14:38:18.621073: train_loss -0.7413 +2024-11-21 14:38:18.621281: val_loss -0.7197 +2024-11-21 14:38:18.621362: Pseudo dice [0.8135] +2024-11-21 14:38:18.621443: Epoch time: 19.88 s +2024-11-21 14:38:19.434125: +2024-11-21 14:38:19.434352: Epoch 727 +2024-11-21 14:38:19.434467: Current learning rate: 0.00918 +2024-11-21 14:38:38.977633: train_loss -0.7596 +2024-11-21 14:38:38.979988: val_loss -0.7594 +2024-11-21 14:38:38.980105: Pseudo dice [0.8233] +2024-11-21 14:38:38.980182: Epoch time: 19.54 s +2024-11-21 14:38:39.804129: +2024-11-21 14:38:39.804333: Epoch 728 +2024-11-21 14:38:39.804446: Current learning rate: 0.00918 +2024-11-21 14:38:58.152105: train_loss -0.7569 +2024-11-21 14:38:58.152322: val_loss -0.7412 +2024-11-21 14:38:58.152398: Pseudo dice [0.8207] +2024-11-21 14:38:58.152475: Epoch time: 18.35 s +2024-11-21 14:38:58.964900: +2024-11-21 14:38:58.965128: Epoch 729 +2024-11-21 14:38:58.965250: Current learning rate: 0.00918 +2024-11-21 14:39:17.487622: train_loss -0.7624 +2024-11-21 14:39:17.487857: val_loss -0.7057 +2024-11-21 14:39:17.487929: Pseudo dice [0.8009] +2024-11-21 14:39:17.488016: Epoch time: 18.52 s +2024-11-21 14:39:18.303529: +2024-11-21 14:39:18.303759: Epoch 730 +2024-11-21 14:39:18.303880: Current learning rate: 0.00917 +2024-11-21 14:39:38.200321: train_loss -0.7587 +2024-11-21 14:39:38.200533: val_loss -0.7512 +2024-11-21 14:39:38.200608: Pseudo dice [0.8081] +2024-11-21 14:39:38.200684: Epoch time: 19.9 s +2024-11-21 14:39:39.019644: +2024-11-21 14:39:39.019853: Epoch 731 +2024-11-21 14:39:39.019967: Current learning rate: 0.00917 +2024-11-21 14:39:59.074701: train_loss -0.753 +2024-11-21 14:39:59.074911: val_loss -0.7506 +2024-11-21 14:39:59.074997: Pseudo dice [0.8093] +2024-11-21 14:39:59.075070: Epoch time: 20.06 s +2024-11-21 14:39:59.886879: +2024-11-21 14:39:59.887091: Epoch 732 +2024-11-21 14:39:59.887203: Current learning rate: 0.00917 +2024-11-21 14:40:18.375287: train_loss -0.7695 +2024-11-21 14:40:18.375505: val_loss -0.762 +2024-11-21 14:40:18.375578: Pseudo dice [0.8322] +2024-11-21 14:40:18.375662: Epoch time: 18.49 s +2024-11-21 14:40:19.261892: +2024-11-21 14:40:19.262078: Epoch 733 +2024-11-21 14:40:19.262187: Current learning rate: 0.00917 +2024-11-21 14:40:37.231049: train_loss -0.7664 +2024-11-21 14:40:37.231283: val_loss -0.7185 +2024-11-21 14:40:37.231360: Pseudo dice [0.7983] +2024-11-21 14:40:37.231439: Epoch time: 17.97 s +2024-11-21 14:40:38.044027: +2024-11-21 14:40:38.044246: Epoch 734 +2024-11-21 14:40:38.044368: Current learning rate: 0.00917 +2024-11-21 14:40:57.201431: train_loss -0.7646 +2024-11-21 14:40:57.201638: val_loss -0.7281 +2024-11-21 14:40:57.201714: Pseudo dice [0.8308] +2024-11-21 14:40:57.201793: Epoch time: 19.16 s +2024-11-21 14:40:58.013878: +2024-11-21 14:40:58.014067: Epoch 735 +2024-11-21 14:40:58.014180: Current learning rate: 0.00917 +2024-11-21 14:41:15.880436: train_loss -0.7578 +2024-11-21 14:41:15.880675: val_loss -0.6914 +2024-11-21 14:41:15.880748: Pseudo dice [0.7939] +2024-11-21 14:41:15.880826: Epoch time: 17.87 s +2024-11-21 14:41:16.804109: +2024-11-21 14:41:16.804341: Epoch 736 +2024-11-21 14:41:16.804456: Current learning rate: 0.00917 +2024-11-21 14:41:35.050157: train_loss -0.7461 +2024-11-21 14:41:35.050401: val_loss -0.6969 +2024-11-21 14:41:35.050476: Pseudo dice [0.7848] +2024-11-21 14:41:35.050558: Epoch time: 18.25 s +2024-11-21 14:41:35.863364: +2024-11-21 14:41:35.863887: Epoch 737 +2024-11-21 14:41:35.864018: Current learning rate: 0.00917 +2024-11-21 14:41:54.076285: train_loss -0.7365 +2024-11-21 14:41:54.076550: val_loss -0.7294 +2024-11-21 14:41:54.076625: Pseudo dice [0.8103] +2024-11-21 14:41:54.076699: Epoch time: 18.21 s +2024-11-21 14:41:54.918920: +2024-11-21 14:41:54.919132: Epoch 738 +2024-11-21 14:41:54.919247: Current learning rate: 0.00917 +2024-11-21 14:42:13.764215: train_loss -0.7493 +2024-11-21 14:42:13.764431: val_loss -0.7234 +2024-11-21 14:42:13.764506: Pseudo dice [0.815] +2024-11-21 14:42:13.764583: Epoch time: 18.85 s +2024-11-21 14:42:14.575634: +2024-11-21 14:42:14.575878: Epoch 739 +2024-11-21 14:42:14.575997: Current learning rate: 0.00916 +2024-11-21 14:42:33.135667: train_loss -0.7545 +2024-11-21 14:42:33.135923: val_loss -0.7636 +2024-11-21 14:42:33.136005: Pseudo dice [0.8378] +2024-11-21 14:42:33.136098: Epoch time: 18.56 s +2024-11-21 14:42:33.951917: +2024-11-21 14:42:33.952152: Epoch 740 +2024-11-21 14:42:33.952275: Current learning rate: 0.00916 +2024-11-21 14:42:52.289669: train_loss -0.7704 +2024-11-21 14:42:52.292518: val_loss -0.75 +2024-11-21 14:42:52.292642: Pseudo dice [0.8137] +2024-11-21 14:42:52.292724: Epoch time: 18.34 s +2024-11-21 14:42:53.201178: +2024-11-21 14:42:53.201459: Epoch 741 +2024-11-21 14:42:53.201588: Current learning rate: 0.00916 +2024-11-21 14:43:11.605326: train_loss -0.749 +2024-11-21 14:43:11.605534: val_loss -0.7373 +2024-11-21 14:43:11.605610: Pseudo dice [0.8254] +2024-11-21 14:43:11.605687: Epoch time: 18.4 s +2024-11-21 14:43:12.419710: +2024-11-21 14:43:12.419919: Epoch 742 +2024-11-21 14:43:12.420039: Current learning rate: 0.00916 +2024-11-21 14:43:30.662731: train_loss -0.7679 +2024-11-21 14:43:30.662947: val_loss -0.7458 +2024-11-21 14:43:30.663027: Pseudo dice [0.8241] +2024-11-21 14:43:30.663104: Epoch time: 18.24 s +2024-11-21 14:43:31.479129: +2024-11-21 14:43:31.479313: Epoch 743 +2024-11-21 14:43:31.479426: Current learning rate: 0.00916 +2024-11-21 14:43:50.031578: train_loss -0.7664 +2024-11-21 14:43:50.031810: val_loss -0.7177 +2024-11-21 14:43:50.031885: Pseudo dice [0.8195] +2024-11-21 14:43:50.031970: Epoch time: 18.55 s +2024-11-21 14:43:50.855519: +2024-11-21 14:43:50.855707: Epoch 744 +2024-11-21 14:43:50.855820: Current learning rate: 0.00916 +2024-11-21 14:44:10.707046: train_loss -0.7585 +2024-11-21 14:44:10.707257: val_loss -0.747 +2024-11-21 14:44:10.707329: Pseudo dice [0.8226] +2024-11-21 14:44:10.707406: Epoch time: 19.85 s +2024-11-21 14:44:11.526466: +2024-11-21 14:44:11.526657: Epoch 745 +2024-11-21 14:44:11.526768: Current learning rate: 0.00916 +2024-11-21 14:44:30.923929: train_loss -0.7452 +2024-11-21 14:44:30.929302: val_loss -0.7264 +2024-11-21 14:44:30.929458: Pseudo dice [0.8257] +2024-11-21 14:44:30.929539: Epoch time: 19.4 s +2024-11-21 14:44:31.907109: +2024-11-21 14:44:31.907323: Epoch 746 +2024-11-21 14:44:31.907440: Current learning rate: 0.00916 +2024-11-21 14:44:50.671769: train_loss -0.7537 +2024-11-21 14:44:50.671977: val_loss -0.735 +2024-11-21 14:44:50.672059: Pseudo dice [0.8272] +2024-11-21 14:44:50.672140: Epoch time: 18.77 s +2024-11-21 14:44:51.485205: +2024-11-21 14:44:51.485408: Epoch 747 +2024-11-21 14:44:51.485521: Current learning rate: 0.00916 +2024-11-21 14:45:10.129534: train_loss -0.7713 +2024-11-21 14:45:10.129851: val_loss -0.7459 +2024-11-21 14:45:10.129924: Pseudo dice [0.8287] +2024-11-21 14:45:10.130009: Epoch time: 18.65 s +2024-11-21 14:45:11.336648: +2024-11-21 14:45:11.336933: Epoch 748 +2024-11-21 14:45:11.337047: Current learning rate: 0.00915 +2024-11-21 14:45:29.357153: train_loss -0.7726 +2024-11-21 14:45:29.357364: val_loss -0.7513 +2024-11-21 14:45:29.357460: Pseudo dice [0.8259] +2024-11-21 14:45:29.357539: Epoch time: 18.02 s +2024-11-21 14:45:30.168790: +2024-11-21 14:45:30.169070: Epoch 749 +2024-11-21 14:45:30.169186: Current learning rate: 0.00915 +2024-11-21 14:45:48.694845: train_loss -0.7516 +2024-11-21 14:45:48.695070: val_loss -0.7325 +2024-11-21 14:45:48.695143: Pseudo dice [0.8121] +2024-11-21 14:45:48.695820: Epoch time: 18.53 s +2024-11-21 14:45:49.792365: +2024-11-21 14:45:49.792591: Epoch 750 +2024-11-21 14:45:49.792702: Current learning rate: 0.00915 +2024-11-21 14:46:08.562195: train_loss -0.756 +2024-11-21 14:46:08.562428: val_loss -0.7421 +2024-11-21 14:46:08.562500: Pseudo dice [0.812] +2024-11-21 14:46:08.562585: Epoch time: 18.77 s +2024-11-21 14:46:09.384513: +2024-11-21 14:46:09.384723: Epoch 751 +2024-11-21 14:46:09.384833: Current learning rate: 0.00915 +2024-11-21 14:46:27.913409: train_loss -0.7694 +2024-11-21 14:46:27.913670: val_loss -0.7424 +2024-11-21 14:46:27.913745: Pseudo dice [0.8232] +2024-11-21 14:46:27.913822: Epoch time: 18.53 s +2024-11-21 14:46:28.729440: +2024-11-21 14:46:28.729689: Epoch 752 +2024-11-21 14:46:28.729810: Current learning rate: 0.00915 +2024-11-21 14:46:47.803913: train_loss -0.7654 +2024-11-21 14:46:47.804132: val_loss -0.7537 +2024-11-21 14:46:47.804208: Pseudo dice [0.8177] +2024-11-21 14:46:47.804282: Epoch time: 19.08 s +2024-11-21 14:46:48.622401: +2024-11-21 14:46:48.622616: Epoch 753 +2024-11-21 14:46:48.622728: Current learning rate: 0.00915 +2024-11-21 14:47:08.805234: train_loss -0.7696 +2024-11-21 14:47:08.805481: val_loss -0.7447 +2024-11-21 14:47:08.805559: Pseudo dice [0.8151] +2024-11-21 14:47:08.805988: Epoch time: 20.18 s +2024-11-21 14:47:09.623739: +2024-11-21 14:47:09.623958: Epoch 754 +2024-11-21 14:47:09.624080: Current learning rate: 0.00915 +2024-11-21 14:47:27.236280: train_loss -0.7581 +2024-11-21 14:47:27.236490: val_loss -0.755 +2024-11-21 14:47:27.236566: Pseudo dice [0.8195] +2024-11-21 14:47:27.236642: Epoch time: 17.61 s +2024-11-21 14:47:28.046489: +2024-11-21 14:47:28.046709: Epoch 755 +2024-11-21 14:47:28.046828: Current learning rate: 0.00915 +2024-11-21 14:47:46.647956: train_loss -0.764 +2024-11-21 14:47:46.648178: val_loss -0.7081 +2024-11-21 14:47:46.648258: Pseudo dice [0.815] +2024-11-21 14:47:46.648338: Epoch time: 18.6 s +2024-11-21 14:47:47.464530: +2024-11-21 14:47:47.464736: Epoch 756 +2024-11-21 14:47:47.464852: Current learning rate: 0.00915 +2024-11-21 14:48:06.815427: train_loss -0.7522 +2024-11-21 14:48:06.815631: val_loss -0.7129 +2024-11-21 14:48:06.815705: Pseudo dice [0.8034] +2024-11-21 14:48:06.815787: Epoch time: 19.35 s +2024-11-21 14:48:07.624011: +2024-11-21 14:48:07.624246: Epoch 757 +2024-11-21 14:48:07.624366: Current learning rate: 0.00914 +2024-11-21 14:48:26.085717: train_loss -0.7544 +2024-11-21 14:48:26.085972: val_loss -0.728 +2024-11-21 14:48:26.086054: Pseudo dice [0.8548] +2024-11-21 14:48:26.086137: Epoch time: 18.46 s +2024-11-21 14:48:27.023594: +2024-11-21 14:48:27.023804: Epoch 758 +2024-11-21 14:48:27.023919: Current learning rate: 0.00914 +2024-11-21 14:48:47.398408: train_loss -0.7535 +2024-11-21 14:48:47.398619: val_loss -0.7343 +2024-11-21 14:48:47.398691: Pseudo dice [0.8211] +2024-11-21 14:48:47.398766: Epoch time: 20.38 s +2024-11-21 14:48:48.222024: +2024-11-21 14:48:48.222303: Epoch 759 +2024-11-21 14:48:48.222420: Current learning rate: 0.00914 +2024-11-21 14:49:07.661129: train_loss -0.7643 +2024-11-21 14:49:07.661335: val_loss -0.7197 +2024-11-21 14:49:07.661411: Pseudo dice [0.7798] +2024-11-21 14:49:07.661484: Epoch time: 19.44 s +2024-11-21 14:49:08.473628: +2024-11-21 14:49:08.473887: Epoch 760 +2024-11-21 14:49:08.474017: Current learning rate: 0.00914 +2024-11-21 14:49:27.077311: train_loss -0.762 +2024-11-21 14:49:27.077544: val_loss -0.7664 +2024-11-21 14:49:27.077617: Pseudo dice [0.8301] +2024-11-21 14:49:27.077703: Epoch time: 18.6 s +2024-11-21 14:49:27.903922: +2024-11-21 14:49:27.904155: Epoch 761 +2024-11-21 14:49:27.904269: Current learning rate: 0.00914 +2024-11-21 14:49:46.239458: train_loss -0.7643 +2024-11-21 14:49:46.239663: val_loss -0.753 +2024-11-21 14:49:46.239737: Pseudo dice [0.8391] +2024-11-21 14:49:46.239811: Epoch time: 18.34 s +2024-11-21 14:49:47.048549: +2024-11-21 14:49:47.048758: Epoch 762 +2024-11-21 14:49:47.048873: Current learning rate: 0.00914 +2024-11-21 14:50:05.634743: train_loss -0.765 +2024-11-21 14:50:05.635231: val_loss -0.7226 +2024-11-21 14:50:05.635319: Pseudo dice [0.8241] +2024-11-21 14:50:05.635410: Epoch time: 18.59 s +2024-11-21 14:50:06.453286: +2024-11-21 14:50:06.453627: Epoch 763 +2024-11-21 14:50:06.453748: Current learning rate: 0.00914 +2024-11-21 14:50:25.117833: train_loss -0.7697 +2024-11-21 14:50:25.118092: val_loss -0.7375 +2024-11-21 14:50:25.118184: Pseudo dice [0.8122] +2024-11-21 14:50:25.118263: Epoch time: 18.66 s +2024-11-21 14:50:26.087707: +2024-11-21 14:50:26.087938: Epoch 764 +2024-11-21 14:50:26.088065: Current learning rate: 0.00914 +2024-11-21 14:50:45.429158: train_loss -0.7723 +2024-11-21 14:50:45.429399: val_loss -0.7404 +2024-11-21 14:50:45.429474: Pseudo dice [0.8279] +2024-11-21 14:50:45.429556: Epoch time: 19.34 s +2024-11-21 14:50:46.255344: +2024-11-21 14:50:46.255540: Epoch 765 +2024-11-21 14:50:46.255661: Current learning rate: 0.00914 +2024-11-21 14:51:03.404521: train_loss -0.7648 +2024-11-21 14:51:03.404751: val_loss -0.748 +2024-11-21 14:51:03.404825: Pseudo dice [0.8191] +2024-11-21 14:51:03.404904: Epoch time: 17.15 s +2024-11-21 14:51:04.345960: +2024-11-21 14:51:04.346232: Epoch 766 +2024-11-21 14:51:04.346347: Current learning rate: 0.00913 +2024-11-21 14:51:22.696374: train_loss -0.7707 +2024-11-21 14:51:22.696583: val_loss -0.736 +2024-11-21 14:51:22.696656: Pseudo dice [0.8327] +2024-11-21 14:51:22.696733: Epoch time: 18.35 s +2024-11-21 14:51:23.515478: +2024-11-21 14:51:23.515665: Epoch 767 +2024-11-21 14:51:23.515779: Current learning rate: 0.00913 +2024-11-21 14:51:41.991424: train_loss -0.7623 +2024-11-21 14:51:41.993803: val_loss -0.7361 +2024-11-21 14:51:41.993900: Pseudo dice [0.8177] +2024-11-21 14:51:41.993976: Epoch time: 18.48 s +2024-11-21 14:51:43.081005: +2024-11-21 14:51:43.081203: Epoch 768 +2024-11-21 14:51:43.081319: Current learning rate: 0.00913 +2024-11-21 14:52:01.812159: train_loss -0.7666 +2024-11-21 14:52:01.812396: val_loss -0.7408 +2024-11-21 14:52:01.812473: Pseudo dice [0.8102] +2024-11-21 14:52:01.812555: Epoch time: 18.73 s +2024-11-21 14:52:02.630054: +2024-11-21 14:52:02.630247: Epoch 769 +2024-11-21 14:52:02.630363: Current learning rate: 0.00913 +2024-11-21 14:52:20.019170: train_loss -0.7683 +2024-11-21 14:52:20.019388: val_loss -0.7525 +2024-11-21 14:52:20.019622: Pseudo dice [0.812] +2024-11-21 14:52:20.019712: Epoch time: 17.39 s +2024-11-21 14:52:21.193516: +2024-11-21 14:52:21.193732: Epoch 770 +2024-11-21 14:52:21.193851: Current learning rate: 0.00913 +2024-11-21 14:52:39.824761: train_loss -0.7624 +2024-11-21 14:52:39.824986: val_loss -0.7608 +2024-11-21 14:52:39.825069: Pseudo dice [0.8278] +2024-11-21 14:52:39.825147: Epoch time: 18.63 s +2024-11-21 14:52:40.673689: +2024-11-21 14:52:40.673913: Epoch 771 +2024-11-21 14:52:40.674044: Current learning rate: 0.00913 +2024-11-21 14:52:59.426411: train_loss -0.7605 +2024-11-21 14:52:59.426648: val_loss -0.7312 +2024-11-21 14:52:59.426727: Pseudo dice [0.8171] +2024-11-21 14:52:59.426812: Epoch time: 18.75 s +2024-11-21 14:53:00.251405: +2024-11-21 14:53:00.251608: Epoch 772 +2024-11-21 14:53:00.251719: Current learning rate: 0.00913 +2024-11-21 14:53:19.748964: train_loss -0.7595 +2024-11-21 14:53:19.749189: val_loss -0.7394 +2024-11-21 14:53:19.749269: Pseudo dice [0.8253] +2024-11-21 14:53:19.749348: Epoch time: 19.5 s +2024-11-21 14:53:20.746055: +2024-11-21 14:53:20.746367: Epoch 773 +2024-11-21 14:53:20.746482: Current learning rate: 0.00913 +2024-11-21 14:53:39.294411: train_loss -0.754 +2024-11-21 14:53:39.294623: val_loss -0.7407 +2024-11-21 14:53:39.294698: Pseudo dice [0.8237] +2024-11-21 14:53:39.294772: Epoch time: 18.55 s +2024-11-21 14:53:40.116009: +2024-11-21 14:53:40.116361: Epoch 774 +2024-11-21 14:53:40.116476: Current learning rate: 0.00912 +2024-11-21 14:53:58.189514: train_loss -0.756 +2024-11-21 14:53:58.189724: val_loss -0.7216 +2024-11-21 14:53:58.191985: Pseudo dice [0.7973] +2024-11-21 14:53:58.192080: Epoch time: 18.07 s +2024-11-21 14:53:59.169417: +2024-11-21 14:53:59.169631: Epoch 775 +2024-11-21 14:53:59.169744: Current learning rate: 0.00912 +2024-11-21 14:54:17.758091: train_loss -0.7573 +2024-11-21 14:54:17.761294: val_loss -0.7481 +2024-11-21 14:54:17.761410: Pseudo dice [0.8286] +2024-11-21 14:54:17.761499: Epoch time: 18.59 s +2024-11-21 14:54:18.593962: +2024-11-21 14:54:18.594152: Epoch 776 +2024-11-21 14:54:18.594294: Current learning rate: 0.00912 +2024-11-21 14:54:38.390272: train_loss -0.7621 +2024-11-21 14:54:38.390481: val_loss -0.7279 +2024-11-21 14:54:38.390604: Pseudo dice [0.8277] +2024-11-21 14:54:38.390680: Epoch time: 19.8 s +2024-11-21 14:54:39.213449: +2024-11-21 14:54:39.213671: Epoch 777 +2024-11-21 14:54:39.213796: Current learning rate: 0.00912 +2024-11-21 14:54:58.202960: train_loss -0.7612 +2024-11-21 14:54:58.203182: val_loss -0.744 +2024-11-21 14:54:58.203254: Pseudo dice [0.8108] +2024-11-21 14:54:58.203330: Epoch time: 18.99 s +2024-11-21 14:54:59.021295: +2024-11-21 14:54:59.021494: Epoch 778 +2024-11-21 14:54:59.021610: Current learning rate: 0.00912 +2024-11-21 14:55:17.435911: train_loss -0.7556 +2024-11-21 14:55:17.436147: val_loss -0.7301 +2024-11-21 14:55:17.436226: Pseudo dice [0.8163] +2024-11-21 14:55:17.436310: Epoch time: 18.42 s +2024-11-21 14:55:18.331733: +2024-11-21 14:55:18.332009: Epoch 779 +2024-11-21 14:55:18.332121: Current learning rate: 0.00912 +2024-11-21 14:55:36.852887: train_loss -0.7564 +2024-11-21 14:55:36.853121: val_loss -0.7188 +2024-11-21 14:55:36.853195: Pseudo dice [0.8074] +2024-11-21 14:55:36.853271: Epoch time: 18.52 s +2024-11-21 14:55:37.675454: +2024-11-21 14:55:37.675715: Epoch 780 +2024-11-21 14:55:37.675828: Current learning rate: 0.00912 +2024-11-21 14:55:56.135244: train_loss -0.7641 +2024-11-21 14:55:56.135491: val_loss -0.7563 +2024-11-21 14:55:56.135569: Pseudo dice [0.8267] +2024-11-21 14:55:56.135648: Epoch time: 18.46 s +2024-11-21 14:55:57.077460: +2024-11-21 14:55:57.077655: Epoch 781 +2024-11-21 14:55:57.077770: Current learning rate: 0.00912 +2024-11-21 14:56:15.717447: train_loss -0.7655 +2024-11-21 14:56:15.717654: val_loss -0.7356 +2024-11-21 14:56:15.717729: Pseudo dice [0.8286] +2024-11-21 14:56:15.717804: Epoch time: 18.64 s +2024-11-21 14:56:17.153953: +2024-11-21 14:56:17.154194: Epoch 782 +2024-11-21 14:56:17.154307: Current learning rate: 0.00912 +2024-11-21 14:56:36.005783: train_loss -0.7531 +2024-11-21 14:56:36.006027: val_loss -0.7514 +2024-11-21 14:56:36.006103: Pseudo dice [0.8175] +2024-11-21 14:56:36.006193: Epoch time: 18.85 s +2024-11-21 14:56:36.830123: +2024-11-21 14:56:36.830364: Epoch 783 +2024-11-21 14:56:36.830484: Current learning rate: 0.00911 +2024-11-21 14:56:55.437924: train_loss -0.7383 +2024-11-21 14:56:55.438151: val_loss -0.6829 +2024-11-21 14:56:55.438233: Pseudo dice [0.7337] +2024-11-21 14:56:55.438327: Epoch time: 18.61 s +2024-11-21 14:56:56.265520: +2024-11-21 14:56:56.265801: Epoch 784 +2024-11-21 14:56:56.265921: Current learning rate: 0.00911 +2024-11-21 14:57:15.353510: train_loss -0.7357 +2024-11-21 14:57:15.353719: val_loss -0.7294 +2024-11-21 14:57:15.353794: Pseudo dice [0.7996] +2024-11-21 14:57:15.353872: Epoch time: 19.09 s +2024-11-21 14:57:16.272371: +2024-11-21 14:57:16.272562: Epoch 785 +2024-11-21 14:57:16.272671: Current learning rate: 0.00911 +2024-11-21 14:57:34.445463: train_loss -0.7527 +2024-11-21 14:57:34.450857: val_loss -0.7313 +2024-11-21 14:57:34.450974: Pseudo dice [0.817] +2024-11-21 14:57:34.451074: Epoch time: 18.17 s +2024-11-21 14:57:35.533187: +2024-11-21 14:57:35.533417: Epoch 786 +2024-11-21 14:57:35.533537: Current learning rate: 0.00911 +2024-11-21 14:57:53.972412: train_loss -0.7483 +2024-11-21 14:57:53.972655: val_loss -0.7152 +2024-11-21 14:57:53.972729: Pseudo dice [0.7969] +2024-11-21 14:57:53.972810: Epoch time: 18.44 s +2024-11-21 14:57:55.085792: +2024-11-21 14:57:55.086016: Epoch 787 +2024-11-21 14:57:55.086132: Current learning rate: 0.00911 +2024-11-21 14:58:13.078187: train_loss -0.7465 +2024-11-21 14:58:13.078406: val_loss -0.7058 +2024-11-21 14:58:13.078480: Pseudo dice [0.7937] +2024-11-21 14:58:13.078555: Epoch time: 17.99 s +2024-11-21 14:58:14.137932: +2024-11-21 14:58:14.138153: Epoch 788 +2024-11-21 14:58:14.138267: Current learning rate: 0.00911 +2024-11-21 14:58:33.259389: train_loss -0.7556 +2024-11-21 14:58:33.259619: val_loss -0.72 +2024-11-21 14:58:33.259695: Pseudo dice [0.8281] +2024-11-21 14:58:33.259773: Epoch time: 19.12 s +2024-11-21 14:58:34.084139: +2024-11-21 14:58:34.084504: Epoch 789 +2024-11-21 14:58:34.084623: Current learning rate: 0.00911 +2024-11-21 14:58:53.114880: train_loss -0.7505 +2024-11-21 14:58:53.116210: val_loss -0.7031 +2024-11-21 14:58:53.116360: Pseudo dice [0.8143] +2024-11-21 14:58:53.116455: Epoch time: 19.03 s +2024-11-21 14:58:53.944898: +2024-11-21 14:58:53.945128: Epoch 790 +2024-11-21 14:58:53.945250: Current learning rate: 0.00911 +2024-11-21 14:59:13.897419: train_loss -0.7451 +2024-11-21 14:59:13.897674: val_loss -0.7092 +2024-11-21 14:59:13.897749: Pseudo dice [0.8119] +2024-11-21 14:59:13.897831: Epoch time: 19.95 s +2024-11-21 14:59:14.740110: +2024-11-21 14:59:14.740308: Epoch 791 +2024-11-21 14:59:14.740425: Current learning rate: 0.00911 +2024-11-21 14:59:33.978057: train_loss -0.7242 +2024-11-21 14:59:33.978277: val_loss -0.7246 +2024-11-21 14:59:33.978351: Pseudo dice [0.8004] +2024-11-21 14:59:33.978440: Epoch time: 19.24 s +2024-11-21 14:59:34.794966: +2024-11-21 14:59:34.795177: Epoch 792 +2024-11-21 14:59:34.795296: Current learning rate: 0.0091 +2024-11-21 14:59:54.551169: train_loss -0.7496 +2024-11-21 14:59:54.551368: val_loss -0.7187 +2024-11-21 14:59:54.551442: Pseudo dice [0.8052] +2024-11-21 14:59:54.551517: Epoch time: 19.76 s +2024-11-21 14:59:55.756959: +2024-11-21 14:59:55.757345: Epoch 793 +2024-11-21 14:59:55.757466: Current learning rate: 0.0091 +2024-11-21 15:00:14.564929: train_loss -0.7568 +2024-11-21 15:00:14.565210: val_loss -0.7218 +2024-11-21 15:00:14.565287: Pseudo dice [0.817] +2024-11-21 15:00:14.565372: Epoch time: 18.81 s +2024-11-21 15:00:15.424382: +2024-11-21 15:00:15.424725: Epoch 794 +2024-11-21 15:00:15.424846: Current learning rate: 0.0091 +2024-11-21 15:00:34.714262: train_loss -0.7604 +2024-11-21 15:00:34.714504: val_loss -0.7065 +2024-11-21 15:00:34.714580: Pseudo dice [0.8238] +2024-11-21 15:00:34.714659: Epoch time: 19.29 s +2024-11-21 15:00:35.541375: +2024-11-21 15:00:35.541638: Epoch 795 +2024-11-21 15:00:35.541752: Current learning rate: 0.0091 +2024-11-21 15:00:54.616500: train_loss -0.7415 +2024-11-21 15:00:54.616780: val_loss -0.7417 +2024-11-21 15:00:54.616862: Pseudo dice [0.819] +2024-11-21 15:00:54.616944: Epoch time: 19.08 s +2024-11-21 15:00:55.542010: +2024-11-21 15:00:55.542211: Epoch 796 +2024-11-21 15:00:55.542322: Current learning rate: 0.0091 +2024-11-21 15:01:14.211463: train_loss -0.7507 +2024-11-21 15:01:14.211675: val_loss -0.7314 +2024-11-21 15:01:14.211749: Pseudo dice [0.8168] +2024-11-21 15:01:14.211840: Epoch time: 18.67 s +2024-11-21 15:01:15.037949: +2024-11-21 15:01:15.038160: Epoch 797 +2024-11-21 15:01:15.038275: Current learning rate: 0.0091 +2024-11-21 15:01:32.758717: train_loss -0.7613 +2024-11-21 15:01:32.758959: val_loss -0.7116 +2024-11-21 15:01:32.759042: Pseudo dice [0.8054] +2024-11-21 15:01:32.759128: Epoch time: 17.72 s +2024-11-21 15:01:33.587062: +2024-11-21 15:01:33.587279: Epoch 798 +2024-11-21 15:01:33.587395: Current learning rate: 0.0091 +2024-11-21 15:01:51.013693: train_loss -0.7533 +2024-11-21 15:01:51.013911: val_loss -0.7391 +2024-11-21 15:01:51.013984: Pseudo dice [0.8163] +2024-11-21 15:01:51.014066: Epoch time: 17.43 s +2024-11-21 15:01:51.856548: +2024-11-21 15:01:51.856802: Epoch 799 +2024-11-21 15:01:51.856918: Current learning rate: 0.0091 +2024-11-21 15:02:11.076264: train_loss -0.7584 +2024-11-21 15:02:11.076474: val_loss -0.7403 +2024-11-21 15:02:11.076545: Pseudo dice [0.8252] +2024-11-21 15:02:11.076617: Epoch time: 19.22 s +2024-11-21 15:02:12.194257: +2024-11-21 15:02:12.194500: Epoch 800 +2024-11-21 15:02:12.194618: Current learning rate: 0.0091 +2024-11-21 15:02:30.973330: train_loss -0.7657 +2024-11-21 15:02:30.973545: val_loss -0.7526 +2024-11-21 15:02:30.973645: Pseudo dice [0.8262] +2024-11-21 15:02:30.980222: Epoch time: 18.78 s +2024-11-21 15:02:31.807795: +2024-11-21 15:02:31.808029: Epoch 801 +2024-11-21 15:02:31.808147: Current learning rate: 0.00909 +2024-11-21 15:02:50.363604: train_loss -0.7636 +2024-11-21 15:02:50.363857: val_loss -0.7485 +2024-11-21 15:02:50.363960: Pseudo dice [0.8183] +2024-11-21 15:02:50.364048: Epoch time: 18.56 s +2024-11-21 15:02:51.196630: +2024-11-21 15:02:51.196918: Epoch 802 +2024-11-21 15:02:51.197042: Current learning rate: 0.00909 +2024-11-21 15:03:09.300634: train_loss -0.7606 +2024-11-21 15:03:09.300841: val_loss -0.7259 +2024-11-21 15:03:09.300913: Pseudo dice [0.8242] +2024-11-21 15:03:09.300988: Epoch time: 18.1 s +2024-11-21 15:03:10.125259: +2024-11-21 15:03:10.125444: Epoch 803 +2024-11-21 15:03:10.125589: Current learning rate: 0.00909 +2024-11-21 15:03:27.832747: train_loss -0.7659 +2024-11-21 15:03:27.832948: val_loss -0.7356 +2024-11-21 15:03:27.833031: Pseudo dice [0.8256] +2024-11-21 15:03:27.833105: Epoch time: 17.71 s +2024-11-21 15:03:29.028206: +2024-11-21 15:03:29.028470: Epoch 804 +2024-11-21 15:03:29.028589: Current learning rate: 0.00909 +2024-11-21 15:03:47.498499: train_loss -0.7673 +2024-11-21 15:03:47.498756: val_loss -0.7322 +2024-11-21 15:03:47.507148: Pseudo dice [0.8317] +2024-11-21 15:03:47.507313: Epoch time: 18.47 s +2024-11-21 15:03:48.418939: +2024-11-21 15:03:48.419188: Epoch 805 +2024-11-21 15:03:48.419301: Current learning rate: 0.00909 +2024-11-21 15:04:07.812821: train_loss -0.7654 +2024-11-21 15:04:07.813040: val_loss -0.7143 +2024-11-21 15:04:07.813112: Pseudo dice [0.8211] +2024-11-21 15:04:07.813188: Epoch time: 19.39 s +2024-11-21 15:04:08.638298: +2024-11-21 15:04:08.638539: Epoch 806 +2024-11-21 15:04:08.638652: Current learning rate: 0.00909 +2024-11-21 15:04:26.635706: train_loss -0.7661 +2024-11-21 15:04:26.635935: val_loss -0.7471 +2024-11-21 15:04:26.636018: Pseudo dice [0.8431] +2024-11-21 15:04:26.636094: Epoch time: 18.0 s +2024-11-21 15:04:27.466290: +2024-11-21 15:04:27.466504: Epoch 807 +2024-11-21 15:04:27.466621: Current learning rate: 0.00909 +2024-11-21 15:04:45.868246: train_loss -0.7602 +2024-11-21 15:04:45.868456: val_loss -0.7459 +2024-11-21 15:04:45.868532: Pseudo dice [0.8106] +2024-11-21 15:04:45.868610: Epoch time: 18.4 s +2024-11-21 15:04:46.702740: +2024-11-21 15:04:46.702955: Epoch 808 +2024-11-21 15:04:46.703090: Current learning rate: 0.00909 +2024-11-21 15:05:05.987507: train_loss -0.7656 +2024-11-21 15:05:05.987741: val_loss -0.7326 +2024-11-21 15:05:05.987816: Pseudo dice [0.8087] +2024-11-21 15:05:05.987898: Epoch time: 19.29 s +2024-11-21 15:05:06.816156: +2024-11-21 15:05:06.816364: Epoch 809 +2024-11-21 15:05:06.816480: Current learning rate: 0.00909 +2024-11-21 15:05:26.405831: train_loss -0.7685 +2024-11-21 15:05:26.406052: val_loss -0.7077 +2024-11-21 15:05:26.406126: Pseudo dice [0.8091] +2024-11-21 15:05:26.410419: Epoch time: 19.59 s +2024-11-21 15:05:27.282978: +2024-11-21 15:05:27.283405: Epoch 810 +2024-11-21 15:05:27.283525: Current learning rate: 0.00908 +2024-11-21 15:05:46.193639: train_loss -0.7476 +2024-11-21 15:05:46.193857: val_loss -0.7388 +2024-11-21 15:05:46.193932: Pseudo dice [0.8068] +2024-11-21 15:05:46.194017: Epoch time: 18.91 s +2024-11-21 15:05:47.019559: +2024-11-21 15:05:47.019785: Epoch 811 +2024-11-21 15:05:47.019900: Current learning rate: 0.00908 +2024-11-21 15:06:05.698101: train_loss -0.7635 +2024-11-21 15:06:05.698321: val_loss -0.7339 +2024-11-21 15:06:05.698395: Pseudo dice [0.7992] +2024-11-21 15:06:05.698476: Epoch time: 18.68 s +2024-11-21 15:06:06.521023: +2024-11-21 15:06:06.521207: Epoch 812 +2024-11-21 15:06:06.521324: Current learning rate: 0.00908 +2024-11-21 15:06:24.776358: train_loss -0.7529 +2024-11-21 15:06:24.776629: val_loss -0.7349 +2024-11-21 15:06:24.776709: Pseudo dice [0.8126] +2024-11-21 15:06:24.776848: Epoch time: 18.26 s +2024-11-21 15:06:25.639922: +2024-11-21 15:06:25.640131: Epoch 813 +2024-11-21 15:06:25.640248: Current learning rate: 0.00908 +2024-11-21 15:06:44.950096: train_loss -0.7575 +2024-11-21 15:06:44.961343: val_loss -0.7449 +2024-11-21 15:06:44.961430: Pseudo dice [0.817] +2024-11-21 15:06:44.961507: Epoch time: 19.31 s +2024-11-21 15:06:45.796102: +2024-11-21 15:06:45.796297: Epoch 814 +2024-11-21 15:06:45.796417: Current learning rate: 0.00908 +2024-11-21 15:07:04.195797: train_loss -0.7675 +2024-11-21 15:07:04.196803: val_loss -0.7421 +2024-11-21 15:07:04.196880: Pseudo dice [0.8291] +2024-11-21 15:07:04.196953: Epoch time: 18.4 s +2024-11-21 15:07:05.020441: +2024-11-21 15:07:05.020828: Epoch 815 +2024-11-21 15:07:05.020951: Current learning rate: 0.00908 +2024-11-21 15:07:23.741930: train_loss -0.7663 +2024-11-21 15:07:23.742172: val_loss -0.7595 +2024-11-21 15:07:23.742246: Pseudo dice [0.8316] +2024-11-21 15:07:23.742330: Epoch time: 18.72 s +2024-11-21 15:07:24.996530: +2024-11-21 15:07:24.996854: Epoch 816 +2024-11-21 15:07:24.996974: Current learning rate: 0.00908 +2024-11-21 15:07:43.388109: train_loss -0.7615 +2024-11-21 15:07:43.388336: val_loss -0.7586 +2024-11-21 15:07:43.388411: Pseudo dice [0.8381] +2024-11-21 15:07:43.393688: Epoch time: 18.39 s +2024-11-21 15:07:44.380563: +2024-11-21 15:07:44.380843: Epoch 817 +2024-11-21 15:07:44.380959: Current learning rate: 0.00908 +2024-11-21 15:08:03.389232: train_loss -0.7576 +2024-11-21 15:08:03.389465: val_loss -0.7378 +2024-11-21 15:08:03.389538: Pseudo dice [0.8167] +2024-11-21 15:08:03.389615: Epoch time: 19.01 s +2024-11-21 15:08:04.211775: +2024-11-21 15:08:04.212007: Epoch 818 +2024-11-21 15:08:04.212122: Current learning rate: 0.00907 +2024-11-21 15:08:23.406812: train_loss -0.7599 +2024-11-21 15:08:23.407063: val_loss -0.7441 +2024-11-21 15:08:23.407140: Pseudo dice [0.8144] +2024-11-21 15:08:23.407227: Epoch time: 19.2 s +2024-11-21 15:08:24.378772: +2024-11-21 15:08:24.378971: Epoch 819 +2024-11-21 15:08:24.379089: Current learning rate: 0.00907 +2024-11-21 15:08:42.174201: train_loss -0.7639 +2024-11-21 15:08:42.179606: val_loss -0.7394 +2024-11-21 15:08:42.179694: Pseudo dice [0.8083] +2024-11-21 15:08:42.179776: Epoch time: 17.8 s +2024-11-21 15:08:43.023707: +2024-11-21 15:08:43.023909: Epoch 820 +2024-11-21 15:08:43.024026: Current learning rate: 0.00907 +2024-11-21 15:09:01.522233: train_loss -0.7555 +2024-11-21 15:09:01.522444: val_loss -0.7342 +2024-11-21 15:09:01.522523: Pseudo dice [0.8174] +2024-11-21 15:09:01.522609: Epoch time: 18.5 s +2024-11-21 15:09:02.324766: +2024-11-21 15:09:02.324960: Epoch 821 +2024-11-21 15:09:02.325077: Current learning rate: 0.00907 +2024-11-21 15:09:20.232190: train_loss -0.7633 +2024-11-21 15:09:20.232419: val_loss -0.7446 +2024-11-21 15:09:20.232496: Pseudo dice [0.8144] +2024-11-21 15:09:20.232601: Epoch time: 17.91 s +2024-11-21 15:09:21.033863: +2024-11-21 15:09:21.034087: Epoch 822 +2024-11-21 15:09:21.034212: Current learning rate: 0.00907 +2024-11-21 15:09:40.273609: train_loss -0.7735 +2024-11-21 15:09:40.273850: val_loss -0.7418 +2024-11-21 15:09:40.273954: Pseudo dice [0.8267] +2024-11-21 15:09:40.274043: Epoch time: 19.24 s +2024-11-21 15:09:41.070421: +2024-11-21 15:09:41.070774: Epoch 823 +2024-11-21 15:09:41.070889: Current learning rate: 0.00907 +2024-11-21 15:09:59.460342: train_loss -0.7613 +2024-11-21 15:09:59.460546: val_loss -0.6953 +2024-11-21 15:09:59.460622: Pseudo dice [0.8024] +2024-11-21 15:09:59.460695: Epoch time: 18.39 s +2024-11-21 15:10:00.269659: +2024-11-21 15:10:00.269881: Epoch 824 +2024-11-21 15:10:00.270010: Current learning rate: 0.00907 +2024-11-21 15:10:19.605288: train_loss -0.7717 +2024-11-21 15:10:19.605519: val_loss -0.7076 +2024-11-21 15:10:19.605593: Pseudo dice [0.8178] +2024-11-21 15:10:19.605669: Epoch time: 19.34 s +2024-11-21 15:10:20.406071: +2024-11-21 15:10:20.406352: Epoch 825 +2024-11-21 15:10:20.406466: Current learning rate: 0.00907 +2024-11-21 15:10:40.170737: train_loss -0.7629 +2024-11-21 15:10:40.170966: val_loss -0.7493 +2024-11-21 15:10:40.171053: Pseudo dice [0.8354] +2024-11-21 15:10:40.171137: Epoch time: 19.77 s +2024-11-21 15:10:40.974130: +2024-11-21 15:10:40.974400: Epoch 826 +2024-11-21 15:10:40.974512: Current learning rate: 0.00907 +2024-11-21 15:11:01.246185: train_loss -0.7553 +2024-11-21 15:11:01.246395: val_loss -0.7211 +2024-11-21 15:11:01.246470: Pseudo dice [0.8086] +2024-11-21 15:11:01.246547: Epoch time: 20.27 s +2024-11-21 15:11:02.037191: +2024-11-21 15:11:02.037396: Epoch 827 +2024-11-21 15:11:02.037513: Current learning rate: 0.00906 +2024-11-21 15:11:21.163769: train_loss -0.7698 +2024-11-21 15:11:21.163981: val_loss -0.7366 +2024-11-21 15:11:21.164090: Pseudo dice [0.8021] +2024-11-21 15:11:21.164167: Epoch time: 19.13 s +2024-11-21 15:11:22.302117: +2024-11-21 15:11:22.302354: Epoch 828 +2024-11-21 15:11:22.302468: Current learning rate: 0.00906 +2024-11-21 15:11:40.474941: train_loss -0.7505 +2024-11-21 15:11:40.475219: val_loss -0.7414 +2024-11-21 15:11:40.475374: Pseudo dice [0.8102] +2024-11-21 15:11:40.475460: Epoch time: 18.17 s +2024-11-21 15:11:41.280035: +2024-11-21 15:11:41.280285: Epoch 829 +2024-11-21 15:11:41.280398: Current learning rate: 0.00906 +2024-11-21 15:12:00.413082: train_loss -0.7609 +2024-11-21 15:12:00.415580: val_loss -0.7484 +2024-11-21 15:12:00.415675: Pseudo dice [0.8157] +2024-11-21 15:12:00.415749: Epoch time: 19.13 s +2024-11-21 15:12:01.225283: +2024-11-21 15:12:01.225512: Epoch 830 +2024-11-21 15:12:01.225628: Current learning rate: 0.00906 +2024-11-21 15:12:19.236334: train_loss -0.7621 +2024-11-21 15:12:19.236538: val_loss -0.7185 +2024-11-21 15:12:19.236609: Pseudo dice [0.8104] +2024-11-21 15:12:19.236685: Epoch time: 18.01 s +2024-11-21 15:12:20.032004: +2024-11-21 15:12:20.032223: Epoch 831 +2024-11-21 15:12:20.032338: Current learning rate: 0.00906 +2024-11-21 15:12:39.541004: train_loss -0.7603 +2024-11-21 15:12:39.542739: val_loss -0.7166 +2024-11-21 15:12:39.542830: Pseudo dice [0.8297] +2024-11-21 15:12:39.542971: Epoch time: 19.51 s +2024-11-21 15:12:40.456848: +2024-11-21 15:12:40.457067: Epoch 832 +2024-11-21 15:12:40.457183: Current learning rate: 0.00906 +2024-11-21 15:12:58.896968: train_loss -0.7689 +2024-11-21 15:12:58.897203: val_loss -0.7501 +2024-11-21 15:12:58.897276: Pseudo dice [0.8201] +2024-11-21 15:12:58.897352: Epoch time: 18.44 s +2024-11-21 15:12:59.706006: +2024-11-21 15:12:59.706235: Epoch 833 +2024-11-21 15:12:59.706352: Current learning rate: 0.00906 +2024-11-21 15:13:18.493842: train_loss -0.7685 +2024-11-21 15:13:18.494056: val_loss -0.7162 +2024-11-21 15:13:18.494129: Pseudo dice [0.8204] +2024-11-21 15:13:18.494203: Epoch time: 18.79 s +2024-11-21 15:13:19.283509: +2024-11-21 15:13:19.283720: Epoch 834 +2024-11-21 15:13:19.283825: Current learning rate: 0.00906 +2024-11-21 15:13:36.753122: train_loss -0.7692 +2024-11-21 15:13:36.753339: val_loss -0.7083 +2024-11-21 15:13:36.753413: Pseudo dice [0.8173] +2024-11-21 15:13:36.753493: Epoch time: 17.47 s +2024-11-21 15:13:37.551850: +2024-11-21 15:13:37.552059: Epoch 835 +2024-11-21 15:13:37.552169: Current learning rate: 0.00906 +2024-11-21 15:13:57.017156: train_loss -0.7658 +2024-11-21 15:13:57.017376: val_loss -0.7229 +2024-11-21 15:13:57.017455: Pseudo dice [0.8375] +2024-11-21 15:13:57.017534: Epoch time: 19.47 s +2024-11-21 15:13:57.816116: +2024-11-21 15:13:57.816388: Epoch 836 +2024-11-21 15:13:57.816500: Current learning rate: 0.00905 +2024-11-21 15:14:16.285964: train_loss -0.7659 +2024-11-21 15:14:16.286238: val_loss -0.7191 +2024-11-21 15:14:16.286315: Pseudo dice [0.8295] +2024-11-21 15:14:16.286392: Epoch time: 18.47 s +2024-11-21 15:14:17.079159: +2024-11-21 15:14:17.079388: Epoch 837 +2024-11-21 15:14:17.079503: Current learning rate: 0.00905 +2024-11-21 15:14:36.390343: train_loss -0.7667 +2024-11-21 15:14:36.390564: val_loss -0.748 +2024-11-21 15:14:36.395832: Pseudo dice [0.8159] +2024-11-21 15:14:36.395957: Epoch time: 19.31 s +2024-11-21 15:14:37.238282: +2024-11-21 15:14:37.238502: Epoch 838 +2024-11-21 15:14:37.238617: Current learning rate: 0.00905 +2024-11-21 15:14:57.141795: train_loss -0.7686 +2024-11-21 15:14:57.142029: val_loss -0.7413 +2024-11-21 15:14:57.142112: Pseudo dice [0.8155] +2024-11-21 15:14:57.142236: Epoch time: 19.9 s +2024-11-21 15:14:57.973018: +2024-11-21 15:14:57.973218: Epoch 839 +2024-11-21 15:14:57.973329: Current learning rate: 0.00905 +2024-11-21 15:15:17.311072: train_loss -0.7601 +2024-11-21 15:15:17.311296: val_loss -0.7499 +2024-11-21 15:15:17.311371: Pseudo dice [0.828] +2024-11-21 15:15:17.311452: Epoch time: 19.34 s +2024-11-21 15:15:18.477940: +2024-11-21 15:15:18.478161: Epoch 840 +2024-11-21 15:15:18.478275: Current learning rate: 0.00905 +2024-11-21 15:15:37.116819: train_loss -0.7689 +2024-11-21 15:15:37.117055: val_loss -0.7463 +2024-11-21 15:15:37.117133: Pseudo dice [0.809] +2024-11-21 15:15:37.117210: Epoch time: 18.64 s +2024-11-21 15:15:37.907905: +2024-11-21 15:15:37.908182: Epoch 841 +2024-11-21 15:15:37.908310: Current learning rate: 0.00905 +2024-11-21 15:15:57.014858: train_loss -0.7564 +2024-11-21 15:15:57.015085: val_loss -0.7362 +2024-11-21 15:15:57.015158: Pseudo dice [0.8208] +2024-11-21 15:15:57.015234: Epoch time: 19.11 s +2024-11-21 15:15:57.795588: +2024-11-21 15:15:57.795816: Epoch 842 +2024-11-21 15:15:57.795927: Current learning rate: 0.00905 +2024-11-21 15:16:16.744890: train_loss -0.7513 +2024-11-21 15:16:16.745468: val_loss -0.6988 +2024-11-21 15:16:16.745566: Pseudo dice [0.7848] +2024-11-21 15:16:16.745651: Epoch time: 18.95 s +2024-11-21 15:16:17.550323: +2024-11-21 15:16:17.550559: Epoch 843 +2024-11-21 15:16:17.550678: Current learning rate: 0.00905 +2024-11-21 15:16:35.685603: train_loss -0.7509 +2024-11-21 15:16:35.685809: val_loss -0.7347 +2024-11-21 15:16:35.685886: Pseudo dice [0.8152] +2024-11-21 15:16:35.686023: Epoch time: 18.14 s +2024-11-21 15:16:36.583690: +2024-11-21 15:16:36.583918: Epoch 844 +2024-11-21 15:16:36.584041: Current learning rate: 0.00905 +2024-11-21 15:16:54.659330: train_loss -0.7674 +2024-11-21 15:16:54.659544: val_loss -0.7301 +2024-11-21 15:16:54.659617: Pseudo dice [0.817] +2024-11-21 15:16:54.659704: Epoch time: 18.08 s +2024-11-21 15:16:55.472205: +2024-11-21 15:16:55.472439: Epoch 845 +2024-11-21 15:16:55.472557: Current learning rate: 0.00904 +2024-11-21 15:17:14.352614: train_loss -0.7419 +2024-11-21 15:17:14.352829: val_loss -0.7252 +2024-11-21 15:17:14.352903: Pseudo dice [0.8065] +2024-11-21 15:17:14.352982: Epoch time: 18.88 s +2024-11-21 15:17:15.157130: +2024-11-21 15:17:15.157377: Epoch 846 +2024-11-21 15:17:15.157499: Current learning rate: 0.00904 +2024-11-21 15:17:34.401565: train_loss -0.7636 +2024-11-21 15:17:34.401803: val_loss -0.7408 +2024-11-21 15:17:34.402951: Pseudo dice [0.8242] +2024-11-21 15:17:34.403058: Epoch time: 19.25 s +2024-11-21 15:17:35.241724: +2024-11-21 15:17:35.241944: Epoch 847 +2024-11-21 15:17:35.242057: Current learning rate: 0.00904 +2024-11-21 15:17:54.232996: train_loss -0.7606 +2024-11-21 15:17:54.233237: val_loss -0.7293 +2024-11-21 15:17:54.233310: Pseudo dice [0.7891] +2024-11-21 15:17:54.233386: Epoch time: 18.99 s +2024-11-21 15:17:55.030266: +2024-11-21 15:17:55.030472: Epoch 848 +2024-11-21 15:17:55.030590: Current learning rate: 0.00904 +2024-11-21 15:18:12.609989: train_loss -0.7591 +2024-11-21 15:18:12.610217: val_loss -0.7449 +2024-11-21 15:18:12.610291: Pseudo dice [0.821] +2024-11-21 15:18:12.610367: Epoch time: 17.58 s +2024-11-21 15:18:13.513580: +2024-11-21 15:18:13.513828: Epoch 849 +2024-11-21 15:18:13.513943: Current learning rate: 0.00904 +2024-11-21 15:18:32.056268: train_loss -0.7563 +2024-11-21 15:18:32.056517: val_loss -0.7542 +2024-11-21 15:18:32.056597: Pseudo dice [0.838] +2024-11-21 15:18:32.056683: Epoch time: 18.54 s +2024-11-21 15:18:33.195918: +2024-11-21 15:18:33.196100: Epoch 850 +2024-11-21 15:18:33.196207: Current learning rate: 0.00904 +2024-11-21 15:18:51.616985: train_loss -0.7538 +2024-11-21 15:18:51.617203: val_loss -0.7351 +2024-11-21 15:18:51.617276: Pseudo dice [0.8308] +2024-11-21 15:18:51.617349: Epoch time: 18.42 s +2024-11-21 15:18:52.408336: +2024-11-21 15:18:52.408530: Epoch 851 +2024-11-21 15:18:52.408642: Current learning rate: 0.00904 +2024-11-21 15:19:09.640088: train_loss -0.7664 +2024-11-21 15:19:09.640304: val_loss -0.7109 +2024-11-21 15:19:09.642763: Pseudo dice [0.8238] +2024-11-21 15:19:09.642872: Epoch time: 17.23 s +2024-11-21 15:19:10.887545: +2024-11-21 15:19:10.887752: Epoch 852 +2024-11-21 15:19:10.887858: Current learning rate: 0.00904 +2024-11-21 15:19:28.274037: train_loss -0.7596 +2024-11-21 15:19:28.274285: val_loss -0.7273 +2024-11-21 15:19:28.274362: Pseudo dice [0.8073] +2024-11-21 15:19:28.274449: Epoch time: 17.39 s +2024-11-21 15:19:29.182374: +2024-11-21 15:19:29.182615: Epoch 853 +2024-11-21 15:19:29.182725: Current learning rate: 0.00904 +2024-11-21 15:19:47.897958: train_loss -0.7612 +2024-11-21 15:19:47.898171: val_loss -0.7546 +2024-11-21 15:19:47.898244: Pseudo dice [0.8355] +2024-11-21 15:19:47.898321: Epoch time: 18.72 s +2024-11-21 15:19:48.698533: +2024-11-21 15:19:48.698750: Epoch 854 +2024-11-21 15:19:48.698920: Current learning rate: 0.00903 +2024-11-21 15:20:08.129571: train_loss -0.7581 +2024-11-21 15:20:08.129828: val_loss -0.7457 +2024-11-21 15:20:08.129915: Pseudo dice [0.8179] +2024-11-21 15:20:08.130003: Epoch time: 19.43 s +2024-11-21 15:20:08.936687: +2024-11-21 15:20:08.936908: Epoch 855 +2024-11-21 15:20:08.937033: Current learning rate: 0.00903 +2024-11-21 15:20:26.994725: train_loss -0.7627 +2024-11-21 15:20:26.994940: val_loss -0.7242 +2024-11-21 15:20:26.995019: Pseudo dice [0.8105] +2024-11-21 15:20:26.995102: Epoch time: 18.06 s +2024-11-21 15:20:27.874102: +2024-11-21 15:20:27.874308: Epoch 856 +2024-11-21 15:20:27.874420: Current learning rate: 0.00903 +2024-11-21 15:20:45.679962: train_loss -0.7664 +2024-11-21 15:20:45.680199: val_loss -0.7278 +2024-11-21 15:20:45.680278: Pseudo dice [0.8087] +2024-11-21 15:20:45.680358: Epoch time: 17.81 s +2024-11-21 15:20:46.482713: +2024-11-21 15:20:46.482925: Epoch 857 +2024-11-21 15:20:46.483043: Current learning rate: 0.00903 +2024-11-21 15:21:05.125950: train_loss -0.766 +2024-11-21 15:21:05.126172: val_loss -0.7632 +2024-11-21 15:21:05.126247: Pseudo dice [0.8363] +2024-11-21 15:21:05.126398: Epoch time: 18.64 s +2024-11-21 15:21:05.930349: +2024-11-21 15:21:05.930610: Epoch 858 +2024-11-21 15:21:05.930736: Current learning rate: 0.00903 +2024-11-21 15:21:25.059739: train_loss -0.7705 +2024-11-21 15:21:25.059960: val_loss -0.761 +2024-11-21 15:21:25.060040: Pseudo dice [0.8264] +2024-11-21 15:21:25.060116: Epoch time: 19.13 s +2024-11-21 15:21:25.861941: +2024-11-21 15:21:25.862149: Epoch 859 +2024-11-21 15:21:25.862261: Current learning rate: 0.00903 +2024-11-21 15:21:43.577910: train_loss -0.7657 +2024-11-21 15:21:43.578172: val_loss -0.7341 +2024-11-21 15:21:43.578247: Pseudo dice [0.824] +2024-11-21 15:21:43.578356: Epoch time: 17.72 s +2024-11-21 15:21:44.549349: +2024-11-21 15:21:44.549559: Epoch 860 +2024-11-21 15:21:44.549671: Current learning rate: 0.00903 +2024-11-21 15:22:02.531063: train_loss -0.7706 +2024-11-21 15:22:02.531323: val_loss -0.709 +2024-11-21 15:22:02.531404: Pseudo dice [0.8046] +2024-11-21 15:22:02.531483: Epoch time: 17.98 s +2024-11-21 15:22:03.333694: +2024-11-21 15:22:03.333924: Epoch 861 +2024-11-21 15:22:03.334043: Current learning rate: 0.00903 +2024-11-21 15:22:22.323905: train_loss -0.7645 +2024-11-21 15:22:22.324127: val_loss -0.736 +2024-11-21 15:22:22.324200: Pseudo dice [0.819] +2024-11-21 15:22:22.324276: Epoch time: 18.99 s +2024-11-21 15:22:23.259106: +2024-11-21 15:22:23.259326: Epoch 862 +2024-11-21 15:22:23.259444: Current learning rate: 0.00902 +2024-11-21 15:22:40.479087: train_loss -0.7688 +2024-11-21 15:22:40.479311: val_loss -0.738 +2024-11-21 15:22:40.479391: Pseudo dice [0.8079] +2024-11-21 15:22:40.479472: Epoch time: 17.22 s +2024-11-21 15:22:41.284312: +2024-11-21 15:22:41.284506: Epoch 863 +2024-11-21 15:22:41.284616: Current learning rate: 0.00902 +2024-11-21 15:22:59.992123: train_loss -0.7738 +2024-11-21 15:22:59.992369: val_loss -0.7371 +2024-11-21 15:22:59.992445: Pseudo dice [0.8016] +2024-11-21 15:22:59.992564: Epoch time: 18.71 s +2024-11-21 15:23:01.178420: +2024-11-21 15:23:01.178728: Epoch 864 +2024-11-21 15:23:01.178844: Current learning rate: 0.00902 +2024-11-21 15:23:20.014327: train_loss -0.7611 +2024-11-21 15:23:20.015265: val_loss -0.737 +2024-11-21 15:23:20.015347: Pseudo dice [0.8255] +2024-11-21 15:23:20.015427: Epoch time: 18.84 s +2024-11-21 15:23:20.813412: +2024-11-21 15:23:20.813680: Epoch 865 +2024-11-21 15:23:20.813792: Current learning rate: 0.00902 +2024-11-21 15:23:39.814392: train_loss -0.7379 +2024-11-21 15:23:39.814613: val_loss -0.7161 +2024-11-21 15:23:39.814694: Pseudo dice [0.8164] +2024-11-21 15:23:39.814771: Epoch time: 19.0 s +2024-11-21 15:23:40.618845: +2024-11-21 15:23:40.619079: Epoch 866 +2024-11-21 15:23:40.619204: Current learning rate: 0.00902 +2024-11-21 15:23:59.129665: train_loss -0.7453 +2024-11-21 15:23:59.129910: val_loss -0.7415 +2024-11-21 15:23:59.129982: Pseudo dice [0.8026] +2024-11-21 15:23:59.130071: Epoch time: 18.51 s +2024-11-21 15:24:00.057778: +2024-11-21 15:24:00.058128: Epoch 867 +2024-11-21 15:24:00.058252: Current learning rate: 0.00902 +2024-11-21 15:24:19.099089: train_loss -0.7568 +2024-11-21 15:24:19.099308: val_loss -0.7219 +2024-11-21 15:24:19.099383: Pseudo dice [0.8238] +2024-11-21 15:24:19.099463: Epoch time: 19.04 s +2024-11-21 15:24:20.057004: +2024-11-21 15:24:20.057285: Epoch 868 +2024-11-21 15:24:20.057400: Current learning rate: 0.00902 +2024-11-21 15:24:38.967377: train_loss -0.761 +2024-11-21 15:24:38.967594: val_loss -0.7478 +2024-11-21 15:24:38.967672: Pseudo dice [0.8352] +2024-11-21 15:24:38.967752: Epoch time: 18.91 s +2024-11-21 15:24:39.774809: +2024-11-21 15:24:39.775022: Epoch 869 +2024-11-21 15:24:39.775132: Current learning rate: 0.00902 +2024-11-21 15:24:58.332784: train_loss -0.7644 +2024-11-21 15:24:58.333029: val_loss -0.7539 +2024-11-21 15:24:58.333109: Pseudo dice [0.8377] +2024-11-21 15:24:58.333188: Epoch time: 18.56 s +2024-11-21 15:24:59.137377: +2024-11-21 15:24:59.137607: Epoch 870 +2024-11-21 15:24:59.137723: Current learning rate: 0.00902 +2024-11-21 15:25:18.244590: train_loss -0.7592 +2024-11-21 15:25:18.244834: val_loss -0.7454 +2024-11-21 15:25:18.244908: Pseudo dice [0.8092] +2024-11-21 15:25:18.244997: Epoch time: 19.11 s +2024-11-21 15:25:19.049568: +2024-11-21 15:25:19.049773: Epoch 871 +2024-11-21 15:25:19.049885: Current learning rate: 0.00901 +2024-11-21 15:25:36.537354: train_loss -0.764 +2024-11-21 15:25:36.542286: val_loss -0.7327 +2024-11-21 15:25:36.542396: Pseudo dice [0.8233] +2024-11-21 15:25:36.542484: Epoch time: 17.49 s +2024-11-21 15:25:37.433311: +2024-11-21 15:25:37.433520: Epoch 872 +2024-11-21 15:25:37.433636: Current learning rate: 0.00901 +2024-11-21 15:25:56.764743: train_loss -0.7614 +2024-11-21 15:25:56.764957: val_loss -0.7451 +2024-11-21 15:25:56.767283: Pseudo dice [0.8222] +2024-11-21 15:25:56.767385: Epoch time: 19.33 s +2024-11-21 15:25:57.665427: +2024-11-21 15:25:57.665646: Epoch 873 +2024-11-21 15:25:57.665765: Current learning rate: 0.00901 +2024-11-21 15:26:16.828307: train_loss -0.7647 +2024-11-21 15:26:16.828543: val_loss -0.7363 +2024-11-21 15:26:16.828615: Pseudo dice [0.8253] +2024-11-21 15:26:16.828698: Epoch time: 19.16 s +2024-11-21 15:26:17.628729: +2024-11-21 15:26:17.628939: Epoch 874 +2024-11-21 15:26:17.629059: Current learning rate: 0.00901 +2024-11-21 15:26:35.810411: train_loss -0.7704 +2024-11-21 15:26:35.810620: val_loss -0.7248 +2024-11-21 15:26:35.810692: Pseudo dice [0.8173] +2024-11-21 15:26:35.810765: Epoch time: 18.18 s +2024-11-21 15:26:36.699847: +2024-11-21 15:26:36.700095: Epoch 875 +2024-11-21 15:26:36.700207: Current learning rate: 0.00901 +2024-11-21 15:26:55.749921: train_loss -0.7602 +2024-11-21 15:26:55.750154: val_loss -0.7284 +2024-11-21 15:26:55.750230: Pseudo dice [0.8108] +2024-11-21 15:26:55.750306: Epoch time: 19.05 s +2024-11-21 15:26:56.967492: +2024-11-21 15:26:56.967923: Epoch 876 +2024-11-21 15:26:56.968064: Current learning rate: 0.00901 +2024-11-21 15:27:14.793504: train_loss -0.7593 +2024-11-21 15:27:14.793834: val_loss -0.719 +2024-11-21 15:27:14.793916: Pseudo dice [0.8057] +2024-11-21 15:27:14.794010: Epoch time: 17.83 s +2024-11-21 15:27:15.598259: +2024-11-21 15:27:15.598547: Epoch 877 +2024-11-21 15:27:15.612884: Current learning rate: 0.00901 +2024-11-21 15:27:33.969726: train_loss -0.7613 +2024-11-21 15:27:33.969943: val_loss -0.7297 +2024-11-21 15:27:33.970024: Pseudo dice [0.8174] +2024-11-21 15:27:33.970106: Epoch time: 18.37 s +2024-11-21 15:27:34.782833: +2024-11-21 15:27:34.783076: Epoch 878 +2024-11-21 15:27:34.783192: Current learning rate: 0.00901 +2024-11-21 15:27:53.746614: train_loss -0.7655 +2024-11-21 15:27:53.746821: val_loss -0.7424 +2024-11-21 15:27:53.746899: Pseudo dice [0.8242] +2024-11-21 15:27:53.746975: Epoch time: 18.96 s +2024-11-21 15:27:54.553766: +2024-11-21 15:27:54.553963: Epoch 879 +2024-11-21 15:27:54.554080: Current learning rate: 0.00901 +2024-11-21 15:28:14.159585: train_loss -0.7691 +2024-11-21 15:28:14.159868: val_loss -0.737 +2024-11-21 15:28:14.159944: Pseudo dice [0.8152] +2024-11-21 15:28:14.160034: Epoch time: 19.61 s +2024-11-21 15:28:14.967534: +2024-11-21 15:28:14.967775: Epoch 880 +2024-11-21 15:28:14.967892: Current learning rate: 0.009 +2024-11-21 15:28:33.922044: train_loss -0.7545 +2024-11-21 15:28:33.922275: val_loss -0.7354 +2024-11-21 15:28:33.922351: Pseudo dice [0.8223] +2024-11-21 15:28:33.922431: Epoch time: 18.96 s +2024-11-21 15:28:34.788191: +2024-11-21 15:28:34.788398: Epoch 881 +2024-11-21 15:28:34.788507: Current learning rate: 0.009 +2024-11-21 15:28:53.645575: train_loss -0.7622 +2024-11-21 15:28:53.645787: val_loss -0.722 +2024-11-21 15:28:53.645868: Pseudo dice [0.8189] +2024-11-21 15:28:53.645972: Epoch time: 18.86 s +2024-11-21 15:28:54.452117: +2024-11-21 15:28:54.452321: Epoch 882 +2024-11-21 15:28:54.452431: Current learning rate: 0.009 +2024-11-21 15:29:14.081174: train_loss -0.7546 +2024-11-21 15:29:14.081390: val_loss -0.7138 +2024-11-21 15:29:14.081462: Pseudo dice [0.8046] +2024-11-21 15:29:14.081538: Epoch time: 19.63 s +2024-11-21 15:29:14.882138: +2024-11-21 15:29:14.882347: Epoch 883 +2024-11-21 15:29:14.882459: Current learning rate: 0.009 +2024-11-21 15:29:33.035664: train_loss -0.7416 +2024-11-21 15:29:33.035912: val_loss -0.7069 +2024-11-21 15:29:33.035989: Pseudo dice [0.8067] +2024-11-21 15:29:33.036071: Epoch time: 18.15 s +2024-11-21 15:29:33.842672: +2024-11-21 15:29:33.842867: Epoch 884 +2024-11-21 15:29:33.842978: Current learning rate: 0.009 +2024-11-21 15:29:52.274895: train_loss -0.7329 +2024-11-21 15:29:52.275144: val_loss -0.7288 +2024-11-21 15:29:52.275220: Pseudo dice [0.7984] +2024-11-21 15:29:52.275301: Epoch time: 18.43 s +2024-11-21 15:29:53.077796: +2024-11-21 15:29:53.078011: Epoch 885 +2024-11-21 15:29:53.078121: Current learning rate: 0.009 +2024-11-21 15:30:11.105942: train_loss -0.7509 +2024-11-21 15:30:11.106212: val_loss -0.7267 +2024-11-21 15:30:11.106286: Pseudo dice [0.8163] +2024-11-21 15:30:11.106365: Epoch time: 18.03 s +2024-11-21 15:30:11.907859: +2024-11-21 15:30:11.908095: Epoch 886 +2024-11-21 15:30:11.908222: Current learning rate: 0.009 +2024-11-21 15:30:31.254133: train_loss -0.7591 +2024-11-21 15:30:31.254340: val_loss -0.7495 +2024-11-21 15:30:31.254411: Pseudo dice [0.8419] +2024-11-21 15:30:31.254492: Epoch time: 19.35 s +2024-11-21 15:30:32.057967: +2024-11-21 15:30:32.058227: Epoch 887 +2024-11-21 15:30:32.058340: Current learning rate: 0.009 +2024-11-21 15:30:52.212856: train_loss -0.7593 +2024-11-21 15:30:52.215268: val_loss -0.7318 +2024-11-21 15:30:52.215372: Pseudo dice [0.8335] +2024-11-21 15:30:52.215466: Epoch time: 20.16 s +2024-11-21 15:30:53.445364: +2024-11-21 15:30:53.445599: Epoch 888 +2024-11-21 15:30:53.445712: Current learning rate: 0.009 +2024-11-21 15:31:12.113647: train_loss -0.7594 +2024-11-21 15:31:12.113946: val_loss -0.7346 +2024-11-21 15:31:12.114032: Pseudo dice [0.7959] +2024-11-21 15:31:12.114107: Epoch time: 18.67 s +2024-11-21 15:31:12.917624: +2024-11-21 15:31:12.917825: Epoch 889 +2024-11-21 15:31:12.917935: Current learning rate: 0.00899 +2024-11-21 15:31:31.393820: train_loss -0.7622 +2024-11-21 15:31:31.394051: val_loss -0.6967 +2024-11-21 15:31:31.394126: Pseudo dice [0.8191] +2024-11-21 15:31:31.394204: Epoch time: 18.48 s +2024-11-21 15:31:32.212970: +2024-11-21 15:31:32.213234: Epoch 890 +2024-11-21 15:31:32.213346: Current learning rate: 0.00899 +2024-11-21 15:31:50.855289: train_loss -0.7504 +2024-11-21 15:31:50.855529: val_loss -0.737 +2024-11-21 15:31:50.855633: Pseudo dice [0.8215] +2024-11-21 15:31:50.855749: Epoch time: 18.64 s +2024-11-21 15:31:51.661509: +2024-11-21 15:31:51.661717: Epoch 891 +2024-11-21 15:31:51.661831: Current learning rate: 0.00899 +2024-11-21 15:32:10.580559: train_loss -0.7437 +2024-11-21 15:32:10.580773: val_loss -0.7287 +2024-11-21 15:32:10.583058: Pseudo dice [0.827] +2024-11-21 15:32:10.583164: Epoch time: 18.92 s +2024-11-21 15:32:11.534479: +2024-11-21 15:32:11.534736: Epoch 892 +2024-11-21 15:32:11.534850: Current learning rate: 0.00899 +2024-11-21 15:32:29.195974: train_loss -0.7479 +2024-11-21 15:32:29.196203: val_loss -0.7196 +2024-11-21 15:32:29.196280: Pseudo dice [0.7887] +2024-11-21 15:32:29.196360: Epoch time: 17.66 s +2024-11-21 15:32:30.017129: +2024-11-21 15:32:30.017470: Epoch 893 +2024-11-21 15:32:30.017587: Current learning rate: 0.00899 +2024-11-21 15:32:49.072507: train_loss -0.7508 +2024-11-21 15:32:49.072720: val_loss -0.7347 +2024-11-21 15:32:49.072793: Pseudo dice [0.8085] +2024-11-21 15:32:49.072868: Epoch time: 19.06 s +2024-11-21 15:32:49.877385: +2024-11-21 15:32:49.877605: Epoch 894 +2024-11-21 15:32:49.877723: Current learning rate: 0.00899 +2024-11-21 15:33:08.740400: train_loss -0.7527 +2024-11-21 15:33:08.740655: val_loss -0.7362 +2024-11-21 15:33:08.740734: Pseudo dice [0.828] +2024-11-21 15:33:08.740819: Epoch time: 18.86 s +2024-11-21 15:33:09.544570: +2024-11-21 15:33:09.544777: Epoch 895 +2024-11-21 15:33:09.544889: Current learning rate: 0.00899 +2024-11-21 15:33:27.653128: train_loss -0.761 +2024-11-21 15:33:27.653346: val_loss -0.758 +2024-11-21 15:33:27.653418: Pseudo dice [0.8325] +2024-11-21 15:33:27.653547: Epoch time: 18.11 s +2024-11-21 15:33:28.501998: +2024-11-21 15:33:28.502200: Epoch 896 +2024-11-21 15:33:28.502317: Current learning rate: 0.00899 +2024-11-21 15:33:46.720687: train_loss -0.7599 +2024-11-21 15:33:46.720902: val_loss -0.7408 +2024-11-21 15:33:46.721028: Pseudo dice [0.8253] +2024-11-21 15:33:46.721116: Epoch time: 18.22 s +2024-11-21 15:33:47.520551: +2024-11-21 15:33:47.520844: Epoch 897 +2024-11-21 15:33:47.520953: Current learning rate: 0.00898 +2024-11-21 15:34:06.841714: train_loss -0.7653 +2024-11-21 15:34:06.844126: val_loss -0.7213 +2024-11-21 15:34:06.844226: Pseudo dice [0.7928] +2024-11-21 15:34:06.844311: Epoch time: 19.32 s +2024-11-21 15:34:07.679220: +2024-11-21 15:34:07.679523: Epoch 898 +2024-11-21 15:34:07.679640: Current learning rate: 0.00898 +2024-11-21 15:34:26.222865: train_loss -0.7663 +2024-11-21 15:34:26.223086: val_loss -0.7112 +2024-11-21 15:34:26.223162: Pseudo dice [0.7986] +2024-11-21 15:34:26.223241: Epoch time: 18.54 s +2024-11-21 15:34:27.029511: +2024-11-21 15:34:27.029807: Epoch 899 +2024-11-21 15:34:27.029923: Current learning rate: 0.00898 +2024-11-21 15:34:44.576525: train_loss -0.7677 +2024-11-21 15:34:44.576739: val_loss -0.737 +2024-11-21 15:34:44.576830: Pseudo dice [0.8311] +2024-11-21 15:34:44.576913: Epoch time: 17.55 s +2024-11-21 15:34:46.001729: +2024-11-21 15:34:46.002024: Epoch 900 +2024-11-21 15:34:46.002140: Current learning rate: 0.00898 +2024-11-21 15:35:05.493969: train_loss -0.7643 +2024-11-21 15:35:05.494200: val_loss -0.7448 +2024-11-21 15:35:05.494299: Pseudo dice [0.8296] +2024-11-21 15:35:05.494378: Epoch time: 19.49 s +2024-11-21 15:35:06.290487: +2024-11-21 15:35:06.290716: Epoch 901 +2024-11-21 15:35:06.290830: Current learning rate: 0.00898 +2024-11-21 15:35:25.616476: train_loss -0.7616 +2024-11-21 15:35:25.618900: val_loss -0.748 +2024-11-21 15:35:25.619037: Pseudo dice [0.8177] +2024-11-21 15:35:25.619123: Epoch time: 19.33 s +2024-11-21 15:35:26.457805: +2024-11-21 15:35:26.458049: Epoch 902 +2024-11-21 15:35:26.458166: Current learning rate: 0.00898 +2024-11-21 15:35:46.321739: train_loss -0.7644 +2024-11-21 15:35:46.321960: val_loss -0.7317 +2024-11-21 15:35:46.322048: Pseudo dice [0.8161] +2024-11-21 15:35:46.322129: Epoch time: 19.86 s +2024-11-21 15:35:47.131119: +2024-11-21 15:35:47.131353: Epoch 903 +2024-11-21 15:35:47.131467: Current learning rate: 0.00898 +2024-11-21 15:36:05.141580: train_loss -0.7596 +2024-11-21 15:36:05.141792: val_loss -0.7503 +2024-11-21 15:36:05.141865: Pseudo dice [0.8281] +2024-11-21 15:36:05.141941: Epoch time: 18.01 s +2024-11-21 15:36:06.105705: +2024-11-21 15:36:06.105911: Epoch 904 +2024-11-21 15:36:06.106029: Current learning rate: 0.00898 +2024-11-21 15:36:24.082360: train_loss -0.7633 +2024-11-21 15:36:24.082597: val_loss -0.7344 +2024-11-21 15:36:24.082676: Pseudo dice [0.8323] +2024-11-21 15:36:24.082763: Epoch time: 17.98 s +2024-11-21 15:36:24.886342: +2024-11-21 15:36:24.886545: Epoch 905 +2024-11-21 15:36:24.886656: Current learning rate: 0.00898 +2024-11-21 15:36:43.413969: train_loss -0.7565 +2024-11-21 15:36:43.414183: val_loss -0.7518 +2024-11-21 15:36:43.414255: Pseudo dice [0.8278] +2024-11-21 15:36:43.414331: Epoch time: 18.53 s +2024-11-21 15:36:44.340874: +2024-11-21 15:36:44.341187: Epoch 906 +2024-11-21 15:36:44.341304: Current learning rate: 0.00897 +2024-11-21 15:37:02.749163: train_loss -0.7598 +2024-11-21 15:37:02.749378: val_loss -0.6894 +2024-11-21 15:37:02.749453: Pseudo dice [0.8201] +2024-11-21 15:37:02.749530: Epoch time: 18.41 s +2024-11-21 15:37:03.655305: +2024-11-21 15:37:03.655535: Epoch 907 +2024-11-21 15:37:03.655647: Current learning rate: 0.00897 +2024-11-21 15:37:22.472297: train_loss -0.7641 +2024-11-21 15:37:22.472515: val_loss -0.7104 +2024-11-21 15:37:22.472595: Pseudo dice [0.8127] +2024-11-21 15:37:22.472682: Epoch time: 18.82 s +2024-11-21 15:37:23.276144: +2024-11-21 15:37:23.276356: Epoch 908 +2024-11-21 15:37:23.276469: Current learning rate: 0.00897 +2024-11-21 15:37:41.915997: train_loss -0.7592 +2024-11-21 15:37:41.916223: val_loss -0.7512 +2024-11-21 15:37:41.916295: Pseudo dice [0.8333] +2024-11-21 15:37:41.916375: Epoch time: 18.64 s +2024-11-21 15:37:42.771182: +2024-11-21 15:37:42.771383: Epoch 909 +2024-11-21 15:37:42.771500: Current learning rate: 0.00897 +2024-11-21 15:38:01.070387: train_loss -0.761 +2024-11-21 15:38:01.070601: val_loss -0.7755 +2024-11-21 15:38:01.070692: Pseudo dice [0.8304] +2024-11-21 15:38:01.070771: Epoch time: 18.3 s +2024-11-21 15:38:01.875748: +2024-11-21 15:38:01.876006: Epoch 910 +2024-11-21 15:38:01.876118: Current learning rate: 0.00897 +2024-11-21 15:38:20.006770: train_loss -0.7746 +2024-11-21 15:38:20.007002: val_loss -0.7228 +2024-11-21 15:38:20.007079: Pseudo dice [0.7986] +2024-11-21 15:38:20.007155: Epoch time: 18.13 s +2024-11-21 15:38:20.915173: +2024-11-21 15:38:20.915497: Epoch 911 +2024-11-21 15:38:20.915623: Current learning rate: 0.00897 +2024-11-21 15:38:40.924032: train_loss -0.7602 +2024-11-21 15:38:40.924284: val_loss -0.7385 +2024-11-21 15:38:40.924359: Pseudo dice [0.8183] +2024-11-21 15:38:40.924447: Epoch time: 20.01 s +2024-11-21 15:38:42.107678: +2024-11-21 15:38:42.107907: Epoch 912 +2024-11-21 15:38:42.108029: Current learning rate: 0.00897 +2024-11-21 15:39:01.304114: train_loss -0.7714 +2024-11-21 15:39:01.304332: val_loss -0.7523 +2024-11-21 15:39:01.304410: Pseudo dice [0.8322] +2024-11-21 15:39:01.304485: Epoch time: 19.2 s +2024-11-21 15:39:02.108197: +2024-11-21 15:39:02.108395: Epoch 913 +2024-11-21 15:39:02.108507: Current learning rate: 0.00897 +2024-11-21 15:39:21.567576: train_loss -0.7715 +2024-11-21 15:39:21.567792: val_loss -0.7423 +2024-11-21 15:39:21.567865: Pseudo dice [0.8238] +2024-11-21 15:39:21.567939: Epoch time: 19.46 s +2024-11-21 15:39:22.374257: +2024-11-21 15:39:22.374478: Epoch 914 +2024-11-21 15:39:22.374592: Current learning rate: 0.00897 +2024-11-21 15:39:41.053626: train_loss -0.7676 +2024-11-21 15:39:41.053837: val_loss -0.7423 +2024-11-21 15:39:41.053910: Pseudo dice [0.8187] +2024-11-21 15:39:41.053984: Epoch time: 18.68 s +2024-11-21 15:39:41.858592: +2024-11-21 15:39:41.858822: Epoch 915 +2024-11-21 15:39:41.858968: Current learning rate: 0.00896 +2024-11-21 15:40:00.576090: train_loss -0.7612 +2024-11-21 15:40:00.576320: val_loss -0.7002 +2024-11-21 15:40:00.576395: Pseudo dice [0.8117] +2024-11-21 15:40:00.576475: Epoch time: 18.72 s +2024-11-21 15:40:01.382165: +2024-11-21 15:40:01.382366: Epoch 916 +2024-11-21 15:40:01.382475: Current learning rate: 0.00896 +2024-11-21 15:40:19.663191: train_loss -0.7664 +2024-11-21 15:40:19.663411: val_loss -0.7342 +2024-11-21 15:40:19.663485: Pseudo dice [0.824] +2024-11-21 15:40:19.663562: Epoch time: 18.28 s +2024-11-21 15:40:20.484392: +2024-11-21 15:40:20.484610: Epoch 917 +2024-11-21 15:40:20.484721: Current learning rate: 0.00896 +2024-11-21 15:40:38.468280: train_loss -0.7648 +2024-11-21 15:40:38.468496: val_loss -0.7388 +2024-11-21 15:40:38.468570: Pseudo dice [0.8135] +2024-11-21 15:40:38.468665: Epoch time: 17.98 s +2024-11-21 15:40:39.272309: +2024-11-21 15:40:39.272569: Epoch 918 +2024-11-21 15:40:39.272686: Current learning rate: 0.00896 +2024-11-21 15:40:57.822674: train_loss -0.7712 +2024-11-21 15:40:57.822957: val_loss -0.7601 +2024-11-21 15:40:57.823041: Pseudo dice [0.8461] +2024-11-21 15:40:57.823119: Epoch time: 18.55 s +2024-11-21 15:40:58.629469: +2024-11-21 15:40:58.629706: Epoch 919 +2024-11-21 15:40:58.629945: Current learning rate: 0.00896 +2024-11-21 15:41:17.279868: train_loss -0.7672 +2024-11-21 15:41:17.280113: val_loss -0.7158 +2024-11-21 15:41:17.280189: Pseudo dice [0.8089] +2024-11-21 15:41:17.280271: Epoch time: 18.65 s +2024-11-21 15:41:18.084439: +2024-11-21 15:41:18.084634: Epoch 920 +2024-11-21 15:41:18.084745: Current learning rate: 0.00896 +2024-11-21 15:41:36.132966: train_loss -0.7715 +2024-11-21 15:41:36.133179: val_loss -0.7052 +2024-11-21 15:41:36.133254: Pseudo dice [0.8153] +2024-11-21 15:41:36.133332: Epoch time: 18.05 s +2024-11-21 15:41:36.937956: +2024-11-21 15:41:36.938251: Epoch 921 +2024-11-21 15:41:36.938368: Current learning rate: 0.00896 +2024-11-21 15:41:54.922749: train_loss -0.7653 +2024-11-21 15:41:54.922967: val_loss -0.7619 +2024-11-21 15:41:54.923049: Pseudo dice [0.8346] +2024-11-21 15:41:54.923129: Epoch time: 17.99 s +2024-11-21 15:41:55.938902: +2024-11-21 15:41:55.939107: Epoch 922 +2024-11-21 15:41:55.939220: Current learning rate: 0.00896 +2024-11-21 15:42:15.514534: train_loss -0.759 +2024-11-21 15:42:15.514778: val_loss -0.7118 +2024-11-21 15:42:15.514853: Pseudo dice [0.8016] +2024-11-21 15:42:15.514934: Epoch time: 19.58 s +2024-11-21 15:42:16.337607: +2024-11-21 15:42:16.337808: Epoch 923 +2024-11-21 15:42:16.337919: Current learning rate: 0.00896 +2024-11-21 15:42:35.382271: train_loss -0.7369 +2024-11-21 15:42:35.382490: val_loss -0.7212 +2024-11-21 15:42:35.382562: Pseudo dice [0.8132] +2024-11-21 15:42:35.382642: Epoch time: 19.05 s +2024-11-21 15:42:36.589120: +2024-11-21 15:42:36.589335: Epoch 924 +2024-11-21 15:42:36.589452: Current learning rate: 0.00895 +2024-11-21 15:42:56.118459: train_loss -0.7472 +2024-11-21 15:42:56.118669: val_loss -0.7177 +2024-11-21 15:42:56.118740: Pseudo dice [0.8014] +2024-11-21 15:42:56.118813: Epoch time: 19.53 s +2024-11-21 15:42:57.060349: +2024-11-21 15:42:57.060559: Epoch 925 +2024-11-21 15:42:57.060678: Current learning rate: 0.00895 +2024-11-21 15:43:15.166760: train_loss -0.7514 +2024-11-21 15:43:15.167007: val_loss -0.7474 +2024-11-21 15:43:15.167086: Pseudo dice [0.8342] +2024-11-21 15:43:15.167174: Epoch time: 18.11 s +2024-11-21 15:43:15.971736: +2024-11-21 15:43:15.971936: Epoch 926 +2024-11-21 15:43:15.972055: Current learning rate: 0.00895 +2024-11-21 15:43:35.117002: train_loss -0.7599 +2024-11-21 15:43:35.117209: val_loss -0.7515 +2024-11-21 15:43:35.117286: Pseudo dice [0.8249] +2024-11-21 15:43:35.117363: Epoch time: 19.15 s +2024-11-21 15:43:35.922901: +2024-11-21 15:43:35.923108: Epoch 927 +2024-11-21 15:43:35.923219: Current learning rate: 0.00895 +2024-11-21 15:43:55.314194: train_loss -0.7639 +2024-11-21 15:43:55.314445: val_loss -0.7446 +2024-11-21 15:43:55.314524: Pseudo dice [0.8229] +2024-11-21 15:43:55.314602: Epoch time: 19.39 s +2024-11-21 15:43:56.124601: +2024-11-21 15:43:56.124876: Epoch 928 +2024-11-21 15:43:56.125004: Current learning rate: 0.00895 +2024-11-21 15:44:14.507463: train_loss -0.768 +2024-11-21 15:44:14.507666: val_loss -0.7336 +2024-11-21 15:44:14.507737: Pseudo dice [0.8206] +2024-11-21 15:44:14.507808: Epoch time: 18.38 s +2024-11-21 15:44:15.366844: +2024-11-21 15:44:15.367072: Epoch 929 +2024-11-21 15:44:15.367185: Current learning rate: 0.00895 +2024-11-21 15:44:33.819561: train_loss -0.7576 +2024-11-21 15:44:33.819808: val_loss -0.7427 +2024-11-21 15:44:33.819884: Pseudo dice [0.8219] +2024-11-21 15:44:33.824383: Epoch time: 18.45 s +2024-11-21 15:44:34.730293: +2024-11-21 15:44:34.730505: Epoch 930 +2024-11-21 15:44:34.730624: Current learning rate: 0.00895 +2024-11-21 15:44:53.834768: train_loss -0.7554 +2024-11-21 15:44:53.835071: val_loss -0.7228 +2024-11-21 15:44:53.835145: Pseudo dice [0.8208] +2024-11-21 15:44:53.835222: Epoch time: 19.11 s +2024-11-21 15:44:54.640243: +2024-11-21 15:44:54.640472: Epoch 931 +2024-11-21 15:44:54.640592: Current learning rate: 0.00895 +2024-11-21 15:45:14.492496: train_loss -0.7588 +2024-11-21 15:45:14.492705: val_loss -0.7176 +2024-11-21 15:45:14.492776: Pseudo dice [0.7954] +2024-11-21 15:45:14.492849: Epoch time: 19.85 s +2024-11-21 15:45:15.298527: +2024-11-21 15:45:15.298754: Epoch 932 +2024-11-21 15:45:15.298868: Current learning rate: 0.00895 +2024-11-21 15:45:33.523758: train_loss -0.7743 +2024-11-21 15:45:33.524013: val_loss -0.7369 +2024-11-21 15:45:33.524090: Pseudo dice [0.8292] +2024-11-21 15:45:33.524165: Epoch time: 18.23 s +2024-11-21 15:45:34.330265: +2024-11-21 15:45:34.330470: Epoch 933 +2024-11-21 15:45:34.330583: Current learning rate: 0.00894 +2024-11-21 15:45:53.283069: train_loss -0.754 +2024-11-21 15:45:53.283311: val_loss -0.735 +2024-11-21 15:45:53.283385: Pseudo dice [0.8311] +2024-11-21 15:45:53.283470: Epoch time: 18.95 s +2024-11-21 15:45:54.148337: +2024-11-21 15:45:54.148570: Epoch 934 +2024-11-21 15:45:54.148690: Current learning rate: 0.00894 +2024-11-21 15:46:13.069420: train_loss -0.7549 +2024-11-21 15:46:13.069639: val_loss -0.7516 +2024-11-21 15:46:13.069711: Pseudo dice [0.8207] +2024-11-21 15:46:13.069785: Epoch time: 18.92 s +2024-11-21 15:46:14.026331: +2024-11-21 15:46:14.026556: Epoch 935 +2024-11-21 15:46:14.026670: Current learning rate: 0.00894 +2024-11-21 15:46:32.718813: train_loss -0.7469 +2024-11-21 15:46:32.719035: val_loss -0.734 +2024-11-21 15:46:32.719113: Pseudo dice [0.8243] +2024-11-21 15:46:32.719191: Epoch time: 18.69 s +2024-11-21 15:46:33.888277: +2024-11-21 15:46:33.888617: Epoch 936 +2024-11-21 15:46:33.888734: Current learning rate: 0.00894 +2024-11-21 15:46:52.475575: train_loss -0.7554 +2024-11-21 15:46:52.475833: val_loss -0.744 +2024-11-21 15:46:52.475909: Pseudo dice [0.8248] +2024-11-21 15:46:52.476003: Epoch time: 18.59 s +2024-11-21 15:46:53.307259: +2024-11-21 15:46:53.307600: Epoch 937 +2024-11-21 15:46:53.307712: Current learning rate: 0.00894 +2024-11-21 15:47:12.103823: train_loss -0.7537 +2024-11-21 15:47:12.104061: val_loss -0.729 +2024-11-21 15:47:12.104212: Pseudo dice [0.8245] +2024-11-21 15:47:12.104291: Epoch time: 18.8 s +2024-11-21 15:47:12.911615: +2024-11-21 15:47:12.911832: Epoch 938 +2024-11-21 15:47:12.911946: Current learning rate: 0.00894 +2024-11-21 15:47:32.061654: train_loss -0.7593 +2024-11-21 15:47:32.061915: val_loss -0.7425 +2024-11-21 15:47:32.061996: Pseudo dice [0.8245] +2024-11-21 15:47:32.062074: Epoch time: 19.15 s +2024-11-21 15:47:32.860514: +2024-11-21 15:47:32.860732: Epoch 939 +2024-11-21 15:47:32.860845: Current learning rate: 0.00894 +2024-11-21 15:47:51.528149: train_loss -0.7575 +2024-11-21 15:47:51.528358: val_loss -0.7347 +2024-11-21 15:47:51.528431: Pseudo dice [0.8314] +2024-11-21 15:47:51.528505: Epoch time: 18.67 s +2024-11-21 15:47:52.447247: +2024-11-21 15:47:52.447460: Epoch 940 +2024-11-21 15:47:52.447572: Current learning rate: 0.00894 +2024-11-21 15:48:11.032964: train_loss -0.7653 +2024-11-21 15:48:11.033210: val_loss -0.7371 +2024-11-21 15:48:11.033285: Pseudo dice [0.8358] +2024-11-21 15:48:11.033372: Epoch time: 18.59 s +2024-11-21 15:48:11.842685: +2024-11-21 15:48:11.842893: Epoch 941 +2024-11-21 15:48:11.843009: Current learning rate: 0.00893 +2024-11-21 15:48:30.477953: train_loss -0.7679 +2024-11-21 15:48:30.478189: val_loss -0.7376 +2024-11-21 15:48:30.478270: Pseudo dice [0.8195] +2024-11-21 15:48:30.483551: Epoch time: 18.64 s +2024-11-21 15:48:31.379042: +2024-11-21 15:48:31.379254: Epoch 942 +2024-11-21 15:48:31.379367: Current learning rate: 0.00893 +2024-11-21 15:48:50.215473: train_loss -0.7687 +2024-11-21 15:48:50.215702: val_loss -0.7338 +2024-11-21 15:48:50.215779: Pseudo dice [0.838] +2024-11-21 15:48:50.215862: Epoch time: 18.84 s +2024-11-21 15:48:50.215932: Yayy! New best EMA pseudo Dice: 0.825 +2024-11-21 15:48:51.287527: +2024-11-21 15:48:51.287785: Epoch 943 +2024-11-21 15:48:51.287903: Current learning rate: 0.00893 +2024-11-21 15:49:10.087383: train_loss -0.761 +2024-11-21 15:49:10.092762: val_loss -0.7293 +2024-11-21 15:49:10.092874: Pseudo dice [0.8047] +2024-11-21 15:49:10.092954: Epoch time: 18.8 s +2024-11-21 15:49:11.047489: +2024-11-21 15:49:11.047709: Epoch 944 +2024-11-21 15:49:11.047824: Current learning rate: 0.00893 +2024-11-21 15:49:29.112558: train_loss -0.7685 +2024-11-21 15:49:29.112790: val_loss -0.7378 +2024-11-21 15:49:29.112863: Pseudo dice [0.828] +2024-11-21 15:49:29.112941: Epoch time: 18.07 s +2024-11-21 15:49:29.914002: +2024-11-21 15:49:29.914264: Epoch 945 +2024-11-21 15:49:29.914377: Current learning rate: 0.00893 +2024-11-21 15:49:49.077042: train_loss -0.7629 +2024-11-21 15:49:49.077256: val_loss -0.7511 +2024-11-21 15:49:49.077329: Pseudo dice [0.816] +2024-11-21 15:49:49.077401: Epoch time: 19.16 s +2024-11-21 15:49:49.885421: +2024-11-21 15:49:49.885709: Epoch 946 +2024-11-21 15:49:49.885823: Current learning rate: 0.00893 +2024-11-21 15:50:07.942487: train_loss -0.7652 +2024-11-21 15:50:07.942698: val_loss -0.7265 +2024-11-21 15:50:07.942770: Pseudo dice [0.8268] +2024-11-21 15:50:07.942847: Epoch time: 18.06 s +2024-11-21 15:50:08.752303: +2024-11-21 15:50:08.752599: Epoch 947 +2024-11-21 15:50:08.752709: Current learning rate: 0.00893 +2024-11-21 15:50:27.286894: train_loss -0.7679 +2024-11-21 15:50:27.287161: val_loss -0.761 +2024-11-21 15:50:27.287241: Pseudo dice [0.8218] +2024-11-21 15:50:27.287326: Epoch time: 18.54 s +2024-11-21 15:50:28.544696: +2024-11-21 15:50:28.544923: Epoch 948 +2024-11-21 15:50:28.545042: Current learning rate: 0.00893 +2024-11-21 15:50:46.641889: train_loss -0.7584 +2024-11-21 15:50:46.642115: val_loss -0.7574 +2024-11-21 15:50:46.642194: Pseudo dice [0.8216] +2024-11-21 15:50:46.642278: Epoch time: 18.1 s +2024-11-21 15:50:47.450667: +2024-11-21 15:50:47.450894: Epoch 949 +2024-11-21 15:50:47.451015: Current learning rate: 0.00893 +2024-11-21 15:51:06.652041: train_loss -0.772 +2024-11-21 15:51:06.652259: val_loss -0.7332 +2024-11-21 15:51:06.652336: Pseudo dice [0.8268] +2024-11-21 15:51:06.652412: Epoch time: 19.2 s +2024-11-21 15:51:07.757378: +2024-11-21 15:51:07.757586: Epoch 950 +2024-11-21 15:51:07.757696: Current learning rate: 0.00892 +2024-11-21 15:51:26.262556: train_loss -0.762 +2024-11-21 15:51:26.262786: val_loss -0.7533 +2024-11-21 15:51:26.262861: Pseudo dice [0.8212] +2024-11-21 15:51:26.262944: Epoch time: 18.51 s +2024-11-21 15:51:27.067478: +2024-11-21 15:51:27.067684: Epoch 951 +2024-11-21 15:51:27.067799: Current learning rate: 0.00892 +2024-11-21 15:51:44.713018: train_loss -0.7663 +2024-11-21 15:51:44.713222: val_loss -0.7452 +2024-11-21 15:51:44.713300: Pseudo dice [0.8134] +2024-11-21 15:51:44.713387: Epoch time: 17.65 s +2024-11-21 15:51:45.520103: +2024-11-21 15:51:45.520410: Epoch 952 +2024-11-21 15:51:45.520527: Current learning rate: 0.00892 +2024-11-21 15:52:04.963892: train_loss -0.7603 +2024-11-21 15:52:04.964096: val_loss -0.7338 +2024-11-21 15:52:04.964167: Pseudo dice [0.8315] +2024-11-21 15:52:04.964245: Epoch time: 19.44 s +2024-11-21 15:52:05.796237: +2024-11-21 15:52:05.796440: Epoch 953 +2024-11-21 15:52:05.796551: Current learning rate: 0.00892 +2024-11-21 15:52:23.840470: train_loss -0.7618 +2024-11-21 15:52:23.840689: val_loss -0.7224 +2024-11-21 15:52:23.840766: Pseudo dice [0.8242] +2024-11-21 15:52:23.840848: Epoch time: 18.05 s +2024-11-21 15:52:24.676527: +2024-11-21 15:52:24.676784: Epoch 954 +2024-11-21 15:52:24.676896: Current learning rate: 0.00892 +2024-11-21 15:52:43.248549: train_loss -0.7566 +2024-11-21 15:52:43.248782: val_loss -0.7386 +2024-11-21 15:52:43.248859: Pseudo dice [0.8297] +2024-11-21 15:52:43.248943: Epoch time: 18.57 s +2024-11-21 15:52:44.065393: +2024-11-21 15:52:44.065634: Epoch 955 +2024-11-21 15:52:44.065754: Current learning rate: 0.00892 +2024-11-21 15:53:03.438148: train_loss -0.7592 +2024-11-21 15:53:03.438357: val_loss -0.7212 +2024-11-21 15:53:03.438431: Pseudo dice [0.829] +2024-11-21 15:53:03.438507: Epoch time: 19.37 s +2024-11-21 15:53:04.254679: +2024-11-21 15:53:04.254906: Epoch 956 +2024-11-21 15:53:04.255027: Current learning rate: 0.00892 +2024-11-21 15:53:23.148758: train_loss -0.7497 +2024-11-21 15:53:23.148982: val_loss -0.7378 +2024-11-21 15:53:23.149069: Pseudo dice [0.8215] +2024-11-21 15:53:23.149148: Epoch time: 18.89 s +2024-11-21 15:53:23.954617: +2024-11-21 15:53:23.954838: Epoch 957 +2024-11-21 15:53:23.954967: Current learning rate: 0.00892 +2024-11-21 15:53:42.225842: train_loss -0.7498 +2024-11-21 15:53:42.226095: val_loss -0.7299 +2024-11-21 15:53:42.226171: Pseudo dice [0.8273] +2024-11-21 15:53:42.226255: Epoch time: 18.27 s +2024-11-21 15:53:43.070720: +2024-11-21 15:53:43.070950: Epoch 958 +2024-11-21 15:53:43.071069: Current learning rate: 0.00892 +2024-11-21 15:54:02.227805: train_loss -0.7454 +2024-11-21 15:54:02.228024: val_loss -0.751 +2024-11-21 15:54:02.228101: Pseudo dice [0.8208] +2024-11-21 15:54:02.228178: Epoch time: 19.16 s +2024-11-21 15:54:03.048450: +2024-11-21 15:54:03.048649: Epoch 959 +2024-11-21 15:54:03.048763: Current learning rate: 0.00891 +2024-11-21 15:54:21.610970: train_loss -0.7543 +2024-11-21 15:54:21.611190: val_loss -0.7449 +2024-11-21 15:54:21.611261: Pseudo dice [0.8302] +2024-11-21 15:54:21.611340: Epoch time: 18.56 s +2024-11-21 15:54:22.790578: +2024-11-21 15:54:22.790784: Epoch 960 +2024-11-21 15:54:22.790898: Current learning rate: 0.00891 +2024-11-21 15:54:41.813081: train_loss -0.76 +2024-11-21 15:54:41.813336: val_loss -0.74 +2024-11-21 15:54:41.813411: Pseudo dice [0.7884] +2024-11-21 15:54:41.815003: Epoch time: 19.02 s +2024-11-21 15:54:42.664599: +2024-11-21 15:54:42.664958: Epoch 961 +2024-11-21 15:54:42.665080: Current learning rate: 0.00891 +2024-11-21 15:55:01.762162: train_loss -0.7399 +2024-11-21 15:55:01.762384: val_loss -0.7397 +2024-11-21 15:55:01.762465: Pseudo dice [0.8166] +2024-11-21 15:55:01.762544: Epoch time: 19.1 s +2024-11-21 15:55:02.640951: +2024-11-21 15:55:02.641202: Epoch 962 +2024-11-21 15:55:02.641319: Current learning rate: 0.00891 +2024-11-21 15:55:21.849581: train_loss -0.7474 +2024-11-21 15:55:21.849796: val_loss -0.7443 +2024-11-21 15:55:21.849875: Pseudo dice [0.8287] +2024-11-21 15:55:21.849954: Epoch time: 19.21 s +2024-11-21 15:55:22.665139: +2024-11-21 15:55:22.665330: Epoch 963 +2024-11-21 15:55:22.665467: Current learning rate: 0.00891 +2024-11-21 15:55:41.545516: train_loss -0.7564 +2024-11-21 15:55:41.545731: val_loss -0.7467 +2024-11-21 15:55:41.545805: Pseudo dice [0.8264] +2024-11-21 15:55:41.545885: Epoch time: 18.88 s +2024-11-21 15:55:42.355148: +2024-11-21 15:55:42.355378: Epoch 964 +2024-11-21 15:55:42.355500: Current learning rate: 0.00891 +2024-11-21 15:56:01.072775: train_loss -0.7682 +2024-11-21 15:56:01.073023: val_loss -0.7337 +2024-11-21 15:56:01.073100: Pseudo dice [0.7976] +2024-11-21 15:56:01.073182: Epoch time: 18.72 s +2024-11-21 15:56:01.912380: +2024-11-21 15:56:01.912570: Epoch 965 +2024-11-21 15:56:01.912681: Current learning rate: 0.00891 +2024-11-21 15:56:20.975598: train_loss -0.7672 +2024-11-21 15:56:20.975812: val_loss -0.7509 +2024-11-21 15:56:20.975885: Pseudo dice [0.8283] +2024-11-21 15:56:20.975961: Epoch time: 19.06 s +2024-11-21 15:56:21.788055: +2024-11-21 15:56:21.788349: Epoch 966 +2024-11-21 15:56:21.788462: Current learning rate: 0.00891 +2024-11-21 15:56:40.703057: train_loss -0.7598 +2024-11-21 15:56:40.703265: val_loss -0.732 +2024-11-21 15:56:40.703337: Pseudo dice [0.8101] +2024-11-21 15:56:40.703452: Epoch time: 18.92 s +2024-11-21 15:56:41.519812: +2024-11-21 15:56:41.520076: Epoch 967 +2024-11-21 15:56:41.520185: Current learning rate: 0.00891 +2024-11-21 15:56:59.990875: train_loss -0.7729 +2024-11-21 15:56:59.991132: val_loss -0.7431 +2024-11-21 15:56:59.991206: Pseudo dice [0.8276] +2024-11-21 15:56:59.991291: Epoch time: 18.47 s +2024-11-21 15:57:00.879718: +2024-11-21 15:57:00.879957: Epoch 968 +2024-11-21 15:57:00.880074: Current learning rate: 0.0089 +2024-11-21 15:57:20.481555: train_loss -0.7625 +2024-11-21 15:57:20.481769: val_loss -0.7499 +2024-11-21 15:57:20.481841: Pseudo dice [0.8339] +2024-11-21 15:57:20.481921: Epoch time: 19.6 s +2024-11-21 15:57:21.296968: +2024-11-21 15:57:21.297170: Epoch 969 +2024-11-21 15:57:21.297299: Current learning rate: 0.0089 +2024-11-21 15:57:40.158098: train_loss -0.7679 +2024-11-21 15:57:40.158314: val_loss -0.7313 +2024-11-21 15:57:40.158396: Pseudo dice [0.8248] +2024-11-21 15:57:40.158476: Epoch time: 18.86 s +2024-11-21 15:57:40.972041: +2024-11-21 15:57:40.972242: Epoch 970 +2024-11-21 15:57:40.972357: Current learning rate: 0.0089 +2024-11-21 15:57:58.725603: train_loss -0.7713 +2024-11-21 15:57:58.725841: val_loss -0.7322 +2024-11-21 15:57:58.725915: Pseudo dice [0.8165] +2024-11-21 15:57:58.726009: Epoch time: 17.75 s +2024-11-21 15:57:59.537380: +2024-11-21 15:57:59.537596: Epoch 971 +2024-11-21 15:57:59.537713: Current learning rate: 0.0089 +2024-11-21 15:58:18.424287: train_loss -0.7615 +2024-11-21 15:58:18.424491: val_loss -0.7214 +2024-11-21 15:58:18.424564: Pseudo dice [0.8085] +2024-11-21 15:58:18.424639: Epoch time: 18.89 s +2024-11-21 15:58:19.614146: +2024-11-21 15:58:19.614366: Epoch 972 +2024-11-21 15:58:19.614480: Current learning rate: 0.0089 +2024-11-21 15:58:38.997005: train_loss -0.7541 +2024-11-21 15:58:38.997218: val_loss -0.7268 +2024-11-21 15:58:38.997291: Pseudo dice [0.8194] +2024-11-21 15:58:38.997367: Epoch time: 19.38 s +2024-11-21 15:58:39.811787: +2024-11-21 15:58:39.812018: Epoch 973 +2024-11-21 15:58:39.812144: Current learning rate: 0.0089 +2024-11-21 15:58:59.829976: train_loss -0.7738 +2024-11-21 15:58:59.830186: val_loss -0.7278 +2024-11-21 15:58:59.830258: Pseudo dice [0.8423] +2024-11-21 15:58:59.830409: Epoch time: 20.02 s +2024-11-21 15:59:00.641710: +2024-11-21 15:59:00.642012: Epoch 974 +2024-11-21 15:59:00.642127: Current learning rate: 0.0089 +2024-11-21 15:59:19.456121: train_loss -0.7614 +2024-11-21 15:59:19.456369: val_loss -0.7545 +2024-11-21 15:59:19.456446: Pseudo dice [0.8266] +2024-11-21 15:59:19.456529: Epoch time: 18.82 s +2024-11-21 15:59:20.273540: +2024-11-21 15:59:20.273747: Epoch 975 +2024-11-21 15:59:20.273863: Current learning rate: 0.0089 +2024-11-21 15:59:39.332929: train_loss -0.7683 +2024-11-21 15:59:39.334663: val_loss -0.7332 +2024-11-21 15:59:39.334798: Pseudo dice [0.816] +2024-11-21 15:59:39.334900: Epoch time: 19.06 s +2024-11-21 15:59:40.150491: +2024-11-21 15:59:40.150826: Epoch 976 +2024-11-21 15:59:40.150941: Current learning rate: 0.00889 +2024-11-21 15:59:59.568925: train_loss -0.7544 +2024-11-21 15:59:59.569154: val_loss -0.7229 +2024-11-21 15:59:59.569260: Pseudo dice [0.8162] +2024-11-21 15:59:59.569344: Epoch time: 19.42 s +2024-11-21 16:00:00.385842: +2024-11-21 16:00:00.386049: Epoch 977 +2024-11-21 16:00:00.386166: Current learning rate: 0.00889 +2024-11-21 16:00:19.406406: train_loss -0.7453 +2024-11-21 16:00:19.406626: val_loss -0.7218 +2024-11-21 16:00:19.406704: Pseudo dice [0.8199] +2024-11-21 16:00:19.406784: Epoch time: 19.02 s +2024-11-21 16:00:20.223670: +2024-11-21 16:00:20.223886: Epoch 978 +2024-11-21 16:00:20.224030: Current learning rate: 0.00889 +2024-11-21 16:00:37.608181: train_loss -0.7669 +2024-11-21 16:00:37.611624: val_loss -0.7304 +2024-11-21 16:00:37.611747: Pseudo dice [0.8329] +2024-11-21 16:00:37.611844: Epoch time: 17.39 s +2024-11-21 16:00:38.480807: +2024-11-21 16:00:38.481017: Epoch 979 +2024-11-21 16:00:38.481134: Current learning rate: 0.00889 +2024-11-21 16:00:57.032132: train_loss -0.7669 +2024-11-21 16:00:57.032382: val_loss -0.7627 +2024-11-21 16:00:57.032458: Pseudo dice [0.8253] +2024-11-21 16:00:57.032536: Epoch time: 18.55 s +2024-11-21 16:00:57.851014: +2024-11-21 16:00:57.851205: Epoch 980 +2024-11-21 16:00:57.851313: Current learning rate: 0.00889 +2024-11-21 16:01:16.565626: train_loss -0.769 +2024-11-21 16:01:16.565841: val_loss -0.7379 +2024-11-21 16:01:16.565928: Pseudo dice [0.8228] +2024-11-21 16:01:16.566010: Epoch time: 18.72 s +2024-11-21 16:01:17.374887: +2024-11-21 16:01:17.375151: Epoch 981 +2024-11-21 16:01:17.375269: Current learning rate: 0.00889 +2024-11-21 16:01:36.479761: train_loss -0.7625 +2024-11-21 16:01:36.479988: val_loss -0.7513 +2024-11-21 16:01:36.480074: Pseudo dice [0.8362] +2024-11-21 16:01:36.480163: Epoch time: 19.11 s +2024-11-21 16:01:37.291243: +2024-11-21 16:01:37.291493: Epoch 982 +2024-11-21 16:01:37.291605: Current learning rate: 0.00889 +2024-11-21 16:01:55.909291: train_loss -0.7657 +2024-11-21 16:01:55.909548: val_loss -0.7303 +2024-11-21 16:01:55.909622: Pseudo dice [0.8112] +2024-11-21 16:01:55.909698: Epoch time: 18.62 s +2024-11-21 16:01:56.718762: +2024-11-21 16:01:56.719060: Epoch 983 +2024-11-21 16:01:56.719173: Current learning rate: 0.00889 +2024-11-21 16:02:16.007638: train_loss -0.7598 +2024-11-21 16:02:16.007862: val_loss -0.7169 +2024-11-21 16:02:16.007937: Pseudo dice [0.7943] +2024-11-21 16:02:16.008039: Epoch time: 19.29 s +2024-11-21 16:02:17.196215: +2024-11-21 16:02:17.196519: Epoch 984 +2024-11-21 16:02:17.196629: Current learning rate: 0.00889 +2024-11-21 16:02:36.281072: train_loss -0.7571 +2024-11-21 16:02:36.286525: val_loss -0.7344 +2024-11-21 16:02:36.286648: Pseudo dice [0.8262] +2024-11-21 16:02:36.286740: Epoch time: 19.09 s +2024-11-21 16:02:37.267286: +2024-11-21 16:02:37.267520: Epoch 985 +2024-11-21 16:02:37.267636: Current learning rate: 0.00888 +2024-11-21 16:02:55.312536: train_loss -0.7563 +2024-11-21 16:02:55.312769: val_loss -0.726 +2024-11-21 16:02:55.312845: Pseudo dice [0.8213] +2024-11-21 16:02:55.312963: Epoch time: 18.05 s +2024-11-21 16:02:56.136635: +2024-11-21 16:02:56.136864: Epoch 986 +2024-11-21 16:02:56.137002: Current learning rate: 0.00888 +2024-11-21 16:03:14.397013: train_loss -0.768 +2024-11-21 16:03:14.397554: val_loss -0.7398 +2024-11-21 16:03:14.397630: Pseudo dice [0.8223] +2024-11-21 16:03:14.397706: Epoch time: 18.26 s +2024-11-21 16:03:15.203815: +2024-11-21 16:03:15.204026: Epoch 987 +2024-11-21 16:03:15.204145: Current learning rate: 0.00888 +2024-11-21 16:03:34.216722: train_loss -0.7569 +2024-11-21 16:03:34.216931: val_loss -0.7135 +2024-11-21 16:03:34.217029: Pseudo dice [0.8182] +2024-11-21 16:03:34.217109: Epoch time: 19.01 s +2024-11-21 16:03:35.028144: +2024-11-21 16:03:35.028355: Epoch 988 +2024-11-21 16:03:35.028471: Current learning rate: 0.00888 +2024-11-21 16:03:53.869136: train_loss -0.7524 +2024-11-21 16:03:53.869369: val_loss -0.7442 +2024-11-21 16:03:53.869447: Pseudo dice [0.8149] +2024-11-21 16:03:53.869524: Epoch time: 18.84 s +2024-11-21 16:03:54.694221: +2024-11-21 16:03:54.694441: Epoch 989 +2024-11-21 16:03:54.694558: Current learning rate: 0.00888 +2024-11-21 16:04:13.205983: train_loss -0.7489 +2024-11-21 16:04:13.206193: val_loss -0.7148 +2024-11-21 16:04:13.206268: Pseudo dice [0.8056] +2024-11-21 16:04:13.206348: Epoch time: 18.51 s +2024-11-21 16:04:14.019399: +2024-11-21 16:04:14.019635: Epoch 990 +2024-11-21 16:04:14.019759: Current learning rate: 0.00888 +2024-11-21 16:04:33.329640: train_loss -0.7462 +2024-11-21 16:04:33.329869: val_loss -0.754 +2024-11-21 16:04:33.329944: Pseudo dice [0.8395] +2024-11-21 16:04:33.330027: Epoch time: 19.31 s +2024-11-21 16:04:34.141559: +2024-11-21 16:04:34.141768: Epoch 991 +2024-11-21 16:04:34.141883: Current learning rate: 0.00888 +2024-11-21 16:04:52.390028: train_loss -0.7711 +2024-11-21 16:04:52.390247: val_loss -0.7566 +2024-11-21 16:04:52.402879: Pseudo dice [0.8123] +2024-11-21 16:04:52.402989: Epoch time: 18.25 s +2024-11-21 16:04:53.213522: +2024-11-21 16:04:53.213739: Epoch 992 +2024-11-21 16:04:53.213852: Current learning rate: 0.00888 +2024-11-21 16:05:12.085273: train_loss -0.7622 +2024-11-21 16:05:12.085509: val_loss -0.7295 +2024-11-21 16:05:12.085585: Pseudo dice [0.8192] +2024-11-21 16:05:12.085672: Epoch time: 18.87 s +2024-11-21 16:05:12.902955: +2024-11-21 16:05:12.903163: Epoch 993 +2024-11-21 16:05:12.903279: Current learning rate: 0.00888 +2024-11-21 16:05:31.546172: train_loss -0.7625 +2024-11-21 16:05:31.546373: val_loss -0.7394 +2024-11-21 16:05:31.546448: Pseudo dice [0.8106] +2024-11-21 16:05:31.546524: Epoch time: 18.64 s +2024-11-21 16:05:32.355886: +2024-11-21 16:05:32.356099: Epoch 994 +2024-11-21 16:05:32.356225: Current learning rate: 0.00887 +2024-11-21 16:05:50.925838: train_loss -0.7661 +2024-11-21 16:05:50.926054: val_loss -0.7235 +2024-11-21 16:05:50.926132: Pseudo dice [0.8068] +2024-11-21 16:05:50.926211: Epoch time: 18.57 s +2024-11-21 16:05:51.735325: +2024-11-21 16:05:51.735519: Epoch 995 +2024-11-21 16:05:51.735632: Current learning rate: 0.00887 +2024-11-21 16:06:10.140173: train_loss -0.766 +2024-11-21 16:06:10.140407: val_loss -0.7437 +2024-11-21 16:06:10.140486: Pseudo dice [0.8378] +2024-11-21 16:06:10.140571: Epoch time: 18.41 s +2024-11-21 16:06:11.344346: +2024-11-21 16:06:11.344608: Epoch 996 +2024-11-21 16:06:11.344724: Current learning rate: 0.00887 +2024-11-21 16:06:29.612878: train_loss -0.7567 +2024-11-21 16:06:29.613118: val_loss -0.7456 +2024-11-21 16:06:29.613192: Pseudo dice [0.8396] +2024-11-21 16:06:29.613267: Epoch time: 18.27 s +2024-11-21 16:06:30.427688: +2024-11-21 16:06:30.427916: Epoch 997 +2024-11-21 16:06:30.428035: Current learning rate: 0.00887 +2024-11-21 16:06:48.655946: train_loss -0.7629 +2024-11-21 16:06:48.656167: val_loss -0.7366 +2024-11-21 16:06:48.656245: Pseudo dice [0.814] +2024-11-21 16:06:48.656326: Epoch time: 18.23 s +2024-11-21 16:06:49.482329: +2024-11-21 16:06:49.482535: Epoch 998 +2024-11-21 16:06:49.482646: Current learning rate: 0.00887 +2024-11-21 16:07:08.585498: train_loss -0.7561 +2024-11-21 16:07:08.585754: val_loss -0.7264 +2024-11-21 16:07:08.585832: Pseudo dice [0.8374] +2024-11-21 16:07:08.585916: Epoch time: 19.1 s +2024-11-21 16:07:09.399451: +2024-11-21 16:07:09.399731: Epoch 999 +2024-11-21 16:07:09.399846: Current learning rate: 0.00887 +2024-11-21 16:07:27.821147: train_loss -0.7615 +2024-11-21 16:07:27.821361: val_loss -0.7454 +2024-11-21 16:07:27.821440: Pseudo dice [0.8271] +2024-11-21 16:07:27.821518: Epoch time: 18.42 s +2024-11-21 16:07:28.936167: +2024-11-21 16:07:28.936391: Epoch 1000 +2024-11-21 16:07:28.936506: Current learning rate: 0.00887 +2024-11-21 16:07:47.072831: train_loss -0.7591 +2024-11-21 16:07:47.073058: val_loss -0.7534 +2024-11-21 16:07:47.073133: Pseudo dice [0.82] +2024-11-21 16:07:47.073215: Epoch time: 18.14 s +2024-11-21 16:07:47.902353: +2024-11-21 16:07:47.902589: Epoch 1001 +2024-11-21 16:07:47.902699: Current learning rate: 0.00887 +2024-11-21 16:08:06.596462: train_loss -0.7667 +2024-11-21 16:08:06.596670: val_loss -0.715 +2024-11-21 16:08:06.596746: Pseudo dice [0.828] +2024-11-21 16:08:06.596825: Epoch time: 18.69 s +2024-11-21 16:08:07.408151: +2024-11-21 16:08:07.408354: Epoch 1002 +2024-11-21 16:08:07.408468: Current learning rate: 0.00887 +2024-11-21 16:08:26.232039: train_loss -0.7695 +2024-11-21 16:08:26.232273: val_loss -0.7385 +2024-11-21 16:08:26.236959: Pseudo dice [0.826] +2024-11-21 16:08:26.237103: Epoch time: 18.82 s +2024-11-21 16:08:27.054453: +2024-11-21 16:08:27.054663: Epoch 1003 +2024-11-21 16:08:27.054777: Current learning rate: 0.00886 +2024-11-21 16:08:45.175551: train_loss -0.7545 +2024-11-21 16:08:45.178763: val_loss -0.7495 +2024-11-21 16:08:45.178857: Pseudo dice [0.8222] +2024-11-21 16:08:45.178941: Epoch time: 18.12 s +2024-11-21 16:08:46.139073: +2024-11-21 16:08:46.139293: Epoch 1004 +2024-11-21 16:08:46.139407: Current learning rate: 0.00886 +2024-11-21 16:09:04.584046: train_loss -0.7625 +2024-11-21 16:09:04.584283: val_loss -0.7276 +2024-11-21 16:09:04.584361: Pseudo dice [0.8148] +2024-11-21 16:09:04.584454: Epoch time: 18.45 s +2024-11-21 16:09:05.394619: +2024-11-21 16:09:05.394887: Epoch 1005 +2024-11-21 16:09:05.395009: Current learning rate: 0.00886 +2024-11-21 16:09:24.288308: train_loss -0.753 +2024-11-21 16:09:24.288540: val_loss -0.7461 +2024-11-21 16:09:24.288614: Pseudo dice [0.8282] +2024-11-21 16:09:24.288697: Epoch time: 18.89 s +2024-11-21 16:09:25.174828: +2024-11-21 16:09:25.175050: Epoch 1006 +2024-11-21 16:09:25.175169: Current learning rate: 0.00886 +2024-11-21 16:09:42.908309: train_loss -0.7564 +2024-11-21 16:09:42.908534: val_loss -0.7117 +2024-11-21 16:09:42.908611: Pseudo dice [0.8292] +2024-11-21 16:09:42.908690: Epoch time: 17.73 s +2024-11-21 16:09:43.721259: +2024-11-21 16:09:43.721444: Epoch 1007 +2024-11-21 16:09:43.721575: Current learning rate: 0.00886 +2024-11-21 16:10:02.322040: train_loss -0.7505 +2024-11-21 16:10:02.322280: val_loss -0.7285 +2024-11-21 16:10:02.322355: Pseudo dice [0.8122] +2024-11-21 16:10:02.322491: Epoch time: 18.6 s +2024-11-21 16:10:03.136943: +2024-11-21 16:10:03.137207: Epoch 1008 +2024-11-21 16:10:03.137336: Current learning rate: 0.00886 +2024-11-21 16:10:21.122553: train_loss -0.7651 +2024-11-21 16:10:21.122828: val_loss -0.7463 +2024-11-21 16:10:21.122903: Pseudo dice [0.8282] +2024-11-21 16:10:21.122987: Epoch time: 17.99 s +2024-11-21 16:10:21.982313: +2024-11-21 16:10:21.982531: Epoch 1009 +2024-11-21 16:10:21.982652: Current learning rate: 0.00886 +2024-11-21 16:10:41.871538: train_loss -0.7559 +2024-11-21 16:10:41.880360: val_loss -0.7251 +2024-11-21 16:10:41.880497: Pseudo dice [0.8172] +2024-11-21 16:10:41.880575: Epoch time: 19.89 s +2024-11-21 16:10:42.707179: +2024-11-21 16:10:42.707485: Epoch 1010 +2024-11-21 16:10:42.707604: Current learning rate: 0.00886 +2024-11-21 16:11:01.785719: train_loss -0.7607 +2024-11-21 16:11:01.785931: val_loss -0.7248 +2024-11-21 16:11:01.786022: Pseudo dice [0.8154] +2024-11-21 16:11:01.786099: Epoch time: 19.08 s +2024-11-21 16:11:02.777520: +2024-11-21 16:11:02.777741: Epoch 1011 +2024-11-21 16:11:02.777860: Current learning rate: 0.00886 +2024-11-21 16:11:22.272385: train_loss -0.7633 +2024-11-21 16:11:22.272598: val_loss -0.7458 +2024-11-21 16:11:22.272673: Pseudo dice [0.8123] +2024-11-21 16:11:22.272751: Epoch time: 19.5 s +2024-11-21 16:11:23.104367: +2024-11-21 16:11:23.104583: Epoch 1012 +2024-11-21 16:11:23.104699: Current learning rate: 0.00885 +2024-11-21 16:11:41.720346: train_loss -0.7567 +2024-11-21 16:11:41.723049: val_loss -0.7222 +2024-11-21 16:11:41.723276: Pseudo dice [0.8054] +2024-11-21 16:11:41.723363: Epoch time: 18.62 s +2024-11-21 16:11:42.702055: +2024-11-21 16:11:42.702297: Epoch 1013 +2024-11-21 16:11:42.702414: Current learning rate: 0.00885 +2024-11-21 16:12:00.225788: train_loss -0.7692 +2024-11-21 16:12:00.226012: val_loss -0.7461 +2024-11-21 16:12:00.226085: Pseudo dice [0.8362] +2024-11-21 16:12:00.226161: Epoch time: 17.52 s +2024-11-21 16:12:01.043269: +2024-11-21 16:12:01.043486: Epoch 1014 +2024-11-21 16:12:01.043604: Current learning rate: 0.00885 +2024-11-21 16:12:18.537136: train_loss -0.7623 +2024-11-21 16:12:18.537690: val_loss -0.7181 +2024-11-21 16:12:18.537767: Pseudo dice [0.8242] +2024-11-21 16:12:18.537842: Epoch time: 17.49 s +2024-11-21 16:12:19.351792: +2024-11-21 16:12:19.351965: Epoch 1015 +2024-11-21 16:12:19.352101: Current learning rate: 0.00885 +2024-11-21 16:12:38.121362: train_loss -0.7633 +2024-11-21 16:12:38.123187: val_loss -0.7102 +2024-11-21 16:12:38.123305: Pseudo dice [0.8058] +2024-11-21 16:12:38.123392: Epoch time: 18.77 s +2024-11-21 16:12:38.986559: +2024-11-21 16:12:38.986763: Epoch 1016 +2024-11-21 16:12:38.986884: Current learning rate: 0.00885 +2024-11-21 16:12:57.399734: train_loss -0.7682 +2024-11-21 16:12:57.399940: val_loss -0.7256 +2024-11-21 16:12:57.400023: Pseudo dice [0.8253] +2024-11-21 16:12:57.400099: Epoch time: 18.41 s +2024-11-21 16:12:58.216235: +2024-11-21 16:12:58.216656: Epoch 1017 +2024-11-21 16:12:58.216774: Current learning rate: 0.00885 +2024-11-21 16:13:16.781912: train_loss -0.7679 +2024-11-21 16:13:16.782151: val_loss -0.753 +2024-11-21 16:13:16.782224: Pseudo dice [0.8184] +2024-11-21 16:13:16.782299: Epoch time: 18.57 s +2024-11-21 16:13:17.602710: +2024-11-21 16:13:17.602899: Epoch 1018 +2024-11-21 16:13:17.603017: Current learning rate: 0.00885 +2024-11-21 16:13:36.119314: train_loss -0.7639 +2024-11-21 16:13:36.124692: val_loss -0.7366 +2024-11-21 16:13:36.124865: Pseudo dice [0.8181] +2024-11-21 16:13:36.124958: Epoch time: 18.52 s +2024-11-21 16:13:37.370749: +2024-11-21 16:13:37.371013: Epoch 1019 +2024-11-21 16:13:37.371128: Current learning rate: 0.00885 +2024-11-21 16:13:56.390465: train_loss -0.7703 +2024-11-21 16:13:56.390729: val_loss -0.7348 +2024-11-21 16:13:56.390825: Pseudo dice [0.8254] +2024-11-21 16:13:56.390906: Epoch time: 19.02 s +2024-11-21 16:13:57.207741: +2024-11-21 16:13:57.207961: Epoch 1020 +2024-11-21 16:13:57.208077: Current learning rate: 0.00884 +2024-11-21 16:14:16.048839: train_loss -0.7686 +2024-11-21 16:14:16.049056: val_loss -0.7471 +2024-11-21 16:14:16.049131: Pseudo dice [0.828] +2024-11-21 16:14:16.049205: Epoch time: 18.84 s +2024-11-21 16:14:16.897014: +2024-11-21 16:14:16.897253: Epoch 1021 +2024-11-21 16:14:16.897371: Current learning rate: 0.00884 +2024-11-21 16:14:36.854333: train_loss -0.7681 +2024-11-21 16:14:36.854540: val_loss -0.7384 +2024-11-21 16:14:36.854613: Pseudo dice [0.8182] +2024-11-21 16:14:36.854690: Epoch time: 19.96 s +2024-11-21 16:14:37.679440: +2024-11-21 16:14:37.679713: Epoch 1022 +2024-11-21 16:14:37.679834: Current learning rate: 0.00884 +2024-11-21 16:14:57.039896: train_loss -0.7627 +2024-11-21 16:14:57.040147: val_loss -0.7398 +2024-11-21 16:14:57.040222: Pseudo dice [0.8318] +2024-11-21 16:14:57.040429: Epoch time: 19.36 s +2024-11-21 16:14:57.861904: +2024-11-21 16:14:57.862119: Epoch 1023 +2024-11-21 16:14:57.862238: Current learning rate: 0.00884 +2024-11-21 16:15:15.379718: train_loss -0.774 +2024-11-21 16:15:15.379926: val_loss -0.7642 +2024-11-21 16:15:15.380006: Pseudo dice [0.8328] +2024-11-21 16:15:15.380080: Epoch time: 17.52 s +2024-11-21 16:15:16.194404: +2024-11-21 16:15:16.194661: Epoch 1024 +2024-11-21 16:15:16.194774: Current learning rate: 0.00884 +2024-11-21 16:15:35.333245: train_loss -0.7664 +2024-11-21 16:15:35.333450: val_loss -0.7321 +2024-11-21 16:15:35.333523: Pseudo dice [0.8238] +2024-11-21 16:15:35.333600: Epoch time: 19.14 s +2024-11-21 16:15:36.155676: +2024-11-21 16:15:36.155906: Epoch 1025 +2024-11-21 16:15:36.156024: Current learning rate: 0.00884 +2024-11-21 16:15:54.188507: train_loss -0.764 +2024-11-21 16:15:54.188762: val_loss -0.7399 +2024-11-21 16:15:54.188844: Pseudo dice [0.8367] +2024-11-21 16:15:54.188925: Epoch time: 18.03 s +2024-11-21 16:15:55.023074: +2024-11-21 16:15:55.023458: Epoch 1026 +2024-11-21 16:15:55.023568: Current learning rate: 0.00884 +2024-11-21 16:16:14.056443: train_loss -0.77 +2024-11-21 16:16:14.056698: val_loss -0.7265 +2024-11-21 16:16:14.056783: Pseudo dice [0.7873] +2024-11-21 16:16:14.056870: Epoch time: 19.03 s +2024-11-21 16:16:14.873565: +2024-11-21 16:16:14.873843: Epoch 1027 +2024-11-21 16:16:14.873960: Current learning rate: 0.00884 +2024-11-21 16:16:33.248664: train_loss -0.7752 +2024-11-21 16:16:33.248876: val_loss -0.7155 +2024-11-21 16:16:33.248949: Pseudo dice [0.814] +2024-11-21 16:16:33.249056: Epoch time: 18.38 s +2024-11-21 16:16:34.064890: +2024-11-21 16:16:34.065081: Epoch 1028 +2024-11-21 16:16:34.065192: Current learning rate: 0.00884 +2024-11-21 16:16:52.924425: train_loss -0.7676 +2024-11-21 16:16:52.924635: val_loss -0.72 +2024-11-21 16:16:52.924712: Pseudo dice [0.8112] +2024-11-21 16:16:52.924804: Epoch time: 18.86 s +2024-11-21 16:16:53.748288: +2024-11-21 16:16:53.748479: Epoch 1029 +2024-11-21 16:16:53.748589: Current learning rate: 0.00883 +2024-11-21 16:17:12.493525: train_loss -0.752 +2024-11-21 16:17:12.493736: val_loss -0.7399 +2024-11-21 16:17:12.493813: Pseudo dice [0.8284] +2024-11-21 16:17:12.494984: Epoch time: 18.75 s +2024-11-21 16:17:13.357359: +2024-11-21 16:17:13.357577: Epoch 1030 +2024-11-21 16:17:13.357689: Current learning rate: 0.00883 +2024-11-21 16:17:31.010469: train_loss -0.7647 +2024-11-21 16:17:31.010685: val_loss -0.7126 +2024-11-21 16:17:31.010759: Pseudo dice [0.8265] +2024-11-21 16:17:31.010902: Epoch time: 17.65 s +2024-11-21 16:17:32.185205: +2024-11-21 16:17:32.185482: Epoch 1031 +2024-11-21 16:17:32.185593: Current learning rate: 0.00883 +2024-11-21 16:17:50.632058: train_loss -0.7716 +2024-11-21 16:17:50.632276: val_loss -0.7328 +2024-11-21 16:17:50.632351: Pseudo dice [0.8203] +2024-11-21 16:17:50.632424: Epoch time: 18.45 s +2024-11-21 16:17:51.449044: +2024-11-21 16:17:51.449239: Epoch 1032 +2024-11-21 16:17:51.449349: Current learning rate: 0.00883 +2024-11-21 16:18:09.584881: train_loss -0.7739 +2024-11-21 16:18:09.585104: val_loss -0.7219 +2024-11-21 16:18:09.585180: Pseudo dice [0.8281] +2024-11-21 16:18:09.585258: Epoch time: 18.14 s +2024-11-21 16:18:10.401532: +2024-11-21 16:18:10.401741: Epoch 1033 +2024-11-21 16:18:10.401853: Current learning rate: 0.00883 +2024-11-21 16:18:29.251531: train_loss -0.7653 +2024-11-21 16:18:29.251765: val_loss -0.7165 +2024-11-21 16:18:29.251839: Pseudo dice [0.8049] +2024-11-21 16:18:29.251920: Epoch time: 18.85 s +2024-11-21 16:18:30.073344: +2024-11-21 16:18:30.073598: Epoch 1034 +2024-11-21 16:18:30.073710: Current learning rate: 0.00883 +2024-11-21 16:18:48.296763: train_loss -0.7471 +2024-11-21 16:18:48.297008: val_loss -0.7285 +2024-11-21 16:18:48.297082: Pseudo dice [0.8127] +2024-11-21 16:18:48.297159: Epoch time: 18.22 s +2024-11-21 16:18:49.133225: +2024-11-21 16:18:49.133449: Epoch 1035 +2024-11-21 16:18:49.133569: Current learning rate: 0.00883 +2024-11-21 16:19:08.645575: train_loss -0.7662 +2024-11-21 16:19:08.645781: val_loss -0.7268 +2024-11-21 16:19:08.645854: Pseudo dice [0.8198] +2024-11-21 16:19:08.645930: Epoch time: 19.51 s +2024-11-21 16:19:09.467984: +2024-11-21 16:19:09.468189: Epoch 1036 +2024-11-21 16:19:09.468307: Current learning rate: 0.00883 +2024-11-21 16:19:28.069591: train_loss -0.7703 +2024-11-21 16:19:28.069844: val_loss -0.7348 +2024-11-21 16:19:28.069925: Pseudo dice [0.8133] +2024-11-21 16:19:28.070091: Epoch time: 18.6 s +2024-11-21 16:19:28.896158: +2024-11-21 16:19:28.896373: Epoch 1037 +2024-11-21 16:19:28.896486: Current learning rate: 0.00883 +2024-11-21 16:19:47.438113: train_loss -0.762 +2024-11-21 16:19:47.438331: val_loss -0.7426 +2024-11-21 16:19:47.438408: Pseudo dice [0.8217] +2024-11-21 16:19:47.438492: Epoch time: 18.54 s +2024-11-21 16:19:48.256692: +2024-11-21 16:19:48.256924: Epoch 1038 +2024-11-21 16:19:48.257039: Current learning rate: 0.00882 +2024-11-21 16:20:08.237011: train_loss -0.7571 +2024-11-21 16:20:08.237272: val_loss -0.7371 +2024-11-21 16:20:08.237351: Pseudo dice [0.8014] +2024-11-21 16:20:08.237435: Epoch time: 19.98 s +2024-11-21 16:20:09.166496: +2024-11-21 16:20:09.166687: Epoch 1039 +2024-11-21 16:20:09.166798: Current learning rate: 0.00882 +2024-11-21 16:20:28.082814: train_loss -0.7571 +2024-11-21 16:20:28.083033: val_loss -0.7549 +2024-11-21 16:20:28.083109: Pseudo dice [0.823] +2024-11-21 16:20:28.083187: Epoch time: 18.92 s +2024-11-21 16:20:29.123189: +2024-11-21 16:20:29.123380: Epoch 1040 +2024-11-21 16:20:29.123497: Current learning rate: 0.00882 +2024-11-21 16:20:47.054543: train_loss -0.77 +2024-11-21 16:20:47.054778: val_loss -0.7282 +2024-11-21 16:20:47.054870: Pseudo dice [0.8292] +2024-11-21 16:20:47.055017: Epoch time: 17.93 s +2024-11-21 16:20:47.879696: +2024-11-21 16:20:47.879969: Epoch 1041 +2024-11-21 16:20:47.880082: Current learning rate: 0.00882 +2024-11-21 16:21:06.290334: train_loss -0.7633 +2024-11-21 16:21:06.290605: val_loss -0.714 +2024-11-21 16:21:06.290686: Pseudo dice [0.8101] +2024-11-21 16:21:06.290764: Epoch time: 18.41 s +2024-11-21 16:21:07.142222: +2024-11-21 16:21:07.142399: Epoch 1042 +2024-11-21 16:21:07.142512: Current learning rate: 0.00882 +2024-11-21 16:21:25.231131: train_loss -0.764 +2024-11-21 16:21:25.234798: val_loss -0.7654 +2024-11-21 16:21:25.234886: Pseudo dice [0.8343] +2024-11-21 16:21:25.234969: Epoch time: 18.09 s +2024-11-21 16:21:26.425939: +2024-11-21 16:21:26.426159: Epoch 1043 +2024-11-21 16:21:26.426268: Current learning rate: 0.00882 +2024-11-21 16:21:45.910141: train_loss -0.7615 +2024-11-21 16:21:45.914561: val_loss -0.7538 +2024-11-21 16:21:45.914690: Pseudo dice [0.8236] +2024-11-21 16:21:45.914786: Epoch time: 19.48 s +2024-11-21 16:21:46.894248: +2024-11-21 16:21:46.894475: Epoch 1044 +2024-11-21 16:21:46.894589: Current learning rate: 0.00882 +2024-11-21 16:22:05.507905: train_loss -0.7623 +2024-11-21 16:22:05.508191: val_loss -0.7502 +2024-11-21 16:22:05.508266: Pseudo dice [0.8171] +2024-11-21 16:22:05.508368: Epoch time: 18.61 s +2024-11-21 16:22:06.318999: +2024-11-21 16:22:06.319326: Epoch 1045 +2024-11-21 16:22:06.319443: Current learning rate: 0.00882 +2024-11-21 16:22:24.859297: train_loss -0.7702 +2024-11-21 16:22:24.859566: val_loss -0.7457 +2024-11-21 16:22:24.859645: Pseudo dice [0.8323] +2024-11-21 16:22:24.859728: Epoch time: 18.54 s +2024-11-21 16:22:25.679785: +2024-11-21 16:22:25.680000: Epoch 1046 +2024-11-21 16:22:25.680111: Current learning rate: 0.00882 +2024-11-21 16:22:44.375525: train_loss -0.7644 +2024-11-21 16:22:44.375743: val_loss -0.7084 +2024-11-21 16:22:44.375818: Pseudo dice [0.8108] +2024-11-21 16:22:44.375902: Epoch time: 18.7 s +2024-11-21 16:22:45.227054: +2024-11-21 16:22:45.227338: Epoch 1047 +2024-11-21 16:22:45.227454: Current learning rate: 0.00881 +2024-11-21 16:23:04.397137: train_loss -0.769 +2024-11-21 16:23:04.397362: val_loss -0.7634 +2024-11-21 16:23:04.397478: Pseudo dice [0.838] +2024-11-21 16:23:04.397559: Epoch time: 19.17 s +2024-11-21 16:23:05.229612: +2024-11-21 16:23:05.229819: Epoch 1048 +2024-11-21 16:23:05.229942: Current learning rate: 0.00881 +2024-11-21 16:23:22.641271: train_loss -0.7717 +2024-11-21 16:23:22.641531: val_loss -0.756 +2024-11-21 16:23:22.641605: Pseudo dice [0.8428] +2024-11-21 16:23:22.641801: Epoch time: 17.41 s +2024-11-21 16:23:23.452182: +2024-11-21 16:23:23.452398: Epoch 1049 +2024-11-21 16:23:23.452513: Current learning rate: 0.00881 +2024-11-21 16:23:42.239817: train_loss -0.7837 +2024-11-21 16:23:42.240036: val_loss -0.7243 +2024-11-21 16:23:42.240109: Pseudo dice [0.8163] +2024-11-21 16:23:42.240187: Epoch time: 18.79 s +2024-11-21 16:23:43.357054: +2024-11-21 16:23:43.357277: Epoch 1050 +2024-11-21 16:23:43.357404: Current learning rate: 0.00881 +2024-11-21 16:24:02.261740: train_loss -0.764 +2024-11-21 16:24:02.262013: val_loss -0.7313 +2024-11-21 16:24:02.262159: Pseudo dice [0.8097] +2024-11-21 16:24:02.262245: Epoch time: 18.91 s +2024-11-21 16:24:03.148978: +2024-11-21 16:24:03.149196: Epoch 1051 +2024-11-21 16:24:03.149323: Current learning rate: 0.00881 +2024-11-21 16:24:21.758062: train_loss -0.769 +2024-11-21 16:24:21.758273: val_loss -0.7492 +2024-11-21 16:24:21.758345: Pseudo dice [0.8316] +2024-11-21 16:24:21.758420: Epoch time: 18.61 s +2024-11-21 16:24:22.580576: +2024-11-21 16:24:22.580812: Epoch 1052 +2024-11-21 16:24:22.580930: Current learning rate: 0.00881 +2024-11-21 16:24:41.476278: train_loss -0.7559 +2024-11-21 16:24:41.476499: val_loss -0.7366 +2024-11-21 16:24:41.476589: Pseudo dice [0.8167] +2024-11-21 16:24:41.476674: Epoch time: 18.9 s +2024-11-21 16:24:42.289972: +2024-11-21 16:24:42.290235: Epoch 1053 +2024-11-21 16:24:42.290365: Current learning rate: 0.00881 +2024-11-21 16:25:01.007581: train_loss -0.734 +2024-11-21 16:25:01.007832: val_loss -0.7326 +2024-11-21 16:25:01.007912: Pseudo dice [0.8196] +2024-11-21 16:25:01.008022: Epoch time: 18.72 s +2024-11-21 16:25:01.829834: +2024-11-21 16:25:01.830044: Epoch 1054 +2024-11-21 16:25:01.830160: Current learning rate: 0.00881 +2024-11-21 16:25:20.500696: train_loss -0.7597 +2024-11-21 16:25:20.500907: val_loss -0.7527 +2024-11-21 16:25:20.500983: Pseudo dice [0.8263] +2024-11-21 16:25:20.501078: Epoch time: 18.67 s +2024-11-21 16:25:21.317359: +2024-11-21 16:25:21.317566: Epoch 1055 +2024-11-21 16:25:21.317955: Current learning rate: 0.0088 +2024-11-21 16:25:39.987662: train_loss -0.7658 +2024-11-21 16:25:39.987875: val_loss -0.7397 +2024-11-21 16:25:39.987951: Pseudo dice [0.8171] +2024-11-21 16:25:39.988035: Epoch time: 18.67 s +2024-11-21 16:25:40.808807: +2024-11-21 16:25:40.809030: Epoch 1056 +2024-11-21 16:25:40.809141: Current learning rate: 0.0088 +2024-11-21 16:25:59.136253: train_loss -0.7587 +2024-11-21 16:25:59.143030: val_loss -0.736 +2024-11-21 16:25:59.143157: Pseudo dice [0.8236] +2024-11-21 16:25:59.143243: Epoch time: 18.33 s +2024-11-21 16:26:00.128132: +2024-11-21 16:26:00.128377: Epoch 1057 +2024-11-21 16:26:00.128497: Current learning rate: 0.0088 +2024-11-21 16:26:18.016707: train_loss -0.7617 +2024-11-21 16:26:18.016923: val_loss -0.72 +2024-11-21 16:26:18.017020: Pseudo dice [0.8207] +2024-11-21 16:26:18.017104: Epoch time: 17.89 s +2024-11-21 16:26:18.834309: +2024-11-21 16:26:18.834518: Epoch 1058 +2024-11-21 16:26:18.834633: Current learning rate: 0.0088 +2024-11-21 16:26:37.054569: train_loss -0.7589 +2024-11-21 16:26:37.054787: val_loss -0.7378 +2024-11-21 16:26:37.054863: Pseudo dice [0.8052] +2024-11-21 16:26:37.054941: Epoch time: 18.22 s +2024-11-21 16:26:38.045567: +2024-11-21 16:26:38.045782: Epoch 1059 +2024-11-21 16:26:38.045895: Current learning rate: 0.0088 +2024-11-21 16:26:57.359209: train_loss -0.7594 +2024-11-21 16:26:57.359436: val_loss -0.7316 +2024-11-21 16:26:57.359520: Pseudo dice [0.8186] +2024-11-21 16:26:57.359603: Epoch time: 19.31 s +2024-11-21 16:26:58.174545: +2024-11-21 16:26:58.174750: Epoch 1060 +2024-11-21 16:26:58.174862: Current learning rate: 0.0088 +2024-11-21 16:27:17.317966: train_loss -0.7503 +2024-11-21 16:27:17.318213: val_loss -0.7163 +2024-11-21 16:27:17.318297: Pseudo dice [0.8076] +2024-11-21 16:27:17.318386: Epoch time: 19.14 s +2024-11-21 16:27:18.133513: +2024-11-21 16:27:18.133733: Epoch 1061 +2024-11-21 16:27:18.133849: Current learning rate: 0.0088 +2024-11-21 16:27:37.498256: train_loss -0.7544 +2024-11-21 16:27:37.498464: val_loss -0.7108 +2024-11-21 16:27:37.498539: Pseudo dice [0.8214] +2024-11-21 16:27:37.498614: Epoch time: 19.37 s +2024-11-21 16:27:38.312453: +2024-11-21 16:27:38.312640: Epoch 1062 +2024-11-21 16:27:38.312762: Current learning rate: 0.0088 +2024-11-21 16:27:56.158409: train_loss -0.7561 +2024-11-21 16:27:56.158632: val_loss -0.7284 +2024-11-21 16:27:56.158707: Pseudo dice [0.8294] +2024-11-21 16:27:56.158782: Epoch time: 17.85 s +2024-11-21 16:27:57.085555: +2024-11-21 16:27:57.085755: Epoch 1063 +2024-11-21 16:27:57.085875: Current learning rate: 0.0088 +2024-11-21 16:28:14.754626: train_loss -0.759 +2024-11-21 16:28:14.754840: val_loss -0.7409 +2024-11-21 16:28:14.754937: Pseudo dice [0.828] +2024-11-21 16:28:14.755081: Epoch time: 17.67 s +2024-11-21 16:28:15.568296: +2024-11-21 16:28:15.568532: Epoch 1064 +2024-11-21 16:28:15.568644: Current learning rate: 0.00879 +2024-11-21 16:28:33.944077: train_loss -0.7609 +2024-11-21 16:28:33.944339: val_loss -0.7076 +2024-11-21 16:28:33.944416: Pseudo dice [0.805] +2024-11-21 16:28:33.944499: Epoch time: 18.38 s +2024-11-21 16:28:34.763586: +2024-11-21 16:28:34.763762: Epoch 1065 +2024-11-21 16:28:34.763872: Current learning rate: 0.00879 +2024-11-21 16:28:53.137731: train_loss -0.755 +2024-11-21 16:28:53.137937: val_loss -0.7142 +2024-11-21 16:28:53.138017: Pseudo dice [0.8088] +2024-11-21 16:28:53.138098: Epoch time: 18.37 s +2024-11-21 16:28:54.322578: +2024-11-21 16:28:54.322807: Epoch 1066 +2024-11-21 16:28:54.322924: Current learning rate: 0.00879 +2024-11-21 16:29:12.618790: train_loss -0.7494 +2024-11-21 16:29:12.619025: val_loss -0.7241 +2024-11-21 16:29:12.619100: Pseudo dice [0.8007] +2024-11-21 16:29:12.619179: Epoch time: 18.3 s +2024-11-21 16:29:13.440143: +2024-11-21 16:29:13.440344: Epoch 1067 +2024-11-21 16:29:13.440457: Current learning rate: 0.00879 +2024-11-21 16:29:31.730579: train_loss -0.7443 +2024-11-21 16:29:31.730823: val_loss -0.7225 +2024-11-21 16:29:31.730895: Pseudo dice [0.7932] +2024-11-21 16:29:31.730980: Epoch time: 18.29 s +2024-11-21 16:29:32.565985: +2024-11-21 16:29:32.566192: Epoch 1068 +2024-11-21 16:29:32.566306: Current learning rate: 0.00879 +2024-11-21 16:29:51.857014: train_loss -0.7589 +2024-11-21 16:29:51.857239: val_loss -0.715 +2024-11-21 16:29:51.857317: Pseudo dice [0.8169] +2024-11-21 16:29:51.857393: Epoch time: 19.29 s +2024-11-21 16:29:52.719733: +2024-11-21 16:29:52.719944: Epoch 1069 +2024-11-21 16:29:52.720060: Current learning rate: 0.00879 +2024-11-21 16:30:11.839568: train_loss -0.7619 +2024-11-21 16:30:11.839790: val_loss -0.7567 +2024-11-21 16:30:11.839935: Pseudo dice [0.818] +2024-11-21 16:30:11.840027: Epoch time: 19.12 s +2024-11-21 16:30:12.820097: +2024-11-21 16:30:12.820356: Epoch 1070 +2024-11-21 16:30:12.820470: Current learning rate: 0.00879 +2024-11-21 16:30:31.561045: train_loss -0.771 +2024-11-21 16:30:31.561261: val_loss -0.7533 +2024-11-21 16:30:31.561340: Pseudo dice [0.835] +2024-11-21 16:30:31.561419: Epoch time: 18.74 s +2024-11-21 16:30:32.386545: +2024-11-21 16:30:32.386768: Epoch 1071 +2024-11-21 16:30:32.386881: Current learning rate: 0.00879 +2024-11-21 16:30:50.117781: train_loss -0.767 +2024-11-21 16:30:50.118026: val_loss -0.7231 +2024-11-21 16:30:50.118102: Pseudo dice [0.8048] +2024-11-21 16:30:50.118190: Epoch time: 17.73 s +2024-11-21 16:30:50.938525: +2024-11-21 16:30:50.938772: Epoch 1072 +2024-11-21 16:30:50.938886: Current learning rate: 0.00879 +2024-11-21 16:31:09.986056: train_loss -0.7687 +2024-11-21 16:31:09.986265: val_loss -0.7478 +2024-11-21 16:31:09.986337: Pseudo dice [0.8283] +2024-11-21 16:31:09.986410: Epoch time: 19.05 s +2024-11-21 16:31:10.799369: +2024-11-21 16:31:10.799571: Epoch 1073 +2024-11-21 16:31:10.799683: Current learning rate: 0.00878 +2024-11-21 16:31:29.164410: train_loss -0.7632 +2024-11-21 16:31:29.164683: val_loss -0.7426 +2024-11-21 16:31:29.164760: Pseudo dice [0.8117] +2024-11-21 16:31:29.164839: Epoch time: 18.37 s +2024-11-21 16:31:29.985297: +2024-11-21 16:31:29.985502: Epoch 1074 +2024-11-21 16:31:29.985610: Current learning rate: 0.00878 +2024-11-21 16:31:48.738853: train_loss -0.7596 +2024-11-21 16:31:48.739100: val_loss -0.7443 +2024-11-21 16:31:48.739178: Pseudo dice [0.8195] +2024-11-21 16:31:48.739527: Epoch time: 18.75 s +2024-11-21 16:31:49.608359: +2024-11-21 16:31:49.608622: Epoch 1075 +2024-11-21 16:31:49.608735: Current learning rate: 0.00878 +2024-11-21 16:32:07.206158: train_loss -0.767 +2024-11-21 16:32:07.206366: val_loss -0.7464 +2024-11-21 16:32:07.206441: Pseudo dice [0.8272] +2024-11-21 16:32:07.206516: Epoch time: 17.6 s +2024-11-21 16:32:08.022898: +2024-11-21 16:32:08.023099: Epoch 1076 +2024-11-21 16:32:08.023212: Current learning rate: 0.00878 +2024-11-21 16:32:26.704412: train_loss -0.7654 +2024-11-21 16:32:26.704624: val_loss -0.7401 +2024-11-21 16:32:26.704697: Pseudo dice [0.8173] +2024-11-21 16:32:26.704772: Epoch time: 18.68 s +2024-11-21 16:32:27.520542: +2024-11-21 16:32:27.520757: Epoch 1077 +2024-11-21 16:32:27.520875: Current learning rate: 0.00878 +2024-11-21 16:32:45.643200: train_loss -0.7474 +2024-11-21 16:32:45.643492: val_loss -0.727 +2024-11-21 16:32:45.643571: Pseudo dice [0.8067] +2024-11-21 16:32:45.643653: Epoch time: 18.12 s +2024-11-21 16:32:46.846581: +2024-11-21 16:32:46.846894: Epoch 1078 +2024-11-21 16:32:46.847015: Current learning rate: 0.00878 +2024-11-21 16:33:05.517851: train_loss -0.7469 +2024-11-21 16:33:05.518152: val_loss -0.7359 +2024-11-21 16:33:05.518230: Pseudo dice [0.8174] +2024-11-21 16:33:05.518315: Epoch time: 18.67 s +2024-11-21 16:33:06.343238: +2024-11-21 16:33:06.343453: Epoch 1079 +2024-11-21 16:33:06.343563: Current learning rate: 0.00878 +2024-11-21 16:33:26.514395: train_loss -0.768 +2024-11-21 16:33:26.514669: val_loss -0.7448 +2024-11-21 16:33:26.514745: Pseudo dice [0.8155] +2024-11-21 16:33:26.514826: Epoch time: 20.17 s +2024-11-21 16:33:27.335535: +2024-11-21 16:33:27.335769: Epoch 1080 +2024-11-21 16:33:27.335885: Current learning rate: 0.00878 +2024-11-21 16:33:45.456191: train_loss -0.7672 +2024-11-21 16:33:45.456399: val_loss -0.729 +2024-11-21 16:33:45.468658: Pseudo dice [0.8085] +2024-11-21 16:33:45.468829: Epoch time: 18.12 s +2024-11-21 16:33:46.292415: +2024-11-21 16:33:46.292660: Epoch 1081 +2024-11-21 16:33:46.292777: Current learning rate: 0.00878 +2024-11-21 16:34:04.248177: train_loss -0.7597 +2024-11-21 16:34:04.248421: val_loss -0.7295 +2024-11-21 16:34:04.248500: Pseudo dice [0.8122] +2024-11-21 16:34:04.248587: Epoch time: 17.96 s +2024-11-21 16:34:05.072086: +2024-11-21 16:34:05.072384: Epoch 1082 +2024-11-21 16:34:05.072503: Current learning rate: 0.00877 +2024-11-21 16:34:24.134686: train_loss -0.7666 +2024-11-21 16:34:24.134907: val_loss -0.7344 +2024-11-21 16:34:24.134988: Pseudo dice [0.8396] +2024-11-21 16:34:24.135072: Epoch time: 19.06 s +2024-11-21 16:34:24.944912: +2024-11-21 16:34:24.945120: Epoch 1083 +2024-11-21 16:34:24.945239: Current learning rate: 0.00877 +2024-11-21 16:34:44.442219: train_loss -0.7612 +2024-11-21 16:34:44.442428: val_loss -0.7189 +2024-11-21 16:34:44.442501: Pseudo dice [0.8189] +2024-11-21 16:34:44.442578: Epoch time: 19.5 s +2024-11-21 16:34:45.259256: +2024-11-21 16:34:45.259479: Epoch 1084 +2024-11-21 16:34:45.259589: Current learning rate: 0.00877 +2024-11-21 16:35:04.209989: train_loss -0.7676 +2024-11-21 16:35:04.210203: val_loss -0.7396 +2024-11-21 16:35:04.210276: Pseudo dice [0.8327] +2024-11-21 16:35:04.210349: Epoch time: 18.95 s +2024-11-21 16:35:05.021325: +2024-11-21 16:35:05.021520: Epoch 1085 +2024-11-21 16:35:05.021634: Current learning rate: 0.00877 +2024-11-21 16:35:23.760203: train_loss -0.755 +2024-11-21 16:35:23.760442: val_loss -0.7058 +2024-11-21 16:35:23.760515: Pseudo dice [0.7888] +2024-11-21 16:35:23.760596: Epoch time: 18.74 s +2024-11-21 16:35:24.582748: +2024-11-21 16:35:24.582953: Epoch 1086 +2024-11-21 16:35:24.583071: Current learning rate: 0.00877 +2024-11-21 16:35:43.977600: train_loss -0.7661 +2024-11-21 16:35:43.977803: val_loss -0.7237 +2024-11-21 16:35:43.977882: Pseudo dice [0.8126] +2024-11-21 16:35:43.977959: Epoch time: 19.4 s +2024-11-21 16:35:44.787046: +2024-11-21 16:35:44.787238: Epoch 1087 +2024-11-21 16:35:44.787356: Current learning rate: 0.00877 +2024-11-21 16:36:02.726315: train_loss -0.753 +2024-11-21 16:36:02.730115: val_loss -0.7229 +2024-11-21 16:36:02.730225: Pseudo dice [0.7945] +2024-11-21 16:36:02.730304: Epoch time: 17.94 s +2024-11-21 16:36:03.646115: +2024-11-21 16:36:03.646305: Epoch 1088 +2024-11-21 16:36:03.646418: Current learning rate: 0.00877 +2024-11-21 16:36:23.015216: train_loss -0.7588 +2024-11-21 16:36:23.015424: val_loss -0.7028 +2024-11-21 16:36:23.015499: Pseudo dice [0.8109] +2024-11-21 16:36:23.015581: Epoch time: 19.37 s +2024-11-21 16:36:23.829768: +2024-11-21 16:36:23.829966: Epoch 1089 +2024-11-21 16:36:23.830085: Current learning rate: 0.00877 +2024-11-21 16:36:43.060869: train_loss -0.7696 +2024-11-21 16:36:43.061114: val_loss -0.7241 +2024-11-21 16:36:43.061190: Pseudo dice [0.8287] +2024-11-21 16:36:43.061270: Epoch time: 19.23 s +2024-11-21 16:36:44.281072: +2024-11-21 16:36:44.281284: Epoch 1090 +2024-11-21 16:36:44.281396: Current learning rate: 0.00876 +2024-11-21 16:37:02.462975: train_loss -0.7578 +2024-11-21 16:37:02.463195: val_loss -0.7448 +2024-11-21 16:37:02.465441: Pseudo dice [0.8354] +2024-11-21 16:37:02.465544: Epoch time: 18.18 s +2024-11-21 16:37:03.320154: +2024-11-21 16:37:03.320379: Epoch 1091 +2024-11-21 16:37:03.320494: Current learning rate: 0.00876 +2024-11-21 16:37:21.512294: train_loss -0.756 +2024-11-21 16:37:21.512502: val_loss -0.7348 +2024-11-21 16:37:21.512578: Pseudo dice [0.8323] +2024-11-21 16:37:21.512657: Epoch time: 18.19 s +2024-11-21 16:37:22.329666: +2024-11-21 16:37:22.329881: Epoch 1092 +2024-11-21 16:37:22.330000: Current learning rate: 0.00876 +2024-11-21 16:37:40.192472: train_loss -0.7626 +2024-11-21 16:37:40.192724: val_loss -0.7586 +2024-11-21 16:37:40.192800: Pseudo dice [0.8234] +2024-11-21 16:37:40.192881: Epoch time: 17.86 s +2024-11-21 16:37:41.008162: +2024-11-21 16:37:41.008376: Epoch 1093 +2024-11-21 16:37:41.008489: Current learning rate: 0.00876 +2024-11-21 16:38:00.414133: train_loss -0.769 +2024-11-21 16:38:00.414331: val_loss -0.7504 +2024-11-21 16:38:00.414405: Pseudo dice [0.8127] +2024-11-21 16:38:00.414480: Epoch time: 19.41 s +2024-11-21 16:38:01.250837: +2024-11-21 16:38:01.251043: Epoch 1094 +2024-11-21 16:38:01.251157: Current learning rate: 0.00876 +2024-11-21 16:38:20.851038: train_loss -0.7671 +2024-11-21 16:38:20.851247: val_loss -0.74 +2024-11-21 16:38:20.851324: Pseudo dice [0.8223] +2024-11-21 16:38:20.851403: Epoch time: 19.6 s +2024-11-21 16:38:21.667912: +2024-11-21 16:38:21.668166: Epoch 1095 +2024-11-21 16:38:21.668277: Current learning rate: 0.00876 +2024-11-21 16:38:40.709255: train_loss -0.7666 +2024-11-21 16:38:40.709497: val_loss -0.7291 +2024-11-21 16:38:40.709573: Pseudo dice [0.8177] +2024-11-21 16:38:40.709728: Epoch time: 19.04 s +2024-11-21 16:38:41.535142: +2024-11-21 16:38:41.535406: Epoch 1096 +2024-11-21 16:38:41.535519: Current learning rate: 0.00876 +2024-11-21 16:38:59.831333: train_loss -0.7723 +2024-11-21 16:38:59.831550: val_loss -0.7285 +2024-11-21 16:38:59.831625: Pseudo dice [0.8128] +2024-11-21 16:38:59.836877: Epoch time: 18.3 s +2024-11-21 16:39:00.988745: +2024-11-21 16:39:00.988947: Epoch 1097 +2024-11-21 16:39:00.989078: Current learning rate: 0.00876 +2024-11-21 16:39:19.149032: train_loss -0.7636 +2024-11-21 16:39:19.149243: val_loss -0.7572 +2024-11-21 16:39:19.149323: Pseudo dice [0.8218] +2024-11-21 16:39:19.149400: Epoch time: 18.16 s +2024-11-21 16:39:19.966328: +2024-11-21 16:39:19.966543: Epoch 1098 +2024-11-21 16:39:19.966657: Current learning rate: 0.00876 +2024-11-21 16:39:38.531303: train_loss -0.7761 +2024-11-21 16:39:38.531591: val_loss -0.7274 +2024-11-21 16:39:38.531672: Pseudo dice [0.8239] +2024-11-21 16:39:38.531749: Epoch time: 18.57 s +2024-11-21 16:39:39.380154: +2024-11-21 16:39:39.380395: Epoch 1099 +2024-11-21 16:39:39.380503: Current learning rate: 0.00875 +2024-11-21 16:39:58.187517: train_loss -0.7706 +2024-11-21 16:39:58.187758: val_loss -0.7456 +2024-11-21 16:39:58.187835: Pseudo dice [0.8115] +2024-11-21 16:39:58.187921: Epoch time: 18.81 s +2024-11-21 16:39:59.243642: +2024-11-21 16:39:59.243835: Epoch 1100 +2024-11-21 16:39:59.243952: Current learning rate: 0.00875 +2024-11-21 16:40:17.949661: train_loss -0.7743 +2024-11-21 16:40:17.949873: val_loss -0.7447 +2024-11-21 16:40:17.949948: Pseudo dice [0.8163] +2024-11-21 16:40:17.950149: Epoch time: 18.71 s +2024-11-21 16:40:18.773880: +2024-11-21 16:40:18.774108: Epoch 1101 +2024-11-21 16:40:18.774226: Current learning rate: 0.00875 +2024-11-21 16:40:37.045412: train_loss -0.7616 +2024-11-21 16:40:37.045635: val_loss -0.7437 +2024-11-21 16:40:37.045708: Pseudo dice [0.8187] +2024-11-21 16:40:37.045782: Epoch time: 18.27 s +2024-11-21 16:40:37.862367: +2024-11-21 16:40:37.862568: Epoch 1102 +2024-11-21 16:40:37.862681: Current learning rate: 0.00875 +2024-11-21 16:40:56.208714: train_loss -0.7704 +2024-11-21 16:40:56.209030: val_loss -0.7205 +2024-11-21 16:40:56.209111: Pseudo dice [0.8275] +2024-11-21 16:40:56.209198: Epoch time: 18.35 s +2024-11-21 16:40:57.031458: +2024-11-21 16:40:57.031672: Epoch 1103 +2024-11-21 16:40:57.031783: Current learning rate: 0.00875 +2024-11-21 16:41:16.223553: train_loss -0.7719 +2024-11-21 16:41:16.228938: val_loss -0.7594 +2024-11-21 16:41:16.229069: Pseudo dice [0.8225] +2024-11-21 16:41:16.229147: Epoch time: 19.19 s +2024-11-21 16:41:17.142710: +2024-11-21 16:41:17.143007: Epoch 1104 +2024-11-21 16:41:17.143119: Current learning rate: 0.00875 +2024-11-21 16:41:35.024142: train_loss -0.7731 +2024-11-21 16:41:35.024352: val_loss -0.7471 +2024-11-21 16:41:35.024425: Pseudo dice [0.8299] +2024-11-21 16:41:35.024523: Epoch time: 17.88 s +2024-11-21 16:41:35.839123: +2024-11-21 16:41:35.839382: Epoch 1105 +2024-11-21 16:41:35.839499: Current learning rate: 0.00875 +2024-11-21 16:41:55.223135: train_loss -0.7739 +2024-11-21 16:41:55.226794: val_loss -0.709 +2024-11-21 16:41:55.226923: Pseudo dice [0.8032] +2024-11-21 16:41:55.227020: Epoch time: 19.38 s +2024-11-21 16:41:56.052474: +2024-11-21 16:41:56.052686: Epoch 1106 +2024-11-21 16:41:56.052804: Current learning rate: 0.00875 +2024-11-21 16:42:14.577783: train_loss -0.7322 +2024-11-21 16:42:14.578041: val_loss -0.7268 +2024-11-21 16:42:14.578120: Pseudo dice [0.8166] +2024-11-21 16:42:14.578197: Epoch time: 18.53 s +2024-11-21 16:42:15.416183: +2024-11-21 16:42:15.416384: Epoch 1107 +2024-11-21 16:42:15.416496: Current learning rate: 0.00875 +2024-11-21 16:42:34.470093: train_loss -0.7578 +2024-11-21 16:42:34.470305: val_loss -0.75 +2024-11-21 16:42:34.470379: Pseudo dice [0.8158] +2024-11-21 16:42:34.470459: Epoch time: 19.05 s +2024-11-21 16:42:35.331771: +2024-11-21 16:42:35.331966: Epoch 1108 +2024-11-21 16:42:35.332079: Current learning rate: 0.00874 +2024-11-21 16:42:54.836216: train_loss -0.7645 +2024-11-21 16:42:54.836437: val_loss -0.7534 +2024-11-21 16:42:54.836514: Pseudo dice [0.8275] +2024-11-21 16:42:54.836636: Epoch time: 19.51 s +2024-11-21 16:42:55.773123: +2024-11-21 16:42:55.773327: Epoch 1109 +2024-11-21 16:42:55.773439: Current learning rate: 0.00874 +2024-11-21 16:43:15.330041: train_loss -0.7623 +2024-11-21 16:43:15.330263: val_loss -0.7049 +2024-11-21 16:43:15.332518: Pseudo dice [0.8028] +2024-11-21 16:43:15.332636: Epoch time: 19.56 s +2024-11-21 16:43:16.205989: +2024-11-21 16:43:16.206204: Epoch 1110 +2024-11-21 16:43:16.206316: Current learning rate: 0.00874 +2024-11-21 16:43:35.356876: train_loss -0.74 +2024-11-21 16:43:35.357106: val_loss -0.7234 +2024-11-21 16:43:35.357181: Pseudo dice [0.7678] +2024-11-21 16:43:35.357264: Epoch time: 19.15 s +2024-11-21 16:43:36.178758: +2024-11-21 16:43:36.179008: Epoch 1111 +2024-11-21 16:43:36.179128: Current learning rate: 0.00874 +2024-11-21 16:43:55.054116: train_loss -0.749 +2024-11-21 16:43:55.054329: val_loss -0.7044 +2024-11-21 16:43:55.054402: Pseudo dice [0.8279] +2024-11-21 16:43:55.054477: Epoch time: 18.88 s +2024-11-21 16:43:55.874378: +2024-11-21 16:43:55.874636: Epoch 1112 +2024-11-21 16:43:55.874748: Current learning rate: 0.00874 +2024-11-21 16:44:15.289968: train_loss -0.7535 +2024-11-21 16:44:15.290187: val_loss -0.7358 +2024-11-21 16:44:15.290261: Pseudo dice [0.8329] +2024-11-21 16:44:15.290337: Epoch time: 19.42 s +2024-11-21 16:44:16.465336: +2024-11-21 16:44:16.465574: Epoch 1113 +2024-11-21 16:44:16.465690: Current learning rate: 0.00874 +2024-11-21 16:44:35.666926: train_loss -0.7237 +2024-11-21 16:44:35.667176: val_loss -0.742 +2024-11-21 16:44:35.667249: Pseudo dice [0.8156] +2024-11-21 16:44:35.667328: Epoch time: 19.2 s +2024-11-21 16:44:36.487766: +2024-11-21 16:44:36.487968: Epoch 1114 +2024-11-21 16:44:36.488089: Current learning rate: 0.00874 +2024-11-21 16:44:54.643725: train_loss -0.7499 +2024-11-21 16:44:54.643938: val_loss -0.7206 +2024-11-21 16:44:54.644020: Pseudo dice [0.8092] +2024-11-21 16:44:54.644095: Epoch time: 18.16 s +2024-11-21 16:44:55.558105: +2024-11-21 16:44:55.558325: Epoch 1115 +2024-11-21 16:44:55.558439: Current learning rate: 0.00874 +2024-11-21 16:45:14.855046: train_loss -0.7408 +2024-11-21 16:45:14.855343: val_loss -0.7261 +2024-11-21 16:45:14.855422: Pseudo dice [0.8129] +2024-11-21 16:45:14.855497: Epoch time: 19.3 s +2024-11-21 16:45:15.773862: +2024-11-21 16:45:15.774095: Epoch 1116 +2024-11-21 16:45:15.774213: Current learning rate: 0.00874 +2024-11-21 16:45:35.353034: train_loss -0.7292 +2024-11-21 16:45:35.353318: val_loss -0.7251 +2024-11-21 16:45:35.353395: Pseudo dice [0.7987] +2024-11-21 16:45:35.353475: Epoch time: 19.58 s +2024-11-21 16:45:36.178822: +2024-11-21 16:45:36.179046: Epoch 1117 +2024-11-21 16:45:36.179162: Current learning rate: 0.00873 +2024-11-21 16:45:54.352571: train_loss -0.7461 +2024-11-21 16:45:54.352805: val_loss -0.7357 +2024-11-21 16:45:54.352879: Pseudo dice [0.8229] +2024-11-21 16:45:54.352956: Epoch time: 18.17 s +2024-11-21 16:45:55.170298: +2024-11-21 16:45:55.170540: Epoch 1118 +2024-11-21 16:45:55.170650: Current learning rate: 0.00873 +2024-11-21 16:46:13.896633: train_loss -0.7304 +2024-11-21 16:46:13.896842: val_loss -0.7334 +2024-11-21 16:46:13.896914: Pseudo dice [0.8132] +2024-11-21 16:46:13.896989: Epoch time: 18.73 s +2024-11-21 16:46:14.726317: +2024-11-21 16:46:14.726540: Epoch 1119 +2024-11-21 16:46:14.726659: Current learning rate: 0.00873 +2024-11-21 16:46:33.165139: train_loss -0.7515 +2024-11-21 16:46:33.165361: val_loss -0.7199 +2024-11-21 16:46:33.165433: Pseudo dice [0.808] +2024-11-21 16:46:33.165506: Epoch time: 18.44 s +2024-11-21 16:46:33.986590: +2024-11-21 16:46:33.986791: Epoch 1120 +2024-11-21 16:46:33.986897: Current learning rate: 0.00873 +2024-11-21 16:46:51.691030: train_loss -0.7616 +2024-11-21 16:46:51.691265: val_loss -0.7421 +2024-11-21 16:46:51.691338: Pseudo dice [0.8318] +2024-11-21 16:46:51.691420: Epoch time: 17.71 s +2024-11-21 16:46:52.520094: +2024-11-21 16:46:52.520279: Epoch 1121 +2024-11-21 16:46:52.520385: Current learning rate: 0.00873 +2024-11-21 16:47:10.124646: train_loss -0.7569 +2024-11-21 16:47:10.124864: val_loss -0.7383 +2024-11-21 16:47:10.125008: Pseudo dice [0.8106] +2024-11-21 16:47:10.125089: Epoch time: 17.61 s +2024-11-21 16:47:10.943720: +2024-11-21 16:47:10.944039: Epoch 1122 +2024-11-21 16:47:10.944155: Current learning rate: 0.00873 +2024-11-21 16:47:29.980219: train_loss -0.7662 +2024-11-21 16:47:29.980437: val_loss -0.727 +2024-11-21 16:47:29.980509: Pseudo dice [0.8048] +2024-11-21 16:47:29.980585: Epoch time: 19.04 s +2024-11-21 16:47:30.800688: +2024-11-21 16:47:30.800910: Epoch 1123 +2024-11-21 16:47:30.801025: Current learning rate: 0.00873 +2024-11-21 16:47:49.220629: train_loss -0.7585 +2024-11-21 16:47:49.220838: val_loss -0.7231 +2024-11-21 16:47:49.220911: Pseudo dice [0.8176] +2024-11-21 16:47:49.220987: Epoch time: 18.42 s +2024-11-21 16:47:50.054970: +2024-11-21 16:47:50.055195: Epoch 1124 +2024-11-21 16:47:50.055308: Current learning rate: 0.00873 +2024-11-21 16:48:10.446982: train_loss -0.7625 +2024-11-21 16:48:10.447223: val_loss -0.7499 +2024-11-21 16:48:10.447297: Pseudo dice [0.8327] +2024-11-21 16:48:10.447381: Epoch time: 20.39 s +2024-11-21 16:48:11.680233: +2024-11-21 16:48:11.680458: Epoch 1125 +2024-11-21 16:48:11.680571: Current learning rate: 0.00872 +2024-11-21 16:48:30.755699: train_loss -0.7681 +2024-11-21 16:48:30.755913: val_loss -0.729 +2024-11-21 16:48:30.755985: Pseudo dice [0.819] +2024-11-21 16:48:30.756066: Epoch time: 19.08 s +2024-11-21 16:48:31.571726: +2024-11-21 16:48:31.571928: Epoch 1126 +2024-11-21 16:48:31.572048: Current learning rate: 0.00872 +2024-11-21 16:48:50.358093: train_loss -0.7674 +2024-11-21 16:48:50.358315: val_loss -0.7358 +2024-11-21 16:48:50.359828: Pseudo dice [0.8342] +2024-11-21 16:48:50.359964: Epoch time: 18.79 s +2024-11-21 16:48:51.329569: +2024-11-21 16:48:51.329822: Epoch 1127 +2024-11-21 16:48:51.329936: Current learning rate: 0.00872 +2024-11-21 16:49:09.493396: train_loss -0.7633 +2024-11-21 16:49:09.493641: val_loss -0.7467 +2024-11-21 16:49:09.493797: Pseudo dice [0.8369] +2024-11-21 16:49:09.493881: Epoch time: 18.16 s +2024-11-21 16:49:10.313997: +2024-11-21 16:49:10.314212: Epoch 1128 +2024-11-21 16:49:10.314327: Current learning rate: 0.00872 +2024-11-21 16:49:29.481143: train_loss -0.7701 +2024-11-21 16:49:29.486530: val_loss -0.7236 +2024-11-21 16:49:29.486690: Pseudo dice [0.8268] +2024-11-21 16:49:29.486771: Epoch time: 19.17 s +2024-11-21 16:49:30.570664: +2024-11-21 16:49:30.570879: Epoch 1129 +2024-11-21 16:49:30.571003: Current learning rate: 0.00872 +2024-11-21 16:49:49.409620: train_loss -0.7678 +2024-11-21 16:49:49.409883: val_loss -0.7366 +2024-11-21 16:49:49.409958: Pseudo dice [0.8226] +2024-11-21 16:49:49.410042: Epoch time: 18.84 s +2024-11-21 16:49:50.225474: +2024-11-21 16:49:50.225668: Epoch 1130 +2024-11-21 16:49:50.225785: Current learning rate: 0.00872 +2024-11-21 16:50:08.598665: train_loss -0.7629 +2024-11-21 16:50:08.598879: val_loss -0.755 +2024-11-21 16:50:08.598953: Pseudo dice [0.8101] +2024-11-21 16:50:08.599035: Epoch time: 18.37 s +2024-11-21 16:50:09.424256: +2024-11-21 16:50:09.424482: Epoch 1131 +2024-11-21 16:50:09.424602: Current learning rate: 0.00872 +2024-11-21 16:50:28.719695: train_loss -0.7601 +2024-11-21 16:50:28.719934: val_loss -0.7214 +2024-11-21 16:50:28.720015: Pseudo dice [0.8116] +2024-11-21 16:50:28.720097: Epoch time: 19.3 s +2024-11-21 16:50:29.549463: +2024-11-21 16:50:29.549660: Epoch 1132 +2024-11-21 16:50:29.549780: Current learning rate: 0.00872 +2024-11-21 16:50:48.649604: train_loss -0.7603 +2024-11-21 16:50:48.649823: val_loss -0.753 +2024-11-21 16:50:48.649899: Pseudo dice [0.8261] +2024-11-21 16:50:48.649983: Epoch time: 19.1 s +2024-11-21 16:50:49.487726: +2024-11-21 16:50:49.487925: Epoch 1133 +2024-11-21 16:50:49.488042: Current learning rate: 0.00872 +2024-11-21 16:51:07.961853: train_loss -0.7604 +2024-11-21 16:51:07.962078: val_loss -0.7248 +2024-11-21 16:51:07.962153: Pseudo dice [0.824] +2024-11-21 16:51:07.962230: Epoch time: 18.47 s +2024-11-21 16:51:08.884830: +2024-11-21 16:51:08.885053: Epoch 1134 +2024-11-21 16:51:08.885170: Current learning rate: 0.00871 +2024-11-21 16:51:27.720462: train_loss -0.7669 +2024-11-21 16:51:27.720694: val_loss -0.7518 +2024-11-21 16:51:27.720789: Pseudo dice [0.809] +2024-11-21 16:51:27.720886: Epoch time: 18.84 s +2024-11-21 16:51:28.539828: +2024-11-21 16:51:28.540025: Epoch 1135 +2024-11-21 16:51:28.540142: Current learning rate: 0.00871 +2024-11-21 16:51:46.968126: train_loss -0.767 +2024-11-21 16:51:46.968341: val_loss -0.7629 +2024-11-21 16:51:46.968416: Pseudo dice [0.8328] +2024-11-21 16:51:46.968493: Epoch time: 18.43 s +2024-11-21 16:51:47.915456: +2024-11-21 16:51:47.915689: Epoch 1136 +2024-11-21 16:51:47.915804: Current learning rate: 0.00871 +2024-11-21 16:52:06.177783: train_loss -0.7692 +2024-11-21 16:52:06.178000: val_loss -0.7571 +2024-11-21 16:52:06.178077: Pseudo dice [0.8454] +2024-11-21 16:52:06.178155: Epoch time: 18.26 s +2024-11-21 16:52:07.399419: +2024-11-21 16:52:07.399633: Epoch 1137 +2024-11-21 16:52:07.399745: Current learning rate: 0.00871 +2024-11-21 16:52:26.984651: train_loss -0.7675 +2024-11-21 16:52:26.984902: val_loss -0.7225 +2024-11-21 16:52:26.984977: Pseudo dice [0.8266] +2024-11-21 16:52:26.985101: Epoch time: 19.59 s +2024-11-21 16:52:27.818616: +2024-11-21 16:52:27.818899: Epoch 1138 +2024-11-21 16:52:27.819021: Current learning rate: 0.00871 +2024-11-21 16:52:46.596261: train_loss -0.7599 +2024-11-21 16:52:46.596468: val_loss -0.7393 +2024-11-21 16:52:46.596544: Pseudo dice [0.7659] +2024-11-21 16:52:46.596636: Epoch time: 18.78 s +2024-11-21 16:52:47.415676: +2024-11-21 16:52:47.415894: Epoch 1139 +2024-11-21 16:52:47.416013: Current learning rate: 0.00871 +2024-11-21 16:53:06.919575: train_loss -0.7602 +2024-11-21 16:53:06.921726: val_loss -0.7496 +2024-11-21 16:53:06.921893: Pseudo dice [0.8328] +2024-11-21 16:53:06.921972: Epoch time: 19.5 s +2024-11-21 16:53:07.746513: +2024-11-21 16:53:07.746705: Epoch 1140 +2024-11-21 16:53:07.746814: Current learning rate: 0.00871 +2024-11-21 16:53:26.839883: train_loss -0.7525 +2024-11-21 16:53:26.840110: val_loss -0.7048 +2024-11-21 16:53:26.840186: Pseudo dice [0.8202] +2024-11-21 16:53:26.840266: Epoch time: 19.09 s +2024-11-21 16:53:27.663455: +2024-11-21 16:53:27.663813: Epoch 1141 +2024-11-21 16:53:27.663930: Current learning rate: 0.00871 +2024-11-21 16:53:45.370706: train_loss -0.7644 +2024-11-21 16:53:45.370939: val_loss -0.7294 +2024-11-21 16:53:45.371023: Pseudo dice [0.8062] +2024-11-21 16:53:45.371098: Epoch time: 17.71 s +2024-11-21 16:53:46.196629: +2024-11-21 16:53:46.196835: Epoch 1142 +2024-11-21 16:53:46.196946: Current learning rate: 0.00871 +2024-11-21 16:54:05.679015: train_loss -0.7712 +2024-11-21 16:54:05.679229: val_loss -0.7518 +2024-11-21 16:54:05.679300: Pseudo dice [0.8406] +2024-11-21 16:54:05.679374: Epoch time: 19.48 s +2024-11-21 16:54:06.626882: +2024-11-21 16:54:06.627156: Epoch 1143 +2024-11-21 16:54:06.627272: Current learning rate: 0.0087 +2024-11-21 16:54:26.365880: train_loss -0.7698 +2024-11-21 16:54:26.366100: val_loss -0.7689 +2024-11-21 16:54:26.366171: Pseudo dice [0.8202] +2024-11-21 16:54:26.366245: Epoch time: 19.74 s +2024-11-21 16:54:27.192833: +2024-11-21 16:54:27.193030: Epoch 1144 +2024-11-21 16:54:27.193770: Current learning rate: 0.0087 +2024-11-21 16:54:45.598232: train_loss -0.7696 +2024-11-21 16:54:45.598478: val_loss -0.7469 +2024-11-21 16:54:45.598555: Pseudo dice [0.8285] +2024-11-21 16:54:45.598639: Epoch time: 18.41 s +2024-11-21 16:54:46.424080: +2024-11-21 16:54:46.424266: Epoch 1145 +2024-11-21 16:54:46.424379: Current learning rate: 0.0087 +2024-11-21 16:55:05.802069: train_loss -0.7685 +2024-11-21 16:55:05.802282: val_loss -0.7236 +2024-11-21 16:55:05.802378: Pseudo dice [0.7995] +2024-11-21 16:55:05.802456: Epoch time: 19.38 s +2024-11-21 16:55:06.716257: +2024-11-21 16:55:06.716454: Epoch 1146 +2024-11-21 16:55:06.716570: Current learning rate: 0.0087 +2024-11-21 16:55:24.626933: train_loss -0.7708 +2024-11-21 16:55:24.627159: val_loss -0.7684 +2024-11-21 16:55:24.627233: Pseudo dice [0.8353] +2024-11-21 16:55:24.627310: Epoch time: 17.91 s +2024-11-21 16:55:25.521396: +2024-11-21 16:55:25.521608: Epoch 1147 +2024-11-21 16:55:25.521725: Current learning rate: 0.0087 +2024-11-21 16:55:44.712294: train_loss -0.7682 +2024-11-21 16:55:44.717641: val_loss -0.7407 +2024-11-21 16:55:44.717790: Pseudo dice [0.8193] +2024-11-21 16:55:44.717874: Epoch time: 19.19 s +2024-11-21 16:55:45.615586: +2024-11-21 16:55:45.615772: Epoch 1148 +2024-11-21 16:55:45.615885: Current learning rate: 0.0087 +2024-11-21 16:56:04.095410: train_loss -0.7629 +2024-11-21 16:56:04.096864: val_loss -0.7398 +2024-11-21 16:56:04.096979: Pseudo dice [0.8328] +2024-11-21 16:56:04.097073: Epoch time: 18.48 s +2024-11-21 16:56:04.926580: +2024-11-21 16:56:04.926780: Epoch 1149 +2024-11-21 16:56:04.926891: Current learning rate: 0.0087 +2024-11-21 16:56:24.016549: train_loss -0.7638 +2024-11-21 16:56:24.016755: val_loss -0.738 +2024-11-21 16:56:24.016834: Pseudo dice [0.8272] +2024-11-21 16:56:24.016909: Epoch time: 19.09 s +2024-11-21 16:56:25.105810: +2024-11-21 16:56:25.106042: Epoch 1150 +2024-11-21 16:56:25.106153: Current learning rate: 0.0087 +2024-11-21 16:56:44.357790: train_loss -0.7592 +2024-11-21 16:56:44.358033: val_loss -0.7391 +2024-11-21 16:56:44.358110: Pseudo dice [0.7981] +2024-11-21 16:56:44.358186: Epoch time: 19.25 s +2024-11-21 16:56:45.256955: +2024-11-21 16:56:45.257206: Epoch 1151 +2024-11-21 16:56:45.257322: Current learning rate: 0.0087 +2024-11-21 16:57:04.209843: train_loss -0.7546 +2024-11-21 16:57:04.210087: val_loss -0.7492 +2024-11-21 16:57:04.210162: Pseudo dice [0.8136] +2024-11-21 16:57:04.210245: Epoch time: 18.95 s +2024-11-21 16:57:05.036015: +2024-11-21 16:57:05.036244: Epoch 1152 +2024-11-21 16:57:05.036364: Current learning rate: 0.00869 +2024-11-21 16:57:23.979031: train_loss -0.7556 +2024-11-21 16:57:23.979237: val_loss -0.7552 +2024-11-21 16:57:23.979453: Pseudo dice [0.8403] +2024-11-21 16:57:23.979542: Epoch time: 18.94 s +2024-11-21 16:57:24.880771: +2024-11-21 16:57:24.881011: Epoch 1153 +2024-11-21 16:57:24.881120: Current learning rate: 0.00869 +2024-11-21 16:57:43.618983: train_loss -0.7597 +2024-11-21 16:57:43.624417: val_loss -0.7418 +2024-11-21 16:57:43.624558: Pseudo dice [0.8205] +2024-11-21 16:57:43.624656: Epoch time: 18.74 s +2024-11-21 16:57:44.470838: +2024-11-21 16:57:44.471045: Epoch 1154 +2024-11-21 16:57:44.471159: Current learning rate: 0.00869 +2024-11-21 16:58:02.851988: train_loss -0.7557 +2024-11-21 16:58:02.852212: val_loss -0.7317 +2024-11-21 16:58:02.852284: Pseudo dice [0.795] +2024-11-21 16:58:02.852364: Epoch time: 18.38 s +2024-11-21 16:58:03.868930: +2024-11-21 16:58:03.869230: Epoch 1155 +2024-11-21 16:58:03.869349: Current learning rate: 0.00869 +2024-11-21 16:58:21.265845: train_loss -0.76 +2024-11-21 16:58:21.266085: val_loss -0.7162 +2024-11-21 16:58:21.266160: Pseudo dice [0.8285] +2024-11-21 16:58:21.266245: Epoch time: 17.4 s +2024-11-21 16:58:22.092337: +2024-11-21 16:58:22.092537: Epoch 1156 +2024-11-21 16:58:22.092649: Current learning rate: 0.00869 +2024-11-21 16:58:41.489072: train_loss -0.767 +2024-11-21 16:58:41.489282: val_loss -0.75 +2024-11-21 16:58:41.489414: Pseudo dice [0.8219] +2024-11-21 16:58:41.489496: Epoch time: 19.4 s +2024-11-21 16:58:42.332093: +2024-11-21 16:58:42.332299: Epoch 1157 +2024-11-21 16:58:42.332413: Current learning rate: 0.00869 +2024-11-21 16:59:00.061612: train_loss -0.775 +2024-11-21 16:59:00.061816: val_loss -0.759 +2024-11-21 16:59:00.061889: Pseudo dice [0.8237] +2024-11-21 16:59:00.061963: Epoch time: 17.73 s +2024-11-21 16:59:00.886594: +2024-11-21 16:59:00.886792: Epoch 1158 +2024-11-21 16:59:00.886904: Current learning rate: 0.00869 +2024-11-21 16:59:18.640736: train_loss -0.7573 +2024-11-21 16:59:18.640946: val_loss -0.7351 +2024-11-21 16:59:18.641030: Pseudo dice [0.8048] +2024-11-21 16:59:18.641108: Epoch time: 17.75 s +2024-11-21 16:59:19.468565: +2024-11-21 16:59:19.468748: Epoch 1159 +2024-11-21 16:59:19.468862: Current learning rate: 0.00869 +2024-11-21 16:59:39.418536: train_loss -0.7521 +2024-11-21 16:59:39.418756: val_loss -0.7204 +2024-11-21 16:59:39.418830: Pseudo dice [0.8162] +2024-11-21 16:59:39.418906: Epoch time: 19.95 s +2024-11-21 16:59:40.262025: +2024-11-21 16:59:40.262240: Epoch 1160 +2024-11-21 16:59:40.262355: Current learning rate: 0.00868 +2024-11-21 16:59:58.775784: train_loss -0.7525 +2024-11-21 16:59:58.775999: val_loss -0.742 +2024-11-21 16:59:58.776072: Pseudo dice [0.8289] +2024-11-21 16:59:58.776148: Epoch time: 18.51 s +2024-11-21 16:59:59.606728: +2024-11-21 16:59:59.606954: Epoch 1161 +2024-11-21 16:59:59.607074: Current learning rate: 0.00868 +2024-11-21 17:00:18.146429: train_loss -0.7288 +2024-11-21 17:00:18.146643: val_loss -0.6884 +2024-11-21 17:00:18.146720: Pseudo dice [0.7695] +2024-11-21 17:00:18.146799: Epoch time: 18.54 s +2024-11-21 17:00:18.980185: +2024-11-21 17:00:18.980418: Epoch 1162 +2024-11-21 17:00:18.980534: Current learning rate: 0.00868 +2024-11-21 17:00:36.674068: train_loss -0.7291 +2024-11-21 17:00:36.674288: val_loss -0.7277 +2024-11-21 17:00:36.674361: Pseudo dice [0.7899] +2024-11-21 17:00:36.674441: Epoch time: 17.69 s +2024-11-21 17:00:37.490621: +2024-11-21 17:00:37.490829: Epoch 1163 +2024-11-21 17:00:37.490938: Current learning rate: 0.00868 +2024-11-21 17:00:56.705828: train_loss -0.7491 +2024-11-21 17:00:56.708226: val_loss -0.7099 +2024-11-21 17:00:56.708310: Pseudo dice [0.8033] +2024-11-21 17:00:56.708386: Epoch time: 19.22 s +2024-11-21 17:00:57.688825: +2024-11-21 17:00:57.689026: Epoch 1164 +2024-11-21 17:00:57.689154: Current learning rate: 0.00868 +2024-11-21 17:01:17.139521: train_loss -0.745 +2024-11-21 17:01:17.139729: val_loss -0.7097 +2024-11-21 17:01:17.139802: Pseudo dice [0.7743] +2024-11-21 17:01:17.139877: Epoch time: 19.45 s +2024-11-21 17:01:17.963167: +2024-11-21 17:01:17.963362: Epoch 1165 +2024-11-21 17:01:17.963475: Current learning rate: 0.00868 +2024-11-21 17:01:36.095645: train_loss -0.7574 +2024-11-21 17:01:36.095907: val_loss -0.7279 +2024-11-21 17:01:36.095983: Pseudo dice [0.8103] +2024-11-21 17:01:36.096078: Epoch time: 18.13 s +2024-11-21 17:01:36.970471: +2024-11-21 17:01:36.970661: Epoch 1166 +2024-11-21 17:01:36.970773: Current learning rate: 0.00868 +2024-11-21 17:01:54.732356: train_loss -0.7608 +2024-11-21 17:01:54.732567: val_loss -0.743 +2024-11-21 17:01:54.732641: Pseudo dice [0.8137] +2024-11-21 17:01:54.732718: Epoch time: 17.76 s +2024-11-21 17:01:55.575022: +2024-11-21 17:01:55.575213: Epoch 1167 +2024-11-21 17:01:55.575326: Current learning rate: 0.00868 +2024-11-21 17:02:12.884865: train_loss -0.7705 +2024-11-21 17:02:12.885106: val_loss -0.7599 +2024-11-21 17:02:12.885184: Pseudo dice [0.8434] +2024-11-21 17:02:12.885262: Epoch time: 17.31 s +2024-11-21 17:02:13.713425: +2024-11-21 17:02:13.713614: Epoch 1168 +2024-11-21 17:02:13.713723: Current learning rate: 0.00868 +2024-11-21 17:02:33.424048: train_loss -0.7699 +2024-11-21 17:02:33.426428: val_loss -0.731 +2024-11-21 17:02:33.426539: Pseudo dice [0.8153] +2024-11-21 17:02:33.426621: Epoch time: 19.71 s +2024-11-21 17:02:34.279807: +2024-11-21 17:02:34.280013: Epoch 1169 +2024-11-21 17:02:34.280124: Current learning rate: 0.00867 +2024-11-21 17:02:53.316271: train_loss -0.7519 +2024-11-21 17:02:53.316556: val_loss -0.7442 +2024-11-21 17:02:53.317197: Pseudo dice [0.8116] +2024-11-21 17:02:53.317332: Epoch time: 19.04 s +2024-11-21 17:02:54.143331: +2024-11-21 17:02:54.143679: Epoch 1170 +2024-11-21 17:02:54.143794: Current learning rate: 0.00867 +2024-11-21 17:03:12.983832: train_loss -0.7771 +2024-11-21 17:03:12.984055: val_loss -0.7293 +2024-11-21 17:03:12.984130: Pseudo dice [0.8286] +2024-11-21 17:03:12.984208: Epoch time: 18.84 s +2024-11-21 17:03:14.339748: +2024-11-21 17:03:14.339971: Epoch 1171 +2024-11-21 17:03:14.340087: Current learning rate: 0.00867 +2024-11-21 17:03:33.579006: train_loss -0.7746 +2024-11-21 17:03:33.579232: val_loss -0.7605 +2024-11-21 17:03:33.579305: Pseudo dice [0.8423] +2024-11-21 17:03:33.579381: Epoch time: 19.24 s +2024-11-21 17:03:34.401840: +2024-11-21 17:03:34.402085: Epoch 1172 +2024-11-21 17:03:34.402197: Current learning rate: 0.00867 +2024-11-21 17:03:53.492705: train_loss -0.7617 +2024-11-21 17:03:53.492950: val_loss -0.7208 +2024-11-21 17:03:53.493036: Pseudo dice [0.8137] +2024-11-21 17:03:53.493122: Epoch time: 19.09 s +2024-11-21 17:03:54.323814: +2024-11-21 17:03:54.324145: Epoch 1173 +2024-11-21 17:03:54.324255: Current learning rate: 0.00867 +2024-11-21 17:04:13.821166: train_loss -0.7436 +2024-11-21 17:04:13.821382: val_loss -0.7176 +2024-11-21 17:04:13.821456: Pseudo dice [0.803] +2024-11-21 17:04:13.821534: Epoch time: 19.5 s +2024-11-21 17:04:14.847329: +2024-11-21 17:04:14.847577: Epoch 1174 +2024-11-21 17:04:14.847698: Current learning rate: 0.00867 +2024-11-21 17:04:32.870365: train_loss -0.7608 +2024-11-21 17:04:32.872724: val_loss -0.7442 +2024-11-21 17:04:32.872878: Pseudo dice [0.8317] +2024-11-21 17:04:32.872954: Epoch time: 18.02 s +2024-11-21 17:04:33.728964: +2024-11-21 17:04:33.729183: Epoch 1175 +2024-11-21 17:04:33.729293: Current learning rate: 0.00867 +2024-11-21 17:04:52.308114: train_loss -0.7728 +2024-11-21 17:04:52.308356: val_loss -0.706 +2024-11-21 17:04:52.308434: Pseudo dice [0.7907] +2024-11-21 17:04:52.308524: Epoch time: 18.58 s +2024-11-21 17:04:53.137902: +2024-11-21 17:04:53.138156: Epoch 1176 +2024-11-21 17:04:53.138269: Current learning rate: 0.00867 +2024-11-21 17:05:11.575334: train_loss -0.7642 +2024-11-21 17:05:11.575595: val_loss -0.7524 +2024-11-21 17:05:11.575679: Pseudo dice [0.8273] +2024-11-21 17:05:11.575776: Epoch time: 18.44 s +2024-11-21 17:05:12.406313: +2024-11-21 17:05:12.406533: Epoch 1177 +2024-11-21 17:05:12.406647: Current learning rate: 0.00867 +2024-11-21 17:05:30.698672: train_loss -0.7699 +2024-11-21 17:05:30.700666: val_loss -0.767 +2024-11-21 17:05:30.700755: Pseudo dice [0.8295] +2024-11-21 17:05:30.700836: Epoch time: 18.29 s +2024-11-21 17:05:31.574224: +2024-11-21 17:05:31.574424: Epoch 1178 +2024-11-21 17:05:31.574547: Current learning rate: 0.00866 +2024-11-21 17:05:49.459881: train_loss -0.7726 +2024-11-21 17:05:49.460530: val_loss -0.7652 +2024-11-21 17:05:49.460617: Pseudo dice [0.8206] +2024-11-21 17:05:49.460693: Epoch time: 17.89 s +2024-11-21 17:05:50.286281: +2024-11-21 17:05:50.286491: Epoch 1179 +2024-11-21 17:05:50.286599: Current learning rate: 0.00866 +2024-11-21 17:06:07.828563: train_loss -0.7729 +2024-11-21 17:06:07.828781: val_loss -0.7708 +2024-11-21 17:06:07.828864: Pseudo dice [0.8423] +2024-11-21 17:06:07.828946: Epoch time: 17.54 s +2024-11-21 17:06:08.667328: +2024-11-21 17:06:08.667547: Epoch 1180 +2024-11-21 17:06:08.667659: Current learning rate: 0.00866 +2024-11-21 17:06:26.979145: train_loss -0.7656 +2024-11-21 17:06:26.979357: val_loss -0.7422 +2024-11-21 17:06:26.979431: Pseudo dice [0.8164] +2024-11-21 17:06:26.979509: Epoch time: 18.31 s +2024-11-21 17:06:27.803852: +2024-11-21 17:06:27.804052: Epoch 1181 +2024-11-21 17:06:27.804169: Current learning rate: 0.00866 +2024-11-21 17:06:46.319164: train_loss -0.7727 +2024-11-21 17:06:46.319376: val_loss -0.7362 +2024-11-21 17:06:46.319450: Pseudo dice [0.8276] +2024-11-21 17:06:46.319525: Epoch time: 18.52 s +2024-11-21 17:06:47.276867: +2024-11-21 17:06:47.277073: Epoch 1182 +2024-11-21 17:06:47.277189: Current learning rate: 0.00866 +2024-11-21 17:07:05.853876: train_loss -0.7744 +2024-11-21 17:07:05.854107: val_loss -0.713 +2024-11-21 17:07:05.854182: Pseudo dice [0.8351] +2024-11-21 17:07:05.854259: Epoch time: 18.58 s +2024-11-21 17:07:06.695167: +2024-11-21 17:07:06.695436: Epoch 1183 +2024-11-21 17:07:06.695590: Current learning rate: 0.00866 +2024-11-21 17:07:25.989472: train_loss -0.7587 +2024-11-21 17:07:25.994893: val_loss -0.7353 +2024-11-21 17:07:25.995030: Pseudo dice [0.835] +2024-11-21 17:07:25.995115: Epoch time: 19.3 s +2024-11-21 17:07:26.841319: +2024-11-21 17:07:26.841525: Epoch 1184 +2024-11-21 17:07:26.841637: Current learning rate: 0.00866 +2024-11-21 17:07:45.448938: train_loss -0.7717 +2024-11-21 17:07:45.449158: val_loss -0.7152 +2024-11-21 17:07:45.449242: Pseudo dice [0.8242] +2024-11-21 17:07:45.449320: Epoch time: 18.61 s +2024-11-21 17:07:46.282233: +2024-11-21 17:07:46.282480: Epoch 1185 +2024-11-21 17:07:46.282594: Current learning rate: 0.00866 +2024-11-21 17:08:05.174762: train_loss -0.7699 +2024-11-21 17:08:05.174973: val_loss -0.7383 +2024-11-21 17:08:05.175069: Pseudo dice [0.8141] +2024-11-21 17:08:05.175145: Epoch time: 18.89 s +2024-11-21 17:08:06.008951: +2024-11-21 17:08:06.009173: Epoch 1186 +2024-11-21 17:08:06.009286: Current learning rate: 0.00866 +2024-11-21 17:08:23.329288: train_loss -0.769 +2024-11-21 17:08:23.329531: val_loss -0.7283 +2024-11-21 17:08:23.329622: Pseudo dice [0.8158] +2024-11-21 17:08:23.329726: Epoch time: 17.32 s +2024-11-21 17:08:24.160155: +2024-11-21 17:08:24.160356: Epoch 1187 +2024-11-21 17:08:24.160470: Current learning rate: 0.00865 +2024-11-21 17:08:43.038143: train_loss -0.76 +2024-11-21 17:08:43.038361: val_loss -0.7327 +2024-11-21 17:08:43.038439: Pseudo dice [0.8129] +2024-11-21 17:08:43.038516: Epoch time: 18.88 s +2024-11-21 17:08:43.879465: +2024-11-21 17:08:43.879654: Epoch 1188 +2024-11-21 17:08:43.879766: Current learning rate: 0.00865 +2024-11-21 17:09:02.769949: train_loss -0.762 +2024-11-21 17:09:02.770163: val_loss -0.7572 +2024-11-21 17:09:02.770235: Pseudo dice [0.828] +2024-11-21 17:09:02.770311: Epoch time: 18.89 s +2024-11-21 17:09:03.778786: +2024-11-21 17:09:03.778984: Epoch 1189 +2024-11-21 17:09:03.779104: Current learning rate: 0.00865 +2024-11-21 17:09:21.897283: train_loss -0.7669 +2024-11-21 17:09:21.897496: val_loss -0.749 +2024-11-21 17:09:21.897574: Pseudo dice [0.8149] +2024-11-21 17:09:21.897648: Epoch time: 18.12 s +2024-11-21 17:09:22.797261: +2024-11-21 17:09:22.797726: Epoch 1190 +2024-11-21 17:09:22.797836: Current learning rate: 0.00865 +2024-11-21 17:09:42.118582: train_loss -0.7653 +2024-11-21 17:09:42.118831: val_loss -0.7479 +2024-11-21 17:09:42.118907: Pseudo dice [0.8158] +2024-11-21 17:09:42.118989: Epoch time: 19.32 s +2024-11-21 17:09:43.022067: +2024-11-21 17:09:43.022263: Epoch 1191 +2024-11-21 17:09:43.022376: Current learning rate: 0.00865 +2024-11-21 17:10:02.053286: train_loss -0.7688 +2024-11-21 17:10:02.053502: val_loss -0.7532 +2024-11-21 17:10:02.053575: Pseudo dice [0.8171] +2024-11-21 17:10:02.053651: Epoch time: 19.03 s +2024-11-21 17:10:02.950010: +2024-11-21 17:10:02.950202: Epoch 1192 +2024-11-21 17:10:02.950319: Current learning rate: 0.00865 +2024-11-21 17:10:21.627365: train_loss -0.7649 +2024-11-21 17:10:21.627586: val_loss -0.7611 +2024-11-21 17:10:21.627659: Pseudo dice [0.8244] +2024-11-21 17:10:21.627734: Epoch time: 18.68 s +2024-11-21 17:10:22.461075: +2024-11-21 17:10:22.461274: Epoch 1193 +2024-11-21 17:10:22.461386: Current learning rate: 0.00865 +2024-11-21 17:10:41.845470: train_loss -0.7613 +2024-11-21 17:10:41.845693: val_loss -0.7421 +2024-11-21 17:10:41.845768: Pseudo dice [0.833] +2024-11-21 17:10:41.845851: Epoch time: 19.39 s +2024-11-21 17:10:43.043566: +2024-11-21 17:10:43.043816: Epoch 1194 +2024-11-21 17:10:43.043960: Current learning rate: 0.00865 +2024-11-21 17:11:01.092363: train_loss -0.7673 +2024-11-21 17:11:01.092586: val_loss -0.7427 +2024-11-21 17:11:01.092659: Pseudo dice [0.8268] +2024-11-21 17:11:01.092736: Epoch time: 18.05 s +2024-11-21 17:11:01.947208: +2024-11-21 17:11:01.947435: Epoch 1195 +2024-11-21 17:11:01.947555: Current learning rate: 0.00864 +2024-11-21 17:11:21.216258: train_loss -0.7545 +2024-11-21 17:11:21.216480: val_loss -0.7199 +2024-11-21 17:11:21.216564: Pseudo dice [0.8112] +2024-11-21 17:11:21.216643: Epoch time: 19.27 s +2024-11-21 17:11:22.055301: +2024-11-21 17:11:22.055523: Epoch 1196 +2024-11-21 17:11:22.055638: Current learning rate: 0.00864 +2024-11-21 17:11:41.744799: train_loss -0.759 +2024-11-21 17:11:41.745020: val_loss -0.718 +2024-11-21 17:11:41.745093: Pseudo dice [0.8381] +2024-11-21 17:11:41.745170: Epoch time: 19.69 s +2024-11-21 17:11:42.572735: +2024-11-21 17:11:42.572953: Epoch 1197 +2024-11-21 17:11:42.573072: Current learning rate: 0.00864 +2024-11-21 17:12:01.342875: train_loss -0.7744 +2024-11-21 17:12:01.343121: val_loss -0.7185 +2024-11-21 17:12:01.343200: Pseudo dice [0.8158] +2024-11-21 17:12:01.343282: Epoch time: 18.77 s +2024-11-21 17:12:02.169305: +2024-11-21 17:12:02.169507: Epoch 1198 +2024-11-21 17:12:02.169617: Current learning rate: 0.00864 +2024-11-21 17:12:20.486873: train_loss -0.7672 +2024-11-21 17:12:20.487200: val_loss -0.7302 +2024-11-21 17:12:20.487275: Pseudo dice [0.8205] +2024-11-21 17:12:20.487351: Epoch time: 18.32 s +2024-11-21 17:12:21.319735: +2024-11-21 17:12:21.320006: Epoch 1199 +2024-11-21 17:12:21.320122: Current learning rate: 0.00864 +2024-11-21 17:12:39.740971: train_loss -0.7654 +2024-11-21 17:12:39.741195: val_loss -0.7487 +2024-11-21 17:12:39.741267: Pseudo dice [0.8109] +2024-11-21 17:12:39.741346: Epoch time: 18.42 s +2024-11-21 17:12:40.796813: +2024-11-21 17:12:40.797030: Epoch 1200 +2024-11-21 17:12:40.797145: Current learning rate: 0.00864 +2024-11-21 17:12:59.741197: train_loss -0.7703 +2024-11-21 17:12:59.741413: val_loss -0.7377 +2024-11-21 17:12:59.741489: Pseudo dice [0.8195] +2024-11-21 17:12:59.741570: Epoch time: 18.95 s +2024-11-21 17:13:00.577519: +2024-11-21 17:13:00.577724: Epoch 1201 +2024-11-21 17:13:00.577835: Current learning rate: 0.00864 +2024-11-21 17:13:20.224768: train_loss -0.7463 +2024-11-21 17:13:20.225026: val_loss -0.7254 +2024-11-21 17:13:20.225102: Pseudo dice [0.7992] +2024-11-21 17:13:20.225186: Epoch time: 19.65 s +2024-11-21 17:13:21.060854: +2024-11-21 17:13:21.061072: Epoch 1202 +2024-11-21 17:13:21.061192: Current learning rate: 0.00864 +2024-11-21 17:13:40.204298: train_loss -0.7461 +2024-11-21 17:13:40.204514: val_loss -0.7365 +2024-11-21 17:13:40.204585: Pseudo dice [0.8022] +2024-11-21 17:13:40.204659: Epoch time: 19.14 s +2024-11-21 17:13:41.238267: +2024-11-21 17:13:41.238462: Epoch 1203 +2024-11-21 17:13:41.238575: Current learning rate: 0.00864 +2024-11-21 17:14:00.211816: train_loss -0.753 +2024-11-21 17:14:00.214971: val_loss -0.7049 +2024-11-21 17:14:00.215096: Pseudo dice [0.8135] +2024-11-21 17:14:00.215178: Epoch time: 18.97 s +2024-11-21 17:14:01.078218: +2024-11-21 17:14:01.078452: Epoch 1204 +2024-11-21 17:14:01.078572: Current learning rate: 0.00863 +2024-11-21 17:14:20.070861: train_loss -0.7574 +2024-11-21 17:14:20.071235: val_loss -0.7274 +2024-11-21 17:14:20.071325: Pseudo dice [0.8254] +2024-11-21 17:14:20.071407: Epoch time: 18.99 s +2024-11-21 17:14:20.899759: +2024-11-21 17:14:20.900018: Epoch 1205 +2024-11-21 17:14:20.900139: Current learning rate: 0.00863 +2024-11-21 17:14:39.208744: train_loss -0.7732 +2024-11-21 17:14:39.209253: val_loss -0.753 +2024-11-21 17:14:39.209349: Pseudo dice [0.8388] +2024-11-21 17:14:39.209427: Epoch time: 18.31 s +2024-11-21 17:14:40.050266: +2024-11-21 17:14:40.050481: Epoch 1206 +2024-11-21 17:14:40.050596: Current learning rate: 0.00863 +2024-11-21 17:14:58.848031: train_loss -0.7617 +2024-11-21 17:14:58.848262: val_loss -0.7261 +2024-11-21 17:14:58.848340: Pseudo dice [0.8222] +2024-11-21 17:14:58.848418: Epoch time: 18.8 s +2024-11-21 17:14:59.681785: +2024-11-21 17:14:59.682065: Epoch 1207 +2024-11-21 17:14:59.682180: Current learning rate: 0.00863 +2024-11-21 17:15:19.008895: train_loss -0.7598 +2024-11-21 17:15:19.009151: val_loss -0.7117 +2024-11-21 17:15:19.011393: Pseudo dice [0.8086] +2024-11-21 17:15:19.011551: Epoch time: 19.33 s +2024-11-21 17:15:19.868758: +2024-11-21 17:15:19.868978: Epoch 1208 +2024-11-21 17:15:19.869101: Current learning rate: 0.00863 +2024-11-21 17:15:38.943580: train_loss -0.7579 +2024-11-21 17:15:38.943789: val_loss -0.742 +2024-11-21 17:15:38.943864: Pseudo dice [0.8208] +2024-11-21 17:15:38.943943: Epoch time: 19.08 s +2024-11-21 17:15:39.778799: +2024-11-21 17:15:39.779016: Epoch 1209 +2024-11-21 17:15:39.779141: Current learning rate: 0.00863 +2024-11-21 17:15:58.760783: train_loss -0.7473 +2024-11-21 17:15:58.761047: val_loss -0.7374 +2024-11-21 17:15:58.761125: Pseudo dice [0.818] +2024-11-21 17:15:58.761203: Epoch time: 18.98 s +2024-11-21 17:15:59.660250: +2024-11-21 17:15:59.660460: Epoch 1210 +2024-11-21 17:15:59.660575: Current learning rate: 0.00863 +2024-11-21 17:16:19.079603: train_loss -0.7527 +2024-11-21 17:16:19.079816: val_loss -0.743 +2024-11-21 17:16:19.079886: Pseudo dice [0.8135] +2024-11-21 17:16:19.079960: Epoch time: 19.42 s +2024-11-21 17:16:19.949059: +2024-11-21 17:16:19.949279: Epoch 1211 +2024-11-21 17:16:19.949397: Current learning rate: 0.00863 +2024-11-21 17:16:38.413099: train_loss -0.7534 +2024-11-21 17:16:38.418522: val_loss -0.7221 +2024-11-21 17:16:38.418642: Pseudo dice [0.8306] +2024-11-21 17:16:38.418743: Epoch time: 18.46 s +2024-11-21 17:16:39.271204: +2024-11-21 17:16:39.271413: Epoch 1212 +2024-11-21 17:16:39.271528: Current learning rate: 0.00863 +2024-11-21 17:16:57.611819: train_loss -0.7509 +2024-11-21 17:16:57.612037: val_loss -0.7238 +2024-11-21 17:16:57.612127: Pseudo dice [0.8184] +2024-11-21 17:16:57.612204: Epoch time: 18.34 s +2024-11-21 17:16:58.444344: +2024-11-21 17:16:58.444573: Epoch 1213 +2024-11-21 17:16:58.444692: Current learning rate: 0.00862 +2024-11-21 17:17:17.097408: train_loss -0.7665 +2024-11-21 17:17:17.097610: val_loss -0.7455 +2024-11-21 17:17:17.097682: Pseudo dice [0.8279] +2024-11-21 17:17:17.097755: Epoch time: 18.65 s +2024-11-21 17:17:17.958567: +2024-11-21 17:17:17.958879: Epoch 1214 +2024-11-21 17:17:17.959008: Current learning rate: 0.00862 +2024-11-21 17:17:37.105396: train_loss -0.7656 +2024-11-21 17:17:37.105604: val_loss -0.7318 +2024-11-21 17:17:37.105679: Pseudo dice [0.8177] +2024-11-21 17:17:37.105758: Epoch time: 19.15 s +2024-11-21 17:17:37.936914: +2024-11-21 17:17:37.937125: Epoch 1215 +2024-11-21 17:17:37.937235: Current learning rate: 0.00862 +2024-11-21 17:17:57.439646: train_loss -0.7525 +2024-11-21 17:17:57.442084: val_loss -0.7328 +2024-11-21 17:17:57.442185: Pseudo dice [0.8242] +2024-11-21 17:17:57.442269: Epoch time: 19.5 s +2024-11-21 17:17:58.374807: +2024-11-21 17:17:58.375008: Epoch 1216 +2024-11-21 17:17:58.375123: Current learning rate: 0.00862 +2024-11-21 17:18:17.287627: train_loss -0.7729 +2024-11-21 17:18:17.287838: val_loss -0.7392 +2024-11-21 17:18:17.287912: Pseudo dice [0.8006] +2024-11-21 17:18:17.287996: Epoch time: 18.91 s +2024-11-21 17:18:18.528901: +2024-11-21 17:18:18.529113: Epoch 1217 +2024-11-21 17:18:18.529221: Current learning rate: 0.00862 +2024-11-21 17:18:37.569264: train_loss -0.7542 +2024-11-21 17:18:37.569486: val_loss -0.7394 +2024-11-21 17:18:37.569566: Pseudo dice [0.8376] +2024-11-21 17:18:37.569646: Epoch time: 19.04 s +2024-11-21 17:18:38.404703: +2024-11-21 17:18:38.404896: Epoch 1218 +2024-11-21 17:18:38.405012: Current learning rate: 0.00862 +2024-11-21 17:18:56.535682: train_loss -0.7595 +2024-11-21 17:18:56.535912: val_loss -0.7333 +2024-11-21 17:18:56.535985: Pseudo dice [0.8102] +2024-11-21 17:18:56.536076: Epoch time: 18.13 s +2024-11-21 17:18:57.399270: +2024-11-21 17:18:57.399483: Epoch 1219 +2024-11-21 17:18:57.399600: Current learning rate: 0.00862 +2024-11-21 17:19:16.526796: train_loss -0.7723 +2024-11-21 17:19:16.531404: val_loss -0.7473 +2024-11-21 17:19:16.531547: Pseudo dice [0.8116] +2024-11-21 17:19:16.531658: Epoch time: 19.13 s +2024-11-21 17:19:17.429307: +2024-11-21 17:19:17.429566: Epoch 1220 +2024-11-21 17:19:17.429678: Current learning rate: 0.00862 +2024-11-21 17:19:34.906473: train_loss -0.7545 +2024-11-21 17:19:34.906695: val_loss -0.7476 +2024-11-21 17:19:34.906769: Pseudo dice [0.8293] +2024-11-21 17:19:34.906847: Epoch time: 17.48 s +2024-11-21 17:19:35.738156: +2024-11-21 17:19:35.738362: Epoch 1221 +2024-11-21 17:19:35.738474: Current learning rate: 0.00862 +2024-11-21 17:19:54.349617: train_loss -0.7674 +2024-11-21 17:19:54.349876: val_loss -0.7537 +2024-11-21 17:19:54.349953: Pseudo dice [0.8222] +2024-11-21 17:19:54.350039: Epoch time: 18.61 s +2024-11-21 17:19:55.258015: +2024-11-21 17:19:55.258209: Epoch 1222 +2024-11-21 17:19:55.258318: Current learning rate: 0.00861 +2024-11-21 17:20:13.644289: train_loss -0.7666 +2024-11-21 17:20:13.644603: val_loss -0.6734 +2024-11-21 17:20:13.644682: Pseudo dice [0.808] +2024-11-21 17:20:13.644762: Epoch time: 18.39 s +2024-11-21 17:20:14.541052: +2024-11-21 17:20:14.541262: Epoch 1223 +2024-11-21 17:20:14.541377: Current learning rate: 0.00861 +2024-11-21 17:20:33.756460: train_loss -0.7657 +2024-11-21 17:20:33.756670: val_loss -0.715 +2024-11-21 17:20:33.756746: Pseudo dice [0.7812] +2024-11-21 17:20:33.756823: Epoch time: 19.22 s +2024-11-21 17:20:34.649878: +2024-11-21 17:20:34.650072: Epoch 1224 +2024-11-21 17:20:34.650185: Current learning rate: 0.00861 +2024-11-21 17:20:54.615720: train_loss -0.7692 +2024-11-21 17:20:54.615932: val_loss -0.7475 +2024-11-21 17:20:54.618148: Pseudo dice [0.838] +2024-11-21 17:20:54.618258: Epoch time: 19.97 s +2024-11-21 17:20:55.603932: +2024-11-21 17:20:55.604142: Epoch 1225 +2024-11-21 17:20:55.604253: Current learning rate: 0.00861 +2024-11-21 17:21:14.945738: train_loss -0.7673 +2024-11-21 17:21:14.946020: val_loss -0.7496 +2024-11-21 17:21:14.946103: Pseudo dice [0.8216] +2024-11-21 17:21:14.946182: Epoch time: 19.34 s +2024-11-21 17:21:15.780365: +2024-11-21 17:21:15.780583: Epoch 1226 +2024-11-21 17:21:15.780695: Current learning rate: 0.00861 +2024-11-21 17:21:34.127456: train_loss -0.7694 +2024-11-21 17:21:34.127689: val_loss -0.7399 +2024-11-21 17:21:34.127763: Pseudo dice [0.8266] +2024-11-21 17:21:34.127843: Epoch time: 18.35 s +2024-11-21 17:21:35.195610: +2024-11-21 17:21:35.195873: Epoch 1227 +2024-11-21 17:21:35.195987: Current learning rate: 0.00861 +2024-11-21 17:21:54.053359: train_loss -0.7747 +2024-11-21 17:21:54.058760: val_loss -0.7346 +2024-11-21 17:21:54.058879: Pseudo dice [0.814] +2024-11-21 17:21:54.058964: Epoch time: 18.86 s +2024-11-21 17:21:55.310700: +2024-11-21 17:21:55.310988: Epoch 1228 +2024-11-21 17:21:55.311107: Current learning rate: 0.00861 +2024-11-21 17:22:13.106227: train_loss -0.7634 +2024-11-21 17:22:13.106451: val_loss -0.7497 +2024-11-21 17:22:13.106522: Pseudo dice [0.8409] +2024-11-21 17:22:13.106600: Epoch time: 17.8 s +2024-11-21 17:22:13.945899: +2024-11-21 17:22:13.946138: Epoch 1229 +2024-11-21 17:22:13.946293: Current learning rate: 0.00861 +2024-11-21 17:22:32.267505: train_loss -0.7431 +2024-11-21 17:22:32.267715: val_loss -0.7036 +2024-11-21 17:22:32.267788: Pseudo dice [0.7795] +2024-11-21 17:22:32.267866: Epoch time: 18.32 s +2024-11-21 17:22:33.202525: +2024-11-21 17:22:33.202745: Epoch 1230 +2024-11-21 17:22:33.202858: Current learning rate: 0.0086 +2024-11-21 17:22:52.698611: train_loss -0.7419 +2024-11-21 17:22:52.698953: val_loss -0.7132 +2024-11-21 17:22:52.699048: Pseudo dice [0.7941] +2024-11-21 17:22:52.699127: Epoch time: 19.5 s +2024-11-21 17:22:53.567439: +2024-11-21 17:22:53.567639: Epoch 1231 +2024-11-21 17:22:53.567749: Current learning rate: 0.0086 +2024-11-21 17:23:12.478416: train_loss -0.7516 +2024-11-21 17:23:12.478692: val_loss -0.722 +2024-11-21 17:23:12.478768: Pseudo dice [0.8161] +2024-11-21 17:23:12.478843: Epoch time: 18.91 s +2024-11-21 17:23:13.312052: +2024-11-21 17:23:13.312275: Epoch 1232 +2024-11-21 17:23:13.312387: Current learning rate: 0.0086 +2024-11-21 17:23:31.230590: train_loss -0.7474 +2024-11-21 17:23:31.230824: val_loss -0.724 +2024-11-21 17:23:31.230898: Pseudo dice [0.798] +2024-11-21 17:23:31.230979: Epoch time: 17.92 s +2024-11-21 17:23:32.178881: +2024-11-21 17:23:32.179128: Epoch 1233 +2024-11-21 17:23:32.179675: Current learning rate: 0.0086 +2024-11-21 17:23:50.706779: train_loss -0.7619 +2024-11-21 17:23:50.706984: val_loss -0.7345 +2024-11-21 17:23:50.707067: Pseudo dice [0.8058] +2024-11-21 17:23:50.707144: Epoch time: 18.53 s +2024-11-21 17:23:51.543655: +2024-11-21 17:23:51.543869: Epoch 1234 +2024-11-21 17:23:51.543995: Current learning rate: 0.0086 +2024-11-21 17:24:09.337357: train_loss -0.7551 +2024-11-21 17:24:09.337569: val_loss -0.7422 +2024-11-21 17:24:09.337644: Pseudo dice [0.8229] +2024-11-21 17:24:09.337721: Epoch time: 17.79 s +2024-11-21 17:24:10.263377: +2024-11-21 17:24:10.263577: Epoch 1235 +2024-11-21 17:24:10.263689: Current learning rate: 0.0086 +2024-11-21 17:24:29.530492: train_loss -0.7582 +2024-11-21 17:24:29.530702: val_loss -0.7281 +2024-11-21 17:24:29.530776: Pseudo dice [0.8223] +2024-11-21 17:24:29.530852: Epoch time: 19.27 s +2024-11-21 17:24:30.374954: +2024-11-21 17:24:30.375172: Epoch 1236 +2024-11-21 17:24:30.375294: Current learning rate: 0.0086 +2024-11-21 17:24:48.483975: train_loss -0.7648 +2024-11-21 17:24:48.484225: val_loss -0.726 +2024-11-21 17:24:48.484298: Pseudo dice [0.8143] +2024-11-21 17:24:48.484380: Epoch time: 18.11 s +2024-11-21 17:24:49.323166: +2024-11-21 17:24:49.323402: Epoch 1237 +2024-11-21 17:24:49.323517: Current learning rate: 0.0086 +2024-11-21 17:25:08.546233: train_loss -0.7701 +2024-11-21 17:25:08.546436: val_loss -0.7607 +2024-11-21 17:25:08.546509: Pseudo dice [0.8154] +2024-11-21 17:25:08.546581: Epoch time: 19.22 s +2024-11-21 17:25:09.380725: +2024-11-21 17:25:09.380985: Epoch 1238 +2024-11-21 17:25:09.381103: Current learning rate: 0.0086 +2024-11-21 17:25:28.383185: train_loss -0.7566 +2024-11-21 17:25:28.385063: val_loss -0.7425 +2024-11-21 17:25:28.385153: Pseudo dice [0.8108] +2024-11-21 17:25:28.385232: Epoch time: 19.0 s +2024-11-21 17:25:29.317609: +2024-11-21 17:25:29.317891: Epoch 1239 +2024-11-21 17:25:29.318011: Current learning rate: 0.00859 +2024-11-21 17:25:47.456673: train_loss -0.7678 +2024-11-21 17:25:47.456945: val_loss -0.7277 +2024-11-21 17:25:47.457024: Pseudo dice [0.7981] +2024-11-21 17:25:47.457109: Epoch time: 18.14 s +2024-11-21 17:25:48.738714: +2024-11-21 17:25:48.738914: Epoch 1240 +2024-11-21 17:25:48.739039: Current learning rate: 0.00859 +2024-11-21 17:26:06.855917: train_loss -0.7688 +2024-11-21 17:26:06.856148: val_loss -0.7463 +2024-11-21 17:26:06.856225: Pseudo dice [0.8126] +2024-11-21 17:26:06.856355: Epoch time: 18.12 s +2024-11-21 17:26:07.693893: +2024-11-21 17:26:07.694129: Epoch 1241 +2024-11-21 17:26:07.694241: Current learning rate: 0.00859 +2024-11-21 17:26:27.053906: train_loss -0.7658 +2024-11-21 17:26:27.054130: val_loss -0.7157 +2024-11-21 17:26:27.054207: Pseudo dice [0.8116] +2024-11-21 17:26:27.054282: Epoch time: 19.36 s +2024-11-21 17:26:27.888375: +2024-11-21 17:26:27.888597: Epoch 1242 +2024-11-21 17:26:27.888710: Current learning rate: 0.00859 +2024-11-21 17:26:46.703607: train_loss -0.7754 +2024-11-21 17:26:46.703850: val_loss -0.7374 +2024-11-21 17:26:46.703932: Pseudo dice [0.8406] +2024-11-21 17:26:46.704026: Epoch time: 18.82 s +2024-11-21 17:26:47.537482: +2024-11-21 17:26:47.537673: Epoch 1243 +2024-11-21 17:26:47.537820: Current learning rate: 0.00859 +2024-11-21 17:27:06.277725: train_loss -0.7714 +2024-11-21 17:27:06.277932: val_loss -0.7214 +2024-11-21 17:27:06.278011: Pseudo dice [0.8171] +2024-11-21 17:27:06.278086: Epoch time: 18.74 s +2024-11-21 17:27:07.112257: +2024-11-21 17:27:07.112465: Epoch 1244 +2024-11-21 17:27:07.112579: Current learning rate: 0.00859 +2024-11-21 17:27:24.781955: train_loss -0.7698 +2024-11-21 17:27:24.782161: val_loss -0.7051 +2024-11-21 17:27:24.782234: Pseudo dice [0.813] +2024-11-21 17:27:24.782309: Epoch time: 17.67 s +2024-11-21 17:27:25.639851: +2024-11-21 17:27:25.640053: Epoch 1245 +2024-11-21 17:27:25.640166: Current learning rate: 0.00859 +2024-11-21 17:27:45.132926: train_loss -0.7665 +2024-11-21 17:27:45.133141: val_loss -0.7422 +2024-11-21 17:27:45.133221: Pseudo dice [0.8226] +2024-11-21 17:27:45.133957: Epoch time: 19.49 s +2024-11-21 17:27:45.961813: +2024-11-21 17:27:45.962001: Epoch 1246 +2024-11-21 17:27:45.962117: Current learning rate: 0.00859 +2024-11-21 17:28:04.822530: train_loss -0.7607 +2024-11-21 17:28:04.822761: val_loss -0.73 +2024-11-21 17:28:04.822834: Pseudo dice [0.8067] +2024-11-21 17:28:04.822915: Epoch time: 18.86 s +2024-11-21 17:28:05.658217: +2024-11-21 17:28:05.658415: Epoch 1247 +2024-11-21 17:28:05.658523: Current learning rate: 0.00859 +2024-11-21 17:28:24.447863: train_loss -0.7666 +2024-11-21 17:28:24.448095: val_loss -0.7507 +2024-11-21 17:28:24.448205: Pseudo dice [0.8223] +2024-11-21 17:28:24.448284: Epoch time: 18.79 s +2024-11-21 17:28:25.280517: +2024-11-21 17:28:25.280729: Epoch 1248 +2024-11-21 17:28:25.280835: Current learning rate: 0.00858 +2024-11-21 17:28:43.953641: train_loss -0.7689 +2024-11-21 17:28:43.953871: val_loss -0.7235 +2024-11-21 17:28:43.953947: Pseudo dice [0.8029] +2024-11-21 17:28:43.954031: Epoch time: 18.67 s +2024-11-21 17:28:44.773042: +2024-11-21 17:28:44.773219: Epoch 1249 +2024-11-21 17:28:44.773338: Current learning rate: 0.00858 +2024-11-21 17:29:03.869370: train_loss -0.7736 +2024-11-21 17:29:03.869597: val_loss -0.743 +2024-11-21 17:29:03.869668: Pseudo dice [0.8297] +2024-11-21 17:29:03.869749: Epoch time: 19.1 s +2024-11-21 17:29:04.967721: +2024-11-21 17:29:04.967928: Epoch 1250 +2024-11-21 17:29:04.968050: Current learning rate: 0.00858 +2024-11-21 17:29:23.034250: train_loss -0.7715 +2024-11-21 17:29:23.034466: val_loss -0.7551 +2024-11-21 17:29:23.034538: Pseudo dice [0.8362] +2024-11-21 17:29:23.034613: Epoch time: 18.07 s +2024-11-21 17:29:23.911410: +2024-11-21 17:29:23.911838: Epoch 1251 +2024-11-21 17:29:23.911971: Current learning rate: 0.00858 +2024-11-21 17:29:42.265597: train_loss -0.7708 +2024-11-21 17:29:42.270165: val_loss -0.7618 +2024-11-21 17:29:42.270277: Pseudo dice [0.8468] +2024-11-21 17:29:42.270357: Epoch time: 18.35 s +2024-11-21 17:29:43.227004: +2024-11-21 17:29:43.227212: Epoch 1252 +2024-11-21 17:29:43.227330: Current learning rate: 0.00858 +2024-11-21 17:30:02.747288: train_loss -0.7733 +2024-11-21 17:30:02.747523: val_loss -0.7325 +2024-11-21 17:30:02.747600: Pseudo dice [0.8255] +2024-11-21 17:30:02.747760: Epoch time: 19.52 s +2024-11-21 17:30:03.602039: +2024-11-21 17:30:03.602265: Epoch 1253 +2024-11-21 17:30:03.602380: Current learning rate: 0.00858 +2024-11-21 17:30:22.379660: train_loss -0.772 +2024-11-21 17:30:22.379869: val_loss -0.7457 +2024-11-21 17:30:22.379946: Pseudo dice [0.8337] +2024-11-21 17:30:22.380032: Epoch time: 18.78 s +2024-11-21 17:30:23.286430: +2024-11-21 17:30:23.286652: Epoch 1254 +2024-11-21 17:30:23.286757: Current learning rate: 0.00858 +2024-11-21 17:30:42.505923: train_loss -0.7744 +2024-11-21 17:30:42.506155: val_loss -0.7237 +2024-11-21 17:30:42.506233: Pseudo dice [0.82] +2024-11-21 17:30:42.506324: Epoch time: 19.22 s +2024-11-21 17:30:43.424442: +2024-11-21 17:30:43.424678: Epoch 1255 +2024-11-21 17:30:43.424787: Current learning rate: 0.00858 +2024-11-21 17:31:02.708105: train_loss -0.773 +2024-11-21 17:31:02.708389: val_loss -0.7409 +2024-11-21 17:31:02.708475: Pseudo dice [0.8141] +2024-11-21 17:31:02.708561: Epoch time: 19.28 s +2024-11-21 17:31:03.530945: +2024-11-21 17:31:03.531163: Epoch 1256 +2024-11-21 17:31:03.531278: Current learning rate: 0.00858 +2024-11-21 17:31:21.797984: train_loss -0.7833 +2024-11-21 17:31:21.798298: val_loss -0.7352 +2024-11-21 17:31:21.798376: Pseudo dice [0.8406] +2024-11-21 17:31:21.798454: Epoch time: 18.27 s +2024-11-21 17:31:22.678481: +2024-11-21 17:31:22.678689: Epoch 1257 +2024-11-21 17:31:22.678798: Current learning rate: 0.00857 +2024-11-21 17:31:41.449200: train_loss -0.7721 +2024-11-21 17:31:41.449465: val_loss -0.75 +2024-11-21 17:31:41.449540: Pseudo dice [0.8187] +2024-11-21 17:31:41.449616: Epoch time: 18.77 s +2024-11-21 17:31:42.289497: +2024-11-21 17:31:42.289736: Epoch 1258 +2024-11-21 17:31:42.289852: Current learning rate: 0.00857 +2024-11-21 17:32:00.921805: train_loss -0.7636 +2024-11-21 17:32:00.922387: val_loss -0.7293 +2024-11-21 17:32:00.922501: Pseudo dice [0.812] +2024-11-21 17:32:00.922580: Epoch time: 18.63 s +2024-11-21 17:32:01.794556: +2024-11-21 17:32:01.794767: Epoch 1259 +2024-11-21 17:32:01.794883: Current learning rate: 0.00857 +2024-11-21 17:32:20.981364: train_loss -0.7601 +2024-11-21 17:32:20.981571: val_loss -0.7455 +2024-11-21 17:32:20.981652: Pseudo dice [0.825] +2024-11-21 17:32:20.981752: Epoch time: 19.19 s +2024-11-21 17:32:21.827339: +2024-11-21 17:32:21.827570: Epoch 1260 +2024-11-21 17:32:21.827686: Current learning rate: 0.00857 +2024-11-21 17:32:40.433722: train_loss -0.7697 +2024-11-21 17:32:40.433937: val_loss -0.732 +2024-11-21 17:32:40.434018: Pseudo dice [0.8171] +2024-11-21 17:32:40.434094: Epoch time: 18.61 s +2024-11-21 17:32:41.280267: +2024-11-21 17:32:41.280462: Epoch 1261 +2024-11-21 17:32:41.280571: Current learning rate: 0.00857 +2024-11-21 17:32:59.785155: train_loss -0.7707 +2024-11-21 17:32:59.785371: val_loss -0.7517 +2024-11-21 17:32:59.785445: Pseudo dice [0.8334] +2024-11-21 17:32:59.785521: Epoch time: 18.51 s +2024-11-21 17:33:00.779264: +2024-11-21 17:33:00.779469: Epoch 1262 +2024-11-21 17:33:00.779593: Current learning rate: 0.00857 +2024-11-21 17:33:18.321090: train_loss -0.7711 +2024-11-21 17:33:18.321294: val_loss -0.7289 +2024-11-21 17:33:18.321370: Pseudo dice [0.8364] +2024-11-21 17:33:18.321448: Epoch time: 17.54 s +2024-11-21 17:33:19.536180: +2024-11-21 17:33:19.536390: Epoch 1263 +2024-11-21 17:33:19.536507: Current learning rate: 0.00857 +2024-11-21 17:33:38.672406: train_loss -0.768 +2024-11-21 17:33:38.672645: val_loss -0.747 +2024-11-21 17:33:38.672780: Pseudo dice [0.8041] +2024-11-21 17:33:38.672864: Epoch time: 19.14 s +2024-11-21 17:33:39.555129: +2024-11-21 17:33:39.555340: Epoch 1264 +2024-11-21 17:33:39.555452: Current learning rate: 0.00857 +2024-11-21 17:33:58.942862: train_loss -0.7722 +2024-11-21 17:33:58.943084: val_loss -0.7397 +2024-11-21 17:33:58.943159: Pseudo dice [0.8295] +2024-11-21 17:33:58.943235: Epoch time: 19.39 s +2024-11-21 17:33:59.773283: +2024-11-21 17:33:59.773515: Epoch 1265 +2024-11-21 17:33:59.773627: Current learning rate: 0.00856 +2024-11-21 17:34:19.016583: train_loss -0.7812 +2024-11-21 17:34:19.016795: val_loss -0.7168 +2024-11-21 17:34:19.016868: Pseudo dice [0.8099] +2024-11-21 17:34:19.017032: Epoch time: 19.24 s +2024-11-21 17:34:19.844408: +2024-11-21 17:34:19.844600: Epoch 1266 +2024-11-21 17:34:19.844711: Current learning rate: 0.00856 +2024-11-21 17:34:39.077220: train_loss -0.7647 +2024-11-21 17:34:39.077435: val_loss -0.7417 +2024-11-21 17:34:39.077507: Pseudo dice [0.8295] +2024-11-21 17:34:39.077586: Epoch time: 19.23 s +2024-11-21 17:34:39.915787: +2024-11-21 17:34:39.915988: Epoch 1267 +2024-11-21 17:34:39.916102: Current learning rate: 0.00856 +2024-11-21 17:34:58.285900: train_loss -0.7633 +2024-11-21 17:34:58.286175: val_loss -0.7279 +2024-11-21 17:34:58.286251: Pseudo dice [0.8312] +2024-11-21 17:34:58.286330: Epoch time: 18.37 s +2024-11-21 17:34:59.121190: +2024-11-21 17:34:59.121445: Epoch 1268 +2024-11-21 17:34:59.121553: Current learning rate: 0.00856 +2024-11-21 17:35:17.708987: train_loss -0.7721 +2024-11-21 17:35:17.709201: val_loss -0.7239 +2024-11-21 17:35:17.709275: Pseudo dice [0.8123] +2024-11-21 17:35:17.709351: Epoch time: 18.59 s +2024-11-21 17:35:18.644792: +2024-11-21 17:35:18.645015: Epoch 1269 +2024-11-21 17:35:18.645140: Current learning rate: 0.00856 +2024-11-21 17:35:37.419561: train_loss -0.7613 +2024-11-21 17:35:37.419777: val_loss -0.7388 +2024-11-21 17:35:37.419849: Pseudo dice [0.8327] +2024-11-21 17:35:37.419926: Epoch time: 18.78 s +2024-11-21 17:35:38.259973: +2024-11-21 17:35:38.260182: Epoch 1270 +2024-11-21 17:35:38.260315: Current learning rate: 0.00856 +2024-11-21 17:35:57.306579: train_loss -0.7648 +2024-11-21 17:35:57.306869: val_loss -0.7496 +2024-11-21 17:35:57.306942: Pseudo dice [0.8182] +2024-11-21 17:35:57.307033: Epoch time: 19.05 s +2024-11-21 17:35:58.197430: +2024-11-21 17:35:58.197648: Epoch 1271 +2024-11-21 17:35:58.197770: Current learning rate: 0.00856 +2024-11-21 17:36:16.497128: train_loss -0.769 +2024-11-21 17:36:16.497339: val_loss -0.7366 +2024-11-21 17:36:16.497416: Pseudo dice [0.8399] +2024-11-21 17:36:16.497491: Epoch time: 18.3 s +2024-11-21 17:36:17.333235: +2024-11-21 17:36:17.333462: Epoch 1272 +2024-11-21 17:36:17.333579: Current learning rate: 0.00856 +2024-11-21 17:36:36.674143: train_loss -0.7651 +2024-11-21 17:36:36.674359: val_loss -0.7393 +2024-11-21 17:36:36.674448: Pseudo dice [0.8371] +2024-11-21 17:36:36.674521: Epoch time: 19.34 s +2024-11-21 17:36:36.674583: Yayy! New best EMA pseudo Dice: 0.8257 +2024-11-21 17:36:37.697309: +2024-11-21 17:36:37.697506: Epoch 1273 +2024-11-21 17:36:37.697616: Current learning rate: 0.00856 +2024-11-21 17:36:56.115469: train_loss -0.7638 +2024-11-21 17:36:56.115679: val_loss -0.7429 +2024-11-21 17:36:56.115754: Pseudo dice [0.8351] +2024-11-21 17:36:56.115830: Epoch time: 18.42 s +2024-11-21 17:36:56.115891: Yayy! New best EMA pseudo Dice: 0.8266 +2024-11-21 17:36:57.507171: +2024-11-21 17:36:57.507371: Epoch 1274 +2024-11-21 17:36:57.507481: Current learning rate: 0.00855 +2024-11-21 17:37:16.759952: train_loss -0.7677 +2024-11-21 17:37:16.760208: val_loss -0.7641 +2024-11-21 17:37:16.760280: Pseudo dice [0.8226] +2024-11-21 17:37:16.760360: Epoch time: 19.25 s +2024-11-21 17:37:17.600278: +2024-11-21 17:37:17.600487: Epoch 1275 +2024-11-21 17:37:17.600598: Current learning rate: 0.00855 +2024-11-21 17:37:36.278434: train_loss -0.7588 +2024-11-21 17:37:36.278638: val_loss -0.7384 +2024-11-21 17:37:36.278713: Pseudo dice [0.8274] +2024-11-21 17:37:36.278792: Epoch time: 18.68 s +2024-11-21 17:37:37.116923: +2024-11-21 17:37:37.117131: Epoch 1276 +2024-11-21 17:37:37.117244: Current learning rate: 0.00855 +2024-11-21 17:37:55.808738: train_loss -0.7582 +2024-11-21 17:37:55.819308: val_loss -0.7476 +2024-11-21 17:37:55.819403: Pseudo dice [0.8251] +2024-11-21 17:37:55.819483: Epoch time: 18.69 s +2024-11-21 17:37:56.839255: +2024-11-21 17:37:56.839457: Epoch 1277 +2024-11-21 17:37:56.839572: Current learning rate: 0.00855 +2024-11-21 17:38:15.157085: train_loss -0.7504 +2024-11-21 17:38:15.157314: val_loss -0.7332 +2024-11-21 17:38:15.157395: Pseudo dice [0.8316] +2024-11-21 17:38:15.159728: Epoch time: 18.32 s +2024-11-21 17:38:15.159822: Yayy! New best EMA pseudo Dice: 0.8268 +2024-11-21 17:38:16.199420: +2024-11-21 17:38:16.199674: Epoch 1278 +2024-11-21 17:38:16.199824: Current learning rate: 0.00855 +2024-11-21 17:38:34.037011: train_loss -0.7687 +2024-11-21 17:38:34.037222: val_loss -0.7256 +2024-11-21 17:38:34.037295: Pseudo dice [0.8152] +2024-11-21 17:38:34.037374: Epoch time: 17.84 s +2024-11-21 17:38:34.901351: +2024-11-21 17:38:34.901560: Epoch 1279 +2024-11-21 17:38:34.901673: Current learning rate: 0.00855 +2024-11-21 17:38:53.795828: train_loss -0.7722 +2024-11-21 17:38:53.796084: val_loss -0.7489 +2024-11-21 17:38:53.796174: Pseudo dice [0.832] +2024-11-21 17:38:53.796249: Epoch time: 18.9 s +2024-11-21 17:38:54.629659: +2024-11-21 17:38:54.629886: Epoch 1280 +2024-11-21 17:38:54.629999: Current learning rate: 0.00855 +2024-11-21 17:39:12.406071: train_loss -0.7716 +2024-11-21 17:39:12.406276: val_loss -0.7491 +2024-11-21 17:39:12.406349: Pseudo dice [0.8357] +2024-11-21 17:39:12.406423: Epoch time: 17.78 s +2024-11-21 17:39:12.406482: Yayy! New best EMA pseudo Dice: 0.8272 +2024-11-21 17:39:13.451257: +2024-11-21 17:39:13.451474: Epoch 1281 +2024-11-21 17:39:13.451597: Current learning rate: 0.00855 +2024-11-21 17:39:31.644005: train_loss -0.7664 +2024-11-21 17:39:31.644464: val_loss -0.735 +2024-11-21 17:39:31.644556: Pseudo dice [0.8158] +2024-11-21 17:39:31.644644: Epoch time: 18.19 s +2024-11-21 17:39:32.477271: +2024-11-21 17:39:32.477468: Epoch 1282 +2024-11-21 17:39:32.477580: Current learning rate: 0.00855 +2024-11-21 17:39:50.432031: train_loss -0.7575 +2024-11-21 17:39:50.432247: val_loss -0.7449 +2024-11-21 17:39:50.432324: Pseudo dice [0.8181] +2024-11-21 17:39:50.432400: Epoch time: 17.96 s +2024-11-21 17:39:51.276621: +2024-11-21 17:39:51.297626: Epoch 1283 +2024-11-21 17:39:51.297756: Current learning rate: 0.00854 +2024-11-21 17:40:09.605403: train_loss -0.7626 +2024-11-21 17:40:09.605616: val_loss -0.736 +2024-11-21 17:40:09.605723: Pseudo dice [0.8141] +2024-11-21 17:40:09.605808: Epoch time: 18.33 s +2024-11-21 17:40:10.449455: +2024-11-21 17:40:10.449801: Epoch 1284 +2024-11-21 17:40:10.449913: Current learning rate: 0.00854 +2024-11-21 17:40:29.311032: train_loss -0.7617 +2024-11-21 17:40:29.311234: val_loss -0.7473 +2024-11-21 17:40:29.311311: Pseudo dice [0.8131] +2024-11-21 17:40:29.311386: Epoch time: 18.86 s +2024-11-21 17:40:30.161782: +2024-11-21 17:40:30.162016: Epoch 1285 +2024-11-21 17:40:30.162134: Current learning rate: 0.00854 +2024-11-21 17:40:48.476730: train_loss -0.7561 +2024-11-21 17:40:48.477271: val_loss -0.7571 +2024-11-21 17:40:48.477449: Pseudo dice [0.8302] +2024-11-21 17:40:48.477536: Epoch time: 18.32 s +2024-11-21 17:40:49.318223: +2024-11-21 17:40:49.318449: Epoch 1286 +2024-11-21 17:40:49.318563: Current learning rate: 0.00854 +2024-11-21 17:41:08.367278: train_loss -0.7482 +2024-11-21 17:41:08.367502: val_loss -0.7458 +2024-11-21 17:41:08.367576: Pseudo dice [0.8209] +2024-11-21 17:41:08.367654: Epoch time: 19.05 s +2024-11-21 17:41:09.197596: +2024-11-21 17:41:09.197817: Epoch 1287 +2024-11-21 17:41:09.197929: Current learning rate: 0.00854 +2024-11-21 17:41:28.171354: train_loss -0.7498 +2024-11-21 17:41:28.171566: val_loss -0.7186 +2024-11-21 17:41:28.171639: Pseudo dice [0.7937] +2024-11-21 17:41:28.171718: Epoch time: 18.97 s +2024-11-21 17:41:29.002829: +2024-11-21 17:41:29.003049: Epoch 1288 +2024-11-21 17:41:29.003166: Current learning rate: 0.00854 +2024-11-21 17:41:48.422851: train_loss -0.7463 +2024-11-21 17:41:48.423106: val_loss -0.747 +2024-11-21 17:41:48.423179: Pseudo dice [0.8212] +2024-11-21 17:41:48.423260: Epoch time: 19.42 s +2024-11-21 17:41:49.264963: +2024-11-21 17:41:49.265208: Epoch 1289 +2024-11-21 17:41:49.265321: Current learning rate: 0.00854 +2024-11-21 17:42:08.008633: train_loss -0.7633 +2024-11-21 17:42:08.008844: val_loss -0.7231 +2024-11-21 17:42:08.008918: Pseudo dice [0.827] +2024-11-21 17:42:08.009007: Epoch time: 18.74 s +2024-11-21 17:42:08.849738: +2024-11-21 17:42:08.849961: Epoch 1290 +2024-11-21 17:42:08.850077: Current learning rate: 0.00854 +2024-11-21 17:42:27.714944: train_loss -0.7682 +2024-11-21 17:42:27.715171: val_loss -0.7445 +2024-11-21 17:42:27.715257: Pseudo dice [0.8273] +2024-11-21 17:42:27.715332: Epoch time: 18.87 s +2024-11-21 17:42:28.561377: +2024-11-21 17:42:28.561622: Epoch 1291 +2024-11-21 17:42:28.561734: Current learning rate: 0.00854 +2024-11-21 17:42:47.590966: train_loss -0.7693 +2024-11-21 17:42:47.591205: val_loss -0.7469 +2024-11-21 17:42:47.591301: Pseudo dice [0.8324] +2024-11-21 17:42:47.591383: Epoch time: 19.03 s +2024-11-21 17:42:48.431721: +2024-11-21 17:42:48.431983: Epoch 1292 +2024-11-21 17:42:48.432103: Current learning rate: 0.00853 +2024-11-21 17:43:08.319003: train_loss -0.7634 +2024-11-21 17:43:08.319210: val_loss -0.7115 +2024-11-21 17:43:08.319287: Pseudo dice [0.7912] +2024-11-21 17:43:08.319366: Epoch time: 19.89 s +2024-11-21 17:43:09.150660: +2024-11-21 17:43:09.150865: Epoch 1293 +2024-11-21 17:43:09.150980: Current learning rate: 0.00853 +2024-11-21 17:43:27.044628: train_loss -0.771 +2024-11-21 17:43:27.044868: val_loss -0.722 +2024-11-21 17:43:27.044943: Pseudo dice [0.8196] +2024-11-21 17:43:27.045025: Epoch time: 17.89 s +2024-11-21 17:43:27.883350: +2024-11-21 17:43:27.883547: Epoch 1294 +2024-11-21 17:43:27.883658: Current learning rate: 0.00853 +2024-11-21 17:43:46.382068: train_loss -0.776 +2024-11-21 17:43:46.382275: val_loss -0.7099 +2024-11-21 17:43:46.382348: Pseudo dice [0.8164] +2024-11-21 17:43:46.382443: Epoch time: 18.5 s +2024-11-21 17:43:47.243732: +2024-11-21 17:43:47.243950: Epoch 1295 +2024-11-21 17:43:47.244073: Current learning rate: 0.00853 +2024-11-21 17:44:06.487979: train_loss -0.7583 +2024-11-21 17:44:06.488217: val_loss -0.7315 +2024-11-21 17:44:06.488289: Pseudo dice [0.817] +2024-11-21 17:44:06.507621: Epoch time: 19.25 s +2024-11-21 17:44:07.342921: +2024-11-21 17:44:07.343127: Epoch 1296 +2024-11-21 17:44:07.343242: Current learning rate: 0.00853 +2024-11-21 17:44:25.863774: train_loss -0.7678 +2024-11-21 17:44:25.863984: val_loss -0.7236 +2024-11-21 17:44:25.864063: Pseudo dice [0.8156] +2024-11-21 17:44:25.864139: Epoch time: 18.52 s +2024-11-21 17:44:27.149797: +2024-11-21 17:44:27.150044: Epoch 1297 +2024-11-21 17:44:27.150165: Current learning rate: 0.00853 +2024-11-21 17:44:45.114283: train_loss -0.77 +2024-11-21 17:44:45.114543: val_loss -0.7178 +2024-11-21 17:44:45.114625: Pseudo dice [0.8137] +2024-11-21 17:44:45.114710: Epoch time: 17.97 s +2024-11-21 17:44:45.946155: +2024-11-21 17:44:45.946377: Epoch 1298 +2024-11-21 17:44:45.946486: Current learning rate: 0.00853 +2024-11-21 17:45:04.567792: train_loss -0.7744 +2024-11-21 17:45:04.568070: val_loss -0.7374 +2024-11-21 17:45:04.568177: Pseudo dice [0.8421] +2024-11-21 17:45:04.568262: Epoch time: 18.62 s +2024-11-21 17:45:05.459298: +2024-11-21 17:45:05.459547: Epoch 1299 +2024-11-21 17:45:05.459674: Current learning rate: 0.00853 +2024-11-21 17:45:24.095507: train_loss -0.7789 +2024-11-21 17:45:24.095720: val_loss -0.7474 +2024-11-21 17:45:24.095794: Pseudo dice [0.8379] +2024-11-21 17:45:24.095870: Epoch time: 18.64 s +2024-11-21 17:45:25.270712: +2024-11-21 17:45:25.270945: Epoch 1300 +2024-11-21 17:45:25.271071: Current learning rate: 0.00852 +2024-11-21 17:45:45.139284: train_loss -0.7615 +2024-11-21 17:45:45.139494: val_loss -0.7119 +2024-11-21 17:45:45.139585: Pseudo dice [0.8015] +2024-11-21 17:45:45.139661: Epoch time: 19.87 s +2024-11-21 17:45:45.985260: +2024-11-21 17:45:45.985487: Epoch 1301 +2024-11-21 17:45:45.985600: Current learning rate: 0.00852 +2024-11-21 17:46:04.744769: train_loss -0.7603 +2024-11-21 17:46:04.744978: val_loss -0.7549 +2024-11-21 17:46:04.745090: Pseudo dice [0.8265] +2024-11-21 17:46:04.745203: Epoch time: 18.76 s +2024-11-21 17:46:05.583075: +2024-11-21 17:46:05.583287: Epoch 1302 +2024-11-21 17:46:05.583400: Current learning rate: 0.00852 +2024-11-21 17:46:23.625521: train_loss -0.7652 +2024-11-21 17:46:23.625760: val_loss -0.7544 +2024-11-21 17:46:23.625834: Pseudo dice [0.8311] +2024-11-21 17:46:23.625914: Epoch time: 18.04 s +2024-11-21 17:46:24.609700: +2024-11-21 17:46:24.609937: Epoch 1303 +2024-11-21 17:46:24.610067: Current learning rate: 0.00852 +2024-11-21 17:46:42.581571: train_loss -0.767 +2024-11-21 17:46:42.581773: val_loss -0.7529 +2024-11-21 17:46:42.581846: Pseudo dice [0.8113] +2024-11-21 17:46:42.581923: Epoch time: 17.97 s +2024-11-21 17:46:43.578294: +2024-11-21 17:46:43.578551: Epoch 1304 +2024-11-21 17:46:43.578668: Current learning rate: 0.00852 +2024-11-21 17:47:02.147902: train_loss -0.7716 +2024-11-21 17:47:02.148130: val_loss -0.756 +2024-11-21 17:47:02.148207: Pseudo dice [0.8257] +2024-11-21 17:47:02.148284: Epoch time: 18.57 s +2024-11-21 17:47:02.986825: +2024-11-21 17:47:02.987031: Epoch 1305 +2024-11-21 17:47:02.987151: Current learning rate: 0.00852 +2024-11-21 17:47:22.789274: train_loss -0.7649 +2024-11-21 17:47:22.789527: val_loss -0.7384 +2024-11-21 17:47:22.789601: Pseudo dice [0.8289] +2024-11-21 17:47:22.789681: Epoch time: 19.8 s +2024-11-21 17:47:23.629441: +2024-11-21 17:47:23.629629: Epoch 1306 +2024-11-21 17:47:23.629742: Current learning rate: 0.00852 +2024-11-21 17:47:42.544326: train_loss -0.7613 +2024-11-21 17:47:42.547645: val_loss -0.7532 +2024-11-21 17:47:42.547779: Pseudo dice [0.8213] +2024-11-21 17:47:42.547889: Epoch time: 18.92 s +2024-11-21 17:47:43.433707: +2024-11-21 17:47:43.433945: Epoch 1307 +2024-11-21 17:47:43.434071: Current learning rate: 0.00852 +2024-11-21 17:48:02.004053: train_loss -0.759 +2024-11-21 17:48:02.004372: val_loss -0.7276 +2024-11-21 17:48:02.009525: Pseudo dice [0.8166] +2024-11-21 17:48:02.009766: Epoch time: 18.57 s +2024-11-21 17:48:02.921263: +2024-11-21 17:48:02.921459: Epoch 1308 +2024-11-21 17:48:02.921569: Current learning rate: 0.00852 +2024-11-21 17:48:22.547674: train_loss -0.7705 +2024-11-21 17:48:22.548621: val_loss -0.7493 +2024-11-21 17:48:22.548711: Pseudo dice [0.8197] +2024-11-21 17:48:22.548789: Epoch time: 19.63 s +2024-11-21 17:48:23.386078: +2024-11-21 17:48:23.386306: Epoch 1309 +2024-11-21 17:48:23.386422: Current learning rate: 0.00851 +2024-11-21 17:48:41.914159: train_loss -0.7701 +2024-11-21 17:48:41.919581: val_loss -0.7318 +2024-11-21 17:48:41.919696: Pseudo dice [0.8041] +2024-11-21 17:48:41.919786: Epoch time: 18.53 s +2024-11-21 17:48:42.869490: +2024-11-21 17:48:42.869730: Epoch 1310 +2024-11-21 17:48:42.869845: Current learning rate: 0.00851 +2024-11-21 17:49:01.970802: train_loss -0.7629 +2024-11-21 17:49:01.971020: val_loss -0.7391 +2024-11-21 17:49:01.971096: Pseudo dice [0.825] +2024-11-21 17:49:01.971172: Epoch time: 19.1 s +2024-11-21 17:49:02.835048: +2024-11-21 17:49:02.835274: Epoch 1311 +2024-11-21 17:49:02.835396: Current learning rate: 0.00851 +2024-11-21 17:49:21.394170: train_loss -0.773 +2024-11-21 17:49:21.394369: val_loss -0.7369 +2024-11-21 17:49:21.394441: Pseudo dice [0.8129] +2024-11-21 17:49:21.394515: Epoch time: 18.56 s +2024-11-21 17:49:22.227430: +2024-11-21 17:49:22.227645: Epoch 1312 +2024-11-21 17:49:22.227759: Current learning rate: 0.00851 +2024-11-21 17:49:41.272334: train_loss -0.7714 +2024-11-21 17:49:41.272570: val_loss -0.7385 +2024-11-21 17:49:41.272644: Pseudo dice [0.7974] +2024-11-21 17:49:41.272726: Epoch time: 19.05 s +2024-11-21 17:49:42.105036: +2024-11-21 17:49:42.105244: Epoch 1313 +2024-11-21 17:49:42.105356: Current learning rate: 0.00851 +2024-11-21 17:50:00.224712: train_loss -0.7651 +2024-11-21 17:50:00.224920: val_loss -0.7349 +2024-11-21 17:50:00.225001: Pseudo dice [0.8233] +2024-11-21 17:50:00.225077: Epoch time: 18.12 s +2024-11-21 17:50:01.067293: +2024-11-21 17:50:01.067506: Epoch 1314 +2024-11-21 17:50:01.067620: Current learning rate: 0.00851 +2024-11-21 17:50:19.048872: train_loss -0.7797 +2024-11-21 17:50:19.052673: val_loss -0.7621 +2024-11-21 17:50:19.052758: Pseudo dice [0.847] +2024-11-21 17:50:19.052835: Epoch time: 17.98 s +2024-11-21 17:50:19.920579: +2024-11-21 17:50:19.920901: Epoch 1315 +2024-11-21 17:50:19.921022: Current learning rate: 0.00851 +2024-11-21 17:50:38.983627: train_loss -0.778 +2024-11-21 17:50:38.983837: val_loss -0.7487 +2024-11-21 17:50:38.983915: Pseudo dice [0.8357] +2024-11-21 17:50:38.984010: Epoch time: 19.06 s +2024-11-21 17:50:39.904042: +2024-11-21 17:50:39.904304: Epoch 1316 +2024-11-21 17:50:39.904416: Current learning rate: 0.00851 +2024-11-21 17:50:59.538236: train_loss -0.7679 +2024-11-21 17:50:59.538494: val_loss -0.7422 +2024-11-21 17:50:59.538634: Pseudo dice [0.8302] +2024-11-21 17:50:59.538719: Epoch time: 19.64 s +2024-11-21 17:51:00.383184: +2024-11-21 17:51:00.383384: Epoch 1317 +2024-11-21 17:51:00.383497: Current learning rate: 0.00851 +2024-11-21 17:51:18.638356: train_loss -0.7694 +2024-11-21 17:51:18.638559: val_loss -0.7466 +2024-11-21 17:51:18.638633: Pseudo dice [0.8163] +2024-11-21 17:51:18.638709: Epoch time: 18.26 s +2024-11-21 17:51:19.470291: +2024-11-21 17:51:19.470511: Epoch 1318 +2024-11-21 17:51:19.470626: Current learning rate: 0.0085 +2024-11-21 17:51:38.072161: train_loss -0.7733 +2024-11-21 17:51:38.072378: val_loss -0.7468 +2024-11-21 17:51:38.072455: Pseudo dice [0.8231] +2024-11-21 17:51:38.072539: Epoch time: 18.6 s +2024-11-21 17:51:38.899746: +2024-11-21 17:51:38.899942: Epoch 1319 +2024-11-21 17:51:38.900060: Current learning rate: 0.0085 +2024-11-21 17:51:57.914625: train_loss -0.7731 +2024-11-21 17:51:57.914868: val_loss -0.7537 +2024-11-21 17:51:57.914940: Pseudo dice [0.8407] +2024-11-21 17:51:57.915029: Epoch time: 19.02 s +2024-11-21 17:51:59.196110: +2024-11-21 17:51:59.196321: Epoch 1320 +2024-11-21 17:51:59.196431: Current learning rate: 0.0085 +2024-11-21 17:52:18.637482: train_loss -0.7653 +2024-11-21 17:52:18.637708: val_loss -0.7176 +2024-11-21 17:52:18.637785: Pseudo dice [0.802] +2024-11-21 17:52:18.637865: Epoch time: 19.44 s +2024-11-21 17:52:19.537162: +2024-11-21 17:52:19.537424: Epoch 1321 +2024-11-21 17:52:19.537998: Current learning rate: 0.0085 +2024-11-21 17:52:37.935542: train_loss -0.7572 +2024-11-21 17:52:37.935774: val_loss -0.7501 +2024-11-21 17:52:37.935855: Pseudo dice [0.8088] +2024-11-21 17:52:37.935939: Epoch time: 18.4 s +2024-11-21 17:52:38.976162: +2024-11-21 17:52:38.976370: Epoch 1322 +2024-11-21 17:52:38.976486: Current learning rate: 0.0085 +2024-11-21 17:52:57.963076: train_loss -0.758 +2024-11-21 17:52:57.963317: val_loss -0.7284 +2024-11-21 17:52:57.963397: Pseudo dice [0.8099] +2024-11-21 17:52:57.963478: Epoch time: 18.99 s +2024-11-21 17:52:58.805409: +2024-11-21 17:52:58.805648: Epoch 1323 +2024-11-21 17:52:58.805763: Current learning rate: 0.0085 +2024-11-21 17:53:17.728837: train_loss -0.7581 +2024-11-21 17:53:17.729048: val_loss -0.7385 +2024-11-21 17:53:17.729123: Pseudo dice [0.8176] +2024-11-21 17:53:17.729198: Epoch time: 18.92 s +2024-11-21 17:53:18.667769: +2024-11-21 17:53:18.668044: Epoch 1324 +2024-11-21 17:53:18.668187: Current learning rate: 0.0085 +2024-11-21 17:53:37.000520: train_loss -0.7654 +2024-11-21 17:53:37.000736: val_loss -0.7326 +2024-11-21 17:53:37.000820: Pseudo dice [0.8121] +2024-11-21 17:53:37.000905: Epoch time: 18.33 s +2024-11-21 17:53:37.829535: +2024-11-21 17:53:37.829753: Epoch 1325 +2024-11-21 17:53:37.829868: Current learning rate: 0.0085 +2024-11-21 17:53:56.571831: train_loss -0.7669 +2024-11-21 17:53:56.572040: val_loss -0.7135 +2024-11-21 17:53:56.572118: Pseudo dice [0.8044] +2024-11-21 17:53:56.572201: Epoch time: 18.74 s +2024-11-21 17:53:57.409974: +2024-11-21 17:53:57.410181: Epoch 1326 +2024-11-21 17:53:57.410292: Current learning rate: 0.0085 +2024-11-21 17:54:15.031349: train_loss -0.7761 +2024-11-21 17:54:15.031581: val_loss -0.7432 +2024-11-21 17:54:15.031657: Pseudo dice [0.8098] +2024-11-21 17:54:15.031741: Epoch time: 17.62 s +2024-11-21 17:54:15.870371: +2024-11-21 17:54:15.870566: Epoch 1327 +2024-11-21 17:54:15.870683: Current learning rate: 0.00849 +2024-11-21 17:54:34.206500: train_loss -0.7645 +2024-11-21 17:54:34.211893: val_loss -0.7543 +2024-11-21 17:54:34.211973: Pseudo dice [0.8117] +2024-11-21 17:54:34.212057: Epoch time: 18.34 s +2024-11-21 17:54:35.127927: +2024-11-21 17:54:35.128124: Epoch 1328 +2024-11-21 17:54:35.128237: Current learning rate: 0.00849 +2024-11-21 17:54:53.025727: train_loss -0.7631 +2024-11-21 17:54:53.025932: val_loss -0.744 +2024-11-21 17:54:53.026012: Pseudo dice [0.8125] +2024-11-21 17:54:53.026087: Epoch time: 17.9 s +2024-11-21 17:54:53.849299: +2024-11-21 17:54:53.849498: Epoch 1329 +2024-11-21 17:54:53.849605: Current learning rate: 0.00849 +2024-11-21 17:55:13.143778: train_loss -0.7723 +2024-11-21 17:55:13.144106: val_loss -0.7355 +2024-11-21 17:55:13.144185: Pseudo dice [0.8323] +2024-11-21 17:55:13.144268: Epoch time: 19.3 s +2024-11-21 17:55:13.985469: +2024-11-21 17:55:13.985717: Epoch 1330 +2024-11-21 17:55:13.985827: Current learning rate: 0.00849 +2024-11-21 17:55:32.658818: train_loss -0.7762 +2024-11-21 17:55:32.661297: val_loss -0.7146 +2024-11-21 17:55:32.661428: Pseudo dice [0.8312] +2024-11-21 17:55:32.661505: Epoch time: 18.67 s +2024-11-21 17:55:33.494615: +2024-11-21 17:55:33.494807: Epoch 1331 +2024-11-21 17:55:33.494919: Current learning rate: 0.00849 +2024-11-21 17:55:52.454744: train_loss -0.768 +2024-11-21 17:55:52.455211: val_loss -0.7345 +2024-11-21 17:55:52.455308: Pseudo dice [0.8248] +2024-11-21 17:55:52.455386: Epoch time: 18.96 s +2024-11-21 17:55:53.290511: +2024-11-21 17:55:53.290755: Epoch 1332 +2024-11-21 17:55:53.290872: Current learning rate: 0.00849 +2024-11-21 17:56:11.718744: train_loss -0.7595 +2024-11-21 17:56:11.718982: val_loss -0.7332 +2024-11-21 17:56:11.719065: Pseudo dice [0.833] +2024-11-21 17:56:11.719150: Epoch time: 18.43 s +2024-11-21 17:56:12.557860: +2024-11-21 17:56:12.558090: Epoch 1333 +2024-11-21 17:56:12.558199: Current learning rate: 0.00849 +2024-11-21 17:56:30.298104: train_loss -0.7712 +2024-11-21 17:56:30.298307: val_loss -0.7233 +2024-11-21 17:56:30.298381: Pseudo dice [0.8139] +2024-11-21 17:56:30.298456: Epoch time: 17.74 s +2024-11-21 17:56:31.129305: +2024-11-21 17:56:31.129534: Epoch 1334 +2024-11-21 17:56:31.129642: Current learning rate: 0.00849 +2024-11-21 17:56:50.978775: train_loss -0.7806 +2024-11-21 17:56:50.979012: val_loss -0.732 +2024-11-21 17:56:50.979088: Pseudo dice [0.8377] +2024-11-21 17:56:50.979165: Epoch time: 19.85 s +2024-11-21 17:56:51.842161: +2024-11-21 17:56:51.842391: Epoch 1335 +2024-11-21 17:56:51.842507: Current learning rate: 0.00848 +2024-11-21 17:57:09.635727: train_loss -0.7555 +2024-11-21 17:57:09.641134: val_loss -0.7247 +2024-11-21 17:57:09.641302: Pseudo dice [0.8309] +2024-11-21 17:57:09.641393: Epoch time: 17.79 s +2024-11-21 17:57:10.563712: +2024-11-21 17:57:10.563919: Epoch 1336 +2024-11-21 17:57:10.564035: Current learning rate: 0.00848 +2024-11-21 17:57:29.026884: train_loss -0.7545 +2024-11-21 17:57:29.027123: val_loss -0.7267 +2024-11-21 17:57:29.027199: Pseudo dice [0.8128] +2024-11-21 17:57:29.029408: Epoch time: 18.46 s +2024-11-21 17:57:29.945720: +2024-11-21 17:57:29.945935: Epoch 1337 +2024-11-21 17:57:29.946051: Current learning rate: 0.00848 +2024-11-21 17:57:48.749642: train_loss -0.7613 +2024-11-21 17:57:48.749860: val_loss -0.7367 +2024-11-21 17:57:48.749934: Pseudo dice [0.8159] +2024-11-21 17:57:48.750019: Epoch time: 18.8 s +2024-11-21 17:57:49.664321: +2024-11-21 17:57:49.664553: Epoch 1338 +2024-11-21 17:57:49.664668: Current learning rate: 0.00848 +2024-11-21 17:58:07.783413: train_loss -0.7564 +2024-11-21 17:58:07.783641: val_loss -0.7131 +2024-11-21 17:58:07.783718: Pseudo dice [0.8048] +2024-11-21 17:58:07.783800: Epoch time: 18.12 s +2024-11-21 17:58:08.644280: +2024-11-21 17:58:08.644499: Epoch 1339 +2024-11-21 17:58:08.644616: Current learning rate: 0.00848 +2024-11-21 17:58:28.023788: train_loss -0.7751 +2024-11-21 17:58:28.023999: val_loss -0.7336 +2024-11-21 17:58:28.024081: Pseudo dice [0.8148] +2024-11-21 17:58:28.024159: Epoch time: 19.38 s +2024-11-21 17:58:28.883703: +2024-11-21 17:58:28.883918: Epoch 1340 +2024-11-21 17:58:28.884035: Current learning rate: 0.00848 +2024-11-21 17:58:47.733500: train_loss -0.7632 +2024-11-21 17:58:47.733740: val_loss -0.7191 +2024-11-21 17:58:47.733811: Pseudo dice [0.8206] +2024-11-21 17:58:47.733914: Epoch time: 18.85 s +2024-11-21 17:58:48.582215: +2024-11-21 17:58:48.582400: Epoch 1341 +2024-11-21 17:58:48.582506: Current learning rate: 0.00848 +2024-11-21 17:59:07.409695: train_loss -0.767 +2024-11-21 17:59:07.409953: val_loss -0.7518 +2024-11-21 17:59:07.410038: Pseudo dice [0.8233] +2024-11-21 17:59:07.410116: Epoch time: 18.83 s +2024-11-21 17:59:08.248926: +2024-11-21 17:59:08.249124: Epoch 1342 +2024-11-21 17:59:08.249236: Current learning rate: 0.00848 +2024-11-21 17:59:26.451396: train_loss -0.7721 +2024-11-21 17:59:26.451881: val_loss -0.7376 +2024-11-21 17:59:26.451977: Pseudo dice [0.8147] +2024-11-21 17:59:26.452069: Epoch time: 18.2 s +2024-11-21 17:59:27.276598: +2024-11-21 17:59:27.276803: Epoch 1343 +2024-11-21 17:59:27.276913: Current learning rate: 0.00848 +2024-11-21 17:59:46.303552: train_loss -0.7669 +2024-11-21 17:59:46.303778: val_loss -0.7427 +2024-11-21 17:59:46.303854: Pseudo dice [0.8299] +2024-11-21 17:59:46.303930: Epoch time: 19.03 s +2024-11-21 17:59:47.145852: +2024-11-21 17:59:47.146082: Epoch 1344 +2024-11-21 17:59:47.146199: Current learning rate: 0.00847 +2024-11-21 18:00:06.141013: train_loss -0.7775 +2024-11-21 18:00:06.141220: val_loss -0.7203 +2024-11-21 18:00:06.141294: Pseudo dice [0.8162] +2024-11-21 18:00:06.141381: Epoch time: 19.0 s +2024-11-21 18:00:06.973428: +2024-11-21 18:00:06.973622: Epoch 1345 +2024-11-21 18:00:06.973729: Current learning rate: 0.00847 +2024-11-21 18:00:26.173580: train_loss -0.7716 +2024-11-21 18:00:26.173789: val_loss -0.7606 +2024-11-21 18:00:26.173858: Pseudo dice [0.8208] +2024-11-21 18:00:26.173931: Epoch time: 19.2 s +2024-11-21 18:00:27.104939: +2024-11-21 18:00:27.105165: Epoch 1346 +2024-11-21 18:00:27.105283: Current learning rate: 0.00847 +2024-11-21 18:00:47.174016: train_loss -0.7654 +2024-11-21 18:00:47.174263: val_loss -0.735 +2024-11-21 18:00:47.176821: Pseudo dice [0.8051] +2024-11-21 18:00:47.177001: Epoch time: 20.07 s +2024-11-21 18:00:48.048360: +2024-11-21 18:00:48.048596: Epoch 1347 +2024-11-21 18:00:48.048709: Current learning rate: 0.00847 +2024-11-21 18:01:06.877066: train_loss -0.7642 +2024-11-21 18:01:06.877269: val_loss -0.7433 +2024-11-21 18:01:06.877342: Pseudo dice [0.8225] +2024-11-21 18:01:06.877414: Epoch time: 18.83 s +2024-11-21 18:01:07.712057: +2024-11-21 18:01:07.712258: Epoch 1348 +2024-11-21 18:01:07.712371: Current learning rate: 0.00847 +2024-11-21 18:01:27.588139: train_loss -0.7645 +2024-11-21 18:01:27.588356: val_loss -0.75 +2024-11-21 18:01:27.588434: Pseudo dice [0.8258] +2024-11-21 18:01:27.588509: Epoch time: 19.88 s +2024-11-21 18:01:28.429388: +2024-11-21 18:01:28.429592: Epoch 1349 +2024-11-21 18:01:28.429701: Current learning rate: 0.00847 +2024-11-21 18:01:46.376149: train_loss -0.7648 +2024-11-21 18:01:46.376380: val_loss -0.7206 +2024-11-21 18:01:46.376453: Pseudo dice [0.7993] +2024-11-21 18:01:46.376526: Epoch time: 17.95 s +2024-11-21 18:01:47.390602: +2024-11-21 18:01:47.390801: Epoch 1350 +2024-11-21 18:01:47.390914: Current learning rate: 0.00847 +2024-11-21 18:02:06.547044: train_loss -0.7569 +2024-11-21 18:02:06.547268: val_loss -0.7401 +2024-11-21 18:02:06.547341: Pseudo dice [0.8238] +2024-11-21 18:02:06.547422: Epoch time: 19.16 s +2024-11-21 18:02:07.380547: +2024-11-21 18:02:07.380748: Epoch 1351 +2024-11-21 18:02:07.380875: Current learning rate: 0.00847 +2024-11-21 18:02:26.302295: train_loss -0.7685 +2024-11-21 18:02:26.302494: val_loss -0.7382 +2024-11-21 18:02:26.302568: Pseudo dice [0.8014] +2024-11-21 18:02:26.302643: Epoch time: 18.92 s +2024-11-21 18:02:27.130745: +2024-11-21 18:02:27.130954: Epoch 1352 +2024-11-21 18:02:27.131069: Current learning rate: 0.00847 +2024-11-21 18:02:45.354321: train_loss -0.7725 +2024-11-21 18:02:45.354541: val_loss -0.7573 +2024-11-21 18:02:45.354614: Pseudo dice [0.835] +2024-11-21 18:02:45.354691: Epoch time: 18.22 s +2024-11-21 18:02:46.576186: +2024-11-21 18:02:46.576408: Epoch 1353 +2024-11-21 18:02:46.576517: Current learning rate: 0.00846 +2024-11-21 18:03:06.329026: train_loss -0.7625 +2024-11-21 18:03:06.329296: val_loss -0.736 +2024-11-21 18:03:06.329430: Pseudo dice [0.7957] +2024-11-21 18:03:06.329518: Epoch time: 19.75 s +2024-11-21 18:03:07.168278: +2024-11-21 18:03:07.168489: Epoch 1354 +2024-11-21 18:03:07.168602: Current learning rate: 0.00846 +2024-11-21 18:03:26.850665: train_loss -0.7536 +2024-11-21 18:03:26.850913: val_loss -0.7154 +2024-11-21 18:03:26.850987: Pseudo dice [0.8063] +2024-11-21 18:03:26.851067: Epoch time: 19.68 s +2024-11-21 18:03:27.694081: +2024-11-21 18:03:27.694311: Epoch 1355 +2024-11-21 18:03:27.694425: Current learning rate: 0.00846 +2024-11-21 18:03:46.923946: train_loss -0.7628 +2024-11-21 18:03:46.924166: val_loss -0.7189 +2024-11-21 18:03:46.924240: Pseudo dice [0.8091] +2024-11-21 18:03:46.924318: Epoch time: 19.23 s +2024-11-21 18:03:47.794727: +2024-11-21 18:03:47.794921: Epoch 1356 +2024-11-21 18:03:47.795038: Current learning rate: 0.00846 +2024-11-21 18:04:06.073524: train_loss -0.7641 +2024-11-21 18:04:06.073722: val_loss -0.7441 +2024-11-21 18:04:06.073794: Pseudo dice [0.8139] +2024-11-21 18:04:06.073867: Epoch time: 18.28 s +2024-11-21 18:04:06.916013: +2024-11-21 18:04:06.916235: Epoch 1357 +2024-11-21 18:04:06.916348: Current learning rate: 0.00846 +2024-11-21 18:04:26.163653: train_loss -0.7666 +2024-11-21 18:04:26.163909: val_loss -0.7454 +2024-11-21 18:04:26.163990: Pseudo dice [0.8307] +2024-11-21 18:04:26.164084: Epoch time: 19.25 s +2024-11-21 18:04:27.007809: +2024-11-21 18:04:27.008088: Epoch 1358 +2024-11-21 18:04:27.008204: Current learning rate: 0.00846 +2024-11-21 18:04:45.191516: train_loss -0.761 +2024-11-21 18:04:45.191729: val_loss -0.7214 +2024-11-21 18:04:45.191803: Pseudo dice [0.8182] +2024-11-21 18:04:45.191879: Epoch time: 18.18 s +2024-11-21 18:04:46.140038: +2024-11-21 18:04:46.140247: Epoch 1359 +2024-11-21 18:04:46.140381: Current learning rate: 0.00846 +2024-11-21 18:05:04.297415: train_loss -0.7477 +2024-11-21 18:05:04.297633: val_loss -0.7598 +2024-11-21 18:05:04.297704: Pseudo dice [0.8316] +2024-11-21 18:05:04.300015: Epoch time: 18.16 s +2024-11-21 18:05:05.303240: +2024-11-21 18:05:05.303464: Epoch 1360 +2024-11-21 18:05:05.303578: Current learning rate: 0.00846 +2024-11-21 18:05:23.814848: train_loss -0.7655 +2024-11-21 18:05:23.815137: val_loss -0.7402 +2024-11-21 18:05:23.815216: Pseudo dice [0.8194] +2024-11-21 18:05:23.815292: Epoch time: 18.51 s +2024-11-21 18:05:24.659451: +2024-11-21 18:05:24.659640: Epoch 1361 +2024-11-21 18:05:24.659755: Current learning rate: 0.00845 +2024-11-21 18:05:42.926028: train_loss -0.7656 +2024-11-21 18:05:42.926269: val_loss -0.7605 +2024-11-21 18:05:42.926344: Pseudo dice [0.8393] +2024-11-21 18:05:42.926423: Epoch time: 18.27 s +2024-11-21 18:05:43.767308: +2024-11-21 18:05:43.767514: Epoch 1362 +2024-11-21 18:05:43.767627: Current learning rate: 0.00845 +2024-11-21 18:06:02.616971: train_loss -0.7726 +2024-11-21 18:06:02.617222: val_loss -0.739 +2024-11-21 18:06:02.617301: Pseudo dice [0.821] +2024-11-21 18:06:02.617378: Epoch time: 18.85 s +2024-11-21 18:06:03.588082: +2024-11-21 18:06:03.588279: Epoch 1363 +2024-11-21 18:06:03.588390: Current learning rate: 0.00845 +2024-11-21 18:06:22.683872: train_loss -0.7646 +2024-11-21 18:06:22.684096: val_loss -0.7383 +2024-11-21 18:06:22.684172: Pseudo dice [0.83] +2024-11-21 18:06:22.684246: Epoch time: 19.1 s +2024-11-21 18:06:23.590780: +2024-11-21 18:06:23.590955: Epoch 1364 +2024-11-21 18:06:23.591065: Current learning rate: 0.00845 +2024-11-21 18:06:42.815053: train_loss -0.7721 +2024-11-21 18:06:42.815295: val_loss -0.7313 +2024-11-21 18:06:42.815372: Pseudo dice [0.8379] +2024-11-21 18:06:42.815457: Epoch time: 19.23 s +2024-11-21 18:06:44.070616: +2024-11-21 18:06:44.070932: Epoch 1365 +2024-11-21 18:06:44.071045: Current learning rate: 0.00845 +2024-11-21 18:07:02.824030: train_loss -0.7658 +2024-11-21 18:07:02.824268: val_loss -0.7397 +2024-11-21 18:07:02.824344: Pseudo dice [0.8289] +2024-11-21 18:07:02.824426: Epoch time: 18.75 s +2024-11-21 18:07:03.669883: +2024-11-21 18:07:03.670117: Epoch 1366 +2024-11-21 18:07:03.670236: Current learning rate: 0.00845 +2024-11-21 18:07:22.625793: train_loss -0.7731 +2024-11-21 18:07:22.626010: val_loss -0.7388 +2024-11-21 18:07:22.626083: Pseudo dice [0.8161] +2024-11-21 18:07:22.626159: Epoch time: 18.96 s +2024-11-21 18:07:23.564250: +2024-11-21 18:07:23.564454: Epoch 1367 +2024-11-21 18:07:23.564568: Current learning rate: 0.00845 +2024-11-21 18:07:42.135646: train_loss -0.7714 +2024-11-21 18:07:42.135853: val_loss -0.7492 +2024-11-21 18:07:42.137477: Pseudo dice [0.8357] +2024-11-21 18:07:42.137571: Epoch time: 18.57 s +2024-11-21 18:07:43.196085: +2024-11-21 18:07:43.196320: Epoch 1368 +2024-11-21 18:07:43.196435: Current learning rate: 0.00845 +2024-11-21 18:08:02.001051: train_loss -0.7629 +2024-11-21 18:08:02.001301: val_loss -0.7159 +2024-11-21 18:08:02.001381: Pseudo dice [0.8177] +2024-11-21 18:08:02.001464: Epoch time: 18.81 s +2024-11-21 18:08:02.850857: +2024-11-21 18:08:02.851057: Epoch 1369 +2024-11-21 18:08:02.851170: Current learning rate: 0.00845 +2024-11-21 18:08:20.109541: train_loss -0.7583 +2024-11-21 18:08:20.109760: val_loss -0.7276 +2024-11-21 18:08:20.111182: Pseudo dice [0.8287] +2024-11-21 18:08:20.111306: Epoch time: 17.26 s +2024-11-21 18:08:21.072811: +2024-11-21 18:08:21.073039: Epoch 1370 +2024-11-21 18:08:21.073153: Current learning rate: 0.00844 +2024-11-21 18:08:40.489936: train_loss -0.762 +2024-11-21 18:08:40.490160: val_loss -0.7408 +2024-11-21 18:08:40.490237: Pseudo dice [0.8244] +2024-11-21 18:08:40.490318: Epoch time: 19.42 s +2024-11-21 18:08:41.334987: +2024-11-21 18:08:41.335203: Epoch 1371 +2024-11-21 18:08:41.335309: Current learning rate: 0.00844 +2024-11-21 18:08:59.322567: train_loss -0.7663 +2024-11-21 18:08:59.322798: val_loss -0.7377 +2024-11-21 18:08:59.322885: Pseudo dice [0.8316] +2024-11-21 18:08:59.322964: Epoch time: 17.99 s +2024-11-21 18:09:00.162778: +2024-11-21 18:09:00.175072: Epoch 1372 +2024-11-21 18:09:00.175189: Current learning rate: 0.00844 +2024-11-21 18:09:18.852050: train_loss -0.7708 +2024-11-21 18:09:18.852285: val_loss -0.7573 +2024-11-21 18:09:18.852357: Pseudo dice [0.8287] +2024-11-21 18:09:18.852439: Epoch time: 18.69 s +2024-11-21 18:09:19.699061: +2024-11-21 18:09:19.699272: Epoch 1373 +2024-11-21 18:09:19.699384: Current learning rate: 0.00844 +2024-11-21 18:09:38.738171: train_loss -0.7592 +2024-11-21 18:09:38.738379: val_loss -0.7224 +2024-11-21 18:09:38.738456: Pseudo dice [0.7805] +2024-11-21 18:09:38.738531: Epoch time: 19.04 s +2024-11-21 18:09:39.581185: +2024-11-21 18:09:39.581372: Epoch 1374 +2024-11-21 18:09:39.581484: Current learning rate: 0.00844 +2024-11-21 18:09:57.725152: train_loss -0.767 +2024-11-21 18:09:57.725363: val_loss -0.7381 +2024-11-21 18:09:57.725439: Pseudo dice [0.8152] +2024-11-21 18:09:57.725514: Epoch time: 18.14 s +2024-11-21 18:09:58.581296: +2024-11-21 18:09:58.581482: Epoch 1375 +2024-11-21 18:09:58.581590: Current learning rate: 0.00844 +2024-11-21 18:10:16.636290: train_loss -0.7723 +2024-11-21 18:10:16.636526: val_loss -0.7294 +2024-11-21 18:10:16.636600: Pseudo dice [0.8122] +2024-11-21 18:10:16.636682: Epoch time: 18.06 s +2024-11-21 18:10:17.873652: +2024-11-21 18:10:17.873875: Epoch 1376 +2024-11-21 18:10:17.874075: Current learning rate: 0.00844 +2024-11-21 18:10:37.818241: train_loss -0.7624 +2024-11-21 18:10:37.818460: val_loss -0.7182 +2024-11-21 18:10:37.823729: Pseudo dice [0.8238] +2024-11-21 18:10:37.823847: Epoch time: 19.95 s +2024-11-21 18:10:38.704747: +2024-11-21 18:10:38.705024: Epoch 1377 +2024-11-21 18:10:38.705141: Current learning rate: 0.00844 +2024-11-21 18:10:57.560974: train_loss -0.7546 +2024-11-21 18:10:57.563366: val_loss -0.7397 +2024-11-21 18:10:57.563485: Pseudo dice [0.8267] +2024-11-21 18:10:57.563562: Epoch time: 18.86 s +2024-11-21 18:10:58.576535: +2024-11-21 18:10:58.576739: Epoch 1378 +2024-11-21 18:10:58.576851: Current learning rate: 0.00844 +2024-11-21 18:11:17.384938: train_loss -0.7622 +2024-11-21 18:11:17.385194: val_loss -0.7197 +2024-11-21 18:11:17.385274: Pseudo dice [0.8045] +2024-11-21 18:11:17.385356: Epoch time: 18.81 s +2024-11-21 18:11:18.236176: +2024-11-21 18:11:18.236385: Epoch 1379 +2024-11-21 18:11:18.236501: Current learning rate: 0.00843 +2024-11-21 18:11:36.730956: train_loss -0.7629 +2024-11-21 18:11:36.731200: val_loss -0.7598 +2024-11-21 18:11:36.731279: Pseudo dice [0.8433] +2024-11-21 18:11:36.731362: Epoch time: 18.5 s +2024-11-21 18:11:37.583097: +2024-11-21 18:11:37.583322: Epoch 1380 +2024-11-21 18:11:37.583435: Current learning rate: 0.00843 +2024-11-21 18:11:57.214051: train_loss -0.7629 +2024-11-21 18:11:57.214266: val_loss -0.7149 +2024-11-21 18:11:57.214339: Pseudo dice [0.8015] +2024-11-21 18:11:57.214416: Epoch time: 19.63 s +2024-11-21 18:11:58.075600: +2024-11-21 18:11:58.075800: Epoch 1381 +2024-11-21 18:11:58.075909: Current learning rate: 0.00843 +2024-11-21 18:12:15.648487: train_loss -0.7784 +2024-11-21 18:12:15.648698: val_loss -0.7436 +2024-11-21 18:12:15.648776: Pseudo dice [0.8162] +2024-11-21 18:12:15.648854: Epoch time: 17.57 s +2024-11-21 18:12:16.492226: +2024-11-21 18:12:16.492433: Epoch 1382 +2024-11-21 18:12:16.492548: Current learning rate: 0.00843 +2024-11-21 18:12:36.382143: train_loss -0.7806 +2024-11-21 18:12:36.382358: val_loss -0.7252 +2024-11-21 18:12:36.382444: Pseudo dice [0.8038] +2024-11-21 18:12:36.382552: Epoch time: 19.89 s +2024-11-21 18:12:37.240292: +2024-11-21 18:12:37.240506: Epoch 1383 +2024-11-21 18:12:37.240612: Current learning rate: 0.00843 +2024-11-21 18:12:56.053565: train_loss -0.7694 +2024-11-21 18:12:56.053800: val_loss -0.7439 +2024-11-21 18:12:56.053873: Pseudo dice [0.8274] +2024-11-21 18:12:56.053951: Epoch time: 18.81 s +2024-11-21 18:12:56.967428: +2024-11-21 18:12:56.967626: Epoch 1384 +2024-11-21 18:12:56.967736: Current learning rate: 0.00843 +2024-11-21 18:13:15.592282: train_loss -0.7738 +2024-11-21 18:13:15.592499: val_loss -0.7221 +2024-11-21 18:13:15.592580: Pseudo dice [0.8237] +2024-11-21 18:13:15.594218: Epoch time: 18.63 s +2024-11-21 18:13:16.500599: +2024-11-21 18:13:16.500816: Epoch 1385 +2024-11-21 18:13:16.500931: Current learning rate: 0.00843 +2024-11-21 18:13:35.108497: train_loss -0.7741 +2024-11-21 18:13:35.108701: val_loss -0.7285 +2024-11-21 18:13:35.108776: Pseudo dice [0.8231] +2024-11-21 18:13:35.108852: Epoch time: 18.61 s +2024-11-21 18:13:35.939839: +2024-11-21 18:13:35.940223: Epoch 1386 +2024-11-21 18:13:35.940411: Current learning rate: 0.00843 +2024-11-21 18:13:54.364611: train_loss -0.7565 +2024-11-21 18:13:54.364841: val_loss -0.7261 +2024-11-21 18:13:54.364912: Pseudo dice [0.8066] +2024-11-21 18:13:54.365000: Epoch time: 18.43 s +2024-11-21 18:13:55.208662: +2024-11-21 18:13:55.208869: Epoch 1387 +2024-11-21 18:13:55.208982: Current learning rate: 0.00843 +2024-11-21 18:14:14.139495: train_loss -0.7655 +2024-11-21 18:14:14.139704: val_loss -0.7424 +2024-11-21 18:14:14.139778: Pseudo dice [0.8374] +2024-11-21 18:14:14.139868: Epoch time: 18.93 s +2024-11-21 18:14:15.427037: +2024-11-21 18:14:15.427253: Epoch 1388 +2024-11-21 18:14:15.427364: Current learning rate: 0.00842 +2024-11-21 18:14:34.436464: train_loss -0.7785 +2024-11-21 18:14:34.436675: val_loss -0.7216 +2024-11-21 18:14:34.436747: Pseudo dice [0.8241] +2024-11-21 18:14:34.436821: Epoch time: 19.01 s +2024-11-21 18:14:35.268740: +2024-11-21 18:14:35.268979: Epoch 1389 +2024-11-21 18:14:35.269096: Current learning rate: 0.00842 +2024-11-21 18:14:54.021724: train_loss -0.7713 +2024-11-21 18:14:54.021973: val_loss -0.7502 +2024-11-21 18:14:54.022065: Pseudo dice [0.8159] +2024-11-21 18:14:54.022153: Epoch time: 18.75 s +2024-11-21 18:14:54.875962: +2024-11-21 18:14:54.876211: Epoch 1390 +2024-11-21 18:14:54.876326: Current learning rate: 0.00842 +2024-11-21 18:15:13.479579: train_loss -0.7624 +2024-11-21 18:15:13.479832: val_loss -0.7265 +2024-11-21 18:15:13.479909: Pseudo dice [0.829] +2024-11-21 18:15:13.479989: Epoch time: 18.6 s +2024-11-21 18:15:14.348233: +2024-11-21 18:15:14.348434: Epoch 1391 +2024-11-21 18:15:14.348549: Current learning rate: 0.00842 +2024-11-21 18:15:33.468510: train_loss -0.7672 +2024-11-21 18:15:33.468781: val_loss -0.7622 +2024-11-21 18:15:33.468857: Pseudo dice [0.8277] +2024-11-21 18:15:33.468931: Epoch time: 19.12 s +2024-11-21 18:15:34.307009: +2024-11-21 18:15:34.307211: Epoch 1392 +2024-11-21 18:15:34.307316: Current learning rate: 0.00842 +2024-11-21 18:15:52.604443: train_loss -0.7692 +2024-11-21 18:15:52.604696: val_loss -0.7535 +2024-11-21 18:15:52.604776: Pseudo dice [0.8288] +2024-11-21 18:15:52.604859: Epoch time: 18.3 s +2024-11-21 18:15:53.449353: +2024-11-21 18:15:53.449559: Epoch 1393 +2024-11-21 18:15:53.449677: Current learning rate: 0.00842 +2024-11-21 18:16:12.275084: train_loss -0.7641 +2024-11-21 18:16:12.277673: val_loss -0.7325 +2024-11-21 18:16:12.277776: Pseudo dice [0.8178] +2024-11-21 18:16:12.277862: Epoch time: 18.82 s +2024-11-21 18:16:13.231637: +2024-11-21 18:16:13.231843: Epoch 1394 +2024-11-21 18:16:13.231960: Current learning rate: 0.00842 +2024-11-21 18:16:31.778045: train_loss -0.7737 +2024-11-21 18:16:31.778248: val_loss -0.7072 +2024-11-21 18:16:31.778325: Pseudo dice [0.814] +2024-11-21 18:16:31.778408: Epoch time: 18.55 s +2024-11-21 18:16:32.632382: +2024-11-21 18:16:32.632582: Epoch 1395 +2024-11-21 18:16:32.632690: Current learning rate: 0.00842 +2024-11-21 18:16:51.127192: train_loss -0.7597 +2024-11-21 18:16:51.127411: val_loss -0.7168 +2024-11-21 18:16:51.127487: Pseudo dice [0.8191] +2024-11-21 18:16:51.127564: Epoch time: 18.5 s +2024-11-21 18:16:52.019392: +2024-11-21 18:16:52.019592: Epoch 1396 +2024-11-21 18:16:52.019705: Current learning rate: 0.00841 +2024-11-21 18:17:10.033341: train_loss -0.764 +2024-11-21 18:17:10.033576: val_loss -0.7264 +2024-11-21 18:17:10.033645: Pseudo dice [0.785] +2024-11-21 18:17:10.033724: Epoch time: 18.01 s +2024-11-21 18:17:10.887821: +2024-11-21 18:17:10.888027: Epoch 1397 +2024-11-21 18:17:10.888139: Current learning rate: 0.00841 +2024-11-21 18:17:30.448637: train_loss -0.7682 +2024-11-21 18:17:30.448859: val_loss -0.7545 +2024-11-21 18:17:30.448934: Pseudo dice [0.8349] +2024-11-21 18:17:30.449016: Epoch time: 19.56 s +2024-11-21 18:17:31.301187: +2024-11-21 18:17:31.301376: Epoch 1398 +2024-11-21 18:17:31.301491: Current learning rate: 0.00841 +2024-11-21 18:17:50.359870: train_loss -0.7647 +2024-11-21 18:17:50.360080: val_loss -0.7438 +2024-11-21 18:17:50.360155: Pseudo dice [0.8259] +2024-11-21 18:17:50.360233: Epoch time: 19.06 s +2024-11-21 18:17:51.703191: +2024-11-21 18:17:51.703429: Epoch 1399 +2024-11-21 18:17:51.703544: Current learning rate: 0.00841 +2024-11-21 18:18:10.863228: train_loss -0.7709 +2024-11-21 18:18:10.863475: val_loss -0.7444 +2024-11-21 18:18:10.863553: Pseudo dice [0.8262] +2024-11-21 18:18:10.863644: Epoch time: 19.16 s +2024-11-21 18:18:11.889477: +2024-11-21 18:18:11.889721: Epoch 1400 +2024-11-21 18:18:11.889839: Current learning rate: 0.00841 +2024-11-21 18:18:31.457296: train_loss -0.7644 +2024-11-21 18:18:31.457523: val_loss -0.7202 +2024-11-21 18:18:31.457603: Pseudo dice [0.8177] +2024-11-21 18:18:31.457680: Epoch time: 19.57 s +2024-11-21 18:18:32.303915: +2024-11-21 18:18:32.304136: Epoch 1401 +2024-11-21 18:18:32.304246: Current learning rate: 0.00841 +2024-11-21 18:18:51.606613: train_loss -0.7573 +2024-11-21 18:18:51.606823: val_loss -0.7478 +2024-11-21 18:18:51.606894: Pseudo dice [0.8241] +2024-11-21 18:18:51.606974: Epoch time: 19.3 s +2024-11-21 18:18:52.449212: +2024-11-21 18:18:52.449412: Epoch 1402 +2024-11-21 18:18:52.449537: Current learning rate: 0.00841 +2024-11-21 18:19:10.404572: train_loss -0.7649 +2024-11-21 18:19:10.404784: val_loss -0.7628 +2024-11-21 18:19:10.404859: Pseudo dice [0.8269] +2024-11-21 18:19:10.404937: Epoch time: 17.96 s +2024-11-21 18:19:11.256796: +2024-11-21 18:19:11.257031: Epoch 1403 +2024-11-21 18:19:11.257145: Current learning rate: 0.00841 +2024-11-21 18:19:30.679527: train_loss -0.7665 +2024-11-21 18:19:30.679797: val_loss -0.7046 +2024-11-21 18:19:30.679874: Pseudo dice [0.8035] +2024-11-21 18:19:30.679956: Epoch time: 19.42 s +2024-11-21 18:19:31.536863: +2024-11-21 18:19:31.537159: Epoch 1404 +2024-11-21 18:19:31.537270: Current learning rate: 0.00841 +2024-11-21 18:19:49.502450: train_loss -0.7626 +2024-11-21 18:19:49.502697: val_loss -0.7378 +2024-11-21 18:19:49.502769: Pseudo dice [0.8251] +2024-11-21 18:19:49.502843: Epoch time: 17.97 s +2024-11-21 18:19:50.393272: +2024-11-21 18:19:50.393495: Epoch 1405 +2024-11-21 18:19:50.393616: Current learning rate: 0.0084 +2024-11-21 18:20:10.020257: train_loss -0.7726 +2024-11-21 18:20:10.020523: val_loss -0.7328 +2024-11-21 18:20:10.020602: Pseudo dice [0.8205] +2024-11-21 18:20:10.020679: Epoch time: 19.63 s +2024-11-21 18:20:10.872385: +2024-11-21 18:20:10.872603: Epoch 1406 +2024-11-21 18:20:10.872717: Current learning rate: 0.0084 +2024-11-21 18:20:30.337915: train_loss -0.7617 +2024-11-21 18:20:30.338124: val_loss -0.7447 +2024-11-21 18:20:30.338198: Pseudo dice [0.816] +2024-11-21 18:20:30.338274: Epoch time: 19.47 s +2024-11-21 18:20:31.186712: +2024-11-21 18:20:31.187029: Epoch 1407 +2024-11-21 18:20:31.187157: Current learning rate: 0.0084 +2024-11-21 18:20:50.040048: train_loss -0.768 +2024-11-21 18:20:50.040374: val_loss -0.7619 +2024-11-21 18:20:50.040465: Pseudo dice [0.8222] +2024-11-21 18:20:50.040552: Epoch time: 18.85 s +2024-11-21 18:20:50.893207: +2024-11-21 18:20:50.893457: Epoch 1408 +2024-11-21 18:20:50.893571: Current learning rate: 0.0084 +2024-11-21 18:21:08.746701: train_loss -0.7676 +2024-11-21 18:21:08.746933: val_loss -0.7065 +2024-11-21 18:21:08.747019: Pseudo dice [0.813] +2024-11-21 18:21:08.747097: Epoch time: 17.85 s +2024-11-21 18:21:09.741834: +2024-11-21 18:21:09.742112: Epoch 1409 +2024-11-21 18:21:09.742220: Current learning rate: 0.0084 +2024-11-21 18:21:28.196975: train_loss -0.7623 +2024-11-21 18:21:28.197196: val_loss -0.7272 +2024-11-21 18:21:28.197268: Pseudo dice [0.7916] +2024-11-21 18:21:28.197345: Epoch time: 18.46 s +2024-11-21 18:21:29.488478: +2024-11-21 18:21:29.488712: Epoch 1410 +2024-11-21 18:21:29.488827: Current learning rate: 0.0084 +2024-11-21 18:21:48.783761: train_loss -0.7635 +2024-11-21 18:21:48.784044: val_loss -0.7385 +2024-11-21 18:21:48.784120: Pseudo dice [0.8177] +2024-11-21 18:21:48.784200: Epoch time: 19.3 s +2024-11-21 18:21:49.637096: +2024-11-21 18:21:49.637361: Epoch 1411 +2024-11-21 18:21:49.637586: Current learning rate: 0.0084 +2024-11-21 18:22:08.930319: train_loss -0.7608 +2024-11-21 18:22:08.930544: val_loss -0.7256 +2024-11-21 18:22:08.930618: Pseudo dice [0.8227] +2024-11-21 18:22:08.930695: Epoch time: 19.29 s +2024-11-21 18:22:09.898901: +2024-11-21 18:22:09.899119: Epoch 1412 +2024-11-21 18:22:09.899230: Current learning rate: 0.0084 +2024-11-21 18:22:28.371224: train_loss -0.7659 +2024-11-21 18:22:28.371480: val_loss -0.7572 +2024-11-21 18:22:28.371558: Pseudo dice [0.8273] +2024-11-21 18:22:28.371638: Epoch time: 18.47 s +2024-11-21 18:22:29.224408: +2024-11-21 18:22:29.224639: Epoch 1413 +2024-11-21 18:22:29.224756: Current learning rate: 0.0084 +2024-11-21 18:22:47.260272: train_loss -0.7695 +2024-11-21 18:22:47.260495: val_loss -0.7293 +2024-11-21 18:22:47.260569: Pseudo dice [0.8064] +2024-11-21 18:22:47.260649: Epoch time: 18.04 s +2024-11-21 18:22:48.129535: +2024-11-21 18:22:48.129741: Epoch 1414 +2024-11-21 18:22:48.129851: Current learning rate: 0.00839 +2024-11-21 18:23:07.431554: train_loss -0.7728 +2024-11-21 18:23:07.431804: val_loss -0.7079 +2024-11-21 18:23:07.431880: Pseudo dice [0.8038] +2024-11-21 18:23:07.431958: Epoch time: 19.3 s +2024-11-21 18:23:08.286551: +2024-11-21 18:23:08.286819: Epoch 1415 +2024-11-21 18:23:08.286936: Current learning rate: 0.00839 +2024-11-21 18:23:25.949825: train_loss -0.7779 +2024-11-21 18:23:25.950059: val_loss -0.7297 +2024-11-21 18:23:25.950147: Pseudo dice [0.8319] +2024-11-21 18:23:25.950231: Epoch time: 17.66 s +2024-11-21 18:23:26.792875: +2024-11-21 18:23:26.793085: Epoch 1416 +2024-11-21 18:23:26.793192: Current learning rate: 0.00839 +2024-11-21 18:23:45.542917: train_loss -0.7799 +2024-11-21 18:23:45.543129: val_loss -0.7568 +2024-11-21 18:23:45.543204: Pseudo dice [0.8337] +2024-11-21 18:23:45.543278: Epoch time: 18.75 s +2024-11-21 18:23:46.390411: +2024-11-21 18:23:46.390611: Epoch 1417 +2024-11-21 18:23:46.390726: Current learning rate: 0.00839 +2024-11-21 18:24:04.810534: train_loss -0.7712 +2024-11-21 18:24:04.810766: val_loss -0.7305 +2024-11-21 18:24:04.810838: Pseudo dice [0.8183] +2024-11-21 18:24:04.810922: Epoch time: 18.42 s +2024-11-21 18:24:05.652194: +2024-11-21 18:24:05.652407: Epoch 1418 +2024-11-21 18:24:05.652519: Current learning rate: 0.00839 +2024-11-21 18:24:24.131832: train_loss -0.7618 +2024-11-21 18:24:24.132057: val_loss -0.7517 +2024-11-21 18:24:24.132129: Pseudo dice [0.833] +2024-11-21 18:24:24.132204: Epoch time: 18.48 s +2024-11-21 18:24:25.024115: +2024-11-21 18:24:25.024522: Epoch 1419 +2024-11-21 18:24:25.024638: Current learning rate: 0.00839 +2024-11-21 18:24:43.394344: train_loss -0.7616 +2024-11-21 18:24:43.394578: val_loss -0.7425 +2024-11-21 18:24:43.394655: Pseudo dice [0.8348] +2024-11-21 18:24:43.394781: Epoch time: 18.37 s +2024-11-21 18:24:44.255126: +2024-11-21 18:24:44.255327: Epoch 1420 +2024-11-21 18:24:44.255437: Current learning rate: 0.00839 +2024-11-21 18:25:03.334189: train_loss -0.7699 +2024-11-21 18:25:03.335212: val_loss -0.724 +2024-11-21 18:25:03.335299: Pseudo dice [0.8121] +2024-11-21 18:25:03.335381: Epoch time: 19.08 s +2024-11-21 18:25:04.557437: +2024-11-21 18:25:04.557664: Epoch 1421 +2024-11-21 18:25:04.557780: Current learning rate: 0.00839 +2024-11-21 18:25:23.085720: train_loss -0.7727 +2024-11-21 18:25:23.085978: val_loss -0.7294 +2024-11-21 18:25:23.086080: Pseudo dice [0.8389] +2024-11-21 18:25:23.086175: Epoch time: 18.53 s +2024-11-21 18:25:23.929237: +2024-11-21 18:25:23.929465: Epoch 1422 +2024-11-21 18:25:23.929572: Current learning rate: 0.00839 +2024-11-21 18:25:42.887990: train_loss -0.7754 +2024-11-21 18:25:42.890683: val_loss -0.7281 +2024-11-21 18:25:42.890842: Pseudo dice [0.812] +2024-11-21 18:25:42.892750: Epoch time: 18.96 s +2024-11-21 18:25:43.794794: +2024-11-21 18:25:43.795018: Epoch 1423 +2024-11-21 18:25:43.795136: Current learning rate: 0.00838 +2024-11-21 18:26:02.305699: train_loss -0.7646 +2024-11-21 18:26:02.305930: val_loss -0.7424 +2024-11-21 18:26:02.306013: Pseudo dice [0.7931] +2024-11-21 18:26:02.306099: Epoch time: 18.51 s +2024-11-21 18:26:03.152046: +2024-11-21 18:26:03.152271: Epoch 1424 +2024-11-21 18:26:03.152388: Current learning rate: 0.00838 +2024-11-21 18:26:22.754205: train_loss -0.7587 +2024-11-21 18:26:22.754423: val_loss -0.7564 +2024-11-21 18:26:22.754499: Pseudo dice [0.8177] +2024-11-21 18:26:22.754589: Epoch time: 19.6 s +2024-11-21 18:26:23.604631: +2024-11-21 18:26:23.604862: Epoch 1425 +2024-11-21 18:26:23.604980: Current learning rate: 0.00838 +2024-11-21 18:26:43.278120: train_loss -0.7552 +2024-11-21 18:26:43.278381: val_loss -0.727 +2024-11-21 18:26:43.278457: Pseudo dice [0.8172] +2024-11-21 18:26:43.278535: Epoch time: 19.67 s +2024-11-21 18:26:44.212304: +2024-11-21 18:26:44.212504: Epoch 1426 +2024-11-21 18:26:44.212615: Current learning rate: 0.00838 +2024-11-21 18:27:02.141024: train_loss -0.7581 +2024-11-21 18:27:02.141234: val_loss -0.7261 +2024-11-21 18:27:02.141310: Pseudo dice [0.8208] +2024-11-21 18:27:02.141392: Epoch time: 17.93 s +2024-11-21 18:27:02.984137: +2024-11-21 18:27:02.984356: Epoch 1427 +2024-11-21 18:27:02.984466: Current learning rate: 0.00838 +2024-11-21 18:27:21.205892: train_loss -0.7676 +2024-11-21 18:27:21.206146: val_loss -0.7308 +2024-11-21 18:27:21.206221: Pseudo dice [0.8258] +2024-11-21 18:27:21.206302: Epoch time: 18.22 s +2024-11-21 18:27:22.053000: +2024-11-21 18:27:22.053260: Epoch 1428 +2024-11-21 18:27:22.053379: Current learning rate: 0.00838 +2024-11-21 18:27:41.027154: train_loss -0.776 +2024-11-21 18:27:41.027364: val_loss -0.754 +2024-11-21 18:27:41.027437: Pseudo dice [0.8194] +2024-11-21 18:27:41.027512: Epoch time: 18.97 s +2024-11-21 18:27:41.871044: +2024-11-21 18:27:41.871273: Epoch 1429 +2024-11-21 18:27:41.871383: Current learning rate: 0.00838 +2024-11-21 18:28:00.880613: train_loss -0.7544 +2024-11-21 18:28:00.880822: val_loss -0.7248 +2024-11-21 18:28:00.880918: Pseudo dice [0.8244] +2024-11-21 18:28:00.881011: Epoch time: 19.01 s +2024-11-21 18:28:01.722956: +2024-11-21 18:28:01.723169: Epoch 1430 +2024-11-21 18:28:01.723279: Current learning rate: 0.00838 +2024-11-21 18:28:19.822197: train_loss -0.7603 +2024-11-21 18:28:19.822418: val_loss -0.7198 +2024-11-21 18:28:19.822490: Pseudo dice [0.8172] +2024-11-21 18:28:19.822569: Epoch time: 18.1 s +2024-11-21 18:28:20.699326: +2024-11-21 18:28:20.699553: Epoch 1431 +2024-11-21 18:28:20.699662: Current learning rate: 0.00837 +2024-11-21 18:28:38.918287: train_loss -0.7435 +2024-11-21 18:28:38.918506: val_loss -0.7112 +2024-11-21 18:28:38.918578: Pseudo dice [0.8263] +2024-11-21 18:28:38.920912: Epoch time: 18.22 s +2024-11-21 18:28:40.247076: +2024-11-21 18:28:40.247276: Epoch 1432 +2024-11-21 18:28:40.247388: Current learning rate: 0.00837 +2024-11-21 18:28:59.761775: train_loss -0.7604 +2024-11-21 18:28:59.762001: val_loss -0.7148 +2024-11-21 18:28:59.762075: Pseudo dice [0.8207] +2024-11-21 18:28:59.762149: Epoch time: 19.52 s +2024-11-21 18:29:00.608634: +2024-11-21 18:29:00.608845: Epoch 1433 +2024-11-21 18:29:00.608956: Current learning rate: 0.00837 +2024-11-21 18:29:20.100807: train_loss -0.7695 +2024-11-21 18:29:20.101018: val_loss -0.7296 +2024-11-21 18:29:20.101095: Pseudo dice [0.8132] +2024-11-21 18:29:20.101178: Epoch time: 19.49 s +2024-11-21 18:29:21.000212: +2024-11-21 18:29:21.000471: Epoch 1434 +2024-11-21 18:29:21.000584: Current learning rate: 0.00837 +2024-11-21 18:29:38.805980: train_loss -0.7643 +2024-11-21 18:29:38.806228: val_loss -0.7253 +2024-11-21 18:29:38.806324: Pseudo dice [0.8192] +2024-11-21 18:29:38.806407: Epoch time: 17.81 s +2024-11-21 18:29:39.655131: +2024-11-21 18:29:39.655328: Epoch 1435 +2024-11-21 18:29:39.655439: Current learning rate: 0.00837 +2024-11-21 18:29:59.249938: train_loss -0.7779 +2024-11-21 18:29:59.251493: val_loss -0.7301 +2024-11-21 18:29:59.251620: Pseudo dice [0.8281] +2024-11-21 18:29:59.251700: Epoch time: 19.6 s +2024-11-21 18:30:00.293934: +2024-11-21 18:30:00.294140: Epoch 1436 +2024-11-21 18:30:00.294257: Current learning rate: 0.00837 +2024-11-21 18:30:19.338280: train_loss -0.7644 +2024-11-21 18:30:19.338498: val_loss -0.7474 +2024-11-21 18:30:19.338591: Pseudo dice [0.828] +2024-11-21 18:30:19.338667: Epoch time: 19.05 s +2024-11-21 18:30:20.188920: +2024-11-21 18:30:20.189141: Epoch 1437 +2024-11-21 18:30:20.189384: Current learning rate: 0.00837 +2024-11-21 18:30:37.829631: train_loss -0.781 +2024-11-21 18:30:37.830702: val_loss -0.7122 +2024-11-21 18:30:37.830786: Pseudo dice [0.8113] +2024-11-21 18:30:37.830889: Epoch time: 17.64 s +2024-11-21 18:30:38.677455: +2024-11-21 18:30:38.677650: Epoch 1438 +2024-11-21 18:30:38.677764: Current learning rate: 0.00837 +2024-11-21 18:30:58.157219: train_loss -0.7765 +2024-11-21 18:30:58.157449: val_loss -0.7133 +2024-11-21 18:30:58.157531: Pseudo dice [0.8057] +2024-11-21 18:30:58.157608: Epoch time: 19.48 s +2024-11-21 18:30:59.107999: +2024-11-21 18:30:59.108207: Epoch 1439 +2024-11-21 18:30:59.108320: Current learning rate: 0.00837 +2024-11-21 18:31:17.654765: train_loss -0.766 +2024-11-21 18:31:17.654979: val_loss -0.7523 +2024-11-21 18:31:17.655057: Pseudo dice [0.8326] +2024-11-21 18:31:17.655133: Epoch time: 18.55 s +2024-11-21 18:31:18.697482: +2024-11-21 18:31:18.697705: Epoch 1440 +2024-11-21 18:31:18.697819: Current learning rate: 0.00836 +2024-11-21 18:31:37.733343: train_loss -0.7742 +2024-11-21 18:31:37.733607: val_loss -0.7517 +2024-11-21 18:31:37.733689: Pseudo dice [0.8332] +2024-11-21 18:31:37.733768: Epoch time: 19.04 s +2024-11-21 18:31:38.582038: +2024-11-21 18:31:38.582241: Epoch 1441 +2024-11-21 18:31:38.582361: Current learning rate: 0.00836 +2024-11-21 18:31:56.980866: train_loss -0.769 +2024-11-21 18:31:56.981138: val_loss -0.7067 +2024-11-21 18:31:56.981228: Pseudo dice [0.8242] +2024-11-21 18:31:56.981319: Epoch time: 18.4 s +2024-11-21 18:31:57.814755: +2024-11-21 18:31:57.814987: Epoch 1442 +2024-11-21 18:31:57.815112: Current learning rate: 0.00836 +2024-11-21 18:32:16.731918: train_loss -0.7648 +2024-11-21 18:32:16.732140: val_loss -0.7356 +2024-11-21 18:32:16.732214: Pseudo dice [0.8234] +2024-11-21 18:32:16.732292: Epoch time: 18.92 s +2024-11-21 18:32:18.048546: +2024-11-21 18:32:18.048769: Epoch 1443 +2024-11-21 18:32:18.048883: Current learning rate: 0.00836 +2024-11-21 18:32:35.979244: train_loss -0.7754 +2024-11-21 18:32:35.979464: val_loss -0.7324 +2024-11-21 18:32:35.979539: Pseudo dice [0.8071] +2024-11-21 18:32:35.979617: Epoch time: 17.93 s +2024-11-21 18:32:36.817472: +2024-11-21 18:32:36.817725: Epoch 1444 +2024-11-21 18:32:36.817836: Current learning rate: 0.00836 +2024-11-21 18:32:55.525449: train_loss -0.7777 +2024-11-21 18:32:55.530875: val_loss -0.7422 +2024-11-21 18:32:55.531012: Pseudo dice [0.8526] +2024-11-21 18:32:55.531099: Epoch time: 18.71 s +2024-11-21 18:32:56.457919: +2024-11-21 18:32:56.458141: Epoch 1445 +2024-11-21 18:32:56.458254: Current learning rate: 0.00836 +2024-11-21 18:33:16.393565: train_loss -0.77 +2024-11-21 18:33:16.393783: val_loss -0.7393 +2024-11-21 18:33:16.396073: Pseudo dice [0.8143] +2024-11-21 18:33:16.396175: Epoch time: 19.94 s +2024-11-21 18:33:17.269085: +2024-11-21 18:33:17.269281: Epoch 1446 +2024-11-21 18:33:17.269394: Current learning rate: 0.00836 +2024-11-21 18:33:36.234921: train_loss -0.7736 +2024-11-21 18:33:36.235141: val_loss -0.7367 +2024-11-21 18:33:36.235218: Pseudo dice [0.821] +2024-11-21 18:33:36.235294: Epoch time: 18.97 s +2024-11-21 18:33:37.074461: +2024-11-21 18:33:37.074669: Epoch 1447 +2024-11-21 18:33:37.074782: Current learning rate: 0.00836 +2024-11-21 18:33:55.413306: train_loss -0.7715 +2024-11-21 18:33:55.413551: val_loss -0.7082 +2024-11-21 18:33:55.413629: Pseudo dice [0.8066] +2024-11-21 18:33:55.413710: Epoch time: 18.34 s +2024-11-21 18:33:56.253900: +2024-11-21 18:33:56.254135: Epoch 1448 +2024-11-21 18:33:56.254247: Current learning rate: 0.00836 +2024-11-21 18:34:14.209039: train_loss -0.7731 +2024-11-21 18:34:14.209240: val_loss -0.7404 +2024-11-21 18:34:14.209316: Pseudo dice [0.8234] +2024-11-21 18:34:14.209392: Epoch time: 17.96 s +2024-11-21 18:34:15.129557: +2024-11-21 18:34:15.129836: Epoch 1449 +2024-11-21 18:34:15.129955: Current learning rate: 0.00835 +2024-11-21 18:34:33.962474: train_loss -0.772 +2024-11-21 18:34:33.962690: val_loss -0.7418 +2024-11-21 18:34:33.962767: Pseudo dice [0.8265] +2024-11-21 18:34:33.962847: Epoch time: 18.83 s +2024-11-21 18:34:35.082176: +2024-11-21 18:34:35.082370: Epoch 1450 +2024-11-21 18:34:35.082485: Current learning rate: 0.00835 +2024-11-21 18:34:54.218078: train_loss -0.7626 +2024-11-21 18:34:54.218289: val_loss -0.7428 +2024-11-21 18:34:54.218365: Pseudo dice [0.8302] +2024-11-21 18:34:54.218443: Epoch time: 19.14 s +2024-11-21 18:34:55.063029: +2024-11-21 18:34:55.063255: Epoch 1451 +2024-11-21 18:34:55.063371: Current learning rate: 0.00835 +2024-11-21 18:35:13.530307: train_loss -0.7701 +2024-11-21 18:35:13.530550: val_loss -0.7514 +2024-11-21 18:35:13.530626: Pseudo dice [0.8136] +2024-11-21 18:35:13.530711: Epoch time: 18.47 s +2024-11-21 18:35:14.375127: +2024-11-21 18:35:14.375315: Epoch 1452 +2024-11-21 18:35:14.375429: Current learning rate: 0.00835 +2024-11-21 18:35:33.160457: train_loss -0.7628 +2024-11-21 18:35:33.160671: val_loss -0.7367 +2024-11-21 18:35:33.160744: Pseudo dice [0.8274] +2024-11-21 18:35:33.160822: Epoch time: 18.79 s +2024-11-21 18:35:34.113622: +2024-11-21 18:35:34.113818: Epoch 1453 +2024-11-21 18:35:34.113934: Current learning rate: 0.00835 +2024-11-21 18:35:52.312004: train_loss -0.7749 +2024-11-21 18:35:52.312279: val_loss -0.7398 +2024-11-21 18:35:52.312354: Pseudo dice [0.8347] +2024-11-21 18:35:52.312432: Epoch time: 18.2 s +2024-11-21 18:35:53.168580: +2024-11-21 18:35:53.168783: Epoch 1454 +2024-11-21 18:35:53.168895: Current learning rate: 0.00835 +2024-11-21 18:36:11.196063: train_loss -0.775 +2024-11-21 18:36:11.196645: val_loss -0.7671 +2024-11-21 18:36:11.196749: Pseudo dice [0.826] +2024-11-21 18:36:11.196838: Epoch time: 18.03 s +2024-11-21 18:36:12.038337: +2024-11-21 18:36:12.038581: Epoch 1455 +2024-11-21 18:36:12.038699: Current learning rate: 0.00835 +2024-11-21 18:36:30.118808: train_loss -0.7668 +2024-11-21 18:36:30.119034: val_loss -0.7312 +2024-11-21 18:36:30.119108: Pseudo dice [0.8291] +2024-11-21 18:36:30.119183: Epoch time: 18.08 s +2024-11-21 18:36:30.953905: +2024-11-21 18:36:30.954208: Epoch 1456 +2024-11-21 18:36:30.954319: Current learning rate: 0.00835 +2024-11-21 18:36:48.906938: train_loss -0.7643 +2024-11-21 18:36:48.907160: val_loss -0.7287 +2024-11-21 18:36:48.907240: Pseudo dice [0.8272] +2024-11-21 18:36:48.907320: Epoch time: 17.95 s +2024-11-21 18:36:49.752602: +2024-11-21 18:36:49.752900: Epoch 1457 +2024-11-21 18:36:49.753025: Current learning rate: 0.00834 +2024-11-21 18:37:07.357157: train_loss -0.767 +2024-11-21 18:37:07.358489: val_loss -0.7464 +2024-11-21 18:37:07.358569: Pseudo dice [0.822] +2024-11-21 18:37:07.358658: Epoch time: 17.61 s +2024-11-21 18:37:08.204571: +2024-11-21 18:37:08.204804: Epoch 1458 +2024-11-21 18:37:08.204924: Current learning rate: 0.00834 +2024-11-21 18:37:27.441535: train_loss -0.7679 +2024-11-21 18:37:27.443984: val_loss -0.7474 +2024-11-21 18:37:27.444078: Pseudo dice [0.8277] +2024-11-21 18:37:27.444158: Epoch time: 19.24 s +2024-11-21 18:37:28.394333: +2024-11-21 18:37:28.394532: Epoch 1459 +2024-11-21 18:37:28.394661: Current learning rate: 0.00834 +2024-11-21 18:37:46.614488: train_loss -0.7611 +2024-11-21 18:37:46.614698: val_loss -0.7666 +2024-11-21 18:37:46.614772: Pseudo dice [0.8337] +2024-11-21 18:37:46.614850: Epoch time: 18.22 s +2024-11-21 18:37:47.456116: +2024-11-21 18:37:47.456346: Epoch 1460 +2024-11-21 18:37:47.456462: Current learning rate: 0.00834 +2024-11-21 18:38:06.928749: train_loss -0.7717 +2024-11-21 18:38:06.928964: val_loss -0.7604 +2024-11-21 18:38:06.929042: Pseudo dice [0.8341] +2024-11-21 18:38:06.929118: Epoch time: 19.47 s +2024-11-21 18:38:07.800600: +2024-11-21 18:38:07.800812: Epoch 1461 +2024-11-21 18:38:07.800928: Current learning rate: 0.00834 +2024-11-21 18:38:26.802347: train_loss -0.7688 +2024-11-21 18:38:26.802553: val_loss -0.7559 +2024-11-21 18:38:26.802625: Pseudo dice [0.8315] +2024-11-21 18:38:26.802702: Epoch time: 19.0 s +2024-11-21 18:38:27.644508: +2024-11-21 18:38:27.644737: Epoch 1462 +2024-11-21 18:38:27.644853: Current learning rate: 0.00834 +2024-11-21 18:38:46.277823: train_loss -0.7692 +2024-11-21 18:38:46.278069: val_loss -0.7473 +2024-11-21 18:38:46.278143: Pseudo dice [0.8258] +2024-11-21 18:38:46.278225: Epoch time: 18.63 s +2024-11-21 18:38:47.121150: +2024-11-21 18:38:47.121505: Epoch 1463 +2024-11-21 18:38:47.121635: Current learning rate: 0.00834 +2024-11-21 18:39:05.650775: train_loss -0.778 +2024-11-21 18:39:05.651028: val_loss -0.7548 +2024-11-21 18:39:05.651115: Pseudo dice [0.8317] +2024-11-21 18:39:05.651209: Epoch time: 18.53 s +2024-11-21 18:39:05.651291: Yayy! New best EMA pseudo Dice: 0.8273 +2024-11-21 18:39:06.827546: +2024-11-21 18:39:06.827783: Epoch 1464 +2024-11-21 18:39:06.827900: Current learning rate: 0.00834 +2024-11-21 18:39:24.741153: train_loss -0.7701 +2024-11-21 18:39:24.741374: val_loss -0.7267 +2024-11-21 18:39:24.741450: Pseudo dice [0.8047] +2024-11-21 18:39:24.741531: Epoch time: 17.91 s +2024-11-21 18:39:25.659941: +2024-11-21 18:39:25.660179: Epoch 1465 +2024-11-21 18:39:25.660307: Current learning rate: 0.00834 +2024-11-21 18:39:44.956398: train_loss -0.7685 +2024-11-21 18:39:44.958588: val_loss -0.7354 +2024-11-21 18:39:44.958719: Pseudo dice [0.8081] +2024-11-21 18:39:44.958811: Epoch time: 19.3 s +2024-11-21 18:39:45.828520: +2024-11-21 18:39:45.828728: Epoch 1466 +2024-11-21 18:39:45.828837: Current learning rate: 0.00833 +2024-11-21 18:40:04.318876: train_loss -0.768 +2024-11-21 18:40:04.320330: val_loss -0.745 +2024-11-21 18:40:04.320439: Pseudo dice [0.8293] +2024-11-21 18:40:04.320518: Epoch time: 18.49 s +2024-11-21 18:40:05.327132: +2024-11-21 18:40:05.327454: Epoch 1467 +2024-11-21 18:40:05.327567: Current learning rate: 0.00833 +2024-11-21 18:40:23.737489: train_loss -0.774 +2024-11-21 18:40:23.737707: val_loss -0.7489 +2024-11-21 18:40:23.737782: Pseudo dice [0.8404] +2024-11-21 18:40:23.737861: Epoch time: 18.41 s +2024-11-21 18:40:24.578580: +2024-11-21 18:40:24.578804: Epoch 1468 +2024-11-21 18:40:24.578919: Current learning rate: 0.00833 +2024-11-21 18:40:45.336380: train_loss -0.7702 +2024-11-21 18:40:45.336653: val_loss -0.748 +2024-11-21 18:40:45.336739: Pseudo dice [0.8136] +2024-11-21 18:40:45.336846: Epoch time: 20.76 s +2024-11-21 18:40:46.188973: +2024-11-21 18:40:46.189238: Epoch 1469 +2024-11-21 18:40:46.189361: Current learning rate: 0.00833 +2024-11-21 18:41:05.590406: train_loss -0.7797 +2024-11-21 18:41:05.590622: val_loss -0.7196 +2024-11-21 18:41:05.590699: Pseudo dice [0.8378] +2024-11-21 18:41:05.590775: Epoch time: 19.4 s +2024-11-21 18:41:06.434428: +2024-11-21 18:41:06.434628: Epoch 1470 +2024-11-21 18:41:06.434737: Current learning rate: 0.00833 +2024-11-21 18:41:25.407038: train_loss -0.7764 +2024-11-21 18:41:25.407264: val_loss -0.7477 +2024-11-21 18:41:25.407342: Pseudo dice [0.8126] +2024-11-21 18:41:25.407423: Epoch time: 18.97 s +2024-11-21 18:41:26.245626: +2024-11-21 18:41:26.245825: Epoch 1471 +2024-11-21 18:41:26.245934: Current learning rate: 0.00833 +2024-11-21 18:41:44.703921: train_loss -0.7579 +2024-11-21 18:41:44.704144: val_loss -0.7527 +2024-11-21 18:41:44.704219: Pseudo dice [0.8383] +2024-11-21 18:41:44.704297: Epoch time: 18.46 s +2024-11-21 18:41:45.555761: +2024-11-21 18:41:45.555975: Epoch 1472 +2024-11-21 18:41:45.556094: Current learning rate: 0.00833 +2024-11-21 18:42:04.177745: train_loss -0.7625 +2024-11-21 18:42:04.178102: val_loss -0.7364 +2024-11-21 18:42:04.178188: Pseudo dice [0.8065] +2024-11-21 18:42:04.178271: Epoch time: 18.62 s +2024-11-21 18:42:05.023872: +2024-11-21 18:42:05.024085: Epoch 1473 +2024-11-21 18:42:05.024196: Current learning rate: 0.00833 +2024-11-21 18:42:23.975469: train_loss -0.7786 +2024-11-21 18:42:23.976378: val_loss -0.7545 +2024-11-21 18:42:23.976455: Pseudo dice [0.8266] +2024-11-21 18:42:23.976532: Epoch time: 18.95 s +2024-11-21 18:42:24.815851: +2024-11-21 18:42:24.816051: Epoch 1474 +2024-11-21 18:42:24.816163: Current learning rate: 0.00833 +2024-11-21 18:42:44.137502: train_loss -0.7751 +2024-11-21 18:42:44.137719: val_loss -0.7366 +2024-11-21 18:42:44.137798: Pseudo dice [0.8351] +2024-11-21 18:42:44.137876: Epoch time: 19.32 s +2024-11-21 18:42:44.987649: +2024-11-21 18:42:44.987846: Epoch 1475 +2024-11-21 18:42:44.987960: Current learning rate: 0.00832 +2024-11-21 18:43:03.483278: train_loss -0.7677 +2024-11-21 18:43:03.483522: val_loss -0.7189 +2024-11-21 18:43:03.483598: Pseudo dice [0.8198] +2024-11-21 18:43:03.483683: Epoch time: 18.5 s +2024-11-21 18:43:04.700886: +2024-11-21 18:43:04.701102: Epoch 1476 +2024-11-21 18:43:04.701216: Current learning rate: 0.00832 +2024-11-21 18:43:24.168260: train_loss -0.7667 +2024-11-21 18:43:24.168480: val_loss -0.7117 +2024-11-21 18:43:24.168551: Pseudo dice [0.8209] +2024-11-21 18:43:24.168647: Epoch time: 19.47 s +2024-11-21 18:43:25.014131: +2024-11-21 18:43:25.014410: Epoch 1477 +2024-11-21 18:43:25.014520: Current learning rate: 0.00832 +2024-11-21 18:43:42.929374: train_loss -0.7699 +2024-11-21 18:43:42.929599: val_loss -0.7583 +2024-11-21 18:43:42.929670: Pseudo dice [0.813] +2024-11-21 18:43:42.929747: Epoch time: 17.92 s +2024-11-21 18:43:43.906613: +2024-11-21 18:43:43.906938: Epoch 1478 +2024-11-21 18:43:43.907066: Current learning rate: 0.00832 +2024-11-21 18:44:02.169752: train_loss -0.7814 +2024-11-21 18:44:02.169968: val_loss -0.7215 +2024-11-21 18:44:02.170049: Pseudo dice [0.8306] +2024-11-21 18:44:02.170137: Epoch time: 18.26 s +2024-11-21 18:44:03.162609: +2024-11-21 18:44:03.162823: Epoch 1479 +2024-11-21 18:44:03.162970: Current learning rate: 0.00832 +2024-11-21 18:44:21.377671: train_loss -0.7794 +2024-11-21 18:44:21.377916: val_loss -0.7481 +2024-11-21 18:44:21.378054: Pseudo dice [0.8195] +2024-11-21 18:44:21.378138: Epoch time: 18.22 s +2024-11-21 18:44:22.228897: +2024-11-21 18:44:22.229123: Epoch 1480 +2024-11-21 18:44:22.229245: Current learning rate: 0.00832 +2024-11-21 18:44:41.053950: train_loss -0.775 +2024-11-21 18:44:41.054222: val_loss -0.7323 +2024-11-21 18:44:41.054298: Pseudo dice [0.814] +2024-11-21 18:44:41.054376: Epoch time: 18.83 s +2024-11-21 18:44:41.903088: +2024-11-21 18:44:41.903305: Epoch 1481 +2024-11-21 18:44:41.903415: Current learning rate: 0.00832 +2024-11-21 18:45:00.316688: train_loss -0.7556 +2024-11-21 18:45:00.316907: val_loss -0.7112 +2024-11-21 18:45:00.316985: Pseudo dice [0.8056] +2024-11-21 18:45:00.317095: Epoch time: 18.41 s +2024-11-21 18:45:01.163840: +2024-11-21 18:45:01.164042: Epoch 1482 +2024-11-21 18:45:01.164153: Current learning rate: 0.00832 +2024-11-21 18:45:20.466350: train_loss -0.7737 +2024-11-21 18:45:20.466560: val_loss -0.7455 +2024-11-21 18:45:20.466635: Pseudo dice [0.8358] +2024-11-21 18:45:20.466713: Epoch time: 19.3 s +2024-11-21 18:45:21.309004: +2024-11-21 18:45:21.309208: Epoch 1483 +2024-11-21 18:45:21.309323: Current learning rate: 0.00831 +2024-11-21 18:45:40.987890: train_loss -0.7605 +2024-11-21 18:45:40.988141: val_loss -0.7606 +2024-11-21 18:45:40.988219: Pseudo dice [0.8431] +2024-11-21 18:45:40.988298: Epoch time: 19.68 s +2024-11-21 18:45:41.836235: +2024-11-21 18:45:41.836422: Epoch 1484 +2024-11-21 18:45:41.836532: Current learning rate: 0.00831 +2024-11-21 18:46:00.824106: train_loss -0.7689 +2024-11-21 18:46:00.824323: val_loss -0.7345 +2024-11-21 18:46:00.829567: Pseudo dice [0.8292] +2024-11-21 18:46:00.829741: Epoch time: 18.99 s +2024-11-21 18:46:01.753441: +2024-11-21 18:46:01.753629: Epoch 1485 +2024-11-21 18:46:01.753742: Current learning rate: 0.00831 +2024-11-21 18:46:20.207314: train_loss -0.7741 +2024-11-21 18:46:20.207537: val_loss -0.7416 +2024-11-21 18:46:20.207612: Pseudo dice [0.8207] +2024-11-21 18:46:20.207690: Epoch time: 18.45 s +2024-11-21 18:46:21.050350: +2024-11-21 18:46:21.050608: Epoch 1486 +2024-11-21 18:46:21.066462: Current learning rate: 0.00831 +2024-11-21 18:46:38.833948: train_loss -0.7729 +2024-11-21 18:46:38.834254: val_loss -0.75 +2024-11-21 18:46:38.834337: Pseudo dice [0.8116] +2024-11-21 18:46:38.834421: Epoch time: 17.78 s +2024-11-21 18:46:39.682984: +2024-11-21 18:46:39.683186: Epoch 1487 +2024-11-21 18:46:39.683302: Current learning rate: 0.00831 +2024-11-21 18:46:57.998581: train_loss -0.7682 +2024-11-21 18:46:57.998792: val_loss -0.7624 +2024-11-21 18:46:57.998864: Pseudo dice [0.8448] +2024-11-21 18:46:57.998939: Epoch time: 18.32 s +2024-11-21 18:46:59.277552: +2024-11-21 18:46:59.277757: Epoch 1488 +2024-11-21 18:46:59.277867: Current learning rate: 0.00831 +2024-11-21 18:47:18.029633: train_loss -0.7624 +2024-11-21 18:47:18.029876: val_loss -0.7446 +2024-11-21 18:47:18.029952: Pseudo dice [0.8077] +2024-11-21 18:47:18.030151: Epoch time: 18.75 s +2024-11-21 18:47:18.872315: +2024-11-21 18:47:18.872535: Epoch 1489 +2024-11-21 18:47:18.872649: Current learning rate: 0.00831 +2024-11-21 18:47:37.962883: train_loss -0.7776 +2024-11-21 18:47:37.963125: val_loss -0.7403 +2024-11-21 18:47:37.963202: Pseudo dice [0.8251] +2024-11-21 18:47:37.963289: Epoch time: 19.09 s +2024-11-21 18:47:38.816539: +2024-11-21 18:47:38.816759: Epoch 1490 +2024-11-21 18:47:38.816875: Current learning rate: 0.00831 +2024-11-21 18:47:58.351015: train_loss -0.772 +2024-11-21 18:47:58.351223: val_loss -0.748 +2024-11-21 18:47:58.351296: Pseudo dice [0.8206] +2024-11-21 18:47:58.351372: Epoch time: 19.54 s +2024-11-21 18:47:59.197943: +2024-11-21 18:47:59.198154: Epoch 1491 +2024-11-21 18:47:59.198269: Current learning rate: 0.00831 +2024-11-21 18:48:17.148138: train_loss -0.7745 +2024-11-21 18:48:17.148350: val_loss -0.7615 +2024-11-21 18:48:17.148427: Pseudo dice [0.83] +2024-11-21 18:48:17.148505: Epoch time: 17.95 s +2024-11-21 18:48:18.240083: +2024-11-21 18:48:18.240290: Epoch 1492 +2024-11-21 18:48:18.240402: Current learning rate: 0.0083 +2024-11-21 18:48:36.717373: train_loss -0.7664 +2024-11-21 18:48:36.717588: val_loss -0.7295 +2024-11-21 18:48:36.717662: Pseudo dice [0.8] +2024-11-21 18:48:36.717737: Epoch time: 18.48 s +2024-11-21 18:48:37.568772: +2024-11-21 18:48:37.569113: Epoch 1493 +2024-11-21 18:48:37.569229: Current learning rate: 0.0083 +2024-11-21 18:48:55.289694: train_loss -0.744 +2024-11-21 18:48:55.295139: val_loss -0.7549 +2024-11-21 18:48:55.295265: Pseudo dice [0.8281] +2024-11-21 18:48:55.295354: Epoch time: 17.72 s +2024-11-21 18:48:56.203965: +2024-11-21 18:48:56.204206: Epoch 1494 +2024-11-21 18:48:56.204322: Current learning rate: 0.0083 +2024-11-21 18:49:13.717624: train_loss -0.7698 +2024-11-21 18:49:13.717883: val_loss -0.7376 +2024-11-21 18:49:13.717964: Pseudo dice [0.8356] +2024-11-21 18:49:13.718047: Epoch time: 17.51 s +2024-11-21 18:49:14.560032: +2024-11-21 18:49:14.560288: Epoch 1495 +2024-11-21 18:49:14.560401: Current learning rate: 0.0083 +2024-11-21 18:49:32.447599: train_loss -0.7662 +2024-11-21 18:49:32.447815: val_loss -0.755 +2024-11-21 18:49:32.447897: Pseudo dice [0.8299] +2024-11-21 18:49:32.447976: Epoch time: 17.89 s +2024-11-21 18:49:33.308613: +2024-11-21 18:49:33.308835: Epoch 1496 +2024-11-21 18:49:33.308952: Current learning rate: 0.0083 +2024-11-21 18:49:51.495380: train_loss -0.7644 +2024-11-21 18:49:51.495624: val_loss -0.7481 +2024-11-21 18:49:51.495700: Pseudo dice [0.824] +2024-11-21 18:49:51.495784: Epoch time: 18.19 s +2024-11-21 18:49:52.344726: +2024-11-21 18:49:52.344961: Epoch 1497 +2024-11-21 18:49:52.345081: Current learning rate: 0.0083 +2024-11-21 18:50:11.499375: train_loss -0.7711 +2024-11-21 18:50:11.499592: val_loss -0.7372 +2024-11-21 18:50:11.499665: Pseudo dice [0.825] +2024-11-21 18:50:11.499742: Epoch time: 19.16 s +2024-11-21 18:50:12.346206: +2024-11-21 18:50:12.346390: Epoch 1498 +2024-11-21 18:50:12.346499: Current learning rate: 0.0083 +2024-11-21 18:50:29.981817: train_loss -0.767 +2024-11-21 18:50:29.982102: val_loss -0.7518 +2024-11-21 18:50:29.982181: Pseudo dice [0.8232] +2024-11-21 18:50:29.982257: Epoch time: 17.64 s +2024-11-21 18:50:31.286852: +2024-11-21 18:50:31.287064: Epoch 1499 +2024-11-21 18:50:31.287179: Current learning rate: 0.0083 +2024-11-21 18:50:50.050616: train_loss -0.7712 +2024-11-21 18:50:50.050928: val_loss -0.7378 +2024-11-21 18:50:50.051014: Pseudo dice [0.8238] +2024-11-21 18:50:50.051100: Epoch time: 18.76 s +2024-11-21 18:50:51.130669: +2024-11-21 18:50:51.130938: Epoch 1500 +2024-11-21 18:50:51.131059: Current learning rate: 0.0083 +2024-11-21 18:51:11.328090: train_loss -0.7689 +2024-11-21 18:51:11.328300: val_loss -0.7488 +2024-11-21 18:51:11.328376: Pseudo dice [0.832] +2024-11-21 18:51:11.333646: Epoch time: 20.2 s +2024-11-21 18:51:12.304301: +2024-11-21 18:51:12.304534: Epoch 1501 +2024-11-21 18:51:12.304644: Current learning rate: 0.00829 +2024-11-21 18:51:31.734733: train_loss -0.7693 +2024-11-21 18:51:31.734953: val_loss -0.7216 +2024-11-21 18:51:31.735034: Pseudo dice [0.8326] +2024-11-21 18:51:31.735108: Epoch time: 19.43 s +2024-11-21 18:51:32.579454: +2024-11-21 18:51:32.579673: Epoch 1502 +2024-11-21 18:51:32.579788: Current learning rate: 0.00829 +2024-11-21 18:51:51.221822: train_loss -0.7666 +2024-11-21 18:51:51.222044: val_loss -0.75 +2024-11-21 18:51:51.224309: Pseudo dice [0.8224] +2024-11-21 18:51:51.224404: Epoch time: 18.64 s +2024-11-21 18:51:52.074468: +2024-11-21 18:51:52.074659: Epoch 1503 +2024-11-21 18:51:52.074769: Current learning rate: 0.00829 +2024-11-21 18:52:09.946412: train_loss -0.7748 +2024-11-21 18:52:09.951902: val_loss -0.7509 +2024-11-21 18:52:09.952021: Pseudo dice [0.8304] +2024-11-21 18:52:09.952108: Epoch time: 17.87 s +2024-11-21 18:52:10.833057: +2024-11-21 18:52:10.833297: Epoch 1504 +2024-11-21 18:52:10.833411: Current learning rate: 0.00829 +2024-11-21 18:52:29.328866: train_loss -0.7738 +2024-11-21 18:52:29.329077: val_loss -0.7365 +2024-11-21 18:52:29.329149: Pseudo dice [0.8163] +2024-11-21 18:52:29.329222: Epoch time: 18.5 s +2024-11-21 18:52:30.172098: +2024-11-21 18:52:30.172413: Epoch 1505 +2024-11-21 18:52:30.172531: Current learning rate: 0.00829 +2024-11-21 18:52:49.707754: train_loss -0.7722 +2024-11-21 18:52:49.707969: val_loss -0.7248 +2024-11-21 18:52:49.708054: Pseudo dice [0.8178] +2024-11-21 18:52:49.708130: Epoch time: 19.54 s +2024-11-21 18:52:50.597218: +2024-11-21 18:52:50.597603: Epoch 1506 +2024-11-21 18:52:50.597716: Current learning rate: 0.00829 +2024-11-21 18:53:09.254633: train_loss -0.7631 +2024-11-21 18:53:09.261032: val_loss -0.7201 +2024-11-21 18:53:09.261155: Pseudo dice [0.8282] +2024-11-21 18:53:09.261243: Epoch time: 18.66 s +2024-11-21 18:53:10.269759: +2024-11-21 18:53:10.270023: Epoch 1507 +2024-11-21 18:53:10.270130: Current learning rate: 0.00829 +2024-11-21 18:53:28.807881: train_loss -0.7748 +2024-11-21 18:53:28.808124: val_loss -0.7574 +2024-11-21 18:53:28.808200: Pseudo dice [0.8371] +2024-11-21 18:53:28.808279: Epoch time: 18.54 s +2024-11-21 18:53:29.641575: +2024-11-21 18:53:29.641794: Epoch 1508 +2024-11-21 18:53:29.641902: Current learning rate: 0.00829 +2024-11-21 18:53:47.918331: train_loss -0.7519 +2024-11-21 18:53:47.919130: val_loss -0.702 +2024-11-21 18:53:47.919221: Pseudo dice [0.7944] +2024-11-21 18:53:47.919301: Epoch time: 18.28 s +2024-11-21 18:53:48.775149: +2024-11-21 18:53:48.775372: Epoch 1509 +2024-11-21 18:53:48.775486: Current learning rate: 0.00829 +2024-11-21 18:54:07.699234: train_loss -0.7432 +2024-11-21 18:54:07.701618: val_loss -0.7404 +2024-11-21 18:54:07.701743: Pseudo dice [0.8118] +2024-11-21 18:54:07.701823: Epoch time: 18.92 s +2024-11-21 18:54:09.015319: +2024-11-21 18:54:09.015571: Epoch 1510 +2024-11-21 18:54:09.015684: Current learning rate: 0.00828 +2024-11-21 18:54:28.506861: train_loss -0.7367 +2024-11-21 18:54:28.507478: val_loss -0.7271 +2024-11-21 18:54:28.507561: Pseudo dice [0.8037] +2024-11-21 18:54:28.507646: Epoch time: 19.49 s +2024-11-21 18:54:29.353091: +2024-11-21 18:54:29.353294: Epoch 1511 +2024-11-21 18:54:29.353402: Current learning rate: 0.00828 +2024-11-21 18:54:47.823658: train_loss -0.7574 +2024-11-21 18:54:47.823862: val_loss -0.7087 +2024-11-21 18:54:47.825435: Pseudo dice [0.8224] +2024-11-21 18:54:47.825553: Epoch time: 18.47 s +2024-11-21 18:54:48.690848: +2024-11-21 18:54:48.691050: Epoch 1512 +2024-11-21 18:54:48.691158: Current learning rate: 0.00828 +2024-11-21 18:55:06.893691: train_loss -0.7573 +2024-11-21 18:55:06.893908: val_loss -0.7273 +2024-11-21 18:55:06.893981: Pseudo dice [0.821] +2024-11-21 18:55:06.894065: Epoch time: 18.2 s +2024-11-21 18:55:07.736000: +2024-11-21 18:55:07.736210: Epoch 1513 +2024-11-21 18:55:07.736317: Current learning rate: 0.00828 +2024-11-21 18:55:26.955291: train_loss -0.768 +2024-11-21 18:55:26.955503: val_loss -0.7327 +2024-11-21 18:55:26.955579: Pseudo dice [0.8109] +2024-11-21 18:55:26.955658: Epoch time: 19.22 s +2024-11-21 18:55:27.803233: +2024-11-21 18:55:27.803463: Epoch 1514 +2024-11-21 18:55:27.803584: Current learning rate: 0.00828 +2024-11-21 18:55:47.415464: train_loss -0.7569 +2024-11-21 18:55:47.415691: val_loss -0.7075 +2024-11-21 18:55:47.415762: Pseudo dice [0.8061] +2024-11-21 18:55:47.415957: Epoch time: 19.61 s +2024-11-21 18:55:48.255427: +2024-11-21 18:55:48.255625: Epoch 1515 +2024-11-21 18:55:48.255738: Current learning rate: 0.00828 +2024-11-21 18:56:08.011781: train_loss -0.728 +2024-11-21 18:56:08.012004: val_loss -0.7095 +2024-11-21 18:56:08.012078: Pseudo dice [0.8038] +2024-11-21 18:56:08.012154: Epoch time: 19.76 s +2024-11-21 18:56:08.885833: +2024-11-21 18:56:08.886053: Epoch 1516 +2024-11-21 18:56:08.886175: Current learning rate: 0.00828 +2024-11-21 18:56:26.845841: train_loss -0.7366 +2024-11-21 18:56:26.846126: val_loss -0.7274 +2024-11-21 18:56:26.846203: Pseudo dice [0.8046] +2024-11-21 18:56:26.846279: Epoch time: 17.96 s +2024-11-21 18:56:27.703321: +2024-11-21 18:56:27.703573: Epoch 1517 +2024-11-21 18:56:27.703687: Current learning rate: 0.00828 +2024-11-21 18:56:46.653763: train_loss -0.7408 +2024-11-21 18:56:46.654017: val_loss -0.6983 +2024-11-21 18:56:46.654098: Pseudo dice [0.8061] +2024-11-21 18:56:46.654200: Epoch time: 18.95 s +2024-11-21 18:56:47.537593: +2024-11-21 18:56:47.537802: Epoch 1518 +2024-11-21 18:56:47.537917: Current learning rate: 0.00827 +2024-11-21 18:57:05.422698: train_loss -0.7404 +2024-11-21 18:57:05.422939: val_loss -0.7209 +2024-11-21 18:57:05.423036: Pseudo dice [0.8066] +2024-11-21 18:57:05.423114: Epoch time: 17.89 s +2024-11-21 18:57:06.271943: +2024-11-21 18:57:06.272160: Epoch 1519 +2024-11-21 18:57:06.272275: Current learning rate: 0.00827 +2024-11-21 18:57:24.138739: train_loss -0.7575 +2024-11-21 18:57:24.139900: val_loss -0.7367 +2024-11-21 18:57:24.140012: Pseudo dice [0.8141] +2024-11-21 18:57:24.140091: Epoch time: 17.87 s +2024-11-21 18:57:24.984958: +2024-11-21 18:57:24.985166: Epoch 1520 +2024-11-21 18:57:24.985279: Current learning rate: 0.00827 +2024-11-21 18:57:43.923345: train_loss -0.7668 +2024-11-21 18:57:43.923563: val_loss -0.738 +2024-11-21 18:57:43.923641: Pseudo dice [0.8256] +2024-11-21 18:57:43.923723: Epoch time: 18.94 s +2024-11-21 18:57:44.877170: +2024-11-21 18:57:44.877581: Epoch 1521 +2024-11-21 18:57:44.877699: Current learning rate: 0.00827 +2024-11-21 18:58:03.547926: train_loss -0.7709 +2024-11-21 18:58:03.548180: val_loss -0.7404 +2024-11-21 18:58:03.548258: Pseudo dice [0.8176] +2024-11-21 18:58:03.548343: Epoch time: 18.67 s +2024-11-21 18:58:04.809176: +2024-11-21 18:58:04.809446: Epoch 1522 +2024-11-21 18:58:04.809564: Current learning rate: 0.00827 +2024-11-21 18:58:24.041869: train_loss -0.7644 +2024-11-21 18:58:24.042096: val_loss -0.7329 +2024-11-21 18:58:24.042169: Pseudo dice [0.8262] +2024-11-21 18:58:24.042245: Epoch time: 19.23 s +2024-11-21 18:58:24.933320: +2024-11-21 18:58:24.933556: Epoch 1523 +2024-11-21 18:58:24.933679: Current learning rate: 0.00827 +2024-11-21 18:58:43.032915: train_loss -0.7651 +2024-11-21 18:58:43.033141: val_loss -0.7625 +2024-11-21 18:58:43.033215: Pseudo dice [0.831] +2024-11-21 18:58:43.033297: Epoch time: 18.1 s +2024-11-21 18:58:44.012405: +2024-11-21 18:58:44.012636: Epoch 1524 +2024-11-21 18:58:44.012753: Current learning rate: 0.00827 +2024-11-21 18:59:02.011553: train_loss -0.77 +2024-11-21 18:59:02.011814: val_loss -0.7627 +2024-11-21 18:59:02.011892: Pseudo dice [0.8241] +2024-11-21 18:59:02.011971: Epoch time: 18.0 s +2024-11-21 18:59:02.863767: +2024-11-21 18:59:02.864048: Epoch 1525 +2024-11-21 18:59:02.864162: Current learning rate: 0.00827 +2024-11-21 18:59:21.433756: train_loss -0.7774 +2024-11-21 18:59:21.433974: val_loss -0.7409 +2024-11-21 18:59:21.434052: Pseudo dice [0.831] +2024-11-21 18:59:21.436161: Epoch time: 18.57 s +2024-11-21 18:59:22.291805: +2024-11-21 18:59:22.292085: Epoch 1526 +2024-11-21 18:59:22.292201: Current learning rate: 0.00827 +2024-11-21 18:59:40.821491: train_loss -0.7785 +2024-11-21 18:59:40.821714: val_loss -0.7531 +2024-11-21 18:59:40.821785: Pseudo dice [0.8427] +2024-11-21 18:59:40.821861: Epoch time: 18.53 s +2024-11-21 18:59:41.673735: +2024-11-21 18:59:41.673958: Epoch 1527 +2024-11-21 18:59:41.674073: Current learning rate: 0.00826 +2024-11-21 19:00:01.603314: train_loss -0.7662 +2024-11-21 19:00:01.603591: val_loss -0.7353 +2024-11-21 19:00:01.603674: Pseudo dice [0.8146] +2024-11-21 19:00:01.603754: Epoch time: 19.93 s +2024-11-21 19:00:02.456309: +2024-11-21 19:00:02.456515: Epoch 1528 +2024-11-21 19:00:02.456630: Current learning rate: 0.00826 +2024-11-21 19:00:20.769185: train_loss -0.773 +2024-11-21 19:00:20.769422: val_loss -0.748 +2024-11-21 19:00:20.769496: Pseudo dice [0.8228] +2024-11-21 19:00:20.769577: Epoch time: 18.31 s +2024-11-21 19:00:21.623136: +2024-11-21 19:00:21.623331: Epoch 1529 +2024-11-21 19:00:21.623440: Current learning rate: 0.00826 +2024-11-21 19:00:39.556598: train_loss -0.7667 +2024-11-21 19:00:39.556799: val_loss -0.7505 +2024-11-21 19:00:39.556875: Pseudo dice [0.8291] +2024-11-21 19:00:39.556950: Epoch time: 17.93 s +2024-11-21 19:00:40.406118: +2024-11-21 19:00:40.406324: Epoch 1530 +2024-11-21 19:00:40.406436: Current learning rate: 0.00826 +2024-11-21 19:00:59.120144: train_loss -0.7716 +2024-11-21 19:00:59.120371: val_loss -0.7447 +2024-11-21 19:00:59.120449: Pseudo dice [0.8273] +2024-11-21 19:00:59.120530: Epoch time: 18.71 s +2024-11-21 19:01:00.089792: +2024-11-21 19:01:00.090073: Epoch 1531 +2024-11-21 19:01:00.090193: Current learning rate: 0.00826 +2024-11-21 19:01:19.182659: train_loss -0.7717 +2024-11-21 19:01:19.182896: val_loss -0.7461 +2024-11-21 19:01:19.182967: Pseudo dice [0.8246] +2024-11-21 19:01:19.183136: Epoch time: 19.09 s +2024-11-21 19:01:20.205948: +2024-11-21 19:01:20.206144: Epoch 1532 +2024-11-21 19:01:20.206295: Current learning rate: 0.00826 +2024-11-21 19:01:39.554271: train_loss -0.7757 +2024-11-21 19:01:39.554483: val_loss -0.7405 +2024-11-21 19:01:39.554557: Pseudo dice [0.8132] +2024-11-21 19:01:39.554632: Epoch time: 19.35 s +2024-11-21 19:01:40.836143: +2024-11-21 19:01:40.836396: Epoch 1533 +2024-11-21 19:01:40.836506: Current learning rate: 0.00826 +2024-11-21 19:01:58.691138: train_loss -0.772 +2024-11-21 19:01:58.691357: val_loss -0.7587 +2024-11-21 19:01:58.691432: Pseudo dice [0.8183] +2024-11-21 19:01:58.691507: Epoch time: 17.86 s +2024-11-21 19:01:59.539883: +2024-11-21 19:01:59.540116: Epoch 1534 +2024-11-21 19:01:59.540227: Current learning rate: 0.00826 +2024-11-21 19:02:18.179825: train_loss -0.7757 +2024-11-21 19:02:18.180068: val_loss -0.7624 +2024-11-21 19:02:18.180150: Pseudo dice [0.8171] +2024-11-21 19:02:18.180229: Epoch time: 18.64 s +2024-11-21 19:02:19.053449: +2024-11-21 19:02:19.053660: Epoch 1535 +2024-11-21 19:02:19.053772: Current learning rate: 0.00826 +2024-11-21 19:02:37.145172: train_loss -0.7668 +2024-11-21 19:02:37.145413: val_loss -0.7356 +2024-11-21 19:02:37.145487: Pseudo dice [0.8244] +2024-11-21 19:02:37.145605: Epoch time: 18.09 s +2024-11-21 19:02:37.999849: +2024-11-21 19:02:38.000067: Epoch 1536 +2024-11-21 19:02:38.000177: Current learning rate: 0.00825 +2024-11-21 19:02:55.873117: train_loss -0.7583 +2024-11-21 19:02:55.873337: val_loss -0.7555 +2024-11-21 19:02:55.873412: Pseudo dice [0.8157] +2024-11-21 19:02:55.873490: Epoch time: 17.87 s +2024-11-21 19:02:56.746949: +2024-11-21 19:02:56.747145: Epoch 1537 +2024-11-21 19:02:56.747255: Current learning rate: 0.00825 +2024-11-21 19:03:15.279896: train_loss -0.7483 +2024-11-21 19:03:15.280117: val_loss -0.727 +2024-11-21 19:03:15.280193: Pseudo dice [0.8136] +2024-11-21 19:03:15.280273: Epoch time: 18.53 s +2024-11-21 19:03:16.134304: +2024-11-21 19:03:16.134525: Epoch 1538 +2024-11-21 19:03:16.134639: Current learning rate: 0.00825 +2024-11-21 19:03:35.428305: train_loss -0.7608 +2024-11-21 19:03:35.428549: val_loss -0.7497 +2024-11-21 19:03:35.428628: Pseudo dice [0.8463] +2024-11-21 19:03:35.428707: Epoch time: 19.29 s +2024-11-21 19:03:36.389621: +2024-11-21 19:03:36.389813: Epoch 1539 +2024-11-21 19:03:36.389927: Current learning rate: 0.00825 +2024-11-21 19:03:55.194487: train_loss -0.7639 +2024-11-21 19:03:55.194731: val_loss -0.7234 +2024-11-21 19:03:55.194809: Pseudo dice [0.8134] +2024-11-21 19:03:55.194894: Epoch time: 18.81 s +2024-11-21 19:03:56.044894: +2024-11-21 19:03:56.045109: Epoch 1540 +2024-11-21 19:03:56.045228: Current learning rate: 0.00825 +2024-11-21 19:04:14.984861: train_loss -0.7739 +2024-11-21 19:04:14.985089: val_loss -0.7466 +2024-11-21 19:04:14.985308: Pseudo dice [0.8224] +2024-11-21 19:04:14.985391: Epoch time: 18.94 s +2024-11-21 19:04:15.842893: +2024-11-21 19:04:15.843153: Epoch 1541 +2024-11-21 19:04:15.843264: Current learning rate: 0.00825 +2024-11-21 19:04:34.218167: train_loss -0.7714 +2024-11-21 19:04:34.218386: val_loss -0.7422 +2024-11-21 19:04:34.220652: Pseudo dice [0.8192] +2024-11-21 19:04:34.220793: Epoch time: 18.38 s +2024-11-21 19:04:35.291321: +2024-11-21 19:04:35.291531: Epoch 1542 +2024-11-21 19:04:35.291647: Current learning rate: 0.00825 +2024-11-21 19:04:53.999876: train_loss -0.769 +2024-11-21 19:04:54.000124: val_loss -0.7343 +2024-11-21 19:04:54.000199: Pseudo dice [0.8153] +2024-11-21 19:04:54.000283: Epoch time: 18.71 s +2024-11-21 19:04:54.957965: +2024-11-21 19:04:54.958197: Epoch 1543 +2024-11-21 19:04:54.958308: Current learning rate: 0.00825 +2024-11-21 19:05:14.000130: train_loss -0.7637 +2024-11-21 19:05:14.000405: val_loss -0.7355 +2024-11-21 19:05:14.000485: Pseudo dice [0.8198] +2024-11-21 19:05:14.000566: Epoch time: 19.04 s +2024-11-21 19:05:15.245041: +2024-11-21 19:05:15.245255: Epoch 1544 +2024-11-21 19:05:15.245366: Current learning rate: 0.00824 +2024-11-21 19:05:33.122604: train_loss -0.7685 +2024-11-21 19:05:33.122896: val_loss -0.7622 +2024-11-21 19:05:33.122975: Pseudo dice [0.8281] +2024-11-21 19:05:33.123054: Epoch time: 17.88 s +2024-11-21 19:05:33.976692: +2024-11-21 19:05:33.976921: Epoch 1545 +2024-11-21 19:05:33.977040: Current learning rate: 0.00824 +2024-11-21 19:05:51.723322: train_loss -0.7601 +2024-11-21 19:05:51.723641: val_loss -0.7565 +2024-11-21 19:05:51.723718: Pseudo dice [0.8089] +2024-11-21 19:05:51.723804: Epoch time: 17.75 s +2024-11-21 19:05:52.582479: +2024-11-21 19:05:52.582721: Epoch 1546 +2024-11-21 19:05:52.582834: Current learning rate: 0.00824 +2024-11-21 19:06:12.869620: train_loss -0.7623 +2024-11-21 19:06:12.869837: val_loss -0.7391 +2024-11-21 19:06:12.869911: Pseudo dice [0.8149] +2024-11-21 19:06:12.870594: Epoch time: 20.29 s +2024-11-21 19:06:13.815365: +2024-11-21 19:06:13.815566: Epoch 1547 +2024-11-21 19:06:13.815678: Current learning rate: 0.00824 +2024-11-21 19:06:32.475638: train_loss -0.7722 +2024-11-21 19:06:32.475863: val_loss -0.7562 +2024-11-21 19:06:32.475946: Pseudo dice [0.8153] +2024-11-21 19:06:32.476029: Epoch time: 18.66 s +2024-11-21 19:06:33.333492: +2024-11-21 19:06:33.333700: Epoch 1548 +2024-11-21 19:06:33.333813: Current learning rate: 0.00824 +2024-11-21 19:06:51.531652: train_loss -0.7695 +2024-11-21 19:06:51.534054: val_loss -0.7554 +2024-11-21 19:06:51.534140: Pseudo dice [0.8293] +2024-11-21 19:06:51.534218: Epoch time: 18.2 s +2024-11-21 19:06:52.505641: +2024-11-21 19:06:52.505872: Epoch 1549 +2024-11-21 19:06:52.505985: Current learning rate: 0.00824 +2024-11-21 19:07:11.857621: train_loss -0.7574 +2024-11-21 19:07:11.857836: val_loss -0.7528 +2024-11-21 19:07:11.866114: Pseudo dice [0.8313] +2024-11-21 19:07:11.866281: Epoch time: 19.35 s +2024-11-21 19:07:12.915467: +2024-11-21 19:07:12.915689: Epoch 1550 +2024-11-21 19:07:12.915796: Current learning rate: 0.00824 +2024-11-21 19:07:32.996737: train_loss -0.7633 +2024-11-21 19:07:32.999100: val_loss -0.714 +2024-11-21 19:07:32.999230: Pseudo dice [0.8139] +2024-11-21 19:07:32.999315: Epoch time: 20.08 s +2024-11-21 19:07:33.905417: +2024-11-21 19:07:33.905605: Epoch 1551 +2024-11-21 19:07:33.905722: Current learning rate: 0.00824 +2024-11-21 19:07:51.748721: train_loss -0.7644 +2024-11-21 19:07:51.748950: val_loss -0.7161 +2024-11-21 19:07:51.749044: Pseudo dice [0.8208] +2024-11-21 19:07:51.749130: Epoch time: 17.84 s +2024-11-21 19:07:52.727772: +2024-11-21 19:07:52.727956: Epoch 1552 +2024-11-21 19:07:52.728072: Current learning rate: 0.00824 +2024-11-21 19:08:10.718003: train_loss -0.7697 +2024-11-21 19:08:10.718220: val_loss -0.744 +2024-11-21 19:08:10.718294: Pseudo dice [0.8205] +2024-11-21 19:08:10.718371: Epoch time: 17.99 s +2024-11-21 19:08:11.544995: +2024-11-21 19:08:11.545416: Epoch 1553 +2024-11-21 19:08:11.545526: Current learning rate: 0.00823 +2024-11-21 19:08:30.609140: train_loss -0.7659 +2024-11-21 19:08:30.609383: val_loss -0.7121 +2024-11-21 19:08:30.609465: Pseudo dice [0.8007] +2024-11-21 19:08:30.609559: Epoch time: 19.06 s +2024-11-21 19:08:31.454622: +2024-11-21 19:08:31.454816: Epoch 1554 +2024-11-21 19:08:31.454925: Current learning rate: 0.00823 +2024-11-21 19:08:49.827397: train_loss -0.7587 +2024-11-21 19:08:49.827606: val_loss -0.729 +2024-11-21 19:08:49.827684: Pseudo dice [0.8148] +2024-11-21 19:08:49.827764: Epoch time: 18.37 s +2024-11-21 19:08:51.033098: +2024-11-21 19:08:51.033317: Epoch 1555 +2024-11-21 19:08:51.033438: Current learning rate: 0.00823 +2024-11-21 19:09:09.481113: train_loss -0.7562 +2024-11-21 19:09:09.481333: val_loss -0.7289 +2024-11-21 19:09:09.481406: Pseudo dice [0.8148] +2024-11-21 19:09:09.481482: Epoch time: 18.45 s +2024-11-21 19:09:10.343336: +2024-11-21 19:09:10.343558: Epoch 1556 +2024-11-21 19:09:10.343672: Current learning rate: 0.00823 +2024-11-21 19:09:28.924189: train_loss -0.7729 +2024-11-21 19:09:28.924428: val_loss -0.7364 +2024-11-21 19:09:28.924506: Pseudo dice [0.8262] +2024-11-21 19:09:28.924602: Epoch time: 18.58 s +2024-11-21 19:09:29.783759: +2024-11-21 19:09:29.784033: Epoch 1557 +2024-11-21 19:09:29.784191: Current learning rate: 0.00823 +2024-11-21 19:09:47.328218: train_loss -0.7773 +2024-11-21 19:09:47.328435: val_loss -0.7546 +2024-11-21 19:09:47.328510: Pseudo dice [0.8244] +2024-11-21 19:09:47.328589: Epoch time: 17.55 s +2024-11-21 19:09:48.186593: +2024-11-21 19:09:48.186864: Epoch 1558 +2024-11-21 19:09:48.186979: Current learning rate: 0.00823 +2024-11-21 19:10:06.671141: train_loss -0.7767 +2024-11-21 19:10:06.671360: val_loss -0.7622 +2024-11-21 19:10:06.671435: Pseudo dice [0.8218] +2024-11-21 19:10:06.671515: Epoch time: 18.49 s +2024-11-21 19:10:07.548702: +2024-11-21 19:10:07.548912: Epoch 1559 +2024-11-21 19:10:07.549032: Current learning rate: 0.00823 +2024-11-21 19:10:25.774501: train_loss -0.772 +2024-11-21 19:10:25.774723: val_loss -0.7287 +2024-11-21 19:10:25.774796: Pseudo dice [0.8209] +2024-11-21 19:10:25.774871: Epoch time: 18.23 s +2024-11-21 19:10:26.623207: +2024-11-21 19:10:26.623489: Epoch 1560 +2024-11-21 19:10:26.623604: Current learning rate: 0.00823 +2024-11-21 19:10:45.857701: train_loss -0.7736 +2024-11-21 19:10:45.857942: val_loss -0.715 +2024-11-21 19:10:45.858029: Pseudo dice [0.8215] +2024-11-21 19:10:45.858113: Epoch time: 19.24 s +2024-11-21 19:10:46.733307: +2024-11-21 19:10:46.733589: Epoch 1561 +2024-11-21 19:10:46.733707: Current learning rate: 0.00823 +2024-11-21 19:11:06.121882: train_loss -0.7709 +2024-11-21 19:11:06.124269: val_loss -0.7454 +2024-11-21 19:11:06.124369: Pseudo dice [0.8241] +2024-11-21 19:11:06.124447: Epoch time: 19.39 s +2024-11-21 19:11:07.117863: +2024-11-21 19:11:07.118054: Epoch 1562 +2024-11-21 19:11:07.118170: Current learning rate: 0.00822 +2024-11-21 19:11:25.782552: train_loss -0.7674 +2024-11-21 19:11:25.782770: val_loss -0.7353 +2024-11-21 19:11:25.782844: Pseudo dice [0.8144] +2024-11-21 19:11:25.782922: Epoch time: 18.67 s +2024-11-21 19:11:26.631905: +2024-11-21 19:11:26.632117: Epoch 1563 +2024-11-21 19:11:26.632242: Current learning rate: 0.00822 +2024-11-21 19:11:44.667313: train_loss -0.765 +2024-11-21 19:11:44.667586: val_loss -0.7508 +2024-11-21 19:11:44.667664: Pseudo dice [0.8182] +2024-11-21 19:11:44.667744: Epoch time: 18.04 s +2024-11-21 19:11:45.513780: +2024-11-21 19:11:45.513986: Epoch 1564 +2024-11-21 19:11:45.514106: Current learning rate: 0.00822 +2024-11-21 19:12:04.164358: train_loss -0.7709 +2024-11-21 19:12:04.165375: val_loss -0.7337 +2024-11-21 19:12:04.165552: Pseudo dice [0.8209] +2024-11-21 19:12:04.165642: Epoch time: 18.65 s +2024-11-21 19:12:05.022961: +2024-11-21 19:12:05.023174: Epoch 1565 +2024-11-21 19:12:05.023288: Current learning rate: 0.00822 +2024-11-21 19:12:24.397530: train_loss -0.7745 +2024-11-21 19:12:24.397738: val_loss -0.7496 +2024-11-21 19:12:24.400023: Pseudo dice [0.8349] +2024-11-21 19:12:24.400126: Epoch time: 19.38 s +2024-11-21 19:12:25.922530: +2024-11-21 19:12:25.922763: Epoch 1566 +2024-11-21 19:12:25.922874: Current learning rate: 0.00822 +2024-11-21 19:12:43.824462: train_loss -0.7615 +2024-11-21 19:12:43.824669: val_loss -0.7308 +2024-11-21 19:12:43.824879: Pseudo dice [0.8136] +2024-11-21 19:12:43.824960: Epoch time: 17.9 s +2024-11-21 19:12:44.702031: +2024-11-21 19:12:44.702313: Epoch 1567 +2024-11-21 19:12:44.702434: Current learning rate: 0.00822 +2024-11-21 19:13:03.914618: train_loss -0.7678 +2024-11-21 19:13:03.914859: val_loss -0.7508 +2024-11-21 19:13:03.914935: Pseudo dice [0.8376] +2024-11-21 19:13:03.915018: Epoch time: 19.21 s +2024-11-21 19:13:04.764549: +2024-11-21 19:13:04.764755: Epoch 1568 +2024-11-21 19:13:04.764868: Current learning rate: 0.00822 +2024-11-21 19:13:23.934468: train_loss -0.7741 +2024-11-21 19:13:23.934682: val_loss -0.7392 +2024-11-21 19:13:23.934755: Pseudo dice [0.824] +2024-11-21 19:13:23.934830: Epoch time: 19.17 s +2024-11-21 19:13:24.784382: +2024-11-21 19:13:24.784596: Epoch 1569 +2024-11-21 19:13:24.784712: Current learning rate: 0.00822 +2024-11-21 19:13:42.383315: train_loss -0.7802 +2024-11-21 19:13:42.409318: val_loss -0.7266 +2024-11-21 19:13:42.409470: Pseudo dice [0.8098] +2024-11-21 19:13:42.409556: Epoch time: 17.6 s +2024-11-21 19:13:43.351907: +2024-11-21 19:13:43.352119: Epoch 1570 +2024-11-21 19:13:43.352235: Current learning rate: 0.00822 +2024-11-21 19:14:01.264531: train_loss -0.7835 +2024-11-21 19:14:01.264782: val_loss -0.7502 +2024-11-21 19:14:01.264859: Pseudo dice [0.8271] +2024-11-21 19:14:01.264957: Epoch time: 17.91 s +2024-11-21 19:14:02.122588: +2024-11-21 19:14:02.122838: Epoch 1571 +2024-11-21 19:14:02.122954: Current learning rate: 0.00821 +2024-11-21 19:14:20.795717: train_loss -0.7824 +2024-11-21 19:14:20.795921: val_loss -0.7485 +2024-11-21 19:14:20.796009: Pseudo dice [0.8425] +2024-11-21 19:14:20.796088: Epoch time: 18.67 s +2024-11-21 19:14:21.645491: +2024-11-21 19:14:21.645698: Epoch 1572 +2024-11-21 19:14:21.645811: Current learning rate: 0.00821 +2024-11-21 19:14:40.577960: train_loss -0.78 +2024-11-21 19:14:40.578174: val_loss -0.7405 +2024-11-21 19:14:40.578249: Pseudo dice [0.8148] +2024-11-21 19:14:40.578323: Epoch time: 18.93 s +2024-11-21 19:14:41.428295: +2024-11-21 19:14:41.428486: Epoch 1573 +2024-11-21 19:14:41.428603: Current learning rate: 0.00821 +2024-11-21 19:14:59.510642: train_loss -0.7705 +2024-11-21 19:14:59.510852: val_loss -0.7175 +2024-11-21 19:14:59.511068: Pseudo dice [0.8288] +2024-11-21 19:14:59.511157: Epoch time: 18.08 s +2024-11-21 19:15:00.363633: +2024-11-21 19:15:00.363897: Epoch 1574 +2024-11-21 19:15:00.364021: Current learning rate: 0.00821 +2024-11-21 19:15:18.964492: train_loss -0.7763 +2024-11-21 19:15:18.964731: val_loss -0.7529 +2024-11-21 19:15:18.964803: Pseudo dice [0.8385] +2024-11-21 19:15:18.964880: Epoch time: 18.6 s +2024-11-21 19:15:19.816577: +2024-11-21 19:15:19.834280: Epoch 1575 +2024-11-21 19:15:19.834410: Current learning rate: 0.00821 +2024-11-21 19:15:38.254771: train_loss -0.7751 +2024-11-21 19:15:38.254986: val_loss -0.74 +2024-11-21 19:15:38.255069: Pseudo dice [0.8221] +2024-11-21 19:15:38.255146: Epoch time: 18.44 s +2024-11-21 19:15:39.108874: +2024-11-21 19:15:39.109105: Epoch 1576 +2024-11-21 19:15:39.109223: Current learning rate: 0.00821 +2024-11-21 19:15:58.405085: train_loss -0.7719 +2024-11-21 19:15:58.405305: val_loss -0.7228 +2024-11-21 19:15:58.405382: Pseudo dice [0.819] +2024-11-21 19:15:58.405462: Epoch time: 19.3 s +2024-11-21 19:15:59.669768: +2024-11-21 19:15:59.669998: Epoch 1577 +2024-11-21 19:15:59.670121: Current learning rate: 0.00821 +2024-11-21 19:16:19.721203: train_loss -0.7733 +2024-11-21 19:16:19.721447: val_loss -0.7428 +2024-11-21 19:16:19.721526: Pseudo dice [0.8265] +2024-11-21 19:16:19.721629: Epoch time: 20.05 s +2024-11-21 19:16:20.681375: +2024-11-21 19:16:20.681595: Epoch 1578 +2024-11-21 19:16:20.681708: Current learning rate: 0.00821 +2024-11-21 19:16:38.577210: train_loss -0.7716 +2024-11-21 19:16:38.577422: val_loss -0.7248 +2024-11-21 19:16:38.577515: Pseudo dice [0.8021] +2024-11-21 19:16:38.577596: Epoch time: 17.9 s +2024-11-21 19:16:39.428240: +2024-11-21 19:16:39.428490: Epoch 1579 +2024-11-21 19:16:39.428604: Current learning rate: 0.0082 +2024-11-21 19:16:58.547549: train_loss -0.7618 +2024-11-21 19:16:58.547761: val_loss -0.7443 +2024-11-21 19:16:58.547834: Pseudo dice [0.8279] +2024-11-21 19:16:58.547912: Epoch time: 19.12 s +2024-11-21 19:16:59.393874: +2024-11-21 19:16:59.394113: Epoch 1580 +2024-11-21 19:16:59.394225: Current learning rate: 0.0082 +2024-11-21 19:17:17.200012: train_loss -0.7644 +2024-11-21 19:17:17.200233: val_loss -0.7086 +2024-11-21 19:17:17.200310: Pseudo dice [0.8051] +2024-11-21 19:17:17.200393: Epoch time: 17.81 s +2024-11-21 19:17:18.055068: +2024-11-21 19:17:18.055277: Epoch 1581 +2024-11-21 19:17:18.055391: Current learning rate: 0.0082 +2024-11-21 19:17:37.169999: train_loss -0.7509 +2024-11-21 19:17:37.170228: val_loss -0.706 +2024-11-21 19:17:37.170299: Pseudo dice [0.8198] +2024-11-21 19:17:37.170377: Epoch time: 19.12 s +2024-11-21 19:17:38.038379: +2024-11-21 19:17:38.038611: Epoch 1582 +2024-11-21 19:17:38.038729: Current learning rate: 0.0082 +2024-11-21 19:17:56.294600: train_loss -0.7525 +2024-11-21 19:17:56.294816: val_loss -0.7297 +2024-11-21 19:17:56.294887: Pseudo dice [0.8185] +2024-11-21 19:17:56.294961: Epoch time: 18.26 s +2024-11-21 19:17:57.200310: +2024-11-21 19:17:57.200527: Epoch 1583 +2024-11-21 19:17:57.200640: Current learning rate: 0.0082 +2024-11-21 19:18:15.482829: train_loss -0.757 +2024-11-21 19:18:15.483095: val_loss -0.7118 +2024-11-21 19:18:15.483172: Pseudo dice [0.7871] +2024-11-21 19:18:15.483249: Epoch time: 18.28 s +2024-11-21 19:18:16.337608: +2024-11-21 19:18:16.337805: Epoch 1584 +2024-11-21 19:18:16.337913: Current learning rate: 0.0082 +2024-11-21 19:18:34.801538: train_loss -0.7604 +2024-11-21 19:18:34.801763: val_loss -0.7401 +2024-11-21 19:18:34.801832: Pseudo dice [0.8259] +2024-11-21 19:18:34.801916: Epoch time: 18.46 s +2024-11-21 19:18:35.686677: +2024-11-21 19:18:35.686899: Epoch 1585 +2024-11-21 19:18:35.687016: Current learning rate: 0.0082 +2024-11-21 19:18:54.918113: train_loss -0.764 +2024-11-21 19:18:54.920456: val_loss -0.7307 +2024-11-21 19:18:54.920552: Pseudo dice [0.8337] +2024-11-21 19:18:54.920632: Epoch time: 19.23 s +2024-11-21 19:18:55.799588: +2024-11-21 19:18:55.799807: Epoch 1586 +2024-11-21 19:18:55.799925: Current learning rate: 0.0082 +2024-11-21 19:19:14.465143: train_loss -0.7637 +2024-11-21 19:19:14.465405: val_loss -0.7345 +2024-11-21 19:19:14.465486: Pseudo dice [0.8405] +2024-11-21 19:19:14.465568: Epoch time: 18.67 s +2024-11-21 19:19:15.733161: +2024-11-21 19:19:15.733439: Epoch 1587 +2024-11-21 19:19:15.733560: Current learning rate: 0.0082 +2024-11-21 19:19:34.621054: train_loss -0.7726 +2024-11-21 19:19:34.621267: val_loss -0.7355 +2024-11-21 19:19:34.621341: Pseudo dice [0.8341] +2024-11-21 19:19:34.635632: Epoch time: 18.89 s +2024-11-21 19:19:35.876153: +2024-11-21 19:19:35.876363: Epoch 1588 +2024-11-21 19:19:35.876473: Current learning rate: 0.00819 +2024-11-21 19:19:54.628200: train_loss -0.7605 +2024-11-21 19:19:54.628458: val_loss -0.7547 +2024-11-21 19:19:54.628531: Pseudo dice [0.8436] +2024-11-21 19:19:54.628612: Epoch time: 18.75 s +2024-11-21 19:19:55.515157: +2024-11-21 19:19:55.515397: Epoch 1589 +2024-11-21 19:19:55.515525: Current learning rate: 0.00819 +2024-11-21 19:20:14.145915: train_loss -0.7655 +2024-11-21 19:20:14.146129: val_loss -0.7382 +2024-11-21 19:20:14.146203: Pseudo dice [0.8259] +2024-11-21 19:20:14.146277: Epoch time: 18.63 s +2024-11-21 19:20:14.994684: +2024-11-21 19:20:14.994945: Epoch 1590 +2024-11-21 19:20:14.995067: Current learning rate: 0.00819 +2024-11-21 19:20:34.509771: train_loss -0.7835 +2024-11-21 19:20:34.509989: val_loss -0.7429 +2024-11-21 19:20:34.510077: Pseudo dice [0.8321] +2024-11-21 19:20:34.510155: Epoch time: 19.52 s +2024-11-21 19:20:35.359308: +2024-11-21 19:20:35.359524: Epoch 1591 +2024-11-21 19:20:35.359636: Current learning rate: 0.00819 +2024-11-21 19:20:54.728280: train_loss -0.7518 +2024-11-21 19:20:54.728537: val_loss -0.747 +2024-11-21 19:20:54.728612: Pseudo dice [0.8297] +2024-11-21 19:20:54.728698: Epoch time: 19.37 s +2024-11-21 19:20:55.580876: +2024-11-21 19:20:55.581079: Epoch 1592 +2024-11-21 19:20:55.581199: Current learning rate: 0.00819 +2024-11-21 19:21:14.777552: train_loss -0.7681 +2024-11-21 19:21:14.777893: val_loss -0.7397 +2024-11-21 19:21:14.777979: Pseudo dice [0.8287] +2024-11-21 19:21:14.778061: Epoch time: 19.2 s +2024-11-21 19:21:15.651652: +2024-11-21 19:21:15.651899: Epoch 1593 +2024-11-21 19:21:15.652011: Current learning rate: 0.00819 +2024-11-21 19:21:34.852988: train_loss -0.7642 +2024-11-21 19:21:34.853213: val_loss -0.7138 +2024-11-21 19:21:34.853285: Pseudo dice [0.8043] +2024-11-21 19:21:34.853361: Epoch time: 19.2 s +2024-11-21 19:21:35.748318: +2024-11-21 19:21:35.748568: Epoch 1594 +2024-11-21 19:21:35.748687: Current learning rate: 0.00819 +2024-11-21 19:21:54.711902: train_loss -0.7702 +2024-11-21 19:21:54.712118: val_loss -0.7004 +2024-11-21 19:21:54.712192: Pseudo dice [0.8198] +2024-11-21 19:21:54.712270: Epoch time: 18.96 s +2024-11-21 19:21:55.565433: +2024-11-21 19:21:55.565758: Epoch 1595 +2024-11-21 19:21:55.565870: Current learning rate: 0.00819 +2024-11-21 19:22:14.593402: train_loss -0.7688 +2024-11-21 19:22:14.593645: val_loss -0.7376 +2024-11-21 19:22:14.593719: Pseudo dice [0.8153] +2024-11-21 19:22:14.593803: Epoch time: 19.03 s +2024-11-21 19:22:15.435997: +2024-11-21 19:22:15.436200: Epoch 1596 +2024-11-21 19:22:15.436314: Current learning rate: 0.00819 +2024-11-21 19:22:35.246263: train_loss -0.7706 +2024-11-21 19:22:35.246469: val_loss -0.7266 +2024-11-21 19:22:35.246542: Pseudo dice [0.8294] +2024-11-21 19:22:35.246619: Epoch time: 19.81 s +2024-11-21 19:22:36.095758: +2024-11-21 19:22:36.095961: Epoch 1597 +2024-11-21 19:22:36.096079: Current learning rate: 0.00818 +2024-11-21 19:22:55.450318: train_loss -0.7752 +2024-11-21 19:22:55.450524: val_loss -0.7707 +2024-11-21 19:22:55.450598: Pseudo dice [0.8275] +2024-11-21 19:22:55.450728: Epoch time: 19.36 s +2024-11-21 19:22:56.307117: +2024-11-21 19:22:56.307330: Epoch 1598 +2024-11-21 19:22:56.307447: Current learning rate: 0.00818 +2024-11-21 19:23:14.154830: train_loss -0.7776 +2024-11-21 19:23:14.155042: val_loss -0.7216 +2024-11-21 19:23:14.155119: Pseudo dice [0.7995] +2024-11-21 19:23:14.155196: Epoch time: 17.85 s +2024-11-21 19:23:15.284168: +2024-11-21 19:23:15.284420: Epoch 1599 +2024-11-21 19:23:15.284573: Current learning rate: 0.00818 +2024-11-21 19:23:34.069808: train_loss -0.7744 +2024-11-21 19:23:34.070029: val_loss -0.7112 +2024-11-21 19:23:34.070123: Pseudo dice [0.8098] +2024-11-21 19:23:34.070203: Epoch time: 18.79 s +2024-11-21 19:23:35.146538: +2024-11-21 19:23:35.146768: Epoch 1600 +2024-11-21 19:23:35.146881: Current learning rate: 0.00818 +2024-11-21 19:23:53.849497: train_loss -0.7637 +2024-11-21 19:23:53.863364: val_loss -0.6941 +2024-11-21 19:23:53.863516: Pseudo dice [0.8002] +2024-11-21 19:23:53.863598: Epoch time: 18.7 s +2024-11-21 19:23:54.752800: +2024-11-21 19:23:54.753098: Epoch 1601 +2024-11-21 19:23:54.753212: Current learning rate: 0.00818 +2024-11-21 19:24:13.858236: train_loss -0.7627 +2024-11-21 19:24:13.863632: val_loss -0.7481 +2024-11-21 19:24:13.863759: Pseudo dice [0.8163] +2024-11-21 19:24:13.863842: Epoch time: 19.11 s +2024-11-21 19:24:14.871979: +2024-11-21 19:24:14.872237: Epoch 1602 +2024-11-21 19:24:14.872355: Current learning rate: 0.00818 +2024-11-21 19:24:35.148848: train_loss -0.7584 +2024-11-21 19:24:35.149095: val_loss -0.7119 +2024-11-21 19:24:35.149169: Pseudo dice [0.7753] +2024-11-21 19:24:35.149254: Epoch time: 20.28 s +2024-11-21 19:24:36.105111: +2024-11-21 19:24:36.105342: Epoch 1603 +2024-11-21 19:24:36.105457: Current learning rate: 0.00818 +2024-11-21 19:24:53.963688: train_loss -0.7622 +2024-11-21 19:24:53.963903: val_loss -0.7272 +2024-11-21 19:24:53.963978: Pseudo dice [0.8168] +2024-11-21 19:24:53.964061: Epoch time: 17.86 s +2024-11-21 19:24:54.867625: +2024-11-21 19:24:54.867837: Epoch 1604 +2024-11-21 19:24:54.867951: Current learning rate: 0.00818 +2024-11-21 19:25:13.962827: train_loss -0.7538 +2024-11-21 19:25:13.963044: val_loss -0.7385 +2024-11-21 19:25:13.963120: Pseudo dice [0.8123] +2024-11-21 19:25:13.963197: Epoch time: 19.1 s +2024-11-21 19:25:14.815496: +2024-11-21 19:25:14.815697: Epoch 1605 +2024-11-21 19:25:14.815809: Current learning rate: 0.00817 +2024-11-21 19:25:33.211345: train_loss -0.7555 +2024-11-21 19:25:33.211559: val_loss -0.7137 +2024-11-21 19:25:33.211632: Pseudo dice [0.8175] +2024-11-21 19:25:33.211710: Epoch time: 18.4 s +2024-11-21 19:25:34.062491: +2024-11-21 19:25:34.062700: Epoch 1606 +2024-11-21 19:25:34.062825: Current learning rate: 0.00817 +2024-11-21 19:25:52.533507: train_loss -0.7622 +2024-11-21 19:25:52.533768: val_loss -0.7291 +2024-11-21 19:25:52.533904: Pseudo dice [0.8251] +2024-11-21 19:25:52.533989: Epoch time: 18.47 s +2024-11-21 19:25:53.390544: +2024-11-21 19:25:53.390767: Epoch 1607 +2024-11-21 19:25:53.390887: Current learning rate: 0.00817 +2024-11-21 19:26:12.259014: train_loss -0.7694 +2024-11-21 19:26:12.259236: val_loss -0.7378 +2024-11-21 19:26:12.263963: Pseudo dice [0.8335] +2024-11-21 19:26:12.264221: Epoch time: 18.87 s +2024-11-21 19:26:13.220325: +2024-11-21 19:26:13.220508: Epoch 1608 +2024-11-21 19:26:13.220617: Current learning rate: 0.00817 +2024-11-21 19:26:32.829160: train_loss -0.7657 +2024-11-21 19:26:32.829379: val_loss -0.7485 +2024-11-21 19:26:32.829453: Pseudo dice [0.8315] +2024-11-21 19:26:32.829531: Epoch time: 19.61 s +2024-11-21 19:26:33.680270: +2024-11-21 19:26:33.680516: Epoch 1609 +2024-11-21 19:26:33.680631: Current learning rate: 0.00817 +2024-11-21 19:26:52.181119: train_loss -0.7673 +2024-11-21 19:26:52.181344: val_loss -0.7218 +2024-11-21 19:26:52.181418: Pseudo dice [0.8304] +2024-11-21 19:26:52.181496: Epoch time: 18.5 s +2024-11-21 19:26:53.417147: +2024-11-21 19:26:53.417360: Epoch 1610 +2024-11-21 19:26:53.417470: Current learning rate: 0.00817 +2024-11-21 19:27:13.065001: train_loss -0.7693 +2024-11-21 19:27:13.065232: val_loss -0.7437 +2024-11-21 19:27:13.065306: Pseudo dice [0.8212] +2024-11-21 19:27:13.065386: Epoch time: 19.65 s +2024-11-21 19:27:13.912104: +2024-11-21 19:27:13.912322: Epoch 1611 +2024-11-21 19:27:13.912436: Current learning rate: 0.00817 +2024-11-21 19:27:33.118719: train_loss -0.7754 +2024-11-21 19:27:33.118935: val_loss -0.7296 +2024-11-21 19:27:33.119019: Pseudo dice [0.812] +2024-11-21 19:27:33.124340: Epoch time: 19.21 s +2024-11-21 19:27:34.006622: +2024-11-21 19:27:34.006913: Epoch 1612 +2024-11-21 19:27:34.007035: Current learning rate: 0.00817 +2024-11-21 19:27:53.147589: train_loss -0.7659 +2024-11-21 19:27:53.147858: val_loss -0.7372 +2024-11-21 19:27:53.147940: Pseudo dice [0.8034] +2024-11-21 19:27:53.148026: Epoch time: 19.14 s +2024-11-21 19:27:54.002579: +2024-11-21 19:27:54.002801: Epoch 1613 +2024-11-21 19:27:54.002922: Current learning rate: 0.00817 +2024-11-21 19:28:13.592742: train_loss -0.7639 +2024-11-21 19:28:13.593343: val_loss -0.7316 +2024-11-21 19:28:13.593421: Pseudo dice [0.8092] +2024-11-21 19:28:13.593504: Epoch time: 19.59 s +2024-11-21 19:28:14.447708: +2024-11-21 19:28:14.447920: Epoch 1614 +2024-11-21 19:28:14.448036: Current learning rate: 0.00816 +2024-11-21 19:28:33.749968: train_loss -0.7748 +2024-11-21 19:28:33.750194: val_loss -0.7552 +2024-11-21 19:28:33.750269: Pseudo dice [0.8317] +2024-11-21 19:28:33.750346: Epoch time: 19.3 s +2024-11-21 19:28:34.778312: +2024-11-21 19:28:34.778578: Epoch 1615 +2024-11-21 19:28:34.778695: Current learning rate: 0.00816 +2024-11-21 19:28:52.853975: train_loss -0.7775 +2024-11-21 19:28:52.854202: val_loss -0.7665 +2024-11-21 19:28:52.854278: Pseudo dice [0.8371] +2024-11-21 19:28:52.854358: Epoch time: 18.08 s +2024-11-21 19:28:53.704532: +2024-11-21 19:28:53.704746: Epoch 1616 +2024-11-21 19:28:53.704863: Current learning rate: 0.00816 +2024-11-21 19:29:11.924508: train_loss -0.771 +2024-11-21 19:29:11.924745: val_loss -0.7533 +2024-11-21 19:29:11.924825: Pseudo dice [0.8231] +2024-11-21 19:29:11.924906: Epoch time: 18.22 s +2024-11-21 19:29:12.961112: +2024-11-21 19:29:12.961371: Epoch 1617 +2024-11-21 19:29:12.961482: Current learning rate: 0.00816 +2024-11-21 19:29:31.261703: train_loss -0.7811 +2024-11-21 19:29:31.261952: val_loss -0.724 +2024-11-21 19:29:31.262032: Pseudo dice [0.8219] +2024-11-21 19:29:31.262115: Epoch time: 18.3 s +2024-11-21 19:29:32.116882: +2024-11-21 19:29:32.117139: Epoch 1618 +2024-11-21 19:29:32.117258: Current learning rate: 0.00816 +2024-11-21 19:29:50.414384: train_loss -0.7761 +2024-11-21 19:29:50.414787: val_loss -0.7337 +2024-11-21 19:29:50.414875: Pseudo dice [0.8288] +2024-11-21 19:29:50.414952: Epoch time: 18.3 s +2024-11-21 19:29:51.264527: +2024-11-21 19:29:51.264724: Epoch 1619 +2024-11-21 19:29:51.264840: Current learning rate: 0.00816 +2024-11-21 19:30:08.507960: train_loss -0.7768 +2024-11-21 19:30:08.508245: val_loss -0.7334 +2024-11-21 19:30:08.508319: Pseudo dice [0.8284] +2024-11-21 19:30:08.508394: Epoch time: 17.24 s +2024-11-21 19:30:09.366938: +2024-11-21 19:30:09.367165: Epoch 1620 +2024-11-21 19:30:09.367279: Current learning rate: 0.00816 +2024-11-21 19:30:28.266499: train_loss -0.7812 +2024-11-21 19:30:28.266749: val_loss -0.7092 +2024-11-21 19:30:28.266828: Pseudo dice [0.8062] +2024-11-21 19:30:28.266913: Epoch time: 18.9 s +2024-11-21 19:30:29.527200: +2024-11-21 19:30:29.527502: Epoch 1621 +2024-11-21 19:30:29.527624: Current learning rate: 0.00816 +2024-11-21 19:30:48.142864: train_loss -0.7692 +2024-11-21 19:30:48.143086: val_loss -0.7582 +2024-11-21 19:30:48.143162: Pseudo dice [0.8218] +2024-11-21 19:30:48.143309: Epoch time: 18.62 s +2024-11-21 19:30:49.001943: +2024-11-21 19:30:49.002156: Epoch 1622 +2024-11-21 19:30:49.002268: Current learning rate: 0.00816 +2024-11-21 19:31:07.449742: train_loss -0.7727 +2024-11-21 19:31:07.449960: val_loss -0.7441 +2024-11-21 19:31:07.450044: Pseudo dice [0.8308] +2024-11-21 19:31:07.450125: Epoch time: 18.45 s +2024-11-21 19:31:08.319001: +2024-11-21 19:31:08.319279: Epoch 1623 +2024-11-21 19:31:08.319389: Current learning rate: 0.00815 +2024-11-21 19:31:25.988620: train_loss -0.7664 +2024-11-21 19:31:25.988837: val_loss -0.7386 +2024-11-21 19:31:25.988912: Pseudo dice [0.8201] +2024-11-21 19:31:25.988989: Epoch time: 17.67 s +2024-11-21 19:31:26.853218: +2024-11-21 19:31:26.853422: Epoch 1624 +2024-11-21 19:31:26.853532: Current learning rate: 0.00815 +2024-11-21 19:31:45.399036: train_loss -0.766 +2024-11-21 19:31:45.399275: val_loss -0.754 +2024-11-21 19:31:45.399355: Pseudo dice [0.8194] +2024-11-21 19:31:45.399468: Epoch time: 18.55 s +2024-11-21 19:31:46.254849: +2024-11-21 19:31:46.255058: Epoch 1625 +2024-11-21 19:31:46.255172: Current learning rate: 0.00815 +2024-11-21 19:32:05.497724: train_loss -0.7685 +2024-11-21 19:32:05.497930: val_loss -0.7424 +2024-11-21 19:32:05.498008: Pseudo dice [0.8191] +2024-11-21 19:32:05.498082: Epoch time: 19.24 s +2024-11-21 19:32:06.416626: +2024-11-21 19:32:06.416838: Epoch 1626 +2024-11-21 19:32:06.416950: Current learning rate: 0.00815 +2024-11-21 19:32:24.746726: train_loss -0.7676 +2024-11-21 19:32:24.746941: val_loss -0.7471 +2024-11-21 19:32:24.747022: Pseudo dice [0.8379] +2024-11-21 19:32:24.747096: Epoch time: 18.33 s +2024-11-21 19:32:25.612934: +2024-11-21 19:32:25.613254: Epoch 1627 +2024-11-21 19:32:25.613368: Current learning rate: 0.00815 +2024-11-21 19:32:43.993480: train_loss -0.7742 +2024-11-21 19:32:43.993752: val_loss -0.734 +2024-11-21 19:32:43.993886: Pseudo dice [0.8119] +2024-11-21 19:32:43.993968: Epoch time: 18.38 s +2024-11-21 19:32:44.848222: +2024-11-21 19:32:44.848509: Epoch 1628 +2024-11-21 19:32:44.848621: Current learning rate: 0.00815 +2024-11-21 19:33:04.171436: train_loss -0.7773 +2024-11-21 19:33:04.171675: val_loss -0.7579 +2024-11-21 19:33:04.171748: Pseudo dice [0.833] +2024-11-21 19:33:04.173980: Epoch time: 19.32 s +2024-11-21 19:33:05.156041: +2024-11-21 19:33:05.156238: Epoch 1629 +2024-11-21 19:33:05.156353: Current learning rate: 0.00815 +2024-11-21 19:33:23.623945: train_loss -0.7692 +2024-11-21 19:33:23.624169: val_loss -0.7331 +2024-11-21 19:33:23.626483: Pseudo dice [0.8313] +2024-11-21 19:33:23.626596: Epoch time: 18.47 s +2024-11-21 19:33:24.578594: +2024-11-21 19:33:24.578781: Epoch 1630 +2024-11-21 19:33:24.578895: Current learning rate: 0.00815 +2024-11-21 19:33:44.115919: train_loss -0.7686 +2024-11-21 19:33:44.116156: val_loss -0.7381 +2024-11-21 19:33:44.116238: Pseudo dice [0.8066] +2024-11-21 19:33:44.116314: Epoch time: 19.54 s +2024-11-21 19:33:44.970425: +2024-11-21 19:33:44.970624: Epoch 1631 +2024-11-21 19:33:44.970735: Current learning rate: 0.00814 +2024-11-21 19:34:04.493404: train_loss -0.7697 +2024-11-21 19:34:04.495849: val_loss -0.7605 +2024-11-21 19:34:04.495977: Pseudo dice [0.8434] +2024-11-21 19:34:04.496083: Epoch time: 19.52 s +2024-11-21 19:34:05.775327: +2024-11-21 19:34:05.775614: Epoch 1632 +2024-11-21 19:34:05.775731: Current learning rate: 0.00814 +2024-11-21 19:34:25.028140: train_loss -0.7704 +2024-11-21 19:34:25.028387: val_loss -0.7173 +2024-11-21 19:34:25.028463: Pseudo dice [0.8205] +2024-11-21 19:34:25.028560: Epoch time: 19.25 s +2024-11-21 19:34:25.884789: +2024-11-21 19:34:25.885036: Epoch 1633 +2024-11-21 19:34:25.885154: Current learning rate: 0.00814 +2024-11-21 19:34:45.004042: train_loss -0.7604 +2024-11-21 19:34:45.004259: val_loss -0.7395 +2024-11-21 19:34:45.004336: Pseudo dice [0.8345] +2024-11-21 19:34:45.004412: Epoch time: 19.12 s +2024-11-21 19:34:45.873727: +2024-11-21 19:34:45.874045: Epoch 1634 +2024-11-21 19:34:45.874242: Current learning rate: 0.00814 +2024-11-21 19:35:04.429872: train_loss -0.7657 +2024-11-21 19:35:04.430099: val_loss -0.7214 +2024-11-21 19:35:04.430180: Pseudo dice [0.7885] +2024-11-21 19:35:04.430255: Epoch time: 18.56 s +2024-11-21 19:35:05.303518: +2024-11-21 19:35:05.303855: Epoch 1635 +2024-11-21 19:35:05.304001: Current learning rate: 0.00814 +2024-11-21 19:35:24.406476: train_loss -0.7738 +2024-11-21 19:35:24.406713: val_loss -0.7591 +2024-11-21 19:35:24.406875: Pseudo dice [0.8467] +2024-11-21 19:35:24.406969: Epoch time: 19.1 s +2024-11-21 19:35:25.260500: +2024-11-21 19:35:25.260707: Epoch 1636 +2024-11-21 19:35:25.260817: Current learning rate: 0.00814 +2024-11-21 19:35:43.197821: train_loss -0.7738 +2024-11-21 19:35:43.198055: val_loss -0.7202 +2024-11-21 19:35:43.198128: Pseudo dice [0.8267] +2024-11-21 19:35:43.198205: Epoch time: 17.94 s +2024-11-21 19:35:44.181848: +2024-11-21 19:35:44.182058: Epoch 1637 +2024-11-21 19:35:44.182177: Current learning rate: 0.00814 +2024-11-21 19:36:03.729282: train_loss -0.7595 +2024-11-21 19:36:03.729493: val_loss -0.7404 +2024-11-21 19:36:03.729567: Pseudo dice [0.8196] +2024-11-21 19:36:03.729644: Epoch time: 19.55 s +2024-11-21 19:36:04.734257: +2024-11-21 19:36:04.734458: Epoch 1638 +2024-11-21 19:36:04.734571: Current learning rate: 0.00814 +2024-11-21 19:36:22.986427: train_loss -0.7666 +2024-11-21 19:36:22.991839: val_loss -0.741 +2024-11-21 19:36:22.992673: Pseudo dice [0.8309] +2024-11-21 19:36:22.992804: Epoch time: 18.25 s +2024-11-21 19:36:23.869550: +2024-11-21 19:36:23.869745: Epoch 1639 +2024-11-21 19:36:23.869858: Current learning rate: 0.00814 +2024-11-21 19:36:43.160427: train_loss -0.7644 +2024-11-21 19:36:43.160666: val_loss -0.7221 +2024-11-21 19:36:43.160742: Pseudo dice [0.8181] +2024-11-21 19:36:43.160873: Epoch time: 19.29 s +2024-11-21 19:36:43.996791: +2024-11-21 19:36:43.997086: Epoch 1640 +2024-11-21 19:36:43.997197: Current learning rate: 0.00813 +2024-11-21 19:37:02.173180: train_loss -0.7705 +2024-11-21 19:37:02.173401: val_loss -0.7323 +2024-11-21 19:37:02.173477: Pseudo dice [0.8196] +2024-11-21 19:37:02.173555: Epoch time: 18.18 s +2024-11-21 19:37:03.055166: +2024-11-21 19:37:03.055456: Epoch 1641 +2024-11-21 19:37:03.055573: Current learning rate: 0.00813 +2024-11-21 19:37:21.431289: train_loss -0.7781 +2024-11-21 19:37:21.431506: val_loss -0.7384 +2024-11-21 19:37:21.431580: Pseudo dice [0.8333] +2024-11-21 19:37:21.431655: Epoch time: 18.38 s +2024-11-21 19:37:22.302211: +2024-11-21 19:37:22.302432: Epoch 1642 +2024-11-21 19:37:22.302551: Current learning rate: 0.00813 +2024-11-21 19:37:41.409443: train_loss -0.7723 +2024-11-21 19:37:41.409687: val_loss -0.7088 +2024-11-21 19:37:41.409761: Pseudo dice [0.7652] +2024-11-21 19:37:41.409851: Epoch time: 19.11 s +2024-11-21 19:37:42.248526: +2024-11-21 19:37:42.248736: Epoch 1643 +2024-11-21 19:37:42.248849: Current learning rate: 0.00813 +2024-11-21 19:38:00.983603: train_loss -0.7645 +2024-11-21 19:38:00.986207: val_loss -0.7373 +2024-11-21 19:38:00.986325: Pseudo dice [0.833] +2024-11-21 19:38:00.986403: Epoch time: 18.74 s +2024-11-21 19:38:01.987420: +2024-11-21 19:38:01.987668: Epoch 1644 +2024-11-21 19:38:01.987790: Current learning rate: 0.00813 +2024-11-21 19:38:20.445278: train_loss -0.766 +2024-11-21 19:38:20.445848: val_loss -0.7734 +2024-11-21 19:38:20.445955: Pseudo dice [0.8433] +2024-11-21 19:38:20.446043: Epoch time: 18.46 s +2024-11-21 19:38:21.282107: +2024-11-21 19:38:21.282337: Epoch 1645 +2024-11-21 19:38:21.282454: Current learning rate: 0.00813 +2024-11-21 19:38:39.572268: train_loss -0.766 +2024-11-21 19:38:39.572539: val_loss -0.7519 +2024-11-21 19:38:39.572614: Pseudo dice [0.8143] +2024-11-21 19:38:39.572701: Epoch time: 18.29 s +2024-11-21 19:38:40.417149: +2024-11-21 19:38:40.417367: Epoch 1646 +2024-11-21 19:38:40.417483: Current learning rate: 0.00813 +2024-11-21 19:38:59.009280: train_loss -0.7636 +2024-11-21 19:38:59.009532: val_loss -0.7256 +2024-11-21 19:38:59.009664: Pseudo dice [0.8221] +2024-11-21 19:38:59.009748: Epoch time: 18.59 s +2024-11-21 19:38:59.954972: +2024-11-21 19:38:59.955202: Epoch 1647 +2024-11-21 19:38:59.955317: Current learning rate: 0.00813 +2024-11-21 19:39:19.112405: train_loss -0.7692 +2024-11-21 19:39:19.112618: val_loss -0.7431 +2024-11-21 19:39:19.112696: Pseudo dice [0.8079] +2024-11-21 19:39:19.112773: Epoch time: 19.16 s +2024-11-21 19:39:19.956722: +2024-11-21 19:39:19.956942: Epoch 1648 +2024-11-21 19:39:19.957062: Current learning rate: 0.00813 +2024-11-21 19:39:38.172072: train_loss -0.7655 +2024-11-21 19:39:38.172283: val_loss -0.7351 +2024-11-21 19:39:38.172411: Pseudo dice [0.8069] +2024-11-21 19:39:38.172495: Epoch time: 18.22 s +2024-11-21 19:39:39.015174: +2024-11-21 19:39:39.015398: Epoch 1649 +2024-11-21 19:39:39.015516: Current learning rate: 0.00812 +2024-11-21 19:39:57.557232: train_loss -0.7713 +2024-11-21 19:39:57.557474: val_loss -0.7203 +2024-11-21 19:39:57.557554: Pseudo dice [0.8235] +2024-11-21 19:39:57.557640: Epoch time: 18.54 s +2024-11-21 19:39:58.645880: +2024-11-21 19:39:58.646115: Epoch 1650 +2024-11-21 19:39:58.646230: Current learning rate: 0.00812 +2024-11-21 19:40:16.685202: train_loss -0.7643 +2024-11-21 19:40:16.685427: val_loss -0.7127 +2024-11-21 19:40:16.685500: Pseudo dice [0.8058] +2024-11-21 19:40:16.685576: Epoch time: 18.04 s +2024-11-21 19:40:17.545315: +2024-11-21 19:40:17.545526: Epoch 1651 +2024-11-21 19:40:17.545642: Current learning rate: 0.00812 +2024-11-21 19:40:36.831231: train_loss -0.7536 +2024-11-21 19:40:36.831448: val_loss -0.7293 +2024-11-21 19:40:36.831519: Pseudo dice [0.8064] +2024-11-21 19:40:36.831593: Epoch time: 19.29 s +2024-11-21 19:40:37.671812: +2024-11-21 19:40:37.672021: Epoch 1652 +2024-11-21 19:40:37.672133: Current learning rate: 0.00812 +2024-11-21 19:40:56.136853: train_loss -0.7621 +2024-11-21 19:40:56.137478: val_loss -0.742 +2024-11-21 19:40:56.137558: Pseudo dice [0.8037] +2024-11-21 19:40:56.137638: Epoch time: 18.47 s +2024-11-21 19:40:56.978211: +2024-11-21 19:40:56.978461: Epoch 1653 +2024-11-21 19:40:56.978576: Current learning rate: 0.00812 +2024-11-21 19:41:16.973588: train_loss -0.759 +2024-11-21 19:41:16.973808: val_loss -0.7293 +2024-11-21 19:41:16.973881: Pseudo dice [0.8102] +2024-11-21 19:41:16.973961: Epoch time: 20.0 s +2024-11-21 19:41:17.812425: +2024-11-21 19:41:17.812628: Epoch 1654 +2024-11-21 19:41:17.812741: Current learning rate: 0.00812 +2024-11-21 19:41:37.247873: train_loss -0.7678 +2024-11-21 19:41:37.248425: val_loss -0.732 +2024-11-21 19:41:37.248570: Pseudo dice [0.8226] +2024-11-21 19:41:37.248680: Epoch time: 19.44 s +2024-11-21 19:41:38.087141: +2024-11-21 19:41:38.087342: Epoch 1655 +2024-11-21 19:41:38.087453: Current learning rate: 0.00812 +2024-11-21 19:41:56.734060: train_loss -0.7719 +2024-11-21 19:41:56.734367: val_loss -0.7542 +2024-11-21 19:41:56.734449: Pseudo dice [0.8229] +2024-11-21 19:41:56.734531: Epoch time: 18.65 s +2024-11-21 19:41:57.634564: +2024-11-21 19:41:57.634840: Epoch 1656 +2024-11-21 19:41:57.634953: Current learning rate: 0.00812 +2024-11-21 19:42:16.689488: train_loss -0.767 +2024-11-21 19:42:16.689729: val_loss -0.7396 +2024-11-21 19:42:16.689807: Pseudo dice [0.8074] +2024-11-21 19:42:16.689950: Epoch time: 19.06 s +2024-11-21 19:42:17.531978: +2024-11-21 19:42:17.532188: Epoch 1657 +2024-11-21 19:42:17.532301: Current learning rate: 0.00811 +2024-11-21 19:42:36.634401: train_loss -0.7608 +2024-11-21 19:42:36.634608: val_loss -0.7371 +2024-11-21 19:42:36.634681: Pseudo dice [0.8124] +2024-11-21 19:42:36.634754: Epoch time: 19.1 s +2024-11-21 19:42:37.483244: +2024-11-21 19:42:37.483455: Epoch 1658 +2024-11-21 19:42:37.483572: Current learning rate: 0.00811 +2024-11-21 19:42:55.737772: train_loss -0.7572 +2024-11-21 19:42:55.738036: val_loss -0.7054 +2024-11-21 19:42:55.738111: Pseudo dice [0.7973] +2024-11-21 19:42:55.738188: Epoch time: 18.26 s +2024-11-21 19:42:56.578871: +2024-11-21 19:42:56.579146: Epoch 1659 +2024-11-21 19:42:56.579257: Current learning rate: 0.00811 +2024-11-21 19:43:14.935567: train_loss -0.7716 +2024-11-21 19:43:14.935868: val_loss -0.7242 +2024-11-21 19:43:14.935947: Pseudo dice [0.8094] +2024-11-21 19:43:14.936043: Epoch time: 18.36 s +2024-11-21 19:43:15.865972: +2024-11-21 19:43:15.866194: Epoch 1660 +2024-11-21 19:43:15.866303: Current learning rate: 0.00811 +2024-11-21 19:43:34.117388: train_loss -0.7689 +2024-11-21 19:43:34.117611: val_loss -0.7163 +2024-11-21 19:43:34.117690: Pseudo dice [0.8113] +2024-11-21 19:43:34.117768: Epoch time: 18.25 s +2024-11-21 19:43:34.958602: +2024-11-21 19:43:34.958786: Epoch 1661 +2024-11-21 19:43:34.958900: Current learning rate: 0.00811 +2024-11-21 19:43:54.201129: train_loss -0.7707 +2024-11-21 19:43:54.201335: val_loss -0.7153 +2024-11-21 19:43:54.201410: Pseudo dice [0.8161] +2024-11-21 19:43:54.201488: Epoch time: 19.24 s +2024-11-21 19:43:55.041926: +2024-11-21 19:43:55.042116: Epoch 1662 +2024-11-21 19:43:55.042233: Current learning rate: 0.00811 +2024-11-21 19:44:13.552974: train_loss -0.7699 +2024-11-21 19:44:13.553222: val_loss -0.7596 +2024-11-21 19:44:13.553300: Pseudo dice [0.8247] +2024-11-21 19:44:13.553387: Epoch time: 18.51 s +2024-11-21 19:44:14.398032: +2024-11-21 19:44:14.398239: Epoch 1663 +2024-11-21 19:44:14.398356: Current learning rate: 0.00811 +2024-11-21 19:44:33.899675: train_loss -0.7712 +2024-11-21 19:44:33.899921: val_loss -0.755 +2024-11-21 19:44:33.900000: Pseudo dice [0.8125] +2024-11-21 19:44:33.900080: Epoch time: 19.5 s +2024-11-21 19:44:34.887824: +2024-11-21 19:44:34.888046: Epoch 1664 +2024-11-21 19:44:34.888156: Current learning rate: 0.00811 +2024-11-21 19:44:53.930238: train_loss -0.7723 +2024-11-21 19:44:53.930450: val_loss -0.761 +2024-11-21 19:44:53.930526: Pseudo dice [0.8303] +2024-11-21 19:44:53.930603: Epoch time: 19.04 s +2024-11-21 19:44:54.767786: +2024-11-21 19:44:54.767968: Epoch 1665 +2024-11-21 19:44:54.768082: Current learning rate: 0.00811 +2024-11-21 19:45:13.246166: train_loss -0.7687 +2024-11-21 19:45:13.246382: val_loss -0.728 +2024-11-21 19:45:13.246455: Pseudo dice [0.8076] +2024-11-21 19:45:13.246530: Epoch time: 18.48 s +2024-11-21 19:45:14.490460: +2024-11-21 19:45:14.490679: Epoch 1666 +2024-11-21 19:45:14.490794: Current learning rate: 0.0081 +2024-11-21 19:45:33.334088: train_loss -0.7789 +2024-11-21 19:45:33.334350: val_loss -0.7405 +2024-11-21 19:45:33.334426: Pseudo dice [0.8122] +2024-11-21 19:45:33.334515: Epoch time: 18.84 s +2024-11-21 19:45:34.175279: +2024-11-21 19:45:34.175513: Epoch 1667 +2024-11-21 19:45:34.175627: Current learning rate: 0.0081 +2024-11-21 19:45:52.494258: train_loss -0.7753 +2024-11-21 19:45:52.494476: val_loss -0.7336 +2024-11-21 19:45:52.494550: Pseudo dice [0.8275] +2024-11-21 19:45:52.499826: Epoch time: 18.32 s +2024-11-21 19:45:53.433744: +2024-11-21 19:45:53.433970: Epoch 1668 +2024-11-21 19:45:53.434088: Current learning rate: 0.0081 +2024-11-21 19:46:13.418103: train_loss -0.7714 +2024-11-21 19:46:13.418321: val_loss -0.72 +2024-11-21 19:46:13.418398: Pseudo dice [0.8174] +2024-11-21 19:46:13.418477: Epoch time: 19.99 s +2024-11-21 19:46:14.261055: +2024-11-21 19:46:14.261267: Epoch 1669 +2024-11-21 19:46:14.261379: Current learning rate: 0.0081 +2024-11-21 19:46:33.885381: train_loss -0.7693 +2024-11-21 19:46:33.885608: val_loss -0.7318 +2024-11-21 19:46:33.885689: Pseudo dice [0.8217] +2024-11-21 19:46:33.885775: Epoch time: 19.63 s +2024-11-21 19:46:34.735878: +2024-11-21 19:46:34.736129: Epoch 1670 +2024-11-21 19:46:34.736246: Current learning rate: 0.0081 +2024-11-21 19:46:53.662867: train_loss -0.7687 +2024-11-21 19:46:53.663129: val_loss -0.727 +2024-11-21 19:46:53.663202: Pseudo dice [0.8165] +2024-11-21 19:46:53.663284: Epoch time: 18.93 s +2024-11-21 19:46:54.678515: +2024-11-21 19:46:54.678735: Epoch 1671 +2024-11-21 19:46:54.678849: Current learning rate: 0.0081 +2024-11-21 19:47:12.678671: train_loss -0.7753 +2024-11-21 19:47:12.678883: val_loss -0.7314 +2024-11-21 19:47:12.679012: Pseudo dice [0.8122] +2024-11-21 19:47:12.679092: Epoch time: 18.0 s +2024-11-21 19:47:13.536057: +2024-11-21 19:47:13.536257: Epoch 1672 +2024-11-21 19:47:13.536371: Current learning rate: 0.0081 +2024-11-21 19:47:31.399737: train_loss -0.7696 +2024-11-21 19:47:31.400041: val_loss -0.7201 +2024-11-21 19:47:31.400122: Pseudo dice [0.8083] +2024-11-21 19:47:31.400199: Epoch time: 17.86 s +2024-11-21 19:47:32.243279: +2024-11-21 19:47:32.243465: Epoch 1673 +2024-11-21 19:47:32.243618: Current learning rate: 0.0081 +2024-11-21 19:47:49.918517: train_loss -0.7761 +2024-11-21 19:47:49.918733: val_loss -0.7434 +2024-11-21 19:47:49.918806: Pseudo dice [0.8109] +2024-11-21 19:47:49.918886: Epoch time: 17.68 s +2024-11-21 19:47:50.763863: +2024-11-21 19:47:50.764091: Epoch 1674 +2024-11-21 19:47:50.764208: Current learning rate: 0.0081 +2024-11-21 19:48:10.228297: train_loss -0.7788 +2024-11-21 19:48:10.228548: val_loss -0.762 +2024-11-21 19:48:10.228621: Pseudo dice [0.8215] +2024-11-21 19:48:10.228725: Epoch time: 19.47 s +2024-11-21 19:48:11.070839: +2024-11-21 19:48:11.071042: Epoch 1675 +2024-11-21 19:48:11.071169: Current learning rate: 0.00809 +2024-11-21 19:48:29.649888: train_loss -0.7783 +2024-11-21 19:48:29.650187: val_loss -0.7345 +2024-11-21 19:48:29.650277: Pseudo dice [0.8218] +2024-11-21 19:48:29.650357: Epoch time: 18.58 s +2024-11-21 19:48:30.542452: +2024-11-21 19:48:30.542661: Epoch 1676 +2024-11-21 19:48:30.542776: Current learning rate: 0.00809 +2024-11-21 19:48:48.542351: train_loss -0.7726 +2024-11-21 19:48:48.542570: val_loss -0.7578 +2024-11-21 19:48:48.542648: Pseudo dice [0.834] +2024-11-21 19:48:48.543350: Epoch time: 18.0 s +2024-11-21 19:48:49.737952: +2024-11-21 19:48:49.738218: Epoch 1677 +2024-11-21 19:48:49.738379: Current learning rate: 0.00809 +2024-11-21 19:49:09.390764: train_loss -0.7653 +2024-11-21 19:49:09.393177: val_loss -0.7219 +2024-11-21 19:49:09.393296: Pseudo dice [0.8239] +2024-11-21 19:49:09.393381: Epoch time: 19.65 s +2024-11-21 19:49:10.256196: +2024-11-21 19:49:10.256451: Epoch 1678 +2024-11-21 19:49:10.256564: Current learning rate: 0.00809 +2024-11-21 19:49:30.240028: train_loss -0.761 +2024-11-21 19:49:30.240240: val_loss -0.7329 +2024-11-21 19:49:30.240315: Pseudo dice [0.8327] +2024-11-21 19:49:30.240391: Epoch time: 19.98 s +2024-11-21 19:49:31.090752: +2024-11-21 19:49:31.090961: Epoch 1679 +2024-11-21 19:49:31.091080: Current learning rate: 0.00809 +2024-11-21 19:49:48.876612: train_loss -0.7701 +2024-11-21 19:49:48.876819: val_loss -0.7283 +2024-11-21 19:49:48.876892: Pseudo dice [0.8227] +2024-11-21 19:49:48.876966: Epoch time: 17.79 s +2024-11-21 19:49:49.759181: +2024-11-21 19:49:49.759478: Epoch 1680 +2024-11-21 19:49:49.759593: Current learning rate: 0.00809 +2024-11-21 19:50:08.063233: train_loss -0.7658 +2024-11-21 19:50:08.063483: val_loss -0.7332 +2024-11-21 19:50:08.063561: Pseudo dice [0.8315] +2024-11-21 19:50:08.063710: Epoch time: 18.3 s +2024-11-21 19:50:08.917026: +2024-11-21 19:50:08.917245: Epoch 1681 +2024-11-21 19:50:08.917359: Current learning rate: 0.00809 +2024-11-21 19:50:27.113664: train_loss -0.7688 +2024-11-21 19:50:27.113884: val_loss -0.741 +2024-11-21 19:50:27.113973: Pseudo dice [0.828] +2024-11-21 19:50:27.114094: Epoch time: 18.2 s +2024-11-21 19:50:27.960323: +2024-11-21 19:50:27.960534: Epoch 1682 +2024-11-21 19:50:27.960647: Current learning rate: 0.00809 +2024-11-21 19:50:45.755938: train_loss -0.757 +2024-11-21 19:50:45.775396: val_loss -0.7324 +2024-11-21 19:50:45.775557: Pseudo dice [0.8015] +2024-11-21 19:50:45.775639: Epoch time: 17.8 s +2024-11-21 19:50:46.678759: +2024-11-21 19:50:46.678976: Epoch 1683 +2024-11-21 19:50:46.679089: Current learning rate: 0.00808 +2024-11-21 19:51:05.628279: train_loss -0.7668 +2024-11-21 19:51:05.628492: val_loss -0.7469 +2024-11-21 19:51:05.628568: Pseudo dice [0.8315] +2024-11-21 19:51:05.628648: Epoch time: 18.95 s +2024-11-21 19:51:06.494538: +2024-11-21 19:51:06.494831: Epoch 1684 +2024-11-21 19:51:06.494945: Current learning rate: 0.00808 +2024-11-21 19:51:24.893439: train_loss -0.7782 +2024-11-21 19:51:24.893677: val_loss -0.7644 +2024-11-21 19:51:24.893750: Pseudo dice [0.8286] +2024-11-21 19:51:24.893829: Epoch time: 18.4 s +2024-11-21 19:51:25.763935: +2024-11-21 19:51:25.764189: Epoch 1685 +2024-11-21 19:51:25.764308: Current learning rate: 0.00808 +2024-11-21 19:51:43.951283: train_loss -0.7733 +2024-11-21 19:51:43.951498: val_loss -0.738 +2024-11-21 19:51:43.951571: Pseudo dice [0.8216] +2024-11-21 19:51:43.951647: Epoch time: 18.19 s +2024-11-21 19:51:44.798333: +2024-11-21 19:51:44.798536: Epoch 1686 +2024-11-21 19:51:44.798649: Current learning rate: 0.00808 +2024-11-21 19:52:02.875865: train_loss -0.7712 +2024-11-21 19:52:02.876097: val_loss -0.7358 +2024-11-21 19:52:02.876173: Pseudo dice [0.8247] +2024-11-21 19:52:02.876253: Epoch time: 18.08 s +2024-11-21 19:52:03.891349: +2024-11-21 19:52:03.891603: Epoch 1687 +2024-11-21 19:52:03.891711: Current learning rate: 0.00808 +2024-11-21 19:52:22.314008: train_loss -0.773 +2024-11-21 19:52:22.314250: val_loss -0.7575 +2024-11-21 19:52:22.314323: Pseudo dice [0.8309] +2024-11-21 19:52:22.314412: Epoch time: 18.42 s +2024-11-21 19:52:23.204590: +2024-11-21 19:52:23.204787: Epoch 1688 +2024-11-21 19:52:23.204898: Current learning rate: 0.00808 +2024-11-21 19:52:41.811910: train_loss -0.77 +2024-11-21 19:52:41.813232: val_loss -0.7273 +2024-11-21 19:52:41.813340: Pseudo dice [0.8233] +2024-11-21 19:52:41.813427: Epoch time: 18.61 s +2024-11-21 19:52:43.083357: +2024-11-21 19:52:43.083581: Epoch 1689 +2024-11-21 19:52:43.083696: Current learning rate: 0.00808 +2024-11-21 19:53:01.805212: train_loss -0.7707 +2024-11-21 19:53:01.821696: val_loss -0.7259 +2024-11-21 19:53:01.821852: Pseudo dice [0.8163] +2024-11-21 19:53:01.821937: Epoch time: 18.72 s +2024-11-21 19:53:02.682673: +2024-11-21 19:53:02.682871: Epoch 1690 +2024-11-21 19:53:02.682986: Current learning rate: 0.00808 +2024-11-21 19:53:21.268892: train_loss -0.7729 +2024-11-21 19:53:21.269141: val_loss -0.7275 +2024-11-21 19:53:21.269223: Pseudo dice [0.7989] +2024-11-21 19:53:21.269309: Epoch time: 18.59 s +2024-11-21 19:53:22.122510: +2024-11-21 19:53:22.122712: Epoch 1691 +2024-11-21 19:53:22.122821: Current learning rate: 0.00808 +2024-11-21 19:53:40.929356: train_loss -0.7709 +2024-11-21 19:53:40.930405: val_loss -0.7381 +2024-11-21 19:53:40.930491: Pseudo dice [0.8375] +2024-11-21 19:53:40.930570: Epoch time: 18.81 s +2024-11-21 19:53:41.781662: +2024-11-21 19:53:41.781902: Epoch 1692 +2024-11-21 19:53:41.782021: Current learning rate: 0.00807 +2024-11-21 19:54:00.216091: train_loss -0.7827 +2024-11-21 19:54:00.216311: val_loss -0.7452 +2024-11-21 19:54:00.216391: Pseudo dice [0.8228] +2024-11-21 19:54:00.216465: Epoch time: 18.44 s +2024-11-21 19:54:01.064079: +2024-11-21 19:54:01.064284: Epoch 1693 +2024-11-21 19:54:01.064401: Current learning rate: 0.00807 +2024-11-21 19:54:20.009721: train_loss -0.7532 +2024-11-21 19:54:20.009940: val_loss -0.7182 +2024-11-21 19:54:20.010028: Pseudo dice [0.7751] +2024-11-21 19:54:20.010106: Epoch time: 18.95 s +2024-11-21 19:54:20.862702: +2024-11-21 19:54:20.862905: Epoch 1694 +2024-11-21 19:54:20.863028: Current learning rate: 0.00807 +2024-11-21 19:54:40.556224: train_loss -0.7531 +2024-11-21 19:54:40.556472: val_loss -0.7039 +2024-11-21 19:54:40.556560: Pseudo dice [0.8259] +2024-11-21 19:54:40.561824: Epoch time: 19.69 s +2024-11-21 19:54:41.456296: +2024-11-21 19:54:41.456520: Epoch 1695 +2024-11-21 19:54:41.456632: Current learning rate: 0.00807 +2024-11-21 19:55:01.139736: train_loss -0.7576 +2024-11-21 19:55:01.140029: val_loss -0.7445 +2024-11-21 19:55:01.140112: Pseudo dice [0.8203] +2024-11-21 19:55:01.140193: Epoch time: 19.68 s +2024-11-21 19:55:02.091666: +2024-11-21 19:55:02.091891: Epoch 1696 +2024-11-21 19:55:02.092020: Current learning rate: 0.00807 +2024-11-21 19:55:19.792323: train_loss -0.773 +2024-11-21 19:55:19.792541: val_loss -0.7462 +2024-11-21 19:55:19.794848: Pseudo dice [0.8331] +2024-11-21 19:55:19.794958: Epoch time: 17.7 s +2024-11-21 19:55:20.651657: +2024-11-21 19:55:20.651856: Epoch 1697 +2024-11-21 19:55:20.651972: Current learning rate: 0.00807 +2024-11-21 19:55:39.451245: train_loss -0.7738 +2024-11-21 19:55:39.451454: val_loss -0.7564 +2024-11-21 19:55:39.451527: Pseudo dice [0.8284] +2024-11-21 19:55:39.451604: Epoch time: 18.8 s +2024-11-21 19:55:40.301616: +2024-11-21 19:55:40.301802: Epoch 1698 +2024-11-21 19:55:40.301920: Current learning rate: 0.00807 +2024-11-21 19:55:58.984587: train_loss -0.771 +2024-11-21 19:55:58.984835: val_loss -0.7319 +2024-11-21 19:55:58.984911: Pseudo dice [0.8074] +2024-11-21 19:55:58.984999: Epoch time: 18.68 s +2024-11-21 19:55:59.870174: +2024-11-21 19:55:59.870413: Epoch 1699 +2024-11-21 19:55:59.870530: Current learning rate: 0.00807 +2024-11-21 19:56:18.205899: train_loss -0.7747 +2024-11-21 19:56:18.206118: val_loss -0.7424 +2024-11-21 19:56:18.206195: Pseudo dice [0.8301] +2024-11-21 19:56:18.206272: Epoch time: 18.34 s +2024-11-21 19:56:19.642810: +2024-11-21 19:56:19.643192: Epoch 1700 +2024-11-21 19:56:19.643314: Current learning rate: 0.00807 +2024-11-21 19:56:38.483650: train_loss -0.7733 +2024-11-21 19:56:38.483865: val_loss -0.759 +2024-11-21 19:56:38.483942: Pseudo dice [0.8218] +2024-11-21 19:56:38.484030: Epoch time: 18.84 s +2024-11-21 19:56:39.467345: +2024-11-21 19:56:39.467565: Epoch 1701 +2024-11-21 19:56:39.467679: Current learning rate: 0.00806 +2024-11-21 19:56:58.725537: train_loss -0.78 +2024-11-21 19:56:58.726094: val_loss -0.77 +2024-11-21 19:56:58.726182: Pseudo dice [0.839] +2024-11-21 19:56:58.726292: Epoch time: 19.26 s +2024-11-21 19:56:59.573238: +2024-11-21 19:56:59.573453: Epoch 1702 +2024-11-21 19:56:59.599904: Current learning rate: 0.00806 +2024-11-21 19:57:18.500043: train_loss -0.7699 +2024-11-21 19:57:18.500273: val_loss -0.7383 +2024-11-21 19:57:18.502610: Pseudo dice [0.8185] +2024-11-21 19:57:18.502712: Epoch time: 18.93 s +2024-11-21 19:57:19.386584: +2024-11-21 19:57:19.386792: Epoch 1703 +2024-11-21 19:57:19.386909: Current learning rate: 0.00806 +2024-11-21 19:57:38.459946: train_loss -0.7668 +2024-11-21 19:57:38.460217: val_loss -0.7399 +2024-11-21 19:57:38.460296: Pseudo dice [0.8219] +2024-11-21 19:57:38.460375: Epoch time: 19.07 s +2024-11-21 19:57:39.309030: +2024-11-21 19:57:39.309221: Epoch 1704 +2024-11-21 19:57:39.309330: Current learning rate: 0.00806 +2024-11-21 19:57:57.145449: train_loss -0.7743 +2024-11-21 19:57:57.145695: val_loss -0.7392 +2024-11-21 19:57:57.145771: Pseudo dice [0.8199] +2024-11-21 19:57:57.145857: Epoch time: 17.84 s +2024-11-21 19:57:57.992656: +2024-11-21 19:57:57.992849: Epoch 1705 +2024-11-21 19:57:57.992960: Current learning rate: 0.00806 +2024-11-21 19:58:16.370739: train_loss -0.7735 +2024-11-21 19:58:16.370966: val_loss -0.7623 +2024-11-21 19:58:16.371055: Pseudo dice [0.8241] +2024-11-21 19:58:16.371131: Epoch time: 18.38 s +2024-11-21 19:58:17.221995: +2024-11-21 19:58:17.222426: Epoch 1706 +2024-11-21 19:58:17.222539: Current learning rate: 0.00806 +2024-11-21 19:58:37.123064: train_loss -0.77 +2024-11-21 19:58:37.123278: val_loss -0.7372 +2024-11-21 19:58:37.123387: Pseudo dice [0.8181] +2024-11-21 19:58:37.123467: Epoch time: 19.9 s +2024-11-21 19:58:37.972225: +2024-11-21 19:58:37.972429: Epoch 1707 +2024-11-21 19:58:37.972539: Current learning rate: 0.00806 +2024-11-21 19:58:58.151460: train_loss -0.7776 +2024-11-21 19:58:58.151684: val_loss -0.7393 +2024-11-21 19:58:58.151762: Pseudo dice [0.8353] +2024-11-21 19:58:58.151843: Epoch time: 20.18 s +2024-11-21 19:58:59.015954: +2024-11-21 19:58:59.016147: Epoch 1708 +2024-11-21 19:58:59.016259: Current learning rate: 0.00806 +2024-11-21 19:59:17.967390: train_loss -0.7743 +2024-11-21 19:59:17.967687: val_loss -0.7395 +2024-11-21 19:59:17.967772: Pseudo dice [0.8249] +2024-11-21 19:59:17.967861: Epoch time: 18.95 s +2024-11-21 19:59:18.979688: +2024-11-21 19:59:18.979891: Epoch 1709 +2024-11-21 19:59:18.980011: Current learning rate: 0.00806 +2024-11-21 19:59:37.236776: train_loss -0.7713 +2024-11-21 19:59:37.237015: val_loss -0.7522 +2024-11-21 19:59:37.242280: Pseudo dice [0.8198] +2024-11-21 19:59:37.242396: Epoch time: 18.26 s +2024-11-21 19:59:38.159726: +2024-11-21 19:59:38.159963: Epoch 1710 +2024-11-21 19:59:38.160085: Current learning rate: 0.00805 +2024-11-21 19:59:57.056627: train_loss -0.7628 +2024-11-21 19:59:57.056846: val_loss -0.749 +2024-11-21 19:59:57.056920: Pseudo dice [0.8261] +2024-11-21 19:59:57.057006: Epoch time: 18.9 s +2024-11-21 19:59:57.905341: +2024-11-21 19:59:57.905536: Epoch 1711 +2024-11-21 19:59:57.905649: Current learning rate: 0.00805 +2024-11-21 20:00:16.339783: train_loss -0.7659 +2024-11-21 20:00:16.340348: val_loss -0.716 +2024-11-21 20:00:16.340486: Pseudo dice [0.8055] +2024-11-21 20:00:16.340581: Epoch time: 18.44 s +2024-11-21 20:00:17.188573: +2024-11-21 20:00:17.188786: Epoch 1712 +2024-11-21 20:00:17.188904: Current learning rate: 0.00805 +2024-11-21 20:00:36.088736: train_loss -0.7627 +2024-11-21 20:00:36.088952: val_loss -0.7182 +2024-11-21 20:00:36.089037: Pseudo dice [0.8085] +2024-11-21 20:00:36.089118: Epoch time: 18.9 s +2024-11-21 20:00:36.935552: +2024-11-21 20:00:36.935818: Epoch 1713 +2024-11-21 20:00:36.935928: Current learning rate: 0.00805 +2024-11-21 20:00:54.997453: train_loss -0.7749 +2024-11-21 20:00:54.997668: val_loss -0.7569 +2024-11-21 20:00:54.997746: Pseudo dice [0.8334] +2024-11-21 20:00:54.997823: Epoch time: 18.06 s +2024-11-21 20:00:55.951962: +2024-11-21 20:00:55.952355: Epoch 1714 +2024-11-21 20:00:55.952472: Current learning rate: 0.00805 +2024-11-21 20:01:14.460295: train_loss -0.7592 +2024-11-21 20:01:14.462650: val_loss -0.7331 +2024-11-21 20:01:14.462875: Pseudo dice [0.8343] +2024-11-21 20:01:14.462974: Epoch time: 18.51 s +2024-11-21 20:01:15.340304: +2024-11-21 20:01:15.340517: Epoch 1715 +2024-11-21 20:01:15.340625: Current learning rate: 0.00805 +2024-11-21 20:01:33.677561: train_loss -0.7638 +2024-11-21 20:01:33.677782: val_loss -0.7296 +2024-11-21 20:01:33.677857: Pseudo dice [0.8369] +2024-11-21 20:01:33.677931: Epoch time: 18.34 s +2024-11-21 20:01:34.545822: +2024-11-21 20:01:34.546024: Epoch 1716 +2024-11-21 20:01:34.546139: Current learning rate: 0.00805 +2024-11-21 20:01:53.588655: train_loss -0.7724 +2024-11-21 20:01:53.589588: val_loss -0.7516 +2024-11-21 20:01:53.589679: Pseudo dice [0.8432] +2024-11-21 20:01:53.589758: Epoch time: 19.04 s +2024-11-21 20:01:54.473875: +2024-11-21 20:01:54.474071: Epoch 1717 +2024-11-21 20:01:54.474207: Current learning rate: 0.00805 +2024-11-21 20:02:12.681552: train_loss -0.7656 +2024-11-21 20:02:12.681779: val_loss -0.7369 +2024-11-21 20:02:12.681879: Pseudo dice [0.8201] +2024-11-21 20:02:12.681985: Epoch time: 18.21 s +2024-11-21 20:02:13.638310: +2024-11-21 20:02:13.638551: Epoch 1718 +2024-11-21 20:02:13.638669: Current learning rate: 0.00804 +2024-11-21 20:02:32.230685: train_loss -0.7754 +2024-11-21 20:02:32.235408: val_loss -0.7607 +2024-11-21 20:02:32.235604: Pseudo dice [0.8384] +2024-11-21 20:02:32.235692: Epoch time: 18.59 s +2024-11-21 20:02:33.092214: +2024-11-21 20:02:33.092408: Epoch 1719 +2024-11-21 20:02:33.092521: Current learning rate: 0.00804 +2024-11-21 20:02:51.466350: train_loss -0.7412 +2024-11-21 20:02:51.466619: val_loss -0.7287 +2024-11-21 20:02:51.466697: Pseudo dice [0.8183] +2024-11-21 20:02:51.466789: Epoch time: 18.37 s +2024-11-21 20:02:52.325145: +2024-11-21 20:02:52.325342: Epoch 1720 +2024-11-21 20:02:52.325456: Current learning rate: 0.00804 +2024-11-21 20:03:11.238316: train_loss -0.7559 +2024-11-21 20:03:11.238518: val_loss -0.7342 +2024-11-21 20:03:11.238590: Pseudo dice [0.7947] +2024-11-21 20:03:11.238663: Epoch time: 18.91 s +2024-11-21 20:03:12.130292: +2024-11-21 20:03:12.130539: Epoch 1721 +2024-11-21 20:03:12.130650: Current learning rate: 0.00804 +2024-11-21 20:03:30.933807: train_loss -0.7716 +2024-11-21 20:03:30.934039: val_loss -0.7439 +2024-11-21 20:03:30.934120: Pseudo dice [0.8082] +2024-11-21 20:03:30.934198: Epoch time: 18.8 s +2024-11-21 20:03:32.172595: +2024-11-21 20:03:32.172827: Epoch 1722 +2024-11-21 20:03:32.173017: Current learning rate: 0.00804 +2024-11-21 20:03:51.212034: train_loss -0.776 +2024-11-21 20:03:51.212295: val_loss -0.7218 +2024-11-21 20:03:51.212371: Pseudo dice [0.7937] +2024-11-21 20:03:51.212458: Epoch time: 19.04 s +2024-11-21 20:03:52.060881: +2024-11-21 20:03:52.061100: Epoch 1723 +2024-11-21 20:03:52.061213: Current learning rate: 0.00804 +2024-11-21 20:04:10.052078: train_loss -0.7698 +2024-11-21 20:04:10.052294: val_loss -0.7482 +2024-11-21 20:04:10.052368: Pseudo dice [0.8229] +2024-11-21 20:04:10.052445: Epoch time: 17.99 s +2024-11-21 20:04:10.902836: +2024-11-21 20:04:10.903054: Epoch 1724 +2024-11-21 20:04:10.903172: Current learning rate: 0.00804 +2024-11-21 20:04:29.438516: train_loss -0.7782 +2024-11-21 20:04:29.438740: val_loss -0.7014 +2024-11-21 20:04:29.438815: Pseudo dice [0.8279] +2024-11-21 20:04:29.438892: Epoch time: 18.54 s +2024-11-21 20:04:30.300401: +2024-11-21 20:04:30.300597: Epoch 1725 +2024-11-21 20:04:30.300710: Current learning rate: 0.00804 +2024-11-21 20:04:48.973279: train_loss -0.773 +2024-11-21 20:04:48.973500: val_loss -0.7435 +2024-11-21 20:04:48.973577: Pseudo dice [0.8131] +2024-11-21 20:04:48.973659: Epoch time: 18.67 s +2024-11-21 20:04:49.824024: +2024-11-21 20:04:49.824239: Epoch 1726 +2024-11-21 20:04:49.824363: Current learning rate: 0.00804 +2024-11-21 20:05:09.537861: train_loss -0.7717 +2024-11-21 20:05:09.538121: val_loss -0.7416 +2024-11-21 20:05:09.538200: Pseudo dice [0.8275] +2024-11-21 20:05:09.538284: Epoch time: 19.71 s +2024-11-21 20:05:10.394253: +2024-11-21 20:05:10.394453: Epoch 1727 +2024-11-21 20:05:10.394567: Current learning rate: 0.00803 +2024-11-21 20:05:30.304802: train_loss -0.7598 +2024-11-21 20:05:30.306422: val_loss -0.7099 +2024-11-21 20:05:30.306552: Pseudo dice [0.8004] +2024-11-21 20:05:30.306634: Epoch time: 19.91 s +2024-11-21 20:05:31.206350: +2024-11-21 20:05:31.206541: Epoch 1728 +2024-11-21 20:05:31.206651: Current learning rate: 0.00803 +2024-11-21 20:05:50.072764: train_loss -0.7687 +2024-11-21 20:05:50.072983: val_loss -0.7348 +2024-11-21 20:05:50.073062: Pseudo dice [0.8038] +2024-11-21 20:05:50.073139: Epoch time: 18.87 s +2024-11-21 20:05:50.923831: +2024-11-21 20:05:50.924033: Epoch 1729 +2024-11-21 20:05:50.924152: Current learning rate: 0.00803 +2024-11-21 20:06:09.199265: train_loss -0.7664 +2024-11-21 20:06:09.199530: val_loss -0.7199 +2024-11-21 20:06:09.199670: Pseudo dice [0.8028] +2024-11-21 20:06:09.199761: Epoch time: 18.28 s +2024-11-21 20:06:10.071712: +2024-11-21 20:06:10.071918: Epoch 1730 +2024-11-21 20:06:10.072035: Current learning rate: 0.00803 +2024-11-21 20:06:29.539102: train_loss -0.7746 +2024-11-21 20:06:29.539319: val_loss -0.7415 +2024-11-21 20:06:29.539393: Pseudo dice [0.8291] +2024-11-21 20:06:29.539471: Epoch time: 19.47 s +2024-11-21 20:06:30.390387: +2024-11-21 20:06:30.390593: Epoch 1731 +2024-11-21 20:06:30.390707: Current learning rate: 0.00803 +2024-11-21 20:06:47.903106: train_loss -0.7783 +2024-11-21 20:06:47.903322: val_loss -0.7431 +2024-11-21 20:06:47.903402: Pseudo dice [0.8201] +2024-11-21 20:06:47.903484: Epoch time: 17.51 s +2024-11-21 20:06:48.754000: +2024-11-21 20:06:48.754203: Epoch 1732 +2024-11-21 20:06:48.754317: Current learning rate: 0.00803 +2024-11-21 20:07:07.274981: train_loss -0.7804 +2024-11-21 20:07:07.275214: val_loss -0.7355 +2024-11-21 20:07:07.275356: Pseudo dice [0.8324] +2024-11-21 20:07:07.275438: Epoch time: 18.52 s +2024-11-21 20:07:08.126205: +2024-11-21 20:07:08.126462: Epoch 1733 +2024-11-21 20:07:08.126576: Current learning rate: 0.00803 +2024-11-21 20:07:27.095598: train_loss -0.7758 +2024-11-21 20:07:27.095865: val_loss -0.7536 +2024-11-21 20:07:27.095939: Pseudo dice [0.8259] +2024-11-21 20:07:27.096030: Epoch time: 18.97 s +2024-11-21 20:07:28.348595: +2024-11-21 20:07:28.348794: Epoch 1734 +2024-11-21 20:07:28.348911: Current learning rate: 0.00803 +2024-11-21 20:07:46.991247: train_loss -0.7685 +2024-11-21 20:07:46.991482: val_loss -0.7295 +2024-11-21 20:07:46.991557: Pseudo dice [0.8179] +2024-11-21 20:07:46.991636: Epoch time: 18.64 s +2024-11-21 20:07:47.904115: +2024-11-21 20:07:47.904376: Epoch 1735 +2024-11-21 20:07:47.904493: Current learning rate: 0.00803 +2024-11-21 20:08:07.729584: train_loss -0.7699 +2024-11-21 20:08:07.729797: val_loss -0.741 +2024-11-21 20:08:07.729877: Pseudo dice [0.8206] +2024-11-21 20:08:07.729953: Epoch time: 19.83 s +2024-11-21 20:08:08.691325: +2024-11-21 20:08:08.691555: Epoch 1736 +2024-11-21 20:08:08.691672: Current learning rate: 0.00802 +2024-11-21 20:08:27.463055: train_loss -0.762 +2024-11-21 20:08:27.463312: val_loss -0.7294 +2024-11-21 20:08:27.468574: Pseudo dice [0.8076] +2024-11-21 20:08:27.468698: Epoch time: 18.77 s +2024-11-21 20:08:28.330832: +2024-11-21 20:08:28.331052: Epoch 1737 +2024-11-21 20:08:28.331166: Current learning rate: 0.00802 +2024-11-21 20:08:48.801861: train_loss -0.7628 +2024-11-21 20:08:48.802085: val_loss -0.7292 +2024-11-21 20:08:48.802161: Pseudo dice [0.8065] +2024-11-21 20:08:48.802241: Epoch time: 20.47 s +2024-11-21 20:08:49.655481: +2024-11-21 20:08:49.655714: Epoch 1738 +2024-11-21 20:08:49.655827: Current learning rate: 0.00802 +2024-11-21 20:09:09.369768: train_loss -0.7763 +2024-11-21 20:09:09.370046: val_loss -0.7461 +2024-11-21 20:09:09.370123: Pseudo dice [0.8268] +2024-11-21 20:09:09.370203: Epoch time: 19.72 s +2024-11-21 20:09:10.221479: +2024-11-21 20:09:10.221699: Epoch 1739 +2024-11-21 20:09:10.221808: Current learning rate: 0.00802 +2024-11-21 20:09:29.931846: train_loss -0.773 +2024-11-21 20:09:29.932069: val_loss -0.7692 +2024-11-21 20:09:29.932147: Pseudo dice [0.8372] +2024-11-21 20:09:29.932224: Epoch time: 19.71 s +2024-11-21 20:09:30.780599: +2024-11-21 20:09:30.780795: Epoch 1740 +2024-11-21 20:09:30.780909: Current learning rate: 0.00802 +2024-11-21 20:09:48.815489: train_loss -0.778 +2024-11-21 20:09:48.815736: val_loss -0.737 +2024-11-21 20:09:48.815813: Pseudo dice [0.8487] +2024-11-21 20:09:48.815901: Epoch time: 18.04 s +2024-11-21 20:09:49.668542: +2024-11-21 20:09:49.668746: Epoch 1741 +2024-11-21 20:09:49.668864: Current learning rate: 0.00802 +2024-11-21 20:10:07.583485: train_loss -0.7721 +2024-11-21 20:10:07.583704: val_loss -0.7035 +2024-11-21 20:10:07.583781: Pseudo dice [0.8067] +2024-11-21 20:10:07.583858: Epoch time: 17.92 s +2024-11-21 20:10:08.436397: +2024-11-21 20:10:08.436592: Epoch 1742 +2024-11-21 20:10:08.436699: Current learning rate: 0.00802 +2024-11-21 20:10:27.007704: train_loss -0.7637 +2024-11-21 20:10:27.007926: val_loss -0.7292 +2024-11-21 20:10:27.008013: Pseudo dice [0.8332] +2024-11-21 20:10:27.008090: Epoch time: 18.57 s +2024-11-21 20:10:27.859087: +2024-11-21 20:10:27.859363: Epoch 1743 +2024-11-21 20:10:27.859478: Current learning rate: 0.00802 +2024-11-21 20:10:47.748379: train_loss -0.7736 +2024-11-21 20:10:47.748591: val_loss -0.736 +2024-11-21 20:10:47.748670: Pseudo dice [0.8112] +2024-11-21 20:10:47.748748: Epoch time: 19.89 s +2024-11-21 20:10:48.599957: +2024-11-21 20:10:48.600155: Epoch 1744 +2024-11-21 20:10:48.600272: Current learning rate: 0.00801 +2024-11-21 20:11:07.096145: train_loss -0.7764 +2024-11-21 20:11:07.096388: val_loss -0.7465 +2024-11-21 20:11:07.096467: Pseudo dice [0.82] +2024-11-21 20:11:07.096552: Epoch time: 18.5 s +2024-11-21 20:11:08.322750: +2024-11-21 20:11:08.322996: Epoch 1745 +2024-11-21 20:11:08.323112: Current learning rate: 0.00801 +2024-11-21 20:11:27.578773: train_loss -0.7745 +2024-11-21 20:11:27.579021: val_loss -0.7169 +2024-11-21 20:11:27.579097: Pseudo dice [0.8455] +2024-11-21 20:11:27.579177: Epoch time: 19.26 s +2024-11-21 20:11:28.430727: +2024-11-21 20:11:28.430945: Epoch 1746 +2024-11-21 20:11:28.431062: Current learning rate: 0.00801 +2024-11-21 20:11:46.332641: train_loss -0.7815 +2024-11-21 20:11:46.332855: val_loss -0.7378 +2024-11-21 20:11:46.333013: Pseudo dice [0.8301] +2024-11-21 20:11:46.333094: Epoch time: 17.9 s +2024-11-21 20:11:47.273652: +2024-11-21 20:11:47.273924: Epoch 1747 +2024-11-21 20:11:47.274045: Current learning rate: 0.00801 +2024-11-21 20:12:05.903444: train_loss -0.7724 +2024-11-21 20:12:05.903690: val_loss -0.7248 +2024-11-21 20:12:05.903767: Pseudo dice [0.81] +2024-11-21 20:12:05.903853: Epoch time: 18.63 s +2024-11-21 20:12:06.775001: +2024-11-21 20:12:06.775221: Epoch 1748 +2024-11-21 20:12:06.775471: Current learning rate: 0.00801 +2024-11-21 20:12:24.916779: train_loss -0.7753 +2024-11-21 20:12:24.916986: val_loss -0.7174 +2024-11-21 20:12:24.917069: Pseudo dice [0.7806] +2024-11-21 20:12:24.917156: Epoch time: 18.14 s +2024-11-21 20:12:25.773111: +2024-11-21 20:12:25.773367: Epoch 1749 +2024-11-21 20:12:25.773488: Current learning rate: 0.00801 +2024-11-21 20:12:44.550694: train_loss -0.7676 +2024-11-21 20:12:44.551023: val_loss -0.7389 +2024-11-21 20:12:44.551105: Pseudo dice [0.823] +2024-11-21 20:12:44.551186: Epoch time: 18.77 s +2024-11-21 20:12:45.917407: +2024-11-21 20:12:45.917667: Epoch 1750 +2024-11-21 20:12:45.917779: Current learning rate: 0.00801 +2024-11-21 20:13:05.007859: train_loss -0.7685 +2024-11-21 20:13:05.008099: val_loss -0.763 +2024-11-21 20:13:05.008175: Pseudo dice [0.8269] +2024-11-21 20:13:05.008255: Epoch time: 19.09 s +2024-11-21 20:13:06.002512: +2024-11-21 20:13:06.002701: Epoch 1751 +2024-11-21 20:13:06.002810: Current learning rate: 0.00801 +2024-11-21 20:13:25.416756: train_loss -0.7707 +2024-11-21 20:13:25.417054: val_loss -0.7537 +2024-11-21 20:13:25.417133: Pseudo dice [0.8241] +2024-11-21 20:13:25.417218: Epoch time: 19.42 s +2024-11-21 20:13:26.270472: +2024-11-21 20:13:26.270765: Epoch 1752 +2024-11-21 20:13:26.270880: Current learning rate: 0.00801 +2024-11-21 20:13:45.985108: train_loss -0.7566 +2024-11-21 20:13:45.985326: val_loss -0.7495 +2024-11-21 20:13:45.985402: Pseudo dice [0.8251] +2024-11-21 20:13:45.985479: Epoch time: 19.72 s +2024-11-21 20:13:46.867998: +2024-11-21 20:13:46.868193: Epoch 1753 +2024-11-21 20:13:46.868310: Current learning rate: 0.008 +2024-11-21 20:14:05.279499: train_loss -0.7715 +2024-11-21 20:14:05.279711: val_loss -0.7278 +2024-11-21 20:14:05.279781: Pseudo dice [0.8254] +2024-11-21 20:14:05.279883: Epoch time: 18.41 s +2024-11-21 20:14:06.135307: +2024-11-21 20:14:06.135594: Epoch 1754 +2024-11-21 20:14:06.135708: Current learning rate: 0.008 +2024-11-21 20:14:25.498143: train_loss -0.7756 +2024-11-21 20:14:25.498357: val_loss -0.7355 +2024-11-21 20:14:25.498435: Pseudo dice [0.8265] +2024-11-21 20:14:25.498515: Epoch time: 19.36 s +2024-11-21 20:14:26.348316: +2024-11-21 20:14:26.348517: Epoch 1755 +2024-11-21 20:14:26.348631: Current learning rate: 0.008 +2024-11-21 20:14:44.437009: train_loss -0.7676 +2024-11-21 20:14:44.437253: val_loss -0.7223 +2024-11-21 20:14:44.437330: Pseudo dice [0.8258] +2024-11-21 20:14:44.437412: Epoch time: 18.09 s +2024-11-21 20:14:45.689603: +2024-11-21 20:14:45.689824: Epoch 1756 +2024-11-21 20:14:45.689934: Current learning rate: 0.008 +2024-11-21 20:15:03.647411: train_loss -0.7698 +2024-11-21 20:15:03.647639: val_loss -0.75 +2024-11-21 20:15:03.647714: Pseudo dice [0.8177] +2024-11-21 20:15:03.647789: Epoch time: 17.96 s +2024-11-21 20:15:04.500341: +2024-11-21 20:15:04.500570: Epoch 1757 +2024-11-21 20:15:04.500684: Current learning rate: 0.008 +2024-11-21 20:15:22.212095: train_loss -0.7708 +2024-11-21 20:15:22.212320: val_loss -0.7379 +2024-11-21 20:15:22.212399: Pseudo dice [0.8083] +2024-11-21 20:15:22.212476: Epoch time: 17.71 s +2024-11-21 20:15:23.246196: +2024-11-21 20:15:23.246440: Epoch 1758 +2024-11-21 20:15:23.246557: Current learning rate: 0.008 +2024-11-21 20:15:43.187647: train_loss -0.7764 +2024-11-21 20:15:43.187945: val_loss -0.7416 +2024-11-21 20:15:43.188097: Pseudo dice [0.835] +2024-11-21 20:15:43.188184: Epoch time: 19.94 s +2024-11-21 20:15:44.132759: +2024-11-21 20:15:44.132965: Epoch 1759 +2024-11-21 20:15:44.133079: Current learning rate: 0.008 +2024-11-21 20:16:03.492338: train_loss -0.7692 +2024-11-21 20:16:03.492554: val_loss -0.7335 +2024-11-21 20:16:03.492629: Pseudo dice [0.8082] +2024-11-21 20:16:03.492709: Epoch time: 19.36 s +2024-11-21 20:16:04.346031: +2024-11-21 20:16:04.346241: Epoch 1760 +2024-11-21 20:16:04.346355: Current learning rate: 0.008 +2024-11-21 20:16:23.497495: train_loss -0.7818 +2024-11-21 20:16:23.497713: val_loss -0.7648 +2024-11-21 20:16:23.497785: Pseudo dice [0.8077] +2024-11-21 20:16:23.497861: Epoch time: 19.15 s +2024-11-21 20:16:24.448601: +2024-11-21 20:16:24.448827: Epoch 1761 +2024-11-21 20:16:24.448949: Current learning rate: 0.008 +2024-11-21 20:16:43.316903: train_loss -0.7732 +2024-11-21 20:16:43.317132: val_loss -0.7453 +2024-11-21 20:16:43.317206: Pseudo dice [0.8372] +2024-11-21 20:16:43.317288: Epoch time: 18.87 s +2024-11-21 20:16:44.261937: +2024-11-21 20:16:44.262208: Epoch 1762 +2024-11-21 20:16:44.262321: Current learning rate: 0.00799 +2024-11-21 20:17:01.906780: train_loss -0.7743 +2024-11-21 20:17:01.912240: val_loss -0.7222 +2024-11-21 20:17:01.912357: Pseudo dice [0.8107] +2024-11-21 20:17:01.912448: Epoch time: 17.65 s +2024-11-21 20:17:02.801170: +2024-11-21 20:17:02.801438: Epoch 1763 +2024-11-21 20:17:02.801556: Current learning rate: 0.00799 +2024-11-21 20:17:21.945528: train_loss -0.7717 +2024-11-21 20:17:21.945807: val_loss -0.7494 +2024-11-21 20:17:21.945884: Pseudo dice [0.8186] +2024-11-21 20:17:21.945961: Epoch time: 19.15 s +2024-11-21 20:17:22.808223: +2024-11-21 20:17:22.808436: Epoch 1764 +2024-11-21 20:17:22.808553: Current learning rate: 0.00799 +2024-11-21 20:17:42.034381: train_loss -0.7745 +2024-11-21 20:17:42.034608: val_loss -0.749 +2024-11-21 20:17:42.034685: Pseudo dice [0.8139] +2024-11-21 20:17:42.034762: Epoch time: 19.23 s +2024-11-21 20:17:42.885915: +2024-11-21 20:17:42.886195: Epoch 1765 +2024-11-21 20:17:42.886312: Current learning rate: 0.00799 +2024-11-21 20:18:02.205399: train_loss -0.7595 +2024-11-21 20:18:02.205620: val_loss -0.7279 +2024-11-21 20:18:02.205700: Pseudo dice [0.8335] +2024-11-21 20:18:02.207469: Epoch time: 19.32 s +2024-11-21 20:18:03.096617: +2024-11-21 20:18:03.096830: Epoch 1766 +2024-11-21 20:18:03.096951: Current learning rate: 0.00799 +2024-11-21 20:18:22.375713: train_loss -0.7598 +2024-11-21 20:18:22.375935: val_loss -0.7285 +2024-11-21 20:18:22.376016: Pseudo dice [0.817] +2024-11-21 20:18:22.376093: Epoch time: 19.28 s +2024-11-21 20:18:23.622084: +2024-11-21 20:18:23.622381: Epoch 1767 +2024-11-21 20:18:23.622495: Current learning rate: 0.00799 +2024-11-21 20:18:42.811444: train_loss -0.7567 +2024-11-21 20:18:42.811692: val_loss -0.7165 +2024-11-21 20:18:42.811769: Pseudo dice [0.8058] +2024-11-21 20:18:42.811844: Epoch time: 19.19 s +2024-11-21 20:18:43.658714: +2024-11-21 20:18:43.658936: Epoch 1768 +2024-11-21 20:18:43.659050: Current learning rate: 0.00799 +2024-11-21 20:19:02.775937: train_loss -0.7562 +2024-11-21 20:19:02.776161: val_loss -0.7278 +2024-11-21 20:19:02.776235: Pseudo dice [0.8137] +2024-11-21 20:19:02.776312: Epoch time: 19.12 s +2024-11-21 20:19:03.676906: +2024-11-21 20:19:03.677129: Epoch 1769 +2024-11-21 20:19:03.677241: Current learning rate: 0.00799 +2024-11-21 20:19:23.354816: train_loss -0.7591 +2024-11-21 20:19:23.357263: val_loss -0.7209 +2024-11-21 20:19:23.357359: Pseudo dice [0.8387] +2024-11-21 20:19:23.357447: Epoch time: 19.68 s +2024-11-21 20:19:24.358682: +2024-11-21 20:19:24.358884: Epoch 1770 +2024-11-21 20:19:24.359003: Current learning rate: 0.00798 +2024-11-21 20:19:42.431657: train_loss -0.7689 +2024-11-21 20:19:42.431879: val_loss -0.7361 +2024-11-21 20:19:42.432045: Pseudo dice [0.8305] +2024-11-21 20:19:42.432124: Epoch time: 18.07 s +2024-11-21 20:19:43.289188: +2024-11-21 20:19:43.289418: Epoch 1771 +2024-11-21 20:19:43.289541: Current learning rate: 0.00798 +2024-11-21 20:20:02.200773: train_loss -0.772 +2024-11-21 20:20:02.201000: val_loss -0.7185 +2024-11-21 20:20:02.201074: Pseudo dice [0.8088] +2024-11-21 20:20:02.201149: Epoch time: 18.91 s +2024-11-21 20:20:03.048354: +2024-11-21 20:20:03.048636: Epoch 1772 +2024-11-21 20:20:03.048758: Current learning rate: 0.00798 +2024-11-21 20:20:23.225989: train_loss -0.7758 +2024-11-21 20:20:23.226216: val_loss -0.731 +2024-11-21 20:20:23.226287: Pseudo dice [0.8259] +2024-11-21 20:20:23.226364: Epoch time: 20.18 s +2024-11-21 20:20:24.078752: +2024-11-21 20:20:24.079006: Epoch 1773 +2024-11-21 20:20:24.079136: Current learning rate: 0.00798 +2024-11-21 20:20:43.433594: train_loss -0.7587 +2024-11-21 20:20:43.433849: val_loss -0.7145 +2024-11-21 20:20:43.433923: Pseudo dice [0.8028] +2024-11-21 20:20:43.434011: Epoch time: 19.36 s +2024-11-21 20:20:44.279725: +2024-11-21 20:20:44.279975: Epoch 1774 +2024-11-21 20:20:44.280217: Current learning rate: 0.00798 +2024-11-21 20:21:03.984831: train_loss -0.7662 +2024-11-21 20:21:03.985055: val_loss -0.7311 +2024-11-21 20:21:03.985136: Pseudo dice [0.813] +2024-11-21 20:21:03.985217: Epoch time: 19.71 s +2024-11-21 20:21:04.942129: +2024-11-21 20:21:04.942344: Epoch 1775 +2024-11-21 20:21:04.942458: Current learning rate: 0.00798 +2024-11-21 20:21:23.419345: train_loss -0.7711 +2024-11-21 20:21:23.419560: val_loss -0.7398 +2024-11-21 20:21:23.419635: Pseudo dice [0.8002] +2024-11-21 20:21:23.419710: Epoch time: 18.48 s +2024-11-21 20:21:24.559111: +2024-11-21 20:21:24.559313: Epoch 1776 +2024-11-21 20:21:24.559430: Current learning rate: 0.00798 +2024-11-21 20:21:43.320913: train_loss -0.7764 +2024-11-21 20:21:43.321159: val_loss -0.7557 +2024-11-21 20:21:43.321236: Pseudo dice [0.8268] +2024-11-21 20:21:43.321325: Epoch time: 18.76 s +2024-11-21 20:21:44.162510: +2024-11-21 20:21:44.162717: Epoch 1777 +2024-11-21 20:21:44.162830: Current learning rate: 0.00798 +2024-11-21 20:22:03.044098: train_loss -0.781 +2024-11-21 20:22:03.044308: val_loss -0.754 +2024-11-21 20:22:03.044384: Pseudo dice [0.8231] +2024-11-21 20:22:03.044463: Epoch time: 18.88 s +2024-11-21 20:22:04.185294: +2024-11-21 20:22:04.185547: Epoch 1778 +2024-11-21 20:22:04.185659: Current learning rate: 0.00798 +2024-11-21 20:22:24.248483: train_loss -0.7702 +2024-11-21 20:22:24.250917: val_loss -0.7461 +2024-11-21 20:22:24.251015: Pseudo dice [0.8051] +2024-11-21 20:22:24.251096: Epoch time: 20.06 s +2024-11-21 20:22:25.102680: +2024-11-21 20:22:25.102898: Epoch 1779 +2024-11-21 20:22:25.103014: Current learning rate: 0.00797 +2024-11-21 20:22:43.242653: train_loss -0.7632 +2024-11-21 20:22:43.242865: val_loss -0.7257 +2024-11-21 20:22:43.242942: Pseudo dice [0.8081] +2024-11-21 20:22:43.243028: Epoch time: 18.14 s +2024-11-21 20:22:44.088691: +2024-11-21 20:22:44.089071: Epoch 1780 +2024-11-21 20:22:44.089183: Current learning rate: 0.00797 +2024-11-21 20:23:03.502584: train_loss -0.7699 +2024-11-21 20:23:03.502828: val_loss -0.7337 +2024-11-21 20:23:03.502906: Pseudo dice [0.8145] +2024-11-21 20:23:03.502990: Epoch time: 19.41 s +2024-11-21 20:23:04.359785: +2024-11-21 20:23:04.360012: Epoch 1781 +2024-11-21 20:23:04.360130: Current learning rate: 0.00797 +2024-11-21 20:23:22.584332: train_loss -0.761 +2024-11-21 20:23:22.584549: val_loss -0.7182 +2024-11-21 20:23:22.584624: Pseudo dice [0.8024] +2024-11-21 20:23:22.584700: Epoch time: 18.23 s +2024-11-21 20:23:23.491648: +2024-11-21 20:23:23.491866: Epoch 1782 +2024-11-21 20:23:23.491986: Current learning rate: 0.00797 +2024-11-21 20:23:42.637965: train_loss -0.7551 +2024-11-21 20:23:42.638185: val_loss -0.7432 +2024-11-21 20:23:42.638258: Pseudo dice [0.828] +2024-11-21 20:23:42.638335: Epoch time: 19.15 s +2024-11-21 20:23:43.500826: +2024-11-21 20:23:43.501059: Epoch 1783 +2024-11-21 20:23:43.501172: Current learning rate: 0.00797 +2024-11-21 20:24:02.943114: train_loss -0.7529 +2024-11-21 20:24:02.943332: val_loss -0.7224 +2024-11-21 20:24:02.943412: Pseudo dice [0.8356] +2024-11-21 20:24:02.943496: Epoch time: 19.44 s +2024-11-21 20:24:03.791756: +2024-11-21 20:24:03.791963: Epoch 1784 +2024-11-21 20:24:03.792080: Current learning rate: 0.00797 +2024-11-21 20:24:22.221632: train_loss -0.7642 +2024-11-21 20:24:22.221956: val_loss -0.7304 +2024-11-21 20:24:22.222049: Pseudo dice [0.8201] +2024-11-21 20:24:22.222133: Epoch time: 18.43 s +2024-11-21 20:24:23.075358: +2024-11-21 20:24:23.075641: Epoch 1785 +2024-11-21 20:24:23.075756: Current learning rate: 0.00797 +2024-11-21 20:24:42.955361: train_loss -0.7523 +2024-11-21 20:24:42.955574: val_loss -0.7266 +2024-11-21 20:24:42.955646: Pseudo dice [0.8157] +2024-11-21 20:24:42.957953: Epoch time: 19.88 s +2024-11-21 20:24:43.848903: +2024-11-21 20:24:43.849114: Epoch 1786 +2024-11-21 20:24:43.849223: Current learning rate: 0.00797 +2024-11-21 20:25:02.169946: train_loss -0.7629 +2024-11-21 20:25:02.170169: val_loss -0.764 +2024-11-21 20:25:02.170242: Pseudo dice [0.8418] +2024-11-21 20:25:02.170317: Epoch time: 18.32 s +2024-11-21 20:25:03.023134: +2024-11-21 20:25:03.023380: Epoch 1787 +2024-11-21 20:25:03.023495: Current learning rate: 0.00797 +2024-11-21 20:25:21.424158: train_loss -0.7638 +2024-11-21 20:25:21.424399: val_loss -0.7342 +2024-11-21 20:25:21.424475: Pseudo dice [0.8162] +2024-11-21 20:25:21.424562: Epoch time: 18.4 s +2024-11-21 20:25:22.280452: +2024-11-21 20:25:22.280645: Epoch 1788 +2024-11-21 20:25:22.280765: Current learning rate: 0.00796 +2024-11-21 20:25:40.907264: train_loss -0.7653 +2024-11-21 20:25:40.907479: val_loss -0.7447 +2024-11-21 20:25:40.907555: Pseudo dice [0.817] +2024-11-21 20:25:40.907631: Epoch time: 18.63 s +2024-11-21 20:25:42.134860: +2024-11-21 20:25:42.135182: Epoch 1789 +2024-11-21 20:25:42.135294: Current learning rate: 0.00796 +2024-11-21 20:26:00.022209: train_loss -0.7751 +2024-11-21 20:26:00.022468: val_loss -0.7561 +2024-11-21 20:26:00.022551: Pseudo dice [0.8201] +2024-11-21 20:26:00.022634: Epoch time: 17.89 s +2024-11-21 20:26:01.132936: +2024-11-21 20:26:01.133173: Epoch 1790 +2024-11-21 20:26:01.133288: Current learning rate: 0.00796 +2024-11-21 20:26:20.200403: train_loss -0.7666 +2024-11-21 20:26:20.200653: val_loss -0.7568 +2024-11-21 20:26:20.200729: Pseudo dice [0.8295] +2024-11-21 20:26:20.200814: Epoch time: 19.07 s +2024-11-21 20:26:21.069269: +2024-11-21 20:26:21.084199: Epoch 1791 +2024-11-21 20:26:21.084334: Current learning rate: 0.00796 +2024-11-21 20:26:40.777805: train_loss -0.7745 +2024-11-21 20:26:40.783203: val_loss -0.7445 +2024-11-21 20:26:40.783338: Pseudo dice [0.8197] +2024-11-21 20:26:40.783419: Epoch time: 19.71 s +2024-11-21 20:26:41.771275: +2024-11-21 20:26:41.771485: Epoch 1792 +2024-11-21 20:26:41.771600: Current learning rate: 0.00796 +2024-11-21 20:27:01.031810: train_loss -0.7801 +2024-11-21 20:27:01.032042: val_loss -0.7403 +2024-11-21 20:27:01.032117: Pseudo dice [0.8318] +2024-11-21 20:27:01.032195: Epoch time: 19.26 s +2024-11-21 20:27:01.882823: +2024-11-21 20:27:01.883029: Epoch 1793 +2024-11-21 20:27:01.883141: Current learning rate: 0.00796 +2024-11-21 20:27:20.809039: train_loss -0.7758 +2024-11-21 20:27:20.809265: val_loss -0.7097 +2024-11-21 20:27:20.809347: Pseudo dice [0.7997] +2024-11-21 20:27:20.809425: Epoch time: 18.93 s +2024-11-21 20:27:21.666536: +2024-11-21 20:27:21.666723: Epoch 1794 +2024-11-21 20:27:21.666834: Current learning rate: 0.00796 +2024-11-21 20:27:39.482969: train_loss -0.7754 +2024-11-21 20:27:39.483221: val_loss -0.7495 +2024-11-21 20:27:39.483296: Pseudo dice [0.8175] +2024-11-21 20:27:39.483388: Epoch time: 17.82 s +2024-11-21 20:27:40.334508: +2024-11-21 20:27:40.334719: Epoch 1795 +2024-11-21 20:27:40.334834: Current learning rate: 0.00796 +2024-11-21 20:27:59.596860: train_loss -0.7709 +2024-11-21 20:27:59.597079: val_loss -0.734 +2024-11-21 20:27:59.597157: Pseudo dice [0.8107] +2024-11-21 20:27:59.597239: Epoch time: 19.26 s +2024-11-21 20:28:00.447923: +2024-11-21 20:28:00.448119: Epoch 1796 +2024-11-21 20:28:00.448234: Current learning rate: 0.00795 +2024-11-21 20:28:19.906586: train_loss -0.7726 +2024-11-21 20:28:19.906798: val_loss -0.7422 +2024-11-21 20:28:19.906874: Pseudo dice [0.8235] +2024-11-21 20:28:19.906952: Epoch time: 19.46 s +2024-11-21 20:28:20.758698: +2024-11-21 20:28:20.758897: Epoch 1797 +2024-11-21 20:28:20.759014: Current learning rate: 0.00795 +2024-11-21 20:28:38.551675: train_loss -0.7729 +2024-11-21 20:28:38.551886: val_loss -0.7453 +2024-11-21 20:28:38.551969: Pseudo dice [0.8297] +2024-11-21 20:28:38.552062: Epoch time: 17.79 s +2024-11-21 20:28:39.401232: +2024-11-21 20:28:39.401432: Epoch 1798 +2024-11-21 20:28:39.401545: Current learning rate: 0.00795 +2024-11-21 20:28:59.065051: train_loss -0.7713 +2024-11-21 20:28:59.070019: val_loss -0.6988 +2024-11-21 20:28:59.070135: Pseudo dice [0.803] +2024-11-21 20:28:59.070224: Epoch time: 19.66 s +2024-11-21 20:28:59.937394: +2024-11-21 20:28:59.937600: Epoch 1799 +2024-11-21 20:28:59.937712: Current learning rate: 0.00795 +2024-11-21 20:29:19.654300: train_loss -0.7665 +2024-11-21 20:29:19.654574: val_loss -0.7377 +2024-11-21 20:29:19.654661: Pseudo dice [0.8258] +2024-11-21 20:29:19.654742: Epoch time: 19.72 s +2024-11-21 20:29:21.089575: +2024-11-21 20:29:21.089862: Epoch 1800 +2024-11-21 20:29:21.089990: Current learning rate: 0.00795 +2024-11-21 20:29:39.242714: train_loss -0.7686 +2024-11-21 20:29:39.242961: val_loss -0.7252 +2024-11-21 20:29:39.243043: Pseudo dice [0.8288] +2024-11-21 20:29:39.243128: Epoch time: 18.15 s +2024-11-21 20:29:40.095511: +2024-11-21 20:29:40.095751: Epoch 1801 +2024-11-21 20:29:40.095877: Current learning rate: 0.00795 +2024-11-21 20:29:58.818367: train_loss -0.7727 +2024-11-21 20:29:58.818569: val_loss -0.7407 +2024-11-21 20:29:58.818644: Pseudo dice [0.8213] +2024-11-21 20:29:58.818720: Epoch time: 18.72 s +2024-11-21 20:29:59.669454: +2024-11-21 20:29:59.669686: Epoch 1802 +2024-11-21 20:29:59.669800: Current learning rate: 0.00795 +2024-11-21 20:30:18.003013: train_loss -0.7817 +2024-11-21 20:30:18.003241: val_loss -0.739 +2024-11-21 20:30:18.003322: Pseudo dice [0.8371] +2024-11-21 20:30:18.003403: Epoch time: 18.33 s +2024-11-21 20:30:18.853575: +2024-11-21 20:30:18.853786: Epoch 1803 +2024-11-21 20:30:18.853901: Current learning rate: 0.00795 +2024-11-21 20:30:38.245946: train_loss -0.7742 +2024-11-21 20:30:38.246203: val_loss -0.7089 +2024-11-21 20:30:38.246279: Pseudo dice [0.7932] +2024-11-21 20:30:38.272291: Epoch time: 19.39 s +2024-11-21 20:30:39.130229: +2024-11-21 20:30:39.130457: Epoch 1804 +2024-11-21 20:30:39.130599: Current learning rate: 0.00795 +2024-11-21 20:30:57.453983: train_loss -0.778 +2024-11-21 20:30:57.454245: val_loss -0.7336 +2024-11-21 20:30:57.454323: Pseudo dice [0.8041] +2024-11-21 20:30:57.454463: Epoch time: 18.32 s +2024-11-21 20:30:58.311362: +2024-11-21 20:30:58.311595: Epoch 1805 +2024-11-21 20:30:58.311715: Current learning rate: 0.00794 +2024-11-21 20:31:16.521738: train_loss -0.7631 +2024-11-21 20:31:16.522017: val_loss -0.7302 +2024-11-21 20:31:16.522093: Pseudo dice [0.8069] +2024-11-21 20:31:16.522169: Epoch time: 18.21 s +2024-11-21 20:31:17.368937: +2024-11-21 20:31:17.369194: Epoch 1806 +2024-11-21 20:31:17.369313: Current learning rate: 0.00794 +2024-11-21 20:31:37.486340: train_loss -0.7618 +2024-11-21 20:31:37.486559: val_loss -0.7166 +2024-11-21 20:31:37.486635: Pseudo dice [0.8252] +2024-11-21 20:31:37.486711: Epoch time: 20.12 s +2024-11-21 20:31:38.341885: +2024-11-21 20:31:38.342163: Epoch 1807 +2024-11-21 20:31:38.342278: Current learning rate: 0.00794 +2024-11-21 20:31:56.757663: train_loss -0.7751 +2024-11-21 20:31:56.757876: val_loss -0.7572 +2024-11-21 20:31:56.757948: Pseudo dice [0.824] +2024-11-21 20:31:56.758032: Epoch time: 18.42 s +2024-11-21 20:31:57.612729: +2024-11-21 20:31:57.612921: Epoch 1808 +2024-11-21 20:31:57.613050: Current learning rate: 0.00794 +2024-11-21 20:32:16.609449: train_loss -0.7632 +2024-11-21 20:32:16.609694: val_loss -0.7486 +2024-11-21 20:32:16.609785: Pseudo dice [0.8165] +2024-11-21 20:32:16.609866: Epoch time: 19.0 s +2024-11-21 20:32:17.460922: +2024-11-21 20:32:17.461312: Epoch 1809 +2024-11-21 20:32:17.461428: Current learning rate: 0.00794 +2024-11-21 20:32:35.216879: train_loss -0.7679 +2024-11-21 20:32:35.217166: val_loss -0.7579 +2024-11-21 20:32:35.217240: Pseudo dice [0.8272] +2024-11-21 20:32:35.217318: Epoch time: 17.76 s +2024-11-21 20:32:36.067348: +2024-11-21 20:32:36.067549: Epoch 1810 +2024-11-21 20:32:36.067667: Current learning rate: 0.00794 +2024-11-21 20:32:54.760628: train_loss -0.7665 +2024-11-21 20:32:54.760843: val_loss -0.7089 +2024-11-21 20:32:54.760919: Pseudo dice [0.8036] +2024-11-21 20:32:54.761009: Epoch time: 18.69 s +2024-11-21 20:32:55.608106: +2024-11-21 20:32:55.608299: Epoch 1811 +2024-11-21 20:32:55.608408: Current learning rate: 0.00794 +2024-11-21 20:33:14.378933: train_loss -0.7653 +2024-11-21 20:33:14.379236: val_loss -0.7344 +2024-11-21 20:33:14.379312: Pseudo dice [0.833] +2024-11-21 20:33:14.379399: Epoch time: 18.77 s +2024-11-21 20:33:15.639256: +2024-11-21 20:33:15.639754: Epoch 1812 +2024-11-21 20:33:15.639868: Current learning rate: 0.00794 +2024-11-21 20:33:33.264482: train_loss -0.777 +2024-11-21 20:33:33.264708: val_loss -0.7446 +2024-11-21 20:33:33.264842: Pseudo dice [0.832] +2024-11-21 20:33:33.264919: Epoch time: 17.63 s +2024-11-21 20:33:34.109120: +2024-11-21 20:33:34.109334: Epoch 1813 +2024-11-21 20:33:34.109445: Current learning rate: 0.00794 +2024-11-21 20:33:53.411382: train_loss -0.7767 +2024-11-21 20:33:53.411594: val_loss -0.7614 +2024-11-21 20:33:53.411670: Pseudo dice [0.8346] +2024-11-21 20:33:53.411746: Epoch time: 19.3 s +2024-11-21 20:33:54.360208: +2024-11-21 20:33:54.360432: Epoch 1814 +2024-11-21 20:33:54.360548: Current learning rate: 0.00793 +2024-11-21 20:34:14.214085: train_loss -0.7703 +2024-11-21 20:34:14.214333: val_loss -0.7328 +2024-11-21 20:34:14.214407: Pseudo dice [0.782] +2024-11-21 20:34:14.214496: Epoch time: 19.85 s +2024-11-21 20:34:15.064711: +2024-11-21 20:34:15.064925: Epoch 1815 +2024-11-21 20:34:15.065040: Current learning rate: 0.00793 +2024-11-21 20:34:34.192408: train_loss -0.7778 +2024-11-21 20:34:34.192624: val_loss -0.7564 +2024-11-21 20:34:34.192697: Pseudo dice [0.8311] +2024-11-21 20:34:34.192771: Epoch time: 19.13 s +2024-11-21 20:34:35.040043: +2024-11-21 20:34:35.040248: Epoch 1816 +2024-11-21 20:34:35.040364: Current learning rate: 0.00793 +2024-11-21 20:34:53.698539: train_loss -0.7767 +2024-11-21 20:34:53.698763: val_loss -0.7547 +2024-11-21 20:34:53.698838: Pseudo dice [0.8204] +2024-11-21 20:34:53.698918: Epoch time: 18.66 s +2024-11-21 20:34:54.573637: +2024-11-21 20:34:54.573845: Epoch 1817 +2024-11-21 20:34:54.573961: Current learning rate: 0.00793 +2024-11-21 20:35:12.786550: train_loss -0.7853 +2024-11-21 20:35:12.791337: val_loss -0.7368 +2024-11-21 20:35:12.791471: Pseudo dice [0.8252] +2024-11-21 20:35:12.791552: Epoch time: 18.21 s +2024-11-21 20:35:13.638884: +2024-11-21 20:35:13.639072: Epoch 1818 +2024-11-21 20:35:13.639185: Current learning rate: 0.00793 +2024-11-21 20:35:32.107916: train_loss -0.7742 +2024-11-21 20:35:32.108137: val_loss -0.7606 +2024-11-21 20:35:32.108217: Pseudo dice [0.8457] +2024-11-21 20:35:32.108299: Epoch time: 18.47 s +2024-11-21 20:35:32.959780: +2024-11-21 20:35:32.959997: Epoch 1819 +2024-11-21 20:35:32.960115: Current learning rate: 0.00793 +2024-11-21 20:35:51.998570: train_loss -0.7625 +2024-11-21 20:35:51.998806: val_loss -0.7485 +2024-11-21 20:35:51.998878: Pseudo dice [0.8392] +2024-11-21 20:35:51.998958: Epoch time: 19.04 s +2024-11-21 20:35:52.842657: +2024-11-21 20:35:52.842851: Epoch 1820 +2024-11-21 20:35:52.842965: Current learning rate: 0.00793 +2024-11-21 20:36:11.460896: train_loss -0.7786 +2024-11-21 20:36:11.461148: val_loss -0.7562 +2024-11-21 20:36:11.461241: Pseudo dice [0.8322] +2024-11-21 20:36:11.461333: Epoch time: 18.62 s +2024-11-21 20:36:12.310106: +2024-11-21 20:36:12.310327: Epoch 1821 +2024-11-21 20:36:12.310440: Current learning rate: 0.00793 +2024-11-21 20:36:31.452340: train_loss -0.7652 +2024-11-21 20:36:31.452550: val_loss -0.7305 +2024-11-21 20:36:31.452626: Pseudo dice [0.8202] +2024-11-21 20:36:31.452703: Epoch time: 19.14 s +2024-11-21 20:36:32.394831: +2024-11-21 20:36:32.395086: Epoch 1822 +2024-11-21 20:36:32.395199: Current learning rate: 0.00792 +2024-11-21 20:36:51.485967: train_loss -0.767 +2024-11-21 20:36:51.486211: val_loss -0.7406 +2024-11-21 20:36:51.486286: Pseudo dice [0.8226] +2024-11-21 20:36:51.486371: Epoch time: 19.09 s +2024-11-21 20:36:52.333898: +2024-11-21 20:36:52.334171: Epoch 1823 +2024-11-21 20:36:52.334285: Current learning rate: 0.00792 +2024-11-21 20:37:10.643973: train_loss -0.7621 +2024-11-21 20:37:10.644469: val_loss -0.7122 +2024-11-21 20:37:10.644572: Pseudo dice [0.8066] +2024-11-21 20:37:10.644661: Epoch time: 18.31 s +2024-11-21 20:37:11.486411: +2024-11-21 20:37:11.486730: Epoch 1824 +2024-11-21 20:37:11.486844: Current learning rate: 0.00792 +2024-11-21 20:37:29.918308: train_loss -0.7697 +2024-11-21 20:37:29.918574: val_loss -0.7334 +2024-11-21 20:37:29.918648: Pseudo dice [0.8066] +2024-11-21 20:37:29.918725: Epoch time: 18.43 s +2024-11-21 20:37:30.768005: +2024-11-21 20:37:30.768220: Epoch 1825 +2024-11-21 20:37:30.768337: Current learning rate: 0.00792 +2024-11-21 20:37:49.801896: train_loss -0.7677 +2024-11-21 20:37:49.807318: val_loss -0.7581 +2024-11-21 20:37:49.807444: Pseudo dice [0.829] +2024-11-21 20:37:49.807542: Epoch time: 19.03 s +2024-11-21 20:37:50.686395: +2024-11-21 20:37:50.686690: Epoch 1826 +2024-11-21 20:37:50.686803: Current learning rate: 0.00792 +2024-11-21 20:38:08.657119: train_loss -0.7684 +2024-11-21 20:38:08.657634: val_loss -0.7112 +2024-11-21 20:38:08.657744: Pseudo dice [0.8031] +2024-11-21 20:38:08.657825: Epoch time: 17.97 s +2024-11-21 20:38:09.661645: +2024-11-21 20:38:09.661927: Epoch 1827 +2024-11-21 20:38:09.662039: Current learning rate: 0.00792 +2024-11-21 20:38:27.618304: train_loss -0.7627 +2024-11-21 20:38:27.618531: val_loss -0.7632 +2024-11-21 20:38:27.618603: Pseudo dice [0.8303] +2024-11-21 20:38:27.618680: Epoch time: 17.96 s +2024-11-21 20:38:28.601148: +2024-11-21 20:38:28.601357: Epoch 1828 +2024-11-21 20:38:28.601470: Current learning rate: 0.00792 +2024-11-21 20:38:48.063437: train_loss -0.7796 +2024-11-21 20:38:48.063656: val_loss -0.7442 +2024-11-21 20:38:48.063732: Pseudo dice [0.8338] +2024-11-21 20:38:48.063810: Epoch time: 19.46 s +2024-11-21 20:38:48.909594: +2024-11-21 20:38:48.909821: Epoch 1829 +2024-11-21 20:38:48.910651: Current learning rate: 0.00792 +2024-11-21 20:39:07.697138: train_loss -0.7815 +2024-11-21 20:39:07.697382: val_loss -0.746 +2024-11-21 20:39:07.699265: Pseudo dice [0.8308] +2024-11-21 20:39:07.699377: Epoch time: 18.79 s +2024-11-21 20:39:08.584505: +2024-11-21 20:39:08.584748: Epoch 1830 +2024-11-21 20:39:08.584861: Current learning rate: 0.00792 +2024-11-21 20:39:27.005053: train_loss -0.7792 +2024-11-21 20:39:27.005277: val_loss -0.7342 +2024-11-21 20:39:27.005350: Pseudo dice [0.8096] +2024-11-21 20:39:27.005424: Epoch time: 18.42 s +2024-11-21 20:39:27.849187: +2024-11-21 20:39:27.849427: Epoch 1831 +2024-11-21 20:39:27.849549: Current learning rate: 0.00791 +2024-11-21 20:39:46.667332: train_loss -0.7658 +2024-11-21 20:39:46.671006: val_loss -0.7589 +2024-11-21 20:39:46.671130: Pseudo dice [0.8248] +2024-11-21 20:39:46.671211: Epoch time: 18.82 s +2024-11-21 20:39:47.528268: +2024-11-21 20:39:47.528470: Epoch 1832 +2024-11-21 20:39:47.528581: Current learning rate: 0.00791 +2024-11-21 20:40:06.034819: train_loss -0.778 +2024-11-21 20:40:06.035067: val_loss -0.7552 +2024-11-21 20:40:06.035143: Pseudo dice [0.818] +2024-11-21 20:40:06.035268: Epoch time: 18.51 s +2024-11-21 20:40:06.882870: +2024-11-21 20:40:06.883073: Epoch 1833 +2024-11-21 20:40:06.883185: Current learning rate: 0.00791 +2024-11-21 20:40:24.761547: train_loss -0.7748 +2024-11-21 20:40:24.761752: val_loss -0.74 +2024-11-21 20:40:24.761825: Pseudo dice [0.8368] +2024-11-21 20:40:24.761902: Epoch time: 17.88 s +2024-11-21 20:40:25.609394: +2024-11-21 20:40:25.609590: Epoch 1834 +2024-11-21 20:40:25.609700: Current learning rate: 0.00791 +2024-11-21 20:40:44.719444: train_loss -0.7779 +2024-11-21 20:40:44.719657: val_loss -0.7372 +2024-11-21 20:40:44.719733: Pseudo dice [0.818] +2024-11-21 20:40:44.719809: Epoch time: 19.11 s +2024-11-21 20:40:45.999086: +2024-11-21 20:40:45.999304: Epoch 1835 +2024-11-21 20:40:45.999423: Current learning rate: 0.00791 +2024-11-21 20:41:04.683242: train_loss -0.7568 +2024-11-21 20:41:04.683491: val_loss -0.7464 +2024-11-21 20:41:04.683568: Pseudo dice [0.8201] +2024-11-21 20:41:04.683655: Epoch time: 18.68 s +2024-11-21 20:41:05.533864: +2024-11-21 20:41:05.534083: Epoch 1836 +2024-11-21 20:41:05.534199: Current learning rate: 0.00791 +2024-11-21 20:41:25.352510: train_loss -0.7573 +2024-11-21 20:41:25.352721: val_loss -0.7118 +2024-11-21 20:41:25.352794: Pseudo dice [0.7872] +2024-11-21 20:41:25.352870: Epoch time: 19.82 s +2024-11-21 20:41:26.226597: +2024-11-21 20:41:26.226823: Epoch 1837 +2024-11-21 20:41:26.226939: Current learning rate: 0.00791 +2024-11-21 20:41:45.789082: train_loss -0.7672 +2024-11-21 20:41:45.789303: val_loss -0.7174 +2024-11-21 20:41:45.789381: Pseudo dice [0.8208] +2024-11-21 20:41:45.789459: Epoch time: 19.56 s +2024-11-21 20:41:46.639226: +2024-11-21 20:41:46.639431: Epoch 1838 +2024-11-21 20:41:46.639546: Current learning rate: 0.00791 +2024-11-21 20:42:05.745160: train_loss -0.7612 +2024-11-21 20:42:05.745396: val_loss -0.7109 +2024-11-21 20:42:05.745536: Pseudo dice [0.8109] +2024-11-21 20:42:05.745615: Epoch time: 19.11 s +2024-11-21 20:42:06.694650: +2024-11-21 20:42:06.694890: Epoch 1839 +2024-11-21 20:42:06.695011: Current learning rate: 0.00791 +2024-11-21 20:42:24.883471: train_loss -0.7784 +2024-11-21 20:42:24.883705: val_loss -0.7412 +2024-11-21 20:42:24.883781: Pseudo dice [0.8247] +2024-11-21 20:42:24.883863: Epoch time: 18.19 s +2024-11-21 20:42:25.735821: +2024-11-21 20:42:25.736046: Epoch 1840 +2024-11-21 20:42:25.736161: Current learning rate: 0.0079 +2024-11-21 20:42:44.231873: train_loss -0.7694 +2024-11-21 20:42:44.234751: val_loss -0.7668 +2024-11-21 20:42:44.234894: Pseudo dice [0.8331] +2024-11-21 20:42:44.234973: Epoch time: 18.5 s +2024-11-21 20:42:45.116802: +2024-11-21 20:42:45.117006: Epoch 1841 +2024-11-21 20:42:45.117122: Current learning rate: 0.0079 +2024-11-21 20:43:04.583371: train_loss -0.7751 +2024-11-21 20:43:04.583578: val_loss -0.7413 +2024-11-21 20:43:04.583657: Pseudo dice [0.8355] +2024-11-21 20:43:04.583733: Epoch time: 19.47 s +2024-11-21 20:43:05.430607: +2024-11-21 20:43:05.430861: Epoch 1842 +2024-11-21 20:43:05.430971: Current learning rate: 0.0079 +2024-11-21 20:43:24.480595: train_loss -0.7782 +2024-11-21 20:43:24.480819: val_loss -0.7337 +2024-11-21 20:43:24.480893: Pseudo dice [0.8265] +2024-11-21 20:43:24.480972: Epoch time: 19.05 s +2024-11-21 20:43:25.338058: +2024-11-21 20:43:25.338272: Epoch 1843 +2024-11-21 20:43:25.338391: Current learning rate: 0.0079 +2024-11-21 20:43:44.649431: train_loss -0.7715 +2024-11-21 20:43:44.649677: val_loss -0.7652 +2024-11-21 20:43:44.649751: Pseudo dice [0.8432] +2024-11-21 20:43:44.649828: Epoch time: 19.31 s +2024-11-21 20:43:45.496704: +2024-11-21 20:43:45.496887: Epoch 1844 +2024-11-21 20:43:45.497000: Current learning rate: 0.0079 +2024-11-21 20:44:04.713874: train_loss -0.7713 +2024-11-21 20:44:04.714094: val_loss -0.7581 +2024-11-21 20:44:04.714171: Pseudo dice [0.8327] +2024-11-21 20:44:04.714247: Epoch time: 19.22 s +2024-11-21 20:44:05.562170: +2024-11-21 20:44:05.562376: Epoch 1845 +2024-11-21 20:44:05.562494: Current learning rate: 0.0079 +2024-11-21 20:44:23.706674: train_loss -0.7757 +2024-11-21 20:44:23.706890: val_loss -0.736 +2024-11-21 20:44:23.706965: Pseudo dice [0.8344] +2024-11-21 20:44:23.707048: Epoch time: 18.15 s +2024-11-21 20:44:24.553646: +2024-11-21 20:44:24.553838: Epoch 1846 +2024-11-21 20:44:24.553956: Current learning rate: 0.0079 +2024-11-21 20:44:43.905006: train_loss -0.7789 +2024-11-21 20:44:43.908140: val_loss -0.7416 +2024-11-21 20:44:43.908267: Pseudo dice [0.8317] +2024-11-21 20:44:43.908355: Epoch time: 19.35 s +2024-11-21 20:44:44.784582: +2024-11-21 20:44:44.784867: Epoch 1847 +2024-11-21 20:44:44.784977: Current learning rate: 0.0079 +2024-11-21 20:45:02.535983: train_loss -0.7715 +2024-11-21 20:45:02.536208: val_loss -0.7339 +2024-11-21 20:45:02.536283: Pseudo dice [0.82] +2024-11-21 20:45:02.536366: Epoch time: 17.75 s +2024-11-21 20:45:03.380347: +2024-11-21 20:45:03.380562: Epoch 1848 +2024-11-21 20:45:03.380674: Current learning rate: 0.00789 +2024-11-21 20:45:22.196957: train_loss -0.7759 +2024-11-21 20:45:22.197188: val_loss -0.7403 +2024-11-21 20:45:22.197264: Pseudo dice [0.8153] +2024-11-21 20:45:22.197344: Epoch time: 18.82 s +2024-11-21 20:45:23.046649: +2024-11-21 20:45:23.046867: Epoch 1849 +2024-11-21 20:45:23.046978: Current learning rate: 0.00789 +2024-11-21 20:45:40.738554: train_loss -0.7758 +2024-11-21 20:45:40.738801: val_loss -0.7446 +2024-11-21 20:45:40.738875: Pseudo dice [0.838] +2024-11-21 20:45:40.739018: Epoch time: 17.69 s +2024-11-21 20:45:41.831435: +2024-11-21 20:45:41.831650: Epoch 1850 +2024-11-21 20:45:41.831764: Current learning rate: 0.00789 +2024-11-21 20:46:00.501862: train_loss -0.7603 +2024-11-21 20:46:00.502079: val_loss -0.7316 +2024-11-21 20:46:00.502153: Pseudo dice [0.8125] +2024-11-21 20:46:00.502230: Epoch time: 18.67 s +2024-11-21 20:46:01.376260: +2024-11-21 20:46:01.376497: Epoch 1851 +2024-11-21 20:46:01.376615: Current learning rate: 0.00789 +2024-11-21 20:46:19.913872: train_loss -0.7525 +2024-11-21 20:46:19.914096: val_loss -0.7167 +2024-11-21 20:46:19.914171: Pseudo dice [0.8025] +2024-11-21 20:46:19.914250: Epoch time: 18.54 s +2024-11-21 20:46:20.761569: +2024-11-21 20:46:20.761790: Epoch 1852 +2024-11-21 20:46:20.761900: Current learning rate: 0.00789 +2024-11-21 20:46:40.590384: train_loss -0.7417 +2024-11-21 20:46:40.590591: val_loss -0.7204 +2024-11-21 20:46:40.590667: Pseudo dice [0.8149] +2024-11-21 20:46:40.590743: Epoch time: 19.83 s +2024-11-21 20:46:41.437091: +2024-11-21 20:46:41.437292: Epoch 1853 +2024-11-21 20:46:41.437408: Current learning rate: 0.00789 +2024-11-21 20:47:00.197883: train_loss -0.7667 +2024-11-21 20:47:00.198127: val_loss -0.714 +2024-11-21 20:47:00.198203: Pseudo dice [0.8308] +2024-11-21 20:47:00.198285: Epoch time: 18.76 s +2024-11-21 20:47:01.089531: +2024-11-21 20:47:01.089721: Epoch 1854 +2024-11-21 20:47:01.089830: Current learning rate: 0.00789 +2024-11-21 20:47:19.808681: train_loss -0.7705 +2024-11-21 20:47:19.808903: val_loss -0.7309 +2024-11-21 20:47:19.809741: Pseudo dice [0.8021] +2024-11-21 20:47:19.809865: Epoch time: 18.72 s +2024-11-21 20:47:20.717911: +2024-11-21 20:47:20.718110: Epoch 1855 +2024-11-21 20:47:20.718238: Current learning rate: 0.00789 +2024-11-21 20:47:38.499006: train_loss -0.7757 +2024-11-21 20:47:38.499229: val_loss -0.7336 +2024-11-21 20:47:38.499305: Pseudo dice [0.8032] +2024-11-21 20:47:38.499382: Epoch time: 17.78 s +2024-11-21 20:47:39.351633: +2024-11-21 20:47:39.351906: Epoch 1856 +2024-11-21 20:47:39.352023: Current learning rate: 0.00789 +2024-11-21 20:47:58.927097: train_loss -0.7695 +2024-11-21 20:47:58.927320: val_loss -0.7222 +2024-11-21 20:47:58.927396: Pseudo dice [0.8226] +2024-11-21 20:47:58.927473: Epoch time: 19.58 s +2024-11-21 20:48:00.014500: +2024-11-21 20:48:00.014714: Epoch 1857 +2024-11-21 20:48:00.014836: Current learning rate: 0.00788 +2024-11-21 20:48:18.412232: train_loss -0.7712 +2024-11-21 20:48:18.412807: val_loss -0.7399 +2024-11-21 20:48:18.412908: Pseudo dice [0.8134] +2024-11-21 20:48:18.412998: Epoch time: 18.4 s +2024-11-21 20:48:19.254416: +2024-11-21 20:48:19.254626: Epoch 1858 +2024-11-21 20:48:19.254741: Current learning rate: 0.00788 +2024-11-21 20:48:39.148036: train_loss -0.7816 +2024-11-21 20:48:39.148254: val_loss -0.7236 +2024-11-21 20:48:39.148329: Pseudo dice [0.8125] +2024-11-21 20:48:39.148405: Epoch time: 19.89 s +2024-11-21 20:48:39.993520: +2024-11-21 20:48:39.993752: Epoch 1859 +2024-11-21 20:48:39.993868: Current learning rate: 0.00788 +2024-11-21 20:48:58.594635: train_loss -0.7846 +2024-11-21 20:48:58.594858: val_loss -0.7233 +2024-11-21 20:48:58.594938: Pseudo dice [0.822] +2024-11-21 20:48:58.595029: Epoch time: 18.6 s +2024-11-21 20:48:59.441590: +2024-11-21 20:48:59.441805: Epoch 1860 +2024-11-21 20:48:59.441916: Current learning rate: 0.00788 +2024-11-21 20:49:17.591394: train_loss -0.7782 +2024-11-21 20:49:17.591641: val_loss -0.7408 +2024-11-21 20:49:17.591720: Pseudo dice [0.8198] +2024-11-21 20:49:17.591805: Epoch time: 18.15 s +2024-11-21 20:49:18.443779: +2024-11-21 20:49:18.444025: Epoch 1861 +2024-11-21 20:49:18.444142: Current learning rate: 0.00788 +2024-11-21 20:49:36.893635: train_loss -0.7752 +2024-11-21 20:49:36.893835: val_loss -0.7556 +2024-11-21 20:49:36.893908: Pseudo dice [0.8314] +2024-11-21 20:49:36.893985: Epoch time: 18.45 s +2024-11-21 20:49:37.772923: +2024-11-21 20:49:37.773209: Epoch 1862 +2024-11-21 20:49:37.773324: Current learning rate: 0.00788 +2024-11-21 20:49:56.873086: train_loss -0.7793 +2024-11-21 20:49:56.873353: val_loss -0.7263 +2024-11-21 20:49:56.873430: Pseudo dice [0.8171] +2024-11-21 20:49:56.873507: Epoch time: 19.1 s +2024-11-21 20:49:57.727404: +2024-11-21 20:49:57.727636: Epoch 1863 +2024-11-21 20:49:57.727752: Current learning rate: 0.00788 +2024-11-21 20:50:16.635137: train_loss -0.7805 +2024-11-21 20:50:16.635353: val_loss -0.7271 +2024-11-21 20:50:16.635433: Pseudo dice [0.8055] +2024-11-21 20:50:16.635510: Epoch time: 18.91 s +2024-11-21 20:50:17.536683: +2024-11-21 20:50:17.536886: Epoch 1864 +2024-11-21 20:50:17.537010: Current learning rate: 0.00788 +2024-11-21 20:50:36.278098: train_loss -0.7718 +2024-11-21 20:50:36.278345: val_loss -0.7337 +2024-11-21 20:50:36.278419: Pseudo dice [0.8392] +2024-11-21 20:50:36.278501: Epoch time: 18.74 s +2024-11-21 20:50:37.133463: +2024-11-21 20:50:37.133648: Epoch 1865 +2024-11-21 20:50:37.133756: Current learning rate: 0.00788 +2024-11-21 20:50:56.155189: train_loss -0.7688 +2024-11-21 20:50:56.155404: val_loss -0.7368 +2024-11-21 20:50:56.155480: Pseudo dice [0.8294] +2024-11-21 20:50:56.155555: Epoch time: 19.02 s +2024-11-21 20:50:57.002936: +2024-11-21 20:50:57.003125: Epoch 1866 +2024-11-21 20:50:57.003235: Current learning rate: 0.00787 +2024-11-21 20:51:15.938573: train_loss -0.7761 +2024-11-21 20:51:15.938789: val_loss -0.7471 +2024-11-21 20:51:15.944046: Pseudo dice [0.8293] +2024-11-21 20:51:15.944220: Epoch time: 18.94 s +2024-11-21 20:51:16.814665: +2024-11-21 20:51:16.814866: Epoch 1867 +2024-11-21 20:51:16.814978: Current learning rate: 0.00787 +2024-11-21 20:51:34.872407: train_loss -0.774 +2024-11-21 20:51:34.872620: val_loss -0.7092 +2024-11-21 20:51:34.872693: Pseudo dice [0.7978] +2024-11-21 20:51:34.872771: Epoch time: 18.06 s +2024-11-21 20:51:35.722290: +2024-11-21 20:51:35.722491: Epoch 1868 +2024-11-21 20:51:35.722603: Current learning rate: 0.00787 +2024-11-21 20:51:55.104677: train_loss -0.7691 +2024-11-21 20:51:55.104916: val_loss -0.727 +2024-11-21 20:51:55.104996: Pseudo dice [0.8199] +2024-11-21 20:51:55.105077: Epoch time: 19.38 s +2024-11-21 20:51:56.352895: +2024-11-21 20:51:56.353125: Epoch 1869 +2024-11-21 20:51:56.353241: Current learning rate: 0.00787 +2024-11-21 20:52:15.469589: train_loss -0.7595 +2024-11-21 20:52:15.475015: val_loss -0.747 +2024-11-21 20:52:15.475127: Pseudo dice [0.8283] +2024-11-21 20:52:15.475208: Epoch time: 19.12 s +2024-11-21 20:52:16.563408: +2024-11-21 20:52:16.563631: Epoch 1870 +2024-11-21 20:52:16.563745: Current learning rate: 0.00787 +2024-11-21 20:52:35.340883: train_loss -0.7755 +2024-11-21 20:52:35.343279: val_loss -0.7273 +2024-11-21 20:52:35.343361: Pseudo dice [0.8156] +2024-11-21 20:52:35.343442: Epoch time: 18.78 s +2024-11-21 20:52:36.294210: +2024-11-21 20:52:36.294418: Epoch 1871 +2024-11-21 20:52:36.294533: Current learning rate: 0.00787 +2024-11-21 20:52:54.964229: train_loss -0.7701 +2024-11-21 20:52:54.964468: val_loss -0.713 +2024-11-21 20:52:54.964545: Pseudo dice [0.8135] +2024-11-21 20:52:54.964628: Epoch time: 18.67 s +2024-11-21 20:52:55.815156: +2024-11-21 20:52:55.815384: Epoch 1872 +2024-11-21 20:52:55.815502: Current learning rate: 0.00787 +2024-11-21 20:53:14.573902: train_loss -0.7864 +2024-11-21 20:53:14.574132: val_loss -0.7394 +2024-11-21 20:53:14.574209: Pseudo dice [0.8344] +2024-11-21 20:53:14.574286: Epoch time: 18.76 s +2024-11-21 20:53:15.528702: +2024-11-21 20:53:15.528893: Epoch 1873 +2024-11-21 20:53:15.529009: Current learning rate: 0.00787 +2024-11-21 20:53:34.505851: train_loss -0.7777 +2024-11-21 20:53:34.507357: val_loss -0.7387 +2024-11-21 20:53:34.507452: Pseudo dice [0.8109] +2024-11-21 20:53:34.507531: Epoch time: 18.98 s +2024-11-21 20:53:35.357147: +2024-11-21 20:53:35.357332: Epoch 1874 +2024-11-21 20:53:35.357451: Current learning rate: 0.00786 +2024-11-21 20:53:54.999080: train_loss -0.7656 +2024-11-21 20:53:54.999307: val_loss -0.743 +2024-11-21 20:53:54.999385: Pseudo dice [0.8208] +2024-11-21 20:53:54.999464: Epoch time: 19.64 s +2024-11-21 20:53:55.848268: +2024-11-21 20:53:55.848554: Epoch 1875 +2024-11-21 20:53:55.848664: Current learning rate: 0.00786 +2024-11-21 20:54:14.225791: train_loss -0.7602 +2024-11-21 20:54:14.226060: val_loss -0.724 +2024-11-21 20:54:14.226137: Pseudo dice [0.8358] +2024-11-21 20:54:14.226219: Epoch time: 18.38 s +2024-11-21 20:54:15.116291: +2024-11-21 20:54:15.116518: Epoch 1876 +2024-11-21 20:54:15.116636: Current learning rate: 0.00786 +2024-11-21 20:54:34.332278: train_loss -0.7607 +2024-11-21 20:54:34.332494: val_loss -0.7392 +2024-11-21 20:54:34.332569: Pseudo dice [0.7892] +2024-11-21 20:54:34.332650: Epoch time: 19.22 s +2024-11-21 20:54:35.185593: +2024-11-21 20:54:35.185827: Epoch 1877 +2024-11-21 20:54:35.185946: Current learning rate: 0.00786 +2024-11-21 20:54:53.975363: train_loss -0.7761 +2024-11-21 20:54:53.975580: val_loss -0.7514 +2024-11-21 20:54:53.975652: Pseudo dice [0.8279] +2024-11-21 20:54:53.975844: Epoch time: 18.79 s +2024-11-21 20:54:54.822233: +2024-11-21 20:54:54.822508: Epoch 1878 +2024-11-21 20:54:54.822620: Current learning rate: 0.00786 +2024-11-21 20:55:13.114957: train_loss -0.7704 +2024-11-21 20:55:13.115207: val_loss -0.748 +2024-11-21 20:55:13.115282: Pseudo dice [0.8187] +2024-11-21 20:55:13.115378: Epoch time: 18.29 s +2024-11-21 20:55:13.964452: +2024-11-21 20:55:13.964675: Epoch 1879 +2024-11-21 20:55:13.964787: Current learning rate: 0.00786 +2024-11-21 20:55:32.379392: train_loss -0.7708 +2024-11-21 20:55:32.379625: val_loss -0.715 +2024-11-21 20:55:32.379708: Pseudo dice [0.8116] +2024-11-21 20:55:32.379785: Epoch time: 18.42 s +2024-11-21 20:55:33.277106: +2024-11-21 20:55:33.277391: Epoch 1880 +2024-11-21 20:55:33.277506: Current learning rate: 0.00786 +2024-11-21 20:55:52.197265: train_loss -0.7707 +2024-11-21 20:55:52.197754: val_loss -0.7288 +2024-11-21 20:55:52.197856: Pseudo dice [0.8203] +2024-11-21 20:55:52.197935: Epoch time: 18.92 s +2024-11-21 20:55:53.041433: +2024-11-21 20:55:53.041647: Epoch 1881 +2024-11-21 20:55:53.041762: Current learning rate: 0.00786 +2024-11-21 20:56:11.333634: train_loss -0.7646 +2024-11-21 20:56:11.333882: val_loss -0.724 +2024-11-21 20:56:11.333961: Pseudo dice [0.8344] +2024-11-21 20:56:11.334052: Epoch time: 18.29 s +2024-11-21 20:56:12.183206: +2024-11-21 20:56:12.183424: Epoch 1882 +2024-11-21 20:56:12.183539: Current learning rate: 0.00786 +2024-11-21 20:56:31.137512: train_loss -0.7765 +2024-11-21 20:56:31.137727: val_loss -0.7425 +2024-11-21 20:56:31.137800: Pseudo dice [0.8202] +2024-11-21 20:56:31.137876: Epoch time: 18.96 s +2024-11-21 20:56:31.984857: +2024-11-21 20:56:31.985076: Epoch 1883 +2024-11-21 20:56:31.985186: Current learning rate: 0.00785 +2024-11-21 20:56:49.699611: train_loss -0.7725 +2024-11-21 20:56:49.699830: val_loss -0.734 +2024-11-21 20:56:49.699906: Pseudo dice [0.8021] +2024-11-21 20:56:49.699999: Epoch time: 17.72 s +2024-11-21 20:56:50.587821: +2024-11-21 20:56:50.588058: Epoch 1884 +2024-11-21 20:56:50.588174: Current learning rate: 0.00785 +2024-11-21 20:57:08.578634: train_loss -0.7787 +2024-11-21 20:57:08.578874: val_loss -0.7484 +2024-11-21 20:57:08.578951: Pseudo dice [0.8221] +2024-11-21 20:57:08.579043: Epoch time: 17.99 s +2024-11-21 20:57:09.594146: +2024-11-21 20:57:09.594353: Epoch 1885 +2024-11-21 20:57:09.594467: Current learning rate: 0.00785 +2024-11-21 20:57:27.889353: train_loss -0.7683 +2024-11-21 20:57:27.889603: val_loss -0.7569 +2024-11-21 20:57:27.889679: Pseudo dice [0.8203] +2024-11-21 20:57:27.889770: Epoch time: 18.3 s +2024-11-21 20:57:28.745603: +2024-11-21 20:57:28.745794: Epoch 1886 +2024-11-21 20:57:28.745906: Current learning rate: 0.00785 +2024-11-21 20:57:48.593940: train_loss -0.7743 +2024-11-21 20:57:48.594157: val_loss -0.7474 +2024-11-21 20:57:48.594229: Pseudo dice [0.839] +2024-11-21 20:57:48.594304: Epoch time: 19.85 s +2024-11-21 20:57:49.441701: +2024-11-21 20:57:49.441931: Epoch 1887 +2024-11-21 20:57:49.442052: Current learning rate: 0.00785 +2024-11-21 20:58:08.363178: train_loss -0.7768 +2024-11-21 20:58:08.363398: val_loss -0.7083 +2024-11-21 20:58:08.363471: Pseudo dice [0.8065] +2024-11-21 20:58:08.363547: Epoch time: 18.92 s +2024-11-21 20:58:09.227477: +2024-11-21 20:58:09.227667: Epoch 1888 +2024-11-21 20:58:09.227814: Current learning rate: 0.00785 +2024-11-21 20:58:28.647189: train_loss -0.762 +2024-11-21 20:58:28.647408: val_loss -0.7461 +2024-11-21 20:58:28.647479: Pseudo dice [0.8145] +2024-11-21 20:58:28.647556: Epoch time: 19.42 s +2024-11-21 20:58:29.496271: +2024-11-21 20:58:29.496478: Epoch 1889 +2024-11-21 20:58:29.496592: Current learning rate: 0.00785 +2024-11-21 20:58:47.435734: train_loss -0.7634 +2024-11-21 20:58:47.435970: val_loss -0.7183 +2024-11-21 20:58:47.438243: Pseudo dice [0.8175] +2024-11-21 20:58:47.438338: Epoch time: 17.94 s +2024-11-21 20:58:48.536462: +2024-11-21 20:58:48.536686: Epoch 1890 +2024-11-21 20:58:48.536799: Current learning rate: 0.00785 +2024-11-21 20:59:07.203441: train_loss -0.7501 +2024-11-21 20:59:07.203673: val_loss -0.7173 +2024-11-21 20:59:07.203751: Pseudo dice [0.8094] +2024-11-21 20:59:07.203832: Epoch time: 18.67 s +2024-11-21 20:59:08.054860: +2024-11-21 20:59:08.055084: Epoch 1891 +2024-11-21 20:59:08.055206: Current learning rate: 0.00784 +2024-11-21 20:59:26.912710: train_loss -0.7592 +2024-11-21 20:59:26.912922: val_loss -0.728 +2024-11-21 20:59:26.913004: Pseudo dice [0.8135] +2024-11-21 20:59:26.913080: Epoch time: 18.86 s +2024-11-21 20:59:28.143021: +2024-11-21 20:59:28.143270: Epoch 1892 +2024-11-21 20:59:28.143380: Current learning rate: 0.00784 +2024-11-21 20:59:46.638582: train_loss -0.765 +2024-11-21 20:59:46.638838: val_loss -0.7529 +2024-11-21 20:59:46.638916: Pseudo dice [0.8436] +2024-11-21 20:59:46.651728: Epoch time: 18.5 s +2024-11-21 20:59:47.502378: +2024-11-21 20:59:47.502602: Epoch 1893 +2024-11-21 20:59:47.502720: Current learning rate: 0.00784 +2024-11-21 21:00:05.737462: train_loss -0.7724 +2024-11-21 21:00:05.740152: val_loss -0.7597 +2024-11-21 21:00:05.740256: Pseudo dice [0.8315] +2024-11-21 21:00:05.740333: Epoch time: 18.24 s +2024-11-21 21:00:06.596933: +2024-11-21 21:00:06.597228: Epoch 1894 +2024-11-21 21:00:06.597343: Current learning rate: 0.00784 +2024-11-21 21:00:25.531185: train_loss -0.7581 +2024-11-21 21:00:25.531405: val_loss -0.7243 +2024-11-21 21:00:25.531480: Pseudo dice [0.8189] +2024-11-21 21:00:25.531557: Epoch time: 18.94 s +2024-11-21 21:00:26.380140: +2024-11-21 21:00:26.380396: Epoch 1895 +2024-11-21 21:00:26.380516: Current learning rate: 0.00784 +2024-11-21 21:00:45.551347: train_loss -0.7752 +2024-11-21 21:00:45.551581: val_loss -0.7523 +2024-11-21 21:00:45.551656: Pseudo dice [0.8343] +2024-11-21 21:00:45.551736: Epoch time: 19.17 s +2024-11-21 21:00:46.430327: +2024-11-21 21:00:46.430536: Epoch 1896 +2024-11-21 21:00:46.430665: Current learning rate: 0.00784 +2024-11-21 21:01:04.252584: train_loss -0.7615 +2024-11-21 21:01:04.252843: val_loss -0.7602 +2024-11-21 21:01:04.252920: Pseudo dice [0.8314] +2024-11-21 21:01:04.253007: Epoch time: 17.82 s +2024-11-21 21:01:05.104209: +2024-11-21 21:01:05.104426: Epoch 1897 +2024-11-21 21:01:05.104548: Current learning rate: 0.00784 +2024-11-21 21:01:23.414963: train_loss -0.7698 +2024-11-21 21:01:23.415293: val_loss -0.7381 +2024-11-21 21:01:23.415376: Pseudo dice [0.8214] +2024-11-21 21:01:23.415457: Epoch time: 18.31 s +2024-11-21 21:01:24.267095: +2024-11-21 21:01:24.267316: Epoch 1898 +2024-11-21 21:01:24.267431: Current learning rate: 0.00784 +2024-11-21 21:01:43.139762: train_loss -0.7728 +2024-11-21 21:01:43.139982: val_loss -0.7451 +2024-11-21 21:01:43.140064: Pseudo dice [0.8472] +2024-11-21 21:01:43.140141: Epoch time: 18.87 s +2024-11-21 21:01:43.985930: +2024-11-21 21:01:43.986126: Epoch 1899 +2024-11-21 21:01:43.986241: Current learning rate: 0.00784 +2024-11-21 21:02:02.918379: train_loss -0.7724 +2024-11-21 21:02:02.918621: val_loss -0.7169 +2024-11-21 21:02:02.918696: Pseudo dice [0.7994] +2024-11-21 21:02:02.918778: Epoch time: 18.93 s +2024-11-21 21:02:03.968746: +2024-11-21 21:02:03.968943: Epoch 1900 +2024-11-21 21:02:03.969062: Current learning rate: 0.00783 +2024-11-21 21:02:23.268815: train_loss -0.7624 +2024-11-21 21:02:23.269039: val_loss -0.7411 +2024-11-21 21:02:23.269113: Pseudo dice [0.8155] +2024-11-21 21:02:23.269190: Epoch time: 19.3 s +2024-11-21 21:02:24.145122: +2024-11-21 21:02:24.145332: Epoch 1901 +2024-11-21 21:02:24.145443: Current learning rate: 0.00783 +2024-11-21 21:02:42.310311: train_loss -0.766 +2024-11-21 21:02:42.310532: val_loss -0.7372 +2024-11-21 21:02:42.310606: Pseudo dice [0.8177] +2024-11-21 21:02:42.310682: Epoch time: 18.17 s +2024-11-21 21:02:43.157428: +2024-11-21 21:02:43.157636: Epoch 1902 +2024-11-21 21:02:43.157748: Current learning rate: 0.00783 +2024-11-21 21:03:02.730846: train_loss -0.7747 +2024-11-21 21:03:02.731071: val_loss -0.7644 +2024-11-21 21:03:02.731149: Pseudo dice [0.8288] +2024-11-21 21:03:02.731227: Epoch time: 19.57 s +2024-11-21 21:03:03.697411: +2024-11-21 21:03:03.697622: Epoch 1903 +2024-11-21 21:03:03.697738: Current learning rate: 0.00783 +2024-11-21 21:03:21.972347: train_loss -0.7688 +2024-11-21 21:03:21.972971: val_loss -0.7637 +2024-11-21 21:03:21.973080: Pseudo dice [0.8172] +2024-11-21 21:03:21.973234: Epoch time: 18.28 s +2024-11-21 21:03:22.826256: +2024-11-21 21:03:22.826451: Epoch 1904 +2024-11-21 21:03:22.826564: Current learning rate: 0.00783 +2024-11-21 21:03:40.574799: train_loss -0.7748 +2024-11-21 21:03:40.575032: val_loss -0.7353 +2024-11-21 21:03:40.575109: Pseudo dice [0.824] +2024-11-21 21:03:40.575186: Epoch time: 17.75 s +2024-11-21 21:03:41.580985: +2024-11-21 21:03:41.581200: Epoch 1905 +2024-11-21 21:03:41.581318: Current learning rate: 0.00783 +2024-11-21 21:03:59.353591: train_loss -0.7746 +2024-11-21 21:03:59.353813: val_loss -0.7497 +2024-11-21 21:03:59.353888: Pseudo dice [0.8269] +2024-11-21 21:03:59.353984: Epoch time: 17.77 s +2024-11-21 21:04:00.210647: +2024-11-21 21:04:00.210865: Epoch 1906 +2024-11-21 21:04:00.210995: Current learning rate: 0.00783 +2024-11-21 21:04:18.408483: train_loss -0.7805 +2024-11-21 21:04:18.408725: val_loss -0.7512 +2024-11-21 21:04:18.408804: Pseudo dice [0.8265] +2024-11-21 21:04:18.408885: Epoch time: 18.2 s +2024-11-21 21:04:19.267415: +2024-11-21 21:04:19.267650: Epoch 1907 +2024-11-21 21:04:19.267756: Current learning rate: 0.00783 +2024-11-21 21:04:39.011301: train_loss -0.7762 +2024-11-21 21:04:39.016686: val_loss -0.741 +2024-11-21 21:04:39.016822: Pseudo dice [0.8302] +2024-11-21 21:04:39.016904: Epoch time: 19.74 s +2024-11-21 21:04:39.887578: +2024-11-21 21:04:39.887790: Epoch 1908 +2024-11-21 21:04:39.887902: Current learning rate: 0.00783 +2024-11-21 21:04:59.379781: train_loss -0.7726 +2024-11-21 21:04:59.380001: val_loss -0.7509 +2024-11-21 21:04:59.380080: Pseudo dice [0.8186] +2024-11-21 21:04:59.380157: Epoch time: 19.49 s +2024-11-21 21:05:00.340227: +2024-11-21 21:05:00.340416: Epoch 1909 +2024-11-21 21:05:00.340528: Current learning rate: 0.00782 +2024-11-21 21:05:19.353509: train_loss -0.7778 +2024-11-21 21:05:19.353722: val_loss -0.7493 +2024-11-21 21:05:19.353799: Pseudo dice [0.8447] +2024-11-21 21:05:19.353882: Epoch time: 19.01 s +2024-11-21 21:05:20.202150: +2024-11-21 21:05:20.202368: Epoch 1910 +2024-11-21 21:05:20.202480: Current learning rate: 0.00782 +2024-11-21 21:05:39.666699: train_loss -0.7807 +2024-11-21 21:05:39.666939: val_loss -0.7462 +2024-11-21 21:05:39.667020: Pseudo dice [0.8182] +2024-11-21 21:05:39.667103: Epoch time: 19.47 s +2024-11-21 21:05:40.519823: +2024-11-21 21:05:40.520040: Epoch 1911 +2024-11-21 21:05:40.520153: Current learning rate: 0.00782 +2024-11-21 21:05:58.834760: train_loss -0.7786 +2024-11-21 21:05:58.834977: val_loss -0.7565 +2024-11-21 21:05:58.835064: Pseudo dice [0.8139] +2024-11-21 21:05:58.835143: Epoch time: 18.32 s +2024-11-21 21:05:59.683107: +2024-11-21 21:05:59.683317: Epoch 1912 +2024-11-21 21:05:59.683425: Current learning rate: 0.00782 +2024-11-21 21:06:20.324342: train_loss -0.7739 +2024-11-21 21:06:20.324559: val_loss -0.7392 +2024-11-21 21:06:20.324629: Pseudo dice [0.8309] +2024-11-21 21:06:20.324705: Epoch time: 20.64 s +2024-11-21 21:06:21.236996: +2024-11-21 21:06:21.237216: Epoch 1913 +2024-11-21 21:06:21.237340: Current learning rate: 0.00782 +2024-11-21 21:06:39.888143: train_loss -0.7581 +2024-11-21 21:06:39.888461: val_loss -0.7282 +2024-11-21 21:06:39.888542: Pseudo dice [0.8159] +2024-11-21 21:06:39.888631: Epoch time: 18.65 s +2024-11-21 21:06:41.108222: +2024-11-21 21:06:41.108462: Epoch 1914 +2024-11-21 21:06:41.108576: Current learning rate: 0.00782 +2024-11-21 21:07:00.397969: train_loss -0.7665 +2024-11-21 21:07:00.398224: val_loss -0.729 +2024-11-21 21:07:00.398308: Pseudo dice [0.8171] +2024-11-21 21:07:00.398384: Epoch time: 19.29 s +2024-11-21 21:07:01.252329: +2024-11-21 21:07:01.252536: Epoch 1915 +2024-11-21 21:07:01.252647: Current learning rate: 0.00782 +2024-11-21 21:07:19.655911: train_loss -0.7744 +2024-11-21 21:07:19.656145: val_loss -0.7443 +2024-11-21 21:07:19.656224: Pseudo dice [0.8287] +2024-11-21 21:07:19.656306: Epoch time: 18.4 s +2024-11-21 21:07:20.594226: +2024-11-21 21:07:20.594420: Epoch 1916 +2024-11-21 21:07:20.594530: Current learning rate: 0.00782 +2024-11-21 21:07:40.905931: train_loss -0.7737 +2024-11-21 21:07:40.906142: val_loss -0.7614 +2024-11-21 21:07:40.906216: Pseudo dice [0.8478] +2024-11-21 21:07:40.906297: Epoch time: 20.31 s +2024-11-21 21:07:41.791047: +2024-11-21 21:07:41.791264: Epoch 1917 +2024-11-21 21:07:41.791380: Current learning rate: 0.00781 +2024-11-21 21:08:00.615711: train_loss -0.7717 +2024-11-21 21:08:00.615962: val_loss -0.7377 +2024-11-21 21:08:00.616048: Pseudo dice [0.8049] +2024-11-21 21:08:00.616130: Epoch time: 18.83 s +2024-11-21 21:08:01.686166: +2024-11-21 21:08:01.686381: Epoch 1918 +2024-11-21 21:08:01.686500: Current learning rate: 0.00781 +2024-11-21 21:08:20.588786: train_loss -0.753 +2024-11-21 21:08:20.589065: val_loss -0.7273 +2024-11-21 21:08:20.589142: Pseudo dice [0.8161] +2024-11-21 21:08:20.589217: Epoch time: 18.9 s +2024-11-21 21:08:21.474897: +2024-11-21 21:08:21.475102: Epoch 1919 +2024-11-21 21:08:21.475217: Current learning rate: 0.00781 +2024-11-21 21:08:39.570373: train_loss -0.7743 +2024-11-21 21:08:39.570585: val_loss -0.7506 +2024-11-21 21:08:39.570661: Pseudo dice [0.8132] +2024-11-21 21:08:39.570740: Epoch time: 18.1 s +2024-11-21 21:08:40.531332: +2024-11-21 21:08:40.531546: Epoch 1920 +2024-11-21 21:08:40.531661: Current learning rate: 0.00781 +2024-11-21 21:08:59.710485: train_loss -0.7656 +2024-11-21 21:08:59.710702: val_loss -0.7311 +2024-11-21 21:08:59.710777: Pseudo dice [0.8315] +2024-11-21 21:08:59.710855: Epoch time: 19.18 s +2024-11-21 21:09:00.574339: +2024-11-21 21:09:00.574540: Epoch 1921 +2024-11-21 21:09:00.574654: Current learning rate: 0.00781 +2024-11-21 21:09:20.209419: train_loss -0.7686 +2024-11-21 21:09:20.209717: val_loss -0.7449 +2024-11-21 21:09:20.209794: Pseudo dice [0.8134] +2024-11-21 21:09:20.209874: Epoch time: 19.64 s +2024-11-21 21:09:21.170516: +2024-11-21 21:09:21.170715: Epoch 1922 +2024-11-21 21:09:21.170826: Current learning rate: 0.00781 +2024-11-21 21:09:39.965953: train_loss -0.7715 +2024-11-21 21:09:39.966174: val_loss -0.7248 +2024-11-21 21:09:39.966249: Pseudo dice [0.807] +2024-11-21 21:09:39.966325: Epoch time: 18.8 s +2024-11-21 21:09:40.825689: +2024-11-21 21:09:40.825888: Epoch 1923 +2024-11-21 21:09:40.826007: Current learning rate: 0.00781 +2024-11-21 21:09:58.159881: train_loss -0.7838 +2024-11-21 21:09:58.161886: val_loss -0.7568 +2024-11-21 21:09:58.162004: Pseudo dice [0.8221] +2024-11-21 21:09:58.164232: Epoch time: 17.33 s +2024-11-21 21:09:59.019524: +2024-11-21 21:09:59.019732: Epoch 1924 +2024-11-21 21:09:59.019851: Current learning rate: 0.00781 +2024-11-21 21:10:18.321774: train_loss -0.7797 +2024-11-21 21:10:18.322003: val_loss -0.7273 +2024-11-21 21:10:18.322072: Pseudo dice [0.8253] +2024-11-21 21:10:18.322158: Epoch time: 19.3 s +2024-11-21 21:10:19.189399: +2024-11-21 21:10:19.189623: Epoch 1925 +2024-11-21 21:10:19.189743: Current learning rate: 0.00781 +2024-11-21 21:10:39.045185: train_loss -0.7755 +2024-11-21 21:10:39.045825: val_loss -0.738 +2024-11-21 21:10:39.045902: Pseudo dice [0.8158] +2024-11-21 21:10:39.045979: Epoch time: 19.86 s +2024-11-21 21:10:40.285599: +2024-11-21 21:10:40.285818: Epoch 1926 +2024-11-21 21:10:40.285931: Current learning rate: 0.0078 +2024-11-21 21:10:59.276112: train_loss -0.784 +2024-11-21 21:10:59.276347: val_loss -0.7275 +2024-11-21 21:10:59.276431: Pseudo dice [0.8187] +2024-11-21 21:10:59.276510: Epoch time: 18.99 s +2024-11-21 21:11:00.129266: +2024-11-21 21:11:00.129474: Epoch 1927 +2024-11-21 21:11:00.129583: Current learning rate: 0.0078 +2024-11-21 21:11:18.210787: train_loss -0.7805 +2024-11-21 21:11:18.215633: val_loss -0.7453 +2024-11-21 21:11:18.215759: Pseudo dice [0.8085] +2024-11-21 21:11:18.215849: Epoch time: 18.08 s +2024-11-21 21:11:19.075028: +2024-11-21 21:11:19.075403: Epoch 1928 +2024-11-21 21:11:19.075520: Current learning rate: 0.0078 +2024-11-21 21:11:37.249907: train_loss -0.7789 +2024-11-21 21:11:37.250126: val_loss -0.7349 +2024-11-21 21:11:37.250201: Pseudo dice [0.8106] +2024-11-21 21:11:37.250279: Epoch time: 18.18 s +2024-11-21 21:11:38.104772: +2024-11-21 21:11:38.105022: Epoch 1929 +2024-11-21 21:11:38.105138: Current learning rate: 0.0078 +2024-11-21 21:11:57.725516: train_loss -0.7685 +2024-11-21 21:11:57.731013: val_loss -0.7002 +2024-11-21 21:11:57.731285: Pseudo dice [0.7838] +2024-11-21 21:11:57.731375: Epoch time: 19.62 s +2024-11-21 21:11:58.598970: +2024-11-21 21:11:58.599205: Epoch 1930 +2024-11-21 21:11:58.599322: Current learning rate: 0.0078 +2024-11-21 21:12:17.374676: train_loss -0.7604 +2024-11-21 21:12:17.374885: val_loss -0.7278 +2024-11-21 21:12:17.374957: Pseudo dice [0.7981] +2024-11-21 21:12:17.393017: Epoch time: 18.78 s +2024-11-21 21:12:18.250614: +2024-11-21 21:12:18.250827: Epoch 1931 +2024-11-21 21:12:18.250943: Current learning rate: 0.0078 +2024-11-21 21:12:37.798790: train_loss -0.75 +2024-11-21 21:12:37.799040: val_loss -0.7235 +2024-11-21 21:12:37.799117: Pseudo dice [0.8199] +2024-11-21 21:12:37.799202: Epoch time: 19.55 s +2024-11-21 21:12:38.657497: +2024-11-21 21:12:38.657701: Epoch 1932 +2024-11-21 21:12:38.657815: Current learning rate: 0.0078 +2024-11-21 21:12:57.701685: train_loss -0.7694 +2024-11-21 21:12:57.701900: val_loss -0.7374 +2024-11-21 21:12:57.701975: Pseudo dice [0.8208] +2024-11-21 21:12:57.702058: Epoch time: 19.04 s +2024-11-21 21:12:58.556868: +2024-11-21 21:12:58.557082: Epoch 1933 +2024-11-21 21:12:58.557202: Current learning rate: 0.0078 +2024-11-21 21:13:16.680255: train_loss -0.7606 +2024-11-21 21:13:16.680480: val_loss -0.7229 +2024-11-21 21:13:16.680554: Pseudo dice [0.805] +2024-11-21 21:13:16.680630: Epoch time: 18.12 s +2024-11-21 21:13:17.534165: +2024-11-21 21:13:17.534379: Epoch 1934 +2024-11-21 21:13:17.534504: Current learning rate: 0.0078 +2024-11-21 21:13:37.458020: train_loss -0.7639 +2024-11-21 21:13:37.464128: val_loss -0.7519 +2024-11-21 21:13:37.464252: Pseudo dice [0.803] +2024-11-21 21:13:37.464341: Epoch time: 19.92 s +2024-11-21 21:13:38.341945: +2024-11-21 21:13:38.342182: Epoch 1935 +2024-11-21 21:13:38.342297: Current learning rate: 0.00779 +2024-11-21 21:13:57.357268: train_loss -0.778 +2024-11-21 21:13:57.357490: val_loss -0.7547 +2024-11-21 21:13:57.357569: Pseudo dice [0.8191] +2024-11-21 21:13:57.357655: Epoch time: 19.02 s +2024-11-21 21:13:58.213752: +2024-11-21 21:13:58.213950: Epoch 1936 +2024-11-21 21:13:58.214070: Current learning rate: 0.00779 +2024-11-21 21:14:17.286407: train_loss -0.7685 +2024-11-21 21:14:17.286633: val_loss -0.7233 +2024-11-21 21:14:17.286705: Pseudo dice [0.8223] +2024-11-21 21:14:17.286783: Epoch time: 19.07 s +2024-11-21 21:14:18.555035: +2024-11-21 21:14:18.555283: Epoch 1937 +2024-11-21 21:14:18.555406: Current learning rate: 0.00779 +2024-11-21 21:14:38.011508: train_loss -0.7716 +2024-11-21 21:14:38.011726: val_loss -0.7092 +2024-11-21 21:14:38.011828: Pseudo dice [0.8101] +2024-11-21 21:14:38.011918: Epoch time: 19.46 s +2024-11-21 21:14:38.866860: +2024-11-21 21:14:38.867109: Epoch 1938 +2024-11-21 21:14:38.867227: Current learning rate: 0.00779 +2024-11-21 21:14:57.730799: train_loss -0.7634 +2024-11-21 21:14:57.731051: val_loss -0.7343 +2024-11-21 21:14:57.731127: Pseudo dice [0.8325] +2024-11-21 21:14:57.731209: Epoch time: 18.86 s +2024-11-21 21:14:58.587806: +2024-11-21 21:14:58.588027: Epoch 1939 +2024-11-21 21:14:58.588137: Current learning rate: 0.00779 +2024-11-21 21:15:16.769372: train_loss -0.7684 +2024-11-21 21:15:16.771728: val_loss -0.7386 +2024-11-21 21:15:16.771852: Pseudo dice [0.8431] +2024-11-21 21:15:16.771931: Epoch time: 18.18 s +2024-11-21 21:15:17.667410: +2024-11-21 21:15:17.667778: Epoch 1940 +2024-11-21 21:15:17.667899: Current learning rate: 0.00779 +2024-11-21 21:15:37.030034: train_loss -0.7769 +2024-11-21 21:15:37.030252: val_loss -0.7387 +2024-11-21 21:15:37.030327: Pseudo dice [0.8119] +2024-11-21 21:15:37.030401: Epoch time: 19.36 s +2024-11-21 21:15:37.892010: +2024-11-21 21:15:37.892211: Epoch 1941 +2024-11-21 21:15:37.892329: Current learning rate: 0.00779 +2024-11-21 21:15:57.285791: train_loss -0.7775 +2024-11-21 21:15:57.287645: val_loss -0.7407 +2024-11-21 21:15:57.287750: Pseudo dice [0.8096] +2024-11-21 21:15:57.287840: Epoch time: 19.39 s +2024-11-21 21:15:58.242381: +2024-11-21 21:15:58.242604: Epoch 1942 +2024-11-21 21:15:58.242719: Current learning rate: 0.00779 +2024-11-21 21:16:17.263716: train_loss -0.7634 +2024-11-21 21:16:17.263932: val_loss -0.6933 +2024-11-21 21:16:17.264017: Pseudo dice [0.8069] +2024-11-21 21:16:17.264105: Epoch time: 19.02 s +2024-11-21 21:16:18.119815: +2024-11-21 21:16:18.120114: Epoch 1943 +2024-11-21 21:16:18.120230: Current learning rate: 0.00778 +2024-11-21 21:16:37.205511: train_loss -0.7699 +2024-11-21 21:16:37.213441: val_loss -0.7468 +2024-11-21 21:16:37.213578: Pseudo dice [0.8162] +2024-11-21 21:16:37.213664: Epoch time: 19.09 s +2024-11-21 21:16:38.075747: +2024-11-21 21:16:38.075947: Epoch 1944 +2024-11-21 21:16:38.076066: Current learning rate: 0.00778 +2024-11-21 21:16:57.448586: train_loss -0.7709 +2024-11-21 21:16:57.448851: val_loss -0.7337 +2024-11-21 21:16:57.448922: Pseudo dice [0.8198] +2024-11-21 21:16:57.449006: Epoch time: 19.37 s +2024-11-21 21:16:58.332395: +2024-11-21 21:16:58.332587: Epoch 1945 +2024-11-21 21:16:58.332701: Current learning rate: 0.00778 +2024-11-21 21:17:16.602077: train_loss -0.775 +2024-11-21 21:17:16.602336: val_loss -0.7443 +2024-11-21 21:17:16.602413: Pseudo dice [0.8213] +2024-11-21 21:17:16.602503: Epoch time: 18.27 s +2024-11-21 21:17:17.465926: +2024-11-21 21:17:17.466179: Epoch 1946 +2024-11-21 21:17:17.466289: Current learning rate: 0.00778 +2024-11-21 21:17:36.678006: train_loss -0.7644 +2024-11-21 21:17:36.678216: val_loss -0.7473 +2024-11-21 21:17:36.678289: Pseudo dice [0.8275] +2024-11-21 21:17:36.678387: Epoch time: 19.21 s +2024-11-21 21:17:37.530811: +2024-11-21 21:17:37.531018: Epoch 1947 +2024-11-21 21:17:37.531132: Current learning rate: 0.00778 +2024-11-21 21:17:56.223685: train_loss -0.7678 +2024-11-21 21:17:56.223922: val_loss -0.7086 +2024-11-21 21:17:56.229228: Pseudo dice [0.8012] +2024-11-21 21:17:56.229321: Epoch time: 18.69 s +2024-11-21 21:17:57.119098: +2024-11-21 21:17:57.119371: Epoch 1948 +2024-11-21 21:17:57.119486: Current learning rate: 0.00778 +2024-11-21 21:18:16.992450: train_loss -0.7682 +2024-11-21 21:18:16.992674: val_loss -0.7167 +2024-11-21 21:18:16.992751: Pseudo dice [0.8341] +2024-11-21 21:18:16.992867: Epoch time: 19.87 s +2024-11-21 21:18:18.230523: +2024-11-21 21:18:18.230832: Epoch 1949 +2024-11-21 21:18:18.230947: Current learning rate: 0.00778 +2024-11-21 21:18:36.331944: train_loss -0.764 +2024-11-21 21:18:36.332212: val_loss -0.7185 +2024-11-21 21:18:36.332290: Pseudo dice [0.8111] +2024-11-21 21:18:36.332370: Epoch time: 18.1 s +2024-11-21 21:18:37.385722: +2024-11-21 21:18:37.385945: Epoch 1950 +2024-11-21 21:18:37.386068: Current learning rate: 0.00778 +2024-11-21 21:18:56.112219: train_loss -0.7719 +2024-11-21 21:18:56.112442: val_loss -0.7507 +2024-11-21 21:18:56.112521: Pseudo dice [0.8179] +2024-11-21 21:18:56.112600: Epoch time: 18.73 s +2024-11-21 21:18:57.044344: +2024-11-21 21:18:57.044547: Epoch 1951 +2024-11-21 21:18:57.044657: Current learning rate: 0.00778 +2024-11-21 21:19:15.119529: train_loss -0.7751 +2024-11-21 21:19:15.119778: val_loss -0.707 +2024-11-21 21:19:15.119852: Pseudo dice [0.79] +2024-11-21 21:19:15.119931: Epoch time: 18.08 s +2024-11-21 21:19:16.006033: +2024-11-21 21:19:16.006239: Epoch 1952 +2024-11-21 21:19:16.006350: Current learning rate: 0.00777 +2024-11-21 21:19:34.182968: train_loss -0.7606 +2024-11-21 21:19:34.183229: val_loss -0.7144 +2024-11-21 21:19:34.183303: Pseudo dice [0.8083] +2024-11-21 21:19:34.183384: Epoch time: 18.18 s +2024-11-21 21:19:35.038735: +2024-11-21 21:19:35.038936: Epoch 1953 +2024-11-21 21:19:35.039062: Current learning rate: 0.00777 +2024-11-21 21:19:53.466342: train_loss -0.7633 +2024-11-21 21:19:53.466552: val_loss -0.736 +2024-11-21 21:19:53.466627: Pseudo dice [0.8257] +2024-11-21 21:19:53.466702: Epoch time: 18.43 s +2024-11-21 21:19:54.325921: +2024-11-21 21:19:54.326125: Epoch 1954 +2024-11-21 21:19:54.326240: Current learning rate: 0.00777 +2024-11-21 21:20:13.380525: train_loss -0.7724 +2024-11-21 21:20:13.380749: val_loss -0.7545 +2024-11-21 21:20:13.380827: Pseudo dice [0.8147] +2024-11-21 21:20:13.380906: Epoch time: 19.06 s +2024-11-21 21:20:14.235420: +2024-11-21 21:20:14.235660: Epoch 1955 +2024-11-21 21:20:14.235774: Current learning rate: 0.00777 +2024-11-21 21:20:32.796563: train_loss -0.7699 +2024-11-21 21:20:32.796783: val_loss -0.7357 +2024-11-21 21:20:32.797035: Pseudo dice [0.8104] +2024-11-21 21:20:32.797117: Epoch time: 18.56 s +2024-11-21 21:20:33.658926: +2024-11-21 21:20:33.659125: Epoch 1956 +2024-11-21 21:20:33.659245: Current learning rate: 0.00777 +2024-11-21 21:20:51.877636: train_loss -0.7679 +2024-11-21 21:20:51.877884: val_loss -0.727 +2024-11-21 21:20:51.877959: Pseudo dice [0.7884] +2024-11-21 21:20:51.878047: Epoch time: 18.22 s +2024-11-21 21:20:52.737414: +2024-11-21 21:20:52.737601: Epoch 1957 +2024-11-21 21:20:52.737713: Current learning rate: 0.00777 +2024-11-21 21:21:11.389697: train_loss -0.761 +2024-11-21 21:21:11.389916: val_loss -0.7386 +2024-11-21 21:21:11.389989: Pseudo dice [0.8322] +2024-11-21 21:21:11.390077: Epoch time: 18.65 s +2024-11-21 21:21:12.247144: +2024-11-21 21:21:12.247559: Epoch 1958 +2024-11-21 21:21:12.247675: Current learning rate: 0.00777 +2024-11-21 21:21:30.511335: train_loss -0.7663 +2024-11-21 21:21:30.511556: val_loss -0.7509 +2024-11-21 21:21:30.511635: Pseudo dice [0.8133] +2024-11-21 21:21:30.511713: Epoch time: 18.26 s +2024-11-21 21:21:31.375986: +2024-11-21 21:21:31.376175: Epoch 1959 +2024-11-21 21:21:31.376284: Current learning rate: 0.00777 +2024-11-21 21:21:49.766224: train_loss -0.7701 +2024-11-21 21:21:49.766478: val_loss -0.7178 +2024-11-21 21:21:49.766557: Pseudo dice [0.8124] +2024-11-21 21:21:49.766642: Epoch time: 18.39 s +2024-11-21 21:21:51.017534: +2024-11-21 21:21:51.017752: Epoch 1960 +2024-11-21 21:21:51.017867: Current learning rate: 0.00777 +2024-11-21 21:22:09.824339: train_loss -0.7605 +2024-11-21 21:22:09.824559: val_loss -0.6975 +2024-11-21 21:22:09.824652: Pseudo dice [0.7869] +2024-11-21 21:22:09.824732: Epoch time: 18.81 s +2024-11-21 21:22:10.682875: +2024-11-21 21:22:10.683194: Epoch 1961 +2024-11-21 21:22:10.683308: Current learning rate: 0.00776 +2024-11-21 21:22:29.517197: train_loss -0.7605 +2024-11-21 21:22:29.517419: val_loss -0.7105 +2024-11-21 21:22:29.517494: Pseudo dice [0.7852] +2024-11-21 21:22:29.517570: Epoch time: 18.84 s +2024-11-21 21:22:30.379044: +2024-11-21 21:22:30.379270: Epoch 1962 +2024-11-21 21:22:30.379398: Current learning rate: 0.00776 +2024-11-21 21:22:49.173312: train_loss -0.7709 +2024-11-21 21:22:49.173542: val_loss -0.7407 +2024-11-21 21:22:49.173620: Pseudo dice [0.8326] +2024-11-21 21:22:49.173698: Epoch time: 18.8 s +2024-11-21 21:22:50.038922: +2024-11-21 21:22:50.039207: Epoch 1963 +2024-11-21 21:22:50.039329: Current learning rate: 0.00776 +2024-11-21 21:23:08.008334: train_loss -0.7687 +2024-11-21 21:23:08.008604: val_loss -0.7519 +2024-11-21 21:23:08.008679: Pseudo dice [0.829] +2024-11-21 21:23:08.008760: Epoch time: 17.97 s +2024-11-21 21:23:08.878665: +2024-11-21 21:23:08.878857: Epoch 1964 +2024-11-21 21:23:08.878964: Current learning rate: 0.00776 +2024-11-21 21:23:28.068654: train_loss -0.7821 +2024-11-21 21:23:28.068883: val_loss -0.746 +2024-11-21 21:23:28.068968: Pseudo dice [0.8312] +2024-11-21 21:23:28.069054: Epoch time: 19.19 s +2024-11-21 21:23:28.929811: +2024-11-21 21:23:28.930021: Epoch 1965 +2024-11-21 21:23:28.930134: Current learning rate: 0.00776 +2024-11-21 21:23:47.043807: train_loss -0.7771 +2024-11-21 21:23:47.044038: val_loss -0.7419 +2024-11-21 21:23:47.044114: Pseudo dice [0.8286] +2024-11-21 21:23:47.044192: Epoch time: 18.11 s +2024-11-21 21:23:47.900458: +2024-11-21 21:23:47.900676: Epoch 1966 +2024-11-21 21:23:47.900789: Current learning rate: 0.00776 +2024-11-21 21:24:06.377912: train_loss -0.7766 +2024-11-21 21:24:06.380275: val_loss -0.7442 +2024-11-21 21:24:06.380361: Pseudo dice [0.8169] +2024-11-21 21:24:06.380447: Epoch time: 18.48 s +2024-11-21 21:24:07.413246: +2024-11-21 21:24:07.413481: Epoch 1967 +2024-11-21 21:24:07.413592: Current learning rate: 0.00776 +2024-11-21 21:24:26.563012: train_loss -0.7725 +2024-11-21 21:24:26.563251: val_loss -0.7305 +2024-11-21 21:24:26.563333: Pseudo dice [0.8356] +2024-11-21 21:24:26.563424: Epoch time: 19.15 s +2024-11-21 21:24:27.585193: +2024-11-21 21:24:27.585374: Epoch 1968 +2024-11-21 21:24:27.585481: Current learning rate: 0.00776 +2024-11-21 21:24:45.508516: train_loss -0.7654 +2024-11-21 21:24:45.508745: val_loss -0.7432 +2024-11-21 21:24:45.508821: Pseudo dice [0.8314] +2024-11-21 21:24:45.508899: Epoch time: 17.92 s +2024-11-21 21:24:46.360828: +2024-11-21 21:24:46.361092: Epoch 1969 +2024-11-21 21:24:46.361208: Current learning rate: 0.00775 +2024-11-21 21:25:05.623342: train_loss -0.7864 +2024-11-21 21:25:05.623548: val_loss -0.7368 +2024-11-21 21:25:05.623622: Pseudo dice [0.819] +2024-11-21 21:25:05.623701: Epoch time: 19.26 s +2024-11-21 21:25:06.483983: +2024-11-21 21:25:06.484188: Epoch 1970 +2024-11-21 21:25:06.484300: Current learning rate: 0.00775 +2024-11-21 21:25:25.706483: train_loss -0.7734 +2024-11-21 21:25:25.706720: val_loss -0.758 +2024-11-21 21:25:25.706796: Pseudo dice [0.8327] +2024-11-21 21:25:25.706874: Epoch time: 19.22 s +2024-11-21 21:25:26.961197: +2024-11-21 21:25:26.961407: Epoch 1971 +2024-11-21 21:25:26.961519: Current learning rate: 0.00775 +2024-11-21 21:25:46.259797: train_loss -0.7767 +2024-11-21 21:25:46.260045: val_loss -0.7616 +2024-11-21 21:25:46.260118: Pseudo dice [0.8311] +2024-11-21 21:25:46.260195: Epoch time: 19.3 s +2024-11-21 21:25:47.143366: +2024-11-21 21:25:47.143584: Epoch 1972 +2024-11-21 21:25:47.143696: Current learning rate: 0.00775 +2024-11-21 21:26:05.689167: train_loss -0.776 +2024-11-21 21:26:05.689444: val_loss -0.733 +2024-11-21 21:26:05.689527: Pseudo dice [0.8279] +2024-11-21 21:26:05.689607: Epoch time: 18.55 s +2024-11-21 21:26:06.544963: +2024-11-21 21:26:06.545199: Epoch 1973 +2024-11-21 21:26:06.545312: Current learning rate: 0.00775 +2024-11-21 21:26:25.897336: train_loss -0.7637 +2024-11-21 21:26:25.897584: val_loss -0.7489 +2024-11-21 21:26:25.897657: Pseudo dice [0.8096] +2024-11-21 21:26:25.897742: Epoch time: 19.35 s +2024-11-21 21:26:26.761051: +2024-11-21 21:26:26.761294: Epoch 1974 +2024-11-21 21:26:26.761422: Current learning rate: 0.00775 +2024-11-21 21:26:44.461667: train_loss -0.7842 +2024-11-21 21:26:44.461880: val_loss -0.7333 +2024-11-21 21:26:44.461955: Pseudo dice [0.8192] +2024-11-21 21:26:44.462035: Epoch time: 17.7 s +2024-11-21 21:26:45.443593: +2024-11-21 21:26:45.443824: Epoch 1975 +2024-11-21 21:26:45.443937: Current learning rate: 0.00775 +2024-11-21 21:27:04.504468: train_loss -0.7731 +2024-11-21 21:27:04.504981: val_loss -0.7628 +2024-11-21 21:27:04.505104: Pseudo dice [0.8361] +2024-11-21 21:27:04.505186: Epoch time: 19.06 s +2024-11-21 21:27:05.359624: +2024-11-21 21:27:05.359817: Epoch 1976 +2024-11-21 21:27:05.359926: Current learning rate: 0.00775 +2024-11-21 21:27:23.780764: train_loss -0.7639 +2024-11-21 21:27:23.780986: val_loss -0.7411 +2024-11-21 21:27:23.781067: Pseudo dice [0.8295] +2024-11-21 21:27:23.781144: Epoch time: 18.42 s +2024-11-21 21:27:24.681668: +2024-11-21 21:27:24.681877: Epoch 1977 +2024-11-21 21:27:24.682003: Current learning rate: 0.00775 +2024-11-21 21:27:43.160908: train_loss -0.7673 +2024-11-21 21:27:43.161199: val_loss -0.7601 +2024-11-21 21:27:43.161275: Pseudo dice [0.8153] +2024-11-21 21:27:43.161370: Epoch time: 18.48 s +2024-11-21 21:27:44.050604: +2024-11-21 21:27:44.050797: Epoch 1978 +2024-11-21 21:27:44.050907: Current learning rate: 0.00774 +2024-11-21 21:28:02.312675: train_loss -0.7738 +2024-11-21 21:28:02.312886: val_loss -0.7344 +2024-11-21 21:28:02.312962: Pseudo dice [0.8204] +2024-11-21 21:28:02.313043: Epoch time: 18.26 s +2024-11-21 21:28:03.172940: +2024-11-21 21:28:03.173287: Epoch 1979 +2024-11-21 21:28:03.173405: Current learning rate: 0.00774 +2024-11-21 21:28:22.268294: train_loss -0.7781 +2024-11-21 21:28:22.268508: val_loss -0.7423 +2024-11-21 21:28:22.268581: Pseudo dice [0.8303] +2024-11-21 21:28:22.268656: Epoch time: 19.1 s +2024-11-21 21:28:23.127410: +2024-11-21 21:28:23.127640: Epoch 1980 +2024-11-21 21:28:23.127759: Current learning rate: 0.00774 +2024-11-21 21:28:42.419481: train_loss -0.7694 +2024-11-21 21:28:42.419688: val_loss -0.744 +2024-11-21 21:28:42.419762: Pseudo dice [0.8139] +2024-11-21 21:28:42.419839: Epoch time: 19.29 s +2024-11-21 21:28:43.380934: +2024-11-21 21:28:43.381137: Epoch 1981 +2024-11-21 21:28:43.381248: Current learning rate: 0.00774 +2024-11-21 21:29:00.647016: train_loss -0.7646 +2024-11-21 21:29:00.647310: val_loss -0.7583 +2024-11-21 21:29:00.649388: Pseudo dice [0.8448] +2024-11-21 21:29:00.649525: Epoch time: 17.27 s +2024-11-21 21:29:01.607893: +2024-11-21 21:29:01.608303: Epoch 1982 +2024-11-21 21:29:01.608435: Current learning rate: 0.00774 +2024-11-21 21:29:19.382981: train_loss -0.7696 +2024-11-21 21:29:19.383205: val_loss -0.7565 +2024-11-21 21:29:19.383278: Pseudo dice [0.8418] +2024-11-21 21:29:19.383352: Epoch time: 17.78 s +2024-11-21 21:29:20.660470: +2024-11-21 21:29:20.660910: Epoch 1983 +2024-11-21 21:29:20.661032: Current learning rate: 0.00774 +2024-11-21 21:29:39.131074: train_loss -0.7657 +2024-11-21 21:29:39.131324: val_loss -0.7457 +2024-11-21 21:29:39.131402: Pseudo dice [0.8305] +2024-11-21 21:29:39.131492: Epoch time: 18.47 s +2024-11-21 21:29:40.032195: +2024-11-21 21:29:40.032423: Epoch 1984 +2024-11-21 21:29:40.032538: Current learning rate: 0.00774 +2024-11-21 21:29:59.002241: train_loss -0.7698 +2024-11-21 21:29:59.002471: val_loss -0.7552 +2024-11-21 21:29:59.002552: Pseudo dice [0.8378] +2024-11-21 21:29:59.002627: Epoch time: 18.97 s +2024-11-21 21:29:59.002687: Yayy! New best EMA pseudo Dice: 0.8276 +2024-11-21 21:30:00.058570: +2024-11-21 21:30:00.058917: Epoch 1985 +2024-11-21 21:30:00.059039: Current learning rate: 0.00774 +2024-11-21 21:30:18.160687: train_loss -0.7726 +2024-11-21 21:30:18.160915: val_loss -0.7388 +2024-11-21 21:30:18.160989: Pseudo dice [0.8153] +2024-11-21 21:30:18.161075: Epoch time: 18.1 s +2024-11-21 21:30:19.090275: +2024-11-21 21:30:19.090478: Epoch 1986 +2024-11-21 21:30:19.090597: Current learning rate: 0.00774 +2024-11-21 21:30:38.570224: train_loss -0.7769 +2024-11-21 21:30:38.570445: val_loss -0.7389 +2024-11-21 21:30:38.570525: Pseudo dice [0.8206] +2024-11-21 21:30:38.570606: Epoch time: 19.48 s +2024-11-21 21:30:39.426723: +2024-11-21 21:30:39.426938: Epoch 1987 +2024-11-21 21:30:39.427055: Current learning rate: 0.00773 +2024-11-21 21:30:56.954485: train_loss -0.7605 +2024-11-21 21:30:56.954803: val_loss -0.7362 +2024-11-21 21:30:56.954887: Pseudo dice [0.8218] +2024-11-21 21:30:56.954971: Epoch time: 17.53 s +2024-11-21 21:30:57.813507: +2024-11-21 21:30:57.813695: Epoch 1988 +2024-11-21 21:30:57.813806: Current learning rate: 0.00773 +2024-11-21 21:31:16.031519: train_loss -0.7596 +2024-11-21 21:31:16.031731: val_loss -0.74 +2024-11-21 21:31:16.031805: Pseudo dice [0.8091] +2024-11-21 21:31:16.031880: Epoch time: 18.22 s +2024-11-21 21:31:16.887983: +2024-11-21 21:31:16.888191: Epoch 1989 +2024-11-21 21:31:16.888304: Current learning rate: 0.00773 +2024-11-21 21:31:36.631247: train_loss -0.7705 +2024-11-21 21:31:36.631459: val_loss -0.7553 +2024-11-21 21:31:36.631534: Pseudo dice [0.8148] +2024-11-21 21:31:36.631608: Epoch time: 19.74 s +2024-11-21 21:31:37.495973: +2024-11-21 21:31:37.496191: Epoch 1990 +2024-11-21 21:31:37.496297: Current learning rate: 0.00773 +2024-11-21 21:31:56.192729: train_loss -0.7666 +2024-11-21 21:31:56.192986: val_loss -0.7135 +2024-11-21 21:31:56.193075: Pseudo dice [0.7929] +2024-11-21 21:31:56.193209: Epoch time: 18.7 s +2024-11-21 21:31:57.058756: +2024-11-21 21:31:57.058972: Epoch 1991 +2024-11-21 21:31:57.059090: Current learning rate: 0.00773 +2024-11-21 21:32:14.581465: train_loss -0.7647 +2024-11-21 21:32:14.581705: val_loss -0.7163 +2024-11-21 21:32:14.581785: Pseudo dice [0.8231] +2024-11-21 21:32:14.581866: Epoch time: 17.52 s +2024-11-21 21:32:15.482772: +2024-11-21 21:32:15.483013: Epoch 1992 +2024-11-21 21:32:15.483124: Current learning rate: 0.00773 +2024-11-21 21:32:34.472099: train_loss -0.7697 +2024-11-21 21:32:34.472310: val_loss -0.7119 +2024-11-21 21:32:34.472390: Pseudo dice [0.8094] +2024-11-21 21:32:34.472467: Epoch time: 18.99 s +2024-11-21 21:32:35.331463: +2024-11-21 21:32:35.331686: Epoch 1993 +2024-11-21 21:32:35.331800: Current learning rate: 0.00773 +2024-11-21 21:32:54.716427: train_loss -0.7675 +2024-11-21 21:32:54.716635: val_loss -0.7406 +2024-11-21 21:32:54.716710: Pseudo dice [0.8219] +2024-11-21 21:32:54.716817: Epoch time: 19.39 s +2024-11-21 21:32:55.962924: +2024-11-21 21:32:55.963149: Epoch 1994 +2024-11-21 21:32:55.978395: Current learning rate: 0.00773 +2024-11-21 21:33:14.053918: train_loss -0.7347 +2024-11-21 21:33:14.054239: val_loss -0.7277 +2024-11-21 21:33:14.054319: Pseudo dice [0.7803] +2024-11-21 21:33:14.054406: Epoch time: 18.09 s +2024-11-21 21:33:14.915329: +2024-11-21 21:33:14.915539: Epoch 1995 +2024-11-21 21:33:14.915649: Current learning rate: 0.00772 +2024-11-21 21:33:33.323461: train_loss -0.7443 +2024-11-21 21:33:33.323683: val_loss -0.7513 +2024-11-21 21:33:33.323761: Pseudo dice [0.8127] +2024-11-21 21:33:33.323837: Epoch time: 18.41 s +2024-11-21 21:33:34.201607: +2024-11-21 21:33:34.201891: Epoch 1996 +2024-11-21 21:33:34.202010: Current learning rate: 0.00772 +2024-11-21 21:33:52.453555: train_loss -0.7583 +2024-11-21 21:33:52.453783: val_loss -0.7319 +2024-11-21 21:33:52.456059: Pseudo dice [0.8184] +2024-11-21 21:33:52.456216: Epoch time: 18.25 s +2024-11-21 21:33:53.368969: +2024-11-21 21:33:53.369181: Epoch 1997 +2024-11-21 21:33:53.369300: Current learning rate: 0.00772 +2024-11-21 21:34:11.286812: train_loss -0.7651 +2024-11-21 21:34:11.287028: val_loss -0.7293 +2024-11-21 21:34:11.287162: Pseudo dice [0.8287] +2024-11-21 21:34:11.287244: Epoch time: 17.92 s +2024-11-21 21:34:12.148885: +2024-11-21 21:34:12.149106: Epoch 1998 +2024-11-21 21:34:12.149220: Current learning rate: 0.00772 +2024-11-21 21:34:31.542895: train_loss -0.7568 +2024-11-21 21:34:31.543139: val_loss -0.7489 +2024-11-21 21:34:31.543216: Pseudo dice [0.8207] +2024-11-21 21:34:31.543298: Epoch time: 19.39 s +2024-11-21 21:34:32.402662: +2024-11-21 21:34:32.402853: Epoch 1999 +2024-11-21 21:34:32.402968: Current learning rate: 0.00772 +2024-11-21 21:34:50.919620: train_loss -0.7725 +2024-11-21 21:34:50.919832: val_loss -0.7277 +2024-11-21 21:34:50.919907: Pseudo dice [0.8254] +2024-11-21 21:34:50.919981: Epoch time: 18.52 s +2024-11-21 21:34:51.977794: +2024-11-21 21:34:51.978014: Epoch 2000 +2024-11-21 21:34:51.978132: Current learning rate: 0.00772 +2024-11-21 21:35:10.966608: train_loss -0.767 +2024-11-21 21:35:10.966829: val_loss -0.7348 +2024-11-21 21:35:10.966903: Pseudo dice [0.823] +2024-11-21 21:35:10.966976: Epoch time: 18.99 s +2024-11-21 21:35:11.939400: +2024-11-21 21:35:11.939615: Epoch 2001 +2024-11-21 21:35:11.939727: Current learning rate: 0.00772 +2024-11-21 21:35:29.755525: train_loss -0.7706 +2024-11-21 21:35:29.755757: val_loss -0.7631 +2024-11-21 21:35:29.755834: Pseudo dice [0.8395] +2024-11-21 21:35:29.755915: Epoch time: 17.82 s +2024-11-21 21:35:30.674621: +2024-11-21 21:35:30.674895: Epoch 2002 +2024-11-21 21:35:30.675022: Current learning rate: 0.00772 +2024-11-21 21:35:48.585054: train_loss -0.7746 +2024-11-21 21:35:48.585273: val_loss -0.7578 +2024-11-21 21:35:48.585345: Pseudo dice [0.8233] +2024-11-21 21:35:48.586715: Epoch time: 17.91 s +2024-11-21 21:35:49.453757: +2024-11-21 21:35:49.453946: Epoch 2003 +2024-11-21 21:35:49.454063: Current learning rate: 0.00772 +2024-11-21 21:36:08.618828: train_loss -0.7664 +2024-11-21 21:36:08.619054: val_loss -0.7357 +2024-11-21 21:36:08.619128: Pseudo dice [0.8271] +2024-11-21 21:36:08.619208: Epoch time: 19.17 s +2024-11-21 21:36:09.480858: +2024-11-21 21:36:09.481059: Epoch 2004 +2024-11-21 21:36:09.481173: Current learning rate: 0.00771 +2024-11-21 21:36:28.330657: train_loss -0.7647 +2024-11-21 21:36:28.330914: val_loss -0.7265 +2024-11-21 21:36:28.330990: Pseudo dice [0.8307] +2024-11-21 21:36:28.331080: Epoch time: 18.85 s +2024-11-21 21:36:29.594916: +2024-11-21 21:36:29.595146: Epoch 2005 +2024-11-21 21:36:29.595260: Current learning rate: 0.00771 +2024-11-21 21:36:48.830366: train_loss -0.772 +2024-11-21 21:36:48.830598: val_loss -0.7047 +2024-11-21 21:36:48.830674: Pseudo dice [0.8399] +2024-11-21 21:36:48.830749: Epoch time: 19.24 s +2024-11-21 21:36:49.686982: +2024-11-21 21:36:49.687287: Epoch 2006 +2024-11-21 21:36:49.687400: Current learning rate: 0.00771 +2024-11-21 21:37:08.188705: train_loss -0.7663 +2024-11-21 21:37:08.191116: val_loss -0.7225 +2024-11-21 21:37:08.191248: Pseudo dice [0.8042] +2024-11-21 21:37:08.211705: Epoch time: 18.5 s +2024-11-21 21:37:09.222307: +2024-11-21 21:37:09.222531: Epoch 2007 +2024-11-21 21:37:09.222644: Current learning rate: 0.00771 +2024-11-21 21:37:28.272850: train_loss -0.7718 +2024-11-21 21:37:28.273077: val_loss -0.6788 +2024-11-21 21:37:28.273152: Pseudo dice [0.8079] +2024-11-21 21:37:28.273229: Epoch time: 19.05 s +2024-11-21 21:37:29.283462: +2024-11-21 21:37:29.283675: Epoch 2008 +2024-11-21 21:37:29.283788: Current learning rate: 0.00771 +2024-11-21 21:37:48.375510: train_loss -0.7614 +2024-11-21 21:37:48.375763: val_loss -0.7208 +2024-11-21 21:37:48.375836: Pseudo dice [0.8305] +2024-11-21 21:37:48.375920: Epoch time: 19.09 s +2024-11-21 21:37:49.239032: +2024-11-21 21:37:49.239264: Epoch 2009 +2024-11-21 21:37:49.239381: Current learning rate: 0.00771 +2024-11-21 21:38:07.957273: train_loss -0.7819 +2024-11-21 21:38:07.957495: val_loss -0.7506 +2024-11-21 21:38:07.957568: Pseudo dice [0.8133] +2024-11-21 21:38:07.957644: Epoch time: 18.72 s +2024-11-21 21:38:08.888315: +2024-11-21 21:38:08.888542: Epoch 2010 +2024-11-21 21:38:08.888657: Current learning rate: 0.00771 +2024-11-21 21:38:26.600142: train_loss -0.7671 +2024-11-21 21:38:26.600371: val_loss -0.7375 +2024-11-21 21:38:26.600446: Pseudo dice [0.8129] +2024-11-21 21:38:26.600536: Epoch time: 17.71 s +2024-11-21 21:38:27.479892: +2024-11-21 21:38:27.480118: Epoch 2011 +2024-11-21 21:38:27.480232: Current learning rate: 0.00771 +2024-11-21 21:38:45.638286: train_loss -0.7632 +2024-11-21 21:38:45.638505: val_loss -0.7452 +2024-11-21 21:38:45.638586: Pseudo dice [0.8418] +2024-11-21 21:38:45.638668: Epoch time: 18.16 s +2024-11-21 21:38:46.494913: +2024-11-21 21:38:46.495108: Epoch 2012 +2024-11-21 21:38:46.495220: Current learning rate: 0.0077 +2024-11-21 21:39:05.156083: train_loss -0.7758 +2024-11-21 21:39:05.156325: val_loss -0.7521 +2024-11-21 21:39:05.156421: Pseudo dice [0.8306] +2024-11-21 21:39:05.156561: Epoch time: 18.66 s +2024-11-21 21:39:06.016454: +2024-11-21 21:39:06.016650: Epoch 2013 +2024-11-21 21:39:06.016765: Current learning rate: 0.0077 +2024-11-21 21:39:24.848528: train_loss -0.7675 +2024-11-21 21:39:24.848742: val_loss -0.721 +2024-11-21 21:39:24.848816: Pseudo dice [0.8047] +2024-11-21 21:39:24.848894: Epoch time: 18.83 s +2024-11-21 21:39:25.781541: +2024-11-21 21:39:25.781752: Epoch 2014 +2024-11-21 21:39:25.781866: Current learning rate: 0.0077 +2024-11-21 21:39:45.158942: train_loss -0.7681 +2024-11-21 21:39:45.160188: val_loss -0.7611 +2024-11-21 21:39:45.160308: Pseudo dice [0.8324] +2024-11-21 21:39:45.160386: Epoch time: 19.38 s +2024-11-21 21:39:46.022301: +2024-11-21 21:39:46.022709: Epoch 2015 +2024-11-21 21:39:46.022843: Current learning rate: 0.0077 +2024-11-21 21:40:04.061172: train_loss -0.7718 +2024-11-21 21:40:04.061419: val_loss -0.7348 +2024-11-21 21:40:04.061499: Pseudo dice [0.8381] +2024-11-21 21:40:04.061595: Epoch time: 18.04 s +2024-11-21 21:40:05.005268: +2024-11-21 21:40:05.005663: Epoch 2016 +2024-11-21 21:40:05.005796: Current learning rate: 0.0077 +2024-11-21 21:40:23.525592: train_loss -0.7685 +2024-11-21 21:40:23.526053: val_loss -0.7485 +2024-11-21 21:40:23.526151: Pseudo dice [0.8175] +2024-11-21 21:40:23.526228: Epoch time: 18.52 s +2024-11-21 21:40:24.376794: +2024-11-21 21:40:24.377017: Epoch 2017 +2024-11-21 21:40:24.377143: Current learning rate: 0.0077 +2024-11-21 21:40:42.220179: train_loss -0.7711 +2024-11-21 21:40:42.220399: val_loss -0.7676 +2024-11-21 21:40:42.220476: Pseudo dice [0.8251] +2024-11-21 21:40:42.220552: Epoch time: 17.84 s +2024-11-21 21:40:43.181672: +2024-11-21 21:40:43.182045: Epoch 2018 +2024-11-21 21:40:43.182160: Current learning rate: 0.0077 +2024-11-21 21:41:02.739419: train_loss -0.7803 +2024-11-21 21:41:02.739635: val_loss -0.7516 +2024-11-21 21:41:02.739713: Pseudo dice [0.8183] +2024-11-21 21:41:02.739795: Epoch time: 19.56 s +2024-11-21 21:41:03.620124: +2024-11-21 21:41:03.620386: Epoch 2019 +2024-11-21 21:41:03.620542: Current learning rate: 0.0077 +2024-11-21 21:41:22.473989: train_loss -0.7789 +2024-11-21 21:41:22.486701: val_loss -0.7282 +2024-11-21 21:41:22.486861: Pseudo dice [0.821] +2024-11-21 21:41:22.486975: Epoch time: 18.85 s +2024-11-21 21:41:23.350704: +2024-11-21 21:41:23.350910: Epoch 2020 +2024-11-21 21:41:23.351034: Current learning rate: 0.0077 +2024-11-21 21:41:42.833509: train_loss -0.7715 +2024-11-21 21:41:42.833726: val_loss -0.73 +2024-11-21 21:41:42.833813: Pseudo dice [0.8133] +2024-11-21 21:41:42.833892: Epoch time: 19.48 s +2024-11-21 21:41:43.689505: +2024-11-21 21:41:43.689716: Epoch 2021 +2024-11-21 21:41:43.689836: Current learning rate: 0.00769 +2024-11-21 21:42:03.041968: train_loss -0.7647 +2024-11-21 21:42:03.042207: val_loss -0.7138 +2024-11-21 21:42:03.042342: Pseudo dice [0.8289] +2024-11-21 21:42:03.042422: Epoch time: 19.35 s +2024-11-21 21:42:03.900000: +2024-11-21 21:42:03.900190: Epoch 2022 +2024-11-21 21:42:03.900305: Current learning rate: 0.00769 +2024-11-21 21:42:21.704210: train_loss -0.7748 +2024-11-21 21:42:21.708639: val_loss -0.7335 +2024-11-21 21:42:21.708827: Pseudo dice [0.8345] +2024-11-21 21:42:21.708915: Epoch time: 17.8 s +2024-11-21 21:42:22.598087: +2024-11-21 21:42:22.598306: Epoch 2023 +2024-11-21 21:42:22.598418: Current learning rate: 0.00769 +2024-11-21 21:42:40.498777: train_loss -0.7772 +2024-11-21 21:42:40.499026: val_loss -0.738 +2024-11-21 21:42:40.499102: Pseudo dice [0.8238] +2024-11-21 21:42:40.499184: Epoch time: 17.9 s +2024-11-21 21:42:41.366038: +2024-11-21 21:42:41.366239: Epoch 2024 +2024-11-21 21:42:41.366353: Current learning rate: 0.00769 +2024-11-21 21:42:59.634540: train_loss -0.7735 +2024-11-21 21:42:59.634754: val_loss -0.718 +2024-11-21 21:42:59.634832: Pseudo dice [0.7776] +2024-11-21 21:42:59.634959: Epoch time: 18.27 s +2024-11-21 21:43:00.493148: +2024-11-21 21:43:00.493335: Epoch 2025 +2024-11-21 21:43:00.493447: Current learning rate: 0.00769 +2024-11-21 21:43:19.799172: train_loss -0.7677 +2024-11-21 21:43:19.799388: val_loss -0.7549 +2024-11-21 21:43:19.799463: Pseudo dice [0.833] +2024-11-21 21:43:19.799542: Epoch time: 19.31 s +2024-11-21 21:43:20.714844: +2024-11-21 21:43:20.715056: Epoch 2026 +2024-11-21 21:43:20.715170: Current learning rate: 0.00769 +2024-11-21 21:43:39.559191: train_loss -0.7786 +2024-11-21 21:43:39.559434: val_loss -0.7278 +2024-11-21 21:43:39.559507: Pseudo dice [0.8164] +2024-11-21 21:43:39.559608: Epoch time: 18.85 s +2024-11-21 21:43:40.947088: +2024-11-21 21:43:40.947344: Epoch 2027 +2024-11-21 21:43:40.947468: Current learning rate: 0.00769 +2024-11-21 21:43:59.223263: train_loss -0.7795 +2024-11-21 21:43:59.223487: val_loss -0.7505 +2024-11-21 21:43:59.223567: Pseudo dice [0.8186] +2024-11-21 21:43:59.223645: Epoch time: 18.28 s +2024-11-21 21:44:00.082532: +2024-11-21 21:44:00.082747: Epoch 2028 +2024-11-21 21:44:00.082859: Current learning rate: 0.00769 +2024-11-21 21:44:19.886240: train_loss -0.7705 +2024-11-21 21:44:19.886455: val_loss -0.7526 +2024-11-21 21:44:19.886528: Pseudo dice [0.8167] +2024-11-21 21:44:19.886605: Epoch time: 19.8 s +2024-11-21 21:44:20.746163: +2024-11-21 21:44:20.746379: Epoch 2029 +2024-11-21 21:44:20.746493: Current learning rate: 0.00769 +2024-11-21 21:44:39.327533: train_loss -0.7684 +2024-11-21 21:44:39.327768: val_loss -0.7562 +2024-11-21 21:44:39.327846: Pseudo dice [0.8255] +2024-11-21 21:44:39.327932: Epoch time: 18.58 s +2024-11-21 21:44:40.224424: +2024-11-21 21:44:40.224676: Epoch 2030 +2024-11-21 21:44:40.224791: Current learning rate: 0.00768 +2024-11-21 21:44:58.865664: train_loss -0.7808 +2024-11-21 21:44:58.865873: val_loss -0.7391 +2024-11-21 21:44:58.865947: Pseudo dice [0.8325] +2024-11-21 21:44:58.866031: Epoch time: 18.64 s +2024-11-21 21:44:59.950974: +2024-11-21 21:44:59.951196: Epoch 2031 +2024-11-21 21:44:59.951310: Current learning rate: 0.00768 +2024-11-21 21:45:19.007128: train_loss -0.7721 +2024-11-21 21:45:19.007345: val_loss -0.7297 +2024-11-21 21:45:19.007418: Pseudo dice [0.825] +2024-11-21 21:45:19.007493: Epoch time: 19.06 s +2024-11-21 21:45:19.863957: +2024-11-21 21:45:19.864218: Epoch 2032 +2024-11-21 21:45:19.864331: Current learning rate: 0.00768 +2024-11-21 21:45:39.805937: train_loss -0.7651 +2024-11-21 21:45:39.806147: val_loss -0.7391 +2024-11-21 21:45:39.806230: Pseudo dice [0.7984] +2024-11-21 21:45:39.806336: Epoch time: 19.94 s +2024-11-21 21:45:40.659636: +2024-11-21 21:45:40.659830: Epoch 2033 +2024-11-21 21:45:40.660511: Current learning rate: 0.00768 +2024-11-21 21:45:58.767347: train_loss -0.7783 +2024-11-21 21:45:58.767592: val_loss -0.7327 +2024-11-21 21:45:58.767667: Pseudo dice [0.8299] +2024-11-21 21:45:58.767748: Epoch time: 18.11 s +2024-11-21 21:45:59.627506: +2024-11-21 21:45:59.627795: Epoch 2034 +2024-11-21 21:45:59.627904: Current learning rate: 0.00768 +2024-11-21 21:46:20.318414: train_loss -0.7773 +2024-11-21 21:46:20.318646: val_loss -0.7355 +2024-11-21 21:46:20.318730: Pseudo dice [0.8049] +2024-11-21 21:46:20.318812: Epoch time: 20.69 s +2024-11-21 21:46:21.173544: +2024-11-21 21:46:21.173745: Epoch 2035 +2024-11-21 21:46:21.173853: Current learning rate: 0.00768 +2024-11-21 21:46:39.189352: train_loss -0.7869 +2024-11-21 21:46:39.189595: val_loss -0.7414 +2024-11-21 21:46:39.189673: Pseudo dice [0.8299] +2024-11-21 21:46:39.189753: Epoch time: 18.02 s +2024-11-21 21:46:40.049781: +2024-11-21 21:46:40.049965: Epoch 2036 +2024-11-21 21:46:40.050081: Current learning rate: 0.00768 +2024-11-21 21:46:58.455290: train_loss -0.7818 +2024-11-21 21:46:58.455593: val_loss -0.7433 +2024-11-21 21:46:58.455671: Pseudo dice [0.8376] +2024-11-21 21:46:58.455754: Epoch time: 18.41 s +2024-11-21 21:46:59.388105: +2024-11-21 21:46:59.388305: Epoch 2037 +2024-11-21 21:46:59.388421: Current learning rate: 0.00768 +2024-11-21 21:47:18.295492: train_loss -0.7815 +2024-11-21 21:47:18.296434: val_loss -0.7462 +2024-11-21 21:47:18.296579: Pseudo dice [0.8066] +2024-11-21 21:47:18.296667: Epoch time: 18.91 s +2024-11-21 21:47:19.157696: +2024-11-21 21:47:19.157922: Epoch 2038 +2024-11-21 21:47:19.158050: Current learning rate: 0.00767 +2024-11-21 21:47:38.507494: train_loss -0.7749 +2024-11-21 21:47:38.507705: val_loss -0.7276 +2024-11-21 21:47:38.507776: Pseudo dice [0.8042] +2024-11-21 21:47:38.507850: Epoch time: 19.35 s +2024-11-21 21:47:39.800800: +2024-11-21 21:47:39.800989: Epoch 2039 +2024-11-21 21:47:39.801111: Current learning rate: 0.00767 +2024-11-21 21:47:58.764592: train_loss -0.7697 +2024-11-21 21:47:58.764846: val_loss -0.7578 +2024-11-21 21:47:58.764919: Pseudo dice [0.8391] +2024-11-21 21:47:58.765034: Epoch time: 18.96 s +2024-11-21 21:47:59.628177: +2024-11-21 21:47:59.628411: Epoch 2040 +2024-11-21 21:47:59.628535: Current learning rate: 0.00767 +2024-11-21 21:48:16.996439: train_loss -0.7685 +2024-11-21 21:48:16.996652: val_loss -0.7375 +2024-11-21 21:48:16.996729: Pseudo dice [0.8131] +2024-11-21 21:48:16.996805: Epoch time: 17.37 s +2024-11-21 21:48:17.852104: +2024-11-21 21:48:17.852360: Epoch 2041 +2024-11-21 21:48:17.852480: Current learning rate: 0.00767 +2024-11-21 21:48:36.273082: train_loss -0.7612 +2024-11-21 21:48:36.273299: val_loss -0.7277 +2024-11-21 21:48:36.273373: Pseudo dice [0.7711] +2024-11-21 21:48:36.273453: Epoch time: 18.42 s +2024-11-21 21:48:37.130177: +2024-11-21 21:48:37.130391: Epoch 2042 +2024-11-21 21:48:37.130510: Current learning rate: 0.00767 +2024-11-21 21:48:57.050722: train_loss -0.769 +2024-11-21 21:48:57.050947: val_loss -0.7094 +2024-11-21 21:48:57.051052: Pseudo dice [0.821] +2024-11-21 21:48:57.051137: Epoch time: 19.92 s +2024-11-21 21:48:57.909187: +2024-11-21 21:48:57.909404: Epoch 2043 +2024-11-21 21:48:57.909520: Current learning rate: 0.00767 +2024-11-21 21:49:17.919968: train_loss -0.7663 +2024-11-21 21:49:17.933242: val_loss -0.7399 +2024-11-21 21:49:17.933359: Pseudo dice [0.834] +2024-11-21 21:49:17.933442: Epoch time: 20.01 s +2024-11-21 21:49:18.840441: +2024-11-21 21:49:18.840672: Epoch 2044 +2024-11-21 21:49:18.840788: Current learning rate: 0.00767 +2024-11-21 21:49:37.204253: train_loss -0.7736 +2024-11-21 21:49:37.204466: val_loss -0.7363 +2024-11-21 21:49:37.204540: Pseudo dice [0.8283] +2024-11-21 21:49:37.204616: Epoch time: 18.36 s +2024-11-21 21:49:38.084305: +2024-11-21 21:49:38.084507: Epoch 2045 +2024-11-21 21:49:38.084616: Current learning rate: 0.00767 +2024-11-21 21:49:57.578959: train_loss -0.7821 +2024-11-21 21:49:57.579189: val_loss -0.7394 +2024-11-21 21:49:57.579266: Pseudo dice [0.8282] +2024-11-21 21:49:57.579344: Epoch time: 19.5 s +2024-11-21 21:49:58.436933: +2024-11-21 21:49:58.437154: Epoch 2046 +2024-11-21 21:49:58.437269: Current learning rate: 0.00767 +2024-11-21 21:50:17.433764: train_loss -0.7749 +2024-11-21 21:50:17.434019: val_loss -0.7315 +2024-11-21 21:50:17.434095: Pseudo dice [0.8219] +2024-11-21 21:50:17.434179: Epoch time: 19.0 s +2024-11-21 21:50:18.273098: +2024-11-21 21:50:18.273285: Epoch 2047 +2024-11-21 21:50:18.273396: Current learning rate: 0.00766 +2024-11-21 21:50:37.662354: train_loss -0.7675 +2024-11-21 21:50:37.662579: val_loss -0.7425 +2024-11-21 21:50:37.662652: Pseudo dice [0.8123] +2024-11-21 21:50:37.662729: Epoch time: 19.39 s +2024-11-21 21:50:38.492950: +2024-11-21 21:50:38.493158: Epoch 2048 +2024-11-21 21:50:38.493269: Current learning rate: 0.00766 +2024-11-21 21:50:57.001236: train_loss -0.7615 +2024-11-21 21:50:57.001728: val_loss -0.7504 +2024-11-21 21:50:57.001808: Pseudo dice [0.8141] +2024-11-21 21:50:57.001885: Epoch time: 18.51 s +2024-11-21 21:50:57.827347: +2024-11-21 21:50:57.827624: Epoch 2049 +2024-11-21 21:50:57.827743: Current learning rate: 0.00766 +2024-11-21 21:51:16.673833: train_loss -0.7638 +2024-11-21 21:51:16.674052: val_loss -0.7367 +2024-11-21 21:51:16.674127: Pseudo dice [0.8164] +2024-11-21 21:51:16.674204: Epoch time: 18.85 s +2024-11-21 21:51:18.120657: +2024-11-21 21:51:18.120881: Epoch 2050 +2024-11-21 21:51:18.121001: Current learning rate: 0.00766 +2024-11-21 21:51:37.430449: train_loss -0.7716 +2024-11-21 21:51:37.430748: val_loss -0.7575 +2024-11-21 21:51:37.430825: Pseudo dice [0.8317] +2024-11-21 21:51:37.430911: Epoch time: 19.31 s +2024-11-21 21:51:38.285742: +2024-11-21 21:51:38.285984: Epoch 2051 +2024-11-21 21:51:38.286101: Current learning rate: 0.00766 +2024-11-21 21:51:56.560026: train_loss -0.7823 +2024-11-21 21:51:56.560240: val_loss -0.7346 +2024-11-21 21:51:56.560314: Pseudo dice [0.8149] +2024-11-21 21:51:56.560390: Epoch time: 18.28 s +2024-11-21 21:51:57.471612: +2024-11-21 21:51:57.471833: Epoch 2052 +2024-11-21 21:51:57.471947: Current learning rate: 0.00766 +2024-11-21 21:52:16.921590: train_loss -0.765 +2024-11-21 21:52:16.921816: val_loss -0.7142 +2024-11-21 21:52:16.931095: Pseudo dice [0.8217] +2024-11-21 21:52:16.931208: Epoch time: 19.45 s +2024-11-21 21:52:18.172603: +2024-11-21 21:52:18.172824: Epoch 2053 +2024-11-21 21:52:18.172938: Current learning rate: 0.00766 +2024-11-21 21:52:36.780561: train_loss -0.7657 +2024-11-21 21:52:36.780809: val_loss -0.7511 +2024-11-21 21:52:36.780898: Pseudo dice [0.8484] +2024-11-21 21:52:36.780983: Epoch time: 18.61 s +2024-11-21 21:52:37.610941: +2024-11-21 21:52:37.611174: Epoch 2054 +2024-11-21 21:52:37.611289: Current learning rate: 0.00766 +2024-11-21 21:52:55.729006: train_loss -0.7618 +2024-11-21 21:52:55.730961: val_loss -0.7394 +2024-11-21 21:52:55.731060: Pseudo dice [0.8307] +2024-11-21 21:52:55.731147: Epoch time: 18.12 s +2024-11-21 21:52:56.565416: +2024-11-21 21:52:56.565623: Epoch 2055 +2024-11-21 21:52:56.565737: Current learning rate: 0.00766 +2024-11-21 21:53:15.313914: train_loss -0.7668 +2024-11-21 21:53:15.314139: val_loss -0.741 +2024-11-21 21:53:15.314220: Pseudo dice [0.816] +2024-11-21 21:53:15.314296: Epoch time: 18.75 s +2024-11-21 21:53:16.188241: +2024-11-21 21:53:16.188530: Epoch 2056 +2024-11-21 21:53:16.188653: Current learning rate: 0.00765 +2024-11-21 21:53:34.525747: train_loss -0.7697 +2024-11-21 21:53:34.525949: val_loss -0.7641 +2024-11-21 21:53:34.526048: Pseudo dice [0.8331] +2024-11-21 21:53:34.526124: Epoch time: 18.34 s +2024-11-21 21:53:35.376620: +2024-11-21 21:53:35.376871: Epoch 2057 +2024-11-21 21:53:35.376984: Current learning rate: 0.00765 +2024-11-21 21:53:54.656612: train_loss -0.7759 +2024-11-21 21:53:54.656857: val_loss -0.7017 +2024-11-21 21:53:54.658266: Pseudo dice [0.797] +2024-11-21 21:53:54.658396: Epoch time: 19.28 s +2024-11-21 21:53:55.531140: +2024-11-21 21:53:55.531347: Epoch 2058 +2024-11-21 21:53:55.531460: Current learning rate: 0.00765 +2024-11-21 21:54:13.508703: train_loss -0.7696 +2024-11-21 21:54:13.508922: val_loss -0.7582 +2024-11-21 21:54:13.509005: Pseudo dice [0.8175] +2024-11-21 21:54:13.509085: Epoch time: 17.98 s +2024-11-21 21:54:14.345674: +2024-11-21 21:54:14.345882: Epoch 2059 +2024-11-21 21:54:14.346133: Current learning rate: 0.00765 +2024-11-21 21:54:33.512911: train_loss -0.7742 +2024-11-21 21:54:33.513149: val_loss -0.7407 +2024-11-21 21:54:33.513223: Pseudo dice [0.8344] +2024-11-21 21:54:33.513299: Epoch time: 19.17 s +2024-11-21 21:54:34.376837: +2024-11-21 21:54:34.377056: Epoch 2060 +2024-11-21 21:54:34.377173: Current learning rate: 0.00765 +2024-11-21 21:54:52.825432: train_loss -0.7783 +2024-11-21 21:54:52.825657: val_loss -0.7463 +2024-11-21 21:54:52.825737: Pseudo dice [0.8293] +2024-11-21 21:54:52.825816: Epoch time: 18.45 s +2024-11-21 21:54:53.655661: +2024-11-21 21:54:53.655859: Epoch 2061 +2024-11-21 21:54:53.655968: Current learning rate: 0.00765 +2024-11-21 21:55:12.351150: train_loss -0.7657 +2024-11-21 21:55:12.351424: val_loss -0.7438 +2024-11-21 21:55:12.351504: Pseudo dice [0.8019] +2024-11-21 21:55:12.351587: Epoch time: 18.7 s +2024-11-21 21:55:13.186894: +2024-11-21 21:55:13.187107: Epoch 2062 +2024-11-21 21:55:13.187221: Current learning rate: 0.00765 +2024-11-21 21:55:31.894235: train_loss -0.7759 +2024-11-21 21:55:31.894779: val_loss -0.752 +2024-11-21 21:55:31.894875: Pseudo dice [0.8385] +2024-11-21 21:55:31.894954: Epoch time: 18.71 s +2024-11-21 21:55:32.726435: +2024-11-21 21:55:32.726651: Epoch 2063 +2024-11-21 21:55:32.726768: Current learning rate: 0.00765 +2024-11-21 21:55:51.278715: train_loss -0.771 +2024-11-21 21:55:51.278934: val_loss -0.716 +2024-11-21 21:55:51.279017: Pseudo dice [0.8041] +2024-11-21 21:55:51.279101: Epoch time: 18.55 s +2024-11-21 21:55:52.114926: +2024-11-21 21:55:52.115151: Epoch 2064 +2024-11-21 21:55:52.115268: Current learning rate: 0.00764 +2024-11-21 21:56:11.049338: train_loss -0.7783 +2024-11-21 21:56:11.049583: val_loss -0.7507 +2024-11-21 21:56:11.049665: Pseudo dice [0.815] +2024-11-21 21:56:11.049745: Epoch time: 18.94 s +2024-11-21 21:56:11.892468: +2024-11-21 21:56:11.892706: Epoch 2065 +2024-11-21 21:56:11.892821: Current learning rate: 0.00764 +2024-11-21 21:56:30.025133: train_loss -0.7669 +2024-11-21 21:56:30.025398: val_loss -0.7462 +2024-11-21 21:56:30.025475: Pseudo dice [0.8246] +2024-11-21 21:56:30.025551: Epoch time: 18.13 s +2024-11-21 21:56:30.860325: +2024-11-21 21:56:30.860565: Epoch 2066 +2024-11-21 21:56:30.860680: Current learning rate: 0.00764 +2024-11-21 21:56:48.775188: train_loss -0.766 +2024-11-21 21:56:48.775413: val_loss -0.7435 +2024-11-21 21:56:48.775491: Pseudo dice [0.8297] +2024-11-21 21:56:48.775570: Epoch time: 17.92 s +2024-11-21 21:56:49.607082: +2024-11-21 21:56:49.607295: Epoch 2067 +2024-11-21 21:56:49.607406: Current learning rate: 0.00764 +2024-11-21 21:57:08.208316: train_loss -0.779 +2024-11-21 21:57:08.208536: val_loss -0.7643 +2024-11-21 21:57:08.208612: Pseudo dice [0.8283] +2024-11-21 21:57:08.208694: Epoch time: 18.6 s +2024-11-21 21:57:09.047307: +2024-11-21 21:57:09.047526: Epoch 2068 +2024-11-21 21:57:09.047638: Current learning rate: 0.00764 +2024-11-21 21:57:27.817511: train_loss -0.7667 +2024-11-21 21:57:27.817755: val_loss -0.728 +2024-11-21 21:57:27.817839: Pseudo dice [0.826] +2024-11-21 21:57:27.817922: Epoch time: 18.77 s +2024-11-21 21:57:28.646809: +2024-11-21 21:57:28.647029: Epoch 2069 +2024-11-21 21:57:28.647142: Current learning rate: 0.00764 +2024-11-21 21:57:47.366769: train_loss -0.7726 +2024-11-21 21:57:47.366987: val_loss -0.7397 +2024-11-21 21:57:47.367068: Pseudo dice [0.8237] +2024-11-21 21:57:47.372347: Epoch time: 18.72 s +2024-11-21 21:57:48.358748: +2024-11-21 21:57:48.359010: Epoch 2070 +2024-11-21 21:57:48.359127: Current learning rate: 0.00764 +2024-11-21 21:58:06.306147: train_loss -0.7743 +2024-11-21 21:58:06.306355: val_loss -0.7434 +2024-11-21 21:58:06.306427: Pseudo dice [0.8351] +2024-11-21 21:58:06.306503: Epoch time: 17.95 s +2024-11-21 21:58:07.137656: +2024-11-21 21:58:07.137877: Epoch 2071 +2024-11-21 21:58:07.137985: Current learning rate: 0.00764 +2024-11-21 21:58:26.105479: train_loss -0.7727 +2024-11-21 21:58:26.105729: val_loss -0.724 +2024-11-21 21:58:26.105804: Pseudo dice [0.803] +2024-11-21 21:58:26.105886: Epoch time: 18.97 s +2024-11-21 21:58:26.957422: +2024-11-21 21:58:26.957632: Epoch 2072 +2024-11-21 21:58:26.957745: Current learning rate: 0.00764 +2024-11-21 21:58:45.640047: train_loss -0.776 +2024-11-21 21:58:45.640336: val_loss -0.7346 +2024-11-21 21:58:45.640412: Pseudo dice [0.817] +2024-11-21 21:58:45.640487: Epoch time: 18.68 s +2024-11-21 21:58:46.472915: +2024-11-21 21:58:46.473157: Epoch 2073 +2024-11-21 21:58:46.473275: Current learning rate: 0.00763 +2024-11-21 21:59:06.204127: train_loss -0.7791 +2024-11-21 21:59:06.204340: val_loss -0.7023 +2024-11-21 21:59:06.204413: Pseudo dice [0.8226] +2024-11-21 21:59:06.204487: Epoch time: 19.73 s +2024-11-21 21:59:07.037936: +2024-11-21 21:59:07.038197: Epoch 2074 +2024-11-21 21:59:07.038317: Current learning rate: 0.00763 +2024-11-21 21:59:25.855537: train_loss -0.7721 +2024-11-21 21:59:25.856027: val_loss -0.7327 +2024-11-21 21:59:25.856126: Pseudo dice [0.8235] +2024-11-21 21:59:25.856210: Epoch time: 18.82 s +2024-11-21 21:59:26.812216: +2024-11-21 21:59:26.812425: Epoch 2075 +2024-11-21 21:59:26.812539: Current learning rate: 0.00763 +2024-11-21 21:59:44.787390: train_loss -0.7716 +2024-11-21 21:59:44.792814: val_loss -0.7507 +2024-11-21 21:59:44.792899: Pseudo dice [0.8276] +2024-11-21 21:59:44.792982: Epoch time: 17.98 s +2024-11-21 21:59:45.683907: +2024-11-21 21:59:45.684149: Epoch 2076 +2024-11-21 21:59:45.684267: Current learning rate: 0.00763 +2024-11-21 22:00:03.864832: train_loss -0.77 +2024-11-21 22:00:03.865132: val_loss -0.7387 +2024-11-21 22:00:03.865214: Pseudo dice [0.8038] +2024-11-21 22:00:03.865295: Epoch time: 18.18 s +2024-11-21 22:00:04.757834: +2024-11-21 22:00:04.758065: Epoch 2077 +2024-11-21 22:00:04.758183: Current learning rate: 0.00763 +2024-11-21 22:00:22.755420: train_loss -0.78 +2024-11-21 22:00:22.755639: val_loss -0.7172 +2024-11-21 22:00:22.755712: Pseudo dice [0.8046] +2024-11-21 22:00:22.755788: Epoch time: 18.0 s +2024-11-21 22:00:23.593297: +2024-11-21 22:00:23.593601: Epoch 2078 +2024-11-21 22:00:23.593710: Current learning rate: 0.00763 +2024-11-21 22:00:44.380213: train_loss -0.7725 +2024-11-21 22:00:44.380467: val_loss -0.7361 +2024-11-21 22:00:44.380544: Pseudo dice [0.8406] +2024-11-21 22:00:44.382817: Epoch time: 20.79 s +2024-11-21 22:00:45.239089: +2024-11-21 22:00:45.239294: Epoch 2079 +2024-11-21 22:00:45.239413: Current learning rate: 0.00763 +2024-11-21 22:01:03.289902: train_loss -0.7707 +2024-11-21 22:01:03.290126: val_loss -0.7199 +2024-11-21 22:01:03.290208: Pseudo dice [0.8167] +2024-11-21 22:01:03.290286: Epoch time: 18.05 s +2024-11-21 22:01:04.127277: +2024-11-21 22:01:04.127488: Epoch 2080 +2024-11-21 22:01:04.127601: Current learning rate: 0.00763 +2024-11-21 22:01:22.516094: train_loss -0.7719 +2024-11-21 22:01:22.516322: val_loss -0.7381 +2024-11-21 22:01:22.516396: Pseudo dice [0.8161] +2024-11-21 22:01:22.516472: Epoch time: 18.39 s +2024-11-21 22:01:23.520807: +2024-11-21 22:01:23.521004: Epoch 2081 +2024-11-21 22:01:23.521118: Current learning rate: 0.00763 +2024-11-21 22:01:43.181738: train_loss -0.7758 +2024-11-21 22:01:43.181958: val_loss -0.7166 +2024-11-21 22:01:43.182040: Pseudo dice [0.8097] +2024-11-21 22:01:43.182120: Epoch time: 19.66 s +2024-11-21 22:01:44.018562: +2024-11-21 22:01:44.018820: Epoch 2082 +2024-11-21 22:01:44.018933: Current learning rate: 0.00762 +2024-11-21 22:02:03.983005: train_loss -0.7767 +2024-11-21 22:02:03.983241: val_loss -0.7302 +2024-11-21 22:02:03.983318: Pseudo dice [0.8237] +2024-11-21 22:02:03.983403: Epoch time: 19.97 s +2024-11-21 22:02:04.815942: +2024-11-21 22:02:04.827028: Epoch 2083 +2024-11-21 22:02:04.827160: Current learning rate: 0.00762 +2024-11-21 22:02:23.820928: train_loss -0.7718 +2024-11-21 22:02:23.821159: val_loss -0.749 +2024-11-21 22:02:23.821234: Pseudo dice [0.8233] +2024-11-21 22:02:23.826560: Epoch time: 19.01 s +2024-11-21 22:02:24.704402: +2024-11-21 22:02:24.704607: Epoch 2084 +2024-11-21 22:02:24.704717: Current learning rate: 0.00762 +2024-11-21 22:02:43.678432: train_loss -0.7665 +2024-11-21 22:02:43.679019: val_loss -0.7566 +2024-11-21 22:02:43.679098: Pseudo dice [0.8521] +2024-11-21 22:02:43.679173: Epoch time: 18.97 s +2024-11-21 22:02:44.523194: +2024-11-21 22:02:44.523557: Epoch 2085 +2024-11-21 22:02:44.523675: Current learning rate: 0.00762 +2024-11-21 22:03:03.908412: train_loss -0.7711 +2024-11-21 22:03:03.908626: val_loss -0.7199 +2024-11-21 22:03:03.908701: Pseudo dice [0.7955] +2024-11-21 22:03:03.908778: Epoch time: 19.39 s +2024-11-21 22:03:04.740452: +2024-11-21 22:03:04.740656: Epoch 2086 +2024-11-21 22:03:04.740773: Current learning rate: 0.00762 +2024-11-21 22:03:23.058127: train_loss -0.7773 +2024-11-21 22:03:23.058720: val_loss -0.7296 +2024-11-21 22:03:23.058822: Pseudo dice [0.8219] +2024-11-21 22:03:23.058923: Epoch time: 18.32 s +2024-11-21 22:03:23.892122: +2024-11-21 22:03:23.892328: Epoch 2087 +2024-11-21 22:03:23.892445: Current learning rate: 0.00762 +2024-11-21 22:03:42.216935: train_loss -0.7812 +2024-11-21 22:03:42.217191: val_loss -0.7368 +2024-11-21 22:03:42.217309: Pseudo dice [0.8287] +2024-11-21 22:03:42.217413: Epoch time: 18.33 s +2024-11-21 22:03:43.099822: +2024-11-21 22:03:43.100085: Epoch 2088 +2024-11-21 22:03:43.100203: Current learning rate: 0.00762 +2024-11-21 22:04:01.938767: train_loss -0.7758 +2024-11-21 22:04:01.938986: val_loss -0.7316 +2024-11-21 22:04:01.939067: Pseudo dice [0.8247] +2024-11-21 22:04:01.939145: Epoch time: 18.84 s +2024-11-21 22:04:02.777588: +2024-11-21 22:04:02.777797: Epoch 2089 +2024-11-21 22:04:02.777909: Current learning rate: 0.00762 +2024-11-21 22:04:22.300244: train_loss -0.7733 +2024-11-21 22:04:22.300500: val_loss -0.7385 +2024-11-21 22:04:22.300582: Pseudo dice [0.8176] +2024-11-21 22:04:22.300675: Epoch time: 19.52 s +2024-11-21 22:04:23.138608: +2024-11-21 22:04:23.138832: Epoch 2090 +2024-11-21 22:04:23.138945: Current learning rate: 0.00761 +2024-11-21 22:04:43.372730: train_loss -0.7614 +2024-11-21 22:04:43.372961: val_loss -0.75 +2024-11-21 22:04:43.373044: Pseudo dice [0.8317] +2024-11-21 22:04:43.373125: Epoch time: 20.23 s +2024-11-21 22:04:44.337479: +2024-11-21 22:04:44.337693: Epoch 2091 +2024-11-21 22:04:44.337819: Current learning rate: 0.00761 +2024-11-21 22:05:02.490299: train_loss -0.7692 +2024-11-21 22:05:02.490529: val_loss -0.7505 +2024-11-21 22:05:02.490605: Pseudo dice [0.842] +2024-11-21 22:05:02.490685: Epoch time: 18.15 s +2024-11-21 22:05:03.329855: +2024-11-21 22:05:03.330057: Epoch 2092 +2024-11-21 22:05:03.330169: Current learning rate: 0.00761 +2024-11-21 22:05:21.651423: train_loss -0.7756 +2024-11-21 22:05:21.652608: val_loss -0.743 +2024-11-21 22:05:21.652732: Pseudo dice [0.814] +2024-11-21 22:05:21.652813: Epoch time: 18.32 s +2024-11-21 22:05:22.494341: +2024-11-21 22:05:22.494571: Epoch 2093 +2024-11-21 22:05:22.494705: Current learning rate: 0.00761 +2024-11-21 22:05:41.742313: train_loss -0.7773 +2024-11-21 22:05:41.744863: val_loss -0.7237 +2024-11-21 22:05:41.744962: Pseudo dice [0.8224] +2024-11-21 22:05:41.745055: Epoch time: 19.25 s +2024-11-21 22:05:42.613728: +2024-11-21 22:05:42.613968: Epoch 2094 +2024-11-21 22:05:42.614086: Current learning rate: 0.00761 +2024-11-21 22:06:01.261488: train_loss -0.7734 +2024-11-21 22:06:01.261714: val_loss -0.7044 +2024-11-21 22:06:01.261790: Pseudo dice [0.8198] +2024-11-21 22:06:01.261868: Epoch time: 18.65 s +2024-11-21 22:06:02.106956: +2024-11-21 22:06:02.107168: Epoch 2095 +2024-11-21 22:06:02.107285: Current learning rate: 0.00761 +2024-11-21 22:06:20.050886: train_loss -0.7766 +2024-11-21 22:06:20.051122: val_loss -0.7381 +2024-11-21 22:06:20.051198: Pseudo dice [0.8263] +2024-11-21 22:06:20.063381: Epoch time: 17.94 s +2024-11-21 22:06:21.003952: +2024-11-21 22:06:21.004168: Epoch 2096 +2024-11-21 22:06:21.004277: Current learning rate: 0.00761 +2024-11-21 22:06:39.154736: train_loss -0.7681 +2024-11-21 22:06:39.154986: val_loss -0.7314 +2024-11-21 22:06:39.155077: Pseudo dice [0.8059] +2024-11-21 22:06:39.155173: Epoch time: 18.15 s +2024-11-21 22:06:39.989897: +2024-11-21 22:06:39.990106: Epoch 2097 +2024-11-21 22:06:39.990221: Current learning rate: 0.00761 +2024-11-21 22:06:58.526446: train_loss -0.735 +2024-11-21 22:06:58.526665: val_loss -0.7054 +2024-11-21 22:06:58.526743: Pseudo dice [0.7863] +2024-11-21 22:06:58.526821: Epoch time: 18.54 s +2024-11-21 22:06:59.359952: +2024-11-21 22:06:59.360162: Epoch 2098 +2024-11-21 22:06:59.360275: Current learning rate: 0.00761 +2024-11-21 22:07:18.101227: train_loss -0.7284 +2024-11-21 22:07:18.101529: val_loss -0.7186 +2024-11-21 22:07:18.101608: Pseudo dice [0.7941] +2024-11-21 22:07:18.101684: Epoch time: 18.74 s +2024-11-21 22:07:18.984336: +2024-11-21 22:07:18.984550: Epoch 2099 +2024-11-21 22:07:18.984662: Current learning rate: 0.0076 +2024-11-21 22:07:38.602650: train_loss -0.7512 +2024-11-21 22:07:38.602879: val_loss -0.7366 +2024-11-21 22:07:38.602953: Pseudo dice [0.8188] +2024-11-21 22:07:38.603044: Epoch time: 19.62 s +2024-11-21 22:07:39.744003: +2024-11-21 22:07:39.744259: Epoch 2100 +2024-11-21 22:07:39.744416: Current learning rate: 0.0076 +2024-11-21 22:07:58.442268: train_loss -0.7555 +2024-11-21 22:07:58.442515: val_loss -0.7427 +2024-11-21 22:07:58.442594: Pseudo dice [0.8372] +2024-11-21 22:07:58.442672: Epoch time: 18.7 s +2024-11-21 22:07:59.329405: +2024-11-21 22:07:59.329690: Epoch 2101 +2024-11-21 22:07:59.329819: Current learning rate: 0.0076 +2024-11-21 22:08:18.120539: train_loss -0.7599 +2024-11-21 22:08:18.120749: val_loss -0.7142 +2024-11-21 22:08:18.120822: Pseudo dice [0.8086] +2024-11-21 22:08:18.120899: Epoch time: 18.79 s +2024-11-21 22:08:19.007654: +2024-11-21 22:08:19.007875: Epoch 2102 +2024-11-21 22:08:19.007994: Current learning rate: 0.0076 +2024-11-21 22:08:38.357566: train_loss -0.7575 +2024-11-21 22:08:38.357789: val_loss -0.6834 +2024-11-21 22:08:38.357865: Pseudo dice [0.7804] +2024-11-21 22:08:38.357941: Epoch time: 19.35 s +2024-11-21 22:08:39.194597: +2024-11-21 22:08:39.194803: Epoch 2103 +2024-11-21 22:08:39.194915: Current learning rate: 0.0076 +2024-11-21 22:08:58.600751: train_loss -0.7505 +2024-11-21 22:08:58.601549: val_loss -0.7267 +2024-11-21 22:08:58.601635: Pseudo dice [0.815] +2024-11-21 22:08:58.601716: Epoch time: 19.41 s +2024-11-21 22:08:59.446636: +2024-11-21 22:08:59.446883: Epoch 2104 +2024-11-21 22:08:59.447002: Current learning rate: 0.0076 +2024-11-21 22:09:17.636061: train_loss -0.7673 +2024-11-21 22:09:17.636296: val_loss -0.7591 +2024-11-21 22:09:17.636369: Pseudo dice [0.8364] +2024-11-21 22:09:17.642733: Epoch time: 18.19 s +2024-11-21 22:09:18.519746: +2024-11-21 22:09:18.519942: Epoch 2105 +2024-11-21 22:09:18.520059: Current learning rate: 0.0076 +2024-11-21 22:09:37.796571: train_loss -0.7867 +2024-11-21 22:09:37.796860: val_loss -0.7384 +2024-11-21 22:09:37.796946: Pseudo dice [0.8497] +2024-11-21 22:09:37.797032: Epoch time: 19.28 s +2024-11-21 22:09:38.693264: +2024-11-21 22:09:38.693526: Epoch 2106 +2024-11-21 22:09:38.693637: Current learning rate: 0.0076 +2024-11-21 22:09:55.995045: train_loss -0.7764 +2024-11-21 22:09:55.995272: val_loss -0.7662 +2024-11-21 22:09:55.995349: Pseudo dice [0.8371] +2024-11-21 22:09:55.995425: Epoch time: 17.3 s +2024-11-21 22:09:56.835371: +2024-11-21 22:09:56.835659: Epoch 2107 +2024-11-21 22:09:56.835771: Current learning rate: 0.00759 +2024-11-21 22:10:16.718271: train_loss -0.774 +2024-11-21 22:10:16.718512: val_loss -0.7606 +2024-11-21 22:10:16.718649: Pseudo dice [0.8254] +2024-11-21 22:10:16.718737: Epoch time: 19.88 s +2024-11-21 22:10:17.559755: +2024-11-21 22:10:17.559984: Epoch 2108 +2024-11-21 22:10:17.560102: Current learning rate: 0.00759 +2024-11-21 22:10:36.648560: train_loss -0.7742 +2024-11-21 22:10:36.675836: val_loss -0.7172 +2024-11-21 22:10:36.675979: Pseudo dice [0.8073] +2024-11-21 22:10:36.676071: Epoch time: 19.09 s +2024-11-21 22:10:37.515642: +2024-11-21 22:10:37.515831: Epoch 2109 +2024-11-21 22:10:37.515942: Current learning rate: 0.00759 +2024-11-21 22:10:56.087694: train_loss -0.7724 +2024-11-21 22:10:56.087905: val_loss -0.7275 +2024-11-21 22:10:56.087983: Pseudo dice [0.8265] +2024-11-21 22:10:56.088115: Epoch time: 18.57 s +2024-11-21 22:10:56.919966: +2024-11-21 22:10:56.920161: Epoch 2110 +2024-11-21 22:10:56.920265: Current learning rate: 0.00759 +2024-11-21 22:11:16.403106: train_loss -0.7623 +2024-11-21 22:11:16.403364: val_loss -0.7122 +2024-11-21 22:11:16.403437: Pseudo dice [0.7959] +2024-11-21 22:11:16.403517: Epoch time: 19.48 s +2024-11-21 22:11:17.270219: +2024-11-21 22:11:17.270415: Epoch 2111 +2024-11-21 22:11:17.270525: Current learning rate: 0.00759 +2024-11-21 22:11:35.960215: train_loss -0.7678 +2024-11-21 22:11:35.960439: val_loss -0.7219 +2024-11-21 22:11:35.960513: Pseudo dice [0.821] +2024-11-21 22:11:35.960587: Epoch time: 18.69 s +2024-11-21 22:11:36.827556: +2024-11-21 22:11:36.827843: Epoch 2112 +2024-11-21 22:11:36.827958: Current learning rate: 0.00759 +2024-11-21 22:11:55.791710: train_loss -0.7772 +2024-11-21 22:11:55.791941: val_loss -0.7517 +2024-11-21 22:11:55.792023: Pseudo dice [0.8304] +2024-11-21 22:11:55.792102: Epoch time: 18.96 s +2024-11-21 22:11:56.626527: +2024-11-21 22:11:56.626719: Epoch 2113 +2024-11-21 22:11:56.626830: Current learning rate: 0.00759 +2024-11-21 22:12:14.474445: train_loss -0.7655 +2024-11-21 22:12:14.474732: val_loss -0.7257 +2024-11-21 22:12:14.474813: Pseudo dice [0.8149] +2024-11-21 22:12:14.474896: Epoch time: 17.85 s +2024-11-21 22:12:15.296880: +2024-11-21 22:12:15.297099: Epoch 2114 +2024-11-21 22:12:15.297213: Current learning rate: 0.00759 +2024-11-21 22:12:35.263407: train_loss -0.7784 +2024-11-21 22:12:35.263645: val_loss -0.7471 +2024-11-21 22:12:35.263719: Pseudo dice [0.8226] +2024-11-21 22:12:35.263801: Epoch time: 19.97 s +2024-11-21 22:12:36.100772: +2024-11-21 22:12:36.100977: Epoch 2115 +2024-11-21 22:12:36.101093: Current learning rate: 0.00759 +2024-11-21 22:12:55.590328: train_loss -0.7595 +2024-11-21 22:12:55.590541: val_loss -0.7222 +2024-11-21 22:12:55.590619: Pseudo dice [0.821] +2024-11-21 22:12:55.590694: Epoch time: 19.49 s +2024-11-21 22:12:56.428294: +2024-11-21 22:12:56.428505: Epoch 2116 +2024-11-21 22:12:56.428620: Current learning rate: 0.00758 +2024-11-21 22:13:15.058430: train_loss -0.7661 +2024-11-21 22:13:15.058645: val_loss -0.7187 +2024-11-21 22:13:15.058717: Pseudo dice [0.8229] +2024-11-21 22:13:15.058796: Epoch time: 18.63 s +2024-11-21 22:13:15.914108: +2024-11-21 22:13:15.914321: Epoch 2117 +2024-11-21 22:13:15.914430: Current learning rate: 0.00758 +2024-11-21 22:13:34.524413: train_loss -0.7717 +2024-11-21 22:13:34.524699: val_loss -0.7572 +2024-11-21 22:13:34.524774: Pseudo dice [0.8234] +2024-11-21 22:13:34.524854: Epoch time: 18.61 s +2024-11-21 22:13:35.359328: +2024-11-21 22:13:35.359520: Epoch 2118 +2024-11-21 22:13:35.359631: Current learning rate: 0.00758 +2024-11-21 22:13:54.989661: train_loss -0.7723 +2024-11-21 22:13:54.989905: val_loss -0.7383 +2024-11-21 22:13:54.989981: Pseudo dice [0.8146] +2024-11-21 22:13:54.990077: Epoch time: 19.63 s +2024-11-21 22:13:55.823040: +2024-11-21 22:13:55.823263: Epoch 2119 +2024-11-21 22:13:55.823381: Current learning rate: 0.00758 +2024-11-21 22:14:13.606194: train_loss -0.7697 +2024-11-21 22:14:13.606406: val_loss -0.7632 +2024-11-21 22:14:13.606480: Pseudo dice [0.8226] +2024-11-21 22:14:13.606557: Epoch time: 17.78 s +2024-11-21 22:14:14.445104: +2024-11-21 22:14:14.445307: Epoch 2120 +2024-11-21 22:14:14.445419: Current learning rate: 0.00758 +2024-11-21 22:14:32.327464: train_loss -0.7649 +2024-11-21 22:14:32.327675: val_loss -0.7145 +2024-11-21 22:14:32.327746: Pseudo dice [0.7805] +2024-11-21 22:14:32.327823: Epoch time: 17.88 s +2024-11-21 22:14:33.260166: +2024-11-21 22:14:33.260379: Epoch 2121 +2024-11-21 22:14:33.260493: Current learning rate: 0.00758 +2024-11-21 22:14:51.276218: train_loss -0.7637 +2024-11-21 22:14:51.276477: val_loss -0.7444 +2024-11-21 22:14:51.276551: Pseudo dice [0.8206] +2024-11-21 22:14:51.276708: Epoch time: 18.02 s +2024-11-21 22:14:52.117904: +2024-11-21 22:14:52.118169: Epoch 2122 +2024-11-21 22:14:52.118281: Current learning rate: 0.00758 +2024-11-21 22:15:10.919651: train_loss -0.7605 +2024-11-21 22:15:10.919887: val_loss -0.7326 +2024-11-21 22:15:10.919960: Pseudo dice [0.8042] +2024-11-21 22:15:10.920040: Epoch time: 18.8 s +2024-11-21 22:15:11.911295: +2024-11-21 22:15:11.911522: Epoch 2123 +2024-11-21 22:15:11.911641: Current learning rate: 0.00758 +2024-11-21 22:15:31.120908: train_loss -0.7714 +2024-11-21 22:15:31.121133: val_loss -0.7459 +2024-11-21 22:15:31.121208: Pseudo dice [0.8304] +2024-11-21 22:15:31.121286: Epoch time: 19.21 s +2024-11-21 22:15:31.962354: +2024-11-21 22:15:31.962550: Epoch 2124 +2024-11-21 22:15:31.962657: Current learning rate: 0.00758 +2024-11-21 22:15:50.748506: train_loss -0.779 +2024-11-21 22:15:50.748749: val_loss -0.7637 +2024-11-21 22:15:50.748832: Pseudo dice [0.8219] +2024-11-21 22:15:50.748917: Epoch time: 18.79 s +2024-11-21 22:15:51.756418: +2024-11-21 22:15:51.756616: Epoch 2125 +2024-11-21 22:15:51.756731: Current learning rate: 0.00757 +2024-11-21 22:16:10.141470: train_loss -0.7738 +2024-11-21 22:16:10.141671: val_loss -0.752 +2024-11-21 22:16:10.141744: Pseudo dice [0.8252] +2024-11-21 22:16:10.141823: Epoch time: 18.39 s +2024-11-21 22:16:10.960310: +2024-11-21 22:16:10.960531: Epoch 2126 +2024-11-21 22:16:10.960646: Current learning rate: 0.00757 +2024-11-21 22:16:29.763540: train_loss -0.7706 +2024-11-21 22:16:29.763747: val_loss -0.769 +2024-11-21 22:16:29.763821: Pseudo dice [0.8295] +2024-11-21 22:16:29.763894: Epoch time: 18.8 s +2024-11-21 22:16:30.591188: +2024-11-21 22:16:30.591392: Epoch 2127 +2024-11-21 22:16:30.591501: Current learning rate: 0.00757 +2024-11-21 22:16:49.158554: train_loss -0.7629 +2024-11-21 22:16:49.158776: val_loss -0.6887 +2024-11-21 22:16:49.158859: Pseudo dice [0.8217] +2024-11-21 22:16:49.158942: Epoch time: 18.57 s +2024-11-21 22:16:49.998473: +2024-11-21 22:16:49.998681: Epoch 2128 +2024-11-21 22:16:49.998796: Current learning rate: 0.00757 +2024-11-21 22:17:08.332560: train_loss -0.7554 +2024-11-21 22:17:08.337264: val_loss -0.7252 +2024-11-21 22:17:08.337384: Pseudo dice [0.8027] +2024-11-21 22:17:08.337471: Epoch time: 18.33 s +2024-11-21 22:17:09.375232: +2024-11-21 22:17:09.375460: Epoch 2129 +2024-11-21 22:17:09.375571: Current learning rate: 0.00757 +2024-11-21 22:17:28.392348: train_loss -0.7679 +2024-11-21 22:17:28.392567: val_loss -0.7247 +2024-11-21 22:17:28.392641: Pseudo dice [0.8111] +2024-11-21 22:17:28.392719: Epoch time: 19.02 s +2024-11-21 22:17:29.265303: +2024-11-21 22:17:29.265564: Epoch 2130 +2024-11-21 22:17:29.265669: Current learning rate: 0.00757 +2024-11-21 22:17:47.754576: train_loss -0.7664 +2024-11-21 22:17:47.754785: val_loss -0.7272 +2024-11-21 22:17:47.754857: Pseudo dice [0.8193] +2024-11-21 22:17:47.754936: Epoch time: 18.49 s +2024-11-21 22:17:48.583507: +2024-11-21 22:17:48.583707: Epoch 2131 +2024-11-21 22:17:48.583814: Current learning rate: 0.00757 +2024-11-21 22:18:07.245690: train_loss -0.7617 +2024-11-21 22:18:07.245929: val_loss -0.7436 +2024-11-21 22:18:07.246010: Pseudo dice [0.8283] +2024-11-21 22:18:07.246099: Epoch time: 18.66 s +2024-11-21 22:18:08.172434: +2024-11-21 22:18:08.172649: Epoch 2132 +2024-11-21 22:18:08.172761: Current learning rate: 0.00757 +2024-11-21 22:18:26.750185: train_loss -0.7611 +2024-11-21 22:18:26.750404: val_loss -0.7231 +2024-11-21 22:18:26.750481: Pseudo dice [0.8093] +2024-11-21 22:18:26.750559: Epoch time: 18.58 s +2024-11-21 22:18:27.592259: +2024-11-21 22:18:27.592452: Epoch 2133 +2024-11-21 22:18:27.592561: Current learning rate: 0.00756 +2024-11-21 22:18:46.620576: train_loss -0.7598 +2024-11-21 22:18:46.620791: val_loss -0.7018 +2024-11-21 22:18:46.620867: Pseudo dice [0.814] +2024-11-21 22:18:46.626097: Epoch time: 19.03 s +2024-11-21 22:18:47.734200: +2024-11-21 22:18:47.734420: Epoch 2134 +2024-11-21 22:18:47.734533: Current learning rate: 0.00756 +2024-11-21 22:19:05.845151: train_loss -0.7761 +2024-11-21 22:19:05.845381: val_loss -0.7517 +2024-11-21 22:19:05.845455: Pseudo dice [0.8446] +2024-11-21 22:19:05.845535: Epoch time: 18.11 s +2024-11-21 22:19:06.686802: +2024-11-21 22:19:06.687083: Epoch 2135 +2024-11-21 22:19:06.687195: Current learning rate: 0.00756 +2024-11-21 22:19:24.986217: train_loss -0.7739 +2024-11-21 22:19:24.986461: val_loss -0.7388 +2024-11-21 22:19:24.986542: Pseudo dice [0.8304] +2024-11-21 22:19:24.986629: Epoch time: 18.3 s +2024-11-21 22:19:25.824144: +2024-11-21 22:19:25.824409: Epoch 2136 +2024-11-21 22:19:25.824529: Current learning rate: 0.00756 +2024-11-21 22:19:44.169628: train_loss -0.7726 +2024-11-21 22:19:44.169841: val_loss -0.7498 +2024-11-21 22:19:44.169915: Pseudo dice [0.8277] +2024-11-21 22:19:44.169989: Epoch time: 18.35 s +2024-11-21 22:19:45.005008: +2024-11-21 22:19:45.005214: Epoch 2137 +2024-11-21 22:19:45.005330: Current learning rate: 0.00756 +2024-11-21 22:20:03.823361: train_loss -0.7653 +2024-11-21 22:20:03.823573: val_loss -0.7459 +2024-11-21 22:20:03.823652: Pseudo dice [0.8199] +2024-11-21 22:20:03.823728: Epoch time: 18.82 s +2024-11-21 22:20:04.666160: +2024-11-21 22:20:04.666407: Epoch 2138 +2024-11-21 22:20:04.666518: Current learning rate: 0.00756 +2024-11-21 22:20:22.510320: train_loss -0.7601 +2024-11-21 22:20:22.510572: val_loss -0.7283 +2024-11-21 22:20:22.510650: Pseudo dice [0.7993] +2024-11-21 22:20:22.510734: Epoch time: 17.84 s +2024-11-21 22:20:23.383269: +2024-11-21 22:20:23.383479: Epoch 2139 +2024-11-21 22:20:23.383596: Current learning rate: 0.00756 +2024-11-21 22:20:42.292466: train_loss -0.766 +2024-11-21 22:20:42.292687: val_loss -0.7313 +2024-11-21 22:20:42.292765: Pseudo dice [0.823] +2024-11-21 22:20:42.292843: Epoch time: 18.91 s +2024-11-21 22:20:43.132601: +2024-11-21 22:20:43.132806: Epoch 2140 +2024-11-21 22:20:43.132919: Current learning rate: 0.00756 +2024-11-21 22:21:02.301568: train_loss -0.7779 +2024-11-21 22:21:02.301781: val_loss -0.7572 +2024-11-21 22:21:02.301855: Pseudo dice [0.8417] +2024-11-21 22:21:02.301929: Epoch time: 19.17 s +2024-11-21 22:21:03.135926: +2024-11-21 22:21:03.136132: Epoch 2141 +2024-11-21 22:21:03.136241: Current learning rate: 0.00756 +2024-11-21 22:21:22.019389: train_loss -0.7781 +2024-11-21 22:21:22.020820: val_loss -0.7609 +2024-11-21 22:21:22.020900: Pseudo dice [0.8526] +2024-11-21 22:21:22.020977: Epoch time: 18.88 s +2024-11-21 22:21:22.857974: +2024-11-21 22:21:22.858190: Epoch 2142 +2024-11-21 22:21:22.858302: Current learning rate: 0.00755 +2024-11-21 22:21:41.826686: train_loss -0.7788 +2024-11-21 22:21:41.826922: val_loss -0.7437 +2024-11-21 22:21:41.827008: Pseudo dice [0.8304] +2024-11-21 22:21:41.827094: Epoch time: 18.97 s +2024-11-21 22:21:42.665245: +2024-11-21 22:21:42.665463: Epoch 2143 +2024-11-21 22:21:42.665581: Current learning rate: 0.00755 +2024-11-21 22:22:03.279785: train_loss -0.778 +2024-11-21 22:22:03.280010: val_loss -0.709 +2024-11-21 22:22:03.280086: Pseudo dice [0.8254] +2024-11-21 22:22:03.280225: Epoch time: 20.62 s +2024-11-21 22:22:04.191084: +2024-11-21 22:22:04.191326: Epoch 2144 +2024-11-21 22:22:04.191438: Current learning rate: 0.00755 +2024-11-21 22:22:21.819664: train_loss -0.7836 +2024-11-21 22:22:21.819878: val_loss -0.7239 +2024-11-21 22:22:21.820043: Pseudo dice [0.8344] +2024-11-21 22:22:21.820125: Epoch time: 17.63 s +2024-11-21 22:22:22.659035: +2024-11-21 22:22:22.659237: Epoch 2145 +2024-11-21 22:22:22.659353: Current learning rate: 0.00755 +2024-11-21 22:22:41.449806: train_loss -0.7722 +2024-11-21 22:22:41.450060: val_loss -0.7633 +2024-11-21 22:22:41.450136: Pseudo dice [0.8433] +2024-11-21 22:22:41.450222: Epoch time: 18.79 s +2024-11-21 22:22:41.450285: Yayy! New best EMA pseudo Dice: 0.828 +2024-11-21 22:22:42.877602: +2024-11-21 22:22:42.877878: Epoch 2146 +2024-11-21 22:22:42.877989: Current learning rate: 0.00755 +2024-11-21 22:23:01.765940: train_loss -0.7706 +2024-11-21 22:23:01.766183: val_loss -0.7298 +2024-11-21 22:23:01.766261: Pseudo dice [0.8097] +2024-11-21 22:23:01.766335: Epoch time: 18.89 s +2024-11-21 22:23:02.592357: +2024-11-21 22:23:02.592554: Epoch 2147 +2024-11-21 22:23:02.592664: Current learning rate: 0.00755 +2024-11-21 22:23:20.813730: train_loss -0.7757 +2024-11-21 22:23:20.813949: val_loss -0.7378 +2024-11-21 22:23:20.814039: Pseudo dice [0.8314] +2024-11-21 22:23:20.814136: Epoch time: 18.22 s +2024-11-21 22:23:21.649444: +2024-11-21 22:23:21.649686: Epoch 2148 +2024-11-21 22:23:21.649811: Current learning rate: 0.00755 +2024-11-21 22:23:39.489097: train_loss -0.7843 +2024-11-21 22:23:39.489363: val_loss -0.7494 +2024-11-21 22:23:39.489443: Pseudo dice [0.8372] +2024-11-21 22:23:39.489531: Epoch time: 17.84 s +2024-11-21 22:23:40.360404: +2024-11-21 22:23:40.360644: Epoch 2149 +2024-11-21 22:23:40.360754: Current learning rate: 0.00755 +2024-11-21 22:23:58.883073: train_loss -0.7944 +2024-11-21 22:23:58.883283: val_loss -0.755 +2024-11-21 22:23:58.883358: Pseudo dice [0.8272] +2024-11-21 22:23:58.883433: Epoch time: 18.52 s +2024-11-21 22:23:59.924219: +2024-11-21 22:23:59.924420: Epoch 2150 +2024-11-21 22:23:59.924533: Current learning rate: 0.00755 +2024-11-21 22:24:18.654898: train_loss -0.7717 +2024-11-21 22:24:18.655133: val_loss -0.7478 +2024-11-21 22:24:18.655207: Pseudo dice [0.8171] +2024-11-21 22:24:18.655282: Epoch time: 18.73 s +2024-11-21 22:24:19.481766: +2024-11-21 22:24:19.481973: Epoch 2151 +2024-11-21 22:24:19.482091: Current learning rate: 0.00754 +2024-11-21 22:24:37.155625: train_loss -0.7619 +2024-11-21 22:24:37.155848: val_loss -0.7326 +2024-11-21 22:24:37.155925: Pseudo dice [0.7891] +2024-11-21 22:24:37.156010: Epoch time: 17.67 s +2024-11-21 22:24:38.034508: +2024-11-21 22:24:38.034717: Epoch 2152 +2024-11-21 22:24:38.034829: Current learning rate: 0.00754 +2024-11-21 22:24:56.044072: train_loss -0.7572 +2024-11-21 22:24:56.044349: val_loss -0.6981 +2024-11-21 22:24:56.044428: Pseudo dice [0.8197] +2024-11-21 22:24:56.044506: Epoch time: 18.01 s +2024-11-21 22:24:56.883623: +2024-11-21 22:24:56.883890: Epoch 2153 +2024-11-21 22:24:56.884012: Current learning rate: 0.00754 +2024-11-21 22:25:14.935348: train_loss -0.7694 +2024-11-21 22:25:14.935582: val_loss -0.7305 +2024-11-21 22:25:14.935654: Pseudo dice [0.8118] +2024-11-21 22:25:14.935733: Epoch time: 18.05 s +2024-11-21 22:25:15.894442: +2024-11-21 22:25:15.894663: Epoch 2154 +2024-11-21 22:25:15.894778: Current learning rate: 0.00754 +2024-11-21 22:25:34.798862: train_loss -0.773 +2024-11-21 22:25:34.799083: val_loss -0.7402 +2024-11-21 22:25:34.799161: Pseudo dice [0.8178] +2024-11-21 22:25:34.799237: Epoch time: 18.91 s +2024-11-21 22:25:35.636978: +2024-11-21 22:25:35.637193: Epoch 2155 +2024-11-21 22:25:35.637306: Current learning rate: 0.00754 +2024-11-21 22:25:54.679856: train_loss -0.7688 +2024-11-21 22:25:54.680132: val_loss -0.7214 +2024-11-21 22:25:54.680207: Pseudo dice [0.8191] +2024-11-21 22:25:54.680283: Epoch time: 19.04 s +2024-11-21 22:25:55.512429: +2024-11-21 22:25:55.512637: Epoch 2156 +2024-11-21 22:25:55.512748: Current learning rate: 0.00754 +2024-11-21 22:26:13.993897: train_loss -0.7638 +2024-11-21 22:26:13.994178: val_loss -0.7245 +2024-11-21 22:26:13.994255: Pseudo dice [0.81] +2024-11-21 22:26:13.994339: Epoch time: 18.48 s +2024-11-21 22:26:14.839425: +2024-11-21 22:26:14.839628: Epoch 2157 +2024-11-21 22:26:14.839741: Current learning rate: 0.00754 +2024-11-21 22:26:32.533686: train_loss -0.7602 +2024-11-21 22:26:32.533913: val_loss -0.735 +2024-11-21 22:26:32.533988: Pseudo dice [0.8154] +2024-11-21 22:26:32.534078: Epoch time: 17.7 s +2024-11-21 22:26:33.786298: +2024-11-21 22:26:33.786511: Epoch 2158 +2024-11-21 22:26:33.786623: Current learning rate: 0.00754 +2024-11-21 22:26:53.071910: train_loss -0.7672 +2024-11-21 22:26:53.072175: val_loss -0.7399 +2024-11-21 22:26:53.072258: Pseudo dice [0.8273] +2024-11-21 22:26:53.072337: Epoch time: 19.29 s +2024-11-21 22:26:53.920502: +2024-11-21 22:26:53.920764: Epoch 2159 +2024-11-21 22:26:53.920879: Current learning rate: 0.00753 +2024-11-21 22:27:11.365160: train_loss -0.7714 +2024-11-21 22:27:11.365407: val_loss -0.7386 +2024-11-21 22:27:11.365479: Pseudo dice [0.8241] +2024-11-21 22:27:11.365561: Epoch time: 17.45 s +2024-11-21 22:27:12.328981: +2024-11-21 22:27:12.329236: Epoch 2160 +2024-11-21 22:27:12.329366: Current learning rate: 0.00753 +2024-11-21 22:27:30.972023: train_loss -0.766 +2024-11-21 22:27:30.972234: val_loss -0.7574 +2024-11-21 22:27:30.972309: Pseudo dice [0.8235] +2024-11-21 22:27:30.972387: Epoch time: 18.64 s +2024-11-21 22:27:31.813096: +2024-11-21 22:27:31.813359: Epoch 2161 +2024-11-21 22:27:31.813479: Current learning rate: 0.00753 +2024-11-21 22:27:50.162110: train_loss -0.7686 +2024-11-21 22:27:50.162324: val_loss -0.744 +2024-11-21 22:27:50.162398: Pseudo dice [0.8234] +2024-11-21 22:27:50.162476: Epoch time: 18.35 s +2024-11-21 22:27:51.003946: +2024-11-21 22:27:51.004156: Epoch 2162 +2024-11-21 22:27:51.004267: Current learning rate: 0.00753 +2024-11-21 22:28:08.951794: train_loss -0.7681 +2024-11-21 22:28:08.952022: val_loss -0.7148 +2024-11-21 22:28:08.952335: Pseudo dice [0.8162] +2024-11-21 22:28:08.952424: Epoch time: 17.95 s +2024-11-21 22:28:09.792923: +2024-11-21 22:28:09.793131: Epoch 2163 +2024-11-21 22:28:09.793245: Current learning rate: 0.00753 +2024-11-21 22:28:28.635319: train_loss -0.782 +2024-11-21 22:28:28.636730: val_loss -0.7518 +2024-11-21 22:28:28.636857: Pseudo dice [0.8314] +2024-11-21 22:28:28.636974: Epoch time: 18.84 s +2024-11-21 22:28:29.500016: +2024-11-21 22:28:29.500393: Epoch 2164 +2024-11-21 22:28:29.500517: Current learning rate: 0.00753 +2024-11-21 22:28:49.034011: train_loss -0.7777 +2024-11-21 22:28:49.034233: val_loss -0.7424 +2024-11-21 22:28:49.034311: Pseudo dice [0.8212] +2024-11-21 22:28:49.034390: Epoch time: 19.53 s +2024-11-21 22:28:49.916773: +2024-11-21 22:28:49.917001: Epoch 2165 +2024-11-21 22:28:49.917121: Current learning rate: 0.00753 +2024-11-21 22:29:08.765204: train_loss -0.7786 +2024-11-21 22:29:08.765418: val_loss -0.7314 +2024-11-21 22:29:08.765493: Pseudo dice [0.7864] +2024-11-21 22:29:08.765572: Epoch time: 18.85 s +2024-11-21 22:29:09.598196: +2024-11-21 22:29:09.598413: Epoch 2166 +2024-11-21 22:29:09.598529: Current learning rate: 0.00753 +2024-11-21 22:29:28.677593: train_loss -0.7605 +2024-11-21 22:29:28.677839: val_loss -0.7144 +2024-11-21 22:29:28.677913: Pseudo dice [0.8197] +2024-11-21 22:29:28.683211: Epoch time: 19.08 s +2024-11-21 22:29:29.537441: +2024-11-21 22:29:29.537632: Epoch 2167 +2024-11-21 22:29:29.537743: Current learning rate: 0.00753 +2024-11-21 22:29:48.286219: train_loss -0.7616 +2024-11-21 22:29:48.286429: val_loss -0.7562 +2024-11-21 22:29:48.286502: Pseudo dice [0.8243] +2024-11-21 22:29:48.286656: Epoch time: 18.75 s +2024-11-21 22:29:49.121626: +2024-11-21 22:29:49.121837: Epoch 2168 +2024-11-21 22:29:49.121950: Current learning rate: 0.00752 +2024-11-21 22:30:08.675353: train_loss -0.7759 +2024-11-21 22:30:08.675571: val_loss -0.7188 +2024-11-21 22:30:08.675647: Pseudo dice [0.8221] +2024-11-21 22:30:08.675724: Epoch time: 19.55 s +2024-11-21 22:30:09.512599: +2024-11-21 22:30:09.512829: Epoch 2169 +2024-11-21 22:30:09.512946: Current learning rate: 0.00752 +2024-11-21 22:30:27.780797: train_loss -0.7742 +2024-11-21 22:30:27.782386: val_loss -0.735 +2024-11-21 22:30:27.782495: Pseudo dice [0.8238] +2024-11-21 22:30:27.782578: Epoch time: 18.27 s +2024-11-21 22:30:29.042196: +2024-11-21 22:30:29.042492: Epoch 2170 +2024-11-21 22:30:29.042613: Current learning rate: 0.00752 +2024-11-21 22:30:46.871238: train_loss -0.7785 +2024-11-21 22:30:46.871491: val_loss -0.7235 +2024-11-21 22:30:46.871566: Pseudo dice [0.8376] +2024-11-21 22:30:46.871646: Epoch time: 17.83 s +2024-11-21 22:30:47.810963: +2024-11-21 22:30:47.811170: Epoch 2171 +2024-11-21 22:30:47.811281: Current learning rate: 0.00752 +2024-11-21 22:31:06.016410: train_loss -0.7773 +2024-11-21 22:31:06.016623: val_loss -0.7308 +2024-11-21 22:31:06.016704: Pseudo dice [0.8127] +2024-11-21 22:31:06.035141: Epoch time: 18.21 s +2024-11-21 22:31:06.870277: +2024-11-21 22:31:06.870509: Epoch 2172 +2024-11-21 22:31:06.870626: Current learning rate: 0.00752 +2024-11-21 22:31:25.054878: train_loss -0.7841 +2024-11-21 22:31:25.055129: val_loss -0.7417 +2024-11-21 22:31:25.055208: Pseudo dice [0.8367] +2024-11-21 22:31:25.055287: Epoch time: 18.19 s +2024-11-21 22:31:25.891964: +2024-11-21 22:31:25.892171: Epoch 2173 +2024-11-21 22:31:25.892280: Current learning rate: 0.00752 +2024-11-21 22:31:43.863093: train_loss -0.7719 +2024-11-21 22:31:43.863350: val_loss -0.7532 +2024-11-21 22:31:43.863429: Pseudo dice [0.8127] +2024-11-21 22:31:43.863513: Epoch time: 17.97 s +2024-11-21 22:31:44.704036: +2024-11-21 22:31:44.704278: Epoch 2174 +2024-11-21 22:31:44.704390: Current learning rate: 0.00752 +2024-11-21 22:32:03.848105: train_loss -0.7703 +2024-11-21 22:32:03.848360: val_loss -0.7364 +2024-11-21 22:32:03.848431: Pseudo dice [0.7986] +2024-11-21 22:32:03.848503: Epoch time: 19.14 s +2024-11-21 22:32:04.875256: +2024-11-21 22:32:04.875630: Epoch 2175 +2024-11-21 22:32:04.875742: Current learning rate: 0.00752 +2024-11-21 22:32:22.497877: train_loss -0.7891 +2024-11-21 22:32:22.498098: val_loss -0.761 +2024-11-21 22:32:22.498170: Pseudo dice [0.8318] +2024-11-21 22:32:22.498246: Epoch time: 17.62 s +2024-11-21 22:32:23.331868: +2024-11-21 22:32:23.332088: Epoch 2176 +2024-11-21 22:32:23.332201: Current learning rate: 0.00751 +2024-11-21 22:32:42.720039: train_loss -0.7782 +2024-11-21 22:32:42.720263: val_loss -0.7344 +2024-11-21 22:32:42.720341: Pseudo dice [0.8224] +2024-11-21 22:32:42.720426: Epoch time: 19.39 s +2024-11-21 22:32:43.561874: +2024-11-21 22:32:43.562086: Epoch 2177 +2024-11-21 22:32:43.562199: Current learning rate: 0.00751 +2024-11-21 22:33:01.974184: train_loss -0.7747 +2024-11-21 22:33:01.974507: val_loss -0.7424 +2024-11-21 22:33:01.974587: Pseudo dice [0.8089] +2024-11-21 22:33:01.974668: Epoch time: 18.41 s +2024-11-21 22:33:02.815201: +2024-11-21 22:33:02.815420: Epoch 2178 +2024-11-21 22:33:02.815534: Current learning rate: 0.00751 +2024-11-21 22:33:21.954772: train_loss -0.7723 +2024-11-21 22:33:21.955410: val_loss -0.7277 +2024-11-21 22:33:21.955488: Pseudo dice [0.8304] +2024-11-21 22:33:21.955566: Epoch time: 19.14 s +2024-11-21 22:33:22.792910: +2024-11-21 22:33:22.793180: Epoch 2179 +2024-11-21 22:33:22.793299: Current learning rate: 0.00751 +2024-11-21 22:33:41.838518: train_loss -0.782 +2024-11-21 22:33:41.838734: val_loss -0.7432 +2024-11-21 22:33:41.838812: Pseudo dice [0.8298] +2024-11-21 22:33:41.838923: Epoch time: 19.05 s +2024-11-21 22:33:42.673385: +2024-11-21 22:33:42.673580: Epoch 2180 +2024-11-21 22:33:42.673695: Current learning rate: 0.00751 +2024-11-21 22:34:01.755143: train_loss -0.7777 +2024-11-21 22:34:01.755384: val_loss -0.7285 +2024-11-21 22:34:01.755458: Pseudo dice [0.8193] +2024-11-21 22:34:01.755539: Epoch time: 19.08 s +2024-11-21 22:34:02.595348: +2024-11-21 22:34:02.595564: Epoch 2181 +2024-11-21 22:34:02.595673: Current learning rate: 0.00751 +2024-11-21 22:34:21.664609: train_loss -0.7696 +2024-11-21 22:34:21.664822: val_loss -0.7376 +2024-11-21 22:34:21.664900: Pseudo dice [0.8142] +2024-11-21 22:34:21.664978: Epoch time: 19.07 s +2024-11-21 22:34:22.908720: +2024-11-21 22:34:22.908954: Epoch 2182 +2024-11-21 22:34:22.909070: Current learning rate: 0.00751 +2024-11-21 22:34:42.524654: train_loss -0.7653 +2024-11-21 22:34:42.524928: val_loss -0.7336 +2024-11-21 22:34:42.525007: Pseudo dice [0.8117] +2024-11-21 22:34:42.525082: Epoch time: 19.62 s +2024-11-21 22:34:43.375232: +2024-11-21 22:34:43.375498: Epoch 2183 +2024-11-21 22:34:43.375613: Current learning rate: 0.00751 +2024-11-21 22:35:01.207940: train_loss -0.7582 +2024-11-21 22:35:01.208185: val_loss -0.7471 +2024-11-21 22:35:01.208266: Pseudo dice [0.8274] +2024-11-21 22:35:01.208350: Epoch time: 17.83 s +2024-11-21 22:35:02.045319: +2024-11-21 22:35:02.045544: Epoch 2184 +2024-11-21 22:35:02.045655: Current learning rate: 0.00751 +2024-11-21 22:35:21.640158: train_loss -0.7636 +2024-11-21 22:35:21.642626: val_loss -0.7499 +2024-11-21 22:35:21.642745: Pseudo dice [0.84] +2024-11-21 22:35:21.642826: Epoch time: 19.6 s +2024-11-21 22:35:22.486683: +2024-11-21 22:35:22.486883: Epoch 2185 +2024-11-21 22:35:22.486999: Current learning rate: 0.0075 +2024-11-21 22:35:40.743110: train_loss -0.7736 +2024-11-21 22:35:40.743347: val_loss -0.7225 +2024-11-21 22:35:40.743426: Pseudo dice [0.812] +2024-11-21 22:35:40.743505: Epoch time: 18.26 s +2024-11-21 22:35:41.613535: +2024-11-21 22:35:41.613892: Epoch 2186 +2024-11-21 22:35:41.614013: Current learning rate: 0.0075 +2024-11-21 22:35:59.589606: train_loss -0.7728 +2024-11-21 22:35:59.589899: val_loss -0.7288 +2024-11-21 22:35:59.589977: Pseudo dice [0.8149] +2024-11-21 22:35:59.590064: Epoch time: 17.98 s +2024-11-21 22:36:00.430341: +2024-11-21 22:36:00.430527: Epoch 2187 +2024-11-21 22:36:00.430636: Current learning rate: 0.0075 +2024-11-21 22:36:19.486851: train_loss -0.771 +2024-11-21 22:36:19.487095: val_loss -0.7022 +2024-11-21 22:36:19.487173: Pseudo dice [0.8173] +2024-11-21 22:36:19.487259: Epoch time: 19.06 s +2024-11-21 22:36:20.336419: +2024-11-21 22:36:20.336634: Epoch 2188 +2024-11-21 22:36:20.336745: Current learning rate: 0.0075 +2024-11-21 22:36:38.308863: train_loss -0.7668 +2024-11-21 22:36:38.309293: val_loss -0.7279 +2024-11-21 22:36:38.309385: Pseudo dice [0.8158] +2024-11-21 22:36:38.309466: Epoch time: 17.97 s +2024-11-21 22:36:39.364363: +2024-11-21 22:36:39.364564: Epoch 2189 +2024-11-21 22:36:39.364684: Current learning rate: 0.0075 +2024-11-21 22:36:58.059178: train_loss -0.7745 +2024-11-21 22:36:58.059407: val_loss -0.7214 +2024-11-21 22:36:58.059481: Pseudo dice [0.8087] +2024-11-21 22:36:58.059560: Epoch time: 18.7 s +2024-11-21 22:36:58.940421: +2024-11-21 22:36:58.940639: Epoch 2190 +2024-11-21 22:36:58.940751: Current learning rate: 0.0075 +2024-11-21 22:37:18.151694: train_loss -0.7778 +2024-11-21 22:37:18.151969: val_loss -0.7249 +2024-11-21 22:37:18.152056: Pseudo dice [0.8107] +2024-11-21 22:37:18.152136: Epoch time: 19.21 s +2024-11-21 22:37:18.993919: +2024-11-21 22:37:18.994132: Epoch 2191 +2024-11-21 22:37:18.994244: Current learning rate: 0.0075 +2024-11-21 22:37:39.166767: train_loss -0.7778 +2024-11-21 22:37:39.166986: val_loss -0.7226 +2024-11-21 22:37:39.167070: Pseudo dice [0.8039] +2024-11-21 22:37:39.167149: Epoch time: 20.17 s +2024-11-21 22:37:40.040224: +2024-11-21 22:37:40.040420: Epoch 2192 +2024-11-21 22:37:40.040535: Current learning rate: 0.0075 +2024-11-21 22:37:58.481937: train_loss -0.7827 +2024-11-21 22:37:58.482167: val_loss -0.7639 +2024-11-21 22:37:58.482243: Pseudo dice [0.8364] +2024-11-21 22:37:58.482321: Epoch time: 18.44 s +2024-11-21 22:37:59.322018: +2024-11-21 22:37:59.322244: Epoch 2193 +2024-11-21 22:37:59.322354: Current learning rate: 0.0075 +2024-11-21 22:38:17.672706: train_loss -0.7702 +2024-11-21 22:38:17.672949: val_loss -0.746 +2024-11-21 22:38:17.673039: Pseudo dice [0.8255] +2024-11-21 22:38:17.673121: Epoch time: 18.35 s +2024-11-21 22:38:18.934862: +2024-11-21 22:38:18.935115: Epoch 2194 +2024-11-21 22:38:18.935227: Current learning rate: 0.00749 +2024-11-21 22:38:37.258885: train_loss -0.7616 +2024-11-21 22:38:37.259197: val_loss -0.6928 +2024-11-21 22:38:37.259294: Pseudo dice [0.7813] +2024-11-21 22:38:37.259377: Epoch time: 18.32 s +2024-11-21 22:38:38.098447: +2024-11-21 22:38:38.098675: Epoch 2195 +2024-11-21 22:38:38.098802: Current learning rate: 0.00749 +2024-11-21 22:38:56.735926: train_loss -0.7671 +2024-11-21 22:38:56.736139: val_loss -0.7619 +2024-11-21 22:38:56.736212: Pseudo dice [0.8405] +2024-11-21 22:38:56.736419: Epoch time: 18.64 s +2024-11-21 22:38:57.624811: +2024-11-21 22:38:57.625024: Epoch 2196 +2024-11-21 22:38:57.625137: Current learning rate: 0.00749 +2024-11-21 22:39:16.008400: train_loss -0.778 +2024-11-21 22:39:16.008623: val_loss -0.77 +2024-11-21 22:39:16.008708: Pseudo dice [0.8211] +2024-11-21 22:39:16.008801: Epoch time: 18.38 s +2024-11-21 22:39:17.025915: +2024-11-21 22:39:17.026149: Epoch 2197 +2024-11-21 22:39:17.041068: Current learning rate: 0.00749 +2024-11-21 22:39:34.431798: train_loss -0.7784 +2024-11-21 22:39:34.432044: val_loss -0.7356 +2024-11-21 22:39:34.432119: Pseudo dice [0.8289] +2024-11-21 22:39:34.432203: Epoch time: 17.41 s +2024-11-21 22:39:35.272220: +2024-11-21 22:39:35.272431: Epoch 2198 +2024-11-21 22:39:35.272544: Current learning rate: 0.00749 +2024-11-21 22:39:53.534028: train_loss -0.7844 +2024-11-21 22:39:53.534252: val_loss -0.7406 +2024-11-21 22:39:53.534332: Pseudo dice [0.8208] +2024-11-21 22:39:53.534412: Epoch time: 18.26 s +2024-11-21 22:39:54.371916: +2024-11-21 22:39:54.372138: Epoch 2199 +2024-11-21 22:39:54.372254: Current learning rate: 0.00749 +2024-11-21 22:40:12.730202: train_loss -0.7827 +2024-11-21 22:40:12.730417: val_loss -0.7173 +2024-11-21 22:40:12.730491: Pseudo dice [0.8038] +2024-11-21 22:40:12.730567: Epoch time: 18.36 s +2024-11-21 22:40:13.783326: +2024-11-21 22:40:13.783603: Epoch 2200 +2024-11-21 22:40:13.783720: Current learning rate: 0.00749 +2024-11-21 22:40:33.232046: train_loss -0.7838 +2024-11-21 22:40:33.232270: val_loss -0.7579 +2024-11-21 22:40:33.232352: Pseudo dice [0.8195] +2024-11-21 22:40:33.232429: Epoch time: 19.45 s +2024-11-21 22:40:34.066288: +2024-11-21 22:40:34.066493: Epoch 2201 +2024-11-21 22:40:34.066603: Current learning rate: 0.00749 +2024-11-21 22:40:52.387962: train_loss -0.7695 +2024-11-21 22:40:52.388207: val_loss -0.732 +2024-11-21 22:40:52.388282: Pseudo dice [0.8197] +2024-11-21 22:40:52.388365: Epoch time: 18.32 s +2024-11-21 22:40:53.391682: +2024-11-21 22:40:53.391949: Epoch 2202 +2024-11-21 22:40:53.392068: Current learning rate: 0.00748 +2024-11-21 22:41:11.569103: train_loss -0.7715 +2024-11-21 22:41:11.569316: val_loss -0.7549 +2024-11-21 22:41:11.569392: Pseudo dice [0.8173] +2024-11-21 22:41:11.569469: Epoch time: 18.18 s +2024-11-21 22:41:12.407370: +2024-11-21 22:41:12.407638: Epoch 2203 +2024-11-21 22:41:12.407747: Current learning rate: 0.00748 +2024-11-21 22:41:31.668070: train_loss -0.7676 +2024-11-21 22:41:31.668290: val_loss -0.7315 +2024-11-21 22:41:31.668363: Pseudo dice [0.7805] +2024-11-21 22:41:31.668441: Epoch time: 19.26 s +2024-11-21 22:41:32.506790: +2024-11-21 22:41:32.507000: Epoch 2204 +2024-11-21 22:41:32.507113: Current learning rate: 0.00748 +2024-11-21 22:41:51.119361: train_loss -0.7623 +2024-11-21 22:41:51.119651: val_loss -0.747 +2024-11-21 22:41:51.119733: Pseudo dice [0.8306] +2024-11-21 22:41:51.119812: Epoch time: 18.61 s +2024-11-21 22:41:51.955404: +2024-11-21 22:41:51.955614: Epoch 2205 +2024-11-21 22:41:51.955723: Current learning rate: 0.00748 +2024-11-21 22:42:10.453838: train_loss -0.768 +2024-11-21 22:42:10.454084: val_loss -0.7567 +2024-11-21 22:42:10.454158: Pseudo dice [0.8223] +2024-11-21 22:42:10.454241: Epoch time: 18.5 s +2024-11-21 22:42:11.681769: +2024-11-21 22:42:11.681984: Epoch 2206 +2024-11-21 22:42:11.682104: Current learning rate: 0.00748 +2024-11-21 22:42:29.511471: train_loss -0.7675 +2024-11-21 22:42:29.511759: val_loss -0.7276 +2024-11-21 22:42:29.511834: Pseudo dice [0.8225] +2024-11-21 22:42:29.511912: Epoch time: 17.83 s +2024-11-21 22:42:30.395292: +2024-11-21 22:42:30.395514: Epoch 2207 +2024-11-21 22:42:30.395628: Current learning rate: 0.00748 +2024-11-21 22:42:49.078606: train_loss -0.7647 +2024-11-21 22:42:49.078812: val_loss -0.7219 +2024-11-21 22:42:49.078887: Pseudo dice [0.801] +2024-11-21 22:42:49.078960: Epoch time: 18.68 s +2024-11-21 22:42:49.941061: +2024-11-21 22:42:49.941291: Epoch 2208 +2024-11-21 22:42:49.941416: Current learning rate: 0.00748 +2024-11-21 22:43:09.029685: train_loss -0.7544 +2024-11-21 22:43:09.029925: val_loss -0.7475 +2024-11-21 22:43:09.030007: Pseudo dice [0.8254] +2024-11-21 22:43:09.030089: Epoch time: 19.09 s +2024-11-21 22:43:09.865424: +2024-11-21 22:43:09.865707: Epoch 2209 +2024-11-21 22:43:09.865824: Current learning rate: 0.00748 +2024-11-21 22:43:28.877232: train_loss -0.772 +2024-11-21 22:43:28.877444: val_loss -0.744 +2024-11-21 22:43:28.877518: Pseudo dice [0.8323] +2024-11-21 22:43:28.877595: Epoch time: 19.01 s +2024-11-21 22:43:29.755424: +2024-11-21 22:43:29.755656: Epoch 2210 +2024-11-21 22:43:29.755780: Current learning rate: 0.00748 +2024-11-21 22:43:48.532908: train_loss -0.7769 +2024-11-21 22:43:48.534803: val_loss -0.7426 +2024-11-21 22:43:48.534916: Pseudo dice [0.8518] +2024-11-21 22:43:48.535000: Epoch time: 18.78 s +2024-11-21 22:43:49.376492: +2024-11-21 22:43:49.376694: Epoch 2211 +2024-11-21 22:43:49.376802: Current learning rate: 0.00747 +2024-11-21 22:44:08.148883: train_loss -0.7797 +2024-11-21 22:44:08.149115: val_loss -0.7424 +2024-11-21 22:44:08.149192: Pseudo dice [0.8156] +2024-11-21 22:44:08.149270: Epoch time: 18.77 s +2024-11-21 22:44:08.995010: +2024-11-21 22:44:08.995202: Epoch 2212 +2024-11-21 22:44:08.995316: Current learning rate: 0.00747 +2024-11-21 22:44:27.384179: train_loss -0.7794 +2024-11-21 22:44:27.384456: val_loss -0.7479 +2024-11-21 22:44:27.384531: Pseudo dice [0.819] +2024-11-21 22:44:27.384682: Epoch time: 18.39 s +2024-11-21 22:44:28.227071: +2024-11-21 22:44:28.227290: Epoch 2213 +2024-11-21 22:44:28.227403: Current learning rate: 0.00747 +2024-11-21 22:44:46.363635: train_loss -0.782 +2024-11-21 22:44:46.363863: val_loss -0.7341 +2024-11-21 22:44:46.363937: Pseudo dice [0.8351] +2024-11-21 22:44:46.364023: Epoch time: 18.14 s +2024-11-21 22:44:47.223239: +2024-11-21 22:44:47.223443: Epoch 2214 +2024-11-21 22:44:47.223556: Current learning rate: 0.00747 +2024-11-21 22:45:05.892948: train_loss -0.7777 +2024-11-21 22:45:05.893321: val_loss -0.6793 +2024-11-21 22:45:05.893406: Pseudo dice [0.8092] +2024-11-21 22:45:05.893485: Epoch time: 18.67 s +2024-11-21 22:45:06.731725: +2024-11-21 22:45:06.731934: Epoch 2215 +2024-11-21 22:45:06.732051: Current learning rate: 0.00747 +2024-11-21 22:45:25.955152: train_loss -0.7733 +2024-11-21 22:45:25.955402: val_loss -0.759 +2024-11-21 22:45:25.955480: Pseudo dice [0.8144] +2024-11-21 22:45:25.955571: Epoch time: 19.22 s +2024-11-21 22:45:26.836010: +2024-11-21 22:45:26.836212: Epoch 2216 +2024-11-21 22:45:26.836324: Current learning rate: 0.00747 +2024-11-21 22:45:45.455603: train_loss -0.7731 +2024-11-21 22:45:45.455815: val_loss -0.7252 +2024-11-21 22:45:45.455890: Pseudo dice [0.8267] +2024-11-21 22:45:45.455965: Epoch time: 18.62 s +2024-11-21 22:45:46.291063: +2024-11-21 22:45:46.291268: Epoch 2217 +2024-11-21 22:45:46.291381: Current learning rate: 0.00747 +2024-11-21 22:46:05.024523: train_loss -0.7735 +2024-11-21 22:46:05.024742: val_loss -0.7244 +2024-11-21 22:46:05.024819: Pseudo dice [0.8222] +2024-11-21 22:46:05.024899: Epoch time: 18.73 s +2024-11-21 22:46:06.255302: +2024-11-21 22:46:06.255525: Epoch 2218 +2024-11-21 22:46:06.255639: Current learning rate: 0.00747 +2024-11-21 22:46:25.277140: train_loss -0.781 +2024-11-21 22:46:25.277395: val_loss -0.734 +2024-11-21 22:46:25.277473: Pseudo dice [0.8298] +2024-11-21 22:46:25.277557: Epoch time: 19.02 s +2024-11-21 22:46:26.116323: +2024-11-21 22:46:26.116528: Epoch 2219 +2024-11-21 22:46:26.116643: Current learning rate: 0.00746 +2024-11-21 22:46:45.307669: train_loss -0.7578 +2024-11-21 22:46:45.307883: val_loss -0.7611 +2024-11-21 22:46:45.313170: Pseudo dice [0.834] +2024-11-21 22:46:45.313294: Epoch time: 19.19 s +2024-11-21 22:46:46.329812: +2024-11-21 22:46:46.330014: Epoch 2220 +2024-11-21 22:46:46.330123: Current learning rate: 0.00746 +2024-11-21 22:47:04.590025: train_loss -0.775 +2024-11-21 22:47:04.590244: val_loss -0.7436 +2024-11-21 22:47:04.590320: Pseudo dice [0.8239] +2024-11-21 22:47:04.590398: Epoch time: 18.26 s +2024-11-21 22:47:05.430856: +2024-11-21 22:47:05.431062: Epoch 2221 +2024-11-21 22:47:05.431174: Current learning rate: 0.00746 +2024-11-21 22:47:24.702686: train_loss -0.7759 +2024-11-21 22:47:24.708083: val_loss -0.7654 +2024-11-21 22:47:24.708249: Pseudo dice [0.8316] +2024-11-21 22:47:24.708346: Epoch time: 19.27 s +2024-11-21 22:47:25.684654: +2024-11-21 22:47:25.684902: Epoch 2222 +2024-11-21 22:47:25.685025: Current learning rate: 0.00746 +2024-11-21 22:47:44.818815: train_loss -0.7617 +2024-11-21 22:47:44.819060: val_loss -0.7538 +2024-11-21 22:47:44.819460: Pseudo dice [0.8315] +2024-11-21 22:47:44.819583: Epoch time: 19.13 s +2024-11-21 22:47:45.662186: +2024-11-21 22:47:45.662391: Epoch 2223 +2024-11-21 22:47:45.662500: Current learning rate: 0.00746 +2024-11-21 22:48:04.778687: train_loss -0.7758 +2024-11-21 22:48:04.778903: val_loss -0.7397 +2024-11-21 22:48:04.778980: Pseudo dice [0.8155] +2024-11-21 22:48:04.779064: Epoch time: 19.12 s +2024-11-21 22:48:05.622203: +2024-11-21 22:48:05.622396: Epoch 2224 +2024-11-21 22:48:05.622505: Current learning rate: 0.00746 +2024-11-21 22:48:23.933233: train_loss -0.7811 +2024-11-21 22:48:23.933455: val_loss -0.7415 +2024-11-21 22:48:23.933529: Pseudo dice [0.8114] +2024-11-21 22:48:23.933611: Epoch time: 18.31 s +2024-11-21 22:48:24.833643: +2024-11-21 22:48:24.833869: Epoch 2225 +2024-11-21 22:48:24.833981: Current learning rate: 0.00746 +2024-11-21 22:48:44.302367: train_loss -0.7797 +2024-11-21 22:48:44.302581: val_loss -0.7411 +2024-11-21 22:48:44.302660: Pseudo dice [0.8287] +2024-11-21 22:48:44.302741: Epoch time: 19.47 s +2024-11-21 22:48:45.148134: +2024-11-21 22:48:45.148348: Epoch 2226 +2024-11-21 22:48:45.148463: Current learning rate: 0.00746 +2024-11-21 22:49:03.733921: train_loss -0.7742 +2024-11-21 22:49:03.737548: val_loss -0.7332 +2024-11-21 22:49:03.737664: Pseudo dice [0.8157] +2024-11-21 22:49:03.737749: Epoch time: 18.59 s +2024-11-21 22:49:04.630130: +2024-11-21 22:49:04.630331: Epoch 2227 +2024-11-21 22:49:04.630445: Current learning rate: 0.00746 +2024-11-21 22:49:22.838235: train_loss -0.7652 +2024-11-21 22:49:22.840657: val_loss -0.7268 +2024-11-21 22:49:22.840761: Pseudo dice [0.813] +2024-11-21 22:49:22.840843: Epoch time: 18.21 s +2024-11-21 22:49:23.682046: +2024-11-21 22:49:23.682239: Epoch 2228 +2024-11-21 22:49:23.682351: Current learning rate: 0.00745 +2024-11-21 22:49:42.185288: train_loss -0.779 +2024-11-21 22:49:42.185519: val_loss -0.7409 +2024-11-21 22:49:42.185597: Pseudo dice [0.8253] +2024-11-21 22:49:42.190864: Epoch time: 18.5 s +2024-11-21 22:49:43.191185: +2024-11-21 22:49:43.191411: Epoch 2229 +2024-11-21 22:49:43.191524: Current learning rate: 0.00745 +2024-11-21 22:50:01.140280: train_loss -0.7795 +2024-11-21 22:50:01.140539: val_loss -0.7559 +2024-11-21 22:50:01.140641: Pseudo dice [0.8317] +2024-11-21 22:50:01.140727: Epoch time: 17.95 s +2024-11-21 22:50:02.398043: +2024-11-21 22:50:02.398245: Epoch 2230 +2024-11-21 22:50:02.398358: Current learning rate: 0.00745 +2024-11-21 22:50:21.471367: train_loss -0.7747 +2024-11-21 22:50:21.471597: val_loss -0.7414 +2024-11-21 22:50:21.471673: Pseudo dice [0.8293] +2024-11-21 22:50:21.471751: Epoch time: 19.07 s +2024-11-21 22:50:22.334459: +2024-11-21 22:50:22.334657: Epoch 2231 +2024-11-21 22:50:22.334769: Current learning rate: 0.00745 +2024-11-21 22:50:41.038548: train_loss -0.7728 +2024-11-21 22:50:41.038806: val_loss -0.7577 +2024-11-21 22:50:41.038884: Pseudo dice [0.8182] +2024-11-21 22:50:41.038961: Epoch time: 18.7 s +2024-11-21 22:50:41.875803: +2024-11-21 22:50:41.876020: Epoch 2232 +2024-11-21 22:50:41.876127: Current learning rate: 0.00745 +2024-11-21 22:51:00.261843: train_loss -0.7761 +2024-11-21 22:51:00.262095: val_loss -0.7601 +2024-11-21 22:51:00.262179: Pseudo dice [0.8294] +2024-11-21 22:51:00.262265: Epoch time: 18.39 s +2024-11-21 22:51:01.102025: +2024-11-21 22:51:01.102227: Epoch 2233 +2024-11-21 22:51:01.102337: Current learning rate: 0.00745 +2024-11-21 22:51:19.841414: train_loss -0.7851 +2024-11-21 22:51:19.841627: val_loss -0.7429 +2024-11-21 22:51:19.841700: Pseudo dice [0.8186] +2024-11-21 22:51:19.841775: Epoch time: 18.74 s +2024-11-21 22:51:20.695820: +2024-11-21 22:51:20.696049: Epoch 2234 +2024-11-21 22:51:20.696165: Current learning rate: 0.00745 +2024-11-21 22:51:40.158876: train_loss -0.772 +2024-11-21 22:51:40.159112: val_loss -0.7154 +2024-11-21 22:51:40.159186: Pseudo dice [0.8128] +2024-11-21 22:51:40.159259: Epoch time: 19.46 s +2024-11-21 22:51:40.988346: +2024-11-21 22:51:40.988547: Epoch 2235 +2024-11-21 22:51:40.988662: Current learning rate: 0.00745 +2024-11-21 22:52:00.391802: train_loss -0.7776 +2024-11-21 22:52:00.392024: val_loss -0.7465 +2024-11-21 22:52:00.392100: Pseudo dice [0.8179] +2024-11-21 22:52:00.392178: Epoch time: 19.4 s +2024-11-21 22:52:01.235418: +2024-11-21 22:52:01.235664: Epoch 2236 +2024-11-21 22:52:01.235776: Current learning rate: 0.00745 +2024-11-21 22:52:20.996962: train_loss -0.7795 +2024-11-21 22:52:20.997179: val_loss -0.7353 +2024-11-21 22:52:20.997255: Pseudo dice [0.8374] +2024-11-21 22:52:20.997335: Epoch time: 19.76 s +2024-11-21 22:52:21.840683: +2024-11-21 22:52:21.840959: Epoch 2237 +2024-11-21 22:52:21.841076: Current learning rate: 0.00744 +2024-11-21 22:52:41.088769: train_loss -0.7732 +2024-11-21 22:52:41.088989: val_loss -0.7469 +2024-11-21 22:52:41.089083: Pseudo dice [0.8177] +2024-11-21 22:52:41.089165: Epoch time: 19.25 s +2024-11-21 22:52:41.949905: +2024-11-21 22:52:41.950114: Epoch 2238 +2024-11-21 22:52:41.950226: Current learning rate: 0.00744 +2024-11-21 22:52:59.474620: train_loss -0.7765 +2024-11-21 22:52:59.474900: val_loss -0.7578 +2024-11-21 22:52:59.474980: Pseudo dice [0.8195] +2024-11-21 22:52:59.475066: Epoch time: 17.53 s +2024-11-21 22:53:00.316890: +2024-11-21 22:53:00.317096: Epoch 2239 +2024-11-21 22:53:00.317209: Current learning rate: 0.00744 +2024-11-21 22:53:18.841133: train_loss -0.7731 +2024-11-21 22:53:18.841352: val_loss -0.7648 +2024-11-21 22:53:18.841429: Pseudo dice [0.8339] +2024-11-21 22:53:18.841507: Epoch time: 18.53 s +2024-11-21 22:53:19.678534: +2024-11-21 22:53:19.678756: Epoch 2240 +2024-11-21 22:53:19.678867: Current learning rate: 0.00744 +2024-11-21 22:53:37.987137: train_loss -0.7787 +2024-11-21 22:53:37.987393: val_loss -0.7478 +2024-11-21 22:53:37.990039: Pseudo dice [0.8305] +2024-11-21 22:53:37.990259: Epoch time: 18.31 s +2024-11-21 22:53:38.831836: +2024-11-21 22:53:38.832039: Epoch 2241 +2024-11-21 22:53:38.832152: Current learning rate: 0.00744 +2024-11-21 22:53:57.848282: train_loss -0.7787 +2024-11-21 22:53:57.848503: val_loss -0.7419 +2024-11-21 22:53:57.848605: Pseudo dice [0.8516] +2024-11-21 22:53:57.848685: Epoch time: 19.02 s +2024-11-21 22:53:59.064996: +2024-11-21 22:53:59.065291: Epoch 2242 +2024-11-21 22:53:59.065404: Current learning rate: 0.00744 +2024-11-21 22:54:17.463569: train_loss -0.7744 +2024-11-21 22:54:17.463806: val_loss -0.7349 +2024-11-21 22:54:17.463885: Pseudo dice [0.8223] +2024-11-21 22:54:17.463964: Epoch time: 18.4 s +2024-11-21 22:54:18.300800: +2024-11-21 22:54:18.301069: Epoch 2243 +2024-11-21 22:54:18.301190: Current learning rate: 0.00744 +2024-11-21 22:54:36.679224: train_loss -0.7724 +2024-11-21 22:54:36.679529: val_loss -0.7538 +2024-11-21 22:54:36.679606: Pseudo dice [0.8267] +2024-11-21 22:54:36.679689: Epoch time: 18.38 s +2024-11-21 22:54:37.525692: +2024-11-21 22:54:37.525997: Epoch 2244 +2024-11-21 22:54:37.526114: Current learning rate: 0.00744 +2024-11-21 22:54:55.935330: train_loss -0.7691 +2024-11-21 22:54:55.935585: val_loss -0.7538 +2024-11-21 22:54:55.935670: Pseudo dice [0.8391] +2024-11-21 22:54:55.935751: Epoch time: 18.41 s +2024-11-21 22:54:56.770831: +2024-11-21 22:54:56.771064: Epoch 2245 +2024-11-21 22:54:56.771181: Current learning rate: 0.00743 +2024-11-21 22:55:15.658691: train_loss -0.7821 +2024-11-21 22:55:15.658898: val_loss -0.7557 +2024-11-21 22:55:15.658971: Pseudo dice [0.8198] +2024-11-21 22:55:15.659055: Epoch time: 18.89 s +2024-11-21 22:55:16.499433: +2024-11-21 22:55:16.499643: Epoch 2246 +2024-11-21 22:55:16.499757: Current learning rate: 0.00743 +2024-11-21 22:55:36.112438: train_loss -0.776 +2024-11-21 22:55:36.112659: val_loss -0.7184 +2024-11-21 22:55:36.112735: Pseudo dice [0.8176] +2024-11-21 22:55:36.112812: Epoch time: 19.61 s +2024-11-21 22:55:36.956015: +2024-11-21 22:55:36.956324: Epoch 2247 +2024-11-21 22:55:36.956441: Current learning rate: 0.00743 +2024-11-21 22:55:55.006252: train_loss -0.7777 +2024-11-21 22:55:55.006498: val_loss -0.7387 +2024-11-21 22:55:55.006575: Pseudo dice [0.8268] +2024-11-21 22:55:55.006655: Epoch time: 18.05 s +2024-11-21 22:55:55.844585: +2024-11-21 22:55:55.844797: Epoch 2248 +2024-11-21 22:55:55.844908: Current learning rate: 0.00743 +2024-11-21 22:56:14.332203: train_loss -0.7736 +2024-11-21 22:56:14.332477: val_loss -0.7033 +2024-11-21 22:56:14.332557: Pseudo dice [0.8124] +2024-11-21 22:56:14.332632: Epoch time: 18.49 s +2024-11-21 22:56:15.172037: +2024-11-21 22:56:15.172347: Epoch 2249 +2024-11-21 22:56:15.172467: Current learning rate: 0.00743 +2024-11-21 22:56:32.936439: train_loss -0.7604 +2024-11-21 22:56:32.936657: val_loss -0.7362 +2024-11-21 22:56:32.936731: Pseudo dice [0.7986] +2024-11-21 22:56:32.936807: Epoch time: 17.77 s +2024-11-21 22:56:33.977503: +2024-11-21 22:56:33.977710: Epoch 2250 +2024-11-21 22:56:33.977820: Current learning rate: 0.00743 +2024-11-21 22:56:53.505300: train_loss -0.7698 +2024-11-21 22:56:53.505549: val_loss -0.7098 +2024-11-21 22:56:53.507828: Pseudo dice [0.8123] +2024-11-21 22:56:53.507937: Epoch time: 19.53 s +2024-11-21 22:56:54.555146: +2024-11-21 22:56:54.555343: Epoch 2251 +2024-11-21 22:56:54.555455: Current learning rate: 0.00743 +2024-11-21 22:57:13.506161: train_loss -0.7765 +2024-11-21 22:57:13.506378: val_loss -0.7522 +2024-11-21 22:57:13.506452: Pseudo dice [0.8245] +2024-11-21 22:57:13.506528: Epoch time: 18.95 s +2024-11-21 22:57:14.391417: +2024-11-21 22:57:14.391638: Epoch 2252 +2024-11-21 22:57:14.391755: Current learning rate: 0.00743 +2024-11-21 22:57:33.276695: train_loss -0.7696 +2024-11-21 22:57:33.276917: val_loss -0.7455 +2024-11-21 22:57:33.277000: Pseudo dice [0.8408] +2024-11-21 22:57:33.277079: Epoch time: 18.89 s +2024-11-21 22:57:34.148257: +2024-11-21 22:57:34.148469: Epoch 2253 +2024-11-21 22:57:34.148580: Current learning rate: 0.00743 +2024-11-21 22:57:53.622783: train_loss -0.7814 +2024-11-21 22:57:53.628185: val_loss -0.7446 +2024-11-21 22:57:53.628295: Pseudo dice [0.8293] +2024-11-21 22:57:53.628380: Epoch time: 19.48 s +2024-11-21 22:57:55.072777: +2024-11-21 22:57:55.073052: Epoch 2254 +2024-11-21 22:57:55.073202: Current learning rate: 0.00742 +2024-11-21 22:58:14.134368: train_loss -0.7786 +2024-11-21 22:58:14.134608: val_loss -0.7553 +2024-11-21 22:58:14.134681: Pseudo dice [0.8199] +2024-11-21 22:58:14.134760: Epoch time: 19.06 s +2024-11-21 22:58:14.968651: +2024-11-21 22:58:14.968864: Epoch 2255 +2024-11-21 22:58:14.968977: Current learning rate: 0.00742 +2024-11-21 22:58:34.462058: train_loss -0.7807 +2024-11-21 22:58:34.462279: val_loss -0.7329 +2024-11-21 22:58:34.462356: Pseudo dice [0.8203] +2024-11-21 22:58:34.462433: Epoch time: 19.49 s +2024-11-21 22:58:35.301634: +2024-11-21 22:58:35.301867: Epoch 2256 +2024-11-21 22:58:35.301980: Current learning rate: 0.00742 +2024-11-21 22:58:53.610344: train_loss -0.7675 +2024-11-21 22:58:53.610578: val_loss -0.7157 +2024-11-21 22:58:53.610690: Pseudo dice [0.8119] +2024-11-21 22:58:53.610770: Epoch time: 18.31 s +2024-11-21 22:58:54.445030: +2024-11-21 22:58:54.445238: Epoch 2257 +2024-11-21 22:58:54.445349: Current learning rate: 0.00742 +2024-11-21 22:59:12.934915: train_loss -0.7623 +2024-11-21 22:59:12.940329: val_loss -0.7437 +2024-11-21 22:59:12.940413: Pseudo dice [0.8205] +2024-11-21 22:59:12.940508: Epoch time: 18.49 s +2024-11-21 22:59:13.799292: +2024-11-21 22:59:13.799500: Epoch 2258 +2024-11-21 22:59:13.799610: Current learning rate: 0.00742 +2024-11-21 22:59:31.982614: train_loss -0.7802 +2024-11-21 22:59:31.982830: val_loss -0.7299 +2024-11-21 22:59:31.982950: Pseudo dice [0.8272] +2024-11-21 22:59:31.983069: Epoch time: 18.18 s +2024-11-21 22:59:32.897943: +2024-11-21 22:59:32.898465: Epoch 2259 +2024-11-21 22:59:32.898578: Current learning rate: 0.00742 +2024-11-21 22:59:51.138069: train_loss -0.7719 +2024-11-21 22:59:51.138339: val_loss -0.7534 +2024-11-21 22:59:51.138417: Pseudo dice [0.8235] +2024-11-21 22:59:51.138496: Epoch time: 18.24 s +2024-11-21 22:59:52.074130: +2024-11-21 22:59:52.074361: Epoch 2260 +2024-11-21 22:59:52.074480: Current learning rate: 0.00742 +2024-11-21 23:00:10.943283: train_loss -0.7831 +2024-11-21 23:00:10.943505: val_loss -0.7163 +2024-11-21 23:00:10.944362: Pseudo dice [0.8115] +2024-11-21 23:00:10.944461: Epoch time: 18.87 s +2024-11-21 23:00:11.790426: +2024-11-21 23:00:11.790656: Epoch 2261 +2024-11-21 23:00:11.790769: Current learning rate: 0.00742 +2024-11-21 23:00:30.513899: train_loss -0.79 +2024-11-21 23:00:30.514195: val_loss -0.7593 +2024-11-21 23:00:30.514269: Pseudo dice [0.8455] +2024-11-21 23:00:30.514349: Epoch time: 18.72 s +2024-11-21 23:00:31.455508: +2024-11-21 23:00:31.455752: Epoch 2262 +2024-11-21 23:00:31.455863: Current learning rate: 0.00741 +2024-11-21 23:00:50.566094: train_loss -0.7786 +2024-11-21 23:00:50.566314: val_loss -0.7527 +2024-11-21 23:00:50.566396: Pseudo dice [0.8167] +2024-11-21 23:00:50.566474: Epoch time: 19.11 s +2024-11-21 23:00:51.399027: +2024-11-21 23:00:51.399245: Epoch 2263 +2024-11-21 23:00:51.399360: Current learning rate: 0.00741 +2024-11-21 23:01:09.962319: train_loss -0.7817 +2024-11-21 23:01:09.964957: val_loss -0.7589 +2024-11-21 23:01:09.965086: Pseudo dice [0.8286] +2024-11-21 23:01:09.965177: Epoch time: 18.56 s +2024-11-21 23:01:10.803242: +2024-11-21 23:01:10.803451: Epoch 2264 +2024-11-21 23:01:10.803560: Current learning rate: 0.00741 +2024-11-21 23:01:28.624996: train_loss -0.7783 +2024-11-21 23:01:28.625235: val_loss -0.7445 +2024-11-21 23:01:28.625308: Pseudo dice [0.8162] +2024-11-21 23:01:28.625391: Epoch time: 17.82 s +2024-11-21 23:01:29.468015: +2024-11-21 23:01:29.468226: Epoch 2265 +2024-11-21 23:01:29.468343: Current learning rate: 0.00741 +2024-11-21 23:01:48.781437: train_loss -0.7802 +2024-11-21 23:01:48.781655: val_loss -0.7714 +2024-11-21 23:01:48.781731: Pseudo dice [0.8347] +2024-11-21 23:01:48.781807: Epoch time: 19.31 s +2024-11-21 23:01:50.072119: +2024-11-21 23:01:50.072344: Epoch 2266 +2024-11-21 23:01:50.072455: Current learning rate: 0.00741 +2024-11-21 23:02:08.672335: train_loss -0.7868 +2024-11-21 23:02:08.672566: val_loss -0.7296 +2024-11-21 23:02:08.672639: Pseudo dice [0.823] +2024-11-21 23:02:08.672714: Epoch time: 18.6 s +2024-11-21 23:02:09.515329: +2024-11-21 23:02:09.515538: Epoch 2267 +2024-11-21 23:02:09.515653: Current learning rate: 0.00741 +2024-11-21 23:02:27.778919: train_loss -0.7822 +2024-11-21 23:02:27.779163: val_loss -0.75 +2024-11-21 23:02:27.779236: Pseudo dice [0.8321] +2024-11-21 23:02:27.779325: Epoch time: 18.26 s +2024-11-21 23:02:28.611891: +2024-11-21 23:02:28.612103: Epoch 2268 +2024-11-21 23:02:28.612220: Current learning rate: 0.00741 +2024-11-21 23:02:46.945739: train_loss -0.7511 +2024-11-21 23:02:46.946042: val_loss -0.7521 +2024-11-21 23:02:46.946124: Pseudo dice [0.8151] +2024-11-21 23:02:46.946242: Epoch time: 18.33 s +2024-11-21 23:02:47.778285: +2024-11-21 23:02:47.778484: Epoch 2269 +2024-11-21 23:02:47.778599: Current learning rate: 0.00741 +2024-11-21 23:03:06.800206: train_loss -0.7646 +2024-11-21 23:03:06.800483: val_loss -0.7452 +2024-11-21 23:03:06.800595: Pseudo dice [0.8177] +2024-11-21 23:03:06.800675: Epoch time: 19.02 s +2024-11-21 23:03:07.641045: +2024-11-21 23:03:07.641248: Epoch 2270 +2024-11-21 23:03:07.641360: Current learning rate: 0.00741 +2024-11-21 23:03:27.502502: train_loss -0.7734 +2024-11-21 23:03:27.502719: val_loss -0.7144 +2024-11-21 23:03:27.502797: Pseudo dice [0.8311] +2024-11-21 23:03:27.502874: Epoch time: 19.86 s +2024-11-21 23:03:28.441765: +2024-11-21 23:03:28.441963: Epoch 2271 +2024-11-21 23:03:28.442084: Current learning rate: 0.0074 +2024-11-21 23:03:48.318349: train_loss -0.773 +2024-11-21 23:03:48.318638: val_loss -0.7647 +2024-11-21 23:03:48.318713: Pseudo dice [0.8373] +2024-11-21 23:03:48.318795: Epoch time: 19.88 s +2024-11-21 23:03:49.156967: +2024-11-21 23:03:49.157188: Epoch 2272 +2024-11-21 23:03:49.157310: Current learning rate: 0.0074 +2024-11-21 23:04:07.650296: train_loss -0.7678 +2024-11-21 23:04:07.650527: val_loss -0.756 +2024-11-21 23:04:07.650619: Pseudo dice [0.8328] +2024-11-21 23:04:07.650749: Epoch time: 18.49 s +2024-11-21 23:04:08.493412: +2024-11-21 23:04:08.493622: Epoch 2273 +2024-11-21 23:04:08.493734: Current learning rate: 0.0074 +2024-11-21 23:04:26.908629: train_loss -0.7741 +2024-11-21 23:04:26.908843: val_loss -0.7399 +2024-11-21 23:04:26.908921: Pseudo dice [0.8278] +2024-11-21 23:04:26.909017: Epoch time: 18.42 s +2024-11-21 23:04:27.750901: +2024-11-21 23:04:27.751115: Epoch 2274 +2024-11-21 23:04:27.751227: Current learning rate: 0.0074 +2024-11-21 23:04:46.142192: train_loss -0.7567 +2024-11-21 23:04:46.142491: val_loss -0.7178 +2024-11-21 23:04:46.142573: Pseudo dice [0.824] +2024-11-21 23:04:46.142656: Epoch time: 18.39 s +2024-11-21 23:04:46.986665: +2024-11-21 23:04:46.986862: Epoch 2275 +2024-11-21 23:04:46.986973: Current learning rate: 0.0074 +2024-11-21 23:05:06.943957: train_loss -0.7665 +2024-11-21 23:05:06.944199: val_loss -0.74 +2024-11-21 23:05:06.944273: Pseudo dice [0.8427] +2024-11-21 23:05:06.944351: Epoch time: 19.96 s +2024-11-21 23:05:07.794166: +2024-11-21 23:05:07.794379: Epoch 2276 +2024-11-21 23:05:07.794500: Current learning rate: 0.0074 +2024-11-21 23:05:26.689980: train_loss -0.7711 +2024-11-21 23:05:26.690206: val_loss -0.7357 +2024-11-21 23:05:26.690283: Pseudo dice [0.8213] +2024-11-21 23:05:26.692586: Epoch time: 18.9 s +2024-11-21 23:05:27.564957: +2024-11-21 23:05:27.565259: Epoch 2277 +2024-11-21 23:05:27.565371: Current learning rate: 0.0074 +2024-11-21 23:05:46.565117: train_loss -0.7674 +2024-11-21 23:05:46.565355: val_loss -0.7407 +2024-11-21 23:05:46.565428: Pseudo dice [0.8223] +2024-11-21 23:05:46.569406: Epoch time: 19.0 s +2024-11-21 23:05:47.860359: +2024-11-21 23:05:47.860572: Epoch 2278 +2024-11-21 23:05:47.860683: Current learning rate: 0.0074 +2024-11-21 23:06:06.966849: train_loss -0.7798 +2024-11-21 23:06:06.978043: val_loss -0.7313 +2024-11-21 23:06:06.978148: Pseudo dice [0.8373] +2024-11-21 23:06:06.978228: Epoch time: 19.11 s +2024-11-21 23:06:07.836670: +2024-11-21 23:06:07.836872: Epoch 2279 +2024-11-21 23:06:07.836983: Current learning rate: 0.0074 +2024-11-21 23:06:26.905018: train_loss -0.7817 +2024-11-21 23:06:26.905253: val_loss -0.7343 +2024-11-21 23:06:26.905329: Pseudo dice [0.8218] +2024-11-21 23:06:26.905410: Epoch time: 19.07 s +2024-11-21 23:06:27.852458: +2024-11-21 23:06:27.852680: Epoch 2280 +2024-11-21 23:06:27.852794: Current learning rate: 0.00739 +2024-11-21 23:06:45.749457: train_loss -0.7818 +2024-11-21 23:06:45.749675: val_loss -0.7406 +2024-11-21 23:06:45.749749: Pseudo dice [0.8178] +2024-11-21 23:06:45.749836: Epoch time: 17.9 s +2024-11-21 23:06:46.592048: +2024-11-21 23:06:46.592334: Epoch 2281 +2024-11-21 23:06:46.592444: Current learning rate: 0.00739 +2024-11-21 23:07:05.148574: train_loss -0.7715 +2024-11-21 23:07:05.148813: val_loss -0.7433 +2024-11-21 23:07:05.148892: Pseudo dice [0.8292] +2024-11-21 23:07:05.148977: Epoch time: 18.56 s +2024-11-21 23:07:05.989140: +2024-11-21 23:07:05.989350: Epoch 2282 +2024-11-21 23:07:05.989469: Current learning rate: 0.00739 +2024-11-21 23:07:26.323727: train_loss -0.7692 +2024-11-21 23:07:26.323954: val_loss -0.7314 +2024-11-21 23:07:26.326233: Pseudo dice [0.8206] +2024-11-21 23:07:26.326324: Epoch time: 20.34 s +2024-11-21 23:07:27.195929: +2024-11-21 23:07:27.196153: Epoch 2283 +2024-11-21 23:07:27.196263: Current learning rate: 0.00739 +2024-11-21 23:07:46.113546: train_loss -0.7711 +2024-11-21 23:07:46.113774: val_loss -0.7562 +2024-11-21 23:07:46.119055: Pseudo dice [0.8279] +2024-11-21 23:07:46.119194: Epoch time: 18.92 s +2024-11-21 23:07:47.234654: +2024-11-21 23:07:47.234855: Epoch 2284 +2024-11-21 23:07:47.234971: Current learning rate: 0.00739 +2024-11-21 23:08:06.267426: train_loss -0.7727 +2024-11-21 23:08:06.267643: val_loss -0.7434 +2024-11-21 23:08:06.267720: Pseudo dice [0.8239] +2024-11-21 23:08:06.267797: Epoch time: 19.03 s +2024-11-21 23:08:07.107591: +2024-11-21 23:08:07.107835: Epoch 2285 +2024-11-21 23:08:07.107950: Current learning rate: 0.00739 +2024-11-21 23:08:26.408704: train_loss -0.771 +2024-11-21 23:08:26.409248: val_loss -0.7517 +2024-11-21 23:08:26.409338: Pseudo dice [0.8442] +2024-11-21 23:08:26.409421: Epoch time: 19.3 s +2024-11-21 23:08:27.369388: +2024-11-21 23:08:27.370223: Epoch 2286 +2024-11-21 23:08:27.370339: Current learning rate: 0.00739 +2024-11-21 23:08:45.640157: train_loss -0.7706 +2024-11-21 23:08:45.640376: val_loss -0.7411 +2024-11-21 23:08:45.640452: Pseudo dice [0.8189] +2024-11-21 23:08:45.640528: Epoch time: 18.27 s +2024-11-21 23:08:46.482988: +2024-11-21 23:08:46.483292: Epoch 2287 +2024-11-21 23:08:46.483402: Current learning rate: 0.00739 +2024-11-21 23:09:05.157210: train_loss -0.7762 +2024-11-21 23:09:05.158061: val_loss -0.7624 +2024-11-21 23:09:05.158176: Pseudo dice [0.8207] +2024-11-21 23:09:05.158256: Epoch time: 18.67 s +2024-11-21 23:09:06.000422: +2024-11-21 23:09:06.000624: Epoch 2288 +2024-11-21 23:09:06.000732: Current learning rate: 0.00738 +2024-11-21 23:09:25.299217: train_loss -0.7716 +2024-11-21 23:09:25.299458: val_loss -0.7224 +2024-11-21 23:09:25.299534: Pseudo dice [0.8238] +2024-11-21 23:09:25.299617: Epoch time: 19.3 s +2024-11-21 23:09:26.146551: +2024-11-21 23:09:26.146770: Epoch 2289 +2024-11-21 23:09:26.146883: Current learning rate: 0.00738 +2024-11-21 23:09:46.164250: train_loss -0.7571 +2024-11-21 23:09:46.164456: val_loss -0.6975 +2024-11-21 23:09:46.164529: Pseudo dice [0.8218] +2024-11-21 23:09:46.164602: Epoch time: 20.02 s +2024-11-21 23:09:47.501051: +2024-11-21 23:09:47.501273: Epoch 2290 +2024-11-21 23:09:47.501389: Current learning rate: 0.00738 +2024-11-21 23:10:06.406073: train_loss -0.7774 +2024-11-21 23:10:06.406298: val_loss -0.7418 +2024-11-21 23:10:06.406393: Pseudo dice [0.821] +2024-11-21 23:10:06.406487: Epoch time: 18.91 s +2024-11-21 23:10:07.240012: +2024-11-21 23:10:07.240222: Epoch 2291 +2024-11-21 23:10:07.240335: Current learning rate: 0.00738 +2024-11-21 23:10:25.766301: train_loss -0.7703 +2024-11-21 23:10:25.766517: val_loss -0.742 +2024-11-21 23:10:25.766592: Pseudo dice [0.839] +2024-11-21 23:10:25.766672: Epoch time: 18.53 s +2024-11-21 23:10:26.611404: +2024-11-21 23:10:26.611670: Epoch 2292 +2024-11-21 23:10:26.611830: Current learning rate: 0.00738 +2024-11-21 23:10:45.734578: train_loss -0.7789 +2024-11-21 23:10:45.744342: val_loss -0.7512 +2024-11-21 23:10:45.744479: Pseudo dice [0.8247] +2024-11-21 23:10:45.744651: Epoch time: 19.12 s +2024-11-21 23:10:46.590501: +2024-11-21 23:10:46.590731: Epoch 2293 +2024-11-21 23:10:46.590846: Current learning rate: 0.00738 +2024-11-21 23:11:05.344570: train_loss -0.7778 +2024-11-21 23:11:05.344843: val_loss -0.7415 +2024-11-21 23:11:05.344943: Pseudo dice [0.8066] +2024-11-21 23:11:05.345027: Epoch time: 18.75 s +2024-11-21 23:11:06.186078: +2024-11-21 23:11:06.186291: Epoch 2294 +2024-11-21 23:11:06.186409: Current learning rate: 0.00738 +2024-11-21 23:11:24.385885: train_loss -0.7701 +2024-11-21 23:11:24.386119: val_loss -0.7494 +2024-11-21 23:11:24.386194: Pseudo dice [0.8212] +2024-11-21 23:11:24.386271: Epoch time: 18.2 s +2024-11-21 23:11:25.411475: +2024-11-21 23:11:25.411698: Epoch 2295 +2024-11-21 23:11:25.411813: Current learning rate: 0.00738 +2024-11-21 23:11:44.540704: train_loss -0.7669 +2024-11-21 23:11:44.540945: val_loss -0.7518 +2024-11-21 23:11:44.541033: Pseudo dice [0.8371] +2024-11-21 23:11:44.541114: Epoch time: 19.13 s +2024-11-21 23:11:45.510659: +2024-11-21 23:11:45.510873: Epoch 2296 +2024-11-21 23:11:45.510989: Current learning rate: 0.00738 +2024-11-21 23:12:03.892854: train_loss -0.7801 +2024-11-21 23:12:03.893083: val_loss -0.7204 +2024-11-21 23:12:03.893158: Pseudo dice [0.8094] +2024-11-21 23:12:03.893234: Epoch time: 18.38 s +2024-11-21 23:12:04.733691: +2024-11-21 23:12:04.733903: Epoch 2297 +2024-11-21 23:12:04.734018: Current learning rate: 0.00737 +2024-11-21 23:12:24.423425: train_loss -0.787 +2024-11-21 23:12:24.423650: val_loss -0.7496 +2024-11-21 23:12:24.423724: Pseudo dice [0.8309] +2024-11-21 23:12:24.423801: Epoch time: 19.69 s +2024-11-21 23:12:25.261285: +2024-11-21 23:12:25.261493: Epoch 2298 +2024-11-21 23:12:25.261609: Current learning rate: 0.00737 +2024-11-21 23:12:44.230158: train_loss -0.7721 +2024-11-21 23:12:44.230371: val_loss -0.7297 +2024-11-21 23:12:44.230448: Pseudo dice [0.8127] +2024-11-21 23:12:44.248498: Epoch time: 18.97 s +2024-11-21 23:12:45.085819: +2024-11-21 23:12:45.086039: Epoch 2299 +2024-11-21 23:12:45.086149: Current learning rate: 0.00737 +2024-11-21 23:13:03.766804: train_loss -0.7733 +2024-11-21 23:13:03.767028: val_loss -0.7366 +2024-11-21 23:13:03.767102: Pseudo dice [0.8253] +2024-11-21 23:13:03.767202: Epoch time: 18.68 s +2024-11-21 23:13:04.815059: +2024-11-21 23:13:04.815392: Epoch 2300 +2024-11-21 23:13:04.815515: Current learning rate: 0.00737 +2024-11-21 23:13:23.050262: train_loss -0.7719 +2024-11-21 23:13:23.050491: val_loss -0.7521 +2024-11-21 23:13:23.050568: Pseudo dice [0.8212] +2024-11-21 23:13:23.050712: Epoch time: 18.24 s +2024-11-21 23:13:23.897568: +2024-11-21 23:13:23.897836: Epoch 2301 +2024-11-21 23:13:23.897951: Current learning rate: 0.00737 +2024-11-21 23:13:42.896096: train_loss -0.775 +2024-11-21 23:13:42.896325: val_loss -0.7483 +2024-11-21 23:13:42.896432: Pseudo dice [0.823] +2024-11-21 23:13:42.896511: Epoch time: 19.0 s +2024-11-21 23:13:44.117013: +2024-11-21 23:13:44.117224: Epoch 2302 +2024-11-21 23:13:44.117334: Current learning rate: 0.00737 +2024-11-21 23:14:02.702959: train_loss -0.765 +2024-11-21 23:14:02.703226: val_loss -0.7512 +2024-11-21 23:14:02.703302: Pseudo dice [0.8287] +2024-11-21 23:14:02.703389: Epoch time: 18.59 s +2024-11-21 23:14:03.653661: +2024-11-21 23:14:03.653882: Epoch 2303 +2024-11-21 23:14:03.654000: Current learning rate: 0.00737 +2024-11-21 23:14:21.411300: train_loss -0.7716 +2024-11-21 23:14:21.411522: val_loss -0.7415 +2024-11-21 23:14:21.411598: Pseudo dice [0.8202] +2024-11-21 23:14:21.413933: Epoch time: 17.76 s +2024-11-21 23:14:22.304182: +2024-11-21 23:14:22.304384: Epoch 2304 +2024-11-21 23:14:22.304495: Current learning rate: 0.00737 +2024-11-21 23:14:40.833188: train_loss -0.7669 +2024-11-21 23:14:40.833417: val_loss -0.7495 +2024-11-21 23:14:40.833499: Pseudo dice [0.8286] +2024-11-21 23:14:40.833582: Epoch time: 18.53 s +2024-11-21 23:14:41.760947: +2024-11-21 23:14:41.761214: Epoch 2305 +2024-11-21 23:14:41.761330: Current learning rate: 0.00736 +2024-11-21 23:14:59.897553: train_loss -0.775 +2024-11-21 23:14:59.897870: val_loss -0.7281 +2024-11-21 23:14:59.897950: Pseudo dice [0.8301] +2024-11-21 23:14:59.898039: Epoch time: 18.14 s +2024-11-21 23:15:00.740491: +2024-11-21 23:15:00.740713: Epoch 2306 +2024-11-21 23:15:00.740826: Current learning rate: 0.00736 +2024-11-21 23:15:19.416599: train_loss -0.775 +2024-11-21 23:15:19.416815: val_loss -0.7467 +2024-11-21 23:15:19.416888: Pseudo dice [0.8345] +2024-11-21 23:15:19.416971: Epoch time: 18.68 s +2024-11-21 23:15:20.359322: +2024-11-21 23:15:20.359603: Epoch 2307 +2024-11-21 23:15:20.359717: Current learning rate: 0.00736 +2024-11-21 23:15:39.481341: train_loss -0.7798 +2024-11-21 23:15:39.481570: val_loss -0.7488 +2024-11-21 23:15:39.481645: Pseudo dice [0.8285] +2024-11-21 23:15:39.481816: Epoch time: 19.12 s +2024-11-21 23:15:40.346920: +2024-11-21 23:15:40.347156: Epoch 2308 +2024-11-21 23:15:40.347282: Current learning rate: 0.00736 +2024-11-21 23:15:58.932100: train_loss -0.7743 +2024-11-21 23:15:58.932356: val_loss -0.7533 +2024-11-21 23:15:58.932433: Pseudo dice [0.8337] +2024-11-21 23:15:58.932511: Epoch time: 18.59 s +2024-11-21 23:15:59.772037: +2024-11-21 23:15:59.772323: Epoch 2309 +2024-11-21 23:15:59.772436: Current learning rate: 0.00736 +2024-11-21 23:16:18.426522: train_loss -0.7651 +2024-11-21 23:16:18.426764: val_loss -0.7103 +2024-11-21 23:16:18.426872: Pseudo dice [0.8035] +2024-11-21 23:16:18.426960: Epoch time: 18.66 s +2024-11-21 23:16:19.269199: +2024-11-21 23:16:19.269423: Epoch 2310 +2024-11-21 23:16:19.269540: Current learning rate: 0.00736 +2024-11-21 23:16:38.284796: train_loss -0.7635 +2024-11-21 23:16:38.285013: val_loss -0.7338 +2024-11-21 23:16:38.285088: Pseudo dice [0.82] +2024-11-21 23:16:38.285163: Epoch time: 19.02 s +2024-11-21 23:16:39.127485: +2024-11-21 23:16:39.127717: Epoch 2311 +2024-11-21 23:16:39.127838: Current learning rate: 0.00736 +2024-11-21 23:16:57.098456: train_loss -0.7748 +2024-11-21 23:16:57.114227: val_loss -0.7405 +2024-11-21 23:16:57.114377: Pseudo dice [0.8315] +2024-11-21 23:16:57.114460: Epoch time: 17.97 s +2024-11-21 23:16:58.083908: +2024-11-21 23:16:58.084142: Epoch 2312 +2024-11-21 23:16:58.084259: Current learning rate: 0.00736 +2024-11-21 23:17:16.869809: train_loss -0.7642 +2024-11-21 23:17:16.875250: val_loss -0.7341 +2024-11-21 23:17:16.875379: Pseudo dice [0.8193] +2024-11-21 23:17:16.875473: Epoch time: 18.79 s +2024-11-21 23:17:17.757578: +2024-11-21 23:17:17.757777: Epoch 2313 +2024-11-21 23:17:17.757891: Current learning rate: 0.00736 +2024-11-21 23:17:35.811429: train_loss -0.7639 +2024-11-21 23:17:35.811642: val_loss -0.739 +2024-11-21 23:17:35.811715: Pseudo dice [0.8121] +2024-11-21 23:17:35.811790: Epoch time: 18.05 s +2024-11-21 23:17:37.030908: +2024-11-21 23:17:37.031142: Epoch 2314 +2024-11-21 23:17:37.031257: Current learning rate: 0.00735 +2024-11-21 23:17:56.947666: train_loss -0.7701 +2024-11-21 23:17:56.947898: val_loss -0.7289 +2024-11-21 23:17:56.947985: Pseudo dice [0.809] +2024-11-21 23:17:56.948078: Epoch time: 19.92 s +2024-11-21 23:17:57.790277: +2024-11-21 23:17:57.790589: Epoch 2315 +2024-11-21 23:17:57.790707: Current learning rate: 0.00735 +2024-11-21 23:18:16.789731: train_loss -0.7734 +2024-11-21 23:18:16.792132: val_loss -0.7408 +2024-11-21 23:18:16.792226: Pseudo dice [0.8262] +2024-11-21 23:18:16.792310: Epoch time: 19.0 s +2024-11-21 23:18:17.698220: +2024-11-21 23:18:17.698464: Epoch 2316 +2024-11-21 23:18:17.698581: Current learning rate: 0.00735 +2024-11-21 23:18:37.549817: train_loss -0.7848 +2024-11-21 23:18:37.550036: val_loss -0.7483 +2024-11-21 23:18:37.550108: Pseudo dice [0.8359] +2024-11-21 23:18:37.550183: Epoch time: 19.85 s +2024-11-21 23:18:38.391364: +2024-11-21 23:18:38.391592: Epoch 2317 +2024-11-21 23:18:38.391702: Current learning rate: 0.00735 +2024-11-21 23:18:56.842327: train_loss -0.7763 +2024-11-21 23:18:56.844738: val_loss -0.7239 +2024-11-21 23:18:56.844833: Pseudo dice [0.8325] +2024-11-21 23:18:56.844915: Epoch time: 18.45 s +2024-11-21 23:18:57.803943: +2024-11-21 23:18:57.804226: Epoch 2318 +2024-11-21 23:18:57.804480: Current learning rate: 0.00735 +2024-11-21 23:19:16.788375: train_loss -0.7755 +2024-11-21 23:19:16.788633: val_loss -0.7258 +2024-11-21 23:19:16.788709: Pseudo dice [0.8277] +2024-11-21 23:19:16.788789: Epoch time: 18.99 s +2024-11-21 23:19:17.633167: +2024-11-21 23:19:17.633362: Epoch 2319 +2024-11-21 23:19:17.633476: Current learning rate: 0.00735 +2024-11-21 23:19:36.944566: train_loss -0.7818 +2024-11-21 23:19:36.944809: val_loss -0.7323 +2024-11-21 23:19:36.944885: Pseudo dice [0.8293] +2024-11-21 23:19:36.944968: Epoch time: 19.31 s +2024-11-21 23:19:37.917542: +2024-11-21 23:19:37.917771: Epoch 2320 +2024-11-21 23:19:37.917884: Current learning rate: 0.00735 +2024-11-21 23:19:57.173073: train_loss -0.7742 +2024-11-21 23:19:57.173293: val_loss -0.7181 +2024-11-21 23:19:57.173368: Pseudo dice [0.8217] +2024-11-21 23:19:57.173445: Epoch time: 19.26 s +2024-11-21 23:19:58.014686: +2024-11-21 23:19:58.014900: Epoch 2321 +2024-11-21 23:19:58.015017: Current learning rate: 0.00735 +2024-11-21 23:20:16.796574: train_loss -0.7855 +2024-11-21 23:20:16.796806: val_loss -0.7612 +2024-11-21 23:20:16.796879: Pseudo dice [0.8239] +2024-11-21 23:20:16.796957: Epoch time: 18.78 s +2024-11-21 23:20:17.636581: +2024-11-21 23:20:17.636789: Epoch 2322 +2024-11-21 23:20:17.636935: Current learning rate: 0.00735 +2024-11-21 23:20:36.350548: train_loss -0.7822 +2024-11-21 23:20:36.353662: val_loss -0.7569 +2024-11-21 23:20:36.353815: Pseudo dice [0.829] +2024-11-21 23:20:36.353900: Epoch time: 18.71 s +2024-11-21 23:20:37.245900: +2024-11-21 23:20:37.246117: Epoch 2323 +2024-11-21 23:20:37.246235: Current learning rate: 0.00734 +2024-11-21 23:20:56.049039: train_loss -0.7826 +2024-11-21 23:20:56.049379: val_loss -0.7403 +2024-11-21 23:20:56.049460: Pseudo dice [0.821] +2024-11-21 23:20:56.049546: Epoch time: 18.8 s +2024-11-21 23:20:57.127591: +2024-11-21 23:20:57.127853: Epoch 2324 +2024-11-21 23:20:57.128211: Current learning rate: 0.00734 +2024-11-21 23:21:15.558763: train_loss -0.7667 +2024-11-21 23:21:15.558976: val_loss -0.7458 +2024-11-21 23:21:15.559056: Pseudo dice [0.8238] +2024-11-21 23:21:15.559134: Epoch time: 18.43 s +2024-11-21 23:21:16.575241: +2024-11-21 23:21:16.575454: Epoch 2325 +2024-11-21 23:21:16.575569: Current learning rate: 0.00734 +2024-11-21 23:21:35.295265: train_loss -0.7706 +2024-11-21 23:21:35.295482: val_loss -0.7347 +2024-11-21 23:21:35.295561: Pseudo dice [0.8125] +2024-11-21 23:21:35.295644: Epoch time: 18.72 s +2024-11-21 23:21:36.509665: +2024-11-21 23:21:36.509883: Epoch 2326 +2024-11-21 23:21:36.510002: Current learning rate: 0.00734 +2024-11-21 23:21:55.514791: train_loss -0.7734 +2024-11-21 23:21:55.515418: val_loss -0.7688 +2024-11-21 23:21:55.515518: Pseudo dice [0.8398] +2024-11-21 23:21:55.515602: Epoch time: 19.01 s +2024-11-21 23:21:56.431305: +2024-11-21 23:21:56.431513: Epoch 2327 +2024-11-21 23:21:56.431631: Current learning rate: 0.00734 +2024-11-21 23:22:14.972194: train_loss -0.7804 +2024-11-21 23:22:14.972442: val_loss -0.7321 +2024-11-21 23:22:14.972517: Pseudo dice [0.832] +2024-11-21 23:22:14.972593: Epoch time: 18.54 s +2024-11-21 23:22:15.884067: +2024-11-21 23:22:15.884309: Epoch 2328 +2024-11-21 23:22:15.884423: Current learning rate: 0.00734 +2024-11-21 23:22:35.595669: train_loss -0.7734 +2024-11-21 23:22:35.595890: val_loss -0.7407 +2024-11-21 23:22:35.595976: Pseudo dice [0.8271] +2024-11-21 23:22:35.596075: Epoch time: 19.71 s +2024-11-21 23:22:36.530174: +2024-11-21 23:22:36.530384: Epoch 2329 +2024-11-21 23:22:36.530498: Current learning rate: 0.00734 +2024-11-21 23:22:55.898821: train_loss -0.7776 +2024-11-21 23:22:55.899050: val_loss -0.7412 +2024-11-21 23:22:55.899126: Pseudo dice [0.8104] +2024-11-21 23:22:55.901433: Epoch time: 19.37 s +2024-11-21 23:22:56.838184: +2024-11-21 23:22:56.838387: Epoch 2330 +2024-11-21 23:22:56.838499: Current learning rate: 0.00734 +2024-11-21 23:23:15.243760: train_loss -0.7764 +2024-11-21 23:23:15.243998: val_loss -0.7412 +2024-11-21 23:23:15.244072: Pseudo dice [0.8137] +2024-11-21 23:23:15.244150: Epoch time: 18.41 s +2024-11-21 23:23:16.087431: +2024-11-21 23:23:16.087635: Epoch 2331 +2024-11-21 23:23:16.087746: Current learning rate: 0.00733 +2024-11-21 23:23:33.728552: train_loss -0.7724 +2024-11-21 23:23:33.728766: val_loss -0.736 +2024-11-21 23:23:33.728873: Pseudo dice [0.8138] +2024-11-21 23:23:33.728956: Epoch time: 17.64 s +2024-11-21 23:23:34.568931: +2024-11-21 23:23:34.569130: Epoch 2332 +2024-11-21 23:23:34.569243: Current learning rate: 0.00733 +2024-11-21 23:23:52.604928: train_loss -0.7721 +2024-11-21 23:23:52.605147: val_loss -0.7298 +2024-11-21 23:23:52.605229: Pseudo dice [0.8236] +2024-11-21 23:23:52.605307: Epoch time: 18.04 s +2024-11-21 23:23:53.442872: +2024-11-21 23:23:53.443092: Epoch 2333 +2024-11-21 23:23:53.443210: Current learning rate: 0.00733 +2024-11-21 23:24:12.729591: train_loss -0.7616 +2024-11-21 23:24:12.729835: val_loss -0.7363 +2024-11-21 23:24:12.729911: Pseudo dice [0.8381] +2024-11-21 23:24:12.730001: Epoch time: 19.29 s +2024-11-21 23:24:13.663014: +2024-11-21 23:24:13.663236: Epoch 2334 +2024-11-21 23:24:13.663351: Current learning rate: 0.00733 +2024-11-21 23:24:31.977881: train_loss -0.7784 +2024-11-21 23:24:31.978100: val_loss -0.7076 +2024-11-21 23:24:31.978183: Pseudo dice [0.8085] +2024-11-21 23:24:31.978261: Epoch time: 18.32 s +2024-11-21 23:24:32.822654: +2024-11-21 23:24:32.822859: Epoch 2335 +2024-11-21 23:24:32.822968: Current learning rate: 0.00733 +2024-11-21 23:24:51.501825: train_loss -0.7665 +2024-11-21 23:24:51.502100: val_loss -0.7252 +2024-11-21 23:24:51.502180: Pseudo dice [0.8014] +2024-11-21 23:24:51.502259: Epoch time: 18.68 s +2024-11-21 23:24:52.338423: +2024-11-21 23:24:52.338684: Epoch 2336 +2024-11-21 23:24:52.338797: Current learning rate: 0.00733 +2024-11-21 23:25:10.785877: train_loss -0.7738 +2024-11-21 23:25:10.786103: val_loss -0.7386 +2024-11-21 23:25:10.786178: Pseudo dice [0.8268] +2024-11-21 23:25:10.786259: Epoch time: 18.45 s +2024-11-21 23:25:11.633266: +2024-11-21 23:25:11.633510: Epoch 2337 +2024-11-21 23:25:11.633627: Current learning rate: 0.00733 +2024-11-21 23:25:30.623506: train_loss -0.7681 +2024-11-21 23:25:30.623748: val_loss -0.7293 +2024-11-21 23:25:30.623825: Pseudo dice [0.8241] +2024-11-21 23:25:30.623907: Epoch time: 18.99 s +2024-11-21 23:25:31.823620: +2024-11-21 23:25:31.823838: Epoch 2338 +2024-11-21 23:25:31.823952: Current learning rate: 0.00733 +2024-11-21 23:25:50.928524: train_loss -0.7566 +2024-11-21 23:25:50.928748: val_loss -0.7288 +2024-11-21 23:25:50.928825: Pseudo dice [0.8058] +2024-11-21 23:25:50.928901: Epoch time: 19.11 s +2024-11-21 23:25:51.769696: +2024-11-21 23:25:51.769921: Epoch 2339 +2024-11-21 23:25:51.770038: Current learning rate: 0.00733 +2024-11-21 23:26:10.885643: train_loss -0.766 +2024-11-21 23:26:10.885864: val_loss -0.7272 +2024-11-21 23:26:10.885937: Pseudo dice [0.812] +2024-11-21 23:26:10.886026: Epoch time: 19.12 s +2024-11-21 23:26:11.737637: +2024-11-21 23:26:11.737848: Epoch 2340 +2024-11-21 23:26:11.737959: Current learning rate: 0.00732 +2024-11-21 23:26:30.517395: train_loss -0.7764 +2024-11-21 23:26:30.517634: val_loss -0.754 +2024-11-21 23:26:30.517711: Pseudo dice [0.8383] +2024-11-21 23:26:30.517791: Epoch time: 18.78 s +2024-11-21 23:26:31.364134: +2024-11-21 23:26:31.364372: Epoch 2341 +2024-11-21 23:26:31.364485: Current learning rate: 0.00732 +2024-11-21 23:26:50.219310: train_loss -0.7769 +2024-11-21 23:26:50.219525: val_loss -0.7271 +2024-11-21 23:26:50.219600: Pseudo dice [0.8267] +2024-11-21 23:26:50.219679: Epoch time: 18.86 s +2024-11-21 23:26:51.067356: +2024-11-21 23:26:51.067553: Epoch 2342 +2024-11-21 23:26:51.067668: Current learning rate: 0.00732 +2024-11-21 23:27:08.900355: train_loss -0.7755 +2024-11-21 23:27:08.900577: val_loss -0.7506 +2024-11-21 23:27:08.900661: Pseudo dice [0.8202] +2024-11-21 23:27:08.900742: Epoch time: 17.83 s +2024-11-21 23:27:09.777236: +2024-11-21 23:27:09.777512: Epoch 2343 +2024-11-21 23:27:09.777643: Current learning rate: 0.00732 +2024-11-21 23:27:29.782055: train_loss -0.7798 +2024-11-21 23:27:29.782275: val_loss -0.7607 +2024-11-21 23:27:29.782349: Pseudo dice [0.835] +2024-11-21 23:27:29.782426: Epoch time: 20.01 s +2024-11-21 23:27:30.640333: +2024-11-21 23:27:30.640542: Epoch 2344 +2024-11-21 23:27:30.640776: Current learning rate: 0.00732 +2024-11-21 23:27:48.949562: train_loss -0.7826 +2024-11-21 23:27:48.949815: val_loss -0.7518 +2024-11-21 23:27:48.949889: Pseudo dice [0.8376] +2024-11-21 23:27:48.949970: Epoch time: 18.31 s +2024-11-21 23:27:49.789235: +2024-11-21 23:27:49.789438: Epoch 2345 +2024-11-21 23:27:49.789554: Current learning rate: 0.00732 +2024-11-21 23:28:08.406792: train_loss -0.7752 +2024-11-21 23:28:08.407017: val_loss -0.7487 +2024-11-21 23:28:08.407092: Pseudo dice [0.8331] +2024-11-21 23:28:08.407169: Epoch time: 18.62 s +2024-11-21 23:28:09.249771: +2024-11-21 23:28:09.250001: Epoch 2346 +2024-11-21 23:28:09.250116: Current learning rate: 0.00732 +2024-11-21 23:28:28.505048: train_loss -0.7769 +2024-11-21 23:28:28.505269: val_loss -0.7346 +2024-11-21 23:28:28.505342: Pseudo dice [0.8295] +2024-11-21 23:28:28.505443: Epoch time: 19.26 s +2024-11-21 23:28:29.348980: +2024-11-21 23:28:29.349204: Epoch 2347 +2024-11-21 23:28:29.349320: Current learning rate: 0.00732 +2024-11-21 23:28:47.763395: train_loss -0.7725 +2024-11-21 23:28:47.763630: val_loss -0.7492 +2024-11-21 23:28:47.763703: Pseudo dice [0.7981] +2024-11-21 23:28:47.763785: Epoch time: 18.42 s +2024-11-21 23:28:48.708838: +2024-11-21 23:28:48.709079: Epoch 2348 +2024-11-21 23:28:48.709192: Current learning rate: 0.00731 +2024-11-21 23:29:06.413153: train_loss -0.7822 +2024-11-21 23:29:06.413419: val_loss -0.7411 +2024-11-21 23:29:06.413494: Pseudo dice [0.8328] +2024-11-21 23:29:06.413567: Epoch time: 17.71 s +2024-11-21 23:29:07.263663: +2024-11-21 23:29:07.263855: Epoch 2349 +2024-11-21 23:29:07.263968: Current learning rate: 0.00731 +2024-11-21 23:29:27.575501: train_loss -0.7644 +2024-11-21 23:29:27.575759: val_loss -0.7294 +2024-11-21 23:29:27.576472: Pseudo dice [0.825] +2024-11-21 23:29:27.576553: Epoch time: 20.31 s +2024-11-21 23:29:28.993003: +2024-11-21 23:29:28.993216: Epoch 2350 +2024-11-21 23:29:28.993333: Current learning rate: 0.00731 +2024-11-21 23:29:46.714094: train_loss -0.7793 +2024-11-21 23:29:46.714344: val_loss -0.7529 +2024-11-21 23:29:46.714418: Pseudo dice [0.829] +2024-11-21 23:29:46.714498: Epoch time: 17.72 s +2024-11-21 23:29:47.552589: +2024-11-21 23:29:47.552813: Epoch 2351 +2024-11-21 23:29:47.552925: Current learning rate: 0.00731 +2024-11-21 23:30:05.542195: train_loss -0.7842 +2024-11-21 23:30:05.542426: val_loss -0.7334 +2024-11-21 23:30:05.542501: Pseudo dice [0.8268] +2024-11-21 23:30:05.542577: Epoch time: 17.99 s +2024-11-21 23:30:06.380034: +2024-11-21 23:30:06.380264: Epoch 2352 +2024-11-21 23:30:06.380381: Current learning rate: 0.00731 +2024-11-21 23:30:26.657102: train_loss -0.775 +2024-11-21 23:30:26.657319: val_loss -0.7387 +2024-11-21 23:30:26.657391: Pseudo dice [0.8267] +2024-11-21 23:30:26.657467: Epoch time: 20.28 s +2024-11-21 23:30:27.538203: +2024-11-21 23:30:27.538407: Epoch 2353 +2024-11-21 23:30:27.538520: Current learning rate: 0.00731 +2024-11-21 23:30:45.751209: train_loss -0.7731 +2024-11-21 23:30:45.751520: val_loss -0.7384 +2024-11-21 23:30:45.751598: Pseudo dice [0.8457] +2024-11-21 23:30:45.751682: Epoch time: 18.21 s +2024-11-21 23:30:46.591695: +2024-11-21 23:30:46.591896: Epoch 2354 +2024-11-21 23:30:46.592021: Current learning rate: 0.00731 +2024-11-21 23:31:05.032354: train_loss -0.7605 +2024-11-21 23:31:05.032572: val_loss -0.7142 +2024-11-21 23:31:05.032645: Pseudo dice [0.8168] +2024-11-21 23:31:05.032717: Epoch time: 18.44 s +2024-11-21 23:31:05.869531: +2024-11-21 23:31:05.869821: Epoch 2355 +2024-11-21 23:31:05.869934: Current learning rate: 0.00731 +2024-11-21 23:31:25.073565: train_loss -0.7697 +2024-11-21 23:31:25.073797: val_loss -0.7249 +2024-11-21 23:31:25.073884: Pseudo dice [0.8048] +2024-11-21 23:31:25.073972: Epoch time: 19.2 s +2024-11-21 23:31:25.924611: +2024-11-21 23:31:25.924814: Epoch 2356 +2024-11-21 23:31:25.924929: Current learning rate: 0.00731 +2024-11-21 23:31:44.253288: train_loss -0.7842 +2024-11-21 23:31:44.253503: val_loss -0.7245 +2024-11-21 23:31:44.253579: Pseudo dice [0.804] +2024-11-21 23:31:44.253655: Epoch time: 18.33 s +2024-11-21 23:31:45.099719: +2024-11-21 23:31:45.099927: Epoch 2357 +2024-11-21 23:31:45.100046: Current learning rate: 0.0073 +2024-11-21 23:32:03.584038: train_loss -0.7696 +2024-11-21 23:32:03.584334: val_loss -0.7365 +2024-11-21 23:32:03.584416: Pseudo dice [0.8129] +2024-11-21 23:32:03.584506: Epoch time: 18.49 s +2024-11-21 23:32:04.432089: +2024-11-21 23:32:04.432373: Epoch 2358 +2024-11-21 23:32:04.432487: Current learning rate: 0.0073 +2024-11-21 23:32:23.400123: train_loss -0.7797 +2024-11-21 23:32:23.400359: val_loss -0.7327 +2024-11-21 23:32:23.400441: Pseudo dice [0.8268] +2024-11-21 23:32:23.400519: Epoch time: 18.97 s +2024-11-21 23:32:24.242103: +2024-11-21 23:32:24.242322: Epoch 2359 +2024-11-21 23:32:24.242434: Current learning rate: 0.0073 +2024-11-21 23:32:43.812752: train_loss -0.768 +2024-11-21 23:32:43.812979: val_loss -0.7353 +2024-11-21 23:32:43.813061: Pseudo dice [0.8384] +2024-11-21 23:32:43.815350: Epoch time: 19.57 s +2024-11-21 23:32:44.846596: +2024-11-21 23:32:44.846795: Epoch 2360 +2024-11-21 23:32:44.846906: Current learning rate: 0.0073 +2024-11-21 23:33:03.148593: train_loss -0.771 +2024-11-21 23:33:03.153998: val_loss -0.7716 +2024-11-21 23:33:03.154115: Pseudo dice [0.8391] +2024-11-21 23:33:03.154198: Epoch time: 18.3 s +2024-11-21 23:33:04.188917: +2024-11-21 23:33:04.189143: Epoch 2361 +2024-11-21 23:33:04.189255: Current learning rate: 0.0073 +2024-11-21 23:33:23.256299: train_loss -0.782 +2024-11-21 23:33:23.256532: val_loss -0.7337 +2024-11-21 23:33:23.256660: Pseudo dice [0.8344] +2024-11-21 23:33:23.256744: Epoch time: 19.07 s +2024-11-21 23:33:24.490258: +2024-11-21 23:33:24.490472: Epoch 2362 +2024-11-21 23:33:24.490588: Current learning rate: 0.0073 +2024-11-21 23:33:42.172590: train_loss -0.7764 +2024-11-21 23:33:42.172878: val_loss -0.714 +2024-11-21 23:33:42.172958: Pseudo dice [0.82] +2024-11-21 23:33:42.173040: Epoch time: 17.68 s +2024-11-21 23:33:43.014790: +2024-11-21 23:33:43.015029: Epoch 2363 +2024-11-21 23:33:43.015143: Current learning rate: 0.0073 +2024-11-21 23:34:02.915447: train_loss -0.7675 +2024-11-21 23:34:02.915664: val_loss -0.7399 +2024-11-21 23:34:02.915738: Pseudo dice [0.8195] +2024-11-21 23:34:02.915813: Epoch time: 19.9 s +2024-11-21 23:34:03.758586: +2024-11-21 23:34:03.758797: Epoch 2364 +2024-11-21 23:34:03.758908: Current learning rate: 0.0073 +2024-11-21 23:34:22.954776: train_loss -0.7764 +2024-11-21 23:34:22.957203: val_loss -0.7495 +2024-11-21 23:34:22.957286: Pseudo dice [0.8203] +2024-11-21 23:34:22.957368: Epoch time: 19.2 s +2024-11-21 23:34:23.947018: +2024-11-21 23:34:23.947225: Epoch 2365 +2024-11-21 23:34:23.947335: Current learning rate: 0.00729 +2024-11-21 23:34:43.907702: train_loss -0.7766 +2024-11-21 23:34:43.907921: val_loss -0.7212 +2024-11-21 23:34:43.908002: Pseudo dice [0.8288] +2024-11-21 23:34:43.908077: Epoch time: 19.96 s +2024-11-21 23:34:44.755239: +2024-11-21 23:34:44.755533: Epoch 2366 +2024-11-21 23:34:44.755643: Current learning rate: 0.00729 +2024-11-21 23:35:02.834902: train_loss -0.7793 +2024-11-21 23:35:02.835121: val_loss -0.7647 +2024-11-21 23:35:02.835197: Pseudo dice [0.8343] +2024-11-21 23:35:02.835273: Epoch time: 18.08 s +2024-11-21 23:35:03.679726: +2024-11-21 23:35:03.680014: Epoch 2367 +2024-11-21 23:35:03.680133: Current learning rate: 0.00729 +2024-11-21 23:35:22.503827: train_loss -0.7761 +2024-11-21 23:35:22.506197: val_loss -0.7393 +2024-11-21 23:35:22.506297: Pseudo dice [0.8338] +2024-11-21 23:35:22.506380: Epoch time: 18.82 s +2024-11-21 23:35:23.426299: +2024-11-21 23:35:23.426569: Epoch 2368 +2024-11-21 23:35:23.426680: Current learning rate: 0.00729 +2024-11-21 23:35:42.485800: train_loss -0.7765 +2024-11-21 23:35:42.486064: val_loss -0.7493 +2024-11-21 23:35:42.486139: Pseudo dice [0.8251] +2024-11-21 23:35:42.486225: Epoch time: 19.06 s +2024-11-21 23:35:43.339080: +2024-11-21 23:35:43.339316: Epoch 2369 +2024-11-21 23:35:43.339448: Current learning rate: 0.00729 +2024-11-21 23:36:02.266335: train_loss -0.7686 +2024-11-21 23:36:02.266564: val_loss -0.737 +2024-11-21 23:36:02.266638: Pseudo dice [0.8035] +2024-11-21 23:36:02.266712: Epoch time: 18.93 s +2024-11-21 23:36:03.120366: +2024-11-21 23:36:03.120713: Epoch 2370 +2024-11-21 23:36:03.120836: Current learning rate: 0.00729 +2024-11-21 23:36:22.198148: train_loss -0.7807 +2024-11-21 23:36:22.198377: val_loss -0.7653 +2024-11-21 23:36:22.198452: Pseudo dice [0.8418] +2024-11-21 23:36:22.198532: Epoch time: 19.08 s +2024-11-21 23:36:23.050351: +2024-11-21 23:36:23.050580: Epoch 2371 +2024-11-21 23:36:23.050695: Current learning rate: 0.00729 +2024-11-21 23:36:41.996483: train_loss -0.7789 +2024-11-21 23:36:41.996723: val_loss -0.7177 +2024-11-21 23:36:41.996800: Pseudo dice [0.8149] +2024-11-21 23:36:41.996879: Epoch time: 18.95 s +2024-11-21 23:36:43.083459: +2024-11-21 23:36:43.083797: Epoch 2372 +2024-11-21 23:36:43.083914: Current learning rate: 0.00729 +2024-11-21 23:37:01.613874: train_loss -0.7803 +2024-11-21 23:37:01.614093: val_loss -0.7218 +2024-11-21 23:37:01.614167: Pseudo dice [0.8094] +2024-11-21 23:37:01.614247: Epoch time: 18.53 s +2024-11-21 23:37:02.457226: +2024-11-21 23:37:02.457431: Epoch 2373 +2024-11-21 23:37:02.457544: Current learning rate: 0.00729 +2024-11-21 23:37:21.640891: train_loss -0.7746 +2024-11-21 23:37:21.641120: val_loss -0.7232 +2024-11-21 23:37:21.641205: Pseudo dice [0.8014] +2024-11-21 23:37:21.641287: Epoch time: 19.18 s +2024-11-21 23:37:22.913985: +2024-11-21 23:37:22.914218: Epoch 2374 +2024-11-21 23:37:22.914325: Current learning rate: 0.00728 +2024-11-21 23:37:41.031783: train_loss -0.7815 +2024-11-21 23:37:41.032095: val_loss -0.7436 +2024-11-21 23:37:41.032174: Pseudo dice [0.8278] +2024-11-21 23:37:41.032259: Epoch time: 18.12 s +2024-11-21 23:37:41.886553: +2024-11-21 23:37:41.886768: Epoch 2375 +2024-11-21 23:37:41.886885: Current learning rate: 0.00728 +2024-11-21 23:38:00.327850: train_loss -0.7817 +2024-11-21 23:38:00.328120: val_loss -0.7335 +2024-11-21 23:38:00.328201: Pseudo dice [0.7998] +2024-11-21 23:38:00.328284: Epoch time: 18.44 s +2024-11-21 23:38:01.174339: +2024-11-21 23:38:01.174562: Epoch 2376 +2024-11-21 23:38:01.174676: Current learning rate: 0.00728 +2024-11-21 23:38:19.887294: train_loss -0.781 +2024-11-21 23:38:19.887507: val_loss -0.7393 +2024-11-21 23:38:19.887579: Pseudo dice [0.8093] +2024-11-21 23:38:19.887655: Epoch time: 18.71 s +2024-11-21 23:38:20.731615: +2024-11-21 23:38:20.731908: Epoch 2377 +2024-11-21 23:38:20.732028: Current learning rate: 0.00728 +2024-11-21 23:38:38.924552: train_loss -0.7725 +2024-11-21 23:38:38.924839: val_loss -0.7604 +2024-11-21 23:38:38.924916: Pseudo dice [0.846] +2024-11-21 23:38:38.925009: Epoch time: 18.19 s +2024-11-21 23:38:39.770325: +2024-11-21 23:38:39.770597: Epoch 2378 +2024-11-21 23:38:39.770714: Current learning rate: 0.00728 +2024-11-21 23:38:59.002931: train_loss -0.7741 +2024-11-21 23:38:59.003175: val_loss -0.735 +2024-11-21 23:38:59.003248: Pseudo dice [0.8246] +2024-11-21 23:38:59.003325: Epoch time: 19.23 s +2024-11-21 23:38:59.871685: +2024-11-21 23:38:59.872008: Epoch 2379 +2024-11-21 23:38:59.872130: Current learning rate: 0.00728 +2024-11-21 23:39:18.568205: train_loss -0.7619 +2024-11-21 23:39:18.568430: val_loss -0.7178 +2024-11-21 23:39:18.568508: Pseudo dice [0.8126] +2024-11-21 23:39:18.568586: Epoch time: 18.7 s +2024-11-21 23:39:19.412472: +2024-11-21 23:39:19.412835: Epoch 2380 +2024-11-21 23:39:19.412948: Current learning rate: 0.00728 +2024-11-21 23:39:37.613563: train_loss -0.762 +2024-11-21 23:39:37.613840: val_loss -0.7289 +2024-11-21 23:39:37.613917: Pseudo dice [0.7981] +2024-11-21 23:39:37.614003: Epoch time: 18.2 s +2024-11-21 23:39:38.464708: +2024-11-21 23:39:38.464911: Epoch 2381 +2024-11-21 23:39:38.465026: Current learning rate: 0.00728 +2024-11-21 23:39:57.845252: train_loss -0.7568 +2024-11-21 23:39:57.845558: val_loss -0.7322 +2024-11-21 23:39:57.845633: Pseudo dice [0.8047] +2024-11-21 23:39:57.845715: Epoch time: 19.38 s +2024-11-21 23:39:58.693363: +2024-11-21 23:39:58.693644: Epoch 2382 +2024-11-21 23:39:58.693760: Current learning rate: 0.00728 +2024-11-21 23:40:18.580660: train_loss -0.75 +2024-11-21 23:40:18.580887: val_loss -0.7506 +2024-11-21 23:40:18.580963: Pseudo dice [0.8137] +2024-11-21 23:40:18.581050: Epoch time: 19.89 s +2024-11-21 23:40:19.459670: +2024-11-21 23:40:19.459865: Epoch 2383 +2024-11-21 23:40:19.459977: Current learning rate: 0.00727 +2024-11-21 23:40:37.027822: train_loss -0.7629 +2024-11-21 23:40:37.028059: val_loss -0.7276 +2024-11-21 23:40:37.033380: Pseudo dice [0.812] +2024-11-21 23:40:37.033477: Epoch time: 17.57 s +2024-11-21 23:40:38.313237: +2024-11-21 23:40:38.313489: Epoch 2384 +2024-11-21 23:40:38.313606: Current learning rate: 0.00727 +2024-11-21 23:40:57.310599: train_loss -0.7653 +2024-11-21 23:40:57.310838: val_loss -0.7458 +2024-11-21 23:40:57.310917: Pseudo dice [0.8387] +2024-11-21 23:40:57.311010: Epoch time: 19.0 s +2024-11-21 23:40:58.156124: +2024-11-21 23:40:58.156318: Epoch 2385 +2024-11-21 23:40:58.156431: Current learning rate: 0.00727 +2024-11-21 23:41:16.729257: train_loss -0.7732 +2024-11-21 23:41:16.729526: val_loss -0.722 +2024-11-21 23:41:16.729601: Pseudo dice [0.821] +2024-11-21 23:41:16.729678: Epoch time: 18.57 s +2024-11-21 23:41:17.990452: +2024-11-21 23:41:17.990741: Epoch 2386 +2024-11-21 23:41:17.990852: Current learning rate: 0.00727 +2024-11-21 23:41:36.967041: train_loss -0.765 +2024-11-21 23:41:36.967339: val_loss -0.7325 +2024-11-21 23:41:36.967417: Pseudo dice [0.8151] +2024-11-21 23:41:36.967496: Epoch time: 18.98 s +2024-11-21 23:41:37.821895: +2024-11-21 23:41:37.822116: Epoch 2387 +2024-11-21 23:41:37.822234: Current learning rate: 0.00727 +2024-11-21 23:41:57.148117: train_loss -0.7622 +2024-11-21 23:41:57.148336: val_loss -0.7528 +2024-11-21 23:41:57.148407: Pseudo dice [0.8167] +2024-11-21 23:41:57.148751: Epoch time: 19.33 s +2024-11-21 23:41:58.000995: +2024-11-21 23:41:58.001210: Epoch 2388 +2024-11-21 23:41:58.001329: Current learning rate: 0.00727 +2024-11-21 23:42:16.896273: train_loss -0.7676 +2024-11-21 23:42:16.896512: val_loss -0.7388 +2024-11-21 23:42:16.896587: Pseudo dice [0.823] +2024-11-21 23:42:16.896671: Epoch time: 18.9 s +2024-11-21 23:42:17.765904: +2024-11-21 23:42:17.766207: Epoch 2389 +2024-11-21 23:42:17.766324: Current learning rate: 0.00727 +2024-11-21 23:42:36.948895: train_loss -0.7626 +2024-11-21 23:42:36.951196: val_loss -0.7373 +2024-11-21 23:42:36.951312: Pseudo dice [0.8174] +2024-11-21 23:42:36.951399: Epoch time: 19.18 s +2024-11-21 23:42:37.954193: +2024-11-21 23:42:37.954497: Epoch 2390 +2024-11-21 23:42:37.954616: Current learning rate: 0.00727 +2024-11-21 23:42:57.054888: train_loss -0.7733 +2024-11-21 23:42:57.055109: val_loss -0.7376 +2024-11-21 23:42:57.055185: Pseudo dice [0.8167] +2024-11-21 23:42:57.055265: Epoch time: 19.1 s +2024-11-21 23:42:57.906112: +2024-11-21 23:42:57.906297: Epoch 2391 +2024-11-21 23:42:57.906409: Current learning rate: 0.00726 +2024-11-21 23:43:17.280703: train_loss -0.7623 +2024-11-21 23:43:17.280913: val_loss -0.7591 +2024-11-21 23:43:17.280988: Pseudo dice [0.8338] +2024-11-21 23:43:17.281070: Epoch time: 19.38 s +2024-11-21 23:43:18.132034: +2024-11-21 23:43:18.132293: Epoch 2392 +2024-11-21 23:43:18.132520: Current learning rate: 0.00726 +2024-11-21 23:43:36.872292: train_loss -0.7628 +2024-11-21 23:43:36.872525: val_loss -0.75 +2024-11-21 23:43:36.872601: Pseudo dice [0.8426] +2024-11-21 23:43:36.872682: Epoch time: 18.74 s +2024-11-21 23:43:37.724237: +2024-11-21 23:43:37.724525: Epoch 2393 +2024-11-21 23:43:37.724643: Current learning rate: 0.00726 +2024-11-21 23:43:56.564487: train_loss -0.7764 +2024-11-21 23:43:56.564695: val_loss -0.7355 +2024-11-21 23:43:56.564769: Pseudo dice [0.8243] +2024-11-21 23:43:56.564845: Epoch time: 18.84 s +2024-11-21 23:43:57.416739: +2024-11-21 23:43:57.417006: Epoch 2394 +2024-11-21 23:43:57.417118: Current learning rate: 0.00726 +2024-11-21 23:44:16.356215: train_loss -0.7767 +2024-11-21 23:44:16.356430: val_loss -0.7284 +2024-11-21 23:44:16.356520: Pseudo dice [0.8271] +2024-11-21 23:44:16.356604: Epoch time: 18.94 s +2024-11-21 23:44:17.203861: +2024-11-21 23:44:17.204085: Epoch 2395 +2024-11-21 23:44:17.204201: Current learning rate: 0.00726 +2024-11-21 23:44:36.629777: train_loss -0.776 +2024-11-21 23:44:36.630036: val_loss -0.7303 +2024-11-21 23:44:36.630111: Pseudo dice [0.8081] +2024-11-21 23:44:36.630194: Epoch time: 19.43 s +2024-11-21 23:44:37.710947: +2024-11-21 23:44:37.711797: Epoch 2396 +2024-11-21 23:44:37.712014: Current learning rate: 0.00726 +2024-11-21 23:44:56.465351: train_loss -0.7824 +2024-11-21 23:44:56.465571: val_loss -0.7343 +2024-11-21 23:44:56.465659: Pseudo dice [0.8469] +2024-11-21 23:44:56.465744: Epoch time: 18.76 s +2024-11-21 23:44:57.319169: +2024-11-21 23:44:57.319417: Epoch 2397 +2024-11-21 23:44:57.319534: Current learning rate: 0.00726 +2024-11-21 23:45:15.397463: train_loss -0.7857 +2024-11-21 23:45:15.397688: val_loss -0.7541 +2024-11-21 23:45:15.397765: Pseudo dice [0.8271] +2024-11-21 23:45:15.402977: Epoch time: 18.08 s +2024-11-21 23:45:16.686561: +2024-11-21 23:45:16.686820: Epoch 2398 +2024-11-21 23:45:16.686934: Current learning rate: 0.00726 +2024-11-21 23:45:35.095471: train_loss -0.7739 +2024-11-21 23:45:35.095736: val_loss -0.7438 +2024-11-21 23:45:35.095811: Pseudo dice [0.8226] +2024-11-21 23:45:35.095895: Epoch time: 18.41 s +2024-11-21 23:45:35.948982: +2024-11-21 23:45:35.949201: Epoch 2399 +2024-11-21 23:45:35.949317: Current learning rate: 0.00726 +2024-11-21 23:45:54.583946: train_loss -0.7785 +2024-11-21 23:45:54.584222: val_loss -0.7519 +2024-11-21 23:45:54.584300: Pseudo dice [0.8365] +2024-11-21 23:45:54.584386: Epoch time: 18.64 s +2024-11-21 23:45:55.649082: +2024-11-21 23:45:55.649333: Epoch 2400 +2024-11-21 23:45:55.649444: Current learning rate: 0.00725 +2024-11-21 23:46:14.400263: train_loss -0.7846 +2024-11-21 23:46:14.418894: val_loss -0.7398 +2024-11-21 23:46:14.418987: Pseudo dice [0.8341] +2024-11-21 23:46:14.419070: Epoch time: 18.75 s +2024-11-21 23:46:15.263450: +2024-11-21 23:46:15.263653: Epoch 2401 +2024-11-21 23:46:15.263766: Current learning rate: 0.00725 +2024-11-21 23:46:32.935055: train_loss -0.7771 +2024-11-21 23:46:32.935311: val_loss -0.7393 +2024-11-21 23:46:32.935386: Pseudo dice [0.83] +2024-11-21 23:46:32.935472: Epoch time: 17.67 s +2024-11-21 23:46:33.802207: +2024-11-21 23:46:33.802432: Epoch 2402 +2024-11-21 23:46:33.802545: Current learning rate: 0.00725 +2024-11-21 23:46:53.133272: train_loss -0.7872 +2024-11-21 23:46:53.133493: val_loss -0.7372 +2024-11-21 23:46:53.133568: Pseudo dice [0.8221] +2024-11-21 23:46:53.138868: Epoch time: 19.33 s +2024-11-21 23:46:54.011131: +2024-11-21 23:46:54.011390: Epoch 2403 +2024-11-21 23:46:54.011509: Current learning rate: 0.00725 +2024-11-21 23:47:14.030333: train_loss -0.7739 +2024-11-21 23:47:14.035756: val_loss -0.7396 +2024-11-21 23:47:14.035841: Pseudo dice [0.8212] +2024-11-21 23:47:14.035923: Epoch time: 20.02 s +2024-11-21 23:47:14.888923: +2024-11-21 23:47:14.889146: Epoch 2404 +2024-11-21 23:47:14.889261: Current learning rate: 0.00725 +2024-11-21 23:47:33.310390: train_loss -0.7814 +2024-11-21 23:47:33.310607: val_loss -0.7484 +2024-11-21 23:47:33.310683: Pseudo dice [0.8339] +2024-11-21 23:47:33.310760: Epoch time: 18.42 s +2024-11-21 23:47:34.154622: +2024-11-21 23:47:34.154815: Epoch 2405 +2024-11-21 23:47:34.154957: Current learning rate: 0.00725 +2024-11-21 23:47:53.352083: train_loss -0.7694 +2024-11-21 23:47:53.352315: val_loss -0.7507 +2024-11-21 23:47:53.352389: Pseudo dice [0.8264] +2024-11-21 23:47:53.352476: Epoch time: 19.2 s +2024-11-21 23:47:54.202955: +2024-11-21 23:47:54.203153: Epoch 2406 +2024-11-21 23:47:54.203268: Current learning rate: 0.00725 +2024-11-21 23:48:13.346788: train_loss -0.7762 +2024-11-21 23:48:13.347008: val_loss -0.7528 +2024-11-21 23:48:13.347082: Pseudo dice [0.8365] +2024-11-21 23:48:13.347156: Epoch time: 19.14 s +2024-11-21 23:48:14.182909: +2024-11-21 23:48:14.183122: Epoch 2407 +2024-11-21 23:48:14.183234: Current learning rate: 0.00725 +2024-11-21 23:48:33.092245: train_loss -0.7708 +2024-11-21 23:48:33.092460: val_loss -0.7355 +2024-11-21 23:48:33.092536: Pseudo dice [0.8066] +2024-11-21 23:48:33.092616: Epoch time: 18.91 s +2024-11-21 23:48:33.936179: +2024-11-21 23:48:33.936379: Epoch 2408 +2024-11-21 23:48:33.936491: Current learning rate: 0.00724 +2024-11-21 23:48:52.934261: train_loss -0.7781 +2024-11-21 23:48:52.934484: val_loss -0.7264 +2024-11-21 23:48:52.934560: Pseudo dice [0.8311] +2024-11-21 23:48:52.934635: Epoch time: 19.0 s +2024-11-21 23:48:53.778494: +2024-11-21 23:48:53.778675: Epoch 2409 +2024-11-21 23:48:53.778784: Current learning rate: 0.00724 +2024-11-21 23:49:12.422091: train_loss -0.7765 +2024-11-21 23:49:12.422331: val_loss -0.7416 +2024-11-21 23:49:12.422406: Pseudo dice [0.8265] +2024-11-21 23:49:12.422487: Epoch time: 18.64 s +2024-11-21 23:49:13.656586: +2024-11-21 23:49:13.656791: Epoch 2410 +2024-11-21 23:49:13.656903: Current learning rate: 0.00724 +2024-11-21 23:49:32.228884: train_loss -0.7564 +2024-11-21 23:49:32.229122: val_loss -0.7289 +2024-11-21 23:49:32.229197: Pseudo dice [0.8091] +2024-11-21 23:49:32.229273: Epoch time: 18.57 s +2024-11-21 23:49:33.076936: +2024-11-21 23:49:33.077150: Epoch 2411 +2024-11-21 23:49:33.077265: Current learning rate: 0.00724 +2024-11-21 23:49:51.205414: train_loss -0.767 +2024-11-21 23:49:51.205970: val_loss -0.7479 +2024-11-21 23:49:51.206053: Pseudo dice [0.8265] +2024-11-21 23:49:51.206127: Epoch time: 18.13 s +2024-11-21 23:49:52.047493: +2024-11-21 23:49:52.047738: Epoch 2412 +2024-11-21 23:49:52.047849: Current learning rate: 0.00724 +2024-11-21 23:50:11.577566: train_loss -0.7822 +2024-11-21 23:50:11.577798: val_loss -0.744 +2024-11-21 23:50:11.577875: Pseudo dice [0.7984] +2024-11-21 23:50:11.577959: Epoch time: 19.53 s +2024-11-21 23:50:12.459255: +2024-11-21 23:50:12.459467: Epoch 2413 +2024-11-21 23:50:12.486482: Current learning rate: 0.00724 +2024-11-21 23:50:31.688030: train_loss -0.7751 +2024-11-21 23:50:31.688257: val_loss -0.7529 +2024-11-21 23:50:31.688333: Pseudo dice [0.8256] +2024-11-21 23:50:31.688413: Epoch time: 19.23 s +2024-11-21 23:50:32.538688: +2024-11-21 23:50:32.538872: Epoch 2414 +2024-11-21 23:50:32.539010: Current learning rate: 0.00724 +2024-11-21 23:50:51.530164: train_loss -0.7794 +2024-11-21 23:50:51.530386: val_loss -0.7557 +2024-11-21 23:50:51.530462: Pseudo dice [0.8135] +2024-11-21 23:50:51.530539: Epoch time: 18.99 s +2024-11-21 23:50:52.377597: +2024-11-21 23:50:52.377790: Epoch 2415 +2024-11-21 23:50:52.377904: Current learning rate: 0.00724 +2024-11-21 23:51:11.209160: train_loss -0.7778 +2024-11-21 23:51:11.209373: val_loss -0.7649 +2024-11-21 23:51:11.209448: Pseudo dice [0.8213] +2024-11-21 23:51:11.209532: Epoch time: 18.83 s +2024-11-21 23:51:12.055675: +2024-11-21 23:51:12.055865: Epoch 2416 +2024-11-21 23:51:12.055976: Current learning rate: 0.00724 +2024-11-21 23:51:30.789072: train_loss -0.7853 +2024-11-21 23:51:30.789326: val_loss -0.7515 +2024-11-21 23:51:30.789402: Pseudo dice [0.8348] +2024-11-21 23:51:30.789485: Epoch time: 18.73 s +2024-11-21 23:51:31.641353: +2024-11-21 23:51:31.641556: Epoch 2417 +2024-11-21 23:51:31.641670: Current learning rate: 0.00723 +2024-11-21 23:51:49.790317: train_loss -0.7739 +2024-11-21 23:51:49.790534: val_loss -0.7374 +2024-11-21 23:51:49.790610: Pseudo dice [0.8317] +2024-11-21 23:51:49.790686: Epoch time: 18.15 s +2024-11-21 23:51:50.667069: +2024-11-21 23:51:50.667258: Epoch 2418 +2024-11-21 23:51:50.667372: Current learning rate: 0.00723 +2024-11-21 23:52:09.709469: train_loss -0.775 +2024-11-21 23:52:09.709696: val_loss -0.7386 +2024-11-21 23:52:09.709773: Pseudo dice [0.8323] +2024-11-21 23:52:09.709850: Epoch time: 19.04 s +2024-11-21 23:52:10.648092: +2024-11-21 23:52:10.648318: Epoch 2419 +2024-11-21 23:52:10.648433: Current learning rate: 0.00723 +2024-11-21 23:52:29.597604: train_loss -0.7611 +2024-11-21 23:52:29.597823: val_loss -0.7221 +2024-11-21 23:52:29.597901: Pseudo dice [0.8143] +2024-11-21 23:52:29.597978: Epoch time: 18.95 s +2024-11-21 23:52:30.446548: +2024-11-21 23:52:30.446824: Epoch 2420 +2024-11-21 23:52:30.446936: Current learning rate: 0.00723 +2024-11-21 23:52:49.326206: train_loss -0.7602 +2024-11-21 23:52:49.326448: val_loss -0.7462 +2024-11-21 23:52:49.326523: Pseudo dice [0.8141] +2024-11-21 23:52:49.326605: Epoch time: 18.88 s +2024-11-21 23:52:50.217951: +2024-11-21 23:52:50.218174: Epoch 2421 +2024-11-21 23:52:50.218289: Current learning rate: 0.00723 +2024-11-21 23:53:09.476926: train_loss -0.758 +2024-11-21 23:53:09.477237: val_loss -0.747 +2024-11-21 23:53:09.477314: Pseudo dice [0.829] +2024-11-21 23:53:09.477395: Epoch time: 19.26 s +2024-11-21 23:53:10.760261: +2024-11-21 23:53:10.760473: Epoch 2422 +2024-11-21 23:53:10.760586: Current learning rate: 0.00723 +2024-11-21 23:53:30.271782: train_loss -0.7667 +2024-11-21 23:53:30.272024: val_loss -0.7497 +2024-11-21 23:53:30.272102: Pseudo dice [0.8106] +2024-11-21 23:53:30.272185: Epoch time: 19.51 s +2024-11-21 23:53:31.121668: +2024-11-21 23:53:31.121907: Epoch 2423 +2024-11-21 23:53:31.122076: Current learning rate: 0.00723 +2024-11-21 23:53:49.448526: train_loss -0.7768 +2024-11-21 23:53:49.448747: val_loss -0.7596 +2024-11-21 23:53:49.448821: Pseudo dice [0.8174] +2024-11-21 23:53:49.451111: Epoch time: 18.33 s +2024-11-21 23:53:50.306922: +2024-11-21 23:53:50.307129: Epoch 2424 +2024-11-21 23:53:50.307242: Current learning rate: 0.00723 +2024-11-21 23:54:08.553079: train_loss -0.7802 +2024-11-21 23:54:08.553307: val_loss -0.7483 +2024-11-21 23:54:08.553386: Pseudo dice [0.8236] +2024-11-21 23:54:08.553461: Epoch time: 18.25 s +2024-11-21 23:54:09.441059: +2024-11-21 23:54:09.441327: Epoch 2425 +2024-11-21 23:54:09.441448: Current learning rate: 0.00723 +2024-11-21 23:54:28.021741: train_loss -0.7832 +2024-11-21 23:54:28.021956: val_loss -0.7406 +2024-11-21 23:54:28.022038: Pseudo dice [0.8172] +2024-11-21 23:54:28.022186: Epoch time: 18.58 s +2024-11-21 23:54:28.875751: +2024-11-21 23:54:28.875937: Epoch 2426 +2024-11-21 23:54:28.876050: Current learning rate: 0.00722 +2024-11-21 23:54:48.028646: train_loss -0.7792 +2024-11-21 23:54:48.028894: val_loss -0.7463 +2024-11-21 23:54:48.028971: Pseudo dice [0.8269] +2024-11-21 23:54:48.029078: Epoch time: 19.15 s +2024-11-21 23:54:48.982931: +2024-11-21 23:54:48.983171: Epoch 2427 +2024-11-21 23:54:48.983284: Current learning rate: 0.00722 +2024-11-21 23:55:08.031615: train_loss -0.7857 +2024-11-21 23:55:08.031866: val_loss -0.7675 +2024-11-21 23:55:08.031987: Pseudo dice [0.8248] +2024-11-21 23:55:08.032094: Epoch time: 19.05 s +2024-11-21 23:55:08.981133: +2024-11-21 23:55:08.981420: Epoch 2428 +2024-11-21 23:55:08.981536: Current learning rate: 0.00722 +2024-11-21 23:55:27.701668: train_loss -0.7701 +2024-11-21 23:55:27.701884: val_loss -0.7416 +2024-11-21 23:55:27.701958: Pseudo dice [0.8196] +2024-11-21 23:55:27.702046: Epoch time: 18.72 s +2024-11-21 23:55:28.547551: +2024-11-21 23:55:28.547796: Epoch 2429 +2024-11-21 23:55:28.547915: Current learning rate: 0.00722 +2024-11-21 23:55:47.788658: train_loss -0.7753 +2024-11-21 23:55:47.791073: val_loss -0.7134 +2024-11-21 23:55:47.791185: Pseudo dice [0.814] +2024-11-21 23:55:47.791273: Epoch time: 19.24 s +2024-11-21 23:55:48.685206: +2024-11-21 23:55:48.685419: Epoch 2430 +2024-11-21 23:55:48.685529: Current learning rate: 0.00722 +2024-11-21 23:56:07.266537: train_loss -0.7746 +2024-11-21 23:56:07.266774: val_loss -0.7325 +2024-11-21 23:56:07.266849: Pseudo dice [0.8122] +2024-11-21 23:56:07.267003: Epoch time: 18.58 s +2024-11-21 23:56:08.121917: +2024-11-21 23:56:08.122141: Epoch 2431 +2024-11-21 23:56:08.122252: Current learning rate: 0.00722 +2024-11-21 23:56:26.304492: train_loss -0.783 +2024-11-21 23:56:26.304710: val_loss -0.7637 +2024-11-21 23:56:26.304796: Pseudo dice [0.8352] +2024-11-21 23:56:26.304878: Epoch time: 18.18 s +2024-11-21 23:56:27.150815: +2024-11-21 23:56:27.151099: Epoch 2432 +2024-11-21 23:56:27.151210: Current learning rate: 0.00722 +2024-11-21 23:56:45.722135: train_loss -0.7807 +2024-11-21 23:56:45.722343: val_loss -0.7215 +2024-11-21 23:56:45.722414: Pseudo dice [0.8283] +2024-11-21 23:56:45.722489: Epoch time: 18.57 s +2024-11-21 23:56:46.566751: +2024-11-21 23:56:46.566962: Epoch 2433 +2024-11-21 23:56:46.567097: Current learning rate: 0.00722 +2024-11-21 23:57:04.803494: train_loss -0.7816 +2024-11-21 23:57:04.803772: val_loss -0.7571 +2024-11-21 23:57:04.803849: Pseudo dice [0.8305] +2024-11-21 23:57:04.803935: Epoch time: 18.24 s +2024-11-21 23:57:06.073372: +2024-11-21 23:57:06.073587: Epoch 2434 +2024-11-21 23:57:06.073697: Current learning rate: 0.00721 +2024-11-21 23:57:23.431314: train_loss -0.7769 +2024-11-21 23:57:23.431630: val_loss -0.7511 +2024-11-21 23:57:23.431708: Pseudo dice [0.8396] +2024-11-21 23:57:23.431785: Epoch time: 17.36 s +2024-11-21 23:57:24.282864: +2024-11-21 23:57:24.283198: Epoch 2435 +2024-11-21 23:57:24.283319: Current learning rate: 0.00721 +2024-11-21 23:57:42.911459: train_loss -0.7759 +2024-11-21 23:57:42.911683: val_loss -0.7499 +2024-11-21 23:57:42.911770: Pseudo dice [0.8199] +2024-11-21 23:57:42.911847: Epoch time: 18.63 s +2024-11-21 23:57:43.930987: +2024-11-21 23:57:43.931196: Epoch 2436 +2024-11-21 23:57:43.931312: Current learning rate: 0.00721 +2024-11-21 23:58:02.799335: train_loss -0.7825 +2024-11-21 23:58:02.799585: val_loss -0.7576 +2024-11-21 23:58:02.799657: Pseudo dice [0.8303] +2024-11-21 23:58:02.799743: Epoch time: 18.87 s +2024-11-21 23:58:03.654324: +2024-11-21 23:58:03.654553: Epoch 2437 +2024-11-21 23:58:03.654672: Current learning rate: 0.00721 +2024-11-21 23:58:21.395772: train_loss -0.7707 +2024-11-21 23:58:21.395988: val_loss -0.7161 +2024-11-21 23:58:21.396069: Pseudo dice [0.8181] +2024-11-21 23:58:21.396143: Epoch time: 17.74 s +2024-11-21 23:58:22.267546: +2024-11-21 23:58:22.267736: Epoch 2438 +2024-11-21 23:58:22.267849: Current learning rate: 0.00721 +2024-11-21 23:58:40.487365: train_loss -0.7589 +2024-11-21 23:58:40.489789: val_loss -0.753 +2024-11-21 23:58:40.489879: Pseudo dice [0.8511] +2024-11-21 23:58:40.489959: Epoch time: 18.22 s +2024-11-21 23:58:41.424303: +2024-11-21 23:58:41.424536: Epoch 2439 +2024-11-21 23:58:41.424649: Current learning rate: 0.00721 +2024-11-21 23:59:00.892033: train_loss -0.7791 +2024-11-21 23:59:00.892258: val_loss -0.7152 +2024-11-21 23:59:00.892332: Pseudo dice [0.8273] +2024-11-21 23:59:00.892409: Epoch time: 19.47 s +2024-11-21 23:59:01.906830: +2024-11-21 23:59:01.907040: Epoch 2440 +2024-11-21 23:59:01.907156: Current learning rate: 0.00721 +2024-11-21 23:59:21.649803: train_loss -0.7769 +2024-11-21 23:59:21.650092: val_loss -0.7344 +2024-11-21 23:59:21.650174: Pseudo dice [0.8227] +2024-11-21 23:59:21.650263: Epoch time: 19.74 s +2024-11-21 23:59:22.500789: +2024-11-21 23:59:22.500998: Epoch 2441 +2024-11-21 23:59:22.501115: Current learning rate: 0.00721 +2024-11-21 23:59:42.901406: train_loss -0.7745 +2024-11-21 23:59:42.901619: val_loss -0.7541 +2024-11-21 23:59:42.901693: Pseudo dice [0.8414] +2024-11-21 23:59:42.901773: Epoch time: 20.4 s +2024-11-21 23:59:43.750181: +2024-11-21 23:59:43.750386: Epoch 2442 +2024-11-21 23:59:43.750504: Current learning rate: 0.00721 +2024-11-22 00:00:02.532311: train_loss -0.7724 +2024-11-22 00:00:02.532537: val_loss -0.7589 +2024-11-22 00:00:02.532692: Pseudo dice [0.8292] +2024-11-22 00:00:02.532773: Epoch time: 18.78 s +2024-11-22 00:00:02.532834: Yayy! New best EMA pseudo Dice: 0.8281 +2024-11-22 00:00:03.661620: +2024-11-22 00:00:03.661839: Epoch 2443 +2024-11-22 00:00:03.661959: Current learning rate: 0.0072 +2024-11-22 00:00:22.717531: train_loss -0.7803 +2024-11-22 00:00:22.719945: val_loss -0.7524 +2024-11-22 00:00:22.720044: Pseudo dice [0.8267] +2024-11-22 00:00:22.720132: Epoch time: 19.06 s +2024-11-22 00:00:23.593496: +2024-11-22 00:00:23.593704: Epoch 2444 +2024-11-22 00:00:23.593819: Current learning rate: 0.0072 +2024-11-22 00:00:42.287865: train_loss -0.779 +2024-11-22 00:00:42.288080: val_loss -0.727 +2024-11-22 00:00:42.288155: Pseudo dice [0.8186] +2024-11-22 00:00:42.288235: Epoch time: 18.7 s +2024-11-22 00:00:43.133496: +2024-11-22 00:00:43.133699: Epoch 2445 +2024-11-22 00:00:43.133811: Current learning rate: 0.0072 +2024-11-22 00:01:01.942250: train_loss -0.778 +2024-11-22 00:01:01.947475: val_loss -0.7323 +2024-11-22 00:01:01.947608: Pseudo dice [0.8077] +2024-11-22 00:01:01.947695: Epoch time: 18.81 s +2024-11-22 00:01:03.222078: +2024-11-22 00:01:03.222303: Epoch 2446 +2024-11-22 00:01:03.222416: Current learning rate: 0.0072 +2024-11-22 00:01:22.793704: train_loss -0.7306 +2024-11-22 00:01:22.793964: val_loss -0.7149 +2024-11-22 00:01:22.794053: Pseudo dice [0.7997] +2024-11-22 00:01:22.794138: Epoch time: 19.57 s +2024-11-22 00:01:23.746121: +2024-11-22 00:01:23.746341: Epoch 2447 +2024-11-22 00:01:23.746459: Current learning rate: 0.0072 +2024-11-22 00:01:42.337680: train_loss -0.7435 +2024-11-22 00:01:42.338175: val_loss -0.7293 +2024-11-22 00:01:42.338384: Pseudo dice [0.8044] +2024-11-22 00:01:42.338467: Epoch time: 18.59 s +2024-11-22 00:01:43.183250: +2024-11-22 00:01:43.183458: Epoch 2448 +2024-11-22 00:01:43.183573: Current learning rate: 0.0072 +2024-11-22 00:02:00.816640: train_loss -0.7552 +2024-11-22 00:02:00.816854: val_loss -0.7267 +2024-11-22 00:02:00.816934: Pseudo dice [0.8044] +2024-11-22 00:02:00.817020: Epoch time: 17.63 s +2024-11-22 00:02:01.664353: +2024-11-22 00:02:01.664628: Epoch 2449 +2024-11-22 00:02:01.664744: Current learning rate: 0.0072 +2024-11-22 00:02:20.405694: train_loss -0.7591 +2024-11-22 00:02:20.405924: val_loss -0.7535 +2024-11-22 00:02:20.406014: Pseudo dice [0.8259] +2024-11-22 00:02:20.406104: Epoch time: 18.74 s +2024-11-22 00:02:21.481297: +2024-11-22 00:02:21.481487: Epoch 2450 +2024-11-22 00:02:21.481598: Current learning rate: 0.0072 +2024-11-22 00:02:40.018004: train_loss -0.7688 +2024-11-22 00:02:40.018240: val_loss -0.7257 +2024-11-22 00:02:40.018313: Pseudo dice [0.8315] +2024-11-22 00:02:40.018392: Epoch time: 18.54 s +2024-11-22 00:02:40.867867: +2024-11-22 00:02:40.880918: Epoch 2451 +2024-11-22 00:02:40.881058: Current learning rate: 0.00719 +2024-11-22 00:03:00.196961: train_loss -0.7642 +2024-11-22 00:03:00.197232: val_loss -0.7298 +2024-11-22 00:03:00.197311: Pseudo dice [0.8101] +2024-11-22 00:03:00.197391: Epoch time: 19.33 s +2024-11-22 00:03:01.047611: +2024-11-22 00:03:01.047812: Epoch 2452 +2024-11-22 00:03:01.047923: Current learning rate: 0.00719 +2024-11-22 00:03:18.490606: train_loss -0.7764 +2024-11-22 00:03:18.490822: val_loss -0.7063 +2024-11-22 00:03:18.490894: Pseudo dice [0.8142] +2024-11-22 00:03:18.490973: Epoch time: 17.44 s +2024-11-22 00:03:19.336052: +2024-11-22 00:03:19.336309: Epoch 2453 +2024-11-22 00:03:19.336424: Current learning rate: 0.00719 +2024-11-22 00:03:38.555443: train_loss -0.7741 +2024-11-22 00:03:38.555691: val_loss -0.7224 +2024-11-22 00:03:38.555771: Pseudo dice [0.8054] +2024-11-22 00:03:38.555855: Epoch time: 19.22 s +2024-11-22 00:03:39.462833: +2024-11-22 00:03:39.463065: Epoch 2454 +2024-11-22 00:03:39.463190: Current learning rate: 0.00719 +2024-11-22 00:03:58.810018: train_loss -0.7688 +2024-11-22 00:03:58.810244: val_loss -0.7344 +2024-11-22 00:03:58.810320: Pseudo dice [0.8118] +2024-11-22 00:03:58.810399: Epoch time: 19.35 s +2024-11-22 00:03:59.725510: +2024-11-22 00:03:59.725712: Epoch 2455 +2024-11-22 00:03:59.725822: Current learning rate: 0.00719 +2024-11-22 00:04:18.767515: train_loss -0.7756 +2024-11-22 00:04:18.767729: val_loss -0.716 +2024-11-22 00:04:18.767803: Pseudo dice [0.8077] +2024-11-22 00:04:18.767881: Epoch time: 19.04 s +2024-11-22 00:04:19.620769: +2024-11-22 00:04:19.621054: Epoch 2456 +2024-11-22 00:04:19.621168: Current learning rate: 0.00719 +2024-11-22 00:04:37.363050: train_loss -0.7725 +2024-11-22 00:04:37.363320: val_loss -0.7545 +2024-11-22 00:04:37.363399: Pseudo dice [0.8335] +2024-11-22 00:04:37.363480: Epoch time: 17.74 s +2024-11-22 00:04:38.211436: +2024-11-22 00:04:38.211633: Epoch 2457 +2024-11-22 00:04:38.211746: Current learning rate: 0.00719 +2024-11-22 00:04:56.884042: train_loss -0.7753 +2024-11-22 00:04:56.884279: val_loss -0.7406 +2024-11-22 00:04:56.884355: Pseudo dice [0.8329] +2024-11-22 00:04:56.884434: Epoch time: 18.67 s +2024-11-22 00:04:58.167209: +2024-11-22 00:04:58.167425: Epoch 2458 +2024-11-22 00:04:58.167535: Current learning rate: 0.00719 +2024-11-22 00:05:17.515400: train_loss -0.7655 +2024-11-22 00:05:17.515694: val_loss -0.7056 +2024-11-22 00:05:17.515776: Pseudo dice [0.7952] +2024-11-22 00:05:17.515856: Epoch time: 19.35 s +2024-11-22 00:05:18.365890: +2024-11-22 00:05:18.366124: Epoch 2459 +2024-11-22 00:05:18.366239: Current learning rate: 0.00719 +2024-11-22 00:05:37.296483: train_loss -0.7716 +2024-11-22 00:05:37.296750: val_loss -0.7262 +2024-11-22 00:05:37.296833: Pseudo dice [0.8232] +2024-11-22 00:05:37.296911: Epoch time: 18.93 s +2024-11-22 00:05:38.146775: +2024-11-22 00:05:38.147084: Epoch 2460 +2024-11-22 00:05:38.147199: Current learning rate: 0.00718 +2024-11-22 00:05:56.962550: train_loss -0.7688 +2024-11-22 00:05:56.967914: val_loss -0.7517 +2024-11-22 00:05:56.968082: Pseudo dice [0.8269] +2024-11-22 00:05:56.968174: Epoch time: 18.82 s +2024-11-22 00:05:57.928930: +2024-11-22 00:05:57.929186: Epoch 2461 +2024-11-22 00:05:57.929299: Current learning rate: 0.00718 +2024-11-22 00:06:16.755032: train_loss -0.7692 +2024-11-22 00:06:16.755244: val_loss -0.7588 +2024-11-22 00:06:16.755318: Pseudo dice [0.8259] +2024-11-22 00:06:16.755394: Epoch time: 18.83 s +2024-11-22 00:06:17.608242: +2024-11-22 00:06:17.608472: Epoch 2462 +2024-11-22 00:06:17.608591: Current learning rate: 0.00718 +2024-11-22 00:06:35.836231: train_loss -0.7595 +2024-11-22 00:06:35.836516: val_loss -0.7247 +2024-11-22 00:06:35.836593: Pseudo dice [0.7873] +2024-11-22 00:06:35.836673: Epoch time: 18.23 s +2024-11-22 00:06:36.688733: +2024-11-22 00:06:36.688945: Epoch 2463 +2024-11-22 00:06:36.689060: Current learning rate: 0.00718 +2024-11-22 00:06:55.594597: train_loss -0.7689 +2024-11-22 00:06:55.594868: val_loss -0.7511 +2024-11-22 00:06:55.595614: Pseudo dice [0.8119] +2024-11-22 00:06:55.595706: Epoch time: 18.91 s +2024-11-22 00:06:56.445528: +2024-11-22 00:06:56.445829: Epoch 2464 +2024-11-22 00:06:56.445950: Current learning rate: 0.00718 +2024-11-22 00:07:15.372696: train_loss -0.7789 +2024-11-22 00:07:15.372934: val_loss -0.7366 +2024-11-22 00:07:15.373013: Pseudo dice [0.8189] +2024-11-22 00:07:15.373095: Epoch time: 18.93 s +2024-11-22 00:07:16.214417: +2024-11-22 00:07:16.214622: Epoch 2465 +2024-11-22 00:07:16.214755: Current learning rate: 0.00718 +2024-11-22 00:07:34.216686: train_loss -0.7455 +2024-11-22 00:07:34.216916: val_loss -0.7079 +2024-11-22 00:07:34.217003: Pseudo dice [0.8184] +2024-11-22 00:07:34.217084: Epoch time: 18.0 s +2024-11-22 00:07:35.069530: +2024-11-22 00:07:35.069780: Epoch 2466 +2024-11-22 00:07:35.069894: Current learning rate: 0.00718 +2024-11-22 00:07:53.497406: train_loss -0.7688 +2024-11-22 00:07:53.497611: val_loss -0.7294 +2024-11-22 00:07:53.497687: Pseudo dice [0.8296] +2024-11-22 00:07:53.497764: Epoch time: 18.43 s +2024-11-22 00:07:54.344204: +2024-11-22 00:07:54.344435: Epoch 2467 +2024-11-22 00:07:54.344561: Current learning rate: 0.00718 +2024-11-22 00:08:12.194085: train_loss -0.7746 +2024-11-22 00:08:12.194324: val_loss -0.7358 +2024-11-22 00:08:12.194399: Pseudo dice [0.8172] +2024-11-22 00:08:12.194481: Epoch time: 17.85 s +2024-11-22 00:08:13.043767: +2024-11-22 00:08:13.043957: Epoch 2468 +2024-11-22 00:08:13.044075: Current learning rate: 0.00717 +2024-11-22 00:08:30.919751: train_loss -0.7767 +2024-11-22 00:08:30.919968: val_loss -0.73 +2024-11-22 00:08:30.920049: Pseudo dice [0.8216] +2024-11-22 00:08:30.920126: Epoch time: 17.88 s +2024-11-22 00:08:31.765585: +2024-11-22 00:08:31.765786: Epoch 2469 +2024-11-22 00:08:31.765901: Current learning rate: 0.00717 +2024-11-22 00:08:51.296388: train_loss -0.7733 +2024-11-22 00:08:51.296618: val_loss -0.72 +2024-11-22 00:08:51.296701: Pseudo dice [0.8218] +2024-11-22 00:08:51.296780: Epoch time: 19.53 s +2024-11-22 00:08:52.521252: +2024-11-22 00:08:52.521471: Epoch 2470 +2024-11-22 00:08:52.521590: Current learning rate: 0.00717 +2024-11-22 00:09:11.044760: train_loss -0.7794 +2024-11-22 00:09:11.045040: val_loss -0.7298 +2024-11-22 00:09:11.045119: Pseudo dice [0.8315] +2024-11-22 00:09:11.045209: Epoch time: 18.52 s +2024-11-22 00:09:11.940133: +2024-11-22 00:09:11.940544: Epoch 2471 +2024-11-22 00:09:11.940667: Current learning rate: 0.00717 +2024-11-22 00:09:30.259940: train_loss -0.7792 +2024-11-22 00:09:30.260160: val_loss -0.7658 +2024-11-22 00:09:30.260236: Pseudo dice [0.8199] +2024-11-22 00:09:30.260309: Epoch time: 18.32 s +2024-11-22 00:09:31.108871: +2024-11-22 00:09:31.109078: Epoch 2472 +2024-11-22 00:09:31.109189: Current learning rate: 0.00717 +2024-11-22 00:09:49.499505: train_loss -0.7812 +2024-11-22 00:09:49.499712: val_loss -0.7368 +2024-11-22 00:09:49.499790: Pseudo dice [0.8232] +2024-11-22 00:09:49.499872: Epoch time: 18.39 s +2024-11-22 00:09:50.509968: +2024-11-22 00:09:50.510189: Epoch 2473 +2024-11-22 00:09:50.510301: Current learning rate: 0.00717 +2024-11-22 00:10:10.184675: train_loss -0.7706 +2024-11-22 00:10:10.184922: val_loss -0.7567 +2024-11-22 00:10:10.185229: Pseudo dice [0.8161] +2024-11-22 00:10:10.185323: Epoch time: 19.68 s +2024-11-22 00:10:11.038866: +2024-11-22 00:10:11.039068: Epoch 2474 +2024-11-22 00:10:11.039185: Current learning rate: 0.00717 +2024-11-22 00:10:29.467798: train_loss -0.781 +2024-11-22 00:10:29.470201: val_loss -0.7429 +2024-11-22 00:10:29.470286: Pseudo dice [0.8265] +2024-11-22 00:10:29.470368: Epoch time: 18.43 s +2024-11-22 00:10:30.520875: +2024-11-22 00:10:30.521097: Epoch 2475 +2024-11-22 00:10:30.521207: Current learning rate: 0.00717 +2024-11-22 00:10:49.608443: train_loss -0.7735 +2024-11-22 00:10:49.608659: val_loss -0.7417 +2024-11-22 00:10:49.608732: Pseudo dice [0.8207] +2024-11-22 00:10:49.608808: Epoch time: 19.09 s +2024-11-22 00:10:50.458128: +2024-11-22 00:10:50.458319: Epoch 2476 +2024-11-22 00:10:50.458430: Current learning rate: 0.00717 +2024-11-22 00:11:08.566172: train_loss -0.7721 +2024-11-22 00:11:08.566391: val_loss -0.7064 +2024-11-22 00:11:08.566467: Pseudo dice [0.8114] +2024-11-22 00:11:08.566544: Epoch time: 18.11 s +2024-11-22 00:11:09.430522: +2024-11-22 00:11:09.430794: Epoch 2477 +2024-11-22 00:11:09.430912: Current learning rate: 0.00716 +2024-11-22 00:11:27.971642: train_loss -0.7635 +2024-11-22 00:11:27.971895: val_loss -0.7337 +2024-11-22 00:11:27.972061: Pseudo dice [0.8094] +2024-11-22 00:11:27.972153: Epoch time: 18.54 s +2024-11-22 00:11:28.828527: +2024-11-22 00:11:28.828745: Epoch 2478 +2024-11-22 00:11:28.828856: Current learning rate: 0.00716 +2024-11-22 00:11:47.774730: train_loss -0.7784 +2024-11-22 00:11:47.774945: val_loss -0.7494 +2024-11-22 00:11:47.775027: Pseudo dice [0.8423] +2024-11-22 00:11:47.775101: Epoch time: 18.95 s +2024-11-22 00:11:48.622279: +2024-11-22 00:11:48.622508: Epoch 2479 +2024-11-22 00:11:48.622624: Current learning rate: 0.00716 +2024-11-22 00:12:07.786565: train_loss -0.7821 +2024-11-22 00:12:07.786791: val_loss -0.7271 +2024-11-22 00:12:07.786865: Pseudo dice [0.8227] +2024-11-22 00:12:07.786943: Epoch time: 19.17 s +2024-11-22 00:12:08.646584: +2024-11-22 00:12:08.646788: Epoch 2480 +2024-11-22 00:12:08.646903: Current learning rate: 0.00716 +2024-11-22 00:12:27.603667: train_loss -0.7746 +2024-11-22 00:12:27.606113: val_loss -0.709 +2024-11-22 00:12:27.606205: Pseudo dice [0.8268] +2024-11-22 00:12:27.606292: Epoch time: 18.96 s +2024-11-22 00:12:28.487565: +2024-11-22 00:12:28.487773: Epoch 2481 +2024-11-22 00:12:28.487890: Current learning rate: 0.00716 +2024-11-22 00:12:47.523173: train_loss -0.7696 +2024-11-22 00:12:47.523420: val_loss -0.7221 +2024-11-22 00:12:47.523495: Pseudo dice [0.7826] +2024-11-22 00:12:47.523576: Epoch time: 19.04 s +2024-11-22 00:12:48.754275: +2024-11-22 00:12:48.754527: Epoch 2482 +2024-11-22 00:12:48.754638: Current learning rate: 0.00716 +2024-11-22 00:13:06.971854: train_loss -0.7674 +2024-11-22 00:13:06.972095: val_loss -0.7411 +2024-11-22 00:13:06.972172: Pseudo dice [0.8235] +2024-11-22 00:13:06.972247: Epoch time: 18.22 s +2024-11-22 00:13:07.862867: +2024-11-22 00:13:07.863097: Epoch 2483 +2024-11-22 00:13:07.863213: Current learning rate: 0.00716 +2024-11-22 00:13:26.634763: train_loss -0.7729 +2024-11-22 00:13:26.634986: val_loss -0.7328 +2024-11-22 00:13:26.635068: Pseudo dice [0.8123] +2024-11-22 00:13:26.635146: Epoch time: 18.77 s +2024-11-22 00:13:27.486897: +2024-11-22 00:13:27.487111: Epoch 2484 +2024-11-22 00:13:27.487227: Current learning rate: 0.00716 +2024-11-22 00:13:45.012922: train_loss -0.7765 +2024-11-22 00:13:45.013176: val_loss -0.724 +2024-11-22 00:13:45.019495: Pseudo dice [0.8236] +2024-11-22 00:13:45.019650: Epoch time: 17.53 s +2024-11-22 00:13:45.905064: +2024-11-22 00:13:45.905273: Epoch 2485 +2024-11-22 00:13:45.905388: Current learning rate: 0.00716 +2024-11-22 00:14:03.998666: train_loss -0.7736 +2024-11-22 00:14:03.998889: val_loss -0.761 +2024-11-22 00:14:03.998968: Pseudo dice [0.8396] +2024-11-22 00:14:03.999057: Epoch time: 18.09 s +2024-11-22 00:14:04.849499: +2024-11-22 00:14:04.849705: Epoch 2486 +2024-11-22 00:14:04.849819: Current learning rate: 0.00715 +2024-11-22 00:14:23.455807: train_loss -0.7856 +2024-11-22 00:14:23.456026: val_loss -0.7242 +2024-11-22 00:14:23.456098: Pseudo dice [0.8105] +2024-11-22 00:14:23.456177: Epoch time: 18.61 s +2024-11-22 00:14:24.314736: +2024-11-22 00:14:24.314970: Epoch 2487 +2024-11-22 00:14:24.315089: Current learning rate: 0.00715 +2024-11-22 00:14:44.261614: train_loss -0.7825 +2024-11-22 00:14:44.261835: val_loss -0.7531 +2024-11-22 00:14:44.261909: Pseudo dice [0.8386] +2024-11-22 00:14:44.261999: Epoch time: 19.95 s +2024-11-22 00:14:45.107763: +2024-11-22 00:14:45.107958: Epoch 2488 +2024-11-22 00:14:45.108069: Current learning rate: 0.00715 +2024-11-22 00:15:03.211773: train_loss -0.7777 +2024-11-22 00:15:03.217206: val_loss -0.7536 +2024-11-22 00:15:03.217290: Pseudo dice [0.83] +2024-11-22 00:15:03.217375: Epoch time: 18.1 s +2024-11-22 00:15:04.148730: +2024-11-22 00:15:04.158336: Epoch 2489 +2024-11-22 00:15:04.158454: Current learning rate: 0.00715 +2024-11-22 00:15:24.021786: train_loss -0.7778 +2024-11-22 00:15:24.022009: val_loss -0.7559 +2024-11-22 00:15:24.022083: Pseudo dice [0.8523] +2024-11-22 00:15:24.022160: Epoch time: 19.87 s +2024-11-22 00:15:24.959893: +2024-11-22 00:15:24.960118: Epoch 2490 +2024-11-22 00:15:24.960228: Current learning rate: 0.00715 +2024-11-22 00:15:43.643112: train_loss -0.7801 +2024-11-22 00:15:43.643938: val_loss -0.7326 +2024-11-22 00:15:43.644019: Pseudo dice [0.8197] +2024-11-22 00:15:43.644096: Epoch time: 18.68 s +2024-11-22 00:15:44.483223: +2024-11-22 00:15:44.483434: Epoch 2491 +2024-11-22 00:15:44.483546: Current learning rate: 0.00715 +2024-11-22 00:16:03.556582: train_loss -0.7737 +2024-11-22 00:16:03.556828: val_loss -0.7318 +2024-11-22 00:16:03.556907: Pseudo dice [0.8133] +2024-11-22 00:16:03.556998: Epoch time: 19.07 s +2024-11-22 00:16:04.405046: +2024-11-22 00:16:04.405507: Epoch 2492 +2024-11-22 00:16:04.405638: Current learning rate: 0.00715 +2024-11-22 00:16:22.947664: train_loss -0.774 +2024-11-22 00:16:22.947877: val_loss -0.7349 +2024-11-22 00:16:22.947951: Pseudo dice [0.8287] +2024-11-22 00:16:22.948033: Epoch time: 18.54 s +2024-11-22 00:16:23.810093: +2024-11-22 00:16:23.810328: Epoch 2493 +2024-11-22 00:16:23.810440: Current learning rate: 0.00715 +2024-11-22 00:16:42.932166: train_loss -0.7667 +2024-11-22 00:16:42.932375: val_loss -0.7566 +2024-11-22 00:16:42.932449: Pseudo dice [0.8362] +2024-11-22 00:16:42.932527: Epoch time: 19.12 s +2024-11-22 00:16:44.071767: +2024-11-22 00:16:44.071977: Epoch 2494 +2024-11-22 00:16:44.072093: Current learning rate: 0.00714 +2024-11-22 00:17:02.486763: train_loss -0.7707 +2024-11-22 00:17:02.490619: val_loss -0.7319 +2024-11-22 00:17:02.490745: Pseudo dice [0.8087] +2024-11-22 00:17:02.490844: Epoch time: 18.42 s +2024-11-22 00:17:03.521276: +2024-11-22 00:17:03.521491: Epoch 2495 +2024-11-22 00:17:03.521603: Current learning rate: 0.00714 +2024-11-22 00:17:22.722163: train_loss -0.7716 +2024-11-22 00:17:22.722367: val_loss -0.7238 +2024-11-22 00:17:22.722440: Pseudo dice [0.8152] +2024-11-22 00:17:22.722514: Epoch time: 19.2 s +2024-11-22 00:17:23.592093: +2024-11-22 00:17:23.592289: Epoch 2496 +2024-11-22 00:17:23.592402: Current learning rate: 0.00714 +2024-11-22 00:17:42.991668: train_loss -0.7664 +2024-11-22 00:17:42.991883: val_loss -0.74 +2024-11-22 00:17:42.991960: Pseudo dice [0.816] +2024-11-22 00:17:42.992042: Epoch time: 19.4 s +2024-11-22 00:17:43.850330: +2024-11-22 00:17:43.850552: Epoch 2497 +2024-11-22 00:17:43.850670: Current learning rate: 0.00714 +2024-11-22 00:18:02.102395: train_loss -0.7671 +2024-11-22 00:18:02.102612: val_loss -0.7487 +2024-11-22 00:18:02.102688: Pseudo dice [0.8334] +2024-11-22 00:18:02.102770: Epoch time: 18.25 s +2024-11-22 00:18:02.945027: +2024-11-22 00:18:02.945231: Epoch 2498 +2024-11-22 00:18:02.945341: Current learning rate: 0.00714 +2024-11-22 00:18:21.895071: train_loss -0.7793 +2024-11-22 00:18:21.895336: val_loss -0.7464 +2024-11-22 00:18:21.895411: Pseudo dice [0.8277] +2024-11-22 00:18:21.895491: Epoch time: 18.95 s +2024-11-22 00:18:22.842201: +2024-11-22 00:18:22.842421: Epoch 2499 +2024-11-22 00:18:22.842536: Current learning rate: 0.00714 +2024-11-22 00:18:42.405453: train_loss -0.7769 +2024-11-22 00:18:42.405688: val_loss -0.729 +2024-11-22 00:18:42.405890: Pseudo dice [0.8082] +2024-11-22 00:18:42.405973: Epoch time: 19.56 s +2024-11-22 00:18:43.530003: +2024-11-22 00:18:43.530205: Epoch 2500 +2024-11-22 00:18:43.530321: Current learning rate: 0.00714 +2024-11-22 00:19:03.069459: train_loss -0.7726 +2024-11-22 00:19:03.069683: val_loss -0.7561 +2024-11-22 00:19:03.069756: Pseudo dice [0.832] +2024-11-22 00:19:03.069831: Epoch time: 19.54 s +2024-11-22 00:19:04.022417: +2024-11-22 00:19:04.022642: Epoch 2501 +2024-11-22 00:19:04.022755: Current learning rate: 0.00714 +2024-11-22 00:19:23.340283: train_loss -0.7517 +2024-11-22 00:19:23.340517: val_loss -0.7071 +2024-11-22 00:19:23.340607: Pseudo dice [0.8058] +2024-11-22 00:19:23.354032: Epoch time: 19.32 s +2024-11-22 00:19:24.223578: +2024-11-22 00:19:24.223841: Epoch 2502 +2024-11-22 00:19:24.224001: Current learning rate: 0.00714 +2024-11-22 00:19:44.064405: train_loss -0.752 +2024-11-22 00:19:44.064659: val_loss -0.7461 +2024-11-22 00:19:44.064738: Pseudo dice [0.8161] +2024-11-22 00:19:44.064821: Epoch time: 19.84 s +2024-11-22 00:19:44.918493: +2024-11-22 00:19:44.918705: Epoch 2503 +2024-11-22 00:19:44.918838: Current learning rate: 0.00713 +2024-11-22 00:20:04.626979: train_loss -0.7661 +2024-11-22 00:20:04.627227: val_loss -0.7666 +2024-11-22 00:20:04.627301: Pseudo dice [0.8374] +2024-11-22 00:20:04.627379: Epoch time: 19.71 s +2024-11-22 00:20:05.483234: +2024-11-22 00:20:05.483650: Epoch 2504 +2024-11-22 00:20:05.483790: Current learning rate: 0.00713 +2024-11-22 00:20:24.517059: train_loss -0.7536 +2024-11-22 00:20:24.517273: val_loss -0.7333 +2024-11-22 00:20:24.517348: Pseudo dice [0.8219] +2024-11-22 00:20:24.517424: Epoch time: 19.03 s +2024-11-22 00:20:25.424612: +2024-11-22 00:20:25.424846: Epoch 2505 +2024-11-22 00:20:25.424954: Current learning rate: 0.00713 +2024-11-22 00:20:43.360137: train_loss -0.7525 +2024-11-22 00:20:43.360614: val_loss -0.7007 +2024-11-22 00:20:43.360711: Pseudo dice [0.8158] +2024-11-22 00:20:43.360793: Epoch time: 17.94 s +2024-11-22 00:20:44.213195: +2024-11-22 00:20:44.213425: Epoch 2506 +2024-11-22 00:20:44.213542: Current learning rate: 0.00713 +2024-11-22 00:21:02.246584: train_loss -0.7608 +2024-11-22 00:21:02.246808: val_loss -0.7277 +2024-11-22 00:21:02.246891: Pseudo dice [0.8251] +2024-11-22 00:21:02.246968: Epoch time: 18.03 s +2024-11-22 00:21:03.163835: +2024-11-22 00:21:03.164041: Epoch 2507 +2024-11-22 00:21:03.164152: Current learning rate: 0.00713 +2024-11-22 00:21:21.865579: train_loss -0.7542 +2024-11-22 00:21:21.867980: val_loss -0.6958 +2024-11-22 00:21:21.868140: Pseudo dice [0.8008] +2024-11-22 00:21:21.868222: Epoch time: 18.7 s +2024-11-22 00:21:22.742858: +2024-11-22 00:21:22.743079: Epoch 2508 +2024-11-22 00:21:22.743195: Current learning rate: 0.00713 +2024-11-22 00:21:40.678677: train_loss -0.7592 +2024-11-22 00:21:40.678928: val_loss -0.7289 +2024-11-22 00:21:40.679015: Pseudo dice [0.8218] +2024-11-22 00:21:40.679098: Epoch time: 17.94 s +2024-11-22 00:21:41.577641: +2024-11-22 00:21:41.577873: Epoch 2509 +2024-11-22 00:21:41.577998: Current learning rate: 0.00713 +2024-11-22 00:21:59.639681: train_loss -0.7731 +2024-11-22 00:21:59.639901: val_loss -0.7312 +2024-11-22 00:21:59.639974: Pseudo dice [0.8283] +2024-11-22 00:21:59.640056: Epoch time: 18.06 s +2024-11-22 00:22:00.492941: +2024-11-22 00:22:00.493163: Epoch 2510 +2024-11-22 00:22:00.493277: Current learning rate: 0.00713 +2024-11-22 00:22:19.304416: train_loss -0.7673 +2024-11-22 00:22:19.307867: val_loss -0.755 +2024-11-22 00:22:19.308044: Pseudo dice [0.8107] +2024-11-22 00:22:19.308151: Epoch time: 18.81 s +2024-11-22 00:22:20.202594: +2024-11-22 00:22:20.202781: Epoch 2511 +2024-11-22 00:22:20.202890: Current learning rate: 0.00712 +2024-11-22 00:22:38.538685: train_loss -0.7764 +2024-11-22 00:22:38.538947: val_loss -0.7457 +2024-11-22 00:22:38.539031: Pseudo dice [0.8261] +2024-11-22 00:22:38.539107: Epoch time: 18.34 s +2024-11-22 00:22:39.393444: +2024-11-22 00:22:39.393652: Epoch 2512 +2024-11-22 00:22:39.393764: Current learning rate: 0.00712 +2024-11-22 00:22:58.202338: train_loss -0.7849 +2024-11-22 00:22:58.202582: val_loss -0.7702 +2024-11-22 00:22:58.202659: Pseudo dice [0.85] +2024-11-22 00:22:58.202741: Epoch time: 18.81 s +2024-11-22 00:22:59.058730: +2024-11-22 00:22:59.058952: Epoch 2513 +2024-11-22 00:22:59.059069: Current learning rate: 0.00712 +2024-11-22 00:23:17.334815: train_loss -0.7822 +2024-11-22 00:23:17.335038: val_loss -0.7466 +2024-11-22 00:23:17.335122: Pseudo dice [0.8156] +2024-11-22 00:23:17.335196: Epoch time: 18.28 s +2024-11-22 00:23:18.202714: +2024-11-22 00:23:18.202966: Epoch 2514 +2024-11-22 00:23:18.203085: Current learning rate: 0.00712 +2024-11-22 00:23:37.764249: train_loss -0.7667 +2024-11-22 00:23:37.793926: val_loss -0.7439 +2024-11-22 00:23:37.794101: Pseudo dice [0.8506] +2024-11-22 00:23:37.794192: Epoch time: 19.56 s +2024-11-22 00:23:38.689628: +2024-11-22 00:23:38.690083: Epoch 2515 +2024-11-22 00:23:38.690216: Current learning rate: 0.00712 +2024-11-22 00:23:57.674144: train_loss -0.7789 +2024-11-22 00:23:57.674392: val_loss -0.7648 +2024-11-22 00:23:57.674471: Pseudo dice [0.8424] +2024-11-22 00:23:57.674556: Epoch time: 18.99 s +2024-11-22 00:23:58.542764: +2024-11-22 00:23:58.542953: Epoch 2516 +2024-11-22 00:23:58.543097: Current learning rate: 0.00712 +2024-11-22 00:24:18.518295: train_loss -0.7708 +2024-11-22 00:24:18.518506: val_loss -0.7398 +2024-11-22 00:24:18.518578: Pseudo dice [0.8111] +2024-11-22 00:24:18.518653: Epoch time: 19.98 s +2024-11-22 00:24:19.757473: +2024-11-22 00:24:19.757716: Epoch 2517 +2024-11-22 00:24:19.757831: Current learning rate: 0.00712 +2024-11-22 00:24:38.234001: train_loss -0.7723 +2024-11-22 00:24:38.234266: val_loss -0.7471 +2024-11-22 00:24:38.234344: Pseudo dice [0.8306] +2024-11-22 00:24:38.234423: Epoch time: 18.48 s +2024-11-22 00:24:39.093204: +2024-11-22 00:24:39.093413: Epoch 2518 +2024-11-22 00:24:39.093528: Current learning rate: 0.00712 +2024-11-22 00:24:57.897284: train_loss -0.7698 +2024-11-22 00:24:57.897520: val_loss -0.7281 +2024-11-22 00:24:57.897648: Pseudo dice [0.8089] +2024-11-22 00:24:57.897732: Epoch time: 18.8 s +2024-11-22 00:24:58.751966: +2024-11-22 00:24:58.752192: Epoch 2519 +2024-11-22 00:24:58.752307: Current learning rate: 0.00712 +2024-11-22 00:25:17.839596: train_loss -0.773 +2024-11-22 00:25:17.839847: val_loss -0.7338 +2024-11-22 00:25:17.839930: Pseudo dice [0.81] +2024-11-22 00:25:17.840017: Epoch time: 19.09 s +2024-11-22 00:25:18.698159: +2024-11-22 00:25:18.698376: Epoch 2520 +2024-11-22 00:25:18.698486: Current learning rate: 0.00711 +2024-11-22 00:25:37.616447: train_loss -0.7708 +2024-11-22 00:25:37.616677: val_loss -0.7056 +2024-11-22 00:25:37.616751: Pseudo dice [0.8241] +2024-11-22 00:25:37.616828: Epoch time: 18.92 s +2024-11-22 00:25:38.473730: +2024-11-22 00:25:38.473947: Epoch 2521 +2024-11-22 00:25:38.474080: Current learning rate: 0.00711 +2024-11-22 00:25:57.410315: train_loss -0.7532 +2024-11-22 00:25:57.410542: val_loss -0.72 +2024-11-22 00:25:57.410621: Pseudo dice [0.7727] +2024-11-22 00:25:57.410699: Epoch time: 18.94 s +2024-11-22 00:25:58.417400: +2024-11-22 00:25:58.417592: Epoch 2522 +2024-11-22 00:25:58.417705: Current learning rate: 0.00711 +2024-11-22 00:26:17.041516: train_loss -0.7437 +2024-11-22 00:26:17.041733: val_loss -0.7411 +2024-11-22 00:26:17.041809: Pseudo dice [0.8176] +2024-11-22 00:26:17.041891: Epoch time: 18.62 s +2024-11-22 00:26:17.982070: +2024-11-22 00:26:17.982260: Epoch 2523 +2024-11-22 00:26:17.982376: Current learning rate: 0.00711 +2024-11-22 00:26:36.373395: train_loss -0.7499 +2024-11-22 00:26:36.373647: val_loss -0.735 +2024-11-22 00:26:36.373727: Pseudo dice [0.8187] +2024-11-22 00:26:36.373817: Epoch time: 18.39 s +2024-11-22 00:26:37.230556: +2024-11-22 00:26:37.230829: Epoch 2524 +2024-11-22 00:26:37.230948: Current learning rate: 0.00711 +2024-11-22 00:26:55.901498: train_loss -0.7526 +2024-11-22 00:26:55.901716: val_loss -0.715 +2024-11-22 00:26:55.901790: Pseudo dice [0.7885] +2024-11-22 00:26:55.904081: Epoch time: 18.67 s +2024-11-22 00:26:56.919635: +2024-11-22 00:26:56.919889: Epoch 2525 +2024-11-22 00:26:56.920004: Current learning rate: 0.00711 +2024-11-22 00:27:15.851845: train_loss -0.7527 +2024-11-22 00:27:15.852253: val_loss -0.7444 +2024-11-22 00:27:15.852342: Pseudo dice [0.8262] +2024-11-22 00:27:15.852421: Epoch time: 18.93 s +2024-11-22 00:27:16.711379: +2024-11-22 00:27:16.711649: Epoch 2526 +2024-11-22 00:27:16.711766: Current learning rate: 0.00711 +2024-11-22 00:27:34.950154: train_loss -0.7709 +2024-11-22 00:27:34.950361: val_loss -0.7138 +2024-11-22 00:27:34.950438: Pseudo dice [0.8261] +2024-11-22 00:27:34.950518: Epoch time: 18.24 s +2024-11-22 00:27:35.807043: +2024-11-22 00:27:35.807267: Epoch 2527 +2024-11-22 00:27:35.807428: Current learning rate: 0.00711 +2024-11-22 00:27:55.520542: train_loss -0.7621 +2024-11-22 00:27:55.525013: val_loss -0.7408 +2024-11-22 00:27:55.525143: Pseudo dice [0.8145] +2024-11-22 00:27:55.525229: Epoch time: 19.71 s +2024-11-22 00:27:56.469959: +2024-11-22 00:27:56.470176: Epoch 2528 +2024-11-22 00:27:56.470293: Current learning rate: 0.0071 +2024-11-22 00:28:14.565879: train_loss -0.7795 +2024-11-22 00:28:14.566110: val_loss -0.7543 +2024-11-22 00:28:14.566192: Pseudo dice [0.8183] +2024-11-22 00:28:14.566271: Epoch time: 18.1 s +2024-11-22 00:28:15.828579: +2024-11-22 00:28:15.828854: Epoch 2529 +2024-11-22 00:28:15.828970: Current learning rate: 0.0071 +2024-11-22 00:28:34.195489: train_loss -0.7723 +2024-11-22 00:28:34.200975: val_loss -0.7424 +2024-11-22 00:28:34.201095: Pseudo dice [0.8179] +2024-11-22 00:28:34.201184: Epoch time: 18.37 s +2024-11-22 00:28:35.075833: +2024-11-22 00:28:35.076071: Epoch 2530 +2024-11-22 00:28:35.076188: Current learning rate: 0.0071 +2024-11-22 00:28:53.410497: train_loss -0.7795 +2024-11-22 00:28:53.410724: val_loss -0.7675 +2024-11-22 00:28:53.410802: Pseudo dice [0.82] +2024-11-22 00:28:53.410877: Epoch time: 18.34 s +2024-11-22 00:28:54.269093: +2024-11-22 00:28:54.269325: Epoch 2531 +2024-11-22 00:28:54.269444: Current learning rate: 0.0071 +2024-11-22 00:29:13.445428: train_loss -0.7753 +2024-11-22 00:29:13.445639: val_loss -0.7077 +2024-11-22 00:29:13.445729: Pseudo dice [0.8223] +2024-11-22 00:29:13.445846: Epoch time: 19.18 s +2024-11-22 00:29:14.300745: +2024-11-22 00:29:14.301019: Epoch 2532 +2024-11-22 00:29:14.301137: Current learning rate: 0.0071 +2024-11-22 00:29:32.301581: train_loss -0.7569 +2024-11-22 00:29:32.301802: val_loss -0.7457 +2024-11-22 00:29:32.301878: Pseudo dice [0.8191] +2024-11-22 00:29:32.301960: Epoch time: 18.0 s +2024-11-22 00:29:33.156970: +2024-11-22 00:29:33.157163: Epoch 2533 +2024-11-22 00:29:33.157274: Current learning rate: 0.0071 +2024-11-22 00:29:51.446913: train_loss -0.7617 +2024-11-22 00:29:51.447162: val_loss -0.7257 +2024-11-22 00:29:51.447234: Pseudo dice [0.8213] +2024-11-22 00:29:51.447312: Epoch time: 18.29 s +2024-11-22 00:29:52.394012: +2024-11-22 00:29:52.394224: Epoch 2534 +2024-11-22 00:29:52.394338: Current learning rate: 0.0071 +2024-11-22 00:30:09.825679: train_loss -0.7688 +2024-11-22 00:30:09.825899: val_loss -0.7323 +2024-11-22 00:30:09.825975: Pseudo dice [0.8181] +2024-11-22 00:30:09.826059: Epoch time: 17.43 s +2024-11-22 00:30:10.913811: +2024-11-22 00:30:10.914042: Epoch 2535 +2024-11-22 00:30:10.914160: Current learning rate: 0.0071 +2024-11-22 00:30:30.127550: train_loss -0.7751 +2024-11-22 00:30:30.127769: val_loss -0.7202 +2024-11-22 00:30:30.127843: Pseudo dice [0.8213] +2024-11-22 00:30:30.127923: Epoch time: 19.21 s +2024-11-22 00:30:30.979932: +2024-11-22 00:30:30.980230: Epoch 2536 +2024-11-22 00:30:30.980347: Current learning rate: 0.0071 +2024-11-22 00:30:49.942657: train_loss -0.7698 +2024-11-22 00:30:49.942906: val_loss -0.7628 +2024-11-22 00:30:49.942980: Pseudo dice [0.8213] +2024-11-22 00:30:49.943075: Epoch time: 18.96 s +2024-11-22 00:30:50.795108: +2024-11-22 00:30:50.795377: Epoch 2537 +2024-11-22 00:30:50.795499: Current learning rate: 0.00709 +2024-11-22 00:31:08.853370: train_loss -0.7673 +2024-11-22 00:31:08.853594: val_loss -0.7595 +2024-11-22 00:31:08.853670: Pseudo dice [0.8237] +2024-11-22 00:31:08.853744: Epoch time: 18.06 s +2024-11-22 00:31:09.703629: +2024-11-22 00:31:09.703828: Epoch 2538 +2024-11-22 00:31:09.703938: Current learning rate: 0.00709 +2024-11-22 00:31:27.980880: train_loss -0.7509 +2024-11-22 00:31:27.981101: val_loss -0.7184 +2024-11-22 00:31:27.981173: Pseudo dice [0.8104] +2024-11-22 00:31:27.981251: Epoch time: 18.28 s +2024-11-22 00:31:28.828890: +2024-11-22 00:31:28.829101: Epoch 2539 +2024-11-22 00:31:28.829216: Current learning rate: 0.00709 +2024-11-22 00:31:47.845049: train_loss -0.7557 +2024-11-22 00:31:47.845270: val_loss -0.7478 +2024-11-22 00:31:47.845344: Pseudo dice [0.8333] +2024-11-22 00:31:47.845421: Epoch time: 19.02 s +2024-11-22 00:31:48.712662: +2024-11-22 00:31:48.712850: Epoch 2540 +2024-11-22 00:31:48.712961: Current learning rate: 0.00709 +2024-11-22 00:32:07.222149: train_loss -0.764 +2024-11-22 00:32:07.222397: val_loss -0.7378 +2024-11-22 00:32:07.222473: Pseudo dice [0.81] +2024-11-22 00:32:07.222559: Epoch time: 18.51 s +2024-11-22 00:32:08.496484: +2024-11-22 00:32:08.496707: Epoch 2541 +2024-11-22 00:32:08.496822: Current learning rate: 0.00709 +2024-11-22 00:32:26.528079: train_loss -0.7567 +2024-11-22 00:32:26.528296: val_loss -0.7512 +2024-11-22 00:32:26.528368: Pseudo dice [0.8162] +2024-11-22 00:32:26.528444: Epoch time: 18.03 s +2024-11-22 00:32:27.369779: +2024-11-22 00:32:27.369989: Epoch 2542 +2024-11-22 00:32:27.370103: Current learning rate: 0.00709 +2024-11-22 00:32:45.725715: train_loss -0.7583 +2024-11-22 00:32:45.725934: val_loss -0.7384 +2024-11-22 00:32:45.726013: Pseudo dice [0.8156] +2024-11-22 00:32:45.726096: Epoch time: 18.36 s +2024-11-22 00:32:46.582637: +2024-11-22 00:32:46.582848: Epoch 2543 +2024-11-22 00:32:46.582954: Current learning rate: 0.00709 +2024-11-22 00:33:06.350664: train_loss -0.7639 +2024-11-22 00:33:06.350907: val_loss -0.7594 +2024-11-22 00:33:06.350984: Pseudo dice [0.8175] +2024-11-22 00:33:06.351075: Epoch time: 19.77 s +2024-11-22 00:33:07.241086: +2024-11-22 00:33:07.241309: Epoch 2544 +2024-11-22 00:33:07.241427: Current learning rate: 0.00709 +2024-11-22 00:33:26.582783: train_loss -0.7705 +2024-11-22 00:33:26.583021: val_loss -0.7281 +2024-11-22 00:33:26.583113: Pseudo dice [0.8111] +2024-11-22 00:33:26.583192: Epoch time: 19.34 s +2024-11-22 00:33:27.596927: +2024-11-22 00:33:27.597175: Epoch 2545 +2024-11-22 00:33:27.597296: Current learning rate: 0.00708 +2024-11-22 00:33:46.214347: train_loss -0.7757 +2024-11-22 00:33:46.214628: val_loss -0.7421 +2024-11-22 00:33:46.214706: Pseudo dice [0.8281] +2024-11-22 00:33:46.214785: Epoch time: 18.62 s +2024-11-22 00:33:47.139094: +2024-11-22 00:33:47.139301: Epoch 2546 +2024-11-22 00:33:47.139409: Current learning rate: 0.00708 +2024-11-22 00:34:06.088062: train_loss -0.7715 +2024-11-22 00:34:06.088272: val_loss -0.7326 +2024-11-22 00:34:06.088345: Pseudo dice [0.8171] +2024-11-22 00:34:06.088419: Epoch time: 18.95 s +2024-11-22 00:34:07.047044: +2024-11-22 00:34:07.047264: Epoch 2547 +2024-11-22 00:34:07.047381: Current learning rate: 0.00708 +2024-11-22 00:34:25.220645: train_loss -0.7818 +2024-11-22 00:34:25.220889: val_loss -0.7596 +2024-11-22 00:34:25.220962: Pseudo dice [0.8355] +2024-11-22 00:34:25.221060: Epoch time: 18.17 s +2024-11-22 00:34:26.146132: +2024-11-22 00:34:26.146337: Epoch 2548 +2024-11-22 00:34:26.146449: Current learning rate: 0.00708 +2024-11-22 00:34:45.333487: train_loss -0.7807 +2024-11-22 00:34:45.333692: val_loss -0.7459 +2024-11-22 00:34:45.333800: Pseudo dice [0.8241] +2024-11-22 00:34:45.333877: Epoch time: 19.19 s +2024-11-22 00:34:46.193094: +2024-11-22 00:34:46.193293: Epoch 2549 +2024-11-22 00:34:46.193405: Current learning rate: 0.00708 +2024-11-22 00:35:05.240772: train_loss -0.7772 +2024-11-22 00:35:05.240996: val_loss -0.7381 +2024-11-22 00:35:05.241074: Pseudo dice [0.8419] +2024-11-22 00:35:05.241151: Epoch time: 19.05 s +2024-11-22 00:35:06.310574: +2024-11-22 00:35:06.310816: Epoch 2550 +2024-11-22 00:35:06.310932: Current learning rate: 0.00708 +2024-11-22 00:35:24.629044: train_loss -0.7753 +2024-11-22 00:35:24.629281: val_loss -0.7461 +2024-11-22 00:35:24.629362: Pseudo dice [0.8254] +2024-11-22 00:35:24.629446: Epoch time: 18.32 s +2024-11-22 00:35:25.488616: +2024-11-22 00:35:25.488834: Epoch 2551 +2024-11-22 00:35:25.488943: Current learning rate: 0.00708 +2024-11-22 00:35:44.371684: train_loss -0.7641 +2024-11-22 00:35:44.372055: val_loss -0.742 +2024-11-22 00:35:44.372149: Pseudo dice [0.8204] +2024-11-22 00:35:44.372237: Epoch time: 18.88 s +2024-11-22 00:35:45.224931: +2024-11-22 00:35:45.225138: Epoch 2552 +2024-11-22 00:35:45.225243: Current learning rate: 0.00708 +2024-11-22 00:36:03.742278: train_loss -0.7709 +2024-11-22 00:36:03.746864: val_loss -0.7435 +2024-11-22 00:36:03.748931: Pseudo dice [0.8228] +2024-11-22 00:36:03.749065: Epoch time: 18.52 s +2024-11-22 00:36:04.619123: +2024-11-22 00:36:04.619354: Epoch 2553 +2024-11-22 00:36:04.619468: Current learning rate: 0.00708 +2024-11-22 00:36:22.549853: train_loss -0.7847 +2024-11-22 00:36:22.550087: val_loss -0.7664 +2024-11-22 00:36:22.552368: Pseudo dice [0.8331] +2024-11-22 00:36:22.552510: Epoch time: 17.93 s +2024-11-22 00:36:23.476119: +2024-11-22 00:36:23.476323: Epoch 2554 +2024-11-22 00:36:23.476463: Current learning rate: 0.00707 +2024-11-22 00:36:43.264257: train_loss -0.7729 +2024-11-22 00:36:43.264493: val_loss -0.7512 +2024-11-22 00:36:43.264568: Pseudo dice [0.8438] +2024-11-22 00:36:43.264646: Epoch time: 19.79 s +2024-11-22 00:36:44.110343: +2024-11-22 00:36:44.110539: Epoch 2555 +2024-11-22 00:36:44.110650: Current learning rate: 0.00707 +2024-11-22 00:37:01.419701: train_loss -0.7724 +2024-11-22 00:37:01.419935: val_loss -0.7397 +2024-11-22 00:37:01.420017: Pseudo dice [0.8262] +2024-11-22 00:37:01.420094: Epoch time: 17.31 s +2024-11-22 00:37:02.304084: +2024-11-22 00:37:02.304302: Epoch 2556 +2024-11-22 00:37:02.304426: Current learning rate: 0.00707 +2024-11-22 00:37:21.891736: train_loss -0.7759 +2024-11-22 00:37:21.891954: val_loss -0.7425 +2024-11-22 00:37:21.892035: Pseudo dice [0.8345] +2024-11-22 00:37:21.892114: Epoch time: 19.59 s +2024-11-22 00:37:22.789741: +2024-11-22 00:37:22.789950: Epoch 2557 +2024-11-22 00:37:22.790067: Current learning rate: 0.00707 +2024-11-22 00:37:40.677860: train_loss -0.7722 +2024-11-22 00:37:40.683263: val_loss -0.7541 +2024-11-22 00:37:40.683414: Pseudo dice [0.8364] +2024-11-22 00:37:40.683503: Epoch time: 17.89 s +2024-11-22 00:37:41.710794: +2024-11-22 00:37:41.711002: Epoch 2558 +2024-11-22 00:37:41.711118: Current learning rate: 0.00707 +2024-11-22 00:38:01.111086: train_loss -0.7766 +2024-11-22 00:38:01.111324: val_loss -0.7715 +2024-11-22 00:38:01.111399: Pseudo dice [0.8342] +2024-11-22 00:38:01.111482: Epoch time: 19.4 s +2024-11-22 00:38:01.111542: Yayy! New best EMA pseudo Dice: 0.8283 +2024-11-22 00:38:02.191413: +2024-11-22 00:38:02.191635: Epoch 2559 +2024-11-22 00:38:02.191758: Current learning rate: 0.00707 +2024-11-22 00:38:21.220911: train_loss -0.7809 +2024-11-22 00:38:21.221232: val_loss -0.7222 +2024-11-22 00:38:21.221310: Pseudo dice [0.8123] +2024-11-22 00:38:21.221394: Epoch time: 19.03 s +2024-11-22 00:38:22.081829: +2024-11-22 00:38:22.082046: Epoch 2560 +2024-11-22 00:38:22.082163: Current learning rate: 0.00707 +2024-11-22 00:38:40.226660: train_loss -0.7782 +2024-11-22 00:38:40.226947: val_loss -0.7338 +2024-11-22 00:38:40.227030: Pseudo dice [0.8043] +2024-11-22 00:38:40.227117: Epoch time: 18.15 s +2024-11-22 00:38:41.085094: +2024-11-22 00:38:41.085372: Epoch 2561 +2024-11-22 00:38:41.085486: Current learning rate: 0.00707 +2024-11-22 00:38:58.843236: train_loss -0.7779 +2024-11-22 00:38:58.843484: val_loss -0.7506 +2024-11-22 00:38:58.843560: Pseudo dice [0.8093] +2024-11-22 00:38:58.843638: Epoch time: 17.76 s +2024-11-22 00:38:59.697619: +2024-11-22 00:38:59.697819: Epoch 2562 +2024-11-22 00:38:59.697932: Current learning rate: 0.00707 +2024-11-22 00:39:18.035682: train_loss -0.7762 +2024-11-22 00:39:18.035892: val_loss -0.7461 +2024-11-22 00:39:18.035965: Pseudo dice [0.832] +2024-11-22 00:39:18.036046: Epoch time: 18.34 s +2024-11-22 00:39:18.889168: +2024-11-22 00:39:18.889373: Epoch 2563 +2024-11-22 00:39:18.889486: Current learning rate: 0.00706 +2024-11-22 00:39:38.255826: train_loss -0.7854 +2024-11-22 00:39:38.256055: val_loss -0.7295 +2024-11-22 00:39:38.256130: Pseudo dice [0.8242] +2024-11-22 00:39:38.258432: Epoch time: 19.37 s +2024-11-22 00:39:39.522763: +2024-11-22 00:39:39.522970: Epoch 2564 +2024-11-22 00:39:39.523088: Current learning rate: 0.00706 +2024-11-22 00:39:58.161749: train_loss -0.7888 +2024-11-22 00:39:58.161998: val_loss -0.7625 +2024-11-22 00:39:58.162074: Pseudo dice [0.8324] +2024-11-22 00:39:58.162158: Epoch time: 18.64 s +2024-11-22 00:39:59.018869: +2024-11-22 00:39:59.019674: Epoch 2565 +2024-11-22 00:39:59.019794: Current learning rate: 0.00706 +2024-11-22 00:40:18.152299: train_loss -0.7826 +2024-11-22 00:40:18.152512: val_loss -0.7218 +2024-11-22 00:40:18.152588: Pseudo dice [0.8147] +2024-11-22 00:40:18.152666: Epoch time: 19.13 s +2024-11-22 00:40:19.010857: +2024-11-22 00:40:19.011065: Epoch 2566 +2024-11-22 00:40:19.011181: Current learning rate: 0.00706 +2024-11-22 00:40:36.613274: train_loss -0.7901 +2024-11-22 00:40:36.613488: val_loss -0.7586 +2024-11-22 00:40:36.613562: Pseudo dice [0.8338] +2024-11-22 00:40:36.613645: Epoch time: 17.6 s +2024-11-22 00:40:37.466535: +2024-11-22 00:40:37.466735: Epoch 2567 +2024-11-22 00:40:37.466844: Current learning rate: 0.00706 +2024-11-22 00:40:57.764192: train_loss -0.7722 +2024-11-22 00:40:57.764420: val_loss -0.7481 +2024-11-22 00:40:57.764496: Pseudo dice [0.8291] +2024-11-22 00:40:57.764580: Epoch time: 20.3 s +2024-11-22 00:40:58.793442: +2024-11-22 00:40:58.793637: Epoch 2568 +2024-11-22 00:40:58.793749: Current learning rate: 0.00706 +2024-11-22 00:41:18.443948: train_loss -0.7758 +2024-11-22 00:41:18.444185: val_loss -0.7534 +2024-11-22 00:41:18.444268: Pseudo dice [0.8316] +2024-11-22 00:41:18.444357: Epoch time: 19.65 s +2024-11-22 00:41:19.306436: +2024-11-22 00:41:19.306631: Epoch 2569 +2024-11-22 00:41:19.306743: Current learning rate: 0.00706 +2024-11-22 00:41:36.484618: train_loss -0.7734 +2024-11-22 00:41:36.484839: val_loss -0.7476 +2024-11-22 00:41:36.484915: Pseudo dice [0.8229] +2024-11-22 00:41:36.485001: Epoch time: 17.18 s +2024-11-22 00:41:37.334740: +2024-11-22 00:41:37.334947: Epoch 2570 +2024-11-22 00:41:37.335069: Current learning rate: 0.00706 +2024-11-22 00:41:55.803337: train_loss -0.7624 +2024-11-22 00:41:55.803562: val_loss -0.7462 +2024-11-22 00:41:55.803638: Pseudo dice [0.8368] +2024-11-22 00:41:55.803717: Epoch time: 18.47 s +2024-11-22 00:41:56.659049: +2024-11-22 00:41:56.659263: Epoch 2571 +2024-11-22 00:41:56.659377: Current learning rate: 0.00705 +2024-11-22 00:42:15.896693: train_loss -0.77 +2024-11-22 00:42:15.896973: val_loss -0.7351 +2024-11-22 00:42:15.897056: Pseudo dice [0.824] +2024-11-22 00:42:15.897138: Epoch time: 19.24 s +2024-11-22 00:42:16.831445: +2024-11-22 00:42:16.831681: Epoch 2572 +2024-11-22 00:42:16.831798: Current learning rate: 0.00705 +2024-11-22 00:42:35.580231: train_loss -0.7779 +2024-11-22 00:42:35.580455: val_loss -0.7338 +2024-11-22 00:42:35.580529: Pseudo dice [0.8148] +2024-11-22 00:42:35.580606: Epoch time: 18.75 s +2024-11-22 00:42:36.431437: +2024-11-22 00:42:36.431686: Epoch 2573 +2024-11-22 00:42:36.431799: Current learning rate: 0.00705 +2024-11-22 00:42:55.126256: train_loss -0.7809 +2024-11-22 00:42:55.126476: val_loss -0.7476 +2024-11-22 00:42:55.126550: Pseudo dice [0.8228] +2024-11-22 00:42:55.126626: Epoch time: 18.7 s +2024-11-22 00:42:55.979032: +2024-11-22 00:42:55.979227: Epoch 2574 +2024-11-22 00:42:55.979336: Current learning rate: 0.00705 +2024-11-22 00:43:14.274101: train_loss -0.7797 +2024-11-22 00:43:14.274322: val_loss -0.7346 +2024-11-22 00:43:14.274397: Pseudo dice [0.8383] +2024-11-22 00:43:14.274489: Epoch time: 18.3 s +2024-11-22 00:43:15.136827: +2024-11-22 00:43:15.137079: Epoch 2575 +2024-11-22 00:43:15.137210: Current learning rate: 0.00705 +2024-11-22 00:43:32.933404: train_loss -0.7806 +2024-11-22 00:43:32.933640: val_loss -0.7321 +2024-11-22 00:43:32.933716: Pseudo dice [0.8319] +2024-11-22 00:43:32.933797: Epoch time: 17.8 s +2024-11-22 00:43:34.175570: +2024-11-22 00:43:34.175977: Epoch 2576 +2024-11-22 00:43:34.176093: Current learning rate: 0.00705 +2024-11-22 00:43:52.398893: train_loss -0.778 +2024-11-22 00:43:52.399123: val_loss -0.7466 +2024-11-22 00:43:52.399206: Pseudo dice [0.8113] +2024-11-22 00:43:52.399289: Epoch time: 18.22 s +2024-11-22 00:43:53.252435: +2024-11-22 00:43:53.252650: Epoch 2577 +2024-11-22 00:43:53.252764: Current learning rate: 0.00705 +2024-11-22 00:44:12.205362: train_loss -0.7661 +2024-11-22 00:44:12.205575: val_loss -0.7487 +2024-11-22 00:44:12.205648: Pseudo dice [0.8383] +2024-11-22 00:44:12.206357: Epoch time: 18.95 s +2024-11-22 00:44:13.064981: +2024-11-22 00:44:13.065184: Epoch 2578 +2024-11-22 00:44:13.065303: Current learning rate: 0.00705 +2024-11-22 00:44:31.871905: train_loss -0.7672 +2024-11-22 00:44:31.874359: val_loss -0.7455 +2024-11-22 00:44:31.874457: Pseudo dice [0.8289] +2024-11-22 00:44:31.874549: Epoch time: 18.81 s +2024-11-22 00:44:32.844953: +2024-11-22 00:44:32.845248: Epoch 2579 +2024-11-22 00:44:32.845363: Current learning rate: 0.00705 +2024-11-22 00:44:50.828771: train_loss -0.7802 +2024-11-22 00:44:50.829000: val_loss -0.7449 +2024-11-22 00:44:50.829073: Pseudo dice [0.8225] +2024-11-22 00:44:50.829150: Epoch time: 17.98 s +2024-11-22 00:44:51.689635: +2024-11-22 00:44:51.689824: Epoch 2580 +2024-11-22 00:44:51.689968: Current learning rate: 0.00704 +2024-11-22 00:45:10.572088: train_loss -0.7714 +2024-11-22 00:45:10.572307: val_loss -0.7313 +2024-11-22 00:45:10.572386: Pseudo dice [0.8175] +2024-11-22 00:45:10.572463: Epoch time: 18.88 s +2024-11-22 00:45:11.713487: +2024-11-22 00:45:11.713716: Epoch 2581 +2024-11-22 00:45:11.713836: Current learning rate: 0.00704 +2024-11-22 00:45:30.092116: train_loss -0.7827 +2024-11-22 00:45:30.092359: val_loss -0.7369 +2024-11-22 00:45:30.092441: Pseudo dice [0.8417] +2024-11-22 00:45:30.092516: Epoch time: 18.38 s +2024-11-22 00:45:30.950176: +2024-11-22 00:45:30.950434: Epoch 2582 +2024-11-22 00:45:30.950553: Current learning rate: 0.00704 +2024-11-22 00:45:49.916601: train_loss -0.7773 +2024-11-22 00:45:49.916840: val_loss -0.7675 +2024-11-22 00:45:49.916912: Pseudo dice [0.8139] +2024-11-22 00:45:49.917001: Epoch time: 18.97 s +2024-11-22 00:45:50.937748: +2024-11-22 00:45:50.937958: Epoch 2583 +2024-11-22 00:45:50.938075: Current learning rate: 0.00704 +2024-11-22 00:46:09.790029: train_loss -0.7863 +2024-11-22 00:46:09.790308: val_loss -0.744 +2024-11-22 00:46:09.790389: Pseudo dice [0.8251] +2024-11-22 00:46:09.790467: Epoch time: 18.85 s +2024-11-22 00:46:10.647123: +2024-11-22 00:46:10.647326: Epoch 2584 +2024-11-22 00:46:10.647444: Current learning rate: 0.00704 +2024-11-22 00:46:30.342613: train_loss -0.773 +2024-11-22 00:46:30.346101: val_loss -0.7615 +2024-11-22 00:46:30.346264: Pseudo dice [0.8316] +2024-11-22 00:46:30.346348: Epoch time: 19.7 s +2024-11-22 00:46:31.249251: +2024-11-22 00:46:31.249444: Epoch 2585 +2024-11-22 00:46:31.249561: Current learning rate: 0.00704 +2024-11-22 00:46:49.434908: train_loss -0.7787 +2024-11-22 00:46:49.435129: val_loss -0.7614 +2024-11-22 00:46:49.435202: Pseudo dice [0.8387] +2024-11-22 00:46:49.435281: Epoch time: 18.19 s +2024-11-22 00:46:50.330122: +2024-11-22 00:46:50.330317: Epoch 2586 +2024-11-22 00:46:50.330428: Current learning rate: 0.00704 +2024-11-22 00:47:08.142061: train_loss -0.7893 +2024-11-22 00:47:08.142305: val_loss -0.7198 +2024-11-22 00:47:08.142380: Pseudo dice [0.8171] +2024-11-22 00:47:08.142462: Epoch time: 17.81 s +2024-11-22 00:47:08.998512: +2024-11-22 00:47:08.998711: Epoch 2587 +2024-11-22 00:47:08.998846: Current learning rate: 0.00704 +2024-11-22 00:47:26.866705: train_loss -0.7835 +2024-11-22 00:47:26.866957: val_loss -0.7332 +2024-11-22 00:47:26.867040: Pseudo dice [0.8381] +2024-11-22 00:47:26.867120: Epoch time: 17.87 s +2024-11-22 00:47:28.120728: +2024-11-22 00:47:28.120945: Epoch 2588 +2024-11-22 00:47:28.121066: Current learning rate: 0.00703 +2024-11-22 00:47:46.201741: train_loss -0.7775 +2024-11-22 00:47:46.201988: val_loss -0.7645 +2024-11-22 00:47:46.202074: Pseudo dice [0.8303] +2024-11-22 00:47:46.202156: Epoch time: 18.08 s +2024-11-22 00:47:47.116559: +2024-11-22 00:47:47.116804: Epoch 2589 +2024-11-22 00:47:47.116921: Current learning rate: 0.00703 +2024-11-22 00:48:06.391046: train_loss -0.7741 +2024-11-22 00:48:06.391319: val_loss -0.7399 +2024-11-22 00:48:06.391392: Pseudo dice [0.827] +2024-11-22 00:48:06.391472: Epoch time: 19.28 s +2024-11-22 00:48:07.302441: +2024-11-22 00:48:07.302670: Epoch 2590 +2024-11-22 00:48:07.302781: Current learning rate: 0.00703 +2024-11-22 00:48:26.645015: train_loss -0.7704 +2024-11-22 00:48:26.645885: val_loss -0.7463 +2024-11-22 00:48:26.645972: Pseudo dice [0.8333] +2024-11-22 00:48:26.646057: Epoch time: 19.34 s +2024-11-22 00:48:26.646116: Yayy! New best EMA pseudo Dice: 0.8284 +2024-11-22 00:48:27.713131: +2024-11-22 00:48:27.713326: Epoch 2591 +2024-11-22 00:48:27.713439: Current learning rate: 0.00703 +2024-11-22 00:48:46.173247: train_loss -0.7699 +2024-11-22 00:48:46.175618: val_loss -0.7577 +2024-11-22 00:48:46.175710: Pseudo dice [0.8312] +2024-11-22 00:48:46.175787: Epoch time: 18.46 s +2024-11-22 00:48:46.175846: Yayy! New best EMA pseudo Dice: 0.8287 +2024-11-22 00:48:47.428856: +2024-11-22 00:48:47.429067: Epoch 2592 +2024-11-22 00:48:47.429193: Current learning rate: 0.00703 +2024-11-22 00:49:06.371255: train_loss -0.7836 +2024-11-22 00:49:06.371542: val_loss -0.706 +2024-11-22 00:49:06.371621: Pseudo dice [0.8349] +2024-11-22 00:49:06.371705: Epoch time: 18.94 s +2024-11-22 00:49:06.371768: Yayy! New best EMA pseudo Dice: 0.8293 +2024-11-22 00:49:07.440105: +2024-11-22 00:49:07.440347: Epoch 2593 +2024-11-22 00:49:07.440469: Current learning rate: 0.00703 +2024-11-22 00:49:25.878040: train_loss -0.7826 +2024-11-22 00:49:25.878279: val_loss -0.7345 +2024-11-22 00:49:25.878354: Pseudo dice [0.8111] +2024-11-22 00:49:25.878431: Epoch time: 18.44 s +2024-11-22 00:49:26.881458: +2024-11-22 00:49:26.881692: Epoch 2594 +2024-11-22 00:49:26.881813: Current learning rate: 0.00703 +2024-11-22 00:49:45.674916: train_loss -0.7771 +2024-11-22 00:49:45.675134: val_loss -0.7141 +2024-11-22 00:49:45.675204: Pseudo dice [0.8064] +2024-11-22 00:49:45.675279: Epoch time: 18.79 s +2024-11-22 00:49:46.535782: +2024-11-22 00:49:46.536010: Epoch 2595 +2024-11-22 00:49:46.536126: Current learning rate: 0.00703 +2024-11-22 00:50:04.730388: train_loss -0.7739 +2024-11-22 00:50:04.730604: val_loss -0.712 +2024-11-22 00:50:04.730678: Pseudo dice [0.803] +2024-11-22 00:50:04.730761: Epoch time: 18.2 s +2024-11-22 00:50:05.594423: +2024-11-22 00:50:05.594632: Epoch 2596 +2024-11-22 00:50:05.594745: Current learning rate: 0.00703 +2024-11-22 00:50:23.648856: train_loss -0.7692 +2024-11-22 00:50:23.649145: val_loss -0.7576 +2024-11-22 00:50:23.649222: Pseudo dice [0.828] +2024-11-22 00:50:23.649301: Epoch time: 18.06 s +2024-11-22 00:50:24.508643: +2024-11-22 00:50:24.508839: Epoch 2597 +2024-11-22 00:50:24.508954: Current learning rate: 0.00702 +2024-11-22 00:50:43.714906: train_loss -0.7802 +2024-11-22 00:50:43.715140: val_loss -0.7376 +2024-11-22 00:50:43.715213: Pseudo dice [0.8261] +2024-11-22 00:50:43.715292: Epoch time: 19.21 s +2024-11-22 00:50:44.570299: +2024-11-22 00:50:44.570503: Epoch 2598 +2024-11-22 00:50:44.570616: Current learning rate: 0.00702 +2024-11-22 00:51:02.810022: train_loss -0.7791 +2024-11-22 00:51:02.810235: val_loss -0.7448 +2024-11-22 00:51:02.810310: Pseudo dice [0.8144] +2024-11-22 00:51:02.810388: Epoch time: 18.24 s +2024-11-22 00:51:04.071912: +2024-11-22 00:51:04.072117: Epoch 2599 +2024-11-22 00:51:04.072230: Current learning rate: 0.00702 +2024-11-22 00:51:23.227243: train_loss -0.783 +2024-11-22 00:51:23.227493: val_loss -0.7597 +2024-11-22 00:51:23.227573: Pseudo dice [0.8239] +2024-11-22 00:51:23.227662: Epoch time: 19.16 s +2024-11-22 00:51:24.305957: +2024-11-22 00:51:24.306195: Epoch 2600 +2024-11-22 00:51:24.306311: Current learning rate: 0.00702 +2024-11-22 00:51:42.386053: train_loss -0.7855 +2024-11-22 00:51:42.386270: val_loss -0.7541 +2024-11-22 00:51:42.386344: Pseudo dice [0.8245] +2024-11-22 00:51:42.386420: Epoch time: 18.08 s +2024-11-22 00:51:43.240946: +2024-11-22 00:51:43.241170: Epoch 2601 +2024-11-22 00:51:43.241285: Current learning rate: 0.00702 +2024-11-22 00:52:02.612284: train_loss -0.7889 +2024-11-22 00:52:02.612510: val_loss -0.7423 +2024-11-22 00:52:02.612586: Pseudo dice [0.8234] +2024-11-22 00:52:02.612664: Epoch time: 19.37 s +2024-11-22 00:52:03.499225: +2024-11-22 00:52:03.499463: Epoch 2602 +2024-11-22 00:52:03.499588: Current learning rate: 0.00702 +2024-11-22 00:52:21.594091: train_loss -0.7823 +2024-11-22 00:52:21.594458: val_loss -0.7343 +2024-11-22 00:52:21.619493: Pseudo dice [0.8226] +2024-11-22 00:52:21.619680: Epoch time: 18.1 s +2024-11-22 00:52:22.482207: +2024-11-22 00:52:22.482431: Epoch 2603 +2024-11-22 00:52:22.482545: Current learning rate: 0.00702 +2024-11-22 00:52:41.137175: train_loss -0.7641 +2024-11-22 00:52:41.137423: val_loss -0.7148 +2024-11-22 00:52:41.137501: Pseudo dice [0.8083] +2024-11-22 00:52:41.137583: Epoch time: 18.66 s +2024-11-22 00:52:41.986916: +2024-11-22 00:52:41.987117: Epoch 2604 +2024-11-22 00:52:41.987235: Current learning rate: 0.00702 +2024-11-22 00:53:01.096401: train_loss -0.7811 +2024-11-22 00:53:01.096637: val_loss -0.7446 +2024-11-22 00:53:01.096772: Pseudo dice [0.8246] +2024-11-22 00:53:01.096852: Epoch time: 19.11 s +2024-11-22 00:53:02.134842: +2024-11-22 00:53:02.135117: Epoch 2605 +2024-11-22 00:53:02.135228: Current learning rate: 0.00701 +2024-11-22 00:53:20.145487: train_loss -0.785 +2024-11-22 00:53:20.145723: val_loss -0.7543 +2024-11-22 00:53:20.145800: Pseudo dice [0.8268] +2024-11-22 00:53:20.145879: Epoch time: 18.01 s +2024-11-22 00:53:21.005422: +2024-11-22 00:53:21.005608: Epoch 2606 +2024-11-22 00:53:21.005722: Current learning rate: 0.00701 +2024-11-22 00:53:41.040288: train_loss -0.7776 +2024-11-22 00:53:41.040502: val_loss -0.7568 +2024-11-22 00:53:41.040577: Pseudo dice [0.8259] +2024-11-22 00:53:41.040658: Epoch time: 20.04 s +2024-11-22 00:53:41.896541: +2024-11-22 00:53:41.896742: Epoch 2607 +2024-11-22 00:53:41.896888: Current learning rate: 0.00701 +2024-11-22 00:54:00.696341: train_loss -0.7768 +2024-11-22 00:54:00.696563: val_loss -0.7283 +2024-11-22 00:54:00.696638: Pseudo dice [0.817] +2024-11-22 00:54:00.696716: Epoch time: 18.8 s +2024-11-22 00:54:01.608747: +2024-11-22 00:54:01.609010: Epoch 2608 +2024-11-22 00:54:01.609121: Current learning rate: 0.00701 +2024-11-22 00:54:20.163875: train_loss -0.7853 +2024-11-22 00:54:20.164134: val_loss -0.7526 +2024-11-22 00:54:20.164212: Pseudo dice [0.8164] +2024-11-22 00:54:20.164288: Epoch time: 18.56 s +2024-11-22 00:54:21.012527: +2024-11-22 00:54:21.012761: Epoch 2609 +2024-11-22 00:54:21.012873: Current learning rate: 0.00701 +2024-11-22 00:54:40.219845: train_loss -0.7831 +2024-11-22 00:54:40.225254: val_loss -0.7302 +2024-11-22 00:54:40.225382: Pseudo dice [0.8204] +2024-11-22 00:54:40.225466: Epoch time: 19.21 s +2024-11-22 00:54:41.233239: +2024-11-22 00:54:41.233437: Epoch 2610 +2024-11-22 00:54:41.233548: Current learning rate: 0.00701 +2024-11-22 00:55:00.227050: train_loss -0.772 +2024-11-22 00:55:00.227576: val_loss -0.7591 +2024-11-22 00:55:00.227677: Pseudo dice [0.8339] +2024-11-22 00:55:00.227767: Epoch time: 18.99 s +2024-11-22 00:55:01.087703: +2024-11-22 00:55:01.087926: Epoch 2611 +2024-11-22 00:55:01.088049: Current learning rate: 0.00701 +2024-11-22 00:55:19.696975: train_loss -0.7681 +2024-11-22 00:55:19.697233: val_loss -0.7439 +2024-11-22 00:55:19.697315: Pseudo dice [0.8164] +2024-11-22 00:55:19.697394: Epoch time: 18.61 s +2024-11-22 00:55:20.552913: +2024-11-22 00:55:20.553129: Epoch 2612 +2024-11-22 00:55:20.553241: Current learning rate: 0.00701 +2024-11-22 00:55:39.253017: train_loss -0.7733 +2024-11-22 00:55:39.253237: val_loss -0.7319 +2024-11-22 00:55:39.253314: Pseudo dice [0.8243] +2024-11-22 00:55:39.253397: Epoch time: 18.7 s +2024-11-22 00:55:40.105270: +2024-11-22 00:55:40.105469: Epoch 2613 +2024-11-22 00:55:40.105583: Current learning rate: 0.00701 +2024-11-22 00:55:58.831414: train_loss -0.7751 +2024-11-22 00:55:58.831686: val_loss -0.7185 +2024-11-22 00:55:58.831761: Pseudo dice [0.8199] +2024-11-22 00:55:58.831845: Epoch time: 18.73 s +2024-11-22 00:55:59.752890: +2024-11-22 00:55:59.753101: Epoch 2614 +2024-11-22 00:55:59.753215: Current learning rate: 0.007 +2024-11-22 00:56:18.555846: train_loss -0.7816 +2024-11-22 00:56:18.561239: val_loss -0.7416 +2024-11-22 00:56:18.561380: Pseudo dice [0.83] +2024-11-22 00:56:18.561463: Epoch time: 18.8 s +2024-11-22 00:56:19.584135: +2024-11-22 00:56:19.584367: Epoch 2615 +2024-11-22 00:56:19.584491: Current learning rate: 0.007 +2024-11-22 00:56:39.054271: train_loss -0.7748 +2024-11-22 00:56:39.054497: val_loss -0.7502 +2024-11-22 00:56:39.054572: Pseudo dice [0.8152] +2024-11-22 00:56:39.054650: Epoch time: 19.47 s +2024-11-22 00:56:39.904311: +2024-11-22 00:56:39.904518: Epoch 2616 +2024-11-22 00:56:39.904632: Current learning rate: 0.007 +2024-11-22 00:56:58.589715: train_loss -0.7713 +2024-11-22 00:56:58.590002: val_loss -0.7331 +2024-11-22 00:56:58.590083: Pseudo dice [0.8204] +2024-11-22 00:56:58.590162: Epoch time: 18.69 s +2024-11-22 00:56:59.443673: +2024-11-22 00:56:59.443891: Epoch 2617 +2024-11-22 00:56:59.444014: Current learning rate: 0.007 +2024-11-22 00:57:17.814904: train_loss -0.7756 +2024-11-22 00:57:17.815171: val_loss -0.7514 +2024-11-22 00:57:17.815253: Pseudo dice [0.8364] +2024-11-22 00:57:17.815344: Epoch time: 18.37 s +2024-11-22 00:57:18.772385: +2024-11-22 00:57:18.772740: Epoch 2618 +2024-11-22 00:57:18.772854: Current learning rate: 0.007 +2024-11-22 00:57:38.049637: train_loss -0.7757 +2024-11-22 00:57:38.049911: val_loss -0.7334 +2024-11-22 00:57:38.049990: Pseudo dice [0.8139] +2024-11-22 00:57:38.050076: Epoch time: 19.28 s +2024-11-22 00:57:39.151583: +2024-11-22 00:57:39.151789: Epoch 2619 +2024-11-22 00:57:39.151899: Current learning rate: 0.007 +2024-11-22 00:57:57.660789: train_loss -0.766 +2024-11-22 00:57:57.661038: val_loss -0.748 +2024-11-22 00:57:57.661116: Pseudo dice [0.8257] +2024-11-22 00:57:57.661198: Epoch time: 18.51 s +2024-11-22 00:57:58.517895: +2024-11-22 00:57:58.518091: Epoch 2620 +2024-11-22 00:57:58.518229: Current learning rate: 0.007 +2024-11-22 00:58:17.701378: train_loss -0.768 +2024-11-22 00:58:17.701594: val_loss -0.7298 +2024-11-22 00:58:17.701674: Pseudo dice [0.8146] +2024-11-22 00:58:17.701751: Epoch time: 19.18 s +2024-11-22 00:58:18.556848: +2024-11-22 00:58:18.557059: Epoch 2621 +2024-11-22 00:58:18.557171: Current learning rate: 0.007 +2024-11-22 00:58:37.072337: train_loss -0.7774 +2024-11-22 00:58:37.072576: val_loss -0.7626 +2024-11-22 00:58:37.072654: Pseudo dice [0.8327] +2024-11-22 00:58:37.072736: Epoch time: 18.52 s +2024-11-22 00:58:38.322377: +2024-11-22 00:58:38.322600: Epoch 2622 +2024-11-22 00:58:38.322710: Current learning rate: 0.00699 +2024-11-22 00:58:57.703408: train_loss -0.7653 +2024-11-22 00:58:57.703633: val_loss -0.7427 +2024-11-22 00:58:57.703713: Pseudo dice [0.8067] +2024-11-22 00:58:57.703795: Epoch time: 19.38 s +2024-11-22 00:58:58.556612: +2024-11-22 00:58:58.556923: Epoch 2623 +2024-11-22 00:58:58.557043: Current learning rate: 0.00699 +2024-11-22 00:59:17.897050: train_loss -0.7668 +2024-11-22 00:59:17.897259: val_loss -0.7478 +2024-11-22 00:59:17.897334: Pseudo dice [0.8378] +2024-11-22 00:59:17.897410: Epoch time: 19.34 s +2024-11-22 00:59:18.747464: +2024-11-22 00:59:18.747772: Epoch 2624 +2024-11-22 00:59:18.747888: Current learning rate: 0.00699 +2024-11-22 00:59:37.710874: train_loss -0.7795 +2024-11-22 00:59:37.711125: val_loss -0.7477 +2024-11-22 00:59:37.711201: Pseudo dice [0.8349] +2024-11-22 00:59:37.711290: Epoch time: 18.96 s +2024-11-22 00:59:38.569357: +2024-11-22 00:59:38.569568: Epoch 2625 +2024-11-22 00:59:38.569679: Current learning rate: 0.00699 +2024-11-22 00:59:57.273036: train_loss -0.7808 +2024-11-22 00:59:57.273282: val_loss -0.7319 +2024-11-22 00:59:57.273358: Pseudo dice [0.8086] +2024-11-22 00:59:57.273432: Epoch time: 18.7 s +2024-11-22 00:59:58.128458: +2024-11-22 00:59:58.128656: Epoch 2626 +2024-11-22 00:59:58.128775: Current learning rate: 0.00699 +2024-11-22 01:00:16.888222: train_loss -0.7741 +2024-11-22 01:00:16.888434: val_loss -0.7357 +2024-11-22 01:00:16.888522: Pseudo dice [0.8312] +2024-11-22 01:00:16.888657: Epoch time: 18.76 s +2024-11-22 01:00:17.750222: +2024-11-22 01:00:17.750416: Epoch 2627 +2024-11-22 01:00:17.750530: Current learning rate: 0.00699 +2024-11-22 01:00:36.885306: train_loss -0.7767 +2024-11-22 01:00:36.887729: val_loss -0.7694 +2024-11-22 01:00:36.887830: Pseudo dice [0.8457] +2024-11-22 01:00:36.887910: Epoch time: 19.14 s +2024-11-22 01:00:37.788745: +2024-11-22 01:00:37.788970: Epoch 2628 +2024-11-22 01:00:37.789092: Current learning rate: 0.00699 +2024-11-22 01:00:55.813565: train_loss -0.7787 +2024-11-22 01:00:55.815113: val_loss -0.756 +2024-11-22 01:00:55.815230: Pseudo dice [0.8374] +2024-11-22 01:00:55.815314: Epoch time: 18.03 s +2024-11-22 01:00:56.673158: +2024-11-22 01:00:56.673358: Epoch 2629 +2024-11-22 01:00:56.673466: Current learning rate: 0.00699 +2024-11-22 01:01:14.336500: train_loss -0.7657 +2024-11-22 01:01:14.336717: val_loss -0.7158 +2024-11-22 01:01:14.336790: Pseudo dice [0.8299] +2024-11-22 01:01:14.336866: Epoch time: 17.66 s +2024-11-22 01:01:15.190857: +2024-11-22 01:01:15.191070: Epoch 2630 +2024-11-22 01:01:15.191185: Current learning rate: 0.00699 +2024-11-22 01:01:33.757406: train_loss -0.7856 +2024-11-22 01:01:33.757698: val_loss -0.7425 +2024-11-22 01:01:33.757808: Pseudo dice [0.8298] +2024-11-22 01:01:33.757887: Epoch time: 18.57 s +2024-11-22 01:01:34.611918: +2024-11-22 01:01:34.612123: Epoch 2631 +2024-11-22 01:01:34.612236: Current learning rate: 0.00698 +2024-11-22 01:01:53.212828: train_loss -0.7676 +2024-11-22 01:01:53.213077: val_loss -0.723 +2024-11-22 01:01:53.213155: Pseudo dice [0.811] +2024-11-22 01:01:53.213240: Epoch time: 18.6 s +2024-11-22 01:01:54.070407: +2024-11-22 01:01:54.070608: Epoch 2632 +2024-11-22 01:01:54.070727: Current learning rate: 0.00698 +2024-11-22 01:02:13.079652: train_loss -0.7619 +2024-11-22 01:02:13.079870: val_loss -0.7439 +2024-11-22 01:02:13.079945: Pseudo dice [0.8251] +2024-11-22 01:02:13.080032: Epoch time: 19.01 s +2024-11-22 01:02:13.931656: +2024-11-22 01:02:13.931910: Epoch 2633 +2024-11-22 01:02:13.932030: Current learning rate: 0.00698 +2024-11-22 01:02:32.747400: train_loss -0.7717 +2024-11-22 01:02:32.747622: val_loss -0.739 +2024-11-22 01:02:32.747699: Pseudo dice [0.8197] +2024-11-22 01:02:32.747780: Epoch time: 18.82 s +2024-11-22 01:02:33.988468: +2024-11-22 01:02:33.988672: Epoch 2634 +2024-11-22 01:02:33.988782: Current learning rate: 0.00698 +2024-11-22 01:02:51.840703: train_loss -0.7791 +2024-11-22 01:02:51.843122: val_loss -0.76 +2024-11-22 01:02:51.843217: Pseudo dice [0.8291] +2024-11-22 01:02:51.843302: Epoch time: 17.85 s +2024-11-22 01:02:52.718813: +2024-11-22 01:02:52.719087: Epoch 2635 +2024-11-22 01:02:52.719205: Current learning rate: 0.00698 +2024-11-22 01:03:11.192883: train_loss -0.7833 +2024-11-22 01:03:11.193113: val_loss -0.7266 +2024-11-22 01:03:11.193190: Pseudo dice [0.8101] +2024-11-22 01:03:11.193281: Epoch time: 18.47 s +2024-11-22 01:03:12.048766: +2024-11-22 01:03:12.048974: Epoch 2636 +2024-11-22 01:03:12.049105: Current learning rate: 0.00698 +2024-11-22 01:03:30.972313: train_loss -0.7842 +2024-11-22 01:03:30.973900: val_loss -0.765 +2024-11-22 01:03:30.974015: Pseudo dice [0.8352] +2024-11-22 01:03:30.974094: Epoch time: 18.92 s +2024-11-22 01:03:31.837853: +2024-11-22 01:03:31.838096: Epoch 2637 +2024-11-22 01:03:31.838218: Current learning rate: 0.00698 +2024-11-22 01:03:49.718158: train_loss -0.7851 +2024-11-22 01:03:49.718381: val_loss -0.727 +2024-11-22 01:03:49.718457: Pseudo dice [0.825] +2024-11-22 01:03:49.718540: Epoch time: 17.88 s +2024-11-22 01:03:50.613471: +2024-11-22 01:03:50.613672: Epoch 2638 +2024-11-22 01:03:50.613783: Current learning rate: 0.00698 +2024-11-22 01:04:09.475678: train_loss -0.7826 +2024-11-22 01:04:09.475921: val_loss -0.7426 +2024-11-22 01:04:09.476003: Pseudo dice [0.819] +2024-11-22 01:04:09.476082: Epoch time: 18.86 s +2024-11-22 01:04:10.400383: +2024-11-22 01:04:10.400602: Epoch 2639 +2024-11-22 01:04:10.400715: Current learning rate: 0.00697 +2024-11-22 01:04:28.252350: train_loss -0.7726 +2024-11-22 01:04:28.252562: val_loss -0.7401 +2024-11-22 01:04:28.252636: Pseudo dice [0.8194] +2024-11-22 01:04:28.252716: Epoch time: 17.85 s +2024-11-22 01:04:29.275414: +2024-11-22 01:04:29.275766: Epoch 2640 +2024-11-22 01:04:29.275882: Current learning rate: 0.00697 +2024-11-22 01:04:47.822968: train_loss -0.7803 +2024-11-22 01:04:47.828390: val_loss -0.7685 +2024-11-22 01:04:47.828509: Pseudo dice [0.8376] +2024-11-22 01:04:47.828596: Epoch time: 18.55 s +2024-11-22 01:04:48.719296: +2024-11-22 01:04:48.719504: Epoch 2641 +2024-11-22 01:04:48.719615: Current learning rate: 0.00697 +2024-11-22 01:05:08.137833: train_loss -0.7758 +2024-11-22 01:05:08.138088: val_loss -0.7221 +2024-11-22 01:05:08.138167: Pseudo dice [0.8054] +2024-11-22 01:05:08.138257: Epoch time: 19.42 s +2024-11-22 01:05:09.032610: +2024-11-22 01:05:09.032845: Epoch 2642 +2024-11-22 01:05:09.032964: Current learning rate: 0.00697 +2024-11-22 01:05:28.042192: train_loss -0.7831 +2024-11-22 01:05:28.042414: val_loss -0.7279 +2024-11-22 01:05:28.042487: Pseudo dice [0.836] +2024-11-22 01:05:28.042564: Epoch time: 19.01 s +2024-11-22 01:05:28.897609: +2024-11-22 01:05:28.897839: Epoch 2643 +2024-11-22 01:05:28.897959: Current learning rate: 0.00697 +2024-11-22 01:05:49.179941: train_loss -0.776 +2024-11-22 01:05:49.180171: val_loss -0.742 +2024-11-22 01:05:49.180247: Pseudo dice [0.8209] +2024-11-22 01:05:49.180328: Epoch time: 20.28 s +2024-11-22 01:05:50.041341: +2024-11-22 01:05:50.041546: Epoch 2644 +2024-11-22 01:05:50.041658: Current learning rate: 0.00697 +2024-11-22 01:06:07.799675: train_loss -0.7732 +2024-11-22 01:06:07.799892: val_loss -0.7431 +2024-11-22 01:06:07.799972: Pseudo dice [0.8082] +2024-11-22 01:06:07.800081: Epoch time: 17.76 s +2024-11-22 01:06:08.647366: +2024-11-22 01:06:08.647823: Epoch 2645 +2024-11-22 01:06:08.648005: Current learning rate: 0.00697 +2024-11-22 01:06:27.149970: train_loss -0.773 +2024-11-22 01:06:27.150197: val_loss -0.7523 +2024-11-22 01:06:27.150274: Pseudo dice [0.822] +2024-11-22 01:06:27.150357: Epoch time: 18.5 s +2024-11-22 01:06:28.397181: +2024-11-22 01:06:28.397414: Epoch 2646 +2024-11-22 01:06:28.397525: Current learning rate: 0.00697 +2024-11-22 01:06:47.260531: train_loss -0.7894 +2024-11-22 01:06:47.261203: val_loss -0.7511 +2024-11-22 01:06:47.261306: Pseudo dice [0.8248] +2024-11-22 01:06:47.261405: Epoch time: 18.86 s +2024-11-22 01:06:48.109741: +2024-11-22 01:06:48.109977: Epoch 2647 +2024-11-22 01:06:48.110099: Current learning rate: 0.00697 +2024-11-22 01:07:06.946397: train_loss -0.7842 +2024-11-22 01:07:06.946622: val_loss -0.7503 +2024-11-22 01:07:06.946706: Pseudo dice [0.8288] +2024-11-22 01:07:06.946787: Epoch time: 18.84 s +2024-11-22 01:07:07.799960: +2024-11-22 01:07:07.800215: Epoch 2648 +2024-11-22 01:07:07.800334: Current learning rate: 0.00696 +2024-11-22 01:07:26.354596: train_loss -0.7748 +2024-11-22 01:07:26.354849: val_loss -0.735 +2024-11-22 01:07:26.354925: Pseudo dice [0.819] +2024-11-22 01:07:26.355016: Epoch time: 18.56 s +2024-11-22 01:07:27.210800: +2024-11-22 01:07:27.211053: Epoch 2649 +2024-11-22 01:07:27.211166: Current learning rate: 0.00696 +2024-11-22 01:07:45.883265: train_loss -0.7856 +2024-11-22 01:07:45.883837: val_loss -0.7372 +2024-11-22 01:07:45.883913: Pseudo dice [0.823] +2024-11-22 01:07:45.883997: Epoch time: 18.67 s +2024-11-22 01:07:46.963125: +2024-11-22 01:07:46.963413: Epoch 2650 +2024-11-22 01:07:46.963527: Current learning rate: 0.00696 +2024-11-22 01:08:06.163127: train_loss -0.7776 +2024-11-22 01:08:06.163341: val_loss -0.7615 +2024-11-22 01:08:06.163415: Pseudo dice [0.8414] +2024-11-22 01:08:06.163492: Epoch time: 19.2 s +2024-11-22 01:08:07.022573: +2024-11-22 01:08:07.022776: Epoch 2651 +2024-11-22 01:08:07.022891: Current learning rate: 0.00696 +2024-11-22 01:08:25.866327: train_loss -0.7794 +2024-11-22 01:08:25.866551: val_loss -0.7543 +2024-11-22 01:08:25.866627: Pseudo dice [0.8304] +2024-11-22 01:08:25.866703: Epoch time: 18.84 s +2024-11-22 01:08:26.720435: +2024-11-22 01:08:26.720642: Epoch 2652 +2024-11-22 01:08:26.720752: Current learning rate: 0.00696 +2024-11-22 01:08:46.212169: train_loss -0.782 +2024-11-22 01:08:46.212411: val_loss -0.7496 +2024-11-22 01:08:46.212491: Pseudo dice [0.8054] +2024-11-22 01:08:46.212578: Epoch time: 19.49 s +2024-11-22 01:08:47.069304: +2024-11-22 01:08:47.069567: Epoch 2653 +2024-11-22 01:08:47.069679: Current learning rate: 0.00696 +2024-11-22 01:09:04.785585: train_loss -0.7853 +2024-11-22 01:09:04.806655: val_loss -0.7304 +2024-11-22 01:09:04.806748: Pseudo dice [0.833] +2024-11-22 01:09:04.806837: Epoch time: 17.72 s +2024-11-22 01:09:05.657424: +2024-11-22 01:09:05.657622: Epoch 2654 +2024-11-22 01:09:05.657733: Current learning rate: 0.00696 +2024-11-22 01:09:24.564750: train_loss -0.7697 +2024-11-22 01:09:24.565170: val_loss -0.7465 +2024-11-22 01:09:24.565266: Pseudo dice [0.8264] +2024-11-22 01:09:24.565347: Epoch time: 18.91 s +2024-11-22 01:09:25.587526: +2024-11-22 01:09:25.587724: Epoch 2655 +2024-11-22 01:09:25.587837: Current learning rate: 0.00696 +2024-11-22 01:09:44.155343: train_loss -0.7681 +2024-11-22 01:09:44.155659: val_loss -0.7263 +2024-11-22 01:09:44.155740: Pseudo dice [0.8185] +2024-11-22 01:09:44.155836: Epoch time: 18.56 s +2024-11-22 01:09:45.102695: +2024-11-22 01:09:45.102900: Epoch 2656 +2024-11-22 01:09:45.103017: Current learning rate: 0.00696 +2024-11-22 01:10:02.986405: train_loss -0.7762 +2024-11-22 01:10:02.986630: val_loss -0.7667 +2024-11-22 01:10:02.986708: Pseudo dice [0.8181] +2024-11-22 01:10:02.986784: Epoch time: 17.88 s +2024-11-22 01:10:03.938689: +2024-11-22 01:10:03.938877: Epoch 2657 +2024-11-22 01:10:03.938999: Current learning rate: 0.00695 +2024-11-22 01:10:23.345439: train_loss -0.7706 +2024-11-22 01:10:23.345926: val_loss -0.7148 +2024-11-22 01:10:23.346034: Pseudo dice [0.8254] +2024-11-22 01:10:23.351331: Epoch time: 19.41 s +2024-11-22 01:10:24.238690: +2024-11-22 01:10:24.238936: Epoch 2658 +2024-11-22 01:10:24.239060: Current learning rate: 0.00695 +2024-11-22 01:10:42.918846: train_loss -0.7876 +2024-11-22 01:10:42.919091: val_loss -0.7481 +2024-11-22 01:10:42.919174: Pseudo dice [0.826] +2024-11-22 01:10:42.919259: Epoch time: 18.68 s +2024-11-22 01:10:43.798166: +2024-11-22 01:10:43.798482: Epoch 2659 +2024-11-22 01:10:43.798642: Current learning rate: 0.00695 +2024-11-22 01:11:01.790673: train_loss -0.7835 +2024-11-22 01:11:01.790928: val_loss -0.7506 +2024-11-22 01:11:01.791019: Pseudo dice [0.8357] +2024-11-22 01:11:01.791101: Epoch time: 17.99 s +2024-11-22 01:11:02.756016: +2024-11-22 01:11:02.756249: Epoch 2660 +2024-11-22 01:11:02.756362: Current learning rate: 0.00695 +2024-11-22 01:11:21.643692: train_loss -0.774 +2024-11-22 01:11:21.646065: val_loss -0.7438 +2024-11-22 01:11:21.646201: Pseudo dice [0.823] +2024-11-22 01:11:21.646279: Epoch time: 18.89 s +2024-11-22 01:11:22.531326: +2024-11-22 01:11:22.531545: Epoch 2661 +2024-11-22 01:11:22.531658: Current learning rate: 0.00695 +2024-11-22 01:11:40.755622: train_loss -0.7718 +2024-11-22 01:11:40.755846: val_loss -0.7326 +2024-11-22 01:11:40.755917: Pseudo dice [0.8239] +2024-11-22 01:11:40.756000: Epoch time: 18.23 s +2024-11-22 01:11:41.628301: +2024-11-22 01:11:41.628714: Epoch 2662 +2024-11-22 01:11:41.628836: Current learning rate: 0.00695 +2024-11-22 01:12:00.654883: train_loss -0.7736 +2024-11-22 01:12:00.655137: val_loss -0.7469 +2024-11-22 01:12:00.655212: Pseudo dice [0.8184] +2024-11-22 01:12:00.655299: Epoch time: 19.03 s +2024-11-22 01:12:01.512626: +2024-11-22 01:12:01.512831: Epoch 2663 +2024-11-22 01:12:01.512941: Current learning rate: 0.00695 +2024-11-22 01:12:20.975344: train_loss -0.7746 +2024-11-22 01:12:20.975562: val_loss -0.7349 +2024-11-22 01:12:20.975641: Pseudo dice [0.812] +2024-11-22 01:12:20.975721: Epoch time: 19.46 s +2024-11-22 01:12:21.822017: +2024-11-22 01:12:21.822234: Epoch 2664 +2024-11-22 01:12:21.822352: Current learning rate: 0.00695 +2024-11-22 01:12:40.263399: train_loss -0.7789 +2024-11-22 01:12:40.263617: val_loss -0.7488 +2024-11-22 01:12:40.268870: Pseudo dice [0.8212] +2024-11-22 01:12:40.269051: Epoch time: 18.44 s +2024-11-22 01:12:41.146245: +2024-11-22 01:12:41.146447: Epoch 2665 +2024-11-22 01:12:41.146559: Current learning rate: 0.00694 +2024-11-22 01:13:00.238763: train_loss -0.7737 +2024-11-22 01:13:00.238985: val_loss -0.7685 +2024-11-22 01:13:00.239068: Pseudo dice [0.8263] +2024-11-22 01:13:00.239150: Epoch time: 19.09 s +2024-11-22 01:13:01.093116: +2024-11-22 01:13:01.093306: Epoch 2666 +2024-11-22 01:13:01.107923: Current learning rate: 0.00694 +2024-11-22 01:13:18.846078: train_loss -0.7759 +2024-11-22 01:13:18.846321: val_loss -0.7335 +2024-11-22 01:13:18.846397: Pseudo dice [0.8304] +2024-11-22 01:13:18.846482: Epoch time: 17.75 s +2024-11-22 01:13:19.699716: +2024-11-22 01:13:19.699925: Epoch 2667 +2024-11-22 01:13:19.700040: Current learning rate: 0.00694 +2024-11-22 01:13:38.564695: train_loss -0.7903 +2024-11-22 01:13:38.564909: val_loss -0.751 +2024-11-22 01:13:38.564981: Pseudo dice [0.8358] +2024-11-22 01:13:38.565064: Epoch time: 18.87 s +2024-11-22 01:13:39.420532: +2024-11-22 01:13:39.420748: Epoch 2668 +2024-11-22 01:13:39.420860: Current learning rate: 0.00694 +2024-11-22 01:13:58.350520: train_loss -0.7871 +2024-11-22 01:13:58.350747: val_loss -0.7359 +2024-11-22 01:13:58.350821: Pseudo dice [0.8081] +2024-11-22 01:13:58.350900: Epoch time: 18.93 s +2024-11-22 01:13:59.605559: +2024-11-22 01:13:59.605862: Epoch 2669 +2024-11-22 01:13:59.605979: Current learning rate: 0.00694 +2024-11-22 01:14:17.530421: train_loss -0.7749 +2024-11-22 01:14:17.535886: val_loss -0.7321 +2024-11-22 01:14:17.536017: Pseudo dice [0.8151] +2024-11-22 01:14:17.536110: Epoch time: 17.93 s +2024-11-22 01:14:18.412680: +2024-11-22 01:14:18.412931: Epoch 2670 +2024-11-22 01:14:18.413049: Current learning rate: 0.00694 +2024-11-22 01:14:37.140579: train_loss -0.7614 +2024-11-22 01:14:37.140850: val_loss -0.7203 +2024-11-22 01:14:37.140926: Pseudo dice [0.8154] +2024-11-22 01:14:37.141016: Epoch time: 18.73 s +2024-11-22 01:14:38.117149: +2024-11-22 01:14:38.117357: Epoch 2671 +2024-11-22 01:14:38.117469: Current learning rate: 0.00694 +2024-11-22 01:14:56.969403: train_loss -0.7744 +2024-11-22 01:14:56.969620: val_loss -0.7393 +2024-11-22 01:14:56.969695: Pseudo dice [0.8217] +2024-11-22 01:14:56.969774: Epoch time: 18.85 s +2024-11-22 01:14:57.822907: +2024-11-22 01:14:57.823122: Epoch 2672 +2024-11-22 01:14:57.823231: Current learning rate: 0.00694 +2024-11-22 01:15:16.408110: train_loss -0.7662 +2024-11-22 01:15:16.408380: val_loss -0.7503 +2024-11-22 01:15:16.408457: Pseudo dice [0.8155] +2024-11-22 01:15:16.408539: Epoch time: 18.59 s +2024-11-22 01:15:17.269115: +2024-11-22 01:15:17.269315: Epoch 2673 +2024-11-22 01:15:17.269447: Current learning rate: 0.00694 +2024-11-22 01:15:35.472827: train_loss -0.7762 +2024-11-22 01:15:35.473073: val_loss -0.7365 +2024-11-22 01:15:35.473146: Pseudo dice [0.836] +2024-11-22 01:15:35.473226: Epoch time: 18.2 s +2024-11-22 01:15:36.337426: +2024-11-22 01:15:36.337705: Epoch 2674 +2024-11-22 01:15:36.337825: Current learning rate: 0.00693 +2024-11-22 01:15:55.481101: train_loss -0.7835 +2024-11-22 01:15:55.482042: val_loss -0.7535 +2024-11-22 01:15:55.482125: Pseudo dice [0.8345] +2024-11-22 01:15:55.482204: Epoch time: 19.14 s +2024-11-22 01:15:56.338726: +2024-11-22 01:15:56.338922: Epoch 2675 +2024-11-22 01:15:56.339047: Current learning rate: 0.00693 +2024-11-22 01:16:14.707108: train_loss -0.7822 +2024-11-22 01:16:14.707319: val_loss -0.7362 +2024-11-22 01:16:14.707390: Pseudo dice [0.835] +2024-11-22 01:16:14.707467: Epoch time: 18.37 s +2024-11-22 01:16:15.560120: +2024-11-22 01:16:15.560323: Epoch 2676 +2024-11-22 01:16:15.560448: Current learning rate: 0.00693 +2024-11-22 01:16:33.726827: train_loss -0.7687 +2024-11-22 01:16:33.727138: val_loss -0.7139 +2024-11-22 01:16:33.727217: Pseudo dice [0.836] +2024-11-22 01:16:33.727303: Epoch time: 18.17 s +2024-11-22 01:16:34.582995: +2024-11-22 01:16:34.583182: Epoch 2677 +2024-11-22 01:16:34.583297: Current learning rate: 0.00693 +2024-11-22 01:16:54.242549: train_loss -0.7735 +2024-11-22 01:16:54.242851: val_loss -0.7576 +2024-11-22 01:16:54.242932: Pseudo dice [0.8339] +2024-11-22 01:16:54.243014: Epoch time: 19.66 s +2024-11-22 01:16:55.104336: +2024-11-22 01:16:55.104562: Epoch 2678 +2024-11-22 01:16:55.104673: Current learning rate: 0.00693 +2024-11-22 01:17:13.314773: train_loss -0.7786 +2024-11-22 01:17:13.315030: val_loss -0.7105 +2024-11-22 01:17:13.315105: Pseudo dice [0.8224] +2024-11-22 01:17:13.316124: Epoch time: 18.21 s +2024-11-22 01:17:14.190452: +2024-11-22 01:17:14.190658: Epoch 2679 +2024-11-22 01:17:14.190770: Current learning rate: 0.00693 +2024-11-22 01:17:32.085635: train_loss -0.7758 +2024-11-22 01:17:32.085887: val_loss -0.7562 +2024-11-22 01:17:32.086136: Pseudo dice [0.822] +2024-11-22 01:17:32.086228: Epoch time: 17.9 s +2024-11-22 01:17:32.941782: +2024-11-22 01:17:32.941979: Epoch 2680 +2024-11-22 01:17:32.942099: Current learning rate: 0.00693 +2024-11-22 01:17:52.127259: train_loss -0.7756 +2024-11-22 01:17:52.127588: val_loss -0.7545 +2024-11-22 01:17:52.127679: Pseudo dice [0.8189] +2024-11-22 01:17:52.127756: Epoch time: 19.19 s +2024-11-22 01:17:53.373915: +2024-11-22 01:17:53.374203: Epoch 2681 +2024-11-22 01:17:53.374318: Current learning rate: 0.00693 +2024-11-22 01:18:11.367026: train_loss -0.7807 +2024-11-22 01:18:11.367261: val_loss -0.7281 +2024-11-22 01:18:11.367338: Pseudo dice [0.8235] +2024-11-22 01:18:11.367418: Epoch time: 17.99 s +2024-11-22 01:18:12.249384: +2024-11-22 01:18:12.249628: Epoch 2682 +2024-11-22 01:18:12.249741: Current learning rate: 0.00692 +2024-11-22 01:18:30.547322: train_loss -0.7735 +2024-11-22 01:18:30.547554: val_loss -0.7339 +2024-11-22 01:18:30.547633: Pseudo dice [0.8191] +2024-11-22 01:18:30.547717: Epoch time: 18.3 s +2024-11-22 01:18:31.431006: +2024-11-22 01:18:31.431225: Epoch 2683 +2024-11-22 01:18:31.431334: Current learning rate: 0.00692 +2024-11-22 01:18:50.383577: train_loss -0.7695 +2024-11-22 01:18:50.383806: val_loss -0.7437 +2024-11-22 01:18:50.383883: Pseudo dice [0.8396] +2024-11-22 01:18:50.383959: Epoch time: 18.95 s +2024-11-22 01:18:51.269806: +2024-11-22 01:18:51.270062: Epoch 2684 +2024-11-22 01:18:51.270177: Current learning rate: 0.00692 +2024-11-22 01:19:10.254540: train_loss -0.7762 +2024-11-22 01:19:10.254752: val_loss -0.7554 +2024-11-22 01:19:10.254841: Pseudo dice [0.8373] +2024-11-22 01:19:10.254920: Epoch time: 18.99 s +2024-11-22 01:19:11.110279: +2024-11-22 01:19:11.110484: Epoch 2685 +2024-11-22 01:19:11.110598: Current learning rate: 0.00692 +2024-11-22 01:19:28.752284: train_loss -0.7659 +2024-11-22 01:19:28.752527: val_loss -0.7315 +2024-11-22 01:19:28.752607: Pseudo dice [0.8313] +2024-11-22 01:19:28.752687: Epoch time: 17.64 s +2024-11-22 01:19:29.605876: +2024-11-22 01:19:29.606152: Epoch 2686 +2024-11-22 01:19:29.606268: Current learning rate: 0.00692 +2024-11-22 01:19:48.562394: train_loss -0.7921 +2024-11-22 01:19:48.562687: val_loss -0.7506 +2024-11-22 01:19:48.562766: Pseudo dice [0.8273] +2024-11-22 01:19:48.562847: Epoch time: 18.96 s +2024-11-22 01:19:49.524251: +2024-11-22 01:19:49.524473: Epoch 2687 +2024-11-22 01:19:49.524589: Current learning rate: 0.00692 +2024-11-22 01:20:07.593788: train_loss -0.7875 +2024-11-22 01:20:07.594033: val_loss -0.7342 +2024-11-22 01:20:07.594111: Pseudo dice [0.8258] +2024-11-22 01:20:07.594194: Epoch time: 18.07 s +2024-11-22 01:20:08.448764: +2024-11-22 01:20:08.448961: Epoch 2688 +2024-11-22 01:20:08.449081: Current learning rate: 0.00692 +2024-11-22 01:20:27.242665: train_loss -0.7648 +2024-11-22 01:20:27.242919: val_loss -0.7432 +2024-11-22 01:20:27.242998: Pseudo dice [0.8159] +2024-11-22 01:20:27.243081: Epoch time: 18.79 s +2024-11-22 01:20:28.092010: +2024-11-22 01:20:28.092256: Epoch 2689 +2024-11-22 01:20:28.092366: Current learning rate: 0.00692 +2024-11-22 01:20:46.011416: train_loss -0.7697 +2024-11-22 01:20:46.011628: val_loss -0.7456 +2024-11-22 01:20:46.011713: Pseudo dice [0.8244] +2024-11-22 01:20:46.011807: Epoch time: 17.92 s +2024-11-22 01:20:46.935347: +2024-11-22 01:20:46.935557: Epoch 2690 +2024-11-22 01:20:46.935671: Current learning rate: 0.00692 +2024-11-22 01:21:05.020444: train_loss -0.7729 +2024-11-22 01:21:05.020689: val_loss -0.7349 +2024-11-22 01:21:05.020766: Pseudo dice [0.8015] +2024-11-22 01:21:05.020846: Epoch time: 18.09 s +2024-11-22 01:21:05.908123: +2024-11-22 01:21:05.908363: Epoch 2691 +2024-11-22 01:21:05.908475: Current learning rate: 0.00691 +2024-11-22 01:21:24.516779: train_loss -0.7787 +2024-11-22 01:21:24.519263: val_loss -0.7651 +2024-11-22 01:21:24.519385: Pseudo dice [0.8278] +2024-11-22 01:21:24.519463: Epoch time: 18.61 s +2024-11-22 01:21:25.443681: +2024-11-22 01:21:25.443894: Epoch 2692 +2024-11-22 01:21:25.444010: Current learning rate: 0.00691 +2024-11-22 01:21:44.236245: train_loss -0.789 +2024-11-22 01:21:44.236463: val_loss -0.7406 +2024-11-22 01:21:44.236537: Pseudo dice [0.8259] +2024-11-22 01:21:44.236612: Epoch time: 18.79 s +2024-11-22 01:21:45.486420: +2024-11-22 01:21:45.486650: Epoch 2693 +2024-11-22 01:21:45.486763: Current learning rate: 0.00691 +2024-11-22 01:22:04.397318: train_loss -0.7841 +2024-11-22 01:22:04.397621: val_loss -0.7257 +2024-11-22 01:22:04.397721: Pseudo dice [0.8184] +2024-11-22 01:22:04.397887: Epoch time: 18.91 s +2024-11-22 01:22:05.256119: +2024-11-22 01:22:05.256333: Epoch 2694 +2024-11-22 01:22:05.256444: Current learning rate: 0.00691 +2024-11-22 01:22:23.919618: train_loss -0.7772 +2024-11-22 01:22:23.919841: val_loss -0.7498 +2024-11-22 01:22:23.919916: Pseudo dice [0.8255] +2024-11-22 01:22:23.920002: Epoch time: 18.66 s +2024-11-22 01:22:24.773540: +2024-11-22 01:22:24.773757: Epoch 2695 +2024-11-22 01:22:24.773873: Current learning rate: 0.00691 +2024-11-22 01:22:43.333044: train_loss -0.7792 +2024-11-22 01:22:43.333269: val_loss -0.7403 +2024-11-22 01:22:43.333343: Pseudo dice [0.8169] +2024-11-22 01:22:43.333422: Epoch time: 18.56 s +2024-11-22 01:22:44.193044: +2024-11-22 01:22:44.193323: Epoch 2696 +2024-11-22 01:22:44.193436: Current learning rate: 0.00691 +2024-11-22 01:23:01.753196: train_loss -0.7724 +2024-11-22 01:23:01.753424: val_loss -0.7282 +2024-11-22 01:23:01.753502: Pseudo dice [0.8301] +2024-11-22 01:23:01.753591: Epoch time: 17.56 s +2024-11-22 01:23:02.607888: +2024-11-22 01:23:02.608092: Epoch 2697 +2024-11-22 01:23:02.608207: Current learning rate: 0.00691 +2024-11-22 01:23:20.785682: train_loss -0.7604 +2024-11-22 01:23:20.785914: val_loss -0.7395 +2024-11-22 01:23:20.785989: Pseudo dice [0.831] +2024-11-22 01:23:20.786072: Epoch time: 18.18 s +2024-11-22 01:23:21.631684: +2024-11-22 01:23:21.631902: Epoch 2698 +2024-11-22 01:23:21.632017: Current learning rate: 0.00691 +2024-11-22 01:23:40.364845: train_loss -0.7604 +2024-11-22 01:23:40.366547: val_loss -0.7266 +2024-11-22 01:23:40.366646: Pseudo dice [0.8041] +2024-11-22 01:23:40.366725: Epoch time: 18.73 s +2024-11-22 01:23:41.231932: +2024-11-22 01:23:41.232144: Epoch 2699 +2024-11-22 01:23:41.232259: Current learning rate: 0.0069 +2024-11-22 01:23:59.990156: train_loss -0.76 +2024-11-22 01:23:59.990385: val_loss -0.7135 +2024-11-22 01:23:59.990459: Pseudo dice [0.8046] +2024-11-22 01:23:59.990535: Epoch time: 18.76 s +2024-11-22 01:24:01.112556: +2024-11-22 01:24:01.112769: Epoch 2700 +2024-11-22 01:24:01.112879: Current learning rate: 0.0069 +2024-11-22 01:24:18.991293: train_loss -0.7602 +2024-11-22 01:24:18.991533: val_loss -0.7232 +2024-11-22 01:24:18.991608: Pseudo dice [0.8231] +2024-11-22 01:24:18.991690: Epoch time: 17.88 s +2024-11-22 01:24:19.846686: +2024-11-22 01:24:19.846880: Epoch 2701 +2024-11-22 01:24:19.847000: Current learning rate: 0.0069 +2024-11-22 01:24:39.002800: train_loss -0.7766 +2024-11-22 01:24:39.003031: val_loss -0.7502 +2024-11-22 01:24:39.003108: Pseudo dice [0.8282] +2024-11-22 01:24:39.003216: Epoch time: 19.16 s +2024-11-22 01:24:39.856177: +2024-11-22 01:24:39.856381: Epoch 2702 +2024-11-22 01:24:39.856493: Current learning rate: 0.0069 +2024-11-22 01:24:59.685966: train_loss -0.7696 +2024-11-22 01:24:59.686188: val_loss -0.7515 +2024-11-22 01:24:59.686259: Pseudo dice [0.8407] +2024-11-22 01:24:59.686334: Epoch time: 19.83 s +2024-11-22 01:25:00.545986: +2024-11-22 01:25:00.546222: Epoch 2703 +2024-11-22 01:25:00.546329: Current learning rate: 0.0069 +2024-11-22 01:25:19.690733: train_loss -0.7643 +2024-11-22 01:25:19.690957: val_loss -0.7398 +2024-11-22 01:25:19.691042: Pseudo dice [0.8212] +2024-11-22 01:25:19.691126: Epoch time: 19.15 s +2024-11-22 01:25:20.549317: +2024-11-22 01:25:20.549518: Epoch 2704 +2024-11-22 01:25:20.549629: Current learning rate: 0.0069 +2024-11-22 01:25:39.422533: train_loss -0.7792 +2024-11-22 01:25:39.423049: val_loss -0.7544 +2024-11-22 01:25:39.423150: Pseudo dice [0.8326] +2024-11-22 01:25:39.423254: Epoch time: 18.87 s +2024-11-22 01:25:40.337870: +2024-11-22 01:25:40.338086: Epoch 2705 +2024-11-22 01:25:40.338200: Current learning rate: 0.0069 +2024-11-22 01:25:58.312602: train_loss -0.7847 +2024-11-22 01:25:58.312836: val_loss -0.7397 +2024-11-22 01:25:58.312912: Pseudo dice [0.8174] +2024-11-22 01:25:58.312999: Epoch time: 17.98 s +2024-11-22 01:25:59.171648: +2024-11-22 01:25:59.171868: Epoch 2706 +2024-11-22 01:25:59.171977: Current learning rate: 0.0069 +2024-11-22 01:26:17.654336: train_loss -0.7785 +2024-11-22 01:26:17.654545: val_loss -0.7401 +2024-11-22 01:26:17.654619: Pseudo dice [0.8298] +2024-11-22 01:26:17.654745: Epoch time: 18.48 s +2024-11-22 01:26:18.516598: +2024-11-22 01:26:18.516834: Epoch 2707 +2024-11-22 01:26:18.516951: Current learning rate: 0.0069 +2024-11-22 01:26:37.578198: train_loss -0.7824 +2024-11-22 01:26:37.578509: val_loss -0.7548 +2024-11-22 01:26:37.578587: Pseudo dice [0.8254] +2024-11-22 01:26:37.578669: Epoch time: 19.06 s +2024-11-22 01:26:38.435089: +2024-11-22 01:26:38.435278: Epoch 2708 +2024-11-22 01:26:38.435393: Current learning rate: 0.00689 +2024-11-22 01:26:57.738012: train_loss -0.7837 +2024-11-22 01:26:57.738234: val_loss -0.7618 +2024-11-22 01:26:57.738315: Pseudo dice [0.8446] +2024-11-22 01:26:57.738395: Epoch time: 19.3 s +2024-11-22 01:26:58.601670: +2024-11-22 01:26:58.601920: Epoch 2709 +2024-11-22 01:26:58.602039: Current learning rate: 0.00689 +2024-11-22 01:27:17.971214: train_loss -0.7861 +2024-11-22 01:27:17.971432: val_loss -0.754 +2024-11-22 01:27:17.971512: Pseudo dice [0.8386] +2024-11-22 01:27:17.971592: Epoch time: 19.37 s +2024-11-22 01:27:18.829716: +2024-11-22 01:27:18.829983: Epoch 2710 +2024-11-22 01:27:18.830108: Current learning rate: 0.00689 +2024-11-22 01:27:38.487907: train_loss -0.7838 +2024-11-22 01:27:38.488130: val_loss -0.7687 +2024-11-22 01:27:38.488209: Pseudo dice [0.842] +2024-11-22 01:27:38.488302: Epoch time: 19.66 s +2024-11-22 01:27:39.347513: +2024-11-22 01:27:39.347736: Epoch 2711 +2024-11-22 01:27:39.347844: Current learning rate: 0.00689 +2024-11-22 01:27:58.272721: train_loss -0.784 +2024-11-22 01:27:58.272960: val_loss -0.7442 +2024-11-22 01:27:58.273041: Pseudo dice [0.8315] +2024-11-22 01:27:58.273122: Epoch time: 18.93 s +2024-11-22 01:27:59.147060: +2024-11-22 01:27:59.147262: Epoch 2712 +2024-11-22 01:27:59.147373: Current learning rate: 0.00689 +2024-11-22 01:28:17.417006: train_loss -0.7872 +2024-11-22 01:28:17.417217: val_loss -0.7614 +2024-11-22 01:28:17.417291: Pseudo dice [0.827] +2024-11-22 01:28:17.417369: Epoch time: 18.27 s +2024-11-22 01:28:18.269815: +2024-11-22 01:28:18.270037: Epoch 2713 +2024-11-22 01:28:18.270156: Current learning rate: 0.00689 +2024-11-22 01:28:37.860523: train_loss -0.7881 +2024-11-22 01:28:37.861052: val_loss -0.7401 +2024-11-22 01:28:37.861128: Pseudo dice [0.803] +2024-11-22 01:28:37.861202: Epoch time: 19.59 s +2024-11-22 01:28:38.704201: +2024-11-22 01:28:38.704398: Epoch 2714 +2024-11-22 01:28:38.704508: Current learning rate: 0.00689 +2024-11-22 01:28:57.021530: train_loss -0.7773 +2024-11-22 01:28:57.021786: val_loss -0.7713 +2024-11-22 01:28:57.021868: Pseudo dice [0.8351] +2024-11-22 01:28:57.021953: Epoch time: 18.32 s +2024-11-22 01:28:57.982876: +2024-11-22 01:28:57.983099: Epoch 2715 +2024-11-22 01:28:57.983212: Current learning rate: 0.00689 +2024-11-22 01:29:18.108371: train_loss -0.7715 +2024-11-22 01:29:18.108587: val_loss -0.732 +2024-11-22 01:29:18.108662: Pseudo dice [0.8042] +2024-11-22 01:29:18.108742: Epoch time: 20.13 s +2024-11-22 01:29:19.327130: +2024-11-22 01:29:19.327417: Epoch 2716 +2024-11-22 01:29:19.327533: Current learning rate: 0.00688 +2024-11-22 01:29:38.189988: train_loss -0.7651 +2024-11-22 01:29:38.190212: val_loss -0.7424 +2024-11-22 01:29:38.190292: Pseudo dice [0.8272] +2024-11-22 01:29:38.190373: Epoch time: 18.86 s +2024-11-22 01:29:39.063091: +2024-11-22 01:29:39.063304: Epoch 2717 +2024-11-22 01:29:39.063421: Current learning rate: 0.00688 +2024-11-22 01:29:58.867760: train_loss -0.7699 +2024-11-22 01:29:58.868015: val_loss -0.7489 +2024-11-22 01:29:58.868096: Pseudo dice [0.8369] +2024-11-22 01:29:58.868186: Epoch time: 19.81 s +2024-11-22 01:29:59.723640: +2024-11-22 01:29:59.723892: Epoch 2718 +2024-11-22 01:29:59.724012: Current learning rate: 0.00688 +2024-11-22 01:30:18.558576: train_loss -0.7786 +2024-11-22 01:30:18.558810: val_loss -0.7536 +2024-11-22 01:30:18.558886: Pseudo dice [0.8503] +2024-11-22 01:30:18.558965: Epoch time: 18.84 s +2024-11-22 01:30:19.431085: +2024-11-22 01:30:19.431310: Epoch 2719 +2024-11-22 01:30:19.431422: Current learning rate: 0.00688 +2024-11-22 01:30:39.127046: train_loss -0.7747 +2024-11-22 01:30:39.127296: val_loss -0.7389 +2024-11-22 01:30:39.127372: Pseudo dice [0.8454] +2024-11-22 01:30:39.127517: Epoch time: 19.7 s +2024-11-22 01:30:39.127581: Yayy! New best EMA pseudo Dice: 0.8304 +2024-11-22 01:30:40.216873: +2024-11-22 01:30:40.217143: Epoch 2720 +2024-11-22 01:30:40.217268: Current learning rate: 0.00688 +2024-11-22 01:30:58.480759: train_loss -0.7804 +2024-11-22 01:30:58.480972: val_loss -0.727 +2024-11-22 01:30:58.481051: Pseudo dice [0.8163] +2024-11-22 01:30:58.481128: Epoch time: 18.26 s +2024-11-22 01:30:59.503800: +2024-11-22 01:30:59.504049: Epoch 2721 +2024-11-22 01:30:59.504165: Current learning rate: 0.00688 +2024-11-22 01:31:18.105717: train_loss -0.79 +2024-11-22 01:31:18.105965: val_loss -0.7297 +2024-11-22 01:31:18.106050: Pseudo dice [0.7976] +2024-11-22 01:31:18.106137: Epoch time: 18.6 s +2024-11-22 01:31:18.962658: +2024-11-22 01:31:18.962852: Epoch 2722 +2024-11-22 01:31:18.962960: Current learning rate: 0.00688 +2024-11-22 01:31:37.086425: train_loss -0.7737 +2024-11-22 01:31:37.086637: val_loss -0.7271 +2024-11-22 01:31:37.086712: Pseudo dice [0.8029] +2024-11-22 01:31:37.086789: Epoch time: 18.12 s +2024-11-22 01:31:37.940979: +2024-11-22 01:31:37.941202: Epoch 2723 +2024-11-22 01:31:37.941314: Current learning rate: 0.00688 +2024-11-22 01:31:57.310558: train_loss -0.7572 +2024-11-22 01:31:57.310776: val_loss -0.732 +2024-11-22 01:31:57.310855: Pseudo dice [0.8233] +2024-11-22 01:31:57.310934: Epoch time: 19.37 s +2024-11-22 01:31:58.172008: +2024-11-22 01:31:58.172194: Epoch 2724 +2024-11-22 01:31:58.172303: Current learning rate: 0.00688 +2024-11-22 01:32:16.914629: train_loss -0.7532 +2024-11-22 01:32:16.914846: val_loss -0.7192 +2024-11-22 01:32:16.914932: Pseudo dice [0.817] +2024-11-22 01:32:16.915025: Epoch time: 18.74 s +2024-11-22 01:32:17.773941: +2024-11-22 01:32:17.774172: Epoch 2725 +2024-11-22 01:32:17.774290: Current learning rate: 0.00687 +2024-11-22 01:32:36.837798: train_loss -0.7571 +2024-11-22 01:32:36.838036: val_loss -0.7288 +2024-11-22 01:32:36.838115: Pseudo dice [0.8233] +2024-11-22 01:32:36.838196: Epoch time: 19.06 s +2024-11-22 01:32:37.735541: +2024-11-22 01:32:37.735742: Epoch 2726 +2024-11-22 01:32:37.735857: Current learning rate: 0.00687 +2024-11-22 01:32:56.235569: train_loss -0.7694 +2024-11-22 01:32:56.235835: val_loss -0.7422 +2024-11-22 01:32:56.235914: Pseudo dice [0.8194] +2024-11-22 01:32:56.236006: Epoch time: 18.5 s +2024-11-22 01:32:57.088987: +2024-11-22 01:32:57.089194: Epoch 2727 +2024-11-22 01:32:57.089343: Current learning rate: 0.00687 +2024-11-22 01:33:15.630357: train_loss -0.7662 +2024-11-22 01:33:15.630930: val_loss -0.7345 +2024-11-22 01:33:15.631089: Pseudo dice [0.8157] +2024-11-22 01:33:15.631174: Epoch time: 18.54 s +2024-11-22 01:33:16.489129: +2024-11-22 01:33:16.489365: Epoch 2728 +2024-11-22 01:33:16.489519: Current learning rate: 0.00687 +2024-11-22 01:33:35.448684: train_loss -0.7651 +2024-11-22 01:33:35.448902: val_loss -0.7264 +2024-11-22 01:33:35.448976: Pseudo dice [0.8141] +2024-11-22 01:33:35.449059: Epoch time: 18.96 s +2024-11-22 01:33:36.301054: +2024-11-22 01:33:36.301311: Epoch 2729 +2024-11-22 01:33:36.301426: Current learning rate: 0.00687 +2024-11-22 01:33:55.547529: train_loss -0.7687 +2024-11-22 01:33:55.547761: val_loss -0.7406 +2024-11-22 01:33:55.547838: Pseudo dice [0.8065] +2024-11-22 01:33:55.547921: Epoch time: 19.25 s +2024-11-22 01:33:56.402515: +2024-11-22 01:33:56.402782: Epoch 2730 +2024-11-22 01:33:56.402902: Current learning rate: 0.00687 +2024-11-22 01:34:14.713509: train_loss -0.7793 +2024-11-22 01:34:14.713738: val_loss -0.7453 +2024-11-22 01:34:14.713876: Pseudo dice [0.8166] +2024-11-22 01:34:14.713963: Epoch time: 18.31 s +2024-11-22 01:34:15.569538: +2024-11-22 01:34:15.569744: Epoch 2731 +2024-11-22 01:34:15.569860: Current learning rate: 0.00687 +2024-11-22 01:34:33.876656: train_loss -0.7893 +2024-11-22 01:34:33.876901: val_loss -0.7537 +2024-11-22 01:34:33.876977: Pseudo dice [0.8322] +2024-11-22 01:34:33.877067: Epoch time: 18.31 s +2024-11-22 01:34:34.733495: +2024-11-22 01:34:34.733950: Epoch 2732 +2024-11-22 01:34:34.734080: Current learning rate: 0.00687 +2024-11-22 01:34:53.068261: train_loss -0.7784 +2024-11-22 01:34:53.068475: val_loss -0.7375 +2024-11-22 01:34:53.068549: Pseudo dice [0.8122] +2024-11-22 01:34:53.068625: Epoch time: 18.34 s +2024-11-22 01:34:54.015730: +2024-11-22 01:34:54.015925: Epoch 2733 +2024-11-22 01:34:54.016042: Current learning rate: 0.00686 +2024-11-22 01:35:12.728575: train_loss -0.7805 +2024-11-22 01:35:12.728775: val_loss -0.7087 +2024-11-22 01:35:12.728862: Pseudo dice [0.8099] +2024-11-22 01:35:12.728945: Epoch time: 18.71 s +2024-11-22 01:35:13.583305: +2024-11-22 01:35:13.583501: Epoch 2734 +2024-11-22 01:35:13.583612: Current learning rate: 0.00686 +2024-11-22 01:35:32.953187: train_loss -0.7741 +2024-11-22 01:35:32.953395: val_loss -0.7244 +2024-11-22 01:35:32.953469: Pseudo dice [0.8181] +2024-11-22 01:35:32.953547: Epoch time: 19.37 s +2024-11-22 01:35:33.817830: +2024-11-22 01:35:33.818060: Epoch 2735 +2024-11-22 01:35:33.818180: Current learning rate: 0.00686 +2024-11-22 01:35:53.803362: train_loss -0.7778 +2024-11-22 01:35:53.803608: val_loss -0.7767 +2024-11-22 01:35:53.803684: Pseudo dice [0.8373] +2024-11-22 01:35:53.803803: Epoch time: 19.99 s +2024-11-22 01:35:54.655658: +2024-11-22 01:35:54.655909: Epoch 2736 +2024-11-22 01:35:54.656029: Current learning rate: 0.00686 +2024-11-22 01:36:12.572527: train_loss -0.7827 +2024-11-22 01:36:12.572742: val_loss -0.7434 +2024-11-22 01:36:12.572815: Pseudo dice [0.8279] +2024-11-22 01:36:12.572890: Epoch time: 17.92 s +2024-11-22 01:36:13.467461: +2024-11-22 01:36:13.467650: Epoch 2737 +2024-11-22 01:36:13.467762: Current learning rate: 0.00686 +2024-11-22 01:36:32.167137: train_loss -0.7917 +2024-11-22 01:36:32.167347: val_loss -0.7591 +2024-11-22 01:36:32.167423: Pseudo dice [0.8384] +2024-11-22 01:36:32.167500: Epoch time: 18.7 s +2024-11-22 01:36:33.030044: +2024-11-22 01:36:33.030243: Epoch 2738 +2024-11-22 01:36:33.030358: Current learning rate: 0.00686 +2024-11-22 01:36:51.753455: train_loss -0.7905 +2024-11-22 01:36:51.753704: val_loss -0.7673 +2024-11-22 01:36:51.753781: Pseudo dice [0.839] +2024-11-22 01:36:51.753866: Epoch time: 18.72 s +2024-11-22 01:36:53.000114: +2024-11-22 01:36:53.000367: Epoch 2739 +2024-11-22 01:36:53.000479: Current learning rate: 0.00686 +2024-11-22 01:37:10.919060: train_loss -0.7867 +2024-11-22 01:37:10.919578: val_loss -0.7457 +2024-11-22 01:37:10.919674: Pseudo dice [0.8447] +2024-11-22 01:37:10.919755: Epoch time: 17.92 s +2024-11-22 01:37:11.898436: +2024-11-22 01:37:11.898646: Epoch 2740 +2024-11-22 01:37:11.898763: Current learning rate: 0.00686 +2024-11-22 01:37:29.845235: train_loss -0.7865 +2024-11-22 01:37:29.845451: val_loss -0.7314 +2024-11-22 01:37:29.845529: Pseudo dice [0.8102] +2024-11-22 01:37:29.845607: Epoch time: 17.95 s +2024-11-22 01:37:30.723025: +2024-11-22 01:37:30.723236: Epoch 2741 +2024-11-22 01:37:30.723350: Current learning rate: 0.00686 +2024-11-22 01:37:49.182470: train_loss -0.7766 +2024-11-22 01:37:49.182682: val_loss -0.7541 +2024-11-22 01:37:49.182755: Pseudo dice [0.8417] +2024-11-22 01:37:49.182829: Epoch time: 18.46 s +2024-11-22 01:37:50.043285: +2024-11-22 01:37:50.043540: Epoch 2742 +2024-11-22 01:37:50.043698: Current learning rate: 0.00685 +2024-11-22 01:38:09.098038: train_loss -0.7724 +2024-11-22 01:38:09.098279: val_loss -0.7199 +2024-11-22 01:38:09.098356: Pseudo dice [0.8077] +2024-11-22 01:38:09.098439: Epoch time: 19.06 s +2024-11-22 01:38:09.957504: +2024-11-22 01:38:09.957840: Epoch 2743 +2024-11-22 01:38:09.957954: Current learning rate: 0.00685 +2024-11-22 01:38:28.415933: train_loss -0.7692 +2024-11-22 01:38:28.416166: val_loss -0.7133 +2024-11-22 01:38:28.416240: Pseudo dice [0.8237] +2024-11-22 01:38:28.416317: Epoch time: 18.46 s +2024-11-22 01:38:29.276038: +2024-11-22 01:38:29.276242: Epoch 2744 +2024-11-22 01:38:29.276359: Current learning rate: 0.00685 +2024-11-22 01:38:47.713607: train_loss -0.767 +2024-11-22 01:38:47.713817: val_loss -0.7348 +2024-11-22 01:38:47.713888: Pseudo dice [0.8061] +2024-11-22 01:38:47.713964: Epoch time: 18.44 s +2024-11-22 01:38:48.564042: +2024-11-22 01:38:48.564276: Epoch 2745 +2024-11-22 01:38:48.564390: Current learning rate: 0.00685 +2024-11-22 01:39:07.775834: train_loss -0.7538 +2024-11-22 01:39:07.776070: val_loss -0.7214 +2024-11-22 01:39:07.776147: Pseudo dice [0.795] +2024-11-22 01:39:07.776232: Epoch time: 19.21 s +2024-11-22 01:39:08.639797: +2024-11-22 01:39:08.640024: Epoch 2746 +2024-11-22 01:39:08.640133: Current learning rate: 0.00685 +2024-11-22 01:39:26.713700: train_loss -0.7668 +2024-11-22 01:39:26.713922: val_loss -0.7492 +2024-11-22 01:39:26.714687: Pseudo dice [0.8217] +2024-11-22 01:39:26.714871: Epoch time: 18.07 s +2024-11-22 01:39:27.588558: +2024-11-22 01:39:27.588825: Epoch 2747 +2024-11-22 01:39:27.588934: Current learning rate: 0.00685 +2024-11-22 01:39:45.398150: train_loss -0.7686 +2024-11-22 01:39:45.398379: val_loss -0.7299 +2024-11-22 01:39:45.398452: Pseudo dice [0.8359] +2024-11-22 01:39:45.398527: Epoch time: 17.81 s +2024-11-22 01:39:46.251250: +2024-11-22 01:39:46.251454: Epoch 2748 +2024-11-22 01:39:46.251567: Current learning rate: 0.00685 +2024-11-22 01:40:05.171105: train_loss -0.7784 +2024-11-22 01:40:05.171308: val_loss -0.7539 +2024-11-22 01:40:05.171383: Pseudo dice [0.8217] +2024-11-22 01:40:05.171460: Epoch time: 18.92 s +2024-11-22 01:40:06.028610: +2024-11-22 01:40:06.028809: Epoch 2749 +2024-11-22 01:40:06.028921: Current learning rate: 0.00685 +2024-11-22 01:40:25.436131: train_loss -0.7734 +2024-11-22 01:40:25.436418: val_loss -0.7285 +2024-11-22 01:40:25.436498: Pseudo dice [0.7888] +2024-11-22 01:40:25.436582: Epoch time: 19.41 s +2024-11-22 01:40:26.521623: +2024-11-22 01:40:26.521825: Epoch 2750 +2024-11-22 01:40:26.521934: Current learning rate: 0.00684 +2024-11-22 01:40:45.474957: train_loss -0.7758 +2024-11-22 01:40:45.475469: val_loss -0.7411 +2024-11-22 01:40:45.475568: Pseudo dice [0.8214] +2024-11-22 01:40:45.475648: Epoch time: 18.95 s +2024-11-22 01:40:46.485895: +2024-11-22 01:40:46.486219: Epoch 2751 +2024-11-22 01:40:46.486331: Current learning rate: 0.00684 +2024-11-22 01:41:05.547731: train_loss -0.7749 +2024-11-22 01:41:05.547940: val_loss -0.7493 +2024-11-22 01:41:05.548026: Pseudo dice [0.8288] +2024-11-22 01:41:05.548108: Epoch time: 19.06 s +2024-11-22 01:41:06.514411: +2024-11-22 01:41:06.514616: Epoch 2752 +2024-11-22 01:41:06.514731: Current learning rate: 0.00684 +2024-11-22 01:41:25.571871: train_loss -0.7671 +2024-11-22 01:41:25.577301: val_loss -0.73 +2024-11-22 01:41:25.577412: Pseudo dice [0.8251] +2024-11-22 01:41:25.577497: Epoch time: 19.06 s +2024-11-22 01:41:26.490617: +2024-11-22 01:41:26.490835: Epoch 2753 +2024-11-22 01:41:26.490947: Current learning rate: 0.00684 +2024-11-22 01:41:45.501216: train_loss -0.779 +2024-11-22 01:41:45.501488: val_loss -0.7452 +2024-11-22 01:41:45.501562: Pseudo dice [0.8453] +2024-11-22 01:41:45.501638: Epoch time: 19.01 s +2024-11-22 01:41:46.353985: +2024-11-22 01:41:46.354238: Epoch 2754 +2024-11-22 01:41:46.354359: Current learning rate: 0.00684 +2024-11-22 01:42:05.531124: train_loss -0.7669 +2024-11-22 01:42:05.531348: val_loss -0.7286 +2024-11-22 01:42:05.531426: Pseudo dice [0.8131] +2024-11-22 01:42:05.531505: Epoch time: 19.18 s +2024-11-22 01:42:06.432593: +2024-11-22 01:42:06.432803: Epoch 2755 +2024-11-22 01:42:06.432915: Current learning rate: 0.00684 +2024-11-22 01:42:25.587499: train_loss -0.781 +2024-11-22 01:42:25.587721: val_loss -0.7422 +2024-11-22 01:42:25.587802: Pseudo dice [0.8242] +2024-11-22 01:42:25.587880: Epoch time: 19.16 s +2024-11-22 01:42:26.446527: +2024-11-22 01:42:26.446755: Epoch 2756 +2024-11-22 01:42:26.446868: Current learning rate: 0.00684 +2024-11-22 01:42:44.357144: train_loss -0.767 +2024-11-22 01:42:44.357393: val_loss -0.7322 +2024-11-22 01:42:44.357471: Pseudo dice [0.8172] +2024-11-22 01:42:44.357555: Epoch time: 17.91 s +2024-11-22 01:42:45.211575: +2024-11-22 01:42:45.211775: Epoch 2757 +2024-11-22 01:42:45.211890: Current learning rate: 0.00684 +2024-11-22 01:43:03.843947: train_loss -0.7664 +2024-11-22 01:43:03.844159: val_loss -0.7365 +2024-11-22 01:43:03.844230: Pseudo dice [0.8188] +2024-11-22 01:43:03.844303: Epoch time: 18.63 s +2024-11-22 01:43:04.712662: +2024-11-22 01:43:04.712883: Epoch 2758 +2024-11-22 01:43:04.713004: Current learning rate: 0.00684 +2024-11-22 01:43:23.969402: train_loss -0.7781 +2024-11-22 01:43:23.969666: val_loss -0.7404 +2024-11-22 01:43:23.969745: Pseudo dice [0.8308] +2024-11-22 01:43:23.969821: Epoch time: 19.26 s +2024-11-22 01:43:24.827261: +2024-11-22 01:43:24.827497: Epoch 2759 +2024-11-22 01:43:24.827646: Current learning rate: 0.00683 +2024-11-22 01:43:44.580697: train_loss -0.7729 +2024-11-22 01:43:44.580933: val_loss -0.7533 +2024-11-22 01:43:44.581010: Pseudo dice [0.833] +2024-11-22 01:43:44.581096: Epoch time: 19.75 s +2024-11-22 01:43:45.471840: +2024-11-22 01:43:45.472079: Epoch 2760 +2024-11-22 01:43:45.472193: Current learning rate: 0.00683 +2024-11-22 01:44:04.219106: train_loss -0.7727 +2024-11-22 01:44:04.219321: val_loss -0.7464 +2024-11-22 01:44:04.219397: Pseudo dice [0.8349] +2024-11-22 01:44:04.221673: Epoch time: 18.75 s +2024-11-22 01:44:05.101242: +2024-11-22 01:44:05.101454: Epoch 2761 +2024-11-22 01:44:05.101570: Current learning rate: 0.00683 +2024-11-22 01:44:23.804412: train_loss -0.7732 +2024-11-22 01:44:23.804631: val_loss -0.7573 +2024-11-22 01:44:23.804706: Pseudo dice [0.8421] +2024-11-22 01:44:23.804782: Epoch time: 18.7 s +2024-11-22 01:44:25.016377: +2024-11-22 01:44:25.016663: Epoch 2762 +2024-11-22 01:44:25.016774: Current learning rate: 0.00683 +2024-11-22 01:44:44.260247: train_loss -0.7617 +2024-11-22 01:44:44.260506: val_loss -0.7447 +2024-11-22 01:44:44.260582: Pseudo dice [0.8008] +2024-11-22 01:44:44.260670: Epoch time: 19.24 s +2024-11-22 01:44:45.134632: +2024-11-22 01:44:45.134845: Epoch 2763 +2024-11-22 01:44:45.134962: Current learning rate: 0.00683 +2024-11-22 01:45:02.200273: train_loss -0.7487 +2024-11-22 01:45:02.200543: val_loss -0.709 +2024-11-22 01:45:02.200623: Pseudo dice [0.8086] +2024-11-22 01:45:02.200704: Epoch time: 17.07 s +2024-11-22 01:45:03.053317: +2024-11-22 01:45:03.053522: Epoch 2764 +2024-11-22 01:45:03.053636: Current learning rate: 0.00683 +2024-11-22 01:45:21.437132: train_loss -0.757 +2024-11-22 01:45:21.437344: val_loss -0.7057 +2024-11-22 01:45:21.437418: Pseudo dice [0.826] +2024-11-22 01:45:21.437497: Epoch time: 18.38 s +2024-11-22 01:45:22.326573: +2024-11-22 01:45:22.326780: Epoch 2765 +2024-11-22 01:45:22.326896: Current learning rate: 0.00683 +2024-11-22 01:45:41.238277: train_loss -0.752 +2024-11-22 01:45:41.238552: val_loss -0.7235 +2024-11-22 01:45:41.238627: Pseudo dice [0.8168] +2024-11-22 01:45:41.238716: Epoch time: 18.91 s +2024-11-22 01:45:42.158448: +2024-11-22 01:45:42.158701: Epoch 2766 +2024-11-22 01:45:42.158817: Current learning rate: 0.00683 +2024-11-22 01:46:00.986429: train_loss -0.7685 +2024-11-22 01:46:00.986673: val_loss -0.7531 +2024-11-22 01:46:00.986747: Pseudo dice [0.832] +2024-11-22 01:46:00.986824: Epoch time: 18.83 s +2024-11-22 01:46:01.844058: +2024-11-22 01:46:01.844269: Epoch 2767 +2024-11-22 01:46:01.844382: Current learning rate: 0.00682 +2024-11-22 01:46:20.222087: train_loss -0.7717 +2024-11-22 01:46:20.222301: val_loss -0.7365 +2024-11-22 01:46:20.222375: Pseudo dice [0.8294] +2024-11-22 01:46:20.222451: Epoch time: 18.38 s +2024-11-22 01:46:21.083011: +2024-11-22 01:46:21.083272: Epoch 2768 +2024-11-22 01:46:21.083384: Current learning rate: 0.00682 +2024-11-22 01:46:39.339368: train_loss -0.7788 +2024-11-22 01:46:39.339581: val_loss -0.7055 +2024-11-22 01:46:39.339656: Pseudo dice [0.8087] +2024-11-22 01:46:39.339736: Epoch time: 18.26 s +2024-11-22 01:46:40.221110: +2024-11-22 01:46:40.221318: Epoch 2769 +2024-11-22 01:46:40.221427: Current learning rate: 0.00682 +2024-11-22 01:46:59.370295: train_loss -0.779 +2024-11-22 01:46:59.370521: val_loss -0.745 +2024-11-22 01:46:59.370603: Pseudo dice [0.8169] +2024-11-22 01:46:59.370688: Epoch time: 19.15 s +2024-11-22 01:47:00.233413: +2024-11-22 01:47:00.233620: Epoch 2770 +2024-11-22 01:47:00.233735: Current learning rate: 0.00682 +2024-11-22 01:47:17.266854: train_loss -0.7753 +2024-11-22 01:47:17.267103: val_loss -0.7353 +2024-11-22 01:47:17.267178: Pseudo dice [0.8144] +2024-11-22 01:47:17.267261: Epoch time: 17.03 s +2024-11-22 01:47:18.124396: +2024-11-22 01:47:18.124582: Epoch 2771 +2024-11-22 01:47:18.124693: Current learning rate: 0.00682 +2024-11-22 01:47:35.954390: train_loss -0.772 +2024-11-22 01:47:35.954606: val_loss -0.7324 +2024-11-22 01:47:35.954680: Pseudo dice [0.8216] +2024-11-22 01:47:35.954758: Epoch time: 17.83 s +2024-11-22 01:47:36.809366: +2024-11-22 01:47:36.809600: Epoch 2772 +2024-11-22 01:47:36.809717: Current learning rate: 0.00682 +2024-11-22 01:47:55.286385: train_loss -0.77 +2024-11-22 01:47:55.286598: val_loss -0.7381 +2024-11-22 01:47:55.286674: Pseudo dice [0.8239] +2024-11-22 01:47:55.286757: Epoch time: 18.48 s +2024-11-22 01:47:56.144253: +2024-11-22 01:47:56.144484: Epoch 2773 +2024-11-22 01:47:56.144602: Current learning rate: 0.00682 +2024-11-22 01:48:14.038872: train_loss -0.7753 +2024-11-22 01:48:14.039116: val_loss -0.7436 +2024-11-22 01:48:14.039190: Pseudo dice [0.826] +2024-11-22 01:48:14.039274: Epoch time: 17.9 s +2024-11-22 01:48:15.305399: +2024-11-22 01:48:15.305633: Epoch 2774 +2024-11-22 01:48:15.305746: Current learning rate: 0.00682 +2024-11-22 01:48:33.571417: train_loss -0.7805 +2024-11-22 01:48:33.571642: val_loss -0.7016 +2024-11-22 01:48:33.571720: Pseudo dice [0.8073] +2024-11-22 01:48:33.571796: Epoch time: 18.27 s +2024-11-22 01:48:34.420358: +2024-11-22 01:48:34.420561: Epoch 2775 +2024-11-22 01:48:34.420678: Current learning rate: 0.00682 +2024-11-22 01:48:53.286945: train_loss -0.7775 +2024-11-22 01:48:53.287204: val_loss -0.7162 +2024-11-22 01:48:53.287284: Pseudo dice [0.7999] +2024-11-22 01:48:53.287360: Epoch time: 18.87 s +2024-11-22 01:48:54.293779: +2024-11-22 01:48:54.294014: Epoch 2776 +2024-11-22 01:48:54.294128: Current learning rate: 0.00681 +2024-11-22 01:49:13.494235: train_loss -0.785 +2024-11-22 01:49:13.494471: val_loss -0.754 +2024-11-22 01:49:13.494544: Pseudo dice [0.8186] +2024-11-22 01:49:13.494628: Epoch time: 19.2 s +2024-11-22 01:49:14.357826: +2024-11-22 01:49:14.358042: Epoch 2777 +2024-11-22 01:49:14.358154: Current learning rate: 0.00681 +2024-11-22 01:49:34.360415: train_loss -0.7679 +2024-11-22 01:49:34.360634: val_loss -0.7214 +2024-11-22 01:49:34.360712: Pseudo dice [0.838] +2024-11-22 01:49:34.360792: Epoch time: 20.0 s +2024-11-22 01:49:35.223511: +2024-11-22 01:49:35.223735: Epoch 2778 +2024-11-22 01:49:35.223844: Current learning rate: 0.00681 +2024-11-22 01:49:54.185685: train_loss -0.7493 +2024-11-22 01:49:54.185897: val_loss -0.7284 +2024-11-22 01:49:54.185971: Pseudo dice [0.806] +2024-11-22 01:49:54.186070: Epoch time: 18.96 s +2024-11-22 01:49:55.038997: +2024-11-22 01:49:55.039224: Epoch 2779 +2024-11-22 01:49:55.039339: Current learning rate: 0.00681 +2024-11-22 01:50:12.702834: train_loss -0.7585 +2024-11-22 01:50:12.703069: val_loss -0.7331 +2024-11-22 01:50:12.703143: Pseudo dice [0.8259] +2024-11-22 01:50:12.703219: Epoch time: 17.66 s +2024-11-22 01:50:13.556462: +2024-11-22 01:50:13.556643: Epoch 2780 +2024-11-22 01:50:13.556758: Current learning rate: 0.00681 +2024-11-22 01:50:32.391251: train_loss -0.7788 +2024-11-22 01:50:32.391546: val_loss -0.7215 +2024-11-22 01:50:32.391629: Pseudo dice [0.8296] +2024-11-22 01:50:32.391712: Epoch time: 18.84 s +2024-11-22 01:50:33.266608: +2024-11-22 01:50:33.266815: Epoch 2781 +2024-11-22 01:50:33.266929: Current learning rate: 0.00681 +2024-11-22 01:50:50.963505: train_loss -0.7657 +2024-11-22 01:50:50.963727: val_loss -0.733 +2024-11-22 01:50:50.963804: Pseudo dice [0.8176] +2024-11-22 01:50:50.963887: Epoch time: 17.7 s +2024-11-22 01:50:51.868898: +2024-11-22 01:50:51.869106: Epoch 2782 +2024-11-22 01:50:51.869217: Current learning rate: 0.00681 +2024-11-22 01:51:10.624366: train_loss -0.7717 +2024-11-22 01:51:10.628232: val_loss -0.7203 +2024-11-22 01:51:10.628358: Pseudo dice [0.8256] +2024-11-22 01:51:10.628440: Epoch time: 18.76 s +2024-11-22 01:51:11.527780: +2024-11-22 01:51:11.527997: Epoch 2783 +2024-11-22 01:51:11.528114: Current learning rate: 0.00681 +2024-11-22 01:51:29.973828: train_loss -0.7767 +2024-11-22 01:51:29.974049: val_loss -0.7278 +2024-11-22 01:51:29.974125: Pseudo dice [0.8189] +2024-11-22 01:51:29.974205: Epoch time: 18.45 s +2024-11-22 01:51:30.915427: +2024-11-22 01:51:30.915626: Epoch 2784 +2024-11-22 01:51:30.915739: Current learning rate: 0.0068 +2024-11-22 01:51:49.568928: train_loss -0.7729 +2024-11-22 01:51:49.569259: val_loss -0.7698 +2024-11-22 01:51:49.569339: Pseudo dice [0.8452] +2024-11-22 01:51:49.569421: Epoch time: 18.65 s +2024-11-22 01:51:50.428972: +2024-11-22 01:51:50.429168: Epoch 2785 +2024-11-22 01:51:50.429282: Current learning rate: 0.0068 +2024-11-22 01:52:09.519105: train_loss -0.772 +2024-11-22 01:52:09.519381: val_loss -0.7265 +2024-11-22 01:52:09.519455: Pseudo dice [0.8245] +2024-11-22 01:52:09.519532: Epoch time: 19.09 s +2024-11-22 01:52:10.753287: +2024-11-22 01:52:10.753499: Epoch 2786 +2024-11-22 01:52:10.753613: Current learning rate: 0.0068 +2024-11-22 01:52:29.342114: train_loss -0.7752 +2024-11-22 01:52:29.342368: val_loss -0.7162 +2024-11-22 01:52:29.342452: Pseudo dice [0.8136] +2024-11-22 01:52:29.342538: Epoch time: 18.59 s +2024-11-22 01:52:30.196526: +2024-11-22 01:52:30.196737: Epoch 2787 +2024-11-22 01:52:30.196851: Current learning rate: 0.0068 +2024-11-22 01:52:49.514380: train_loss -0.7792 +2024-11-22 01:52:49.514594: val_loss -0.7101 +2024-11-22 01:52:49.514673: Pseudo dice [0.8311] +2024-11-22 01:52:49.514752: Epoch time: 19.32 s +2024-11-22 01:52:50.372313: +2024-11-22 01:52:50.372520: Epoch 2788 +2024-11-22 01:52:50.372630: Current learning rate: 0.0068 +2024-11-22 01:53:08.754915: train_loss -0.7734 +2024-11-22 01:53:08.755135: val_loss -0.7303 +2024-11-22 01:53:08.755208: Pseudo dice [0.8025] +2024-11-22 01:53:08.755286: Epoch time: 18.38 s +2024-11-22 01:53:09.607349: +2024-11-22 01:53:09.607560: Epoch 2789 +2024-11-22 01:53:09.607673: Current learning rate: 0.0068 +2024-11-22 01:53:27.473879: train_loss -0.7762 +2024-11-22 01:53:27.474102: val_loss -0.7463 +2024-11-22 01:53:27.474179: Pseudo dice [0.8428] +2024-11-22 01:53:27.474260: Epoch time: 17.87 s +2024-11-22 01:53:28.333726: +2024-11-22 01:53:28.333936: Epoch 2790 +2024-11-22 01:53:28.334058: Current learning rate: 0.0068 +2024-11-22 01:53:47.361086: train_loss -0.7827 +2024-11-22 01:53:47.361324: val_loss -0.7467 +2024-11-22 01:53:47.363580: Pseudo dice [0.8186] +2024-11-22 01:53:47.363683: Epoch time: 19.03 s +2024-11-22 01:53:48.242626: +2024-11-22 01:53:48.243029: Epoch 2791 +2024-11-22 01:53:48.243143: Current learning rate: 0.0068 +2024-11-22 01:54:07.297700: train_loss -0.7686 +2024-11-22 01:54:07.297913: val_loss -0.7422 +2024-11-22 01:54:07.297988: Pseudo dice [0.8404] +2024-11-22 01:54:07.298079: Epoch time: 19.06 s +2024-11-22 01:54:08.159850: +2024-11-22 01:54:08.160067: Epoch 2792 +2024-11-22 01:54:08.160174: Current learning rate: 0.0068 +2024-11-22 01:54:27.395901: train_loss -0.7753 +2024-11-22 01:54:27.396131: val_loss -0.7273 +2024-11-22 01:54:27.398398: Pseudo dice [0.8143] +2024-11-22 01:54:27.398485: Epoch time: 19.24 s +2024-11-22 01:54:28.390527: +2024-11-22 01:54:28.390735: Epoch 2793 +2024-11-22 01:54:28.390850: Current learning rate: 0.00679 +2024-11-22 01:54:46.271512: train_loss -0.7726 +2024-11-22 01:54:46.271768: val_loss -0.7535 +2024-11-22 01:54:46.271851: Pseudo dice [0.8229] +2024-11-22 01:54:46.271935: Epoch time: 17.88 s +2024-11-22 01:54:47.129067: +2024-11-22 01:54:47.129260: Epoch 2794 +2024-11-22 01:54:47.129373: Current learning rate: 0.00679 +2024-11-22 01:55:05.186834: train_loss -0.7739 +2024-11-22 01:55:05.187068: val_loss -0.7487 +2024-11-22 01:55:05.187141: Pseudo dice [0.8433] +2024-11-22 01:55:05.187218: Epoch time: 18.06 s +2024-11-22 01:55:06.053334: +2024-11-22 01:55:06.053545: Epoch 2795 +2024-11-22 01:55:06.053658: Current learning rate: 0.00679 +2024-11-22 01:55:25.643246: train_loss -0.772 +2024-11-22 01:55:25.643467: val_loss -0.7497 +2024-11-22 01:55:25.643541: Pseudo dice [0.8345] +2024-11-22 01:55:25.643617: Epoch time: 19.59 s +2024-11-22 01:55:26.664225: +2024-11-22 01:55:26.664422: Epoch 2796 +2024-11-22 01:55:26.664538: Current learning rate: 0.00679 +2024-11-22 01:55:45.488733: train_loss -0.7775 +2024-11-22 01:55:45.488954: val_loss -0.7464 +2024-11-22 01:55:45.489040: Pseudo dice [0.8398] +2024-11-22 01:55:45.489120: Epoch time: 18.83 s +2024-11-22 01:55:46.346939: +2024-11-22 01:55:46.347147: Epoch 2797 +2024-11-22 01:55:46.347267: Current learning rate: 0.00679 +2024-11-22 01:56:03.775850: train_loss -0.7842 +2024-11-22 01:56:03.778270: val_loss -0.7414 +2024-11-22 01:56:03.778395: Pseudo dice [0.8127] +2024-11-22 01:56:03.778486: Epoch time: 17.43 s +2024-11-22 01:56:05.234506: +2024-11-22 01:56:05.234754: Epoch 2798 +2024-11-22 01:56:05.234865: Current learning rate: 0.00679 +2024-11-22 01:56:25.037391: train_loss -0.784 +2024-11-22 01:56:25.037624: val_loss -0.7327 +2024-11-22 01:56:25.037697: Pseudo dice [0.8391] +2024-11-22 01:56:25.040056: Epoch time: 19.8 s +2024-11-22 01:56:25.933840: +2024-11-22 01:56:25.934089: Epoch 2799 +2024-11-22 01:56:25.934208: Current learning rate: 0.00679 +2024-11-22 01:56:44.710680: train_loss -0.7766 +2024-11-22 01:56:44.710898: val_loss -0.7702 +2024-11-22 01:56:44.710975: Pseudo dice [0.834] +2024-11-22 01:56:44.711060: Epoch time: 18.78 s +2024-11-22 01:56:45.801124: +2024-11-22 01:56:45.801331: Epoch 2800 +2024-11-22 01:56:45.801451: Current learning rate: 0.00679 +2024-11-22 01:57:04.619897: train_loss -0.781 +2024-11-22 01:57:04.620149: val_loss -0.7383 +2024-11-22 01:57:04.620223: Pseudo dice [0.8246] +2024-11-22 01:57:04.620306: Epoch time: 18.82 s +2024-11-22 01:57:05.484253: +2024-11-22 01:57:05.484479: Epoch 2801 +2024-11-22 01:57:05.484591: Current learning rate: 0.00678 +2024-11-22 01:57:24.961277: train_loss -0.7812 +2024-11-22 01:57:24.961499: val_loss -0.7525 +2024-11-22 01:57:24.961623: Pseudo dice [0.8327] +2024-11-22 01:57:24.961702: Epoch time: 19.48 s +2024-11-22 01:57:25.827276: +2024-11-22 01:57:25.827600: Epoch 2802 +2024-11-22 01:57:25.827710: Current learning rate: 0.00678 +2024-11-22 01:57:44.078848: train_loss -0.7789 +2024-11-22 01:57:44.079080: val_loss -0.7295 +2024-11-22 01:57:44.079164: Pseudo dice [0.8032] +2024-11-22 01:57:44.079250: Epoch time: 18.25 s +2024-11-22 01:57:44.935732: +2024-11-22 01:57:44.935942: Epoch 2803 +2024-11-22 01:57:44.936060: Current learning rate: 0.00678 +2024-11-22 01:58:04.096324: train_loss -0.7793 +2024-11-22 01:58:04.096554: val_loss -0.7409 +2024-11-22 01:58:04.096641: Pseudo dice [0.8423] +2024-11-22 01:58:04.098199: Epoch time: 19.16 s +2024-11-22 01:58:04.980125: +2024-11-22 01:58:04.980341: Epoch 2804 +2024-11-22 01:58:04.980451: Current learning rate: 0.00678 +2024-11-22 01:58:23.749083: train_loss -0.7782 +2024-11-22 01:58:23.749370: val_loss -0.7444 +2024-11-22 01:58:23.749458: Pseudo dice [0.8308] +2024-11-22 01:58:23.749551: Epoch time: 18.77 s +2024-11-22 01:58:24.607570: +2024-11-22 01:58:24.607791: Epoch 2805 +2024-11-22 01:58:24.607914: Current learning rate: 0.00678 +2024-11-22 01:58:43.093539: train_loss -0.7716 +2024-11-22 01:58:43.093756: val_loss -0.7366 +2024-11-22 01:58:43.112971: Pseudo dice [0.8365] +2024-11-22 01:58:43.113063: Epoch time: 18.49 s +2024-11-22 01:58:43.968816: +2024-11-22 01:58:43.969012: Epoch 2806 +2024-11-22 01:58:43.969118: Current learning rate: 0.00678 +2024-11-22 01:59:02.217346: train_loss -0.7771 +2024-11-22 01:59:02.217562: val_loss -0.757 +2024-11-22 01:59:02.217635: Pseudo dice [0.8397] +2024-11-22 01:59:02.217713: Epoch time: 18.25 s +2024-11-22 01:59:03.090529: +2024-11-22 01:59:03.090734: Epoch 2807 +2024-11-22 01:59:03.090849: Current learning rate: 0.00678 +2024-11-22 01:59:23.038869: train_loss -0.767 +2024-11-22 01:59:23.039124: val_loss -0.7214 +2024-11-22 01:59:23.039204: Pseudo dice [0.8288] +2024-11-22 01:59:23.039308: Epoch time: 19.95 s +2024-11-22 01:59:23.893430: +2024-11-22 01:59:23.893621: Epoch 2808 +2024-11-22 01:59:23.893733: Current learning rate: 0.00678 +2024-11-22 01:59:43.379241: train_loss -0.7788 +2024-11-22 01:59:43.379476: val_loss -0.7591 +2024-11-22 01:59:43.379551: Pseudo dice [0.8291] +2024-11-22 01:59:43.379632: Epoch time: 19.49 s +2024-11-22 01:59:44.352601: +2024-11-22 01:59:44.352806: Epoch 2809 +2024-11-22 01:59:44.352921: Current learning rate: 0.00678 +2024-11-22 02:00:02.688951: train_loss -0.7811 +2024-11-22 02:00:02.689538: val_loss -0.741 +2024-11-22 02:00:02.689646: Pseudo dice [0.829] +2024-11-22 02:00:02.689797: Epoch time: 18.34 s +2024-11-22 02:00:03.546906: +2024-11-22 02:00:03.547126: Epoch 2810 +2024-11-22 02:00:03.547236: Current learning rate: 0.00677 +2024-11-22 02:00:22.877400: train_loss -0.7913 +2024-11-22 02:00:22.877626: val_loss -0.7506 +2024-11-22 02:00:22.879939: Pseudo dice [0.8374] +2024-11-22 02:00:22.880046: Epoch time: 19.33 s +2024-11-22 02:00:23.764440: +2024-11-22 02:00:23.764677: Epoch 2811 +2024-11-22 02:00:23.764788: Current learning rate: 0.00677 +2024-11-22 02:00:44.356476: train_loss -0.7827 +2024-11-22 02:00:44.357072: val_loss -0.7564 +2024-11-22 02:00:44.357152: Pseudo dice [0.8339] +2024-11-22 02:00:44.357234: Epoch time: 20.59 s +2024-11-22 02:00:44.357300: Yayy! New best EMA pseudo Dice: 0.8307 +2024-11-22 02:00:45.445529: +2024-11-22 02:00:45.445750: Epoch 2812 +2024-11-22 02:00:45.445867: Current learning rate: 0.00677 +2024-11-22 02:01:04.453906: train_loss -0.7669 +2024-11-22 02:01:04.454199: val_loss -0.7412 +2024-11-22 02:01:04.454277: Pseudo dice [0.8107] +2024-11-22 02:01:04.454355: Epoch time: 19.01 s +2024-11-22 02:01:05.311636: +2024-11-22 02:01:05.311828: Epoch 2813 +2024-11-22 02:01:05.311938: Current learning rate: 0.00677 +2024-11-22 02:01:25.467941: train_loss -0.7472 +2024-11-22 02:01:25.468163: val_loss -0.7509 +2024-11-22 02:01:25.468237: Pseudo dice [0.8302] +2024-11-22 02:01:25.468311: Epoch time: 20.16 s +2024-11-22 02:01:26.320882: +2024-11-22 02:01:26.321101: Epoch 2814 +2024-11-22 02:01:26.321215: Current learning rate: 0.00677 +2024-11-22 02:01:43.652529: train_loss -0.7648 +2024-11-22 02:01:43.652748: val_loss -0.7122 +2024-11-22 02:01:43.652829: Pseudo dice [0.8269] +2024-11-22 02:01:43.652931: Epoch time: 17.33 s +2024-11-22 02:01:44.522963: +2024-11-22 02:01:44.523232: Epoch 2815 +2024-11-22 02:01:44.523349: Current learning rate: 0.00677 +2024-11-22 02:02:02.121877: train_loss -0.7778 +2024-11-22 02:02:02.122131: val_loss -0.7513 +2024-11-22 02:02:02.122209: Pseudo dice [0.8247] +2024-11-22 02:02:02.122293: Epoch time: 17.6 s +2024-11-22 02:02:02.980577: +2024-11-22 02:02:02.980799: Epoch 2816 +2024-11-22 02:02:02.980910: Current learning rate: 0.00677 +2024-11-22 02:02:22.027482: train_loss -0.7772 +2024-11-22 02:02:22.027698: val_loss -0.7252 +2024-11-22 02:02:22.027775: Pseudo dice [0.8217] +2024-11-22 02:02:22.027851: Epoch time: 19.05 s +2024-11-22 02:02:22.885229: +2024-11-22 02:02:22.885435: Epoch 2817 +2024-11-22 02:02:22.885552: Current learning rate: 0.00677 +2024-11-22 02:02:42.164014: train_loss -0.7695 +2024-11-22 02:02:42.164225: val_loss -0.7722 +2024-11-22 02:02:42.164298: Pseudo dice [0.8318] +2024-11-22 02:02:42.164377: Epoch time: 19.28 s +2024-11-22 02:02:43.015625: +2024-11-22 02:02:43.015931: Epoch 2818 +2024-11-22 02:02:43.032353: Current learning rate: 0.00676 +2024-11-22 02:03:02.260519: train_loss -0.7802 +2024-11-22 02:03:02.260781: val_loss -0.7636 +2024-11-22 02:03:02.260864: Pseudo dice [0.8355] +2024-11-22 02:03:02.260957: Epoch time: 19.25 s +2024-11-22 02:03:03.123322: +2024-11-22 02:03:03.123525: Epoch 2819 +2024-11-22 02:03:03.123635: Current learning rate: 0.00676 +2024-11-22 02:03:21.831789: train_loss -0.7742 +2024-11-22 02:03:21.832019: val_loss -0.7292 +2024-11-22 02:03:21.832092: Pseudo dice [0.8277] +2024-11-22 02:03:21.832170: Epoch time: 18.71 s +2024-11-22 02:03:22.710246: +2024-11-22 02:03:22.710464: Epoch 2820 +2024-11-22 02:03:22.710582: Current learning rate: 0.00676 +2024-11-22 02:03:42.749663: train_loss -0.7715 +2024-11-22 02:03:42.749949: val_loss -0.7262 +2024-11-22 02:03:42.750033: Pseudo dice [0.8128] +2024-11-22 02:03:42.750112: Epoch time: 20.04 s +2024-11-22 02:03:44.020282: +2024-11-22 02:03:44.020510: Epoch 2821 +2024-11-22 02:03:44.020626: Current learning rate: 0.00676 +2024-11-22 02:04:02.706205: train_loss -0.7847 +2024-11-22 02:04:02.706458: val_loss -0.7358 +2024-11-22 02:04:02.706540: Pseudo dice [0.8196] +2024-11-22 02:04:02.706642: Epoch time: 18.69 s +2024-11-22 02:04:03.569114: +2024-11-22 02:04:03.569367: Epoch 2822 +2024-11-22 02:04:03.569480: Current learning rate: 0.00676 +2024-11-22 02:04:21.550918: train_loss -0.7819 +2024-11-22 02:04:21.551179: val_loss -0.7601 +2024-11-22 02:04:21.551257: Pseudo dice [0.8194] +2024-11-22 02:04:21.551335: Epoch time: 17.98 s +2024-11-22 02:04:22.409029: +2024-11-22 02:04:22.409231: Epoch 2823 +2024-11-22 02:04:22.409345: Current learning rate: 0.00676 +2024-11-22 02:04:40.494308: train_loss -0.781 +2024-11-22 02:04:40.494564: val_loss -0.7566 +2024-11-22 02:04:40.494651: Pseudo dice [0.8247] +2024-11-22 02:04:40.494731: Epoch time: 18.09 s +2024-11-22 02:04:41.358505: +2024-11-22 02:04:41.358711: Epoch 2824 +2024-11-22 02:04:41.358823: Current learning rate: 0.00676 +2024-11-22 02:05:01.875095: train_loss -0.7891 +2024-11-22 02:05:01.875324: val_loss -0.7413 +2024-11-22 02:05:01.875399: Pseudo dice [0.8259] +2024-11-22 02:05:01.875549: Epoch time: 20.52 s +2024-11-22 02:05:02.741732: +2024-11-22 02:05:02.741960: Epoch 2825 +2024-11-22 02:05:02.742083: Current learning rate: 0.00676 +2024-11-22 02:05:21.782887: train_loss -0.7826 +2024-11-22 02:05:21.783144: val_loss -0.7373 +2024-11-22 02:05:21.783229: Pseudo dice [0.8188] +2024-11-22 02:05:21.783329: Epoch time: 19.04 s +2024-11-22 02:05:22.638480: +2024-11-22 02:05:22.638689: Epoch 2826 +2024-11-22 02:05:22.638802: Current learning rate: 0.00676 +2024-11-22 02:05:40.108537: train_loss -0.7836 +2024-11-22 02:05:40.108755: val_loss -0.7248 +2024-11-22 02:05:40.108828: Pseudo dice [0.8177] +2024-11-22 02:05:40.108903: Epoch time: 17.47 s +2024-11-22 02:05:40.972270: +2024-11-22 02:05:40.972484: Epoch 2827 +2024-11-22 02:05:40.972596: Current learning rate: 0.00675 +2024-11-22 02:06:01.319700: train_loss -0.7721 +2024-11-22 02:06:01.319921: val_loss -0.7518 +2024-11-22 02:06:01.320002: Pseudo dice [0.8295] +2024-11-22 02:06:01.320080: Epoch time: 20.35 s +2024-11-22 02:06:02.184197: +2024-11-22 02:06:02.184473: Epoch 2828 +2024-11-22 02:06:02.184587: Current learning rate: 0.00675 +2024-11-22 02:06:21.596377: train_loss -0.7732 +2024-11-22 02:06:21.596628: val_loss -0.7643 +2024-11-22 02:06:21.596721: Pseudo dice [0.8321] +2024-11-22 02:06:21.596837: Epoch time: 19.41 s +2024-11-22 02:06:22.458361: +2024-11-22 02:06:22.458552: Epoch 2829 +2024-11-22 02:06:22.458666: Current learning rate: 0.00675 +2024-11-22 02:06:41.278185: train_loss -0.778 +2024-11-22 02:06:41.278406: val_loss -0.7374 +2024-11-22 02:06:41.278482: Pseudo dice [0.8272] +2024-11-22 02:06:41.278563: Epoch time: 18.82 s +2024-11-22 02:06:42.136975: +2024-11-22 02:06:42.137239: Epoch 2830 +2024-11-22 02:06:42.137351: Current learning rate: 0.00675 +2024-11-22 02:07:00.618717: train_loss -0.7753 +2024-11-22 02:07:00.618937: val_loss -0.7554 +2024-11-22 02:07:00.619019: Pseudo dice [0.8351] +2024-11-22 02:07:00.619097: Epoch time: 18.48 s +2024-11-22 02:07:01.473695: +2024-11-22 02:07:01.473876: Epoch 2831 +2024-11-22 02:07:01.473986: Current learning rate: 0.00675 +2024-11-22 02:07:20.765645: train_loss -0.7836 +2024-11-22 02:07:20.767740: val_loss -0.7516 +2024-11-22 02:07:20.767885: Pseudo dice [0.8396] +2024-11-22 02:07:20.767964: Epoch time: 19.29 s +2024-11-22 02:07:21.625935: +2024-11-22 02:07:21.626171: Epoch 2832 +2024-11-22 02:07:21.626289: Current learning rate: 0.00675 +2024-11-22 02:07:39.864515: train_loss -0.772 +2024-11-22 02:07:39.864758: val_loss -0.7215 +2024-11-22 02:07:39.864838: Pseudo dice [0.8165] +2024-11-22 02:07:39.864921: Epoch time: 18.24 s +2024-11-22 02:07:41.131907: +2024-11-22 02:07:41.132133: Epoch 2833 +2024-11-22 02:07:41.132243: Current learning rate: 0.00675 +2024-11-22 02:07:59.680663: train_loss -0.7524 +2024-11-22 02:07:59.680887: val_loss -0.712 +2024-11-22 02:07:59.680983: Pseudo dice [0.8027] +2024-11-22 02:07:59.681073: Epoch time: 18.55 s +2024-11-22 02:08:00.535954: +2024-11-22 02:08:00.536211: Epoch 2834 +2024-11-22 02:08:00.536331: Current learning rate: 0.00675 +2024-11-22 02:08:18.795796: train_loss -0.7587 +2024-11-22 02:08:18.796081: val_loss -0.7336 +2024-11-22 02:08:18.796158: Pseudo dice [0.8297] +2024-11-22 02:08:18.796236: Epoch time: 18.26 s +2024-11-22 02:08:19.654231: +2024-11-22 02:08:19.654499: Epoch 2835 +2024-11-22 02:08:19.654619: Current learning rate: 0.00675 +2024-11-22 02:08:39.332299: train_loss -0.757 +2024-11-22 02:08:39.332552: val_loss -0.7305 +2024-11-22 02:08:39.332772: Pseudo dice [0.8168] +2024-11-22 02:08:39.332858: Epoch time: 19.68 s +2024-11-22 02:08:40.192325: +2024-11-22 02:08:40.192531: Epoch 2836 +2024-11-22 02:08:40.192647: Current learning rate: 0.00674 +2024-11-22 02:08:59.153478: train_loss -0.759 +2024-11-22 02:08:59.153699: val_loss -0.754 +2024-11-22 02:08:59.153777: Pseudo dice [0.8352] +2024-11-22 02:08:59.153858: Epoch time: 18.96 s +2024-11-22 02:09:00.009526: +2024-11-22 02:09:00.009749: Epoch 2837 +2024-11-22 02:09:00.009864: Current learning rate: 0.00674 +2024-11-22 02:09:18.217631: train_loss -0.7781 +2024-11-22 02:09:18.217862: val_loss -0.7604 +2024-11-22 02:09:18.217941: Pseudo dice [0.8323] +2024-11-22 02:09:18.218031: Epoch time: 18.21 s +2024-11-22 02:09:19.083526: +2024-11-22 02:09:19.083768: Epoch 2838 +2024-11-22 02:09:19.083885: Current learning rate: 0.00674 +2024-11-22 02:09:37.796677: train_loss -0.7787 +2024-11-22 02:09:37.796901: val_loss -0.7301 +2024-11-22 02:09:37.796975: Pseudo dice [0.8178] +2024-11-22 02:09:37.797062: Epoch time: 18.71 s +2024-11-22 02:09:38.653870: +2024-11-22 02:09:38.654081: Epoch 2839 +2024-11-22 02:09:38.654192: Current learning rate: 0.00674 +2024-11-22 02:09:56.626734: train_loss -0.7714 +2024-11-22 02:09:56.626987: val_loss -0.7489 +2024-11-22 02:09:56.627066: Pseudo dice [0.8338] +2024-11-22 02:09:56.627147: Epoch time: 17.97 s +2024-11-22 02:09:57.483252: +2024-11-22 02:09:57.483459: Epoch 2840 +2024-11-22 02:09:57.483577: Current learning rate: 0.00674 +2024-11-22 02:10:16.511954: train_loss -0.7791 +2024-11-22 02:10:16.512182: val_loss -0.746 +2024-11-22 02:10:16.512318: Pseudo dice [0.8397] +2024-11-22 02:10:16.512398: Epoch time: 19.03 s +2024-11-22 02:10:17.372190: +2024-11-22 02:10:17.372385: Epoch 2841 +2024-11-22 02:10:17.372495: Current learning rate: 0.00674 +2024-11-22 02:10:36.231924: train_loss -0.7773 +2024-11-22 02:10:36.232161: val_loss -0.742 +2024-11-22 02:10:36.232235: Pseudo dice [0.8296] +2024-11-22 02:10:36.232346: Epoch time: 18.86 s +2024-11-22 02:10:37.098767: +2024-11-22 02:10:37.098955: Epoch 2842 +2024-11-22 02:10:37.099074: Current learning rate: 0.00674 +2024-11-22 02:10:56.008296: train_loss -0.7744 +2024-11-22 02:10:56.008547: val_loss -0.7067 +2024-11-22 02:10:56.008636: Pseudo dice [0.8107] +2024-11-22 02:10:56.008748: Epoch time: 18.91 s +2024-11-22 02:10:56.909142: +2024-11-22 02:10:56.909342: Epoch 2843 +2024-11-22 02:10:56.909455: Current learning rate: 0.00674 +2024-11-22 02:11:14.917600: train_loss -0.777 +2024-11-22 02:11:14.917812: val_loss -0.7158 +2024-11-22 02:11:14.917887: Pseudo dice [0.8111] +2024-11-22 02:11:14.917965: Epoch time: 18.01 s +2024-11-22 02:11:15.778802: +2024-11-22 02:11:15.779023: Epoch 2844 +2024-11-22 02:11:15.779166: Current learning rate: 0.00673 +2024-11-22 02:11:33.500152: train_loss -0.7775 +2024-11-22 02:11:33.500372: val_loss -0.728 +2024-11-22 02:11:33.500447: Pseudo dice [0.8229] +2024-11-22 02:11:33.500522: Epoch time: 17.72 s +2024-11-22 02:11:34.784702: +2024-11-22 02:11:34.784918: Epoch 2845 +2024-11-22 02:11:34.785036: Current learning rate: 0.00673 +2024-11-22 02:11:53.530751: train_loss -0.7942 +2024-11-22 02:11:53.531020: val_loss -0.7804 +2024-11-22 02:11:53.531112: Pseudo dice [0.8532] +2024-11-22 02:11:53.531206: Epoch time: 18.75 s +2024-11-22 02:11:54.411928: +2024-11-22 02:11:54.412195: Epoch 2846 +2024-11-22 02:11:54.412309: Current learning rate: 0.00673 +2024-11-22 02:12:12.993101: train_loss -0.7773 +2024-11-22 02:12:12.993318: val_loss -0.7498 +2024-11-22 02:12:12.993393: Pseudo dice [0.8282] +2024-11-22 02:12:12.993470: Epoch time: 18.58 s +2024-11-22 02:12:13.845876: +2024-11-22 02:12:13.846117: Epoch 2847 +2024-11-22 02:12:13.846234: Current learning rate: 0.00673 +2024-11-22 02:12:32.272205: train_loss -0.7695 +2024-11-22 02:12:32.272425: val_loss -0.7302 +2024-11-22 02:12:32.272542: Pseudo dice [0.8071] +2024-11-22 02:12:32.272622: Epoch time: 18.43 s +2024-11-22 02:12:33.129885: +2024-11-22 02:12:33.130132: Epoch 2848 +2024-11-22 02:12:33.130250: Current learning rate: 0.00673 +2024-11-22 02:12:52.152750: train_loss -0.7762 +2024-11-22 02:12:52.153007: val_loss -0.7342 +2024-11-22 02:12:52.153087: Pseudo dice [0.8326] +2024-11-22 02:12:52.153171: Epoch time: 19.02 s +2024-11-22 02:12:53.012235: +2024-11-22 02:12:53.012431: Epoch 2849 +2024-11-22 02:12:53.012546: Current learning rate: 0.00673 +2024-11-22 02:13:12.185344: train_loss -0.7815 +2024-11-22 02:13:12.185643: val_loss -0.7527 +2024-11-22 02:13:12.185721: Pseudo dice [0.8274] +2024-11-22 02:13:12.185815: Epoch time: 19.17 s +2024-11-22 02:13:13.263642: +2024-11-22 02:13:13.263848: Epoch 2850 +2024-11-22 02:13:13.263958: Current learning rate: 0.00673 +2024-11-22 02:13:31.108119: train_loss -0.7877 +2024-11-22 02:13:31.108338: val_loss -0.7422 +2024-11-22 02:13:31.108411: Pseudo dice [0.8186] +2024-11-22 02:13:31.108490: Epoch time: 17.85 s +2024-11-22 02:13:31.975470: +2024-11-22 02:13:31.975678: Epoch 2851 +2024-11-22 02:13:31.975789: Current learning rate: 0.00673 +2024-11-22 02:13:50.130415: train_loss -0.7849 +2024-11-22 02:13:50.130662: val_loss -0.7579 +2024-11-22 02:13:50.130737: Pseudo dice [0.8362] +2024-11-22 02:13:50.130824: Epoch time: 18.16 s +2024-11-22 02:13:51.064169: +2024-11-22 02:13:51.064439: Epoch 2852 +2024-11-22 02:13:51.064553: Current learning rate: 0.00673 +2024-11-22 02:14:10.519470: train_loss -0.7814 +2024-11-22 02:14:10.519689: val_loss -0.7607 +2024-11-22 02:14:10.519792: Pseudo dice [0.8392] +2024-11-22 02:14:10.519868: Epoch time: 19.46 s +2024-11-22 02:14:11.375926: +2024-11-22 02:14:11.376137: Epoch 2853 +2024-11-22 02:14:11.376255: Current learning rate: 0.00672 +2024-11-22 02:14:30.151153: train_loss -0.7842 +2024-11-22 02:14:30.151379: val_loss -0.7307 +2024-11-22 02:14:30.151456: Pseudo dice [0.8407] +2024-11-22 02:14:30.151534: Epoch time: 18.78 s +2024-11-22 02:14:31.006424: +2024-11-22 02:14:31.006622: Epoch 2854 +2024-11-22 02:14:31.006734: Current learning rate: 0.00672 +2024-11-22 02:14:49.415515: train_loss -0.7749 +2024-11-22 02:14:49.415730: val_loss -0.7275 +2024-11-22 02:14:49.415804: Pseudo dice [0.8192] +2024-11-22 02:14:49.415880: Epoch time: 18.41 s +2024-11-22 02:14:50.278059: +2024-11-22 02:14:50.278287: Epoch 2855 +2024-11-22 02:14:50.278425: Current learning rate: 0.00672 +2024-11-22 02:15:08.897388: train_loss -0.7693 +2024-11-22 02:15:08.897626: val_loss -0.7497 +2024-11-22 02:15:08.897698: Pseudo dice [0.8213] +2024-11-22 02:15:08.897852: Epoch time: 18.62 s +2024-11-22 02:15:09.751749: +2024-11-22 02:15:09.751953: Epoch 2856 +2024-11-22 02:15:09.752162: Current learning rate: 0.00672 +2024-11-22 02:15:28.840480: train_loss -0.7799 +2024-11-22 02:15:28.844127: val_loss -0.7688 +2024-11-22 02:15:28.844244: Pseudo dice [0.8285] +2024-11-22 02:15:28.844324: Epoch time: 19.09 s +2024-11-22 02:15:29.703362: +2024-11-22 02:15:29.703650: Epoch 2857 +2024-11-22 02:15:29.703763: Current learning rate: 0.00672 +2024-11-22 02:15:48.429692: train_loss -0.7763 +2024-11-22 02:15:48.429925: val_loss -0.7338 +2024-11-22 02:15:48.430008: Pseudo dice [0.8123] +2024-11-22 02:15:48.430090: Epoch time: 18.73 s +2024-11-22 02:15:49.289663: +2024-11-22 02:15:49.289875: Epoch 2858 +2024-11-22 02:15:49.289997: Current learning rate: 0.00672 +2024-11-22 02:16:07.715817: train_loss -0.7798 +2024-11-22 02:16:07.716067: val_loss -0.7494 +2024-11-22 02:16:07.716140: Pseudo dice [0.8301] +2024-11-22 02:16:07.716225: Epoch time: 18.43 s +2024-11-22 02:16:08.583465: +2024-11-22 02:16:08.583684: Epoch 2859 +2024-11-22 02:16:08.583797: Current learning rate: 0.00672 +2024-11-22 02:16:27.043465: train_loss -0.7813 +2024-11-22 02:16:27.043700: val_loss -0.7299 +2024-11-22 02:16:27.043776: Pseudo dice [0.8257] +2024-11-22 02:16:27.043858: Epoch time: 18.46 s +2024-11-22 02:16:27.907052: +2024-11-22 02:16:27.907258: Epoch 2860 +2024-11-22 02:16:27.907377: Current learning rate: 0.00672 +2024-11-22 02:16:46.910518: train_loss -0.7885 +2024-11-22 02:16:46.910739: val_loss -0.7246 +2024-11-22 02:16:46.910812: Pseudo dice [0.8309] +2024-11-22 02:16:46.910904: Epoch time: 19.0 s +2024-11-22 02:16:47.838196: +2024-11-22 02:16:47.838443: Epoch 2861 +2024-11-22 02:16:47.838567: Current learning rate: 0.00671 +2024-11-22 02:17:06.055821: train_loss -0.782 +2024-11-22 02:17:06.056238: val_loss -0.7366 +2024-11-22 02:17:06.056327: Pseudo dice [0.8291] +2024-11-22 02:17:06.056405: Epoch time: 18.22 s +2024-11-22 02:17:06.932975: +2024-11-22 02:17:06.933199: Epoch 2862 +2024-11-22 02:17:06.933319: Current learning rate: 0.00671 +2024-11-22 02:17:24.285553: train_loss -0.7639 +2024-11-22 02:17:24.285847: val_loss -0.7197 +2024-11-22 02:17:24.285923: Pseudo dice [0.8096] +2024-11-22 02:17:24.286009: Epoch time: 17.35 s +2024-11-22 02:17:25.200020: +2024-11-22 02:17:25.200236: Epoch 2863 +2024-11-22 02:17:25.200349: Current learning rate: 0.00671 +2024-11-22 02:17:43.207080: train_loss -0.7679 +2024-11-22 02:17:43.207300: val_loss -0.7358 +2024-11-22 02:17:43.207378: Pseudo dice [0.8128] +2024-11-22 02:17:43.207456: Epoch time: 18.01 s +2024-11-22 02:17:44.065202: +2024-11-22 02:17:44.065389: Epoch 2864 +2024-11-22 02:17:44.065499: Current learning rate: 0.00671 +2024-11-22 02:18:03.479588: train_loss -0.7841 +2024-11-22 02:18:03.479805: val_loss -0.7552 +2024-11-22 02:18:03.479882: Pseudo dice [0.8065] +2024-11-22 02:18:03.479961: Epoch time: 19.42 s +2024-11-22 02:18:04.340140: +2024-11-22 02:18:04.340335: Epoch 2865 +2024-11-22 02:18:04.340453: Current learning rate: 0.00671 +2024-11-22 02:18:22.055334: train_loss -0.7814 +2024-11-22 02:18:22.055584: val_loss -0.715 +2024-11-22 02:18:22.055658: Pseudo dice [0.8328] +2024-11-22 02:18:22.055824: Epoch time: 17.72 s +2024-11-22 02:18:22.924103: +2024-11-22 02:18:22.924302: Epoch 2866 +2024-11-22 02:18:22.924418: Current learning rate: 0.00671 +2024-11-22 02:18:42.122215: train_loss -0.7677 +2024-11-22 02:18:42.122424: val_loss -0.7418 +2024-11-22 02:18:42.122495: Pseudo dice [0.8138] +2024-11-22 02:18:42.122570: Epoch time: 19.2 s +2024-11-22 02:18:42.986692: +2024-11-22 02:18:42.986889: Epoch 2867 +2024-11-22 02:18:42.987010: Current learning rate: 0.00671 +2024-11-22 02:19:01.463475: train_loss -0.7795 +2024-11-22 02:19:01.463711: val_loss -0.7377 +2024-11-22 02:19:01.463789: Pseudo dice [0.8123] +2024-11-22 02:19:01.463867: Epoch time: 18.48 s +2024-11-22 02:19:02.723146: +2024-11-22 02:19:02.723419: Epoch 2868 +2024-11-22 02:19:02.723533: Current learning rate: 0.00671 +2024-11-22 02:19:22.668541: train_loss -0.7816 +2024-11-22 02:19:22.668799: val_loss -0.7559 +2024-11-22 02:19:22.668877: Pseudo dice [0.8401] +2024-11-22 02:19:22.668962: Epoch time: 19.95 s +2024-11-22 02:19:23.538491: +2024-11-22 02:19:23.538711: Epoch 2869 +2024-11-22 02:19:23.538824: Current learning rate: 0.00671 +2024-11-22 02:19:41.683020: train_loss -0.7759 +2024-11-22 02:19:41.683236: val_loss -0.736 +2024-11-22 02:19:41.683313: Pseudo dice [0.8354] +2024-11-22 02:19:41.683392: Epoch time: 18.15 s +2024-11-22 02:19:42.555500: +2024-11-22 02:19:42.555734: Epoch 2870 +2024-11-22 02:19:42.555848: Current learning rate: 0.0067 +2024-11-22 02:20:01.915004: train_loss -0.7463 +2024-11-22 02:20:01.915223: val_loss -0.7152 +2024-11-22 02:20:01.915353: Pseudo dice [0.7951] +2024-11-22 02:20:01.915435: Epoch time: 19.36 s +2024-11-22 02:20:02.782601: +2024-11-22 02:20:02.782816: Epoch 2871 +2024-11-22 02:20:02.782927: Current learning rate: 0.0067 +2024-11-22 02:20:21.695244: train_loss -0.7401 +2024-11-22 02:20:21.695491: val_loss -0.7292 +2024-11-22 02:20:21.695568: Pseudo dice [0.8076] +2024-11-22 02:20:21.695654: Epoch time: 18.91 s +2024-11-22 02:20:22.557635: +2024-11-22 02:20:22.557831: Epoch 2872 +2024-11-22 02:20:22.557946: Current learning rate: 0.0067 +2024-11-22 02:20:40.528220: train_loss -0.7666 +2024-11-22 02:20:40.528438: val_loss -0.7063 +2024-11-22 02:20:40.528515: Pseudo dice [0.8181] +2024-11-22 02:20:40.528592: Epoch time: 17.97 s +2024-11-22 02:20:41.396086: +2024-11-22 02:20:41.396290: Epoch 2873 +2024-11-22 02:20:41.396402: Current learning rate: 0.0067 +2024-11-22 02:21:00.991958: train_loss -0.7684 +2024-11-22 02:21:00.992164: val_loss -0.7652 +2024-11-22 02:21:00.994440: Pseudo dice [0.8429] +2024-11-22 02:21:00.994528: Epoch time: 19.6 s +2024-11-22 02:21:01.869355: +2024-11-22 02:21:01.869559: Epoch 2874 +2024-11-22 02:21:01.869669: Current learning rate: 0.0067 +2024-11-22 02:21:21.728176: train_loss -0.7685 +2024-11-22 02:21:21.728425: val_loss -0.7445 +2024-11-22 02:21:21.728498: Pseudo dice [0.8234] +2024-11-22 02:21:21.728574: Epoch time: 19.86 s +2024-11-22 02:21:22.602034: +2024-11-22 02:21:22.602316: Epoch 2875 +2024-11-22 02:21:22.602434: Current learning rate: 0.0067 +2024-11-22 02:21:41.543920: train_loss -0.7637 +2024-11-22 02:21:41.544190: val_loss -0.7347 +2024-11-22 02:21:41.544271: Pseudo dice [0.802] +2024-11-22 02:21:41.544358: Epoch time: 18.94 s +2024-11-22 02:21:42.570323: +2024-11-22 02:21:42.570514: Epoch 2876 +2024-11-22 02:21:42.570625: Current learning rate: 0.0067 +2024-11-22 02:22:01.687469: train_loss -0.7831 +2024-11-22 02:22:01.687689: val_loss -0.7648 +2024-11-22 02:22:01.687767: Pseudo dice [0.8365] +2024-11-22 02:22:01.687850: Epoch time: 19.12 s +2024-11-22 02:22:02.554515: +2024-11-22 02:22:02.554785: Epoch 2877 +2024-11-22 02:22:02.554897: Current learning rate: 0.0067 +2024-11-22 02:22:21.345675: train_loss -0.7693 +2024-11-22 02:22:21.345896: val_loss -0.7521 +2024-11-22 02:22:21.345970: Pseudo dice [0.8181] +2024-11-22 02:22:21.346052: Epoch time: 18.79 s +2024-11-22 02:22:22.271193: +2024-11-22 02:22:22.271423: Epoch 2878 +2024-11-22 02:22:22.271538: Current learning rate: 0.00669 +2024-11-22 02:22:41.723747: train_loss -0.7702 +2024-11-22 02:22:41.723962: val_loss -0.7674 +2024-11-22 02:22:41.724046: Pseudo dice [0.842] +2024-11-22 02:22:41.724133: Epoch time: 19.45 s +2024-11-22 02:22:42.588752: +2024-11-22 02:22:42.588957: Epoch 2879 +2024-11-22 02:22:42.589081: Current learning rate: 0.00669 +2024-11-22 02:23:01.325053: train_loss -0.7745 +2024-11-22 02:23:01.325585: val_loss -0.7193 +2024-11-22 02:23:01.325682: Pseudo dice [0.7937] +2024-11-22 02:23:01.325900: Epoch time: 18.74 s +2024-11-22 02:23:02.193875: +2024-11-22 02:23:02.194078: Epoch 2880 +2024-11-22 02:23:02.194196: Current learning rate: 0.00669 +2024-11-22 02:23:20.741770: train_loss -0.7682 +2024-11-22 02:23:20.741998: val_loss -0.7312 +2024-11-22 02:23:20.742075: Pseudo dice [0.8152] +2024-11-22 02:23:20.742152: Epoch time: 18.55 s +2024-11-22 02:23:21.610197: +2024-11-22 02:23:21.610395: Epoch 2881 +2024-11-22 02:23:21.610506: Current learning rate: 0.00669 +2024-11-22 02:23:39.885388: train_loss -0.7732 +2024-11-22 02:23:39.885610: val_loss -0.7452 +2024-11-22 02:23:39.885684: Pseudo dice [0.8244] +2024-11-22 02:23:39.885761: Epoch time: 18.28 s +2024-11-22 02:23:40.756907: +2024-11-22 02:23:40.757126: Epoch 2882 +2024-11-22 02:23:40.757242: Current learning rate: 0.00669 +2024-11-22 02:24:00.699324: train_loss -0.7851 +2024-11-22 02:24:00.699567: val_loss -0.7475 +2024-11-22 02:24:00.699680: Pseudo dice [0.8151] +2024-11-22 02:24:00.699762: Epoch time: 19.94 s +2024-11-22 02:24:01.568675: +2024-11-22 02:24:01.568997: Epoch 2883 +2024-11-22 02:24:01.569108: Current learning rate: 0.00669 +2024-11-22 02:24:20.902351: train_loss -0.7686 +2024-11-22 02:24:20.902577: val_loss -0.7555 +2024-11-22 02:24:20.902654: Pseudo dice [0.8334] +2024-11-22 02:24:20.902736: Epoch time: 19.33 s +2024-11-22 02:24:21.806233: +2024-11-22 02:24:21.806516: Epoch 2884 +2024-11-22 02:24:21.806631: Current learning rate: 0.00669 +2024-11-22 02:24:40.887830: train_loss -0.7736 +2024-11-22 02:24:40.888104: val_loss -0.7387 +2024-11-22 02:24:40.888188: Pseudo dice [0.8267] +2024-11-22 02:24:40.888272: Epoch time: 19.08 s +2024-11-22 02:24:41.761497: +2024-11-22 02:24:41.761713: Epoch 2885 +2024-11-22 02:24:41.761825: Current learning rate: 0.00669 +2024-11-22 02:25:00.404678: train_loss -0.7852 +2024-11-22 02:25:00.404901: val_loss -0.7506 +2024-11-22 02:25:00.404979: Pseudo dice [0.82] +2024-11-22 02:25:00.405061: Epoch time: 18.64 s +2024-11-22 02:25:01.269801: +2024-11-22 02:25:01.270051: Epoch 2886 +2024-11-22 02:25:01.270162: Current learning rate: 0.00669 +2024-11-22 02:25:20.529234: train_loss -0.7891 +2024-11-22 02:25:20.531646: val_loss -0.7501 +2024-11-22 02:25:20.531731: Pseudo dice [0.8343] +2024-11-22 02:25:20.531816: Epoch time: 19.26 s +2024-11-22 02:25:21.423768: +2024-11-22 02:25:21.423972: Epoch 2887 +2024-11-22 02:25:21.424092: Current learning rate: 0.00668 +2024-11-22 02:25:39.922230: train_loss -0.7861 +2024-11-22 02:25:39.924721: val_loss -0.7585 +2024-11-22 02:25:39.924847: Pseudo dice [0.8203] +2024-11-22 02:25:39.924930: Epoch time: 18.5 s +2024-11-22 02:25:40.990108: +2024-11-22 02:25:40.990309: Epoch 2888 +2024-11-22 02:25:40.990422: Current learning rate: 0.00668 +2024-11-22 02:26:00.034522: train_loss -0.7627 +2024-11-22 02:26:00.034742: val_loss -0.7211 +2024-11-22 02:26:00.034816: Pseudo dice [0.8125] +2024-11-22 02:26:00.034892: Epoch time: 19.05 s +2024-11-22 02:26:00.901544: +2024-11-22 02:26:00.901731: Epoch 2889 +2024-11-22 02:26:00.901857: Current learning rate: 0.00668 +2024-11-22 02:26:19.484226: train_loss -0.7549 +2024-11-22 02:26:19.484436: val_loss -0.7227 +2024-11-22 02:26:19.484511: Pseudo dice [0.8315] +2024-11-22 02:26:19.486739: Epoch time: 18.58 s +2024-11-22 02:26:20.375276: +2024-11-22 02:26:20.375471: Epoch 2890 +2024-11-22 02:26:20.375587: Current learning rate: 0.00668 +2024-11-22 02:26:38.085884: train_loss -0.7678 +2024-11-22 02:26:38.086137: val_loss -0.7439 +2024-11-22 02:26:38.086213: Pseudo dice [0.822] +2024-11-22 02:26:38.091509: Epoch time: 17.71 s +2024-11-22 02:26:39.462614: +2024-11-22 02:26:39.462836: Epoch 2891 +2024-11-22 02:26:39.462945: Current learning rate: 0.00668 +2024-11-22 02:26:58.261169: train_loss -0.7664 +2024-11-22 02:26:58.261381: val_loss -0.7404 +2024-11-22 02:26:58.261460: Pseudo dice [0.816] +2024-11-22 02:26:58.261537: Epoch time: 18.8 s +2024-11-22 02:26:59.119334: +2024-11-22 02:26:59.119538: Epoch 2892 +2024-11-22 02:26:59.119652: Current learning rate: 0.00668 +2024-11-22 02:27:18.953695: train_loss -0.7719 +2024-11-22 02:27:18.959131: val_loss -0.7333 +2024-11-22 02:27:18.959274: Pseudo dice [0.8267] +2024-11-22 02:27:18.959362: Epoch time: 19.84 s +2024-11-22 02:27:19.968264: +2024-11-22 02:27:19.968551: Epoch 2893 +2024-11-22 02:27:19.968666: Current learning rate: 0.00668 +2024-11-22 02:27:38.615971: train_loss -0.7732 +2024-11-22 02:27:38.616225: val_loss -0.7498 +2024-11-22 02:27:38.616297: Pseudo dice [0.8278] +2024-11-22 02:27:38.616377: Epoch time: 18.65 s +2024-11-22 02:27:39.583253: +2024-11-22 02:27:39.583450: Epoch 2894 +2024-11-22 02:27:39.583567: Current learning rate: 0.00668 +2024-11-22 02:27:58.499581: train_loss -0.7676 +2024-11-22 02:27:58.499825: val_loss -0.762 +2024-11-22 02:27:58.499903: Pseudo dice [0.84] +2024-11-22 02:27:58.499982: Epoch time: 18.92 s +2024-11-22 02:27:59.368192: +2024-11-22 02:27:59.368389: Epoch 2895 +2024-11-22 02:27:59.368500: Current learning rate: 0.00667 +2024-11-22 02:28:18.366641: train_loss -0.7697 +2024-11-22 02:28:18.371179: val_loss -0.7444 +2024-11-22 02:28:18.371294: Pseudo dice [0.8204] +2024-11-22 02:28:18.371374: Epoch time: 19.0 s +2024-11-22 02:28:19.245257: +2024-11-22 02:28:19.245452: Epoch 2896 +2024-11-22 02:28:19.245568: Current learning rate: 0.00667 +2024-11-22 02:28:38.325286: train_loss -0.7779 +2024-11-22 02:28:38.325508: val_loss -0.7603 +2024-11-22 02:28:38.325584: Pseudo dice [0.8295] +2024-11-22 02:28:38.325659: Epoch time: 19.08 s +2024-11-22 02:28:39.363486: +2024-11-22 02:28:39.363687: Epoch 2897 +2024-11-22 02:28:39.363800: Current learning rate: 0.00667 +2024-11-22 02:28:58.892963: train_loss -0.775 +2024-11-22 02:28:58.893215: val_loss -0.7311 +2024-11-22 02:28:58.893291: Pseudo dice [0.8066] +2024-11-22 02:28:58.893374: Epoch time: 19.53 s +2024-11-22 02:28:59.765456: +2024-11-22 02:28:59.765678: Epoch 2898 +2024-11-22 02:28:59.765794: Current learning rate: 0.00667 +2024-11-22 02:29:18.965263: train_loss -0.7807 +2024-11-22 02:29:18.965490: val_loss -0.7539 +2024-11-22 02:29:18.965570: Pseudo dice [0.8287] +2024-11-22 02:29:18.965651: Epoch time: 19.2 s +2024-11-22 02:29:19.835585: +2024-11-22 02:29:19.835771: Epoch 2899 +2024-11-22 02:29:19.835886: Current learning rate: 0.00667 +2024-11-22 02:29:38.321812: train_loss -0.7709 +2024-11-22 02:29:38.322028: val_loss -0.7145 +2024-11-22 02:29:38.322104: Pseudo dice [0.8299] +2024-11-22 02:29:38.322178: Epoch time: 18.49 s +2024-11-22 02:29:39.407977: +2024-11-22 02:29:39.408180: Epoch 2900 +2024-11-22 02:29:39.408289: Current learning rate: 0.00667 +2024-11-22 02:29:58.455225: train_loss -0.7741 +2024-11-22 02:29:58.455464: val_loss -0.7506 +2024-11-22 02:29:58.455540: Pseudo dice [0.8208] +2024-11-22 02:29:58.455624: Epoch time: 19.05 s +2024-11-22 02:29:59.319140: +2024-11-22 02:29:59.319344: Epoch 2901 +2024-11-22 02:29:59.319458: Current learning rate: 0.00667 +2024-11-22 02:30:18.614167: train_loss -0.7755 +2024-11-22 02:30:18.614392: val_loss -0.7209 +2024-11-22 02:30:18.614467: Pseudo dice [0.808] +2024-11-22 02:30:18.614546: Epoch time: 19.3 s +2024-11-22 02:30:19.628318: +2024-11-22 02:30:19.628519: Epoch 2902 +2024-11-22 02:30:19.628631: Current learning rate: 0.00667 +2024-11-22 02:30:37.380719: train_loss -0.7725 +2024-11-22 02:30:37.381306: val_loss -0.7511 +2024-11-22 02:30:37.381408: Pseudo dice [0.8359] +2024-11-22 02:30:37.381491: Epoch time: 17.75 s +2024-11-22 02:30:38.250195: +2024-11-22 02:30:38.250415: Epoch 2903 +2024-11-22 02:30:38.250527: Current learning rate: 0.00667 +2024-11-22 02:30:56.905929: train_loss -0.7776 +2024-11-22 02:30:56.906185: val_loss -0.7446 +2024-11-22 02:30:56.906262: Pseudo dice [0.8144] +2024-11-22 02:30:56.906345: Epoch time: 18.66 s +2024-11-22 02:30:58.044609: +2024-11-22 02:30:58.044833: Epoch 2904 +2024-11-22 02:30:58.044944: Current learning rate: 0.00666 +2024-11-22 02:31:16.421383: train_loss -0.7753 +2024-11-22 02:31:16.421599: val_loss -0.7482 +2024-11-22 02:31:16.421673: Pseudo dice [0.8306] +2024-11-22 02:31:16.421753: Epoch time: 18.38 s +2024-11-22 02:31:17.290977: +2024-11-22 02:31:17.291193: Epoch 2905 +2024-11-22 02:31:17.291310: Current learning rate: 0.00666 +2024-11-22 02:31:35.613083: train_loss -0.767 +2024-11-22 02:31:35.613302: val_loss -0.7067 +2024-11-22 02:31:35.613374: Pseudo dice [0.814] +2024-11-22 02:31:35.613451: Epoch time: 18.32 s +2024-11-22 02:31:36.489615: +2024-11-22 02:31:36.489838: Epoch 2906 +2024-11-22 02:31:36.489951: Current learning rate: 0.00666 +2024-11-22 02:31:55.704080: train_loss -0.7699 +2024-11-22 02:31:55.704340: val_loss -0.725 +2024-11-22 02:31:55.704419: Pseudo dice [0.8143] +2024-11-22 02:31:55.704506: Epoch time: 19.22 s +2024-11-22 02:31:56.592096: +2024-11-22 02:31:56.608091: Epoch 2907 +2024-11-22 02:31:56.608227: Current learning rate: 0.00666 +2024-11-22 02:32:15.380894: train_loss -0.7789 +2024-11-22 02:32:15.381120: val_loss -0.7464 +2024-11-22 02:32:15.381196: Pseudo dice [0.8229] +2024-11-22 02:32:15.381272: Epoch time: 18.79 s +2024-11-22 02:32:16.253165: +2024-11-22 02:32:16.253377: Epoch 2908 +2024-11-22 02:32:16.253489: Current learning rate: 0.00666 +2024-11-22 02:32:34.946640: train_loss -0.7777 +2024-11-22 02:32:34.946871: val_loss -0.7291 +2024-11-22 02:32:34.946949: Pseudo dice [0.8312] +2024-11-22 02:32:34.947036: Epoch time: 18.69 s +2024-11-22 02:32:35.821956: +2024-11-22 02:32:35.822182: Epoch 2909 +2024-11-22 02:32:35.822299: Current learning rate: 0.00666 +2024-11-22 02:32:55.858772: train_loss -0.7669 +2024-11-22 02:32:55.858984: val_loss -0.7293 +2024-11-22 02:32:55.859065: Pseudo dice [0.8307] +2024-11-22 02:32:55.859152: Epoch time: 20.04 s +2024-11-22 02:32:56.725915: +2024-11-22 02:32:56.726118: Epoch 2910 +2024-11-22 02:32:56.726232: Current learning rate: 0.00666 +2024-11-22 02:33:15.893972: train_loss -0.7689 +2024-11-22 02:33:15.894227: val_loss -0.7446 +2024-11-22 02:33:15.894305: Pseudo dice [0.8264] +2024-11-22 02:33:15.894389: Epoch time: 19.17 s +2024-11-22 02:33:16.765539: +2024-11-22 02:33:16.765742: Epoch 2911 +2024-11-22 02:33:16.765854: Current learning rate: 0.00666 +2024-11-22 02:33:34.877720: train_loss -0.7827 +2024-11-22 02:33:34.883144: val_loss -0.7226 +2024-11-22 02:33:34.883271: Pseudo dice [0.8225] +2024-11-22 02:33:34.883349: Epoch time: 18.11 s +2024-11-22 02:33:35.781312: +2024-11-22 02:33:35.781498: Epoch 2912 +2024-11-22 02:33:35.781608: Current learning rate: 0.00665 +2024-11-22 02:33:53.980312: train_loss -0.7833 +2024-11-22 02:33:53.980532: val_loss -0.7381 +2024-11-22 02:33:53.980613: Pseudo dice [0.8319] +2024-11-22 02:33:53.980689: Epoch time: 18.2 s +2024-11-22 02:33:54.855381: +2024-11-22 02:33:54.855700: Epoch 2913 +2024-11-22 02:33:54.855823: Current learning rate: 0.00665 +2024-11-22 02:34:12.917286: train_loss -0.7765 +2024-11-22 02:34:12.917534: val_loss -0.7337 +2024-11-22 02:34:12.917632: Pseudo dice [0.8167] +2024-11-22 02:34:12.917718: Epoch time: 18.06 s +2024-11-22 02:34:14.167164: +2024-11-22 02:34:14.167369: Epoch 2914 +2024-11-22 02:34:14.167477: Current learning rate: 0.00665 +2024-11-22 02:34:32.888937: train_loss -0.7809 +2024-11-22 02:34:32.889182: val_loss -0.716 +2024-11-22 02:34:32.889256: Pseudo dice [0.8068] +2024-11-22 02:34:32.889332: Epoch time: 18.72 s +2024-11-22 02:34:33.861948: +2024-11-22 02:34:33.862256: Epoch 2915 +2024-11-22 02:34:33.862370: Current learning rate: 0.00665 +2024-11-22 02:34:52.568365: train_loss -0.7819 +2024-11-22 02:34:52.568581: val_loss -0.7627 +2024-11-22 02:34:52.568657: Pseudo dice [0.8204] +2024-11-22 02:34:52.568740: Epoch time: 18.71 s +2024-11-22 02:34:53.441066: +2024-11-22 02:34:53.441278: Epoch 2916 +2024-11-22 02:34:53.441390: Current learning rate: 0.00665 +2024-11-22 02:35:11.603953: train_loss -0.7785 +2024-11-22 02:35:11.604177: val_loss -0.7125 +2024-11-22 02:35:11.604255: Pseudo dice [0.8004] +2024-11-22 02:35:11.604331: Epoch time: 18.16 s +2024-11-22 02:35:12.480748: +2024-11-22 02:35:12.480987: Epoch 2917 +2024-11-22 02:35:12.481110: Current learning rate: 0.00665 +2024-11-22 02:35:30.345335: train_loss -0.7853 +2024-11-22 02:35:30.345605: val_loss -0.7561 +2024-11-22 02:35:30.345686: Pseudo dice [0.8272] +2024-11-22 02:35:30.345769: Epoch time: 17.87 s +2024-11-22 02:35:31.218444: +2024-11-22 02:35:31.218675: Epoch 2918 +2024-11-22 02:35:31.218804: Current learning rate: 0.00665 +2024-11-22 02:35:49.668077: train_loss -0.7805 +2024-11-22 02:35:49.670636: val_loss -0.7309 +2024-11-22 02:35:49.670749: Pseudo dice [0.8309] +2024-11-22 02:35:49.670828: Epoch time: 18.45 s +2024-11-22 02:35:50.576939: +2024-11-22 02:35:50.577136: Epoch 2919 +2024-11-22 02:35:50.577251: Current learning rate: 0.00665 +2024-11-22 02:36:08.894399: train_loss -0.7614 +2024-11-22 02:36:08.894619: val_loss -0.7369 +2024-11-22 02:36:08.894691: Pseudo dice [0.8168] +2024-11-22 02:36:08.915824: Epoch time: 18.32 s +2024-11-22 02:36:09.785589: +2024-11-22 02:36:09.785777: Epoch 2920 +2024-11-22 02:36:09.785890: Current learning rate: 0.00665 +2024-11-22 02:36:27.222830: train_loss -0.7721 +2024-11-22 02:36:27.223052: val_loss -0.7251 +2024-11-22 02:36:27.223127: Pseudo dice [0.8223] +2024-11-22 02:36:27.223208: Epoch time: 17.44 s +2024-11-22 02:36:28.096530: +2024-11-22 02:36:28.096757: Epoch 2921 +2024-11-22 02:36:28.096881: Current learning rate: 0.00664 +2024-11-22 02:36:47.120447: train_loss -0.7805 +2024-11-22 02:36:47.120698: val_loss -0.7381 +2024-11-22 02:36:47.120770: Pseudo dice [0.8349] +2024-11-22 02:36:47.120851: Epoch time: 19.02 s +2024-11-22 02:36:47.993224: +2024-11-22 02:36:47.993486: Epoch 2922 +2024-11-22 02:36:47.993599: Current learning rate: 0.00664 +2024-11-22 02:37:06.799128: train_loss -0.7733 +2024-11-22 02:37:06.799360: val_loss -0.7382 +2024-11-22 02:37:06.799433: Pseudo dice [0.8321] +2024-11-22 02:37:06.799508: Epoch time: 18.81 s +2024-11-22 02:37:07.779209: +2024-11-22 02:37:07.779418: Epoch 2923 +2024-11-22 02:37:07.779528: Current learning rate: 0.00664 +2024-11-22 02:37:25.130312: train_loss -0.7742 +2024-11-22 02:37:25.130536: val_loss -0.7468 +2024-11-22 02:37:25.130615: Pseudo dice [0.8349] +2024-11-22 02:37:25.130699: Epoch time: 17.35 s +2024-11-22 02:37:26.004160: +2024-11-22 02:37:26.004389: Epoch 2924 +2024-11-22 02:37:26.004513: Current learning rate: 0.00664 +2024-11-22 02:37:44.358490: train_loss -0.7764 +2024-11-22 02:37:44.358732: val_loss -0.7527 +2024-11-22 02:37:44.358807: Pseudo dice [0.8233] +2024-11-22 02:37:44.358887: Epoch time: 18.36 s +2024-11-22 02:37:45.227028: +2024-11-22 02:37:45.227239: Epoch 2925 +2024-11-22 02:37:45.227352: Current learning rate: 0.00664 +2024-11-22 02:38:03.798310: train_loss -0.784 +2024-11-22 02:38:03.798532: val_loss -0.744 +2024-11-22 02:38:03.798607: Pseudo dice [0.8161] +2024-11-22 02:38:03.798685: Epoch time: 18.57 s +2024-11-22 02:38:04.666651: +2024-11-22 02:38:04.666870: Epoch 2926 +2024-11-22 02:38:04.666986: Current learning rate: 0.00664 +2024-11-22 02:38:24.678249: train_loss -0.7842 +2024-11-22 02:38:24.678468: val_loss -0.7398 +2024-11-22 02:38:24.683706: Pseudo dice [0.8313] +2024-11-22 02:38:24.683850: Epoch time: 20.01 s +2024-11-22 02:38:25.652683: +2024-11-22 02:38:25.652886: Epoch 2927 +2024-11-22 02:38:25.653011: Current learning rate: 0.00664 +2024-11-22 02:38:43.886004: train_loss -0.7779 +2024-11-22 02:38:43.886258: val_loss -0.7442 +2024-11-22 02:38:43.886337: Pseudo dice [0.8227] +2024-11-22 02:38:43.886420: Epoch time: 18.23 s +2024-11-22 02:38:44.756586: +2024-11-22 02:38:44.756793: Epoch 2928 +2024-11-22 02:38:44.756906: Current learning rate: 0.00664 +2024-11-22 02:39:03.705348: train_loss -0.7711 +2024-11-22 02:39:03.705579: val_loss -0.7443 +2024-11-22 02:39:03.705658: Pseudo dice [0.8324] +2024-11-22 02:39:03.705745: Epoch time: 18.95 s +2024-11-22 02:39:04.680275: +2024-11-22 02:39:04.680495: Epoch 2929 +2024-11-22 02:39:04.680607: Current learning rate: 0.00663 +2024-11-22 02:39:23.054811: train_loss -0.7818 +2024-11-22 02:39:23.055062: val_loss -0.7617 +2024-11-22 02:39:23.055136: Pseudo dice [0.824] +2024-11-22 02:39:23.055212: Epoch time: 18.38 s +2024-11-22 02:39:23.925542: +2024-11-22 02:39:23.925750: Epoch 2930 +2024-11-22 02:39:23.925862: Current learning rate: 0.00663 +2024-11-22 02:39:42.505392: train_loss -0.7786 +2024-11-22 02:39:42.505657: val_loss -0.7191 +2024-11-22 02:39:42.505732: Pseudo dice [0.8298] +2024-11-22 02:39:42.505810: Epoch time: 18.58 s +2024-11-22 02:39:43.370028: +2024-11-22 02:39:43.370390: Epoch 2931 +2024-11-22 02:39:43.370507: Current learning rate: 0.00663 +2024-11-22 02:40:02.354187: train_loss -0.7777 +2024-11-22 02:40:02.354405: val_loss -0.7355 +2024-11-22 02:40:02.354481: Pseudo dice [0.8356] +2024-11-22 02:40:02.354558: Epoch time: 18.98 s +2024-11-22 02:40:03.219746: +2024-11-22 02:40:03.219937: Epoch 2932 +2024-11-22 02:40:03.220057: Current learning rate: 0.00663 +2024-11-22 02:40:21.329733: train_loss -0.7811 +2024-11-22 02:40:21.329974: val_loss -0.7186 +2024-11-22 02:40:21.330061: Pseudo dice [0.8165] +2024-11-22 02:40:21.330148: Epoch time: 18.11 s +2024-11-22 02:40:22.203532: +2024-11-22 02:40:22.203813: Epoch 2933 +2024-11-22 02:40:22.203937: Current learning rate: 0.00663 +2024-11-22 02:40:39.948295: train_loss -0.7762 +2024-11-22 02:40:39.948572: val_loss -0.7413 +2024-11-22 02:40:39.948649: Pseudo dice [0.8477] +2024-11-22 02:40:39.948726: Epoch time: 17.75 s +2024-11-22 02:40:40.817823: +2024-11-22 02:40:40.818058: Epoch 2934 +2024-11-22 02:40:40.818176: Current learning rate: 0.00663 +2024-11-22 02:40:58.951542: train_loss -0.7782 +2024-11-22 02:40:58.951763: val_loss -0.7395 +2024-11-22 02:40:58.951838: Pseudo dice [0.832] +2024-11-22 02:40:58.951915: Epoch time: 18.13 s +2024-11-22 02:40:59.838585: +2024-11-22 02:40:59.838808: Epoch 2935 +2024-11-22 02:40:59.838932: Current learning rate: 0.00663 +2024-11-22 02:41:19.048828: train_loss -0.7727 +2024-11-22 02:41:19.049075: val_loss -0.7447 +2024-11-22 02:41:19.049153: Pseudo dice [0.8208] +2024-11-22 02:41:19.049235: Epoch time: 19.21 s +2024-11-22 02:41:19.933243: +2024-11-22 02:41:19.933458: Epoch 2936 +2024-11-22 02:41:19.933576: Current learning rate: 0.00663 +2024-11-22 02:41:37.389714: train_loss -0.7841 +2024-11-22 02:41:37.389924: val_loss -0.7293 +2024-11-22 02:41:37.390007: Pseudo dice [0.8256] +2024-11-22 02:41:37.390087: Epoch time: 17.46 s +2024-11-22 02:41:38.634437: +2024-11-22 02:41:38.634663: Epoch 2937 +2024-11-22 02:41:38.634778: Current learning rate: 0.00663 +2024-11-22 02:41:57.214608: train_loss -0.779 +2024-11-22 02:41:57.214838: val_loss -0.7458 +2024-11-22 02:41:57.214912: Pseudo dice [0.8401] +2024-11-22 02:41:57.214986: Epoch time: 18.58 s +2024-11-22 02:41:58.086527: +2024-11-22 02:41:58.086838: Epoch 2938 +2024-11-22 02:41:58.086956: Current learning rate: 0.00662 +2024-11-22 02:42:16.288978: train_loss -0.7704 +2024-11-22 02:42:16.289229: val_loss -0.7488 +2024-11-22 02:42:16.289305: Pseudo dice [0.8116] +2024-11-22 02:42:16.289385: Epoch time: 18.2 s +2024-11-22 02:42:17.157182: +2024-11-22 02:42:17.157389: Epoch 2939 +2024-11-22 02:42:17.157501: Current learning rate: 0.00662 +2024-11-22 02:42:35.362651: train_loss -0.7797 +2024-11-22 02:42:35.362870: val_loss -0.7411 +2024-11-22 02:42:35.362945: Pseudo dice [0.8317] +2024-11-22 02:42:35.363025: Epoch time: 18.21 s +2024-11-22 02:42:36.229705: +2024-11-22 02:42:36.229965: Epoch 2940 +2024-11-22 02:42:36.230082: Current learning rate: 0.00662 +2024-11-22 02:42:54.655626: train_loss -0.7769 +2024-11-22 02:42:54.655848: val_loss -0.7501 +2024-11-22 02:42:54.655934: Pseudo dice [0.8358] +2024-11-22 02:42:54.656025: Epoch time: 18.43 s +2024-11-22 02:42:55.524133: +2024-11-22 02:42:55.524357: Epoch 2941 +2024-11-22 02:42:55.524467: Current learning rate: 0.00662 +2024-11-22 02:43:14.631857: train_loss -0.7843 +2024-11-22 02:43:14.632087: val_loss -0.7416 +2024-11-22 02:43:14.632162: Pseudo dice [0.8225] +2024-11-22 02:43:14.632239: Epoch time: 19.11 s +2024-11-22 02:43:15.600180: +2024-11-22 02:43:15.600385: Epoch 2942 +2024-11-22 02:43:15.600497: Current learning rate: 0.00662 +2024-11-22 02:43:33.909086: train_loss -0.7643 +2024-11-22 02:43:33.909349: val_loss -0.7204 +2024-11-22 02:43:33.909426: Pseudo dice [0.7948] +2024-11-22 02:43:33.909515: Epoch time: 18.31 s +2024-11-22 02:43:34.849478: +2024-11-22 02:43:34.849789: Epoch 2943 +2024-11-22 02:43:34.849910: Current learning rate: 0.00662 +2024-11-22 02:43:53.938801: train_loss -0.7629 +2024-11-22 02:43:53.939030: val_loss -0.707 +2024-11-22 02:43:53.939109: Pseudo dice [0.7999] +2024-11-22 02:43:53.939183: Epoch time: 19.09 s +2024-11-22 02:43:54.807308: +2024-11-22 02:43:54.807561: Epoch 2944 +2024-11-22 02:43:54.807677: Current learning rate: 0.00662 +2024-11-22 02:44:12.827103: train_loss -0.7559 +2024-11-22 02:44:12.827333: val_loss -0.7301 +2024-11-22 02:44:12.827414: Pseudo dice [0.8281] +2024-11-22 02:44:12.827501: Epoch time: 18.02 s +2024-11-22 02:44:13.697583: +2024-11-22 02:44:13.697764: Epoch 2945 +2024-11-22 02:44:13.697877: Current learning rate: 0.00662 +2024-11-22 02:44:32.583262: train_loss -0.7695 +2024-11-22 02:44:32.588651: val_loss -0.7453 +2024-11-22 02:44:32.588767: Pseudo dice [0.8338] +2024-11-22 02:44:32.588851: Epoch time: 18.89 s +2024-11-22 02:44:33.617892: +2024-11-22 02:44:33.618162: Epoch 2946 +2024-11-22 02:44:33.618275: Current learning rate: 0.00661 +2024-11-22 02:44:51.790023: train_loss -0.7668 +2024-11-22 02:44:51.790266: val_loss -0.7116 +2024-11-22 02:44:51.790340: Pseudo dice [0.7986] +2024-11-22 02:44:51.790422: Epoch time: 18.17 s +2024-11-22 02:44:52.660177: +2024-11-22 02:44:52.660376: Epoch 2947 +2024-11-22 02:44:52.660487: Current learning rate: 0.00661 +2024-11-22 02:45:11.213251: train_loss -0.7579 +2024-11-22 02:45:11.222836: val_loss -0.7391 +2024-11-22 02:45:11.222979: Pseudo dice [0.8375] +2024-11-22 02:45:11.223063: Epoch time: 18.55 s +2024-11-22 02:45:12.305223: +2024-11-22 02:45:12.305409: Epoch 2948 +2024-11-22 02:45:12.305525: Current learning rate: 0.00661 +2024-11-22 02:45:31.416064: train_loss -0.761 +2024-11-22 02:45:31.416281: val_loss -0.7307 +2024-11-22 02:45:31.416356: Pseudo dice [0.8224] +2024-11-22 02:45:31.416433: Epoch time: 19.11 s +2024-11-22 02:45:32.289279: +2024-11-22 02:45:32.289545: Epoch 2949 +2024-11-22 02:45:32.289655: Current learning rate: 0.00661 +2024-11-22 02:45:50.379695: train_loss -0.7622 +2024-11-22 02:45:50.379937: val_loss -0.7316 +2024-11-22 02:45:50.380019: Pseudo dice [0.8158] +2024-11-22 02:45:50.380112: Epoch time: 18.09 s +2024-11-22 02:45:51.472672: +2024-11-22 02:45:51.472887: Epoch 2950 +2024-11-22 02:45:51.473011: Current learning rate: 0.00661 +2024-11-22 02:46:10.428446: train_loss -0.77 +2024-11-22 02:46:10.428662: val_loss -0.7219 +2024-11-22 02:46:10.428739: Pseudo dice [0.7792] +2024-11-22 02:46:10.428815: Epoch time: 18.96 s +2024-11-22 02:46:11.298456: +2024-11-22 02:46:11.298717: Epoch 2951 +2024-11-22 02:46:11.298831: Current learning rate: 0.00661 +2024-11-22 02:46:30.557962: train_loss -0.7594 +2024-11-22 02:46:30.558215: val_loss -0.7437 +2024-11-22 02:46:30.558292: Pseudo dice [0.8178] +2024-11-22 02:46:30.558370: Epoch time: 19.26 s +2024-11-22 02:46:31.432276: +2024-11-22 02:46:31.432498: Epoch 2952 +2024-11-22 02:46:31.432615: Current learning rate: 0.00661 +2024-11-22 02:46:50.444420: train_loss -0.7581 +2024-11-22 02:46:50.444649: val_loss -0.754 +2024-11-22 02:46:50.449869: Pseudo dice [0.7969] +2024-11-22 02:46:50.450049: Epoch time: 19.01 s +2024-11-22 02:46:51.484705: +2024-11-22 02:46:51.484895: Epoch 2953 +2024-11-22 02:46:51.485007: Current learning rate: 0.00661 +2024-11-22 02:47:10.430356: train_loss -0.7676 +2024-11-22 02:47:10.430592: val_loss -0.7176 +2024-11-22 02:47:10.430667: Pseudo dice [0.8162] +2024-11-22 02:47:10.430746: Epoch time: 18.95 s +2024-11-22 02:47:11.344079: +2024-11-22 02:47:11.344275: Epoch 2954 +2024-11-22 02:47:11.344392: Current learning rate: 0.0066 +2024-11-22 02:47:29.618035: train_loss -0.7733 +2024-11-22 02:47:29.618258: val_loss -0.7305 +2024-11-22 02:47:29.618335: Pseudo dice [0.8094] +2024-11-22 02:47:29.618413: Epoch time: 18.27 s +2024-11-22 02:47:30.508568: +2024-11-22 02:47:30.508916: Epoch 2955 +2024-11-22 02:47:30.509034: Current learning rate: 0.0066 +2024-11-22 02:47:49.755931: train_loss -0.774 +2024-11-22 02:47:49.756166: val_loss -0.7244 +2024-11-22 02:47:49.756296: Pseudo dice [0.8166] +2024-11-22 02:47:49.756373: Epoch time: 19.25 s +2024-11-22 02:47:50.615872: +2024-11-22 02:47:50.616079: Epoch 2956 +2024-11-22 02:47:50.616191: Current learning rate: 0.0066 +2024-11-22 02:48:09.212823: train_loss -0.7807 +2024-11-22 02:48:09.213113: val_loss -0.7131 +2024-11-22 02:48:09.213196: Pseudo dice [0.7937] +2024-11-22 02:48:09.213289: Epoch time: 18.59 s +2024-11-22 02:48:10.272537: +2024-11-22 02:48:10.272724: Epoch 2957 +2024-11-22 02:48:10.272831: Current learning rate: 0.0066 +2024-11-22 02:48:29.681150: train_loss -0.7809 +2024-11-22 02:48:29.681359: val_loss -0.7593 +2024-11-22 02:48:29.681511: Pseudo dice [0.8314] +2024-11-22 02:48:29.681589: Epoch time: 19.41 s +2024-11-22 02:48:30.536312: +2024-11-22 02:48:30.536515: Epoch 2958 +2024-11-22 02:48:30.536627: Current learning rate: 0.0066 +2024-11-22 02:48:48.950248: train_loss -0.7818 +2024-11-22 02:48:48.950469: val_loss -0.7369 +2024-11-22 02:48:48.950541: Pseudo dice [0.8036] +2024-11-22 02:48:48.950618: Epoch time: 18.41 s +2024-11-22 02:48:49.873520: +2024-11-22 02:48:49.873705: Epoch 2959 +2024-11-22 02:48:49.873812: Current learning rate: 0.0066 +2024-11-22 02:49:08.836321: train_loss -0.7816 +2024-11-22 02:49:08.836533: val_loss -0.7043 +2024-11-22 02:49:08.836607: Pseudo dice [0.8308] +2024-11-22 02:49:08.836707: Epoch time: 18.96 s +2024-11-22 02:49:09.688245: +2024-11-22 02:49:09.688502: Epoch 2960 +2024-11-22 02:49:09.688611: Current learning rate: 0.0066 +2024-11-22 02:49:28.219647: train_loss -0.7875 +2024-11-22 02:49:28.219895: val_loss -0.7127 +2024-11-22 02:49:28.220042: Pseudo dice [0.8179] +2024-11-22 02:49:28.220128: Epoch time: 18.53 s +2024-11-22 02:49:29.092816: +2024-11-22 02:49:29.093021: Epoch 2961 +2024-11-22 02:49:29.093124: Current learning rate: 0.0066 +2024-11-22 02:49:48.327927: train_loss -0.7881 +2024-11-22 02:49:48.328155: val_loss -0.7552 +2024-11-22 02:49:48.328235: Pseudo dice [0.8427] +2024-11-22 02:49:48.328322: Epoch time: 19.24 s +2024-11-22 02:49:49.198812: +2024-11-22 02:49:49.199053: Epoch 2962 +2024-11-22 02:49:49.199171: Current learning rate: 0.0066 +2024-11-22 02:50:09.130059: train_loss -0.7644 +2024-11-22 02:50:09.130308: val_loss -0.7333 +2024-11-22 02:50:09.130384: Pseudo dice [0.8192] +2024-11-22 02:50:09.130469: Epoch time: 19.93 s +2024-11-22 02:50:10.095774: +2024-11-22 02:50:10.096006: Epoch 2963 +2024-11-22 02:50:10.096131: Current learning rate: 0.00659 +2024-11-22 02:50:28.543002: train_loss -0.7822 +2024-11-22 02:50:28.543225: val_loss -0.7296 +2024-11-22 02:50:28.543300: Pseudo dice [0.8158] +2024-11-22 02:50:28.543377: Epoch time: 18.45 s +2024-11-22 02:50:29.416713: +2024-11-22 02:50:29.416924: Epoch 2964 +2024-11-22 02:50:29.417036: Current learning rate: 0.00659 +2024-11-22 02:50:48.156549: train_loss -0.7743 +2024-11-22 02:50:48.159233: val_loss -0.7549 +2024-11-22 02:50:48.159327: Pseudo dice [0.8137] +2024-11-22 02:50:48.159405: Epoch time: 18.74 s +2024-11-22 02:50:49.061246: +2024-11-22 02:50:49.061466: Epoch 2965 +2024-11-22 02:50:49.061697: Current learning rate: 0.00659 +2024-11-22 02:51:07.493167: train_loss -0.7829 +2024-11-22 02:51:07.493398: val_loss -0.742 +2024-11-22 02:51:07.493473: Pseudo dice [0.8133] +2024-11-22 02:51:07.495726: Epoch time: 18.43 s +2024-11-22 02:51:08.459251: +2024-11-22 02:51:08.459479: Epoch 2966 +2024-11-22 02:51:08.459590: Current learning rate: 0.00659 +2024-11-22 02:51:27.126474: train_loss -0.776 +2024-11-22 02:51:27.126760: val_loss -0.7431 +2024-11-22 02:51:27.126838: Pseudo dice [0.8132] +2024-11-22 02:51:27.126918: Epoch time: 18.67 s +2024-11-22 02:51:28.006644: +2024-11-22 02:51:28.006961: Epoch 2967 +2024-11-22 02:51:28.007072: Current learning rate: 0.00659 +2024-11-22 02:51:46.705760: train_loss -0.7846 +2024-11-22 02:51:46.706017: val_loss -0.7521 +2024-11-22 02:51:46.706091: Pseudo dice [0.8281] +2024-11-22 02:51:46.706172: Epoch time: 18.7 s +2024-11-22 02:51:47.581883: +2024-11-22 02:51:47.582080: Epoch 2968 +2024-11-22 02:51:47.582193: Current learning rate: 0.00659 +2024-11-22 02:52:06.030943: train_loss -0.7863 +2024-11-22 02:52:06.031174: val_loss -0.7409 +2024-11-22 02:52:06.031254: Pseudo dice [0.8447] +2024-11-22 02:52:06.031333: Epoch time: 18.45 s +2024-11-22 02:52:07.066386: +2024-11-22 02:52:07.066618: Epoch 2969 +2024-11-22 02:52:07.066745: Current learning rate: 0.00659 +2024-11-22 02:52:25.282662: train_loss -0.7835 +2024-11-22 02:52:25.284889: val_loss -0.7341 +2024-11-22 02:52:25.284983: Pseudo dice [0.8262] +2024-11-22 02:52:25.285068: Epoch time: 18.22 s +2024-11-22 02:52:26.206350: +2024-11-22 02:52:26.206566: Epoch 2970 +2024-11-22 02:52:26.206677: Current learning rate: 0.00659 +2024-11-22 02:52:44.950610: train_loss -0.7448 +2024-11-22 02:52:44.950833: val_loss -0.7496 +2024-11-22 02:52:44.950909: Pseudo dice [0.8234] +2024-11-22 02:52:44.950989: Epoch time: 18.75 s +2024-11-22 02:52:46.274497: +2024-11-22 02:52:46.274715: Epoch 2971 +2024-11-22 02:52:46.274832: Current learning rate: 0.00658 +2024-11-22 02:53:05.038118: train_loss -0.7583 +2024-11-22 02:53:05.038359: val_loss -0.7214 +2024-11-22 02:53:05.038435: Pseudo dice [0.8086] +2024-11-22 02:53:05.038514: Epoch time: 18.76 s +2024-11-22 02:53:05.923759: +2024-11-22 02:53:05.923965: Epoch 2972 +2024-11-22 02:53:05.924087: Current learning rate: 0.00658 +2024-11-22 02:53:23.881719: train_loss -0.7636 +2024-11-22 02:53:23.881946: val_loss -0.7444 +2024-11-22 02:53:23.882026: Pseudo dice [0.8219] +2024-11-22 02:53:23.882101: Epoch time: 17.96 s +2024-11-22 02:53:24.747977: +2024-11-22 02:53:24.748214: Epoch 2973 +2024-11-22 02:53:24.748333: Current learning rate: 0.00658 +2024-11-22 02:53:42.862059: train_loss -0.7619 +2024-11-22 02:53:42.862281: val_loss -0.7637 +2024-11-22 02:53:42.862358: Pseudo dice [0.8384] +2024-11-22 02:53:42.862436: Epoch time: 18.11 s +2024-11-22 02:53:43.730424: +2024-11-22 02:53:43.730638: Epoch 2974 +2024-11-22 02:53:43.730750: Current learning rate: 0.00658 +2024-11-22 02:54:02.778942: train_loss -0.7758 +2024-11-22 02:54:02.779195: val_loss -0.7769 +2024-11-22 02:54:02.779305: Pseudo dice [0.8428] +2024-11-22 02:54:02.779394: Epoch time: 19.05 s +2024-11-22 02:54:03.651922: +2024-11-22 02:54:03.652132: Epoch 2975 +2024-11-22 02:54:03.652245: Current learning rate: 0.00658 +2024-11-22 02:54:23.195118: train_loss -0.77 +2024-11-22 02:54:23.195400: val_loss -0.7385 +2024-11-22 02:54:23.195478: Pseudo dice [0.8389] +2024-11-22 02:54:23.195557: Epoch time: 19.54 s +2024-11-22 02:54:24.152205: +2024-11-22 02:54:24.152411: Epoch 2976 +2024-11-22 02:54:24.152521: Current learning rate: 0.00658 +2024-11-22 02:54:42.550079: train_loss -0.7687 +2024-11-22 02:54:42.550290: val_loss -0.7109 +2024-11-22 02:54:42.550361: Pseudo dice [0.8038] +2024-11-22 02:54:42.550434: Epoch time: 18.4 s +2024-11-22 02:54:43.415837: +2024-11-22 02:54:43.416054: Epoch 2977 +2024-11-22 02:54:43.416171: Current learning rate: 0.00658 +2024-11-22 02:55:01.996907: train_loss -0.7448 +2024-11-22 02:55:01.997142: val_loss -0.7141 +2024-11-22 02:55:01.997218: Pseudo dice [0.8006] +2024-11-22 02:55:01.997295: Epoch time: 18.58 s +2024-11-22 02:55:02.876841: +2024-11-22 02:55:02.877034: Epoch 2978 +2024-11-22 02:55:02.877147: Current learning rate: 0.00658 +2024-11-22 02:55:21.088711: train_loss -0.7699 +2024-11-22 02:55:21.088967: val_loss -0.7456 +2024-11-22 02:55:21.089048: Pseudo dice [0.8264] +2024-11-22 02:55:21.094285: Epoch time: 18.21 s +2024-11-22 02:55:22.103916: +2024-11-22 02:55:22.104219: Epoch 2979 +2024-11-22 02:55:22.104336: Current learning rate: 0.00658 +2024-11-22 02:55:40.754036: train_loss -0.7849 +2024-11-22 02:55:40.754259: val_loss -0.7343 +2024-11-22 02:55:40.754334: Pseudo dice [0.8131] +2024-11-22 02:55:40.754409: Epoch time: 18.65 s +2024-11-22 02:55:41.631128: +2024-11-22 02:55:41.631318: Epoch 2980 +2024-11-22 02:55:41.631433: Current learning rate: 0.00657 +2024-11-22 02:56:00.365909: train_loss -0.7741 +2024-11-22 02:56:00.366132: val_loss -0.714 +2024-11-22 02:56:00.366208: Pseudo dice [0.823] +2024-11-22 02:56:00.366282: Epoch time: 18.74 s +2024-11-22 02:56:01.230443: +2024-11-22 02:56:01.230633: Epoch 2981 +2024-11-22 02:56:01.230743: Current learning rate: 0.00657 +2024-11-22 02:56:20.772863: train_loss -0.7716 +2024-11-22 02:56:20.773088: val_loss -0.7525 +2024-11-22 02:56:20.773162: Pseudo dice [0.8216] +2024-11-22 02:56:20.773238: Epoch time: 19.54 s +2024-11-22 02:56:21.647676: +2024-11-22 02:56:21.647898: Epoch 2982 +2024-11-22 02:56:21.648053: Current learning rate: 0.00657 +2024-11-22 02:56:40.248798: train_loss -0.7783 +2024-11-22 02:56:40.249655: val_loss -0.7508 +2024-11-22 02:56:40.249736: Pseudo dice [0.8191] +2024-11-22 02:56:40.249814: Epoch time: 18.6 s +2024-11-22 02:56:41.124032: +2024-11-22 02:56:41.124270: Epoch 2983 +2024-11-22 02:56:41.124387: Current learning rate: 0.00657 +2024-11-22 02:56:59.705563: train_loss -0.7731 +2024-11-22 02:56:59.705783: val_loss -0.7539 +2024-11-22 02:56:59.705860: Pseudo dice [0.8294] +2024-11-22 02:56:59.705938: Epoch time: 18.58 s +2024-11-22 02:57:00.576399: +2024-11-22 02:57:00.576620: Epoch 2984 +2024-11-22 02:57:00.576736: Current learning rate: 0.00657 +2024-11-22 02:57:19.575313: train_loss -0.7854 +2024-11-22 02:57:19.575531: val_loss -0.7453 +2024-11-22 02:57:19.575608: Pseudo dice [0.8423] +2024-11-22 02:57:19.575684: Epoch time: 19.0 s +2024-11-22 02:57:20.446939: +2024-11-22 02:57:20.447155: Epoch 2985 +2024-11-22 02:57:20.447265: Current learning rate: 0.00657 +2024-11-22 02:57:38.558146: train_loss -0.7871 +2024-11-22 02:57:38.558387: val_loss -0.7399 +2024-11-22 02:57:38.558459: Pseudo dice [0.8166] +2024-11-22 02:57:38.558538: Epoch time: 18.11 s +2024-11-22 02:57:39.431393: +2024-11-22 02:57:39.431626: Epoch 2986 +2024-11-22 02:57:39.431737: Current learning rate: 0.00657 +2024-11-22 02:57:57.779128: train_loss -0.7859 +2024-11-22 02:57:57.779395: val_loss -0.7308 +2024-11-22 02:57:57.779470: Pseudo dice [0.8322] +2024-11-22 02:57:57.779546: Epoch time: 18.35 s +2024-11-22 02:57:58.653630: +2024-11-22 02:57:58.653835: Epoch 2987 +2024-11-22 02:57:58.653950: Current learning rate: 0.00657 +2024-11-22 02:58:16.642502: train_loss -0.7757 +2024-11-22 02:58:16.642726: val_loss -0.7202 +2024-11-22 02:58:16.642807: Pseudo dice [0.8263] +2024-11-22 02:58:16.642882: Epoch time: 17.99 s +2024-11-22 02:58:17.510553: +2024-11-22 02:58:17.510762: Epoch 2988 +2024-11-22 02:58:17.510878: Current learning rate: 0.00656 +2024-11-22 02:58:36.729798: train_loss -0.7828 +2024-11-22 02:58:36.730034: val_loss -0.7716 +2024-11-22 02:58:36.732308: Pseudo dice [0.8501] +2024-11-22 02:58:36.732476: Epoch time: 19.22 s +2024-11-22 02:58:37.685524: +2024-11-22 02:58:37.685745: Epoch 2989 +2024-11-22 02:58:37.685851: Current learning rate: 0.00656 +2024-11-22 02:58:56.436720: train_loss -0.7851 +2024-11-22 02:58:56.436968: val_loss -0.7301 +2024-11-22 02:58:56.437048: Pseudo dice [0.8162] +2024-11-22 02:58:56.437130: Epoch time: 18.75 s +2024-11-22 02:58:57.313808: +2024-11-22 02:58:57.314018: Epoch 2990 +2024-11-22 02:58:57.314138: Current learning rate: 0.00656 +2024-11-22 02:59:17.097771: train_loss -0.7778 +2024-11-22 02:59:17.098015: val_loss -0.7275 +2024-11-22 02:59:17.098093: Pseudo dice [0.819] +2024-11-22 02:59:17.098173: Epoch time: 19.78 s +2024-11-22 02:59:17.970672: +2024-11-22 02:59:17.970903: Epoch 2991 +2024-11-22 02:59:17.971600: Current learning rate: 0.00656 +2024-11-22 02:59:36.490450: train_loss -0.7836 +2024-11-22 02:59:36.490675: val_loss -0.7348 +2024-11-22 02:59:36.490748: Pseudo dice [0.8152] +2024-11-22 02:59:36.490824: Epoch time: 18.52 s +2024-11-22 02:59:37.363869: +2024-11-22 02:59:37.364095: Epoch 2992 +2024-11-22 02:59:37.364214: Current learning rate: 0.00656 +2024-11-22 02:59:55.867426: train_loss -0.7807 +2024-11-22 02:59:55.867672: val_loss -0.748 +2024-11-22 02:59:55.867746: Pseudo dice [0.8434] +2024-11-22 02:59:55.867829: Epoch time: 18.5 s +2024-11-22 02:59:56.737894: +2024-11-22 02:59:56.738121: Epoch 2993 +2024-11-22 02:59:56.738241: Current learning rate: 0.00656 +2024-11-22 03:00:15.093909: train_loss -0.7829 +2024-11-22 03:00:15.094266: val_loss -0.7398 +2024-11-22 03:00:15.094347: Pseudo dice [0.8238] +2024-11-22 03:00:15.094427: Epoch time: 18.36 s +2024-11-22 03:00:16.335834: +2024-11-22 03:00:16.336066: Epoch 2994 +2024-11-22 03:00:16.336184: Current learning rate: 0.00656 +2024-11-22 03:00:35.745805: train_loss -0.7792 +2024-11-22 03:00:35.746044: val_loss -0.7298 +2024-11-22 03:00:35.746120: Pseudo dice [0.8065] +2024-11-22 03:00:35.746197: Epoch time: 19.41 s +2024-11-22 03:00:36.617876: +2024-11-22 03:00:36.618084: Epoch 2995 +2024-11-22 03:00:36.618219: Current learning rate: 0.00656 +2024-11-22 03:00:54.229906: train_loss -0.7903 +2024-11-22 03:00:54.230153: val_loss -0.7444 +2024-11-22 03:00:54.230233: Pseudo dice [0.8341] +2024-11-22 03:00:54.230315: Epoch time: 17.61 s +2024-11-22 03:00:55.102319: +2024-11-22 03:00:55.102587: Epoch 2996 +2024-11-22 03:00:55.102725: Current learning rate: 0.00656 +2024-11-22 03:01:12.677559: train_loss -0.7886 +2024-11-22 03:01:12.677784: val_loss -0.7504 +2024-11-22 03:01:12.677860: Pseudo dice [0.8346] +2024-11-22 03:01:12.677940: Epoch time: 17.58 s +2024-11-22 03:01:13.547006: +2024-11-22 03:01:13.547206: Epoch 2997 +2024-11-22 03:01:13.547320: Current learning rate: 0.00655 +2024-11-22 03:01:33.054566: train_loss -0.7928 +2024-11-22 03:01:33.054782: val_loss -0.7293 +2024-11-22 03:01:33.054854: Pseudo dice [0.8236] +2024-11-22 03:01:33.054929: Epoch time: 19.51 s +2024-11-22 03:01:33.934138: +2024-11-22 03:01:33.934370: Epoch 2998 +2024-11-22 03:01:33.934491: Current learning rate: 0.00655 +2024-11-22 03:01:53.166725: train_loss -0.7882 +2024-11-22 03:01:53.166963: val_loss -0.7523 +2024-11-22 03:01:53.167047: Pseudo dice [0.8215] +2024-11-22 03:01:53.167127: Epoch time: 19.23 s +2024-11-22 03:01:54.148973: +2024-11-22 03:01:54.149229: Epoch 2999 +2024-11-22 03:01:54.149345: Current learning rate: 0.00655 +2024-11-22 03:02:12.395492: train_loss -0.7604 +2024-11-22 03:02:12.395823: val_loss -0.7164 +2024-11-22 03:02:12.395906: Pseudo dice [0.8174] +2024-11-22 03:02:12.396002: Epoch time: 18.25 s +2024-11-22 03:02:13.517256: +2024-11-22 03:02:13.517518: Epoch 3000 +2024-11-22 03:02:13.517630: Current learning rate: 0.00655 +2024-11-22 03:02:32.365707: train_loss -0.761 +2024-11-22 03:02:32.365922: val_loss -0.7032 +2024-11-22 03:02:32.366005: Pseudo dice [0.8052] +2024-11-22 03:02:32.366090: Epoch time: 18.85 s +2024-11-22 03:02:33.231501: +2024-11-22 03:02:33.231707: Epoch 3001 +2024-11-22 03:02:33.231817: Current learning rate: 0.00655 +2024-11-22 03:02:52.906836: train_loss -0.77 +2024-11-22 03:02:52.907129: val_loss -0.7416 +2024-11-22 03:02:52.907212: Pseudo dice [0.822] +2024-11-22 03:02:52.907299: Epoch time: 19.68 s +2024-11-22 03:02:53.777056: +2024-11-22 03:02:53.777250: Epoch 3002 +2024-11-22 03:02:53.777362: Current learning rate: 0.00655 +2024-11-22 03:03:11.674630: train_loss -0.7815 +2024-11-22 03:03:11.674849: val_loss -0.7326 +2024-11-22 03:03:11.674926: Pseudo dice [0.8414] +2024-11-22 03:03:11.675008: Epoch time: 17.9 s +2024-11-22 03:03:12.549314: +2024-11-22 03:03:12.549534: Epoch 3003 +2024-11-22 03:03:12.549662: Current learning rate: 0.00655 +2024-11-22 03:03:31.323242: train_loss -0.7751 +2024-11-22 03:03:31.323479: val_loss -0.7396 +2024-11-22 03:03:31.323551: Pseudo dice [0.8337] +2024-11-22 03:03:31.323631: Epoch time: 18.77 s +2024-11-22 03:03:32.199712: +2024-11-22 03:03:32.199924: Epoch 3004 +2024-11-22 03:03:32.200047: Current learning rate: 0.00655 +2024-11-22 03:03:50.871663: train_loss -0.7854 +2024-11-22 03:03:50.871942: val_loss -0.7413 +2024-11-22 03:03:50.872024: Pseudo dice [0.8366] +2024-11-22 03:03:50.872101: Epoch time: 18.67 s +2024-11-22 03:03:51.742803: +2024-11-22 03:03:51.743013: Epoch 3005 +2024-11-22 03:03:51.743125: Current learning rate: 0.00654 +2024-11-22 03:04:10.460133: train_loss -0.7859 +2024-11-22 03:04:10.460712: val_loss -0.7315 +2024-11-22 03:04:10.460815: Pseudo dice [0.8247] +2024-11-22 03:04:10.460892: Epoch time: 18.72 s +2024-11-22 03:04:11.329576: +2024-11-22 03:04:11.329775: Epoch 3006 +2024-11-22 03:04:11.329887: Current learning rate: 0.00654 +2024-11-22 03:04:30.160900: train_loss -0.787 +2024-11-22 03:04:30.161158: val_loss -0.7469 +2024-11-22 03:04:30.161236: Pseudo dice [0.8241] +2024-11-22 03:04:30.161323: Epoch time: 18.83 s +2024-11-22 03:04:31.035224: +2024-11-22 03:04:31.035429: Epoch 3007 +2024-11-22 03:04:31.035538: Current learning rate: 0.00654 +2024-11-22 03:04:49.673110: train_loss -0.7815 +2024-11-22 03:04:49.673399: val_loss -0.7463 +2024-11-22 03:04:49.673482: Pseudo dice [0.8292] +2024-11-22 03:04:49.673562: Epoch time: 18.64 s +2024-11-22 03:04:50.543456: +2024-11-22 03:04:50.543663: Epoch 3008 +2024-11-22 03:04:50.543773: Current learning rate: 0.00654 +2024-11-22 03:05:08.773212: train_loss -0.7813 +2024-11-22 03:05:08.773424: val_loss -0.7489 +2024-11-22 03:05:08.773500: Pseudo dice [0.8247] +2024-11-22 03:05:08.773575: Epoch time: 18.23 s +2024-11-22 03:05:09.648011: +2024-11-22 03:05:09.648194: Epoch 3009 +2024-11-22 03:05:09.648338: Current learning rate: 0.00654 +2024-11-22 03:05:29.650452: train_loss -0.774 +2024-11-22 03:05:29.650749: val_loss -0.7557 +2024-11-22 03:05:29.650825: Pseudo dice [0.8419] +2024-11-22 03:05:29.650906: Epoch time: 20.0 s +2024-11-22 03:05:30.525097: +2024-11-22 03:05:30.525332: Epoch 3010 +2024-11-22 03:05:30.525454: Current learning rate: 0.00654 +2024-11-22 03:05:49.521825: train_loss -0.7852 +2024-11-22 03:05:49.527187: val_loss -0.7631 +2024-11-22 03:05:49.527295: Pseudo dice [0.8338] +2024-11-22 03:05:49.527373: Epoch time: 19.0 s +2024-11-22 03:05:50.565319: +2024-11-22 03:05:50.565526: Epoch 3011 +2024-11-22 03:05:50.565640: Current learning rate: 0.00654 +2024-11-22 03:06:09.892330: train_loss -0.783 +2024-11-22 03:06:09.892548: val_loss -0.746 +2024-11-22 03:06:09.892625: Pseudo dice [0.8213] +2024-11-22 03:06:09.892702: Epoch time: 19.33 s +2024-11-22 03:06:10.761743: +2024-11-22 03:06:10.761961: Epoch 3012 +2024-11-22 03:06:10.762082: Current learning rate: 0.00654 +2024-11-22 03:06:29.298320: train_loss -0.7774 +2024-11-22 03:06:29.298540: val_loss -0.7472 +2024-11-22 03:06:29.298618: Pseudo dice [0.8353] +2024-11-22 03:06:29.298696: Epoch time: 18.54 s +2024-11-22 03:06:30.170240: +2024-11-22 03:06:30.170439: Epoch 3013 +2024-11-22 03:06:30.170564: Current learning rate: 0.00654 +2024-11-22 03:06:48.845907: train_loss -0.7838 +2024-11-22 03:06:48.846193: val_loss -0.7521 +2024-11-22 03:06:48.846272: Pseudo dice [0.8369] +2024-11-22 03:06:48.846362: Epoch time: 18.68 s +2024-11-22 03:06:49.758492: +2024-11-22 03:06:49.758688: Epoch 3014 +2024-11-22 03:06:49.758804: Current learning rate: 0.00653 +2024-11-22 03:07:08.516681: train_loss -0.7771 +2024-11-22 03:07:08.516902: val_loss -0.7565 +2024-11-22 03:07:08.516977: Pseudo dice [0.826] +2024-11-22 03:07:08.517059: Epoch time: 18.76 s +2024-11-22 03:07:09.450258: +2024-11-22 03:07:09.450452: Epoch 3015 +2024-11-22 03:07:09.450562: Current learning rate: 0.00653 +2024-11-22 03:07:28.389742: train_loss -0.7839 +2024-11-22 03:07:28.389945: val_loss -0.748 +2024-11-22 03:07:28.390033: Pseudo dice [0.8314] +2024-11-22 03:07:28.390106: Epoch time: 18.94 s +2024-11-22 03:07:29.463792: +2024-11-22 03:07:29.463978: Epoch 3016 +2024-11-22 03:07:29.464095: Current learning rate: 0.00653 +2024-11-22 03:07:48.943547: train_loss -0.7762 +2024-11-22 03:07:48.943770: val_loss -0.7176 +2024-11-22 03:07:48.943844: Pseudo dice [0.8191] +2024-11-22 03:07:48.943922: Epoch time: 19.48 s +2024-11-22 03:07:50.229765: +2024-11-22 03:07:50.230048: Epoch 3017 +2024-11-22 03:07:50.230177: Current learning rate: 0.00653 +2024-11-22 03:08:09.397451: train_loss -0.7783 +2024-11-22 03:08:09.397679: val_loss -0.7387 +2024-11-22 03:08:09.397751: Pseudo dice [0.8392] +2024-11-22 03:08:09.397830: Epoch time: 19.17 s +2024-11-22 03:08:10.298400: +2024-11-22 03:08:10.298641: Epoch 3018 +2024-11-22 03:08:10.298753: Current learning rate: 0.00653 +2024-11-22 03:08:28.863866: train_loss -0.7791 +2024-11-22 03:08:28.864089: val_loss -0.753 +2024-11-22 03:08:28.864167: Pseudo dice [0.8254] +2024-11-22 03:08:28.864249: Epoch time: 18.57 s +2024-11-22 03:08:29.733311: +2024-11-22 03:08:29.733531: Epoch 3019 +2024-11-22 03:08:29.733649: Current learning rate: 0.00653 +2024-11-22 03:08:48.208894: train_loss -0.7803 +2024-11-22 03:08:48.209119: val_loss -0.7469 +2024-11-22 03:08:48.209194: Pseudo dice [0.8127] +2024-11-22 03:08:48.209273: Epoch time: 18.48 s +2024-11-22 03:08:49.083512: +2024-11-22 03:08:49.083722: Epoch 3020 +2024-11-22 03:08:49.083840: Current learning rate: 0.00653 +2024-11-22 03:09:07.153096: train_loss -0.7811 +2024-11-22 03:09:07.153340: val_loss -0.724 +2024-11-22 03:09:07.153420: Pseudo dice [0.8141] +2024-11-22 03:09:07.153506: Epoch time: 18.07 s +2024-11-22 03:09:08.023863: +2024-11-22 03:09:08.024093: Epoch 3021 +2024-11-22 03:09:08.024212: Current learning rate: 0.00653 +2024-11-22 03:09:26.892207: train_loss -0.7726 +2024-11-22 03:09:26.893654: val_loss -0.7539 +2024-11-22 03:09:26.893759: Pseudo dice [0.8286] +2024-11-22 03:09:26.893833: Epoch time: 18.87 s +2024-11-22 03:09:27.839025: +2024-11-22 03:09:27.839218: Epoch 3022 +2024-11-22 03:09:27.839328: Current learning rate: 0.00652 +2024-11-22 03:09:46.469498: train_loss -0.7731 +2024-11-22 03:09:46.474126: val_loss -0.742 +2024-11-22 03:09:46.474253: Pseudo dice [0.8348] +2024-11-22 03:09:46.474334: Epoch time: 18.63 s +2024-11-22 03:09:47.465188: +2024-11-22 03:09:47.465386: Epoch 3023 +2024-11-22 03:09:47.465499: Current learning rate: 0.00652 +2024-11-22 03:10:06.454484: train_loss -0.7785 +2024-11-22 03:10:06.454708: val_loss -0.7539 +2024-11-22 03:10:06.454785: Pseudo dice [0.8331] +2024-11-22 03:10:06.454870: Epoch time: 18.99 s +2024-11-22 03:10:07.327866: +2024-11-22 03:10:07.328070: Epoch 3024 +2024-11-22 03:10:07.328185: Current learning rate: 0.00652 +2024-11-22 03:10:25.791033: train_loss -0.7596 +2024-11-22 03:10:25.791277: val_loss -0.7283 +2024-11-22 03:10:25.791353: Pseudo dice [0.8133] +2024-11-22 03:10:25.791439: Epoch time: 18.46 s +2024-11-22 03:10:26.766998: +2024-11-22 03:10:26.767203: Epoch 3025 +2024-11-22 03:10:26.767315: Current learning rate: 0.00652 +2024-11-22 03:10:44.437805: train_loss -0.7577 +2024-11-22 03:10:44.438021: val_loss -0.7341 +2024-11-22 03:10:44.438095: Pseudo dice [0.8221] +2024-11-22 03:10:44.438170: Epoch time: 17.67 s +2024-11-22 03:10:45.310927: +2024-11-22 03:10:45.311151: Epoch 3026 +2024-11-22 03:10:45.311265: Current learning rate: 0.00652 +2024-11-22 03:11:03.928645: train_loss -0.7608 +2024-11-22 03:11:03.928857: val_loss -0.7614 +2024-11-22 03:11:03.928933: Pseudo dice [0.8235] +2024-11-22 03:11:03.929015: Epoch time: 18.62 s +2024-11-22 03:11:04.804466: +2024-11-22 03:11:04.804663: Epoch 3027 +2024-11-22 03:11:04.804778: Current learning rate: 0.00652 +2024-11-22 03:11:23.336300: train_loss -0.7668 +2024-11-22 03:11:23.336544: val_loss -0.7537 +2024-11-22 03:11:23.336619: Pseudo dice [0.818] +2024-11-22 03:11:23.336704: Epoch time: 18.53 s +2024-11-22 03:11:24.229925: +2024-11-22 03:11:24.230137: Epoch 3028 +2024-11-22 03:11:24.230251: Current learning rate: 0.00652 +2024-11-22 03:11:41.586487: train_loss -0.7704 +2024-11-22 03:11:41.586959: val_loss -0.7515 +2024-11-22 03:11:41.587064: Pseudo dice [0.8322] +2024-11-22 03:11:41.587143: Epoch time: 17.36 s +2024-11-22 03:11:42.454242: +2024-11-22 03:11:42.454532: Epoch 3029 +2024-11-22 03:11:42.454646: Current learning rate: 0.00652 +2024-11-22 03:12:00.625557: train_loss -0.7724 +2024-11-22 03:12:00.625777: val_loss -0.736 +2024-11-22 03:12:00.625852: Pseudo dice [0.824] +2024-11-22 03:12:00.625933: Epoch time: 18.17 s +2024-11-22 03:12:01.493411: +2024-11-22 03:12:01.493632: Epoch 3030 +2024-11-22 03:12:01.493742: Current learning rate: 0.00652 +2024-11-22 03:12:20.123441: train_loss -0.7686 +2024-11-22 03:12:20.123692: val_loss -0.7147 +2024-11-22 03:12:20.123771: Pseudo dice [0.7995] +2024-11-22 03:12:20.123855: Epoch time: 18.63 s +2024-11-22 03:12:20.994570: +2024-11-22 03:12:20.994786: Epoch 3031 +2024-11-22 03:12:20.994898: Current learning rate: 0.00651 +2024-11-22 03:12:40.716791: train_loss -0.7654 +2024-11-22 03:12:40.717021: val_loss -0.7498 +2024-11-22 03:12:40.717097: Pseudo dice [0.8307] +2024-11-22 03:12:40.717173: Epoch time: 19.72 s +2024-11-22 03:12:41.883973: +2024-11-22 03:12:41.884191: Epoch 3032 +2024-11-22 03:12:41.884306: Current learning rate: 0.00651 +2024-11-22 03:13:00.902504: train_loss -0.7699 +2024-11-22 03:13:00.902729: val_loss -0.7413 +2024-11-22 03:13:00.902807: Pseudo dice [0.819] +2024-11-22 03:13:00.902890: Epoch time: 19.02 s +2024-11-22 03:13:01.776490: +2024-11-22 03:13:01.776704: Epoch 3033 +2024-11-22 03:13:01.776822: Current learning rate: 0.00651 +2024-11-22 03:13:21.817954: train_loss -0.7772 +2024-11-22 03:13:21.818181: val_loss -0.731 +2024-11-22 03:13:21.818253: Pseudo dice [0.8247] +2024-11-22 03:13:21.818329: Epoch time: 20.04 s +2024-11-22 03:13:22.714945: +2024-11-22 03:13:22.715810: Epoch 3034 +2024-11-22 03:13:22.715922: Current learning rate: 0.00651 +2024-11-22 03:13:40.118894: train_loss -0.7822 +2024-11-22 03:13:40.119150: val_loss -0.7497 +2024-11-22 03:13:40.119229: Pseudo dice [0.841] +2024-11-22 03:13:40.119315: Epoch time: 17.4 s +2024-11-22 03:13:40.992503: +2024-11-22 03:13:40.992761: Epoch 3035 +2024-11-22 03:13:40.992874: Current learning rate: 0.00651 +2024-11-22 03:13:59.260905: train_loss -0.7782 +2024-11-22 03:13:59.261137: val_loss -0.7448 +2024-11-22 03:13:59.261210: Pseudo dice [0.8286] +2024-11-22 03:13:59.261290: Epoch time: 18.27 s +2024-11-22 03:14:00.135799: +2024-11-22 03:14:00.136039: Epoch 3036 +2024-11-22 03:14:00.136150: Current learning rate: 0.00651 +2024-11-22 03:14:18.645412: train_loss -0.7756 +2024-11-22 03:14:18.645698: val_loss -0.7486 +2024-11-22 03:14:18.645774: Pseudo dice [0.8267] +2024-11-22 03:14:18.645852: Epoch time: 18.51 s +2024-11-22 03:14:19.511055: +2024-11-22 03:14:19.511271: Epoch 3037 +2024-11-22 03:14:19.511386: Current learning rate: 0.00651 +2024-11-22 03:14:38.157052: train_loss -0.787 +2024-11-22 03:14:38.157266: val_loss -0.7471 +2024-11-22 03:14:38.157361: Pseudo dice [0.8193] +2024-11-22 03:14:38.157438: Epoch time: 18.65 s +2024-11-22 03:14:39.069220: +2024-11-22 03:14:39.069491: Epoch 3038 +2024-11-22 03:14:39.069608: Current learning rate: 0.00651 +2024-11-22 03:14:57.749869: train_loss -0.7787 +2024-11-22 03:14:57.750148: val_loss -0.7148 +2024-11-22 03:14:57.750223: Pseudo dice [0.8197] +2024-11-22 03:14:57.750303: Epoch time: 18.68 s +2024-11-22 03:14:58.651265: +2024-11-22 03:14:58.651470: Epoch 3039 +2024-11-22 03:14:58.651584: Current learning rate: 0.0065 +2024-11-22 03:15:17.745780: train_loss -0.7793 +2024-11-22 03:15:17.746389: val_loss -0.7583 +2024-11-22 03:15:17.746495: Pseudo dice [0.8409] +2024-11-22 03:15:17.746572: Epoch time: 19.1 s +2024-11-22 03:15:18.995733: +2024-11-22 03:15:18.995941: Epoch 3040 +2024-11-22 03:15:18.996058: Current learning rate: 0.0065 +2024-11-22 03:15:38.398359: train_loss -0.7808 +2024-11-22 03:15:38.398572: val_loss -0.7527 +2024-11-22 03:15:38.398644: Pseudo dice [0.8251] +2024-11-22 03:15:38.400919: Epoch time: 19.4 s +2024-11-22 03:15:39.327230: +2024-11-22 03:15:39.327467: Epoch 3041 +2024-11-22 03:15:39.327627: Current learning rate: 0.0065 +2024-11-22 03:15:58.586850: train_loss -0.7809 +2024-11-22 03:15:58.587137: val_loss -0.7589 +2024-11-22 03:15:58.587212: Pseudo dice [0.8332] +2024-11-22 03:15:58.587291: Epoch time: 19.26 s +2024-11-22 03:15:59.458847: +2024-11-22 03:15:59.459080: Epoch 3042 +2024-11-22 03:15:59.459196: Current learning rate: 0.0065 +2024-11-22 03:16:18.478976: train_loss -0.7741 +2024-11-22 03:16:18.479203: val_loss -0.7611 +2024-11-22 03:16:18.479279: Pseudo dice [0.8299] +2024-11-22 03:16:18.479356: Epoch time: 19.02 s +2024-11-22 03:16:19.352346: +2024-11-22 03:16:19.352535: Epoch 3043 +2024-11-22 03:16:19.352649: Current learning rate: 0.0065 +2024-11-22 03:16:38.585461: train_loss -0.7761 +2024-11-22 03:16:38.585678: val_loss -0.727 +2024-11-22 03:16:38.585754: Pseudo dice [0.807] +2024-11-22 03:16:38.585832: Epoch time: 19.23 s +2024-11-22 03:16:39.454640: +2024-11-22 03:16:39.454889: Epoch 3044 +2024-11-22 03:16:39.455016: Current learning rate: 0.0065 +2024-11-22 03:16:57.936789: train_loss -0.7793 +2024-11-22 03:16:57.937043: val_loss -0.7647 +2024-11-22 03:16:57.937122: Pseudo dice [0.8205] +2024-11-22 03:16:57.937204: Epoch time: 18.48 s +2024-11-22 03:16:58.808110: +2024-11-22 03:16:58.808314: Epoch 3045 +2024-11-22 03:16:58.808429: Current learning rate: 0.0065 +2024-11-22 03:17:18.148506: train_loss -0.7761 +2024-11-22 03:17:18.150280: val_loss -0.7195 +2024-11-22 03:17:18.150401: Pseudo dice [0.8353] +2024-11-22 03:17:18.150483: Epoch time: 19.34 s +2024-11-22 03:17:19.051809: +2024-11-22 03:17:19.052016: Epoch 3046 +2024-11-22 03:17:19.052133: Current learning rate: 0.0065 +2024-11-22 03:17:38.884513: train_loss -0.7719 +2024-11-22 03:17:38.884767: val_loss -0.7532 +2024-11-22 03:17:38.884901: Pseudo dice [0.8289] +2024-11-22 03:17:38.886698: Epoch time: 19.83 s +2024-11-22 03:17:39.761698: +2024-11-22 03:17:39.761881: Epoch 3047 +2024-11-22 03:17:39.762000: Current learning rate: 0.0065 +2024-11-22 03:17:59.735415: train_loss -0.7728 +2024-11-22 03:17:59.735633: val_loss -0.7385 +2024-11-22 03:17:59.735710: Pseudo dice [0.8075] +2024-11-22 03:17:59.735789: Epoch time: 19.97 s +2024-11-22 03:18:00.608494: +2024-11-22 03:18:00.608701: Epoch 3048 +2024-11-22 03:18:00.608817: Current learning rate: 0.00649 +2024-11-22 03:18:20.038122: train_loss -0.781 +2024-11-22 03:18:20.038378: val_loss -0.7494 +2024-11-22 03:18:20.038456: Pseudo dice [0.831] +2024-11-22 03:18:20.038571: Epoch time: 19.43 s +2024-11-22 03:18:20.913093: +2024-11-22 03:18:20.913394: Epoch 3049 +2024-11-22 03:18:20.913530: Current learning rate: 0.00649 +2024-11-22 03:18:39.498287: train_loss -0.789 +2024-11-22 03:18:39.498507: val_loss -0.7573 +2024-11-22 03:18:39.498582: Pseudo dice [0.8343] +2024-11-22 03:18:39.498658: Epoch time: 18.59 s +2024-11-22 03:18:40.597725: +2024-11-22 03:18:40.597975: Epoch 3050 +2024-11-22 03:18:40.598097: Current learning rate: 0.00649 +2024-11-22 03:19:00.231599: train_loss -0.7858 +2024-11-22 03:19:00.231827: val_loss -0.7676 +2024-11-22 03:19:00.231900: Pseudo dice [0.8408] +2024-11-22 03:19:00.231975: Epoch time: 19.63 s +2024-11-22 03:19:01.162547: +2024-11-22 03:19:01.162767: Epoch 3051 +2024-11-22 03:19:01.162879: Current learning rate: 0.00649 +2024-11-22 03:19:19.505954: train_loss -0.7805 +2024-11-22 03:19:19.506472: val_loss -0.7481 +2024-11-22 03:19:19.506627: Pseudo dice [0.8274] +2024-11-22 03:19:19.506713: Epoch time: 18.34 s +2024-11-22 03:19:20.372278: +2024-11-22 03:19:20.372508: Epoch 3052 +2024-11-22 03:19:20.372622: Current learning rate: 0.00649 +2024-11-22 03:19:39.020593: train_loss -0.7814 +2024-11-22 03:19:39.020817: val_loss -0.7548 +2024-11-22 03:19:39.020892: Pseudo dice [0.8242] +2024-11-22 03:19:39.020970: Epoch time: 18.65 s +2024-11-22 03:19:39.888508: +2024-11-22 03:19:39.888742: Epoch 3053 +2024-11-22 03:19:39.888853: Current learning rate: 0.00649 +2024-11-22 03:19:58.250217: train_loss -0.7789 +2024-11-22 03:19:58.250433: val_loss -0.7552 +2024-11-22 03:19:58.250511: Pseudo dice [0.8195] +2024-11-22 03:19:58.250594: Epoch time: 18.36 s +2024-11-22 03:19:59.121813: +2024-11-22 03:19:59.122047: Epoch 3054 +2024-11-22 03:19:59.122160: Current learning rate: 0.00649 +2024-11-22 03:20:17.683762: train_loss -0.7854 +2024-11-22 03:20:17.686173: val_loss -0.7366 +2024-11-22 03:20:17.686259: Pseudo dice [0.826] +2024-11-22 03:20:17.686342: Epoch time: 18.56 s +2024-11-22 03:20:18.785447: +2024-11-22 03:20:18.785675: Epoch 3055 +2024-11-22 03:20:18.785788: Current learning rate: 0.00649 +2024-11-22 03:20:36.979635: train_loss -0.7854 +2024-11-22 03:20:36.979856: val_loss -0.7382 +2024-11-22 03:20:36.979931: Pseudo dice [0.8083] +2024-11-22 03:20:36.985174: Epoch time: 18.2 s +2024-11-22 03:20:37.862088: +2024-11-22 03:20:37.862292: Epoch 3056 +2024-11-22 03:20:37.862405: Current learning rate: 0.00648 +2024-11-22 03:20:57.017230: train_loss -0.7827 +2024-11-22 03:20:57.017450: val_loss -0.7378 +2024-11-22 03:20:57.017524: Pseudo dice [0.8149] +2024-11-22 03:20:57.017597: Epoch time: 19.16 s +2024-11-22 03:20:57.886628: +2024-11-22 03:20:57.886842: Epoch 3057 +2024-11-22 03:20:57.886956: Current learning rate: 0.00648 +2024-11-22 03:21:16.579711: train_loss -0.7892 +2024-11-22 03:21:16.579932: val_loss -0.7305 +2024-11-22 03:21:16.582128: Pseudo dice [0.8235] +2024-11-22 03:21:16.582210: Epoch time: 18.69 s +2024-11-22 03:21:17.483334: +2024-11-22 03:21:17.483639: Epoch 3058 +2024-11-22 03:21:17.483767: Current learning rate: 0.00648 +2024-11-22 03:21:35.829152: train_loss -0.7694 +2024-11-22 03:21:35.829393: val_loss -0.7559 +2024-11-22 03:21:35.829467: Pseudo dice [0.8206] +2024-11-22 03:21:35.829551: Epoch time: 18.35 s +2024-11-22 03:21:36.698880: +2024-11-22 03:21:36.699153: Epoch 3059 +2024-11-22 03:21:36.699261: Current learning rate: 0.00648 +2024-11-22 03:21:55.518555: train_loss -0.7656 +2024-11-22 03:21:55.519091: val_loss -0.7393 +2024-11-22 03:21:55.519169: Pseudo dice [0.8099] +2024-11-22 03:21:55.519244: Epoch time: 18.82 s +2024-11-22 03:21:56.385723: +2024-11-22 03:21:56.385932: Epoch 3060 +2024-11-22 03:21:56.386049: Current learning rate: 0.00648 +2024-11-22 03:22:14.863299: train_loss -0.7752 +2024-11-22 03:22:14.863540: val_loss -0.7573 +2024-11-22 03:22:14.863620: Pseudo dice [0.8418] +2024-11-22 03:22:14.863695: Epoch time: 18.48 s +2024-11-22 03:22:15.727768: +2024-11-22 03:22:15.728004: Epoch 3061 +2024-11-22 03:22:15.728131: Current learning rate: 0.00648 +2024-11-22 03:22:35.022467: train_loss -0.7785 +2024-11-22 03:22:35.022708: val_loss -0.6987 +2024-11-22 03:22:35.022782: Pseudo dice [0.7851] +2024-11-22 03:22:35.022872: Epoch time: 19.3 s +2024-11-22 03:22:35.897032: +2024-11-22 03:22:35.897227: Epoch 3062 +2024-11-22 03:22:35.897336: Current learning rate: 0.00648 +2024-11-22 03:22:55.261916: train_loss -0.7648 +2024-11-22 03:22:55.262195: val_loss -0.7119 +2024-11-22 03:22:55.262275: Pseudo dice [0.8148] +2024-11-22 03:22:55.262357: Epoch time: 19.37 s +2024-11-22 03:22:56.552349: +2024-11-22 03:22:56.552569: Epoch 3063 +2024-11-22 03:22:56.552687: Current learning rate: 0.00648 +2024-11-22 03:23:15.120863: train_loss -0.7759 +2024-11-22 03:23:15.121095: val_loss -0.7328 +2024-11-22 03:23:15.121169: Pseudo dice [0.8231] +2024-11-22 03:23:15.121246: Epoch time: 18.57 s +2024-11-22 03:23:15.989545: +2024-11-22 03:23:15.989766: Epoch 3064 +2024-11-22 03:23:15.989881: Current learning rate: 0.00648 +2024-11-22 03:23:34.424876: train_loss -0.7707 +2024-11-22 03:23:34.425124: val_loss -0.7489 +2024-11-22 03:23:34.425204: Pseudo dice [0.82] +2024-11-22 03:23:34.425278: Epoch time: 18.44 s +2024-11-22 03:23:35.300207: +2024-11-22 03:23:35.300526: Epoch 3065 +2024-11-22 03:23:35.300654: Current learning rate: 0.00647 +2024-11-22 03:23:54.717658: train_loss -0.7671 +2024-11-22 03:23:54.717887: val_loss -0.7675 +2024-11-22 03:23:54.717965: Pseudo dice [0.8265] +2024-11-22 03:23:54.718052: Epoch time: 19.42 s +2024-11-22 03:23:55.588958: +2024-11-22 03:23:55.589234: Epoch 3066 +2024-11-22 03:23:55.589347: Current learning rate: 0.00647 +2024-11-22 03:24:14.037720: train_loss -0.7701 +2024-11-22 03:24:14.037934: val_loss -0.7661 +2024-11-22 03:24:14.038018: Pseudo dice [0.8373] +2024-11-22 03:24:14.038098: Epoch time: 18.45 s +2024-11-22 03:24:14.914092: +2024-11-22 03:24:14.914313: Epoch 3067 +2024-11-22 03:24:14.914430: Current learning rate: 0.00647 +2024-11-22 03:24:33.376581: train_loss -0.7683 +2024-11-22 03:24:33.376816: val_loss -0.7143 +2024-11-22 03:24:33.376891: Pseudo dice [0.8201] +2024-11-22 03:24:33.376973: Epoch time: 18.46 s +2024-11-22 03:24:34.250721: +2024-11-22 03:24:34.250956: Epoch 3068 +2024-11-22 03:24:34.251072: Current learning rate: 0.00647 +2024-11-22 03:24:52.483798: train_loss -0.7874 +2024-11-22 03:24:52.484042: val_loss -0.7444 +2024-11-22 03:24:52.484119: Pseudo dice [0.8236] +2024-11-22 03:24:52.484200: Epoch time: 18.23 s +2024-11-22 03:24:53.357569: +2024-11-22 03:24:53.357852: Epoch 3069 +2024-11-22 03:24:53.357970: Current learning rate: 0.00647 +2024-11-22 03:25:12.187225: train_loss -0.7801 +2024-11-22 03:25:12.187485: val_loss -0.7298 +2024-11-22 03:25:12.187637: Pseudo dice [0.8254] +2024-11-22 03:25:12.187725: Epoch time: 18.83 s +2024-11-22 03:25:13.062301: +2024-11-22 03:25:13.062506: Epoch 3070 +2024-11-22 03:25:13.062619: Current learning rate: 0.00647 +2024-11-22 03:25:32.896612: train_loss -0.7706 +2024-11-22 03:25:32.896842: val_loss -0.7187 +2024-11-22 03:25:32.896924: Pseudo dice [0.8069] +2024-11-22 03:25:32.897009: Epoch time: 19.84 s +2024-11-22 03:25:33.766363: +2024-11-22 03:25:33.766641: Epoch 3071 +2024-11-22 03:25:33.766758: Current learning rate: 0.00647 +2024-11-22 03:25:52.879341: train_loss -0.7773 +2024-11-22 03:25:52.879556: val_loss -0.7654 +2024-11-22 03:25:52.879630: Pseudo dice [0.8288] +2024-11-22 03:25:52.879704: Epoch time: 19.11 s +2024-11-22 03:25:53.759258: +2024-11-22 03:25:53.759473: Epoch 3072 +2024-11-22 03:25:53.759855: Current learning rate: 0.00647 +2024-11-22 03:26:11.901234: train_loss -0.7788 +2024-11-22 03:26:11.901477: val_loss -0.7178 +2024-11-22 03:26:11.901561: Pseudo dice [0.8149] +2024-11-22 03:26:11.901649: Epoch time: 18.14 s +2024-11-22 03:26:12.774666: +2024-11-22 03:26:12.774896: Epoch 3073 +2024-11-22 03:26:12.775024: Current learning rate: 0.00646 +2024-11-22 03:26:31.174884: train_loss -0.7895 +2024-11-22 03:26:31.175110: val_loss -0.7637 +2024-11-22 03:26:31.175186: Pseudo dice [0.8215] +2024-11-22 03:26:31.175265: Epoch time: 18.4 s +2024-11-22 03:26:32.042356: +2024-11-22 03:26:32.042560: Epoch 3074 +2024-11-22 03:26:32.042669: Current learning rate: 0.00646 +2024-11-22 03:26:50.987295: train_loss -0.7795 +2024-11-22 03:26:50.987864: val_loss -0.7322 +2024-11-22 03:26:50.987967: Pseudo dice [0.8192] +2024-11-22 03:26:50.988058: Epoch time: 18.95 s +2024-11-22 03:26:51.899249: +2024-11-22 03:26:51.899455: Epoch 3075 +2024-11-22 03:26:51.899567: Current learning rate: 0.00646 +2024-11-22 03:27:11.354316: train_loss -0.7728 +2024-11-22 03:27:11.354564: val_loss -0.7399 +2024-11-22 03:27:11.354640: Pseudo dice [0.8209] +2024-11-22 03:27:11.354725: Epoch time: 19.46 s +2024-11-22 03:27:12.310586: +2024-11-22 03:27:12.310826: Epoch 3076 +2024-11-22 03:27:12.310943: Current learning rate: 0.00646 +2024-11-22 03:27:30.686547: train_loss -0.7805 +2024-11-22 03:27:30.686763: val_loss -0.7403 +2024-11-22 03:27:30.686858: Pseudo dice [0.8234] +2024-11-22 03:27:30.686939: Epoch time: 18.38 s +2024-11-22 03:27:31.561680: +2024-11-22 03:27:31.561894: Epoch 3077 +2024-11-22 03:27:31.562013: Current learning rate: 0.00646 +2024-11-22 03:27:50.009358: train_loss -0.7772 +2024-11-22 03:27:50.009581: val_loss -0.734 +2024-11-22 03:27:50.009700: Pseudo dice [0.8176] +2024-11-22 03:27:50.009781: Epoch time: 18.45 s +2024-11-22 03:27:50.889321: +2024-11-22 03:27:50.889605: Epoch 3078 +2024-11-22 03:27:50.889722: Current learning rate: 0.00646 +2024-11-22 03:28:09.193609: train_loss -0.7821 +2024-11-22 03:28:09.193847: val_loss -0.7461 +2024-11-22 03:28:09.193929: Pseudo dice [0.8142] +2024-11-22 03:28:09.194020: Epoch time: 18.31 s +2024-11-22 03:28:10.063473: +2024-11-22 03:28:10.063699: Epoch 3079 +2024-11-22 03:28:10.063818: Current learning rate: 0.00646 +2024-11-22 03:28:27.912317: train_loss -0.7883 +2024-11-22 03:28:27.912536: val_loss -0.7542 +2024-11-22 03:28:27.912612: Pseudo dice [0.8303] +2024-11-22 03:28:27.912689: Epoch time: 17.85 s +2024-11-22 03:28:28.848778: +2024-11-22 03:28:28.848983: Epoch 3080 +2024-11-22 03:28:28.849102: Current learning rate: 0.00646 +2024-11-22 03:28:46.882712: train_loss -0.7901 +2024-11-22 03:28:46.882938: val_loss -0.7674 +2024-11-22 03:28:46.883019: Pseudo dice [0.838] +2024-11-22 03:28:46.883096: Epoch time: 18.03 s +2024-11-22 03:28:47.825465: +2024-11-22 03:28:47.825686: Epoch 3081 +2024-11-22 03:28:47.825806: Current learning rate: 0.00646 +2024-11-22 03:29:07.001667: train_loss -0.7911 +2024-11-22 03:29:07.001877: val_loss -0.7441 +2024-11-22 03:29:07.004186: Pseudo dice [0.8287] +2024-11-22 03:29:07.004348: Epoch time: 19.18 s +2024-11-22 03:29:07.886149: +2024-11-22 03:29:07.886341: Epoch 3082 +2024-11-22 03:29:07.886450: Current learning rate: 0.00645 +2024-11-22 03:29:27.054876: train_loss -0.7903 +2024-11-22 03:29:27.055142: val_loss -0.7657 +2024-11-22 03:29:27.057444: Pseudo dice [0.8385] +2024-11-22 03:29:27.057551: Epoch time: 19.17 s +2024-11-22 03:29:28.099396: +2024-11-22 03:29:28.099605: Epoch 3083 +2024-11-22 03:29:28.099722: Current learning rate: 0.00645 +2024-11-22 03:29:45.667475: train_loss -0.7882 +2024-11-22 03:29:45.667700: val_loss -0.7528 +2024-11-22 03:29:45.667776: Pseudo dice [0.8248] +2024-11-22 03:29:45.667854: Epoch time: 17.57 s +2024-11-22 03:29:46.535563: +2024-11-22 03:29:46.535909: Epoch 3084 +2024-11-22 03:29:46.536027: Current learning rate: 0.00645 +2024-11-22 03:30:05.620703: train_loss -0.7815 +2024-11-22 03:30:05.620918: val_loss -0.7513 +2024-11-22 03:30:05.620997: Pseudo dice [0.8313] +2024-11-22 03:30:05.621072: Epoch time: 19.09 s +2024-11-22 03:30:06.516441: +2024-11-22 03:30:06.516655: Epoch 3085 +2024-11-22 03:30:06.516767: Current learning rate: 0.00645 +2024-11-22 03:30:25.296836: train_loss -0.7883 +2024-11-22 03:30:25.297098: val_loss -0.7372 +2024-11-22 03:30:25.297175: Pseudo dice [0.8308] +2024-11-22 03:30:25.297257: Epoch time: 18.78 s +2024-11-22 03:30:26.727319: +2024-11-22 03:30:26.727518: Epoch 3086 +2024-11-22 03:30:26.727655: Current learning rate: 0.00645 +2024-11-22 03:30:45.092362: train_loss -0.7862 +2024-11-22 03:30:45.092593: val_loss -0.7467 +2024-11-22 03:30:45.092672: Pseudo dice [0.8317] +2024-11-22 03:30:45.092750: Epoch time: 18.37 s +2024-11-22 03:30:45.959411: +2024-11-22 03:30:45.959697: Epoch 3087 +2024-11-22 03:30:45.959811: Current learning rate: 0.00645 +2024-11-22 03:31:04.700165: train_loss -0.7841 +2024-11-22 03:31:04.700389: val_loss -0.7569 +2024-11-22 03:31:04.700465: Pseudo dice [0.8411] +2024-11-22 03:31:04.700543: Epoch time: 18.74 s +2024-11-22 03:31:05.566986: +2024-11-22 03:31:05.567209: Epoch 3088 +2024-11-22 03:31:05.567324: Current learning rate: 0.00645 +2024-11-22 03:31:24.942148: train_loss -0.7773 +2024-11-22 03:31:24.942384: val_loss -0.7385 +2024-11-22 03:31:24.942461: Pseudo dice [0.8183] +2024-11-22 03:31:24.942557: Epoch time: 19.38 s +2024-11-22 03:31:25.816782: +2024-11-22 03:31:25.816973: Epoch 3089 +2024-11-22 03:31:25.817110: Current learning rate: 0.00645 +2024-11-22 03:31:44.797282: train_loss -0.7765 +2024-11-22 03:31:44.799653: val_loss -0.7366 +2024-11-22 03:31:44.799737: Pseudo dice [0.8159] +2024-11-22 03:31:44.799816: Epoch time: 18.98 s +2024-11-22 03:31:45.725434: +2024-11-22 03:31:45.725638: Epoch 3090 +2024-11-22 03:31:45.725752: Current learning rate: 0.00644 +2024-11-22 03:32:05.069824: train_loss -0.7824 +2024-11-22 03:32:05.070050: val_loss -0.7491 +2024-11-22 03:32:05.070128: Pseudo dice [0.8262] +2024-11-22 03:32:05.070204: Epoch time: 19.35 s +2024-11-22 03:32:05.942072: +2024-11-22 03:32:05.942278: Epoch 3091 +2024-11-22 03:32:05.942397: Current learning rate: 0.00644 +2024-11-22 03:32:24.701888: train_loss -0.7897 +2024-11-22 03:32:24.702167: val_loss -0.7525 +2024-11-22 03:32:24.702246: Pseudo dice [0.8343] +2024-11-22 03:32:24.702323: Epoch time: 18.76 s +2024-11-22 03:32:25.571244: +2024-11-22 03:32:25.571455: Epoch 3092 +2024-11-22 03:32:25.571564: Current learning rate: 0.00644 +2024-11-22 03:32:44.229077: train_loss -0.782 +2024-11-22 03:32:44.229305: val_loss -0.7644 +2024-11-22 03:32:44.229383: Pseudo dice [0.8293] +2024-11-22 03:32:44.229465: Epoch time: 18.66 s +2024-11-22 03:32:45.100555: +2024-11-22 03:32:45.100769: Epoch 3093 +2024-11-22 03:32:45.100885: Current learning rate: 0.00644 +2024-11-22 03:33:03.500068: train_loss -0.7808 +2024-11-22 03:33:03.500306: val_loss -0.7434 +2024-11-22 03:33:03.500376: Pseudo dice [0.8159] +2024-11-22 03:33:03.500455: Epoch time: 18.4 s +2024-11-22 03:33:04.514070: +2024-11-22 03:33:04.514289: Epoch 3094 +2024-11-22 03:33:04.514408: Current learning rate: 0.00644 +2024-11-22 03:33:23.126521: train_loss -0.7801 +2024-11-22 03:33:23.126724: val_loss -0.7474 +2024-11-22 03:33:23.126796: Pseudo dice [0.8406] +2024-11-22 03:33:23.127003: Epoch time: 18.61 s +2024-11-22 03:33:24.030794: +2024-11-22 03:33:24.031054: Epoch 3095 +2024-11-22 03:33:24.031166: Current learning rate: 0.00644 +2024-11-22 03:33:41.060808: train_loss -0.7851 +2024-11-22 03:33:41.061035: val_loss -0.735 +2024-11-22 03:33:41.061113: Pseudo dice [0.8233] +2024-11-22 03:33:41.061191: Epoch time: 17.03 s +2024-11-22 03:33:41.934983: +2024-11-22 03:33:41.935196: Epoch 3096 +2024-11-22 03:33:41.935307: Current learning rate: 0.00644 +2024-11-22 03:34:00.703123: train_loss -0.7845 +2024-11-22 03:34:00.703342: val_loss -0.7586 +2024-11-22 03:34:00.703432: Pseudo dice [0.8486] +2024-11-22 03:34:00.703513: Epoch time: 18.77 s +2024-11-22 03:34:01.573819: +2024-11-22 03:34:01.574063: Epoch 3097 +2024-11-22 03:34:01.574216: Current learning rate: 0.00644 +2024-11-22 03:34:21.350587: train_loss -0.7951 +2024-11-22 03:34:21.366746: val_loss -0.749 +2024-11-22 03:34:21.366871: Pseudo dice [0.8401] +2024-11-22 03:34:21.366954: Epoch time: 19.78 s +2024-11-22 03:34:22.235581: +2024-11-22 03:34:22.235868: Epoch 3098 +2024-11-22 03:34:22.235983: Current learning rate: 0.00644 +2024-11-22 03:34:41.648799: train_loss -0.7816 +2024-11-22 03:34:41.649025: val_loss -0.745 +2024-11-22 03:34:41.649101: Pseudo dice [0.8261] +2024-11-22 03:34:41.649177: Epoch time: 19.41 s +2024-11-22 03:34:42.521717: +2024-11-22 03:34:42.521960: Epoch 3099 +2024-11-22 03:34:42.522083: Current learning rate: 0.00643 +2024-11-22 03:35:01.702536: train_loss -0.7806 +2024-11-22 03:35:01.702749: val_loss -0.7442 +2024-11-22 03:35:01.702824: Pseudo dice [0.8145] +2024-11-22 03:35:01.702903: Epoch time: 19.18 s +2024-11-22 03:35:02.829721: +2024-11-22 03:35:02.829920: Epoch 3100 +2024-11-22 03:35:02.830042: Current learning rate: 0.00643 +2024-11-22 03:35:21.059975: train_loss -0.7871 +2024-11-22 03:35:21.060255: val_loss -0.7722 +2024-11-22 03:35:21.060334: Pseudo dice [0.8465] +2024-11-22 03:35:21.060416: Epoch time: 18.23 s +2024-11-22 03:35:21.940447: +2024-11-22 03:35:21.940691: Epoch 3101 +2024-11-22 03:35:21.940808: Current learning rate: 0.00643 +2024-11-22 03:35:41.031234: train_loss -0.7771 +2024-11-22 03:35:41.031450: val_loss -0.7464 +2024-11-22 03:35:41.031528: Pseudo dice [0.8357] +2024-11-22 03:35:41.031606: Epoch time: 19.09 s +2024-11-22 03:35:41.031667: Yayy! New best EMA pseudo Dice: 0.8307 +2024-11-22 03:35:42.131831: +2024-11-22 03:35:42.132058: Epoch 3102 +2024-11-22 03:35:42.132170: Current learning rate: 0.00643 +2024-11-22 03:36:01.260999: train_loss -0.7854 +2024-11-22 03:36:01.261210: val_loss -0.7428 +2024-11-22 03:36:01.261283: Pseudo dice [0.8157] +2024-11-22 03:36:01.261358: Epoch time: 19.13 s +2024-11-22 03:36:02.155477: +2024-11-22 03:36:02.155708: Epoch 3103 +2024-11-22 03:36:02.155830: Current learning rate: 0.00643 +2024-11-22 03:36:20.215508: train_loss -0.792 +2024-11-22 03:36:20.215731: val_loss -0.7398 +2024-11-22 03:36:20.215807: Pseudo dice [0.8265] +2024-11-22 03:36:20.215887: Epoch time: 18.06 s +2024-11-22 03:36:21.089709: +2024-11-22 03:36:21.089915: Epoch 3104 +2024-11-22 03:36:21.090034: Current learning rate: 0.00643 +2024-11-22 03:36:41.021641: train_loss -0.7838 +2024-11-22 03:36:41.023764: val_loss -0.7237 +2024-11-22 03:36:41.023878: Pseudo dice [0.8218] +2024-11-22 03:36:41.023963: Epoch time: 19.93 s +2024-11-22 03:36:41.925125: +2024-11-22 03:36:41.925344: Epoch 3105 +2024-11-22 03:36:41.925458: Current learning rate: 0.00643 +2024-11-22 03:37:01.013111: train_loss -0.7774 +2024-11-22 03:37:01.013314: val_loss -0.7444 +2024-11-22 03:37:01.013388: Pseudo dice [0.8363] +2024-11-22 03:37:01.013464: Epoch time: 19.09 s +2024-11-22 03:37:02.092024: +2024-11-22 03:37:02.092248: Epoch 3106 +2024-11-22 03:37:02.092365: Current learning rate: 0.00643 +2024-11-22 03:37:20.660167: train_loss -0.7687 +2024-11-22 03:37:20.660384: val_loss -0.7312 +2024-11-22 03:37:20.660459: Pseudo dice [0.8109] +2024-11-22 03:37:20.660534: Epoch time: 18.57 s +2024-11-22 03:37:21.528787: +2024-11-22 03:37:21.528976: Epoch 3107 +2024-11-22 03:37:21.529102: Current learning rate: 0.00642 +2024-11-22 03:37:41.218917: train_loss -0.7756 +2024-11-22 03:37:41.219196: val_loss -0.7498 +2024-11-22 03:37:41.219285: Pseudo dice [0.8188] +2024-11-22 03:37:41.219427: Epoch time: 19.69 s +2024-11-22 03:37:42.599284: +2024-11-22 03:37:42.599515: Epoch 3108 +2024-11-22 03:37:42.599633: Current learning rate: 0.00642 +2024-11-22 03:38:00.550251: train_loss -0.7871 +2024-11-22 03:38:00.550487: val_loss -0.7465 +2024-11-22 03:38:00.550564: Pseudo dice [0.8296] +2024-11-22 03:38:00.550644: Epoch time: 17.95 s +2024-11-22 03:38:01.512807: +2024-11-22 03:38:01.513051: Epoch 3109 +2024-11-22 03:38:01.513169: Current learning rate: 0.00642 +2024-11-22 03:38:19.628221: train_loss -0.7792 +2024-11-22 03:38:19.628434: val_loss -0.7232 +2024-11-22 03:38:19.628505: Pseudo dice [0.8243] +2024-11-22 03:38:19.628581: Epoch time: 18.12 s +2024-11-22 03:38:20.523551: +2024-11-22 03:38:20.542349: Epoch 3110 +2024-11-22 03:38:20.542489: Current learning rate: 0.00642 +2024-11-22 03:38:39.527117: train_loss -0.778 +2024-11-22 03:38:39.527341: val_loss -0.7777 +2024-11-22 03:38:39.527419: Pseudo dice [0.8351] +2024-11-22 03:38:39.527505: Epoch time: 19.0 s +2024-11-22 03:38:40.397783: +2024-11-22 03:38:40.398066: Epoch 3111 +2024-11-22 03:38:40.398180: Current learning rate: 0.00642 +2024-11-22 03:38:58.414152: train_loss -0.7891 +2024-11-22 03:38:58.414443: val_loss -0.7326 +2024-11-22 03:38:58.414524: Pseudo dice [0.8042] +2024-11-22 03:38:58.414605: Epoch time: 18.02 s +2024-11-22 03:38:59.284869: +2024-11-22 03:38:59.285084: Epoch 3112 +2024-11-22 03:38:59.285197: Current learning rate: 0.00642 +2024-11-22 03:39:17.151551: train_loss -0.786 +2024-11-22 03:39:17.151802: val_loss -0.7489 +2024-11-22 03:39:17.151879: Pseudo dice [0.8187] +2024-11-22 03:39:17.152001: Epoch time: 17.87 s +2024-11-22 03:39:18.025103: +2024-11-22 03:39:18.025326: Epoch 3113 +2024-11-22 03:39:18.025439: Current learning rate: 0.00642 +2024-11-22 03:39:37.730944: train_loss -0.7786 +2024-11-22 03:39:37.731602: val_loss -0.7397 +2024-11-22 03:39:37.731718: Pseudo dice [0.8213] +2024-11-22 03:39:37.731799: Epoch time: 19.71 s +2024-11-22 03:39:38.603501: +2024-11-22 03:39:38.603703: Epoch 3114 +2024-11-22 03:39:38.603818: Current learning rate: 0.00642 +2024-11-22 03:39:56.215830: train_loss -0.7859 +2024-11-22 03:39:56.216082: val_loss -0.7275 +2024-11-22 03:39:56.216158: Pseudo dice [0.8315] +2024-11-22 03:39:56.216240: Epoch time: 17.61 s +2024-11-22 03:39:57.210739: +2024-11-22 03:39:57.211047: Epoch 3115 +2024-11-22 03:39:57.211165: Current learning rate: 0.00642 +2024-11-22 03:40:16.325387: train_loss -0.7826 +2024-11-22 03:40:16.325601: val_loss -0.7181 +2024-11-22 03:40:16.325673: Pseudo dice [0.8087] +2024-11-22 03:40:16.325749: Epoch time: 19.12 s +2024-11-22 03:40:17.239428: +2024-11-22 03:40:17.239648: Epoch 3116 +2024-11-22 03:40:17.239768: Current learning rate: 0.00641 +2024-11-22 03:40:36.503117: train_loss -0.7759 +2024-11-22 03:40:36.503337: val_loss -0.7453 +2024-11-22 03:40:36.503413: Pseudo dice [0.8155] +2024-11-22 03:40:36.503488: Epoch time: 19.26 s +2024-11-22 03:40:37.376604: +2024-11-22 03:40:37.376920: Epoch 3117 +2024-11-22 03:40:37.377042: Current learning rate: 0.00641 +2024-11-22 03:40:56.380749: train_loss -0.7823 +2024-11-22 03:40:56.380960: val_loss -0.7474 +2024-11-22 03:40:56.381043: Pseudo dice [0.8137] +2024-11-22 03:40:56.381119: Epoch time: 19.0 s +2024-11-22 03:40:57.471858: +2024-11-22 03:40:57.472073: Epoch 3118 +2024-11-22 03:40:57.472186: Current learning rate: 0.00641 +2024-11-22 03:41:16.272466: train_loss -0.7781 +2024-11-22 03:41:16.272700: val_loss -0.7449 +2024-11-22 03:41:16.272775: Pseudo dice [0.8361] +2024-11-22 03:41:16.274960: Epoch time: 18.8 s +2024-11-22 03:41:17.169966: +2024-11-22 03:41:17.170171: Epoch 3119 +2024-11-22 03:41:17.170282: Current learning rate: 0.00641 +2024-11-22 03:41:36.118314: train_loss -0.7801 +2024-11-22 03:41:36.118521: val_loss -0.7482 +2024-11-22 03:41:36.118595: Pseudo dice [0.8209] +2024-11-22 03:41:36.118670: Epoch time: 18.95 s +2024-11-22 03:41:37.376678: +2024-11-22 03:41:37.376884: Epoch 3120 +2024-11-22 03:41:37.377003: Current learning rate: 0.00641 +2024-11-22 03:41:56.525633: train_loss -0.7787 +2024-11-22 03:41:56.525980: val_loss -0.7601 +2024-11-22 03:41:56.526073: Pseudo dice [0.8441] +2024-11-22 03:41:56.526218: Epoch time: 19.15 s +2024-11-22 03:41:57.407933: +2024-11-22 03:41:57.408209: Epoch 3121 +2024-11-22 03:41:57.408372: Current learning rate: 0.00641 +2024-11-22 03:42:17.079332: train_loss -0.7897 +2024-11-22 03:42:17.079556: val_loss -0.7558 +2024-11-22 03:42:17.079634: Pseudo dice [0.8357] +2024-11-22 03:42:17.079713: Epoch time: 19.67 s +2024-11-22 03:42:17.950033: +2024-11-22 03:42:17.950236: Epoch 3122 +2024-11-22 03:42:17.950349: Current learning rate: 0.00641 +2024-11-22 03:42:36.781922: train_loss -0.7804 +2024-11-22 03:42:36.782176: val_loss -0.7491 +2024-11-22 03:42:36.782253: Pseudo dice [0.8302] +2024-11-22 03:42:36.806610: Epoch time: 18.83 s +2024-11-22 03:42:37.681776: +2024-11-22 03:42:37.682019: Epoch 3123 +2024-11-22 03:42:37.682134: Current learning rate: 0.00641 +2024-11-22 03:42:56.465681: train_loss -0.7873 +2024-11-22 03:42:56.465899: val_loss -0.7466 +2024-11-22 03:42:56.465978: Pseudo dice [0.8203] +2024-11-22 03:42:56.466065: Epoch time: 18.78 s +2024-11-22 03:42:57.341352: +2024-11-22 03:42:57.341549: Epoch 3124 +2024-11-22 03:42:57.341667: Current learning rate: 0.0064 +2024-11-22 03:43:16.390134: train_loss -0.7843 +2024-11-22 03:43:16.390460: val_loss -0.7471 +2024-11-22 03:43:16.390545: Pseudo dice [0.8294] +2024-11-22 03:43:16.390636: Epoch time: 19.05 s +2024-11-22 03:43:17.364648: +2024-11-22 03:43:17.364842: Epoch 3125 +2024-11-22 03:43:17.364971: Current learning rate: 0.0064 +2024-11-22 03:43:35.837802: train_loss -0.7816 +2024-11-22 03:43:35.838031: val_loss -0.7516 +2024-11-22 03:43:35.838110: Pseudo dice [0.8198] +2024-11-22 03:43:35.838187: Epoch time: 18.47 s +2024-11-22 03:43:36.755417: +2024-11-22 03:43:36.755638: Epoch 3126 +2024-11-22 03:43:36.755751: Current learning rate: 0.0064 +2024-11-22 03:43:56.247440: train_loss -0.7783 +2024-11-22 03:43:56.247656: val_loss -0.751 +2024-11-22 03:43:56.247728: Pseudo dice [0.8141] +2024-11-22 03:43:56.247805: Epoch time: 19.49 s +2024-11-22 03:43:57.117968: +2024-11-22 03:43:57.118200: Epoch 3127 +2024-11-22 03:43:57.118314: Current learning rate: 0.0064 +2024-11-22 03:44:16.124232: train_loss -0.772 +2024-11-22 03:44:16.124460: val_loss -0.7629 +2024-11-22 03:44:16.124535: Pseudo dice [0.8321] +2024-11-22 03:44:16.124618: Epoch time: 19.01 s +2024-11-22 03:44:17.070727: +2024-11-22 03:44:17.070951: Epoch 3128 +2024-11-22 03:44:17.071062: Current learning rate: 0.0064 +2024-11-22 03:44:34.676439: train_loss -0.7558 +2024-11-22 03:44:34.676652: val_loss -0.7056 +2024-11-22 03:44:34.676726: Pseudo dice [0.7779] +2024-11-22 03:44:34.676800: Epoch time: 17.61 s +2024-11-22 03:44:35.614794: +2024-11-22 03:44:35.615060: Epoch 3129 +2024-11-22 03:44:35.615174: Current learning rate: 0.0064 +2024-11-22 03:44:55.251297: train_loss -0.7631 +2024-11-22 03:44:55.251527: val_loss -0.7195 +2024-11-22 03:44:55.251599: Pseudo dice [0.831] +2024-11-22 03:44:55.251676: Epoch time: 19.64 s +2024-11-22 03:44:56.124388: +2024-11-22 03:44:56.124598: Epoch 3130 +2024-11-22 03:44:56.124710: Current learning rate: 0.0064 +2024-11-22 03:45:16.054781: train_loss -0.7744 +2024-11-22 03:45:16.054999: val_loss -0.7499 +2024-11-22 03:45:16.055072: Pseudo dice [0.8144] +2024-11-22 03:45:16.055150: Epoch time: 19.93 s +2024-11-22 03:45:16.924159: +2024-11-22 03:45:16.924381: Epoch 3131 +2024-11-22 03:45:16.924506: Current learning rate: 0.0064 +2024-11-22 03:45:36.979409: train_loss -0.7739 +2024-11-22 03:45:36.979876: val_loss -0.7394 +2024-11-22 03:45:36.979972: Pseudo dice [0.8291] +2024-11-22 03:45:36.980058: Epoch time: 20.06 s +2024-11-22 03:45:37.871201: +2024-11-22 03:45:37.871473: Epoch 3132 +2024-11-22 03:45:37.871596: Current learning rate: 0.00639 +2024-11-22 03:45:58.213902: train_loss -0.7662 +2024-11-22 03:45:58.214155: val_loss -0.7246 +2024-11-22 03:45:58.214235: Pseudo dice [0.8202] +2024-11-22 03:45:58.214311: Epoch time: 20.34 s +2024-11-22 03:45:59.099937: +2024-11-22 03:45:59.100192: Epoch 3133 +2024-11-22 03:45:59.100306: Current learning rate: 0.00639 +2024-11-22 03:46:17.886751: train_loss -0.7783 +2024-11-22 03:46:17.886986: val_loss -0.7215 +2024-11-22 03:46:17.887064: Pseudo dice [0.814] +2024-11-22 03:46:17.887140: Epoch time: 18.79 s +2024-11-22 03:46:18.776254: +2024-11-22 03:46:18.776603: Epoch 3134 +2024-11-22 03:46:18.776717: Current learning rate: 0.00639 +2024-11-22 03:46:38.022390: train_loss -0.7766 +2024-11-22 03:46:38.022658: val_loss -0.753 +2024-11-22 03:46:38.022742: Pseudo dice [0.8369] +2024-11-22 03:46:38.022829: Epoch time: 19.25 s +2024-11-22 03:46:38.897840: +2024-11-22 03:46:38.898083: Epoch 3135 +2024-11-22 03:46:38.898200: Current learning rate: 0.00639 +2024-11-22 03:46:56.680649: train_loss -0.7832 +2024-11-22 03:46:56.683025: val_loss -0.7781 +2024-11-22 03:46:56.683141: Pseudo dice [0.852] +2024-11-22 03:46:56.683225: Epoch time: 17.78 s +2024-11-22 03:46:57.619135: +2024-11-22 03:46:57.619344: Epoch 3136 +2024-11-22 03:46:57.619459: Current learning rate: 0.00639 +2024-11-22 03:47:15.915439: train_loss -0.7853 +2024-11-22 03:47:15.915650: val_loss -0.7343 +2024-11-22 03:47:15.915766: Pseudo dice [0.8346] +2024-11-22 03:47:15.915844: Epoch time: 18.3 s +2024-11-22 03:47:16.791203: +2024-11-22 03:47:16.791416: Epoch 3137 +2024-11-22 03:47:16.791533: Current learning rate: 0.00639 +2024-11-22 03:47:34.808032: train_loss -0.7673 +2024-11-22 03:47:34.808249: val_loss -0.7493 +2024-11-22 03:47:34.808325: Pseudo dice [0.8066] +2024-11-22 03:47:34.808407: Epoch time: 18.02 s +2024-11-22 03:47:35.679538: +2024-11-22 03:47:35.679743: Epoch 3138 +2024-11-22 03:47:35.679853: Current learning rate: 0.00639 +2024-11-22 03:47:54.313375: train_loss -0.7672 +2024-11-22 03:47:54.313618: val_loss -0.7198 +2024-11-22 03:47:54.313691: Pseudo dice [0.8192] +2024-11-22 03:47:54.313775: Epoch time: 18.63 s +2024-11-22 03:47:55.185310: +2024-11-22 03:47:55.185513: Epoch 3139 +2024-11-22 03:47:55.185623: Current learning rate: 0.00639 +2024-11-22 03:48:14.621240: train_loss -0.769 +2024-11-22 03:48:14.621477: val_loss -0.7344 +2024-11-22 03:48:14.621553: Pseudo dice [0.8077] +2024-11-22 03:48:14.621629: Epoch time: 19.44 s +2024-11-22 03:48:15.493727: +2024-11-22 03:48:15.493924: Epoch 3140 +2024-11-22 03:48:15.494044: Current learning rate: 0.00639 +2024-11-22 03:48:35.400308: train_loss -0.7724 +2024-11-22 03:48:35.400533: val_loss -0.7221 +2024-11-22 03:48:35.400611: Pseudo dice [0.8176] +2024-11-22 03:48:35.400687: Epoch time: 19.91 s +2024-11-22 03:48:36.271724: +2024-11-22 03:48:36.271935: Epoch 3141 +2024-11-22 03:48:36.272053: Current learning rate: 0.00638 +2024-11-22 03:48:53.761473: train_loss -0.7758 +2024-11-22 03:48:53.761706: val_loss -0.7569 +2024-11-22 03:48:53.761780: Pseudo dice [0.8438] +2024-11-22 03:48:53.761860: Epoch time: 17.49 s +2024-11-22 03:48:54.738775: +2024-11-22 03:48:54.739001: Epoch 3142 +2024-11-22 03:48:54.739117: Current learning rate: 0.00638 +2024-11-22 03:49:13.434414: train_loss -0.7761 +2024-11-22 03:49:13.434648: val_loss -0.7182 +2024-11-22 03:49:13.434724: Pseudo dice [0.8255] +2024-11-22 03:49:13.434821: Epoch time: 18.7 s +2024-11-22 03:49:14.767344: +2024-11-22 03:49:14.767588: Epoch 3143 +2024-11-22 03:49:14.767702: Current learning rate: 0.00638 +2024-11-22 03:49:34.435241: train_loss -0.7775 +2024-11-22 03:49:34.435473: val_loss -0.7622 +2024-11-22 03:49:34.435553: Pseudo dice [0.83] +2024-11-22 03:49:34.435628: Epoch time: 19.67 s +2024-11-22 03:49:35.305541: +2024-11-22 03:49:35.305759: Epoch 3144 +2024-11-22 03:49:35.305872: Current learning rate: 0.00638 +2024-11-22 03:49:53.726006: train_loss -0.7728 +2024-11-22 03:49:53.726235: val_loss -0.7432 +2024-11-22 03:49:53.726313: Pseudo dice [0.826] +2024-11-22 03:49:53.726394: Epoch time: 18.42 s +2024-11-22 03:49:54.599805: +2024-11-22 03:49:54.600016: Epoch 3145 +2024-11-22 03:49:54.600129: Current learning rate: 0.00638 +2024-11-22 03:50:13.359036: train_loss -0.7835 +2024-11-22 03:50:13.361505: val_loss -0.7446 +2024-11-22 03:50:13.361592: Pseudo dice [0.8256] +2024-11-22 03:50:13.361681: Epoch time: 18.76 s +2024-11-22 03:50:14.388034: +2024-11-22 03:50:14.388254: Epoch 3146 +2024-11-22 03:50:14.388371: Current learning rate: 0.00638 +2024-11-22 03:50:33.824590: train_loss -0.7696 +2024-11-22 03:50:33.824933: val_loss -0.7469 +2024-11-22 03:50:33.825026: Pseudo dice [0.8189] +2024-11-22 03:50:33.825125: Epoch time: 19.44 s +2024-11-22 03:50:34.702108: +2024-11-22 03:50:34.702318: Epoch 3147 +2024-11-22 03:50:34.702426: Current learning rate: 0.00638 +2024-11-22 03:50:53.570362: train_loss -0.7727 +2024-11-22 03:50:53.570577: val_loss -0.7557 +2024-11-22 03:50:53.570653: Pseudo dice [0.8308] +2024-11-22 03:50:53.570728: Epoch time: 18.87 s +2024-11-22 03:50:54.441726: +2024-11-22 03:50:54.441926: Epoch 3148 +2024-11-22 03:50:54.442045: Current learning rate: 0.00638 +2024-11-22 03:51:12.913544: train_loss -0.7817 +2024-11-22 03:51:12.915964: val_loss -0.7237 +2024-11-22 03:51:12.916065: Pseudo dice [0.8132] +2024-11-22 03:51:12.916145: Epoch time: 18.47 s +2024-11-22 03:51:13.920627: +2024-11-22 03:51:13.921046: Epoch 3149 +2024-11-22 03:51:13.921175: Current learning rate: 0.00637 +2024-11-22 03:51:33.014789: train_loss -0.7864 +2024-11-22 03:51:33.015048: val_loss -0.7465 +2024-11-22 03:51:33.015126: Pseudo dice [0.8156] +2024-11-22 03:51:33.015208: Epoch time: 19.1 s +2024-11-22 03:51:34.163677: +2024-11-22 03:51:34.163878: Epoch 3150 +2024-11-22 03:51:34.163988: Current learning rate: 0.00637 +2024-11-22 03:51:51.938970: train_loss -0.7853 +2024-11-22 03:51:51.939192: val_loss -0.7571 +2024-11-22 03:51:51.939265: Pseudo dice [0.8345] +2024-11-22 03:51:51.939342: Epoch time: 17.78 s +2024-11-22 03:51:52.815599: +2024-11-22 03:51:52.815796: Epoch 3151 +2024-11-22 03:51:52.815906: Current learning rate: 0.00637 +2024-11-22 03:52:12.242233: train_loss -0.786 +2024-11-22 03:52:12.242511: val_loss -0.7272 +2024-11-22 03:52:12.242586: Pseudo dice [0.8085] +2024-11-22 03:52:12.242660: Epoch time: 19.43 s +2024-11-22 03:52:13.197469: +2024-11-22 03:52:13.197664: Epoch 3152 +2024-11-22 03:52:13.197779: Current learning rate: 0.00637 +2024-11-22 03:52:33.020256: train_loss -0.7737 +2024-11-22 03:52:33.020482: val_loss -0.7325 +2024-11-22 03:52:33.025757: Pseudo dice [0.8274] +2024-11-22 03:52:33.025895: Epoch time: 19.82 s +2024-11-22 03:52:34.019203: +2024-11-22 03:52:34.019617: Epoch 3153 +2024-11-22 03:52:34.019753: Current learning rate: 0.00637 +2024-11-22 03:52:52.105339: train_loss -0.7846 +2024-11-22 03:52:52.105609: val_loss -0.7453 +2024-11-22 03:52:52.105688: Pseudo dice [0.8371] +2024-11-22 03:52:52.105770: Epoch time: 18.09 s +2024-11-22 03:52:52.973780: +2024-11-22 03:52:52.973970: Epoch 3154 +2024-11-22 03:52:52.974090: Current learning rate: 0.00637 +2024-11-22 03:53:12.241056: train_loss -0.7915 +2024-11-22 03:53:12.241572: val_loss -0.7588 +2024-11-22 03:53:12.241670: Pseudo dice [0.8303] +2024-11-22 03:53:12.241748: Epoch time: 19.27 s +2024-11-22 03:53:13.113403: +2024-11-22 03:53:13.113625: Epoch 3155 +2024-11-22 03:53:13.113745: Current learning rate: 0.00637 +2024-11-22 03:53:31.196513: train_loss -0.7919 +2024-11-22 03:53:31.196766: val_loss -0.7564 +2024-11-22 03:53:31.196852: Pseudo dice [0.8418] +2024-11-22 03:53:31.196968: Epoch time: 18.08 s +2024-11-22 03:53:32.081471: +2024-11-22 03:53:32.081723: Epoch 3156 +2024-11-22 03:53:32.081839: Current learning rate: 0.00637 +2024-11-22 03:53:49.900126: train_loss -0.789 +2024-11-22 03:53:49.900379: val_loss -0.7162 +2024-11-22 03:53:49.900453: Pseudo dice [0.8309] +2024-11-22 03:53:49.900537: Epoch time: 17.82 s +2024-11-22 03:53:50.771668: +2024-11-22 03:53:50.771865: Epoch 3157 +2024-11-22 03:53:50.771975: Current learning rate: 0.00637 +2024-11-22 03:54:08.880401: train_loss -0.7894 +2024-11-22 03:54:08.880609: val_loss -0.7422 +2024-11-22 03:54:08.880682: Pseudo dice [0.8339] +2024-11-22 03:54:08.880760: Epoch time: 18.11 s +2024-11-22 03:54:09.755490: +2024-11-22 03:54:09.755689: Epoch 3158 +2024-11-22 03:54:09.755805: Current learning rate: 0.00636 +2024-11-22 03:54:29.246741: train_loss -0.7838 +2024-11-22 03:54:29.246963: val_loss -0.7489 +2024-11-22 03:54:29.247043: Pseudo dice [0.8517] +2024-11-22 03:54:29.247118: Epoch time: 19.49 s +2024-11-22 03:54:30.118059: +2024-11-22 03:54:30.118258: Epoch 3159 +2024-11-22 03:54:30.118373: Current learning rate: 0.00636 +2024-11-22 03:54:49.274895: train_loss -0.7734 +2024-11-22 03:54:49.275223: val_loss -0.7101 +2024-11-22 03:54:49.275309: Pseudo dice [0.7964] +2024-11-22 03:54:49.275390: Epoch time: 19.16 s +2024-11-22 03:54:50.249961: +2024-11-22 03:54:50.250196: Epoch 3160 +2024-11-22 03:54:50.250312: Current learning rate: 0.00636 +2024-11-22 03:55:08.013947: train_loss -0.7719 +2024-11-22 03:55:08.014194: val_loss -0.7177 +2024-11-22 03:55:08.014269: Pseudo dice [0.7981] +2024-11-22 03:55:08.014348: Epoch time: 17.76 s +2024-11-22 03:55:08.886248: +2024-11-22 03:55:08.886484: Epoch 3161 +2024-11-22 03:55:08.886598: Current learning rate: 0.00636 +2024-11-22 03:55:27.679615: train_loss -0.7664 +2024-11-22 03:55:27.679837: val_loss -0.746 +2024-11-22 03:55:27.679924: Pseudo dice [0.821] +2024-11-22 03:55:27.680022: Epoch time: 18.79 s +2024-11-22 03:55:28.554363: +2024-11-22 03:55:28.554573: Epoch 3162 +2024-11-22 03:55:28.554692: Current learning rate: 0.00636 +2024-11-22 03:55:47.864052: train_loss -0.7685 +2024-11-22 03:55:47.864273: val_loss -0.7467 +2024-11-22 03:55:47.864347: Pseudo dice [0.8123] +2024-11-22 03:55:47.864425: Epoch time: 19.31 s +2024-11-22 03:55:48.741680: +2024-11-22 03:55:48.741948: Epoch 3163 +2024-11-22 03:55:48.742066: Current learning rate: 0.00636 +2024-11-22 03:56:07.534837: train_loss -0.7743 +2024-11-22 03:56:07.535092: val_loss -0.7246 +2024-11-22 03:56:07.535168: Pseudo dice [0.8279] +2024-11-22 03:56:07.535250: Epoch time: 18.79 s +2024-11-22 03:56:08.411710: +2024-11-22 03:56:08.412122: Epoch 3164 +2024-11-22 03:56:08.412256: Current learning rate: 0.00636 +2024-11-22 03:56:26.822621: train_loss -0.7846 +2024-11-22 03:56:26.822889: val_loss -0.7413 +2024-11-22 03:56:26.822964: Pseudo dice [0.8072] +2024-11-22 03:56:26.823044: Epoch time: 18.41 s +2024-11-22 03:56:27.696321: +2024-11-22 03:56:27.696522: Epoch 3165 +2024-11-22 03:56:27.696633: Current learning rate: 0.00636 +2024-11-22 03:56:47.067873: train_loss -0.7792 +2024-11-22 03:56:47.068095: val_loss -0.7231 +2024-11-22 03:56:47.068171: Pseudo dice [0.816] +2024-11-22 03:56:47.068248: Epoch time: 19.37 s +2024-11-22 03:56:48.349586: +2024-11-22 03:56:48.349810: Epoch 3166 +2024-11-22 03:56:48.349932: Current learning rate: 0.00635 +2024-11-22 03:57:06.690009: train_loss -0.7797 +2024-11-22 03:57:06.690290: val_loss -0.7448 +2024-11-22 03:57:06.690377: Pseudo dice [0.8202] +2024-11-22 03:57:06.690476: Epoch time: 18.34 s +2024-11-22 03:57:07.564291: +2024-11-22 03:57:07.564544: Epoch 3167 +2024-11-22 03:57:07.564659: Current learning rate: 0.00635 +2024-11-22 03:57:25.735516: train_loss -0.7786 +2024-11-22 03:57:25.735737: val_loss -0.7374 +2024-11-22 03:57:25.735813: Pseudo dice [0.829] +2024-11-22 03:57:25.735889: Epoch time: 18.17 s +2024-11-22 03:57:26.606684: +2024-11-22 03:57:26.606896: Epoch 3168 +2024-11-22 03:57:26.607008: Current learning rate: 0.00635 +2024-11-22 03:57:45.621245: train_loss -0.7536 +2024-11-22 03:57:45.621459: val_loss -0.7117 +2024-11-22 03:57:45.621533: Pseudo dice [0.8191] +2024-11-22 03:57:45.621609: Epoch time: 19.02 s +2024-11-22 03:57:46.494106: +2024-11-22 03:57:46.494307: Epoch 3169 +2024-11-22 03:57:46.494422: Current learning rate: 0.00635 +2024-11-22 03:58:03.862292: train_loss -0.7633 +2024-11-22 03:58:03.862576: val_loss -0.7457 +2024-11-22 03:58:03.862651: Pseudo dice [0.8223] +2024-11-22 03:58:03.862735: Epoch time: 17.37 s +2024-11-22 03:58:04.740367: +2024-11-22 03:58:04.740564: Epoch 3170 +2024-11-22 03:58:04.740678: Current learning rate: 0.00635 +2024-11-22 03:58:23.496875: train_loss -0.7678 +2024-11-22 03:58:23.497119: val_loss -0.7099 +2024-11-22 03:58:23.497195: Pseudo dice [0.8174] +2024-11-22 03:58:23.497270: Epoch time: 18.76 s +2024-11-22 03:58:24.380241: +2024-11-22 03:58:24.380432: Epoch 3171 +2024-11-22 03:58:24.380572: Current learning rate: 0.00635 +2024-11-22 03:58:43.306571: train_loss -0.768 +2024-11-22 03:58:43.306867: val_loss -0.7375 +2024-11-22 03:58:43.306943: Pseudo dice [0.8169] +2024-11-22 03:58:43.307027: Epoch time: 18.93 s +2024-11-22 03:58:44.204131: +2024-11-22 03:58:44.204318: Epoch 3172 +2024-11-22 03:58:44.204430: Current learning rate: 0.00635 +2024-11-22 03:59:02.557104: train_loss -0.7744 +2024-11-22 03:59:02.557545: val_loss -0.7183 +2024-11-22 03:59:02.557634: Pseudo dice [0.8022] +2024-11-22 03:59:02.557721: Epoch time: 18.35 s +2024-11-22 03:59:03.649984: +2024-11-22 03:59:03.650247: Epoch 3173 +2024-11-22 03:59:03.650363: Current learning rate: 0.00635 +2024-11-22 03:59:22.636690: train_loss -0.7687 +2024-11-22 03:59:22.636923: val_loss -0.7595 +2024-11-22 03:59:22.637004: Pseudo dice [0.8388] +2024-11-22 03:59:22.637084: Epoch time: 18.99 s +2024-11-22 03:59:23.512200: +2024-11-22 03:59:23.512391: Epoch 3174 +2024-11-22 03:59:23.512503: Current learning rate: 0.00635 +2024-11-22 03:59:42.302109: train_loss -0.7779 +2024-11-22 03:59:42.302318: val_loss -0.7336 +2024-11-22 03:59:42.302390: Pseudo dice [0.8347] +2024-11-22 03:59:42.302465: Epoch time: 18.79 s +2024-11-22 03:59:43.166773: +2024-11-22 03:59:43.167069: Epoch 3175 +2024-11-22 03:59:43.167184: Current learning rate: 0.00634 +2024-11-22 04:00:01.646330: train_loss -0.7888 +2024-11-22 04:00:01.646544: val_loss -0.7271 +2024-11-22 04:00:01.646620: Pseudo dice [0.8158] +2024-11-22 04:00:01.646694: Epoch time: 18.48 s +2024-11-22 04:00:02.516886: +2024-11-22 04:00:02.517294: Epoch 3176 +2024-11-22 04:00:02.517462: Current learning rate: 0.00634 +2024-11-22 04:00:22.047657: train_loss -0.7857 +2024-11-22 04:00:22.050075: val_loss -0.7531 +2024-11-22 04:00:22.050160: Pseudo dice [0.8269] +2024-11-22 04:00:22.050250: Epoch time: 19.53 s +2024-11-22 04:00:23.027898: +2024-11-22 04:00:23.028124: Epoch 3177 +2024-11-22 04:00:23.028243: Current learning rate: 0.00634 +2024-11-22 04:00:41.823506: train_loss -0.7852 +2024-11-22 04:00:41.824098: val_loss -0.7356 +2024-11-22 04:00:41.824202: Pseudo dice [0.8132] +2024-11-22 04:00:41.824280: Epoch time: 18.8 s +2024-11-22 04:00:42.697959: +2024-11-22 04:00:42.698182: Epoch 3178 +2024-11-22 04:00:42.698300: Current learning rate: 0.00634 +2024-11-22 04:01:02.326226: train_loss -0.782 +2024-11-22 04:01:02.326451: val_loss -0.7445 +2024-11-22 04:01:02.326526: Pseudo dice [0.8196] +2024-11-22 04:01:02.326646: Epoch time: 19.63 s +2024-11-22 04:01:03.237931: +2024-11-22 04:01:03.238150: Epoch 3179 +2024-11-22 04:01:03.238269: Current learning rate: 0.00634 +2024-11-22 04:01:21.781256: train_loss -0.7811 +2024-11-22 04:01:21.781497: val_loss -0.7349 +2024-11-22 04:01:21.781576: Pseudo dice [0.824] +2024-11-22 04:01:21.781663: Epoch time: 18.54 s +2024-11-22 04:01:22.656963: +2024-11-22 04:01:22.657327: Epoch 3180 +2024-11-22 04:01:22.657439: Current learning rate: 0.00634 +2024-11-22 04:01:41.015837: train_loss -0.7846 +2024-11-22 04:01:41.016063: val_loss -0.75 +2024-11-22 04:01:41.016137: Pseudo dice [0.825] +2024-11-22 04:01:41.016212: Epoch time: 18.36 s +2024-11-22 04:01:41.907516: +2024-11-22 04:01:41.907814: Epoch 3181 +2024-11-22 04:01:41.907928: Current learning rate: 0.00634 +2024-11-22 04:02:00.245038: train_loss -0.7848 +2024-11-22 04:02:00.245251: val_loss -0.724 +2024-11-22 04:02:00.245367: Pseudo dice [0.8208] +2024-11-22 04:02:00.245445: Epoch time: 18.34 s +2024-11-22 04:02:01.118815: +2024-11-22 04:02:01.119036: Epoch 3182 +2024-11-22 04:02:01.119153: Current learning rate: 0.00634 +2024-11-22 04:02:19.254755: train_loss -0.7871 +2024-11-22 04:02:19.254970: val_loss -0.7827 +2024-11-22 04:02:19.255050: Pseudo dice [0.8394] +2024-11-22 04:02:19.255129: Epoch time: 18.14 s +2024-11-22 04:02:20.229126: +2024-11-22 04:02:20.229414: Epoch 3183 +2024-11-22 04:02:20.229526: Current learning rate: 0.00633 +2024-11-22 04:02:38.899961: train_loss -0.7823 +2024-11-22 04:02:38.900266: val_loss -0.7623 +2024-11-22 04:02:38.900343: Pseudo dice [0.8281] +2024-11-22 04:02:38.900421: Epoch time: 18.67 s +2024-11-22 04:02:39.774332: +2024-11-22 04:02:39.774518: Epoch 3184 +2024-11-22 04:02:39.774632: Current learning rate: 0.00633 +2024-11-22 04:02:58.113431: train_loss -0.7821 +2024-11-22 04:02:58.113674: val_loss -0.7216 +2024-11-22 04:02:58.113751: Pseudo dice [0.8283] +2024-11-22 04:02:58.113832: Epoch time: 18.34 s +2024-11-22 04:02:58.991167: +2024-11-22 04:02:58.991421: Epoch 3185 +2024-11-22 04:02:58.991536: Current learning rate: 0.00633 +2024-11-22 04:03:17.433933: train_loss -0.782 +2024-11-22 04:03:17.434155: val_loss -0.7377 +2024-11-22 04:03:17.434232: Pseudo dice [0.8278] +2024-11-22 04:03:17.434312: Epoch time: 18.44 s +2024-11-22 04:03:18.446391: +2024-11-22 04:03:18.446607: Epoch 3186 +2024-11-22 04:03:18.446724: Current learning rate: 0.00633 +2024-11-22 04:03:36.903515: train_loss -0.7758 +2024-11-22 04:03:36.903727: val_loss -0.7438 +2024-11-22 04:03:36.903797: Pseudo dice [0.8133] +2024-11-22 04:03:36.903875: Epoch time: 18.46 s +2024-11-22 04:03:37.770389: +2024-11-22 04:03:37.770608: Epoch 3187 +2024-11-22 04:03:37.770754: Current learning rate: 0.00633 +2024-11-22 04:03:56.169520: train_loss -0.7779 +2024-11-22 04:03:56.169738: val_loss -0.7399 +2024-11-22 04:03:56.169818: Pseudo dice [0.8198] +2024-11-22 04:03:56.169893: Epoch time: 18.4 s +2024-11-22 04:03:57.085454: +2024-11-22 04:03:57.085896: Epoch 3188 +2024-11-22 04:03:57.086043: Current learning rate: 0.00633 +2024-11-22 04:04:16.274664: train_loss -0.7725 +2024-11-22 04:04:16.274901: val_loss -0.7508 +2024-11-22 04:04:16.274976: Pseudo dice [0.8235] +2024-11-22 04:04:16.275062: Epoch time: 19.19 s +2024-11-22 04:04:17.546578: +2024-11-22 04:04:17.546785: Epoch 3189 +2024-11-22 04:04:17.546900: Current learning rate: 0.00633 +2024-11-22 04:04:36.622141: train_loss -0.7688 +2024-11-22 04:04:36.622358: val_loss -0.7508 +2024-11-22 04:04:36.622435: Pseudo dice [0.829] +2024-11-22 04:04:36.622515: Epoch time: 19.08 s +2024-11-22 04:04:37.503826: +2024-11-22 04:04:37.504094: Epoch 3190 +2024-11-22 04:04:37.504210: Current learning rate: 0.00633 +2024-11-22 04:04:56.562424: train_loss -0.7846 +2024-11-22 04:04:56.562643: val_loss -0.7475 +2024-11-22 04:04:56.562717: Pseudo dice [0.8281] +2024-11-22 04:04:56.562795: Epoch time: 19.06 s +2024-11-22 04:04:57.433873: +2024-11-22 04:04:57.434079: Epoch 3191 +2024-11-22 04:04:57.434191: Current learning rate: 0.00633 +2024-11-22 04:05:15.974049: train_loss -0.784 +2024-11-22 04:05:15.974297: val_loss -0.7283 +2024-11-22 04:05:15.974390: Pseudo dice [0.8264] +2024-11-22 04:05:15.974478: Epoch time: 18.54 s +2024-11-22 04:05:16.900750: +2024-11-22 04:05:16.900957: Epoch 3192 +2024-11-22 04:05:16.901067: Current learning rate: 0.00632 +2024-11-22 04:05:35.831443: train_loss -0.7788 +2024-11-22 04:05:35.831654: val_loss -0.7442 +2024-11-22 04:05:35.831728: Pseudo dice [0.8447] +2024-11-22 04:05:35.833987: Epoch time: 18.93 s +2024-11-22 04:05:36.804707: +2024-11-22 04:05:36.804940: Epoch 3193 +2024-11-22 04:05:36.805054: Current learning rate: 0.00632 +2024-11-22 04:05:55.522742: train_loss -0.7841 +2024-11-22 04:05:55.525170: val_loss -0.7333 +2024-11-22 04:05:55.525270: Pseudo dice [0.837] +2024-11-22 04:05:55.525349: Epoch time: 18.72 s +2024-11-22 04:05:56.403310: +2024-11-22 04:05:56.403542: Epoch 3194 +2024-11-22 04:05:56.403653: Current learning rate: 0.00632 +2024-11-22 04:06:15.521834: train_loss -0.7614 +2024-11-22 04:06:15.522045: val_loss -0.7321 +2024-11-22 04:06:15.522115: Pseudo dice [0.8325] +2024-11-22 04:06:15.522199: Epoch time: 19.12 s +2024-11-22 04:06:16.419910: +2024-11-22 04:06:16.420110: Epoch 3195 +2024-11-22 04:06:16.420221: Current learning rate: 0.00632 +2024-11-22 04:06:35.434838: train_loss -0.7815 +2024-11-22 04:06:35.436850: val_loss -0.7253 +2024-11-22 04:06:35.436939: Pseudo dice [0.8515] +2024-11-22 04:06:35.437142: Epoch time: 19.02 s +2024-11-22 04:06:36.353998: +2024-11-22 04:06:36.354202: Epoch 3196 +2024-11-22 04:06:36.354316: Current learning rate: 0.00632 +2024-11-22 04:06:55.619801: train_loss -0.7848 +2024-11-22 04:06:55.620026: val_loss -0.7563 +2024-11-22 04:06:55.620103: Pseudo dice [0.8215] +2024-11-22 04:06:55.620184: Epoch time: 19.27 s +2024-11-22 04:06:56.497417: +2024-11-22 04:06:56.497629: Epoch 3197 +2024-11-22 04:06:56.497744: Current learning rate: 0.00632 +2024-11-22 04:07:15.150524: train_loss -0.7736 +2024-11-22 04:07:15.150740: val_loss -0.7332 +2024-11-22 04:07:15.150816: Pseudo dice [0.8315] +2024-11-22 04:07:15.150898: Epoch time: 18.65 s +2024-11-22 04:07:16.078046: +2024-11-22 04:07:16.078237: Epoch 3198 +2024-11-22 04:07:16.078351: Current learning rate: 0.00632 +2024-11-22 04:07:35.584780: train_loss -0.7826 +2024-11-22 04:07:35.585005: val_loss -0.7375 +2024-11-22 04:07:35.585088: Pseudo dice [0.8205] +2024-11-22 04:07:35.585173: Epoch time: 19.51 s +2024-11-22 04:07:36.458024: +2024-11-22 04:07:36.458244: Epoch 3199 +2024-11-22 04:07:36.458361: Current learning rate: 0.00632 +2024-11-22 04:07:54.681018: train_loss -0.7834 +2024-11-22 04:07:54.681240: val_loss -0.7546 +2024-11-22 04:07:54.681313: Pseudo dice [0.8257] +2024-11-22 04:07:54.681393: Epoch time: 18.22 s +2024-11-22 04:07:56.142803: +2024-11-22 04:07:56.143048: Epoch 3200 +2024-11-22 04:07:56.143160: Current learning rate: 0.00631 +2024-11-22 04:08:14.344043: train_loss -0.7843 +2024-11-22 04:08:14.344277: val_loss -0.731 +2024-11-22 04:08:14.344352: Pseudo dice [0.826] +2024-11-22 04:08:14.344438: Epoch time: 18.2 s +2024-11-22 04:08:15.290950: +2024-11-22 04:08:15.291188: Epoch 3201 +2024-11-22 04:08:15.291317: Current learning rate: 0.00631 +2024-11-22 04:08:33.930189: train_loss -0.7925 +2024-11-22 04:08:33.930413: val_loss -0.7593 +2024-11-22 04:08:33.930500: Pseudo dice [0.8239] +2024-11-22 04:08:33.930586: Epoch time: 18.64 s +2024-11-22 04:08:34.806302: +2024-11-22 04:08:34.806519: Epoch 3202 +2024-11-22 04:08:34.806647: Current learning rate: 0.00631 +2024-11-22 04:08:53.326822: train_loss -0.7738 +2024-11-22 04:08:53.327068: val_loss -0.7301 +2024-11-22 04:08:53.327144: Pseudo dice [0.8256] +2024-11-22 04:08:53.327239: Epoch time: 18.52 s +2024-11-22 04:08:54.210056: +2024-11-22 04:08:54.210255: Epoch 3203 +2024-11-22 04:08:54.210365: Current learning rate: 0.00631 +2024-11-22 04:09:13.721116: train_loss -0.7896 +2024-11-22 04:09:13.721337: val_loss -0.7447 +2024-11-22 04:09:13.721423: Pseudo dice [0.838] +2024-11-22 04:09:13.721500: Epoch time: 19.51 s +2024-11-22 04:09:14.595070: +2024-11-22 04:09:14.595285: Epoch 3204 +2024-11-22 04:09:14.595404: Current learning rate: 0.00631 +2024-11-22 04:09:31.587939: train_loss -0.7956 +2024-11-22 04:09:31.588163: val_loss -0.7752 +2024-11-22 04:09:31.588236: Pseudo dice [0.8323] +2024-11-22 04:09:31.588312: Epoch time: 16.99 s +2024-11-22 04:09:32.463618: +2024-11-22 04:09:32.463824: Epoch 3205 +2024-11-22 04:09:32.463937: Current learning rate: 0.00631 +2024-11-22 04:09:51.282458: train_loss -0.7795 +2024-11-22 04:09:51.282688: val_loss -0.7242 +2024-11-22 04:09:51.282770: Pseudo dice [0.8205] +2024-11-22 04:09:51.282854: Epoch time: 18.82 s +2024-11-22 04:09:52.157559: +2024-11-22 04:09:52.157778: Epoch 3206 +2024-11-22 04:09:52.157891: Current learning rate: 0.00631 +2024-11-22 04:10:11.000802: train_loss -0.7877 +2024-11-22 04:10:11.001049: val_loss -0.7536 +2024-11-22 04:10:11.001122: Pseudo dice [0.8133] +2024-11-22 04:10:11.001202: Epoch time: 18.84 s +2024-11-22 04:10:11.879282: +2024-11-22 04:10:11.879486: Epoch 3207 +2024-11-22 04:10:11.879597: Current learning rate: 0.00631 +2024-11-22 04:10:31.902004: train_loss -0.7775 +2024-11-22 04:10:31.902220: val_loss -0.7208 +2024-11-22 04:10:31.902376: Pseudo dice [0.8063] +2024-11-22 04:10:31.902460: Epoch time: 20.02 s +2024-11-22 04:10:32.862769: +2024-11-22 04:10:32.862973: Epoch 3208 +2024-11-22 04:10:32.863088: Current learning rate: 0.0063 +2024-11-22 04:10:52.804756: train_loss -0.775 +2024-11-22 04:10:52.804979: val_loss -0.75 +2024-11-22 04:10:52.805067: Pseudo dice [0.8306] +2024-11-22 04:10:52.805147: Epoch time: 19.94 s +2024-11-22 04:10:53.682904: +2024-11-22 04:10:53.683099: Epoch 3209 +2024-11-22 04:10:53.683213: Current learning rate: 0.0063 +2024-11-22 04:11:12.860530: train_loss -0.7811 +2024-11-22 04:11:12.860787: val_loss -0.7365 +2024-11-22 04:11:12.860865: Pseudo dice [0.8212] +2024-11-22 04:11:12.866293: Epoch time: 19.18 s +2024-11-22 04:11:13.773718: +2024-11-22 04:11:13.773920: Epoch 3210 +2024-11-22 04:11:13.774045: Current learning rate: 0.0063 +2024-11-22 04:11:32.638764: train_loss -0.7906 +2024-11-22 04:11:32.638972: val_loss -0.7199 +2024-11-22 04:11:32.639052: Pseudo dice [0.8229] +2024-11-22 04:11:32.639127: Epoch time: 18.87 s +2024-11-22 04:11:33.513060: +2024-11-22 04:11:33.513248: Epoch 3211 +2024-11-22 04:11:33.513365: Current learning rate: 0.0063 +2024-11-22 04:11:52.797164: train_loss -0.7863 +2024-11-22 04:11:52.797386: val_loss -0.7556 +2024-11-22 04:11:52.797464: Pseudo dice [0.8226] +2024-11-22 04:11:52.797544: Epoch time: 19.28 s +2024-11-22 04:11:54.045981: +2024-11-22 04:11:54.046210: Epoch 3212 +2024-11-22 04:11:54.046324: Current learning rate: 0.0063 +2024-11-22 04:12:12.117357: train_loss -0.7863 +2024-11-22 04:12:12.117604: val_loss -0.7764 +2024-11-22 04:12:12.117681: Pseudo dice [0.8341] +2024-11-22 04:12:12.117761: Epoch time: 18.07 s +2024-11-22 04:12:12.989558: +2024-11-22 04:12:12.989783: Epoch 3213 +2024-11-22 04:12:12.989898: Current learning rate: 0.0063 +2024-11-22 04:12:32.773035: train_loss -0.7854 +2024-11-22 04:12:32.773253: val_loss -0.7498 +2024-11-22 04:12:32.773328: Pseudo dice [0.8267] +2024-11-22 04:12:32.773402: Epoch time: 19.78 s +2024-11-22 04:12:33.643595: +2024-11-22 04:12:33.643895: Epoch 3214 +2024-11-22 04:12:33.644016: Current learning rate: 0.0063 +2024-11-22 04:12:50.381355: train_loss -0.7729 +2024-11-22 04:12:50.381565: val_loss -0.7502 +2024-11-22 04:12:50.381638: Pseudo dice [0.8364] +2024-11-22 04:12:50.381714: Epoch time: 16.74 s +2024-11-22 04:12:51.250182: +2024-11-22 04:12:51.250378: Epoch 3215 +2024-11-22 04:12:51.250493: Current learning rate: 0.0063 +2024-11-22 04:13:09.228004: train_loss -0.7871 +2024-11-22 04:13:09.228220: val_loss -0.7492 +2024-11-22 04:13:09.228293: Pseudo dice [0.8288] +2024-11-22 04:13:09.228377: Epoch time: 17.98 s +2024-11-22 04:13:10.107139: +2024-11-22 04:13:10.107355: Epoch 3216 +2024-11-22 04:13:10.107471: Current learning rate: 0.0063 +2024-11-22 04:13:28.477077: train_loss -0.7767 +2024-11-22 04:13:28.479489: val_loss -0.736 +2024-11-22 04:13:28.479573: Pseudo dice [0.8359] +2024-11-22 04:13:28.479653: Epoch time: 18.37 s +2024-11-22 04:13:29.497809: +2024-11-22 04:13:29.498061: Epoch 3217 +2024-11-22 04:13:29.498179: Current learning rate: 0.00629 +2024-11-22 04:13:47.327700: train_loss -0.77 +2024-11-22 04:13:47.327932: val_loss -0.7425 +2024-11-22 04:13:47.328020: Pseudo dice [0.8276] +2024-11-22 04:13:47.328098: Epoch time: 17.83 s +2024-11-22 04:13:48.200743: +2024-11-22 04:13:48.200957: Epoch 3218 +2024-11-22 04:13:48.201080: Current learning rate: 0.00629 +2024-11-22 04:14:07.590748: train_loss -0.777 +2024-11-22 04:14:07.591036: val_loss -0.7399 +2024-11-22 04:14:07.591117: Pseudo dice [0.8129] +2024-11-22 04:14:07.591193: Epoch time: 19.39 s +2024-11-22 04:14:08.465264: +2024-11-22 04:14:08.465458: Epoch 3219 +2024-11-22 04:14:08.465570: Current learning rate: 0.00629 +2024-11-22 04:14:26.775559: train_loss -0.7768 +2024-11-22 04:14:26.780408: val_loss -0.7704 +2024-11-22 04:14:26.780541: Pseudo dice [0.8251] +2024-11-22 04:14:26.780637: Epoch time: 18.31 s +2024-11-22 04:14:27.659960: +2024-11-22 04:14:27.660167: Epoch 3220 +2024-11-22 04:14:27.660286: Current learning rate: 0.00629 +2024-11-22 04:14:45.481645: train_loss -0.7773 +2024-11-22 04:14:45.481856: val_loss -0.701 +2024-11-22 04:14:45.481952: Pseudo dice [0.7904] +2024-11-22 04:14:45.482034: Epoch time: 17.82 s +2024-11-22 04:14:46.355549: +2024-11-22 04:14:46.355760: Epoch 3221 +2024-11-22 04:14:46.355875: Current learning rate: 0.00629 +2024-11-22 04:15:05.931425: train_loss -0.7673 +2024-11-22 04:15:05.931634: val_loss -0.716 +2024-11-22 04:15:05.931707: Pseudo dice [0.8093] +2024-11-22 04:15:05.931781: Epoch time: 19.58 s +2024-11-22 04:15:06.807245: +2024-11-22 04:15:06.807456: Epoch 3222 +2024-11-22 04:15:06.807567: Current learning rate: 0.00629 +2024-11-22 04:15:25.713156: train_loss -0.7919 +2024-11-22 04:15:25.713375: val_loss -0.7313 +2024-11-22 04:15:25.713452: Pseudo dice [0.814] +2024-11-22 04:15:25.713531: Epoch time: 18.91 s +2024-11-22 04:15:26.588876: +2024-11-22 04:15:26.589078: Epoch 3223 +2024-11-22 04:15:26.589194: Current learning rate: 0.00629 +2024-11-22 04:15:44.606330: train_loss -0.7789 +2024-11-22 04:15:44.606779: val_loss -0.7593 +2024-11-22 04:15:44.606874: Pseudo dice [0.8244] +2024-11-22 04:15:44.606960: Epoch time: 18.02 s +2024-11-22 04:15:45.482307: +2024-11-22 04:15:45.482547: Epoch 3224 +2024-11-22 04:15:45.482661: Current learning rate: 0.00629 +2024-11-22 04:16:04.472877: train_loss -0.7747 +2024-11-22 04:16:04.473101: val_loss -0.7119 +2024-11-22 04:16:04.473179: Pseudo dice [0.8068] +2024-11-22 04:16:04.473259: Epoch time: 18.99 s +2024-11-22 04:16:05.356315: +2024-11-22 04:16:05.356623: Epoch 3225 +2024-11-22 04:16:05.356735: Current learning rate: 0.00628 +2024-11-22 04:16:24.223608: train_loss -0.7726 +2024-11-22 04:16:24.223827: val_loss -0.7452 +2024-11-22 04:16:24.223902: Pseudo dice [0.812] +2024-11-22 04:16:24.223982: Epoch time: 18.87 s +2024-11-22 04:16:25.261147: +2024-11-22 04:16:25.261351: Epoch 3226 +2024-11-22 04:16:25.261462: Current learning rate: 0.00628 +2024-11-22 04:16:44.617023: train_loss -0.7801 +2024-11-22 04:16:44.617267: val_loss -0.7445 +2024-11-22 04:16:44.617343: Pseudo dice [0.831] +2024-11-22 04:16:44.617422: Epoch time: 19.36 s +2024-11-22 04:16:45.498327: +2024-11-22 04:16:45.498562: Epoch 3227 +2024-11-22 04:16:45.498676: Current learning rate: 0.00628 +2024-11-22 04:17:04.966114: train_loss -0.7786 +2024-11-22 04:17:04.966362: val_loss -0.7462 +2024-11-22 04:17:04.966435: Pseudo dice [0.814] +2024-11-22 04:17:04.966514: Epoch time: 19.47 s +2024-11-22 04:17:05.871385: +2024-11-22 04:17:05.871598: Epoch 3228 +2024-11-22 04:17:05.871711: Current learning rate: 0.00628 +2024-11-22 04:17:24.509537: train_loss -0.7834 +2024-11-22 04:17:24.509759: val_loss -0.7546 +2024-11-22 04:17:24.509839: Pseudo dice [0.8313] +2024-11-22 04:17:24.509917: Epoch time: 18.64 s +2024-11-22 04:17:25.379447: +2024-11-22 04:17:25.379668: Epoch 3229 +2024-11-22 04:17:25.379780: Current learning rate: 0.00628 +2024-11-22 04:17:43.365395: train_loss -0.7842 +2024-11-22 04:17:43.365649: val_loss -0.7655 +2024-11-22 04:17:43.365722: Pseudo dice [0.8392] +2024-11-22 04:17:43.365802: Epoch time: 17.99 s +2024-11-22 04:17:44.240227: +2024-11-22 04:17:44.240429: Epoch 3230 +2024-11-22 04:17:44.240544: Current learning rate: 0.00628 +2024-11-22 04:18:03.984512: train_loss -0.7896 +2024-11-22 04:18:03.984816: val_loss -0.7032 +2024-11-22 04:18:03.984899: Pseudo dice [0.8162] +2024-11-22 04:18:03.984983: Epoch time: 19.75 s +2024-11-22 04:18:04.858257: +2024-11-22 04:18:04.858449: Epoch 3231 +2024-11-22 04:18:04.858563: Current learning rate: 0.00628 +2024-11-22 04:18:23.898578: train_loss -0.7862 +2024-11-22 04:18:23.898798: val_loss -0.7118 +2024-11-22 04:18:23.898871: Pseudo dice [0.8072] +2024-11-22 04:18:23.898947: Epoch time: 19.04 s +2024-11-22 04:18:24.773210: +2024-11-22 04:18:24.773416: Epoch 3232 +2024-11-22 04:18:24.773530: Current learning rate: 0.00628 +2024-11-22 04:18:43.846275: train_loss -0.7813 +2024-11-22 04:18:43.846497: val_loss -0.7556 +2024-11-22 04:18:43.846573: Pseudo dice [0.837] +2024-11-22 04:18:43.846648: Epoch time: 19.07 s +2024-11-22 04:18:44.815667: +2024-11-22 04:18:44.815857: Epoch 3233 +2024-11-22 04:18:44.815974: Current learning rate: 0.00628 +2024-11-22 04:19:03.123818: train_loss -0.7696 +2024-11-22 04:19:03.124069: val_loss -0.7051 +2024-11-22 04:19:03.124143: Pseudo dice [0.789] +2024-11-22 04:19:03.124266: Epoch time: 18.31 s +2024-11-22 04:19:04.007264: +2024-11-22 04:19:04.007449: Epoch 3234 +2024-11-22 04:19:04.007562: Current learning rate: 0.00627 +2024-11-22 04:19:21.246821: train_loss -0.7682 +2024-11-22 04:19:21.247041: val_loss -0.7384 +2024-11-22 04:19:21.247118: Pseudo dice [0.8424] +2024-11-22 04:19:21.247195: Epoch time: 17.24 s +2024-11-22 04:19:22.482548: +2024-11-22 04:19:22.482743: Epoch 3235 +2024-11-22 04:19:22.482855: Current learning rate: 0.00627 +2024-11-22 04:19:42.321443: train_loss -0.7703 +2024-11-22 04:19:42.321672: val_loss -0.7481 +2024-11-22 04:19:42.321769: Pseudo dice [0.8389] +2024-11-22 04:19:42.321848: Epoch time: 19.84 s +2024-11-22 04:19:43.194840: +2024-11-22 04:19:43.195068: Epoch 3236 +2024-11-22 04:19:43.195180: Current learning rate: 0.00627 +2024-11-22 04:20:01.309926: train_loss -0.7806 +2024-11-22 04:20:01.310186: val_loss -0.7615 +2024-11-22 04:20:01.310267: Pseudo dice [0.8397] +2024-11-22 04:20:01.310353: Epoch time: 18.12 s +2024-11-22 04:20:02.186355: +2024-11-22 04:20:02.186671: Epoch 3237 +2024-11-22 04:20:02.186789: Current learning rate: 0.00627 +2024-11-22 04:20:21.899982: train_loss -0.7725 +2024-11-22 04:20:21.900196: val_loss -0.7375 +2024-11-22 04:20:21.900275: Pseudo dice [0.8075] +2024-11-22 04:20:21.900359: Epoch time: 19.71 s +2024-11-22 04:20:22.807184: +2024-11-22 04:20:22.807384: Epoch 3238 +2024-11-22 04:20:22.807497: Current learning rate: 0.00627 +2024-11-22 04:20:42.333600: train_loss -0.7812 +2024-11-22 04:20:42.333821: val_loss -0.7347 +2024-11-22 04:20:42.333896: Pseudo dice [0.8366] +2024-11-22 04:20:42.333972: Epoch time: 19.53 s +2024-11-22 04:20:43.209957: +2024-11-22 04:20:43.210182: Epoch 3239 +2024-11-22 04:20:43.210300: Current learning rate: 0.00627 +2024-11-22 04:21:02.120360: train_loss -0.7786 +2024-11-22 04:21:02.120658: val_loss -0.7498 +2024-11-22 04:21:02.120743: Pseudo dice [0.8226] +2024-11-22 04:21:02.120820: Epoch time: 18.91 s +2024-11-22 04:21:03.010964: +2024-11-22 04:21:03.011192: Epoch 3240 +2024-11-22 04:21:03.011307: Current learning rate: 0.00627 +2024-11-22 04:21:22.735121: train_loss -0.7843 +2024-11-22 04:21:22.735380: val_loss -0.7292 +2024-11-22 04:21:22.735466: Pseudo dice [0.8283] +2024-11-22 04:21:22.735551: Epoch time: 19.72 s +2024-11-22 04:21:23.639817: +2024-11-22 04:21:23.640091: Epoch 3241 +2024-11-22 04:21:23.640204: Current learning rate: 0.00627 +2024-11-22 04:21:41.980313: train_loss -0.785 +2024-11-22 04:21:41.980528: val_loss -0.759 +2024-11-22 04:21:41.980628: Pseudo dice [0.815] +2024-11-22 04:21:41.980709: Epoch time: 18.34 s +2024-11-22 04:21:42.851137: +2024-11-22 04:21:42.851354: Epoch 3242 +2024-11-22 04:21:42.851469: Current learning rate: 0.00626 +2024-11-22 04:22:02.134371: train_loss -0.7849 +2024-11-22 04:22:02.134655: val_loss -0.7146 +2024-11-22 04:22:02.134732: Pseudo dice [0.7876] +2024-11-22 04:22:02.134808: Epoch time: 19.28 s +2024-11-22 04:22:03.017069: +2024-11-22 04:22:03.017273: Epoch 3243 +2024-11-22 04:22:03.017382: Current learning rate: 0.00626 +2024-11-22 04:22:22.002898: train_loss -0.779 +2024-11-22 04:22:22.003134: val_loss -0.7178 +2024-11-22 04:22:22.003213: Pseudo dice [0.7946] +2024-11-22 04:22:22.003289: Epoch time: 18.99 s +2024-11-22 04:22:22.883969: +2024-11-22 04:22:22.884165: Epoch 3244 +2024-11-22 04:22:22.884274: Current learning rate: 0.00626 +2024-11-22 04:22:41.719101: train_loss -0.7754 +2024-11-22 04:22:41.719360: val_loss -0.7267 +2024-11-22 04:22:41.719441: Pseudo dice [0.8401] +2024-11-22 04:22:41.719522: Epoch time: 18.84 s +2024-11-22 04:22:42.600741: +2024-11-22 04:22:42.600934: Epoch 3245 +2024-11-22 04:22:42.601051: Current learning rate: 0.00626 +2024-11-22 04:23:00.633338: train_loss -0.7692 +2024-11-22 04:23:00.633553: val_loss -0.7377 +2024-11-22 04:23:00.633639: Pseudo dice [0.8257] +2024-11-22 04:23:00.633727: Epoch time: 18.03 s +2024-11-22 04:23:01.506224: +2024-11-22 04:23:01.506429: Epoch 3246 +2024-11-22 04:23:01.506543: Current learning rate: 0.00626 +2024-11-22 04:23:19.762707: train_loss -0.7697 +2024-11-22 04:23:19.763272: val_loss -0.7209 +2024-11-22 04:23:19.763381: Pseudo dice [0.8072] +2024-11-22 04:23:19.763471: Epoch time: 18.26 s +2024-11-22 04:23:20.655089: +2024-11-22 04:23:20.655338: Epoch 3247 +2024-11-22 04:23:20.655452: Current learning rate: 0.00626 +2024-11-22 04:23:40.887773: train_loss -0.7675 +2024-11-22 04:23:40.887982: val_loss -0.7459 +2024-11-22 04:23:40.888086: Pseudo dice [0.825] +2024-11-22 04:23:40.888163: Epoch time: 20.23 s +2024-11-22 04:23:41.747716: +2024-11-22 04:23:41.747940: Epoch 3248 +2024-11-22 04:23:41.748086: Current learning rate: 0.00626 +2024-11-22 04:24:00.907680: train_loss -0.7786 +2024-11-22 04:24:00.907906: val_loss -0.7603 +2024-11-22 04:24:00.907983: Pseudo dice [0.8282] +2024-11-22 04:24:00.908066: Epoch time: 19.16 s +2024-11-22 04:24:01.792515: +2024-11-22 04:24:01.792715: Epoch 3249 +2024-11-22 04:24:01.792826: Current learning rate: 0.00626 +2024-11-22 04:24:20.921161: train_loss -0.7876 +2024-11-22 04:24:20.921407: val_loss -0.759 +2024-11-22 04:24:20.921483: Pseudo dice [0.8355] +2024-11-22 04:24:20.921566: Epoch time: 19.13 s +2024-11-22 04:24:22.093533: +2024-11-22 04:24:22.093723: Epoch 3250 +2024-11-22 04:24:22.093835: Current learning rate: 0.00626 +2024-11-22 04:24:40.606538: train_loss -0.7795 +2024-11-22 04:24:40.606747: val_loss -0.7365 +2024-11-22 04:24:40.606819: Pseudo dice [0.8205] +2024-11-22 04:24:40.606896: Epoch time: 18.51 s +2024-11-22 04:24:41.625450: +2024-11-22 04:24:41.625675: Epoch 3251 +2024-11-22 04:24:41.625789: Current learning rate: 0.00625 +2024-11-22 04:24:59.613168: train_loss -0.7879 +2024-11-22 04:24:59.613385: val_loss -0.7505 +2024-11-22 04:24:59.613458: Pseudo dice [0.814] +2024-11-22 04:24:59.613534: Epoch time: 17.99 s +2024-11-22 04:25:00.479131: +2024-11-22 04:25:00.479385: Epoch 3252 +2024-11-22 04:25:00.479503: Current learning rate: 0.00625 +2024-11-22 04:25:19.139352: train_loss -0.7779 +2024-11-22 04:25:19.139573: val_loss -0.739 +2024-11-22 04:25:19.139647: Pseudo dice [0.8329] +2024-11-22 04:25:19.139722: Epoch time: 18.66 s +2024-11-22 04:25:20.035852: +2024-11-22 04:25:20.036059: Epoch 3253 +2024-11-22 04:25:20.036177: Current learning rate: 0.00625 +2024-11-22 04:25:38.348770: train_loss -0.7891 +2024-11-22 04:25:38.348988: val_loss -0.7453 +2024-11-22 04:25:38.349072: Pseudo dice [0.819] +2024-11-22 04:25:38.349160: Epoch time: 18.31 s +2024-11-22 04:25:39.361467: +2024-11-22 04:25:39.361692: Epoch 3254 +2024-11-22 04:25:39.361808: Current learning rate: 0.00625 +2024-11-22 04:25:57.794526: train_loss -0.7881 +2024-11-22 04:25:57.794766: val_loss -0.755 +2024-11-22 04:25:57.794841: Pseudo dice [0.8208] +2024-11-22 04:25:57.794922: Epoch time: 18.43 s +2024-11-22 04:25:58.711297: +2024-11-22 04:25:58.711505: Epoch 3255 +2024-11-22 04:25:58.711613: Current learning rate: 0.00625 +2024-11-22 04:26:17.471233: train_loss -0.7882 +2024-11-22 04:26:17.471439: val_loss -0.7425 +2024-11-22 04:26:17.471523: Pseudo dice [0.8068] +2024-11-22 04:26:17.471601: Epoch time: 18.76 s +2024-11-22 04:26:18.322470: +2024-11-22 04:26:18.322662: Epoch 3256 +2024-11-22 04:26:18.322776: Current learning rate: 0.00625 +2024-11-22 04:26:37.078998: train_loss -0.7889 +2024-11-22 04:26:37.079207: val_loss -0.7223 +2024-11-22 04:26:37.079287: Pseudo dice [0.818] +2024-11-22 04:26:37.079363: Epoch time: 18.76 s +2024-11-22 04:26:37.949593: +2024-11-22 04:26:37.949814: Epoch 3257 +2024-11-22 04:26:37.949936: Current learning rate: 0.00625 +2024-11-22 04:26:58.285878: train_loss -0.7829 +2024-11-22 04:26:58.286140: val_loss -0.7445 +2024-11-22 04:26:58.286215: Pseudo dice [0.8152] +2024-11-22 04:26:58.286296: Epoch time: 20.34 s +2024-11-22 04:26:59.277590: +2024-11-22 04:26:59.277799: Epoch 3258 +2024-11-22 04:26:59.277910: Current learning rate: 0.00625 +2024-11-22 04:27:18.371480: train_loss -0.7756 +2024-11-22 04:27:18.371700: val_loss -0.7598 +2024-11-22 04:27:18.371838: Pseudo dice [0.835] +2024-11-22 04:27:18.371916: Epoch time: 19.09 s +2024-11-22 04:27:19.249333: +2024-11-22 04:27:19.249562: Epoch 3259 +2024-11-22 04:27:19.249678: Current learning rate: 0.00624 +2024-11-22 04:27:38.392107: train_loss -0.7598 +2024-11-22 04:27:38.392324: val_loss -0.7382 +2024-11-22 04:27:38.392397: Pseudo dice [0.8086] +2024-11-22 04:27:38.392480: Epoch time: 19.14 s +2024-11-22 04:27:39.265832: +2024-11-22 04:27:39.266036: Epoch 3260 +2024-11-22 04:27:39.266151: Current learning rate: 0.00624 +2024-11-22 04:27:57.761840: train_loss -0.7756 +2024-11-22 04:27:57.762150: val_loss -0.75 +2024-11-22 04:27:57.762229: Pseudo dice [0.8197] +2024-11-22 04:27:57.762314: Epoch time: 18.5 s +2024-11-22 04:27:58.642903: +2024-11-22 04:27:58.643137: Epoch 3261 +2024-11-22 04:27:58.643256: Current learning rate: 0.00624 +2024-11-22 04:28:17.365641: train_loss -0.7805 +2024-11-22 04:28:17.365850: val_loss -0.7487 +2024-11-22 04:28:17.365927: Pseudo dice [0.809] +2024-11-22 04:28:17.366010: Epoch time: 18.72 s +2024-11-22 04:28:18.447071: +2024-11-22 04:28:18.447267: Epoch 3262 +2024-11-22 04:28:18.447380: Current learning rate: 0.00624 +2024-11-22 04:28:37.177453: train_loss -0.7755 +2024-11-22 04:28:37.177668: val_loss -0.7455 +2024-11-22 04:28:37.177741: Pseudo dice [0.8165] +2024-11-22 04:28:37.177818: Epoch time: 18.73 s +2024-11-22 04:28:38.076385: +2024-11-22 04:28:38.076591: Epoch 3263 +2024-11-22 04:28:38.076708: Current learning rate: 0.00624 +2024-11-22 04:28:56.515721: train_loss -0.7781 +2024-11-22 04:28:56.516004: val_loss -0.7386 +2024-11-22 04:28:56.516083: Pseudo dice [0.826] +2024-11-22 04:28:56.516160: Epoch time: 18.44 s +2024-11-22 04:28:57.401552: +2024-11-22 04:28:57.401919: Epoch 3264 +2024-11-22 04:28:57.402038: Current learning rate: 0.00624 +2024-11-22 04:29:15.892931: train_loss -0.7871 +2024-11-22 04:29:15.893193: val_loss -0.7655 +2024-11-22 04:29:15.893273: Pseudo dice [0.8271] +2024-11-22 04:29:15.893356: Epoch time: 18.49 s +2024-11-22 04:29:16.763798: +2024-11-22 04:29:16.763997: Epoch 3265 +2024-11-22 04:29:16.764110: Current learning rate: 0.00624 +2024-11-22 04:29:34.853366: train_loss -0.7845 +2024-11-22 04:29:34.853587: val_loss -0.7526 +2024-11-22 04:29:34.853671: Pseudo dice [0.8233] +2024-11-22 04:29:34.853753: Epoch time: 18.09 s +2024-11-22 04:29:35.802388: +2024-11-22 04:29:35.802607: Epoch 3266 +2024-11-22 04:29:35.802759: Current learning rate: 0.00624 +2024-11-22 04:29:53.924163: train_loss -0.7891 +2024-11-22 04:29:53.924382: val_loss -0.7563 +2024-11-22 04:29:53.924455: Pseudo dice [0.8281] +2024-11-22 04:29:53.924532: Epoch time: 18.12 s +2024-11-22 04:29:54.851880: +2024-11-22 04:29:54.852088: Epoch 3267 +2024-11-22 04:29:54.852238: Current learning rate: 0.00624 +2024-11-22 04:30:13.342888: train_loss -0.7856 +2024-11-22 04:30:13.343170: val_loss -0.7662 +2024-11-22 04:30:13.343249: Pseudo dice [0.8387] +2024-11-22 04:30:13.343332: Epoch time: 18.49 s +2024-11-22 04:30:14.220617: +2024-11-22 04:30:14.220799: Epoch 3268 +2024-11-22 04:30:14.220911: Current learning rate: 0.00623 +2024-11-22 04:30:33.073132: train_loss -0.7752 +2024-11-22 04:30:33.073355: val_loss -0.7413 +2024-11-22 04:30:33.073429: Pseudo dice [0.8189] +2024-11-22 04:30:33.073503: Epoch time: 18.85 s +2024-11-22 04:30:34.369926: +2024-11-22 04:30:34.370128: Epoch 3269 +2024-11-22 04:30:34.370242: Current learning rate: 0.00623 +2024-11-22 04:30:52.937666: train_loss -0.7845 +2024-11-22 04:30:52.937888: val_loss -0.7531 +2024-11-22 04:30:52.937981: Pseudo dice [0.8449] +2024-11-22 04:30:52.938064: Epoch time: 18.57 s +2024-11-22 04:30:53.806107: +2024-11-22 04:30:53.806325: Epoch 3270 +2024-11-22 04:30:53.806438: Current learning rate: 0.00623 +2024-11-22 04:31:12.936088: train_loss -0.781 +2024-11-22 04:31:12.936298: val_loss -0.7459 +2024-11-22 04:31:12.936373: Pseudo dice [0.8314] +2024-11-22 04:31:12.936450: Epoch time: 19.13 s +2024-11-22 04:31:13.840194: +2024-11-22 04:31:13.840429: Epoch 3271 +2024-11-22 04:31:13.840542: Current learning rate: 0.00623 +2024-11-22 04:31:33.006619: train_loss -0.7783 +2024-11-22 04:31:33.006849: val_loss -0.7476 +2024-11-22 04:31:33.006922: Pseudo dice [0.8129] +2024-11-22 04:31:33.007006: Epoch time: 19.17 s +2024-11-22 04:31:33.880574: +2024-11-22 04:31:33.880783: Epoch 3272 +2024-11-22 04:31:33.880898: Current learning rate: 0.00623 +2024-11-22 04:31:51.902193: train_loss -0.789 +2024-11-22 04:31:51.902401: val_loss -0.7615 +2024-11-22 04:31:51.902478: Pseudo dice [0.8318] +2024-11-22 04:31:51.902563: Epoch time: 18.02 s +2024-11-22 04:31:52.804806: +2024-11-22 04:31:52.805002: Epoch 3273 +2024-11-22 04:31:52.805110: Current learning rate: 0.00623 +2024-11-22 04:32:10.785970: train_loss -0.7845 +2024-11-22 04:32:10.786215: val_loss -0.7423 +2024-11-22 04:32:10.786292: Pseudo dice [0.827] +2024-11-22 04:32:10.786369: Epoch time: 17.98 s +2024-11-22 04:32:11.691123: +2024-11-22 04:32:11.691360: Epoch 3274 +2024-11-22 04:32:11.691473: Current learning rate: 0.00623 +2024-11-22 04:32:30.766668: train_loss -0.7824 +2024-11-22 04:32:30.766906: val_loss -0.7247 +2024-11-22 04:32:30.766999: Pseudo dice [0.8096] +2024-11-22 04:32:30.767081: Epoch time: 19.08 s +2024-11-22 04:32:31.645883: +2024-11-22 04:32:31.646104: Epoch 3275 +2024-11-22 04:32:31.646221: Current learning rate: 0.00623 +2024-11-22 04:32:51.427951: train_loss -0.7856 +2024-11-22 04:32:51.428244: val_loss -0.7475 +2024-11-22 04:32:51.428323: Pseudo dice [0.8123] +2024-11-22 04:32:51.428408: Epoch time: 19.78 s +2024-11-22 04:32:52.301660: +2024-11-22 04:32:52.301881: Epoch 3276 +2024-11-22 04:32:52.302124: Current learning rate: 0.00622 +2024-11-22 04:33:11.184022: train_loss -0.7917 +2024-11-22 04:33:11.184240: val_loss -0.7204 +2024-11-22 04:33:11.184313: Pseudo dice [0.8094] +2024-11-22 04:33:11.184392: Epoch time: 18.88 s +2024-11-22 04:33:12.074907: +2024-11-22 04:33:12.075143: Epoch 3277 +2024-11-22 04:33:12.075261: Current learning rate: 0.00622 +2024-11-22 04:33:31.546136: train_loss -0.7664 +2024-11-22 04:33:31.546364: val_loss -0.728 +2024-11-22 04:33:31.546435: Pseudo dice [0.8213] +2024-11-22 04:33:31.546511: Epoch time: 19.47 s +2024-11-22 04:33:32.621374: +2024-11-22 04:33:32.621586: Epoch 3278 +2024-11-22 04:33:32.621704: Current learning rate: 0.00622 +2024-11-22 04:33:50.491267: train_loss -0.7762 +2024-11-22 04:33:50.491511: val_loss -0.7383 +2024-11-22 04:33:50.491590: Pseudo dice [0.8219] +2024-11-22 04:33:50.491672: Epoch time: 17.87 s +2024-11-22 04:33:51.365892: +2024-11-22 04:33:51.366102: Epoch 3279 +2024-11-22 04:33:51.366215: Current learning rate: 0.00622 +2024-11-22 04:34:09.962985: train_loss -0.7797 +2024-11-22 04:34:09.963216: val_loss -0.7318 +2024-11-22 04:34:09.963290: Pseudo dice [0.8229] +2024-11-22 04:34:09.963365: Epoch time: 18.6 s +2024-11-22 04:34:10.839840: +2024-11-22 04:34:10.840029: Epoch 3280 +2024-11-22 04:34:10.840146: Current learning rate: 0.00622 +2024-11-22 04:34:29.362432: train_loss -0.7714 +2024-11-22 04:34:29.365085: val_loss -0.7484 +2024-11-22 04:34:29.365208: Pseudo dice [0.8309] +2024-11-22 04:34:29.365298: Epoch time: 18.52 s +2024-11-22 04:34:30.273800: +2024-11-22 04:34:30.274086: Epoch 3281 +2024-11-22 04:34:30.274204: Current learning rate: 0.00622 +2024-11-22 04:34:49.619396: train_loss -0.7788 +2024-11-22 04:34:49.619634: val_loss -0.764 +2024-11-22 04:34:49.619710: Pseudo dice [0.8326] +2024-11-22 04:34:49.619789: Epoch time: 19.35 s +2024-11-22 04:34:50.510974: +2024-11-22 04:34:50.511184: Epoch 3282 +2024-11-22 04:34:50.511295: Current learning rate: 0.00622 +2024-11-22 04:35:09.870442: train_loss -0.7681 +2024-11-22 04:35:09.870668: val_loss -0.7376 +2024-11-22 04:35:09.870742: Pseudo dice [0.8253] +2024-11-22 04:35:09.870816: Epoch time: 19.36 s +2024-11-22 04:35:10.852681: +2024-11-22 04:35:10.852948: Epoch 3283 +2024-11-22 04:35:10.853069: Current learning rate: 0.00622 +2024-11-22 04:35:28.962140: train_loss -0.7839 +2024-11-22 04:35:28.962355: val_loss -0.7481 +2024-11-22 04:35:28.962431: Pseudo dice [0.8263] +2024-11-22 04:35:28.962508: Epoch time: 18.11 s +2024-11-22 04:35:29.894439: +2024-11-22 04:35:29.894634: Epoch 3284 +2024-11-22 04:35:29.894741: Current learning rate: 0.00621 +2024-11-22 04:35:48.820211: train_loss -0.7806 +2024-11-22 04:35:48.821971: val_loss -0.7421 +2024-11-22 04:35:48.822086: Pseudo dice [0.834] +2024-11-22 04:35:48.822174: Epoch time: 18.93 s +2024-11-22 04:35:49.833126: +2024-11-22 04:35:49.833326: Epoch 3285 +2024-11-22 04:35:49.833438: Current learning rate: 0.00621 +2024-11-22 04:36:07.715240: train_loss -0.785 +2024-11-22 04:36:07.715456: val_loss -0.7436 +2024-11-22 04:36:07.715535: Pseudo dice [0.8383] +2024-11-22 04:36:07.715612: Epoch time: 17.88 s +2024-11-22 04:36:08.594928: +2024-11-22 04:36:08.595123: Epoch 3286 +2024-11-22 04:36:08.595233: Current learning rate: 0.00621 +2024-11-22 04:36:28.053142: train_loss -0.783 +2024-11-22 04:36:28.053372: val_loss -0.7471 +2024-11-22 04:36:28.053450: Pseudo dice [0.8241] +2024-11-22 04:36:28.053528: Epoch time: 19.46 s +2024-11-22 04:36:28.929306: +2024-11-22 04:36:28.929504: Epoch 3287 +2024-11-22 04:36:28.929615: Current learning rate: 0.00621 +2024-11-22 04:36:47.553682: train_loss -0.7906 +2024-11-22 04:36:47.553903: val_loss -0.739 +2024-11-22 04:36:47.556180: Pseudo dice [0.8249] +2024-11-22 04:36:47.556275: Epoch time: 18.63 s +2024-11-22 04:36:48.428798: +2024-11-22 04:36:48.429010: Epoch 3288 +2024-11-22 04:36:48.429122: Current learning rate: 0.00621 +2024-11-22 04:37:06.565997: train_loss -0.7888 +2024-11-22 04:37:06.566249: val_loss -0.7304 +2024-11-22 04:37:06.566328: Pseudo dice [0.8033] +2024-11-22 04:37:06.566411: Epoch time: 18.14 s +2024-11-22 04:37:07.420640: +2024-11-22 04:37:07.420827: Epoch 3289 +2024-11-22 04:37:07.420928: Current learning rate: 0.00621 +2024-11-22 04:37:26.628659: train_loss -0.7776 +2024-11-22 04:37:26.628896: val_loss -0.7582 +2024-11-22 04:37:26.628977: Pseudo dice [0.8328] +2024-11-22 04:37:26.629060: Epoch time: 19.21 s +2024-11-22 04:37:27.484753: +2024-11-22 04:37:27.484960: Epoch 3290 +2024-11-22 04:37:27.485088: Current learning rate: 0.00621 +2024-11-22 04:37:46.387098: train_loss -0.7798 +2024-11-22 04:37:46.387317: val_loss -0.7373 +2024-11-22 04:37:46.387393: Pseudo dice [0.8296] +2024-11-22 04:37:46.387470: Epoch time: 18.9 s +2024-11-22 04:37:47.307276: +2024-11-22 04:37:47.307518: Epoch 3291 +2024-11-22 04:37:47.307632: Current learning rate: 0.00621 +2024-11-22 04:38:04.858868: train_loss -0.7766 +2024-11-22 04:38:04.859097: val_loss -0.7374 +2024-11-22 04:38:04.861391: Pseudo dice [0.8223] +2024-11-22 04:38:04.861496: Epoch time: 17.55 s +2024-11-22 04:38:06.395356: +2024-11-22 04:38:06.395581: Epoch 3292 +2024-11-22 04:38:06.395694: Current learning rate: 0.00621 +2024-11-22 04:38:25.871356: train_loss -0.7756 +2024-11-22 04:38:25.871927: val_loss -0.7527 +2024-11-22 04:38:25.872045: Pseudo dice [0.8329] +2024-11-22 04:38:25.872126: Epoch time: 19.48 s +2024-11-22 04:38:26.740706: +2024-11-22 04:38:26.740918: Epoch 3293 +2024-11-22 04:38:26.741036: Current learning rate: 0.0062 +2024-11-22 04:38:45.896293: train_loss -0.7784 +2024-11-22 04:38:45.896529: val_loss -0.7131 +2024-11-22 04:38:45.896624: Pseudo dice [0.8148] +2024-11-22 04:38:45.896715: Epoch time: 19.16 s +2024-11-22 04:38:46.762015: +2024-11-22 04:38:46.762239: Epoch 3294 +2024-11-22 04:38:46.762357: Current learning rate: 0.0062 +2024-11-22 04:39:05.096737: train_loss -0.7811 +2024-11-22 04:39:05.096943: val_loss -0.7675 +2024-11-22 04:39:05.097026: Pseudo dice [0.8302] +2024-11-22 04:39:05.097102: Epoch time: 18.34 s +2024-11-22 04:39:05.959196: +2024-11-22 04:39:05.959417: Epoch 3295 +2024-11-22 04:39:05.959530: Current learning rate: 0.0062 +2024-11-22 04:39:23.427240: train_loss -0.7817 +2024-11-22 04:39:23.429677: val_loss -0.7291 +2024-11-22 04:39:23.429800: Pseudo dice [0.8248] +2024-11-22 04:39:23.429886: Epoch time: 17.47 s +2024-11-22 04:39:24.482646: +2024-11-22 04:39:24.482935: Epoch 3296 +2024-11-22 04:39:24.483051: Current learning rate: 0.0062 +2024-11-22 04:39:43.064008: train_loss -0.7799 +2024-11-22 04:39:43.064214: val_loss -0.7226 +2024-11-22 04:39:43.064286: Pseudo dice [0.8389] +2024-11-22 04:39:43.064361: Epoch time: 18.58 s +2024-11-22 04:39:43.940358: +2024-11-22 04:39:43.940615: Epoch 3297 +2024-11-22 04:39:43.940727: Current learning rate: 0.0062 +2024-11-22 04:40:02.780212: train_loss -0.783 +2024-11-22 04:40:02.780438: val_loss -0.7571 +2024-11-22 04:40:02.780518: Pseudo dice [0.8411] +2024-11-22 04:40:02.780597: Epoch time: 18.84 s +2024-11-22 04:40:03.662775: +2024-11-22 04:40:03.662981: Epoch 3298 +2024-11-22 04:40:03.663095: Current learning rate: 0.0062 +2024-11-22 04:40:23.741156: train_loss -0.7893 +2024-11-22 04:40:23.741390: val_loss -0.7511 +2024-11-22 04:40:23.741472: Pseudo dice [0.835] +2024-11-22 04:40:23.741576: Epoch time: 20.08 s +2024-11-22 04:40:24.607615: +2024-11-22 04:40:24.607806: Epoch 3299 +2024-11-22 04:40:24.607917: Current learning rate: 0.0062 +2024-11-22 04:40:42.959828: train_loss -0.7864 +2024-11-22 04:40:42.960071: val_loss -0.7336 +2024-11-22 04:40:42.960229: Pseudo dice [0.8248] +2024-11-22 04:40:42.960310: Epoch time: 18.35 s +2024-11-22 04:40:44.106196: +2024-11-22 04:40:44.106433: Epoch 3300 +2024-11-22 04:40:44.106551: Current learning rate: 0.0062 +2024-11-22 04:41:02.939959: train_loss -0.785 +2024-11-22 04:41:02.940184: val_loss -0.7421 +2024-11-22 04:41:02.942495: Pseudo dice [0.8116] +2024-11-22 04:41:02.942608: Epoch time: 18.83 s +2024-11-22 04:41:03.993256: +2024-11-22 04:41:03.993469: Epoch 3301 +2024-11-22 04:41:03.993583: Current learning rate: 0.00619 +2024-11-22 04:41:22.777503: train_loss -0.7972 +2024-11-22 04:41:22.782921: val_loss -0.7622 +2024-11-22 04:41:22.783033: Pseudo dice [0.8344] +2024-11-22 04:41:22.783113: Epoch time: 18.79 s +2024-11-22 04:41:23.776352: +2024-11-22 04:41:23.776555: Epoch 3302 +2024-11-22 04:41:23.776782: Current learning rate: 0.00619 +2024-11-22 04:41:42.094983: train_loss -0.7894 +2024-11-22 04:41:42.095236: val_loss -0.7568 +2024-11-22 04:41:42.095316: Pseudo dice [0.8237] +2024-11-22 04:41:42.095400: Epoch time: 18.32 s +2024-11-22 04:41:42.972279: +2024-11-22 04:41:42.972525: Epoch 3303 +2024-11-22 04:41:42.972634: Current learning rate: 0.00619 +2024-11-22 04:42:02.164496: train_loss -0.7845 +2024-11-22 04:42:02.164986: val_loss -0.7365 +2024-11-22 04:42:02.165093: Pseudo dice [0.8357] +2024-11-22 04:42:02.165192: Epoch time: 19.19 s +2024-11-22 04:42:03.034069: +2024-11-22 04:42:03.034291: Epoch 3304 +2024-11-22 04:42:03.034402: Current learning rate: 0.00619 +2024-11-22 04:42:21.381258: train_loss -0.7935 +2024-11-22 04:42:21.381484: val_loss -0.7363 +2024-11-22 04:42:21.381566: Pseudo dice [0.82] +2024-11-22 04:42:21.381647: Epoch time: 18.35 s +2024-11-22 04:42:22.253134: +2024-11-22 04:42:22.253344: Epoch 3305 +2024-11-22 04:42:22.253455: Current learning rate: 0.00619 +2024-11-22 04:42:41.521896: train_loss -0.7913 +2024-11-22 04:42:41.522200: val_loss -0.7257 +2024-11-22 04:42:41.522280: Pseudo dice [0.8291] +2024-11-22 04:42:41.522371: Epoch time: 19.27 s +2024-11-22 04:42:42.421381: +2024-11-22 04:42:42.421587: Epoch 3306 +2024-11-22 04:42:42.421697: Current learning rate: 0.00619 +2024-11-22 04:43:01.341170: train_loss -0.7893 +2024-11-22 04:43:01.341395: val_loss -0.7269 +2024-11-22 04:43:01.341470: Pseudo dice [0.8258] +2024-11-22 04:43:01.341549: Epoch time: 18.92 s +2024-11-22 04:43:02.217500: +2024-11-22 04:43:02.217706: Epoch 3307 +2024-11-22 04:43:02.217821: Current learning rate: 0.00619 +2024-11-22 04:43:20.250946: train_loss -0.7853 +2024-11-22 04:43:20.251175: val_loss -0.7412 +2024-11-22 04:43:20.251252: Pseudo dice [0.8286] +2024-11-22 04:43:20.251331: Epoch time: 18.03 s +2024-11-22 04:43:21.311867: +2024-11-22 04:43:21.312096: Epoch 3308 +2024-11-22 04:43:21.312212: Current learning rate: 0.00619 +2024-11-22 04:43:39.296080: train_loss -0.7959 +2024-11-22 04:43:39.296299: val_loss -0.7811 +2024-11-22 04:43:39.296375: Pseudo dice [0.8297] +2024-11-22 04:43:39.296448: Epoch time: 17.98 s +2024-11-22 04:43:40.193217: +2024-11-22 04:43:40.193478: Epoch 3309 +2024-11-22 04:43:40.193588: Current learning rate: 0.00619 +2024-11-22 04:43:59.623165: train_loss -0.7874 +2024-11-22 04:43:59.623379: val_loss -0.7525 +2024-11-22 04:43:59.623455: Pseudo dice [0.8228] +2024-11-22 04:43:59.623533: Epoch time: 19.43 s +2024-11-22 04:44:00.643651: +2024-11-22 04:44:00.643913: Epoch 3310 +2024-11-22 04:44:00.644031: Current learning rate: 0.00618 +2024-11-22 04:44:19.528200: train_loss -0.7793 +2024-11-22 04:44:19.528439: val_loss -0.7421 +2024-11-22 04:44:19.528515: Pseudo dice [0.8227] +2024-11-22 04:44:19.528595: Epoch time: 18.89 s +2024-11-22 04:44:20.400101: +2024-11-22 04:44:20.400342: Epoch 3311 +2024-11-22 04:44:20.400454: Current learning rate: 0.00618 +2024-11-22 04:44:38.693295: train_loss -0.7853 +2024-11-22 04:44:38.693526: val_loss -0.7466 +2024-11-22 04:44:38.693598: Pseudo dice [0.82] +2024-11-22 04:44:38.693674: Epoch time: 18.29 s +2024-11-22 04:44:39.586103: +2024-11-22 04:44:39.586304: Epoch 3312 +2024-11-22 04:44:39.586415: Current learning rate: 0.00618 +2024-11-22 04:44:58.331139: train_loss -0.7633 +2024-11-22 04:44:58.331355: val_loss -0.7499 +2024-11-22 04:44:58.331430: Pseudo dice [0.8272] +2024-11-22 04:44:58.331505: Epoch time: 18.75 s +2024-11-22 04:44:59.195895: +2024-11-22 04:44:59.196115: Epoch 3313 +2024-11-22 04:44:59.196229: Current learning rate: 0.00618 +2024-11-22 04:45:18.810056: train_loss -0.7756 +2024-11-22 04:45:18.810298: val_loss -0.7423 +2024-11-22 04:45:18.810373: Pseudo dice [0.8051] +2024-11-22 04:45:18.810453: Epoch time: 19.61 s +2024-11-22 04:45:19.683949: +2024-11-22 04:45:19.684152: Epoch 3314 +2024-11-22 04:45:19.684269: Current learning rate: 0.00618 +2024-11-22 04:45:37.874464: train_loss -0.78 +2024-11-22 04:45:37.874671: val_loss -0.7517 +2024-11-22 04:45:37.874745: Pseudo dice [0.8488] +2024-11-22 04:45:37.874881: Epoch time: 18.19 s +2024-11-22 04:45:39.038774: +2024-11-22 04:45:39.039012: Epoch 3315 +2024-11-22 04:45:39.039138: Current learning rate: 0.00618 +2024-11-22 04:45:58.106577: train_loss -0.7845 +2024-11-22 04:45:58.106810: val_loss -0.7642 +2024-11-22 04:45:58.106883: Pseudo dice [0.846] +2024-11-22 04:45:58.106959: Epoch time: 19.07 s +2024-11-22 04:45:58.977310: +2024-11-22 04:45:58.977533: Epoch 3316 +2024-11-22 04:45:58.977644: Current learning rate: 0.00618 +2024-11-22 04:46:17.738922: train_loss -0.7832 +2024-11-22 04:46:17.739176: val_loss -0.7567 +2024-11-22 04:46:17.739259: Pseudo dice [0.8434] +2024-11-22 04:46:17.739347: Epoch time: 18.76 s +2024-11-22 04:46:18.624162: +2024-11-22 04:46:18.624369: Epoch 3317 +2024-11-22 04:46:18.624480: Current learning rate: 0.00618 +2024-11-22 04:46:37.649324: train_loss -0.7771 +2024-11-22 04:46:37.649546: val_loss -0.7616 +2024-11-22 04:46:37.649619: Pseudo dice [0.8368] +2024-11-22 04:46:37.649697: Epoch time: 19.03 s +2024-11-22 04:46:38.528639: +2024-11-22 04:46:38.528878: Epoch 3318 +2024-11-22 04:46:38.529000: Current learning rate: 0.00617 +2024-11-22 04:46:57.446927: train_loss -0.7712 +2024-11-22 04:46:57.447148: val_loss -0.7326 +2024-11-22 04:46:57.447222: Pseudo dice [0.8163] +2024-11-22 04:46:57.447301: Epoch time: 18.92 s +2024-11-22 04:46:58.472489: +2024-11-22 04:46:58.472708: Epoch 3319 +2024-11-22 04:46:58.472822: Current learning rate: 0.00617 +2024-11-22 04:47:17.979596: train_loss -0.7779 +2024-11-22 04:47:17.979860: val_loss -0.7372 +2024-11-22 04:47:17.979942: Pseudo dice [0.8333] +2024-11-22 04:47:17.980027: Epoch time: 19.51 s +2024-11-22 04:47:18.860158: +2024-11-22 04:47:18.860387: Epoch 3320 +2024-11-22 04:47:18.860501: Current learning rate: 0.00617 +2024-11-22 04:47:37.461267: train_loss -0.7672 +2024-11-22 04:47:37.461538: val_loss -0.7292 +2024-11-22 04:47:37.461612: Pseudo dice [0.8102] +2024-11-22 04:47:37.461694: Epoch time: 18.6 s +2024-11-22 04:47:38.457685: +2024-11-22 04:47:38.457927: Epoch 3321 +2024-11-22 04:47:38.458043: Current learning rate: 0.00617 +2024-11-22 04:47:56.494837: train_loss -0.7747 +2024-11-22 04:47:56.495145: val_loss -0.7258 +2024-11-22 04:47:56.495225: Pseudo dice [0.8148] +2024-11-22 04:47:56.495302: Epoch time: 18.04 s +2024-11-22 04:47:57.374020: +2024-11-22 04:47:57.374218: Epoch 3322 +2024-11-22 04:47:57.374335: Current learning rate: 0.00617 +2024-11-22 04:48:15.513316: train_loss -0.781 +2024-11-22 04:48:15.513541: val_loss -0.7136 +2024-11-22 04:48:15.513618: Pseudo dice [0.8274] +2024-11-22 04:48:15.513693: Epoch time: 18.14 s +2024-11-22 04:48:16.387430: +2024-11-22 04:48:16.387647: Epoch 3323 +2024-11-22 04:48:16.387768: Current learning rate: 0.00617 +2024-11-22 04:48:34.548658: train_loss -0.7884 +2024-11-22 04:48:34.548879: val_loss -0.748 +2024-11-22 04:48:34.548955: Pseudo dice [0.816] +2024-11-22 04:48:34.549043: Epoch time: 18.16 s +2024-11-22 04:48:35.424287: +2024-11-22 04:48:35.424480: Epoch 3324 +2024-11-22 04:48:35.424593: Current learning rate: 0.00617 +2024-11-22 04:48:54.118550: train_loss -0.7946 +2024-11-22 04:48:54.118850: val_loss -0.7585 +2024-11-22 04:48:54.118925: Pseudo dice [0.8297] +2024-11-22 04:48:54.119014: Epoch time: 18.7 s +2024-11-22 04:48:54.990777: +2024-11-22 04:48:54.990967: Epoch 3325 +2024-11-22 04:48:54.991084: Current learning rate: 0.00617 +2024-11-22 04:49:14.550196: train_loss -0.787 +2024-11-22 04:49:14.550407: val_loss -0.7596 +2024-11-22 04:49:14.550482: Pseudo dice [0.8245] +2024-11-22 04:49:14.550560: Epoch time: 19.56 s +2024-11-22 04:49:15.450640: +2024-11-22 04:49:15.450869: Epoch 3326 +2024-11-22 04:49:15.450994: Current learning rate: 0.00617 +2024-11-22 04:49:33.936578: train_loss -0.7854 +2024-11-22 04:49:33.937129: val_loss -0.7521 +2024-11-22 04:49:33.937245: Pseudo dice [0.8264] +2024-11-22 04:49:33.937327: Epoch time: 18.49 s +2024-11-22 04:49:34.846037: +2024-11-22 04:49:34.846273: Epoch 3327 +2024-11-22 04:49:34.846381: Current learning rate: 0.00616 +2024-11-22 04:49:53.918710: train_loss -0.777 +2024-11-22 04:49:53.919032: val_loss -0.7516 +2024-11-22 04:49:53.919112: Pseudo dice [0.8369] +2024-11-22 04:49:53.919199: Epoch time: 19.07 s +2024-11-22 04:49:54.798969: +2024-11-22 04:49:54.799309: Epoch 3328 +2024-11-22 04:49:54.799433: Current learning rate: 0.00616 +2024-11-22 04:50:13.468582: train_loss -0.7774 +2024-11-22 04:50:13.468806: val_loss -0.7354 +2024-11-22 04:50:13.468884: Pseudo dice [0.8312] +2024-11-22 04:50:13.468962: Epoch time: 18.67 s +2024-11-22 04:50:14.410896: +2024-11-22 04:50:14.411137: Epoch 3329 +2024-11-22 04:50:14.411254: Current learning rate: 0.00616 +2024-11-22 04:50:32.179457: train_loss -0.7807 +2024-11-22 04:50:32.179684: val_loss -0.719 +2024-11-22 04:50:32.179825: Pseudo dice [0.8001] +2024-11-22 04:50:32.179909: Epoch time: 17.77 s +2024-11-22 04:50:33.141179: +2024-11-22 04:50:33.141376: Epoch 3330 +2024-11-22 04:50:33.141490: Current learning rate: 0.00616 +2024-11-22 04:50:51.306135: train_loss -0.7649 +2024-11-22 04:50:51.306375: val_loss -0.7382 +2024-11-22 04:50:51.306447: Pseudo dice [0.8114] +2024-11-22 04:50:51.306530: Epoch time: 18.17 s +2024-11-22 04:50:52.187223: +2024-11-22 04:50:52.187415: Epoch 3331 +2024-11-22 04:50:52.187534: Current learning rate: 0.00616 +2024-11-22 04:51:10.785637: train_loss -0.7708 +2024-11-22 04:51:10.785860: val_loss -0.7736 +2024-11-22 04:51:10.785935: Pseudo dice [0.8143] +2024-11-22 04:51:10.786018: Epoch time: 18.6 s +2024-11-22 04:51:11.775837: +2024-11-22 04:51:11.776111: Epoch 3332 +2024-11-22 04:51:11.776224: Current learning rate: 0.00616 +2024-11-22 04:51:29.819553: train_loss -0.7797 +2024-11-22 04:51:29.819773: val_loss -0.7004 +2024-11-22 04:51:29.819846: Pseudo dice [0.8088] +2024-11-22 04:51:29.819921: Epoch time: 18.04 s +2024-11-22 04:51:30.698678: +2024-11-22 04:51:30.698872: Epoch 3333 +2024-11-22 04:51:30.698982: Current learning rate: 0.00616 +2024-11-22 04:51:50.206828: train_loss -0.7782 +2024-11-22 04:51:50.207060: val_loss -0.7307 +2024-11-22 04:51:50.207141: Pseudo dice [0.828] +2024-11-22 04:51:50.207240: Epoch time: 19.51 s +2024-11-22 04:51:51.080814: +2024-11-22 04:51:51.081045: Epoch 3334 +2024-11-22 04:51:51.081160: Current learning rate: 0.00616 +2024-11-22 04:52:10.018151: train_loss -0.7677 +2024-11-22 04:52:10.018399: val_loss -0.7497 +2024-11-22 04:52:10.018472: Pseudo dice [0.8235] +2024-11-22 04:52:10.018556: Epoch time: 18.94 s +2024-11-22 04:52:10.897274: +2024-11-22 04:52:10.897464: Epoch 3335 +2024-11-22 04:52:10.897579: Current learning rate: 0.00615 +2024-11-22 04:52:30.302035: train_loss -0.7704 +2024-11-22 04:52:30.302283: val_loss -0.7486 +2024-11-22 04:52:30.302370: Pseudo dice [0.8305] +2024-11-22 04:52:30.302449: Epoch time: 19.41 s +2024-11-22 04:52:31.206417: +2024-11-22 04:52:31.206616: Epoch 3336 +2024-11-22 04:52:31.206735: Current learning rate: 0.00615 +2024-11-22 04:52:49.233986: train_loss -0.7586 +2024-11-22 04:52:49.234209: val_loss -0.739 +2024-11-22 04:52:49.234286: Pseudo dice [0.8249] +2024-11-22 04:52:49.234363: Epoch time: 18.03 s +2024-11-22 04:52:50.115955: +2024-11-22 04:52:50.116180: Epoch 3337 +2024-11-22 04:52:50.116301: Current learning rate: 0.00615 +2024-11-22 04:53:09.294424: train_loss -0.7776 +2024-11-22 04:53:09.294669: val_loss -0.7307 +2024-11-22 04:53:09.294743: Pseudo dice [0.8119] +2024-11-22 04:53:09.294827: Epoch time: 19.18 s +2024-11-22 04:53:10.571255: +2024-11-22 04:53:10.571559: Epoch 3338 +2024-11-22 04:53:10.571674: Current learning rate: 0.00615 +2024-11-22 04:53:29.170490: train_loss -0.7742 +2024-11-22 04:53:29.170716: val_loss -0.7516 +2024-11-22 04:53:29.170796: Pseudo dice [0.8212] +2024-11-22 04:53:29.170873: Epoch time: 18.6 s +2024-11-22 04:53:30.229269: +2024-11-22 04:53:30.229498: Epoch 3339 +2024-11-22 04:53:30.229610: Current learning rate: 0.00615 +2024-11-22 04:53:48.693897: train_loss -0.7699 +2024-11-22 04:53:48.694134: val_loss -0.7437 +2024-11-22 04:53:48.696470: Pseudo dice [0.8336] +2024-11-22 04:53:48.696572: Epoch time: 18.47 s +2024-11-22 04:53:49.656057: +2024-11-22 04:53:49.656283: Epoch 3340 +2024-11-22 04:53:49.656398: Current learning rate: 0.00615 +2024-11-22 04:54:09.134554: train_loss -0.7767 +2024-11-22 04:54:09.134790: val_loss -0.7616 +2024-11-22 04:54:09.134867: Pseudo dice [0.8153] +2024-11-22 04:54:09.134996: Epoch time: 19.48 s +2024-11-22 04:54:10.017633: +2024-11-22 04:54:10.017858: Epoch 3341 +2024-11-22 04:54:10.017971: Current learning rate: 0.00615 +2024-11-22 04:54:29.254496: train_loss -0.7802 +2024-11-22 04:54:29.254706: val_loss -0.7353 +2024-11-22 04:54:29.254777: Pseudo dice [0.8197] +2024-11-22 04:54:29.254851: Epoch time: 19.24 s +2024-11-22 04:54:30.176863: +2024-11-22 04:54:30.177079: Epoch 3342 +2024-11-22 04:54:30.177191: Current learning rate: 0.00615 +2024-11-22 04:54:48.604765: train_loss -0.7816 +2024-11-22 04:54:48.610184: val_loss -0.7511 +2024-11-22 04:54:48.610352: Pseudo dice [0.8287] +2024-11-22 04:54:48.610435: Epoch time: 18.43 s +2024-11-22 04:54:49.664745: +2024-11-22 04:54:49.664948: Epoch 3343 +2024-11-22 04:54:49.665065: Current learning rate: 0.00614 +2024-11-22 04:55:08.366039: train_loss -0.7885 +2024-11-22 04:55:08.366282: val_loss -0.7352 +2024-11-22 04:55:08.366358: Pseudo dice [0.8121] +2024-11-22 04:55:08.366435: Epoch time: 18.7 s +2024-11-22 04:55:09.244119: +2024-11-22 04:55:09.244334: Epoch 3344 +2024-11-22 04:55:09.244449: Current learning rate: 0.00614 +2024-11-22 04:55:28.186722: train_loss -0.7819 +2024-11-22 04:55:28.186937: val_loss -0.771 +2024-11-22 04:55:28.187022: Pseudo dice [0.8255] +2024-11-22 04:55:28.187106: Epoch time: 18.94 s +2024-11-22 04:55:29.065742: +2024-11-22 04:55:29.065945: Epoch 3345 +2024-11-22 04:55:29.066066: Current learning rate: 0.00614 +2024-11-22 04:55:47.668255: train_loss -0.791 +2024-11-22 04:55:47.668502: val_loss -0.7652 +2024-11-22 04:55:47.668575: Pseudo dice [0.8302] +2024-11-22 04:55:47.668653: Epoch time: 18.6 s +2024-11-22 04:55:48.555171: +2024-11-22 04:55:48.555428: Epoch 3346 +2024-11-22 04:55:48.555544: Current learning rate: 0.00614 +2024-11-22 04:56:07.503590: train_loss -0.7782 +2024-11-22 04:56:07.503817: val_loss -0.7421 +2024-11-22 04:56:07.503892: Pseudo dice [0.826] +2024-11-22 04:56:07.503967: Epoch time: 18.95 s +2024-11-22 04:56:08.386330: +2024-11-22 04:56:08.386547: Epoch 3347 +2024-11-22 04:56:08.386667: Current learning rate: 0.00614 +2024-11-22 04:56:26.680221: train_loss -0.7793 +2024-11-22 04:56:26.680424: val_loss -0.7583 +2024-11-22 04:56:26.680495: Pseudo dice [0.8392] +2024-11-22 04:56:26.680568: Epoch time: 18.29 s +2024-11-22 04:56:27.574454: +2024-11-22 04:56:27.574645: Epoch 3348 +2024-11-22 04:56:27.574754: Current learning rate: 0.00614 +2024-11-22 04:56:45.728446: train_loss -0.7775 +2024-11-22 04:56:45.728755: val_loss -0.7581 +2024-11-22 04:56:45.728859: Pseudo dice [0.8357] +2024-11-22 04:56:45.728948: Epoch time: 18.15 s +2024-11-22 04:56:47.053044: +2024-11-22 04:56:47.053290: Epoch 3349 +2024-11-22 04:56:47.053409: Current learning rate: 0.00614 +2024-11-22 04:57:06.172137: train_loss -0.7739 +2024-11-22 04:57:06.172362: val_loss -0.7601 +2024-11-22 04:57:06.172438: Pseudo dice [0.8256] +2024-11-22 04:57:06.172517: Epoch time: 19.12 s +2024-11-22 04:57:07.301200: +2024-11-22 04:57:07.301400: Epoch 3350 +2024-11-22 04:57:07.301507: Current learning rate: 0.00614 +2024-11-22 04:57:25.984895: train_loss -0.7905 +2024-11-22 04:57:25.985115: val_loss -0.7485 +2024-11-22 04:57:25.985189: Pseudo dice [0.8323] +2024-11-22 04:57:25.985271: Epoch time: 18.68 s +2024-11-22 04:57:26.862833: +2024-11-22 04:57:26.863085: Epoch 3351 +2024-11-22 04:57:26.863199: Current learning rate: 0.00614 +2024-11-22 04:57:45.900117: train_loss -0.7906 +2024-11-22 04:57:45.900362: val_loss -0.7574 +2024-11-22 04:57:45.900438: Pseudo dice [0.8335] +2024-11-22 04:57:45.900521: Epoch time: 19.04 s +2024-11-22 04:57:46.787897: +2024-11-22 04:57:46.788101: Epoch 3352 +2024-11-22 04:57:46.788250: Current learning rate: 0.00613 +2024-11-22 04:58:05.670708: train_loss -0.7845 +2024-11-22 04:58:05.671007: val_loss -0.7396 +2024-11-22 04:58:05.671086: Pseudo dice [0.824] +2024-11-22 04:58:05.671161: Epoch time: 18.88 s +2024-11-22 04:58:06.665589: +2024-11-22 04:58:06.665817: Epoch 3353 +2024-11-22 04:58:06.665932: Current learning rate: 0.00613 +2024-11-22 04:58:25.496599: train_loss -0.7831 +2024-11-22 04:58:25.496819: val_loss -0.7233 +2024-11-22 04:58:25.496897: Pseudo dice [0.785] +2024-11-22 04:58:25.496972: Epoch time: 18.83 s +2024-11-22 04:58:26.378006: +2024-11-22 04:58:26.378215: Epoch 3354 +2024-11-22 04:58:26.378328: Current learning rate: 0.00613 +2024-11-22 04:58:43.730065: train_loss -0.7852 +2024-11-22 04:58:43.730290: val_loss -0.7524 +2024-11-22 04:58:43.730364: Pseudo dice [0.8289] +2024-11-22 04:58:43.730439: Epoch time: 17.35 s +2024-11-22 04:58:44.615070: +2024-11-22 04:58:44.615371: Epoch 3355 +2024-11-22 04:58:44.615485: Current learning rate: 0.00613 +2024-11-22 04:59:03.508544: train_loss -0.7939 +2024-11-22 04:59:03.508807: val_loss -0.7582 +2024-11-22 04:59:03.508881: Pseudo dice [0.835] +2024-11-22 04:59:03.508966: Epoch time: 18.89 s +2024-11-22 04:59:04.395049: +2024-11-22 04:59:04.395260: Epoch 3356 +2024-11-22 04:59:04.395381: Current learning rate: 0.00613 +2024-11-22 04:59:23.307999: train_loss -0.7831 +2024-11-22 04:59:23.308285: val_loss -0.7599 +2024-11-22 04:59:23.308367: Pseudo dice [0.8222] +2024-11-22 04:59:23.308446: Epoch time: 18.91 s +2024-11-22 04:59:24.194744: +2024-11-22 04:59:24.194977: Epoch 3357 +2024-11-22 04:59:24.195101: Current learning rate: 0.00613 +2024-11-22 04:59:42.705592: train_loss -0.794 +2024-11-22 04:59:42.706131: val_loss -0.7425 +2024-11-22 04:59:42.706213: Pseudo dice [0.8193] +2024-11-22 04:59:42.706290: Epoch time: 18.51 s +2024-11-22 04:59:43.591121: +2024-11-22 04:59:43.591322: Epoch 3358 +2024-11-22 04:59:43.591435: Current learning rate: 0.00613 +2024-11-22 05:00:04.306907: train_loss -0.7806 +2024-11-22 05:00:04.307128: val_loss -0.7503 +2024-11-22 05:00:04.307251: Pseudo dice [0.808] +2024-11-22 05:00:04.307336: Epoch time: 20.72 s +2024-11-22 05:00:05.193823: +2024-11-22 05:00:05.194048: Epoch 3359 +2024-11-22 05:00:05.194159: Current learning rate: 0.00613 +2024-11-22 05:00:23.060613: train_loss -0.7935 +2024-11-22 05:00:23.060866: val_loss -0.7411 +2024-11-22 05:00:23.060946: Pseudo dice [0.8238] +2024-11-22 05:00:23.061033: Epoch time: 17.87 s +2024-11-22 05:00:24.326082: +2024-11-22 05:00:24.326367: Epoch 3360 +2024-11-22 05:00:24.326481: Current learning rate: 0.00612 +2024-11-22 05:00:43.390977: train_loss -0.7764 +2024-11-22 05:00:43.391204: val_loss -0.7232 +2024-11-22 05:00:43.393438: Pseudo dice [0.8079] +2024-11-22 05:00:43.393565: Epoch time: 19.07 s +2024-11-22 05:00:44.316676: +2024-11-22 05:00:44.317003: Epoch 3361 +2024-11-22 05:00:44.317125: Current learning rate: 0.00612 +2024-11-22 05:01:03.605498: train_loss -0.7829 +2024-11-22 05:01:03.605711: val_loss -0.741 +2024-11-22 05:01:03.605784: Pseudo dice [0.8277] +2024-11-22 05:01:03.605862: Epoch time: 19.29 s +2024-11-22 05:01:04.492492: +2024-11-22 05:01:04.492713: Epoch 3362 +2024-11-22 05:01:04.492830: Current learning rate: 0.00612 +2024-11-22 05:01:23.968837: train_loss -0.7825 +2024-11-22 05:01:23.969083: val_loss -0.7347 +2024-11-22 05:01:23.969162: Pseudo dice [0.8178] +2024-11-22 05:01:23.969245: Epoch time: 19.48 s +2024-11-22 05:01:24.855268: +2024-11-22 05:01:24.855548: Epoch 3363 +2024-11-22 05:01:24.855668: Current learning rate: 0.00612 +2024-11-22 05:01:43.712319: train_loss -0.7837 +2024-11-22 05:01:43.712532: val_loss -0.7762 +2024-11-22 05:01:43.717770: Pseudo dice [0.8339] +2024-11-22 05:01:43.717933: Epoch time: 18.86 s +2024-11-22 05:01:44.788059: +2024-11-22 05:01:44.807399: Epoch 3364 +2024-11-22 05:01:44.807546: Current learning rate: 0.00612 +2024-11-22 05:02:02.517303: train_loss -0.7744 +2024-11-22 05:02:02.517523: val_loss -0.7275 +2024-11-22 05:02:02.517597: Pseudo dice [0.8268] +2024-11-22 05:02:02.517674: Epoch time: 17.73 s +2024-11-22 05:02:03.400742: +2024-11-22 05:02:03.400957: Epoch 3365 +2024-11-22 05:02:03.401077: Current learning rate: 0.00612 +2024-11-22 05:02:23.085727: train_loss -0.7711 +2024-11-22 05:02:23.086031: val_loss -0.7424 +2024-11-22 05:02:23.086111: Pseudo dice [0.8417] +2024-11-22 05:02:23.086190: Epoch time: 19.69 s +2024-11-22 05:02:23.971840: +2024-11-22 05:02:23.972036: Epoch 3366 +2024-11-22 05:02:23.972148: Current learning rate: 0.00612 +2024-11-22 05:02:43.877772: train_loss -0.7757 +2024-11-22 05:02:43.878061: val_loss -0.7554 +2024-11-22 05:02:43.878149: Pseudo dice [0.8323] +2024-11-22 05:02:43.878242: Epoch time: 19.91 s +2024-11-22 05:02:44.771928: +2024-11-22 05:02:44.772130: Epoch 3367 +2024-11-22 05:02:44.772244: Current learning rate: 0.00612 +2024-11-22 05:03:03.198271: train_loss -0.7759 +2024-11-22 05:03:03.198495: val_loss -0.7462 +2024-11-22 05:03:03.198578: Pseudo dice [0.8349] +2024-11-22 05:03:03.198657: Epoch time: 18.43 s +2024-11-22 05:03:04.089268: +2024-11-22 05:03:04.089472: Epoch 3368 +2024-11-22 05:03:04.089589: Current learning rate: 0.00612 +2024-11-22 05:03:22.761575: train_loss -0.7716 +2024-11-22 05:03:22.761797: val_loss -0.7233 +2024-11-22 05:03:22.761875: Pseudo dice [0.8274] +2024-11-22 05:03:22.761951: Epoch time: 18.67 s +2024-11-22 05:03:23.646914: +2024-11-22 05:03:23.647131: Epoch 3369 +2024-11-22 05:03:23.647245: Current learning rate: 0.00611 +2024-11-22 05:03:41.569301: train_loss -0.7802 +2024-11-22 05:03:41.569607: val_loss -0.7481 +2024-11-22 05:03:41.569689: Pseudo dice [0.8217] +2024-11-22 05:03:41.569772: Epoch time: 17.92 s +2024-11-22 05:03:42.452752: +2024-11-22 05:03:42.452957: Epoch 3370 +2024-11-22 05:03:42.453074: Current learning rate: 0.00611 +2024-11-22 05:04:01.140572: train_loss -0.7865 +2024-11-22 05:04:01.140781: val_loss -0.7157 +2024-11-22 05:04:01.140857: Pseudo dice [0.8207] +2024-11-22 05:04:01.140936: Epoch time: 18.69 s +2024-11-22 05:04:02.028975: +2024-11-22 05:04:02.029169: Epoch 3371 +2024-11-22 05:04:02.029277: Current learning rate: 0.00611 +2024-11-22 05:04:21.923901: train_loss -0.784 +2024-11-22 05:04:21.924396: val_loss -0.7419 +2024-11-22 05:04:21.924500: Pseudo dice [0.8251] +2024-11-22 05:04:21.924581: Epoch time: 19.9 s +2024-11-22 05:04:22.809206: +2024-11-22 05:04:22.809430: Epoch 3372 +2024-11-22 05:04:22.809545: Current learning rate: 0.00611 +2024-11-22 05:04:41.301345: train_loss -0.7916 +2024-11-22 05:04:41.301589: val_loss -0.7541 +2024-11-22 05:04:41.301669: Pseudo dice [0.827] +2024-11-22 05:04:41.301748: Epoch time: 18.49 s +2024-11-22 05:04:42.179593: +2024-11-22 05:04:42.179810: Epoch 3373 +2024-11-22 05:04:42.179922: Current learning rate: 0.00611 +2024-11-22 05:04:59.926546: train_loss -0.7908 +2024-11-22 05:04:59.926807: val_loss -0.7429 +2024-11-22 05:04:59.926883: Pseudo dice [0.8278] +2024-11-22 05:04:59.926964: Epoch time: 17.75 s +2024-11-22 05:05:00.910602: +2024-11-22 05:05:00.910825: Epoch 3374 +2024-11-22 05:05:00.910937: Current learning rate: 0.00611 +2024-11-22 05:05:19.056010: train_loss -0.7846 +2024-11-22 05:05:19.056223: val_loss -0.7609 +2024-11-22 05:05:19.056297: Pseudo dice [0.8301] +2024-11-22 05:05:19.056373: Epoch time: 18.15 s +2024-11-22 05:05:19.940383: +2024-11-22 05:05:19.940666: Epoch 3375 +2024-11-22 05:05:19.940776: Current learning rate: 0.00611 +2024-11-22 05:05:39.463714: train_loss -0.776 +2024-11-22 05:05:39.463966: val_loss -0.7551 +2024-11-22 05:05:39.464051: Pseudo dice [0.8199] +2024-11-22 05:05:39.464137: Epoch time: 19.52 s +2024-11-22 05:05:40.371185: +2024-11-22 05:05:40.371394: Epoch 3376 +2024-11-22 05:05:40.371505: Current learning rate: 0.00611 +2024-11-22 05:05:58.000483: train_loss -0.7891 +2024-11-22 05:05:58.000693: val_loss -0.7441 +2024-11-22 05:05:58.000767: Pseudo dice [0.8329] +2024-11-22 05:05:58.012278: Epoch time: 17.63 s +2024-11-22 05:05:58.894779: +2024-11-22 05:05:58.895002: Epoch 3377 +2024-11-22 05:05:58.895115: Current learning rate: 0.0061 +2024-11-22 05:06:17.929497: train_loss -0.7854 +2024-11-22 05:06:17.929719: val_loss -0.7413 +2024-11-22 05:06:17.929797: Pseudo dice [0.8282] +2024-11-22 05:06:17.929871: Epoch time: 19.04 s +2024-11-22 05:06:18.887712: +2024-11-22 05:06:18.887918: Epoch 3378 +2024-11-22 05:06:18.888033: Current learning rate: 0.0061 +2024-11-22 05:06:37.181689: train_loss -0.7763 +2024-11-22 05:06:37.181975: val_loss -0.7316 +2024-11-22 05:06:37.182063: Pseudo dice [0.8394] +2024-11-22 05:06:37.182142: Epoch time: 18.29 s +2024-11-22 05:06:38.213496: +2024-11-22 05:06:38.213822: Epoch 3379 +2024-11-22 05:06:38.213942: Current learning rate: 0.0061 +2024-11-22 05:06:56.976622: train_loss -0.7859 +2024-11-22 05:06:56.976883: val_loss -0.7269 +2024-11-22 05:06:56.976966: Pseudo dice [0.8352] +2024-11-22 05:06:56.977058: Epoch time: 18.76 s +2024-11-22 05:06:57.951848: +2024-11-22 05:06:57.952058: Epoch 3380 +2024-11-22 05:06:57.952168: Current learning rate: 0.0061 +2024-11-22 05:07:16.222111: train_loss -0.7866 +2024-11-22 05:07:16.222396: val_loss -0.7258 +2024-11-22 05:07:16.222507: Pseudo dice [0.8286] +2024-11-22 05:07:16.222587: Epoch time: 18.27 s +2024-11-22 05:07:17.109577: +2024-11-22 05:07:17.109790: Epoch 3381 +2024-11-22 05:07:17.109898: Current learning rate: 0.0061 +2024-11-22 05:07:36.146360: train_loss -0.7882 +2024-11-22 05:07:36.146607: val_loss -0.7346 +2024-11-22 05:07:36.146684: Pseudo dice [0.8282] +2024-11-22 05:07:36.146761: Epoch time: 19.04 s +2024-11-22 05:07:37.395020: +2024-11-22 05:07:37.395240: Epoch 3382 +2024-11-22 05:07:37.395354: Current learning rate: 0.0061 +2024-11-22 05:07:56.083022: train_loss -0.7738 +2024-11-22 05:07:56.083282: val_loss -0.7112 +2024-11-22 05:07:56.083356: Pseudo dice [0.8179] +2024-11-22 05:07:56.083441: Epoch time: 18.69 s +2024-11-22 05:07:57.003788: +2024-11-22 05:07:57.004027: Epoch 3383 +2024-11-22 05:07:57.004137: Current learning rate: 0.0061 +2024-11-22 05:08:15.849320: train_loss -0.7619 +2024-11-22 05:08:15.849540: val_loss -0.7334 +2024-11-22 05:08:15.849614: Pseudo dice [0.8312] +2024-11-22 05:08:15.849689: Epoch time: 18.85 s +2024-11-22 05:08:16.738547: +2024-11-22 05:08:16.738765: Epoch 3384 +2024-11-22 05:08:16.738882: Current learning rate: 0.0061 +2024-11-22 05:08:34.506316: train_loss -0.7767 +2024-11-22 05:08:34.506853: val_loss -0.7351 +2024-11-22 05:08:34.506933: Pseudo dice [0.8299] +2024-11-22 05:08:34.507053: Epoch time: 17.77 s +2024-11-22 05:08:35.389437: +2024-11-22 05:08:35.389716: Epoch 3385 +2024-11-22 05:08:35.389826: Current learning rate: 0.00609 +2024-11-22 05:08:53.466381: train_loss -0.7835 +2024-11-22 05:08:53.468977: val_loss -0.7342 +2024-11-22 05:08:53.469094: Pseudo dice [0.8187] +2024-11-22 05:08:53.469178: Epoch time: 18.08 s +2024-11-22 05:08:54.596292: +2024-11-22 05:08:54.596523: Epoch 3386 +2024-11-22 05:08:54.596639: Current learning rate: 0.00609 +2024-11-22 05:09:12.378742: train_loss -0.7878 +2024-11-22 05:09:12.384162: val_loss -0.7511 +2024-11-22 05:09:12.384252: Pseudo dice [0.8187] +2024-11-22 05:09:12.384332: Epoch time: 17.78 s +2024-11-22 05:09:13.286854: +2024-11-22 05:09:13.287085: Epoch 3387 +2024-11-22 05:09:13.287200: Current learning rate: 0.00609 +2024-11-22 05:09:32.548856: train_loss -0.7722 +2024-11-22 05:09:32.549076: val_loss -0.7389 +2024-11-22 05:09:32.549152: Pseudo dice [0.8227] +2024-11-22 05:09:32.549232: Epoch time: 19.26 s +2024-11-22 05:09:33.436112: +2024-11-22 05:09:33.436314: Epoch 3388 +2024-11-22 05:09:33.436433: Current learning rate: 0.00609 +2024-11-22 05:09:52.524071: train_loss -0.7792 +2024-11-22 05:09:52.524336: val_loss -0.7292 +2024-11-22 05:09:52.524418: Pseudo dice [0.8137] +2024-11-22 05:09:52.524493: Epoch time: 19.09 s +2024-11-22 05:09:53.413152: +2024-11-22 05:09:53.413469: Epoch 3389 +2024-11-22 05:09:53.413599: Current learning rate: 0.00609 +2024-11-22 05:10:11.064464: train_loss -0.7808 +2024-11-22 05:10:11.065375: val_loss -0.7239 +2024-11-22 05:10:11.065492: Pseudo dice [0.8148] +2024-11-22 05:10:11.065594: Epoch time: 17.65 s +2024-11-22 05:10:12.041970: +2024-11-22 05:10:12.042204: Epoch 3390 +2024-11-22 05:10:12.042327: Current learning rate: 0.00609 +2024-11-22 05:10:30.942347: train_loss -0.7781 +2024-11-22 05:10:30.942559: val_loss -0.7364 +2024-11-22 05:10:30.942633: Pseudo dice [0.8222] +2024-11-22 05:10:30.942710: Epoch time: 18.9 s +2024-11-22 05:10:31.820350: +2024-11-22 05:10:31.820549: Epoch 3391 +2024-11-22 05:10:31.820661: Current learning rate: 0.00609 +2024-11-22 05:10:50.682755: train_loss -0.7843 +2024-11-22 05:10:50.682988: val_loss -0.7602 +2024-11-22 05:10:50.683074: Pseudo dice [0.8433] +2024-11-22 05:10:50.683154: Epoch time: 18.86 s +2024-11-22 05:10:51.564914: +2024-11-22 05:10:51.565106: Epoch 3392 +2024-11-22 05:10:51.565217: Current learning rate: 0.00609 +2024-11-22 05:11:10.020785: train_loss -0.792 +2024-11-22 05:11:10.021009: val_loss -0.7652 +2024-11-22 05:11:10.021088: Pseudo dice [0.8373] +2024-11-22 05:11:10.021173: Epoch time: 18.46 s +2024-11-22 05:11:11.107638: +2024-11-22 05:11:11.107873: Epoch 3393 +2024-11-22 05:11:11.107985: Current learning rate: 0.00609 +2024-11-22 05:11:30.000177: train_loss -0.7811 +2024-11-22 05:11:30.000482: val_loss -0.7526 +2024-11-22 05:11:30.000559: Pseudo dice [0.8275] +2024-11-22 05:11:30.000638: Epoch time: 18.89 s +2024-11-22 05:11:31.261059: +2024-11-22 05:11:31.261285: Epoch 3394 +2024-11-22 05:11:31.261398: Current learning rate: 0.00608 +2024-11-22 05:11:49.171842: train_loss -0.7859 +2024-11-22 05:11:49.172071: val_loss -0.7542 +2024-11-22 05:11:49.172146: Pseudo dice [0.822] +2024-11-22 05:11:49.172226: Epoch time: 17.91 s +2024-11-22 05:11:50.038698: +2024-11-22 05:11:50.038903: Epoch 3395 +2024-11-22 05:11:50.039020: Current learning rate: 0.00608 +2024-11-22 05:12:08.350289: train_loss -0.7864 +2024-11-22 05:12:08.350506: val_loss -0.7379 +2024-11-22 05:12:08.350581: Pseudo dice [0.8218] +2024-11-22 05:12:08.350659: Epoch time: 18.31 s +2024-11-22 05:12:09.348104: +2024-11-22 05:12:09.348333: Epoch 3396 +2024-11-22 05:12:09.348452: Current learning rate: 0.00608 +2024-11-22 05:12:27.363504: train_loss -0.7934 +2024-11-22 05:12:27.363753: val_loss -0.7629 +2024-11-22 05:12:27.363830: Pseudo dice [0.8354] +2024-11-22 05:12:27.363916: Epoch time: 18.02 s +2024-11-22 05:12:28.240894: +2024-11-22 05:12:28.241120: Epoch 3397 +2024-11-22 05:12:28.241230: Current learning rate: 0.00608 +2024-11-22 05:12:47.351414: train_loss -0.7773 +2024-11-22 05:12:47.351653: val_loss -0.7464 +2024-11-22 05:12:47.351780: Pseudo dice [0.8062] +2024-11-22 05:12:47.351857: Epoch time: 19.11 s +2024-11-22 05:12:48.224367: +2024-11-22 05:12:48.224638: Epoch 3398 +2024-11-22 05:12:48.224759: Current learning rate: 0.00608 +2024-11-22 05:13:06.946889: train_loss -0.7759 +2024-11-22 05:13:06.947483: val_loss -0.754 +2024-11-22 05:13:06.947563: Pseudo dice [0.835] +2024-11-22 05:13:06.947640: Epoch time: 18.72 s +2024-11-22 05:13:07.834459: +2024-11-22 05:13:07.834660: Epoch 3399 +2024-11-22 05:13:07.834775: Current learning rate: 0.00608 +2024-11-22 05:13:26.857374: train_loss -0.7929 +2024-11-22 05:13:26.857655: val_loss -0.7298 +2024-11-22 05:13:26.857732: Pseudo dice [0.8335] +2024-11-22 05:13:26.857811: Epoch time: 19.02 s +2024-11-22 05:13:27.990561: +2024-11-22 05:13:27.990765: Epoch 3400 +2024-11-22 05:13:27.990877: Current learning rate: 0.00608 +2024-11-22 05:13:45.977849: train_loss -0.782 +2024-11-22 05:13:45.978085: val_loss -0.7502 +2024-11-22 05:13:45.978158: Pseudo dice [0.832] +2024-11-22 05:13:45.978297: Epoch time: 17.99 s +2024-11-22 05:13:46.863262: +2024-11-22 05:13:46.863476: Epoch 3401 +2024-11-22 05:13:46.863592: Current learning rate: 0.00608 +2024-11-22 05:14:05.926724: train_loss -0.7902 +2024-11-22 05:14:05.927014: val_loss -0.7422 +2024-11-22 05:14:05.927090: Pseudo dice [0.826] +2024-11-22 05:14:05.927169: Epoch time: 19.06 s +2024-11-22 05:14:06.813600: +2024-11-22 05:14:06.813793: Epoch 3402 +2024-11-22 05:14:06.814153: Current learning rate: 0.00607 +2024-11-22 05:14:26.443830: train_loss -0.7915 +2024-11-22 05:14:26.444056: val_loss -0.7534 +2024-11-22 05:14:26.444134: Pseudo dice [0.8189] +2024-11-22 05:14:26.444211: Epoch time: 19.63 s +2024-11-22 05:14:27.352338: +2024-11-22 05:14:27.352536: Epoch 3403 +2024-11-22 05:14:27.352655: Current learning rate: 0.00607 +2024-11-22 05:14:46.052790: train_loss -0.7836 +2024-11-22 05:14:46.053109: val_loss -0.7364 +2024-11-22 05:14:46.053201: Pseudo dice [0.8345] +2024-11-22 05:14:46.053286: Epoch time: 18.7 s +2024-11-22 05:14:46.942843: +2024-11-22 05:14:46.943063: Epoch 3404 +2024-11-22 05:14:46.943185: Current learning rate: 0.00607 +2024-11-22 05:15:06.832087: train_loss -0.7896 +2024-11-22 05:15:06.832299: val_loss -0.7087 +2024-11-22 05:15:06.833398: Pseudo dice [0.827] +2024-11-22 05:15:06.833500: Epoch time: 19.89 s +2024-11-22 05:15:08.191731: +2024-11-22 05:15:08.191929: Epoch 3405 +2024-11-22 05:15:08.192053: Current learning rate: 0.00607 +2024-11-22 05:15:26.606911: train_loss -0.7782 +2024-11-22 05:15:26.609324: val_loss -0.7281 +2024-11-22 05:15:26.609455: Pseudo dice [0.8013] +2024-11-22 05:15:26.609612: Epoch time: 18.42 s +2024-11-22 05:15:27.590331: +2024-11-22 05:15:27.590618: Epoch 3406 +2024-11-22 05:15:27.590735: Current learning rate: 0.00607 +2024-11-22 05:15:45.909141: train_loss -0.788 +2024-11-22 05:15:45.909387: val_loss -0.7575 +2024-11-22 05:15:45.909464: Pseudo dice [0.8336] +2024-11-22 05:15:45.909556: Epoch time: 18.32 s +2024-11-22 05:15:46.795128: +2024-11-22 05:15:46.795333: Epoch 3407 +2024-11-22 05:15:46.795443: Current learning rate: 0.00607 +2024-11-22 05:16:05.402514: train_loss -0.7846 +2024-11-22 05:16:05.402732: val_loss -0.7434 +2024-11-22 05:16:05.402810: Pseudo dice [0.822] +2024-11-22 05:16:05.402893: Epoch time: 18.61 s +2024-11-22 05:16:06.503543: +2024-11-22 05:16:06.503735: Epoch 3408 +2024-11-22 05:16:06.503852: Current learning rate: 0.00607 +2024-11-22 05:16:24.875803: train_loss -0.787 +2024-11-22 05:16:24.878203: val_loss -0.7359 +2024-11-22 05:16:24.878295: Pseudo dice [0.8191] +2024-11-22 05:16:24.878376: Epoch time: 18.37 s +2024-11-22 05:16:25.934593: +2024-11-22 05:16:25.934823: Epoch 3409 +2024-11-22 05:16:25.934935: Current learning rate: 0.00607 +2024-11-22 05:16:43.824275: train_loss -0.7725 +2024-11-22 05:16:43.824493: val_loss -0.7384 +2024-11-22 05:16:43.824569: Pseudo dice [0.8131] +2024-11-22 05:16:43.824645: Epoch time: 17.89 s +2024-11-22 05:16:44.710820: +2024-11-22 05:16:44.711025: Epoch 3410 +2024-11-22 05:16:44.711136: Current learning rate: 0.00607 +2024-11-22 05:17:02.832782: train_loss -0.7913 +2024-11-22 05:17:02.833031: val_loss -0.7593 +2024-11-22 05:17:02.833104: Pseudo dice [0.8341] +2024-11-22 05:17:02.833189: Epoch time: 18.12 s +2024-11-22 05:17:03.719997: +2024-11-22 05:17:03.720285: Epoch 3411 +2024-11-22 05:17:03.720397: Current learning rate: 0.00606 +2024-11-22 05:17:21.763828: train_loss -0.7765 +2024-11-22 05:17:21.766252: val_loss -0.7305 +2024-11-22 05:17:21.766381: Pseudo dice [0.808] +2024-11-22 05:17:21.766465: Epoch time: 18.04 s +2024-11-22 05:17:22.714405: +2024-11-22 05:17:22.714619: Epoch 3412 +2024-11-22 05:17:22.714733: Current learning rate: 0.00606 +2024-11-22 05:17:41.985473: train_loss -0.7862 +2024-11-22 05:17:41.985744: val_loss -0.745 +2024-11-22 05:17:41.985830: Pseudo dice [0.8209] +2024-11-22 05:17:41.985908: Epoch time: 19.27 s +2024-11-22 05:17:42.881512: +2024-11-22 05:17:42.881700: Epoch 3413 +2024-11-22 05:17:42.881811: Current learning rate: 0.00606 +2024-11-22 05:18:01.478681: train_loss -0.7859 +2024-11-22 05:18:01.478921: val_loss -0.7361 +2024-11-22 05:18:01.479009: Pseudo dice [0.8002] +2024-11-22 05:18:01.479099: Epoch time: 18.6 s +2024-11-22 05:18:02.379197: +2024-11-22 05:18:02.379388: Epoch 3414 +2024-11-22 05:18:02.379505: Current learning rate: 0.00606 +2024-11-22 05:18:21.886564: train_loss -0.7653 +2024-11-22 05:18:21.886848: val_loss -0.7469 +2024-11-22 05:18:21.886926: Pseudo dice [0.8246] +2024-11-22 05:18:21.887057: Epoch time: 19.51 s +2024-11-22 05:18:22.790132: +2024-11-22 05:18:22.790323: Epoch 3415 +2024-11-22 05:18:22.790438: Current learning rate: 0.00606 +2024-11-22 05:18:41.828309: train_loss -0.7675 +2024-11-22 05:18:41.829591: val_loss -0.7192 +2024-11-22 05:18:41.829669: Pseudo dice [0.7984] +2024-11-22 05:18:41.829744: Epoch time: 19.04 s +2024-11-22 05:18:43.186373: +2024-11-22 05:18:43.186626: Epoch 3416 +2024-11-22 05:18:43.186751: Current learning rate: 0.00606 +2024-11-22 05:19:01.098628: train_loss -0.7792 +2024-11-22 05:19:01.098917: val_loss -0.7573 +2024-11-22 05:19:01.099006: Pseudo dice [0.8463] +2024-11-22 05:19:01.099087: Epoch time: 17.91 s +2024-11-22 05:19:02.008234: +2024-11-22 05:19:02.008453: Epoch 3417 +2024-11-22 05:19:02.008564: Current learning rate: 0.00606 +2024-11-22 05:19:20.258633: train_loss -0.7731 +2024-11-22 05:19:20.258874: val_loss -0.7586 +2024-11-22 05:19:20.258952: Pseudo dice [0.8139] +2024-11-22 05:19:20.259050: Epoch time: 18.25 s +2024-11-22 05:19:21.256294: +2024-11-22 05:19:21.256595: Epoch 3418 +2024-11-22 05:19:21.256710: Current learning rate: 0.00606 +2024-11-22 05:19:41.211280: train_loss -0.7543 +2024-11-22 05:19:41.211790: val_loss -0.7117 +2024-11-22 05:19:41.211887: Pseudo dice [0.7946] +2024-11-22 05:19:41.211967: Epoch time: 19.96 s +2024-11-22 05:19:42.095106: +2024-11-22 05:19:42.095319: Epoch 3419 +2024-11-22 05:19:42.095434: Current learning rate: 0.00605 +2024-11-22 05:19:59.956177: train_loss -0.7622 +2024-11-22 05:19:59.956404: val_loss -0.7236 +2024-11-22 05:19:59.956487: Pseudo dice [0.815] +2024-11-22 05:19:59.956565: Epoch time: 17.86 s +2024-11-22 05:20:00.838492: +2024-11-22 05:20:00.838713: Epoch 3420 +2024-11-22 05:20:00.838831: Current learning rate: 0.00605 +2024-11-22 05:20:20.091027: train_loss -0.7713 +2024-11-22 05:20:20.091255: val_loss -0.7188 +2024-11-22 05:20:20.091341: Pseudo dice [0.8351] +2024-11-22 05:20:20.091421: Epoch time: 19.25 s +2024-11-22 05:20:20.975605: +2024-11-22 05:20:20.975830: Epoch 3421 +2024-11-22 05:20:20.975947: Current learning rate: 0.00605 +2024-11-22 05:20:39.560033: train_loss -0.7795 +2024-11-22 05:20:39.560253: val_loss -0.7476 +2024-11-22 05:20:39.560341: Pseudo dice [0.8244] +2024-11-22 05:20:39.560429: Epoch time: 18.59 s +2024-11-22 05:20:40.455412: +2024-11-22 05:20:40.455625: Epoch 3422 +2024-11-22 05:20:40.455740: Current learning rate: 0.00605 +2024-11-22 05:20:59.773370: train_loss -0.7587 +2024-11-22 05:20:59.773623: val_loss -0.7594 +2024-11-22 05:20:59.773700: Pseudo dice [0.8359] +2024-11-22 05:20:59.773789: Epoch time: 19.32 s +2024-11-22 05:21:00.744554: +2024-11-22 05:21:00.744748: Epoch 3423 +2024-11-22 05:21:00.744862: Current learning rate: 0.00605 +2024-11-22 05:21:20.371816: train_loss -0.7771 +2024-11-22 05:21:20.372046: val_loss -0.7497 +2024-11-22 05:21:20.372125: Pseudo dice [0.8371] +2024-11-22 05:21:20.372208: Epoch time: 19.63 s +2024-11-22 05:21:21.284522: +2024-11-22 05:21:21.284741: Epoch 3424 +2024-11-22 05:21:21.284855: Current learning rate: 0.00605 +2024-11-22 05:21:38.599012: train_loss -0.7898 +2024-11-22 05:21:38.599241: val_loss -0.7434 +2024-11-22 05:21:38.599326: Pseudo dice [0.8257] +2024-11-22 05:21:38.599415: Epoch time: 17.32 s +2024-11-22 05:21:39.633270: +2024-11-22 05:21:39.633481: Epoch 3425 +2024-11-22 05:21:39.633600: Current learning rate: 0.00605 +2024-11-22 05:21:57.734556: train_loss -0.7854 +2024-11-22 05:21:57.734796: val_loss -0.7622 +2024-11-22 05:21:57.734877: Pseudo dice [0.8421] +2024-11-22 05:21:57.734962: Epoch time: 18.1 s +2024-11-22 05:21:58.614758: +2024-11-22 05:21:58.614962: Epoch 3426 +2024-11-22 05:21:58.615076: Current learning rate: 0.00605 +2024-11-22 05:22:17.333805: train_loss -0.7884 +2024-11-22 05:22:17.334021: val_loss -0.7394 +2024-11-22 05:22:17.334093: Pseudo dice [0.8235] +2024-11-22 05:22:17.334168: Epoch time: 18.72 s +2024-11-22 05:22:18.378175: +2024-11-22 05:22:18.378377: Epoch 3427 +2024-11-22 05:22:18.378487: Current learning rate: 0.00605 +2024-11-22 05:22:36.264146: train_loss -0.7694 +2024-11-22 05:22:36.264366: val_loss -0.7406 +2024-11-22 05:22:36.287674: Pseudo dice [0.8291] +2024-11-22 05:22:36.287835: Epoch time: 17.89 s +2024-11-22 05:22:37.572328: +2024-11-22 05:22:37.572565: Epoch 3428 +2024-11-22 05:22:37.572682: Current learning rate: 0.00604 +2024-11-22 05:22:55.869018: train_loss -0.7611 +2024-11-22 05:22:55.869264: val_loss -0.754 +2024-11-22 05:22:55.869343: Pseudo dice [0.8166] +2024-11-22 05:22:55.869428: Epoch time: 18.3 s +2024-11-22 05:22:56.753278: +2024-11-22 05:22:56.753509: Epoch 3429 +2024-11-22 05:22:56.753630: Current learning rate: 0.00604 +2024-11-22 05:23:14.495308: train_loss -0.7738 +2024-11-22 05:23:14.495516: val_loss -0.7309 +2024-11-22 05:23:14.495587: Pseudo dice [0.8178] +2024-11-22 05:23:14.495663: Epoch time: 17.74 s +2024-11-22 05:23:15.371023: +2024-11-22 05:23:15.371241: Epoch 3430 +2024-11-22 05:23:15.371354: Current learning rate: 0.00604 +2024-11-22 05:23:34.431888: train_loss -0.7768 +2024-11-22 05:23:34.432107: val_loss -0.7339 +2024-11-22 05:23:34.432184: Pseudo dice [0.83] +2024-11-22 05:23:34.432261: Epoch time: 19.06 s +2024-11-22 05:23:35.319310: +2024-11-22 05:23:35.319555: Epoch 3431 +2024-11-22 05:23:35.319672: Current learning rate: 0.00604 +2024-11-22 05:23:54.564430: train_loss -0.7842 +2024-11-22 05:23:54.564651: val_loss -0.7291 +2024-11-22 05:23:54.564725: Pseudo dice [0.8305] +2024-11-22 05:23:54.564959: Epoch time: 19.25 s +2024-11-22 05:23:55.559299: +2024-11-22 05:23:55.559506: Epoch 3432 +2024-11-22 05:23:55.559614: Current learning rate: 0.00604 +2024-11-22 05:24:13.708581: train_loss -0.7907 +2024-11-22 05:24:13.708822: val_loss -0.7295 +2024-11-22 05:24:13.708896: Pseudo dice [0.8067] +2024-11-22 05:24:13.708975: Epoch time: 18.15 s +2024-11-22 05:24:14.592174: +2024-11-22 05:24:14.592378: Epoch 3433 +2024-11-22 05:24:14.592492: Current learning rate: 0.00604 +2024-11-22 05:24:33.244931: train_loss -0.7842 +2024-11-22 05:24:33.245150: val_loss -0.7659 +2024-11-22 05:24:33.245229: Pseudo dice [0.8305] +2024-11-22 05:24:33.245314: Epoch time: 18.65 s +2024-11-22 05:24:34.126052: +2024-11-22 05:24:34.126313: Epoch 3434 +2024-11-22 05:24:34.126431: Current learning rate: 0.00604 +2024-11-22 05:24:52.596011: train_loss -0.7864 +2024-11-22 05:24:52.596238: val_loss -0.7664 +2024-11-22 05:24:52.596350: Pseudo dice [0.8356] +2024-11-22 05:24:52.596483: Epoch time: 18.47 s +2024-11-22 05:24:53.485734: +2024-11-22 05:24:53.485965: Epoch 3435 +2024-11-22 05:24:53.486083: Current learning rate: 0.00604 +2024-11-22 05:25:12.282440: train_loss -0.7949 +2024-11-22 05:25:12.282690: val_loss -0.7468 +2024-11-22 05:25:12.282770: Pseudo dice [0.8254] +2024-11-22 05:25:12.288139: Epoch time: 18.8 s +2024-11-22 05:25:13.489890: +2024-11-22 05:25:13.490111: Epoch 3436 +2024-11-22 05:25:13.490223: Current learning rate: 0.00603 +2024-11-22 05:25:31.109951: train_loss -0.792 +2024-11-22 05:25:31.110173: val_loss -0.7696 +2024-11-22 05:25:31.110249: Pseudo dice [0.8257] +2024-11-22 05:25:31.110330: Epoch time: 17.62 s +2024-11-22 05:25:31.978663: +2024-11-22 05:25:31.978863: Epoch 3437 +2024-11-22 05:25:31.978973: Current learning rate: 0.00603 +2024-11-22 05:25:50.264025: train_loss -0.786 +2024-11-22 05:25:50.264237: val_loss -0.7521 +2024-11-22 05:25:50.264312: Pseudo dice [0.8361] +2024-11-22 05:25:50.264388: Epoch time: 18.29 s +2024-11-22 05:25:51.148055: +2024-11-22 05:25:51.148247: Epoch 3438 +2024-11-22 05:25:51.148361: Current learning rate: 0.00603 +2024-11-22 05:26:09.252901: train_loss -0.796 +2024-11-22 05:26:09.253132: val_loss -0.7474 +2024-11-22 05:26:09.253210: Pseudo dice [0.8242] +2024-11-22 05:26:09.253288: Epoch time: 18.11 s +2024-11-22 05:26:10.528055: +2024-11-22 05:26:10.528270: Epoch 3439 +2024-11-22 05:26:10.528382: Current learning rate: 0.00603 +2024-11-22 05:26:28.971738: train_loss -0.7925 +2024-11-22 05:26:28.972008: val_loss -0.7636 +2024-11-22 05:26:28.972089: Pseudo dice [0.8449] +2024-11-22 05:26:28.972172: Epoch time: 18.44 s +2024-11-22 05:26:29.851028: +2024-11-22 05:26:29.851228: Epoch 3440 +2024-11-22 05:26:29.851333: Current learning rate: 0.00603 +2024-11-22 05:26:49.325545: train_loss -0.7816 +2024-11-22 05:26:49.325752: val_loss -0.755 +2024-11-22 05:26:49.325827: Pseudo dice [0.8497] +2024-11-22 05:26:49.325937: Epoch time: 19.48 s +2024-11-22 05:26:50.203908: +2024-11-22 05:26:50.204239: Epoch 3441 +2024-11-22 05:26:50.204357: Current learning rate: 0.00603 +2024-11-22 05:27:09.252617: train_loss -0.792 +2024-11-22 05:27:09.252836: val_loss -0.7493 +2024-11-22 05:27:09.252916: Pseudo dice [0.8297] +2024-11-22 05:27:09.253003: Epoch time: 19.05 s +2024-11-22 05:27:10.128881: +2024-11-22 05:27:10.129096: Epoch 3442 +2024-11-22 05:27:10.129216: Current learning rate: 0.00603 +2024-11-22 05:27:30.052948: train_loss -0.7783 +2024-11-22 05:27:30.056785: val_loss -0.7289 +2024-11-22 05:27:30.056913: Pseudo dice [0.8165] +2024-11-22 05:27:30.057002: Epoch time: 19.93 s +2024-11-22 05:27:31.147895: +2024-11-22 05:27:31.148121: Epoch 3443 +2024-11-22 05:27:31.148237: Current learning rate: 0.00603 +2024-11-22 05:27:49.853252: train_loss -0.782 +2024-11-22 05:27:49.853460: val_loss -0.735 +2024-11-22 05:27:49.853542: Pseudo dice [0.8047] +2024-11-22 05:27:49.853617: Epoch time: 18.71 s +2024-11-22 05:27:50.735359: +2024-11-22 05:27:50.735564: Epoch 3444 +2024-11-22 05:27:50.735677: Current learning rate: 0.00602 +2024-11-22 05:28:10.195093: train_loss -0.7766 +2024-11-22 05:28:10.195362: val_loss -0.7149 +2024-11-22 05:28:10.195440: Pseudo dice [0.8006] +2024-11-22 05:28:10.195519: Epoch time: 19.46 s +2024-11-22 05:28:11.120210: +2024-11-22 05:28:11.120432: Epoch 3445 +2024-11-22 05:28:11.120547: Current learning rate: 0.00602 +2024-11-22 05:28:30.104668: train_loss -0.7756 +2024-11-22 05:28:30.107060: val_loss -0.7382 +2024-11-22 05:28:30.107146: Pseudo dice [0.8256] +2024-11-22 05:28:30.107229: Epoch time: 18.99 s +2024-11-22 05:28:31.043828: +2024-11-22 05:28:31.044137: Epoch 3446 +2024-11-22 05:28:31.044249: Current learning rate: 0.00602 +2024-11-22 05:28:49.962059: train_loss -0.7845 +2024-11-22 05:28:49.962279: val_loss -0.725 +2024-11-22 05:28:49.962354: Pseudo dice [0.8244] +2024-11-22 05:28:49.962433: Epoch time: 18.92 s +2024-11-22 05:28:50.848058: +2024-11-22 05:28:50.848273: Epoch 3447 +2024-11-22 05:28:50.848388: Current learning rate: 0.00602 +2024-11-22 05:29:08.351438: train_loss -0.7855 +2024-11-22 05:29:08.351977: val_loss -0.7501 +2024-11-22 05:29:08.352061: Pseudo dice [0.8319] +2024-11-22 05:29:08.352139: Epoch time: 17.5 s +2024-11-22 05:29:09.326038: +2024-11-22 05:29:09.326242: Epoch 3448 +2024-11-22 05:29:09.326360: Current learning rate: 0.00602 +2024-11-22 05:29:26.893233: train_loss -0.7819 +2024-11-22 05:29:26.893446: val_loss -0.753 +2024-11-22 05:29:26.893521: Pseudo dice [0.8529] +2024-11-22 05:29:26.893599: Epoch time: 17.57 s +2024-11-22 05:29:27.772908: +2024-11-22 05:29:27.773129: Epoch 3449 +2024-11-22 05:29:27.773262: Current learning rate: 0.00602 +2024-11-22 05:29:45.789348: train_loss -0.7661 +2024-11-22 05:29:45.789580: val_loss -0.7512 +2024-11-22 05:29:45.789655: Pseudo dice [0.8192] +2024-11-22 05:29:45.789769: Epoch time: 18.02 s +2024-11-22 05:29:46.882036: +2024-11-22 05:29:46.882238: Epoch 3450 +2024-11-22 05:29:46.882351: Current learning rate: 0.00602 +2024-11-22 05:30:05.391482: train_loss -0.7783 +2024-11-22 05:30:05.391948: val_loss -0.7236 +2024-11-22 05:30:05.392054: Pseudo dice [0.8076] +2024-11-22 05:30:05.392131: Epoch time: 18.51 s +2024-11-22 05:30:06.290221: +2024-11-22 05:30:06.290447: Epoch 3451 +2024-11-22 05:30:06.290560: Current learning rate: 0.00602 +2024-11-22 05:30:24.464679: train_loss -0.7695 +2024-11-22 05:30:24.464898: val_loss -0.7539 +2024-11-22 05:30:24.464976: Pseudo dice [0.8151] +2024-11-22 05:30:24.465062: Epoch time: 18.18 s +2024-11-22 05:30:25.461017: +2024-11-22 05:30:25.461231: Epoch 3452 +2024-11-22 05:30:25.461344: Current learning rate: 0.00602 +2024-11-22 05:30:43.374025: train_loss -0.7865 +2024-11-22 05:30:43.374252: val_loss -0.7496 +2024-11-22 05:30:43.374326: Pseudo dice [0.8266] +2024-11-22 05:30:43.374404: Epoch time: 17.91 s +2024-11-22 05:30:44.254806: +2024-11-22 05:30:44.255018: Epoch 3453 +2024-11-22 05:30:44.255124: Current learning rate: 0.00601 +2024-11-22 05:31:02.093432: train_loss -0.79 +2024-11-22 05:31:02.093645: val_loss -0.7524 +2024-11-22 05:31:02.093719: Pseudo dice [0.8359] +2024-11-22 05:31:02.093796: Epoch time: 17.84 s +2024-11-22 05:31:03.087686: +2024-11-22 05:31:03.087890: Epoch 3454 +2024-11-22 05:31:03.088005: Current learning rate: 0.00601 +2024-11-22 05:31:21.804441: train_loss -0.7921 +2024-11-22 05:31:21.804654: val_loss -0.7189 +2024-11-22 05:31:21.804730: Pseudo dice [0.8322] +2024-11-22 05:31:21.804830: Epoch time: 18.72 s +2024-11-22 05:31:22.693367: +2024-11-22 05:31:22.693650: Epoch 3455 +2024-11-22 05:31:22.693761: Current learning rate: 0.00601 +2024-11-22 05:31:42.503593: train_loss -0.7791 +2024-11-22 05:31:42.503804: val_loss -0.7458 +2024-11-22 05:31:42.503879: Pseudo dice [0.8256] +2024-11-22 05:31:42.503953: Epoch time: 19.81 s +2024-11-22 05:31:43.394714: +2024-11-22 05:31:43.394933: Epoch 3456 +2024-11-22 05:31:43.395054: Current learning rate: 0.00601 +2024-11-22 05:32:02.230345: train_loss -0.7939 +2024-11-22 05:32:02.235772: val_loss -0.7478 +2024-11-22 05:32:02.235919: Pseudo dice [0.8256] +2024-11-22 05:32:02.236016: Epoch time: 18.84 s +2024-11-22 05:32:03.141201: +2024-11-22 05:32:03.141425: Epoch 3457 +2024-11-22 05:32:03.141547: Current learning rate: 0.00601 +2024-11-22 05:32:21.539429: train_loss -0.7811 +2024-11-22 05:32:21.539654: val_loss -0.7584 +2024-11-22 05:32:21.539728: Pseudo dice [0.8344] +2024-11-22 05:32:21.539953: Epoch time: 18.4 s +2024-11-22 05:32:22.556393: +2024-11-22 05:32:22.556593: Epoch 3458 +2024-11-22 05:32:22.556701: Current learning rate: 0.00601 +2024-11-22 05:32:41.345550: train_loss -0.7507 +2024-11-22 05:32:41.345780: val_loss -0.7208 +2024-11-22 05:32:41.345862: Pseudo dice [0.8076] +2024-11-22 05:32:41.345941: Epoch time: 18.79 s +2024-11-22 05:32:42.256195: +2024-11-22 05:32:42.256479: Epoch 3459 +2024-11-22 05:32:42.256593: Current learning rate: 0.00601 +2024-11-22 05:33:01.799717: train_loss -0.751 +2024-11-22 05:33:01.799958: val_loss -0.7399 +2024-11-22 05:33:01.800042: Pseudo dice [0.8254] +2024-11-22 05:33:01.800125: Epoch time: 19.54 s +2024-11-22 05:33:02.691153: +2024-11-22 05:33:02.691343: Epoch 3460 +2024-11-22 05:33:02.691456: Current learning rate: 0.00601 +2024-11-22 05:33:22.467810: train_loss -0.7538 +2024-11-22 05:33:22.468031: val_loss -0.7482 +2024-11-22 05:33:22.468108: Pseudo dice [0.8186] +2024-11-22 05:33:22.468186: Epoch time: 19.78 s +2024-11-22 05:33:23.666041: +2024-11-22 05:33:23.666224: Epoch 3461 +2024-11-22 05:33:23.666317: Current learning rate: 0.006 +2024-11-22 05:33:43.143031: train_loss -0.7625 +2024-11-22 05:33:43.143257: val_loss -0.7583 +2024-11-22 05:33:43.144467: Pseudo dice [0.8316] +2024-11-22 05:33:43.144578: Epoch time: 19.48 s +2024-11-22 05:33:44.041760: +2024-11-22 05:33:44.041982: Epoch 3462 +2024-11-22 05:33:44.042101: Current learning rate: 0.006 +2024-11-22 05:34:03.586298: train_loss -0.7802 +2024-11-22 05:34:03.586514: val_loss -0.7315 +2024-11-22 05:34:03.586602: Pseudo dice [0.8188] +2024-11-22 05:34:03.586685: Epoch time: 19.55 s +2024-11-22 05:34:04.449180: +2024-11-22 05:34:04.449401: Epoch 3463 +2024-11-22 05:34:04.449515: Current learning rate: 0.006 +2024-11-22 05:34:23.928646: train_loss -0.7871 +2024-11-22 05:34:23.928943: val_loss -0.7385 +2024-11-22 05:34:23.929030: Pseudo dice [0.833] +2024-11-22 05:34:23.929133: Epoch time: 19.48 s +2024-11-22 05:34:24.815512: +2024-11-22 05:34:24.815710: Epoch 3464 +2024-11-22 05:34:24.815824: Current learning rate: 0.006 +2024-11-22 05:34:43.831198: train_loss -0.7838 +2024-11-22 05:34:43.831425: val_loss -0.71 +2024-11-22 05:34:43.831501: Pseudo dice [0.8196] +2024-11-22 05:34:43.831577: Epoch time: 19.02 s +2024-11-22 05:34:44.775667: +2024-11-22 05:34:44.775880: Epoch 3465 +2024-11-22 05:34:44.775996: Current learning rate: 0.006 +2024-11-22 05:35:03.661553: train_loss -0.7882 +2024-11-22 05:35:03.661776: val_loss -0.7134 +2024-11-22 05:35:03.661855: Pseudo dice [0.7991] +2024-11-22 05:35:03.662612: Epoch time: 18.89 s +2024-11-22 05:35:04.682613: +2024-11-22 05:35:04.682830: Epoch 3466 +2024-11-22 05:35:04.682943: Current learning rate: 0.006 +2024-11-22 05:35:23.611663: train_loss -0.782 +2024-11-22 05:35:23.611873: val_loss -0.7545 +2024-11-22 05:35:23.611947: Pseudo dice [0.8309] +2024-11-22 05:35:23.612030: Epoch time: 18.93 s +2024-11-22 05:35:24.498252: +2024-11-22 05:35:24.498456: Epoch 3467 +2024-11-22 05:35:24.498568: Current learning rate: 0.006 +2024-11-22 05:35:43.089670: train_loss -0.7987 +2024-11-22 05:35:43.089909: val_loss -0.756 +2024-11-22 05:35:43.089985: Pseudo dice [0.8293] +2024-11-22 05:35:43.090074: Epoch time: 18.59 s +2024-11-22 05:35:43.981111: +2024-11-22 05:35:43.981325: Epoch 3468 +2024-11-22 05:35:43.981444: Current learning rate: 0.006 +2024-11-22 05:36:03.983781: train_loss -0.7949 +2024-11-22 05:36:03.984005: val_loss -0.7628 +2024-11-22 05:36:03.984082: Pseudo dice [0.8423] +2024-11-22 05:36:03.984160: Epoch time: 20.0 s +2024-11-22 05:36:04.873187: +2024-11-22 05:36:04.873392: Epoch 3469 +2024-11-22 05:36:04.873506: Current learning rate: 0.006 +2024-11-22 05:36:22.909818: train_loss -0.7839 +2024-11-22 05:36:22.910063: val_loss -0.7521 +2024-11-22 05:36:22.910205: Pseudo dice [0.8408] +2024-11-22 05:36:22.910289: Epoch time: 18.04 s +2024-11-22 05:36:23.791075: +2024-11-22 05:36:23.791266: Epoch 3470 +2024-11-22 05:36:23.791375: Current learning rate: 0.00599 +2024-11-22 05:36:42.246075: train_loss -0.788 +2024-11-22 05:36:42.246328: val_loss -0.7457 +2024-11-22 05:36:42.246406: Pseudo dice [0.8322] +2024-11-22 05:36:42.246515: Epoch time: 18.46 s +2024-11-22 05:36:43.177438: +2024-11-22 05:36:43.177633: Epoch 3471 +2024-11-22 05:36:43.177746: Current learning rate: 0.00599 +2024-11-22 05:37:01.659646: train_loss -0.7863 +2024-11-22 05:37:01.660821: val_loss -0.7377 +2024-11-22 05:37:01.660928: Pseudo dice [0.8155] +2024-11-22 05:37:01.661020: Epoch time: 18.48 s +2024-11-22 05:37:02.542444: +2024-11-22 05:37:02.542896: Epoch 3472 +2024-11-22 05:37:02.543037: Current learning rate: 0.00599 +2024-11-22 05:37:22.077695: train_loss -0.7688 +2024-11-22 05:37:22.083092: val_loss -0.7304 +2024-11-22 05:37:22.083199: Pseudo dice [0.8191] +2024-11-22 05:37:22.083278: Epoch time: 19.54 s +2024-11-22 05:37:23.493542: +2024-11-22 05:37:23.493768: Epoch 3473 +2024-11-22 05:37:23.493880: Current learning rate: 0.00599 +2024-11-22 05:37:41.984355: train_loss -0.7762 +2024-11-22 05:37:41.984921: val_loss -0.7559 +2024-11-22 05:37:41.985023: Pseudo dice [0.835] +2024-11-22 05:37:41.985112: Epoch time: 18.49 s +2024-11-22 05:37:42.878532: +2024-11-22 05:37:42.878758: Epoch 3474 +2024-11-22 05:37:42.878874: Current learning rate: 0.00599 +2024-11-22 05:38:01.444723: train_loss -0.7963 +2024-11-22 05:38:01.444980: val_loss -0.7532 +2024-11-22 05:38:01.445060: Pseudo dice [0.8319] +2024-11-22 05:38:01.445137: Epoch time: 18.57 s +2024-11-22 05:38:02.334120: +2024-11-22 05:38:02.334356: Epoch 3475 +2024-11-22 05:38:02.334475: Current learning rate: 0.00599 +2024-11-22 05:38:21.177490: train_loss -0.7866 +2024-11-22 05:38:21.177708: val_loss -0.7725 +2024-11-22 05:38:21.177782: Pseudo dice [0.8254] +2024-11-22 05:38:21.177856: Epoch time: 18.84 s +2024-11-22 05:38:22.063678: +2024-11-22 05:38:22.063888: Epoch 3476 +2024-11-22 05:38:22.064012: Current learning rate: 0.00599 +2024-11-22 05:38:41.047598: train_loss -0.7768 +2024-11-22 05:38:41.047820: val_loss -0.7264 +2024-11-22 05:38:41.047899: Pseudo dice [0.808] +2024-11-22 05:38:41.047984: Epoch time: 18.98 s +2024-11-22 05:38:41.931229: +2024-11-22 05:38:41.931443: Epoch 3477 +2024-11-22 05:38:41.931569: Current learning rate: 0.00599 +2024-11-22 05:39:00.447773: train_loss -0.7838 +2024-11-22 05:39:00.448027: val_loss -0.7358 +2024-11-22 05:39:00.450291: Pseudo dice [0.8255] +2024-11-22 05:39:00.450394: Epoch time: 18.52 s +2024-11-22 05:39:01.440101: +2024-11-22 05:39:01.440323: Epoch 3478 +2024-11-22 05:39:01.440438: Current learning rate: 0.00598 +2024-11-22 05:39:20.675276: train_loss -0.7777 +2024-11-22 05:39:20.678210: val_loss -0.755 +2024-11-22 05:39:20.678329: Pseudo dice [0.828] +2024-11-22 05:39:20.678410: Epoch time: 19.24 s +2024-11-22 05:39:21.703160: +2024-11-22 05:39:21.703355: Epoch 3479 +2024-11-22 05:39:21.703466: Current learning rate: 0.00598 +2024-11-22 05:39:41.654334: train_loss -0.7851 +2024-11-22 05:39:41.654557: val_loss -0.7455 +2024-11-22 05:39:41.654634: Pseudo dice [0.8248] +2024-11-22 05:39:41.654713: Epoch time: 19.95 s +2024-11-22 05:39:42.650315: +2024-11-22 05:39:42.650531: Epoch 3480 +2024-11-22 05:39:42.650646: Current learning rate: 0.00598 +2024-11-22 05:40:01.848089: train_loss -0.7771 +2024-11-22 05:40:01.848333: val_loss -0.7317 +2024-11-22 05:40:01.848486: Pseudo dice [0.8195] +2024-11-22 05:40:01.848575: Epoch time: 19.2 s +2024-11-22 05:40:02.737787: +2024-11-22 05:40:02.738041: Epoch 3481 +2024-11-22 05:40:02.738157: Current learning rate: 0.00598 +2024-11-22 05:40:20.718670: train_loss -0.7779 +2024-11-22 05:40:20.718988: val_loss -0.7588 +2024-11-22 05:40:20.719074: Pseudo dice [0.8397] +2024-11-22 05:40:20.719150: Epoch time: 17.98 s +2024-11-22 05:40:21.606525: +2024-11-22 05:40:21.606734: Epoch 3482 +2024-11-22 05:40:21.606846: Current learning rate: 0.00598 +2024-11-22 05:40:39.156518: train_loss -0.7889 +2024-11-22 05:40:39.156758: val_loss -0.7518 +2024-11-22 05:40:39.156837: Pseudo dice [0.8271] +2024-11-22 05:40:39.156915: Epoch time: 17.55 s +2024-11-22 05:40:40.045263: +2024-11-22 05:40:40.045472: Epoch 3483 +2024-11-22 05:40:40.045586: Current learning rate: 0.00598 +2024-11-22 05:40:58.903896: train_loss -0.7866 +2024-11-22 05:40:58.904124: val_loss -0.7461 +2024-11-22 05:40:58.904209: Pseudo dice [0.8232] +2024-11-22 05:40:58.904422: Epoch time: 18.86 s +2024-11-22 05:41:00.150327: +2024-11-22 05:41:00.150536: Epoch 3484 +2024-11-22 05:41:00.150650: Current learning rate: 0.00598 +2024-11-22 05:41:18.474750: train_loss -0.7736 +2024-11-22 05:41:18.475024: val_loss -0.7452 +2024-11-22 05:41:18.475106: Pseudo dice [0.8233] +2024-11-22 05:41:18.475247: Epoch time: 18.33 s +2024-11-22 05:41:19.363298: +2024-11-22 05:41:19.363505: Epoch 3485 +2024-11-22 05:41:19.363617: Current learning rate: 0.00598 +2024-11-22 05:41:38.179415: train_loss -0.7845 +2024-11-22 05:41:38.179641: val_loss -0.7168 +2024-11-22 05:41:38.179716: Pseudo dice [0.8251] +2024-11-22 05:41:38.179793: Epoch time: 18.82 s +2024-11-22 05:41:39.088641: +2024-11-22 05:41:39.088903: Epoch 3486 +2024-11-22 05:41:39.089025: Current learning rate: 0.00597 +2024-11-22 05:41:58.222690: train_loss -0.7763 +2024-11-22 05:41:58.222921: val_loss -0.76 +2024-11-22 05:41:58.223000: Pseudo dice [0.8269] +2024-11-22 05:41:58.223084: Epoch time: 19.13 s +2024-11-22 05:41:59.146141: +2024-11-22 05:41:59.146346: Epoch 3487 +2024-11-22 05:41:59.146456: Current learning rate: 0.00597 +2024-11-22 05:42:18.700392: train_loss -0.779 +2024-11-22 05:42:18.700608: val_loss -0.7327 +2024-11-22 05:42:18.700685: Pseudo dice [0.8162] +2024-11-22 05:42:18.700760: Epoch time: 19.56 s +2024-11-22 05:42:19.583999: +2024-11-22 05:42:19.584214: Epoch 3488 +2024-11-22 05:42:19.584330: Current learning rate: 0.00597 +2024-11-22 05:42:38.581526: train_loss -0.7794 +2024-11-22 05:42:38.581738: val_loss -0.7353 +2024-11-22 05:42:38.581812: Pseudo dice [0.82] +2024-11-22 05:42:38.581888: Epoch time: 19.0 s +2024-11-22 05:42:39.472206: +2024-11-22 05:42:39.472437: Epoch 3489 +2024-11-22 05:42:39.472550: Current learning rate: 0.00597 +2024-11-22 05:42:58.713195: train_loss -0.7855 +2024-11-22 05:42:58.715585: val_loss -0.7653 +2024-11-22 05:42:58.715705: Pseudo dice [0.8313] +2024-11-22 05:42:58.715787: Epoch time: 19.24 s +2024-11-22 05:42:59.634691: +2024-11-22 05:42:59.634903: Epoch 3490 +2024-11-22 05:42:59.635022: Current learning rate: 0.00597 +2024-11-22 05:43:17.652455: train_loss -0.7805 +2024-11-22 05:43:17.652673: val_loss -0.7208 +2024-11-22 05:43:17.652754: Pseudo dice [0.8101] +2024-11-22 05:43:17.652832: Epoch time: 18.02 s +2024-11-22 05:43:18.536855: +2024-11-22 05:43:18.537237: Epoch 3491 +2024-11-22 05:43:18.537989: Current learning rate: 0.00597 +2024-11-22 05:43:37.473128: train_loss -0.782 +2024-11-22 05:43:37.473356: val_loss -0.752 +2024-11-22 05:43:37.473435: Pseudo dice [0.8476] +2024-11-22 05:43:37.473513: Epoch time: 18.94 s +2024-11-22 05:43:38.358229: +2024-11-22 05:43:38.358426: Epoch 3492 +2024-11-22 05:43:38.358537: Current learning rate: 0.00597 +2024-11-22 05:43:57.423143: train_loss -0.7673 +2024-11-22 05:43:57.423354: val_loss -0.7412 +2024-11-22 05:43:57.423427: Pseudo dice [0.8181] +2024-11-22 05:43:57.423505: Epoch time: 19.07 s +2024-11-22 05:43:58.306029: +2024-11-22 05:43:58.306232: Epoch 3493 +2024-11-22 05:43:58.306346: Current learning rate: 0.00597 +2024-11-22 05:44:17.459125: train_loss -0.7756 +2024-11-22 05:44:17.459334: val_loss -0.7155 +2024-11-22 05:44:17.459408: Pseudo dice [0.8244] +2024-11-22 05:44:17.459489: Epoch time: 19.15 s +2024-11-22 05:44:18.341767: +2024-11-22 05:44:18.341980: Epoch 3494 +2024-11-22 05:44:18.342095: Current learning rate: 0.00597 +2024-11-22 05:44:36.142834: train_loss -0.7623 +2024-11-22 05:44:36.143139: val_loss -0.7537 +2024-11-22 05:44:36.143213: Pseudo dice [0.821] +2024-11-22 05:44:36.143295: Epoch time: 17.8 s +2024-11-22 05:44:37.519469: +2024-11-22 05:44:37.519697: Epoch 3495 +2024-11-22 05:44:37.519816: Current learning rate: 0.00596 +2024-11-22 05:44:56.180408: train_loss -0.7708 +2024-11-22 05:44:56.180649: val_loss -0.7406 +2024-11-22 05:44:56.185872: Pseudo dice [0.8224] +2024-11-22 05:44:56.186042: Epoch time: 18.66 s +2024-11-22 05:44:57.236803: +2024-11-22 05:44:57.237028: Epoch 3496 +2024-11-22 05:44:57.237143: Current learning rate: 0.00596 +2024-11-22 05:45:15.704469: train_loss -0.7481 +2024-11-22 05:45:15.704707: val_loss -0.712 +2024-11-22 05:45:15.704786: Pseudo dice [0.8189] +2024-11-22 05:45:15.704867: Epoch time: 18.47 s +2024-11-22 05:45:16.587070: +2024-11-22 05:45:16.587285: Epoch 3497 +2024-11-22 05:45:16.587401: Current learning rate: 0.00596 +2024-11-22 05:45:35.906431: train_loss -0.7608 +2024-11-22 05:45:35.906667: val_loss -0.7214 +2024-11-22 05:45:35.906742: Pseudo dice [0.836] +2024-11-22 05:45:35.906823: Epoch time: 19.32 s +2024-11-22 05:45:36.907538: +2024-11-22 05:45:36.907795: Epoch 3498 +2024-11-22 05:45:36.907905: Current learning rate: 0.00596 +2024-11-22 05:45:56.134122: train_loss -0.7589 +2024-11-22 05:45:56.134364: val_loss -0.7135 +2024-11-22 05:45:56.134441: Pseudo dice [0.7984] +2024-11-22 05:45:56.134517: Epoch time: 19.23 s +2024-11-22 05:45:57.239562: +2024-11-22 05:45:57.239773: Epoch 3499 +2024-11-22 05:45:57.239903: Current learning rate: 0.00596 +2024-11-22 05:46:15.698631: train_loss -0.7713 +2024-11-22 05:46:15.698856: val_loss -0.7367 +2024-11-22 05:46:15.698935: Pseudo dice [0.8049] +2024-11-22 05:46:15.699043: Epoch time: 18.46 s +2024-11-22 05:46:16.831498: +2024-11-22 05:46:16.831718: Epoch 3500 +2024-11-22 05:46:16.831830: Current learning rate: 0.00596 +2024-11-22 05:46:33.751609: train_loss -0.7782 +2024-11-22 05:46:33.751828: val_loss -0.746 +2024-11-22 05:46:33.751905: Pseudo dice [0.8216] +2024-11-22 05:46:33.751981: Epoch time: 16.92 s +2024-11-22 05:46:34.629644: +2024-11-22 05:46:34.630008: Epoch 3501 +2024-11-22 05:46:34.630124: Current learning rate: 0.00596 +2024-11-22 05:46:53.312234: train_loss -0.7632 +2024-11-22 05:46:53.312492: val_loss -0.734 +2024-11-22 05:46:53.312573: Pseudo dice [0.8184] +2024-11-22 05:46:53.312656: Epoch time: 18.68 s +2024-11-22 05:46:54.199399: +2024-11-22 05:46:54.199619: Epoch 3502 +2024-11-22 05:46:54.199730: Current learning rate: 0.00596 +2024-11-22 05:47:12.474481: train_loss -0.7839 +2024-11-22 05:47:12.474700: val_loss -0.7397 +2024-11-22 05:47:12.474771: Pseudo dice [0.8027] +2024-11-22 05:47:12.474846: Epoch time: 18.28 s +2024-11-22 05:47:13.364015: +2024-11-22 05:47:13.364226: Epoch 3503 +2024-11-22 05:47:13.364336: Current learning rate: 0.00595 +2024-11-22 05:47:32.955772: train_loss -0.7706 +2024-11-22 05:47:32.956007: val_loss -0.7419 +2024-11-22 05:47:32.956085: Pseudo dice [0.8313] +2024-11-22 05:47:32.956161: Epoch time: 19.59 s +2024-11-22 05:47:33.840140: +2024-11-22 05:47:33.840340: Epoch 3504 +2024-11-22 05:47:33.840451: Current learning rate: 0.00595 +2024-11-22 05:47:52.048828: train_loss -0.7873 +2024-11-22 05:47:52.049095: val_loss -0.7448 +2024-11-22 05:47:52.049173: Pseudo dice [0.8188] +2024-11-22 05:47:52.049262: Epoch time: 18.21 s +2024-11-22 05:47:52.937526: +2024-11-22 05:47:52.937726: Epoch 3505 +2024-11-22 05:47:52.937839: Current learning rate: 0.00595 +2024-11-22 05:48:11.465184: train_loss -0.7872 +2024-11-22 05:48:11.465403: val_loss -0.7342 +2024-11-22 05:48:11.465476: Pseudo dice [0.8366] +2024-11-22 05:48:11.465551: Epoch time: 18.53 s +2024-11-22 05:48:12.368688: +2024-11-22 05:48:12.368895: Epoch 3506 +2024-11-22 05:48:12.369018: Current learning rate: 0.00595 +2024-11-22 05:48:31.272796: train_loss -0.7848 +2024-11-22 05:48:31.275384: val_loss -0.7305 +2024-11-22 05:48:31.275483: Pseudo dice [0.8145] +2024-11-22 05:48:31.275561: Epoch time: 18.9 s +2024-11-22 05:48:32.283061: +2024-11-22 05:48:32.283267: Epoch 3507 +2024-11-22 05:48:32.283381: Current learning rate: 0.00595 +2024-11-22 05:48:50.490241: train_loss -0.7781 +2024-11-22 05:48:50.490456: val_loss -0.7379 +2024-11-22 05:48:50.490534: Pseudo dice [0.8189] +2024-11-22 05:48:50.490611: Epoch time: 18.21 s +2024-11-22 05:48:51.368816: +2024-11-22 05:48:51.369053: Epoch 3508 +2024-11-22 05:48:51.369177: Current learning rate: 0.00595 +2024-11-22 05:49:09.767521: train_loss -0.7804 +2024-11-22 05:49:09.767825: val_loss -0.7655 +2024-11-22 05:49:09.767905: Pseudo dice [0.8196] +2024-11-22 05:49:09.767985: Epoch time: 18.4 s +2024-11-22 05:49:10.656377: +2024-11-22 05:49:10.656592: Epoch 3509 +2024-11-22 05:49:10.656706: Current learning rate: 0.00595 +2024-11-22 05:49:29.885738: train_loss -0.7879 +2024-11-22 05:49:29.885951: val_loss -0.7305 +2024-11-22 05:49:29.886178: Pseudo dice [0.8265] +2024-11-22 05:49:29.886265: Epoch time: 19.23 s +2024-11-22 05:49:30.769081: +2024-11-22 05:49:30.769337: Epoch 3510 +2024-11-22 05:49:30.769461: Current learning rate: 0.00595 +2024-11-22 05:49:49.316294: train_loss -0.7853 +2024-11-22 05:49:49.316514: val_loss -0.7411 +2024-11-22 05:49:49.316589: Pseudo dice [0.8323] +2024-11-22 05:49:49.316664: Epoch time: 18.55 s +2024-11-22 05:49:50.207285: +2024-11-22 05:49:50.207478: Epoch 3511 +2024-11-22 05:49:50.207595: Current learning rate: 0.00595 +2024-11-22 05:50:09.252934: train_loss -0.7779 +2024-11-22 05:50:09.253166: val_loss -0.7241 +2024-11-22 05:50:09.253243: Pseudo dice [0.8339] +2024-11-22 05:50:09.253324: Epoch time: 19.05 s +2024-11-22 05:50:10.144604: +2024-11-22 05:50:10.144795: Epoch 3512 +2024-11-22 05:50:10.144906: Current learning rate: 0.00594 +2024-11-22 05:50:28.905358: train_loss -0.7729 +2024-11-22 05:50:28.910773: val_loss -0.7378 +2024-11-22 05:50:28.910946: Pseudo dice [0.8234] +2024-11-22 05:50:28.911054: Epoch time: 18.76 s +2024-11-22 05:50:29.948463: +2024-11-22 05:50:29.948704: Epoch 3513 +2024-11-22 05:50:29.948826: Current learning rate: 0.00594 +2024-11-22 05:50:48.525852: train_loss -0.7737 +2024-11-22 05:50:48.526085: val_loss -0.7301 +2024-11-22 05:50:48.526165: Pseudo dice [0.8337] +2024-11-22 05:50:48.526241: Epoch time: 18.58 s +2024-11-22 05:50:49.409683: +2024-11-22 05:50:49.409873: Epoch 3514 +2024-11-22 05:50:49.409986: Current learning rate: 0.00594 +2024-11-22 05:51:08.005522: train_loss -0.7677 +2024-11-22 05:51:08.005745: val_loss -0.7335 +2024-11-22 05:51:08.005821: Pseudo dice [0.8321] +2024-11-22 05:51:08.005898: Epoch time: 18.6 s +2024-11-22 05:51:08.898800: +2024-11-22 05:51:08.899058: Epoch 3515 +2024-11-22 05:51:08.899197: Current learning rate: 0.00594 +2024-11-22 05:51:27.100374: train_loss -0.774 +2024-11-22 05:51:27.100623: val_loss -0.7384 +2024-11-22 05:51:27.100710: Pseudo dice [0.8303] +2024-11-22 05:51:27.100797: Epoch time: 18.2 s +2024-11-22 05:51:27.981728: +2024-11-22 05:51:27.981925: Epoch 3516 +2024-11-22 05:51:27.982046: Current learning rate: 0.00594 +2024-11-22 05:51:46.053614: train_loss -0.7728 +2024-11-22 05:51:46.053833: val_loss -0.7191 +2024-11-22 05:51:46.067084: Pseudo dice [0.8115] +2024-11-22 05:51:46.067247: Epoch time: 18.07 s +2024-11-22 05:51:47.346265: +2024-11-22 05:51:47.346573: Epoch 3517 +2024-11-22 05:51:47.346689: Current learning rate: 0.00594 +2024-11-22 05:52:05.532782: train_loss -0.7797 +2024-11-22 05:52:05.533030: val_loss -0.7538 +2024-11-22 05:52:05.533111: Pseudo dice [0.8194] +2024-11-22 05:52:05.533194: Epoch time: 18.19 s +2024-11-22 05:52:06.420551: +2024-11-22 05:52:06.420815: Epoch 3518 +2024-11-22 05:52:06.420928: Current learning rate: 0.00594 +2024-11-22 05:52:24.975837: train_loss -0.7787 +2024-11-22 05:52:24.976085: val_loss -0.7656 +2024-11-22 05:52:24.976163: Pseudo dice [0.8412] +2024-11-22 05:52:24.976251: Epoch time: 18.56 s +2024-11-22 05:52:25.863128: +2024-11-22 05:52:25.863353: Epoch 3519 +2024-11-22 05:52:25.863469: Current learning rate: 0.00594 +2024-11-22 05:52:44.009617: train_loss -0.7848 +2024-11-22 05:52:44.015019: val_loss -0.7599 +2024-11-22 05:52:44.015136: Pseudo dice [0.8363] +2024-11-22 05:52:44.015216: Epoch time: 18.15 s +2024-11-22 05:52:44.963951: +2024-11-22 05:52:44.964209: Epoch 3520 +2024-11-22 05:52:44.964319: Current learning rate: 0.00593 +2024-11-22 05:53:03.818884: train_loss -0.7883 +2024-11-22 05:53:03.819119: val_loss -0.7423 +2024-11-22 05:53:03.819197: Pseudo dice [0.8127] +2024-11-22 05:53:03.819279: Epoch time: 18.86 s +2024-11-22 05:53:04.728383: +2024-11-22 05:53:04.728614: Epoch 3521 +2024-11-22 05:53:04.728730: Current learning rate: 0.00593 +2024-11-22 05:53:22.533928: train_loss -0.7891 +2024-11-22 05:53:22.534148: val_loss -0.777 +2024-11-22 05:53:22.534225: Pseudo dice [0.8403] +2024-11-22 05:53:22.534299: Epoch time: 17.81 s +2024-11-22 05:53:23.445204: +2024-11-22 05:53:23.445514: Epoch 3522 +2024-11-22 05:53:23.445634: Current learning rate: 0.00593 +2024-11-22 05:53:41.943826: train_loss -0.7875 +2024-11-22 05:53:41.944094: val_loss -0.7536 +2024-11-22 05:53:41.944171: Pseudo dice [0.8278] +2024-11-22 05:53:41.944260: Epoch time: 18.5 s +2024-11-22 05:53:42.907759: +2024-11-22 05:53:42.907988: Epoch 3523 +2024-11-22 05:53:42.908110: Current learning rate: 0.00593 +2024-11-22 05:54:00.508415: train_loss -0.7929 +2024-11-22 05:54:00.508630: val_loss -0.7556 +2024-11-22 05:54:00.508702: Pseudo dice [0.8336] +2024-11-22 05:54:00.508778: Epoch time: 17.6 s +2024-11-22 05:54:01.396277: +2024-11-22 05:54:01.396481: Epoch 3524 +2024-11-22 05:54:01.396592: Current learning rate: 0.00593 +2024-11-22 05:54:19.682666: train_loss -0.7864 +2024-11-22 05:54:19.682884: val_loss -0.7552 +2024-11-22 05:54:19.682957: Pseudo dice [0.8288] +2024-11-22 05:54:19.683041: Epoch time: 18.29 s +2024-11-22 05:54:20.567296: +2024-11-22 05:54:20.567507: Epoch 3525 +2024-11-22 05:54:20.567620: Current learning rate: 0.00593 +2024-11-22 05:54:39.029753: train_loss -0.7895 +2024-11-22 05:54:39.030009: val_loss -0.7546 +2024-11-22 05:54:39.030085: Pseudo dice [0.8305] +2024-11-22 05:54:39.030168: Epoch time: 18.46 s +2024-11-22 05:54:39.921360: +2024-11-22 05:54:39.921590: Epoch 3526 +2024-11-22 05:54:39.921699: Current learning rate: 0.00593 +2024-11-22 05:54:57.556448: train_loss -0.7798 +2024-11-22 05:54:57.556672: val_loss -0.7395 +2024-11-22 05:54:57.556745: Pseudo dice [0.8371] +2024-11-22 05:54:57.556822: Epoch time: 17.64 s +2024-11-22 05:54:58.439585: +2024-11-22 05:54:58.439780: Epoch 3527 +2024-11-22 05:54:58.439893: Current learning rate: 0.00593 +2024-11-22 05:55:16.234310: train_loss -0.7833 +2024-11-22 05:55:16.234525: val_loss -0.7652 +2024-11-22 05:55:16.234602: Pseudo dice [0.8228] +2024-11-22 05:55:16.234681: Epoch time: 17.8 s +2024-11-22 05:55:17.118220: +2024-11-22 05:55:17.118422: Epoch 3528 +2024-11-22 05:55:17.118534: Current learning rate: 0.00592 +2024-11-22 05:55:36.956204: train_loss -0.784 +2024-11-22 05:55:36.956433: val_loss -0.7182 +2024-11-22 05:55:36.956512: Pseudo dice [0.8248] +2024-11-22 05:55:36.958768: Epoch time: 19.84 s +2024-11-22 05:55:38.348648: +2024-11-22 05:55:38.348899: Epoch 3529 +2024-11-22 05:55:38.349055: Current learning rate: 0.00592 +2024-11-22 05:55:57.674277: train_loss -0.7889 +2024-11-22 05:55:57.674501: val_loss -0.7319 +2024-11-22 05:55:57.674575: Pseudo dice [0.8068] +2024-11-22 05:55:57.674654: Epoch time: 19.33 s +2024-11-22 05:55:58.562061: +2024-11-22 05:55:58.562286: Epoch 3530 +2024-11-22 05:55:58.562398: Current learning rate: 0.00592 +2024-11-22 05:56:17.782770: train_loss -0.7895 +2024-11-22 05:56:17.783003: val_loss -0.7229 +2024-11-22 05:56:17.783088: Pseudo dice [0.8111] +2024-11-22 05:56:17.783207: Epoch time: 19.22 s +2024-11-22 05:56:18.773686: +2024-11-22 05:56:18.773955: Epoch 3531 +2024-11-22 05:56:18.774085: Current learning rate: 0.00592 +2024-11-22 05:56:36.834496: train_loss -0.7886 +2024-11-22 05:56:36.837539: val_loss -0.7529 +2024-11-22 05:56:36.837656: Pseudo dice [0.8313] +2024-11-22 05:56:36.837754: Epoch time: 18.06 s +2024-11-22 05:56:37.902148: +2024-11-22 05:56:37.902365: Epoch 3532 +2024-11-22 05:56:37.902475: Current learning rate: 0.00592 +2024-11-22 05:56:56.243755: train_loss -0.79 +2024-11-22 05:56:56.244002: val_loss -0.7316 +2024-11-22 05:56:56.244079: Pseudo dice [0.8297] +2024-11-22 05:56:56.244153: Epoch time: 18.34 s +2024-11-22 05:56:57.131728: +2024-11-22 05:56:57.131949: Epoch 3533 +2024-11-22 05:56:57.132067: Current learning rate: 0.00592 +2024-11-22 05:57:16.331029: train_loss -0.7967 +2024-11-22 05:57:16.331241: val_loss -0.7369 +2024-11-22 05:57:16.331316: Pseudo dice [0.8399] +2024-11-22 05:57:16.331392: Epoch time: 19.2 s +2024-11-22 05:57:17.221188: +2024-11-22 05:57:17.221430: Epoch 3534 +2024-11-22 05:57:17.221542: Current learning rate: 0.00592 +2024-11-22 05:57:36.471595: train_loss -0.7886 +2024-11-22 05:57:36.471838: val_loss -0.7485 +2024-11-22 05:57:36.471920: Pseudo dice [0.8144] +2024-11-22 05:57:36.483193: Epoch time: 19.25 s +2024-11-22 05:57:37.372634: +2024-11-22 05:57:37.372861: Epoch 3535 +2024-11-22 05:57:37.372976: Current learning rate: 0.00592 +2024-11-22 05:57:55.940692: train_loss -0.7876 +2024-11-22 05:57:55.940935: val_loss -0.7162 +2024-11-22 05:57:55.941171: Pseudo dice [0.8232] +2024-11-22 05:57:55.941271: Epoch time: 18.57 s +2024-11-22 05:57:56.822218: +2024-11-22 05:57:56.822422: Epoch 3536 +2024-11-22 05:57:56.822533: Current learning rate: 0.00592 +2024-11-22 05:58:15.482441: train_loss -0.7848 +2024-11-22 05:58:15.482656: val_loss -0.7342 +2024-11-22 05:58:15.482727: Pseudo dice [0.8448] +2024-11-22 05:58:15.482809: Epoch time: 18.66 s +2024-11-22 05:58:16.550370: +2024-11-22 05:58:16.550556: Epoch 3537 +2024-11-22 05:58:16.550667: Current learning rate: 0.00591 +2024-11-22 05:58:35.402566: train_loss -0.7926 +2024-11-22 05:58:35.402786: val_loss -0.7515 +2024-11-22 05:58:35.402859: Pseudo dice [0.827] +2024-11-22 05:58:35.402936: Epoch time: 18.85 s +2024-11-22 05:58:36.299823: +2024-11-22 05:58:36.300142: Epoch 3538 +2024-11-22 05:58:36.300285: Current learning rate: 0.00591 +2024-11-22 05:58:55.545044: train_loss -0.7891 +2024-11-22 05:58:55.545280: val_loss -0.745 +2024-11-22 05:58:55.545359: Pseudo dice [0.8111] +2024-11-22 05:58:55.545444: Epoch time: 19.25 s +2024-11-22 05:58:56.438838: +2024-11-22 05:58:56.439027: Epoch 3539 +2024-11-22 05:58:56.439136: Current learning rate: 0.00591 +2024-11-22 05:59:14.623469: train_loss -0.7856 +2024-11-22 05:59:14.623751: val_loss -0.724 +2024-11-22 05:59:14.623832: Pseudo dice [0.8193] +2024-11-22 05:59:14.623915: Epoch time: 18.19 s +2024-11-22 05:59:16.020348: +2024-11-22 05:59:16.020594: Epoch 3540 +2024-11-22 05:59:16.020710: Current learning rate: 0.00591 +2024-11-22 05:59:35.234935: train_loss -0.7849 +2024-11-22 05:59:35.235176: val_loss -0.7313 +2024-11-22 05:59:35.235259: Pseudo dice [0.8305] +2024-11-22 05:59:35.235340: Epoch time: 19.22 s +2024-11-22 05:59:36.120740: +2024-11-22 05:59:36.120996: Epoch 3541 +2024-11-22 05:59:36.121112: Current learning rate: 0.00591 +2024-11-22 05:59:55.833544: train_loss -0.77 +2024-11-22 05:59:55.833771: val_loss -0.744 +2024-11-22 05:59:55.839047: Pseudo dice [0.8169] +2024-11-22 05:59:55.839171: Epoch time: 19.71 s +2024-11-22 05:59:56.775764: +2024-11-22 05:59:56.775974: Epoch 3542 +2024-11-22 05:59:56.776094: Current learning rate: 0.00591 +2024-11-22 06:00:15.360651: train_loss -0.76 +2024-11-22 06:00:15.360892: val_loss -0.7355 +2024-11-22 06:00:15.360970: Pseudo dice [0.8169] +2024-11-22 06:00:15.361131: Epoch time: 18.59 s +2024-11-22 06:00:16.244677: +2024-11-22 06:00:16.244923: Epoch 3543 +2024-11-22 06:00:16.245045: Current learning rate: 0.00591 +2024-11-22 06:00:35.438508: train_loss -0.7606 +2024-11-22 06:00:35.438747: val_loss -0.7129 +2024-11-22 06:00:35.438831: Pseudo dice [0.8138] +2024-11-22 06:00:35.438908: Epoch time: 19.19 s +2024-11-22 06:00:36.328164: +2024-11-22 06:00:36.328362: Epoch 3544 +2024-11-22 06:00:36.328477: Current learning rate: 0.00591 +2024-11-22 06:00:55.171527: train_loss -0.7687 +2024-11-22 06:00:55.171748: val_loss -0.746 +2024-11-22 06:00:55.171828: Pseudo dice [0.8019] +2024-11-22 06:00:55.171907: Epoch time: 18.84 s +2024-11-22 06:00:56.054051: +2024-11-22 06:00:56.054241: Epoch 3545 +2024-11-22 06:00:56.054433: Current learning rate: 0.0059 +2024-11-22 06:01:15.226059: train_loss -0.7823 +2024-11-22 06:01:15.226277: val_loss -0.7231 +2024-11-22 06:01:15.226357: Pseudo dice [0.8165] +2024-11-22 06:01:15.226449: Epoch time: 19.17 s +2024-11-22 06:01:16.118221: +2024-11-22 06:01:16.118442: Epoch 3546 +2024-11-22 06:01:16.118560: Current learning rate: 0.0059 +2024-11-22 06:01:35.037129: train_loss -0.7859 +2024-11-22 06:01:35.037344: val_loss -0.7659 +2024-11-22 06:01:35.037416: Pseudo dice [0.8343] +2024-11-22 06:01:35.037494: Epoch time: 18.92 s +2024-11-22 06:01:35.949273: +2024-11-22 06:01:35.949494: Epoch 3547 +2024-11-22 06:01:35.949600: Current learning rate: 0.0059 +2024-11-22 06:01:55.028666: train_loss -0.7943 +2024-11-22 06:01:55.028894: val_loss -0.7267 +2024-11-22 06:01:55.028966: Pseudo dice [0.8323] +2024-11-22 06:01:55.029054: Epoch time: 19.08 s +2024-11-22 06:01:55.945917: +2024-11-22 06:01:55.946179: Epoch 3548 +2024-11-22 06:01:55.946290: Current learning rate: 0.0059 +2024-11-22 06:02:13.964801: train_loss -0.7904 +2024-11-22 06:02:13.965067: val_loss -0.7396 +2024-11-22 06:02:13.967339: Pseudo dice [0.8529] +2024-11-22 06:02:13.967425: Epoch time: 18.02 s +2024-11-22 06:02:14.855297: +2024-11-22 06:02:14.855514: Epoch 3549 +2024-11-22 06:02:14.855633: Current learning rate: 0.0059 +2024-11-22 06:02:35.253648: train_loss -0.7945 +2024-11-22 06:02:35.258088: val_loss -0.7508 +2024-11-22 06:02:35.258209: Pseudo dice [0.8201] +2024-11-22 06:02:35.258287: Epoch time: 20.4 s +2024-11-22 06:02:36.397557: +2024-11-22 06:02:36.397749: Epoch 3550 +2024-11-22 06:02:36.397861: Current learning rate: 0.0059 +2024-11-22 06:02:55.391578: train_loss -0.7921 +2024-11-22 06:02:55.391830: val_loss -0.7355 +2024-11-22 06:02:55.391969: Pseudo dice [0.8406] +2024-11-22 06:02:55.392063: Epoch time: 18.99 s +2024-11-22 06:02:56.275873: +2024-11-22 06:02:56.276090: Epoch 3551 +2024-11-22 06:02:56.276203: Current learning rate: 0.0059 +2024-11-22 06:03:15.019498: train_loss -0.7935 +2024-11-22 06:03:15.019712: val_loss -0.7296 +2024-11-22 06:03:15.019787: Pseudo dice [0.8243] +2024-11-22 06:03:15.019861: Epoch time: 18.74 s +2024-11-22 06:03:16.318502: +2024-11-22 06:03:16.318712: Epoch 3552 +2024-11-22 06:03:16.318825: Current learning rate: 0.0059 +2024-11-22 06:03:35.856148: train_loss -0.798 +2024-11-22 06:03:35.856369: val_loss -0.7419 +2024-11-22 06:03:35.856450: Pseudo dice [0.8299] +2024-11-22 06:03:35.856529: Epoch time: 19.54 s +2024-11-22 06:03:36.776619: +2024-11-22 06:03:36.776893: Epoch 3553 +2024-11-22 06:03:36.777010: Current learning rate: 0.00589 +2024-11-22 06:03:55.700890: train_loss -0.7796 +2024-11-22 06:03:55.701137: val_loss -0.7469 +2024-11-22 06:03:55.712743: Pseudo dice [0.8294] +2024-11-22 06:03:55.712900: Epoch time: 18.93 s +2024-11-22 06:03:56.698169: +2024-11-22 06:03:56.698443: Epoch 3554 +2024-11-22 06:03:56.698555: Current learning rate: 0.00589 +2024-11-22 06:04:15.941477: train_loss -0.7792 +2024-11-22 06:04:15.941698: val_loss -0.7439 +2024-11-22 06:04:15.961776: Pseudo dice [0.8265] +2024-11-22 06:04:15.961937: Epoch time: 19.24 s +2024-11-22 06:04:16.846686: +2024-11-22 06:04:16.846902: Epoch 3555 +2024-11-22 06:04:16.847019: Current learning rate: 0.00589 +2024-11-22 06:04:35.460755: train_loss -0.7846 +2024-11-22 06:04:35.461019: val_loss -0.7428 +2024-11-22 06:04:35.461095: Pseudo dice [0.8281] +2024-11-22 06:04:35.461169: Epoch time: 18.61 s +2024-11-22 06:04:36.359591: +2024-11-22 06:04:36.359775: Epoch 3556 +2024-11-22 06:04:36.359885: Current learning rate: 0.00589 +2024-11-22 06:04:54.994079: train_loss -0.7806 +2024-11-22 06:04:54.994288: val_loss -0.745 +2024-11-22 06:04:54.994362: Pseudo dice [0.8166] +2024-11-22 06:04:54.994442: Epoch time: 18.64 s +2024-11-22 06:04:55.883558: +2024-11-22 06:04:55.883770: Epoch 3557 +2024-11-22 06:04:55.883880: Current learning rate: 0.00589 +2024-11-22 06:05:13.326639: train_loss -0.7893 +2024-11-22 06:05:13.326870: val_loss -0.7232 +2024-11-22 06:05:13.326948: Pseudo dice [0.8205] +2024-11-22 06:05:13.327035: Epoch time: 17.44 s +2024-11-22 06:05:14.214468: +2024-11-22 06:05:14.214705: Epoch 3558 +2024-11-22 06:05:14.214852: Current learning rate: 0.00589 +2024-11-22 06:05:33.610108: train_loss -0.7801 +2024-11-22 06:05:33.610327: val_loss -0.7303 +2024-11-22 06:05:33.610404: Pseudo dice [0.8125] +2024-11-22 06:05:33.610484: Epoch time: 19.4 s +2024-11-22 06:05:34.504188: +2024-11-22 06:05:34.504380: Epoch 3559 +2024-11-22 06:05:34.504491: Current learning rate: 0.00589 +2024-11-22 06:05:54.194495: train_loss -0.7795 +2024-11-22 06:05:54.194712: val_loss -0.7497 +2024-11-22 06:05:54.194786: Pseudo dice [0.8093] +2024-11-22 06:05:54.194860: Epoch time: 19.69 s +2024-11-22 06:05:55.076066: +2024-11-22 06:05:55.076290: Epoch 3560 +2024-11-22 06:05:55.076415: Current learning rate: 0.00589 +2024-11-22 06:06:13.923034: train_loss -0.7756 +2024-11-22 06:06:13.923251: val_loss -0.7367 +2024-11-22 06:06:13.923326: Pseudo dice [0.8284] +2024-11-22 06:06:13.923413: Epoch time: 18.85 s +2024-11-22 06:06:14.910336: +2024-11-22 06:06:14.910548: Epoch 3561 +2024-11-22 06:06:14.910662: Current learning rate: 0.00589 +2024-11-22 06:06:33.795759: train_loss -0.7821 +2024-11-22 06:06:33.796167: val_loss -0.7427 +2024-11-22 06:06:33.796255: Pseudo dice [0.8298] +2024-11-22 06:06:33.796347: Epoch time: 18.89 s +2024-11-22 06:06:34.673795: +2024-11-22 06:06:34.673984: Epoch 3562 +2024-11-22 06:06:34.674097: Current learning rate: 0.00588 +2024-11-22 06:06:53.784541: train_loss -0.7831 +2024-11-22 06:06:53.784757: val_loss -0.725 +2024-11-22 06:06:53.784830: Pseudo dice [0.8212] +2024-11-22 06:06:53.784902: Epoch time: 19.11 s +2024-11-22 06:06:54.671291: +2024-11-22 06:06:54.671498: Epoch 3563 +2024-11-22 06:06:54.671607: Current learning rate: 0.00588 +2024-11-22 06:07:13.356745: train_loss -0.7913 +2024-11-22 06:07:13.357247: val_loss -0.73 +2024-11-22 06:07:13.357350: Pseudo dice [0.8227] +2024-11-22 06:07:13.357433: Epoch time: 18.69 s +2024-11-22 06:07:14.242711: +2024-11-22 06:07:14.242936: Epoch 3564 +2024-11-22 06:07:14.243050: Current learning rate: 0.00588 +2024-11-22 06:07:33.259700: train_loss -0.7891 +2024-11-22 06:07:33.260018: val_loss -0.7555 +2024-11-22 06:07:33.260112: Pseudo dice [0.8335] +2024-11-22 06:07:33.260194: Epoch time: 19.02 s +2024-11-22 06:07:34.148969: +2024-11-22 06:07:34.149209: Epoch 3565 +2024-11-22 06:07:34.149316: Current learning rate: 0.00588 +2024-11-22 06:07:53.800605: train_loss -0.782 +2024-11-22 06:07:53.800827: val_loss -0.7465 +2024-11-22 06:07:53.800905: Pseudo dice [0.8198] +2024-11-22 06:07:53.800984: Epoch time: 19.65 s +2024-11-22 06:07:54.678711: +2024-11-22 06:07:54.678918: Epoch 3566 +2024-11-22 06:07:54.679039: Current learning rate: 0.00588 +2024-11-22 06:08:13.314671: train_loss -0.7946 +2024-11-22 06:08:13.314885: val_loss -0.7483 +2024-11-22 06:08:13.314963: Pseudo dice [0.8494] +2024-11-22 06:08:13.315050: Epoch time: 18.64 s +2024-11-22 06:08:14.187284: +2024-11-22 06:08:14.187467: Epoch 3567 +2024-11-22 06:08:14.187578: Current learning rate: 0.00588 +2024-11-22 06:08:32.129015: train_loss -0.7951 +2024-11-22 06:08:32.129261: val_loss -0.7561 +2024-11-22 06:08:32.129342: Pseudo dice [0.838] +2024-11-22 06:08:32.129424: Epoch time: 17.94 s +2024-11-22 06:08:33.023670: +2024-11-22 06:08:33.023880: Epoch 3568 +2024-11-22 06:08:33.023999: Current learning rate: 0.00588 +2024-11-22 06:08:51.687670: train_loss -0.7832 +2024-11-22 06:08:51.687958: val_loss -0.7524 +2024-11-22 06:08:51.688040: Pseudo dice [0.8225] +2024-11-22 06:08:51.688117: Epoch time: 18.66 s +2024-11-22 06:08:52.558756: +2024-11-22 06:08:52.559015: Epoch 3569 +2024-11-22 06:08:52.559128: Current learning rate: 0.00588 +2024-11-22 06:09:09.841688: train_loss -0.7841 +2024-11-22 06:09:09.842005: val_loss -0.7579 +2024-11-22 06:09:09.842083: Pseudo dice [0.8389] +2024-11-22 06:09:09.842158: Epoch time: 17.28 s +2024-11-22 06:09:10.724072: +2024-11-22 06:09:10.724370: Epoch 3570 +2024-11-22 06:09:10.724481: Current learning rate: 0.00587 +2024-11-22 06:09:29.885072: train_loss -0.7952 +2024-11-22 06:09:29.885294: val_loss -0.7223 +2024-11-22 06:09:29.885373: Pseudo dice [0.8327] +2024-11-22 06:09:29.885450: Epoch time: 19.16 s +2024-11-22 06:09:30.764026: +2024-11-22 06:09:30.764256: Epoch 3571 +2024-11-22 06:09:30.764380: Current learning rate: 0.00587 +2024-11-22 06:09:49.934064: train_loss -0.7894 +2024-11-22 06:09:49.934341: val_loss -0.7507 +2024-11-22 06:09:49.934416: Pseudo dice [0.8214] +2024-11-22 06:09:49.934503: Epoch time: 19.17 s +2024-11-22 06:09:51.022488: +2024-11-22 06:09:51.022721: Epoch 3572 +2024-11-22 06:09:51.022832: Current learning rate: 0.00587 +2024-11-22 06:10:09.040781: train_loss -0.7845 +2024-11-22 06:10:09.041070: val_loss -0.751 +2024-11-22 06:10:09.041146: Pseudo dice [0.8233] +2024-11-22 06:10:09.041225: Epoch time: 18.02 s +2024-11-22 06:10:09.932340: +2024-11-22 06:10:09.932613: Epoch 3573 +2024-11-22 06:10:09.932727: Current learning rate: 0.00587 +2024-11-22 06:10:29.200455: train_loss -0.7904 +2024-11-22 06:10:29.200688: val_loss -0.7622 +2024-11-22 06:10:29.200763: Pseudo dice [0.8348] +2024-11-22 06:10:29.200840: Epoch time: 19.27 s +2024-11-22 06:10:30.099499: +2024-11-22 06:10:30.099732: Epoch 3574 +2024-11-22 06:10:30.099844: Current learning rate: 0.00587 +2024-11-22 06:10:48.205439: train_loss -0.7922 +2024-11-22 06:10:48.205660: val_loss -0.7369 +2024-11-22 06:10:48.205737: Pseudo dice [0.8264] +2024-11-22 06:10:48.205832: Epoch time: 18.11 s +2024-11-22 06:10:49.474900: +2024-11-22 06:10:49.475157: Epoch 3575 +2024-11-22 06:10:49.475311: Current learning rate: 0.00587 +2024-11-22 06:11:07.535574: train_loss -0.7914 +2024-11-22 06:11:07.535795: val_loss -0.7519 +2024-11-22 06:11:07.535870: Pseudo dice [0.8109] +2024-11-22 06:11:07.535951: Epoch time: 18.06 s +2024-11-22 06:11:08.483379: +2024-11-22 06:11:08.483594: Epoch 3576 +2024-11-22 06:11:08.483704: Current learning rate: 0.00587 +2024-11-22 06:11:26.957769: train_loss -0.7859 +2024-11-22 06:11:26.957983: val_loss -0.7557 +2024-11-22 06:11:26.958063: Pseudo dice [0.8335] +2024-11-22 06:11:26.958141: Epoch time: 18.48 s +2024-11-22 06:11:27.929203: +2024-11-22 06:11:27.929418: Epoch 3577 +2024-11-22 06:11:27.929528: Current learning rate: 0.00587 +2024-11-22 06:11:47.031857: train_loss -0.7808 +2024-11-22 06:11:47.032130: val_loss -0.7498 +2024-11-22 06:11:47.032206: Pseudo dice [0.8389] +2024-11-22 06:11:47.032279: Epoch time: 19.1 s +2024-11-22 06:11:47.924184: +2024-11-22 06:11:47.924424: Epoch 3578 +2024-11-22 06:11:47.924535: Current learning rate: 0.00587 +2024-11-22 06:12:06.040253: train_loss -0.786 +2024-11-22 06:12:06.040551: val_loss -0.7724 +2024-11-22 06:12:06.040627: Pseudo dice [0.8253] +2024-11-22 06:12:06.040709: Epoch time: 18.12 s +2024-11-22 06:12:06.989203: +2024-11-22 06:12:06.989468: Epoch 3579 +2024-11-22 06:12:06.989588: Current learning rate: 0.00586 +2024-11-22 06:12:25.019368: train_loss -0.7927 +2024-11-22 06:12:25.019585: val_loss -0.704 +2024-11-22 06:12:25.019660: Pseudo dice [0.8212] +2024-11-22 06:12:25.019737: Epoch time: 18.03 s +2024-11-22 06:12:25.895478: +2024-11-22 06:12:25.895892: Epoch 3580 +2024-11-22 06:12:25.896016: Current learning rate: 0.00586 +2024-11-22 06:12:44.844086: train_loss -0.7913 +2024-11-22 06:12:44.844295: val_loss -0.7815 +2024-11-22 06:12:44.844367: Pseudo dice [0.8476] +2024-11-22 06:12:44.844443: Epoch time: 18.95 s +2024-11-22 06:12:45.743330: +2024-11-22 06:12:45.743543: Epoch 3581 +2024-11-22 06:12:45.743649: Current learning rate: 0.00586 +2024-11-22 06:13:04.228961: train_loss -0.7892 +2024-11-22 06:13:04.234314: val_loss -0.7356 +2024-11-22 06:13:04.234403: Pseudo dice [0.8138] +2024-11-22 06:13:04.234490: Epoch time: 18.49 s +2024-11-22 06:13:05.123532: +2024-11-22 06:13:05.124000: Epoch 3582 +2024-11-22 06:13:05.124110: Current learning rate: 0.00586 +2024-11-22 06:13:23.834117: train_loss -0.793 +2024-11-22 06:13:23.834437: val_loss -0.7668 +2024-11-22 06:13:23.834514: Pseudo dice [0.8336] +2024-11-22 06:13:23.834593: Epoch time: 18.71 s +2024-11-22 06:13:24.718341: +2024-11-22 06:13:24.718559: Epoch 3583 +2024-11-22 06:13:24.718670: Current learning rate: 0.00586 +2024-11-22 06:13:42.606169: train_loss -0.7917 +2024-11-22 06:13:42.606382: val_loss -0.7518 +2024-11-22 06:13:42.606469: Pseudo dice [0.8395] +2024-11-22 06:13:42.606554: Epoch time: 17.89 s +2024-11-22 06:13:43.490372: +2024-11-22 06:13:43.490584: Epoch 3584 +2024-11-22 06:13:43.490700: Current learning rate: 0.00586 +2024-11-22 06:14:02.011411: train_loss -0.7886 +2024-11-22 06:14:02.014134: val_loss -0.7601 +2024-11-22 06:14:02.014250: Pseudo dice [0.8173] +2024-11-22 06:14:02.014330: Epoch time: 18.52 s +2024-11-22 06:14:02.909063: +2024-11-22 06:14:02.909323: Epoch 3585 +2024-11-22 06:14:02.909436: Current learning rate: 0.00586 +2024-11-22 06:14:21.185595: train_loss -0.7883 +2024-11-22 06:14:21.185840: val_loss -0.7446 +2024-11-22 06:14:21.185920: Pseudo dice [0.8144] +2024-11-22 06:14:21.186070: Epoch time: 18.28 s +2024-11-22 06:14:22.069202: +2024-11-22 06:14:22.069406: Epoch 3586 +2024-11-22 06:14:22.069520: Current learning rate: 0.00586 +2024-11-22 06:14:40.984967: train_loss -0.7908 +2024-11-22 06:14:40.990654: val_loss -0.7342 +2024-11-22 06:14:40.990764: Pseudo dice [0.8292] +2024-11-22 06:14:40.990845: Epoch time: 18.92 s +2024-11-22 06:14:42.034562: +2024-11-22 06:14:42.034762: Epoch 3587 +2024-11-22 06:14:42.034877: Current learning rate: 0.00585 +2024-11-22 06:15:01.601168: train_loss -0.7743 +2024-11-22 06:15:01.601481: val_loss -0.7595 +2024-11-22 06:15:01.601567: Pseudo dice [0.8444] +2024-11-22 06:15:01.601643: Epoch time: 19.57 s +2024-11-22 06:15:02.482006: +2024-11-22 06:15:02.482223: Epoch 3588 +2024-11-22 06:15:02.482331: Current learning rate: 0.00585 +2024-11-22 06:15:21.028715: train_loss -0.7942 +2024-11-22 06:15:21.028961: val_loss -0.7543 +2024-11-22 06:15:21.029052: Pseudo dice [0.8306] +2024-11-22 06:15:21.029136: Epoch time: 18.55 s +2024-11-22 06:15:21.944670: +2024-11-22 06:15:21.944878: Epoch 3589 +2024-11-22 06:15:21.944989: Current learning rate: 0.00585 +2024-11-22 06:15:39.396143: train_loss -0.7883 +2024-11-22 06:15:39.396363: val_loss -0.7372 +2024-11-22 06:15:39.396446: Pseudo dice [0.8226] +2024-11-22 06:15:39.396523: Epoch time: 17.45 s +2024-11-22 06:15:40.274985: +2024-11-22 06:15:40.275196: Epoch 3590 +2024-11-22 06:15:40.275306: Current learning rate: 0.00585 +2024-11-22 06:15:59.970686: train_loss -0.7881 +2024-11-22 06:15:59.973553: val_loss -0.7459 +2024-11-22 06:15:59.973641: Pseudo dice [0.8315] +2024-11-22 06:15:59.973720: Epoch time: 19.7 s +2024-11-22 06:16:01.044726: +2024-11-22 06:16:01.044919: Epoch 3591 +2024-11-22 06:16:01.045051: Current learning rate: 0.00585 +2024-11-22 06:16:19.778669: train_loss -0.7841 +2024-11-22 06:16:19.780733: val_loss -0.7315 +2024-11-22 06:16:19.780869: Pseudo dice [0.8153] +2024-11-22 06:16:19.780951: Epoch time: 18.73 s +2024-11-22 06:16:20.674238: +2024-11-22 06:16:20.674476: Epoch 3592 +2024-11-22 06:16:20.674591: Current learning rate: 0.00585 +2024-11-22 06:16:40.142714: train_loss -0.7874 +2024-11-22 06:16:40.142945: val_loss -0.7516 +2024-11-22 06:16:40.143028: Pseudo dice [0.8395] +2024-11-22 06:16:40.143429: Epoch time: 19.47 s +2024-11-22 06:16:41.021250: +2024-11-22 06:16:41.021467: Epoch 3593 +2024-11-22 06:16:41.021580: Current learning rate: 0.00585 +2024-11-22 06:16:59.680615: train_loss -0.78 +2024-11-22 06:16:59.681558: val_loss -0.7335 +2024-11-22 06:16:59.681643: Pseudo dice [0.8058] +2024-11-22 06:16:59.681725: Epoch time: 18.66 s +2024-11-22 06:17:00.558222: +2024-11-22 06:17:00.558447: Epoch 3594 +2024-11-22 06:17:00.558563: Current learning rate: 0.00585 +2024-11-22 06:17:19.922441: train_loss -0.7742 +2024-11-22 06:17:19.922657: val_loss -0.7404 +2024-11-22 06:17:19.922732: Pseudo dice [0.8129] +2024-11-22 06:17:19.922806: Epoch time: 19.36 s +2024-11-22 06:17:20.800858: +2024-11-22 06:17:20.801160: Epoch 3595 +2024-11-22 06:17:20.801275: Current learning rate: 0.00584 +2024-11-22 06:17:39.506700: train_loss -0.7735 +2024-11-22 06:17:39.506946: val_loss -0.7336 +2024-11-22 06:17:39.507029: Pseudo dice [0.8187] +2024-11-22 06:17:39.507105: Epoch time: 18.71 s +2024-11-22 06:17:40.385038: +2024-11-22 06:17:40.385237: Epoch 3596 +2024-11-22 06:17:40.385345: Current learning rate: 0.00584 +2024-11-22 06:17:58.418493: train_loss -0.7697 +2024-11-22 06:17:58.418838: val_loss -0.7508 +2024-11-22 06:17:58.418923: Pseudo dice [0.8324] +2024-11-22 06:17:58.419026: Epoch time: 18.03 s +2024-11-22 06:17:59.307393: +2024-11-22 06:17:59.307579: Epoch 3597 +2024-11-22 06:17:59.307690: Current learning rate: 0.00584 +2024-11-22 06:18:18.093982: train_loss -0.7794 +2024-11-22 06:18:18.094196: val_loss -0.7592 +2024-11-22 06:18:18.094269: Pseudo dice [0.8259] +2024-11-22 06:18:18.097783: Epoch time: 18.79 s +2024-11-22 06:18:19.370244: +2024-11-22 06:18:19.370449: Epoch 3598 +2024-11-22 06:18:19.370562: Current learning rate: 0.00584 +2024-11-22 06:18:38.058323: train_loss -0.7666 +2024-11-22 06:18:38.058569: val_loss -0.7444 +2024-11-22 06:18:38.058648: Pseudo dice [0.8247] +2024-11-22 06:18:38.058726: Epoch time: 18.69 s +2024-11-22 06:18:38.964636: +2024-11-22 06:18:38.964851: Epoch 3599 +2024-11-22 06:18:38.964963: Current learning rate: 0.00584 +2024-11-22 06:18:56.963268: train_loss -0.7855 +2024-11-22 06:18:56.963511: val_loss -0.7272 +2024-11-22 06:18:56.963591: Pseudo dice [0.8061] +2024-11-22 06:18:56.963676: Epoch time: 18.0 s +2024-11-22 06:18:58.124173: +2024-11-22 06:18:58.124378: Epoch 3600 +2024-11-22 06:18:58.124493: Current learning rate: 0.00584 +2024-11-22 06:19:17.580943: train_loss -0.7805 +2024-11-22 06:19:17.581258: val_loss -0.7709 +2024-11-22 06:19:17.581340: Pseudo dice [0.8131] +2024-11-22 06:19:17.581419: Epoch time: 19.46 s +2024-11-22 06:19:18.559631: +2024-11-22 06:19:18.559842: Epoch 3601 +2024-11-22 06:19:18.559955: Current learning rate: 0.00584 +2024-11-22 06:19:37.887528: train_loss -0.7678 +2024-11-22 06:19:37.887750: val_loss -0.7422 +2024-11-22 06:19:37.887829: Pseudo dice [0.8192] +2024-11-22 06:19:37.887904: Epoch time: 19.33 s +2024-11-22 06:19:38.780248: +2024-11-22 06:19:38.780447: Epoch 3602 +2024-11-22 06:19:38.780560: Current learning rate: 0.00584 +2024-11-22 06:19:56.837799: train_loss -0.7559 +2024-11-22 06:19:56.843058: val_loss -0.7352 +2024-11-22 06:19:56.843195: Pseudo dice [0.8165] +2024-11-22 06:19:56.843276: Epoch time: 18.06 s +2024-11-22 06:19:57.786695: +2024-11-22 06:19:57.786892: Epoch 3603 +2024-11-22 06:19:57.787011: Current learning rate: 0.00584 +2024-11-22 06:20:16.248725: train_loss -0.7726 +2024-11-22 06:20:16.248963: val_loss -0.7237 +2024-11-22 06:20:16.249042: Pseudo dice [0.8233] +2024-11-22 06:20:16.249129: Epoch time: 18.46 s +2024-11-22 06:20:17.138537: +2024-11-22 06:20:17.138719: Epoch 3604 +2024-11-22 06:20:17.138829: Current learning rate: 0.00583 +2024-11-22 06:20:35.787605: train_loss -0.7782 +2024-11-22 06:20:35.787825: val_loss -0.7536 +2024-11-22 06:20:35.787902: Pseudo dice [0.8146] +2024-11-22 06:20:35.787980: Epoch time: 18.65 s +2024-11-22 06:20:36.667724: +2024-11-22 06:20:36.667916: Epoch 3605 +2024-11-22 06:20:36.668039: Current learning rate: 0.00583 +2024-11-22 06:20:55.820197: train_loss -0.7656 +2024-11-22 06:20:55.820670: val_loss -0.7463 +2024-11-22 06:20:55.820762: Pseudo dice [0.8123] +2024-11-22 06:20:55.820844: Epoch time: 19.15 s +2024-11-22 06:20:56.707194: +2024-11-22 06:20:56.707529: Epoch 3606 +2024-11-22 06:20:56.707656: Current learning rate: 0.00583 +2024-11-22 06:21:15.819281: train_loss -0.7651 +2024-11-22 06:21:15.819510: val_loss -0.7202 +2024-11-22 06:21:15.819587: Pseudo dice [0.8137] +2024-11-22 06:21:15.819668: Epoch time: 19.11 s +2024-11-22 06:21:16.808959: +2024-11-22 06:21:16.809166: Epoch 3607 +2024-11-22 06:21:16.809283: Current learning rate: 0.00583 +2024-11-22 06:21:35.327700: train_loss -0.764 +2024-11-22 06:21:35.327949: val_loss -0.7453 +2024-11-22 06:21:35.328031: Pseudo dice [0.8373] +2024-11-22 06:21:35.328111: Epoch time: 18.52 s +2024-11-22 06:21:36.209680: +2024-11-22 06:21:36.209874: Epoch 3608 +2024-11-22 06:21:36.209986: Current learning rate: 0.00583 +2024-11-22 06:21:55.028335: train_loss -0.7764 +2024-11-22 06:21:55.028555: val_loss -0.7398 +2024-11-22 06:21:55.028639: Pseudo dice [0.827] +2024-11-22 06:21:55.028720: Epoch time: 18.82 s +2024-11-22 06:21:55.912724: +2024-11-22 06:21:55.912996: Epoch 3609 +2024-11-22 06:21:55.913109: Current learning rate: 0.00583 +2024-11-22 06:22:13.365007: train_loss -0.7621 +2024-11-22 06:22:13.370952: val_loss -0.7271 +2024-11-22 06:22:13.371125: Pseudo dice [0.8231] +2024-11-22 06:22:13.371213: Epoch time: 17.45 s +2024-11-22 06:22:14.256178: +2024-11-22 06:22:14.256423: Epoch 3610 +2024-11-22 06:22:14.256581: Current learning rate: 0.00583 +2024-11-22 06:22:33.601937: train_loss -0.7702 +2024-11-22 06:22:33.602170: val_loss -0.6922 +2024-11-22 06:22:33.602249: Pseudo dice [0.8118] +2024-11-22 06:22:33.602332: Epoch time: 19.35 s +2024-11-22 06:22:34.628029: +2024-11-22 06:22:34.628263: Epoch 3611 +2024-11-22 06:22:34.628380: Current learning rate: 0.00583 +2024-11-22 06:22:52.957595: train_loss -0.7739 +2024-11-22 06:22:52.957817: val_loss -0.7522 +2024-11-22 06:22:52.957913: Pseudo dice [0.8306] +2024-11-22 06:22:52.958000: Epoch time: 18.33 s +2024-11-22 06:22:53.837757: +2024-11-22 06:22:53.837977: Epoch 3612 +2024-11-22 06:22:53.838091: Current learning rate: 0.00582 +2024-11-22 06:23:11.372653: train_loss -0.7762 +2024-11-22 06:23:11.372874: val_loss -0.7382 +2024-11-22 06:23:11.372951: Pseudo dice [0.811] +2024-11-22 06:23:11.373048: Epoch time: 17.54 s +2024-11-22 06:23:12.256584: +2024-11-22 06:23:12.256790: Epoch 3613 +2024-11-22 06:23:12.256901: Current learning rate: 0.00582 +2024-11-22 06:23:31.377355: train_loss -0.7849 +2024-11-22 06:23:31.377596: val_loss -0.7566 +2024-11-22 06:23:31.377671: Pseudo dice [0.8269] +2024-11-22 06:23:31.377752: Epoch time: 19.12 s +2024-11-22 06:23:32.353604: +2024-11-22 06:23:32.353891: Epoch 3614 +2024-11-22 06:23:32.354009: Current learning rate: 0.00582 +2024-11-22 06:23:50.547957: train_loss -0.7796 +2024-11-22 06:23:50.548210: val_loss -0.6951 +2024-11-22 06:23:50.548297: Pseudo dice [0.8031] +2024-11-22 06:23:50.548375: Epoch time: 18.2 s +2024-11-22 06:23:51.427785: +2024-11-22 06:23:51.428006: Epoch 3615 +2024-11-22 06:23:51.428116: Current learning rate: 0.00582 +2024-11-22 06:24:11.409335: train_loss -0.7888 +2024-11-22 06:24:11.409570: val_loss -0.776 +2024-11-22 06:24:11.409710: Pseudo dice [0.852] +2024-11-22 06:24:11.409789: Epoch time: 19.98 s +2024-11-22 06:24:12.319006: +2024-11-22 06:24:12.319224: Epoch 3616 +2024-11-22 06:24:12.319340: Current learning rate: 0.00582 +2024-11-22 06:24:31.701063: train_loss -0.7906 +2024-11-22 06:24:31.701280: val_loss -0.7464 +2024-11-22 06:24:31.701356: Pseudo dice [0.8254] +2024-11-22 06:24:31.701437: Epoch time: 19.38 s +2024-11-22 06:24:32.583168: +2024-11-22 06:24:32.583377: Epoch 3617 +2024-11-22 06:24:32.583552: Current learning rate: 0.00582 +2024-11-22 06:24:51.022277: train_loss -0.7844 +2024-11-22 06:24:51.022510: val_loss -0.762 +2024-11-22 06:24:51.022586: Pseudo dice [0.8382] +2024-11-22 06:24:51.022667: Epoch time: 18.44 s +2024-11-22 06:24:51.998463: +2024-11-22 06:24:51.998667: Epoch 3618 +2024-11-22 06:24:52.011178: Current learning rate: 0.00582 +2024-11-22 06:25:11.624952: train_loss -0.7917 +2024-11-22 06:25:11.625170: val_loss -0.73 +2024-11-22 06:25:11.625245: Pseudo dice [0.819] +2024-11-22 06:25:11.625319: Epoch time: 19.63 s +2024-11-22 06:25:12.525815: +2024-11-22 06:25:12.526014: Epoch 3619 +2024-11-22 06:25:12.526126: Current learning rate: 0.00582 +2024-11-22 06:25:31.949253: train_loss -0.7885 +2024-11-22 06:25:31.949454: val_loss -0.7521 +2024-11-22 06:25:31.949526: Pseudo dice [0.8303] +2024-11-22 06:25:31.949603: Epoch time: 19.42 s +2024-11-22 06:25:32.823796: +2024-11-22 06:25:32.824017: Epoch 3620 +2024-11-22 06:25:32.824131: Current learning rate: 0.00581 +2024-11-22 06:25:51.036451: train_loss -0.7908 +2024-11-22 06:25:51.036696: val_loss -0.7588 +2024-11-22 06:25:51.036771: Pseudo dice [0.8257] +2024-11-22 06:25:51.036854: Epoch time: 18.21 s +2024-11-22 06:25:52.237411: +2024-11-22 06:25:52.237616: Epoch 3621 +2024-11-22 06:25:52.237729: Current learning rate: 0.00581 +2024-11-22 06:26:10.337224: train_loss -0.785 +2024-11-22 06:26:10.337439: val_loss -0.7221 +2024-11-22 06:26:10.337515: Pseudo dice [0.8187] +2024-11-22 06:26:10.337592: Epoch time: 18.1 s +2024-11-22 06:26:11.201344: +2024-11-22 06:26:11.201548: Epoch 3622 +2024-11-22 06:26:11.201654: Current learning rate: 0.00581 +2024-11-22 06:26:31.103803: train_loss -0.7912 +2024-11-22 06:26:31.104083: val_loss -0.7466 +2024-11-22 06:26:31.104199: Pseudo dice [0.8288] +2024-11-22 06:26:31.104275: Epoch time: 19.9 s +2024-11-22 06:26:31.981435: +2024-11-22 06:26:31.981680: Epoch 3623 +2024-11-22 06:26:31.981797: Current learning rate: 0.00581 +2024-11-22 06:26:49.917150: train_loss -0.7865 +2024-11-22 06:26:49.917400: val_loss -0.7547 +2024-11-22 06:26:49.917480: Pseudo dice [0.8247] +2024-11-22 06:26:49.917566: Epoch time: 17.94 s +2024-11-22 06:26:50.789790: +2024-11-22 06:26:50.790000: Epoch 3624 +2024-11-22 06:26:50.790114: Current learning rate: 0.00581 +2024-11-22 06:27:08.704139: train_loss -0.7882 +2024-11-22 06:27:08.704358: val_loss -0.7588 +2024-11-22 06:27:08.704434: Pseudo dice [0.8339] +2024-11-22 06:27:08.704514: Epoch time: 17.92 s +2024-11-22 06:27:09.600112: +2024-11-22 06:27:09.600339: Epoch 3625 +2024-11-22 06:27:09.600452: Current learning rate: 0.00581 +2024-11-22 06:27:28.577498: train_loss -0.7964 +2024-11-22 06:27:28.577708: val_loss -0.7494 +2024-11-22 06:27:28.577785: Pseudo dice [0.8352] +2024-11-22 06:27:28.577864: Epoch time: 18.98 s +2024-11-22 06:27:29.655388: +2024-11-22 06:27:29.655591: Epoch 3626 +2024-11-22 06:27:29.655701: Current learning rate: 0.00581 +2024-11-22 06:27:48.387241: train_loss -0.787 +2024-11-22 06:27:48.387455: val_loss -0.7254 +2024-11-22 06:27:48.387529: Pseudo dice [0.8115] +2024-11-22 06:27:48.387606: Epoch time: 18.73 s +2024-11-22 06:27:49.295202: +2024-11-22 06:27:49.295399: Epoch 3627 +2024-11-22 06:27:49.295513: Current learning rate: 0.00581 +2024-11-22 06:28:07.574753: train_loss -0.7985 +2024-11-22 06:28:07.574996: val_loss -0.7679 +2024-11-22 06:28:07.575078: Pseudo dice [0.8441] +2024-11-22 06:28:07.575161: Epoch time: 18.28 s +2024-11-22 06:28:08.462698: +2024-11-22 06:28:08.462905: Epoch 3628 +2024-11-22 06:28:08.463017: Current learning rate: 0.00581 +2024-11-22 06:28:26.912095: train_loss -0.7973 +2024-11-22 06:28:26.912349: val_loss -0.7618 +2024-11-22 06:28:26.912428: Pseudo dice [0.8359] +2024-11-22 06:28:26.912508: Epoch time: 18.45 s +2024-11-22 06:28:27.797969: +2024-11-22 06:28:27.798173: Epoch 3629 +2024-11-22 06:28:27.798287: Current learning rate: 0.0058 +2024-11-22 06:28:47.025551: train_loss -0.7883 +2024-11-22 06:28:47.025778: val_loss -0.7582 +2024-11-22 06:28:47.025854: Pseudo dice [0.8272] +2024-11-22 06:28:47.025934: Epoch time: 19.23 s +2024-11-22 06:28:47.920444: +2024-11-22 06:28:47.920641: Epoch 3630 +2024-11-22 06:28:47.920758: Current learning rate: 0.0058 +2024-11-22 06:29:06.509080: train_loss -0.7826 +2024-11-22 06:29:06.509296: val_loss -0.7289 +2024-11-22 06:29:06.509371: Pseudo dice [0.8035] +2024-11-22 06:29:06.509456: Epoch time: 18.59 s +2024-11-22 06:29:07.418327: +2024-11-22 06:29:07.418596: Epoch 3631 +2024-11-22 06:29:07.418724: Current learning rate: 0.0058 +2024-11-22 06:29:25.650534: train_loss -0.7849 +2024-11-22 06:29:25.650800: val_loss -0.7463 +2024-11-22 06:29:25.650883: Pseudo dice [0.8436] +2024-11-22 06:29:25.650972: Epoch time: 18.23 s +2024-11-22 06:29:26.671965: +2024-11-22 06:29:26.672194: Epoch 3632 +2024-11-22 06:29:26.672306: Current learning rate: 0.0058 +2024-11-22 06:29:45.689937: train_loss -0.7792 +2024-11-22 06:29:45.690520: val_loss -0.7401 +2024-11-22 06:29:45.690618: Pseudo dice [0.8077] +2024-11-22 06:29:45.690694: Epoch time: 19.02 s +2024-11-22 06:29:46.582360: +2024-11-22 06:29:46.582565: Epoch 3633 +2024-11-22 06:29:46.582678: Current learning rate: 0.0058 +2024-11-22 06:30:04.519397: train_loss -0.78 +2024-11-22 06:30:04.519614: val_loss -0.7551 +2024-11-22 06:30:04.519689: Pseudo dice [0.8379] +2024-11-22 06:30:04.519764: Epoch time: 17.94 s +2024-11-22 06:30:05.404027: +2024-11-22 06:30:05.404255: Epoch 3634 +2024-11-22 06:30:05.404369: Current learning rate: 0.0058 +2024-11-22 06:30:25.792398: train_loss -0.783 +2024-11-22 06:30:25.792649: val_loss -0.7231 +2024-11-22 06:30:25.792729: Pseudo dice [0.8354] +2024-11-22 06:30:25.792814: Epoch time: 20.39 s +2024-11-22 06:30:26.748714: +2024-11-22 06:30:26.748933: Epoch 3635 +2024-11-22 06:30:26.749059: Current learning rate: 0.0058 +2024-11-22 06:30:46.399744: train_loss -0.7856 +2024-11-22 06:30:46.399965: val_loss -0.7265 +2024-11-22 06:30:46.400048: Pseudo dice [0.8267] +2024-11-22 06:30:46.402275: Epoch time: 19.65 s +2024-11-22 06:30:47.419940: +2024-11-22 06:30:47.420161: Epoch 3636 +2024-11-22 06:30:47.420283: Current learning rate: 0.0058 +2024-11-22 06:31:06.054952: train_loss -0.7854 +2024-11-22 06:31:06.055174: val_loss -0.7531 +2024-11-22 06:31:06.055250: Pseudo dice [0.8351] +2024-11-22 06:31:06.055329: Epoch time: 18.64 s +2024-11-22 06:31:06.975443: +2024-11-22 06:31:06.975670: Epoch 3637 +2024-11-22 06:31:06.975776: Current learning rate: 0.00579 +2024-11-22 06:31:26.195395: train_loss -0.7803 +2024-11-22 06:31:26.195586: val_loss -0.7436 +2024-11-22 06:31:26.195659: Pseudo dice [0.8357] +2024-11-22 06:31:26.195750: Epoch time: 19.22 s +2024-11-22 06:31:27.069642: +2024-11-22 06:31:27.069864: Epoch 3638 +2024-11-22 06:31:27.069980: Current learning rate: 0.00579 +2024-11-22 06:31:45.759499: train_loss -0.7934 +2024-11-22 06:31:45.759780: val_loss -0.7558 +2024-11-22 06:31:45.759862: Pseudo dice [0.8276] +2024-11-22 06:31:45.759949: Epoch time: 18.69 s +2024-11-22 06:31:46.666209: +2024-11-22 06:31:46.666407: Epoch 3639 +2024-11-22 06:31:46.666522: Current learning rate: 0.00579 +2024-11-22 06:32:04.690961: train_loss -0.7938 +2024-11-22 06:32:04.693364: val_loss -0.7621 +2024-11-22 06:32:04.693489: Pseudo dice [0.8432] +2024-11-22 06:32:04.693568: Epoch time: 18.03 s +2024-11-22 06:32:05.793755: +2024-11-22 06:32:05.793956: Epoch 3640 +2024-11-22 06:32:05.794070: Current learning rate: 0.00579 +2024-11-22 06:32:24.230251: train_loss -0.783 +2024-11-22 06:32:24.230456: val_loss -0.7403 +2024-11-22 06:32:24.230530: Pseudo dice [0.8339] +2024-11-22 06:32:24.230607: Epoch time: 18.44 s +2024-11-22 06:32:25.199655: +2024-11-22 06:32:25.199854: Epoch 3641 +2024-11-22 06:32:25.199963: Current learning rate: 0.00579 +2024-11-22 06:32:44.082371: train_loss -0.7691 +2024-11-22 06:32:44.082566: val_loss -0.7405 +2024-11-22 06:32:44.082641: Pseudo dice [0.8118] +2024-11-22 06:32:44.082716: Epoch time: 18.88 s +2024-11-22 06:32:44.959434: +2024-11-22 06:32:44.959641: Epoch 3642 +2024-11-22 06:32:44.959750: Current learning rate: 0.00579 +2024-11-22 06:33:03.539892: train_loss -0.7757 +2024-11-22 06:33:03.541672: val_loss -0.7438 +2024-11-22 06:33:03.541785: Pseudo dice [0.8228] +2024-11-22 06:33:03.541871: Epoch time: 18.58 s +2024-11-22 06:33:04.436192: +2024-11-22 06:33:04.436405: Epoch 3643 +2024-11-22 06:33:04.436519: Current learning rate: 0.00579 +2024-11-22 06:33:22.234893: train_loss -0.7791 +2024-11-22 06:33:22.235120: val_loss -0.7456 +2024-11-22 06:33:22.252310: Pseudo dice [0.8291] +2024-11-22 06:33:22.252471: Epoch time: 17.8 s +2024-11-22 06:33:23.535620: +2024-11-22 06:33:23.535823: Epoch 3644 +2024-11-22 06:33:23.535931: Current learning rate: 0.00579 +2024-11-22 06:33:42.312411: train_loss -0.7823 +2024-11-22 06:33:42.312704: val_loss -0.7239 +2024-11-22 06:33:42.312782: Pseudo dice [0.8221] +2024-11-22 06:33:42.312873: Epoch time: 18.78 s +2024-11-22 06:33:43.209830: +2024-11-22 06:33:43.210116: Epoch 3645 +2024-11-22 06:33:43.210231: Current learning rate: 0.00579 +2024-11-22 06:34:01.639362: train_loss -0.7835 +2024-11-22 06:34:01.639583: val_loss -0.7554 +2024-11-22 06:34:01.639657: Pseudo dice [0.8385] +2024-11-22 06:34:01.639733: Epoch time: 18.43 s +2024-11-22 06:34:02.528808: +2024-11-22 06:34:02.529033: Epoch 3646 +2024-11-22 06:34:02.529149: Current learning rate: 0.00578 +2024-11-22 06:34:21.471001: train_loss -0.7863 +2024-11-22 06:34:21.471218: val_loss -0.735 +2024-11-22 06:34:21.471293: Pseudo dice [0.8136] +2024-11-22 06:34:21.471372: Epoch time: 18.94 s +2024-11-22 06:34:22.355001: +2024-11-22 06:34:22.355224: Epoch 3647 +2024-11-22 06:34:22.355343: Current learning rate: 0.00578 +2024-11-22 06:34:40.074636: train_loss -0.7821 +2024-11-22 06:34:40.074885: val_loss -0.7457 +2024-11-22 06:34:40.074965: Pseudo dice [0.8148] +2024-11-22 06:34:40.075050: Epoch time: 17.72 s +2024-11-22 06:34:40.962913: +2024-11-22 06:34:40.963128: Epoch 3648 +2024-11-22 06:34:40.963244: Current learning rate: 0.00578 +2024-11-22 06:35:00.103135: train_loss -0.7717 +2024-11-22 06:35:00.103426: val_loss -0.7449 +2024-11-22 06:35:00.103513: Pseudo dice [0.8177] +2024-11-22 06:35:00.103606: Epoch time: 19.14 s +2024-11-22 06:35:01.135404: +2024-11-22 06:35:01.135620: Epoch 3649 +2024-11-22 06:35:01.135724: Current learning rate: 0.00578 +2024-11-22 06:35:19.455698: train_loss -0.7836 +2024-11-22 06:35:19.455899: val_loss -0.7595 +2024-11-22 06:35:19.455976: Pseudo dice [0.8239] +2024-11-22 06:35:19.456056: Epoch time: 18.32 s +2024-11-22 06:35:20.576467: +2024-11-22 06:35:20.576674: Epoch 3650 +2024-11-22 06:35:20.576799: Current learning rate: 0.00578 +2024-11-22 06:35:39.715203: train_loss -0.7798 +2024-11-22 06:35:39.715430: val_loss -0.7384 +2024-11-22 06:35:39.715504: Pseudo dice [0.8306] +2024-11-22 06:35:39.715581: Epoch time: 19.14 s +2024-11-22 06:35:40.625358: +2024-11-22 06:35:40.625590: Epoch 3651 +2024-11-22 06:35:40.625704: Current learning rate: 0.00578 +2024-11-22 06:35:59.435520: train_loss -0.7879 +2024-11-22 06:35:59.435741: val_loss -0.7415 +2024-11-22 06:35:59.435820: Pseudo dice [0.8301] +2024-11-22 06:35:59.435904: Epoch time: 18.81 s +2024-11-22 06:36:00.319045: +2024-11-22 06:36:00.319276: Epoch 3652 +2024-11-22 06:36:00.319404: Current learning rate: 0.00578 +2024-11-22 06:36:19.519227: train_loss -0.7997 +2024-11-22 06:36:19.519435: val_loss -0.7626 +2024-11-22 06:36:19.519514: Pseudo dice [0.8305] +2024-11-22 06:36:19.519591: Epoch time: 19.2 s +2024-11-22 06:36:20.435524: +2024-11-22 06:36:20.435725: Epoch 3653 +2024-11-22 06:36:20.435841: Current learning rate: 0.00578 +2024-11-22 06:36:38.840648: train_loss -0.795 +2024-11-22 06:36:38.846103: val_loss -0.7498 +2024-11-22 06:36:38.846261: Pseudo dice [0.8216] +2024-11-22 06:36:38.846346: Epoch time: 18.41 s +2024-11-22 06:36:39.839062: +2024-11-22 06:36:39.839362: Epoch 3654 +2024-11-22 06:36:39.839473: Current learning rate: 0.00577 +2024-11-22 06:36:57.868365: train_loss -0.7895 +2024-11-22 06:36:57.868583: val_loss -0.7489 +2024-11-22 06:36:57.868659: Pseudo dice [0.8308] +2024-11-22 06:36:57.868736: Epoch time: 18.03 s +2024-11-22 06:36:58.755617: +2024-11-22 06:36:58.755979: Epoch 3655 +2024-11-22 06:36:58.756094: Current learning rate: 0.00577 +2024-11-22 06:37:16.915110: train_loss -0.7895 +2024-11-22 06:37:16.915704: val_loss -0.7556 +2024-11-22 06:37:16.915806: Pseudo dice [0.827] +2024-11-22 06:37:16.915889: Epoch time: 18.16 s +2024-11-22 06:37:17.799316: +2024-11-22 06:37:17.799536: Epoch 3656 +2024-11-22 06:37:17.799650: Current learning rate: 0.00577 +2024-11-22 06:37:35.002200: train_loss -0.7821 +2024-11-22 06:37:35.002415: val_loss -0.7689 +2024-11-22 06:37:35.002491: Pseudo dice [0.8399] +2024-11-22 06:37:35.002568: Epoch time: 17.2 s +2024-11-22 06:37:35.879305: +2024-11-22 06:37:35.879535: Epoch 3657 +2024-11-22 06:37:35.879649: Current learning rate: 0.00577 +2024-11-22 06:37:54.805439: train_loss -0.7876 +2024-11-22 06:37:54.805654: val_loss -0.7455 +2024-11-22 06:37:54.805728: Pseudo dice [0.8404] +2024-11-22 06:37:54.805808: Epoch time: 18.93 s +2024-11-22 06:37:55.707577: +2024-11-22 06:37:55.707785: Epoch 3658 +2024-11-22 06:37:55.707904: Current learning rate: 0.00577 +2024-11-22 06:38:13.929391: train_loss -0.7865 +2024-11-22 06:38:13.929637: val_loss -0.755 +2024-11-22 06:38:13.929715: Pseudo dice [0.8206] +2024-11-22 06:38:13.929796: Epoch time: 18.22 s +2024-11-22 06:38:14.860415: +2024-11-22 06:38:14.860632: Epoch 3659 +2024-11-22 06:38:14.860747: Current learning rate: 0.00577 +2024-11-22 06:38:33.226667: train_loss -0.7827 +2024-11-22 06:38:33.226883: val_loss -0.711 +2024-11-22 06:38:33.226961: Pseudo dice [0.8091] +2024-11-22 06:38:33.227045: Epoch time: 18.37 s +2024-11-22 06:38:34.107342: +2024-11-22 06:38:34.107543: Epoch 3660 +2024-11-22 06:38:34.107652: Current learning rate: 0.00577 +2024-11-22 06:38:52.612943: train_loss -0.7722 +2024-11-22 06:38:52.613163: val_loss -0.7537 +2024-11-22 06:38:52.613241: Pseudo dice [0.8369] +2024-11-22 06:38:52.613319: Epoch time: 18.51 s +2024-11-22 06:38:53.496330: +2024-11-22 06:38:53.496529: Epoch 3661 +2024-11-22 06:38:53.496647: Current learning rate: 0.00577 +2024-11-22 06:39:13.095181: train_loss -0.7801 +2024-11-22 06:39:13.095400: val_loss -0.7379 +2024-11-22 06:39:13.095476: Pseudo dice [0.827] +2024-11-22 06:39:13.095555: Epoch time: 19.6 s +2024-11-22 06:39:13.994137: +2024-11-22 06:39:13.994358: Epoch 3662 +2024-11-22 06:39:13.994480: Current learning rate: 0.00576 +2024-11-22 06:39:32.614578: train_loss -0.7823 +2024-11-22 06:39:32.614815: val_loss -0.7245 +2024-11-22 06:39:32.614888: Pseudo dice [0.8119] +2024-11-22 06:39:32.614969: Epoch time: 18.62 s +2024-11-22 06:39:33.498627: +2024-11-22 06:39:33.498836: Epoch 3663 +2024-11-22 06:39:33.498949: Current learning rate: 0.00576 +2024-11-22 06:39:52.070554: train_loss -0.7806 +2024-11-22 06:39:52.070844: val_loss -0.7414 +2024-11-22 06:39:52.070923: Pseudo dice [0.8074] +2024-11-22 06:39:52.071008: Epoch time: 18.57 s +2024-11-22 06:39:52.997647: +2024-11-22 06:39:52.997877: Epoch 3664 +2024-11-22 06:39:52.997999: Current learning rate: 0.00576 +2024-11-22 06:40:11.564837: train_loss -0.7731 +2024-11-22 06:40:11.565058: val_loss -0.6822 +2024-11-22 06:40:11.565140: Pseudo dice [0.7767] +2024-11-22 06:40:11.565219: Epoch time: 18.57 s +2024-11-22 06:40:12.444813: +2024-11-22 06:40:12.445007: Epoch 3665 +2024-11-22 06:40:12.445230: Current learning rate: 0.00576 +2024-11-22 06:40:31.867695: train_loss -0.7484 +2024-11-22 06:40:31.867941: val_loss -0.7325 +2024-11-22 06:40:31.868028: Pseudo dice [0.8073] +2024-11-22 06:40:31.868116: Epoch time: 19.42 s +2024-11-22 06:40:32.747405: +2024-11-22 06:40:32.747669: Epoch 3666 +2024-11-22 06:40:32.747785: Current learning rate: 0.00576 +2024-11-22 06:40:51.117841: train_loss -0.7581 +2024-11-22 06:40:51.118099: val_loss -0.7451 +2024-11-22 06:40:51.118174: Pseudo dice [0.832] +2024-11-22 06:40:51.118252: Epoch time: 18.37 s +2024-11-22 06:40:52.454568: +2024-11-22 06:40:52.454781: Epoch 3667 +2024-11-22 06:40:52.454895: Current learning rate: 0.00576 +2024-11-22 06:41:10.036783: train_loss -0.7674 +2024-11-22 06:41:10.037030: val_loss -0.737 +2024-11-22 06:41:10.037105: Pseudo dice [0.821] +2024-11-22 06:41:10.037182: Epoch time: 17.58 s +2024-11-22 06:41:10.918157: +2024-11-22 06:41:10.918366: Epoch 3668 +2024-11-22 06:41:10.918477: Current learning rate: 0.00576 +2024-11-22 06:41:29.819017: train_loss -0.7794 +2024-11-22 06:41:29.819270: val_loss -0.7289 +2024-11-22 06:41:29.819347: Pseudo dice [0.8218] +2024-11-22 06:41:29.819438: Epoch time: 18.9 s +2024-11-22 06:41:30.838779: +2024-11-22 06:41:30.838985: Epoch 3669 +2024-11-22 06:41:30.839104: Current learning rate: 0.00576 +2024-11-22 06:41:49.226742: train_loss -0.7803 +2024-11-22 06:41:49.226969: val_loss -0.7389 +2024-11-22 06:41:49.227053: Pseudo dice [0.8039] +2024-11-22 06:41:49.227134: Epoch time: 18.39 s +2024-11-22 06:41:50.106572: +2024-11-22 06:41:50.106805: Epoch 3670 +2024-11-22 06:41:50.106924: Current learning rate: 0.00576 +2024-11-22 06:42:09.377682: train_loss -0.7775 +2024-11-22 06:42:09.377888: val_loss -0.7287 +2024-11-22 06:42:09.377962: Pseudo dice [0.8145] +2024-11-22 06:42:09.378040: Epoch time: 19.27 s +2024-11-22 06:42:10.257923: +2024-11-22 06:42:10.258141: Epoch 3671 +2024-11-22 06:42:10.258256: Current learning rate: 0.00575 +2024-11-22 06:42:28.724908: train_loss -0.7811 +2024-11-22 06:42:28.725131: val_loss -0.7484 +2024-11-22 06:42:28.725213: Pseudo dice [0.8266] +2024-11-22 06:42:28.725291: Epoch time: 18.47 s +2024-11-22 06:42:29.605953: +2024-11-22 06:42:29.606189: Epoch 3672 +2024-11-22 06:42:29.606305: Current learning rate: 0.00575 +2024-11-22 06:42:47.662793: train_loss -0.7803 +2024-11-22 06:42:47.663023: val_loss -0.7333 +2024-11-22 06:42:47.663125: Pseudo dice [0.8157] +2024-11-22 06:42:47.663207: Epoch time: 18.06 s +2024-11-22 06:42:48.548490: +2024-11-22 06:42:48.548681: Epoch 3673 +2024-11-22 06:42:48.548791: Current learning rate: 0.00575 +2024-11-22 06:43:06.992889: train_loss -0.7861 +2024-11-22 06:43:06.993129: val_loss -0.7469 +2024-11-22 06:43:06.993205: Pseudo dice [0.8175] +2024-11-22 06:43:06.993287: Epoch time: 18.45 s +2024-11-22 06:43:07.874862: +2024-11-22 06:43:07.875094: Epoch 3674 +2024-11-22 06:43:07.875212: Current learning rate: 0.00575 +2024-11-22 06:43:26.551495: train_loss -0.7905 +2024-11-22 06:43:26.551716: val_loss -0.7092 +2024-11-22 06:43:26.551794: Pseudo dice [0.828] +2024-11-22 06:43:26.551871: Epoch time: 18.68 s +2024-11-22 06:43:27.435365: +2024-11-22 06:43:27.435611: Epoch 3675 +2024-11-22 06:43:27.435725: Current learning rate: 0.00575 +2024-11-22 06:43:45.949012: train_loss -0.7737 +2024-11-22 06:43:45.949232: val_loss -0.7483 +2024-11-22 06:43:45.949312: Pseudo dice [0.8117] +2024-11-22 06:43:45.949406: Epoch time: 18.51 s +2024-11-22 06:43:46.827419: +2024-11-22 06:43:46.827621: Epoch 3676 +2024-11-22 06:43:46.827734: Current learning rate: 0.00575 +2024-11-22 06:44:05.890836: train_loss -0.7788 +2024-11-22 06:44:05.891115: val_loss -0.7281 +2024-11-22 06:44:05.891193: Pseudo dice [0.8252] +2024-11-22 06:44:05.891277: Epoch time: 19.06 s +2024-11-22 06:44:06.774762: +2024-11-22 06:44:06.774968: Epoch 3677 +2024-11-22 06:44:06.775090: Current learning rate: 0.00575 +2024-11-22 06:44:26.123628: train_loss -0.7788 +2024-11-22 06:44:26.123846: val_loss -0.7451 +2024-11-22 06:44:26.123918: Pseudo dice [0.8118] +2024-11-22 06:44:26.124003: Epoch time: 19.35 s +2024-11-22 06:44:27.436626: +2024-11-22 06:44:27.436845: Epoch 3678 +2024-11-22 06:44:27.436962: Current learning rate: 0.00575 +2024-11-22 06:44:45.801674: train_loss -0.7766 +2024-11-22 06:44:45.801898: val_loss -0.7581 +2024-11-22 06:44:45.801974: Pseudo dice [0.8304] +2024-11-22 06:44:45.802059: Epoch time: 18.37 s +2024-11-22 06:44:46.680762: +2024-11-22 06:44:46.681038: Epoch 3679 +2024-11-22 06:44:46.681157: Current learning rate: 0.00574 +2024-11-22 06:45:04.553883: train_loss -0.7796 +2024-11-22 06:45:04.554138: val_loss -0.7314 +2024-11-22 06:45:04.554216: Pseudo dice [0.8237] +2024-11-22 06:45:04.554300: Epoch time: 17.87 s +2024-11-22 06:45:05.438121: +2024-11-22 06:45:05.438318: Epoch 3680 +2024-11-22 06:45:05.438428: Current learning rate: 0.00574 +2024-11-22 06:45:24.230201: train_loss -0.7843 +2024-11-22 06:45:24.230433: val_loss -0.7475 +2024-11-22 06:45:24.230506: Pseudo dice [0.8322] +2024-11-22 06:45:24.230582: Epoch time: 18.79 s +2024-11-22 06:45:25.114695: +2024-11-22 06:45:25.114910: Epoch 3681 +2024-11-22 06:45:25.115026: Current learning rate: 0.00574 +2024-11-22 06:45:43.141905: train_loss -0.7844 +2024-11-22 06:45:43.144295: val_loss -0.7206 +2024-11-22 06:45:43.163759: Pseudo dice [0.8185] +2024-11-22 06:45:43.163933: Epoch time: 18.03 s +2024-11-22 06:45:44.099416: +2024-11-22 06:45:44.099635: Epoch 3682 +2024-11-22 06:45:44.099749: Current learning rate: 0.00574 +2024-11-22 06:46:02.341930: train_loss -0.7762 +2024-11-22 06:46:02.342163: val_loss -0.7398 +2024-11-22 06:46:02.342240: Pseudo dice [0.8362] +2024-11-22 06:46:02.342319: Epoch time: 18.24 s +2024-11-22 06:46:03.238070: +2024-11-22 06:46:03.238296: Epoch 3683 +2024-11-22 06:46:03.238414: Current learning rate: 0.00574 +2024-11-22 06:46:21.815887: train_loss -0.7914 +2024-11-22 06:46:21.816141: val_loss -0.7378 +2024-11-22 06:46:21.816219: Pseudo dice [0.8138] +2024-11-22 06:46:21.816306: Epoch time: 18.58 s +2024-11-22 06:46:22.732734: +2024-11-22 06:46:22.732984: Epoch 3684 +2024-11-22 06:46:22.733099: Current learning rate: 0.00574 +2024-11-22 06:46:41.665088: train_loss -0.7886 +2024-11-22 06:46:41.665310: val_loss -0.7364 +2024-11-22 06:46:41.670578: Pseudo dice [0.8226] +2024-11-22 06:46:41.670753: Epoch time: 18.93 s +2024-11-22 06:46:42.615929: +2024-11-22 06:46:42.616148: Epoch 3685 +2024-11-22 06:46:42.616269: Current learning rate: 0.00574 +2024-11-22 06:47:00.449028: train_loss -0.7832 +2024-11-22 06:47:00.449250: val_loss -0.742 +2024-11-22 06:47:00.449325: Pseudo dice [0.823] +2024-11-22 06:47:00.449403: Epoch time: 17.83 s +2024-11-22 06:47:01.330073: +2024-11-22 06:47:01.330277: Epoch 3686 +2024-11-22 06:47:01.330390: Current learning rate: 0.00574 +2024-11-22 06:47:20.316265: train_loss -0.7852 +2024-11-22 06:47:20.316516: val_loss -0.7474 +2024-11-22 06:47:20.316617: Pseudo dice [0.8238] +2024-11-22 06:47:20.316700: Epoch time: 18.99 s +2024-11-22 06:47:21.210298: +2024-11-22 06:47:21.210494: Epoch 3687 +2024-11-22 06:47:21.210608: Current learning rate: 0.00573 +2024-11-22 06:47:39.784073: train_loss -0.788 +2024-11-22 06:47:39.784312: val_loss -0.7473 +2024-11-22 06:47:39.784390: Pseudo dice [0.8331] +2024-11-22 06:47:39.784472: Epoch time: 18.57 s +2024-11-22 06:47:40.668192: +2024-11-22 06:47:40.668382: Epoch 3688 +2024-11-22 06:47:40.668493: Current learning rate: 0.00573 +2024-11-22 06:47:59.668224: train_loss -0.7886 +2024-11-22 06:47:59.668448: val_loss -0.7632 +2024-11-22 06:47:59.668523: Pseudo dice [0.8368] +2024-11-22 06:47:59.668600: Epoch time: 19.0 s +2024-11-22 06:48:00.709241: +2024-11-22 06:48:00.709450: Epoch 3689 +2024-11-22 06:48:00.709559: Current learning rate: 0.00573 +2024-11-22 06:48:20.005800: train_loss -0.7989 +2024-11-22 06:48:20.006038: val_loss -0.739 +2024-11-22 06:48:20.006115: Pseudo dice [0.823] +2024-11-22 06:48:20.006196: Epoch time: 19.3 s +2024-11-22 06:48:21.501755: +2024-11-22 06:48:21.501997: Epoch 3690 +2024-11-22 06:48:21.502109: Current learning rate: 0.00573 +2024-11-22 06:48:40.051412: train_loss -0.7886 +2024-11-22 06:48:40.051662: val_loss -0.747 +2024-11-22 06:48:40.051740: Pseudo dice [0.8312] +2024-11-22 06:48:40.051820: Epoch time: 18.55 s +2024-11-22 06:48:40.938909: +2024-11-22 06:48:40.939234: Epoch 3691 +2024-11-22 06:48:40.939355: Current learning rate: 0.00573 +2024-11-22 06:48:59.454051: train_loss -0.7872 +2024-11-22 06:48:59.454268: val_loss -0.7454 +2024-11-22 06:48:59.454342: Pseudo dice [0.8352] +2024-11-22 06:48:59.454417: Epoch time: 18.52 s +2024-11-22 06:49:00.336161: +2024-11-22 06:49:00.336380: Epoch 3692 +2024-11-22 06:49:00.336493: Current learning rate: 0.00573 +2024-11-22 06:49:19.379591: train_loss -0.7865 +2024-11-22 06:49:19.379784: val_loss -0.7529 +2024-11-22 06:49:19.379856: Pseudo dice [0.8322] +2024-11-22 06:49:19.379935: Epoch time: 19.04 s +2024-11-22 06:49:20.298515: +2024-11-22 06:49:20.298806: Epoch 3693 +2024-11-22 06:49:20.298923: Current learning rate: 0.00573 +2024-11-22 06:49:39.266454: train_loss -0.7718 +2024-11-22 06:49:39.266705: val_loss -0.7311 +2024-11-22 06:49:39.266784: Pseudo dice [0.8181] +2024-11-22 06:49:39.266875: Epoch time: 18.97 s +2024-11-22 06:49:40.158800: +2024-11-22 06:49:40.159010: Epoch 3694 +2024-11-22 06:49:40.159124: Current learning rate: 0.00573 +2024-11-22 06:49:58.553418: train_loss -0.7872 +2024-11-22 06:49:58.553654: val_loss -0.7514 +2024-11-22 06:49:58.553732: Pseudo dice [0.8329] +2024-11-22 06:49:58.553810: Epoch time: 18.4 s +2024-11-22 06:49:59.436297: +2024-11-22 06:49:59.436588: Epoch 3695 +2024-11-22 06:49:59.436704: Current learning rate: 0.00573 +2024-11-22 06:50:17.549629: train_loss -0.7818 +2024-11-22 06:50:17.549884: val_loss -0.721 +2024-11-22 06:50:17.549960: Pseudo dice [0.8] +2024-11-22 06:50:17.550107: Epoch time: 18.11 s +2024-11-22 06:50:18.488407: +2024-11-22 06:50:18.488703: Epoch 3696 +2024-11-22 06:50:18.488821: Current learning rate: 0.00572 +2024-11-22 06:50:36.596185: train_loss -0.7897 +2024-11-22 06:50:36.596407: val_loss -0.7379 +2024-11-22 06:50:36.596579: Pseudo dice [0.8336] +2024-11-22 06:50:36.596662: Epoch time: 18.11 s +2024-11-22 06:50:37.485671: +2024-11-22 06:50:37.485899: Epoch 3697 +2024-11-22 06:50:37.486030: Current learning rate: 0.00572 +2024-11-22 06:50:56.011111: train_loss -0.7804 +2024-11-22 06:50:56.011358: val_loss -0.7647 +2024-11-22 06:50:56.011445: Pseudo dice [0.836] +2024-11-22 06:50:56.011533: Epoch time: 18.53 s +2024-11-22 06:50:56.891852: +2024-11-22 06:50:56.892055: Epoch 3698 +2024-11-22 06:50:56.892164: Current learning rate: 0.00572 +2024-11-22 06:51:14.059189: train_loss -0.7927 +2024-11-22 06:51:14.059426: val_loss -0.7468 +2024-11-22 06:51:14.059507: Pseudo dice [0.8396] +2024-11-22 06:51:14.059583: Epoch time: 17.17 s +2024-11-22 06:51:14.937655: +2024-11-22 06:51:14.937870: Epoch 3699 +2024-11-22 06:51:14.937981: Current learning rate: 0.00572 +2024-11-22 06:51:32.539400: train_loss -0.7905 +2024-11-22 06:51:32.539611: val_loss -0.757 +2024-11-22 06:51:32.539691: Pseudo dice [0.8249] +2024-11-22 06:51:32.539771: Epoch time: 17.6 s +2024-11-22 06:51:33.688698: +2024-11-22 06:51:33.688920: Epoch 3700 +2024-11-22 06:51:33.689041: Current learning rate: 0.00572 +2024-11-22 06:51:52.777215: train_loss -0.7902 +2024-11-22 06:51:52.777507: val_loss -0.7404 +2024-11-22 06:51:52.777584: Pseudo dice [0.8148] +2024-11-22 06:51:52.777670: Epoch time: 19.09 s +2024-11-22 06:51:53.658712: +2024-11-22 06:51:53.658911: Epoch 3701 +2024-11-22 06:51:53.659026: Current learning rate: 0.00572 +2024-11-22 06:52:11.208186: train_loss -0.7842 +2024-11-22 06:52:11.208658: val_loss -0.7421 +2024-11-22 06:52:11.210942: Pseudo dice [0.8135] +2024-11-22 06:52:11.212976: Epoch time: 17.55 s +2024-11-22 06:52:12.104818: +2024-11-22 06:52:12.105115: Epoch 3702 +2024-11-22 06:52:12.105230: Current learning rate: 0.00572 +2024-11-22 06:52:30.083604: train_loss -0.7847 +2024-11-22 06:52:30.084092: val_loss -0.7238 +2024-11-22 06:52:30.084193: Pseudo dice [0.8132] +2024-11-22 06:52:30.084300: Epoch time: 17.98 s +2024-11-22 06:52:30.962412: +2024-11-22 06:52:30.962688: Epoch 3703 +2024-11-22 06:52:30.962803: Current learning rate: 0.00572 +2024-11-22 06:52:48.790505: train_loss -0.7528 +2024-11-22 06:52:48.790746: val_loss -0.7382 +2024-11-22 06:52:48.790860: Pseudo dice [0.8214] +2024-11-22 06:52:48.790949: Epoch time: 17.83 s +2024-11-22 06:52:49.669752: +2024-11-22 06:52:49.669966: Epoch 3704 +2024-11-22 06:52:49.670085: Current learning rate: 0.00571 +2024-11-22 06:53:08.167847: train_loss -0.7612 +2024-11-22 06:53:08.168085: val_loss -0.7224 +2024-11-22 06:53:08.168166: Pseudo dice [0.8216] +2024-11-22 06:53:08.173453: Epoch time: 18.5 s +2024-11-22 06:53:09.108794: +2024-11-22 06:53:09.109018: Epoch 3705 +2024-11-22 06:53:09.109129: Current learning rate: 0.00571 +2024-11-22 06:53:27.021828: train_loss -0.7741 +2024-11-22 06:53:27.022048: val_loss -0.7583 +2024-11-22 06:53:27.022129: Pseudo dice [0.8308] +2024-11-22 06:53:27.022206: Epoch time: 17.91 s +2024-11-22 06:53:27.900878: +2024-11-22 06:53:27.901124: Epoch 3706 +2024-11-22 06:53:27.901240: Current learning rate: 0.00571 +2024-11-22 06:53:46.283696: train_loss -0.772 +2024-11-22 06:53:46.283909: val_loss -0.7483 +2024-11-22 06:53:46.283980: Pseudo dice [0.8222] +2024-11-22 06:53:46.284060: Epoch time: 18.38 s +2024-11-22 06:53:47.210023: +2024-11-22 06:53:47.210216: Epoch 3707 +2024-11-22 06:53:47.210564: Current learning rate: 0.00571 +2024-11-22 06:54:05.706792: train_loss -0.7719 +2024-11-22 06:54:05.707035: val_loss -0.7551 +2024-11-22 06:54:05.707114: Pseudo dice [0.819] +2024-11-22 06:54:05.707199: Epoch time: 18.5 s +2024-11-22 06:54:06.596037: +2024-11-22 06:54:06.596265: Epoch 3708 +2024-11-22 06:54:06.596378: Current learning rate: 0.00571 +2024-11-22 06:54:26.337301: train_loss -0.762 +2024-11-22 06:54:26.339663: val_loss -0.7055 +2024-11-22 06:54:26.339798: Pseudo dice [0.8119] +2024-11-22 06:54:26.339913: Epoch time: 19.74 s +2024-11-22 06:54:27.410865: +2024-11-22 06:54:27.411098: Epoch 3709 +2024-11-22 06:54:27.411214: Current learning rate: 0.00571 +2024-11-22 06:54:46.065121: train_loss -0.7654 +2024-11-22 06:54:46.065424: val_loss -0.7159 +2024-11-22 06:54:46.065502: Pseudo dice [0.8178] +2024-11-22 06:54:46.065580: Epoch time: 18.66 s +2024-11-22 06:54:46.955303: +2024-11-22 06:54:46.955563: Epoch 3710 +2024-11-22 06:54:46.955679: Current learning rate: 0.00571 +2024-11-22 06:55:05.903290: train_loss -0.7762 +2024-11-22 06:55:05.903501: val_loss -0.7466 +2024-11-22 06:55:05.903577: Pseudo dice [0.8332] +2024-11-22 06:55:05.903657: Epoch time: 18.95 s +2024-11-22 06:55:06.791080: +2024-11-22 06:55:06.791272: Epoch 3711 +2024-11-22 06:55:06.791383: Current learning rate: 0.00571 +2024-11-22 06:55:25.256601: train_loss -0.7729 +2024-11-22 06:55:25.256837: val_loss -0.7365 +2024-11-22 06:55:25.256914: Pseudo dice [0.8188] +2024-11-22 06:55:25.257004: Epoch time: 18.47 s +2024-11-22 06:55:26.139609: +2024-11-22 06:55:26.139872: Epoch 3712 +2024-11-22 06:55:26.139986: Current learning rate: 0.0057 +2024-11-22 06:55:43.600668: train_loss -0.7879 +2024-11-22 06:55:43.600884: val_loss -0.735 +2024-11-22 06:55:43.600967: Pseudo dice [0.816] +2024-11-22 06:55:43.601047: Epoch time: 17.46 s +2024-11-22 06:55:44.754278: +2024-11-22 06:55:44.754496: Epoch 3713 +2024-11-22 06:55:44.754610: Current learning rate: 0.0057 +2024-11-22 06:56:03.055876: train_loss -0.7879 +2024-11-22 06:56:03.056094: val_loss -0.7398 +2024-11-22 06:56:03.056169: Pseudo dice [0.8276] +2024-11-22 06:56:03.056248: Epoch time: 18.3 s +2024-11-22 06:56:03.930977: +2024-11-22 06:56:03.931206: Epoch 3714 +2024-11-22 06:56:03.931319: Current learning rate: 0.0057 +2024-11-22 06:56:22.917342: train_loss -0.7808 +2024-11-22 06:56:22.917591: val_loss -0.7478 +2024-11-22 06:56:22.917666: Pseudo dice [0.8093] +2024-11-22 06:56:22.919964: Epoch time: 18.99 s +2024-11-22 06:56:23.904715: +2024-11-22 06:56:23.904965: Epoch 3715 +2024-11-22 06:56:23.905086: Current learning rate: 0.0057 +2024-11-22 06:56:43.389697: train_loss -0.7816 +2024-11-22 06:56:43.389909: val_loss -0.7114 +2024-11-22 06:56:43.390039: Pseudo dice [0.829] +2024-11-22 06:56:43.390142: Epoch time: 19.49 s +2024-11-22 06:56:44.276878: +2024-11-22 06:56:44.277075: Epoch 3716 +2024-11-22 06:56:44.277206: Current learning rate: 0.0057 +2024-11-22 06:57:03.512686: train_loss -0.7647 +2024-11-22 06:57:03.512894: val_loss -0.7268 +2024-11-22 06:57:03.512967: Pseudo dice [0.8318] +2024-11-22 06:57:03.513047: Epoch time: 19.24 s +2024-11-22 06:57:04.399463: +2024-11-22 06:57:04.399713: Epoch 3717 +2024-11-22 06:57:04.399833: Current learning rate: 0.0057 +2024-11-22 06:57:23.497673: train_loss -0.7629 +2024-11-22 06:57:23.497896: val_loss -0.7079 +2024-11-22 06:57:23.500205: Pseudo dice [0.8124] +2024-11-22 06:57:23.500311: Epoch time: 19.1 s +2024-11-22 06:57:24.385250: +2024-11-22 06:57:24.385445: Epoch 3718 +2024-11-22 06:57:24.385556: Current learning rate: 0.0057 +2024-11-22 06:57:42.807823: train_loss -0.7791 +2024-11-22 06:57:42.808065: val_loss -0.7568 +2024-11-22 06:57:42.808140: Pseudo dice [0.8338] +2024-11-22 06:57:42.808225: Epoch time: 18.42 s +2024-11-22 06:57:43.693898: +2024-11-22 06:57:43.694196: Epoch 3719 +2024-11-22 06:57:43.694311: Current learning rate: 0.0057 +2024-11-22 06:58:01.798355: train_loss -0.7737 +2024-11-22 06:58:01.798569: val_loss -0.744 +2024-11-22 06:58:01.798643: Pseudo dice [0.8173] +2024-11-22 06:58:01.817548: Epoch time: 18.11 s +2024-11-22 06:58:02.701104: +2024-11-22 06:58:02.701322: Epoch 3720 +2024-11-22 06:58:02.701445: Current learning rate: 0.0057 +2024-11-22 06:58:20.988428: train_loss -0.7828 +2024-11-22 06:58:20.988640: val_loss -0.7233 +2024-11-22 06:58:20.988714: Pseudo dice [0.8124] +2024-11-22 06:58:20.988791: Epoch time: 18.29 s +2024-11-22 06:58:21.931085: +2024-11-22 06:58:21.931286: Epoch 3721 +2024-11-22 06:58:21.931396: Current learning rate: 0.00569 +2024-11-22 06:58:39.967770: train_loss -0.7685 +2024-11-22 06:58:39.968047: val_loss -0.7369 +2024-11-22 06:58:39.968124: Pseudo dice [0.8325] +2024-11-22 06:58:39.968205: Epoch time: 18.04 s +2024-11-22 06:58:40.884546: +2024-11-22 06:58:40.884748: Epoch 3722 +2024-11-22 06:58:40.884863: Current learning rate: 0.00569 +2024-11-22 06:58:58.001193: train_loss -0.7814 +2024-11-22 06:58:58.001513: val_loss -0.7278 +2024-11-22 06:58:58.001591: Pseudo dice [0.7858] +2024-11-22 06:58:58.001680: Epoch time: 17.12 s +2024-11-22 06:58:58.992497: +2024-11-22 06:58:58.992723: Epoch 3723 +2024-11-22 06:58:58.992831: Current learning rate: 0.00569 +2024-11-22 06:59:17.193510: train_loss -0.7551 +2024-11-22 06:59:17.193726: val_loss -0.6914 +2024-11-22 06:59:17.193798: Pseudo dice [0.7938] +2024-11-22 06:59:17.193876: Epoch time: 18.2 s +2024-11-22 06:59:18.081365: +2024-11-22 06:59:18.081584: Epoch 3724 +2024-11-22 06:59:18.081698: Current learning rate: 0.00569 +2024-11-22 06:59:37.101420: train_loss -0.7535 +2024-11-22 06:59:37.101950: val_loss -0.7359 +2024-11-22 06:59:37.102062: Pseudo dice [0.822] +2024-11-22 06:59:37.102157: Epoch time: 19.02 s +2024-11-22 06:59:38.011289: +2024-11-22 06:59:38.011493: Epoch 3725 +2024-11-22 06:59:38.011610: Current learning rate: 0.00569 +2024-11-22 06:59:56.567653: train_loss -0.773 +2024-11-22 06:59:56.567869: val_loss -0.7575 +2024-11-22 06:59:56.567944: Pseudo dice [0.836] +2024-11-22 06:59:56.568027: Epoch time: 18.56 s +2024-11-22 06:59:57.451333: +2024-11-22 06:59:57.451531: Epoch 3726 +2024-11-22 06:59:57.451648: Current learning rate: 0.00569 +2024-11-22 07:00:15.898209: train_loss -0.7782 +2024-11-22 07:00:15.898426: val_loss -0.7234 +2024-11-22 07:00:15.898503: Pseudo dice [0.8142] +2024-11-22 07:00:15.898582: Epoch time: 18.45 s +2024-11-22 07:00:16.787504: +2024-11-22 07:00:16.787701: Epoch 3727 +2024-11-22 07:00:16.787817: Current learning rate: 0.00569 +2024-11-22 07:00:35.555126: train_loss -0.7638 +2024-11-22 07:00:35.555368: val_loss -0.7245 +2024-11-22 07:00:35.555450: Pseudo dice [0.8197] +2024-11-22 07:00:35.555534: Epoch time: 18.77 s +2024-11-22 07:00:36.455043: +2024-11-22 07:00:36.455254: Epoch 3728 +2024-11-22 07:00:36.455365: Current learning rate: 0.00569 +2024-11-22 07:00:55.387493: train_loss -0.7714 +2024-11-22 07:00:55.387713: val_loss -0.7652 +2024-11-22 07:00:55.387788: Pseudo dice [0.8195] +2024-11-22 07:00:55.387936: Epoch time: 18.93 s +2024-11-22 07:00:56.407169: +2024-11-22 07:00:56.407381: Epoch 3729 +2024-11-22 07:00:56.407497: Current learning rate: 0.00568 +2024-11-22 07:01:15.228885: train_loss -0.7687 +2024-11-22 07:01:15.229111: val_loss -0.7531 +2024-11-22 07:01:15.229186: Pseudo dice [0.829] +2024-11-22 07:01:15.229262: Epoch time: 18.82 s +2024-11-22 07:01:16.111761: +2024-11-22 07:01:16.111983: Epoch 3730 +2024-11-22 07:01:16.112107: Current learning rate: 0.00568 +2024-11-22 07:01:34.903727: train_loss -0.7755 +2024-11-22 07:01:34.903944: val_loss -0.7685 +2024-11-22 07:01:34.904028: Pseudo dice [0.8342] +2024-11-22 07:01:34.904103: Epoch time: 18.79 s +2024-11-22 07:01:35.789560: +2024-11-22 07:01:35.789787: Epoch 3731 +2024-11-22 07:01:35.789905: Current learning rate: 0.00568 +2024-11-22 07:01:54.836659: train_loss -0.7704 +2024-11-22 07:01:54.836935: val_loss -0.7268 +2024-11-22 07:01:54.837029: Pseudo dice [0.8167] +2024-11-22 07:01:54.837113: Epoch time: 19.05 s +2024-11-22 07:01:55.721949: +2024-11-22 07:01:55.722179: Epoch 3732 +2024-11-22 07:01:55.722296: Current learning rate: 0.00568 +2024-11-22 07:02:14.206754: train_loss -0.7845 +2024-11-22 07:02:14.233513: val_loss -0.7498 +2024-11-22 07:02:14.233667: Pseudo dice [0.8135] +2024-11-22 07:02:14.233762: Epoch time: 18.49 s +2024-11-22 07:02:15.118110: +2024-11-22 07:02:15.118296: Epoch 3733 +2024-11-22 07:02:15.118411: Current learning rate: 0.00568 +2024-11-22 07:02:33.501259: train_loss -0.7752 +2024-11-22 07:02:33.503640: val_loss -0.725 +2024-11-22 07:02:33.503731: Pseudo dice [0.8185] +2024-11-22 07:02:33.503808: Epoch time: 18.38 s +2024-11-22 07:02:34.437208: +2024-11-22 07:02:34.437414: Epoch 3734 +2024-11-22 07:02:34.437525: Current learning rate: 0.00568 +2024-11-22 07:02:53.271770: train_loss -0.7756 +2024-11-22 07:02:53.271982: val_loss -0.7258 +2024-11-22 07:02:53.272066: Pseudo dice [0.8172] +2024-11-22 07:02:53.272143: Epoch time: 18.84 s +2024-11-22 07:02:54.149419: +2024-11-22 07:02:54.149607: Epoch 3735 +2024-11-22 07:02:54.149723: Current learning rate: 0.00568 +2024-11-22 07:03:13.008629: train_loss -0.7828 +2024-11-22 07:03:13.011065: val_loss -0.748 +2024-11-22 07:03:13.011156: Pseudo dice [0.8298] +2024-11-22 07:03:13.011247: Epoch time: 18.86 s +2024-11-22 07:03:14.359890: +2024-11-22 07:03:14.360095: Epoch 3736 +2024-11-22 07:03:14.360206: Current learning rate: 0.00568 +2024-11-22 07:03:33.128630: train_loss -0.7835 +2024-11-22 07:03:33.128871: val_loss -0.7739 +2024-11-22 07:03:33.128945: Pseudo dice [0.8295] +2024-11-22 07:03:33.129025: Epoch time: 18.77 s +2024-11-22 07:03:34.012558: +2024-11-22 07:03:34.012793: Epoch 3737 +2024-11-22 07:03:34.012905: Current learning rate: 0.00567 +2024-11-22 07:03:52.453985: train_loss -0.7768 +2024-11-22 07:03:52.459421: val_loss -0.7464 +2024-11-22 07:03:52.459555: Pseudo dice [0.8307] +2024-11-22 07:03:52.459636: Epoch time: 18.44 s +2024-11-22 07:03:53.351595: +2024-11-22 07:03:53.351871: Epoch 3738 +2024-11-22 07:03:53.351983: Current learning rate: 0.00567 +2024-11-22 07:04:12.995808: train_loss -0.7833 +2024-11-22 07:04:12.996066: val_loss -0.7227 +2024-11-22 07:04:12.996142: Pseudo dice [0.8108] +2024-11-22 07:04:12.996230: Epoch time: 19.64 s +2024-11-22 07:04:13.883443: +2024-11-22 07:04:13.883730: Epoch 3739 +2024-11-22 07:04:13.883843: Current learning rate: 0.00567 +2024-11-22 07:04:32.591140: train_loss -0.7696 +2024-11-22 07:04:32.596534: val_loss -0.7477 +2024-11-22 07:04:32.596653: Pseudo dice [0.8265] +2024-11-22 07:04:32.596732: Epoch time: 18.71 s +2024-11-22 07:04:33.737385: +2024-11-22 07:04:33.737623: Epoch 3740 +2024-11-22 07:04:33.737736: Current learning rate: 0.00567 +2024-11-22 07:04:52.007629: train_loss -0.7798 +2024-11-22 07:04:52.009445: val_loss -0.7443 +2024-11-22 07:04:52.009549: Pseudo dice [0.843] +2024-11-22 07:04:52.009628: Epoch time: 18.27 s +2024-11-22 07:04:52.908783: +2024-11-22 07:04:52.908995: Epoch 3741 +2024-11-22 07:04:52.909111: Current learning rate: 0.00567 +2024-11-22 07:05:11.424471: train_loss -0.7727 +2024-11-22 07:05:11.424763: val_loss -0.7602 +2024-11-22 07:05:11.424843: Pseudo dice [0.8117] +2024-11-22 07:05:11.424920: Epoch time: 18.52 s +2024-11-22 07:05:12.331260: +2024-11-22 07:05:12.331455: Epoch 3742 +2024-11-22 07:05:12.331566: Current learning rate: 0.00567 +2024-11-22 07:05:29.736045: train_loss -0.7837 +2024-11-22 07:05:29.736335: val_loss -0.7469 +2024-11-22 07:05:29.736413: Pseudo dice [0.8181] +2024-11-22 07:05:29.736502: Epoch time: 17.41 s +2024-11-22 07:05:30.729685: +2024-11-22 07:05:30.730016: Epoch 3743 +2024-11-22 07:05:30.730131: Current learning rate: 0.00567 +2024-11-22 07:05:50.890307: train_loss -0.7887 +2024-11-22 07:05:50.890532: val_loss -0.7506 +2024-11-22 07:05:50.890606: Pseudo dice [0.8173] +2024-11-22 07:05:50.890685: Epoch time: 20.16 s +2024-11-22 07:05:51.779847: +2024-11-22 07:05:51.780188: Epoch 3744 +2024-11-22 07:05:51.780298: Current learning rate: 0.00567 +2024-11-22 07:06:10.984892: train_loss -0.7888 +2024-11-22 07:06:10.985132: val_loss -0.7464 +2024-11-22 07:06:10.985226: Pseudo dice [0.8068] +2024-11-22 07:06:10.985475: Epoch time: 19.21 s +2024-11-22 07:06:11.870129: +2024-11-22 07:06:11.870350: Epoch 3745 +2024-11-22 07:06:11.870465: Current learning rate: 0.00567 +2024-11-22 07:06:31.341964: train_loss -0.7933 +2024-11-22 07:06:31.342196: val_loss -0.7473 +2024-11-22 07:06:31.342276: Pseudo dice [0.8406] +2024-11-22 07:06:31.342357: Epoch time: 19.47 s +2024-11-22 07:06:32.226204: +2024-11-22 07:06:32.226396: Epoch 3746 +2024-11-22 07:06:32.226503: Current learning rate: 0.00566 +2024-11-22 07:06:51.393253: train_loss -0.7911 +2024-11-22 07:06:51.393525: val_loss -0.7602 +2024-11-22 07:06:51.393663: Pseudo dice [0.8436] +2024-11-22 07:06:51.393746: Epoch time: 19.17 s +2024-11-22 07:06:52.279629: +2024-11-22 07:06:52.280053: Epoch 3747 +2024-11-22 07:06:52.280191: Current learning rate: 0.00566 +2024-11-22 07:07:10.790397: train_loss -0.7799 +2024-11-22 07:07:10.790890: val_loss -0.7267 +2024-11-22 07:07:10.790997: Pseudo dice [0.825] +2024-11-22 07:07:10.791076: Epoch time: 18.51 s +2024-11-22 07:07:11.735220: +2024-11-22 07:07:11.735435: Epoch 3748 +2024-11-22 07:07:11.735553: Current learning rate: 0.00566 +2024-11-22 07:07:29.969879: train_loss -0.7738 +2024-11-22 07:07:29.970141: val_loss -0.7526 +2024-11-22 07:07:29.970217: Pseudo dice [0.8354] +2024-11-22 07:07:29.970305: Epoch time: 18.24 s +2024-11-22 07:07:30.973495: +2024-11-22 07:07:30.973787: Epoch 3749 +2024-11-22 07:07:30.973900: Current learning rate: 0.00566 +2024-11-22 07:07:49.106116: train_loss -0.7847 +2024-11-22 07:07:49.106338: val_loss -0.7624 +2024-11-22 07:07:49.106414: Pseudo dice [0.8487] +2024-11-22 07:07:49.106493: Epoch time: 18.13 s +2024-11-22 07:07:50.241702: +2024-11-22 07:07:50.241910: Epoch 3750 +2024-11-22 07:07:50.242032: Current learning rate: 0.00566 +2024-11-22 07:08:09.320216: train_loss -0.7867 +2024-11-22 07:08:09.322606: val_loss -0.7641 +2024-11-22 07:08:09.322701: Pseudo dice [0.8325] +2024-11-22 07:08:09.322780: Epoch time: 19.08 s +2024-11-22 07:08:10.283987: +2024-11-22 07:08:10.284201: Epoch 3751 +2024-11-22 07:08:10.284317: Current learning rate: 0.00566 +2024-11-22 07:08:28.062961: train_loss -0.7886 +2024-11-22 07:08:28.067863: val_loss -0.7664 +2024-11-22 07:08:28.067957: Pseudo dice [0.8266] +2024-11-22 07:08:28.068053: Epoch time: 17.78 s +2024-11-22 07:08:29.096730: +2024-11-22 07:08:29.096938: Epoch 3752 +2024-11-22 07:08:29.097057: Current learning rate: 0.00566 +2024-11-22 07:08:47.410557: train_loss -0.7852 +2024-11-22 07:08:47.410776: val_loss -0.7466 +2024-11-22 07:08:47.413058: Pseudo dice [0.8202] +2024-11-22 07:08:47.413152: Epoch time: 18.31 s +2024-11-22 07:08:48.370107: +2024-11-22 07:08:48.370315: Epoch 3753 +2024-11-22 07:08:48.370433: Current learning rate: 0.00566 +2024-11-22 07:09:08.483777: train_loss -0.7881 +2024-11-22 07:09:08.484017: val_loss -0.7622 +2024-11-22 07:09:08.484094: Pseudo dice [0.8243] +2024-11-22 07:09:08.484175: Epoch time: 20.11 s +2024-11-22 07:09:09.368633: +2024-11-22 07:09:09.368841: Epoch 3754 +2024-11-22 07:09:09.368959: Current learning rate: 0.00565 +2024-11-22 07:09:28.756410: train_loss -0.7885 +2024-11-22 07:09:28.756623: val_loss -0.7229 +2024-11-22 07:09:28.756731: Pseudo dice [0.8149] +2024-11-22 07:09:28.756811: Epoch time: 19.39 s +2024-11-22 07:09:29.640831: +2024-11-22 07:09:29.641044: Epoch 3755 +2024-11-22 07:09:29.641159: Current learning rate: 0.00565 +2024-11-22 07:09:48.506466: train_loss -0.7801 +2024-11-22 07:09:48.506707: val_loss -0.7406 +2024-11-22 07:09:48.506781: Pseudo dice [0.8202] +2024-11-22 07:09:48.506867: Epoch time: 18.87 s +2024-11-22 07:09:49.435633: +2024-11-22 07:09:49.435838: Epoch 3756 +2024-11-22 07:09:49.435950: Current learning rate: 0.00565 +2024-11-22 07:10:07.496019: train_loss -0.7938 +2024-11-22 07:10:07.496246: val_loss -0.7483 +2024-11-22 07:10:07.496322: Pseudo dice [0.8241] +2024-11-22 07:10:07.496399: Epoch time: 18.06 s +2024-11-22 07:10:08.490927: +2024-11-22 07:10:08.491149: Epoch 3757 +2024-11-22 07:10:08.491265: Current learning rate: 0.00565 +2024-11-22 07:10:26.807714: train_loss -0.7943 +2024-11-22 07:10:26.808003: val_loss -0.712 +2024-11-22 07:10:26.808084: Pseudo dice [0.8346] +2024-11-22 07:10:26.808165: Epoch time: 18.32 s +2024-11-22 07:10:27.697754: +2024-11-22 07:10:27.697948: Epoch 3758 +2024-11-22 07:10:27.698074: Current learning rate: 0.00565 +2024-11-22 07:10:47.091111: train_loss -0.787 +2024-11-22 07:10:47.091785: val_loss -0.7644 +2024-11-22 07:10:47.091888: Pseudo dice [0.843] +2024-11-22 07:10:47.091978: Epoch time: 19.39 s +2024-11-22 07:10:47.982211: +2024-11-22 07:10:47.982418: Epoch 3759 +2024-11-22 07:10:47.982527: Current learning rate: 0.00565 +2024-11-22 07:11:06.109005: train_loss -0.7824 +2024-11-22 07:11:06.109223: val_loss -0.7465 +2024-11-22 07:11:06.109296: Pseudo dice [0.8329] +2024-11-22 07:11:06.109371: Epoch time: 18.13 s +2024-11-22 07:11:07.043157: +2024-11-22 07:11:07.043401: Epoch 3760 +2024-11-22 07:11:07.043516: Current learning rate: 0.00565 +2024-11-22 07:11:25.576097: train_loss -0.7919 +2024-11-22 07:11:25.576331: val_loss -0.7697 +2024-11-22 07:11:25.576406: Pseudo dice [0.8457] +2024-11-22 07:11:25.576483: Epoch time: 18.53 s +2024-11-22 07:11:26.455249: +2024-11-22 07:11:26.455482: Epoch 3761 +2024-11-22 07:11:26.455595: Current learning rate: 0.00565 +2024-11-22 07:11:44.754334: train_loss -0.7914 +2024-11-22 07:11:44.754570: val_loss -0.772 +2024-11-22 07:11:44.754741: Pseudo dice [0.8441] +2024-11-22 07:11:44.754829: Epoch time: 18.3 s +2024-11-22 07:11:44.754896: Yayy! New best EMA pseudo Dice: 0.8315 +2024-11-22 07:11:45.888574: +2024-11-22 07:11:45.888795: Epoch 3762 +2024-11-22 07:11:45.888909: Current learning rate: 0.00564 +2024-11-22 07:12:04.609166: train_loss -0.7906 +2024-11-22 07:12:04.609380: val_loss -0.7302 +2024-11-22 07:12:04.609459: Pseudo dice [0.8281] +2024-11-22 07:12:04.609535: Epoch time: 18.72 s +2024-11-22 07:12:05.497964: +2024-11-22 07:12:05.498271: Epoch 3763 +2024-11-22 07:12:05.498385: Current learning rate: 0.00564 +2024-11-22 07:12:24.370850: train_loss -0.7867 +2024-11-22 07:12:24.371070: val_loss -0.7593 +2024-11-22 07:12:24.371147: Pseudo dice [0.8175] +2024-11-22 07:12:24.371232: Epoch time: 18.87 s +2024-11-22 07:12:25.358667: +2024-11-22 07:12:25.358880: Epoch 3764 +2024-11-22 07:12:25.359004: Current learning rate: 0.00564 +2024-11-22 07:12:43.534183: train_loss -0.7847 +2024-11-22 07:12:43.535720: val_loss -0.7463 +2024-11-22 07:12:43.535827: Pseudo dice [0.8157] +2024-11-22 07:12:43.535903: Epoch time: 18.18 s +2024-11-22 07:12:44.429548: +2024-11-22 07:12:44.429759: Epoch 3765 +2024-11-22 07:12:44.429874: Current learning rate: 0.00564 +2024-11-22 07:13:03.500072: train_loss -0.7795 +2024-11-22 07:13:03.500321: val_loss -0.7383 +2024-11-22 07:13:03.500400: Pseudo dice [0.8084] +2024-11-22 07:13:03.500485: Epoch time: 19.07 s +2024-11-22 07:13:04.381463: +2024-11-22 07:13:04.381661: Epoch 3766 +2024-11-22 07:13:04.381769: Current learning rate: 0.00564 +2024-11-22 07:13:24.350375: train_loss -0.7893 +2024-11-22 07:13:24.350592: val_loss -0.7574 +2024-11-22 07:13:24.350664: Pseudo dice [0.841] +2024-11-22 07:13:24.350740: Epoch time: 19.97 s +2024-11-22 07:13:25.269871: +2024-11-22 07:13:25.270082: Epoch 3767 +2024-11-22 07:13:25.270199: Current learning rate: 0.00564 +2024-11-22 07:13:44.728371: train_loss -0.7877 +2024-11-22 07:13:44.728584: val_loss -0.7298 +2024-11-22 07:13:44.728769: Pseudo dice [0.8255] +2024-11-22 07:13:44.728850: Epoch time: 19.46 s +2024-11-22 07:13:45.610412: +2024-11-22 07:13:45.610605: Epoch 3768 +2024-11-22 07:13:45.610725: Current learning rate: 0.00564 +2024-11-22 07:14:03.987375: train_loss -0.7822 +2024-11-22 07:14:03.987674: val_loss -0.7675 +2024-11-22 07:14:03.987884: Pseudo dice [0.8328] +2024-11-22 07:14:03.987969: Epoch time: 18.38 s +2024-11-22 07:14:05.031965: +2024-11-22 07:14:05.032159: Epoch 3769 +2024-11-22 07:14:05.032270: Current learning rate: 0.00564 +2024-11-22 07:14:23.288752: train_loss -0.7931 +2024-11-22 07:14:23.289310: val_loss -0.7566 +2024-11-22 07:14:23.289421: Pseudo dice [0.8245] +2024-11-22 07:14:23.289506: Epoch time: 18.26 s +2024-11-22 07:14:24.171856: +2024-11-22 07:14:24.172096: Epoch 3770 +2024-11-22 07:14:24.172207: Current learning rate: 0.00564 +2024-11-22 07:14:43.540174: train_loss -0.7942 +2024-11-22 07:14:43.540426: val_loss -0.7502 +2024-11-22 07:14:43.540502: Pseudo dice [0.8239] +2024-11-22 07:14:43.540580: Epoch time: 19.37 s +2024-11-22 07:14:44.421577: +2024-11-22 07:14:44.421819: Epoch 3771 +2024-11-22 07:14:44.421931: Current learning rate: 0.00563 +2024-11-22 07:15:02.825897: train_loss -0.7925 +2024-11-22 07:15:02.826159: val_loss -0.7688 +2024-11-22 07:15:02.826235: Pseudo dice [0.8419] +2024-11-22 07:15:02.826324: Epoch time: 18.41 s +2024-11-22 07:15:03.713347: +2024-11-22 07:15:03.713571: Epoch 3772 +2024-11-22 07:15:03.713681: Current learning rate: 0.00563 +2024-11-22 07:15:23.228681: train_loss -0.7948 +2024-11-22 07:15:23.228907: val_loss -0.7562 +2024-11-22 07:15:23.228983: Pseudo dice [0.8311] +2024-11-22 07:15:23.229083: Epoch time: 19.52 s +2024-11-22 07:15:24.113549: +2024-11-22 07:15:24.113749: Epoch 3773 +2024-11-22 07:15:24.113856: Current learning rate: 0.00563 +2024-11-22 07:15:43.122116: train_loss -0.7882 +2024-11-22 07:15:43.122337: val_loss -0.7571 +2024-11-22 07:15:43.122417: Pseudo dice [0.8386] +2024-11-22 07:15:43.124710: Epoch time: 19.01 s +2024-11-22 07:15:44.262545: +2024-11-22 07:15:44.262753: Epoch 3774 +2024-11-22 07:15:44.262861: Current learning rate: 0.00563 +2024-11-22 07:16:05.050265: train_loss -0.7834 +2024-11-22 07:16:05.050501: val_loss -0.7419 +2024-11-22 07:16:05.050578: Pseudo dice [0.8112] +2024-11-22 07:16:05.050655: Epoch time: 20.79 s +2024-11-22 07:16:06.011043: +2024-11-22 07:16:06.011257: Epoch 3775 +2024-11-22 07:16:06.011375: Current learning rate: 0.00563 +2024-11-22 07:16:25.671911: train_loss -0.7909 +2024-11-22 07:16:25.672173: val_loss -0.7345 +2024-11-22 07:16:25.672249: Pseudo dice [0.8226] +2024-11-22 07:16:25.672332: Epoch time: 19.66 s +2024-11-22 07:16:26.637432: +2024-11-22 07:16:26.637715: Epoch 3776 +2024-11-22 07:16:26.637829: Current learning rate: 0.00563 +2024-11-22 07:16:45.091058: train_loss -0.7968 +2024-11-22 07:16:45.091279: val_loss -0.7273 +2024-11-22 07:16:45.091407: Pseudo dice [0.8232] +2024-11-22 07:16:45.091491: Epoch time: 18.45 s +2024-11-22 07:16:45.969721: +2024-11-22 07:16:45.969937: Epoch 3777 +2024-11-22 07:16:45.970052: Current learning rate: 0.00563 +2024-11-22 07:17:05.077619: train_loss -0.7833 +2024-11-22 07:17:05.077847: val_loss -0.7335 +2024-11-22 07:17:05.077926: Pseudo dice [0.8202] +2024-11-22 07:17:05.078013: Epoch time: 19.11 s +2024-11-22 07:17:05.961696: +2024-11-22 07:17:05.961954: Epoch 3778 +2024-11-22 07:17:05.962072: Current learning rate: 0.00563 +2024-11-22 07:17:25.126177: train_loss -0.7941 +2024-11-22 07:17:25.126388: val_loss -0.7334 +2024-11-22 07:17:25.126495: Pseudo dice [0.8137] +2024-11-22 07:17:25.126580: Epoch time: 19.17 s +2024-11-22 07:17:26.013378: +2024-11-22 07:17:26.013602: Epoch 3779 +2024-11-22 07:17:26.013716: Current learning rate: 0.00562 +2024-11-22 07:17:45.223193: train_loss -0.7922 +2024-11-22 07:17:45.223431: val_loss -0.7633 +2024-11-22 07:17:45.223504: Pseudo dice [0.8281] +2024-11-22 07:17:45.223586: Epoch time: 19.21 s +2024-11-22 07:17:46.105849: +2024-11-22 07:17:46.106073: Epoch 3780 +2024-11-22 07:17:46.106187: Current learning rate: 0.00562 +2024-11-22 07:18:04.905608: train_loss -0.7834 +2024-11-22 07:18:04.911023: val_loss -0.7657 +2024-11-22 07:18:04.911148: Pseudo dice [0.8292] +2024-11-22 07:18:04.911231: Epoch time: 18.8 s +2024-11-22 07:18:06.317549: +2024-11-22 07:18:06.317761: Epoch 3781 +2024-11-22 07:18:06.317874: Current learning rate: 0.00562 +2024-11-22 07:18:25.600492: train_loss -0.7891 +2024-11-22 07:18:25.601199: val_loss -0.7322 +2024-11-22 07:18:25.601278: Pseudo dice [0.8324] +2024-11-22 07:18:25.601373: Epoch time: 19.28 s +2024-11-22 07:18:26.597162: +2024-11-22 07:18:26.597393: Epoch 3782 +2024-11-22 07:18:26.597504: Current learning rate: 0.00562 +2024-11-22 07:18:45.794885: train_loss -0.7781 +2024-11-22 07:18:45.795125: val_loss -0.7429 +2024-11-22 07:18:45.795201: Pseudo dice [0.818] +2024-11-22 07:18:45.795310: Epoch time: 19.2 s +2024-11-22 07:18:46.684427: +2024-11-22 07:18:46.684836: Epoch 3783 +2024-11-22 07:18:46.684950: Current learning rate: 0.00562 +2024-11-22 07:19:05.245055: train_loss -0.7758 +2024-11-22 07:19:05.245270: val_loss -0.7478 +2024-11-22 07:19:05.245346: Pseudo dice [0.791] +2024-11-22 07:19:05.245425: Epoch time: 18.56 s +2024-11-22 07:19:06.136550: +2024-11-22 07:19:06.136900: Epoch 3784 +2024-11-22 07:19:06.137021: Current learning rate: 0.00562 +2024-11-22 07:19:24.427443: train_loss -0.7842 +2024-11-22 07:19:24.427691: val_loss -0.7399 +2024-11-22 07:19:24.427768: Pseudo dice [0.8197] +2024-11-22 07:19:24.427843: Epoch time: 18.29 s +2024-11-22 07:19:25.310889: +2024-11-22 07:19:25.311095: Epoch 3785 +2024-11-22 07:19:25.311224: Current learning rate: 0.00562 +2024-11-22 07:19:43.841326: train_loss -0.7834 +2024-11-22 07:19:43.841570: val_loss -0.7137 +2024-11-22 07:19:43.841644: Pseudo dice [0.8005] +2024-11-22 07:19:43.841731: Epoch time: 18.53 s +2024-11-22 07:19:44.733250: +2024-11-22 07:19:44.733446: Epoch 3786 +2024-11-22 07:19:44.733556: Current learning rate: 0.00562 +2024-11-22 07:20:02.662554: train_loss -0.7835 +2024-11-22 07:20:02.662794: val_loss -0.7374 +2024-11-22 07:20:02.662869: Pseudo dice [0.8168] +2024-11-22 07:20:02.662946: Epoch time: 17.93 s +2024-11-22 07:20:03.549051: +2024-11-22 07:20:03.549332: Epoch 3787 +2024-11-22 07:20:03.549441: Current learning rate: 0.00562 +2024-11-22 07:20:22.317785: train_loss -0.7818 +2024-11-22 07:20:22.318017: val_loss -0.7404 +2024-11-22 07:20:22.318092: Pseudo dice [0.8112] +2024-11-22 07:20:22.318168: Epoch time: 18.77 s +2024-11-22 07:20:23.242413: +2024-11-22 07:20:23.242624: Epoch 3788 +2024-11-22 07:20:23.242738: Current learning rate: 0.00561 +2024-11-22 07:20:40.654707: train_loss -0.7898 +2024-11-22 07:20:40.654928: val_loss -0.7387 +2024-11-22 07:20:40.655016: Pseudo dice [0.8339] +2024-11-22 07:20:40.655104: Epoch time: 17.41 s +2024-11-22 07:20:41.546451: +2024-11-22 07:20:41.546721: Epoch 3789 +2024-11-22 07:20:41.546834: Current learning rate: 0.00561 +2024-11-22 07:20:59.735909: train_loss -0.7878 +2024-11-22 07:20:59.736161: val_loss -0.7598 +2024-11-22 07:20:59.736243: Pseudo dice [0.8353] +2024-11-22 07:20:59.736324: Epoch time: 18.19 s +2024-11-22 07:21:00.617439: +2024-11-22 07:21:00.617632: Epoch 3790 +2024-11-22 07:21:00.617742: Current learning rate: 0.00561 +2024-11-22 07:21:19.255587: train_loss -0.7803 +2024-11-22 07:21:19.255814: val_loss -0.7186 +2024-11-22 07:21:19.255889: Pseudo dice [0.8337] +2024-11-22 07:21:19.255966: Epoch time: 18.64 s +2024-11-22 07:21:20.144814: +2024-11-22 07:21:20.145024: Epoch 3791 +2024-11-22 07:21:20.145136: Current learning rate: 0.00561 +2024-11-22 07:21:38.528811: train_loss -0.7865 +2024-11-22 07:21:38.529063: val_loss -0.7706 +2024-11-22 07:21:38.529141: Pseudo dice [0.817] +2024-11-22 07:21:38.529220: Epoch time: 18.38 s +2024-11-22 07:21:39.428338: +2024-11-22 07:21:39.428608: Epoch 3792 +2024-11-22 07:21:39.428718: Current learning rate: 0.00561 +2024-11-22 07:21:57.377156: train_loss -0.7941 +2024-11-22 07:21:57.377687: val_loss -0.76 +2024-11-22 07:21:57.377786: Pseudo dice [0.8365] +2024-11-22 07:21:57.377872: Epoch time: 17.95 s +2024-11-22 07:21:58.261511: +2024-11-22 07:21:58.261742: Epoch 3793 +2024-11-22 07:21:58.261863: Current learning rate: 0.00561 +2024-11-22 07:22:16.328009: train_loss -0.7856 +2024-11-22 07:22:16.328216: val_loss -0.7426 +2024-11-22 07:22:16.328289: Pseudo dice [0.8345] +2024-11-22 07:22:16.328365: Epoch time: 18.07 s +2024-11-22 07:22:17.210581: +2024-11-22 07:22:17.210808: Epoch 3794 +2024-11-22 07:22:17.210935: Current learning rate: 0.00561 +2024-11-22 07:22:35.330811: train_loss -0.789 +2024-11-22 07:22:35.331146: val_loss -0.7496 +2024-11-22 07:22:35.331243: Pseudo dice [0.8236] +2024-11-22 07:22:35.331324: Epoch time: 18.12 s +2024-11-22 07:22:36.221688: +2024-11-22 07:22:36.221875: Epoch 3795 +2024-11-22 07:22:36.221982: Current learning rate: 0.00561 +2024-11-22 07:22:54.690362: train_loss -0.7874 +2024-11-22 07:22:54.690612: val_loss -0.7311 +2024-11-22 07:22:54.690686: Pseudo dice [0.819] +2024-11-22 07:22:54.691454: Epoch time: 18.47 s +2024-11-22 07:22:55.710075: +2024-11-22 07:22:55.710287: Epoch 3796 +2024-11-22 07:22:55.710400: Current learning rate: 0.0056 +2024-11-22 07:23:14.241227: train_loss -0.7765 +2024-11-22 07:23:14.241447: val_loss -0.7457 +2024-11-22 07:23:14.241525: Pseudo dice [0.8174] +2024-11-22 07:23:14.241601: Epoch time: 18.53 s +2024-11-22 07:23:15.126223: +2024-11-22 07:23:15.126475: Epoch 3797 +2024-11-22 07:23:15.126591: Current learning rate: 0.0056 +2024-11-22 07:23:34.141330: train_loss -0.7812 +2024-11-22 07:23:34.141547: val_loss -0.7383 +2024-11-22 07:23:34.141623: Pseudo dice [0.8293] +2024-11-22 07:23:34.141701: Epoch time: 19.02 s +2024-11-22 07:23:35.053723: +2024-11-22 07:23:35.053919: Epoch 3798 +2024-11-22 07:23:35.054037: Current learning rate: 0.0056 +2024-11-22 07:23:53.708970: train_loss -0.7932 +2024-11-22 07:23:53.709191: val_loss -0.734 +2024-11-22 07:23:53.709266: Pseudo dice [0.8166] +2024-11-22 07:23:53.709341: Epoch time: 18.66 s +2024-11-22 07:23:54.592097: +2024-11-22 07:23:54.592310: Epoch 3799 +2024-11-22 07:23:54.592425: Current learning rate: 0.0056 +2024-11-22 07:24:14.167681: train_loss -0.7934 +2024-11-22 07:24:14.170113: val_loss -0.7664 +2024-11-22 07:24:14.170201: Pseudo dice [0.8491] +2024-11-22 07:24:14.170293: Epoch time: 19.58 s +2024-11-22 07:24:15.375627: +2024-11-22 07:24:15.375840: Epoch 3800 +2024-11-22 07:24:15.375953: Current learning rate: 0.0056 +2024-11-22 07:24:34.626402: train_loss -0.7938 +2024-11-22 07:24:34.631793: val_loss -0.7534 +2024-11-22 07:24:34.631908: Pseudo dice [0.83] +2024-11-22 07:24:34.631989: Epoch time: 19.25 s +2024-11-22 07:24:35.670240: +2024-11-22 07:24:35.670581: Epoch 3801 +2024-11-22 07:24:35.670695: Current learning rate: 0.0056 +2024-11-22 07:24:54.179087: train_loss -0.7813 +2024-11-22 07:24:54.179306: val_loss -0.738 +2024-11-22 07:24:54.179380: Pseudo dice [0.8148] +2024-11-22 07:24:54.179456: Epoch time: 18.51 s +2024-11-22 07:24:55.063586: +2024-11-22 07:24:55.063852: Epoch 3802 +2024-11-22 07:24:55.063966: Current learning rate: 0.0056 +2024-11-22 07:25:13.922045: train_loss -0.7802 +2024-11-22 07:25:13.922335: val_loss -0.7487 +2024-11-22 07:25:13.922423: Pseudo dice [0.831] +2024-11-22 07:25:13.922506: Epoch time: 18.86 s +2024-11-22 07:25:14.811428: +2024-11-22 07:25:14.811636: Epoch 3803 +2024-11-22 07:25:14.811749: Current learning rate: 0.0056 +2024-11-22 07:25:32.835007: train_loss -0.792 +2024-11-22 07:25:32.835243: val_loss -0.7431 +2024-11-22 07:25:32.835324: Pseudo dice [0.7967] +2024-11-22 07:25:32.835401: Epoch time: 18.02 s +2024-11-22 07:25:33.722327: +2024-11-22 07:25:33.722543: Epoch 3804 +2024-11-22 07:25:33.722655: Current learning rate: 0.00559 +2024-11-22 07:25:53.271879: train_loss -0.7828 +2024-11-22 07:25:53.272105: val_loss -0.7528 +2024-11-22 07:25:53.272181: Pseudo dice [0.8344] +2024-11-22 07:25:53.272257: Epoch time: 19.55 s +2024-11-22 07:25:54.155456: +2024-11-22 07:25:54.155674: Epoch 3805 +2024-11-22 07:25:54.155784: Current learning rate: 0.00559 +2024-11-22 07:26:11.581494: train_loss -0.7932 +2024-11-22 07:26:11.581710: val_loss -0.7597 +2024-11-22 07:26:11.581781: Pseudo dice [0.835] +2024-11-22 07:26:11.581858: Epoch time: 17.43 s +2024-11-22 07:26:12.489234: +2024-11-22 07:26:12.489462: Epoch 3806 +2024-11-22 07:26:12.489575: Current learning rate: 0.00559 +2024-11-22 07:26:31.694347: train_loss -0.7857 +2024-11-22 07:26:31.694598: val_loss -0.7246 +2024-11-22 07:26:31.694673: Pseudo dice [0.8327] +2024-11-22 07:26:31.694755: Epoch time: 19.21 s +2024-11-22 07:26:32.604532: +2024-11-22 07:26:32.604731: Epoch 3807 +2024-11-22 07:26:32.604839: Current learning rate: 0.00559 +2024-11-22 07:26:50.749578: train_loss -0.7848 +2024-11-22 07:26:50.749792: val_loss -0.7214 +2024-11-22 07:26:50.749865: Pseudo dice [0.8025] +2024-11-22 07:26:50.749942: Epoch time: 18.15 s +2024-11-22 07:26:51.638096: +2024-11-22 07:26:51.638326: Epoch 3808 +2024-11-22 07:26:51.638443: Current learning rate: 0.00559 +2024-11-22 07:27:10.778150: train_loss -0.783 +2024-11-22 07:27:10.778618: val_loss -0.7562 +2024-11-22 07:27:10.778700: Pseudo dice [0.8384] +2024-11-22 07:27:10.778868: Epoch time: 19.14 s +2024-11-22 07:27:11.661324: +2024-11-22 07:27:11.661529: Epoch 3809 +2024-11-22 07:27:11.661641: Current learning rate: 0.00559 +2024-11-22 07:27:30.919594: train_loss -0.7837 +2024-11-22 07:27:30.919811: val_loss -0.7307 +2024-11-22 07:27:30.919887: Pseudo dice [0.8245] +2024-11-22 07:27:30.919969: Epoch time: 19.26 s +2024-11-22 07:27:31.806656: +2024-11-22 07:27:31.806884: Epoch 3810 +2024-11-22 07:27:31.807004: Current learning rate: 0.00559 +2024-11-22 07:27:50.684782: train_loss -0.7747 +2024-11-22 07:27:50.685039: val_loss -0.7197 +2024-11-22 07:27:50.685182: Pseudo dice [0.8097] +2024-11-22 07:27:50.685271: Epoch time: 18.88 s +2024-11-22 07:27:51.584382: +2024-11-22 07:27:51.584597: Epoch 3811 +2024-11-22 07:27:51.584703: Current learning rate: 0.00559 +2024-11-22 07:28:09.501337: train_loss -0.7869 +2024-11-22 07:28:09.501562: val_loss -0.7531 +2024-11-22 07:28:09.501649: Pseudo dice [0.8345] +2024-11-22 07:28:09.501732: Epoch time: 17.92 s +2024-11-22 07:28:10.490330: +2024-11-22 07:28:10.490551: Epoch 3812 +2024-11-22 07:28:10.490669: Current learning rate: 0.00559 +2024-11-22 07:28:28.970373: train_loss -0.7808 +2024-11-22 07:28:28.970594: val_loss -0.7631 +2024-11-22 07:28:28.970729: Pseudo dice [0.8383] +2024-11-22 07:28:28.970807: Epoch time: 18.48 s +2024-11-22 07:28:29.859987: +2024-11-22 07:28:29.860195: Epoch 3813 +2024-11-22 07:28:29.860304: Current learning rate: 0.00558 +2024-11-22 07:28:47.405921: train_loss -0.7899 +2024-11-22 07:28:47.406200: val_loss -0.7745 +2024-11-22 07:28:47.406278: Pseudo dice [0.8313] +2024-11-22 07:28:47.406364: Epoch time: 17.55 s +2024-11-22 07:28:48.523538: +2024-11-22 07:28:48.523740: Epoch 3814 +2024-11-22 07:28:48.523858: Current learning rate: 0.00558 +2024-11-22 07:29:07.820291: train_loss -0.7872 +2024-11-22 07:29:07.820504: val_loss -0.7375 +2024-11-22 07:29:07.820576: Pseudo dice [0.837] +2024-11-22 07:29:07.820714: Epoch time: 19.3 s +2024-11-22 07:29:09.097072: +2024-11-22 07:29:09.097285: Epoch 3815 +2024-11-22 07:29:09.097401: Current learning rate: 0.00558 +2024-11-22 07:29:28.358639: train_loss -0.7845 +2024-11-22 07:29:28.358861: val_loss -0.755 +2024-11-22 07:29:28.358936: Pseudo dice [0.823] +2024-11-22 07:29:28.359017: Epoch time: 19.26 s +2024-11-22 07:29:29.286351: +2024-11-22 07:29:29.286560: Epoch 3816 +2024-11-22 07:29:29.286669: Current learning rate: 0.00558 +2024-11-22 07:29:47.925920: train_loss -0.7946 +2024-11-22 07:29:47.926180: val_loss -0.7606 +2024-11-22 07:29:47.926258: Pseudo dice [0.8451] +2024-11-22 07:29:47.926345: Epoch time: 18.64 s +2024-11-22 07:29:48.815271: +2024-11-22 07:29:48.815531: Epoch 3817 +2024-11-22 07:29:48.815642: Current learning rate: 0.00558 +2024-11-22 07:30:09.377599: train_loss -0.7826 +2024-11-22 07:30:09.377819: val_loss -0.746 +2024-11-22 07:30:09.380148: Pseudo dice [0.8262] +2024-11-22 07:30:09.380248: Epoch time: 20.56 s +2024-11-22 07:30:10.426332: +2024-11-22 07:30:10.426534: Epoch 3818 +2024-11-22 07:30:10.426641: Current learning rate: 0.00558 +2024-11-22 07:30:29.081577: train_loss -0.7806 +2024-11-22 07:30:29.081809: val_loss -0.7238 +2024-11-22 07:30:29.087118: Pseudo dice [0.8128] +2024-11-22 07:30:29.087244: Epoch time: 18.66 s +2024-11-22 07:30:30.048705: +2024-11-22 07:30:30.048930: Epoch 3819 +2024-11-22 07:30:30.049042: Current learning rate: 0.00558 +2024-11-22 07:30:48.115332: train_loss -0.775 +2024-11-22 07:30:48.115561: val_loss -0.7622 +2024-11-22 07:30:48.115638: Pseudo dice [0.8259] +2024-11-22 07:30:48.115724: Epoch time: 18.07 s +2024-11-22 07:30:49.011429: +2024-11-22 07:30:49.011655: Epoch 3820 +2024-11-22 07:30:49.011769: Current learning rate: 0.00558 +2024-11-22 07:31:08.880140: train_loss -0.7795 +2024-11-22 07:31:08.880497: val_loss -0.7367 +2024-11-22 07:31:08.880581: Pseudo dice [0.8257] +2024-11-22 07:31:08.880657: Epoch time: 19.87 s +2024-11-22 07:31:09.770648: +2024-11-22 07:31:09.770879: Epoch 3821 +2024-11-22 07:31:09.782260: Current learning rate: 0.00557 +2024-11-22 07:31:30.001054: train_loss -0.7892 +2024-11-22 07:31:30.001277: val_loss -0.7454 +2024-11-22 07:31:30.001355: Pseudo dice [0.838] +2024-11-22 07:31:30.001436: Epoch time: 20.23 s +2024-11-22 07:31:30.899307: +2024-11-22 07:31:30.899553: Epoch 3822 +2024-11-22 07:31:30.899672: Current learning rate: 0.00557 +2024-11-22 07:31:49.067438: train_loss -0.7842 +2024-11-22 07:31:49.067652: val_loss -0.7453 +2024-11-22 07:31:49.067726: Pseudo dice [0.825] +2024-11-22 07:31:49.067801: Epoch time: 18.17 s +2024-11-22 07:31:49.961276: +2024-11-22 07:31:49.961461: Epoch 3823 +2024-11-22 07:31:49.961573: Current learning rate: 0.00557 +2024-11-22 07:32:08.859637: train_loss -0.7865 +2024-11-22 07:32:08.865030: val_loss -0.75 +2024-11-22 07:32:08.865205: Pseudo dice [0.8363] +2024-11-22 07:32:08.865295: Epoch time: 18.9 s +2024-11-22 07:32:09.767239: +2024-11-22 07:32:09.767449: Epoch 3824 +2024-11-22 07:32:09.767564: Current learning rate: 0.00557 +2024-11-22 07:32:28.669690: train_loss -0.7863 +2024-11-22 07:32:28.669936: val_loss -0.7387 +2024-11-22 07:32:28.672193: Pseudo dice [0.8268] +2024-11-22 07:32:28.672333: Epoch time: 18.9 s +2024-11-22 07:32:29.657998: +2024-11-22 07:32:29.658196: Epoch 3825 +2024-11-22 07:32:29.658308: Current learning rate: 0.00557 +2024-11-22 07:32:48.227197: train_loss -0.7854 +2024-11-22 07:32:48.227417: val_loss -0.7637 +2024-11-22 07:32:48.227493: Pseudo dice [0.8245] +2024-11-22 07:32:48.227568: Epoch time: 18.57 s +2024-11-22 07:32:49.486788: +2024-11-22 07:32:49.487043: Epoch 3826 +2024-11-22 07:32:49.487163: Current learning rate: 0.00557 +2024-11-22 07:33:07.534415: train_loss -0.7897 +2024-11-22 07:33:07.534639: val_loss -0.7342 +2024-11-22 07:33:07.534715: Pseudo dice [0.8396] +2024-11-22 07:33:07.534863: Epoch time: 18.05 s +2024-11-22 07:33:08.431058: +2024-11-22 07:33:08.431298: Epoch 3827 +2024-11-22 07:33:08.431415: Current learning rate: 0.00557 +2024-11-22 07:33:27.967392: train_loss -0.7797 +2024-11-22 07:33:27.967644: val_loss -0.7312 +2024-11-22 07:33:27.967717: Pseudo dice [0.8192] +2024-11-22 07:33:27.967804: Epoch time: 19.54 s +2024-11-22 07:33:28.867007: +2024-11-22 07:33:28.867239: Epoch 3828 +2024-11-22 07:33:28.867356: Current learning rate: 0.00557 +2024-11-22 07:33:47.820914: train_loss -0.7789 +2024-11-22 07:33:47.821125: val_loss -0.7706 +2024-11-22 07:33:47.821197: Pseudo dice [0.8422] +2024-11-22 07:33:47.821270: Epoch time: 18.95 s +2024-11-22 07:33:48.709752: +2024-11-22 07:33:48.710057: Epoch 3829 +2024-11-22 07:33:48.710173: Current learning rate: 0.00556 +2024-11-22 07:34:07.584870: train_loss -0.7637 +2024-11-22 07:34:07.585092: val_loss -0.7422 +2024-11-22 07:34:07.585168: Pseudo dice [0.8132] +2024-11-22 07:34:07.585245: Epoch time: 18.88 s +2024-11-22 07:34:08.478683: +2024-11-22 07:34:08.478925: Epoch 3830 +2024-11-22 07:34:08.479048: Current learning rate: 0.00556 +2024-11-22 07:34:27.644487: train_loss -0.7791 +2024-11-22 07:34:27.644725: val_loss -0.7463 +2024-11-22 07:34:27.644803: Pseudo dice [0.8232] +2024-11-22 07:34:27.644889: Epoch time: 19.17 s +2024-11-22 07:34:28.531165: +2024-11-22 07:34:28.531389: Epoch 3831 +2024-11-22 07:34:28.531505: Current learning rate: 0.00556 +2024-11-22 07:34:48.541034: train_loss -0.7831 +2024-11-22 07:34:48.541550: val_loss -0.7523 +2024-11-22 07:34:48.541626: Pseudo dice [0.8367] +2024-11-22 07:34:48.541704: Epoch time: 20.01 s +2024-11-22 07:34:49.434538: +2024-11-22 07:34:49.434736: Epoch 3832 +2024-11-22 07:34:49.434848: Current learning rate: 0.00556 +2024-11-22 07:35:08.501858: train_loss -0.7792 +2024-11-22 07:35:08.502127: val_loss -0.7445 +2024-11-22 07:35:08.502207: Pseudo dice [0.8315] +2024-11-22 07:35:08.502286: Epoch time: 19.07 s +2024-11-22 07:35:09.397932: +2024-11-22 07:35:09.398160: Epoch 3833 +2024-11-22 07:35:09.398278: Current learning rate: 0.00556 +2024-11-22 07:35:27.288922: train_loss -0.7865 +2024-11-22 07:35:27.289182: val_loss -0.7288 +2024-11-22 07:35:27.289266: Pseudo dice [0.8173] +2024-11-22 07:35:27.289345: Epoch time: 17.89 s +2024-11-22 07:35:28.214227: +2024-11-22 07:35:28.214449: Epoch 3834 +2024-11-22 07:35:28.214563: Current learning rate: 0.00556 +2024-11-22 07:35:46.329132: train_loss -0.7826 +2024-11-22 07:35:46.329360: val_loss -0.7363 +2024-11-22 07:35:46.329436: Pseudo dice [0.8097] +2024-11-22 07:35:46.329515: Epoch time: 18.12 s +2024-11-22 07:35:47.216787: +2024-11-22 07:35:47.217029: Epoch 3835 +2024-11-22 07:35:47.217144: Current learning rate: 0.00556 +2024-11-22 07:36:06.675273: train_loss -0.7588 +2024-11-22 07:36:06.675589: val_loss -0.7414 +2024-11-22 07:36:06.675666: Pseudo dice [0.8229] +2024-11-22 07:36:06.675752: Epoch time: 19.46 s +2024-11-22 07:36:07.704099: +2024-11-22 07:36:07.704312: Epoch 3836 +2024-11-22 07:36:07.704424: Current learning rate: 0.00556 +2024-11-22 07:36:26.448326: train_loss -0.7877 +2024-11-22 07:36:26.448607: val_loss -0.7514 +2024-11-22 07:36:26.448684: Pseudo dice [0.8315] +2024-11-22 07:36:26.448761: Epoch time: 18.75 s +2024-11-22 07:36:27.332010: +2024-11-22 07:36:27.332211: Epoch 3837 +2024-11-22 07:36:27.332321: Current learning rate: 0.00556 +2024-11-22 07:36:45.206344: train_loss -0.7864 +2024-11-22 07:36:45.206554: val_loss -0.7388 +2024-11-22 07:36:45.206631: Pseudo dice [0.836] +2024-11-22 07:36:45.206714: Epoch time: 17.88 s +2024-11-22 07:36:46.553609: +2024-11-22 07:36:46.553802: Epoch 3838 +2024-11-22 07:36:46.553910: Current learning rate: 0.00555 +2024-11-22 07:37:05.693520: train_loss -0.7878 +2024-11-22 07:37:05.693776: val_loss -0.7597 +2024-11-22 07:37:05.696051: Pseudo dice [0.8267] +2024-11-22 07:37:05.696236: Epoch time: 19.14 s +2024-11-22 07:37:06.634014: +2024-11-22 07:37:06.634250: Epoch 3839 +2024-11-22 07:37:06.634375: Current learning rate: 0.00555 +2024-11-22 07:37:24.474483: train_loss -0.7918 +2024-11-22 07:37:24.474716: val_loss -0.7324 +2024-11-22 07:37:24.474801: Pseudo dice [0.8216] +2024-11-22 07:37:24.474879: Epoch time: 17.84 s +2024-11-22 07:37:25.589272: +2024-11-22 07:37:25.589571: Epoch 3840 +2024-11-22 07:37:25.589685: Current learning rate: 0.00555 +2024-11-22 07:37:43.848630: train_loss -0.7855 +2024-11-22 07:37:43.848864: val_loss -0.7622 +2024-11-22 07:37:43.848947: Pseudo dice [0.837] +2024-11-22 07:37:43.849035: Epoch time: 18.26 s +2024-11-22 07:37:44.747943: +2024-11-22 07:37:44.748151: Epoch 3841 +2024-11-22 07:37:44.748263: Current learning rate: 0.00555 +2024-11-22 07:38:02.704228: train_loss -0.7918 +2024-11-22 07:38:02.704458: val_loss -0.7532 +2024-11-22 07:38:02.704534: Pseudo dice [0.8319] +2024-11-22 07:38:02.704612: Epoch time: 17.96 s +2024-11-22 07:38:03.606873: +2024-11-22 07:38:03.607100: Epoch 3842 +2024-11-22 07:38:03.607210: Current learning rate: 0.00555 +2024-11-22 07:38:23.709897: train_loss -0.7834 +2024-11-22 07:38:23.710136: val_loss -0.7286 +2024-11-22 07:38:23.710211: Pseudo dice [0.7969] +2024-11-22 07:38:23.710294: Epoch time: 20.1 s +2024-11-22 07:38:24.647222: +2024-11-22 07:38:24.647488: Epoch 3843 +2024-11-22 07:38:24.647602: Current learning rate: 0.00555 +2024-11-22 07:38:42.682861: train_loss -0.7768 +2024-11-22 07:38:42.683073: val_loss -0.7548 +2024-11-22 07:38:42.683144: Pseudo dice [0.8195] +2024-11-22 07:38:42.683218: Epoch time: 18.04 s +2024-11-22 07:38:43.721498: +2024-11-22 07:38:43.721704: Epoch 3844 +2024-11-22 07:38:43.721815: Current learning rate: 0.00555 +2024-11-22 07:39:03.011168: train_loss -0.785 +2024-11-22 07:39:03.011449: val_loss -0.7473 +2024-11-22 07:39:03.011528: Pseudo dice [0.8239] +2024-11-22 07:39:03.011603: Epoch time: 19.29 s +2024-11-22 07:39:03.903167: +2024-11-22 07:39:03.903394: Epoch 3845 +2024-11-22 07:39:03.903507: Current learning rate: 0.00555 +2024-11-22 07:39:23.636714: train_loss -0.7716 +2024-11-22 07:39:23.642157: val_loss -0.7165 +2024-11-22 07:39:23.642237: Pseudo dice [0.7923] +2024-11-22 07:39:23.642334: Epoch time: 19.73 s +2024-11-22 07:39:24.566411: +2024-11-22 07:39:24.566616: Epoch 3846 +2024-11-22 07:39:24.566730: Current learning rate: 0.00554 +2024-11-22 07:39:44.655591: train_loss -0.7709 +2024-11-22 07:39:44.655925: val_loss -0.7131 +2024-11-22 07:39:44.656014: Pseudo dice [0.8086] +2024-11-22 07:39:44.656089: Epoch time: 20.09 s +2024-11-22 07:39:45.547620: +2024-11-22 07:39:45.547828: Epoch 3847 +2024-11-22 07:39:45.547947: Current learning rate: 0.00554 +2024-11-22 07:40:04.556103: train_loss -0.7841 +2024-11-22 07:40:04.556323: val_loss -0.7622 +2024-11-22 07:40:04.561634: Pseudo dice [0.8353] +2024-11-22 07:40:04.561769: Epoch time: 19.01 s +2024-11-22 07:40:05.675418: +2024-11-22 07:40:05.675635: Epoch 3848 +2024-11-22 07:40:05.675751: Current learning rate: 0.00554 +2024-11-22 07:40:23.853603: train_loss -0.7741 +2024-11-22 07:40:23.856026: val_loss -0.7606 +2024-11-22 07:40:23.856128: Pseudo dice [0.8335] +2024-11-22 07:40:23.856212: Epoch time: 18.18 s +2024-11-22 07:40:25.160773: +2024-11-22 07:40:25.161004: Epoch 3849 +2024-11-22 07:40:25.161116: Current learning rate: 0.00554 +2024-11-22 07:40:42.930348: train_loss -0.7862 +2024-11-22 07:40:42.932523: val_loss -0.7567 +2024-11-22 07:40:42.932623: Pseudo dice [0.8193] +2024-11-22 07:40:42.932717: Epoch time: 17.77 s +2024-11-22 07:40:44.346962: +2024-11-22 07:40:44.347197: Epoch 3850 +2024-11-22 07:40:44.347311: Current learning rate: 0.00554 +2024-11-22 07:41:02.514341: train_loss -0.7817 +2024-11-22 07:41:02.514577: val_loss -0.7714 +2024-11-22 07:41:02.514654: Pseudo dice [0.8248] +2024-11-22 07:41:02.514733: Epoch time: 18.17 s +2024-11-22 07:41:03.404814: +2024-11-22 07:41:03.405052: Epoch 3851 +2024-11-22 07:41:03.405162: Current learning rate: 0.00554 +2024-11-22 07:41:21.676804: train_loss -0.7763 +2024-11-22 07:41:21.679220: val_loss -0.7266 +2024-11-22 07:41:21.679326: Pseudo dice [0.8206] +2024-11-22 07:41:21.679424: Epoch time: 18.27 s +2024-11-22 07:41:22.650225: +2024-11-22 07:41:22.650435: Epoch 3852 +2024-11-22 07:41:22.650552: Current learning rate: 0.00554 +2024-11-22 07:41:41.077007: train_loss -0.7832 +2024-11-22 07:41:41.082450: val_loss -0.7533 +2024-11-22 07:41:41.082565: Pseudo dice [0.8307] +2024-11-22 07:41:41.082652: Epoch time: 18.43 s +2024-11-22 07:41:42.128768: +2024-11-22 07:41:42.128996: Epoch 3853 +2024-11-22 07:41:42.129114: Current learning rate: 0.00554 +2024-11-22 07:42:00.909771: train_loss -0.7871 +2024-11-22 07:42:00.910004: val_loss -0.7405 +2024-11-22 07:42:00.910079: Pseudo dice [0.8213] +2024-11-22 07:42:00.910166: Epoch time: 18.78 s +2024-11-22 07:42:01.885014: +2024-11-22 07:42:01.885213: Epoch 3854 +2024-11-22 07:42:01.885331: Current learning rate: 0.00553 +2024-11-22 07:42:19.640947: train_loss -0.7771 +2024-11-22 07:42:19.641171: val_loss -0.739 +2024-11-22 07:42:19.641246: Pseudo dice [0.8182] +2024-11-22 07:42:19.641321: Epoch time: 17.76 s +2024-11-22 07:42:20.810004: +2024-11-22 07:42:20.810196: Epoch 3855 +2024-11-22 07:42:20.810310: Current learning rate: 0.00553 +2024-11-22 07:42:39.372816: train_loss -0.7689 +2024-11-22 07:42:39.373046: val_loss -0.746 +2024-11-22 07:42:39.373124: Pseudo dice [0.8341] +2024-11-22 07:42:39.373201: Epoch time: 18.56 s +2024-11-22 07:42:40.265357: +2024-11-22 07:42:40.265555: Epoch 3856 +2024-11-22 07:42:40.265668: Current learning rate: 0.00553 +2024-11-22 07:42:59.162288: train_loss -0.7808 +2024-11-22 07:42:59.165228: val_loss -0.749 +2024-11-22 07:42:59.165327: Pseudo dice [0.8343] +2024-11-22 07:42:59.165419: Epoch time: 18.9 s +2024-11-22 07:43:00.235335: +2024-11-22 07:43:00.235548: Epoch 3857 +2024-11-22 07:43:00.235670: Current learning rate: 0.00553 +2024-11-22 07:43:20.031489: train_loss -0.7794 +2024-11-22 07:43:20.031705: val_loss -0.7471 +2024-11-22 07:43:20.031779: Pseudo dice [0.8226] +2024-11-22 07:43:20.031854: Epoch time: 19.8 s +2024-11-22 07:43:20.926622: +2024-11-22 07:43:20.926891: Epoch 3858 +2024-11-22 07:43:20.927012: Current learning rate: 0.00553 +2024-11-22 07:43:39.684024: train_loss -0.7652 +2024-11-22 07:43:39.686428: val_loss -0.7342 +2024-11-22 07:43:39.686568: Pseudo dice [0.8267] +2024-11-22 07:43:39.686650: Epoch time: 18.76 s +2024-11-22 07:43:40.591704: +2024-11-22 07:43:40.591965: Epoch 3859 +2024-11-22 07:43:40.592087: Current learning rate: 0.00553 +2024-11-22 07:43:59.807057: train_loss -0.777 +2024-11-22 07:43:59.807311: val_loss -0.7306 +2024-11-22 07:43:59.807394: Pseudo dice [0.8292] +2024-11-22 07:43:59.807482: Epoch time: 19.22 s +2024-11-22 07:44:01.034847: +2024-11-22 07:44:01.035369: Epoch 3860 +2024-11-22 07:44:01.035502: Current learning rate: 0.00553 +2024-11-22 07:44:19.572228: train_loss -0.7682 +2024-11-22 07:44:19.572455: val_loss -0.736 +2024-11-22 07:44:19.572531: Pseudo dice [0.8299] +2024-11-22 07:44:19.572608: Epoch time: 18.54 s +2024-11-22 07:44:20.463114: +2024-11-22 07:44:20.463554: Epoch 3861 +2024-11-22 07:44:20.463685: Current learning rate: 0.00553 +2024-11-22 07:44:38.539411: train_loss -0.7828 +2024-11-22 07:44:38.539630: val_loss -0.7501 +2024-11-22 07:44:38.539705: Pseudo dice [0.8203] +2024-11-22 07:44:38.539783: Epoch time: 18.08 s +2024-11-22 07:44:39.475686: +2024-11-22 07:44:39.476149: Epoch 3862 +2024-11-22 07:44:39.476285: Current learning rate: 0.00552 +2024-11-22 07:44:57.522408: train_loss -0.7856 +2024-11-22 07:44:57.522628: val_loss -0.7361 +2024-11-22 07:44:57.522711: Pseudo dice [0.8309] +2024-11-22 07:44:57.522787: Epoch time: 18.05 s +2024-11-22 07:44:58.420396: +2024-11-22 07:44:58.420869: Epoch 3863 +2024-11-22 07:44:58.421016: Current learning rate: 0.00552 +2024-11-22 07:45:16.654622: train_loss -0.7828 +2024-11-22 07:45:16.654895: val_loss -0.7427 +2024-11-22 07:45:16.654971: Pseudo dice [0.8281] +2024-11-22 07:45:16.655055: Epoch time: 18.24 s +2024-11-22 07:45:17.556723: +2024-11-22 07:45:17.557222: Epoch 3864 +2024-11-22 07:45:17.557358: Current learning rate: 0.00552 +2024-11-22 07:45:37.534411: train_loss -0.7792 +2024-11-22 07:45:37.534672: val_loss -0.7356 +2024-11-22 07:45:37.534749: Pseudo dice [0.8205] +2024-11-22 07:45:37.534829: Epoch time: 19.98 s +2024-11-22 07:45:38.585339: +2024-11-22 07:45:38.585740: Epoch 3865 +2024-11-22 07:45:38.585871: Current learning rate: 0.00552 +2024-11-22 07:45:57.189837: train_loss -0.7789 +2024-11-22 07:45:57.190059: val_loss -0.7662 +2024-11-22 07:45:57.190133: Pseudo dice [0.8244] +2024-11-22 07:45:57.190207: Epoch time: 18.61 s +2024-11-22 07:45:58.076040: +2024-11-22 07:45:58.076509: Epoch 3866 +2024-11-22 07:45:58.076646: Current learning rate: 0.00552 +2024-11-22 07:46:16.524322: train_loss -0.7722 +2024-11-22 07:46:16.524546: val_loss -0.7363 +2024-11-22 07:46:16.524623: Pseudo dice [0.8337] +2024-11-22 07:46:16.526894: Epoch time: 18.45 s +2024-11-22 07:46:17.553661: +2024-11-22 07:46:17.554193: Epoch 3867 +2024-11-22 07:46:17.554324: Current learning rate: 0.00552 +2024-11-22 07:46:35.338537: train_loss -0.7837 +2024-11-22 07:46:35.338824: val_loss -0.7483 +2024-11-22 07:46:35.338902: Pseudo dice [0.8367] +2024-11-22 07:46:35.338987: Epoch time: 17.79 s +2024-11-22 07:46:36.230192: +2024-11-22 07:46:36.230627: Epoch 3868 +2024-11-22 07:46:36.230766: Current learning rate: 0.00552 +2024-11-22 07:46:54.749242: train_loss -0.7687 +2024-11-22 07:46:54.749456: val_loss -0.7467 +2024-11-22 07:46:54.749533: Pseudo dice [0.8076] +2024-11-22 07:46:54.749613: Epoch time: 18.52 s +2024-11-22 07:46:55.642837: +2024-11-22 07:46:55.643330: Epoch 3869 +2024-11-22 07:46:55.643470: Current learning rate: 0.00552 +2024-11-22 07:47:14.380421: train_loss -0.7894 +2024-11-22 07:47:14.385817: val_loss -0.7262 +2024-11-22 07:47:14.385978: Pseudo dice [0.8291] +2024-11-22 07:47:14.386067: Epoch time: 18.74 s +2024-11-22 07:47:15.313258: +2024-11-22 07:47:15.313675: Epoch 3870 +2024-11-22 07:47:15.313808: Current learning rate: 0.00552 +2024-11-22 07:47:34.101090: train_loss -0.795 +2024-11-22 07:47:34.101409: val_loss -0.7134 +2024-11-22 07:47:34.101492: Pseudo dice [0.8196] +2024-11-22 07:47:34.101581: Epoch time: 18.79 s +2024-11-22 07:47:35.062191: +2024-11-22 07:47:35.062380: Epoch 3871 +2024-11-22 07:47:35.062494: Current learning rate: 0.00551 +2024-11-22 07:47:53.155326: train_loss -0.7889 +2024-11-22 07:47:53.155550: val_loss -0.752 +2024-11-22 07:47:53.155628: Pseudo dice [0.8315] +2024-11-22 07:47:53.155708: Epoch time: 18.09 s +2024-11-22 07:47:54.474706: +2024-11-22 07:47:54.474913: Epoch 3872 +2024-11-22 07:47:54.475029: Current learning rate: 0.00551 +2024-11-22 07:48:12.565759: train_loss -0.7925 +2024-11-22 07:48:12.565987: val_loss -0.7525 +2024-11-22 07:48:12.566069: Pseudo dice [0.8189] +2024-11-22 07:48:12.566145: Epoch time: 18.09 s +2024-11-22 07:48:13.461684: +2024-11-22 07:48:13.461900: Epoch 3873 +2024-11-22 07:48:13.462021: Current learning rate: 0.00551 +2024-11-22 07:48:31.355250: train_loss -0.7848 +2024-11-22 07:48:31.355578: val_loss -0.7676 +2024-11-22 07:48:31.355660: Pseudo dice [0.8349] +2024-11-22 07:48:31.355750: Epoch time: 17.89 s +2024-11-22 07:48:32.246317: +2024-11-22 07:48:32.246533: Epoch 3874 +2024-11-22 07:48:32.246643: Current learning rate: 0.00551 +2024-11-22 07:48:50.016205: train_loss -0.7934 +2024-11-22 07:48:50.016413: val_loss -0.7578 +2024-11-22 07:48:50.016488: Pseudo dice [0.8302] +2024-11-22 07:48:50.016564: Epoch time: 17.77 s +2024-11-22 07:48:50.895611: +2024-11-22 07:48:50.895833: Epoch 3875 +2024-11-22 07:48:50.895950: Current learning rate: 0.00551 +2024-11-22 07:49:10.296424: train_loss -0.7857 +2024-11-22 07:49:10.296643: val_loss -0.7408 +2024-11-22 07:49:10.296719: Pseudo dice [0.8226] +2024-11-22 07:49:10.296793: Epoch time: 19.4 s +2024-11-22 07:49:11.185545: +2024-11-22 07:49:11.185984: Epoch 3876 +2024-11-22 07:49:11.186103: Current learning rate: 0.00551 +2024-11-22 07:49:30.216124: train_loss -0.7639 +2024-11-22 07:49:30.216352: val_loss -0.7515 +2024-11-22 07:49:30.216433: Pseudo dice [0.8309] +2024-11-22 07:49:30.216514: Epoch time: 19.03 s +2024-11-22 07:49:31.110954: +2024-11-22 07:49:31.111157: Epoch 3877 +2024-11-22 07:49:31.111269: Current learning rate: 0.00551 +2024-11-22 07:49:50.006008: train_loss -0.7644 +2024-11-22 07:49:50.006581: val_loss -0.707 +2024-11-22 07:49:50.006663: Pseudo dice [0.821] +2024-11-22 07:49:50.006743: Epoch time: 18.9 s +2024-11-22 07:49:50.898803: +2024-11-22 07:49:50.899027: Epoch 3878 +2024-11-22 07:49:50.899142: Current learning rate: 0.00551 +2024-11-22 07:50:09.816843: train_loss -0.7682 +2024-11-22 07:50:09.817070: val_loss -0.7418 +2024-11-22 07:50:09.817146: Pseudo dice [0.8324] +2024-11-22 07:50:09.817223: Epoch time: 18.92 s +2024-11-22 07:50:10.770112: +2024-11-22 07:50:10.770351: Epoch 3879 +2024-11-22 07:50:10.770466: Current learning rate: 0.0055 +2024-11-22 07:50:30.419846: train_loss -0.7748 +2024-11-22 07:50:30.420118: val_loss -0.7277 +2024-11-22 07:50:30.420191: Pseudo dice [0.8185] +2024-11-22 07:50:30.420264: Epoch time: 19.65 s +2024-11-22 07:50:31.309563: +2024-11-22 07:50:31.309776: Epoch 3880 +2024-11-22 07:50:31.309894: Current learning rate: 0.0055 +2024-11-22 07:50:50.392282: train_loss -0.7792 +2024-11-22 07:50:50.392524: val_loss -0.7368 +2024-11-22 07:50:50.392599: Pseudo dice [0.8249] +2024-11-22 07:50:50.392679: Epoch time: 19.08 s +2024-11-22 07:50:51.335752: +2024-11-22 07:50:51.335971: Epoch 3881 +2024-11-22 07:50:51.336092: Current learning rate: 0.0055 +2024-11-22 07:51:10.547373: train_loss -0.7804 +2024-11-22 07:51:10.547592: val_loss -0.7419 +2024-11-22 07:51:10.547668: Pseudo dice [0.8348] +2024-11-22 07:51:10.547761: Epoch time: 19.21 s +2024-11-22 07:51:11.437582: +2024-11-22 07:51:11.437774: Epoch 3882 +2024-11-22 07:51:11.437886: Current learning rate: 0.0055 +2024-11-22 07:51:29.939946: train_loss -0.7857 +2024-11-22 07:51:29.940167: val_loss -0.7459 +2024-11-22 07:51:29.940240: Pseudo dice [0.8251] +2024-11-22 07:51:29.940313: Epoch time: 18.5 s +2024-11-22 07:51:30.877220: +2024-11-22 07:51:30.877448: Epoch 3883 +2024-11-22 07:51:30.877568: Current learning rate: 0.0055 +2024-11-22 07:51:49.169456: train_loss -0.7941 +2024-11-22 07:51:49.170036: val_loss -0.756 +2024-11-22 07:51:49.170142: Pseudo dice [0.813] +2024-11-22 07:51:49.170232: Epoch time: 18.29 s +2024-11-22 07:51:50.065503: +2024-11-22 07:51:50.065725: Epoch 3884 +2024-11-22 07:51:50.065841: Current learning rate: 0.0055 +2024-11-22 07:52:08.022968: train_loss -0.7905 +2024-11-22 07:52:08.024971: val_loss -0.7439 +2024-11-22 07:52:08.025123: Pseudo dice [0.8087] +2024-11-22 07:52:08.035859: Epoch time: 17.96 s +2024-11-22 07:52:08.934768: +2024-11-22 07:52:08.934978: Epoch 3885 +2024-11-22 07:52:08.935098: Current learning rate: 0.0055 +2024-11-22 07:52:28.457369: train_loss -0.7903 +2024-11-22 07:52:28.457603: val_loss -0.7437 +2024-11-22 07:52:28.457677: Pseudo dice [0.8342] +2024-11-22 07:52:28.457755: Epoch time: 19.52 s +2024-11-22 07:52:29.352426: +2024-11-22 07:52:29.352639: Epoch 3886 +2024-11-22 07:52:29.352751: Current learning rate: 0.0055 +2024-11-22 07:52:47.697322: train_loss -0.7867 +2024-11-22 07:52:47.697538: val_loss -0.7324 +2024-11-22 07:52:47.697615: Pseudo dice [0.811] +2024-11-22 07:52:47.697690: Epoch time: 18.35 s +2024-11-22 07:52:48.587885: +2024-11-22 07:52:48.588132: Epoch 3887 +2024-11-22 07:52:48.588241: Current learning rate: 0.00549 +2024-11-22 07:53:06.794687: train_loss -0.7886 +2024-11-22 07:53:06.794932: val_loss -0.7637 +2024-11-22 07:53:06.795015: Pseudo dice [0.8267] +2024-11-22 07:53:06.795100: Epoch time: 18.21 s +2024-11-22 07:53:07.693085: +2024-11-22 07:53:07.693294: Epoch 3888 +2024-11-22 07:53:07.693408: Current learning rate: 0.00549 +2024-11-22 07:53:26.136850: train_loss -0.7904 +2024-11-22 07:53:26.137088: val_loss -0.7503 +2024-11-22 07:53:26.137163: Pseudo dice [0.8274] +2024-11-22 07:53:26.137242: Epoch time: 18.44 s +2024-11-22 07:53:27.028394: +2024-11-22 07:53:27.028704: Epoch 3889 +2024-11-22 07:53:27.028825: Current learning rate: 0.00549 +2024-11-22 07:53:45.416291: train_loss -0.792 +2024-11-22 07:53:45.416509: val_loss -0.7513 +2024-11-22 07:53:45.416586: Pseudo dice [0.8174] +2024-11-22 07:53:45.416669: Epoch time: 18.39 s +2024-11-22 07:53:46.334679: +2024-11-22 07:53:46.334891: Epoch 3890 +2024-11-22 07:53:46.335011: Current learning rate: 0.00549 +2024-11-22 07:54:04.633306: train_loss -0.7972 +2024-11-22 07:54:04.633523: val_loss -0.7499 +2024-11-22 07:54:04.633599: Pseudo dice [0.81] +2024-11-22 07:54:04.633679: Epoch time: 18.3 s +2024-11-22 07:54:05.523832: +2024-11-22 07:54:05.524108: Epoch 3891 +2024-11-22 07:54:05.524223: Current learning rate: 0.00549 +2024-11-22 07:54:23.624482: train_loss -0.7812 +2024-11-22 07:54:23.624725: val_loss -0.7344 +2024-11-22 07:54:23.624800: Pseudo dice [0.814] +2024-11-22 07:54:23.624880: Epoch time: 18.1 s +2024-11-22 07:54:24.745795: +2024-11-22 07:54:24.746053: Epoch 3892 +2024-11-22 07:54:24.746167: Current learning rate: 0.00549 +2024-11-22 07:54:43.474898: train_loss -0.7868 +2024-11-22 07:54:43.475112: val_loss -0.7508 +2024-11-22 07:54:43.475188: Pseudo dice [0.8297] +2024-11-22 07:54:43.475261: Epoch time: 18.73 s +2024-11-22 07:54:44.361291: +2024-11-22 07:54:44.361496: Epoch 3893 +2024-11-22 07:54:44.361645: Current learning rate: 0.00549 +2024-11-22 07:55:03.080064: train_loss -0.7863 +2024-11-22 07:55:03.080284: val_loss -0.7337 +2024-11-22 07:55:03.080359: Pseudo dice [0.8318] +2024-11-22 07:55:03.080435: Epoch time: 18.72 s +2024-11-22 07:55:04.407187: +2024-11-22 07:55:04.407476: Epoch 3894 +2024-11-22 07:55:04.407595: Current learning rate: 0.00549 +2024-11-22 07:55:23.014170: train_loss -0.7792 +2024-11-22 07:55:23.014409: val_loss -0.7748 +2024-11-22 07:55:23.014494: Pseudo dice [0.8322] +2024-11-22 07:55:23.014606: Epoch time: 18.61 s +2024-11-22 07:55:23.895186: +2024-11-22 07:55:23.895401: Epoch 3895 +2024-11-22 07:55:23.895515: Current learning rate: 0.00549 +2024-11-22 07:55:42.867021: train_loss -0.7873 +2024-11-22 07:55:42.867253: val_loss -0.7552 +2024-11-22 07:55:42.867331: Pseudo dice [0.8275] +2024-11-22 07:55:42.867410: Epoch time: 18.97 s +2024-11-22 07:55:43.758978: +2024-11-22 07:55:43.759246: Epoch 3896 +2024-11-22 07:55:43.759366: Current learning rate: 0.00548 +2024-11-22 07:56:01.832211: train_loss -0.78 +2024-11-22 07:56:01.832433: val_loss -0.7323 +2024-11-22 07:56:01.832514: Pseudo dice [0.8288] +2024-11-22 07:56:01.837749: Epoch time: 18.07 s +2024-11-22 07:56:02.893334: +2024-11-22 07:56:02.893538: Epoch 3897 +2024-11-22 07:56:02.893648: Current learning rate: 0.00548 +2024-11-22 07:56:21.372136: train_loss -0.7858 +2024-11-22 07:56:21.372620: val_loss -0.7333 +2024-11-22 07:56:21.372702: Pseudo dice [0.8182] +2024-11-22 07:56:21.372784: Epoch time: 18.48 s +2024-11-22 07:56:22.248808: +2024-11-22 07:56:22.249027: Epoch 3898 +2024-11-22 07:56:22.249139: Current learning rate: 0.00548 +2024-11-22 07:56:40.733941: train_loss -0.7894 +2024-11-22 07:56:40.734262: val_loss -0.7433 +2024-11-22 07:56:40.734340: Pseudo dice [0.8254] +2024-11-22 07:56:40.734424: Epoch time: 18.49 s +2024-11-22 07:56:41.630971: +2024-11-22 07:56:41.631205: Epoch 3899 +2024-11-22 07:56:41.631310: Current learning rate: 0.00548 +2024-11-22 07:56:59.485204: train_loss -0.7938 +2024-11-22 07:56:59.485432: val_loss -0.7604 +2024-11-22 07:56:59.485505: Pseudo dice [0.8285] +2024-11-22 07:56:59.485580: Epoch time: 17.86 s +2024-11-22 07:57:00.722882: +2024-11-22 07:57:00.723079: Epoch 3900 +2024-11-22 07:57:00.723191: Current learning rate: 0.00548 +2024-11-22 07:57:18.597117: train_loss -0.7869 +2024-11-22 07:57:18.597351: val_loss -0.6977 +2024-11-22 07:57:18.597483: Pseudo dice [0.8146] +2024-11-22 07:57:18.597561: Epoch time: 17.88 s +2024-11-22 07:57:19.492467: +2024-11-22 07:57:19.492667: Epoch 3901 +2024-11-22 07:57:19.492780: Current learning rate: 0.00548 +2024-11-22 07:57:39.227975: train_loss -0.7813 +2024-11-22 07:57:39.228228: val_loss -0.7166 +2024-11-22 07:57:39.228329: Pseudo dice [0.825] +2024-11-22 07:57:39.228414: Epoch time: 19.74 s +2024-11-22 07:57:40.129357: +2024-11-22 07:57:40.129572: Epoch 3902 +2024-11-22 07:57:40.129684: Current learning rate: 0.00548 +2024-11-22 07:57:59.725727: train_loss -0.7881 +2024-11-22 07:57:59.726021: val_loss -0.734 +2024-11-22 07:57:59.726104: Pseudo dice [0.8324] +2024-11-22 07:57:59.726180: Epoch time: 19.6 s +2024-11-22 07:58:00.607736: +2024-11-22 07:58:00.607923: Epoch 3903 +2024-11-22 07:58:00.608157: Current learning rate: 0.00548 +2024-11-22 07:58:19.178492: train_loss -0.7863 +2024-11-22 07:58:19.178723: val_loss -0.7625 +2024-11-22 07:58:19.178798: Pseudo dice [0.8344] +2024-11-22 07:58:19.178875: Epoch time: 18.57 s +2024-11-22 07:58:20.261232: +2024-11-22 07:58:20.261451: Epoch 3904 +2024-11-22 07:58:20.261562: Current learning rate: 0.00547 +2024-11-22 07:58:39.015285: train_loss -0.7658 +2024-11-22 07:58:39.015501: val_loss -0.7453 +2024-11-22 07:58:39.015578: Pseudo dice [0.8254] +2024-11-22 07:58:39.015657: Epoch time: 18.75 s +2024-11-22 07:58:39.908979: +2024-11-22 07:58:39.909189: Epoch 3905 +2024-11-22 07:58:39.909299: Current learning rate: 0.00547 +2024-11-22 07:58:58.755279: train_loss -0.7678 +2024-11-22 07:58:58.761040: val_loss -0.7248 +2024-11-22 07:58:58.761159: Pseudo dice [0.8114] +2024-11-22 07:58:58.761249: Epoch time: 18.85 s +2024-11-22 07:58:59.685077: +2024-11-22 07:58:59.685284: Epoch 3906 +2024-11-22 07:58:59.685394: Current learning rate: 0.00547 +2024-11-22 07:59:18.713900: train_loss -0.7783 +2024-11-22 07:59:18.717110: val_loss -0.7504 +2024-11-22 07:59:18.717244: Pseudo dice [0.8325] +2024-11-22 07:59:18.717326: Epoch time: 19.03 s +2024-11-22 07:59:19.620720: +2024-11-22 07:59:19.621130: Epoch 3907 +2024-11-22 07:59:19.621247: Current learning rate: 0.00547 +2024-11-22 07:59:38.712609: train_loss -0.7853 +2024-11-22 07:59:38.712820: val_loss -0.7551 +2024-11-22 07:59:38.712894: Pseudo dice [0.8279] +2024-11-22 07:59:38.712972: Epoch time: 19.09 s +2024-11-22 07:59:39.603005: +2024-11-22 07:59:39.603219: Epoch 3908 +2024-11-22 07:59:39.603337: Current learning rate: 0.00547 +2024-11-22 07:59:57.833875: train_loss -0.7777 +2024-11-22 07:59:57.834124: val_loss -0.7598 +2024-11-22 07:59:57.834204: Pseudo dice [0.8192] +2024-11-22 07:59:57.834289: Epoch time: 18.23 s +2024-11-22 07:59:58.727369: +2024-11-22 07:59:58.727575: Epoch 3909 +2024-11-22 07:59:58.727689: Current learning rate: 0.00547 +2024-11-22 08:00:18.267046: train_loss -0.7726 +2024-11-22 08:00:18.267259: val_loss -0.7253 +2024-11-22 08:00:18.267337: Pseudo dice [0.8067] +2024-11-22 08:00:18.267414: Epoch time: 19.54 s +2024-11-22 08:00:19.293358: +2024-11-22 08:00:19.293564: Epoch 3910 +2024-11-22 08:00:19.293891: Current learning rate: 0.00547 +2024-11-22 08:00:37.385934: train_loss -0.78 +2024-11-22 08:00:37.386479: val_loss -0.752 +2024-11-22 08:00:37.386555: Pseudo dice [0.8448] +2024-11-22 08:00:37.386632: Epoch time: 18.09 s +2024-11-22 08:00:38.283262: +2024-11-22 08:00:38.283495: Epoch 3911 +2024-11-22 08:00:38.283609: Current learning rate: 0.00547 +2024-11-22 08:00:56.222669: train_loss -0.7883 +2024-11-22 08:00:56.222882: val_loss -0.7479 +2024-11-22 08:00:56.223000: Pseudo dice [0.824] +2024-11-22 08:00:56.223079: Epoch time: 17.94 s +2024-11-22 08:00:57.137579: +2024-11-22 08:00:57.137794: Epoch 3912 +2024-11-22 08:00:57.137907: Current learning rate: 0.00546 +2024-11-22 08:01:14.877954: train_loss -0.7882 +2024-11-22 08:01:14.878199: val_loss -0.7604 +2024-11-22 08:01:14.878276: Pseudo dice [0.8347] +2024-11-22 08:01:14.878359: Epoch time: 17.74 s +2024-11-22 08:01:15.780504: +2024-11-22 08:01:15.780707: Epoch 3913 +2024-11-22 08:01:15.780818: Current learning rate: 0.00546 +2024-11-22 08:01:34.011898: train_loss -0.7895 +2024-11-22 08:01:34.012126: val_loss -0.7719 +2024-11-22 08:01:34.012203: Pseudo dice [0.8352] +2024-11-22 08:01:34.012279: Epoch time: 18.23 s +2024-11-22 08:01:34.904173: +2024-11-22 08:01:34.904382: Epoch 3914 +2024-11-22 08:01:34.904502: Current learning rate: 0.00546 +2024-11-22 08:01:54.647834: train_loss -0.7861 +2024-11-22 08:01:54.648062: val_loss -0.7369 +2024-11-22 08:01:54.648137: Pseudo dice [0.8322] +2024-11-22 08:01:54.648212: Epoch time: 19.74 s +2024-11-22 08:01:55.538787: +2024-11-22 08:01:55.539089: Epoch 3915 +2024-11-22 08:01:55.539208: Current learning rate: 0.00546 +2024-11-22 08:02:15.574708: train_loss -0.7908 +2024-11-22 08:02:15.574944: val_loss -0.7537 +2024-11-22 08:02:15.575032: Pseudo dice [0.8251] +2024-11-22 08:02:15.575121: Epoch time: 20.04 s +2024-11-22 08:02:16.841737: +2024-11-22 08:02:16.842010: Epoch 3916 +2024-11-22 08:02:16.842158: Current learning rate: 0.00546 +2024-11-22 08:02:35.459166: train_loss -0.7948 +2024-11-22 08:02:35.459385: val_loss -0.7366 +2024-11-22 08:02:35.459459: Pseudo dice [0.8293] +2024-11-22 08:02:35.459535: Epoch time: 18.62 s +2024-11-22 08:02:36.352480: +2024-11-22 08:02:36.352682: Epoch 3917 +2024-11-22 08:02:36.352790: Current learning rate: 0.00546 +2024-11-22 08:02:56.499326: train_loss -0.7805 +2024-11-22 08:02:56.499543: val_loss -0.717 +2024-11-22 08:02:56.499617: Pseudo dice [0.8134] +2024-11-22 08:02:56.499763: Epoch time: 20.15 s +2024-11-22 08:02:57.391141: +2024-11-22 08:02:57.391360: Epoch 3918 +2024-11-22 08:02:57.391473: Current learning rate: 0.00546 +2024-11-22 08:03:15.413735: train_loss -0.7776 +2024-11-22 08:03:15.413940: val_loss -0.7422 +2024-11-22 08:03:15.414020: Pseudo dice [0.8406] +2024-11-22 08:03:15.414094: Epoch time: 18.02 s +2024-11-22 08:03:16.314681: +2024-11-22 08:03:16.314875: Epoch 3919 +2024-11-22 08:03:16.314982: Current learning rate: 0.00546 +2024-11-22 08:03:34.820224: train_loss -0.7782 +2024-11-22 08:03:34.820480: val_loss -0.746 +2024-11-22 08:03:34.820567: Pseudo dice [0.8181] +2024-11-22 08:03:34.820742: Epoch time: 18.51 s +2024-11-22 08:03:35.719451: +2024-11-22 08:03:35.719675: Epoch 3920 +2024-11-22 08:03:35.719782: Current learning rate: 0.00546 +2024-11-22 08:03:54.581645: train_loss -0.7854 +2024-11-22 08:03:54.581861: val_loss -0.741 +2024-11-22 08:03:54.581935: Pseudo dice [0.8122] +2024-11-22 08:03:54.582025: Epoch time: 18.86 s +2024-11-22 08:03:55.474477: +2024-11-22 08:03:55.474680: Epoch 3921 +2024-11-22 08:03:55.474792: Current learning rate: 0.00545 +2024-11-22 08:04:14.119560: train_loss -0.7947 +2024-11-22 08:04:14.124952: val_loss -0.7572 +2024-11-22 08:04:14.125056: Pseudo dice [0.8324] +2024-11-22 08:04:14.125134: Epoch time: 18.65 s +2024-11-22 08:04:15.178795: +2024-11-22 08:04:15.179026: Epoch 3922 +2024-11-22 08:04:15.179133: Current learning rate: 0.00545 +2024-11-22 08:04:34.633120: train_loss -0.7808 +2024-11-22 08:04:34.633339: val_loss -0.7136 +2024-11-22 08:04:34.633411: Pseudo dice [0.8246] +2024-11-22 08:04:34.645776: Epoch time: 19.46 s +2024-11-22 08:04:35.538520: +2024-11-22 08:04:35.538751: Epoch 3923 +2024-11-22 08:04:35.538873: Current learning rate: 0.00545 +2024-11-22 08:04:54.361583: train_loss -0.7887 +2024-11-22 08:04:54.361859: val_loss -0.7285 +2024-11-22 08:04:54.361950: Pseudo dice [0.816] +2024-11-22 08:04:54.362104: Epoch time: 18.82 s +2024-11-22 08:04:55.261341: +2024-11-22 08:04:55.261552: Epoch 3924 +2024-11-22 08:04:55.261666: Current learning rate: 0.00545 +2024-11-22 08:05:14.026205: train_loss -0.7803 +2024-11-22 08:05:14.031573: val_loss -0.755 +2024-11-22 08:05:14.031739: Pseudo dice [0.8222] +2024-11-22 08:05:14.031824: Epoch time: 18.77 s +2024-11-22 08:05:14.922053: +2024-11-22 08:05:14.922269: Epoch 3925 +2024-11-22 08:05:14.922387: Current learning rate: 0.00545 +2024-11-22 08:05:33.269783: train_loss -0.7924 +2024-11-22 08:05:33.270001: val_loss -0.7361 +2024-11-22 08:05:33.270077: Pseudo dice [0.8312] +2024-11-22 08:05:33.270152: Epoch time: 18.35 s +2024-11-22 08:05:34.150995: +2024-11-22 08:05:34.151185: Epoch 3926 +2024-11-22 08:05:34.151294: Current learning rate: 0.00545 +2024-11-22 08:05:52.506172: train_loss -0.785 +2024-11-22 08:05:52.506413: val_loss -0.7512 +2024-11-22 08:05:52.506524: Pseudo dice [0.8305] +2024-11-22 08:05:52.506609: Epoch time: 18.36 s +2024-11-22 08:05:53.404788: +2024-11-22 08:05:53.405218: Epoch 3927 +2024-11-22 08:05:53.405352: Current learning rate: 0.00545 +2024-11-22 08:06:12.010078: train_loss -0.7902 +2024-11-22 08:06:12.015612: val_loss -0.7312 +2024-11-22 08:06:12.015741: Pseudo dice [0.8157] +2024-11-22 08:06:12.015824: Epoch time: 18.61 s +2024-11-22 08:06:13.480900: +2024-11-22 08:06:13.481131: Epoch 3928 +2024-11-22 08:06:13.481249: Current learning rate: 0.00545 +2024-11-22 08:06:32.152974: train_loss -0.7928 +2024-11-22 08:06:32.153213: val_loss -0.753 +2024-11-22 08:06:32.153296: Pseudo dice [0.8214] +2024-11-22 08:06:32.153374: Epoch time: 18.67 s +2024-11-22 08:06:33.036681: +2024-11-22 08:06:33.036900: Epoch 3929 +2024-11-22 08:06:33.037020: Current learning rate: 0.00544 +2024-11-22 08:06:51.541397: train_loss -0.7898 +2024-11-22 08:06:51.546822: val_loss -0.7465 +2024-11-22 08:06:51.546908: Pseudo dice [0.8115] +2024-11-22 08:06:51.547004: Epoch time: 18.51 s +2024-11-22 08:06:52.483386: +2024-11-22 08:06:52.483599: Epoch 3930 +2024-11-22 08:06:52.483719: Current learning rate: 0.00544 +2024-11-22 08:07:10.896805: train_loss -0.787 +2024-11-22 08:07:10.897032: val_loss -0.7659 +2024-11-22 08:07:10.897110: Pseudo dice [0.8306] +2024-11-22 08:07:10.897186: Epoch time: 18.41 s +2024-11-22 08:07:11.787025: +2024-11-22 08:07:11.787240: Epoch 3931 +2024-11-22 08:07:11.787374: Current learning rate: 0.00544 +2024-11-22 08:07:29.938013: train_loss -0.786 +2024-11-22 08:07:29.938231: val_loss -0.7212 +2024-11-22 08:07:29.938307: Pseudo dice [0.8243] +2024-11-22 08:07:29.938389: Epoch time: 18.15 s +2024-11-22 08:07:30.836234: +2024-11-22 08:07:30.836522: Epoch 3932 +2024-11-22 08:07:30.836635: Current learning rate: 0.00544 +2024-11-22 08:07:49.635834: train_loss -0.7966 +2024-11-22 08:07:49.636067: val_loss -0.7583 +2024-11-22 08:07:49.636145: Pseudo dice [0.8332] +2024-11-22 08:07:49.636221: Epoch time: 18.8 s +2024-11-22 08:07:50.632143: +2024-11-22 08:07:50.632344: Epoch 3933 +2024-11-22 08:07:50.632459: Current learning rate: 0.00544 +2024-11-22 08:08:09.198197: train_loss -0.79 +2024-11-22 08:08:09.198438: val_loss -0.7541 +2024-11-22 08:08:09.198579: Pseudo dice [0.8295] +2024-11-22 08:08:09.198665: Epoch time: 18.57 s +2024-11-22 08:08:10.104102: +2024-11-22 08:08:10.104324: Epoch 3934 +2024-11-22 08:08:10.104435: Current learning rate: 0.00544 +2024-11-22 08:08:28.787052: train_loss -0.7844 +2024-11-22 08:08:28.787275: val_loss -0.7437 +2024-11-22 08:08:28.787350: Pseudo dice [0.8122] +2024-11-22 08:08:28.787427: Epoch time: 18.68 s +2024-11-22 08:08:29.677149: +2024-11-22 08:08:29.677411: Epoch 3935 +2024-11-22 08:08:29.677527: Current learning rate: 0.00544 +2024-11-22 08:08:49.410705: train_loss -0.7807 +2024-11-22 08:08:49.437482: val_loss -0.7709 +2024-11-22 08:08:49.437652: Pseudo dice [0.8279] +2024-11-22 08:08:49.437738: Epoch time: 19.73 s +2024-11-22 08:08:50.336091: +2024-11-22 08:08:50.336287: Epoch 3936 +2024-11-22 08:08:50.336397: Current learning rate: 0.00544 +2024-11-22 08:09:09.069709: train_loss -0.7842 +2024-11-22 08:09:09.069932: val_loss -0.7391 +2024-11-22 08:09:09.070021: Pseudo dice [0.8252] +2024-11-22 08:09:09.070098: Epoch time: 18.73 s +2024-11-22 08:09:09.954673: +2024-11-22 08:09:09.954896: Epoch 3937 +2024-11-22 08:09:09.955024: Current learning rate: 0.00543 +2024-11-22 08:09:28.929143: train_loss -0.7884 +2024-11-22 08:09:28.929386: val_loss -0.7268 +2024-11-22 08:09:28.929468: Pseudo dice [0.8271] +2024-11-22 08:09:28.929553: Epoch time: 18.98 s +2024-11-22 08:09:29.827930: +2024-11-22 08:09:29.828125: Epoch 3938 +2024-11-22 08:09:29.828237: Current learning rate: 0.00543 +2024-11-22 08:09:48.866961: train_loss -0.7843 +2024-11-22 08:09:48.867190: val_loss -0.7361 +2024-11-22 08:09:48.867267: Pseudo dice [0.8261] +2024-11-22 08:09:48.867344: Epoch time: 19.04 s +2024-11-22 08:09:50.195443: +2024-11-22 08:09:50.195732: Epoch 3939 +2024-11-22 08:09:50.195843: Current learning rate: 0.00543 +2024-11-22 08:10:09.355508: train_loss -0.7656 +2024-11-22 08:10:09.355747: val_loss -0.7463 +2024-11-22 08:10:09.355825: Pseudo dice [0.8371] +2024-11-22 08:10:09.355904: Epoch time: 19.16 s +2024-11-22 08:10:10.246473: +2024-11-22 08:10:10.246698: Epoch 3940 +2024-11-22 08:10:10.246809: Current learning rate: 0.00543 +2024-11-22 08:10:28.803296: train_loss -0.773 +2024-11-22 08:10:28.803564: val_loss -0.7352 +2024-11-22 08:10:28.803638: Pseudo dice [0.8258] +2024-11-22 08:10:28.803724: Epoch time: 18.56 s +2024-11-22 08:10:29.722952: +2024-11-22 08:10:29.723188: Epoch 3941 +2024-11-22 08:10:29.723300: Current learning rate: 0.00543 +2024-11-22 08:10:47.315424: train_loss -0.7814 +2024-11-22 08:10:47.320974: val_loss -0.7331 +2024-11-22 08:10:47.321099: Pseudo dice [0.8202] +2024-11-22 08:10:47.321188: Epoch time: 17.59 s +2024-11-22 08:10:48.376204: +2024-11-22 08:10:48.376405: Epoch 3942 +2024-11-22 08:10:48.376518: Current learning rate: 0.00543 +2024-11-22 08:11:07.803093: train_loss -0.7762 +2024-11-22 08:11:07.803387: val_loss -0.7524 +2024-11-22 08:11:07.803466: Pseudo dice [0.8093] +2024-11-22 08:11:07.803542: Epoch time: 19.43 s +2024-11-22 08:11:08.698502: +2024-11-22 08:11:08.698719: Epoch 3943 +2024-11-22 08:11:08.698832: Current learning rate: 0.00543 +2024-11-22 08:11:26.735498: train_loss -0.7835 +2024-11-22 08:11:26.735708: val_loss -0.7386 +2024-11-22 08:11:26.735789: Pseudo dice [0.8153] +2024-11-22 08:11:26.735864: Epoch time: 18.04 s +2024-11-22 08:11:27.640105: +2024-11-22 08:11:27.640327: Epoch 3944 +2024-11-22 08:11:27.640444: Current learning rate: 0.00543 +2024-11-22 08:11:45.026509: train_loss -0.7885 +2024-11-22 08:11:45.026752: val_loss -0.7502 +2024-11-22 08:11:45.026827: Pseudo dice [0.8305] +2024-11-22 08:11:45.026921: Epoch time: 17.39 s +2024-11-22 08:11:45.915276: +2024-11-22 08:11:45.915486: Epoch 3945 +2024-11-22 08:11:45.915600: Current learning rate: 0.00543 +2024-11-22 08:12:04.745534: train_loss -0.7913 +2024-11-22 08:12:04.745754: val_loss -0.7463 +2024-11-22 08:12:04.745830: Pseudo dice [0.8124] +2024-11-22 08:12:04.745909: Epoch time: 18.83 s +2024-11-22 08:12:05.632877: +2024-11-22 08:12:05.633099: Epoch 3946 +2024-11-22 08:12:05.633226: Current learning rate: 0.00542 +2024-11-22 08:12:23.593189: train_loss -0.7925 +2024-11-22 08:12:23.593478: val_loss -0.7479 +2024-11-22 08:12:23.593558: Pseudo dice [0.8367] +2024-11-22 08:12:23.593636: Epoch time: 17.96 s +2024-11-22 08:12:24.484364: +2024-11-22 08:12:24.484559: Epoch 3947 +2024-11-22 08:12:24.484699: Current learning rate: 0.00542 +2024-11-22 08:12:42.797404: train_loss -0.7987 +2024-11-22 08:12:42.797627: val_loss -0.7631 +2024-11-22 08:12:42.797706: Pseudo dice [0.8243] +2024-11-22 08:12:42.797785: Epoch time: 18.31 s +2024-11-22 08:12:43.795142: +2024-11-22 08:12:43.795367: Epoch 3948 +2024-11-22 08:12:43.795480: Current learning rate: 0.00542 +2024-11-22 08:13:03.507409: train_loss -0.7933 +2024-11-22 08:13:03.509399: val_loss -0.7583 +2024-11-22 08:13:03.509505: Pseudo dice [0.8285] +2024-11-22 08:13:03.509623: Epoch time: 19.71 s +2024-11-22 08:13:04.417768: +2024-11-22 08:13:04.417962: Epoch 3949 +2024-11-22 08:13:04.418079: Current learning rate: 0.00542 +2024-11-22 08:13:23.206244: train_loss -0.7957 +2024-11-22 08:13:23.206453: val_loss -0.7406 +2024-11-22 08:13:23.206531: Pseudo dice [0.8327] +2024-11-22 08:13:23.206607: Epoch time: 18.79 s +2024-11-22 08:13:24.375003: +2024-11-22 08:13:24.375278: Epoch 3950 +2024-11-22 08:13:24.375501: Current learning rate: 0.00542 +2024-11-22 08:13:43.021909: train_loss -0.7946 +2024-11-22 08:13:43.022443: val_loss -0.7555 +2024-11-22 08:13:43.022539: Pseudo dice [0.8205] +2024-11-22 08:13:43.022619: Epoch time: 18.65 s +2024-11-22 08:13:43.912519: +2024-11-22 08:13:43.912738: Epoch 3951 +2024-11-22 08:13:43.912852: Current learning rate: 0.00542 +2024-11-22 08:14:02.211975: train_loss -0.7894 +2024-11-22 08:14:02.212231: val_loss -0.744 +2024-11-22 08:14:02.212308: Pseudo dice [0.8251] +2024-11-22 08:14:02.212391: Epoch time: 18.3 s +2024-11-22 08:14:03.103403: +2024-11-22 08:14:03.103632: Epoch 3952 +2024-11-22 08:14:03.103743: Current learning rate: 0.00542 +2024-11-22 08:14:21.906830: train_loss -0.7992 +2024-11-22 08:14:21.907083: val_loss -0.7709 +2024-11-22 08:14:21.907160: Pseudo dice [0.8414] +2024-11-22 08:14:21.907241: Epoch time: 18.8 s +2024-11-22 08:14:23.025015: +2024-11-22 08:14:23.025263: Epoch 3953 +2024-11-22 08:14:23.025375: Current learning rate: 0.00542 +2024-11-22 08:14:42.122077: train_loss -0.7945 +2024-11-22 08:14:42.122341: val_loss -0.728 +2024-11-22 08:14:42.122415: Pseudo dice [0.8153] +2024-11-22 08:14:42.122504: Epoch time: 19.1 s +2024-11-22 08:14:43.014079: +2024-11-22 08:14:43.014275: Epoch 3954 +2024-11-22 08:14:43.014385: Current learning rate: 0.00541 +2024-11-22 08:15:02.331640: train_loss -0.7998 +2024-11-22 08:15:02.331851: val_loss -0.739 +2024-11-22 08:15:02.331930: Pseudo dice [0.8159] +2024-11-22 08:15:02.332016: Epoch time: 19.32 s +2024-11-22 08:15:03.225762: +2024-11-22 08:15:03.225969: Epoch 3955 +2024-11-22 08:15:03.226089: Current learning rate: 0.00541 +2024-11-22 08:15:21.732345: train_loss -0.7884 +2024-11-22 08:15:21.732559: val_loss -0.7611 +2024-11-22 08:15:21.732636: Pseudo dice [0.8245] +2024-11-22 08:15:21.732723: Epoch time: 18.51 s +2024-11-22 08:15:22.629331: +2024-11-22 08:15:22.629616: Epoch 3956 +2024-11-22 08:15:22.629730: Current learning rate: 0.00541 +2024-11-22 08:15:41.662293: train_loss -0.7913 +2024-11-22 08:15:41.662514: val_loss -0.7736 +2024-11-22 08:15:41.662588: Pseudo dice [0.8487] +2024-11-22 08:15:41.662665: Epoch time: 19.03 s +2024-11-22 08:15:42.555936: +2024-11-22 08:15:42.556141: Epoch 3957 +2024-11-22 08:15:42.556251: Current learning rate: 0.00541 +2024-11-22 08:16:01.210381: train_loss -0.7848 +2024-11-22 08:16:01.210597: val_loss -0.7482 +2024-11-22 08:16:01.210671: Pseudo dice [0.8255] +2024-11-22 08:16:01.210745: Epoch time: 18.66 s +2024-11-22 08:16:02.102093: +2024-11-22 08:16:02.102324: Epoch 3958 +2024-11-22 08:16:02.102448: Current learning rate: 0.00541 +2024-11-22 08:16:20.855582: train_loss -0.7832 +2024-11-22 08:16:20.855864: val_loss -0.7355 +2024-11-22 08:16:20.855942: Pseudo dice [0.8298] +2024-11-22 08:16:20.856032: Epoch time: 18.75 s +2024-11-22 08:16:21.749451: +2024-11-22 08:16:21.749664: Epoch 3959 +2024-11-22 08:16:21.749774: Current learning rate: 0.00541 +2024-11-22 08:16:40.241862: train_loss -0.7882 +2024-11-22 08:16:40.242097: val_loss -0.7454 +2024-11-22 08:16:40.242174: Pseudo dice [0.8265] +2024-11-22 08:16:40.242249: Epoch time: 18.49 s +2024-11-22 08:16:41.188251: +2024-11-22 08:16:41.188454: Epoch 3960 +2024-11-22 08:16:41.188568: Current learning rate: 0.00541 +2024-11-22 08:16:59.397089: train_loss -0.7817 +2024-11-22 08:16:59.397308: val_loss -0.754 +2024-11-22 08:16:59.397384: Pseudo dice [0.8125] +2024-11-22 08:16:59.397465: Epoch time: 18.21 s +2024-11-22 08:17:00.293105: +2024-11-22 08:17:00.293350: Epoch 3961 +2024-11-22 08:17:00.293463: Current learning rate: 0.00541 +2024-11-22 08:17:17.805763: train_loss -0.7916 +2024-11-22 08:17:17.806324: val_loss -0.7557 +2024-11-22 08:17:17.806427: Pseudo dice [0.8282] +2024-11-22 08:17:17.806509: Epoch time: 17.51 s +2024-11-22 08:17:18.700426: +2024-11-22 08:17:18.700643: Epoch 3962 +2024-11-22 08:17:18.700761: Current learning rate: 0.0054 +2024-11-22 08:17:37.927172: train_loss -0.7936 +2024-11-22 08:17:37.927423: val_loss -0.756 +2024-11-22 08:17:37.927497: Pseudo dice [0.8413] +2024-11-22 08:17:37.927580: Epoch time: 19.23 s +2024-11-22 08:17:38.834818: +2024-11-22 08:17:38.835055: Epoch 3963 +2024-11-22 08:17:38.835171: Current learning rate: 0.0054 +2024-11-22 08:17:57.475113: train_loss -0.7936 +2024-11-22 08:17:57.480489: val_loss -0.7392 +2024-11-22 08:17:57.480674: Pseudo dice [0.8212] +2024-11-22 08:17:57.480761: Epoch time: 18.64 s +2024-11-22 08:17:58.388325: +2024-11-22 08:17:58.388539: Epoch 3964 +2024-11-22 08:17:58.388653: Current learning rate: 0.0054 +2024-11-22 08:18:15.763346: train_loss -0.7898 +2024-11-22 08:18:15.763579: val_loss -0.7266 +2024-11-22 08:18:15.763652: Pseudo dice [0.8212] +2024-11-22 08:18:15.763790: Epoch time: 17.38 s +2024-11-22 08:18:16.664372: +2024-11-22 08:18:16.664664: Epoch 3965 +2024-11-22 08:18:16.664777: Current learning rate: 0.0054 +2024-11-22 08:18:34.874965: train_loss -0.7979 +2024-11-22 08:18:34.875221: val_loss -0.7504 +2024-11-22 08:18:34.875301: Pseudo dice [0.8413] +2024-11-22 08:18:34.875406: Epoch time: 18.21 s +2024-11-22 08:18:35.768271: +2024-11-22 08:18:35.768495: Epoch 3966 +2024-11-22 08:18:35.768610: Current learning rate: 0.0054 +2024-11-22 08:18:55.648598: train_loss -0.798 +2024-11-22 08:18:55.648823: val_loss -0.7431 +2024-11-22 08:18:55.648908: Pseudo dice [0.8438] +2024-11-22 08:18:55.649020: Epoch time: 19.88 s +2024-11-22 08:18:56.541111: +2024-11-22 08:18:56.541307: Epoch 3967 +2024-11-22 08:18:56.541423: Current learning rate: 0.0054 +2024-11-22 08:19:14.950579: train_loss -0.7981 +2024-11-22 08:19:14.950811: val_loss -0.747 +2024-11-22 08:19:14.950886: Pseudo dice [0.8224] +2024-11-22 08:19:14.950963: Epoch time: 18.41 s +2024-11-22 08:19:15.846218: +2024-11-22 08:19:15.846425: Epoch 3968 +2024-11-22 08:19:15.846535: Current learning rate: 0.0054 +2024-11-22 08:19:35.493484: train_loss -0.7892 +2024-11-22 08:19:35.495545: val_loss -0.7508 +2024-11-22 08:19:35.495641: Pseudo dice [0.8182] +2024-11-22 08:19:35.495720: Epoch time: 19.65 s +2024-11-22 08:19:36.396193: +2024-11-22 08:19:36.396402: Epoch 3969 +2024-11-22 08:19:36.396530: Current learning rate: 0.0054 +2024-11-22 08:19:55.490278: train_loss -0.7845 +2024-11-22 08:19:55.492714: val_loss -0.7632 +2024-11-22 08:19:55.492803: Pseudo dice [0.8334] +2024-11-22 08:19:55.492889: Epoch time: 19.1 s +2024-11-22 08:19:56.457716: +2024-11-22 08:19:56.457945: Epoch 3970 +2024-11-22 08:19:56.458066: Current learning rate: 0.0054 +2024-11-22 08:20:14.968140: train_loss -0.7838 +2024-11-22 08:20:14.968353: val_loss -0.7435 +2024-11-22 08:20:14.968427: Pseudo dice [0.8382] +2024-11-22 08:20:14.968507: Epoch time: 18.51 s +2024-11-22 08:20:15.898384: +2024-11-22 08:20:15.898586: Epoch 3971 +2024-11-22 08:20:15.898699: Current learning rate: 0.00539 +2024-11-22 08:20:33.974934: train_loss -0.788 +2024-11-22 08:20:33.975162: val_loss -0.72 +2024-11-22 08:20:33.975239: Pseudo dice [0.8204] +2024-11-22 08:20:33.975319: Epoch time: 18.08 s +2024-11-22 08:20:35.216899: +2024-11-22 08:20:35.217124: Epoch 3972 +2024-11-22 08:20:35.217233: Current learning rate: 0.00539 +2024-11-22 08:20:54.252087: train_loss -0.786 +2024-11-22 08:20:54.252348: val_loss -0.7591 +2024-11-22 08:20:54.252422: Pseudo dice [0.8472] +2024-11-22 08:20:54.252504: Epoch time: 19.04 s +2024-11-22 08:20:55.146131: +2024-11-22 08:20:55.146362: Epoch 3973 +2024-11-22 08:20:55.146478: Current learning rate: 0.00539 +2024-11-22 08:21:13.810319: train_loss -0.7864 +2024-11-22 08:21:13.810536: val_loss -0.732 +2024-11-22 08:21:13.811287: Pseudo dice [0.802] +2024-11-22 08:21:13.811376: Epoch time: 18.66 s +2024-11-22 08:21:14.700418: +2024-11-22 08:21:14.700796: Epoch 3974 +2024-11-22 08:21:14.700913: Current learning rate: 0.00539 +2024-11-22 08:21:34.341359: train_loss -0.7832 +2024-11-22 08:21:34.341584: val_loss -0.7471 +2024-11-22 08:21:34.341717: Pseudo dice [0.8297] +2024-11-22 08:21:34.341795: Epoch time: 19.64 s +2024-11-22 08:21:35.234833: +2024-11-22 08:21:35.235058: Epoch 3975 +2024-11-22 08:21:35.235170: Current learning rate: 0.00539 +2024-11-22 08:21:53.698312: train_loss -0.7808 +2024-11-22 08:21:53.698574: val_loss -0.7399 +2024-11-22 08:21:53.698651: Pseudo dice [0.8244] +2024-11-22 08:21:53.698740: Epoch time: 18.46 s +2024-11-22 08:21:54.637866: +2024-11-22 08:21:54.638085: Epoch 3976 +2024-11-22 08:21:54.638641: Current learning rate: 0.00539 +2024-11-22 08:22:13.364396: train_loss -0.7903 +2024-11-22 08:22:13.364622: val_loss -0.7292 +2024-11-22 08:22:13.364702: Pseudo dice [0.8171] +2024-11-22 08:22:13.364782: Epoch time: 18.73 s +2024-11-22 08:22:14.253518: +2024-11-22 08:22:14.253734: Epoch 3977 +2024-11-22 08:22:14.253851: Current learning rate: 0.00539 +2024-11-22 08:22:32.924211: train_loss -0.775 +2024-11-22 08:22:32.924427: val_loss -0.7506 +2024-11-22 08:22:32.924503: Pseudo dice [0.8276] +2024-11-22 08:22:32.924635: Epoch time: 18.67 s +2024-11-22 08:22:33.925700: +2024-11-22 08:22:33.926058: Epoch 3978 +2024-11-22 08:22:33.926170: Current learning rate: 0.00539 +2024-11-22 08:22:52.410114: train_loss -0.7716 +2024-11-22 08:22:52.410335: val_loss -0.7453 +2024-11-22 08:22:52.410408: Pseudo dice [0.8244] +2024-11-22 08:22:52.410484: Epoch time: 18.49 s +2024-11-22 08:22:53.304604: +2024-11-22 08:22:53.304835: Epoch 3979 +2024-11-22 08:22:53.304954: Current learning rate: 0.00538 +2024-11-22 08:23:11.399116: train_loss -0.7797 +2024-11-22 08:23:11.399364: val_loss -0.7518 +2024-11-22 08:23:11.399437: Pseudo dice [0.8207] +2024-11-22 08:23:11.399518: Epoch time: 18.1 s +2024-11-22 08:23:12.296276: +2024-11-22 08:23:12.296481: Epoch 3980 +2024-11-22 08:23:12.296594: Current learning rate: 0.00538 +2024-11-22 08:23:30.663377: train_loss -0.7759 +2024-11-22 08:23:30.663645: val_loss -0.7552 +2024-11-22 08:23:30.663722: Pseudo dice [0.813] +2024-11-22 08:23:30.663800: Epoch time: 18.37 s +2024-11-22 08:23:31.608729: +2024-11-22 08:23:31.608928: Epoch 3981 +2024-11-22 08:23:31.609042: Current learning rate: 0.00538 +2024-11-22 08:23:50.072434: train_loss -0.7697 +2024-11-22 08:23:50.072654: val_loss -0.718 +2024-11-22 08:23:50.072730: Pseudo dice [0.817] +2024-11-22 08:23:50.072807: Epoch time: 18.46 s +2024-11-22 08:23:50.963868: +2024-11-22 08:23:50.964134: Epoch 3982 +2024-11-22 08:23:50.964247: Current learning rate: 0.00538 +2024-11-22 08:24:09.092296: train_loss -0.7809 +2024-11-22 08:24:09.092540: val_loss -0.7151 +2024-11-22 08:24:09.092636: Pseudo dice [0.7959] +2024-11-22 08:24:09.092722: Epoch time: 18.13 s +2024-11-22 08:24:09.995885: +2024-11-22 08:24:09.996085: Epoch 3983 +2024-11-22 08:24:09.996197: Current learning rate: 0.00538 +2024-11-22 08:24:28.419784: train_loss -0.7906 +2024-11-22 08:24:28.420005: val_loss -0.7572 +2024-11-22 08:24:28.420082: Pseudo dice [0.8274] +2024-11-22 08:24:28.420160: Epoch time: 18.42 s +2024-11-22 08:24:29.749851: +2024-11-22 08:24:29.750069: Epoch 3984 +2024-11-22 08:24:29.750181: Current learning rate: 0.00538 +2024-11-22 08:24:47.772095: train_loss -0.7938 +2024-11-22 08:24:47.772324: val_loss -0.7388 +2024-11-22 08:24:47.772399: Pseudo dice [0.8294] +2024-11-22 08:24:47.772474: Epoch time: 18.02 s +2024-11-22 08:24:48.674884: +2024-11-22 08:24:48.675100: Epoch 3985 +2024-11-22 08:24:48.675214: Current learning rate: 0.00538 +2024-11-22 08:25:06.764414: train_loss -0.7884 +2024-11-22 08:25:06.764658: val_loss -0.7398 +2024-11-22 08:25:06.764736: Pseudo dice [0.8199] +2024-11-22 08:25:06.764822: Epoch time: 18.09 s +2024-11-22 08:25:07.685296: +2024-11-22 08:25:07.685675: Epoch 3986 +2024-11-22 08:25:07.685785: Current learning rate: 0.00538 +2024-11-22 08:25:27.543953: train_loss -0.7851 +2024-11-22 08:25:27.544173: val_loss -0.7114 +2024-11-22 08:25:27.544307: Pseudo dice [0.8147] +2024-11-22 08:25:27.544384: Epoch time: 19.86 s +2024-11-22 08:25:28.438651: +2024-11-22 08:25:28.438880: Epoch 3987 +2024-11-22 08:25:28.438997: Current learning rate: 0.00537 +2024-11-22 08:25:47.692794: train_loss -0.7764 +2024-11-22 08:25:47.693014: val_loss -0.7371 +2024-11-22 08:25:47.693090: Pseudo dice [0.8118] +2024-11-22 08:25:47.693168: Epoch time: 19.25 s +2024-11-22 08:25:48.739002: +2024-11-22 08:25:48.739237: Epoch 3988 +2024-11-22 08:25:48.739345: Current learning rate: 0.00537 +2024-11-22 08:26:07.324700: train_loss -0.7801 +2024-11-22 08:26:07.324908: val_loss -0.7595 +2024-11-22 08:26:07.324982: Pseudo dice [0.8157] +2024-11-22 08:26:07.325066: Epoch time: 18.59 s +2024-11-22 08:26:08.222756: +2024-11-22 08:26:08.223043: Epoch 3989 +2024-11-22 08:26:08.223172: Current learning rate: 0.00537 +2024-11-22 08:26:26.444445: train_loss -0.7921 +2024-11-22 08:26:26.444733: val_loss -0.7317 +2024-11-22 08:26:26.444815: Pseudo dice [0.8243] +2024-11-22 08:26:26.444896: Epoch time: 18.22 s +2024-11-22 08:26:27.344849: +2024-11-22 08:26:27.345144: Epoch 3990 +2024-11-22 08:26:27.345266: Current learning rate: 0.00537 +2024-11-22 08:26:44.868700: train_loss -0.7893 +2024-11-22 08:26:44.868954: val_loss -0.7432 +2024-11-22 08:26:44.869038: Pseudo dice [0.8219] +2024-11-22 08:26:44.869123: Epoch time: 17.52 s +2024-11-22 08:26:45.852816: +2024-11-22 08:26:45.853061: Epoch 3991 +2024-11-22 08:26:45.853179: Current learning rate: 0.00537 +2024-11-22 08:27:05.202027: train_loss -0.7989 +2024-11-22 08:27:05.202245: val_loss -0.7603 +2024-11-22 08:27:05.202321: Pseudo dice [0.8321] +2024-11-22 08:27:05.202399: Epoch time: 19.35 s +2024-11-22 08:27:06.101010: +2024-11-22 08:27:06.101207: Epoch 3992 +2024-11-22 08:27:06.101324: Current learning rate: 0.00537 +2024-11-22 08:27:25.488788: train_loss -0.785 +2024-11-22 08:27:25.489021: val_loss -0.7543 +2024-11-22 08:27:25.489094: Pseudo dice [0.8111] +2024-11-22 08:27:25.489170: Epoch time: 19.39 s +2024-11-22 08:27:26.451031: +2024-11-22 08:27:26.451254: Epoch 3993 +2024-11-22 08:27:26.451364: Current learning rate: 0.00537 +2024-11-22 08:27:44.266627: train_loss -0.7916 +2024-11-22 08:27:44.266909: val_loss -0.7442 +2024-11-22 08:27:44.267037: Pseudo dice [0.8331] +2024-11-22 08:27:44.267140: Epoch time: 17.82 s +2024-11-22 08:27:45.180010: +2024-11-22 08:27:45.180206: Epoch 3994 +2024-11-22 08:27:45.180320: Current learning rate: 0.00537 +2024-11-22 08:28:04.410944: train_loss -0.7929 +2024-11-22 08:28:04.411169: val_loss -0.7496 +2024-11-22 08:28:04.411242: Pseudo dice [0.8226] +2024-11-22 08:28:04.411319: Epoch time: 19.23 s +2024-11-22 08:28:05.675692: +2024-11-22 08:28:05.675911: Epoch 3995 +2024-11-22 08:28:05.676025: Current learning rate: 0.00536 +2024-11-22 08:28:24.271301: train_loss -0.7862 +2024-11-22 08:28:24.273703: val_loss -0.7447 +2024-11-22 08:28:24.273825: Pseudo dice [0.8281] +2024-11-22 08:28:24.273909: Epoch time: 18.6 s +2024-11-22 08:28:25.325580: +2024-11-22 08:28:25.325811: Epoch 3996 +2024-11-22 08:28:25.325921: Current learning rate: 0.00536 +2024-11-22 08:28:44.548854: train_loss -0.7803 +2024-11-22 08:28:44.549109: val_loss -0.7507 +2024-11-22 08:28:44.549186: Pseudo dice [0.8292] +2024-11-22 08:28:44.549268: Epoch time: 19.22 s +2024-11-22 08:28:45.444026: +2024-11-22 08:28:45.444276: Epoch 3997 +2024-11-22 08:28:45.444394: Current learning rate: 0.00536 +2024-11-22 08:29:03.888403: train_loss -0.7891 +2024-11-22 08:29:03.888623: val_loss -0.745 +2024-11-22 08:29:03.888696: Pseudo dice [0.8366] +2024-11-22 08:29:03.888771: Epoch time: 18.45 s +2024-11-22 08:29:04.851178: +2024-11-22 08:29:04.851409: Epoch 3998 +2024-11-22 08:29:04.851525: Current learning rate: 0.00536 +2024-11-22 08:29:22.691124: train_loss -0.7942 +2024-11-22 08:29:22.691347: val_loss -0.7473 +2024-11-22 08:29:22.691432: Pseudo dice [0.8147] +2024-11-22 08:29:22.691511: Epoch time: 17.84 s +2024-11-22 08:29:23.584234: +2024-11-22 08:29:23.585042: Epoch 3999 +2024-11-22 08:29:23.585157: Current learning rate: 0.00536 +2024-11-22 08:29:41.410868: train_loss -0.7847 +2024-11-22 08:29:41.411085: val_loss -0.7377 +2024-11-22 08:29:41.411161: Pseudo dice [0.8343] +2024-11-22 08:29:41.411244: Epoch time: 17.83 s +2024-11-22 08:29:42.553642: +2024-11-22 08:29:42.553846: Epoch 4000 +2024-11-22 08:29:42.553959: Current learning rate: 0.00536 +2024-11-22 08:30:01.316419: train_loss -0.7859 +2024-11-22 08:30:01.316689: val_loss -0.7463 +2024-11-22 08:30:01.316765: Pseudo dice [0.8181] +2024-11-22 08:30:01.316850: Epoch time: 18.76 s +2024-11-22 08:30:02.303147: +2024-11-22 08:30:02.303354: Epoch 4001 +2024-11-22 08:30:02.303465: Current learning rate: 0.00536 +2024-11-22 08:30:20.823772: train_loss -0.787 +2024-11-22 08:30:20.824051: val_loss -0.7759 +2024-11-22 08:30:20.824128: Pseudo dice [0.8303] +2024-11-22 08:30:20.824203: Epoch time: 18.52 s +2024-11-22 08:30:21.719475: +2024-11-22 08:30:21.719813: Epoch 4002 +2024-11-22 08:30:21.719936: Current learning rate: 0.00536 +2024-11-22 08:30:40.418181: train_loss -0.7931 +2024-11-22 08:30:40.418414: val_loss -0.7598 +2024-11-22 08:30:40.418490: Pseudo dice [0.8455] +2024-11-22 08:30:40.418571: Epoch time: 18.7 s +2024-11-22 08:30:41.313061: +2024-11-22 08:30:41.313258: Epoch 4003 +2024-11-22 08:30:41.313368: Current learning rate: 0.00536 +2024-11-22 08:30:59.246135: train_loss -0.7868 +2024-11-22 08:30:59.246350: val_loss -0.7326 +2024-11-22 08:30:59.246425: Pseudo dice [0.8217] +2024-11-22 08:30:59.246505: Epoch time: 17.93 s +2024-11-22 08:31:00.138351: +2024-11-22 08:31:00.138619: Epoch 4004 +2024-11-22 08:31:00.138731: Current learning rate: 0.00535 +2024-11-22 08:31:19.857645: train_loss -0.7904 +2024-11-22 08:31:19.857880: val_loss -0.7439 +2024-11-22 08:31:19.857956: Pseudo dice [0.8065] +2024-11-22 08:31:19.858044: Epoch time: 19.72 s +2024-11-22 08:31:20.770996: +2024-11-22 08:31:20.771194: Epoch 4005 +2024-11-22 08:31:20.771307: Current learning rate: 0.00535 +2024-11-22 08:31:39.636803: train_loss -0.7922 +2024-11-22 08:31:39.637026: val_loss -0.759 +2024-11-22 08:31:39.637103: Pseudo dice [0.8221] +2024-11-22 08:31:39.637182: Epoch time: 18.87 s +2024-11-22 08:31:40.922940: +2024-11-22 08:31:40.923182: Epoch 4006 +2024-11-22 08:31:40.923294: Current learning rate: 0.00535 +2024-11-22 08:31:59.730645: train_loss -0.7796 +2024-11-22 08:31:59.730909: val_loss -0.7395 +2024-11-22 08:31:59.731001: Pseudo dice [0.8195] +2024-11-22 08:31:59.731090: Epoch time: 18.81 s +2024-11-22 08:32:00.629774: +2024-11-22 08:32:00.630029: Epoch 4007 +2024-11-22 08:32:00.630145: Current learning rate: 0.00535 +2024-11-22 08:32:18.568973: train_loss -0.7727 +2024-11-22 08:32:18.569203: val_loss -0.7328 +2024-11-22 08:32:18.569276: Pseudo dice [0.8195] +2024-11-22 08:32:18.569350: Epoch time: 17.94 s +2024-11-22 08:32:19.460028: +2024-11-22 08:32:19.460273: Epoch 4008 +2024-11-22 08:32:19.460391: Current learning rate: 0.00535 +2024-11-22 08:32:38.409904: train_loss -0.7856 +2024-11-22 08:32:38.410131: val_loss -0.7607 +2024-11-22 08:32:38.410208: Pseudo dice [0.8215] +2024-11-22 08:32:38.410310: Epoch time: 18.95 s +2024-11-22 08:32:39.306540: +2024-11-22 08:32:39.306801: Epoch 4009 +2024-11-22 08:32:39.306919: Current learning rate: 0.00535 +2024-11-22 08:32:58.719369: train_loss -0.7697 +2024-11-22 08:32:58.719594: val_loss -0.7611 +2024-11-22 08:32:58.719673: Pseudo dice [0.8205] +2024-11-22 08:32:58.719751: Epoch time: 19.41 s +2024-11-22 08:32:59.608359: +2024-11-22 08:32:59.608592: Epoch 4010 +2024-11-22 08:32:59.608709: Current learning rate: 0.00535 +2024-11-22 08:33:19.221222: train_loss -0.7736 +2024-11-22 08:33:19.221463: val_loss -0.7641 +2024-11-22 08:33:19.221537: Pseudo dice [0.8377] +2024-11-22 08:33:19.221622: Epoch time: 19.61 s +2024-11-22 08:33:20.123764: +2024-11-22 08:33:20.123977: Epoch 4011 +2024-11-22 08:33:20.124100: Current learning rate: 0.00535 +2024-11-22 08:33:38.273241: train_loss -0.7645 +2024-11-22 08:33:38.273471: val_loss -0.7286 +2024-11-22 08:33:38.273547: Pseudo dice [0.8151] +2024-11-22 08:33:38.273868: Epoch time: 18.15 s +2024-11-22 08:33:39.166442: +2024-11-22 08:33:39.166770: Epoch 4012 +2024-11-22 08:33:39.166886: Current learning rate: 0.00534 +2024-11-22 08:33:58.329052: train_loss -0.766 +2024-11-22 08:33:58.329272: val_loss -0.7318 +2024-11-22 08:33:58.329347: Pseudo dice [0.8264] +2024-11-22 08:33:58.329424: Epoch time: 19.16 s +2024-11-22 08:33:59.223773: +2024-11-22 08:33:59.223977: Epoch 4013 +2024-11-22 08:33:59.224093: Current learning rate: 0.00534 +2024-11-22 08:34:18.142802: train_loss -0.7773 +2024-11-22 08:34:18.143101: val_loss -0.7514 +2024-11-22 08:34:18.143177: Pseudo dice [0.8423] +2024-11-22 08:34:18.143266: Epoch time: 18.92 s +2024-11-22 08:34:19.143547: +2024-11-22 08:34:19.143756: Epoch 4014 +2024-11-22 08:34:19.143872: Current learning rate: 0.00534 +2024-11-22 08:34:37.313013: train_loss -0.7741 +2024-11-22 08:34:37.313233: val_loss -0.7564 +2024-11-22 08:34:37.313372: Pseudo dice [0.8163] +2024-11-22 08:34:37.313451: Epoch time: 18.17 s +2024-11-22 08:34:38.207717: +2024-11-22 08:34:38.207916: Epoch 4015 +2024-11-22 08:34:38.208043: Current learning rate: 0.00534 +2024-11-22 08:34:57.379802: train_loss -0.7823 +2024-11-22 08:34:57.380076: val_loss -0.7448 +2024-11-22 08:34:57.380154: Pseudo dice [0.8413] +2024-11-22 08:34:57.380240: Epoch time: 19.17 s +2024-11-22 08:34:58.275502: +2024-11-22 08:34:58.275719: Epoch 4016 +2024-11-22 08:34:58.275834: Current learning rate: 0.00534 +2024-11-22 08:35:17.062923: train_loss -0.7836 +2024-11-22 08:35:17.063161: val_loss -0.7509 +2024-11-22 08:35:17.063237: Pseudo dice [0.8278] +2024-11-22 08:35:17.068462: Epoch time: 18.79 s +2024-11-22 08:35:18.158536: +2024-11-22 08:35:18.158735: Epoch 4017 +2024-11-22 08:35:18.158870: Current learning rate: 0.00534 +2024-11-22 08:35:37.145823: train_loss -0.7677 +2024-11-22 08:35:37.146067: val_loss -0.7404 +2024-11-22 08:35:37.146143: Pseudo dice [0.8233] +2024-11-22 08:35:37.146225: Epoch time: 18.99 s +2024-11-22 08:35:38.420576: +2024-11-22 08:35:38.420875: Epoch 4018 +2024-11-22 08:35:38.420988: Current learning rate: 0.00534 +2024-11-22 08:35:57.434108: train_loss -0.7814 +2024-11-22 08:35:57.434330: val_loss -0.7706 +2024-11-22 08:35:57.434405: Pseudo dice [0.845] +2024-11-22 08:35:57.434479: Epoch time: 19.01 s +2024-11-22 08:35:58.335294: +2024-11-22 08:35:58.335518: Epoch 4019 +2024-11-22 08:35:58.335632: Current learning rate: 0.00534 +2024-11-22 08:36:16.065631: train_loss -0.7832 +2024-11-22 08:36:16.065853: val_loss -0.7622 +2024-11-22 08:36:16.065932: Pseudo dice [0.8418] +2024-11-22 08:36:16.066018: Epoch time: 17.73 s +2024-11-22 08:36:16.978569: +2024-11-22 08:36:16.978956: Epoch 4020 +2024-11-22 08:36:16.979073: Current learning rate: 0.00533 +2024-11-22 08:36:36.194519: train_loss -0.7848 +2024-11-22 08:36:36.194752: val_loss -0.751 +2024-11-22 08:36:36.194830: Pseudo dice [0.8087] +2024-11-22 08:36:36.194918: Epoch time: 19.22 s +2024-11-22 08:36:37.088851: +2024-11-22 08:36:37.089159: Epoch 4021 +2024-11-22 08:36:37.089274: Current learning rate: 0.00533 +2024-11-22 08:36:56.290386: train_loss -0.7865 +2024-11-22 08:36:56.293601: val_loss -0.7553 +2024-11-22 08:36:56.293681: Pseudo dice [0.8283] +2024-11-22 08:36:56.293761: Epoch time: 19.2 s +2024-11-22 08:36:57.214724: +2024-11-22 08:36:57.214947: Epoch 4022 +2024-11-22 08:36:57.215075: Current learning rate: 0.00533 +2024-11-22 08:37:15.316540: train_loss -0.8027 +2024-11-22 08:37:15.316850: val_loss -0.7298 +2024-11-22 08:37:15.316928: Pseudo dice [0.8233] +2024-11-22 08:37:15.317014: Epoch time: 18.1 s +2024-11-22 08:37:16.211366: +2024-11-22 08:37:16.211586: Epoch 4023 +2024-11-22 08:37:16.211705: Current learning rate: 0.00533 +2024-11-22 08:37:34.715545: train_loss -0.7894 +2024-11-22 08:37:34.715762: val_loss -0.7436 +2024-11-22 08:37:34.715842: Pseudo dice [0.8331] +2024-11-22 08:37:34.715919: Epoch time: 18.5 s +2024-11-22 08:37:35.822971: +2024-11-22 08:37:35.823249: Epoch 4024 +2024-11-22 08:37:35.823359: Current learning rate: 0.00533 +2024-11-22 08:37:55.315191: train_loss -0.7813 +2024-11-22 08:37:55.332924: val_loss -0.7668 +2024-11-22 08:37:55.333089: Pseudo dice [0.8457] +2024-11-22 08:37:55.333189: Epoch time: 19.49 s +2024-11-22 08:37:56.237608: +2024-11-22 08:37:56.237826: Epoch 4025 +2024-11-22 08:37:56.237943: Current learning rate: 0.00533 +2024-11-22 08:38:14.978080: train_loss -0.7855 +2024-11-22 08:38:14.978323: val_loss -0.7375 +2024-11-22 08:38:14.978402: Pseudo dice [0.8272] +2024-11-22 08:38:14.978484: Epoch time: 18.74 s +2024-11-22 08:38:15.945753: +2024-11-22 08:38:15.945948: Epoch 4026 +2024-11-22 08:38:15.946063: Current learning rate: 0.00533 +2024-11-22 08:38:35.111345: train_loss -0.7888 +2024-11-22 08:38:35.111562: val_loss -0.6998 +2024-11-22 08:38:35.111635: Pseudo dice [0.8127] +2024-11-22 08:38:35.111711: Epoch time: 19.17 s +2024-11-22 08:38:36.004262: +2024-11-22 08:38:36.004467: Epoch 4027 +2024-11-22 08:38:36.004579: Current learning rate: 0.00533 +2024-11-22 08:38:54.430830: train_loss -0.7943 +2024-11-22 08:38:54.431152: val_loss -0.7246 +2024-11-22 08:38:54.431262: Pseudo dice [0.8106] +2024-11-22 08:38:54.431345: Epoch time: 18.43 s +2024-11-22 08:38:55.331515: +2024-11-22 08:38:55.331753: Epoch 4028 +2024-11-22 08:38:55.331909: Current learning rate: 0.00533 +2024-11-22 08:39:14.607055: train_loss -0.7939 +2024-11-22 08:39:14.621273: val_loss -0.738 +2024-11-22 08:39:14.621365: Pseudo dice [0.8423] +2024-11-22 08:39:14.621448: Epoch time: 19.28 s +2024-11-22 08:39:15.951655: +2024-11-22 08:39:15.951939: Epoch 4029 +2024-11-22 08:39:15.952068: Current learning rate: 0.00532 +2024-11-22 08:39:34.152625: train_loss -0.7772 +2024-11-22 08:39:34.152854: val_loss -0.743 +2024-11-22 08:39:34.152941: Pseudo dice [0.8316] +2024-11-22 08:39:34.153023: Epoch time: 18.2 s +2024-11-22 08:39:35.060111: +2024-11-22 08:39:35.060360: Epoch 4030 +2024-11-22 08:39:35.060475: Current learning rate: 0.00532 +2024-11-22 08:39:53.695228: train_loss -0.7753 +2024-11-22 08:39:53.695442: val_loss -0.7322 +2024-11-22 08:39:53.695559: Pseudo dice [0.805] +2024-11-22 08:39:53.695648: Epoch time: 18.64 s +2024-11-22 08:39:54.593494: +2024-11-22 08:39:54.593736: Epoch 4031 +2024-11-22 08:39:54.593853: Current learning rate: 0.00532 +2024-11-22 08:40:13.791233: train_loss -0.7773 +2024-11-22 08:40:13.791513: val_loss -0.7231 +2024-11-22 08:40:13.791591: Pseudo dice [0.8128] +2024-11-22 08:40:13.791678: Epoch time: 19.2 s +2024-11-22 08:40:14.693200: +2024-11-22 08:40:14.693409: Epoch 4032 +2024-11-22 08:40:14.693521: Current learning rate: 0.00532 +2024-11-22 08:40:33.365129: train_loss -0.7794 +2024-11-22 08:40:33.365379: val_loss -0.7487 +2024-11-22 08:40:33.365456: Pseudo dice [0.8399] +2024-11-22 08:40:33.365535: Epoch time: 18.67 s +2024-11-22 08:40:34.261667: +2024-11-22 08:40:34.261925: Epoch 4033 +2024-11-22 08:40:34.262069: Current learning rate: 0.00532 +2024-11-22 08:40:53.464145: train_loss -0.7854 +2024-11-22 08:40:53.464385: val_loss -0.7434 +2024-11-22 08:40:53.464459: Pseudo dice [0.8283] +2024-11-22 08:40:53.464538: Epoch time: 19.2 s +2024-11-22 08:40:54.560050: +2024-11-22 08:40:54.560284: Epoch 4034 +2024-11-22 08:40:54.560402: Current learning rate: 0.00532 +2024-11-22 08:41:12.972333: train_loss -0.7804 +2024-11-22 08:41:12.974714: val_loss -0.754 +2024-11-22 08:41:12.974840: Pseudo dice [0.8435] +2024-11-22 08:41:12.974927: Epoch time: 18.41 s +2024-11-22 08:41:13.887953: +2024-11-22 08:41:13.888174: Epoch 4035 +2024-11-22 08:41:13.888285: Current learning rate: 0.00532 +2024-11-22 08:41:32.682566: train_loss -0.7722 +2024-11-22 08:41:32.682813: val_loss -0.7342 +2024-11-22 08:41:32.682893: Pseudo dice [0.8174] +2024-11-22 08:41:32.682986: Epoch time: 18.8 s +2024-11-22 08:41:33.574361: +2024-11-22 08:41:33.574570: Epoch 4036 +2024-11-22 08:41:33.574684: Current learning rate: 0.00532 +2024-11-22 08:41:52.861940: train_loss -0.7852 +2024-11-22 08:41:52.862160: val_loss -0.7432 +2024-11-22 08:41:52.862236: Pseudo dice [0.8175] +2024-11-22 08:41:52.862311: Epoch time: 19.29 s +2024-11-22 08:41:53.757748: +2024-11-22 08:41:53.757942: Epoch 4037 +2024-11-22 08:41:53.785236: Current learning rate: 0.00531 +2024-11-22 08:42:12.420956: train_loss -0.7884 +2024-11-22 08:42:12.421184: val_loss -0.7724 +2024-11-22 08:42:12.421262: Pseudo dice [0.8268] +2024-11-22 08:42:12.421342: Epoch time: 18.66 s +2024-11-22 08:42:13.481566: +2024-11-22 08:42:13.481808: Epoch 4038 +2024-11-22 08:42:13.481925: Current learning rate: 0.00531 +2024-11-22 08:42:32.359444: train_loss -0.7845 +2024-11-22 08:42:32.359689: val_loss -0.7253 +2024-11-22 08:42:32.359791: Pseudo dice [0.8192] +2024-11-22 08:42:32.359893: Epoch time: 18.88 s +2024-11-22 08:42:33.253551: +2024-11-22 08:42:33.253760: Epoch 4039 +2024-11-22 08:42:33.253877: Current learning rate: 0.00531 +2024-11-22 08:42:52.098663: train_loss -0.7911 +2024-11-22 08:42:52.098871: val_loss -0.686 +2024-11-22 08:42:52.098944: Pseudo dice [0.8033] +2024-11-22 08:42:52.099027: Epoch time: 18.85 s +2024-11-22 08:42:52.991627: +2024-11-22 08:42:52.991826: Epoch 4040 +2024-11-22 08:42:52.991937: Current learning rate: 0.00531 +2024-11-22 08:43:11.036982: train_loss -0.7872 +2024-11-22 08:43:11.037227: val_loss -0.7197 +2024-11-22 08:43:11.037315: Pseudo dice [0.8293] +2024-11-22 08:43:11.037416: Epoch time: 18.05 s +2024-11-22 08:43:12.314456: +2024-11-22 08:43:12.314751: Epoch 4041 +2024-11-22 08:43:12.314863: Current learning rate: 0.00531 +2024-11-22 08:43:30.590961: train_loss -0.7942 +2024-11-22 08:43:30.591218: val_loss -0.743 +2024-11-22 08:43:30.591299: Pseudo dice [0.8178] +2024-11-22 08:43:30.591383: Epoch time: 18.28 s +2024-11-22 08:43:31.484345: +2024-11-22 08:43:31.484554: Epoch 4042 +2024-11-22 08:43:31.484665: Current learning rate: 0.00531 +2024-11-22 08:43:51.105777: train_loss -0.79 +2024-11-22 08:43:51.106004: val_loss -0.7326 +2024-11-22 08:43:51.106081: Pseudo dice [0.8206] +2024-11-22 08:43:51.106156: Epoch time: 19.62 s +2024-11-22 08:43:52.000765: +2024-11-22 08:43:52.000987: Epoch 4043 +2024-11-22 08:43:52.001104: Current learning rate: 0.00531 +2024-11-22 08:44:09.588611: train_loss -0.7968 +2024-11-22 08:44:09.591021: val_loss -0.7519 +2024-11-22 08:44:09.591115: Pseudo dice [0.8394] +2024-11-22 08:44:09.591191: Epoch time: 17.59 s +2024-11-22 08:44:10.506637: +2024-11-22 08:44:10.506853: Epoch 4044 +2024-11-22 08:44:10.506968: Current learning rate: 0.00531 +2024-11-22 08:44:28.727911: train_loss -0.7903 +2024-11-22 08:44:28.728142: val_loss -0.7072 +2024-11-22 08:44:28.728221: Pseudo dice [0.8253] +2024-11-22 08:44:28.728305: Epoch time: 18.22 s +2024-11-22 08:44:29.623241: +2024-11-22 08:44:29.623450: Epoch 4045 +2024-11-22 08:44:29.623565: Current learning rate: 0.0053 +2024-11-22 08:44:49.408800: train_loss -0.788 +2024-11-22 08:44:49.409040: val_loss -0.7711 +2024-11-22 08:44:49.409114: Pseudo dice [0.8432] +2024-11-22 08:44:49.411408: Epoch time: 19.79 s +2024-11-22 08:44:50.459129: +2024-11-22 08:44:50.459372: Epoch 4046 +2024-11-22 08:44:50.459486: Current learning rate: 0.0053 +2024-11-22 08:45:10.620963: train_loss -0.7945 +2024-11-22 08:45:10.621188: val_loss -0.7576 +2024-11-22 08:45:10.621261: Pseudo dice [0.8389] +2024-11-22 08:45:10.621338: Epoch time: 20.16 s +2024-11-22 08:45:11.514677: +2024-11-22 08:45:11.514895: Epoch 4047 +2024-11-22 08:45:11.515017: Current learning rate: 0.0053 +2024-11-22 08:45:29.562578: train_loss -0.7908 +2024-11-22 08:45:29.562798: val_loss -0.7082 +2024-11-22 08:45:29.562871: Pseudo dice [0.8093] +2024-11-22 08:45:29.562945: Epoch time: 18.05 s +2024-11-22 08:45:30.456060: +2024-11-22 08:45:30.456297: Epoch 4048 +2024-11-22 08:45:30.456409: Current learning rate: 0.0053 +2024-11-22 08:45:49.464277: train_loss -0.7842 +2024-11-22 08:45:49.467433: val_loss -0.7472 +2024-11-22 08:45:49.467549: Pseudo dice [0.8348] +2024-11-22 08:45:49.467641: Epoch time: 19.01 s +2024-11-22 08:45:50.531035: +2024-11-22 08:45:50.531235: Epoch 4049 +2024-11-22 08:45:50.531348: Current learning rate: 0.0053 +2024-11-22 08:46:08.960191: train_loss -0.7828 +2024-11-22 08:46:08.960399: val_loss -0.7539 +2024-11-22 08:46:08.960474: Pseudo dice [0.8357] +2024-11-22 08:46:08.960552: Epoch time: 18.43 s +2024-11-22 08:46:10.177956: +2024-11-22 08:46:10.178228: Epoch 4050 +2024-11-22 08:46:10.178353: Current learning rate: 0.0053 +2024-11-22 08:46:29.503330: train_loss -0.7778 +2024-11-22 08:46:29.503549: val_loss -0.7165 +2024-11-22 08:46:29.503622: Pseudo dice [0.8041] +2024-11-22 08:46:29.503697: Epoch time: 19.33 s +2024-11-22 08:46:30.398767: +2024-11-22 08:46:30.399050: Epoch 4051 +2024-11-22 08:46:30.399166: Current learning rate: 0.0053 +2024-11-22 08:46:49.530847: train_loss -0.7838 +2024-11-22 08:46:49.531090: val_loss -0.735 +2024-11-22 08:46:49.531170: Pseudo dice [0.8144] +2024-11-22 08:46:49.531249: Epoch time: 19.13 s +2024-11-22 08:46:50.820451: +2024-11-22 08:46:50.820683: Epoch 4052 +2024-11-22 08:46:50.820843: Current learning rate: 0.0053 +2024-11-22 08:47:09.365845: train_loss -0.7794 +2024-11-22 08:47:09.368253: val_loss -0.7398 +2024-11-22 08:47:09.368337: Pseudo dice [0.8065] +2024-11-22 08:47:09.368421: Epoch time: 18.55 s +2024-11-22 08:47:10.522776: +2024-11-22 08:47:10.523014: Epoch 4053 +2024-11-22 08:47:10.523144: Current learning rate: 0.00529 +2024-11-22 08:47:29.715481: train_loss -0.7805 +2024-11-22 08:47:29.715692: val_loss -0.759 +2024-11-22 08:47:29.715769: Pseudo dice [0.8305] +2024-11-22 08:47:29.715845: Epoch time: 19.19 s +2024-11-22 08:47:30.610625: +2024-11-22 08:47:30.610856: Epoch 4054 +2024-11-22 08:47:30.610968: Current learning rate: 0.00529 +2024-11-22 08:47:49.281476: train_loss -0.7793 +2024-11-22 08:47:49.281700: val_loss -0.7681 +2024-11-22 08:47:49.281779: Pseudo dice [0.8318] +2024-11-22 08:47:49.281858: Epoch time: 18.67 s +2024-11-22 08:47:50.279369: +2024-11-22 08:47:50.279604: Epoch 4055 +2024-11-22 08:47:50.279722: Current learning rate: 0.00529 +2024-11-22 08:48:09.590603: train_loss -0.79 +2024-11-22 08:48:09.590842: val_loss -0.7383 +2024-11-22 08:48:09.590922: Pseudo dice [0.8367] +2024-11-22 08:48:09.591017: Epoch time: 19.31 s +2024-11-22 08:48:10.488663: +2024-11-22 08:48:10.488872: Epoch 4056 +2024-11-22 08:48:10.489002: Current learning rate: 0.00529 +2024-11-22 08:48:29.471786: train_loss -0.7707 +2024-11-22 08:48:29.472005: val_loss -0.7608 +2024-11-22 08:48:29.472081: Pseudo dice [0.8314] +2024-11-22 08:48:29.472161: Epoch time: 18.98 s +2024-11-22 08:48:30.422854: +2024-11-22 08:48:30.423100: Epoch 4057 +2024-11-22 08:48:30.423207: Current learning rate: 0.00529 +2024-11-22 08:48:49.285981: train_loss -0.7747 +2024-11-22 08:48:49.286252: val_loss -0.7336 +2024-11-22 08:48:49.286327: Pseudo dice [0.832] +2024-11-22 08:48:49.286405: Epoch time: 18.86 s +2024-11-22 08:48:50.183798: +2024-11-22 08:48:50.184032: Epoch 4058 +2024-11-22 08:48:50.184153: Current learning rate: 0.00529 +2024-11-22 08:49:08.771511: train_loss -0.7766 +2024-11-22 08:49:08.771735: val_loss -0.7448 +2024-11-22 08:49:08.771813: Pseudo dice [0.8141] +2024-11-22 08:49:08.771895: Epoch time: 18.59 s +2024-11-22 08:49:09.663744: +2024-11-22 08:49:09.663953: Epoch 4059 +2024-11-22 08:49:09.664086: Current learning rate: 0.00529 +2024-11-22 08:49:27.285109: train_loss -0.7872 +2024-11-22 08:49:27.285350: val_loss -0.75 +2024-11-22 08:49:27.285422: Pseudo dice [0.8282] +2024-11-22 08:49:27.285503: Epoch time: 17.62 s +2024-11-22 08:49:28.176510: +2024-11-22 08:49:28.176711: Epoch 4060 +2024-11-22 08:49:28.176822: Current learning rate: 0.00529 +2024-11-22 08:49:46.372503: train_loss -0.7968 +2024-11-22 08:49:46.372715: val_loss -0.7676 +2024-11-22 08:49:46.372790: Pseudo dice [0.835] +2024-11-22 08:49:46.372865: Epoch time: 18.2 s +2024-11-22 08:49:47.265719: +2024-11-22 08:49:47.265980: Epoch 4061 +2024-11-22 08:49:47.266096: Current learning rate: 0.00529 +2024-11-22 08:50:06.159763: train_loss -0.7912 +2024-11-22 08:50:06.159977: val_loss -0.7807 +2024-11-22 08:50:06.160060: Pseudo dice [0.8287] +2024-11-22 08:50:06.160140: Epoch time: 18.89 s +2024-11-22 08:50:07.059548: +2024-11-22 08:50:07.059845: Epoch 4062 +2024-11-22 08:50:07.059962: Current learning rate: 0.00528 +2024-11-22 08:50:26.111787: train_loss -0.7967 +2024-11-22 08:50:26.112042: val_loss -0.7114 +2024-11-22 08:50:26.112761: Pseudo dice [0.8175] +2024-11-22 08:50:26.112854: Epoch time: 19.05 s +2024-11-22 08:50:27.376255: +2024-11-22 08:50:27.376521: Epoch 4063 +2024-11-22 08:50:27.376640: Current learning rate: 0.00528 +2024-11-22 08:50:46.741319: train_loss -0.7849 +2024-11-22 08:50:46.741539: val_loss -0.7302 +2024-11-22 08:50:46.741610: Pseudo dice [0.8241] +2024-11-22 08:50:46.741685: Epoch time: 19.37 s +2024-11-22 08:50:47.634375: +2024-11-22 08:50:47.634609: Epoch 4064 +2024-11-22 08:50:47.634724: Current learning rate: 0.00528 +2024-11-22 08:51:06.314002: train_loss -0.7878 +2024-11-22 08:51:06.314279: val_loss -0.7542 +2024-11-22 08:51:06.314360: Pseudo dice [0.8235] +2024-11-22 08:51:06.314435: Epoch time: 18.68 s +2024-11-22 08:51:07.208462: +2024-11-22 08:51:07.208680: Epoch 4065 +2024-11-22 08:51:07.208791: Current learning rate: 0.00528 +2024-11-22 08:51:26.221174: train_loss -0.7875 +2024-11-22 08:51:26.221400: val_loss -0.7482 +2024-11-22 08:51:26.221476: Pseudo dice [0.8236] +2024-11-22 08:51:26.221561: Epoch time: 19.01 s +2024-11-22 08:51:27.119831: +2024-11-22 08:51:27.120120: Epoch 4066 +2024-11-22 08:51:27.120234: Current learning rate: 0.00528 +2024-11-22 08:51:46.635785: train_loss -0.79 +2024-11-22 08:51:46.636024: val_loss -0.7628 +2024-11-22 08:51:46.636101: Pseudo dice [0.8236] +2024-11-22 08:51:46.636177: Epoch time: 19.52 s +2024-11-22 08:51:47.533293: +2024-11-22 08:51:47.533552: Epoch 4067 +2024-11-22 08:51:47.533668: Current learning rate: 0.00528 +2024-11-22 08:52:06.331463: train_loss -0.7868 +2024-11-22 08:52:06.331682: val_loss -0.7317 +2024-11-22 08:52:06.331755: Pseudo dice [0.82] +2024-11-22 08:52:06.331831: Epoch time: 18.8 s +2024-11-22 08:52:07.403952: +2024-11-22 08:52:07.404198: Epoch 4068 +2024-11-22 08:52:07.404314: Current learning rate: 0.00528 +2024-11-22 08:52:26.459441: train_loss -0.7971 +2024-11-22 08:52:26.459702: val_loss -0.741 +2024-11-22 08:52:26.459780: Pseudo dice [0.8369] +2024-11-22 08:52:26.459857: Epoch time: 19.06 s +2024-11-22 08:52:27.354334: +2024-11-22 08:52:27.354580: Epoch 4069 +2024-11-22 08:52:27.354697: Current learning rate: 0.00528 +2024-11-22 08:52:45.819830: train_loss -0.778 +2024-11-22 08:52:45.820090: val_loss -0.7514 +2024-11-22 08:52:45.820206: Pseudo dice [0.8464] +2024-11-22 08:52:45.820294: Epoch time: 18.47 s +2024-11-22 08:52:46.717696: +2024-11-22 08:52:46.717903: Epoch 4070 +2024-11-22 08:52:46.718022: Current learning rate: 0.00527 +2024-11-22 08:53:05.926290: train_loss -0.7754 +2024-11-22 08:53:05.926546: val_loss -0.7426 +2024-11-22 08:53:05.926622: Pseudo dice [0.8262] +2024-11-22 08:53:05.926696: Epoch time: 19.21 s +2024-11-22 08:53:06.858720: +2024-11-22 08:53:06.858986: Epoch 4071 +2024-11-22 08:53:06.859101: Current learning rate: 0.00527 +2024-11-22 08:53:26.182039: train_loss -0.7799 +2024-11-22 08:53:26.182258: val_loss -0.7381 +2024-11-22 08:53:26.182337: Pseudo dice [0.8203] +2024-11-22 08:53:26.182413: Epoch time: 19.32 s +2024-11-22 08:53:27.080384: +2024-11-22 08:53:27.080608: Epoch 4072 +2024-11-22 08:53:27.080725: Current learning rate: 0.00527 +2024-11-22 08:53:45.024825: train_loss -0.7814 +2024-11-22 08:53:45.025051: val_loss -0.7318 +2024-11-22 08:53:45.025126: Pseudo dice [0.8202] +2024-11-22 08:53:45.025203: Epoch time: 17.95 s +2024-11-22 08:53:45.982976: +2024-11-22 08:53:45.983178: Epoch 4073 +2024-11-22 08:53:45.983288: Current learning rate: 0.00527 +2024-11-22 08:54:04.735041: train_loss -0.7882 +2024-11-22 08:54:04.735299: val_loss -0.7465 +2024-11-22 08:54:04.737568: Pseudo dice [0.822] +2024-11-22 08:54:04.737665: Epoch time: 18.75 s +2024-11-22 08:54:05.796973: +2024-11-22 08:54:05.797165: Epoch 4074 +2024-11-22 08:54:05.797275: Current learning rate: 0.00527 +2024-11-22 08:54:24.302977: train_loss -0.7748 +2024-11-22 08:54:24.303199: val_loss -0.7402 +2024-11-22 08:54:24.303272: Pseudo dice [0.8371] +2024-11-22 08:54:24.303344: Epoch time: 18.51 s +2024-11-22 08:54:25.553230: +2024-11-22 08:54:25.553472: Epoch 4075 +2024-11-22 08:54:25.553585: Current learning rate: 0.00527 +2024-11-22 08:54:44.357222: train_loss -0.7591 +2024-11-22 08:54:44.357439: val_loss -0.7345 +2024-11-22 08:54:44.357510: Pseudo dice [0.822] +2024-11-22 08:54:44.357589: Epoch time: 18.8 s +2024-11-22 08:54:45.249790: +2024-11-22 08:54:45.250000: Epoch 4076 +2024-11-22 08:54:45.250131: Current learning rate: 0.00527 +2024-11-22 08:55:03.927214: train_loss -0.7526 +2024-11-22 08:55:03.927465: val_loss -0.7244 +2024-11-22 08:55:03.927540: Pseudo dice [0.8147] +2024-11-22 08:55:03.927622: Epoch time: 18.68 s +2024-11-22 08:55:04.829484: +2024-11-22 08:55:04.829704: Epoch 4077 +2024-11-22 08:55:04.829816: Current learning rate: 0.00527 +2024-11-22 08:55:23.515635: train_loss -0.7731 +2024-11-22 08:55:23.515860: val_loss -0.741 +2024-11-22 08:55:23.515935: Pseudo dice [0.8323] +2024-11-22 08:55:23.516018: Epoch time: 18.69 s +2024-11-22 08:55:24.403722: +2024-11-22 08:55:24.403942: Epoch 4078 +2024-11-22 08:55:24.404070: Current learning rate: 0.00526 +2024-11-22 08:55:43.215905: train_loss -0.7743 +2024-11-22 08:55:43.216128: val_loss -0.7314 +2024-11-22 08:55:43.216205: Pseudo dice [0.8074] +2024-11-22 08:55:43.216282: Epoch time: 18.81 s +2024-11-22 08:55:44.165715: +2024-11-22 08:55:44.165965: Epoch 4079 +2024-11-22 08:55:44.166089: Current learning rate: 0.00526 +2024-11-22 08:56:02.312982: train_loss -0.7812 +2024-11-22 08:56:02.313220: val_loss -0.7558 +2024-11-22 08:56:02.313304: Pseudo dice [0.8202] +2024-11-22 08:56:02.313386: Epoch time: 18.15 s +2024-11-22 08:56:03.209802: +2024-11-22 08:56:03.210009: Epoch 4080 +2024-11-22 08:56:03.210124: Current learning rate: 0.00526 +2024-11-22 08:56:21.149351: train_loss -0.7604 +2024-11-22 08:56:21.149593: val_loss -0.7493 +2024-11-22 08:56:21.149667: Pseudo dice [0.8296] +2024-11-22 08:56:21.149753: Epoch time: 17.94 s +2024-11-22 08:56:22.046627: +2024-11-22 08:56:22.046835: Epoch 4081 +2024-11-22 08:56:22.046947: Current learning rate: 0.00526 +2024-11-22 08:56:40.329089: train_loss -0.7719 +2024-11-22 08:56:40.329317: val_loss -0.7358 +2024-11-22 08:56:40.329395: Pseudo dice [0.8167] +2024-11-22 08:56:40.329473: Epoch time: 18.28 s +2024-11-22 08:56:41.219301: +2024-11-22 08:56:41.219534: Epoch 4082 +2024-11-22 08:56:41.219652: Current learning rate: 0.00526 +2024-11-22 08:57:00.801753: train_loss -0.7717 +2024-11-22 08:57:00.807173: val_loss -0.7432 +2024-11-22 08:57:00.807309: Pseudo dice [0.8186] +2024-11-22 08:57:00.807389: Epoch time: 19.58 s +2024-11-22 08:57:01.766884: +2024-11-22 08:57:01.767091: Epoch 4083 +2024-11-22 08:57:01.767203: Current learning rate: 0.00526 +2024-11-22 08:57:19.413707: train_loss -0.7726 +2024-11-22 08:57:19.413926: val_loss -0.7282 +2024-11-22 08:57:19.414014: Pseudo dice [0.8159] +2024-11-22 08:57:19.414093: Epoch time: 17.65 s +2024-11-22 08:57:20.304466: +2024-11-22 08:57:20.304661: Epoch 4084 +2024-11-22 08:57:20.304772: Current learning rate: 0.00526 +2024-11-22 08:57:38.311961: train_loss -0.785 +2024-11-22 08:57:38.312210: val_loss -0.7378 +2024-11-22 08:57:38.312287: Pseudo dice [0.7953] +2024-11-22 08:57:38.312369: Epoch time: 18.01 s +2024-11-22 08:57:39.206671: +2024-11-22 08:57:39.206878: Epoch 4085 +2024-11-22 08:57:39.206995: Current learning rate: 0.00526 +2024-11-22 08:57:57.805089: train_loss -0.7783 +2024-11-22 08:57:57.805620: val_loss -0.7575 +2024-11-22 08:57:57.805696: Pseudo dice [0.825] +2024-11-22 08:57:57.805773: Epoch time: 18.6 s +2024-11-22 08:57:59.082075: +2024-11-22 08:57:59.082412: Epoch 4086 +2024-11-22 08:57:59.082530: Current learning rate: 0.00526 +2024-11-22 08:58:17.278148: train_loss -0.7917 +2024-11-22 08:58:17.278374: val_loss -0.7612 +2024-11-22 08:58:17.278450: Pseudo dice [0.8334] +2024-11-22 08:58:17.278533: Epoch time: 18.2 s +2024-11-22 08:58:18.174900: +2024-11-22 08:58:18.175162: Epoch 4087 +2024-11-22 08:58:18.175323: Current learning rate: 0.00525 +2024-11-22 08:58:37.258047: train_loss -0.7782 +2024-11-22 08:58:37.263489: val_loss -0.7111 +2024-11-22 08:58:37.263604: Pseudo dice [0.8029] +2024-11-22 08:58:37.263690: Epoch time: 19.08 s +2024-11-22 08:58:38.364771: +2024-11-22 08:58:38.365007: Epoch 4088 +2024-11-22 08:58:38.365126: Current learning rate: 0.00525 +2024-11-22 08:58:57.239815: train_loss -0.7774 +2024-11-22 08:58:57.240042: val_loss -0.7399 +2024-11-22 08:58:57.240121: Pseudo dice [0.8075] +2024-11-22 08:58:57.240200: Epoch time: 18.88 s +2024-11-22 08:58:58.136974: +2024-11-22 08:58:58.137201: Epoch 4089 +2024-11-22 08:58:58.137336: Current learning rate: 0.00525 +2024-11-22 08:59:16.025665: train_loss -0.7868 +2024-11-22 08:59:16.025919: val_loss -0.7485 +2024-11-22 08:59:16.026001: Pseudo dice [0.816] +2024-11-22 08:59:16.026079: Epoch time: 17.89 s +2024-11-22 08:59:16.925401: +2024-11-22 08:59:16.925608: Epoch 4090 +2024-11-22 08:59:16.925723: Current learning rate: 0.00525 +2024-11-22 08:59:35.077364: train_loss -0.7889 +2024-11-22 08:59:35.077648: val_loss -0.7409 +2024-11-22 08:59:35.077729: Pseudo dice [0.8341] +2024-11-22 08:59:35.077814: Epoch time: 18.15 s +2024-11-22 08:59:35.975445: +2024-11-22 08:59:35.975646: Epoch 4091 +2024-11-22 08:59:35.975758: Current learning rate: 0.00525 +2024-11-22 08:59:55.700087: train_loss -0.7746 +2024-11-22 08:59:55.700304: val_loss -0.718 +2024-11-22 08:59:55.700380: Pseudo dice [0.8025] +2024-11-22 08:59:55.700455: Epoch time: 19.73 s +2024-11-22 08:59:56.566891: +2024-11-22 08:59:56.567132: Epoch 4092 +2024-11-22 08:59:56.567247: Current learning rate: 0.00525 +2024-11-22 09:00:15.118029: train_loss -0.7725 +2024-11-22 09:00:15.118305: val_loss -0.7407 +2024-11-22 09:00:15.118381: Pseudo dice [0.8399] +2024-11-22 09:00:15.118459: Epoch time: 18.55 s +2024-11-22 09:00:15.982836: +2024-11-22 09:00:15.983068: Epoch 4093 +2024-11-22 09:00:15.983188: Current learning rate: 0.00525 +2024-11-22 09:00:33.731421: train_loss -0.7862 +2024-11-22 09:00:33.731662: val_loss -0.7423 +2024-11-22 09:00:33.731739: Pseudo dice [0.8191] +2024-11-22 09:00:33.731817: Epoch time: 17.75 s +2024-11-22 09:00:34.595575: +2024-11-22 09:00:34.596045: Epoch 4094 +2024-11-22 09:00:34.596175: Current learning rate: 0.00525 +2024-11-22 09:00:52.753373: train_loss -0.7968 +2024-11-22 09:00:52.753622: val_loss -0.7662 +2024-11-22 09:00:52.753697: Pseudo dice [0.8264] +2024-11-22 09:00:52.753778: Epoch time: 18.16 s +2024-11-22 09:00:53.620817: +2024-11-22 09:00:53.621039: Epoch 4095 +2024-11-22 09:00:53.621155: Current learning rate: 0.00524 +2024-11-22 09:01:12.991894: train_loss -0.7854 +2024-11-22 09:01:12.994330: val_loss -0.7586 +2024-11-22 09:01:12.994418: Pseudo dice [0.8202] +2024-11-22 09:01:12.994494: Epoch time: 19.37 s +2024-11-22 09:01:13.883408: +2024-11-22 09:01:13.883601: Epoch 4096 +2024-11-22 09:01:13.883716: Current learning rate: 0.00524 +2024-11-22 09:01:33.116818: train_loss -0.7894 +2024-11-22 09:01:33.117050: val_loss -0.7637 +2024-11-22 09:01:33.117189: Pseudo dice [0.8337] +2024-11-22 09:01:33.117311: Epoch time: 19.23 s +2024-11-22 09:01:33.983969: +2024-11-22 09:01:33.984181: Epoch 4097 +2024-11-22 09:01:33.984291: Current learning rate: 0.00524 +2024-11-22 09:01:53.166876: train_loss -0.787 +2024-11-22 09:01:53.168794: val_loss -0.7543 +2024-11-22 09:01:53.168942: Pseudo dice [0.8198] +2024-11-22 09:01:53.169031: Epoch time: 19.18 s +2024-11-22 09:01:54.042189: +2024-11-22 09:01:54.042401: Epoch 4098 +2024-11-22 09:01:54.042511: Current learning rate: 0.00524 +2024-11-22 09:02:11.667502: train_loss -0.797 +2024-11-22 09:02:11.667733: val_loss -0.7427 +2024-11-22 09:02:11.667859: Pseudo dice [0.8206] +2024-11-22 09:02:11.667938: Epoch time: 17.63 s +2024-11-22 09:02:12.534388: +2024-11-22 09:02:12.534646: Epoch 4099 +2024-11-22 09:02:12.534761: Current learning rate: 0.00524 +2024-11-22 09:02:32.256021: train_loss -0.7881 +2024-11-22 09:02:32.256261: val_loss -0.7828 +2024-11-22 09:02:32.256342: Pseudo dice [0.8267] +2024-11-22 09:02:32.258682: Epoch time: 19.72 s +2024-11-22 09:02:33.491224: +2024-11-22 09:02:33.491504: Epoch 4100 +2024-11-22 09:02:33.491662: Current learning rate: 0.00524 +2024-11-22 09:02:52.335525: train_loss -0.7811 +2024-11-22 09:02:52.335787: val_loss -0.744 +2024-11-22 09:02:52.338451: Pseudo dice [0.8282] +2024-11-22 09:02:52.338608: Epoch time: 18.85 s +2024-11-22 09:02:53.252801: +2024-11-22 09:02:53.253023: Epoch 4101 +2024-11-22 09:02:53.253138: Current learning rate: 0.00524 +2024-11-22 09:03:11.797067: train_loss -0.7822 +2024-11-22 09:03:11.797300: val_loss -0.7588 +2024-11-22 09:03:11.797375: Pseudo dice [0.8231] +2024-11-22 09:03:11.797453: Epoch time: 18.55 s +2024-11-22 09:03:12.669409: +2024-11-22 09:03:12.669638: Epoch 4102 +2024-11-22 09:03:12.669753: Current learning rate: 0.00524 +2024-11-22 09:03:31.279084: train_loss -0.7762 +2024-11-22 09:03:31.279329: val_loss -0.7461 +2024-11-22 09:03:31.279427: Pseudo dice [0.8175] +2024-11-22 09:03:31.279512: Epoch time: 18.61 s +2024-11-22 09:03:32.152645: +2024-11-22 09:03:32.152886: Epoch 4103 +2024-11-22 09:03:32.153006: Current learning rate: 0.00523 +2024-11-22 09:03:50.680572: train_loss -0.7849 +2024-11-22 09:03:50.680790: val_loss -0.7639 +2024-11-22 09:03:50.680863: Pseudo dice [0.8314] +2024-11-22 09:03:50.680941: Epoch time: 18.53 s +2024-11-22 09:03:51.552292: +2024-11-22 09:03:51.552557: Epoch 4104 +2024-11-22 09:03:51.552673: Current learning rate: 0.00523 +2024-11-22 09:04:10.544522: train_loss -0.786 +2024-11-22 09:04:10.544769: val_loss -0.7279 +2024-11-22 09:04:10.544845: Pseudo dice [0.836] +2024-11-22 09:04:10.544926: Epoch time: 18.99 s +2024-11-22 09:04:11.467829: +2024-11-22 09:04:11.468039: Epoch 4105 +2024-11-22 09:04:11.468155: Current learning rate: 0.00523 +2024-11-22 09:04:30.331073: train_loss -0.7828 +2024-11-22 09:04:30.331289: val_loss -0.7521 +2024-11-22 09:04:30.331367: Pseudo dice [0.8437] +2024-11-22 09:04:30.331596: Epoch time: 18.86 s +2024-11-22 09:04:31.200191: +2024-11-22 09:04:31.200452: Epoch 4106 +2024-11-22 09:04:31.200574: Current learning rate: 0.00523 +2024-11-22 09:04:49.683163: train_loss -0.7843 +2024-11-22 09:04:49.683389: val_loss -0.7464 +2024-11-22 09:04:49.683460: Pseudo dice [0.8279] +2024-11-22 09:04:49.683596: Epoch time: 18.48 s +2024-11-22 09:04:50.558743: +2024-11-22 09:04:50.558966: Epoch 4107 +2024-11-22 09:04:50.559114: Current learning rate: 0.00523 +2024-11-22 09:05:09.155794: train_loss -0.7938 +2024-11-22 09:05:09.156018: val_loss -0.75 +2024-11-22 09:05:09.156098: Pseudo dice [0.825] +2024-11-22 09:05:09.156179: Epoch time: 18.6 s +2024-11-22 09:05:10.025940: +2024-11-22 09:05:10.026154: Epoch 4108 +2024-11-22 09:05:10.026268: Current learning rate: 0.00523 +2024-11-22 09:05:29.666332: train_loss -0.7871 +2024-11-22 09:05:29.666582: val_loss -0.7341 +2024-11-22 09:05:29.666655: Pseudo dice [0.8029] +2024-11-22 09:05:29.666734: Epoch time: 19.64 s +2024-11-22 09:05:30.535342: +2024-11-22 09:05:30.535570: Epoch 4109 +2024-11-22 09:05:30.535682: Current learning rate: 0.00523 +2024-11-22 09:05:50.151997: train_loss -0.7852 +2024-11-22 09:05:50.152213: val_loss -0.7556 +2024-11-22 09:05:50.152289: Pseudo dice [0.8357] +2024-11-22 09:05:50.152367: Epoch time: 19.62 s +2024-11-22 09:05:51.021438: +2024-11-22 09:05:51.021648: Epoch 4110 +2024-11-22 09:05:51.021768: Current learning rate: 0.00523 +2024-11-22 09:06:10.109916: train_loss -0.7899 +2024-11-22 09:06:10.110141: val_loss -0.7622 +2024-11-22 09:06:10.110217: Pseudo dice [0.8289] +2024-11-22 09:06:10.110317: Epoch time: 19.09 s +2024-11-22 09:06:11.088358: +2024-11-22 09:06:11.088768: Epoch 4111 +2024-11-22 09:06:11.088879: Current learning rate: 0.00522 +2024-11-22 09:06:29.310056: train_loss -0.7969 +2024-11-22 09:06:29.310297: val_loss -0.7319 +2024-11-22 09:06:29.310375: Pseudo dice [0.8144] +2024-11-22 09:06:29.310465: Epoch time: 18.22 s +2024-11-22 09:06:30.191326: +2024-11-22 09:06:30.191536: Epoch 4112 +2024-11-22 09:06:30.191648: Current learning rate: 0.00522 +2024-11-22 09:06:49.932506: train_loss -0.7878 +2024-11-22 09:06:49.932724: val_loss -0.7583 +2024-11-22 09:06:49.932809: Pseudo dice [0.8199] +2024-11-22 09:06:49.932904: Epoch time: 19.74 s +2024-11-22 09:06:50.795331: +2024-11-22 09:06:50.795556: Epoch 4113 +2024-11-22 09:06:50.795671: Current learning rate: 0.00522 +2024-11-22 09:07:09.617213: train_loss -0.7811 +2024-11-22 09:07:09.617433: val_loss -0.7454 +2024-11-22 09:07:09.617509: Pseudo dice [0.8349] +2024-11-22 09:07:09.617584: Epoch time: 18.82 s +2024-11-22 09:07:10.484103: +2024-11-22 09:07:10.484339: Epoch 4114 +2024-11-22 09:07:10.484457: Current learning rate: 0.00522 +2024-11-22 09:07:29.091031: train_loss -0.7928 +2024-11-22 09:07:29.091257: val_loss -0.7457 +2024-11-22 09:07:29.091334: Pseudo dice [0.8401] +2024-11-22 09:07:29.091419: Epoch time: 18.61 s +2024-11-22 09:07:29.973944: +2024-11-22 09:07:29.974227: Epoch 4115 +2024-11-22 09:07:29.974356: Current learning rate: 0.00522 +2024-11-22 09:07:48.791834: train_loss -0.7965 +2024-11-22 09:07:48.792054: val_loss -0.7547 +2024-11-22 09:07:48.792132: Pseudo dice [0.8339] +2024-11-22 09:07:48.792210: Epoch time: 18.82 s +2024-11-22 09:07:49.656277: +2024-11-22 09:07:49.656482: Epoch 4116 +2024-11-22 09:07:49.656605: Current learning rate: 0.00522 +2024-11-22 09:08:08.408643: train_loss -0.7963 +2024-11-22 09:08:08.408861: val_loss -0.7469 +2024-11-22 09:08:08.408934: Pseudo dice [0.8205] +2024-11-22 09:08:08.409018: Epoch time: 18.75 s +2024-11-22 09:08:09.279938: +2024-11-22 09:08:09.280149: Epoch 4117 +2024-11-22 09:08:09.280260: Current learning rate: 0.00522 +2024-11-22 09:08:27.446695: train_loss -0.7957 +2024-11-22 09:08:27.446896: val_loss -0.7257 +2024-11-22 09:08:27.446970: Pseudo dice [0.7996] +2024-11-22 09:08:27.447048: Epoch time: 18.17 s +2024-11-22 09:08:28.305792: +2024-11-22 09:08:28.306017: Epoch 4118 +2024-11-22 09:08:28.306136: Current learning rate: 0.00522 +2024-11-22 09:08:46.476263: train_loss -0.7953 +2024-11-22 09:08:46.476501: val_loss -0.7643 +2024-11-22 09:08:46.476574: Pseudo dice [0.8321] +2024-11-22 09:08:46.476654: Epoch time: 18.17 s +2024-11-22 09:08:47.341635: +2024-11-22 09:08:47.341825: Epoch 4119 +2024-11-22 09:08:47.341932: Current learning rate: 0.00522 +2024-11-22 09:09:05.791772: train_loss -0.7935 +2024-11-22 09:09:05.792005: val_loss -0.73 +2024-11-22 09:09:05.792081: Pseudo dice [0.8263] +2024-11-22 09:09:05.794327: Epoch time: 18.45 s +2024-11-22 09:09:06.678047: +2024-11-22 09:09:06.678246: Epoch 4120 +2024-11-22 09:09:06.678357: Current learning rate: 0.00521 +2024-11-22 09:09:25.684373: train_loss -0.7959 +2024-11-22 09:09:25.684587: val_loss -0.7509 +2024-11-22 09:09:25.684678: Pseudo dice [0.8283] +2024-11-22 09:09:25.684754: Epoch time: 19.01 s +2024-11-22 09:09:26.540688: +2024-11-22 09:09:26.540921: Epoch 4121 +2024-11-22 09:09:26.541036: Current learning rate: 0.00521 +2024-11-22 09:09:45.111315: train_loss -0.7855 +2024-11-22 09:09:45.111534: val_loss -0.7708 +2024-11-22 09:09:45.111610: Pseudo dice [0.837] +2024-11-22 09:09:45.111688: Epoch time: 18.57 s +2024-11-22 09:09:46.018475: +2024-11-22 09:09:46.018881: Epoch 4122 +2024-11-22 09:09:46.019001: Current learning rate: 0.00521 +2024-11-22 09:10:05.167418: train_loss -0.7876 +2024-11-22 09:10:05.173107: val_loss -0.7408 +2024-11-22 09:10:05.173219: Pseudo dice [0.8355] +2024-11-22 09:10:05.173300: Epoch time: 19.15 s +2024-11-22 09:10:06.193351: +2024-11-22 09:10:06.193564: Epoch 4123 +2024-11-22 09:10:06.193677: Current learning rate: 0.00521 +2024-11-22 09:10:25.224363: train_loss -0.7837 +2024-11-22 09:10:25.224922: val_loss -0.7515 +2024-11-22 09:10:25.225031: Pseudo dice [0.8314] +2024-11-22 09:10:25.225114: Epoch time: 19.03 s +2024-11-22 09:10:26.289107: +2024-11-22 09:10:26.289350: Epoch 4124 +2024-11-22 09:10:26.289467: Current learning rate: 0.00521 +2024-11-22 09:10:45.665723: train_loss -0.785 +2024-11-22 09:10:45.668077: val_loss -0.7524 +2024-11-22 09:10:45.668160: Pseudo dice [0.8542] +2024-11-22 09:10:45.668238: Epoch time: 19.38 s +2024-11-22 09:10:46.568908: +2024-11-22 09:10:46.569210: Epoch 4125 +2024-11-22 09:10:46.569338: Current learning rate: 0.00521 +2024-11-22 09:11:05.036771: train_loss -0.7911 +2024-11-22 09:11:05.042234: val_loss -0.7388 +2024-11-22 09:11:05.042378: Pseudo dice [0.8223] +2024-11-22 09:11:05.042478: Epoch time: 18.47 s +2024-11-22 09:11:05.941044: +2024-11-22 09:11:05.963941: Epoch 4126 +2024-11-22 09:11:05.964073: Current learning rate: 0.00521 +2024-11-22 09:11:25.029126: train_loss -0.7793 +2024-11-22 09:11:25.029338: val_loss -0.7357 +2024-11-22 09:11:25.029412: Pseudo dice [0.8037] +2024-11-22 09:11:25.029486: Epoch time: 19.09 s +2024-11-22 09:11:26.059056: +2024-11-22 09:11:26.059281: Epoch 4127 +2024-11-22 09:11:26.059399: Current learning rate: 0.00521 +2024-11-22 09:11:45.886069: train_loss -0.7758 +2024-11-22 09:11:45.886274: val_loss -0.7356 +2024-11-22 09:11:45.886347: Pseudo dice [0.8317] +2024-11-22 09:11:45.886425: Epoch time: 19.83 s +2024-11-22 09:11:46.757264: +2024-11-22 09:11:46.757492: Epoch 4128 +2024-11-22 09:11:46.757611: Current learning rate: 0.0052 +2024-11-22 09:12:04.562651: train_loss -0.7876 +2024-11-22 09:12:04.562865: val_loss -0.7306 +2024-11-22 09:12:04.562937: Pseudo dice [0.8057] +2024-11-22 09:12:04.563023: Epoch time: 17.81 s +2024-11-22 09:12:05.455783: +2024-11-22 09:12:05.456021: Epoch 4129 +2024-11-22 09:12:05.456138: Current learning rate: 0.0052 +2024-11-22 09:12:23.409424: train_loss -0.7925 +2024-11-22 09:12:23.409666: val_loss -0.7393 +2024-11-22 09:12:23.409744: Pseudo dice [0.8301] +2024-11-22 09:12:23.409829: Epoch time: 17.95 s +2024-11-22 09:12:24.334401: +2024-11-22 09:12:24.334646: Epoch 4130 +2024-11-22 09:12:24.334754: Current learning rate: 0.0052 +2024-11-22 09:12:43.604816: train_loss -0.7928 +2024-11-22 09:12:43.605037: val_loss -0.7393 +2024-11-22 09:12:43.605120: Pseudo dice [0.8154] +2024-11-22 09:12:43.605223: Epoch time: 19.27 s +2024-11-22 09:12:44.473715: +2024-11-22 09:12:44.473939: Epoch 4131 +2024-11-22 09:12:44.474060: Current learning rate: 0.0052 +2024-11-22 09:13:03.616031: train_loss -0.7919 +2024-11-22 09:13:03.616253: val_loss -0.7688 +2024-11-22 09:13:03.616328: Pseudo dice [0.846] +2024-11-22 09:13:03.616542: Epoch time: 19.14 s +2024-11-22 09:13:04.511602: +2024-11-22 09:13:04.511818: Epoch 4132 +2024-11-22 09:13:04.511930: Current learning rate: 0.0052 +2024-11-22 09:13:22.786960: train_loss -0.8031 +2024-11-22 09:13:22.787211: val_loss -0.7409 +2024-11-22 09:13:22.787291: Pseudo dice [0.819] +2024-11-22 09:13:22.787377: Epoch time: 18.28 s +2024-11-22 09:13:23.658982: +2024-11-22 09:13:23.659452: Epoch 4133 +2024-11-22 09:13:23.659596: Current learning rate: 0.0052 +2024-11-22 09:13:42.365000: train_loss -0.783 +2024-11-22 09:13:42.365301: val_loss -0.7575 +2024-11-22 09:13:42.368421: Pseudo dice [0.8272] +2024-11-22 09:13:42.368549: Epoch time: 18.71 s +2024-11-22 09:13:43.236400: +2024-11-22 09:13:43.236614: Epoch 4134 +2024-11-22 09:13:43.236726: Current learning rate: 0.0052 +2024-11-22 09:14:02.991017: train_loss -0.7912 +2024-11-22 09:14:02.991470: val_loss -0.7664 +2024-11-22 09:14:02.991570: Pseudo dice [0.8347] +2024-11-22 09:14:02.991690: Epoch time: 19.76 s +2024-11-22 09:14:03.864986: +2024-11-22 09:14:03.865222: Epoch 4135 +2024-11-22 09:14:03.865336: Current learning rate: 0.0052 +2024-11-22 09:14:22.384672: train_loss -0.7867 +2024-11-22 09:14:22.384880: val_loss -0.7222 +2024-11-22 09:14:22.384954: Pseudo dice [0.8121] +2024-11-22 09:14:22.385038: Epoch time: 18.52 s +2024-11-22 09:14:23.240089: +2024-11-22 09:14:23.240318: Epoch 4136 +2024-11-22 09:14:23.240428: Current learning rate: 0.00519 +2024-11-22 09:14:41.564835: train_loss -0.7886 +2024-11-22 09:14:41.565076: val_loss -0.7465 +2024-11-22 09:14:41.565149: Pseudo dice [0.8176] +2024-11-22 09:14:41.565228: Epoch time: 18.33 s +2024-11-22 09:14:42.474370: +2024-11-22 09:14:42.474610: Epoch 4137 +2024-11-22 09:14:42.474724: Current learning rate: 0.00519 +2024-11-22 09:15:02.736852: train_loss -0.7723 +2024-11-22 09:15:02.737084: val_loss -0.7473 +2024-11-22 09:15:02.737163: Pseudo dice [0.8245] +2024-11-22 09:15:02.737240: Epoch time: 20.26 s +2024-11-22 09:15:03.608937: +2024-11-22 09:15:03.609154: Epoch 4138 +2024-11-22 09:15:03.609267: Current learning rate: 0.00519 +2024-11-22 09:15:22.415159: train_loss -0.7874 +2024-11-22 09:15:22.415380: val_loss -0.7451 +2024-11-22 09:15:22.415495: Pseudo dice [0.8331] +2024-11-22 09:15:22.437331: Epoch time: 18.81 s +2024-11-22 09:15:23.311290: +2024-11-22 09:15:23.311559: Epoch 4139 +2024-11-22 09:15:23.311678: Current learning rate: 0.00519 +2024-11-22 09:15:40.894714: train_loss -0.7844 +2024-11-22 09:15:40.894939: val_loss -0.7271 +2024-11-22 09:15:40.895026: Pseudo dice [0.8093] +2024-11-22 09:15:40.895106: Epoch time: 17.58 s +2024-11-22 09:15:41.765579: +2024-11-22 09:15:41.765920: Epoch 4140 +2024-11-22 09:15:41.766041: Current learning rate: 0.00519 +2024-11-22 09:16:00.136285: train_loss -0.7804 +2024-11-22 09:16:00.136526: val_loss -0.729 +2024-11-22 09:16:00.136602: Pseudo dice [0.8242] +2024-11-22 09:16:00.136689: Epoch time: 18.37 s +2024-11-22 09:16:01.011196: +2024-11-22 09:16:01.011398: Epoch 4141 +2024-11-22 09:16:01.011510: Current learning rate: 0.00519 +2024-11-22 09:16:18.925382: train_loss -0.7877 +2024-11-22 09:16:18.925611: val_loss -0.733 +2024-11-22 09:16:18.925689: Pseudo dice [0.8217] +2024-11-22 09:16:18.925765: Epoch time: 17.91 s +2024-11-22 09:16:19.806902: +2024-11-22 09:16:19.807103: Epoch 4142 +2024-11-22 09:16:19.807218: Current learning rate: 0.00519 +2024-11-22 09:16:37.900596: train_loss -0.7927 +2024-11-22 09:16:37.900805: val_loss -0.7488 +2024-11-22 09:16:37.900877: Pseudo dice [0.8165] +2024-11-22 09:16:37.900953: Epoch time: 18.09 s +2024-11-22 09:16:38.768039: +2024-11-22 09:16:38.768241: Epoch 4143 +2024-11-22 09:16:38.768356: Current learning rate: 0.00519 +2024-11-22 09:16:56.713288: train_loss -0.7948 +2024-11-22 09:16:56.713521: val_loss -0.7409 +2024-11-22 09:16:56.713595: Pseudo dice [0.8139] +2024-11-22 09:16:56.713677: Epoch time: 17.95 s +2024-11-22 09:16:57.573320: +2024-11-22 09:16:57.573525: Epoch 4144 +2024-11-22 09:16:57.573639: Current learning rate: 0.00518 +2024-11-22 09:17:16.297803: train_loss -0.7963 +2024-11-22 09:17:16.298024: val_loss -0.7434 +2024-11-22 09:17:16.298102: Pseudo dice [0.8359] +2024-11-22 09:17:16.298179: Epoch time: 18.73 s +2024-11-22 09:17:17.222443: +2024-11-22 09:17:17.222653: Epoch 4145 +2024-11-22 09:17:17.222772: Current learning rate: 0.00518 +2024-11-22 09:17:35.928523: train_loss -0.7937 +2024-11-22 09:17:35.928744: val_loss -0.7516 +2024-11-22 09:17:35.928818: Pseudo dice [0.8354] +2024-11-22 09:17:35.928915: Epoch time: 18.71 s +2024-11-22 09:17:36.789431: +2024-11-22 09:17:36.789629: Epoch 4146 +2024-11-22 09:17:36.789744: Current learning rate: 0.00518 +2024-11-22 09:17:55.502136: train_loss -0.7842 +2024-11-22 09:17:55.502625: val_loss -0.7547 +2024-11-22 09:17:55.502725: Pseudo dice [0.8473] +2024-11-22 09:17:55.502813: Epoch time: 18.71 s +2024-11-22 09:17:56.354188: +2024-11-22 09:17:56.354394: Epoch 4147 +2024-11-22 09:17:56.354510: Current learning rate: 0.00518 +2024-11-22 09:18:14.777230: train_loss -0.7869 +2024-11-22 09:18:14.777451: val_loss -0.7241 +2024-11-22 09:18:14.777528: Pseudo dice [0.8297] +2024-11-22 09:18:14.777606: Epoch time: 18.42 s +2024-11-22 09:18:15.749526: +2024-11-22 09:18:15.749730: Epoch 4148 +2024-11-22 09:18:15.749844: Current learning rate: 0.00518 +2024-11-22 09:18:33.988543: train_loss -0.7842 +2024-11-22 09:18:33.988757: val_loss -0.7499 +2024-11-22 09:18:33.988832: Pseudo dice [0.8253] +2024-11-22 09:18:33.988906: Epoch time: 18.24 s +2024-11-22 09:18:34.850950: +2024-11-22 09:18:34.851185: Epoch 4149 +2024-11-22 09:18:34.851301: Current learning rate: 0.00518 +2024-11-22 09:18:54.350704: train_loss -0.7758 +2024-11-22 09:18:54.350948: val_loss -0.7408 +2024-11-22 09:18:54.351031: Pseudo dice [0.8204] +2024-11-22 09:18:54.351118: Epoch time: 19.5 s +2024-11-22 09:18:55.505574: +2024-11-22 09:18:55.505793: Epoch 4150 +2024-11-22 09:18:55.505906: Current learning rate: 0.00518 +2024-11-22 09:19:14.396046: train_loss -0.7839 +2024-11-22 09:19:14.396269: val_loss -0.7438 +2024-11-22 09:19:14.396344: Pseudo dice [0.8291] +2024-11-22 09:19:14.396420: Epoch time: 18.89 s +2024-11-22 09:19:15.268790: +2024-11-22 09:19:15.269011: Epoch 4151 +2024-11-22 09:19:15.269124: Current learning rate: 0.00518 +2024-11-22 09:19:33.818836: train_loss -0.7848 +2024-11-22 09:19:33.819051: val_loss -0.7656 +2024-11-22 09:19:33.819124: Pseudo dice [0.817] +2024-11-22 09:19:33.819213: Epoch time: 18.55 s +2024-11-22 09:19:34.693128: +2024-11-22 09:19:34.693341: Epoch 4152 +2024-11-22 09:19:34.693450: Current learning rate: 0.00518 +2024-11-22 09:19:52.583859: train_loss -0.7888 +2024-11-22 09:19:52.584083: val_loss -0.7422 +2024-11-22 09:19:52.584155: Pseudo dice [0.8189] +2024-11-22 09:19:52.584232: Epoch time: 17.89 s +2024-11-22 09:19:53.449393: +2024-11-22 09:19:53.449677: Epoch 4153 +2024-11-22 09:19:53.449794: Current learning rate: 0.00517 +2024-11-22 09:20:12.272444: train_loss -0.7835 +2024-11-22 09:20:12.272686: val_loss -0.7539 +2024-11-22 09:20:12.272761: Pseudo dice [0.8401] +2024-11-22 09:20:12.272843: Epoch time: 18.82 s +2024-11-22 09:20:13.148413: +2024-11-22 09:20:13.148612: Epoch 4154 +2024-11-22 09:20:13.148722: Current learning rate: 0.00517 +2024-11-22 09:20:31.184243: train_loss -0.7725 +2024-11-22 09:20:31.184456: val_loss -0.7372 +2024-11-22 09:20:31.184530: Pseudo dice [0.8263] +2024-11-22 09:20:31.184610: Epoch time: 18.04 s +2024-11-22 09:20:32.060287: +2024-11-22 09:20:32.060478: Epoch 4155 +2024-11-22 09:20:32.060591: Current learning rate: 0.00517 +2024-11-22 09:20:50.399540: train_loss -0.7771 +2024-11-22 09:20:50.399751: val_loss -0.7577 +2024-11-22 09:20:50.399822: Pseudo dice [0.8123] +2024-11-22 09:20:50.399896: Epoch time: 18.34 s +2024-11-22 09:20:51.260145: +2024-11-22 09:20:51.260379: Epoch 4156 +2024-11-22 09:20:51.260494: Current learning rate: 0.00517 +2024-11-22 09:21:09.565576: train_loss -0.7943 +2024-11-22 09:21:09.565793: val_loss -0.7544 +2024-11-22 09:21:09.565866: Pseudo dice [0.8347] +2024-11-22 09:21:09.565941: Epoch time: 18.31 s +2024-11-22 09:21:10.423253: +2024-11-22 09:21:10.423470: Epoch 4157 +2024-11-22 09:21:10.423591: Current learning rate: 0.00517 +2024-11-22 09:21:29.790550: train_loss -0.7895 +2024-11-22 09:21:29.790805: val_loss -0.7354 +2024-11-22 09:21:29.791070: Pseudo dice [0.8097] +2024-11-22 09:21:29.791189: Epoch time: 19.37 s +2024-11-22 09:21:30.677329: +2024-11-22 09:21:30.677525: Epoch 4158 +2024-11-22 09:21:30.677635: Current learning rate: 0.00517 +2024-11-22 09:21:49.036192: train_loss -0.7876 +2024-11-22 09:21:49.036632: val_loss -0.7373 +2024-11-22 09:21:49.036734: Pseudo dice [0.8353] +2024-11-22 09:21:49.036817: Epoch time: 18.36 s +2024-11-22 09:21:49.904592: +2024-11-22 09:21:49.904904: Epoch 4159 +2024-11-22 09:21:49.905044: Current learning rate: 0.00517 +2024-11-22 09:22:08.439826: train_loss -0.7904 +2024-11-22 09:22:08.440056: val_loss -0.7242 +2024-11-22 09:22:08.440133: Pseudo dice [0.819] +2024-11-22 09:22:08.440212: Epoch time: 18.54 s +2024-11-22 09:22:09.346361: +2024-11-22 09:22:09.346648: Epoch 4160 +2024-11-22 09:22:09.346762: Current learning rate: 0.00517 +2024-11-22 09:22:27.722656: train_loss -0.7844 +2024-11-22 09:22:27.722897: val_loss -0.7561 +2024-11-22 09:22:27.722973: Pseudo dice [0.8427] +2024-11-22 09:22:27.723068: Epoch time: 18.38 s +2024-11-22 09:22:28.593832: +2024-11-22 09:22:28.594132: Epoch 4161 +2024-11-22 09:22:28.594245: Current learning rate: 0.00516 +2024-11-22 09:22:47.485059: train_loss -0.7889 +2024-11-22 09:22:47.485278: val_loss -0.7328 +2024-11-22 09:22:47.485353: Pseudo dice [0.8158] +2024-11-22 09:22:47.485430: Epoch time: 18.89 s +2024-11-22 09:22:48.503736: +2024-11-22 09:22:48.503938: Epoch 4162 +2024-11-22 09:22:48.504055: Current learning rate: 0.00516 +2024-11-22 09:23:06.480662: train_loss -0.7992 +2024-11-22 09:23:06.480961: val_loss -0.7323 +2024-11-22 09:23:06.481045: Pseudo dice [0.8432] +2024-11-22 09:23:06.481121: Epoch time: 17.98 s +2024-11-22 09:23:07.399841: +2024-11-22 09:23:07.400054: Epoch 4163 +2024-11-22 09:23:07.400168: Current learning rate: 0.00516 +2024-11-22 09:23:26.148786: train_loss -0.7966 +2024-11-22 09:23:26.149083: val_loss -0.7634 +2024-11-22 09:23:26.149160: Pseudo dice [0.8334] +2024-11-22 09:23:26.149239: Epoch time: 18.75 s +2024-11-22 09:23:27.017747: +2024-11-22 09:23:27.017972: Epoch 4164 +2024-11-22 09:23:27.018094: Current learning rate: 0.00516 +2024-11-22 09:23:46.309880: train_loss -0.7882 +2024-11-22 09:23:46.310139: val_loss -0.751 +2024-11-22 09:23:46.310215: Pseudo dice [0.8472] +2024-11-22 09:23:46.310301: Epoch time: 19.29 s +2024-11-22 09:23:47.185900: +2024-11-22 09:23:47.186119: Epoch 4165 +2024-11-22 09:23:47.186231: Current learning rate: 0.00516 +2024-11-22 09:24:05.328572: train_loss -0.7952 +2024-11-22 09:24:05.328787: val_loss -0.7513 +2024-11-22 09:24:05.328861: Pseudo dice [0.8275] +2024-11-22 09:24:05.328939: Epoch time: 18.14 s +2024-11-22 09:24:06.208812: +2024-11-22 09:24:06.209068: Epoch 4166 +2024-11-22 09:24:06.209181: Current learning rate: 0.00516 +2024-11-22 09:24:25.326360: train_loss -0.7965 +2024-11-22 09:24:25.326569: val_loss -0.7342 +2024-11-22 09:24:25.326644: Pseudo dice [0.8258] +2024-11-22 09:24:25.326720: Epoch time: 19.12 s +2024-11-22 09:24:26.208846: +2024-11-22 09:24:26.209155: Epoch 4167 +2024-11-22 09:24:26.209268: Current learning rate: 0.00516 +2024-11-22 09:24:45.254556: train_loss -0.7864 +2024-11-22 09:24:45.254773: val_loss -0.7453 +2024-11-22 09:24:45.254854: Pseudo dice [0.8177] +2024-11-22 09:24:45.254934: Epoch time: 19.05 s +2024-11-22 09:24:46.123257: +2024-11-22 09:24:46.123498: Epoch 4168 +2024-11-22 09:24:46.123614: Current learning rate: 0.00516 +2024-11-22 09:25:05.640483: train_loss -0.7773 +2024-11-22 09:25:05.641075: val_loss -0.7511 +2024-11-22 09:25:05.641154: Pseudo dice [0.8538] +2024-11-22 09:25:05.641290: Epoch time: 19.52 s +2024-11-22 09:25:06.513292: +2024-11-22 09:25:06.513500: Epoch 4169 +2024-11-22 09:25:06.513611: Current learning rate: 0.00515 +2024-11-22 09:25:25.664088: train_loss -0.7856 +2024-11-22 09:25:25.664639: val_loss -0.7373 +2024-11-22 09:25:25.664740: Pseudo dice [0.8491] +2024-11-22 09:25:25.664817: Epoch time: 19.15 s +2024-11-22 09:25:25.664878: Yayy! New best EMA pseudo Dice: 0.8325 +2024-11-22 09:25:27.158778: +2024-11-22 09:25:27.159004: Epoch 4170 +2024-11-22 09:25:27.159116: Current learning rate: 0.00515 +2024-11-22 09:25:47.105967: train_loss -0.7855 +2024-11-22 09:25:47.106229: val_loss -0.7248 +2024-11-22 09:25:47.106309: Pseudo dice [0.8083] +2024-11-22 09:25:47.106389: Epoch time: 19.95 s +2024-11-22 09:25:48.034338: +2024-11-22 09:25:48.034581: Epoch 4171 +2024-11-22 09:25:48.034699: Current learning rate: 0.00515 +2024-11-22 09:26:06.862683: train_loss -0.7939 +2024-11-22 09:26:06.862925: val_loss -0.7724 +2024-11-22 09:26:06.863006: Pseudo dice [0.8261] +2024-11-22 09:26:06.863087: Epoch time: 18.83 s +2024-11-22 09:26:07.749772: +2024-11-22 09:26:07.750002: Epoch 4172 +2024-11-22 09:26:07.750118: Current learning rate: 0.00515 +2024-11-22 09:26:26.384262: train_loss -0.7781 +2024-11-22 09:26:26.384480: val_loss -0.7323 +2024-11-22 09:26:26.384554: Pseudo dice [0.8351] +2024-11-22 09:26:26.384630: Epoch time: 18.64 s +2024-11-22 09:26:27.258817: +2024-11-22 09:26:27.259059: Epoch 4173 +2024-11-22 09:26:27.259172: Current learning rate: 0.00515 +2024-11-22 09:26:45.510754: train_loss -0.7941 +2024-11-22 09:26:45.510966: val_loss -0.7503 +2024-11-22 09:26:45.511046: Pseudo dice [0.8391] +2024-11-22 09:26:45.513311: Epoch time: 18.25 s +2024-11-22 09:26:46.399101: +2024-11-22 09:26:46.399332: Epoch 4174 +2024-11-22 09:26:46.399451: Current learning rate: 0.00515 +2024-11-22 09:27:04.634604: train_loss -0.7922 +2024-11-22 09:27:04.639984: val_loss -0.7604 +2024-11-22 09:27:04.640144: Pseudo dice [0.8411] +2024-11-22 09:27:04.640235: Epoch time: 18.24 s +2024-11-22 09:27:05.607724: +2024-11-22 09:27:05.607929: Epoch 4175 +2024-11-22 09:27:05.608066: Current learning rate: 0.00515 +2024-11-22 09:27:23.710248: train_loss -0.7944 +2024-11-22 09:27:23.710470: val_loss -0.7493 +2024-11-22 09:27:23.710572: Pseudo dice [0.8302] +2024-11-22 09:27:23.710656: Epoch time: 18.1 s +2024-11-22 09:27:24.575601: +2024-11-22 09:27:24.575815: Epoch 4176 +2024-11-22 09:27:24.575928: Current learning rate: 0.00515 +2024-11-22 09:27:43.576978: train_loss -0.793 +2024-11-22 09:27:43.577194: val_loss -0.7224 +2024-11-22 09:27:43.577531: Pseudo dice [0.8196] +2024-11-22 09:27:43.577606: Epoch time: 19.0 s +2024-11-22 09:27:44.441133: +2024-11-22 09:27:44.441345: Epoch 4177 +2024-11-22 09:27:44.441458: Current learning rate: 0.00514 +2024-11-22 09:28:02.277449: train_loss -0.8031 +2024-11-22 09:28:02.277740: val_loss -0.7244 +2024-11-22 09:28:02.277824: Pseudo dice [0.8315] +2024-11-22 09:28:02.277906: Epoch time: 17.84 s +2024-11-22 09:28:03.156683: +2024-11-22 09:28:03.156918: Epoch 4178 +2024-11-22 09:28:03.157039: Current learning rate: 0.00514 +2024-11-22 09:28:21.495840: train_loss -0.7947 +2024-11-22 09:28:21.496072: val_loss -0.7634 +2024-11-22 09:28:21.496145: Pseudo dice [0.8336] +2024-11-22 09:28:21.496222: Epoch time: 18.34 s +2024-11-22 09:28:22.377258: +2024-11-22 09:28:22.377473: Epoch 4179 +2024-11-22 09:28:22.377584: Current learning rate: 0.00514 +2024-11-22 09:28:40.151949: train_loss -0.789 +2024-11-22 09:28:40.152178: val_loss -0.7592 +2024-11-22 09:28:40.152278: Pseudo dice [0.8392] +2024-11-22 09:28:40.152359: Epoch time: 17.78 s +2024-11-22 09:28:41.023650: +2024-11-22 09:28:41.023916: Epoch 4180 +2024-11-22 09:28:41.024031: Current learning rate: 0.00514 +2024-11-22 09:29:00.146306: train_loss -0.7931 +2024-11-22 09:29:00.146546: val_loss -0.7585 +2024-11-22 09:29:00.146621: Pseudo dice [0.8396] +2024-11-22 09:29:00.146698: Epoch time: 19.12 s +2024-11-22 09:29:00.146758: Yayy! New best EMA pseudo Dice: 0.8326 +2024-11-22 09:29:01.284032: +2024-11-22 09:29:01.284253: Epoch 4181 +2024-11-22 09:29:01.284378: Current learning rate: 0.00514 +2024-11-22 09:29:19.870186: train_loss -0.7856 +2024-11-22 09:29:19.870505: val_loss -0.7555 +2024-11-22 09:29:19.870585: Pseudo dice [0.814] +2024-11-22 09:29:19.870668: Epoch time: 18.59 s +2024-11-22 09:29:20.746246: +2024-11-22 09:29:20.746450: Epoch 4182 +2024-11-22 09:29:20.746560: Current learning rate: 0.00514 +2024-11-22 09:29:40.656817: train_loss -0.7834 +2024-11-22 09:29:40.657265: val_loss -0.7571 +2024-11-22 09:29:40.657387: Pseudo dice [0.8552] +2024-11-22 09:29:40.657526: Epoch time: 19.91 s +2024-11-22 09:29:40.657588: Yayy! New best EMA pseudo Dice: 0.8332 +2024-11-22 09:29:41.784982: +2024-11-22 09:29:41.785437: Epoch 4183 +2024-11-22 09:29:41.785567: Current learning rate: 0.00514 +2024-11-22 09:30:00.458261: train_loss -0.7896 +2024-11-22 09:30:00.458797: val_loss -0.7494 +2024-11-22 09:30:00.459013: Pseudo dice [0.8256] +2024-11-22 09:30:00.459098: Epoch time: 18.67 s +2024-11-22 09:30:01.333428: +2024-11-22 09:30:01.333648: Epoch 4184 +2024-11-22 09:30:01.333764: Current learning rate: 0.00514 +2024-11-22 09:30:19.752007: train_loss -0.7872 +2024-11-22 09:30:19.752247: val_loss -0.7526 +2024-11-22 09:30:19.754565: Pseudo dice [0.8358] +2024-11-22 09:30:19.754674: Epoch time: 18.42 s +2024-11-22 09:30:20.640103: +2024-11-22 09:30:20.640333: Epoch 4185 +2024-11-22 09:30:20.640450: Current learning rate: 0.00514 +2024-11-22 09:30:39.022644: train_loss -0.7872 +2024-11-22 09:30:39.022858: val_loss -0.746 +2024-11-22 09:30:39.022936: Pseudo dice [0.8335] +2024-11-22 09:30:39.023021: Epoch time: 18.38 s +2024-11-22 09:30:39.896979: +2024-11-22 09:30:39.897230: Epoch 4186 +2024-11-22 09:30:39.897352: Current learning rate: 0.00513 +2024-11-22 09:30:57.649740: train_loss -0.7934 +2024-11-22 09:30:57.649956: val_loss -0.7292 +2024-11-22 09:30:57.650039: Pseudo dice [0.8167] +2024-11-22 09:30:57.650120: Epoch time: 17.75 s +2024-11-22 09:30:58.611222: +2024-11-22 09:30:58.611449: Epoch 4187 +2024-11-22 09:30:58.611559: Current learning rate: 0.00513 +2024-11-22 09:31:17.023617: train_loss -0.7804 +2024-11-22 09:31:17.023831: val_loss -0.7315 +2024-11-22 09:31:17.023908: Pseudo dice [0.807] +2024-11-22 09:31:17.023986: Epoch time: 18.41 s +2024-11-22 09:31:17.894996: +2024-11-22 09:31:17.895211: Epoch 4188 +2024-11-22 09:31:17.895322: Current learning rate: 0.00513 +2024-11-22 09:31:37.057792: train_loss -0.7674 +2024-11-22 09:31:37.058036: val_loss -0.7602 +2024-11-22 09:31:37.058110: Pseudo dice [0.8274] +2024-11-22 09:31:37.058192: Epoch time: 19.16 s +2024-11-22 09:31:37.930487: +2024-11-22 09:31:37.930705: Epoch 4189 +2024-11-22 09:31:37.930815: Current learning rate: 0.00513 +2024-11-22 09:31:56.835373: train_loss -0.7753 +2024-11-22 09:31:56.835593: val_loss -0.7377 +2024-11-22 09:31:56.835745: Pseudo dice [0.8269] +2024-11-22 09:31:56.835824: Epoch time: 18.91 s +2024-11-22 09:31:57.714669: +2024-11-22 09:31:57.714866: Epoch 4190 +2024-11-22 09:31:57.714982: Current learning rate: 0.00513 +2024-11-22 09:32:17.292206: train_loss -0.7706 +2024-11-22 09:32:17.292420: val_loss -0.767 +2024-11-22 09:32:17.292493: Pseudo dice [0.8377] +2024-11-22 09:32:17.292575: Epoch time: 19.58 s +2024-11-22 09:32:18.170775: +2024-11-22 09:32:18.171001: Epoch 4191 +2024-11-22 09:32:18.171118: Current learning rate: 0.00513 +2024-11-22 09:32:36.487498: train_loss -0.7818 +2024-11-22 09:32:36.487746: val_loss -0.7509 +2024-11-22 09:32:36.487821: Pseudo dice [0.8418] +2024-11-22 09:32:36.487903: Epoch time: 18.32 s +2024-11-22 09:32:37.440633: +2024-11-22 09:32:37.440847: Epoch 4192 +2024-11-22 09:32:37.440964: Current learning rate: 0.00513 +2024-11-22 09:32:55.720957: train_loss -0.7627 +2024-11-22 09:32:55.721181: val_loss -0.6982 +2024-11-22 09:32:55.721254: Pseudo dice [0.8031] +2024-11-22 09:32:55.721333: Epoch time: 18.28 s +2024-11-22 09:32:56.594877: +2024-11-22 09:32:56.595093: Epoch 4193 +2024-11-22 09:32:56.595203: Current learning rate: 0.00513 +2024-11-22 09:33:15.659370: train_loss -0.7759 +2024-11-22 09:33:15.659594: val_loss -0.7443 +2024-11-22 09:33:15.659672: Pseudo dice [0.8234] +2024-11-22 09:33:15.659751: Epoch time: 19.07 s +2024-11-22 09:33:16.535747: +2024-11-22 09:33:16.535957: Epoch 4194 +2024-11-22 09:33:16.536076: Current learning rate: 0.00512 +2024-11-22 09:33:34.979786: train_loss -0.7639 +2024-11-22 09:33:34.980025: val_loss -0.7349 +2024-11-22 09:33:34.980101: Pseudo dice [0.8171] +2024-11-22 09:33:34.980188: Epoch time: 18.44 s +2024-11-22 09:33:35.859782: +2024-11-22 09:33:35.859988: Epoch 4195 +2024-11-22 09:33:35.860107: Current learning rate: 0.00512 +2024-11-22 09:33:54.346338: train_loss -0.7783 +2024-11-22 09:33:54.346560: val_loss -0.7301 +2024-11-22 09:33:54.346632: Pseudo dice [0.8029] +2024-11-22 09:33:54.346709: Epoch time: 18.49 s +2024-11-22 09:33:55.294402: +2024-11-22 09:33:55.294656: Epoch 4196 +2024-11-22 09:33:55.294771: Current learning rate: 0.00512 +2024-11-22 09:34:14.294112: train_loss -0.7712 +2024-11-22 09:34:14.294337: val_loss -0.763 +2024-11-22 09:34:14.294412: Pseudo dice [0.8441] +2024-11-22 09:34:14.294486: Epoch time: 19.0 s +2024-11-22 09:34:15.165593: +2024-11-22 09:34:15.165806: Epoch 4197 +2024-11-22 09:34:15.165921: Current learning rate: 0.00512 +2024-11-22 09:34:33.255108: train_loss -0.7808 +2024-11-22 09:34:33.255360: val_loss -0.7569 +2024-11-22 09:34:33.255442: Pseudo dice [0.8162] +2024-11-22 09:34:33.255529: Epoch time: 18.09 s +2024-11-22 09:34:34.134012: +2024-11-22 09:34:34.134218: Epoch 4198 +2024-11-22 09:34:34.134329: Current learning rate: 0.00512 +2024-11-22 09:34:51.915998: train_loss -0.7868 +2024-11-22 09:34:51.916233: val_loss -0.721 +2024-11-22 09:34:51.916309: Pseudo dice [0.8301] +2024-11-22 09:34:51.916386: Epoch time: 17.78 s +2024-11-22 09:34:52.814048: +2024-11-22 09:34:52.814247: Epoch 4199 +2024-11-22 09:34:52.814363: Current learning rate: 0.00512 +2024-11-22 09:35:11.371287: train_loss -0.7876 +2024-11-22 09:35:11.371508: val_loss -0.7419 +2024-11-22 09:35:11.371583: Pseudo dice [0.8311] +2024-11-22 09:35:11.371660: Epoch time: 18.56 s +2024-11-22 09:35:12.680202: +2024-11-22 09:35:12.680404: Epoch 4200 +2024-11-22 09:35:12.680520: Current learning rate: 0.00512 +2024-11-22 09:35:32.107457: train_loss -0.7849 +2024-11-22 09:35:32.107694: val_loss -0.763 +2024-11-22 09:35:32.107767: Pseudo dice [0.8296] +2024-11-22 09:35:32.107845: Epoch time: 19.43 s +2024-11-22 09:35:32.980557: +2024-11-22 09:35:32.980753: Epoch 4201 +2024-11-22 09:35:32.980865: Current learning rate: 0.00512 +2024-11-22 09:35:52.832809: train_loss -0.7834 +2024-11-22 09:35:52.833062: val_loss -0.7328 +2024-11-22 09:35:52.833446: Pseudo dice [0.8114] +2024-11-22 09:35:52.833558: Epoch time: 19.85 s +2024-11-22 09:35:53.715338: +2024-11-22 09:35:53.715563: Epoch 4202 +2024-11-22 09:35:53.715669: Current learning rate: 0.00511 +2024-11-22 09:36:13.316007: train_loss -0.7841 +2024-11-22 09:36:13.316216: val_loss -0.7364 +2024-11-22 09:36:13.316289: Pseudo dice [0.8434] +2024-11-22 09:36:13.316365: Epoch time: 19.6 s +2024-11-22 09:36:14.211653: +2024-11-22 09:36:14.211872: Epoch 4203 +2024-11-22 09:36:14.211984: Current learning rate: 0.00511 +2024-11-22 09:36:33.276904: train_loss -0.7453 +2024-11-22 09:36:33.277122: val_loss -0.7248 +2024-11-22 09:36:33.277202: Pseudo dice [0.8043] +2024-11-22 09:36:33.277277: Epoch time: 19.07 s +2024-11-22 09:36:34.145667: +2024-11-22 09:36:34.145855: Epoch 4204 +2024-11-22 09:36:34.145983: Current learning rate: 0.00511 +2024-11-22 09:36:52.778833: train_loss -0.7677 +2024-11-22 09:36:52.779054: val_loss -0.7374 +2024-11-22 09:36:52.779128: Pseudo dice [0.8082] +2024-11-22 09:36:52.779204: Epoch time: 18.63 s +2024-11-22 09:36:53.657075: +2024-11-22 09:36:53.657318: Epoch 4205 +2024-11-22 09:36:53.657450: Current learning rate: 0.00511 +2024-11-22 09:37:12.207903: train_loss -0.7682 +2024-11-22 09:37:12.208157: val_loss -0.7532 +2024-11-22 09:37:12.208233: Pseudo dice [0.8221] +2024-11-22 09:37:12.208315: Epoch time: 18.55 s +2024-11-22 09:37:13.079647: +2024-11-22 09:37:13.079848: Epoch 4206 +2024-11-22 09:37:13.079962: Current learning rate: 0.00511 +2024-11-22 09:37:32.031028: train_loss -0.7658 +2024-11-22 09:37:32.031261: val_loss -0.7338 +2024-11-22 09:37:32.031336: Pseudo dice [0.817] +2024-11-22 09:37:32.031413: Epoch time: 18.95 s +2024-11-22 09:37:32.898932: +2024-11-22 09:37:32.899150: Epoch 4207 +2024-11-22 09:37:32.899269: Current learning rate: 0.00511 +2024-11-22 09:37:50.980328: train_loss -0.7631 +2024-11-22 09:37:50.980541: val_loss -0.7399 +2024-11-22 09:37:50.980622: Pseudo dice [0.8308] +2024-11-22 09:37:50.980717: Epoch time: 18.08 s +2024-11-22 09:37:51.863833: +2024-11-22 09:37:51.864048: Epoch 4208 +2024-11-22 09:37:51.864160: Current learning rate: 0.00511 +2024-11-22 09:38:11.665036: train_loss -0.7762 +2024-11-22 09:38:11.665283: val_loss -0.7416 +2024-11-22 09:38:11.665364: Pseudo dice [0.8209] +2024-11-22 09:38:11.665596: Epoch time: 19.8 s +2024-11-22 09:38:12.541185: +2024-11-22 09:38:12.541388: Epoch 4209 +2024-11-22 09:38:12.541503: Current learning rate: 0.00511 +2024-11-22 09:38:30.001382: train_loss -0.78 +2024-11-22 09:38:30.001593: val_loss -0.7719 +2024-11-22 09:38:30.001672: Pseudo dice [0.8333] +2024-11-22 09:38:30.001749: Epoch time: 17.46 s +2024-11-22 09:38:30.873129: +2024-11-22 09:38:30.873337: Epoch 4210 +2024-11-22 09:38:30.873450: Current learning rate: 0.0051 +2024-11-22 09:38:49.477806: train_loss -0.7855 +2024-11-22 09:38:49.478099: val_loss -0.7483 +2024-11-22 09:38:49.478175: Pseudo dice [0.8303] +2024-11-22 09:38:49.478253: Epoch time: 18.61 s +2024-11-22 09:38:50.346127: +2024-11-22 09:38:50.346502: Epoch 4211 +2024-11-22 09:38:50.346639: Current learning rate: 0.0051 +2024-11-22 09:39:09.767515: train_loss -0.7756 +2024-11-22 09:39:09.767730: val_loss -0.7621 +2024-11-22 09:39:09.767829: Pseudo dice [0.8363] +2024-11-22 09:39:09.767906: Epoch time: 19.42 s +2024-11-22 09:39:10.632710: +2024-11-22 09:39:10.632940: Epoch 4212 +2024-11-22 09:39:10.633060: Current learning rate: 0.0051 +2024-11-22 09:39:29.945852: train_loss -0.7872 +2024-11-22 09:39:29.946160: val_loss -0.7513 +2024-11-22 09:39:29.946237: Pseudo dice [0.836] +2024-11-22 09:39:29.946319: Epoch time: 19.31 s +2024-11-22 09:39:30.822694: +2024-11-22 09:39:30.823022: Epoch 4213 +2024-11-22 09:39:30.823140: Current learning rate: 0.0051 +2024-11-22 09:39:49.205104: train_loss -0.7849 +2024-11-22 09:39:49.205320: val_loss -0.7555 +2024-11-22 09:39:49.205393: Pseudo dice [0.8253] +2024-11-22 09:39:49.205475: Epoch time: 18.38 s +2024-11-22 09:39:50.078005: +2024-11-22 09:39:50.078242: Epoch 4214 +2024-11-22 09:39:50.078353: Current learning rate: 0.0051 +2024-11-22 09:40:09.149011: train_loss -0.7893 +2024-11-22 09:40:09.149239: val_loss -0.7505 +2024-11-22 09:40:09.149313: Pseudo dice [0.8316] +2024-11-22 09:40:09.149414: Epoch time: 19.07 s +2024-11-22 09:40:10.024787: +2024-11-22 09:40:10.025033: Epoch 4215 +2024-11-22 09:40:10.025146: Current learning rate: 0.0051 +2024-11-22 09:40:27.498327: train_loss -0.7947 +2024-11-22 09:40:27.498548: val_loss -0.7467 +2024-11-22 09:40:27.498625: Pseudo dice [0.8331] +2024-11-22 09:40:27.498702: Epoch time: 17.47 s +2024-11-22 09:40:28.370924: +2024-11-22 09:40:28.371135: Epoch 4216 +2024-11-22 09:40:28.371248: Current learning rate: 0.0051 +2024-11-22 09:40:47.184830: train_loss -0.7906 +2024-11-22 09:40:47.189083: val_loss -0.7733 +2024-11-22 09:40:47.189169: Pseudo dice [0.8391] +2024-11-22 09:40:47.189253: Epoch time: 18.81 s +2024-11-22 09:40:48.071750: +2024-11-22 09:40:48.072014: Epoch 4217 +2024-11-22 09:40:48.072129: Current learning rate: 0.0051 +2024-11-22 09:41:07.374736: train_loss -0.7873 +2024-11-22 09:41:07.374955: val_loss -0.7146 +2024-11-22 09:41:07.375040: Pseudo dice [0.8289] +2024-11-22 09:41:07.375118: Epoch time: 19.3 s +2024-11-22 09:41:08.243146: +2024-11-22 09:41:08.243426: Epoch 4218 +2024-11-22 09:41:08.243542: Current learning rate: 0.0051 +2024-11-22 09:41:26.704108: train_loss -0.7802 +2024-11-22 09:41:26.704663: val_loss -0.7578 +2024-11-22 09:41:26.704766: Pseudo dice [0.8139] +2024-11-22 09:41:26.704848: Epoch time: 18.46 s +2024-11-22 09:41:27.583780: +2024-11-22 09:41:27.584047: Epoch 4219 +2024-11-22 09:41:27.584164: Current learning rate: 0.00509 +2024-11-22 09:41:47.104528: train_loss -0.7934 +2024-11-22 09:41:47.104777: val_loss -0.7434 +2024-11-22 09:41:47.104857: Pseudo dice [0.8158] +2024-11-22 09:41:47.104939: Epoch time: 19.52 s +2024-11-22 09:41:48.032121: +2024-11-22 09:41:48.032383: Epoch 4220 +2024-11-22 09:41:48.032496: Current learning rate: 0.00509 +2024-11-22 09:42:06.459043: train_loss -0.7893 +2024-11-22 09:42:06.459262: val_loss -0.7471 +2024-11-22 09:42:06.459341: Pseudo dice [0.8166] +2024-11-22 09:42:06.459418: Epoch time: 18.43 s +2024-11-22 09:42:07.500656: +2024-11-22 09:42:07.500876: Epoch 4221 +2024-11-22 09:42:07.500997: Current learning rate: 0.00509 +2024-11-22 09:42:26.569740: train_loss -0.7846 +2024-11-22 09:42:26.569970: val_loss -0.7363 +2024-11-22 09:42:26.570085: Pseudo dice [0.8112] +2024-11-22 09:42:26.570168: Epoch time: 19.07 s +2024-11-22 09:42:27.438465: +2024-11-22 09:42:27.438689: Epoch 4222 +2024-11-22 09:42:27.438800: Current learning rate: 0.00509 +2024-11-22 09:42:47.263895: train_loss -0.7967 +2024-11-22 09:42:47.264148: val_loss -0.7719 +2024-11-22 09:42:47.266421: Pseudo dice [0.8444] +2024-11-22 09:42:47.266568: Epoch time: 19.83 s +2024-11-22 09:42:48.427372: +2024-11-22 09:42:48.427596: Epoch 4223 +2024-11-22 09:42:48.427709: Current learning rate: 0.00509 +2024-11-22 09:43:07.214689: train_loss -0.7744 +2024-11-22 09:43:07.214910: val_loss -0.7268 +2024-11-22 09:43:07.214987: Pseudo dice [0.7687] +2024-11-22 09:43:07.215068: Epoch time: 18.79 s +2024-11-22 09:43:08.154675: +2024-11-22 09:43:08.154930: Epoch 4224 +2024-11-22 09:43:08.155053: Current learning rate: 0.00509 +2024-11-22 09:43:27.139660: train_loss -0.7639 +2024-11-22 09:43:27.142047: val_loss -0.7474 +2024-11-22 09:43:27.142169: Pseudo dice [0.8303] +2024-11-22 09:43:27.142251: Epoch time: 18.99 s +2024-11-22 09:43:28.029077: +2024-11-22 09:43:28.029336: Epoch 4225 +2024-11-22 09:43:28.029450: Current learning rate: 0.00509 +2024-11-22 09:43:46.078664: train_loss -0.7759 +2024-11-22 09:43:46.078882: val_loss -0.7756 +2024-11-22 09:43:46.078958: Pseudo dice [0.8285] +2024-11-22 09:43:46.079041: Epoch time: 18.05 s +2024-11-22 09:43:46.938221: +2024-11-22 09:43:46.938421: Epoch 4226 +2024-11-22 09:43:46.938530: Current learning rate: 0.00509 +2024-11-22 09:44:05.390483: train_loss -0.7877 +2024-11-22 09:44:05.401714: val_loss -0.7574 +2024-11-22 09:44:05.401809: Pseudo dice [0.8377] +2024-11-22 09:44:05.401896: Epoch time: 18.45 s +2024-11-22 09:44:06.284798: +2024-11-22 09:44:06.285666: Epoch 4227 +2024-11-22 09:44:06.285777: Current learning rate: 0.00508 +2024-11-22 09:44:24.500728: train_loss -0.7863 +2024-11-22 09:44:24.500968: val_loss -0.7533 +2024-11-22 09:44:24.501121: Pseudo dice [0.8487] +2024-11-22 09:44:24.501200: Epoch time: 18.22 s +2024-11-22 09:44:25.374975: +2024-11-22 09:44:25.375203: Epoch 4228 +2024-11-22 09:44:25.375308: Current learning rate: 0.00508 +2024-11-22 09:44:43.339917: train_loss -0.7937 +2024-11-22 09:44:43.340146: val_loss -0.7581 +2024-11-22 09:44:43.340229: Pseudo dice [0.8297] +2024-11-22 09:44:43.340305: Epoch time: 17.97 s +2024-11-22 09:44:44.212757: +2024-11-22 09:44:44.213046: Epoch 4229 +2024-11-22 09:44:44.213164: Current learning rate: 0.00508 +2024-11-22 09:45:03.713208: train_loss -0.7974 +2024-11-22 09:45:03.713445: val_loss -0.7677 +2024-11-22 09:45:03.713518: Pseudo dice [0.8306] +2024-11-22 09:45:03.713599: Epoch time: 19.5 s +2024-11-22 09:45:04.694081: +2024-11-22 09:45:04.694365: Epoch 4230 +2024-11-22 09:45:04.694477: Current learning rate: 0.00508 +2024-11-22 09:45:24.037911: train_loss -0.7866 +2024-11-22 09:45:24.038383: val_loss -0.726 +2024-11-22 09:45:24.038480: Pseudo dice [0.8359] +2024-11-22 09:45:24.038556: Epoch time: 19.34 s +2024-11-22 09:45:24.917989: +2024-11-22 09:45:24.918186: Epoch 4231 +2024-11-22 09:45:24.918302: Current learning rate: 0.00508 +2024-11-22 09:45:43.561382: train_loss -0.7893 +2024-11-22 09:45:43.561642: val_loss -0.755 +2024-11-22 09:45:43.561787: Pseudo dice [0.8371] +2024-11-22 09:45:43.561872: Epoch time: 18.64 s +2024-11-22 09:45:44.542227: +2024-11-22 09:45:44.542453: Epoch 4232 +2024-11-22 09:45:44.542569: Current learning rate: 0.00508 +2024-11-22 09:46:02.060589: train_loss -0.7952 +2024-11-22 09:46:02.060840: val_loss -0.7583 +2024-11-22 09:46:02.060917: Pseudo dice [0.8166] +2024-11-22 09:46:02.061019: Epoch time: 17.52 s +2024-11-22 09:46:02.932488: +2024-11-22 09:46:02.932719: Epoch 4233 +2024-11-22 09:46:02.932827: Current learning rate: 0.00508 +2024-11-22 09:46:21.486297: train_loss -0.7928 +2024-11-22 09:46:21.487179: val_loss -0.7476 +2024-11-22 09:46:21.487375: Pseudo dice [0.8346] +2024-11-22 09:46:21.487492: Epoch time: 18.55 s +2024-11-22 09:46:22.388372: +2024-11-22 09:46:22.388577: Epoch 4234 +2024-11-22 09:46:22.388694: Current learning rate: 0.00508 +2024-11-22 09:46:42.635506: train_loss -0.7823 +2024-11-22 09:46:42.635748: val_loss -0.7522 +2024-11-22 09:46:42.635866: Pseudo dice [0.8231] +2024-11-22 09:46:42.636075: Epoch time: 20.25 s +2024-11-22 09:46:43.517927: +2024-11-22 09:46:43.518158: Epoch 4235 +2024-11-22 09:46:43.518297: Current learning rate: 0.00507 +2024-11-22 09:47:03.220956: train_loss -0.7843 +2024-11-22 09:47:03.221182: val_loss -0.7339 +2024-11-22 09:47:03.221261: Pseudo dice [0.8198] +2024-11-22 09:47:03.221351: Epoch time: 19.7 s +2024-11-22 09:47:04.089781: +2024-11-22 09:47:04.089988: Epoch 4236 +2024-11-22 09:47:04.090094: Current learning rate: 0.00507 +2024-11-22 09:47:21.838884: train_loss -0.7977 +2024-11-22 09:47:21.839107: val_loss -0.7528 +2024-11-22 09:47:21.839184: Pseudo dice [0.8344] +2024-11-22 09:47:21.839264: Epoch time: 17.75 s +2024-11-22 09:47:22.718080: +2024-11-22 09:47:22.718285: Epoch 4237 +2024-11-22 09:47:22.718396: Current learning rate: 0.00507 +2024-11-22 09:47:43.133365: train_loss -0.7946 +2024-11-22 09:47:43.133610: val_loss -0.748 +2024-11-22 09:47:43.133684: Pseudo dice [0.8309] +2024-11-22 09:47:43.133767: Epoch time: 20.42 s +2024-11-22 09:47:44.014372: +2024-11-22 09:47:44.014611: Epoch 4238 +2024-11-22 09:47:44.014723: Current learning rate: 0.00507 +2024-11-22 09:48:03.389209: train_loss -0.7851 +2024-11-22 09:48:03.389450: val_loss -0.763 +2024-11-22 09:48:03.389527: Pseudo dice [0.8358] +2024-11-22 09:48:03.389605: Epoch time: 19.38 s +2024-11-22 09:48:04.263880: +2024-11-22 09:48:04.264102: Epoch 4239 +2024-11-22 09:48:04.264217: Current learning rate: 0.00507 +2024-11-22 09:48:23.209906: train_loss -0.787 +2024-11-22 09:48:23.210125: val_loss -0.7378 +2024-11-22 09:48:23.210198: Pseudo dice [0.8307] +2024-11-22 09:48:23.230242: Epoch time: 18.95 s +2024-11-22 09:48:24.087024: +2024-11-22 09:48:24.087219: Epoch 4240 +2024-11-22 09:48:24.087318: Current learning rate: 0.00507 +2024-11-22 09:48:42.036019: train_loss -0.792 +2024-11-22 09:48:42.036242: val_loss -0.7428 +2024-11-22 09:48:42.036321: Pseudo dice [0.8212] +2024-11-22 09:48:42.036405: Epoch time: 17.95 s +2024-11-22 09:48:42.964228: +2024-11-22 09:48:42.964444: Epoch 4241 +2024-11-22 09:48:42.964556: Current learning rate: 0.00507 +2024-11-22 09:49:01.963850: train_loss -0.7912 +2024-11-22 09:49:01.964081: val_loss -0.7614 +2024-11-22 09:49:01.964155: Pseudo dice [0.8318] +2024-11-22 09:49:01.964233: Epoch time: 19.0 s +2024-11-22 09:49:02.839938: +2024-11-22 09:49:02.840243: Epoch 4242 +2024-11-22 09:49:02.840353: Current learning rate: 0.00507 +2024-11-22 09:49:21.648160: train_loss -0.7947 +2024-11-22 09:49:21.648700: val_loss -0.7579 +2024-11-22 09:49:21.648798: Pseudo dice [0.8326] +2024-11-22 09:49:21.648878: Epoch time: 18.81 s +2024-11-22 09:49:22.522137: +2024-11-22 09:49:22.522398: Epoch 4243 +2024-11-22 09:49:22.522510: Current learning rate: 0.00506 +2024-11-22 09:49:40.840610: train_loss -0.7965 +2024-11-22 09:49:40.840850: val_loss -0.7724 +2024-11-22 09:49:40.840934: Pseudo dice [0.853] +2024-11-22 09:49:40.841022: Epoch time: 18.32 s +2024-11-22 09:49:41.735351: +2024-11-22 09:49:41.735563: Epoch 4244 +2024-11-22 09:49:41.735672: Current learning rate: 0.00506 +2024-11-22 09:50:00.457633: train_loss -0.7976 +2024-11-22 09:50:00.457873: val_loss -0.7428 +2024-11-22 09:50:00.457948: Pseudo dice [0.8267] +2024-11-22 09:50:00.458038: Epoch time: 18.72 s +2024-11-22 09:50:01.330497: +2024-11-22 09:50:01.330717: Epoch 4245 +2024-11-22 09:50:01.330830: Current learning rate: 0.00506 +2024-11-22 09:50:21.367224: train_loss -0.7986 +2024-11-22 09:50:21.367449: val_loss -0.7633 +2024-11-22 09:50:21.367521: Pseudo dice [0.8469] +2024-11-22 09:50:21.367653: Epoch time: 20.04 s +2024-11-22 09:50:22.242406: +2024-11-22 09:50:22.242629: Epoch 4246 +2024-11-22 09:50:22.242747: Current learning rate: 0.00506 +2024-11-22 09:50:40.055012: train_loss -0.795 +2024-11-22 09:50:40.055230: val_loss -0.7367 +2024-11-22 09:50:40.055305: Pseudo dice [0.8458] +2024-11-22 09:50:40.055384: Epoch time: 17.81 s +2024-11-22 09:50:40.055443: Yayy! New best EMA pseudo Dice: 0.8338 +2024-11-22 09:50:41.189847: +2024-11-22 09:50:41.190063: Epoch 4247 +2024-11-22 09:50:41.190175: Current learning rate: 0.00506 +2024-11-22 09:50:59.369646: train_loss -0.7975 +2024-11-22 09:50:59.369857: val_loss -0.7484 +2024-11-22 09:50:59.369933: Pseudo dice [0.829] +2024-11-22 09:50:59.370014: Epoch time: 18.18 s +2024-11-22 09:51:00.238976: +2024-11-22 09:51:00.239257: Epoch 4248 +2024-11-22 09:51:00.239378: Current learning rate: 0.00506 +2024-11-22 09:51:19.136929: train_loss -0.7864 +2024-11-22 09:51:19.137172: val_loss -0.7532 +2024-11-22 09:51:19.137245: Pseudo dice [0.848] +2024-11-22 09:51:19.137327: Epoch time: 18.9 s +2024-11-22 09:51:19.137388: Yayy! New best EMA pseudo Dice: 0.8348 +2024-11-22 09:51:20.240619: +2024-11-22 09:51:20.240812: Epoch 4249 +2024-11-22 09:51:20.240924: Current learning rate: 0.00506 +2024-11-22 09:51:38.914490: train_loss -0.7846 +2024-11-22 09:51:38.914713: val_loss -0.7571 +2024-11-22 09:51:38.914787: Pseudo dice [0.8255] +2024-11-22 09:51:38.914862: Epoch time: 18.67 s +2024-11-22 09:51:40.275193: +2024-11-22 09:51:40.275393: Epoch 4250 +2024-11-22 09:51:40.275507: Current learning rate: 0.00506 +2024-11-22 09:51:58.633336: train_loss -0.8005 +2024-11-22 09:51:58.633620: val_loss -0.7336 +2024-11-22 09:51:58.633696: Pseudo dice [0.8412] +2024-11-22 09:51:58.633774: Epoch time: 18.36 s +2024-11-22 09:51:59.544958: +2024-11-22 09:51:59.545185: Epoch 4251 +2024-11-22 09:51:59.545291: Current learning rate: 0.00506 +2024-11-22 09:52:18.074442: train_loss -0.7951 +2024-11-22 09:52:18.074732: val_loss -0.7598 +2024-11-22 09:52:18.074812: Pseudo dice [0.8283] +2024-11-22 09:52:18.074903: Epoch time: 18.53 s +2024-11-22 09:52:19.071970: +2024-11-22 09:52:19.072173: Epoch 4252 +2024-11-22 09:52:19.072280: Current learning rate: 0.00505 +2024-11-22 09:52:39.330425: train_loss -0.7882 +2024-11-22 09:52:39.330660: val_loss -0.7516 +2024-11-22 09:52:39.330737: Pseudo dice [0.8288] +2024-11-22 09:52:39.330816: Epoch time: 20.26 s +2024-11-22 09:52:40.209393: +2024-11-22 09:52:40.209604: Epoch 4253 +2024-11-22 09:52:40.209720: Current learning rate: 0.00505 +2024-11-22 09:52:58.922307: train_loss -0.7932 +2024-11-22 09:52:58.922520: val_loss -0.7612 +2024-11-22 09:52:58.922592: Pseudo dice [0.8375] +2024-11-22 09:52:58.922667: Epoch time: 18.71 s +2024-11-22 09:53:00.198201: +2024-11-22 09:53:00.198649: Epoch 4254 +2024-11-22 09:53:00.198784: Current learning rate: 0.00505 +2024-11-22 09:53:19.429134: train_loss -0.7928 +2024-11-22 09:53:19.429397: val_loss -0.7301 +2024-11-22 09:53:19.429474: Pseudo dice [0.8257] +2024-11-22 09:53:19.429559: Epoch time: 19.23 s +2024-11-22 09:53:20.299827: +2024-11-22 09:53:20.300265: Epoch 4255 +2024-11-22 09:53:20.300398: Current learning rate: 0.00505 +2024-11-22 09:53:39.423265: train_loss -0.7989 +2024-11-22 09:53:39.423493: val_loss -0.7379 +2024-11-22 09:53:39.423567: Pseudo dice [0.8164] +2024-11-22 09:53:39.423641: Epoch time: 19.12 s +2024-11-22 09:53:40.329234: +2024-11-22 09:53:40.329695: Epoch 4256 +2024-11-22 09:53:40.329832: Current learning rate: 0.00505 +2024-11-22 09:53:57.614999: train_loss -0.7931 +2024-11-22 09:53:57.615208: val_loss -0.759 +2024-11-22 09:53:57.615291: Pseudo dice [0.8304] +2024-11-22 09:53:57.615372: Epoch time: 17.29 s +2024-11-22 09:53:58.580437: +2024-11-22 09:53:58.580852: Epoch 4257 +2024-11-22 09:53:58.580989: Current learning rate: 0.00505 +2024-11-22 09:54:16.901638: train_loss -0.7925 +2024-11-22 09:54:16.901858: val_loss -0.7725 +2024-11-22 09:54:16.901935: Pseudo dice [0.8402] +2024-11-22 09:54:16.902027: Epoch time: 18.32 s +2024-11-22 09:54:17.782141: +2024-11-22 09:54:17.782579: Epoch 4258 +2024-11-22 09:54:17.782715: Current learning rate: 0.00505 +2024-11-22 09:54:37.017637: train_loss -0.7986 +2024-11-22 09:54:37.017881: val_loss -0.7779 +2024-11-22 09:54:37.017958: Pseudo dice [0.8265] +2024-11-22 09:54:37.018047: Epoch time: 19.24 s +2024-11-22 09:54:37.875071: +2024-11-22 09:54:37.875579: Epoch 4259 +2024-11-22 09:54:37.875710: Current learning rate: 0.00505 +2024-11-22 09:54:57.315836: train_loss -0.7906 +2024-11-22 09:54:57.316056: val_loss -0.7379 +2024-11-22 09:54:57.316133: Pseudo dice [0.817] +2024-11-22 09:54:57.316213: Epoch time: 19.44 s +2024-11-22 09:54:58.189448: +2024-11-22 09:54:58.189952: Epoch 4260 +2024-11-22 09:54:58.190090: Current learning rate: 0.00504 +2024-11-22 09:55:17.246838: train_loss -0.7805 +2024-11-22 09:55:17.247070: val_loss -0.7494 +2024-11-22 09:55:17.247158: Pseudo dice [0.8253] +2024-11-22 09:55:17.247240: Epoch time: 19.06 s +2024-11-22 09:55:18.116652: +2024-11-22 09:55:18.117124: Epoch 4261 +2024-11-22 09:55:18.117273: Current learning rate: 0.00504 +2024-11-22 09:55:37.391959: train_loss -0.7951 +2024-11-22 09:55:37.392212: val_loss -0.7417 +2024-11-22 09:55:37.392293: Pseudo dice [0.8435] +2024-11-22 09:55:37.392376: Epoch time: 19.28 s +2024-11-22 09:55:38.270167: +2024-11-22 09:55:38.270580: Epoch 4262 +2024-11-22 09:55:38.270713: Current learning rate: 0.00504 +2024-11-22 09:55:56.242142: train_loss -0.7925 +2024-11-22 09:55:56.242373: val_loss -0.7382 +2024-11-22 09:55:56.242448: Pseudo dice [0.8203] +2024-11-22 09:55:56.242524: Epoch time: 17.97 s +2024-11-22 09:55:57.186185: +2024-11-22 09:55:57.186644: Epoch 4263 +2024-11-22 09:55:57.186782: Current learning rate: 0.00504 +2024-11-22 09:56:15.900886: train_loss -0.7919 +2024-11-22 09:56:15.901120: val_loss -0.7584 +2024-11-22 09:56:15.901196: Pseudo dice [0.8338] +2024-11-22 09:56:15.901273: Epoch time: 18.72 s +2024-11-22 09:56:16.784420: +2024-11-22 09:56:16.784855: Epoch 4264 +2024-11-22 09:56:16.785000: Current learning rate: 0.00504 +2024-11-22 09:56:35.293460: train_loss -0.7869 +2024-11-22 09:56:35.293700: val_loss -0.7442 +2024-11-22 09:56:35.293777: Pseudo dice [0.822] +2024-11-22 09:56:35.293862: Epoch time: 18.51 s +2024-11-22 09:56:36.166986: +2024-11-22 09:56:36.167190: Epoch 4265 +2024-11-22 09:56:36.167300: Current learning rate: 0.00504 +2024-11-22 09:56:53.907612: train_loss -0.7755 +2024-11-22 09:56:53.907827: val_loss -0.763 +2024-11-22 09:56:53.907903: Pseudo dice [0.8318] +2024-11-22 09:56:53.907980: Epoch time: 17.74 s +2024-11-22 09:56:55.062871: +2024-11-22 09:56:55.063307: Epoch 4266 +2024-11-22 09:56:55.063442: Current learning rate: 0.00504 +2024-11-22 09:57:13.225094: train_loss -0.7806 +2024-11-22 09:57:13.225332: val_loss -0.7454 +2024-11-22 09:57:13.225405: Pseudo dice [0.815] +2024-11-22 09:57:13.225480: Epoch time: 18.16 s +2024-11-22 09:57:14.137154: +2024-11-22 09:57:14.137604: Epoch 4267 +2024-11-22 09:57:14.137737: Current learning rate: 0.00504 +2024-11-22 09:57:32.303232: train_loss -0.7788 +2024-11-22 09:57:32.303448: val_loss -0.7109 +2024-11-22 09:57:32.303529: Pseudo dice [0.7898] +2024-11-22 09:57:32.303604: Epoch time: 18.17 s +2024-11-22 09:57:33.177827: +2024-11-22 09:57:33.178222: Epoch 4268 +2024-11-22 09:57:33.178348: Current learning rate: 0.00503 +2024-11-22 09:57:51.885864: train_loss -0.787 +2024-11-22 09:57:51.886108: val_loss -0.7453 +2024-11-22 09:57:51.886182: Pseudo dice [0.8154] +2024-11-22 09:57:51.886274: Epoch time: 18.71 s +2024-11-22 09:57:52.761659: +2024-11-22 09:57:52.762112: Epoch 4269 +2024-11-22 09:57:52.762238: Current learning rate: 0.00503 +2024-11-22 09:58:11.750572: train_loss -0.7874 +2024-11-22 09:58:11.750787: val_loss -0.7438 +2024-11-22 09:58:11.753029: Pseudo dice [0.8407] +2024-11-22 09:58:11.753115: Epoch time: 18.99 s +2024-11-22 09:58:12.777448: +2024-11-22 09:58:12.777857: Epoch 4270 +2024-11-22 09:58:12.778002: Current learning rate: 0.00503 +2024-11-22 09:58:30.591884: train_loss -0.7924 +2024-11-22 09:58:30.592112: val_loss -0.7251 +2024-11-22 09:58:30.592190: Pseudo dice [0.8006] +2024-11-22 09:58:30.592266: Epoch time: 17.82 s +2024-11-22 09:58:31.465336: +2024-11-22 09:58:31.465775: Epoch 4271 +2024-11-22 09:58:31.465917: Current learning rate: 0.00503 +2024-11-22 09:58:50.107561: train_loss -0.7922 +2024-11-22 09:58:50.107785: val_loss -0.759 +2024-11-22 09:58:50.113100: Pseudo dice [0.8212] +2024-11-22 09:58:50.113248: Epoch time: 18.64 s +2024-11-22 09:58:51.054437: +2024-11-22 09:58:51.054842: Epoch 4272 +2024-11-22 09:58:51.054977: Current learning rate: 0.00503 +2024-11-22 09:59:09.640983: train_loss -0.7899 +2024-11-22 09:59:09.641227: val_loss -0.7521 +2024-11-22 09:59:09.641303: Pseudo dice [0.8208] +2024-11-22 09:59:09.641383: Epoch time: 18.59 s +2024-11-22 09:59:10.525254: +2024-11-22 09:59:10.525691: Epoch 4273 +2024-11-22 09:59:10.525830: Current learning rate: 0.00503 +2024-11-22 09:59:28.907597: train_loss -0.796 +2024-11-22 09:59:28.907835: val_loss -0.7788 +2024-11-22 09:59:28.907910: Pseudo dice [0.8334] +2024-11-22 09:59:28.907999: Epoch time: 18.38 s +2024-11-22 09:59:29.962235: +2024-11-22 09:59:29.962820: Epoch 4274 +2024-11-22 09:59:29.962958: Current learning rate: 0.00503 +2024-11-22 09:59:48.873455: train_loss -0.7951 +2024-11-22 09:59:48.873674: val_loss -0.7553 +2024-11-22 09:59:48.873754: Pseudo dice [0.8466] +2024-11-22 09:59:48.873833: Epoch time: 18.91 s +2024-11-22 09:59:49.741453: +2024-11-22 09:59:49.741867: Epoch 4275 +2024-11-22 09:59:49.742003: Current learning rate: 0.00503 +2024-11-22 10:00:08.797000: train_loss -0.777 +2024-11-22 10:00:08.797246: val_loss -0.7351 +2024-11-22 10:00:08.797328: Pseudo dice [0.827] +2024-11-22 10:00:08.797415: Epoch time: 19.06 s +2024-11-22 10:00:09.771890: +2024-11-22 10:00:09.772356: Epoch 4276 +2024-11-22 10:00:09.772494: Current learning rate: 0.00502 +2024-11-22 10:00:28.271939: train_loss -0.7656 +2024-11-22 10:00:28.272154: val_loss -0.7304 +2024-11-22 10:00:28.272230: Pseudo dice [0.8007] +2024-11-22 10:00:28.272306: Epoch time: 18.5 s +2024-11-22 10:00:29.143955: +2024-11-22 10:00:29.144338: Epoch 4277 +2024-11-22 10:00:29.144454: Current learning rate: 0.00502 +2024-11-22 10:00:48.939359: train_loss -0.7494 +2024-11-22 10:00:48.939577: val_loss -0.7082 +2024-11-22 10:00:48.939651: Pseudo dice [0.7955] +2024-11-22 10:00:48.939731: Epoch time: 19.8 s +2024-11-22 10:00:50.304631: +2024-11-22 10:00:50.305089: Epoch 4278 +2024-11-22 10:00:50.305221: Current learning rate: 0.00502 +2024-11-22 10:01:08.675373: train_loss -0.7599 +2024-11-22 10:01:08.677827: val_loss -0.7612 +2024-11-22 10:01:08.677925: Pseudo dice [0.8104] +2024-11-22 10:01:08.678019: Epoch time: 18.37 s +2024-11-22 10:01:09.774080: +2024-11-22 10:01:09.774519: Epoch 4279 +2024-11-22 10:01:09.774651: Current learning rate: 0.00502 +2024-11-22 10:01:26.954940: train_loss -0.7708 +2024-11-22 10:01:26.955158: val_loss -0.755 +2024-11-22 10:01:26.955232: Pseudo dice [0.8273] +2024-11-22 10:01:26.955310: Epoch time: 17.18 s +2024-11-22 10:01:27.827490: +2024-11-22 10:01:27.828051: Epoch 4280 +2024-11-22 10:01:27.828187: Current learning rate: 0.00502 +2024-11-22 10:01:46.168183: train_loss -0.776 +2024-11-22 10:01:46.168401: val_loss -0.7412 +2024-11-22 10:01:46.168476: Pseudo dice [0.8093] +2024-11-22 10:01:46.168552: Epoch time: 18.34 s +2024-11-22 10:01:47.041509: +2024-11-22 10:01:47.041936: Epoch 4281 +2024-11-22 10:01:47.042074: Current learning rate: 0.00502 +2024-11-22 10:02:06.950357: train_loss -0.7898 +2024-11-22 10:02:06.950574: val_loss -0.7505 +2024-11-22 10:02:06.950649: Pseudo dice [0.8352] +2024-11-22 10:02:06.950732: Epoch time: 19.91 s +2024-11-22 10:02:07.838203: +2024-11-22 10:02:07.838636: Epoch 4282 +2024-11-22 10:02:07.838768: Current learning rate: 0.00502 +2024-11-22 10:02:27.448530: train_loss -0.7823 +2024-11-22 10:02:27.453934: val_loss -0.7436 +2024-11-22 10:02:27.454045: Pseudo dice [0.8346] +2024-11-22 10:02:27.454130: Epoch time: 19.61 s +2024-11-22 10:02:28.420964: +2024-11-22 10:02:28.421465: Epoch 4283 +2024-11-22 10:02:28.421603: Current learning rate: 0.00502 +2024-11-22 10:02:45.972398: train_loss -0.7865 +2024-11-22 10:02:45.972626: val_loss -0.7376 +2024-11-22 10:02:45.972709: Pseudo dice [0.8267] +2024-11-22 10:02:45.972811: Epoch time: 17.55 s +2024-11-22 10:02:46.848479: +2024-11-22 10:02:46.849038: Epoch 4284 +2024-11-22 10:02:46.849180: Current learning rate: 0.00502 +2024-11-22 10:03:05.253419: train_loss -0.7925 +2024-11-22 10:03:05.253660: val_loss -0.747 +2024-11-22 10:03:05.253744: Pseudo dice [0.8154] +2024-11-22 10:03:05.253832: Epoch time: 18.41 s +2024-11-22 10:03:06.149506: +2024-11-22 10:03:06.149940: Epoch 4285 +2024-11-22 10:03:06.150077: Current learning rate: 0.00501 +2024-11-22 10:03:25.422314: train_loss -0.7922 +2024-11-22 10:03:25.422564: val_loss -0.7639 +2024-11-22 10:03:25.422643: Pseudo dice [0.8315] +2024-11-22 10:03:25.422736: Epoch time: 19.27 s +2024-11-22 10:03:26.325253: +2024-11-22 10:03:26.325781: Epoch 4286 +2024-11-22 10:03:26.325912: Current learning rate: 0.00501 +2024-11-22 10:03:45.017988: train_loss -0.7863 +2024-11-22 10:03:45.018205: val_loss -0.7165 +2024-11-22 10:03:45.018278: Pseudo dice [0.8298] +2024-11-22 10:03:45.018354: Epoch time: 18.69 s +2024-11-22 10:03:45.892614: +2024-11-22 10:03:45.893037: Epoch 4287 +2024-11-22 10:03:45.893171: Current learning rate: 0.00501 +2024-11-22 10:04:04.733563: train_loss -0.7955 +2024-11-22 10:04:04.733783: val_loss -0.7408 +2024-11-22 10:04:04.733860: Pseudo dice [0.8246] +2024-11-22 10:04:04.733940: Epoch time: 18.84 s +2024-11-22 10:04:05.602908: +2024-11-22 10:04:05.603328: Epoch 4288 +2024-11-22 10:04:05.603456: Current learning rate: 0.00501 +2024-11-22 10:04:23.960048: train_loss -0.7946 +2024-11-22 10:04:23.960268: val_loss -0.7412 +2024-11-22 10:04:23.960364: Pseudo dice [0.8459] +2024-11-22 10:04:23.960507: Epoch time: 18.36 s +2024-11-22 10:04:24.844810: +2024-11-22 10:04:24.845019: Epoch 4289 +2024-11-22 10:04:24.845129: Current learning rate: 0.00501 +2024-11-22 10:04:42.991638: train_loss -0.796 +2024-11-22 10:04:42.991889: val_loss -0.7405 +2024-11-22 10:04:42.991965: Pseudo dice [0.8266] +2024-11-22 10:04:42.992057: Epoch time: 18.15 s +2024-11-22 10:04:44.306542: +2024-11-22 10:04:44.306954: Epoch 4290 +2024-11-22 10:04:44.307094: Current learning rate: 0.00501 +2024-11-22 10:05:03.152012: train_loss -0.7847 +2024-11-22 10:05:03.152242: val_loss -0.7343 +2024-11-22 10:05:03.152317: Pseudo dice [0.8273] +2024-11-22 10:05:03.152392: Epoch time: 18.85 s +2024-11-22 10:05:04.022209: +2024-11-22 10:05:04.022669: Epoch 4291 +2024-11-22 10:05:04.022811: Current learning rate: 0.00501 +2024-11-22 10:05:23.288478: train_loss -0.7905 +2024-11-22 10:05:23.288695: val_loss -0.7698 +2024-11-22 10:05:23.288769: Pseudo dice [0.8221] +2024-11-22 10:05:23.288845: Epoch time: 19.27 s +2024-11-22 10:05:24.164819: +2024-11-22 10:05:24.165270: Epoch 4292 +2024-11-22 10:05:24.165404: Current learning rate: 0.00501 +2024-11-22 10:05:42.525511: train_loss -0.7734 +2024-11-22 10:05:42.525756: val_loss -0.7497 +2024-11-22 10:05:42.525832: Pseudo dice [0.8323] +2024-11-22 10:05:42.525912: Epoch time: 18.36 s +2024-11-22 10:05:43.474785: +2024-11-22 10:05:43.475236: Epoch 4293 +2024-11-22 10:05:43.475379: Current learning rate: 0.005 +2024-11-22 10:06:02.802316: train_loss -0.7885 +2024-11-22 10:06:02.802533: val_loss -0.7397 +2024-11-22 10:06:02.802608: Pseudo dice [0.8202] +2024-11-22 10:06:02.802683: Epoch time: 19.33 s +2024-11-22 10:06:03.675603: +2024-11-22 10:06:03.676081: Epoch 4294 +2024-11-22 10:06:03.676214: Current learning rate: 0.005 +2024-11-22 10:06:22.895704: train_loss -0.7863 +2024-11-22 10:06:22.895931: val_loss -0.7572 +2024-11-22 10:06:22.896013: Pseudo dice [0.8474] +2024-11-22 10:06:22.896095: Epoch time: 19.22 s +2024-11-22 10:06:23.772175: +2024-11-22 10:06:23.772615: Epoch 4295 +2024-11-22 10:06:23.772755: Current learning rate: 0.005 +2024-11-22 10:06:42.852865: train_loss -0.7934 +2024-11-22 10:06:42.853091: val_loss -0.7388 +2024-11-22 10:06:42.853167: Pseudo dice [0.8254] +2024-11-22 10:06:42.853243: Epoch time: 19.08 s +2024-11-22 10:06:43.729398: +2024-11-22 10:06:43.729836: Epoch 4296 +2024-11-22 10:06:43.729987: Current learning rate: 0.005 +2024-11-22 10:07:02.244977: train_loss -0.7966 +2024-11-22 10:07:02.245239: val_loss -0.7449 +2024-11-22 10:07:02.245318: Pseudo dice [0.8296] +2024-11-22 10:07:02.245400: Epoch time: 18.52 s +2024-11-22 10:07:03.113794: +2024-11-22 10:07:03.114252: Epoch 4297 +2024-11-22 10:07:03.114394: Current learning rate: 0.005 +2024-11-22 10:07:21.561972: train_loss -0.7826 +2024-11-22 10:07:21.562196: val_loss -0.7375 +2024-11-22 10:07:21.562270: Pseudo dice [0.8197] +2024-11-22 10:07:21.562346: Epoch time: 18.45 s +2024-11-22 10:07:22.433964: +2024-11-22 10:07:22.434444: Epoch 4298 +2024-11-22 10:07:22.434576: Current learning rate: 0.005 +2024-11-22 10:07:41.254239: train_loss -0.7903 +2024-11-22 10:07:41.254456: val_loss -0.7536 +2024-11-22 10:07:41.254532: Pseudo dice [0.8181] +2024-11-22 10:07:41.254612: Epoch time: 18.82 s +2024-11-22 10:07:42.216103: +2024-11-22 10:07:42.216621: Epoch 4299 +2024-11-22 10:07:42.216753: Current learning rate: 0.005 +2024-11-22 10:08:00.605187: train_loss -0.7937 +2024-11-22 10:08:00.605489: val_loss -0.7484 +2024-11-22 10:08:00.605566: Pseudo dice [0.8211] +2024-11-22 10:08:00.605649: Epoch time: 18.39 s +2024-11-22 10:08:01.795024: +2024-11-22 10:08:01.795442: Epoch 4300 +2024-11-22 10:08:01.795576: Current learning rate: 0.005 +2024-11-22 10:08:20.759732: train_loss -0.7945 +2024-11-22 10:08:20.759948: val_loss -0.7528 +2024-11-22 10:08:20.760031: Pseudo dice [0.8279] +2024-11-22 10:08:20.760109: Epoch time: 18.97 s +2024-11-22 10:08:21.633613: +2024-11-22 10:08:21.633808: Epoch 4301 +2024-11-22 10:08:21.633917: Current learning rate: 0.00499 +2024-11-22 10:08:41.191723: train_loss -0.7963 +2024-11-22 10:08:41.191947: val_loss -0.7622 +2024-11-22 10:08:41.192034: Pseudo dice [0.8396] +2024-11-22 10:08:41.192114: Epoch time: 19.56 s +2024-11-22 10:08:42.517374: +2024-11-22 10:08:42.517804: Epoch 4302 +2024-11-22 10:08:42.517937: Current learning rate: 0.00499 +2024-11-22 10:09:01.601223: train_loss -0.7925 +2024-11-22 10:09:01.601464: val_loss -0.769 +2024-11-22 10:09:01.601540: Pseudo dice [0.8383] +2024-11-22 10:09:01.601624: Epoch time: 19.08 s +2024-11-22 10:09:02.479486: +2024-11-22 10:09:02.479914: Epoch 4303 +2024-11-22 10:09:02.480046: Current learning rate: 0.00499 +2024-11-22 10:09:20.735066: train_loss -0.8004 +2024-11-22 10:09:20.735286: val_loss -0.7628 +2024-11-22 10:09:20.735367: Pseudo dice [0.8388] +2024-11-22 10:09:20.735450: Epoch time: 18.26 s +2024-11-22 10:09:21.617266: +2024-11-22 10:09:21.617697: Epoch 4304 +2024-11-22 10:09:21.617831: Current learning rate: 0.00499 +2024-11-22 10:09:40.995435: train_loss -0.7939 +2024-11-22 10:09:40.995637: val_loss -0.7676 +2024-11-22 10:09:40.995706: Pseudo dice [0.8428] +2024-11-22 10:09:40.995782: Epoch time: 19.38 s +2024-11-22 10:09:41.931700: +2024-11-22 10:09:41.932127: Epoch 4305 +2024-11-22 10:09:41.932263: Current learning rate: 0.00499 +2024-11-22 10:10:00.711813: train_loss -0.8006 +2024-11-22 10:10:00.712115: val_loss -0.7693 +2024-11-22 10:10:00.712198: Pseudo dice [0.831] +2024-11-22 10:10:00.712287: Epoch time: 18.78 s +2024-11-22 10:10:01.584789: +2024-11-22 10:10:01.585220: Epoch 4306 +2024-11-22 10:10:01.585350: Current learning rate: 0.00499 +2024-11-22 10:10:20.993480: train_loss -0.7922 +2024-11-22 10:10:20.993733: val_loss -0.7288 +2024-11-22 10:10:20.993811: Pseudo dice [0.8083] +2024-11-22 10:10:20.993891: Epoch time: 19.41 s +2024-11-22 10:10:21.865137: +2024-11-22 10:10:21.865579: Epoch 4307 +2024-11-22 10:10:21.865714: Current learning rate: 0.00499 +2024-11-22 10:10:40.879740: train_loss -0.793 +2024-11-22 10:10:40.879965: val_loss -0.7322 +2024-11-22 10:10:40.880051: Pseudo dice [0.8363] +2024-11-22 10:10:40.880137: Epoch time: 19.02 s +2024-11-22 10:10:41.753862: +2024-11-22 10:10:41.754295: Epoch 4308 +2024-11-22 10:10:41.754433: Current learning rate: 0.00499 +2024-11-22 10:10:59.968214: train_loss -0.795 +2024-11-22 10:10:59.968431: val_loss -0.7442 +2024-11-22 10:10:59.968507: Pseudo dice [0.8422] +2024-11-22 10:10:59.968581: Epoch time: 18.22 s +2024-11-22 10:11:00.896019: +2024-11-22 10:11:00.896512: Epoch 4309 +2024-11-22 10:11:00.896647: Current learning rate: 0.00498 +2024-11-22 10:11:19.338366: train_loss -0.7934 +2024-11-22 10:11:19.338614: val_loss -0.7514 +2024-11-22 10:11:19.338689: Pseudo dice [0.8455] +2024-11-22 10:11:19.338771: Epoch time: 18.44 s +2024-11-22 10:11:20.215575: +2024-11-22 10:11:20.216177: Epoch 4310 +2024-11-22 10:11:20.216320: Current learning rate: 0.00498 +2024-11-22 10:11:39.627997: train_loss -0.7953 +2024-11-22 10:11:39.628218: val_loss -0.7451 +2024-11-22 10:11:39.628291: Pseudo dice [0.805] +2024-11-22 10:11:39.628366: Epoch time: 19.41 s +2024-11-22 10:11:40.506831: +2024-11-22 10:11:40.507267: Epoch 4311 +2024-11-22 10:11:40.507399: Current learning rate: 0.00498 +2024-11-22 10:11:58.797795: train_loss -0.7938 +2024-11-22 10:11:58.798013: val_loss -0.7333 +2024-11-22 10:11:58.798089: Pseudo dice [0.8187] +2024-11-22 10:11:58.798164: Epoch time: 18.29 s +2024-11-22 10:11:59.702732: +2024-11-22 10:11:59.703317: Epoch 4312 +2024-11-22 10:11:59.703560: Current learning rate: 0.00498 +2024-11-22 10:12:18.700222: train_loss -0.7837 +2024-11-22 10:12:18.700430: val_loss -0.7437 +2024-11-22 10:12:18.700505: Pseudo dice [0.8162] +2024-11-22 10:12:18.700608: Epoch time: 19.0 s +2024-11-22 10:12:19.574903: +2024-11-22 10:12:19.575191: Epoch 4313 +2024-11-22 10:12:19.575308: Current learning rate: 0.00498 +2024-11-22 10:12:38.487107: train_loss -0.7941 +2024-11-22 10:12:38.487407: val_loss -0.7671 +2024-11-22 10:12:38.487484: Pseudo dice [0.8334] +2024-11-22 10:12:38.487570: Epoch time: 18.91 s +2024-11-22 10:12:39.777362: +2024-11-22 10:12:39.777911: Epoch 4314 +2024-11-22 10:12:39.778059: Current learning rate: 0.00498 +2024-11-22 10:12:58.212450: train_loss -0.7974 +2024-11-22 10:12:58.217875: val_loss -0.7511 +2024-11-22 10:12:58.217981: Pseudo dice [0.832] +2024-11-22 10:12:58.218066: Epoch time: 18.44 s +2024-11-22 10:12:59.136087: +2024-11-22 10:12:59.136519: Epoch 4315 +2024-11-22 10:12:59.136650: Current learning rate: 0.00498 +2024-11-22 10:13:17.485362: train_loss -0.7877 +2024-11-22 10:13:17.485594: val_loss -0.7327 +2024-11-22 10:13:17.485669: Pseudo dice [0.8298] +2024-11-22 10:13:17.485749: Epoch time: 18.35 s +2024-11-22 10:13:18.359387: +2024-11-22 10:13:18.359875: Epoch 4316 +2024-11-22 10:13:18.360018: Current learning rate: 0.00498 +2024-11-22 10:13:36.657186: train_loss -0.7921 +2024-11-22 10:13:36.657416: val_loss -0.7333 +2024-11-22 10:13:36.657491: Pseudo dice [0.8203] +2024-11-22 10:13:36.657573: Epoch time: 18.3 s +2024-11-22 10:13:37.522480: +2024-11-22 10:13:37.523002: Epoch 4317 +2024-11-22 10:13:37.523135: Current learning rate: 0.00498 +2024-11-22 10:13:55.716806: train_loss -0.797 +2024-11-22 10:13:55.717036: val_loss -0.7615 +2024-11-22 10:13:55.717112: Pseudo dice [0.839] +2024-11-22 10:13:55.717188: Epoch time: 18.2 s +2024-11-22 10:13:56.587283: +2024-11-22 10:13:56.587716: Epoch 4318 +2024-11-22 10:13:56.587848: Current learning rate: 0.00497 +2024-11-22 10:14:14.699154: train_loss -0.795 +2024-11-22 10:14:14.699373: val_loss -0.7368 +2024-11-22 10:14:14.699459: Pseudo dice [0.8234] +2024-11-22 10:14:14.699537: Epoch time: 18.11 s +2024-11-22 10:14:15.585834: +2024-11-22 10:14:15.586290: Epoch 4319 +2024-11-22 10:14:15.586443: Current learning rate: 0.00497 +2024-11-22 10:14:33.959928: train_loss -0.8017 +2024-11-22 10:14:33.960181: val_loss -0.7178 +2024-11-22 10:14:33.960258: Pseudo dice [0.8122] +2024-11-22 10:14:33.965554: Epoch time: 18.37 s +2024-11-22 10:14:34.880316: +2024-11-22 10:14:34.880735: Epoch 4320 +2024-11-22 10:14:34.880870: Current learning rate: 0.00497 +2024-11-22 10:14:53.657536: train_loss -0.7918 +2024-11-22 10:14:53.659938: val_loss -0.7515 +2024-11-22 10:14:53.660067: Pseudo dice [0.8373] +2024-11-22 10:14:53.660147: Epoch time: 18.78 s +2024-11-22 10:14:54.618339: +2024-11-22 10:14:54.618761: Epoch 4321 +2024-11-22 10:14:54.618892: Current learning rate: 0.00497 +2024-11-22 10:15:13.464058: train_loss -0.7892 +2024-11-22 10:15:13.464354: val_loss -0.7583 +2024-11-22 10:15:13.464439: Pseudo dice [0.8388] +2024-11-22 10:15:13.464515: Epoch time: 18.85 s +2024-11-22 10:15:14.337019: +2024-11-22 10:15:14.337420: Epoch 4322 +2024-11-22 10:15:14.337549: Current learning rate: 0.00497 +2024-11-22 10:15:32.396348: train_loss -0.7955 +2024-11-22 10:15:32.396574: val_loss -0.7464 +2024-11-22 10:15:32.396650: Pseudo dice [0.8301] +2024-11-22 10:15:32.396727: Epoch time: 18.06 s +2024-11-22 10:15:33.375466: +2024-11-22 10:15:33.375680: Epoch 4323 +2024-11-22 10:15:33.375804: Current learning rate: 0.00497 +2024-11-22 10:15:52.481982: train_loss -0.7931 +2024-11-22 10:15:52.482236: val_loss -0.7406 +2024-11-22 10:15:52.482310: Pseudo dice [0.8088] +2024-11-22 10:15:52.482430: Epoch time: 19.11 s +2024-11-22 10:15:53.364191: +2024-11-22 10:15:53.364387: Epoch 4324 +2024-11-22 10:15:53.364501: Current learning rate: 0.00497 +2024-11-22 10:16:12.787190: train_loss -0.7934 +2024-11-22 10:16:12.787410: val_loss -0.7547 +2024-11-22 10:16:12.787485: Pseudo dice [0.8192] +2024-11-22 10:16:12.787561: Epoch time: 19.42 s +2024-11-22 10:16:13.661276: +2024-11-22 10:16:13.661581: Epoch 4325 +2024-11-22 10:16:13.661694: Current learning rate: 0.00497 +2024-11-22 10:16:31.935601: train_loss -0.7852 +2024-11-22 10:16:31.935822: val_loss -0.748 +2024-11-22 10:16:31.935898: Pseudo dice [0.8328] +2024-11-22 10:16:31.935974: Epoch time: 18.28 s +2024-11-22 10:16:32.808855: +2024-11-22 10:16:32.809061: Epoch 4326 +2024-11-22 10:16:32.809175: Current learning rate: 0.00496 +2024-11-22 10:16:51.133698: train_loss -0.7979 +2024-11-22 10:16:51.133945: val_loss -0.7379 +2024-11-22 10:16:51.134035: Pseudo dice [0.8343] +2024-11-22 10:16:51.134118: Epoch time: 18.33 s +2024-11-22 10:16:52.051545: +2024-11-22 10:16:52.051754: Epoch 4327 +2024-11-22 10:16:52.051864: Current learning rate: 0.00496 +2024-11-22 10:17:10.758397: train_loss -0.792 +2024-11-22 10:17:10.758619: val_loss -0.765 +2024-11-22 10:17:10.758697: Pseudo dice [0.8346] +2024-11-22 10:17:10.758773: Epoch time: 18.71 s +2024-11-22 10:17:11.625664: +2024-11-22 10:17:11.625900: Epoch 4328 +2024-11-22 10:17:11.626020: Current learning rate: 0.00496 +2024-11-22 10:17:29.672019: train_loss -0.7924 +2024-11-22 10:17:29.672232: val_loss -0.7171 +2024-11-22 10:17:29.672309: Pseudo dice [0.8226] +2024-11-22 10:17:29.672390: Epoch time: 18.05 s +2024-11-22 10:17:30.537090: +2024-11-22 10:17:30.537309: Epoch 4329 +2024-11-22 10:17:30.537421: Current learning rate: 0.00496 +2024-11-22 10:17:48.136305: train_loss -0.7723 +2024-11-22 10:17:48.138682: val_loss -0.7281 +2024-11-22 10:17:48.138778: Pseudo dice [0.8231] +2024-11-22 10:17:48.138865: Epoch time: 17.6 s +2024-11-22 10:17:49.263734: +2024-11-22 10:17:49.263951: Epoch 4330 +2024-11-22 10:17:49.264073: Current learning rate: 0.00496 +2024-11-22 10:18:09.199227: train_loss -0.7738 +2024-11-22 10:18:09.199446: val_loss -0.7477 +2024-11-22 10:18:09.199522: Pseudo dice [0.8167] +2024-11-22 10:18:09.199598: Epoch time: 19.94 s +2024-11-22 10:18:10.100117: +2024-11-22 10:18:10.100349: Epoch 4331 +2024-11-22 10:18:10.100466: Current learning rate: 0.00496 +2024-11-22 10:18:27.935415: train_loss -0.7573 +2024-11-22 10:18:27.935657: val_loss -0.7246 +2024-11-22 10:18:27.935732: Pseudo dice [0.8122] +2024-11-22 10:18:27.935807: Epoch time: 17.84 s +2024-11-22 10:18:28.811223: +2024-11-22 10:18:28.811453: Epoch 4332 +2024-11-22 10:18:28.811563: Current learning rate: 0.00496 +2024-11-22 10:18:47.752124: train_loss -0.7742 +2024-11-22 10:18:47.752387: val_loss -0.7604 +2024-11-22 10:18:47.752466: Pseudo dice [0.8183] +2024-11-22 10:18:47.752547: Epoch time: 18.94 s +2024-11-22 10:18:48.680595: +2024-11-22 10:18:48.680798: Epoch 4333 +2024-11-22 10:18:48.680907: Current learning rate: 0.00496 +2024-11-22 10:19:07.033078: train_loss -0.7887 +2024-11-22 10:19:07.033322: val_loss -0.7631 +2024-11-22 10:19:07.034286: Pseudo dice [0.8199] +2024-11-22 10:19:07.036118: Epoch time: 18.35 s +2024-11-22 10:19:07.943494: +2024-11-22 10:19:07.943709: Epoch 4334 +2024-11-22 10:19:07.943828: Current learning rate: 0.00495 +2024-11-22 10:19:26.829522: train_loss -0.79 +2024-11-22 10:19:26.829737: val_loss -0.7581 +2024-11-22 10:19:26.829812: Pseudo dice [0.8359] +2024-11-22 10:19:26.829887: Epoch time: 18.89 s +2024-11-22 10:19:27.702887: +2024-11-22 10:19:27.703154: Epoch 4335 +2024-11-22 10:19:27.703271: Current learning rate: 0.00495 +2024-11-22 10:19:47.480617: train_loss -0.7852 +2024-11-22 10:19:47.480831: val_loss -0.7446 +2024-11-22 10:19:47.480908: Pseudo dice [0.8181] +2024-11-22 10:19:47.480986: Epoch time: 19.78 s +2024-11-22 10:19:48.377270: +2024-11-22 10:19:48.377506: Epoch 4336 +2024-11-22 10:19:48.377623: Current learning rate: 0.00495 +2024-11-22 10:20:07.535910: train_loss -0.7925 +2024-11-22 10:20:07.536230: val_loss -0.7509 +2024-11-22 10:20:07.536315: Pseudo dice [0.8361] +2024-11-22 10:20:07.536394: Epoch time: 19.16 s +2024-11-22 10:20:08.441018: +2024-11-22 10:20:08.441248: Epoch 4337 +2024-11-22 10:20:08.441399: Current learning rate: 0.00495 +2024-11-22 10:20:28.405545: train_loss -0.7937 +2024-11-22 10:20:28.405779: val_loss -0.7597 +2024-11-22 10:20:28.405859: Pseudo dice [0.847] +2024-11-22 10:20:28.405944: Epoch time: 19.97 s +2024-11-22 10:20:29.275669: +2024-11-22 10:20:29.275873: Epoch 4338 +2024-11-22 10:20:29.276101: Current learning rate: 0.00495 +2024-11-22 10:20:48.166349: train_loss -0.7918 +2024-11-22 10:20:48.166921: val_loss -0.7288 +2024-11-22 10:20:48.167032: Pseudo dice [0.8288] +2024-11-22 10:20:48.167114: Epoch time: 18.89 s +2024-11-22 10:20:49.040770: +2024-11-22 10:20:49.041005: Epoch 4339 +2024-11-22 10:20:49.041123: Current learning rate: 0.00495 +2024-11-22 10:21:07.882580: train_loss -0.784 +2024-11-22 10:21:07.882794: val_loss -0.7493 +2024-11-22 10:21:07.882868: Pseudo dice [0.8378] +2024-11-22 10:21:07.882945: Epoch time: 18.84 s +2024-11-22 10:21:08.828572: +2024-11-22 10:21:08.828784: Epoch 4340 +2024-11-22 10:21:08.828898: Current learning rate: 0.00495 +2024-11-22 10:21:27.728248: train_loss -0.7918 +2024-11-22 10:21:27.728534: val_loss -0.7227 +2024-11-22 10:21:27.728616: Pseudo dice [0.8243] +2024-11-22 10:21:27.728701: Epoch time: 18.9 s +2024-11-22 10:21:28.607104: +2024-11-22 10:21:28.607299: Epoch 4341 +2024-11-22 10:21:28.607404: Current learning rate: 0.00495 +2024-11-22 10:21:48.643858: train_loss -0.7846 +2024-11-22 10:21:48.644127: val_loss -0.7299 +2024-11-22 10:21:48.644208: Pseudo dice [0.8219] +2024-11-22 10:21:48.644282: Epoch time: 20.04 s +2024-11-22 10:21:49.515704: +2024-11-22 10:21:49.515913: Epoch 4342 +2024-11-22 10:21:49.516030: Current learning rate: 0.00494 +2024-11-22 10:22:08.641323: train_loss -0.7919 +2024-11-22 10:22:08.641537: val_loss -0.7233 +2024-11-22 10:22:08.641616: Pseudo dice [0.8295] +2024-11-22 10:22:08.641696: Epoch time: 19.13 s +2024-11-22 10:22:09.515394: +2024-11-22 10:22:09.515596: Epoch 4343 +2024-11-22 10:22:09.515708: Current learning rate: 0.00494 +2024-11-22 10:22:27.969740: train_loss -0.7969 +2024-11-22 10:22:27.969951: val_loss -0.7334 +2024-11-22 10:22:27.970037: Pseudo dice [0.8357] +2024-11-22 10:22:27.970118: Epoch time: 18.46 s +2024-11-22 10:22:28.828453: +2024-11-22 10:22:28.828676: Epoch 4344 +2024-11-22 10:22:28.828789: Current learning rate: 0.00494 +2024-11-22 10:22:46.973376: train_loss -0.7966 +2024-11-22 10:22:46.973612: val_loss -0.7531 +2024-11-22 10:22:46.973686: Pseudo dice [0.8418] +2024-11-22 10:22:46.973763: Epoch time: 18.15 s +2024-11-22 10:22:48.214358: +2024-11-22 10:22:48.214552: Epoch 4345 +2024-11-22 10:22:48.214659: Current learning rate: 0.00494 +2024-11-22 10:23:07.420931: train_loss -0.7945 +2024-11-22 10:23:07.423125: val_loss -0.7405 +2024-11-22 10:23:07.423303: Pseudo dice [0.8352] +2024-11-22 10:23:07.423417: Epoch time: 19.21 s +2024-11-22 10:23:08.313367: +2024-11-22 10:23:08.313604: Epoch 4346 +2024-11-22 10:23:08.313720: Current learning rate: 0.00494 +2024-11-22 10:23:27.217862: train_loss -0.7943 +2024-11-22 10:23:27.218090: val_loss -0.7614 +2024-11-22 10:23:27.218170: Pseudo dice [0.8438] +2024-11-22 10:23:27.218249: Epoch time: 18.91 s +2024-11-22 10:23:28.087867: +2024-11-22 10:23:28.088082: Epoch 4347 +2024-11-22 10:23:28.088194: Current learning rate: 0.00494 +2024-11-22 10:23:48.416690: train_loss -0.8002 +2024-11-22 10:23:48.416943: val_loss -0.7625 +2024-11-22 10:23:48.417025: Pseudo dice [0.8465] +2024-11-22 10:23:48.417111: Epoch time: 20.33 s +2024-11-22 10:23:49.410293: +2024-11-22 10:23:49.410617: Epoch 4348 +2024-11-22 10:23:49.410729: Current learning rate: 0.00494 +2024-11-22 10:24:07.734446: train_loss -0.7938 +2024-11-22 10:24:07.734659: val_loss -0.755 +2024-11-22 10:24:07.734733: Pseudo dice [0.8366] +2024-11-22 10:24:07.734807: Epoch time: 18.32 s +2024-11-22 10:24:08.653142: +2024-11-22 10:24:08.653348: Epoch 4349 +2024-11-22 10:24:08.653481: Current learning rate: 0.00494 +2024-11-22 10:24:26.936728: train_loss -0.7959 +2024-11-22 10:24:26.936943: val_loss -0.773 +2024-11-22 10:24:26.937025: Pseudo dice [0.8272] +2024-11-22 10:24:26.937103: Epoch time: 18.28 s +2024-11-22 10:24:28.437396: +2024-11-22 10:24:28.437703: Epoch 4350 +2024-11-22 10:24:28.437822: Current learning rate: 0.00493 +2024-11-22 10:24:46.914905: train_loss -0.7906 +2024-11-22 10:24:46.917386: val_loss -0.7339 +2024-11-22 10:24:46.917481: Pseudo dice [0.8113] +2024-11-22 10:24:46.917576: Epoch time: 18.48 s +2024-11-22 10:24:48.050703: +2024-11-22 10:24:48.050918: Epoch 4351 +2024-11-22 10:24:48.051035: Current learning rate: 0.00493 +2024-11-22 10:25:07.047986: train_loss -0.7976 +2024-11-22 10:25:07.048202: val_loss -0.7482 +2024-11-22 10:25:07.048278: Pseudo dice [0.8392] +2024-11-22 10:25:07.048353: Epoch time: 19.0 s +2024-11-22 10:25:07.918812: +2024-11-22 10:25:07.919058: Epoch 4352 +2024-11-22 10:25:07.919171: Current learning rate: 0.00493 +2024-11-22 10:25:26.971729: train_loss -0.7902 +2024-11-22 10:25:26.971951: val_loss -0.7608 +2024-11-22 10:25:26.972040: Pseudo dice [0.8264] +2024-11-22 10:25:26.972119: Epoch time: 19.05 s +2024-11-22 10:25:27.849435: +2024-11-22 10:25:27.849741: Epoch 4353 +2024-11-22 10:25:27.849853: Current learning rate: 0.00493 +2024-11-22 10:25:46.628825: train_loss -0.789 +2024-11-22 10:25:46.629068: val_loss -0.7275 +2024-11-22 10:25:46.630152: Pseudo dice [0.8114] +2024-11-22 10:25:46.630292: Epoch time: 18.78 s +2024-11-22 10:25:47.510275: +2024-11-22 10:25:47.510517: Epoch 4354 +2024-11-22 10:25:47.510630: Current learning rate: 0.00493 +2024-11-22 10:26:06.854591: train_loss -0.7727 +2024-11-22 10:26:06.854801: val_loss -0.7382 +2024-11-22 10:26:06.854875: Pseudo dice [0.8067] +2024-11-22 10:26:06.854950: Epoch time: 19.35 s +2024-11-22 10:26:07.843983: +2024-11-22 10:26:07.844193: Epoch 4355 +2024-11-22 10:26:07.844304: Current learning rate: 0.00493 +2024-11-22 10:26:25.496168: train_loss -0.7876 +2024-11-22 10:26:25.496403: val_loss -0.7623 +2024-11-22 10:26:25.496561: Pseudo dice [0.8524] +2024-11-22 10:26:25.496643: Epoch time: 17.65 s +2024-11-22 10:26:26.391731: +2024-11-22 10:26:26.391929: Epoch 4356 +2024-11-22 10:26:26.392053: Current learning rate: 0.00493 +2024-11-22 10:26:44.729754: train_loss -0.7892 +2024-11-22 10:26:44.729967: val_loss -0.7514 +2024-11-22 10:26:44.730051: Pseudo dice [0.8196] +2024-11-22 10:26:44.730130: Epoch time: 18.34 s +2024-11-22 10:26:45.650774: +2024-11-22 10:26:45.650969: Epoch 4357 +2024-11-22 10:26:45.651085: Current learning rate: 0.00493 +2024-11-22 10:27:04.009457: train_loss -0.7784 +2024-11-22 10:27:04.009693: val_loss -0.7616 +2024-11-22 10:27:04.009769: Pseudo dice [0.825] +2024-11-22 10:27:04.009850: Epoch time: 18.36 s +2024-11-22 10:27:04.885790: +2024-11-22 10:27:04.885987: Epoch 4358 +2024-11-22 10:27:04.886109: Current learning rate: 0.00493 +2024-11-22 10:27:24.516635: train_loss -0.7735 +2024-11-22 10:27:24.516870: val_loss -0.7322 +2024-11-22 10:27:24.516953: Pseudo dice [0.8155] +2024-11-22 10:27:24.517039: Epoch time: 19.63 s +2024-11-22 10:27:25.392015: +2024-11-22 10:27:25.392222: Epoch 4359 +2024-11-22 10:27:25.392339: Current learning rate: 0.00492 +2024-11-22 10:27:44.234093: train_loss -0.7679 +2024-11-22 10:27:44.234310: val_loss -0.758 +2024-11-22 10:27:44.234387: Pseudo dice [0.8287] +2024-11-22 10:27:44.234462: Epoch time: 18.84 s +2024-11-22 10:27:45.102752: +2024-11-22 10:27:45.102970: Epoch 4360 +2024-11-22 10:27:45.103089: Current learning rate: 0.00492 +2024-11-22 10:28:02.818568: train_loss -0.7841 +2024-11-22 10:28:02.818816: val_loss -0.7471 +2024-11-22 10:28:02.818892: Pseudo dice [0.8222] +2024-11-22 10:28:02.818976: Epoch time: 17.72 s +2024-11-22 10:28:03.969921: +2024-11-22 10:28:03.970136: Epoch 4361 +2024-11-22 10:28:03.970248: Current learning rate: 0.00492 +2024-11-22 10:28:22.584202: train_loss -0.7877 +2024-11-22 10:28:22.584413: val_loss -0.7466 +2024-11-22 10:28:22.584486: Pseudo dice [0.8397] +2024-11-22 10:28:22.584561: Epoch time: 18.62 s +2024-11-22 10:28:23.444079: +2024-11-22 10:28:23.444273: Epoch 4362 +2024-11-22 10:28:23.444381: Current learning rate: 0.00492 +2024-11-22 10:28:41.987675: train_loss -0.7951 +2024-11-22 10:28:41.988225: val_loss -0.7234 +2024-11-22 10:28:41.988325: Pseudo dice [0.8391] +2024-11-22 10:28:41.988402: Epoch time: 18.54 s +2024-11-22 10:28:42.855875: +2024-11-22 10:28:42.856122: Epoch 4363 +2024-11-22 10:28:42.856239: Current learning rate: 0.00492 +2024-11-22 10:29:00.936501: train_loss -0.7962 +2024-11-22 10:29:00.936761: val_loss -0.7397 +2024-11-22 10:29:00.936840: Pseudo dice [0.8198] +2024-11-22 10:29:00.942135: Epoch time: 18.08 s +2024-11-22 10:29:01.874295: +2024-11-22 10:29:01.874687: Epoch 4364 +2024-11-22 10:29:01.874811: Current learning rate: 0.00492 +2024-11-22 10:29:21.210724: train_loss -0.7982 +2024-11-22 10:29:21.210925: val_loss -0.7267 +2024-11-22 10:29:21.211006: Pseudo dice [0.8208] +2024-11-22 10:29:21.211080: Epoch time: 19.34 s +2024-11-22 10:29:22.065935: +2024-11-22 10:29:22.066148: Epoch 4365 +2024-11-22 10:29:22.066261: Current learning rate: 0.00492 +2024-11-22 10:29:40.783805: train_loss -0.783 +2024-11-22 10:29:40.784026: val_loss -0.7487 +2024-11-22 10:29:40.784104: Pseudo dice [0.8271] +2024-11-22 10:29:40.784186: Epoch time: 18.72 s +2024-11-22 10:29:41.851220: +2024-11-22 10:29:41.851443: Epoch 4366 +2024-11-22 10:29:41.851558: Current learning rate: 0.00492 +2024-11-22 10:30:01.191632: train_loss -0.7828 +2024-11-22 10:30:01.191865: val_loss -0.7458 +2024-11-22 10:30:01.191940: Pseudo dice [0.8344] +2024-11-22 10:30:01.192033: Epoch time: 19.34 s +2024-11-22 10:30:02.082239: +2024-11-22 10:30:02.082433: Epoch 4367 +2024-11-22 10:30:02.082549: Current learning rate: 0.00491 +2024-11-22 10:30:20.433269: train_loss -0.788 +2024-11-22 10:30:20.433483: val_loss -0.7501 +2024-11-22 10:30:20.433556: Pseudo dice [0.8257] +2024-11-22 10:30:20.436629: Epoch time: 18.35 s +2024-11-22 10:30:21.458958: +2024-11-22 10:30:21.459168: Epoch 4368 +2024-11-22 10:30:21.459297: Current learning rate: 0.00491 +2024-11-22 10:30:40.059909: train_loss -0.7965 +2024-11-22 10:30:40.060139: val_loss -0.7485 +2024-11-22 10:30:40.060218: Pseudo dice [0.807] +2024-11-22 10:30:40.060298: Epoch time: 18.6 s +2024-11-22 10:30:40.933762: +2024-11-22 10:30:40.933981: Epoch 4369 +2024-11-22 10:30:40.934103: Current learning rate: 0.00491 +2024-11-22 10:30:58.893666: train_loss -0.8006 +2024-11-22 10:30:58.893972: val_loss -0.7363 +2024-11-22 10:30:58.894059: Pseudo dice [0.8233] +2024-11-22 10:30:58.894139: Epoch time: 17.96 s +2024-11-22 10:30:59.922393: +2024-11-22 10:30:59.922626: Epoch 4370 +2024-11-22 10:30:59.922740: Current learning rate: 0.00491 +2024-11-22 10:31:19.589632: train_loss -0.797 +2024-11-22 10:31:19.589844: val_loss -0.7331 +2024-11-22 10:31:19.589918: Pseudo dice [0.8307] +2024-11-22 10:31:19.590000: Epoch time: 19.67 s +2024-11-22 10:31:20.443391: +2024-11-22 10:31:20.443601: Epoch 4371 +2024-11-22 10:31:20.443710: Current learning rate: 0.00491 +2024-11-22 10:31:38.416395: train_loss -0.7805 +2024-11-22 10:31:38.416631: val_loss -0.7559 +2024-11-22 10:31:38.416706: Pseudo dice [0.8149] +2024-11-22 10:31:38.416781: Epoch time: 17.97 s +2024-11-22 10:31:39.305167: +2024-11-22 10:31:39.305383: Epoch 4372 +2024-11-22 10:31:39.305490: Current learning rate: 0.00491 +2024-11-22 10:31:58.930998: train_loss -0.7842 +2024-11-22 10:31:58.931218: val_loss -0.742 +2024-11-22 10:31:58.931332: Pseudo dice [0.8107] +2024-11-22 10:31:58.931410: Epoch time: 19.63 s +2024-11-22 10:31:59.808797: +2024-11-22 10:31:59.809010: Epoch 4373 +2024-11-22 10:31:59.809129: Current learning rate: 0.00491 +2024-11-22 10:32:18.330662: train_loss -0.7896 +2024-11-22 10:32:18.330902: val_loss -0.7364 +2024-11-22 10:32:18.330977: Pseudo dice [0.8106] +2024-11-22 10:32:18.331070: Epoch time: 18.52 s +2024-11-22 10:32:19.215557: +2024-11-22 10:32:19.215750: Epoch 4374 +2024-11-22 10:32:19.215860: Current learning rate: 0.00491 +2024-11-22 10:32:38.610868: train_loss -0.7916 +2024-11-22 10:32:38.611367: val_loss -0.751 +2024-11-22 10:32:38.613654: Pseudo dice [0.8179] +2024-11-22 10:32:38.613742: Epoch time: 19.4 s +2024-11-22 10:32:39.511844: +2024-11-22 10:32:39.512112: Epoch 4375 +2024-11-22 10:32:39.512228: Current learning rate: 0.0049 +2024-11-22 10:32:56.764797: train_loss -0.8 +2024-11-22 10:32:56.765012: val_loss -0.759 +2024-11-22 10:32:56.765086: Pseudo dice [0.835] +2024-11-22 10:32:56.765160: Epoch time: 17.25 s +2024-11-22 10:32:57.630039: +2024-11-22 10:32:57.630296: Epoch 4376 +2024-11-22 10:32:57.630406: Current learning rate: 0.0049 +2024-11-22 10:33:17.228113: train_loss -0.7927 +2024-11-22 10:33:17.228346: val_loss -0.746 +2024-11-22 10:33:17.228419: Pseudo dice [0.8585] +2024-11-22 10:33:17.228504: Epoch time: 19.6 s +2024-11-22 10:33:18.093567: +2024-11-22 10:33:18.093770: Epoch 4377 +2024-11-22 10:33:18.093878: Current learning rate: 0.0049 +2024-11-22 10:33:36.609087: train_loss -0.7969 +2024-11-22 10:33:36.609299: val_loss -0.7685 +2024-11-22 10:33:36.609372: Pseudo dice [0.8337] +2024-11-22 10:33:36.609445: Epoch time: 18.52 s +2024-11-22 10:33:37.461670: +2024-11-22 10:33:37.461884: Epoch 4378 +2024-11-22 10:33:37.462001: Current learning rate: 0.0049 +2024-11-22 10:33:56.669645: train_loss -0.8015 +2024-11-22 10:33:56.669856: val_loss -0.7351 +2024-11-22 10:33:56.669931: Pseudo dice [0.8419] +2024-11-22 10:33:56.670015: Epoch time: 19.21 s +2024-11-22 10:33:57.534240: +2024-11-22 10:33:57.551760: Epoch 4379 +2024-11-22 10:33:57.551884: Current learning rate: 0.0049 +2024-11-22 10:34:16.157683: train_loss -0.7775 +2024-11-22 10:34:16.157905: val_loss -0.7133 +2024-11-22 10:34:16.157976: Pseudo dice [0.8038] +2024-11-22 10:34:16.158059: Epoch time: 18.62 s +2024-11-22 10:34:17.153707: +2024-11-22 10:34:17.153923: Epoch 4380 +2024-11-22 10:34:17.154040: Current learning rate: 0.0049 +2024-11-22 10:34:36.033998: train_loss -0.793 +2024-11-22 10:34:36.034262: val_loss -0.7473 +2024-11-22 10:34:36.034345: Pseudo dice [0.8299] +2024-11-22 10:34:36.034431: Epoch time: 18.88 s +2024-11-22 10:34:36.904352: +2024-11-22 10:34:36.904570: Epoch 4381 +2024-11-22 10:34:36.904686: Current learning rate: 0.0049 +2024-11-22 10:34:56.083437: train_loss -0.789 +2024-11-22 10:34:56.083654: val_loss -0.7404 +2024-11-22 10:34:56.083730: Pseudo dice [0.8242] +2024-11-22 10:34:56.083805: Epoch time: 19.18 s +2024-11-22 10:34:56.954427: +2024-11-22 10:34:56.954679: Epoch 4382 +2024-11-22 10:34:56.954798: Current learning rate: 0.0049 +2024-11-22 10:35:15.983630: train_loss -0.7883 +2024-11-22 10:35:15.983885: val_loss -0.7465 +2024-11-22 10:35:15.983997: Pseudo dice [0.8266] +2024-11-22 10:35:15.984078: Epoch time: 19.03 s +2024-11-22 10:35:16.840599: +2024-11-22 10:35:16.840810: Epoch 4383 +2024-11-22 10:35:16.840921: Current learning rate: 0.00489 +2024-11-22 10:35:35.282028: train_loss -0.7883 +2024-11-22 10:35:35.284433: val_loss -0.7343 +2024-11-22 10:35:35.284527: Pseudo dice [0.8178] +2024-11-22 10:35:35.284610: Epoch time: 18.44 s +2024-11-22 10:35:36.160512: +2024-11-22 10:35:36.160730: Epoch 4384 +2024-11-22 10:35:36.160845: Current learning rate: 0.00489 +2024-11-22 10:35:54.154454: train_loss -0.7715 +2024-11-22 10:35:54.154697: val_loss -0.7156 +2024-11-22 10:35:54.154772: Pseudo dice [0.8107] +2024-11-22 10:35:54.154851: Epoch time: 17.99 s +2024-11-22 10:35:55.063367: +2024-11-22 10:35:55.063704: Epoch 4385 +2024-11-22 10:35:55.063817: Current learning rate: 0.00489 +2024-11-22 10:36:13.563616: train_loss -0.7715 +2024-11-22 10:36:13.563829: val_loss -0.73 +2024-11-22 10:36:13.563905: Pseudo dice [0.8296] +2024-11-22 10:36:13.563987: Epoch time: 18.5 s +2024-11-22 10:36:14.440535: +2024-11-22 10:36:14.440830: Epoch 4386 +2024-11-22 10:36:14.440943: Current learning rate: 0.00489 +2024-11-22 10:36:33.656522: train_loss -0.7729 +2024-11-22 10:36:33.656765: val_loss -0.7569 +2024-11-22 10:36:33.656842: Pseudo dice [0.8247] +2024-11-22 10:36:33.656925: Epoch time: 19.22 s +2024-11-22 10:36:34.543540: +2024-11-22 10:36:34.543808: Epoch 4387 +2024-11-22 10:36:34.543923: Current learning rate: 0.00489 +2024-11-22 10:36:53.305160: train_loss -0.7758 +2024-11-22 10:36:53.305379: val_loss -0.7365 +2024-11-22 10:36:53.305454: Pseudo dice [0.8099] +2024-11-22 10:36:53.305533: Epoch time: 18.76 s +2024-11-22 10:36:54.204931: +2024-11-22 10:36:54.205226: Epoch 4388 +2024-11-22 10:36:54.205343: Current learning rate: 0.00489 +2024-11-22 10:37:12.908062: train_loss -0.7814 +2024-11-22 10:37:12.908274: val_loss -0.7557 +2024-11-22 10:37:12.908349: Pseudo dice [0.8226] +2024-11-22 10:37:12.908425: Epoch time: 18.7 s +2024-11-22 10:37:13.789757: +2024-11-22 10:37:13.789966: Epoch 4389 +2024-11-22 10:37:13.790087: Current learning rate: 0.00489 +2024-11-22 10:37:32.521892: train_loss -0.7812 +2024-11-22 10:37:32.522142: val_loss -0.7381 +2024-11-22 10:37:32.522214: Pseudo dice [0.8205] +2024-11-22 10:37:32.522296: Epoch time: 18.73 s +2024-11-22 10:37:33.468322: +2024-11-22 10:37:33.468669: Epoch 4390 +2024-11-22 10:37:33.468791: Current learning rate: 0.00489 +2024-11-22 10:37:52.704271: train_loss -0.7772 +2024-11-22 10:37:52.704487: val_loss -0.7272 +2024-11-22 10:37:52.704559: Pseudo dice [0.81] +2024-11-22 10:37:52.704637: Epoch time: 19.24 s +2024-11-22 10:37:53.728129: +2024-11-22 10:37:53.728357: Epoch 4391 +2024-11-22 10:37:53.728467: Current learning rate: 0.00489 +2024-11-22 10:38:12.892860: train_loss -0.7628 +2024-11-22 10:38:12.893097: val_loss -0.7398 +2024-11-22 10:38:12.893181: Pseudo dice [0.8121] +2024-11-22 10:38:12.893499: Epoch time: 19.17 s +2024-11-22 10:38:13.823511: +2024-11-22 10:38:13.823724: Epoch 4392 +2024-11-22 10:38:13.823828: Current learning rate: 0.00488 +2024-11-22 10:38:33.055903: train_loss -0.7659 +2024-11-22 10:38:33.056118: val_loss -0.7378 +2024-11-22 10:38:33.056200: Pseudo dice [0.8293] +2024-11-22 10:38:33.056281: Epoch time: 19.23 s +2024-11-22 10:38:33.936625: +2024-11-22 10:38:33.936819: Epoch 4393 +2024-11-22 10:38:33.936921: Current learning rate: 0.00488 +2024-11-22 10:38:52.282486: train_loss -0.7787 +2024-11-22 10:38:52.282789: val_loss -0.7108 +2024-11-22 10:38:52.282872: Pseudo dice [0.8136] +2024-11-22 10:38:52.282980: Epoch time: 18.35 s +2024-11-22 10:38:53.148319: +2024-11-22 10:38:53.148543: Epoch 4394 +2024-11-22 10:38:53.148659: Current learning rate: 0.00488 +2024-11-22 10:39:11.699668: train_loss -0.7804 +2024-11-22 10:39:11.699880: val_loss -0.74 +2024-11-22 10:39:11.699956: Pseudo dice [0.8423] +2024-11-22 10:39:11.700038: Epoch time: 18.55 s +2024-11-22 10:39:12.639828: +2024-11-22 10:39:12.640043: Epoch 4395 +2024-11-22 10:39:12.640153: Current learning rate: 0.00488 +2024-11-22 10:39:30.124412: train_loss -0.7872 +2024-11-22 10:39:30.124692: val_loss -0.7512 +2024-11-22 10:39:30.124769: Pseudo dice [0.8219] +2024-11-22 10:39:30.124849: Epoch time: 17.49 s +2024-11-22 10:39:30.994300: +2024-11-22 10:39:30.994528: Epoch 4396 +2024-11-22 10:39:30.994637: Current learning rate: 0.00488 +2024-11-22 10:39:49.127445: train_loss -0.7827 +2024-11-22 10:39:49.127661: val_loss -0.758 +2024-11-22 10:39:49.127738: Pseudo dice [0.825] +2024-11-22 10:39:49.127823: Epoch time: 18.13 s +2024-11-22 10:39:50.096026: +2024-11-22 10:39:50.096285: Epoch 4397 +2024-11-22 10:39:50.096398: Current learning rate: 0.00488 +2024-11-22 10:40:07.987680: train_loss -0.7912 +2024-11-22 10:40:07.987916: val_loss -0.7549 +2024-11-22 10:40:07.987988: Pseudo dice [0.818] +2024-11-22 10:40:07.988079: Epoch time: 17.89 s +2024-11-22 10:40:08.856918: +2024-11-22 10:40:08.857153: Epoch 4398 +2024-11-22 10:40:08.857265: Current learning rate: 0.00488 +2024-11-22 10:40:27.657139: train_loss -0.7924 +2024-11-22 10:40:27.657379: val_loss -0.745 +2024-11-22 10:40:27.657459: Pseudo dice [0.8388] +2024-11-22 10:40:27.657539: Epoch time: 18.8 s +2024-11-22 10:40:28.658811: +2024-11-22 10:40:28.659015: Epoch 4399 +2024-11-22 10:40:28.659123: Current learning rate: 0.00488 +2024-11-22 10:40:47.072805: train_loss -0.7852 +2024-11-22 10:40:47.073034: val_loss -0.7472 +2024-11-22 10:40:47.073112: Pseudo dice [0.8294] +2024-11-22 10:40:47.073192: Epoch time: 18.41 s +2024-11-22 10:40:48.206751: +2024-11-22 10:40:48.206968: Epoch 4400 +2024-11-22 10:40:48.207089: Current learning rate: 0.00487 +2024-11-22 10:41:06.915318: train_loss -0.7878 +2024-11-22 10:41:06.915562: val_loss -0.7418 +2024-11-22 10:41:06.915655: Pseudo dice [0.8234] +2024-11-22 10:41:06.915798: Epoch time: 18.71 s +2024-11-22 10:41:07.790307: +2024-11-22 10:41:07.790529: Epoch 4401 +2024-11-22 10:41:07.790654: Current learning rate: 0.00487 +2024-11-22 10:41:26.327793: train_loss -0.7928 +2024-11-22 10:41:26.328020: val_loss -0.7549 +2024-11-22 10:41:26.328097: Pseudo dice [0.8153] +2024-11-22 10:41:26.328177: Epoch time: 18.54 s +2024-11-22 10:41:27.214416: +2024-11-22 10:41:27.214650: Epoch 4402 +2024-11-22 10:41:27.214770: Current learning rate: 0.00487 +2024-11-22 10:41:45.342614: train_loss -0.7957 +2024-11-22 10:41:45.342841: val_loss -0.7565 +2024-11-22 10:41:45.342921: Pseudo dice [0.8371] +2024-11-22 10:41:45.348148: Epoch time: 18.13 s +2024-11-22 10:41:46.229047: +2024-11-22 10:41:46.229324: Epoch 4403 +2024-11-22 10:41:46.229437: Current learning rate: 0.00487 +2024-11-22 10:42:04.015126: train_loss -0.7969 +2024-11-22 10:42:04.015344: val_loss -0.75 +2024-11-22 10:42:04.015419: Pseudo dice [0.8334] +2024-11-22 10:42:04.015499: Epoch time: 17.79 s +2024-11-22 10:42:04.887717: +2024-11-22 10:42:04.887982: Epoch 4404 +2024-11-22 10:42:04.888099: Current learning rate: 0.00487 +2024-11-22 10:42:23.205487: train_loss -0.7991 +2024-11-22 10:42:23.206035: val_loss -0.7718 +2024-11-22 10:42:23.206127: Pseudo dice [0.8422] +2024-11-22 10:42:23.206209: Epoch time: 18.32 s +2024-11-22 10:42:24.074347: +2024-11-22 10:42:24.074567: Epoch 4405 +2024-11-22 10:42:24.074678: Current learning rate: 0.00487 +2024-11-22 10:42:42.732025: train_loss -0.8002 +2024-11-22 10:42:42.732237: val_loss -0.7532 +2024-11-22 10:42:42.732307: Pseudo dice [0.838] +2024-11-22 10:42:42.732383: Epoch time: 18.66 s +2024-11-22 10:42:43.635656: +2024-11-22 10:42:43.635864: Epoch 4406 +2024-11-22 10:42:43.635985: Current learning rate: 0.00487 +2024-11-22 10:43:02.721741: train_loss -0.7921 +2024-11-22 10:43:02.721956: val_loss -0.7349 +2024-11-22 10:43:02.722038: Pseudo dice [0.8198] +2024-11-22 10:43:02.722113: Epoch time: 19.09 s +2024-11-22 10:43:03.595837: +2024-11-22 10:43:03.596059: Epoch 4407 +2024-11-22 10:43:03.596176: Current learning rate: 0.00487 +2024-11-22 10:43:22.332614: train_loss -0.7886 +2024-11-22 10:43:22.332903: val_loss -0.7515 +2024-11-22 10:43:22.332985: Pseudo dice [0.828] +2024-11-22 10:43:22.333082: Epoch time: 18.73 s +2024-11-22 10:43:23.367149: +2024-11-22 10:43:23.367376: Epoch 4408 +2024-11-22 10:43:23.367500: Current learning rate: 0.00486 +2024-11-22 10:43:41.565078: train_loss -0.7964 +2024-11-22 10:43:41.565291: val_loss -0.7454 +2024-11-22 10:43:41.565375: Pseudo dice [0.8031] +2024-11-22 10:43:41.565456: Epoch time: 18.2 s +2024-11-22 10:43:42.436783: +2024-11-22 10:43:42.437025: Epoch 4409 +2024-11-22 10:43:42.437145: Current learning rate: 0.00486 +2024-11-22 10:44:00.946722: train_loss -0.7865 +2024-11-22 10:44:00.946943: val_loss -0.7633 +2024-11-22 10:44:00.947139: Pseudo dice [0.8325] +2024-11-22 10:44:00.947224: Epoch time: 18.51 s +2024-11-22 10:44:01.820638: +2024-11-22 10:44:01.820861: Epoch 4410 +2024-11-22 10:44:01.820976: Current learning rate: 0.00486 +2024-11-22 10:44:20.271457: train_loss -0.8032 +2024-11-22 10:44:20.274039: val_loss -0.771 +2024-11-22 10:44:20.274160: Pseudo dice [0.8414] +2024-11-22 10:44:20.274255: Epoch time: 18.45 s +2024-11-22 10:44:21.238584: +2024-11-22 10:44:21.238807: Epoch 4411 +2024-11-22 10:44:21.238918: Current learning rate: 0.00486 +2024-11-22 10:44:38.981393: train_loss -0.7977 +2024-11-22 10:44:38.981609: val_loss -0.7651 +2024-11-22 10:44:38.981683: Pseudo dice [0.822] +2024-11-22 10:44:38.981757: Epoch time: 17.74 s +2024-11-22 10:44:39.857047: +2024-11-22 10:44:39.857278: Epoch 4412 +2024-11-22 10:44:39.857395: Current learning rate: 0.00486 +2024-11-22 10:44:58.737564: train_loss -0.7951 +2024-11-22 10:44:58.737784: val_loss -0.7632 +2024-11-22 10:44:58.737910: Pseudo dice [0.847] +2024-11-22 10:44:58.738001: Epoch time: 18.88 s +2024-11-22 10:44:59.611552: +2024-11-22 10:44:59.611793: Epoch 4413 +2024-11-22 10:44:59.611907: Current learning rate: 0.00486 +2024-11-22 10:45:19.298774: train_loss -0.7889 +2024-11-22 10:45:19.299066: val_loss -0.7556 +2024-11-22 10:45:19.299141: Pseudo dice [0.8424] +2024-11-22 10:45:19.299224: Epoch time: 19.69 s +2024-11-22 10:45:20.324277: +2024-11-22 10:45:20.324509: Epoch 4414 +2024-11-22 10:45:20.324624: Current learning rate: 0.00486 +2024-11-22 10:45:38.609466: train_loss -0.7942 +2024-11-22 10:45:38.609684: val_loss -0.7646 +2024-11-22 10:45:38.609757: Pseudo dice [0.8307] +2024-11-22 10:45:38.609831: Epoch time: 18.29 s +2024-11-22 10:45:39.479472: +2024-11-22 10:45:39.479709: Epoch 4415 +2024-11-22 10:45:39.479823: Current learning rate: 0.00486 +2024-11-22 10:45:57.863182: train_loss -0.7924 +2024-11-22 10:45:57.863410: val_loss -0.6975 +2024-11-22 10:45:57.863486: Pseudo dice [0.8167] +2024-11-22 10:45:57.863564: Epoch time: 18.38 s +2024-11-22 10:45:58.741923: +2024-11-22 10:45:58.742147: Epoch 4416 +2024-11-22 10:45:58.742261: Current learning rate: 0.00485 +2024-11-22 10:46:17.215281: train_loss -0.7758 +2024-11-22 10:46:17.215504: val_loss -0.737 +2024-11-22 10:46:17.215580: Pseudo dice [0.8321] +2024-11-22 10:46:17.215665: Epoch time: 18.47 s +2024-11-22 10:46:18.177307: +2024-11-22 10:46:18.177507: Epoch 4417 +2024-11-22 10:46:18.190293: Current learning rate: 0.00485 +2024-11-22 10:46:35.940830: train_loss -0.7874 +2024-11-22 10:46:35.941127: val_loss -0.7605 +2024-11-22 10:46:35.941201: Pseudo dice [0.826] +2024-11-22 10:46:35.941282: Epoch time: 17.76 s +2024-11-22 10:46:36.815974: +2024-11-22 10:46:36.816211: Epoch 4418 +2024-11-22 10:46:36.816324: Current learning rate: 0.00485 +2024-11-22 10:46:56.635189: train_loss -0.7854 +2024-11-22 10:46:56.635398: val_loss -0.74 +2024-11-22 10:46:56.635471: Pseudo dice [0.8225] +2024-11-22 10:46:56.635547: Epoch time: 19.82 s +2024-11-22 10:46:57.520092: +2024-11-22 10:46:57.520344: Epoch 4419 +2024-11-22 10:46:57.520458: Current learning rate: 0.00485 +2024-11-22 10:47:16.077956: train_loss -0.7839 +2024-11-22 10:47:16.078189: val_loss -0.7459 +2024-11-22 10:47:16.078288: Pseudo dice [0.8312] +2024-11-22 10:47:16.078368: Epoch time: 18.56 s +2024-11-22 10:47:16.949445: +2024-11-22 10:47:16.949653: Epoch 4420 +2024-11-22 10:47:16.949769: Current learning rate: 0.00485 +2024-11-22 10:47:36.605576: train_loss -0.7864 +2024-11-22 10:47:36.605824: val_loss -0.7466 +2024-11-22 10:47:36.605898: Pseudo dice [0.8361] +2024-11-22 10:47:36.606025: Epoch time: 19.66 s +2024-11-22 10:47:37.483238: +2024-11-22 10:47:37.483430: Epoch 4421 +2024-11-22 10:47:37.483543: Current learning rate: 0.00485 +2024-11-22 10:47:56.229137: train_loss -0.7875 +2024-11-22 10:47:56.229359: val_loss -0.732 +2024-11-22 10:47:56.229438: Pseudo dice [0.8225] +2024-11-22 10:47:56.229521: Epoch time: 18.75 s +2024-11-22 10:47:57.096429: +2024-11-22 10:47:57.096640: Epoch 4422 +2024-11-22 10:47:57.096751: Current learning rate: 0.00485 +2024-11-22 10:48:16.047371: train_loss -0.7946 +2024-11-22 10:48:16.047651: val_loss -0.73 +2024-11-22 10:48:16.047728: Pseudo dice [0.829] +2024-11-22 10:48:16.047807: Epoch time: 18.95 s +2024-11-22 10:48:16.952686: +2024-11-22 10:48:16.952904: Epoch 4423 +2024-11-22 10:48:16.953019: Current learning rate: 0.00485 +2024-11-22 10:48:34.227830: train_loss -0.7801 +2024-11-22 10:48:34.230240: val_loss -0.7357 +2024-11-22 10:48:34.230362: Pseudo dice [0.8083] +2024-11-22 10:48:34.230448: Epoch time: 17.28 s +2024-11-22 10:48:35.235923: +2024-11-22 10:48:35.236153: Epoch 4424 +2024-11-22 10:48:35.236265: Current learning rate: 0.00484 +2024-11-22 10:48:54.332428: train_loss -0.7922 +2024-11-22 10:48:54.332646: val_loss -0.737 +2024-11-22 10:48:54.332720: Pseudo dice [0.8188] +2024-11-22 10:48:54.332799: Epoch time: 19.1 s +2024-11-22 10:48:55.237746: +2024-11-22 10:48:55.237954: Epoch 4425 +2024-11-22 10:48:55.238073: Current learning rate: 0.00484 +2024-11-22 10:49:14.200587: train_loss -0.7904 +2024-11-22 10:49:14.200800: val_loss -0.7529 +2024-11-22 10:49:14.200920: Pseudo dice [0.8348] +2024-11-22 10:49:14.201005: Epoch time: 18.96 s +2024-11-22 10:49:15.078823: +2024-11-22 10:49:15.079033: Epoch 4426 +2024-11-22 10:49:15.079151: Current learning rate: 0.00484 +2024-11-22 10:49:32.876528: train_loss -0.7846 +2024-11-22 10:49:32.876832: val_loss -0.7325 +2024-11-22 10:49:32.876912: Pseudo dice [0.8315] +2024-11-22 10:49:32.877005: Epoch time: 17.8 s +2024-11-22 10:49:33.749449: +2024-11-22 10:49:33.749658: Epoch 4427 +2024-11-22 10:49:33.749774: Current learning rate: 0.00484 +2024-11-22 10:49:54.272203: train_loss -0.7931 +2024-11-22 10:49:54.272464: val_loss -0.7267 +2024-11-22 10:49:54.272547: Pseudo dice [0.8176] +2024-11-22 10:49:54.272633: Epoch time: 20.52 s +2024-11-22 10:49:55.250803: +2024-11-22 10:49:55.251007: Epoch 4428 +2024-11-22 10:49:55.251120: Current learning rate: 0.00484 +2024-11-22 10:50:13.775510: train_loss -0.7922 +2024-11-22 10:50:13.775721: val_loss -0.7258 +2024-11-22 10:50:13.775793: Pseudo dice [0.8328] +2024-11-22 10:50:13.775872: Epoch time: 18.53 s +2024-11-22 10:50:14.660988: +2024-11-22 10:50:14.661187: Epoch 4429 +2024-11-22 10:50:14.661296: Current learning rate: 0.00484 +2024-11-22 10:50:33.309466: train_loss -0.7822 +2024-11-22 10:50:33.311836: val_loss -0.7634 +2024-11-22 10:50:33.311934: Pseudo dice [0.8339] +2024-11-22 10:50:33.312019: Epoch time: 18.65 s +2024-11-22 10:50:34.212595: +2024-11-22 10:50:34.212784: Epoch 4430 +2024-11-22 10:50:34.212891: Current learning rate: 0.00484 +2024-11-22 10:50:53.011681: train_loss -0.7892 +2024-11-22 10:50:53.012316: val_loss -0.7675 +2024-11-22 10:50:53.012414: Pseudo dice [0.8321] +2024-11-22 10:50:53.012497: Epoch time: 18.8 s +2024-11-22 10:50:53.888498: +2024-11-22 10:50:53.888701: Epoch 4431 +2024-11-22 10:50:53.888808: Current learning rate: 0.00484 +2024-11-22 10:51:11.552457: train_loss -0.7969 +2024-11-22 10:51:11.552676: val_loss -0.7638 +2024-11-22 10:51:11.552776: Pseudo dice [0.8335] +2024-11-22 10:51:11.552857: Epoch time: 17.66 s +2024-11-22 10:51:12.423305: +2024-11-22 10:51:12.423523: Epoch 4432 +2024-11-22 10:51:12.423641: Current learning rate: 0.00484 +2024-11-22 10:51:29.592396: train_loss -0.7924 +2024-11-22 10:51:29.592616: val_loss -0.7434 +2024-11-22 10:51:29.592694: Pseudo dice [0.8207] +2024-11-22 10:51:29.592773: Epoch time: 17.17 s +2024-11-22 10:51:30.463740: +2024-11-22 10:51:30.463942: Epoch 4433 +2024-11-22 10:51:30.464058: Current learning rate: 0.00483 +2024-11-22 10:51:49.508780: train_loss -0.7843 +2024-11-22 10:51:49.509074: val_loss -0.7374 +2024-11-22 10:51:49.509155: Pseudo dice [0.8339] +2024-11-22 10:51:49.509234: Epoch time: 19.05 s +2024-11-22 10:51:50.390543: +2024-11-22 10:51:50.390755: Epoch 4434 +2024-11-22 10:51:50.390871: Current learning rate: 0.00483 +2024-11-22 10:52:09.367255: train_loss -0.7917 +2024-11-22 10:52:09.367728: val_loss -0.7558 +2024-11-22 10:52:09.367883: Pseudo dice [0.8224] +2024-11-22 10:52:09.367968: Epoch time: 18.98 s +2024-11-22 10:52:10.265492: +2024-11-22 10:52:10.265706: Epoch 4435 +2024-11-22 10:52:10.265816: Current learning rate: 0.00483 +2024-11-22 10:52:28.741317: train_loss -0.7963 +2024-11-22 10:52:28.741539: val_loss -0.7478 +2024-11-22 10:52:28.741616: Pseudo dice [0.8213] +2024-11-22 10:52:28.741695: Epoch time: 18.48 s +2024-11-22 10:52:29.610577: +2024-11-22 10:52:29.610857: Epoch 4436 +2024-11-22 10:52:29.610975: Current learning rate: 0.00483 +2024-11-22 10:52:49.072696: train_loss -0.79 +2024-11-22 10:52:49.072919: val_loss -0.767 +2024-11-22 10:52:49.073001: Pseudo dice [0.8192] +2024-11-22 10:52:49.073080: Epoch time: 19.46 s +2024-11-22 10:52:50.076102: +2024-11-22 10:52:50.076371: Epoch 4437 +2024-11-22 10:52:50.076484: Current learning rate: 0.00483 +2024-11-22 10:53:09.394053: train_loss -0.7916 +2024-11-22 10:53:09.394298: val_loss -0.7453 +2024-11-22 10:53:09.394375: Pseudo dice [0.8219] +2024-11-22 10:53:09.394455: Epoch time: 19.32 s +2024-11-22 10:53:10.268729: +2024-11-22 10:53:10.268956: Epoch 4438 +2024-11-22 10:53:10.269074: Current learning rate: 0.00483 +2024-11-22 10:53:28.800176: train_loss -0.7948 +2024-11-22 10:53:28.800403: val_loss -0.757 +2024-11-22 10:53:28.800538: Pseudo dice [0.8451] +2024-11-22 10:53:28.800617: Epoch time: 18.53 s +2024-11-22 10:53:29.674839: +2024-11-22 10:53:29.675045: Epoch 4439 +2024-11-22 10:53:29.675167: Current learning rate: 0.00483 +2024-11-22 10:53:47.728184: train_loss -0.7901 +2024-11-22 10:53:47.728484: val_loss -0.735 +2024-11-22 10:53:47.728565: Pseudo dice [0.8309] +2024-11-22 10:53:47.728645: Epoch time: 18.05 s +2024-11-22 10:53:48.605013: +2024-11-22 10:53:48.605235: Epoch 4440 +2024-11-22 10:53:48.605351: Current learning rate: 0.00483 +2024-11-22 10:54:07.138112: train_loss -0.7734 +2024-11-22 10:54:07.138335: val_loss -0.7404 +2024-11-22 10:54:07.138414: Pseudo dice [0.8242] +2024-11-22 10:54:07.138495: Epoch time: 18.53 s +2024-11-22 10:54:08.015759: +2024-11-22 10:54:08.016000: Epoch 4441 +2024-11-22 10:54:08.016121: Current learning rate: 0.00482 +2024-11-22 10:54:27.059324: train_loss -0.7807 +2024-11-22 10:54:27.059577: val_loss -0.7493 +2024-11-22 10:54:27.059649: Pseudo dice [0.8404] +2024-11-22 10:54:27.059731: Epoch time: 19.04 s +2024-11-22 10:54:27.974029: +2024-11-22 10:54:27.974231: Epoch 4442 +2024-11-22 10:54:27.974346: Current learning rate: 0.00482 +2024-11-22 10:54:47.637552: train_loss -0.7862 +2024-11-22 10:54:47.637801: val_loss -0.7515 +2024-11-22 10:54:47.669469: Pseudo dice [0.8305] +2024-11-22 10:54:47.669618: Epoch time: 19.66 s +2024-11-22 10:54:48.540339: +2024-11-22 10:54:48.540698: Epoch 4443 +2024-11-22 10:54:48.540812: Current learning rate: 0.00482 +2024-11-22 10:55:07.140375: train_loss -0.7856 +2024-11-22 10:55:07.142777: val_loss -0.7601 +2024-11-22 10:55:07.142903: Pseudo dice [0.8426] +2024-11-22 10:55:07.142984: Epoch time: 18.6 s +2024-11-22 10:55:08.219489: +2024-11-22 10:55:08.219699: Epoch 4444 +2024-11-22 10:55:08.219810: Current learning rate: 0.00482 +2024-11-22 10:55:27.354180: train_loss -0.7779 +2024-11-22 10:55:27.354452: val_loss -0.7526 +2024-11-22 10:55:27.354533: Pseudo dice [0.8348] +2024-11-22 10:55:27.354610: Epoch time: 19.14 s +2024-11-22 10:55:28.233193: +2024-11-22 10:55:28.233426: Epoch 4445 +2024-11-22 10:55:28.233541: Current learning rate: 0.00482 +2024-11-22 10:55:47.465424: train_loss -0.7857 +2024-11-22 10:55:47.465643: val_loss -0.7457 +2024-11-22 10:55:47.465718: Pseudo dice [0.8351] +2024-11-22 10:55:47.465797: Epoch time: 19.23 s +2024-11-22 10:55:48.339672: +2024-11-22 10:55:48.339864: Epoch 4446 +2024-11-22 10:55:48.339974: Current learning rate: 0.00482 +2024-11-22 10:56:06.920485: train_loss -0.7817 +2024-11-22 10:56:06.920982: val_loss -0.752 +2024-11-22 10:56:06.921089: Pseudo dice [0.8374] +2024-11-22 10:56:06.921168: Epoch time: 18.58 s +2024-11-22 10:56:07.838796: +2024-11-22 10:56:07.839063: Epoch 4447 +2024-11-22 10:56:07.839178: Current learning rate: 0.00482 +2024-11-22 10:56:27.426852: train_loss -0.7896 +2024-11-22 10:56:27.427074: val_loss -0.7422 +2024-11-22 10:56:27.427157: Pseudo dice [0.8295] +2024-11-22 10:56:27.427237: Epoch time: 19.59 s +2024-11-22 10:56:28.463799: +2024-11-22 10:56:28.464016: Epoch 4448 +2024-11-22 10:56:28.464131: Current learning rate: 0.00482 +2024-11-22 10:56:47.446741: train_loss -0.7952 +2024-11-22 10:56:47.447002: val_loss -0.7424 +2024-11-22 10:56:47.447099: Pseudo dice [0.8338] +2024-11-22 10:56:47.447186: Epoch time: 18.98 s +2024-11-22 10:56:48.323601: +2024-11-22 10:56:48.323805: Epoch 4449 +2024-11-22 10:56:48.323922: Current learning rate: 0.00481 +2024-11-22 10:57:07.715904: train_loss -0.7942 +2024-11-22 10:57:07.716110: val_loss -0.7683 +2024-11-22 10:57:07.716182: Pseudo dice [0.8199] +2024-11-22 10:57:07.717248: Epoch time: 19.39 s +2024-11-22 10:57:08.870344: +2024-11-22 10:57:08.870550: Epoch 4450 +2024-11-22 10:57:08.870663: Current learning rate: 0.00481 +2024-11-22 10:57:27.919659: train_loss -0.7907 +2024-11-22 10:57:27.919889: val_loss -0.7442 +2024-11-22 10:57:27.919966: Pseudo dice [0.8239] +2024-11-22 10:57:27.920050: Epoch time: 19.05 s +2024-11-22 10:57:28.799528: +2024-11-22 10:57:28.799754: Epoch 4451 +2024-11-22 10:57:28.799870: Current learning rate: 0.00481 +2024-11-22 10:57:47.709764: train_loss -0.7975 +2024-11-22 10:57:47.709979: val_loss -0.7401 +2024-11-22 10:57:47.710059: Pseudo dice [0.8297] +2024-11-22 10:57:47.710136: Epoch time: 18.91 s +2024-11-22 10:57:48.593170: +2024-11-22 10:57:48.593420: Epoch 4452 +2024-11-22 10:57:48.593556: Current learning rate: 0.00481 +2024-11-22 10:58:07.347406: train_loss -0.7898 +2024-11-22 10:58:07.347662: val_loss -0.7378 +2024-11-22 10:58:07.347744: Pseudo dice [0.8259] +2024-11-22 10:58:07.347827: Epoch time: 18.76 s +2024-11-22 10:58:08.222922: +2024-11-22 10:58:08.223159: Epoch 4453 +2024-11-22 10:58:08.223283: Current learning rate: 0.00481 +2024-11-22 10:58:25.997734: train_loss -0.7958 +2024-11-22 10:58:25.997958: val_loss -0.7542 +2024-11-22 10:58:25.998043: Pseudo dice [0.8256] +2024-11-22 10:58:25.998121: Epoch time: 17.78 s +2024-11-22 10:58:26.927054: +2024-11-22 10:58:26.927261: Epoch 4454 +2024-11-22 10:58:26.927373: Current learning rate: 0.00481 +2024-11-22 10:58:46.875656: train_loss -0.788 +2024-11-22 10:58:46.875921: val_loss -0.7323 +2024-11-22 10:58:46.876009: Pseudo dice [0.8204] +2024-11-22 10:58:46.876089: Epoch time: 19.95 s +2024-11-22 10:58:47.746206: +2024-11-22 10:58:47.746407: Epoch 4455 +2024-11-22 10:58:47.746528: Current learning rate: 0.00481 +2024-11-22 10:59:07.344644: train_loss -0.7934 +2024-11-22 10:59:07.344860: val_loss -0.7596 +2024-11-22 10:59:07.344934: Pseudo dice [0.8341] +2024-11-22 10:59:07.345016: Epoch time: 19.6 s +2024-11-22 10:59:08.224356: +2024-11-22 10:59:08.224612: Epoch 4456 +2024-11-22 10:59:08.224726: Current learning rate: 0.00481 +2024-11-22 10:59:28.125910: train_loss -0.7873 +2024-11-22 10:59:28.126135: val_loss -0.7091 +2024-11-22 10:59:28.126209: Pseudo dice [0.8115] +2024-11-22 10:59:28.126282: Epoch time: 19.9 s +2024-11-22 10:59:29.037973: +2024-11-22 10:59:29.038213: Epoch 4457 +2024-11-22 10:59:29.038330: Current learning rate: 0.0048 +2024-11-22 10:59:48.839193: train_loss -0.7917 +2024-11-22 10:59:48.839425: val_loss -0.7359 +2024-11-22 10:59:48.839521: Pseudo dice [0.8419] +2024-11-22 10:59:48.839599: Epoch time: 19.8 s +2024-11-22 10:59:49.712838: +2024-11-22 10:59:49.713054: Epoch 4458 +2024-11-22 10:59:49.713165: Current learning rate: 0.0048 +2024-11-22 11:00:07.779933: train_loss -0.794 +2024-11-22 11:00:07.790797: val_loss -0.7327 +2024-11-22 11:00:07.790915: Pseudo dice [0.8318] +2024-11-22 11:00:07.791013: Epoch time: 18.07 s +2024-11-22 11:00:08.850546: +2024-11-22 11:00:08.850768: Epoch 4459 +2024-11-22 11:00:08.850883: Current learning rate: 0.0048 +2024-11-22 11:00:27.770522: train_loss -0.7756 +2024-11-22 11:00:27.770771: val_loss -0.7479 +2024-11-22 11:00:27.770860: Pseudo dice [0.8198] +2024-11-22 11:00:27.770945: Epoch time: 18.92 s +2024-11-22 11:00:28.642276: +2024-11-22 11:00:28.642498: Epoch 4460 +2024-11-22 11:00:28.642609: Current learning rate: 0.0048 +2024-11-22 11:00:47.047631: train_loss -0.7914 +2024-11-22 11:00:47.047861: val_loss -0.7509 +2024-11-22 11:00:47.047938: Pseudo dice [0.8178] +2024-11-22 11:00:47.048020: Epoch time: 18.41 s +2024-11-22 11:00:47.926145: +2024-11-22 11:00:47.926450: Epoch 4461 +2024-11-22 11:00:47.926563: Current learning rate: 0.0048 +2024-11-22 11:01:05.688113: train_loss -0.7901 +2024-11-22 11:01:05.688386: val_loss -0.7375 +2024-11-22 11:01:05.688461: Pseudo dice [0.8228] +2024-11-22 11:01:05.688537: Epoch time: 17.76 s +2024-11-22 11:01:06.565329: +2024-11-22 11:01:06.565576: Epoch 4462 +2024-11-22 11:01:06.565737: Current learning rate: 0.0048 +2024-11-22 11:01:25.024724: train_loss -0.7943 +2024-11-22 11:01:25.025001: val_loss -0.7517 +2024-11-22 11:01:25.025079: Pseudo dice [0.8179] +2024-11-22 11:01:25.025162: Epoch time: 18.46 s +2024-11-22 11:01:25.899055: +2024-11-22 11:01:25.899298: Epoch 4463 +2024-11-22 11:01:25.899414: Current learning rate: 0.0048 +2024-11-22 11:01:44.166268: train_loss -0.7873 +2024-11-22 11:01:44.166488: val_loss -0.7664 +2024-11-22 11:01:44.166567: Pseudo dice [0.8497] +2024-11-22 11:01:44.166646: Epoch time: 18.27 s +2024-11-22 11:01:45.044698: +2024-11-22 11:01:45.045017: Epoch 4464 +2024-11-22 11:01:45.045128: Current learning rate: 0.0048 +2024-11-22 11:02:05.497175: train_loss -0.7888 +2024-11-22 11:02:05.497406: val_loss -0.7618 +2024-11-22 11:02:05.497481: Pseudo dice [0.828] +2024-11-22 11:02:05.497632: Epoch time: 20.45 s +2024-11-22 11:02:06.379182: +2024-11-22 11:02:06.379387: Epoch 4465 +2024-11-22 11:02:06.379495: Current learning rate: 0.00479 +2024-11-22 11:02:25.641450: train_loss -0.7898 +2024-11-22 11:02:25.641659: val_loss -0.7516 +2024-11-22 11:02:25.641733: Pseudo dice [0.8236] +2024-11-22 11:02:25.641812: Epoch time: 19.26 s +2024-11-22 11:02:26.524430: +2024-11-22 11:02:26.524680: Epoch 4466 +2024-11-22 11:02:26.524792: Current learning rate: 0.00479 +2024-11-22 11:02:45.619670: train_loss -0.7807 +2024-11-22 11:02:45.619919: val_loss -0.7334 +2024-11-22 11:02:45.620006: Pseudo dice [0.8206] +2024-11-22 11:02:45.620093: Epoch time: 19.1 s +2024-11-22 11:02:46.587795: +2024-11-22 11:02:46.588042: Epoch 4467 +2024-11-22 11:02:46.588156: Current learning rate: 0.00479 +2024-11-22 11:03:04.834697: train_loss -0.7709 +2024-11-22 11:03:04.834922: val_loss -0.7049 +2024-11-22 11:03:04.835004: Pseudo dice [0.8045] +2024-11-22 11:03:04.835212: Epoch time: 18.25 s +2024-11-22 11:03:05.708521: +2024-11-22 11:03:05.708720: Epoch 4468 +2024-11-22 11:03:05.708832: Current learning rate: 0.00479 +2024-11-22 11:03:24.544703: train_loss -0.7812 +2024-11-22 11:03:24.544982: val_loss -0.7521 +2024-11-22 11:03:24.545083: Pseudo dice [0.836] +2024-11-22 11:03:24.545164: Epoch time: 18.84 s +2024-11-22 11:03:25.419476: +2024-11-22 11:03:25.419709: Epoch 4469 +2024-11-22 11:03:25.419829: Current learning rate: 0.00479 +2024-11-22 11:03:43.596257: train_loss -0.7897 +2024-11-22 11:03:43.598669: val_loss -0.726 +2024-11-22 11:03:43.598784: Pseudo dice [0.827] +2024-11-22 11:03:43.598888: Epoch time: 18.18 s +2024-11-22 11:03:44.472943: +2024-11-22 11:03:44.473356: Epoch 4470 +2024-11-22 11:03:44.473487: Current learning rate: 0.00479 +2024-11-22 11:04:02.397220: train_loss -0.7905 +2024-11-22 11:04:02.397734: val_loss -0.7728 +2024-11-22 11:04:02.397847: Pseudo dice [0.8353] +2024-11-22 11:04:02.397961: Epoch time: 17.93 s +2024-11-22 11:04:03.268808: +2024-11-22 11:04:03.269052: Epoch 4471 +2024-11-22 11:04:03.269165: Current learning rate: 0.00479 +2024-11-22 11:04:21.809955: train_loss -0.8011 +2024-11-22 11:04:21.810194: val_loss -0.7267 +2024-11-22 11:04:21.810273: Pseudo dice [0.8246] +2024-11-22 11:04:21.810356: Epoch time: 18.54 s +2024-11-22 11:04:22.791849: +2024-11-22 11:04:22.792096: Epoch 4472 +2024-11-22 11:04:22.792217: Current learning rate: 0.00479 +2024-11-22 11:04:41.366790: train_loss -0.7898 +2024-11-22 11:04:41.367038: val_loss -0.7412 +2024-11-22 11:04:41.367114: Pseudo dice [0.8256] +2024-11-22 11:04:41.367198: Epoch time: 18.58 s +2024-11-22 11:04:42.282144: +2024-11-22 11:04:42.282351: Epoch 4473 +2024-11-22 11:04:42.282460: Current learning rate: 0.00479 +2024-11-22 11:05:01.139869: train_loss -0.7852 +2024-11-22 11:05:01.140773: val_loss -0.7741 +2024-11-22 11:05:01.140885: Pseudo dice [0.8467] +2024-11-22 11:05:01.140966: Epoch time: 18.86 s +2024-11-22 11:05:02.017296: +2024-11-22 11:05:02.017506: Epoch 4474 +2024-11-22 11:05:02.017624: Current learning rate: 0.00478 +2024-11-22 11:05:20.294415: train_loss -0.7819 +2024-11-22 11:05:20.294631: val_loss -0.73 +2024-11-22 11:05:20.294706: Pseudo dice [0.807] +2024-11-22 11:05:20.294806: Epoch time: 18.28 s +2024-11-22 11:05:21.171077: +2024-11-22 11:05:21.171354: Epoch 4475 +2024-11-22 11:05:21.171470: Current learning rate: 0.00478 +2024-11-22 11:05:40.094307: train_loss -0.7879 +2024-11-22 11:05:40.094549: val_loss -0.7625 +2024-11-22 11:05:40.094682: Pseudo dice [0.8278] +2024-11-22 11:05:40.094762: Epoch time: 18.92 s +2024-11-22 11:05:40.996640: +2024-11-22 11:05:40.996910: Epoch 4476 +2024-11-22 11:05:40.997032: Current learning rate: 0.00478 +2024-11-22 11:05:59.748095: train_loss -0.7961 +2024-11-22 11:05:59.748352: val_loss -0.7231 +2024-11-22 11:05:59.748429: Pseudo dice [0.8237] +2024-11-22 11:05:59.748512: Epoch time: 18.75 s +2024-11-22 11:06:00.624844: +2024-11-22 11:06:00.625058: Epoch 4477 +2024-11-22 11:06:00.625193: Current learning rate: 0.00478 +2024-11-22 11:06:19.226491: train_loss -0.7962 +2024-11-22 11:06:19.226717: val_loss -0.7735 +2024-11-22 11:06:19.226791: Pseudo dice [0.8377] +2024-11-22 11:06:19.226866: Epoch time: 18.6 s +2024-11-22 11:06:20.101933: +2024-11-22 11:06:20.102133: Epoch 4478 +2024-11-22 11:06:20.102254: Current learning rate: 0.00478 +2024-11-22 11:06:37.656330: train_loss -0.8 +2024-11-22 11:06:37.656551: val_loss -0.7359 +2024-11-22 11:06:37.656624: Pseudo dice [0.8228] +2024-11-22 11:06:37.656704: Epoch time: 17.56 s +2024-11-22 11:06:38.533971: +2024-11-22 11:06:38.534269: Epoch 4479 +2024-11-22 11:06:38.534386: Current learning rate: 0.00478 +2024-11-22 11:06:56.629742: train_loss -0.7946 +2024-11-22 11:06:56.629966: val_loss -0.7335 +2024-11-22 11:06:56.630055: Pseudo dice [0.8144] +2024-11-22 11:06:56.630139: Epoch time: 18.1 s +2024-11-22 11:06:57.507175: +2024-11-22 11:06:57.507381: Epoch 4480 +2024-11-22 11:06:57.507492: Current learning rate: 0.00478 +2024-11-22 11:07:16.236612: train_loss -0.792 +2024-11-22 11:07:16.236879: val_loss -0.7655 +2024-11-22 11:07:16.236988: Pseudo dice [0.8407] +2024-11-22 11:07:16.237077: Epoch time: 18.73 s +2024-11-22 11:07:17.112078: +2024-11-22 11:07:17.112282: Epoch 4481 +2024-11-22 11:07:17.112391: Current learning rate: 0.00478 +2024-11-22 11:07:35.917903: train_loss -0.7939 +2024-11-22 11:07:35.918121: val_loss -0.7807 +2024-11-22 11:07:35.918236: Pseudo dice [0.8409] +2024-11-22 11:07:35.918315: Epoch time: 18.81 s +2024-11-22 11:07:36.792835: +2024-11-22 11:07:36.793240: Epoch 4482 +2024-11-22 11:07:36.793370: Current learning rate: 0.00477 +2024-11-22 11:07:55.229355: train_loss -0.7932 +2024-11-22 11:07:55.230025: val_loss -0.7407 +2024-11-22 11:07:55.230130: Pseudo dice [0.8087] +2024-11-22 11:07:55.230223: Epoch time: 18.44 s +2024-11-22 11:07:56.109408: +2024-11-22 11:07:56.109642: Epoch 4483 +2024-11-22 11:07:56.109756: Current learning rate: 0.00477 +2024-11-22 11:08:15.587774: train_loss -0.7947 +2024-11-22 11:08:15.588000: val_loss -0.7592 +2024-11-22 11:08:15.588077: Pseudo dice [0.8139] +2024-11-22 11:08:15.588155: Epoch time: 19.48 s +2024-11-22 11:08:16.494295: +2024-11-22 11:08:16.494515: Epoch 4484 +2024-11-22 11:08:16.494623: Current learning rate: 0.00477 +2024-11-22 11:08:35.803856: train_loss -0.7996 +2024-11-22 11:08:35.804084: val_loss -0.7366 +2024-11-22 11:08:35.804159: Pseudo dice [0.809] +2024-11-22 11:08:35.804234: Epoch time: 19.31 s +2024-11-22 11:08:36.679221: +2024-11-22 11:08:36.679443: Epoch 4485 +2024-11-22 11:08:36.679560: Current learning rate: 0.00477 +2024-11-22 11:08:54.887259: train_loss -0.7975 +2024-11-22 11:08:54.887508: val_loss -0.7697 +2024-11-22 11:08:54.887622: Pseudo dice [0.8313] +2024-11-22 11:08:54.887710: Epoch time: 18.21 s +2024-11-22 11:08:55.845958: +2024-11-22 11:08:55.846257: Epoch 4486 +2024-11-22 11:08:55.846373: Current learning rate: 0.00477 +2024-11-22 11:09:15.422352: train_loss -0.7966 +2024-11-22 11:09:15.422568: val_loss -0.7472 +2024-11-22 11:09:15.422640: Pseudo dice [0.8314] +2024-11-22 11:09:15.422716: Epoch time: 19.58 s +2024-11-22 11:09:16.303336: +2024-11-22 11:09:16.303566: Epoch 4487 +2024-11-22 11:09:16.303681: Current learning rate: 0.00477 +2024-11-22 11:09:34.079484: train_loss -0.7906 +2024-11-22 11:09:34.079709: val_loss -0.7523 +2024-11-22 11:09:34.079787: Pseudo dice [0.8235] +2024-11-22 11:09:34.079905: Epoch time: 17.78 s +2024-11-22 11:09:34.960915: +2024-11-22 11:09:34.961125: Epoch 4488 +2024-11-22 11:09:34.961240: Current learning rate: 0.00477 +2024-11-22 11:09:53.297789: train_loss -0.7982 +2024-11-22 11:09:53.298010: val_loss -0.7529 +2024-11-22 11:09:53.298084: Pseudo dice [0.8264] +2024-11-22 11:09:53.298160: Epoch time: 18.34 s +2024-11-22 11:09:54.288479: +2024-11-22 11:09:54.288705: Epoch 4489 +2024-11-22 11:09:54.288817: Current learning rate: 0.00477 +2024-11-22 11:10:12.311127: train_loss -0.7979 +2024-11-22 11:10:12.311368: val_loss -0.754 +2024-11-22 11:10:12.311445: Pseudo dice [0.8156] +2024-11-22 11:10:12.311532: Epoch time: 18.02 s +2024-11-22 11:10:13.188661: +2024-11-22 11:10:13.188857: Epoch 4490 +2024-11-22 11:10:13.188971: Current learning rate: 0.00476 +2024-11-22 11:10:31.054127: train_loss -0.7974 +2024-11-22 11:10:31.054345: val_loss -0.7587 +2024-11-22 11:10:31.054436: Pseudo dice [0.8295] +2024-11-22 11:10:31.054518: Epoch time: 17.87 s +2024-11-22 11:10:31.930742: +2024-11-22 11:10:31.930948: Epoch 4491 +2024-11-22 11:10:31.931069: Current learning rate: 0.00476 +2024-11-22 11:10:50.802450: train_loss -0.781 +2024-11-22 11:10:50.802672: val_loss -0.7463 +2024-11-22 11:10:50.802747: Pseudo dice [0.8343] +2024-11-22 11:10:50.802822: Epoch time: 18.87 s +2024-11-22 11:10:51.673016: +2024-11-22 11:10:51.673234: Epoch 4492 +2024-11-22 11:10:51.673351: Current learning rate: 0.00476 +2024-11-22 11:11:09.979130: train_loss -0.7764 +2024-11-22 11:11:09.979335: val_loss -0.7194 +2024-11-22 11:11:09.979408: Pseudo dice [0.8323] +2024-11-22 11:11:09.979481: Epoch time: 18.31 s +2024-11-22 11:11:10.850337: +2024-11-22 11:11:10.850760: Epoch 4493 +2024-11-22 11:11:10.850899: Current learning rate: 0.00476 +2024-11-22 11:11:30.895026: train_loss -0.787 +2024-11-22 11:11:30.895272: val_loss -0.7613 +2024-11-22 11:11:30.895345: Pseudo dice [0.8362] +2024-11-22 11:11:30.900246: Epoch time: 20.05 s +2024-11-22 11:11:31.853943: +2024-11-22 11:11:31.854157: Epoch 4494 +2024-11-22 11:11:31.854273: Current learning rate: 0.00476 +2024-11-22 11:11:50.637535: train_loss -0.7924 +2024-11-22 11:11:50.638068: val_loss -0.7462 +2024-11-22 11:11:50.638170: Pseudo dice [0.8116] +2024-11-22 11:11:50.638250: Epoch time: 18.78 s +2024-11-22 11:11:51.511055: +2024-11-22 11:11:51.511302: Epoch 4495 +2024-11-22 11:11:51.511418: Current learning rate: 0.00476 +2024-11-22 11:12:09.182361: train_loss -0.7951 +2024-11-22 11:12:09.182600: val_loss -0.738 +2024-11-22 11:12:09.182674: Pseudo dice [0.8124] +2024-11-22 11:12:09.182753: Epoch time: 17.67 s +2024-11-22 11:12:10.215726: +2024-11-22 11:12:10.215941: Epoch 4496 +2024-11-22 11:12:10.216062: Current learning rate: 0.00476 +2024-11-22 11:12:28.810718: train_loss -0.79 +2024-11-22 11:12:28.810986: val_loss -0.7811 +2024-11-22 11:12:28.811072: Pseudo dice [0.837] +2024-11-22 11:12:28.811162: Epoch time: 18.6 s +2024-11-22 11:12:29.806660: +2024-11-22 11:12:29.806866: Epoch 4497 +2024-11-22 11:12:29.806978: Current learning rate: 0.00476 +2024-11-22 11:12:49.006726: train_loss -0.7951 +2024-11-22 11:12:49.006983: val_loss -0.7661 +2024-11-22 11:12:49.007065: Pseudo dice [0.8414] +2024-11-22 11:12:49.007145: Epoch time: 19.2 s +2024-11-22 11:12:49.883032: +2024-11-22 11:12:49.883255: Epoch 4498 +2024-11-22 11:12:49.883375: Current learning rate: 0.00475 +2024-11-22 11:13:09.198012: train_loss -0.7975 +2024-11-22 11:13:09.198225: val_loss -0.7612 +2024-11-22 11:13:09.198300: Pseudo dice [0.8442] +2024-11-22 11:13:09.198379: Epoch time: 19.32 s +2024-11-22 11:13:10.069174: +2024-11-22 11:13:10.069453: Epoch 4499 +2024-11-22 11:13:10.069568: Current learning rate: 0.00475 +2024-11-22 11:13:29.006807: train_loss -0.7991 +2024-11-22 11:13:29.007417: val_loss -0.7413 +2024-11-22 11:13:29.007503: Pseudo dice [0.8393] +2024-11-22 11:13:29.007583: Epoch time: 18.94 s +2024-11-22 11:13:30.144347: +2024-11-22 11:13:30.144566: Epoch 4500 +2024-11-22 11:13:30.144678: Current learning rate: 0.00475 +2024-11-22 11:13:49.106966: train_loss -0.8012 +2024-11-22 11:13:49.107222: val_loss -0.767 +2024-11-22 11:13:49.107304: Pseudo dice [0.8305] +2024-11-22 11:13:49.107387: Epoch time: 18.96 s +2024-11-22 11:13:50.002013: +2024-11-22 11:13:50.002338: Epoch 4501 +2024-11-22 11:13:50.002466: Current learning rate: 0.00475 +2024-11-22 11:14:09.319592: train_loss -0.8022 +2024-11-22 11:14:09.319825: val_loss -0.729 +2024-11-22 11:14:09.319904: Pseudo dice [0.8155] +2024-11-22 11:14:09.319988: Epoch time: 19.32 s +2024-11-22 11:14:10.209461: +2024-11-22 11:14:10.209691: Epoch 4502 +2024-11-22 11:14:10.209806: Current learning rate: 0.00475 +2024-11-22 11:14:29.120730: train_loss -0.7977 +2024-11-22 11:14:29.120946: val_loss -0.7451 +2024-11-22 11:14:29.121027: Pseudo dice [0.8289] +2024-11-22 11:14:29.121106: Epoch time: 18.91 s +2024-11-22 11:14:29.997963: +2024-11-22 11:14:29.998160: Epoch 4503 +2024-11-22 11:14:29.998271: Current learning rate: 0.00475 +2024-11-22 11:14:48.543629: train_loss -0.802 +2024-11-22 11:14:48.543839: val_loss -0.7497 +2024-11-22 11:14:48.543915: Pseudo dice [0.8381] +2024-11-22 11:14:48.544001: Epoch time: 18.55 s +2024-11-22 11:14:49.416485: +2024-11-22 11:14:49.416702: Epoch 4504 +2024-11-22 11:14:49.416816: Current learning rate: 0.00475 +2024-11-22 11:15:08.929633: train_loss -0.7934 +2024-11-22 11:15:08.929868: val_loss -0.7319 +2024-11-22 11:15:08.929941: Pseudo dice [0.835] +2024-11-22 11:15:08.930106: Epoch time: 19.51 s +2024-11-22 11:15:09.807122: +2024-11-22 11:15:09.807556: Epoch 4505 +2024-11-22 11:15:09.807688: Current learning rate: 0.00475 +2024-11-22 11:15:28.972480: train_loss -0.7967 +2024-11-22 11:15:28.972690: val_loss -0.7368 +2024-11-22 11:15:28.972770: Pseudo dice [0.8248] +2024-11-22 11:15:28.972850: Epoch time: 19.17 s +2024-11-22 11:15:29.849941: +2024-11-22 11:15:29.850217: Epoch 4506 +2024-11-22 11:15:29.864233: Current learning rate: 0.00474 +2024-11-22 11:15:48.879788: train_loss -0.7903 +2024-11-22 11:15:48.880264: val_loss -0.7632 +2024-11-22 11:15:48.880365: Pseudo dice [0.8389] +2024-11-22 11:15:48.880443: Epoch time: 19.03 s +2024-11-22 11:15:49.753324: +2024-11-22 11:15:49.753553: Epoch 4507 +2024-11-22 11:15:49.753675: Current learning rate: 0.00474 +2024-11-22 11:16:08.126578: train_loss -0.797 +2024-11-22 11:16:08.126830: val_loss -0.7549 +2024-11-22 11:16:08.126908: Pseudo dice [0.8573] +2024-11-22 11:16:08.126988: Epoch time: 18.37 s +2024-11-22 11:16:08.995792: +2024-11-22 11:16:08.996011: Epoch 4508 +2024-11-22 11:16:08.996125: Current learning rate: 0.00474 +2024-11-22 11:16:26.420812: train_loss -0.7989 +2024-11-22 11:16:26.421080: val_loss -0.7622 +2024-11-22 11:16:26.421160: Pseudo dice [0.8404] +2024-11-22 11:16:26.421240: Epoch time: 17.43 s +2024-11-22 11:16:27.295751: +2024-11-22 11:16:27.295945: Epoch 4509 +2024-11-22 11:16:27.296060: Current learning rate: 0.00474 +2024-11-22 11:16:45.818626: train_loss -0.7939 +2024-11-22 11:16:45.818865: val_loss -0.7489 +2024-11-22 11:16:45.818943: Pseudo dice [0.8473] +2024-11-22 11:16:45.819031: Epoch time: 18.52 s +2024-11-22 11:16:45.819093: Yayy! New best EMA pseudo Dice: 0.8352 +2024-11-22 11:16:46.982591: +2024-11-22 11:16:46.982807: Epoch 4510 +2024-11-22 11:16:46.982947: Current learning rate: 0.00474 +2024-11-22 11:17:07.133420: train_loss -0.7873 +2024-11-22 11:17:07.133670: val_loss -0.7572 +2024-11-22 11:17:07.133746: Pseudo dice [0.8129] +2024-11-22 11:17:07.133829: Epoch time: 20.15 s +2024-11-22 11:17:08.013360: +2024-11-22 11:17:08.013576: Epoch 4511 +2024-11-22 11:17:08.013698: Current learning rate: 0.00474 +2024-11-22 11:17:26.305755: train_loss -0.7937 +2024-11-22 11:17:26.305969: val_loss -0.769 +2024-11-22 11:17:26.306068: Pseudo dice [0.8416] +2024-11-22 11:17:26.306142: Epoch time: 18.29 s +2024-11-22 11:17:27.174788: +2024-11-22 11:17:27.174989: Epoch 4512 +2024-11-22 11:17:27.175226: Current learning rate: 0.00474 +2024-11-22 11:17:46.228563: train_loss -0.7859 +2024-11-22 11:17:46.228828: val_loss -0.7445 +2024-11-22 11:17:46.228906: Pseudo dice [0.8265] +2024-11-22 11:17:46.228983: Epoch time: 19.05 s +2024-11-22 11:17:47.106838: +2024-11-22 11:17:47.107065: Epoch 4513 +2024-11-22 11:17:47.107179: Current learning rate: 0.00474 +2024-11-22 11:18:04.959801: train_loss -0.7949 +2024-11-22 11:18:04.960034: val_loss -0.747 +2024-11-22 11:18:04.960113: Pseudo dice [0.8301] +2024-11-22 11:18:04.960193: Epoch time: 17.85 s +2024-11-22 11:18:05.836710: +2024-11-22 11:18:05.836908: Epoch 4514 +2024-11-22 11:18:05.837027: Current learning rate: 0.00473 +2024-11-22 11:18:23.827623: train_loss -0.7982 +2024-11-22 11:18:23.827892: val_loss -0.7716 +2024-11-22 11:18:23.827968: Pseudo dice [0.8251] +2024-11-22 11:18:23.828057: Epoch time: 17.99 s +2024-11-22 11:18:24.699093: +2024-11-22 11:18:24.699308: Epoch 4515 +2024-11-22 11:18:24.699418: Current learning rate: 0.00473 +2024-11-22 11:18:43.585226: train_loss -0.7943 +2024-11-22 11:18:43.585430: val_loss -0.7467 +2024-11-22 11:18:43.585502: Pseudo dice [0.8187] +2024-11-22 11:18:43.585632: Epoch time: 18.89 s +2024-11-22 11:18:44.460014: +2024-11-22 11:18:44.460475: Epoch 4516 +2024-11-22 11:18:44.460609: Current learning rate: 0.00473 +2024-11-22 11:19:02.662851: train_loss -0.8024 +2024-11-22 11:19:02.663136: val_loss -0.7297 +2024-11-22 11:19:02.663215: Pseudo dice [0.8261] +2024-11-22 11:19:02.663291: Epoch time: 18.2 s +2024-11-22 11:19:03.557426: +2024-11-22 11:19:03.557636: Epoch 4517 +2024-11-22 11:19:03.557747: Current learning rate: 0.00473 +2024-11-22 11:19:23.134965: train_loss -0.7991 +2024-11-22 11:19:23.135187: val_loss -0.7253 +2024-11-22 11:19:23.135261: Pseudo dice [0.8147] +2024-11-22 11:19:23.135340: Epoch time: 19.58 s +2024-11-22 11:19:24.011978: +2024-11-22 11:19:24.012285: Epoch 4518 +2024-11-22 11:19:24.012402: Current learning rate: 0.00473 +2024-11-22 11:19:42.195596: train_loss -0.7988 +2024-11-22 11:19:42.201270: val_loss -0.7604 +2024-11-22 11:19:42.219349: Pseudo dice [0.8345] +2024-11-22 11:19:42.219522: Epoch time: 18.18 s +2024-11-22 11:19:43.192687: +2024-11-22 11:19:43.192970: Epoch 4519 +2024-11-22 11:19:43.193090: Current learning rate: 0.00473 +2024-11-22 11:20:02.057163: train_loss -0.7852 +2024-11-22 11:20:02.057488: val_loss -0.7567 +2024-11-22 11:20:02.057638: Pseudo dice [0.8168] +2024-11-22 11:20:02.057720: Epoch time: 18.87 s +2024-11-22 11:20:03.026956: +2024-11-22 11:20:03.027229: Epoch 4520 +2024-11-22 11:20:03.027343: Current learning rate: 0.00473 +2024-11-22 11:20:22.380258: train_loss -0.7682 +2024-11-22 11:20:22.380482: val_loss -0.745 +2024-11-22 11:20:22.380557: Pseudo dice [0.8117] +2024-11-22 11:20:22.380634: Epoch time: 19.35 s +2024-11-22 11:20:23.280864: +2024-11-22 11:20:23.281174: Epoch 4521 +2024-11-22 11:20:23.281284: Current learning rate: 0.00473 +2024-11-22 11:20:41.188706: train_loss -0.7624 +2024-11-22 11:20:41.194140: val_loss -0.7119 +2024-11-22 11:20:41.194247: Pseudo dice [0.8045] +2024-11-22 11:20:41.194335: Epoch time: 17.91 s +2024-11-22 11:20:42.236423: +2024-11-22 11:20:42.236673: Epoch 4522 +2024-11-22 11:20:42.236787: Current learning rate: 0.00473 +2024-11-22 11:21:01.417147: train_loss -0.7769 +2024-11-22 11:21:01.417431: val_loss -0.7358 +2024-11-22 11:21:01.417510: Pseudo dice [0.8255] +2024-11-22 11:21:01.417591: Epoch time: 19.18 s +2024-11-22 11:21:02.295302: +2024-11-22 11:21:02.295534: Epoch 4523 +2024-11-22 11:21:02.295648: Current learning rate: 0.00472 +2024-11-22 11:21:21.541780: train_loss -0.774 +2024-11-22 11:21:21.542008: val_loss -0.742 +2024-11-22 11:21:21.542083: Pseudo dice [0.8122] +2024-11-22 11:21:21.542160: Epoch time: 19.25 s +2024-11-22 11:21:22.418453: +2024-11-22 11:21:22.418666: Epoch 4524 +2024-11-22 11:21:22.418777: Current learning rate: 0.00472 +2024-11-22 11:21:40.477226: train_loss -0.778 +2024-11-22 11:21:40.477436: val_loss -0.753 +2024-11-22 11:21:40.477514: Pseudo dice [0.8207] +2024-11-22 11:21:40.477592: Epoch time: 18.06 s +2024-11-22 11:21:41.367801: +2024-11-22 11:21:41.368114: Epoch 4525 +2024-11-22 11:21:41.368237: Current learning rate: 0.00472 +2024-11-22 11:22:00.580799: train_loss -0.7697 +2024-11-22 11:22:00.581088: val_loss -0.7488 +2024-11-22 11:22:00.581168: Pseudo dice [0.8393] +2024-11-22 11:22:00.581255: Epoch time: 19.21 s +2024-11-22 11:22:01.725434: +2024-11-22 11:22:01.725670: Epoch 4526 +2024-11-22 11:22:01.725791: Current learning rate: 0.00472 +2024-11-22 11:22:20.387601: train_loss -0.7791 +2024-11-22 11:22:20.387816: val_loss -0.747 +2024-11-22 11:22:20.387890: Pseudo dice [0.8288] +2024-11-22 11:22:20.387968: Epoch time: 18.66 s +2024-11-22 11:22:21.266507: +2024-11-22 11:22:21.266733: Epoch 4527 +2024-11-22 11:22:21.266856: Current learning rate: 0.00472 +2024-11-22 11:22:40.997469: train_loss -0.787 +2024-11-22 11:22:40.997692: val_loss -0.7586 +2024-11-22 11:22:40.997771: Pseudo dice [0.8451] +2024-11-22 11:22:40.997847: Epoch time: 19.73 s +2024-11-22 11:22:41.867377: +2024-11-22 11:22:41.867936: Epoch 4528 +2024-11-22 11:22:41.868090: Current learning rate: 0.00472 +2024-11-22 11:22:59.845492: train_loss -0.7873 +2024-11-22 11:22:59.845701: val_loss -0.7608 +2024-11-22 11:22:59.845780: Pseudo dice [0.8313] +2024-11-22 11:22:59.845861: Epoch time: 17.98 s +2024-11-22 11:23:00.721645: +2024-11-22 11:23:00.721852: Epoch 4529 +2024-11-22 11:23:00.721969: Current learning rate: 0.00472 +2024-11-22 11:23:19.472666: train_loss -0.786 +2024-11-22 11:23:19.472916: val_loss -0.7418 +2024-11-22 11:23:19.472999: Pseudo dice [0.8327] +2024-11-22 11:23:19.473083: Epoch time: 18.75 s +2024-11-22 11:23:20.345626: +2024-11-22 11:23:20.345847: Epoch 4530 +2024-11-22 11:23:20.345962: Current learning rate: 0.00472 +2024-11-22 11:23:39.605016: train_loss -0.7774 +2024-11-22 11:23:39.605504: val_loss -0.7618 +2024-11-22 11:23:39.605599: Pseudo dice [0.8335] +2024-11-22 11:23:39.605748: Epoch time: 19.26 s +2024-11-22 11:23:40.531096: +2024-11-22 11:23:40.531406: Epoch 4531 +2024-11-22 11:23:40.531518: Current learning rate: 0.00471 +2024-11-22 11:23:59.695331: train_loss -0.7681 +2024-11-22 11:23:59.695573: val_loss -0.7254 +2024-11-22 11:23:59.695647: Pseudo dice [0.8141] +2024-11-22 11:23:59.695729: Epoch time: 19.16 s +2024-11-22 11:24:00.572757: +2024-11-22 11:24:00.572969: Epoch 4532 +2024-11-22 11:24:00.573085: Current learning rate: 0.00471 +2024-11-22 11:24:18.430483: train_loss -0.7849 +2024-11-22 11:24:18.430695: val_loss -0.7566 +2024-11-22 11:24:18.430769: Pseudo dice [0.829] +2024-11-22 11:24:18.430845: Epoch time: 17.86 s +2024-11-22 11:24:19.307195: +2024-11-22 11:24:19.307426: Epoch 4533 +2024-11-22 11:24:19.307537: Current learning rate: 0.00471 +2024-11-22 11:24:36.949322: train_loss -0.7949 +2024-11-22 11:24:36.949543: val_loss -0.7329 +2024-11-22 11:24:36.951808: Pseudo dice [0.8293] +2024-11-22 11:24:36.951944: Epoch time: 17.64 s +2024-11-22 11:24:38.112117: +2024-11-22 11:24:38.112357: Epoch 4534 +2024-11-22 11:24:38.112468: Current learning rate: 0.00471 +2024-11-22 11:24:55.781149: train_loss -0.7736 +2024-11-22 11:24:55.781372: val_loss -0.7432 +2024-11-22 11:24:55.781447: Pseudo dice [0.8194] +2024-11-22 11:24:55.781526: Epoch time: 17.67 s +2024-11-22 11:24:56.655369: +2024-11-22 11:24:56.655627: Epoch 4535 +2024-11-22 11:24:56.655745: Current learning rate: 0.00471 +2024-11-22 11:25:14.998720: train_loss -0.7863 +2024-11-22 11:25:14.999043: val_loss -0.7317 +2024-11-22 11:25:14.999123: Pseudo dice [0.8217] +2024-11-22 11:25:14.999232: Epoch time: 18.34 s +2024-11-22 11:25:15.880498: +2024-11-22 11:25:15.880759: Epoch 4536 +2024-11-22 11:25:15.880879: Current learning rate: 0.00471 +2024-11-22 11:25:35.525636: train_loss -0.7873 +2024-11-22 11:25:35.528015: val_loss -0.7548 +2024-11-22 11:25:35.528135: Pseudo dice [0.8184] +2024-11-22 11:25:35.528213: Epoch time: 19.65 s +2024-11-22 11:25:36.630417: +2024-11-22 11:25:36.630701: Epoch 4537 +2024-11-22 11:25:36.630824: Current learning rate: 0.00471 +2024-11-22 11:25:55.366954: train_loss -0.7893 +2024-11-22 11:25:55.367182: val_loss -0.7616 +2024-11-22 11:25:55.367256: Pseudo dice [0.8369] +2024-11-22 11:25:55.367331: Epoch time: 18.74 s +2024-11-22 11:25:56.244781: +2024-11-22 11:25:56.245014: Epoch 4538 +2024-11-22 11:25:56.245125: Current learning rate: 0.00471 +2024-11-22 11:26:14.166070: train_loss -0.7724 +2024-11-22 11:26:14.166648: val_loss -0.7121 +2024-11-22 11:26:14.166724: Pseudo dice [0.7853] +2024-11-22 11:26:14.166808: Epoch time: 17.92 s +2024-11-22 11:26:15.041350: +2024-11-22 11:26:15.041563: Epoch 4539 +2024-11-22 11:26:15.041677: Current learning rate: 0.0047 +2024-11-22 11:26:33.623487: train_loss -0.7838 +2024-11-22 11:26:33.623700: val_loss -0.7799 +2024-11-22 11:26:33.623775: Pseudo dice [0.8309] +2024-11-22 11:26:33.623892: Epoch time: 18.58 s +2024-11-22 11:26:34.502530: +2024-11-22 11:26:34.502750: Epoch 4540 +2024-11-22 11:26:34.502864: Current learning rate: 0.0047 +2024-11-22 11:26:53.567004: train_loss -0.7801 +2024-11-22 11:26:53.569413: val_loss -0.7405 +2024-11-22 11:26:53.569509: Pseudo dice [0.8139] +2024-11-22 11:26:53.569591: Epoch time: 19.07 s +2024-11-22 11:26:54.526447: +2024-11-22 11:26:54.526869: Epoch 4541 +2024-11-22 11:26:54.527005: Current learning rate: 0.0047 +2024-11-22 11:27:13.970465: train_loss -0.7894 +2024-11-22 11:27:13.970672: val_loss -0.7563 +2024-11-22 11:27:13.970745: Pseudo dice [0.8313] +2024-11-22 11:27:13.970828: Epoch time: 19.44 s +2024-11-22 11:27:14.845431: +2024-11-22 11:27:14.845643: Epoch 4542 +2024-11-22 11:27:14.845757: Current learning rate: 0.0047 +2024-11-22 11:27:33.519872: train_loss -0.7885 +2024-11-22 11:27:33.520467: val_loss -0.7584 +2024-11-22 11:27:33.520568: Pseudo dice [0.8333] +2024-11-22 11:27:33.520648: Epoch time: 18.68 s +2024-11-22 11:27:34.394941: +2024-11-22 11:27:34.395152: Epoch 4543 +2024-11-22 11:27:34.395265: Current learning rate: 0.0047 +2024-11-22 11:27:52.668260: train_loss -0.7956 +2024-11-22 11:27:52.668741: val_loss -0.7556 +2024-11-22 11:27:52.668836: Pseudo dice [0.8317] +2024-11-22 11:27:52.668914: Epoch time: 18.27 s +2024-11-22 11:27:53.542594: +2024-11-22 11:27:53.568838: Epoch 4544 +2024-11-22 11:27:53.568976: Current learning rate: 0.0047 +2024-11-22 11:28:11.451562: train_loss -0.8018 +2024-11-22 11:28:11.451783: val_loss -0.7502 +2024-11-22 11:28:11.451859: Pseudo dice [0.8273] +2024-11-22 11:28:11.451940: Epoch time: 17.91 s +2024-11-22 11:28:12.328019: +2024-11-22 11:28:12.328241: Epoch 4545 +2024-11-22 11:28:12.328356: Current learning rate: 0.0047 +2024-11-22 11:28:30.973665: train_loss -0.7923 +2024-11-22 11:28:30.974064: val_loss -0.7423 +2024-11-22 11:28:30.974146: Pseudo dice [0.8436] +2024-11-22 11:28:30.974226: Epoch time: 18.65 s +2024-11-22 11:28:31.848729: +2024-11-22 11:28:31.848929: Epoch 4546 +2024-11-22 11:28:31.849054: Current learning rate: 0.0047 +2024-11-22 11:28:51.389744: train_loss -0.8024 +2024-11-22 11:28:51.389967: val_loss -0.7618 +2024-11-22 11:28:51.390050: Pseudo dice [0.8347] +2024-11-22 11:28:51.390131: Epoch time: 19.54 s +2024-11-22 11:28:52.262386: +2024-11-22 11:28:52.262630: Epoch 4547 +2024-11-22 11:28:52.262741: Current learning rate: 0.00469 +2024-11-22 11:29:10.310755: train_loss -0.7969 +2024-11-22 11:29:10.310975: val_loss -0.7245 +2024-11-22 11:29:10.311056: Pseudo dice [0.833] +2024-11-22 11:29:10.311134: Epoch time: 18.05 s +2024-11-22 11:29:11.189381: +2024-11-22 11:29:11.189665: Epoch 4548 +2024-11-22 11:29:11.189782: Current learning rate: 0.00469 +2024-11-22 11:29:29.781106: train_loss -0.7911 +2024-11-22 11:29:29.781431: val_loss -0.7667 +2024-11-22 11:29:29.781512: Pseudo dice [0.8451] +2024-11-22 11:29:29.781603: Epoch time: 18.59 s +2024-11-22 11:29:30.660951: +2024-11-22 11:29:30.661175: Epoch 4549 +2024-11-22 11:29:30.661288: Current learning rate: 0.00469 +2024-11-22 11:29:49.403349: train_loss -0.7921 +2024-11-22 11:29:49.403567: val_loss -0.7097 +2024-11-22 11:29:49.403642: Pseudo dice [0.8028] +2024-11-22 11:29:49.403719: Epoch time: 18.74 s +2024-11-22 11:29:50.563630: +2024-11-22 11:29:50.563832: Epoch 4550 +2024-11-22 11:29:50.563944: Current learning rate: 0.00469 +2024-11-22 11:30:10.479601: train_loss -0.7728 +2024-11-22 11:30:10.479831: val_loss -0.7456 +2024-11-22 11:30:10.479909: Pseudo dice [0.8388] +2024-11-22 11:30:10.479999: Epoch time: 19.92 s +2024-11-22 11:30:11.356002: +2024-11-22 11:30:11.356524: Epoch 4551 +2024-11-22 11:30:11.356663: Current learning rate: 0.00469 +2024-11-22 11:30:30.303483: train_loss -0.7895 +2024-11-22 11:30:30.303707: val_loss -0.7157 +2024-11-22 11:30:30.303779: Pseudo dice [0.7987] +2024-11-22 11:30:30.303876: Epoch time: 18.95 s +2024-11-22 11:30:31.186343: +2024-11-22 11:30:31.186565: Epoch 4552 +2024-11-22 11:30:31.186677: Current learning rate: 0.00469 +2024-11-22 11:30:50.105337: train_loss -0.7866 +2024-11-22 11:30:50.105626: val_loss -0.7575 +2024-11-22 11:30:50.107779: Pseudo dice [0.8162] +2024-11-22 11:30:50.107903: Epoch time: 18.92 s +2024-11-22 11:30:51.011289: +2024-11-22 11:30:51.011486: Epoch 4553 +2024-11-22 11:30:51.011597: Current learning rate: 0.00469 +2024-11-22 11:31:09.194485: train_loss -0.7814 +2024-11-22 11:31:09.194689: val_loss -0.7301 +2024-11-22 11:31:09.194763: Pseudo dice [0.8168] +2024-11-22 11:31:09.194836: Epoch time: 18.18 s +2024-11-22 11:31:10.054123: +2024-11-22 11:31:10.054332: Epoch 4554 +2024-11-22 11:31:10.054442: Current learning rate: 0.00469 +2024-11-22 11:31:29.301062: train_loss -0.7826 +2024-11-22 11:31:29.301485: val_loss -0.747 +2024-11-22 11:31:29.301581: Pseudo dice [0.8252] +2024-11-22 11:31:29.301661: Epoch time: 19.25 s +2024-11-22 11:31:30.167711: +2024-11-22 11:31:30.167913: Epoch 4555 +2024-11-22 11:31:30.168030: Current learning rate: 0.00468 +2024-11-22 11:31:47.748964: train_loss -0.7923 +2024-11-22 11:31:47.749223: val_loss -0.7365 +2024-11-22 11:31:47.749299: Pseudo dice [0.8138] +2024-11-22 11:31:47.749381: Epoch time: 17.58 s +2024-11-22 11:31:48.625882: +2024-11-22 11:31:48.626132: Epoch 4556 +2024-11-22 11:31:48.626241: Current learning rate: 0.00468 +2024-11-22 11:32:07.578258: train_loss -0.7735 +2024-11-22 11:32:07.578488: val_loss -0.7551 +2024-11-22 11:32:07.578561: Pseudo dice [0.8347] +2024-11-22 11:32:07.578638: Epoch time: 18.95 s +2024-11-22 11:32:08.458873: +2024-11-22 11:32:08.459118: Epoch 4557 +2024-11-22 11:32:08.459229: Current learning rate: 0.00468 +2024-11-22 11:32:28.351363: train_loss -0.7849 +2024-11-22 11:32:28.351576: val_loss -0.7429 +2024-11-22 11:32:28.351650: Pseudo dice [0.8178] +2024-11-22 11:32:28.351721: Epoch time: 19.89 s +2024-11-22 11:32:29.228030: +2024-11-22 11:32:29.228296: Epoch 4558 +2024-11-22 11:32:29.228443: Current learning rate: 0.00468 +2024-11-22 11:32:48.377188: train_loss -0.7949 +2024-11-22 11:32:48.377435: val_loss -0.7399 +2024-11-22 11:32:48.377511: Pseudo dice [0.8281] +2024-11-22 11:32:48.377594: Epoch time: 19.15 s +2024-11-22 11:32:49.390826: +2024-11-22 11:32:49.391053: Epoch 4559 +2024-11-22 11:32:49.391171: Current learning rate: 0.00468 +2024-11-22 11:33:07.228220: train_loss -0.7986 +2024-11-22 11:33:07.228432: val_loss -0.7518 +2024-11-22 11:33:07.228544: Pseudo dice [0.8323] +2024-11-22 11:33:07.228623: Epoch time: 17.84 s +2024-11-22 11:33:08.103050: +2024-11-22 11:33:08.103265: Epoch 4560 +2024-11-22 11:33:08.103376: Current learning rate: 0.00468 +2024-11-22 11:33:25.978394: train_loss -0.7944 +2024-11-22 11:33:25.978612: val_loss -0.7716 +2024-11-22 11:33:25.978690: Pseudo dice [0.8411] +2024-11-22 11:33:25.978770: Epoch time: 17.88 s +2024-11-22 11:33:26.854658: +2024-11-22 11:33:26.854904: Epoch 4561 +2024-11-22 11:33:26.855025: Current learning rate: 0.00468 +2024-11-22 11:33:45.444786: train_loss -0.7918 +2024-11-22 11:33:45.447196: val_loss -0.7441 +2024-11-22 11:33:45.447285: Pseudo dice [0.8169] +2024-11-22 11:33:45.447366: Epoch time: 18.59 s +2024-11-22 11:33:46.548389: +2024-11-22 11:33:46.548593: Epoch 4562 +2024-11-22 11:33:46.548711: Current learning rate: 0.00468 +2024-11-22 11:34:06.340910: train_loss -0.7895 +2024-11-22 11:34:06.341155: val_loss -0.7606 +2024-11-22 11:34:06.346377: Pseudo dice [0.8362] +2024-11-22 11:34:06.346542: Epoch time: 19.79 s +2024-11-22 11:34:07.239219: +2024-11-22 11:34:07.239641: Epoch 4563 +2024-11-22 11:34:07.239770: Current learning rate: 0.00467 +2024-11-22 11:34:27.254100: train_loss -0.7924 +2024-11-22 11:34:27.254313: val_loss -0.7544 +2024-11-22 11:34:27.254387: Pseudo dice [0.8359] +2024-11-22 11:34:27.254463: Epoch time: 20.02 s +2024-11-22 11:34:28.130481: +2024-11-22 11:34:28.130749: Epoch 4564 +2024-11-22 11:34:28.130866: Current learning rate: 0.00467 +2024-11-22 11:34:46.587303: train_loss -0.7873 +2024-11-22 11:34:46.587512: val_loss -0.7719 +2024-11-22 11:34:46.587586: Pseudo dice [0.8368] +2024-11-22 11:34:46.587666: Epoch time: 18.46 s +2024-11-22 11:34:47.467653: +2024-11-22 11:34:47.467928: Epoch 4565 +2024-11-22 11:34:47.468051: Current learning rate: 0.00467 +2024-11-22 11:35:05.662025: train_loss -0.7917 +2024-11-22 11:35:05.662278: val_loss -0.7528 +2024-11-22 11:35:05.662357: Pseudo dice [0.8252] +2024-11-22 11:35:05.662445: Epoch time: 18.2 s +2024-11-22 11:35:06.539119: +2024-11-22 11:35:06.539339: Epoch 4566 +2024-11-22 11:35:06.539453: Current learning rate: 0.00467 +2024-11-22 11:35:25.585015: train_loss -0.7885 +2024-11-22 11:35:25.585490: val_loss -0.7654 +2024-11-22 11:35:25.585597: Pseudo dice [0.8358] +2024-11-22 11:35:25.585674: Epoch time: 19.05 s +2024-11-22 11:35:26.505525: +2024-11-22 11:35:26.505743: Epoch 4567 +2024-11-22 11:35:26.505857: Current learning rate: 0.00467 +2024-11-22 11:35:45.763434: train_loss -0.7917 +2024-11-22 11:35:45.765829: val_loss -0.7452 +2024-11-22 11:35:45.765918: Pseudo dice [0.834] +2024-11-22 11:35:45.766003: Epoch time: 19.26 s +2024-11-22 11:35:46.738441: +2024-11-22 11:35:46.738659: Epoch 4568 +2024-11-22 11:35:46.738771: Current learning rate: 0.00467 +2024-11-22 11:36:05.280126: train_loss -0.7845 +2024-11-22 11:36:05.280382: val_loss -0.715 +2024-11-22 11:36:05.280459: Pseudo dice [0.8171] +2024-11-22 11:36:05.280544: Epoch time: 18.54 s +2024-11-22 11:36:06.232999: +2024-11-22 11:36:06.233213: Epoch 4569 +2024-11-22 11:36:06.233325: Current learning rate: 0.00467 +2024-11-22 11:36:24.248674: train_loss -0.7824 +2024-11-22 11:36:24.264467: val_loss -0.7424 +2024-11-22 11:36:24.264564: Pseudo dice [0.8071] +2024-11-22 11:36:24.264642: Epoch time: 18.02 s +2024-11-22 11:36:25.138520: +2024-11-22 11:36:25.138783: Epoch 4570 +2024-11-22 11:36:25.138892: Current learning rate: 0.00467 +2024-11-22 11:36:43.377389: train_loss -0.8 +2024-11-22 11:36:43.377602: val_loss -0.7418 +2024-11-22 11:36:43.377676: Pseudo dice [0.8075] +2024-11-22 11:36:43.377756: Epoch time: 18.24 s +2024-11-22 11:36:44.248852: +2024-11-22 11:36:44.249064: Epoch 4571 +2024-11-22 11:36:44.249177: Current learning rate: 0.00467 +2024-11-22 11:37:02.903780: train_loss -0.8007 +2024-11-22 11:37:02.904161: val_loss -0.7387 +2024-11-22 11:37:02.904248: Pseudo dice [0.8201] +2024-11-22 11:37:02.904326: Epoch time: 18.66 s +2024-11-22 11:37:03.795491: +2024-11-22 11:37:03.795706: Epoch 4572 +2024-11-22 11:37:03.795819: Current learning rate: 0.00466 +2024-11-22 11:37:23.222234: train_loss -0.7957 +2024-11-22 11:37:23.222506: val_loss -0.777 +2024-11-22 11:37:23.222581: Pseudo dice [0.8429] +2024-11-22 11:37:23.222665: Epoch time: 19.43 s +2024-11-22 11:37:24.118972: +2024-11-22 11:37:24.119204: Epoch 4573 +2024-11-22 11:37:24.119317: Current learning rate: 0.00466 +2024-11-22 11:37:44.163270: train_loss -0.7941 +2024-11-22 11:37:44.163482: val_loss -0.7483 +2024-11-22 11:37:44.163557: Pseudo dice [0.8334] +2024-11-22 11:37:44.163659: Epoch time: 20.05 s +2024-11-22 11:37:45.051126: +2024-11-22 11:37:45.051373: Epoch 4574 +2024-11-22 11:37:45.051492: Current learning rate: 0.00466 +2024-11-22 11:38:03.562712: train_loss -0.8023 +2024-11-22 11:38:03.562922: val_loss -0.7051 +2024-11-22 11:38:03.563006: Pseudo dice [0.8072] +2024-11-22 11:38:03.563082: Epoch time: 18.51 s +2024-11-22 11:38:04.438804: +2024-11-22 11:38:04.439022: Epoch 4575 +2024-11-22 11:38:04.439138: Current learning rate: 0.00466 +2024-11-22 11:38:23.098478: train_loss -0.7999 +2024-11-22 11:38:23.098682: val_loss -0.7573 +2024-11-22 11:38:23.098753: Pseudo dice [0.8172] +2024-11-22 11:38:23.098829: Epoch time: 18.66 s +2024-11-22 11:38:23.986334: +2024-11-22 11:38:23.986741: Epoch 4576 +2024-11-22 11:38:23.986870: Current learning rate: 0.00466 +2024-11-22 11:38:42.648109: train_loss -0.7993 +2024-11-22 11:38:42.648350: val_loss -0.7262 +2024-11-22 11:38:42.648425: Pseudo dice [0.811] +2024-11-22 11:38:42.648506: Epoch time: 18.66 s +2024-11-22 11:38:43.523351: +2024-11-22 11:38:43.523564: Epoch 4577 +2024-11-22 11:38:43.523676: Current learning rate: 0.00466 +2024-11-22 11:39:01.778984: train_loss -0.7948 +2024-11-22 11:39:01.779198: val_loss -0.7394 +2024-11-22 11:39:01.779274: Pseudo dice [0.8085] +2024-11-22 11:39:01.779349: Epoch time: 18.26 s +2024-11-22 11:39:02.662542: +2024-11-22 11:39:02.662735: Epoch 4578 +2024-11-22 11:39:02.662847: Current learning rate: 0.00466 +2024-11-22 11:39:21.287351: train_loss -0.7978 +2024-11-22 11:39:21.287818: val_loss -0.7522 +2024-11-22 11:39:21.287916: Pseudo dice [0.834] +2024-11-22 11:39:21.288002: Epoch time: 18.63 s +2024-11-22 11:39:22.168190: +2024-11-22 11:39:22.168424: Epoch 4579 +2024-11-22 11:39:22.168537: Current learning rate: 0.00466 +2024-11-22 11:39:40.813872: train_loss -0.8074 +2024-11-22 11:39:40.814146: val_loss -0.752 +2024-11-22 11:39:40.814220: Pseudo dice [0.8456] +2024-11-22 11:39:40.814306: Epoch time: 18.65 s +2024-11-22 11:39:41.704797: +2024-11-22 11:39:41.705039: Epoch 4580 +2024-11-22 11:39:41.705153: Current learning rate: 0.00465 +2024-11-22 11:39:59.046526: train_loss -0.8024 +2024-11-22 11:39:59.046737: val_loss -0.7542 +2024-11-22 11:39:59.046814: Pseudo dice [0.8349] +2024-11-22 11:39:59.046890: Epoch time: 17.34 s +2024-11-22 11:39:59.926388: +2024-11-22 11:39:59.926622: Epoch 4581 +2024-11-22 11:39:59.926741: Current learning rate: 0.00465 +2024-11-22 11:40:18.414165: train_loss -0.7993 +2024-11-22 11:40:18.414379: val_loss -0.7547 +2024-11-22 11:40:18.414453: Pseudo dice [0.8392] +2024-11-22 11:40:18.419721: Epoch time: 18.49 s +2024-11-22 11:40:19.330123: +2024-11-22 11:40:19.330395: Epoch 4582 +2024-11-22 11:40:19.331137: Current learning rate: 0.00465 +2024-11-22 11:40:38.242897: train_loss -0.7953 +2024-11-22 11:40:38.243150: val_loss -0.7516 +2024-11-22 11:40:38.243229: Pseudo dice [0.821] +2024-11-22 11:40:38.243311: Epoch time: 18.91 s +2024-11-22 11:40:39.187677: +2024-11-22 11:40:39.187911: Epoch 4583 +2024-11-22 11:40:39.188036: Current learning rate: 0.00465 +2024-11-22 11:40:57.792767: train_loss -0.8008 +2024-11-22 11:40:57.793000: val_loss -0.7556 +2024-11-22 11:40:57.793080: Pseudo dice [0.8241] +2024-11-22 11:40:57.793162: Epoch time: 18.61 s +2024-11-22 11:40:58.756568: +2024-11-22 11:40:58.756780: Epoch 4584 +2024-11-22 11:40:58.756891: Current learning rate: 0.00465 +2024-11-22 11:41:17.770885: train_loss -0.795 +2024-11-22 11:41:17.771109: val_loss -0.768 +2024-11-22 11:41:17.771185: Pseudo dice [0.8377] +2024-11-22 11:41:17.771270: Epoch time: 19.02 s +2024-11-22 11:41:18.648525: +2024-11-22 11:41:18.648715: Epoch 4585 +2024-11-22 11:41:18.648829: Current learning rate: 0.00465 +2024-11-22 11:41:36.810640: train_loss -0.7979 +2024-11-22 11:41:36.810863: val_loss -0.7481 +2024-11-22 11:41:36.810939: Pseudo dice [0.8309] +2024-11-22 11:41:36.813233: Epoch time: 18.16 s +2024-11-22 11:41:37.714562: +2024-11-22 11:41:37.714789: Epoch 4586 +2024-11-22 11:41:37.714907: Current learning rate: 0.00465 +2024-11-22 11:41:56.088554: train_loss -0.8024 +2024-11-22 11:41:56.088799: val_loss -0.7602 +2024-11-22 11:41:56.088883: Pseudo dice [0.8316] +2024-11-22 11:41:56.088967: Epoch time: 18.37 s +2024-11-22 11:41:56.990219: +2024-11-22 11:41:56.990417: Epoch 4587 +2024-11-22 11:41:56.990530: Current learning rate: 0.00465 +2024-11-22 11:42:14.839491: train_loss -0.8042 +2024-11-22 11:42:14.839707: val_loss -0.7536 +2024-11-22 11:42:14.839787: Pseudo dice [0.8416] +2024-11-22 11:42:14.839865: Epoch time: 17.85 s +2024-11-22 11:42:15.707717: +2024-11-22 11:42:15.708164: Epoch 4588 +2024-11-22 11:42:15.708299: Current learning rate: 0.00464 +2024-11-22 11:42:34.785022: train_loss -0.7973 +2024-11-22 11:42:34.785234: val_loss -0.7529 +2024-11-22 11:42:34.785308: Pseudo dice [0.8461] +2024-11-22 11:42:34.785387: Epoch time: 19.08 s +2024-11-22 11:42:35.665316: +2024-11-22 11:42:35.665513: Epoch 4589 +2024-11-22 11:42:35.665625: Current learning rate: 0.00464 +2024-11-22 11:42:53.823246: train_loss -0.7941 +2024-11-22 11:42:53.823495: val_loss -0.7547 +2024-11-22 11:42:53.823569: Pseudo dice [0.8335] +2024-11-22 11:42:53.823652: Epoch time: 18.16 s +2024-11-22 11:42:54.800621: +2024-11-22 11:42:54.800893: Epoch 4590 +2024-11-22 11:42:54.801017: Current learning rate: 0.00464 +2024-11-22 11:43:14.427510: train_loss -0.8023 +2024-11-22 11:43:14.427974: val_loss -0.7284 +2024-11-22 11:43:14.428079: Pseudo dice [0.8305] +2024-11-22 11:43:14.428156: Epoch time: 19.63 s +2024-11-22 11:43:15.300924: +2024-11-22 11:43:15.301144: Epoch 4591 +2024-11-22 11:43:15.301256: Current learning rate: 0.00464 +2024-11-22 11:43:34.242626: train_loss -0.8052 +2024-11-22 11:43:34.242909: val_loss -0.7482 +2024-11-22 11:43:34.242998: Pseudo dice [0.8326] +2024-11-22 11:43:34.243081: Epoch time: 18.94 s +2024-11-22 11:43:35.123706: +2024-11-22 11:43:35.123924: Epoch 4592 +2024-11-22 11:43:35.124048: Current learning rate: 0.00464 +2024-11-22 11:43:54.715214: train_loss -0.8057 +2024-11-22 11:43:54.715463: val_loss -0.7583 +2024-11-22 11:43:54.715536: Pseudo dice [0.8169] +2024-11-22 11:43:54.715620: Epoch time: 19.59 s +2024-11-22 11:43:55.754676: +2024-11-22 11:43:55.754894: Epoch 4593 +2024-11-22 11:43:55.755016: Current learning rate: 0.00464 +2024-11-22 11:44:13.844160: train_loss -0.7958 +2024-11-22 11:44:13.844415: val_loss -0.7455 +2024-11-22 11:44:13.844492: Pseudo dice [0.8501] +2024-11-22 11:44:13.844571: Epoch time: 18.09 s +2024-11-22 11:44:14.789618: +2024-11-22 11:44:14.789852: Epoch 4594 +2024-11-22 11:44:14.789966: Current learning rate: 0.00464 +2024-11-22 11:44:34.556528: train_loss -0.7938 +2024-11-22 11:44:34.556750: val_loss -0.7519 +2024-11-22 11:44:34.556822: Pseudo dice [0.8362] +2024-11-22 11:44:34.557625: Epoch time: 19.77 s +2024-11-22 11:44:35.470023: +2024-11-22 11:44:35.470275: Epoch 4595 +2024-11-22 11:44:35.470387: Current learning rate: 0.00464 +2024-11-22 11:44:54.944684: train_loss -0.7931 +2024-11-22 11:44:54.944946: val_loss -0.7595 +2024-11-22 11:44:54.945035: Pseudo dice [0.8392] +2024-11-22 11:44:54.945110: Epoch time: 19.48 s +2024-11-22 11:44:55.821762: +2024-11-22 11:44:55.822047: Epoch 4596 +2024-11-22 11:44:55.822170: Current learning rate: 0.00463 +2024-11-22 11:45:15.514061: train_loss -0.7969 +2024-11-22 11:45:15.514346: val_loss -0.7241 +2024-11-22 11:45:15.514426: Pseudo dice [0.8379] +2024-11-22 11:45:15.514517: Epoch time: 19.69 s +2024-11-22 11:45:16.452645: +2024-11-22 11:45:16.452861: Epoch 4597 +2024-11-22 11:45:16.452973: Current learning rate: 0.00463 +2024-11-22 11:45:35.170044: train_loss -0.7872 +2024-11-22 11:45:35.170265: val_loss -0.7703 +2024-11-22 11:45:35.170344: Pseudo dice [0.8399] +2024-11-22 11:45:35.172564: Epoch time: 18.72 s +2024-11-22 11:45:36.141032: +2024-11-22 11:45:36.141277: Epoch 4598 +2024-11-22 11:45:36.141390: Current learning rate: 0.00463 +2024-11-22 11:45:54.867897: train_loss -0.7883 +2024-11-22 11:45:54.868123: val_loss -0.7569 +2024-11-22 11:45:54.868201: Pseudo dice [0.8324] +2024-11-22 11:45:54.868277: Epoch time: 18.73 s +2024-11-22 11:45:55.749535: +2024-11-22 11:45:55.749774: Epoch 4599 +2024-11-22 11:45:55.749889: Current learning rate: 0.00463 +2024-11-22 11:46:14.414434: train_loss -0.7893 +2024-11-22 11:46:14.414693: val_loss -0.7471 +2024-11-22 11:46:14.414771: Pseudo dice [0.8189] +2024-11-22 11:46:14.414850: Epoch time: 18.67 s +2024-11-22 11:46:15.548668: +2024-11-22 11:46:15.548894: Epoch 4600 +2024-11-22 11:46:15.549016: Current learning rate: 0.00463 +2024-11-22 11:46:33.869978: train_loss -0.7804 +2024-11-22 11:46:33.870223: val_loss -0.7227 +2024-11-22 11:46:33.870299: Pseudo dice [0.813] +2024-11-22 11:46:33.870386: Epoch time: 18.32 s +2024-11-22 11:46:34.745965: +2024-11-22 11:46:34.746413: Epoch 4601 +2024-11-22 11:46:34.746554: Current learning rate: 0.00463 +2024-11-22 11:46:53.593514: train_loss -0.7881 +2024-11-22 11:46:53.593796: val_loss -0.7319 +2024-11-22 11:46:53.593972: Pseudo dice [0.8437] +2024-11-22 11:46:53.594061: Epoch time: 18.85 s +2024-11-22 11:46:54.465861: +2024-11-22 11:46:54.466069: Epoch 4602 +2024-11-22 11:46:54.466179: Current learning rate: 0.00463 +2024-11-22 11:47:12.634211: train_loss -0.7938 +2024-11-22 11:47:12.634746: val_loss -0.7622 +2024-11-22 11:47:12.634846: Pseudo dice [0.8412] +2024-11-22 11:47:12.634922: Epoch time: 18.17 s +2024-11-22 11:47:13.511126: +2024-11-22 11:47:13.511345: Epoch 4603 +2024-11-22 11:47:13.511456: Current learning rate: 0.00463 +2024-11-22 11:47:32.517660: train_loss -0.7912 +2024-11-22 11:47:32.517906: val_loss -0.7327 +2024-11-22 11:47:32.517982: Pseudo dice [0.836] +2024-11-22 11:47:32.518074: Epoch time: 19.01 s +2024-11-22 11:47:33.403638: +2024-11-22 11:47:33.403865: Epoch 4604 +2024-11-22 11:47:33.403979: Current learning rate: 0.00462 +2024-11-22 11:47:52.234745: train_loss -0.7943 +2024-11-22 11:47:52.234956: val_loss -0.7509 +2024-11-22 11:47:52.240281: Pseudo dice [0.8102] +2024-11-22 11:47:52.240377: Epoch time: 18.83 s +2024-11-22 11:47:53.153227: +2024-11-22 11:47:53.153436: Epoch 4605 +2024-11-22 11:47:53.153547: Current learning rate: 0.00462 +2024-11-22 11:48:12.485269: train_loss -0.7995 +2024-11-22 11:48:12.485488: val_loss -0.7217 +2024-11-22 11:48:12.485565: Pseudo dice [0.8352] +2024-11-22 11:48:12.485693: Epoch time: 19.33 s +2024-11-22 11:48:13.366804: +2024-11-22 11:48:13.367085: Epoch 4606 +2024-11-22 11:48:13.367204: Current learning rate: 0.00462 +2024-11-22 11:48:31.580292: train_loss -0.797 +2024-11-22 11:48:31.580522: val_loss -0.7605 +2024-11-22 11:48:31.580600: Pseudo dice [0.8272] +2024-11-22 11:48:31.580684: Epoch time: 18.21 s +2024-11-22 11:48:32.456689: +2024-11-22 11:48:32.456979: Epoch 4607 +2024-11-22 11:48:32.457120: Current learning rate: 0.00462 +2024-11-22 11:48:51.551075: train_loss -0.7934 +2024-11-22 11:48:51.551551: val_loss -0.755 +2024-11-22 11:48:51.551628: Pseudo dice [0.8138] +2024-11-22 11:48:51.551705: Epoch time: 19.1 s +2024-11-22 11:48:52.425548: +2024-11-22 11:48:52.425768: Epoch 4608 +2024-11-22 11:48:52.425883: Current learning rate: 0.00462 +2024-11-22 11:49:10.749869: train_loss -0.7969 +2024-11-22 11:49:10.750096: val_loss -0.7727 +2024-11-22 11:49:10.750171: Pseudo dice [0.8419] +2024-11-22 11:49:10.750307: Epoch time: 18.33 s +2024-11-22 11:49:11.626202: +2024-11-22 11:49:11.626405: Epoch 4609 +2024-11-22 11:49:11.626513: Current learning rate: 0.00462 +2024-11-22 11:49:29.359168: train_loss -0.7925 +2024-11-22 11:49:29.359392: val_loss -0.7642 +2024-11-22 11:49:29.359530: Pseudo dice [0.8354] +2024-11-22 11:49:29.359611: Epoch time: 17.73 s +2024-11-22 11:49:30.291747: +2024-11-22 11:49:30.291972: Epoch 4610 +2024-11-22 11:49:30.292093: Current learning rate: 0.00462 +2024-11-22 11:49:48.086571: train_loss -0.8038 +2024-11-22 11:49:48.091938: val_loss -0.7511 +2024-11-22 11:49:48.092098: Pseudo dice [0.8289] +2024-11-22 11:49:48.092191: Epoch time: 17.8 s +2024-11-22 11:49:49.113565: +2024-11-22 11:49:49.113832: Epoch 4611 +2024-11-22 11:49:49.113944: Current learning rate: 0.00462 +2024-11-22 11:50:09.008155: train_loss -0.8023 +2024-11-22 11:50:09.008383: val_loss -0.7566 +2024-11-22 11:50:09.008463: Pseudo dice [0.8438] +2024-11-22 11:50:09.008540: Epoch time: 19.9 s +2024-11-22 11:50:10.015337: +2024-11-22 11:50:10.015529: Epoch 4612 +2024-11-22 11:50:10.015653: Current learning rate: 0.00461 +2024-11-22 11:50:28.563177: train_loss -0.7959 +2024-11-22 11:50:28.563395: val_loss -0.7441 +2024-11-22 11:50:28.563470: Pseudo dice [0.8206] +2024-11-22 11:50:28.563544: Epoch time: 18.55 s +2024-11-22 11:50:29.450974: +2024-11-22 11:50:29.451179: Epoch 4613 +2024-11-22 11:50:29.451288: Current learning rate: 0.00461 +2024-11-22 11:50:48.683574: train_loss -0.7968 +2024-11-22 11:50:48.683844: val_loss -0.7681 +2024-11-22 11:50:48.683928: Pseudo dice [0.84] +2024-11-22 11:50:48.684029: Epoch time: 19.23 s +2024-11-22 11:50:49.560603: +2024-11-22 11:50:49.560802: Epoch 4614 +2024-11-22 11:50:49.560911: Current learning rate: 0.00461 +2024-11-22 11:51:08.698633: train_loss -0.7911 +2024-11-22 11:51:08.699174: val_loss -0.7422 +2024-11-22 11:51:08.699275: Pseudo dice [0.828] +2024-11-22 11:51:08.699351: Epoch time: 19.14 s +2024-11-22 11:51:09.567502: +2024-11-22 11:51:09.567723: Epoch 4615 +2024-11-22 11:51:09.567832: Current learning rate: 0.00461 +2024-11-22 11:51:27.519780: train_loss -0.7854 +2024-11-22 11:51:27.520006: val_loss -0.7165 +2024-11-22 11:51:27.520080: Pseudo dice [0.8273] +2024-11-22 11:51:27.520155: Epoch time: 17.95 s +2024-11-22 11:51:28.573586: +2024-11-22 11:51:28.573810: Epoch 4616 +2024-11-22 11:51:28.573923: Current learning rate: 0.00461 +2024-11-22 11:51:47.538356: train_loss -0.7906 +2024-11-22 11:51:47.538677: val_loss -0.7453 +2024-11-22 11:51:47.538760: Pseudo dice [0.8222] +2024-11-22 11:51:47.538849: Epoch time: 18.97 s +2024-11-22 11:51:48.404498: +2024-11-22 11:51:48.404710: Epoch 4617 +2024-11-22 11:51:48.404824: Current learning rate: 0.00461 +2024-11-22 11:52:06.801841: train_loss -0.7936 +2024-11-22 11:52:06.802078: val_loss -0.7406 +2024-11-22 11:52:06.802155: Pseudo dice [0.8188] +2024-11-22 11:52:06.802233: Epoch time: 18.4 s +2024-11-22 11:52:07.676411: +2024-11-22 11:52:07.676647: Epoch 4618 +2024-11-22 11:52:07.676762: Current learning rate: 0.00461 +2024-11-22 11:52:24.836822: train_loss -0.7905 +2024-11-22 11:52:24.837047: val_loss -0.7262 +2024-11-22 11:52:24.837120: Pseudo dice [0.8306] +2024-11-22 11:52:24.837196: Epoch time: 17.16 s +2024-11-22 11:52:25.717081: +2024-11-22 11:52:25.717288: Epoch 4619 +2024-11-22 11:52:25.717402: Current learning rate: 0.00461 +2024-11-22 11:52:43.974427: train_loss -0.7912 +2024-11-22 11:52:43.974652: val_loss -0.7317 +2024-11-22 11:52:43.974730: Pseudo dice [0.8278] +2024-11-22 11:52:43.974812: Epoch time: 18.26 s +2024-11-22 11:52:44.850959: +2024-11-22 11:52:44.851162: Epoch 4620 +2024-11-22 11:52:44.851470: Current learning rate: 0.00461 +2024-11-22 11:53:04.006397: train_loss -0.7905 +2024-11-22 11:53:04.006645: val_loss -0.7667 +2024-11-22 11:53:04.006725: Pseudo dice [0.8325] +2024-11-22 11:53:04.006812: Epoch time: 19.16 s +2024-11-22 11:53:04.896382: +2024-11-22 11:53:04.896581: Epoch 4621 +2024-11-22 11:53:04.896693: Current learning rate: 0.0046 +2024-11-22 11:53:23.547883: train_loss -0.7935 +2024-11-22 11:53:23.548109: val_loss -0.7527 +2024-11-22 11:53:23.548184: Pseudo dice [0.8443] +2024-11-22 11:53:23.548259: Epoch time: 18.65 s +2024-11-22 11:53:24.470218: +2024-11-22 11:53:24.470440: Epoch 4622 +2024-11-22 11:53:24.470549: Current learning rate: 0.0046 +2024-11-22 11:53:43.538282: train_loss -0.8014 +2024-11-22 11:53:43.538501: val_loss -0.74 +2024-11-22 11:53:43.538577: Pseudo dice [0.8407] +2024-11-22 11:53:43.538653: Epoch time: 19.07 s +2024-11-22 11:53:44.432537: +2024-11-22 11:53:44.432739: Epoch 4623 +2024-11-22 11:53:44.432870: Current learning rate: 0.0046 +2024-11-22 11:54:02.430595: train_loss -0.7988 +2024-11-22 11:54:02.430822: val_loss -0.7478 +2024-11-22 11:54:02.430902: Pseudo dice [0.8326] +2024-11-22 11:54:02.430985: Epoch time: 18.0 s +2024-11-22 11:54:03.304816: +2024-11-22 11:54:03.305027: Epoch 4624 +2024-11-22 11:54:03.305132: Current learning rate: 0.0046 +2024-11-22 11:54:22.383338: train_loss -0.7956 +2024-11-22 11:54:22.383562: val_loss -0.744 +2024-11-22 11:54:22.383636: Pseudo dice [0.8266] +2024-11-22 11:54:22.383717: Epoch time: 19.08 s +2024-11-22 11:54:23.274540: +2024-11-22 11:54:23.274758: Epoch 4625 +2024-11-22 11:54:23.274869: Current learning rate: 0.0046 +2024-11-22 11:54:41.659360: train_loss -0.7991 +2024-11-22 11:54:41.659629: val_loss -0.769 +2024-11-22 11:54:41.659704: Pseudo dice [0.8429] +2024-11-22 11:54:41.659783: Epoch time: 18.39 s +2024-11-22 11:54:42.601512: +2024-11-22 11:54:42.601727: Epoch 4626 +2024-11-22 11:54:42.601835: Current learning rate: 0.0046 +2024-11-22 11:55:01.254608: train_loss -0.7879 +2024-11-22 11:55:01.255122: val_loss -0.7459 +2024-11-22 11:55:01.255222: Pseudo dice [0.8179] +2024-11-22 11:55:01.255309: Epoch time: 18.65 s +2024-11-22 11:55:02.240289: +2024-11-22 11:55:02.240529: Epoch 4627 +2024-11-22 11:55:02.240646: Current learning rate: 0.0046 +2024-11-22 11:55:22.007381: train_loss -0.7881 +2024-11-22 11:55:22.007824: val_loss -0.761 +2024-11-22 11:55:22.007921: Pseudo dice [0.8306] +2024-11-22 11:55:22.008004: Epoch time: 19.77 s +2024-11-22 11:55:22.865677: +2024-11-22 11:55:22.865890: Epoch 4628 +2024-11-22 11:55:22.866015: Current learning rate: 0.0046 +2024-11-22 11:55:42.074851: train_loss -0.7896 +2024-11-22 11:55:42.075124: val_loss -0.7355 +2024-11-22 11:55:42.075199: Pseudo dice [0.8296] +2024-11-22 11:55:42.075273: Epoch time: 19.21 s +2024-11-22 11:55:42.945306: +2024-11-22 11:55:42.945516: Epoch 4629 +2024-11-22 11:55:42.945632: Current learning rate: 0.00459 +2024-11-22 11:56:02.159534: train_loss -0.7968 +2024-11-22 11:56:02.159753: val_loss -0.7616 +2024-11-22 11:56:02.159833: Pseudo dice [0.842] +2024-11-22 11:56:02.159917: Epoch time: 19.22 s +2024-11-22 11:56:03.041728: +2024-11-22 11:56:03.041950: Epoch 4630 +2024-11-22 11:56:03.042071: Current learning rate: 0.00459 +2024-11-22 11:56:22.398622: train_loss -0.7969 +2024-11-22 11:56:22.398860: val_loss -0.7775 +2024-11-22 11:56:22.398935: Pseudo dice [0.8461] +2024-11-22 11:56:22.399023: Epoch time: 19.36 s +2024-11-22 11:56:23.275324: +2024-11-22 11:56:23.275574: Epoch 4631 +2024-11-22 11:56:23.275685: Current learning rate: 0.00459 +2024-11-22 11:56:41.889669: train_loss -0.7967 +2024-11-22 11:56:41.889881: val_loss -0.7435 +2024-11-22 11:56:41.889952: Pseudo dice [0.8232] +2024-11-22 11:56:41.890035: Epoch time: 18.62 s +2024-11-22 11:56:42.771466: +2024-11-22 11:56:42.771691: Epoch 4632 +2024-11-22 11:56:42.771812: Current learning rate: 0.00459 +2024-11-22 11:57:01.055714: train_loss -0.7932 +2024-11-22 11:57:01.055951: val_loss -0.7466 +2024-11-22 11:57:01.056032: Pseudo dice [0.8207] +2024-11-22 11:57:01.056107: Epoch time: 18.29 s +2024-11-22 11:57:01.945029: +2024-11-22 11:57:01.945250: Epoch 4633 +2024-11-22 11:57:01.945360: Current learning rate: 0.00459 +2024-11-22 11:57:20.904942: train_loss -0.7959 +2024-11-22 11:57:20.905169: val_loss -0.7643 +2024-11-22 11:57:20.905249: Pseudo dice [0.8243] +2024-11-22 11:57:20.905329: Epoch time: 18.96 s +2024-11-22 11:57:21.785210: +2024-11-22 11:57:21.785477: Epoch 4634 +2024-11-22 11:57:21.785595: Current learning rate: 0.00459 +2024-11-22 11:57:40.249014: train_loss -0.8041 +2024-11-22 11:57:40.249257: val_loss -0.747 +2024-11-22 11:57:40.249331: Pseudo dice [0.8396] +2024-11-22 11:57:40.249415: Epoch time: 18.46 s +2024-11-22 11:57:41.154060: +2024-11-22 11:57:41.154479: Epoch 4635 +2024-11-22 11:57:41.154624: Current learning rate: 0.00459 +2024-11-22 11:58:00.406428: train_loss -0.795 +2024-11-22 11:58:00.406697: val_loss -0.771 +2024-11-22 11:58:00.406774: Pseudo dice [0.8316] +2024-11-22 11:58:00.406850: Epoch time: 19.25 s +2024-11-22 11:58:01.280268: +2024-11-22 11:58:01.280689: Epoch 4636 +2024-11-22 11:58:01.280820: Current learning rate: 0.00459 +2024-11-22 11:58:19.949535: train_loss -0.7921 +2024-11-22 11:58:19.949752: val_loss -0.7459 +2024-11-22 11:58:19.949826: Pseudo dice [0.8314] +2024-11-22 11:58:19.949901: Epoch time: 18.67 s +2024-11-22 11:58:20.841197: +2024-11-22 11:58:20.841649: Epoch 4637 +2024-11-22 11:58:20.841778: Current learning rate: 0.00458 +2024-11-22 11:58:39.241427: train_loss -0.7913 +2024-11-22 11:58:39.241667: val_loss -0.7362 +2024-11-22 11:58:39.241740: Pseudo dice [0.8276] +2024-11-22 11:58:39.241820: Epoch time: 18.4 s +2024-11-22 11:58:40.116370: +2024-11-22 11:58:40.116565: Epoch 4638 +2024-11-22 11:58:40.116676: Current learning rate: 0.00458 +2024-11-22 11:58:59.385513: train_loss -0.7794 +2024-11-22 11:58:59.386042: val_loss -0.7419 +2024-11-22 11:58:59.386143: Pseudo dice [0.8386] +2024-11-22 11:58:59.386223: Epoch time: 19.27 s +2024-11-22 11:59:00.260936: +2024-11-22 11:59:00.261174: Epoch 4639 +2024-11-22 11:59:00.261292: Current learning rate: 0.00458 +2024-11-22 11:59:19.151342: train_loss -0.7928 +2024-11-22 11:59:19.151555: val_loss -0.7371 +2024-11-22 11:59:19.151631: Pseudo dice [0.8289] +2024-11-22 11:59:19.151708: Epoch time: 18.89 s +2024-11-22 11:59:20.026001: +2024-11-22 11:59:20.026326: Epoch 4640 +2024-11-22 11:59:20.026441: Current learning rate: 0.00458 +2024-11-22 11:59:38.477242: train_loss -0.7951 +2024-11-22 11:59:38.477483: val_loss -0.7616 +2024-11-22 11:59:38.477565: Pseudo dice [0.8529] +2024-11-22 11:59:38.477708: Epoch time: 18.45 s +2024-11-22 11:59:39.358878: +2024-11-22 11:59:39.359094: Epoch 4641 +2024-11-22 11:59:39.359207: Current learning rate: 0.00458 +2024-11-22 11:59:57.792277: train_loss -0.7961 +2024-11-22 11:59:57.792496: val_loss -0.7386 +2024-11-22 11:59:57.792570: Pseudo dice [0.8329] +2024-11-22 11:59:57.792645: Epoch time: 18.43 s +2024-11-22 11:59:58.683808: +2024-11-22 11:59:58.684038: Epoch 4642 +2024-11-22 11:59:58.684149: Current learning rate: 0.00458 +2024-11-22 12:00:18.054659: train_loss -0.7926 +2024-11-22 12:00:18.054880: val_loss -0.7286 +2024-11-22 12:00:18.055006: Pseudo dice [0.8204] +2024-11-22 12:00:18.055117: Epoch time: 19.37 s +2024-11-22 12:00:18.934696: +2024-11-22 12:00:18.934895: Epoch 4643 +2024-11-22 12:00:18.935017: Current learning rate: 0.00458 +2024-11-22 12:00:37.738769: train_loss -0.7943 +2024-11-22 12:00:37.739003: val_loss -0.7325 +2024-11-22 12:00:37.739083: Pseudo dice [0.8248] +2024-11-22 12:00:37.739161: Epoch time: 18.8 s +2024-11-22 12:00:38.641410: +2024-11-22 12:00:38.641610: Epoch 4644 +2024-11-22 12:00:38.641729: Current learning rate: 0.00458 +2024-11-22 12:00:57.028665: train_loss -0.7977 +2024-11-22 12:00:57.028932: val_loss -0.7636 +2024-11-22 12:00:57.029016: Pseudo dice [0.8248] +2024-11-22 12:00:57.029094: Epoch time: 18.39 s +2024-11-22 12:00:57.903316: +2024-11-22 12:00:57.903539: Epoch 4645 +2024-11-22 12:00:57.903653: Current learning rate: 0.00457 +2024-11-22 12:01:16.531927: train_loss -0.7944 +2024-11-22 12:01:16.532188: val_loss -0.7525 +2024-11-22 12:01:16.549514: Pseudo dice [0.8321] +2024-11-22 12:01:16.549695: Epoch time: 18.63 s +2024-11-22 12:01:17.436441: +2024-11-22 12:01:17.436726: Epoch 4646 +2024-11-22 12:01:17.436842: Current learning rate: 0.00457 +2024-11-22 12:01:35.262949: train_loss -0.8077 +2024-11-22 12:01:35.263176: val_loss -0.7522 +2024-11-22 12:01:35.263254: Pseudo dice [0.8195] +2024-11-22 12:01:35.263333: Epoch time: 17.83 s +2024-11-22 12:01:36.148174: +2024-11-22 12:01:36.148626: Epoch 4647 +2024-11-22 12:01:36.148763: Current learning rate: 0.00457 +2024-11-22 12:01:54.787609: train_loss -0.7969 +2024-11-22 12:01:54.787829: val_loss -0.7529 +2024-11-22 12:01:54.787904: Pseudo dice [0.8348] +2024-11-22 12:01:54.787982: Epoch time: 18.64 s +2024-11-22 12:01:55.678989: +2024-11-22 12:01:55.679404: Epoch 4648 +2024-11-22 12:01:55.679536: Current learning rate: 0.00457 +2024-11-22 12:02:13.878217: train_loss -0.798 +2024-11-22 12:02:13.878473: val_loss -0.7604 +2024-11-22 12:02:13.878554: Pseudo dice [0.8246] +2024-11-22 12:02:13.878638: Epoch time: 18.2 s +2024-11-22 12:02:14.754932: +2024-11-22 12:02:14.755360: Epoch 4649 +2024-11-22 12:02:14.755604: Current learning rate: 0.00457 +2024-11-22 12:02:33.351400: train_loss -0.7913 +2024-11-22 12:02:33.351622: val_loss -0.74 +2024-11-22 12:02:33.351754: Pseudo dice [0.8147] +2024-11-22 12:02:33.351831: Epoch time: 18.6 s +2024-11-22 12:02:34.978346: +2024-11-22 12:02:34.978559: Epoch 4650 +2024-11-22 12:02:34.978670: Current learning rate: 0.00457 +2024-11-22 12:02:54.225783: train_loss -0.7876 +2024-11-22 12:02:54.229133: val_loss -0.7563 +2024-11-22 12:02:54.229260: Pseudo dice [0.8354] +2024-11-22 12:02:54.229342: Epoch time: 19.25 s +2024-11-22 12:02:55.203361: +2024-11-22 12:02:55.203564: Epoch 4651 +2024-11-22 12:02:55.203680: Current learning rate: 0.00457 +2024-11-22 12:03:13.748582: train_loss -0.8022 +2024-11-22 12:03:13.748823: val_loss -0.7687 +2024-11-22 12:03:13.748899: Pseudo dice [0.833] +2024-11-22 12:03:13.748985: Epoch time: 18.55 s +2024-11-22 12:03:14.633673: +2024-11-22 12:03:14.633958: Epoch 4652 +2024-11-22 12:03:14.634079: Current learning rate: 0.00457 +2024-11-22 12:03:32.905281: train_loss -0.8009 +2024-11-22 12:03:32.905500: val_loss -0.7448 +2024-11-22 12:03:32.905583: Pseudo dice [0.8273] +2024-11-22 12:03:32.905663: Epoch time: 18.27 s +2024-11-22 12:03:33.781317: +2024-11-22 12:03:33.781574: Epoch 4653 +2024-11-22 12:03:33.781687: Current learning rate: 0.00456 +2024-11-22 12:03:52.301763: train_loss -0.7923 +2024-11-22 12:03:52.301980: val_loss -0.757 +2024-11-22 12:03:52.302064: Pseudo dice [0.8431] +2024-11-22 12:03:52.302145: Epoch time: 18.52 s +2024-11-22 12:03:53.197702: +2024-11-22 12:03:53.197923: Epoch 4654 +2024-11-22 12:03:53.198042: Current learning rate: 0.00456 +2024-11-22 12:04:11.805183: train_loss -0.7958 +2024-11-22 12:04:11.805409: val_loss -0.746 +2024-11-22 12:04:11.805488: Pseudo dice [0.8456] +2024-11-22 12:04:11.805566: Epoch time: 18.61 s +2024-11-22 12:04:12.954139: +2024-11-22 12:04:12.954345: Epoch 4655 +2024-11-22 12:04:12.954461: Current learning rate: 0.00456 +2024-11-22 12:04:32.643212: train_loss -0.7985 +2024-11-22 12:04:32.643524: val_loss -0.7371 +2024-11-22 12:04:32.643599: Pseudo dice [0.8162] +2024-11-22 12:04:32.643683: Epoch time: 19.69 s +2024-11-22 12:04:33.550838: +2024-11-22 12:04:33.551043: Epoch 4656 +2024-11-22 12:04:33.551156: Current learning rate: 0.00456 +2024-11-22 12:04:52.312360: train_loss -0.801 +2024-11-22 12:04:52.312588: val_loss -0.7166 +2024-11-22 12:04:52.312664: Pseudo dice [0.8159] +2024-11-22 12:04:52.312743: Epoch time: 18.76 s +2024-11-22 12:04:53.185774: +2024-11-22 12:04:53.185977: Epoch 4657 +2024-11-22 12:04:53.186096: Current learning rate: 0.00456 +2024-11-22 12:05:12.582666: train_loss -0.797 +2024-11-22 12:05:12.582875: val_loss -0.7189 +2024-11-22 12:05:12.582948: Pseudo dice [0.8329] +2024-11-22 12:05:12.583030: Epoch time: 19.4 s +2024-11-22 12:05:13.457412: +2024-11-22 12:05:13.457622: Epoch 4658 +2024-11-22 12:05:13.457733: Current learning rate: 0.00456 +2024-11-22 12:05:31.500233: train_loss -0.7871 +2024-11-22 12:05:31.500445: val_loss -0.7468 +2024-11-22 12:05:31.500522: Pseudo dice [0.8396] +2024-11-22 12:05:31.500600: Epoch time: 18.04 s +2024-11-22 12:05:32.417245: +2024-11-22 12:05:32.417476: Epoch 4659 +2024-11-22 12:05:32.417599: Current learning rate: 0.00456 +2024-11-22 12:05:50.024495: train_loss -0.7962 +2024-11-22 12:05:50.026896: val_loss -0.764 +2024-11-22 12:05:50.027018: Pseudo dice [0.8124] +2024-11-22 12:05:50.027105: Epoch time: 17.61 s +2024-11-22 12:05:50.968606: +2024-11-22 12:05:50.968803: Epoch 4660 +2024-11-22 12:05:50.968915: Current learning rate: 0.00456 +2024-11-22 12:06:10.493325: train_loss -0.7917 +2024-11-22 12:06:10.493547: val_loss -0.7435 +2024-11-22 12:06:10.493621: Pseudo dice [0.832] +2024-11-22 12:06:10.493698: Epoch time: 19.53 s +2024-11-22 12:06:11.375939: +2024-11-22 12:06:11.376149: Epoch 4661 +2024-11-22 12:06:11.376265: Current learning rate: 0.00455 +2024-11-22 12:06:29.680522: train_loss -0.7831 +2024-11-22 12:06:29.680733: val_loss -0.7578 +2024-11-22 12:06:29.680810: Pseudo dice [0.8448] +2024-11-22 12:06:29.680888: Epoch time: 18.31 s +2024-11-22 12:06:30.568255: +2024-11-22 12:06:30.568688: Epoch 4662 +2024-11-22 12:06:30.568820: Current learning rate: 0.00455 +2024-11-22 12:06:48.908054: train_loss -0.795 +2024-11-22 12:06:48.908607: val_loss -0.7453 +2024-11-22 12:06:48.908709: Pseudo dice [0.8108] +2024-11-22 12:06:48.908798: Epoch time: 18.34 s +2024-11-22 12:06:49.819749: +2024-11-22 12:06:49.820040: Epoch 4663 +2024-11-22 12:06:49.820159: Current learning rate: 0.00455 +2024-11-22 12:07:09.567847: train_loss -0.7987 +2024-11-22 12:07:09.568071: val_loss -0.7254 +2024-11-22 12:07:09.568148: Pseudo dice [0.8173] +2024-11-22 12:07:09.568224: Epoch time: 19.75 s +2024-11-22 12:07:10.463447: +2024-11-22 12:07:10.463677: Epoch 4664 +2024-11-22 12:07:10.463792: Current learning rate: 0.00455 +2024-11-22 12:07:30.332231: train_loss -0.7976 +2024-11-22 12:07:30.332534: val_loss -0.7553 +2024-11-22 12:07:30.332613: Pseudo dice [0.8317] +2024-11-22 12:07:30.332692: Epoch time: 19.87 s +2024-11-22 12:07:31.226986: +2024-11-22 12:07:31.227278: Epoch 4665 +2024-11-22 12:07:31.227398: Current learning rate: 0.00455 +2024-11-22 12:07:50.751346: train_loss -0.7937 +2024-11-22 12:07:50.751599: val_loss -0.7283 +2024-11-22 12:07:50.751678: Pseudo dice [0.8223] +2024-11-22 12:07:50.751778: Epoch time: 19.53 s +2024-11-22 12:07:51.641182: +2024-11-22 12:07:51.641435: Epoch 4666 +2024-11-22 12:07:51.641551: Current learning rate: 0.00455 +2024-11-22 12:08:10.655864: train_loss -0.7944 +2024-11-22 12:08:10.658756: val_loss -0.7632 +2024-11-22 12:08:10.658945: Pseudo dice [0.844] +2024-11-22 12:08:10.659037: Epoch time: 19.02 s +2024-11-22 12:08:11.627190: +2024-11-22 12:08:11.627407: Epoch 4667 +2024-11-22 12:08:11.627526: Current learning rate: 0.00455 +2024-11-22 12:08:30.294162: train_loss -0.7975 +2024-11-22 12:08:30.294376: val_loss -0.7594 +2024-11-22 12:08:30.294453: Pseudo dice [0.8371] +2024-11-22 12:08:30.294528: Epoch time: 18.67 s +2024-11-22 12:08:31.189334: +2024-11-22 12:08:31.189543: Epoch 4668 +2024-11-22 12:08:31.189658: Current learning rate: 0.00455 +2024-11-22 12:08:51.582061: train_loss -0.796 +2024-11-22 12:08:51.582284: val_loss -0.7377 +2024-11-22 12:08:51.582357: Pseudo dice [0.8271] +2024-11-22 12:08:51.582438: Epoch time: 20.39 s +2024-11-22 12:08:52.466182: +2024-11-22 12:08:52.466409: Epoch 4669 +2024-11-22 12:08:52.466523: Current learning rate: 0.00455 +2024-11-22 12:09:10.818997: train_loss -0.7893 +2024-11-22 12:09:10.819241: val_loss -0.7408 +2024-11-22 12:09:10.819318: Pseudo dice [0.7899] +2024-11-22 12:09:10.819399: Epoch time: 18.35 s +2024-11-22 12:09:11.744013: +2024-11-22 12:09:11.744205: Epoch 4670 +2024-11-22 12:09:11.744321: Current learning rate: 0.00454 +2024-11-22 12:09:30.477605: train_loss -0.7846 +2024-11-22 12:09:30.477835: val_loss -0.7543 +2024-11-22 12:09:30.477912: Pseudo dice [0.8191] +2024-11-22 12:09:30.477990: Epoch time: 18.73 s +2024-11-22 12:09:31.421577: +2024-11-22 12:09:31.422406: Epoch 4671 +2024-11-22 12:09:31.422522: Current learning rate: 0.00454 +2024-11-22 12:09:49.907333: train_loss -0.8005 +2024-11-22 12:09:49.907551: val_loss -0.7543 +2024-11-22 12:09:49.907637: Pseudo dice [0.8364] +2024-11-22 12:09:49.907730: Epoch time: 18.49 s +2024-11-22 12:09:50.786263: +2024-11-22 12:09:50.786551: Epoch 4672 +2024-11-22 12:09:50.786662: Current learning rate: 0.00454 +2024-11-22 12:10:09.612103: train_loss -0.7956 +2024-11-22 12:10:09.612349: val_loss -0.7678 +2024-11-22 12:10:09.612425: Pseudo dice [0.8278] +2024-11-22 12:10:09.612509: Epoch time: 18.83 s +2024-11-22 12:10:10.488915: +2024-11-22 12:10:10.489130: Epoch 4673 +2024-11-22 12:10:10.489245: Current learning rate: 0.00454 +2024-11-22 12:10:30.806602: train_loss -0.7938 +2024-11-22 12:10:30.806818: val_loss -0.7474 +2024-11-22 12:10:30.806893: Pseudo dice [0.8338] +2024-11-22 12:10:30.806970: Epoch time: 20.32 s +2024-11-22 12:10:31.717599: +2024-11-22 12:10:31.717900: Epoch 4674 +2024-11-22 12:10:31.718024: Current learning rate: 0.00454 +2024-11-22 12:10:50.512127: train_loss -0.796 +2024-11-22 12:10:50.512618: val_loss -0.7358 +2024-11-22 12:10:50.512720: Pseudo dice [0.8283] +2024-11-22 12:10:50.512796: Epoch time: 18.8 s +2024-11-22 12:10:51.388613: +2024-11-22 12:10:51.388827: Epoch 4675 +2024-11-22 12:10:51.389089: Current learning rate: 0.00454 +2024-11-22 12:11:09.595058: train_loss -0.7884 +2024-11-22 12:11:09.595308: val_loss -0.7546 +2024-11-22 12:11:09.595384: Pseudo dice [0.8266] +2024-11-22 12:11:09.595464: Epoch time: 18.21 s +2024-11-22 12:11:10.488609: +2024-11-22 12:11:10.488827: Epoch 4676 +2024-11-22 12:11:10.488941: Current learning rate: 0.00454 +2024-11-22 12:11:29.131095: train_loss -0.7921 +2024-11-22 12:11:29.131329: val_loss -0.7424 +2024-11-22 12:11:29.131406: Pseudo dice [0.8306] +2024-11-22 12:11:29.131488: Epoch time: 18.64 s +2024-11-22 12:11:30.006665: +2024-11-22 12:11:30.007017: Epoch 4677 +2024-11-22 12:11:30.007128: Current learning rate: 0.00454 +2024-11-22 12:11:49.647560: train_loss -0.7961 +2024-11-22 12:11:49.647778: val_loss -0.7569 +2024-11-22 12:11:49.647854: Pseudo dice [0.8301] +2024-11-22 12:11:49.647932: Epoch time: 19.64 s +2024-11-22 12:11:50.525430: +2024-11-22 12:11:50.525702: Epoch 4678 +2024-11-22 12:11:50.525817: Current learning rate: 0.00453 +2024-11-22 12:12:08.470132: train_loss -0.7936 +2024-11-22 12:12:08.470341: val_loss -0.7607 +2024-11-22 12:12:08.470415: Pseudo dice [0.8309] +2024-11-22 12:12:08.470491: Epoch time: 17.95 s +2024-11-22 12:12:09.348373: +2024-11-22 12:12:09.348639: Epoch 4679 +2024-11-22 12:12:09.348760: Current learning rate: 0.00453 +2024-11-22 12:12:28.119540: train_loss -0.792 +2024-11-22 12:12:28.119758: val_loss -0.7672 +2024-11-22 12:12:28.119834: Pseudo dice [0.8401] +2024-11-22 12:12:28.119914: Epoch time: 18.77 s +2024-11-22 12:12:29.028392: +2024-11-22 12:12:29.028670: Epoch 4680 +2024-11-22 12:12:29.028786: Current learning rate: 0.00453 +2024-11-22 12:12:47.435796: train_loss -0.8018 +2024-11-22 12:12:47.436092: val_loss -0.7595 +2024-11-22 12:12:47.436174: Pseudo dice [0.8183] +2024-11-22 12:12:47.436264: Epoch time: 18.4 s +2024-11-22 12:12:48.540149: +2024-11-22 12:12:48.540357: Epoch 4681 +2024-11-22 12:12:48.540472: Current learning rate: 0.00453 +2024-11-22 12:13:07.015300: train_loss -0.8 +2024-11-22 12:13:07.015515: val_loss -0.7644 +2024-11-22 12:13:07.015599: Pseudo dice [0.8426] +2024-11-22 12:13:07.015677: Epoch time: 18.48 s +2024-11-22 12:13:07.901349: +2024-11-22 12:13:07.901565: Epoch 4682 +2024-11-22 12:13:07.901678: Current learning rate: 0.00453 +2024-11-22 12:13:25.768647: train_loss -0.8013 +2024-11-22 12:13:25.768864: val_loss -0.7402 +2024-11-22 12:13:25.768941: Pseudo dice [0.8481] +2024-11-22 12:13:25.769100: Epoch time: 17.87 s +2024-11-22 12:13:26.667542: +2024-11-22 12:13:26.667754: Epoch 4683 +2024-11-22 12:13:26.667865: Current learning rate: 0.00453 +2024-11-22 12:13:45.105329: train_loss -0.8007 +2024-11-22 12:13:45.105571: val_loss -0.7578 +2024-11-22 12:13:45.105649: Pseudo dice [0.8406] +2024-11-22 12:13:45.119560: Epoch time: 18.44 s +2024-11-22 12:13:45.998430: +2024-11-22 12:13:45.998631: Epoch 4684 +2024-11-22 12:13:45.998748: Current learning rate: 0.00453 +2024-11-22 12:14:04.093261: train_loss -0.7988 +2024-11-22 12:14:04.093478: val_loss -0.7418 +2024-11-22 12:14:04.093555: Pseudo dice [0.8297] +2024-11-22 12:14:04.093639: Epoch time: 18.1 s +2024-11-22 12:14:04.977806: +2024-11-22 12:14:04.978013: Epoch 4685 +2024-11-22 12:14:04.978128: Current learning rate: 0.00453 +2024-11-22 12:14:24.177140: train_loss -0.7962 +2024-11-22 12:14:24.177369: val_loss -0.7507 +2024-11-22 12:14:24.177447: Pseudo dice [0.8341] +2024-11-22 12:14:24.177527: Epoch time: 19.2 s +2024-11-22 12:14:25.063459: +2024-11-22 12:14:25.063664: Epoch 4686 +2024-11-22 12:14:25.063775: Current learning rate: 0.00452 +2024-11-22 12:14:44.213635: train_loss -0.7978 +2024-11-22 12:14:44.214280: val_loss -0.7631 +2024-11-22 12:14:44.214388: Pseudo dice [0.836] +2024-11-22 12:14:44.214478: Epoch time: 19.15 s +2024-11-22 12:14:45.095024: +2024-11-22 12:14:45.095236: Epoch 4687 +2024-11-22 12:14:45.095346: Current learning rate: 0.00452 +2024-11-22 12:15:04.215108: train_loss -0.8043 +2024-11-22 12:15:04.215323: val_loss -0.7763 +2024-11-22 12:15:04.215408: Pseudo dice [0.8563] +2024-11-22 12:15:04.215517: Epoch time: 19.12 s +2024-11-22 12:15:05.088229: +2024-11-22 12:15:05.088442: Epoch 4688 +2024-11-22 12:15:05.088557: Current learning rate: 0.00452 +2024-11-22 12:15:23.172554: train_loss -0.7992 +2024-11-22 12:15:23.172772: val_loss -0.7569 +2024-11-22 12:15:23.172849: Pseudo dice [0.8241] +2024-11-22 12:15:23.172926: Epoch time: 18.09 s +2024-11-22 12:15:24.058434: +2024-11-22 12:15:24.058641: Epoch 4689 +2024-11-22 12:15:24.058750: Current learning rate: 0.00452 +2024-11-22 12:15:42.275571: train_loss -0.7986 +2024-11-22 12:15:42.275816: val_loss -0.7399 +2024-11-22 12:15:42.275893: Pseudo dice [0.8164] +2024-11-22 12:15:42.275976: Epoch time: 18.22 s +2024-11-22 12:15:43.169711: +2024-11-22 12:15:43.169944: Epoch 4690 +2024-11-22 12:15:43.170070: Current learning rate: 0.00452 +2024-11-22 12:16:00.744250: train_loss -0.7933 +2024-11-22 12:16:00.744486: val_loss -0.7775 +2024-11-22 12:16:00.744598: Pseudo dice [0.8437] +2024-11-22 12:16:00.744680: Epoch time: 17.58 s +2024-11-22 12:16:01.630236: +2024-11-22 12:16:01.630464: Epoch 4691 +2024-11-22 12:16:01.630582: Current learning rate: 0.00452 +2024-11-22 12:16:20.160950: train_loss -0.8002 +2024-11-22 12:16:20.161170: val_loss -0.769 +2024-11-22 12:16:20.161245: Pseudo dice [0.8405] +2024-11-22 12:16:20.161322: Epoch time: 18.53 s +2024-11-22 12:16:21.045762: +2024-11-22 12:16:21.045971: Epoch 4692 +2024-11-22 12:16:21.046085: Current learning rate: 0.00452 +2024-11-22 12:16:40.054054: train_loss -0.7951 +2024-11-22 12:16:40.054281: val_loss -0.7503 +2024-11-22 12:16:40.054367: Pseudo dice [0.837] +2024-11-22 12:16:40.054444: Epoch time: 19.01 s +2024-11-22 12:16:41.030272: +2024-11-22 12:16:41.030492: Epoch 4693 +2024-11-22 12:16:41.030604: Current learning rate: 0.00452 +2024-11-22 12:17:00.170380: train_loss -0.7877 +2024-11-22 12:17:00.170622: val_loss -0.7512 +2024-11-22 12:17:00.170698: Pseudo dice [0.83] +2024-11-22 12:17:00.170800: Epoch time: 19.14 s +2024-11-22 12:17:01.056372: +2024-11-22 12:17:01.056610: Epoch 4694 +2024-11-22 12:17:01.056732: Current learning rate: 0.00451 +2024-11-22 12:17:19.476328: train_loss -0.7946 +2024-11-22 12:17:19.478722: val_loss -0.739 +2024-11-22 12:17:19.478812: Pseudo dice [0.8323] +2024-11-22 12:17:19.478891: Epoch time: 18.42 s +2024-11-22 12:17:20.481671: +2024-11-22 12:17:20.481910: Epoch 4695 +2024-11-22 12:17:20.482028: Current learning rate: 0.00451 +2024-11-22 12:17:38.550472: train_loss -0.7939 +2024-11-22 12:17:38.550686: val_loss -0.7403 +2024-11-22 12:17:38.550762: Pseudo dice [0.823] +2024-11-22 12:17:38.550840: Epoch time: 18.07 s +2024-11-22 12:17:39.430426: +2024-11-22 12:17:39.430637: Epoch 4696 +2024-11-22 12:17:39.430752: Current learning rate: 0.00451 +2024-11-22 12:17:57.612015: train_loss -0.8068 +2024-11-22 12:17:57.625358: val_loss -0.7337 +2024-11-22 12:17:57.625510: Pseudo dice [0.8157] +2024-11-22 12:17:57.625609: Epoch time: 18.18 s +2024-11-22 12:17:58.532807: +2024-11-22 12:17:58.533032: Epoch 4697 +2024-11-22 12:17:58.533144: Current learning rate: 0.00451 +2024-11-22 12:18:19.027729: train_loss -0.7913 +2024-11-22 12:18:19.028010: val_loss -0.7167 +2024-11-22 12:18:19.028086: Pseudo dice [0.8065] +2024-11-22 12:18:19.028163: Epoch time: 20.5 s +2024-11-22 12:18:19.908786: +2024-11-22 12:18:19.909027: Epoch 4698 +2024-11-22 12:18:19.909138: Current learning rate: 0.00451 +2024-11-22 12:18:37.609589: train_loss -0.787 +2024-11-22 12:18:37.610064: val_loss -0.7296 +2024-11-22 12:18:37.610164: Pseudo dice [0.8086] +2024-11-22 12:18:37.610242: Epoch time: 17.7 s +2024-11-22 12:18:38.467327: +2024-11-22 12:18:38.467523: Epoch 4699 +2024-11-22 12:18:38.467634: Current learning rate: 0.00451 +2024-11-22 12:18:57.240766: train_loss -0.7878 +2024-11-22 12:18:57.241005: val_loss -0.7504 +2024-11-22 12:18:57.241140: Pseudo dice [0.8342] +2024-11-22 12:18:57.241220: Epoch time: 18.77 s +2024-11-22 12:18:58.418441: +2024-11-22 12:18:58.418655: Epoch 4700 +2024-11-22 12:18:58.418770: Current learning rate: 0.00451 +2024-11-22 12:19:16.890122: train_loss -0.7916 +2024-11-22 12:19:16.890372: val_loss -0.754 +2024-11-22 12:19:16.890450: Pseudo dice [0.8248] +2024-11-22 12:19:16.890530: Epoch time: 18.47 s +2024-11-22 12:19:17.762724: +2024-11-22 12:19:17.763053: Epoch 4701 +2024-11-22 12:19:17.763172: Current learning rate: 0.00451 +2024-11-22 12:19:36.024650: train_loss -0.7785 +2024-11-22 12:19:36.024854: val_loss -0.753 +2024-11-22 12:19:36.024929: Pseudo dice [0.8237] +2024-11-22 12:19:36.025008: Epoch time: 18.26 s +2024-11-22 12:19:36.901757: +2024-11-22 12:19:36.901987: Epoch 4702 +2024-11-22 12:19:36.902102: Current learning rate: 0.0045 +2024-11-22 12:19:55.517127: train_loss -0.7834 +2024-11-22 12:19:55.517353: val_loss -0.741 +2024-11-22 12:19:55.517430: Pseudo dice [0.8271] +2024-11-22 12:19:55.517510: Epoch time: 18.62 s +2024-11-22 12:19:56.482392: +2024-11-22 12:19:56.482633: Epoch 4703 +2024-11-22 12:19:56.482745: Current learning rate: 0.0045 +2024-11-22 12:20:15.404489: train_loss -0.7918 +2024-11-22 12:20:15.404709: val_loss -0.7704 +2024-11-22 12:20:15.404791: Pseudo dice [0.8353] +2024-11-22 12:20:15.404881: Epoch time: 18.92 s +2024-11-22 12:20:16.310979: +2024-11-22 12:20:16.311214: Epoch 4704 +2024-11-22 12:20:16.311333: Current learning rate: 0.0045 +2024-11-22 12:20:34.908865: train_loss -0.7858 +2024-11-22 12:20:34.909109: val_loss -0.7589 +2024-11-22 12:20:34.909184: Pseudo dice [0.8413] +2024-11-22 12:20:34.909267: Epoch time: 18.6 s +2024-11-22 12:20:35.867500: +2024-11-22 12:20:35.867820: Epoch 4705 +2024-11-22 12:20:35.867945: Current learning rate: 0.0045 +2024-11-22 12:20:55.712903: train_loss -0.7692 +2024-11-22 12:20:55.713133: val_loss -0.7521 +2024-11-22 12:20:55.713207: Pseudo dice [0.8276] +2024-11-22 12:20:55.713289: Epoch time: 19.85 s +2024-11-22 12:20:56.615389: +2024-11-22 12:20:56.615627: Epoch 4706 +2024-11-22 12:20:56.615741: Current learning rate: 0.0045 +2024-11-22 12:21:16.116568: train_loss -0.764 +2024-11-22 12:21:16.116787: val_loss -0.7486 +2024-11-22 12:21:16.116863: Pseudo dice [0.8301] +2024-11-22 12:21:16.116943: Epoch time: 19.5 s +2024-11-22 12:21:17.001450: +2024-11-22 12:21:17.001678: Epoch 4707 +2024-11-22 12:21:17.001790: Current learning rate: 0.0045 +2024-11-22 12:21:36.300234: train_loss -0.7826 +2024-11-22 12:21:36.300489: val_loss -0.7443 +2024-11-22 12:21:36.300577: Pseudo dice [0.8243] +2024-11-22 12:21:36.300672: Epoch time: 19.3 s +2024-11-22 12:21:37.183891: +2024-11-22 12:21:37.184118: Epoch 4708 +2024-11-22 12:21:37.184229: Current learning rate: 0.0045 +2024-11-22 12:21:54.608582: train_loss -0.7873 +2024-11-22 12:21:54.608795: val_loss -0.7498 +2024-11-22 12:21:54.608872: Pseudo dice [0.8265] +2024-11-22 12:21:54.608948: Epoch time: 17.43 s +2024-11-22 12:21:55.541781: +2024-11-22 12:21:55.542004: Epoch 4709 +2024-11-22 12:21:55.551741: Current learning rate: 0.0045 +2024-11-22 12:22:15.162190: train_loss -0.7737 +2024-11-22 12:22:15.162418: val_loss -0.7362 +2024-11-22 12:22:15.162494: Pseudo dice [0.8261] +2024-11-22 12:22:15.162567: Epoch time: 19.62 s +2024-11-22 12:22:16.192027: +2024-11-22 12:22:16.192255: Epoch 4710 +2024-11-22 12:22:16.192366: Current learning rate: 0.00449 +2024-11-22 12:22:34.612606: train_loss -0.7595 +2024-11-22 12:22:34.613172: val_loss -0.7027 +2024-11-22 12:22:34.613274: Pseudo dice [0.7899] +2024-11-22 12:22:34.613366: Epoch time: 18.42 s +2024-11-22 12:22:35.500212: +2024-11-22 12:22:35.500412: Epoch 4711 +2024-11-22 12:22:35.500513: Current learning rate: 0.00449 +2024-11-22 12:22:53.937735: train_loss -0.7702 +2024-11-22 12:22:53.937952: val_loss -0.7363 +2024-11-22 12:22:53.938050: Pseudo dice [0.8258] +2024-11-22 12:22:53.938138: Epoch time: 18.44 s +2024-11-22 12:22:54.809060: +2024-11-22 12:22:54.809266: Epoch 4712 +2024-11-22 12:22:54.809373: Current learning rate: 0.00449 +2024-11-22 12:23:12.942212: train_loss -0.7778 +2024-11-22 12:23:12.942430: val_loss -0.7604 +2024-11-22 12:23:12.942503: Pseudo dice [0.8304] +2024-11-22 12:23:12.942579: Epoch time: 18.13 s +2024-11-22 12:23:13.815841: +2024-11-22 12:23:13.816070: Epoch 4713 +2024-11-22 12:23:13.816183: Current learning rate: 0.00449 +2024-11-22 12:23:32.846591: train_loss -0.7871 +2024-11-22 12:23:32.849044: val_loss -0.7421 +2024-11-22 12:23:32.849150: Pseudo dice [0.8194] +2024-11-22 12:23:32.849236: Epoch time: 19.03 s +2024-11-22 12:23:33.801533: +2024-11-22 12:23:33.801742: Epoch 4714 +2024-11-22 12:23:33.801852: Current learning rate: 0.00449 +2024-11-22 12:23:53.524237: train_loss -0.7949 +2024-11-22 12:23:53.524472: val_loss -0.7222 +2024-11-22 12:23:53.526736: Pseudo dice [0.7977] +2024-11-22 12:23:53.526835: Epoch time: 19.72 s +2024-11-22 12:23:54.452863: +2024-11-22 12:23:54.453084: Epoch 4715 +2024-11-22 12:23:54.453200: Current learning rate: 0.00449 +2024-11-22 12:24:13.687094: train_loss -0.7924 +2024-11-22 12:24:13.687315: val_loss -0.7555 +2024-11-22 12:24:13.687391: Pseudo dice [0.8247] +2024-11-22 12:24:13.692663: Epoch time: 19.24 s +2024-11-22 12:24:14.743281: +2024-11-22 12:24:14.743559: Epoch 4716 +2024-11-22 12:24:14.743676: Current learning rate: 0.00449 +2024-11-22 12:24:32.589387: train_loss -0.792 +2024-11-22 12:24:32.589613: val_loss -0.7661 +2024-11-22 12:24:32.589685: Pseudo dice [0.8309] +2024-11-22 12:24:32.589768: Epoch time: 17.85 s +2024-11-22 12:24:33.487476: +2024-11-22 12:24:33.487716: Epoch 4717 +2024-11-22 12:24:33.487824: Current learning rate: 0.00449 +2024-11-22 12:24:52.207199: train_loss -0.7839 +2024-11-22 12:24:52.214768: val_loss -0.7442 +2024-11-22 12:24:52.214894: Pseudo dice [0.7975] +2024-11-22 12:24:52.214986: Epoch time: 18.72 s +2024-11-22 12:24:53.253297: +2024-11-22 12:24:53.253682: Epoch 4718 +2024-11-22 12:24:53.253792: Current learning rate: 0.00448 +2024-11-22 12:25:13.658597: train_loss -0.7904 +2024-11-22 12:25:13.658813: val_loss -0.7256 +2024-11-22 12:25:13.658888: Pseudo dice [0.8151] +2024-11-22 12:25:13.658969: Epoch time: 20.41 s +2024-11-22 12:25:14.524905: +2024-11-22 12:25:14.525120: Epoch 4719 +2024-11-22 12:25:14.525230: Current learning rate: 0.00448 +2024-11-22 12:25:32.891157: train_loss -0.8023 +2024-11-22 12:25:32.891939: val_loss -0.7728 +2024-11-22 12:25:32.892041: Pseudo dice [0.8384] +2024-11-22 12:25:32.892116: Epoch time: 18.37 s +2024-11-22 12:25:33.764996: +2024-11-22 12:25:33.765206: Epoch 4720 +2024-11-22 12:25:33.765317: Current learning rate: 0.00448 +2024-11-22 12:25:51.453947: train_loss -0.7829 +2024-11-22 12:25:51.454199: val_loss -0.7338 +2024-11-22 12:25:51.454275: Pseudo dice [0.8063] +2024-11-22 12:25:51.454364: Epoch time: 17.69 s +2024-11-22 12:25:52.330486: +2024-11-22 12:25:52.330705: Epoch 4721 +2024-11-22 12:25:52.330823: Current learning rate: 0.00448 +2024-11-22 12:26:11.351663: train_loss -0.7885 +2024-11-22 12:26:11.351901: val_loss -0.7491 +2024-11-22 12:26:11.351976: Pseudo dice [0.8438] +2024-11-22 12:26:11.352066: Epoch time: 19.02 s +2024-11-22 12:26:12.289459: +2024-11-22 12:26:12.289683: Epoch 4722 +2024-11-22 12:26:12.289799: Current learning rate: 0.00448 +2024-11-22 12:26:31.963951: train_loss -0.7975 +2024-11-22 12:26:31.964394: val_loss -0.7453 +2024-11-22 12:26:31.964488: Pseudo dice [0.8507] +2024-11-22 12:26:31.964567: Epoch time: 19.68 s +2024-11-22 12:26:32.828546: +2024-11-22 12:26:32.828771: Epoch 4723 +2024-11-22 12:26:32.828884: Current learning rate: 0.00448 +2024-11-22 12:26:51.916317: train_loss -0.795 +2024-11-22 12:26:51.916557: val_loss -0.7546 +2024-11-22 12:26:51.916640: Pseudo dice [0.8346] +2024-11-22 12:26:51.916729: Epoch time: 19.09 s +2024-11-22 12:26:52.790602: +2024-11-22 12:26:52.790821: Epoch 4724 +2024-11-22 12:26:52.790931: Current learning rate: 0.00448 +2024-11-22 12:27:11.227252: train_loss -0.7971 +2024-11-22 12:27:11.227461: val_loss -0.755 +2024-11-22 12:27:11.227536: Pseudo dice [0.8106] +2024-11-22 12:27:11.227628: Epoch time: 18.44 s +2024-11-22 12:27:12.112035: +2024-11-22 12:27:12.112277: Epoch 4725 +2024-11-22 12:27:12.112386: Current learning rate: 0.00448 +2024-11-22 12:27:29.798931: train_loss -0.7979 +2024-11-22 12:27:29.805723: val_loss -0.7207 +2024-11-22 12:27:29.805871: Pseudo dice [0.8159] +2024-11-22 12:27:29.805952: Epoch time: 17.69 s +2024-11-22 12:27:30.756714: +2024-11-22 12:27:30.756917: Epoch 4726 +2024-11-22 12:27:30.757038: Current learning rate: 0.00447 +2024-11-22 12:27:50.262756: train_loss -0.7984 +2024-11-22 12:27:50.262960: val_loss -0.7409 +2024-11-22 12:27:50.263038: Pseudo dice [0.7955] +2024-11-22 12:27:50.263111: Epoch time: 19.51 s +2024-11-22 12:27:51.174941: +2024-11-22 12:27:51.175157: Epoch 4727 +2024-11-22 12:27:51.175269: Current learning rate: 0.00447 +2024-11-22 12:28:08.795245: train_loss -0.798 +2024-11-22 12:28:08.795485: val_loss -0.717 +2024-11-22 12:28:08.795562: Pseudo dice [0.8158] +2024-11-22 12:28:08.795646: Epoch time: 17.62 s +2024-11-22 12:28:09.702011: +2024-11-22 12:28:09.702223: Epoch 4728 +2024-11-22 12:28:09.702343: Current learning rate: 0.00447 +2024-11-22 12:28:27.035220: train_loss -0.7935 +2024-11-22 12:28:27.035443: val_loss -0.7649 +2024-11-22 12:28:27.035522: Pseudo dice [0.8322] +2024-11-22 12:28:27.035599: Epoch time: 17.33 s +2024-11-22 12:28:28.071849: +2024-11-22 12:28:28.072128: Epoch 4729 +2024-11-22 12:28:28.072243: Current learning rate: 0.00447 +2024-11-22 12:28:46.597591: train_loss -0.7953 +2024-11-22 12:28:46.597812: val_loss -0.7569 +2024-11-22 12:28:46.597887: Pseudo dice [0.8348] +2024-11-22 12:28:46.597964: Epoch time: 18.53 s +2024-11-22 12:28:47.547531: +2024-11-22 12:28:47.547868: Epoch 4730 +2024-11-22 12:28:47.547984: Current learning rate: 0.00447 +2024-11-22 12:29:06.282242: train_loss -0.8045 +2024-11-22 12:29:06.282468: val_loss -0.7419 +2024-11-22 12:29:06.282551: Pseudo dice [0.8187] +2024-11-22 12:29:06.282637: Epoch time: 18.74 s +2024-11-22 12:29:07.168202: +2024-11-22 12:29:07.168473: Epoch 4731 +2024-11-22 12:29:07.168590: Current learning rate: 0.00447 +2024-11-22 12:29:26.339621: train_loss -0.7965 +2024-11-22 12:29:26.339869: val_loss -0.7314 +2024-11-22 12:29:26.339945: Pseudo dice [0.8232] +2024-11-22 12:29:26.340065: Epoch time: 19.17 s +2024-11-22 12:29:27.237182: +2024-11-22 12:29:27.237408: Epoch 4732 +2024-11-22 12:29:27.237516: Current learning rate: 0.00447 +2024-11-22 12:29:45.951794: train_loss -0.7946 +2024-11-22 12:29:45.952028: val_loss -0.7328 +2024-11-22 12:29:45.952102: Pseudo dice [0.8448] +2024-11-22 12:29:45.952178: Epoch time: 18.72 s +2024-11-22 12:29:46.839470: +2024-11-22 12:29:46.839753: Epoch 4733 +2024-11-22 12:29:46.839864: Current learning rate: 0.00447 +2024-11-22 12:30:05.444624: train_loss -0.7957 +2024-11-22 12:30:05.444837: val_loss -0.7525 +2024-11-22 12:30:05.444914: Pseudo dice [0.8388] +2024-11-22 12:30:05.445001: Epoch time: 18.61 s +2024-11-22 12:30:06.415413: +2024-11-22 12:30:06.415709: Epoch 4734 +2024-11-22 12:30:06.415822: Current learning rate: 0.00447 +2024-11-22 12:30:25.765218: train_loss -0.7903 +2024-11-22 12:30:25.767868: val_loss -0.7723 +2024-11-22 12:30:25.787079: Pseudo dice [0.8363] +2024-11-22 12:30:25.787243: Epoch time: 19.35 s +2024-11-22 12:30:26.881547: +2024-11-22 12:30:26.881756: Epoch 4735 +2024-11-22 12:30:26.881867: Current learning rate: 0.00446 +2024-11-22 12:30:44.873169: train_loss -0.8008 +2024-11-22 12:30:44.873388: val_loss -0.7463 +2024-11-22 12:30:44.873466: Pseudo dice [0.8297] +2024-11-22 12:30:44.873547: Epoch time: 17.99 s +2024-11-22 12:30:45.758905: +2024-11-22 12:30:45.759136: Epoch 4736 +2024-11-22 12:30:45.759252: Current learning rate: 0.00446 +2024-11-22 12:31:04.555559: train_loss -0.7922 +2024-11-22 12:31:04.555784: val_loss -0.744 +2024-11-22 12:31:04.555862: Pseudo dice [0.8228] +2024-11-22 12:31:04.555941: Epoch time: 18.8 s +2024-11-22 12:31:05.446380: +2024-11-22 12:31:05.446610: Epoch 4737 +2024-11-22 12:31:05.446722: Current learning rate: 0.00446 +2024-11-22 12:31:24.718517: train_loss -0.795 +2024-11-22 12:31:24.718769: val_loss -0.7603 +2024-11-22 12:31:24.718844: Pseudo dice [0.834] +2024-11-22 12:31:24.718925: Epoch time: 19.27 s +2024-11-22 12:31:25.600969: +2024-11-22 12:31:25.601192: Epoch 4738 +2024-11-22 12:31:25.601309: Current learning rate: 0.00446 +2024-11-22 12:31:44.668171: train_loss -0.788 +2024-11-22 12:31:44.670122: val_loss -0.7366 +2024-11-22 12:31:44.670245: Pseudo dice [0.8168] +2024-11-22 12:31:44.670331: Epoch time: 19.07 s +2024-11-22 12:31:45.567928: +2024-11-22 12:31:45.568156: Epoch 4739 +2024-11-22 12:31:45.568276: Current learning rate: 0.00446 +2024-11-22 12:32:03.740023: train_loss -0.7923 +2024-11-22 12:32:03.740248: val_loss -0.7334 +2024-11-22 12:32:03.740319: Pseudo dice [0.8287] +2024-11-22 12:32:03.740396: Epoch time: 18.17 s +2024-11-22 12:32:04.644479: +2024-11-22 12:32:04.644692: Epoch 4740 +2024-11-22 12:32:04.644809: Current learning rate: 0.00446 +2024-11-22 12:32:22.240272: train_loss -0.7939 +2024-11-22 12:32:22.240492: val_loss -0.7604 +2024-11-22 12:32:22.240571: Pseudo dice [0.8255] +2024-11-22 12:32:22.240652: Epoch time: 17.6 s +2024-11-22 12:32:23.152474: +2024-11-22 12:32:23.152692: Epoch 4741 +2024-11-22 12:32:23.152811: Current learning rate: 0.00446 +2024-11-22 12:32:42.430325: train_loss -0.7789 +2024-11-22 12:32:42.430629: val_loss -0.7477 +2024-11-22 12:32:42.430706: Pseudo dice [0.8158] +2024-11-22 12:32:42.430789: Epoch time: 19.28 s +2024-11-22 12:32:43.318817: +2024-11-22 12:32:43.319025: Epoch 4742 +2024-11-22 12:32:43.319145: Current learning rate: 0.00446 +2024-11-22 12:33:02.143575: train_loss -0.7883 +2024-11-22 12:33:02.143829: val_loss -0.6951 +2024-11-22 12:33:02.143902: Pseudo dice [0.7966] +2024-11-22 12:33:02.143982: Epoch time: 18.83 s +2024-11-22 12:33:03.018410: +2024-11-22 12:33:03.018621: Epoch 4743 +2024-11-22 12:33:03.018729: Current learning rate: 0.00445 +2024-11-22 12:33:21.382845: train_loss -0.7906 +2024-11-22 12:33:21.383096: val_loss -0.7313 +2024-11-22 12:33:21.383175: Pseudo dice [0.8316] +2024-11-22 12:33:21.383252: Epoch time: 18.37 s +2024-11-22 12:33:22.288687: +2024-11-22 12:33:22.288913: Epoch 4744 +2024-11-22 12:33:22.289033: Current learning rate: 0.00445 +2024-11-22 12:33:40.994130: train_loss -0.7923 +2024-11-22 12:33:40.994421: val_loss -0.7639 +2024-11-22 12:33:40.994504: Pseudo dice [0.8327] +2024-11-22 12:33:40.994588: Epoch time: 18.71 s +2024-11-22 12:33:41.906582: +2024-11-22 12:33:41.906872: Epoch 4745 +2024-11-22 12:33:41.906994: Current learning rate: 0.00445 +2024-11-22 12:33:59.980194: train_loss -0.7892 +2024-11-22 12:33:59.980431: val_loss -0.7619 +2024-11-22 12:33:59.980565: Pseudo dice [0.8351] +2024-11-22 12:33:59.980648: Epoch time: 18.07 s +2024-11-22 12:34:00.868791: +2024-11-22 12:34:00.869026: Epoch 4746 +2024-11-22 12:34:00.869137: Current learning rate: 0.00445 +2024-11-22 12:34:18.911449: train_loss -0.7899 +2024-11-22 12:34:18.917149: val_loss -0.7274 +2024-11-22 12:34:18.917259: Pseudo dice [0.8226] +2024-11-22 12:34:18.917336: Epoch time: 18.04 s +2024-11-22 12:34:19.990942: +2024-11-22 12:34:19.991149: Epoch 4747 +2024-11-22 12:34:19.991263: Current learning rate: 0.00445 +2024-11-22 12:34:38.359165: train_loss -0.7785 +2024-11-22 12:34:38.359390: val_loss -0.7368 +2024-11-22 12:34:38.359468: Pseudo dice [0.8193] +2024-11-22 12:34:38.359548: Epoch time: 18.37 s +2024-11-22 12:34:39.249973: +2024-11-22 12:34:39.250182: Epoch 4748 +2024-11-22 12:34:39.250295: Current learning rate: 0.00445 +2024-11-22 12:34:59.686115: train_loss -0.7833 +2024-11-22 12:34:59.686362: val_loss -0.7516 +2024-11-22 12:34:59.686441: Pseudo dice [0.8168] +2024-11-22 12:34:59.686525: Epoch time: 20.44 s +2024-11-22 12:35:00.580081: +2024-11-22 12:35:00.580277: Epoch 4749 +2024-11-22 12:35:00.580394: Current learning rate: 0.00445 +2024-11-22 12:35:19.732721: train_loss -0.7762 +2024-11-22 12:35:19.732948: val_loss -0.7629 +2024-11-22 12:35:19.738230: Pseudo dice [0.8245] +2024-11-22 12:35:19.738343: Epoch time: 19.15 s +2024-11-22 12:35:21.000223: +2024-11-22 12:35:21.000522: Epoch 4750 +2024-11-22 12:35:21.000638: Current learning rate: 0.00445 +2024-11-22 12:35:38.820142: train_loss -0.7752 +2024-11-22 12:35:38.820366: val_loss -0.7664 +2024-11-22 12:35:38.820440: Pseudo dice [0.8446] +2024-11-22 12:35:38.820515: Epoch time: 17.82 s +2024-11-22 12:35:39.756335: +2024-11-22 12:35:39.756593: Epoch 4751 +2024-11-22 12:35:39.756706: Current learning rate: 0.00444 +2024-11-22 12:35:58.384828: train_loss -0.7836 +2024-11-22 12:35:58.385053: val_loss -0.7267 +2024-11-22 12:35:58.385131: Pseudo dice [0.8185] +2024-11-22 12:35:58.385212: Epoch time: 18.63 s +2024-11-22 12:35:59.260444: +2024-11-22 12:35:59.260674: Epoch 4752 +2024-11-22 12:35:59.260788: Current learning rate: 0.00444 +2024-11-22 12:36:19.465163: train_loss -0.7888 +2024-11-22 12:36:19.465408: val_loss -0.7301 +2024-11-22 12:36:19.465483: Pseudo dice [0.8002] +2024-11-22 12:36:19.465565: Epoch time: 20.21 s +2024-11-22 12:36:20.476738: +2024-11-22 12:36:20.477055: Epoch 4753 +2024-11-22 12:36:20.477178: Current learning rate: 0.00444 +2024-11-22 12:36:39.431241: train_loss -0.785 +2024-11-22 12:36:39.431466: val_loss -0.723 +2024-11-22 12:36:39.431540: Pseudo dice [0.8131] +2024-11-22 12:36:39.431615: Epoch time: 18.96 s +2024-11-22 12:36:40.320312: +2024-11-22 12:36:40.320513: Epoch 4754 +2024-11-22 12:36:40.320625: Current learning rate: 0.00444 +2024-11-22 12:36:57.676854: train_loss -0.7887 +2024-11-22 12:36:57.677086: val_loss -0.7589 +2024-11-22 12:36:57.677162: Pseudo dice [0.8345] +2024-11-22 12:36:57.677246: Epoch time: 17.36 s +2024-11-22 12:36:58.563326: +2024-11-22 12:36:58.563538: Epoch 4755 +2024-11-22 12:36:58.563646: Current learning rate: 0.00444 +2024-11-22 12:37:17.342462: train_loss -0.7905 +2024-11-22 12:37:17.342790: val_loss -0.7468 +2024-11-22 12:37:17.342869: Pseudo dice [0.8422] +2024-11-22 12:37:17.342955: Epoch time: 18.78 s +2024-11-22 12:37:18.330865: +2024-11-22 12:37:18.331107: Epoch 4756 +2024-11-22 12:37:18.331223: Current learning rate: 0.00444 +2024-11-22 12:37:37.693568: train_loss -0.7804 +2024-11-22 12:37:37.693794: val_loss -0.7346 +2024-11-22 12:37:37.693869: Pseudo dice [0.8206] +2024-11-22 12:37:37.699118: Epoch time: 19.36 s +2024-11-22 12:37:38.715216: +2024-11-22 12:37:38.715514: Epoch 4757 +2024-11-22 12:37:38.715626: Current learning rate: 0.00444 +2024-11-22 12:37:56.724735: train_loss -0.7719 +2024-11-22 12:37:56.724948: val_loss -0.7468 +2024-11-22 12:37:56.725027: Pseudo dice [0.8182] +2024-11-22 12:37:56.725104: Epoch time: 18.01 s +2024-11-22 12:37:57.610885: +2024-11-22 12:37:57.611333: Epoch 4758 +2024-11-22 12:37:57.611473: Current learning rate: 0.00444 +2024-11-22 12:38:16.057933: train_loss -0.7678 +2024-11-22 12:38:16.058537: val_loss -0.7408 +2024-11-22 12:38:16.058633: Pseudo dice [0.8173] +2024-11-22 12:38:16.058726: Epoch time: 18.45 s +2024-11-22 12:38:16.948449: +2024-11-22 12:38:16.948761: Epoch 4759 +2024-11-22 12:38:16.948880: Current learning rate: 0.00443 +2024-11-22 12:38:35.285219: train_loss -0.7842 +2024-11-22 12:38:35.285441: val_loss -0.7462 +2024-11-22 12:38:35.285519: Pseudo dice [0.8152] +2024-11-22 12:38:35.285595: Epoch time: 18.34 s +2024-11-22 12:38:36.166399: +2024-11-22 12:38:36.166673: Epoch 4760 +2024-11-22 12:38:36.166791: Current learning rate: 0.00443 +2024-11-22 12:38:54.813404: train_loss -0.7842 +2024-11-22 12:38:54.813628: val_loss -0.7312 +2024-11-22 12:38:54.813705: Pseudo dice [0.8235] +2024-11-22 12:38:54.813784: Epoch time: 18.65 s +2024-11-22 12:38:55.701779: +2024-11-22 12:38:55.702019: Epoch 4761 +2024-11-22 12:38:55.702132: Current learning rate: 0.00443 +2024-11-22 12:39:13.907300: train_loss -0.7705 +2024-11-22 12:39:13.907552: val_loss -0.7578 +2024-11-22 12:39:13.907629: Pseudo dice [0.8291] +2024-11-22 12:39:13.907714: Epoch time: 18.21 s +2024-11-22 12:39:14.797063: +2024-11-22 12:39:14.797279: Epoch 4762 +2024-11-22 12:39:14.797392: Current learning rate: 0.00443 +2024-11-22 12:39:33.480364: train_loss -0.7757 +2024-11-22 12:39:33.480580: val_loss -0.7362 +2024-11-22 12:39:33.480654: Pseudo dice [0.8392] +2024-11-22 12:39:33.480746: Epoch time: 18.68 s +2024-11-22 12:39:34.366835: +2024-11-22 12:39:34.367169: Epoch 4763 +2024-11-22 12:39:34.367284: Current learning rate: 0.00443 +2024-11-22 12:39:53.346410: train_loss -0.7814 +2024-11-22 12:39:53.346705: val_loss -0.75 +2024-11-22 12:39:53.346784: Pseudo dice [0.8315] +2024-11-22 12:39:53.346869: Epoch time: 18.98 s +2024-11-22 12:39:54.264768: +2024-11-22 12:39:54.265010: Epoch 4764 +2024-11-22 12:39:54.265130: Current learning rate: 0.00443 +2024-11-22 12:40:12.717920: train_loss -0.7732 +2024-11-22 12:40:12.718161: val_loss -0.7426 +2024-11-22 12:40:12.718242: Pseudo dice [0.8126] +2024-11-22 12:40:12.718323: Epoch time: 18.45 s +2024-11-22 12:40:13.643679: +2024-11-22 12:40:13.643885: Epoch 4765 +2024-11-22 12:40:13.643998: Current learning rate: 0.00443 +2024-11-22 12:40:31.434768: train_loss -0.7834 +2024-11-22 12:40:31.435060: val_loss -0.7473 +2024-11-22 12:40:31.435142: Pseudo dice [0.8098] +2024-11-22 12:40:31.435233: Epoch time: 17.79 s +2024-11-22 12:40:32.655075: +2024-11-22 12:40:32.655309: Epoch 4766 +2024-11-22 12:40:32.655427: Current learning rate: 0.00443 +2024-11-22 12:40:51.936017: train_loss -0.7798 +2024-11-22 12:40:51.936239: val_loss -0.7387 +2024-11-22 12:40:51.936314: Pseudo dice [0.8341] +2024-11-22 12:40:51.936392: Epoch time: 19.28 s +2024-11-22 12:40:52.884380: +2024-11-22 12:40:52.884599: Epoch 4767 +2024-11-22 12:40:52.884714: Current learning rate: 0.00442 +2024-11-22 12:41:12.051101: train_loss -0.7858 +2024-11-22 12:41:12.051314: val_loss -0.7513 +2024-11-22 12:41:12.051391: Pseudo dice [0.8261] +2024-11-22 12:41:12.051470: Epoch time: 19.17 s +2024-11-22 12:41:12.948436: +2024-11-22 12:41:12.948709: Epoch 4768 +2024-11-22 12:41:12.948825: Current learning rate: 0.00442 +2024-11-22 12:41:31.607214: train_loss -0.7835 +2024-11-22 12:41:31.607427: val_loss -0.7412 +2024-11-22 12:41:31.607504: Pseudo dice [0.8273] +2024-11-22 12:41:31.607610: Epoch time: 18.66 s +2024-11-22 12:41:32.502398: +2024-11-22 12:41:32.504277: Epoch 4769 +2024-11-22 12:41:32.504393: Current learning rate: 0.00442 +2024-11-22 12:41:50.472314: train_loss -0.7997 +2024-11-22 12:41:50.472550: val_loss -0.7545 +2024-11-22 12:41:50.472645: Pseudo dice [0.836] +2024-11-22 12:41:50.472726: Epoch time: 17.97 s +2024-11-22 12:41:51.357638: +2024-11-22 12:41:51.358145: Epoch 4770 +2024-11-22 12:41:51.358279: Current learning rate: 0.00442 +2024-11-22 12:42:10.194519: train_loss -0.7925 +2024-11-22 12:42:10.197523: val_loss -0.7555 +2024-11-22 12:42:10.197649: Pseudo dice [0.8243] +2024-11-22 12:42:10.197733: Epoch time: 18.84 s +2024-11-22 12:42:11.089512: +2024-11-22 12:42:11.089720: Epoch 4771 +2024-11-22 12:42:11.089835: Current learning rate: 0.00442 +2024-11-22 12:42:29.513719: train_loss -0.7942 +2024-11-22 12:42:29.513927: val_loss -0.7402 +2024-11-22 12:42:29.514019: Pseudo dice [0.8287] +2024-11-22 12:42:29.514153: Epoch time: 18.43 s +2024-11-22 12:42:30.450722: +2024-11-22 12:42:30.450964: Epoch 4772 +2024-11-22 12:42:30.451086: Current learning rate: 0.00442 +2024-11-22 12:42:47.898962: train_loss -0.7864 +2024-11-22 12:42:47.899286: val_loss -0.7399 +2024-11-22 12:42:47.913757: Pseudo dice [0.8225] +2024-11-22 12:42:47.913887: Epoch time: 17.45 s +2024-11-22 12:42:48.811845: +2024-11-22 12:42:48.812070: Epoch 4773 +2024-11-22 12:42:48.812183: Current learning rate: 0.00442 +2024-11-22 12:43:08.063394: train_loss -0.7939 +2024-11-22 12:43:08.063600: val_loss -0.7505 +2024-11-22 12:43:08.063673: Pseudo dice [0.8246] +2024-11-22 12:43:08.063753: Epoch time: 19.25 s +2024-11-22 12:43:08.945103: +2024-11-22 12:43:08.945306: Epoch 4774 +2024-11-22 12:43:08.945416: Current learning rate: 0.00442 +2024-11-22 12:43:26.583705: train_loss -0.7996 +2024-11-22 12:43:26.586115: val_loss -0.7365 +2024-11-22 12:43:26.586200: Pseudo dice [0.8346] +2024-11-22 12:43:26.586279: Epoch time: 17.64 s +2024-11-22 12:43:27.549435: +2024-11-22 12:43:27.549754: Epoch 4775 +2024-11-22 12:43:27.549869: Current learning rate: 0.00441 +2024-11-22 12:43:46.496599: train_loss -0.7809 +2024-11-22 12:43:46.496883: val_loss -0.7516 +2024-11-22 12:43:46.496957: Pseudo dice [0.8316] +2024-11-22 12:43:46.497045: Epoch time: 18.95 s +2024-11-22 12:43:47.440625: +2024-11-22 12:43:47.440823: Epoch 4776 +2024-11-22 12:43:47.440938: Current learning rate: 0.00441 +2024-11-22 12:44:06.444823: train_loss -0.7863 +2024-11-22 12:44:06.445105: val_loss -0.7463 +2024-11-22 12:44:06.445184: Pseudo dice [0.8202] +2024-11-22 12:44:06.445270: Epoch time: 19.0 s +2024-11-22 12:44:07.344519: +2024-11-22 12:44:07.344746: Epoch 4777 +2024-11-22 12:44:07.344863: Current learning rate: 0.00441 +2024-11-22 12:44:26.657256: train_loss -0.7924 +2024-11-22 12:44:26.657525: val_loss -0.7553 +2024-11-22 12:44:26.657602: Pseudo dice [0.8195] +2024-11-22 12:44:26.657679: Epoch time: 19.31 s +2024-11-22 12:44:27.587871: +2024-11-22 12:44:27.588143: Epoch 4778 +2024-11-22 12:44:27.588260: Current learning rate: 0.00441 +2024-11-22 12:44:46.006491: train_loss -0.7982 +2024-11-22 12:44:46.006723: val_loss -0.7637 +2024-11-22 12:44:46.006802: Pseudo dice [0.8158] +2024-11-22 12:44:46.007024: Epoch time: 18.42 s +2024-11-22 12:44:47.008676: +2024-11-22 12:44:47.008889: Epoch 4779 +2024-11-22 12:44:47.009012: Current learning rate: 0.00441 +2024-11-22 12:45:06.454647: train_loss -0.7913 +2024-11-22 12:45:06.454864: val_loss -0.7557 +2024-11-22 12:45:06.454938: Pseudo dice [0.8138] +2024-11-22 12:45:06.455025: Epoch time: 19.45 s +2024-11-22 12:45:07.351660: +2024-11-22 12:45:07.351889: Epoch 4780 +2024-11-22 12:45:07.352055: Current learning rate: 0.00441 +2024-11-22 12:45:25.692172: train_loss -0.7925 +2024-11-22 12:45:25.692401: val_loss -0.7598 +2024-11-22 12:45:25.692481: Pseudo dice [0.8373] +2024-11-22 12:45:25.692562: Epoch time: 18.34 s +2024-11-22 12:45:26.578410: +2024-11-22 12:45:26.578605: Epoch 4781 +2024-11-22 12:45:26.578715: Current learning rate: 0.00441 +2024-11-22 12:45:45.937865: train_loss -0.7898 +2024-11-22 12:45:45.938093: val_loss -0.7435 +2024-11-22 12:45:45.938168: Pseudo dice [0.8471] +2024-11-22 12:45:45.938246: Epoch time: 19.36 s +2024-11-22 12:45:46.823499: +2024-11-22 12:45:46.823918: Epoch 4782 +2024-11-22 12:45:46.824058: Current learning rate: 0.00441 +2024-11-22 12:46:05.812567: train_loss -0.7836 +2024-11-22 12:46:05.813131: val_loss -0.7292 +2024-11-22 12:46:05.813243: Pseudo dice [0.8119] +2024-11-22 12:46:05.813335: Epoch time: 18.98 s +2024-11-22 12:46:06.877062: +2024-11-22 12:46:06.877312: Epoch 4783 +2024-11-22 12:46:06.877430: Current learning rate: 0.0044 +2024-11-22 12:46:25.575706: train_loss -0.7868 +2024-11-22 12:46:25.575933: val_loss -0.7514 +2024-11-22 12:46:25.576013: Pseudo dice [0.8254] +2024-11-22 12:46:25.576094: Epoch time: 18.7 s +2024-11-22 12:46:26.511791: +2024-11-22 12:46:26.512013: Epoch 4784 +2024-11-22 12:46:26.512128: Current learning rate: 0.0044 +2024-11-22 12:46:45.819651: train_loss -0.7862 +2024-11-22 12:46:45.819895: val_loss -0.761 +2024-11-22 12:46:45.819972: Pseudo dice [0.8327] +2024-11-22 12:46:45.820068: Epoch time: 19.31 s +2024-11-22 12:46:46.707983: +2024-11-22 12:46:46.708186: Epoch 4785 +2024-11-22 12:46:46.708296: Current learning rate: 0.0044 +2024-11-22 12:47:05.203557: train_loss -0.7919 +2024-11-22 12:47:05.203781: val_loss -0.753 +2024-11-22 12:47:05.203858: Pseudo dice [0.8415] +2024-11-22 12:47:05.203937: Epoch time: 18.5 s +2024-11-22 12:47:06.080730: +2024-11-22 12:47:06.080934: Epoch 4786 +2024-11-22 12:47:06.081058: Current learning rate: 0.0044 +2024-11-22 12:47:25.187122: train_loss -0.7972 +2024-11-22 12:47:25.187394: val_loss -0.7284 +2024-11-22 12:47:25.187468: Pseudo dice [0.8176] +2024-11-22 12:47:25.187554: Epoch time: 19.11 s +2024-11-22 12:47:26.255112: +2024-11-22 12:47:26.255324: Epoch 4787 +2024-11-22 12:47:26.255441: Current learning rate: 0.0044 +2024-11-22 12:47:45.337879: train_loss -0.7952 +2024-11-22 12:47:45.338121: val_loss -0.7601 +2024-11-22 12:47:45.338204: Pseudo dice [0.8328] +2024-11-22 12:47:45.338286: Epoch time: 19.08 s +2024-11-22 12:47:46.451981: +2024-11-22 12:47:46.452197: Epoch 4788 +2024-11-22 12:47:46.452315: Current learning rate: 0.0044 +2024-11-22 12:48:04.976290: train_loss -0.7912 +2024-11-22 12:48:04.976506: val_loss -0.7463 +2024-11-22 12:48:04.976582: Pseudo dice [0.8225] +2024-11-22 12:48:04.976659: Epoch time: 18.53 s +2024-11-22 12:48:05.859631: +2024-11-22 12:48:05.859951: Epoch 4789 +2024-11-22 12:48:05.860072: Current learning rate: 0.0044 +2024-11-22 12:48:23.372236: train_loss -0.8 +2024-11-22 12:48:23.372445: val_loss -0.7565 +2024-11-22 12:48:23.372524: Pseudo dice [0.8372] +2024-11-22 12:48:23.372600: Epoch time: 17.51 s +2024-11-22 12:48:24.272089: +2024-11-22 12:48:24.272304: Epoch 4790 +2024-11-22 12:48:24.272415: Current learning rate: 0.0044 +2024-11-22 12:48:42.045584: train_loss -0.807 +2024-11-22 12:48:42.045829: val_loss -0.7638 +2024-11-22 12:48:42.045905: Pseudo dice [0.8222] +2024-11-22 12:48:42.046005: Epoch time: 17.77 s +2024-11-22 12:48:42.962576: +2024-11-22 12:48:42.962778: Epoch 4791 +2024-11-22 12:48:42.962886: Current learning rate: 0.00439 +2024-11-22 12:49:01.842469: train_loss -0.8036 +2024-11-22 12:49:01.842689: val_loss -0.7491 +2024-11-22 12:49:01.842761: Pseudo dice [0.8237] +2024-11-22 12:49:01.842839: Epoch time: 18.88 s +2024-11-22 12:49:02.721898: +2024-11-22 12:49:02.722112: Epoch 4792 +2024-11-22 12:49:02.722227: Current learning rate: 0.00439 +2024-11-22 12:49:21.548127: train_loss -0.8061 +2024-11-22 12:49:21.548350: val_loss -0.7434 +2024-11-22 12:49:21.548425: Pseudo dice [0.8176] +2024-11-22 12:49:21.548500: Epoch time: 18.83 s +2024-11-22 12:49:22.437708: +2024-11-22 12:49:22.438164: Epoch 4793 +2024-11-22 12:49:22.438301: Current learning rate: 0.00439 +2024-11-22 12:49:40.926219: train_loss -0.798 +2024-11-22 12:49:40.927649: val_loss -0.75 +2024-11-22 12:49:40.927778: Pseudo dice [0.8343] +2024-11-22 12:49:40.927872: Epoch time: 18.49 s +2024-11-22 12:49:41.822494: +2024-11-22 12:49:41.822911: Epoch 4794 +2024-11-22 12:49:41.823047: Current learning rate: 0.00439 +2024-11-22 12:50:00.235257: train_loss -0.8014 +2024-11-22 12:50:00.235886: val_loss -0.7456 +2024-11-22 12:50:00.235988: Pseudo dice [0.8464] +2024-11-22 12:50:00.236073: Epoch time: 18.41 s +2024-11-22 12:50:01.126194: +2024-11-22 12:50:01.126414: Epoch 4795 +2024-11-22 12:50:01.126528: Current learning rate: 0.00439 +2024-11-22 12:50:20.766647: train_loss -0.7988 +2024-11-22 12:50:20.766872: val_loss -0.7482 +2024-11-22 12:50:20.766955: Pseudo dice [0.8324] +2024-11-22 12:50:20.767038: Epoch time: 19.64 s +2024-11-22 12:50:21.645025: +2024-11-22 12:50:21.645265: Epoch 4796 +2024-11-22 12:50:21.645383: Current learning rate: 0.00439 +2024-11-22 12:50:41.571123: train_loss -0.7931 +2024-11-22 12:50:41.571372: val_loss -0.7565 +2024-11-22 12:50:41.571451: Pseudo dice [0.8301] +2024-11-22 12:50:41.571537: Epoch time: 19.93 s +2024-11-22 12:50:42.532389: +2024-11-22 12:50:42.532610: Epoch 4797 +2024-11-22 12:50:42.532727: Current learning rate: 0.00439 +2024-11-22 12:51:01.738844: train_loss -0.7924 +2024-11-22 12:51:01.739064: val_loss -0.7638 +2024-11-22 12:51:01.739138: Pseudo dice [0.8323] +2024-11-22 12:51:01.739215: Epoch time: 19.21 s +2024-11-22 12:51:02.621780: +2024-11-22 12:51:02.622680: Epoch 4798 +2024-11-22 12:51:02.622796: Current learning rate: 0.00439 +2024-11-22 12:51:21.558749: train_loss -0.8016 +2024-11-22 12:51:21.558971: val_loss -0.7583 +2024-11-22 12:51:21.559081: Pseudo dice [0.8403] +2024-11-22 12:51:21.559159: Epoch time: 18.94 s +2024-11-22 12:51:22.446265: +2024-11-22 12:51:22.446490: Epoch 4799 +2024-11-22 12:51:22.446607: Current learning rate: 0.00439 +2024-11-22 12:51:40.465850: train_loss -0.8036 +2024-11-22 12:51:40.466084: val_loss -0.7268 +2024-11-22 12:51:40.468337: Pseudo dice [0.8278] +2024-11-22 12:51:40.468469: Epoch time: 18.02 s +2024-11-22 12:51:41.674091: +2024-11-22 12:51:41.674315: Epoch 4800 +2024-11-22 12:51:41.674429: Current learning rate: 0.00438 +2024-11-22 12:52:00.038233: train_loss -0.7994 +2024-11-22 12:52:00.038448: val_loss -0.746 +2024-11-22 12:52:00.038525: Pseudo dice [0.8129] +2024-11-22 12:52:00.038604: Epoch time: 18.36 s +2024-11-22 12:52:00.966011: +2024-11-22 12:52:00.966228: Epoch 4801 +2024-11-22 12:52:00.966344: Current learning rate: 0.00438 +2024-11-22 12:52:18.607274: train_loss -0.792 +2024-11-22 12:52:18.607518: val_loss -0.7381 +2024-11-22 12:52:18.607595: Pseudo dice [0.8115] +2024-11-22 12:52:18.607683: Epoch time: 17.64 s +2024-11-22 12:52:19.491090: +2024-11-22 12:52:19.491312: Epoch 4802 +2024-11-22 12:52:19.491422: Current learning rate: 0.00438 +2024-11-22 12:52:38.106575: train_loss -0.803 +2024-11-22 12:52:38.106841: val_loss -0.7517 +2024-11-22 12:52:38.106916: Pseudo dice [0.8142] +2024-11-22 12:52:38.106995: Epoch time: 18.62 s +2024-11-22 12:52:38.995118: +2024-11-22 12:52:38.995330: Epoch 4803 +2024-11-22 12:52:38.995443: Current learning rate: 0.00438 +2024-11-22 12:52:57.585563: train_loss -0.8 +2024-11-22 12:52:57.585779: val_loss -0.7284 +2024-11-22 12:52:57.585859: Pseudo dice [0.8224] +2024-11-22 12:52:57.585999: Epoch time: 18.59 s +2024-11-22 12:52:58.468632: +2024-11-22 12:52:58.468822: Epoch 4804 +2024-11-22 12:52:58.468936: Current learning rate: 0.00438 +2024-11-22 12:53:17.329511: train_loss -0.798 +2024-11-22 12:53:17.329793: val_loss -0.7497 +2024-11-22 12:53:17.329871: Pseudo dice [0.826] +2024-11-22 12:53:17.330128: Epoch time: 18.86 s +2024-11-22 12:53:18.217039: +2024-11-22 12:53:18.217248: Epoch 4805 +2024-11-22 12:53:18.217355: Current learning rate: 0.00438 +2024-11-22 12:53:35.395989: train_loss -0.8031 +2024-11-22 12:53:35.396276: val_loss -0.739 +2024-11-22 12:53:35.396353: Pseudo dice [0.8352] +2024-11-22 12:53:35.396431: Epoch time: 17.18 s +2024-11-22 12:53:36.695685: +2024-11-22 12:53:36.695897: Epoch 4806 +2024-11-22 12:53:36.696015: Current learning rate: 0.00438 +2024-11-22 12:53:54.537722: train_loss -0.7984 +2024-11-22 12:53:54.537944: val_loss -0.7698 +2024-11-22 12:53:54.538028: Pseudo dice [0.8424] +2024-11-22 12:53:54.538107: Epoch time: 17.84 s +2024-11-22 12:53:55.404387: +2024-11-22 12:53:55.404597: Epoch 4807 +2024-11-22 12:53:55.404713: Current learning rate: 0.00438 +2024-11-22 12:54:14.868844: train_loss -0.802 +2024-11-22 12:54:14.869090: val_loss -0.7452 +2024-11-22 12:54:14.869165: Pseudo dice [0.8321] +2024-11-22 12:54:14.869251: Epoch time: 19.47 s +2024-11-22 12:54:15.753664: +2024-11-22 12:54:15.753880: Epoch 4808 +2024-11-22 12:54:15.754002: Current learning rate: 0.00437 +2024-11-22 12:54:33.957894: train_loss -0.7986 +2024-11-22 12:54:33.958135: val_loss -0.7481 +2024-11-22 12:54:33.958214: Pseudo dice [0.8012] +2024-11-22 12:54:33.958293: Epoch time: 18.21 s +2024-11-22 12:54:34.842535: +2024-11-22 12:54:34.842770: Epoch 4809 +2024-11-22 12:54:34.842884: Current learning rate: 0.00437 +2024-11-22 12:54:53.208315: train_loss -0.7989 +2024-11-22 12:54:53.208595: val_loss -0.752 +2024-11-22 12:54:53.208674: Pseudo dice [0.8378] +2024-11-22 12:54:53.208756: Epoch time: 18.37 s +2024-11-22 12:54:54.104108: +2024-11-22 12:54:54.104299: Epoch 4810 +2024-11-22 12:54:54.104407: Current learning rate: 0.00437 +2024-11-22 12:55:13.528797: train_loss -0.8052 +2024-11-22 12:55:13.529084: val_loss -0.7612 +2024-11-22 12:55:13.529173: Pseudo dice [0.8418] +2024-11-22 12:55:13.529910: Epoch time: 19.43 s +2024-11-22 12:55:14.437453: +2024-11-22 12:55:14.437646: Epoch 4811 +2024-11-22 12:55:14.437761: Current learning rate: 0.00437 +2024-11-22 12:55:32.192397: train_loss -0.7991 +2024-11-22 12:55:32.192650: val_loss -0.7591 +2024-11-22 12:55:32.192736: Pseudo dice [0.8344] +2024-11-22 12:55:32.192823: Epoch time: 17.76 s +2024-11-22 12:55:33.083046: +2024-11-22 12:55:33.083261: Epoch 4812 +2024-11-22 12:55:33.083380: Current learning rate: 0.00437 +2024-11-22 12:55:51.822566: train_loss -0.7997 +2024-11-22 12:55:51.822838: val_loss -0.7534 +2024-11-22 12:55:51.822916: Pseudo dice [0.8336] +2024-11-22 12:55:51.822996: Epoch time: 18.74 s +2024-11-22 12:55:52.691563: +2024-11-22 12:55:52.691787: Epoch 4813 +2024-11-22 12:55:52.691896: Current learning rate: 0.00437 +2024-11-22 12:56:10.210648: train_loss -0.7966 +2024-11-22 12:56:10.210869: val_loss -0.7617 +2024-11-22 12:56:10.210942: Pseudo dice [0.8307] +2024-11-22 12:56:10.211025: Epoch time: 17.52 s +2024-11-22 12:56:11.104744: +2024-11-22 12:56:11.104974: Epoch 4814 +2024-11-22 12:56:11.105088: Current learning rate: 0.00437 +2024-11-22 12:56:28.403418: train_loss -0.7988 +2024-11-22 12:56:28.403618: val_loss -0.7353 +2024-11-22 12:56:28.403695: Pseudo dice [0.8187] +2024-11-22 12:56:28.403775: Epoch time: 17.3 s +2024-11-22 12:56:29.290157: +2024-11-22 12:56:29.290362: Epoch 4815 +2024-11-22 12:56:29.290476: Current learning rate: 0.00437 +2024-11-22 12:56:47.960469: train_loss -0.8089 +2024-11-22 12:56:47.960724: val_loss -0.7759 +2024-11-22 12:56:47.960801: Pseudo dice [0.8429] +2024-11-22 12:56:47.960883: Epoch time: 18.67 s +2024-11-22 12:56:48.887857: +2024-11-22 12:56:48.888058: Epoch 4816 +2024-11-22 12:56:48.888169: Current learning rate: 0.00436 +2024-11-22 12:57:08.390224: train_loss -0.8 +2024-11-22 12:57:08.390441: val_loss -0.7328 +2024-11-22 12:57:08.390517: Pseudo dice [0.8288] +2024-11-22 12:57:08.390594: Epoch time: 19.5 s +2024-11-22 12:57:09.273645: +2024-11-22 12:57:09.274060: Epoch 4817 +2024-11-22 12:57:09.274199: Current learning rate: 0.00436 +2024-11-22 12:57:28.505565: train_loss -0.7948 +2024-11-22 12:57:28.505776: val_loss -0.7459 +2024-11-22 12:57:28.505849: Pseudo dice [0.822] +2024-11-22 12:57:28.505930: Epoch time: 19.23 s +2024-11-22 12:57:29.871649: +2024-11-22 12:57:29.871855: Epoch 4818 +2024-11-22 12:57:29.871971: Current learning rate: 0.00436 +2024-11-22 12:57:48.114691: train_loss -0.7802 +2024-11-22 12:57:48.115074: val_loss -0.7351 +2024-11-22 12:57:48.115154: Pseudo dice [0.8235] +2024-11-22 12:57:48.115239: Epoch time: 18.24 s +2024-11-22 12:57:49.003384: +2024-11-22 12:57:49.003607: Epoch 4819 +2024-11-22 12:57:49.003719: Current learning rate: 0.00436 +2024-11-22 12:58:08.781357: train_loss -0.7923 +2024-11-22 12:58:08.781637: val_loss -0.7621 +2024-11-22 12:58:08.781715: Pseudo dice [0.8257] +2024-11-22 12:58:08.781798: Epoch time: 19.78 s +2024-11-22 12:58:09.673315: +2024-11-22 12:58:09.673527: Epoch 4820 +2024-11-22 12:58:09.673641: Current learning rate: 0.00436 +2024-11-22 12:58:28.442457: train_loss -0.8008 +2024-11-22 12:58:28.442671: val_loss -0.7574 +2024-11-22 12:58:28.442748: Pseudo dice [0.8327] +2024-11-22 12:58:28.442826: Epoch time: 18.77 s +2024-11-22 12:58:29.333930: +2024-11-22 12:58:29.334135: Epoch 4821 +2024-11-22 12:58:29.334252: Current learning rate: 0.00436 +2024-11-22 12:58:48.480959: train_loss -0.7997 +2024-11-22 12:58:48.481173: val_loss -0.756 +2024-11-22 12:58:48.481247: Pseudo dice [0.8518] +2024-11-22 12:58:48.481326: Epoch time: 19.15 s +2024-11-22 12:58:49.475202: +2024-11-22 12:58:49.475398: Epoch 4822 +2024-11-22 12:58:49.475514: Current learning rate: 0.00436 +2024-11-22 12:59:08.736554: train_loss -0.7902 +2024-11-22 12:59:08.736923: val_loss -0.7586 +2024-11-22 12:59:08.737015: Pseudo dice [0.82] +2024-11-22 12:59:08.737096: Epoch time: 19.26 s +2024-11-22 12:59:09.614637: +2024-11-22 12:59:09.614822: Epoch 4823 +2024-11-22 12:59:09.614932: Current learning rate: 0.00436 +2024-11-22 12:59:27.670943: train_loss -0.8041 +2024-11-22 12:59:27.686760: val_loss -0.7565 +2024-11-22 12:59:27.686910: Pseudo dice [0.815] +2024-11-22 12:59:27.687024: Epoch time: 18.06 s +2024-11-22 12:59:28.615076: +2024-11-22 12:59:28.615290: Epoch 4824 +2024-11-22 12:59:28.615405: Current learning rate: 0.00435 +2024-11-22 12:59:48.716703: train_loss -0.7957 +2024-11-22 12:59:48.716914: val_loss -0.7522 +2024-11-22 12:59:48.716989: Pseudo dice [0.8322] +2024-11-22 12:59:48.717070: Epoch time: 20.1 s +2024-11-22 12:59:49.593136: +2024-11-22 12:59:49.593347: Epoch 4825 +2024-11-22 12:59:49.593467: Current learning rate: 0.00435 +2024-11-22 13:00:08.763188: train_loss -0.8028 +2024-11-22 13:00:08.763433: val_loss -0.7556 +2024-11-22 13:00:08.763508: Pseudo dice [0.8323] +2024-11-22 13:00:08.763591: Epoch time: 19.17 s +2024-11-22 13:00:09.639347: +2024-11-22 13:00:09.639530: Epoch 4826 +2024-11-22 13:00:09.639646: Current learning rate: 0.00435 +2024-11-22 13:00:27.785347: train_loss -0.7998 +2024-11-22 13:00:27.785851: val_loss -0.773 +2024-11-22 13:00:27.785928: Pseudo dice [0.8297] +2024-11-22 13:00:27.786016: Epoch time: 18.15 s +2024-11-22 13:00:28.669843: +2024-11-22 13:00:28.670051: Epoch 4827 +2024-11-22 13:00:28.670162: Current learning rate: 0.00435 +2024-11-22 13:00:47.379113: train_loss -0.7942 +2024-11-22 13:00:47.381501: val_loss -0.7661 +2024-11-22 13:00:47.381580: Pseudo dice [0.8413] +2024-11-22 13:00:47.381657: Epoch time: 18.71 s +2024-11-22 13:00:48.302770: +2024-11-22 13:00:48.302995: Epoch 4828 +2024-11-22 13:00:48.303103: Current learning rate: 0.00435 +2024-11-22 13:01:08.946150: train_loss -0.7966 +2024-11-22 13:01:08.946352: val_loss -0.7459 +2024-11-22 13:01:08.946432: Pseudo dice [0.82] +2024-11-22 13:01:08.946512: Epoch time: 20.64 s +2024-11-22 13:01:09.827011: +2024-11-22 13:01:09.827246: Epoch 4829 +2024-11-22 13:01:09.827356: Current learning rate: 0.00435 +2024-11-22 13:01:28.784784: train_loss -0.7883 +2024-11-22 13:01:28.785024: val_loss -0.7647 +2024-11-22 13:01:28.785101: Pseudo dice [0.8462] +2024-11-22 13:01:28.785182: Epoch time: 18.96 s +2024-11-22 13:01:29.981905: +2024-11-22 13:01:29.982184: Epoch 4830 +2024-11-22 13:01:29.982296: Current learning rate: 0.00435 +2024-11-22 13:01:48.654961: train_loss -0.7936 +2024-11-22 13:01:48.656758: val_loss -0.7501 +2024-11-22 13:01:48.656876: Pseudo dice [0.8233] +2024-11-22 13:01:48.657039: Epoch time: 18.67 s +2024-11-22 13:01:49.569625: +2024-11-22 13:01:49.569844: Epoch 4831 +2024-11-22 13:01:49.569953: Current learning rate: 0.00435 +2024-11-22 13:02:08.120319: train_loss -0.802 +2024-11-22 13:02:08.120529: val_loss -0.7661 +2024-11-22 13:02:08.120602: Pseudo dice [0.8421] +2024-11-22 13:02:08.120677: Epoch time: 18.55 s +2024-11-22 13:02:09.009931: +2024-11-22 13:02:09.010155: Epoch 4832 +2024-11-22 13:02:09.010268: Current learning rate: 0.00434 +2024-11-22 13:02:29.206337: train_loss -0.7993 +2024-11-22 13:02:29.206610: val_loss -0.7484 +2024-11-22 13:02:29.206686: Pseudo dice [0.8154] +2024-11-22 13:02:29.206769: Epoch time: 20.2 s +2024-11-22 13:02:30.097152: +2024-11-22 13:02:30.097352: Epoch 4833 +2024-11-22 13:02:30.097466: Current learning rate: 0.00434 +2024-11-22 13:02:48.950143: train_loss -0.7955 +2024-11-22 13:02:48.950368: val_loss -0.7552 +2024-11-22 13:02:48.950444: Pseudo dice [0.8208] +2024-11-22 13:02:48.950522: Epoch time: 18.85 s +2024-11-22 13:02:49.835947: +2024-11-22 13:02:49.836197: Epoch 4834 +2024-11-22 13:02:49.836309: Current learning rate: 0.00434 +2024-11-22 13:03:07.777539: train_loss -0.7746 +2024-11-22 13:03:07.777784: val_loss -0.7451 +2024-11-22 13:03:07.777866: Pseudo dice [0.8147] +2024-11-22 13:03:07.777980: Epoch time: 17.94 s +2024-11-22 13:03:08.671617: +2024-11-22 13:03:08.671830: Epoch 4835 +2024-11-22 13:03:08.671944: Current learning rate: 0.00434 +2024-11-22 13:03:27.687791: train_loss -0.783 +2024-11-22 13:03:27.688072: val_loss -0.7485 +2024-11-22 13:03:27.688149: Pseudo dice [0.829] +2024-11-22 13:03:27.688226: Epoch time: 19.02 s +2024-11-22 13:03:28.619641: +2024-11-22 13:03:28.619894: Epoch 4836 +2024-11-22 13:03:28.636819: Current learning rate: 0.00434 +2024-11-22 13:03:46.778266: train_loss -0.7895 +2024-11-22 13:03:46.778505: val_loss -0.7309 +2024-11-22 13:03:46.778586: Pseudo dice [0.8231] +2024-11-22 13:03:46.778673: Epoch time: 18.16 s +2024-11-22 13:03:47.660317: +2024-11-22 13:03:47.660525: Epoch 4837 +2024-11-22 13:03:47.660637: Current learning rate: 0.00434 +2024-11-22 13:04:06.135243: train_loss -0.7913 +2024-11-22 13:04:06.135447: val_loss -0.762 +2024-11-22 13:04:06.135521: Pseudo dice [0.836] +2024-11-22 13:04:06.135597: Epoch time: 18.48 s +2024-11-22 13:04:07.012126: +2024-11-22 13:04:07.012323: Epoch 4838 +2024-11-22 13:04:07.012439: Current learning rate: 0.00434 +2024-11-22 13:04:24.945653: train_loss -0.7885 +2024-11-22 13:04:24.945874: val_loss -0.7269 +2024-11-22 13:04:24.945951: Pseudo dice [0.8264] +2024-11-22 13:04:24.946035: Epoch time: 17.93 s +2024-11-22 13:04:25.832878: +2024-11-22 13:04:25.833121: Epoch 4839 +2024-11-22 13:04:25.833236: Current learning rate: 0.00434 +2024-11-22 13:04:44.526890: train_loss -0.7893 +2024-11-22 13:04:44.527168: val_loss -0.733 +2024-11-22 13:04:44.527246: Pseudo dice [0.8352] +2024-11-22 13:04:44.527329: Epoch time: 18.69 s +2024-11-22 13:04:45.417586: +2024-11-22 13:04:45.417815: Epoch 4840 +2024-11-22 13:04:45.417925: Current learning rate: 0.00433 +2024-11-22 13:05:04.189616: train_loss -0.7914 +2024-11-22 13:05:04.189842: val_loss -0.7414 +2024-11-22 13:05:04.189914: Pseudo dice [0.8307] +2024-11-22 13:05:04.190000: Epoch time: 18.77 s +2024-11-22 13:05:05.130780: +2024-11-22 13:05:05.130968: Epoch 4841 +2024-11-22 13:05:05.131088: Current learning rate: 0.00433 +2024-11-22 13:05:24.155583: train_loss -0.79 +2024-11-22 13:05:24.155797: val_loss -0.7515 +2024-11-22 13:05:24.155870: Pseudo dice [0.8331] +2024-11-22 13:05:24.155945: Epoch time: 19.03 s +2024-11-22 13:05:25.449750: +2024-11-22 13:05:25.449983: Epoch 4842 +2024-11-22 13:05:25.450099: Current learning rate: 0.00433 +2024-11-22 13:05:43.574047: train_loss -0.8048 +2024-11-22 13:05:43.574356: val_loss -0.7441 +2024-11-22 13:05:43.574446: Pseudo dice [0.8364] +2024-11-22 13:05:43.574527: Epoch time: 18.13 s +2024-11-22 13:05:44.467164: +2024-11-22 13:05:44.467393: Epoch 4843 +2024-11-22 13:05:44.467509: Current learning rate: 0.00433 +2024-11-22 13:06:03.192256: train_loss -0.8011 +2024-11-22 13:06:03.192494: val_loss -0.7435 +2024-11-22 13:06:03.192566: Pseudo dice [0.8261] +2024-11-22 13:06:03.192647: Epoch time: 18.73 s +2024-11-22 13:06:04.171421: +2024-11-22 13:06:04.171638: Epoch 4844 +2024-11-22 13:06:04.171755: Current learning rate: 0.00433 +2024-11-22 13:06:22.377389: train_loss -0.8009 +2024-11-22 13:06:22.377623: val_loss -0.7451 +2024-11-22 13:06:22.377694: Pseudo dice [0.8418] +2024-11-22 13:06:22.377773: Epoch time: 18.21 s +2024-11-22 13:06:23.273594: +2024-11-22 13:06:23.273831: Epoch 4845 +2024-11-22 13:06:23.273944: Current learning rate: 0.00433 +2024-11-22 13:06:41.997028: train_loss -0.7967 +2024-11-22 13:06:41.997246: val_loss -0.7533 +2024-11-22 13:06:41.997320: Pseudo dice [0.8479] +2024-11-22 13:06:41.997396: Epoch time: 18.72 s +2024-11-22 13:06:42.889879: +2024-11-22 13:06:42.890205: Epoch 4846 +2024-11-22 13:06:42.890316: Current learning rate: 0.00433 +2024-11-22 13:07:00.910262: train_loss -0.7985 +2024-11-22 13:07:00.910475: val_loss -0.7603 +2024-11-22 13:07:00.910548: Pseudo dice [0.8147] +2024-11-22 13:07:00.910628: Epoch time: 18.02 s +2024-11-22 13:07:01.792781: +2024-11-22 13:07:01.792977: Epoch 4847 +2024-11-22 13:07:01.793095: Current learning rate: 0.00433 +2024-11-22 13:07:21.177477: train_loss -0.7946 +2024-11-22 13:07:21.177717: val_loss -0.7516 +2024-11-22 13:07:21.177796: Pseudo dice [0.8204] +2024-11-22 13:07:21.177883: Epoch time: 19.39 s +2024-11-22 13:07:22.059709: +2024-11-22 13:07:22.059933: Epoch 4848 +2024-11-22 13:07:22.060060: Current learning rate: 0.00432 +2024-11-22 13:07:40.931089: train_loss -0.7979 +2024-11-22 13:07:40.931296: val_loss -0.7715 +2024-11-22 13:07:40.931371: Pseudo dice [0.8354] +2024-11-22 13:07:40.931447: Epoch time: 18.87 s +2024-11-22 13:07:41.852510: +2024-11-22 13:07:41.852700: Epoch 4849 +2024-11-22 13:07:41.852812: Current learning rate: 0.00432 +2024-11-22 13:08:01.602090: train_loss -0.8018 +2024-11-22 13:08:01.602320: val_loss -0.7589 +2024-11-22 13:08:01.602480: Pseudo dice [0.8327] +2024-11-22 13:08:01.602559: Epoch time: 19.75 s +2024-11-22 13:08:02.756083: +2024-11-22 13:08:02.756281: Epoch 4850 +2024-11-22 13:08:02.756394: Current learning rate: 0.00432 +2024-11-22 13:08:22.234641: train_loss -0.7945 +2024-11-22 13:08:22.237937: val_loss -0.7627 +2024-11-22 13:08:22.238084: Pseudo dice [0.8208] +2024-11-22 13:08:22.238180: Epoch time: 19.48 s +2024-11-22 13:08:23.141165: +2024-11-22 13:08:23.141377: Epoch 4851 +2024-11-22 13:08:23.141494: Current learning rate: 0.00432 +2024-11-22 13:08:41.687381: train_loss -0.7984 +2024-11-22 13:08:41.687592: val_loss -0.7473 +2024-11-22 13:08:41.687667: Pseudo dice [0.8233] +2024-11-22 13:08:41.687743: Epoch time: 18.55 s +2024-11-22 13:08:42.573585: +2024-11-22 13:08:42.573827: Epoch 4852 +2024-11-22 13:08:42.573940: Current learning rate: 0.00432 +2024-11-22 13:09:01.000347: train_loss -0.7979 +2024-11-22 13:09:01.000567: val_loss -0.7576 +2024-11-22 13:09:01.000641: Pseudo dice [0.8343] +2024-11-22 13:09:01.000718: Epoch time: 18.43 s +2024-11-22 13:09:01.883418: +2024-11-22 13:09:01.883685: Epoch 4853 +2024-11-22 13:09:01.883797: Current learning rate: 0.00432 +2024-11-22 13:09:21.260752: train_loss -0.7998 +2024-11-22 13:09:21.260972: val_loss -0.7263 +2024-11-22 13:09:21.261060: Pseudo dice [0.8103] +2024-11-22 13:09:21.261139: Epoch time: 19.38 s +2024-11-22 13:09:22.565605: +2024-11-22 13:09:22.565840: Epoch 4854 +2024-11-22 13:09:22.565955: Current learning rate: 0.00432 +2024-11-22 13:09:41.738469: train_loss -0.8016 +2024-11-22 13:09:41.738748: val_loss -0.7496 +2024-11-22 13:09:41.738824: Pseudo dice [0.8283] +2024-11-22 13:09:41.738903: Epoch time: 19.17 s +2024-11-22 13:09:42.630263: +2024-11-22 13:09:42.630485: Epoch 4855 +2024-11-22 13:09:42.630600: Current learning rate: 0.00432 +2024-11-22 13:10:01.565317: train_loss -0.793 +2024-11-22 13:10:01.565530: val_loss -0.7344 +2024-11-22 13:10:01.565603: Pseudo dice [0.8066] +2024-11-22 13:10:01.565678: Epoch time: 18.94 s +2024-11-22 13:10:02.444837: +2024-11-22 13:10:02.445045: Epoch 4856 +2024-11-22 13:10:02.445158: Current learning rate: 0.00431 +2024-11-22 13:10:21.348795: train_loss -0.7974 +2024-11-22 13:10:21.349045: val_loss -0.7573 +2024-11-22 13:10:21.349217: Pseudo dice [0.8214] +2024-11-22 13:10:21.349309: Epoch time: 18.9 s +2024-11-22 13:10:22.309272: +2024-11-22 13:10:22.309498: Epoch 4857 +2024-11-22 13:10:22.309640: Current learning rate: 0.00431 +2024-11-22 13:10:41.374129: train_loss -0.8037 +2024-11-22 13:10:41.374426: val_loss -0.7383 +2024-11-22 13:10:41.374503: Pseudo dice [0.8284] +2024-11-22 13:10:41.374585: Epoch time: 19.07 s +2024-11-22 13:10:42.263927: +2024-11-22 13:10:42.264166: Epoch 4858 +2024-11-22 13:10:42.264284: Current learning rate: 0.00431 +2024-11-22 13:11:00.915525: train_loss -0.8081 +2024-11-22 13:11:00.915743: val_loss -0.7565 +2024-11-22 13:11:00.915818: Pseudo dice [0.8354] +2024-11-22 13:11:00.915896: Epoch time: 18.65 s +2024-11-22 13:11:01.800223: +2024-11-22 13:11:01.800425: Epoch 4859 +2024-11-22 13:11:01.800535: Current learning rate: 0.00431 +2024-11-22 13:11:20.934489: train_loss -0.7923 +2024-11-22 13:11:20.934713: val_loss -0.7357 +2024-11-22 13:11:20.934789: Pseudo dice [0.8224] +2024-11-22 13:11:20.934870: Epoch time: 19.14 s +2024-11-22 13:11:21.848408: +2024-11-22 13:11:21.848599: Epoch 4860 +2024-11-22 13:11:21.848705: Current learning rate: 0.00431 +2024-11-22 13:11:40.207505: train_loss -0.7992 +2024-11-22 13:11:40.207752: val_loss -0.754 +2024-11-22 13:11:40.207830: Pseudo dice [0.8425] +2024-11-22 13:11:40.207919: Epoch time: 18.36 s +2024-11-22 13:11:41.089696: +2024-11-22 13:11:41.089888: Epoch 4861 +2024-11-22 13:11:41.089998: Current learning rate: 0.00431 +2024-11-22 13:11:58.980479: train_loss -0.796 +2024-11-22 13:11:58.980687: val_loss -0.7473 +2024-11-22 13:11:58.983082: Pseudo dice [0.8402] +2024-11-22 13:11:58.983206: Epoch time: 17.89 s +2024-11-22 13:11:59.878712: +2024-11-22 13:11:59.878995: Epoch 4862 +2024-11-22 13:11:59.879110: Current learning rate: 0.00431 +2024-11-22 13:12:18.435361: train_loss -0.7919 +2024-11-22 13:12:18.435579: val_loss -0.7468 +2024-11-22 13:12:18.435660: Pseudo dice [0.8251] +2024-11-22 13:12:18.435736: Epoch time: 18.56 s +2024-11-22 13:12:19.415906: +2024-11-22 13:12:19.416119: Epoch 4863 +2024-11-22 13:12:19.416231: Current learning rate: 0.00431 +2024-11-22 13:12:37.146758: train_loss -0.7933 +2024-11-22 13:12:37.146977: val_loss -0.7499 +2024-11-22 13:12:37.147092: Pseudo dice [0.8333] +2024-11-22 13:12:37.147175: Epoch time: 17.73 s +2024-11-22 13:12:38.034269: +2024-11-22 13:12:38.034489: Epoch 4864 +2024-11-22 13:12:38.034604: Current learning rate: 0.0043 +2024-11-22 13:12:57.154231: train_loss -0.7934 +2024-11-22 13:12:57.154476: val_loss -0.7341 +2024-11-22 13:12:57.154553: Pseudo dice [0.8409] +2024-11-22 13:12:57.154636: Epoch time: 19.12 s +2024-11-22 13:12:58.137009: +2024-11-22 13:12:58.137315: Epoch 4865 +2024-11-22 13:12:58.137439: Current learning rate: 0.0043 +2024-11-22 13:13:17.159596: train_loss -0.7863 +2024-11-22 13:13:17.159802: val_loss -0.7519 +2024-11-22 13:13:17.159877: Pseudo dice [0.8391] +2024-11-22 13:13:17.159951: Epoch time: 19.02 s +2024-11-22 13:13:18.430071: +2024-11-22 13:13:18.430309: Epoch 4866 +2024-11-22 13:13:18.430422: Current learning rate: 0.0043 +2024-11-22 13:13:36.876187: train_loss -0.7924 +2024-11-22 13:13:36.876405: val_loss -0.7346 +2024-11-22 13:13:36.876482: Pseudo dice [0.84] +2024-11-22 13:13:36.876557: Epoch time: 18.45 s +2024-11-22 13:13:37.754932: +2024-11-22 13:13:37.755146: Epoch 4867 +2024-11-22 13:13:37.755259: Current learning rate: 0.0043 +2024-11-22 13:13:56.597885: train_loss -0.7944 +2024-11-22 13:13:56.598131: val_loss -0.764 +2024-11-22 13:13:56.598216: Pseudo dice [0.8399] +2024-11-22 13:13:56.598306: Epoch time: 18.84 s +2024-11-22 13:13:57.490544: +2024-11-22 13:13:57.490797: Epoch 4868 +2024-11-22 13:13:57.490908: Current learning rate: 0.0043 +2024-11-22 13:14:15.656471: train_loss -0.7999 +2024-11-22 13:14:15.656740: val_loss -0.7483 +2024-11-22 13:14:15.656817: Pseudo dice [0.8588] +2024-11-22 13:14:15.656894: Epoch time: 18.17 s +2024-11-22 13:14:15.656955: Yayy! New best EMA pseudo Dice: 0.8354 +2024-11-22 13:14:16.843566: +2024-11-22 13:14:16.843848: Epoch 4869 +2024-11-22 13:14:16.843960: Current learning rate: 0.0043 +2024-11-22 13:14:34.818634: train_loss -0.8035 +2024-11-22 13:14:34.818846: val_loss -0.7431 +2024-11-22 13:14:34.818919: Pseudo dice [0.8358] +2024-11-22 13:14:34.824099: Epoch time: 17.98 s +2024-11-22 13:14:34.824227: Yayy! New best EMA pseudo Dice: 0.8354 +2024-11-22 13:14:36.034671: +2024-11-22 13:14:36.034885: Epoch 4870 +2024-11-22 13:14:36.035007: Current learning rate: 0.0043 +2024-11-22 13:14:55.929606: train_loss -0.7984 +2024-11-22 13:14:55.929822: val_loss -0.7518 +2024-11-22 13:14:55.929897: Pseudo dice [0.8294] +2024-11-22 13:14:55.929979: Epoch time: 19.9 s +2024-11-22 13:14:56.824209: +2024-11-22 13:14:56.824412: Epoch 4871 +2024-11-22 13:14:56.824524: Current learning rate: 0.0043 +2024-11-22 13:15:14.753923: train_loss -0.8003 +2024-11-22 13:15:14.754173: val_loss -0.7613 +2024-11-22 13:15:14.754268: Pseudo dice [0.8365] +2024-11-22 13:15:14.754351: Epoch time: 17.93 s +2024-11-22 13:15:15.640263: +2024-11-22 13:15:15.640475: Epoch 4872 +2024-11-22 13:15:15.640589: Current learning rate: 0.00429 +2024-11-22 13:15:34.560078: train_loss -0.8064 +2024-11-22 13:15:34.560296: val_loss -0.7421 +2024-11-22 13:15:34.560381: Pseudo dice [0.8375] +2024-11-22 13:15:34.560459: Epoch time: 18.92 s +2024-11-22 13:15:35.445509: +2024-11-22 13:15:35.445762: Epoch 4873 +2024-11-22 13:15:35.445880: Current learning rate: 0.00429 +2024-11-22 13:15:53.506080: train_loss -0.8008 +2024-11-22 13:15:53.506313: val_loss -0.7474 +2024-11-22 13:15:53.506390: Pseudo dice [0.8427] +2024-11-22 13:15:53.506470: Epoch time: 18.06 s +2024-11-22 13:15:53.507493: Yayy! New best EMA pseudo Dice: 0.836 +2024-11-22 13:15:54.668751: +2024-11-22 13:15:54.669016: Epoch 4874 +2024-11-22 13:15:54.669134: Current learning rate: 0.00429 +2024-11-22 13:16:13.519762: train_loss -0.7995 +2024-11-22 13:16:13.519989: val_loss -0.7592 +2024-11-22 13:16:13.520081: Pseudo dice [0.8313] +2024-11-22 13:16:13.520163: Epoch time: 18.85 s +2024-11-22 13:16:14.401533: +2024-11-22 13:16:14.401796: Epoch 4875 +2024-11-22 13:16:14.401911: Current learning rate: 0.00429 +2024-11-22 13:16:33.294601: train_loss -0.7863 +2024-11-22 13:16:33.294864: val_loss -0.7384 +2024-11-22 13:16:33.294944: Pseudo dice [0.8175] +2024-11-22 13:16:33.295035: Epoch time: 18.89 s +2024-11-22 13:16:34.325274: +2024-11-22 13:16:34.325571: Epoch 4876 +2024-11-22 13:16:34.325691: Current learning rate: 0.00429 +2024-11-22 13:16:52.752723: train_loss -0.7905 +2024-11-22 13:16:52.752940: val_loss -0.7532 +2024-11-22 13:16:52.753021: Pseudo dice [0.8336] +2024-11-22 13:16:52.753098: Epoch time: 18.43 s +2024-11-22 13:16:53.633941: +2024-11-22 13:16:53.634163: Epoch 4877 +2024-11-22 13:16:53.634275: Current learning rate: 0.00429 +2024-11-22 13:17:12.009532: train_loss -0.7995 +2024-11-22 13:17:12.015202: val_loss -0.7346 +2024-11-22 13:17:12.015314: Pseudo dice [0.8232] +2024-11-22 13:17:12.015399: Epoch time: 18.38 s +2024-11-22 13:17:12.921540: +2024-11-22 13:17:12.921788: Epoch 4878 +2024-11-22 13:17:12.921936: Current learning rate: 0.00429 +2024-11-22 13:17:31.912422: train_loss -0.7956 +2024-11-22 13:17:31.913124: val_loss -0.7704 +2024-11-22 13:17:31.913229: Pseudo dice [0.8291] +2024-11-22 13:17:31.913315: Epoch time: 18.99 s +2024-11-22 13:17:32.819912: +2024-11-22 13:17:32.820156: Epoch 4879 +2024-11-22 13:17:32.820272: Current learning rate: 0.00429 +2024-11-22 13:17:52.767614: train_loss -0.7902 +2024-11-22 13:17:52.767831: val_loss -0.7544 +2024-11-22 13:17:52.767976: Pseudo dice [0.8257] +2024-11-22 13:17:52.768062: Epoch time: 19.95 s +2024-11-22 13:17:53.650975: +2024-11-22 13:17:53.651240: Epoch 4880 +2024-11-22 13:17:53.651367: Current learning rate: 0.00429 +2024-11-22 13:18:12.477838: train_loss -0.7941 +2024-11-22 13:18:12.478057: val_loss -0.7593 +2024-11-22 13:18:12.478193: Pseudo dice [0.8371] +2024-11-22 13:18:12.478269: Epoch time: 18.83 s +2024-11-22 13:18:13.391785: +2024-11-22 13:18:13.391982: Epoch 4881 +2024-11-22 13:18:13.392103: Current learning rate: 0.00428 +2024-11-22 13:18:32.327243: train_loss -0.7837 +2024-11-22 13:18:32.327494: val_loss -0.7406 +2024-11-22 13:18:32.327574: Pseudo dice [0.8151] +2024-11-22 13:18:32.327659: Epoch time: 18.94 s +2024-11-22 13:18:33.224889: +2024-11-22 13:18:33.225115: Epoch 4882 +2024-11-22 13:18:33.225235: Current learning rate: 0.00428 +2024-11-22 13:18:51.680825: train_loss -0.7793 +2024-11-22 13:18:51.681050: val_loss -0.7177 +2024-11-22 13:18:51.681128: Pseudo dice [0.8232] +2024-11-22 13:18:51.681208: Epoch time: 18.46 s +2024-11-22 13:18:52.708972: +2024-11-22 13:18:52.709186: Epoch 4883 +2024-11-22 13:18:52.709301: Current learning rate: 0.00428 +2024-11-22 13:19:11.366574: train_loss -0.7889 +2024-11-22 13:19:11.366793: val_loss -0.7264 +2024-11-22 13:19:11.366866: Pseudo dice [0.8164] +2024-11-22 13:19:11.366944: Epoch time: 18.66 s +2024-11-22 13:19:12.259876: +2024-11-22 13:19:12.260170: Epoch 4884 +2024-11-22 13:19:12.260284: Current learning rate: 0.00428 +2024-11-22 13:19:30.839301: train_loss -0.7717 +2024-11-22 13:19:30.839552: val_loss -0.7468 +2024-11-22 13:19:30.839626: Pseudo dice [0.8375] +2024-11-22 13:19:30.839719: Epoch time: 18.58 s +2024-11-22 13:19:31.733469: +2024-11-22 13:19:31.733656: Epoch 4885 +2024-11-22 13:19:31.733776: Current learning rate: 0.00428 +2024-11-22 13:19:50.311056: train_loss -0.7717 +2024-11-22 13:19:50.311261: val_loss -0.7397 +2024-11-22 13:19:50.313444: Pseudo dice [0.8183] +2024-11-22 13:19:50.313656: Epoch time: 18.58 s +2024-11-22 13:19:51.215274: +2024-11-22 13:19:51.215479: Epoch 4886 +2024-11-22 13:19:51.215599: Current learning rate: 0.00428 +2024-11-22 13:20:09.388076: train_loss -0.7739 +2024-11-22 13:20:09.388296: val_loss -0.7345 +2024-11-22 13:20:09.388370: Pseudo dice [0.8301] +2024-11-22 13:20:09.388448: Epoch time: 18.17 s +2024-11-22 13:20:10.391757: +2024-11-22 13:20:10.392020: Epoch 4887 +2024-11-22 13:20:10.392131: Current learning rate: 0.00428 +2024-11-22 13:20:30.900588: train_loss -0.7685 +2024-11-22 13:20:30.900807: val_loss -0.7393 +2024-11-22 13:20:30.900881: Pseudo dice [0.8354] +2024-11-22 13:20:30.900962: Epoch time: 20.51 s +2024-11-22 13:20:31.795184: +2024-11-22 13:20:31.795493: Epoch 4888 +2024-11-22 13:20:31.795609: Current learning rate: 0.00428 +2024-11-22 13:20:49.928506: train_loss -0.7685 +2024-11-22 13:20:49.928743: val_loss -0.719 +2024-11-22 13:20:49.928816: Pseudo dice [0.7867] +2024-11-22 13:20:49.928900: Epoch time: 18.13 s +2024-11-22 13:20:51.217942: +2024-11-22 13:20:51.218191: Epoch 4889 +2024-11-22 13:20:51.218303: Current learning rate: 0.00427 +2024-11-22 13:21:10.607306: train_loss -0.7704 +2024-11-22 13:21:10.607817: val_loss -0.7573 +2024-11-22 13:21:10.607918: Pseudo dice [0.8221] +2024-11-22 13:21:10.608007: Epoch time: 19.39 s +2024-11-22 13:21:11.498098: +2024-11-22 13:21:11.498374: Epoch 4890 +2024-11-22 13:21:11.498489: Current learning rate: 0.00427 +2024-11-22 13:21:31.037537: train_loss -0.7713 +2024-11-22 13:21:31.037753: val_loss -0.7405 +2024-11-22 13:21:31.037830: Pseudo dice [0.8341] +2024-11-22 13:21:31.037909: Epoch time: 19.54 s +2024-11-22 13:21:31.928401: +2024-11-22 13:21:31.928606: Epoch 4891 +2024-11-22 13:21:31.928718: Current learning rate: 0.00427 +2024-11-22 13:21:50.977669: train_loss -0.7951 +2024-11-22 13:21:50.977893: val_loss -0.7432 +2024-11-22 13:21:50.977977: Pseudo dice [0.8311] +2024-11-22 13:21:50.978120: Epoch time: 19.05 s +2024-11-22 13:21:51.878203: +2024-11-22 13:21:51.878434: Epoch 4892 +2024-11-22 13:21:51.878557: Current learning rate: 0.00427 +2024-11-22 13:22:10.899246: train_loss -0.7785 +2024-11-22 13:22:10.899490: val_loss -0.7351 +2024-11-22 13:22:10.899586: Pseudo dice [0.8304] +2024-11-22 13:22:10.899672: Epoch time: 19.02 s +2024-11-22 13:22:11.792611: +2024-11-22 13:22:11.792928: Epoch 4893 +2024-11-22 13:22:11.793051: Current learning rate: 0.00427 +2024-11-22 13:22:29.618841: train_loss -0.7744 +2024-11-22 13:22:29.621220: val_loss -0.747 +2024-11-22 13:22:29.621313: Pseudo dice [0.8234] +2024-11-22 13:22:29.621393: Epoch time: 17.83 s +2024-11-22 13:22:30.561028: +2024-11-22 13:22:30.561334: Epoch 4894 +2024-11-22 13:22:30.561454: Current learning rate: 0.00427 +2024-11-22 13:22:48.941762: train_loss -0.7817 +2024-11-22 13:22:48.948271: val_loss -0.7462 +2024-11-22 13:22:48.948395: Pseudo dice [0.8218] +2024-11-22 13:22:48.948474: Epoch time: 18.38 s +2024-11-22 13:22:49.904942: +2024-11-22 13:22:49.905158: Epoch 4895 +2024-11-22 13:22:49.905270: Current learning rate: 0.00427 +2024-11-22 13:23:09.576646: train_loss -0.7775 +2024-11-22 13:23:09.576916: val_loss -0.7136 +2024-11-22 13:23:09.576995: Pseudo dice [0.8398] +2024-11-22 13:23:09.577075: Epoch time: 19.67 s +2024-11-22 13:23:10.470182: +2024-11-22 13:23:10.470384: Epoch 4896 +2024-11-22 13:23:10.470499: Current learning rate: 0.00427 +2024-11-22 13:23:28.977223: train_loss -0.7763 +2024-11-22 13:23:28.977509: val_loss -0.7311 +2024-11-22 13:23:28.977585: Pseudo dice [0.804] +2024-11-22 13:23:28.977667: Epoch time: 18.51 s +2024-11-22 13:23:29.901447: +2024-11-22 13:23:29.901789: Epoch 4897 +2024-11-22 13:23:29.901901: Current learning rate: 0.00426 +2024-11-22 13:23:47.438563: train_loss -0.7881 +2024-11-22 13:23:47.438777: val_loss -0.7434 +2024-11-22 13:23:47.438851: Pseudo dice [0.8241] +2024-11-22 13:23:47.438927: Epoch time: 17.54 s +2024-11-22 13:23:48.328788: +2024-11-22 13:23:48.329014: Epoch 4898 +2024-11-22 13:23:48.329126: Current learning rate: 0.00426 +2024-11-22 13:24:06.796368: train_loss -0.7798 +2024-11-22 13:24:06.796576: val_loss -0.7468 +2024-11-22 13:24:06.796653: Pseudo dice [0.829] +2024-11-22 13:24:06.796733: Epoch time: 18.47 s +2024-11-22 13:24:07.681865: +2024-11-22 13:24:07.693176: Epoch 4899 +2024-11-22 13:24:07.693299: Current learning rate: 0.00426 +2024-11-22 13:24:25.432217: train_loss -0.7899 +2024-11-22 13:24:25.432481: val_loss -0.7508 +2024-11-22 13:24:25.432559: Pseudo dice [0.8343] +2024-11-22 13:24:25.432647: Epoch time: 17.75 s +2024-11-22 13:24:26.949321: +2024-11-22 13:24:26.949551: Epoch 4900 +2024-11-22 13:24:26.949665: Current learning rate: 0.00426 +2024-11-22 13:24:45.305362: train_loss -0.7929 +2024-11-22 13:24:45.305604: val_loss -0.7605 +2024-11-22 13:24:45.305681: Pseudo dice [0.848] +2024-11-22 13:24:45.305757: Epoch time: 18.36 s +2024-11-22 13:24:46.196712: +2024-11-22 13:24:46.196934: Epoch 4901 +2024-11-22 13:24:46.197049: Current learning rate: 0.00426 +2024-11-22 13:25:04.981849: train_loss -0.7912 +2024-11-22 13:25:04.982078: val_loss -0.7475 +2024-11-22 13:25:04.982151: Pseudo dice [0.8415] +2024-11-22 13:25:04.982230: Epoch time: 18.79 s +2024-11-22 13:25:05.976612: +2024-11-22 13:25:05.976832: Epoch 4902 +2024-11-22 13:25:05.976941: Current learning rate: 0.00426 +2024-11-22 13:25:24.831608: train_loss -0.7749 +2024-11-22 13:25:24.837068: val_loss -0.7432 +2024-11-22 13:25:24.837149: Pseudo dice [0.8175] +2024-11-22 13:25:24.837239: Epoch time: 18.86 s +2024-11-22 13:25:25.917190: +2024-11-22 13:25:25.917399: Epoch 4903 +2024-11-22 13:25:25.917516: Current learning rate: 0.00426 +2024-11-22 13:25:45.105704: train_loss -0.7828 +2024-11-22 13:25:45.105935: val_loss -0.7778 +2024-11-22 13:25:45.106020: Pseudo dice [0.8357] +2024-11-22 13:25:45.106102: Epoch time: 19.19 s +2024-11-22 13:25:45.992110: +2024-11-22 13:25:45.992307: Epoch 4904 +2024-11-22 13:25:45.992425: Current learning rate: 0.00426 +2024-11-22 13:26:04.297294: train_loss -0.7947 +2024-11-22 13:26:04.297520: val_loss -0.7389 +2024-11-22 13:26:04.302764: Pseudo dice [0.8162] +2024-11-22 13:26:04.302930: Epoch time: 18.31 s +2024-11-22 13:26:05.207498: +2024-11-22 13:26:05.207710: Epoch 4905 +2024-11-22 13:26:05.207824: Current learning rate: 0.00425 +2024-11-22 13:26:23.383888: train_loss -0.793 +2024-11-22 13:26:23.384120: val_loss -0.7474 +2024-11-22 13:26:23.384197: Pseudo dice [0.8361] +2024-11-22 13:26:23.384278: Epoch time: 18.18 s +2024-11-22 13:26:24.317787: +2024-11-22 13:26:24.318020: Epoch 4906 +2024-11-22 13:26:24.318135: Current learning rate: 0.00425 +2024-11-22 13:26:43.329454: train_loss -0.7985 +2024-11-22 13:26:43.329691: val_loss -0.7439 +2024-11-22 13:26:43.329764: Pseudo dice [0.8218] +2024-11-22 13:26:43.329842: Epoch time: 19.01 s +2024-11-22 13:26:44.217951: +2024-11-22 13:26:44.218155: Epoch 4907 +2024-11-22 13:26:44.218268: Current learning rate: 0.00425 +2024-11-22 13:27:02.536904: train_loss -0.797 +2024-11-22 13:27:02.537128: val_loss -0.7571 +2024-11-22 13:27:02.537202: Pseudo dice [0.8394] +2024-11-22 13:27:02.537278: Epoch time: 18.32 s +2024-11-22 13:27:03.431203: +2024-11-22 13:27:03.431408: Epoch 4908 +2024-11-22 13:27:03.431521: Current learning rate: 0.00425 +2024-11-22 13:27:22.613547: train_loss -0.7929 +2024-11-22 13:27:22.613766: val_loss -0.7497 +2024-11-22 13:27:22.613844: Pseudo dice [0.831] +2024-11-22 13:27:22.613933: Epoch time: 19.18 s +2024-11-22 13:27:23.506939: +2024-11-22 13:27:23.507138: Epoch 4909 +2024-11-22 13:27:23.507251: Current learning rate: 0.00425 +2024-11-22 13:27:41.444681: train_loss -0.8011 +2024-11-22 13:27:41.444979: val_loss -0.7427 +2024-11-22 13:27:41.445061: Pseudo dice [0.8239] +2024-11-22 13:27:41.445148: Epoch time: 17.94 s +2024-11-22 13:27:42.342966: +2024-11-22 13:27:42.343176: Epoch 4910 +2024-11-22 13:27:42.343290: Current learning rate: 0.00425 +2024-11-22 13:28:01.352719: train_loss -0.7848 +2024-11-22 13:28:01.352944: val_loss -0.7516 +2024-11-22 13:28:01.353096: Pseudo dice [0.8375] +2024-11-22 13:28:01.353176: Epoch time: 19.01 s +2024-11-22 13:28:02.240441: +2024-11-22 13:28:02.240659: Epoch 4911 +2024-11-22 13:28:02.240775: Current learning rate: 0.00425 +2024-11-22 13:28:21.031591: train_loss -0.7838 +2024-11-22 13:28:21.031873: val_loss -0.7415 +2024-11-22 13:28:21.031955: Pseudo dice [0.818] +2024-11-22 13:28:21.034002: Epoch time: 18.79 s +2024-11-22 13:28:21.950076: +2024-11-22 13:28:21.950272: Epoch 4912 +2024-11-22 13:28:21.950382: Current learning rate: 0.00425 +2024-11-22 13:28:40.237293: train_loss -0.7827 +2024-11-22 13:28:40.239984: val_loss -0.7336 +2024-11-22 13:28:40.240119: Pseudo dice [0.82] +2024-11-22 13:28:40.240209: Epoch time: 18.29 s +2024-11-22 13:28:41.281030: +2024-11-22 13:28:41.281232: Epoch 4913 +2024-11-22 13:28:41.281344: Current learning rate: 0.00424 +2024-11-22 13:29:00.977890: train_loss -0.7792 +2024-11-22 13:29:00.978120: val_loss -0.7432 +2024-11-22 13:29:00.978195: Pseudo dice [0.8034] +2024-11-22 13:29:00.978273: Epoch time: 19.7 s +2024-11-22 13:29:01.871488: +2024-11-22 13:29:01.871721: Epoch 4914 +2024-11-22 13:29:01.871831: Current learning rate: 0.00424 +2024-11-22 13:29:19.368251: train_loss -0.7843 +2024-11-22 13:29:19.368463: val_loss -0.7555 +2024-11-22 13:29:19.368541: Pseudo dice [0.8124] +2024-11-22 13:29:19.368620: Epoch time: 17.5 s +2024-11-22 13:29:20.257785: +2024-11-22 13:29:20.258038: Epoch 4915 +2024-11-22 13:29:20.258157: Current learning rate: 0.00424 +2024-11-22 13:29:38.717091: train_loss -0.7759 +2024-11-22 13:29:38.717316: val_loss -0.7245 +2024-11-22 13:29:38.717394: Pseudo dice [0.8231] +2024-11-22 13:29:38.717474: Epoch time: 18.46 s +2024-11-22 13:29:39.604905: +2024-11-22 13:29:39.605113: Epoch 4916 +2024-11-22 13:29:39.605221: Current learning rate: 0.00424 +2024-11-22 13:29:57.730731: train_loss -0.7864 +2024-11-22 13:29:57.730978: val_loss -0.7683 +2024-11-22 13:29:57.731103: Pseudo dice [0.8307] +2024-11-22 13:29:57.731211: Epoch time: 18.13 s +2024-11-22 13:29:58.629622: +2024-11-22 13:29:58.629823: Epoch 4917 +2024-11-22 13:29:58.629940: Current learning rate: 0.00424 +2024-11-22 13:30:17.388050: train_loss -0.7934 +2024-11-22 13:30:17.388268: val_loss -0.7577 +2024-11-22 13:30:17.388344: Pseudo dice [0.839] +2024-11-22 13:30:17.388420: Epoch time: 18.76 s +2024-11-22 13:30:18.277349: +2024-11-22 13:30:18.277550: Epoch 4918 +2024-11-22 13:30:18.277669: Current learning rate: 0.00424 +2024-11-22 13:30:36.748409: train_loss -0.7937 +2024-11-22 13:30:36.748624: val_loss -0.7393 +2024-11-22 13:30:36.748698: Pseudo dice [0.8185] +2024-11-22 13:30:36.748775: Epoch time: 18.47 s +2024-11-22 13:30:37.645326: +2024-11-22 13:30:37.645613: Epoch 4919 +2024-11-22 13:30:37.645727: Current learning rate: 0.00424 +2024-11-22 13:30:56.499913: train_loss -0.7917 +2024-11-22 13:30:56.500145: val_loss -0.7321 +2024-11-22 13:30:56.500223: Pseudo dice [0.8405] +2024-11-22 13:30:56.500306: Epoch time: 18.86 s +2024-11-22 13:30:57.392009: +2024-11-22 13:30:57.392222: Epoch 4920 +2024-11-22 13:30:57.392334: Current learning rate: 0.00424 +2024-11-22 13:31:15.763743: train_loss -0.7865 +2024-11-22 13:31:15.764003: val_loss -0.7261 +2024-11-22 13:31:15.764080: Pseudo dice [0.8236] +2024-11-22 13:31:15.764165: Epoch time: 18.37 s +2024-11-22 13:31:16.855131: +2024-11-22 13:31:16.855347: Epoch 4921 +2024-11-22 13:31:16.855465: Current learning rate: 0.00423 +2024-11-22 13:31:36.186970: train_loss -0.7971 +2024-11-22 13:31:36.187202: val_loss -0.7241 +2024-11-22 13:31:36.187276: Pseudo dice [0.8047] +2024-11-22 13:31:36.187354: Epoch time: 19.33 s +2024-11-22 13:31:37.087133: +2024-11-22 13:31:37.087357: Epoch 4922 +2024-11-22 13:31:37.087471: Current learning rate: 0.00423 +2024-11-22 13:31:56.583360: train_loss -0.7784 +2024-11-22 13:31:56.583589: val_loss -0.7338 +2024-11-22 13:31:56.583666: Pseudo dice [0.8278] +2024-11-22 13:31:56.583746: Epoch time: 19.5 s +2024-11-22 13:31:57.650579: +2024-11-22 13:31:57.650772: Epoch 4923 +2024-11-22 13:31:57.650892: Current learning rate: 0.00423 +2024-11-22 13:32:16.594298: train_loss -0.7813 +2024-11-22 13:32:16.594554: val_loss -0.7297 +2024-11-22 13:32:16.594632: Pseudo dice [0.8094] +2024-11-22 13:32:16.594722: Epoch time: 18.94 s +2024-11-22 13:32:17.887302: +2024-11-22 13:32:17.887586: Epoch 4924 +2024-11-22 13:32:17.887697: Current learning rate: 0.00423 +2024-11-22 13:32:36.632220: train_loss -0.7917 +2024-11-22 13:32:36.633104: val_loss -0.7527 +2024-11-22 13:32:36.633183: Pseudo dice [0.8273] +2024-11-22 13:32:36.633281: Epoch time: 18.75 s +2024-11-22 13:32:37.523342: +2024-11-22 13:32:37.523564: Epoch 4925 +2024-11-22 13:32:37.523680: Current learning rate: 0.00423 +2024-11-22 13:32:55.939956: train_loss -0.7959 +2024-11-22 13:32:55.940194: val_loss -0.7594 +2024-11-22 13:32:55.940268: Pseudo dice [0.8301] +2024-11-22 13:32:55.940345: Epoch time: 18.42 s +2024-11-22 13:32:56.836145: +2024-11-22 13:32:56.836350: Epoch 4926 +2024-11-22 13:32:56.836460: Current learning rate: 0.00423 +2024-11-22 13:33:14.800452: train_loss -0.7951 +2024-11-22 13:33:14.800671: val_loss -0.7453 +2024-11-22 13:33:14.800747: Pseudo dice [0.8255] +2024-11-22 13:33:14.800899: Epoch time: 17.97 s +2024-11-22 13:33:15.694021: +2024-11-22 13:33:15.694332: Epoch 4927 +2024-11-22 13:33:15.694451: Current learning rate: 0.00423 +2024-11-22 13:33:33.887715: train_loss -0.7973 +2024-11-22 13:33:33.887989: val_loss -0.7562 +2024-11-22 13:33:33.888071: Pseudo dice [0.8155] +2024-11-22 13:33:33.888153: Epoch time: 18.19 s +2024-11-22 13:33:34.783681: +2024-11-22 13:33:34.783913: Epoch 4928 +2024-11-22 13:33:34.784038: Current learning rate: 0.00423 +2024-11-22 13:33:55.255065: train_loss -0.7704 +2024-11-22 13:33:55.255291: val_loss -0.7467 +2024-11-22 13:33:55.255365: Pseudo dice [0.8073] +2024-11-22 13:33:55.255442: Epoch time: 20.47 s +2024-11-22 13:33:56.160088: +2024-11-22 13:33:56.160293: Epoch 4929 +2024-11-22 13:33:56.160414: Current learning rate: 0.00422 +2024-11-22 13:34:14.320677: train_loss -0.7869 +2024-11-22 13:34:14.320912: val_loss -0.7475 +2024-11-22 13:34:14.321002: Pseudo dice [0.835] +2024-11-22 13:34:14.321082: Epoch time: 18.16 s +2024-11-22 13:34:15.218969: +2024-11-22 13:34:15.219168: Epoch 4930 +2024-11-22 13:34:15.219281: Current learning rate: 0.00422 +2024-11-22 13:34:33.967256: train_loss -0.7924 +2024-11-22 13:34:33.967511: val_loss -0.7647 +2024-11-22 13:34:33.967589: Pseudo dice [0.8207] +2024-11-22 13:34:33.967682: Epoch time: 18.75 s +2024-11-22 13:34:34.857643: +2024-11-22 13:34:34.857866: Epoch 4931 +2024-11-22 13:34:34.857979: Current learning rate: 0.00422 +2024-11-22 13:34:53.663070: train_loss -0.7967 +2024-11-22 13:34:53.663287: val_loss -0.743 +2024-11-22 13:34:53.663361: Pseudo dice [0.8068] +2024-11-22 13:34:53.665793: Epoch time: 18.81 s +2024-11-22 13:34:54.572904: +2024-11-22 13:34:54.573225: Epoch 4932 +2024-11-22 13:34:54.573346: Current learning rate: 0.00422 +2024-11-22 13:35:12.995612: train_loss -0.8028 +2024-11-22 13:35:12.995837: val_loss -0.7327 +2024-11-22 13:35:12.995912: Pseudo dice [0.8271] +2024-11-22 13:35:12.995987: Epoch time: 18.42 s +2024-11-22 13:35:14.074665: +2024-11-22 13:35:14.074866: Epoch 4933 +2024-11-22 13:35:14.074983: Current learning rate: 0.00422 +2024-11-22 13:35:32.458570: train_loss -0.8062 +2024-11-22 13:35:32.458792: val_loss -0.7745 +2024-11-22 13:35:32.458872: Pseudo dice [0.8447] +2024-11-22 13:35:32.459100: Epoch time: 18.38 s +2024-11-22 13:35:33.349587: +2024-11-22 13:35:33.349798: Epoch 4934 +2024-11-22 13:35:33.349913: Current learning rate: 0.00422 +2024-11-22 13:35:52.016468: train_loss -0.7977 +2024-11-22 13:35:52.016714: val_loss -0.7633 +2024-11-22 13:35:52.016791: Pseudo dice [0.8417] +2024-11-22 13:35:52.016878: Epoch time: 18.67 s +2024-11-22 13:35:52.915835: +2024-11-22 13:35:52.916040: Epoch 4935 +2024-11-22 13:35:52.916151: Current learning rate: 0.00422 +2024-11-22 13:36:11.114315: train_loss -0.7973 +2024-11-22 13:36:11.114582: val_loss -0.7803 +2024-11-22 13:36:11.114665: Pseudo dice [0.8425] +2024-11-22 13:36:11.114748: Epoch time: 18.2 s +2024-11-22 13:36:12.413907: +2024-11-22 13:36:12.414137: Epoch 4936 +2024-11-22 13:36:12.414247: Current learning rate: 0.00422 +2024-11-22 13:36:31.758687: train_loss -0.7901 +2024-11-22 13:36:31.758963: val_loss -0.768 +2024-11-22 13:36:31.759048: Pseudo dice [0.8456] +2024-11-22 13:36:31.759128: Epoch time: 19.34 s +2024-11-22 13:36:32.829863: +2024-11-22 13:36:32.830189: Epoch 4937 +2024-11-22 13:36:32.847401: Current learning rate: 0.00421 +2024-11-22 13:36:51.053668: train_loss -0.7911 +2024-11-22 13:36:51.053887: val_loss -0.7699 +2024-11-22 13:36:51.053961: Pseudo dice [0.8442] +2024-11-22 13:36:51.054047: Epoch time: 18.22 s +2024-11-22 13:36:51.949814: +2024-11-22 13:36:51.950104: Epoch 4938 +2024-11-22 13:36:51.950222: Current learning rate: 0.00421 +2024-11-22 13:37:10.126796: train_loss -0.7984 +2024-11-22 13:37:10.127023: val_loss -0.778 +2024-11-22 13:37:10.127098: Pseudo dice [0.8427] +2024-11-22 13:37:10.127179: Epoch time: 18.18 s +2024-11-22 13:37:11.017430: +2024-11-22 13:37:11.017646: Epoch 4939 +2024-11-22 13:37:11.017761: Current learning rate: 0.00421 +2024-11-22 13:37:29.783542: train_loss -0.7984 +2024-11-22 13:37:29.783757: val_loss -0.7688 +2024-11-22 13:37:29.783834: Pseudo dice [0.8449] +2024-11-22 13:37:29.783911: Epoch time: 18.77 s +2024-11-22 13:37:30.672142: +2024-11-22 13:37:30.672338: Epoch 4940 +2024-11-22 13:37:30.672451: Current learning rate: 0.00421 +2024-11-22 13:37:48.865390: train_loss -0.8 +2024-11-22 13:37:48.865678: val_loss -0.7618 +2024-11-22 13:37:48.865763: Pseudo dice [0.8307] +2024-11-22 13:37:48.865844: Epoch time: 18.19 s +2024-11-22 13:37:49.758954: +2024-11-22 13:37:49.759161: Epoch 4941 +2024-11-22 13:37:49.759276: Current learning rate: 0.00421 +2024-11-22 13:38:08.298208: train_loss -0.7957 +2024-11-22 13:38:08.298423: val_loss -0.7695 +2024-11-22 13:38:08.298500: Pseudo dice [0.8477] +2024-11-22 13:38:08.298579: Epoch time: 18.54 s +2024-11-22 13:38:09.192770: +2024-11-22 13:38:09.192977: Epoch 4942 +2024-11-22 13:38:09.193097: Current learning rate: 0.00421 +2024-11-22 13:38:27.181453: train_loss -0.8048 +2024-11-22 13:38:27.181700: val_loss -0.7654 +2024-11-22 13:38:27.181781: Pseudo dice [0.8325] +2024-11-22 13:38:27.181865: Epoch time: 17.99 s +2024-11-22 13:38:28.078214: +2024-11-22 13:38:28.078493: Epoch 4943 +2024-11-22 13:38:28.078604: Current learning rate: 0.00421 +2024-11-22 13:38:46.637265: train_loss -0.7951 +2024-11-22 13:38:46.637481: val_loss -0.7496 +2024-11-22 13:38:46.637560: Pseudo dice [0.8328] +2024-11-22 13:38:46.637641: Epoch time: 18.56 s +2024-11-22 13:38:47.524837: +2024-11-22 13:38:47.525033: Epoch 4944 +2024-11-22 13:38:47.525147: Current learning rate: 0.00421 +2024-11-22 13:39:05.820950: train_loss -0.8098 +2024-11-22 13:39:05.823360: val_loss -0.7143 +2024-11-22 13:39:05.823447: Pseudo dice [0.8173] +2024-11-22 13:39:05.823525: Epoch time: 18.3 s +2024-11-22 13:39:06.749353: +2024-11-22 13:39:06.749576: Epoch 4945 +2024-11-22 13:39:06.749687: Current learning rate: 0.0042 +2024-11-22 13:39:25.205855: train_loss -0.7994 +2024-11-22 13:39:25.206099: val_loss -0.7535 +2024-11-22 13:39:25.206176: Pseudo dice [0.8313] +2024-11-22 13:39:25.206259: Epoch time: 18.46 s +2024-11-22 13:39:26.107806: +2024-11-22 13:39:26.108022: Epoch 4946 +2024-11-22 13:39:26.108137: Current learning rate: 0.0042 +2024-11-22 13:39:43.984781: train_loss -0.7936 +2024-11-22 13:39:43.984979: val_loss -0.7611 +2024-11-22 13:39:43.985058: Pseudo dice [0.8337] +2024-11-22 13:39:43.985131: Epoch time: 17.88 s +2024-11-22 13:39:44.866088: +2024-11-22 13:39:44.866288: Epoch 4947 +2024-11-22 13:39:44.866401: Current learning rate: 0.0042 +2024-11-22 13:40:04.817631: train_loss -0.7942 +2024-11-22 13:40:04.817864: val_loss -0.743 +2024-11-22 13:40:04.817944: Pseudo dice [0.8152] +2024-11-22 13:40:04.818030: Epoch time: 19.95 s +2024-11-22 13:40:06.161266: +2024-11-22 13:40:06.161495: Epoch 4948 +2024-11-22 13:40:06.161605: Current learning rate: 0.0042 +2024-11-22 13:40:24.847318: train_loss -0.8032 +2024-11-22 13:40:24.847612: val_loss -0.7586 +2024-11-22 13:40:24.847693: Pseudo dice [0.8299] +2024-11-22 13:40:24.847774: Epoch time: 18.69 s +2024-11-22 13:40:25.736594: +2024-11-22 13:40:25.736846: Epoch 4949 +2024-11-22 13:40:25.736957: Current learning rate: 0.0042 +2024-11-22 13:40:44.355983: train_loss -0.7976 +2024-11-22 13:40:44.356222: val_loss -0.7529 +2024-11-22 13:40:44.356297: Pseudo dice [0.8375] +2024-11-22 13:40:44.356378: Epoch time: 18.62 s +2024-11-22 13:40:45.559277: +2024-11-22 13:40:45.559581: Epoch 4950 +2024-11-22 13:40:45.559694: Current learning rate: 0.0042 +2024-11-22 13:41:04.518667: train_loss -0.8041 +2024-11-22 13:41:04.518944: val_loss -0.7612 +2024-11-22 13:41:04.519025: Pseudo dice [0.8301] +2024-11-22 13:41:04.519100: Epoch time: 18.96 s +2024-11-22 13:41:05.408211: +2024-11-22 13:41:05.408422: Epoch 4951 +2024-11-22 13:41:05.408535: Current learning rate: 0.0042 +2024-11-22 13:41:23.739084: train_loss -0.7927 +2024-11-22 13:41:23.739348: val_loss -0.75 +2024-11-22 13:41:23.739421: Pseudo dice [0.834] +2024-11-22 13:41:23.739496: Epoch time: 18.33 s +2024-11-22 13:41:24.679186: +2024-11-22 13:41:24.679442: Epoch 4952 +2024-11-22 13:41:24.679552: Current learning rate: 0.0042 +2024-11-22 13:41:44.137780: train_loss -0.7891 +2024-11-22 13:41:44.138004: val_loss -0.7353 +2024-11-22 13:41:44.138079: Pseudo dice [0.8147] +2024-11-22 13:41:44.138156: Epoch time: 19.46 s +2024-11-22 13:41:45.024954: +2024-11-22 13:41:45.025155: Epoch 4953 +2024-11-22 13:41:45.025269: Current learning rate: 0.00419 +2024-11-22 13:42:04.909179: train_loss -0.7909 +2024-11-22 13:42:04.909503: val_loss -0.7397 +2024-11-22 13:42:04.909585: Pseudo dice [0.8261] +2024-11-22 13:42:04.909669: Epoch time: 19.88 s +2024-11-22 13:42:05.807132: +2024-11-22 13:42:05.807419: Epoch 4954 +2024-11-22 13:42:05.807534: Current learning rate: 0.00419 +2024-11-22 13:42:25.510607: train_loss -0.7965 +2024-11-22 13:42:25.510818: val_loss -0.74 +2024-11-22 13:42:25.510889: Pseudo dice [0.8272] +2024-11-22 13:42:25.510966: Epoch time: 19.7 s +2024-11-22 13:42:26.434903: +2024-11-22 13:42:26.435139: Epoch 4955 +2024-11-22 13:42:26.435253: Current learning rate: 0.00419 +2024-11-22 13:42:44.964253: train_loss -0.7952 +2024-11-22 13:42:44.964470: val_loss -0.769 +2024-11-22 13:42:44.964544: Pseudo dice [0.8248] +2024-11-22 13:42:44.964618: Epoch time: 18.53 s +2024-11-22 13:42:45.849614: +2024-11-22 13:42:45.849840: Epoch 4956 +2024-11-22 13:42:45.849957: Current learning rate: 0.00419 +2024-11-22 13:43:04.378282: train_loss -0.8042 +2024-11-22 13:43:04.378510: val_loss -0.7662 +2024-11-22 13:43:04.378582: Pseudo dice [0.8442] +2024-11-22 13:43:04.380931: Epoch time: 18.53 s +2024-11-22 13:43:05.279176: +2024-11-22 13:43:05.279368: Epoch 4957 +2024-11-22 13:43:05.279481: Current learning rate: 0.00419 +2024-11-22 13:43:23.956815: train_loss -0.8004 +2024-11-22 13:43:23.957078: val_loss -0.7359 +2024-11-22 13:43:23.957163: Pseudo dice [0.834] +2024-11-22 13:43:23.962398: Epoch time: 18.68 s +2024-11-22 13:43:24.871215: +2024-11-22 13:43:24.871428: Epoch 4958 +2024-11-22 13:43:24.871548: Current learning rate: 0.00419 +2024-11-22 13:43:44.342264: train_loss -0.7947 +2024-11-22 13:43:44.342483: val_loss -0.7625 +2024-11-22 13:43:44.342557: Pseudo dice [0.839] +2024-11-22 13:43:44.342634: Epoch time: 19.47 s +2024-11-22 13:43:45.247557: +2024-11-22 13:43:45.247767: Epoch 4959 +2024-11-22 13:43:45.247882: Current learning rate: 0.00419 +2024-11-22 13:44:04.943031: train_loss -0.7972 +2024-11-22 13:44:04.948439: val_loss -0.718 +2024-11-22 13:44:04.948564: Pseudo dice [0.8007] +2024-11-22 13:44:04.948725: Epoch time: 19.7 s +2024-11-22 13:44:06.037822: +2024-11-22 13:44:06.038030: Epoch 4960 +2024-11-22 13:44:06.038150: Current learning rate: 0.00419 +2024-11-22 13:44:24.750981: train_loss -0.7901 +2024-11-22 13:44:24.751258: val_loss -0.7576 +2024-11-22 13:44:24.751338: Pseudo dice [0.8345] +2024-11-22 13:44:24.751428: Epoch time: 18.71 s +2024-11-22 13:44:25.745909: +2024-11-22 13:44:25.746125: Epoch 4961 +2024-11-22 13:44:25.746240: Current learning rate: 0.00418 +2024-11-22 13:44:45.036504: train_loss -0.7962 +2024-11-22 13:44:45.036740: val_loss -0.7297 +2024-11-22 13:44:45.036820: Pseudo dice [0.8312] +2024-11-22 13:44:45.036900: Epoch time: 19.29 s +2024-11-22 13:44:45.930064: +2024-11-22 13:44:45.930299: Epoch 4962 +2024-11-22 13:44:45.930414: Current learning rate: 0.00418 +2024-11-22 13:45:05.588524: train_loss -0.7743 +2024-11-22 13:45:05.588765: val_loss -0.74 +2024-11-22 13:45:05.588844: Pseudo dice [0.8194] +2024-11-22 13:45:05.588998: Epoch time: 19.66 s +2024-11-22 13:45:06.477297: +2024-11-22 13:45:06.477490: Epoch 4963 +2024-11-22 13:45:06.477599: Current learning rate: 0.00418 +2024-11-22 13:45:25.516591: train_loss -0.7829 +2024-11-22 13:45:25.516823: val_loss -0.7749 +2024-11-22 13:45:25.516898: Pseudo dice [0.8431] +2024-11-22 13:45:25.516981: Epoch time: 19.04 s +2024-11-22 13:45:26.417912: +2024-11-22 13:45:26.418205: Epoch 4964 +2024-11-22 13:45:26.418319: Current learning rate: 0.00418 +2024-11-22 13:45:44.178456: train_loss -0.7859 +2024-11-22 13:45:44.178698: val_loss -0.7393 +2024-11-22 13:45:44.178772: Pseudo dice [0.8178] +2024-11-22 13:45:44.178849: Epoch time: 17.76 s +2024-11-22 13:45:45.069681: +2024-11-22 13:45:45.069889: Epoch 4965 +2024-11-22 13:45:45.070007: Current learning rate: 0.00418 +2024-11-22 13:46:04.433283: train_loss -0.7972 +2024-11-22 13:46:04.433508: val_loss -0.7443 +2024-11-22 13:46:04.433587: Pseudo dice [0.8385] +2024-11-22 13:46:04.433723: Epoch time: 19.36 s +2024-11-22 13:46:05.413365: +2024-11-22 13:46:05.413559: Epoch 4966 +2024-11-22 13:46:05.413675: Current learning rate: 0.00418 +2024-11-22 13:46:25.001739: train_loss -0.7858 +2024-11-22 13:46:25.001958: val_loss -0.7434 +2024-11-22 13:46:25.002057: Pseudo dice [0.8168] +2024-11-22 13:46:25.002132: Epoch time: 19.59 s +2024-11-22 13:46:25.890579: +2024-11-22 13:46:25.890771: Epoch 4967 +2024-11-22 13:46:25.890883: Current learning rate: 0.00418 +2024-11-22 13:46:44.451006: train_loss -0.8029 +2024-11-22 13:46:44.456448: val_loss -0.7359 +2024-11-22 13:46:44.456586: Pseudo dice [0.8398] +2024-11-22 13:46:44.456674: Epoch time: 18.56 s +2024-11-22 13:46:45.347766: +2024-11-22 13:46:45.347957: Epoch 4968 +2024-11-22 13:46:45.348076: Current learning rate: 0.00418 +2024-11-22 13:47:03.694778: train_loss -0.8099 +2024-11-22 13:47:03.695002: val_loss -0.7383 +2024-11-22 13:47:03.695093: Pseudo dice [0.8364] +2024-11-22 13:47:03.701802: Epoch time: 18.35 s +2024-11-22 13:47:04.628449: +2024-11-22 13:47:04.628666: Epoch 4969 +2024-11-22 13:47:04.628785: Current learning rate: 0.00417 +2024-11-22 13:47:24.139092: train_loss -0.8006 +2024-11-22 13:47:24.139308: val_loss -0.7577 +2024-11-22 13:47:24.139382: Pseudo dice [0.8368] +2024-11-22 13:47:24.139458: Epoch time: 19.51 s +2024-11-22 13:47:25.046244: +2024-11-22 13:47:25.046454: Epoch 4970 +2024-11-22 13:47:25.046568: Current learning rate: 0.00417 +2024-11-22 13:47:42.913692: train_loss -0.797 +2024-11-22 13:47:42.913939: val_loss -0.754 +2024-11-22 13:47:42.914028: Pseudo dice [0.8241] +2024-11-22 13:47:42.914119: Epoch time: 17.87 s +2024-11-22 13:47:44.292211: +2024-11-22 13:47:44.292418: Epoch 4971 +2024-11-22 13:47:44.292535: Current learning rate: 0.00417 +2024-11-22 13:48:03.023037: train_loss -0.7898 +2024-11-22 13:48:03.023381: val_loss -0.7387 +2024-11-22 13:48:03.023465: Pseudo dice [0.8385] +2024-11-22 13:48:03.023554: Epoch time: 18.73 s +2024-11-22 13:48:03.909970: +2024-11-22 13:48:03.910230: Epoch 4972 +2024-11-22 13:48:03.910343: Current learning rate: 0.00417 +2024-11-22 13:48:22.163200: train_loss -0.7836 +2024-11-22 13:48:22.163441: val_loss -0.7465 +2024-11-22 13:48:22.163517: Pseudo dice [0.8393] +2024-11-22 13:48:22.163653: Epoch time: 18.25 s +2024-11-22 13:48:23.051581: +2024-11-22 13:48:23.051789: Epoch 4973 +2024-11-22 13:48:23.051902: Current learning rate: 0.00417 +2024-11-22 13:48:42.128511: train_loss -0.7822 +2024-11-22 13:48:42.128737: val_loss -0.748 +2024-11-22 13:48:42.128812: Pseudo dice [0.8221] +2024-11-22 13:48:42.128888: Epoch time: 19.08 s +2024-11-22 13:48:43.059604: +2024-11-22 13:48:43.059905: Epoch 4974 +2024-11-22 13:48:43.060033: Current learning rate: 0.00417 +2024-11-22 13:49:01.933498: train_loss -0.778 +2024-11-22 13:49:01.933794: val_loss -0.7519 +2024-11-22 13:49:01.933872: Pseudo dice [0.8205] +2024-11-22 13:49:01.934004: Epoch time: 18.87 s +2024-11-22 13:49:02.843481: +2024-11-22 13:49:02.843697: Epoch 4975 +2024-11-22 13:49:02.843809: Current learning rate: 0.00417 +2024-11-22 13:49:20.931734: train_loss -0.7924 +2024-11-22 13:49:20.931967: val_loss -0.7604 +2024-11-22 13:49:20.934228: Pseudo dice [0.8313] +2024-11-22 13:49:20.934319: Epoch time: 18.09 s +2024-11-22 13:49:21.933922: +2024-11-22 13:49:21.934153: Epoch 4976 +2024-11-22 13:49:21.934266: Current learning rate: 0.00417 +2024-11-22 13:49:40.084355: train_loss -0.7942 +2024-11-22 13:49:40.084583: val_loss -0.7658 +2024-11-22 13:49:40.084684: Pseudo dice [0.8404] +2024-11-22 13:49:40.084765: Epoch time: 18.15 s +2024-11-22 13:49:40.977571: +2024-11-22 13:49:40.977757: Epoch 4977 +2024-11-22 13:49:40.977870: Current learning rate: 0.00416 +2024-11-22 13:49:59.857574: train_loss -0.7914 +2024-11-22 13:49:59.857833: val_loss -0.7286 +2024-11-22 13:49:59.857915: Pseudo dice [0.8393] +2024-11-22 13:49:59.858001: Epoch time: 18.88 s +2024-11-22 13:50:00.747616: +2024-11-22 13:50:00.747903: Epoch 4978 +2024-11-22 13:50:00.748019: Current learning rate: 0.00416 +2024-11-22 13:50:19.680277: train_loss -0.7923 +2024-11-22 13:50:19.680522: val_loss -0.7411 +2024-11-22 13:50:19.680601: Pseudo dice [0.8111] +2024-11-22 13:50:19.680685: Epoch time: 18.93 s +2024-11-22 13:50:20.562354: +2024-11-22 13:50:20.562567: Epoch 4979 +2024-11-22 13:50:20.562677: Current learning rate: 0.00416 +2024-11-22 13:50:38.602729: train_loss -0.7998 +2024-11-22 13:50:38.602962: val_loss -0.7506 +2024-11-22 13:50:38.603043: Pseudo dice [0.8349] +2024-11-22 13:50:38.603120: Epoch time: 18.04 s +2024-11-22 13:50:39.498544: +2024-11-22 13:50:39.498747: Epoch 4980 +2024-11-22 13:50:39.498866: Current learning rate: 0.00416 +2024-11-22 13:50:57.904789: train_loss -0.8051 +2024-11-22 13:50:57.905017: val_loss -0.7499 +2024-11-22 13:50:57.905091: Pseudo dice [0.8328] +2024-11-22 13:50:57.905173: Epoch time: 18.41 s +2024-11-22 13:50:58.798344: +2024-11-22 13:50:58.798594: Epoch 4981 +2024-11-22 13:50:58.798704: Current learning rate: 0.00416 +2024-11-22 13:51:17.309434: train_loss -0.8059 +2024-11-22 13:51:17.309673: val_loss -0.759 +2024-11-22 13:51:17.309750: Pseudo dice [0.8408] +2024-11-22 13:51:17.309834: Epoch time: 18.51 s +2024-11-22 13:51:18.204202: +2024-11-22 13:51:18.204407: Epoch 4982 +2024-11-22 13:51:18.204520: Current learning rate: 0.00416 +2024-11-22 13:51:37.628128: train_loss -0.8103 +2024-11-22 13:51:37.628350: val_loss -0.763 +2024-11-22 13:51:37.628425: Pseudo dice [0.8436] +2024-11-22 13:51:37.628505: Epoch time: 19.42 s +2024-11-22 13:51:38.908743: +2024-11-22 13:51:38.908988: Epoch 4983 +2024-11-22 13:51:38.909106: Current learning rate: 0.00416 +2024-11-22 13:51:58.102344: train_loss -0.8056 +2024-11-22 13:51:58.102585: val_loss -0.7461 +2024-11-22 13:51:58.102661: Pseudo dice [0.8405] +2024-11-22 13:51:58.102740: Epoch time: 19.19 s +2024-11-22 13:51:59.086799: +2024-11-22 13:51:59.087019: Epoch 4984 +2024-11-22 13:51:59.087140: Current learning rate: 0.00416 +2024-11-22 13:52:16.870951: train_loss -0.8087 +2024-11-22 13:52:16.871219: val_loss -0.7627 +2024-11-22 13:52:16.871323: Pseudo dice [0.8403] +2024-11-22 13:52:16.871415: Epoch time: 17.78 s +2024-11-22 13:52:17.844824: +2024-11-22 13:52:17.845057: Epoch 4985 +2024-11-22 13:52:17.845167: Current learning rate: 0.00416 +2024-11-22 13:52:36.353771: train_loss -0.8071 +2024-11-22 13:52:36.354010: val_loss -0.7777 +2024-11-22 13:52:36.354087: Pseudo dice [0.8397] +2024-11-22 13:52:36.354368: Epoch time: 18.51 s +2024-11-22 13:52:37.245038: +2024-11-22 13:52:37.245252: Epoch 4986 +2024-11-22 13:52:37.245368: Current learning rate: 0.00415 +2024-11-22 13:52:55.552038: train_loss -0.7993 +2024-11-22 13:52:55.552285: val_loss -0.7343 +2024-11-22 13:52:55.552362: Pseudo dice [0.83] +2024-11-22 13:52:55.552441: Epoch time: 18.31 s +2024-11-22 13:52:56.443627: +2024-11-22 13:52:56.443830: Epoch 4987 +2024-11-22 13:52:56.443944: Current learning rate: 0.00415 +2024-11-22 13:53:15.819666: train_loss -0.799 +2024-11-22 13:53:15.819898: val_loss -0.7447 +2024-11-22 13:53:15.819974: Pseudo dice [0.8309] +2024-11-22 13:53:15.820059: Epoch time: 19.38 s +2024-11-22 13:53:16.726351: +2024-11-22 13:53:16.726564: Epoch 4988 +2024-11-22 13:53:16.726675: Current learning rate: 0.00415 +2024-11-22 13:53:35.072296: train_loss -0.8035 +2024-11-22 13:53:35.074714: val_loss -0.7614 +2024-11-22 13:53:35.074853: Pseudo dice [0.8296] +2024-11-22 13:53:35.074945: Epoch time: 18.35 s +2024-11-22 13:53:36.033850: +2024-11-22 13:53:36.034163: Epoch 4989 +2024-11-22 13:53:36.034281: Current learning rate: 0.00415 +2024-11-22 13:53:54.704452: train_loss -0.7737 +2024-11-22 13:53:54.704727: val_loss -0.7325 +2024-11-22 13:53:54.704806: Pseudo dice [0.798] +2024-11-22 13:53:54.704887: Epoch time: 18.67 s +2024-11-22 13:53:55.591223: +2024-11-22 13:53:55.591448: Epoch 4990 +2024-11-22 13:53:55.591557: Current learning rate: 0.00415 +2024-11-22 13:54:13.490347: train_loss -0.7723 +2024-11-22 13:54:13.490563: val_loss -0.7314 +2024-11-22 13:54:13.490636: Pseudo dice [0.8363] +2024-11-22 13:54:13.490712: Epoch time: 17.9 s +2024-11-22 13:54:14.369198: +2024-11-22 13:54:14.369397: Epoch 4991 +2024-11-22 13:54:14.369511: Current learning rate: 0.00415 +2024-11-22 13:54:34.448809: train_loss -0.7841 +2024-11-22 13:54:34.449019: val_loss -0.7659 +2024-11-22 13:54:34.449099: Pseudo dice [0.8408] +2024-11-22 13:54:34.449175: Epoch time: 20.08 s +2024-11-22 13:54:35.331321: +2024-11-22 13:54:35.331497: Epoch 4992 +2024-11-22 13:54:35.331608: Current learning rate: 0.00415 +2024-11-22 13:54:53.372647: train_loss -0.7869 +2024-11-22 13:54:53.372882: val_loss -0.7435 +2024-11-22 13:54:53.378103: Pseudo dice [0.8387] +2024-11-22 13:54:53.378272: Epoch time: 18.04 s +2024-11-22 13:54:54.296615: +2024-11-22 13:54:54.296825: Epoch 4993 +2024-11-22 13:54:54.296939: Current learning rate: 0.00415 +2024-11-22 13:55:13.555736: train_loss -0.7934 +2024-11-22 13:55:13.555954: val_loss -0.7361 +2024-11-22 13:55:13.556039: Pseudo dice [0.808] +2024-11-22 13:55:13.556118: Epoch time: 19.26 s +2024-11-22 13:55:14.451313: +2024-11-22 13:55:14.451508: Epoch 4994 +2024-11-22 13:55:14.451622: Current learning rate: 0.00414 +2024-11-22 13:55:33.984890: train_loss -0.7879 +2024-11-22 13:55:33.985108: val_loss -0.7584 +2024-11-22 13:55:33.985181: Pseudo dice [0.8453] +2024-11-22 13:55:33.985263: Epoch time: 19.53 s +2024-11-22 13:55:35.245364: +2024-11-22 13:55:35.245566: Epoch 4995 +2024-11-22 13:55:35.245675: Current learning rate: 0.00414 +2024-11-22 13:55:54.267809: train_loss -0.7984 +2024-11-22 13:55:54.268082: val_loss -0.7415 +2024-11-22 13:55:54.268160: Pseudo dice [0.8278] +2024-11-22 13:55:54.268247: Epoch time: 19.02 s +2024-11-22 13:55:55.185275: +2024-11-22 13:55:55.185513: Epoch 4996 +2024-11-22 13:55:55.185627: Current learning rate: 0.00414 +2024-11-22 13:56:14.343748: train_loss -0.7951 +2024-11-22 13:56:14.347140: val_loss -0.7635 +2024-11-22 13:56:14.347274: Pseudo dice [0.8446] +2024-11-22 13:56:14.347355: Epoch time: 19.16 s +2024-11-22 13:56:15.352996: +2024-11-22 13:56:15.353345: Epoch 4997 +2024-11-22 13:56:15.353458: Current learning rate: 0.00414 +2024-11-22 13:56:33.782321: train_loss -0.7928 +2024-11-22 13:56:33.782538: val_loss -0.7359 +2024-11-22 13:56:33.782614: Pseudo dice [0.8311] +2024-11-22 13:56:33.782689: Epoch time: 18.43 s +2024-11-22 13:56:34.677307: +2024-11-22 13:56:34.677521: Epoch 4998 +2024-11-22 13:56:34.677642: Current learning rate: 0.00414 +2024-11-22 13:56:52.152286: train_loss -0.7945 +2024-11-22 13:56:52.152496: val_loss -0.7114 +2024-11-22 13:56:52.152571: Pseudo dice [0.8066] +2024-11-22 13:56:52.152646: Epoch time: 17.48 s +2024-11-22 13:56:53.375675: +2024-11-22 13:56:53.375880: Epoch 4999 +2024-11-22 13:56:53.375999: Current learning rate: 0.00414 +2024-11-22 13:57:12.075688: train_loss -0.7953 +2024-11-22 13:57:12.075922: val_loss -0.7363 +2024-11-22 13:57:12.076009: Pseudo dice [0.8322] +2024-11-22 13:57:12.076097: Epoch time: 18.7 s +2024-11-22 13:57:13.265523: +2024-11-22 13:57:13.265959: Epoch 5000 +2024-11-22 13:57:13.266081: Current learning rate: 0.00414 +2024-11-22 13:57:31.196565: train_loss -0.7945 +2024-11-22 13:57:31.196773: val_loss -0.7686 +2024-11-22 13:57:31.214524: Pseudo dice [0.8345] +2024-11-22 13:57:31.214623: Epoch time: 17.93 s +2024-11-22 13:57:32.099899: +2024-11-22 13:57:32.100130: Epoch 5001 +2024-11-22 13:57:32.100245: Current learning rate: 0.00414 +2024-11-22 13:57:51.022662: train_loss -0.7859 +2024-11-22 13:57:51.022885: val_loss -0.7539 +2024-11-22 13:57:51.022961: Pseudo dice [0.8239] +2024-11-22 13:57:51.023044: Epoch time: 18.92 s +2024-11-22 13:57:51.906371: +2024-11-22 13:57:51.906600: Epoch 5002 +2024-11-22 13:57:51.906714: Current learning rate: 0.00413 +2024-11-22 13:58:10.964200: train_loss -0.7738 +2024-11-22 13:58:10.964446: val_loss -0.7465 +2024-11-22 13:58:10.964519: Pseudo dice [0.8264] +2024-11-22 13:58:10.964602: Epoch time: 19.06 s +2024-11-22 13:58:11.861133: +2024-11-22 13:58:11.861485: Epoch 5003 +2024-11-22 13:58:11.861607: Current learning rate: 0.00413 +2024-11-22 13:58:32.066464: train_loss -0.7833 +2024-11-22 13:58:32.066686: val_loss -0.7156 +2024-11-22 13:58:32.066764: Pseudo dice [0.8296] +2024-11-22 13:58:32.066839: Epoch time: 20.21 s +2024-11-22 13:58:32.975686: +2024-11-22 13:58:32.975929: Epoch 5004 +2024-11-22 13:58:32.976044: Current learning rate: 0.00413 +2024-11-22 13:58:51.545196: train_loss -0.7942 +2024-11-22 13:58:51.545443: val_loss -0.7528 +2024-11-22 13:58:51.545521: Pseudo dice [0.8261] +2024-11-22 13:58:51.545600: Epoch time: 18.57 s +2024-11-22 13:58:52.584047: +2024-11-22 13:58:52.584236: Epoch 5005 +2024-11-22 13:58:52.584346: Current learning rate: 0.00413 +2024-11-22 13:59:11.668915: train_loss -0.7784 +2024-11-22 13:59:11.669148: val_loss -0.7504 +2024-11-22 13:59:11.669225: Pseudo dice [0.8236] +2024-11-22 13:59:11.669302: Epoch time: 19.09 s +2024-11-22 13:59:12.564676: +2024-11-22 13:59:12.564908: Epoch 5006 +2024-11-22 13:59:12.565034: Current learning rate: 0.00413 +2024-11-22 13:59:31.458085: train_loss -0.7894 +2024-11-22 13:59:31.458333: val_loss -0.7678 +2024-11-22 13:59:31.458413: Pseudo dice [0.819] +2024-11-22 13:59:31.458490: Epoch time: 18.89 s +2024-11-22 13:59:32.347626: +2024-11-22 13:59:32.347869: Epoch 5007 +2024-11-22 13:59:32.347996: Current learning rate: 0.00413 +2024-11-22 13:59:51.624611: train_loss -0.7966 +2024-11-22 13:59:51.624853: val_loss -0.7379 +2024-11-22 13:59:51.624928: Pseudo dice [0.8367] +2024-11-22 13:59:51.625008: Epoch time: 19.28 s +2024-11-22 13:59:52.510969: +2024-11-22 13:59:52.511189: Epoch 5008 +2024-11-22 13:59:52.511300: Current learning rate: 0.00413 +2024-11-22 14:00:12.304096: train_loss -0.7989 +2024-11-22 14:00:12.307418: val_loss -0.7326 +2024-11-22 14:00:12.307575: Pseudo dice [0.8272] +2024-11-22 14:00:12.307661: Epoch time: 19.79 s +2024-11-22 14:00:13.194412: +2024-11-22 14:00:13.194676: Epoch 5009 +2024-11-22 14:00:13.194791: Current learning rate: 0.00413 +2024-11-22 14:00:33.106270: train_loss -0.7821 +2024-11-22 14:00:33.106546: val_loss -0.7334 +2024-11-22 14:00:33.106623: Pseudo dice [0.8226] +2024-11-22 14:00:33.106706: Epoch time: 19.91 s +2024-11-22 14:00:34.059769: +2024-11-22 14:00:34.059961: Epoch 5010 +2024-11-22 14:00:34.060079: Current learning rate: 0.00412 +2024-11-22 14:00:52.987508: train_loss -0.7831 +2024-11-22 14:00:52.987739: val_loss -0.7478 +2024-11-22 14:00:52.987815: Pseudo dice [0.8239] +2024-11-22 14:00:52.987891: Epoch time: 18.93 s +2024-11-22 14:00:53.902745: +2024-11-22 14:00:53.902941: Epoch 5011 +2024-11-22 14:00:53.903061: Current learning rate: 0.00412 +2024-11-22 14:01:11.760453: train_loss -0.7853 +2024-11-22 14:01:11.760691: val_loss -0.7662 +2024-11-22 14:01:11.760918: Pseudo dice [0.8374] +2024-11-22 14:01:11.761010: Epoch time: 17.86 s +2024-11-22 14:01:12.651423: +2024-11-22 14:01:12.651624: Epoch 5012 +2024-11-22 14:01:12.651744: Current learning rate: 0.00412 +2024-11-22 14:01:30.578500: train_loss -0.7846 +2024-11-22 14:01:30.578737: val_loss -0.7715 +2024-11-22 14:01:30.578815: Pseudo dice [0.8404] +2024-11-22 14:01:30.578895: Epoch time: 17.93 s +2024-11-22 14:01:31.609895: +2024-11-22 14:01:31.610102: Epoch 5013 +2024-11-22 14:01:31.610217: Current learning rate: 0.00412 +2024-11-22 14:01:50.063135: train_loss -0.795 +2024-11-22 14:01:50.063389: val_loss -0.7604 +2024-11-22 14:01:50.063464: Pseudo dice [0.8283] +2024-11-22 14:01:50.063545: Epoch time: 18.45 s +2024-11-22 14:01:51.093886: +2024-11-22 14:01:51.094167: Epoch 5014 +2024-11-22 14:01:51.094287: Current learning rate: 0.00412 +2024-11-22 14:02:09.937982: train_loss -0.7985 +2024-11-22 14:02:09.938202: val_loss -0.7499 +2024-11-22 14:02:09.938279: Pseudo dice [0.8255] +2024-11-22 14:02:09.938356: Epoch time: 18.84 s +2024-11-22 14:02:10.831337: +2024-11-22 14:02:10.831564: Epoch 5015 +2024-11-22 14:02:10.831681: Current learning rate: 0.00412 +2024-11-22 14:02:29.439519: train_loss -0.7914 +2024-11-22 14:02:29.439734: val_loss -0.7671 +2024-11-22 14:02:29.439811: Pseudo dice [0.8363] +2024-11-22 14:02:29.439889: Epoch time: 18.61 s +2024-11-22 14:02:30.329333: +2024-11-22 14:02:30.329531: Epoch 5016 +2024-11-22 14:02:30.329645: Current learning rate: 0.00412 +2024-11-22 14:02:49.954473: train_loss -0.7821 +2024-11-22 14:02:49.959877: val_loss -0.7423 +2024-11-22 14:02:49.960041: Pseudo dice [0.8347] +2024-11-22 14:02:49.960127: Epoch time: 19.63 s +2024-11-22 14:02:51.017443: +2024-11-22 14:02:51.017683: Epoch 5017 +2024-11-22 14:02:51.017810: Current learning rate: 0.00412 +2024-11-22 14:03:09.897852: train_loss -0.7909 +2024-11-22 14:03:09.898099: val_loss -0.7592 +2024-11-22 14:03:09.898176: Pseudo dice [0.835] +2024-11-22 14:03:09.898315: Epoch time: 18.88 s +2024-11-22 14:03:11.189794: +2024-11-22 14:03:11.190028: Epoch 5018 +2024-11-22 14:03:11.190140: Current learning rate: 0.00411 +2024-11-22 14:03:29.998787: train_loss -0.7917 +2024-11-22 14:03:30.004227: val_loss -0.7586 +2024-11-22 14:03:30.004350: Pseudo dice [0.8405] +2024-11-22 14:03:30.004429: Epoch time: 18.81 s +2024-11-22 14:03:31.059975: +2024-11-22 14:03:31.060211: Epoch 5019 +2024-11-22 14:03:31.060327: Current learning rate: 0.00411 +2024-11-22 14:03:50.250138: train_loss -0.7962 +2024-11-22 14:03:50.250401: val_loss -0.7715 +2024-11-22 14:03:50.250478: Pseudo dice [0.8519] +2024-11-22 14:03:50.250564: Epoch time: 19.19 s +2024-11-22 14:03:51.140380: +2024-11-22 14:03:51.140621: Epoch 5020 +2024-11-22 14:03:51.140744: Current learning rate: 0.00411 +2024-11-22 14:04:09.193024: train_loss -0.796 +2024-11-22 14:04:09.193301: val_loss -0.7548 +2024-11-22 14:04:09.193379: Pseudo dice [0.8333] +2024-11-22 14:04:09.193459: Epoch time: 18.05 s +2024-11-22 14:04:10.081735: +2024-11-22 14:04:10.081936: Epoch 5021 +2024-11-22 14:04:10.082058: Current learning rate: 0.00411 +2024-11-22 14:04:28.023315: train_loss -0.7899 +2024-11-22 14:04:28.023540: val_loss -0.7435 +2024-11-22 14:04:28.023618: Pseudo dice [0.8064] +2024-11-22 14:04:28.023695: Epoch time: 17.94 s +2024-11-22 14:04:28.908753: +2024-11-22 14:04:28.908954: Epoch 5022 +2024-11-22 14:04:28.909076: Current learning rate: 0.00411 +2024-11-22 14:04:47.181505: train_loss -0.7992 +2024-11-22 14:04:47.181728: val_loss -0.751 +2024-11-22 14:04:47.181802: Pseudo dice [0.8364] +2024-11-22 14:04:47.181879: Epoch time: 18.27 s +2024-11-22 14:04:48.071582: +2024-11-22 14:04:48.071784: Epoch 5023 +2024-11-22 14:04:48.071897: Current learning rate: 0.00411 +2024-11-22 14:05:06.665648: train_loss -0.7937 +2024-11-22 14:05:06.665905: val_loss -0.7505 +2024-11-22 14:05:06.665987: Pseudo dice [0.8344] +2024-11-22 14:05:06.666080: Epoch time: 18.59 s +2024-11-22 14:05:07.560434: +2024-11-22 14:05:07.560652: Epoch 5024 +2024-11-22 14:05:07.560772: Current learning rate: 0.00411 +2024-11-22 14:05:26.332403: train_loss -0.7988 +2024-11-22 14:05:26.332627: val_loss -0.7395 +2024-11-22 14:05:26.332702: Pseudo dice [0.8338] +2024-11-22 14:05:26.332781: Epoch time: 18.77 s +2024-11-22 14:05:27.217029: +2024-11-22 14:05:27.217249: Epoch 5025 +2024-11-22 14:05:27.217365: Current learning rate: 0.00411 +2024-11-22 14:05:45.713887: train_loss -0.7986 +2024-11-22 14:05:45.714123: val_loss -0.7532 +2024-11-22 14:05:45.714200: Pseudo dice [0.8507] +2024-11-22 14:05:45.714279: Epoch time: 18.5 s +2024-11-22 14:05:46.644778: +2024-11-22 14:05:46.661928: Epoch 5026 +2024-11-22 14:05:46.662068: Current learning rate: 0.0041 +2024-11-22 14:06:04.620092: train_loss -0.7989 +2024-11-22 14:06:04.620305: val_loss -0.7665 +2024-11-22 14:06:04.620382: Pseudo dice [0.8427] +2024-11-22 14:06:04.620461: Epoch time: 17.98 s +2024-11-22 14:06:05.514374: +2024-11-22 14:06:05.514798: Epoch 5027 +2024-11-22 14:06:05.514918: Current learning rate: 0.0041 +2024-11-22 14:06:25.111601: train_loss -0.8035 +2024-11-22 14:06:25.111853: val_loss -0.7364 +2024-11-22 14:06:25.111927: Pseudo dice [0.8172] +2024-11-22 14:06:25.112013: Epoch time: 19.6 s +2024-11-22 14:06:26.007565: +2024-11-22 14:06:26.007777: Epoch 5028 +2024-11-22 14:06:26.007894: Current learning rate: 0.0041 +2024-11-22 14:06:44.800149: train_loss -0.8048 +2024-11-22 14:06:44.800376: val_loss -0.736 +2024-11-22 14:06:44.805587: Pseudo dice [0.8139] +2024-11-22 14:06:44.805759: Epoch time: 18.79 s +2024-11-22 14:06:45.900440: +2024-11-22 14:06:45.900639: Epoch 5029 +2024-11-22 14:06:45.900747: Current learning rate: 0.0041 +2024-11-22 14:07:04.924680: train_loss -0.7945 +2024-11-22 14:07:04.924952: val_loss -0.7629 +2024-11-22 14:07:04.925039: Pseudo dice [0.8315] +2024-11-22 14:07:04.925117: Epoch time: 19.03 s +2024-11-22 14:07:06.248889: +2024-11-22 14:07:06.249109: Epoch 5030 +2024-11-22 14:07:06.249223: Current learning rate: 0.0041 +2024-11-22 14:07:24.894104: train_loss -0.7997 +2024-11-22 14:07:24.896550: val_loss -0.7573 +2024-11-22 14:07:24.896655: Pseudo dice [0.8297] +2024-11-22 14:07:24.896743: Epoch time: 18.65 s +2024-11-22 14:07:25.820496: +2024-11-22 14:07:25.820737: Epoch 5031 +2024-11-22 14:07:25.820856: Current learning rate: 0.0041 +2024-11-22 14:07:44.450955: train_loss -0.7888 +2024-11-22 14:07:44.456422: val_loss -0.7538 +2024-11-22 14:07:44.456532: Pseudo dice [0.8312] +2024-11-22 14:07:44.456632: Epoch time: 18.63 s +2024-11-22 14:07:45.489472: +2024-11-22 14:07:45.489692: Epoch 5032 +2024-11-22 14:07:45.489806: Current learning rate: 0.0041 +2024-11-22 14:08:03.313382: train_loss -0.8024 +2024-11-22 14:08:03.317207: val_loss -0.7765 +2024-11-22 14:08:03.317440: Pseudo dice [0.848] +2024-11-22 14:08:03.317526: Epoch time: 17.82 s +2024-11-22 14:08:04.330916: +2024-11-22 14:08:04.331125: Epoch 5033 +2024-11-22 14:08:04.331238: Current learning rate: 0.0041 +2024-11-22 14:08:22.839240: train_loss -0.7954 +2024-11-22 14:08:22.839488: val_loss -0.7355 +2024-11-22 14:08:22.839566: Pseudo dice [0.8316] +2024-11-22 14:08:22.839651: Epoch time: 18.51 s +2024-11-22 14:08:23.940469: +2024-11-22 14:08:23.940713: Epoch 5034 +2024-11-22 14:08:23.940831: Current learning rate: 0.00409 +2024-11-22 14:08:43.230529: train_loss -0.7954 +2024-11-22 14:08:43.232982: val_loss -0.7586 +2024-11-22 14:08:43.233081: Pseudo dice [0.8287] +2024-11-22 14:08:43.233164: Epoch time: 19.29 s +2024-11-22 14:08:44.265189: +2024-11-22 14:08:44.265393: Epoch 5035 +2024-11-22 14:08:44.265510: Current learning rate: 0.00409 +2024-11-22 14:09:00.913530: train_loss -0.7911 +2024-11-22 14:09:00.913779: val_loss -0.7553 +2024-11-22 14:09:00.913859: Pseudo dice [0.8271] +2024-11-22 14:09:00.913960: Epoch time: 16.65 s +2024-11-22 14:09:01.906032: +2024-11-22 14:09:01.906240: Epoch 5036 +2024-11-22 14:09:01.906350: Current learning rate: 0.00409 +2024-11-22 14:09:21.313640: train_loss -0.7924 +2024-11-22 14:09:21.313871: val_loss -0.7619 +2024-11-22 14:09:21.313948: Pseudo dice [0.841] +2024-11-22 14:09:21.314038: Epoch time: 19.41 s +2024-11-22 14:09:22.388379: +2024-11-22 14:09:22.388571: Epoch 5037 +2024-11-22 14:09:22.388688: Current learning rate: 0.00409 +2024-11-22 14:09:40.582903: train_loss -0.7917 +2024-11-22 14:09:40.583230: val_loss -0.7687 +2024-11-22 14:09:40.583441: Pseudo dice [0.8152] +2024-11-22 14:09:40.583531: Epoch time: 18.2 s +2024-11-22 14:09:41.477561: +2024-11-22 14:09:41.477742: Epoch 5038 +2024-11-22 14:09:41.477858: Current learning rate: 0.00409 +2024-11-22 14:10:00.423508: train_loss -0.7898 +2024-11-22 14:10:00.423736: val_loss -0.7292 +2024-11-22 14:10:00.423817: Pseudo dice [0.824] +2024-11-22 14:10:00.442737: Epoch time: 18.95 s +2024-11-22 14:10:01.346918: +2024-11-22 14:10:01.347262: Epoch 5039 +2024-11-22 14:10:01.347373: Current learning rate: 0.00409 +2024-11-22 14:10:19.022450: train_loss -0.7378 +2024-11-22 14:10:19.022660: val_loss -0.7309 +2024-11-22 14:10:19.022736: Pseudo dice [0.8207] +2024-11-22 14:10:19.022814: Epoch time: 17.68 s +2024-11-22 14:10:19.917895: +2024-11-22 14:10:19.918174: Epoch 5040 +2024-11-22 14:10:19.918288: Current learning rate: 0.00409 +2024-11-22 14:10:39.437944: train_loss -0.7664 +2024-11-22 14:10:39.438251: val_loss -0.7406 +2024-11-22 14:10:39.438329: Pseudo dice [0.8098] +2024-11-22 14:10:39.438417: Epoch time: 19.52 s +2024-11-22 14:10:40.335069: +2024-11-22 14:10:40.335263: Epoch 5041 +2024-11-22 14:10:40.335381: Current learning rate: 0.00409 +2024-11-22 14:10:59.162967: train_loss -0.7884 +2024-11-22 14:10:59.163255: val_loss -0.7487 +2024-11-22 14:10:59.163334: Pseudo dice [0.8366] +2024-11-22 14:10:59.163411: Epoch time: 18.83 s +2024-11-22 14:11:00.475145: +2024-11-22 14:11:00.475359: Epoch 5042 +2024-11-22 14:11:00.475475: Current learning rate: 0.00408 +2024-11-22 14:11:18.830512: train_loss -0.7837 +2024-11-22 14:11:18.830746: val_loss -0.7468 +2024-11-22 14:11:18.830835: Pseudo dice [0.8478] +2024-11-22 14:11:18.830917: Epoch time: 18.36 s +2024-11-22 14:11:19.741837: +2024-11-22 14:11:19.742075: Epoch 5043 +2024-11-22 14:11:19.742189: Current learning rate: 0.00408 +2024-11-22 14:11:37.626565: train_loss -0.7778 +2024-11-22 14:11:37.626847: val_loss -0.7451 +2024-11-22 14:11:37.626926: Pseudo dice [0.8203] +2024-11-22 14:11:37.627016: Epoch time: 17.89 s +2024-11-22 14:11:38.632267: +2024-11-22 14:11:38.632490: Epoch 5044 +2024-11-22 14:11:38.632603: Current learning rate: 0.00408 +2024-11-22 14:11:56.941504: train_loss -0.7697 +2024-11-22 14:11:56.941730: val_loss -0.7197 +2024-11-22 14:11:56.941803: Pseudo dice [0.787] +2024-11-22 14:11:56.941878: Epoch time: 18.31 s +2024-11-22 14:11:57.990525: +2024-11-22 14:11:57.990751: Epoch 5045 +2024-11-22 14:11:57.990865: Current learning rate: 0.00408 +2024-11-22 14:12:16.963688: train_loss -0.7786 +2024-11-22 14:12:16.963960: val_loss -0.7299 +2024-11-22 14:12:16.964041: Pseudo dice [0.8017] +2024-11-22 14:12:16.964116: Epoch time: 18.97 s +2024-11-22 14:12:17.861395: +2024-11-22 14:12:17.861618: Epoch 5046 +2024-11-22 14:12:17.861732: Current learning rate: 0.00408 +2024-11-22 14:12:37.530796: train_loss -0.7906 +2024-11-22 14:12:37.531029: val_loss -0.7513 +2024-11-22 14:12:37.531105: Pseudo dice [0.8265] +2024-11-22 14:12:37.531181: Epoch time: 19.67 s +2024-11-22 14:12:38.624714: +2024-11-22 14:12:38.624909: Epoch 5047 +2024-11-22 14:12:38.625030: Current learning rate: 0.00408 +2024-11-22 14:12:57.886765: train_loss -0.7952 +2024-11-22 14:12:57.887014: val_loss -0.7437 +2024-11-22 14:12:57.887093: Pseudo dice [0.8338] +2024-11-22 14:12:57.887180: Epoch time: 19.26 s +2024-11-22 14:12:58.785342: +2024-11-22 14:12:58.785573: Epoch 5048 +2024-11-22 14:12:58.785685: Current learning rate: 0.00408 +2024-11-22 14:13:17.699103: train_loss -0.7838 +2024-11-22 14:13:17.699322: val_loss -0.7655 +2024-11-22 14:13:17.699399: Pseudo dice [0.816] +2024-11-22 14:13:17.699522: Epoch time: 18.91 s +2024-11-22 14:13:18.590686: +2024-11-22 14:13:18.590875: Epoch 5049 +2024-11-22 14:13:18.590985: Current learning rate: 0.00408 +2024-11-22 14:13:37.180716: train_loss -0.7995 +2024-11-22 14:13:37.180967: val_loss -0.723 +2024-11-22 14:13:37.181047: Pseudo dice [0.8172] +2024-11-22 14:13:37.181125: Epoch time: 18.59 s +2024-11-22 14:13:38.353626: +2024-11-22 14:13:38.353822: Epoch 5050 +2024-11-22 14:13:38.353928: Current learning rate: 0.00407 +2024-11-22 14:13:56.095357: train_loss -0.7922 +2024-11-22 14:13:56.095578: val_loss -0.7454 +2024-11-22 14:13:56.095709: Pseudo dice [0.8235] +2024-11-22 14:13:56.095818: Epoch time: 17.74 s +2024-11-22 14:13:56.990357: +2024-11-22 14:13:56.990568: Epoch 5051 +2024-11-22 14:13:56.990679: Current learning rate: 0.00407 +2024-11-22 14:14:15.260929: train_loss -0.7965 +2024-11-22 14:14:15.292020: val_loss -0.76 +2024-11-22 14:14:15.292186: Pseudo dice [0.8278] +2024-11-22 14:14:15.292300: Epoch time: 18.27 s +2024-11-22 14:14:16.216604: +2024-11-22 14:14:16.216793: Epoch 5052 +2024-11-22 14:14:16.216897: Current learning rate: 0.00407 +2024-11-22 14:14:34.363169: train_loss -0.804 +2024-11-22 14:14:34.363390: val_loss -0.7237 +2024-11-22 14:14:34.363466: Pseudo dice [0.8001] +2024-11-22 14:14:34.363545: Epoch time: 18.15 s +2024-11-22 14:14:35.253903: +2024-11-22 14:14:35.254094: Epoch 5053 +2024-11-22 14:14:35.254205: Current learning rate: 0.00407 +2024-11-22 14:14:53.365514: train_loss -0.7873 +2024-11-22 14:14:53.366001: val_loss -0.7444 +2024-11-22 14:14:53.366102: Pseudo dice [0.8318] +2024-11-22 14:14:53.366179: Epoch time: 18.11 s +2024-11-22 14:14:54.256047: +2024-11-22 14:14:54.256254: Epoch 5054 +2024-11-22 14:14:54.256368: Current learning rate: 0.00407 +2024-11-22 14:15:11.900446: train_loss -0.8015 +2024-11-22 14:15:11.900667: val_loss -0.7701 +2024-11-22 14:15:11.900745: Pseudo dice [0.8463] +2024-11-22 14:15:11.900825: Epoch time: 17.65 s +2024-11-22 14:15:12.976202: +2024-11-22 14:15:12.976407: Epoch 5055 +2024-11-22 14:15:12.976519: Current learning rate: 0.00407 +2024-11-22 14:15:32.609826: train_loss -0.7948 +2024-11-22 14:15:32.610076: val_loss -0.7341 +2024-11-22 14:15:32.610152: Pseudo dice [0.8284] +2024-11-22 14:15:32.610233: Epoch time: 19.63 s +2024-11-22 14:15:33.507827: +2024-11-22 14:15:33.508128: Epoch 5056 +2024-11-22 14:15:33.508240: Current learning rate: 0.00407 +2024-11-22 14:15:52.550694: train_loss -0.795 +2024-11-22 14:15:52.550982: val_loss -0.7612 +2024-11-22 14:15:52.551068: Pseudo dice [0.82] +2024-11-22 14:15:52.551147: Epoch time: 19.04 s +2024-11-22 14:15:53.448040: +2024-11-22 14:15:53.448302: Epoch 5057 +2024-11-22 14:15:53.448422: Current learning rate: 0.00407 +2024-11-22 14:16:12.126837: train_loss -0.791 +2024-11-22 14:16:12.129735: val_loss -0.742 +2024-11-22 14:16:12.129883: Pseudo dice [0.8315] +2024-11-22 14:16:12.129966: Epoch time: 18.68 s +2024-11-22 14:16:13.163020: +2024-11-22 14:16:13.163220: Epoch 5058 +2024-11-22 14:16:13.163334: Current learning rate: 0.00406 +2024-11-22 14:16:32.789264: train_loss -0.7985 +2024-11-22 14:16:32.789487: val_loss -0.7397 +2024-11-22 14:16:32.789561: Pseudo dice [0.8337] +2024-11-22 14:16:32.789642: Epoch time: 19.63 s +2024-11-22 14:16:33.686455: +2024-11-22 14:16:33.686661: Epoch 5059 +2024-11-22 14:16:33.686774: Current learning rate: 0.00406 +2024-11-22 14:16:53.251150: train_loss -0.7877 +2024-11-22 14:16:53.251407: val_loss -0.7468 +2024-11-22 14:16:53.251524: Pseudo dice [0.8196] +2024-11-22 14:16:53.251608: Epoch time: 19.57 s +2024-11-22 14:16:54.144460: +2024-11-22 14:16:54.144654: Epoch 5060 +2024-11-22 14:16:54.144767: Current learning rate: 0.00406 +2024-11-22 14:17:12.217150: train_loss -0.7954 +2024-11-22 14:17:12.217368: val_loss -0.7533 +2024-11-22 14:17:12.217444: Pseudo dice [0.8137] +2024-11-22 14:17:12.217521: Epoch time: 18.07 s +2024-11-22 14:17:13.104359: +2024-11-22 14:17:13.104577: Epoch 5061 +2024-11-22 14:17:13.104689: Current learning rate: 0.00406 +2024-11-22 14:17:30.522409: train_loss -0.8068 +2024-11-22 14:17:30.526639: val_loss -0.751 +2024-11-22 14:17:30.526755: Pseudo dice [0.8186] +2024-11-22 14:17:30.526834: Epoch time: 17.42 s +2024-11-22 14:17:31.427399: +2024-11-22 14:17:31.427628: Epoch 5062 +2024-11-22 14:17:31.427742: Current learning rate: 0.00406 +2024-11-22 14:17:49.731225: train_loss -0.7946 +2024-11-22 14:17:49.731475: val_loss -0.7375 +2024-11-22 14:17:49.731551: Pseudo dice [0.8085] +2024-11-22 14:17:49.731675: Epoch time: 18.3 s +2024-11-22 14:17:50.627395: +2024-11-22 14:17:50.627578: Epoch 5063 +2024-11-22 14:17:50.627695: Current learning rate: 0.00406 +2024-11-22 14:18:09.602144: train_loss -0.803 +2024-11-22 14:18:09.604676: val_loss -0.7429 +2024-11-22 14:18:09.604779: Pseudo dice [0.8336] +2024-11-22 14:18:09.604904: Epoch time: 18.98 s +2024-11-22 14:18:10.505378: +2024-11-22 14:18:10.505579: Epoch 5064 +2024-11-22 14:18:10.505699: Current learning rate: 0.00406 +2024-11-22 14:18:28.568784: train_loss -0.8095 +2024-11-22 14:18:28.569006: val_loss -0.7554 +2024-11-22 14:18:28.569083: Pseudo dice [0.829] +2024-11-22 14:18:28.569160: Epoch time: 18.06 s +2024-11-22 14:18:29.853380: +2024-11-22 14:18:29.853740: Epoch 5065 +2024-11-22 14:18:29.853869: Current learning rate: 0.00406 +2024-11-22 14:18:47.658784: train_loss -0.8036 +2024-11-22 14:18:47.659042: val_loss -0.7397 +2024-11-22 14:18:47.659119: Pseudo dice [0.8207] +2024-11-22 14:18:47.659203: Epoch time: 17.81 s +2024-11-22 14:18:48.546013: +2024-11-22 14:18:48.546220: Epoch 5066 +2024-11-22 14:18:48.546333: Current learning rate: 0.00405 +2024-11-22 14:19:07.603487: train_loss -0.8087 +2024-11-22 14:19:07.603716: val_loss -0.7667 +2024-11-22 14:19:07.603798: Pseudo dice [0.8324] +2024-11-22 14:19:07.603873: Epoch time: 19.06 s +2024-11-22 14:19:08.506669: +2024-11-22 14:19:08.506893: Epoch 5067 +2024-11-22 14:19:08.507012: Current learning rate: 0.00405 +2024-11-22 14:19:27.267162: train_loss -0.8005 +2024-11-22 14:19:27.267383: val_loss -0.7669 +2024-11-22 14:19:27.267599: Pseudo dice [0.8477] +2024-11-22 14:19:27.267683: Epoch time: 18.76 s +2024-11-22 14:19:28.161420: +2024-11-22 14:19:28.161640: Epoch 5068 +2024-11-22 14:19:28.161756: Current learning rate: 0.00405 +2024-11-22 14:19:46.723942: train_loss -0.794 +2024-11-22 14:19:46.724177: val_loss -0.7621 +2024-11-22 14:19:46.724254: Pseudo dice [0.8331] +2024-11-22 14:19:46.724337: Epoch time: 18.56 s +2024-11-22 14:19:47.614739: +2024-11-22 14:19:47.615017: Epoch 5069 +2024-11-22 14:19:47.615130: Current learning rate: 0.00405 +2024-11-22 14:20:06.065520: train_loss -0.8019 +2024-11-22 14:20:06.065754: val_loss -0.7607 +2024-11-22 14:20:06.065829: Pseudo dice [0.8479] +2024-11-22 14:20:06.065984: Epoch time: 18.45 s +2024-11-22 14:20:06.957678: +2024-11-22 14:20:06.957899: Epoch 5070 +2024-11-22 14:20:06.958014: Current learning rate: 0.00405 +2024-11-22 14:20:25.947867: train_loss -0.7985 +2024-11-22 14:20:25.950286: val_loss -0.7561 +2024-11-22 14:20:25.950374: Pseudo dice [0.8259] +2024-11-22 14:20:25.950455: Epoch time: 18.99 s +2024-11-22 14:20:26.869749: +2024-11-22 14:20:26.869965: Epoch 5071 +2024-11-22 14:20:26.870084: Current learning rate: 0.00405 +2024-11-22 14:20:46.178832: train_loss -0.7995 +2024-11-22 14:20:46.179057: val_loss -0.7654 +2024-11-22 14:20:46.179135: Pseudo dice [0.8413] +2024-11-22 14:20:46.179212: Epoch time: 19.31 s +2024-11-22 14:20:47.070682: +2024-11-22 14:20:47.070947: Epoch 5072 +2024-11-22 14:20:47.071074: Current learning rate: 0.00405 +2024-11-22 14:21:05.656024: train_loss -0.7935 +2024-11-22 14:21:05.656273: val_loss -0.7434 +2024-11-22 14:21:05.656348: Pseudo dice [0.8319] +2024-11-22 14:21:05.656433: Epoch time: 18.59 s +2024-11-22 14:21:06.555143: +2024-11-22 14:21:06.555353: Epoch 5073 +2024-11-22 14:21:06.555463: Current learning rate: 0.00405 +2024-11-22 14:21:25.911232: train_loss -0.8008 +2024-11-22 14:21:25.911453: val_loss -0.7362 +2024-11-22 14:21:25.911530: Pseudo dice [0.8171] +2024-11-22 14:21:25.911611: Epoch time: 19.36 s +2024-11-22 14:21:26.806959: +2024-11-22 14:21:26.807225: Epoch 5074 +2024-11-22 14:21:26.807342: Current learning rate: 0.00404 +2024-11-22 14:21:46.091258: train_loss -0.7993 +2024-11-22 14:21:46.091466: val_loss -0.7613 +2024-11-22 14:21:46.091539: Pseudo dice [0.8309] +2024-11-22 14:21:46.091613: Epoch time: 19.29 s +2024-11-22 14:21:46.999170: +2024-11-22 14:21:46.999431: Epoch 5075 +2024-11-22 14:21:46.999557: Current learning rate: 0.00404 +2024-11-22 14:22:05.600040: train_loss -0.8021 +2024-11-22 14:22:05.600342: val_loss -0.7546 +2024-11-22 14:22:05.600428: Pseudo dice [0.8364] +2024-11-22 14:22:05.600507: Epoch time: 18.6 s +2024-11-22 14:22:06.498349: +2024-11-22 14:22:06.498537: Epoch 5076 +2024-11-22 14:22:06.498652: Current learning rate: 0.00404 +2024-11-22 14:22:25.397793: train_loss -0.803 +2024-11-22 14:22:25.398037: val_loss -0.747 +2024-11-22 14:22:25.400290: Pseudo dice [0.8262] +2024-11-22 14:22:25.400387: Epoch time: 18.9 s +2024-11-22 14:22:26.692532: +2024-11-22 14:22:26.692775: Epoch 5077 +2024-11-22 14:22:26.692894: Current learning rate: 0.00404 +2024-11-22 14:22:45.576566: train_loss -0.8021 +2024-11-22 14:22:45.580069: val_loss -0.7563 +2024-11-22 14:22:45.580189: Pseudo dice [0.8229] +2024-11-22 14:22:45.580270: Epoch time: 18.88 s +2024-11-22 14:22:46.506115: +2024-11-22 14:22:46.506337: Epoch 5078 +2024-11-22 14:22:46.506450: Current learning rate: 0.00404 +2024-11-22 14:23:05.272678: train_loss -0.8048 +2024-11-22 14:23:05.275117: val_loss -0.7232 +2024-11-22 14:23:05.275210: Pseudo dice [0.8112] +2024-11-22 14:23:05.275287: Epoch time: 18.77 s +2024-11-22 14:23:06.194910: +2024-11-22 14:23:06.195202: Epoch 5079 +2024-11-22 14:23:06.195321: Current learning rate: 0.00404 +2024-11-22 14:23:24.730010: train_loss -0.8028 +2024-11-22 14:23:24.730257: val_loss -0.7161 +2024-11-22 14:23:24.730334: Pseudo dice [0.8149] +2024-11-22 14:23:24.730419: Epoch time: 18.54 s +2024-11-22 14:23:25.625969: +2024-11-22 14:23:25.626217: Epoch 5080 +2024-11-22 14:23:25.626334: Current learning rate: 0.00404 +2024-11-22 14:23:43.143626: train_loss -0.7995 +2024-11-22 14:23:43.143837: val_loss -0.7675 +2024-11-22 14:23:43.143912: Pseudo dice [0.848] +2024-11-22 14:23:43.143988: Epoch time: 17.52 s +2024-11-22 14:23:44.034663: +2024-11-22 14:23:44.034862: Epoch 5081 +2024-11-22 14:23:44.034976: Current learning rate: 0.00404 +2024-11-22 14:24:02.479429: train_loss -0.8021 +2024-11-22 14:24:02.479655: val_loss -0.7578 +2024-11-22 14:24:02.479731: Pseudo dice [0.8421] +2024-11-22 14:24:02.479812: Epoch time: 18.45 s +2024-11-22 14:24:03.406618: +2024-11-22 14:24:03.406878: Epoch 5082 +2024-11-22 14:24:03.407002: Current learning rate: 0.00403 +2024-11-22 14:24:22.368100: train_loss -0.7929 +2024-11-22 14:24:22.368305: val_loss -0.7702 +2024-11-22 14:24:22.368378: Pseudo dice [0.8244] +2024-11-22 14:24:22.368454: Epoch time: 18.96 s +2024-11-22 14:24:23.258843: +2024-11-22 14:24:23.259059: Epoch 5083 +2024-11-22 14:24:23.259176: Current learning rate: 0.00403 +2024-11-22 14:24:42.124623: train_loss -0.8008 +2024-11-22 14:24:42.124870: val_loss -0.7248 +2024-11-22 14:24:42.124947: Pseudo dice [0.8412] +2024-11-22 14:24:42.125036: Epoch time: 18.87 s +2024-11-22 14:24:43.021986: +2024-11-22 14:24:43.022278: Epoch 5084 +2024-11-22 14:24:43.022390: Current learning rate: 0.00403 +2024-11-22 14:25:01.027229: train_loss -0.8031 +2024-11-22 14:25:01.027447: val_loss -0.7363 +2024-11-22 14:25:01.027519: Pseudo dice [0.8353] +2024-11-22 14:25:01.027596: Epoch time: 18.01 s +2024-11-22 14:25:01.924608: +2024-11-22 14:25:01.924924: Epoch 5085 +2024-11-22 14:25:01.925044: Current learning rate: 0.00403 +2024-11-22 14:25:20.220752: train_loss -0.7953 +2024-11-22 14:25:20.220958: val_loss -0.7328 +2024-11-22 14:25:20.221038: Pseudo dice [0.8158] +2024-11-22 14:25:20.221114: Epoch time: 18.3 s +2024-11-22 14:25:21.118362: +2024-11-22 14:25:21.118563: Epoch 5086 +2024-11-22 14:25:21.118677: Current learning rate: 0.00403 +2024-11-22 14:25:38.461777: train_loss -0.7959 +2024-11-22 14:25:38.467208: val_loss -0.7326 +2024-11-22 14:25:38.467319: Pseudo dice [0.8326] +2024-11-22 14:25:38.467406: Epoch time: 17.34 s +2024-11-22 14:25:39.575897: +2024-11-22 14:25:39.576156: Epoch 5087 +2024-11-22 14:25:39.576267: Current learning rate: 0.00403 +2024-11-22 14:25:58.743366: train_loss -0.7722 +2024-11-22 14:25:58.743597: val_loss -0.7702 +2024-11-22 14:25:58.743668: Pseudo dice [0.8387] +2024-11-22 14:25:58.743748: Epoch time: 19.17 s +2024-11-22 14:25:59.647997: +2024-11-22 14:25:59.648471: Epoch 5088 +2024-11-22 14:25:59.648614: Current learning rate: 0.00403 +2024-11-22 14:26:18.397017: train_loss -0.7862 +2024-11-22 14:26:18.397260: val_loss -0.7162 +2024-11-22 14:26:18.397334: Pseudo dice [0.8249] +2024-11-22 14:26:18.397413: Epoch time: 18.75 s +2024-11-22 14:26:19.729851: +2024-11-22 14:26:19.730074: Epoch 5089 +2024-11-22 14:26:19.730186: Current learning rate: 0.00403 +2024-11-22 14:26:38.796471: train_loss -0.7708 +2024-11-22 14:26:38.796834: val_loss -0.7326 +2024-11-22 14:26:38.813660: Pseudo dice [0.8402] +2024-11-22 14:26:38.813845: Epoch time: 19.07 s +2024-11-22 14:26:39.711933: +2024-11-22 14:26:39.712153: Epoch 5090 +2024-11-22 14:26:39.712268: Current learning rate: 0.00402 +2024-11-22 14:26:57.402337: train_loss -0.7695 +2024-11-22 14:26:57.402580: val_loss -0.7504 +2024-11-22 14:26:57.402655: Pseudo dice [0.8311] +2024-11-22 14:26:57.402735: Epoch time: 17.69 s +2024-11-22 14:26:58.298288: +2024-11-22 14:26:58.298523: Epoch 5091 +2024-11-22 14:26:58.298640: Current learning rate: 0.00402 +2024-11-22 14:27:16.348702: train_loss -0.7738 +2024-11-22 14:27:16.348921: val_loss -0.7408 +2024-11-22 14:27:16.349005: Pseudo dice [0.809] +2024-11-22 14:27:16.349080: Epoch time: 18.05 s +2024-11-22 14:27:17.239498: +2024-11-22 14:27:17.239711: Epoch 5092 +2024-11-22 14:27:17.239828: Current learning rate: 0.00402 +2024-11-22 14:27:36.551196: train_loss -0.7793 +2024-11-22 14:27:36.551410: val_loss -0.724 +2024-11-22 14:27:36.551487: Pseudo dice [0.8273] +2024-11-22 14:27:36.551564: Epoch time: 19.31 s +2024-11-22 14:27:37.439855: +2024-11-22 14:27:37.440059: Epoch 5093 +2024-11-22 14:27:37.440171: Current learning rate: 0.00402 +2024-11-22 14:27:55.891711: train_loss -0.7852 +2024-11-22 14:27:55.891962: val_loss -0.7363 +2024-11-22 14:27:55.892045: Pseudo dice [0.838] +2024-11-22 14:27:55.892136: Epoch time: 18.45 s +2024-11-22 14:27:56.787356: +2024-11-22 14:27:56.787611: Epoch 5094 +2024-11-22 14:27:56.787731: Current learning rate: 0.00402 +2024-11-22 14:28:15.186406: train_loss -0.7906 +2024-11-22 14:28:15.193257: val_loss -0.7297 +2024-11-22 14:28:15.193388: Pseudo dice [0.8207] +2024-11-22 14:28:15.193471: Epoch time: 18.4 s +2024-11-22 14:28:16.200319: +2024-11-22 14:28:16.200540: Epoch 5095 +2024-11-22 14:28:16.200654: Current learning rate: 0.00402 +2024-11-22 14:28:34.376387: train_loss -0.7863 +2024-11-22 14:28:34.376609: val_loss -0.7416 +2024-11-22 14:28:34.376689: Pseudo dice [0.8254] +2024-11-22 14:28:34.376772: Epoch time: 18.18 s +2024-11-22 14:28:35.273206: +2024-11-22 14:28:35.273407: Epoch 5096 +2024-11-22 14:28:35.273525: Current learning rate: 0.00402 +2024-11-22 14:28:53.829539: train_loss -0.789 +2024-11-22 14:28:53.829759: val_loss -0.7526 +2024-11-22 14:28:53.829837: Pseudo dice [0.8355] +2024-11-22 14:28:53.829921: Epoch time: 18.56 s +2024-11-22 14:28:54.742532: +2024-11-22 14:28:54.742801: Epoch 5097 +2024-11-22 14:28:54.742914: Current learning rate: 0.00402 +2024-11-22 14:29:12.492981: train_loss -0.7956 +2024-11-22 14:29:12.493230: val_loss -0.7435 +2024-11-22 14:29:12.493314: Pseudo dice [0.8164] +2024-11-22 14:29:12.493397: Epoch time: 17.75 s +2024-11-22 14:29:13.388237: +2024-11-22 14:29:13.388435: Epoch 5098 +2024-11-22 14:29:13.388551: Current learning rate: 0.00401 +2024-11-22 14:29:32.143031: train_loss -0.7938 +2024-11-22 14:29:32.143273: val_loss -0.7569 +2024-11-22 14:29:32.143352: Pseudo dice [0.8322] +2024-11-22 14:29:32.143432: Epoch time: 18.76 s +2024-11-22 14:29:33.124532: +2024-11-22 14:29:33.124718: Epoch 5099 +2024-11-22 14:29:33.124832: Current learning rate: 0.00401 +2024-11-22 14:29:52.414884: train_loss -0.7929 +2024-11-22 14:29:52.417278: val_loss -0.7462 +2024-11-22 14:29:52.417365: Pseudo dice [0.8298] +2024-11-22 14:29:52.417441: Epoch time: 19.29 s +2024-11-22 14:29:53.668425: +2024-11-22 14:29:53.668914: Epoch 5100 +2024-11-22 14:29:53.669052: Current learning rate: 0.00401 +2024-11-22 14:30:13.164383: train_loss -0.7976 +2024-11-22 14:30:13.164889: val_loss -0.7603 +2024-11-22 14:30:13.164988: Pseudo dice [0.831] +2024-11-22 14:30:13.165074: Epoch time: 19.5 s +2024-11-22 14:30:14.066683: +2024-11-22 14:30:14.066978: Epoch 5101 +2024-11-22 14:30:14.067101: Current learning rate: 0.00401 +2024-11-22 14:30:33.029122: train_loss -0.7945 +2024-11-22 14:30:33.029354: val_loss -0.7298 +2024-11-22 14:30:33.029433: Pseudo dice [0.8175] +2024-11-22 14:30:33.029511: Epoch time: 18.96 s +2024-11-22 14:30:33.915953: +2024-11-22 14:30:33.916187: Epoch 5102 +2024-11-22 14:30:33.916298: Current learning rate: 0.00401 +2024-11-22 14:30:52.335609: train_loss -0.796 +2024-11-22 14:30:52.335881: val_loss -0.7744 +2024-11-22 14:30:52.335960: Pseudo dice [0.8404] +2024-11-22 14:30:52.336045: Epoch time: 18.42 s +2024-11-22 14:30:53.229150: +2024-11-22 14:30:53.229387: Epoch 5103 +2024-11-22 14:30:53.229501: Current learning rate: 0.00401 +2024-11-22 14:31:10.657777: train_loss -0.8032 +2024-11-22 14:31:10.658054: val_loss -0.7455 +2024-11-22 14:31:10.658131: Pseudo dice [0.8403] +2024-11-22 14:31:10.658218: Epoch time: 17.43 s +2024-11-22 14:31:11.604866: +2024-11-22 14:31:11.605151: Epoch 5104 +2024-11-22 14:31:11.605270: Current learning rate: 0.00401 +2024-11-22 14:31:31.312496: train_loss -0.802 +2024-11-22 14:31:31.312707: val_loss -0.7373 +2024-11-22 14:31:31.312781: Pseudo dice [0.8336] +2024-11-22 14:31:31.312859: Epoch time: 19.71 s +2024-11-22 14:31:32.211806: +2024-11-22 14:31:32.212020: Epoch 5105 +2024-11-22 14:31:32.212132: Current learning rate: 0.00401 +2024-11-22 14:31:50.442334: train_loss -0.796 +2024-11-22 14:31:50.442552: val_loss -0.7622 +2024-11-22 14:31:50.442632: Pseudo dice [0.8322] +2024-11-22 14:31:50.442713: Epoch time: 18.23 s +2024-11-22 14:31:51.338128: +2024-11-22 14:31:51.338340: Epoch 5106 +2024-11-22 14:31:51.338493: Current learning rate: 0.004 +2024-11-22 14:32:10.089588: train_loss -0.7998 +2024-11-22 14:32:10.089810: val_loss -0.7496 +2024-11-22 14:32:10.089884: Pseudo dice [0.8218] +2024-11-22 14:32:10.089959: Epoch time: 18.75 s +2024-11-22 14:32:10.981738: +2024-11-22 14:32:10.982012: Epoch 5107 +2024-11-22 14:32:10.982126: Current learning rate: 0.004 +2024-11-22 14:32:29.927470: train_loss -0.8078 +2024-11-22 14:32:29.927718: val_loss -0.7693 +2024-11-22 14:32:29.927851: Pseudo dice [0.8268] +2024-11-22 14:32:29.927941: Epoch time: 18.95 s +2024-11-22 14:32:30.823035: +2024-11-22 14:32:30.823250: Epoch 5108 +2024-11-22 14:32:30.823364: Current learning rate: 0.004 +2024-11-22 14:32:50.407397: train_loss -0.7978 +2024-11-22 14:32:50.407713: val_loss -0.7735 +2024-11-22 14:32:50.407795: Pseudo dice [0.8365] +2024-11-22 14:32:50.407871: Epoch time: 19.59 s +2024-11-22 14:32:51.302297: +2024-11-22 14:32:51.302492: Epoch 5109 +2024-11-22 14:32:51.302600: Current learning rate: 0.004 +2024-11-22 14:33:09.793295: train_loss -0.8071 +2024-11-22 14:33:09.793520: val_loss -0.7743 +2024-11-22 14:33:09.793594: Pseudo dice [0.848] +2024-11-22 14:33:09.793672: Epoch time: 18.49 s +2024-11-22 14:33:10.731879: +2024-11-22 14:33:10.732098: Epoch 5110 +2024-11-22 14:33:10.732208: Current learning rate: 0.004 +2024-11-22 14:33:30.188696: train_loss -0.8066 +2024-11-22 14:33:30.188905: val_loss -0.7616 +2024-11-22 14:33:30.188985: Pseudo dice [0.8281] +2024-11-22 14:33:30.189066: Epoch time: 19.46 s +2024-11-22 14:33:31.081574: +2024-11-22 14:33:31.081785: Epoch 5111 +2024-11-22 14:33:31.081902: Current learning rate: 0.004 +2024-11-22 14:33:50.403566: train_loss -0.8022 +2024-11-22 14:33:50.403821: val_loss -0.7443 +2024-11-22 14:33:50.403894: Pseudo dice [0.8094] +2024-11-22 14:33:50.403980: Epoch time: 19.32 s +2024-11-22 14:33:51.699312: +2024-11-22 14:33:51.699518: Epoch 5112 +2024-11-22 14:33:51.699630: Current learning rate: 0.004 +2024-11-22 14:34:10.681436: train_loss -0.8053 +2024-11-22 14:34:10.681666: val_loss -0.7717 +2024-11-22 14:34:10.681738: Pseudo dice [0.8389] +2024-11-22 14:34:10.681813: Epoch time: 18.98 s +2024-11-22 14:34:11.574369: +2024-11-22 14:34:11.574629: Epoch 5113 +2024-11-22 14:34:11.574743: Current learning rate: 0.004 +2024-11-22 14:34:29.329121: train_loss -0.8013 +2024-11-22 14:34:29.329342: val_loss -0.7545 +2024-11-22 14:34:29.329495: Pseudo dice [0.826] +2024-11-22 14:34:29.329576: Epoch time: 17.76 s +2024-11-22 14:34:30.232352: +2024-11-22 14:34:30.232559: Epoch 5114 +2024-11-22 14:34:30.232675: Current learning rate: 0.00399 +2024-11-22 14:34:48.629303: train_loss -0.7929 +2024-11-22 14:34:48.629544: val_loss -0.7724 +2024-11-22 14:34:48.629648: Pseudo dice [0.8425] +2024-11-22 14:34:48.629725: Epoch time: 18.4 s +2024-11-22 14:34:49.526259: +2024-11-22 14:34:49.544365: Epoch 5115 +2024-11-22 14:34:49.544554: Current learning rate: 0.00399 +2024-11-22 14:35:07.786548: train_loss -0.7979 +2024-11-22 14:35:07.787032: val_loss -0.7493 +2024-11-22 14:35:07.787123: Pseudo dice [0.8336] +2024-11-22 14:35:07.787205: Epoch time: 18.26 s +2024-11-22 14:35:08.701572: +2024-11-22 14:35:08.701776: Epoch 5116 +2024-11-22 14:35:08.701889: Current learning rate: 0.00399 +2024-11-22 14:35:27.052489: train_loss -0.8009 +2024-11-22 14:35:27.052733: val_loss -0.752 +2024-11-22 14:35:27.052812: Pseudo dice [0.8201] +2024-11-22 14:35:27.052892: Epoch time: 18.35 s +2024-11-22 14:35:27.942317: +2024-11-22 14:35:27.942515: Epoch 5117 +2024-11-22 14:35:27.942627: Current learning rate: 0.00399 +2024-11-22 14:35:46.496428: train_loss -0.8064 +2024-11-22 14:35:46.496653: val_loss -0.7219 +2024-11-22 14:35:46.496728: Pseudo dice [0.8489] +2024-11-22 14:35:46.496867: Epoch time: 18.55 s +2024-11-22 14:35:47.421851: +2024-11-22 14:35:47.422053: Epoch 5118 +2024-11-22 14:35:47.422166: Current learning rate: 0.00399 +2024-11-22 14:36:05.197734: train_loss -0.8022 +2024-11-22 14:36:05.197977: val_loss -0.7553 +2024-11-22 14:36:05.198061: Pseudo dice [0.8312] +2024-11-22 14:36:05.198151: Epoch time: 17.78 s +2024-11-22 14:36:06.093834: +2024-11-22 14:36:06.094058: Epoch 5119 +2024-11-22 14:36:06.094174: Current learning rate: 0.00399 +2024-11-22 14:36:25.049273: train_loss -0.8047 +2024-11-22 14:36:25.049495: val_loss -0.7327 +2024-11-22 14:36:25.049569: Pseudo dice [0.8272] +2024-11-22 14:36:25.049647: Epoch time: 18.96 s +2024-11-22 14:36:25.957995: +2024-11-22 14:36:25.958208: Epoch 5120 +2024-11-22 14:36:25.958325: Current learning rate: 0.00399 +2024-11-22 14:36:44.376905: train_loss -0.7992 +2024-11-22 14:36:44.377136: val_loss -0.7742 +2024-11-22 14:36:44.377294: Pseudo dice [0.8375] +2024-11-22 14:36:44.377371: Epoch time: 18.42 s +2024-11-22 14:36:45.276121: +2024-11-22 14:36:45.276304: Epoch 5121 +2024-11-22 14:36:45.276411: Current learning rate: 0.00399 +2024-11-22 14:37:04.681007: train_loss -0.7959 +2024-11-22 14:37:04.681238: val_loss -0.7539 +2024-11-22 14:37:04.681316: Pseudo dice [0.8372] +2024-11-22 14:37:04.681400: Epoch time: 19.41 s +2024-11-22 14:37:05.573796: +2024-11-22 14:37:05.574143: Epoch 5122 +2024-11-22 14:37:05.574253: Current learning rate: 0.00398 +2024-11-22 14:37:23.260563: train_loss -0.8068 +2024-11-22 14:37:23.260798: val_loss -0.7713 +2024-11-22 14:37:23.260875: Pseudo dice [0.8362] +2024-11-22 14:37:23.260956: Epoch time: 17.69 s +2024-11-22 14:37:24.151305: +2024-11-22 14:37:24.151513: Epoch 5123 +2024-11-22 14:37:24.151628: Current learning rate: 0.00398 +2024-11-22 14:37:41.861836: train_loss -0.7957 +2024-11-22 14:37:41.862121: val_loss -0.7602 +2024-11-22 14:37:41.862196: Pseudo dice [0.8403] +2024-11-22 14:37:41.862271: Epoch time: 17.71 s +2024-11-22 14:37:43.060951: +2024-11-22 14:37:43.061179: Epoch 5124 +2024-11-22 14:37:43.061290: Current learning rate: 0.00398 +2024-11-22 14:38:02.391322: train_loss -0.7952 +2024-11-22 14:38:02.393710: val_loss -0.7479 +2024-11-22 14:38:02.393825: Pseudo dice [0.8163] +2024-11-22 14:38:02.393903: Epoch time: 19.33 s +2024-11-22 14:38:03.335204: +2024-11-22 14:38:03.335490: Epoch 5125 +2024-11-22 14:38:03.335612: Current learning rate: 0.00398 +2024-11-22 14:38:21.663965: train_loss -0.7996 +2024-11-22 14:38:21.664194: val_loss -0.7536 +2024-11-22 14:38:21.664269: Pseudo dice [0.8407] +2024-11-22 14:38:21.664352: Epoch time: 18.33 s +2024-11-22 14:38:22.550715: +2024-11-22 14:38:22.550940: Epoch 5126 +2024-11-22 14:38:22.551061: Current learning rate: 0.00398 +2024-11-22 14:38:41.592300: train_loss -0.807 +2024-11-22 14:38:41.592511: val_loss -0.7534 +2024-11-22 14:38:41.592582: Pseudo dice [0.8444] +2024-11-22 14:38:41.592655: Epoch time: 19.04 s +2024-11-22 14:38:42.589853: +2024-11-22 14:38:42.590069: Epoch 5127 +2024-11-22 14:38:42.590184: Current learning rate: 0.00398 +2024-11-22 14:39:00.818940: train_loss -0.7988 +2024-11-22 14:39:00.823111: val_loss -0.7541 +2024-11-22 14:39:00.823304: Pseudo dice [0.8292] +2024-11-22 14:39:00.824019: Epoch time: 18.23 s +2024-11-22 14:39:01.764699: +2024-11-22 14:39:01.764949: Epoch 5128 +2024-11-22 14:39:01.765073: Current learning rate: 0.00398 +2024-11-22 14:39:19.810286: train_loss -0.7984 +2024-11-22 14:39:19.810511: val_loss -0.7514 +2024-11-22 14:39:19.810585: Pseudo dice [0.8155] +2024-11-22 14:39:19.810664: Epoch time: 18.05 s +2024-11-22 14:39:20.691298: +2024-11-22 14:39:20.691522: Epoch 5129 +2024-11-22 14:39:20.691632: Current learning rate: 0.00398 +2024-11-22 14:39:38.677545: train_loss -0.8045 +2024-11-22 14:39:38.677786: val_loss -0.7376 +2024-11-22 14:39:38.677859: Pseudo dice [0.8355] +2024-11-22 14:39:38.677946: Epoch time: 17.99 s +2024-11-22 14:39:39.628747: +2024-11-22 14:39:39.628977: Epoch 5130 +2024-11-22 14:39:39.629095: Current learning rate: 0.00397 +2024-11-22 14:39:58.151022: train_loss -0.7956 +2024-11-22 14:39:58.151235: val_loss -0.7485 +2024-11-22 14:39:58.151314: Pseudo dice [0.8243] +2024-11-22 14:39:58.151389: Epoch time: 18.52 s +2024-11-22 14:39:59.108953: +2024-11-22 14:39:59.109173: Epoch 5131 +2024-11-22 14:39:59.109291: Current learning rate: 0.00397 +2024-11-22 14:40:17.860636: train_loss -0.8006 +2024-11-22 14:40:17.860854: val_loss -0.7869 +2024-11-22 14:40:17.860929: Pseudo dice [0.8425] +2024-11-22 14:40:17.861019: Epoch time: 18.75 s +2024-11-22 14:40:18.907547: +2024-11-22 14:40:18.907762: Epoch 5132 +2024-11-22 14:40:18.907878: Current learning rate: 0.00397 +2024-11-22 14:40:36.750988: train_loss -0.8091 +2024-11-22 14:40:36.751224: val_loss -0.7377 +2024-11-22 14:40:36.751304: Pseudo dice [0.8187] +2024-11-22 14:40:36.751394: Epoch time: 17.84 s +2024-11-22 14:40:37.869103: +2024-11-22 14:40:37.869302: Epoch 5133 +2024-11-22 14:40:37.869410: Current learning rate: 0.00397 +2024-11-22 14:40:57.250110: train_loss -0.804 +2024-11-22 14:40:57.250362: val_loss -0.7463 +2024-11-22 14:40:57.250437: Pseudo dice [0.8382] +2024-11-22 14:40:57.250534: Epoch time: 19.38 s +2024-11-22 14:40:58.152814: +2024-11-22 14:40:58.153030: Epoch 5134 +2024-11-22 14:40:58.153147: Current learning rate: 0.00397 +2024-11-22 14:41:16.868361: train_loss -0.8013 +2024-11-22 14:41:16.868582: val_loss -0.7597 +2024-11-22 14:41:16.868654: Pseudo dice [0.8426] +2024-11-22 14:41:16.868731: Epoch time: 18.72 s +2024-11-22 14:41:17.771415: +2024-11-22 14:41:17.771609: Epoch 5135 +2024-11-22 14:41:17.771725: Current learning rate: 0.00397 +2024-11-22 14:41:36.291442: train_loss -0.8029 +2024-11-22 14:41:36.291657: val_loss -0.7486 +2024-11-22 14:41:36.291734: Pseudo dice [0.8243] +2024-11-22 14:41:36.291810: Epoch time: 18.52 s +2024-11-22 14:41:37.592160: +2024-11-22 14:41:37.592371: Epoch 5136 +2024-11-22 14:41:37.592478: Current learning rate: 0.00397 +2024-11-22 14:41:56.496917: train_loss -0.8006 +2024-11-22 14:41:56.497251: val_loss -0.7619 +2024-11-22 14:41:56.497330: Pseudo dice [0.8293] +2024-11-22 14:41:56.497414: Epoch time: 18.91 s +2024-11-22 14:41:57.394683: +2024-11-22 14:41:57.394891: Epoch 5137 +2024-11-22 14:41:57.395008: Current learning rate: 0.00397 +2024-11-22 14:42:16.200219: train_loss -0.8037 +2024-11-22 14:42:16.200454: val_loss -0.7665 +2024-11-22 14:42:16.200532: Pseudo dice [0.8423] +2024-11-22 14:42:16.200623: Epoch time: 18.81 s +2024-11-22 14:42:17.093819: +2024-11-22 14:42:17.094115: Epoch 5138 +2024-11-22 14:42:17.094239: Current learning rate: 0.00396 +2024-11-22 14:42:34.830694: train_loss -0.7951 +2024-11-22 14:42:34.830924: val_loss -0.7428 +2024-11-22 14:42:34.831006: Pseudo dice [0.8412] +2024-11-22 14:42:34.831082: Epoch time: 17.74 s +2024-11-22 14:42:35.722569: +2024-11-22 14:42:35.722792: Epoch 5139 +2024-11-22 14:42:35.722905: Current learning rate: 0.00396 +2024-11-22 14:42:52.934290: train_loss -0.7983 +2024-11-22 14:42:52.934520: val_loss -0.7463 +2024-11-22 14:42:52.934595: Pseudo dice [0.8307] +2024-11-22 14:42:52.934680: Epoch time: 17.21 s +2024-11-22 14:42:53.828679: +2024-11-22 14:42:53.828892: Epoch 5140 +2024-11-22 14:42:53.829014: Current learning rate: 0.00396 +2024-11-22 14:43:11.477376: train_loss -0.7891 +2024-11-22 14:43:11.497246: val_loss -0.7609 +2024-11-22 14:43:11.497422: Pseudo dice [0.8301] +2024-11-22 14:43:11.497519: Epoch time: 17.65 s +2024-11-22 14:43:12.411071: +2024-11-22 14:43:12.411290: Epoch 5141 +2024-11-22 14:43:12.411399: Current learning rate: 0.00396 +2024-11-22 14:43:31.177151: train_loss -0.7779 +2024-11-22 14:43:31.177365: val_loss -0.7473 +2024-11-22 14:43:31.177437: Pseudo dice [0.8359] +2024-11-22 14:43:31.177512: Epoch time: 18.77 s +2024-11-22 14:43:32.149785: +2024-11-22 14:43:32.150031: Epoch 5142 +2024-11-22 14:43:32.150142: Current learning rate: 0.00396 +2024-11-22 14:43:51.933742: train_loss -0.781 +2024-11-22 14:43:51.933978: val_loss -0.7288 +2024-11-22 14:43:51.934070: Pseudo dice [0.8347] +2024-11-22 14:43:51.934153: Epoch time: 19.78 s +2024-11-22 14:43:52.865334: +2024-11-22 14:43:52.865557: Epoch 5143 +2024-11-22 14:43:52.865681: Current learning rate: 0.00396 +2024-11-22 14:44:11.396057: train_loss -0.7872 +2024-11-22 14:44:11.396295: val_loss -0.7758 +2024-11-22 14:44:11.396370: Pseudo dice [0.8315] +2024-11-22 14:44:11.401594: Epoch time: 18.53 s +2024-11-22 14:44:12.368957: +2024-11-22 14:44:12.369239: Epoch 5144 +2024-11-22 14:44:12.369354: Current learning rate: 0.00396 +2024-11-22 14:44:31.220352: train_loss -0.7899 +2024-11-22 14:44:31.220586: val_loss -0.7335 +2024-11-22 14:44:31.220661: Pseudo dice [0.8152] +2024-11-22 14:44:31.220738: Epoch time: 18.85 s +2024-11-22 14:44:32.282001: +2024-11-22 14:44:32.282205: Epoch 5145 +2024-11-22 14:44:32.282321: Current learning rate: 0.00396 +2024-11-22 14:44:49.807903: train_loss -0.7962 +2024-11-22 14:44:49.808205: val_loss -0.7613 +2024-11-22 14:44:49.808286: Pseudo dice [0.851] +2024-11-22 14:44:49.808362: Epoch time: 17.53 s +2024-11-22 14:44:50.695510: +2024-11-22 14:44:50.695737: Epoch 5146 +2024-11-22 14:44:50.695851: Current learning rate: 0.00395 +2024-11-22 14:45:10.416483: train_loss -0.7843 +2024-11-22 14:45:10.416777: val_loss -0.7447 +2024-11-22 14:45:10.416857: Pseudo dice [0.8404] +2024-11-22 14:45:10.416963: Epoch time: 19.72 s +2024-11-22 14:45:11.309221: +2024-11-22 14:45:11.309439: Epoch 5147 +2024-11-22 14:45:11.309559: Current learning rate: 0.00395 +2024-11-22 14:45:30.161592: train_loss -0.7914 +2024-11-22 14:45:30.161804: val_loss -0.7493 +2024-11-22 14:45:30.164119: Pseudo dice [0.8264] +2024-11-22 14:45:30.164232: Epoch time: 18.85 s +2024-11-22 14:45:31.530746: +2024-11-22 14:45:31.530978: Epoch 5148 +2024-11-22 14:45:31.531103: Current learning rate: 0.00395 +2024-11-22 14:45:50.652323: train_loss -0.7957 +2024-11-22 14:45:50.652554: val_loss -0.7519 +2024-11-22 14:45:50.652633: Pseudo dice [0.8163] +2024-11-22 14:45:50.652711: Epoch time: 19.12 s +2024-11-22 14:45:51.574045: +2024-11-22 14:45:51.574267: Epoch 5149 +2024-11-22 14:45:51.574386: Current learning rate: 0.00395 +2024-11-22 14:46:10.852221: train_loss -0.7884 +2024-11-22 14:46:10.852512: val_loss -0.745 +2024-11-22 14:46:10.852589: Pseudo dice [0.836] +2024-11-22 14:46:10.852676: Epoch time: 19.28 s +2024-11-22 14:46:12.048808: +2024-11-22 14:46:12.049085: Epoch 5150 +2024-11-22 14:46:12.049198: Current learning rate: 0.00395 +2024-11-22 14:46:30.467811: train_loss -0.7796 +2024-11-22 14:46:30.468031: val_loss -0.7547 +2024-11-22 14:46:30.468106: Pseudo dice [0.8334] +2024-11-22 14:46:30.468182: Epoch time: 18.42 s +2024-11-22 14:46:31.358928: +2024-11-22 14:46:31.359137: Epoch 5151 +2024-11-22 14:46:31.359248: Current learning rate: 0.00395 +2024-11-22 14:46:50.930467: train_loss -0.7824 +2024-11-22 14:46:50.932876: val_loss -0.7481 +2024-11-22 14:46:50.932969: Pseudo dice [0.8349] +2024-11-22 14:46:50.933056: Epoch time: 19.57 s +2024-11-22 14:46:51.824089: +2024-11-22 14:46:51.824394: Epoch 5152 +2024-11-22 14:46:51.824507: Current learning rate: 0.00395 +2024-11-22 14:47:10.220392: train_loss -0.7852 +2024-11-22 14:47:10.220616: val_loss -0.7177 +2024-11-22 14:47:10.220691: Pseudo dice [0.8204] +2024-11-22 14:47:10.220768: Epoch time: 18.4 s +2024-11-22 14:47:11.127182: +2024-11-22 14:47:11.127388: Epoch 5153 +2024-11-22 14:47:11.150638: Current learning rate: 0.00395 +2024-11-22 14:47:29.460909: train_loss -0.7698 +2024-11-22 14:47:29.461129: val_loss -0.7315 +2024-11-22 14:47:29.461202: Pseudo dice [0.8172] +2024-11-22 14:47:29.461282: Epoch time: 18.33 s +2024-11-22 14:47:30.354584: +2024-11-22 14:47:30.355068: Epoch 5154 +2024-11-22 14:47:30.355186: Current learning rate: 0.00394 +2024-11-22 14:47:50.182567: train_loss -0.793 +2024-11-22 14:47:50.182814: val_loss -0.7331 +2024-11-22 14:47:50.182893: Pseudo dice [0.8176] +2024-11-22 14:47:50.182975: Epoch time: 19.83 s +2024-11-22 14:47:51.076009: +2024-11-22 14:47:51.076226: Epoch 5155 +2024-11-22 14:47:51.076337: Current learning rate: 0.00394 +2024-11-22 14:48:10.294564: train_loss -0.7882 +2024-11-22 14:48:10.294790: val_loss -0.7353 +2024-11-22 14:48:10.294866: Pseudo dice [0.8437] +2024-11-22 14:48:10.294948: Epoch time: 19.22 s +2024-11-22 14:48:11.194141: +2024-11-22 14:48:11.194328: Epoch 5156 +2024-11-22 14:48:11.194438: Current learning rate: 0.00394 +2024-11-22 14:48:29.500087: train_loss -0.7878 +2024-11-22 14:48:29.502484: val_loss -0.7367 +2024-11-22 14:48:29.502618: Pseudo dice [0.8189] +2024-11-22 14:48:29.502697: Epoch time: 18.31 s +2024-11-22 14:48:30.575573: +2024-11-22 14:48:30.575794: Epoch 5157 +2024-11-22 14:48:30.575907: Current learning rate: 0.00394 +2024-11-22 14:48:48.002733: train_loss -0.7897 +2024-11-22 14:48:48.003050: val_loss -0.7371 +2024-11-22 14:48:48.003126: Pseudo dice [0.8212] +2024-11-22 14:48:48.003211: Epoch time: 17.43 s +2024-11-22 14:48:48.903421: +2024-11-22 14:48:48.903618: Epoch 5158 +2024-11-22 14:48:48.903731: Current learning rate: 0.00394 +2024-11-22 14:49:08.124221: train_loss -0.7926 +2024-11-22 14:49:08.124453: val_loss -0.7538 +2024-11-22 14:49:08.124529: Pseudo dice [0.8357] +2024-11-22 14:49:08.124609: Epoch time: 19.22 s +2024-11-22 14:49:09.024874: +2024-11-22 14:49:09.025089: Epoch 5159 +2024-11-22 14:49:09.025201: Current learning rate: 0.00394 +2024-11-22 14:49:27.806775: train_loss -0.7902 +2024-11-22 14:49:27.807306: val_loss -0.7483 +2024-11-22 14:49:27.807407: Pseudo dice [0.8095] +2024-11-22 14:49:27.807484: Epoch time: 18.78 s +2024-11-22 14:49:28.704672: +2024-11-22 14:49:28.704880: Epoch 5160 +2024-11-22 14:49:28.704999: Current learning rate: 0.00394 +2024-11-22 14:49:47.931157: train_loss -0.7925 +2024-11-22 14:49:47.931414: val_loss -0.7461 +2024-11-22 14:49:47.931493: Pseudo dice [0.8375] +2024-11-22 14:49:47.931582: Epoch time: 19.23 s +2024-11-22 14:49:48.874492: +2024-11-22 14:49:48.874739: Epoch 5161 +2024-11-22 14:49:48.874893: Current learning rate: 0.00394 +2024-11-22 14:50:07.937594: train_loss -0.8004 +2024-11-22 14:50:07.937879: val_loss -0.7418 +2024-11-22 14:50:07.937955: Pseudo dice [0.8241] +2024-11-22 14:50:07.938044: Epoch time: 19.06 s +2024-11-22 14:50:08.834833: +2024-11-22 14:50:08.835073: Epoch 5162 +2024-11-22 14:50:08.835192: Current learning rate: 0.00393 +2024-11-22 14:50:27.954744: train_loss -0.7976 +2024-11-22 14:50:27.954960: val_loss -0.7593 +2024-11-22 14:50:27.955087: Pseudo dice [0.8195] +2024-11-22 14:50:27.955184: Epoch time: 19.12 s +2024-11-22 14:50:28.847984: +2024-11-22 14:50:28.848224: Epoch 5163 +2024-11-22 14:50:28.848335: Current learning rate: 0.00393 +2024-11-22 14:50:48.717546: train_loss -0.8018 +2024-11-22 14:50:48.717776: val_loss -0.7567 +2024-11-22 14:50:48.717853: Pseudo dice [0.837] +2024-11-22 14:50:48.717928: Epoch time: 19.87 s +2024-11-22 14:50:49.619006: +2024-11-22 14:50:49.619221: Epoch 5164 +2024-11-22 14:50:49.619339: Current learning rate: 0.00393 +2024-11-22 14:51:08.102630: train_loss -0.7905 +2024-11-22 14:51:08.102869: val_loss -0.7519 +2024-11-22 14:51:08.102947: Pseudo dice [0.8421] +2024-11-22 14:51:08.103083: Epoch time: 18.48 s +2024-11-22 14:51:09.002490: +2024-11-22 14:51:09.002697: Epoch 5165 +2024-11-22 14:51:09.002803: Current learning rate: 0.00393 +2024-11-22 14:51:27.991554: train_loss -0.7928 +2024-11-22 14:51:27.991773: val_loss -0.7768 +2024-11-22 14:51:27.991853: Pseudo dice [0.8152] +2024-11-22 14:51:27.991929: Epoch time: 18.99 s +2024-11-22 14:51:28.925688: +2024-11-22 14:51:28.925906: Epoch 5166 +2024-11-22 14:51:28.926021: Current learning rate: 0.00393 +2024-11-22 14:51:48.270723: train_loss -0.7939 +2024-11-22 14:51:48.270940: val_loss -0.7527 +2024-11-22 14:51:48.271024: Pseudo dice [0.8326] +2024-11-22 14:51:48.271101: Epoch time: 19.35 s +2024-11-22 14:51:49.165097: +2024-11-22 14:51:49.165441: Epoch 5167 +2024-11-22 14:51:49.165553: Current learning rate: 0.00393 +2024-11-22 14:52:07.845476: train_loss -0.8014 +2024-11-22 14:52:07.845757: val_loss -0.7547 +2024-11-22 14:52:07.845837: Pseudo dice [0.8283] +2024-11-22 14:52:07.845916: Epoch time: 18.68 s +2024-11-22 14:52:08.827974: +2024-11-22 14:52:08.828212: Epoch 5168 +2024-11-22 14:52:08.828326: Current learning rate: 0.00393 +2024-11-22 14:52:27.622151: train_loss -0.7963 +2024-11-22 14:52:27.622378: val_loss -0.7457 +2024-11-22 14:52:27.622450: Pseudo dice [0.8199] +2024-11-22 14:52:27.622533: Epoch time: 18.79 s +2024-11-22 14:52:28.513336: +2024-11-22 14:52:28.513538: Epoch 5169 +2024-11-22 14:52:28.513650: Current learning rate: 0.00393 +2024-11-22 14:52:47.160547: train_loss -0.8094 +2024-11-22 14:52:47.160767: val_loss -0.769 +2024-11-22 14:52:47.160844: Pseudo dice [0.852] +2024-11-22 14:52:47.160931: Epoch time: 18.65 s +2024-11-22 14:52:48.051663: +2024-11-22 14:52:48.051870: Epoch 5170 +2024-11-22 14:52:48.051984: Current learning rate: 0.00392 +2024-11-22 14:53:07.552478: train_loss -0.7996 +2024-11-22 14:53:07.552701: val_loss -0.7606 +2024-11-22 14:53:07.552779: Pseudo dice [0.8392] +2024-11-22 14:53:07.552862: Epoch time: 19.5 s +2024-11-22 14:53:08.821420: +2024-11-22 14:53:08.821633: Epoch 5171 +2024-11-22 14:53:08.821739: Current learning rate: 0.00392 +2024-11-22 14:53:28.254097: train_loss -0.7937 +2024-11-22 14:53:28.256540: val_loss -0.7538 +2024-11-22 14:53:28.256637: Pseudo dice [0.8242] +2024-11-22 14:53:28.256731: Epoch time: 19.43 s +2024-11-22 14:53:29.431352: +2024-11-22 14:53:29.431577: Epoch 5172 +2024-11-22 14:53:29.431685: Current learning rate: 0.00392 +2024-11-22 14:53:48.700364: train_loss -0.8066 +2024-11-22 14:53:48.700577: val_loss -0.7615 +2024-11-22 14:53:48.700650: Pseudo dice [0.8487] +2024-11-22 14:53:48.700724: Epoch time: 19.27 s +2024-11-22 14:53:49.602081: +2024-11-22 14:53:49.602298: Epoch 5173 +2024-11-22 14:53:49.602426: Current learning rate: 0.00392 +2024-11-22 14:54:08.172848: train_loss -0.8002 +2024-11-22 14:54:08.173188: val_loss -0.7547 +2024-11-22 14:54:08.173272: Pseudo dice [0.82] +2024-11-22 14:54:08.173359: Epoch time: 18.57 s +2024-11-22 14:54:09.062959: +2024-11-22 14:54:09.063175: Epoch 5174 +2024-11-22 14:54:09.063288: Current learning rate: 0.00392 +2024-11-22 14:54:27.864848: train_loss -0.7966 +2024-11-22 14:54:27.865079: val_loss -0.7546 +2024-11-22 14:54:27.865154: Pseudo dice [0.8324] +2024-11-22 14:54:27.865232: Epoch time: 18.8 s +2024-11-22 14:54:28.761333: +2024-11-22 14:54:28.761518: Epoch 5175 +2024-11-22 14:54:28.761627: Current learning rate: 0.00392 +2024-11-22 14:54:47.338526: train_loss -0.8002 +2024-11-22 14:54:47.338735: val_loss -0.7656 +2024-11-22 14:54:47.338809: Pseudo dice [0.8444] +2024-11-22 14:54:47.338885: Epoch time: 18.58 s +2024-11-22 14:54:48.229424: +2024-11-22 14:54:48.229635: Epoch 5176 +2024-11-22 14:54:48.229752: Current learning rate: 0.00392 +2024-11-22 14:55:07.125751: train_loss -0.8082 +2024-11-22 14:55:07.126040: val_loss -0.7443 +2024-11-22 14:55:07.126122: Pseudo dice [0.8303] +2024-11-22 14:55:07.126198: Epoch time: 18.9 s +2024-11-22 14:55:08.098283: +2024-11-22 14:55:08.098484: Epoch 5177 +2024-11-22 14:55:08.098595: Current learning rate: 0.00392 +2024-11-22 14:55:25.650686: train_loss -0.7974 +2024-11-22 14:55:25.650926: val_loss -0.7464 +2024-11-22 14:55:25.651008: Pseudo dice [0.8414] +2024-11-22 14:55:25.651094: Epoch time: 17.55 s +2024-11-22 14:55:26.543770: +2024-11-22 14:55:26.544008: Epoch 5178 +2024-11-22 14:55:26.544121: Current learning rate: 0.00391 +2024-11-22 14:55:44.918138: train_loss -0.8004 +2024-11-22 14:55:44.918370: val_loss -0.751 +2024-11-22 14:55:44.918447: Pseudo dice [0.83] +2024-11-22 14:55:44.918523: Epoch time: 18.38 s +2024-11-22 14:55:45.819712: +2024-11-22 14:55:45.819937: Epoch 5179 +2024-11-22 14:55:45.820068: Current learning rate: 0.00391 +2024-11-22 14:56:03.938360: train_loss -0.8005 +2024-11-22 14:56:03.938577: val_loss -0.769 +2024-11-22 14:56:03.938652: Pseudo dice [0.8458] +2024-11-22 14:56:03.938728: Epoch time: 18.12 s +2024-11-22 14:56:04.832860: +2024-11-22 14:56:04.833055: Epoch 5180 +2024-11-22 14:56:04.833170: Current learning rate: 0.00391 +2024-11-22 14:56:23.904256: train_loss -0.8038 +2024-11-22 14:56:23.904511: val_loss -0.7515 +2024-11-22 14:56:23.904591: Pseudo dice [0.831] +2024-11-22 14:56:23.904684: Epoch time: 19.07 s +2024-11-22 14:56:24.804397: +2024-11-22 14:56:24.804653: Epoch 5181 +2024-11-22 14:56:24.804768: Current learning rate: 0.00391 +2024-11-22 14:56:44.144834: train_loss -0.7944 +2024-11-22 14:56:44.145062: val_loss -0.7229 +2024-11-22 14:56:44.148032: Pseudo dice [0.8174] +2024-11-22 14:56:44.148282: Epoch time: 19.34 s +2024-11-22 14:56:45.052061: +2024-11-22 14:56:45.052287: Epoch 5182 +2024-11-22 14:56:45.052401: Current learning rate: 0.00391 +2024-11-22 14:57:04.210262: train_loss -0.7964 +2024-11-22 14:57:04.210514: val_loss -0.7508 +2024-11-22 14:57:04.210591: Pseudo dice [0.8322] +2024-11-22 14:57:04.210668: Epoch time: 19.16 s +2024-11-22 14:57:05.494085: +2024-11-22 14:57:05.494335: Epoch 5183 +2024-11-22 14:57:05.494440: Current learning rate: 0.00391 +2024-11-22 14:57:24.384460: train_loss -0.7969 +2024-11-22 14:57:24.384701: val_loss -0.7585 +2024-11-22 14:57:24.386929: Pseudo dice [0.8434] +2024-11-22 14:57:24.387087: Epoch time: 18.89 s +2024-11-22 14:57:25.304014: +2024-11-22 14:57:25.304247: Epoch 5184 +2024-11-22 14:57:25.304355: Current learning rate: 0.00391 +2024-11-22 14:57:43.919439: train_loss -0.8098 +2024-11-22 14:57:43.920096: val_loss -0.7619 +2024-11-22 14:57:43.920249: Pseudo dice [0.8206] +2024-11-22 14:57:43.920345: Epoch time: 18.62 s +2024-11-22 14:57:44.799561: +2024-11-22 14:57:44.799751: Epoch 5185 +2024-11-22 14:57:44.799859: Current learning rate: 0.00391 +2024-11-22 14:58:03.257359: train_loss -0.8097 +2024-11-22 14:58:03.257574: val_loss -0.7523 +2024-11-22 14:58:03.257648: Pseudo dice [0.8298] +2024-11-22 14:58:03.257721: Epoch time: 18.46 s +2024-11-22 14:58:04.208104: +2024-11-22 14:58:04.208334: Epoch 5186 +2024-11-22 14:58:04.208451: Current learning rate: 0.0039 +2024-11-22 14:58:23.350473: train_loss -0.7982 +2024-11-22 14:58:23.350681: val_loss -0.7309 +2024-11-22 14:58:23.350754: Pseudo dice [0.8175] +2024-11-22 14:58:23.350831: Epoch time: 19.14 s +2024-11-22 14:58:24.235042: +2024-11-22 14:58:24.235240: Epoch 5187 +2024-11-22 14:58:24.235350: Current learning rate: 0.0039 +2024-11-22 14:58:42.415232: train_loss -0.8012 +2024-11-22 14:58:42.415457: val_loss -0.7609 +2024-11-22 14:58:42.415536: Pseudo dice [0.8361] +2024-11-22 14:58:42.415620: Epoch time: 18.18 s +2024-11-22 14:58:43.313364: +2024-11-22 14:58:43.313569: Epoch 5188 +2024-11-22 14:58:43.313680: Current learning rate: 0.0039 +2024-11-22 14:59:01.788250: train_loss -0.7918 +2024-11-22 14:59:01.788507: val_loss -0.7464 +2024-11-22 14:59:01.788584: Pseudo dice [0.8346] +2024-11-22 14:59:01.788667: Epoch time: 18.48 s +2024-11-22 14:59:02.726985: +2024-11-22 14:59:02.727188: Epoch 5189 +2024-11-22 14:59:02.727305: Current learning rate: 0.0039 +2024-11-22 14:59:21.535434: train_loss -0.8019 +2024-11-22 14:59:21.535646: val_loss -0.7608 +2024-11-22 14:59:21.535731: Pseudo dice [0.8401] +2024-11-22 14:59:21.535811: Epoch time: 18.81 s +2024-11-22 14:59:22.512513: +2024-11-22 14:59:22.512709: Epoch 5190 +2024-11-22 14:59:22.512832: Current learning rate: 0.0039 +2024-11-22 14:59:40.403033: train_loss -0.8025 +2024-11-22 14:59:40.403252: val_loss -0.7317 +2024-11-22 14:59:40.403327: Pseudo dice [0.8385] +2024-11-22 14:59:40.403410: Epoch time: 17.89 s +2024-11-22 14:59:41.530519: +2024-11-22 14:59:41.530698: Epoch 5191 +2024-11-22 14:59:41.531056: Current learning rate: 0.0039 +2024-11-22 15:00:00.413273: train_loss -0.7943 +2024-11-22 15:00:00.413549: val_loss -0.7842 +2024-11-22 15:00:00.413676: Pseudo dice [0.8334] +2024-11-22 15:00:00.413766: Epoch time: 18.88 s +2024-11-22 15:00:01.339108: +2024-11-22 15:00:01.339322: Epoch 5192 +2024-11-22 15:00:01.339440: Current learning rate: 0.0039 +2024-11-22 15:00:19.715863: train_loss -0.8041 +2024-11-22 15:00:19.716092: val_loss -0.7403 +2024-11-22 15:00:19.716167: Pseudo dice [0.8305] +2024-11-22 15:00:19.716244: Epoch time: 18.38 s +2024-11-22 15:00:20.652731: +2024-11-22 15:00:20.652932: Epoch 5193 +2024-11-22 15:00:20.653169: Current learning rate: 0.0039 +2024-11-22 15:00:39.390451: train_loss -0.8026 +2024-11-22 15:00:39.390670: val_loss -0.7561 +2024-11-22 15:00:39.390747: Pseudo dice [0.8429] +2024-11-22 15:00:39.390824: Epoch time: 18.74 s +2024-11-22 15:00:40.286866: +2024-11-22 15:00:40.287102: Epoch 5194 +2024-11-22 15:00:40.287215: Current learning rate: 0.00389 +2024-11-22 15:00:59.407345: train_loss -0.8 +2024-11-22 15:00:59.407598: val_loss -0.7418 +2024-11-22 15:00:59.407695: Pseudo dice [0.8459] +2024-11-22 15:00:59.407781: Epoch time: 19.12 s +2024-11-22 15:01:00.710005: +2024-11-22 15:01:00.710218: Epoch 5195 +2024-11-22 15:01:00.710327: Current learning rate: 0.00389 +2024-11-22 15:01:19.405235: train_loss -0.7983 +2024-11-22 15:01:19.405513: val_loss -0.7207 +2024-11-22 15:01:19.405586: Pseudo dice [0.8255] +2024-11-22 15:01:19.405663: Epoch time: 18.7 s +2024-11-22 15:01:20.394884: +2024-11-22 15:01:20.395173: Epoch 5196 +2024-11-22 15:01:20.395280: Current learning rate: 0.00389 +2024-11-22 15:01:37.983583: train_loss -0.802 +2024-11-22 15:01:37.983803: val_loss -0.7301 +2024-11-22 15:01:37.983876: Pseudo dice [0.8258] +2024-11-22 15:01:37.983952: Epoch time: 17.59 s +2024-11-22 15:01:38.970634: +2024-11-22 15:01:38.970864: Epoch 5197 +2024-11-22 15:01:38.970976: Current learning rate: 0.00389 +2024-11-22 15:01:58.233928: train_loss -0.8035 +2024-11-22 15:01:58.234186: val_loss -0.7596 +2024-11-22 15:01:58.234265: Pseudo dice [0.8279] +2024-11-22 15:01:58.234349: Epoch time: 19.26 s +2024-11-22 15:01:59.128474: +2024-11-22 15:01:59.128684: Epoch 5198 +2024-11-22 15:01:59.128798: Current learning rate: 0.00389 +2024-11-22 15:02:18.429949: train_loss -0.8032 +2024-11-22 15:02:18.430172: val_loss -0.7693 +2024-11-22 15:02:18.430247: Pseudo dice [0.8442] +2024-11-22 15:02:18.430325: Epoch time: 19.3 s +2024-11-22 15:02:19.332595: +2024-11-22 15:02:19.332789: Epoch 5199 +2024-11-22 15:02:19.332898: Current learning rate: 0.00389 +2024-11-22 15:02:37.733278: train_loss -0.8036 +2024-11-22 15:02:37.733541: val_loss -0.7533 +2024-11-22 15:02:37.733622: Pseudo dice [0.8298] +2024-11-22 15:02:37.733703: Epoch time: 18.4 s +2024-11-22 15:02:38.931797: +2024-11-22 15:02:38.932020: Epoch 5200 +2024-11-22 15:02:38.932131: Current learning rate: 0.00389 +2024-11-22 15:02:57.189850: train_loss -0.8108 +2024-11-22 15:02:57.190102: val_loss -0.7798 +2024-11-22 15:02:57.190178: Pseudo dice [0.8308] +2024-11-22 15:02:57.190255: Epoch time: 18.26 s +2024-11-22 15:02:58.088690: +2024-11-22 15:02:58.088914: Epoch 5201 +2024-11-22 15:02:58.089032: Current learning rate: 0.00389 +2024-11-22 15:03:17.279357: train_loss -0.806 +2024-11-22 15:03:17.279602: val_loss -0.7776 +2024-11-22 15:03:17.279675: Pseudo dice [0.8312] +2024-11-22 15:03:17.279762: Epoch time: 19.19 s +2024-11-22 15:03:18.296949: +2024-11-22 15:03:18.297170: Epoch 5202 +2024-11-22 15:03:18.297283: Current learning rate: 0.00388 +2024-11-22 15:03:37.888973: train_loss -0.7955 +2024-11-22 15:03:37.889207: val_loss -0.7435 +2024-11-22 15:03:37.889283: Pseudo dice [0.8335] +2024-11-22 15:03:37.889369: Epoch time: 19.59 s +2024-11-22 15:03:38.792977: +2024-11-22 15:03:38.793191: Epoch 5203 +2024-11-22 15:03:38.793306: Current learning rate: 0.00388 +2024-11-22 15:03:56.804655: train_loss -0.8036 +2024-11-22 15:03:56.804873: val_loss -0.7435 +2024-11-22 15:03:56.804947: Pseudo dice [0.8337] +2024-11-22 15:03:56.805059: Epoch time: 18.01 s +2024-11-22 15:03:57.700687: +2024-11-22 15:03:57.700909: Epoch 5204 +2024-11-22 15:03:57.701035: Current learning rate: 0.00388 +2024-11-22 15:04:17.955745: train_loss -0.8051 +2024-11-22 15:04:17.956014: val_loss -0.7444 +2024-11-22 15:04:17.956092: Pseudo dice [0.8257] +2024-11-22 15:04:17.956179: Epoch time: 20.26 s +2024-11-22 15:04:18.854528: +2024-11-22 15:04:18.854721: Epoch 5205 +2024-11-22 15:04:18.854833: Current learning rate: 0.00388 +2024-11-22 15:04:37.465665: train_loss -0.8049 +2024-11-22 15:04:37.465896: val_loss -0.7586 +2024-11-22 15:04:37.465976: Pseudo dice [0.8425] +2024-11-22 15:04:37.466074: Epoch time: 18.61 s +2024-11-22 15:04:38.632452: +2024-11-22 15:04:38.632644: Epoch 5206 +2024-11-22 15:04:38.632757: Current learning rate: 0.00388 +2024-11-22 15:04:56.974016: train_loss -0.8052 +2024-11-22 15:04:56.974512: val_loss -0.7441 +2024-11-22 15:04:56.979820: Pseudo dice [0.8084] +2024-11-22 15:04:56.979955: Epoch time: 18.34 s +2024-11-22 15:04:57.920742: +2024-11-22 15:04:57.920970: Epoch 5207 +2024-11-22 15:04:57.921087: Current learning rate: 0.00388 +2024-11-22 15:05:15.879884: train_loss -0.8083 +2024-11-22 15:05:15.880137: val_loss -0.7656 +2024-11-22 15:05:15.880218: Pseudo dice [0.8386] +2024-11-22 15:05:15.880302: Epoch time: 17.96 s +2024-11-22 15:05:17.005315: +2024-11-22 15:05:17.005539: Epoch 5208 +2024-11-22 15:05:17.005654: Current learning rate: 0.00388 +2024-11-22 15:05:35.484039: train_loss -0.8109 +2024-11-22 15:05:35.484263: val_loss -0.7457 +2024-11-22 15:05:35.484340: Pseudo dice [0.8079] +2024-11-22 15:05:35.484418: Epoch time: 18.48 s +2024-11-22 15:05:36.379421: +2024-11-22 15:05:36.379640: Epoch 5209 +2024-11-22 15:05:36.379754: Current learning rate: 0.00388 +2024-11-22 15:05:54.510756: train_loss -0.7876 +2024-11-22 15:05:54.511863: val_loss -0.7484 +2024-11-22 15:05:54.512007: Pseudo dice [0.821] +2024-11-22 15:05:54.512092: Epoch time: 18.13 s +2024-11-22 15:05:55.417628: +2024-11-22 15:05:55.417849: Epoch 5210 +2024-11-22 15:05:55.417966: Current learning rate: 0.00387 +2024-11-22 15:06:13.168870: train_loss -0.7787 +2024-11-22 15:06:13.169088: val_loss -0.7392 +2024-11-22 15:06:13.171414: Pseudo dice [0.8163] +2024-11-22 15:06:13.171581: Epoch time: 17.75 s +2024-11-22 15:06:14.085413: +2024-11-22 15:06:14.085674: Epoch 5211 +2024-11-22 15:06:14.085798: Current learning rate: 0.00387 +2024-11-22 15:06:32.353622: train_loss -0.7841 +2024-11-22 15:06:32.355433: val_loss -0.759 +2024-11-22 15:06:32.355515: Pseudo dice [0.8244] +2024-11-22 15:06:32.355598: Epoch time: 18.27 s +2024-11-22 15:06:33.324245: +2024-11-22 15:06:33.324454: Epoch 5212 +2024-11-22 15:06:33.324569: Current learning rate: 0.00387 +2024-11-22 15:06:52.019845: train_loss -0.7926 +2024-11-22 15:06:52.020064: val_loss -0.7162 +2024-11-22 15:06:52.020138: Pseudo dice [0.8014] +2024-11-22 15:06:52.020215: Epoch time: 18.7 s +2024-11-22 15:06:52.914371: +2024-11-22 15:06:52.914583: Epoch 5213 +2024-11-22 15:06:52.914692: Current learning rate: 0.00387 +2024-11-22 15:07:11.231400: train_loss -0.7787 +2024-11-22 15:07:11.231619: val_loss -0.7461 +2024-11-22 15:07:11.231694: Pseudo dice [0.8321] +2024-11-22 15:07:11.231769: Epoch time: 18.32 s +2024-11-22 15:07:12.123197: +2024-11-22 15:07:12.123405: Epoch 5214 +2024-11-22 15:07:12.123522: Current learning rate: 0.00387 +2024-11-22 15:07:30.755817: train_loss -0.7931 +2024-11-22 15:07:30.756090: val_loss -0.7274 +2024-11-22 15:07:30.756166: Pseudo dice [0.8198] +2024-11-22 15:07:30.756249: Epoch time: 18.63 s +2024-11-22 15:07:31.673053: +2024-11-22 15:07:31.673239: Epoch 5215 +2024-11-22 15:07:31.673373: Current learning rate: 0.00387 +2024-11-22 15:07:50.265602: train_loss -0.7899 +2024-11-22 15:07:50.265823: val_loss -0.7589 +2024-11-22 15:07:50.265898: Pseudo dice [0.8404] +2024-11-22 15:07:50.265973: Epoch time: 18.59 s +2024-11-22 15:07:51.164977: +2024-11-22 15:07:51.165209: Epoch 5216 +2024-11-22 15:07:51.165325: Current learning rate: 0.00387 +2024-11-22 15:08:10.112800: train_loss -0.7971 +2024-11-22 15:08:10.113046: val_loss -0.7645 +2024-11-22 15:08:10.114803: Pseudo dice [0.839] +2024-11-22 15:08:10.114946: Epoch time: 18.95 s +2024-11-22 15:08:11.034329: +2024-11-22 15:08:11.034525: Epoch 5217 +2024-11-22 15:08:11.034639: Current learning rate: 0.00387 +2024-11-22 15:08:30.179214: train_loss -0.7805 +2024-11-22 15:08:30.179478: val_loss -0.7332 +2024-11-22 15:08:30.179555: Pseudo dice [0.8252] +2024-11-22 15:08:30.184880: Epoch time: 19.15 s +2024-11-22 15:08:31.472913: +2024-11-22 15:08:31.473137: Epoch 5218 +2024-11-22 15:08:31.473266: Current learning rate: 0.00386 +2024-11-22 15:08:49.905272: train_loss -0.779 +2024-11-22 15:08:49.905507: val_loss -0.7609 +2024-11-22 15:08:49.905586: Pseudo dice [0.8301] +2024-11-22 15:08:49.905664: Epoch time: 18.43 s +2024-11-22 15:08:50.793222: +2024-11-22 15:08:50.793439: Epoch 5219 +2024-11-22 15:08:50.793627: Current learning rate: 0.00386 +2024-11-22 15:09:09.556081: train_loss -0.7815 +2024-11-22 15:09:09.556322: val_loss -0.7591 +2024-11-22 15:09:09.556412: Pseudo dice [0.826] +2024-11-22 15:09:09.556542: Epoch time: 18.76 s +2024-11-22 15:09:10.536373: +2024-11-22 15:09:10.536616: Epoch 5220 +2024-11-22 15:09:10.536733: Current learning rate: 0.00386 +2024-11-22 15:09:28.730749: train_loss -0.7837 +2024-11-22 15:09:28.730975: val_loss -0.7401 +2024-11-22 15:09:28.731058: Pseudo dice [0.8305] +2024-11-22 15:09:28.731133: Epoch time: 18.2 s +2024-11-22 15:09:29.623362: +2024-11-22 15:09:29.623633: Epoch 5221 +2024-11-22 15:09:29.623746: Current learning rate: 0.00386 +2024-11-22 15:09:48.828789: train_loss -0.7883 +2024-11-22 15:09:48.829045: val_loss -0.7478 +2024-11-22 15:09:48.829122: Pseudo dice [0.8288] +2024-11-22 15:09:48.829209: Epoch time: 19.21 s +2024-11-22 15:09:49.724498: +2024-11-22 15:09:49.724690: Epoch 5222 +2024-11-22 15:09:49.724801: Current learning rate: 0.00386 +2024-11-22 15:10:09.074892: train_loss -0.7911 +2024-11-22 15:10:09.075108: val_loss -0.7768 +2024-11-22 15:10:09.075183: Pseudo dice [0.8288] +2024-11-22 15:10:09.075258: Epoch time: 19.35 s +2024-11-22 15:10:09.961839: +2024-11-22 15:10:09.962050: Epoch 5223 +2024-11-22 15:10:09.962163: Current learning rate: 0.00386 +2024-11-22 15:10:27.993373: train_loss -0.7985 +2024-11-22 15:10:27.993591: val_loss -0.7423 +2024-11-22 15:10:27.993665: Pseudo dice [0.8282] +2024-11-22 15:10:27.998924: Epoch time: 18.03 s +2024-11-22 15:10:28.915532: +2024-11-22 15:10:28.915766: Epoch 5224 +2024-11-22 15:10:28.915889: Current learning rate: 0.00386 +2024-11-22 15:10:48.621265: train_loss -0.7991 +2024-11-22 15:10:48.621484: val_loss -0.7385 +2024-11-22 15:10:48.621561: Pseudo dice [0.8378] +2024-11-22 15:10:48.621645: Epoch time: 19.71 s +2024-11-22 15:10:49.517426: +2024-11-22 15:10:49.517642: Epoch 5225 +2024-11-22 15:10:49.517761: Current learning rate: 0.00386 +2024-11-22 15:11:07.542483: train_loss -0.8015 +2024-11-22 15:11:07.542707: val_loss -0.7571 +2024-11-22 15:11:07.542791: Pseudo dice [0.8226] +2024-11-22 15:11:07.542871: Epoch time: 18.03 s +2024-11-22 15:11:08.438882: +2024-11-22 15:11:08.439091: Epoch 5226 +2024-11-22 15:11:08.439211: Current learning rate: 0.00385 +2024-11-22 15:11:26.755950: train_loss -0.8065 +2024-11-22 15:11:26.756203: val_loss -0.7422 +2024-11-22 15:11:26.756280: Pseudo dice [0.8299] +2024-11-22 15:11:26.756355: Epoch time: 18.32 s +2024-11-22 15:11:27.649494: +2024-11-22 15:11:27.649694: Epoch 5227 +2024-11-22 15:11:27.649809: Current learning rate: 0.00385 +2024-11-22 15:11:46.320869: train_loss -0.7941 +2024-11-22 15:11:46.321097: val_loss -0.7804 +2024-11-22 15:11:46.321170: Pseudo dice [0.8548] +2024-11-22 15:11:46.321245: Epoch time: 18.67 s +2024-11-22 15:11:47.209853: +2024-11-22 15:11:47.210091: Epoch 5228 +2024-11-22 15:11:47.210218: Current learning rate: 0.00385 +2024-11-22 15:12:06.476807: train_loss -0.7928 +2024-11-22 15:12:06.477111: val_loss -0.7554 +2024-11-22 15:12:06.477186: Pseudo dice [0.8467] +2024-11-22 15:12:06.477267: Epoch time: 19.27 s +2024-11-22 15:12:07.371392: +2024-11-22 15:12:07.371809: Epoch 5229 +2024-11-22 15:12:07.371945: Current learning rate: 0.00385 +2024-11-22 15:12:27.056102: train_loss -0.8002 +2024-11-22 15:12:27.056303: val_loss -0.7398 +2024-11-22 15:12:27.056374: Pseudo dice [0.8364] +2024-11-22 15:12:27.056447: Epoch time: 19.69 s +2024-11-22 15:12:28.412386: +2024-11-22 15:12:28.412597: Epoch 5230 +2024-11-22 15:12:28.412713: Current learning rate: 0.00385 +2024-11-22 15:12:47.584966: train_loss -0.8022 +2024-11-22 15:12:47.585209: val_loss -0.7606 +2024-11-22 15:12:47.585289: Pseudo dice [0.8359] +2024-11-22 15:12:47.585367: Epoch time: 19.17 s +2024-11-22 15:12:48.471019: +2024-11-22 15:12:48.471253: Epoch 5231 +2024-11-22 15:12:48.471366: Current learning rate: 0.00385 +2024-11-22 15:13:06.621659: train_loss -0.8004 +2024-11-22 15:13:06.621898: val_loss -0.7667 +2024-11-22 15:13:06.621969: Pseudo dice [0.8515] +2024-11-22 15:13:06.622061: Epoch time: 18.15 s +2024-11-22 15:13:07.518559: +2024-11-22 15:13:07.518802: Epoch 5232 +2024-11-22 15:13:07.518917: Current learning rate: 0.00385 +2024-11-22 15:13:26.363823: train_loss -0.7963 +2024-11-22 15:13:26.364057: val_loss -0.7631 +2024-11-22 15:13:26.364139: Pseudo dice [0.8261] +2024-11-22 15:13:26.364218: Epoch time: 18.85 s +2024-11-22 15:13:27.315288: +2024-11-22 15:13:27.315499: Epoch 5233 +2024-11-22 15:13:27.315614: Current learning rate: 0.00385 +2024-11-22 15:13:45.958236: train_loss -0.7992 +2024-11-22 15:13:45.958451: val_loss -0.7491 +2024-11-22 15:13:45.958528: Pseudo dice [0.8376] +2024-11-22 15:13:45.958608: Epoch time: 18.64 s +2024-11-22 15:13:46.860961: +2024-11-22 15:13:46.861273: Epoch 5234 +2024-11-22 15:13:46.861384: Current learning rate: 0.00384 +2024-11-22 15:14:05.277274: train_loss -0.8064 +2024-11-22 15:14:05.277599: val_loss -0.7251 +2024-11-22 15:14:05.277723: Pseudo dice [0.8293] +2024-11-22 15:14:05.277853: Epoch time: 18.42 s +2024-11-22 15:14:06.185151: +2024-11-22 15:14:06.185416: Epoch 5235 +2024-11-22 15:14:06.185524: Current learning rate: 0.00384 +2024-11-22 15:14:26.128652: train_loss -0.799 +2024-11-22 15:14:26.128942: val_loss -0.7687 +2024-11-22 15:14:26.129032: Pseudo dice [0.8435] +2024-11-22 15:14:26.129115: Epoch time: 19.94 s +2024-11-22 15:14:27.027478: +2024-11-22 15:14:27.027765: Epoch 5236 +2024-11-22 15:14:27.027876: Current learning rate: 0.00384 +2024-11-22 15:14:46.724107: train_loss -0.7979 +2024-11-22 15:14:46.724333: val_loss -0.7584 +2024-11-22 15:14:46.724407: Pseudo dice [0.827] +2024-11-22 15:14:46.724486: Epoch time: 19.7 s +2024-11-22 15:14:47.798352: +2024-11-22 15:14:47.798539: Epoch 5237 +2024-11-22 15:14:47.798687: Current learning rate: 0.00384 +2024-11-22 15:15:07.028374: train_loss -0.8014 +2024-11-22 15:15:07.028592: val_loss -0.7712 +2024-11-22 15:15:07.028663: Pseudo dice [0.8326] +2024-11-22 15:15:07.028739: Epoch time: 19.23 s +2024-11-22 15:15:07.996260: +2024-11-22 15:15:07.996473: Epoch 5238 +2024-11-22 15:15:07.996593: Current learning rate: 0.00384 +2024-11-22 15:15:27.015892: train_loss -0.793 +2024-11-22 15:15:27.016119: val_loss -0.7524 +2024-11-22 15:15:27.016199: Pseudo dice [0.8442] +2024-11-22 15:15:27.016278: Epoch time: 19.02 s +2024-11-22 15:15:27.989029: +2024-11-22 15:15:27.989257: Epoch 5239 +2024-11-22 15:15:27.989372: Current learning rate: 0.00384 +2024-11-22 15:15:47.339765: train_loss -0.7981 +2024-11-22 15:15:47.342599: val_loss -0.769 +2024-11-22 15:15:47.342773: Pseudo dice [0.8303] +2024-11-22 15:15:47.342864: Epoch time: 19.35 s +2024-11-22 15:15:48.243557: +2024-11-22 15:15:48.243790: Epoch 5240 +2024-11-22 15:15:48.243905: Current learning rate: 0.00384 +2024-11-22 15:16:07.040418: train_loss -0.7959 +2024-11-22 15:16:07.040645: val_loss -0.7535 +2024-11-22 15:16:07.040723: Pseudo dice [0.8348] +2024-11-22 15:16:07.040802: Epoch time: 18.8 s +2024-11-22 15:16:07.933138: +2024-11-22 15:16:07.933356: Epoch 5241 +2024-11-22 15:16:07.933471: Current learning rate: 0.00384 +2024-11-22 15:16:26.620088: train_loss -0.8036 +2024-11-22 15:16:26.620306: val_loss -0.7554 +2024-11-22 15:16:26.620382: Pseudo dice [0.8292] +2024-11-22 15:16:26.620459: Epoch time: 18.69 s +2024-11-22 15:16:27.892404: +2024-11-22 15:16:27.923179: Epoch 5242 +2024-11-22 15:16:27.923331: Current learning rate: 0.00383 +2024-11-22 15:16:46.183948: train_loss -0.79 +2024-11-22 15:16:46.184293: val_loss -0.7385 +2024-11-22 15:16:46.184378: Pseudo dice [0.8178] +2024-11-22 15:16:46.184463: Epoch time: 18.29 s +2024-11-22 15:16:47.195820: +2024-11-22 15:16:47.196033: Epoch 5243 +2024-11-22 15:16:47.196152: Current learning rate: 0.00383 +2024-11-22 15:17:05.579133: train_loss -0.8014 +2024-11-22 15:17:05.579350: val_loss -0.7635 +2024-11-22 15:17:05.579425: Pseudo dice [0.8179] +2024-11-22 15:17:05.579501: Epoch time: 18.38 s +2024-11-22 15:17:06.474818: +2024-11-22 15:17:06.475049: Epoch 5244 +2024-11-22 15:17:06.475179: Current learning rate: 0.00383 +2024-11-22 15:17:24.565543: train_loss -0.8044 +2024-11-22 15:17:24.565803: val_loss -0.7297 +2024-11-22 15:17:24.565889: Pseudo dice [0.8315] +2024-11-22 15:17:24.565968: Epoch time: 18.09 s +2024-11-22 15:17:25.521163: +2024-11-22 15:17:25.522009: Epoch 5245 +2024-11-22 15:17:25.522186: Current learning rate: 0.00383 +2024-11-22 15:17:43.610183: train_loss -0.8001 +2024-11-22 15:17:43.610414: val_loss -0.7685 +2024-11-22 15:17:43.610533: Pseudo dice [0.8498] +2024-11-22 15:17:43.610620: Epoch time: 18.09 s +2024-11-22 15:17:44.501087: +2024-11-22 15:17:44.501292: Epoch 5246 +2024-11-22 15:17:44.501406: Current learning rate: 0.00383 +2024-11-22 15:18:03.726736: train_loss -0.8004 +2024-11-22 15:18:03.726975: val_loss -0.7251 +2024-11-22 15:18:03.727056: Pseudo dice [0.8426] +2024-11-22 15:18:03.727133: Epoch time: 19.23 s +2024-11-22 15:18:04.622484: +2024-11-22 15:18:04.622865: Epoch 5247 +2024-11-22 15:18:04.622981: Current learning rate: 0.00383 +2024-11-22 15:18:22.903053: train_loss -0.8075 +2024-11-22 15:18:22.903272: val_loss -0.7522 +2024-11-22 15:18:22.903347: Pseudo dice [0.8262] +2024-11-22 15:18:22.903431: Epoch time: 18.28 s +2024-11-22 15:18:23.795044: +2024-11-22 15:18:23.795227: Epoch 5248 +2024-11-22 15:18:23.795339: Current learning rate: 0.00383 +2024-11-22 15:18:42.263875: train_loss -0.8015 +2024-11-22 15:18:42.268678: val_loss -0.7849 +2024-11-22 15:18:42.268805: Pseudo dice [0.8411] +2024-11-22 15:18:42.268887: Epoch time: 18.47 s +2024-11-22 15:18:43.435475: +2024-11-22 15:18:43.435710: Epoch 5249 +2024-11-22 15:18:43.435826: Current learning rate: 0.00383 +2024-11-22 15:19:01.982472: train_loss -0.8057 +2024-11-22 15:19:01.982713: val_loss -0.7549 +2024-11-22 15:19:01.982797: Pseudo dice [0.825] +2024-11-22 15:19:01.982885: Epoch time: 18.55 s +2024-11-22 15:19:03.177592: +2024-11-22 15:19:03.177815: Epoch 5250 +2024-11-22 15:19:03.177933: Current learning rate: 0.00382 +2024-11-22 15:19:22.298982: train_loss -0.8021 +2024-11-22 15:19:22.299189: val_loss -0.7354 +2024-11-22 15:19:22.299264: Pseudo dice [0.8227] +2024-11-22 15:19:22.299337: Epoch time: 19.12 s +2024-11-22 15:19:23.193071: +2024-11-22 15:19:23.193333: Epoch 5251 +2024-11-22 15:19:23.193464: Current learning rate: 0.00382 +2024-11-22 15:19:41.236977: train_loss -0.8026 +2024-11-22 15:19:41.237200: val_loss -0.7363 +2024-11-22 15:19:41.237325: Pseudo dice [0.8243] +2024-11-22 15:19:41.237436: Epoch time: 18.04 s +2024-11-22 15:19:42.130758: +2024-11-22 15:19:42.130971: Epoch 5252 +2024-11-22 15:19:42.131088: Current learning rate: 0.00382 +2024-11-22 15:20:01.630477: train_loss -0.8044 +2024-11-22 15:20:01.630687: val_loss -0.7396 +2024-11-22 15:20:01.630758: Pseudo dice [0.8219] +2024-11-22 15:20:01.630833: Epoch time: 19.5 s +2024-11-22 15:20:02.633650: +2024-11-22 15:20:02.633853: Epoch 5253 +2024-11-22 15:20:02.633968: Current learning rate: 0.00382 +2024-11-22 15:20:21.437966: train_loss -0.8025 +2024-11-22 15:20:21.438548: val_loss -0.7768 +2024-11-22 15:20:21.438649: Pseudo dice [0.8453] +2024-11-22 15:20:21.438733: Epoch time: 18.81 s +2024-11-22 15:20:22.346231: +2024-11-22 15:20:22.346469: Epoch 5254 +2024-11-22 15:20:22.346585: Current learning rate: 0.00382 +2024-11-22 15:20:40.878245: train_loss -0.8156 +2024-11-22 15:20:40.878474: val_loss -0.7381 +2024-11-22 15:20:40.878547: Pseudo dice [0.8144] +2024-11-22 15:20:40.900852: Epoch time: 18.53 s +2024-11-22 15:20:41.839423: +2024-11-22 15:20:41.839638: Epoch 5255 +2024-11-22 15:20:41.839749: Current learning rate: 0.00382 +2024-11-22 15:21:00.651779: train_loss -0.8052 +2024-11-22 15:21:00.652012: val_loss -0.7435 +2024-11-22 15:21:00.652128: Pseudo dice [0.82] +2024-11-22 15:21:00.652205: Epoch time: 18.81 s +2024-11-22 15:21:01.572639: +2024-11-22 15:21:01.572949: Epoch 5256 +2024-11-22 15:21:01.573076: Current learning rate: 0.00382 +2024-11-22 15:21:19.332718: train_loss -0.8087 +2024-11-22 15:21:19.332967: val_loss -0.7356 +2024-11-22 15:21:19.333051: Pseudo dice [0.8282] +2024-11-22 15:21:19.333134: Epoch time: 17.76 s +2024-11-22 15:21:20.227933: +2024-11-22 15:21:20.228154: Epoch 5257 +2024-11-22 15:21:20.228266: Current learning rate: 0.00382 +2024-11-22 15:21:38.143424: train_loss -0.8002 +2024-11-22 15:21:38.143642: val_loss -0.7408 +2024-11-22 15:21:38.143718: Pseudo dice [0.8239] +2024-11-22 15:21:38.143797: Epoch time: 17.92 s +2024-11-22 15:21:39.037330: +2024-11-22 15:21:39.037560: Epoch 5258 +2024-11-22 15:21:39.037677: Current learning rate: 0.00381 +2024-11-22 15:21:57.978783: train_loss -0.7939 +2024-11-22 15:21:57.981201: val_loss -0.7513 +2024-11-22 15:21:57.981292: Pseudo dice [0.8305] +2024-11-22 15:21:57.981369: Epoch time: 18.94 s +2024-11-22 15:21:58.938341: +2024-11-22 15:21:58.938633: Epoch 5259 +2024-11-22 15:21:58.938754: Current learning rate: 0.00381 +2024-11-22 15:22:17.055820: train_loss -0.7967 +2024-11-22 15:22:17.056047: val_loss -0.726 +2024-11-22 15:22:17.056124: Pseudo dice [0.8115] +2024-11-22 15:22:17.056204: Epoch time: 18.12 s +2024-11-22 15:22:17.950541: +2024-11-22 15:22:17.950737: Epoch 5260 +2024-11-22 15:22:17.950849: Current learning rate: 0.00381 +2024-11-22 15:22:36.426775: train_loss -0.806 +2024-11-22 15:22:36.427020: val_loss -0.7424 +2024-11-22 15:22:36.427100: Pseudo dice [0.8472] +2024-11-22 15:22:36.427184: Epoch time: 18.48 s +2024-11-22 15:22:37.326755: +2024-11-22 15:22:37.326971: Epoch 5261 +2024-11-22 15:22:37.327096: Current learning rate: 0.00381 +2024-11-22 15:22:56.381206: train_loss -0.7979 +2024-11-22 15:22:56.382096: val_loss -0.7434 +2024-11-22 15:22:56.382188: Pseudo dice [0.8155] +2024-11-22 15:22:56.382265: Epoch time: 19.06 s +2024-11-22 15:22:57.298552: +2024-11-22 15:22:57.298741: Epoch 5262 +2024-11-22 15:22:57.298855: Current learning rate: 0.00381 +2024-11-22 15:23:15.467621: train_loss -0.8012 +2024-11-22 15:23:15.467910: val_loss -0.7446 +2024-11-22 15:23:15.468011: Pseudo dice [0.8275] +2024-11-22 15:23:15.468091: Epoch time: 18.17 s +2024-11-22 15:23:16.362564: +2024-11-22 15:23:16.362753: Epoch 5263 +2024-11-22 15:23:16.362869: Current learning rate: 0.00381 +2024-11-22 15:23:34.421333: train_loss -0.8019 +2024-11-22 15:23:34.421566: val_loss -0.7598 +2024-11-22 15:23:34.421642: Pseudo dice [0.8363] +2024-11-22 15:23:34.421727: Epoch time: 18.06 s +2024-11-22 15:23:35.334188: +2024-11-22 15:23:35.334387: Epoch 5264 +2024-11-22 15:23:35.334499: Current learning rate: 0.00381 +2024-11-22 15:23:53.539578: train_loss -0.7987 +2024-11-22 15:23:53.539775: val_loss -0.725 +2024-11-22 15:23:53.539849: Pseudo dice [0.816] +2024-11-22 15:23:53.539926: Epoch time: 18.21 s +2024-11-22 15:23:54.743986: +2024-11-22 15:23:54.744207: Epoch 5265 +2024-11-22 15:23:54.744319: Current learning rate: 0.00381 +2024-11-22 15:24:13.527366: train_loss -0.7969 +2024-11-22 15:24:13.527898: val_loss -0.7209 +2024-11-22 15:24:13.527980: Pseudo dice [0.8254] +2024-11-22 15:24:13.528063: Epoch time: 18.78 s +2024-11-22 15:24:14.415747: +2024-11-22 15:24:14.415965: Epoch 5266 +2024-11-22 15:24:14.416076: Current learning rate: 0.0038 +2024-11-22 15:24:32.101488: train_loss -0.789 +2024-11-22 15:24:32.101734: val_loss -0.7508 +2024-11-22 15:24:32.101809: Pseudo dice [0.8281] +2024-11-22 15:24:32.101897: Epoch time: 17.69 s +2024-11-22 15:24:33.005791: +2024-11-22 15:24:33.006001: Epoch 5267 +2024-11-22 15:24:33.006113: Current learning rate: 0.0038 +2024-11-22 15:24:51.230624: train_loss -0.7869 +2024-11-22 15:24:51.231641: val_loss -0.726 +2024-11-22 15:24:51.231833: Pseudo dice [0.8178] +2024-11-22 15:24:51.231974: Epoch time: 18.23 s +2024-11-22 15:24:52.152416: +2024-11-22 15:24:52.152745: Epoch 5268 +2024-11-22 15:24:52.152863: Current learning rate: 0.0038 +2024-11-22 15:25:09.957026: train_loss -0.792 +2024-11-22 15:25:09.957250: val_loss -0.7481 +2024-11-22 15:25:09.957323: Pseudo dice [0.8299] +2024-11-22 15:25:09.957398: Epoch time: 17.81 s +2024-11-22 15:25:10.950960: +2024-11-22 15:25:10.951219: Epoch 5269 +2024-11-22 15:25:10.951330: Current learning rate: 0.0038 +2024-11-22 15:25:30.301343: train_loss -0.7975 +2024-11-22 15:25:30.301573: val_loss -0.7739 +2024-11-22 15:25:30.301646: Pseudo dice [0.8422] +2024-11-22 15:25:30.301731: Epoch time: 19.35 s +2024-11-22 15:25:31.239594: +2024-11-22 15:25:31.239810: Epoch 5270 +2024-11-22 15:25:31.239920: Current learning rate: 0.0038 +2024-11-22 15:25:51.174160: train_loss -0.7928 +2024-11-22 15:25:51.174372: val_loss -0.7274 +2024-11-22 15:25:51.174445: Pseudo dice [0.8209] +2024-11-22 15:25:51.174523: Epoch time: 19.94 s +2024-11-22 15:25:52.090000: +2024-11-22 15:25:52.090212: Epoch 5271 +2024-11-22 15:25:52.090326: Current learning rate: 0.0038 +2024-11-22 15:26:11.470116: train_loss -0.8 +2024-11-22 15:26:11.470349: val_loss -0.7768 +2024-11-22 15:26:11.470424: Pseudo dice [0.8494] +2024-11-22 15:26:11.470507: Epoch time: 19.38 s +2024-11-22 15:26:12.339208: +2024-11-22 15:26:12.339461: Epoch 5272 +2024-11-22 15:26:12.339578: Current learning rate: 0.0038 +2024-11-22 15:26:31.742711: train_loss -0.7822 +2024-11-22 15:26:31.742924: val_loss -0.7647 +2024-11-22 15:26:31.743008: Pseudo dice [0.8377] +2024-11-22 15:26:31.743084: Epoch time: 19.4 s +2024-11-22 15:26:32.638582: +2024-11-22 15:26:32.638873: Epoch 5273 +2024-11-22 15:26:32.639000: Current learning rate: 0.0038 +2024-11-22 15:26:51.280729: train_loss -0.7941 +2024-11-22 15:26:51.280938: val_loss -0.7642 +2024-11-22 15:26:51.281020: Pseudo dice [0.8291] +2024-11-22 15:26:51.281096: Epoch time: 18.64 s +2024-11-22 15:26:52.167376: +2024-11-22 15:26:52.167563: Epoch 5274 +2024-11-22 15:26:52.167680: Current learning rate: 0.00379 +2024-11-22 15:27:11.702841: train_loss -0.7897 +2024-11-22 15:27:11.703111: val_loss -0.7656 +2024-11-22 15:27:11.703241: Pseudo dice [0.8404] +2024-11-22 15:27:11.703328: Epoch time: 19.54 s +2024-11-22 15:27:12.607844: +2024-11-22 15:27:12.608148: Epoch 5275 +2024-11-22 15:27:12.608263: Current learning rate: 0.00379 +2024-11-22 15:27:31.241378: train_loss -0.7864 +2024-11-22 15:27:31.242646: val_loss -0.7311 +2024-11-22 15:27:31.242734: Pseudo dice [0.828] +2024-11-22 15:27:31.242816: Epoch time: 18.63 s +2024-11-22 15:27:32.368647: +2024-11-22 15:27:32.368840: Epoch 5276 +2024-11-22 15:27:32.368954: Current learning rate: 0.00379 +2024-11-22 15:27:51.183477: train_loss -0.784 +2024-11-22 15:27:51.183707: val_loss -0.7412 +2024-11-22 15:27:51.183785: Pseudo dice [0.8358] +2024-11-22 15:27:51.183863: Epoch time: 18.82 s +2024-11-22 15:27:52.533212: +2024-11-22 15:27:52.533427: Epoch 5277 +2024-11-22 15:27:52.533540: Current learning rate: 0.00379 +2024-11-22 15:28:11.688906: train_loss -0.7689 +2024-11-22 15:28:11.689176: val_loss -0.7317 +2024-11-22 15:28:11.689251: Pseudo dice [0.8125] +2024-11-22 15:28:11.689334: Epoch time: 19.16 s +2024-11-22 15:28:12.587320: +2024-11-22 15:28:12.587542: Epoch 5278 +2024-11-22 15:28:12.587658: Current learning rate: 0.00379 +2024-11-22 15:28:32.399689: train_loss -0.7805 +2024-11-22 15:28:32.399924: val_loss -0.7546 +2024-11-22 15:28:32.400007: Pseudo dice [0.8225] +2024-11-22 15:28:32.400090: Epoch time: 19.81 s +2024-11-22 15:28:33.437726: +2024-11-22 15:28:33.437928: Epoch 5279 +2024-11-22 15:28:33.438044: Current learning rate: 0.00379 +2024-11-22 15:28:51.911818: train_loss -0.7704 +2024-11-22 15:28:51.912055: val_loss -0.7261 +2024-11-22 15:28:51.912130: Pseudo dice [0.8077] +2024-11-22 15:28:51.912209: Epoch time: 18.47 s +2024-11-22 15:28:52.834255: +2024-11-22 15:28:52.834476: Epoch 5280 +2024-11-22 15:28:52.834795: Current learning rate: 0.00379 +2024-11-22 15:29:10.791594: train_loss -0.7808 +2024-11-22 15:29:10.791817: val_loss -0.7507 +2024-11-22 15:29:10.791890: Pseudo dice [0.8263] +2024-11-22 15:29:10.791970: Epoch time: 17.96 s +2024-11-22 15:29:11.687665: +2024-11-22 15:29:11.687898: Epoch 5281 +2024-11-22 15:29:11.688020: Current learning rate: 0.00379 +2024-11-22 15:29:31.111240: train_loss -0.7947 +2024-11-22 15:29:31.111490: val_loss -0.749 +2024-11-22 15:29:31.111564: Pseudo dice [0.8385] +2024-11-22 15:29:31.111645: Epoch time: 19.42 s +2024-11-22 15:29:32.000946: +2024-11-22 15:29:32.001173: Epoch 5282 +2024-11-22 15:29:32.001287: Current learning rate: 0.00378 +2024-11-22 15:29:50.495417: train_loss -0.7847 +2024-11-22 15:29:50.495636: val_loss -0.7549 +2024-11-22 15:29:50.495716: Pseudo dice [0.8434] +2024-11-22 15:29:50.495792: Epoch time: 18.5 s +2024-11-22 15:29:51.392317: +2024-11-22 15:29:51.392553: Epoch 5283 +2024-11-22 15:29:51.392670: Current learning rate: 0.00378 +2024-11-22 15:30:10.794717: train_loss -0.8001 +2024-11-22 15:30:10.803083: val_loss -0.759 +2024-11-22 15:30:10.808078: Pseudo dice [0.8402] +2024-11-22 15:30:10.808242: Epoch time: 19.4 s +2024-11-22 15:30:11.742747: +2024-11-22 15:30:11.742948: Epoch 5284 +2024-11-22 15:30:11.743064: Current learning rate: 0.00378 +2024-11-22 15:30:30.182164: train_loss -0.7944 +2024-11-22 15:30:30.182412: val_loss -0.7545 +2024-11-22 15:30:30.182489: Pseudo dice [0.832] +2024-11-22 15:30:30.182575: Epoch time: 18.44 s +2024-11-22 15:30:31.079128: +2024-11-22 15:30:31.079396: Epoch 5285 +2024-11-22 15:30:31.079510: Current learning rate: 0.00378 +2024-11-22 15:30:50.927269: train_loss -0.7855 +2024-11-22 15:30:50.927476: val_loss -0.7314 +2024-11-22 15:30:50.927549: Pseudo dice [0.8212] +2024-11-22 15:30:50.927623: Epoch time: 19.85 s +2024-11-22 15:30:51.815136: +2024-11-22 15:30:51.815332: Epoch 5286 +2024-11-22 15:30:51.815444: Current learning rate: 0.00378 +2024-11-22 15:31:10.339826: train_loss -0.7984 +2024-11-22 15:31:10.340045: val_loss -0.7582 +2024-11-22 15:31:10.340121: Pseudo dice [0.8512] +2024-11-22 15:31:10.340196: Epoch time: 18.53 s +2024-11-22 15:31:11.231172: +2024-11-22 15:31:11.231442: Epoch 5287 +2024-11-22 15:31:11.231553: Current learning rate: 0.00378 +2024-11-22 15:31:30.545343: train_loss -0.7957 +2024-11-22 15:31:30.545565: val_loss -0.7317 +2024-11-22 15:31:30.545641: Pseudo dice [0.8231] +2024-11-22 15:31:30.545720: Epoch time: 19.31 s +2024-11-22 15:31:31.442893: +2024-11-22 15:31:31.443121: Epoch 5288 +2024-11-22 15:31:31.443238: Current learning rate: 0.00378 +2024-11-22 15:31:50.397952: train_loss -0.8021 +2024-11-22 15:31:50.400378: val_loss -0.7447 +2024-11-22 15:31:50.400510: Pseudo dice [0.8222] +2024-11-22 15:31:50.400602: Epoch time: 18.96 s +2024-11-22 15:31:51.712303: +2024-11-22 15:31:51.712551: Epoch 5289 +2024-11-22 15:31:51.712666: Current learning rate: 0.00378 +2024-11-22 15:32:10.766418: train_loss -0.8039 +2024-11-22 15:32:10.766648: val_loss -0.7583 +2024-11-22 15:32:10.766722: Pseudo dice [0.8098] +2024-11-22 15:32:10.766805: Epoch time: 19.05 s +2024-11-22 15:32:11.656606: +2024-11-22 15:32:11.656873: Epoch 5290 +2024-11-22 15:32:11.656985: Current learning rate: 0.00377 +2024-11-22 15:32:30.095997: train_loss -0.7966 +2024-11-22 15:32:30.096211: val_loss -0.7484 +2024-11-22 15:32:30.096287: Pseudo dice [0.8418] +2024-11-22 15:32:30.096371: Epoch time: 18.44 s +2024-11-22 15:32:31.060700: +2024-11-22 15:32:31.061002: Epoch 5291 +2024-11-22 15:32:31.061113: Current learning rate: 0.00377 +2024-11-22 15:32:49.764785: train_loss -0.795 +2024-11-22 15:32:49.765049: val_loss -0.7635 +2024-11-22 15:32:49.765126: Pseudo dice [0.8434] +2024-11-22 15:32:49.765211: Epoch time: 18.7 s +2024-11-22 15:32:50.665840: +2024-11-22 15:32:50.666044: Epoch 5292 +2024-11-22 15:32:50.666168: Current learning rate: 0.00377 +2024-11-22 15:33:08.497168: train_loss -0.7988 +2024-11-22 15:33:08.497388: val_loss -0.7444 +2024-11-22 15:33:08.497463: Pseudo dice [0.8398] +2024-11-22 15:33:08.498734: Epoch time: 17.83 s +2024-11-22 15:33:09.410652: +2024-11-22 15:33:09.410980: Epoch 5293 +2024-11-22 15:33:09.411095: Current learning rate: 0.00377 +2024-11-22 15:33:27.498669: train_loss -0.795 +2024-11-22 15:33:27.502807: val_loss -0.7344 +2024-11-22 15:33:27.502969: Pseudo dice [0.8335] +2024-11-22 15:33:27.503053: Epoch time: 18.09 s +2024-11-22 15:33:28.409538: +2024-11-22 15:33:28.409739: Epoch 5294 +2024-11-22 15:33:28.409852: Current learning rate: 0.00377 +2024-11-22 15:33:48.144377: train_loss -0.7924 +2024-11-22 15:33:48.144587: val_loss -0.7717 +2024-11-22 15:33:48.144664: Pseudo dice [0.8437] +2024-11-22 15:33:48.144739: Epoch time: 19.74 s +2024-11-22 15:33:49.037739: +2024-11-22 15:33:49.038051: Epoch 5295 +2024-11-22 15:33:49.038174: Current learning rate: 0.00377 +2024-11-22 15:34:08.121166: train_loss -0.7926 +2024-11-22 15:34:08.122045: val_loss -0.759 +2024-11-22 15:34:08.122136: Pseudo dice [0.8311] +2024-11-22 15:34:08.122235: Epoch time: 19.08 s +2024-11-22 15:34:09.016721: +2024-11-22 15:34:09.016924: Epoch 5296 +2024-11-22 15:34:09.017043: Current learning rate: 0.00377 +2024-11-22 15:34:28.895185: train_loss -0.7939 +2024-11-22 15:34:28.895447: val_loss -0.7247 +2024-11-22 15:34:28.895528: Pseudo dice [0.812] +2024-11-22 15:34:28.895607: Epoch time: 19.88 s +2024-11-22 15:34:29.790712: +2024-11-22 15:34:29.790984: Epoch 5297 +2024-11-22 15:34:29.791104: Current learning rate: 0.00377 +2024-11-22 15:34:47.692683: train_loss -0.7879 +2024-11-22 15:34:47.692899: val_loss -0.7443 +2024-11-22 15:34:47.693036: Pseudo dice [0.8209] +2024-11-22 15:34:47.693115: Epoch time: 17.9 s +2024-11-22 15:34:48.615411: +2024-11-22 15:34:48.615624: Epoch 5298 +2024-11-22 15:34:48.615743: Current learning rate: 0.00376 +2024-11-22 15:35:07.417141: train_loss -0.7906 +2024-11-22 15:35:07.420627: val_loss -0.7541 +2024-11-22 15:35:07.420760: Pseudo dice [0.8288] +2024-11-22 15:35:07.420842: Epoch time: 18.8 s +2024-11-22 15:35:08.321191: +2024-11-22 15:35:08.321392: Epoch 5299 +2024-11-22 15:35:08.321505: Current learning rate: 0.00376 +2024-11-22 15:35:27.076840: train_loss -0.793 +2024-11-22 15:35:27.077099: val_loss -0.7835 +2024-11-22 15:35:27.077177: Pseudo dice [0.8411] +2024-11-22 15:35:27.077261: Epoch time: 18.76 s +2024-11-22 15:35:28.252110: +2024-11-22 15:35:28.252344: Epoch 5300 +2024-11-22 15:35:28.252463: Current learning rate: 0.00376 +2024-11-22 15:35:46.763249: train_loss -0.7995 +2024-11-22 15:35:46.763527: val_loss -0.7545 +2024-11-22 15:35:46.763613: Pseudo dice [0.8359] +2024-11-22 15:35:46.763693: Epoch time: 18.51 s +2024-11-22 15:35:48.061578: +2024-11-22 15:35:48.061826: Epoch 5301 +2024-11-22 15:35:48.061943: Current learning rate: 0.00376 +2024-11-22 15:36:07.536183: train_loss -0.805 +2024-11-22 15:36:07.536420: val_loss -0.7342 +2024-11-22 15:36:07.536496: Pseudo dice [0.8358] +2024-11-22 15:36:07.536573: Epoch time: 19.48 s +2024-11-22 15:36:08.453170: +2024-11-22 15:36:08.453480: Epoch 5302 +2024-11-22 15:36:08.453596: Current learning rate: 0.00376 +2024-11-22 15:36:27.293053: train_loss -0.8091 +2024-11-22 15:36:27.293309: val_loss -0.7552 +2024-11-22 15:36:27.293385: Pseudo dice [0.8392] +2024-11-22 15:36:27.293528: Epoch time: 18.84 s +2024-11-22 15:36:28.191321: +2024-11-22 15:36:28.191560: Epoch 5303 +2024-11-22 15:36:28.191675: Current learning rate: 0.00376 +2024-11-22 15:36:46.813820: train_loss -0.7964 +2024-11-22 15:36:46.816213: val_loss -0.7628 +2024-11-22 15:36:46.816316: Pseudo dice [0.8377] +2024-11-22 15:36:46.816396: Epoch time: 18.62 s +2024-11-22 15:36:47.853402: +2024-11-22 15:36:47.853614: Epoch 5304 +2024-11-22 15:36:47.853729: Current learning rate: 0.00376 +2024-11-22 15:37:07.070766: train_loss -0.796 +2024-11-22 15:37:07.070977: val_loss -0.7572 +2024-11-22 15:37:07.071073: Pseudo dice [0.8422] +2024-11-22 15:37:07.071150: Epoch time: 19.22 s +2024-11-22 15:37:07.963792: +2024-11-22 15:37:07.963987: Epoch 5305 +2024-11-22 15:37:07.964100: Current learning rate: 0.00376 +2024-11-22 15:37:27.140945: train_loss -0.8005 +2024-11-22 15:37:27.141532: val_loss -0.7581 +2024-11-22 15:37:27.141613: Pseudo dice [0.8076] +2024-11-22 15:37:27.141690: Epoch time: 19.18 s +2024-11-22 15:37:28.033403: +2024-11-22 15:37:28.033640: Epoch 5306 +2024-11-22 15:37:28.033753: Current learning rate: 0.00375 +2024-11-22 15:37:45.878949: train_loss -0.8004 +2024-11-22 15:37:45.879203: val_loss -0.7469 +2024-11-22 15:37:45.879282: Pseudo dice [0.8228] +2024-11-22 15:37:45.879371: Epoch time: 17.85 s +2024-11-22 15:37:46.781150: +2024-11-22 15:37:46.781370: Epoch 5307 +2024-11-22 15:37:46.781484: Current learning rate: 0.00375 +2024-11-22 15:38:04.841087: train_loss -0.8022 +2024-11-22 15:38:04.841340: val_loss -0.7458 +2024-11-22 15:38:04.841419: Pseudo dice [0.8393] +2024-11-22 15:38:04.841498: Epoch time: 18.06 s +2024-11-22 15:38:05.775823: +2024-11-22 15:38:05.776082: Epoch 5308 +2024-11-22 15:38:05.776198: Current learning rate: 0.00375 +2024-11-22 15:38:23.832527: train_loss -0.7931 +2024-11-22 15:38:23.832743: val_loss -0.7449 +2024-11-22 15:38:23.832820: Pseudo dice [0.8325] +2024-11-22 15:38:23.832901: Epoch time: 18.06 s +2024-11-22 15:38:24.722510: +2024-11-22 15:38:24.722695: Epoch 5309 +2024-11-22 15:38:24.722803: Current learning rate: 0.00375 +2024-11-22 15:38:43.862221: train_loss -0.8016 +2024-11-22 15:38:43.862461: val_loss -0.741 +2024-11-22 15:38:43.862536: Pseudo dice [0.8041] +2024-11-22 15:38:43.862611: Epoch time: 19.14 s +2024-11-22 15:38:44.764104: +2024-11-22 15:38:44.764319: Epoch 5310 +2024-11-22 15:38:44.764432: Current learning rate: 0.00375 +2024-11-22 15:39:03.507702: train_loss -0.7987 +2024-11-22 15:39:03.507953: val_loss -0.7587 +2024-11-22 15:39:03.508031: Pseudo dice [0.8336] +2024-11-22 15:39:03.508113: Epoch time: 18.74 s +2024-11-22 15:39:04.398099: +2024-11-22 15:39:04.398304: Epoch 5311 +2024-11-22 15:39:04.398418: Current learning rate: 0.00375 +2024-11-22 15:39:23.620209: train_loss -0.8 +2024-11-22 15:39:23.620433: val_loss -0.7429 +2024-11-22 15:39:23.620511: Pseudo dice [0.8063] +2024-11-22 15:39:23.620590: Epoch time: 19.22 s +2024-11-22 15:39:24.527602: +2024-11-22 15:39:24.527858: Epoch 5312 +2024-11-22 15:39:24.527972: Current learning rate: 0.00375 +2024-11-22 15:39:43.577266: train_loss -0.7994 +2024-11-22 15:39:43.577477: val_loss -0.7581 +2024-11-22 15:39:43.577553: Pseudo dice [0.83] +2024-11-22 15:39:43.577630: Epoch time: 19.05 s +2024-11-22 15:39:44.881482: +2024-11-22 15:39:44.881697: Epoch 5313 +2024-11-22 15:39:44.881808: Current learning rate: 0.00375 +2024-11-22 15:40:03.226739: train_loss -0.8081 +2024-11-22 15:40:03.226971: val_loss -0.7548 +2024-11-22 15:40:03.227054: Pseudo dice [0.829] +2024-11-22 15:40:03.227133: Epoch time: 18.35 s +2024-11-22 15:40:04.118596: +2024-11-22 15:40:04.118805: Epoch 5314 +2024-11-22 15:40:04.118916: Current learning rate: 0.00374 +2024-11-22 15:40:22.734967: train_loss -0.7874 +2024-11-22 15:40:22.735214: val_loss -0.741 +2024-11-22 15:40:22.735290: Pseudo dice [0.8426] +2024-11-22 15:40:22.735374: Epoch time: 18.62 s +2024-11-22 15:40:23.632083: +2024-11-22 15:40:23.632302: Epoch 5315 +2024-11-22 15:40:23.632413: Current learning rate: 0.00374 +2024-11-22 15:40:41.773584: train_loss -0.7986 +2024-11-22 15:40:41.773805: val_loss -0.7688 +2024-11-22 15:40:41.773880: Pseudo dice [0.8208] +2024-11-22 15:40:41.779138: Epoch time: 18.14 s +2024-11-22 15:40:42.701008: +2024-11-22 15:40:42.701228: Epoch 5316 +2024-11-22 15:40:42.701340: Current learning rate: 0.00374 +2024-11-22 15:41:00.127501: train_loss -0.8011 +2024-11-22 15:41:00.127716: val_loss -0.726 +2024-11-22 15:41:00.127792: Pseudo dice [0.8192] +2024-11-22 15:41:00.127868: Epoch time: 17.43 s +2024-11-22 15:41:01.016448: +2024-11-22 15:41:01.016654: Epoch 5317 +2024-11-22 15:41:01.016768: Current learning rate: 0.00374 +2024-11-22 15:41:19.256123: train_loss -0.7973 +2024-11-22 15:41:19.256334: val_loss -0.7376 +2024-11-22 15:41:19.256407: Pseudo dice [0.8235] +2024-11-22 15:41:19.256482: Epoch time: 18.24 s +2024-11-22 15:41:20.157438: +2024-11-22 15:41:20.157660: Epoch 5318 +2024-11-22 15:41:20.157790: Current learning rate: 0.00374 +2024-11-22 15:41:39.691441: train_loss -0.8034 +2024-11-22 15:41:39.691682: val_loss -0.77 +2024-11-22 15:41:39.691756: Pseudo dice [0.8504] +2024-11-22 15:41:39.691840: Epoch time: 19.53 s +2024-11-22 15:41:40.590006: +2024-11-22 15:41:40.590289: Epoch 5319 +2024-11-22 15:41:40.590406: Current learning rate: 0.00374 +2024-11-22 15:42:00.740939: train_loss -0.8049 +2024-11-22 15:42:00.741169: val_loss -0.7291 +2024-11-22 15:42:00.741246: Pseudo dice [0.8397] +2024-11-22 15:42:00.741326: Epoch time: 20.15 s +2024-11-22 15:42:01.632391: +2024-11-22 15:42:01.632600: Epoch 5320 +2024-11-22 15:42:01.632712: Current learning rate: 0.00374 +2024-11-22 15:42:20.199472: train_loss -0.8094 +2024-11-22 15:42:20.199691: val_loss -0.7503 +2024-11-22 15:42:20.199767: Pseudo dice [0.8355] +2024-11-22 15:42:20.199845: Epoch time: 18.57 s +2024-11-22 15:42:21.100038: +2024-11-22 15:42:21.100302: Epoch 5321 +2024-11-22 15:42:21.100421: Current learning rate: 0.00374 +2024-11-22 15:42:40.677705: train_loss -0.7972 +2024-11-22 15:42:40.677973: val_loss -0.7589 +2024-11-22 15:42:40.678058: Pseudo dice [0.8335] +2024-11-22 15:42:40.678137: Epoch time: 19.58 s +2024-11-22 15:42:41.573141: +2024-11-22 15:42:41.573420: Epoch 5322 +2024-11-22 15:42:41.573547: Current learning rate: 0.00373 +2024-11-22 15:42:59.894582: train_loss -0.7964 +2024-11-22 15:42:59.894822: val_loss -0.7613 +2024-11-22 15:42:59.894894: Pseudo dice [0.832] +2024-11-22 15:42:59.895117: Epoch time: 18.32 s +2024-11-22 15:43:00.844108: +2024-11-22 15:43:00.844545: Epoch 5323 +2024-11-22 15:43:00.844678: Current learning rate: 0.00373 +2024-11-22 15:43:19.974601: train_loss -0.8027 +2024-11-22 15:43:19.974855: val_loss -0.7551 +2024-11-22 15:43:19.974970: Pseudo dice [0.8393] +2024-11-22 15:43:19.975052: Epoch time: 19.13 s +2024-11-22 15:43:20.864424: +2024-11-22 15:43:20.864635: Epoch 5324 +2024-11-22 15:43:20.864753: Current learning rate: 0.00373 +2024-11-22 15:43:40.389907: train_loss -0.7975 +2024-11-22 15:43:40.391945: val_loss -0.7743 +2024-11-22 15:43:40.392031: Pseudo dice [0.8391] +2024-11-22 15:43:40.392109: Epoch time: 19.53 s +2024-11-22 15:43:41.662079: +2024-11-22 15:43:41.662338: Epoch 5325 +2024-11-22 15:43:41.662452: Current learning rate: 0.00373 +2024-11-22 15:44:00.342232: train_loss -0.7937 +2024-11-22 15:44:00.342478: val_loss -0.7455 +2024-11-22 15:44:00.342554: Pseudo dice [0.8299] +2024-11-22 15:44:00.342640: Epoch time: 18.68 s +2024-11-22 15:44:01.239920: +2024-11-22 15:44:01.240179: Epoch 5326 +2024-11-22 15:44:01.240289: Current learning rate: 0.00373 +2024-11-22 15:44:20.199640: train_loss -0.7986 +2024-11-22 15:44:20.199855: val_loss -0.7517 +2024-11-22 15:44:20.199930: Pseudo dice [0.8281] +2024-11-22 15:44:20.200015: Epoch time: 18.96 s +2024-11-22 15:44:21.090438: +2024-11-22 15:44:21.090654: Epoch 5327 +2024-11-22 15:44:21.090765: Current learning rate: 0.00373 +2024-11-22 15:44:39.834390: train_loss -0.8045 +2024-11-22 15:44:39.834604: val_loss -0.7291 +2024-11-22 15:44:39.834678: Pseudo dice [0.8346] +2024-11-22 15:44:39.834751: Epoch time: 18.74 s +2024-11-22 15:44:40.731457: +2024-11-22 15:44:40.731738: Epoch 5328 +2024-11-22 15:44:40.731854: Current learning rate: 0.00373 +2024-11-22 15:45:00.059174: train_loss -0.8029 +2024-11-22 15:45:00.062208: val_loss -0.7512 +2024-11-22 15:45:00.062336: Pseudo dice [0.8142] +2024-11-22 15:45:00.062425: Epoch time: 19.33 s +2024-11-22 15:45:00.967860: +2024-11-22 15:45:00.968137: Epoch 5329 +2024-11-22 15:45:00.968251: Current learning rate: 0.00373 +2024-11-22 15:45:20.005701: train_loss -0.8007 +2024-11-22 15:45:20.005948: val_loss -0.75 +2024-11-22 15:45:20.006037: Pseudo dice [0.8429] +2024-11-22 15:45:20.006120: Epoch time: 19.04 s +2024-11-22 15:45:20.916051: +2024-11-22 15:45:20.916256: Epoch 5330 +2024-11-22 15:45:20.916368: Current learning rate: 0.00372 +2024-11-22 15:45:39.529585: train_loss -0.8125 +2024-11-22 15:45:39.529795: val_loss -0.757 +2024-11-22 15:45:39.529869: Pseudo dice [0.8352] +2024-11-22 15:45:39.529947: Epoch time: 18.61 s +2024-11-22 15:45:40.450408: +2024-11-22 15:45:40.450686: Epoch 5331 +2024-11-22 15:45:40.450802: Current learning rate: 0.00372 +2024-11-22 15:45:59.466081: train_loss -0.8 +2024-11-22 15:45:59.466316: val_loss -0.7657 +2024-11-22 15:45:59.466396: Pseudo dice [0.8319] +2024-11-22 15:45:59.466472: Epoch time: 19.02 s +2024-11-22 15:46:00.362137: +2024-11-22 15:46:00.362416: Epoch 5332 +2024-11-22 15:46:00.362533: Current learning rate: 0.00372 +2024-11-22 15:46:19.232964: train_loss -0.8126 +2024-11-22 15:46:19.233219: val_loss -0.7339 +2024-11-22 15:46:19.233297: Pseudo dice [0.8351] +2024-11-22 15:46:19.233381: Epoch time: 18.87 s +2024-11-22 15:46:20.129027: +2024-11-22 15:46:20.129238: Epoch 5333 +2024-11-22 15:46:20.129354: Current learning rate: 0.00372 +2024-11-22 15:46:38.011503: train_loss -0.8071 +2024-11-22 15:46:38.012864: val_loss -0.7638 +2024-11-22 15:46:38.013069: Pseudo dice [0.838] +2024-11-22 15:46:38.013153: Epoch time: 17.88 s +2024-11-22 15:46:38.909517: +2024-11-22 15:46:38.909919: Epoch 5334 +2024-11-22 15:46:38.910050: Current learning rate: 0.00372 +2024-11-22 15:46:58.005466: train_loss -0.8033 +2024-11-22 15:46:58.005681: val_loss -0.7626 +2024-11-22 15:46:58.005756: Pseudo dice [0.8315] +2024-11-22 15:46:58.005837: Epoch time: 19.1 s +2024-11-22 15:46:59.032043: +2024-11-22 15:46:59.032262: Epoch 5335 +2024-11-22 15:46:59.032385: Current learning rate: 0.00372 +2024-11-22 15:47:17.670125: train_loss -0.8118 +2024-11-22 15:47:17.670357: val_loss -0.7477 +2024-11-22 15:47:17.670431: Pseudo dice [0.8295] +2024-11-22 15:47:17.670515: Epoch time: 18.64 s +2024-11-22 15:47:18.576545: +2024-11-22 15:47:18.576755: Epoch 5336 +2024-11-22 15:47:18.576870: Current learning rate: 0.00372 +2024-11-22 15:47:37.317474: train_loss -0.8029 +2024-11-22 15:47:37.317688: val_loss -0.7466 +2024-11-22 15:47:37.317761: Pseudo dice [0.8299] +2024-11-22 15:47:37.317837: Epoch time: 18.74 s +2024-11-22 15:47:38.604532: +2024-11-22 15:47:38.604763: Epoch 5337 +2024-11-22 15:47:38.604875: Current learning rate: 0.00372 +2024-11-22 15:47:57.466214: train_loss -0.8042 +2024-11-22 15:47:57.466444: val_loss -0.7623 +2024-11-22 15:47:57.466519: Pseudo dice [0.8337] +2024-11-22 15:47:57.466594: Epoch time: 18.86 s +2024-11-22 15:47:58.357031: +2024-11-22 15:47:58.357250: Epoch 5338 +2024-11-22 15:47:58.357367: Current learning rate: 0.00371 +2024-11-22 15:48:17.609786: train_loss -0.8066 +2024-11-22 15:48:17.610010: val_loss -0.7638 +2024-11-22 15:48:17.610097: Pseudo dice [0.8383] +2024-11-22 15:48:17.610176: Epoch time: 19.25 s +2024-11-22 15:48:18.505467: +2024-11-22 15:48:18.505698: Epoch 5339 +2024-11-22 15:48:18.505814: Current learning rate: 0.00371 +2024-11-22 15:48:37.918053: train_loss -0.8091 +2024-11-22 15:48:37.918270: val_loss -0.7579 +2024-11-22 15:48:37.918345: Pseudo dice [0.8352] +2024-11-22 15:48:37.918424: Epoch time: 19.41 s +2024-11-22 15:48:38.815345: +2024-11-22 15:48:38.815572: Epoch 5340 +2024-11-22 15:48:38.815727: Current learning rate: 0.00371 +2024-11-22 15:48:57.976304: train_loss -0.8024 +2024-11-22 15:48:57.976516: val_loss -0.7587 +2024-11-22 15:48:57.976588: Pseudo dice [0.8378] +2024-11-22 15:48:57.978652: Epoch time: 19.16 s +2024-11-22 15:48:58.875860: +2024-11-22 15:48:58.876112: Epoch 5341 +2024-11-22 15:48:58.876238: Current learning rate: 0.00371 +2024-11-22 15:49:17.812414: train_loss -0.8038 +2024-11-22 15:49:17.812706: val_loss -0.7451 +2024-11-22 15:49:17.812789: Pseudo dice [0.8214] +2024-11-22 15:49:17.812872: Epoch time: 18.94 s +2024-11-22 15:49:18.712443: +2024-11-22 15:49:18.712661: Epoch 5342 +2024-11-22 15:49:18.712775: Current learning rate: 0.00371 +2024-11-22 15:49:36.230501: train_loss -0.8067 +2024-11-22 15:49:36.230728: val_loss -0.7667 +2024-11-22 15:49:36.230808: Pseudo dice [0.8285] +2024-11-22 15:49:36.230891: Epoch time: 17.52 s +2024-11-22 15:49:37.131429: +2024-11-22 15:49:37.131694: Epoch 5343 +2024-11-22 15:49:37.131808: Current learning rate: 0.00371 +2024-11-22 15:49:55.926213: train_loss -0.7962 +2024-11-22 15:49:55.926501: val_loss -0.7573 +2024-11-22 15:49:55.939711: Pseudo dice [0.8307] +2024-11-22 15:49:55.939897: Epoch time: 18.8 s +2024-11-22 15:49:56.838236: +2024-11-22 15:49:56.838444: Epoch 5344 +2024-11-22 15:49:56.838561: Current learning rate: 0.00371 +2024-11-22 15:50:16.218877: train_loss -0.8092 +2024-11-22 15:50:16.219111: val_loss -0.7576 +2024-11-22 15:50:16.221413: Pseudo dice [0.8485] +2024-11-22 15:50:16.221505: Epoch time: 19.38 s +2024-11-22 15:50:17.302131: +2024-11-22 15:50:17.302338: Epoch 5345 +2024-11-22 15:50:17.302458: Current learning rate: 0.00371 +2024-11-22 15:50:36.227033: train_loss -0.804 +2024-11-22 15:50:36.227269: val_loss -0.7444 +2024-11-22 15:50:36.227348: Pseudo dice [0.8293] +2024-11-22 15:50:36.227428: Epoch time: 18.93 s +2024-11-22 15:50:37.116674: +2024-11-22 15:50:37.117079: Epoch 5346 +2024-11-22 15:50:37.117213: Current learning rate: 0.0037 +2024-11-22 15:50:55.823858: train_loss -0.8037 +2024-11-22 15:50:55.824083: val_loss -0.7699 +2024-11-22 15:50:55.824158: Pseudo dice [0.8428] +2024-11-22 15:50:55.824237: Epoch time: 18.71 s +2024-11-22 15:50:56.798018: +2024-11-22 15:50:56.798221: Epoch 5347 +2024-11-22 15:50:56.798336: Current learning rate: 0.0037 +2024-11-22 15:51:14.251391: train_loss -0.8068 +2024-11-22 15:51:14.251639: val_loss -0.7541 +2024-11-22 15:51:14.251751: Pseudo dice [0.8485] +2024-11-22 15:51:14.251838: Epoch time: 17.45 s +2024-11-22 15:51:15.152687: +2024-11-22 15:51:15.152884: Epoch 5348 +2024-11-22 15:51:15.153006: Current learning rate: 0.0037 +2024-11-22 15:51:33.393255: train_loss -0.8067 +2024-11-22 15:51:33.393470: val_loss -0.7651 +2024-11-22 15:51:33.393544: Pseudo dice [0.851] +2024-11-22 15:51:33.393739: Epoch time: 18.24 s +2024-11-22 15:51:33.393805: Yayy! New best EMA pseudo Dice: 0.8371 +2024-11-22 15:51:34.966762: +2024-11-22 15:51:34.967006: Epoch 5349 +2024-11-22 15:51:34.967121: Current learning rate: 0.0037 +2024-11-22 15:51:54.481145: train_loss -0.8072 +2024-11-22 15:51:54.481366: val_loss -0.7453 +2024-11-22 15:51:54.481443: Pseudo dice [0.8202] +2024-11-22 15:51:54.481520: Epoch time: 19.52 s +2024-11-22 15:51:55.700859: +2024-11-22 15:51:55.701066: Epoch 5350 +2024-11-22 15:51:55.701180: Current learning rate: 0.0037 +2024-11-22 15:52:15.584349: train_loss -0.7963 +2024-11-22 15:52:15.584593: val_loss -0.7506 +2024-11-22 15:52:15.584671: Pseudo dice [0.8193] +2024-11-22 15:52:15.584755: Epoch time: 19.88 s +2024-11-22 15:52:16.479180: +2024-11-22 15:52:16.479392: Epoch 5351 +2024-11-22 15:52:16.479505: Current learning rate: 0.0037 +2024-11-22 15:52:34.356052: train_loss -0.804 +2024-11-22 15:52:34.356267: val_loss -0.7517 +2024-11-22 15:52:34.356350: Pseudo dice [0.8394] +2024-11-22 15:52:34.356430: Epoch time: 17.88 s +2024-11-22 15:52:35.266490: +2024-11-22 15:52:35.266700: Epoch 5352 +2024-11-22 15:52:35.266809: Current learning rate: 0.0037 +2024-11-22 15:52:54.071901: train_loss -0.8003 +2024-11-22 15:52:54.072191: val_loss -0.7526 +2024-11-22 15:52:54.072268: Pseudo dice [0.8261] +2024-11-22 15:52:54.072346: Epoch time: 18.81 s +2024-11-22 15:52:54.988271: +2024-11-22 15:52:54.988483: Epoch 5353 +2024-11-22 15:52:54.988600: Current learning rate: 0.0037 +2024-11-22 15:53:14.581977: train_loss -0.8055 +2024-11-22 15:53:14.582267: val_loss -0.7507 +2024-11-22 15:53:14.582348: Pseudo dice [0.8332] +2024-11-22 15:53:14.582433: Epoch time: 19.59 s +2024-11-22 15:53:15.486958: +2024-11-22 15:53:15.487186: Epoch 5354 +2024-11-22 15:53:15.487302: Current learning rate: 0.00369 +2024-11-22 15:53:34.874013: train_loss -0.7988 +2024-11-22 15:53:34.874266: val_loss -0.7592 +2024-11-22 15:53:34.874352: Pseudo dice [0.8288] +2024-11-22 15:53:34.874436: Epoch time: 19.39 s +2024-11-22 15:53:35.770456: +2024-11-22 15:53:35.770681: Epoch 5355 +2024-11-22 15:53:35.770803: Current learning rate: 0.00369 +2024-11-22 15:53:53.911731: train_loss -0.8089 +2024-11-22 15:53:53.911948: val_loss -0.7736 +2024-11-22 15:53:53.912030: Pseudo dice [0.8495] +2024-11-22 15:53:53.912105: Epoch time: 18.14 s +2024-11-22 15:53:54.807882: +2024-11-22 15:53:54.808080: Epoch 5356 +2024-11-22 15:53:54.832049: Current learning rate: 0.00369 +2024-11-22 15:54:13.098788: train_loss -0.8032 +2024-11-22 15:54:13.099025: val_loss -0.7416 +2024-11-22 15:54:13.099100: Pseudo dice [0.8391] +2024-11-22 15:54:13.099176: Epoch time: 18.29 s +2024-11-22 15:54:13.990939: +2024-11-22 15:54:13.991133: Epoch 5357 +2024-11-22 15:54:13.991244: Current learning rate: 0.00369 +2024-11-22 15:54:32.198066: train_loss -0.8004 +2024-11-22 15:54:32.198290: val_loss -0.7408 +2024-11-22 15:54:32.198366: Pseudo dice [0.8311] +2024-11-22 15:54:32.198444: Epoch time: 18.21 s +2024-11-22 15:54:33.097209: +2024-11-22 15:54:33.097429: Epoch 5358 +2024-11-22 15:54:33.097542: Current learning rate: 0.00369 +2024-11-22 15:54:51.324506: train_loss -0.7872 +2024-11-22 15:54:51.324740: val_loss -0.751 +2024-11-22 15:54:51.324817: Pseudo dice [0.8384] +2024-11-22 15:54:51.324901: Epoch time: 18.23 s +2024-11-22 15:54:52.218046: +2024-11-22 15:54:52.218449: Epoch 5359 +2024-11-22 15:54:52.218582: Current learning rate: 0.00369 +2024-11-22 15:55:11.513519: train_loss -0.7994 +2024-11-22 15:55:11.513744: val_loss -0.7621 +2024-11-22 15:55:11.513818: Pseudo dice [0.8304] +2024-11-22 15:55:11.513894: Epoch time: 19.3 s +2024-11-22 15:55:12.770200: +2024-11-22 15:55:12.770434: Epoch 5360 +2024-11-22 15:55:12.770549: Current learning rate: 0.00369 +2024-11-22 15:55:31.537180: train_loss -0.7943 +2024-11-22 15:55:31.537440: val_loss -0.7556 +2024-11-22 15:55:31.537526: Pseudo dice [0.8389] +2024-11-22 15:55:31.537605: Epoch time: 18.77 s +2024-11-22 15:55:32.608422: +2024-11-22 15:55:32.608620: Epoch 5361 +2024-11-22 15:55:32.608730: Current learning rate: 0.00369 +2024-11-22 15:55:51.887423: train_loss -0.7953 +2024-11-22 15:55:51.889821: val_loss -0.7419 +2024-11-22 15:55:51.889913: Pseudo dice [0.8325] +2024-11-22 15:55:51.890000: Epoch time: 19.28 s +2024-11-22 15:55:52.955214: +2024-11-22 15:55:52.955423: Epoch 5362 +2024-11-22 15:55:52.955536: Current learning rate: 0.00368 +2024-11-22 15:56:11.064735: train_loss -0.7991 +2024-11-22 15:56:11.067161: val_loss -0.7674 +2024-11-22 15:56:11.067252: Pseudo dice [0.8424] +2024-11-22 15:56:11.067340: Epoch time: 18.11 s +2024-11-22 15:56:12.011622: +2024-11-22 15:56:12.011852: Epoch 5363 +2024-11-22 15:56:12.011970: Current learning rate: 0.00368 +2024-11-22 15:56:31.013074: train_loss -0.8058 +2024-11-22 15:56:31.013303: val_loss -0.7614 +2024-11-22 15:56:31.013377: Pseudo dice [0.8345] +2024-11-22 15:56:31.013452: Epoch time: 19.0 s +2024-11-22 15:56:32.049203: +2024-11-22 15:56:32.049422: Epoch 5364 +2024-11-22 15:56:32.049533: Current learning rate: 0.00368 +2024-11-22 15:56:50.605116: train_loss -0.8045 +2024-11-22 15:56:50.605356: val_loss -0.7384 +2024-11-22 15:56:50.605433: Pseudo dice [0.8151] +2024-11-22 15:56:50.605511: Epoch time: 18.56 s +2024-11-22 15:56:51.609274: +2024-11-22 15:56:51.609527: Epoch 5365 +2024-11-22 15:56:51.609647: Current learning rate: 0.00368 +2024-11-22 15:57:10.613198: train_loss -0.803 +2024-11-22 15:57:10.613426: val_loss -0.765 +2024-11-22 15:57:10.613503: Pseudo dice [0.8496] +2024-11-22 15:57:10.613586: Epoch time: 19.0 s +2024-11-22 15:57:11.540834: +2024-11-22 15:57:11.541098: Epoch 5366 +2024-11-22 15:57:11.541213: Current learning rate: 0.00368 +2024-11-22 15:57:30.573204: train_loss -0.7944 +2024-11-22 15:57:30.573451: val_loss -0.7427 +2024-11-22 15:57:30.573548: Pseudo dice [0.8214] +2024-11-22 15:57:30.573640: Epoch time: 19.03 s +2024-11-22 15:57:31.477695: +2024-11-22 15:57:31.478019: Epoch 5367 +2024-11-22 15:57:31.478136: Current learning rate: 0.00368 +2024-11-22 15:57:50.305465: train_loss -0.7971 +2024-11-22 15:57:50.305658: val_loss -0.7311 +2024-11-22 15:57:50.305732: Pseudo dice [0.8432] +2024-11-22 15:57:50.305806: Epoch time: 18.83 s +2024-11-22 15:57:51.207148: +2024-11-22 15:57:51.207345: Epoch 5368 +2024-11-22 15:57:51.207456: Current learning rate: 0.00368 +2024-11-22 15:58:10.586422: train_loss -0.7943 +2024-11-22 15:58:10.586641: val_loss -0.7446 +2024-11-22 15:58:10.586717: Pseudo dice [0.8317] +2024-11-22 15:58:10.586796: Epoch time: 19.38 s +2024-11-22 15:58:11.484557: +2024-11-22 15:58:11.484794: Epoch 5369 +2024-11-22 15:58:11.484908: Current learning rate: 0.00368 +2024-11-22 15:58:30.817449: train_loss -0.7968 +2024-11-22 15:58:30.817726: val_loss -0.755 +2024-11-22 15:58:30.817808: Pseudo dice [0.8375] +2024-11-22 15:58:30.817895: Epoch time: 19.33 s +2024-11-22 15:58:31.722122: +2024-11-22 15:58:31.722447: Epoch 5370 +2024-11-22 15:58:31.722558: Current learning rate: 0.00367 +2024-11-22 15:58:51.355839: train_loss -0.7969 +2024-11-22 15:58:51.356065: val_loss -0.744 +2024-11-22 15:58:51.356142: Pseudo dice [0.8149] +2024-11-22 15:58:51.361407: Epoch time: 19.63 s +2024-11-22 15:58:52.392186: +2024-11-22 15:58:52.392390: Epoch 5371 +2024-11-22 15:58:52.392500: Current learning rate: 0.00367 +2024-11-22 15:59:10.589696: train_loss -0.7946 +2024-11-22 15:59:10.589917: val_loss -0.7422 +2024-11-22 15:59:10.590000: Pseudo dice [0.8292] +2024-11-22 15:59:10.590077: Epoch time: 18.2 s +2024-11-22 15:59:11.952260: +2024-11-22 15:59:11.952470: Epoch 5372 +2024-11-22 15:59:11.952586: Current learning rate: 0.00367 +2024-11-22 15:59:30.690951: train_loss -0.8018 +2024-11-22 15:59:30.691188: val_loss -0.7421 +2024-11-22 15:59:30.691266: Pseudo dice [0.8241] +2024-11-22 15:59:30.691349: Epoch time: 18.74 s +2024-11-22 15:59:31.586875: +2024-11-22 15:59:31.587134: Epoch 5373 +2024-11-22 15:59:31.587250: Current learning rate: 0.00367 +2024-11-22 15:59:50.130538: train_loss -0.8033 +2024-11-22 15:59:50.130794: val_loss -0.7372 +2024-11-22 15:59:50.130871: Pseudo dice [0.823] +2024-11-22 15:59:50.130953: Epoch time: 18.54 s +2024-11-22 15:59:51.146416: +2024-11-22 15:59:51.146636: Epoch 5374 +2024-11-22 15:59:51.146749: Current learning rate: 0.00367 +2024-11-22 16:00:09.546115: train_loss -0.8016 +2024-11-22 16:00:09.548691: val_loss -0.75 +2024-11-22 16:00:09.548842: Pseudo dice [0.8232] +2024-11-22 16:00:09.548922: Epoch time: 18.4 s +2024-11-22 16:00:10.538481: +2024-11-22 16:00:10.538738: Epoch 5375 +2024-11-22 16:00:10.538858: Current learning rate: 0.00367 +2024-11-22 16:00:28.829885: train_loss -0.7968 +2024-11-22 16:00:28.830137: val_loss -0.7338 +2024-11-22 16:00:28.830217: Pseudo dice [0.8462] +2024-11-22 16:00:28.830296: Epoch time: 18.29 s +2024-11-22 16:00:29.894538: +2024-11-22 16:00:29.894734: Epoch 5376 +2024-11-22 16:00:29.894861: Current learning rate: 0.00367 +2024-11-22 16:00:48.717146: train_loss -0.7932 +2024-11-22 16:00:48.717403: val_loss -0.7522 +2024-11-22 16:00:48.717478: Pseudo dice [0.8335] +2024-11-22 16:00:48.717572: Epoch time: 18.82 s +2024-11-22 16:00:49.616127: +2024-11-22 16:00:49.616479: Epoch 5377 +2024-11-22 16:00:49.616597: Current learning rate: 0.00367 +2024-11-22 16:01:08.280962: train_loss -0.7923 +2024-11-22 16:01:08.281187: val_loss -0.7498 +2024-11-22 16:01:08.281266: Pseudo dice [0.8081] +2024-11-22 16:01:08.281342: Epoch time: 18.67 s +2024-11-22 16:01:09.175541: +2024-11-22 16:01:09.175756: Epoch 5378 +2024-11-22 16:01:09.175873: Current learning rate: 0.00366 +2024-11-22 16:01:28.277942: train_loss -0.791 +2024-11-22 16:01:28.278225: val_loss -0.726 +2024-11-22 16:01:28.278301: Pseudo dice [0.8226] +2024-11-22 16:01:28.278378: Epoch time: 19.1 s +2024-11-22 16:01:29.169203: +2024-11-22 16:01:29.169410: Epoch 5379 +2024-11-22 16:01:29.169525: Current learning rate: 0.00366 +2024-11-22 16:01:48.107038: train_loss -0.7795 +2024-11-22 16:01:48.107328: val_loss -0.745 +2024-11-22 16:01:48.107411: Pseudo dice [0.8207] +2024-11-22 16:01:48.107491: Epoch time: 18.94 s +2024-11-22 16:01:48.997724: +2024-11-22 16:01:48.998016: Epoch 5380 +2024-11-22 16:01:48.998132: Current learning rate: 0.00366 +2024-11-22 16:02:07.630323: train_loss -0.7922 +2024-11-22 16:02:07.630624: val_loss -0.7512 +2024-11-22 16:02:07.630708: Pseudo dice [0.8373] +2024-11-22 16:02:07.630788: Epoch time: 18.63 s +2024-11-22 16:02:08.518897: +2024-11-22 16:02:08.519115: Epoch 5381 +2024-11-22 16:02:08.519230: Current learning rate: 0.00366 +2024-11-22 16:02:26.342791: train_loss -0.7948 +2024-11-22 16:02:26.343031: val_loss -0.7532 +2024-11-22 16:02:26.343109: Pseudo dice [0.826] +2024-11-22 16:02:26.343185: Epoch time: 17.82 s +2024-11-22 16:02:27.242754: +2024-11-22 16:02:27.242945: Epoch 5382 +2024-11-22 16:02:27.243062: Current learning rate: 0.00366 +2024-11-22 16:02:46.764895: train_loss -0.7955 +2024-11-22 16:02:46.765123: val_loss -0.7767 +2024-11-22 16:02:46.765206: Pseudo dice [0.8362] +2024-11-22 16:02:46.765285: Epoch time: 19.52 s +2024-11-22 16:02:47.657071: +2024-11-22 16:02:47.657338: Epoch 5383 +2024-11-22 16:02:47.657450: Current learning rate: 0.00366 +2024-11-22 16:03:06.072639: train_loss -0.7947 +2024-11-22 16:03:06.072883: val_loss -0.7584 +2024-11-22 16:03:06.072960: Pseudo dice [0.8289] +2024-11-22 16:03:06.073052: Epoch time: 18.42 s +2024-11-22 16:03:07.370238: +2024-11-22 16:03:07.370468: Epoch 5384 +2024-11-22 16:03:07.370580: Current learning rate: 0.00366 +2024-11-22 16:03:25.817861: train_loss -0.8041 +2024-11-22 16:03:25.818094: val_loss -0.7518 +2024-11-22 16:03:25.818169: Pseudo dice [0.8363] +2024-11-22 16:03:25.818245: Epoch time: 18.45 s +2024-11-22 16:03:26.756198: +2024-11-22 16:03:26.756628: Epoch 5385 +2024-11-22 16:03:26.756742: Current learning rate: 0.00366 +2024-11-22 16:03:45.176574: train_loss -0.7981 +2024-11-22 16:03:45.176809: val_loss -0.7708 +2024-11-22 16:03:45.176889: Pseudo dice [0.8423] +2024-11-22 16:03:45.176970: Epoch time: 18.42 s +2024-11-22 16:03:46.172300: +2024-11-22 16:03:46.172508: Epoch 5386 +2024-11-22 16:03:46.172621: Current learning rate: 0.00365 +2024-11-22 16:04:04.911974: train_loss -0.7981 +2024-11-22 16:04:04.912249: val_loss -0.7529 +2024-11-22 16:04:04.912327: Pseudo dice [0.8389] +2024-11-22 16:04:04.912410: Epoch time: 18.74 s +2024-11-22 16:04:05.910542: +2024-11-22 16:04:05.910774: Epoch 5387 +2024-11-22 16:04:05.910893: Current learning rate: 0.00365 +2024-11-22 16:04:24.209321: train_loss -0.7994 +2024-11-22 16:04:24.209558: val_loss -0.7427 +2024-11-22 16:04:24.209633: Pseudo dice [0.8371] +2024-11-22 16:04:24.209713: Epoch time: 18.3 s +2024-11-22 16:04:25.132457: +2024-11-22 16:04:25.132665: Epoch 5388 +2024-11-22 16:04:25.132776: Current learning rate: 0.00365 +2024-11-22 16:04:44.356050: train_loss -0.797 +2024-11-22 16:04:44.356275: val_loss -0.7525 +2024-11-22 16:04:44.356368: Pseudo dice [0.8438] +2024-11-22 16:04:44.361597: Epoch time: 19.22 s +2024-11-22 16:04:45.325804: +2024-11-22 16:04:45.326029: Epoch 5389 +2024-11-22 16:04:45.326146: Current learning rate: 0.00365 +2024-11-22 16:05:03.636381: train_loss -0.7974 +2024-11-22 16:05:03.636612: val_loss -0.774 +2024-11-22 16:05:03.636689: Pseudo dice [0.847] +2024-11-22 16:05:03.636765: Epoch time: 18.31 s +2024-11-22 16:05:04.559128: +2024-11-22 16:05:04.559346: Epoch 5390 +2024-11-22 16:05:04.559466: Current learning rate: 0.00365 +2024-11-22 16:05:22.111949: train_loss -0.802 +2024-11-22 16:05:22.112204: val_loss -0.7647 +2024-11-22 16:05:22.112280: Pseudo dice [0.8397] +2024-11-22 16:05:22.112366: Epoch time: 17.55 s +2024-11-22 16:05:23.010463: +2024-11-22 16:05:23.010728: Epoch 5391 +2024-11-22 16:05:23.010845: Current learning rate: 0.00365 +2024-11-22 16:05:42.276672: train_loss -0.7994 +2024-11-22 16:05:42.276925: val_loss -0.7478 +2024-11-22 16:05:42.277005: Pseudo dice [0.8082] +2024-11-22 16:05:42.277083: Epoch time: 19.27 s +2024-11-22 16:05:43.173388: +2024-11-22 16:05:43.173692: Epoch 5392 +2024-11-22 16:05:43.173823: Current learning rate: 0.00365 +2024-11-22 16:06:02.094649: train_loss -0.7974 +2024-11-22 16:06:02.094866: val_loss -0.7524 +2024-11-22 16:06:02.094939: Pseudo dice [0.8443] +2024-11-22 16:06:02.095023: Epoch time: 18.92 s +2024-11-22 16:06:02.982472: +2024-11-22 16:06:02.982688: Epoch 5393 +2024-11-22 16:06:02.982801: Current learning rate: 0.00365 +2024-11-22 16:06:21.444017: train_loss -0.8021 +2024-11-22 16:06:21.444257: val_loss -0.7605 +2024-11-22 16:06:21.444343: Pseudo dice [0.8237] +2024-11-22 16:06:21.444422: Epoch time: 18.46 s +2024-11-22 16:06:22.438195: +2024-11-22 16:06:22.438390: Epoch 5394 +2024-11-22 16:06:22.438501: Current learning rate: 0.00364 +2024-11-22 16:06:41.099166: train_loss -0.7964 +2024-11-22 16:06:41.099413: val_loss -0.7321 +2024-11-22 16:06:41.099487: Pseudo dice [0.8085] +2024-11-22 16:06:41.099570: Epoch time: 18.66 s +2024-11-22 16:06:41.998493: +2024-11-22 16:06:41.998687: Epoch 5395 +2024-11-22 16:06:41.998801: Current learning rate: 0.00364 +2024-11-22 16:07:00.923892: train_loss -0.7926 +2024-11-22 16:07:00.924147: val_loss -0.739 +2024-11-22 16:07:00.924244: Pseudo dice [0.8226] +2024-11-22 16:07:00.924322: Epoch time: 18.93 s +2024-11-22 16:07:02.251837: +2024-11-22 16:07:02.252079: Epoch 5396 +2024-11-22 16:07:02.252193: Current learning rate: 0.00364 +2024-11-22 16:07:22.495973: train_loss -0.7942 +2024-11-22 16:07:22.496216: val_loss -0.7702 +2024-11-22 16:07:22.496290: Pseudo dice [0.853] +2024-11-22 16:07:22.496376: Epoch time: 20.24 s +2024-11-22 16:07:23.383934: +2024-11-22 16:07:23.384188: Epoch 5397 +2024-11-22 16:07:23.384300: Current learning rate: 0.00364 +2024-11-22 16:07:42.470472: train_loss -0.7945 +2024-11-22 16:07:42.470757: val_loss -0.7571 +2024-11-22 16:07:42.470833: Pseudo dice [0.8363] +2024-11-22 16:07:42.470923: Epoch time: 19.09 s +2024-11-22 16:07:43.436207: +2024-11-22 16:07:43.436423: Epoch 5398 +2024-11-22 16:07:43.436535: Current learning rate: 0.00364 +2024-11-22 16:08:01.522305: train_loss -0.7939 +2024-11-22 16:08:01.522535: val_loss -0.762 +2024-11-22 16:08:01.522646: Pseudo dice [0.8383] +2024-11-22 16:08:01.522723: Epoch time: 18.09 s +2024-11-22 16:08:02.413777: +2024-11-22 16:08:02.413999: Epoch 5399 +2024-11-22 16:08:02.414117: Current learning rate: 0.00364 +2024-11-22 16:08:21.844088: train_loss -0.7998 +2024-11-22 16:08:21.844321: val_loss -0.7546 +2024-11-22 16:08:21.844395: Pseudo dice [0.8426] +2024-11-22 16:08:21.844478: Epoch time: 19.43 s +2024-11-22 16:08:23.026558: +2024-11-22 16:08:23.026863: Epoch 5400 +2024-11-22 16:08:23.026977: Current learning rate: 0.00364 +2024-11-22 16:08:41.730359: train_loss -0.7963 +2024-11-22 16:08:41.730711: val_loss -0.7618 +2024-11-22 16:08:41.730817: Pseudo dice [0.8373] +2024-11-22 16:08:41.730900: Epoch time: 18.7 s +2024-11-22 16:08:42.626499: +2024-11-22 16:08:42.626731: Epoch 5401 +2024-11-22 16:08:42.626847: Current learning rate: 0.00364 +2024-11-22 16:09:01.079670: train_loss -0.7963 +2024-11-22 16:09:01.079949: val_loss -0.765 +2024-11-22 16:09:01.080050: Pseudo dice [0.8281] +2024-11-22 16:09:01.080175: Epoch time: 18.45 s +2024-11-22 16:09:02.022193: +2024-11-22 16:09:02.022401: Epoch 5402 +2024-11-22 16:09:02.022518: Current learning rate: 0.00363 +2024-11-22 16:09:20.239068: train_loss -0.8026 +2024-11-22 16:09:20.239296: val_loss -0.7685 +2024-11-22 16:09:20.239371: Pseudo dice [0.8415] +2024-11-22 16:09:20.239448: Epoch time: 18.22 s +2024-11-22 16:09:21.133229: +2024-11-22 16:09:21.133443: Epoch 5403 +2024-11-22 16:09:21.133558: Current learning rate: 0.00363 +2024-11-22 16:09:40.442446: train_loss -0.8012 +2024-11-22 16:09:40.442653: val_loss -0.7215 +2024-11-22 16:09:40.442727: Pseudo dice [0.8362] +2024-11-22 16:09:40.442803: Epoch time: 19.31 s +2024-11-22 16:09:41.328431: +2024-11-22 16:09:41.328656: Epoch 5404 +2024-11-22 16:09:41.328775: Current learning rate: 0.00363 +2024-11-22 16:09:59.734018: train_loss -0.8005 +2024-11-22 16:09:59.734241: val_loss -0.747 +2024-11-22 16:09:59.734316: Pseudo dice [0.8087] +2024-11-22 16:09:59.734392: Epoch time: 18.41 s +2024-11-22 16:10:00.624229: +2024-11-22 16:10:00.624425: Epoch 5405 +2024-11-22 16:10:00.624542: Current learning rate: 0.00363 +2024-11-22 16:10:20.521760: train_loss -0.8024 +2024-11-22 16:10:20.522032: val_loss -0.7394 +2024-11-22 16:10:20.522111: Pseudo dice [0.8322] +2024-11-22 16:10:20.522204: Epoch time: 19.9 s +2024-11-22 16:10:21.496344: +2024-11-22 16:10:21.496551: Epoch 5406 +2024-11-22 16:10:21.496663: Current learning rate: 0.00363 +2024-11-22 16:10:40.955440: train_loss -0.7791 +2024-11-22 16:10:40.955661: val_loss -0.7605 +2024-11-22 16:10:40.955738: Pseudo dice [0.8242] +2024-11-22 16:10:40.955814: Epoch time: 19.46 s +2024-11-22 16:10:41.854624: +2024-11-22 16:10:41.854831: Epoch 5407 +2024-11-22 16:10:41.854942: Current learning rate: 0.00363 +2024-11-22 16:11:01.730910: train_loss -0.7819 +2024-11-22 16:11:01.731192: val_loss -0.7345 +2024-11-22 16:11:01.731271: Pseudo dice [0.8197] +2024-11-22 16:11:01.731349: Epoch time: 19.88 s +2024-11-22 16:11:02.615961: +2024-11-22 16:11:02.616196: Epoch 5408 +2024-11-22 16:11:02.616310: Current learning rate: 0.00363 +2024-11-22 16:11:21.951041: train_loss -0.7748 +2024-11-22 16:11:21.951260: val_loss -0.7388 +2024-11-22 16:11:21.951333: Pseudo dice [0.8254] +2024-11-22 16:11:21.951413: Epoch time: 19.34 s +2024-11-22 16:11:22.838380: +2024-11-22 16:11:22.838578: Epoch 5409 +2024-11-22 16:11:22.838689: Current learning rate: 0.00363 +2024-11-22 16:11:42.566265: train_loss -0.7838 +2024-11-22 16:11:42.566529: val_loss -0.7507 +2024-11-22 16:11:42.566609: Pseudo dice [0.8325] +2024-11-22 16:11:42.566696: Epoch time: 19.73 s +2024-11-22 16:11:43.464728: +2024-11-22 16:11:43.464939: Epoch 5410 +2024-11-22 16:11:43.465062: Current learning rate: 0.00362 +2024-11-22 16:12:02.360301: train_loss -0.7817 +2024-11-22 16:12:02.360520: val_loss -0.7329 +2024-11-22 16:12:02.362763: Pseudo dice [0.8416] +2024-11-22 16:12:02.362912: Epoch time: 18.9 s +2024-11-22 16:12:03.375248: +2024-11-22 16:12:03.375441: Epoch 5411 +2024-11-22 16:12:03.375557: Current learning rate: 0.00362 +2024-11-22 16:12:22.445957: train_loss -0.7837 +2024-11-22 16:12:22.446196: val_loss -0.7429 +2024-11-22 16:12:22.446273: Pseudo dice [0.8319] +2024-11-22 16:12:22.446351: Epoch time: 19.07 s +2024-11-22 16:12:23.376965: +2024-11-22 16:12:23.377168: Epoch 5412 +2024-11-22 16:12:23.377279: Current learning rate: 0.00362 +2024-11-22 16:12:41.310390: train_loss -0.795 +2024-11-22 16:12:41.310631: val_loss -0.7539 +2024-11-22 16:12:41.310708: Pseudo dice [0.8196] +2024-11-22 16:12:41.310782: Epoch time: 17.93 s +2024-11-22 16:12:42.202581: +2024-11-22 16:12:42.202788: Epoch 5413 +2024-11-22 16:12:42.202908: Current learning rate: 0.00362 +2024-11-22 16:13:01.352005: train_loss -0.8024 +2024-11-22 16:13:01.352246: val_loss -0.7671 +2024-11-22 16:13:01.352324: Pseudo dice [0.8331] +2024-11-22 16:13:01.352409: Epoch time: 19.15 s +2024-11-22 16:13:02.263448: +2024-11-22 16:13:02.263691: Epoch 5414 +2024-11-22 16:13:02.263812: Current learning rate: 0.00362 +2024-11-22 16:13:20.857351: train_loss -0.8023 +2024-11-22 16:13:20.857566: val_loss -0.7499 +2024-11-22 16:13:20.857640: Pseudo dice [0.8219] +2024-11-22 16:13:20.857715: Epoch time: 18.59 s +2024-11-22 16:13:21.754837: +2024-11-22 16:13:21.755083: Epoch 5415 +2024-11-22 16:13:21.755198: Current learning rate: 0.00362 +2024-11-22 16:13:41.127941: train_loss -0.8003 +2024-11-22 16:13:41.128168: val_loss -0.7456 +2024-11-22 16:13:41.128243: Pseudo dice [0.8365] +2024-11-22 16:13:41.128322: Epoch time: 19.37 s +2024-11-22 16:13:42.020884: +2024-11-22 16:13:42.021095: Epoch 5416 +2024-11-22 16:13:42.021212: Current learning rate: 0.00362 +2024-11-22 16:13:59.437257: train_loss -0.8074 +2024-11-22 16:13:59.437501: val_loss -0.7542 +2024-11-22 16:13:59.437576: Pseudo dice [0.8377] +2024-11-22 16:13:59.437661: Epoch time: 17.42 s +2024-11-22 16:14:00.332427: +2024-11-22 16:14:00.332637: Epoch 5417 +2024-11-22 16:14:00.332751: Current learning rate: 0.00362 +2024-11-22 16:14:19.470426: train_loss -0.8032 +2024-11-22 16:14:19.470725: val_loss -0.7565 +2024-11-22 16:14:19.470802: Pseudo dice [0.8093] +2024-11-22 16:14:19.470881: Epoch time: 19.14 s +2024-11-22 16:14:20.369033: +2024-11-22 16:14:20.369226: Epoch 5418 +2024-11-22 16:14:20.369343: Current learning rate: 0.00361 +2024-11-22 16:14:39.130098: train_loss -0.7944 +2024-11-22 16:14:39.130361: val_loss -0.7386 +2024-11-22 16:14:39.130442: Pseudo dice [0.8197] +2024-11-22 16:14:39.130524: Epoch time: 18.76 s +2024-11-22 16:14:40.438259: +2024-11-22 16:14:40.438493: Epoch 5419 +2024-11-22 16:14:40.438608: Current learning rate: 0.00361 +2024-11-22 16:14:58.709086: train_loss -0.7874 +2024-11-22 16:14:58.709501: val_loss -0.7553 +2024-11-22 16:14:58.709596: Pseudo dice [0.83] +2024-11-22 16:14:58.709722: Epoch time: 18.27 s +2024-11-22 16:14:59.599203: +2024-11-22 16:14:59.599467: Epoch 5420 +2024-11-22 16:14:59.599585: Current learning rate: 0.00361 +2024-11-22 16:15:18.623867: train_loss -0.7929 +2024-11-22 16:15:18.624170: val_loss -0.7455 +2024-11-22 16:15:18.624247: Pseudo dice [0.8311] +2024-11-22 16:15:18.624323: Epoch time: 19.03 s +2024-11-22 16:15:19.529276: +2024-11-22 16:15:19.529475: Epoch 5421 +2024-11-22 16:15:19.529583: Current learning rate: 0.00361 +2024-11-22 16:15:39.341851: train_loss -0.7991 +2024-11-22 16:15:39.342109: val_loss -0.7541 +2024-11-22 16:15:39.342197: Pseudo dice [0.8301] +2024-11-22 16:15:39.342279: Epoch time: 19.81 s +2024-11-22 16:15:40.409048: +2024-11-22 16:15:40.409328: Epoch 5422 +2024-11-22 16:15:40.409446: Current learning rate: 0.00361 +2024-11-22 16:15:57.719687: train_loss -0.8037 +2024-11-22 16:15:57.719911: val_loss -0.7496 +2024-11-22 16:15:57.719985: Pseudo dice [0.8291] +2024-11-22 16:15:57.720078: Epoch time: 17.31 s +2024-11-22 16:15:58.617572: +2024-11-22 16:15:58.617773: Epoch 5423 +2024-11-22 16:15:58.617886: Current learning rate: 0.00361 +2024-11-22 16:16:18.236041: train_loss -0.7942 +2024-11-22 16:16:18.236285: val_loss -0.7194 +2024-11-22 16:16:18.236358: Pseudo dice [0.8231] +2024-11-22 16:16:18.236439: Epoch time: 19.62 s +2024-11-22 16:16:19.139505: +2024-11-22 16:16:19.139703: Epoch 5424 +2024-11-22 16:16:19.139820: Current learning rate: 0.00361 +2024-11-22 16:16:38.258182: train_loss -0.7979 +2024-11-22 16:16:38.258403: val_loss -0.7715 +2024-11-22 16:16:38.258477: Pseudo dice [0.837] +2024-11-22 16:16:38.263759: Epoch time: 19.12 s +2024-11-22 16:16:39.344308: +2024-11-22 16:16:39.344560: Epoch 5425 +2024-11-22 16:16:39.344676: Current learning rate: 0.00361 +2024-11-22 16:16:58.791349: train_loss -0.7941 +2024-11-22 16:16:58.791825: val_loss -0.7709 +2024-11-22 16:16:58.791909: Pseudo dice [0.8424] +2024-11-22 16:16:58.791998: Epoch time: 19.45 s +2024-11-22 16:16:59.687597: +2024-11-22 16:16:59.687812: Epoch 5426 +2024-11-22 16:16:59.687922: Current learning rate: 0.0036 +2024-11-22 16:17:18.496393: train_loss -0.7856 +2024-11-22 16:17:18.496769: val_loss -0.7356 +2024-11-22 16:17:18.496862: Pseudo dice [0.8129] +2024-11-22 16:17:18.496949: Epoch time: 18.81 s +2024-11-22 16:17:19.454707: +2024-11-22 16:17:19.454911: Epoch 5427 +2024-11-22 16:17:19.455025: Current learning rate: 0.0036 +2024-11-22 16:17:38.345672: train_loss -0.7801 +2024-11-22 16:17:38.345907: val_loss -0.7641 +2024-11-22 16:17:38.345981: Pseudo dice [0.8307] +2024-11-22 16:17:38.346122: Epoch time: 18.89 s +2024-11-22 16:17:39.242730: +2024-11-22 16:17:39.242926: Epoch 5428 +2024-11-22 16:17:39.243039: Current learning rate: 0.0036 +2024-11-22 16:17:57.537345: train_loss -0.7839 +2024-11-22 16:17:57.537558: val_loss -0.7376 +2024-11-22 16:17:57.537633: Pseudo dice [0.8191] +2024-11-22 16:17:57.537709: Epoch time: 18.3 s +2024-11-22 16:17:58.435890: +2024-11-22 16:17:58.436089: Epoch 5429 +2024-11-22 16:17:58.436196: Current learning rate: 0.0036 +2024-11-22 16:18:17.293621: train_loss -0.7865 +2024-11-22 16:18:17.293834: val_loss -0.7676 +2024-11-22 16:18:17.293909: Pseudo dice [0.8512] +2024-11-22 16:18:17.294009: Epoch time: 18.86 s +2024-11-22 16:18:18.184366: +2024-11-22 16:18:18.184667: Epoch 5430 +2024-11-22 16:18:18.184783: Current learning rate: 0.0036 +2024-11-22 16:18:36.502454: train_loss -0.7935 +2024-11-22 16:18:36.502701: val_loss -0.7353 +2024-11-22 16:18:36.502776: Pseudo dice [0.8235] +2024-11-22 16:18:36.502861: Epoch time: 18.32 s +2024-11-22 16:18:37.804928: +2024-11-22 16:18:37.805134: Epoch 5431 +2024-11-22 16:18:37.805243: Current learning rate: 0.0036 +2024-11-22 16:18:56.344983: train_loss -0.7979 +2024-11-22 16:18:56.345226: val_loss -0.7605 +2024-11-22 16:18:56.345304: Pseudo dice [0.8177] +2024-11-22 16:18:56.345380: Epoch time: 18.54 s +2024-11-22 16:18:57.240086: +2024-11-22 16:18:57.240301: Epoch 5432 +2024-11-22 16:18:57.240411: Current learning rate: 0.0036 +2024-11-22 16:19:15.227264: train_loss -0.7962 +2024-11-22 16:19:15.227843: val_loss -0.7458 +2024-11-22 16:19:15.227931: Pseudo dice [0.8296] +2024-11-22 16:19:15.228016: Epoch time: 17.99 s +2024-11-22 16:19:16.121544: +2024-11-22 16:19:16.121760: Epoch 5433 +2024-11-22 16:19:16.121879: Current learning rate: 0.0036 +2024-11-22 16:19:33.563568: train_loss -0.801 +2024-11-22 16:19:33.563812: val_loss -0.7446 +2024-11-22 16:19:33.563889: Pseudo dice [0.8531] +2024-11-22 16:19:33.563972: Epoch time: 17.44 s +2024-11-22 16:19:34.510536: +2024-11-22 16:19:34.510732: Epoch 5434 +2024-11-22 16:19:34.510848: Current learning rate: 0.00359 +2024-11-22 16:19:52.993528: train_loss -0.7998 +2024-11-22 16:19:52.993746: val_loss -0.7511 +2024-11-22 16:19:52.993825: Pseudo dice [0.8371] +2024-11-22 16:19:52.993904: Epoch time: 18.48 s +2024-11-22 16:19:53.874877: +2024-11-22 16:19:53.875069: Epoch 5435 +2024-11-22 16:19:53.875179: Current learning rate: 0.00359 +2024-11-22 16:20:12.132201: train_loss -0.8014 +2024-11-22 16:20:12.132428: val_loss -0.7491 +2024-11-22 16:20:12.132505: Pseudo dice [0.8255] +2024-11-22 16:20:12.132581: Epoch time: 18.26 s +2024-11-22 16:20:13.110237: +2024-11-22 16:20:13.110433: Epoch 5436 +2024-11-22 16:20:13.110547: Current learning rate: 0.00359 +2024-11-22 16:20:32.088854: train_loss -0.7981 +2024-11-22 16:20:32.089083: val_loss -0.7545 +2024-11-22 16:20:32.089160: Pseudo dice [0.8516] +2024-11-22 16:20:32.089242: Epoch time: 18.98 s +2024-11-22 16:20:32.988753: +2024-11-22 16:20:32.988951: Epoch 5437 +2024-11-22 16:20:32.989071: Current learning rate: 0.00359 +2024-11-22 16:20:52.122578: train_loss -0.8004 +2024-11-22 16:20:52.122814: val_loss -0.7495 +2024-11-22 16:20:52.122890: Pseudo dice [0.8503] +2024-11-22 16:20:52.128256: Epoch time: 19.13 s +2024-11-22 16:20:53.021241: +2024-11-22 16:20:53.021454: Epoch 5438 +2024-11-22 16:20:53.021576: Current learning rate: 0.00359 +2024-11-22 16:21:12.467256: train_loss -0.8001 +2024-11-22 16:21:12.467463: val_loss -0.7519 +2024-11-22 16:21:12.467541: Pseudo dice [0.792] +2024-11-22 16:21:12.467620: Epoch time: 19.45 s +2024-11-22 16:21:13.550722: +2024-11-22 16:21:13.550911: Epoch 5439 +2024-11-22 16:21:13.551029: Current learning rate: 0.00359 +2024-11-22 16:21:31.919838: train_loss -0.8045 +2024-11-22 16:21:31.920076: val_loss -0.7364 +2024-11-22 16:21:31.920152: Pseudo dice [0.8296] +2024-11-22 16:21:31.920230: Epoch time: 18.37 s +2024-11-22 16:21:32.944308: +2024-11-22 16:21:32.944535: Epoch 5440 +2024-11-22 16:21:32.944660: Current learning rate: 0.00359 +2024-11-22 16:21:52.287575: train_loss -0.8044 +2024-11-22 16:21:52.287809: val_loss -0.7406 +2024-11-22 16:21:52.287884: Pseudo dice [0.8254] +2024-11-22 16:21:52.287970: Epoch time: 19.34 s +2024-11-22 16:21:53.166020: +2024-11-22 16:21:53.166198: Epoch 5441 +2024-11-22 16:21:53.166298: Current learning rate: 0.00358 +2024-11-22 16:22:12.068381: train_loss -0.7997 +2024-11-22 16:22:12.068598: val_loss -0.7803 +2024-11-22 16:22:12.068676: Pseudo dice [0.842] +2024-11-22 16:22:12.068755: Epoch time: 18.9 s +2024-11-22 16:22:12.989528: +2024-11-22 16:22:12.989710: Epoch 5442 +2024-11-22 16:22:12.989823: Current learning rate: 0.00358 +2024-11-22 16:22:32.196499: train_loss -0.7976 +2024-11-22 16:22:32.196713: val_loss -0.7761 +2024-11-22 16:22:32.196792: Pseudo dice [0.8336] +2024-11-22 16:22:32.196872: Epoch time: 19.21 s +2024-11-22 16:22:33.464616: +2024-11-22 16:22:33.464847: Epoch 5443 +2024-11-22 16:22:33.464960: Current learning rate: 0.00358 +2024-11-22 16:22:52.344765: train_loss -0.805 +2024-11-22 16:22:52.345027: val_loss -0.7691 +2024-11-22 16:22:52.345107: Pseudo dice [0.8362] +2024-11-22 16:22:52.345205: Epoch time: 18.88 s +2024-11-22 16:22:53.242335: +2024-11-22 16:22:53.242618: Epoch 5444 +2024-11-22 16:22:53.242734: Current learning rate: 0.00358 +2024-11-22 16:23:12.171697: train_loss -0.7981 +2024-11-22 16:23:12.171958: val_loss -0.7834 +2024-11-22 16:23:12.174257: Pseudo dice [0.8229] +2024-11-22 16:23:12.174369: Epoch time: 18.93 s +2024-11-22 16:23:13.223277: +2024-11-22 16:23:13.236292: Epoch 5445 +2024-11-22 16:23:13.236418: Current learning rate: 0.00358 +2024-11-22 16:23:32.540658: train_loss -0.7937 +2024-11-22 16:23:32.540888: val_loss -0.766 +2024-11-22 16:23:32.540965: Pseudo dice [0.8506] +2024-11-22 16:23:32.541048: Epoch time: 19.32 s +2024-11-22 16:23:33.533177: +2024-11-22 16:23:33.533361: Epoch 5446 +2024-11-22 16:23:33.533476: Current learning rate: 0.00358 +2024-11-22 16:23:51.786031: train_loss -0.7973 +2024-11-22 16:23:51.786263: val_loss -0.7616 +2024-11-22 16:23:51.786338: Pseudo dice [0.8269] +2024-11-22 16:23:51.786413: Epoch time: 18.25 s +2024-11-22 16:23:52.690250: +2024-11-22 16:23:52.690453: Epoch 5447 +2024-11-22 16:23:52.690570: Current learning rate: 0.00358 +2024-11-22 16:24:11.936921: train_loss -0.7936 +2024-11-22 16:24:11.937146: val_loss -0.7396 +2024-11-22 16:24:11.937221: Pseudo dice [0.829] +2024-11-22 16:24:11.937302: Epoch time: 19.25 s +2024-11-22 16:24:12.839634: +2024-11-22 16:24:12.839968: Epoch 5448 +2024-11-22 16:24:12.840097: Current learning rate: 0.00358 +2024-11-22 16:24:32.029291: train_loss -0.7996 +2024-11-22 16:24:32.029532: val_loss -0.7641 +2024-11-22 16:24:32.029607: Pseudo dice [0.8384] +2024-11-22 16:24:32.029691: Epoch time: 19.19 s +2024-11-22 16:24:33.073060: +2024-11-22 16:24:33.073277: Epoch 5449 +2024-11-22 16:24:33.073388: Current learning rate: 0.00357 +2024-11-22 16:24:52.241711: train_loss -0.7919 +2024-11-22 16:24:52.242028: val_loss -0.7322 +2024-11-22 16:24:52.242109: Pseudo dice [0.8249] +2024-11-22 16:24:52.242185: Epoch time: 19.17 s +2024-11-22 16:24:53.476004: +2024-11-22 16:24:53.476219: Epoch 5450 +2024-11-22 16:24:53.476328: Current learning rate: 0.00357 +2024-11-22 16:25:11.609678: train_loss -0.7951 +2024-11-22 16:25:11.609899: val_loss -0.7554 +2024-11-22 16:25:11.609974: Pseudo dice [0.8501] +2024-11-22 16:25:11.610056: Epoch time: 18.13 s +2024-11-22 16:25:12.696985: +2024-11-22 16:25:12.697203: Epoch 5451 +2024-11-22 16:25:12.697316: Current learning rate: 0.00357 +2024-11-22 16:25:31.623401: train_loss -0.8066 +2024-11-22 16:25:31.623615: val_loss -0.7672 +2024-11-22 16:25:31.628860: Pseudo dice [0.8464] +2024-11-22 16:25:31.629091: Epoch time: 18.93 s +2024-11-22 16:25:32.552273: +2024-11-22 16:25:32.552484: Epoch 5452 +2024-11-22 16:25:32.552597: Current learning rate: 0.00357 +2024-11-22 16:25:51.981225: train_loss -0.8025 +2024-11-22 16:25:51.981467: val_loss -0.7502 +2024-11-22 16:25:51.981549: Pseudo dice [0.8332] +2024-11-22 16:25:51.981633: Epoch time: 19.43 s +2024-11-22 16:25:52.896384: +2024-11-22 16:25:52.896583: Epoch 5453 +2024-11-22 16:25:52.896698: Current learning rate: 0.00357 +2024-11-22 16:26:11.310171: train_loss -0.7955 +2024-11-22 16:26:11.310394: val_loss -0.7556 +2024-11-22 16:26:11.310480: Pseudo dice [0.8457] +2024-11-22 16:26:11.310557: Epoch time: 18.41 s +2024-11-22 16:26:12.204876: +2024-11-22 16:26:12.205069: Epoch 5454 +2024-11-22 16:26:12.205184: Current learning rate: 0.00357 +2024-11-22 16:26:30.632635: train_loss -0.7934 +2024-11-22 16:26:30.632958: val_loss -0.7537 +2024-11-22 16:26:30.633048: Pseudo dice [0.8381] +2024-11-22 16:26:30.633136: Epoch time: 18.43 s +2024-11-22 16:26:31.526274: +2024-11-22 16:26:31.526498: Epoch 5455 +2024-11-22 16:26:31.526609: Current learning rate: 0.00357 +2024-11-22 16:26:50.182639: train_loss -0.7886 +2024-11-22 16:26:50.182871: val_loss -0.7424 +2024-11-22 16:26:50.182946: Pseudo dice [0.8289] +2024-11-22 16:26:50.183028: Epoch time: 18.66 s +2024-11-22 16:26:51.228631: +2024-11-22 16:26:51.228852: Epoch 5456 +2024-11-22 16:26:51.228964: Current learning rate: 0.00357 +2024-11-22 16:27:10.665185: train_loss -0.8014 +2024-11-22 16:27:10.665435: val_loss -0.763 +2024-11-22 16:27:10.665513: Pseudo dice [0.833] +2024-11-22 16:27:10.665590: Epoch time: 19.44 s +2024-11-22 16:27:11.560112: +2024-11-22 16:27:11.560328: Epoch 5457 +2024-11-22 16:27:11.560444: Current learning rate: 0.00356 +2024-11-22 16:27:30.391083: train_loss -0.8039 +2024-11-22 16:27:30.391332: val_loss -0.7384 +2024-11-22 16:27:30.391410: Pseudo dice [0.8278] +2024-11-22 16:27:30.415812: Epoch time: 18.83 s +2024-11-22 16:27:31.305939: +2024-11-22 16:27:31.306179: Epoch 5458 +2024-11-22 16:27:31.306294: Current learning rate: 0.00356 +2024-11-22 16:27:50.573429: train_loss -0.8057 +2024-11-22 16:27:50.573677: val_loss -0.7527 +2024-11-22 16:27:50.573752: Pseudo dice [0.8343] +2024-11-22 16:27:50.573831: Epoch time: 19.27 s +2024-11-22 16:27:51.474303: +2024-11-22 16:27:51.474523: Epoch 5459 +2024-11-22 16:27:51.474662: Current learning rate: 0.00356 +2024-11-22 16:28:10.293408: train_loss -0.8049 +2024-11-22 16:28:10.293630: val_loss -0.7456 +2024-11-22 16:28:10.293705: Pseudo dice [0.8476] +2024-11-22 16:28:10.293796: Epoch time: 18.82 s +2024-11-22 16:28:11.291070: +2024-11-22 16:28:11.291279: Epoch 5460 +2024-11-22 16:28:11.291394: Current learning rate: 0.00356 +2024-11-22 16:28:30.061846: train_loss -0.8082 +2024-11-22 16:28:30.062079: val_loss -0.7738 +2024-11-22 16:28:30.062170: Pseudo dice [0.8253] +2024-11-22 16:28:30.062253: Epoch time: 18.77 s +2024-11-22 16:28:30.955627: +2024-11-22 16:28:30.955905: Epoch 5461 +2024-11-22 16:28:30.956024: Current learning rate: 0.00356 +2024-11-22 16:28:50.363015: train_loss -0.8069 +2024-11-22 16:28:50.363339: val_loss -0.7506 +2024-11-22 16:28:50.363421: Pseudo dice [0.8437] +2024-11-22 16:28:50.363517: Epoch time: 19.41 s +2024-11-22 16:28:51.261632: +2024-11-22 16:28:51.261925: Epoch 5462 +2024-11-22 16:28:51.262040: Current learning rate: 0.00356 +2024-11-22 16:29:11.067173: train_loss -0.8008 +2024-11-22 16:29:11.067381: val_loss -0.7505 +2024-11-22 16:29:11.067454: Pseudo dice [0.8309] +2024-11-22 16:29:11.067529: Epoch time: 19.81 s +2024-11-22 16:29:11.980311: +2024-11-22 16:29:11.980502: Epoch 5463 +2024-11-22 16:29:11.980615: Current learning rate: 0.00356 +2024-11-22 16:29:29.188119: train_loss -0.8095 +2024-11-22 16:29:29.188341: val_loss -0.774 +2024-11-22 16:29:29.188415: Pseudo dice [0.8493] +2024-11-22 16:29:29.188490: Epoch time: 17.21 s +2024-11-22 16:29:30.085695: +2024-11-22 16:29:30.085899: Epoch 5464 +2024-11-22 16:29:30.086020: Current learning rate: 0.00356 +2024-11-22 16:29:49.717944: train_loss -0.8019 +2024-11-22 16:29:49.718167: val_loss -0.7594 +2024-11-22 16:29:49.718243: Pseudo dice [0.8366] +2024-11-22 16:29:49.718325: Epoch time: 19.63 s +2024-11-22 16:29:50.624987: +2024-11-22 16:29:50.625196: Epoch 5465 +2024-11-22 16:29:50.625310: Current learning rate: 0.00355 +2024-11-22 16:30:09.237435: train_loss -0.7996 +2024-11-22 16:30:09.237682: val_loss -0.7668 +2024-11-22 16:30:09.237761: Pseudo dice [0.834] +2024-11-22 16:30:09.237844: Epoch time: 18.61 s +2024-11-22 16:30:10.525846: +2024-11-22 16:30:10.526066: Epoch 5466 +2024-11-22 16:30:10.526181: Current learning rate: 0.00355 +2024-11-22 16:30:29.835245: train_loss -0.8094 +2024-11-22 16:30:29.835506: val_loss -0.7667 +2024-11-22 16:30:29.835582: Pseudo dice [0.8492] +2024-11-22 16:30:29.835659: Epoch time: 19.31 s +2024-11-22 16:30:29.835721: Yayy! New best EMA pseudo Dice: 0.8376 +2024-11-22 16:30:31.028216: +2024-11-22 16:30:31.028466: Epoch 5467 +2024-11-22 16:30:31.028584: Current learning rate: 0.00355 +2024-11-22 16:30:49.683314: train_loss -0.8048 +2024-11-22 16:30:49.683601: val_loss -0.7764 +2024-11-22 16:30:49.683681: Pseudo dice [0.8345] +2024-11-22 16:30:49.683769: Epoch time: 18.66 s +2024-11-22 16:30:50.621879: +2024-11-22 16:30:50.622100: Epoch 5468 +2024-11-22 16:30:50.622216: Current learning rate: 0.00355 +2024-11-22 16:31:09.178981: train_loss -0.8058 +2024-11-22 16:31:09.181387: val_loss -0.7725 +2024-11-22 16:31:09.181480: Pseudo dice [0.8433] +2024-11-22 16:31:09.181558: Epoch time: 18.56 s +2024-11-22 16:31:09.181621: Yayy! New best EMA pseudo Dice: 0.8379 +2024-11-22 16:31:10.562455: +2024-11-22 16:31:10.562679: Epoch 5469 +2024-11-22 16:31:10.562793: Current learning rate: 0.00355 +2024-11-22 16:31:28.383132: train_loss -0.8022 +2024-11-22 16:31:28.383368: val_loss -0.7679 +2024-11-22 16:31:28.383443: Pseudo dice [0.844] +2024-11-22 16:31:28.383518: Epoch time: 17.82 s +2024-11-22 16:31:28.383579: Yayy! New best EMA pseudo Dice: 0.8385 +2024-11-22 16:31:29.570803: +2024-11-22 16:31:29.571012: Epoch 5470 +2024-11-22 16:31:29.571128: Current learning rate: 0.00355 +2024-11-22 16:31:47.815987: train_loss -0.8039 +2024-11-22 16:31:47.816213: val_loss -0.7405 +2024-11-22 16:31:47.816305: Pseudo dice [0.8445] +2024-11-22 16:31:47.816450: Epoch time: 18.25 s +2024-11-22 16:31:47.816513: Yayy! New best EMA pseudo Dice: 0.8391 +2024-11-22 16:31:48.991895: +2024-11-22 16:31:48.992124: Epoch 5471 +2024-11-22 16:31:48.992238: Current learning rate: 0.00355 +2024-11-22 16:32:08.133851: train_loss -0.8003 +2024-11-22 16:32:08.134096: val_loss -0.7613 +2024-11-22 16:32:08.134176: Pseudo dice [0.8357] +2024-11-22 16:32:08.134259: Epoch time: 19.14 s +2024-11-22 16:32:09.130739: +2024-11-22 16:32:09.130961: Epoch 5472 +2024-11-22 16:32:09.131087: Current learning rate: 0.00355 +2024-11-22 16:32:28.519737: train_loss -0.7994 +2024-11-22 16:32:28.520018: val_loss -0.7499 +2024-11-22 16:32:28.520098: Pseudo dice [0.8298] +2024-11-22 16:32:28.520183: Epoch time: 19.38 s +2024-11-22 16:32:29.473967: +2024-11-22 16:32:29.474265: Epoch 5473 +2024-11-22 16:32:29.474380: Current learning rate: 0.00354 +2024-11-22 16:32:47.737686: train_loss -0.7892 +2024-11-22 16:32:47.737904: val_loss -0.7065 +2024-11-22 16:32:47.737996: Pseudo dice [0.8214] +2024-11-22 16:32:47.738070: Epoch time: 18.26 s +2024-11-22 16:32:48.733255: +2024-11-22 16:32:48.733450: Epoch 5474 +2024-11-22 16:32:48.733569: Current learning rate: 0.00354 +2024-11-22 16:33:07.785329: train_loss -0.7952 +2024-11-22 16:33:07.785548: val_loss -0.7632 +2024-11-22 16:33:07.785621: Pseudo dice [0.8316] +2024-11-22 16:33:07.785698: Epoch time: 19.05 s +2024-11-22 16:33:08.690037: +2024-11-22 16:33:08.690257: Epoch 5475 +2024-11-22 16:33:08.690370: Current learning rate: 0.00354 +2024-11-22 16:33:27.389712: train_loss -0.7947 +2024-11-22 16:33:27.389953: val_loss -0.7373 +2024-11-22 16:33:27.390038: Pseudo dice [0.8283] +2024-11-22 16:33:27.390122: Epoch time: 18.7 s +2024-11-22 16:33:28.296190: +2024-11-22 16:33:28.296682: Epoch 5476 +2024-11-22 16:33:28.296820: Current learning rate: 0.00354 +2024-11-22 16:33:47.212703: train_loss -0.7944 +2024-11-22 16:33:47.212915: val_loss -0.7375 +2024-11-22 16:33:47.212987: Pseudo dice [0.8415] +2024-11-22 16:33:47.213071: Epoch time: 18.92 s +2024-11-22 16:33:48.489935: +2024-11-22 16:33:48.490165: Epoch 5477 +2024-11-22 16:33:48.490291: Current learning rate: 0.00354 +2024-11-22 16:34:07.496924: train_loss -0.8027 +2024-11-22 16:34:07.497158: val_loss -0.7266 +2024-11-22 16:34:07.497234: Pseudo dice [0.8117] +2024-11-22 16:34:07.497312: Epoch time: 19.01 s +2024-11-22 16:34:08.413767: +2024-11-22 16:34:08.413985: Epoch 5478 +2024-11-22 16:34:08.414103: Current learning rate: 0.00354 +2024-11-22 16:34:26.619720: train_loss -0.804 +2024-11-22 16:34:26.619941: val_loss -0.7757 +2024-11-22 16:34:26.620024: Pseudo dice [0.8481] +2024-11-22 16:34:26.620102: Epoch time: 18.21 s +2024-11-22 16:34:27.631979: +2024-11-22 16:34:27.632263: Epoch 5479 +2024-11-22 16:34:27.632423: Current learning rate: 0.00354 +2024-11-22 16:34:45.659701: train_loss -0.8021 +2024-11-22 16:34:45.659938: val_loss -0.781 +2024-11-22 16:34:45.660025: Pseudo dice [0.8427] +2024-11-22 16:34:45.660108: Epoch time: 18.03 s +2024-11-22 16:34:46.554631: +2024-11-22 16:34:46.554858: Epoch 5480 +2024-11-22 16:34:46.554979: Current learning rate: 0.00354 +2024-11-22 16:35:04.764646: train_loss -0.8063 +2024-11-22 16:35:04.767962: val_loss -0.7545 +2024-11-22 16:35:04.768150: Pseudo dice [0.8249] +2024-11-22 16:35:04.768234: Epoch time: 18.21 s +2024-11-22 16:35:05.654835: +2024-11-22 16:35:05.655035: Epoch 5481 +2024-11-22 16:35:05.655151: Current learning rate: 0.00353 +2024-11-22 16:35:25.624902: train_loss -0.8052 +2024-11-22 16:35:25.625120: val_loss -0.7534 +2024-11-22 16:35:25.625196: Pseudo dice [0.8307] +2024-11-22 16:35:25.625271: Epoch time: 19.97 s +2024-11-22 16:35:26.520604: +2024-11-22 16:35:26.520797: Epoch 5482 +2024-11-22 16:35:26.520912: Current learning rate: 0.00353 +2024-11-22 16:35:46.100850: train_loss -0.8037 +2024-11-22 16:35:46.101075: val_loss -0.7688 +2024-11-22 16:35:46.101151: Pseudo dice [0.8341] +2024-11-22 16:35:46.101229: Epoch time: 19.58 s +2024-11-22 16:35:46.996928: +2024-11-22 16:35:46.997194: Epoch 5483 +2024-11-22 16:35:46.997310: Current learning rate: 0.00353 +2024-11-22 16:36:04.514784: train_loss -0.8048 +2024-11-22 16:36:04.517232: val_loss -0.7667 +2024-11-22 16:36:04.517365: Pseudo dice [0.8231] +2024-11-22 16:36:04.517452: Epoch time: 17.52 s +2024-11-22 16:36:05.445746: +2024-11-22 16:36:05.446022: Epoch 5484 +2024-11-22 16:36:05.446138: Current learning rate: 0.00353 +2024-11-22 16:36:23.138683: train_loss -0.805 +2024-11-22 16:36:23.138916: val_loss -0.7594 +2024-11-22 16:36:23.139002: Pseudo dice [0.8393] +2024-11-22 16:36:23.139078: Epoch time: 17.69 s +2024-11-22 16:36:24.043740: +2024-11-22 16:36:24.043938: Epoch 5485 +2024-11-22 16:36:24.044062: Current learning rate: 0.00353 +2024-11-22 16:36:42.487560: train_loss -0.7996 +2024-11-22 16:36:42.489623: val_loss -0.7438 +2024-11-22 16:36:42.489794: Pseudo dice [0.8356] +2024-11-22 16:36:42.489875: Epoch time: 18.44 s +2024-11-22 16:36:43.386903: +2024-11-22 16:36:43.387103: Epoch 5486 +2024-11-22 16:36:43.387217: Current learning rate: 0.00353 +2024-11-22 16:37:01.443645: train_loss -0.8034 +2024-11-22 16:37:01.443868: val_loss -0.744 +2024-11-22 16:37:01.443942: Pseudo dice [0.8183] +2024-11-22 16:37:01.444027: Epoch time: 18.06 s +2024-11-22 16:37:02.472059: +2024-11-22 16:37:02.472328: Epoch 5487 +2024-11-22 16:37:02.472446: Current learning rate: 0.00353 +2024-11-22 16:37:20.376829: train_loss -0.8039 +2024-11-22 16:37:20.377073: val_loss -0.7604 +2024-11-22 16:37:20.377158: Pseudo dice [0.8327] +2024-11-22 16:37:20.377241: Epoch time: 17.91 s +2024-11-22 16:37:21.367682: +2024-11-22 16:37:21.367976: Epoch 5488 +2024-11-22 16:37:21.368101: Current learning rate: 0.00353 +2024-11-22 16:37:40.309293: train_loss -0.8015 +2024-11-22 16:37:40.309519: val_loss -0.7461 +2024-11-22 16:37:40.309597: Pseudo dice [0.8129] +2024-11-22 16:37:40.314847: Epoch time: 18.94 s +2024-11-22 16:37:41.639514: +2024-11-22 16:37:41.639742: Epoch 5489 +2024-11-22 16:37:41.639858: Current learning rate: 0.00352 +2024-11-22 16:37:59.843370: train_loss -0.7918 +2024-11-22 16:37:59.843605: val_loss -0.7545 +2024-11-22 16:37:59.843681: Pseudo dice [0.8422] +2024-11-22 16:37:59.843757: Epoch time: 18.2 s +2024-11-22 16:38:00.739313: +2024-11-22 16:38:00.739575: Epoch 5490 +2024-11-22 16:38:00.739685: Current learning rate: 0.00352 +2024-11-22 16:38:20.432792: train_loss -0.7969 +2024-11-22 16:38:20.433053: val_loss -0.7456 +2024-11-22 16:38:20.433133: Pseudo dice [0.8124] +2024-11-22 16:38:20.433223: Epoch time: 19.69 s +2024-11-22 16:38:21.326752: +2024-11-22 16:38:21.326975: Epoch 5491 +2024-11-22 16:38:21.327098: Current learning rate: 0.00352 +2024-11-22 16:38:40.446939: train_loss -0.8003 +2024-11-22 16:38:40.447169: val_loss -0.7378 +2024-11-22 16:38:40.447249: Pseudo dice [0.8239] +2024-11-22 16:38:40.447326: Epoch time: 19.12 s +2024-11-22 16:38:41.460328: +2024-11-22 16:38:41.460546: Epoch 5492 +2024-11-22 16:38:41.460656: Current learning rate: 0.00352 +2024-11-22 16:39:01.130542: train_loss -0.8058 +2024-11-22 16:39:01.130785: val_loss -0.7381 +2024-11-22 16:39:01.130861: Pseudo dice [0.8343] +2024-11-22 16:39:01.130939: Epoch time: 19.67 s +2024-11-22 16:39:02.194728: +2024-11-22 16:39:02.194945: Epoch 5493 +2024-11-22 16:39:02.195068: Current learning rate: 0.00352 +2024-11-22 16:39:20.966672: train_loss -0.8022 +2024-11-22 16:39:20.966890: val_loss -0.7699 +2024-11-22 16:39:20.966964: Pseudo dice [0.8357] +2024-11-22 16:39:20.969299: Epoch time: 18.77 s +2024-11-22 16:39:21.953112: +2024-11-22 16:39:21.953302: Epoch 5494 +2024-11-22 16:39:21.953414: Current learning rate: 0.00352 +2024-11-22 16:39:41.463097: train_loss -0.7972 +2024-11-22 16:39:41.463354: val_loss -0.7644 +2024-11-22 16:39:41.463428: Pseudo dice [0.8357] +2024-11-22 16:39:41.463513: Epoch time: 19.51 s +2024-11-22 16:39:42.357044: +2024-11-22 16:39:42.357292: Epoch 5495 +2024-11-22 16:39:42.357405: Current learning rate: 0.00352 +2024-11-22 16:40:00.978338: train_loss -0.7901 +2024-11-22 16:40:00.978562: val_loss -0.7434 +2024-11-22 16:40:00.978636: Pseudo dice [0.8237] +2024-11-22 16:40:00.978712: Epoch time: 18.62 s +2024-11-22 16:40:01.879638: +2024-11-22 16:40:01.879835: Epoch 5496 +2024-11-22 16:40:01.879948: Current learning rate: 0.00352 +2024-11-22 16:40:20.776121: train_loss -0.7945 +2024-11-22 16:40:20.776342: val_loss -0.7501 +2024-11-22 16:40:20.776417: Pseudo dice [0.8269] +2024-11-22 16:40:20.776492: Epoch time: 18.9 s +2024-11-22 16:40:21.683967: +2024-11-22 16:40:21.684208: Epoch 5497 +2024-11-22 16:40:21.684329: Current learning rate: 0.00351 +2024-11-22 16:40:41.119602: train_loss -0.7986 +2024-11-22 16:40:41.119828: val_loss -0.7642 +2024-11-22 16:40:41.119904: Pseudo dice [0.8273] +2024-11-22 16:40:41.119982: Epoch time: 19.44 s +2024-11-22 16:40:42.146468: +2024-11-22 16:40:42.146686: Epoch 5498 +2024-11-22 16:40:42.146800: Current learning rate: 0.00351 +2024-11-22 16:40:59.697881: train_loss -0.8012 +2024-11-22 16:40:59.698128: val_loss -0.7569 +2024-11-22 16:40:59.698205: Pseudo dice [0.8161] +2024-11-22 16:40:59.698291: Epoch time: 17.55 s +2024-11-22 16:41:00.596466: +2024-11-22 16:41:00.596689: Epoch 5499 +2024-11-22 16:41:00.596804: Current learning rate: 0.00351 +2024-11-22 16:41:19.932024: train_loss -0.8009 +2024-11-22 16:41:19.932250: val_loss -0.7495 +2024-11-22 16:41:19.932328: Pseudo dice [0.8385] +2024-11-22 16:41:19.934594: Epoch time: 19.34 s +2024-11-22 16:41:21.187281: +2024-11-22 16:41:21.187502: Epoch 5500 +2024-11-22 16:41:21.187616: Current learning rate: 0.00351 +2024-11-22 16:41:40.913784: train_loss -0.8057 +2024-11-22 16:41:40.914035: val_loss -0.7616 +2024-11-22 16:41:40.914109: Pseudo dice [0.8411] +2024-11-22 16:41:40.914183: Epoch time: 19.73 s +2024-11-22 16:41:41.851967: +2024-11-22 16:41:41.852312: Epoch 5501 +2024-11-22 16:41:41.852425: Current learning rate: 0.00351 +2024-11-22 16:42:01.661840: train_loss -0.8039 +2024-11-22 16:42:01.664231: val_loss -0.7515 +2024-11-22 16:42:01.664330: Pseudo dice [0.8364] +2024-11-22 16:42:01.664413: Epoch time: 19.81 s +2024-11-22 16:42:02.599365: +2024-11-22 16:42:02.599572: Epoch 5502 +2024-11-22 16:42:02.599685: Current learning rate: 0.00351 +2024-11-22 16:42:19.906957: train_loss -0.8076 +2024-11-22 16:42:19.907215: val_loss -0.7677 +2024-11-22 16:42:19.907293: Pseudo dice [0.8374] +2024-11-22 16:42:19.907379: Epoch time: 17.31 s +2024-11-22 16:42:20.896196: +2024-11-22 16:42:20.896410: Epoch 5503 +2024-11-22 16:42:20.896523: Current learning rate: 0.00351 +2024-11-22 16:42:39.740410: train_loss -0.8064 +2024-11-22 16:42:39.740653: val_loss -0.7552 +2024-11-22 16:42:39.740732: Pseudo dice [0.8302] +2024-11-22 16:42:39.740813: Epoch time: 18.85 s +2024-11-22 16:42:40.631067: +2024-11-22 16:42:40.631308: Epoch 5504 +2024-11-22 16:42:40.631427: Current learning rate: 0.00351 +2024-11-22 16:43:00.975806: train_loss -0.8117 +2024-11-22 16:43:00.976052: val_loss -0.7521 +2024-11-22 16:43:00.976135: Pseudo dice [0.8487] +2024-11-22 16:43:00.976216: Epoch time: 20.35 s +2024-11-22 16:43:01.877263: +2024-11-22 16:43:01.877463: Epoch 5505 +2024-11-22 16:43:01.877580: Current learning rate: 0.0035 +2024-11-22 16:43:19.784291: train_loss -0.8046 +2024-11-22 16:43:19.784517: val_loss -0.7337 +2024-11-22 16:43:19.784593: Pseudo dice [0.8229] +2024-11-22 16:43:19.784671: Epoch time: 17.91 s +2024-11-22 16:43:20.814636: +2024-11-22 16:43:20.814821: Epoch 5506 +2024-11-22 16:43:20.814964: Current learning rate: 0.0035 +2024-11-22 16:43:39.619457: train_loss -0.8056 +2024-11-22 16:43:39.619758: val_loss -0.7422 +2024-11-22 16:43:39.619839: Pseudo dice [0.8231] +2024-11-22 16:43:39.619924: Epoch time: 18.81 s +2024-11-22 16:43:40.517381: +2024-11-22 16:43:40.517575: Epoch 5507 +2024-11-22 16:43:40.517689: Current learning rate: 0.0035 +2024-11-22 16:43:58.008019: train_loss -0.8095 +2024-11-22 16:43:58.008238: val_loss -0.7577 +2024-11-22 16:43:58.010447: Pseudo dice [0.8246] +2024-11-22 16:43:58.010573: Epoch time: 17.49 s +2024-11-22 16:43:58.957422: +2024-11-22 16:43:58.957654: Epoch 5508 +2024-11-22 16:43:58.957778: Current learning rate: 0.0035 +2024-11-22 16:44:17.074180: train_loss -0.8135 +2024-11-22 16:44:17.074407: val_loss -0.7575 +2024-11-22 16:44:17.074483: Pseudo dice [0.8233] +2024-11-22 16:44:17.074559: Epoch time: 18.12 s +2024-11-22 16:44:18.013363: +2024-11-22 16:44:18.013564: Epoch 5509 +2024-11-22 16:44:18.013675: Current learning rate: 0.0035 +2024-11-22 16:44:36.530835: train_loss -0.8004 +2024-11-22 16:44:36.531086: val_loss -0.7637 +2024-11-22 16:44:36.531159: Pseudo dice [0.8382] +2024-11-22 16:44:36.531244: Epoch time: 18.52 s +2024-11-22 16:44:37.429174: +2024-11-22 16:44:37.429384: Epoch 5510 +2024-11-22 16:44:37.429502: Current learning rate: 0.0035 +2024-11-22 16:44:56.718658: train_loss -0.7936 +2024-11-22 16:44:56.718880: val_loss -0.7811 +2024-11-22 16:44:56.718959: Pseudo dice [0.8394] +2024-11-22 16:44:56.719044: Epoch time: 19.29 s +2024-11-22 16:44:57.612423: +2024-11-22 16:44:57.612630: Epoch 5511 +2024-11-22 16:44:57.612749: Current learning rate: 0.0035 +2024-11-22 16:45:16.154116: train_loss -0.797 +2024-11-22 16:45:16.154330: val_loss -0.7655 +2024-11-22 16:45:16.154408: Pseudo dice [0.8435] +2024-11-22 16:45:16.154481: Epoch time: 18.54 s +2024-11-22 16:45:17.415756: +2024-11-22 16:45:17.415989: Epoch 5512 +2024-11-22 16:45:17.416107: Current learning rate: 0.0035 +2024-11-22 16:45:35.765984: train_loss -0.8045 +2024-11-22 16:45:35.766336: val_loss -0.737 +2024-11-22 16:45:35.766420: Pseudo dice [0.8324] +2024-11-22 16:45:35.766512: Epoch time: 18.35 s +2024-11-22 16:45:36.687191: +2024-11-22 16:45:36.687587: Epoch 5513 +2024-11-22 16:45:36.687707: Current learning rate: 0.00349 +2024-11-22 16:45:54.879507: train_loss -0.8054 +2024-11-22 16:45:54.879737: val_loss -0.7496 +2024-11-22 16:45:54.879815: Pseudo dice [0.8319] +2024-11-22 16:45:54.879890: Epoch time: 18.19 s +2024-11-22 16:45:55.768347: +2024-11-22 16:45:55.768596: Epoch 5514 +2024-11-22 16:45:55.768707: Current learning rate: 0.00349 +2024-11-22 16:46:14.136787: train_loss -0.8085 +2024-11-22 16:46:14.137089: val_loss -0.742 +2024-11-22 16:46:14.137170: Pseudo dice [0.8166] +2024-11-22 16:46:14.137251: Epoch time: 18.37 s +2024-11-22 16:46:15.032367: +2024-11-22 16:46:15.032598: Epoch 5515 +2024-11-22 16:46:15.032710: Current learning rate: 0.00349 +2024-11-22 16:46:32.868417: train_loss -0.8061 +2024-11-22 16:46:32.868638: val_loss -0.76 +2024-11-22 16:46:32.868740: Pseudo dice [0.8362] +2024-11-22 16:46:32.868820: Epoch time: 17.84 s +2024-11-22 16:46:33.773226: +2024-11-22 16:46:33.773458: Epoch 5516 +2024-11-22 16:46:33.773585: Current learning rate: 0.00349 +2024-11-22 16:46:53.240213: train_loss -0.8036 +2024-11-22 16:46:53.240488: val_loss -0.7648 +2024-11-22 16:46:53.240570: Pseudo dice [0.8288] +2024-11-22 16:46:53.240655: Epoch time: 19.47 s +2024-11-22 16:46:54.143482: +2024-11-22 16:46:54.143702: Epoch 5517 +2024-11-22 16:46:54.143816: Current learning rate: 0.00349 +2024-11-22 16:47:12.480504: train_loss -0.8048 +2024-11-22 16:47:12.480723: val_loss -0.7491 +2024-11-22 16:47:12.480798: Pseudo dice [0.8341] +2024-11-22 16:47:12.480875: Epoch time: 18.34 s +2024-11-22 16:47:13.388284: +2024-11-22 16:47:13.388503: Epoch 5518 +2024-11-22 16:47:13.388614: Current learning rate: 0.00349 +2024-11-22 16:47:32.173147: train_loss -0.8037 +2024-11-22 16:47:32.173376: val_loss -0.7406 +2024-11-22 16:47:32.178609: Pseudo dice [0.8421] +2024-11-22 16:47:32.178753: Epoch time: 18.79 s +2024-11-22 16:47:33.179832: +2024-11-22 16:47:33.180053: Epoch 5519 +2024-11-22 16:47:33.180168: Current learning rate: 0.00349 +2024-11-22 16:47:52.922448: train_loss -0.7987 +2024-11-22 16:47:52.922679: val_loss -0.7393 +2024-11-22 16:47:52.922758: Pseudo dice [0.8225] +2024-11-22 16:47:52.922841: Epoch time: 19.74 s +2024-11-22 16:47:53.816697: +2024-11-22 16:47:53.816920: Epoch 5520 +2024-11-22 16:47:53.817046: Current learning rate: 0.00349 +2024-11-22 16:48:11.807467: train_loss -0.8032 +2024-11-22 16:48:11.807679: val_loss -0.7726 +2024-11-22 16:48:11.807753: Pseudo dice [0.8357] +2024-11-22 16:48:11.807842: Epoch time: 17.99 s +2024-11-22 16:48:12.704808: +2024-11-22 16:48:12.705027: Epoch 5521 +2024-11-22 16:48:12.705148: Current learning rate: 0.00348 +2024-11-22 16:48:31.625154: train_loss -0.8039 +2024-11-22 16:48:31.625393: val_loss -0.7696 +2024-11-22 16:48:31.625466: Pseudo dice [0.8458] +2024-11-22 16:48:31.625543: Epoch time: 18.92 s +2024-11-22 16:48:32.787410: +2024-11-22 16:48:32.787623: Epoch 5522 +2024-11-22 16:48:32.787742: Current learning rate: 0.00348 +2024-11-22 16:48:51.316421: train_loss -0.7994 +2024-11-22 16:48:51.316637: val_loss -0.7345 +2024-11-22 16:48:51.316716: Pseudo dice [0.8179] +2024-11-22 16:48:51.316797: Epoch time: 18.53 s +2024-11-22 16:48:52.212255: +2024-11-22 16:48:52.212669: Epoch 5523 +2024-11-22 16:48:52.212807: Current learning rate: 0.00348 +2024-11-22 16:49:10.769192: train_loss -0.7981 +2024-11-22 16:49:10.769433: val_loss -0.728 +2024-11-22 16:49:10.769508: Pseudo dice [0.808] +2024-11-22 16:49:10.769587: Epoch time: 18.56 s +2024-11-22 16:49:12.063662: +2024-11-22 16:49:12.063874: Epoch 5524 +2024-11-22 16:49:12.063989: Current learning rate: 0.00348 +2024-11-22 16:49:30.711870: train_loss -0.7982 +2024-11-22 16:49:30.712101: val_loss -0.7491 +2024-11-22 16:49:30.712179: Pseudo dice [0.8283] +2024-11-22 16:49:30.712263: Epoch time: 18.65 s +2024-11-22 16:49:31.637811: +2024-11-22 16:49:31.638092: Epoch 5525 +2024-11-22 16:49:31.638206: Current learning rate: 0.00348 +2024-11-22 16:49:50.661936: train_loss -0.7873 +2024-11-22 16:49:50.662205: val_loss -0.7428 +2024-11-22 16:49:50.662283: Pseudo dice [0.8263] +2024-11-22 16:49:50.662360: Epoch time: 19.02 s +2024-11-22 16:49:51.567662: +2024-11-22 16:49:51.567866: Epoch 5526 +2024-11-22 16:49:51.567976: Current learning rate: 0.00348 +2024-11-22 16:50:10.109042: train_loss -0.7889 +2024-11-22 16:50:10.109285: val_loss -0.778 +2024-11-22 16:50:10.109360: Pseudo dice [0.8288] +2024-11-22 16:50:10.109443: Epoch time: 18.54 s +2024-11-22 16:50:11.022003: +2024-11-22 16:50:11.022225: Epoch 5527 +2024-11-22 16:50:11.022340: Current learning rate: 0.00348 +2024-11-22 16:50:29.675146: train_loss -0.7996 +2024-11-22 16:50:29.675396: val_loss -0.7672 +2024-11-22 16:50:29.675472: Pseudo dice [0.849] +2024-11-22 16:50:29.675545: Epoch time: 18.65 s +2024-11-22 16:50:30.670743: +2024-11-22 16:50:30.670962: Epoch 5528 +2024-11-22 16:50:30.671084: Current learning rate: 0.00348 +2024-11-22 16:50:49.326066: train_loss -0.7965 +2024-11-22 16:50:49.326296: val_loss -0.732 +2024-11-22 16:50:49.326375: Pseudo dice [0.8156] +2024-11-22 16:50:49.326450: Epoch time: 18.66 s +2024-11-22 16:50:50.242780: +2024-11-22 16:50:50.243057: Epoch 5529 +2024-11-22 16:50:50.243177: Current learning rate: 0.00347 +2024-11-22 16:51:08.261011: train_loss -0.7916 +2024-11-22 16:51:08.261241: val_loss -0.7532 +2024-11-22 16:51:08.261317: Pseudo dice [0.8204] +2024-11-22 16:51:08.261401: Epoch time: 18.02 s +2024-11-22 16:51:09.156700: +2024-11-22 16:51:09.156900: Epoch 5530 +2024-11-22 16:51:09.157024: Current learning rate: 0.00347 +2024-11-22 16:51:27.867135: train_loss -0.7996 +2024-11-22 16:51:27.867385: val_loss -0.7351 +2024-11-22 16:51:27.867465: Pseudo dice [0.8226] +2024-11-22 16:51:27.867623: Epoch time: 18.71 s +2024-11-22 16:51:28.762817: +2024-11-22 16:51:28.763067: Epoch 5531 +2024-11-22 16:51:28.763182: Current learning rate: 0.00347 +2024-11-22 16:51:48.548667: train_loss -0.802 +2024-11-22 16:51:48.548878: val_loss -0.7183 +2024-11-22 16:51:48.548973: Pseudo dice [0.8273] +2024-11-22 16:51:48.549064: Epoch time: 19.79 s +2024-11-22 16:51:49.441540: +2024-11-22 16:51:49.441736: Epoch 5532 +2024-11-22 16:51:49.441845: Current learning rate: 0.00347 +2024-11-22 16:52:07.966933: train_loss -0.8034 +2024-11-22 16:52:07.967155: val_loss -0.7513 +2024-11-22 16:52:07.967235: Pseudo dice [0.8387] +2024-11-22 16:52:07.967313: Epoch time: 18.53 s +2024-11-22 16:52:08.865254: +2024-11-22 16:52:08.865449: Epoch 5533 +2024-11-22 16:52:08.866001: Current learning rate: 0.00347 +2024-11-22 16:52:27.288340: train_loss -0.809 +2024-11-22 16:52:27.288573: val_loss -0.7573 +2024-11-22 16:52:27.288658: Pseudo dice [0.8192] +2024-11-22 16:52:27.288743: Epoch time: 18.42 s +2024-11-22 16:52:28.184150: +2024-11-22 16:52:28.184370: Epoch 5534 +2024-11-22 16:52:28.184487: Current learning rate: 0.00347 +2024-11-22 16:52:47.444397: train_loss -0.7998 +2024-11-22 16:52:47.444645: val_loss -0.7613 +2024-11-22 16:52:47.444721: Pseudo dice [0.8489] +2024-11-22 16:52:47.444805: Epoch time: 19.26 s +2024-11-22 16:52:48.407018: +2024-11-22 16:52:48.407204: Epoch 5535 +2024-11-22 16:52:48.407317: Current learning rate: 0.00347 +2024-11-22 16:53:08.153673: train_loss -0.8052 +2024-11-22 16:53:08.153888: val_loss -0.7483 +2024-11-22 16:53:08.153962: Pseudo dice [0.836] +2024-11-22 16:53:08.154045: Epoch time: 19.75 s +2024-11-22 16:53:09.453008: +2024-11-22 16:53:09.453228: Epoch 5536 +2024-11-22 16:53:09.453341: Current learning rate: 0.00346 +2024-11-22 16:53:28.039194: train_loss -0.8063 +2024-11-22 16:53:28.039430: val_loss -0.7753 +2024-11-22 16:53:28.039505: Pseudo dice [0.8415] +2024-11-22 16:53:28.039585: Epoch time: 18.59 s +2024-11-22 16:53:28.938149: +2024-11-22 16:53:28.938385: Epoch 5537 +2024-11-22 16:53:28.938501: Current learning rate: 0.00346 +2024-11-22 16:53:47.720428: train_loss -0.8042 +2024-11-22 16:53:47.720657: val_loss -0.7631 +2024-11-22 16:53:47.720732: Pseudo dice [0.8498] +2024-11-22 16:53:47.720811: Epoch time: 18.78 s +2024-11-22 16:53:48.615646: +2024-11-22 16:53:48.615867: Epoch 5538 +2024-11-22 16:53:48.615983: Current learning rate: 0.00346 +2024-11-22 16:54:07.892542: train_loss -0.8056 +2024-11-22 16:54:07.893889: val_loss -0.7686 +2024-11-22 16:54:07.894035: Pseudo dice [0.8305] +2024-11-22 16:54:07.894114: Epoch time: 19.28 s +2024-11-22 16:54:08.814972: +2024-11-22 16:54:08.815236: Epoch 5539 +2024-11-22 16:54:08.815363: Current learning rate: 0.00346 +2024-11-22 16:54:26.614695: train_loss -0.8079 +2024-11-22 16:54:26.614914: val_loss -0.7695 +2024-11-22 16:54:26.614989: Pseudo dice [0.8538] +2024-11-22 16:54:26.615089: Epoch time: 17.8 s +2024-11-22 16:54:27.501184: +2024-11-22 16:54:27.501393: Epoch 5540 +2024-11-22 16:54:27.501512: Current learning rate: 0.00346 +2024-11-22 16:54:46.483023: train_loss -0.8068 +2024-11-22 16:54:46.483264: val_loss -0.753 +2024-11-22 16:54:46.483340: Pseudo dice [0.8246] +2024-11-22 16:54:46.483426: Epoch time: 18.98 s +2024-11-22 16:54:47.466655: +2024-11-22 16:54:47.466889: Epoch 5541 +2024-11-22 16:54:47.467010: Current learning rate: 0.00346 +2024-11-22 16:55:05.720386: train_loss -0.8122 +2024-11-22 16:55:05.720605: val_loss -0.7678 +2024-11-22 16:55:05.720682: Pseudo dice [0.8319] +2024-11-22 16:55:05.720754: Epoch time: 18.25 s +2024-11-22 16:55:06.835279: +2024-11-22 16:55:06.835476: Epoch 5542 +2024-11-22 16:55:06.835586: Current learning rate: 0.00346 +2024-11-22 16:55:25.892366: train_loss -0.8052 +2024-11-22 16:55:25.892572: val_loss -0.7691 +2024-11-22 16:55:25.892645: Pseudo dice [0.8375] +2024-11-22 16:55:25.892720: Epoch time: 19.06 s +2024-11-22 16:55:26.772668: +2024-11-22 16:55:26.772873: Epoch 5543 +2024-11-22 16:55:26.772984: Current learning rate: 0.00346 +2024-11-22 16:55:46.072798: train_loss -0.8088 +2024-11-22 16:55:46.073030: val_loss -0.7786 +2024-11-22 16:55:46.073107: Pseudo dice [0.8333] +2024-11-22 16:55:46.073190: Epoch time: 19.3 s +2024-11-22 16:55:46.969676: +2024-11-22 16:55:46.969885: Epoch 5544 +2024-11-22 16:55:46.970004: Current learning rate: 0.00345 +2024-11-22 16:56:05.498341: train_loss -0.8064 +2024-11-22 16:56:05.498581: val_loss -0.7566 +2024-11-22 16:56:05.498659: Pseudo dice [0.8314] +2024-11-22 16:56:05.498737: Epoch time: 18.53 s +2024-11-22 16:56:06.388226: +2024-11-22 16:56:06.388472: Epoch 5545 +2024-11-22 16:56:06.388579: Current learning rate: 0.00345 +2024-11-22 16:56:26.007780: train_loss -0.8062 +2024-11-22 16:56:26.010168: val_loss -0.7518 +2024-11-22 16:56:26.010286: Pseudo dice [0.8313] +2024-11-22 16:56:26.037698: Epoch time: 19.62 s +2024-11-22 16:56:27.097876: +2024-11-22 16:56:27.098139: Epoch 5546 +2024-11-22 16:56:27.098252: Current learning rate: 0.00345 +2024-11-22 16:56:46.180611: train_loss -0.8041 +2024-11-22 16:56:46.183010: val_loss -0.7538 +2024-11-22 16:56:46.183114: Pseudo dice [0.8179] +2024-11-22 16:56:46.183194: Epoch time: 19.08 s +2024-11-22 16:56:47.120113: +2024-11-22 16:56:47.120313: Epoch 5547 +2024-11-22 16:56:47.120427: Current learning rate: 0.00345 +2024-11-22 16:57:06.277201: train_loss -0.804 +2024-11-22 16:57:06.277449: val_loss -0.7494 +2024-11-22 16:57:06.277523: Pseudo dice [0.8236] +2024-11-22 16:57:06.277606: Epoch time: 19.16 s +2024-11-22 16:57:07.582383: +2024-11-22 16:57:07.582683: Epoch 5548 +2024-11-22 16:57:07.582797: Current learning rate: 0.00345 +2024-11-22 16:57:26.062598: train_loss -0.7999 +2024-11-22 16:57:26.062825: val_loss -0.7692 +2024-11-22 16:57:26.062898: Pseudo dice [0.8229] +2024-11-22 16:57:26.063051: Epoch time: 18.48 s +2024-11-22 16:57:26.960841: +2024-11-22 16:57:26.961063: Epoch 5549 +2024-11-22 16:57:26.961177: Current learning rate: 0.00345 +2024-11-22 16:57:45.309274: train_loss -0.8037 +2024-11-22 16:57:45.309492: val_loss -0.7429 +2024-11-22 16:57:45.309566: Pseudo dice [0.8209] +2024-11-22 16:57:45.309648: Epoch time: 18.35 s +2024-11-22 16:57:46.516680: +2024-11-22 16:57:46.516895: Epoch 5550 +2024-11-22 16:57:46.517008: Current learning rate: 0.00345 +2024-11-22 16:58:05.441400: train_loss -0.7938 +2024-11-22 16:58:05.441642: val_loss -0.7547 +2024-11-22 16:58:05.441716: Pseudo dice [0.8318] +2024-11-22 16:58:05.441799: Epoch time: 18.93 s +2024-11-22 16:58:06.326967: +2024-11-22 16:58:06.327181: Epoch 5551 +2024-11-22 16:58:06.327297: Current learning rate: 0.00345 +2024-11-22 16:58:25.138540: train_loss -0.8052 +2024-11-22 16:58:25.138770: val_loss -0.7461 +2024-11-22 16:58:25.138845: Pseudo dice [0.8314] +2024-11-22 16:58:25.138921: Epoch time: 18.81 s +2024-11-22 16:58:26.019562: +2024-11-22 16:58:26.019761: Epoch 5552 +2024-11-22 16:58:26.019864: Current learning rate: 0.00344 +2024-11-22 16:58:43.837971: train_loss -0.8037 +2024-11-22 16:58:43.838198: val_loss -0.7397 +2024-11-22 16:58:43.838271: Pseudo dice [0.8268] +2024-11-22 16:58:43.838346: Epoch time: 17.82 s +2024-11-22 16:58:44.822726: +2024-11-22 16:58:44.822941: Epoch 5553 +2024-11-22 16:58:44.823060: Current learning rate: 0.00344 +2024-11-22 16:59:02.997911: train_loss -0.8152 +2024-11-22 16:59:02.998141: val_loss -0.7844 +2024-11-22 16:59:02.998222: Pseudo dice [0.8463] +2024-11-22 16:59:02.998301: Epoch time: 18.18 s +2024-11-22 16:59:03.896570: +2024-11-22 16:59:03.896784: Epoch 5554 +2024-11-22 16:59:03.896897: Current learning rate: 0.00344 +2024-11-22 16:59:22.471605: train_loss -0.8054 +2024-11-22 16:59:22.471905: val_loss -0.7775 +2024-11-22 16:59:22.471982: Pseudo dice [0.8399] +2024-11-22 16:59:22.472073: Epoch time: 18.58 s +2024-11-22 16:59:23.367677: +2024-11-22 16:59:23.367897: Epoch 5555 +2024-11-22 16:59:23.368167: Current learning rate: 0.00344 +2024-11-22 16:59:41.553880: train_loss -0.8168 +2024-11-22 16:59:41.554112: val_loss -0.7587 +2024-11-22 16:59:41.554291: Pseudo dice [0.8253] +2024-11-22 16:59:41.554384: Epoch time: 18.19 s +2024-11-22 16:59:42.458801: +2024-11-22 16:59:42.459013: Epoch 5556 +2024-11-22 16:59:42.459132: Current learning rate: 0.00344 +2024-11-22 17:00:00.292859: train_loss -0.8064 +2024-11-22 17:00:00.293086: val_loss -0.7657 +2024-11-22 17:00:00.293161: Pseudo dice [0.8479] +2024-11-22 17:00:00.293239: Epoch time: 17.83 s +2024-11-22 17:00:01.287952: +2024-11-22 17:00:01.288178: Epoch 5557 +2024-11-22 17:00:01.288291: Current learning rate: 0.00344 +2024-11-22 17:00:20.469292: train_loss -0.799 +2024-11-22 17:00:20.469517: val_loss -0.7445 +2024-11-22 17:00:20.469593: Pseudo dice [0.825] +2024-11-22 17:00:20.469671: Epoch time: 19.18 s +2024-11-22 17:00:21.368309: +2024-11-22 17:00:21.368507: Epoch 5558 +2024-11-22 17:00:21.368622: Current learning rate: 0.00344 +2024-11-22 17:00:40.535765: train_loss -0.8024 +2024-11-22 17:00:40.560462: val_loss -0.7556 +2024-11-22 17:00:40.560554: Pseudo dice [0.8403] +2024-11-22 17:00:40.560642: Epoch time: 19.17 s +2024-11-22 17:00:41.457846: +2024-11-22 17:00:41.458059: Epoch 5559 +2024-11-22 17:00:41.458175: Current learning rate: 0.00344 +2024-11-22 17:00:59.295969: train_loss -0.8076 +2024-11-22 17:00:59.296206: val_loss -0.7779 +2024-11-22 17:00:59.296281: Pseudo dice [0.8444] +2024-11-22 17:00:59.296357: Epoch time: 17.84 s +2024-11-22 17:01:00.639851: +2024-11-22 17:01:00.640152: Epoch 5560 +2024-11-22 17:01:00.640271: Current learning rate: 0.00343 +2024-11-22 17:01:19.086178: train_loss -0.7984 +2024-11-22 17:01:19.086423: val_loss -0.7563 +2024-11-22 17:01:19.086500: Pseudo dice [0.8224] +2024-11-22 17:01:19.086579: Epoch time: 18.45 s +2024-11-22 17:01:20.074146: +2024-11-22 17:01:20.074387: Epoch 5561 +2024-11-22 17:01:20.074507: Current learning rate: 0.00343 +2024-11-22 17:01:38.091286: train_loss -0.8047 +2024-11-22 17:01:38.091538: val_loss -0.772 +2024-11-22 17:01:38.091614: Pseudo dice [0.8445] +2024-11-22 17:01:38.096870: Epoch time: 18.02 s +2024-11-22 17:01:39.193667: +2024-11-22 17:01:39.193877: Epoch 5562 +2024-11-22 17:01:39.193989: Current learning rate: 0.00343 +2024-11-22 17:01:59.634925: train_loss -0.8029 +2024-11-22 17:01:59.635158: val_loss -0.7472 +2024-11-22 17:01:59.635235: Pseudo dice [0.8206] +2024-11-22 17:01:59.635313: Epoch time: 20.44 s +2024-11-22 17:02:00.527765: +2024-11-22 17:02:00.528094: Epoch 5563 +2024-11-22 17:02:00.528217: Current learning rate: 0.00343 +2024-11-22 17:02:18.389128: train_loss -0.8064 +2024-11-22 17:02:18.389357: val_loss -0.7743 +2024-11-22 17:02:18.391656: Pseudo dice [0.8548] +2024-11-22 17:02:18.391773: Epoch time: 17.86 s +2024-11-22 17:02:19.308308: +2024-11-22 17:02:19.308533: Epoch 5564 +2024-11-22 17:02:19.308654: Current learning rate: 0.00343 +2024-11-22 17:02:38.251275: train_loss -0.8059 +2024-11-22 17:02:38.251511: val_loss -0.7496 +2024-11-22 17:02:38.251586: Pseudo dice [0.8383] +2024-11-22 17:02:38.251663: Epoch time: 18.94 s +2024-11-22 17:02:39.354782: +2024-11-22 17:02:39.355002: Epoch 5565 +2024-11-22 17:02:39.355114: Current learning rate: 0.00343 +2024-11-22 17:02:58.265013: train_loss -0.7959 +2024-11-22 17:02:58.265346: val_loss -0.7519 +2024-11-22 17:02:58.265426: Pseudo dice [0.8535] +2024-11-22 17:02:58.265515: Epoch time: 18.91 s +2024-11-22 17:02:59.184809: +2024-11-22 17:02:59.185025: Epoch 5566 +2024-11-22 17:02:59.185139: Current learning rate: 0.00343 +2024-11-22 17:03:17.693874: train_loss -0.7992 +2024-11-22 17:03:17.694107: val_loss -0.7649 +2024-11-22 17:03:17.694186: Pseudo dice [0.8306] +2024-11-22 17:03:17.694262: Epoch time: 18.51 s +2024-11-22 17:03:18.611961: +2024-11-22 17:03:18.612260: Epoch 5567 +2024-11-22 17:03:18.612373: Current learning rate: 0.00343 +2024-11-22 17:03:37.397135: train_loss -0.8012 +2024-11-22 17:03:37.397381: val_loss -0.7321 +2024-11-22 17:03:37.397461: Pseudo dice [0.8353] +2024-11-22 17:03:37.397542: Epoch time: 18.79 s +2024-11-22 17:03:38.298356: +2024-11-22 17:03:38.298545: Epoch 5568 +2024-11-22 17:03:38.298655: Current learning rate: 0.00342 +2024-11-22 17:03:57.323700: train_loss -0.7976 +2024-11-22 17:03:57.323924: val_loss -0.733 +2024-11-22 17:03:57.324011: Pseudo dice [0.824] +2024-11-22 17:03:57.324088: Epoch time: 19.03 s +2024-11-22 17:03:58.229544: +2024-11-22 17:03:58.229769: Epoch 5569 +2024-11-22 17:03:58.229881: Current learning rate: 0.00342 +2024-11-22 17:04:16.521827: train_loss -0.7944 +2024-11-22 17:04:16.522090: val_loss -0.7434 +2024-11-22 17:04:16.522165: Pseudo dice [0.8209] +2024-11-22 17:04:16.522253: Epoch time: 18.29 s +2024-11-22 17:04:17.418599: +2024-11-22 17:04:17.419105: Epoch 5570 +2024-11-22 17:04:17.419248: Current learning rate: 0.00342 +2024-11-22 17:04:35.838106: train_loss -0.8044 +2024-11-22 17:04:35.838341: val_loss -0.7558 +2024-11-22 17:04:35.838416: Pseudo dice [0.8563] +2024-11-22 17:04:35.838496: Epoch time: 18.42 s +2024-11-22 17:04:36.747873: +2024-11-22 17:04:36.748070: Epoch 5571 +2024-11-22 17:04:36.748185: Current learning rate: 0.00342 +2024-11-22 17:04:55.680292: train_loss -0.8025 +2024-11-22 17:04:55.680532: val_loss -0.7424 +2024-11-22 17:04:55.680606: Pseudo dice [0.8308] +2024-11-22 17:04:55.680681: Epoch time: 18.93 s +2024-11-22 17:04:56.991863: +2024-11-22 17:04:56.992083: Epoch 5572 +2024-11-22 17:04:56.992200: Current learning rate: 0.00342 +2024-11-22 17:05:15.468835: train_loss -0.7956 +2024-11-22 17:05:15.469064: val_loss -0.7275 +2024-11-22 17:05:15.469141: Pseudo dice [0.8398] +2024-11-22 17:05:15.469221: Epoch time: 18.48 s +2024-11-22 17:05:16.368187: +2024-11-22 17:05:16.368444: Epoch 5573 +2024-11-22 17:05:16.368604: Current learning rate: 0.00342 +2024-11-22 17:05:35.054544: train_loss -0.7926 +2024-11-22 17:05:35.054774: val_loss -0.7588 +2024-11-22 17:05:35.054850: Pseudo dice [0.8226] +2024-11-22 17:05:35.054929: Epoch time: 18.69 s +2024-11-22 17:05:36.084564: +2024-11-22 17:05:36.084774: Epoch 5574 +2024-11-22 17:05:36.084883: Current learning rate: 0.00342 +2024-11-22 17:05:54.422147: train_loss -0.7821 +2024-11-22 17:05:54.422388: val_loss -0.7639 +2024-11-22 17:05:54.422472: Pseudo dice [0.8326] +2024-11-22 17:05:54.422550: Epoch time: 18.34 s +2024-11-22 17:05:55.330563: +2024-11-22 17:05:55.330784: Epoch 5575 +2024-11-22 17:05:55.330899: Current learning rate: 0.00342 +2024-11-22 17:06:14.325922: train_loss -0.7941 +2024-11-22 17:06:14.326153: val_loss -0.7525 +2024-11-22 17:06:14.326235: Pseudo dice [0.8325] +2024-11-22 17:06:14.326311: Epoch time: 19.0 s +2024-11-22 17:06:15.287600: +2024-11-22 17:06:15.287807: Epoch 5576 +2024-11-22 17:06:15.287919: Current learning rate: 0.00341 +2024-11-22 17:06:34.829392: train_loss -0.7777 +2024-11-22 17:06:34.829635: val_loss -0.7505 +2024-11-22 17:06:34.829734: Pseudo dice [0.8294] +2024-11-22 17:06:34.829854: Epoch time: 19.54 s +2024-11-22 17:06:35.732046: +2024-11-22 17:06:35.732279: Epoch 5577 +2024-11-22 17:06:35.732393: Current learning rate: 0.00341 +2024-11-22 17:06:54.127757: train_loss -0.7895 +2024-11-22 17:06:54.127979: val_loss -0.7437 +2024-11-22 17:06:54.128061: Pseudo dice [0.8059] +2024-11-22 17:06:54.130328: Epoch time: 18.4 s +2024-11-22 17:06:55.150284: +2024-11-22 17:06:55.150507: Epoch 5578 +2024-11-22 17:06:55.150624: Current learning rate: 0.00341 +2024-11-22 17:07:13.045950: train_loss -0.7908 +2024-11-22 17:07:13.046190: val_loss -0.7609 +2024-11-22 17:07:13.046264: Pseudo dice [0.8159] +2024-11-22 17:07:13.046339: Epoch time: 17.9 s +2024-11-22 17:07:14.200187: +2024-11-22 17:07:14.200390: Epoch 5579 +2024-11-22 17:07:14.200501: Current learning rate: 0.00341 +2024-11-22 17:07:33.260232: train_loss -0.7902 +2024-11-22 17:07:33.260479: val_loss -0.7364 +2024-11-22 17:07:33.260571: Pseudo dice [0.8183] +2024-11-22 17:07:33.260701: Epoch time: 19.06 s +2024-11-22 17:07:34.157386: +2024-11-22 17:07:34.157614: Epoch 5580 +2024-11-22 17:07:34.157731: Current learning rate: 0.00341 +2024-11-22 17:07:52.762666: train_loss -0.794 +2024-11-22 17:07:52.762909: val_loss -0.7567 +2024-11-22 17:07:52.762986: Pseudo dice [0.8308] +2024-11-22 17:07:52.763075: Epoch time: 18.61 s +2024-11-22 17:07:53.650330: +2024-11-22 17:07:53.651022: Epoch 5581 +2024-11-22 17:07:53.651175: Current learning rate: 0.00341 +2024-11-22 17:08:11.101179: train_loss -0.8007 +2024-11-22 17:08:11.101391: val_loss -0.748 +2024-11-22 17:08:11.101463: Pseudo dice [0.8331] +2024-11-22 17:08:11.101537: Epoch time: 17.45 s +2024-11-22 17:08:12.047226: +2024-11-22 17:08:12.047570: Epoch 5582 +2024-11-22 17:08:12.047688: Current learning rate: 0.00341 +2024-11-22 17:08:30.402650: train_loss -0.7956 +2024-11-22 17:08:30.402973: val_loss -0.7534 +2024-11-22 17:08:30.403062: Pseudo dice [0.8198] +2024-11-22 17:08:30.403137: Epoch time: 18.36 s +2024-11-22 17:08:31.295048: +2024-11-22 17:08:31.295277: Epoch 5583 +2024-11-22 17:08:31.295400: Current learning rate: 0.00341 +2024-11-22 17:08:50.403892: train_loss -0.7996 +2024-11-22 17:08:50.404140: val_loss -0.7486 +2024-11-22 17:08:50.404219: Pseudo dice [0.8243] +2024-11-22 17:08:50.404302: Epoch time: 19.11 s +2024-11-22 17:08:51.709465: +2024-11-22 17:08:51.709690: Epoch 5584 +2024-11-22 17:08:51.709807: Current learning rate: 0.0034 +2024-11-22 17:09:09.594398: train_loss -0.8004 +2024-11-22 17:09:09.594635: val_loss -0.7738 +2024-11-22 17:09:09.594711: Pseudo dice [0.8349] +2024-11-22 17:09:09.594789: Epoch time: 17.89 s +2024-11-22 17:09:10.545608: +2024-11-22 17:09:10.545836: Epoch 5585 +2024-11-22 17:09:10.545949: Current learning rate: 0.0034 +2024-11-22 17:09:29.040277: train_loss -0.8014 +2024-11-22 17:09:29.040502: val_loss -0.7441 +2024-11-22 17:09:29.040576: Pseudo dice [0.8431] +2024-11-22 17:09:29.040655: Epoch time: 18.5 s +2024-11-22 17:09:29.935087: +2024-11-22 17:09:29.935300: Epoch 5586 +2024-11-22 17:09:29.935411: Current learning rate: 0.0034 +2024-11-22 17:09:48.761745: train_loss -0.8022 +2024-11-22 17:09:48.761950: val_loss -0.7336 +2024-11-22 17:09:48.762027: Pseudo dice [0.8126] +2024-11-22 17:09:48.762107: Epoch time: 18.83 s +2024-11-22 17:09:49.803560: +2024-11-22 17:09:49.803807: Epoch 5587 +2024-11-22 17:09:49.803919: Current learning rate: 0.0034 +2024-11-22 17:10:08.009433: train_loss -0.8044 +2024-11-22 17:10:08.009650: val_loss -0.7559 +2024-11-22 17:10:08.009725: Pseudo dice [0.8399] +2024-11-22 17:10:08.009800: Epoch time: 18.21 s +2024-11-22 17:10:08.906156: +2024-11-22 17:10:08.906365: Epoch 5588 +2024-11-22 17:10:08.906483: Current learning rate: 0.0034 +2024-11-22 17:10:27.471199: train_loss -0.8018 +2024-11-22 17:10:27.474086: val_loss -0.7515 +2024-11-22 17:10:27.474176: Pseudo dice [0.8273] +2024-11-22 17:10:27.474250: Epoch time: 18.57 s +2024-11-22 17:10:28.408079: +2024-11-22 17:10:28.408303: Epoch 5589 +2024-11-22 17:10:28.408416: Current learning rate: 0.0034 +2024-11-22 17:10:47.514600: train_loss -0.7976 +2024-11-22 17:10:47.514819: val_loss -0.7505 +2024-11-22 17:10:47.514891: Pseudo dice [0.8381] +2024-11-22 17:10:47.520087: Epoch time: 19.11 s +2024-11-22 17:10:48.566171: +2024-11-22 17:10:48.566542: Epoch 5590 +2024-11-22 17:10:48.566669: Current learning rate: 0.0034 +2024-11-22 17:11:07.512625: train_loss -0.8091 +2024-11-22 17:11:07.512928: val_loss -0.7299 +2024-11-22 17:11:07.513015: Pseudo dice [0.8333] +2024-11-22 17:11:07.513098: Epoch time: 18.95 s +2024-11-22 17:11:08.438707: +2024-11-22 17:11:08.438929: Epoch 5591 +2024-11-22 17:11:08.439049: Current learning rate: 0.0034 +2024-11-22 17:11:26.902613: train_loss -0.8075 +2024-11-22 17:11:26.902833: val_loss -0.7289 +2024-11-22 17:11:26.902932: Pseudo dice [0.836] +2024-11-22 17:11:26.903016: Epoch time: 18.46 s +2024-11-22 17:11:27.804091: +2024-11-22 17:11:27.804307: Epoch 5592 +2024-11-22 17:11:27.804416: Current learning rate: 0.00339 +2024-11-22 17:11:45.911530: train_loss -0.8072 +2024-11-22 17:11:45.911756: val_loss -0.7728 +2024-11-22 17:11:45.911829: Pseudo dice [0.8348] +2024-11-22 17:11:45.911905: Epoch time: 18.11 s +2024-11-22 17:11:46.803912: +2024-11-22 17:11:46.804116: Epoch 5593 +2024-11-22 17:11:46.804225: Current learning rate: 0.00339 +2024-11-22 17:12:05.065291: train_loss -0.812 +2024-11-22 17:12:05.065568: val_loss -0.7575 +2024-11-22 17:12:05.065651: Pseudo dice [0.8254] +2024-11-22 17:12:05.065732: Epoch time: 18.26 s +2024-11-22 17:12:05.962499: +2024-11-22 17:12:05.962906: Epoch 5594 +2024-11-22 17:12:05.963048: Current learning rate: 0.00339 +2024-11-22 17:12:24.446360: train_loss -0.8065 +2024-11-22 17:12:24.446614: val_loss -0.7701 +2024-11-22 17:12:24.446691: Pseudo dice [0.8351] +2024-11-22 17:12:24.446772: Epoch time: 18.48 s +2024-11-22 17:12:25.342292: +2024-11-22 17:12:25.342541: Epoch 5595 +2024-11-22 17:12:25.342652: Current learning rate: 0.00339 +2024-11-22 17:12:44.029751: train_loss -0.8039 +2024-11-22 17:12:44.029971: val_loss -0.759 +2024-11-22 17:12:44.030056: Pseudo dice [0.8276] +2024-11-22 17:12:44.030133: Epoch time: 18.69 s +2024-11-22 17:12:45.395408: +2024-11-22 17:12:45.395624: Epoch 5596 +2024-11-22 17:12:45.395738: Current learning rate: 0.00339 +2024-11-22 17:13:03.927478: train_loss -0.8068 +2024-11-22 17:13:03.927708: val_loss -0.7638 +2024-11-22 17:13:03.927783: Pseudo dice [0.8434] +2024-11-22 17:13:03.927859: Epoch time: 18.53 s +2024-11-22 17:13:04.826012: +2024-11-22 17:13:04.826220: Epoch 5597 +2024-11-22 17:13:04.826331: Current learning rate: 0.00339 +2024-11-22 17:13:23.786157: train_loss -0.8024 +2024-11-22 17:13:23.786407: val_loss -0.7615 +2024-11-22 17:13:23.786498: Pseudo dice [0.8227] +2024-11-22 17:13:23.786623: Epoch time: 18.96 s +2024-11-22 17:13:24.683898: +2024-11-22 17:13:24.684169: Epoch 5598 +2024-11-22 17:13:24.684279: Current learning rate: 0.00339 +2024-11-22 17:13:43.398128: train_loss -0.8067 +2024-11-22 17:13:43.398336: val_loss -0.7561 +2024-11-22 17:13:43.398409: Pseudo dice [0.844] +2024-11-22 17:13:43.398484: Epoch time: 18.72 s +2024-11-22 17:13:44.333024: +2024-11-22 17:13:44.333265: Epoch 5599 +2024-11-22 17:13:44.333385: Current learning rate: 0.00339 +2024-11-22 17:14:03.868424: train_loss -0.7983 +2024-11-22 17:14:03.868647: val_loss -0.7302 +2024-11-22 17:14:03.868725: Pseudo dice [0.8231] +2024-11-22 17:14:03.868803: Epoch time: 19.54 s +2024-11-22 17:14:05.141937: +2024-11-22 17:14:05.142161: Epoch 5600 +2024-11-22 17:14:05.142276: Current learning rate: 0.00338 +2024-11-22 17:14:23.454490: train_loss -0.8043 +2024-11-22 17:14:23.454723: val_loss -0.747 +2024-11-22 17:14:23.454799: Pseudo dice [0.8358] +2024-11-22 17:14:23.457106: Epoch time: 18.31 s +2024-11-22 17:14:24.526587: +2024-11-22 17:14:24.526803: Epoch 5601 +2024-11-22 17:14:24.526916: Current learning rate: 0.00338 +2024-11-22 17:14:42.751110: train_loss -0.8076 +2024-11-22 17:14:42.751353: val_loss -0.7599 +2024-11-22 17:14:42.751430: Pseudo dice [0.831] +2024-11-22 17:14:42.751518: Epoch time: 18.23 s +2024-11-22 17:14:43.651145: +2024-11-22 17:14:43.651366: Epoch 5602 +2024-11-22 17:14:43.651479: Current learning rate: 0.00338 +2024-11-22 17:15:03.137383: train_loss -0.8065 +2024-11-22 17:15:03.137616: val_loss -0.758 +2024-11-22 17:15:03.137689: Pseudo dice [0.8152] +2024-11-22 17:15:03.137766: Epoch time: 19.49 s +2024-11-22 17:15:04.062850: +2024-11-22 17:15:04.063191: Epoch 5603 +2024-11-22 17:15:04.063301: Current learning rate: 0.00338 +2024-11-22 17:15:22.898602: train_loss -0.7997 +2024-11-22 17:15:22.898825: val_loss -0.7565 +2024-11-22 17:15:22.898901: Pseudo dice [0.8218] +2024-11-22 17:15:22.898977: Epoch time: 18.84 s +2024-11-22 17:15:24.102843: +2024-11-22 17:15:24.103055: Epoch 5604 +2024-11-22 17:15:24.103173: Current learning rate: 0.00338 +2024-11-22 17:15:41.936536: train_loss -0.8021 +2024-11-22 17:15:41.936775: val_loss -0.7574 +2024-11-22 17:15:41.936849: Pseudo dice [0.8347] +2024-11-22 17:15:41.936926: Epoch time: 17.83 s +2024-11-22 17:15:42.829322: +2024-11-22 17:15:42.829526: Epoch 5605 +2024-11-22 17:15:42.829640: Current learning rate: 0.00338 +2024-11-22 17:16:02.299386: train_loss -0.7937 +2024-11-22 17:16:02.299670: val_loss -0.747 +2024-11-22 17:16:02.299750: Pseudo dice [0.8291] +2024-11-22 17:16:02.299837: Epoch time: 19.47 s +2024-11-22 17:16:03.279137: +2024-11-22 17:16:03.279570: Epoch 5606 +2024-11-22 17:16:03.279707: Current learning rate: 0.00338 +2024-11-22 17:16:22.088546: train_loss -0.804 +2024-11-22 17:16:22.093959: val_loss -0.7525 +2024-11-22 17:16:22.094077: Pseudo dice [0.8376] +2024-11-22 17:16:22.094157: Epoch time: 18.81 s +2024-11-22 17:16:23.176311: +2024-11-22 17:16:23.176494: Epoch 5607 +2024-11-22 17:16:23.176606: Current learning rate: 0.00337 +2024-11-22 17:16:42.293039: train_loss -0.8085 +2024-11-22 17:16:42.293289: val_loss -0.7742 +2024-11-22 17:16:42.293368: Pseudo dice [0.8344] +2024-11-22 17:16:42.293446: Epoch time: 19.12 s +2024-11-22 17:16:43.188543: +2024-11-22 17:16:43.188771: Epoch 5608 +2024-11-22 17:16:43.188888: Current learning rate: 0.00337 +2024-11-22 17:17:01.223424: train_loss -0.8109 +2024-11-22 17:17:01.223652: val_loss -0.7753 +2024-11-22 17:17:01.223753: Pseudo dice [0.8365] +2024-11-22 17:17:01.223835: Epoch time: 18.04 s +2024-11-22 17:17:02.118438: +2024-11-22 17:17:02.118661: Epoch 5609 +2024-11-22 17:17:02.118774: Current learning rate: 0.00337 +2024-11-22 17:17:20.283809: train_loss -0.8078 +2024-11-22 17:17:20.284135: val_loss -0.7395 +2024-11-22 17:17:20.284219: Pseudo dice [0.8335] +2024-11-22 17:17:20.284303: Epoch time: 18.17 s +2024-11-22 17:17:21.178954: +2024-11-22 17:17:21.179221: Epoch 5610 +2024-11-22 17:17:21.179336: Current learning rate: 0.00337 +2024-11-22 17:17:40.020009: train_loss -0.8103 +2024-11-22 17:17:40.020293: val_loss -0.7614 +2024-11-22 17:17:40.020372: Pseudo dice [0.8462] +2024-11-22 17:17:40.020454: Epoch time: 18.84 s +2024-11-22 17:17:40.910667: +2024-11-22 17:17:40.910877: Epoch 5611 +2024-11-22 17:17:40.910994: Current learning rate: 0.00337 +2024-11-22 17:17:59.659503: train_loss -0.8054 +2024-11-22 17:17:59.659741: val_loss -0.7264 +2024-11-22 17:17:59.659820: Pseudo dice [0.8307] +2024-11-22 17:17:59.659900: Epoch time: 18.75 s +2024-11-22 17:18:00.567746: +2024-11-22 17:18:00.567964: Epoch 5612 +2024-11-22 17:18:00.568082: Current learning rate: 0.00337 +2024-11-22 17:18:19.209769: train_loss -0.8089 +2024-11-22 17:18:19.210006: val_loss -0.7639 +2024-11-22 17:18:19.210086: Pseudo dice [0.8362] +2024-11-22 17:18:19.210168: Epoch time: 18.64 s +2024-11-22 17:18:20.104155: +2024-11-22 17:18:20.104487: Epoch 5613 +2024-11-22 17:18:20.104601: Current learning rate: 0.00337 +2024-11-22 17:18:39.067157: train_loss -0.8029 +2024-11-22 17:18:39.067411: val_loss -0.7328 +2024-11-22 17:18:39.067487: Pseudo dice [0.8148] +2024-11-22 17:18:39.067575: Epoch time: 18.96 s +2024-11-22 17:18:40.069211: +2024-11-22 17:18:40.069431: Epoch 5614 +2024-11-22 17:18:40.069551: Current learning rate: 0.00337 +2024-11-22 17:18:58.560792: train_loss -0.8078 +2024-11-22 17:18:58.561023: val_loss -0.7666 +2024-11-22 17:18:58.561099: Pseudo dice [0.8519] +2024-11-22 17:18:58.561177: Epoch time: 18.49 s +2024-11-22 17:18:59.452804: +2024-11-22 17:18:59.453022: Epoch 5615 +2024-11-22 17:18:59.453137: Current learning rate: 0.00336 +2024-11-22 17:19:17.884195: train_loss -0.7989 +2024-11-22 17:19:17.884423: val_loss -0.7462 +2024-11-22 17:19:17.884507: Pseudo dice [0.8368] +2024-11-22 17:19:17.884581: Epoch time: 18.43 s +2024-11-22 17:19:18.778475: +2024-11-22 17:19:18.778793: Epoch 5616 +2024-11-22 17:19:18.778912: Current learning rate: 0.00336 +2024-11-22 17:19:37.679396: train_loss -0.804 +2024-11-22 17:19:37.679609: val_loss -0.7394 +2024-11-22 17:19:37.679687: Pseudo dice [0.8041] +2024-11-22 17:19:37.679768: Epoch time: 18.9 s +2024-11-22 17:19:38.574871: +2024-11-22 17:19:38.575074: Epoch 5617 +2024-11-22 17:19:38.575193: Current learning rate: 0.00336 +2024-11-22 17:19:56.747191: train_loss -0.8014 +2024-11-22 17:19:56.752615: val_loss -0.7605 +2024-11-22 17:19:56.752698: Pseudo dice [0.8314] +2024-11-22 17:19:56.752792: Epoch time: 18.17 s +2024-11-22 17:19:57.812434: +2024-11-22 17:19:57.812636: Epoch 5618 +2024-11-22 17:19:57.812747: Current learning rate: 0.00336 +2024-11-22 17:20:15.845829: train_loss -0.8048 +2024-11-22 17:20:15.846043: val_loss -0.7485 +2024-11-22 17:20:15.846119: Pseudo dice [0.8263] +2024-11-22 17:20:15.846208: Epoch time: 18.03 s +2024-11-22 17:20:17.076420: +2024-11-22 17:20:17.076643: Epoch 5619 +2024-11-22 17:20:17.076756: Current learning rate: 0.00336 +2024-11-22 17:20:35.455106: train_loss -0.8002 +2024-11-22 17:20:35.455351: val_loss -0.7735 +2024-11-22 17:20:35.455425: Pseudo dice [0.8361] +2024-11-22 17:20:35.455503: Epoch time: 18.38 s +2024-11-22 17:20:36.376318: +2024-11-22 17:20:36.376623: Epoch 5620 +2024-11-22 17:20:36.376736: Current learning rate: 0.00336 +2024-11-22 17:20:55.715350: train_loss -0.8004 +2024-11-22 17:20:55.715653: val_loss -0.7456 +2024-11-22 17:20:55.715731: Pseudo dice [0.8263] +2024-11-22 17:20:55.715814: Epoch time: 19.34 s +2024-11-22 17:20:56.676579: +2024-11-22 17:20:56.676785: Epoch 5621 +2024-11-22 17:20:56.676897: Current learning rate: 0.00336 +2024-11-22 17:21:15.753649: train_loss -0.7981 +2024-11-22 17:21:15.753876: val_loss -0.7705 +2024-11-22 17:21:15.753951: Pseudo dice [0.8417] +2024-11-22 17:21:15.754036: Epoch time: 19.08 s +2024-11-22 17:21:16.641610: +2024-11-22 17:21:16.641811: Epoch 5622 +2024-11-22 17:21:16.641917: Current learning rate: 0.00336 +2024-11-22 17:21:35.243347: train_loss -0.7944 +2024-11-22 17:21:35.243605: val_loss -0.7567 +2024-11-22 17:21:35.243682: Pseudo dice [0.8386] +2024-11-22 17:21:35.245989: Epoch time: 18.6 s +2024-11-22 17:21:36.330895: +2024-11-22 17:21:36.331118: Epoch 5623 +2024-11-22 17:21:36.331234: Current learning rate: 0.00335 +2024-11-22 17:21:56.195269: train_loss -0.7892 +2024-11-22 17:21:56.195492: val_loss -0.7462 +2024-11-22 17:21:56.195565: Pseudo dice [0.8388] +2024-11-22 17:21:56.195641: Epoch time: 19.87 s +2024-11-22 17:21:57.075212: +2024-11-22 17:21:57.075424: Epoch 5624 +2024-11-22 17:21:57.075539: Current learning rate: 0.00335 +2024-11-22 17:22:15.992378: train_loss -0.7857 +2024-11-22 17:22:15.992598: val_loss -0.7395 +2024-11-22 17:22:15.992673: Pseudo dice [0.8238] +2024-11-22 17:22:15.992754: Epoch time: 18.92 s +2024-11-22 17:22:16.879879: +2024-11-22 17:22:16.880110: Epoch 5625 +2024-11-22 17:22:16.880265: Current learning rate: 0.00335 +2024-11-22 17:22:34.692464: train_loss -0.7884 +2024-11-22 17:22:34.692700: val_loss -0.7252 +2024-11-22 17:22:34.697917: Pseudo dice [0.8307] +2024-11-22 17:22:34.698075: Epoch time: 17.81 s +2024-11-22 17:22:35.722576: +2024-11-22 17:22:35.723014: Epoch 5626 +2024-11-22 17:22:35.723142: Current learning rate: 0.00335 +2024-11-22 17:22:54.736753: train_loss -0.8009 +2024-11-22 17:22:54.736969: val_loss -0.732 +2024-11-22 17:22:54.737062: Pseudo dice [0.8305] +2024-11-22 17:22:54.737144: Epoch time: 19.01 s +2024-11-22 17:22:55.627667: +2024-11-22 17:22:55.627924: Epoch 5627 +2024-11-22 17:22:55.628039: Current learning rate: 0.00335 +2024-11-22 17:23:14.884176: train_loss -0.7974 +2024-11-22 17:23:14.884386: val_loss -0.7551 +2024-11-22 17:23:14.884459: Pseudo dice [0.8352] +2024-11-22 17:23:14.884533: Epoch time: 19.26 s +2024-11-22 17:23:15.764737: +2024-11-22 17:23:15.764955: Epoch 5628 +2024-11-22 17:23:15.765086: Current learning rate: 0.00335 +2024-11-22 17:23:34.255477: train_loss -0.7958 +2024-11-22 17:23:34.255717: val_loss -0.7643 +2024-11-22 17:23:34.255789: Pseudo dice [0.8424] +2024-11-22 17:23:34.255868: Epoch time: 18.49 s +2024-11-22 17:23:35.153948: +2024-11-22 17:23:35.154158: Epoch 5629 +2024-11-22 17:23:35.154264: Current learning rate: 0.00335 +2024-11-22 17:23:53.712848: train_loss -0.7966 +2024-11-22 17:23:53.713135: val_loss -0.744 +2024-11-22 17:23:53.713212: Pseudo dice [0.8367] +2024-11-22 17:23:53.713288: Epoch time: 18.56 s +2024-11-22 17:23:54.641146: +2024-11-22 17:23:54.641345: Epoch 5630 +2024-11-22 17:23:54.641458: Current learning rate: 0.00335 +2024-11-22 17:24:13.637046: train_loss -0.7996 +2024-11-22 17:24:13.637284: val_loss -0.7462 +2024-11-22 17:24:13.637357: Pseudo dice [0.829] +2024-11-22 17:24:13.637433: Epoch time: 19.0 s +2024-11-22 17:24:15.029505: +2024-11-22 17:24:15.029801: Epoch 5631 +2024-11-22 17:24:15.029919: Current learning rate: 0.00334 +2024-11-22 17:24:33.380327: train_loss -0.8014 +2024-11-22 17:24:33.380602: val_loss -0.758 +2024-11-22 17:24:33.380685: Pseudo dice [0.8253] +2024-11-22 17:24:33.380807: Epoch time: 18.35 s +2024-11-22 17:24:34.284328: +2024-11-22 17:24:34.284555: Epoch 5632 +2024-11-22 17:24:34.284663: Current learning rate: 0.00334 +2024-11-22 17:24:52.094968: train_loss -0.8079 +2024-11-22 17:24:52.095208: val_loss -0.7192 +2024-11-22 17:24:52.100451: Pseudo dice [0.8249] +2024-11-22 17:24:52.100623: Epoch time: 17.81 s +2024-11-22 17:24:53.179321: +2024-11-22 17:24:53.179522: Epoch 5633 +2024-11-22 17:24:53.179632: Current learning rate: 0.00334 +2024-11-22 17:25:12.887348: train_loss -0.8103 +2024-11-22 17:25:12.887587: val_loss -0.7508 +2024-11-22 17:25:12.887662: Pseudo dice [0.8427] +2024-11-22 17:25:12.887740: Epoch time: 19.71 s +2024-11-22 17:25:13.876297: +2024-11-22 17:25:13.876522: Epoch 5634 +2024-11-22 17:25:13.876641: Current learning rate: 0.00334 +2024-11-22 17:25:32.498064: train_loss -0.8072 +2024-11-22 17:25:32.498277: val_loss -0.7585 +2024-11-22 17:25:32.498356: Pseudo dice [0.8209] +2024-11-22 17:25:32.498436: Epoch time: 18.62 s +2024-11-22 17:25:33.379029: +2024-11-22 17:25:33.379230: Epoch 5635 +2024-11-22 17:25:33.379336: Current learning rate: 0.00334 +2024-11-22 17:25:51.547612: train_loss -0.8017 +2024-11-22 17:25:51.547864: val_loss -0.7381 +2024-11-22 17:25:51.547945: Pseudo dice [0.8377] +2024-11-22 17:25:51.548040: Epoch time: 18.17 s +2024-11-22 17:25:52.440597: +2024-11-22 17:25:52.440830: Epoch 5636 +2024-11-22 17:25:52.440940: Current learning rate: 0.00334 +2024-11-22 17:26:11.721328: train_loss -0.8055 +2024-11-22 17:26:11.721548: val_loss -0.719 +2024-11-22 17:26:11.721626: Pseudo dice [0.8305] +2024-11-22 17:26:11.721705: Epoch time: 19.28 s +2024-11-22 17:26:12.631299: +2024-11-22 17:26:12.631607: Epoch 5637 +2024-11-22 17:26:12.631720: Current learning rate: 0.00334 +2024-11-22 17:26:31.492969: train_loss -0.804 +2024-11-22 17:26:31.499500: val_loss -0.7561 +2024-11-22 17:26:31.499604: Pseudo dice [0.8256] +2024-11-22 17:26:31.499683: Epoch time: 18.86 s +2024-11-22 17:26:32.573639: +2024-11-22 17:26:32.573825: Epoch 5638 +2024-11-22 17:26:32.573934: Current learning rate: 0.00334 +2024-11-22 17:26:50.580930: train_loss -0.802 +2024-11-22 17:26:50.581186: val_loss -0.7622 +2024-11-22 17:26:50.581262: Pseudo dice [0.8366] +2024-11-22 17:26:50.581347: Epoch time: 18.01 s +2024-11-22 17:26:51.477277: +2024-11-22 17:26:51.477486: Epoch 5639 +2024-11-22 17:26:51.477608: Current learning rate: 0.00333 +2024-11-22 17:27:10.294522: train_loss -0.8052 +2024-11-22 17:27:10.294747: val_loss -0.7589 +2024-11-22 17:27:10.294827: Pseudo dice [0.8362] +2024-11-22 17:27:10.294906: Epoch time: 18.82 s +2024-11-22 17:27:11.196684: +2024-11-22 17:27:11.197124: Epoch 5640 +2024-11-22 17:27:11.197264: Current learning rate: 0.00333 +2024-11-22 17:27:30.117290: train_loss -0.8027 +2024-11-22 17:27:30.117503: val_loss -0.7533 +2024-11-22 17:27:30.117576: Pseudo dice [0.835] +2024-11-22 17:27:30.117651: Epoch time: 18.92 s +2024-11-22 17:27:31.011251: +2024-11-22 17:27:31.011432: Epoch 5641 +2024-11-22 17:27:31.011540: Current learning rate: 0.00333 +2024-11-22 17:27:50.490254: train_loss -0.8111 +2024-11-22 17:27:50.490523: val_loss -0.7541 +2024-11-22 17:27:50.490602: Pseudo dice [0.8362] +2024-11-22 17:27:50.490686: Epoch time: 19.48 s +2024-11-22 17:27:51.363234: +2024-11-22 17:27:51.363437: Epoch 5642 +2024-11-22 17:27:51.363549: Current learning rate: 0.00333 +2024-11-22 17:28:10.601582: train_loss -0.8096 +2024-11-22 17:28:10.601802: val_loss -0.7456 +2024-11-22 17:28:10.601880: Pseudo dice [0.8377] +2024-11-22 17:28:10.601956: Epoch time: 19.24 s +2024-11-22 17:28:11.882662: +2024-11-22 17:28:11.882899: Epoch 5643 +2024-11-22 17:28:11.883016: Current learning rate: 0.00333 +2024-11-22 17:28:29.663119: train_loss -0.8115 +2024-11-22 17:28:29.663357: val_loss -0.753 +2024-11-22 17:28:29.663435: Pseudo dice [0.832] +2024-11-22 17:28:29.663512: Epoch time: 17.78 s +2024-11-22 17:28:30.558349: +2024-11-22 17:28:30.558566: Epoch 5644 +2024-11-22 17:28:30.558683: Current learning rate: 0.00333 +2024-11-22 17:28:49.649513: train_loss -0.8008 +2024-11-22 17:28:49.649784: val_loss -0.7486 +2024-11-22 17:28:49.649866: Pseudo dice [0.8377] +2024-11-22 17:28:49.649990: Epoch time: 19.09 s +2024-11-22 17:28:50.542287: +2024-11-22 17:28:50.542536: Epoch 5645 +2024-11-22 17:28:50.542648: Current learning rate: 0.00333 +2024-11-22 17:29:08.994130: train_loss -0.7992 +2024-11-22 17:29:08.994365: val_loss -0.7455 +2024-11-22 17:29:08.994442: Pseudo dice [0.8401] +2024-11-22 17:29:08.994523: Epoch time: 18.45 s +2024-11-22 17:29:09.891567: +2024-11-22 17:29:09.891770: Epoch 5646 +2024-11-22 17:29:09.891894: Current learning rate: 0.00333 +2024-11-22 17:29:29.741564: train_loss -0.8022 +2024-11-22 17:29:29.741798: val_loss -0.728 +2024-11-22 17:29:29.741873: Pseudo dice [0.8325] +2024-11-22 17:29:29.741947: Epoch time: 19.85 s +2024-11-22 17:29:30.746637: +2024-11-22 17:29:30.746827: Epoch 5647 +2024-11-22 17:29:30.746940: Current learning rate: 0.00332 +2024-11-22 17:29:49.652051: train_loss -0.7981 +2024-11-22 17:29:49.652287: val_loss -0.7373 +2024-11-22 17:29:49.652366: Pseudo dice [0.7973] +2024-11-22 17:29:49.652443: Epoch time: 18.91 s +2024-11-22 17:29:50.547558: +2024-11-22 17:29:50.547829: Epoch 5648 +2024-11-22 17:29:50.547943: Current learning rate: 0.00332 +2024-11-22 17:30:10.106541: train_loss -0.7912 +2024-11-22 17:30:10.106768: val_loss -0.7332 +2024-11-22 17:30:10.106845: Pseudo dice [0.8197] +2024-11-22 17:30:10.106925: Epoch time: 19.56 s +2024-11-22 17:30:11.009876: +2024-11-22 17:30:11.010071: Epoch 5649 +2024-11-22 17:30:11.010181: Current learning rate: 0.00332 +2024-11-22 17:30:29.558372: train_loss -0.7866 +2024-11-22 17:30:29.564841: val_loss -0.7672 +2024-11-22 17:30:29.564964: Pseudo dice [0.8387] +2024-11-22 17:30:29.565060: Epoch time: 18.55 s +2024-11-22 17:30:30.762077: +2024-11-22 17:30:30.762267: Epoch 5650 +2024-11-22 17:30:30.762382: Current learning rate: 0.00332 +2024-11-22 17:30:49.745196: train_loss -0.7987 +2024-11-22 17:30:49.745407: val_loss -0.7626 +2024-11-22 17:30:49.745483: Pseudo dice [0.8351] +2024-11-22 17:30:49.745558: Epoch time: 18.98 s +2024-11-22 17:30:50.643606: +2024-11-22 17:30:50.643807: Epoch 5651 +2024-11-22 17:30:50.643918: Current learning rate: 0.00332 +2024-11-22 17:31:10.074226: train_loss -0.8022 +2024-11-22 17:31:10.074447: val_loss -0.7512 +2024-11-22 17:31:10.074525: Pseudo dice [0.8174] +2024-11-22 17:31:10.074603: Epoch time: 19.43 s +2024-11-22 17:31:10.981090: +2024-11-22 17:31:10.981331: Epoch 5652 +2024-11-22 17:31:10.981466: Current learning rate: 0.00332 +2024-11-22 17:31:29.290025: train_loss -0.7959 +2024-11-22 17:31:29.290239: val_loss -0.7128 +2024-11-22 17:31:29.290320: Pseudo dice [0.8149] +2024-11-22 17:31:29.290460: Epoch time: 18.31 s +2024-11-22 17:31:30.197931: +2024-11-22 17:31:30.198161: Epoch 5653 +2024-11-22 17:31:30.198317: Current learning rate: 0.00332 +2024-11-22 17:31:48.718475: train_loss -0.8013 +2024-11-22 17:31:48.718751: val_loss -0.7592 +2024-11-22 17:31:48.718828: Pseudo dice [0.8254] +2024-11-22 17:31:48.718907: Epoch time: 18.52 s +2024-11-22 17:31:49.719811: +2024-11-22 17:31:49.720096: Epoch 5654 +2024-11-22 17:31:49.720212: Current learning rate: 0.00332 +2024-11-22 17:32:09.814273: train_loss -0.8024 +2024-11-22 17:32:09.814521: val_loss -0.7411 +2024-11-22 17:32:09.814597: Pseudo dice [0.8425] +2024-11-22 17:32:09.814676: Epoch time: 20.1 s +2024-11-22 17:32:10.708874: +2024-11-22 17:32:10.709109: Epoch 5655 +2024-11-22 17:32:10.709229: Current learning rate: 0.00331 +2024-11-22 17:32:28.745120: train_loss -0.8079 +2024-11-22 17:32:28.745410: val_loss -0.7767 +2024-11-22 17:32:28.745489: Pseudo dice [0.8433] +2024-11-22 17:32:28.745569: Epoch time: 18.04 s +2024-11-22 17:32:29.695707: +2024-11-22 17:32:29.695988: Epoch 5656 +2024-11-22 17:32:29.696106: Current learning rate: 0.00331 +2024-11-22 17:32:48.695259: train_loss -0.8076 +2024-11-22 17:32:48.695517: val_loss -0.7521 +2024-11-22 17:32:48.695598: Pseudo dice [0.8464] +2024-11-22 17:32:48.695681: Epoch time: 19.0 s +2024-11-22 17:32:49.608623: +2024-11-22 17:32:49.608906: Epoch 5657 +2024-11-22 17:32:49.609030: Current learning rate: 0.00331 +2024-11-22 17:33:08.326800: train_loss -0.8068 +2024-11-22 17:33:08.327044: val_loss -0.7454 +2024-11-22 17:33:08.327122: Pseudo dice [0.8324] +2024-11-22 17:33:08.327199: Epoch time: 18.72 s +2024-11-22 17:33:09.261048: +2024-11-22 17:33:09.261375: Epoch 5658 +2024-11-22 17:33:09.261497: Current learning rate: 0.00331 +2024-11-22 17:33:28.366320: train_loss -0.8051 +2024-11-22 17:33:28.366612: val_loss -0.7799 +2024-11-22 17:33:28.366722: Pseudo dice [0.8256] +2024-11-22 17:33:28.366950: Epoch time: 19.11 s +2024-11-22 17:33:29.268267: +2024-11-22 17:33:29.268477: Epoch 5659 +2024-11-22 17:33:29.268594: Current learning rate: 0.00331 +2024-11-22 17:33:47.531267: train_loss -0.8053 +2024-11-22 17:33:47.531490: val_loss -0.7704 +2024-11-22 17:33:47.531572: Pseudo dice [0.8454] +2024-11-22 17:33:47.531658: Epoch time: 18.26 s +2024-11-22 17:33:48.414540: +2024-11-22 17:33:48.436265: Epoch 5660 +2024-11-22 17:33:48.436402: Current learning rate: 0.00331 +2024-11-22 17:34:07.107274: train_loss -0.8067 +2024-11-22 17:34:07.107525: val_loss -0.7644 +2024-11-22 17:34:07.107598: Pseudo dice [0.8396] +2024-11-22 17:34:07.107680: Epoch time: 18.69 s +2024-11-22 17:34:08.013510: +2024-11-22 17:34:08.013706: Epoch 5661 +2024-11-22 17:34:08.013819: Current learning rate: 0.00331 +2024-11-22 17:34:27.787757: train_loss -0.7948 +2024-11-22 17:34:27.787986: val_loss -0.7449 +2024-11-22 17:34:27.793241: Pseudo dice [0.8229] +2024-11-22 17:34:27.793389: Epoch time: 19.78 s +2024-11-22 17:34:28.845572: +2024-11-22 17:34:28.845772: Epoch 5662 +2024-11-22 17:34:28.845883: Current learning rate: 0.00331 +2024-11-22 17:34:47.230384: train_loss -0.795 +2024-11-22 17:34:47.230605: val_loss -0.7397 +2024-11-22 17:34:47.230681: Pseudo dice [0.8475] +2024-11-22 17:34:47.230760: Epoch time: 18.39 s +2024-11-22 17:34:48.142889: +2024-11-22 17:34:48.143175: Epoch 5663 +2024-11-22 17:34:48.143293: Current learning rate: 0.0033 +2024-11-22 17:35:07.365216: train_loss -0.7943 +2024-11-22 17:35:07.365463: val_loss -0.7495 +2024-11-22 17:35:07.365539: Pseudo dice [0.8285] +2024-11-22 17:35:07.365623: Epoch time: 19.22 s +2024-11-22 17:35:08.268857: +2024-11-22 17:35:08.269059: Epoch 5664 +2024-11-22 17:35:08.269174: Current learning rate: 0.0033 +2024-11-22 17:35:26.690467: train_loss -0.7984 +2024-11-22 17:35:26.690682: val_loss -0.756 +2024-11-22 17:35:26.690763: Pseudo dice [0.8366] +2024-11-22 17:35:26.690840: Epoch time: 18.42 s +2024-11-22 17:35:27.594715: +2024-11-22 17:35:27.594930: Epoch 5665 +2024-11-22 17:35:27.595045: Current learning rate: 0.0033 +2024-11-22 17:35:46.949975: train_loss -0.7952 +2024-11-22 17:35:46.955781: val_loss -0.7444 +2024-11-22 17:35:46.955917: Pseudo dice [0.8275] +2024-11-22 17:35:46.956004: Epoch time: 19.36 s +2024-11-22 17:35:48.324742: +2024-11-22 17:35:48.325056: Epoch 5666 +2024-11-22 17:35:48.325170: Current learning rate: 0.0033 +2024-11-22 17:36:06.501742: train_loss -0.7937 +2024-11-22 17:36:06.504211: val_loss -0.7327 +2024-11-22 17:36:06.504314: Pseudo dice [0.8308] +2024-11-22 17:36:06.504403: Epoch time: 18.18 s +2024-11-22 17:36:07.571421: +2024-11-22 17:36:07.571663: Epoch 5667 +2024-11-22 17:36:07.571779: Current learning rate: 0.0033 +2024-11-22 17:36:26.375357: train_loss -0.8041 +2024-11-22 17:36:26.375600: val_loss -0.7339 +2024-11-22 17:36:26.375679: Pseudo dice [0.8423] +2024-11-22 17:36:26.375796: Epoch time: 18.8 s +2024-11-22 17:36:27.278703: +2024-11-22 17:36:27.278974: Epoch 5668 +2024-11-22 17:36:27.279092: Current learning rate: 0.0033 +2024-11-22 17:36:45.941320: train_loss -0.8031 +2024-11-22 17:36:45.941569: val_loss -0.7644 +2024-11-22 17:36:45.942084: Pseudo dice [0.8272] +2024-11-22 17:36:45.942181: Epoch time: 18.66 s +2024-11-22 17:36:46.872378: +2024-11-22 17:36:46.872596: Epoch 5669 +2024-11-22 17:36:46.872716: Current learning rate: 0.0033 +2024-11-22 17:37:04.964826: train_loss -0.7983 +2024-11-22 17:37:04.965068: val_loss -0.724 +2024-11-22 17:37:04.965147: Pseudo dice [0.823] +2024-11-22 17:37:04.965228: Epoch time: 18.09 s +2024-11-22 17:37:05.868727: +2024-11-22 17:37:05.868919: Epoch 5670 +2024-11-22 17:37:05.869037: Current learning rate: 0.00329 +2024-11-22 17:37:22.866660: train_loss -0.8047 +2024-11-22 17:37:22.866912: val_loss -0.7425 +2024-11-22 17:37:22.866989: Pseudo dice [0.842] +2024-11-22 17:37:22.867087: Epoch time: 17.0 s +2024-11-22 17:37:23.774544: +2024-11-22 17:37:23.774774: Epoch 5671 +2024-11-22 17:37:23.774901: Current learning rate: 0.00329 +2024-11-22 17:37:41.563128: train_loss -0.7997 +2024-11-22 17:37:41.563366: val_loss -0.7495 +2024-11-22 17:37:41.563441: Pseudo dice [0.8222] +2024-11-22 17:37:41.563530: Epoch time: 17.79 s +2024-11-22 17:37:42.477236: +2024-11-22 17:37:42.477434: Epoch 5672 +2024-11-22 17:37:42.477554: Current learning rate: 0.00329 +2024-11-22 17:38:01.459161: train_loss -0.8029 +2024-11-22 17:38:01.459423: val_loss -0.7559 +2024-11-22 17:38:01.459501: Pseudo dice [0.8282] +2024-11-22 17:38:01.459578: Epoch time: 18.98 s +2024-11-22 17:38:02.360919: +2024-11-22 17:38:02.361116: Epoch 5673 +2024-11-22 17:38:02.361229: Current learning rate: 0.00329 +2024-11-22 17:38:21.394968: train_loss -0.8091 +2024-11-22 17:38:21.395225: val_loss -0.7377 +2024-11-22 17:38:21.395299: Pseudo dice [0.8285] +2024-11-22 17:38:21.395384: Epoch time: 19.03 s +2024-11-22 17:38:22.302795: +2024-11-22 17:38:22.303040: Epoch 5674 +2024-11-22 17:38:22.303155: Current learning rate: 0.00329 +2024-11-22 17:38:42.114619: train_loss -0.8021 +2024-11-22 17:38:42.114839: val_loss -0.7378 +2024-11-22 17:38:42.114912: Pseudo dice [0.8123] +2024-11-22 17:38:42.114990: Epoch time: 19.81 s +2024-11-22 17:38:43.047285: +2024-11-22 17:38:43.047502: Epoch 5675 +2024-11-22 17:38:43.047617: Current learning rate: 0.00329 +2024-11-22 17:39:01.710549: train_loss -0.8012 +2024-11-22 17:39:01.710778: val_loss -0.7568 +2024-11-22 17:39:01.710850: Pseudo dice [0.8296] +2024-11-22 17:39:01.710939: Epoch time: 18.66 s +2024-11-22 17:39:02.615644: +2024-11-22 17:39:02.615859: Epoch 5676 +2024-11-22 17:39:02.615978: Current learning rate: 0.00329 +2024-11-22 17:39:21.381139: train_loss -0.8074 +2024-11-22 17:39:21.381387: val_loss -0.7234 +2024-11-22 17:39:21.381526: Pseudo dice [0.8359] +2024-11-22 17:39:21.381611: Epoch time: 18.77 s +2024-11-22 17:39:22.283504: +2024-11-22 17:39:22.283744: Epoch 5677 +2024-11-22 17:39:22.283859: Current learning rate: 0.00329 +2024-11-22 17:39:40.547581: train_loss -0.812 +2024-11-22 17:39:40.547807: val_loss -0.7602 +2024-11-22 17:39:40.547881: Pseudo dice [0.8257] +2024-11-22 17:39:40.547960: Epoch time: 18.26 s +2024-11-22 17:39:41.840190: +2024-11-22 17:39:41.840420: Epoch 5678 +2024-11-22 17:39:41.840536: Current learning rate: 0.00328 +2024-11-22 17:40:01.132441: train_loss -0.8016 +2024-11-22 17:40:01.132673: val_loss -0.7286 +2024-11-22 17:40:01.132751: Pseudo dice [0.8149] +2024-11-22 17:40:01.132886: Epoch time: 19.29 s +2024-11-22 17:40:02.031641: +2024-11-22 17:40:02.031855: Epoch 5679 +2024-11-22 17:40:02.031965: Current learning rate: 0.00328 +2024-11-22 17:40:20.417852: train_loss -0.8087 +2024-11-22 17:40:20.418118: val_loss -0.7786 +2024-11-22 17:40:20.418198: Pseudo dice [0.8403] +2024-11-22 17:40:20.418285: Epoch time: 18.39 s +2024-11-22 17:40:21.319296: +2024-11-22 17:40:21.319500: Epoch 5680 +2024-11-22 17:40:21.319612: Current learning rate: 0.00328 +2024-11-22 17:40:40.420117: train_loss -0.8042 +2024-11-22 17:40:40.420356: val_loss -0.7639 +2024-11-22 17:40:40.420429: Pseudo dice [0.8414] +2024-11-22 17:40:40.420506: Epoch time: 19.1 s +2024-11-22 17:40:41.344350: +2024-11-22 17:40:41.344803: Epoch 5681 +2024-11-22 17:40:41.344917: Current learning rate: 0.00328 +2024-11-22 17:40:59.450585: train_loss -0.7959 +2024-11-22 17:40:59.450829: val_loss -0.7405 +2024-11-22 17:40:59.450905: Pseudo dice [0.8128] +2024-11-22 17:40:59.450982: Epoch time: 18.11 s +2024-11-22 17:41:00.408986: +2024-11-22 17:41:00.409213: Epoch 5682 +2024-11-22 17:41:00.409323: Current learning rate: 0.00328 +2024-11-22 17:41:18.726538: train_loss -0.8016 +2024-11-22 17:41:18.726785: val_loss -0.7732 +2024-11-22 17:41:18.726861: Pseudo dice [0.8384] +2024-11-22 17:41:18.726939: Epoch time: 18.31 s +2024-11-22 17:41:19.785167: +2024-11-22 17:41:19.785364: Epoch 5683 +2024-11-22 17:41:19.785474: Current learning rate: 0.00328 +2024-11-22 17:41:39.260594: train_loss -0.798 +2024-11-22 17:41:39.260875: val_loss -0.7617 +2024-11-22 17:41:39.260955: Pseudo dice [0.8385] +2024-11-22 17:41:39.261048: Epoch time: 19.48 s +2024-11-22 17:41:40.165619: +2024-11-22 17:41:40.165843: Epoch 5684 +2024-11-22 17:41:40.165956: Current learning rate: 0.00328 +2024-11-22 17:41:59.206360: train_loss -0.7997 +2024-11-22 17:41:59.206581: val_loss -0.7633 +2024-11-22 17:41:59.206654: Pseudo dice [0.8246] +2024-11-22 17:41:59.206870: Epoch time: 19.04 s +2024-11-22 17:42:00.113107: +2024-11-22 17:42:00.113330: Epoch 5685 +2024-11-22 17:42:00.113444: Current learning rate: 0.00328 +2024-11-22 17:42:18.028544: train_loss -0.7952 +2024-11-22 17:42:18.028766: val_loss -0.7559 +2024-11-22 17:42:18.028839: Pseudo dice [0.8359] +2024-11-22 17:42:18.028916: Epoch time: 17.92 s +2024-11-22 17:42:19.113185: +2024-11-22 17:42:19.113379: Epoch 5686 +2024-11-22 17:42:19.113492: Current learning rate: 0.00327 +2024-11-22 17:42:36.892051: train_loss -0.8042 +2024-11-22 17:42:36.892262: val_loss -0.7685 +2024-11-22 17:42:36.892336: Pseudo dice [0.8425] +2024-11-22 17:42:36.892419: Epoch time: 17.78 s +2024-11-22 17:42:37.790199: +2024-11-22 17:42:37.790399: Epoch 5687 +2024-11-22 17:42:37.790514: Current learning rate: 0.00327 +2024-11-22 17:42:57.846463: train_loss -0.7916 +2024-11-22 17:42:57.846709: val_loss -0.754 +2024-11-22 17:42:57.846785: Pseudo dice [0.8392] +2024-11-22 17:42:57.846866: Epoch time: 20.06 s +2024-11-22 17:42:58.808360: +2024-11-22 17:42:58.808589: Epoch 5688 +2024-11-22 17:42:58.808703: Current learning rate: 0.00327 +2024-11-22 17:43:16.846354: train_loss -0.7943 +2024-11-22 17:43:16.846576: val_loss -0.7492 +2024-11-22 17:43:16.846653: Pseudo dice [0.8393] +2024-11-22 17:43:16.846730: Epoch time: 18.04 s +2024-11-22 17:43:17.746213: +2024-11-22 17:43:17.746405: Epoch 5689 +2024-11-22 17:43:17.746520: Current learning rate: 0.00327 +2024-11-22 17:43:36.838957: train_loss -0.8024 +2024-11-22 17:43:36.839189: val_loss -0.7644 +2024-11-22 17:43:36.839264: Pseudo dice [0.8128] +2024-11-22 17:43:36.843823: Epoch time: 19.09 s +2024-11-22 17:43:38.255313: +2024-11-22 17:43:38.255547: Epoch 5690 +2024-11-22 17:43:38.255658: Current learning rate: 0.00327 +2024-11-22 17:43:56.228256: train_loss -0.8082 +2024-11-22 17:43:56.228529: val_loss -0.7541 +2024-11-22 17:43:56.228610: Pseudo dice [0.8377] +2024-11-22 17:43:56.228699: Epoch time: 17.97 s +2024-11-22 17:43:57.178548: +2024-11-22 17:43:57.178808: Epoch 5691 +2024-11-22 17:43:57.178918: Current learning rate: 0.00327 +2024-11-22 17:44:15.257113: train_loss -0.8134 +2024-11-22 17:44:15.257358: val_loss -0.7607 +2024-11-22 17:44:15.257444: Pseudo dice [0.841] +2024-11-22 17:44:15.257529: Epoch time: 18.08 s +2024-11-22 17:44:16.154750: +2024-11-22 17:44:16.154987: Epoch 5692 +2024-11-22 17:44:16.155106: Current learning rate: 0.00327 +2024-11-22 17:44:34.619633: train_loss -0.8071 +2024-11-22 17:44:34.619873: val_loss -0.738 +2024-11-22 17:44:34.619956: Pseudo dice [0.8264] +2024-11-22 17:44:34.620050: Epoch time: 18.47 s +2024-11-22 17:44:35.520144: +2024-11-22 17:44:35.520344: Epoch 5693 +2024-11-22 17:44:35.520459: Current learning rate: 0.00327 +2024-11-22 17:44:54.265023: train_loss -0.8056 +2024-11-22 17:44:54.265260: val_loss -0.7558 +2024-11-22 17:44:54.265343: Pseudo dice [0.8398] +2024-11-22 17:44:54.265427: Epoch time: 18.75 s +2024-11-22 17:44:55.172607: +2024-11-22 17:44:55.172813: Epoch 5694 +2024-11-22 17:44:55.172929: Current learning rate: 0.00326 +2024-11-22 17:45:13.155290: train_loss -0.8055 +2024-11-22 17:45:13.157748: val_loss -0.7267 +2024-11-22 17:45:13.157855: Pseudo dice [0.8231] +2024-11-22 17:45:13.157939: Epoch time: 17.98 s +2024-11-22 17:45:14.080029: +2024-11-22 17:45:14.080305: Epoch 5695 +2024-11-22 17:45:14.080422: Current learning rate: 0.00326 +2024-11-22 17:45:32.889110: train_loss -0.8078 +2024-11-22 17:45:32.889333: val_loss -0.7669 +2024-11-22 17:45:32.889408: Pseudo dice [0.8159] +2024-11-22 17:45:32.889486: Epoch time: 18.81 s +2024-11-22 17:45:33.806497: +2024-11-22 17:45:33.806776: Epoch 5696 +2024-11-22 17:45:33.806890: Current learning rate: 0.00326 +2024-11-22 17:45:52.271714: train_loss -0.7999 +2024-11-22 17:45:52.271983: val_loss -0.7557 +2024-11-22 17:45:52.272069: Pseudo dice [0.8295] +2024-11-22 17:45:52.272145: Epoch time: 18.47 s +2024-11-22 17:45:53.174996: +2024-11-22 17:45:53.175428: Epoch 5697 +2024-11-22 17:45:53.175547: Current learning rate: 0.00326 +2024-11-22 17:46:11.681520: train_loss -0.8017 +2024-11-22 17:46:11.681764: val_loss -0.7631 +2024-11-22 17:46:11.681839: Pseudo dice [0.8309] +2024-11-22 17:46:11.681927: Epoch time: 18.51 s +2024-11-22 17:46:12.586409: +2024-11-22 17:46:12.586621: Epoch 5698 +2024-11-22 17:46:12.586740: Current learning rate: 0.00326 +2024-11-22 17:46:32.356208: train_loss -0.8014 +2024-11-22 17:46:32.356426: val_loss -0.7576 +2024-11-22 17:46:32.356504: Pseudo dice [0.8355] +2024-11-22 17:46:32.356579: Epoch time: 19.77 s +2024-11-22 17:46:33.266695: +2024-11-22 17:46:33.266918: Epoch 5699 +2024-11-22 17:46:33.267038: Current learning rate: 0.00326 +2024-11-22 17:46:50.940264: train_loss -0.8055 +2024-11-22 17:46:50.945663: val_loss -0.7662 +2024-11-22 17:46:50.945851: Pseudo dice [0.8198] +2024-11-22 17:46:50.945941: Epoch time: 17.67 s +2024-11-22 17:46:52.175747: +2024-11-22 17:46:52.176011: Epoch 5700 +2024-11-22 17:46:52.176127: Current learning rate: 0.00326 +2024-11-22 17:47:12.025182: train_loss -0.7995 +2024-11-22 17:47:12.025415: val_loss -0.7547 +2024-11-22 17:47:12.025491: Pseudo dice [0.8398] +2024-11-22 17:47:12.025572: Epoch time: 19.85 s +2024-11-22 17:47:12.933298: +2024-11-22 17:47:12.933512: Epoch 5701 +2024-11-22 17:47:12.933624: Current learning rate: 0.00326 +2024-11-22 17:47:31.929007: train_loss -0.8051 +2024-11-22 17:47:31.929262: val_loss -0.7314 +2024-11-22 17:47:31.929339: Pseudo dice [0.828] +2024-11-22 17:47:31.929419: Epoch time: 19.0 s +2024-11-22 17:47:33.025183: +2024-11-22 17:47:33.025415: Epoch 5702 +2024-11-22 17:47:33.025531: Current learning rate: 0.00325 +2024-11-22 17:47:51.167252: train_loss -0.8005 +2024-11-22 17:47:51.167518: val_loss -0.7698 +2024-11-22 17:47:51.167608: Pseudo dice [0.8301] +2024-11-22 17:47:51.167739: Epoch time: 18.14 s +2024-11-22 17:47:52.068501: +2024-11-22 17:47:52.068719: Epoch 5703 +2024-11-22 17:47:52.068832: Current learning rate: 0.00325 +2024-11-22 17:48:11.679559: train_loss -0.7881 +2024-11-22 17:48:11.679791: val_loss -0.7495 +2024-11-22 17:48:11.679867: Pseudo dice [0.8287] +2024-11-22 17:48:11.679948: Epoch time: 19.61 s +2024-11-22 17:48:12.580087: +2024-11-22 17:48:12.580320: Epoch 5704 +2024-11-22 17:48:12.580436: Current learning rate: 0.00325 +2024-11-22 17:48:31.367358: train_loss -0.7981 +2024-11-22 17:48:31.367628: val_loss -0.7558 +2024-11-22 17:48:31.367710: Pseudo dice [0.8272] +2024-11-22 17:48:31.367801: Epoch time: 18.79 s +2024-11-22 17:48:32.344606: +2024-11-22 17:48:32.344880: Epoch 5705 +2024-11-22 17:48:32.345003: Current learning rate: 0.00325 +2024-11-22 17:48:50.368654: train_loss -0.7945 +2024-11-22 17:48:50.368881: val_loss -0.7666 +2024-11-22 17:48:50.368963: Pseudo dice [0.8475] +2024-11-22 17:48:50.369045: Epoch time: 18.02 s +2024-11-22 17:48:51.269333: +2024-11-22 17:48:51.269529: Epoch 5706 +2024-11-22 17:48:51.269641: Current learning rate: 0.00325 +2024-11-22 17:49:08.565477: train_loss -0.7998 +2024-11-22 17:49:08.565716: val_loss -0.745 +2024-11-22 17:49:08.565790: Pseudo dice [0.8173] +2024-11-22 17:49:08.565887: Epoch time: 17.3 s +2024-11-22 17:49:09.466424: +2024-11-22 17:49:09.466618: Epoch 5707 +2024-11-22 17:49:09.466728: Current learning rate: 0.00325 +2024-11-22 17:49:29.136847: train_loss -0.8068 +2024-11-22 17:49:29.137115: val_loss -0.7574 +2024-11-22 17:49:29.139397: Pseudo dice [0.8174] +2024-11-22 17:49:29.139501: Epoch time: 19.67 s +2024-11-22 17:49:30.089230: +2024-11-22 17:49:30.089418: Epoch 5708 +2024-11-22 17:49:30.089562: Current learning rate: 0.00325 +2024-11-22 17:49:49.022146: train_loss -0.8025 +2024-11-22 17:49:49.022389: val_loss -0.7512 +2024-11-22 17:49:49.022463: Pseudo dice [0.8175] +2024-11-22 17:49:49.022542: Epoch time: 18.93 s +2024-11-22 17:49:49.925079: +2024-11-22 17:49:49.925271: Epoch 5709 +2024-11-22 17:49:49.925386: Current learning rate: 0.00325 +2024-11-22 17:50:08.337537: train_loss -0.8034 +2024-11-22 17:50:08.337810: val_loss -0.7439 +2024-11-22 17:50:08.337884: Pseudo dice [0.8192] +2024-11-22 17:50:08.337961: Epoch time: 18.41 s +2024-11-22 17:50:09.280254: +2024-11-22 17:50:09.280458: Epoch 5710 +2024-11-22 17:50:09.280571: Current learning rate: 0.00324 +2024-11-22 17:50:28.149320: train_loss -0.8065 +2024-11-22 17:50:28.149538: val_loss -0.77 +2024-11-22 17:50:28.149741: Pseudo dice [0.8375] +2024-11-22 17:50:28.149822: Epoch time: 18.87 s +2024-11-22 17:50:29.059038: +2024-11-22 17:50:29.059240: Epoch 5711 +2024-11-22 17:50:29.059356: Current learning rate: 0.00324 +2024-11-22 17:50:48.199646: train_loss -0.8001 +2024-11-22 17:50:48.199908: val_loss -0.7626 +2024-11-22 17:50:48.199984: Pseudo dice [0.8492] +2024-11-22 17:50:48.200071: Epoch time: 19.14 s +2024-11-22 17:50:49.160612: +2024-11-22 17:50:49.160851: Epoch 5712 +2024-11-22 17:50:49.160966: Current learning rate: 0.00324 +2024-11-22 17:51:08.638065: train_loss -0.8072 +2024-11-22 17:51:08.638321: val_loss -0.7506 +2024-11-22 17:51:08.638395: Pseudo dice [0.8355] +2024-11-22 17:51:08.638480: Epoch time: 19.48 s +2024-11-22 17:51:10.074176: +2024-11-22 17:51:10.074399: Epoch 5713 +2024-11-22 17:51:10.074512: Current learning rate: 0.00324 +2024-11-22 17:51:28.894375: train_loss -0.8068 +2024-11-22 17:51:28.894646: val_loss -0.7448 +2024-11-22 17:51:28.894725: Pseudo dice [0.8449] +2024-11-22 17:51:28.894808: Epoch time: 18.82 s +2024-11-22 17:51:29.798039: +2024-11-22 17:51:29.798435: Epoch 5714 +2024-11-22 17:51:29.798547: Current learning rate: 0.00324 +2024-11-22 17:51:48.366773: train_loss -0.8124 +2024-11-22 17:51:48.367011: val_loss -0.7571 +2024-11-22 17:51:48.367088: Pseudo dice [0.8278] +2024-11-22 17:51:48.367164: Epoch time: 18.57 s +2024-11-22 17:51:49.287227: +2024-11-22 17:51:49.287442: Epoch 5715 +2024-11-22 17:51:49.287553: Current learning rate: 0.00324 +2024-11-22 17:52:09.570385: train_loss -0.8123 +2024-11-22 17:52:09.570656: val_loss -0.7473 +2024-11-22 17:52:09.570741: Pseudo dice [0.8316] +2024-11-22 17:52:09.570828: Epoch time: 20.28 s +2024-11-22 17:52:10.617801: +2024-11-22 17:52:10.618017: Epoch 5716 +2024-11-22 17:52:10.618135: Current learning rate: 0.00324 +2024-11-22 17:52:29.126981: train_loss -0.8032 +2024-11-22 17:52:29.127229: val_loss -0.756 +2024-11-22 17:52:29.127303: Pseudo dice [0.8285] +2024-11-22 17:52:29.127380: Epoch time: 18.51 s +2024-11-22 17:52:30.047192: +2024-11-22 17:52:30.047402: Epoch 5717 +2024-11-22 17:52:30.047517: Current learning rate: 0.00324 +2024-11-22 17:52:48.965935: train_loss -0.787 +2024-11-22 17:52:48.967260: val_loss -0.7255 +2024-11-22 17:52:48.967350: Pseudo dice [0.8322] +2024-11-22 17:52:48.967438: Epoch time: 18.92 s +2024-11-22 17:52:49.905446: +2024-11-22 17:52:49.905640: Epoch 5718 +2024-11-22 17:52:49.905753: Current learning rate: 0.00323 +2024-11-22 17:53:08.397234: train_loss -0.7956 +2024-11-22 17:53:08.397464: val_loss -0.7647 +2024-11-22 17:53:08.397543: Pseudo dice [0.8358] +2024-11-22 17:53:08.397624: Epoch time: 18.49 s +2024-11-22 17:53:09.312945: +2024-11-22 17:53:09.313148: Epoch 5719 +2024-11-22 17:53:09.313260: Current learning rate: 0.00323 +2024-11-22 17:53:28.401812: train_loss -0.8078 +2024-11-22 17:53:28.402062: val_loss -0.7272 +2024-11-22 17:53:28.402138: Pseudo dice [0.8199] +2024-11-22 17:53:28.402224: Epoch time: 19.09 s +2024-11-22 17:53:29.343303: +2024-11-22 17:53:29.343534: Epoch 5720 +2024-11-22 17:53:29.343648: Current learning rate: 0.00323 +2024-11-22 17:53:47.017443: train_loss -0.8159 +2024-11-22 17:53:47.017670: val_loss -0.7498 +2024-11-22 17:53:47.017748: Pseudo dice [0.8042] +2024-11-22 17:53:47.017830: Epoch time: 17.67 s +2024-11-22 17:53:47.930671: +2024-11-22 17:53:47.930881: Epoch 5721 +2024-11-22 17:53:47.931002: Current learning rate: 0.00323 +2024-11-22 17:54:06.923232: train_loss -0.8104 +2024-11-22 17:54:06.923444: val_loss -0.728 +2024-11-22 17:54:06.923518: Pseudo dice [0.8293] +2024-11-22 17:54:06.923595: Epoch time: 18.99 s +2024-11-22 17:54:07.831451: +2024-11-22 17:54:07.831670: Epoch 5722 +2024-11-22 17:54:07.831789: Current learning rate: 0.00323 +2024-11-22 17:54:25.705848: train_loss -0.8112 +2024-11-22 17:54:25.706096: val_loss -0.7476 +2024-11-22 17:54:25.706176: Pseudo dice [0.8241] +2024-11-22 17:54:25.706257: Epoch time: 17.88 s +2024-11-22 17:54:26.612335: +2024-11-22 17:54:26.612516: Epoch 5723 +2024-11-22 17:54:26.612628: Current learning rate: 0.00323 +2024-11-22 17:54:45.055179: train_loss -0.8055 +2024-11-22 17:54:45.055418: val_loss -0.7539 +2024-11-22 17:54:45.055489: Pseudo dice [0.8368] +2024-11-22 17:54:45.055570: Epoch time: 18.44 s +2024-11-22 17:54:45.983273: +2024-11-22 17:54:45.983888: Epoch 5724 +2024-11-22 17:54:45.984027: Current learning rate: 0.00323 +2024-11-22 17:55:04.500737: train_loss -0.8065 +2024-11-22 17:55:04.500973: val_loss -0.722 +2024-11-22 17:55:04.501062: Pseudo dice [0.82] +2024-11-22 17:55:04.501140: Epoch time: 18.52 s +2024-11-22 17:55:05.413935: +2024-11-22 17:55:05.414197: Epoch 5725 +2024-11-22 17:55:05.414317: Current learning rate: 0.00322 +2024-11-22 17:55:24.864892: train_loss -0.8041 +2024-11-22 17:55:24.865134: val_loss -0.7576 +2024-11-22 17:55:24.865220: Pseudo dice [0.8325] +2024-11-22 17:55:24.865297: Epoch time: 19.45 s +2024-11-22 17:55:25.772756: +2024-11-22 17:55:25.773057: Epoch 5726 +2024-11-22 17:55:25.773185: Current learning rate: 0.00322 +2024-11-22 17:55:44.145805: train_loss -0.8063 +2024-11-22 17:55:44.151231: val_loss -0.747 +2024-11-22 17:55:44.151313: Pseudo dice [0.8291] +2024-11-22 17:55:44.151404: Epoch time: 18.37 s +2024-11-22 17:55:45.178654: +2024-11-22 17:55:45.178898: Epoch 5727 +2024-11-22 17:55:45.179015: Current learning rate: 0.00322 +2024-11-22 17:56:03.549133: train_loss -0.8101 +2024-11-22 17:56:03.549355: val_loss -0.783 +2024-11-22 17:56:03.549430: Pseudo dice [0.8524] +2024-11-22 17:56:03.549509: Epoch time: 18.37 s +2024-11-22 17:56:04.462507: +2024-11-22 17:56:04.462806: Epoch 5728 +2024-11-22 17:56:04.462928: Current learning rate: 0.00322 +2024-11-22 17:56:23.763784: train_loss -0.8111 +2024-11-22 17:56:23.764026: val_loss -0.7479 +2024-11-22 17:56:23.764104: Pseudo dice [0.831] +2024-11-22 17:56:23.764180: Epoch time: 19.3 s +2024-11-22 17:56:24.668618: +2024-11-22 17:56:24.668812: Epoch 5729 +2024-11-22 17:56:24.668925: Current learning rate: 0.00322 +2024-11-22 17:56:43.407033: train_loss -0.8034 +2024-11-22 17:56:43.407253: val_loss -0.751 +2024-11-22 17:56:43.407327: Pseudo dice [0.8416] +2024-11-22 17:56:43.407402: Epoch time: 18.74 s +2024-11-22 17:56:44.310382: +2024-11-22 17:56:44.310598: Epoch 5730 +2024-11-22 17:56:44.310713: Current learning rate: 0.00322 +2024-11-22 17:57:02.878586: train_loss -0.8099 +2024-11-22 17:57:02.878837: val_loss -0.7646 +2024-11-22 17:57:02.878914: Pseudo dice [0.8245] +2024-11-22 17:57:02.879043: Epoch time: 18.57 s +2024-11-22 17:57:03.783468: +2024-11-22 17:57:03.783665: Epoch 5731 +2024-11-22 17:57:03.783774: Current learning rate: 0.00322 +2024-11-22 17:57:23.948871: train_loss -0.8077 +2024-11-22 17:57:23.949123: val_loss -0.7519 +2024-11-22 17:57:23.949202: Pseudo dice [0.8312] +2024-11-22 17:57:23.949279: Epoch time: 20.17 s +2024-11-22 17:57:24.857654: +2024-11-22 17:57:24.857857: Epoch 5732 +2024-11-22 17:57:24.857971: Current learning rate: 0.00322 +2024-11-22 17:57:43.456056: train_loss -0.8051 +2024-11-22 17:57:43.456283: val_loss -0.7503 +2024-11-22 17:57:43.456391: Pseudo dice [0.8405] +2024-11-22 17:57:43.456474: Epoch time: 18.6 s +2024-11-22 17:57:44.360700: +2024-11-22 17:57:44.360890: Epoch 5733 +2024-11-22 17:57:44.361011: Current learning rate: 0.00321 +2024-11-22 17:58:04.015292: train_loss -0.8093 +2024-11-22 17:58:04.015514: val_loss -0.7551 +2024-11-22 17:58:04.015587: Pseudo dice [0.8321] +2024-11-22 17:58:04.015663: Epoch time: 19.66 s +2024-11-22 17:58:04.922909: +2024-11-22 17:58:04.923179: Epoch 5734 +2024-11-22 17:58:04.923298: Current learning rate: 0.00321 +2024-11-22 17:58:22.466332: train_loss -0.808 +2024-11-22 17:58:22.466576: val_loss -0.7796 +2024-11-22 17:58:22.466651: Pseudo dice [0.8566] +2024-11-22 17:58:22.466733: Epoch time: 17.54 s +2024-11-22 17:58:23.532296: +2024-11-22 17:58:23.532720: Epoch 5735 +2024-11-22 17:58:23.532861: Current learning rate: 0.00321 +2024-11-22 17:58:42.571773: train_loss -0.8029 +2024-11-22 17:58:42.572001: val_loss -0.7457 +2024-11-22 17:58:42.572075: Pseudo dice [0.8384] +2024-11-22 17:58:42.572152: Epoch time: 19.04 s +2024-11-22 17:58:43.890185: +2024-11-22 17:58:43.890408: Epoch 5736 +2024-11-22 17:58:43.890518: Current learning rate: 0.00321 +2024-11-22 17:59:03.674484: train_loss -0.8107 +2024-11-22 17:59:03.674718: val_loss -0.7334 +2024-11-22 17:59:03.674873: Pseudo dice [0.8368] +2024-11-22 17:59:03.674963: Epoch time: 19.79 s +2024-11-22 17:59:04.719787: +2024-11-22 17:59:04.720008: Epoch 5737 +2024-11-22 17:59:04.720120: Current learning rate: 0.00321 +2024-11-22 17:59:23.626777: train_loss -0.7956 +2024-11-22 17:59:23.627039: val_loss -0.7545 +2024-11-22 17:59:23.627119: Pseudo dice [0.8443] +2024-11-22 17:59:23.627209: Epoch time: 18.91 s +2024-11-22 17:59:24.530837: +2024-11-22 17:59:24.531066: Epoch 5738 +2024-11-22 17:59:24.531182: Current learning rate: 0.00321 +2024-11-22 17:59:43.176359: train_loss -0.7898 +2024-11-22 17:59:43.176687: val_loss -0.7531 +2024-11-22 17:59:43.176855: Pseudo dice [0.8464] +2024-11-22 17:59:43.176949: Epoch time: 18.65 s +2024-11-22 17:59:44.097841: +2024-11-22 17:59:44.098179: Epoch 5739 +2024-11-22 17:59:44.098295: Current learning rate: 0.00321 +2024-11-22 18:00:02.737128: train_loss -0.7977 +2024-11-22 18:00:02.737381: val_loss -0.7757 +2024-11-22 18:00:02.737454: Pseudo dice [0.8339] +2024-11-22 18:00:02.737532: Epoch time: 18.64 s +2024-11-22 18:00:03.763791: +2024-11-22 18:00:03.764001: Epoch 5740 +2024-11-22 18:00:03.764127: Current learning rate: 0.00321 +2024-11-22 18:00:21.360173: train_loss -0.8058 +2024-11-22 18:00:21.360421: val_loss -0.7354 +2024-11-22 18:00:21.360558: Pseudo dice [0.8054] +2024-11-22 18:00:21.360639: Epoch time: 17.6 s +2024-11-22 18:00:22.268928: +2024-11-22 18:00:22.269136: Epoch 5741 +2024-11-22 18:00:22.269250: Current learning rate: 0.0032 +2024-11-22 18:00:42.046232: train_loss -0.8051 +2024-11-22 18:00:42.046459: val_loss -0.7416 +2024-11-22 18:00:42.046536: Pseudo dice [0.8235] +2024-11-22 18:00:42.046616: Epoch time: 19.78 s +2024-11-22 18:00:42.960030: +2024-11-22 18:00:42.960254: Epoch 5742 +2024-11-22 18:00:42.960376: Current learning rate: 0.0032 +2024-11-22 18:01:01.347661: train_loss -0.8074 +2024-11-22 18:01:01.347913: val_loss -0.7636 +2024-11-22 18:01:01.347989: Pseudo dice [0.8575] +2024-11-22 18:01:01.348076: Epoch time: 18.39 s +2024-11-22 18:01:02.431757: +2024-11-22 18:01:02.431941: Epoch 5743 +2024-11-22 18:01:02.432064: Current learning rate: 0.0032 +2024-11-22 18:01:20.500615: train_loss -0.7996 +2024-11-22 18:01:20.500834: val_loss -0.7487 +2024-11-22 18:01:20.500913: Pseudo dice [0.8295] +2024-11-22 18:01:20.500999: Epoch time: 18.07 s +2024-11-22 18:01:21.409636: +2024-11-22 18:01:21.409840: Epoch 5744 +2024-11-22 18:01:21.409952: Current learning rate: 0.0032 +2024-11-22 18:01:39.893374: train_loss -0.7874 +2024-11-22 18:01:39.893596: val_loss -0.739 +2024-11-22 18:01:39.893673: Pseudo dice [0.8168] +2024-11-22 18:01:39.894802: Epoch time: 18.48 s +2024-11-22 18:01:40.814489: +2024-11-22 18:01:40.814905: Epoch 5745 +2024-11-22 18:01:40.815046: Current learning rate: 0.0032 +2024-11-22 18:02:00.405100: train_loss -0.7943 +2024-11-22 18:02:00.405339: val_loss -0.7433 +2024-11-22 18:02:00.405415: Pseudo dice [0.8272] +2024-11-22 18:02:00.405502: Epoch time: 19.59 s +2024-11-22 18:02:01.320807: +2024-11-22 18:02:01.321008: Epoch 5746 +2024-11-22 18:02:01.321121: Current learning rate: 0.0032 +2024-11-22 18:02:20.515320: train_loss -0.7984 +2024-11-22 18:02:20.515580: val_loss -0.7582 +2024-11-22 18:02:20.515662: Pseudo dice [0.8294] +2024-11-22 18:02:20.515743: Epoch time: 19.19 s +2024-11-22 18:02:21.553429: +2024-11-22 18:02:21.553661: Epoch 5747 +2024-11-22 18:02:21.553783: Current learning rate: 0.0032 +2024-11-22 18:02:40.332298: train_loss -0.8048 +2024-11-22 18:02:40.332603: val_loss -0.7532 +2024-11-22 18:02:40.332683: Pseudo dice [0.8221] +2024-11-22 18:02:40.332758: Epoch time: 18.78 s +2024-11-22 18:02:41.238025: +2024-11-22 18:02:41.238337: Epoch 5748 +2024-11-22 18:02:41.238450: Current learning rate: 0.0032 +2024-11-22 18:02:59.929923: train_loss -0.7993 +2024-11-22 18:02:59.930169: val_loss -0.7587 +2024-11-22 18:02:59.930248: Pseudo dice [0.8482] +2024-11-22 18:02:59.930331: Epoch time: 18.69 s +2024-11-22 18:03:00.897082: +2024-11-22 18:03:00.897357: Epoch 5749 +2024-11-22 18:03:00.897473: Current learning rate: 0.00319 +2024-11-22 18:03:21.315539: train_loss -0.7947 +2024-11-22 18:03:21.315798: val_loss -0.7305 +2024-11-22 18:03:21.315873: Pseudo dice [0.8153] +2024-11-22 18:03:21.321162: Epoch time: 20.42 s +2024-11-22 18:03:22.699090: +2024-11-22 18:03:22.699414: Epoch 5750 +2024-11-22 18:03:22.699527: Current learning rate: 0.00319 +2024-11-22 18:03:41.637345: train_loss -0.7902 +2024-11-22 18:03:41.637586: val_loss -0.7331 +2024-11-22 18:03:41.637670: Pseudo dice [0.8263] +2024-11-22 18:03:41.637748: Epoch time: 18.94 s +2024-11-22 18:03:42.545790: +2024-11-22 18:03:42.546006: Epoch 5751 +2024-11-22 18:03:42.546120: Current learning rate: 0.00319 +2024-11-22 18:04:00.748189: train_loss -0.8003 +2024-11-22 18:04:00.749242: val_loss -0.7665 +2024-11-22 18:04:00.749319: Pseudo dice [0.8347] +2024-11-22 18:04:00.749401: Epoch time: 18.2 s +2024-11-22 18:04:01.662887: +2024-11-22 18:04:01.663180: Epoch 5752 +2024-11-22 18:04:01.663292: Current learning rate: 0.00319 +2024-11-22 18:04:20.086058: train_loss -0.8027 +2024-11-22 18:04:20.086281: val_loss -0.7429 +2024-11-22 18:04:20.086358: Pseudo dice [0.824] +2024-11-22 18:04:20.086434: Epoch time: 18.42 s +2024-11-22 18:04:20.991943: +2024-11-22 18:04:20.992333: Epoch 5753 +2024-11-22 18:04:20.992450: Current learning rate: 0.00319 +2024-11-22 18:04:39.519742: train_loss -0.8078 +2024-11-22 18:04:39.520020: val_loss -0.7447 +2024-11-22 18:04:39.520100: Pseudo dice [0.8308] +2024-11-22 18:04:39.520211: Epoch time: 18.53 s +2024-11-22 18:04:40.437377: +2024-11-22 18:04:40.437570: Epoch 5754 +2024-11-22 18:04:40.437683: Current learning rate: 0.00319 +2024-11-22 18:04:59.316590: train_loss -0.8063 +2024-11-22 18:04:59.316807: val_loss -0.7656 +2024-11-22 18:04:59.316883: Pseudo dice [0.8198] +2024-11-22 18:04:59.316959: Epoch time: 18.88 s +2024-11-22 18:05:00.225641: +2024-11-22 18:05:00.225833: Epoch 5755 +2024-11-22 18:05:00.225951: Current learning rate: 0.00319 +2024-11-22 18:05:18.235583: train_loss -0.807 +2024-11-22 18:05:18.235813: val_loss -0.7583 +2024-11-22 18:05:18.235891: Pseudo dice [0.8254] +2024-11-22 18:05:18.235972: Epoch time: 18.01 s +2024-11-22 18:05:19.146559: +2024-11-22 18:05:19.146776: Epoch 5756 +2024-11-22 18:05:19.146890: Current learning rate: 0.00319 +2024-11-22 18:05:38.612963: train_loss -0.8058 +2024-11-22 18:05:38.613203: val_loss -0.7398 +2024-11-22 18:05:38.613281: Pseudo dice [0.8352] +2024-11-22 18:05:38.613359: Epoch time: 19.47 s +2024-11-22 18:05:39.701115: +2024-11-22 18:05:39.701532: Epoch 5757 +2024-11-22 18:05:39.701665: Current learning rate: 0.00318 +2024-11-22 18:05:58.121783: train_loss -0.8037 +2024-11-22 18:05:58.122046: val_loss -0.756 +2024-11-22 18:05:58.122122: Pseudo dice [0.8167] +2024-11-22 18:05:58.122206: Epoch time: 18.42 s +2024-11-22 18:05:59.036704: +2024-11-22 18:05:59.036905: Epoch 5758 +2024-11-22 18:05:59.037022: Current learning rate: 0.00318 +2024-11-22 18:06:18.369330: train_loss -0.8049 +2024-11-22 18:06:18.369575: val_loss -0.7575 +2024-11-22 18:06:18.369659: Pseudo dice [0.8387] +2024-11-22 18:06:18.369739: Epoch time: 19.33 s +2024-11-22 18:06:19.272820: +2024-11-22 18:06:19.273037: Epoch 5759 +2024-11-22 18:06:19.273149: Current learning rate: 0.00318 +2024-11-22 18:06:37.375320: train_loss -0.806 +2024-11-22 18:06:37.375553: val_loss -0.7688 +2024-11-22 18:06:37.375627: Pseudo dice [0.8333] +2024-11-22 18:06:37.375705: Epoch time: 18.1 s +2024-11-22 18:06:38.288825: +2024-11-22 18:06:38.289058: Epoch 5760 +2024-11-22 18:06:38.289172: Current learning rate: 0.00318 +2024-11-22 18:06:57.555050: train_loss -0.8161 +2024-11-22 18:06:57.555305: val_loss -0.7604 +2024-11-22 18:06:57.555383: Pseudo dice [0.8375] +2024-11-22 18:06:57.555471: Epoch time: 19.27 s +2024-11-22 18:06:58.460654: +2024-11-22 18:06:58.460876: Epoch 5761 +2024-11-22 18:06:58.460995: Current learning rate: 0.00318 +2024-11-22 18:07:17.162934: train_loss -0.8009 +2024-11-22 18:07:17.163157: val_loss -0.7647 +2024-11-22 18:07:17.313924: Pseudo dice [0.8346] +2024-11-22 18:07:17.314082: Epoch time: 18.7 s +2024-11-22 18:07:18.204176: +2024-11-22 18:07:18.204373: Epoch 5762 +2024-11-22 18:07:18.204486: Current learning rate: 0.00318 +2024-11-22 18:07:36.482497: train_loss -0.8068 +2024-11-22 18:07:36.482879: val_loss -0.7554 +2024-11-22 18:07:36.482965: Pseudo dice [0.8118] +2024-11-22 18:07:36.483053: Epoch time: 18.28 s +2024-11-22 18:07:37.379867: +2024-11-22 18:07:37.380070: Epoch 5763 +2024-11-22 18:07:37.380182: Current learning rate: 0.00318 +2024-11-22 18:07:56.143875: train_loss -0.814 +2024-11-22 18:07:56.144108: val_loss -0.7585 +2024-11-22 18:07:56.144187: Pseudo dice [0.8445] +2024-11-22 18:07:56.144263: Epoch time: 18.76 s +2024-11-22 18:07:57.221338: +2024-11-22 18:07:57.221548: Epoch 5764 +2024-11-22 18:07:57.221664: Current learning rate: 0.00317 +2024-11-22 18:08:15.954723: train_loss -0.7996 +2024-11-22 18:08:15.954950: val_loss -0.7461 +2024-11-22 18:08:15.955031: Pseudo dice [0.823] +2024-11-22 18:08:15.955110: Epoch time: 18.73 s +2024-11-22 18:08:16.947762: +2024-11-22 18:08:16.948003: Epoch 5765 +2024-11-22 18:08:16.948157: Current learning rate: 0.00317 +2024-11-22 18:08:36.110960: train_loss -0.8132 +2024-11-22 18:08:36.111244: val_loss -0.7641 +2024-11-22 18:08:36.111322: Pseudo dice [0.8262] +2024-11-22 18:08:36.111402: Epoch time: 19.16 s +2024-11-22 18:08:37.021855: +2024-11-22 18:08:37.022305: Epoch 5766 +2024-11-22 18:08:37.022447: Current learning rate: 0.00317 +2024-11-22 18:08:56.650426: train_loss -0.8138 +2024-11-22 18:08:56.650642: val_loss -0.7607 +2024-11-22 18:08:56.650773: Pseudo dice [0.8171] +2024-11-22 18:08:56.650880: Epoch time: 19.63 s +2024-11-22 18:08:57.637904: +2024-11-22 18:08:57.638374: Epoch 5767 +2024-11-22 18:08:57.638515: Current learning rate: 0.00317 +2024-11-22 18:09:15.629424: train_loss -0.8099 +2024-11-22 18:09:15.629651: val_loss -0.744 +2024-11-22 18:09:15.629726: Pseudo dice [0.8395] +2024-11-22 18:09:15.629803: Epoch time: 17.99 s +2024-11-22 18:09:16.562612: +2024-11-22 18:09:16.563064: Epoch 5768 +2024-11-22 18:09:16.563206: Current learning rate: 0.00317 +2024-11-22 18:09:35.857548: train_loss -0.791 +2024-11-22 18:09:35.857797: val_loss -0.7582 +2024-11-22 18:09:35.857875: Pseudo dice [0.8273] +2024-11-22 18:09:35.857961: Epoch time: 19.3 s +2024-11-22 18:09:36.759829: +2024-11-22 18:09:36.760030: Epoch 5769 +2024-11-22 18:09:36.760148: Current learning rate: 0.00317 +2024-11-22 18:09:54.807778: train_loss -0.8041 +2024-11-22 18:09:54.808018: val_loss -0.7287 +2024-11-22 18:09:54.808098: Pseudo dice [0.8428] +2024-11-22 18:09:54.808175: Epoch time: 18.05 s +2024-11-22 18:09:56.107711: +2024-11-22 18:09:56.107919: Epoch 5770 +2024-11-22 18:09:56.108041: Current learning rate: 0.00317 +2024-11-22 18:10:16.005750: train_loss -0.7983 +2024-11-22 18:10:16.006070: val_loss -0.7425 +2024-11-22 18:10:16.006156: Pseudo dice [0.839] +2024-11-22 18:10:16.006238: Epoch time: 19.9 s +2024-11-22 18:10:16.912475: +2024-11-22 18:10:16.912766: Epoch 5771 +2024-11-22 18:10:16.912882: Current learning rate: 0.00317 +2024-11-22 18:10:35.670072: train_loss -0.8046 +2024-11-22 18:10:35.670323: val_loss -0.7658 +2024-11-22 18:10:35.670399: Pseudo dice [0.8347] +2024-11-22 18:10:35.670485: Epoch time: 18.76 s +2024-11-22 18:10:36.557403: +2024-11-22 18:10:36.557610: Epoch 5772 +2024-11-22 18:10:36.557722: Current learning rate: 0.00316 +2024-11-22 18:10:56.574654: train_loss -0.8061 +2024-11-22 18:10:56.574892: val_loss -0.7375 +2024-11-22 18:10:56.574968: Pseudo dice [0.8199] +2024-11-22 18:10:56.575054: Epoch time: 20.02 s +2024-11-22 18:10:57.501086: +2024-11-22 18:10:57.501303: Epoch 5773 +2024-11-22 18:10:57.501414: Current learning rate: 0.00316 +2024-11-22 18:11:15.399298: train_loss -0.8096 +2024-11-22 18:11:15.399529: val_loss -0.7683 +2024-11-22 18:11:15.399603: Pseudo dice [0.8473] +2024-11-22 18:11:15.399678: Epoch time: 17.9 s +2024-11-22 18:11:16.281759: +2024-11-22 18:11:16.281954: Epoch 5774 +2024-11-22 18:11:16.282069: Current learning rate: 0.00316 +2024-11-22 18:11:34.571598: train_loss -0.8078 +2024-11-22 18:11:34.571824: val_loss -0.7685 +2024-11-22 18:11:34.574117: Pseudo dice [0.8331] +2024-11-22 18:11:34.574208: Epoch time: 18.29 s +2024-11-22 18:11:35.597375: +2024-11-22 18:11:35.597571: Epoch 5775 +2024-11-22 18:11:35.597689: Current learning rate: 0.00316 +2024-11-22 18:11:54.835368: train_loss -0.8098 +2024-11-22 18:11:54.835587: val_loss -0.7434 +2024-11-22 18:11:54.835732: Pseudo dice [0.8307] +2024-11-22 18:11:54.835814: Epoch time: 19.24 s +2024-11-22 18:11:55.749112: +2024-11-22 18:11:55.749412: Epoch 5776 +2024-11-22 18:11:55.749529: Current learning rate: 0.00316 +2024-11-22 18:12:13.644083: train_loss -0.81 +2024-11-22 18:12:13.644326: val_loss -0.7392 +2024-11-22 18:12:13.644403: Pseudo dice [0.8149] +2024-11-22 18:12:13.644481: Epoch time: 17.9 s +2024-11-22 18:12:14.551589: +2024-11-22 18:12:14.551833: Epoch 5777 +2024-11-22 18:12:14.551943: Current learning rate: 0.00316 +2024-11-22 18:12:33.661115: train_loss -0.8064 +2024-11-22 18:12:33.661341: val_loss -0.7654 +2024-11-22 18:12:33.661415: Pseudo dice [0.8338] +2024-11-22 18:12:33.661494: Epoch time: 19.11 s +2024-11-22 18:12:34.703972: +2024-11-22 18:12:34.704417: Epoch 5778 +2024-11-22 18:12:34.704558: Current learning rate: 0.00316 +2024-11-22 18:12:53.989697: train_loss -0.8011 +2024-11-22 18:12:53.989926: val_loss -0.7575 +2024-11-22 18:12:53.990006: Pseudo dice [0.827] +2024-11-22 18:12:53.990084: Epoch time: 19.29 s +2024-11-22 18:12:54.903019: +2024-11-22 18:12:54.903461: Epoch 5779 +2024-11-22 18:12:54.903613: Current learning rate: 0.00316 +2024-11-22 18:13:13.764923: train_loss -0.8047 +2024-11-22 18:13:13.765197: val_loss -0.7411 +2024-11-22 18:13:13.765277: Pseudo dice [0.8353] +2024-11-22 18:13:13.765364: Epoch time: 18.86 s +2024-11-22 18:13:14.674212: +2024-11-22 18:13:14.674448: Epoch 5780 +2024-11-22 18:13:14.674562: Current learning rate: 0.00315 +2024-11-22 18:13:34.281369: train_loss -0.7947 +2024-11-22 18:13:34.286791: val_loss -0.764 +2024-11-22 18:13:34.286919: Pseudo dice [0.843] +2024-11-22 18:13:34.287009: Epoch time: 19.61 s +2024-11-22 18:13:35.379577: +2024-11-22 18:13:35.379791: Epoch 5781 +2024-11-22 18:13:35.379907: Current learning rate: 0.00315 +2024-11-22 18:13:54.375760: train_loss -0.8073 +2024-11-22 18:13:54.376003: val_loss -0.7389 +2024-11-22 18:13:54.376080: Pseudo dice [0.8293] +2024-11-22 18:13:54.376162: Epoch time: 19.0 s +2024-11-22 18:13:55.280117: +2024-11-22 18:13:55.280359: Epoch 5782 +2024-11-22 18:13:55.280475: Current learning rate: 0.00315 +2024-11-22 18:14:13.845180: train_loss -0.8082 +2024-11-22 18:14:13.845442: val_loss -0.7602 +2024-11-22 18:14:13.845524: Pseudo dice [0.819] +2024-11-22 18:14:13.845610: Epoch time: 18.57 s +2024-11-22 18:14:14.762798: +2024-11-22 18:14:14.763116: Epoch 5783 +2024-11-22 18:14:14.763238: Current learning rate: 0.00315 +2024-11-22 18:14:33.132756: train_loss -0.814 +2024-11-22 18:14:33.132999: val_loss -0.7437 +2024-11-22 18:14:33.133077: Pseudo dice [0.8287] +2024-11-22 18:14:33.133157: Epoch time: 18.37 s +2024-11-22 18:14:34.038447: +2024-11-22 18:14:34.038666: Epoch 5784 +2024-11-22 18:14:34.038788: Current learning rate: 0.00315 +2024-11-22 18:14:52.275423: train_loss -0.7936 +2024-11-22 18:14:52.275649: val_loss -0.7682 +2024-11-22 18:14:52.275724: Pseudo dice [0.8448] +2024-11-22 18:14:52.275803: Epoch time: 18.24 s +2024-11-22 18:14:53.177915: +2024-11-22 18:14:53.178133: Epoch 5785 +2024-11-22 18:14:53.178246: Current learning rate: 0.00315 +2024-11-22 18:15:10.825939: train_loss -0.81 +2024-11-22 18:15:10.826241: val_loss -0.7636 +2024-11-22 18:15:10.826320: Pseudo dice [0.8307] +2024-11-22 18:15:10.826409: Epoch time: 17.65 s +2024-11-22 18:15:11.766793: +2024-11-22 18:15:11.767087: Epoch 5786 +2024-11-22 18:15:11.767198: Current learning rate: 0.00315 +2024-11-22 18:15:31.560292: train_loss -0.8044 +2024-11-22 18:15:31.560526: val_loss -0.7105 +2024-11-22 18:15:31.560601: Pseudo dice [0.82] +2024-11-22 18:15:31.560677: Epoch time: 19.79 s +2024-11-22 18:15:32.468999: +2024-11-22 18:15:32.469277: Epoch 5787 +2024-11-22 18:15:32.469386: Current learning rate: 0.00315 +2024-11-22 18:15:50.355412: train_loss -0.8121 +2024-11-22 18:15:50.355647: val_loss -0.7473 +2024-11-22 18:15:50.355722: Pseudo dice [0.8361] +2024-11-22 18:15:50.355799: Epoch time: 17.89 s +2024-11-22 18:15:51.267882: +2024-11-22 18:15:51.268193: Epoch 5788 +2024-11-22 18:15:51.268311: Current learning rate: 0.00314 +2024-11-22 18:16:10.295045: train_loss -0.8046 +2024-11-22 18:16:10.295427: val_loss -0.7536 +2024-11-22 18:16:10.295516: Pseudo dice [0.8356] +2024-11-22 18:16:10.295597: Epoch time: 19.03 s +2024-11-22 18:16:11.210088: +2024-11-22 18:16:11.210270: Epoch 5789 +2024-11-22 18:16:11.210382: Current learning rate: 0.00314 +2024-11-22 18:16:29.862750: train_loss -0.795 +2024-11-22 18:16:29.863004: val_loss -0.7588 +2024-11-22 18:16:29.863081: Pseudo dice [0.8307] +2024-11-22 18:16:29.863164: Epoch time: 18.65 s +2024-11-22 18:16:30.987135: +2024-11-22 18:16:30.987319: Epoch 5790 +2024-11-22 18:16:30.987436: Current learning rate: 0.00314 +2024-11-22 18:16:48.685111: train_loss -0.8049 +2024-11-22 18:16:48.685331: val_loss -0.7482 +2024-11-22 18:16:48.685410: Pseudo dice [0.8218] +2024-11-22 18:16:48.685489: Epoch time: 17.7 s +2024-11-22 18:16:49.597262: +2024-11-22 18:16:49.597451: Epoch 5791 +2024-11-22 18:16:49.597559: Current learning rate: 0.00314 +2024-11-22 18:17:08.409319: train_loss -0.7919 +2024-11-22 18:17:08.409536: val_loss -0.7591 +2024-11-22 18:17:08.409610: Pseudo dice [0.8286] +2024-11-22 18:17:08.409687: Epoch time: 18.81 s +2024-11-22 18:17:09.319813: +2024-11-22 18:17:09.320065: Epoch 5792 +2024-11-22 18:17:09.320183: Current learning rate: 0.00314 +2024-11-22 18:17:29.216824: train_loss -0.7934 +2024-11-22 18:17:29.217081: val_loss -0.7418 +2024-11-22 18:17:29.217162: Pseudo dice [0.8327] +2024-11-22 18:17:29.217250: Epoch time: 19.9 s +2024-11-22 18:17:30.560917: +2024-11-22 18:17:30.561233: Epoch 5793 +2024-11-22 18:17:30.561351: Current learning rate: 0.00314 +2024-11-22 18:17:47.481256: train_loss -0.7982 +2024-11-22 18:17:47.481493: val_loss -0.7491 +2024-11-22 18:17:47.481574: Pseudo dice [0.8274] +2024-11-22 18:17:47.481651: Epoch time: 16.92 s +2024-11-22 18:17:48.384145: +2024-11-22 18:17:48.384351: Epoch 5794 +2024-11-22 18:17:48.384460: Current learning rate: 0.00314 +2024-11-22 18:18:06.204909: train_loss -0.7813 +2024-11-22 18:18:06.205157: val_loss -0.7521 +2024-11-22 18:18:06.205235: Pseudo dice [0.8314] +2024-11-22 18:18:06.205330: Epoch time: 17.82 s +2024-11-22 18:18:07.112583: +2024-11-22 18:18:07.112789: Epoch 5795 +2024-11-22 18:18:07.112903: Current learning rate: 0.00314 +2024-11-22 18:18:26.736747: train_loss -0.7914 +2024-11-22 18:18:26.737072: val_loss -0.7537 +2024-11-22 18:18:26.737159: Pseudo dice [0.8326] +2024-11-22 18:18:26.737250: Epoch time: 19.62 s +2024-11-22 18:18:27.646866: +2024-11-22 18:18:27.647089: Epoch 5796 +2024-11-22 18:18:27.647206: Current learning rate: 0.00313 +2024-11-22 18:18:46.129433: train_loss -0.8045 +2024-11-22 18:18:46.129674: val_loss -0.7569 +2024-11-22 18:18:46.129756: Pseudo dice [0.8194] +2024-11-22 18:18:46.129842: Epoch time: 18.48 s +2024-11-22 18:18:47.039865: +2024-11-22 18:18:47.040127: Epoch 5797 +2024-11-22 18:18:47.040241: Current learning rate: 0.00313 +2024-11-22 18:19:04.956057: train_loss -0.8113 +2024-11-22 18:19:04.956293: val_loss -0.7499 +2024-11-22 18:19:04.956367: Pseudo dice [0.8334] +2024-11-22 18:19:04.956459: Epoch time: 17.92 s +2024-11-22 18:19:05.868470: +2024-11-22 18:19:05.868691: Epoch 5798 +2024-11-22 18:19:05.868808: Current learning rate: 0.00313 +2024-11-22 18:19:24.611401: train_loss -0.8054 +2024-11-22 18:19:24.611620: val_loss -0.7714 +2024-11-22 18:19:24.611716: Pseudo dice [0.8374] +2024-11-22 18:19:24.611795: Epoch time: 18.74 s +2024-11-22 18:19:25.518903: +2024-11-22 18:19:25.519109: Epoch 5799 +2024-11-22 18:19:25.519222: Current learning rate: 0.00313 +2024-11-22 18:19:43.904831: train_loss -0.8089 +2024-11-22 18:19:43.905157: val_loss -0.758 +2024-11-22 18:19:43.905234: Pseudo dice [0.8349] +2024-11-22 18:19:43.905320: Epoch time: 18.39 s +2024-11-22 18:19:45.122972: +2024-11-22 18:19:45.123174: Epoch 5800 +2024-11-22 18:19:45.123293: Current learning rate: 0.00313 +2024-11-22 18:20:04.011498: train_loss -0.805 +2024-11-22 18:20:04.011724: val_loss -0.7772 +2024-11-22 18:20:04.011797: Pseudo dice [0.8386] +2024-11-22 18:20:04.011873: Epoch time: 18.89 s +2024-11-22 18:20:04.927841: +2024-11-22 18:20:04.928063: Epoch 5801 +2024-11-22 18:20:04.928178: Current learning rate: 0.00313 +2024-11-22 18:20:22.961730: train_loss -0.8039 +2024-11-22 18:20:22.961951: val_loss -0.7595 +2024-11-22 18:20:22.962032: Pseudo dice [0.8272] +2024-11-22 18:20:22.962112: Epoch time: 18.03 s +2024-11-22 18:20:23.865689: +2024-11-22 18:20:23.865896: Epoch 5802 +2024-11-22 18:20:23.866011: Current learning rate: 0.00313 +2024-11-22 18:20:41.660253: train_loss -0.8119 +2024-11-22 18:20:41.660470: val_loss -0.7516 +2024-11-22 18:20:41.660540: Pseudo dice [0.8413] +2024-11-22 18:20:41.660617: Epoch time: 17.8 s +2024-11-22 18:20:42.643934: +2024-11-22 18:20:42.644130: Epoch 5803 +2024-11-22 18:20:42.644247: Current learning rate: 0.00313 +2024-11-22 18:21:00.624749: train_loss -0.8097 +2024-11-22 18:21:00.625096: val_loss -0.7508 +2024-11-22 18:21:00.625182: Pseudo dice [0.8488] +2024-11-22 18:21:00.625271: Epoch time: 17.98 s +2024-11-22 18:21:01.529452: +2024-11-22 18:21:01.529648: Epoch 5804 +2024-11-22 18:21:01.529762: Current learning rate: 0.00312 +2024-11-22 18:21:19.859520: train_loss -0.8057 +2024-11-22 18:21:19.861967: val_loss -0.7687 +2024-11-22 18:21:19.862082: Pseudo dice [0.8435] +2024-11-22 18:21:19.862163: Epoch time: 18.33 s +2024-11-22 18:21:20.828458: +2024-11-22 18:21:20.828839: Epoch 5805 +2024-11-22 18:21:20.828954: Current learning rate: 0.00312 +2024-11-22 18:21:39.283205: train_loss -0.8121 +2024-11-22 18:21:39.288623: val_loss -0.7574 +2024-11-22 18:21:39.288758: Pseudo dice [0.8394] +2024-11-22 18:21:39.288841: Epoch time: 18.46 s +2024-11-22 18:21:40.257808: +2024-11-22 18:21:40.258043: Epoch 5806 +2024-11-22 18:21:40.258157: Current learning rate: 0.00312 +2024-11-22 18:21:58.703924: train_loss -0.7999 +2024-11-22 18:21:58.704193: val_loss -0.7565 +2024-11-22 18:21:58.704331: Pseudo dice [0.8398] +2024-11-22 18:21:58.704417: Epoch time: 18.45 s +2024-11-22 18:21:59.627751: +2024-11-22 18:21:59.628071: Epoch 5807 +2024-11-22 18:21:59.628186: Current learning rate: 0.00312 +2024-11-22 18:22:18.492557: train_loss -0.7962 +2024-11-22 18:22:18.492786: val_loss -0.7405 +2024-11-22 18:22:18.492860: Pseudo dice [0.817] +2024-11-22 18:22:18.492938: Epoch time: 18.87 s +2024-11-22 18:22:19.407714: +2024-11-22 18:22:19.407903: Epoch 5808 +2024-11-22 18:22:19.408028: Current learning rate: 0.00312 +2024-11-22 18:22:38.340932: train_loss -0.7854 +2024-11-22 18:22:38.341171: val_loss -0.7398 +2024-11-22 18:22:38.341249: Pseudo dice [0.846] +2024-11-22 18:22:38.341326: Epoch time: 18.93 s +2024-11-22 18:22:39.351147: +2024-11-22 18:22:39.351370: Epoch 5809 +2024-11-22 18:22:39.351485: Current learning rate: 0.00312 +2024-11-22 18:22:58.377731: train_loss -0.7903 +2024-11-22 18:22:58.377967: val_loss -0.7161 +2024-11-22 18:22:58.378057: Pseudo dice [0.836] +2024-11-22 18:22:58.378143: Epoch time: 19.03 s +2024-11-22 18:22:59.288918: +2024-11-22 18:22:59.289112: Epoch 5810 +2024-11-22 18:22:59.289223: Current learning rate: 0.00312 +2024-11-22 18:23:17.932760: train_loss -0.7881 +2024-11-22 18:23:17.933019: val_loss -0.7531 +2024-11-22 18:23:17.933095: Pseudo dice [0.8354] +2024-11-22 18:23:17.933175: Epoch time: 18.64 s +2024-11-22 18:23:18.846144: +2024-11-22 18:23:18.846364: Epoch 5811 +2024-11-22 18:23:18.846484: Current learning rate: 0.00311 +2024-11-22 18:23:37.151629: train_loss -0.8061 +2024-11-22 18:23:37.151852: val_loss -0.7272 +2024-11-22 18:23:37.151933: Pseudo dice [0.8181] +2024-11-22 18:23:37.152020: Epoch time: 18.31 s +2024-11-22 18:23:38.060068: +2024-11-22 18:23:38.060281: Epoch 5812 +2024-11-22 18:23:38.060393: Current learning rate: 0.00311 +2024-11-22 18:23:57.186737: train_loss -0.8069 +2024-11-22 18:23:57.187879: val_loss -0.759 +2024-11-22 18:23:57.187965: Pseudo dice [0.8416] +2024-11-22 18:23:57.188051: Epoch time: 19.13 s +2024-11-22 18:23:58.097132: +2024-11-22 18:23:58.097320: Epoch 5813 +2024-11-22 18:23:58.097433: Current learning rate: 0.00311 +2024-11-22 18:24:16.931598: train_loss -0.7989 +2024-11-22 18:24:16.931826: val_loss -0.7545 +2024-11-22 18:24:16.931905: Pseudo dice [0.8325] +2024-11-22 18:24:16.931983: Epoch time: 18.84 s +2024-11-22 18:24:17.843781: +2024-11-22 18:24:17.844006: Epoch 5814 +2024-11-22 18:24:17.844117: Current learning rate: 0.00311 +2024-11-22 18:24:36.853857: train_loss -0.8003 +2024-11-22 18:24:36.854215: val_loss -0.7537 +2024-11-22 18:24:36.864144: Pseudo dice [0.8163] +2024-11-22 18:24:36.864259: Epoch time: 19.01 s +2024-11-22 18:24:37.948722: +2024-11-22 18:24:37.948925: Epoch 5815 +2024-11-22 18:24:37.949042: Current learning rate: 0.00311 +2024-11-22 18:24:55.855036: train_loss -0.8069 +2024-11-22 18:24:55.855259: val_loss -0.7511 +2024-11-22 18:24:55.857494: Pseudo dice [0.829] +2024-11-22 18:24:55.857633: Epoch time: 17.91 s +2024-11-22 18:24:57.324683: +2024-11-22 18:24:57.324884: Epoch 5816 +2024-11-22 18:24:57.325010: Current learning rate: 0.00311 +2024-11-22 18:25:15.437032: train_loss -0.7901 +2024-11-22 18:25:15.437255: val_loss -0.7519 +2024-11-22 18:25:15.437330: Pseudo dice [0.8396] +2024-11-22 18:25:15.437406: Epoch time: 18.11 s +2024-11-22 18:25:16.349147: +2024-11-22 18:25:16.349370: Epoch 5817 +2024-11-22 18:25:16.349486: Current learning rate: 0.00311 +2024-11-22 18:25:35.279718: train_loss -0.8052 +2024-11-22 18:25:35.279971: val_loss -0.7519 +2024-11-22 18:25:35.280056: Pseudo dice [0.8255] +2024-11-22 18:25:35.280138: Epoch time: 18.93 s +2024-11-22 18:25:36.191042: +2024-11-22 18:25:36.191247: Epoch 5818 +2024-11-22 18:25:36.191360: Current learning rate: 0.00311 +2024-11-22 18:25:55.177454: train_loss -0.802 +2024-11-22 18:25:55.177677: val_loss -0.7632 +2024-11-22 18:25:55.177752: Pseudo dice [0.8342] +2024-11-22 18:25:55.177832: Epoch time: 18.99 s +2024-11-22 18:25:56.082784: +2024-11-22 18:25:56.082979: Epoch 5819 +2024-11-22 18:25:56.083095: Current learning rate: 0.0031 +2024-11-22 18:26:14.841206: train_loss -0.8019 +2024-11-22 18:26:14.841435: val_loss -0.7697 +2024-11-22 18:26:14.841509: Pseudo dice [0.8419] +2024-11-22 18:26:14.841587: Epoch time: 18.76 s +2024-11-22 18:26:15.755984: +2024-11-22 18:26:15.756342: Epoch 5820 +2024-11-22 18:26:15.756454: Current learning rate: 0.0031 +2024-11-22 18:26:33.404665: train_loss -0.8134 +2024-11-22 18:26:33.404893: val_loss -0.7581 +2024-11-22 18:26:33.404968: Pseudo dice [0.8326] +2024-11-22 18:26:33.405051: Epoch time: 17.65 s +2024-11-22 18:26:34.401403: +2024-11-22 18:26:34.401613: Epoch 5821 +2024-11-22 18:26:34.401737: Current learning rate: 0.0031 +2024-11-22 18:26:53.812533: train_loss -0.8022 +2024-11-22 18:26:53.812782: val_loss -0.7392 +2024-11-22 18:26:53.812864: Pseudo dice [0.8014] +2024-11-22 18:26:53.812949: Epoch time: 19.41 s +2024-11-22 18:26:54.723384: +2024-11-22 18:26:54.723569: Epoch 5822 +2024-11-22 18:26:54.723678: Current learning rate: 0.0031 +2024-11-22 18:27:12.914162: train_loss -0.8069 +2024-11-22 18:27:12.914373: val_loss -0.7603 +2024-11-22 18:27:12.914446: Pseudo dice [0.8274] +2024-11-22 18:27:12.914521: Epoch time: 18.19 s +2024-11-22 18:27:13.882926: +2024-11-22 18:27:13.883189: Epoch 5823 +2024-11-22 18:27:13.883306: Current learning rate: 0.0031 +2024-11-22 18:27:32.411822: train_loss -0.8114 +2024-11-22 18:27:32.412046: val_loss -0.747 +2024-11-22 18:27:32.412120: Pseudo dice [0.8304] +2024-11-22 18:27:32.412198: Epoch time: 18.53 s +2024-11-22 18:27:33.386744: +2024-11-22 18:27:33.387066: Epoch 5824 +2024-11-22 18:27:33.387186: Current learning rate: 0.0031 +2024-11-22 18:27:52.058146: train_loss -0.809 +2024-11-22 18:27:52.058361: val_loss -0.7248 +2024-11-22 18:27:52.058434: Pseudo dice [0.8267] +2024-11-22 18:27:52.058514: Epoch time: 18.67 s +2024-11-22 18:27:52.965482: +2024-11-22 18:27:52.965681: Epoch 5825 +2024-11-22 18:27:52.965796: Current learning rate: 0.0031 +2024-11-22 18:28:11.650607: train_loss -0.8039 +2024-11-22 18:28:11.650842: val_loss -0.7414 +2024-11-22 18:28:11.650916: Pseudo dice [0.8272] +2024-11-22 18:28:11.651011: Epoch time: 18.69 s +2024-11-22 18:28:12.595801: +2024-11-22 18:28:12.596077: Epoch 5826 +2024-11-22 18:28:12.596195: Current learning rate: 0.0031 +2024-11-22 18:28:32.516611: train_loss -0.7986 +2024-11-22 18:28:32.516823: val_loss -0.7617 +2024-11-22 18:28:32.516900: Pseudo dice [0.8284] +2024-11-22 18:28:32.516976: Epoch time: 19.92 s +2024-11-22 18:28:33.424918: +2024-11-22 18:28:33.425177: Epoch 5827 +2024-11-22 18:28:33.425293: Current learning rate: 0.00309 +2024-11-22 18:28:52.214905: train_loss -0.8137 +2024-11-22 18:28:52.215135: val_loss -0.7516 +2024-11-22 18:28:52.215212: Pseudo dice [0.8198] +2024-11-22 18:28:52.215288: Epoch time: 18.79 s +2024-11-22 18:28:53.120556: +2024-11-22 18:28:53.120825: Epoch 5828 +2024-11-22 18:28:53.120942: Current learning rate: 0.00309 +2024-11-22 18:29:11.495564: train_loss -0.8131 +2024-11-22 18:29:11.495810: val_loss -0.7558 +2024-11-22 18:29:11.495890: Pseudo dice [0.8241] +2024-11-22 18:29:11.495968: Epoch time: 18.38 s +2024-11-22 18:29:12.441531: +2024-11-22 18:29:12.441788: Epoch 5829 +2024-11-22 18:29:12.441904: Current learning rate: 0.00309 +2024-11-22 18:29:31.629728: train_loss -0.8006 +2024-11-22 18:29:31.632488: val_loss -0.7503 +2024-11-22 18:29:31.632592: Pseudo dice [0.8376] +2024-11-22 18:29:31.632677: Epoch time: 19.19 s +2024-11-22 18:29:32.623350: +2024-11-22 18:29:32.623566: Epoch 5830 +2024-11-22 18:29:32.623679: Current learning rate: 0.00309 +2024-11-22 18:29:51.562352: train_loss -0.8042 +2024-11-22 18:29:51.562576: val_loss -0.73 +2024-11-22 18:29:51.562651: Pseudo dice [0.8137] +2024-11-22 18:29:51.562726: Epoch time: 18.94 s +2024-11-22 18:29:52.470194: +2024-11-22 18:29:52.470434: Epoch 5831 +2024-11-22 18:29:52.470552: Current learning rate: 0.00309 +2024-11-22 18:30:10.285932: train_loss -0.8062 +2024-11-22 18:30:10.286173: val_loss -0.7406 +2024-11-22 18:30:10.286251: Pseudo dice [0.8422] +2024-11-22 18:30:10.286332: Epoch time: 17.82 s +2024-11-22 18:30:11.199261: +2024-11-22 18:30:11.199492: Epoch 5832 +2024-11-22 18:30:11.199608: Current learning rate: 0.00309 +2024-11-22 18:30:30.847742: train_loss -0.7869 +2024-11-22 18:30:30.847983: val_loss -0.766 +2024-11-22 18:30:30.848067: Pseudo dice [0.8132] +2024-11-22 18:30:30.848146: Epoch time: 19.65 s +2024-11-22 18:30:31.769723: +2024-11-22 18:30:31.769928: Epoch 5833 +2024-11-22 18:30:31.770046: Current learning rate: 0.00309 +2024-11-22 18:30:51.227985: train_loss -0.8007 +2024-11-22 18:30:51.228311: val_loss -0.7594 +2024-11-22 18:30:51.228387: Pseudo dice [0.8387] +2024-11-22 18:30:51.228471: Epoch time: 19.46 s +2024-11-22 18:30:52.291181: +2024-11-22 18:30:52.291388: Epoch 5834 +2024-11-22 18:30:52.291504: Current learning rate: 0.00309 +2024-11-22 18:31:11.990130: train_loss -0.798 +2024-11-22 18:31:11.990347: val_loss -0.7651 +2024-11-22 18:31:11.990512: Pseudo dice [0.844] +2024-11-22 18:31:11.990591: Epoch time: 19.7 s +2024-11-22 18:31:12.902891: +2024-11-22 18:31:12.903092: Epoch 5835 +2024-11-22 18:31:12.903205: Current learning rate: 0.00308 +2024-11-22 18:31:32.100530: train_loss -0.8055 +2024-11-22 18:31:32.100751: val_loss -0.7419 +2024-11-22 18:31:32.100827: Pseudo dice [0.8142] +2024-11-22 18:31:32.100902: Epoch time: 19.2 s +2024-11-22 18:31:33.005395: +2024-11-22 18:31:33.005796: Epoch 5836 +2024-11-22 18:31:33.005910: Current learning rate: 0.00308 +2024-11-22 18:31:53.051021: train_loss -0.8055 +2024-11-22 18:31:53.051248: val_loss -0.751 +2024-11-22 18:31:53.051320: Pseudo dice [0.8351] +2024-11-22 18:31:53.055010: Epoch time: 20.05 s +2024-11-22 18:31:54.014349: +2024-11-22 18:31:54.014685: Epoch 5837 +2024-11-22 18:31:54.014797: Current learning rate: 0.00308 +2024-11-22 18:32:12.264453: train_loss -0.8051 +2024-11-22 18:32:12.264697: val_loss -0.7348 +2024-11-22 18:32:12.264771: Pseudo dice [0.8398] +2024-11-22 18:32:12.264854: Epoch time: 18.25 s +2024-11-22 18:32:13.199242: +2024-11-22 18:32:13.199444: Epoch 5838 +2024-11-22 18:32:13.199572: Current learning rate: 0.00308 +2024-11-22 18:32:31.631559: train_loss -0.8026 +2024-11-22 18:32:31.631827: val_loss -0.7574 +2024-11-22 18:32:31.631901: Pseudo dice [0.8288] +2024-11-22 18:32:31.631977: Epoch time: 18.43 s +2024-11-22 18:32:32.960001: +2024-11-22 18:32:32.960232: Epoch 5839 +2024-11-22 18:32:32.960358: Current learning rate: 0.00308 +2024-11-22 18:32:51.604316: train_loss -0.8021 +2024-11-22 18:32:51.604571: val_loss -0.7518 +2024-11-22 18:32:51.609925: Pseudo dice [0.8281] +2024-11-22 18:32:51.610026: Epoch time: 18.65 s +2024-11-22 18:32:52.548331: +2024-11-22 18:32:52.548536: Epoch 5840 +2024-11-22 18:32:52.548646: Current learning rate: 0.00308 +2024-11-22 18:33:11.468031: train_loss -0.7979 +2024-11-22 18:33:11.468283: val_loss -0.7548 +2024-11-22 18:33:11.468361: Pseudo dice [0.8358] +2024-11-22 18:33:11.468447: Epoch time: 18.92 s +2024-11-22 18:33:12.380894: +2024-11-22 18:33:12.381099: Epoch 5841 +2024-11-22 18:33:12.381210: Current learning rate: 0.00308 +2024-11-22 18:33:30.459760: train_loss -0.8065 +2024-11-22 18:33:30.460010: val_loss -0.7559 +2024-11-22 18:33:30.460086: Pseudo dice [0.8414] +2024-11-22 18:33:30.460167: Epoch time: 18.08 s +2024-11-22 18:33:31.605999: +2024-11-22 18:33:31.606217: Epoch 5842 +2024-11-22 18:33:31.606331: Current learning rate: 0.00308 +2024-11-22 18:33:50.302885: train_loss -0.8093 +2024-11-22 18:33:50.303123: val_loss -0.7391 +2024-11-22 18:33:50.303203: Pseudo dice [0.8257] +2024-11-22 18:33:50.303300: Epoch time: 18.7 s +2024-11-22 18:33:51.217847: +2024-11-22 18:33:51.218121: Epoch 5843 +2024-11-22 18:33:51.218237: Current learning rate: 0.00307 +2024-11-22 18:34:09.804210: train_loss -0.804 +2024-11-22 18:34:09.804439: val_loss -0.7604 +2024-11-22 18:34:09.804513: Pseudo dice [0.8422] +2024-11-22 18:34:09.804591: Epoch time: 18.59 s +2024-11-22 18:34:10.749933: +2024-11-22 18:34:10.750134: Epoch 5844 +2024-11-22 18:34:10.750251: Current learning rate: 0.00307 +2024-11-22 18:34:29.582119: train_loss -0.8015 +2024-11-22 18:34:29.582372: val_loss -0.7708 +2024-11-22 18:34:29.582472: Pseudo dice [0.8447] +2024-11-22 18:34:29.582555: Epoch time: 18.83 s +2024-11-22 18:34:30.498291: +2024-11-22 18:34:30.498512: Epoch 5845 +2024-11-22 18:34:30.498633: Current learning rate: 0.00307 +2024-11-22 18:34:50.352899: train_loss -0.8034 +2024-11-22 18:34:50.353148: val_loss -0.7396 +2024-11-22 18:34:50.353246: Pseudo dice [0.8198] +2024-11-22 18:34:50.353329: Epoch time: 19.86 s +2024-11-22 18:34:51.259232: +2024-11-22 18:34:51.259443: Epoch 5846 +2024-11-22 18:34:51.259555: Current learning rate: 0.00307 +2024-11-22 18:35:10.161501: train_loss -0.8039 +2024-11-22 18:35:10.161738: val_loss -0.7532 +2024-11-22 18:35:10.161816: Pseudo dice [0.8315] +2024-11-22 18:35:10.161896: Epoch time: 18.9 s +2024-11-22 18:35:11.076524: +2024-11-22 18:35:11.076738: Epoch 5847 +2024-11-22 18:35:11.076855: Current learning rate: 0.00307 +2024-11-22 18:35:29.629964: train_loss -0.8118 +2024-11-22 18:35:29.630198: val_loss -0.7365 +2024-11-22 18:35:29.632494: Pseudo dice [0.8153] +2024-11-22 18:35:29.632596: Epoch time: 18.55 s +2024-11-22 18:35:30.704890: +2024-11-22 18:35:30.705128: Epoch 5848 +2024-11-22 18:35:30.705245: Current learning rate: 0.00307 +2024-11-22 18:35:49.326613: train_loss -0.8049 +2024-11-22 18:35:49.326830: val_loss -0.7429 +2024-11-22 18:35:49.326909: Pseudo dice [0.8196] +2024-11-22 18:35:49.326998: Epoch time: 18.62 s +2024-11-22 18:35:50.239949: +2024-11-22 18:35:50.240241: Epoch 5849 +2024-11-22 18:35:50.240357: Current learning rate: 0.00307 +2024-11-22 18:36:08.808911: train_loss -0.8068 +2024-11-22 18:36:08.809157: val_loss -0.7263 +2024-11-22 18:36:08.809234: Pseudo dice [0.8234] +2024-11-22 18:36:08.809316: Epoch time: 18.57 s +2024-11-22 18:36:10.393174: +2024-11-22 18:36:10.393465: Epoch 5850 +2024-11-22 18:36:10.393578: Current learning rate: 0.00306 +2024-11-22 18:36:29.000986: train_loss -0.785 +2024-11-22 18:36:29.001227: val_loss -0.7087 +2024-11-22 18:36:29.032426: Pseudo dice [0.8132] +2024-11-22 18:36:29.032528: Epoch time: 18.61 s +2024-11-22 18:36:29.939617: +2024-11-22 18:36:29.939891: Epoch 5851 +2024-11-22 18:36:29.940009: Current learning rate: 0.00306 +2024-11-22 18:36:49.305465: train_loss -0.7698 +2024-11-22 18:36:49.305699: val_loss -0.7534 +2024-11-22 18:36:49.305774: Pseudo dice [0.8375] +2024-11-22 18:36:49.305852: Epoch time: 19.37 s +2024-11-22 18:36:50.218696: +2024-11-22 18:36:50.218975: Epoch 5852 +2024-11-22 18:36:50.219091: Current learning rate: 0.00306 +2024-11-22 18:37:09.131853: train_loss -0.7951 +2024-11-22 18:37:09.132113: val_loss -0.7589 +2024-11-22 18:37:09.132190: Pseudo dice [0.8288] +2024-11-22 18:37:09.132273: Epoch time: 18.91 s +2024-11-22 18:37:10.042392: +2024-11-22 18:37:10.042595: Epoch 5853 +2024-11-22 18:37:10.042709: Current learning rate: 0.00306 +2024-11-22 18:37:29.991331: train_loss -0.788 +2024-11-22 18:37:29.991562: val_loss -0.7402 +2024-11-22 18:37:29.991639: Pseudo dice [0.8233] +2024-11-22 18:37:29.991721: Epoch time: 19.95 s +2024-11-22 18:37:30.983591: +2024-11-22 18:37:30.983872: Epoch 5854 +2024-11-22 18:37:30.983984: Current learning rate: 0.00306 +2024-11-22 18:37:49.402929: train_loss -0.7828 +2024-11-22 18:37:49.403178: val_loss -0.7573 +2024-11-22 18:37:49.403254: Pseudo dice [0.8484] +2024-11-22 18:37:49.403332: Epoch time: 18.42 s +2024-11-22 18:37:50.353803: +2024-11-22 18:37:50.353999: Epoch 5855 +2024-11-22 18:37:50.354111: Current learning rate: 0.00306 +2024-11-22 18:38:09.707739: train_loss -0.7977 +2024-11-22 18:38:09.707964: val_loss -0.7542 +2024-11-22 18:38:09.708054: Pseudo dice [0.8356] +2024-11-22 18:38:09.708135: Epoch time: 19.35 s +2024-11-22 18:38:10.622537: +2024-11-22 18:38:10.622774: Epoch 5856 +2024-11-22 18:38:10.622895: Current learning rate: 0.00306 +2024-11-22 18:38:28.597864: train_loss -0.8033 +2024-11-22 18:38:28.598113: val_loss -0.7332 +2024-11-22 18:38:28.598188: Pseudo dice [0.8212] +2024-11-22 18:38:28.598271: Epoch time: 17.98 s +2024-11-22 18:38:29.570977: +2024-11-22 18:38:29.571208: Epoch 5857 +2024-11-22 18:38:29.571327: Current learning rate: 0.00306 +2024-11-22 18:38:49.241007: train_loss -0.7902 +2024-11-22 18:38:49.241252: val_loss -0.7396 +2024-11-22 18:38:49.241333: Pseudo dice [0.8076] +2024-11-22 18:38:49.241418: Epoch time: 19.67 s +2024-11-22 18:38:50.155968: +2024-11-22 18:38:50.156171: Epoch 5858 +2024-11-22 18:38:50.156288: Current learning rate: 0.00305 +2024-11-22 18:39:08.576330: train_loss -0.8001 +2024-11-22 18:39:08.581731: val_loss -0.7302 +2024-11-22 18:39:08.581883: Pseudo dice [0.8115] +2024-11-22 18:39:08.581965: Epoch time: 18.42 s +2024-11-22 18:39:09.658982: +2024-11-22 18:39:09.659219: Epoch 5859 +2024-11-22 18:39:09.659330: Current learning rate: 0.00305 +2024-11-22 18:39:28.874504: train_loss -0.8071 +2024-11-22 18:39:28.874726: val_loss -0.7737 +2024-11-22 18:39:28.874801: Pseudo dice [0.8443] +2024-11-22 18:39:28.874878: Epoch time: 19.22 s +2024-11-22 18:39:29.785191: +2024-11-22 18:39:29.785448: Epoch 5860 +2024-11-22 18:39:29.785561: Current learning rate: 0.00305 +2024-11-22 18:39:47.967448: train_loss -0.8003 +2024-11-22 18:39:47.967699: val_loss -0.7521 +2024-11-22 18:39:47.967773: Pseudo dice [0.8333] +2024-11-22 18:39:47.967860: Epoch time: 18.18 s +2024-11-22 18:39:48.876770: +2024-11-22 18:39:48.876971: Epoch 5861 +2024-11-22 18:39:48.877090: Current learning rate: 0.00305 +2024-11-22 18:40:08.018975: train_loss -0.7994 +2024-11-22 18:40:08.019202: val_loss -0.7617 +2024-11-22 18:40:08.019278: Pseudo dice [0.8396] +2024-11-22 18:40:08.019352: Epoch time: 19.14 s +2024-11-22 18:40:09.386973: +2024-11-22 18:40:09.387175: Epoch 5862 +2024-11-22 18:40:09.387283: Current learning rate: 0.00305 +2024-11-22 18:40:28.480336: train_loss -0.8043 +2024-11-22 18:40:28.482743: val_loss -0.7322 +2024-11-22 18:40:28.482891: Pseudo dice [0.8055] +2024-11-22 18:40:28.482981: Epoch time: 19.09 s +2024-11-22 18:40:29.407740: +2024-11-22 18:40:29.408082: Epoch 5863 +2024-11-22 18:40:29.408198: Current learning rate: 0.00305 +2024-11-22 18:40:46.952557: train_loss -0.8013 +2024-11-22 18:40:46.952819: val_loss -0.7548 +2024-11-22 18:40:46.952899: Pseudo dice [0.8454] +2024-11-22 18:40:46.952982: Epoch time: 17.55 s +2024-11-22 18:40:47.893622: +2024-11-22 18:40:47.893840: Epoch 5864 +2024-11-22 18:40:47.893952: Current learning rate: 0.00305 +2024-11-22 18:41:06.119419: train_loss -0.8019 +2024-11-22 18:41:06.119648: val_loss -0.7095 +2024-11-22 18:41:06.119725: Pseudo dice [0.8158] +2024-11-22 18:41:06.119803: Epoch time: 18.23 s +2024-11-22 18:41:07.028645: +2024-11-22 18:41:07.028847: Epoch 5865 +2024-11-22 18:41:07.028963: Current learning rate: 0.00305 +2024-11-22 18:41:26.275310: train_loss -0.8038 +2024-11-22 18:41:26.275547: val_loss -0.7681 +2024-11-22 18:41:26.275625: Pseudo dice [0.8346] +2024-11-22 18:41:26.275705: Epoch time: 19.25 s +2024-11-22 18:41:27.186950: +2024-11-22 18:41:27.187197: Epoch 5866 +2024-11-22 18:41:27.187320: Current learning rate: 0.00304 +2024-11-22 18:41:46.363855: train_loss -0.8105 +2024-11-22 18:41:46.364099: val_loss -0.7478 +2024-11-22 18:41:46.364175: Pseudo dice [0.8524] +2024-11-22 18:41:46.364253: Epoch time: 19.18 s +2024-11-22 18:41:47.277345: +2024-11-22 18:41:47.277571: Epoch 5867 +2024-11-22 18:41:47.277689: Current learning rate: 0.00304 +2024-11-22 18:42:05.182683: train_loss -0.8007 +2024-11-22 18:42:05.185117: val_loss -0.7395 +2024-11-22 18:42:05.185212: Pseudo dice [0.8351] +2024-11-22 18:42:05.185302: Epoch time: 17.91 s +2024-11-22 18:42:06.317923: +2024-11-22 18:42:06.318113: Epoch 5868 +2024-11-22 18:42:06.318225: Current learning rate: 0.00304 +2024-11-22 18:42:24.505105: train_loss -0.8004 +2024-11-22 18:42:24.505384: val_loss -0.7571 +2024-11-22 18:42:24.505463: Pseudo dice [0.819] +2024-11-22 18:42:24.505540: Epoch time: 18.19 s +2024-11-22 18:42:25.412996: +2024-11-22 18:42:25.413241: Epoch 5869 +2024-11-22 18:42:25.413352: Current learning rate: 0.00304 +2024-11-22 18:42:44.650976: train_loss -0.8087 +2024-11-22 18:42:44.651210: val_loss -0.761 +2024-11-22 18:42:44.651284: Pseudo dice [0.8366] +2024-11-22 18:42:44.651358: Epoch time: 19.24 s +2024-11-22 18:42:45.559155: +2024-11-22 18:42:45.559354: Epoch 5870 +2024-11-22 18:42:45.559471: Current learning rate: 0.00304 +2024-11-22 18:43:05.102652: train_loss -0.7969 +2024-11-22 18:43:05.102876: val_loss -0.7549 +2024-11-22 18:43:05.102950: Pseudo dice [0.8428] +2024-11-22 18:43:05.103036: Epoch time: 19.54 s +2024-11-22 18:43:06.016040: +2024-11-22 18:43:06.016260: Epoch 5871 +2024-11-22 18:43:06.016371: Current learning rate: 0.00304 +2024-11-22 18:43:23.997149: train_loss -0.8064 +2024-11-22 18:43:24.000757: val_loss -0.754 +2024-11-22 18:43:24.000889: Pseudo dice [0.8424] +2024-11-22 18:43:24.000978: Epoch time: 17.98 s +2024-11-22 18:43:24.954515: +2024-11-22 18:43:24.954772: Epoch 5872 +2024-11-22 18:43:24.954893: Current learning rate: 0.00304 +2024-11-22 18:43:43.331226: train_loss -0.8136 +2024-11-22 18:43:43.336629: val_loss -0.7692 +2024-11-22 18:43:43.336743: Pseudo dice [0.8445] +2024-11-22 18:43:43.336828: Epoch time: 18.38 s +2024-11-22 18:43:44.252936: +2024-11-22 18:43:44.253127: Epoch 5873 +2024-11-22 18:43:44.253241: Current learning rate: 0.00304 +2024-11-22 18:44:04.121456: train_loss -0.8081 +2024-11-22 18:44:04.122655: val_loss -0.7662 +2024-11-22 18:44:04.122764: Pseudo dice [0.8414] +2024-11-22 18:44:04.122845: Epoch time: 19.87 s +2024-11-22 18:44:05.037472: +2024-11-22 18:44:05.037680: Epoch 5874 +2024-11-22 18:44:05.037823: Current learning rate: 0.00303 +2024-11-22 18:44:23.950669: train_loss -0.815 +2024-11-22 18:44:23.950906: val_loss -0.7656 +2024-11-22 18:44:23.950981: Pseudo dice [0.8394] +2024-11-22 18:44:23.951072: Epoch time: 18.91 s +2024-11-22 18:44:24.875100: +2024-11-22 18:44:24.875361: Epoch 5875 +2024-11-22 18:44:24.875474: Current learning rate: 0.00303 +2024-11-22 18:44:44.306832: train_loss -0.7949 +2024-11-22 18:44:44.307079: val_loss -0.7642 +2024-11-22 18:44:44.307219: Pseudo dice [0.8368] +2024-11-22 18:44:44.307297: Epoch time: 19.43 s +2024-11-22 18:44:45.220088: +2024-11-22 18:44:45.220994: Epoch 5876 +2024-11-22 18:44:45.221109: Current learning rate: 0.00303 +2024-11-22 18:45:03.924838: train_loss -0.8003 +2024-11-22 18:45:03.925067: val_loss -0.7371 +2024-11-22 18:45:03.925145: Pseudo dice [0.8252] +2024-11-22 18:45:03.925222: Epoch time: 18.71 s +2024-11-22 18:45:04.857088: +2024-11-22 18:45:04.857337: Epoch 5877 +2024-11-22 18:45:04.857452: Current learning rate: 0.00303 +2024-11-22 18:45:24.291242: train_loss -0.7973 +2024-11-22 18:45:24.291481: val_loss -0.7308 +2024-11-22 18:45:24.291571: Pseudo dice [0.8161] +2024-11-22 18:45:24.291663: Epoch time: 19.43 s +2024-11-22 18:45:25.200410: +2024-11-22 18:45:25.200608: Epoch 5878 +2024-11-22 18:45:25.200723: Current learning rate: 0.00303 +2024-11-22 18:45:44.385337: train_loss -0.8043 +2024-11-22 18:45:44.385588: val_loss -0.7566 +2024-11-22 18:45:44.385664: Pseudo dice [0.8135] +2024-11-22 18:45:44.385743: Epoch time: 19.19 s +2024-11-22 18:45:45.305046: +2024-11-22 18:45:45.305338: Epoch 5879 +2024-11-22 18:45:45.305456: Current learning rate: 0.00303 +2024-11-22 18:46:02.257876: train_loss -0.8101 +2024-11-22 18:46:02.258098: val_loss -0.7469 +2024-11-22 18:46:02.258178: Pseudo dice [0.8385] +2024-11-22 18:46:02.258257: Epoch time: 16.95 s +2024-11-22 18:46:03.172885: +2024-11-22 18:46:03.173118: Epoch 5880 +2024-11-22 18:46:03.173238: Current learning rate: 0.00303 +2024-11-22 18:46:21.892094: train_loss -0.8139 +2024-11-22 18:46:21.892306: val_loss -0.7216 +2024-11-22 18:46:21.892379: Pseudo dice [0.8321] +2024-11-22 18:46:21.892453: Epoch time: 18.72 s +2024-11-22 18:46:22.805905: +2024-11-22 18:46:22.806113: Epoch 5881 +2024-11-22 18:46:22.806223: Current learning rate: 0.00303 +2024-11-22 18:46:41.056417: train_loss -0.8067 +2024-11-22 18:46:41.056669: val_loss -0.7322 +2024-11-22 18:46:41.056746: Pseudo dice [0.8133] +2024-11-22 18:46:41.056852: Epoch time: 18.25 s +2024-11-22 18:46:41.970450: +2024-11-22 18:46:41.970661: Epoch 5882 +2024-11-22 18:46:41.970777: Current learning rate: 0.00302 +2024-11-22 18:46:59.976224: train_loss -0.808 +2024-11-22 18:46:59.976443: val_loss -0.7785 +2024-11-22 18:46:59.976516: Pseudo dice [0.8387] +2024-11-22 18:46:59.976592: Epoch time: 18.01 s +2024-11-22 18:47:00.887071: +2024-11-22 18:47:00.887269: Epoch 5883 +2024-11-22 18:47:00.887384: Current learning rate: 0.00302 +2024-11-22 18:47:19.718510: train_loss -0.8107 +2024-11-22 18:47:19.718739: val_loss -0.7527 +2024-11-22 18:47:19.723955: Pseudo dice [0.8336] +2024-11-22 18:47:19.724109: Epoch time: 18.83 s +2024-11-22 18:47:20.773462: +2024-11-22 18:47:20.773670: Epoch 5884 +2024-11-22 18:47:20.773781: Current learning rate: 0.00302 +2024-11-22 18:47:38.760694: train_loss -0.8054 +2024-11-22 18:47:38.760917: val_loss -0.7594 +2024-11-22 18:47:38.760998: Pseudo dice [0.8228] +2024-11-22 18:47:38.761075: Epoch time: 17.99 s +2024-11-22 18:47:40.101680: +2024-11-22 18:47:40.101884: Epoch 5885 +2024-11-22 18:47:40.102001: Current learning rate: 0.00302 +2024-11-22 18:47:58.034775: train_loss -0.8054 +2024-11-22 18:47:58.035031: val_loss -0.7565 +2024-11-22 18:47:58.035110: Pseudo dice [0.8297] +2024-11-22 18:47:58.035190: Epoch time: 17.93 s +2024-11-22 18:47:58.939958: +2024-11-22 18:47:58.940243: Epoch 5886 +2024-11-22 18:47:58.940359: Current learning rate: 0.00302 +2024-11-22 18:48:17.700862: train_loss -0.8033 +2024-11-22 18:48:17.701087: val_loss -0.7408 +2024-11-22 18:48:17.701162: Pseudo dice [0.8184] +2024-11-22 18:48:17.701242: Epoch time: 18.76 s +2024-11-22 18:48:18.661337: +2024-11-22 18:48:18.661557: Epoch 5887 +2024-11-22 18:48:18.661671: Current learning rate: 0.00302 +2024-11-22 18:48:37.745245: train_loss -0.7945 +2024-11-22 18:48:37.747623: val_loss -0.7546 +2024-11-22 18:48:37.747718: Pseudo dice [0.8114] +2024-11-22 18:48:37.747793: Epoch time: 19.08 s +2024-11-22 18:48:38.776998: +2024-11-22 18:48:38.777247: Epoch 5888 +2024-11-22 18:48:38.777370: Current learning rate: 0.00302 +2024-11-22 18:48:57.303518: train_loss -0.8049 +2024-11-22 18:48:57.303745: val_loss -0.7545 +2024-11-22 18:48:57.304644: Pseudo dice [0.8359] +2024-11-22 18:48:57.304785: Epoch time: 18.53 s +2024-11-22 18:48:58.267274: +2024-11-22 18:48:58.267477: Epoch 5889 +2024-11-22 18:48:58.267587: Current learning rate: 0.00301 +2024-11-22 18:49:18.095320: train_loss -0.8087 +2024-11-22 18:49:18.095546: val_loss -0.7619 +2024-11-22 18:49:18.095623: Pseudo dice [0.8212] +2024-11-22 18:49:18.095702: Epoch time: 19.83 s +2024-11-22 18:49:19.007870: +2024-11-22 18:49:19.008072: Epoch 5890 +2024-11-22 18:49:19.008192: Current learning rate: 0.00301 +2024-11-22 18:49:38.144859: train_loss -0.8025 +2024-11-22 18:49:38.147254: val_loss -0.761 +2024-11-22 18:49:38.147348: Pseudo dice [0.8115] +2024-11-22 18:49:38.147428: Epoch time: 19.14 s +2024-11-22 18:49:39.061425: +2024-11-22 18:49:39.061686: Epoch 5891 +2024-11-22 18:49:39.061811: Current learning rate: 0.00301 +2024-11-22 18:49:57.263207: train_loss -0.8126 +2024-11-22 18:49:57.265231: val_loss -0.7253 +2024-11-22 18:49:57.265356: Pseudo dice [0.8211] +2024-11-22 18:49:57.265450: Epoch time: 18.2 s +2024-11-22 18:49:58.191564: +2024-11-22 18:49:58.191817: Epoch 5892 +2024-11-22 18:49:58.192057: Current learning rate: 0.00301 +2024-11-22 18:50:18.246279: train_loss -0.812 +2024-11-22 18:50:18.246530: val_loss -0.7432 +2024-11-22 18:50:18.246603: Pseudo dice [0.8389] +2024-11-22 18:50:18.246685: Epoch time: 20.06 s +2024-11-22 18:50:19.167594: +2024-11-22 18:50:19.167805: Epoch 5893 +2024-11-22 18:50:19.167927: Current learning rate: 0.00301 +2024-11-22 18:50:37.633706: train_loss -0.8138 +2024-11-22 18:50:37.633931: val_loss -0.7685 +2024-11-22 18:50:37.634014: Pseudo dice [0.8251] +2024-11-22 18:50:37.634093: Epoch time: 18.47 s +2024-11-22 18:50:38.542977: +2024-11-22 18:50:38.543222: Epoch 5894 +2024-11-22 18:50:38.543346: Current learning rate: 0.00301 +2024-11-22 18:50:55.947058: train_loss -0.8031 +2024-11-22 18:50:55.947287: val_loss -0.7748 +2024-11-22 18:50:55.947368: Pseudo dice [0.8363] +2024-11-22 18:50:55.947458: Epoch time: 17.4 s +2024-11-22 18:50:56.860026: +2024-11-22 18:50:56.860232: Epoch 5895 +2024-11-22 18:50:56.860349: Current learning rate: 0.00301 +2024-11-22 18:51:15.209162: train_loss -0.8072 +2024-11-22 18:51:15.209406: val_loss -0.7538 +2024-11-22 18:51:15.209484: Pseudo dice [0.8424] +2024-11-22 18:51:15.209565: Epoch time: 18.35 s +2024-11-22 18:51:16.124354: +2024-11-22 18:51:16.124561: Epoch 5896 +2024-11-22 18:51:16.124674: Current learning rate: 0.00301 +2024-11-22 18:51:35.421752: train_loss -0.8091 +2024-11-22 18:51:35.422258: val_loss -0.7408 +2024-11-22 18:51:35.427571: Pseudo dice [0.8237] +2024-11-22 18:51:35.427685: Epoch time: 19.3 s +2024-11-22 18:51:36.375395: +2024-11-22 18:51:36.375625: Epoch 5897 +2024-11-22 18:51:36.375749: Current learning rate: 0.003 +2024-11-22 18:51:55.092530: train_loss -0.8085 +2024-11-22 18:51:55.092757: val_loss -0.7647 +2024-11-22 18:51:55.092834: Pseudo dice [0.8235] +2024-11-22 18:51:55.092910: Epoch time: 18.72 s +2024-11-22 18:51:56.005616: +2024-11-22 18:51:56.005829: Epoch 5898 +2024-11-22 18:51:56.005946: Current learning rate: 0.003 +2024-11-22 18:52:14.655836: train_loss -0.8082 +2024-11-22 18:52:14.656062: val_loss -0.7586 +2024-11-22 18:52:14.656137: Pseudo dice [0.8378] +2024-11-22 18:52:14.656222: Epoch time: 18.65 s +2024-11-22 18:52:15.575125: +2024-11-22 18:52:15.575350: Epoch 5899 +2024-11-22 18:52:15.575463: Current learning rate: 0.003 +2024-11-22 18:52:33.710269: train_loss -0.806 +2024-11-22 18:52:33.710506: val_loss -0.7559 +2024-11-22 18:52:33.710586: Pseudo dice [0.8206] +2024-11-22 18:52:33.710668: Epoch time: 18.14 s +2024-11-22 18:52:34.916140: +2024-11-22 18:52:34.916350: Epoch 5900 +2024-11-22 18:52:34.916462: Current learning rate: 0.003 +2024-11-22 18:52:53.633217: train_loss -0.8042 +2024-11-22 18:52:53.633442: val_loss -0.767 +2024-11-22 18:52:53.633525: Pseudo dice [0.8423] +2024-11-22 18:52:53.633603: Epoch time: 18.72 s +2024-11-22 18:52:54.543525: +2024-11-22 18:52:54.543726: Epoch 5901 +2024-11-22 18:52:54.543841: Current learning rate: 0.003 +2024-11-22 18:53:13.725620: train_loss -0.8109 +2024-11-22 18:53:13.727913: val_loss -0.7583 +2024-11-22 18:53:13.728035: Pseudo dice [0.8272] +2024-11-22 18:53:13.728119: Epoch time: 19.18 s +2024-11-22 18:53:14.758664: +2024-11-22 18:53:14.758881: Epoch 5902 +2024-11-22 18:53:14.759004: Current learning rate: 0.003 +2024-11-22 18:53:33.700387: train_loss -0.797 +2024-11-22 18:53:33.700610: val_loss -0.7302 +2024-11-22 18:53:33.700689: Pseudo dice [0.8257] +2024-11-22 18:53:33.700770: Epoch time: 18.94 s +2024-11-22 18:53:34.616875: +2024-11-22 18:53:34.617116: Epoch 5903 +2024-11-22 18:53:34.617239: Current learning rate: 0.003 +2024-11-22 18:53:52.857817: train_loss -0.797 +2024-11-22 18:53:52.863242: val_loss -0.7548 +2024-11-22 18:53:52.863373: Pseudo dice [0.8377] +2024-11-22 18:53:52.863458: Epoch time: 18.24 s +2024-11-22 18:53:53.789703: +2024-11-22 18:53:53.789938: Epoch 5904 +2024-11-22 18:53:53.790066: Current learning rate: 0.003 +2024-11-22 18:54:13.136522: train_loss -0.7964 +2024-11-22 18:54:13.136745: val_loss -0.7499 +2024-11-22 18:54:13.136820: Pseudo dice [0.8273] +2024-11-22 18:54:13.136894: Epoch time: 19.35 s +2024-11-22 18:54:14.047029: +2024-11-22 18:54:14.047226: Epoch 5905 +2024-11-22 18:54:14.047339: Current learning rate: 0.00299 +2024-11-22 18:54:33.441083: train_loss -0.799 +2024-11-22 18:54:33.441305: val_loss -0.7553 +2024-11-22 18:54:33.441381: Pseudo dice [0.8456] +2024-11-22 18:54:33.441458: Epoch time: 19.39 s +2024-11-22 18:54:34.379175: +2024-11-22 18:54:34.379389: Epoch 5906 +2024-11-22 18:54:34.379501: Current learning rate: 0.00299 +2024-11-22 18:54:52.407943: train_loss -0.7995 +2024-11-22 18:54:52.408166: val_loss -0.748 +2024-11-22 18:54:52.408245: Pseudo dice [0.8323] +2024-11-22 18:54:52.408395: Epoch time: 18.03 s +2024-11-22 18:54:53.321448: +2024-11-22 18:54:53.321649: Epoch 5907 +2024-11-22 18:54:53.321759: Current learning rate: 0.00299 +2024-11-22 18:55:11.750668: train_loss -0.7972 +2024-11-22 18:55:11.751199: val_loss -0.734 +2024-11-22 18:55:11.751299: Pseudo dice [0.8233] +2024-11-22 18:55:11.751379: Epoch time: 18.43 s +2024-11-22 18:55:12.662787: +2024-11-22 18:55:12.663010: Epoch 5908 +2024-11-22 18:55:12.663124: Current learning rate: 0.00299 +2024-11-22 18:55:32.692686: train_loss -0.8053 +2024-11-22 18:55:32.692941: val_loss -0.7725 +2024-11-22 18:55:32.693031: Pseudo dice [0.8489] +2024-11-22 18:55:32.693134: Epoch time: 20.03 s +2024-11-22 18:55:33.605553: +2024-11-22 18:55:33.605775: Epoch 5909 +2024-11-22 18:55:33.605887: Current learning rate: 0.00299 +2024-11-22 18:55:53.368592: train_loss -0.7987 +2024-11-22 18:55:53.368817: val_loss -0.739 +2024-11-22 18:55:53.368916: Pseudo dice [0.8105] +2024-11-22 18:55:53.369001: Epoch time: 19.76 s +2024-11-22 18:55:54.395827: +2024-11-22 18:55:54.396064: Epoch 5910 +2024-11-22 18:55:54.396173: Current learning rate: 0.00299 +2024-11-22 18:56:13.763346: train_loss -0.803 +2024-11-22 18:56:13.763585: val_loss -0.7537 +2024-11-22 18:56:13.763662: Pseudo dice [0.8115] +2024-11-22 18:56:13.763745: Epoch time: 19.37 s +2024-11-22 18:56:14.754424: +2024-11-22 18:56:14.754640: Epoch 5911 +2024-11-22 18:56:14.754751: Current learning rate: 0.00299 +2024-11-22 18:56:33.526008: train_loss -0.8004 +2024-11-22 18:56:33.526234: val_loss -0.783 +2024-11-22 18:56:33.526315: Pseudo dice [0.8459] +2024-11-22 18:56:33.526393: Epoch time: 18.77 s +2024-11-22 18:56:34.437614: +2024-11-22 18:56:34.437835: Epoch 5912 +2024-11-22 18:56:34.437950: Current learning rate: 0.00299 +2024-11-22 18:56:53.883707: train_loss -0.804 +2024-11-22 18:56:53.883929: val_loss -0.7598 +2024-11-22 18:56:53.884013: Pseudo dice [0.826] +2024-11-22 18:56:53.884089: Epoch time: 19.45 s +2024-11-22 18:56:54.797195: +2024-11-22 18:56:54.797416: Epoch 5913 +2024-11-22 18:56:54.797532: Current learning rate: 0.00298 +2024-11-22 18:57:13.197597: train_loss -0.8048 +2024-11-22 18:57:13.197859: val_loss -0.7574 +2024-11-22 18:57:13.197936: Pseudo dice [0.827] +2024-11-22 18:57:13.198019: Epoch time: 18.4 s +2024-11-22 18:57:14.110254: +2024-11-22 18:57:14.110485: Epoch 5914 +2024-11-22 18:57:14.111410: Current learning rate: 0.00298 +2024-11-22 18:57:33.773561: train_loss -0.8063 +2024-11-22 18:57:33.773816: val_loss -0.7458 +2024-11-22 18:57:33.773972: Pseudo dice [0.8443] +2024-11-22 18:57:33.774118: Epoch time: 19.66 s +2024-11-22 18:57:34.685381: +2024-11-22 18:57:34.685653: Epoch 5915 +2024-11-22 18:57:34.685772: Current learning rate: 0.00298 +2024-11-22 18:57:53.528036: train_loss -0.8086 +2024-11-22 18:57:53.528253: val_loss -0.7561 +2024-11-22 18:57:53.528325: Pseudo dice [0.8376] +2024-11-22 18:57:53.528401: Epoch time: 18.84 s +2024-11-22 18:57:54.433766: +2024-11-22 18:57:54.434129: Epoch 5916 +2024-11-22 18:57:54.434244: Current learning rate: 0.00298 +2024-11-22 18:58:12.639581: train_loss -0.8102 +2024-11-22 18:58:12.639847: val_loss -0.7561 +2024-11-22 18:58:12.639917: Pseudo dice [0.8259] +2024-11-22 18:58:12.639996: Epoch time: 18.21 s +2024-11-22 18:58:13.567917: +2024-11-22 18:58:13.568114: Epoch 5917 +2024-11-22 18:58:13.568225: Current learning rate: 0.00298 +2024-11-22 18:58:32.311352: train_loss -0.8003 +2024-11-22 18:58:32.311574: val_loss -0.7615 +2024-11-22 18:58:32.311652: Pseudo dice [0.8211] +2024-11-22 18:58:32.311736: Epoch time: 18.74 s +2024-11-22 18:58:33.221263: +2024-11-22 18:58:33.221468: Epoch 5918 +2024-11-22 18:58:33.221705: Current learning rate: 0.00298 +2024-11-22 18:58:52.557257: train_loss -0.7983 +2024-11-22 18:58:52.557512: val_loss -0.7432 +2024-11-22 18:58:52.557587: Pseudo dice [0.8329] +2024-11-22 18:58:52.557668: Epoch time: 19.34 s +2024-11-22 18:58:54.051478: +2024-11-22 18:58:54.051709: Epoch 5919 +2024-11-22 18:58:54.051826: Current learning rate: 0.00298 +2024-11-22 18:59:12.823964: train_loss -0.8079 +2024-11-22 18:59:12.824211: val_loss -0.7656 +2024-11-22 18:59:12.824287: Pseudo dice [0.8386] +2024-11-22 18:59:12.824365: Epoch time: 18.77 s +2024-11-22 18:59:13.730519: +2024-11-22 18:59:13.730736: Epoch 5920 +2024-11-22 18:59:13.730853: Current learning rate: 0.00297 +2024-11-22 18:59:32.943152: train_loss -0.8001 +2024-11-22 18:59:32.943378: val_loss -0.7566 +2024-11-22 18:59:32.943452: Pseudo dice [0.8427] +2024-11-22 18:59:32.943529: Epoch time: 19.21 s +2024-11-22 18:59:33.856574: +2024-11-22 18:59:33.856782: Epoch 5921 +2024-11-22 18:59:33.856891: Current learning rate: 0.00297 +2024-11-22 18:59:53.151641: train_loss -0.8025 +2024-11-22 18:59:53.151912: val_loss -0.7315 +2024-11-22 18:59:53.152035: Pseudo dice [0.8207] +2024-11-22 18:59:53.152123: Epoch time: 19.3 s +2024-11-22 18:59:54.056924: +2024-11-22 18:59:54.057165: Epoch 5922 +2024-11-22 18:59:54.057295: Current learning rate: 0.00297 +2024-11-22 19:00:12.877802: train_loss -0.8074 +2024-11-22 19:00:12.878074: val_loss -0.7655 +2024-11-22 19:00:12.878154: Pseudo dice [0.8278] +2024-11-22 19:00:12.878232: Epoch time: 18.82 s +2024-11-22 19:00:13.787065: +2024-11-22 19:00:13.787390: Epoch 5923 +2024-11-22 19:00:13.787511: Current learning rate: 0.00297 +2024-11-22 19:00:31.921981: train_loss -0.8043 +2024-11-22 19:00:31.924128: val_loss -0.7497 +2024-11-22 19:00:31.924253: Pseudo dice [0.8263] +2024-11-22 19:00:31.924335: Epoch time: 18.14 s +2024-11-22 19:00:32.833541: +2024-11-22 19:00:32.833910: Epoch 5924 +2024-11-22 19:00:32.834048: Current learning rate: 0.00297 +2024-11-22 19:00:51.800648: train_loss -0.8103 +2024-11-22 19:00:51.800863: val_loss -0.7761 +2024-11-22 19:00:51.800939: Pseudo dice [0.8456] +2024-11-22 19:00:51.801025: Epoch time: 18.97 s +2024-11-22 19:00:52.727415: +2024-11-22 19:00:52.727629: Epoch 5925 +2024-11-22 19:00:52.727741: Current learning rate: 0.00297 +2024-11-22 19:01:12.510217: train_loss -0.8132 +2024-11-22 19:01:12.510464: val_loss -0.7616 +2024-11-22 19:01:12.510539: Pseudo dice [0.8307] +2024-11-22 19:01:12.510620: Epoch time: 19.78 s +2024-11-22 19:01:13.423224: +2024-11-22 19:01:13.423451: Epoch 5926 +2024-11-22 19:01:13.423576: Current learning rate: 0.00297 +2024-11-22 19:01:31.375567: train_loss -0.8105 +2024-11-22 19:01:31.375800: val_loss -0.7616 +2024-11-22 19:01:31.375880: Pseudo dice [0.8319] +2024-11-22 19:01:31.395521: Epoch time: 17.95 s +2024-11-22 19:01:32.298662: +2024-11-22 19:01:32.298913: Epoch 5927 +2024-11-22 19:01:32.299035: Current learning rate: 0.00297 +2024-11-22 19:01:51.101938: train_loss -0.809 +2024-11-22 19:01:51.102168: val_loss -0.7712 +2024-11-22 19:01:51.102242: Pseudo dice [0.8404] +2024-11-22 19:01:51.102323: Epoch time: 18.8 s +2024-11-22 19:01:52.029628: +2024-11-22 19:01:52.029822: Epoch 5928 +2024-11-22 19:01:52.029936: Current learning rate: 0.00296 +2024-11-22 19:02:10.198409: train_loss -0.8105 +2024-11-22 19:02:10.198635: val_loss -0.7708 +2024-11-22 19:02:10.198715: Pseudo dice [0.8351] +2024-11-22 19:02:10.198793: Epoch time: 18.17 s +2024-11-22 19:02:11.213437: +2024-11-22 19:02:11.213744: Epoch 5929 +2024-11-22 19:02:11.213863: Current learning rate: 0.00296 +2024-11-22 19:02:29.103862: train_loss -0.8125 +2024-11-22 19:02:29.106532: val_loss -0.7484 +2024-11-22 19:02:29.106656: Pseudo dice [0.8389] +2024-11-22 19:02:29.106742: Epoch time: 17.89 s +2024-11-22 19:02:30.055525: +2024-11-22 19:02:30.055749: Epoch 5930 +2024-11-22 19:02:30.055868: Current learning rate: 0.00296 +2024-11-22 19:02:49.803211: train_loss -0.8117 +2024-11-22 19:02:49.803812: val_loss -0.7607 +2024-11-22 19:02:49.803915: Pseudo dice [0.8213] +2024-11-22 19:02:49.803999: Epoch time: 19.74 s +2024-11-22 19:02:50.800180: +2024-11-22 19:02:50.800433: Epoch 5931 +2024-11-22 19:02:50.800552: Current learning rate: 0.00296 +2024-11-22 19:03:08.462263: train_loss -0.8096 +2024-11-22 19:03:08.462490: val_loss -0.756 +2024-11-22 19:03:08.462569: Pseudo dice [0.8302] +2024-11-22 19:03:08.462647: Epoch time: 17.66 s +2024-11-22 19:03:09.386498: +2024-11-22 19:03:09.386711: Epoch 5932 +2024-11-22 19:03:09.386825: Current learning rate: 0.00296 +2024-11-22 19:03:28.308203: train_loss -0.8179 +2024-11-22 19:03:28.308471: val_loss -0.7388 +2024-11-22 19:03:28.308548: Pseudo dice [0.833] +2024-11-22 19:03:28.308647: Epoch time: 18.92 s +2024-11-22 19:03:29.230437: +2024-11-22 19:03:29.230633: Epoch 5933 +2024-11-22 19:03:29.230744: Current learning rate: 0.00296 +2024-11-22 19:03:48.818680: train_loss -0.8107 +2024-11-22 19:03:48.818903: val_loss -0.7694 +2024-11-22 19:03:48.818979: Pseudo dice [0.8509] +2024-11-22 19:03:48.819062: Epoch time: 19.59 s +2024-11-22 19:03:49.763876: +2024-11-22 19:03:49.764169: Epoch 5934 +2024-11-22 19:03:49.764291: Current learning rate: 0.00296 +2024-11-22 19:04:09.062922: train_loss -0.8145 +2024-11-22 19:04:09.063145: val_loss -0.7523 +2024-11-22 19:04:09.068375: Pseudo dice [0.8447] +2024-11-22 19:04:09.068550: Epoch time: 19.3 s +2024-11-22 19:04:10.031828: +2024-11-22 19:04:10.032066: Epoch 5935 +2024-11-22 19:04:10.032183: Current learning rate: 0.00296 +2024-11-22 19:04:28.587291: train_loss -0.8022 +2024-11-22 19:04:28.591678: val_loss -0.7801 +2024-11-22 19:04:28.591816: Pseudo dice [0.8464] +2024-11-22 19:04:28.591899: Epoch time: 18.56 s +2024-11-22 19:04:29.520686: +2024-11-22 19:04:29.520881: Epoch 5936 +2024-11-22 19:04:29.520998: Current learning rate: 0.00295 +2024-11-22 19:04:47.133719: train_loss -0.7911 +2024-11-22 19:04:47.133932: val_loss -0.7505 +2024-11-22 19:04:47.134016: Pseudo dice [0.8465] +2024-11-22 19:04:47.134097: Epoch time: 17.61 s +2024-11-22 19:04:48.048273: +2024-11-22 19:04:48.048463: Epoch 5937 +2024-11-22 19:04:48.048577: Current learning rate: 0.00295 +2024-11-22 19:05:06.243648: train_loss -0.8064 +2024-11-22 19:05:06.243894: val_loss -0.7722 +2024-11-22 19:05:06.243971: Pseudo dice [0.8414] +2024-11-22 19:05:06.244061: Epoch time: 18.2 s +2024-11-22 19:05:07.155874: +2024-11-22 19:05:07.156103: Epoch 5938 +2024-11-22 19:05:07.156221: Current learning rate: 0.00295 +2024-11-22 19:05:26.415395: train_loss -0.8056 +2024-11-22 19:05:26.415596: val_loss -0.7398 +2024-11-22 19:05:26.415664: Pseudo dice [0.8084] +2024-11-22 19:05:26.415739: Epoch time: 19.26 s +2024-11-22 19:05:27.431929: +2024-11-22 19:05:27.432223: Epoch 5939 +2024-11-22 19:05:27.432339: Current learning rate: 0.00295 +2024-11-22 19:05:46.558727: train_loss -0.8038 +2024-11-22 19:05:46.560359: val_loss -0.7498 +2024-11-22 19:05:46.560486: Pseudo dice [0.8196] +2024-11-22 19:05:46.560572: Epoch time: 19.13 s +2024-11-22 19:05:47.516012: +2024-11-22 19:05:47.516209: Epoch 5940 +2024-11-22 19:05:47.516325: Current learning rate: 0.00295 +2024-11-22 19:06:06.649211: train_loss -0.8049 +2024-11-22 19:06:06.649470: val_loss -0.7679 +2024-11-22 19:06:06.649552: Pseudo dice [0.8294] +2024-11-22 19:06:06.649644: Epoch time: 19.13 s +2024-11-22 19:06:07.567645: +2024-11-22 19:06:07.567855: Epoch 5941 +2024-11-22 19:06:07.567967: Current learning rate: 0.00295 +2024-11-22 19:06:26.390653: train_loss -0.8079 +2024-11-22 19:06:26.390884: val_loss -0.7609 +2024-11-22 19:06:26.390966: Pseudo dice [0.8304] +2024-11-22 19:06:26.391052: Epoch time: 18.82 s +2024-11-22 19:06:27.699188: +2024-11-22 19:06:27.699399: Epoch 5942 +2024-11-22 19:06:27.699514: Current learning rate: 0.00295 +2024-11-22 19:06:46.722530: train_loss -0.8061 +2024-11-22 19:06:46.722755: val_loss -0.7408 +2024-11-22 19:06:46.725060: Pseudo dice [0.7981] +2024-11-22 19:06:46.725158: Epoch time: 19.02 s +2024-11-22 19:06:47.791124: +2024-11-22 19:06:47.791337: Epoch 5943 +2024-11-22 19:06:47.791450: Current learning rate: 0.00295 +2024-11-22 19:07:06.626243: train_loss -0.811 +2024-11-22 19:07:06.626464: val_loss -0.7575 +2024-11-22 19:07:06.626544: Pseudo dice [0.849] +2024-11-22 19:07:06.626620: Epoch time: 18.84 s +2024-11-22 19:07:07.638630: +2024-11-22 19:07:07.639001: Epoch 5944 +2024-11-22 19:07:07.639133: Current learning rate: 0.00294 +2024-11-22 19:07:27.340982: train_loss -0.8056 +2024-11-22 19:07:27.341252: val_loss -0.7532 +2024-11-22 19:07:27.341327: Pseudo dice [0.8389] +2024-11-22 19:07:27.341412: Epoch time: 19.7 s +2024-11-22 19:07:28.368310: +2024-11-22 19:07:28.368525: Epoch 5945 +2024-11-22 19:07:28.368638: Current learning rate: 0.00294 +2024-11-22 19:07:47.327400: train_loss -0.8001 +2024-11-22 19:07:47.327612: val_loss -0.7546 +2024-11-22 19:07:47.327686: Pseudo dice [0.8454] +2024-11-22 19:07:47.329932: Epoch time: 18.96 s +2024-11-22 19:07:48.270158: +2024-11-22 19:07:48.270350: Epoch 5946 +2024-11-22 19:07:48.270460: Current learning rate: 0.00294 +2024-11-22 19:08:06.919294: train_loss -0.8084 +2024-11-22 19:08:06.919522: val_loss -0.777 +2024-11-22 19:08:06.919598: Pseudo dice [0.842] +2024-11-22 19:08:06.922219: Epoch time: 18.65 s +2024-11-22 19:08:07.838928: +2024-11-22 19:08:07.839135: Epoch 5947 +2024-11-22 19:08:07.839250: Current learning rate: 0.00294 +2024-11-22 19:08:25.685879: train_loss -0.8101 +2024-11-22 19:08:25.686130: val_loss -0.7748 +2024-11-22 19:08:25.686207: Pseudo dice [0.8425] +2024-11-22 19:08:25.686291: Epoch time: 17.85 s +2024-11-22 19:08:26.598498: +2024-11-22 19:08:26.598796: Epoch 5948 +2024-11-22 19:08:26.598923: Current learning rate: 0.00294 +2024-11-22 19:08:45.641687: train_loss -0.8062 +2024-11-22 19:08:45.641936: val_loss -0.7492 +2024-11-22 19:08:45.642019: Pseudo dice [0.843] +2024-11-22 19:08:45.642101: Epoch time: 19.04 s +2024-11-22 19:08:46.555468: +2024-11-22 19:08:46.555659: Epoch 5949 +2024-11-22 19:08:46.555771: Current learning rate: 0.00294 +2024-11-22 19:09:06.035628: train_loss -0.8056 +2024-11-22 19:09:06.035842: val_loss -0.7354 +2024-11-22 19:09:06.035920: Pseudo dice [0.8397] +2024-11-22 19:09:06.036006: Epoch time: 19.48 s +2024-11-22 19:09:07.236615: +2024-11-22 19:09:07.236839: Epoch 5950 +2024-11-22 19:09:07.236959: Current learning rate: 0.00294 +2024-11-22 19:09:25.956896: train_loss -0.8098 +2024-11-22 19:09:25.957124: val_loss -0.737 +2024-11-22 19:09:25.957197: Pseudo dice [0.8308] +2024-11-22 19:09:25.957275: Epoch time: 18.72 s +2024-11-22 19:09:26.867923: +2024-11-22 19:09:26.868133: Epoch 5951 +2024-11-22 19:09:26.868244: Current learning rate: 0.00293 +2024-11-22 19:09:44.598942: train_loss -0.8142 +2024-11-22 19:09:44.601352: val_loss -0.7699 +2024-11-22 19:09:44.601462: Pseudo dice [0.8176] +2024-11-22 19:09:44.601549: Epoch time: 17.73 s +2024-11-22 19:09:45.649137: +2024-11-22 19:09:45.649333: Epoch 5952 +2024-11-22 19:09:45.649446: Current learning rate: 0.00293 +2024-11-22 19:10:04.673390: train_loss -0.8181 +2024-11-22 19:10:04.673634: val_loss -0.7474 +2024-11-22 19:10:04.673707: Pseudo dice [0.8357] +2024-11-22 19:10:04.673787: Epoch time: 19.03 s +2024-11-22 19:10:05.594219: +2024-11-22 19:10:05.594423: Epoch 5953 +2024-11-22 19:10:05.594534: Current learning rate: 0.00293 +2024-11-22 19:10:25.351454: train_loss -0.8159 +2024-11-22 19:10:25.351953: val_loss -0.7321 +2024-11-22 19:10:25.352059: Pseudo dice [0.8368] +2024-11-22 19:10:25.352134: Epoch time: 19.76 s +2024-11-22 19:10:26.322729: +2024-11-22 19:10:26.322968: Epoch 5954 +2024-11-22 19:10:26.323085: Current learning rate: 0.00293 +2024-11-22 19:10:46.194172: train_loss -0.8122 +2024-11-22 19:10:46.194463: val_loss -0.7609 +2024-11-22 19:10:46.194558: Pseudo dice [0.8378] +2024-11-22 19:10:46.194641: Epoch time: 19.87 s +2024-11-22 19:10:47.106858: +2024-11-22 19:10:47.107120: Epoch 5955 +2024-11-22 19:10:47.107232: Current learning rate: 0.00293 +2024-11-22 19:11:06.182869: train_loss -0.8011 +2024-11-22 19:11:06.183097: val_loss -0.7569 +2024-11-22 19:11:06.183171: Pseudo dice [0.8399] +2024-11-22 19:11:06.183246: Epoch time: 19.08 s +2024-11-22 19:11:07.094750: +2024-11-22 19:11:07.094965: Epoch 5956 +2024-11-22 19:11:07.095081: Current learning rate: 0.00293 +2024-11-22 19:11:25.690911: train_loss -0.802 +2024-11-22 19:11:25.691160: val_loss -0.724 +2024-11-22 19:11:25.691236: Pseudo dice [0.8332] +2024-11-22 19:11:25.691322: Epoch time: 18.6 s +2024-11-22 19:11:26.606925: +2024-11-22 19:11:26.607130: Epoch 5957 +2024-11-22 19:11:26.607242: Current learning rate: 0.00293 +2024-11-22 19:11:45.100612: train_loss -0.813 +2024-11-22 19:11:45.100825: val_loss -0.7747 +2024-11-22 19:11:45.100902: Pseudo dice [0.8442] +2024-11-22 19:11:45.100977: Epoch time: 18.49 s +2024-11-22 19:11:46.005534: +2024-11-22 19:11:46.005843: Epoch 5958 +2024-11-22 19:11:46.005960: Current learning rate: 0.00293 +2024-11-22 19:12:03.866480: train_loss -0.8105 +2024-11-22 19:12:03.866737: val_loss -0.7431 +2024-11-22 19:12:03.866814: Pseudo dice [0.8274] +2024-11-22 19:12:03.866891: Epoch time: 17.86 s +2024-11-22 19:12:04.781612: +2024-11-22 19:12:04.781818: Epoch 5959 +2024-11-22 19:12:04.781930: Current learning rate: 0.00292 +2024-11-22 19:12:22.839456: train_loss -0.8125 +2024-11-22 19:12:22.839743: val_loss -0.7304 +2024-11-22 19:12:22.839818: Pseudo dice [0.8162] +2024-11-22 19:12:22.839896: Epoch time: 18.06 s +2024-11-22 19:12:23.751137: +2024-11-22 19:12:23.751338: Epoch 5960 +2024-11-22 19:12:23.751451: Current learning rate: 0.00292 +2024-11-22 19:12:42.264294: train_loss -0.815 +2024-11-22 19:12:42.264544: val_loss -0.7437 +2024-11-22 19:12:42.264617: Pseudo dice [0.8424] +2024-11-22 19:12:42.264697: Epoch time: 18.51 s +2024-11-22 19:12:43.271813: +2024-11-22 19:12:43.272009: Epoch 5961 +2024-11-22 19:12:43.272122: Current learning rate: 0.00292 +2024-11-22 19:13:01.396276: train_loss -0.8091 +2024-11-22 19:13:01.396517: val_loss -0.7369 +2024-11-22 19:13:01.396595: Pseudo dice [0.8231] +2024-11-22 19:13:01.396672: Epoch time: 18.13 s +2024-11-22 19:13:02.339375: +2024-11-22 19:13:02.339585: Epoch 5962 +2024-11-22 19:13:02.339700: Current learning rate: 0.00292 +2024-11-22 19:13:20.914425: train_loss -0.8137 +2024-11-22 19:13:20.914647: val_loss -0.7473 +2024-11-22 19:13:20.914721: Pseudo dice [0.8246] +2024-11-22 19:13:20.914798: Epoch time: 18.58 s +2024-11-22 19:13:21.853770: +2024-11-22 19:13:21.853981: Epoch 5963 +2024-11-22 19:13:21.854097: Current learning rate: 0.00292 +2024-11-22 19:13:40.172170: train_loss -0.8118 +2024-11-22 19:13:40.172395: val_loss -0.7585 +2024-11-22 19:13:40.172471: Pseudo dice [0.8265] +2024-11-22 19:13:40.172549: Epoch time: 18.32 s +2024-11-22 19:13:41.082803: +2024-11-22 19:13:41.083018: Epoch 5964 +2024-11-22 19:13:41.083129: Current learning rate: 0.00292 +2024-11-22 19:13:59.908506: train_loss -0.8182 +2024-11-22 19:13:59.908763: val_loss -0.7684 +2024-11-22 19:13:59.908890: Pseudo dice [0.8233] +2024-11-22 19:13:59.908973: Epoch time: 18.83 s +2024-11-22 19:14:01.231908: +2024-11-22 19:14:01.232116: Epoch 5965 +2024-11-22 19:14:01.232229: Current learning rate: 0.00292 +2024-11-22 19:14:19.624815: train_loss -0.8091 +2024-11-22 19:14:19.625080: val_loss -0.7665 +2024-11-22 19:14:19.625160: Pseudo dice [0.8232] +2024-11-22 19:14:19.625237: Epoch time: 18.39 s +2024-11-22 19:14:20.559377: +2024-11-22 19:14:20.559652: Epoch 5966 +2024-11-22 19:14:20.559765: Current learning rate: 0.00292 +2024-11-22 19:14:39.015395: train_loss -0.8033 +2024-11-22 19:14:39.015626: val_loss -0.7661 +2024-11-22 19:14:39.015706: Pseudo dice [0.8388] +2024-11-22 19:14:39.015781: Epoch time: 18.46 s +2024-11-22 19:14:39.920478: +2024-11-22 19:14:39.920704: Epoch 5967 +2024-11-22 19:14:39.920817: Current learning rate: 0.00291 +2024-11-22 19:14:59.482679: train_loss -0.8108 +2024-11-22 19:14:59.482925: val_loss -0.7734 +2024-11-22 19:14:59.483008: Pseudo dice [0.8143] +2024-11-22 19:14:59.483091: Epoch time: 19.56 s +2024-11-22 19:15:00.392826: +2024-11-22 19:15:00.393079: Epoch 5968 +2024-11-22 19:15:00.393190: Current learning rate: 0.00291 +2024-11-22 19:15:18.418009: train_loss -0.8104 +2024-11-22 19:15:18.418223: val_loss -0.7585 +2024-11-22 19:15:18.418298: Pseudo dice [0.8481] +2024-11-22 19:15:18.418374: Epoch time: 18.03 s +2024-11-22 19:15:19.334404: +2024-11-22 19:15:19.334605: Epoch 5969 +2024-11-22 19:15:19.334715: Current learning rate: 0.00291 +2024-11-22 19:15:38.103873: train_loss -0.8118 +2024-11-22 19:15:38.104106: val_loss -0.7157 +2024-11-22 19:15:38.104230: Pseudo dice [0.8221] +2024-11-22 19:15:38.104311: Epoch time: 18.77 s +2024-11-22 19:15:39.013420: +2024-11-22 19:15:39.013719: Epoch 5970 +2024-11-22 19:15:39.013842: Current learning rate: 0.00291 +2024-11-22 19:15:57.842065: train_loss -0.8135 +2024-11-22 19:15:57.842284: val_loss -0.743 +2024-11-22 19:15:57.842360: Pseudo dice [0.8171] +2024-11-22 19:15:57.842434: Epoch time: 18.83 s +2024-11-22 19:15:58.761369: +2024-11-22 19:15:58.761607: Epoch 5971 +2024-11-22 19:15:58.761728: Current learning rate: 0.00291 +2024-11-22 19:16:17.048969: train_loss -0.8041 +2024-11-22 19:16:17.049263: val_loss -0.7594 +2024-11-22 19:16:17.049338: Pseudo dice [0.8253] +2024-11-22 19:16:17.049421: Epoch time: 18.29 s +2024-11-22 19:16:18.064988: +2024-11-22 19:16:18.065191: Epoch 5972 +2024-11-22 19:16:18.065306: Current learning rate: 0.00291 +2024-11-22 19:16:37.737158: train_loss -0.8084 +2024-11-22 19:16:37.737377: val_loss -0.7475 +2024-11-22 19:16:37.737452: Pseudo dice [0.821] +2024-11-22 19:16:37.737531: Epoch time: 19.67 s +2024-11-22 19:16:38.650160: +2024-11-22 19:16:38.650364: Epoch 5973 +2024-11-22 19:16:38.650475: Current learning rate: 0.00291 +2024-11-22 19:16:58.279453: train_loss -0.7947 +2024-11-22 19:16:58.279680: val_loss -0.7335 +2024-11-22 19:16:58.279757: Pseudo dice [0.8353] +2024-11-22 19:16:58.279837: Epoch time: 19.63 s +2024-11-22 19:16:59.186468: +2024-11-22 19:16:59.186684: Epoch 5974 +2024-11-22 19:16:59.186802: Current learning rate: 0.00291 +2024-11-22 19:17:17.155751: train_loss -0.8109 +2024-11-22 19:17:17.156013: val_loss -0.7573 +2024-11-22 19:17:17.156090: Pseudo dice [0.8433] +2024-11-22 19:17:17.156175: Epoch time: 17.97 s +2024-11-22 19:17:18.127102: +2024-11-22 19:17:18.127330: Epoch 5975 +2024-11-22 19:17:18.127447: Current learning rate: 0.0029 +2024-11-22 19:17:37.968015: train_loss -0.808 +2024-11-22 19:17:37.968230: val_loss -0.767 +2024-11-22 19:17:37.968307: Pseudo dice [0.8556] +2024-11-22 19:17:37.968382: Epoch time: 19.84 s +2024-11-22 19:17:38.878343: +2024-11-22 19:17:38.878630: Epoch 5976 +2024-11-22 19:17:38.878747: Current learning rate: 0.0029 +2024-11-22 19:17:57.871925: train_loss -0.8044 +2024-11-22 19:17:57.872428: val_loss -0.7428 +2024-11-22 19:17:57.872527: Pseudo dice [0.8233] +2024-11-22 19:17:57.872607: Epoch time: 18.99 s +2024-11-22 19:17:58.791982: +2024-11-22 19:17:58.792205: Epoch 5977 +2024-11-22 19:17:58.792321: Current learning rate: 0.0029 +2024-11-22 19:18:18.865382: train_loss -0.7978 +2024-11-22 19:18:18.865591: val_loss -0.7537 +2024-11-22 19:18:18.865669: Pseudo dice [0.8407] +2024-11-22 19:18:18.865749: Epoch time: 20.07 s +2024-11-22 19:18:19.772316: +2024-11-22 19:18:19.772532: Epoch 5978 +2024-11-22 19:18:19.772646: Current learning rate: 0.0029 +2024-11-22 19:18:38.171652: train_loss -0.7924 +2024-11-22 19:18:38.171889: val_loss -0.7585 +2024-11-22 19:18:38.171967: Pseudo dice [0.8179] +2024-11-22 19:18:38.172051: Epoch time: 18.4 s +2024-11-22 19:18:39.138381: +2024-11-22 19:18:39.138601: Epoch 5979 +2024-11-22 19:18:39.138713: Current learning rate: 0.0029 +2024-11-22 19:18:58.036160: train_loss -0.802 +2024-11-22 19:18:58.036441: val_loss -0.7537 +2024-11-22 19:18:58.036510: Pseudo dice [0.8405] +2024-11-22 19:18:58.036589: Epoch time: 18.9 s +2024-11-22 19:18:58.957108: +2024-11-22 19:18:58.957321: Epoch 5980 +2024-11-22 19:18:58.957435: Current learning rate: 0.0029 +2024-11-22 19:19:17.698730: train_loss -0.7945 +2024-11-22 19:19:17.698948: val_loss -0.7681 +2024-11-22 19:19:17.699029: Pseudo dice [0.8406] +2024-11-22 19:19:17.699106: Epoch time: 18.74 s +2024-11-22 19:19:18.610217: +2024-11-22 19:19:18.610435: Epoch 5981 +2024-11-22 19:19:18.610551: Current learning rate: 0.0029 +2024-11-22 19:19:37.489711: train_loss -0.7782 +2024-11-22 19:19:37.489935: val_loss -0.726 +2024-11-22 19:19:37.490019: Pseudo dice [0.8217] +2024-11-22 19:19:37.490096: Epoch time: 18.88 s +2024-11-22 19:19:38.400402: +2024-11-22 19:19:38.400641: Epoch 5982 +2024-11-22 19:19:38.400765: Current learning rate: 0.00289 +2024-11-22 19:19:56.612771: train_loss -0.7918 +2024-11-22 19:19:56.617005: val_loss -0.7543 +2024-11-22 19:19:56.617152: Pseudo dice [0.8253] +2024-11-22 19:19:56.617241: Epoch time: 18.21 s +2024-11-22 19:19:57.539596: +2024-11-22 19:19:57.539812: Epoch 5983 +2024-11-22 19:19:57.539926: Current learning rate: 0.00289 +2024-11-22 19:20:16.662258: train_loss -0.7969 +2024-11-22 19:20:16.667674: val_loss -0.7273 +2024-11-22 19:20:16.667792: Pseudo dice [0.8271] +2024-11-22 19:20:16.667874: Epoch time: 19.12 s +2024-11-22 19:20:17.590981: +2024-11-22 19:20:17.591184: Epoch 5984 +2024-11-22 19:20:17.591310: Current learning rate: 0.00289 +2024-11-22 19:20:36.289660: train_loss -0.7911 +2024-11-22 19:20:36.289876: val_loss -0.7444 +2024-11-22 19:20:36.289953: Pseudo dice [0.8097] +2024-11-22 19:20:36.290034: Epoch time: 18.7 s +2024-11-22 19:20:37.199083: +2024-11-22 19:20:37.199301: Epoch 5985 +2024-11-22 19:20:37.199412: Current learning rate: 0.00289 +2024-11-22 19:20:55.139514: train_loss -0.799 +2024-11-22 19:20:55.139733: val_loss -0.7382 +2024-11-22 19:20:55.139808: Pseudo dice [0.8281] +2024-11-22 19:20:55.139888: Epoch time: 17.94 s +2024-11-22 19:20:56.194134: +2024-11-22 19:20:56.194362: Epoch 5986 +2024-11-22 19:20:56.194485: Current learning rate: 0.00289 +2024-11-22 19:21:14.539136: train_loss -0.807 +2024-11-22 19:21:14.539385: val_loss -0.7574 +2024-11-22 19:21:14.539464: Pseudo dice [0.8483] +2024-11-22 19:21:14.539552: Epoch time: 18.35 s +2024-11-22 19:21:15.594761: +2024-11-22 19:21:15.594951: Epoch 5987 +2024-11-22 19:21:15.595067: Current learning rate: 0.00289 +2024-11-22 19:21:34.322569: train_loss -0.8113 +2024-11-22 19:21:34.322832: val_loss -0.7543 +2024-11-22 19:21:34.322907: Pseudo dice [0.8357] +2024-11-22 19:21:34.322984: Epoch time: 18.73 s +2024-11-22 19:21:35.639886: +2024-11-22 19:21:35.640123: Epoch 5988 +2024-11-22 19:21:35.640230: Current learning rate: 0.00289 +2024-11-22 19:21:54.792703: train_loss -0.8123 +2024-11-22 19:21:54.792926: val_loss -0.7538 +2024-11-22 19:21:54.793028: Pseudo dice [0.8466] +2024-11-22 19:21:54.793106: Epoch time: 19.15 s +2024-11-22 19:21:55.705070: +2024-11-22 19:21:55.705285: Epoch 5989 +2024-11-22 19:21:55.705396: Current learning rate: 0.00289 +2024-11-22 19:22:14.121591: train_loss -0.806 +2024-11-22 19:22:14.121892: val_loss -0.7541 +2024-11-22 19:22:14.121973: Pseudo dice [0.8257] +2024-11-22 19:22:14.122065: Epoch time: 18.42 s +2024-11-22 19:22:15.036311: +2024-11-22 19:22:15.036525: Epoch 5990 +2024-11-22 19:22:15.036637: Current learning rate: 0.00288 +2024-11-22 19:22:35.134810: train_loss -0.81 +2024-11-22 19:22:35.135032: val_loss -0.7647 +2024-11-22 19:22:35.135103: Pseudo dice [0.8398] +2024-11-22 19:22:35.135173: Epoch time: 20.1 s +2024-11-22 19:22:36.077468: +2024-11-22 19:22:36.077659: Epoch 5991 +2024-11-22 19:22:36.077770: Current learning rate: 0.00288 +2024-11-22 19:22:54.843978: train_loss -0.8052 +2024-11-22 19:22:54.844199: val_loss -0.7617 +2024-11-22 19:22:54.844275: Pseudo dice [0.8378] +2024-11-22 19:22:54.844348: Epoch time: 18.77 s +2024-11-22 19:22:55.889714: +2024-11-22 19:22:55.889899: Epoch 5992 +2024-11-22 19:22:55.890013: Current learning rate: 0.00288 +2024-11-22 19:23:15.108071: train_loss -0.8048 +2024-11-22 19:23:15.108296: val_loss -0.7264 +2024-11-22 19:23:15.108372: Pseudo dice [0.8153] +2024-11-22 19:23:15.108447: Epoch time: 19.22 s +2024-11-22 19:23:16.189236: +2024-11-22 19:23:16.189432: Epoch 5993 +2024-11-22 19:23:16.189543: Current learning rate: 0.00288 +2024-11-22 19:23:34.383995: train_loss -0.8034 +2024-11-22 19:23:34.384244: val_loss -0.7871 +2024-11-22 19:23:34.384318: Pseudo dice [0.8367] +2024-11-22 19:23:34.384403: Epoch time: 18.2 s +2024-11-22 19:23:35.294627: +2024-11-22 19:23:35.294875: Epoch 5994 +2024-11-22 19:23:35.294996: Current learning rate: 0.00288 +2024-11-22 19:23:55.471735: train_loss -0.8034 +2024-11-22 19:23:55.471974: val_loss -0.7441 +2024-11-22 19:23:55.472060: Pseudo dice [0.8255] +2024-11-22 19:23:55.472142: Epoch time: 20.17 s +2024-11-22 19:23:56.599415: +2024-11-22 19:23:56.599607: Epoch 5995 +2024-11-22 19:23:56.599721: Current learning rate: 0.00288 +2024-11-22 19:24:14.641893: train_loss -0.8112 +2024-11-22 19:24:14.642107: val_loss -0.7386 +2024-11-22 19:24:14.642179: Pseudo dice [0.8385] +2024-11-22 19:24:14.642258: Epoch time: 18.04 s +2024-11-22 19:24:15.657203: +2024-11-22 19:24:15.657446: Epoch 5996 +2024-11-22 19:24:15.657558: Current learning rate: 0.00288 +2024-11-22 19:24:33.660332: train_loss -0.8024 +2024-11-22 19:24:33.660551: val_loss -0.7449 +2024-11-22 19:24:33.660634: Pseudo dice [0.8456] +2024-11-22 19:24:33.660709: Epoch time: 18.0 s +2024-11-22 19:24:34.597255: +2024-11-22 19:24:34.597444: Epoch 5997 +2024-11-22 19:24:34.597578: Current learning rate: 0.00288 +2024-11-22 19:24:54.017148: train_loss -0.797 +2024-11-22 19:24:54.017405: val_loss -0.7294 +2024-11-22 19:24:54.017480: Pseudo dice [0.8306] +2024-11-22 19:24:54.017578: Epoch time: 19.42 s +2024-11-22 19:24:54.931843: +2024-11-22 19:24:54.932074: Epoch 5998 +2024-11-22 19:24:54.932191: Current learning rate: 0.00287 +2024-11-22 19:25:13.832494: train_loss -0.7897 +2024-11-22 19:25:13.832711: val_loss -0.7568 +2024-11-22 19:25:13.832786: Pseudo dice [0.8337] +2024-11-22 19:25:13.832862: Epoch time: 18.9 s +2024-11-22 19:25:14.742099: +2024-11-22 19:25:14.742324: Epoch 5999 +2024-11-22 19:25:14.742440: Current learning rate: 0.00287 +2024-11-22 19:25:33.293492: train_loss -0.8033 +2024-11-22 19:25:33.294000: val_loss -0.7484 +2024-11-22 19:25:33.294101: Pseudo dice [0.8194] +2024-11-22 19:25:33.294182: Epoch time: 18.55 s +2024-11-22 19:25:34.533530: +2024-11-22 19:25:34.533757: Epoch 6000 +2024-11-22 19:25:34.533872: Current learning rate: 0.00287 +2024-11-22 19:25:52.810660: train_loss -0.798 +2024-11-22 19:25:52.810874: val_loss -0.7533 +2024-11-22 19:25:52.810948: Pseudo dice [0.835] +2024-11-22 19:25:52.811031: Epoch time: 18.28 s +2024-11-22 19:25:53.719692: +2024-11-22 19:25:53.719918: Epoch 6001 +2024-11-22 19:25:53.720036: Current learning rate: 0.00287 +2024-11-22 19:26:12.122268: train_loss -0.8061 +2024-11-22 19:26:12.122515: val_loss -0.7583 +2024-11-22 19:26:12.122590: Pseudo dice [0.8381] +2024-11-22 19:26:12.122672: Epoch time: 18.4 s +2024-11-22 19:26:13.029458: +2024-11-22 19:26:13.029690: Epoch 6002 +2024-11-22 19:26:13.029804: Current learning rate: 0.00287 +2024-11-22 19:26:32.198227: train_loss -0.8054 +2024-11-22 19:26:32.198460: val_loss -0.7477 +2024-11-22 19:26:32.198538: Pseudo dice [0.8344] +2024-11-22 19:26:32.198616: Epoch time: 19.17 s +2024-11-22 19:26:33.121825: +2024-11-22 19:26:33.122051: Epoch 6003 +2024-11-22 19:26:33.122172: Current learning rate: 0.00287 +2024-11-22 19:26:53.562352: train_loss -0.8063 +2024-11-22 19:26:53.562574: val_loss -0.7731 +2024-11-22 19:26:53.562654: Pseudo dice [0.8399] +2024-11-22 19:26:53.562734: Epoch time: 20.44 s +2024-11-22 19:26:54.476035: +2024-11-22 19:26:54.476291: Epoch 6004 +2024-11-22 19:26:54.476409: Current learning rate: 0.00287 +2024-11-22 19:27:12.297932: train_loss -0.8102 +2024-11-22 19:27:12.298179: val_loss -0.7554 +2024-11-22 19:27:12.298256: Pseudo dice [0.8499] +2024-11-22 19:27:12.298339: Epoch time: 17.82 s +2024-11-22 19:27:13.226073: +2024-11-22 19:27:13.226338: Epoch 6005 +2024-11-22 19:27:13.226453: Current learning rate: 0.00287 +2024-11-22 19:27:32.204073: train_loss -0.8127 +2024-11-22 19:27:32.204317: val_loss -0.7494 +2024-11-22 19:27:32.204390: Pseudo dice [0.8217] +2024-11-22 19:27:32.204471: Epoch time: 18.98 s +2024-11-22 19:27:33.117411: +2024-11-22 19:27:33.117622: Epoch 6006 +2024-11-22 19:27:33.117739: Current learning rate: 0.00286 +2024-11-22 19:27:51.752755: train_loss -0.8099 +2024-11-22 19:27:51.752973: val_loss -0.7633 +2024-11-22 19:27:51.753055: Pseudo dice [0.838] +2024-11-22 19:27:51.753150: Epoch time: 18.64 s +2024-11-22 19:27:52.662562: +2024-11-22 19:27:52.662812: Epoch 6007 +2024-11-22 19:27:52.662931: Current learning rate: 0.00286 +2024-11-22 19:28:10.025423: train_loss -0.8121 +2024-11-22 19:28:10.025645: val_loss -0.7745 +2024-11-22 19:28:10.025719: Pseudo dice [0.8426] +2024-11-22 19:28:10.025795: Epoch time: 17.36 s +2024-11-22 19:28:10.972739: +2024-11-22 19:28:10.973027: Epoch 6008 +2024-11-22 19:28:10.973140: Current learning rate: 0.00286 +2024-11-22 19:28:30.891129: train_loss -0.8126 +2024-11-22 19:28:30.891355: val_loss -0.7335 +2024-11-22 19:28:30.891429: Pseudo dice [0.8387] +2024-11-22 19:28:30.896694: Epoch time: 19.92 s +2024-11-22 19:28:31.992204: +2024-11-22 19:28:31.992429: Epoch 6009 +2024-11-22 19:28:31.992544: Current learning rate: 0.00286 +2024-11-22 19:28:50.817634: train_loss -0.8135 +2024-11-22 19:28:50.817947: val_loss -0.7546 +2024-11-22 19:28:50.818032: Pseudo dice [0.8303] +2024-11-22 19:28:50.818120: Epoch time: 18.83 s +2024-11-22 19:28:51.725331: +2024-11-22 19:28:51.725525: Epoch 6010 +2024-11-22 19:28:51.725637: Current learning rate: 0.00286 +2024-11-22 19:29:11.569725: train_loss -0.7996 +2024-11-22 19:29:11.570213: val_loss -0.7614 +2024-11-22 19:29:11.570308: Pseudo dice [0.8477] +2024-11-22 19:29:11.570386: Epoch time: 19.85 s +2024-11-22 19:29:12.481928: +2024-11-22 19:29:12.482144: Epoch 6011 +2024-11-22 19:29:12.482260: Current learning rate: 0.00286 +2024-11-22 19:29:31.636092: train_loss -0.8025 +2024-11-22 19:29:31.636316: val_loss -0.7514 +2024-11-22 19:29:31.636392: Pseudo dice [0.8096] +2024-11-22 19:29:31.636469: Epoch time: 19.15 s +2024-11-22 19:29:32.594570: +2024-11-22 19:29:32.594809: Epoch 6012 +2024-11-22 19:29:32.594927: Current learning rate: 0.00286 +2024-11-22 19:29:50.547539: train_loss -0.8089 +2024-11-22 19:29:50.547831: val_loss -0.7515 +2024-11-22 19:29:50.547912: Pseudo dice [0.8442] +2024-11-22 19:29:50.548014: Epoch time: 17.95 s +2024-11-22 19:29:51.466931: +2024-11-22 19:29:51.467173: Epoch 6013 +2024-11-22 19:29:51.467285: Current learning rate: 0.00285 +2024-11-22 19:30:09.610190: train_loss -0.8124 +2024-11-22 19:30:09.610403: val_loss -0.7437 +2024-11-22 19:30:09.610478: Pseudo dice [0.8251] +2024-11-22 19:30:09.610557: Epoch time: 18.14 s +2024-11-22 19:30:10.609045: +2024-11-22 19:30:10.609237: Epoch 6014 +2024-11-22 19:30:10.609356: Current learning rate: 0.00285 +2024-11-22 19:30:28.722314: train_loss -0.8094 +2024-11-22 19:30:28.722615: val_loss -0.7521 +2024-11-22 19:30:28.722695: Pseudo dice [0.8303] +2024-11-22 19:30:28.722824: Epoch time: 18.11 s +2024-11-22 19:30:29.629792: +2024-11-22 19:30:29.630006: Epoch 6015 +2024-11-22 19:30:29.630119: Current learning rate: 0.00285 +2024-11-22 19:30:48.542460: train_loss -0.8053 +2024-11-22 19:30:48.542685: val_loss -0.7543 +2024-11-22 19:30:48.542770: Pseudo dice [0.8189] +2024-11-22 19:30:48.542856: Epoch time: 18.91 s +2024-11-22 19:30:49.457613: +2024-11-22 19:30:49.457812: Epoch 6016 +2024-11-22 19:30:49.457946: Current learning rate: 0.00285 +2024-11-22 19:31:08.947525: train_loss -0.8072 +2024-11-22 19:31:08.947767: val_loss -0.7266 +2024-11-22 19:31:08.947841: Pseudo dice [0.8277] +2024-11-22 19:31:08.947923: Epoch time: 19.49 s +2024-11-22 19:31:09.861627: +2024-11-22 19:31:09.861817: Epoch 6017 +2024-11-22 19:31:09.861928: Current learning rate: 0.00285 +2024-11-22 19:31:28.054893: train_loss -0.8037 +2024-11-22 19:31:28.055141: val_loss -0.754 +2024-11-22 19:31:28.055219: Pseudo dice [0.8367] +2024-11-22 19:31:28.055299: Epoch time: 18.19 s +2024-11-22 19:31:28.962263: +2024-11-22 19:31:28.962505: Epoch 6018 +2024-11-22 19:31:28.962629: Current learning rate: 0.00285 +2024-11-22 19:31:47.229267: train_loss -0.8068 +2024-11-22 19:31:47.229485: val_loss -0.7505 +2024-11-22 19:31:47.229571: Pseudo dice [0.8183] +2024-11-22 19:31:47.229655: Epoch time: 18.27 s +2024-11-22 19:31:48.133641: +2024-11-22 19:31:48.133834: Epoch 6019 +2024-11-22 19:31:48.133949: Current learning rate: 0.00285 +2024-11-22 19:32:06.414761: train_loss -0.8024 +2024-11-22 19:32:06.414983: val_loss -0.7604 +2024-11-22 19:32:06.415070: Pseudo dice [0.8499] +2024-11-22 19:32:06.415151: Epoch time: 18.28 s +2024-11-22 19:32:07.329164: +2024-11-22 19:32:07.329385: Epoch 6020 +2024-11-22 19:32:07.329503: Current learning rate: 0.00285 +2024-11-22 19:32:25.478587: train_loss -0.8045 +2024-11-22 19:32:25.478834: val_loss -0.7691 +2024-11-22 19:32:25.478914: Pseudo dice [0.8267] +2024-11-22 19:32:25.479006: Epoch time: 18.15 s +2024-11-22 19:32:26.393375: +2024-11-22 19:32:26.393574: Epoch 6021 +2024-11-22 19:32:26.393693: Current learning rate: 0.00284 +2024-11-22 19:32:45.725734: train_loss -0.808 +2024-11-22 19:32:45.725953: val_loss -0.7287 +2024-11-22 19:32:45.726056: Pseudo dice [0.8123] +2024-11-22 19:32:45.726131: Epoch time: 19.33 s +2024-11-22 19:32:47.027767: +2024-11-22 19:32:47.027971: Epoch 6022 +2024-11-22 19:32:47.028188: Current learning rate: 0.00284 +2024-11-22 19:33:05.635775: train_loss -0.8039 +2024-11-22 19:33:05.636022: val_loss -0.7393 +2024-11-22 19:33:05.636098: Pseudo dice [0.8317] +2024-11-22 19:33:05.636202: Epoch time: 18.61 s +2024-11-22 19:33:06.560188: +2024-11-22 19:33:06.560452: Epoch 6023 +2024-11-22 19:33:06.560563: Current learning rate: 0.00284 +2024-11-22 19:33:24.773298: train_loss -0.8032 +2024-11-22 19:33:24.773515: val_loss -0.7645 +2024-11-22 19:33:24.773586: Pseudo dice [0.8387] +2024-11-22 19:33:24.773664: Epoch time: 18.21 s +2024-11-22 19:33:25.810151: +2024-11-22 19:33:25.810439: Epoch 6024 +2024-11-22 19:33:25.810609: Current learning rate: 0.00284 +2024-11-22 19:33:45.172700: train_loss -0.8059 +2024-11-22 19:33:45.172940: val_loss -0.7589 +2024-11-22 19:33:45.173025: Pseudo dice [0.8516] +2024-11-22 19:33:45.173109: Epoch time: 19.36 s +2024-11-22 19:33:46.100832: +2024-11-22 19:33:46.101074: Epoch 6025 +2024-11-22 19:33:46.101192: Current learning rate: 0.00284 +2024-11-22 19:34:04.832170: train_loss -0.8082 +2024-11-22 19:34:04.832384: val_loss -0.756 +2024-11-22 19:34:04.832458: Pseudo dice [0.8202] +2024-11-22 19:34:04.832534: Epoch time: 18.73 s +2024-11-22 19:34:05.738533: +2024-11-22 19:34:05.738758: Epoch 6026 +2024-11-22 19:34:05.738875: Current learning rate: 0.00284 +2024-11-22 19:34:26.004984: train_loss -0.7977 +2024-11-22 19:34:26.005210: val_loss -0.7314 +2024-11-22 19:34:26.005285: Pseudo dice [0.8286] +2024-11-22 19:34:26.005360: Epoch time: 20.27 s +2024-11-22 19:34:26.919195: +2024-11-22 19:34:26.919392: Epoch 6027 +2024-11-22 19:34:26.919506: Current learning rate: 0.00284 +2024-11-22 19:34:45.769503: train_loss -0.8012 +2024-11-22 19:34:45.769730: val_loss -0.7599 +2024-11-22 19:34:45.769809: Pseudo dice [0.8423] +2024-11-22 19:34:45.769890: Epoch time: 18.85 s +2024-11-22 19:34:46.678282: +2024-11-22 19:34:46.678497: Epoch 6028 +2024-11-22 19:34:46.678615: Current learning rate: 0.00284 +2024-11-22 19:35:04.920477: train_loss -0.8083 +2024-11-22 19:35:04.923489: val_loss -0.7683 +2024-11-22 19:35:04.923610: Pseudo dice [0.8362] +2024-11-22 19:35:04.923696: Epoch time: 18.24 s +2024-11-22 19:35:05.958317: +2024-11-22 19:35:05.958512: Epoch 6029 +2024-11-22 19:35:05.958630: Current learning rate: 0.00283 +2024-11-22 19:35:25.521473: train_loss -0.8054 +2024-11-22 19:35:25.521698: val_loss -0.7323 +2024-11-22 19:35:25.521773: Pseudo dice [0.8341] +2024-11-22 19:35:25.521850: Epoch time: 19.56 s +2024-11-22 19:35:26.431001: +2024-11-22 19:35:26.431189: Epoch 6030 +2024-11-22 19:35:26.431298: Current learning rate: 0.00283 +2024-11-22 19:35:45.740139: train_loss -0.8089 +2024-11-22 19:35:45.742526: val_loss -0.7545 +2024-11-22 19:35:45.742617: Pseudo dice [0.8206] +2024-11-22 19:35:45.742694: Epoch time: 19.31 s +2024-11-22 19:35:46.774228: +2024-11-22 19:35:46.774497: Epoch 6031 +2024-11-22 19:35:46.774609: Current learning rate: 0.00283 +2024-11-22 19:36:06.022139: train_loss -0.807 +2024-11-22 19:36:06.022417: val_loss -0.7839 +2024-11-22 19:36:06.022498: Pseudo dice [0.8342] +2024-11-22 19:36:06.022584: Epoch time: 19.25 s +2024-11-22 19:36:06.938908: +2024-11-22 19:36:06.939130: Epoch 6032 +2024-11-22 19:36:06.939240: Current learning rate: 0.00283 +2024-11-22 19:36:25.678571: train_loss -0.8098 +2024-11-22 19:36:25.678806: val_loss -0.7611 +2024-11-22 19:36:25.678884: Pseudo dice [0.8428] +2024-11-22 19:36:25.678964: Epoch time: 18.74 s +2024-11-22 19:36:26.650825: +2024-11-22 19:36:26.651021: Epoch 6033 +2024-11-22 19:36:26.651132: Current learning rate: 0.00283 +2024-11-22 19:36:45.086423: train_loss -0.8118 +2024-11-22 19:36:45.086950: val_loss -0.7482 +2024-11-22 19:36:45.087057: Pseudo dice [0.8322] +2024-11-22 19:36:45.087136: Epoch time: 18.44 s +2024-11-22 19:36:45.991942: +2024-11-22 19:36:45.992157: Epoch 6034 +2024-11-22 19:36:45.992265: Current learning rate: 0.00283 +2024-11-22 19:37:05.126474: train_loss -0.8078 +2024-11-22 19:37:05.126701: val_loss -0.7646 +2024-11-22 19:37:05.126777: Pseudo dice [0.8381] +2024-11-22 19:37:05.126857: Epoch time: 19.14 s +2024-11-22 19:37:06.038372: +2024-11-22 19:37:06.038700: Epoch 6035 +2024-11-22 19:37:06.038818: Current learning rate: 0.00283 +2024-11-22 19:37:24.999453: train_loss -0.8159 +2024-11-22 19:37:24.999705: val_loss -0.7683 +2024-11-22 19:37:24.999779: Pseudo dice [0.8419] +2024-11-22 19:37:24.999864: Epoch time: 18.96 s +2024-11-22 19:37:25.918734: +2024-11-22 19:37:25.918941: Epoch 6036 +2024-11-22 19:37:25.919062: Current learning rate: 0.00283 +2024-11-22 19:37:44.697496: train_loss -0.8106 +2024-11-22 19:37:44.697735: val_loss -0.7599 +2024-11-22 19:37:44.697856: Pseudo dice [0.8398] +2024-11-22 19:37:44.697936: Epoch time: 18.78 s +2024-11-22 19:37:45.660302: +2024-11-22 19:37:45.660512: Epoch 6037 +2024-11-22 19:37:45.660627: Current learning rate: 0.00282 +2024-11-22 19:38:04.533310: train_loss -0.8152 +2024-11-22 19:38:04.533523: val_loss -0.7455 +2024-11-22 19:38:04.533613: Pseudo dice [0.8282] +2024-11-22 19:38:04.533689: Epoch time: 18.87 s +2024-11-22 19:38:05.445342: +2024-11-22 19:38:05.445539: Epoch 6038 +2024-11-22 19:38:05.445654: Current learning rate: 0.00282 +2024-11-22 19:38:24.578477: train_loss -0.8051 +2024-11-22 19:38:24.578698: val_loss -0.7398 +2024-11-22 19:38:24.578771: Pseudo dice [0.8143] +2024-11-22 19:38:24.578846: Epoch time: 19.13 s +2024-11-22 19:38:25.499160: +2024-11-22 19:38:25.499360: Epoch 6039 +2024-11-22 19:38:25.499470: Current learning rate: 0.00282 +2024-11-22 19:38:44.846225: train_loss -0.8135 +2024-11-22 19:38:44.846463: val_loss -0.7659 +2024-11-22 19:38:44.846540: Pseudo dice [0.8385] +2024-11-22 19:38:44.846621: Epoch time: 19.35 s +2024-11-22 19:38:45.952949: +2024-11-22 19:38:45.953167: Epoch 6040 +2024-11-22 19:38:45.953279: Current learning rate: 0.00282 +2024-11-22 19:39:06.043739: train_loss -0.8108 +2024-11-22 19:39:06.046519: val_loss -0.7753 +2024-11-22 19:39:06.046669: Pseudo dice [0.8236] +2024-11-22 19:39:06.046748: Epoch time: 20.09 s +2024-11-22 19:39:06.970307: +2024-11-22 19:39:06.970510: Epoch 6041 +2024-11-22 19:39:06.970875: Current learning rate: 0.00282 +2024-11-22 19:39:25.031200: train_loss -0.8155 +2024-11-22 19:39:25.031410: val_loss -0.7574 +2024-11-22 19:39:25.031485: Pseudo dice [0.8261] +2024-11-22 19:39:25.031557: Epoch time: 18.06 s +2024-11-22 19:39:25.938410: +2024-11-22 19:39:25.938647: Epoch 6042 +2024-11-22 19:39:25.938759: Current learning rate: 0.00282 +2024-11-22 19:39:45.459031: train_loss -0.8164 +2024-11-22 19:39:45.459245: val_loss -0.7533 +2024-11-22 19:39:45.459324: Pseudo dice [0.8227] +2024-11-22 19:39:45.459402: Epoch time: 19.52 s +2024-11-22 19:39:46.355386: +2024-11-22 19:39:46.355594: Epoch 6043 +2024-11-22 19:39:46.355705: Current learning rate: 0.00282 +2024-11-22 19:40:04.346155: train_loss -0.8081 +2024-11-22 19:40:04.347609: val_loss -0.7706 +2024-11-22 19:40:04.347718: Pseudo dice [0.8462] +2024-11-22 19:40:04.347803: Epoch time: 17.99 s +2024-11-22 19:40:05.263791: +2024-11-22 19:40:05.263989: Epoch 6044 +2024-11-22 19:40:05.264101: Current learning rate: 0.00281 +2024-11-22 19:40:24.098007: train_loss -0.8095 +2024-11-22 19:40:24.098207: val_loss -0.7393 +2024-11-22 19:40:24.098279: Pseudo dice [0.8414] +2024-11-22 19:40:24.098353: Epoch time: 18.83 s +2024-11-22 19:40:25.286644: +2024-11-22 19:40:25.286866: Epoch 6045 +2024-11-22 19:40:25.286983: Current learning rate: 0.00281 +2024-11-22 19:40:43.731338: train_loss -0.8133 +2024-11-22 19:40:43.738219: val_loss -0.7843 +2024-11-22 19:40:43.738328: Pseudo dice [0.8445] +2024-11-22 19:40:43.738408: Epoch time: 18.45 s +2024-11-22 19:40:44.646758: +2024-11-22 19:40:44.646961: Epoch 6046 +2024-11-22 19:40:44.647077: Current learning rate: 0.00281 +2024-11-22 19:41:04.594679: train_loss -0.8035 +2024-11-22 19:41:04.594913: val_loss -0.7409 +2024-11-22 19:41:04.594987: Pseudo dice [0.8256] +2024-11-22 19:41:04.595079: Epoch time: 19.95 s +2024-11-22 19:41:05.502608: +2024-11-22 19:41:05.502805: Epoch 6047 +2024-11-22 19:41:05.502915: Current learning rate: 0.00281 +2024-11-22 19:41:24.064658: train_loss -0.8025 +2024-11-22 19:41:24.064898: val_loss -0.7617 +2024-11-22 19:41:24.064977: Pseudo dice [0.8209] +2024-11-22 19:41:24.065199: Epoch time: 18.56 s +2024-11-22 19:41:24.978222: +2024-11-22 19:41:24.978422: Epoch 6048 +2024-11-22 19:41:24.978538: Current learning rate: 0.00281 +2024-11-22 19:41:43.760855: train_loss -0.8075 +2024-11-22 19:41:43.761080: val_loss -0.7707 +2024-11-22 19:41:43.761157: Pseudo dice [0.8303] +2024-11-22 19:41:43.761235: Epoch time: 18.78 s +2024-11-22 19:41:44.669443: +2024-11-22 19:41:44.669657: Epoch 6049 +2024-11-22 19:41:44.669771: Current learning rate: 0.00281 +2024-11-22 19:42:03.913783: train_loss -0.807 +2024-11-22 19:42:03.914003: val_loss -0.7681 +2024-11-22 19:42:03.914079: Pseudo dice [0.8503] +2024-11-22 19:42:03.914154: Epoch time: 19.25 s +2024-11-22 19:42:05.175860: +2024-11-22 19:42:05.176123: Epoch 6050 +2024-11-22 19:42:05.176237: Current learning rate: 0.00281 +2024-11-22 19:42:24.319513: train_loss -0.8107 +2024-11-22 19:42:24.319730: val_loss -0.7501 +2024-11-22 19:42:24.319802: Pseudo dice [0.8371] +2024-11-22 19:42:24.319879: Epoch time: 19.14 s +2024-11-22 19:42:25.226638: +2024-11-22 19:42:25.226868: Epoch 6051 +2024-11-22 19:42:25.226985: Current learning rate: 0.00281 +2024-11-22 19:42:44.286790: train_loss -0.8065 +2024-11-22 19:42:44.287034: val_loss -0.7541 +2024-11-22 19:42:44.287125: Pseudo dice [0.839] +2024-11-22 19:42:44.287210: Epoch time: 19.06 s +2024-11-22 19:42:45.195131: +2024-11-22 19:42:45.195341: Epoch 6052 +2024-11-22 19:42:45.195452: Current learning rate: 0.0028 +2024-11-22 19:43:05.268013: train_loss -0.8074 +2024-11-22 19:43:05.268239: val_loss -0.7656 +2024-11-22 19:43:05.268312: Pseudo dice [0.8323] +2024-11-22 19:43:05.268392: Epoch time: 20.07 s +2024-11-22 19:43:06.194396: +2024-11-22 19:43:06.194584: Epoch 6053 +2024-11-22 19:43:06.194695: Current learning rate: 0.0028 +2024-11-22 19:43:24.288529: train_loss -0.8138 +2024-11-22 19:43:24.288743: val_loss -0.7455 +2024-11-22 19:43:24.288817: Pseudo dice [0.8223] +2024-11-22 19:43:24.298141: Epoch time: 18.09 s +2024-11-22 19:43:25.257013: +2024-11-22 19:43:25.257211: Epoch 6054 +2024-11-22 19:43:25.257322: Current learning rate: 0.0028 +2024-11-22 19:43:43.457742: train_loss -0.8122 +2024-11-22 19:43:43.457968: val_loss -0.7838 +2024-11-22 19:43:43.458078: Pseudo dice [0.828] +2024-11-22 19:43:43.458158: Epoch time: 18.2 s +2024-11-22 19:43:44.376256: +2024-11-22 19:43:44.376489: Epoch 6055 +2024-11-22 19:43:44.376607: Current learning rate: 0.0028 +2024-11-22 19:44:04.430928: train_loss -0.8141 +2024-11-22 19:44:04.431215: val_loss -0.7789 +2024-11-22 19:44:04.431291: Pseudo dice [0.821] +2024-11-22 19:44:04.431370: Epoch time: 20.06 s +2024-11-22 19:44:05.355580: +2024-11-22 19:44:05.355781: Epoch 6056 +2024-11-22 19:44:05.355895: Current learning rate: 0.0028 +2024-11-22 19:44:23.026680: train_loss -0.808 +2024-11-22 19:44:23.027222: val_loss -0.7681 +2024-11-22 19:44:23.027317: Pseudo dice [0.8305] +2024-11-22 19:44:23.027399: Epoch time: 17.67 s +2024-11-22 19:44:23.929290: +2024-11-22 19:44:23.929502: Epoch 6057 +2024-11-22 19:44:23.929619: Current learning rate: 0.0028 +2024-11-22 19:44:42.173687: train_loss -0.812 +2024-11-22 19:44:42.173900: val_loss -0.7673 +2024-11-22 19:44:42.173977: Pseudo dice [0.8451] +2024-11-22 19:44:42.174062: Epoch time: 18.25 s +2024-11-22 19:44:43.081881: +2024-11-22 19:44:43.082144: Epoch 6058 +2024-11-22 19:44:43.082253: Current learning rate: 0.0028 +2024-11-22 19:45:02.782761: train_loss -0.8134 +2024-11-22 19:45:02.783061: val_loss -0.7501 +2024-11-22 19:45:02.783142: Pseudo dice [0.819] +2024-11-22 19:45:02.783226: Epoch time: 19.7 s +2024-11-22 19:45:03.694897: +2024-11-22 19:45:03.695099: Epoch 6059 +2024-11-22 19:45:03.695208: Current learning rate: 0.0028 +2024-11-22 19:45:22.328389: train_loss -0.8116 +2024-11-22 19:45:22.328603: val_loss -0.7582 +2024-11-22 19:45:22.328676: Pseudo dice [0.8319] +2024-11-22 19:45:22.328751: Epoch time: 18.63 s +2024-11-22 19:45:23.237172: +2024-11-22 19:45:23.237377: Epoch 6060 +2024-11-22 19:45:23.237511: Current learning rate: 0.00279 +2024-11-22 19:45:41.256617: train_loss -0.8054 +2024-11-22 19:45:41.256846: val_loss -0.7494 +2024-11-22 19:45:41.256922: Pseudo dice [0.8449] +2024-11-22 19:45:41.257004: Epoch time: 18.02 s +2024-11-22 19:45:42.162606: +2024-11-22 19:45:42.162860: Epoch 6061 +2024-11-22 19:45:42.162971: Current learning rate: 0.00279 +2024-11-22 19:46:01.081616: train_loss -0.8107 +2024-11-22 19:46:01.081834: val_loss -0.7365 +2024-11-22 19:46:01.081911: Pseudo dice [0.8203] +2024-11-22 19:46:01.081996: Epoch time: 18.92 s +2024-11-22 19:46:01.997247: +2024-11-22 19:46:01.997588: Epoch 6062 +2024-11-22 19:46:01.997699: Current learning rate: 0.00279 +2024-11-22 19:46:19.274333: train_loss -0.8156 +2024-11-22 19:46:19.274569: val_loss -0.7691 +2024-11-22 19:46:19.274645: Pseudo dice [0.8216] +2024-11-22 19:46:19.274733: Epoch time: 17.28 s +2024-11-22 19:46:20.179284: +2024-11-22 19:46:20.179499: Epoch 6063 +2024-11-22 19:46:20.179613: Current learning rate: 0.00279 +2024-11-22 19:46:38.590741: train_loss -0.8049 +2024-11-22 19:46:38.590955: val_loss -0.7661 +2024-11-22 19:46:38.591038: Pseudo dice [0.8321] +2024-11-22 19:46:38.591114: Epoch time: 18.41 s +2024-11-22 19:46:39.491648: +2024-11-22 19:46:39.491854: Epoch 6064 +2024-11-22 19:46:39.491964: Current learning rate: 0.00279 +2024-11-22 19:46:58.071603: train_loss -0.8125 +2024-11-22 19:46:58.071827: val_loss -0.7747 +2024-11-22 19:46:58.071907: Pseudo dice [0.8381] +2024-11-22 19:46:58.071983: Epoch time: 18.58 s +2024-11-22 19:46:58.976722: +2024-11-22 19:46:58.976979: Epoch 6065 +2024-11-22 19:46:58.977095: Current learning rate: 0.00279 +2024-11-22 19:47:17.236307: train_loss -0.8117 +2024-11-22 19:47:17.236515: val_loss -0.7617 +2024-11-22 19:47:17.236589: Pseudo dice [0.8252] +2024-11-22 19:47:17.236666: Epoch time: 18.26 s +2024-11-22 19:47:18.143152: +2024-11-22 19:47:18.143356: Epoch 6066 +2024-11-22 19:47:18.143466: Current learning rate: 0.00279 +2024-11-22 19:47:37.793734: train_loss -0.8084 +2024-11-22 19:47:37.793953: val_loss -0.7632 +2024-11-22 19:47:37.819806: Pseudo dice [0.8261] +2024-11-22 19:47:37.819928: Epoch time: 19.65 s +2024-11-22 19:47:38.719227: +2024-11-22 19:47:38.719425: Epoch 6067 +2024-11-22 19:47:38.719539: Current learning rate: 0.00279 +2024-11-22 19:47:57.473945: train_loss -0.8158 +2024-11-22 19:47:57.474171: val_loss -0.7514 +2024-11-22 19:47:57.474244: Pseudo dice [0.8349] +2024-11-22 19:47:57.474319: Epoch time: 18.76 s +2024-11-22 19:47:58.769527: +2024-11-22 19:47:58.769730: Epoch 6068 +2024-11-22 19:47:58.769841: Current learning rate: 0.00278 +2024-11-22 19:48:17.518113: train_loss -0.8128 +2024-11-22 19:48:17.518360: val_loss -0.7395 +2024-11-22 19:48:17.518439: Pseudo dice [0.8296] +2024-11-22 19:48:17.518523: Epoch time: 18.75 s +2024-11-22 19:48:18.446791: +2024-11-22 19:48:18.446999: Epoch 6069 +2024-11-22 19:48:18.447106: Current learning rate: 0.00278 +2024-11-22 19:48:36.946208: train_loss -0.8106 +2024-11-22 19:48:36.946445: val_loss -0.7412 +2024-11-22 19:48:36.946527: Pseudo dice [0.8227] +2024-11-22 19:48:36.946615: Epoch time: 18.5 s +2024-11-22 19:48:37.850408: +2024-11-22 19:48:37.850619: Epoch 6070 +2024-11-22 19:48:37.850738: Current learning rate: 0.00278 +2024-11-22 19:48:56.412871: train_loss -0.8151 +2024-11-22 19:48:56.413090: val_loss -0.7701 +2024-11-22 19:48:56.413165: Pseudo dice [0.843] +2024-11-22 19:48:56.413241: Epoch time: 18.56 s +2024-11-22 19:48:57.318346: +2024-11-22 19:48:57.318552: Epoch 6071 +2024-11-22 19:48:57.318672: Current learning rate: 0.00278 +2024-11-22 19:49:16.072239: train_loss -0.8081 +2024-11-22 19:49:16.072450: val_loss -0.7653 +2024-11-22 19:49:16.072544: Pseudo dice [0.8347] +2024-11-22 19:49:16.072625: Epoch time: 18.75 s +2024-11-22 19:49:16.957092: +2024-11-22 19:49:16.957296: Epoch 6072 +2024-11-22 19:49:16.957412: Current learning rate: 0.00278 +2024-11-22 19:49:36.122211: train_loss -0.8082 +2024-11-22 19:49:36.122422: val_loss -0.7597 +2024-11-22 19:49:36.122495: Pseudo dice [0.8317] +2024-11-22 19:49:36.122574: Epoch time: 19.17 s +2024-11-22 19:49:37.021686: +2024-11-22 19:49:37.021880: Epoch 6073 +2024-11-22 19:49:37.022002: Current learning rate: 0.00278 +2024-11-22 19:49:56.799065: train_loss -0.7909 +2024-11-22 19:49:56.799288: val_loss -0.7551 +2024-11-22 19:49:56.799361: Pseudo dice [0.8392] +2024-11-22 19:49:56.799568: Epoch time: 19.78 s +2024-11-22 19:49:57.719209: +2024-11-22 19:49:57.719410: Epoch 6074 +2024-11-22 19:49:57.719517: Current learning rate: 0.00278 +2024-11-22 19:50:16.221008: train_loss -0.8016 +2024-11-22 19:50:16.221236: val_loss -0.747 +2024-11-22 19:50:16.221314: Pseudo dice [0.8328] +2024-11-22 19:50:16.221392: Epoch time: 18.5 s +2024-11-22 19:50:17.123566: +2024-11-22 19:50:17.123773: Epoch 6075 +2024-11-22 19:50:17.123883: Current learning rate: 0.00277 +2024-11-22 19:50:36.060441: train_loss -0.8055 +2024-11-22 19:50:36.060650: val_loss -0.756 +2024-11-22 19:50:36.060775: Pseudo dice [0.8397] +2024-11-22 19:50:36.060892: Epoch time: 18.94 s +2024-11-22 19:50:36.972510: +2024-11-22 19:50:36.972707: Epoch 6076 +2024-11-22 19:50:36.972818: Current learning rate: 0.00277 +2024-11-22 19:50:53.969621: train_loss -0.8014 +2024-11-22 19:50:53.969870: val_loss -0.7546 +2024-11-22 19:50:53.969946: Pseudo dice [0.8442] +2024-11-22 19:50:53.970031: Epoch time: 16.99 s +2024-11-22 19:50:54.873090: +2024-11-22 19:50:54.873439: Epoch 6077 +2024-11-22 19:50:54.873559: Current learning rate: 0.00277 +2024-11-22 19:51:13.282442: train_loss -0.8064 +2024-11-22 19:51:13.282681: val_loss -0.7459 +2024-11-22 19:51:13.282758: Pseudo dice [0.8361] +2024-11-22 19:51:13.282842: Epoch time: 18.41 s +2024-11-22 19:51:14.186196: +2024-11-22 19:51:14.186388: Epoch 6078 +2024-11-22 19:51:14.186500: Current learning rate: 0.00277 +2024-11-22 19:51:33.273777: train_loss -0.81 +2024-11-22 19:51:33.274013: val_loss -0.7344 +2024-11-22 19:51:33.274090: Pseudo dice [0.8313] +2024-11-22 19:51:33.274171: Epoch time: 19.09 s +2024-11-22 19:51:34.178112: +2024-11-22 19:51:34.178300: Epoch 6079 +2024-11-22 19:51:34.178410: Current learning rate: 0.00277 +2024-11-22 19:51:53.131567: train_loss -0.8077 +2024-11-22 19:51:53.137245: val_loss -0.7671 +2024-11-22 19:51:53.137356: Pseudo dice [0.8469] +2024-11-22 19:51:53.137444: Epoch time: 18.95 s +2024-11-22 19:51:54.156948: +2024-11-22 19:51:54.157182: Epoch 6080 +2024-11-22 19:51:54.157287: Current learning rate: 0.00277 +2024-11-22 19:52:13.233035: train_loss -0.8058 +2024-11-22 19:52:13.233279: val_loss -0.7673 +2024-11-22 19:52:13.233358: Pseudo dice [0.839] +2024-11-22 19:52:13.233477: Epoch time: 19.08 s +2024-11-22 19:52:14.135061: +2024-11-22 19:52:14.135272: Epoch 6081 +2024-11-22 19:52:14.135384: Current learning rate: 0.00277 +2024-11-22 19:52:32.889179: train_loss -0.803 +2024-11-22 19:52:32.889676: val_loss -0.7431 +2024-11-22 19:52:32.889756: Pseudo dice [0.839] +2024-11-22 19:52:32.889831: Epoch time: 18.75 s +2024-11-22 19:52:33.800121: +2024-11-22 19:52:33.800412: Epoch 6082 +2024-11-22 19:52:33.800526: Current learning rate: 0.00277 +2024-11-22 19:52:51.787124: train_loss -0.813 +2024-11-22 19:52:51.787348: val_loss -0.7254 +2024-11-22 19:52:51.787432: Pseudo dice [0.8369] +2024-11-22 19:52:51.787511: Epoch time: 17.99 s +2024-11-22 19:52:52.696987: +2024-11-22 19:52:52.697189: Epoch 6083 +2024-11-22 19:52:52.697306: Current learning rate: 0.00276 +2024-11-22 19:53:11.280046: train_loss -0.8073 +2024-11-22 19:53:11.280287: val_loss -0.7614 +2024-11-22 19:53:11.280367: Pseudo dice [0.8202] +2024-11-22 19:53:11.280448: Epoch time: 18.58 s +2024-11-22 19:53:12.336531: +2024-11-22 19:53:12.336729: Epoch 6084 +2024-11-22 19:53:12.336842: Current learning rate: 0.00276 +2024-11-22 19:53:30.574348: train_loss -0.8089 +2024-11-22 19:53:30.574585: val_loss -0.7636 +2024-11-22 19:53:30.574664: Pseudo dice [0.8332] +2024-11-22 19:53:30.574771: Epoch time: 18.24 s +2024-11-22 19:53:31.576613: +2024-11-22 19:53:31.576825: Epoch 6085 +2024-11-22 19:53:31.576938: Current learning rate: 0.00276 +2024-11-22 19:53:50.033946: train_loss -0.8127 +2024-11-22 19:53:50.034177: val_loss -0.7769 +2024-11-22 19:53:50.034254: Pseudo dice [0.8323] +2024-11-22 19:53:50.034340: Epoch time: 18.46 s +2024-11-22 19:53:51.032851: +2024-11-22 19:53:51.033048: Epoch 6086 +2024-11-22 19:53:51.033161: Current learning rate: 0.00276 +2024-11-22 19:54:09.951530: train_loss -0.8134 +2024-11-22 19:54:09.951741: val_loss -0.7684 +2024-11-22 19:54:09.951811: Pseudo dice [0.8211] +2024-11-22 19:54:09.951885: Epoch time: 18.92 s +2024-11-22 19:54:10.984213: +2024-11-22 19:54:10.984402: Epoch 6087 +2024-11-22 19:54:10.984521: Current learning rate: 0.00276 +2024-11-22 19:54:30.223882: train_loss -0.817 +2024-11-22 19:54:30.224145: val_loss -0.7625 +2024-11-22 19:54:30.224226: Pseudo dice [0.8324] +2024-11-22 19:54:30.224310: Epoch time: 19.24 s +2024-11-22 19:54:31.130790: +2024-11-22 19:54:31.130986: Epoch 6088 +2024-11-22 19:54:31.131098: Current learning rate: 0.00276 +2024-11-22 19:54:51.048582: train_loss -0.8154 +2024-11-22 19:54:51.048795: val_loss -0.7692 +2024-11-22 19:54:51.048870: Pseudo dice [0.8324] +2024-11-22 19:54:51.048944: Epoch time: 19.92 s +2024-11-22 19:54:51.964046: +2024-11-22 19:54:51.964235: Epoch 6089 +2024-11-22 19:54:51.964338: Current learning rate: 0.00276 +2024-11-22 19:55:11.183832: train_loss -0.8098 +2024-11-22 19:55:11.184088: val_loss -0.7666 +2024-11-22 19:55:11.184166: Pseudo dice [0.8444] +2024-11-22 19:55:11.184241: Epoch time: 19.22 s +2024-11-22 19:55:12.151614: +2024-11-22 19:55:12.151808: Epoch 6090 +2024-11-22 19:55:12.151920: Current learning rate: 0.00276 +2024-11-22 19:55:30.547611: train_loss -0.7995 +2024-11-22 19:55:30.552987: val_loss -0.7785 +2024-11-22 19:55:30.553186: Pseudo dice [0.8432] +2024-11-22 19:55:30.553276: Epoch time: 18.4 s +2024-11-22 19:55:31.854872: +2024-11-22 19:55:31.855092: Epoch 6091 +2024-11-22 19:55:31.855216: Current learning rate: 0.00275 +2024-11-22 19:55:50.713170: train_loss -0.8171 +2024-11-22 19:55:50.713394: val_loss -0.7773 +2024-11-22 19:55:50.713472: Pseudo dice [0.8327] +2024-11-22 19:55:50.713552: Epoch time: 18.86 s +2024-11-22 19:55:51.595103: +2024-11-22 19:55:51.595297: Epoch 6092 +2024-11-22 19:55:51.595401: Current learning rate: 0.00275 +2024-11-22 19:56:10.266056: train_loss -0.8079 +2024-11-22 19:56:10.266279: val_loss -0.7451 +2024-11-22 19:56:10.266353: Pseudo dice [0.8192] +2024-11-22 19:56:10.266429: Epoch time: 18.67 s +2024-11-22 19:56:11.170009: +2024-11-22 19:56:11.170208: Epoch 6093 +2024-11-22 19:56:11.170316: Current learning rate: 0.00275 +2024-11-22 19:56:30.655148: train_loss -0.8078 +2024-11-22 19:56:30.655367: val_loss -0.7568 +2024-11-22 19:56:30.655445: Pseudo dice [0.8461] +2024-11-22 19:56:30.655519: Epoch time: 19.49 s +2024-11-22 19:56:31.563518: +2024-11-22 19:56:31.563733: Epoch 6094 +2024-11-22 19:56:31.563846: Current learning rate: 0.00275 +2024-11-22 19:56:50.463775: train_loss -0.803 +2024-11-22 19:56:50.464021: val_loss -0.7909 +2024-11-22 19:56:50.464159: Pseudo dice [0.8361] +2024-11-22 19:56:50.464244: Epoch time: 18.9 s +2024-11-22 19:56:51.675573: +2024-11-22 19:56:51.675797: Epoch 6095 +2024-11-22 19:56:51.675908: Current learning rate: 0.00275 +2024-11-22 19:57:09.766886: train_loss -0.818 +2024-11-22 19:57:09.767106: val_loss -0.7563 +2024-11-22 19:57:09.767180: Pseudo dice [0.8435] +2024-11-22 19:57:09.767255: Epoch time: 18.09 s +2024-11-22 19:57:10.682269: +2024-11-22 19:57:10.682475: Epoch 6096 +2024-11-22 19:57:10.682592: Current learning rate: 0.00275 +2024-11-22 19:57:28.637780: train_loss -0.818 +2024-11-22 19:57:28.638003: val_loss -0.7668 +2024-11-22 19:57:28.638079: Pseudo dice [0.8447] +2024-11-22 19:57:28.638157: Epoch time: 17.96 s +2024-11-22 19:57:29.540803: +2024-11-22 19:57:29.541006: Epoch 6097 +2024-11-22 19:57:29.541118: Current learning rate: 0.00275 +2024-11-22 19:57:47.525117: train_loss -0.8108 +2024-11-22 19:57:47.525338: val_loss -0.7867 +2024-11-22 19:57:47.525414: Pseudo dice [0.8413] +2024-11-22 19:57:47.525492: Epoch time: 17.99 s +2024-11-22 19:57:48.436416: +2024-11-22 19:57:48.436741: Epoch 6098 +2024-11-22 19:57:48.436854: Current learning rate: 0.00274 +2024-11-22 19:58:07.575386: train_loss -0.8101 +2024-11-22 19:58:07.575649: val_loss -0.764 +2024-11-22 19:58:07.575729: Pseudo dice [0.8406] +2024-11-22 19:58:07.575814: Epoch time: 19.14 s +2024-11-22 19:58:08.545178: +2024-11-22 19:58:08.545388: Epoch 6099 +2024-11-22 19:58:08.545502: Current learning rate: 0.00274 +2024-11-22 19:58:27.747137: train_loss -0.8142 +2024-11-22 19:58:27.747355: val_loss -0.7482 +2024-11-22 19:58:27.749732: Pseudo dice [0.83] +2024-11-22 19:58:27.749874: Epoch time: 19.2 s +2024-11-22 19:58:29.219651: +2024-11-22 19:58:29.219883: Epoch 6100 +2024-11-22 19:58:29.220007: Current learning rate: 0.00274 +2024-11-22 19:58:48.029871: train_loss -0.806 +2024-11-22 19:58:48.030106: val_loss -0.7645 +2024-11-22 19:58:48.030181: Pseudo dice [0.8287] +2024-11-22 19:58:48.030254: Epoch time: 18.81 s +2024-11-22 19:58:48.936480: +2024-11-22 19:58:48.936692: Epoch 6101 +2024-11-22 19:58:48.936798: Current learning rate: 0.00274 +2024-11-22 19:59:06.920441: train_loss -0.8092 +2024-11-22 19:59:06.920685: val_loss -0.74 +2024-11-22 19:59:06.920765: Pseudo dice [0.8424] +2024-11-22 19:59:06.920853: Epoch time: 17.98 s +2024-11-22 19:59:07.839242: +2024-11-22 19:59:07.839460: Epoch 6102 +2024-11-22 19:59:07.839581: Current learning rate: 0.00274 +2024-11-22 19:59:25.885981: train_loss -0.8037 +2024-11-22 19:59:25.886517: val_loss -0.7338 +2024-11-22 19:59:25.886621: Pseudo dice [0.837] +2024-11-22 19:59:25.886697: Epoch time: 18.05 s +2024-11-22 19:59:26.791901: +2024-11-22 19:59:26.792114: Epoch 6103 +2024-11-22 19:59:26.792227: Current learning rate: 0.00274 +2024-11-22 19:59:45.830451: train_loss -0.8065 +2024-11-22 19:59:45.830667: val_loss -0.7647 +2024-11-22 19:59:45.830744: Pseudo dice [0.8293] +2024-11-22 19:59:45.830820: Epoch time: 19.04 s +2024-11-22 19:59:46.733032: +2024-11-22 19:59:46.733449: Epoch 6104 +2024-11-22 19:59:46.733568: Current learning rate: 0.00274 +2024-11-22 20:00:05.202906: train_loss -0.8019 +2024-11-22 20:00:05.203149: val_loss -0.7555 +2024-11-22 20:00:05.204948: Pseudo dice [0.845] +2024-11-22 20:00:05.205098: Epoch time: 18.47 s +2024-11-22 20:00:06.133315: +2024-11-22 20:00:06.133611: Epoch 6105 +2024-11-22 20:00:06.133729: Current learning rate: 0.00274 +2024-11-22 20:00:25.375340: train_loss -0.8113 +2024-11-22 20:00:25.378950: val_loss -0.7563 +2024-11-22 20:00:25.379078: Pseudo dice [0.836] +2024-11-22 20:00:25.379175: Epoch time: 19.24 s +2024-11-22 20:00:26.371455: +2024-11-22 20:00:26.371649: Epoch 6106 +2024-11-22 20:00:26.371757: Current learning rate: 0.00273 +2024-11-22 20:00:45.080694: train_loss -0.8108 +2024-11-22 20:00:45.080910: val_loss -0.7866 +2024-11-22 20:00:45.080986: Pseudo dice [0.8466] +2024-11-22 20:00:45.081071: Epoch time: 18.71 s +2024-11-22 20:00:45.996290: +2024-11-22 20:00:45.996529: Epoch 6107 +2024-11-22 20:00:45.996643: Current learning rate: 0.00273 +2024-11-22 20:01:03.959766: train_loss -0.8082 +2024-11-22 20:01:03.959984: val_loss -0.7399 +2024-11-22 20:01:03.960100: Pseudo dice [0.8273] +2024-11-22 20:01:03.960181: Epoch time: 17.96 s +2024-11-22 20:01:04.869540: +2024-11-22 20:01:04.869745: Epoch 6108 +2024-11-22 20:01:04.869859: Current learning rate: 0.00273 +2024-11-22 20:01:24.136487: train_loss -0.8001 +2024-11-22 20:01:24.136732: val_loss -0.776 +2024-11-22 20:01:24.136810: Pseudo dice [0.8389] +2024-11-22 20:01:24.136897: Epoch time: 19.27 s +2024-11-22 20:01:25.318304: +2024-11-22 20:01:25.318557: Epoch 6109 +2024-11-22 20:01:25.318666: Current learning rate: 0.00273 +2024-11-22 20:01:44.380435: train_loss -0.8138 +2024-11-22 20:01:44.380641: val_loss -0.7661 +2024-11-22 20:01:44.380714: Pseudo dice [0.8308] +2024-11-22 20:01:44.380790: Epoch time: 19.06 s +2024-11-22 20:01:45.274109: +2024-11-22 20:01:45.274300: Epoch 6110 +2024-11-22 20:01:45.274414: Current learning rate: 0.00273 +2024-11-22 20:02:04.563845: train_loss -0.8063 +2024-11-22 20:02:04.564105: val_loss -0.7432 +2024-11-22 20:02:04.564183: Pseudo dice [0.8008] +2024-11-22 20:02:04.564259: Epoch time: 19.29 s +2024-11-22 20:02:05.447144: +2024-11-22 20:02:05.447341: Epoch 6111 +2024-11-22 20:02:05.447452: Current learning rate: 0.00273 +2024-11-22 20:02:23.613904: train_loss -0.7858 +2024-11-22 20:02:23.614128: val_loss -0.7633 +2024-11-22 20:02:23.614209: Pseudo dice [0.8401] +2024-11-22 20:02:23.614288: Epoch time: 18.17 s +2024-11-22 20:02:24.528131: +2024-11-22 20:02:24.528325: Epoch 6112 +2024-11-22 20:02:24.528475: Current learning rate: 0.00273 +2024-11-22 20:02:43.214024: train_loss -0.8104 +2024-11-22 20:02:43.214283: val_loss -0.7518 +2024-11-22 20:02:43.214362: Pseudo dice [0.838] +2024-11-22 20:02:43.214474: Epoch time: 18.69 s +2024-11-22 20:02:44.124935: +2024-11-22 20:02:44.125126: Epoch 6113 +2024-11-22 20:02:44.125236: Current learning rate: 0.00273 +2024-11-22 20:03:03.592660: train_loss -0.8069 +2024-11-22 20:03:03.592867: val_loss -0.7625 +2024-11-22 20:03:03.592940: Pseudo dice [0.8401] +2024-11-22 20:03:03.593027: Epoch time: 19.47 s +2024-11-22 20:03:04.944965: +2024-11-22 20:03:04.945164: Epoch 6114 +2024-11-22 20:03:04.945274: Current learning rate: 0.00272 +2024-11-22 20:03:22.762031: train_loss -0.8036 +2024-11-22 20:03:22.762264: val_loss -0.7481 +2024-11-22 20:03:22.762338: Pseudo dice [0.8208] +2024-11-22 20:03:22.762418: Epoch time: 17.82 s +2024-11-22 20:03:23.807105: +2024-11-22 20:03:23.807333: Epoch 6115 +2024-11-22 20:03:23.807441: Current learning rate: 0.00272 +2024-11-22 20:03:42.934807: train_loss -0.8104 +2024-11-22 20:03:42.935051: val_loss -0.748 +2024-11-22 20:03:42.935127: Pseudo dice [0.8477] +2024-11-22 20:03:42.935214: Epoch time: 19.13 s +2024-11-22 20:03:43.929882: +2024-11-22 20:03:43.930092: Epoch 6116 +2024-11-22 20:03:43.930200: Current learning rate: 0.00272 +2024-11-22 20:04:02.017074: train_loss -0.8176 +2024-11-22 20:04:02.017287: val_loss -0.747 +2024-11-22 20:04:02.017358: Pseudo dice [0.8367] +2024-11-22 20:04:02.017431: Epoch time: 18.09 s +2024-11-22 20:04:03.157417: +2024-11-22 20:04:03.157614: Epoch 6117 +2024-11-22 20:04:03.157727: Current learning rate: 0.00272 +2024-11-22 20:04:21.672884: train_loss -0.8093 +2024-11-22 20:04:21.675253: val_loss -0.7458 +2024-11-22 20:04:21.675348: Pseudo dice [0.8301] +2024-11-22 20:04:21.675426: Epoch time: 18.52 s +2024-11-22 20:04:22.719765: +2024-11-22 20:04:22.719986: Epoch 6118 +2024-11-22 20:04:22.720106: Current learning rate: 0.00272 +2024-11-22 20:04:40.527490: train_loss -0.8092 +2024-11-22 20:04:40.527711: val_loss -0.7531 +2024-11-22 20:04:40.527786: Pseudo dice [0.8127] +2024-11-22 20:04:40.527860: Epoch time: 17.81 s +2024-11-22 20:04:41.582554: +2024-11-22 20:04:41.582758: Epoch 6119 +2024-11-22 20:04:41.582869: Current learning rate: 0.00272 +2024-11-22 20:05:00.153891: train_loss -0.7974 +2024-11-22 20:05:00.154151: val_loss -0.7416 +2024-11-22 20:05:00.154227: Pseudo dice [0.8217] +2024-11-22 20:05:00.154309: Epoch time: 18.57 s +2024-11-22 20:05:01.056297: +2024-11-22 20:05:01.056506: Epoch 6120 +2024-11-22 20:05:01.056618: Current learning rate: 0.00272 +2024-11-22 20:05:19.800004: train_loss -0.7983 +2024-11-22 20:05:19.800216: val_loss -0.7482 +2024-11-22 20:05:19.800288: Pseudo dice [0.8353] +2024-11-22 20:05:19.800363: Epoch time: 18.74 s +2024-11-22 20:05:20.711911: +2024-11-22 20:05:20.712102: Epoch 6121 +2024-11-22 20:05:20.712218: Current learning rate: 0.00271 +2024-11-22 20:05:39.973691: train_loss -0.7999 +2024-11-22 20:05:39.973943: val_loss -0.7745 +2024-11-22 20:05:39.974021: Pseudo dice [0.8635] +2024-11-22 20:05:39.974097: Epoch time: 19.26 s +2024-11-22 20:05:40.942865: +2024-11-22 20:05:40.943059: Epoch 6122 +2024-11-22 20:05:40.943172: Current learning rate: 0.00271 +2024-11-22 20:05:59.383353: train_loss -0.8034 +2024-11-22 20:05:59.383574: val_loss -0.7423 +2024-11-22 20:05:59.383655: Pseudo dice [0.8331] +2024-11-22 20:05:59.383729: Epoch time: 18.44 s +2024-11-22 20:06:00.290959: +2024-11-22 20:06:00.291149: Epoch 6123 +2024-11-22 20:06:00.291268: Current learning rate: 0.00271 +2024-11-22 20:06:19.267149: train_loss -0.8019 +2024-11-22 20:06:19.267386: val_loss -0.7668 +2024-11-22 20:06:19.267460: Pseudo dice [0.8266] +2024-11-22 20:06:19.267542: Epoch time: 18.98 s +2024-11-22 20:06:20.265244: +2024-11-22 20:06:20.265487: Epoch 6124 +2024-11-22 20:06:20.265604: Current learning rate: 0.00271 +2024-11-22 20:06:38.240514: train_loss -0.8136 +2024-11-22 20:06:38.240728: val_loss -0.7737 +2024-11-22 20:06:38.240803: Pseudo dice [0.8546] +2024-11-22 20:06:38.240879: Epoch time: 17.98 s +2024-11-22 20:06:39.148985: +2024-11-22 20:06:39.149185: Epoch 6125 +2024-11-22 20:06:39.149301: Current learning rate: 0.00271 +2024-11-22 20:06:57.792371: train_loss -0.8137 +2024-11-22 20:06:57.798006: val_loss -0.7334 +2024-11-22 20:06:57.798203: Pseudo dice [0.8276] +2024-11-22 20:06:57.798315: Epoch time: 18.64 s +2024-11-22 20:06:58.818057: +2024-11-22 20:06:58.818257: Epoch 6126 +2024-11-22 20:06:58.818370: Current learning rate: 0.00271 +2024-11-22 20:07:16.960629: train_loss -0.8069 +2024-11-22 20:07:16.960875: val_loss -0.7507 +2024-11-22 20:07:16.960964: Pseudo dice [0.8419] +2024-11-22 20:07:16.961082: Epoch time: 18.14 s +2024-11-22 20:07:17.968165: +2024-11-22 20:07:17.968468: Epoch 6127 +2024-11-22 20:07:17.968581: Current learning rate: 0.00271 +2024-11-22 20:07:36.440143: train_loss -0.8053 +2024-11-22 20:07:36.440370: val_loss -0.7747 +2024-11-22 20:07:36.440444: Pseudo dice [0.8439] +2024-11-22 20:07:36.440521: Epoch time: 18.47 s +2024-11-22 20:07:37.341700: +2024-11-22 20:07:37.341915: Epoch 6128 +2024-11-22 20:07:37.342032: Current learning rate: 0.00271 +2024-11-22 20:07:55.878868: train_loss -0.8042 +2024-11-22 20:07:55.879095: val_loss -0.764 +2024-11-22 20:07:55.879169: Pseudo dice [0.8456] +2024-11-22 20:07:55.879245: Epoch time: 18.54 s +2024-11-22 20:07:56.821445: +2024-11-22 20:07:56.821638: Epoch 6129 +2024-11-22 20:07:56.821766: Current learning rate: 0.0027 +2024-11-22 20:08:15.019850: train_loss -0.8057 +2024-11-22 20:08:15.020091: val_loss -0.776 +2024-11-22 20:08:15.020164: Pseudo dice [0.8357] +2024-11-22 20:08:15.020240: Epoch time: 18.2 s +2024-11-22 20:08:16.042650: +2024-11-22 20:08:16.043049: Epoch 6130 +2024-11-22 20:08:16.043165: Current learning rate: 0.0027 +2024-11-22 20:08:33.980508: train_loss -0.8122 +2024-11-22 20:08:33.980742: val_loss -0.7431 +2024-11-22 20:08:33.980823: Pseudo dice [0.8183] +2024-11-22 20:08:33.980904: Epoch time: 17.94 s +2024-11-22 20:08:34.882921: +2024-11-22 20:08:34.883127: Epoch 6131 +2024-11-22 20:08:34.883243: Current learning rate: 0.0027 +2024-11-22 20:08:53.393667: train_loss -0.8107 +2024-11-22 20:08:53.393885: val_loss -0.7398 +2024-11-22 20:08:53.393960: Pseudo dice [0.856] +2024-11-22 20:08:53.394041: Epoch time: 18.51 s +2024-11-22 20:08:54.302214: +2024-11-22 20:08:54.302492: Epoch 6132 +2024-11-22 20:08:54.302605: Current learning rate: 0.0027 +2024-11-22 20:09:12.396427: train_loss -0.8123 +2024-11-22 20:09:12.401839: val_loss -0.7283 +2024-11-22 20:09:12.401955: Pseudo dice [0.8289] +2024-11-22 20:09:12.402045: Epoch time: 18.1 s +2024-11-22 20:09:13.333009: +2024-11-22 20:09:13.333312: Epoch 6133 +2024-11-22 20:09:13.333426: Current learning rate: 0.0027 +2024-11-22 20:09:33.259670: train_loss -0.804 +2024-11-22 20:09:33.259895: val_loss -0.7448 +2024-11-22 20:09:33.259976: Pseudo dice [0.8387] +2024-11-22 20:09:33.260061: Epoch time: 19.93 s +2024-11-22 20:09:34.166821: +2024-11-22 20:09:34.167025: Epoch 6134 +2024-11-22 20:09:34.167142: Current learning rate: 0.0027 +2024-11-22 20:09:52.647079: train_loss -0.812 +2024-11-22 20:09:52.647315: val_loss -0.7339 +2024-11-22 20:09:52.647392: Pseudo dice [0.8474] +2024-11-22 20:09:52.647475: Epoch time: 18.48 s +2024-11-22 20:09:53.551182: +2024-11-22 20:09:53.551385: Epoch 6135 +2024-11-22 20:09:53.551497: Current learning rate: 0.0027 +2024-11-22 20:10:13.182720: train_loss -0.8066 +2024-11-22 20:10:13.182935: val_loss -0.7419 +2024-11-22 20:10:13.183017: Pseudo dice [0.8234] +2024-11-22 20:10:13.183096: Epoch time: 19.63 s +2024-11-22 20:10:14.080965: +2024-11-22 20:10:14.081164: Epoch 6136 +2024-11-22 20:10:14.081275: Current learning rate: 0.0027 +2024-11-22 20:10:33.298214: train_loss -0.8106 +2024-11-22 20:10:33.298437: val_loss -0.7487 +2024-11-22 20:10:33.303736: Pseudo dice [0.8253] +2024-11-22 20:10:33.303871: Epoch time: 19.22 s +2024-11-22 20:10:34.787501: +2024-11-22 20:10:34.787711: Epoch 6137 +2024-11-22 20:10:34.787813: Current learning rate: 0.00269 +2024-11-22 20:10:53.852621: train_loss -0.8064 +2024-11-22 20:10:53.852853: val_loss -0.7425 +2024-11-22 20:10:53.852927: Pseudo dice [0.8493] +2024-11-22 20:10:53.853017: Epoch time: 19.07 s +2024-11-22 20:10:54.739489: +2024-11-22 20:10:54.739689: Epoch 6138 +2024-11-22 20:10:54.739801: Current learning rate: 0.00269 +2024-11-22 20:11:13.429694: train_loss -0.8041 +2024-11-22 20:11:13.429916: val_loss -0.7305 +2024-11-22 20:11:13.429995: Pseudo dice [0.8291] +2024-11-22 20:11:13.430074: Epoch time: 18.69 s +2024-11-22 20:11:14.329621: +2024-11-22 20:11:14.329837: Epoch 6139 +2024-11-22 20:11:14.329945: Current learning rate: 0.00269 +2024-11-22 20:11:33.178816: train_loss -0.8096 +2024-11-22 20:11:33.184229: val_loss -0.7699 +2024-11-22 20:11:33.184350: Pseudo dice [0.821] +2024-11-22 20:11:33.184432: Epoch time: 18.85 s +2024-11-22 20:11:34.194914: +2024-11-22 20:11:34.195195: Epoch 6140 +2024-11-22 20:11:34.195309: Current learning rate: 0.00269 +2024-11-22 20:11:52.300598: train_loss -0.8074 +2024-11-22 20:11:52.300821: val_loss -0.7314 +2024-11-22 20:11:52.300893: Pseudo dice [0.8374] +2024-11-22 20:11:52.300971: Epoch time: 18.11 s +2024-11-22 20:11:53.215753: +2024-11-22 20:11:53.216052: Epoch 6141 +2024-11-22 20:11:53.216166: Current learning rate: 0.00269 +2024-11-22 20:12:12.131348: train_loss -0.8043 +2024-11-22 20:12:12.131609: val_loss -0.7429 +2024-11-22 20:12:12.131681: Pseudo dice [0.8327] +2024-11-22 20:12:12.131765: Epoch time: 18.92 s +2024-11-22 20:12:13.088157: +2024-11-22 20:12:13.088432: Epoch 6142 +2024-11-22 20:12:13.088548: Current learning rate: 0.00269 +2024-11-22 20:12:32.133032: train_loss -0.8076 +2024-11-22 20:12:32.133244: val_loss -0.7416 +2024-11-22 20:12:32.133317: Pseudo dice [0.8183] +2024-11-22 20:12:32.134216: Epoch time: 19.05 s +2024-11-22 20:12:33.064551: +2024-11-22 20:12:33.064742: Epoch 6143 +2024-11-22 20:12:33.064855: Current learning rate: 0.00269 +2024-11-22 20:12:51.464521: train_loss -0.821 +2024-11-22 20:12:51.464750: val_loss -0.7483 +2024-11-22 20:12:51.464826: Pseudo dice [0.8509] +2024-11-22 20:12:51.464900: Epoch time: 18.4 s +2024-11-22 20:12:52.425313: +2024-11-22 20:12:52.425593: Epoch 6144 +2024-11-22 20:12:52.425705: Current learning rate: 0.00268 +2024-11-22 20:13:11.051012: train_loss -0.8141 +2024-11-22 20:13:11.051220: val_loss -0.7375 +2024-11-22 20:13:11.051293: Pseudo dice [0.8305] +2024-11-22 20:13:11.051370: Epoch time: 18.63 s +2024-11-22 20:13:11.955165: +2024-11-22 20:13:11.955532: Epoch 6145 +2024-11-22 20:13:11.955648: Current learning rate: 0.00268 +2024-11-22 20:13:29.744657: train_loss -0.822 +2024-11-22 20:13:29.744918: val_loss -0.7724 +2024-11-22 20:13:29.745000: Pseudo dice [0.8449] +2024-11-22 20:13:29.745083: Epoch time: 17.79 s +2024-11-22 20:13:30.662374: +2024-11-22 20:13:30.662571: Epoch 6146 +2024-11-22 20:13:30.662681: Current learning rate: 0.00268 +2024-11-22 20:13:48.947756: train_loss -0.8145 +2024-11-22 20:13:48.947985: val_loss -0.7554 +2024-11-22 20:13:48.948105: Pseudo dice [0.8518] +2024-11-22 20:13:48.948186: Epoch time: 18.29 s +2024-11-22 20:13:49.931762: +2024-11-22 20:13:49.931959: Epoch 6147 +2024-11-22 20:13:49.932077: Current learning rate: 0.00268 +2024-11-22 20:14:08.062505: train_loss -0.8088 +2024-11-22 20:14:08.062724: val_loss -0.7298 +2024-11-22 20:14:08.062805: Pseudo dice [0.8428] +2024-11-22 20:14:08.062915: Epoch time: 18.13 s +2024-11-22 20:14:08.966582: +2024-11-22 20:14:08.966766: Epoch 6148 +2024-11-22 20:14:08.966879: Current learning rate: 0.00268 +2024-11-22 20:14:28.610101: train_loss -0.8056 +2024-11-22 20:14:28.610600: val_loss -0.7572 +2024-11-22 20:14:28.610701: Pseudo dice [0.8389] +2024-11-22 20:14:28.610795: Epoch time: 19.64 s +2024-11-22 20:14:29.520072: +2024-11-22 20:14:29.520287: Epoch 6149 +2024-11-22 20:14:29.520406: Current learning rate: 0.00268 +2024-11-22 20:14:47.487022: train_loss -0.8169 +2024-11-22 20:14:47.487240: val_loss -0.7591 +2024-11-22 20:14:47.487316: Pseudo dice [0.8501] +2024-11-22 20:14:47.487391: Epoch time: 17.97 s +2024-11-22 20:14:48.687486: +2024-11-22 20:14:48.687680: Epoch 6150 +2024-11-22 20:14:48.687792: Current learning rate: 0.00268 +2024-11-22 20:15:08.871206: train_loss -0.8119 +2024-11-22 20:15:08.871421: val_loss -0.7534 +2024-11-22 20:15:08.871494: Pseudo dice [0.8244] +2024-11-22 20:15:08.871569: Epoch time: 20.18 s +2024-11-22 20:15:09.776171: +2024-11-22 20:15:09.776444: Epoch 6151 +2024-11-22 20:15:09.776550: Current learning rate: 0.00268 +2024-11-22 20:15:28.255188: train_loss -0.8105 +2024-11-22 20:15:28.255495: val_loss -0.7569 +2024-11-22 20:15:28.257766: Pseudo dice [0.8465] +2024-11-22 20:15:28.257857: Epoch time: 18.48 s +2024-11-22 20:15:29.188507: +2024-11-22 20:15:29.188742: Epoch 6152 +2024-11-22 20:15:29.188856: Current learning rate: 0.00267 +2024-11-22 20:15:48.789573: train_loss -0.8089 +2024-11-22 20:15:48.789810: val_loss -0.7676 +2024-11-22 20:15:48.789889: Pseudo dice [0.8373] +2024-11-22 20:15:48.789971: Epoch time: 19.6 s +2024-11-22 20:15:49.756811: +2024-11-22 20:15:49.757065: Epoch 6153 +2024-11-22 20:15:49.757180: Current learning rate: 0.00267 +2024-11-22 20:16:06.686177: train_loss -0.818 +2024-11-22 20:16:06.686390: val_loss -0.751 +2024-11-22 20:16:06.686463: Pseudo dice [0.829] +2024-11-22 20:16:06.686542: Epoch time: 16.93 s +2024-11-22 20:16:07.722448: +2024-11-22 20:16:07.722722: Epoch 6154 +2024-11-22 20:16:07.722836: Current learning rate: 0.00267 +2024-11-22 20:16:25.621629: train_loss -0.8092 +2024-11-22 20:16:25.624608: val_loss -0.748 +2024-11-22 20:16:25.624727: Pseudo dice [0.8292] +2024-11-22 20:16:25.624807: Epoch time: 17.9 s +2024-11-22 20:16:26.683174: +2024-11-22 20:16:26.683434: Epoch 6155 +2024-11-22 20:16:26.683545: Current learning rate: 0.00267 +2024-11-22 20:16:45.392524: train_loss -0.8068 +2024-11-22 20:16:45.414899: val_loss -0.7623 +2024-11-22 20:16:45.415079: Pseudo dice [0.82] +2024-11-22 20:16:45.415179: Epoch time: 18.71 s +2024-11-22 20:16:46.321422: +2024-11-22 20:16:46.321703: Epoch 6156 +2024-11-22 20:16:46.321856: Current learning rate: 0.00267 +2024-11-22 20:17:04.837410: train_loss -0.8095 +2024-11-22 20:17:04.839820: val_loss -0.7526 +2024-11-22 20:17:04.839915: Pseudo dice [0.8449] +2024-11-22 20:17:04.840009: Epoch time: 18.52 s +2024-11-22 20:17:05.976828: +2024-11-22 20:17:05.977036: Epoch 6157 +2024-11-22 20:17:05.977151: Current learning rate: 0.00267 +2024-11-22 20:17:24.053406: train_loss -0.8106 +2024-11-22 20:17:24.053625: val_loss -0.7603 +2024-11-22 20:17:24.053701: Pseudo dice [0.8288] +2024-11-22 20:17:24.053815: Epoch time: 18.08 s +2024-11-22 20:17:24.961184: +2024-11-22 20:17:24.961401: Epoch 6158 +2024-11-22 20:17:24.961510: Current learning rate: 0.00267 +2024-11-22 20:17:44.424187: train_loss -0.8044 +2024-11-22 20:17:44.424415: val_loss -0.7637 +2024-11-22 20:17:44.424489: Pseudo dice [0.8336] +2024-11-22 20:17:44.424567: Epoch time: 19.46 s +2024-11-22 20:17:45.326278: +2024-11-22 20:17:45.326462: Epoch 6159 +2024-11-22 20:17:45.326571: Current learning rate: 0.00267 +2024-11-22 20:18:03.965402: train_loss -0.8087 +2024-11-22 20:18:03.965892: val_loss -0.7403 +2024-11-22 20:18:03.965988: Pseudo dice [0.8296] +2024-11-22 20:18:03.966079: Epoch time: 18.64 s +2024-11-22 20:18:04.870059: +2024-11-22 20:18:04.870278: Epoch 6160 +2024-11-22 20:18:04.870394: Current learning rate: 0.00266 +2024-11-22 20:18:23.636385: train_loss -0.8132 +2024-11-22 20:18:23.636610: val_loss -0.7532 +2024-11-22 20:18:23.636686: Pseudo dice [0.8332] +2024-11-22 20:18:23.636764: Epoch time: 18.77 s +2024-11-22 20:18:24.541797: +2024-11-22 20:18:24.542023: Epoch 6161 +2024-11-22 20:18:24.542136: Current learning rate: 0.00266 +2024-11-22 20:18:44.077392: train_loss -0.8121 +2024-11-22 20:18:44.077671: val_loss -0.752 +2024-11-22 20:18:44.077750: Pseudo dice [0.8163] +2024-11-22 20:18:44.077828: Epoch time: 19.54 s +2024-11-22 20:18:45.142681: +2024-11-22 20:18:45.142902: Epoch 6162 +2024-11-22 20:18:45.143018: Current learning rate: 0.00266 +2024-11-22 20:19:04.621013: train_loss -0.8 +2024-11-22 20:19:04.621316: val_loss -0.7712 +2024-11-22 20:19:04.621393: Pseudo dice [0.8317] +2024-11-22 20:19:04.621477: Epoch time: 19.48 s +2024-11-22 20:19:05.613117: +2024-11-22 20:19:05.613347: Epoch 6163 +2024-11-22 20:19:05.613461: Current learning rate: 0.00266 +2024-11-22 20:19:24.124585: train_loss -0.8117 +2024-11-22 20:19:24.124812: val_loss -0.7518 +2024-11-22 20:19:24.124883: Pseudo dice [0.8292] +2024-11-22 20:19:24.124957: Epoch time: 18.51 s +2024-11-22 20:19:25.071813: +2024-11-22 20:19:25.072058: Epoch 6164 +2024-11-22 20:19:25.072174: Current learning rate: 0.00266 +2024-11-22 20:19:44.364859: train_loss -0.8061 +2024-11-22 20:19:44.365080: val_loss -0.7563 +2024-11-22 20:19:44.365158: Pseudo dice [0.8318] +2024-11-22 20:19:44.365232: Epoch time: 19.29 s +2024-11-22 20:19:45.275681: +2024-11-22 20:19:45.275881: Epoch 6165 +2024-11-22 20:19:45.275996: Current learning rate: 0.00266 +2024-11-22 20:20:03.932689: train_loss -0.8002 +2024-11-22 20:20:03.932916: val_loss -0.745 +2024-11-22 20:20:03.933002: Pseudo dice [0.8274] +2024-11-22 20:20:03.933085: Epoch time: 18.66 s +2024-11-22 20:20:04.841442: +2024-11-22 20:20:04.841634: Epoch 6166 +2024-11-22 20:20:04.841744: Current learning rate: 0.00266 +2024-11-22 20:20:23.189578: train_loss -0.8028 +2024-11-22 20:20:23.189823: val_loss -0.7505 +2024-11-22 20:20:23.189895: Pseudo dice [0.8404] +2024-11-22 20:20:23.189978: Epoch time: 18.35 s +2024-11-22 20:20:24.100468: +2024-11-22 20:20:24.100658: Epoch 6167 +2024-11-22 20:20:24.100770: Current learning rate: 0.00266 +2024-11-22 20:20:43.377875: train_loss -0.8049 +2024-11-22 20:20:43.378092: val_loss -0.7528 +2024-11-22 20:20:43.378165: Pseudo dice [0.8275] +2024-11-22 20:20:43.378239: Epoch time: 19.28 s +2024-11-22 20:20:44.288554: +2024-11-22 20:20:44.288749: Epoch 6168 +2024-11-22 20:20:44.310480: Current learning rate: 0.00265 +2024-11-22 20:21:02.940445: train_loss -0.8183 +2024-11-22 20:21:02.940667: val_loss -0.7497 +2024-11-22 20:21:02.940742: Pseudo dice [0.8219] +2024-11-22 20:21:02.940816: Epoch time: 18.65 s +2024-11-22 20:21:03.847597: +2024-11-22 20:21:03.847810: Epoch 6169 +2024-11-22 20:21:03.847921: Current learning rate: 0.00265 +2024-11-22 20:21:23.008430: train_loss -0.808 +2024-11-22 20:21:23.008668: val_loss -0.7688 +2024-11-22 20:21:23.008749: Pseudo dice [0.8402] +2024-11-22 20:21:23.008841: Epoch time: 19.16 s +2024-11-22 20:21:24.123804: +2024-11-22 20:21:24.124005: Epoch 6170 +2024-11-22 20:21:24.124118: Current learning rate: 0.00265 +2024-11-22 20:21:42.897059: train_loss -0.8109 +2024-11-22 20:21:42.897272: val_loss -0.7599 +2024-11-22 20:21:42.897347: Pseudo dice [0.8319] +2024-11-22 20:21:42.897423: Epoch time: 18.77 s +2024-11-22 20:21:44.179161: +2024-11-22 20:21:44.179358: Epoch 6171 +2024-11-22 20:21:44.179471: Current learning rate: 0.00265 +2024-11-22 20:22:03.423304: train_loss -0.815 +2024-11-22 20:22:03.423519: val_loss -0.7627 +2024-11-22 20:22:03.423594: Pseudo dice [0.8295] +2024-11-22 20:22:03.423670: Epoch time: 19.24 s +2024-11-22 20:22:04.333112: +2024-11-22 20:22:04.333390: Epoch 6172 +2024-11-22 20:22:04.333503: Current learning rate: 0.00265 +2024-11-22 20:22:22.958611: train_loss -0.8188 +2024-11-22 20:22:22.958861: val_loss -0.7774 +2024-11-22 20:22:22.958937: Pseudo dice [0.8387] +2024-11-22 20:22:22.959041: Epoch time: 18.63 s +2024-11-22 20:22:23.875594: +2024-11-22 20:22:23.875798: Epoch 6173 +2024-11-22 20:22:23.875907: Current learning rate: 0.00265 +2024-11-22 20:22:43.320402: train_loss -0.81 +2024-11-22 20:22:43.320625: val_loss -0.7526 +2024-11-22 20:22:43.320702: Pseudo dice [0.8278] +2024-11-22 20:22:43.320776: Epoch time: 19.45 s +2024-11-22 20:22:44.239898: +2024-11-22 20:22:44.240108: Epoch 6174 +2024-11-22 20:22:44.240224: Current learning rate: 0.00265 +2024-11-22 20:23:03.604559: train_loss -0.8121 +2024-11-22 20:23:03.604773: val_loss -0.7812 +2024-11-22 20:23:03.604848: Pseudo dice [0.8493] +2024-11-22 20:23:03.604924: Epoch time: 19.37 s +2024-11-22 20:23:04.618244: +2024-11-22 20:23:04.618444: Epoch 6175 +2024-11-22 20:23:04.618559: Current learning rate: 0.00264 +2024-11-22 20:23:23.856765: train_loss -0.805 +2024-11-22 20:23:23.856979: val_loss -0.7539 +2024-11-22 20:23:23.857059: Pseudo dice [0.8178] +2024-11-22 20:23:23.857133: Epoch time: 19.24 s +2024-11-22 20:23:24.876425: +2024-11-22 20:23:24.876651: Epoch 6176 +2024-11-22 20:23:24.876765: Current learning rate: 0.00264 +2024-11-22 20:23:43.526491: train_loss -0.8141 +2024-11-22 20:23:43.526723: val_loss -0.7543 +2024-11-22 20:23:43.526797: Pseudo dice [0.8357] +2024-11-22 20:23:43.526880: Epoch time: 18.65 s +2024-11-22 20:23:44.458462: +2024-11-22 20:23:44.458653: Epoch 6177 +2024-11-22 20:23:44.458762: Current learning rate: 0.00264 +2024-11-22 20:24:02.523098: train_loss -0.8085 +2024-11-22 20:24:02.523432: val_loss -0.759 +2024-11-22 20:24:02.523520: Pseudo dice [0.8306] +2024-11-22 20:24:02.523609: Epoch time: 18.07 s +2024-11-22 20:24:03.488426: +2024-11-22 20:24:03.488649: Epoch 6178 +2024-11-22 20:24:03.488760: Current learning rate: 0.00264 +2024-11-22 20:24:21.875381: train_loss -0.8014 +2024-11-22 20:24:21.875610: val_loss -0.7536 +2024-11-22 20:24:21.875688: Pseudo dice [0.8256] +2024-11-22 20:24:21.875767: Epoch time: 18.39 s +2024-11-22 20:24:22.783274: +2024-11-22 20:24:22.783479: Epoch 6179 +2024-11-22 20:24:22.783595: Current learning rate: 0.00264 +2024-11-22 20:24:40.877102: train_loss -0.8045 +2024-11-22 20:24:40.877321: val_loss -0.7551 +2024-11-22 20:24:40.877402: Pseudo dice [0.8412] +2024-11-22 20:24:40.877478: Epoch time: 18.09 s +2024-11-22 20:24:41.784353: +2024-11-22 20:24:41.784568: Epoch 6180 +2024-11-22 20:24:41.784685: Current learning rate: 0.00264 +2024-11-22 20:25:01.542455: train_loss -0.8084 +2024-11-22 20:25:01.542691: val_loss -0.7709 +2024-11-22 20:25:01.542767: Pseudo dice [0.823] +2024-11-22 20:25:01.542846: Epoch time: 19.76 s +2024-11-22 20:25:02.443794: +2024-11-22 20:25:02.443985: Epoch 6181 +2024-11-22 20:25:02.444102: Current learning rate: 0.00264 +2024-11-22 20:25:21.091879: train_loss -0.8091 +2024-11-22 20:25:21.092139: val_loss -0.781 +2024-11-22 20:25:21.092222: Pseudo dice [0.8489] +2024-11-22 20:25:21.092303: Epoch time: 18.65 s +2024-11-22 20:25:22.093103: +2024-11-22 20:25:22.093313: Epoch 6182 +2024-11-22 20:25:22.093441: Current learning rate: 0.00264 +2024-11-22 20:25:41.492326: train_loss -0.8114 +2024-11-22 20:25:41.492623: val_loss -0.7313 +2024-11-22 20:25:41.492705: Pseudo dice [0.8215] +2024-11-22 20:25:41.492781: Epoch time: 19.4 s +2024-11-22 20:25:42.398216: +2024-11-22 20:25:42.398523: Epoch 6183 +2024-11-22 20:25:42.398636: Current learning rate: 0.00263 +2024-11-22 20:26:00.995733: train_loss -0.8048 +2024-11-22 20:26:00.995979: val_loss -0.7751 +2024-11-22 20:26:00.996061: Pseudo dice [0.8466] +2024-11-22 20:26:00.996145: Epoch time: 18.6 s +2024-11-22 20:26:02.072869: +2024-11-22 20:26:02.073128: Epoch 6184 +2024-11-22 20:26:02.073252: Current learning rate: 0.00263 +2024-11-22 20:26:21.917237: train_loss -0.8092 +2024-11-22 20:26:21.917506: val_loss -0.7381 +2024-11-22 20:26:21.917581: Pseudo dice [0.8349] +2024-11-22 20:26:21.917656: Epoch time: 19.85 s +2024-11-22 20:26:22.804642: +2024-11-22 20:26:22.804851: Epoch 6185 +2024-11-22 20:26:22.804966: Current learning rate: 0.00263 +2024-11-22 20:26:41.699222: train_loss -0.806 +2024-11-22 20:26:41.699435: val_loss -0.7583 +2024-11-22 20:26:41.699509: Pseudo dice [0.8418] +2024-11-22 20:26:41.699587: Epoch time: 18.9 s +2024-11-22 20:26:42.594715: +2024-11-22 20:26:42.594911: Epoch 6186 +2024-11-22 20:26:42.595027: Current learning rate: 0.00263 +2024-11-22 20:27:01.175009: train_loss -0.8114 +2024-11-22 20:27:01.175237: val_loss -0.7343 +2024-11-22 20:27:01.175312: Pseudo dice [0.8094] +2024-11-22 20:27:01.175395: Epoch time: 18.58 s +2024-11-22 20:27:02.068129: +2024-11-22 20:27:02.068328: Epoch 6187 +2024-11-22 20:27:02.068444: Current learning rate: 0.00263 +2024-11-22 20:27:21.227576: train_loss -0.806 +2024-11-22 20:27:21.227797: val_loss -0.7466 +2024-11-22 20:27:21.227870: Pseudo dice [0.8304] +2024-11-22 20:27:21.227951: Epoch time: 19.16 s +2024-11-22 20:27:22.129858: +2024-11-22 20:27:22.130058: Epoch 6188 +2024-11-22 20:27:22.130173: Current learning rate: 0.00263 +2024-11-22 20:27:40.826684: train_loss -0.8071 +2024-11-22 20:27:40.826906: val_loss -0.7609 +2024-11-22 20:27:40.829141: Pseudo dice [0.8514] +2024-11-22 20:27:40.829229: Epoch time: 18.7 s +2024-11-22 20:27:41.843318: +2024-11-22 20:27:41.843534: Epoch 6189 +2024-11-22 20:27:41.843657: Current learning rate: 0.00263 +2024-11-22 20:28:01.884879: train_loss -0.8043 +2024-11-22 20:28:01.885107: val_loss -0.7624 +2024-11-22 20:28:01.885183: Pseudo dice [0.8417] +2024-11-22 20:28:01.885262: Epoch time: 20.04 s +2024-11-22 20:28:02.797329: +2024-11-22 20:28:02.797526: Epoch 6190 +2024-11-22 20:28:02.797642: Current learning rate: 0.00263 +2024-11-22 20:28:21.799536: train_loss -0.8095 +2024-11-22 20:28:21.799764: val_loss -0.7638 +2024-11-22 20:28:21.799837: Pseudo dice [0.8324] +2024-11-22 20:28:21.799919: Epoch time: 19.0 s +2024-11-22 20:28:22.731030: +2024-11-22 20:28:22.731248: Epoch 6191 +2024-11-22 20:28:22.731359: Current learning rate: 0.00262 +2024-11-22 20:28:40.841312: train_loss -0.8104 +2024-11-22 20:28:40.841524: val_loss -0.7368 +2024-11-22 20:28:40.841598: Pseudo dice [0.8213] +2024-11-22 20:28:40.841674: Epoch time: 18.11 s +2024-11-22 20:28:41.870609: +2024-11-22 20:28:41.870833: Epoch 6192 +2024-11-22 20:28:41.870953: Current learning rate: 0.00262 +2024-11-22 20:28:59.038590: train_loss -0.8131 +2024-11-22 20:28:59.038806: val_loss -0.7811 +2024-11-22 20:28:59.038908: Pseudo dice [0.8451] +2024-11-22 20:28:59.039014: Epoch time: 17.17 s +2024-11-22 20:28:59.947213: +2024-11-22 20:28:59.947417: Epoch 6193 +2024-11-22 20:28:59.947527: Current learning rate: 0.00262 +2024-11-22 20:29:18.391080: train_loss -0.8184 +2024-11-22 20:29:18.391329: val_loss -0.7763 +2024-11-22 20:29:18.391457: Pseudo dice [0.8496] +2024-11-22 20:29:18.391539: Epoch time: 18.44 s +2024-11-22 20:29:19.713945: +2024-11-22 20:29:19.714247: Epoch 6194 +2024-11-22 20:29:19.714359: Current learning rate: 0.00262 +2024-11-22 20:29:37.955028: train_loss -0.8195 +2024-11-22 20:29:37.955260: val_loss -0.7685 +2024-11-22 20:29:37.955334: Pseudo dice [0.8368] +2024-11-22 20:29:37.955413: Epoch time: 18.24 s +2024-11-22 20:29:38.863688: +2024-11-22 20:29:38.863906: Epoch 6195 +2024-11-22 20:29:38.864021: Current learning rate: 0.00262 +2024-11-22 20:29:57.661684: train_loss -0.8146 +2024-11-22 20:29:57.661910: val_loss -0.7664 +2024-11-22 20:29:57.661984: Pseudo dice [0.8283] +2024-11-22 20:29:57.662066: Epoch time: 18.8 s +2024-11-22 20:29:58.566825: +2024-11-22 20:29:58.567038: Epoch 6196 +2024-11-22 20:29:58.567148: Current learning rate: 0.00262 +2024-11-22 20:30:17.056350: train_loss -0.8114 +2024-11-22 20:30:17.056563: val_loss -0.7591 +2024-11-22 20:30:17.056635: Pseudo dice [0.8536] +2024-11-22 20:30:17.056709: Epoch time: 18.49 s +2024-11-22 20:30:18.070046: +2024-11-22 20:30:18.070272: Epoch 6197 +2024-11-22 20:30:18.070392: Current learning rate: 0.00262 +2024-11-22 20:30:36.477200: train_loss -0.8071 +2024-11-22 20:30:36.477442: val_loss -0.7513 +2024-11-22 20:30:36.477516: Pseudo dice [0.8484] +2024-11-22 20:30:36.477603: Epoch time: 18.41 s +2024-11-22 20:30:37.455177: +2024-11-22 20:30:37.455401: Epoch 6198 +2024-11-22 20:30:37.455518: Current learning rate: 0.00261 +2024-11-22 20:30:56.060793: train_loss -0.8182 +2024-11-22 20:30:56.061065: val_loss -0.7673 +2024-11-22 20:30:56.061141: Pseudo dice [0.8467] +2024-11-22 20:30:56.061218: Epoch time: 18.61 s +2024-11-22 20:30:56.955964: +2024-11-22 20:30:56.956197: Epoch 6199 +2024-11-22 20:30:56.956314: Current learning rate: 0.00261 +2024-11-22 20:31:15.495810: train_loss -0.8158 +2024-11-22 20:31:15.499820: val_loss -0.7543 +2024-11-22 20:31:15.499933: Pseudo dice [0.8352] +2024-11-22 20:31:15.500028: Epoch time: 18.54 s +2024-11-22 20:31:16.716135: +2024-11-22 20:31:16.716359: Epoch 6200 +2024-11-22 20:31:16.716473: Current learning rate: 0.00261 +2024-11-22 20:31:34.774807: train_loss -0.808 +2024-11-22 20:31:34.775032: val_loss -0.7582 +2024-11-22 20:31:34.775109: Pseudo dice [0.8297] +2024-11-22 20:31:34.775191: Epoch time: 18.06 s +2024-11-22 20:31:35.679632: +2024-11-22 20:31:35.679823: Epoch 6201 +2024-11-22 20:31:35.679935: Current learning rate: 0.00261 +2024-11-22 20:31:54.932861: train_loss -0.8097 +2024-11-22 20:31:54.933164: val_loss -0.7603 +2024-11-22 20:31:54.933241: Pseudo dice [0.8258] +2024-11-22 20:31:54.933321: Epoch time: 19.25 s +2024-11-22 20:31:55.839428: +2024-11-22 20:31:55.839675: Epoch 6202 +2024-11-22 20:31:55.839787: Current learning rate: 0.00261 +2024-11-22 20:32:14.538241: train_loss -0.8204 +2024-11-22 20:32:14.538451: val_loss -0.7406 +2024-11-22 20:32:14.538527: Pseudo dice [0.8276] +2024-11-22 20:32:14.538605: Epoch time: 18.7 s +2024-11-22 20:32:15.446926: +2024-11-22 20:32:15.447129: Epoch 6203 +2024-11-22 20:32:15.447239: Current learning rate: 0.00261 +2024-11-22 20:32:33.477107: train_loss -0.8079 +2024-11-22 20:32:33.477442: val_loss -0.7695 +2024-11-22 20:32:33.477585: Pseudo dice [0.8221] +2024-11-22 20:32:33.477663: Epoch time: 18.03 s +2024-11-22 20:32:34.384512: +2024-11-22 20:32:34.384762: Epoch 6204 +2024-11-22 20:32:34.384873: Current learning rate: 0.00261 +2024-11-22 20:32:53.120142: train_loss -0.8082 +2024-11-22 20:32:53.120378: val_loss -0.7697 +2024-11-22 20:32:53.120451: Pseudo dice [0.8441] +2024-11-22 20:32:53.120534: Epoch time: 18.74 s +2024-11-22 20:32:54.028696: +2024-11-22 20:32:54.028898: Epoch 6205 +2024-11-22 20:32:54.029016: Current learning rate: 0.00261 +2024-11-22 20:33:12.846542: train_loss -0.8132 +2024-11-22 20:33:12.846766: val_loss -0.7612 +2024-11-22 20:33:12.846848: Pseudo dice [0.8229] +2024-11-22 20:33:12.846928: Epoch time: 18.82 s +2024-11-22 20:33:13.750315: +2024-11-22 20:33:13.750520: Epoch 6206 +2024-11-22 20:33:13.750632: Current learning rate: 0.0026 +2024-11-22 20:33:34.019558: train_loss -0.8131 +2024-11-22 20:33:34.019836: val_loss -0.7678 +2024-11-22 20:33:34.019916: Pseudo dice [0.8354] +2024-11-22 20:33:34.020004: Epoch time: 20.27 s +2024-11-22 20:33:34.929913: +2024-11-22 20:33:34.930105: Epoch 6207 +2024-11-22 20:33:34.930215: Current learning rate: 0.0026 +2024-11-22 20:33:52.394726: train_loss -0.8106 +2024-11-22 20:33:52.394953: val_loss -0.7639 +2024-11-22 20:33:52.395034: Pseudo dice [0.838] +2024-11-22 20:33:52.395117: Epoch time: 17.47 s +2024-11-22 20:33:53.301320: +2024-11-22 20:33:53.301512: Epoch 6208 +2024-11-22 20:33:53.301623: Current learning rate: 0.0026 +2024-11-22 20:34:12.941848: train_loss -0.8142 +2024-11-22 20:34:12.942072: val_loss -0.7425 +2024-11-22 20:34:12.942156: Pseudo dice [0.8269] +2024-11-22 20:34:12.942234: Epoch time: 19.64 s +2024-11-22 20:34:13.865837: +2024-11-22 20:34:13.866046: Epoch 6209 +2024-11-22 20:34:13.866160: Current learning rate: 0.0026 +2024-11-22 20:34:33.248421: train_loss -0.8077 +2024-11-22 20:34:33.251113: val_loss -0.7689 +2024-11-22 20:34:33.251242: Pseudo dice [0.8382] +2024-11-22 20:34:33.251365: Epoch time: 19.38 s +2024-11-22 20:34:34.159235: +2024-11-22 20:34:34.159431: Epoch 6210 +2024-11-22 20:34:34.159542: Current learning rate: 0.0026 +2024-11-22 20:34:52.401327: train_loss -0.8086 +2024-11-22 20:34:52.401536: val_loss -0.7501 +2024-11-22 20:34:52.401611: Pseudo dice [0.8306] +2024-11-22 20:34:52.401683: Epoch time: 18.24 s +2024-11-22 20:34:53.366902: +2024-11-22 20:34:53.367198: Epoch 6211 +2024-11-22 20:34:53.367312: Current learning rate: 0.0026 +2024-11-22 20:35:13.046365: train_loss -0.8055 +2024-11-22 20:35:13.046618: val_loss -0.7398 +2024-11-22 20:35:13.046695: Pseudo dice [0.824] +2024-11-22 20:35:13.046779: Epoch time: 19.68 s +2024-11-22 20:35:13.960838: +2024-11-22 20:35:13.961025: Epoch 6212 +2024-11-22 20:35:13.961158: Current learning rate: 0.0026 +2024-11-22 20:35:32.376276: train_loss -0.8038 +2024-11-22 20:35:32.376486: val_loss -0.7466 +2024-11-22 20:35:32.376561: Pseudo dice [0.8349] +2024-11-22 20:35:32.376637: Epoch time: 18.42 s +2024-11-22 20:35:33.321209: +2024-11-22 20:35:33.321418: Epoch 6213 +2024-11-22 20:35:33.321530: Current learning rate: 0.00259 +2024-11-22 20:35:52.290354: train_loss -0.8043 +2024-11-22 20:35:52.290574: val_loss -0.7134 +2024-11-22 20:35:52.292902: Pseudo dice [0.8069] +2024-11-22 20:35:52.293005: Epoch time: 18.97 s +2024-11-22 20:35:53.367104: +2024-11-22 20:35:53.367300: Epoch 6214 +2024-11-22 20:35:53.367411: Current learning rate: 0.00259 +2024-11-22 20:36:13.035506: train_loss -0.8104 +2024-11-22 20:36:13.035794: val_loss -0.7516 +2024-11-22 20:36:13.035868: Pseudo dice [0.8303] +2024-11-22 20:36:13.035952: Epoch time: 19.67 s +2024-11-22 20:36:13.947904: +2024-11-22 20:36:13.948137: Epoch 6215 +2024-11-22 20:36:13.948246: Current learning rate: 0.00259 +2024-11-22 20:36:33.086840: train_loss -0.8059 +2024-11-22 20:36:33.087080: val_loss -0.7736 +2024-11-22 20:36:33.087157: Pseudo dice [0.8311] +2024-11-22 20:36:33.087239: Epoch time: 19.14 s +2024-11-22 20:36:33.988623: +2024-11-22 20:36:33.988838: Epoch 6216 +2024-11-22 20:36:33.988952: Current learning rate: 0.00259 +2024-11-22 20:36:52.346488: train_loss -0.8094 +2024-11-22 20:36:52.346711: val_loss -0.7646 +2024-11-22 20:36:52.346796: Pseudo dice [0.8404] +2024-11-22 20:36:52.346879: Epoch time: 18.36 s +2024-11-22 20:36:53.618098: +2024-11-22 20:36:53.618305: Epoch 6217 +2024-11-22 20:36:53.618415: Current learning rate: 0.00259 +2024-11-22 20:37:12.440254: train_loss -0.8095 +2024-11-22 20:37:12.440466: val_loss -0.7539 +2024-11-22 20:37:12.440537: Pseudo dice [0.8276] +2024-11-22 20:37:12.440612: Epoch time: 18.82 s +2024-11-22 20:37:13.348081: +2024-11-22 20:37:13.348286: Epoch 6218 +2024-11-22 20:37:13.348397: Current learning rate: 0.00259 +2024-11-22 20:37:31.459848: train_loss -0.8076 +2024-11-22 20:37:31.462262: val_loss -0.7403 +2024-11-22 20:37:31.462368: Pseudo dice [0.8221] +2024-11-22 20:37:31.462456: Epoch time: 18.11 s +2024-11-22 20:37:32.547941: +2024-11-22 20:37:32.548377: Epoch 6219 +2024-11-22 20:37:32.548486: Current learning rate: 0.00259 +2024-11-22 20:37:51.219015: train_loss -0.816 +2024-11-22 20:37:51.219222: val_loss -0.769 +2024-11-22 20:37:51.219297: Pseudo dice [0.8294] +2024-11-22 20:37:51.219373: Epoch time: 18.67 s +2024-11-22 20:37:52.254721: +2024-11-22 20:37:52.255000: Epoch 6220 +2024-11-22 20:37:52.255117: Current learning rate: 0.00259 +2024-11-22 20:38:11.662088: train_loss -0.8091 +2024-11-22 20:38:11.662310: val_loss -0.7126 +2024-11-22 20:38:11.662382: Pseudo dice [0.822] +2024-11-22 20:38:11.662467: Epoch time: 19.41 s +2024-11-22 20:38:12.680477: +2024-11-22 20:38:12.680668: Epoch 6221 +2024-11-22 20:38:12.680777: Current learning rate: 0.00258 +2024-11-22 20:38:31.308339: train_loss -0.815 +2024-11-22 20:38:31.308557: val_loss -0.7791 +2024-11-22 20:38:31.308634: Pseudo dice [0.8392] +2024-11-22 20:38:31.308729: Epoch time: 18.63 s +2024-11-22 20:38:32.246748: +2024-11-22 20:38:32.247012: Epoch 6222 +2024-11-22 20:38:32.247127: Current learning rate: 0.00258 +2024-11-22 20:38:51.451952: train_loss -0.8065 +2024-11-22 20:38:51.452186: val_loss -0.7371 +2024-11-22 20:38:51.452259: Pseudo dice [0.838] +2024-11-22 20:38:51.452341: Epoch time: 19.21 s +2024-11-22 20:38:52.435532: +2024-11-22 20:38:52.435722: Epoch 6223 +2024-11-22 20:38:52.435838: Current learning rate: 0.00258 +2024-11-22 20:39:11.127674: train_loss -0.8112 +2024-11-22 20:39:11.127888: val_loss -0.7453 +2024-11-22 20:39:11.127961: Pseudo dice [0.8418] +2024-11-22 20:39:11.128042: Epoch time: 18.69 s +2024-11-22 20:39:12.139161: +2024-11-22 20:39:12.139356: Epoch 6224 +2024-11-22 20:39:12.139470: Current learning rate: 0.00258 +2024-11-22 20:39:29.851511: train_loss -0.8176 +2024-11-22 20:39:29.851724: val_loss -0.7625 +2024-11-22 20:39:29.851798: Pseudo dice [0.824] +2024-11-22 20:39:29.851872: Epoch time: 17.71 s +2024-11-22 20:39:30.750458: +2024-11-22 20:39:30.750689: Epoch 6225 +2024-11-22 20:39:30.750806: Current learning rate: 0.00258 +2024-11-22 20:39:49.581800: train_loss -0.8152 +2024-11-22 20:39:49.582100: val_loss -0.7727 +2024-11-22 20:39:49.582219: Pseudo dice [0.8409] +2024-11-22 20:39:49.582306: Epoch time: 18.83 s +2024-11-22 20:39:50.511367: +2024-11-22 20:39:50.511586: Epoch 6226 +2024-11-22 20:39:50.511705: Current learning rate: 0.00258 +2024-11-22 20:40:09.157218: train_loss -0.8091 +2024-11-22 20:40:09.157446: val_loss -0.7621 +2024-11-22 20:40:09.157519: Pseudo dice [0.8356] +2024-11-22 20:40:09.157599: Epoch time: 18.65 s +2024-11-22 20:40:10.066174: +2024-11-22 20:40:10.066369: Epoch 6227 +2024-11-22 20:40:10.066481: Current learning rate: 0.00258 +2024-11-22 20:40:29.529109: train_loss -0.81 +2024-11-22 20:40:29.529326: val_loss -0.7575 +2024-11-22 20:40:29.529402: Pseudo dice [0.8434] +2024-11-22 20:40:29.529480: Epoch time: 19.46 s +2024-11-22 20:40:30.432122: +2024-11-22 20:40:30.432332: Epoch 6228 +2024-11-22 20:40:30.432447: Current learning rate: 0.00258 +2024-11-22 20:40:49.398139: train_loss -0.7945 +2024-11-22 20:40:49.398612: val_loss -0.7507 +2024-11-22 20:40:49.398770: Pseudo dice [0.8267] +2024-11-22 20:40:49.398854: Epoch time: 18.97 s +2024-11-22 20:40:50.406447: +2024-11-22 20:40:50.406693: Epoch 6229 +2024-11-22 20:40:50.406806: Current learning rate: 0.00257 +2024-11-22 20:41:09.837398: train_loss -0.795 +2024-11-22 20:41:09.837648: val_loss -0.7424 +2024-11-22 20:41:09.837724: Pseudo dice [0.8293] +2024-11-22 20:41:09.837811: Epoch time: 19.43 s +2024-11-22 20:41:10.871860: +2024-11-22 20:41:10.872161: Epoch 6230 +2024-11-22 20:41:10.872271: Current learning rate: 0.00257 +2024-11-22 20:41:29.419789: train_loss -0.7989 +2024-11-22 20:41:29.420007: val_loss -0.7789 +2024-11-22 20:41:29.420084: Pseudo dice [0.8432] +2024-11-22 20:41:29.420163: Epoch time: 18.55 s +2024-11-22 20:41:30.328372: +2024-11-22 20:41:30.328575: Epoch 6231 +2024-11-22 20:41:30.328685: Current learning rate: 0.00257 +2024-11-22 20:41:49.522682: train_loss -0.7989 +2024-11-22 20:41:49.522902: val_loss -0.7617 +2024-11-22 20:41:49.522988: Pseudo dice [0.8295] +2024-11-22 20:41:49.523743: Epoch time: 19.2 s +2024-11-22 20:41:50.426945: +2024-11-22 20:41:50.427200: Epoch 6232 +2024-11-22 20:41:50.427315: Current learning rate: 0.00257 +2024-11-22 20:42:09.092664: train_loss -0.8061 +2024-11-22 20:42:09.092876: val_loss -0.7616 +2024-11-22 20:42:09.092953: Pseudo dice [0.8267] +2024-11-22 20:42:09.093045: Epoch time: 18.67 s +2024-11-22 20:42:10.006463: +2024-11-22 20:42:10.006691: Epoch 6233 +2024-11-22 20:42:10.006809: Current learning rate: 0.00257 +2024-11-22 20:42:29.748239: train_loss -0.804 +2024-11-22 20:42:29.748472: val_loss -0.7375 +2024-11-22 20:42:29.748549: Pseudo dice [0.8307] +2024-11-22 20:42:29.748630: Epoch time: 19.74 s +2024-11-22 20:42:30.654839: +2024-11-22 20:42:30.655059: Epoch 6234 +2024-11-22 20:42:30.655173: Current learning rate: 0.00257 +2024-11-22 20:42:49.414420: train_loss -0.809 +2024-11-22 20:42:49.414632: val_loss -0.7486 +2024-11-22 20:42:49.414707: Pseudo dice [0.8313] +2024-11-22 20:42:49.414783: Epoch time: 18.76 s +2024-11-22 20:42:50.320395: +2024-11-22 20:42:50.320673: Epoch 6235 +2024-11-22 20:42:50.320791: Current learning rate: 0.00257 +2024-11-22 20:43:08.772289: train_loss -0.8124 +2024-11-22 20:43:08.772524: val_loss -0.7567 +2024-11-22 20:43:08.772600: Pseudo dice [0.8372] +2024-11-22 20:43:08.772675: Epoch time: 18.45 s +2024-11-22 20:43:09.753643: +2024-11-22 20:43:09.753848: Epoch 6236 +2024-11-22 20:43:09.753961: Current learning rate: 0.00256 +2024-11-22 20:43:27.931703: train_loss -0.7988 +2024-11-22 20:43:27.931930: val_loss -0.7357 +2024-11-22 20:43:27.932015: Pseudo dice [0.8292] +2024-11-22 20:43:27.932096: Epoch time: 18.18 s +2024-11-22 20:43:28.844670: +2024-11-22 20:43:28.844875: Epoch 6237 +2024-11-22 20:43:28.844997: Current learning rate: 0.00256 +2024-11-22 20:43:47.953957: train_loss -0.7931 +2024-11-22 20:43:47.954189: val_loss -0.7501 +2024-11-22 20:43:47.954265: Pseudo dice [0.8315] +2024-11-22 20:43:47.954346: Epoch time: 19.11 s +2024-11-22 20:43:48.862239: +2024-11-22 20:43:48.862420: Epoch 6238 +2024-11-22 20:43:48.862530: Current learning rate: 0.00256 +2024-11-22 20:44:07.673671: train_loss -0.7796 +2024-11-22 20:44:07.673897: val_loss -0.7572 +2024-11-22 20:44:07.673973: Pseudo dice [0.8365] +2024-11-22 20:44:07.674058: Epoch time: 18.81 s +2024-11-22 20:44:08.616305: +2024-11-22 20:44:08.616561: Epoch 6239 +2024-11-22 20:44:08.616672: Current learning rate: 0.00256 +2024-11-22 20:44:26.984490: train_loss -0.7927 +2024-11-22 20:44:26.984786: val_loss -0.7469 +2024-11-22 20:44:26.984865: Pseudo dice [0.8272] +2024-11-22 20:44:26.984941: Epoch time: 18.37 s +2024-11-22 20:44:28.259063: +2024-11-22 20:44:28.259265: Epoch 6240 +2024-11-22 20:44:28.259377: Current learning rate: 0.00256 +2024-11-22 20:44:46.771061: train_loss -0.8041 +2024-11-22 20:44:46.771311: val_loss -0.7529 +2024-11-22 20:44:46.771389: Pseudo dice [0.8233] +2024-11-22 20:44:46.771469: Epoch time: 18.51 s +2024-11-22 20:44:47.942681: +2024-11-22 20:44:47.942883: Epoch 6241 +2024-11-22 20:44:47.943004: Current learning rate: 0.00256 +2024-11-22 20:45:06.413300: train_loss -0.8032 +2024-11-22 20:45:06.413514: val_loss -0.7461 +2024-11-22 20:45:06.413618: Pseudo dice [0.8132] +2024-11-22 20:45:06.413694: Epoch time: 18.47 s +2024-11-22 20:45:07.310389: +2024-11-22 20:45:07.310594: Epoch 6242 +2024-11-22 20:45:07.310702: Current learning rate: 0.00256 +2024-11-22 20:45:25.724533: train_loss -0.8098 +2024-11-22 20:45:25.724747: val_loss -0.7679 +2024-11-22 20:45:25.724823: Pseudo dice [0.8453] +2024-11-22 20:45:25.724899: Epoch time: 18.41 s +2024-11-22 20:45:26.632239: +2024-11-22 20:45:26.632442: Epoch 6243 +2024-11-22 20:45:26.632553: Current learning rate: 0.00256 +2024-11-22 20:45:44.727844: train_loss -0.8093 +2024-11-22 20:45:44.728064: val_loss -0.7136 +2024-11-22 20:45:44.728141: Pseudo dice [0.815] +2024-11-22 20:45:44.728224: Epoch time: 18.1 s +2024-11-22 20:45:45.634243: +2024-11-22 20:45:45.634447: Epoch 6244 +2024-11-22 20:45:45.634563: Current learning rate: 0.00255 +2024-11-22 20:46:04.325035: train_loss -0.8143 +2024-11-22 20:46:04.326662: val_loss -0.7687 +2024-11-22 20:46:04.326793: Pseudo dice [0.8501] +2024-11-22 20:46:04.326880: Epoch time: 18.69 s +2024-11-22 20:46:05.409050: +2024-11-22 20:46:05.409259: Epoch 6245 +2024-11-22 20:46:05.409372: Current learning rate: 0.00255 +2024-11-22 20:46:25.110016: train_loss -0.8104 +2024-11-22 20:46:25.110240: val_loss -0.772 +2024-11-22 20:46:25.110313: Pseudo dice [0.8367] +2024-11-22 20:46:25.110388: Epoch time: 19.7 s +2024-11-22 20:46:26.019233: +2024-11-22 20:46:26.019459: Epoch 6246 +2024-11-22 20:46:26.019570: Current learning rate: 0.00255 +2024-11-22 20:46:44.013083: train_loss -0.8086 +2024-11-22 20:46:44.013309: val_loss -0.7633 +2024-11-22 20:46:44.013385: Pseudo dice [0.8308] +2024-11-22 20:46:44.013464: Epoch time: 17.99 s +2024-11-22 20:46:45.085445: +2024-11-22 20:46:45.085667: Epoch 6247 +2024-11-22 20:46:45.085784: Current learning rate: 0.00255 +2024-11-22 20:47:04.122306: train_loss -0.8124 +2024-11-22 20:47:04.122570: val_loss -0.7748 +2024-11-22 20:47:04.122702: Pseudo dice [0.834] +2024-11-22 20:47:04.122788: Epoch time: 19.04 s +2024-11-22 20:47:05.040385: +2024-11-22 20:47:05.040639: Epoch 6248 +2024-11-22 20:47:05.040753: Current learning rate: 0.00255 +2024-11-22 20:47:24.734693: train_loss -0.807 +2024-11-22 20:47:24.734904: val_loss -0.7459 +2024-11-22 20:47:24.737939: Pseudo dice [0.8331] +2024-11-22 20:47:24.738156: Epoch time: 19.7 s +2024-11-22 20:47:25.682718: +2024-11-22 20:47:25.682914: Epoch 6249 +2024-11-22 20:47:25.683028: Current learning rate: 0.00255 +2024-11-22 20:47:44.544345: train_loss -0.8112 +2024-11-22 20:47:44.544613: val_loss -0.7534 +2024-11-22 20:47:44.544687: Pseudo dice [0.824] +2024-11-22 20:47:44.544763: Epoch time: 18.86 s +2024-11-22 20:47:45.756418: +2024-11-22 20:47:45.756615: Epoch 6250 +2024-11-22 20:47:45.756727: Current learning rate: 0.00255 +2024-11-22 20:48:03.607431: train_loss -0.8211 +2024-11-22 20:48:03.607641: val_loss -0.7585 +2024-11-22 20:48:03.607716: Pseudo dice [0.833] +2024-11-22 20:48:03.607793: Epoch time: 17.85 s +2024-11-22 20:48:04.553885: +2024-11-22 20:48:04.554117: Epoch 6251 +2024-11-22 20:48:04.554230: Current learning rate: 0.00255 +2024-11-22 20:48:22.813697: train_loss -0.8077 +2024-11-22 20:48:22.814234: val_loss -0.7834 +2024-11-22 20:48:22.814340: Pseudo dice [0.832] +2024-11-22 20:48:22.814431: Epoch time: 18.26 s +2024-11-22 20:48:23.714764: +2024-11-22 20:48:23.714967: Epoch 6252 +2024-11-22 20:48:23.715081: Current learning rate: 0.00254 +2024-11-22 20:48:43.045648: train_loss -0.8089 +2024-11-22 20:48:43.045864: val_loss -0.7329 +2024-11-22 20:48:43.045937: Pseudo dice [0.8457] +2024-11-22 20:48:43.046033: Epoch time: 19.33 s +2024-11-22 20:48:43.939248: +2024-11-22 20:48:43.939468: Epoch 6253 +2024-11-22 20:48:43.939584: Current learning rate: 0.00254 +2024-11-22 20:49:02.553446: train_loss -0.8123 +2024-11-22 20:49:02.553664: val_loss -0.774 +2024-11-22 20:49:02.553739: Pseudo dice [0.8396] +2024-11-22 20:49:02.553829: Epoch time: 18.61 s +2024-11-22 20:49:03.504129: +2024-11-22 20:49:03.504361: Epoch 6254 +2024-11-22 20:49:03.504475: Current learning rate: 0.00254 +2024-11-22 20:49:22.272323: train_loss -0.8196 +2024-11-22 20:49:22.272554: val_loss -0.7517 +2024-11-22 20:49:22.272631: Pseudo dice [0.8242] +2024-11-22 20:49:22.272713: Epoch time: 18.77 s +2024-11-22 20:49:23.198661: +2024-11-22 20:49:23.198867: Epoch 6255 +2024-11-22 20:49:23.198981: Current learning rate: 0.00254 +2024-11-22 20:49:41.222557: train_loss -0.8091 +2024-11-22 20:49:41.222777: val_loss -0.7284 +2024-11-22 20:49:41.222853: Pseudo dice [0.8237] +2024-11-22 20:49:41.222929: Epoch time: 18.02 s +2024-11-22 20:49:42.130200: +2024-11-22 20:49:42.130446: Epoch 6256 +2024-11-22 20:49:42.130570: Current learning rate: 0.00254 +2024-11-22 20:50:00.182704: train_loss -0.8079 +2024-11-22 20:50:00.182975: val_loss -0.7561 +2024-11-22 20:50:00.183057: Pseudo dice [0.8394] +2024-11-22 20:50:00.183135: Epoch time: 18.05 s +2024-11-22 20:50:01.106663: +2024-11-22 20:50:01.106877: Epoch 6257 +2024-11-22 20:50:01.124667: Current learning rate: 0.00254 +2024-11-22 20:50:20.038045: train_loss -0.8115 +2024-11-22 20:50:20.038350: val_loss -0.7596 +2024-11-22 20:50:20.038426: Pseudo dice [0.8411] +2024-11-22 20:50:20.038502: Epoch time: 18.93 s +2024-11-22 20:50:20.948364: +2024-11-22 20:50:20.948606: Epoch 6258 +2024-11-22 20:50:20.948719: Current learning rate: 0.00254 +2024-11-22 20:50:39.438695: train_loss -0.8137 +2024-11-22 20:50:39.438989: val_loss -0.7496 +2024-11-22 20:50:39.439074: Pseudo dice [0.8259] +2024-11-22 20:50:39.439158: Epoch time: 18.49 s +2024-11-22 20:50:40.349654: +2024-11-22 20:50:40.349871: Epoch 6259 +2024-11-22 20:50:40.349983: Current learning rate: 0.00253 +2024-11-22 20:50:57.919719: train_loss -0.8157 +2024-11-22 20:50:57.919935: val_loss -0.7638 +2024-11-22 20:50:57.920014: Pseudo dice [0.838] +2024-11-22 20:50:57.920087: Epoch time: 17.57 s +2024-11-22 20:50:58.824122: +2024-11-22 20:50:58.824331: Epoch 6260 +2024-11-22 20:50:58.824446: Current learning rate: 0.00253 +2024-11-22 20:51:17.270606: train_loss -0.8093 +2024-11-22 20:51:17.270867: val_loss -0.78 +2024-11-22 20:51:17.270943: Pseudo dice [0.8477] +2024-11-22 20:51:17.271026: Epoch time: 18.45 s +2024-11-22 20:51:18.178647: +2024-11-22 20:51:18.178876: Epoch 6261 +2024-11-22 20:51:18.178998: Current learning rate: 0.00253 +2024-11-22 20:51:37.028850: train_loss -0.8157 +2024-11-22 20:51:37.029075: val_loss -0.7716 +2024-11-22 20:51:37.029153: Pseudo dice [0.8394] +2024-11-22 20:51:37.029234: Epoch time: 18.85 s +2024-11-22 20:51:38.111013: +2024-11-22 20:51:38.111212: Epoch 6262 +2024-11-22 20:51:38.111326: Current learning rate: 0.00253 +2024-11-22 20:51:56.602175: train_loss -0.808 +2024-11-22 20:51:56.602412: val_loss -0.7644 +2024-11-22 20:51:56.602492: Pseudo dice [0.8393] +2024-11-22 20:51:56.602572: Epoch time: 18.49 s +2024-11-22 20:51:57.876760: +2024-11-22 20:51:57.877002: Epoch 6263 +2024-11-22 20:51:57.877123: Current learning rate: 0.00253 +2024-11-22 20:52:16.636517: train_loss -0.8153 +2024-11-22 20:52:16.638900: val_loss -0.7567 +2024-11-22 20:52:16.638996: Pseudo dice [0.8412] +2024-11-22 20:52:16.639078: Epoch time: 18.76 s +2024-11-22 20:52:17.633944: +2024-11-22 20:52:17.634199: Epoch 6264 +2024-11-22 20:52:17.634314: Current learning rate: 0.00253 +2024-11-22 20:52:36.557229: train_loss -0.8001 +2024-11-22 20:52:36.557450: val_loss -0.7643 +2024-11-22 20:52:36.557526: Pseudo dice [0.8172] +2024-11-22 20:52:36.557602: Epoch time: 18.92 s +2024-11-22 20:52:37.459126: +2024-11-22 20:52:37.459355: Epoch 6265 +2024-11-22 20:52:37.459470: Current learning rate: 0.00253 +2024-11-22 20:52:55.503745: train_loss -0.8029 +2024-11-22 20:52:55.504013: val_loss -0.7284 +2024-11-22 20:52:55.504098: Pseudo dice [0.8096] +2024-11-22 20:52:55.504183: Epoch time: 18.05 s +2024-11-22 20:52:56.412603: +2024-11-22 20:52:56.412839: Epoch 6266 +2024-11-22 20:52:56.412954: Current learning rate: 0.00253 +2024-11-22 20:53:16.026966: train_loss -0.7974 +2024-11-22 20:53:16.027520: val_loss -0.7189 +2024-11-22 20:53:16.027631: Pseudo dice [0.8111] +2024-11-22 20:53:16.027718: Epoch time: 19.62 s +2024-11-22 20:53:16.948097: +2024-11-22 20:53:16.948292: Epoch 6267 +2024-11-22 20:53:16.948406: Current learning rate: 0.00252 +2024-11-22 20:53:34.155650: train_loss -0.8024 +2024-11-22 20:53:34.155868: val_loss -0.7655 +2024-11-22 20:53:34.155942: Pseudo dice [0.8329] +2024-11-22 20:53:34.156023: Epoch time: 17.21 s +2024-11-22 20:53:35.078034: +2024-11-22 20:53:35.078276: Epoch 6268 +2024-11-22 20:53:35.078393: Current learning rate: 0.00252 +2024-11-22 20:53:54.634600: train_loss -0.8032 +2024-11-22 20:53:54.634805: val_loss -0.7703 +2024-11-22 20:53:54.634909: Pseudo dice [0.8399] +2024-11-22 20:53:54.635002: Epoch time: 19.56 s +2024-11-22 20:53:55.538505: +2024-11-22 20:53:55.538767: Epoch 6269 +2024-11-22 20:53:55.538887: Current learning rate: 0.00252 +2024-11-22 20:54:13.284973: train_loss -0.7965 +2024-11-22 20:54:13.285211: val_loss -0.738 +2024-11-22 20:54:13.285291: Pseudo dice [0.8114] +2024-11-22 20:54:13.306821: Epoch time: 17.75 s +2024-11-22 20:54:14.217634: +2024-11-22 20:54:14.217832: Epoch 6270 +2024-11-22 20:54:14.217945: Current learning rate: 0.00252 +2024-11-22 20:54:33.904533: train_loss -0.8002 +2024-11-22 20:54:33.904741: val_loss -0.7576 +2024-11-22 20:54:33.904817: Pseudo dice [0.8423] +2024-11-22 20:54:33.904892: Epoch time: 19.69 s +2024-11-22 20:54:34.810923: +2024-11-22 20:54:34.811133: Epoch 6271 +2024-11-22 20:54:34.811249: Current learning rate: 0.00252 +2024-11-22 20:54:53.912957: train_loss -0.7912 +2024-11-22 20:54:53.913184: val_loss -0.7353 +2024-11-22 20:54:53.913258: Pseudo dice [0.8169] +2024-11-22 20:54:53.913332: Epoch time: 19.1 s +2024-11-22 20:54:54.815984: +2024-11-22 20:54:54.816172: Epoch 6272 +2024-11-22 20:54:54.816282: Current learning rate: 0.00252 +2024-11-22 20:55:13.433483: train_loss -0.7908 +2024-11-22 20:55:13.433715: val_loss -0.7532 +2024-11-22 20:55:13.433789: Pseudo dice [0.8372] +2024-11-22 20:55:13.433871: Epoch time: 18.62 s +2024-11-22 20:55:14.453414: +2024-11-22 20:55:14.453680: Epoch 6273 +2024-11-22 20:55:14.453809: Current learning rate: 0.00252 +2024-11-22 20:55:33.037785: train_loss -0.7961 +2024-11-22 20:55:33.038041: val_loss -0.7292 +2024-11-22 20:55:33.038118: Pseudo dice [0.8367] +2024-11-22 20:55:33.038203: Epoch time: 18.59 s +2024-11-22 20:55:33.977499: +2024-11-22 20:55:33.977712: Epoch 6274 +2024-11-22 20:55:33.977860: Current learning rate: 0.00252 +2024-11-22 20:55:52.349771: train_loss -0.794 +2024-11-22 20:55:52.350313: val_loss -0.761 +2024-11-22 20:55:52.350412: Pseudo dice [0.8265] +2024-11-22 20:55:52.350491: Epoch time: 18.37 s +2024-11-22 20:55:53.255765: +2024-11-22 20:55:53.256001: Epoch 6275 +2024-11-22 20:55:53.256121: Current learning rate: 0.00251 +2024-11-22 20:56:11.197752: train_loss -0.7884 +2024-11-22 20:56:11.197978: val_loss -0.7383 +2024-11-22 20:56:11.198057: Pseudo dice [0.8326] +2024-11-22 20:56:11.198132: Epoch time: 17.94 s +2024-11-22 20:56:12.105582: +2024-11-22 20:56:12.105800: Epoch 6276 +2024-11-22 20:56:12.105913: Current learning rate: 0.00251 +2024-11-22 20:56:30.292244: train_loss -0.7949 +2024-11-22 20:56:30.292476: val_loss -0.7325 +2024-11-22 20:56:30.292551: Pseudo dice [0.837] +2024-11-22 20:56:30.292633: Epoch time: 18.19 s +2024-11-22 20:56:31.200138: +2024-11-22 20:56:31.200334: Epoch 6277 +2024-11-22 20:56:31.200443: Current learning rate: 0.00251 +2024-11-22 20:56:50.054014: train_loss -0.804 +2024-11-22 20:56:50.054219: val_loss -0.7212 +2024-11-22 20:56:50.054293: Pseudo dice [0.8183] +2024-11-22 20:56:50.054369: Epoch time: 18.85 s +2024-11-22 20:56:50.957690: +2024-11-22 20:56:50.957939: Epoch 6278 +2024-11-22 20:56:50.958058: Current learning rate: 0.00251 +2024-11-22 20:57:09.202291: train_loss -0.8064 +2024-11-22 20:57:09.206551: val_loss -0.7387 +2024-11-22 20:57:09.206677: Pseudo dice [0.8436] +2024-11-22 20:57:09.206757: Epoch time: 18.25 s +2024-11-22 20:57:10.125266: +2024-11-22 20:57:10.125486: Epoch 6279 +2024-11-22 20:57:10.125604: Current learning rate: 0.00251 +2024-11-22 20:57:28.251748: train_loss -0.8095 +2024-11-22 20:57:28.254119: val_loss -0.7563 +2024-11-22 20:57:28.254209: Pseudo dice [0.8395] +2024-11-22 20:57:28.254286: Epoch time: 18.13 s +2024-11-22 20:57:29.213096: +2024-11-22 20:57:29.213339: Epoch 6280 +2024-11-22 20:57:29.213460: Current learning rate: 0.00251 +2024-11-22 20:57:47.151597: train_loss -0.8048 +2024-11-22 20:57:47.151830: val_loss -0.7825 +2024-11-22 20:57:47.151908: Pseudo dice [0.8386] +2024-11-22 20:57:47.152009: Epoch time: 17.94 s +2024-11-22 20:57:48.087392: +2024-11-22 20:57:48.087615: Epoch 6281 +2024-11-22 20:57:48.087856: Current learning rate: 0.00251 +2024-11-22 20:58:06.980615: train_loss -0.8114 +2024-11-22 20:58:06.980839: val_loss -0.7431 +2024-11-22 20:58:06.980913: Pseudo dice [0.827] +2024-11-22 20:58:06.981003: Epoch time: 18.89 s +2024-11-22 20:58:07.892430: +2024-11-22 20:58:07.892771: Epoch 6282 +2024-11-22 20:58:07.892888: Current learning rate: 0.0025 +2024-11-22 20:58:27.284469: train_loss -0.8006 +2024-11-22 20:58:27.286094: val_loss -0.7766 +2024-11-22 20:58:27.286278: Pseudo dice [0.8431] +2024-11-22 20:58:27.286357: Epoch time: 19.39 s +2024-11-22 20:58:28.198695: +2024-11-22 20:58:28.198921: Epoch 6283 +2024-11-22 20:58:28.199048: Current learning rate: 0.0025 +2024-11-22 20:58:46.274909: train_loss -0.8093 +2024-11-22 20:58:46.275148: val_loss -0.7485 +2024-11-22 20:58:46.275233: Pseudo dice [0.8285] +2024-11-22 20:58:46.275321: Epoch time: 18.08 s +2024-11-22 20:58:47.186295: +2024-11-22 20:58:47.186521: Epoch 6284 +2024-11-22 20:58:47.186639: Current learning rate: 0.0025 +2024-11-22 20:59:06.233881: train_loss -0.8122 +2024-11-22 20:59:06.234121: val_loss -0.7696 +2024-11-22 20:59:06.234195: Pseudo dice [0.8411] +2024-11-22 20:59:06.234276: Epoch time: 19.05 s +2024-11-22 20:59:07.299832: +2024-11-22 20:59:07.300138: Epoch 6285 +2024-11-22 20:59:07.300286: Current learning rate: 0.0025 +2024-11-22 20:59:24.615495: train_loss -0.8113 +2024-11-22 20:59:24.615721: val_loss -0.7768 +2024-11-22 20:59:24.615802: Pseudo dice [0.8443] +2024-11-22 20:59:24.615882: Epoch time: 17.32 s +2024-11-22 20:59:25.900380: +2024-11-22 20:59:25.900643: Epoch 6286 +2024-11-22 20:59:25.900757: Current learning rate: 0.0025 +2024-11-22 20:59:44.945385: train_loss -0.8152 +2024-11-22 20:59:44.945624: val_loss -0.7834 +2024-11-22 20:59:44.945702: Pseudo dice [0.8274] +2024-11-22 20:59:44.945780: Epoch time: 19.05 s +2024-11-22 20:59:45.857338: +2024-11-22 20:59:45.857549: Epoch 6287 +2024-11-22 20:59:45.857663: Current learning rate: 0.0025 +2024-11-22 21:00:04.469785: train_loss -0.8195 +2024-11-22 21:00:04.470026: val_loss -0.7136 +2024-11-22 21:00:04.470103: Pseudo dice [0.8308] +2024-11-22 21:00:04.470184: Epoch time: 18.61 s +2024-11-22 21:00:05.378823: +2024-11-22 21:00:05.379039: Epoch 6288 +2024-11-22 21:00:05.379153: Current learning rate: 0.0025 +2024-11-22 21:00:23.457949: train_loss -0.8134 +2024-11-22 21:00:23.458173: val_loss -0.7773 +2024-11-22 21:00:23.463478: Pseudo dice [0.8554] +2024-11-22 21:00:23.463625: Epoch time: 18.08 s +2024-11-22 21:00:24.453181: +2024-11-22 21:00:24.453515: Epoch 6289 +2024-11-22 21:00:24.453629: Current learning rate: 0.0025 +2024-11-22 21:00:44.008744: train_loss -0.812 +2024-11-22 21:00:44.008965: val_loss -0.7576 +2024-11-22 21:00:44.009053: Pseudo dice [0.8391] +2024-11-22 21:00:44.009132: Epoch time: 19.56 s +2024-11-22 21:00:45.044847: +2024-11-22 21:00:45.045056: Epoch 6290 +2024-11-22 21:00:45.045167: Current learning rate: 0.00249 +2024-11-22 21:01:03.742020: train_loss -0.8112 +2024-11-22 21:01:03.742231: val_loss -0.7401 +2024-11-22 21:01:03.742308: Pseudo dice [0.8427] +2024-11-22 21:01:03.742382: Epoch time: 18.7 s +2024-11-22 21:01:04.645813: +2024-11-22 21:01:04.646006: Epoch 6291 +2024-11-22 21:01:04.646117: Current learning rate: 0.00249 +2024-11-22 21:01:23.525524: train_loss -0.82 +2024-11-22 21:01:23.525760: val_loss -0.7591 +2024-11-22 21:01:23.525836: Pseudo dice [0.8293] +2024-11-22 21:01:23.525919: Epoch time: 18.88 s +2024-11-22 21:01:24.437399: +2024-11-22 21:01:24.437605: Epoch 6292 +2024-11-22 21:01:24.437725: Current learning rate: 0.00249 +2024-11-22 21:01:43.224954: train_loss -0.8066 +2024-11-22 21:01:43.225193: val_loss -0.7552 +2024-11-22 21:01:43.225266: Pseudo dice [0.8333] +2024-11-22 21:01:43.225342: Epoch time: 18.79 s +2024-11-22 21:01:44.134696: +2024-11-22 21:01:44.134901: Epoch 6293 +2024-11-22 21:01:44.135016: Current learning rate: 0.00249 +2024-11-22 21:02:02.118143: train_loss -0.8203 +2024-11-22 21:02:02.118362: val_loss -0.7754 +2024-11-22 21:02:02.118438: Pseudo dice [0.8409] +2024-11-22 21:02:02.118516: Epoch time: 17.98 s +2024-11-22 21:02:03.031434: +2024-11-22 21:02:03.031635: Epoch 6294 +2024-11-22 21:02:03.031748: Current learning rate: 0.00249 +2024-11-22 21:02:21.650714: train_loss -0.8034 +2024-11-22 21:02:21.650944: val_loss -0.7549 +2024-11-22 21:02:21.651026: Pseudo dice [0.8364] +2024-11-22 21:02:21.651105: Epoch time: 18.62 s +2024-11-22 21:02:22.562478: +2024-11-22 21:02:22.562683: Epoch 6295 +2024-11-22 21:02:22.562795: Current learning rate: 0.00249 +2024-11-22 21:02:41.625996: train_loss -0.8134 +2024-11-22 21:02:41.626679: val_loss -0.7533 +2024-11-22 21:02:41.626760: Pseudo dice [0.8323] +2024-11-22 21:02:41.626842: Epoch time: 19.06 s +2024-11-22 21:02:42.535302: +2024-11-22 21:02:42.535521: Epoch 6296 +2024-11-22 21:02:42.535634: Current learning rate: 0.00249 +2024-11-22 21:03:00.423975: train_loss -0.8202 +2024-11-22 21:03:00.424202: val_loss -0.7795 +2024-11-22 21:03:00.424284: Pseudo dice [0.8485] +2024-11-22 21:03:00.424363: Epoch time: 17.89 s +2024-11-22 21:03:01.374608: +2024-11-22 21:03:01.374868: Epoch 6297 +2024-11-22 21:03:01.374984: Current learning rate: 0.00248 +2024-11-22 21:03:20.981071: train_loss -0.8164 +2024-11-22 21:03:20.981687: val_loss -0.7581 +2024-11-22 21:03:20.981763: Pseudo dice [0.824] +2024-11-22 21:03:20.981838: Epoch time: 19.61 s +2024-11-22 21:03:21.881783: +2024-11-22 21:03:21.882004: Epoch 6298 +2024-11-22 21:03:21.882116: Current learning rate: 0.00248 +2024-11-22 21:03:41.074210: train_loss -0.817 +2024-11-22 21:03:41.074448: val_loss -0.7678 +2024-11-22 21:03:41.074524: Pseudo dice [0.8134] +2024-11-22 21:03:41.074607: Epoch time: 19.19 s +2024-11-22 21:03:41.982493: +2024-11-22 21:03:41.982699: Epoch 6299 +2024-11-22 21:03:41.982815: Current learning rate: 0.00248 +2024-11-22 21:04:01.663369: train_loss -0.8037 +2024-11-22 21:04:01.663582: val_loss -0.7324 +2024-11-22 21:04:01.663663: Pseudo dice [0.8277] +2024-11-22 21:04:01.663739: Epoch time: 19.68 s +2024-11-22 21:04:02.874721: +2024-11-22 21:04:02.874930: Epoch 6300 +2024-11-22 21:04:02.875044: Current learning rate: 0.00248 +2024-11-22 21:04:20.974327: train_loss -0.8186 +2024-11-22 21:04:20.974554: val_loss -0.7735 +2024-11-22 21:04:20.974629: Pseudo dice [0.8434] +2024-11-22 21:04:20.976945: Epoch time: 18.1 s +2024-11-22 21:04:21.927792: +2024-11-22 21:04:21.928018: Epoch 6301 +2024-11-22 21:04:21.928138: Current learning rate: 0.00248 +2024-11-22 21:04:40.750091: train_loss -0.8174 +2024-11-22 21:04:40.752725: val_loss -0.7461 +2024-11-22 21:04:40.752843: Pseudo dice [0.8261] +2024-11-22 21:04:40.752930: Epoch time: 18.82 s +2024-11-22 21:04:41.835696: +2024-11-22 21:04:41.835928: Epoch 6302 +2024-11-22 21:04:41.836049: Current learning rate: 0.00248 +2024-11-22 21:05:00.759528: train_loss -0.8089 +2024-11-22 21:05:00.759771: val_loss -0.7581 +2024-11-22 21:05:00.759849: Pseudo dice [0.8434] +2024-11-22 21:05:00.759929: Epoch time: 18.92 s +2024-11-22 21:05:01.773774: +2024-11-22 21:05:01.773969: Epoch 6303 +2024-11-22 21:05:01.774085: Current learning rate: 0.00248 +2024-11-22 21:05:21.144953: train_loss -0.801 +2024-11-22 21:05:21.145168: val_loss -0.7549 +2024-11-22 21:05:21.145245: Pseudo dice [0.8396] +2024-11-22 21:05:21.145323: Epoch time: 19.37 s +2024-11-22 21:05:22.065334: +2024-11-22 21:05:22.065542: Epoch 6304 +2024-11-22 21:05:22.065656: Current learning rate: 0.00248 +2024-11-22 21:05:40.229468: train_loss -0.8141 +2024-11-22 21:05:40.229681: val_loss -0.7601 +2024-11-22 21:05:40.229752: Pseudo dice [0.843] +2024-11-22 21:05:40.229828: Epoch time: 18.16 s +2024-11-22 21:05:41.153836: +2024-11-22 21:05:41.154081: Epoch 6305 +2024-11-22 21:05:41.154201: Current learning rate: 0.00247 +2024-11-22 21:06:01.083947: train_loss -0.8207 +2024-11-22 21:06:01.084188: val_loss -0.7749 +2024-11-22 21:06:01.084264: Pseudo dice [0.8393] +2024-11-22 21:06:01.084382: Epoch time: 19.93 s +2024-11-22 21:06:01.995949: +2024-11-22 21:06:01.996165: Epoch 6306 +2024-11-22 21:06:01.996274: Current learning rate: 0.00247 +2024-11-22 21:06:21.393571: train_loss -0.8205 +2024-11-22 21:06:21.393805: val_loss -0.7727 +2024-11-22 21:06:21.393883: Pseudo dice [0.8403] +2024-11-22 21:06:21.393966: Epoch time: 19.4 s +2024-11-22 21:06:22.299377: +2024-11-22 21:06:22.299682: Epoch 6307 +2024-11-22 21:06:22.299803: Current learning rate: 0.00247 +2024-11-22 21:06:41.138215: train_loss -0.8129 +2024-11-22 21:06:41.138433: val_loss -0.762 +2024-11-22 21:06:41.138509: Pseudo dice [0.8452] +2024-11-22 21:06:41.138586: Epoch time: 18.84 s +2024-11-22 21:06:42.122893: +2024-11-22 21:06:42.123114: Epoch 6308 +2024-11-22 21:06:42.123230: Current learning rate: 0.00247 +2024-11-22 21:07:00.539138: train_loss -0.8144 +2024-11-22 21:07:00.539363: val_loss -0.7844 +2024-11-22 21:07:00.539437: Pseudo dice [0.8465] +2024-11-22 21:07:00.539510: Epoch time: 18.42 s +2024-11-22 21:07:01.830261: +2024-11-22 21:07:01.830470: Epoch 6309 +2024-11-22 21:07:01.830587: Current learning rate: 0.00247 +2024-11-22 21:07:20.953506: train_loss -0.8149 +2024-11-22 21:07:20.953751: val_loss -0.76 +2024-11-22 21:07:20.953849: Pseudo dice [0.8269] +2024-11-22 21:07:20.953950: Epoch time: 19.12 s +2024-11-22 21:07:21.866626: +2024-11-22 21:07:21.866817: Epoch 6310 +2024-11-22 21:07:21.866924: Current learning rate: 0.00247 +2024-11-22 21:07:40.945229: train_loss -0.8203 +2024-11-22 21:07:40.945450: val_loss -0.7597 +2024-11-22 21:07:40.945526: Pseudo dice [0.8298] +2024-11-22 21:07:40.945604: Epoch time: 19.08 s +2024-11-22 21:07:41.880183: +2024-11-22 21:07:41.880408: Epoch 6311 +2024-11-22 21:07:41.880518: Current learning rate: 0.00247 +2024-11-22 21:08:00.608781: train_loss -0.8137 +2024-11-22 21:08:00.609021: val_loss -0.7676 +2024-11-22 21:08:00.609104: Pseudo dice [0.832] +2024-11-22 21:08:00.609186: Epoch time: 18.73 s +2024-11-22 21:08:01.525103: +2024-11-22 21:08:01.525331: Epoch 6312 +2024-11-22 21:08:01.525449: Current learning rate: 0.00247 +2024-11-22 21:08:19.435619: train_loss -0.8142 +2024-11-22 21:08:19.435848: val_loss -0.7414 +2024-11-22 21:08:19.435926: Pseudo dice [0.8111] +2024-11-22 21:08:19.436013: Epoch time: 17.91 s +2024-11-22 21:08:20.348208: +2024-11-22 21:08:20.348422: Epoch 6313 +2024-11-22 21:08:20.348534: Current learning rate: 0.00246 +2024-11-22 21:08:38.895937: train_loss -0.7955 +2024-11-22 21:08:38.896212: val_loss -0.7462 +2024-11-22 21:08:38.896287: Pseudo dice [0.8197] +2024-11-22 21:08:38.896373: Epoch time: 18.55 s +2024-11-22 21:08:39.804332: +2024-11-22 21:08:39.804538: Epoch 6314 +2024-11-22 21:08:39.804657: Current learning rate: 0.00246 +2024-11-22 21:08:58.261624: train_loss -0.7981 +2024-11-22 21:08:58.261847: val_loss -0.7517 +2024-11-22 21:08:58.261922: Pseudo dice [0.8275] +2024-11-22 21:08:58.262005: Epoch time: 18.46 s +2024-11-22 21:08:59.192632: +2024-11-22 21:08:59.192836: Epoch 6315 +2024-11-22 21:08:59.192950: Current learning rate: 0.00246 +2024-11-22 21:09:17.513453: train_loss -0.8028 +2024-11-22 21:09:17.513667: val_loss -0.7785 +2024-11-22 21:09:17.513741: Pseudo dice [0.8467] +2024-11-22 21:09:17.513816: Epoch time: 18.32 s +2024-11-22 21:09:18.418924: +2024-11-22 21:09:18.419168: Epoch 6316 +2024-11-22 21:09:18.419287: Current learning rate: 0.00246 +2024-11-22 21:09:36.750933: train_loss -0.8098 +2024-11-22 21:09:36.751167: val_loss -0.761 +2024-11-22 21:09:36.751245: Pseudo dice [0.8386] +2024-11-22 21:09:36.751348: Epoch time: 18.33 s +2024-11-22 21:09:37.656679: +2024-11-22 21:09:37.656890: Epoch 6317 +2024-11-22 21:09:37.657012: Current learning rate: 0.00246 +2024-11-22 21:09:56.767420: train_loss -0.8115 +2024-11-22 21:09:56.767634: val_loss -0.7665 +2024-11-22 21:09:56.767714: Pseudo dice [0.8248] +2024-11-22 21:09:56.767804: Epoch time: 19.11 s +2024-11-22 21:09:57.840027: +2024-11-22 21:09:57.840256: Epoch 6318 +2024-11-22 21:09:57.840377: Current learning rate: 0.00246 +2024-11-22 21:10:16.052143: train_loss -0.8049 +2024-11-22 21:10:16.052385: val_loss -0.7644 +2024-11-22 21:10:16.052460: Pseudo dice [0.8238] +2024-11-22 21:10:16.052538: Epoch time: 18.21 s +2024-11-22 21:10:16.964960: +2024-11-22 21:10:16.965155: Epoch 6319 +2024-11-22 21:10:16.965271: Current learning rate: 0.00246 +2024-11-22 21:10:34.469977: train_loss -0.8171 +2024-11-22 21:10:34.470246: val_loss -0.7593 +2024-11-22 21:10:34.470330: Pseudo dice [0.8349] +2024-11-22 21:10:34.470410: Epoch time: 17.5 s +2024-11-22 21:10:35.496291: +2024-11-22 21:10:35.496500: Epoch 6320 +2024-11-22 21:10:35.496647: Current learning rate: 0.00245 +2024-11-22 21:10:54.424093: train_loss -0.8035 +2024-11-22 21:10:54.424351: val_loss -0.7716 +2024-11-22 21:10:54.425079: Pseudo dice [0.8355] +2024-11-22 21:10:54.425160: Epoch time: 18.92 s +2024-11-22 21:10:55.356595: +2024-11-22 21:10:55.356882: Epoch 6321 +2024-11-22 21:10:55.357002: Current learning rate: 0.00245 +2024-11-22 21:11:13.892006: train_loss -0.8146 +2024-11-22 21:11:13.892239: val_loss -0.7686 +2024-11-22 21:11:13.892318: Pseudo dice [0.8372] +2024-11-22 21:11:13.892394: Epoch time: 18.54 s +2024-11-22 21:11:15.037922: +2024-11-22 21:11:15.038190: Epoch 6322 +2024-11-22 21:11:15.038303: Current learning rate: 0.00245 +2024-11-22 21:11:33.672199: train_loss -0.8145 +2024-11-22 21:11:33.672430: val_loss -0.7583 +2024-11-22 21:11:33.672506: Pseudo dice [0.8387] +2024-11-22 21:11:33.672589: Epoch time: 18.64 s +2024-11-22 21:11:34.575483: +2024-11-22 21:11:34.575690: Epoch 6323 +2024-11-22 21:11:34.575803: Current learning rate: 0.00245 +2024-11-22 21:11:52.991104: train_loss -0.8156 +2024-11-22 21:11:52.991350: val_loss -0.7622 +2024-11-22 21:11:52.991428: Pseudo dice [0.8378] +2024-11-22 21:11:52.991515: Epoch time: 18.42 s +2024-11-22 21:11:53.901641: +2024-11-22 21:11:53.901927: Epoch 6324 +2024-11-22 21:11:53.902046: Current learning rate: 0.00245 +2024-11-22 21:12:14.437660: train_loss -0.8083 +2024-11-22 21:12:14.437891: val_loss -0.7449 +2024-11-22 21:12:14.437970: Pseudo dice [0.8233] +2024-11-22 21:12:14.438060: Epoch time: 20.54 s +2024-11-22 21:12:15.349534: +2024-11-22 21:12:15.349721: Epoch 6325 +2024-11-22 21:12:15.349830: Current learning rate: 0.00245 +2024-11-22 21:12:33.533194: train_loss -0.8163 +2024-11-22 21:12:33.533415: val_loss -0.7549 +2024-11-22 21:12:33.533489: Pseudo dice [0.809] +2024-11-22 21:12:33.533577: Epoch time: 18.18 s +2024-11-22 21:12:34.575591: +2024-11-22 21:12:34.575784: Epoch 6326 +2024-11-22 21:12:34.575900: Current learning rate: 0.00245 +2024-11-22 21:12:53.000027: train_loss -0.8046 +2024-11-22 21:12:53.000303: val_loss -0.7678 +2024-11-22 21:12:53.000384: Pseudo dice [0.8311] +2024-11-22 21:12:53.000466: Epoch time: 18.43 s +2024-11-22 21:12:53.913295: +2024-11-22 21:12:53.913489: Epoch 6327 +2024-11-22 21:12:53.913612: Current learning rate: 0.00245 +2024-11-22 21:13:13.554296: train_loss -0.8004 +2024-11-22 21:13:13.554537: val_loss -0.7391 +2024-11-22 21:13:13.554636: Pseudo dice [0.8169] +2024-11-22 21:13:13.554731: Epoch time: 19.64 s +2024-11-22 21:13:14.466802: +2024-11-22 21:13:14.467026: Epoch 6328 +2024-11-22 21:13:14.467138: Current learning rate: 0.00244 +2024-11-22 21:13:32.480567: train_loss -0.8101 +2024-11-22 21:13:32.480783: val_loss -0.768 +2024-11-22 21:13:32.480856: Pseudo dice [0.8274] +2024-11-22 21:13:32.480932: Epoch time: 18.01 s +2024-11-22 21:13:33.389612: +2024-11-22 21:13:33.389812: Epoch 6329 +2024-11-22 21:13:33.389924: Current learning rate: 0.00244 +2024-11-22 21:13:51.371173: train_loss -0.8146 +2024-11-22 21:13:51.371397: val_loss -0.7644 +2024-11-22 21:13:51.371475: Pseudo dice [0.8357] +2024-11-22 21:13:51.371562: Epoch time: 17.98 s +2024-11-22 21:13:52.311960: +2024-11-22 21:13:52.312158: Epoch 6330 +2024-11-22 21:13:52.312273: Current learning rate: 0.00244 +2024-11-22 21:14:11.199628: train_loss -0.7993 +2024-11-22 21:14:11.199869: val_loss -0.7334 +2024-11-22 21:14:11.199948: Pseudo dice [0.8235] +2024-11-22 21:14:11.202281: Epoch time: 18.89 s +2024-11-22 21:14:12.151764: +2024-11-22 21:14:12.151980: Epoch 6331 +2024-11-22 21:14:12.152101: Current learning rate: 0.00244 +2024-11-22 21:14:30.511286: train_loss -0.8141 +2024-11-22 21:14:30.511504: val_loss -0.7612 +2024-11-22 21:14:30.511581: Pseudo dice [0.8382] +2024-11-22 21:14:30.513887: Epoch time: 18.36 s +2024-11-22 21:14:31.961889: +2024-11-22 21:14:31.962101: Epoch 6332 +2024-11-22 21:14:31.962213: Current learning rate: 0.00244 +2024-11-22 21:14:50.371554: train_loss -0.8085 +2024-11-22 21:14:50.371861: val_loss -0.7461 +2024-11-22 21:14:50.371948: Pseudo dice [0.8254] +2024-11-22 21:14:50.372034: Epoch time: 18.41 s +2024-11-22 21:14:51.279899: +2024-11-22 21:14:51.280133: Epoch 6333 +2024-11-22 21:14:51.280244: Current learning rate: 0.00244 +2024-11-22 21:15:10.601129: train_loss -0.8119 +2024-11-22 21:15:10.601358: val_loss -0.7674 +2024-11-22 21:15:10.601436: Pseudo dice [0.8406] +2024-11-22 21:15:10.601517: Epoch time: 19.32 s +2024-11-22 21:15:11.526459: +2024-11-22 21:15:11.526700: Epoch 6334 +2024-11-22 21:15:11.526814: Current learning rate: 0.00244 +2024-11-22 21:15:29.614790: train_loss -0.8106 +2024-11-22 21:15:29.615033: val_loss -0.7429 +2024-11-22 21:15:29.615114: Pseudo dice [0.8317] +2024-11-22 21:15:29.615232: Epoch time: 18.09 s +2024-11-22 21:15:30.522263: +2024-11-22 21:15:30.522456: Epoch 6335 +2024-11-22 21:15:30.522568: Current learning rate: 0.00243 +2024-11-22 21:15:51.037884: train_loss -0.8025 +2024-11-22 21:15:51.038110: val_loss -0.7514 +2024-11-22 21:15:51.038184: Pseudo dice [0.8344] +2024-11-22 21:15:51.038262: Epoch time: 20.52 s +2024-11-22 21:15:51.980474: +2024-11-22 21:15:51.980654: Epoch 6336 +2024-11-22 21:15:51.980765: Current learning rate: 0.00243 +2024-11-22 21:16:11.488121: train_loss -0.8092 +2024-11-22 21:16:11.488365: val_loss -0.7702 +2024-11-22 21:16:11.488449: Pseudo dice [0.8389] +2024-11-22 21:16:11.488533: Epoch time: 19.51 s +2024-11-22 21:16:12.399230: +2024-11-22 21:16:12.399422: Epoch 6337 +2024-11-22 21:16:12.399530: Current learning rate: 0.00243 +2024-11-22 21:16:31.633863: train_loss -0.8131 +2024-11-22 21:16:31.634100: val_loss -0.7676 +2024-11-22 21:16:31.639325: Pseudo dice [0.8524] +2024-11-22 21:16:31.639496: Epoch time: 19.24 s +2024-11-22 21:16:32.700273: +2024-11-22 21:16:32.700482: Epoch 6338 +2024-11-22 21:16:32.700593: Current learning rate: 0.00243 +2024-11-22 21:16:52.040096: train_loss -0.8128 +2024-11-22 21:16:52.040334: val_loss -0.7596 +2024-11-22 21:16:52.040411: Pseudo dice [0.8427] +2024-11-22 21:16:52.040498: Epoch time: 19.34 s +2024-11-22 21:16:52.947636: +2024-11-22 21:16:52.947827: Epoch 6339 +2024-11-22 21:16:52.947939: Current learning rate: 0.00243 +2024-11-22 21:17:12.280944: train_loss -0.8117 +2024-11-22 21:17:12.281171: val_loss -0.7638 +2024-11-22 21:17:12.281246: Pseudo dice [0.8357] +2024-11-22 21:17:12.281324: Epoch time: 19.33 s +2024-11-22 21:17:13.236893: +2024-11-22 21:17:13.237090: Epoch 6340 +2024-11-22 21:17:13.237207: Current learning rate: 0.00243 +2024-11-22 21:17:31.167159: train_loss -0.8131 +2024-11-22 21:17:31.167372: val_loss -0.7906 +2024-11-22 21:17:31.167449: Pseudo dice [0.8486] +2024-11-22 21:17:31.167527: Epoch time: 17.93 s +2024-11-22 21:17:32.074260: +2024-11-22 21:17:32.074485: Epoch 6341 +2024-11-22 21:17:32.074621: Current learning rate: 0.00243 +2024-11-22 21:17:50.741104: train_loss -0.8151 +2024-11-22 21:17:50.741341: val_loss -0.7474 +2024-11-22 21:17:50.741417: Pseudo dice [0.8218] +2024-11-22 21:17:50.743690: Epoch time: 18.67 s +2024-11-22 21:17:51.851780: +2024-11-22 21:17:51.852020: Epoch 6342 +2024-11-22 21:17:51.852134: Current learning rate: 0.00243 +2024-11-22 21:18:09.932312: train_loss -0.8127 +2024-11-22 21:18:09.932576: val_loss -0.7705 +2024-11-22 21:18:09.932655: Pseudo dice [0.8477] +2024-11-22 21:18:09.932732: Epoch time: 18.08 s +2024-11-22 21:18:10.841472: +2024-11-22 21:18:10.841669: Epoch 6343 +2024-11-22 21:18:10.841784: Current learning rate: 0.00242 +2024-11-22 21:18:29.240166: train_loss -0.8167 +2024-11-22 21:18:29.240404: val_loss -0.7709 +2024-11-22 21:18:29.240479: Pseudo dice [0.8423] +2024-11-22 21:18:29.240555: Epoch time: 18.4 s +2024-11-22 21:18:30.139935: +2024-11-22 21:18:30.140136: Epoch 6344 +2024-11-22 21:18:30.140249: Current learning rate: 0.00242 +2024-11-22 21:18:50.918439: train_loss -0.8091 +2024-11-22 21:18:50.923869: val_loss -0.7568 +2024-11-22 21:18:50.924004: Pseudo dice [0.8319] +2024-11-22 21:18:50.924105: Epoch time: 20.78 s +2024-11-22 21:18:51.937836: +2024-11-22 21:18:51.938072: Epoch 6345 +2024-11-22 21:18:51.938191: Current learning rate: 0.00242 +2024-11-22 21:19:09.804454: train_loss -0.8174 +2024-11-22 21:19:09.804711: val_loss -0.776 +2024-11-22 21:19:09.804853: Pseudo dice [0.8412] +2024-11-22 21:19:09.804931: Epoch time: 17.87 s +2024-11-22 21:19:10.817117: +2024-11-22 21:19:10.817540: Epoch 6346 +2024-11-22 21:19:10.817652: Current learning rate: 0.00242 +2024-11-22 21:19:29.444875: train_loss -0.8139 +2024-11-22 21:19:29.445106: val_loss -0.7754 +2024-11-22 21:19:29.445180: Pseudo dice [0.8422] +2024-11-22 21:19:29.445257: Epoch time: 18.63 s +2024-11-22 21:19:30.348570: +2024-11-22 21:19:30.348759: Epoch 6347 +2024-11-22 21:19:30.348868: Current learning rate: 0.00242 +2024-11-22 21:19:49.392738: train_loss -0.8164 +2024-11-22 21:19:49.392975: val_loss -0.754 +2024-11-22 21:19:49.393056: Pseudo dice [0.8404] +2024-11-22 21:19:49.393141: Epoch time: 19.04 s +2024-11-22 21:19:50.467381: +2024-11-22 21:19:50.467609: Epoch 6348 +2024-11-22 21:19:50.467730: Current learning rate: 0.00242 +2024-11-22 21:20:09.815385: train_loss -0.8131 +2024-11-22 21:20:09.815605: val_loss -0.7702 +2024-11-22 21:20:09.815679: Pseudo dice [0.8289] +2024-11-22 21:20:09.815753: Epoch time: 19.35 s +2024-11-22 21:20:10.717051: +2024-11-22 21:20:10.717243: Epoch 6349 +2024-11-22 21:20:10.717355: Current learning rate: 0.00242 +2024-11-22 21:20:29.274496: train_loss -0.8129 +2024-11-22 21:20:29.274724: val_loss -0.7282 +2024-11-22 21:20:29.274801: Pseudo dice [0.804] +2024-11-22 21:20:29.274879: Epoch time: 18.56 s +2024-11-22 21:20:30.491609: +2024-11-22 21:20:30.491925: Epoch 6350 +2024-11-22 21:20:30.492043: Current learning rate: 0.00242 +2024-11-22 21:20:49.510942: train_loss -0.819 +2024-11-22 21:20:49.511182: val_loss -0.7701 +2024-11-22 21:20:49.511261: Pseudo dice [0.8438] +2024-11-22 21:20:49.511340: Epoch time: 19.02 s +2024-11-22 21:20:50.459918: +2024-11-22 21:20:50.460142: Epoch 6351 +2024-11-22 21:20:50.460260: Current learning rate: 0.00241 +2024-11-22 21:21:08.516875: train_loss -0.8244 +2024-11-22 21:21:08.517119: val_loss -0.7675 +2024-11-22 21:21:08.517203: Pseudo dice [0.8519] +2024-11-22 21:21:08.517282: Epoch time: 18.06 s +2024-11-22 21:21:09.427174: +2024-11-22 21:21:09.427425: Epoch 6352 +2024-11-22 21:21:09.427540: Current learning rate: 0.00241 +2024-11-22 21:21:27.486394: train_loss -0.8156 +2024-11-22 21:21:27.486628: val_loss -0.7558 +2024-11-22 21:21:27.486705: Pseudo dice [0.8386] +2024-11-22 21:21:27.486783: Epoch time: 18.06 s +2024-11-22 21:21:28.411031: +2024-11-22 21:21:28.411230: Epoch 6353 +2024-11-22 21:21:28.411344: Current learning rate: 0.00241 +2024-11-22 21:21:47.058574: train_loss -0.8079 +2024-11-22 21:21:47.058867: val_loss -0.7624 +2024-11-22 21:21:47.058954: Pseudo dice [0.8369] +2024-11-22 21:21:47.059043: Epoch time: 18.65 s +2024-11-22 21:21:47.966368: +2024-11-22 21:21:47.966607: Epoch 6354 +2024-11-22 21:21:47.966740: Current learning rate: 0.00241 +2024-11-22 21:22:06.857252: train_loss -0.813 +2024-11-22 21:22:06.857493: val_loss -0.7428 +2024-11-22 21:22:06.857568: Pseudo dice [0.8236] +2024-11-22 21:22:06.857650: Epoch time: 18.89 s +2024-11-22 21:22:08.117054: +2024-11-22 21:22:08.117253: Epoch 6355 +2024-11-22 21:22:08.117371: Current learning rate: 0.00241 +2024-11-22 21:22:26.831962: train_loss -0.8036 +2024-11-22 21:22:26.832293: val_loss -0.7565 +2024-11-22 21:22:26.832378: Pseudo dice [0.8285] +2024-11-22 21:22:26.832458: Epoch time: 18.72 s +2024-11-22 21:22:27.743787: +2024-11-22 21:22:27.743985: Epoch 6356 +2024-11-22 21:22:27.744102: Current learning rate: 0.00241 +2024-11-22 21:22:47.354680: train_loss -0.8056 +2024-11-22 21:22:47.354923: val_loss -0.7534 +2024-11-22 21:22:47.355074: Pseudo dice [0.8347] +2024-11-22 21:22:47.355157: Epoch time: 19.61 s +2024-11-22 21:22:48.270303: +2024-11-22 21:22:48.270499: Epoch 6357 +2024-11-22 21:22:48.270614: Current learning rate: 0.00241 +2024-11-22 21:23:05.986293: train_loss -0.8066 +2024-11-22 21:23:05.986523: val_loss -0.7429 +2024-11-22 21:23:05.986603: Pseudo dice [0.8419] +2024-11-22 21:23:05.986683: Epoch time: 17.72 s +2024-11-22 21:23:06.894895: +2024-11-22 21:23:06.895106: Epoch 6358 +2024-11-22 21:23:06.895221: Current learning rate: 0.0024 +2024-11-22 21:23:25.760547: train_loss -0.813 +2024-11-22 21:23:25.760791: val_loss -0.7542 +2024-11-22 21:23:25.760864: Pseudo dice [0.8312] +2024-11-22 21:23:25.774945: Epoch time: 18.87 s +2024-11-22 21:23:26.683197: +2024-11-22 21:23:26.683560: Epoch 6359 +2024-11-22 21:23:26.683676: Current learning rate: 0.0024 +2024-11-22 21:23:44.822961: train_loss -0.8066 +2024-11-22 21:23:44.823190: val_loss -0.7685 +2024-11-22 21:23:44.823271: Pseudo dice [0.8284] +2024-11-22 21:23:44.823356: Epoch time: 18.14 s +2024-11-22 21:23:45.729066: +2024-11-22 21:23:45.729279: Epoch 6360 +2024-11-22 21:23:45.729391: Current learning rate: 0.0024 +2024-11-22 21:24:04.283930: train_loss -0.8181 +2024-11-22 21:24:04.284165: val_loss -0.7645 +2024-11-22 21:24:04.284242: Pseudo dice [0.849] +2024-11-22 21:24:04.284320: Epoch time: 18.56 s +2024-11-22 21:24:05.188323: +2024-11-22 21:24:05.188514: Epoch 6361 +2024-11-22 21:24:05.188629: Current learning rate: 0.0024 +2024-11-22 21:24:24.095164: train_loss -0.8163 +2024-11-22 21:24:24.095499: val_loss -0.7729 +2024-11-22 21:24:24.095583: Pseudo dice [0.8411] +2024-11-22 21:24:24.095684: Epoch time: 18.91 s +2024-11-22 21:24:25.082093: +2024-11-22 21:24:25.082282: Epoch 6362 +2024-11-22 21:24:25.082391: Current learning rate: 0.0024 +2024-11-22 21:24:43.246875: train_loss -0.8107 +2024-11-22 21:24:43.249271: val_loss -0.7636 +2024-11-22 21:24:43.249355: Pseudo dice [0.8134] +2024-11-22 21:24:43.249432: Epoch time: 18.17 s +2024-11-22 21:24:44.361839: +2024-11-22 21:24:44.362040: Epoch 6363 +2024-11-22 21:24:44.362172: Current learning rate: 0.0024 +2024-11-22 21:25:02.351691: train_loss -0.8125 +2024-11-22 21:25:02.351913: val_loss -0.7753 +2024-11-22 21:25:02.351989: Pseudo dice [0.8484] +2024-11-22 21:25:02.352078: Epoch time: 17.99 s +2024-11-22 21:25:03.259577: +2024-11-22 21:25:03.259811: Epoch 6364 +2024-11-22 21:25:03.259926: Current learning rate: 0.0024 +2024-11-22 21:25:21.915248: train_loss -0.8209 +2024-11-22 21:25:21.915526: val_loss -0.753 +2024-11-22 21:25:21.915604: Pseudo dice [0.8201] +2024-11-22 21:25:21.915683: Epoch time: 18.66 s +2024-11-22 21:25:22.931909: +2024-11-22 21:25:22.932105: Epoch 6365 +2024-11-22 21:25:22.932214: Current learning rate: 0.0024 +2024-11-22 21:25:42.557623: train_loss -0.802 +2024-11-22 21:25:42.557859: val_loss -0.734 +2024-11-22 21:25:42.557935: Pseudo dice [0.8136] +2024-11-22 21:25:42.558027: Epoch time: 19.63 s +2024-11-22 21:25:43.637713: +2024-11-22 21:25:43.638024: Epoch 6366 +2024-11-22 21:25:43.638142: Current learning rate: 0.00239 +2024-11-22 21:26:01.591393: train_loss -0.808 +2024-11-22 21:26:01.591651: val_loss -0.7653 +2024-11-22 21:26:01.591728: Pseudo dice [0.8445] +2024-11-22 21:26:01.591814: Epoch time: 17.95 s +2024-11-22 21:26:02.499867: +2024-11-22 21:26:02.500082: Epoch 6367 +2024-11-22 21:26:02.500192: Current learning rate: 0.00239 +2024-11-22 21:26:21.821795: train_loss -0.8132 +2024-11-22 21:26:21.822040: val_loss -0.7557 +2024-11-22 21:26:21.822114: Pseudo dice [0.8518] +2024-11-22 21:26:21.822190: Epoch time: 19.32 s +2024-11-22 21:26:22.727922: +2024-11-22 21:26:22.728124: Epoch 6368 +2024-11-22 21:26:22.728232: Current learning rate: 0.00239 +2024-11-22 21:26:41.423178: train_loss -0.8137 +2024-11-22 21:26:41.423460: val_loss -0.7495 +2024-11-22 21:26:41.423550: Pseudo dice [0.8363] +2024-11-22 21:26:41.428772: Epoch time: 18.7 s +2024-11-22 21:26:42.516239: +2024-11-22 21:26:42.516456: Epoch 6369 +2024-11-22 21:26:42.516568: Current learning rate: 0.00239 +2024-11-22 21:27:02.321531: train_loss -0.8147 +2024-11-22 21:27:02.321765: val_loss -0.7537 +2024-11-22 21:27:02.321845: Pseudo dice [0.8362] +2024-11-22 21:27:02.321944: Epoch time: 19.81 s +2024-11-22 21:27:03.273699: +2024-11-22 21:27:03.273908: Epoch 6370 +2024-11-22 21:27:03.274027: Current learning rate: 0.00239 +2024-11-22 21:27:21.815362: train_loss -0.816 +2024-11-22 21:27:21.815587: val_loss -0.7513 +2024-11-22 21:27:21.815662: Pseudo dice [0.8264] +2024-11-22 21:27:21.815744: Epoch time: 18.54 s +2024-11-22 21:27:22.724622: +2024-11-22 21:27:22.724885: Epoch 6371 +2024-11-22 21:27:22.725005: Current learning rate: 0.00239 +2024-11-22 21:27:42.291356: train_loss -0.8048 +2024-11-22 21:27:42.316771: val_loss -0.7463 +2024-11-22 21:27:42.316926: Pseudo dice [0.83] +2024-11-22 21:27:42.317019: Epoch time: 19.57 s +2024-11-22 21:27:43.222724: +2024-11-22 21:27:43.222912: Epoch 6372 +2024-11-22 21:27:43.223034: Current learning rate: 0.00239 +2024-11-22 21:28:01.879253: train_loss -0.8091 +2024-11-22 21:28:01.879487: val_loss -0.7609 +2024-11-22 21:28:01.879561: Pseudo dice [0.8382] +2024-11-22 21:28:01.879668: Epoch time: 18.66 s +2024-11-22 21:28:02.787181: +2024-11-22 21:28:02.787389: Epoch 6373 +2024-11-22 21:28:02.787506: Current learning rate: 0.00238 +2024-11-22 21:28:20.907876: train_loss -0.8134 +2024-11-22 21:28:20.908104: val_loss -0.762 +2024-11-22 21:28:20.908183: Pseudo dice [0.8336] +2024-11-22 21:28:20.908262: Epoch time: 18.12 s +2024-11-22 21:28:21.822999: +2024-11-22 21:28:21.823207: Epoch 6374 +2024-11-22 21:28:21.823325: Current learning rate: 0.00238 +2024-11-22 21:28:39.974981: train_loss -0.8106 +2024-11-22 21:28:39.975212: val_loss -0.7333 +2024-11-22 21:28:39.975286: Pseudo dice [0.8396] +2024-11-22 21:28:39.975360: Epoch time: 18.15 s +2024-11-22 21:28:40.907437: +2024-11-22 21:28:40.907649: Epoch 6375 +2024-11-22 21:28:40.907760: Current learning rate: 0.00238 +2024-11-22 21:28:59.973839: train_loss -0.8094 +2024-11-22 21:28:59.974070: val_loss -0.7646 +2024-11-22 21:28:59.974148: Pseudo dice [0.8261] +2024-11-22 21:28:59.974225: Epoch time: 19.07 s +2024-11-22 21:29:00.882622: +2024-11-22 21:29:00.882819: Epoch 6376 +2024-11-22 21:29:00.882936: Current learning rate: 0.00238 +2024-11-22 21:29:18.842671: train_loss -0.8155 +2024-11-22 21:29:18.842910: val_loss -0.7576 +2024-11-22 21:29:18.842981: Pseudo dice [0.8226] +2024-11-22 21:29:18.843092: Epoch time: 17.96 s +2024-11-22 21:29:19.758814: +2024-11-22 21:29:19.759026: Epoch 6377 +2024-11-22 21:29:19.759138: Current learning rate: 0.00238 +2024-11-22 21:29:38.549908: train_loss -0.8132 +2024-11-22 21:29:38.550180: val_loss -0.7639 +2024-11-22 21:29:38.550255: Pseudo dice [0.8441] +2024-11-22 21:29:38.550332: Epoch time: 18.79 s +2024-11-22 21:29:39.821478: +2024-11-22 21:29:39.821676: Epoch 6378 +2024-11-22 21:29:39.821793: Current learning rate: 0.00238 +2024-11-22 21:29:58.756860: train_loss -0.816 +2024-11-22 21:29:58.757093: val_loss -0.7733 +2024-11-22 21:29:58.757169: Pseudo dice [0.8375] +2024-11-22 21:29:58.757246: Epoch time: 18.94 s +2024-11-22 21:29:59.672868: +2024-11-22 21:29:59.673126: Epoch 6379 +2024-11-22 21:29:59.673241: Current learning rate: 0.00238 +2024-11-22 21:30:18.676751: train_loss -0.818 +2024-11-22 21:30:18.676962: val_loss -0.7641 +2024-11-22 21:30:18.677044: Pseudo dice [0.8296] +2024-11-22 21:30:18.677119: Epoch time: 19.0 s +2024-11-22 21:30:19.591388: +2024-11-22 21:30:19.591614: Epoch 6380 +2024-11-22 21:30:19.591728: Current learning rate: 0.00238 +2024-11-22 21:30:37.900433: train_loss -0.8161 +2024-11-22 21:30:37.900671: val_loss -0.7562 +2024-11-22 21:30:37.900793: Pseudo dice [0.8379] +2024-11-22 21:30:37.900878: Epoch time: 18.31 s +2024-11-22 21:30:38.814438: +2024-11-22 21:30:38.814632: Epoch 6381 +2024-11-22 21:30:38.814751: Current learning rate: 0.00237 +2024-11-22 21:30:57.591907: train_loss -0.8121 +2024-11-22 21:30:57.592131: val_loss -0.7698 +2024-11-22 21:30:57.592204: Pseudo dice [0.8386] +2024-11-22 21:30:57.592280: Epoch time: 18.78 s +2024-11-22 21:30:58.508961: +2024-11-22 21:30:58.509154: Epoch 6382 +2024-11-22 21:30:58.509262: Current learning rate: 0.00237 +2024-11-22 21:31:16.468164: train_loss -0.8137 +2024-11-22 21:31:16.468385: val_loss -0.7504 +2024-11-22 21:31:16.468462: Pseudo dice [0.8271] +2024-11-22 21:31:16.468539: Epoch time: 17.96 s +2024-11-22 21:31:17.460755: +2024-11-22 21:31:17.460968: Epoch 6383 +2024-11-22 21:31:17.461087: Current learning rate: 0.00237 +2024-11-22 21:31:37.036817: train_loss -0.8091 +2024-11-22 21:31:37.037067: val_loss -0.7543 +2024-11-22 21:31:37.037150: Pseudo dice [0.8284] +2024-11-22 21:31:37.037235: Epoch time: 19.58 s +2024-11-22 21:31:37.953363: +2024-11-22 21:31:37.953608: Epoch 6384 +2024-11-22 21:31:37.953719: Current learning rate: 0.00237 +2024-11-22 21:31:55.824066: train_loss -0.8155 +2024-11-22 21:31:55.824287: val_loss -0.7674 +2024-11-22 21:31:55.824362: Pseudo dice [0.8374] +2024-11-22 21:31:55.824610: Epoch time: 17.87 s +2024-11-22 21:31:56.789952: +2024-11-22 21:31:56.790244: Epoch 6385 +2024-11-22 21:31:56.790355: Current learning rate: 0.00237 +2024-11-22 21:32:15.457037: train_loss -0.8222 +2024-11-22 21:32:15.457819: val_loss -0.7646 +2024-11-22 21:32:15.457996: Pseudo dice [0.8429] +2024-11-22 21:32:15.458177: Epoch time: 18.67 s +2024-11-22 21:32:16.367476: +2024-11-22 21:32:16.367681: Epoch 6386 +2024-11-22 21:32:16.367802: Current learning rate: 0.00237 +2024-11-22 21:32:35.573301: train_loss -0.8209 +2024-11-22 21:32:35.573534: val_loss -0.7873 +2024-11-22 21:32:35.573613: Pseudo dice [0.8598] +2024-11-22 21:32:35.573697: Epoch time: 19.21 s +2024-11-22 21:32:36.491652: +2024-11-22 21:32:36.491870: Epoch 6387 +2024-11-22 21:32:36.491983: Current learning rate: 0.00237 +2024-11-22 21:32:53.853478: train_loss -0.8169 +2024-11-22 21:32:53.853760: val_loss -0.7632 +2024-11-22 21:32:53.853849: Pseudo dice [0.8353] +2024-11-22 21:32:53.853937: Epoch time: 17.36 s +2024-11-22 21:32:54.765556: +2024-11-22 21:32:54.765759: Epoch 6388 +2024-11-22 21:32:54.765872: Current learning rate: 0.00237 +2024-11-22 21:33:13.832730: train_loss -0.8165 +2024-11-22 21:33:13.832941: val_loss -0.7579 +2024-11-22 21:33:13.833021: Pseudo dice [0.824] +2024-11-22 21:33:13.833100: Epoch time: 19.07 s +2024-11-22 21:33:14.746434: +2024-11-22 21:33:14.746641: Epoch 6389 +2024-11-22 21:33:14.746755: Current learning rate: 0.00236 +2024-11-22 21:33:32.939038: train_loss -0.8127 +2024-11-22 21:33:32.939259: val_loss -0.7682 +2024-11-22 21:33:32.939335: Pseudo dice [0.8481] +2024-11-22 21:33:32.939413: Epoch time: 18.19 s +2024-11-22 21:33:33.949015: +2024-11-22 21:33:33.949215: Epoch 6390 +2024-11-22 21:33:33.949326: Current learning rate: 0.00236 +2024-11-22 21:33:53.131008: train_loss -0.813 +2024-11-22 21:33:53.131241: val_loss -0.7459 +2024-11-22 21:33:53.131322: Pseudo dice [0.8345] +2024-11-22 21:33:53.131411: Epoch time: 19.18 s +2024-11-22 21:33:54.038710: +2024-11-22 21:33:54.039000: Epoch 6391 +2024-11-22 21:33:54.039119: Current learning rate: 0.00236 +2024-11-22 21:34:12.437974: train_loss -0.8208 +2024-11-22 21:34:12.438189: val_loss -0.754 +2024-11-22 21:34:12.438284: Pseudo dice [0.8364] +2024-11-22 21:34:12.438362: Epoch time: 18.4 s +2024-11-22 21:34:13.348254: +2024-11-22 21:34:13.348472: Epoch 6392 +2024-11-22 21:34:13.348582: Current learning rate: 0.00236 +2024-11-22 21:34:31.873561: train_loss -0.8129 +2024-11-22 21:34:31.873788: val_loss -0.726 +2024-11-22 21:34:31.873860: Pseudo dice [0.8193] +2024-11-22 21:34:31.873938: Epoch time: 18.53 s +2024-11-22 21:34:32.786845: +2024-11-22 21:34:32.787051: Epoch 6393 +2024-11-22 21:34:32.787179: Current learning rate: 0.00236 +2024-11-22 21:34:50.739302: train_loss -0.8105 +2024-11-22 21:34:50.739507: val_loss -0.7172 +2024-11-22 21:34:50.739587: Pseudo dice [0.8132] +2024-11-22 21:34:50.739666: Epoch time: 17.95 s +2024-11-22 21:34:51.664912: +2024-11-22 21:34:51.665175: Epoch 6394 +2024-11-22 21:34:51.665291: Current learning rate: 0.00236 +2024-11-22 21:35:10.192598: train_loss -0.8132 +2024-11-22 21:35:10.192896: val_loss -0.765 +2024-11-22 21:35:10.192973: Pseudo dice [0.8401] +2024-11-22 21:35:10.193060: Epoch time: 18.53 s +2024-11-22 21:35:11.247797: +2024-11-22 21:35:11.248003: Epoch 6395 +2024-11-22 21:35:11.248121: Current learning rate: 0.00236 +2024-11-22 21:35:29.945318: train_loss -0.8196 +2024-11-22 21:35:29.945536: val_loss -0.7522 +2024-11-22 21:35:29.945612: Pseudo dice [0.8214] +2024-11-22 21:35:29.945691: Epoch time: 18.7 s +2024-11-22 21:35:30.855707: +2024-11-22 21:35:30.855912: Epoch 6396 +2024-11-22 21:35:30.856030: Current learning rate: 0.00235 +2024-11-22 21:35:49.093342: train_loss -0.811 +2024-11-22 21:35:49.093554: val_loss -0.7484 +2024-11-22 21:35:49.093628: Pseudo dice [0.8169] +2024-11-22 21:35:49.096107: Epoch time: 18.24 s +2024-11-22 21:35:50.261809: +2024-11-22 21:35:50.262002: Epoch 6397 +2024-11-22 21:35:50.262114: Current learning rate: 0.00235 +2024-11-22 21:36:08.803116: train_loss -0.7997 +2024-11-22 21:36:08.803360: val_loss -0.7461 +2024-11-22 21:36:08.803434: Pseudo dice [0.8301] +2024-11-22 21:36:08.803519: Epoch time: 18.54 s +2024-11-22 21:36:09.721442: +2024-11-22 21:36:09.721658: Epoch 6398 +2024-11-22 21:36:09.721777: Current learning rate: 0.00235 +2024-11-22 21:36:28.355198: train_loss -0.8184 +2024-11-22 21:36:28.355420: val_loss -0.7476 +2024-11-22 21:36:28.355494: Pseudo dice [0.8331] +2024-11-22 21:36:28.355569: Epoch time: 18.63 s +2024-11-22 21:36:29.430308: +2024-11-22 21:36:29.430495: Epoch 6399 +2024-11-22 21:36:29.430608: Current learning rate: 0.00235 +2024-11-22 21:36:48.334805: train_loss -0.8147 +2024-11-22 21:36:48.335040: val_loss -0.7656 +2024-11-22 21:36:48.335117: Pseudo dice [0.84] +2024-11-22 21:36:48.335193: Epoch time: 18.91 s +2024-11-22 21:36:49.540728: +2024-11-22 21:36:49.540962: Epoch 6400 +2024-11-22 21:36:49.541087: Current learning rate: 0.00235 +2024-11-22 21:37:08.675849: train_loss -0.8061 +2024-11-22 21:37:08.681507: val_loss -0.7612 +2024-11-22 21:37:08.681614: Pseudo dice [0.8494] +2024-11-22 21:37:08.681696: Epoch time: 19.14 s +2024-11-22 21:37:09.918746: +2024-11-22 21:37:09.918949: Epoch 6401 +2024-11-22 21:37:09.919068: Current learning rate: 0.00235 +2024-11-22 21:37:28.007621: train_loss -0.8104 +2024-11-22 21:37:28.007856: val_loss -0.7586 +2024-11-22 21:37:28.007932: Pseudo dice [0.8411] +2024-11-22 21:37:28.008019: Epoch time: 18.09 s +2024-11-22 21:37:28.917524: +2024-11-22 21:37:28.917731: Epoch 6402 +2024-11-22 21:37:28.917846: Current learning rate: 0.00235 +2024-11-22 21:37:48.030611: train_loss -0.8118 +2024-11-22 21:37:48.030824: val_loss -0.7644 +2024-11-22 21:37:48.030900: Pseudo dice [0.8466] +2024-11-22 21:37:48.030977: Epoch time: 19.11 s +2024-11-22 21:37:48.939651: +2024-11-22 21:37:48.939856: Epoch 6403 +2024-11-22 21:37:48.939968: Current learning rate: 0.00235 +2024-11-22 21:38:07.145911: train_loss -0.8161 +2024-11-22 21:38:07.146134: val_loss -0.7607 +2024-11-22 21:38:07.146238: Pseudo dice [0.8349] +2024-11-22 21:38:07.146369: Epoch time: 18.21 s +2024-11-22 21:38:08.054126: +2024-11-22 21:38:08.054329: Epoch 6404 +2024-11-22 21:38:08.054442: Current learning rate: 0.00234 +2024-11-22 21:38:27.575535: train_loss -0.8136 +2024-11-22 21:38:27.575769: val_loss -0.7777 +2024-11-22 21:38:27.575851: Pseudo dice [0.8503] +2024-11-22 21:38:27.575942: Epoch time: 19.52 s +2024-11-22 21:38:28.499576: +2024-11-22 21:38:28.499784: Epoch 6405 +2024-11-22 21:38:28.499911: Current learning rate: 0.00234 +2024-11-22 21:38:48.037504: train_loss -0.8159 +2024-11-22 21:38:48.037719: val_loss -0.7484 +2024-11-22 21:38:48.037795: Pseudo dice [0.8323] +2024-11-22 21:38:48.037874: Epoch time: 19.54 s +2024-11-22 21:38:48.947896: +2024-11-22 21:38:48.948109: Epoch 6406 +2024-11-22 21:38:48.948221: Current learning rate: 0.00234 +2024-11-22 21:39:07.438665: train_loss -0.8134 +2024-11-22 21:39:07.438879: val_loss -0.7561 +2024-11-22 21:39:07.438952: Pseudo dice [0.8325] +2024-11-22 21:39:07.439035: Epoch time: 18.49 s +2024-11-22 21:39:08.341754: +2024-11-22 21:39:08.341967: Epoch 6407 +2024-11-22 21:39:08.342094: Current learning rate: 0.00234 +2024-11-22 21:39:26.415764: train_loss -0.8239 +2024-11-22 21:39:26.415979: val_loss -0.7713 +2024-11-22 21:39:26.416058: Pseudo dice [0.8265] +2024-11-22 21:39:26.421278: Epoch time: 18.07 s +2024-11-22 21:39:27.419789: +2024-11-22 21:39:27.419984: Epoch 6408 +2024-11-22 21:39:27.420104: Current learning rate: 0.00234 +2024-11-22 21:39:46.211216: train_loss -0.8155 +2024-11-22 21:39:46.211449: val_loss -0.7751 +2024-11-22 21:39:46.211529: Pseudo dice [0.8366] +2024-11-22 21:39:46.211612: Epoch time: 18.79 s +2024-11-22 21:39:47.118661: +2024-11-22 21:39:47.118854: Epoch 6409 +2024-11-22 21:39:47.118963: Current learning rate: 0.00234 +2024-11-22 21:40:05.562500: train_loss -0.8218 +2024-11-22 21:40:05.563180: val_loss -0.7476 +2024-11-22 21:40:05.563295: Pseudo dice [0.8223] +2024-11-22 21:40:05.563376: Epoch time: 18.44 s +2024-11-22 21:40:06.467366: +2024-11-22 21:40:06.467569: Epoch 6410 +2024-11-22 21:40:06.467683: Current learning rate: 0.00234 +2024-11-22 21:40:24.443322: train_loss -0.8101 +2024-11-22 21:40:24.443537: val_loss -0.7494 +2024-11-22 21:40:24.443613: Pseudo dice [0.8437] +2024-11-22 21:40:24.443791: Epoch time: 17.98 s +2024-11-22 21:40:25.359724: +2024-11-22 21:40:25.359929: Epoch 6411 +2024-11-22 21:40:25.360044: Current learning rate: 0.00233 +2024-11-22 21:40:44.895520: train_loss -0.8123 +2024-11-22 21:40:44.895775: val_loss -0.7274 +2024-11-22 21:40:44.895852: Pseudo dice [0.8323] +2024-11-22 21:40:44.895936: Epoch time: 19.54 s +2024-11-22 21:40:46.148571: +2024-11-22 21:40:46.148773: Epoch 6412 +2024-11-22 21:40:46.148885: Current learning rate: 0.00233 +2024-11-22 21:41:04.353446: train_loss -0.8096 +2024-11-22 21:41:04.353677: val_loss -0.7562 +2024-11-22 21:41:04.353757: Pseudo dice [0.8291] +2024-11-22 21:41:04.353834: Epoch time: 18.21 s +2024-11-22 21:41:05.493566: +2024-11-22 21:41:05.493792: Epoch 6413 +2024-11-22 21:41:05.493903: Current learning rate: 0.00233 +2024-11-22 21:41:24.104368: train_loss -0.8162 +2024-11-22 21:41:24.104602: val_loss -0.7515 +2024-11-22 21:41:24.104678: Pseudo dice [0.8533] +2024-11-22 21:41:24.104758: Epoch time: 18.61 s +2024-11-22 21:41:25.009387: +2024-11-22 21:41:25.009606: Epoch 6414 +2024-11-22 21:41:25.009712: Current learning rate: 0.00233 +2024-11-22 21:41:43.175620: train_loss -0.8138 +2024-11-22 21:41:43.175864: val_loss -0.7486 +2024-11-22 21:41:43.175942: Pseudo dice [0.8397] +2024-11-22 21:41:43.176040: Epoch time: 18.17 s +2024-11-22 21:41:44.089572: +2024-11-22 21:41:44.089802: Epoch 6415 +2024-11-22 21:41:44.089907: Current learning rate: 0.00233 +2024-11-22 21:42:02.659490: train_loss -0.8195 +2024-11-22 21:42:02.659705: val_loss -0.7324 +2024-11-22 21:42:02.659780: Pseudo dice [0.8393] +2024-11-22 21:42:02.659919: Epoch time: 18.57 s +2024-11-22 21:42:03.596215: +2024-11-22 21:42:03.596519: Epoch 6416 +2024-11-22 21:42:03.596635: Current learning rate: 0.00233 +2024-11-22 21:42:22.766711: train_loss -0.8234 +2024-11-22 21:42:22.766922: val_loss -0.7559 +2024-11-22 21:42:22.767002: Pseudo dice [0.8481] +2024-11-22 21:42:22.767078: Epoch time: 19.17 s +2024-11-22 21:42:23.680709: +2024-11-22 21:42:23.680906: Epoch 6417 +2024-11-22 21:42:23.681022: Current learning rate: 0.00233 +2024-11-22 21:42:42.464912: train_loss -0.8127 +2024-11-22 21:42:42.465128: val_loss -0.7539 +2024-11-22 21:42:42.465202: Pseudo dice [0.8448] +2024-11-22 21:42:42.465278: Epoch time: 18.78 s +2024-11-22 21:42:43.417302: +2024-11-22 21:42:43.417509: Epoch 6418 +2024-11-22 21:42:43.417619: Current learning rate: 0.00233 +2024-11-22 21:43:01.474240: train_loss -0.8221 +2024-11-22 21:43:01.474473: val_loss -0.763 +2024-11-22 21:43:01.474544: Pseudo dice [0.8502] +2024-11-22 21:43:01.474623: Epoch time: 18.06 s +2024-11-22 21:43:01.474685: Yayy! New best EMA pseudo Dice: 0.8397 +2024-11-22 21:43:02.703453: +2024-11-22 21:43:02.703668: Epoch 6419 +2024-11-22 21:43:02.703780: Current learning rate: 0.00232 +2024-11-22 21:43:21.328616: train_loss -0.8133 +2024-11-22 21:43:21.328849: val_loss -0.7643 +2024-11-22 21:43:21.328927: Pseudo dice [0.8307] +2024-11-22 21:43:21.329011: Epoch time: 18.63 s +2024-11-22 21:43:22.430675: +2024-11-22 21:43:22.430891: Epoch 6420 +2024-11-22 21:43:22.431010: Current learning rate: 0.00232 +2024-11-22 21:43:40.744624: train_loss -0.8112 +2024-11-22 21:43:40.744847: val_loss -0.7725 +2024-11-22 21:43:40.744923: Pseudo dice [0.8386] +2024-11-22 21:43:40.745006: Epoch time: 18.31 s +2024-11-22 21:43:41.656923: +2024-11-22 21:43:41.657140: Epoch 6421 +2024-11-22 21:43:41.657252: Current learning rate: 0.00232 +2024-11-22 21:44:00.945908: train_loss -0.8101 +2024-11-22 21:44:00.946155: val_loss -0.7566 +2024-11-22 21:44:00.946247: Pseudo dice [0.8298] +2024-11-22 21:44:00.946337: Epoch time: 19.29 s +2024-11-22 21:44:01.877118: +2024-11-22 21:44:01.877326: Epoch 6422 +2024-11-22 21:44:01.877443: Current learning rate: 0.00232 +2024-11-22 21:44:21.201828: train_loss -0.8078 +2024-11-22 21:44:21.202044: val_loss -0.7715 +2024-11-22 21:44:21.202176: Pseudo dice [0.8393] +2024-11-22 21:44:21.202256: Epoch time: 19.33 s +2024-11-22 21:44:22.111306: +2024-11-22 21:44:22.111507: Epoch 6423 +2024-11-22 21:44:22.111620: Current learning rate: 0.00232 +2024-11-22 21:44:39.817231: train_loss -0.8077 +2024-11-22 21:44:39.817455: val_loss -0.7543 +2024-11-22 21:44:39.817528: Pseudo dice [0.8203] +2024-11-22 21:44:39.817602: Epoch time: 17.71 s +2024-11-22 21:44:40.735733: +2024-11-22 21:44:40.735951: Epoch 6424 +2024-11-22 21:44:40.736074: Current learning rate: 0.00232 +2024-11-22 21:45:00.502295: train_loss -0.8094 +2024-11-22 21:45:00.502544: val_loss -0.7753 +2024-11-22 21:45:00.502620: Pseudo dice [0.827] +2024-11-22 21:45:00.502700: Epoch time: 19.77 s +2024-11-22 21:45:01.419105: +2024-11-22 21:45:01.419315: Epoch 6425 +2024-11-22 21:45:01.419427: Current learning rate: 0.00232 +2024-11-22 21:45:20.162613: train_loss -0.8137 +2024-11-22 21:45:20.162827: val_loss -0.7798 +2024-11-22 21:45:20.162901: Pseudo dice [0.8516] +2024-11-22 21:45:20.162978: Epoch time: 18.74 s +2024-11-22 21:45:21.077121: +2024-11-22 21:45:21.077347: Epoch 6426 +2024-11-22 21:45:21.077464: Current learning rate: 0.00231 +2024-11-22 21:45:39.599934: train_loss -0.8136 +2024-11-22 21:45:39.600159: val_loss -0.7372 +2024-11-22 21:45:39.600231: Pseudo dice [0.8322] +2024-11-22 21:45:39.600309: Epoch time: 18.52 s +2024-11-22 21:45:40.576955: +2024-11-22 21:45:40.577211: Epoch 6427 +2024-11-22 21:45:40.577339: Current learning rate: 0.00231 +2024-11-22 21:46:00.375814: train_loss -0.8087 +2024-11-22 21:46:00.376044: val_loss -0.7628 +2024-11-22 21:46:00.376122: Pseudo dice [0.8407] +2024-11-22 21:46:00.376202: Epoch time: 19.8 s +2024-11-22 21:46:01.287256: +2024-11-22 21:46:01.287471: Epoch 6428 +2024-11-22 21:46:01.287585: Current learning rate: 0.00231 +2024-11-22 21:46:19.679687: train_loss -0.8148 +2024-11-22 21:46:19.679904: val_loss -0.7726 +2024-11-22 21:46:19.679988: Pseudo dice [0.8336] +2024-11-22 21:46:19.680073: Epoch time: 18.39 s +2024-11-22 21:46:20.595628: +2024-11-22 21:46:20.595819: Epoch 6429 +2024-11-22 21:46:20.595932: Current learning rate: 0.00231 +2024-11-22 21:46:39.274876: train_loss -0.8149 +2024-11-22 21:46:39.275115: val_loss -0.77 +2024-11-22 21:46:39.275188: Pseudo dice [0.8342] +2024-11-22 21:46:39.275267: Epoch time: 18.68 s +2024-11-22 21:46:40.188923: +2024-11-22 21:46:40.189121: Epoch 6430 +2024-11-22 21:46:40.189234: Current learning rate: 0.00231 +2024-11-22 21:46:58.801521: train_loss -0.8102 +2024-11-22 21:46:58.801749: val_loss -0.7541 +2024-11-22 21:46:58.801826: Pseudo dice [0.8284] +2024-11-22 21:46:58.801904: Epoch time: 18.61 s +2024-11-22 21:46:59.714683: +2024-11-22 21:46:59.714907: Epoch 6431 +2024-11-22 21:46:59.715025: Current learning rate: 0.00231 +2024-11-22 21:47:17.905557: train_loss -0.8144 +2024-11-22 21:47:17.905833: val_loss -0.7473 +2024-11-22 21:47:17.905910: Pseudo dice [0.8301] +2024-11-22 21:47:17.905988: Epoch time: 18.19 s +2024-11-22 21:47:18.819544: +2024-11-22 21:47:18.819768: Epoch 6432 +2024-11-22 21:47:18.819887: Current learning rate: 0.00231 +2024-11-22 21:47:38.831291: train_loss -0.8107 +2024-11-22 21:47:38.831615: val_loss -0.7519 +2024-11-22 21:47:38.831713: Pseudo dice [0.8215] +2024-11-22 21:47:38.831800: Epoch time: 20.01 s +2024-11-22 21:47:39.749570: +2024-11-22 21:47:39.749779: Epoch 6433 +2024-11-22 21:47:39.749893: Current learning rate: 0.00231 +2024-11-22 21:47:59.359047: train_loss -0.8109 +2024-11-22 21:47:59.359249: val_loss -0.7512 +2024-11-22 21:47:59.359321: Pseudo dice [0.8407] +2024-11-22 21:47:59.359392: Epoch time: 19.61 s +2024-11-22 21:48:00.243133: +2024-11-22 21:48:00.243322: Epoch 6434 +2024-11-22 21:48:00.243435: Current learning rate: 0.0023 +2024-11-22 21:48:17.847261: train_loss -0.8138 +2024-11-22 21:48:17.847485: val_loss -0.7494 +2024-11-22 21:48:17.847561: Pseudo dice [0.8513] +2024-11-22 21:48:17.848814: Epoch time: 17.6 s +2024-11-22 21:48:19.146280: +2024-11-22 21:48:19.146484: Epoch 6435 +2024-11-22 21:48:19.146600: Current learning rate: 0.0023 +2024-11-22 21:48:37.875689: train_loss -0.816 +2024-11-22 21:48:37.875942: val_loss -0.7865 +2024-11-22 21:48:37.876092: Pseudo dice [0.8549] +2024-11-22 21:48:37.876180: Epoch time: 18.73 s +2024-11-22 21:48:38.789847: +2024-11-22 21:48:38.790124: Epoch 6436 +2024-11-22 21:48:38.790231: Current learning rate: 0.0023 +2024-11-22 21:48:57.604846: train_loss -0.8169 +2024-11-22 21:48:57.605222: val_loss -0.7738 +2024-11-22 21:48:57.605316: Pseudo dice [0.8399] +2024-11-22 21:48:57.605395: Epoch time: 18.82 s +2024-11-22 21:48:58.682199: +2024-11-22 21:48:58.682383: Epoch 6437 +2024-11-22 21:48:58.682482: Current learning rate: 0.0023 +2024-11-22 21:49:16.748711: train_loss -0.8074 +2024-11-22 21:49:16.748921: val_loss -0.7237 +2024-11-22 21:49:16.749003: Pseudo dice [0.8262] +2024-11-22 21:49:16.754036: Epoch time: 18.07 s +2024-11-22 21:49:17.771376: +2024-11-22 21:49:17.771581: Epoch 6438 +2024-11-22 21:49:17.771693: Current learning rate: 0.0023 +2024-11-22 21:49:34.955518: train_loss -0.806 +2024-11-22 21:49:34.955735: val_loss -0.766 +2024-11-22 21:49:34.955808: Pseudo dice [0.8451] +2024-11-22 21:49:34.955887: Epoch time: 17.18 s +2024-11-22 21:49:36.068058: +2024-11-22 21:49:36.068257: Epoch 6439 +2024-11-22 21:49:36.068370: Current learning rate: 0.0023 +2024-11-22 21:49:55.327623: train_loss -0.8102 +2024-11-22 21:49:55.327861: val_loss -0.7486 +2024-11-22 21:49:55.327936: Pseudo dice [0.8353] +2024-11-22 21:49:55.328023: Epoch time: 19.26 s +2024-11-22 21:49:56.241707: +2024-11-22 21:49:56.241907: Epoch 6440 +2024-11-22 21:49:56.242024: Current learning rate: 0.0023 +2024-11-22 21:50:15.349708: train_loss -0.8118 +2024-11-22 21:50:15.350275: val_loss -0.7671 +2024-11-22 21:50:15.350359: Pseudo dice [0.8219] +2024-11-22 21:50:15.350436: Epoch time: 19.11 s +2024-11-22 21:50:16.266275: +2024-11-22 21:50:16.266469: Epoch 6441 +2024-11-22 21:50:16.266590: Current learning rate: 0.00229 +2024-11-22 21:50:34.581897: train_loss -0.8194 +2024-11-22 21:50:34.582127: val_loss -0.7328 +2024-11-22 21:50:34.582202: Pseudo dice [0.8257] +2024-11-22 21:50:34.582280: Epoch time: 18.32 s +2024-11-22 21:50:35.495047: +2024-11-22 21:50:35.495296: Epoch 6442 +2024-11-22 21:50:35.495407: Current learning rate: 0.00229 +2024-11-22 21:50:55.231591: train_loss -0.815 +2024-11-22 21:50:55.231811: val_loss -0.76 +2024-11-22 21:50:55.231888: Pseudo dice [0.85] +2024-11-22 21:50:55.231973: Epoch time: 19.74 s +2024-11-22 21:50:56.158005: +2024-11-22 21:50:56.158222: Epoch 6443 +2024-11-22 21:50:56.158334: Current learning rate: 0.00229 +2024-11-22 21:51:13.809445: train_loss -0.8117 +2024-11-22 21:51:13.809677: val_loss -0.7466 +2024-11-22 21:51:13.809755: Pseudo dice [0.8244] +2024-11-22 21:51:13.809834: Epoch time: 17.65 s +2024-11-22 21:51:14.821187: +2024-11-22 21:51:14.821390: Epoch 6444 +2024-11-22 21:51:14.821502: Current learning rate: 0.00229 +2024-11-22 21:51:33.595606: train_loss -0.7969 +2024-11-22 21:51:33.595849: val_loss -0.7253 +2024-11-22 21:51:33.595928: Pseudo dice [0.8137] +2024-11-22 21:51:33.596011: Epoch time: 18.78 s +2024-11-22 21:51:34.502930: +2024-11-22 21:51:34.503135: Epoch 6445 +2024-11-22 21:51:34.503246: Current learning rate: 0.00229 +2024-11-22 21:51:51.976952: train_loss -0.8023 +2024-11-22 21:51:51.977179: val_loss -0.7376 +2024-11-22 21:51:51.977260: Pseudo dice [0.8271] +2024-11-22 21:51:51.977342: Epoch time: 17.47 s +2024-11-22 21:51:53.248119: +2024-11-22 21:51:53.248568: Epoch 6446 +2024-11-22 21:51:53.248706: Current learning rate: 0.00229 +2024-11-22 21:52:11.462431: train_loss -0.8166 +2024-11-22 21:52:11.464847: val_loss -0.7446 +2024-11-22 21:52:11.464966: Pseudo dice [0.8191] +2024-11-22 21:52:11.465061: Epoch time: 18.22 s +2024-11-22 21:52:12.549844: +2024-11-22 21:52:12.550264: Epoch 6447 +2024-11-22 21:52:12.550395: Current learning rate: 0.00229 +2024-11-22 21:52:30.031008: train_loss -0.8153 +2024-11-22 21:52:30.032488: val_loss -0.7563 +2024-11-22 21:52:30.032588: Pseudo dice [0.8254] +2024-11-22 21:52:30.032667: Epoch time: 17.48 s +2024-11-22 21:52:30.948341: +2024-11-22 21:52:30.948773: Epoch 6448 +2024-11-22 21:52:30.948910: Current learning rate: 0.00229 +2024-11-22 21:52:50.159518: train_loss -0.8115 +2024-11-22 21:52:50.159774: val_loss -0.7559 +2024-11-22 21:52:50.159892: Pseudo dice [0.8461] +2024-11-22 21:52:50.159986: Epoch time: 19.21 s +2024-11-22 21:52:51.086541: +2024-11-22 21:52:51.086951: Epoch 6449 +2024-11-22 21:52:51.087090: Current learning rate: 0.00228 +2024-11-22 21:53:10.225094: train_loss -0.8056 +2024-11-22 21:53:10.225336: val_loss -0.769 +2024-11-22 21:53:10.225412: Pseudo dice [0.8355] +2024-11-22 21:53:10.225497: Epoch time: 19.14 s +2024-11-22 21:53:11.469942: +2024-11-22 21:53:11.470494: Epoch 6450 +2024-11-22 21:53:11.470630: Current learning rate: 0.00228 +2024-11-22 21:53:29.647669: train_loss -0.8077 +2024-11-22 21:53:29.648855: val_loss -0.7692 +2024-11-22 21:53:29.649047: Pseudo dice [0.8434] +2024-11-22 21:53:29.649125: Epoch time: 18.18 s +2024-11-22 21:53:30.569415: +2024-11-22 21:53:30.569835: Epoch 6451 +2024-11-22 21:53:30.569967: Current learning rate: 0.00228 +2024-11-22 21:53:49.590718: train_loss -0.8017 +2024-11-22 21:53:49.590939: val_loss -0.7384 +2024-11-22 21:53:49.591021: Pseudo dice [0.8302] +2024-11-22 21:53:49.591112: Epoch time: 19.02 s +2024-11-22 21:53:50.509412: +2024-11-22 21:53:50.509872: Epoch 6452 +2024-11-22 21:53:50.510012: Current learning rate: 0.00228 +2024-11-22 21:54:08.653024: train_loss -0.804 +2024-11-22 21:54:08.653250: val_loss -0.7622 +2024-11-22 21:54:08.658535: Pseudo dice [0.8159] +2024-11-22 21:54:08.658665: Epoch time: 18.14 s +2024-11-22 21:54:09.869920: +2024-11-22 21:54:09.870334: Epoch 6453 +2024-11-22 21:54:09.870467: Current learning rate: 0.00228 +2024-11-22 21:54:28.332880: train_loss -0.8066 +2024-11-22 21:54:28.333175: val_loss -0.761 +2024-11-22 21:54:28.333258: Pseudo dice [0.8214] +2024-11-22 21:54:28.333348: Epoch time: 18.46 s +2024-11-22 21:54:29.247255: +2024-11-22 21:54:29.247673: Epoch 6454 +2024-11-22 21:54:29.247805: Current learning rate: 0.00228 +2024-11-22 21:54:49.116471: train_loss -0.8107 +2024-11-22 21:54:49.116670: val_loss -0.7377 +2024-11-22 21:54:49.116741: Pseudo dice [0.8292] +2024-11-22 21:54:49.116816: Epoch time: 19.87 s +2024-11-22 21:54:50.072259: +2024-11-22 21:54:50.072452: Epoch 6455 +2024-11-22 21:54:50.072562: Current learning rate: 0.00228 +2024-11-22 21:55:09.676394: train_loss -0.8134 +2024-11-22 21:55:09.679137: val_loss -0.7751 +2024-11-22 21:55:09.679268: Pseudo dice [0.8249] +2024-11-22 21:55:09.679344: Epoch time: 19.6 s +2024-11-22 21:55:10.591204: +2024-11-22 21:55:10.591631: Epoch 6456 +2024-11-22 21:55:10.591766: Current learning rate: 0.00228 +2024-11-22 21:55:30.453727: train_loss -0.8122 +2024-11-22 21:55:30.454136: val_loss -0.7433 +2024-11-22 21:55:30.454221: Pseudo dice [0.8382] +2024-11-22 21:55:30.454300: Epoch time: 19.86 s +2024-11-22 21:55:31.391282: +2024-11-22 21:55:31.391592: Epoch 6457 +2024-11-22 21:55:31.391705: Current learning rate: 0.00227 +2024-11-22 21:55:50.186779: train_loss -0.8168 +2024-11-22 21:55:50.187033: val_loss -0.7575 +2024-11-22 21:55:50.187134: Pseudo dice [0.831] +2024-11-22 21:55:50.187221: Epoch time: 18.8 s +2024-11-22 21:55:51.462715: +2024-11-22 21:55:51.462904: Epoch 6458 +2024-11-22 21:55:51.463021: Current learning rate: 0.00227 +2024-11-22 21:56:10.028359: train_loss -0.8106 +2024-11-22 21:56:10.028565: val_loss -0.7348 +2024-11-22 21:56:10.028639: Pseudo dice [0.8457] +2024-11-22 21:56:10.028714: Epoch time: 18.57 s +2024-11-22 21:56:10.948320: +2024-11-22 21:56:10.948520: Epoch 6459 +2024-11-22 21:56:10.948630: Current learning rate: 0.00227 +2024-11-22 21:56:30.454099: train_loss -0.8042 +2024-11-22 21:56:30.454319: val_loss -0.7657 +2024-11-22 21:56:30.454394: Pseudo dice [0.8429] +2024-11-22 21:56:30.454469: Epoch time: 19.51 s +2024-11-22 21:56:31.370264: +2024-11-22 21:56:31.370487: Epoch 6460 +2024-11-22 21:56:31.381849: Current learning rate: 0.00227 +2024-11-22 21:56:49.943513: train_loss -0.8087 +2024-11-22 21:56:49.949177: val_loss -0.7626 +2024-11-22 21:56:49.949310: Pseudo dice [0.8371] +2024-11-22 21:56:49.949437: Epoch time: 18.57 s +2024-11-22 21:56:50.869872: +2024-11-22 21:56:50.870141: Epoch 6461 +2024-11-22 21:56:50.870256: Current learning rate: 0.00227 +2024-11-22 21:57:08.459816: train_loss -0.8104 +2024-11-22 21:57:08.462179: val_loss -0.7642 +2024-11-22 21:57:08.462298: Pseudo dice [0.8319] +2024-11-22 21:57:08.462378: Epoch time: 17.59 s +2024-11-22 21:57:09.538917: +2024-11-22 21:57:09.539156: Epoch 6462 +2024-11-22 21:57:09.539272: Current learning rate: 0.00227 +2024-11-22 21:57:28.284232: train_loss -0.8056 +2024-11-22 21:57:28.284451: val_loss -0.7575 +2024-11-22 21:57:28.284525: Pseudo dice [0.8301] +2024-11-22 21:57:28.284600: Epoch time: 18.75 s +2024-11-22 21:57:29.201248: +2024-11-22 21:57:29.201455: Epoch 6463 +2024-11-22 21:57:29.201568: Current learning rate: 0.00227 +2024-11-22 21:57:48.726237: train_loss -0.8162 +2024-11-22 21:57:48.726456: val_loss -0.7559 +2024-11-22 21:57:48.726534: Pseudo dice [0.826] +2024-11-22 21:57:48.726611: Epoch time: 19.53 s +2024-11-22 21:57:49.640276: +2024-11-22 21:57:49.640535: Epoch 6464 +2024-11-22 21:57:49.640652: Current learning rate: 0.00226 +2024-11-22 21:58:09.379240: train_loss -0.8177 +2024-11-22 21:58:09.384637: val_loss -0.7619 +2024-11-22 21:58:09.384788: Pseudo dice [0.8511] +2024-11-22 21:58:09.384880: Epoch time: 19.74 s +2024-11-22 21:58:10.304782: +2024-11-22 21:58:10.304998: Epoch 6465 +2024-11-22 21:58:10.305109: Current learning rate: 0.00226 +2024-11-22 21:58:28.305068: train_loss -0.819 +2024-11-22 21:58:28.305279: val_loss -0.7641 +2024-11-22 21:58:28.305350: Pseudo dice [0.8341] +2024-11-22 21:58:28.305423: Epoch time: 18.0 s +2024-11-22 21:58:29.261722: +2024-11-22 21:58:29.261940: Epoch 6466 +2024-11-22 21:58:29.262063: Current learning rate: 0.00226 +2024-11-22 21:58:49.898127: train_loss -0.8136 +2024-11-22 21:58:49.898336: val_loss -0.7403 +2024-11-22 21:58:49.898414: Pseudo dice [0.8348] +2024-11-22 21:58:49.898490: Epoch time: 20.64 s +2024-11-22 21:58:50.828933: +2024-11-22 21:58:50.829146: Epoch 6467 +2024-11-22 21:58:50.829255: Current learning rate: 0.00226 +2024-11-22 21:59:09.321311: train_loss -0.8053 +2024-11-22 21:59:09.321516: val_loss -0.7577 +2024-11-22 21:59:09.321590: Pseudo dice [0.8157] +2024-11-22 21:59:09.321668: Epoch time: 18.49 s +2024-11-22 21:59:10.303987: +2024-11-22 21:59:10.304279: Epoch 6468 +2024-11-22 21:59:10.304390: Current learning rate: 0.00226 +2024-11-22 21:59:28.438590: train_loss -0.7979 +2024-11-22 21:59:28.439163: val_loss -0.7479 +2024-11-22 21:59:28.439248: Pseudo dice [0.8276] +2024-11-22 21:59:28.439330: Epoch time: 18.14 s +2024-11-22 21:59:29.352870: +2024-11-22 21:59:29.353059: Epoch 6469 +2024-11-22 21:59:29.353171: Current learning rate: 0.00226 +2024-11-22 21:59:49.064510: train_loss -0.7895 +2024-11-22 21:59:49.064723: val_loss -0.7362 +2024-11-22 21:59:49.064793: Pseudo dice [0.822] +2024-11-22 21:59:49.064869: Epoch time: 19.71 s +2024-11-22 21:59:49.978747: +2024-11-22 21:59:49.979007: Epoch 6470 +2024-11-22 21:59:49.979125: Current learning rate: 0.00226 +2024-11-22 22:00:09.186577: train_loss -0.8017 +2024-11-22 22:00:09.186793: val_loss -0.7754 +2024-11-22 22:00:09.189080: Pseudo dice [0.8435] +2024-11-22 22:00:09.189186: Epoch time: 19.21 s +2024-11-22 22:00:10.216327: +2024-11-22 22:00:10.216564: Epoch 6471 +2024-11-22 22:00:10.216675: Current learning rate: 0.00226 +2024-11-22 22:00:29.507473: train_loss -0.8109 +2024-11-22 22:00:29.507713: val_loss -0.7444 +2024-11-22 22:00:29.507788: Pseudo dice [0.8301] +2024-11-22 22:00:29.507869: Epoch time: 19.29 s +2024-11-22 22:00:30.422329: +2024-11-22 22:00:30.422551: Epoch 6472 +2024-11-22 22:00:30.422664: Current learning rate: 0.00225 +2024-11-22 22:00:48.945597: train_loss -0.8117 +2024-11-22 22:00:48.945807: val_loss -0.7838 +2024-11-22 22:00:48.945881: Pseudo dice [0.8395] +2024-11-22 22:00:48.968866: Epoch time: 18.52 s +2024-11-22 22:00:49.992400: +2024-11-22 22:00:49.992609: Epoch 6473 +2024-11-22 22:00:49.992729: Current learning rate: 0.00225 +2024-11-22 22:01:10.321350: train_loss -0.8123 +2024-11-22 22:01:10.321596: val_loss -0.7356 +2024-11-22 22:01:10.321679: Pseudo dice [0.8261] +2024-11-22 22:01:10.321760: Epoch time: 20.33 s +2024-11-22 22:01:11.264519: +2024-11-22 22:01:11.264792: Epoch 6474 +2024-11-22 22:01:11.264924: Current learning rate: 0.00225 +2024-11-22 22:01:29.716558: train_loss -0.8179 +2024-11-22 22:01:29.716771: val_loss -0.7439 +2024-11-22 22:01:29.716846: Pseudo dice [0.8368] +2024-11-22 22:01:29.716924: Epoch time: 18.45 s +2024-11-22 22:01:30.631313: +2024-11-22 22:01:30.631535: Epoch 6475 +2024-11-22 22:01:30.631647: Current learning rate: 0.00225 +2024-11-22 22:01:48.600492: train_loss -0.8223 +2024-11-22 22:01:48.600725: val_loss -0.7747 +2024-11-22 22:01:48.600804: Pseudo dice [0.8254] +2024-11-22 22:01:48.600897: Epoch time: 17.97 s +2024-11-22 22:01:49.524364: +2024-11-22 22:01:49.524661: Epoch 6476 +2024-11-22 22:01:49.524777: Current learning rate: 0.00225 +2024-11-22 22:02:07.201318: train_loss -0.8219 +2024-11-22 22:02:07.201529: val_loss -0.7628 +2024-11-22 22:02:07.201605: Pseudo dice [0.8341] +2024-11-22 22:02:07.201683: Epoch time: 17.68 s +2024-11-22 22:02:08.109577: +2024-11-22 22:02:08.109836: Epoch 6477 +2024-11-22 22:02:08.109950: Current learning rate: 0.00225 +2024-11-22 22:02:25.467677: train_loss -0.8172 +2024-11-22 22:02:25.467910: val_loss -0.7636 +2024-11-22 22:02:25.468000: Pseudo dice [0.8391] +2024-11-22 22:02:25.468078: Epoch time: 17.36 s +2024-11-22 22:02:26.481635: +2024-11-22 22:02:26.481876: Epoch 6478 +2024-11-22 22:02:26.481989: Current learning rate: 0.00225 +2024-11-22 22:02:44.785249: train_loss -0.8096 +2024-11-22 22:02:44.785477: val_loss -0.7386 +2024-11-22 22:02:44.785553: Pseudo dice [0.8378] +2024-11-22 22:02:44.785635: Epoch time: 18.3 s +2024-11-22 22:02:45.874267: +2024-11-22 22:02:45.874528: Epoch 6479 +2024-11-22 22:02:45.874640: Current learning rate: 0.00224 +2024-11-22 22:03:04.695360: train_loss -0.8205 +2024-11-22 22:03:04.695598: val_loss -0.7503 +2024-11-22 22:03:04.695673: Pseudo dice [0.8274] +2024-11-22 22:03:04.695756: Epoch time: 18.82 s +2024-11-22 22:03:05.610586: +2024-11-22 22:03:05.610782: Epoch 6480 +2024-11-22 22:03:05.610900: Current learning rate: 0.00224 +2024-11-22 22:03:23.581706: train_loss -0.8181 +2024-11-22 22:03:23.581917: val_loss -0.7589 +2024-11-22 22:03:23.581989: Pseudo dice [0.8342] +2024-11-22 22:03:23.582071: Epoch time: 17.97 s +2024-11-22 22:03:24.877519: +2024-11-22 22:03:24.877721: Epoch 6481 +2024-11-22 22:03:24.877836: Current learning rate: 0.00224 +2024-11-22 22:03:43.087378: train_loss -0.8099 +2024-11-22 22:03:43.087628: val_loss -0.777 +2024-11-22 22:03:43.087706: Pseudo dice [0.8431] +2024-11-22 22:03:43.087784: Epoch time: 18.21 s +2024-11-22 22:03:44.044168: +2024-11-22 22:03:44.044392: Epoch 6482 +2024-11-22 22:03:44.044505: Current learning rate: 0.00224 +2024-11-22 22:04:03.327581: train_loss -0.8138 +2024-11-22 22:04:03.327827: val_loss -0.7398 +2024-11-22 22:04:03.328025: Pseudo dice [0.8145] +2024-11-22 22:04:03.328117: Epoch time: 19.28 s +2024-11-22 22:04:04.234393: +2024-11-22 22:04:04.234622: Epoch 6483 +2024-11-22 22:04:04.234738: Current learning rate: 0.00224 +2024-11-22 22:04:23.810848: train_loss -0.8206 +2024-11-22 22:04:23.811066: val_loss -0.7796 +2024-11-22 22:04:23.811139: Pseudo dice [0.8449] +2024-11-22 22:04:23.811210: Epoch time: 19.58 s +2024-11-22 22:04:24.816501: +2024-11-22 22:04:24.816754: Epoch 6484 +2024-11-22 22:04:24.816869: Current learning rate: 0.00224 +2024-11-22 22:04:43.521559: train_loss -0.8109 +2024-11-22 22:04:43.521781: val_loss -0.7345 +2024-11-22 22:04:43.521858: Pseudo dice [0.8239] +2024-11-22 22:04:43.521930: Epoch time: 18.71 s +2024-11-22 22:04:44.475894: +2024-11-22 22:04:44.476096: Epoch 6485 +2024-11-22 22:04:44.476204: Current learning rate: 0.00224 +2024-11-22 22:05:03.299676: train_loss -0.8218 +2024-11-22 22:05:03.299900: val_loss -0.7662 +2024-11-22 22:05:03.299982: Pseudo dice [0.8432] +2024-11-22 22:05:03.300065: Epoch time: 18.82 s +2024-11-22 22:05:04.204545: +2024-11-22 22:05:04.204746: Epoch 6486 +2024-11-22 22:05:04.204856: Current learning rate: 0.00224 +2024-11-22 22:05:22.626850: train_loss -0.8199 +2024-11-22 22:05:22.627087: val_loss -0.7328 +2024-11-22 22:05:22.627170: Pseudo dice [0.818] +2024-11-22 22:05:22.627255: Epoch time: 18.42 s +2024-11-22 22:05:23.544313: +2024-11-22 22:05:23.544535: Epoch 6487 +2024-11-22 22:05:23.544638: Current learning rate: 0.00223 +2024-11-22 22:05:42.065196: train_loss -0.818 +2024-11-22 22:05:42.065402: val_loss -0.7514 +2024-11-22 22:05:42.065477: Pseudo dice [0.8388] +2024-11-22 22:05:42.065552: Epoch time: 18.52 s +2024-11-22 22:05:42.960510: +2024-11-22 22:05:42.960706: Epoch 6488 +2024-11-22 22:05:42.960818: Current learning rate: 0.00223 +2024-11-22 22:06:02.061886: train_loss -0.8107 +2024-11-22 22:06:02.062113: val_loss -0.7636 +2024-11-22 22:06:02.062191: Pseudo dice [0.8406] +2024-11-22 22:06:02.062270: Epoch time: 19.1 s +2024-11-22 22:06:03.132195: +2024-11-22 22:06:03.132462: Epoch 6489 +2024-11-22 22:06:03.132576: Current learning rate: 0.00223 +2024-11-22 22:06:22.379195: train_loss -0.8113 +2024-11-22 22:06:22.379405: val_loss -0.7454 +2024-11-22 22:06:22.379479: Pseudo dice [0.8434] +2024-11-22 22:06:22.379557: Epoch time: 19.25 s +2024-11-22 22:06:23.289902: +2024-11-22 22:06:23.290202: Epoch 6490 +2024-11-22 22:06:23.290318: Current learning rate: 0.00223 +2024-11-22 22:06:42.578322: train_loss -0.8044 +2024-11-22 22:06:42.578551: val_loss -0.7497 +2024-11-22 22:06:42.578627: Pseudo dice [0.8196] +2024-11-22 22:06:42.578707: Epoch time: 19.29 s +2024-11-22 22:06:43.488027: +2024-11-22 22:06:43.488322: Epoch 6491 +2024-11-22 22:06:43.488452: Current learning rate: 0.00223 +2024-11-22 22:07:03.080932: train_loss -0.8128 +2024-11-22 22:07:03.081157: val_loss -0.7588 +2024-11-22 22:07:03.081231: Pseudo dice [0.8383] +2024-11-22 22:07:03.081304: Epoch time: 19.59 s +2024-11-22 22:07:03.999429: +2024-11-22 22:07:03.999649: Epoch 6492 +2024-11-22 22:07:03.999760: Current learning rate: 0.00223 +2024-11-22 22:07:22.895288: train_loss -0.8123 +2024-11-22 22:07:22.895522: val_loss -0.7585 +2024-11-22 22:07:22.895604: Pseudo dice [0.8505] +2024-11-22 22:07:22.895689: Epoch time: 18.9 s +2024-11-22 22:07:23.808114: +2024-11-22 22:07:23.808372: Epoch 6493 +2024-11-22 22:07:23.808481: Current learning rate: 0.00223 +2024-11-22 22:07:42.778564: train_loss -0.8098 +2024-11-22 22:07:42.783997: val_loss -0.7529 +2024-11-22 22:07:42.784075: Pseudo dice [0.8364] +2024-11-22 22:07:42.784161: Epoch time: 18.97 s +2024-11-22 22:07:43.823884: +2024-11-22 22:07:43.824092: Epoch 6494 +2024-11-22 22:07:43.824210: Current learning rate: 0.00222 +2024-11-22 22:08:02.780879: train_loss -0.8164 +2024-11-22 22:08:02.781110: val_loss -0.76 +2024-11-22 22:08:02.781185: Pseudo dice [0.8373] +2024-11-22 22:08:02.783484: Epoch time: 18.96 s +2024-11-22 22:08:03.820721: +2024-11-22 22:08:03.821103: Epoch 6495 +2024-11-22 22:08:03.821217: Current learning rate: 0.00222 +2024-11-22 22:08:22.256616: train_loss -0.8003 +2024-11-22 22:08:22.256830: val_loss -0.7456 +2024-11-22 22:08:22.256908: Pseudo dice [0.8307] +2024-11-22 22:08:22.256985: Epoch time: 18.44 s +2024-11-22 22:08:23.163988: +2024-11-22 22:08:23.164189: Epoch 6496 +2024-11-22 22:08:23.164317: Current learning rate: 0.00222 +2024-11-22 22:08:40.797746: train_loss -0.8142 +2024-11-22 22:08:40.797995: val_loss -0.7488 +2024-11-22 22:08:40.798072: Pseudo dice [0.8301] +2024-11-22 22:08:40.798154: Epoch time: 17.63 s +2024-11-22 22:08:41.737171: +2024-11-22 22:08:41.737365: Epoch 6497 +2024-11-22 22:08:41.737483: Current learning rate: 0.00222 +2024-11-22 22:08:59.947194: train_loss -0.8164 +2024-11-22 22:08:59.947406: val_loss -0.7362 +2024-11-22 22:08:59.947481: Pseudo dice [0.8104] +2024-11-22 22:08:59.947558: Epoch time: 18.21 s +2024-11-22 22:09:00.855366: +2024-11-22 22:09:00.855559: Epoch 6498 +2024-11-22 22:09:00.855670: Current learning rate: 0.00222 +2024-11-22 22:09:21.124217: train_loss -0.8175 +2024-11-22 22:09:21.124444: val_loss -0.7808 +2024-11-22 22:09:21.124522: Pseudo dice [0.8417] +2024-11-22 22:09:21.124601: Epoch time: 20.27 s +2024-11-22 22:09:22.036394: +2024-11-22 22:09:22.036593: Epoch 6499 +2024-11-22 22:09:22.036704: Current learning rate: 0.00222 +2024-11-22 22:09:41.383199: train_loss -0.8193 +2024-11-22 22:09:41.383418: val_loss -0.7609 +2024-11-22 22:09:41.383495: Pseudo dice [0.8393] +2024-11-22 22:09:41.383573: Epoch time: 19.35 s +2024-11-22 22:09:42.597679: +2024-11-22 22:09:42.597874: Epoch 6500 +2024-11-22 22:09:42.597983: Current learning rate: 0.00222 +2024-11-22 22:10:01.094157: train_loss -0.82 +2024-11-22 22:10:01.094461: val_loss -0.7354 +2024-11-22 22:10:01.094538: Pseudo dice [0.8211] +2024-11-22 22:10:01.094624: Epoch time: 18.5 s +2024-11-22 22:10:02.011600: +2024-11-22 22:10:02.011805: Epoch 6501 +2024-11-22 22:10:02.011917: Current learning rate: 0.00222 +2024-11-22 22:10:20.355714: train_loss -0.8183 +2024-11-22 22:10:20.355933: val_loss -0.7567 +2024-11-22 22:10:20.356018: Pseudo dice [0.8347] +2024-11-22 22:10:20.356093: Epoch time: 18.34 s +2024-11-22 22:10:21.264049: +2024-11-22 22:10:21.264253: Epoch 6502 +2024-11-22 22:10:21.264372: Current learning rate: 0.00221 +2024-11-22 22:10:40.208629: train_loss -0.8206 +2024-11-22 22:10:40.213189: val_loss -0.7314 +2024-11-22 22:10:40.213303: Pseudo dice [0.8345] +2024-11-22 22:10:40.213379: Epoch time: 18.95 s +2024-11-22 22:10:41.364134: +2024-11-22 22:10:41.364398: Epoch 6503 +2024-11-22 22:10:41.364511: Current learning rate: 0.00221 +2024-11-22 22:11:01.532297: train_loss -0.8185 +2024-11-22 22:11:01.532789: val_loss -0.7708 +2024-11-22 22:11:01.532889: Pseudo dice [0.845] +2024-11-22 22:11:01.532997: Epoch time: 20.17 s +2024-11-22 22:11:02.512934: +2024-11-22 22:11:02.513155: Epoch 6504 +2024-11-22 22:11:02.513271: Current learning rate: 0.00221 +2024-11-22 22:11:21.657795: train_loss -0.811 +2024-11-22 22:11:21.658012: val_loss -0.7482 +2024-11-22 22:11:21.658089: Pseudo dice [0.8133] +2024-11-22 22:11:21.658169: Epoch time: 19.15 s +2024-11-22 22:11:22.569105: +2024-11-22 22:11:22.569369: Epoch 6505 +2024-11-22 22:11:22.569486: Current learning rate: 0.00221 +2024-11-22 22:11:41.313664: train_loss -0.8049 +2024-11-22 22:11:41.313894: val_loss -0.7605 +2024-11-22 22:11:41.313975: Pseudo dice [0.8391] +2024-11-22 22:11:41.314060: Epoch time: 18.75 s +2024-11-22 22:11:42.223775: +2024-11-22 22:11:42.223975: Epoch 6506 +2024-11-22 22:11:42.224094: Current learning rate: 0.00221 +2024-11-22 22:12:01.457418: train_loss -0.8141 +2024-11-22 22:12:01.457672: val_loss -0.7697 +2024-11-22 22:12:01.457750: Pseudo dice [0.8314] +2024-11-22 22:12:01.457830: Epoch time: 19.23 s +2024-11-22 22:12:02.368171: +2024-11-22 22:12:02.368366: Epoch 6507 +2024-11-22 22:12:02.368483: Current learning rate: 0.00221 +2024-11-22 22:12:20.411400: train_loss -0.8149 +2024-11-22 22:12:20.411640: val_loss -0.759 +2024-11-22 22:12:20.411720: Pseudo dice [0.831] +2024-11-22 22:12:20.411815: Epoch time: 18.04 s +2024-11-22 22:12:21.337913: +2024-11-22 22:12:21.338116: Epoch 6508 +2024-11-22 22:12:21.338224: Current learning rate: 0.00221 +2024-11-22 22:12:40.476612: train_loss -0.8158 +2024-11-22 22:12:40.476837: val_loss -0.7326 +2024-11-22 22:12:40.476911: Pseudo dice [0.8322] +2024-11-22 22:12:40.476987: Epoch time: 19.14 s +2024-11-22 22:12:41.399857: +2024-11-22 22:12:41.400126: Epoch 6509 +2024-11-22 22:12:41.400235: Current learning rate: 0.0022 +2024-11-22 22:13:00.407036: train_loss -0.814 +2024-11-22 22:13:00.407254: val_loss -0.767 +2024-11-22 22:13:00.407327: Pseudo dice [0.8406] +2024-11-22 22:13:00.407402: Epoch time: 19.01 s +2024-11-22 22:13:01.522753: +2024-11-22 22:13:01.522949: Epoch 6510 +2024-11-22 22:13:01.523069: Current learning rate: 0.0022 +2024-11-22 22:13:19.736869: train_loss -0.8124 +2024-11-22 22:13:19.737088: val_loss -0.7497 +2024-11-22 22:13:19.737165: Pseudo dice [0.835] +2024-11-22 22:13:19.737245: Epoch time: 18.21 s +2024-11-22 22:13:20.650287: +2024-11-22 22:13:20.650494: Epoch 6511 +2024-11-22 22:13:20.650607: Current learning rate: 0.0022 +2024-11-22 22:13:39.026600: train_loss -0.8155 +2024-11-22 22:13:39.026907: val_loss -0.7738 +2024-11-22 22:13:39.026984: Pseudo dice [0.8446] +2024-11-22 22:13:39.027068: Epoch time: 18.38 s +2024-11-22 22:13:39.951100: +2024-11-22 22:13:39.951312: Epoch 6512 +2024-11-22 22:13:39.951421: Current learning rate: 0.0022 +2024-11-22 22:13:58.686862: train_loss -0.813 +2024-11-22 22:13:58.687096: val_loss -0.7809 +2024-11-22 22:13:58.687170: Pseudo dice [0.8431] +2024-11-22 22:13:58.687247: Epoch time: 18.74 s +2024-11-22 22:13:59.594855: +2024-11-22 22:13:59.595072: Epoch 6513 +2024-11-22 22:13:59.595184: Current learning rate: 0.0022 +2024-11-22 22:14:18.360368: train_loss -0.8195 +2024-11-22 22:14:18.360584: val_loss -0.785 +2024-11-22 22:14:18.360660: Pseudo dice [0.8484] +2024-11-22 22:14:18.360734: Epoch time: 18.77 s +2024-11-22 22:14:19.282396: +2024-11-22 22:14:19.282597: Epoch 6514 +2024-11-22 22:14:19.282806: Current learning rate: 0.0022 +2024-11-22 22:14:37.695755: train_loss -0.8124 +2024-11-22 22:14:37.695977: val_loss -0.732 +2024-11-22 22:14:37.696056: Pseudo dice [0.8139] +2024-11-22 22:14:37.696137: Epoch time: 18.41 s +2024-11-22 22:14:38.996918: +2024-11-22 22:14:38.997119: Epoch 6515 +2024-11-22 22:14:38.997227: Current learning rate: 0.0022 +2024-11-22 22:14:56.922789: train_loss -0.8134 +2024-11-22 22:14:56.923016: val_loss -0.7616 +2024-11-22 22:14:56.923091: Pseudo dice [0.8323] +2024-11-22 22:14:56.923167: Epoch time: 17.93 s +2024-11-22 22:14:57.831616: +2024-11-22 22:14:57.831814: Epoch 6516 +2024-11-22 22:14:57.831925: Current learning rate: 0.0022 +2024-11-22 22:15:16.492043: train_loss -0.8141 +2024-11-22 22:15:16.492270: val_loss -0.754 +2024-11-22 22:15:16.492343: Pseudo dice [0.8337] +2024-11-22 22:15:16.492421: Epoch time: 18.66 s +2024-11-22 22:15:17.520896: +2024-11-22 22:15:17.521111: Epoch 6517 +2024-11-22 22:15:17.521223: Current learning rate: 0.00219 +2024-11-22 22:15:35.922573: train_loss -0.8235 +2024-11-22 22:15:35.922820: val_loss -0.7653 +2024-11-22 22:15:35.922901: Pseudo dice [0.8391] +2024-11-22 22:15:35.922986: Epoch time: 18.4 s +2024-11-22 22:15:36.835058: +2024-11-22 22:15:36.835325: Epoch 6518 +2024-11-22 22:15:36.835442: Current learning rate: 0.00219 +2024-11-22 22:15:56.197379: train_loss -0.8176 +2024-11-22 22:15:56.199818: val_loss -0.7689 +2024-11-22 22:15:56.199925: Pseudo dice [0.8387] +2024-11-22 22:15:56.200015: Epoch time: 19.36 s +2024-11-22 22:15:57.117489: +2024-11-22 22:15:57.117784: Epoch 6519 +2024-11-22 22:15:57.117895: Current learning rate: 0.00219 +2024-11-22 22:16:15.618025: train_loss -0.8119 +2024-11-22 22:16:15.618246: val_loss -0.7521 +2024-11-22 22:16:15.618320: Pseudo dice [0.83] +2024-11-22 22:16:15.618397: Epoch time: 18.5 s +2024-11-22 22:16:16.547097: +2024-11-22 22:16:16.547328: Epoch 6520 +2024-11-22 22:16:16.547446: Current learning rate: 0.00219 +2024-11-22 22:16:34.130336: train_loss -0.8138 +2024-11-22 22:16:34.130551: val_loss -0.7439 +2024-11-22 22:16:34.130624: Pseudo dice [0.8405] +2024-11-22 22:16:34.130698: Epoch time: 17.58 s +2024-11-22 22:16:35.041188: +2024-11-22 22:16:35.041379: Epoch 6521 +2024-11-22 22:16:35.041492: Current learning rate: 0.00219 +2024-11-22 22:16:53.691084: train_loss -0.8161 +2024-11-22 22:16:53.691352: val_loss -0.7267 +2024-11-22 22:16:53.691429: Pseudo dice [0.8168] +2024-11-22 22:16:53.691512: Epoch time: 18.65 s +2024-11-22 22:16:54.602477: +2024-11-22 22:16:54.602673: Epoch 6522 +2024-11-22 22:16:54.602788: Current learning rate: 0.00219 +2024-11-22 22:17:14.046237: train_loss -0.8148 +2024-11-22 22:17:14.046459: val_loss -0.7459 +2024-11-22 22:17:14.046557: Pseudo dice [0.8277] +2024-11-22 22:17:14.046638: Epoch time: 19.44 s +2024-11-22 22:17:14.956095: +2024-11-22 22:17:14.956293: Epoch 6523 +2024-11-22 22:17:14.956403: Current learning rate: 0.00219 +2024-11-22 22:17:33.620912: train_loss -0.8117 +2024-11-22 22:17:33.621147: val_loss -0.7581 +2024-11-22 22:17:33.637240: Pseudo dice [0.824] +2024-11-22 22:17:33.637408: Epoch time: 18.67 s +2024-11-22 22:17:34.584213: +2024-11-22 22:17:34.584416: Epoch 6524 +2024-11-22 22:17:34.584532: Current learning rate: 0.00218 +2024-11-22 22:17:54.082767: train_loss -0.798 +2024-11-22 22:17:54.082985: val_loss -0.748 +2024-11-22 22:17:54.083069: Pseudo dice [0.8385] +2024-11-22 22:17:54.083147: Epoch time: 19.5 s +2024-11-22 22:17:54.993203: +2024-11-22 22:17:54.993395: Epoch 6525 +2024-11-22 22:17:54.993505: Current learning rate: 0.00218 +2024-11-22 22:18:14.442218: train_loss -0.8165 +2024-11-22 22:18:14.442442: val_loss -0.7503 +2024-11-22 22:18:14.442601: Pseudo dice [0.8287] +2024-11-22 22:18:14.442685: Epoch time: 19.45 s +2024-11-22 22:18:15.359645: +2024-11-22 22:18:15.359987: Epoch 6526 +2024-11-22 22:18:15.360106: Current learning rate: 0.00218 +2024-11-22 22:18:33.693966: train_loss -0.8176 +2024-11-22 22:18:33.694207: val_loss -0.767 +2024-11-22 22:18:33.694282: Pseudo dice [0.8482] +2024-11-22 22:18:33.694358: Epoch time: 18.34 s +2024-11-22 22:18:34.604311: +2024-11-22 22:18:34.604533: Epoch 6527 +2024-11-22 22:18:34.604645: Current learning rate: 0.00218 +2024-11-22 22:18:53.758051: train_loss -0.809 +2024-11-22 22:18:53.758275: val_loss -0.7544 +2024-11-22 22:18:53.758349: Pseudo dice [0.8399] +2024-11-22 22:18:53.758424: Epoch time: 19.15 s +2024-11-22 22:18:54.669019: +2024-11-22 22:18:54.669243: Epoch 6528 +2024-11-22 22:18:54.669357: Current learning rate: 0.00218 +2024-11-22 22:19:13.734575: train_loss -0.8118 +2024-11-22 22:19:13.734824: val_loss -0.7384 +2024-11-22 22:19:13.737129: Pseudo dice [0.8344] +2024-11-22 22:19:13.737253: Epoch time: 19.07 s +2024-11-22 22:19:14.768794: +2024-11-22 22:19:14.768983: Epoch 6529 +2024-11-22 22:19:14.769102: Current learning rate: 0.00218 +2024-11-22 22:19:33.402197: train_loss -0.808 +2024-11-22 22:19:33.404589: val_loss -0.7501 +2024-11-22 22:19:33.404675: Pseudo dice [0.8362] +2024-11-22 22:19:33.404753: Epoch time: 18.63 s +2024-11-22 22:19:34.512568: +2024-11-22 22:19:34.512793: Epoch 6530 +2024-11-22 22:19:34.512908: Current learning rate: 0.00218 +2024-11-22 22:19:52.631401: train_loss -0.8159 +2024-11-22 22:19:52.633824: val_loss -0.7833 +2024-11-22 22:19:52.633932: Pseudo dice [0.8297] +2024-11-22 22:19:52.634017: Epoch time: 18.12 s +2024-11-22 22:19:53.572864: +2024-11-22 22:19:53.573069: Epoch 6531 +2024-11-22 22:19:53.573183: Current learning rate: 0.00218 +2024-11-22 22:20:11.488907: train_loss -0.8109 +2024-11-22 22:20:11.489129: val_loss -0.7487 +2024-11-22 22:20:11.489213: Pseudo dice [0.8292] +2024-11-22 22:20:11.489288: Epoch time: 17.92 s +2024-11-22 22:20:12.397039: +2024-11-22 22:20:12.397333: Epoch 6532 +2024-11-22 22:20:12.397446: Current learning rate: 0.00217 +2024-11-22 22:20:31.103989: train_loss -0.8203 +2024-11-22 22:20:31.104235: val_loss -0.7742 +2024-11-22 22:20:31.104315: Pseudo dice [0.8477] +2024-11-22 22:20:31.104401: Epoch time: 18.71 s +2024-11-22 22:20:32.128353: +2024-11-22 22:20:32.128560: Epoch 6533 +2024-11-22 22:20:32.128671: Current learning rate: 0.00217 +2024-11-22 22:20:50.129081: train_loss -0.8094 +2024-11-22 22:20:50.129302: val_loss -0.7569 +2024-11-22 22:20:50.129379: Pseudo dice [0.8342] +2024-11-22 22:20:50.129457: Epoch time: 18.0 s +2024-11-22 22:20:51.038570: +2024-11-22 22:20:51.038763: Epoch 6534 +2024-11-22 22:20:51.038878: Current learning rate: 0.00217 +2024-11-22 22:21:09.912187: train_loss -0.8193 +2024-11-22 22:21:09.914573: val_loss -0.7665 +2024-11-22 22:21:09.914669: Pseudo dice [0.8379] +2024-11-22 22:21:09.914745: Epoch time: 18.87 s +2024-11-22 22:21:10.902881: +2024-11-22 22:21:10.903088: Epoch 6535 +2024-11-22 22:21:10.903200: Current learning rate: 0.00217 +2024-11-22 22:21:28.534168: train_loss -0.8163 +2024-11-22 22:21:28.534395: val_loss -0.7696 +2024-11-22 22:21:28.534468: Pseudo dice [0.837] +2024-11-22 22:21:28.534543: Epoch time: 17.63 s +2024-11-22 22:21:29.602206: +2024-11-22 22:21:29.602426: Epoch 6536 +2024-11-22 22:21:29.602549: Current learning rate: 0.00217 +2024-11-22 22:21:48.540617: train_loss -0.8138 +2024-11-22 22:21:48.547835: val_loss -0.7502 +2024-11-22 22:21:48.547966: Pseudo dice [0.8488] +2024-11-22 22:21:48.548059: Epoch time: 18.94 s +2024-11-22 22:21:49.520038: +2024-11-22 22:21:49.520232: Epoch 6537 +2024-11-22 22:21:49.520340: Current learning rate: 0.00217 +2024-11-22 22:22:07.594339: train_loss -0.8155 +2024-11-22 22:22:07.594560: val_loss -0.7643 +2024-11-22 22:22:07.594636: Pseudo dice [0.831] +2024-11-22 22:22:07.594711: Epoch time: 18.08 s +2024-11-22 22:22:09.003059: +2024-11-22 22:22:09.003281: Epoch 6538 +2024-11-22 22:22:09.003395: Current learning rate: 0.00217 +2024-11-22 22:22:27.866755: train_loss -0.8204 +2024-11-22 22:22:27.866967: val_loss -0.7489 +2024-11-22 22:22:27.867053: Pseudo dice [0.8469] +2024-11-22 22:22:27.867140: Epoch time: 18.86 s +2024-11-22 22:22:29.026980: +2024-11-22 22:22:29.027203: Epoch 6539 +2024-11-22 22:22:29.027321: Current learning rate: 0.00216 +2024-11-22 22:22:47.045865: train_loss -0.8135 +2024-11-22 22:22:47.046173: val_loss -0.7418 +2024-11-22 22:22:47.046260: Pseudo dice [0.8513] +2024-11-22 22:22:47.046343: Epoch time: 18.02 s +2024-11-22 22:22:47.963383: +2024-11-22 22:22:47.963593: Epoch 6540 +2024-11-22 22:22:47.963853: Current learning rate: 0.00216 +2024-11-22 22:23:06.786295: train_loss -0.8147 +2024-11-22 22:23:06.786593: val_loss -0.7569 +2024-11-22 22:23:06.786683: Pseudo dice [0.83] +2024-11-22 22:23:06.786762: Epoch time: 18.82 s +2024-11-22 22:23:07.812680: +2024-11-22 22:23:07.812945: Epoch 6541 +2024-11-22 22:23:07.813066: Current learning rate: 0.00216 +2024-11-22 22:23:25.653813: train_loss -0.8179 +2024-11-22 22:23:25.654068: val_loss -0.7367 +2024-11-22 22:23:25.654147: Pseudo dice [0.8304] +2024-11-22 22:23:25.654244: Epoch time: 17.84 s +2024-11-22 22:23:26.795448: +2024-11-22 22:23:26.795663: Epoch 6542 +2024-11-22 22:23:26.795773: Current learning rate: 0.00216 +2024-11-22 22:23:44.849972: train_loss -0.8195 +2024-11-22 22:23:44.850193: val_loss -0.77 +2024-11-22 22:23:44.850266: Pseudo dice [0.8475] +2024-11-22 22:23:44.850344: Epoch time: 18.06 s +2024-11-22 22:23:45.764707: +2024-11-22 22:23:45.764918: Epoch 6543 +2024-11-22 22:23:45.765049: Current learning rate: 0.00216 +2024-11-22 22:24:04.730738: train_loss -0.8157 +2024-11-22 22:24:04.731346: val_loss -0.7552 +2024-11-22 22:24:04.731426: Pseudo dice [0.8316] +2024-11-22 22:24:04.731507: Epoch time: 18.97 s +2024-11-22 22:24:05.650000: +2024-11-22 22:24:05.650211: Epoch 6544 +2024-11-22 22:24:05.650324: Current learning rate: 0.00216 +2024-11-22 22:24:24.349408: train_loss -0.8168 +2024-11-22 22:24:24.349631: val_loss -0.7644 +2024-11-22 22:24:24.349701: Pseudo dice [0.8354] +2024-11-22 22:24:24.349777: Epoch time: 18.7 s +2024-11-22 22:24:25.267283: +2024-11-22 22:24:25.267507: Epoch 6545 +2024-11-22 22:24:25.267620: Current learning rate: 0.00216 +2024-11-22 22:24:45.273472: train_loss -0.8162 +2024-11-22 22:24:45.273690: val_loss -0.7617 +2024-11-22 22:24:45.273763: Pseudo dice [0.823] +2024-11-22 22:24:45.273838: Epoch time: 20.01 s +2024-11-22 22:24:46.185070: +2024-11-22 22:24:46.185273: Epoch 6546 +2024-11-22 22:24:46.185384: Current learning rate: 0.00216 +2024-11-22 22:25:05.288548: train_loss -0.8154 +2024-11-22 22:25:05.288772: val_loss -0.7522 +2024-11-22 22:25:05.288851: Pseudo dice [0.8157] +2024-11-22 22:25:05.288932: Epoch time: 19.1 s +2024-11-22 22:25:06.206232: +2024-11-22 22:25:06.206427: Epoch 6547 +2024-11-22 22:25:06.206536: Current learning rate: 0.00215 +2024-11-22 22:25:25.629719: train_loss -0.8109 +2024-11-22 22:25:25.630309: val_loss -0.7818 +2024-11-22 22:25:25.630424: Pseudo dice [0.8513] +2024-11-22 22:25:25.630507: Epoch time: 19.42 s +2024-11-22 22:25:26.539767: +2024-11-22 22:25:26.539972: Epoch 6548 +2024-11-22 22:25:26.540088: Current learning rate: 0.00215 +2024-11-22 22:25:46.161980: train_loss -0.819 +2024-11-22 22:25:46.162197: val_loss -0.7652 +2024-11-22 22:25:46.162270: Pseudo dice [0.8464] +2024-11-22 22:25:46.162347: Epoch time: 19.62 s +2024-11-22 22:25:47.087869: +2024-11-22 22:25:47.088733: Epoch 6549 +2024-11-22 22:25:47.088865: Current learning rate: 0.00215 +2024-11-22 22:26:05.514037: train_loss -0.8109 +2024-11-22 22:26:05.514254: val_loss -0.7243 +2024-11-22 22:26:05.514328: Pseudo dice [0.8259] +2024-11-22 22:26:05.514405: Epoch time: 18.43 s +2024-11-22 22:26:06.728519: +2024-11-22 22:26:06.728725: Epoch 6550 +2024-11-22 22:26:06.728838: Current learning rate: 0.00215 +2024-11-22 22:26:25.025975: train_loss -0.8246 +2024-11-22 22:26:25.031401: val_loss -0.7582 +2024-11-22 22:26:25.031530: Pseudo dice [0.8365] +2024-11-22 22:26:25.031631: Epoch time: 18.3 s +2024-11-22 22:26:26.129116: +2024-11-22 22:26:26.129339: Epoch 6551 +2024-11-22 22:26:26.129447: Current learning rate: 0.00215 +2024-11-22 22:26:44.497116: train_loss -0.8196 +2024-11-22 22:26:44.497346: val_loss -0.7565 +2024-11-22 22:26:44.497420: Pseudo dice [0.8376] +2024-11-22 22:26:44.497491: Epoch time: 18.37 s +2024-11-22 22:26:45.397231: +2024-11-22 22:26:45.397427: Epoch 6552 +2024-11-22 22:26:45.397540: Current learning rate: 0.00215 +2024-11-22 22:27:04.062237: train_loss -0.8094 +2024-11-22 22:27:04.062449: val_loss -0.7655 +2024-11-22 22:27:04.062530: Pseudo dice [0.8379] +2024-11-22 22:27:04.062604: Epoch time: 18.67 s +2024-11-22 22:27:04.956013: +2024-11-22 22:27:04.956220: Epoch 6553 +2024-11-22 22:27:04.956327: Current learning rate: 0.00215 +2024-11-22 22:27:23.738515: train_loss -0.8145 +2024-11-22 22:27:23.738741: val_loss -0.7448 +2024-11-22 22:27:23.738814: Pseudo dice [0.8397] +2024-11-22 22:27:23.738892: Epoch time: 18.78 s +2024-11-22 22:27:24.650571: +2024-11-22 22:27:24.650777: Epoch 6554 +2024-11-22 22:27:24.650887: Current learning rate: 0.00214 +2024-11-22 22:27:42.885158: train_loss -0.8189 +2024-11-22 22:27:42.886859: val_loss -0.765 +2024-11-22 22:27:42.886945: Pseudo dice [0.853] +2024-11-22 22:27:42.887028: Epoch time: 18.24 s +2024-11-22 22:27:43.792556: +2024-11-22 22:27:43.792793: Epoch 6555 +2024-11-22 22:27:43.792910: Current learning rate: 0.00214 +2024-11-22 22:28:02.629169: train_loss -0.8141 +2024-11-22 22:28:02.629400: val_loss -0.7498 +2024-11-22 22:28:02.634653: Pseudo dice [0.8426] +2024-11-22 22:28:02.634812: Epoch time: 18.84 s +2024-11-22 22:28:03.754508: +2024-11-22 22:28:03.754737: Epoch 6556 +2024-11-22 22:28:03.754853: Current learning rate: 0.00214 +2024-11-22 22:28:22.083207: train_loss -0.8231 +2024-11-22 22:28:22.083456: val_loss -0.7625 +2024-11-22 22:28:22.083532: Pseudo dice [0.8313] +2024-11-22 22:28:22.083608: Epoch time: 18.33 s +2024-11-22 22:28:23.000986: +2024-11-22 22:28:23.001200: Epoch 6557 +2024-11-22 22:28:23.001310: Current learning rate: 0.00214 +2024-11-22 22:28:41.861651: train_loss -0.8146 +2024-11-22 22:28:41.861883: val_loss -0.7624 +2024-11-22 22:28:41.861959: Pseudo dice [0.8484] +2024-11-22 22:28:41.862048: Epoch time: 18.86 s +2024-11-22 22:28:42.809782: +2024-11-22 22:28:42.809971: Epoch 6558 +2024-11-22 22:28:42.810094: Current learning rate: 0.00214 +2024-11-22 22:29:01.718678: train_loss -0.8153 +2024-11-22 22:29:01.718914: val_loss -0.7794 +2024-11-22 22:29:01.719005: Pseudo dice [0.8439] +2024-11-22 22:29:01.719084: Epoch time: 18.91 s +2024-11-22 22:29:02.807894: +2024-11-22 22:29:02.808128: Epoch 6559 +2024-11-22 22:29:02.808249: Current learning rate: 0.00214 +2024-11-22 22:29:20.174457: train_loss -0.82 +2024-11-22 22:29:20.174685: val_loss -0.7519 +2024-11-22 22:29:20.174756: Pseudo dice [0.8374] +2024-11-22 22:29:20.174831: Epoch time: 17.37 s +2024-11-22 22:29:21.241820: +2024-11-22 22:29:21.242053: Epoch 6560 +2024-11-22 22:29:21.242172: Current learning rate: 0.00214 +2024-11-22 22:29:39.857063: train_loss -0.8132 +2024-11-22 22:29:39.857536: val_loss -0.7539 +2024-11-22 22:29:39.857639: Pseudo dice [0.8328] +2024-11-22 22:29:39.857731: Epoch time: 18.62 s +2024-11-22 22:29:40.773244: +2024-11-22 22:29:40.773531: Epoch 6561 +2024-11-22 22:29:40.773643: Current learning rate: 0.00214 +2024-11-22 22:29:59.692289: train_loss -0.8153 +2024-11-22 22:29:59.692524: val_loss -0.7363 +2024-11-22 22:29:59.692601: Pseudo dice [0.8207] +2024-11-22 22:29:59.710805: Epoch time: 18.92 s +2024-11-22 22:30:00.626217: +2024-11-22 22:30:00.626440: Epoch 6562 +2024-11-22 22:30:00.626554: Current learning rate: 0.00213 +2024-11-22 22:30:18.967354: train_loss -0.8073 +2024-11-22 22:30:18.967929: val_loss -0.7205 +2024-11-22 22:30:18.968020: Pseudo dice [0.8187] +2024-11-22 22:30:18.968099: Epoch time: 18.34 s +2024-11-22 22:30:19.883862: +2024-11-22 22:30:19.884074: Epoch 6563 +2024-11-22 22:30:19.884184: Current learning rate: 0.00213 +2024-11-22 22:30:38.809832: train_loss -0.8079 +2024-11-22 22:30:38.810049: val_loss -0.7531 +2024-11-22 22:30:38.810179: Pseudo dice [0.8467] +2024-11-22 22:30:38.810258: Epoch time: 18.93 s +2024-11-22 22:30:39.723018: +2024-11-22 22:30:39.723246: Epoch 6564 +2024-11-22 22:30:39.723366: Current learning rate: 0.00213 +2024-11-22 22:30:58.215102: train_loss -0.8193 +2024-11-22 22:30:58.215354: val_loss -0.772 +2024-11-22 22:30:58.215427: Pseudo dice [0.8497] +2024-11-22 22:30:58.215507: Epoch time: 18.49 s +2024-11-22 22:30:59.175146: +2024-11-22 22:30:59.175345: Epoch 6565 +2024-11-22 22:30:59.175456: Current learning rate: 0.00213 +2024-11-22 22:31:18.764112: train_loss -0.8167 +2024-11-22 22:31:18.764321: val_loss -0.7409 +2024-11-22 22:31:18.764398: Pseudo dice [0.8262] +2024-11-22 22:31:18.764475: Epoch time: 19.59 s +2024-11-22 22:31:19.679119: +2024-11-22 22:31:19.679456: Epoch 6566 +2024-11-22 22:31:19.679574: Current learning rate: 0.00213 +2024-11-22 22:31:38.468269: train_loss -0.8129 +2024-11-22 22:31:38.468503: val_loss -0.7784 +2024-11-22 22:31:38.468638: Pseudo dice [0.8414] +2024-11-22 22:31:38.468714: Epoch time: 18.79 s +2024-11-22 22:31:39.383710: +2024-11-22 22:31:39.383918: Epoch 6567 +2024-11-22 22:31:39.384036: Current learning rate: 0.00213 +2024-11-22 22:31:58.341871: train_loss -0.8201 +2024-11-22 22:31:58.342148: val_loss -0.758 +2024-11-22 22:31:58.342228: Pseudo dice [0.8394] +2024-11-22 22:31:58.342335: Epoch time: 18.96 s +2024-11-22 22:31:59.255588: +2024-11-22 22:31:59.255793: Epoch 6568 +2024-11-22 22:31:59.255908: Current learning rate: 0.00213 +2024-11-22 22:32:16.395655: train_loss -0.8229 +2024-11-22 22:32:16.395887: val_loss -0.7564 +2024-11-22 22:32:16.395982: Pseudo dice [0.8291] +2024-11-22 22:32:16.396074: Epoch time: 17.14 s +2024-11-22 22:32:17.312414: +2024-11-22 22:32:17.312629: Epoch 6569 +2024-11-22 22:32:17.312744: Current learning rate: 0.00212 +2024-11-22 22:32:35.857498: train_loss -0.8228 +2024-11-22 22:32:35.857739: val_loss -0.7596 +2024-11-22 22:32:35.857817: Pseudo dice [0.833] +2024-11-22 22:32:35.857902: Epoch time: 18.55 s +2024-11-22 22:32:36.778499: +2024-11-22 22:32:36.778694: Epoch 6570 +2024-11-22 22:32:36.778805: Current learning rate: 0.00212 +2024-11-22 22:32:55.096887: train_loss -0.82 +2024-11-22 22:32:55.099247: val_loss -0.7592 +2024-11-22 22:32:55.099335: Pseudo dice [0.8366] +2024-11-22 22:32:55.099411: Epoch time: 18.32 s +2024-11-22 22:32:56.227264: +2024-11-22 22:32:56.227472: Epoch 6571 +2024-11-22 22:32:56.227586: Current learning rate: 0.00212 +2024-11-22 22:33:14.734468: train_loss -0.809 +2024-11-22 22:33:14.734698: val_loss -0.7448 +2024-11-22 22:33:14.734772: Pseudo dice [0.8264] +2024-11-22 22:33:14.734858: Epoch time: 18.51 s +2024-11-22 22:33:16.012883: +2024-11-22 22:33:16.013117: Epoch 6572 +2024-11-22 22:33:16.013235: Current learning rate: 0.00212 +2024-11-22 22:33:35.121497: train_loss -0.8009 +2024-11-22 22:33:35.122104: val_loss -0.7153 +2024-11-22 22:33:35.122190: Pseudo dice [0.8063] +2024-11-22 22:33:35.122274: Epoch time: 19.11 s +2024-11-22 22:33:36.048934: +2024-11-22 22:33:36.049145: Epoch 6573 +2024-11-22 22:33:36.049256: Current learning rate: 0.00212 +2024-11-22 22:33:54.892261: train_loss -0.8082 +2024-11-22 22:33:54.892483: val_loss -0.7697 +2024-11-22 22:33:54.892557: Pseudo dice [0.8254] +2024-11-22 22:33:54.892633: Epoch time: 18.84 s +2024-11-22 22:33:55.801411: +2024-11-22 22:33:55.801607: Epoch 6574 +2024-11-22 22:33:55.801718: Current learning rate: 0.00212 +2024-11-22 22:34:15.149064: train_loss -0.8136 +2024-11-22 22:34:15.180467: val_loss -0.7348 +2024-11-22 22:34:15.180682: Pseudo dice [0.8029] +2024-11-22 22:34:15.180776: Epoch time: 19.35 s +2024-11-22 22:34:16.102655: +2024-11-22 22:34:16.102895: Epoch 6575 +2024-11-22 22:34:16.103049: Current learning rate: 0.00212 +2024-11-22 22:34:34.489567: train_loss -0.8128 +2024-11-22 22:34:34.489819: val_loss -0.7467 +2024-11-22 22:34:34.489895: Pseudo dice [0.8304] +2024-11-22 22:34:34.489978: Epoch time: 18.39 s +2024-11-22 22:34:35.412723: +2024-11-22 22:34:35.412935: Epoch 6576 +2024-11-22 22:34:35.413057: Current learning rate: 0.00212 +2024-11-22 22:34:55.053074: train_loss -0.8173 +2024-11-22 22:34:55.053308: val_loss -0.7417 +2024-11-22 22:34:55.053386: Pseudo dice [0.8043] +2024-11-22 22:34:55.053464: Epoch time: 19.64 s +2024-11-22 22:34:55.967169: +2024-11-22 22:34:55.967371: Epoch 6577 +2024-11-22 22:34:55.967494: Current learning rate: 0.00211 +2024-11-22 22:35:14.142039: train_loss -0.8137 +2024-11-22 22:35:14.148254: val_loss -0.7617 +2024-11-22 22:35:14.148357: Pseudo dice [0.8419] +2024-11-22 22:35:14.149863: Epoch time: 18.18 s +2024-11-22 22:35:15.069944: +2024-11-22 22:35:15.070189: Epoch 6578 +2024-11-22 22:35:15.070303: Current learning rate: 0.00211 +2024-11-22 22:35:34.119214: train_loss -0.809 +2024-11-22 22:35:34.119442: val_loss -0.7662 +2024-11-22 22:35:34.119517: Pseudo dice [0.8426] +2024-11-22 22:35:34.119601: Epoch time: 19.05 s +2024-11-22 22:35:35.034516: +2024-11-22 22:35:35.034826: Epoch 6579 +2024-11-22 22:35:35.034941: Current learning rate: 0.00211 +2024-11-22 22:35:53.874398: train_loss -0.8121 +2024-11-22 22:35:53.874619: val_loss -0.7588 +2024-11-22 22:35:53.874696: Pseudo dice [0.8364] +2024-11-22 22:35:53.874774: Epoch time: 18.84 s +2024-11-22 22:35:54.786232: +2024-11-22 22:35:54.786495: Epoch 6580 +2024-11-22 22:35:54.786610: Current learning rate: 0.00211 +2024-11-22 22:36:13.556345: train_loss -0.8079 +2024-11-22 22:36:13.556562: val_loss -0.7598 +2024-11-22 22:36:13.556636: Pseudo dice [0.8412] +2024-11-22 22:36:13.556711: Epoch time: 18.77 s +2024-11-22 22:36:14.468020: +2024-11-22 22:36:14.468218: Epoch 6581 +2024-11-22 22:36:14.468329: Current learning rate: 0.00211 +2024-11-22 22:36:33.646862: train_loss -0.8067 +2024-11-22 22:36:33.647136: val_loss -0.7873 +2024-11-22 22:36:33.647214: Pseudo dice [0.8479] +2024-11-22 22:36:33.647293: Epoch time: 19.18 s +2024-11-22 22:36:34.565821: +2024-11-22 22:36:34.566024: Epoch 6582 +2024-11-22 22:36:34.566137: Current learning rate: 0.00211 +2024-11-22 22:36:52.411381: train_loss -0.8156 +2024-11-22 22:36:52.411669: val_loss -0.7309 +2024-11-22 22:36:52.411746: Pseudo dice [0.8248] +2024-11-22 22:36:52.411829: Epoch time: 17.85 s +2024-11-22 22:36:53.336406: +2024-11-22 22:36:53.336604: Epoch 6583 +2024-11-22 22:36:53.336720: Current learning rate: 0.00211 +2024-11-22 22:37:12.774299: train_loss -0.8148 +2024-11-22 22:37:12.774580: val_loss -0.7629 +2024-11-22 22:37:12.774657: Pseudo dice [0.8152] +2024-11-22 22:37:12.774733: Epoch time: 19.44 s +2024-11-22 22:37:13.692214: +2024-11-22 22:37:13.692429: Epoch 6584 +2024-11-22 22:37:13.692542: Current learning rate: 0.0021 +2024-11-22 22:37:32.981305: train_loss -0.8138 +2024-11-22 22:37:32.981529: val_loss -0.7665 +2024-11-22 22:37:32.981601: Pseudo dice [0.8289] +2024-11-22 22:37:32.981674: Epoch time: 19.29 s +2024-11-22 22:37:33.891712: +2024-11-22 22:37:33.891924: Epoch 6585 +2024-11-22 22:37:33.892035: Current learning rate: 0.0021 +2024-11-22 22:37:53.065027: train_loss -0.8248 +2024-11-22 22:37:53.067863: val_loss -0.7643 +2024-11-22 22:37:53.067957: Pseudo dice [0.8198] +2024-11-22 22:37:53.068053: Epoch time: 19.17 s +2024-11-22 22:37:54.184691: +2024-11-22 22:37:54.184920: Epoch 6586 +2024-11-22 22:37:54.185036: Current learning rate: 0.0021 +2024-11-22 22:38:12.403107: train_loss -0.8128 +2024-11-22 22:38:12.403348: val_loss -0.7729 +2024-11-22 22:38:12.403483: Pseudo dice [0.8339] +2024-11-22 22:38:12.403565: Epoch time: 18.22 s +2024-11-22 22:38:13.323161: +2024-11-22 22:38:13.323355: Epoch 6587 +2024-11-22 22:38:13.323473: Current learning rate: 0.0021 +2024-11-22 22:38:32.212253: train_loss -0.8016 +2024-11-22 22:38:32.212489: val_loss -0.7676 +2024-11-22 22:38:32.212566: Pseudo dice [0.838] +2024-11-22 22:38:32.212644: Epoch time: 18.89 s +2024-11-22 22:38:33.135495: +2024-11-22 22:38:33.135689: Epoch 6588 +2024-11-22 22:38:33.135797: Current learning rate: 0.0021 +2024-11-22 22:38:51.084928: train_loss -0.8201 +2024-11-22 22:38:51.085183: val_loss -0.7377 +2024-11-22 22:38:51.085278: Pseudo dice [0.8339] +2024-11-22 22:38:51.085356: Epoch time: 17.95 s +2024-11-22 22:38:52.003169: +2024-11-22 22:38:52.003384: Epoch 6589 +2024-11-22 22:38:52.003503: Current learning rate: 0.0021 +2024-11-22 22:39:10.675654: train_loss -0.8143 +2024-11-22 22:39:10.675887: val_loss -0.7553 +2024-11-22 22:39:10.675962: Pseudo dice [0.8427] +2024-11-22 22:39:10.676051: Epoch time: 18.67 s +2024-11-22 22:39:11.592268: +2024-11-22 22:39:11.592463: Epoch 6590 +2024-11-22 22:39:11.592575: Current learning rate: 0.0021 +2024-11-22 22:39:29.955071: train_loss -0.8114 +2024-11-22 22:39:29.955287: val_loss -0.7715 +2024-11-22 22:39:29.955362: Pseudo dice [0.8462] +2024-11-22 22:39:29.955441: Epoch time: 18.36 s +2024-11-22 22:39:30.875488: +2024-11-22 22:39:30.875684: Epoch 6591 +2024-11-22 22:39:30.875796: Current learning rate: 0.0021 +2024-11-22 22:39:49.176646: train_loss -0.8193 +2024-11-22 22:39:49.176874: val_loss -0.7321 +2024-11-22 22:39:49.176951: Pseudo dice [0.8369] +2024-11-22 22:39:49.177034: Epoch time: 18.3 s +2024-11-22 22:39:50.104640: +2024-11-22 22:39:50.104906: Epoch 6592 +2024-11-22 22:39:50.105022: Current learning rate: 0.00209 +2024-11-22 22:40:09.304139: train_loss -0.8153 +2024-11-22 22:40:09.306527: val_loss -0.7449 +2024-11-22 22:40:09.306619: Pseudo dice [0.8432] +2024-11-22 22:40:09.306703: Epoch time: 19.2 s +2024-11-22 22:40:10.263173: +2024-11-22 22:40:10.263367: Epoch 6593 +2024-11-22 22:40:10.263486: Current learning rate: 0.00209 +2024-11-22 22:40:28.875308: train_loss -0.8228 +2024-11-22 22:40:28.875544: val_loss -0.7395 +2024-11-22 22:40:28.875617: Pseudo dice [0.8308] +2024-11-22 22:40:28.875701: Epoch time: 18.61 s +2024-11-22 22:40:29.785560: +2024-11-22 22:40:29.785762: Epoch 6594 +2024-11-22 22:40:29.785880: Current learning rate: 0.00209 +2024-11-22 22:40:48.651002: train_loss -0.8155 +2024-11-22 22:40:48.651225: val_loss -0.7585 +2024-11-22 22:40:48.651299: Pseudo dice [0.8256] +2024-11-22 22:40:48.656533: Epoch time: 18.87 s +2024-11-22 22:40:50.028724: +2024-11-22 22:40:50.028935: Epoch 6595 +2024-11-22 22:40:50.029057: Current learning rate: 0.00209 +2024-11-22 22:41:08.497597: train_loss -0.8207 +2024-11-22 22:41:08.497829: val_loss -0.7481 +2024-11-22 22:41:08.497906: Pseudo dice [0.8234] +2024-11-22 22:41:08.497987: Epoch time: 18.47 s +2024-11-22 22:41:09.406869: +2024-11-22 22:41:09.407104: Epoch 6596 +2024-11-22 22:41:09.407223: Current learning rate: 0.00209 +2024-11-22 22:41:27.856437: train_loss -0.8219 +2024-11-22 22:41:27.856678: val_loss -0.7667 +2024-11-22 22:41:27.856751: Pseudo dice [0.8379] +2024-11-22 22:41:27.856833: Epoch time: 18.45 s +2024-11-22 22:41:28.774133: +2024-11-22 22:41:28.774351: Epoch 6597 +2024-11-22 22:41:28.774467: Current learning rate: 0.00209 +2024-11-22 22:41:47.005287: train_loss -0.8125 +2024-11-22 22:41:47.005500: val_loss -0.7603 +2024-11-22 22:41:47.005573: Pseudo dice [0.8337] +2024-11-22 22:41:47.005651: Epoch time: 18.23 s +2024-11-22 22:41:47.921838: +2024-11-22 22:41:47.922058: Epoch 6598 +2024-11-22 22:41:47.922172: Current learning rate: 0.00209 +2024-11-22 22:42:05.604501: train_loss -0.8013 +2024-11-22 22:42:05.604719: val_loss -0.7617 +2024-11-22 22:42:05.604793: Pseudo dice [0.824] +2024-11-22 22:42:05.604871: Epoch time: 17.68 s +2024-11-22 22:42:06.518198: +2024-11-22 22:42:06.518399: Epoch 6599 +2024-11-22 22:42:06.518508: Current learning rate: 0.00208 +2024-11-22 22:42:25.538326: train_loss -0.8119 +2024-11-22 22:42:25.538544: val_loss -0.7625 +2024-11-22 22:42:25.538617: Pseudo dice [0.8392] +2024-11-22 22:42:25.538692: Epoch time: 19.02 s +2024-11-22 22:42:26.765527: +2024-11-22 22:42:26.765836: Epoch 6600 +2024-11-22 22:42:26.765949: Current learning rate: 0.00208 +2024-11-22 22:42:44.963319: train_loss -0.8079 +2024-11-22 22:42:44.963570: val_loss -0.7637 +2024-11-22 22:42:44.963645: Pseudo dice [0.8305] +2024-11-22 22:42:44.963731: Epoch time: 18.2 s +2024-11-22 22:42:45.996297: +2024-11-22 22:42:45.996495: Epoch 6601 +2024-11-22 22:42:45.996604: Current learning rate: 0.00208 +2024-11-22 22:43:05.131034: train_loss -0.817 +2024-11-22 22:43:05.131257: val_loss -0.7558 +2024-11-22 22:43:05.131335: Pseudo dice [0.8317] +2024-11-22 22:43:05.131415: Epoch time: 19.14 s +2024-11-22 22:43:06.140144: +2024-11-22 22:43:06.140356: Epoch 6602 +2024-11-22 22:43:06.140479: Current learning rate: 0.00208 +2024-11-22 22:43:24.453034: train_loss -0.8172 +2024-11-22 22:43:24.453286: val_loss -0.7618 +2024-11-22 22:43:24.453362: Pseudo dice [0.8284] +2024-11-22 22:43:24.453463: Epoch time: 18.31 s +2024-11-22 22:43:25.373947: +2024-11-22 22:43:25.374229: Epoch 6603 +2024-11-22 22:43:25.374342: Current learning rate: 0.00208 +2024-11-22 22:43:44.944807: train_loss -0.8176 +2024-11-22 22:43:44.945044: val_loss -0.7377 +2024-11-22 22:43:44.945124: Pseudo dice [0.8383] +2024-11-22 22:43:44.945206: Epoch time: 19.57 s +2024-11-22 22:43:45.859378: +2024-11-22 22:43:45.859591: Epoch 6604 +2024-11-22 22:43:45.859706: Current learning rate: 0.00208 +2024-11-22 22:44:05.067661: train_loss -0.8025 +2024-11-22 22:44:05.068231: val_loss -0.7657 +2024-11-22 22:44:05.068313: Pseudo dice [0.8336] +2024-11-22 22:44:05.068395: Epoch time: 19.21 s +2024-11-22 22:44:05.982785: +2024-11-22 22:44:05.982985: Epoch 6605 +2024-11-22 22:44:05.983101: Current learning rate: 0.00208 +2024-11-22 22:44:24.276947: train_loss -0.8228 +2024-11-22 22:44:24.277196: val_loss -0.7485 +2024-11-22 22:44:24.277281: Pseudo dice [0.8296] +2024-11-22 22:44:24.277357: Epoch time: 18.29 s +2024-11-22 22:44:25.193313: +2024-11-22 22:44:25.193505: Epoch 6606 +2024-11-22 22:44:25.193621: Current learning rate: 0.00208 +2024-11-22 22:44:43.372496: train_loss -0.821 +2024-11-22 22:44:43.372714: val_loss -0.7506 +2024-11-22 22:44:43.372788: Pseudo dice [0.8382] +2024-11-22 22:44:43.372861: Epoch time: 18.18 s +2024-11-22 22:44:44.300653: +2024-11-22 22:44:44.300887: Epoch 6607 +2024-11-22 22:44:44.301005: Current learning rate: 0.00207 +2024-11-22 22:45:03.837827: train_loss -0.8256 +2024-11-22 22:45:03.840246: val_loss -0.7645 +2024-11-22 22:45:03.840331: Pseudo dice [0.845] +2024-11-22 22:45:03.840416: Epoch time: 19.54 s +2024-11-22 22:45:04.788195: +2024-11-22 22:45:04.788404: Epoch 6608 +2024-11-22 22:45:04.788515: Current learning rate: 0.00207 +2024-11-22 22:45:23.196417: train_loss -0.8149 +2024-11-22 22:45:23.196636: val_loss -0.7659 +2024-11-22 22:45:23.196711: Pseudo dice [0.8328] +2024-11-22 22:45:23.196790: Epoch time: 18.41 s +2024-11-22 22:45:24.111686: +2024-11-22 22:45:24.111999: Epoch 6609 +2024-11-22 22:45:24.112117: Current learning rate: 0.00207 +2024-11-22 22:45:42.923476: train_loss -0.813 +2024-11-22 22:45:42.923690: val_loss -0.7645 +2024-11-22 22:45:42.928920: Pseudo dice [0.8486] +2024-11-22 22:45:42.929066: Epoch time: 18.81 s +2024-11-22 22:45:44.137892: +2024-11-22 22:45:44.138119: Epoch 6610 +2024-11-22 22:45:44.138228: Current learning rate: 0.00207 +2024-11-22 22:46:02.642129: train_loss -0.8182 +2024-11-22 22:46:02.642354: val_loss -0.7522 +2024-11-22 22:46:02.642428: Pseudo dice [0.8294] +2024-11-22 22:46:02.642508: Epoch time: 18.5 s +2024-11-22 22:46:03.717493: +2024-11-22 22:46:03.717701: Epoch 6611 +2024-11-22 22:46:03.717809: Current learning rate: 0.00207 +2024-11-22 22:46:21.888171: train_loss -0.8181 +2024-11-22 22:46:21.888426: val_loss -0.7549 +2024-11-22 22:46:21.888554: Pseudo dice [0.8274] +2024-11-22 22:46:21.888636: Epoch time: 18.17 s +2024-11-22 22:46:22.849543: +2024-11-22 22:46:22.849760: Epoch 6612 +2024-11-22 22:46:22.849872: Current learning rate: 0.00207 +2024-11-22 22:46:41.163507: train_loss -0.8061 +2024-11-22 22:46:41.163780: val_loss -0.7456 +2024-11-22 22:46:41.165620: Pseudo dice [0.8435] +2024-11-22 22:46:41.165807: Epoch time: 18.31 s +2024-11-22 22:46:42.092456: +2024-11-22 22:46:42.092680: Epoch 6613 +2024-11-22 22:46:42.092798: Current learning rate: 0.00207 +2024-11-22 22:47:00.339190: train_loss -0.8188 +2024-11-22 22:47:00.339414: val_loss -0.7585 +2024-11-22 22:47:00.339496: Pseudo dice [0.8342] +2024-11-22 22:47:00.339574: Epoch time: 18.25 s +2024-11-22 22:47:01.352848: +2024-11-22 22:47:01.353066: Epoch 6614 +2024-11-22 22:47:01.353180: Current learning rate: 0.00206 +2024-11-22 22:47:20.402790: train_loss -0.8173 +2024-11-22 22:47:20.403032: val_loss -0.7584 +2024-11-22 22:47:20.403108: Pseudo dice [0.8406] +2024-11-22 22:47:20.403194: Epoch time: 19.05 s +2024-11-22 22:47:21.314203: +2024-11-22 22:47:21.314465: Epoch 6615 +2024-11-22 22:47:21.314577: Current learning rate: 0.00206 +2024-11-22 22:47:39.800094: train_loss -0.8191 +2024-11-22 22:47:39.800326: val_loss -0.7362 +2024-11-22 22:47:39.800400: Pseudo dice [0.8179] +2024-11-22 22:47:39.800477: Epoch time: 18.49 s +2024-11-22 22:47:40.879228: +2024-11-22 22:47:40.879442: Epoch 6616 +2024-11-22 22:47:40.879558: Current learning rate: 0.00206 +2024-11-22 22:48:00.034500: train_loss -0.8134 +2024-11-22 22:48:00.034780: val_loss -0.7389 +2024-11-22 22:48:00.034857: Pseudo dice [0.8215] +2024-11-22 22:48:00.034944: Epoch time: 19.16 s +2024-11-22 22:48:00.948959: +2024-11-22 22:48:00.949221: Epoch 6617 +2024-11-22 22:48:00.949343: Current learning rate: 0.00206 +2024-11-22 22:48:18.934843: train_loss -0.8152 +2024-11-22 22:48:18.937189: val_loss -0.778 +2024-11-22 22:48:18.937280: Pseudo dice [0.8566] +2024-11-22 22:48:18.937362: Epoch time: 17.99 s +2024-11-22 22:48:20.300979: +2024-11-22 22:48:20.301177: Epoch 6618 +2024-11-22 22:48:20.301293: Current learning rate: 0.00206 +2024-11-22 22:48:38.808914: train_loss -0.8216 +2024-11-22 22:48:38.809160: val_loss -0.7411 +2024-11-22 22:48:38.809235: Pseudo dice [0.8226] +2024-11-22 22:48:38.809316: Epoch time: 18.51 s +2024-11-22 22:48:39.728686: +2024-11-22 22:48:39.728950: Epoch 6619 +2024-11-22 22:48:39.729070: Current learning rate: 0.00206 +2024-11-22 22:48:58.267713: train_loss -0.8151 +2024-11-22 22:48:58.267932: val_loss -0.7642 +2024-11-22 22:48:58.268010: Pseudo dice [0.8407] +2024-11-22 22:48:58.268085: Epoch time: 18.54 s +2024-11-22 22:48:59.185720: +2024-11-22 22:48:59.185934: Epoch 6620 +2024-11-22 22:48:59.186051: Current learning rate: 0.00206 +2024-11-22 22:49:17.212343: train_loss -0.8247 +2024-11-22 22:49:17.214747: val_loss -0.769 +2024-11-22 22:49:17.214889: Pseudo dice [0.8411] +2024-11-22 22:49:17.214970: Epoch time: 18.03 s +2024-11-22 22:49:18.148237: +2024-11-22 22:49:18.148437: Epoch 6621 +2024-11-22 22:49:18.148667: Current learning rate: 0.00206 +2024-11-22 22:49:36.769835: train_loss -0.814 +2024-11-22 22:49:36.770074: val_loss -0.7627 +2024-11-22 22:49:36.770151: Pseudo dice [0.8377] +2024-11-22 22:49:36.770244: Epoch time: 18.62 s +2024-11-22 22:49:37.702909: +2024-11-22 22:49:37.703170: Epoch 6622 +2024-11-22 22:49:37.703285: Current learning rate: 0.00205 +2024-11-22 22:49:56.740716: train_loss -0.8222 +2024-11-22 22:49:56.740935: val_loss -0.7703 +2024-11-22 22:49:56.741018: Pseudo dice [0.8402] +2024-11-22 22:49:56.741096: Epoch time: 19.04 s +2024-11-22 22:49:57.840674: +2024-11-22 22:49:57.841002: Epoch 6623 +2024-11-22 22:49:57.841119: Current learning rate: 0.00205 +2024-11-22 22:50:16.401713: train_loss -0.8199 +2024-11-22 22:50:16.401930: val_loss -0.7408 +2024-11-22 22:50:16.402021: Pseudo dice [0.8352] +2024-11-22 22:50:16.402099: Epoch time: 18.56 s +2024-11-22 22:50:17.311515: +2024-11-22 22:50:17.311709: Epoch 6624 +2024-11-22 22:50:17.311833: Current learning rate: 0.00205 +2024-11-22 22:50:35.959552: train_loss -0.8193 +2024-11-22 22:50:35.959776: val_loss -0.7548 +2024-11-22 22:50:35.965055: Pseudo dice [0.8365] +2024-11-22 22:50:35.965183: Epoch time: 18.65 s +2024-11-22 22:50:37.048728: +2024-11-22 22:50:37.048929: Epoch 6625 +2024-11-22 22:50:37.049049: Current learning rate: 0.00205 +2024-11-22 22:50:56.354103: train_loss -0.8169 +2024-11-22 22:50:56.354391: val_loss -0.7516 +2024-11-22 22:50:56.354466: Pseudo dice [0.8437] +2024-11-22 22:50:56.354548: Epoch time: 19.31 s +2024-11-22 22:50:57.267928: +2024-11-22 22:50:57.268218: Epoch 6626 +2024-11-22 22:50:57.268337: Current learning rate: 0.00205 +2024-11-22 22:51:15.399186: train_loss -0.8123 +2024-11-22 22:51:15.399409: val_loss -0.7646 +2024-11-22 22:51:15.399485: Pseudo dice [0.834] +2024-11-22 22:51:15.399559: Epoch time: 18.13 s +2024-11-22 22:51:16.356536: +2024-11-22 22:51:16.356737: Epoch 6627 +2024-11-22 22:51:16.356846: Current learning rate: 0.00205 +2024-11-22 22:51:35.937498: train_loss -0.8081 +2024-11-22 22:51:35.937716: val_loss -0.7615 +2024-11-22 22:51:35.937793: Pseudo dice [0.8445] +2024-11-22 22:51:35.937867: Epoch time: 19.58 s +2024-11-22 22:51:36.874576: +2024-11-22 22:51:36.874789: Epoch 6628 +2024-11-22 22:51:36.874903: Current learning rate: 0.00205 +2024-11-22 22:51:55.169115: train_loss -0.8151 +2024-11-22 22:51:55.169363: val_loss -0.7881 +2024-11-22 22:51:55.169440: Pseudo dice [0.8703] +2024-11-22 22:51:55.169528: Epoch time: 18.3 s +2024-11-22 22:51:55.169592: Yayy! New best EMA pseudo Dice: 0.8405 +2024-11-22 22:51:56.774630: +2024-11-22 22:51:56.774869: Epoch 6629 +2024-11-22 22:51:56.774987: Current learning rate: 0.00204 +2024-11-22 22:52:15.210843: train_loss -0.8163 +2024-11-22 22:52:15.211071: val_loss -0.747 +2024-11-22 22:52:15.211162: Pseudo dice [0.8308] +2024-11-22 22:52:15.211292: Epoch time: 18.44 s +2024-11-22 22:52:16.122875: +2024-11-22 22:52:16.123200: Epoch 6630 +2024-11-22 22:52:16.123311: Current learning rate: 0.00204 +2024-11-22 22:52:35.814802: train_loss -0.8173 +2024-11-22 22:52:35.815034: val_loss -0.7569 +2024-11-22 22:52:35.815110: Pseudo dice [0.8317] +2024-11-22 22:52:35.815186: Epoch time: 19.69 s +2024-11-22 22:52:36.721278: +2024-11-22 22:52:36.721529: Epoch 6631 +2024-11-22 22:52:36.721647: Current learning rate: 0.00204 +2024-11-22 22:52:55.027744: train_loss -0.8189 +2024-11-22 22:52:55.028046: val_loss -0.7451 +2024-11-22 22:52:55.028127: Pseudo dice [0.8361] +2024-11-22 22:52:55.028203: Epoch time: 18.31 s +2024-11-22 22:52:55.952930: +2024-11-22 22:52:55.953153: Epoch 6632 +2024-11-22 22:52:55.953276: Current learning rate: 0.00204 +2024-11-22 22:53:15.377798: train_loss -0.8088 +2024-11-22 22:53:15.378066: val_loss -0.7577 +2024-11-22 22:53:15.378145: Pseudo dice [0.8393] +2024-11-22 22:53:15.378235: Epoch time: 19.42 s +2024-11-22 22:53:16.503476: +2024-11-22 22:53:16.503685: Epoch 6633 +2024-11-22 22:53:16.503802: Current learning rate: 0.00204 +2024-11-22 22:53:35.048048: train_loss -0.809 +2024-11-22 22:53:35.048273: val_loss -0.7624 +2024-11-22 22:53:35.048353: Pseudo dice [0.852] +2024-11-22 22:53:35.048442: Epoch time: 18.55 s +2024-11-22 22:53:36.067176: +2024-11-22 22:53:36.067395: Epoch 6634 +2024-11-22 22:53:36.067512: Current learning rate: 0.00204 +2024-11-22 22:53:54.308923: train_loss -0.8176 +2024-11-22 22:53:54.309472: val_loss -0.7614 +2024-11-22 22:53:54.309551: Pseudo dice [0.8297] +2024-11-22 22:53:54.309634: Epoch time: 18.24 s +2024-11-22 22:53:55.236481: +2024-11-22 22:53:55.236678: Epoch 6635 +2024-11-22 22:53:55.236789: Current learning rate: 0.00204 +2024-11-22 22:54:13.727973: train_loss -0.8186 +2024-11-22 22:54:13.728211: val_loss -0.7631 +2024-11-22 22:54:13.728353: Pseudo dice [0.8362] +2024-11-22 22:54:13.728434: Epoch time: 18.49 s +2024-11-22 22:54:14.645986: +2024-11-22 22:54:14.646199: Epoch 6636 +2024-11-22 22:54:14.646348: Current learning rate: 0.00203 +2024-11-22 22:54:32.283201: train_loss -0.818 +2024-11-22 22:54:32.283436: val_loss -0.7778 +2024-11-22 22:54:32.283515: Pseudo dice [0.8566] +2024-11-22 22:54:32.283595: Epoch time: 17.64 s +2024-11-22 22:54:33.193468: +2024-11-22 22:54:33.193697: Epoch 6637 +2024-11-22 22:54:33.193825: Current learning rate: 0.00203 +2024-11-22 22:54:51.741391: train_loss -0.8229 +2024-11-22 22:54:51.741655: val_loss -0.7957 +2024-11-22 22:54:51.741732: Pseudo dice [0.854] +2024-11-22 22:54:51.750638: Epoch time: 18.55 s +2024-11-22 22:54:51.750786: Yayy! New best EMA pseudo Dice: 0.8418 +2024-11-22 22:54:52.988847: +2024-11-22 22:54:52.989069: Epoch 6638 +2024-11-22 22:54:52.989189: Current learning rate: 0.00203 +2024-11-22 22:55:12.900472: train_loss -0.815 +2024-11-22 22:55:12.905865: val_loss -0.7695 +2024-11-22 22:55:12.905968: Pseudo dice [0.8329] +2024-11-22 22:55:12.906055: Epoch time: 19.91 s +2024-11-22 22:55:13.921773: +2024-11-22 22:55:13.922027: Epoch 6639 +2024-11-22 22:55:13.922144: Current learning rate: 0.00203 +2024-11-22 22:55:33.234145: train_loss -0.8117 +2024-11-22 22:55:33.234388: val_loss -0.7438 +2024-11-22 22:55:33.234465: Pseudo dice [0.8436] +2024-11-22 22:55:33.234548: Epoch time: 19.31 s +2024-11-22 22:55:34.174436: +2024-11-22 22:55:34.174642: Epoch 6640 +2024-11-22 22:55:34.174757: Current learning rate: 0.00203 +2024-11-22 22:55:53.294599: train_loss -0.8216 +2024-11-22 22:55:53.294813: val_loss -0.7716 +2024-11-22 22:55:53.294889: Pseudo dice [0.8249] +2024-11-22 22:55:53.295036: Epoch time: 19.12 s +2024-11-22 22:55:54.591053: +2024-11-22 22:55:54.591274: Epoch 6641 +2024-11-22 22:55:54.591390: Current learning rate: 0.00203 +2024-11-22 22:56:13.212851: train_loss -0.8236 +2024-11-22 22:56:13.213084: val_loss -0.7775 +2024-11-22 22:56:13.213158: Pseudo dice [0.8618] +2024-11-22 22:56:13.213234: Epoch time: 18.62 s +2024-11-22 22:56:14.124256: +2024-11-22 22:56:14.124463: Epoch 6642 +2024-11-22 22:56:14.124574: Current learning rate: 0.00203 +2024-11-22 22:56:32.334225: train_loss -0.8207 +2024-11-22 22:56:32.334473: val_loss -0.7596 +2024-11-22 22:56:32.334554: Pseudo dice [0.8181] +2024-11-22 22:56:32.334646: Epoch time: 18.21 s +2024-11-22 22:56:33.267783: +2024-11-22 22:56:33.268010: Epoch 6643 +2024-11-22 22:56:33.268125: Current learning rate: 0.00203 +2024-11-22 22:56:53.284303: train_loss -0.8144 +2024-11-22 22:56:53.284518: val_loss -0.7619 +2024-11-22 22:56:53.284598: Pseudo dice [0.841] +2024-11-22 22:56:53.284685: Epoch time: 20.02 s +2024-11-22 22:56:54.238075: +2024-11-22 22:56:54.238322: Epoch 6644 +2024-11-22 22:56:54.238439: Current learning rate: 0.00202 +2024-11-22 22:57:13.979098: train_loss -0.8114 +2024-11-22 22:57:13.979315: val_loss -0.7709 +2024-11-22 22:57:13.979387: Pseudo dice [0.8397] +2024-11-22 22:57:13.979462: Epoch time: 19.74 s +2024-11-22 22:57:14.892658: +2024-11-22 22:57:14.892894: Epoch 6645 +2024-11-22 22:57:14.893017: Current learning rate: 0.00202 +2024-11-22 22:57:32.775796: train_loss -0.8202 +2024-11-22 22:57:32.776061: val_loss -0.7476 +2024-11-22 22:57:32.776138: Pseudo dice [0.8206] +2024-11-22 22:57:32.776213: Epoch time: 17.88 s +2024-11-22 22:57:33.686768: +2024-11-22 22:57:33.686969: Epoch 6646 +2024-11-22 22:57:33.687089: Current learning rate: 0.00202 +2024-11-22 22:57:51.604265: train_loss -0.8166 +2024-11-22 22:57:51.604517: val_loss -0.7652 +2024-11-22 22:57:51.606922: Pseudo dice [0.8333] +2024-11-22 22:57:51.607049: Epoch time: 17.92 s +2024-11-22 22:57:52.593530: +2024-11-22 22:57:52.593766: Epoch 6647 +2024-11-22 22:57:52.593886: Current learning rate: 0.00202 +2024-11-22 22:58:12.100659: train_loss -0.8184 +2024-11-22 22:58:12.100880: val_loss -0.7521 +2024-11-22 22:58:12.100956: Pseudo dice [0.8252] +2024-11-22 22:58:12.101039: Epoch time: 19.51 s +2024-11-22 22:58:13.007930: +2024-11-22 22:58:13.008135: Epoch 6648 +2024-11-22 22:58:13.008249: Current learning rate: 0.00202 +2024-11-22 22:58:32.461055: train_loss -0.8138 +2024-11-22 22:58:32.461268: val_loss -0.734 +2024-11-22 22:58:32.461748: Pseudo dice [0.8391] +2024-11-22 22:58:32.461833: Epoch time: 19.45 s +2024-11-22 22:58:33.374679: +2024-11-22 22:58:33.374884: Epoch 6649 +2024-11-22 22:58:33.375008: Current learning rate: 0.00202 +2024-11-22 22:58:51.763143: train_loss -0.8198 +2024-11-22 22:58:51.763356: val_loss -0.7475 +2024-11-22 22:58:51.763432: Pseudo dice [0.8431] +2024-11-22 22:58:51.763508: Epoch time: 18.39 s +2024-11-22 22:58:52.984556: +2024-11-22 22:58:52.984781: Epoch 6650 +2024-11-22 22:58:52.984897: Current learning rate: 0.00202 +2024-11-22 22:59:11.704723: train_loss -0.8139 +2024-11-22 22:59:11.704971: val_loss -0.7539 +2024-11-22 22:59:11.705056: Pseudo dice [0.8335] +2024-11-22 22:59:11.705157: Epoch time: 18.72 s +2024-11-22 22:59:12.616894: +2024-11-22 22:59:12.617149: Epoch 6651 +2024-11-22 22:59:12.617262: Current learning rate: 0.00201 +2024-11-22 22:59:31.299495: train_loss -0.8173 +2024-11-22 22:59:31.299715: val_loss -0.7718 +2024-11-22 22:59:31.299789: Pseudo dice [0.8382] +2024-11-22 22:59:31.299867: Epoch time: 18.68 s +2024-11-22 22:59:32.382540: +2024-11-22 22:59:32.382832: Epoch 6652 +2024-11-22 22:59:32.382945: Current learning rate: 0.00201 +2024-11-22 22:59:51.157784: train_loss -0.8185 +2024-11-22 22:59:51.158014: val_loss -0.7314 +2024-11-22 22:59:51.158093: Pseudo dice [0.8342] +2024-11-22 22:59:51.158168: Epoch time: 18.78 s +2024-11-22 22:59:52.071316: +2024-11-22 22:59:52.071548: Epoch 6653 +2024-11-22 22:59:52.071662: Current learning rate: 0.00201 +2024-11-22 23:00:10.431319: train_loss -0.8175 +2024-11-22 23:00:10.431545: val_loss -0.7572 +2024-11-22 23:00:10.431619: Pseudo dice [0.841] +2024-11-22 23:00:10.431700: Epoch time: 18.36 s +2024-11-22 23:00:11.342447: +2024-11-22 23:00:11.342655: Epoch 6654 +2024-11-22 23:00:11.342764: Current learning rate: 0.00201 +2024-11-22 23:00:30.252363: train_loss -0.8192 +2024-11-22 23:00:30.252592: val_loss -0.7244 +2024-11-22 23:00:30.252666: Pseudo dice [0.8242] +2024-11-22 23:00:30.252747: Epoch time: 18.91 s +2024-11-22 23:00:31.235804: +2024-11-22 23:00:31.236010: Epoch 6655 +2024-11-22 23:00:31.236121: Current learning rate: 0.00201 +2024-11-22 23:00:49.721041: train_loss -0.8196 +2024-11-22 23:00:49.721264: val_loss -0.767 +2024-11-22 23:00:49.721339: Pseudo dice [0.8317] +2024-11-22 23:00:49.726622: Epoch time: 18.49 s +2024-11-22 23:00:50.747740: +2024-11-22 23:00:50.747960: Epoch 6656 +2024-11-22 23:00:50.748078: Current learning rate: 0.00201 +2024-11-22 23:01:09.007871: train_loss -0.8194 +2024-11-22 23:01:09.008089: val_loss -0.7497 +2024-11-22 23:01:09.008162: Pseudo dice [0.8273] +2024-11-22 23:01:09.008237: Epoch time: 18.26 s +2024-11-22 23:01:09.916259: +2024-11-22 23:01:09.916477: Epoch 6657 +2024-11-22 23:01:09.916593: Current learning rate: 0.00201 +2024-11-22 23:01:28.448452: train_loss -0.8145 +2024-11-22 23:01:28.448684: val_loss -0.756 +2024-11-22 23:01:28.448764: Pseudo dice [0.8405] +2024-11-22 23:01:28.448849: Epoch time: 18.53 s +2024-11-22 23:01:29.520361: +2024-11-22 23:01:29.520551: Epoch 6658 +2024-11-22 23:01:29.520663: Current learning rate: 0.00201 +2024-11-22 23:01:47.699181: train_loss -0.8206 +2024-11-22 23:01:47.699421: val_loss -0.7726 +2024-11-22 23:01:47.699497: Pseudo dice [0.8303] +2024-11-22 23:01:47.699579: Epoch time: 18.18 s +2024-11-22 23:01:48.822781: +2024-11-22 23:01:48.822996: Epoch 6659 +2024-11-22 23:01:48.823109: Current learning rate: 0.002 +2024-11-22 23:02:07.305419: train_loss -0.8123 +2024-11-22 23:02:07.305704: val_loss -0.7903 +2024-11-22 23:02:07.305787: Pseudo dice [0.8416] +2024-11-22 23:02:07.305872: Epoch time: 18.48 s +2024-11-22 23:02:08.219241: +2024-11-22 23:02:08.219473: Epoch 6660 +2024-11-22 23:02:08.219584: Current learning rate: 0.002 +2024-11-22 23:02:27.303805: train_loss -0.8142 +2024-11-22 23:02:27.304088: val_loss -0.7396 +2024-11-22 23:02:27.304169: Pseudo dice [0.8249] +2024-11-22 23:02:27.304251: Epoch time: 19.09 s +2024-11-22 23:02:28.214142: +2024-11-22 23:02:28.214354: Epoch 6661 +2024-11-22 23:02:28.214480: Current learning rate: 0.002 +2024-11-22 23:02:46.828969: train_loss -0.8163 +2024-11-22 23:02:46.829201: val_loss -0.7472 +2024-11-22 23:02:46.829272: Pseudo dice [0.8162] +2024-11-22 23:02:46.829350: Epoch time: 18.62 s +2024-11-22 23:02:47.740965: +2024-11-22 23:02:47.741179: Epoch 6662 +2024-11-22 23:02:47.741291: Current learning rate: 0.002 +2024-11-22 23:03:06.076148: train_loss -0.8171 +2024-11-22 23:03:06.078517: val_loss -0.7534 +2024-11-22 23:03:06.078638: Pseudo dice [0.8298] +2024-11-22 23:03:06.078723: Epoch time: 18.34 s +2024-11-22 23:03:07.090186: +2024-11-22 23:03:07.090411: Epoch 6663 +2024-11-22 23:03:07.090527: Current learning rate: 0.002 +2024-11-22 23:03:25.094946: train_loss -0.8144 +2024-11-22 23:03:25.095178: val_loss -0.7507 +2024-11-22 23:03:25.095251: Pseudo dice [0.8239] +2024-11-22 23:03:25.095326: Epoch time: 18.01 s +2024-11-22 23:03:26.371932: +2024-11-22 23:03:26.372193: Epoch 6664 +2024-11-22 23:03:26.372306: Current learning rate: 0.002 +2024-11-22 23:03:45.000936: train_loss -0.8164 +2024-11-22 23:03:45.001188: val_loss -0.7794 +2024-11-22 23:03:45.001268: Pseudo dice [0.8461] +2024-11-22 23:03:45.001348: Epoch time: 18.63 s +2024-11-22 23:03:45.918353: +2024-11-22 23:03:45.918680: Epoch 6665 +2024-11-22 23:03:45.918797: Current learning rate: 0.002 +2024-11-22 23:04:04.087895: train_loss -0.8149 +2024-11-22 23:04:04.088133: val_loss -0.7272 +2024-11-22 23:04:04.088210: Pseudo dice [0.8097] +2024-11-22 23:04:04.088290: Epoch time: 18.17 s +2024-11-22 23:04:05.000469: +2024-11-22 23:04:05.000675: Epoch 6666 +2024-11-22 23:04:05.000790: Current learning rate: 0.00199 +2024-11-22 23:04:24.397780: train_loss -0.8179 +2024-11-22 23:04:24.403149: val_loss -0.7432 +2024-11-22 23:04:24.403292: Pseudo dice [0.8327] +2024-11-22 23:04:24.403376: Epoch time: 19.4 s +2024-11-22 23:04:25.340413: +2024-11-22 23:04:25.340743: Epoch 6667 +2024-11-22 23:04:25.340853: Current learning rate: 0.00199 +2024-11-22 23:04:42.813639: train_loss -0.8125 +2024-11-22 23:04:42.813860: val_loss -0.7517 +2024-11-22 23:04:42.813933: Pseudo dice [0.834] +2024-11-22 23:04:42.814019: Epoch time: 17.47 s +2024-11-22 23:04:43.732496: +2024-11-22 23:04:43.732740: Epoch 6668 +2024-11-22 23:04:43.732856: Current learning rate: 0.00199 +2024-11-22 23:05:02.021275: train_loss -0.8125 +2024-11-22 23:05:02.021510: val_loss -0.7817 +2024-11-22 23:05:02.021595: Pseudo dice [0.8421] +2024-11-22 23:05:02.021677: Epoch time: 18.29 s +2024-11-22 23:05:02.935440: +2024-11-22 23:05:02.935672: Epoch 6669 +2024-11-22 23:05:02.935786: Current learning rate: 0.00199 +2024-11-22 23:05:20.364933: train_loss -0.8198 +2024-11-22 23:05:20.365230: val_loss -0.7455 +2024-11-22 23:05:20.365309: Pseudo dice [0.8222] +2024-11-22 23:05:20.365394: Epoch time: 17.43 s +2024-11-22 23:05:21.286999: +2024-11-22 23:05:21.287217: Epoch 6670 +2024-11-22 23:05:21.287333: Current learning rate: 0.00199 +2024-11-22 23:05:39.433755: train_loss -0.8167 +2024-11-22 23:05:39.434004: val_loss -0.7488 +2024-11-22 23:05:39.434083: Pseudo dice [0.8586] +2024-11-22 23:05:39.434159: Epoch time: 18.15 s +2024-11-22 23:05:40.349941: +2024-11-22 23:05:40.350145: Epoch 6671 +2024-11-22 23:05:40.350259: Current learning rate: 0.00199 +2024-11-22 23:05:59.294827: train_loss -0.8177 +2024-11-22 23:05:59.295136: val_loss -0.7785 +2024-11-22 23:05:59.295216: Pseudo dice [0.8488] +2024-11-22 23:05:59.295293: Epoch time: 18.95 s +2024-11-22 23:06:00.318231: +2024-11-22 23:06:00.318439: Epoch 6672 +2024-11-22 23:06:00.318555: Current learning rate: 0.00199 +2024-11-22 23:06:18.413704: train_loss -0.8216 +2024-11-22 23:06:18.413921: val_loss -0.7602 +2024-11-22 23:06:18.414003: Pseudo dice [0.8269] +2024-11-22 23:06:18.414080: Epoch time: 18.1 s +2024-11-22 23:06:19.335746: +2024-11-22 23:06:19.335953: Epoch 6673 +2024-11-22 23:06:19.336074: Current learning rate: 0.00199 +2024-11-22 23:06:38.961037: train_loss -0.8121 +2024-11-22 23:06:38.961273: val_loss -0.7715 +2024-11-22 23:06:38.961348: Pseudo dice [0.8378] +2024-11-22 23:06:38.961430: Epoch time: 19.63 s +2024-11-22 23:06:39.874845: +2024-11-22 23:06:39.875041: Epoch 6674 +2024-11-22 23:06:39.875151: Current learning rate: 0.00198 +2024-11-22 23:06:58.467594: train_loss -0.816 +2024-11-22 23:06:58.467806: val_loss -0.7653 +2024-11-22 23:06:58.467879: Pseudo dice [0.8253] +2024-11-22 23:06:58.467955: Epoch time: 18.59 s +2024-11-22 23:06:59.386873: +2024-11-22 23:06:59.387294: Epoch 6675 +2024-11-22 23:06:59.387430: Current learning rate: 0.00198 +2024-11-22 23:07:18.007285: train_loss -0.8208 +2024-11-22 23:07:18.007537: val_loss -0.7652 +2024-11-22 23:07:18.029665: Pseudo dice [0.828] +2024-11-22 23:07:18.029778: Epoch time: 18.62 s +2024-11-22 23:07:18.947155: +2024-11-22 23:07:18.947355: Epoch 6676 +2024-11-22 23:07:18.947472: Current learning rate: 0.00198 +2024-11-22 23:07:37.619418: train_loss -0.8219 +2024-11-22 23:07:37.621729: val_loss -0.761 +2024-11-22 23:07:37.621851: Pseudo dice [0.8413] +2024-11-22 23:07:37.621938: Epoch time: 18.67 s +2024-11-22 23:07:38.534980: +2024-11-22 23:07:38.535220: Epoch 6677 +2024-11-22 23:07:38.535337: Current learning rate: 0.00198 +2024-11-22 23:07:57.629980: train_loss -0.8213 +2024-11-22 23:07:57.630206: val_loss -0.7591 +2024-11-22 23:07:57.630282: Pseudo dice [0.8209] +2024-11-22 23:07:57.630358: Epoch time: 19.1 s +2024-11-22 23:07:58.548855: +2024-11-22 23:07:58.549100: Epoch 6678 +2024-11-22 23:07:58.549219: Current learning rate: 0.00198 +2024-11-22 23:08:15.959232: train_loss -0.8169 +2024-11-22 23:08:15.959449: val_loss -0.7446 +2024-11-22 23:08:15.959542: Pseudo dice [0.826] +2024-11-22 23:08:15.959650: Epoch time: 17.41 s +2024-11-22 23:08:16.881564: +2024-11-22 23:08:16.881831: Epoch 6679 +2024-11-22 23:08:16.881953: Current learning rate: 0.00198 +2024-11-22 23:08:35.746308: train_loss -0.816 +2024-11-22 23:08:35.746532: val_loss -0.7493 +2024-11-22 23:08:35.746611: Pseudo dice [0.8383] +2024-11-22 23:08:35.746693: Epoch time: 18.87 s +2024-11-22 23:08:36.672332: +2024-11-22 23:08:36.672519: Epoch 6680 +2024-11-22 23:08:36.672633: Current learning rate: 0.00198 +2024-11-22 23:08:55.506146: train_loss -0.8193 +2024-11-22 23:08:55.506374: val_loss -0.7729 +2024-11-22 23:08:55.506451: Pseudo dice [0.8525] +2024-11-22 23:08:55.506529: Epoch time: 18.83 s +2024-11-22 23:08:56.422049: +2024-11-22 23:08:56.422258: Epoch 6681 +2024-11-22 23:08:56.422372: Current learning rate: 0.00197 +2024-11-22 23:09:14.780422: train_loss -0.8234 +2024-11-22 23:09:14.780653: val_loss -0.7489 +2024-11-22 23:09:14.780731: Pseudo dice [0.841] +2024-11-22 23:09:14.780811: Epoch time: 18.36 s +2024-11-22 23:09:15.714043: +2024-11-22 23:09:15.714417: Epoch 6682 +2024-11-22 23:09:15.714535: Current learning rate: 0.00197 +2024-11-22 23:09:34.165733: train_loss -0.8194 +2024-11-22 23:09:34.165951: val_loss -0.7486 +2024-11-22 23:09:34.166033: Pseudo dice [0.8508] +2024-11-22 23:09:34.166111: Epoch time: 18.45 s +2024-11-22 23:09:35.083763: +2024-11-22 23:09:35.083961: Epoch 6683 +2024-11-22 23:09:35.084078: Current learning rate: 0.00197 +2024-11-22 23:09:55.329204: train_loss -0.8155 +2024-11-22 23:09:55.329437: val_loss -0.7537 +2024-11-22 23:09:55.329510: Pseudo dice [0.8438] +2024-11-22 23:09:55.329594: Epoch time: 20.25 s +2024-11-22 23:09:56.267163: +2024-11-22 23:09:56.267375: Epoch 6684 +2024-11-22 23:09:56.267489: Current learning rate: 0.00197 +2024-11-22 23:10:14.936825: train_loss -0.8202 +2024-11-22 23:10:14.937057: val_loss -0.7646 +2024-11-22 23:10:14.937133: Pseudo dice [0.8521] +2024-11-22 23:10:14.941035: Epoch time: 18.67 s +2024-11-22 23:10:15.868497: +2024-11-22 23:10:15.868685: Epoch 6685 +2024-11-22 23:10:15.868796: Current learning rate: 0.00197 +2024-11-22 23:10:34.759566: train_loss -0.818 +2024-11-22 23:10:34.759785: val_loss -0.7474 +2024-11-22 23:10:34.759858: Pseudo dice [0.8337] +2024-11-22 23:10:34.759937: Epoch time: 18.89 s +2024-11-22 23:10:36.025128: +2024-11-22 23:10:36.025341: Epoch 6686 +2024-11-22 23:10:36.025452: Current learning rate: 0.00197 +2024-11-22 23:10:55.503390: train_loss -0.8038 +2024-11-22 23:10:55.503630: val_loss -0.7439 +2024-11-22 23:10:55.503706: Pseudo dice [0.8366] +2024-11-22 23:10:55.503794: Epoch time: 19.48 s +2024-11-22 23:10:56.441964: +2024-11-22 23:10:56.442163: Epoch 6687 +2024-11-22 23:10:56.442273: Current learning rate: 0.00197 +2024-11-22 23:11:15.401481: train_loss -0.8156 +2024-11-22 23:11:15.401694: val_loss -0.7543 +2024-11-22 23:11:15.401770: Pseudo dice [0.8242] +2024-11-22 23:11:15.401851: Epoch time: 18.96 s +2024-11-22 23:11:16.374822: +2024-11-22 23:11:16.375075: Epoch 6688 +2024-11-22 23:11:16.375190: Current learning rate: 0.00196 +2024-11-22 23:11:34.923331: train_loss -0.8111 +2024-11-22 23:11:34.923556: val_loss -0.7649 +2024-11-22 23:11:34.923633: Pseudo dice [0.8384] +2024-11-22 23:11:34.923711: Epoch time: 18.55 s +2024-11-22 23:11:35.839538: +2024-11-22 23:11:35.839760: Epoch 6689 +2024-11-22 23:11:35.839875: Current learning rate: 0.00196 +2024-11-22 23:11:54.380754: train_loss -0.8105 +2024-11-22 23:11:54.383168: val_loss -0.7858 +2024-11-22 23:11:54.383277: Pseudo dice [0.8389] +2024-11-22 23:11:54.383356: Epoch time: 18.54 s +2024-11-22 23:11:55.353154: +2024-11-22 23:11:55.353376: Epoch 6690 +2024-11-22 23:11:55.353523: Current learning rate: 0.00196 +2024-11-22 23:12:14.016234: train_loss -0.8111 +2024-11-22 23:12:14.016529: val_loss -0.7445 +2024-11-22 23:12:14.016608: Pseudo dice [0.8354] +2024-11-22 23:12:14.016691: Epoch time: 18.66 s +2024-11-22 23:12:14.940436: +2024-11-22 23:12:14.940636: Epoch 6691 +2024-11-22 23:12:14.940748: Current learning rate: 0.00196 +2024-11-22 23:12:33.336261: train_loss -0.8166 +2024-11-22 23:12:33.336479: val_loss -0.7652 +2024-11-22 23:12:33.336556: Pseudo dice [0.8375] +2024-11-22 23:12:33.336636: Epoch time: 18.4 s +2024-11-22 23:12:34.321118: +2024-11-22 23:12:34.321345: Epoch 6692 +2024-11-22 23:12:34.321461: Current learning rate: 0.00196 +2024-11-22 23:12:53.210749: train_loss -0.8133 +2024-11-22 23:12:53.210983: val_loss -0.7604 +2024-11-22 23:12:53.211066: Pseudo dice [0.8284] +2024-11-22 23:12:53.211147: Epoch time: 18.89 s +2024-11-22 23:12:54.127759: +2024-11-22 23:12:54.128000: Epoch 6693 +2024-11-22 23:12:54.128109: Current learning rate: 0.00196 +2024-11-22 23:13:12.405594: train_loss -0.821 +2024-11-22 23:13:12.405832: val_loss -0.7507 +2024-11-22 23:13:12.405908: Pseudo dice [0.8285] +2024-11-22 23:13:12.406101: Epoch time: 18.28 s +2024-11-22 23:13:13.323374: +2024-11-22 23:13:13.323623: Epoch 6694 +2024-11-22 23:13:13.323735: Current learning rate: 0.00196 +2024-11-22 23:13:30.790699: train_loss -0.8219 +2024-11-22 23:13:30.790917: val_loss -0.7481 +2024-11-22 23:13:30.791003: Pseudo dice [0.8291] +2024-11-22 23:13:30.791094: Epoch time: 17.47 s +2024-11-22 23:13:31.694511: +2024-11-22 23:13:31.694721: Epoch 6695 +2024-11-22 23:13:31.694954: Current learning rate: 0.00196 +2024-11-22 23:13:50.401429: train_loss -0.8189 +2024-11-22 23:13:50.401648: val_loss -0.7608 +2024-11-22 23:13:50.401722: Pseudo dice [0.8282] +2024-11-22 23:13:50.401796: Epoch time: 18.71 s +2024-11-22 23:13:51.393004: +2024-11-22 23:13:51.393212: Epoch 6696 +2024-11-22 23:13:51.393320: Current learning rate: 0.00195 +2024-11-22 23:14:09.424844: train_loss -0.8227 +2024-11-22 23:14:09.425061: val_loss -0.7683 +2024-11-22 23:14:09.425136: Pseudo dice [0.8483] +2024-11-22 23:14:09.425211: Epoch time: 18.03 s +2024-11-22 23:14:10.491501: +2024-11-22 23:14:10.491902: Epoch 6697 +2024-11-22 23:14:10.492035: Current learning rate: 0.00195 +2024-11-22 23:14:29.566845: train_loss -0.8172 +2024-11-22 23:14:29.567085: val_loss -0.7534 +2024-11-22 23:14:29.567227: Pseudo dice [0.8343] +2024-11-22 23:14:29.567317: Epoch time: 19.08 s +2024-11-22 23:14:30.847696: +2024-11-22 23:14:30.847892: Epoch 6698 +2024-11-22 23:14:30.848007: Current learning rate: 0.00195 +2024-11-22 23:14:49.799978: train_loss -0.8204 +2024-11-22 23:14:49.805418: val_loss -0.756 +2024-11-22 23:14:49.805504: Pseudo dice [0.8429] +2024-11-22 23:14:49.805582: Epoch time: 18.95 s +2024-11-22 23:14:50.794893: +2024-11-22 23:14:50.795216: Epoch 6699 +2024-11-22 23:14:50.795333: Current learning rate: 0.00195 +2024-11-22 23:15:09.643572: train_loss -0.815 +2024-11-22 23:15:09.643788: val_loss -0.7643 +2024-11-22 23:15:09.643869: Pseudo dice [0.8516] +2024-11-22 23:15:09.643948: Epoch time: 18.85 s +2024-11-22 23:15:10.885664: +2024-11-22 23:15:10.885920: Epoch 6700 +2024-11-22 23:15:10.886039: Current learning rate: 0.00195 +2024-11-22 23:15:29.028913: train_loss -0.8177 +2024-11-22 23:15:29.029147: val_loss -0.7482 +2024-11-22 23:15:29.029219: Pseudo dice [0.8293] +2024-11-22 23:15:29.029303: Epoch time: 18.14 s +2024-11-22 23:15:29.932259: +2024-11-22 23:15:29.933106: Epoch 6701 +2024-11-22 23:15:29.933218: Current learning rate: 0.00195 +2024-11-22 23:15:48.280042: train_loss -0.8265 +2024-11-22 23:15:48.280258: val_loss -0.7622 +2024-11-22 23:15:48.280331: Pseudo dice [0.8402] +2024-11-22 23:15:48.280405: Epoch time: 18.35 s +2024-11-22 23:15:49.242750: +2024-11-22 23:15:49.242943: Epoch 6702 +2024-11-22 23:15:49.243055: Current learning rate: 0.00195 +2024-11-22 23:16:08.910233: train_loss -0.8069 +2024-11-22 23:16:08.910451: val_loss -0.7702 +2024-11-22 23:16:08.910525: Pseudo dice [0.8445] +2024-11-22 23:16:08.910600: Epoch time: 19.67 s +2024-11-22 23:16:09.827037: +2024-11-22 23:16:09.827250: Epoch 6703 +2024-11-22 23:16:09.827366: Current learning rate: 0.00194 +2024-11-22 23:16:27.513645: train_loss -0.8205 +2024-11-22 23:16:27.513857: val_loss -0.7711 +2024-11-22 23:16:27.513980: Pseudo dice [0.8526] +2024-11-22 23:16:27.514060: Epoch time: 17.69 s +2024-11-22 23:16:28.413748: +2024-11-22 23:16:28.413955: Epoch 6704 +2024-11-22 23:16:28.414072: Current learning rate: 0.00194 +2024-11-22 23:16:46.667069: train_loss -0.8185 +2024-11-22 23:16:46.667300: val_loss -0.7569 +2024-11-22 23:16:46.667379: Pseudo dice [0.8216] +2024-11-22 23:16:46.667464: Epoch time: 18.25 s +2024-11-22 23:16:47.583720: +2024-11-22 23:16:47.583961: Epoch 6705 +2024-11-22 23:16:47.584088: Current learning rate: 0.00194 +2024-11-22 23:17:06.238152: train_loss -0.8219 +2024-11-22 23:17:06.238378: val_loss -0.7906 +2024-11-22 23:17:06.238451: Pseudo dice [0.8611] +2024-11-22 23:17:06.238525: Epoch time: 18.66 s +2024-11-22 23:17:07.174046: +2024-11-22 23:17:07.174331: Epoch 6706 +2024-11-22 23:17:07.174447: Current learning rate: 0.00194 +2024-11-22 23:17:26.275515: train_loss -0.8204 +2024-11-22 23:17:26.275736: val_loss -0.7792 +2024-11-22 23:17:26.275809: Pseudo dice [0.8642] +2024-11-22 23:17:26.278074: Epoch time: 19.1 s +2024-11-22 23:17:26.278206: Yayy! New best EMA pseudo Dice: 0.8424 +2024-11-22 23:17:27.539793: +2024-11-22 23:17:27.540017: Epoch 6707 +2024-11-22 23:17:27.540129: Current learning rate: 0.00194 +2024-11-22 23:17:45.558357: train_loss -0.8281 +2024-11-22 23:17:45.558591: val_loss -0.7592 +2024-11-22 23:17:45.558671: Pseudo dice [0.8428] +2024-11-22 23:17:45.558766: Epoch time: 18.02 s +2024-11-22 23:17:45.558831: Yayy! New best EMA pseudo Dice: 0.8424 +2024-11-22 23:17:46.792341: +2024-11-22 23:17:46.792590: Epoch 6708 +2024-11-22 23:17:46.792737: Current learning rate: 0.00194 +2024-11-22 23:18:05.431898: train_loss -0.8186 +2024-11-22 23:18:05.432140: val_loss -0.7679 +2024-11-22 23:18:05.432214: Pseudo dice [0.8378] +2024-11-22 23:18:05.432291: Epoch time: 18.64 s +2024-11-22 23:18:06.374762: +2024-11-22 23:18:06.374987: Epoch 6709 +2024-11-22 23:18:06.375104: Current learning rate: 0.00194 +2024-11-22 23:18:25.618390: train_loss -0.8169 +2024-11-22 23:18:25.618623: val_loss -0.7554 +2024-11-22 23:18:25.618713: Pseudo dice [0.8385] +2024-11-22 23:18:25.618791: Epoch time: 19.24 s +2024-11-22 23:18:26.537194: +2024-11-22 23:18:26.537419: Epoch 6710 +2024-11-22 23:18:26.537531: Current learning rate: 0.00194 +2024-11-22 23:18:44.968829: train_loss -0.8221 +2024-11-22 23:18:44.969057: val_loss -0.7515 +2024-11-22 23:18:44.969136: Pseudo dice [0.8301] +2024-11-22 23:18:44.969213: Epoch time: 18.43 s +2024-11-22 23:18:45.890331: +2024-11-22 23:18:45.890559: Epoch 6711 +2024-11-22 23:18:45.890673: Current learning rate: 0.00193 +2024-11-22 23:19:04.117357: train_loss -0.8266 +2024-11-22 23:19:04.117617: val_loss -0.7542 +2024-11-22 23:19:04.117696: Pseudo dice [0.8509] +2024-11-22 23:19:04.117784: Epoch time: 18.23 s +2024-11-22 23:19:05.274156: +2024-11-22 23:19:05.274350: Epoch 6712 +2024-11-22 23:19:05.274462: Current learning rate: 0.00193 +2024-11-22 23:19:23.469774: train_loss -0.8169 +2024-11-22 23:19:23.469986: val_loss -0.7216 +2024-11-22 23:19:23.470063: Pseudo dice [0.8156] +2024-11-22 23:19:23.470138: Epoch time: 18.2 s +2024-11-22 23:19:24.397068: +2024-11-22 23:19:24.397263: Epoch 6713 +2024-11-22 23:19:24.397379: Current learning rate: 0.00193 +2024-11-22 23:19:42.933710: train_loss -0.8237 +2024-11-22 23:19:42.933949: val_loss -0.748 +2024-11-22 23:19:42.934059: Pseudo dice [0.8327] +2024-11-22 23:19:42.934138: Epoch time: 18.54 s +2024-11-22 23:19:43.858802: +2024-11-22 23:19:43.859026: Epoch 6714 +2024-11-22 23:19:43.859137: Current learning rate: 0.00193 +2024-11-22 23:20:02.806382: train_loss -0.8225 +2024-11-22 23:20:02.808459: val_loss -0.7572 +2024-11-22 23:20:02.808561: Pseudo dice [0.8462] +2024-11-22 23:20:02.808697: Epoch time: 18.95 s +2024-11-22 23:20:03.773955: +2024-11-22 23:20:03.774213: Epoch 6715 +2024-11-22 23:20:03.774328: Current learning rate: 0.00193 +2024-11-22 23:20:21.627677: train_loss -0.8185 +2024-11-22 23:20:21.627941: val_loss -0.7733 +2024-11-22 23:20:21.628021: Pseudo dice [0.8415] +2024-11-22 23:20:21.628106: Epoch time: 17.85 s +2024-11-22 23:20:22.568325: +2024-11-22 23:20:22.568614: Epoch 6716 +2024-11-22 23:20:22.568731: Current learning rate: 0.00193 +2024-11-22 23:20:40.100055: train_loss -0.8183 +2024-11-22 23:20:40.100271: val_loss -0.7475 +2024-11-22 23:20:40.100345: Pseudo dice [0.8222] +2024-11-22 23:20:40.100419: Epoch time: 17.53 s +2024-11-22 23:20:41.180651: +2024-11-22 23:20:41.180849: Epoch 6717 +2024-11-22 23:20:41.180964: Current learning rate: 0.00193 +2024-11-22 23:21:00.913512: train_loss -0.8164 +2024-11-22 23:21:00.913749: val_loss -0.742 +2024-11-22 23:21:00.913826: Pseudo dice [0.8114] +2024-11-22 23:21:00.913907: Epoch time: 19.73 s +2024-11-22 23:21:01.945046: +2024-11-22 23:21:01.945364: Epoch 6718 +2024-11-22 23:21:01.945482: Current learning rate: 0.00192 +2024-11-22 23:21:21.149208: train_loss -0.8211 +2024-11-22 23:21:21.149441: val_loss -0.7509 +2024-11-22 23:21:21.149522: Pseudo dice [0.8332] +2024-11-22 23:21:21.149612: Epoch time: 19.2 s +2024-11-22 23:21:22.070076: +2024-11-22 23:21:22.070299: Epoch 6719 +2024-11-22 23:21:22.070414: Current learning rate: 0.00192 +2024-11-22 23:21:42.134533: train_loss -0.8177 +2024-11-22 23:21:42.135033: val_loss -0.7405 +2024-11-22 23:21:42.135136: Pseudo dice [0.8187] +2024-11-22 23:21:42.135215: Epoch time: 20.07 s +2024-11-22 23:21:43.049756: +2024-11-22 23:21:43.049970: Epoch 6720 +2024-11-22 23:21:43.050102: Current learning rate: 0.00192 +2024-11-22 23:22:01.264614: train_loss -0.8183 +2024-11-22 23:22:01.279155: val_loss -0.7685 +2024-11-22 23:22:01.279759: Pseudo dice [0.8441] +2024-11-22 23:22:01.279881: Epoch time: 18.22 s +2024-11-22 23:22:02.212487: +2024-11-22 23:22:02.212696: Epoch 6721 +2024-11-22 23:22:02.212805: Current learning rate: 0.00192 +2024-11-22 23:22:20.380933: train_loss -0.8209 +2024-11-22 23:22:20.381155: val_loss -0.766 +2024-11-22 23:22:20.381228: Pseudo dice [0.8443] +2024-11-22 23:22:20.381309: Epoch time: 18.17 s +2024-11-22 23:22:21.302243: +2024-11-22 23:22:21.302482: Epoch 6722 +2024-11-22 23:22:21.302639: Current learning rate: 0.00192 +2024-11-22 23:22:41.332970: train_loss -0.8195 +2024-11-22 23:22:41.333205: val_loss -0.7743 +2024-11-22 23:22:41.333278: Pseudo dice [0.827] +2024-11-22 23:22:41.333356: Epoch time: 20.03 s +2024-11-22 23:22:42.269419: +2024-11-22 23:22:42.269677: Epoch 6723 +2024-11-22 23:22:42.269799: Current learning rate: 0.00192 +2024-11-22 23:23:00.492224: train_loss -0.8296 +2024-11-22 23:23:00.492438: val_loss -0.7455 +2024-11-22 23:23:00.492514: Pseudo dice [0.8328] +2024-11-22 23:23:00.492590: Epoch time: 18.22 s +2024-11-22 23:23:01.409940: +2024-11-22 23:23:01.410139: Epoch 6724 +2024-11-22 23:23:01.410252: Current learning rate: 0.00192 +2024-11-22 23:23:19.159816: train_loss -0.819 +2024-11-22 23:23:19.160424: val_loss -0.7662 +2024-11-22 23:23:19.160508: Pseudo dice [0.8303] +2024-11-22 23:23:19.160596: Epoch time: 17.75 s +2024-11-22 23:23:20.082074: +2024-11-22 23:23:20.082279: Epoch 6725 +2024-11-22 23:23:20.082396: Current learning rate: 0.00192 +2024-11-22 23:23:38.244701: train_loss -0.8082 +2024-11-22 23:23:38.244929: val_loss -0.7358 +2024-11-22 23:23:38.245016: Pseudo dice [0.8491] +2024-11-22 23:23:38.245103: Epoch time: 18.16 s +2024-11-22 23:23:39.157287: +2024-11-22 23:23:39.165664: Epoch 6726 +2024-11-22 23:23:39.165798: Current learning rate: 0.00191 +2024-11-22 23:23:58.437852: train_loss -0.8177 +2024-11-22 23:23:58.438101: val_loss -0.7666 +2024-11-22 23:23:58.438174: Pseudo dice [0.8478] +2024-11-22 23:23:58.438250: Epoch time: 19.28 s +2024-11-22 23:23:59.354537: +2024-11-22 23:23:59.354743: Epoch 6727 +2024-11-22 23:23:59.354860: Current learning rate: 0.00191 +2024-11-22 23:24:18.086250: train_loss -0.8241 +2024-11-22 23:24:18.086490: val_loss -0.7623 +2024-11-22 23:24:18.086564: Pseudo dice [0.8261] +2024-11-22 23:24:18.086640: Epoch time: 18.73 s +2024-11-22 23:24:19.030306: +2024-11-22 23:24:19.030599: Epoch 6728 +2024-11-22 23:24:19.030719: Current learning rate: 0.00191 +2024-11-22 23:24:38.383226: train_loss -0.8114 +2024-11-22 23:24:38.383434: val_loss -0.7527 +2024-11-22 23:24:38.383522: Pseudo dice [0.843] +2024-11-22 23:24:38.383600: Epoch time: 19.35 s +2024-11-22 23:24:39.333263: +2024-11-22 23:24:39.333464: Epoch 6729 +2024-11-22 23:24:39.333582: Current learning rate: 0.00191 +2024-11-22 23:24:58.966937: train_loss -0.8194 +2024-11-22 23:24:58.967177: val_loss -0.7617 +2024-11-22 23:24:58.967255: Pseudo dice [0.8491] +2024-11-22 23:24:58.967339: Epoch time: 19.63 s +2024-11-22 23:25:00.298364: +2024-11-22 23:25:00.298600: Epoch 6730 +2024-11-22 23:25:00.298715: Current learning rate: 0.00191 +2024-11-22 23:25:18.084982: train_loss -0.8176 +2024-11-22 23:25:18.085206: val_loss -0.748 +2024-11-22 23:25:18.085280: Pseudo dice [0.8239] +2024-11-22 23:25:18.085354: Epoch time: 17.79 s +2024-11-22 23:25:19.077277: +2024-11-22 23:25:19.077497: Epoch 6731 +2024-11-22 23:25:19.077608: Current learning rate: 0.00191 +2024-11-22 23:25:37.421600: train_loss -0.8198 +2024-11-22 23:25:37.421817: val_loss -0.7399 +2024-11-22 23:25:37.421904: Pseudo dice [0.8291] +2024-11-22 23:25:37.422038: Epoch time: 18.35 s +2024-11-22 23:25:38.345577: +2024-11-22 23:25:38.345846: Epoch 6732 +2024-11-22 23:25:38.345959: Current learning rate: 0.00191 +2024-11-22 23:25:58.177965: train_loss -0.8171 +2024-11-22 23:25:58.178193: val_loss -0.7708 +2024-11-22 23:25:58.178267: Pseudo dice [0.8455] +2024-11-22 23:25:58.178344: Epoch time: 19.83 s +2024-11-22 23:25:59.099600: +2024-11-22 23:25:59.099833: Epoch 6733 +2024-11-22 23:25:59.099980: Current learning rate: 0.0019 +2024-11-22 23:26:16.997566: train_loss -0.8179 +2024-11-22 23:26:16.997795: val_loss -0.7589 +2024-11-22 23:26:16.997869: Pseudo dice [0.8458] +2024-11-22 23:26:16.998011: Epoch time: 17.9 s +2024-11-22 23:26:17.920020: +2024-11-22 23:26:17.920223: Epoch 6734 +2024-11-22 23:26:17.920339: Current learning rate: 0.0019 +2024-11-22 23:26:36.688616: train_loss -0.8159 +2024-11-22 23:26:36.688885: val_loss -0.7755 +2024-11-22 23:26:36.688961: Pseudo dice [0.8491] +2024-11-22 23:26:36.689044: Epoch time: 18.77 s +2024-11-22 23:26:37.611757: +2024-11-22 23:26:37.611959: Epoch 6735 +2024-11-22 23:26:37.612074: Current learning rate: 0.0019 +2024-11-22 23:26:55.478673: train_loss -0.8186 +2024-11-22 23:26:55.483297: val_loss -0.7701 +2024-11-22 23:26:55.483423: Pseudo dice [0.8451] +2024-11-22 23:26:55.483503: Epoch time: 17.87 s +2024-11-22 23:26:56.532440: +2024-11-22 23:26:56.532649: Epoch 6736 +2024-11-22 23:26:56.532762: Current learning rate: 0.0019 +2024-11-22 23:27:15.405587: train_loss -0.8266 +2024-11-22 23:27:15.405846: val_loss -0.7652 +2024-11-22 23:27:15.405923: Pseudo dice [0.8379] +2024-11-22 23:27:15.406075: Epoch time: 18.87 s +2024-11-22 23:27:16.320294: +2024-11-22 23:27:16.320610: Epoch 6737 +2024-11-22 23:27:16.320720: Current learning rate: 0.0019 +2024-11-22 23:27:34.680822: train_loss -0.8205 +2024-11-22 23:27:34.681039: val_loss -0.7709 +2024-11-22 23:27:34.681112: Pseudo dice [0.8376] +2024-11-22 23:27:34.681189: Epoch time: 18.36 s +2024-11-22 23:27:35.625116: +2024-11-22 23:27:35.625339: Epoch 6738 +2024-11-22 23:27:35.625456: Current learning rate: 0.0019 +2024-11-22 23:27:53.324803: train_loss -0.8258 +2024-11-22 23:27:53.325079: val_loss -0.722 +2024-11-22 23:27:53.325210: Pseudo dice [0.8127] +2024-11-22 23:27:53.327204: Epoch time: 17.7 s +2024-11-22 23:27:54.294351: +2024-11-22 23:27:54.294569: Epoch 6739 +2024-11-22 23:27:54.294684: Current learning rate: 0.0019 +2024-11-22 23:28:13.268356: train_loss -0.8233 +2024-11-22 23:28:13.270750: val_loss -0.7576 +2024-11-22 23:28:13.270874: Pseudo dice [0.8322] +2024-11-22 23:28:13.270957: Epoch time: 18.97 s +2024-11-22 23:28:14.376747: +2024-11-22 23:28:14.377176: Epoch 6740 +2024-11-22 23:28:14.377316: Current learning rate: 0.00189 +2024-11-22 23:28:33.637388: train_loss -0.8141 +2024-11-22 23:28:33.637673: val_loss -0.7406 +2024-11-22 23:28:33.637751: Pseudo dice [0.8327] +2024-11-22 23:28:33.637845: Epoch time: 19.26 s +2024-11-22 23:28:34.558598: +2024-11-22 23:28:34.558798: Epoch 6741 +2024-11-22 23:28:34.558912: Current learning rate: 0.00189 +2024-11-22 23:28:54.108069: train_loss -0.8195 +2024-11-22 23:28:54.108284: val_loss -0.7613 +2024-11-22 23:28:54.108362: Pseudo dice [0.848] +2024-11-22 23:28:54.108441: Epoch time: 19.55 s +2024-11-22 23:28:55.404265: +2024-11-22 23:28:55.404473: Epoch 6742 +2024-11-22 23:28:55.404583: Current learning rate: 0.00189 +2024-11-22 23:29:13.833447: train_loss -0.8136 +2024-11-22 23:29:13.833694: val_loss -0.736 +2024-11-22 23:29:13.833772: Pseudo dice [0.8365] +2024-11-22 23:29:13.833847: Epoch time: 18.43 s +2024-11-22 23:29:14.747884: +2024-11-22 23:29:14.748178: Epoch 6743 +2024-11-22 23:29:14.748293: Current learning rate: 0.00189 +2024-11-22 23:29:32.963933: train_loss -0.8152 +2024-11-22 23:29:32.964183: val_loss -0.7674 +2024-11-22 23:29:32.964255: Pseudo dice [0.824] +2024-11-22 23:29:32.964338: Epoch time: 18.22 s +2024-11-22 23:29:33.887344: +2024-11-22 23:29:33.887581: Epoch 6744 +2024-11-22 23:29:33.887691: Current learning rate: 0.00189 +2024-11-22 23:29:51.748675: train_loss -0.8063 +2024-11-22 23:29:51.748888: val_loss -0.7216 +2024-11-22 23:29:51.748960: Pseudo dice [0.8266] +2024-11-22 23:29:51.749043: Epoch time: 17.86 s +2024-11-22 23:29:52.709587: +2024-11-22 23:29:52.709791: Epoch 6745 +2024-11-22 23:29:52.709900: Current learning rate: 0.00189 +2024-11-22 23:30:11.200202: train_loss -0.8097 +2024-11-22 23:30:11.200448: val_loss -0.746 +2024-11-22 23:30:11.200524: Pseudo dice [0.8463] +2024-11-22 23:30:11.200600: Epoch time: 18.49 s +2024-11-22 23:30:12.118652: +2024-11-22 23:30:12.118850: Epoch 6746 +2024-11-22 23:30:12.118966: Current learning rate: 0.00189 +2024-11-22 23:30:30.844151: train_loss -0.8167 +2024-11-22 23:30:30.844514: val_loss -0.7698 +2024-11-22 23:30:30.846770: Pseudo dice [0.8352] +2024-11-22 23:30:30.846905: Epoch time: 18.73 s +2024-11-22 23:30:31.908353: +2024-11-22 23:30:31.908584: Epoch 6747 +2024-11-22 23:30:31.908698: Current learning rate: 0.00189 +2024-11-22 23:30:50.697282: train_loss -0.8267 +2024-11-22 23:30:50.697576: val_loss -0.7453 +2024-11-22 23:30:50.697668: Pseudo dice [0.8369] +2024-11-22 23:30:50.697763: Epoch time: 18.79 s +2024-11-22 23:30:51.615633: +2024-11-22 23:30:51.615871: Epoch 6748 +2024-11-22 23:30:51.615999: Current learning rate: 0.00188 +2024-11-22 23:31:09.814488: train_loss -0.8204 +2024-11-22 23:31:09.814708: val_loss -0.7777 +2024-11-22 23:31:09.814783: Pseudo dice [0.8382] +2024-11-22 23:31:09.814859: Epoch time: 18.2 s +2024-11-22 23:31:10.767980: +2024-11-22 23:31:10.768214: Epoch 6749 +2024-11-22 23:31:10.768335: Current learning rate: 0.00188 +2024-11-22 23:31:29.194457: train_loss -0.8182 +2024-11-22 23:31:29.194675: val_loss -0.7563 +2024-11-22 23:31:29.194748: Pseudo dice [0.8421] +2024-11-22 23:31:29.194824: Epoch time: 18.43 s +2024-11-22 23:31:30.426764: +2024-11-22 23:31:30.426962: Epoch 6750 +2024-11-22 23:31:30.427077: Current learning rate: 0.00188 +2024-11-22 23:31:48.931664: train_loss -0.8076 +2024-11-22 23:31:48.931873: val_loss -0.7708 +2024-11-22 23:31:48.931946: Pseudo dice [0.8456] +2024-11-22 23:31:48.932029: Epoch time: 18.51 s +2024-11-22 23:31:49.847741: +2024-11-22 23:31:49.847972: Epoch 6751 +2024-11-22 23:31:49.848097: Current learning rate: 0.00188 +2024-11-22 23:32:08.273934: train_loss -0.8149 +2024-11-22 23:32:08.301239: val_loss -0.7642 +2024-11-22 23:32:08.301442: Pseudo dice [0.8269] +2024-11-22 23:32:08.301551: Epoch time: 18.43 s +2024-11-22 23:32:09.235507: +2024-11-22 23:32:09.235716: Epoch 6752 +2024-11-22 23:32:09.235829: Current learning rate: 0.00188 +2024-11-22 23:32:28.593437: train_loss -0.8212 +2024-11-22 23:32:28.593660: val_loss -0.7636 +2024-11-22 23:32:28.593734: Pseudo dice [0.8416] +2024-11-22 23:32:28.593810: Epoch time: 19.36 s +2024-11-22 23:32:29.895907: +2024-11-22 23:32:29.896142: Epoch 6753 +2024-11-22 23:32:29.896260: Current learning rate: 0.00188 +2024-11-22 23:32:49.044341: train_loss -0.8167 +2024-11-22 23:32:49.044578: val_loss -0.7791 +2024-11-22 23:32:49.044651: Pseudo dice [0.8424] +2024-11-22 23:32:49.044726: Epoch time: 19.15 s +2024-11-22 23:32:49.965011: +2024-11-22 23:32:49.965219: Epoch 6754 +2024-11-22 23:32:49.965331: Current learning rate: 0.00188 +2024-11-22 23:33:07.608656: train_loss -0.8155 +2024-11-22 23:33:07.608924: val_loss -0.7598 +2024-11-22 23:33:07.609008: Pseudo dice [0.8254] +2024-11-22 23:33:07.609092: Epoch time: 17.64 s +2024-11-22 23:33:08.530432: +2024-11-22 23:33:08.530666: Epoch 6755 +2024-11-22 23:33:08.530781: Current learning rate: 0.00187 +2024-11-22 23:33:26.426951: train_loss -0.8136 +2024-11-22 23:33:26.427181: val_loss -0.7894 +2024-11-22 23:33:26.427259: Pseudo dice [0.8635] +2024-11-22 23:33:26.427335: Epoch time: 17.9 s +2024-11-22 23:33:27.343535: +2024-11-22 23:33:27.343754: Epoch 6756 +2024-11-22 23:33:27.343870: Current learning rate: 0.00187 +2024-11-22 23:33:45.701872: train_loss -0.8204 +2024-11-22 23:33:45.702093: val_loss -0.7826 +2024-11-22 23:33:45.702167: Pseudo dice [0.8313] +2024-11-22 23:33:45.702243: Epoch time: 18.36 s +2024-11-22 23:33:46.633729: +2024-11-22 23:33:46.633933: Epoch 6757 +2024-11-22 23:33:46.634052: Current learning rate: 0.00187 +2024-11-22 23:34:05.016610: train_loss -0.8152 +2024-11-22 23:34:05.016836: val_loss -0.7526 +2024-11-22 23:34:05.016915: Pseudo dice [0.8389] +2024-11-22 23:34:05.016999: Epoch time: 18.38 s +2024-11-22 23:34:05.955873: +2024-11-22 23:34:05.956086: Epoch 6758 +2024-11-22 23:34:05.956203: Current learning rate: 0.00187 +2024-11-22 23:34:25.499051: train_loss -0.8117 +2024-11-22 23:34:25.499300: val_loss -0.7528 +2024-11-22 23:34:25.499376: Pseudo dice [0.8135] +2024-11-22 23:34:25.499458: Epoch time: 19.54 s +2024-11-22 23:34:26.450498: +2024-11-22 23:34:26.450697: Epoch 6759 +2024-11-22 23:34:26.450805: Current learning rate: 0.00187 +2024-11-22 23:34:44.734681: train_loss -0.8217 +2024-11-22 23:34:44.734895: val_loss -0.7386 +2024-11-22 23:34:44.734969: Pseudo dice [0.8041] +2024-11-22 23:34:44.735053: Epoch time: 18.28 s +2024-11-22 23:34:45.733833: +2024-11-22 23:34:45.734042: Epoch 6760 +2024-11-22 23:34:45.734158: Current learning rate: 0.00187 +2024-11-22 23:35:03.912954: train_loss -0.8246 +2024-11-22 23:35:03.913190: val_loss -0.7559 +2024-11-22 23:35:03.913268: Pseudo dice [0.8271] +2024-11-22 23:35:03.913347: Epoch time: 18.18 s +2024-11-22 23:35:04.892624: +2024-11-22 23:35:04.892825: Epoch 6761 +2024-11-22 23:35:04.892934: Current learning rate: 0.00187 +2024-11-22 23:35:23.120332: train_loss -0.8142 +2024-11-22 23:35:23.120551: val_loss -0.751 +2024-11-22 23:35:23.122888: Pseudo dice [0.8175] +2024-11-22 23:35:23.123018: Epoch time: 18.23 s +2024-11-22 23:35:24.045385: +2024-11-22 23:35:24.045717: Epoch 6762 +2024-11-22 23:35:24.045832: Current learning rate: 0.00186 +2024-11-22 23:35:43.322111: train_loss -0.8085 +2024-11-22 23:35:43.322343: val_loss -0.7742 +2024-11-22 23:35:43.322418: Pseudo dice [0.826] +2024-11-22 23:35:43.322502: Epoch time: 19.28 s +2024-11-22 23:35:44.243140: +2024-11-22 23:35:44.243335: Epoch 6763 +2024-11-22 23:35:44.243448: Current learning rate: 0.00186 +2024-11-22 23:36:03.540816: train_loss -0.8164 +2024-11-22 23:36:03.541877: val_loss -0.761 +2024-11-22 23:36:03.541963: Pseudo dice [0.8388] +2024-11-22 23:36:03.542056: Epoch time: 19.3 s +2024-11-22 23:36:04.460935: +2024-11-22 23:36:04.461168: Epoch 6764 +2024-11-22 23:36:04.478303: Current learning rate: 0.00186 +2024-11-22 23:36:24.821442: train_loss -0.8103 +2024-11-22 23:36:24.827061: val_loss -0.7806 +2024-11-22 23:36:24.827221: Pseudo dice [0.8526] +2024-11-22 23:36:24.827307: Epoch time: 20.36 s +2024-11-22 23:36:25.865304: +2024-11-22 23:36:25.865530: Epoch 6765 +2024-11-22 23:36:25.865644: Current learning rate: 0.00186 +2024-11-22 23:36:44.044867: train_loss -0.8171 +2024-11-22 23:36:44.045194: val_loss -0.7664 +2024-11-22 23:36:44.045275: Pseudo dice [0.848] +2024-11-22 23:36:44.045360: Epoch time: 18.18 s +2024-11-22 23:36:44.977936: +2024-11-22 23:36:44.978146: Epoch 6766 +2024-11-22 23:36:44.978258: Current learning rate: 0.00186 +2024-11-22 23:37:03.149600: train_loss -0.8149 +2024-11-22 23:37:03.149818: val_loss -0.7725 +2024-11-22 23:37:03.149894: Pseudo dice [0.8576] +2024-11-22 23:37:03.149971: Epoch time: 18.17 s +2024-11-22 23:37:04.062339: +2024-11-22 23:37:04.062558: Epoch 6767 +2024-11-22 23:37:04.062671: Current learning rate: 0.00186 +2024-11-22 23:37:22.500232: train_loss -0.8121 +2024-11-22 23:37:22.500457: val_loss -0.7612 +2024-11-22 23:37:22.500531: Pseudo dice [0.8348] +2024-11-22 23:37:22.500608: Epoch time: 18.44 s +2024-11-22 23:37:23.420826: +2024-11-22 23:37:23.421037: Epoch 6768 +2024-11-22 23:37:23.421152: Current learning rate: 0.00186 +2024-11-22 23:37:42.730135: train_loss -0.811 +2024-11-22 23:37:42.730368: val_loss -0.744 +2024-11-22 23:37:42.730448: Pseudo dice [0.816] +2024-11-22 23:37:42.730536: Epoch time: 19.31 s +2024-11-22 23:37:43.652374: +2024-11-22 23:37:43.652591: Epoch 6769 +2024-11-22 23:37:43.652709: Current learning rate: 0.00186 +2024-11-22 23:38:01.705817: train_loss -0.8137 +2024-11-22 23:38:01.706059: val_loss -0.7571 +2024-11-22 23:38:01.706134: Pseudo dice [0.8362] +2024-11-22 23:38:01.706212: Epoch time: 18.05 s +2024-11-22 23:38:02.719028: +2024-11-22 23:38:02.719234: Epoch 6770 +2024-11-22 23:38:02.719349: Current learning rate: 0.00185 +2024-11-22 23:38:21.243790: train_loss -0.8168 +2024-11-22 23:38:21.244056: val_loss -0.7359 +2024-11-22 23:38:21.244133: Pseudo dice [0.8448] +2024-11-22 23:38:21.244210: Epoch time: 18.53 s +2024-11-22 23:38:22.230787: +2024-11-22 23:38:22.230989: Epoch 6771 +2024-11-22 23:38:22.231107: Current learning rate: 0.00185 +2024-11-22 23:38:41.354322: train_loss -0.8157 +2024-11-22 23:38:41.354547: val_loss -0.7563 +2024-11-22 23:38:41.354620: Pseudo dice [0.8216] +2024-11-22 23:38:41.356925: Epoch time: 19.12 s +2024-11-22 23:38:42.445162: +2024-11-22 23:38:42.445377: Epoch 6772 +2024-11-22 23:38:42.445513: Current learning rate: 0.00185 +2024-11-22 23:39:01.325551: train_loss -0.8154 +2024-11-22 23:39:01.331068: val_loss -0.7514 +2024-11-22 23:39:01.331284: Pseudo dice [0.832] +2024-11-22 23:39:01.331382: Epoch time: 18.88 s +2024-11-22 23:39:02.259019: +2024-11-22 23:39:02.259241: Epoch 6773 +2024-11-22 23:39:02.259368: Current learning rate: 0.00185 +2024-11-22 23:39:21.682995: train_loss -0.8139 +2024-11-22 23:39:21.683209: val_loss -0.7574 +2024-11-22 23:39:21.688420: Pseudo dice [0.8416] +2024-11-22 23:39:21.688571: Epoch time: 19.42 s +2024-11-22 23:39:22.652243: +2024-11-22 23:39:22.652481: Epoch 6774 +2024-11-22 23:39:22.652599: Current learning rate: 0.00185 +2024-11-22 23:39:41.123669: train_loss -0.8249 +2024-11-22 23:39:41.123886: val_loss -0.7707 +2024-11-22 23:39:41.123961: Pseudo dice [0.8341] +2024-11-22 23:39:41.124043: Epoch time: 18.47 s +2024-11-22 23:39:42.534552: +2024-11-22 23:39:42.534782: Epoch 6775 +2024-11-22 23:39:42.534898: Current learning rate: 0.00185 +2024-11-22 23:40:01.293236: train_loss -0.8147 +2024-11-22 23:40:01.293461: val_loss -0.7544 +2024-11-22 23:40:01.293537: Pseudo dice [0.8319] +2024-11-22 23:40:01.293622: Epoch time: 18.76 s +2024-11-22 23:40:02.223341: +2024-11-22 23:40:02.223576: Epoch 6776 +2024-11-22 23:40:02.223689: Current learning rate: 0.00185 +2024-11-22 23:40:21.038523: train_loss -0.8221 +2024-11-22 23:40:21.038763: val_loss -0.7322 +2024-11-22 23:40:21.038836: Pseudo dice [0.8285] +2024-11-22 23:40:21.135062: Epoch time: 18.82 s +2024-11-22 23:40:22.053854: +2024-11-22 23:40:22.054060: Epoch 6777 +2024-11-22 23:40:22.054176: Current learning rate: 0.00184 +2024-11-22 23:40:41.251679: train_loss -0.796 +2024-11-22 23:40:41.251897: val_loss -0.7452 +2024-11-22 23:40:41.251970: Pseudo dice [0.8199] +2024-11-22 23:40:41.252049: Epoch time: 19.2 s +2024-11-22 23:40:42.207949: +2024-11-22 23:40:42.208172: Epoch 6778 +2024-11-22 23:40:42.208286: Current learning rate: 0.00184 +2024-11-22 23:41:01.093079: train_loss -0.8117 +2024-11-22 23:41:01.095505: val_loss -0.7596 +2024-11-22 23:41:01.095603: Pseudo dice [0.8313] +2024-11-22 23:41:01.095681: Epoch time: 18.89 s +2024-11-22 23:41:02.046417: +2024-11-22 23:41:02.046654: Epoch 6779 +2024-11-22 23:41:02.046773: Current learning rate: 0.00184 +2024-11-22 23:41:21.837328: train_loss -0.8078 +2024-11-22 23:41:21.837593: val_loss -0.7565 +2024-11-22 23:41:21.837670: Pseudo dice [0.8427] +2024-11-22 23:41:21.837756: Epoch time: 19.78 s +2024-11-22 23:41:22.904748: +2024-11-22 23:41:22.904955: Epoch 6780 +2024-11-22 23:41:22.905071: Current learning rate: 0.00184 +2024-11-22 23:41:42.347124: train_loss -0.8157 +2024-11-22 23:41:42.347350: val_loss -0.7692 +2024-11-22 23:41:42.347425: Pseudo dice [0.8542] +2024-11-22 23:41:42.347500: Epoch time: 19.44 s +2024-11-22 23:41:43.262009: +2024-11-22 23:41:43.262256: Epoch 6781 +2024-11-22 23:41:43.262377: Current learning rate: 0.00184 +2024-11-22 23:42:01.585948: train_loss -0.815 +2024-11-22 23:42:01.586177: val_loss -0.7757 +2024-11-22 23:42:01.586252: Pseudo dice [0.842] +2024-11-22 23:42:01.586326: Epoch time: 18.32 s +2024-11-22 23:42:02.506083: +2024-11-22 23:42:02.506290: Epoch 6782 +2024-11-22 23:42:02.506404: Current learning rate: 0.00184 +2024-11-22 23:42:20.590475: train_loss -0.8167 +2024-11-22 23:42:20.590709: val_loss -0.7487 +2024-11-22 23:42:20.590796: Pseudo dice [0.8247] +2024-11-22 23:42:20.590881: Epoch time: 18.09 s +2024-11-22 23:42:21.510187: +2024-11-22 23:42:21.510379: Epoch 6783 +2024-11-22 23:42:21.510487: Current learning rate: 0.00184 +2024-11-22 23:42:39.090319: train_loss -0.8197 +2024-11-22 23:42:39.090538: val_loss -0.7659 +2024-11-22 23:42:39.090616: Pseudo dice [0.8497] +2024-11-22 23:42:39.090699: Epoch time: 17.58 s +2024-11-22 23:42:40.089149: +2024-11-22 23:42:40.089350: Epoch 6784 +2024-11-22 23:42:40.089465: Current learning rate: 0.00184 +2024-11-22 23:42:59.460360: train_loss -0.8169 +2024-11-22 23:42:59.460572: val_loss -0.7584 +2024-11-22 23:42:59.460646: Pseudo dice [0.8424] +2024-11-22 23:42:59.460722: Epoch time: 19.37 s +2024-11-22 23:43:00.376719: +2024-11-22 23:43:00.376920: Epoch 6785 +2024-11-22 23:43:00.377045: Current learning rate: 0.00183 +2024-11-22 23:43:18.497579: train_loss -0.821 +2024-11-22 23:43:18.497797: val_loss -0.7725 +2024-11-22 23:43:18.497873: Pseudo dice [0.8314] +2024-11-22 23:43:18.497967: Epoch time: 18.12 s +2024-11-22 23:43:19.411502: +2024-11-22 23:43:19.411699: Epoch 6786 +2024-11-22 23:43:19.411829: Current learning rate: 0.00183 +2024-11-22 23:43:38.669532: train_loss -0.8194 +2024-11-22 23:43:38.669757: val_loss -0.7594 +2024-11-22 23:43:38.669828: Pseudo dice [0.8196] +2024-11-22 23:43:38.669913: Epoch time: 19.26 s +2024-11-22 23:43:40.067898: +2024-11-22 23:43:40.068126: Epoch 6787 +2024-11-22 23:43:40.068241: Current learning rate: 0.00183 +2024-11-22 23:43:57.839500: train_loss -0.8184 +2024-11-22 23:43:57.839723: val_loss -0.7544 +2024-11-22 23:43:57.839802: Pseudo dice [0.8471] +2024-11-22 23:43:57.839885: Epoch time: 17.77 s +2024-11-22 23:43:58.754619: +2024-11-22 23:43:58.754824: Epoch 6788 +2024-11-22 23:43:58.754932: Current learning rate: 0.00183 +2024-11-22 23:44:16.688083: train_loss -0.8178 +2024-11-22 23:44:16.688297: val_loss -0.755 +2024-11-22 23:44:16.688373: Pseudo dice [0.8398] +2024-11-22 23:44:16.688453: Epoch time: 17.93 s +2024-11-22 23:44:17.595733: +2024-11-22 23:44:17.595961: Epoch 6789 +2024-11-22 23:44:17.596079: Current learning rate: 0.00183 +2024-11-22 23:44:35.911657: train_loss -0.8211 +2024-11-22 23:44:35.911895: val_loss -0.7533 +2024-11-22 23:44:35.911971: Pseudo dice [0.8268] +2024-11-22 23:44:35.912083: Epoch time: 18.32 s +2024-11-22 23:44:36.828810: +2024-11-22 23:44:36.829061: Epoch 6790 +2024-11-22 23:44:36.829185: Current learning rate: 0.00183 +2024-11-22 23:44:55.164675: train_loss -0.8223 +2024-11-22 23:44:55.164884: val_loss -0.7426 +2024-11-22 23:44:55.164959: Pseudo dice [0.8323] +2024-11-22 23:44:55.165039: Epoch time: 18.34 s +2024-11-22 23:44:56.296214: +2024-11-22 23:44:56.296428: Epoch 6791 +2024-11-22 23:44:56.296539: Current learning rate: 0.00183 +2024-11-22 23:45:14.974000: train_loss -0.829 +2024-11-22 23:45:14.974210: val_loss -0.7817 +2024-11-22 23:45:14.974285: Pseudo dice [0.8403] +2024-11-22 23:45:14.974361: Epoch time: 18.68 s +2024-11-22 23:45:15.881203: +2024-11-22 23:45:15.881404: Epoch 6792 +2024-11-22 23:45:15.881516: Current learning rate: 0.00182 +2024-11-22 23:45:35.182656: train_loss -0.8087 +2024-11-22 23:45:35.183966: val_loss -0.7764 +2024-11-22 23:45:35.184104: Pseudo dice [0.8347] +2024-11-22 23:45:35.184186: Epoch time: 19.3 s +2024-11-22 23:45:36.101803: +2024-11-22 23:45:36.102034: Epoch 6793 +2024-11-22 23:45:36.102150: Current learning rate: 0.00182 +2024-11-22 23:45:55.003086: train_loss -0.815 +2024-11-22 23:45:55.003327: val_loss -0.7794 +2024-11-22 23:45:55.003404: Pseudo dice [0.8447] +2024-11-22 23:45:55.003490: Epoch time: 18.9 s +2024-11-22 23:45:55.917040: +2024-11-22 23:45:55.917251: Epoch 6794 +2024-11-22 23:45:55.917367: Current learning rate: 0.00182 +2024-11-22 23:46:15.243832: train_loss -0.8155 +2024-11-22 23:46:15.244045: val_loss -0.7783 +2024-11-22 23:46:15.244121: Pseudo dice [0.8489] +2024-11-22 23:46:15.244198: Epoch time: 19.33 s +2024-11-22 23:46:16.143302: +2024-11-22 23:46:16.143497: Epoch 6795 +2024-11-22 23:46:16.143605: Current learning rate: 0.00182 +2024-11-22 23:46:35.525780: train_loss -0.8043 +2024-11-22 23:46:35.526003: val_loss -0.7735 +2024-11-22 23:46:35.526078: Pseudo dice [0.8377] +2024-11-22 23:46:35.526154: Epoch time: 19.38 s +2024-11-22 23:46:36.449367: +2024-11-22 23:46:36.449575: Epoch 6796 +2024-11-22 23:46:36.449685: Current learning rate: 0.00182 +2024-11-22 23:46:54.667775: train_loss -0.8236 +2024-11-22 23:46:54.667978: val_loss -0.7651 +2024-11-22 23:46:54.668061: Pseudo dice [0.8366] +2024-11-22 23:46:54.668136: Epoch time: 18.22 s +2024-11-22 23:46:55.570617: +2024-11-22 23:46:55.570815: Epoch 6797 +2024-11-22 23:46:55.570935: Current learning rate: 0.00182 +2024-11-22 23:47:14.930799: train_loss -0.8144 +2024-11-22 23:47:14.931025: val_loss -0.766 +2024-11-22 23:47:14.931100: Pseudo dice [0.8272] +2024-11-22 23:47:14.931180: Epoch time: 19.36 s +2024-11-22 23:47:15.840259: +2024-11-22 23:47:15.840693: Epoch 6798 +2024-11-22 23:47:15.840830: Current learning rate: 0.00182 +2024-11-22 23:47:35.342087: train_loss -0.8225 +2024-11-22 23:47:35.342315: val_loss -0.776 +2024-11-22 23:47:35.342391: Pseudo dice [0.8557] +2024-11-22 23:47:35.342468: Epoch time: 19.5 s +2024-11-22 23:47:36.251317: +2024-11-22 23:47:36.251532: Epoch 6799 +2024-11-22 23:47:36.251644: Current learning rate: 0.00181 +2024-11-22 23:47:55.510491: train_loss -0.8213 +2024-11-22 23:47:55.510706: val_loss -0.7706 +2024-11-22 23:47:55.510792: Pseudo dice [0.841] +2024-11-22 23:47:55.510866: Epoch time: 19.26 s +2024-11-22 23:47:56.743965: +2024-11-22 23:47:56.744170: Epoch 6800 +2024-11-22 23:47:56.744284: Current learning rate: 0.00181 +2024-11-22 23:48:15.406153: train_loss -0.821 +2024-11-22 23:48:15.406384: val_loss -0.742 +2024-11-22 23:48:15.406460: Pseudo dice [0.8326] +2024-11-22 23:48:15.406539: Epoch time: 18.66 s +2024-11-22 23:48:16.315757: +2024-11-22 23:48:16.315950: Epoch 6801 +2024-11-22 23:48:16.316062: Current learning rate: 0.00181 +2024-11-22 23:48:34.417203: train_loss -0.8214 +2024-11-22 23:48:34.417417: val_loss -0.7539 +2024-11-22 23:48:34.417507: Pseudo dice [0.8278] +2024-11-22 23:48:34.417585: Epoch time: 18.1 s +2024-11-22 23:48:35.326090: +2024-11-22 23:48:35.326287: Epoch 6802 +2024-11-22 23:48:35.326399: Current learning rate: 0.00181 +2024-11-22 23:48:53.031899: train_loss -0.8262 +2024-11-22 23:48:53.032122: val_loss -0.7634 +2024-11-22 23:48:53.032196: Pseudo dice [0.8346] +2024-11-22 23:48:53.032271: Epoch time: 17.71 s +2024-11-22 23:48:53.935349: +2024-11-22 23:48:53.935548: Epoch 6803 +2024-11-22 23:48:53.935658: Current learning rate: 0.00181 +2024-11-22 23:49:13.792953: train_loss -0.8174 +2024-11-22 23:49:13.793172: val_loss -0.7669 +2024-11-22 23:49:13.793246: Pseudo dice [0.8294] +2024-11-22 23:49:13.793324: Epoch time: 19.86 s +2024-11-22 23:49:14.706839: +2024-11-22 23:49:14.707113: Epoch 6804 +2024-11-22 23:49:14.707232: Current learning rate: 0.00181 +2024-11-22 23:49:32.428925: train_loss -0.8163 +2024-11-22 23:49:32.429210: val_loss -0.7532 +2024-11-22 23:49:32.429288: Pseudo dice [0.8348] +2024-11-22 23:49:32.429372: Epoch time: 17.72 s +2024-11-22 23:49:33.337559: +2024-11-22 23:49:33.337772: Epoch 6805 +2024-11-22 23:49:33.337885: Current learning rate: 0.00181 +2024-11-22 23:49:52.274494: train_loss -0.8095 +2024-11-22 23:49:52.274720: val_loss -0.7369 +2024-11-22 23:49:52.274796: Pseudo dice [0.8303] +2024-11-22 23:49:52.274874: Epoch time: 18.94 s +2024-11-22 23:49:53.181725: +2024-11-22 23:49:53.181921: Epoch 6806 +2024-11-22 23:49:53.182037: Current learning rate: 0.00181 +2024-11-22 23:50:11.930943: train_loss -0.8142 +2024-11-22 23:50:11.931181: val_loss -0.7615 +2024-11-22 23:50:11.931269: Pseudo dice [0.8341] +2024-11-22 23:50:11.931352: Epoch time: 18.75 s +2024-11-22 23:50:12.841978: +2024-11-22 23:50:12.842214: Epoch 6807 +2024-11-22 23:50:12.842325: Current learning rate: 0.0018 +2024-11-22 23:50:32.240528: train_loss -0.8164 +2024-11-22 23:50:32.240769: val_loss -0.7358 +2024-11-22 23:50:32.240850: Pseudo dice [0.8381] +2024-11-22 23:50:32.240933: Epoch time: 19.4 s +2024-11-22 23:50:33.159131: +2024-11-22 23:50:33.159331: Epoch 6808 +2024-11-22 23:50:33.159442: Current learning rate: 0.0018 +2024-11-22 23:50:51.143185: train_loss -0.8149 +2024-11-22 23:50:51.143485: val_loss -0.7675 +2024-11-22 23:50:51.143565: Pseudo dice [0.8194] +2024-11-22 23:50:51.143647: Epoch time: 17.99 s +2024-11-22 23:50:52.050110: +2024-11-22 23:50:52.050658: Epoch 6809 +2024-11-22 23:50:52.050798: Current learning rate: 0.0018 +2024-11-22 23:51:12.133046: train_loss -0.8195 +2024-11-22 23:51:12.133269: val_loss -0.7704 +2024-11-22 23:51:12.133343: Pseudo dice [0.8361] +2024-11-22 23:51:12.133422: Epoch time: 20.08 s +2024-11-22 23:51:13.039003: +2024-11-22 23:51:13.039243: Epoch 6810 +2024-11-22 23:51:13.039357: Current learning rate: 0.0018 +2024-11-22 23:51:32.687488: train_loss -0.8193 +2024-11-22 23:51:32.687706: val_loss -0.7646 +2024-11-22 23:51:32.687780: Pseudo dice [0.8458] +2024-11-22 23:51:32.687856: Epoch time: 19.65 s +2024-11-22 23:51:33.606073: +2024-11-22 23:51:33.606284: Epoch 6811 +2024-11-22 23:51:33.606399: Current learning rate: 0.0018 +2024-11-22 23:51:53.680561: train_loss -0.8201 +2024-11-22 23:51:53.680800: val_loss -0.7558 +2024-11-22 23:51:53.680876: Pseudo dice [0.8236] +2024-11-22 23:51:53.680965: Epoch time: 20.08 s +2024-11-22 23:51:54.599303: +2024-11-22 23:51:54.599518: Epoch 6812 +2024-11-22 23:51:54.599634: Current learning rate: 0.0018 +2024-11-22 23:52:13.295812: train_loss -0.8189 +2024-11-22 23:52:13.296039: val_loss -0.7714 +2024-11-22 23:52:13.296114: Pseudo dice [0.8365] +2024-11-22 23:52:13.296190: Epoch time: 18.7 s +2024-11-22 23:52:14.205894: +2024-11-22 23:52:14.206113: Epoch 6813 +2024-11-22 23:52:14.206223: Current learning rate: 0.0018 +2024-11-22 23:52:33.105299: train_loss -0.8219 +2024-11-22 23:52:33.105508: val_loss -0.773 +2024-11-22 23:52:33.105587: Pseudo dice [0.827] +2024-11-22 23:52:33.105661: Epoch time: 18.9 s +2024-11-22 23:52:34.051601: +2024-11-22 23:52:34.051823: Epoch 6814 +2024-11-22 23:52:34.051943: Current learning rate: 0.00179 +2024-11-22 23:52:53.773190: train_loss -0.8241 +2024-11-22 23:52:53.773420: val_loss -0.7596 +2024-11-22 23:52:53.773495: Pseudo dice [0.8306] +2024-11-22 23:52:53.773573: Epoch time: 19.72 s +2024-11-22 23:52:54.699033: +2024-11-22 23:52:54.699254: Epoch 6815 +2024-11-22 23:52:54.699365: Current learning rate: 0.00179 +2024-11-22 23:53:13.053563: train_loss -0.8256 +2024-11-22 23:53:13.053853: val_loss -0.7712 +2024-11-22 23:53:13.053928: Pseudo dice [0.8373] +2024-11-22 23:53:13.054023: Epoch time: 18.36 s +2024-11-22 23:53:13.977470: +2024-11-22 23:53:13.977679: Epoch 6816 +2024-11-22 23:53:13.977791: Current learning rate: 0.00179 +2024-11-22 23:53:33.124444: train_loss -0.8164 +2024-11-22 23:53:33.124654: val_loss -0.7569 +2024-11-22 23:53:33.124728: Pseudo dice [0.8463] +2024-11-22 23:53:33.124802: Epoch time: 19.15 s +2024-11-22 23:53:34.140654: +2024-11-22 23:53:34.140853: Epoch 6817 +2024-11-22 23:53:34.140964: Current learning rate: 0.00179 +2024-11-22 23:53:53.458833: train_loss -0.8179 +2024-11-22 23:53:53.459055: val_loss -0.7649 +2024-11-22 23:53:53.459128: Pseudo dice [0.8385] +2024-11-22 23:53:53.459203: Epoch time: 19.32 s +2024-11-22 23:53:54.375850: +2024-11-22 23:53:54.376074: Epoch 6818 +2024-11-22 23:53:54.376190: Current learning rate: 0.00179 +2024-11-22 23:54:12.892524: train_loss -0.8126 +2024-11-22 23:54:12.892735: val_loss -0.7744 +2024-11-22 23:54:12.892811: Pseudo dice [0.8521] +2024-11-22 23:54:12.892885: Epoch time: 18.52 s +2024-11-22 23:54:13.822619: +2024-11-22 23:54:13.822814: Epoch 6819 +2024-11-22 23:54:13.822924: Current learning rate: 0.00179 +2024-11-22 23:54:34.088476: train_loss -0.8193 +2024-11-22 23:54:34.090883: val_loss -0.7654 +2024-11-22 23:54:34.091010: Pseudo dice [0.8245] +2024-11-22 23:54:34.091100: Epoch time: 20.27 s +2024-11-22 23:54:35.074653: +2024-11-22 23:54:35.074869: Epoch 6820 +2024-11-22 23:54:35.074982: Current learning rate: 0.00179 +2024-11-22 23:54:53.858436: train_loss -0.8216 +2024-11-22 23:54:53.858660: val_loss -0.75 +2024-11-22 23:54:53.858773: Pseudo dice [0.836] +2024-11-22 23:54:53.858851: Epoch time: 18.78 s +2024-11-22 23:54:55.131788: +2024-11-22 23:54:55.132004: Epoch 6821 +2024-11-22 23:54:55.132114: Current learning rate: 0.00178 +2024-11-22 23:55:13.067044: train_loss -0.8192 +2024-11-22 23:55:13.067327: val_loss -0.7655 +2024-11-22 23:55:13.067407: Pseudo dice [0.8368] +2024-11-22 23:55:13.067484: Epoch time: 17.94 s +2024-11-22 23:55:13.979861: +2024-11-22 23:55:13.980111: Epoch 6822 +2024-11-22 23:55:13.980238: Current learning rate: 0.00178 +2024-11-22 23:55:32.258100: train_loss -0.815 +2024-11-22 23:55:32.264525: val_loss -0.7693 +2024-11-22 23:55:32.264661: Pseudo dice [0.8356] +2024-11-22 23:55:32.264748: Epoch time: 18.28 s +2024-11-22 23:55:33.290249: +2024-11-22 23:55:33.290463: Epoch 6823 +2024-11-22 23:55:33.290577: Current learning rate: 0.00178 +2024-11-22 23:55:51.267614: train_loss -0.8184 +2024-11-22 23:55:51.267840: val_loss -0.7633 +2024-11-22 23:55:51.267951: Pseudo dice [0.8243] +2024-11-22 23:55:51.268100: Epoch time: 17.98 s +2024-11-22 23:55:52.255424: +2024-11-22 23:55:52.255657: Epoch 6824 +2024-11-22 23:55:52.255776: Current learning rate: 0.00178 +2024-11-22 23:56:10.662028: train_loss -0.8224 +2024-11-22 23:56:10.662257: val_loss -0.7811 +2024-11-22 23:56:10.662331: Pseudo dice [0.8443] +2024-11-22 23:56:10.662406: Epoch time: 18.41 s +2024-11-22 23:56:11.828098: +2024-11-22 23:56:11.828314: Epoch 6825 +2024-11-22 23:56:11.828431: Current learning rate: 0.00178 +2024-11-22 23:56:30.297310: train_loss -0.8216 +2024-11-22 23:56:30.297532: val_loss -0.7653 +2024-11-22 23:56:30.297607: Pseudo dice [0.8547] +2024-11-22 23:56:30.297688: Epoch time: 18.47 s +2024-11-22 23:56:31.214419: +2024-11-22 23:56:31.214645: Epoch 6826 +2024-11-22 23:56:31.214765: Current learning rate: 0.00178 +2024-11-22 23:56:50.195479: train_loss -0.813 +2024-11-22 23:56:50.195806: val_loss -0.7663 +2024-11-22 23:56:50.195891: Pseudo dice [0.8427] +2024-11-22 23:56:50.195979: Epoch time: 18.98 s +2024-11-22 23:56:51.111592: +2024-11-22 23:56:51.111796: Epoch 6827 +2024-11-22 23:56:51.111910: Current learning rate: 0.00178 +2024-11-22 23:57:09.521176: train_loss -0.8135 +2024-11-22 23:57:09.521419: val_loss -0.7545 +2024-11-22 23:57:09.522711: Pseudo dice [0.8347] +2024-11-22 23:57:09.522807: Epoch time: 18.41 s +2024-11-22 23:57:10.470279: +2024-11-22 23:57:10.470482: Epoch 6828 +2024-11-22 23:57:10.470594: Current learning rate: 0.00178 +2024-11-22 23:57:29.166433: train_loss -0.8159 +2024-11-22 23:57:29.166659: val_loss -0.7825 +2024-11-22 23:57:29.168951: Pseudo dice [0.8557] +2024-11-22 23:57:29.169058: Epoch time: 18.7 s +2024-11-22 23:57:30.080375: +2024-11-22 23:57:30.080684: Epoch 6829 +2024-11-22 23:57:30.080798: Current learning rate: 0.00177 +2024-11-22 23:57:48.339530: train_loss -0.8212 +2024-11-22 23:57:48.339761: val_loss -0.7734 +2024-11-22 23:57:48.339832: Pseudo dice [0.8345] +2024-11-22 23:57:48.339908: Epoch time: 18.26 s +2024-11-22 23:57:49.409049: +2024-11-22 23:57:49.409247: Epoch 6830 +2024-11-22 23:57:49.409362: Current learning rate: 0.00177 +2024-11-22 23:58:07.941144: train_loss -0.8176 +2024-11-22 23:58:07.941383: val_loss -0.7405 +2024-11-22 23:58:07.941458: Pseudo dice [0.8316] +2024-11-22 23:58:07.941544: Epoch time: 18.53 s +2024-11-22 23:58:08.968651: +2024-11-22 23:58:08.968867: Epoch 6831 +2024-11-22 23:58:08.968984: Current learning rate: 0.00177 +2024-11-22 23:58:27.520910: train_loss -0.8226 +2024-11-22 23:58:27.521136: val_loss -0.7671 +2024-11-22 23:58:27.521212: Pseudo dice [0.8288] +2024-11-22 23:58:27.521290: Epoch time: 18.55 s +2024-11-22 23:58:28.444519: +2024-11-22 23:58:28.444735: Epoch 6832 +2024-11-22 23:58:28.444856: Current learning rate: 0.00177 +2024-11-22 23:58:48.143793: train_loss -0.8254 +2024-11-22 23:58:48.144026: val_loss -0.7603 +2024-11-22 23:58:48.144099: Pseudo dice [0.8338] +2024-11-22 23:58:48.144172: Epoch time: 19.7 s +2024-11-22 23:58:49.057577: +2024-11-22 23:58:49.057790: Epoch 6833 +2024-11-22 23:58:49.057898: Current learning rate: 0.00177 +2024-11-22 23:59:08.171964: train_loss -0.8196 +2024-11-22 23:59:08.172214: val_loss -0.7621 +2024-11-22 23:59:08.172292: Pseudo dice [0.842] +2024-11-22 23:59:08.172380: Epoch time: 19.12 s +2024-11-22 23:59:09.091849: +2024-11-22 23:59:09.092061: Epoch 6834 +2024-11-22 23:59:09.092172: Current learning rate: 0.00177 +2024-11-22 23:59:28.198638: train_loss -0.8205 +2024-11-22 23:59:28.198877: val_loss -0.735 +2024-11-22 23:59:28.198958: Pseudo dice [0.8368] +2024-11-22 23:59:28.199045: Epoch time: 19.11 s +2024-11-22 23:59:29.249785: +2024-11-22 23:59:29.249978: Epoch 6835 +2024-11-22 23:59:29.250096: Current learning rate: 0.00177 +2024-11-22 23:59:49.244842: train_loss -0.8147 +2024-11-22 23:59:49.245076: val_loss -0.7368 +2024-11-22 23:59:49.245154: Pseudo dice [0.8351] +2024-11-22 23:59:49.245229: Epoch time: 20.0 s +2024-11-22 23:59:50.285048: +2024-11-22 23:59:50.285247: Epoch 6836 +2024-11-22 23:59:50.285363: Current learning rate: 0.00176 +2024-11-23 00:00:09.331585: train_loss -0.8118 +2024-11-23 00:00:09.331814: val_loss -0.765 +2024-11-23 00:00:09.331889: Pseudo dice [0.8249] +2024-11-23 00:00:09.331967: Epoch time: 19.05 s +2024-11-23 00:00:10.246273: +2024-11-23 00:00:10.246493: Epoch 6837 +2024-11-23 00:00:10.246607: Current learning rate: 0.00176 +2024-11-23 00:00:28.997012: train_loss -0.8152 +2024-11-23 00:00:28.997254: val_loss -0.7755 +2024-11-23 00:00:28.997331: Pseudo dice [0.8392] +2024-11-23 00:00:28.997412: Epoch time: 18.75 s +2024-11-23 00:00:29.914330: +2024-11-23 00:00:29.914555: Epoch 6838 +2024-11-23 00:00:29.914671: Current learning rate: 0.00176 +2024-11-23 00:00:48.359277: train_loss -0.8137 +2024-11-23 00:00:48.359502: val_loss -0.7612 +2024-11-23 00:00:48.359575: Pseudo dice [0.8254] +2024-11-23 00:00:48.359651: Epoch time: 18.45 s +2024-11-23 00:00:49.283451: +2024-11-23 00:00:49.283708: Epoch 6839 +2024-11-23 00:00:49.283823: Current learning rate: 0.00176 +2024-11-23 00:01:07.865622: train_loss -0.8213 +2024-11-23 00:01:07.865836: val_loss -0.7557 +2024-11-23 00:01:07.865913: Pseudo dice [0.8409] +2024-11-23 00:01:07.865988: Epoch time: 18.58 s +2024-11-23 00:01:08.835462: +2024-11-23 00:01:08.835679: Epoch 6840 +2024-11-23 00:01:08.835792: Current learning rate: 0.00176 +2024-11-23 00:01:26.846321: train_loss -0.8169 +2024-11-23 00:01:26.846550: val_loss -0.735 +2024-11-23 00:01:26.846629: Pseudo dice [0.8046] +2024-11-23 00:01:26.846706: Epoch time: 18.01 s +2024-11-23 00:01:27.766935: +2024-11-23 00:01:27.767151: Epoch 6841 +2024-11-23 00:01:27.767263: Current learning rate: 0.00176 +2024-11-23 00:01:46.662401: train_loss -0.8197 +2024-11-23 00:01:46.662621: val_loss -0.7777 +2024-11-23 00:01:46.662721: Pseudo dice [0.8415] +2024-11-23 00:01:46.662802: Epoch time: 18.9 s +2024-11-23 00:01:47.575921: +2024-11-23 00:01:47.576133: Epoch 6842 +2024-11-23 00:01:47.576247: Current learning rate: 0.00176 +2024-11-23 00:02:05.482247: train_loss -0.8205 +2024-11-23 00:02:05.482485: val_loss -0.7612 +2024-11-23 00:02:05.484736: Pseudo dice [0.8452] +2024-11-23 00:02:05.484838: Epoch time: 17.91 s +2024-11-23 00:02:06.484354: +2024-11-23 00:02:06.484752: Epoch 6843 +2024-11-23 00:02:06.484881: Current learning rate: 0.00175 +2024-11-23 00:02:25.315461: train_loss -0.8271 +2024-11-23 00:02:25.316802: val_loss -0.7623 +2024-11-23 00:02:25.316910: Pseudo dice [0.8414] +2024-11-23 00:02:25.316999: Epoch time: 18.83 s +2024-11-23 00:02:26.610234: +2024-11-23 00:02:26.610468: Epoch 6844 +2024-11-23 00:02:26.610584: Current learning rate: 0.00175 +2024-11-23 00:02:45.190888: train_loss -0.8179 +2024-11-23 00:02:45.191179: val_loss -0.7227 +2024-11-23 00:02:45.191257: Pseudo dice [0.8177] +2024-11-23 00:02:45.191339: Epoch time: 18.58 s +2024-11-23 00:02:46.106305: +2024-11-23 00:02:46.106514: Epoch 6845 +2024-11-23 00:02:46.106631: Current learning rate: 0.00175 +2024-11-23 00:03:04.695545: train_loss -0.8229 +2024-11-23 00:03:04.697986: val_loss -0.7336 +2024-11-23 00:03:04.698115: Pseudo dice [0.8279] +2024-11-23 00:03:04.698200: Epoch time: 18.59 s +2024-11-23 00:03:05.974552: +2024-11-23 00:03:05.974806: Epoch 6846 +2024-11-23 00:03:05.974920: Current learning rate: 0.00175 +2024-11-23 00:03:25.000881: train_loss -0.8109 +2024-11-23 00:03:25.001101: val_loss -0.756 +2024-11-23 00:03:25.001178: Pseudo dice [0.8289] +2024-11-23 00:03:25.001255: Epoch time: 19.03 s +2024-11-23 00:03:25.919640: +2024-11-23 00:03:25.919851: Epoch 6847 +2024-11-23 00:03:25.919963: Current learning rate: 0.00175 +2024-11-23 00:03:43.313996: train_loss -0.8162 +2024-11-23 00:03:43.314230: val_loss -0.7332 +2024-11-23 00:03:43.314306: Pseudo dice [0.8437] +2024-11-23 00:03:43.319597: Epoch time: 17.4 s +2024-11-23 00:03:44.332312: +2024-11-23 00:03:44.332609: Epoch 6848 +2024-11-23 00:03:44.332720: Current learning rate: 0.00175 +2024-11-23 00:04:02.849105: train_loss -0.8271 +2024-11-23 00:04:02.849337: val_loss -0.7765 +2024-11-23 00:04:02.849414: Pseudo dice [0.8488] +2024-11-23 00:04:02.849494: Epoch time: 18.52 s +2024-11-23 00:04:03.909187: +2024-11-23 00:04:03.909387: Epoch 6849 +2024-11-23 00:04:03.909501: Current learning rate: 0.00175 +2024-11-23 00:04:22.841392: train_loss -0.8229 +2024-11-23 00:04:22.841652: val_loss -0.7606 +2024-11-23 00:04:22.841781: Pseudo dice [0.8352] +2024-11-23 00:04:22.841862: Epoch time: 18.93 s +2024-11-23 00:04:24.101928: +2024-11-23 00:04:24.102197: Epoch 6850 +2024-11-23 00:04:24.102410: Current learning rate: 0.00175 +2024-11-23 00:04:42.811594: train_loss -0.8178 +2024-11-23 00:04:42.811831: val_loss -0.7635 +2024-11-23 00:04:42.814160: Pseudo dice [0.8395] +2024-11-23 00:04:42.814250: Epoch time: 18.71 s +2024-11-23 00:04:43.733416: +2024-11-23 00:04:43.733632: Epoch 6851 +2024-11-23 00:04:43.733744: Current learning rate: 0.00174 +2024-11-23 00:05:02.435338: train_loss -0.8207 +2024-11-23 00:05:02.435632: val_loss -0.7464 +2024-11-23 00:05:02.435715: Pseudo dice [0.8437] +2024-11-23 00:05:02.435792: Epoch time: 18.7 s +2024-11-23 00:05:03.349373: +2024-11-23 00:05:03.349576: Epoch 6852 +2024-11-23 00:05:03.349692: Current learning rate: 0.00174 +2024-11-23 00:05:20.659341: train_loss -0.8273 +2024-11-23 00:05:20.661711: val_loss -0.7371 +2024-11-23 00:05:20.661825: Pseudo dice [0.8312] +2024-11-23 00:05:20.661911: Epoch time: 17.31 s +2024-11-23 00:05:21.675947: +2024-11-23 00:05:21.686183: Epoch 6853 +2024-11-23 00:05:21.686318: Current learning rate: 0.00174 +2024-11-23 00:05:41.090424: train_loss -0.8186 +2024-11-23 00:05:41.090661: val_loss -0.7357 +2024-11-23 00:05:41.090738: Pseudo dice [0.8167] +2024-11-23 00:05:41.090817: Epoch time: 19.42 s +2024-11-23 00:05:42.003386: +2024-11-23 00:05:42.003575: Epoch 6854 +2024-11-23 00:05:42.003691: Current learning rate: 0.00174 +2024-11-23 00:05:59.428530: train_loss -0.8283 +2024-11-23 00:05:59.428749: val_loss -0.7325 +2024-11-23 00:05:59.428822: Pseudo dice [0.8426] +2024-11-23 00:05:59.428899: Epoch time: 17.43 s +2024-11-23 00:06:00.344661: +2024-11-23 00:06:00.344860: Epoch 6855 +2024-11-23 00:06:00.344976: Current learning rate: 0.00174 +2024-11-23 00:06:18.873068: train_loss -0.8158 +2024-11-23 00:06:18.873298: val_loss -0.7578 +2024-11-23 00:06:18.873424: Pseudo dice [0.8409] +2024-11-23 00:06:18.873507: Epoch time: 18.53 s +2024-11-23 00:06:19.787428: +2024-11-23 00:06:19.787677: Epoch 6856 +2024-11-23 00:06:19.787801: Current learning rate: 0.00174 +2024-11-23 00:06:39.973091: train_loss -0.8205 +2024-11-23 00:06:39.973327: val_loss -0.7549 +2024-11-23 00:06:39.973404: Pseudo dice [0.8393] +2024-11-23 00:06:39.973492: Epoch time: 20.19 s +2024-11-23 00:06:40.884875: +2024-11-23 00:06:40.885132: Epoch 6857 +2024-11-23 00:06:40.885250: Current learning rate: 0.00174 +2024-11-23 00:07:00.114138: train_loss -0.8166 +2024-11-23 00:07:00.114366: val_loss -0.7609 +2024-11-23 00:07:00.114438: Pseudo dice [0.8387] +2024-11-23 00:07:00.114516: Epoch time: 19.23 s +2024-11-23 00:07:01.062205: +2024-11-23 00:07:01.062430: Epoch 6858 +2024-11-23 00:07:01.062541: Current learning rate: 0.00173 +2024-11-23 00:07:20.361152: train_loss -0.8221 +2024-11-23 00:07:20.361435: val_loss -0.7703 +2024-11-23 00:07:20.361511: Pseudo dice [0.8372] +2024-11-23 00:07:20.361589: Epoch time: 19.3 s +2024-11-23 00:07:21.278561: +2024-11-23 00:07:21.278775: Epoch 6859 +2024-11-23 00:07:21.278888: Current learning rate: 0.00173 +2024-11-23 00:07:40.171619: train_loss -0.8149 +2024-11-23 00:07:40.171837: val_loss -0.7822 +2024-11-23 00:07:40.171917: Pseudo dice [0.8555] +2024-11-23 00:07:40.172008: Epoch time: 18.89 s +2024-11-23 00:07:41.091151: +2024-11-23 00:07:41.091374: Epoch 6860 +2024-11-23 00:07:41.091483: Current learning rate: 0.00173 +2024-11-23 00:08:00.014696: train_loss -0.823 +2024-11-23 00:08:00.014919: val_loss -0.7291 +2024-11-23 00:08:00.015001: Pseudo dice [0.8238] +2024-11-23 00:08:00.015078: Epoch time: 18.92 s +2024-11-23 00:08:00.923353: +2024-11-23 00:08:00.923560: Epoch 6861 +2024-11-23 00:08:00.923676: Current learning rate: 0.00173 +2024-11-23 00:08:20.728736: train_loss -0.8181 +2024-11-23 00:08:20.728956: val_loss -0.7645 +2024-11-23 00:08:20.729037: Pseudo dice [0.8308] +2024-11-23 00:08:20.729118: Epoch time: 19.81 s +2024-11-23 00:08:21.732272: +2024-11-23 00:08:21.732489: Epoch 6862 +2024-11-23 00:08:21.732600: Current learning rate: 0.00173 +2024-11-23 00:08:39.316489: train_loss -0.8288 +2024-11-23 00:08:39.316778: val_loss -0.7568 +2024-11-23 00:08:39.316857: Pseudo dice [0.8307] +2024-11-23 00:08:39.316932: Epoch time: 17.58 s +2024-11-23 00:08:40.239363: +2024-11-23 00:08:40.239586: Epoch 6863 +2024-11-23 00:08:40.239715: Current learning rate: 0.00173 +2024-11-23 00:08:59.438782: train_loss -0.8167 +2024-11-23 00:08:59.439042: val_loss -0.7602 +2024-11-23 00:08:59.439122: Pseudo dice [0.8311] +2024-11-23 00:08:59.439206: Epoch time: 19.2 s +2024-11-23 00:09:00.364314: +2024-11-23 00:09:00.364516: Epoch 6864 +2024-11-23 00:09:00.364627: Current learning rate: 0.00173 +2024-11-23 00:09:18.665441: train_loss -0.826 +2024-11-23 00:09:18.665654: val_loss -0.7554 +2024-11-23 00:09:18.665730: Pseudo dice [0.84] +2024-11-23 00:09:18.665814: Epoch time: 18.3 s +2024-11-23 00:09:19.576188: +2024-11-23 00:09:19.576396: Epoch 6865 +2024-11-23 00:09:19.576510: Current learning rate: 0.00172 +2024-11-23 00:09:38.635411: train_loss -0.8205 +2024-11-23 00:09:38.635663: val_loss -0.7863 +2024-11-23 00:09:38.635742: Pseudo dice [0.8539] +2024-11-23 00:09:38.636814: Epoch time: 19.06 s +2024-11-23 00:09:39.545579: +2024-11-23 00:09:39.545843: Epoch 6866 +2024-11-23 00:09:39.545956: Current learning rate: 0.00172 +2024-11-23 00:09:56.893728: train_loss -0.8157 +2024-11-23 00:09:56.893965: val_loss -0.7724 +2024-11-23 00:09:56.894050: Pseudo dice [0.8232] +2024-11-23 00:09:56.894138: Epoch time: 17.35 s +2024-11-23 00:09:58.210172: +2024-11-23 00:09:58.210368: Epoch 6867 +2024-11-23 00:09:58.210481: Current learning rate: 0.00172 +2024-11-23 00:10:16.156318: train_loss -0.8214 +2024-11-23 00:10:16.156542: val_loss -0.7597 +2024-11-23 00:10:16.156621: Pseudo dice [0.83] +2024-11-23 00:10:16.156701: Epoch time: 17.95 s +2024-11-23 00:10:17.072947: +2024-11-23 00:10:17.073155: Epoch 6868 +2024-11-23 00:10:17.073264: Current learning rate: 0.00172 +2024-11-23 00:10:35.191770: train_loss -0.8203 +2024-11-23 00:10:35.195464: val_loss -0.7682 +2024-11-23 00:10:35.195577: Pseudo dice [0.8453] +2024-11-23 00:10:35.195661: Epoch time: 18.12 s +2024-11-23 00:10:36.143857: +2024-11-23 00:10:36.144081: Epoch 6869 +2024-11-23 00:10:36.144207: Current learning rate: 0.00172 +2024-11-23 00:10:54.958337: train_loss -0.8264 +2024-11-23 00:10:54.958572: val_loss -0.7572 +2024-11-23 00:10:54.958646: Pseudo dice [0.8271] +2024-11-23 00:10:54.958729: Epoch time: 18.82 s +2024-11-23 00:10:56.102497: +2024-11-23 00:10:56.102711: Epoch 6870 +2024-11-23 00:10:56.102825: Current learning rate: 0.00172 +2024-11-23 00:11:14.203908: train_loss -0.824 +2024-11-23 00:11:14.204131: val_loss -0.751 +2024-11-23 00:11:14.204205: Pseudo dice [0.8253] +2024-11-23 00:11:14.204283: Epoch time: 18.1 s +2024-11-23 00:11:15.124073: +2024-11-23 00:11:15.124269: Epoch 6871 +2024-11-23 00:11:15.124379: Current learning rate: 0.00172 +2024-11-23 00:11:33.272130: train_loss -0.8212 +2024-11-23 00:11:33.272342: val_loss -0.7692 +2024-11-23 00:11:33.272413: Pseudo dice [0.837] +2024-11-23 00:11:33.272491: Epoch time: 18.15 s +2024-11-23 00:11:34.296246: +2024-11-23 00:11:34.296473: Epoch 6872 +2024-11-23 00:11:34.296587: Current learning rate: 0.00172 +2024-11-23 00:11:52.714300: train_loss -0.8191 +2024-11-23 00:11:52.714527: val_loss -0.7317 +2024-11-23 00:11:52.714607: Pseudo dice [0.8277] +2024-11-23 00:11:52.714688: Epoch time: 18.42 s +2024-11-23 00:11:53.628877: +2024-11-23 00:11:53.629107: Epoch 6873 +2024-11-23 00:11:53.629217: Current learning rate: 0.00171 +2024-11-23 00:12:12.159784: train_loss -0.8084 +2024-11-23 00:12:12.162467: val_loss -0.743 +2024-11-23 00:12:12.162583: Pseudo dice [0.8058] +2024-11-23 00:12:12.162675: Epoch time: 18.53 s +2024-11-23 00:12:13.381316: +2024-11-23 00:12:13.381518: Epoch 6874 +2024-11-23 00:12:13.381639: Current learning rate: 0.00171 +2024-11-23 00:12:32.854723: train_loss -0.8172 +2024-11-23 00:12:32.854944: val_loss -0.7328 +2024-11-23 00:12:32.855026: Pseudo dice [0.8329] +2024-11-23 00:12:32.855104: Epoch time: 19.47 s +2024-11-23 00:12:33.771369: +2024-11-23 00:12:33.771566: Epoch 6875 +2024-11-23 00:12:33.771681: Current learning rate: 0.00171 +2024-11-23 00:12:52.565153: train_loss -0.8228 +2024-11-23 00:12:52.565392: val_loss -0.7434 +2024-11-23 00:12:52.565474: Pseudo dice [0.8337] +2024-11-23 00:12:52.565550: Epoch time: 18.79 s +2024-11-23 00:12:53.478801: +2024-11-23 00:12:53.479187: Epoch 6876 +2024-11-23 00:12:53.479316: Current learning rate: 0.00171 +2024-11-23 00:13:12.715355: train_loss -0.8108 +2024-11-23 00:13:12.715569: val_loss -0.7684 +2024-11-23 00:13:12.715647: Pseudo dice [0.8158] +2024-11-23 00:13:12.715722: Epoch time: 19.24 s +2024-11-23 00:13:13.807643: +2024-11-23 00:13:13.807940: Epoch 6877 +2024-11-23 00:13:13.808064: Current learning rate: 0.00171 +2024-11-23 00:13:32.398509: train_loss -0.8173 +2024-11-23 00:13:32.398756: val_loss -0.7412 +2024-11-23 00:13:32.398831: Pseudo dice [0.8337] +2024-11-23 00:13:32.398911: Epoch time: 18.59 s +2024-11-23 00:13:33.325661: +2024-11-23 00:13:33.326076: Epoch 6878 +2024-11-23 00:13:33.326210: Current learning rate: 0.00171 +2024-11-23 00:13:52.813644: train_loss -0.8136 +2024-11-23 00:13:52.835712: val_loss -0.7602 +2024-11-23 00:13:52.835825: Pseudo dice [0.8353] +2024-11-23 00:13:52.836000: Epoch time: 19.49 s +2024-11-23 00:13:53.747719: +2024-11-23 00:13:53.747932: Epoch 6879 +2024-11-23 00:13:53.748058: Current learning rate: 0.00171 +2024-11-23 00:14:11.742147: train_loss -0.8194 +2024-11-23 00:14:11.742375: val_loss -0.745 +2024-11-23 00:14:11.742454: Pseudo dice [0.8377] +2024-11-23 00:14:11.742536: Epoch time: 18.0 s +2024-11-23 00:14:12.657457: +2024-11-23 00:14:12.657677: Epoch 6880 +2024-11-23 00:14:12.657792: Current learning rate: 0.0017 +2024-11-23 00:14:31.051158: train_loss -0.8138 +2024-11-23 00:14:31.054345: val_loss -0.7423 +2024-11-23 00:14:31.054499: Pseudo dice [0.847] +2024-11-23 00:14:31.054596: Epoch time: 18.39 s +2024-11-23 00:14:31.969781: +2024-11-23 00:14:31.969983: Epoch 6881 +2024-11-23 00:14:31.970099: Current learning rate: 0.0017 +2024-11-23 00:14:49.417754: train_loss -0.817 +2024-11-23 00:14:49.417972: val_loss -0.7496 +2024-11-23 00:14:49.418058: Pseudo dice [0.8256] +2024-11-23 00:14:49.418136: Epoch time: 17.45 s +2024-11-23 00:14:50.326016: +2024-11-23 00:14:50.326235: Epoch 6882 +2024-11-23 00:14:50.326349: Current learning rate: 0.0017 +2024-11-23 00:15:09.347178: train_loss -0.8181 +2024-11-23 00:15:09.347400: val_loss -0.7464 +2024-11-23 00:15:09.347474: Pseudo dice [0.8278] +2024-11-23 00:15:09.347552: Epoch time: 19.02 s +2024-11-23 00:15:10.264735: +2024-11-23 00:15:10.264939: Epoch 6883 +2024-11-23 00:15:10.265069: Current learning rate: 0.0017 +2024-11-23 00:15:28.682485: train_loss -0.8224 +2024-11-23 00:15:28.684784: val_loss -0.7453 +2024-11-23 00:15:28.685021: Pseudo dice [0.831] +2024-11-23 00:15:28.685106: Epoch time: 18.42 s +2024-11-23 00:15:29.671065: +2024-11-23 00:15:29.671267: Epoch 6884 +2024-11-23 00:15:29.671381: Current learning rate: 0.0017 +2024-11-23 00:15:48.744009: train_loss -0.8205 +2024-11-23 00:15:48.744239: val_loss -0.7711 +2024-11-23 00:15:48.744314: Pseudo dice [0.8389] +2024-11-23 00:15:48.744397: Epoch time: 19.07 s +2024-11-23 00:15:49.656420: +2024-11-23 00:15:49.656627: Epoch 6885 +2024-11-23 00:15:49.656756: Current learning rate: 0.0017 +2024-11-23 00:16:08.376694: train_loss -0.8203 +2024-11-23 00:16:08.376938: val_loss -0.7655 +2024-11-23 00:16:08.377034: Pseudo dice [0.8367] +2024-11-23 00:16:08.377123: Epoch time: 18.72 s +2024-11-23 00:16:09.340245: +2024-11-23 00:16:09.340458: Epoch 6886 +2024-11-23 00:16:09.340569: Current learning rate: 0.0017 +2024-11-23 00:16:27.395097: train_loss -0.8258 +2024-11-23 00:16:27.395318: val_loss -0.7714 +2024-11-23 00:16:27.395466: Pseudo dice [0.8341] +2024-11-23 00:16:27.395547: Epoch time: 18.06 s +2024-11-23 00:16:28.308450: +2024-11-23 00:16:28.308639: Epoch 6887 +2024-11-23 00:16:28.308749: Current learning rate: 0.00169 +2024-11-23 00:16:47.842118: train_loss -0.8231 +2024-11-23 00:16:47.842332: val_loss -0.7355 +2024-11-23 00:16:47.844600: Pseudo dice [0.8281] +2024-11-23 00:16:47.844710: Epoch time: 19.53 s +2024-11-23 00:16:48.966789: +2024-11-23 00:16:48.967074: Epoch 6888 +2024-11-23 00:16:48.967190: Current learning rate: 0.00169 +2024-11-23 00:17:07.840296: train_loss -0.8153 +2024-11-23 00:17:07.840541: val_loss -0.7558 +2024-11-23 00:17:07.840621: Pseudo dice [0.8137] +2024-11-23 00:17:07.840705: Epoch time: 18.87 s +2024-11-23 00:17:08.839946: +2024-11-23 00:17:08.840219: Epoch 6889 +2024-11-23 00:17:08.840335: Current learning rate: 0.00169 +2024-11-23 00:17:27.263692: train_loss -0.8183 +2024-11-23 00:17:27.263904: val_loss -0.7765 +2024-11-23 00:17:27.263978: Pseudo dice [0.8449] +2024-11-23 00:17:27.264060: Epoch time: 18.42 s +2024-11-23 00:17:28.564219: +2024-11-23 00:17:28.564426: Epoch 6890 +2024-11-23 00:17:28.564544: Current learning rate: 0.00169 +2024-11-23 00:17:47.366930: train_loss -0.8205 +2024-11-23 00:17:47.367161: val_loss -0.7578 +2024-11-23 00:17:47.367239: Pseudo dice [0.834] +2024-11-23 00:17:47.367319: Epoch time: 18.8 s +2024-11-23 00:17:48.286105: +2024-11-23 00:17:48.286305: Epoch 6891 +2024-11-23 00:17:48.294441: Current learning rate: 0.00169 +2024-11-23 00:18:05.918360: train_loss -0.8226 +2024-11-23 00:18:05.918595: val_loss -0.7332 +2024-11-23 00:18:05.918676: Pseudo dice [0.8163] +2024-11-23 00:18:05.918769: Epoch time: 17.63 s +2024-11-23 00:18:06.829267: +2024-11-23 00:18:06.829496: Epoch 6892 +2024-11-23 00:18:06.829606: Current learning rate: 0.00169 +2024-11-23 00:18:25.510327: train_loss -0.823 +2024-11-23 00:18:25.510552: val_loss -0.7476 +2024-11-23 00:18:25.510626: Pseudo dice [0.8247] +2024-11-23 00:18:25.510702: Epoch time: 18.68 s +2024-11-23 00:18:26.426596: +2024-11-23 00:18:26.426813: Epoch 6893 +2024-11-23 00:18:26.426928: Current learning rate: 0.00169 +2024-11-23 00:18:44.903443: train_loss -0.827 +2024-11-23 00:18:44.903668: val_loss -0.7581 +2024-11-23 00:18:44.903742: Pseudo dice [0.8295] +2024-11-23 00:18:44.903818: Epoch time: 18.48 s +2024-11-23 00:18:45.819123: +2024-11-23 00:18:45.819327: Epoch 6894 +2024-11-23 00:18:45.819439: Current learning rate: 0.00168 +2024-11-23 00:19:04.501464: train_loss -0.8274 +2024-11-23 00:19:04.501683: val_loss -0.7577 +2024-11-23 00:19:04.501755: Pseudo dice [0.8407] +2024-11-23 00:19:04.501831: Epoch time: 18.68 s +2024-11-23 00:19:05.415267: +2024-11-23 00:19:05.415475: Epoch 6895 +2024-11-23 00:19:05.415585: Current learning rate: 0.00168 +2024-11-23 00:19:22.448408: train_loss -0.8258 +2024-11-23 00:19:22.448639: val_loss -0.7899 +2024-11-23 00:19:22.448740: Pseudo dice [0.8408] +2024-11-23 00:19:22.448827: Epoch time: 17.03 s +2024-11-23 00:19:23.360586: +2024-11-23 00:19:23.360858: Epoch 6896 +2024-11-23 00:19:23.360974: Current learning rate: 0.00168 +2024-11-23 00:19:42.394977: train_loss -0.8209 +2024-11-23 00:19:42.395208: val_loss -0.7585 +2024-11-23 00:19:42.395286: Pseudo dice [0.8513] +2024-11-23 00:19:42.395420: Epoch time: 19.04 s +2024-11-23 00:19:43.326837: +2024-11-23 00:19:43.327045: Epoch 6897 +2024-11-23 00:19:43.327154: Current learning rate: 0.00168 +2024-11-23 00:20:02.148584: train_loss -0.8219 +2024-11-23 00:20:02.148806: val_loss -0.7533 +2024-11-23 00:20:02.148878: Pseudo dice [0.831] +2024-11-23 00:20:02.148952: Epoch time: 18.82 s +2024-11-23 00:20:03.079906: +2024-11-23 00:20:03.080142: Epoch 6898 +2024-11-23 00:20:03.080262: Current learning rate: 0.00168 +2024-11-23 00:20:21.679436: train_loss -0.8271 +2024-11-23 00:20:21.679700: val_loss -0.7496 +2024-11-23 00:20:21.679775: Pseudo dice [0.8191] +2024-11-23 00:20:21.679859: Epoch time: 18.6 s +2024-11-23 00:20:22.598661: +2024-11-23 00:20:22.598854: Epoch 6899 +2024-11-23 00:20:22.598965: Current learning rate: 0.00168 +2024-11-23 00:20:41.408468: train_loss -0.8262 +2024-11-23 00:20:41.408715: val_loss -0.7734 +2024-11-23 00:20:41.408789: Pseudo dice [0.8395] +2024-11-23 00:20:41.408871: Epoch time: 18.81 s +2024-11-23 00:20:42.641143: +2024-11-23 00:20:42.641353: Epoch 6900 +2024-11-23 00:20:42.641465: Current learning rate: 0.00168 +2024-11-23 00:21:00.523101: train_loss -0.8251 +2024-11-23 00:21:00.523326: val_loss -0.7515 +2024-11-23 00:21:00.525579: Pseudo dice [0.8359] +2024-11-23 00:21:00.525717: Epoch time: 17.88 s +2024-11-23 00:21:01.609241: +2024-11-23 00:21:01.609665: Epoch 6901 +2024-11-23 00:21:01.609800: Current learning rate: 0.00168 +2024-11-23 00:21:19.613478: train_loss -0.8254 +2024-11-23 00:21:19.613690: val_loss -0.7637 +2024-11-23 00:21:19.613764: Pseudo dice [0.8313] +2024-11-23 00:21:19.613840: Epoch time: 18.01 s +2024-11-23 00:21:20.551108: +2024-11-23 00:21:20.551309: Epoch 6902 +2024-11-23 00:21:20.551423: Current learning rate: 0.00167 +2024-11-23 00:21:38.636450: train_loss -0.828 +2024-11-23 00:21:38.636678: val_loss -0.7562 +2024-11-23 00:21:38.636750: Pseudo dice [0.8349] +2024-11-23 00:21:38.636829: Epoch time: 18.09 s +2024-11-23 00:21:39.746182: +2024-11-23 00:21:39.746397: Epoch 6903 +2024-11-23 00:21:39.746507: Current learning rate: 0.00167 +2024-11-23 00:21:58.500928: train_loss -0.8198 +2024-11-23 00:21:58.501152: val_loss -0.7596 +2024-11-23 00:21:58.501225: Pseudo dice [0.8156] +2024-11-23 00:21:58.501309: Epoch time: 18.76 s +2024-11-23 00:21:59.405921: +2024-11-23 00:21:59.406135: Epoch 6904 +2024-11-23 00:21:59.406246: Current learning rate: 0.00167 +2024-11-23 00:22:18.606552: train_loss -0.8304 +2024-11-23 00:22:18.606783: val_loss -0.759 +2024-11-23 00:22:18.606858: Pseudo dice [0.8422] +2024-11-23 00:22:18.606936: Epoch time: 19.2 s +2024-11-23 00:22:19.496463: +2024-11-23 00:22:19.496667: Epoch 6905 +2024-11-23 00:22:19.496779: Current learning rate: 0.00167 +2024-11-23 00:22:36.850642: train_loss -0.8194 +2024-11-23 00:22:36.850888: val_loss -0.7676 +2024-11-23 00:22:36.850964: Pseudo dice [0.8374] +2024-11-23 00:22:36.851087: Epoch time: 17.35 s +2024-11-23 00:22:37.796629: +2024-11-23 00:22:37.796839: Epoch 6906 +2024-11-23 00:22:37.796955: Current learning rate: 0.00167 +2024-11-23 00:22:56.462630: train_loss -0.8203 +2024-11-23 00:22:56.462857: val_loss -0.7614 +2024-11-23 00:22:56.462929: Pseudo dice [0.8467] +2024-11-23 00:22:56.463013: Epoch time: 18.67 s +2024-11-23 00:22:57.415782: +2024-11-23 00:22:57.415998: Epoch 6907 +2024-11-23 00:22:57.416112: Current learning rate: 0.00167 +2024-11-23 00:23:15.898054: train_loss -0.8181 +2024-11-23 00:23:15.898344: val_loss -0.7621 +2024-11-23 00:23:15.898421: Pseudo dice [0.8196] +2024-11-23 00:23:15.898503: Epoch time: 18.48 s +2024-11-23 00:23:16.847120: +2024-11-23 00:23:16.847322: Epoch 6908 +2024-11-23 00:23:16.847439: Current learning rate: 0.00167 +2024-11-23 00:23:35.482003: train_loss -0.8202 +2024-11-23 00:23:35.482243: val_loss -0.7243 +2024-11-23 00:23:35.482364: Pseudo dice [0.8139] +2024-11-23 00:23:35.482451: Epoch time: 18.64 s +2024-11-23 00:23:36.397317: +2024-11-23 00:23:36.397511: Epoch 6909 +2024-11-23 00:23:36.397624: Current learning rate: 0.00166 +2024-11-23 00:23:55.526545: train_loss -0.8236 +2024-11-23 00:23:55.526772: val_loss -0.7444 +2024-11-23 00:23:55.526849: Pseudo dice [0.8169] +2024-11-23 00:23:55.526922: Epoch time: 19.13 s +2024-11-23 00:23:56.435626: +2024-11-23 00:23:56.435827: Epoch 6910 +2024-11-23 00:23:56.435946: Current learning rate: 0.00166 +2024-11-23 00:24:15.338062: train_loss -0.8184 +2024-11-23 00:24:15.338289: val_loss -0.7456 +2024-11-23 00:24:15.338366: Pseudo dice [0.8448] +2024-11-23 00:24:15.338449: Epoch time: 18.9 s +2024-11-23 00:24:16.320124: +2024-11-23 00:24:16.320323: Epoch 6911 +2024-11-23 00:24:16.320434: Current learning rate: 0.00166 +2024-11-23 00:24:35.659095: train_loss -0.8076 +2024-11-23 00:24:35.659335: val_loss -0.7365 +2024-11-23 00:24:35.659427: Pseudo dice [0.8435] +2024-11-23 00:24:35.659565: Epoch time: 19.34 s +2024-11-23 00:24:36.627450: +2024-11-23 00:24:36.627670: Epoch 6912 +2024-11-23 00:24:36.627782: Current learning rate: 0.00166 +2024-11-23 00:24:55.470373: train_loss -0.806 +2024-11-23 00:24:55.470668: val_loss -0.7658 +2024-11-23 00:24:55.470743: Pseudo dice [0.8286] +2024-11-23 00:24:55.470823: Epoch time: 18.84 s +2024-11-23 00:24:56.773916: +2024-11-23 00:24:56.774128: Epoch 6913 +2024-11-23 00:24:56.774246: Current learning rate: 0.00166 +2024-11-23 00:25:15.474140: train_loss -0.8199 +2024-11-23 00:25:15.474365: val_loss -0.7622 +2024-11-23 00:25:15.474441: Pseudo dice [0.8411] +2024-11-23 00:25:15.474515: Epoch time: 18.7 s +2024-11-23 00:25:16.431566: +2024-11-23 00:25:16.431790: Epoch 6914 +2024-11-23 00:25:16.431906: Current learning rate: 0.00166 +2024-11-23 00:25:35.861465: train_loss -0.8064 +2024-11-23 00:25:35.861694: val_loss -0.7453 +2024-11-23 00:25:35.861778: Pseudo dice [0.8291] +2024-11-23 00:25:35.861861: Epoch time: 19.43 s +2024-11-23 00:25:36.780127: +2024-11-23 00:25:36.780374: Epoch 6915 +2024-11-23 00:25:36.780489: Current learning rate: 0.00166 +2024-11-23 00:25:55.879623: train_loss -0.8102 +2024-11-23 00:25:55.879921: val_loss -0.7388 +2024-11-23 00:25:55.880009: Pseudo dice [0.8217] +2024-11-23 00:25:55.880091: Epoch time: 19.1 s +2024-11-23 00:25:56.800688: +2024-11-23 00:25:56.800891: Epoch 6916 +2024-11-23 00:25:56.801007: Current learning rate: 0.00165 +2024-11-23 00:26:15.573215: train_loss -0.8223 +2024-11-23 00:26:15.573489: val_loss -0.7718 +2024-11-23 00:26:15.587870: Pseudo dice [0.8432] +2024-11-23 00:26:15.588051: Epoch time: 18.77 s +2024-11-23 00:26:16.526680: +2024-11-23 00:26:16.527098: Epoch 6917 +2024-11-23 00:26:16.527209: Current learning rate: 0.00165 +2024-11-23 00:26:34.631322: train_loss -0.8183 +2024-11-23 00:26:34.631549: val_loss -0.7683 +2024-11-23 00:26:34.631626: Pseudo dice [0.8385] +2024-11-23 00:26:34.631708: Epoch time: 18.11 s +2024-11-23 00:26:35.657665: +2024-11-23 00:26:35.657976: Epoch 6918 +2024-11-23 00:26:35.658098: Current learning rate: 0.00165 +2024-11-23 00:26:54.270849: train_loss -0.8186 +2024-11-23 00:26:54.271087: val_loss -0.7798 +2024-11-23 00:26:54.271165: Pseudo dice [0.8307] +2024-11-23 00:26:54.271252: Epoch time: 18.61 s +2024-11-23 00:26:55.195596: +2024-11-23 00:26:55.195800: Epoch 6919 +2024-11-23 00:26:55.195914: Current learning rate: 0.00165 +2024-11-23 00:27:14.477232: train_loss -0.8138 +2024-11-23 00:27:14.477484: val_loss -0.7449 +2024-11-23 00:27:14.477559: Pseudo dice [0.8332] +2024-11-23 00:27:14.477644: Epoch time: 19.28 s +2024-11-23 00:27:15.524399: +2024-11-23 00:27:15.524605: Epoch 6920 +2024-11-23 00:27:15.524716: Current learning rate: 0.00165 +2024-11-23 00:27:34.047622: train_loss -0.8211 +2024-11-23 00:27:34.047835: val_loss -0.7558 +2024-11-23 00:27:34.047917: Pseudo dice [0.8504] +2024-11-23 00:27:34.048004: Epoch time: 18.52 s +2024-11-23 00:27:34.963607: +2024-11-23 00:27:34.963841: Epoch 6921 +2024-11-23 00:27:34.963956: Current learning rate: 0.00165 +2024-11-23 00:27:53.166253: train_loss -0.8167 +2024-11-23 00:27:53.170372: val_loss -0.7545 +2024-11-23 00:27:53.170488: Pseudo dice [0.8234] +2024-11-23 00:27:53.170570: Epoch time: 18.2 s +2024-11-23 00:27:54.095254: +2024-11-23 00:27:54.095515: Epoch 6922 +2024-11-23 00:27:54.095639: Current learning rate: 0.00165 +2024-11-23 00:28:12.696021: train_loss -0.8151 +2024-11-23 00:28:12.696234: val_loss -0.7365 +2024-11-23 00:28:12.696309: Pseudo dice [0.8249] +2024-11-23 00:28:12.696387: Epoch time: 18.6 s +2024-11-23 00:28:13.617083: +2024-11-23 00:28:13.617302: Epoch 6923 +2024-11-23 00:28:13.617447: Current learning rate: 0.00165 +2024-11-23 00:28:31.409466: train_loss -0.8168 +2024-11-23 00:28:31.409694: val_loss -0.7464 +2024-11-23 00:28:31.409829: Pseudo dice [0.8331] +2024-11-23 00:28:31.409909: Epoch time: 17.79 s +2024-11-23 00:28:32.436635: +2024-11-23 00:28:32.436961: Epoch 6924 +2024-11-23 00:28:32.437078: Current learning rate: 0.00164 +2024-11-23 00:28:51.396327: train_loss -0.817 +2024-11-23 00:28:51.396548: val_loss -0.7812 +2024-11-23 00:28:51.396624: Pseudo dice [0.8368] +2024-11-23 00:28:51.396697: Epoch time: 18.96 s +2024-11-23 00:28:52.387624: +2024-11-23 00:28:52.387841: Epoch 6925 +2024-11-23 00:28:52.387948: Current learning rate: 0.00164 +2024-11-23 00:29:09.987887: train_loss -0.8218 +2024-11-23 00:29:09.988102: val_loss -0.7381 +2024-11-23 00:29:09.988186: Pseudo dice [0.8213] +2024-11-23 00:29:09.988304: Epoch time: 17.6 s +2024-11-23 00:29:10.906818: +2024-11-23 00:29:10.907027: Epoch 6926 +2024-11-23 00:29:10.907138: Current learning rate: 0.00164 +2024-11-23 00:29:28.875676: train_loss -0.8154 +2024-11-23 00:29:28.875899: val_loss -0.7354 +2024-11-23 00:29:28.875979: Pseudo dice [0.8369] +2024-11-23 00:29:28.876064: Epoch time: 17.97 s +2024-11-23 00:29:29.794316: +2024-11-23 00:29:29.794511: Epoch 6927 +2024-11-23 00:29:29.794624: Current learning rate: 0.00164 +2024-11-23 00:29:48.947325: train_loss -0.8218 +2024-11-23 00:29:48.947572: val_loss -0.7681 +2024-11-23 00:29:48.947646: Pseudo dice [0.8355] +2024-11-23 00:29:48.947721: Epoch time: 19.15 s +2024-11-23 00:29:49.867213: +2024-11-23 00:29:49.867418: Epoch 6928 +2024-11-23 00:29:49.867526: Current learning rate: 0.00164 +2024-11-23 00:30:07.622480: train_loss -0.8135 +2024-11-23 00:30:07.622700: val_loss -0.7241 +2024-11-23 00:30:07.622844: Pseudo dice [0.8326] +2024-11-23 00:30:07.622926: Epoch time: 17.76 s +2024-11-23 00:30:08.540884: +2024-11-23 00:30:08.541103: Epoch 6929 +2024-11-23 00:30:08.541218: Current learning rate: 0.00164 +2024-11-23 00:30:27.216278: train_loss -0.8126 +2024-11-23 00:30:27.216511: val_loss -0.7649 +2024-11-23 00:30:27.216588: Pseudo dice [0.8482] +2024-11-23 00:30:27.216671: Epoch time: 18.68 s +2024-11-23 00:30:28.129665: +2024-11-23 00:30:28.129898: Epoch 6930 +2024-11-23 00:30:28.130021: Current learning rate: 0.00164 +2024-11-23 00:30:46.318525: train_loss -0.8247 +2024-11-23 00:30:46.318753: val_loss -0.7615 +2024-11-23 00:30:46.318831: Pseudo dice [0.8404] +2024-11-23 00:30:46.318913: Epoch time: 18.19 s +2024-11-23 00:30:47.249598: +2024-11-23 00:30:47.249815: Epoch 6931 +2024-11-23 00:30:47.249932: Current learning rate: 0.00163 +2024-11-23 00:31:06.733218: train_loss -0.8188 +2024-11-23 00:31:06.733485: val_loss -0.7625 +2024-11-23 00:31:06.733565: Pseudo dice [0.8322] +2024-11-23 00:31:06.733641: Epoch time: 19.48 s +2024-11-23 00:31:07.744207: +2024-11-23 00:31:07.744420: Epoch 6932 +2024-11-23 00:31:07.744532: Current learning rate: 0.00163 +2024-11-23 00:31:26.903481: train_loss -0.817 +2024-11-23 00:31:26.903700: val_loss -0.7556 +2024-11-23 00:31:26.903774: Pseudo dice [0.8464] +2024-11-23 00:31:26.903850: Epoch time: 19.16 s +2024-11-23 00:31:27.819644: +2024-11-23 00:31:27.819936: Epoch 6933 +2024-11-23 00:31:27.820053: Current learning rate: 0.00163 +2024-11-23 00:31:47.269459: train_loss -0.8223 +2024-11-23 00:31:47.269727: val_loss -0.7449 +2024-11-23 00:31:47.269822: Pseudo dice [0.8284] +2024-11-23 00:31:47.269943: Epoch time: 19.45 s +2024-11-23 00:31:48.191369: +2024-11-23 00:31:48.191563: Epoch 6934 +2024-11-23 00:31:48.191680: Current learning rate: 0.00163 +2024-11-23 00:32:06.921053: train_loss -0.8234 +2024-11-23 00:32:06.921357: val_loss -0.7629 +2024-11-23 00:32:06.921464: Pseudo dice [0.8319] +2024-11-23 00:32:06.921549: Epoch time: 18.73 s +2024-11-23 00:32:07.847817: +2024-11-23 00:32:07.848081: Epoch 6935 +2024-11-23 00:32:07.848195: Current learning rate: 0.00163 +2024-11-23 00:32:26.430490: train_loss -0.8146 +2024-11-23 00:32:26.430743: val_loss -0.7693 +2024-11-23 00:32:26.430834: Pseudo dice [0.824] +2024-11-23 00:32:26.430967: Epoch time: 18.58 s +2024-11-23 00:32:27.733238: +2024-11-23 00:32:27.733505: Epoch 6936 +2024-11-23 00:32:27.733617: Current learning rate: 0.00163 +2024-11-23 00:32:46.865420: train_loss -0.8238 +2024-11-23 00:32:46.865652: val_loss -0.7444 +2024-11-23 00:32:46.865729: Pseudo dice [0.8313] +2024-11-23 00:32:46.865804: Epoch time: 19.13 s +2024-11-23 00:32:47.788650: +2024-11-23 00:32:47.788945: Epoch 6937 +2024-11-23 00:32:47.789066: Current learning rate: 0.00163 +2024-11-23 00:33:05.864145: train_loss -0.8265 +2024-11-23 00:33:05.864389: val_loss -0.7565 +2024-11-23 00:33:05.864474: Pseudo dice [0.8229] +2024-11-23 00:33:05.864558: Epoch time: 18.08 s +2024-11-23 00:33:06.788817: +2024-11-23 00:33:06.789088: Epoch 6938 +2024-11-23 00:33:06.789199: Current learning rate: 0.00162 +2024-11-23 00:33:27.111810: train_loss -0.8251 +2024-11-23 00:33:27.112042: val_loss -0.7699 +2024-11-23 00:33:27.112118: Pseudo dice [0.8384] +2024-11-23 00:33:27.112219: Epoch time: 20.32 s +2024-11-23 00:33:28.141006: +2024-11-23 00:33:28.141203: Epoch 6939 +2024-11-23 00:33:28.141313: Current learning rate: 0.00162 +2024-11-23 00:33:47.070390: train_loss -0.8201 +2024-11-23 00:33:47.070611: val_loss -0.7699 +2024-11-23 00:33:47.070685: Pseudo dice [0.8376] +2024-11-23 00:33:47.070800: Epoch time: 18.93 s +2024-11-23 00:33:48.001567: +2024-11-23 00:33:48.001767: Epoch 6940 +2024-11-23 00:33:48.001878: Current learning rate: 0.00162 +2024-11-23 00:34:06.966943: train_loss -0.825 +2024-11-23 00:34:06.967178: val_loss -0.7364 +2024-11-23 00:34:06.967256: Pseudo dice [0.8253] +2024-11-23 00:34:06.969510: Epoch time: 18.97 s +2024-11-23 00:34:07.952131: +2024-11-23 00:34:07.952525: Epoch 6941 +2024-11-23 00:34:07.952643: Current learning rate: 0.00162 +2024-11-23 00:34:27.058516: train_loss -0.8105 +2024-11-23 00:34:27.063939: val_loss -0.7457 +2024-11-23 00:34:27.064067: Pseudo dice [0.8334] +2024-11-23 00:34:27.064161: Epoch time: 19.11 s +2024-11-23 00:34:28.206651: +2024-11-23 00:34:28.206854: Epoch 6942 +2024-11-23 00:34:28.206972: Current learning rate: 0.00162 +2024-11-23 00:34:46.052758: train_loss -0.8178 +2024-11-23 00:34:46.052981: val_loss -0.7568 +2024-11-23 00:34:46.053064: Pseudo dice [0.8439] +2024-11-23 00:34:46.053143: Epoch time: 17.85 s +2024-11-23 00:34:46.969256: +2024-11-23 00:34:46.969491: Epoch 6943 +2024-11-23 00:34:46.969612: Current learning rate: 0.00162 +2024-11-23 00:35:05.298762: train_loss -0.8225 +2024-11-23 00:35:05.298980: val_loss -0.7523 +2024-11-23 00:35:05.299062: Pseudo dice [0.8385] +2024-11-23 00:35:05.299137: Epoch time: 18.33 s +2024-11-23 00:35:06.226654: +2024-11-23 00:35:06.226850: Epoch 6944 +2024-11-23 00:35:06.226961: Current learning rate: 0.00162 +2024-11-23 00:35:24.926409: train_loss -0.8158 +2024-11-23 00:35:24.927237: val_loss -0.7425 +2024-11-23 00:35:24.927327: Pseudo dice [0.8364] +2024-11-23 00:35:24.927409: Epoch time: 18.7 s +2024-11-23 00:35:25.949943: +2024-11-23 00:35:25.950149: Epoch 6945 +2024-11-23 00:35:25.950263: Current learning rate: 0.00161 +2024-11-23 00:35:45.160840: train_loss -0.8182 +2024-11-23 00:35:45.163264: val_loss -0.7554 +2024-11-23 00:35:45.163414: Pseudo dice [0.8381] +2024-11-23 00:35:45.163512: Epoch time: 19.21 s +2024-11-23 00:35:46.104655: +2024-11-23 00:35:46.104879: Epoch 6946 +2024-11-23 00:35:46.105004: Current learning rate: 0.00161 +2024-11-23 00:36:04.148468: train_loss -0.8245 +2024-11-23 00:36:04.148696: val_loss -0.7438 +2024-11-23 00:36:04.148803: Pseudo dice [0.8354] +2024-11-23 00:36:04.148883: Epoch time: 18.04 s +2024-11-23 00:36:05.060057: +2024-11-23 00:36:05.060254: Epoch 6947 +2024-11-23 00:36:05.060363: Current learning rate: 0.00161 +2024-11-23 00:36:24.404324: train_loss -0.809 +2024-11-23 00:36:24.404556: val_loss -0.7474 +2024-11-23 00:36:24.404637: Pseudo dice [0.8183] +2024-11-23 00:36:24.409867: Epoch time: 19.35 s +2024-11-23 00:36:25.472699: +2024-11-23 00:36:25.472932: Epoch 6948 +2024-11-23 00:36:25.473044: Current learning rate: 0.00161 +2024-11-23 00:36:44.861176: train_loss -0.8058 +2024-11-23 00:36:44.861413: val_loss -0.7515 +2024-11-23 00:36:44.861487: Pseudo dice [0.859] +2024-11-23 00:36:44.861571: Epoch time: 19.39 s +2024-11-23 00:36:45.779653: +2024-11-23 00:36:45.779878: Epoch 6949 +2024-11-23 00:36:45.779999: Current learning rate: 0.00161 +2024-11-23 00:37:04.175005: train_loss -0.8191 +2024-11-23 00:37:04.175229: val_loss -0.7315 +2024-11-23 00:37:04.175303: Pseudo dice [0.8409] +2024-11-23 00:37:04.175380: Epoch time: 18.4 s +2024-11-23 00:37:05.422874: +2024-11-23 00:37:05.423093: Epoch 6950 +2024-11-23 00:37:05.423209: Current learning rate: 0.00161 +2024-11-23 00:37:24.232342: train_loss -0.8213 +2024-11-23 00:37:24.232566: val_loss -0.7414 +2024-11-23 00:37:24.232640: Pseudo dice [0.8314] +2024-11-23 00:37:24.232714: Epoch time: 18.81 s +2024-11-23 00:37:25.142410: +2024-11-23 00:37:25.142624: Epoch 6951 +2024-11-23 00:37:25.142736: Current learning rate: 0.00161 +2024-11-23 00:37:44.360981: train_loss -0.8186 +2024-11-23 00:37:44.366386: val_loss -0.7852 +2024-11-23 00:37:44.366470: Pseudo dice [0.848] +2024-11-23 00:37:44.366564: Epoch time: 19.22 s +2024-11-23 00:37:45.343914: +2024-11-23 00:37:45.344167: Epoch 6952 +2024-11-23 00:37:45.344281: Current learning rate: 0.00161 +2024-11-23 00:38:03.624359: train_loss -0.8191 +2024-11-23 00:38:03.624581: val_loss -0.7654 +2024-11-23 00:38:03.624656: Pseudo dice [0.8169] +2024-11-23 00:38:03.624732: Epoch time: 18.28 s +2024-11-23 00:38:04.650484: +2024-11-23 00:38:04.650698: Epoch 6953 +2024-11-23 00:38:04.650812: Current learning rate: 0.0016 +2024-11-23 00:38:25.067980: train_loss -0.8174 +2024-11-23 00:38:25.068214: val_loss -0.7498 +2024-11-23 00:38:25.068288: Pseudo dice [0.8453] +2024-11-23 00:38:25.073692: Epoch time: 20.42 s +2024-11-23 00:38:26.012290: +2024-11-23 00:38:26.012497: Epoch 6954 +2024-11-23 00:38:26.012610: Current learning rate: 0.0016 +2024-11-23 00:38:45.354156: train_loss -0.82 +2024-11-23 00:38:45.354394: val_loss -0.7423 +2024-11-23 00:38:45.356663: Pseudo dice [0.8442] +2024-11-23 00:38:45.356802: Epoch time: 19.34 s +2024-11-23 00:38:46.435986: +2024-11-23 00:38:46.436302: Epoch 6955 +2024-11-23 00:38:46.436432: Current learning rate: 0.0016 +2024-11-23 00:39:04.561844: train_loss -0.821 +2024-11-23 00:39:04.562083: val_loss -0.7608 +2024-11-23 00:39:04.562157: Pseudo dice [0.8402] +2024-11-23 00:39:04.562235: Epoch time: 18.13 s +2024-11-23 00:39:05.510105: +2024-11-23 00:39:05.510321: Epoch 6956 +2024-11-23 00:39:05.510438: Current learning rate: 0.0016 +2024-11-23 00:39:24.319589: train_loss -0.8197 +2024-11-23 00:39:24.319817: val_loss -0.7641 +2024-11-23 00:39:24.319894: Pseudo dice [0.844] +2024-11-23 00:39:24.319970: Epoch time: 18.81 s +2024-11-23 00:39:25.236299: +2024-11-23 00:39:25.236527: Epoch 6957 +2024-11-23 00:39:25.236645: Current learning rate: 0.0016 +2024-11-23 00:39:43.825621: train_loss -0.8181 +2024-11-23 00:39:43.828004: val_loss -0.7762 +2024-11-23 00:39:43.828120: Pseudo dice [0.8415] +2024-11-23 00:39:43.828195: Epoch time: 18.59 s +2024-11-23 00:39:44.779799: +2024-11-23 00:39:44.780014: Epoch 6958 +2024-11-23 00:39:44.780128: Current learning rate: 0.0016 +2024-11-23 00:40:02.711572: train_loss -0.8113 +2024-11-23 00:40:02.711814: val_loss -0.7509 +2024-11-23 00:40:02.711891: Pseudo dice [0.8403] +2024-11-23 00:40:02.711980: Epoch time: 17.93 s +2024-11-23 00:40:04.035383: +2024-11-23 00:40:04.035580: Epoch 6959 +2024-11-23 00:40:04.035694: Current learning rate: 0.0016 +2024-11-23 00:40:22.072592: train_loss -0.8175 +2024-11-23 00:40:22.072813: val_loss -0.7565 +2024-11-23 00:40:22.072889: Pseudo dice [0.8384] +2024-11-23 00:40:22.072984: Epoch time: 18.04 s +2024-11-23 00:40:23.008639: +2024-11-23 00:40:23.008854: Epoch 6960 +2024-11-23 00:40:23.008967: Current learning rate: 0.00159 +2024-11-23 00:40:42.125162: train_loss -0.8214 +2024-11-23 00:40:42.125452: val_loss -0.7629 +2024-11-23 00:40:42.125532: Pseudo dice [0.8294] +2024-11-23 00:40:42.125610: Epoch time: 19.12 s +2024-11-23 00:40:43.041076: +2024-11-23 00:40:43.041295: Epoch 6961 +2024-11-23 00:40:43.041403: Current learning rate: 0.00159 +2024-11-23 00:41:02.367628: train_loss -0.816 +2024-11-23 00:41:02.367866: val_loss -0.7598 +2024-11-23 00:41:02.367943: Pseudo dice [0.8553] +2024-11-23 00:41:02.368031: Epoch time: 19.33 s +2024-11-23 00:41:03.366776: +2024-11-23 00:41:03.367029: Epoch 6962 +2024-11-23 00:41:03.367148: Current learning rate: 0.00159 +2024-11-23 00:41:21.902881: train_loss -0.8118 +2024-11-23 00:41:21.903110: val_loss -0.7545 +2024-11-23 00:41:21.903185: Pseudo dice [0.8387] +2024-11-23 00:41:21.903261: Epoch time: 18.54 s +2024-11-23 00:41:22.822418: +2024-11-23 00:41:22.822624: Epoch 6963 +2024-11-23 00:41:22.822741: Current learning rate: 0.00159 +2024-11-23 00:41:40.955704: train_loss -0.8198 +2024-11-23 00:41:40.958080: val_loss -0.7579 +2024-11-23 00:41:40.958166: Pseudo dice [0.8314] +2024-11-23 00:41:40.958245: Epoch time: 18.13 s +2024-11-23 00:41:42.013447: +2024-11-23 00:41:42.013656: Epoch 6964 +2024-11-23 00:41:42.013771: Current learning rate: 0.00159 +2024-11-23 00:42:00.752924: train_loss -0.8155 +2024-11-23 00:42:00.753157: val_loss -0.7531 +2024-11-23 00:42:00.753237: Pseudo dice [0.8334] +2024-11-23 00:42:00.753312: Epoch time: 18.74 s +2024-11-23 00:42:01.774968: +2024-11-23 00:42:01.775168: Epoch 6965 +2024-11-23 00:42:01.775274: Current learning rate: 0.00159 +2024-11-23 00:42:19.755375: train_loss -0.8288 +2024-11-23 00:42:19.755617: val_loss -0.7735 +2024-11-23 00:42:19.755702: Pseudo dice [0.8493] +2024-11-23 00:42:19.755785: Epoch time: 17.98 s +2024-11-23 00:42:20.660333: +2024-11-23 00:42:20.660526: Epoch 6966 +2024-11-23 00:42:20.660641: Current learning rate: 0.00159 +2024-11-23 00:42:41.061180: train_loss -0.8279 +2024-11-23 00:42:41.061397: val_loss -0.7588 +2024-11-23 00:42:41.061476: Pseudo dice [0.8379] +2024-11-23 00:42:41.061550: Epoch time: 20.4 s +2024-11-23 00:42:41.978233: +2024-11-23 00:42:41.978500: Epoch 6967 +2024-11-23 00:42:41.978619: Current learning rate: 0.00158 +2024-11-23 00:43:01.249963: train_loss -0.8257 +2024-11-23 00:43:01.250199: val_loss -0.7454 +2024-11-23 00:43:01.250276: Pseudo dice [0.8328] +2024-11-23 00:43:01.250352: Epoch time: 19.27 s +2024-11-23 00:43:02.166956: +2024-11-23 00:43:02.167170: Epoch 6968 +2024-11-23 00:43:02.167286: Current learning rate: 0.00158 +2024-11-23 00:43:20.578803: train_loss -0.825 +2024-11-23 00:43:20.579041: val_loss -0.7532 +2024-11-23 00:43:20.579123: Pseudo dice [0.8362] +2024-11-23 00:43:20.579207: Epoch time: 18.41 s +2024-11-23 00:43:21.495500: +2024-11-23 00:43:21.495722: Epoch 6969 +2024-11-23 00:43:21.495844: Current learning rate: 0.00158 +2024-11-23 00:43:40.522003: train_loss -0.8231 +2024-11-23 00:43:40.522287: val_loss -0.759 +2024-11-23 00:43:40.522366: Pseudo dice [0.8344] +2024-11-23 00:43:40.522449: Epoch time: 19.03 s +2024-11-23 00:43:41.782611: +2024-11-23 00:43:41.782819: Epoch 6970 +2024-11-23 00:43:41.782930: Current learning rate: 0.00158 +2024-11-23 00:44:00.584797: train_loss -0.8179 +2024-11-23 00:44:00.587200: val_loss -0.768 +2024-11-23 00:44:00.587296: Pseudo dice [0.8446] +2024-11-23 00:44:00.587377: Epoch time: 18.8 s +2024-11-23 00:44:01.564144: +2024-11-23 00:44:01.564346: Epoch 6971 +2024-11-23 00:44:01.564458: Current learning rate: 0.00158 +2024-11-23 00:44:19.435039: train_loss -0.8254 +2024-11-23 00:44:19.435269: val_loss -0.7673 +2024-11-23 00:44:19.435346: Pseudo dice [0.8277] +2024-11-23 00:44:19.435425: Epoch time: 17.87 s +2024-11-23 00:44:20.363883: +2024-11-23 00:44:20.364110: Epoch 6972 +2024-11-23 00:44:20.364218: Current learning rate: 0.00158 +2024-11-23 00:44:39.644782: train_loss -0.8103 +2024-11-23 00:44:39.645003: val_loss -0.7606 +2024-11-23 00:44:39.645078: Pseudo dice [0.8476] +2024-11-23 00:44:39.645160: Epoch time: 19.28 s +2024-11-23 00:44:40.620135: +2024-11-23 00:44:40.620366: Epoch 6973 +2024-11-23 00:44:40.620494: Current learning rate: 0.00158 +2024-11-23 00:44:58.827228: train_loss -0.8188 +2024-11-23 00:44:58.827454: val_loss -0.7531 +2024-11-23 00:44:58.827533: Pseudo dice [0.8344] +2024-11-23 00:44:58.827612: Epoch time: 18.21 s +2024-11-23 00:44:59.792275: +2024-11-23 00:44:59.792499: Epoch 6974 +2024-11-23 00:44:59.792611: Current learning rate: 0.00157 +2024-11-23 00:45:19.347624: train_loss -0.8134 +2024-11-23 00:45:19.347863: val_loss -0.7788 +2024-11-23 00:45:19.347941: Pseudo dice [0.8432] +2024-11-23 00:45:19.348024: Epoch time: 19.56 s +2024-11-23 00:45:20.357533: +2024-11-23 00:45:20.357755: Epoch 6975 +2024-11-23 00:45:20.357869: Current learning rate: 0.00157 +2024-11-23 00:45:39.163547: train_loss -0.8175 +2024-11-23 00:45:39.163762: val_loss -0.76 +2024-11-23 00:45:39.163837: Pseudo dice [0.8298] +2024-11-23 00:45:39.163914: Epoch time: 18.81 s +2024-11-23 00:45:40.089572: +2024-11-23 00:45:40.089791: Epoch 6976 +2024-11-23 00:45:40.089904: Current learning rate: 0.00157 +2024-11-23 00:45:59.093688: train_loss -0.8197 +2024-11-23 00:45:59.093909: val_loss -0.7458 +2024-11-23 00:45:59.093979: Pseudo dice [0.8337] +2024-11-23 00:45:59.094067: Epoch time: 19.0 s +2024-11-23 00:46:00.106392: +2024-11-23 00:46:00.106649: Epoch 6977 +2024-11-23 00:46:00.106766: Current learning rate: 0.00157 +2024-11-23 00:46:19.603550: train_loss -0.8192 +2024-11-23 00:46:19.603820: val_loss -0.7306 +2024-11-23 00:46:19.603895: Pseudo dice [0.8321] +2024-11-23 00:46:19.603969: Epoch time: 19.5 s +2024-11-23 00:46:20.523768: +2024-11-23 00:46:20.523984: Epoch 6978 +2024-11-23 00:46:20.524105: Current learning rate: 0.00157 +2024-11-23 00:46:39.847336: train_loss -0.8213 +2024-11-23 00:46:39.847561: val_loss -0.764 +2024-11-23 00:46:39.847637: Pseudo dice [0.8382] +2024-11-23 00:46:39.847715: Epoch time: 19.32 s +2024-11-23 00:46:40.756610: +2024-11-23 00:46:40.756819: Epoch 6979 +2024-11-23 00:46:40.756928: Current learning rate: 0.00157 +2024-11-23 00:47:00.144234: train_loss -0.8223 +2024-11-23 00:47:00.144464: val_loss -0.7497 +2024-11-23 00:47:00.144539: Pseudo dice [0.8345] +2024-11-23 00:47:00.144771: Epoch time: 19.39 s +2024-11-23 00:47:01.109305: +2024-11-23 00:47:01.136642: Epoch 6980 +2024-11-23 00:47:01.136781: Current learning rate: 0.00157 +2024-11-23 00:47:21.072199: train_loss -0.8132 +2024-11-23 00:47:21.072466: val_loss -0.7536 +2024-11-23 00:47:21.072540: Pseudo dice [0.8232] +2024-11-23 00:47:21.072623: Epoch time: 19.96 s +2024-11-23 00:47:22.026218: +2024-11-23 00:47:22.026425: Epoch 6981 +2024-11-23 00:47:22.026539: Current learning rate: 0.00157 +2024-11-23 00:47:40.355685: train_loss -0.8247 +2024-11-23 00:47:40.355910: val_loss -0.7688 +2024-11-23 00:47:40.355984: Pseudo dice [0.8328] +2024-11-23 00:47:40.356068: Epoch time: 18.33 s +2024-11-23 00:47:41.691693: +2024-11-23 00:47:41.691902: Epoch 6982 +2024-11-23 00:47:41.692016: Current learning rate: 0.00156 +2024-11-23 00:48:00.388461: train_loss -0.8241 +2024-11-23 00:48:00.388698: val_loss -0.7631 +2024-11-23 00:48:00.388773: Pseudo dice [0.8396] +2024-11-23 00:48:00.388853: Epoch time: 18.7 s +2024-11-23 00:48:01.308117: +2024-11-23 00:48:01.308353: Epoch 6983 +2024-11-23 00:48:01.308480: Current learning rate: 0.00156 +2024-11-23 00:48:20.259796: train_loss -0.8221 +2024-11-23 00:48:20.260059: val_loss -0.7552 +2024-11-23 00:48:20.260137: Pseudo dice [0.8334] +2024-11-23 00:48:20.260220: Epoch time: 18.95 s +2024-11-23 00:48:21.218421: +2024-11-23 00:48:21.218636: Epoch 6984 +2024-11-23 00:48:21.218746: Current learning rate: 0.00156 +2024-11-23 00:48:40.262273: train_loss -0.8234 +2024-11-23 00:48:40.262495: val_loss -0.7501 +2024-11-23 00:48:40.262571: Pseudo dice [0.8229] +2024-11-23 00:48:40.262652: Epoch time: 19.04 s +2024-11-23 00:48:41.196606: +2024-11-23 00:48:41.196808: Epoch 6985 +2024-11-23 00:48:41.196918: Current learning rate: 0.00156 +2024-11-23 00:48:58.961685: train_loss -0.8162 +2024-11-23 00:48:58.961943: val_loss -0.7756 +2024-11-23 00:48:58.962023: Pseudo dice [0.853] +2024-11-23 00:48:58.962098: Epoch time: 17.77 s +2024-11-23 00:48:59.879039: +2024-11-23 00:48:59.879332: Epoch 6986 +2024-11-23 00:48:59.879445: Current learning rate: 0.00156 +2024-11-23 00:49:19.012760: train_loss -0.8248 +2024-11-23 00:49:19.012976: val_loss -0.7589 +2024-11-23 00:49:19.013083: Pseudo dice [0.8386] +2024-11-23 00:49:19.013198: Epoch time: 19.13 s +2024-11-23 00:49:19.986232: +2024-11-23 00:49:19.986427: Epoch 6987 +2024-11-23 00:49:19.986541: Current learning rate: 0.00156 +2024-11-23 00:49:38.684804: train_loss -0.8248 +2024-11-23 00:49:38.685050: val_loss -0.754 +2024-11-23 00:49:38.685129: Pseudo dice [0.8393] +2024-11-23 00:49:38.685214: Epoch time: 18.7 s +2024-11-23 00:49:39.641276: +2024-11-23 00:49:39.641477: Epoch 6988 +2024-11-23 00:49:39.641590: Current learning rate: 0.00156 +2024-11-23 00:49:58.207053: train_loss -0.823 +2024-11-23 00:49:58.207271: val_loss -0.7866 +2024-11-23 00:49:58.207353: Pseudo dice [0.8549] +2024-11-23 00:49:58.207434: Epoch time: 18.57 s +2024-11-23 00:49:59.124870: +2024-11-23 00:49:59.125101: Epoch 6989 +2024-11-23 00:49:59.125213: Current learning rate: 0.00155 +2024-11-23 00:50:17.934923: train_loss -0.8253 +2024-11-23 00:50:17.935146: val_loss -0.7429 +2024-11-23 00:50:17.935218: Pseudo dice [0.8463] +2024-11-23 00:50:17.935293: Epoch time: 18.81 s +2024-11-23 00:50:18.885300: +2024-11-23 00:50:18.885502: Epoch 6990 +2024-11-23 00:50:18.885615: Current learning rate: 0.00155 +2024-11-23 00:50:37.593901: train_loss -0.825 +2024-11-23 00:50:37.594164: val_loss -0.759 +2024-11-23 00:50:37.594245: Pseudo dice [0.8408] +2024-11-23 00:50:37.594324: Epoch time: 18.71 s +2024-11-23 00:50:38.512873: +2024-11-23 00:50:38.513099: Epoch 6991 +2024-11-23 00:50:38.513210: Current learning rate: 0.00155 +2024-11-23 00:50:56.375777: train_loss -0.8264 +2024-11-23 00:50:56.376057: val_loss -0.768 +2024-11-23 00:50:56.376135: Pseudo dice [0.8433] +2024-11-23 00:50:56.376220: Epoch time: 17.86 s +2024-11-23 00:50:57.304879: +2024-11-23 00:50:57.305105: Epoch 6992 +2024-11-23 00:50:57.305224: Current learning rate: 0.00155 +2024-11-23 00:51:14.964201: train_loss -0.8248 +2024-11-23 00:51:14.964421: val_loss -0.7565 +2024-11-23 00:51:14.964497: Pseudo dice [0.8155] +2024-11-23 00:51:14.964574: Epoch time: 17.66 s +2024-11-23 00:51:15.921731: +2024-11-23 00:51:15.921934: Epoch 6993 +2024-11-23 00:51:15.922047: Current learning rate: 0.00155 +2024-11-23 00:51:34.492442: train_loss -0.8255 +2024-11-23 00:51:34.492917: val_loss -0.7816 +2024-11-23 00:51:34.493025: Pseudo dice [0.8492] +2024-11-23 00:51:34.493110: Epoch time: 18.57 s +2024-11-23 00:51:35.441590: +2024-11-23 00:51:35.441801: Epoch 6994 +2024-11-23 00:51:35.441913: Current learning rate: 0.00155 +2024-11-23 00:51:54.599590: train_loss -0.8222 +2024-11-23 00:51:54.600233: val_loss -0.7685 +2024-11-23 00:51:54.600336: Pseudo dice [0.8491] +2024-11-23 00:51:54.600427: Epoch time: 19.16 s +2024-11-23 00:51:55.514864: +2024-11-23 00:51:55.515100: Epoch 6995 +2024-11-23 00:51:55.515221: Current learning rate: 0.00155 +2024-11-23 00:52:15.313672: train_loss -0.8096 +2024-11-23 00:52:15.319062: val_loss -0.7558 +2024-11-23 00:52:15.319180: Pseudo dice [0.8431] +2024-11-23 00:52:15.319257: Epoch time: 19.8 s +2024-11-23 00:52:16.240335: +2024-11-23 00:52:16.240571: Epoch 6996 +2024-11-23 00:52:16.240686: Current learning rate: 0.00154 +2024-11-23 00:52:34.630603: train_loss -0.8258 +2024-11-23 00:52:34.630836: val_loss -0.7785 +2024-11-23 00:52:34.630913: Pseudo dice [0.8464] +2024-11-23 00:52:34.631000: Epoch time: 18.39 s +2024-11-23 00:52:35.547656: +2024-11-23 00:52:35.547883: Epoch 6997 +2024-11-23 00:52:35.547998: Current learning rate: 0.00154 +2024-11-23 00:52:54.327358: train_loss -0.8183 +2024-11-23 00:52:54.327593: val_loss -0.7521 +2024-11-23 00:52:54.327669: Pseudo dice [0.8194] +2024-11-23 00:52:54.327755: Epoch time: 18.78 s +2024-11-23 00:52:55.353715: +2024-11-23 00:52:55.353945: Epoch 6998 +2024-11-23 00:52:55.354080: Current learning rate: 0.00154 +2024-11-23 00:53:13.543483: train_loss -0.8141 +2024-11-23 00:53:13.543695: val_loss -0.7642 +2024-11-23 00:53:13.543772: Pseudo dice [0.8463] +2024-11-23 00:53:13.543848: Epoch time: 18.19 s +2024-11-23 00:53:14.563169: +2024-11-23 00:53:14.563421: Epoch 6999 +2024-11-23 00:53:14.563534: Current learning rate: 0.00154 +2024-11-23 00:53:33.753206: train_loss -0.8172 +2024-11-23 00:53:33.753428: val_loss -0.7431 +2024-11-23 00:53:33.753538: Pseudo dice [0.8297] +2024-11-23 00:53:33.753615: Epoch time: 19.19 s +2024-11-23 00:53:35.015902: +2024-11-23 00:53:35.016111: Epoch 7000 +2024-11-23 00:53:35.016227: Current learning rate: 0.00154 +2024-11-23 00:53:52.613270: train_loss -0.8212 +2024-11-23 00:53:52.613496: val_loss -0.7693 +2024-11-23 00:53:52.613572: Pseudo dice [0.8527] +2024-11-23 00:53:52.613650: Epoch time: 17.6 s +2024-11-23 00:53:53.635803: +2024-11-23 00:53:53.636028: Epoch 7001 +2024-11-23 00:53:53.636145: Current learning rate: 0.00154 +2024-11-23 00:54:13.270609: train_loss -0.8201 +2024-11-23 00:54:13.270858: val_loss -0.7575 +2024-11-23 00:54:13.270944: Pseudo dice [0.8267] +2024-11-23 00:54:13.271071: Epoch time: 19.64 s +2024-11-23 00:54:14.197786: +2024-11-23 00:54:14.198120: Epoch 7002 +2024-11-23 00:54:14.198232: Current learning rate: 0.00154 +2024-11-23 00:54:32.178131: train_loss -0.8231 +2024-11-23 00:54:32.178351: val_loss -0.7687 +2024-11-23 00:54:32.178426: Pseudo dice [0.8375] +2024-11-23 00:54:32.178502: Epoch time: 17.98 s +2024-11-23 00:54:33.139018: +2024-11-23 00:54:33.139248: Epoch 7003 +2024-11-23 00:54:33.139366: Current learning rate: 0.00153 +2024-11-23 00:54:51.782363: train_loss -0.8241 +2024-11-23 00:54:51.782576: val_loss -0.7447 +2024-11-23 00:54:51.782648: Pseudo dice [0.8369] +2024-11-23 00:54:51.782723: Epoch time: 18.64 s +2024-11-23 00:54:52.696267: +2024-11-23 00:54:52.696464: Epoch 7004 +2024-11-23 00:54:52.696575: Current learning rate: 0.00153 +2024-11-23 00:55:11.300585: train_loss -0.8272 +2024-11-23 00:55:11.300798: val_loss -0.7556 +2024-11-23 00:55:11.300871: Pseudo dice [0.8363] +2024-11-23 00:55:11.300949: Epoch time: 18.61 s +2024-11-23 00:55:12.585902: +2024-11-23 00:55:12.586125: Epoch 7005 +2024-11-23 00:55:12.586240: Current learning rate: 0.00153 +2024-11-23 00:55:30.841046: train_loss -0.8241 +2024-11-23 00:55:30.841278: val_loss -0.7834 +2024-11-23 00:55:30.842141: Pseudo dice [0.8474] +2024-11-23 00:55:30.842279: Epoch time: 18.26 s +2024-11-23 00:55:31.763448: +2024-11-23 00:55:31.763693: Epoch 7006 +2024-11-23 00:55:31.763805: Current learning rate: 0.00153 +2024-11-23 00:55:50.458229: train_loss -0.8211 +2024-11-23 00:55:50.458449: val_loss -0.7405 +2024-11-23 00:55:50.458523: Pseudo dice [0.8322] +2024-11-23 00:55:50.458602: Epoch time: 18.7 s +2024-11-23 00:55:51.414739: +2024-11-23 00:55:51.415009: Epoch 7007 +2024-11-23 00:55:51.415123: Current learning rate: 0.00153 +2024-11-23 00:56:10.870469: train_loss -0.8208 +2024-11-23 00:56:10.881482: val_loss -0.7663 +2024-11-23 00:56:10.881630: Pseudo dice [0.833] +2024-11-23 00:56:10.881713: Epoch time: 19.46 s +2024-11-23 00:56:11.803344: +2024-11-23 00:56:11.803568: Epoch 7008 +2024-11-23 00:56:11.803680: Current learning rate: 0.00153 +2024-11-23 00:56:30.939345: train_loss -0.827 +2024-11-23 00:56:30.939578: val_loss -0.7383 +2024-11-23 00:56:30.939651: Pseudo dice [0.8311] +2024-11-23 00:56:30.939738: Epoch time: 19.14 s +2024-11-23 00:56:31.858408: +2024-11-23 00:56:31.858632: Epoch 7009 +2024-11-23 00:56:31.858747: Current learning rate: 0.00153 +2024-11-23 00:56:50.947289: train_loss -0.8272 +2024-11-23 00:56:50.947512: val_loss -0.7538 +2024-11-23 00:56:50.947587: Pseudo dice [0.8461] +2024-11-23 00:56:50.947666: Epoch time: 19.09 s +2024-11-23 00:56:51.998042: +2024-11-23 00:56:51.998257: Epoch 7010 +2024-11-23 00:56:51.998374: Current learning rate: 0.00153 +2024-11-23 00:57:10.225333: train_loss -0.8143 +2024-11-23 00:57:10.225560: val_loss -0.7568 +2024-11-23 00:57:10.225633: Pseudo dice [0.8315] +2024-11-23 00:57:10.225713: Epoch time: 18.23 s +2024-11-23 00:57:11.192892: +2024-11-23 00:57:11.193114: Epoch 7011 +2024-11-23 00:57:11.193226: Current learning rate: 0.00152 +2024-11-23 00:57:29.656217: train_loss -0.8237 +2024-11-23 00:57:29.656444: val_loss -0.7501 +2024-11-23 00:57:29.656522: Pseudo dice [0.8394] +2024-11-23 00:57:29.656604: Epoch time: 18.46 s +2024-11-23 00:57:30.650721: +2024-11-23 00:57:30.650983: Epoch 7012 +2024-11-23 00:57:30.651098: Current learning rate: 0.00152 +2024-11-23 00:57:48.027752: train_loss -0.8195 +2024-11-23 00:57:48.027978: val_loss -0.7573 +2024-11-23 00:57:48.028063: Pseudo dice [0.8265] +2024-11-23 00:57:48.028145: Epoch time: 17.38 s +2024-11-23 00:57:48.940358: +2024-11-23 00:57:48.940613: Epoch 7013 +2024-11-23 00:57:48.940731: Current learning rate: 0.00152 +2024-11-23 00:58:07.114532: train_loss -0.8199 +2024-11-23 00:58:07.114760: val_loss -0.7693 +2024-11-23 00:58:07.114839: Pseudo dice [0.8473] +2024-11-23 00:58:07.114920: Epoch time: 18.17 s +2024-11-23 00:58:08.031635: +2024-11-23 00:58:08.031859: Epoch 7014 +2024-11-23 00:58:08.031974: Current learning rate: 0.00152 +2024-11-23 00:58:26.037633: train_loss -0.8251 +2024-11-23 00:58:26.037854: val_loss -0.7375 +2024-11-23 00:58:26.037931: Pseudo dice [0.8329] +2024-11-23 00:58:26.038014: Epoch time: 18.01 s +2024-11-23 00:58:26.945197: +2024-11-23 00:58:26.945407: Epoch 7015 +2024-11-23 00:58:26.945528: Current learning rate: 0.00152 +2024-11-23 00:58:45.726231: train_loss -0.8189 +2024-11-23 00:58:45.726475: val_loss -0.7616 +2024-11-23 00:58:45.726553: Pseudo dice [0.8541] +2024-11-23 00:58:45.726647: Epoch time: 18.78 s +2024-11-23 00:58:46.637541: +2024-11-23 00:58:46.637813: Epoch 7016 +2024-11-23 00:58:46.637928: Current learning rate: 0.00152 +2024-11-23 00:59:05.197324: train_loss -0.8208 +2024-11-23 00:59:05.197848: val_loss -0.751 +2024-11-23 00:59:05.197957: Pseudo dice [0.8532] +2024-11-23 00:59:05.198062: Epoch time: 18.56 s +2024-11-23 00:59:06.138533: +2024-11-23 00:59:06.138763: Epoch 7017 +2024-11-23 00:59:06.138880: Current learning rate: 0.00152 +2024-11-23 00:59:23.395394: train_loss -0.8263 +2024-11-23 00:59:23.395619: val_loss -0.7622 +2024-11-23 00:59:23.395694: Pseudo dice [0.8328] +2024-11-23 00:59:23.395772: Epoch time: 17.26 s +2024-11-23 00:59:24.309863: +2024-11-23 00:59:24.310099: Epoch 7018 +2024-11-23 00:59:24.310214: Current learning rate: 0.00151 +2024-11-23 00:59:43.967423: train_loss -0.8209 +2024-11-23 00:59:43.967658: val_loss -0.7641 +2024-11-23 00:59:43.967732: Pseudo dice [0.822] +2024-11-23 00:59:43.967816: Epoch time: 19.66 s +2024-11-23 00:59:44.903449: +2024-11-23 00:59:44.903652: Epoch 7019 +2024-11-23 00:59:44.903765: Current learning rate: 0.00151 +2024-11-23 01:00:03.365759: train_loss -0.8209 +2024-11-23 01:00:03.365983: val_loss -0.7647 +2024-11-23 01:00:03.366066: Pseudo dice [0.8326] +2024-11-23 01:00:03.371281: Epoch time: 18.46 s +2024-11-23 01:00:04.403323: +2024-11-23 01:00:04.403528: Epoch 7020 +2024-11-23 01:00:04.403638: Current learning rate: 0.00151 +2024-11-23 01:00:23.711142: train_loss -0.825 +2024-11-23 01:00:23.711355: val_loss -0.7484 +2024-11-23 01:00:23.711428: Pseudo dice [0.8444] +2024-11-23 01:00:23.711502: Epoch time: 19.31 s +2024-11-23 01:00:24.758528: +2024-11-23 01:00:24.758731: Epoch 7021 +2024-11-23 01:00:24.758851: Current learning rate: 0.00151 +2024-11-23 01:00:44.631864: train_loss -0.8107 +2024-11-23 01:00:44.632150: val_loss -0.758 +2024-11-23 01:00:44.632234: Pseudo dice [0.8161] +2024-11-23 01:00:44.632313: Epoch time: 19.87 s +2024-11-23 01:00:45.553171: +2024-11-23 01:00:45.553368: Epoch 7022 +2024-11-23 01:00:45.553478: Current learning rate: 0.00151 +2024-11-23 01:01:03.853687: train_loss -0.8075 +2024-11-23 01:01:03.853919: val_loss -0.7592 +2024-11-23 01:01:03.854001: Pseudo dice [0.8343] +2024-11-23 01:01:03.854082: Epoch time: 18.3 s +2024-11-23 01:01:04.787251: +2024-11-23 01:01:04.787460: Epoch 7023 +2024-11-23 01:01:04.787574: Current learning rate: 0.00151 +2024-11-23 01:01:23.122264: train_loss -0.8157 +2024-11-23 01:01:23.122498: val_loss -0.7573 +2024-11-23 01:01:23.122575: Pseudo dice [0.8174] +2024-11-23 01:01:23.122654: Epoch time: 18.34 s +2024-11-23 01:01:24.034309: +2024-11-23 01:01:24.034505: Epoch 7024 +2024-11-23 01:01:24.034616: Current learning rate: 0.00151 +2024-11-23 01:01:41.055975: train_loss -0.8254 +2024-11-23 01:01:41.056209: val_loss -0.7617 +2024-11-23 01:01:41.056286: Pseudo dice [0.8315] +2024-11-23 01:01:41.056362: Epoch time: 17.02 s +2024-11-23 01:01:41.964034: +2024-11-23 01:01:41.964232: Epoch 7025 +2024-11-23 01:01:41.964343: Current learning rate: 0.0015 +2024-11-23 01:02:00.827049: train_loss -0.8252 +2024-11-23 01:02:00.827268: val_loss -0.7781 +2024-11-23 01:02:00.827351: Pseudo dice [0.8489] +2024-11-23 01:02:00.827426: Epoch time: 18.86 s +2024-11-23 01:02:01.752463: +2024-11-23 01:02:01.752675: Epoch 7026 +2024-11-23 01:02:01.752787: Current learning rate: 0.0015 +2024-11-23 01:02:19.890031: train_loss -0.8229 +2024-11-23 01:02:19.890270: val_loss -0.7796 +2024-11-23 01:02:19.890346: Pseudo dice [0.8492] +2024-11-23 01:02:19.890426: Epoch time: 18.14 s +2024-11-23 01:02:20.806209: +2024-11-23 01:02:20.806412: Epoch 7027 +2024-11-23 01:02:20.806522: Current learning rate: 0.0015 +2024-11-23 01:02:39.332090: train_loss -0.8296 +2024-11-23 01:02:39.332341: val_loss -0.7577 +2024-11-23 01:02:39.332446: Pseudo dice [0.8361] +2024-11-23 01:02:39.332522: Epoch time: 18.53 s +2024-11-23 01:02:40.682899: +2024-11-23 01:02:40.683144: Epoch 7028 +2024-11-23 01:02:40.683262: Current learning rate: 0.0015 +2024-11-23 01:02:57.700438: train_loss -0.8219 +2024-11-23 01:02:57.700661: val_loss -0.7459 +2024-11-23 01:02:57.700735: Pseudo dice [0.841] +2024-11-23 01:02:57.700858: Epoch time: 17.02 s +2024-11-23 01:02:58.612549: +2024-11-23 01:02:58.612746: Epoch 7029 +2024-11-23 01:02:58.612857: Current learning rate: 0.0015 +2024-11-23 01:03:16.920955: train_loss -0.8171 +2024-11-23 01:03:16.921202: val_loss -0.7448 +2024-11-23 01:03:16.921280: Pseudo dice [0.8263] +2024-11-23 01:03:16.921363: Epoch time: 18.31 s +2024-11-23 01:03:17.843973: +2024-11-23 01:03:17.844189: Epoch 7030 +2024-11-23 01:03:17.844302: Current learning rate: 0.0015 +2024-11-23 01:03:36.897379: train_loss -0.8188 +2024-11-23 01:03:36.897594: val_loss -0.777 +2024-11-23 01:03:36.897669: Pseudo dice [0.8497] +2024-11-23 01:03:36.897744: Epoch time: 19.05 s +2024-11-23 01:03:37.820978: +2024-11-23 01:03:37.821206: Epoch 7031 +2024-11-23 01:03:37.821320: Current learning rate: 0.0015 +2024-11-23 01:03:56.394547: train_loss -0.8113 +2024-11-23 01:03:56.394770: val_loss -0.7638 +2024-11-23 01:03:56.394981: Pseudo dice [0.8376] +2024-11-23 01:03:56.395072: Epoch time: 18.57 s +2024-11-23 01:03:57.311538: +2024-11-23 01:03:57.311789: Epoch 7032 +2024-11-23 01:03:57.311908: Current learning rate: 0.00149 +2024-11-23 01:04:15.950529: train_loss -0.8185 +2024-11-23 01:04:15.950751: val_loss -0.7673 +2024-11-23 01:04:15.950825: Pseudo dice [0.818] +2024-11-23 01:04:15.950902: Epoch time: 18.64 s +2024-11-23 01:04:16.872920: +2024-11-23 01:04:16.873125: Epoch 7033 +2024-11-23 01:04:16.873243: Current learning rate: 0.00149 +2024-11-23 01:04:35.440769: train_loss -0.8162 +2024-11-23 01:04:35.441021: val_loss -0.7691 +2024-11-23 01:04:35.441097: Pseudo dice [0.8407] +2024-11-23 01:04:35.441182: Epoch time: 18.57 s +2024-11-23 01:04:36.452059: +2024-11-23 01:04:36.452333: Epoch 7034 +2024-11-23 01:04:36.452451: Current learning rate: 0.00149 +2024-11-23 01:04:55.152478: train_loss -0.815 +2024-11-23 01:04:55.152699: val_loss -0.7558 +2024-11-23 01:04:55.152774: Pseudo dice [0.8188] +2024-11-23 01:04:55.155053: Epoch time: 18.7 s +2024-11-23 01:04:56.203547: +2024-11-23 01:04:56.203747: Epoch 7035 +2024-11-23 01:04:56.203861: Current learning rate: 0.00149 +2024-11-23 01:05:14.426998: train_loss -0.8302 +2024-11-23 01:05:14.432414: val_loss -0.7732 +2024-11-23 01:05:14.432550: Pseudo dice [0.8515] +2024-11-23 01:05:14.432631: Epoch time: 18.22 s +2024-11-23 01:05:15.403896: +2024-11-23 01:05:15.404108: Epoch 7036 +2024-11-23 01:05:15.404222: Current learning rate: 0.00149 +2024-11-23 01:05:34.926295: train_loss -0.8229 +2024-11-23 01:05:34.926519: val_loss -0.7687 +2024-11-23 01:05:34.926593: Pseudo dice [0.8305] +2024-11-23 01:05:34.926668: Epoch time: 19.52 s +2024-11-23 01:05:35.848140: +2024-11-23 01:05:35.848337: Epoch 7037 +2024-11-23 01:05:35.848445: Current learning rate: 0.00149 +2024-11-23 01:05:54.362799: train_loss -0.8241 +2024-11-23 01:05:54.363079: val_loss -0.7774 +2024-11-23 01:05:54.363158: Pseudo dice [0.8461] +2024-11-23 01:05:54.363245: Epoch time: 18.52 s +2024-11-23 01:05:55.289643: +2024-11-23 01:05:55.289872: Epoch 7038 +2024-11-23 01:05:55.289995: Current learning rate: 0.00149 +2024-11-23 01:06:13.275814: train_loss -0.8177 +2024-11-23 01:06:13.276048: val_loss -0.7512 +2024-11-23 01:06:13.276126: Pseudo dice [0.8434] +2024-11-23 01:06:13.276204: Epoch time: 17.99 s +2024-11-23 01:06:14.233086: +2024-11-23 01:06:14.233292: Epoch 7039 +2024-11-23 01:06:14.233411: Current learning rate: 0.00148 +2024-11-23 01:06:33.359976: train_loss -0.8235 +2024-11-23 01:06:33.360604: val_loss -0.7495 +2024-11-23 01:06:33.360708: Pseudo dice [0.8302] +2024-11-23 01:06:33.360791: Epoch time: 19.12 s +2024-11-23 01:06:34.386660: +2024-11-23 01:06:34.386930: Epoch 7040 +2024-11-23 01:06:34.387052: Current learning rate: 0.00148 +2024-11-23 01:06:53.989083: train_loss -0.8252 +2024-11-23 01:06:53.989322: val_loss -0.7535 +2024-11-23 01:06:53.989404: Pseudo dice [0.8233] +2024-11-23 01:06:53.989486: Epoch time: 19.6 s +2024-11-23 01:06:54.927668: +2024-11-23 01:06:54.927872: Epoch 7041 +2024-11-23 01:06:54.927985: Current learning rate: 0.00148 +2024-11-23 01:07:13.389178: train_loss -0.8197 +2024-11-23 01:07:13.389393: val_loss -0.7608 +2024-11-23 01:07:13.389466: Pseudo dice [0.8215] +2024-11-23 01:07:13.389544: Epoch time: 18.46 s +2024-11-23 01:07:14.310379: +2024-11-23 01:07:14.310628: Epoch 7042 +2024-11-23 01:07:14.310741: Current learning rate: 0.00148 +2024-11-23 01:07:32.958923: train_loss -0.8135 +2024-11-23 01:07:32.959143: val_loss -0.754 +2024-11-23 01:07:32.959217: Pseudo dice [0.8352] +2024-11-23 01:07:32.959295: Epoch time: 18.65 s +2024-11-23 01:07:33.873412: +2024-11-23 01:07:33.873624: Epoch 7043 +2024-11-23 01:07:33.873740: Current learning rate: 0.00148 +2024-11-23 01:07:52.387208: train_loss -0.8206 +2024-11-23 01:07:52.387470: val_loss -0.7604 +2024-11-23 01:07:52.387572: Pseudo dice [0.8265] +2024-11-23 01:07:52.387663: Epoch time: 18.51 s +2024-11-23 01:07:53.311142: +2024-11-23 01:07:53.311417: Epoch 7044 +2024-11-23 01:07:53.311529: Current learning rate: 0.00148 +2024-11-23 01:08:12.214573: train_loss -0.8225 +2024-11-23 01:08:12.214788: val_loss -0.753 +2024-11-23 01:08:12.214865: Pseudo dice [0.8432] +2024-11-23 01:08:12.214959: Epoch time: 18.9 s +2024-11-23 01:08:13.138907: +2024-11-23 01:08:13.139115: Epoch 7045 +2024-11-23 01:08:13.139224: Current learning rate: 0.00148 +2024-11-23 01:08:32.812617: train_loss -0.8142 +2024-11-23 01:08:32.812844: val_loss -0.7588 +2024-11-23 01:08:32.812919: Pseudo dice [0.8356] +2024-11-23 01:08:32.813004: Epoch time: 19.67 s +2024-11-23 01:08:33.731703: +2024-11-23 01:08:33.731921: Epoch 7046 +2024-11-23 01:08:33.732046: Current learning rate: 0.00148 +2024-11-23 01:08:52.695875: train_loss -0.819 +2024-11-23 01:08:52.696116: val_loss -0.7316 +2024-11-23 01:08:52.696193: Pseudo dice [0.8229] +2024-11-23 01:08:52.696283: Epoch time: 18.96 s +2024-11-23 01:08:53.608110: +2024-11-23 01:08:53.608309: Epoch 7047 +2024-11-23 01:08:53.608428: Current learning rate: 0.00147 +2024-11-23 01:09:12.148550: train_loss -0.8181 +2024-11-23 01:09:12.148771: val_loss -0.7663 +2024-11-23 01:09:12.148849: Pseudo dice [0.8431] +2024-11-23 01:09:12.148926: Epoch time: 18.54 s +2024-11-23 01:09:13.071305: +2024-11-23 01:09:13.071534: Epoch 7048 +2024-11-23 01:09:13.071650: Current learning rate: 0.00147 +2024-11-23 01:09:31.641646: train_loss -0.8252 +2024-11-23 01:09:31.641870: val_loss -0.7753 +2024-11-23 01:09:31.641947: Pseudo dice [0.854] +2024-11-23 01:09:31.642029: Epoch time: 18.57 s +2024-11-23 01:09:32.560960: +2024-11-23 01:09:32.561168: Epoch 7049 +2024-11-23 01:09:32.561285: Current learning rate: 0.00147 +2024-11-23 01:09:51.332072: train_loss -0.8238 +2024-11-23 01:09:51.332286: val_loss -0.7639 +2024-11-23 01:09:51.332362: Pseudo dice [0.8444] +2024-11-23 01:09:51.332439: Epoch time: 18.77 s +2024-11-23 01:09:52.581821: +2024-11-23 01:09:52.582029: Epoch 7050 +2024-11-23 01:09:52.582144: Current learning rate: 0.00147 +2024-11-23 01:10:11.763103: train_loss -0.8263 +2024-11-23 01:10:11.763622: val_loss -0.7436 +2024-11-23 01:10:11.763719: Pseudo dice [0.828] +2024-11-23 01:10:11.763804: Epoch time: 19.18 s +2024-11-23 01:10:12.685587: +2024-11-23 01:10:12.685803: Epoch 7051 +2024-11-23 01:10:12.685915: Current learning rate: 0.00147 +2024-11-23 01:10:30.497794: train_loss -0.8306 +2024-11-23 01:10:30.498018: val_loss -0.7702 +2024-11-23 01:10:30.498094: Pseudo dice [0.8396] +2024-11-23 01:10:30.498172: Epoch time: 17.81 s +2024-11-23 01:10:31.413723: +2024-11-23 01:10:31.413935: Epoch 7052 +2024-11-23 01:10:31.414055: Current learning rate: 0.00147 +2024-11-23 01:10:50.536597: train_loss -0.8315 +2024-11-23 01:10:50.536818: val_loss -0.7708 +2024-11-23 01:10:50.536890: Pseudo dice [0.833] +2024-11-23 01:10:50.537023: Epoch time: 19.12 s +2024-11-23 01:10:51.454853: +2024-11-23 01:10:51.455082: Epoch 7053 +2024-11-23 01:10:51.455201: Current learning rate: 0.00147 +2024-11-23 01:11:10.921842: train_loss -0.8243 +2024-11-23 01:11:10.927263: val_loss -0.7617 +2024-11-23 01:11:10.927373: Pseudo dice [0.8436] +2024-11-23 01:11:10.927464: Epoch time: 19.47 s +2024-11-23 01:11:11.864921: +2024-11-23 01:11:11.865122: Epoch 7054 +2024-11-23 01:11:11.865230: Current learning rate: 0.00146 +2024-11-23 01:11:29.937381: train_loss -0.8215 +2024-11-23 01:11:29.937598: val_loss -0.7801 +2024-11-23 01:11:29.937669: Pseudo dice [0.8458] +2024-11-23 01:11:29.937771: Epoch time: 18.07 s +2024-11-23 01:11:30.863394: +2024-11-23 01:11:30.863592: Epoch 7055 +2024-11-23 01:11:30.863711: Current learning rate: 0.00146 +2024-11-23 01:11:48.454526: train_loss -0.8236 +2024-11-23 01:11:48.454755: val_loss -0.7593 +2024-11-23 01:11:48.454830: Pseudo dice [0.8289] +2024-11-23 01:11:48.454907: Epoch time: 17.59 s +2024-11-23 01:11:49.370910: +2024-11-23 01:11:49.371162: Epoch 7056 +2024-11-23 01:11:49.371282: Current learning rate: 0.00146 +2024-11-23 01:12:07.413687: train_loss -0.8289 +2024-11-23 01:12:07.413944: val_loss -0.7559 +2024-11-23 01:12:07.414032: Pseudo dice [0.8428] +2024-11-23 01:12:07.414116: Epoch time: 18.04 s +2024-11-23 01:12:08.334336: +2024-11-23 01:12:08.334557: Epoch 7057 +2024-11-23 01:12:08.334666: Current learning rate: 0.00146 +2024-11-23 01:12:27.466685: train_loss -0.815 +2024-11-23 01:12:27.467101: val_loss -0.7652 +2024-11-23 01:12:27.469414: Pseudo dice [0.8448] +2024-11-23 01:12:27.469527: Epoch time: 19.13 s +2024-11-23 01:12:28.434564: +2024-11-23 01:12:28.434768: Epoch 7058 +2024-11-23 01:12:28.434883: Current learning rate: 0.00146 +2024-11-23 01:12:46.661553: train_loss -0.8174 +2024-11-23 01:12:46.661829: val_loss -0.7368 +2024-11-23 01:12:46.661910: Pseudo dice [0.8217] +2024-11-23 01:12:46.661987: Epoch time: 18.23 s +2024-11-23 01:12:47.701490: +2024-11-23 01:12:47.701710: Epoch 7059 +2024-11-23 01:12:47.701826: Current learning rate: 0.00146 +2024-11-23 01:13:07.131067: train_loss -0.8229 +2024-11-23 01:13:07.131291: val_loss -0.7502 +2024-11-23 01:13:07.131364: Pseudo dice [0.8364] +2024-11-23 01:13:07.131438: Epoch time: 19.43 s +2024-11-23 01:13:08.051305: +2024-11-23 01:13:08.051515: Epoch 7060 +2024-11-23 01:13:08.051630: Current learning rate: 0.00146 +2024-11-23 01:13:27.671793: train_loss -0.8142 +2024-11-23 01:13:27.672026: val_loss -0.7431 +2024-11-23 01:13:27.672102: Pseudo dice [0.8445] +2024-11-23 01:13:27.672180: Epoch time: 19.62 s +2024-11-23 01:13:28.586585: +2024-11-23 01:13:28.586980: Epoch 7061 +2024-11-23 01:13:28.587123: Current learning rate: 0.00145 +2024-11-23 01:13:47.484489: train_loss -0.8177 +2024-11-23 01:13:47.484730: val_loss -0.7651 +2024-11-23 01:13:47.484805: Pseudo dice [0.839] +2024-11-23 01:13:47.489854: Epoch time: 18.9 s +2024-11-23 01:13:48.781526: +2024-11-23 01:13:48.781762: Epoch 7062 +2024-11-23 01:13:48.781873: Current learning rate: 0.00145 +2024-11-23 01:14:06.400109: train_loss -0.8188 +2024-11-23 01:14:06.400419: val_loss -0.7453 +2024-11-23 01:14:06.400495: Pseudo dice [0.8208] +2024-11-23 01:14:06.400573: Epoch time: 17.62 s +2024-11-23 01:14:07.315571: +2024-11-23 01:14:07.315781: Epoch 7063 +2024-11-23 01:14:07.315894: Current learning rate: 0.00145 +2024-11-23 01:14:25.427543: train_loss -0.8232 +2024-11-23 01:14:25.427773: val_loss -0.7482 +2024-11-23 01:14:25.427848: Pseudo dice [0.83] +2024-11-23 01:14:25.427926: Epoch time: 18.11 s +2024-11-23 01:14:26.346614: +2024-11-23 01:14:26.346830: Epoch 7064 +2024-11-23 01:14:26.346942: Current learning rate: 0.00145 +2024-11-23 01:14:44.637436: train_loss -0.8188 +2024-11-23 01:14:44.637678: val_loss -0.757 +2024-11-23 01:14:44.637754: Pseudo dice [0.8199] +2024-11-23 01:14:44.637854: Epoch time: 18.29 s +2024-11-23 01:14:45.666578: +2024-11-23 01:14:45.666791: Epoch 7065 +2024-11-23 01:14:45.666903: Current learning rate: 0.00145 +2024-11-23 01:15:04.163745: train_loss -0.8168 +2024-11-23 01:15:04.163963: val_loss -0.7542 +2024-11-23 01:15:04.164044: Pseudo dice [0.8409] +2024-11-23 01:15:04.164176: Epoch time: 18.5 s +2024-11-23 01:15:05.079750: +2024-11-23 01:15:05.079953: Epoch 7066 +2024-11-23 01:15:05.080069: Current learning rate: 0.00145 +2024-11-23 01:15:23.540148: train_loss -0.8244 +2024-11-23 01:15:23.541142: val_loss -0.7661 +2024-11-23 01:15:23.541237: Pseudo dice [0.8401] +2024-11-23 01:15:23.541318: Epoch time: 18.46 s +2024-11-23 01:15:24.471499: +2024-11-23 01:15:24.471719: Epoch 7067 +2024-11-23 01:15:24.471831: Current learning rate: 0.00145 +2024-11-23 01:15:42.523642: train_loss -0.8224 +2024-11-23 01:15:42.523857: val_loss -0.7694 +2024-11-23 01:15:42.523933: Pseudo dice [0.8339] +2024-11-23 01:15:42.524022: Epoch time: 18.05 s +2024-11-23 01:15:43.508217: +2024-11-23 01:15:43.508430: Epoch 7068 +2024-11-23 01:15:43.508581: Current learning rate: 0.00144 +2024-11-23 01:16:01.311516: train_loss -0.8197 +2024-11-23 01:16:01.311750: val_loss -0.7384 +2024-11-23 01:16:01.311848: Pseudo dice [0.8305] +2024-11-23 01:16:01.311931: Epoch time: 17.8 s +2024-11-23 01:16:02.225884: +2024-11-23 01:16:02.226139: Epoch 7069 +2024-11-23 01:16:02.226260: Current learning rate: 0.00144 +2024-11-23 01:16:21.569162: train_loss -0.821 +2024-11-23 01:16:21.571502: val_loss -0.7751 +2024-11-23 01:16:21.571677: Pseudo dice [0.8512] +2024-11-23 01:16:21.571755: Epoch time: 19.34 s +2024-11-23 01:16:22.521110: +2024-11-23 01:16:22.521313: Epoch 7070 +2024-11-23 01:16:22.521431: Current learning rate: 0.00144 +2024-11-23 01:16:40.754860: train_loss -0.8237 +2024-11-23 01:16:40.755094: val_loss -0.7376 +2024-11-23 01:16:40.755202: Pseudo dice [0.8312] +2024-11-23 01:16:40.755291: Epoch time: 18.23 s +2024-11-23 01:16:41.674098: +2024-11-23 01:16:41.674310: Epoch 7071 +2024-11-23 01:16:41.674429: Current learning rate: 0.00144 +2024-11-23 01:17:00.257080: train_loss -0.8175 +2024-11-23 01:17:00.258914: val_loss -0.7601 +2024-11-23 01:17:00.259014: Pseudo dice [0.8357] +2024-11-23 01:17:00.259102: Epoch time: 18.58 s +2024-11-23 01:17:01.290977: +2024-11-23 01:17:01.291186: Epoch 7072 +2024-11-23 01:17:01.291302: Current learning rate: 0.00144 +2024-11-23 01:17:18.632620: train_loss -0.8191 +2024-11-23 01:17:18.632841: val_loss -0.7471 +2024-11-23 01:17:18.632913: Pseudo dice [0.844] +2024-11-23 01:17:18.632997: Epoch time: 17.34 s +2024-11-23 01:17:19.550648: +2024-11-23 01:17:19.550911: Epoch 7073 +2024-11-23 01:17:19.551035: Current learning rate: 0.00144 +2024-11-23 01:17:38.351932: train_loss -0.8262 +2024-11-23 01:17:38.352413: val_loss -0.76 +2024-11-23 01:17:38.352515: Pseudo dice [0.8378] +2024-11-23 01:17:38.352589: Epoch time: 18.8 s +2024-11-23 01:17:39.266111: +2024-11-23 01:17:39.266311: Epoch 7074 +2024-11-23 01:17:39.266424: Current learning rate: 0.00144 +2024-11-23 01:17:57.405351: train_loss -0.8252 +2024-11-23 01:17:57.405648: val_loss -0.768 +2024-11-23 01:17:57.405727: Pseudo dice [0.8491] +2024-11-23 01:17:57.405813: Epoch time: 18.14 s +2024-11-23 01:17:58.329607: +2024-11-23 01:17:58.329832: Epoch 7075 +2024-11-23 01:17:58.329945: Current learning rate: 0.00143 +2024-11-23 01:18:16.761881: train_loss -0.8259 +2024-11-23 01:18:16.762101: val_loss -0.7424 +2024-11-23 01:18:16.762208: Pseudo dice [0.855] +2024-11-23 01:18:16.762288: Epoch time: 18.43 s +2024-11-23 01:18:17.675529: +2024-11-23 01:18:17.675822: Epoch 7076 +2024-11-23 01:18:17.675938: Current learning rate: 0.00143 +2024-11-23 01:18:36.457695: train_loss -0.8251 +2024-11-23 01:18:36.457908: val_loss -0.771 +2024-11-23 01:18:36.457983: Pseudo dice [0.8489] +2024-11-23 01:18:36.458066: Epoch time: 18.78 s +2024-11-23 01:18:37.372958: +2024-11-23 01:18:37.373195: Epoch 7077 +2024-11-23 01:18:37.373315: Current learning rate: 0.00143 +2024-11-23 01:18:56.274126: train_loss -0.8239 +2024-11-23 01:18:56.274341: val_loss -0.7702 +2024-11-23 01:18:56.274411: Pseudo dice [0.8508] +2024-11-23 01:18:56.274492: Epoch time: 18.9 s +2024-11-23 01:18:57.193658: +2024-11-23 01:18:57.193874: Epoch 7078 +2024-11-23 01:18:57.193994: Current learning rate: 0.00143 +2024-11-23 01:19:15.907111: train_loss -0.8243 +2024-11-23 01:19:15.912558: val_loss -0.7658 +2024-11-23 01:19:15.912675: Pseudo dice [0.8352] +2024-11-23 01:19:15.912763: Epoch time: 18.71 s +2024-11-23 01:19:17.018923: +2024-11-23 01:19:17.019124: Epoch 7079 +2024-11-23 01:19:17.019237: Current learning rate: 0.00143 +2024-11-23 01:19:35.937012: train_loss -0.8224 +2024-11-23 01:19:35.937231: val_loss -0.7476 +2024-11-23 01:19:35.937306: Pseudo dice [0.8411] +2024-11-23 01:19:35.937387: Epoch time: 18.92 s +2024-11-23 01:19:36.851414: +2024-11-23 01:19:36.851610: Epoch 7080 +2024-11-23 01:19:36.851726: Current learning rate: 0.00143 +2024-11-23 01:19:56.087231: train_loss -0.8261 +2024-11-23 01:19:56.087459: val_loss -0.7693 +2024-11-23 01:19:56.087532: Pseudo dice [0.8487] +2024-11-23 01:19:56.087609: Epoch time: 19.24 s +2024-11-23 01:19:57.008019: +2024-11-23 01:19:57.008371: Epoch 7081 +2024-11-23 01:19:57.008485: Current learning rate: 0.00143 +2024-11-23 01:20:14.806248: train_loss -0.8282 +2024-11-23 01:20:14.806460: val_loss -0.7695 +2024-11-23 01:20:14.806609: Pseudo dice [0.8499] +2024-11-23 01:20:14.838359: Epoch time: 17.8 s +2024-11-23 01:20:14.838472: Yayy! New best EMA pseudo Dice: 0.8425 +2024-11-23 01:20:16.074916: +2024-11-23 01:20:16.075124: Epoch 7082 +2024-11-23 01:20:16.075237: Current learning rate: 0.00142 +2024-11-23 01:20:34.211455: train_loss -0.8276 +2024-11-23 01:20:34.211689: val_loss -0.7742 +2024-11-23 01:20:34.211767: Pseudo dice [0.8497] +2024-11-23 01:20:34.211905: Epoch time: 18.14 s +2024-11-23 01:20:34.211968: Yayy! New best EMA pseudo Dice: 0.8432 +2024-11-23 01:20:35.448573: +2024-11-23 01:20:35.448863: Epoch 7083 +2024-11-23 01:20:35.448981: Current learning rate: 0.00142 +2024-11-23 01:20:53.584127: train_loss -0.8298 +2024-11-23 01:20:53.584358: val_loss -0.762 +2024-11-23 01:20:53.584437: Pseudo dice [0.8463] +2024-11-23 01:20:53.584512: Epoch time: 18.14 s +2024-11-23 01:20:53.584572: Yayy! New best EMA pseudo Dice: 0.8435 +2024-11-23 01:20:55.190665: +2024-11-23 01:20:55.190868: Epoch 7084 +2024-11-23 01:20:55.190983: Current learning rate: 0.00142 +2024-11-23 01:21:13.308460: train_loss -0.8255 +2024-11-23 01:21:13.308685: val_loss -0.7551 +2024-11-23 01:21:13.308759: Pseudo dice [0.8249] +2024-11-23 01:21:13.308836: Epoch time: 18.12 s +2024-11-23 01:21:14.297391: +2024-11-23 01:21:14.297602: Epoch 7085 +2024-11-23 01:21:14.297714: Current learning rate: 0.00142 +2024-11-23 01:21:32.623291: train_loss -0.8249 +2024-11-23 01:21:32.623548: val_loss -0.7455 +2024-11-23 01:21:32.623628: Pseudo dice [0.829] +2024-11-23 01:21:32.623719: Epoch time: 18.33 s +2024-11-23 01:21:33.816587: +2024-11-23 01:21:33.816815: Epoch 7086 +2024-11-23 01:21:33.816929: Current learning rate: 0.00142 +2024-11-23 01:21:53.080816: train_loss -0.8155 +2024-11-23 01:21:53.081032: val_loss -0.7542 +2024-11-23 01:21:53.081111: Pseudo dice [0.8196] +2024-11-23 01:21:53.081187: Epoch time: 19.27 s +2024-11-23 01:21:54.175326: +2024-11-23 01:21:54.175554: Epoch 7087 +2024-11-23 01:21:54.175664: Current learning rate: 0.00142 +2024-11-23 01:22:13.908027: train_loss -0.8255 +2024-11-23 01:22:13.908248: val_loss -0.7442 +2024-11-23 01:22:13.908335: Pseudo dice [0.8424] +2024-11-23 01:22:13.908414: Epoch time: 19.73 s +2024-11-23 01:22:14.832131: +2024-11-23 01:22:14.832635: Epoch 7088 +2024-11-23 01:22:14.832757: Current learning rate: 0.00142 +2024-11-23 01:22:33.466263: train_loss -0.8279 +2024-11-23 01:22:33.466495: val_loss -0.7648 +2024-11-23 01:22:33.466610: Pseudo dice [0.8465] +2024-11-23 01:22:33.466695: Epoch time: 18.63 s +2024-11-23 01:22:34.382671: +2024-11-23 01:22:34.382874: Epoch 7089 +2024-11-23 01:22:34.382988: Current learning rate: 0.00142 +2024-11-23 01:22:54.025545: train_loss -0.8215 +2024-11-23 01:22:54.025782: val_loss -0.7701 +2024-11-23 01:22:54.025854: Pseudo dice [0.8373] +2024-11-23 01:22:54.025935: Epoch time: 19.64 s +2024-11-23 01:22:54.947468: +2024-11-23 01:22:54.947678: Epoch 7090 +2024-11-23 01:22:54.947794: Current learning rate: 0.00141 +2024-11-23 01:23:12.701112: train_loss -0.8305 +2024-11-23 01:23:12.701320: val_loss -0.7709 +2024-11-23 01:23:12.701391: Pseudo dice [0.84] +2024-11-23 01:23:12.701469: Epoch time: 17.75 s +2024-11-23 01:23:13.594508: +2024-11-23 01:23:13.594725: Epoch 7091 +2024-11-23 01:23:13.594839: Current learning rate: 0.00141 +2024-11-23 01:23:31.766956: train_loss -0.8224 +2024-11-23 01:23:31.767191: val_loss -0.7626 +2024-11-23 01:23:31.767266: Pseudo dice [0.841] +2024-11-23 01:23:31.767341: Epoch time: 18.17 s +2024-11-23 01:23:32.686631: +2024-11-23 01:23:32.686885: Epoch 7092 +2024-11-23 01:23:32.687000: Current learning rate: 0.00141 +2024-11-23 01:23:50.795805: train_loss -0.8213 +2024-11-23 01:23:50.796019: val_loss -0.7798 +2024-11-23 01:23:50.796095: Pseudo dice [0.8589] +2024-11-23 01:23:50.796192: Epoch time: 18.11 s +2024-11-23 01:23:51.756806: +2024-11-23 01:23:51.757077: Epoch 7093 +2024-11-23 01:23:51.757186: Current learning rate: 0.00141 +2024-11-23 01:24:10.130685: train_loss -0.8285 +2024-11-23 01:24:10.130924: val_loss -0.7747 +2024-11-23 01:24:10.131007: Pseudo dice [0.8339] +2024-11-23 01:24:10.131090: Epoch time: 18.37 s +2024-11-23 01:24:11.054394: +2024-11-23 01:24:11.054599: Epoch 7094 +2024-11-23 01:24:11.054712: Current learning rate: 0.00141 +2024-11-23 01:24:28.907875: train_loss -0.8299 +2024-11-23 01:24:28.908096: val_loss -0.7715 +2024-11-23 01:24:28.908171: Pseudo dice [0.8358] +2024-11-23 01:24:28.908249: Epoch time: 17.85 s +2024-11-23 01:24:29.829194: +2024-11-23 01:24:29.829574: Epoch 7095 +2024-11-23 01:24:29.829689: Current learning rate: 0.00141 +2024-11-23 01:24:48.741810: train_loss -0.8284 +2024-11-23 01:24:48.742043: val_loss -0.7674 +2024-11-23 01:24:48.742115: Pseudo dice [0.8433] +2024-11-23 01:24:48.742194: Epoch time: 18.91 s +2024-11-23 01:24:50.023302: +2024-11-23 01:24:50.023541: Epoch 7096 +2024-11-23 01:24:50.023653: Current learning rate: 0.00141 +2024-11-23 01:25:09.927665: train_loss -0.8214 +2024-11-23 01:25:09.927919: val_loss -0.7737 +2024-11-23 01:25:09.928009: Pseudo dice [0.8367] +2024-11-23 01:25:09.928094: Epoch time: 19.91 s +2024-11-23 01:25:10.842788: +2024-11-23 01:25:10.843000: Epoch 7097 +2024-11-23 01:25:10.843111: Current learning rate: 0.0014 +2024-11-23 01:25:27.947550: train_loss -0.8225 +2024-11-23 01:25:27.948767: val_loss -0.7624 +2024-11-23 01:25:27.948894: Pseudo dice [0.8409] +2024-11-23 01:25:27.948973: Epoch time: 17.11 s +2024-11-23 01:25:28.867743: +2024-11-23 01:25:28.867971: Epoch 7098 +2024-11-23 01:25:28.868086: Current learning rate: 0.0014 +2024-11-23 01:25:47.302696: train_loss -0.821 +2024-11-23 01:25:47.302918: val_loss -0.7722 +2024-11-23 01:25:47.302996: Pseudo dice [0.8361] +2024-11-23 01:25:47.303072: Epoch time: 18.44 s +2024-11-23 01:25:48.263146: +2024-11-23 01:25:48.263391: Epoch 7099 +2024-11-23 01:25:48.263503: Current learning rate: 0.0014 +2024-11-23 01:26:05.990900: train_loss -0.8256 +2024-11-23 01:26:05.991130: val_loss -0.7788 +2024-11-23 01:26:05.991203: Pseudo dice [0.8392] +2024-11-23 01:26:05.991286: Epoch time: 17.73 s +2024-11-23 01:26:07.252871: +2024-11-23 01:26:07.253111: Epoch 7100 +2024-11-23 01:26:07.253238: Current learning rate: 0.0014 +2024-11-23 01:26:25.640980: train_loss -0.8201 +2024-11-23 01:26:25.641195: val_loss -0.771 +2024-11-23 01:26:25.641268: Pseudo dice [0.8493] +2024-11-23 01:26:25.641343: Epoch time: 18.39 s +2024-11-23 01:26:26.589828: +2024-11-23 01:26:26.590154: Epoch 7101 +2024-11-23 01:26:26.590272: Current learning rate: 0.0014 +2024-11-23 01:26:45.827858: train_loss -0.8265 +2024-11-23 01:26:45.828125: val_loss -0.7752 +2024-11-23 01:26:45.828204: Pseudo dice [0.8456] +2024-11-23 01:26:45.828306: Epoch time: 19.24 s +2024-11-23 01:26:46.741194: +2024-11-23 01:26:46.741416: Epoch 7102 +2024-11-23 01:26:46.741529: Current learning rate: 0.0014 +2024-11-23 01:27:04.433984: train_loss -0.8239 +2024-11-23 01:27:04.434273: val_loss -0.7615 +2024-11-23 01:27:04.434349: Pseudo dice [0.8482] +2024-11-23 01:27:04.434423: Epoch time: 17.69 s +2024-11-23 01:27:05.355161: +2024-11-23 01:27:05.355448: Epoch 7103 +2024-11-23 01:27:05.355563: Current learning rate: 0.0014 +2024-11-23 01:27:24.314753: train_loss -0.8225 +2024-11-23 01:27:24.314998: val_loss -0.7581 +2024-11-23 01:27:24.320216: Pseudo dice [0.8381] +2024-11-23 01:27:24.320374: Epoch time: 18.96 s +2024-11-23 01:27:25.312366: +2024-11-23 01:27:25.312580: Epoch 7104 +2024-11-23 01:27:25.312691: Current learning rate: 0.00139 +2024-11-23 01:27:44.284461: train_loss -0.8218 +2024-11-23 01:27:44.284683: val_loss -0.773 +2024-11-23 01:27:44.284772: Pseudo dice [0.8388] +2024-11-23 01:27:44.284852: Epoch time: 18.97 s +2024-11-23 01:27:45.200092: +2024-11-23 01:27:45.200315: Epoch 7105 +2024-11-23 01:27:45.200428: Current learning rate: 0.00139 +2024-11-23 01:28:03.659700: train_loss -0.8171 +2024-11-23 01:28:03.665124: val_loss -0.7581 +2024-11-23 01:28:03.665242: Pseudo dice [0.8383] +2024-11-23 01:28:03.665320: Epoch time: 18.46 s +2024-11-23 01:28:04.626701: +2024-11-23 01:28:04.626897: Epoch 7106 +2024-11-23 01:28:04.627013: Current learning rate: 0.00139 +2024-11-23 01:28:22.116836: train_loss -0.8202 +2024-11-23 01:28:22.133238: val_loss -0.7391 +2024-11-23 01:28:22.133403: Pseudo dice [0.823] +2024-11-23 01:28:22.133498: Epoch time: 17.49 s +2024-11-23 01:28:23.078326: +2024-11-23 01:28:23.078557: Epoch 7107 +2024-11-23 01:28:23.078707: Current learning rate: 0.00139 +2024-11-23 01:28:41.748955: train_loss -0.8135 +2024-11-23 01:28:41.754691: val_loss -0.7509 +2024-11-23 01:28:41.754866: Pseudo dice [0.8339] +2024-11-23 01:28:41.754951: Epoch time: 18.67 s +2024-11-23 01:28:42.736574: +2024-11-23 01:28:42.736785: Epoch 7108 +2024-11-23 01:28:42.736904: Current learning rate: 0.00139 +2024-11-23 01:29:01.536986: train_loss -0.8193 +2024-11-23 01:29:01.542588: val_loss -0.7363 +2024-11-23 01:29:01.542709: Pseudo dice [0.8318] +2024-11-23 01:29:01.542882: Epoch time: 18.8 s +2024-11-23 01:29:02.484799: +2024-11-23 01:29:02.485059: Epoch 7109 +2024-11-23 01:29:02.485175: Current learning rate: 0.00139 +2024-11-23 01:29:21.590764: train_loss -0.8199 +2024-11-23 01:29:21.591014: val_loss -0.776 +2024-11-23 01:29:21.591089: Pseudo dice [0.8331] +2024-11-23 01:29:21.591178: Epoch time: 19.11 s +2024-11-23 01:29:22.621708: +2024-11-23 01:29:22.621926: Epoch 7110 +2024-11-23 01:29:22.622043: Current learning rate: 0.00139 +2024-11-23 01:29:41.340370: train_loss -0.825 +2024-11-23 01:29:41.340589: val_loss -0.7546 +2024-11-23 01:29:41.340661: Pseudo dice [0.8378] +2024-11-23 01:29:41.340737: Epoch time: 18.72 s +2024-11-23 01:29:42.257172: +2024-11-23 01:29:42.257389: Epoch 7111 +2024-11-23 01:29:42.257508: Current learning rate: 0.00138 +2024-11-23 01:30:01.418330: train_loss -0.8272 +2024-11-23 01:30:01.418623: val_loss -0.7779 +2024-11-23 01:30:01.418706: Pseudo dice [0.8495] +2024-11-23 01:30:01.418786: Epoch time: 19.16 s +2024-11-23 01:30:02.397390: +2024-11-23 01:30:02.397593: Epoch 7112 +2024-11-23 01:30:02.397705: Current learning rate: 0.00138 +2024-11-23 01:30:19.838979: train_loss -0.8283 +2024-11-23 01:30:19.839215: val_loss -0.7604 +2024-11-23 01:30:19.839295: Pseudo dice [0.8401] +2024-11-23 01:30:19.839373: Epoch time: 17.44 s +2024-11-23 01:30:20.958487: +2024-11-23 01:30:20.958709: Epoch 7113 +2024-11-23 01:30:20.958829: Current learning rate: 0.00138 +2024-11-23 01:30:39.511498: train_loss -0.8237 +2024-11-23 01:30:39.511741: val_loss -0.7387 +2024-11-23 01:30:39.514003: Pseudo dice [0.8237] +2024-11-23 01:30:39.514107: Epoch time: 18.55 s +2024-11-23 01:30:40.522113: +2024-11-23 01:30:40.522310: Epoch 7114 +2024-11-23 01:30:40.522431: Current learning rate: 0.00138 +2024-11-23 01:30:59.127353: train_loss -0.8218 +2024-11-23 01:30:59.127586: val_loss -0.7467 +2024-11-23 01:30:59.127666: Pseudo dice [0.8274] +2024-11-23 01:30:59.127744: Epoch time: 18.61 s +2024-11-23 01:31:00.041238: +2024-11-23 01:31:00.041500: Epoch 7115 +2024-11-23 01:31:00.041613: Current learning rate: 0.00138 +2024-11-23 01:31:18.536455: train_loss -0.8251 +2024-11-23 01:31:18.536687: val_loss -0.7577 +2024-11-23 01:31:18.536765: Pseudo dice [0.8352] +2024-11-23 01:31:18.536846: Epoch time: 18.5 s +2024-11-23 01:31:19.457688: +2024-11-23 01:31:19.457896: Epoch 7116 +2024-11-23 01:31:19.458018: Current learning rate: 0.00138 +2024-11-23 01:31:37.519206: train_loss -0.8218 +2024-11-23 01:31:37.519453: val_loss -0.7457 +2024-11-23 01:31:37.519531: Pseudo dice [0.8324] +2024-11-23 01:31:37.519608: Epoch time: 18.06 s +2024-11-23 01:31:38.439542: +2024-11-23 01:31:38.439759: Epoch 7117 +2024-11-23 01:31:38.439881: Current learning rate: 0.00138 +2024-11-23 01:31:55.884742: train_loss -0.8235 +2024-11-23 01:31:55.884984: val_loss -0.7692 +2024-11-23 01:31:55.885067: Pseudo dice [0.8379] +2024-11-23 01:31:55.885150: Epoch time: 17.45 s +2024-11-23 01:31:56.806115: +2024-11-23 01:31:56.806359: Epoch 7118 +2024-11-23 01:31:56.806471: Current learning rate: 0.00137 +2024-11-23 01:32:14.947599: train_loss -0.8293 +2024-11-23 01:32:14.947819: val_loss -0.785 +2024-11-23 01:32:14.947895: Pseudo dice [0.859] +2024-11-23 01:32:14.947971: Epoch time: 18.14 s +2024-11-23 01:32:16.251414: +2024-11-23 01:32:16.251614: Epoch 7119 +2024-11-23 01:32:16.269015: Current learning rate: 0.00137 +2024-11-23 01:32:34.096458: train_loss -0.8262 +2024-11-23 01:32:34.096687: val_loss -0.7493 +2024-11-23 01:32:34.096763: Pseudo dice [0.8227] +2024-11-23 01:32:34.096840: Epoch time: 17.85 s +2024-11-23 01:32:35.010999: +2024-11-23 01:32:35.011224: Epoch 7120 +2024-11-23 01:32:35.011335: Current learning rate: 0.00137 +2024-11-23 01:32:54.158672: train_loss -0.8282 +2024-11-23 01:32:54.158917: val_loss -0.7642 +2024-11-23 01:32:54.159001: Pseudo dice [0.8326] +2024-11-23 01:32:54.159101: Epoch time: 19.15 s +2024-11-23 01:32:55.080456: +2024-11-23 01:32:55.080663: Epoch 7121 +2024-11-23 01:32:55.080775: Current learning rate: 0.00137 +2024-11-23 01:33:13.906215: train_loss -0.8216 +2024-11-23 01:33:13.906451: val_loss -0.7507 +2024-11-23 01:33:13.906536: Pseudo dice [0.8358] +2024-11-23 01:33:13.906622: Epoch time: 18.83 s +2024-11-23 01:33:14.953397: +2024-11-23 01:33:14.953610: Epoch 7122 +2024-11-23 01:33:14.953722: Current learning rate: 0.00137 +2024-11-23 01:33:34.030575: train_loss -0.8236 +2024-11-23 01:33:34.030805: val_loss -0.7667 +2024-11-23 01:33:34.030880: Pseudo dice [0.8233] +2024-11-23 01:33:34.030959: Epoch time: 19.08 s +2024-11-23 01:33:34.951339: +2024-11-23 01:33:34.951549: Epoch 7123 +2024-11-23 01:33:34.951665: Current learning rate: 0.00137 +2024-11-23 01:33:55.065684: train_loss -0.8282 +2024-11-23 01:33:55.065898: val_loss -0.7552 +2024-11-23 01:33:55.065974: Pseudo dice [0.8553] +2024-11-23 01:33:55.066057: Epoch time: 20.12 s +2024-11-23 01:33:55.980083: +2024-11-23 01:33:55.980312: Epoch 7124 +2024-11-23 01:33:55.980428: Current learning rate: 0.00137 +2024-11-23 01:34:15.171783: train_loss -0.8264 +2024-11-23 01:34:15.172092: val_loss -0.7536 +2024-11-23 01:34:15.172173: Pseudo dice [0.8384] +2024-11-23 01:34:15.172264: Epoch time: 19.19 s +2024-11-23 01:34:16.094772: +2024-11-23 01:34:16.095069: Epoch 7125 +2024-11-23 01:34:16.095185: Current learning rate: 0.00136 +2024-11-23 01:34:34.848041: train_loss -0.8234 +2024-11-23 01:34:34.848261: val_loss -0.778 +2024-11-23 01:34:34.848338: Pseudo dice [0.8506] +2024-11-23 01:34:34.848418: Epoch time: 18.75 s +2024-11-23 01:34:35.757619: +2024-11-23 01:34:35.757843: Epoch 7126 +2024-11-23 01:34:35.757956: Current learning rate: 0.00136 +2024-11-23 01:34:54.757107: train_loss -0.8291 +2024-11-23 01:34:54.757314: val_loss -0.7593 +2024-11-23 01:34:54.757388: Pseudo dice [0.8471] +2024-11-23 01:34:54.757461: Epoch time: 19.0 s +2024-11-23 01:34:55.683458: +2024-11-23 01:34:55.683654: Epoch 7127 +2024-11-23 01:34:55.683764: Current learning rate: 0.00136 +2024-11-23 01:35:13.470469: train_loss -0.8239 +2024-11-23 01:35:13.475890: val_loss -0.7828 +2024-11-23 01:35:13.476014: Pseudo dice [0.8581] +2024-11-23 01:35:13.476096: Epoch time: 17.79 s +2024-11-23 01:35:14.408878: +2024-11-23 01:35:14.409091: Epoch 7128 +2024-11-23 01:35:14.409204: Current learning rate: 0.00136 +2024-11-23 01:35:33.681775: train_loss -0.8173 +2024-11-23 01:35:33.682013: val_loss -0.7773 +2024-11-23 01:35:33.682090: Pseudo dice [0.8367] +2024-11-23 01:35:33.682178: Epoch time: 19.27 s +2024-11-23 01:35:34.598747: +2024-11-23 01:35:34.598940: Epoch 7129 +2024-11-23 01:35:34.599062: Current learning rate: 0.00136 +2024-11-23 01:35:53.720006: train_loss -0.8269 +2024-11-23 01:35:53.720225: val_loss -0.7495 +2024-11-23 01:35:53.720298: Pseudo dice [0.8172] +2024-11-23 01:35:53.720394: Epoch time: 19.12 s +2024-11-23 01:35:54.658739: +2024-11-23 01:35:54.658940: Epoch 7130 +2024-11-23 01:35:54.659060: Current learning rate: 0.00136 +2024-11-23 01:36:13.790589: train_loss -0.8256 +2024-11-23 01:36:13.790813: val_loss -0.766 +2024-11-23 01:36:13.790891: Pseudo dice [0.8386] +2024-11-23 01:36:13.790969: Epoch time: 19.13 s +2024-11-23 01:36:14.720328: +2024-11-23 01:36:14.720555: Epoch 7131 +2024-11-23 01:36:14.720674: Current learning rate: 0.00136 +2024-11-23 01:36:32.665227: train_loss -0.8243 +2024-11-23 01:36:32.665463: val_loss -0.7493 +2024-11-23 01:36:32.665565: Pseudo dice [0.8238] +2024-11-23 01:36:32.665648: Epoch time: 17.95 s +2024-11-23 01:36:33.583906: +2024-11-23 01:36:33.584204: Epoch 7132 +2024-11-23 01:36:33.584315: Current learning rate: 0.00135 +2024-11-23 01:36:52.577079: train_loss -0.8206 +2024-11-23 01:36:52.579484: val_loss -0.7682 +2024-11-23 01:36:52.579577: Pseudo dice [0.8289] +2024-11-23 01:36:52.579657: Epoch time: 18.99 s +2024-11-23 01:36:53.529066: +2024-11-23 01:36:53.529290: Epoch 7133 +2024-11-23 01:36:53.529407: Current learning rate: 0.00135 +2024-11-23 01:37:11.243580: train_loss -0.828 +2024-11-23 01:37:11.243814: val_loss -0.7465 +2024-11-23 01:37:11.243892: Pseudo dice [0.8438] +2024-11-23 01:37:11.243968: Epoch time: 17.72 s +2024-11-23 01:37:12.155631: +2024-11-23 01:37:12.155828: Epoch 7134 +2024-11-23 01:37:12.155939: Current learning rate: 0.00135 +2024-11-23 01:37:29.810915: train_loss -0.8264 +2024-11-23 01:37:29.813347: val_loss -0.7574 +2024-11-23 01:37:29.813667: Pseudo dice [0.8436] +2024-11-23 01:37:29.813768: Epoch time: 17.66 s +2024-11-23 01:37:30.735448: +2024-11-23 01:37:30.735643: Epoch 7135 +2024-11-23 01:37:30.735755: Current learning rate: 0.00135 +2024-11-23 01:37:49.327106: train_loss -0.8231 +2024-11-23 01:37:49.327326: val_loss -0.7732 +2024-11-23 01:37:49.327450: Pseudo dice [0.8523] +2024-11-23 01:37:49.327554: Epoch time: 18.59 s +2024-11-23 01:37:50.254702: +2024-11-23 01:37:50.254937: Epoch 7136 +2024-11-23 01:37:50.255053: Current learning rate: 0.00135 +2024-11-23 01:38:07.861988: train_loss -0.824 +2024-11-23 01:38:07.862220: val_loss -0.7772 +2024-11-23 01:38:07.862295: Pseudo dice [0.8286] +2024-11-23 01:38:07.862373: Epoch time: 17.61 s +2024-11-23 01:38:08.786237: +2024-11-23 01:38:08.786535: Epoch 7137 +2024-11-23 01:38:08.786643: Current learning rate: 0.00135 +2024-11-23 01:38:28.194403: train_loss -0.8209 +2024-11-23 01:38:28.194628: val_loss -0.7615 +2024-11-23 01:38:28.194729: Pseudo dice [0.8431] +2024-11-23 01:38:28.194810: Epoch time: 19.41 s +2024-11-23 01:38:29.124953: +2024-11-23 01:38:29.125175: Epoch 7138 +2024-11-23 01:38:29.125289: Current learning rate: 0.00135 +2024-11-23 01:38:47.534136: train_loss -0.8198 +2024-11-23 01:38:47.534432: val_loss -0.7431 +2024-11-23 01:38:47.534510: Pseudo dice [0.8361] +2024-11-23 01:38:47.534592: Epoch time: 18.41 s +2024-11-23 01:38:48.454870: +2024-11-23 01:38:48.455071: Epoch 7139 +2024-11-23 01:38:48.455181: Current learning rate: 0.00134 +2024-11-23 01:39:07.171215: train_loss -0.8251 +2024-11-23 01:39:07.171463: val_loss -0.737 +2024-11-23 01:39:07.171541: Pseudo dice [0.8164] +2024-11-23 01:39:07.171620: Epoch time: 18.71 s +2024-11-23 01:39:08.291186: +2024-11-23 01:39:08.291395: Epoch 7140 +2024-11-23 01:39:08.291506: Current learning rate: 0.00134 +2024-11-23 01:39:28.226923: train_loss -0.8289 +2024-11-23 01:39:28.227161: val_loss -0.7726 +2024-11-23 01:39:28.227237: Pseudo dice [0.8283] +2024-11-23 01:39:28.227321: Epoch time: 19.94 s +2024-11-23 01:39:29.149581: +2024-11-23 01:39:29.149788: Epoch 7141 +2024-11-23 01:39:29.149900: Current learning rate: 0.00134 +2024-11-23 01:39:47.754823: train_loss -0.8255 +2024-11-23 01:39:47.755046: val_loss -0.7559 +2024-11-23 01:39:47.755118: Pseudo dice [0.8348] +2024-11-23 01:39:47.755196: Epoch time: 18.61 s +2024-11-23 01:39:49.067904: +2024-11-23 01:39:49.068209: Epoch 7142 +2024-11-23 01:39:49.068363: Current learning rate: 0.00134 +2024-11-23 01:40:07.747173: train_loss -0.8237 +2024-11-23 01:40:07.749575: val_loss -0.7488 +2024-11-23 01:40:07.749694: Pseudo dice [0.8357] +2024-11-23 01:40:07.749780: Epoch time: 18.68 s +2024-11-23 01:40:08.772084: +2024-11-23 01:40:08.772383: Epoch 7143 +2024-11-23 01:40:08.772498: Current learning rate: 0.00134 +2024-11-23 01:40:26.625726: train_loss -0.8245 +2024-11-23 01:40:26.625961: val_loss -0.7523 +2024-11-23 01:40:26.626048: Pseudo dice [0.8244] +2024-11-23 01:40:26.626128: Epoch time: 17.85 s +2024-11-23 01:40:27.539233: +2024-11-23 01:40:27.539517: Epoch 7144 +2024-11-23 01:40:27.539633: Current learning rate: 0.00134 +2024-11-23 01:40:46.244608: train_loss -0.8238 +2024-11-23 01:40:46.244840: val_loss -0.7634 +2024-11-23 01:40:46.245282: Pseudo dice [0.8193] +2024-11-23 01:40:46.245387: Epoch time: 18.71 s +2024-11-23 01:40:47.167665: +2024-11-23 01:40:47.167886: Epoch 7145 +2024-11-23 01:40:47.168013: Current learning rate: 0.00134 +2024-11-23 01:41:05.127539: train_loss -0.8301 +2024-11-23 01:41:05.127812: val_loss -0.7622 +2024-11-23 01:41:05.127887: Pseudo dice [0.8337] +2024-11-23 01:41:05.127973: Epoch time: 17.96 s +2024-11-23 01:41:06.049129: +2024-11-23 01:41:06.049349: Epoch 7146 +2024-11-23 01:41:06.049460: Current learning rate: 0.00134 +2024-11-23 01:41:25.521145: train_loss -0.8317 +2024-11-23 01:41:25.521372: val_loss -0.7345 +2024-11-23 01:41:25.521446: Pseudo dice [0.8394] +2024-11-23 01:41:25.521523: Epoch time: 19.47 s +2024-11-23 01:41:26.499485: +2024-11-23 01:41:26.499713: Epoch 7147 +2024-11-23 01:41:26.499825: Current learning rate: 0.00133 +2024-11-23 01:41:45.776239: train_loss -0.8248 +2024-11-23 01:41:45.776462: val_loss -0.7754 +2024-11-23 01:41:45.776533: Pseudo dice [0.8414] +2024-11-23 01:41:45.776611: Epoch time: 19.28 s +2024-11-23 01:41:46.692434: +2024-11-23 01:41:46.692645: Epoch 7148 +2024-11-23 01:41:46.692760: Current learning rate: 0.00133 +2024-11-23 01:42:04.265996: train_loss -0.8254 +2024-11-23 01:42:04.266218: val_loss -0.7418 +2024-11-23 01:42:04.266292: Pseudo dice [0.8504] +2024-11-23 01:42:04.266370: Epoch time: 17.57 s +2024-11-23 01:42:05.187680: +2024-11-23 01:42:05.187908: Epoch 7149 +2024-11-23 01:42:05.188027: Current learning rate: 0.00133 +2024-11-23 01:42:23.551881: train_loss -0.8285 +2024-11-23 01:42:23.552120: val_loss -0.7666 +2024-11-23 01:42:23.552194: Pseudo dice [0.8637] +2024-11-23 01:42:23.552274: Epoch time: 18.37 s +2024-11-23 01:42:24.815025: +2024-11-23 01:42:24.815246: Epoch 7150 +2024-11-23 01:42:24.815357: Current learning rate: 0.00133 +2024-11-23 01:42:43.055191: train_loss -0.8328 +2024-11-23 01:42:43.055416: val_loss -0.7951 +2024-11-23 01:42:43.055494: Pseudo dice [0.8481] +2024-11-23 01:42:43.055570: Epoch time: 18.24 s +2024-11-23 01:42:43.988655: +2024-11-23 01:42:43.988875: Epoch 7151 +2024-11-23 01:42:43.988986: Current learning rate: 0.00133 +2024-11-23 01:43:03.006152: train_loss -0.8286 +2024-11-23 01:43:03.007196: val_loss -0.7465 +2024-11-23 01:43:03.007324: Pseudo dice [0.8335] +2024-11-23 01:43:03.007441: Epoch time: 19.02 s +2024-11-23 01:43:03.962137: +2024-11-23 01:43:03.962499: Epoch 7152 +2024-11-23 01:43:03.962619: Current learning rate: 0.00133 +2024-11-23 01:43:22.750738: train_loss -0.83 +2024-11-23 01:43:22.750990: val_loss -0.7611 +2024-11-23 01:43:22.751080: Pseudo dice [0.8415] +2024-11-23 01:43:22.751167: Epoch time: 18.79 s +2024-11-23 01:43:23.783253: +2024-11-23 01:43:23.783456: Epoch 7153 +2024-11-23 01:43:23.783568: Current learning rate: 0.00133 +2024-11-23 01:43:42.510208: train_loss -0.8193 +2024-11-23 01:43:42.510425: val_loss -0.756 +2024-11-23 01:43:42.510498: Pseudo dice [0.8382] +2024-11-23 01:43:42.510571: Epoch time: 18.73 s +2024-11-23 01:43:43.496404: +2024-11-23 01:43:43.496623: Epoch 7154 +2024-11-23 01:43:43.496735: Current learning rate: 0.00132 +2024-11-23 01:44:03.425663: train_loss -0.8287 +2024-11-23 01:44:03.428054: val_loss -0.7642 +2024-11-23 01:44:03.428142: Pseudo dice [0.8317] +2024-11-23 01:44:03.428221: Epoch time: 19.93 s +2024-11-23 01:44:04.361111: +2024-11-23 01:44:04.361322: Epoch 7155 +2024-11-23 01:44:04.361435: Current learning rate: 0.00132 +2024-11-23 01:44:23.847422: train_loss -0.8278 +2024-11-23 01:44:23.847671: val_loss -0.7534 +2024-11-23 01:44:23.847759: Pseudo dice [0.839] +2024-11-23 01:44:23.847855: Epoch time: 19.49 s +2024-11-23 01:44:24.763876: +2024-11-23 01:44:24.764093: Epoch 7156 +2024-11-23 01:44:24.764207: Current learning rate: 0.00132 +2024-11-23 01:44:44.179356: train_loss -0.828 +2024-11-23 01:44:44.179628: val_loss -0.77 +2024-11-23 01:44:44.179708: Pseudo dice [0.8398] +2024-11-23 01:44:44.179792: Epoch time: 19.42 s +2024-11-23 01:44:45.098389: +2024-11-23 01:44:45.098595: Epoch 7157 +2024-11-23 01:44:45.098707: Current learning rate: 0.00132 +2024-11-23 01:45:03.432249: train_loss -0.825 +2024-11-23 01:45:03.432470: val_loss -0.7701 +2024-11-23 01:45:03.432542: Pseudo dice [0.8342] +2024-11-23 01:45:03.432617: Epoch time: 18.33 s +2024-11-23 01:45:04.353033: +2024-11-23 01:45:04.353250: Epoch 7158 +2024-11-23 01:45:04.353367: Current learning rate: 0.00132 +2024-11-23 01:45:22.890157: train_loss -0.8294 +2024-11-23 01:45:22.890388: val_loss -0.7572 +2024-11-23 01:45:22.890481: Pseudo dice [0.838] +2024-11-23 01:45:22.890565: Epoch time: 18.54 s +2024-11-23 01:45:23.818638: +2024-11-23 01:45:23.818862: Epoch 7159 +2024-11-23 01:45:23.818976: Current learning rate: 0.00132 +2024-11-23 01:45:41.793022: train_loss -0.8322 +2024-11-23 01:45:41.793263: val_loss -0.784 +2024-11-23 01:45:41.793336: Pseudo dice [0.8544] +2024-11-23 01:45:41.793419: Epoch time: 17.98 s +2024-11-23 01:45:42.738218: +2024-11-23 01:45:42.738431: Epoch 7160 +2024-11-23 01:45:42.738544: Current learning rate: 0.00132 +2024-11-23 01:46:02.185178: train_loss -0.8273 +2024-11-23 01:46:02.185400: val_loss -0.7604 +2024-11-23 01:46:02.185596: Pseudo dice [0.8425] +2024-11-23 01:46:02.185681: Epoch time: 19.45 s +2024-11-23 01:46:03.105492: +2024-11-23 01:46:03.105692: Epoch 7161 +2024-11-23 01:46:03.105804: Current learning rate: 0.00131 +2024-11-23 01:46:22.208961: train_loss -0.8178 +2024-11-23 01:46:22.209920: val_loss -0.7357 +2024-11-23 01:46:22.210009: Pseudo dice [0.8424] +2024-11-23 01:46:22.210087: Epoch time: 19.1 s +2024-11-23 01:46:23.191173: +2024-11-23 01:46:23.191381: Epoch 7162 +2024-11-23 01:46:23.191499: Current learning rate: 0.00131 +2024-11-23 01:46:41.961048: train_loss -0.8287 +2024-11-23 01:46:41.961284: val_loss -0.755 +2024-11-23 01:46:41.961360: Pseudo dice [0.8431] +2024-11-23 01:46:41.961437: Epoch time: 18.77 s +2024-11-23 01:46:42.880504: +2024-11-23 01:46:42.880750: Epoch 7163 +2024-11-23 01:46:42.880874: Current learning rate: 0.00131 +2024-11-23 01:47:00.586579: train_loss -0.8289 +2024-11-23 01:47:00.586869: val_loss -0.7469 +2024-11-23 01:47:00.586946: Pseudo dice [0.8341] +2024-11-23 01:47:00.587033: Epoch time: 17.71 s +2024-11-23 01:47:01.507617: +2024-11-23 01:47:01.507832: Epoch 7164 +2024-11-23 01:47:01.507944: Current learning rate: 0.00131 +2024-11-23 01:47:21.131534: train_loss -0.8171 +2024-11-23 01:47:21.131752: val_loss -0.7522 +2024-11-23 01:47:21.131829: Pseudo dice [0.8148] +2024-11-23 01:47:21.131905: Epoch time: 19.62 s +2024-11-23 01:47:22.453802: +2024-11-23 01:47:22.454058: Epoch 7165 +2024-11-23 01:47:22.454227: Current learning rate: 0.00131 +2024-11-23 01:47:41.140131: train_loss -0.8139 +2024-11-23 01:47:41.140379: val_loss -0.7656 +2024-11-23 01:47:41.140459: Pseudo dice [0.8305] +2024-11-23 01:47:41.140537: Epoch time: 18.69 s +2024-11-23 01:47:42.139615: +2024-11-23 01:47:42.139924: Epoch 7166 +2024-11-23 01:47:42.140040: Current learning rate: 0.00131 +2024-11-23 01:48:01.406986: train_loss -0.8285 +2024-11-23 01:48:01.407278: val_loss -0.7659 +2024-11-23 01:48:01.407354: Pseudo dice [0.8302] +2024-11-23 01:48:01.407438: Epoch time: 19.27 s +2024-11-23 01:48:02.326563: +2024-11-23 01:48:02.326785: Epoch 7167 +2024-11-23 01:48:02.326893: Current learning rate: 0.00131 +2024-11-23 01:48:20.297042: train_loss -0.8247 +2024-11-23 01:48:20.297256: val_loss -0.7749 +2024-11-23 01:48:20.297333: Pseudo dice [0.836] +2024-11-23 01:48:20.297463: Epoch time: 17.97 s +2024-11-23 01:48:21.219791: +2024-11-23 01:48:21.220025: Epoch 7168 +2024-11-23 01:48:21.220141: Current learning rate: 0.0013 +2024-11-23 01:48:40.297946: train_loss -0.8269 +2024-11-23 01:48:40.298166: val_loss -0.7528 +2024-11-23 01:48:40.298240: Pseudo dice [0.8392] +2024-11-23 01:48:40.298316: Epoch time: 19.08 s +2024-11-23 01:48:41.217211: +2024-11-23 01:48:41.217445: Epoch 7169 +2024-11-23 01:48:41.217559: Current learning rate: 0.0013 +2024-11-23 01:49:00.338873: train_loss -0.8258 +2024-11-23 01:49:00.339108: val_loss -0.7468 +2024-11-23 01:49:00.339189: Pseudo dice [0.8274] +2024-11-23 01:49:00.339266: Epoch time: 19.12 s +2024-11-23 01:49:01.273610: +2024-11-23 01:49:01.273858: Epoch 7170 +2024-11-23 01:49:01.273970: Current learning rate: 0.0013 +2024-11-23 01:49:21.190576: train_loss -0.8161 +2024-11-23 01:49:21.190817: val_loss -0.7365 +2024-11-23 01:49:21.190897: Pseudo dice [0.8256] +2024-11-23 01:49:21.190987: Epoch time: 19.92 s +2024-11-23 01:49:22.111556: +2024-11-23 01:49:22.111769: Epoch 7171 +2024-11-23 01:49:22.111879: Current learning rate: 0.0013 +2024-11-23 01:49:41.042509: train_loss -0.8223 +2024-11-23 01:49:41.042734: val_loss -0.756 +2024-11-23 01:49:41.042811: Pseudo dice [0.8219] +2024-11-23 01:49:41.042884: Epoch time: 18.93 s +2024-11-23 01:49:42.074854: +2024-11-23 01:49:42.075112: Epoch 7172 +2024-11-23 01:49:42.075222: Current learning rate: 0.0013 +2024-11-23 01:50:01.543684: train_loss -0.8232 +2024-11-23 01:50:01.543912: val_loss -0.7619 +2024-11-23 01:50:01.543987: Pseudo dice [0.8468] +2024-11-23 01:50:01.544088: Epoch time: 19.47 s +2024-11-23 01:50:02.463141: +2024-11-23 01:50:02.463339: Epoch 7173 +2024-11-23 01:50:02.463449: Current learning rate: 0.0013 +2024-11-23 01:50:20.446473: train_loss -0.8251 +2024-11-23 01:50:20.446686: val_loss -0.7769 +2024-11-23 01:50:20.446759: Pseudo dice [0.8499] +2024-11-23 01:50:20.446836: Epoch time: 17.98 s +2024-11-23 01:50:21.367512: +2024-11-23 01:50:21.367746: Epoch 7174 +2024-11-23 01:50:21.367872: Current learning rate: 0.0013 +2024-11-23 01:50:39.395092: train_loss -0.8263 +2024-11-23 01:50:39.395321: val_loss -0.77 +2024-11-23 01:50:39.395395: Pseudo dice [0.8355] +2024-11-23 01:50:39.395474: Epoch time: 18.03 s +2024-11-23 01:50:40.313433: +2024-11-23 01:50:40.313649: Epoch 7175 +2024-11-23 01:50:40.313766: Current learning rate: 0.00129 +2024-11-23 01:50:58.883904: train_loss -0.8229 +2024-11-23 01:50:58.884132: val_loss -0.7471 +2024-11-23 01:50:58.884205: Pseudo dice [0.8349] +2024-11-23 01:50:58.884282: Epoch time: 18.57 s +2024-11-23 01:50:59.802516: +2024-11-23 01:50:59.802706: Epoch 7176 +2024-11-23 01:50:59.802818: Current learning rate: 0.00129 +2024-11-23 01:51:18.756964: train_loss -0.8266 +2024-11-23 01:51:18.757182: val_loss -0.7611 +2024-11-23 01:51:18.757257: Pseudo dice [0.8275] +2024-11-23 01:51:18.757334: Epoch time: 18.96 s +2024-11-23 01:51:19.679927: +2024-11-23 01:51:19.680170: Epoch 7177 +2024-11-23 01:51:19.680285: Current learning rate: 0.00129 +2024-11-23 01:51:38.452729: train_loss -0.8278 +2024-11-23 01:51:38.453012: val_loss -0.7486 +2024-11-23 01:51:38.453089: Pseudo dice [0.8211] +2024-11-23 01:51:38.453172: Epoch time: 18.77 s +2024-11-23 01:51:39.373881: +2024-11-23 01:51:39.374138: Epoch 7178 +2024-11-23 01:51:39.374254: Current learning rate: 0.00129 +2024-11-23 01:51:58.117663: train_loss -0.8227 +2024-11-23 01:51:58.117887: val_loss -0.756 +2024-11-23 01:51:58.117963: Pseudo dice [0.8463] +2024-11-23 01:51:58.118045: Epoch time: 18.74 s +2024-11-23 01:51:59.140480: +2024-11-23 01:51:59.140697: Epoch 7179 +2024-11-23 01:51:59.140807: Current learning rate: 0.00129 +2024-11-23 01:52:17.425539: train_loss -0.8263 +2024-11-23 01:52:17.425767: val_loss -0.7569 +2024-11-23 01:52:17.425842: Pseudo dice [0.8189] +2024-11-23 01:52:17.425917: Epoch time: 18.29 s +2024-11-23 01:52:18.345578: +2024-11-23 01:52:18.345785: Epoch 7180 +2024-11-23 01:52:18.345897: Current learning rate: 0.00129 +2024-11-23 01:52:37.796505: train_loss -0.829 +2024-11-23 01:52:37.796724: val_loss -0.7454 +2024-11-23 01:52:37.796800: Pseudo dice [0.836] +2024-11-23 01:52:37.796884: Epoch time: 19.45 s +2024-11-23 01:52:38.713442: +2024-11-23 01:52:38.713715: Epoch 7181 +2024-11-23 01:52:38.713831: Current learning rate: 0.00129 +2024-11-23 01:52:56.489124: train_loss -0.8246 +2024-11-23 01:52:56.489347: val_loss -0.7857 +2024-11-23 01:52:56.489418: Pseudo dice [0.8332] +2024-11-23 01:52:56.489493: Epoch time: 17.78 s +2024-11-23 01:52:57.407946: +2024-11-23 01:52:57.408183: Epoch 7182 +2024-11-23 01:52:57.408297: Current learning rate: 0.00128 +2024-11-23 01:53:16.349020: train_loss -0.8234 +2024-11-23 01:53:16.349243: val_loss -0.7458 +2024-11-23 01:53:16.376611: Pseudo dice [0.843] +2024-11-23 01:53:16.376775: Epoch time: 18.94 s +2024-11-23 01:53:17.440534: +2024-11-23 01:53:17.440737: Epoch 7183 +2024-11-23 01:53:17.440847: Current learning rate: 0.00128 +2024-11-23 01:53:35.415398: train_loss -0.8145 +2024-11-23 01:53:35.415614: val_loss -0.7512 +2024-11-23 01:53:35.415692: Pseudo dice [0.8111] +2024-11-23 01:53:35.415770: Epoch time: 17.98 s +2024-11-23 01:53:36.408740: +2024-11-23 01:53:36.408953: Epoch 7184 +2024-11-23 01:53:36.409070: Current learning rate: 0.00128 +2024-11-23 01:53:55.238117: train_loss -0.8274 +2024-11-23 01:53:55.238366: val_loss -0.7778 +2024-11-23 01:53:55.238445: Pseudo dice [0.8426] +2024-11-23 01:53:55.238529: Epoch time: 18.83 s +2024-11-23 01:53:56.160538: +2024-11-23 01:53:56.160743: Epoch 7185 +2024-11-23 01:53:56.160855: Current learning rate: 0.00128 +2024-11-23 01:54:14.383267: train_loss -0.8204 +2024-11-23 01:54:14.383483: val_loss -0.7232 +2024-11-23 01:54:14.383560: Pseudo dice [0.8198] +2024-11-23 01:54:14.383638: Epoch time: 18.22 s +2024-11-23 01:54:15.306086: +2024-11-23 01:54:15.306365: Epoch 7186 +2024-11-23 01:54:15.306483: Current learning rate: 0.00128 +2024-11-23 01:54:34.153149: train_loss -0.8217 +2024-11-23 01:54:34.153505: val_loss -0.7341 +2024-11-23 01:54:34.153592: Pseudo dice [0.8359] +2024-11-23 01:54:34.153673: Epoch time: 18.85 s +2024-11-23 01:54:35.068635: +2024-11-23 01:54:35.068846: Epoch 7187 +2024-11-23 01:54:35.068960: Current learning rate: 0.00128 +2024-11-23 01:54:54.783877: train_loss -0.8207 +2024-11-23 01:54:54.784156: val_loss -0.7507 +2024-11-23 01:54:54.784236: Pseudo dice [0.8225] +2024-11-23 01:54:54.784321: Epoch time: 19.72 s +2024-11-23 01:54:56.312572: +2024-11-23 01:54:56.312793: Epoch 7188 +2024-11-23 01:54:56.312908: Current learning rate: 0.00128 +2024-11-23 01:55:14.547112: train_loss -0.8223 +2024-11-23 01:55:14.547356: val_loss -0.7728 +2024-11-23 01:55:14.547429: Pseudo dice [0.8412] +2024-11-23 01:55:14.547509: Epoch time: 18.24 s +2024-11-23 01:55:15.497553: +2024-11-23 01:55:15.497777: Epoch 7189 +2024-11-23 01:55:15.497898: Current learning rate: 0.00127 +2024-11-23 01:55:34.181188: train_loss -0.8238 +2024-11-23 01:55:34.181431: val_loss -0.7727 +2024-11-23 01:55:34.181508: Pseudo dice [0.8321] +2024-11-23 01:55:34.181582: Epoch time: 18.68 s +2024-11-23 01:55:35.210217: +2024-11-23 01:55:35.210532: Epoch 7190 +2024-11-23 01:55:35.210648: Current learning rate: 0.00127 +2024-11-23 01:55:53.428257: train_loss -0.831 +2024-11-23 01:55:53.428489: val_loss -0.7806 +2024-11-23 01:55:53.428563: Pseudo dice [0.8491] +2024-11-23 01:55:53.428642: Epoch time: 18.22 s +2024-11-23 01:55:54.347990: +2024-11-23 01:55:54.348220: Epoch 7191 +2024-11-23 01:55:54.348336: Current learning rate: 0.00127 +2024-11-23 01:56:13.918161: train_loss -0.8262 +2024-11-23 01:56:13.918389: val_loss -0.769 +2024-11-23 01:56:13.918464: Pseudo dice [0.8362] +2024-11-23 01:56:13.918547: Epoch time: 19.57 s +2024-11-23 01:56:14.839576: +2024-11-23 01:56:14.839778: Epoch 7192 +2024-11-23 01:56:14.839891: Current learning rate: 0.00127 +2024-11-23 01:56:32.719145: train_loss -0.8327 +2024-11-23 01:56:32.719366: val_loss -0.7548 +2024-11-23 01:56:32.719437: Pseudo dice [0.8539] +2024-11-23 01:56:32.719512: Epoch time: 17.88 s +2024-11-23 01:56:33.678661: +2024-11-23 01:56:33.678904: Epoch 7193 +2024-11-23 01:56:33.679042: Current learning rate: 0.00127 +2024-11-23 01:56:52.429828: train_loss -0.8267 +2024-11-23 01:56:52.430066: val_loss -0.769 +2024-11-23 01:56:52.430146: Pseudo dice [0.8453] +2024-11-23 01:56:52.430224: Epoch time: 18.75 s +2024-11-23 01:56:53.349478: +2024-11-23 01:56:53.349684: Epoch 7194 +2024-11-23 01:56:53.349798: Current learning rate: 0.00127 +2024-11-23 01:57:12.466908: train_loss -0.8199 +2024-11-23 01:57:12.467159: val_loss -0.7409 +2024-11-23 01:57:12.467235: Pseudo dice [0.8168] +2024-11-23 01:57:12.467314: Epoch time: 19.12 s +2024-11-23 01:57:13.455603: +2024-11-23 01:57:13.455819: Epoch 7195 +2024-11-23 01:57:13.455930: Current learning rate: 0.00127 +2024-11-23 01:57:33.491656: train_loss -0.8215 +2024-11-23 01:57:33.491905: val_loss -0.7508 +2024-11-23 01:57:33.491983: Pseudo dice [0.8241] +2024-11-23 01:57:33.492072: Epoch time: 20.04 s +2024-11-23 01:57:34.415128: +2024-11-23 01:57:34.415327: Epoch 7196 +2024-11-23 01:57:34.415464: Current learning rate: 0.00126 +2024-11-23 01:57:52.639730: train_loss -0.8164 +2024-11-23 01:57:52.639952: val_loss -0.7732 +2024-11-23 01:57:52.640035: Pseudo dice [0.8288] +2024-11-23 01:57:52.640110: Epoch time: 18.23 s +2024-11-23 01:57:53.704763: +2024-11-23 01:57:53.705060: Epoch 7197 +2024-11-23 01:57:53.705183: Current learning rate: 0.00126 +2024-11-23 01:58:11.514470: train_loss -0.8241 +2024-11-23 01:58:11.514697: val_loss -0.7676 +2024-11-23 01:58:11.514773: Pseudo dice [0.8326] +2024-11-23 01:58:11.514850: Epoch time: 17.81 s +2024-11-23 01:58:12.451386: +2024-11-23 01:58:12.451599: Epoch 7198 +2024-11-23 01:58:12.451714: Current learning rate: 0.00126 +2024-11-23 01:58:31.180545: train_loss -0.8268 +2024-11-23 01:58:31.185982: val_loss -0.7725 +2024-11-23 01:58:31.186122: Pseudo dice [0.844] +2024-11-23 01:58:31.186222: Epoch time: 18.73 s +2024-11-23 01:58:32.121199: +2024-11-23 01:58:32.121400: Epoch 7199 +2024-11-23 01:58:32.121515: Current learning rate: 0.00126 +2024-11-23 01:58:51.765225: train_loss -0.8272 +2024-11-23 01:58:51.765447: val_loss -0.783 +2024-11-23 01:58:51.765520: Pseudo dice [0.8374] +2024-11-23 01:58:51.765597: Epoch time: 19.64 s +2024-11-23 01:58:53.011413: +2024-11-23 01:58:53.011643: Epoch 7200 +2024-11-23 01:58:53.011759: Current learning rate: 0.00126 +2024-11-23 01:59:12.651512: train_loss -0.8266 +2024-11-23 01:59:12.651770: val_loss -0.7633 +2024-11-23 01:59:12.651846: Pseudo dice [0.8407] +2024-11-23 01:59:12.651924: Epoch time: 19.64 s +2024-11-23 01:59:13.607728: +2024-11-23 01:59:13.607954: Epoch 7201 +2024-11-23 01:59:13.608072: Current learning rate: 0.00126 +2024-11-23 01:59:33.002777: train_loss -0.8237 +2024-11-23 01:59:33.003049: val_loss -0.7735 +2024-11-23 01:59:33.003146: Pseudo dice [0.8282] +2024-11-23 01:59:33.003234: Epoch time: 19.4 s +2024-11-23 01:59:33.926549: +2024-11-23 01:59:33.926755: Epoch 7202 +2024-11-23 01:59:33.926867: Current learning rate: 0.00126 +2024-11-23 01:59:53.079502: train_loss -0.828 +2024-11-23 01:59:53.079718: val_loss -0.726 +2024-11-23 01:59:53.079792: Pseudo dice [0.8202] +2024-11-23 01:59:53.079867: Epoch time: 19.15 s +2024-11-23 01:59:54.000895: +2024-11-23 01:59:54.001123: Epoch 7203 +2024-11-23 01:59:54.001233: Current learning rate: 0.00125 +2024-11-23 02:00:12.694918: train_loss -0.8369 +2024-11-23 02:00:12.695140: val_loss -0.756 +2024-11-23 02:00:12.695216: Pseudo dice [0.8516] +2024-11-23 02:00:12.695294: Epoch time: 18.69 s +2024-11-23 02:00:13.698096: +2024-11-23 02:00:13.698321: Epoch 7204 +2024-11-23 02:00:13.698442: Current learning rate: 0.00125 +2024-11-23 02:00:33.147225: train_loss -0.8222 +2024-11-23 02:00:33.147443: val_loss -0.7725 +2024-11-23 02:00:33.147518: Pseudo dice [0.8489] +2024-11-23 02:00:33.147594: Epoch time: 19.45 s +2024-11-23 02:00:34.066359: +2024-11-23 02:00:34.066574: Epoch 7205 +2024-11-23 02:00:34.066692: Current learning rate: 0.00125 +2024-11-23 02:00:52.849680: train_loss -0.8238 +2024-11-23 02:00:52.849944: val_loss -0.775 +2024-11-23 02:00:52.850032: Pseudo dice [0.8367] +2024-11-23 02:00:52.850123: Epoch time: 18.78 s +2024-11-23 02:00:53.896042: +2024-11-23 02:00:53.896280: Epoch 7206 +2024-11-23 02:00:53.896391: Current learning rate: 0.00125 +2024-11-23 02:01:11.708491: train_loss -0.8252 +2024-11-23 02:01:11.708715: val_loss -0.7649 +2024-11-23 02:01:11.708789: Pseudo dice [0.8454] +2024-11-23 02:01:11.708867: Epoch time: 17.81 s +2024-11-23 02:01:12.838071: +2024-11-23 02:01:12.838274: Epoch 7207 +2024-11-23 02:01:12.838388: Current learning rate: 0.00125 +2024-11-23 02:01:31.567237: train_loss -0.8225 +2024-11-23 02:01:31.567459: val_loss -0.7601 +2024-11-23 02:01:31.567530: Pseudo dice [0.8384] +2024-11-23 02:01:31.567646: Epoch time: 18.73 s +2024-11-23 02:01:32.486388: +2024-11-23 02:01:32.486611: Epoch 7208 +2024-11-23 02:01:32.486726: Current learning rate: 0.00125 +2024-11-23 02:01:51.194920: train_loss -0.8276 +2024-11-23 02:01:51.195149: val_loss -0.7628 +2024-11-23 02:01:51.195265: Pseudo dice [0.8293] +2024-11-23 02:01:51.195348: Epoch time: 18.71 s +2024-11-23 02:01:52.125969: +2024-11-23 02:01:52.126244: Epoch 7209 +2024-11-23 02:01:52.126364: Current learning rate: 0.00125 +2024-11-23 02:02:10.900394: train_loss -0.8288 +2024-11-23 02:02:10.900633: val_loss -0.7647 +2024-11-23 02:02:10.902908: Pseudo dice [0.8483] +2024-11-23 02:02:10.903058: Epoch time: 18.78 s +2024-11-23 02:02:11.840566: +2024-11-23 02:02:11.840787: Epoch 7210 +2024-11-23 02:02:11.840903: Current learning rate: 0.00124 +2024-11-23 02:02:31.566563: train_loss -0.8255 +2024-11-23 02:02:31.567078: val_loss -0.8029 +2024-11-23 02:02:31.567175: Pseudo dice [0.8461] +2024-11-23 02:02:31.567254: Epoch time: 19.73 s +2024-11-23 02:02:32.486736: +2024-11-23 02:02:32.486957: Epoch 7211 +2024-11-23 02:02:32.487072: Current learning rate: 0.00124 +2024-11-23 02:02:51.981269: train_loss -0.8247 +2024-11-23 02:02:51.981491: val_loss -0.7725 +2024-11-23 02:02:51.983717: Pseudo dice [0.8483] +2024-11-23 02:02:51.983810: Epoch time: 19.5 s +2024-11-23 02:02:52.931203: +2024-11-23 02:02:52.931426: Epoch 7212 +2024-11-23 02:02:52.931540: Current learning rate: 0.00124 +2024-11-23 02:03:11.849133: train_loss -0.8294 +2024-11-23 02:03:11.849573: val_loss -0.774 +2024-11-23 02:03:11.849663: Pseudo dice [0.8316] +2024-11-23 02:03:11.849753: Epoch time: 18.92 s +2024-11-23 02:03:12.773247: +2024-11-23 02:03:12.773458: Epoch 7213 +2024-11-23 02:03:12.773568: Current learning rate: 0.00124 +2024-11-23 02:03:31.447273: train_loss -0.834 +2024-11-23 02:03:31.447496: val_loss -0.7599 +2024-11-23 02:03:31.447581: Pseudo dice [0.8467] +2024-11-23 02:03:31.447659: Epoch time: 18.67 s +2024-11-23 02:03:32.368449: +2024-11-23 02:03:32.368664: Epoch 7214 +2024-11-23 02:03:32.368785: Current learning rate: 0.00124 +2024-11-23 02:03:51.108685: train_loss -0.8257 +2024-11-23 02:03:51.108902: val_loss -0.7806 +2024-11-23 02:03:51.108975: Pseudo dice [0.8556] +2024-11-23 02:03:51.109060: Epoch time: 18.74 s +2024-11-23 02:03:52.020615: +2024-11-23 02:03:52.020843: Epoch 7215 +2024-11-23 02:03:52.020955: Current learning rate: 0.00124 +2024-11-23 02:04:11.120628: train_loss -0.8316 +2024-11-23 02:04:11.120836: val_loss -0.7662 +2024-11-23 02:04:11.120909: Pseudo dice [0.8232] +2024-11-23 02:04:11.120987: Epoch time: 19.1 s +2024-11-23 02:04:12.040537: +2024-11-23 02:04:12.040756: Epoch 7216 +2024-11-23 02:04:12.040870: Current learning rate: 0.00124 +2024-11-23 02:04:30.744743: train_loss -0.8262 +2024-11-23 02:04:30.744982: val_loss -0.786 +2024-11-23 02:04:30.747301: Pseudo dice [0.8432] +2024-11-23 02:04:30.747413: Epoch time: 18.7 s +2024-11-23 02:04:31.719740: +2024-11-23 02:04:31.720017: Epoch 7217 +2024-11-23 02:04:31.720143: Current learning rate: 0.00123 +2024-11-23 02:04:49.780477: train_loss -0.8375 +2024-11-23 02:04:49.780693: val_loss -0.7682 +2024-11-23 02:04:49.780768: Pseudo dice [0.8479] +2024-11-23 02:04:49.780846: Epoch time: 18.06 s +2024-11-23 02:04:50.700500: +2024-11-23 02:04:50.700694: Epoch 7218 +2024-11-23 02:04:50.700808: Current learning rate: 0.00123 +2024-11-23 02:05:09.745312: train_loss -0.8301 +2024-11-23 02:05:09.745532: val_loss -0.7521 +2024-11-23 02:05:09.745610: Pseudo dice [0.832] +2024-11-23 02:05:09.745690: Epoch time: 19.05 s +2024-11-23 02:05:10.820412: +2024-11-23 02:05:10.820640: Epoch 7219 +2024-11-23 02:05:10.820753: Current learning rate: 0.00123 +2024-11-23 02:05:31.304399: train_loss -0.8277 +2024-11-23 02:05:31.304624: val_loss -0.7657 +2024-11-23 02:05:31.304694: Pseudo dice [0.8424] +2024-11-23 02:05:31.304769: Epoch time: 20.48 s +2024-11-23 02:05:32.288484: +2024-11-23 02:05:32.288704: Epoch 7220 +2024-11-23 02:05:32.288820: Current learning rate: 0.00123 +2024-11-23 02:05:50.621934: train_loss -0.8227 +2024-11-23 02:05:50.622306: val_loss -0.7727 +2024-11-23 02:05:50.622429: Pseudo dice [0.8587] +2024-11-23 02:05:50.622519: Epoch time: 18.33 s +2024-11-23 02:05:51.543256: +2024-11-23 02:05:51.543452: Epoch 7221 +2024-11-23 02:05:51.543567: Current learning rate: 0.00123 +2024-11-23 02:06:10.566036: train_loss -0.8259 +2024-11-23 02:06:10.566259: val_loss -0.7548 +2024-11-23 02:06:10.566338: Pseudo dice [0.8518] +2024-11-23 02:06:10.566416: Epoch time: 19.02 s +2024-11-23 02:06:11.876225: +2024-11-23 02:06:11.876447: Epoch 7222 +2024-11-23 02:06:11.876574: Current learning rate: 0.00123 +2024-11-23 02:06:32.176902: train_loss -0.827 +2024-11-23 02:06:32.177157: val_loss -0.7541 +2024-11-23 02:06:32.177236: Pseudo dice [0.8352] +2024-11-23 02:06:32.177315: Epoch time: 20.3 s +2024-11-23 02:06:33.271052: +2024-11-23 02:06:33.271306: Epoch 7223 +2024-11-23 02:06:33.271418: Current learning rate: 0.00123 +2024-11-23 02:06:52.801290: train_loss -0.8193 +2024-11-23 02:06:52.801541: val_loss -0.7709 +2024-11-23 02:06:52.801617: Pseudo dice [0.8324] +2024-11-23 02:06:52.801757: Epoch time: 19.53 s +2024-11-23 02:06:53.720815: +2024-11-23 02:06:53.721042: Epoch 7224 +2024-11-23 02:06:53.721159: Current learning rate: 0.00122 +2024-11-23 02:07:12.626807: train_loss -0.832 +2024-11-23 02:07:12.627108: val_loss -0.7656 +2024-11-23 02:07:12.627188: Pseudo dice [0.8406] +2024-11-23 02:07:12.627267: Epoch time: 18.91 s +2024-11-23 02:07:13.550930: +2024-11-23 02:07:13.551201: Epoch 7225 +2024-11-23 02:07:13.551313: Current learning rate: 0.00122 +2024-11-23 02:07:32.567256: train_loss -0.8317 +2024-11-23 02:07:32.567481: val_loss -0.7743 +2024-11-23 02:07:32.567555: Pseudo dice [0.8456] +2024-11-23 02:07:32.567633: Epoch time: 19.02 s +2024-11-23 02:07:33.484998: +2024-11-23 02:07:33.485223: Epoch 7226 +2024-11-23 02:07:33.485338: Current learning rate: 0.00122 +2024-11-23 02:07:51.936215: train_loss -0.8305 +2024-11-23 02:07:51.936434: val_loss -0.7905 +2024-11-23 02:07:51.936507: Pseudo dice [0.8462] +2024-11-23 02:07:51.936581: Epoch time: 18.45 s +2024-11-23 02:07:52.846609: +2024-11-23 02:07:52.846823: Epoch 7227 +2024-11-23 02:07:52.846933: Current learning rate: 0.00122 +2024-11-23 02:08:11.551079: train_loss -0.832 +2024-11-23 02:08:11.551319: val_loss -0.7644 +2024-11-23 02:08:11.551397: Pseudo dice [0.8239] +2024-11-23 02:08:11.551482: Epoch time: 18.71 s +2024-11-23 02:08:12.465977: +2024-11-23 02:08:12.466218: Epoch 7228 +2024-11-23 02:08:12.466333: Current learning rate: 0.00122 +2024-11-23 02:08:32.302436: train_loss -0.8175 +2024-11-23 02:08:32.304821: val_loss -0.7673 +2024-11-23 02:08:32.304931: Pseudo dice [0.8456] +2024-11-23 02:08:32.305024: Epoch time: 19.84 s +2024-11-23 02:08:33.382518: +2024-11-23 02:08:33.382724: Epoch 7229 +2024-11-23 02:08:33.382834: Current learning rate: 0.00122 +2024-11-23 02:08:52.708620: train_loss -0.8192 +2024-11-23 02:08:52.708839: val_loss -0.7694 +2024-11-23 02:08:52.708918: Pseudo dice [0.8467] +2024-11-23 02:08:52.709003: Epoch time: 19.33 s +2024-11-23 02:08:53.626660: +2024-11-23 02:08:53.626960: Epoch 7230 +2024-11-23 02:08:53.627085: Current learning rate: 0.00122 +2024-11-23 02:09:12.890373: train_loss -0.8178 +2024-11-23 02:09:12.892786: val_loss -0.7733 +2024-11-23 02:09:12.892893: Pseudo dice [0.8559] +2024-11-23 02:09:12.892977: Epoch time: 19.26 s +2024-11-23 02:09:13.911296: +2024-11-23 02:09:13.911520: Epoch 7231 +2024-11-23 02:09:13.911638: Current learning rate: 0.00121 +2024-11-23 02:09:33.243465: train_loss -0.8257 +2024-11-23 02:09:33.243727: val_loss -0.7693 +2024-11-23 02:09:33.243854: Pseudo dice [0.8398] +2024-11-23 02:09:33.243943: Epoch time: 19.33 s +2024-11-23 02:09:34.161611: +2024-11-23 02:09:34.161861: Epoch 7232 +2024-11-23 02:09:34.161971: Current learning rate: 0.00121 +2024-11-23 02:09:52.310555: train_loss -0.8239 +2024-11-23 02:09:52.310781: val_loss -0.7562 +2024-11-23 02:09:52.310853: Pseudo dice [0.8525] +2024-11-23 02:09:52.310929: Epoch time: 18.15 s +2024-11-23 02:09:53.330371: +2024-11-23 02:09:53.330563: Epoch 7233 +2024-11-23 02:09:53.330673: Current learning rate: 0.00121 +2024-11-23 02:10:12.539611: train_loss -0.8252 +2024-11-23 02:10:12.539840: val_loss -0.7529 +2024-11-23 02:10:12.539913: Pseudo dice [0.8362] +2024-11-23 02:10:12.539986: Epoch time: 19.21 s +2024-11-23 02:10:13.472363: +2024-11-23 02:10:13.472591: Epoch 7234 +2024-11-23 02:10:13.472717: Current learning rate: 0.00121 +2024-11-23 02:10:31.992459: train_loss -0.8305 +2024-11-23 02:10:31.992696: val_loss -0.7535 +2024-11-23 02:10:31.992773: Pseudo dice [0.8264] +2024-11-23 02:10:31.992859: Epoch time: 18.52 s +2024-11-23 02:10:32.912724: +2024-11-23 02:10:32.913045: Epoch 7235 +2024-11-23 02:10:32.913161: Current learning rate: 0.00121 +2024-11-23 02:10:51.603956: train_loss -0.8203 +2024-11-23 02:10:51.604187: val_loss -0.7646 +2024-11-23 02:10:51.604260: Pseudo dice [0.8395] +2024-11-23 02:10:51.604335: Epoch time: 18.69 s +2024-11-23 02:10:52.631463: +2024-11-23 02:10:52.631675: Epoch 7236 +2024-11-23 02:10:52.631785: Current learning rate: 0.00121 +2024-11-23 02:11:10.640612: train_loss -0.8272 +2024-11-23 02:11:10.640837: val_loss -0.7515 +2024-11-23 02:11:10.640910: Pseudo dice [0.8296] +2024-11-23 02:11:10.640988: Epoch time: 18.01 s +2024-11-23 02:11:11.557314: +2024-11-23 02:11:11.557524: Epoch 7237 +2024-11-23 02:11:11.557641: Current learning rate: 0.00121 +2024-11-23 02:11:29.765550: train_loss -0.82 +2024-11-23 02:11:29.765780: val_loss -0.7614 +2024-11-23 02:11:29.765861: Pseudo dice [0.8472] +2024-11-23 02:11:29.765947: Epoch time: 18.21 s +2024-11-23 02:11:30.691899: +2024-11-23 02:11:30.692133: Epoch 7238 +2024-11-23 02:11:30.692257: Current learning rate: 0.0012 +2024-11-23 02:11:48.553693: train_loss -0.8295 +2024-11-23 02:11:48.553919: val_loss -0.7443 +2024-11-23 02:11:48.554003: Pseudo dice [0.8358] +2024-11-23 02:11:48.554081: Epoch time: 17.86 s +2024-11-23 02:11:49.477892: +2024-11-23 02:11:49.478127: Epoch 7239 +2024-11-23 02:11:49.478243: Current learning rate: 0.0012 +2024-11-23 02:12:08.503787: train_loss -0.821 +2024-11-23 02:12:08.504028: val_loss -0.7812 +2024-11-23 02:12:08.504103: Pseudo dice [0.841] +2024-11-23 02:12:08.504179: Epoch time: 19.03 s +2024-11-23 02:12:09.421328: +2024-11-23 02:12:09.421553: Epoch 7240 +2024-11-23 02:12:09.421676: Current learning rate: 0.0012 +2024-11-23 02:12:28.104185: train_loss -0.823 +2024-11-23 02:12:28.104478: val_loss -0.7413 +2024-11-23 02:12:28.104558: Pseudo dice [0.8157] +2024-11-23 02:12:28.104637: Epoch time: 18.68 s +2024-11-23 02:12:29.019749: +2024-11-23 02:12:29.019948: Epoch 7241 +2024-11-23 02:12:29.020066: Current learning rate: 0.0012 +2024-11-23 02:12:47.457659: train_loss -0.8209 +2024-11-23 02:12:47.457899: val_loss -0.7477 +2024-11-23 02:12:47.457975: Pseudo dice [0.8343] +2024-11-23 02:12:47.458129: Epoch time: 18.44 s +2024-11-23 02:12:48.372294: +2024-11-23 02:12:48.372506: Epoch 7242 +2024-11-23 02:12:48.372620: Current learning rate: 0.0012 +2024-11-23 02:13:08.338183: train_loss -0.8302 +2024-11-23 02:13:08.338406: val_loss -0.7585 +2024-11-23 02:13:08.338483: Pseudo dice [0.8378] +2024-11-23 02:13:08.338559: Epoch time: 19.97 s +2024-11-23 02:13:09.256893: +2024-11-23 02:13:09.257102: Epoch 7243 +2024-11-23 02:13:09.257221: Current learning rate: 0.0012 +2024-11-23 02:13:27.077419: train_loss -0.8215 +2024-11-23 02:13:27.077632: val_loss -0.7727 +2024-11-23 02:13:27.077709: Pseudo dice [0.8351] +2024-11-23 02:13:27.077785: Epoch time: 17.82 s +2024-11-23 02:13:27.988862: +2024-11-23 02:13:27.989178: Epoch 7244 +2024-11-23 02:13:27.989290: Current learning rate: 0.0012 +2024-11-23 02:13:46.532439: train_loss -0.8195 +2024-11-23 02:13:46.532660: val_loss -0.7667 +2024-11-23 02:13:46.532740: Pseudo dice [0.8225] +2024-11-23 02:13:46.532820: Epoch time: 18.54 s +2024-11-23 02:13:47.927924: +2024-11-23 02:13:47.928156: Epoch 7245 +2024-11-23 02:13:47.928306: Current learning rate: 0.0012 +2024-11-23 02:14:07.571697: train_loss -0.827 +2024-11-23 02:14:07.574119: val_loss -0.7626 +2024-11-23 02:14:07.574246: Pseudo dice [0.8394] +2024-11-23 02:14:07.574330: Epoch time: 19.64 s +2024-11-23 02:14:08.664406: +2024-11-23 02:14:08.664623: Epoch 7246 +2024-11-23 02:14:08.664740: Current learning rate: 0.00119 +2024-11-23 02:14:27.023474: train_loss -0.8213 +2024-11-23 02:14:27.023695: val_loss -0.769 +2024-11-23 02:14:27.023770: Pseudo dice [0.842] +2024-11-23 02:14:27.023846: Epoch time: 18.36 s +2024-11-23 02:14:27.938017: +2024-11-23 02:14:27.938241: Epoch 7247 +2024-11-23 02:14:27.938354: Current learning rate: 0.00119 +2024-11-23 02:14:46.272154: train_loss -0.8309 +2024-11-23 02:14:46.272365: val_loss -0.767 +2024-11-23 02:14:46.272437: Pseudo dice [0.8331] +2024-11-23 02:14:46.272511: Epoch time: 18.33 s +2024-11-23 02:14:47.185940: +2024-11-23 02:14:47.186185: Epoch 7248 +2024-11-23 02:14:47.186301: Current learning rate: 0.00119 +2024-11-23 02:15:06.645518: train_loss -0.8242 +2024-11-23 02:15:06.645754: val_loss -0.7523 +2024-11-23 02:15:06.645830: Pseudo dice [0.8285] +2024-11-23 02:15:06.645910: Epoch time: 19.46 s +2024-11-23 02:15:07.572155: +2024-11-23 02:15:07.572456: Epoch 7249 +2024-11-23 02:15:07.572577: Current learning rate: 0.00119 +2024-11-23 02:15:26.419095: train_loss -0.8326 +2024-11-23 02:15:26.419310: val_loss -0.7388 +2024-11-23 02:15:26.419383: Pseudo dice [0.8464] +2024-11-23 02:15:26.419458: Epoch time: 18.85 s +2024-11-23 02:15:27.674509: +2024-11-23 02:15:27.674727: Epoch 7250 +2024-11-23 02:15:27.674841: Current learning rate: 0.00119 +2024-11-23 02:15:47.386017: train_loss -0.824 +2024-11-23 02:15:47.386246: val_loss -0.7299 +2024-11-23 02:15:47.388497: Pseudo dice [0.8201] +2024-11-23 02:15:47.388641: Epoch time: 19.71 s +2024-11-23 02:15:48.571711: +2024-11-23 02:15:48.571915: Epoch 7251 +2024-11-23 02:15:48.572034: Current learning rate: 0.00119 +2024-11-23 02:16:07.415792: train_loss -0.8267 +2024-11-23 02:16:07.416024: val_loss -0.7655 +2024-11-23 02:16:07.416100: Pseudo dice [0.8382] +2024-11-23 02:16:07.416178: Epoch time: 18.84 s +2024-11-23 02:16:08.489369: +2024-11-23 02:16:08.489576: Epoch 7252 +2024-11-23 02:16:08.489692: Current learning rate: 0.00119 +2024-11-23 02:16:26.429504: train_loss -0.8321 +2024-11-23 02:16:26.429753: val_loss -0.7484 +2024-11-23 02:16:26.429830: Pseudo dice [0.8362] +2024-11-23 02:16:26.435145: Epoch time: 17.94 s +2024-11-23 02:16:27.619978: +2024-11-23 02:16:27.620188: Epoch 7253 +2024-11-23 02:16:27.620304: Current learning rate: 0.00118 +2024-11-23 02:16:46.385778: train_loss -0.8271 +2024-11-23 02:16:46.386028: val_loss -0.7599 +2024-11-23 02:16:46.386109: Pseudo dice [0.8391] +2024-11-23 02:16:46.386194: Epoch time: 18.77 s +2024-11-23 02:16:47.306886: +2024-11-23 02:16:47.307172: Epoch 7254 +2024-11-23 02:16:47.307284: Current learning rate: 0.00118 +2024-11-23 02:17:05.733900: train_loss -0.8247 +2024-11-23 02:17:05.734136: val_loss -0.7526 +2024-11-23 02:17:05.734268: Pseudo dice [0.8324] +2024-11-23 02:17:05.734351: Epoch time: 18.43 s +2024-11-23 02:17:06.694245: +2024-11-23 02:17:06.694454: Epoch 7255 +2024-11-23 02:17:06.694565: Current learning rate: 0.00118 +2024-11-23 02:17:25.662526: train_loss -0.8289 +2024-11-23 02:17:25.662834: val_loss -0.7733 +2024-11-23 02:17:25.662915: Pseudo dice [0.853] +2024-11-23 02:17:25.663013: Epoch time: 18.97 s +2024-11-23 02:17:26.579854: +2024-11-23 02:17:26.580081: Epoch 7256 +2024-11-23 02:17:26.580192: Current learning rate: 0.00118 +2024-11-23 02:17:45.735813: train_loss -0.8241 +2024-11-23 02:17:45.736033: val_loss -0.7625 +2024-11-23 02:17:45.736104: Pseudo dice [0.8261] +2024-11-23 02:17:45.736179: Epoch time: 19.16 s +2024-11-23 02:17:46.687149: +2024-11-23 02:17:46.687421: Epoch 7257 +2024-11-23 02:17:46.687537: Current learning rate: 0.00118 +2024-11-23 02:18:05.206472: train_loss -0.8201 +2024-11-23 02:18:05.206717: val_loss -0.7328 +2024-11-23 02:18:05.206795: Pseudo dice [0.8288] +2024-11-23 02:18:05.206871: Epoch time: 18.52 s +2024-11-23 02:18:06.118258: +2024-11-23 02:18:06.118486: Epoch 7258 +2024-11-23 02:18:06.118603: Current learning rate: 0.00118 +2024-11-23 02:18:25.793451: train_loss -0.8289 +2024-11-23 02:18:25.793689: val_loss -0.7381 +2024-11-23 02:18:25.793765: Pseudo dice [0.8398] +2024-11-23 02:18:25.793855: Epoch time: 19.68 s +2024-11-23 02:18:26.713287: +2024-11-23 02:18:26.713504: Epoch 7259 +2024-11-23 02:18:26.713619: Current learning rate: 0.00118 +2024-11-23 02:18:45.801087: train_loss -0.828 +2024-11-23 02:18:45.801316: val_loss -0.7609 +2024-11-23 02:18:45.806545: Pseudo dice [0.8351] +2024-11-23 02:18:45.806747: Epoch time: 19.09 s +2024-11-23 02:18:46.887865: +2024-11-23 02:18:46.888109: Epoch 7260 +2024-11-23 02:18:46.888226: Current learning rate: 0.00117 +2024-11-23 02:19:06.177598: train_loss -0.827 +2024-11-23 02:19:06.177821: val_loss -0.7482 +2024-11-23 02:19:06.177899: Pseudo dice [0.8205] +2024-11-23 02:19:06.177977: Epoch time: 19.29 s +2024-11-23 02:19:07.093338: +2024-11-23 02:19:07.093556: Epoch 7261 +2024-11-23 02:19:07.093693: Current learning rate: 0.00117 +2024-11-23 02:19:25.784746: train_loss -0.8303 +2024-11-23 02:19:25.784971: val_loss -0.7466 +2024-11-23 02:19:25.785054: Pseudo dice [0.8319] +2024-11-23 02:19:25.785129: Epoch time: 18.69 s +2024-11-23 02:19:26.708746: +2024-11-23 02:19:26.709025: Epoch 7262 +2024-11-23 02:19:26.709145: Current learning rate: 0.00117 +2024-11-23 02:19:44.874670: train_loss -0.8332 +2024-11-23 02:19:44.874953: val_loss -0.7426 +2024-11-23 02:19:44.875035: Pseudo dice [0.8361] +2024-11-23 02:19:44.875121: Epoch time: 18.17 s +2024-11-23 02:19:45.903798: +2024-11-23 02:19:45.904009: Epoch 7263 +2024-11-23 02:19:45.904121: Current learning rate: 0.00117 +2024-11-23 02:20:04.070149: train_loss -0.8305 +2024-11-23 02:20:04.070630: val_loss -0.7822 +2024-11-23 02:20:04.070711: Pseudo dice [0.8595] +2024-11-23 02:20:04.070786: Epoch time: 18.17 s +2024-11-23 02:20:04.989510: +2024-11-23 02:20:04.989730: Epoch 7264 +2024-11-23 02:20:04.989846: Current learning rate: 0.00117 +2024-11-23 02:20:23.977618: train_loss -0.8251 +2024-11-23 02:20:23.977843: val_loss -0.7102 +2024-11-23 02:20:23.977918: Pseudo dice [0.8238] +2024-11-23 02:20:23.983103: Epoch time: 18.99 s +2024-11-23 02:20:25.172391: +2024-11-23 02:20:25.172595: Epoch 7265 +2024-11-23 02:20:25.172711: Current learning rate: 0.00117 +2024-11-23 02:20:44.048601: train_loss -0.822 +2024-11-23 02:20:44.048815: val_loss -0.7717 +2024-11-23 02:20:44.048887: Pseudo dice [0.8343] +2024-11-23 02:20:44.048963: Epoch time: 18.88 s +2024-11-23 02:20:44.964881: +2024-11-23 02:20:44.965088: Epoch 7266 +2024-11-23 02:20:44.965200: Current learning rate: 0.00117 +2024-11-23 02:21:03.693736: train_loss -0.823 +2024-11-23 02:21:03.696094: val_loss -0.7706 +2024-11-23 02:21:03.696230: Pseudo dice [0.8419] +2024-11-23 02:21:03.696321: Epoch time: 18.73 s +2024-11-23 02:21:04.700012: +2024-11-23 02:21:04.700216: Epoch 7267 +2024-11-23 02:21:04.700328: Current learning rate: 0.00116 +2024-11-23 02:21:23.438410: train_loss -0.8293 +2024-11-23 02:21:23.438622: val_loss -0.771 +2024-11-23 02:21:23.438697: Pseudo dice [0.8368] +2024-11-23 02:21:23.438775: Epoch time: 18.74 s +2024-11-23 02:21:24.738465: +2024-11-23 02:21:24.738713: Epoch 7268 +2024-11-23 02:21:24.738834: Current learning rate: 0.00116 +2024-11-23 02:21:44.113170: train_loss -0.8246 +2024-11-23 02:21:44.113397: val_loss -0.7538 +2024-11-23 02:21:44.113473: Pseudo dice [0.8444] +2024-11-23 02:21:44.113548: Epoch time: 19.38 s +2024-11-23 02:21:45.026894: +2024-11-23 02:21:45.027107: Epoch 7269 +2024-11-23 02:21:45.027224: Current learning rate: 0.00116 +2024-11-23 02:22:03.814956: train_loss -0.8283 +2024-11-23 02:22:03.815191: val_loss -0.7532 +2024-11-23 02:22:03.815268: Pseudo dice [0.8357] +2024-11-23 02:22:03.815353: Epoch time: 18.79 s +2024-11-23 02:22:04.735376: +2024-11-23 02:22:04.735582: Epoch 7270 +2024-11-23 02:22:04.735696: Current learning rate: 0.00116 +2024-11-23 02:22:24.098366: train_loss -0.8362 +2024-11-23 02:22:24.098642: val_loss -0.7248 +2024-11-23 02:22:24.098721: Pseudo dice [0.823] +2024-11-23 02:22:24.098804: Epoch time: 19.36 s +2024-11-23 02:22:25.029179: +2024-11-23 02:22:25.029388: Epoch 7271 +2024-11-23 02:22:25.029499: Current learning rate: 0.00116 +2024-11-23 02:22:43.875892: train_loss -0.829 +2024-11-23 02:22:43.876114: val_loss -0.7464 +2024-11-23 02:22:43.892222: Pseudo dice [0.838] +2024-11-23 02:22:43.892377: Epoch time: 18.85 s +2024-11-23 02:22:44.817766: +2024-11-23 02:22:44.817993: Epoch 7272 +2024-11-23 02:22:44.818106: Current learning rate: 0.00116 +2024-11-23 02:23:03.570645: train_loss -0.8223 +2024-11-23 02:23:03.570865: val_loss -0.7879 +2024-11-23 02:23:03.570940: Pseudo dice [0.8372] +2024-11-23 02:23:03.571082: Epoch time: 18.75 s +2024-11-23 02:23:04.492220: +2024-11-23 02:23:04.492450: Epoch 7273 +2024-11-23 02:23:04.492573: Current learning rate: 0.00116 +2024-11-23 02:23:23.132455: train_loss -0.8307 +2024-11-23 02:23:23.132685: val_loss -0.7607 +2024-11-23 02:23:23.132760: Pseudo dice [0.8284] +2024-11-23 02:23:23.132843: Epoch time: 18.64 s +2024-11-23 02:23:24.059673: +2024-11-23 02:23:24.059877: Epoch 7274 +2024-11-23 02:23:24.059986: Current learning rate: 0.00115 +2024-11-23 02:23:42.136493: train_loss -0.8234 +2024-11-23 02:23:42.138008: val_loss -0.7762 +2024-11-23 02:23:42.138139: Pseudo dice [0.8482] +2024-11-23 02:23:42.138221: Epoch time: 18.08 s +2024-11-23 02:23:43.067013: +2024-11-23 02:23:43.067223: Epoch 7275 +2024-11-23 02:23:43.067336: Current learning rate: 0.00115 +2024-11-23 02:24:01.549688: train_loss -0.8269 +2024-11-23 02:24:01.549917: val_loss -0.7775 +2024-11-23 02:24:01.550004: Pseudo dice [0.8459] +2024-11-23 02:24:01.550086: Epoch time: 18.48 s +2024-11-23 02:24:02.466960: +2024-11-23 02:24:02.467255: Epoch 7276 +2024-11-23 02:24:02.467384: Current learning rate: 0.00115 +2024-11-23 02:24:21.523894: train_loss -0.829 +2024-11-23 02:24:21.524110: val_loss -0.747 +2024-11-23 02:24:21.524185: Pseudo dice [0.8112] +2024-11-23 02:24:21.524264: Epoch time: 19.06 s +2024-11-23 02:24:22.444260: +2024-11-23 02:24:22.444452: Epoch 7277 +2024-11-23 02:24:22.444565: Current learning rate: 0.00115 +2024-11-23 02:24:40.926764: train_loss -0.825 +2024-11-23 02:24:40.927013: val_loss -0.7526 +2024-11-23 02:24:40.927088: Pseudo dice [0.8284] +2024-11-23 02:24:40.927171: Epoch time: 18.48 s +2024-11-23 02:24:42.091854: +2024-11-23 02:24:42.092050: Epoch 7278 +2024-11-23 02:24:42.092165: Current learning rate: 0.00115 +2024-11-23 02:25:01.421078: train_loss -0.8255 +2024-11-23 02:25:01.421371: val_loss -0.7813 +2024-11-23 02:25:01.421453: Pseudo dice [0.8451] +2024-11-23 02:25:01.421532: Epoch time: 19.33 s +2024-11-23 02:25:02.371508: +2024-11-23 02:25:02.371709: Epoch 7279 +2024-11-23 02:25:02.371824: Current learning rate: 0.00115 +2024-11-23 02:25:22.026985: train_loss -0.8253 +2024-11-23 02:25:22.027213: val_loss -0.7468 +2024-11-23 02:25:22.027295: Pseudo dice [0.8296] +2024-11-23 02:25:22.027372: Epoch time: 19.66 s +2024-11-23 02:25:22.940455: +2024-11-23 02:25:22.940729: Epoch 7280 +2024-11-23 02:25:22.940837: Current learning rate: 0.00115 +2024-11-23 02:25:42.279347: train_loss -0.8318 +2024-11-23 02:25:42.279574: val_loss -0.7681 +2024-11-23 02:25:42.279648: Pseudo dice [0.8396] +2024-11-23 02:25:42.279729: Epoch time: 19.34 s +2024-11-23 02:25:43.300088: +2024-11-23 02:25:43.300325: Epoch 7281 +2024-11-23 02:25:43.300437: Current learning rate: 0.00114 +2024-11-23 02:26:01.999788: train_loss -0.8271 +2024-11-23 02:26:02.000012: val_loss -0.7621 +2024-11-23 02:26:02.000091: Pseudo dice [0.8486] +2024-11-23 02:26:02.000177: Epoch time: 18.7 s +2024-11-23 02:26:02.910012: +2024-11-23 02:26:02.910221: Epoch 7282 +2024-11-23 02:26:02.910327: Current learning rate: 0.00114 +2024-11-23 02:26:21.831553: train_loss -0.8225 +2024-11-23 02:26:21.831777: val_loss -0.7335 +2024-11-23 02:26:21.831851: Pseudo dice [0.8209] +2024-11-23 02:26:21.831925: Epoch time: 18.92 s +2024-11-23 02:26:22.739068: +2024-11-23 02:26:22.739283: Epoch 7283 +2024-11-23 02:26:22.739395: Current learning rate: 0.00114 +2024-11-23 02:26:41.123726: train_loss -0.8255 +2024-11-23 02:26:41.123945: val_loss -0.7739 +2024-11-23 02:26:41.124025: Pseudo dice [0.849] +2024-11-23 02:26:41.124109: Epoch time: 18.39 s +2024-11-23 02:26:42.067245: +2024-11-23 02:26:42.067459: Epoch 7284 +2024-11-23 02:26:42.067575: Current learning rate: 0.00114 +2024-11-23 02:27:01.290531: train_loss -0.8269 +2024-11-23 02:27:01.290759: val_loss -0.7684 +2024-11-23 02:27:01.290831: Pseudo dice [0.8266] +2024-11-23 02:27:01.290909: Epoch time: 19.22 s +2024-11-23 02:27:02.213745: +2024-11-23 02:27:02.213946: Epoch 7285 +2024-11-23 02:27:02.214064: Current learning rate: 0.00114 +2024-11-23 02:27:20.886819: train_loss -0.833 +2024-11-23 02:27:20.887031: val_loss -0.7806 +2024-11-23 02:27:20.896263: Pseudo dice [0.8431] +2024-11-23 02:27:20.896480: Epoch time: 18.67 s +2024-11-23 02:27:21.832170: +2024-11-23 02:27:21.832403: Epoch 7286 +2024-11-23 02:27:21.832511: Current learning rate: 0.00114 +2024-11-23 02:27:40.799061: train_loss -0.8211 +2024-11-23 02:27:40.799336: val_loss -0.78 +2024-11-23 02:27:40.799417: Pseudo dice [0.8342] +2024-11-23 02:27:40.799497: Epoch time: 18.97 s +2024-11-23 02:27:41.819933: +2024-11-23 02:27:41.820208: Epoch 7287 +2024-11-23 02:27:41.820321: Current learning rate: 0.00114 +2024-11-23 02:27:59.472519: train_loss -0.8239 +2024-11-23 02:27:59.472764: val_loss -0.7476 +2024-11-23 02:27:59.472839: Pseudo dice [0.8239] +2024-11-23 02:27:59.472921: Epoch time: 17.65 s +2024-11-23 02:28:00.570623: +2024-11-23 02:28:00.570923: Epoch 7288 +2024-11-23 02:28:00.571043: Current learning rate: 0.00113 +2024-11-23 02:28:18.774205: train_loss -0.8267 +2024-11-23 02:28:18.774423: val_loss -0.7508 +2024-11-23 02:28:18.774495: Pseudo dice [0.8392] +2024-11-23 02:28:18.774569: Epoch time: 18.2 s +2024-11-23 02:28:19.700574: +2024-11-23 02:28:19.700779: Epoch 7289 +2024-11-23 02:28:19.700891: Current learning rate: 0.00113 +2024-11-23 02:28:37.859864: train_loss -0.8327 +2024-11-23 02:28:37.860106: val_loss -0.7682 +2024-11-23 02:28:37.860184: Pseudo dice [0.8203] +2024-11-23 02:28:37.860273: Epoch time: 18.16 s +2024-11-23 02:28:38.776373: +2024-11-23 02:28:38.776582: Epoch 7290 +2024-11-23 02:28:38.776806: Current learning rate: 0.00113 +2024-11-23 02:28:58.168905: train_loss -0.8302 +2024-11-23 02:28:58.169134: val_loss -0.7461 +2024-11-23 02:28:58.169214: Pseudo dice [0.8511] +2024-11-23 02:28:58.169293: Epoch time: 19.39 s +2024-11-23 02:28:59.474798: +2024-11-23 02:28:59.475013: Epoch 7291 +2024-11-23 02:28:59.475129: Current learning rate: 0.00113 +2024-11-23 02:29:17.778749: train_loss -0.8247 +2024-11-23 02:29:17.779013: val_loss -0.7646 +2024-11-23 02:29:17.779118: Pseudo dice [0.8529] +2024-11-23 02:29:17.779210: Epoch time: 18.3 s +2024-11-23 02:29:18.691548: +2024-11-23 02:29:18.691753: Epoch 7292 +2024-11-23 02:29:18.691863: Current learning rate: 0.00113 +2024-11-23 02:29:37.154627: train_loss -0.8363 +2024-11-23 02:29:37.154847: val_loss -0.7334 +2024-11-23 02:29:37.154927: Pseudo dice [0.8345] +2024-11-23 02:29:37.155030: Epoch time: 18.46 s +2024-11-23 02:29:38.075747: +2024-11-23 02:29:38.075997: Epoch 7293 +2024-11-23 02:29:38.076114: Current learning rate: 0.00113 +2024-11-23 02:29:55.819928: train_loss -0.8253 +2024-11-23 02:29:55.820164: val_loss -0.7633 +2024-11-23 02:29:55.820240: Pseudo dice [0.8318] +2024-11-23 02:29:55.820316: Epoch time: 17.74 s +2024-11-23 02:29:56.849559: +2024-11-23 02:29:56.849780: Epoch 7294 +2024-11-23 02:29:56.849902: Current learning rate: 0.00112 +2024-11-23 02:30:16.071199: train_loss -0.8186 +2024-11-23 02:30:16.071450: val_loss -0.7443 +2024-11-23 02:30:16.071544: Pseudo dice [0.8488] +2024-11-23 02:30:16.071662: Epoch time: 19.22 s +2024-11-23 02:30:16.994717: +2024-11-23 02:30:16.994988: Epoch 7295 +2024-11-23 02:30:16.995103: Current learning rate: 0.00112 +2024-11-23 02:30:35.328557: train_loss -0.8298 +2024-11-23 02:30:35.328785: val_loss -0.7694 +2024-11-23 02:30:35.328862: Pseudo dice [0.8286] +2024-11-23 02:30:35.328941: Epoch time: 18.33 s +2024-11-23 02:30:36.357855: +2024-11-23 02:30:36.358164: Epoch 7296 +2024-11-23 02:30:36.358289: Current learning rate: 0.00112 +2024-11-23 02:30:55.321151: train_loss -0.8217 +2024-11-23 02:30:55.321384: val_loss -0.7576 +2024-11-23 02:30:55.323675: Pseudo dice [0.8446] +2024-11-23 02:30:55.323775: Epoch time: 18.96 s +2024-11-23 02:30:56.400398: +2024-11-23 02:30:56.400614: Epoch 7297 +2024-11-23 02:30:56.400727: Current learning rate: 0.00112 +2024-11-23 02:31:14.421806: train_loss -0.8275 +2024-11-23 02:31:14.422074: val_loss -0.7753 +2024-11-23 02:31:14.422156: Pseudo dice [0.8325] +2024-11-23 02:31:14.422236: Epoch time: 18.02 s +2024-11-23 02:31:15.342649: +2024-11-23 02:31:15.342872: Epoch 7298 +2024-11-23 02:31:15.342985: Current learning rate: 0.00112 +2024-11-23 02:31:33.542796: train_loss -0.8254 +2024-11-23 02:31:33.543033: val_loss -0.751 +2024-11-23 02:31:33.543175: Pseudo dice [0.835] +2024-11-23 02:31:33.543258: Epoch time: 18.2 s +2024-11-23 02:31:34.462730: +2024-11-23 02:31:34.462961: Epoch 7299 +2024-11-23 02:31:34.463098: Current learning rate: 0.00112 +2024-11-23 02:31:52.899574: train_loss -0.8291 +2024-11-23 02:31:52.899796: val_loss -0.776 +2024-11-23 02:31:52.899871: Pseudo dice [0.8439] +2024-11-23 02:31:52.899948: Epoch time: 18.44 s +2024-11-23 02:31:54.139964: +2024-11-23 02:31:54.140224: Epoch 7300 +2024-11-23 02:31:54.140340: Current learning rate: 0.00112 +2024-11-23 02:32:11.859149: train_loss -0.8333 +2024-11-23 02:32:11.859379: val_loss -0.7645 +2024-11-23 02:32:11.859453: Pseudo dice [0.8341] +2024-11-23 02:32:11.859529: Epoch time: 17.72 s +2024-11-23 02:32:12.774494: +2024-11-23 02:32:12.774707: Epoch 7301 +2024-11-23 02:32:12.774820: Current learning rate: 0.00111 +2024-11-23 02:32:31.671520: train_loss -0.8279 +2024-11-23 02:32:31.671767: val_loss -0.7763 +2024-11-23 02:32:31.671840: Pseudo dice [0.8331] +2024-11-23 02:32:31.671924: Epoch time: 18.9 s +2024-11-23 02:32:32.597187: +2024-11-23 02:32:32.597448: Epoch 7302 +2024-11-23 02:32:32.597564: Current learning rate: 0.00111 +2024-11-23 02:32:51.126590: train_loss -0.8249 +2024-11-23 02:32:51.126827: val_loss -0.771 +2024-11-23 02:32:51.126904: Pseudo dice [0.8359] +2024-11-23 02:32:51.126984: Epoch time: 18.53 s +2024-11-23 02:32:52.050743: +2024-11-23 02:32:52.050974: Epoch 7303 +2024-11-23 02:32:52.051097: Current learning rate: 0.00111 +2024-11-23 02:33:11.364351: train_loss -0.8267 +2024-11-23 02:33:11.364574: val_loss -0.7729 +2024-11-23 02:33:11.364649: Pseudo dice [0.8488] +2024-11-23 02:33:11.364727: Epoch time: 19.31 s +2024-11-23 02:33:12.287783: +2024-11-23 02:33:12.288027: Epoch 7304 +2024-11-23 02:33:12.288148: Current learning rate: 0.00111 +2024-11-23 02:33:31.236380: train_loss -0.8348 +2024-11-23 02:33:31.236620: val_loss -0.7396 +2024-11-23 02:33:31.236696: Pseudo dice [0.8244] +2024-11-23 02:33:31.236779: Epoch time: 18.95 s +2024-11-23 02:33:32.167785: +2024-11-23 02:33:32.168019: Epoch 7305 +2024-11-23 02:33:32.168132: Current learning rate: 0.00111 +2024-11-23 02:33:51.029674: train_loss -0.8349 +2024-11-23 02:33:51.029890: val_loss -0.7606 +2024-11-23 02:33:51.029967: Pseudo dice [0.8462] +2024-11-23 02:33:51.030058: Epoch time: 18.86 s +2024-11-23 02:33:51.950112: +2024-11-23 02:33:51.950338: Epoch 7306 +2024-11-23 02:33:51.950453: Current learning rate: 0.00111 +2024-11-23 02:34:10.572490: train_loss -0.8281 +2024-11-23 02:34:10.572717: val_loss -0.7848 +2024-11-23 02:34:10.572794: Pseudo dice [0.8682] +2024-11-23 02:34:10.572873: Epoch time: 18.62 s +2024-11-23 02:34:11.494955: +2024-11-23 02:34:11.495237: Epoch 7307 +2024-11-23 02:34:11.495355: Current learning rate: 0.00111 +2024-11-23 02:34:29.530258: train_loss -0.8292 +2024-11-23 02:34:29.530478: val_loss -0.7648 +2024-11-23 02:34:29.530554: Pseudo dice [0.845] +2024-11-23 02:34:29.530630: Epoch time: 18.04 s +2024-11-23 02:34:30.452422: +2024-11-23 02:34:30.452638: Epoch 7308 +2024-11-23 02:34:30.452748: Current learning rate: 0.0011 +2024-11-23 02:34:49.483938: train_loss -0.8298 +2024-11-23 02:34:49.484176: val_loss -0.7593 +2024-11-23 02:34:49.484251: Pseudo dice [0.8302] +2024-11-23 02:34:49.484336: Epoch time: 19.03 s +2024-11-23 02:34:50.405185: +2024-11-23 02:34:50.405382: Epoch 7309 +2024-11-23 02:34:50.405490: Current learning rate: 0.0011 +2024-11-23 02:35:09.356012: train_loss -0.8278 +2024-11-23 02:35:09.356235: val_loss -0.7649 +2024-11-23 02:35:09.356311: Pseudo dice [0.8216] +2024-11-23 02:35:09.356388: Epoch time: 18.95 s +2024-11-23 02:35:10.377765: +2024-11-23 02:35:10.377980: Epoch 7310 +2024-11-23 02:35:10.378101: Current learning rate: 0.0011 +2024-11-23 02:35:28.262323: train_loss -0.8383 +2024-11-23 02:35:28.262542: val_loss -0.7572 +2024-11-23 02:35:28.262617: Pseudo dice [0.8213] +2024-11-23 02:35:28.262693: Epoch time: 17.89 s +2024-11-23 02:35:29.184911: +2024-11-23 02:35:29.185126: Epoch 7311 +2024-11-23 02:35:29.185239: Current learning rate: 0.0011 +2024-11-23 02:35:48.923129: train_loss -0.8257 +2024-11-23 02:35:48.923348: val_loss -0.7742 +2024-11-23 02:35:48.923420: Pseudo dice [0.8372] +2024-11-23 02:35:48.923496: Epoch time: 19.74 s +2024-11-23 02:35:49.837903: +2024-11-23 02:35:49.838103: Epoch 7312 +2024-11-23 02:35:49.838217: Current learning rate: 0.0011 +2024-11-23 02:36:08.769136: train_loss -0.8261 +2024-11-23 02:36:08.769419: val_loss -0.7496 +2024-11-23 02:36:08.769499: Pseudo dice [0.8403] +2024-11-23 02:36:08.769587: Epoch time: 18.93 s +2024-11-23 02:36:09.766937: +2024-11-23 02:36:09.767321: Epoch 7313 +2024-11-23 02:36:09.767453: Current learning rate: 0.0011 +2024-11-23 02:36:28.199179: train_loss -0.8316 +2024-11-23 02:36:28.199450: val_loss -0.7465 +2024-11-23 02:36:28.199542: Pseudo dice [0.8571] +2024-11-23 02:36:28.199620: Epoch time: 18.41 s +2024-11-23 02:36:29.669773: +2024-11-23 02:36:29.669985: Epoch 7314 +2024-11-23 02:36:29.670101: Current learning rate: 0.0011 +2024-11-23 02:36:48.117455: train_loss -0.8282 +2024-11-23 02:36:48.117687: val_loss -0.7565 +2024-11-23 02:36:48.117782: Pseudo dice [0.8339] +2024-11-23 02:36:48.117857: Epoch time: 18.45 s +2024-11-23 02:36:49.035250: +2024-11-23 02:36:49.035495: Epoch 7315 +2024-11-23 02:36:49.035611: Current learning rate: 0.00109 +2024-11-23 02:37:07.686605: train_loss -0.8287 +2024-11-23 02:37:07.686863: val_loss -0.7567 +2024-11-23 02:37:07.686939: Pseudo dice [0.8257] +2024-11-23 02:37:07.687029: Epoch time: 18.65 s +2024-11-23 02:37:08.612258: +2024-11-23 02:37:08.612468: Epoch 7316 +2024-11-23 02:37:08.612729: Current learning rate: 0.00109 +2024-11-23 02:37:27.449331: train_loss -0.8262 +2024-11-23 02:37:27.449554: val_loss -0.7525 +2024-11-23 02:37:27.449634: Pseudo dice [0.8443] +2024-11-23 02:37:27.449713: Epoch time: 18.84 s +2024-11-23 02:37:28.369042: +2024-11-23 02:37:28.369258: Epoch 7317 +2024-11-23 02:37:28.369382: Current learning rate: 0.00109 +2024-11-23 02:37:47.903036: train_loss -0.8349 +2024-11-23 02:37:47.903255: val_loss -0.7391 +2024-11-23 02:37:47.903330: Pseudo dice [0.8308] +2024-11-23 02:37:47.903410: Epoch time: 19.53 s +2024-11-23 02:37:48.831361: +2024-11-23 02:37:48.831596: Epoch 7318 +2024-11-23 02:37:48.831716: Current learning rate: 0.00109 +2024-11-23 02:38:08.652348: train_loss -0.8256 +2024-11-23 02:38:08.652564: val_loss -0.7715 +2024-11-23 02:38:08.652639: Pseudo dice [0.8442] +2024-11-23 02:38:08.657902: Epoch time: 19.82 s +2024-11-23 02:38:09.598971: +2024-11-23 02:38:09.599175: Epoch 7319 +2024-11-23 02:38:09.599290: Current learning rate: 0.00109 +2024-11-23 02:38:27.550733: train_loss -0.8298 +2024-11-23 02:38:27.550969: val_loss -0.7396 +2024-11-23 02:38:27.551067: Pseudo dice [0.8362] +2024-11-23 02:38:27.551150: Epoch time: 17.95 s +2024-11-23 02:38:28.507719: +2024-11-23 02:38:28.507917: Epoch 7320 +2024-11-23 02:38:28.508037: Current learning rate: 0.00109 +2024-11-23 02:38:47.074318: train_loss -0.8276 +2024-11-23 02:38:47.074541: val_loss -0.7817 +2024-11-23 02:38:47.074616: Pseudo dice [0.8281] +2024-11-23 02:38:47.074697: Epoch time: 18.57 s +2024-11-23 02:38:47.993931: +2024-11-23 02:38:47.994147: Epoch 7321 +2024-11-23 02:38:47.994265: Current learning rate: 0.00109 +2024-11-23 02:39:07.035690: train_loss -0.8187 +2024-11-23 02:39:07.035932: val_loss -0.7481 +2024-11-23 02:39:07.036017: Pseudo dice [0.8171] +2024-11-23 02:39:07.036096: Epoch time: 19.04 s +2024-11-23 02:39:07.959318: +2024-11-23 02:39:07.959537: Epoch 7322 +2024-11-23 02:39:07.959656: Current learning rate: 0.00108 +2024-11-23 02:39:26.240149: train_loss -0.8283 +2024-11-23 02:39:26.240372: val_loss -0.7734 +2024-11-23 02:39:26.240510: Pseudo dice [0.8558] +2024-11-23 02:39:26.240597: Epoch time: 18.28 s +2024-11-23 02:39:27.164569: +2024-11-23 02:39:27.164798: Epoch 7323 +2024-11-23 02:39:27.164918: Current learning rate: 0.00108 +2024-11-23 02:39:45.037976: train_loss -0.8335 +2024-11-23 02:39:45.038225: val_loss -0.7502 +2024-11-23 02:39:45.038313: Pseudo dice [0.8232] +2024-11-23 02:39:45.038398: Epoch time: 17.87 s +2024-11-23 02:39:45.963978: +2024-11-23 02:39:45.964290: Epoch 7324 +2024-11-23 02:39:45.964410: Current learning rate: 0.00108 +2024-11-23 02:40:04.935157: train_loss -0.8248 +2024-11-23 02:40:04.935450: val_loss -0.7662 +2024-11-23 02:40:04.935527: Pseudo dice [0.83] +2024-11-23 02:40:04.935608: Epoch time: 18.97 s +2024-11-23 02:40:05.893728: +2024-11-23 02:40:05.893958: Epoch 7325 +2024-11-23 02:40:05.894092: Current learning rate: 0.00108 +2024-11-23 02:40:25.111251: train_loss -0.8341 +2024-11-23 02:40:25.111528: val_loss -0.7695 +2024-11-23 02:40:25.111602: Pseudo dice [0.8438] +2024-11-23 02:40:25.111685: Epoch time: 19.22 s +2024-11-23 02:40:26.036704: +2024-11-23 02:40:26.036909: Epoch 7326 +2024-11-23 02:40:26.037030: Current learning rate: 0.00108 +2024-11-23 02:40:44.055042: train_loss -0.8329 +2024-11-23 02:40:44.055282: val_loss -0.7696 +2024-11-23 02:40:44.055360: Pseudo dice [0.8454] +2024-11-23 02:40:44.055444: Epoch time: 18.02 s +2024-11-23 02:40:44.974764: +2024-11-23 02:40:44.974965: Epoch 7327 +2024-11-23 02:40:44.975085: Current learning rate: 0.00108 +2024-11-23 02:41:03.743231: train_loss -0.8246 +2024-11-23 02:41:03.743454: val_loss -0.7801 +2024-11-23 02:41:03.743527: Pseudo dice [0.8368] +2024-11-23 02:41:03.743608: Epoch time: 18.77 s +2024-11-23 02:41:04.661299: +2024-11-23 02:41:04.661509: Epoch 7328 +2024-11-23 02:41:04.661624: Current learning rate: 0.00108 +2024-11-23 02:41:23.465545: train_loss -0.8265 +2024-11-23 02:41:23.466142: val_loss -0.7626 +2024-11-23 02:41:23.466223: Pseudo dice [0.8238] +2024-11-23 02:41:23.466299: Epoch time: 18.81 s +2024-11-23 02:41:24.391425: +2024-11-23 02:41:24.391633: Epoch 7329 +2024-11-23 02:41:24.391743: Current learning rate: 0.00107 +2024-11-23 02:41:44.223510: train_loss -0.8249 +2024-11-23 02:41:44.223732: val_loss -0.7668 +2024-11-23 02:41:44.223811: Pseudo dice [0.8366] +2024-11-23 02:41:44.223893: Epoch time: 19.83 s +2024-11-23 02:41:45.144878: +2024-11-23 02:41:45.145118: Epoch 7330 +2024-11-23 02:41:45.145246: Current learning rate: 0.00107 +2024-11-23 02:42:02.454327: train_loss -0.828 +2024-11-23 02:42:02.454532: val_loss -0.7804 +2024-11-23 02:42:02.454606: Pseudo dice [0.8616] +2024-11-23 02:42:02.454696: Epoch time: 17.31 s +2024-11-23 02:42:03.369055: +2024-11-23 02:42:03.369256: Epoch 7331 +2024-11-23 02:42:03.369370: Current learning rate: 0.00107 +2024-11-23 02:42:21.033087: train_loss -0.8346 +2024-11-23 02:42:21.033315: val_loss -0.7333 +2024-11-23 02:42:21.033393: Pseudo dice [0.8307] +2024-11-23 02:42:21.033503: Epoch time: 17.66 s +2024-11-23 02:42:21.957623: +2024-11-23 02:42:21.957909: Epoch 7332 +2024-11-23 02:42:21.958042: Current learning rate: 0.00107 +2024-11-23 02:42:40.500364: train_loss -0.8251 +2024-11-23 02:42:40.500608: val_loss -0.7605 +2024-11-23 02:42:40.500690: Pseudo dice [0.8305] +2024-11-23 02:42:40.500771: Epoch time: 18.54 s +2024-11-23 02:42:41.423290: +2024-11-23 02:42:41.423488: Epoch 7333 +2024-11-23 02:42:41.423602: Current learning rate: 0.00107 +2024-11-23 02:43:00.343315: train_loss -0.8289 +2024-11-23 02:43:00.343546: val_loss -0.774 +2024-11-23 02:43:00.343620: Pseudo dice [0.8508] +2024-11-23 02:43:00.343704: Epoch time: 18.92 s +2024-11-23 02:43:01.259625: +2024-11-23 02:43:01.259816: Epoch 7334 +2024-11-23 02:43:01.259955: Current learning rate: 0.00107 +2024-11-23 02:43:18.945300: train_loss -0.8233 +2024-11-23 02:43:18.945519: val_loss -0.7445 +2024-11-23 02:43:18.945595: Pseudo dice [0.8277] +2024-11-23 02:43:18.945678: Epoch time: 17.69 s +2024-11-23 02:43:19.862920: +2024-11-23 02:43:19.863130: Epoch 7335 +2024-11-23 02:43:19.882562: Current learning rate: 0.00107 +2024-11-23 02:43:38.137139: train_loss -0.8263 +2024-11-23 02:43:38.137372: val_loss -0.7643 +2024-11-23 02:43:38.137448: Pseudo dice [0.8446] +2024-11-23 02:43:38.137529: Epoch time: 18.27 s +2024-11-23 02:43:39.160132: +2024-11-23 02:43:39.160326: Epoch 7336 +2024-11-23 02:43:39.160435: Current learning rate: 0.00106 +2024-11-23 02:43:58.509516: train_loss -0.8299 +2024-11-23 02:43:58.509756: val_loss -0.7537 +2024-11-23 02:43:58.509842: Pseudo dice [0.8347] +2024-11-23 02:43:58.509927: Epoch time: 19.35 s +2024-11-23 02:43:59.811924: +2024-11-23 02:43:59.812150: Epoch 7337 +2024-11-23 02:43:59.812262: Current learning rate: 0.00106 +2024-11-23 02:44:18.445712: train_loss -0.8268 +2024-11-23 02:44:18.445947: val_loss -0.7707 +2024-11-23 02:44:18.446031: Pseudo dice [0.8432] +2024-11-23 02:44:18.446108: Epoch time: 18.63 s +2024-11-23 02:44:19.365915: +2024-11-23 02:44:19.366133: Epoch 7338 +2024-11-23 02:44:19.366247: Current learning rate: 0.00106 +2024-11-23 02:44:37.895912: train_loss -0.8196 +2024-11-23 02:44:37.896149: val_loss -0.7463 +2024-11-23 02:44:37.896225: Pseudo dice [0.8209] +2024-11-23 02:44:37.896300: Epoch time: 18.53 s +2024-11-23 02:44:38.811721: +2024-11-23 02:44:38.811945: Epoch 7339 +2024-11-23 02:44:38.812066: Current learning rate: 0.00106 +2024-11-23 02:44:57.827117: train_loss -0.8221 +2024-11-23 02:44:57.829534: val_loss -0.758 +2024-11-23 02:44:57.829636: Pseudo dice [0.824] +2024-11-23 02:44:57.829711: Epoch time: 19.02 s +2024-11-23 02:44:58.810117: +2024-11-23 02:44:58.810328: Epoch 7340 +2024-11-23 02:44:58.810445: Current learning rate: 0.00106 +2024-11-23 02:45:16.435411: train_loss -0.827 +2024-11-23 02:45:16.435676: val_loss -0.7655 +2024-11-23 02:45:16.435755: Pseudo dice [0.8446] +2024-11-23 02:45:16.435846: Epoch time: 17.63 s +2024-11-23 02:45:17.437315: +2024-11-23 02:45:17.437515: Epoch 7341 +2024-11-23 02:45:17.437627: Current learning rate: 0.00106 +2024-11-23 02:45:34.528103: train_loss -0.8277 +2024-11-23 02:45:34.528317: val_loss -0.7372 +2024-11-23 02:45:34.528394: Pseudo dice [0.8459] +2024-11-23 02:45:34.528471: Epoch time: 17.09 s +2024-11-23 02:45:35.442981: +2024-11-23 02:45:35.443402: Epoch 7342 +2024-11-23 02:45:35.443523: Current learning rate: 0.00106 +2024-11-23 02:45:54.462647: train_loss -0.8247 +2024-11-23 02:45:54.462873: val_loss -0.7504 +2024-11-23 02:45:54.462949: Pseudo dice [0.8449] +2024-11-23 02:45:54.463032: Epoch time: 19.02 s +2024-11-23 02:45:55.375900: +2024-11-23 02:45:55.376233: Epoch 7343 +2024-11-23 02:45:55.376348: Current learning rate: 0.00105 +2024-11-23 02:46:14.597279: train_loss -0.8304 +2024-11-23 02:46:14.597574: val_loss -0.7398 +2024-11-23 02:46:14.597654: Pseudo dice [0.8103] +2024-11-23 02:46:14.597744: Epoch time: 19.22 s +2024-11-23 02:46:15.520394: +2024-11-23 02:46:15.520591: Epoch 7344 +2024-11-23 02:46:15.520705: Current learning rate: 0.00105 +2024-11-23 02:46:33.418314: train_loss -0.8303 +2024-11-23 02:46:33.418527: val_loss -0.7553 +2024-11-23 02:46:33.418602: Pseudo dice [0.831] +2024-11-23 02:46:33.418679: Epoch time: 17.9 s +2024-11-23 02:46:34.338440: +2024-11-23 02:46:34.338647: Epoch 7345 +2024-11-23 02:46:34.338764: Current learning rate: 0.00105 +2024-11-23 02:46:53.830059: train_loss -0.8215 +2024-11-23 02:46:53.830284: val_loss -0.7574 +2024-11-23 02:46:53.830359: Pseudo dice [0.8462] +2024-11-23 02:46:53.830438: Epoch time: 19.49 s +2024-11-23 02:46:54.743545: +2024-11-23 02:46:54.743783: Epoch 7346 +2024-11-23 02:46:54.743897: Current learning rate: 0.00105 +2024-11-23 02:47:13.386745: train_loss -0.8272 +2024-11-23 02:47:13.386976: val_loss -0.7837 +2024-11-23 02:47:13.387057: Pseudo dice [0.8677] +2024-11-23 02:47:13.387132: Epoch time: 18.64 s +2024-11-23 02:47:14.327467: +2024-11-23 02:47:14.327682: Epoch 7347 +2024-11-23 02:47:14.327791: Current learning rate: 0.00105 +2024-11-23 02:47:32.704676: train_loss -0.8315 +2024-11-23 02:47:32.704914: val_loss -0.7757 +2024-11-23 02:47:32.705004: Pseudo dice [0.846] +2024-11-23 02:47:32.725219: Epoch time: 18.38 s +2024-11-23 02:47:33.646604: +2024-11-23 02:47:33.646803: Epoch 7348 +2024-11-23 02:47:33.646925: Current learning rate: 0.00105 +2024-11-23 02:47:52.694357: train_loss -0.833 +2024-11-23 02:47:52.694582: val_loss -0.7686 +2024-11-23 02:47:52.694659: Pseudo dice [0.8386] +2024-11-23 02:47:52.694736: Epoch time: 19.05 s +2024-11-23 02:47:53.609418: +2024-11-23 02:47:53.609644: Epoch 7349 +2024-11-23 02:47:53.609756: Current learning rate: 0.00105 +2024-11-23 02:48:12.142731: train_loss -0.8268 +2024-11-23 02:48:12.142973: val_loss -0.7649 +2024-11-23 02:48:12.143056: Pseudo dice [0.8358] +2024-11-23 02:48:12.143130: Epoch time: 18.53 s +2024-11-23 02:48:13.436762: +2024-11-23 02:48:13.436975: Epoch 7350 +2024-11-23 02:48:13.437091: Current learning rate: 0.00104 +2024-11-23 02:48:31.929317: train_loss -0.8291 +2024-11-23 02:48:31.929631: val_loss -0.7803 +2024-11-23 02:48:31.929735: Pseudo dice [0.8551] +2024-11-23 02:48:31.929825: Epoch time: 18.49 s +2024-11-23 02:48:32.869174: +2024-11-23 02:48:32.869382: Epoch 7351 +2024-11-23 02:48:32.869496: Current learning rate: 0.00104 +2024-11-23 02:48:51.867533: train_loss -0.824 +2024-11-23 02:48:51.870719: val_loss -0.7798 +2024-11-23 02:48:51.870880: Pseudo dice [0.8502] +2024-11-23 02:48:51.870962: Epoch time: 19.0 s +2024-11-23 02:48:52.799988: +2024-11-23 02:48:52.800225: Epoch 7352 +2024-11-23 02:48:52.800344: Current learning rate: 0.00104 +2024-11-23 02:49:12.390773: train_loss -0.828 +2024-11-23 02:49:12.391006: val_loss -0.7742 +2024-11-23 02:49:12.391086: Pseudo dice [0.8521] +2024-11-23 02:49:12.393764: Epoch time: 19.59 s +2024-11-23 02:49:13.429644: +2024-11-23 02:49:13.429855: Epoch 7353 +2024-11-23 02:49:13.429971: Current learning rate: 0.00104 +2024-11-23 02:49:32.123712: train_loss -0.8282 +2024-11-23 02:49:32.123928: val_loss -0.7525 +2024-11-23 02:49:32.124009: Pseudo dice [0.8375] +2024-11-23 02:49:32.124088: Epoch time: 18.69 s +2024-11-23 02:49:33.046490: +2024-11-23 02:49:33.046690: Epoch 7354 +2024-11-23 02:49:33.046801: Current learning rate: 0.00104 +2024-11-23 02:49:52.160442: train_loss -0.8305 +2024-11-23 02:49:52.160754: val_loss -0.7556 +2024-11-23 02:49:52.160834: Pseudo dice [0.8334] +2024-11-23 02:49:52.160918: Epoch time: 19.11 s +2024-11-23 02:49:53.193072: +2024-11-23 02:49:53.193282: Epoch 7355 +2024-11-23 02:49:53.193397: Current learning rate: 0.00104 +2024-11-23 02:50:11.988054: train_loss -0.8291 +2024-11-23 02:50:11.988273: val_loss -0.7587 +2024-11-23 02:50:11.988350: Pseudo dice [0.8331] +2024-11-23 02:50:11.988425: Epoch time: 18.8 s +2024-11-23 02:50:12.906094: +2024-11-23 02:50:12.906299: Epoch 7356 +2024-11-23 02:50:12.906409: Current learning rate: 0.00104 +2024-11-23 02:50:31.305349: train_loss -0.8211 +2024-11-23 02:50:31.305568: val_loss -0.7648 +2024-11-23 02:50:31.305651: Pseudo dice [0.8267] +2024-11-23 02:50:31.305730: Epoch time: 18.4 s +2024-11-23 02:50:32.227928: +2024-11-23 02:50:32.228212: Epoch 7357 +2024-11-23 02:50:32.228329: Current learning rate: 0.00103 +2024-11-23 02:50:51.794516: train_loss -0.8302 +2024-11-23 02:50:51.794729: val_loss -0.7668 +2024-11-23 02:50:51.794803: Pseudo dice [0.842] +2024-11-23 02:50:51.794881: Epoch time: 19.57 s +2024-11-23 02:50:52.714209: +2024-11-23 02:50:52.714551: Epoch 7358 +2024-11-23 02:50:52.714665: Current learning rate: 0.00103 +2024-11-23 02:51:11.555473: train_loss -0.8351 +2024-11-23 02:51:11.555714: val_loss -0.7496 +2024-11-23 02:51:11.555788: Pseudo dice [0.838] +2024-11-23 02:51:11.555877: Epoch time: 18.84 s +2024-11-23 02:51:12.475653: +2024-11-23 02:51:12.475854: Epoch 7359 +2024-11-23 02:51:12.475961: Current learning rate: 0.00103 +2024-11-23 02:51:31.307117: train_loss -0.8291 +2024-11-23 02:51:31.307343: val_loss -0.7494 +2024-11-23 02:51:31.307422: Pseudo dice [0.8297] +2024-11-23 02:51:31.307499: Epoch time: 18.83 s +2024-11-23 02:51:32.232229: +2024-11-23 02:51:32.232543: Epoch 7360 +2024-11-23 02:51:32.232665: Current learning rate: 0.00103 +2024-11-23 02:51:51.160326: train_loss -0.8351 +2024-11-23 02:51:51.174692: val_loss -0.761 +2024-11-23 02:51:51.174867: Pseudo dice [0.8404] +2024-11-23 02:51:51.174951: Epoch time: 18.93 s +2024-11-23 02:51:52.092040: +2024-11-23 02:51:52.092258: Epoch 7361 +2024-11-23 02:51:52.092372: Current learning rate: 0.00103 +2024-11-23 02:52:10.734183: train_loss -0.8184 +2024-11-23 02:52:10.747341: val_loss -0.7789 +2024-11-23 02:52:10.747432: Pseudo dice [0.85] +2024-11-23 02:52:10.747533: Epoch time: 18.64 s +2024-11-23 02:52:11.697957: +2024-11-23 02:52:11.698166: Epoch 7362 +2024-11-23 02:52:11.698289: Current learning rate: 0.00103 +2024-11-23 02:52:30.815190: train_loss -0.8308 +2024-11-23 02:52:30.815422: val_loss -0.7591 +2024-11-23 02:52:30.815499: Pseudo dice [0.8387] +2024-11-23 02:52:30.815575: Epoch time: 19.12 s +2024-11-23 02:52:31.739656: +2024-11-23 02:52:31.739857: Epoch 7363 +2024-11-23 02:52:31.739969: Current learning rate: 0.00103 +2024-11-23 02:52:51.173568: train_loss -0.8223 +2024-11-23 02:52:51.173805: val_loss -0.7707 +2024-11-23 02:52:51.173883: Pseudo dice [0.8505] +2024-11-23 02:52:51.173960: Epoch time: 19.43 s +2024-11-23 02:52:52.092421: +2024-11-23 02:52:52.092623: Epoch 7364 +2024-11-23 02:52:52.092735: Current learning rate: 0.00102 +2024-11-23 02:53:11.803617: train_loss -0.829 +2024-11-23 02:53:11.803901: val_loss -0.749 +2024-11-23 02:53:11.803977: Pseudo dice [0.8237] +2024-11-23 02:53:11.804060: Epoch time: 19.71 s +2024-11-23 02:53:12.720519: +2024-11-23 02:53:12.720715: Epoch 7365 +2024-11-23 02:53:12.720824: Current learning rate: 0.00102 +2024-11-23 02:53:32.299854: train_loss -0.8305 +2024-11-23 02:53:32.300095: val_loss -0.7443 +2024-11-23 02:53:32.300173: Pseudo dice [0.8302] +2024-11-23 02:53:32.300261: Epoch time: 19.58 s +2024-11-23 02:53:33.246351: +2024-11-23 02:53:33.246540: Epoch 7366 +2024-11-23 02:53:33.246652: Current learning rate: 0.00102 +2024-11-23 02:53:52.502589: train_loss -0.8304 +2024-11-23 02:53:52.502835: val_loss -0.775 +2024-11-23 02:53:52.502973: Pseudo dice [0.8394] +2024-11-23 02:53:52.503055: Epoch time: 19.26 s +2024-11-23 02:53:53.431488: +2024-11-23 02:53:53.431720: Epoch 7367 +2024-11-23 02:53:53.431848: Current learning rate: 0.00102 +2024-11-23 02:54:12.376057: train_loss -0.833 +2024-11-23 02:54:12.376281: val_loss -0.7738 +2024-11-23 02:54:12.376353: Pseudo dice [0.8461] +2024-11-23 02:54:12.376429: Epoch time: 18.95 s +2024-11-23 02:54:13.296467: +2024-11-23 02:54:13.296678: Epoch 7368 +2024-11-23 02:54:13.296795: Current learning rate: 0.00102 +2024-11-23 02:54:32.816890: train_loss -0.8295 +2024-11-23 02:54:32.817138: val_loss -0.7721 +2024-11-23 02:54:32.817216: Pseudo dice [0.8454] +2024-11-23 02:54:32.817295: Epoch time: 19.52 s +2024-11-23 02:54:33.736518: +2024-11-23 02:54:33.736713: Epoch 7369 +2024-11-23 02:54:33.736827: Current learning rate: 0.00102 +2024-11-23 02:54:52.175142: train_loss -0.8336 +2024-11-23 02:54:52.175380: val_loss -0.7765 +2024-11-23 02:54:52.175458: Pseudo dice [0.848] +2024-11-23 02:54:52.175641: Epoch time: 18.44 s +2024-11-23 02:54:53.093945: +2024-11-23 02:54:53.094149: Epoch 7370 +2024-11-23 02:54:53.094267: Current learning rate: 0.00102 +2024-11-23 02:55:12.254170: train_loss -0.8292 +2024-11-23 02:55:12.254397: val_loss -0.7366 +2024-11-23 02:55:12.254472: Pseudo dice [0.8404] +2024-11-23 02:55:12.254553: Epoch time: 19.16 s +2024-11-23 02:55:13.545610: +2024-11-23 02:55:13.545829: Epoch 7371 +2024-11-23 02:55:13.545941: Current learning rate: 0.00101 +2024-11-23 02:55:33.145424: train_loss -0.8311 +2024-11-23 02:55:33.145665: val_loss -0.7568 +2024-11-23 02:55:33.145742: Pseudo dice [0.8465] +2024-11-23 02:55:33.145823: Epoch time: 19.6 s +2024-11-23 02:55:34.068717: +2024-11-23 02:55:34.068949: Epoch 7372 +2024-11-23 02:55:34.069073: Current learning rate: 0.00101 +2024-11-23 02:55:53.158008: train_loss -0.8273 +2024-11-23 02:55:53.158252: val_loss -0.7618 +2024-11-23 02:55:53.158328: Pseudo dice [0.8356] +2024-11-23 02:55:53.158411: Epoch time: 19.09 s +2024-11-23 02:55:54.086133: +2024-11-23 02:55:54.086391: Epoch 7373 +2024-11-23 02:55:54.086507: Current learning rate: 0.00101 +2024-11-23 02:56:12.336031: train_loss -0.8318 +2024-11-23 02:56:12.336346: val_loss -0.7626 +2024-11-23 02:56:12.336422: Pseudo dice [0.854] +2024-11-23 02:56:12.336514: Epoch time: 18.25 s +2024-11-23 02:56:13.258395: +2024-11-23 02:56:13.258622: Epoch 7374 +2024-11-23 02:56:13.258739: Current learning rate: 0.00101 +2024-11-23 02:56:31.430297: train_loss -0.8267 +2024-11-23 02:56:31.430530: val_loss -0.7785 +2024-11-23 02:56:31.430609: Pseudo dice [0.8442] +2024-11-23 02:56:31.430689: Epoch time: 18.17 s +2024-11-23 02:56:32.344633: +2024-11-23 02:56:32.344839: Epoch 7375 +2024-11-23 02:56:32.344955: Current learning rate: 0.00101 +2024-11-23 02:56:50.123749: train_loss -0.8331 +2024-11-23 02:56:50.124002: val_loss -0.7445 +2024-11-23 02:56:50.124082: Pseudo dice [0.8376] +2024-11-23 02:56:50.124163: Epoch time: 17.78 s +2024-11-23 02:56:51.042746: +2024-11-23 02:56:51.043060: Epoch 7376 +2024-11-23 02:56:51.043176: Current learning rate: 0.00101 +2024-11-23 02:57:09.510297: train_loss -0.8361 +2024-11-23 02:57:09.510535: val_loss -0.7704 +2024-11-23 02:57:09.510632: Pseudo dice [0.8596] +2024-11-23 02:57:09.510777: Epoch time: 18.47 s +2024-11-23 02:57:10.428456: +2024-11-23 02:57:10.428676: Epoch 7377 +2024-11-23 02:57:10.428792: Current learning rate: 0.00101 +2024-11-23 02:57:28.848792: train_loss -0.8265 +2024-11-23 02:57:28.849049: val_loss -0.744 +2024-11-23 02:57:28.849129: Pseudo dice [0.8398] +2024-11-23 02:57:28.849211: Epoch time: 18.42 s +2024-11-23 02:57:29.996824: +2024-11-23 02:57:29.997040: Epoch 7378 +2024-11-23 02:57:29.997161: Current learning rate: 0.001 +2024-11-23 02:57:47.120981: train_loss -0.8343 +2024-11-23 02:57:47.121215: val_loss -0.7698 +2024-11-23 02:57:47.121292: Pseudo dice [0.8391] +2024-11-23 02:57:47.121377: Epoch time: 17.12 s +2024-11-23 02:57:48.040325: +2024-11-23 02:57:48.040544: Epoch 7379 +2024-11-23 02:57:48.040660: Current learning rate: 0.001 +2024-11-23 02:58:07.551003: train_loss -0.8349 +2024-11-23 02:58:07.551220: val_loss -0.7584 +2024-11-23 02:58:07.551297: Pseudo dice [0.8489] +2024-11-23 02:58:07.551379: Epoch time: 19.51 s +2024-11-23 02:58:08.472121: +2024-11-23 02:58:08.474097: Epoch 7380 +2024-11-23 02:58:08.474220: Current learning rate: 0.001 +2024-11-23 02:58:26.881319: train_loss -0.8238 +2024-11-23 02:58:26.881596: val_loss -0.7476 +2024-11-23 02:58:26.881703: Pseudo dice [0.8325] +2024-11-23 02:58:26.881827: Epoch time: 18.41 s +2024-11-23 02:58:27.806095: +2024-11-23 02:58:27.806307: Epoch 7381 +2024-11-23 02:58:27.806426: Current learning rate: 0.001 +2024-11-23 02:58:46.870170: train_loss -0.8278 +2024-11-23 02:58:46.870392: val_loss -0.7555 +2024-11-23 02:58:46.870469: Pseudo dice [0.8354] +2024-11-23 02:58:46.870549: Epoch time: 19.06 s +2024-11-23 02:58:47.880827: +2024-11-23 02:58:47.881023: Epoch 7382 +2024-11-23 02:58:47.881134: Current learning rate: 0.001 +2024-11-23 02:59:07.014346: train_loss -0.8282 +2024-11-23 02:59:07.014575: val_loss -0.7342 +2024-11-23 02:59:07.014649: Pseudo dice [0.8377] +2024-11-23 02:59:07.014723: Epoch time: 19.13 s +2024-11-23 02:59:08.004781: +2024-11-23 02:59:08.005001: Epoch 7383 +2024-11-23 02:59:08.005120: Current learning rate: 0.001 +2024-11-23 02:59:27.035185: train_loss -0.8329 +2024-11-23 02:59:27.035410: val_loss -0.767 +2024-11-23 02:59:27.035484: Pseudo dice [0.835] +2024-11-23 02:59:27.035562: Epoch time: 19.03 s +2024-11-23 02:59:28.110762: +2024-11-23 02:59:28.111007: Epoch 7384 +2024-11-23 02:59:28.111165: Current learning rate: 0.001 +2024-11-23 02:59:46.990500: train_loss -0.8307 +2024-11-23 02:59:46.990741: val_loss -0.7777 +2024-11-23 02:59:46.990815: Pseudo dice [0.8338] +2024-11-23 02:59:46.990895: Epoch time: 18.88 s +2024-11-23 02:59:47.906746: +2024-11-23 02:59:47.906968: Epoch 7385 +2024-11-23 02:59:47.907090: Current learning rate: 0.00099 +2024-11-23 03:00:06.098618: train_loss -0.8327 +2024-11-23 03:00:06.098847: val_loss -0.7699 +2024-11-23 03:00:06.098928: Pseudo dice [0.8339] +2024-11-23 03:00:06.099014: Epoch time: 18.19 s +2024-11-23 03:00:07.041044: +2024-11-23 03:00:07.041278: Epoch 7386 +2024-11-23 03:00:07.041391: Current learning rate: 0.00099 +2024-11-23 03:00:25.421772: train_loss -0.8315 +2024-11-23 03:00:25.422012: val_loss -0.7886 +2024-11-23 03:00:25.422091: Pseudo dice [0.8458] +2024-11-23 03:00:25.422167: Epoch time: 18.38 s +2024-11-23 03:00:26.340204: +2024-11-23 03:00:26.340418: Epoch 7387 +2024-11-23 03:00:26.340526: Current learning rate: 0.00099 +2024-11-23 03:00:43.695385: train_loss -0.8334 +2024-11-23 03:00:43.695645: val_loss -0.7568 +2024-11-23 03:00:43.695723: Pseudo dice [0.8376] +2024-11-23 03:00:43.698012: Epoch time: 17.36 s +2024-11-23 03:00:44.868228: +2024-11-23 03:00:44.868513: Epoch 7388 +2024-11-23 03:00:44.868625: Current learning rate: 0.00099 +2024-11-23 03:01:03.077098: train_loss -0.8289 +2024-11-23 03:01:03.077306: val_loss -0.767 +2024-11-23 03:01:03.077380: Pseudo dice [0.8311] +2024-11-23 03:01:03.077456: Epoch time: 18.21 s +2024-11-23 03:01:03.998808: +2024-11-23 03:01:03.999105: Epoch 7389 +2024-11-23 03:01:03.999228: Current learning rate: 0.00099 +2024-11-23 03:01:22.984062: train_loss -0.8302 +2024-11-23 03:01:22.984283: val_loss -0.7632 +2024-11-23 03:01:22.984357: Pseudo dice [0.8254] +2024-11-23 03:01:22.984435: Epoch time: 18.99 s +2024-11-23 03:01:23.917200: +2024-11-23 03:01:23.917467: Epoch 7390 +2024-11-23 03:01:23.917587: Current learning rate: 0.00099 +2024-11-23 03:01:42.746504: train_loss -0.8284 +2024-11-23 03:01:42.746733: val_loss -0.7666 +2024-11-23 03:01:42.746841: Pseudo dice [0.8417] +2024-11-23 03:01:42.746920: Epoch time: 18.83 s +2024-11-23 03:01:43.666132: +2024-11-23 03:01:43.666341: Epoch 7391 +2024-11-23 03:01:43.666454: Current learning rate: 0.00098 +2024-11-23 03:02:02.117759: train_loss -0.8371 +2024-11-23 03:02:02.117987: val_loss -0.7598 +2024-11-23 03:02:02.118069: Pseudo dice [0.8232] +2024-11-23 03:02:02.118151: Epoch time: 18.45 s +2024-11-23 03:02:03.041398: +2024-11-23 03:02:03.041627: Epoch 7392 +2024-11-23 03:02:03.041739: Current learning rate: 0.00098 +2024-11-23 03:02:22.930403: train_loss -0.8225 +2024-11-23 03:02:22.930635: val_loss -0.7425 +2024-11-23 03:02:22.930709: Pseudo dice [0.823] +2024-11-23 03:02:22.930788: Epoch time: 19.89 s +2024-11-23 03:02:23.845448: +2024-11-23 03:02:23.845645: Epoch 7393 +2024-11-23 03:02:23.845758: Current learning rate: 0.00098 +2024-11-23 03:02:41.138725: train_loss -0.8281 +2024-11-23 03:02:41.138948: val_loss -0.7675 +2024-11-23 03:02:41.139036: Pseudo dice [0.84] +2024-11-23 03:02:41.139111: Epoch time: 17.29 s +2024-11-23 03:02:42.425379: +2024-11-23 03:02:42.425614: Epoch 7394 +2024-11-23 03:02:42.425730: Current learning rate: 0.00098 +2024-11-23 03:03:01.072340: train_loss -0.8309 +2024-11-23 03:03:01.072616: val_loss -0.7406 +2024-11-23 03:03:01.072702: Pseudo dice [0.8309] +2024-11-23 03:03:01.072798: Epoch time: 18.65 s +2024-11-23 03:03:01.997940: +2024-11-23 03:03:01.998157: Epoch 7395 +2024-11-23 03:03:01.998273: Current learning rate: 0.00098 +2024-11-23 03:03:19.202897: train_loss -0.8358 +2024-11-23 03:03:19.203140: val_loss -0.7819 +2024-11-23 03:03:19.203219: Pseudo dice [0.8573] +2024-11-23 03:03:19.203298: Epoch time: 17.21 s +2024-11-23 03:03:20.116030: +2024-11-23 03:03:20.116234: Epoch 7396 +2024-11-23 03:03:20.116350: Current learning rate: 0.00098 +2024-11-23 03:03:38.838044: train_loss -0.8298 +2024-11-23 03:03:38.838283: val_loss -0.77 +2024-11-23 03:03:38.838358: Pseudo dice [0.8402] +2024-11-23 03:03:38.838439: Epoch time: 18.72 s +2024-11-23 03:03:39.756439: +2024-11-23 03:03:39.756635: Epoch 7397 +2024-11-23 03:03:39.756746: Current learning rate: 0.00098 +2024-11-23 03:03:58.684736: train_loss -0.829 +2024-11-23 03:03:58.684968: val_loss -0.7844 +2024-11-23 03:03:58.685051: Pseudo dice [0.8383] +2024-11-23 03:03:58.685133: Epoch time: 18.93 s +2024-11-23 03:03:59.610347: +2024-11-23 03:03:59.610583: Epoch 7398 +2024-11-23 03:03:59.610698: Current learning rate: 0.00097 +2024-11-23 03:04:17.767395: train_loss -0.8334 +2024-11-23 03:04:17.767694: val_loss -0.7556 +2024-11-23 03:04:17.767776: Pseudo dice [0.8444] +2024-11-23 03:04:17.767867: Epoch time: 18.16 s +2024-11-23 03:04:18.686277: +2024-11-23 03:04:18.686475: Epoch 7399 +2024-11-23 03:04:18.686590: Current learning rate: 0.00097 +2024-11-23 03:04:37.645424: train_loss -0.8237 +2024-11-23 03:04:37.645720: val_loss -0.7539 +2024-11-23 03:04:37.645793: Pseudo dice [0.8427] +2024-11-23 03:04:37.645875: Epoch time: 18.96 s +2024-11-23 03:04:38.900824: +2024-11-23 03:04:38.901040: Epoch 7400 +2024-11-23 03:04:38.901154: Current learning rate: 0.00097 +2024-11-23 03:04:57.432604: train_loss -0.8333 +2024-11-23 03:04:57.432837: val_loss -0.7568 +2024-11-23 03:04:57.432914: Pseudo dice [0.8421] +2024-11-23 03:04:57.433002: Epoch time: 18.53 s +2024-11-23 03:04:58.571241: +2024-11-23 03:04:58.571465: Epoch 7401 +2024-11-23 03:04:58.571578: Current learning rate: 0.00097 +2024-11-23 03:05:18.554172: train_loss -0.8353 +2024-11-23 03:05:18.554417: val_loss -0.7651 +2024-11-23 03:05:18.554494: Pseudo dice [0.8316] +2024-11-23 03:05:18.554583: Epoch time: 19.98 s +2024-11-23 03:05:19.476872: +2024-11-23 03:05:19.477111: Epoch 7402 +2024-11-23 03:05:19.477235: Current learning rate: 0.00097 +2024-11-23 03:05:37.798445: train_loss -0.8308 +2024-11-23 03:05:37.798687: val_loss -0.7627 +2024-11-23 03:05:37.798766: Pseudo dice [0.845] +2024-11-23 03:05:37.798845: Epoch time: 18.32 s +2024-11-23 03:05:38.718211: +2024-11-23 03:05:38.718410: Epoch 7403 +2024-11-23 03:05:38.718528: Current learning rate: 0.00097 +2024-11-23 03:05:57.694709: train_loss -0.8315 +2024-11-23 03:05:57.694936: val_loss -0.7557 +2024-11-23 03:05:57.695022: Pseudo dice [0.833] +2024-11-23 03:05:57.695107: Epoch time: 18.98 s +2024-11-23 03:05:58.666409: +2024-11-23 03:05:58.666645: Epoch 7404 +2024-11-23 03:05:58.666758: Current learning rate: 0.00097 +2024-11-23 03:06:16.954107: train_loss -0.8336 +2024-11-23 03:06:16.954326: val_loss -0.7625 +2024-11-23 03:06:16.954417: Pseudo dice [0.8448] +2024-11-23 03:06:16.954548: Epoch time: 18.29 s +2024-11-23 03:06:17.870662: +2024-11-23 03:06:17.870858: Epoch 7405 +2024-11-23 03:06:17.870968: Current learning rate: 0.00096 +2024-11-23 03:06:36.549174: train_loss -0.8334 +2024-11-23 03:06:36.549417: val_loss -0.7499 +2024-11-23 03:06:36.549495: Pseudo dice [0.8222] +2024-11-23 03:06:36.549577: Epoch time: 18.68 s +2024-11-23 03:06:37.489888: +2024-11-23 03:06:37.490108: Epoch 7406 +2024-11-23 03:06:37.490221: Current learning rate: 0.00096 +2024-11-23 03:06:56.339041: train_loss -0.831 +2024-11-23 03:06:56.339269: val_loss -0.7557 +2024-11-23 03:06:56.339344: Pseudo dice [0.8285] +2024-11-23 03:06:56.339422: Epoch time: 18.85 s +2024-11-23 03:06:57.258848: +2024-11-23 03:06:57.259068: Epoch 7407 +2024-11-23 03:06:57.259182: Current learning rate: 0.00096 +2024-11-23 03:07:15.959904: train_loss -0.8347 +2024-11-23 03:07:15.960148: val_loss -0.748 +2024-11-23 03:07:15.960227: Pseudo dice [0.8459] +2024-11-23 03:07:15.960306: Epoch time: 18.7 s +2024-11-23 03:07:16.893230: +2024-11-23 03:07:16.893581: Epoch 7408 +2024-11-23 03:07:16.893703: Current learning rate: 0.00096 +2024-11-23 03:07:36.236682: train_loss -0.8335 +2024-11-23 03:07:36.236935: val_loss -0.7544 +2024-11-23 03:07:36.237016: Pseudo dice [0.8318] +2024-11-23 03:07:36.237103: Epoch time: 19.34 s +2024-11-23 03:07:37.254162: +2024-11-23 03:07:37.254384: Epoch 7409 +2024-11-23 03:07:37.254503: Current learning rate: 0.00096 +2024-11-23 03:07:55.807441: train_loss -0.8317 +2024-11-23 03:07:55.807725: val_loss -0.7763 +2024-11-23 03:07:55.807803: Pseudo dice [0.8402] +2024-11-23 03:07:55.807879: Epoch time: 18.55 s +2024-11-23 03:07:56.729534: +2024-11-23 03:07:56.729768: Epoch 7410 +2024-11-23 03:07:56.729890: Current learning rate: 0.00096 +2024-11-23 03:08:14.623397: train_loss -0.838 +2024-11-23 03:08:14.623695: val_loss -0.7489 +2024-11-23 03:08:14.623773: Pseudo dice [0.8339] +2024-11-23 03:08:14.623852: Epoch time: 17.89 s +2024-11-23 03:08:15.545352: +2024-11-23 03:08:15.545547: Epoch 7411 +2024-11-23 03:08:15.545662: Current learning rate: 0.00096 +2024-11-23 03:08:33.538818: train_loss -0.8319 +2024-11-23 03:08:33.539045: val_loss -0.7676 +2024-11-23 03:08:33.539147: Pseudo dice [0.8399] +2024-11-23 03:08:33.539229: Epoch time: 17.99 s +2024-11-23 03:08:34.462831: +2024-11-23 03:08:34.463060: Epoch 7412 +2024-11-23 03:08:34.463178: Current learning rate: 0.00095 +2024-11-23 03:08:51.393007: train_loss -0.8361 +2024-11-23 03:08:51.393246: val_loss -0.7828 +2024-11-23 03:08:51.393322: Pseudo dice [0.8419] +2024-11-23 03:08:51.393404: Epoch time: 16.93 s +2024-11-23 03:08:52.307533: +2024-11-23 03:08:52.307736: Epoch 7413 +2024-11-23 03:08:52.307852: Current learning rate: 0.00095 +2024-11-23 03:09:11.452546: train_loss -0.8336 +2024-11-23 03:09:11.452759: val_loss -0.7713 +2024-11-23 03:09:11.452831: Pseudo dice [0.8418] +2024-11-23 03:09:11.452907: Epoch time: 19.15 s +2024-11-23 03:09:12.372345: +2024-11-23 03:09:12.372556: Epoch 7414 +2024-11-23 03:09:12.372669: Current learning rate: 0.00095 +2024-11-23 03:09:30.592284: train_loss -0.8388 +2024-11-23 03:09:30.592511: val_loss -0.7621 +2024-11-23 03:09:30.592584: Pseudo dice [0.8386] +2024-11-23 03:09:30.592660: Epoch time: 18.22 s +2024-11-23 03:09:31.508668: +2024-11-23 03:09:31.508870: Epoch 7415 +2024-11-23 03:09:31.508988: Current learning rate: 0.00095 +2024-11-23 03:09:49.572937: train_loss -0.8376 +2024-11-23 03:09:49.573247: val_loss -0.78 +2024-11-23 03:09:49.573326: Pseudo dice [0.8458] +2024-11-23 03:09:49.573413: Epoch time: 18.07 s +2024-11-23 03:09:50.502113: +2024-11-23 03:09:50.502305: Epoch 7416 +2024-11-23 03:09:50.502413: Current learning rate: 0.00095 +2024-11-23 03:10:09.012932: train_loss -0.8346 +2024-11-23 03:10:09.013167: val_loss -0.736 +2024-11-23 03:10:09.013243: Pseudo dice [0.8294] +2024-11-23 03:10:09.013321: Epoch time: 18.51 s +2024-11-23 03:10:10.422087: +2024-11-23 03:10:10.422319: Epoch 7417 +2024-11-23 03:10:10.422434: Current learning rate: 0.00095 +2024-11-23 03:10:29.276469: train_loss -0.8316 +2024-11-23 03:10:29.276709: val_loss -0.7725 +2024-11-23 03:10:29.276782: Pseudo dice [0.837] +2024-11-23 03:10:29.276858: Epoch time: 18.86 s +2024-11-23 03:10:30.206996: +2024-11-23 03:10:30.207227: Epoch 7418 +2024-11-23 03:10:30.207341: Current learning rate: 0.00095 +2024-11-23 03:10:48.225585: train_loss -0.837 +2024-11-23 03:10:48.225821: val_loss -0.7797 +2024-11-23 03:10:48.225898: Pseudo dice [0.8453] +2024-11-23 03:10:48.225980: Epoch time: 18.02 s +2024-11-23 03:10:49.248615: +2024-11-23 03:10:49.248882: Epoch 7419 +2024-11-23 03:10:49.249037: Current learning rate: 0.00094 +2024-11-23 03:11:07.583130: train_loss -0.8316 +2024-11-23 03:11:07.583368: val_loss -0.7646 +2024-11-23 03:11:07.583446: Pseudo dice [0.8477] +2024-11-23 03:11:07.583527: Epoch time: 18.34 s +2024-11-23 03:11:08.502975: +2024-11-23 03:11:08.503207: Epoch 7420 +2024-11-23 03:11:08.503324: Current learning rate: 0.00094 +2024-11-23 03:11:27.846514: train_loss -0.8376 +2024-11-23 03:11:27.846796: val_loss -0.761 +2024-11-23 03:11:27.846872: Pseudo dice [0.8188] +2024-11-23 03:11:27.846948: Epoch time: 19.34 s +2024-11-23 03:11:28.767051: +2024-11-23 03:11:28.767253: Epoch 7421 +2024-11-23 03:11:28.767373: Current learning rate: 0.00094 +2024-11-23 03:11:48.127783: train_loss -0.8305 +2024-11-23 03:11:48.128095: val_loss -0.771 +2024-11-23 03:11:48.128174: Pseudo dice [0.8443] +2024-11-23 03:11:48.128251: Epoch time: 19.36 s +2024-11-23 03:11:49.048558: +2024-11-23 03:11:49.048843: Epoch 7422 +2024-11-23 03:11:49.048957: Current learning rate: 0.00094 +2024-11-23 03:12:07.524776: train_loss -0.8335 +2024-11-23 03:12:07.530167: val_loss -0.7491 +2024-11-23 03:12:07.530360: Pseudo dice [0.8224] +2024-11-23 03:12:07.530457: Epoch time: 18.48 s +2024-11-23 03:12:08.476281: +2024-11-23 03:12:08.476519: Epoch 7423 +2024-11-23 03:12:08.476633: Current learning rate: 0.00094 +2024-11-23 03:12:28.273227: train_loss -0.8331 +2024-11-23 03:12:28.273474: val_loss -0.756 +2024-11-23 03:12:28.273554: Pseudo dice [0.8398] +2024-11-23 03:12:28.273638: Epoch time: 19.8 s +2024-11-23 03:12:29.196287: +2024-11-23 03:12:29.196562: Epoch 7424 +2024-11-23 03:12:29.196683: Current learning rate: 0.00094 +2024-11-23 03:12:47.206311: train_loss -0.8305 +2024-11-23 03:12:47.206539: val_loss -0.7474 +2024-11-23 03:12:47.206616: Pseudo dice [0.8315] +2024-11-23 03:12:47.206694: Epoch time: 18.01 s +2024-11-23 03:12:48.136212: +2024-11-23 03:12:48.136423: Epoch 7425 +2024-11-23 03:12:48.136537: Current learning rate: 0.00094 +2024-11-23 03:13:06.779083: train_loss -0.834 +2024-11-23 03:13:06.779295: val_loss -0.7722 +2024-11-23 03:13:06.779371: Pseudo dice [0.8264] +2024-11-23 03:13:06.779449: Epoch time: 18.64 s +2024-11-23 03:13:07.721177: +2024-11-23 03:13:07.721400: Epoch 7426 +2024-11-23 03:13:07.721520: Current learning rate: 0.00093 +2024-11-23 03:13:26.592420: train_loss -0.8321 +2024-11-23 03:13:26.592653: val_loss -0.779 +2024-11-23 03:13:26.592726: Pseudo dice [0.8515] +2024-11-23 03:13:26.597950: Epoch time: 18.87 s +2024-11-23 03:13:27.527519: +2024-11-23 03:13:27.527773: Epoch 7427 +2024-11-23 03:13:27.527884: Current learning rate: 0.00093 +2024-11-23 03:13:46.052346: train_loss -0.8289 +2024-11-23 03:13:46.052576: val_loss -0.7658 +2024-11-23 03:13:46.052655: Pseudo dice [0.8372] +2024-11-23 03:13:46.052736: Epoch time: 18.53 s +2024-11-23 03:13:46.963462: +2024-11-23 03:13:46.963663: Epoch 7428 +2024-11-23 03:13:46.963773: Current learning rate: 0.00093 +2024-11-23 03:14:05.207753: train_loss -0.8354 +2024-11-23 03:14:05.207986: val_loss -0.7368 +2024-11-23 03:14:05.208078: Pseudo dice [0.8227] +2024-11-23 03:14:05.208155: Epoch time: 18.25 s +2024-11-23 03:14:06.117720: +2024-11-23 03:14:06.117918: Epoch 7429 +2024-11-23 03:14:06.118034: Current learning rate: 0.00093 +2024-11-23 03:14:24.590418: train_loss -0.8286 +2024-11-23 03:14:24.591566: val_loss -0.7637 +2024-11-23 03:14:24.591646: Pseudo dice [0.8421] +2024-11-23 03:14:24.591726: Epoch time: 18.47 s +2024-11-23 03:14:25.514141: +2024-11-23 03:14:25.514403: Epoch 7430 +2024-11-23 03:14:25.514515: Current learning rate: 0.00093 +2024-11-23 03:14:44.393687: train_loss -0.8282 +2024-11-23 03:14:44.394013: val_loss -0.7843 +2024-11-23 03:14:44.394090: Pseudo dice [0.8513] +2024-11-23 03:14:44.394171: Epoch time: 18.88 s +2024-11-23 03:14:45.312726: +2024-11-23 03:14:45.312956: Epoch 7431 +2024-11-23 03:14:45.313071: Current learning rate: 0.00093 +2024-11-23 03:15:05.279153: train_loss -0.8383 +2024-11-23 03:15:05.279388: val_loss -0.7429 +2024-11-23 03:15:05.279466: Pseudo dice [0.8158] +2024-11-23 03:15:05.279544: Epoch time: 19.97 s +2024-11-23 03:15:06.216441: +2024-11-23 03:15:06.216655: Epoch 7432 +2024-11-23 03:15:06.216768: Current learning rate: 0.00092 +2024-11-23 03:15:24.603650: train_loss -0.8317 +2024-11-23 03:15:24.603894: val_loss -0.7708 +2024-11-23 03:15:24.603983: Pseudo dice [0.8433] +2024-11-23 03:15:24.604065: Epoch time: 18.39 s +2024-11-23 03:15:25.525183: +2024-11-23 03:15:25.525414: Epoch 7433 +2024-11-23 03:15:25.525522: Current learning rate: 0.00092 +2024-11-23 03:15:43.672073: train_loss -0.8334 +2024-11-23 03:15:43.672288: val_loss -0.7619 +2024-11-23 03:15:43.672361: Pseudo dice [0.8266] +2024-11-23 03:15:43.672438: Epoch time: 18.15 s +2024-11-23 03:15:44.594970: +2024-11-23 03:15:44.595186: Epoch 7434 +2024-11-23 03:15:44.595302: Current learning rate: 0.00092 +2024-11-23 03:16:03.419283: train_loss -0.8218 +2024-11-23 03:16:03.420241: val_loss -0.745 +2024-11-23 03:16:03.420338: Pseudo dice [0.811] +2024-11-23 03:16:03.420428: Epoch time: 18.83 s +2024-11-23 03:16:04.352075: +2024-11-23 03:16:04.352277: Epoch 7435 +2024-11-23 03:16:04.352389: Current learning rate: 0.00092 +2024-11-23 03:16:23.455862: train_loss -0.8237 +2024-11-23 03:16:23.456087: val_loss -0.7469 +2024-11-23 03:16:23.456161: Pseudo dice [0.8285] +2024-11-23 03:16:23.456238: Epoch time: 19.1 s +2024-11-23 03:16:24.378060: +2024-11-23 03:16:24.378289: Epoch 7436 +2024-11-23 03:16:24.378412: Current learning rate: 0.00092 +2024-11-23 03:16:43.881454: train_loss -0.8265 +2024-11-23 03:16:43.881726: val_loss -0.7749 +2024-11-23 03:16:43.881801: Pseudo dice [0.8478] +2024-11-23 03:16:43.881880: Epoch time: 19.5 s +2024-11-23 03:16:44.817707: +2024-11-23 03:16:44.817976: Epoch 7437 +2024-11-23 03:16:44.818091: Current learning rate: 0.00092 +2024-11-23 03:17:03.268015: train_loss -0.828 +2024-11-23 03:17:03.268250: val_loss -0.7422 +2024-11-23 03:17:03.268331: Pseudo dice [0.8301] +2024-11-23 03:17:03.268410: Epoch time: 18.45 s +2024-11-23 03:17:04.189042: +2024-11-23 03:17:04.189342: Epoch 7438 +2024-11-23 03:17:04.189457: Current learning rate: 0.00092 +2024-11-23 03:17:22.267965: train_loss -0.833 +2024-11-23 03:17:22.268210: val_loss -0.7444 +2024-11-23 03:17:22.268285: Pseudo dice [0.8165] +2024-11-23 03:17:22.268366: Epoch time: 18.08 s +2024-11-23 03:17:23.183198: +2024-11-23 03:17:23.183468: Epoch 7439 +2024-11-23 03:17:23.183588: Current learning rate: 0.00091 +2024-11-23 03:17:42.650652: train_loss -0.8323 +2024-11-23 03:17:42.650877: val_loss -0.756 +2024-11-23 03:17:42.650963: Pseudo dice [0.8405] +2024-11-23 03:17:42.651047: Epoch time: 19.47 s +2024-11-23 03:17:43.977487: +2024-11-23 03:17:43.977684: Epoch 7440 +2024-11-23 03:17:43.977796: Current learning rate: 0.00091 +2024-11-23 03:18:03.587804: train_loss -0.8271 +2024-11-23 03:18:03.589336: val_loss -0.7685 +2024-11-23 03:18:03.589427: Pseudo dice [0.8496] +2024-11-23 03:18:03.589504: Epoch time: 19.61 s +2024-11-23 03:18:04.529371: +2024-11-23 03:18:04.529573: Epoch 7441 +2024-11-23 03:18:04.529686: Current learning rate: 0.00091 +2024-11-23 03:18:24.372268: train_loss -0.8303 +2024-11-23 03:18:24.372522: val_loss -0.7407 +2024-11-23 03:18:24.372606: Pseudo dice [0.838] +2024-11-23 03:18:24.372711: Epoch time: 19.84 s +2024-11-23 03:18:25.289855: +2024-11-23 03:18:25.290086: Epoch 7442 +2024-11-23 03:18:25.290202: Current learning rate: 0.00091 +2024-11-23 03:18:43.858168: train_loss -0.8288 +2024-11-23 03:18:43.858404: val_loss -0.7865 +2024-11-23 03:18:43.858479: Pseudo dice [0.8541] +2024-11-23 03:18:43.858557: Epoch time: 18.57 s +2024-11-23 03:18:44.778171: +2024-11-23 03:18:44.778374: Epoch 7443 +2024-11-23 03:18:44.778487: Current learning rate: 0.00091 +2024-11-23 03:19:02.764255: train_loss -0.8327 +2024-11-23 03:19:02.764470: val_loss -0.7614 +2024-11-23 03:19:02.764547: Pseudo dice [0.8364] +2024-11-23 03:19:02.764625: Epoch time: 17.99 s +2024-11-23 03:19:03.675569: +2024-11-23 03:19:03.675781: Epoch 7444 +2024-11-23 03:19:03.675895: Current learning rate: 0.00091 +2024-11-23 03:19:23.466425: train_loss -0.8292 +2024-11-23 03:19:23.466751: val_loss -0.7634 +2024-11-23 03:19:23.466836: Pseudo dice [0.8364] +2024-11-23 03:19:23.466920: Epoch time: 19.79 s +2024-11-23 03:19:24.387104: +2024-11-23 03:19:24.387323: Epoch 7445 +2024-11-23 03:19:24.387443: Current learning rate: 0.00091 +2024-11-23 03:19:43.617033: train_loss -0.8286 +2024-11-23 03:19:43.617263: val_loss -0.7896 +2024-11-23 03:19:43.617337: Pseudo dice [0.8382] +2024-11-23 03:19:43.617550: Epoch time: 19.23 s +2024-11-23 03:19:44.747852: +2024-11-23 03:19:44.748047: Epoch 7446 +2024-11-23 03:19:44.748159: Current learning rate: 0.0009 +2024-11-23 03:20:03.808159: train_loss -0.8209 +2024-11-23 03:20:03.810578: val_loss -0.7374 +2024-11-23 03:20:03.810718: Pseudo dice [0.8302] +2024-11-23 03:20:03.810802: Epoch time: 19.06 s +2024-11-23 03:20:04.910322: +2024-11-23 03:20:04.910544: Epoch 7447 +2024-11-23 03:20:04.910657: Current learning rate: 0.0009 +2024-11-23 03:20:23.183113: train_loss -0.8357 +2024-11-23 03:20:23.185514: val_loss -0.7507 +2024-11-23 03:20:23.185607: Pseudo dice [0.8411] +2024-11-23 03:20:23.185686: Epoch time: 18.27 s +2024-11-23 03:20:24.254557: +2024-11-23 03:20:24.254915: Epoch 7448 +2024-11-23 03:20:24.255038: Current learning rate: 0.0009 +2024-11-23 03:20:43.891209: train_loss -0.8337 +2024-11-23 03:20:43.891448: val_loss -0.7861 +2024-11-23 03:20:43.891524: Pseudo dice [0.8462] +2024-11-23 03:20:43.891607: Epoch time: 19.64 s +2024-11-23 03:20:44.811806: +2024-11-23 03:20:44.812019: Epoch 7449 +2024-11-23 03:20:44.812131: Current learning rate: 0.0009 +2024-11-23 03:21:04.001221: train_loss -0.825 +2024-11-23 03:21:04.020098: val_loss -0.7518 +2024-11-23 03:21:04.020242: Pseudo dice [0.8222] +2024-11-23 03:21:04.020328: Epoch time: 19.19 s +2024-11-23 03:21:05.416773: +2024-11-23 03:21:05.417005: Epoch 7450 +2024-11-23 03:21:05.417119: Current learning rate: 0.0009 +2024-11-23 03:21:24.549536: train_loss -0.8265 +2024-11-23 03:21:24.549760: val_loss -0.7604 +2024-11-23 03:21:24.549835: Pseudo dice [0.821] +2024-11-23 03:21:24.549913: Epoch time: 19.13 s +2024-11-23 03:21:25.561465: +2024-11-23 03:21:25.561663: Epoch 7451 +2024-11-23 03:21:25.561773: Current learning rate: 0.0009 +2024-11-23 03:21:44.869920: train_loss -0.8318 +2024-11-23 03:21:44.870177: val_loss -0.7454 +2024-11-23 03:21:44.870258: Pseudo dice [0.8271] +2024-11-23 03:21:44.880620: Epoch time: 19.31 s +2024-11-23 03:21:45.870335: +2024-11-23 03:21:45.870538: Epoch 7452 +2024-11-23 03:21:45.870656: Current learning rate: 0.0009 +2024-11-23 03:22:05.039235: train_loss -0.8304 +2024-11-23 03:22:05.039474: val_loss -0.7837 +2024-11-23 03:22:05.039552: Pseudo dice [0.8485] +2024-11-23 03:22:05.039639: Epoch time: 19.17 s +2024-11-23 03:22:05.964575: +2024-11-23 03:22:05.964784: Epoch 7453 +2024-11-23 03:22:05.964899: Current learning rate: 0.00089 +2024-11-23 03:22:23.848303: train_loss -0.8354 +2024-11-23 03:22:23.848585: val_loss -0.7577 +2024-11-23 03:22:23.848668: Pseudo dice [0.845] +2024-11-23 03:22:23.848757: Epoch time: 17.88 s +2024-11-23 03:22:24.826960: +2024-11-23 03:22:24.827207: Epoch 7454 +2024-11-23 03:22:24.827320: Current learning rate: 0.00089 +2024-11-23 03:22:45.057325: train_loss -0.8338 +2024-11-23 03:22:45.057558: val_loss -0.7521 +2024-11-23 03:22:45.057632: Pseudo dice [0.8521] +2024-11-23 03:22:45.062957: Epoch time: 20.23 s +2024-11-23 03:22:46.153095: +2024-11-23 03:22:46.153318: Epoch 7455 +2024-11-23 03:22:46.153432: Current learning rate: 0.00089 +2024-11-23 03:23:05.038832: train_loss -0.8334 +2024-11-23 03:23:05.039057: val_loss -0.7644 +2024-11-23 03:23:05.039135: Pseudo dice [0.844] +2024-11-23 03:23:05.039220: Epoch time: 18.89 s +2024-11-23 03:23:05.967366: +2024-11-23 03:23:05.967576: Epoch 7456 +2024-11-23 03:23:05.967690: Current learning rate: 0.00089 +2024-11-23 03:23:24.291376: train_loss -0.8295 +2024-11-23 03:23:24.291581: val_loss -0.7508 +2024-11-23 03:23:24.291655: Pseudo dice [0.8352] +2024-11-23 03:23:24.291743: Epoch time: 18.32 s +2024-11-23 03:23:25.211418: +2024-11-23 03:23:25.211613: Epoch 7457 +2024-11-23 03:23:25.211730: Current learning rate: 0.00089 +2024-11-23 03:23:45.360731: train_loss -0.8262 +2024-11-23 03:23:45.360959: val_loss -0.7373 +2024-11-23 03:23:45.361041: Pseudo dice [0.8309] +2024-11-23 03:23:45.361123: Epoch time: 20.15 s +2024-11-23 03:23:46.277796: +2024-11-23 03:23:46.278003: Epoch 7458 +2024-11-23 03:23:46.278116: Current learning rate: 0.00089 +2024-11-23 03:24:04.349520: train_loss -0.8351 +2024-11-23 03:24:04.349739: val_loss -0.7548 +2024-11-23 03:24:04.349817: Pseudo dice [0.8371] +2024-11-23 03:24:04.349894: Epoch time: 18.07 s +2024-11-23 03:24:05.278523: +2024-11-23 03:24:05.278757: Epoch 7459 +2024-11-23 03:24:05.278872: Current learning rate: 0.00089 +2024-11-23 03:24:25.056299: train_loss -0.8316 +2024-11-23 03:24:25.056530: val_loss -0.7654 +2024-11-23 03:24:25.056604: Pseudo dice [0.8434] +2024-11-23 03:24:25.056688: Epoch time: 19.78 s +2024-11-23 03:24:25.973681: +2024-11-23 03:24:25.973900: Epoch 7460 +2024-11-23 03:24:25.974023: Current learning rate: 0.00088 +2024-11-23 03:24:44.934062: train_loss -0.8312 +2024-11-23 03:24:44.934294: val_loss -0.7623 +2024-11-23 03:24:44.934367: Pseudo dice [0.8325] +2024-11-23 03:24:44.934442: Epoch time: 18.96 s +2024-11-23 03:24:45.858200: +2024-11-23 03:24:45.858418: Epoch 7461 +2024-11-23 03:24:45.858531: Current learning rate: 0.00088 +2024-11-23 03:25:05.201316: train_loss -0.8262 +2024-11-23 03:25:05.201567: val_loss -0.7436 +2024-11-23 03:25:05.201644: Pseudo dice [0.8326] +2024-11-23 03:25:05.201722: Epoch time: 19.34 s +2024-11-23 03:25:06.151298: +2024-11-23 03:25:06.151540: Epoch 7462 +2024-11-23 03:25:06.169654: Current learning rate: 0.00088 +2024-11-23 03:25:25.216042: train_loss -0.8327 +2024-11-23 03:25:25.216389: val_loss -0.7851 +2024-11-23 03:25:25.216480: Pseudo dice [0.8356] +2024-11-23 03:25:25.216577: Epoch time: 19.06 s +2024-11-23 03:25:26.586042: +2024-11-23 03:25:26.586258: Epoch 7463 +2024-11-23 03:25:26.586382: Current learning rate: 0.00088 +2024-11-23 03:25:45.496598: train_loss -0.8301 +2024-11-23 03:25:45.499029: val_loss -0.7561 +2024-11-23 03:25:45.499172: Pseudo dice [0.8211] +2024-11-23 03:25:45.499260: Epoch time: 18.91 s +2024-11-23 03:25:46.706771: +2024-11-23 03:25:46.707160: Epoch 7464 +2024-11-23 03:25:46.707274: Current learning rate: 0.00088 +2024-11-23 03:26:05.132192: train_loss -0.8348 +2024-11-23 03:26:05.132427: val_loss -0.7531 +2024-11-23 03:26:05.132504: Pseudo dice [0.8308] +2024-11-23 03:26:05.132584: Epoch time: 18.43 s +2024-11-23 03:26:06.111722: +2024-11-23 03:26:06.111926: Epoch 7465 +2024-11-23 03:26:06.112047: Current learning rate: 0.00088 +2024-11-23 03:26:23.129412: train_loss -0.8307 +2024-11-23 03:26:23.129657: val_loss -0.7565 +2024-11-23 03:26:23.129748: Pseudo dice [0.8251] +2024-11-23 03:26:23.129836: Epoch time: 17.02 s +2024-11-23 03:26:24.054168: +2024-11-23 03:26:24.054391: Epoch 7466 +2024-11-23 03:26:24.054507: Current learning rate: 0.00087 +2024-11-23 03:26:42.545374: train_loss -0.8303 +2024-11-23 03:26:42.547802: val_loss -0.7547 +2024-11-23 03:26:42.547903: Pseudo dice [0.8345] +2024-11-23 03:26:42.547995: Epoch time: 18.49 s +2024-11-23 03:26:44.058694: +2024-11-23 03:26:44.058912: Epoch 7467 +2024-11-23 03:26:44.059033: Current learning rate: 0.00087 +2024-11-23 03:27:03.263156: train_loss -0.8201 +2024-11-23 03:27:03.265579: val_loss -0.774 +2024-11-23 03:27:03.265675: Pseudo dice [0.8559] +2024-11-23 03:27:03.265755: Epoch time: 19.21 s +2024-11-23 03:27:04.216073: +2024-11-23 03:27:04.216278: Epoch 7468 +2024-11-23 03:27:04.216388: Current learning rate: 0.00087 +2024-11-23 03:27:22.401180: train_loss -0.8275 +2024-11-23 03:27:22.401396: val_loss -0.7677 +2024-11-23 03:27:22.401464: Pseudo dice [0.833] +2024-11-23 03:27:22.401538: Epoch time: 18.19 s +2024-11-23 03:27:23.340774: +2024-11-23 03:27:23.340983: Epoch 7469 +2024-11-23 03:27:23.341101: Current learning rate: 0.00087 +2024-11-23 03:27:41.115641: train_loss -0.8301 +2024-11-23 03:27:41.115937: val_loss -0.7693 +2024-11-23 03:27:41.116030: Pseudo dice [0.8387] +2024-11-23 03:27:41.116116: Epoch time: 17.78 s +2024-11-23 03:27:42.057131: +2024-11-23 03:27:42.057348: Epoch 7470 +2024-11-23 03:27:42.057462: Current learning rate: 0.00087 +2024-11-23 03:28:00.793128: train_loss -0.8363 +2024-11-23 03:28:00.793361: val_loss -0.7642 +2024-11-23 03:28:00.793436: Pseudo dice [0.8451] +2024-11-23 03:28:00.793517: Epoch time: 18.74 s +2024-11-23 03:28:01.717123: +2024-11-23 03:28:01.717320: Epoch 7471 +2024-11-23 03:28:01.717431: Current learning rate: 0.00087 +2024-11-23 03:28:21.235933: train_loss -0.8333 +2024-11-23 03:28:21.236175: val_loss -0.7485 +2024-11-23 03:28:21.236253: Pseudo dice [0.8355] +2024-11-23 03:28:21.236470: Epoch time: 19.52 s +2024-11-23 03:28:22.157626: +2024-11-23 03:28:22.157862: Epoch 7472 +2024-11-23 03:28:22.157984: Current learning rate: 0.00087 +2024-11-23 03:28:41.119816: train_loss -0.8323 +2024-11-23 03:28:41.122572: val_loss -0.7798 +2024-11-23 03:28:41.122673: Pseudo dice [0.8415] +2024-11-23 03:28:41.122751: Epoch time: 18.96 s +2024-11-23 03:28:42.063567: +2024-11-23 03:28:42.063762: Epoch 7473 +2024-11-23 03:28:42.063874: Current learning rate: 0.00086 +2024-11-23 03:29:00.235083: train_loss -0.8328 +2024-11-23 03:29:00.235297: val_loss -0.7518 +2024-11-23 03:29:00.235368: Pseudo dice [0.836] +2024-11-23 03:29:00.235450: Epoch time: 18.17 s +2024-11-23 03:29:01.591027: +2024-11-23 03:29:01.591260: Epoch 7474 +2024-11-23 03:29:01.591369: Current learning rate: 0.00086 +2024-11-23 03:29:20.146200: train_loss -0.8336 +2024-11-23 03:29:20.150552: val_loss -0.767 +2024-11-23 03:29:20.150716: Pseudo dice [0.8507] +2024-11-23 03:29:20.151535: Epoch time: 18.56 s +2024-11-23 03:29:21.102544: +2024-11-23 03:29:21.102760: Epoch 7475 +2024-11-23 03:29:21.102874: Current learning rate: 0.00086 +2024-11-23 03:29:39.927983: train_loss -0.8364 +2024-11-23 03:29:39.928188: val_loss -0.7651 +2024-11-23 03:29:39.928260: Pseudo dice [0.8515] +2024-11-23 03:29:39.928337: Epoch time: 18.83 s +2024-11-23 03:29:40.880121: +2024-11-23 03:29:40.880342: Epoch 7476 +2024-11-23 03:29:40.880455: Current learning rate: 0.00086 +2024-11-23 03:29:58.792723: train_loss -0.8268 +2024-11-23 03:29:58.792947: val_loss -0.7455 +2024-11-23 03:29:58.793062: Pseudo dice [0.8315] +2024-11-23 03:29:58.793153: Epoch time: 17.91 s +2024-11-23 03:29:59.710189: +2024-11-23 03:29:59.710415: Epoch 7477 +2024-11-23 03:29:59.710527: Current learning rate: 0.00086 +2024-11-23 03:30:17.762438: train_loss -0.8317 +2024-11-23 03:30:17.762678: val_loss -0.7848 +2024-11-23 03:30:17.762752: Pseudo dice [0.8593] +2024-11-23 03:30:17.762830: Epoch time: 18.05 s +2024-11-23 03:30:18.729538: +2024-11-23 03:30:18.729741: Epoch 7478 +2024-11-23 03:30:18.729850: Current learning rate: 0.00086 +2024-11-23 03:30:37.086261: train_loss -0.8337 +2024-11-23 03:30:37.086488: val_loss -0.7766 +2024-11-23 03:30:37.086564: Pseudo dice [0.8525] +2024-11-23 03:30:37.086640: Epoch time: 18.36 s +2024-11-23 03:30:38.009087: +2024-11-23 03:30:38.009286: Epoch 7479 +2024-11-23 03:30:38.009399: Current learning rate: 0.00086 +2024-11-23 03:30:56.228014: train_loss -0.8336 +2024-11-23 03:30:56.228235: val_loss -0.7649 +2024-11-23 03:30:56.228309: Pseudo dice [0.8433] +2024-11-23 03:30:56.228387: Epoch time: 18.22 s +2024-11-23 03:30:57.237966: +2024-11-23 03:30:57.238184: Epoch 7480 +2024-11-23 03:30:57.238296: Current learning rate: 0.00085 +2024-11-23 03:31:16.094606: train_loss -0.8261 +2024-11-23 03:31:16.094838: val_loss -0.7616 +2024-11-23 03:31:16.094918: Pseudo dice [0.8364] +2024-11-23 03:31:16.095013: Epoch time: 18.86 s +2024-11-23 03:31:17.012409: +2024-11-23 03:31:17.012635: Epoch 7481 +2024-11-23 03:31:17.012751: Current learning rate: 0.00085 +2024-11-23 03:31:35.561527: train_loss -0.8323 +2024-11-23 03:31:35.561743: val_loss -0.7808 +2024-11-23 03:31:35.561818: Pseudo dice [0.8477] +2024-11-23 03:31:35.561956: Epoch time: 18.55 s +2024-11-23 03:31:36.481935: +2024-11-23 03:31:36.482147: Epoch 7482 +2024-11-23 03:31:36.482266: Current learning rate: 0.00085 +2024-11-23 03:31:55.896838: train_loss -0.8331 +2024-11-23 03:31:55.897061: val_loss -0.7897 +2024-11-23 03:31:55.897138: Pseudo dice [0.8461] +2024-11-23 03:31:55.897216: Epoch time: 19.42 s +2024-11-23 03:31:56.812823: +2024-11-23 03:31:56.813022: Epoch 7483 +2024-11-23 03:31:56.813136: Current learning rate: 0.00085 +2024-11-23 03:32:15.258320: train_loss -0.8329 +2024-11-23 03:32:15.258531: val_loss -0.7679 +2024-11-23 03:32:15.258631: Pseudo dice [0.8467] +2024-11-23 03:32:15.258708: Epoch time: 18.45 s +2024-11-23 03:32:16.180049: +2024-11-23 03:32:16.180251: Epoch 7484 +2024-11-23 03:32:16.180360: Current learning rate: 0.00085 +2024-11-23 03:32:34.121508: train_loss -0.8344 +2024-11-23 03:32:34.121795: val_loss -0.7663 +2024-11-23 03:32:34.121871: Pseudo dice [0.8259] +2024-11-23 03:32:34.121958: Epoch time: 17.94 s +2024-11-23 03:32:35.043067: +2024-11-23 03:32:35.043287: Epoch 7485 +2024-11-23 03:32:35.043411: Current learning rate: 0.00085 +2024-11-23 03:32:53.041765: train_loss -0.8303 +2024-11-23 03:32:53.041968: val_loss -0.79 +2024-11-23 03:32:53.042050: Pseudo dice [0.8448] +2024-11-23 03:32:53.042126: Epoch time: 18.0 s +2024-11-23 03:32:54.435401: +2024-11-23 03:32:54.435600: Epoch 7486 +2024-11-23 03:32:54.435709: Current learning rate: 0.00085 +2024-11-23 03:33:13.854249: train_loss -0.8289 +2024-11-23 03:33:13.854483: val_loss -0.7503 +2024-11-23 03:33:13.854556: Pseudo dice [0.8446] +2024-11-23 03:33:13.854632: Epoch time: 19.42 s +2024-11-23 03:33:14.779233: +2024-11-23 03:33:14.779472: Epoch 7487 +2024-11-23 03:33:14.779590: Current learning rate: 0.00084 +2024-11-23 03:33:33.395344: train_loss -0.8222 +2024-11-23 03:33:33.395583: val_loss -0.7602 +2024-11-23 03:33:33.423476: Pseudo dice [0.8489] +2024-11-23 03:33:33.423656: Epoch time: 18.62 s +2024-11-23 03:33:34.351351: +2024-11-23 03:33:34.351571: Epoch 7488 +2024-11-23 03:33:34.351683: Current learning rate: 0.00084 +2024-11-23 03:33:54.267026: train_loss -0.8289 +2024-11-23 03:33:54.267252: val_loss -0.7642 +2024-11-23 03:33:54.267326: Pseudo dice [0.8195] +2024-11-23 03:33:54.267404: Epoch time: 19.92 s +2024-11-23 03:33:55.246067: +2024-11-23 03:33:55.246269: Epoch 7489 +2024-11-23 03:33:55.246386: Current learning rate: 0.00084 +2024-11-23 03:34:14.214996: train_loss -0.8271 +2024-11-23 03:34:14.215231: val_loss -0.7862 +2024-11-23 03:34:14.215304: Pseudo dice [0.8495] +2024-11-23 03:34:14.215383: Epoch time: 18.97 s +2024-11-23 03:34:15.218214: +2024-11-23 03:34:15.218440: Epoch 7490 +2024-11-23 03:34:15.218558: Current learning rate: 0.00084 +2024-11-23 03:34:33.863616: train_loss -0.833 +2024-11-23 03:34:33.863838: val_loss -0.7555 +2024-11-23 03:34:33.863914: Pseudo dice [0.8422] +2024-11-23 03:34:33.868053: Epoch time: 18.65 s +2024-11-23 03:34:34.923998: +2024-11-23 03:34:34.924198: Epoch 7491 +2024-11-23 03:34:34.924311: Current learning rate: 0.00084 +2024-11-23 03:34:53.568054: train_loss -0.8351 +2024-11-23 03:34:53.568299: val_loss -0.7525 +2024-11-23 03:34:53.568377: Pseudo dice [0.8288] +2024-11-23 03:34:53.568463: Epoch time: 18.64 s +2024-11-23 03:34:54.654346: +2024-11-23 03:34:54.654546: Epoch 7492 +2024-11-23 03:34:54.654662: Current learning rate: 0.00084 +2024-11-23 03:35:12.671532: train_loss -0.8333 +2024-11-23 03:35:12.671749: val_loss -0.73 +2024-11-23 03:35:12.671826: Pseudo dice [0.8223] +2024-11-23 03:35:12.671904: Epoch time: 18.02 s +2024-11-23 03:35:13.621734: +2024-11-23 03:35:13.621934: Epoch 7493 +2024-11-23 03:35:13.622051: Current learning rate: 0.00084 +2024-11-23 03:35:33.618118: train_loss -0.8264 +2024-11-23 03:35:33.618337: val_loss -0.7656 +2024-11-23 03:35:33.618416: Pseudo dice [0.8334] +2024-11-23 03:35:33.618492: Epoch time: 20.0 s +2024-11-23 03:35:34.539955: +2024-11-23 03:35:34.540170: Epoch 7494 +2024-11-23 03:35:34.540288: Current learning rate: 0.00083 +2024-11-23 03:35:53.261978: train_loss -0.8367 +2024-11-23 03:35:53.262197: val_loss -0.7755 +2024-11-23 03:35:53.262268: Pseudo dice [0.8541] +2024-11-23 03:35:53.262343: Epoch time: 18.72 s +2024-11-23 03:35:54.182765: +2024-11-23 03:35:54.182984: Epoch 7495 +2024-11-23 03:35:54.183104: Current learning rate: 0.00083 +2024-11-23 03:36:13.370153: train_loss -0.8264 +2024-11-23 03:36:13.370391: val_loss -0.7699 +2024-11-23 03:36:13.370466: Pseudo dice [0.8412] +2024-11-23 03:36:13.370551: Epoch time: 19.19 s +2024-11-23 03:36:14.313830: +2024-11-23 03:36:14.314041: Epoch 7496 +2024-11-23 03:36:14.314190: Current learning rate: 0.00083 +2024-11-23 03:36:33.459585: train_loss -0.8371 +2024-11-23 03:36:33.459797: val_loss -0.7641 +2024-11-23 03:36:33.459871: Pseudo dice [0.8323] +2024-11-23 03:36:33.459947: Epoch time: 19.15 s +2024-11-23 03:36:34.735964: +2024-11-23 03:36:34.736200: Epoch 7497 +2024-11-23 03:36:34.736316: Current learning rate: 0.00083 +2024-11-23 03:36:53.322236: train_loss -0.8287 +2024-11-23 03:36:53.322466: val_loss -0.7897 +2024-11-23 03:36:53.322543: Pseudo dice [0.8438] +2024-11-23 03:36:53.322700: Epoch time: 18.59 s +2024-11-23 03:36:54.239831: +2024-11-23 03:36:54.240049: Epoch 7498 +2024-11-23 03:36:54.240161: Current learning rate: 0.00083 +2024-11-23 03:37:12.647278: train_loss -0.8365 +2024-11-23 03:37:12.647573: val_loss -0.7484 +2024-11-23 03:37:12.647653: Pseudo dice [0.842] +2024-11-23 03:37:12.647741: Epoch time: 18.41 s +2024-11-23 03:37:13.596358: +2024-11-23 03:37:13.596576: Epoch 7499 +2024-11-23 03:37:13.596690: Current learning rate: 0.00083 +2024-11-23 03:37:32.302915: train_loss -0.8347 +2024-11-23 03:37:32.303132: val_loss -0.758 +2024-11-23 03:37:32.303206: Pseudo dice [0.8391] +2024-11-23 03:37:32.303281: Epoch time: 18.71 s +2024-11-23 03:37:33.614772: +2024-11-23 03:37:33.614997: Epoch 7500 +2024-11-23 03:37:33.615110: Current learning rate: 0.00082 +2024-11-23 03:37:52.210108: train_loss -0.8314 +2024-11-23 03:37:52.210326: val_loss -0.7765 +2024-11-23 03:37:52.210402: Pseudo dice [0.8653] +2024-11-23 03:37:52.210476: Epoch time: 18.6 s +2024-11-23 03:37:53.130170: +2024-11-23 03:37:53.130479: Epoch 7501 +2024-11-23 03:37:53.130594: Current learning rate: 0.00082 +2024-11-23 03:38:11.132480: train_loss -0.8372 +2024-11-23 03:38:11.132706: val_loss -0.7558 +2024-11-23 03:38:11.132780: Pseudo dice [0.8389] +2024-11-23 03:38:11.132854: Epoch time: 18.0 s +2024-11-23 03:38:12.050501: +2024-11-23 03:38:12.050744: Epoch 7502 +2024-11-23 03:38:12.050856: Current learning rate: 0.00082 +2024-11-23 03:38:30.423818: train_loss -0.8424 +2024-11-23 03:38:30.424060: val_loss -0.7515 +2024-11-23 03:38:30.424135: Pseudo dice [0.846] +2024-11-23 03:38:30.424222: Epoch time: 18.37 s +2024-11-23 03:38:31.349969: +2024-11-23 03:38:31.350203: Epoch 7503 +2024-11-23 03:38:31.350321: Current learning rate: 0.00082 +2024-11-23 03:38:50.560788: train_loss -0.8223 +2024-11-23 03:38:50.561015: val_loss -0.7629 +2024-11-23 03:38:50.561096: Pseudo dice [0.8303] +2024-11-23 03:38:50.561173: Epoch time: 19.21 s +2024-11-23 03:38:51.483548: +2024-11-23 03:38:51.483743: Epoch 7504 +2024-11-23 03:38:51.483850: Current learning rate: 0.00082 +2024-11-23 03:39:10.522435: train_loss -0.8332 +2024-11-23 03:39:10.522659: val_loss -0.769 +2024-11-23 03:39:10.522740: Pseudo dice [0.8471] +2024-11-23 03:39:10.522817: Epoch time: 19.04 s +2024-11-23 03:39:11.448697: +2024-11-23 03:39:11.448891: Epoch 7505 +2024-11-23 03:39:11.449007: Current learning rate: 0.00082 +2024-11-23 03:39:30.585670: train_loss -0.8261 +2024-11-23 03:39:30.585897: val_loss -0.7528 +2024-11-23 03:39:30.585977: Pseudo dice [0.8475] +2024-11-23 03:39:30.586063: Epoch time: 19.14 s +2024-11-23 03:39:31.555588: +2024-11-23 03:39:31.555791: Epoch 7506 +2024-11-23 03:39:31.555900: Current learning rate: 0.00082 +2024-11-23 03:39:49.203030: train_loss -0.8279 +2024-11-23 03:39:49.203269: val_loss -0.7584 +2024-11-23 03:39:49.203343: Pseudo dice [0.8284] +2024-11-23 03:39:49.203428: Epoch time: 17.65 s +2024-11-23 03:39:50.122969: +2024-11-23 03:39:50.123171: Epoch 7507 +2024-11-23 03:39:50.123283: Current learning rate: 0.00081 +2024-11-23 03:40:09.201947: train_loss -0.8322 +2024-11-23 03:40:09.202166: val_loss -0.7609 +2024-11-23 03:40:09.202243: Pseudo dice [0.8354] +2024-11-23 03:40:09.202319: Epoch time: 19.08 s +2024-11-23 03:40:10.122445: +2024-11-23 03:40:10.122658: Epoch 7508 +2024-11-23 03:40:10.122769: Current learning rate: 0.00081 +2024-11-23 03:40:28.476156: train_loss -0.8394 +2024-11-23 03:40:28.476377: val_loss -0.7748 +2024-11-23 03:40:28.476452: Pseudo dice [0.8445] +2024-11-23 03:40:28.476527: Epoch time: 18.35 s +2024-11-23 03:40:29.802101: +2024-11-23 03:40:29.802309: Epoch 7509 +2024-11-23 03:40:29.802422: Current learning rate: 0.00081 +2024-11-23 03:40:47.747899: train_loss -0.8382 +2024-11-23 03:40:47.748165: val_loss -0.7665 +2024-11-23 03:40:47.748245: Pseudo dice [0.8305] +2024-11-23 03:40:47.748331: Epoch time: 17.95 s +2024-11-23 03:40:48.671968: +2024-11-23 03:40:48.672194: Epoch 7510 +2024-11-23 03:40:48.672307: Current learning rate: 0.00081 +2024-11-23 03:41:07.316885: train_loss -0.835 +2024-11-23 03:41:07.317190: val_loss -0.7508 +2024-11-23 03:41:07.317272: Pseudo dice [0.8376] +2024-11-23 03:41:07.317350: Epoch time: 18.65 s +2024-11-23 03:41:08.347125: +2024-11-23 03:41:08.347381: Epoch 7511 +2024-11-23 03:41:08.347501: Current learning rate: 0.00081 +2024-11-23 03:41:27.275513: train_loss -0.8312 +2024-11-23 03:41:27.275734: val_loss -0.7703 +2024-11-23 03:41:27.275809: Pseudo dice [0.8431] +2024-11-23 03:41:27.275882: Epoch time: 18.93 s +2024-11-23 03:41:28.194099: +2024-11-23 03:41:28.194309: Epoch 7512 +2024-11-23 03:41:28.194422: Current learning rate: 0.00081 +2024-11-23 03:41:46.846582: train_loss -0.8274 +2024-11-23 03:41:46.846807: val_loss -0.7635 +2024-11-23 03:41:46.846882: Pseudo dice [0.8324] +2024-11-23 03:41:46.846967: Epoch time: 18.65 s +2024-11-23 03:41:47.975751: +2024-11-23 03:41:47.976041: Epoch 7513 +2024-11-23 03:41:47.976154: Current learning rate: 0.00081 +2024-11-23 03:42:06.022730: train_loss -0.8387 +2024-11-23 03:42:06.022978: val_loss -0.757 +2024-11-23 03:42:06.023058: Pseudo dice [0.8618] +2024-11-23 03:42:06.023203: Epoch time: 18.05 s +2024-11-23 03:42:07.032861: +2024-11-23 03:42:07.033076: Epoch 7514 +2024-11-23 03:42:07.033192: Current learning rate: 0.0008 +2024-11-23 03:42:26.227899: train_loss -0.8288 +2024-11-23 03:42:26.228166: val_loss -0.7524 +2024-11-23 03:42:26.228244: Pseudo dice [0.8445] +2024-11-23 03:42:26.228324: Epoch time: 19.2 s +2024-11-23 03:42:27.150183: +2024-11-23 03:42:27.150450: Epoch 7515 +2024-11-23 03:42:27.150573: Current learning rate: 0.0008 +2024-11-23 03:42:45.831822: train_loss -0.8297 +2024-11-23 03:42:45.832039: val_loss -0.7611 +2024-11-23 03:42:45.832118: Pseudo dice [0.832] +2024-11-23 03:42:45.832194: Epoch time: 18.68 s +2024-11-23 03:42:46.758009: +2024-11-23 03:42:46.758217: Epoch 7516 +2024-11-23 03:42:46.758338: Current learning rate: 0.0008 +2024-11-23 03:43:05.454488: train_loss -0.8346 +2024-11-23 03:43:05.454728: val_loss -0.7383 +2024-11-23 03:43:05.454804: Pseudo dice [0.8485] +2024-11-23 03:43:05.457049: Epoch time: 18.7 s +2024-11-23 03:43:06.443384: +2024-11-23 03:43:06.443591: Epoch 7517 +2024-11-23 03:43:06.443705: Current learning rate: 0.0008 +2024-11-23 03:43:23.918750: train_loss -0.8378 +2024-11-23 03:43:23.918978: val_loss -0.7513 +2024-11-23 03:43:23.919062: Pseudo dice [0.8341] +2024-11-23 03:43:23.919141: Epoch time: 17.48 s +2024-11-23 03:43:24.841839: +2024-11-23 03:43:24.842076: Epoch 7518 +2024-11-23 03:43:24.842189: Current learning rate: 0.0008 +2024-11-23 03:43:44.266625: train_loss -0.8284 +2024-11-23 03:43:44.266838: val_loss -0.744 +2024-11-23 03:43:44.266911: Pseudo dice [0.8324] +2024-11-23 03:43:44.266984: Epoch time: 19.43 s +2024-11-23 03:43:45.184858: +2024-11-23 03:43:45.185089: Epoch 7519 +2024-11-23 03:43:45.185211: Current learning rate: 0.0008 +2024-11-23 03:44:03.392803: train_loss -0.8285 +2024-11-23 03:44:03.393054: val_loss -0.7958 +2024-11-23 03:44:03.393133: Pseudo dice [0.863] +2024-11-23 03:44:03.393219: Epoch time: 18.21 s +2024-11-23 03:44:04.308378: +2024-11-23 03:44:04.308576: Epoch 7520 +2024-11-23 03:44:04.308692: Current learning rate: 0.00079 +2024-11-23 03:44:24.038612: train_loss -0.8359 +2024-11-23 03:44:24.039098: val_loss -0.7765 +2024-11-23 03:44:24.039195: Pseudo dice [0.8476] +2024-11-23 03:44:24.039271: Epoch time: 19.73 s +2024-11-23 03:44:24.953301: +2024-11-23 03:44:24.953521: Epoch 7521 +2024-11-23 03:44:24.953644: Current learning rate: 0.00079 +2024-11-23 03:44:44.189511: train_loss -0.836 +2024-11-23 03:44:44.189727: val_loss -0.7628 +2024-11-23 03:44:44.189820: Pseudo dice [0.8301] +2024-11-23 03:44:44.189900: Epoch time: 19.24 s +2024-11-23 03:44:45.099133: +2024-11-23 03:44:45.099358: Epoch 7522 +2024-11-23 03:44:45.099472: Current learning rate: 0.00079 +2024-11-23 03:45:04.064025: train_loss -0.8346 +2024-11-23 03:45:04.064243: val_loss -0.7554 +2024-11-23 03:45:04.064319: Pseudo dice [0.8458] +2024-11-23 03:45:04.064400: Epoch time: 18.97 s +2024-11-23 03:45:04.989306: +2024-11-23 03:45:04.989524: Epoch 7523 +2024-11-23 03:45:04.989639: Current learning rate: 0.00079 +2024-11-23 03:45:23.493042: train_loss -0.8351 +2024-11-23 03:45:23.493262: val_loss -0.7362 +2024-11-23 03:45:23.493458: Pseudo dice [0.8316] +2024-11-23 03:45:23.493545: Epoch time: 18.5 s +2024-11-23 03:45:24.442969: +2024-11-23 03:45:24.443216: Epoch 7524 +2024-11-23 03:45:24.443334: Current learning rate: 0.00079 +2024-11-23 03:45:42.669833: train_loss -0.8341 +2024-11-23 03:45:42.670063: val_loss -0.7536 +2024-11-23 03:45:42.675273: Pseudo dice [0.832] +2024-11-23 03:45:42.675425: Epoch time: 18.23 s +2024-11-23 03:45:43.748186: +2024-11-23 03:45:43.748396: Epoch 7525 +2024-11-23 03:45:43.748508: Current learning rate: 0.00079 +2024-11-23 03:46:03.135797: train_loss -0.8297 +2024-11-23 03:46:03.136034: val_loss -0.7616 +2024-11-23 03:46:03.136137: Pseudo dice [0.8306] +2024-11-23 03:46:03.136217: Epoch time: 19.39 s +2024-11-23 03:46:04.106821: +2024-11-23 03:46:04.107043: Epoch 7526 +2024-11-23 03:46:04.107157: Current learning rate: 0.00079 +2024-11-23 03:46:22.029496: train_loss -0.8299 +2024-11-23 03:46:22.029758: val_loss -0.7349 +2024-11-23 03:46:22.029849: Pseudo dice [0.8345] +2024-11-23 03:46:22.029928: Epoch time: 17.92 s +2024-11-23 03:46:22.961131: +2024-11-23 03:46:22.961427: Epoch 7527 +2024-11-23 03:46:22.961540: Current learning rate: 0.00078 +2024-11-23 03:46:41.910238: train_loss -0.8339 +2024-11-23 03:46:41.910486: val_loss -0.7296 +2024-11-23 03:46:41.910559: Pseudo dice [0.8237] +2024-11-23 03:46:41.910639: Epoch time: 18.95 s +2024-11-23 03:46:42.832334: +2024-11-23 03:46:42.832540: Epoch 7528 +2024-11-23 03:46:42.832655: Current learning rate: 0.00078 +2024-11-23 03:47:01.157454: train_loss -0.8344 +2024-11-23 03:47:01.157661: val_loss -0.7735 +2024-11-23 03:47:01.157737: Pseudo dice [0.8678] +2024-11-23 03:47:01.157820: Epoch time: 18.33 s +2024-11-23 03:47:02.076303: +2024-11-23 03:47:02.076561: Epoch 7529 +2024-11-23 03:47:02.076675: Current learning rate: 0.00078 +2024-11-23 03:47:20.420181: train_loss -0.8378 +2024-11-23 03:47:20.420796: val_loss -0.7414 +2024-11-23 03:47:20.420883: Pseudo dice [0.8387] +2024-11-23 03:47:20.420964: Epoch time: 18.34 s +2024-11-23 03:47:21.338665: +2024-11-23 03:47:21.338863: Epoch 7530 +2024-11-23 03:47:21.338985: Current learning rate: 0.00078 +2024-11-23 03:47:40.111717: train_loss -0.8279 +2024-11-23 03:47:40.111950: val_loss -0.7765 +2024-11-23 03:47:40.112044: Pseudo dice [0.8257] +2024-11-23 03:47:40.112135: Epoch time: 18.77 s +2024-11-23 03:47:41.034101: +2024-11-23 03:47:41.034303: Epoch 7531 +2024-11-23 03:47:41.034432: Current learning rate: 0.00078 +2024-11-23 03:47:59.062480: train_loss -0.8362 +2024-11-23 03:47:59.062693: val_loss -0.7713 +2024-11-23 03:47:59.062768: Pseudo dice [0.8364] +2024-11-23 03:47:59.062847: Epoch time: 18.03 s +2024-11-23 03:48:00.527592: +2024-11-23 03:48:00.527796: Epoch 7532 +2024-11-23 03:48:00.527908: Current learning rate: 0.00078 +2024-11-23 03:48:19.275841: train_loss -0.8372 +2024-11-23 03:48:19.276083: val_loss -0.762 +2024-11-23 03:48:19.276159: Pseudo dice [0.8399] +2024-11-23 03:48:19.276255: Epoch time: 18.75 s +2024-11-23 03:48:20.199253: +2024-11-23 03:48:20.199481: Epoch 7533 +2024-11-23 03:48:20.199593: Current learning rate: 0.00078 +2024-11-23 03:48:38.678517: train_loss -0.8379 +2024-11-23 03:48:38.683921: val_loss -0.7703 +2024-11-23 03:48:38.684084: Pseudo dice [0.8411] +2024-11-23 03:48:38.684187: Epoch time: 18.48 s +2024-11-23 03:48:39.625558: +2024-11-23 03:48:39.625779: Epoch 7534 +2024-11-23 03:48:39.625891: Current learning rate: 0.00077 +2024-11-23 03:48:57.758529: train_loss -0.8323 +2024-11-23 03:48:57.758754: val_loss -0.748 +2024-11-23 03:48:57.758830: Pseudo dice [0.8201] +2024-11-23 03:48:57.758906: Epoch time: 18.13 s +2024-11-23 03:48:58.681877: +2024-11-23 03:48:58.682094: Epoch 7535 +2024-11-23 03:48:58.682206: Current learning rate: 0.00077 +2024-11-23 03:49:17.994950: train_loss -0.8304 +2024-11-23 03:49:17.995183: val_loss -0.7612 +2024-11-23 03:49:17.995261: Pseudo dice [0.8315] +2024-11-23 03:49:17.995360: Epoch time: 19.31 s +2024-11-23 03:49:18.915510: +2024-11-23 03:49:18.915785: Epoch 7536 +2024-11-23 03:49:18.915898: Current learning rate: 0.00077 +2024-11-23 03:49:37.672599: train_loss -0.8375 +2024-11-23 03:49:37.672818: val_loss -0.746 +2024-11-23 03:49:37.672893: Pseudo dice [0.8564] +2024-11-23 03:49:37.672966: Epoch time: 18.76 s +2024-11-23 03:49:38.757692: +2024-11-23 03:49:38.757920: Epoch 7537 +2024-11-23 03:49:38.758046: Current learning rate: 0.00077 +2024-11-23 03:49:57.909716: train_loss -0.8315 +2024-11-23 03:49:57.909952: val_loss -0.7817 +2024-11-23 03:49:57.910034: Pseudo dice [0.8472] +2024-11-23 03:49:57.910121: Epoch time: 19.15 s +2024-11-23 03:49:58.833725: +2024-11-23 03:49:58.833953: Epoch 7538 +2024-11-23 03:49:58.834072: Current learning rate: 0.00077 +2024-11-23 03:50:17.068393: train_loss -0.8383 +2024-11-23 03:50:17.068628: val_loss -0.768 +2024-11-23 03:50:17.068706: Pseudo dice [0.8239] +2024-11-23 03:50:17.068783: Epoch time: 18.24 s +2024-11-23 03:50:17.988529: +2024-11-23 03:50:17.988827: Epoch 7539 +2024-11-23 03:50:17.988944: Current learning rate: 0.00077 +2024-11-23 03:50:35.444635: train_loss -0.8307 +2024-11-23 03:50:35.444901: val_loss -0.7669 +2024-11-23 03:50:35.444976: Pseudo dice [0.839] +2024-11-23 03:50:35.445055: Epoch time: 17.46 s +2024-11-23 03:50:36.374025: +2024-11-23 03:50:36.374233: Epoch 7540 +2024-11-23 03:50:36.374351: Current learning rate: 0.00077 +2024-11-23 03:50:54.819808: train_loss -0.834 +2024-11-23 03:50:54.820032: val_loss -0.7768 +2024-11-23 03:50:54.820110: Pseudo dice [0.8477] +2024-11-23 03:50:54.820196: Epoch time: 18.45 s +2024-11-23 03:50:55.851860: +2024-11-23 03:50:55.852074: Epoch 7541 +2024-11-23 03:50:55.852192: Current learning rate: 0.00076 +2024-11-23 03:51:14.533333: train_loss -0.8275 +2024-11-23 03:51:14.533627: val_loss -0.7708 +2024-11-23 03:51:14.533711: Pseudo dice [0.8403] +2024-11-23 03:51:14.533793: Epoch time: 18.68 s +2024-11-23 03:51:15.458089: +2024-11-23 03:51:15.458283: Epoch 7542 +2024-11-23 03:51:15.458394: Current learning rate: 0.00076 +2024-11-23 03:51:33.602409: train_loss -0.8285 +2024-11-23 03:51:33.602633: val_loss -0.7484 +2024-11-23 03:51:33.602712: Pseudo dice [0.8551] +2024-11-23 03:51:33.602792: Epoch time: 18.15 s +2024-11-23 03:51:34.631730: +2024-11-23 03:51:34.631973: Epoch 7543 +2024-11-23 03:51:34.632089: Current learning rate: 0.00076 +2024-11-23 03:51:54.474230: train_loss -0.8316 +2024-11-23 03:51:54.476551: val_loss -0.7561 +2024-11-23 03:51:54.476657: Pseudo dice [0.8292] +2024-11-23 03:51:54.476737: Epoch time: 19.84 s +2024-11-23 03:51:55.414269: +2024-11-23 03:51:55.414467: Epoch 7544 +2024-11-23 03:51:55.414581: Current learning rate: 0.00076 +2024-11-23 03:52:13.246952: train_loss -0.8326 +2024-11-23 03:52:13.252384: val_loss -0.7594 +2024-11-23 03:52:13.252504: Pseudo dice [0.8469] +2024-11-23 03:52:13.252597: Epoch time: 17.83 s +2024-11-23 03:52:14.282011: +2024-11-23 03:52:14.282228: Epoch 7545 +2024-11-23 03:52:14.282355: Current learning rate: 0.00076 +2024-11-23 03:52:32.732123: train_loss -0.8311 +2024-11-23 03:52:32.732343: val_loss -0.7952 +2024-11-23 03:52:32.732417: Pseudo dice [0.8316] +2024-11-23 03:52:32.732494: Epoch time: 18.45 s +2024-11-23 03:52:33.803654: +2024-11-23 03:52:33.803882: Epoch 7546 +2024-11-23 03:52:33.804004: Current learning rate: 0.00076 +2024-11-23 03:52:52.188754: train_loss -0.8396 +2024-11-23 03:52:52.189343: val_loss -0.7539 +2024-11-23 03:52:52.189429: Pseudo dice [0.8281] +2024-11-23 03:52:52.189512: Epoch time: 18.39 s +2024-11-23 03:52:53.109894: +2024-11-23 03:52:53.110100: Epoch 7547 +2024-11-23 03:52:53.110216: Current learning rate: 0.00075 +2024-11-23 03:53:11.764175: train_loss -0.8313 +2024-11-23 03:53:11.764502: val_loss -0.7436 +2024-11-23 03:53:11.764582: Pseudo dice [0.8327] +2024-11-23 03:53:11.764666: Epoch time: 18.66 s +2024-11-23 03:53:12.791563: +2024-11-23 03:53:12.791783: Epoch 7548 +2024-11-23 03:53:12.791893: Current learning rate: 0.00075 +2024-11-23 03:53:32.845470: train_loss -0.8314 +2024-11-23 03:53:32.845703: val_loss -0.7815 +2024-11-23 03:53:32.845778: Pseudo dice [0.8372] +2024-11-23 03:53:32.845856: Epoch time: 20.05 s +2024-11-23 03:53:33.769740: +2024-11-23 03:53:33.769952: Epoch 7549 +2024-11-23 03:53:33.770067: Current learning rate: 0.00075 +2024-11-23 03:53:53.197818: train_loss -0.8337 +2024-11-23 03:53:53.198039: val_loss -0.7651 +2024-11-23 03:53:53.198252: Pseudo dice [0.8403] +2024-11-23 03:53:53.198336: Epoch time: 19.43 s +2024-11-23 03:53:54.460109: +2024-11-23 03:53:54.460325: Epoch 7550 +2024-11-23 03:53:54.460437: Current learning rate: 0.00075 +2024-11-23 03:54:13.220222: train_loss -0.8293 +2024-11-23 03:54:13.220446: val_loss -0.7382 +2024-11-23 03:54:13.220531: Pseudo dice [0.8336] +2024-11-23 03:54:13.220612: Epoch time: 18.76 s +2024-11-23 03:54:14.143569: +2024-11-23 03:54:14.144505: Epoch 7551 +2024-11-23 03:54:14.144617: Current learning rate: 0.00075 +2024-11-23 03:54:33.315608: train_loss -0.8322 +2024-11-23 03:54:33.315887: val_loss -0.7551 +2024-11-23 03:54:33.315965: Pseudo dice [0.8351] +2024-11-23 03:54:33.316064: Epoch time: 19.17 s +2024-11-23 03:54:34.245107: +2024-11-23 03:54:34.245311: Epoch 7552 +2024-11-23 03:54:34.245427: Current learning rate: 0.00075 +2024-11-23 03:54:54.009644: train_loss -0.8382 +2024-11-23 03:54:54.009864: val_loss -0.7754 +2024-11-23 03:54:54.009946: Pseudo dice [0.8539] +2024-11-23 03:54:54.010030: Epoch time: 19.77 s +2024-11-23 03:54:54.975285: +2024-11-23 03:54:54.975478: Epoch 7553 +2024-11-23 03:54:54.975595: Current learning rate: 0.00075 +2024-11-23 03:55:12.821779: train_loss -0.8362 +2024-11-23 03:55:12.822011: val_loss -0.7557 +2024-11-23 03:55:12.822087: Pseudo dice [0.8395] +2024-11-23 03:55:12.822162: Epoch time: 17.85 s +2024-11-23 03:55:13.742183: +2024-11-23 03:55:13.742404: Epoch 7554 +2024-11-23 03:55:13.742519: Current learning rate: 0.00074 +2024-11-23 03:55:32.125174: train_loss -0.8297 +2024-11-23 03:55:32.125421: val_loss -0.763 +2024-11-23 03:55:32.125503: Pseudo dice [0.8349] +2024-11-23 03:55:32.125587: Epoch time: 18.38 s +2024-11-23 03:55:33.546020: +2024-11-23 03:55:33.546213: Epoch 7555 +2024-11-23 03:55:33.546324: Current learning rate: 0.00074 +2024-11-23 03:55:53.207669: train_loss -0.8283 +2024-11-23 03:55:53.207944: val_loss -0.7776 +2024-11-23 03:55:53.208034: Pseudo dice [0.8345] +2024-11-23 03:55:53.208134: Epoch time: 19.66 s +2024-11-23 03:55:54.127249: +2024-11-23 03:55:54.127489: Epoch 7556 +2024-11-23 03:55:54.127603: Current learning rate: 0.00074 +2024-11-23 03:56:12.766120: train_loss -0.8361 +2024-11-23 03:56:12.766342: val_loss -0.7669 +2024-11-23 03:56:12.766417: Pseudo dice [0.8379] +2024-11-23 03:56:12.766493: Epoch time: 18.64 s +2024-11-23 03:56:13.685297: +2024-11-23 03:56:13.685537: Epoch 7557 +2024-11-23 03:56:13.685649: Current learning rate: 0.00074 +2024-11-23 03:56:31.200954: train_loss -0.8333 +2024-11-23 03:56:31.201176: val_loss -0.7516 +2024-11-23 03:56:31.201249: Pseudo dice [0.8406] +2024-11-23 03:56:31.201323: Epoch time: 17.52 s +2024-11-23 03:56:32.118438: +2024-11-23 03:56:32.118659: Epoch 7558 +2024-11-23 03:56:32.118774: Current learning rate: 0.00074 +2024-11-23 03:56:52.334241: train_loss -0.838 +2024-11-23 03:56:52.334525: val_loss -0.77 +2024-11-23 03:56:52.334604: Pseudo dice [0.8278] +2024-11-23 03:56:52.334690: Epoch time: 20.22 s +2024-11-23 03:56:53.255346: +2024-11-23 03:56:53.255543: Epoch 7559 +2024-11-23 03:56:53.255660: Current learning rate: 0.00074 +2024-11-23 03:57:11.921488: train_loss -0.8354 +2024-11-23 03:57:11.921695: val_loss -0.7784 +2024-11-23 03:57:11.921792: Pseudo dice [0.8535] +2024-11-23 03:57:11.921871: Epoch time: 18.67 s +2024-11-23 03:57:12.843054: +2024-11-23 03:57:12.843276: Epoch 7560 +2024-11-23 03:57:12.843393: Current learning rate: 0.00074 +2024-11-23 03:57:31.607029: train_loss -0.8323 +2024-11-23 03:57:31.607253: val_loss -0.752 +2024-11-23 03:57:31.607328: Pseudo dice [0.8295] +2024-11-23 03:57:31.607409: Epoch time: 18.76 s +2024-11-23 03:57:32.578655: +2024-11-23 03:57:32.578930: Epoch 7561 +2024-11-23 03:57:32.579050: Current learning rate: 0.00073 +2024-11-23 03:57:52.229231: train_loss -0.8331 +2024-11-23 03:57:52.229461: val_loss -0.7672 +2024-11-23 03:57:52.229536: Pseudo dice [0.8501] +2024-11-23 03:57:52.229615: Epoch time: 19.65 s +2024-11-23 03:57:53.330265: +2024-11-23 03:57:53.330525: Epoch 7562 +2024-11-23 03:57:53.330636: Current learning rate: 0.00073 +2024-11-23 03:58:11.890705: train_loss -0.8317 +2024-11-23 03:58:11.895969: val_loss -0.7597 +2024-11-23 03:58:11.896095: Pseudo dice [0.8245] +2024-11-23 03:58:11.896185: Epoch time: 18.56 s +2024-11-23 03:58:12.894327: +2024-11-23 03:58:12.894525: Epoch 7563 +2024-11-23 03:58:12.894645: Current learning rate: 0.00073 +2024-11-23 03:58:31.106801: train_loss -0.8356 +2024-11-23 03:58:31.107032: val_loss -0.7535 +2024-11-23 03:58:31.107109: Pseudo dice [0.8295] +2024-11-23 03:58:31.108740: Epoch time: 18.21 s +2024-11-23 03:58:32.052125: +2024-11-23 03:58:32.052414: Epoch 7564 +2024-11-23 03:58:32.052526: Current learning rate: 0.00073 +2024-11-23 03:58:50.390476: train_loss -0.8319 +2024-11-23 03:58:50.390699: val_loss -0.7674 +2024-11-23 03:58:50.390780: Pseudo dice [0.8428] +2024-11-23 03:58:50.390859: Epoch time: 18.34 s +2024-11-23 03:58:51.318559: +2024-11-23 03:58:51.318765: Epoch 7565 +2024-11-23 03:58:51.318881: Current learning rate: 0.00073 +2024-11-23 03:59:10.371655: train_loss -0.8346 +2024-11-23 03:59:10.371862: val_loss -0.7634 +2024-11-23 03:59:10.371934: Pseudo dice [0.8277] +2024-11-23 03:59:10.372019: Epoch time: 19.05 s +2024-11-23 03:59:11.299613: +2024-11-23 03:59:11.299840: Epoch 7566 +2024-11-23 03:59:11.299954: Current learning rate: 0.00073 +2024-11-23 03:59:29.760879: train_loss -0.8383 +2024-11-23 03:59:29.761394: val_loss -0.7591 +2024-11-23 03:59:29.761497: Pseudo dice [0.8347] +2024-11-23 03:59:29.761575: Epoch time: 18.46 s +2024-11-23 03:59:30.680701: +2024-11-23 03:59:30.680932: Epoch 7567 +2024-11-23 03:59:30.681047: Current learning rate: 0.00072 +2024-11-23 03:59:50.195850: train_loss -0.8376 +2024-11-23 03:59:50.196079: val_loss -0.7732 +2024-11-23 03:59:50.196154: Pseudo dice [0.8162] +2024-11-23 03:59:50.196239: Epoch time: 19.52 s +2024-11-23 03:59:51.112357: +2024-11-23 03:59:51.112580: Epoch 7568 +2024-11-23 03:59:51.112695: Current learning rate: 0.00072 +2024-11-23 04:00:09.518687: train_loss -0.8369 +2024-11-23 04:00:09.518903: val_loss -0.7581 +2024-11-23 04:00:09.518976: Pseudo dice [0.8425] +2024-11-23 04:00:09.519063: Epoch time: 18.41 s +2024-11-23 04:00:10.548060: +2024-11-23 04:00:10.548290: Epoch 7569 +2024-11-23 04:00:10.548407: Current learning rate: 0.00072 +2024-11-23 04:00:30.436631: train_loss -0.8324 +2024-11-23 04:00:30.436868: val_loss -0.7507 +2024-11-23 04:00:30.436942: Pseudo dice [0.8292] +2024-11-23 04:00:30.437031: Epoch time: 19.89 s +2024-11-23 04:00:31.463188: +2024-11-23 04:00:31.463417: Epoch 7570 +2024-11-23 04:00:31.463531: Current learning rate: 0.00072 +2024-11-23 04:00:50.026637: train_loss -0.8338 +2024-11-23 04:00:50.026873: val_loss -0.761 +2024-11-23 04:00:50.026954: Pseudo dice [0.8325] +2024-11-23 04:00:50.027061: Epoch time: 18.56 s +2024-11-23 04:00:50.953796: +2024-11-23 04:00:50.954016: Epoch 7571 +2024-11-23 04:00:50.954128: Current learning rate: 0.00072 +2024-11-23 04:01:11.024580: train_loss -0.8321 +2024-11-23 04:01:11.024839: val_loss -0.7643 +2024-11-23 04:01:11.024966: Pseudo dice [0.8383] +2024-11-23 04:01:11.025052: Epoch time: 20.07 s +2024-11-23 04:01:11.985987: +2024-11-23 04:01:11.986197: Epoch 7572 +2024-11-23 04:01:11.986310: Current learning rate: 0.00072 +2024-11-23 04:01:30.350439: train_loss -0.8341 +2024-11-23 04:01:30.350664: val_loss -0.7447 +2024-11-23 04:01:30.350744: Pseudo dice [0.8343] +2024-11-23 04:01:30.350826: Epoch time: 18.37 s +2024-11-23 04:01:31.310309: +2024-11-23 04:01:31.310512: Epoch 7573 +2024-11-23 04:01:31.310624: Current learning rate: 0.00072 +2024-11-23 04:01:50.446538: train_loss -0.835 +2024-11-23 04:01:50.446775: val_loss -0.7586 +2024-11-23 04:01:50.446852: Pseudo dice [0.837] +2024-11-23 04:01:50.446942: Epoch time: 19.14 s +2024-11-23 04:01:51.430116: +2024-11-23 04:01:51.430356: Epoch 7574 +2024-11-23 04:01:51.430472: Current learning rate: 0.00071 +2024-11-23 04:02:10.151712: train_loss -0.8265 +2024-11-23 04:02:10.158224: val_loss -0.7677 +2024-11-23 04:02:10.158364: Pseudo dice [0.8253] +2024-11-23 04:02:10.158449: Epoch time: 18.72 s +2024-11-23 04:02:11.126562: +2024-11-23 04:02:11.126838: Epoch 7575 +2024-11-23 04:02:11.126956: Current learning rate: 0.00071 +2024-11-23 04:02:28.579485: train_loss -0.8379 +2024-11-23 04:02:28.579838: val_loss -0.7502 +2024-11-23 04:02:28.579921: Pseudo dice [0.8523] +2024-11-23 04:02:28.580003: Epoch time: 17.45 s +2024-11-23 04:02:29.535899: +2024-11-23 04:02:29.536138: Epoch 7576 +2024-11-23 04:02:29.536255: Current learning rate: 0.00071 +2024-11-23 04:02:48.911063: train_loss -0.8325 +2024-11-23 04:02:48.936797: val_loss -0.7766 +2024-11-23 04:02:48.936961: Pseudo dice [0.8317] +2024-11-23 04:02:48.937068: Epoch time: 19.38 s +2024-11-23 04:02:49.865444: +2024-11-23 04:02:49.865658: Epoch 7577 +2024-11-23 04:02:49.865774: Current learning rate: 0.00071 +2024-11-23 04:03:09.391747: train_loss -0.8337 +2024-11-23 04:03:09.391961: val_loss -0.7543 +2024-11-23 04:03:09.392045: Pseudo dice [0.8325] +2024-11-23 04:03:09.397292: Epoch time: 19.53 s +2024-11-23 04:03:10.779978: +2024-11-23 04:03:10.780193: Epoch 7578 +2024-11-23 04:03:10.780311: Current learning rate: 0.00071 +2024-11-23 04:03:30.662660: train_loss -0.8344 +2024-11-23 04:03:30.665075: val_loss -0.7843 +2024-11-23 04:03:30.665179: Pseudo dice [0.8337] +2024-11-23 04:03:30.665264: Epoch time: 19.88 s +2024-11-23 04:03:31.599662: +2024-11-23 04:03:31.599950: Epoch 7579 +2024-11-23 04:03:31.600074: Current learning rate: 0.00071 +2024-11-23 04:03:50.611047: train_loss -0.8344 +2024-11-23 04:03:50.611276: val_loss -0.7344 +2024-11-23 04:03:50.611357: Pseudo dice [0.8106] +2024-11-23 04:03:50.611443: Epoch time: 19.01 s +2024-11-23 04:03:51.538146: +2024-11-23 04:03:51.538387: Epoch 7580 +2024-11-23 04:03:51.538495: Current learning rate: 0.0007 +2024-11-23 04:04:10.627972: train_loss -0.8366 +2024-11-23 04:04:10.628201: val_loss -0.7647 +2024-11-23 04:04:10.628276: Pseudo dice [0.8276] +2024-11-23 04:04:10.628375: Epoch time: 19.09 s +2024-11-23 04:04:11.651832: +2024-11-23 04:04:11.652081: Epoch 7581 +2024-11-23 04:04:11.652203: Current learning rate: 0.0007 +2024-11-23 04:04:30.349563: train_loss -0.8399 +2024-11-23 04:04:30.351982: val_loss -0.7666 +2024-11-23 04:04:30.352095: Pseudo dice [0.8398] +2024-11-23 04:04:30.352178: Epoch time: 18.7 s +2024-11-23 04:04:31.391666: +2024-11-23 04:04:31.391881: Epoch 7582 +2024-11-23 04:04:31.391999: Current learning rate: 0.0007 +2024-11-23 04:04:49.911649: train_loss -0.8368 +2024-11-23 04:04:49.914006: val_loss -0.7677 +2024-11-23 04:04:49.914126: Pseudo dice [0.8455] +2024-11-23 04:04:49.914206: Epoch time: 18.52 s +2024-11-23 04:04:50.840093: +2024-11-23 04:04:50.840337: Epoch 7583 +2024-11-23 04:04:50.840454: Current learning rate: 0.0007 +2024-11-23 04:05:09.427854: train_loss -0.8343 +2024-11-23 04:05:09.428097: val_loss -0.7447 +2024-11-23 04:05:09.428173: Pseudo dice [0.8115] +2024-11-23 04:05:09.428259: Epoch time: 18.59 s +2024-11-23 04:05:10.345388: +2024-11-23 04:05:10.345624: Epoch 7584 +2024-11-23 04:05:10.345743: Current learning rate: 0.0007 +2024-11-23 04:05:29.612888: train_loss -0.8289 +2024-11-23 04:05:29.613178: val_loss -0.7773 +2024-11-23 04:05:29.613256: Pseudo dice [0.8301] +2024-11-23 04:05:29.613340: Epoch time: 19.27 s +2024-11-23 04:05:30.534854: +2024-11-23 04:05:30.535084: Epoch 7585 +2024-11-23 04:05:30.535195: Current learning rate: 0.0007 +2024-11-23 04:05:48.465611: train_loss -0.8332 +2024-11-23 04:05:48.465829: val_loss -0.7596 +2024-11-23 04:05:48.465905: Pseudo dice [0.828] +2024-11-23 04:05:48.465988: Epoch time: 17.93 s +2024-11-23 04:05:49.390066: +2024-11-23 04:05:49.390360: Epoch 7586 +2024-11-23 04:05:49.390470: Current learning rate: 0.0007 +2024-11-23 04:06:07.115457: train_loss -0.8371 +2024-11-23 04:06:07.115691: val_loss -0.7752 +2024-11-23 04:06:07.115767: Pseudo dice [0.8403] +2024-11-23 04:06:07.115844: Epoch time: 17.73 s +2024-11-23 04:06:08.040500: +2024-11-23 04:06:08.040726: Epoch 7587 +2024-11-23 04:06:08.040842: Current learning rate: 0.00069 +2024-11-23 04:06:27.186852: train_loss -0.8362 +2024-11-23 04:06:27.187098: val_loss -0.7672 +2024-11-23 04:06:27.187176: Pseudo dice [0.8379] +2024-11-23 04:06:27.187261: Epoch time: 19.15 s +2024-11-23 04:06:28.118766: +2024-11-23 04:06:28.119078: Epoch 7588 +2024-11-23 04:06:28.119195: Current learning rate: 0.00069 +2024-11-23 04:06:46.917572: train_loss -0.8272 +2024-11-23 04:06:46.917834: val_loss -0.7702 +2024-11-23 04:06:46.917907: Pseudo dice [0.8371] +2024-11-23 04:06:46.917982: Epoch time: 18.8 s +2024-11-23 04:06:47.843924: +2024-11-23 04:06:47.844119: Epoch 7589 +2024-11-23 04:06:47.873620: Current learning rate: 0.00069 +2024-11-23 04:07:06.788374: train_loss -0.8353 +2024-11-23 04:07:06.788602: val_loss -0.7549 +2024-11-23 04:07:06.788676: Pseudo dice [0.8254] +2024-11-23 04:07:06.788751: Epoch time: 18.95 s +2024-11-23 04:07:07.708683: +2024-11-23 04:07:07.708921: Epoch 7590 +2024-11-23 04:07:07.709037: Current learning rate: 0.00069 +2024-11-23 04:07:26.104647: train_loss -0.8379 +2024-11-23 04:07:26.104888: val_loss -0.7671 +2024-11-23 04:07:26.104965: Pseudo dice [0.829] +2024-11-23 04:07:26.105080: Epoch time: 18.4 s +2024-11-23 04:07:27.029540: +2024-11-23 04:07:27.029756: Epoch 7591 +2024-11-23 04:07:27.029874: Current learning rate: 0.00069 +2024-11-23 04:07:45.954972: train_loss -0.8301 +2024-11-23 04:07:45.955196: val_loss -0.7586 +2024-11-23 04:07:45.955270: Pseudo dice [0.8475] +2024-11-23 04:07:45.955347: Epoch time: 18.93 s +2024-11-23 04:07:46.878352: +2024-11-23 04:07:46.878574: Epoch 7592 +2024-11-23 04:07:46.878685: Current learning rate: 0.00069 +2024-11-23 04:08:05.773290: train_loss -0.83 +2024-11-23 04:08:05.773502: val_loss -0.7624 +2024-11-23 04:08:05.773583: Pseudo dice [0.8536] +2024-11-23 04:08:05.773662: Epoch time: 18.9 s +2024-11-23 04:08:06.759671: +2024-11-23 04:08:06.759881: Epoch 7593 +2024-11-23 04:08:06.759999: Current learning rate: 0.00069 +2024-11-23 04:08:25.468117: train_loss -0.8354 +2024-11-23 04:08:25.468336: val_loss -0.7657 +2024-11-23 04:08:25.468413: Pseudo dice [0.8376] +2024-11-23 04:08:25.468495: Epoch time: 18.71 s +2024-11-23 04:08:26.393710: +2024-11-23 04:08:26.393928: Epoch 7594 +2024-11-23 04:08:26.394051: Current learning rate: 0.00068 +2024-11-23 04:08:45.310692: train_loss -0.831 +2024-11-23 04:08:45.310921: val_loss -0.7589 +2024-11-23 04:08:45.311018: Pseudo dice [0.83] +2024-11-23 04:08:45.311097: Epoch time: 18.92 s +2024-11-23 04:08:46.231093: +2024-11-23 04:08:46.231356: Epoch 7595 +2024-11-23 04:08:46.231474: Current learning rate: 0.00068 +2024-11-23 04:09:04.571949: train_loss -0.8323 +2024-11-23 04:09:04.572172: val_loss -0.7789 +2024-11-23 04:09:04.572251: Pseudo dice [0.8418] +2024-11-23 04:09:04.572331: Epoch time: 18.34 s +2024-11-23 04:09:05.497512: +2024-11-23 04:09:05.497722: Epoch 7596 +2024-11-23 04:09:05.497838: Current learning rate: 0.00068 +2024-11-23 04:09:23.920171: train_loss -0.8322 +2024-11-23 04:09:23.920384: val_loss -0.7517 +2024-11-23 04:09:23.920460: Pseudo dice [0.8272] +2024-11-23 04:09:23.920539: Epoch time: 18.42 s +2024-11-23 04:09:24.837698: +2024-11-23 04:09:24.837945: Epoch 7597 +2024-11-23 04:09:24.838063: Current learning rate: 0.00068 +2024-11-23 04:09:43.813555: train_loss -0.8345 +2024-11-23 04:09:43.813795: val_loss -0.7477 +2024-11-23 04:09:43.813872: Pseudo dice [0.8324] +2024-11-23 04:09:43.813962: Epoch time: 18.98 s +2024-11-23 04:09:44.732856: +2024-11-23 04:09:44.733054: Epoch 7598 +2024-11-23 04:09:44.733163: Current learning rate: 0.00068 +2024-11-23 04:10:03.514285: train_loss -0.8352 +2024-11-23 04:10:03.514505: val_loss -0.7637 +2024-11-23 04:10:03.514581: Pseudo dice [0.8496] +2024-11-23 04:10:03.514657: Epoch time: 18.78 s +2024-11-23 04:10:04.432339: +2024-11-23 04:10:04.432537: Epoch 7599 +2024-11-23 04:10:04.432653: Current learning rate: 0.00068 +2024-11-23 04:10:22.412568: train_loss -0.8318 +2024-11-23 04:10:22.412796: val_loss -0.7675 +2024-11-23 04:10:22.412871: Pseudo dice [0.8344] +2024-11-23 04:10:22.412950: Epoch time: 17.98 s +2024-11-23 04:10:23.696087: +2024-11-23 04:10:23.696323: Epoch 7600 +2024-11-23 04:10:23.696446: Current learning rate: 0.00067 +2024-11-23 04:10:42.925570: train_loss -0.8344 +2024-11-23 04:10:42.926093: val_loss -0.7681 +2024-11-23 04:10:42.926198: Pseudo dice [0.8373] +2024-11-23 04:10:42.926282: Epoch time: 19.23 s +2024-11-23 04:10:43.847803: +2024-11-23 04:10:43.848025: Epoch 7601 +2024-11-23 04:10:43.848137: Current learning rate: 0.00067 +2024-11-23 04:11:02.393423: train_loss -0.8312 +2024-11-23 04:11:02.393794: val_loss -0.7719 +2024-11-23 04:11:02.393886: Pseudo dice [0.8389] +2024-11-23 04:11:02.393975: Epoch time: 18.55 s +2024-11-23 04:11:03.318558: +2024-11-23 04:11:03.318766: Epoch 7602 +2024-11-23 04:11:03.318880: Current learning rate: 0.00067 +2024-11-23 04:11:20.615152: train_loss -0.8388 +2024-11-23 04:11:20.615365: val_loss -0.7586 +2024-11-23 04:11:20.615438: Pseudo dice [0.8398] +2024-11-23 04:11:20.615514: Epoch time: 17.3 s +2024-11-23 04:11:21.709665: +2024-11-23 04:11:21.709908: Epoch 7603 +2024-11-23 04:11:21.710026: Current learning rate: 0.00067 +2024-11-23 04:11:39.754636: train_loss -0.832 +2024-11-23 04:11:39.754852: val_loss -0.7601 +2024-11-23 04:11:39.754926: Pseudo dice [0.8382] +2024-11-23 04:11:39.755010: Epoch time: 18.05 s +2024-11-23 04:11:40.852433: +2024-11-23 04:11:40.852641: Epoch 7604 +2024-11-23 04:11:40.852753: Current learning rate: 0.00067 +2024-11-23 04:11:59.439569: train_loss -0.8351 +2024-11-23 04:11:59.439813: val_loss -0.7758 +2024-11-23 04:11:59.439889: Pseudo dice [0.8495] +2024-11-23 04:11:59.439972: Epoch time: 18.59 s +2024-11-23 04:12:00.363262: +2024-11-23 04:12:00.363481: Epoch 7605 +2024-11-23 04:12:00.363593: Current learning rate: 0.00067 +2024-11-23 04:12:19.171181: train_loss -0.8345 +2024-11-23 04:12:19.171404: val_loss -0.7749 +2024-11-23 04:12:19.171479: Pseudo dice [0.8341] +2024-11-23 04:12:19.171558: Epoch time: 18.81 s +2024-11-23 04:12:20.095886: +2024-11-23 04:12:20.096171: Epoch 7606 +2024-11-23 04:12:20.096285: Current learning rate: 0.00067 +2024-11-23 04:12:38.667305: train_loss -0.8322 +2024-11-23 04:12:38.667513: val_loss -0.7493 +2024-11-23 04:12:38.667586: Pseudo dice [0.8418] +2024-11-23 04:12:38.667662: Epoch time: 18.57 s +2024-11-23 04:12:39.590260: +2024-11-23 04:12:39.590462: Epoch 7607 +2024-11-23 04:12:39.590580: Current learning rate: 0.00066 +2024-11-23 04:12:57.617159: train_loss -0.8341 +2024-11-23 04:12:57.617374: val_loss -0.7697 +2024-11-23 04:12:57.617453: Pseudo dice [0.8496] +2024-11-23 04:12:57.617539: Epoch time: 18.03 s +2024-11-23 04:12:58.554656: +2024-11-23 04:12:58.554892: Epoch 7608 +2024-11-23 04:12:58.555018: Current learning rate: 0.00066 +2024-11-23 04:13:17.314706: train_loss -0.8345 +2024-11-23 04:13:17.314954: val_loss -0.7809 +2024-11-23 04:13:17.315035: Pseudo dice [0.8472] +2024-11-23 04:13:17.315114: Epoch time: 18.76 s +2024-11-23 04:13:18.407746: +2024-11-23 04:13:18.407954: Epoch 7609 +2024-11-23 04:13:18.408076: Current learning rate: 0.00066 +2024-11-23 04:13:37.908760: train_loss -0.8301 +2024-11-23 04:13:37.908981: val_loss -0.7527 +2024-11-23 04:13:37.909062: Pseudo dice [0.8354] +2024-11-23 04:13:37.909138: Epoch time: 19.5 s +2024-11-23 04:13:38.832561: +2024-11-23 04:13:38.832775: Epoch 7610 +2024-11-23 04:13:38.832892: Current learning rate: 0.00066 +2024-11-23 04:13:57.718678: train_loss -0.8346 +2024-11-23 04:13:57.718909: val_loss -0.7558 +2024-11-23 04:13:57.718986: Pseudo dice [0.8354] +2024-11-23 04:13:57.719072: Epoch time: 18.89 s +2024-11-23 04:13:58.743531: +2024-11-23 04:13:58.743775: Epoch 7611 +2024-11-23 04:13:58.743894: Current learning rate: 0.00066 +2024-11-23 04:14:17.945385: train_loss -0.8316 +2024-11-23 04:14:17.947804: val_loss -0.7379 +2024-11-23 04:14:17.947916: Pseudo dice [0.828] +2024-11-23 04:14:17.948016: Epoch time: 19.2 s +2024-11-23 04:14:19.287748: +2024-11-23 04:14:19.288026: Epoch 7612 +2024-11-23 04:14:19.288145: Current learning rate: 0.00066 +2024-11-23 04:14:38.136988: train_loss -0.8368 +2024-11-23 04:14:38.137242: val_loss -0.7511 +2024-11-23 04:14:38.137324: Pseudo dice [0.831] +2024-11-23 04:14:38.137407: Epoch time: 18.85 s +2024-11-23 04:14:39.060852: +2024-11-23 04:14:39.061061: Epoch 7613 +2024-11-23 04:14:39.061176: Current learning rate: 0.00065 +2024-11-23 04:14:59.472550: train_loss -0.8298 +2024-11-23 04:14:59.472765: val_loss -0.7672 +2024-11-23 04:14:59.472838: Pseudo dice [0.8322] +2024-11-23 04:14:59.472915: Epoch time: 20.41 s +2024-11-23 04:15:00.464270: +2024-11-23 04:15:00.464528: Epoch 7614 +2024-11-23 04:15:00.464644: Current learning rate: 0.00065 +2024-11-23 04:15:18.969002: train_loss -0.8366 +2024-11-23 04:15:18.969216: val_loss -0.7598 +2024-11-23 04:15:18.969291: Pseudo dice [0.8331] +2024-11-23 04:15:18.969369: Epoch time: 18.51 s +2024-11-23 04:15:19.893948: +2024-11-23 04:15:19.894193: Epoch 7615 +2024-11-23 04:15:19.894311: Current learning rate: 0.00065 +2024-11-23 04:15:38.923375: train_loss -0.8264 +2024-11-23 04:15:38.923609: val_loss -0.7548 +2024-11-23 04:15:38.923682: Pseudo dice [0.8566] +2024-11-23 04:15:38.923774: Epoch time: 19.03 s +2024-11-23 04:15:39.851820: +2024-11-23 04:15:39.852077: Epoch 7616 +2024-11-23 04:15:39.852184: Current learning rate: 0.00065 +2024-11-23 04:15:59.076888: train_loss -0.8298 +2024-11-23 04:15:59.077178: val_loss -0.7662 +2024-11-23 04:15:59.077256: Pseudo dice [0.8427] +2024-11-23 04:15:59.077331: Epoch time: 19.23 s +2024-11-23 04:15:59.997087: +2024-11-23 04:15:59.997355: Epoch 7617 +2024-11-23 04:15:59.997472: Current learning rate: 0.00065 +2024-11-23 04:16:19.193949: train_loss -0.8315 +2024-11-23 04:16:19.194175: val_loss -0.748 +2024-11-23 04:16:19.194250: Pseudo dice [0.8204] +2024-11-23 04:16:19.194327: Epoch time: 19.2 s +2024-11-23 04:16:20.111953: +2024-11-23 04:16:20.112186: Epoch 7618 +2024-11-23 04:16:20.112302: Current learning rate: 0.00065 +2024-11-23 04:16:38.941432: train_loss -0.837 +2024-11-23 04:16:38.941645: val_loss -0.7584 +2024-11-23 04:16:38.941716: Pseudo dice [0.8506] +2024-11-23 04:16:38.941798: Epoch time: 18.83 s +2024-11-23 04:16:39.867791: +2024-11-23 04:16:39.868032: Epoch 7619 +2024-11-23 04:16:39.868145: Current learning rate: 0.00065 +2024-11-23 04:16:58.261015: train_loss -0.8416 +2024-11-23 04:16:58.261236: val_loss -0.7473 +2024-11-23 04:16:58.261311: Pseudo dice [0.8299] +2024-11-23 04:16:58.261384: Epoch time: 18.39 s +2024-11-23 04:16:59.188020: +2024-11-23 04:16:59.188225: Epoch 7620 +2024-11-23 04:16:59.188344: Current learning rate: 0.00064 +2024-11-23 04:17:16.739469: train_loss -0.8385 +2024-11-23 04:17:16.739766: val_loss -0.78 +2024-11-23 04:17:16.739847: Pseudo dice [0.8334] +2024-11-23 04:17:16.739926: Epoch time: 17.55 s +2024-11-23 04:17:17.664834: +2024-11-23 04:17:17.665045: Epoch 7621 +2024-11-23 04:17:17.665159: Current learning rate: 0.00064 +2024-11-23 04:17:35.527562: train_loss -0.8357 +2024-11-23 04:17:35.527787: val_loss -0.7701 +2024-11-23 04:17:35.527866: Pseudo dice [0.8334] +2024-11-23 04:17:35.527943: Epoch time: 17.86 s +2024-11-23 04:17:36.554498: +2024-11-23 04:17:36.554697: Epoch 7622 +2024-11-23 04:17:36.554809: Current learning rate: 0.00064 +2024-11-23 04:17:55.167924: train_loss -0.8371 +2024-11-23 04:17:55.168164: val_loss -0.7671 +2024-11-23 04:17:55.168242: Pseudo dice [0.8451] +2024-11-23 04:17:55.168326: Epoch time: 18.61 s +2024-11-23 04:17:56.470221: +2024-11-23 04:17:56.470442: Epoch 7623 +2024-11-23 04:17:56.470557: Current learning rate: 0.00064 +2024-11-23 04:18:16.164151: train_loss -0.8318 +2024-11-23 04:18:16.164375: val_loss -0.781 +2024-11-23 04:18:16.164448: Pseudo dice [0.8609] +2024-11-23 04:18:16.164596: Epoch time: 19.69 s +2024-11-23 04:18:17.092190: +2024-11-23 04:18:17.092397: Epoch 7624 +2024-11-23 04:18:17.092512: Current learning rate: 0.00064 +2024-11-23 04:18:36.018700: train_loss -0.8378 +2024-11-23 04:18:36.018916: val_loss -0.7732 +2024-11-23 04:18:36.018998: Pseudo dice [0.8454] +2024-11-23 04:18:36.019075: Epoch time: 18.93 s +2024-11-23 04:18:36.949864: +2024-11-23 04:18:36.950100: Epoch 7625 +2024-11-23 04:18:36.950215: Current learning rate: 0.00064 +2024-11-23 04:18:56.582845: train_loss -0.8383 +2024-11-23 04:18:56.583093: val_loss -0.7674 +2024-11-23 04:18:56.583171: Pseudo dice [0.8221] +2024-11-23 04:18:56.583252: Epoch time: 19.63 s +2024-11-23 04:18:57.518427: +2024-11-23 04:18:57.518626: Epoch 7626 +2024-11-23 04:18:57.518742: Current learning rate: 0.00064 +2024-11-23 04:19:15.558734: train_loss -0.8333 +2024-11-23 04:19:15.558982: val_loss -0.7706 +2024-11-23 04:19:15.559062: Pseudo dice [0.8384] +2024-11-23 04:19:15.559137: Epoch time: 18.04 s +2024-11-23 04:19:16.492170: +2024-11-23 04:19:16.492396: Epoch 7627 +2024-11-23 04:19:16.492511: Current learning rate: 0.00063 +2024-11-23 04:19:35.130014: train_loss -0.8352 +2024-11-23 04:19:35.130229: val_loss -0.748 +2024-11-23 04:19:35.130301: Pseudo dice [0.8259] +2024-11-23 04:19:35.130378: Epoch time: 18.64 s +2024-11-23 04:19:36.062113: +2024-11-23 04:19:36.062312: Epoch 7628 +2024-11-23 04:19:36.062426: Current learning rate: 0.00063 +2024-11-23 04:19:54.847073: train_loss -0.8378 +2024-11-23 04:19:54.847348: val_loss -0.7503 +2024-11-23 04:19:54.847428: Pseudo dice [0.8294] +2024-11-23 04:19:54.847509: Epoch time: 18.79 s +2024-11-23 04:19:55.856248: +2024-11-23 04:19:55.856489: Epoch 7629 +2024-11-23 04:19:55.856602: Current learning rate: 0.00063 +2024-11-23 04:20:16.000545: train_loss -0.8363 +2024-11-23 04:20:16.002920: val_loss -0.7702 +2024-11-23 04:20:16.003043: Pseudo dice [0.83] +2024-11-23 04:20:16.003128: Epoch time: 20.15 s +2024-11-23 04:20:17.003220: +2024-11-23 04:20:17.003473: Epoch 7630 +2024-11-23 04:20:17.003591: Current learning rate: 0.00063 +2024-11-23 04:20:35.752664: train_loss -0.8292 +2024-11-23 04:20:35.752886: val_loss -0.7825 +2024-11-23 04:20:35.752964: Pseudo dice [0.8562] +2024-11-23 04:20:35.753049: Epoch time: 18.75 s +2024-11-23 04:20:36.679056: +2024-11-23 04:20:36.679266: Epoch 7631 +2024-11-23 04:20:36.679379: Current learning rate: 0.00063 +2024-11-23 04:20:54.439638: train_loss -0.8391 +2024-11-23 04:20:54.439856: val_loss -0.7489 +2024-11-23 04:20:54.439930: Pseudo dice [0.8412] +2024-11-23 04:20:54.440012: Epoch time: 17.76 s +2024-11-23 04:20:55.372984: +2024-11-23 04:20:55.373217: Epoch 7632 +2024-11-23 04:20:55.373333: Current learning rate: 0.00063 +2024-11-23 04:21:13.388596: train_loss -0.8389 +2024-11-23 04:21:13.388895: val_loss -0.7573 +2024-11-23 04:21:13.388972: Pseudo dice [0.8266] +2024-11-23 04:21:13.389068: Epoch time: 18.02 s +2024-11-23 04:21:14.314689: +2024-11-23 04:21:14.314917: Epoch 7633 +2024-11-23 04:21:14.315040: Current learning rate: 0.00062 +2024-11-23 04:21:32.706488: train_loss -0.8323 +2024-11-23 04:21:32.706719: val_loss -0.7664 +2024-11-23 04:21:32.706798: Pseudo dice [0.8273] +2024-11-23 04:21:32.706877: Epoch time: 18.39 s +2024-11-23 04:21:33.632796: +2024-11-23 04:21:33.633008: Epoch 7634 +2024-11-23 04:21:33.633122: Current learning rate: 0.00062 +2024-11-23 04:21:52.048939: train_loss -0.835 +2024-11-23 04:21:52.049161: val_loss -0.7956 +2024-11-23 04:21:52.049234: Pseudo dice [0.8434] +2024-11-23 04:21:52.049309: Epoch time: 18.42 s +2024-11-23 04:21:53.344285: +2024-11-23 04:21:53.344486: Epoch 7635 +2024-11-23 04:21:53.344602: Current learning rate: 0.00062 +2024-11-23 04:22:12.043971: train_loss -0.8377 +2024-11-23 04:22:12.044230: val_loss -0.7388 +2024-11-23 04:22:12.044310: Pseudo dice [0.8338] +2024-11-23 04:22:12.044394: Epoch time: 18.7 s +2024-11-23 04:22:12.976031: +2024-11-23 04:22:12.976259: Epoch 7636 +2024-11-23 04:22:12.976369: Current learning rate: 0.00062 +2024-11-23 04:22:31.063337: train_loss -0.8331 +2024-11-23 04:22:31.063560: val_loss -0.7542 +2024-11-23 04:22:31.063637: Pseudo dice [0.8511] +2024-11-23 04:22:31.063715: Epoch time: 18.09 s +2024-11-23 04:22:31.987872: +2024-11-23 04:22:31.988101: Epoch 7637 +2024-11-23 04:22:31.988213: Current learning rate: 0.00062 +2024-11-23 04:22:50.588137: train_loss -0.8337 +2024-11-23 04:22:50.588347: val_loss -0.7413 +2024-11-23 04:22:50.588421: Pseudo dice [0.8286] +2024-11-23 04:22:50.588496: Epoch time: 18.6 s +2024-11-23 04:22:51.543856: +2024-11-23 04:22:51.544097: Epoch 7638 +2024-11-23 04:22:51.544210: Current learning rate: 0.00062 +2024-11-23 04:23:09.432061: train_loss -0.8389 +2024-11-23 04:23:09.432282: val_loss -0.7578 +2024-11-23 04:23:09.432354: Pseudo dice [0.8367] +2024-11-23 04:23:09.432431: Epoch time: 17.89 s +2024-11-23 04:23:10.355643: +2024-11-23 04:23:10.355854: Epoch 7639 +2024-11-23 04:23:10.355966: Current learning rate: 0.00062 +2024-11-23 04:23:30.504555: train_loss -0.8336 +2024-11-23 04:23:30.504805: val_loss -0.7761 +2024-11-23 04:23:30.507828: Pseudo dice [0.8591] +2024-11-23 04:23:30.507999: Epoch time: 20.15 s +2024-11-23 04:23:31.515379: +2024-11-23 04:23:31.515588: Epoch 7640 +2024-11-23 04:23:31.515698: Current learning rate: 0.00061 +2024-11-23 04:23:49.977979: train_loss -0.8398 +2024-11-23 04:23:49.978209: val_loss -0.7461 +2024-11-23 04:23:49.978286: Pseudo dice [0.8412] +2024-11-23 04:23:49.978373: Epoch time: 18.46 s +2024-11-23 04:23:51.076922: +2024-11-23 04:23:51.077149: Epoch 7641 +2024-11-23 04:23:51.077285: Current learning rate: 0.00061 +2024-11-23 04:24:09.518522: train_loss -0.8335 +2024-11-23 04:24:09.518745: val_loss -0.7831 +2024-11-23 04:24:09.518822: Pseudo dice [0.8529] +2024-11-23 04:24:09.518899: Epoch time: 18.44 s +2024-11-23 04:24:10.445642: +2024-11-23 04:24:10.445854: Epoch 7642 +2024-11-23 04:24:10.445971: Current learning rate: 0.00061 +2024-11-23 04:24:27.907667: train_loss -0.8391 +2024-11-23 04:24:27.907903: val_loss -0.7675 +2024-11-23 04:24:27.907997: Pseudo dice [0.8438] +2024-11-23 04:24:27.908090: Epoch time: 17.46 s +2024-11-23 04:24:29.013511: +2024-11-23 04:24:29.013711: Epoch 7643 +2024-11-23 04:24:29.013827: Current learning rate: 0.00061 +2024-11-23 04:24:47.797177: train_loss -0.8267 +2024-11-23 04:24:47.797423: val_loss -0.741 +2024-11-23 04:24:47.797498: Pseudo dice [0.8415] +2024-11-23 04:24:47.797585: Epoch time: 18.78 s +2024-11-23 04:24:48.727724: +2024-11-23 04:24:48.728148: Epoch 7644 +2024-11-23 04:24:48.728283: Current learning rate: 0.00061 +2024-11-23 04:25:06.645741: train_loss -0.8344 +2024-11-23 04:25:06.645959: val_loss -0.7615 +2024-11-23 04:25:06.646043: Pseudo dice [0.8314] +2024-11-23 04:25:06.646125: Epoch time: 17.92 s +2024-11-23 04:25:07.589275: +2024-11-23 04:25:07.589491: Epoch 7645 +2024-11-23 04:25:07.589599: Current learning rate: 0.00061 +2024-11-23 04:25:26.232248: train_loss -0.8321 +2024-11-23 04:25:26.232469: val_loss -0.7552 +2024-11-23 04:25:26.232542: Pseudo dice [0.8282] +2024-11-23 04:25:26.232617: Epoch time: 18.64 s +2024-11-23 04:25:27.157126: +2024-11-23 04:25:27.157318: Epoch 7646 +2024-11-23 04:25:27.157434: Current learning rate: 0.0006 +2024-11-23 04:25:45.668528: train_loss -0.8425 +2024-11-23 04:25:45.668761: val_loss -0.7595 +2024-11-23 04:25:45.668836: Pseudo dice [0.8501] +2024-11-23 04:25:45.668955: Epoch time: 18.51 s +2024-11-23 04:25:46.596251: +2024-11-23 04:25:46.596538: Epoch 7647 +2024-11-23 04:25:46.596654: Current learning rate: 0.0006 +2024-11-23 04:26:06.359625: train_loss -0.8352 +2024-11-23 04:26:06.359867: val_loss -0.7654 +2024-11-23 04:26:06.359944: Pseudo dice [0.8366] +2024-11-23 04:26:06.360031: Epoch time: 19.76 s +2024-11-23 04:26:07.298193: +2024-11-23 04:26:07.298392: Epoch 7648 +2024-11-23 04:26:07.298503: Current learning rate: 0.0006 +2024-11-23 04:26:25.714783: train_loss -0.8321 +2024-11-23 04:26:25.715012: val_loss -0.7709 +2024-11-23 04:26:25.715091: Pseudo dice [0.852] +2024-11-23 04:26:25.715173: Epoch time: 18.42 s +2024-11-23 04:26:26.637633: +2024-11-23 04:26:26.637865: Epoch 7649 +2024-11-23 04:26:26.637981: Current learning rate: 0.0006 +2024-11-23 04:26:45.239930: train_loss -0.831 +2024-11-23 04:26:45.245330: val_loss -0.7746 +2024-11-23 04:26:45.245423: Pseudo dice [0.8449] +2024-11-23 04:26:45.245500: Epoch time: 18.6 s +2024-11-23 04:26:46.680817: +2024-11-23 04:26:46.681050: Epoch 7650 +2024-11-23 04:26:46.681174: Current learning rate: 0.0006 +2024-11-23 04:27:04.801430: train_loss -0.8342 +2024-11-23 04:27:04.801760: val_loss -0.7427 +2024-11-23 04:27:04.801840: Pseudo dice [0.8446] +2024-11-23 04:27:04.801929: Epoch time: 18.12 s +2024-11-23 04:27:05.731334: +2024-11-23 04:27:05.731583: Epoch 7651 +2024-11-23 04:27:05.731719: Current learning rate: 0.0006 +2024-11-23 04:27:25.066426: train_loss -0.8365 +2024-11-23 04:27:25.066639: val_loss -0.7863 +2024-11-23 04:27:25.066716: Pseudo dice [0.8504] +2024-11-23 04:27:25.066792: Epoch time: 19.34 s +2024-11-23 04:27:26.003718: +2024-11-23 04:27:26.003967: Epoch 7652 +2024-11-23 04:27:26.004084: Current learning rate: 0.0006 +2024-11-23 04:27:43.465839: train_loss -0.8365 +2024-11-23 04:27:43.466075: val_loss -0.7434 +2024-11-23 04:27:43.466156: Pseudo dice [0.8362] +2024-11-23 04:27:43.471478: Epoch time: 17.46 s +2024-11-23 04:27:44.428902: +2024-11-23 04:27:44.429119: Epoch 7653 +2024-11-23 04:27:44.429231: Current learning rate: 0.00059 +2024-11-23 04:28:02.864813: train_loss -0.8359 +2024-11-23 04:28:02.865066: val_loss -0.7731 +2024-11-23 04:28:02.865146: Pseudo dice [0.8444] +2024-11-23 04:28:02.865234: Epoch time: 18.44 s +2024-11-23 04:28:03.908978: +2024-11-23 04:28:03.909207: Epoch 7654 +2024-11-23 04:28:03.909319: Current learning rate: 0.00059 +2024-11-23 04:28:22.340677: train_loss -0.8428 +2024-11-23 04:28:22.340918: val_loss -0.7751 +2024-11-23 04:28:22.340999: Pseudo dice [0.8398] +2024-11-23 04:28:22.341083: Epoch time: 18.43 s +2024-11-23 04:28:23.368723: +2024-11-23 04:28:23.368937: Epoch 7655 +2024-11-23 04:28:23.369053: Current learning rate: 0.00059 +2024-11-23 04:28:41.610989: train_loss -0.837 +2024-11-23 04:28:41.611231: val_loss -0.7728 +2024-11-23 04:28:41.611315: Pseudo dice [0.8504] +2024-11-23 04:28:41.611394: Epoch time: 18.24 s +2024-11-23 04:28:42.547533: +2024-11-23 04:28:42.547763: Epoch 7656 +2024-11-23 04:28:42.547877: Current learning rate: 0.00059 +2024-11-23 04:29:01.570394: train_loss -0.8348 +2024-11-23 04:29:01.570623: val_loss -0.768 +2024-11-23 04:29:01.570738: Pseudo dice [0.8428] +2024-11-23 04:29:01.570817: Epoch time: 19.02 s +2024-11-23 04:29:02.859082: +2024-11-23 04:29:02.859305: Epoch 7657 +2024-11-23 04:29:02.859422: Current learning rate: 0.00059 +2024-11-23 04:29:21.183542: train_loss -0.8339 +2024-11-23 04:29:21.183805: val_loss -0.763 +2024-11-23 04:29:21.183933: Pseudo dice [0.8238] +2024-11-23 04:29:21.184066: Epoch time: 18.33 s +2024-11-23 04:29:22.139789: +2024-11-23 04:29:22.140056: Epoch 7658 +2024-11-23 04:29:22.140182: Current learning rate: 0.00059 +2024-11-23 04:29:39.647812: train_loss -0.8373 +2024-11-23 04:29:39.648048: val_loss -0.7548 +2024-11-23 04:29:39.648127: Pseudo dice [0.8396] +2024-11-23 04:29:39.648201: Epoch time: 17.51 s +2024-11-23 04:29:40.579035: +2024-11-23 04:29:40.579269: Epoch 7659 +2024-11-23 04:29:40.579391: Current learning rate: 0.00058 +2024-11-23 04:29:59.872900: train_loss -0.8372 +2024-11-23 04:29:59.873130: val_loss -0.7858 +2024-11-23 04:29:59.873207: Pseudo dice [0.8493] +2024-11-23 04:29:59.873284: Epoch time: 19.29 s +2024-11-23 04:30:00.803115: +2024-11-23 04:30:00.803350: Epoch 7660 +2024-11-23 04:30:00.803471: Current learning rate: 0.00058 +2024-11-23 04:30:19.119267: train_loss -0.8342 +2024-11-23 04:30:19.119509: val_loss -0.7586 +2024-11-23 04:30:19.119588: Pseudo dice [0.8448] +2024-11-23 04:30:19.119675: Epoch time: 18.32 s +2024-11-23 04:30:20.150689: +2024-11-23 04:30:20.150889: Epoch 7661 +2024-11-23 04:30:20.151011: Current learning rate: 0.00058 +2024-11-23 04:30:39.834596: train_loss -0.8373 +2024-11-23 04:30:39.834810: val_loss -0.761 +2024-11-23 04:30:39.834883: Pseudo dice [0.8375] +2024-11-23 04:30:39.834959: Epoch time: 19.68 s +2024-11-23 04:30:40.919434: +2024-11-23 04:30:40.919715: Epoch 7662 +2024-11-23 04:30:40.919828: Current learning rate: 0.00058 +2024-11-23 04:30:59.043737: train_loss -0.8317 +2024-11-23 04:30:59.043961: val_loss -0.7636 +2024-11-23 04:30:59.044044: Pseudo dice [0.8067] +2024-11-23 04:30:59.044123: Epoch time: 18.13 s +2024-11-23 04:31:00.128855: +2024-11-23 04:31:00.129083: Epoch 7663 +2024-11-23 04:31:00.129198: Current learning rate: 0.00058 +2024-11-23 04:31:19.395907: train_loss -0.8394 +2024-11-23 04:31:19.396163: val_loss -0.7695 +2024-11-23 04:31:19.396240: Pseudo dice [0.8615] +2024-11-23 04:31:19.396315: Epoch time: 19.27 s +2024-11-23 04:31:20.331228: +2024-11-23 04:31:20.331438: Epoch 7664 +2024-11-23 04:31:20.331552: Current learning rate: 0.00058 +2024-11-23 04:31:39.128366: train_loss -0.8359 +2024-11-23 04:31:39.128605: val_loss -0.7785 +2024-11-23 04:31:39.128678: Pseudo dice [0.8594] +2024-11-23 04:31:39.128764: Epoch time: 18.8 s +2024-11-23 04:31:40.135218: +2024-11-23 04:31:40.135419: Epoch 7665 +2024-11-23 04:31:40.135537: Current learning rate: 0.00058 +2024-11-23 04:31:58.162333: train_loss -0.8377 +2024-11-23 04:31:58.162602: val_loss -0.7844 +2024-11-23 04:31:58.162678: Pseudo dice [0.8526] +2024-11-23 04:31:58.162752: Epoch time: 18.03 s +2024-11-23 04:31:59.201366: +2024-11-23 04:31:59.201585: Epoch 7666 +2024-11-23 04:31:59.201695: Current learning rate: 0.00057 +2024-11-23 04:32:18.326862: train_loss -0.8328 +2024-11-23 04:32:18.327085: val_loss -0.7495 +2024-11-23 04:32:18.327164: Pseudo dice [0.8233] +2024-11-23 04:32:18.327244: Epoch time: 19.13 s +2024-11-23 04:32:19.253049: +2024-11-23 04:32:19.253265: Epoch 7667 +2024-11-23 04:32:19.253379: Current learning rate: 0.00057 +2024-11-23 04:32:37.724485: train_loss -0.84 +2024-11-23 04:32:37.724705: val_loss -0.7634 +2024-11-23 04:32:37.724781: Pseudo dice [0.8322] +2024-11-23 04:32:37.724859: Epoch time: 18.47 s +2024-11-23 04:32:38.732838: +2024-11-23 04:32:38.733061: Epoch 7668 +2024-11-23 04:32:38.733190: Current learning rate: 0.00057 +2024-11-23 04:32:57.122290: train_loss -0.8389 +2024-11-23 04:32:57.122533: val_loss -0.7582 +2024-11-23 04:32:57.122610: Pseudo dice [0.8446] +2024-11-23 04:32:57.122707: Epoch time: 18.39 s +2024-11-23 04:32:58.411443: +2024-11-23 04:32:58.411650: Epoch 7669 +2024-11-23 04:32:58.411763: Current learning rate: 0.00057 +2024-11-23 04:33:18.643117: train_loss -0.8361 +2024-11-23 04:33:18.645611: val_loss -0.7653 +2024-11-23 04:33:18.645732: Pseudo dice [0.8253] +2024-11-23 04:33:18.645811: Epoch time: 20.23 s +2024-11-23 04:33:19.820248: +2024-11-23 04:33:19.820464: Epoch 7670 +2024-11-23 04:33:19.820576: Current learning rate: 0.00057 +2024-11-23 04:33:38.872041: train_loss -0.8341 +2024-11-23 04:33:38.872264: val_loss -0.7893 +2024-11-23 04:33:38.872337: Pseudo dice [0.8493] +2024-11-23 04:33:38.872413: Epoch time: 19.05 s +2024-11-23 04:33:39.996276: +2024-11-23 04:33:39.996474: Epoch 7671 +2024-11-23 04:33:39.996586: Current learning rate: 0.00057 +2024-11-23 04:34:00.455755: train_loss -0.8403 +2024-11-23 04:34:00.455984: val_loss -0.7704 +2024-11-23 04:34:00.456109: Pseudo dice [0.8507] +2024-11-23 04:34:00.456198: Epoch time: 20.46 s +2024-11-23 04:34:01.387511: +2024-11-23 04:34:01.387733: Epoch 7672 +2024-11-23 04:34:01.387848: Current learning rate: 0.00056 +2024-11-23 04:34:19.164292: train_loss -0.8381 +2024-11-23 04:34:19.164573: val_loss -0.7623 +2024-11-23 04:34:19.164650: Pseudo dice [0.841] +2024-11-23 04:34:19.164727: Epoch time: 17.78 s +2024-11-23 04:34:20.105061: +2024-11-23 04:34:20.105286: Epoch 7673 +2024-11-23 04:34:20.105407: Current learning rate: 0.00056 +2024-11-23 04:34:38.454572: train_loss -0.8307 +2024-11-23 04:34:38.454795: val_loss -0.743 +2024-11-23 04:34:38.454873: Pseudo dice [0.8399] +2024-11-23 04:34:38.454951: Epoch time: 18.35 s +2024-11-23 04:34:39.534388: +2024-11-23 04:34:39.534606: Epoch 7674 +2024-11-23 04:34:39.534719: Current learning rate: 0.00056 +2024-11-23 04:34:58.164799: train_loss -0.8393 +2024-11-23 04:34:58.165032: val_loss -0.763 +2024-11-23 04:34:58.165110: Pseudo dice [0.8422] +2024-11-23 04:34:58.165190: Epoch time: 18.63 s +2024-11-23 04:34:59.104962: +2024-11-23 04:34:59.105190: Epoch 7675 +2024-11-23 04:34:59.105305: Current learning rate: 0.00056 +2024-11-23 04:35:17.898547: train_loss -0.8377 +2024-11-23 04:35:17.898777: val_loss -0.7593 +2024-11-23 04:35:17.898853: Pseudo dice [0.8452] +2024-11-23 04:35:17.898934: Epoch time: 18.79 s +2024-11-23 04:35:18.824585: +2024-11-23 04:35:18.824785: Epoch 7676 +2024-11-23 04:35:18.824901: Current learning rate: 0.00056 +2024-11-23 04:35:37.360971: train_loss -0.8367 +2024-11-23 04:35:37.361192: val_loss -0.7747 +2024-11-23 04:35:37.361264: Pseudo dice [0.8427] +2024-11-23 04:35:37.361340: Epoch time: 18.54 s +2024-11-23 04:35:38.429958: +2024-11-23 04:35:38.430170: Epoch 7677 +2024-11-23 04:35:38.430286: Current learning rate: 0.00056 +2024-11-23 04:35:56.305530: train_loss -0.8392 +2024-11-23 04:35:56.305755: val_loss -0.7598 +2024-11-23 04:35:56.305830: Pseudo dice [0.8352] +2024-11-23 04:35:56.305908: Epoch time: 17.88 s +2024-11-23 04:35:57.239515: +2024-11-23 04:35:57.257294: Epoch 7678 +2024-11-23 04:35:57.257430: Current learning rate: 0.00055 +2024-11-23 04:36:15.277368: train_loss -0.8416 +2024-11-23 04:36:15.277601: val_loss -0.76 +2024-11-23 04:36:15.277681: Pseudo dice [0.8259] +2024-11-23 04:36:15.277764: Epoch time: 18.04 s +2024-11-23 04:36:16.409204: +2024-11-23 04:36:16.409403: Epoch 7679 +2024-11-23 04:36:16.409655: Current learning rate: 0.00055 +2024-11-23 04:36:34.866296: train_loss -0.8399 +2024-11-23 04:36:34.868718: val_loss -0.7631 +2024-11-23 04:36:34.868836: Pseudo dice [0.8254] +2024-11-23 04:36:34.868923: Epoch time: 18.46 s +2024-11-23 04:36:36.248540: +2024-11-23 04:36:36.248737: Epoch 7680 +2024-11-23 04:36:36.248847: Current learning rate: 0.00055 +2024-11-23 04:36:54.923018: train_loss -0.838 +2024-11-23 04:36:54.923248: val_loss -0.7534 +2024-11-23 04:36:54.923327: Pseudo dice [0.8117] +2024-11-23 04:36:54.923404: Epoch time: 18.68 s +2024-11-23 04:36:55.859938: +2024-11-23 04:36:55.860202: Epoch 7681 +2024-11-23 04:36:55.860323: Current learning rate: 0.00055 +2024-11-23 04:37:14.433089: train_loss -0.8294 +2024-11-23 04:37:14.433311: val_loss -0.7534 +2024-11-23 04:37:14.433385: Pseudo dice [0.8188] +2024-11-23 04:37:14.433464: Epoch time: 18.57 s +2024-11-23 04:37:15.398391: +2024-11-23 04:37:15.398605: Epoch 7682 +2024-11-23 04:37:15.398718: Current learning rate: 0.00055 +2024-11-23 04:37:33.521171: train_loss -0.8354 +2024-11-23 04:37:33.521416: val_loss -0.7784 +2024-11-23 04:37:33.521493: Pseudo dice [0.8436] +2024-11-23 04:37:33.521972: Epoch time: 18.12 s +2024-11-23 04:37:34.464978: +2024-11-23 04:37:34.465211: Epoch 7683 +2024-11-23 04:37:34.465329: Current learning rate: 0.00055 +2024-11-23 04:37:54.176956: train_loss -0.8393 +2024-11-23 04:37:54.177187: val_loss -0.7454 +2024-11-23 04:37:54.177262: Pseudo dice [0.8481] +2024-11-23 04:37:54.177339: Epoch time: 19.71 s +2024-11-23 04:37:55.111356: +2024-11-23 04:37:55.111633: Epoch 7684 +2024-11-23 04:37:55.111751: Current learning rate: 0.00055 +2024-11-23 04:38:14.312510: train_loss -0.838 +2024-11-23 04:38:14.312726: val_loss -0.7562 +2024-11-23 04:38:14.312802: Pseudo dice [0.8543] +2024-11-23 04:38:14.312882: Epoch time: 19.2 s +2024-11-23 04:38:15.247373: +2024-11-23 04:38:15.247601: Epoch 7685 +2024-11-23 04:38:15.247716: Current learning rate: 0.00054 +2024-11-23 04:38:34.843432: train_loss -0.8381 +2024-11-23 04:38:34.843729: val_loss -0.7625 +2024-11-23 04:38:34.843818: Pseudo dice [0.8334] +2024-11-23 04:38:34.843912: Epoch time: 19.6 s +2024-11-23 04:38:35.774843: +2024-11-23 04:38:35.775055: Epoch 7686 +2024-11-23 04:38:35.775172: Current learning rate: 0.00054 +2024-11-23 04:38:53.682670: train_loss -0.8421 +2024-11-23 04:38:53.682896: val_loss -0.7566 +2024-11-23 04:38:53.682971: Pseudo dice [0.835] +2024-11-23 04:38:53.683059: Epoch time: 17.91 s +2024-11-23 04:38:54.607539: +2024-11-23 04:38:54.607750: Epoch 7687 +2024-11-23 04:38:54.607862: Current learning rate: 0.00054 +2024-11-23 04:39:12.760398: train_loss -0.8438 +2024-11-23 04:39:12.760623: val_loss -0.7716 +2024-11-23 04:39:12.765927: Pseudo dice [0.8602] +2024-11-23 04:39:12.766055: Epoch time: 18.15 s +2024-11-23 04:39:13.754649: +2024-11-23 04:39:13.754918: Epoch 7688 +2024-11-23 04:39:13.755039: Current learning rate: 0.00054 +2024-11-23 04:39:33.364558: train_loss -0.836 +2024-11-23 04:39:33.364796: val_loss -0.7603 +2024-11-23 04:39:33.367057: Pseudo dice [0.8316] +2024-11-23 04:39:33.367153: Epoch time: 19.61 s +2024-11-23 04:39:34.393642: +2024-11-23 04:39:34.393857: Epoch 7689 +2024-11-23 04:39:34.393968: Current learning rate: 0.00054 +2024-11-23 04:39:54.247155: train_loss -0.8413 +2024-11-23 04:39:54.252578: val_loss -0.7851 +2024-11-23 04:39:54.252733: Pseudo dice [0.8529] +2024-11-23 04:39:54.252822: Epoch time: 19.85 s +2024-11-23 04:39:55.188700: +2024-11-23 04:39:55.188915: Epoch 7690 +2024-11-23 04:39:55.189035: Current learning rate: 0.00054 +2024-11-23 04:40:14.426151: train_loss -0.8354 +2024-11-23 04:40:14.426374: val_loss -0.7661 +2024-11-23 04:40:14.426445: Pseudo dice [0.8398] +2024-11-23 04:40:14.466043: Epoch time: 19.24 s +2024-11-23 04:40:15.422861: +2024-11-23 04:40:15.423101: Epoch 7691 +2024-11-23 04:40:15.423220: Current learning rate: 0.00053 +2024-11-23 04:40:34.640133: train_loss -0.8337 +2024-11-23 04:40:34.640418: val_loss -0.7682 +2024-11-23 04:40:34.640493: Pseudo dice [0.8465] +2024-11-23 04:40:34.640568: Epoch time: 19.22 s +2024-11-23 04:40:35.984584: +2024-11-23 04:40:35.984830: Epoch 7692 +2024-11-23 04:40:35.984944: Current learning rate: 0.00053 +2024-11-23 04:40:54.173653: train_loss -0.8323 +2024-11-23 04:40:54.175285: val_loss -0.7425 +2024-11-23 04:40:54.175377: Pseudo dice [0.8268] +2024-11-23 04:40:54.175466: Epoch time: 18.19 s +2024-11-23 04:40:55.252383: +2024-11-23 04:40:55.252617: Epoch 7693 +2024-11-23 04:40:55.252743: Current learning rate: 0.00053 +2024-11-23 04:41:13.929758: train_loss -0.8343 +2024-11-23 04:41:13.929975: val_loss -0.7383 +2024-11-23 04:41:13.930057: Pseudo dice [0.8564] +2024-11-23 04:41:13.930131: Epoch time: 18.68 s +2024-11-23 04:41:14.858806: +2024-11-23 04:41:14.859038: Epoch 7694 +2024-11-23 04:41:14.859151: Current learning rate: 0.00053 +2024-11-23 04:41:32.372373: train_loss -0.8411 +2024-11-23 04:41:32.372622: val_loss -0.7799 +2024-11-23 04:41:32.372704: Pseudo dice [0.8509] +2024-11-23 04:41:32.372781: Epoch time: 17.51 s +2024-11-23 04:41:33.299505: +2024-11-23 04:41:33.299730: Epoch 7695 +2024-11-23 04:41:33.299846: Current learning rate: 0.00053 +2024-11-23 04:41:51.912163: train_loss -0.8405 +2024-11-23 04:41:51.912406: val_loss -0.7619 +2024-11-23 04:41:51.912484: Pseudo dice [0.8342] +2024-11-23 04:41:51.912569: Epoch time: 18.61 s +2024-11-23 04:41:52.846239: +2024-11-23 04:41:52.846453: Epoch 7696 +2024-11-23 04:41:52.846564: Current learning rate: 0.00053 +2024-11-23 04:42:11.834063: train_loss -0.8385 +2024-11-23 04:42:11.834282: val_loss -0.7825 +2024-11-23 04:42:11.834358: Pseudo dice [0.855] +2024-11-23 04:42:11.834434: Epoch time: 18.99 s +2024-11-23 04:42:12.792375: +2024-11-23 04:42:12.792604: Epoch 7697 +2024-11-23 04:42:12.792714: Current learning rate: 0.00053 +2024-11-23 04:42:31.005322: train_loss -0.8373 +2024-11-23 04:42:31.005546: val_loss -0.7587 +2024-11-23 04:42:31.005632: Pseudo dice [0.8287] +2024-11-23 04:42:31.005739: Epoch time: 18.21 s +2024-11-23 04:42:31.935421: +2024-11-23 04:42:31.935695: Epoch 7698 +2024-11-23 04:42:31.935814: Current learning rate: 0.00052 +2024-11-23 04:42:50.233404: train_loss -0.8459 +2024-11-23 04:42:50.233631: val_loss -0.7565 +2024-11-23 04:42:50.233709: Pseudo dice [0.8207] +2024-11-23 04:42:50.233841: Epoch time: 18.3 s +2024-11-23 04:42:51.163203: +2024-11-23 04:42:51.163455: Epoch 7699 +2024-11-23 04:42:51.163568: Current learning rate: 0.00052 +2024-11-23 04:43:10.698685: train_loss -0.8368 +2024-11-23 04:43:10.698918: val_loss -0.7859 +2024-11-23 04:43:10.698999: Pseudo dice [0.8387] +2024-11-23 04:43:10.699083: Epoch time: 19.54 s +2024-11-23 04:43:12.022559: +2024-11-23 04:43:12.022774: Epoch 7700 +2024-11-23 04:43:12.022886: Current learning rate: 0.00052 +2024-11-23 04:43:30.489737: train_loss -0.8351 +2024-11-23 04:43:30.495148: val_loss -0.7553 +2024-11-23 04:43:30.495276: Pseudo dice [0.8266] +2024-11-23 04:43:30.495357: Epoch time: 18.47 s +2024-11-23 04:43:31.549642: +2024-11-23 04:43:31.549876: Epoch 7701 +2024-11-23 04:43:31.550004: Current learning rate: 0.00052 +2024-11-23 04:43:50.558929: train_loss -0.839 +2024-11-23 04:43:50.559168: val_loss -0.7805 +2024-11-23 04:43:50.559243: Pseudo dice [0.8485] +2024-11-23 04:43:50.559317: Epoch time: 19.01 s +2024-11-23 04:43:51.489734: +2024-11-23 04:43:51.490168: Epoch 7702 +2024-11-23 04:43:51.490304: Current learning rate: 0.00052 +2024-11-23 04:44:09.965320: train_loss -0.8366 +2024-11-23 04:44:09.965554: val_loss -0.7676 +2024-11-23 04:44:09.965631: Pseudo dice [0.8281] +2024-11-23 04:44:09.965714: Epoch time: 18.48 s +2024-11-23 04:44:11.287396: +2024-11-23 04:44:11.287611: Epoch 7703 +2024-11-23 04:44:11.287724: Current learning rate: 0.00052 +2024-11-23 04:44:29.628764: train_loss -0.8397 +2024-11-23 04:44:29.628987: val_loss -0.7668 +2024-11-23 04:44:29.629068: Pseudo dice [0.8245] +2024-11-23 04:44:29.629146: Epoch time: 18.34 s +2024-11-23 04:44:30.587702: +2024-11-23 04:44:30.587943: Epoch 7704 +2024-11-23 04:44:30.588069: Current learning rate: 0.00051 +2024-11-23 04:44:48.878922: train_loss -0.8383 +2024-11-23 04:44:48.881271: val_loss -0.7478 +2024-11-23 04:44:48.881388: Pseudo dice [0.8375] +2024-11-23 04:44:48.881469: Epoch time: 18.29 s +2024-11-23 04:44:49.916672: +2024-11-23 04:44:49.916917: Epoch 7705 +2024-11-23 04:44:49.917109: Current learning rate: 0.00051 +2024-11-23 04:45:08.408334: train_loss -0.8396 +2024-11-23 04:45:08.408548: val_loss -0.7781 +2024-11-23 04:45:08.408620: Pseudo dice [0.8469] +2024-11-23 04:45:08.408696: Epoch time: 18.49 s +2024-11-23 04:45:09.336476: +2024-11-23 04:45:09.336702: Epoch 7706 +2024-11-23 04:45:09.336818: Current learning rate: 0.00051 +2024-11-23 04:45:26.905932: train_loss -0.8368 +2024-11-23 04:45:26.906203: val_loss -0.778 +2024-11-23 04:45:26.906277: Pseudo dice [0.8527] +2024-11-23 04:45:26.906367: Epoch time: 17.57 s +2024-11-23 04:45:27.941567: +2024-11-23 04:45:27.941767: Epoch 7707 +2024-11-23 04:45:27.941883: Current learning rate: 0.00051 +2024-11-23 04:45:47.581013: train_loss -0.8377 +2024-11-23 04:45:47.581240: val_loss -0.7847 +2024-11-23 04:45:47.581311: Pseudo dice [0.8495] +2024-11-23 04:45:47.581392: Epoch time: 19.64 s +2024-11-23 04:45:48.566143: +2024-11-23 04:45:48.566446: Epoch 7708 +2024-11-23 04:45:48.566564: Current learning rate: 0.00051 +2024-11-23 04:46:06.980911: train_loss -0.8351 +2024-11-23 04:46:06.981144: val_loss -0.7704 +2024-11-23 04:46:06.981220: Pseudo dice [0.8548] +2024-11-23 04:46:06.981299: Epoch time: 18.42 s +2024-11-23 04:46:07.914819: +2024-11-23 04:46:07.915082: Epoch 7709 +2024-11-23 04:46:07.915199: Current learning rate: 0.00051 +2024-11-23 04:46:27.178091: train_loss -0.8363 +2024-11-23 04:46:27.178315: val_loss -0.7567 +2024-11-23 04:46:27.178392: Pseudo dice [0.8302] +2024-11-23 04:46:27.178475: Epoch time: 19.26 s +2024-11-23 04:46:28.224838: +2024-11-23 04:46:28.225080: Epoch 7710 +2024-11-23 04:46:28.225202: Current learning rate: 0.00051 +2024-11-23 04:46:47.196064: train_loss -0.8412 +2024-11-23 04:46:47.196290: val_loss -0.7481 +2024-11-23 04:46:47.196366: Pseudo dice [0.8002] +2024-11-23 04:46:47.196445: Epoch time: 18.97 s +2024-11-23 04:46:48.128516: +2024-11-23 04:46:48.128729: Epoch 7711 +2024-11-23 04:46:48.128844: Current learning rate: 0.0005 +2024-11-23 04:47:06.886523: train_loss -0.8431 +2024-11-23 04:47:06.886775: val_loss -0.7665 +2024-11-23 04:47:06.886858: Pseudo dice [0.8406] +2024-11-23 04:47:06.886965: Epoch time: 18.76 s +2024-11-23 04:47:07.831164: +2024-11-23 04:47:07.831367: Epoch 7712 +2024-11-23 04:47:07.831480: Current learning rate: 0.0005 +2024-11-23 04:47:26.324519: train_loss -0.8289 +2024-11-23 04:47:26.324742: val_loss -0.7464 +2024-11-23 04:47:26.324818: Pseudo dice [0.8339] +2024-11-23 04:47:26.325687: Epoch time: 18.49 s +2024-11-23 04:47:27.299130: +2024-11-23 04:47:27.299320: Epoch 7713 +2024-11-23 04:47:27.299432: Current learning rate: 0.0005 +2024-11-23 04:47:45.318980: train_loss -0.8425 +2024-11-23 04:47:45.319241: val_loss -0.7756 +2024-11-23 04:47:45.319316: Pseudo dice [0.8516] +2024-11-23 04:47:45.319398: Epoch time: 18.02 s +2024-11-23 04:47:46.708185: +2024-11-23 04:47:46.708397: Epoch 7714 +2024-11-23 04:47:46.708517: Current learning rate: 0.0005 +2024-11-23 04:48:04.975270: train_loss -0.8389 +2024-11-23 04:48:04.975504: val_loss -0.7509 +2024-11-23 04:48:04.975589: Pseudo dice [0.8345] +2024-11-23 04:48:04.975676: Epoch time: 18.27 s +2024-11-23 04:48:05.909426: +2024-11-23 04:48:05.909639: Epoch 7715 +2024-11-23 04:48:05.909748: Current learning rate: 0.0005 +2024-11-23 04:48:25.294219: train_loss -0.8389 +2024-11-23 04:48:25.294442: val_loss -0.7348 +2024-11-23 04:48:25.294518: Pseudo dice [0.8208] +2024-11-23 04:48:25.294596: Epoch time: 19.39 s +2024-11-23 04:48:26.222054: +2024-11-23 04:48:26.222348: Epoch 7716 +2024-11-23 04:48:26.222462: Current learning rate: 0.0005 +2024-11-23 04:48:45.800555: train_loss -0.8388 +2024-11-23 04:48:45.800791: val_loss -0.7487 +2024-11-23 04:48:45.800864: Pseudo dice [0.8306] +2024-11-23 04:48:45.800946: Epoch time: 19.58 s +2024-11-23 04:48:46.787703: +2024-11-23 04:48:46.787903: Epoch 7717 +2024-11-23 04:48:46.788017: Current learning rate: 0.00049 +2024-11-23 04:49:06.567838: train_loss -0.8406 +2024-11-23 04:49:06.568075: val_loss -0.78 +2024-11-23 04:49:06.568150: Pseudo dice [0.8425] +2024-11-23 04:49:06.568231: Epoch time: 19.78 s +2024-11-23 04:49:07.496952: +2024-11-23 04:49:07.497200: Epoch 7718 +2024-11-23 04:49:07.497317: Current learning rate: 0.00049 +2024-11-23 04:49:26.356417: train_loss -0.8383 +2024-11-23 04:49:26.356634: val_loss -0.7412 +2024-11-23 04:49:26.356712: Pseudo dice [0.8516] +2024-11-23 04:49:26.356791: Epoch time: 18.86 s +2024-11-23 04:49:27.289838: +2024-11-23 04:49:27.290136: Epoch 7719 +2024-11-23 04:49:27.290272: Current learning rate: 0.00049 +2024-11-23 04:49:45.871805: train_loss -0.8399 +2024-11-23 04:49:45.872030: val_loss -0.7603 +2024-11-23 04:49:45.872141: Pseudo dice [0.8505] +2024-11-23 04:49:45.872223: Epoch time: 18.58 s +2024-11-23 04:49:46.802324: +2024-11-23 04:49:46.802540: Epoch 7720 +2024-11-23 04:49:46.802654: Current learning rate: 0.00049 +2024-11-23 04:50:04.444371: train_loss -0.8367 +2024-11-23 04:50:04.445035: val_loss -0.7742 +2024-11-23 04:50:04.445115: Pseudo dice [0.8536] +2024-11-23 04:50:04.445202: Epoch time: 17.64 s +2024-11-23 04:50:05.488762: +2024-11-23 04:50:05.488956: Epoch 7721 +2024-11-23 04:50:05.489074: Current learning rate: 0.00049 +2024-11-23 04:50:23.835907: train_loss -0.8359 +2024-11-23 04:50:23.836128: val_loss -0.7503 +2024-11-23 04:50:23.836205: Pseudo dice [0.8399] +2024-11-23 04:50:23.836280: Epoch time: 18.35 s +2024-11-23 04:50:24.770973: +2024-11-23 04:50:24.771211: Epoch 7722 +2024-11-23 04:50:24.771323: Current learning rate: 0.00049 +2024-11-23 04:50:43.021418: train_loss -0.8419 +2024-11-23 04:50:43.021660: val_loss -0.7679 +2024-11-23 04:50:43.021737: Pseudo dice [0.8398] +2024-11-23 04:50:43.021816: Epoch time: 18.25 s +2024-11-23 04:50:44.121727: +2024-11-23 04:50:44.121922: Epoch 7723 +2024-11-23 04:50:44.122047: Current learning rate: 0.00048 +2024-11-23 04:51:02.507346: train_loss -0.8383 +2024-11-23 04:51:02.507633: val_loss -0.769 +2024-11-23 04:51:02.507713: Pseudo dice [0.8275] +2024-11-23 04:51:02.507796: Epoch time: 18.39 s +2024-11-23 04:51:03.444715: +2024-11-23 04:51:03.444934: Epoch 7724 +2024-11-23 04:51:03.445050: Current learning rate: 0.00048 +2024-11-23 04:51:22.016031: train_loss -0.8418 +2024-11-23 04:51:22.016263: val_loss -0.7583 +2024-11-23 04:51:22.016338: Pseudo dice [0.8183] +2024-11-23 04:51:22.016478: Epoch time: 18.57 s +2024-11-23 04:51:23.021435: +2024-11-23 04:51:23.021658: Epoch 7725 +2024-11-23 04:51:23.021770: Current learning rate: 0.00048 +2024-11-23 04:51:42.927552: train_loss -0.8317 +2024-11-23 04:51:42.927768: val_loss -0.7975 +2024-11-23 04:51:42.927841: Pseudo dice [0.8498] +2024-11-23 04:51:42.927917: Epoch time: 19.91 s +2024-11-23 04:51:44.254559: +2024-11-23 04:51:44.254772: Epoch 7726 +2024-11-23 04:51:44.254893: Current learning rate: 0.00048 +2024-11-23 04:52:03.920686: train_loss -0.8338 +2024-11-23 04:52:03.920961: val_loss -0.7725 +2024-11-23 04:52:03.921129: Pseudo dice [0.8391] +2024-11-23 04:52:03.921226: Epoch time: 19.67 s +2024-11-23 04:52:04.857499: +2024-11-23 04:52:04.857720: Epoch 7727 +2024-11-23 04:52:04.857833: Current learning rate: 0.00048 +2024-11-23 04:52:23.755697: train_loss -0.8379 +2024-11-23 04:52:23.756017: val_loss -0.7962 +2024-11-23 04:52:23.756098: Pseudo dice [0.8536] +2024-11-23 04:52:23.756181: Epoch time: 18.9 s +2024-11-23 04:52:24.695067: +2024-11-23 04:52:24.695282: Epoch 7728 +2024-11-23 04:52:24.695392: Current learning rate: 0.00048 +2024-11-23 04:52:43.467584: train_loss -0.8316 +2024-11-23 04:52:43.467787: val_loss -0.7415 +2024-11-23 04:52:43.467859: Pseudo dice [0.8418] +2024-11-23 04:52:43.467935: Epoch time: 18.77 s +2024-11-23 04:52:44.421721: +2024-11-23 04:52:44.421947: Epoch 7729 +2024-11-23 04:52:44.422073: Current learning rate: 0.00048 +2024-11-23 04:53:03.830464: train_loss -0.8378 +2024-11-23 04:53:03.830681: val_loss -0.7842 +2024-11-23 04:53:03.830753: Pseudo dice [0.8435] +2024-11-23 04:53:03.830825: Epoch time: 19.41 s +2024-11-23 04:53:04.770407: +2024-11-23 04:53:04.770628: Epoch 7730 +2024-11-23 04:53:04.770738: Current learning rate: 0.00047 +2024-11-23 04:53:23.326280: train_loss -0.8342 +2024-11-23 04:53:23.326522: val_loss -0.7671 +2024-11-23 04:53:23.326602: Pseudo dice [0.8316] +2024-11-23 04:53:23.326689: Epoch time: 18.56 s +2024-11-23 04:53:24.261714: +2024-11-23 04:53:24.262097: Epoch 7731 +2024-11-23 04:53:24.262218: Current learning rate: 0.00047 +2024-11-23 04:53:42.965135: train_loss -0.8376 +2024-11-23 04:53:42.965349: val_loss -0.7742 +2024-11-23 04:53:42.965425: Pseudo dice [0.8459] +2024-11-23 04:53:42.965500: Epoch time: 18.7 s +2024-11-23 04:53:43.899979: +2024-11-23 04:53:43.900234: Epoch 7732 +2024-11-23 04:53:43.900355: Current learning rate: 0.00047 +2024-11-23 04:54:02.671597: train_loss -0.8356 +2024-11-23 04:54:02.671840: val_loss -0.7748 +2024-11-23 04:54:02.671919: Pseudo dice [0.8389] +2024-11-23 04:54:02.672012: Epoch time: 18.77 s +2024-11-23 04:54:03.709777: +2024-11-23 04:54:03.709979: Epoch 7733 +2024-11-23 04:54:03.710097: Current learning rate: 0.00047 +2024-11-23 04:54:21.722372: train_loss -0.8401 +2024-11-23 04:54:21.722591: val_loss -0.7673 +2024-11-23 04:54:21.722666: Pseudo dice [0.8483] +2024-11-23 04:54:21.722742: Epoch time: 18.01 s +2024-11-23 04:54:22.687686: +2024-11-23 04:54:22.687892: Epoch 7734 +2024-11-23 04:54:22.688015: Current learning rate: 0.00047 +2024-11-23 04:54:40.724349: train_loss -0.8415 +2024-11-23 04:54:40.724613: val_loss -0.7194 +2024-11-23 04:54:40.724689: Pseudo dice [0.8271] +2024-11-23 04:54:40.724776: Epoch time: 18.04 s +2024-11-23 04:54:41.656858: +2024-11-23 04:54:41.657081: Epoch 7735 +2024-11-23 04:54:41.657194: Current learning rate: 0.00047 +2024-11-23 04:54:59.454652: train_loss -0.8476 +2024-11-23 04:54:59.454940: val_loss -0.7406 +2024-11-23 04:54:59.455030: Pseudo dice [0.8297] +2024-11-23 04:54:59.455112: Epoch time: 17.8 s +2024-11-23 04:55:00.381752: +2024-11-23 04:55:00.381959: Epoch 7736 +2024-11-23 04:55:00.382078: Current learning rate: 0.00046 +2024-11-23 04:55:19.147387: train_loss -0.8442 +2024-11-23 04:55:19.147631: val_loss -0.7649 +2024-11-23 04:55:19.147709: Pseudo dice [0.8338] +2024-11-23 04:55:19.147849: Epoch time: 18.77 s +2024-11-23 04:55:20.440405: +2024-11-23 04:55:20.440609: Epoch 7737 +2024-11-23 04:55:20.440782: Current learning rate: 0.00046 +2024-11-23 04:55:38.688937: train_loss -0.8372 +2024-11-23 04:55:38.691374: val_loss -0.7712 +2024-11-23 04:55:38.691467: Pseudo dice [0.8322] +2024-11-23 04:55:38.691558: Epoch time: 18.25 s +2024-11-23 04:55:39.819445: +2024-11-23 04:55:39.819688: Epoch 7738 +2024-11-23 04:55:39.819806: Current learning rate: 0.00046 +2024-11-23 04:55:57.199835: train_loss -0.8347 +2024-11-23 04:55:57.200070: val_loss -0.7589 +2024-11-23 04:55:57.200146: Pseudo dice [0.8323] +2024-11-23 04:55:57.200222: Epoch time: 17.38 s +2024-11-23 04:55:58.140974: +2024-11-23 04:55:58.141186: Epoch 7739 +2024-11-23 04:55:58.141295: Current learning rate: 0.00046 +2024-11-23 04:56:18.505435: train_loss -0.8426 +2024-11-23 04:56:18.505677: val_loss -0.7807 +2024-11-23 04:56:18.505750: Pseudo dice [0.8412] +2024-11-23 04:56:18.505825: Epoch time: 20.37 s +2024-11-23 04:56:19.436864: +2024-11-23 04:56:19.437157: Epoch 7740 +2024-11-23 04:56:19.437268: Current learning rate: 0.00046 +2024-11-23 04:56:39.084404: train_loss -0.8366 +2024-11-23 04:56:39.084631: val_loss -0.7703 +2024-11-23 04:56:39.084705: Pseudo dice [0.8458] +2024-11-23 04:56:39.084781: Epoch time: 19.65 s +2024-11-23 04:56:40.156440: +2024-11-23 04:56:40.156685: Epoch 7741 +2024-11-23 04:56:40.156801: Current learning rate: 0.00046 +2024-11-23 04:56:58.233685: train_loss -0.8384 +2024-11-23 04:56:58.233949: val_loss -0.7681 +2024-11-23 04:56:58.234561: Pseudo dice [0.8261] +2024-11-23 04:56:58.234657: Epoch time: 18.08 s +2024-11-23 04:56:59.170002: +2024-11-23 04:56:59.170213: Epoch 7742 +2024-11-23 04:56:59.170325: Current learning rate: 0.00045 +2024-11-23 04:57:17.639572: train_loss -0.8444 +2024-11-23 04:57:17.639787: val_loss -0.7784 +2024-11-23 04:57:17.639860: Pseudo dice [0.8327] +2024-11-23 04:57:17.640018: Epoch time: 18.47 s +2024-11-23 04:57:18.572443: +2024-11-23 04:57:18.572640: Epoch 7743 +2024-11-23 04:57:18.572751: Current learning rate: 0.00045 +2024-11-23 04:57:37.811023: train_loss -0.8439 +2024-11-23 04:57:37.811255: val_loss -0.7565 +2024-11-23 04:57:37.811392: Pseudo dice [0.8446] +2024-11-23 04:57:37.811472: Epoch time: 19.24 s +2024-11-23 04:57:38.814638: +2024-11-23 04:57:38.814840: Epoch 7744 +2024-11-23 04:57:38.814955: Current learning rate: 0.00045 +2024-11-23 04:57:57.242836: train_loss -0.8399 +2024-11-23 04:57:57.243076: val_loss -0.7634 +2024-11-23 04:57:57.243150: Pseudo dice [0.8471] +2024-11-23 04:57:57.243232: Epoch time: 18.43 s +2024-11-23 04:57:58.202640: +2024-11-23 04:57:58.202844: Epoch 7745 +2024-11-23 04:57:58.202961: Current learning rate: 0.00045 +2024-11-23 04:58:16.038959: train_loss -0.8385 +2024-11-23 04:58:16.039253: val_loss -0.7803 +2024-11-23 04:58:16.039329: Pseudo dice [0.8439] +2024-11-23 04:58:16.039403: Epoch time: 17.84 s +2024-11-23 04:58:16.976408: +2024-11-23 04:58:16.976637: Epoch 7746 +2024-11-23 04:58:16.976748: Current learning rate: 0.00045 +2024-11-23 04:58:35.316941: train_loss -0.8391 +2024-11-23 04:58:35.317215: val_loss -0.7713 +2024-11-23 04:58:35.317291: Pseudo dice [0.8438] +2024-11-23 04:58:35.317367: Epoch time: 18.34 s +2024-11-23 04:58:36.241910: +2024-11-23 04:58:36.242126: Epoch 7747 +2024-11-23 04:58:36.242236: Current learning rate: 0.00045 +2024-11-23 04:58:54.393827: train_loss -0.8385 +2024-11-23 04:58:54.394066: val_loss -0.7655 +2024-11-23 04:58:54.394141: Pseudo dice [0.847] +2024-11-23 04:58:54.394225: Epoch time: 18.15 s +2024-11-23 04:58:55.321308: +2024-11-23 04:58:55.321520: Epoch 7748 +2024-11-23 04:58:55.321634: Current learning rate: 0.00045 +2024-11-23 04:59:14.654148: train_loss -0.8461 +2024-11-23 04:59:14.654367: val_loss -0.7407 +2024-11-23 04:59:14.654443: Pseudo dice [0.8405] +2024-11-23 04:59:14.654519: Epoch time: 19.33 s +2024-11-23 04:59:16.056230: +2024-11-23 04:59:16.056431: Epoch 7749 +2024-11-23 04:59:16.056544: Current learning rate: 0.00044 +2024-11-23 04:59:33.904092: train_loss -0.8389 +2024-11-23 04:59:33.904333: val_loss -0.7784 +2024-11-23 04:59:33.904409: Pseudo dice [0.8474] +2024-11-23 04:59:33.904487: Epoch time: 17.85 s +2024-11-23 04:59:35.180404: +2024-11-23 04:59:35.180627: Epoch 7750 +2024-11-23 04:59:35.180750: Current learning rate: 0.00044 +2024-11-23 04:59:53.322613: train_loss -0.846 +2024-11-23 04:59:53.322846: val_loss -0.7742 +2024-11-23 04:59:53.322923: Pseudo dice [0.8432] +2024-11-23 04:59:53.323009: Epoch time: 18.14 s +2024-11-23 04:59:54.368239: +2024-11-23 04:59:54.368577: Epoch 7751 +2024-11-23 04:59:54.368740: Current learning rate: 0.00044 +2024-11-23 05:00:13.274153: train_loss -0.8375 +2024-11-23 05:00:13.274381: val_loss -0.7436 +2024-11-23 05:00:13.274457: Pseudo dice [0.8204] +2024-11-23 05:00:13.274536: Epoch time: 18.91 s +2024-11-23 05:00:14.207551: +2024-11-23 05:00:14.207758: Epoch 7752 +2024-11-23 05:00:14.207875: Current learning rate: 0.00044 +2024-11-23 05:00:32.180616: train_loss -0.839 +2024-11-23 05:00:32.180840: val_loss -0.7595 +2024-11-23 05:00:32.180914: Pseudo dice [0.8425] +2024-11-23 05:00:32.180989: Epoch time: 17.97 s +2024-11-23 05:00:33.109779: +2024-11-23 05:00:33.110046: Epoch 7753 +2024-11-23 05:00:33.110164: Current learning rate: 0.00044 +2024-11-23 05:00:52.406260: train_loss -0.8364 +2024-11-23 05:00:52.406493: val_loss -0.7431 +2024-11-23 05:00:52.406571: Pseudo dice [0.8404] +2024-11-23 05:00:52.406651: Epoch time: 19.3 s +2024-11-23 05:00:53.338155: +2024-11-23 05:00:53.338375: Epoch 7754 +2024-11-23 05:00:53.338495: Current learning rate: 0.00044 +2024-11-23 05:01:11.498388: train_loss -0.8436 +2024-11-23 05:01:11.498627: val_loss -0.7543 +2024-11-23 05:01:11.498703: Pseudo dice [0.8301] +2024-11-23 05:01:11.498788: Epoch time: 18.16 s +2024-11-23 05:01:12.428401: +2024-11-23 05:01:12.428607: Epoch 7755 +2024-11-23 05:01:12.428720: Current learning rate: 0.00043 +2024-11-23 05:01:30.768720: train_loss -0.8335 +2024-11-23 05:01:30.768934: val_loss -0.7505 +2024-11-23 05:01:30.769012: Pseudo dice [0.8354] +2024-11-23 05:01:30.769088: Epoch time: 18.34 s +2024-11-23 05:01:31.702215: +2024-11-23 05:01:31.702416: Epoch 7756 +2024-11-23 05:01:31.702527: Current learning rate: 0.00043 +2024-11-23 05:01:50.386982: train_loss -0.8417 +2024-11-23 05:01:50.387222: val_loss -0.7619 +2024-11-23 05:01:50.387304: Pseudo dice [0.8344] +2024-11-23 05:01:50.387389: Epoch time: 18.69 s +2024-11-23 05:01:51.318027: +2024-11-23 05:01:51.318231: Epoch 7757 +2024-11-23 05:01:51.318342: Current learning rate: 0.00043 +2024-11-23 05:02:10.491431: train_loss -0.8378 +2024-11-23 05:02:10.492793: val_loss -0.7541 +2024-11-23 05:02:10.492964: Pseudo dice [0.8306] +2024-11-23 05:02:10.493064: Epoch time: 19.17 s +2024-11-23 05:02:11.430932: +2024-11-23 05:02:11.431165: Epoch 7758 +2024-11-23 05:02:11.431284: Current learning rate: 0.00043 +2024-11-23 05:02:29.703749: train_loss -0.8399 +2024-11-23 05:02:29.703978: val_loss -0.7523 +2024-11-23 05:02:29.704056: Pseudo dice [0.8453] +2024-11-23 05:02:29.704135: Epoch time: 18.27 s +2024-11-23 05:02:30.706521: +2024-11-23 05:02:30.706970: Epoch 7759 +2024-11-23 05:02:30.707114: Current learning rate: 0.00043 +2024-11-23 05:02:49.668315: train_loss -0.8352 +2024-11-23 05:02:49.668525: val_loss -0.753 +2024-11-23 05:02:49.668600: Pseudo dice [0.8342] +2024-11-23 05:02:49.668674: Epoch time: 18.96 s +2024-11-23 05:02:50.976473: +2024-11-23 05:02:50.976722: Epoch 7760 +2024-11-23 05:02:50.976847: Current learning rate: 0.00043 +2024-11-23 05:03:08.650363: train_loss -0.8369 +2024-11-23 05:03:08.650597: val_loss -0.7636 +2024-11-23 05:03:08.650672: Pseudo dice [0.8394] +2024-11-23 05:03:08.650751: Epoch time: 17.67 s +2024-11-23 05:03:09.578319: +2024-11-23 05:03:09.578529: Epoch 7761 +2024-11-23 05:03:09.578641: Current learning rate: 0.00042 +2024-11-23 05:03:28.534025: train_loss -0.8401 +2024-11-23 05:03:28.534325: val_loss -0.7788 +2024-11-23 05:03:28.534405: Pseudo dice [0.8334] +2024-11-23 05:03:28.534497: Epoch time: 18.96 s +2024-11-23 05:03:29.465818: +2024-11-23 05:03:29.466030: Epoch 7762 +2024-11-23 05:03:29.466141: Current learning rate: 0.00042 +2024-11-23 05:03:48.636102: train_loss -0.8273 +2024-11-23 05:03:48.636329: val_loss -0.7603 +2024-11-23 05:03:48.636406: Pseudo dice [0.8348] +2024-11-23 05:03:48.636487: Epoch time: 19.17 s +2024-11-23 05:03:49.755136: +2024-11-23 05:03:49.755351: Epoch 7763 +2024-11-23 05:03:49.755465: Current learning rate: 0.00042 +2024-11-23 05:04:08.219527: train_loss -0.8465 +2024-11-23 05:04:08.219765: val_loss -0.7644 +2024-11-23 05:04:08.219842: Pseudo dice [0.8427] +2024-11-23 05:04:08.219921: Epoch time: 18.47 s +2024-11-23 05:04:09.250421: +2024-11-23 05:04:09.250713: Epoch 7764 +2024-11-23 05:04:09.250829: Current learning rate: 0.00042 +2024-11-23 05:04:27.742128: train_loss -0.8454 +2024-11-23 05:04:27.742354: val_loss -0.7636 +2024-11-23 05:04:27.742430: Pseudo dice [0.8444] +2024-11-23 05:04:27.742508: Epoch time: 18.49 s +2024-11-23 05:04:28.672339: +2024-11-23 05:04:28.672595: Epoch 7765 +2024-11-23 05:04:28.672717: Current learning rate: 0.00042 +2024-11-23 05:04:47.842270: train_loss -0.838 +2024-11-23 05:04:47.842517: val_loss -0.7686 +2024-11-23 05:04:47.842597: Pseudo dice [0.8355] +2024-11-23 05:04:47.842683: Epoch time: 19.17 s +2024-11-23 05:04:48.774197: +2024-11-23 05:04:48.774390: Epoch 7766 +2024-11-23 05:04:48.774503: Current learning rate: 0.00042 +2024-11-23 05:05:07.052128: train_loss -0.8429 +2024-11-23 05:05:07.053457: val_loss -0.7449 +2024-11-23 05:05:07.053552: Pseudo dice [0.8368] +2024-11-23 05:05:07.053630: Epoch time: 18.28 s +2024-11-23 05:05:08.137251: +2024-11-23 05:05:08.137492: Epoch 7767 +2024-11-23 05:05:08.137604: Current learning rate: 0.00041 +2024-11-23 05:05:27.201713: train_loss -0.8335 +2024-11-23 05:05:27.201929: val_loss -0.7466 +2024-11-23 05:05:27.202008: Pseudo dice [0.8337] +2024-11-23 05:05:27.202085: Epoch time: 19.07 s +2024-11-23 05:05:28.137635: +2024-11-23 05:05:28.137854: Epoch 7768 +2024-11-23 05:05:28.137967: Current learning rate: 0.00041 +2024-11-23 05:05:46.392695: train_loss -0.8364 +2024-11-23 05:05:46.392974: val_loss -0.7781 +2024-11-23 05:05:46.393058: Pseudo dice [0.8438] +2024-11-23 05:05:46.393136: Epoch time: 18.26 s +2024-11-23 05:05:47.355842: +2024-11-23 05:05:47.356043: Epoch 7769 +2024-11-23 05:05:47.356158: Current learning rate: 0.00041 +2024-11-23 05:06:06.695829: train_loss -0.8429 +2024-11-23 05:06:06.696068: val_loss -0.7612 +2024-11-23 05:06:06.696147: Pseudo dice [0.8333] +2024-11-23 05:06:06.696229: Epoch time: 19.34 s +2024-11-23 05:06:07.631118: +2024-11-23 05:06:07.631318: Epoch 7770 +2024-11-23 05:06:07.631435: Current learning rate: 0.00041 +2024-11-23 05:06:25.278180: train_loss -0.8381 +2024-11-23 05:06:25.278399: val_loss -0.7733 +2024-11-23 05:06:25.278472: Pseudo dice [0.8597] +2024-11-23 05:06:25.278548: Epoch time: 17.65 s +2024-11-23 05:06:26.600041: +2024-11-23 05:06:26.600295: Epoch 7771 +2024-11-23 05:06:26.600416: Current learning rate: 0.00041 +2024-11-23 05:06:43.612188: train_loss -0.8366 +2024-11-23 05:06:43.612423: val_loss -0.7593 +2024-11-23 05:06:43.612497: Pseudo dice [0.8471] +2024-11-23 05:06:43.612603: Epoch time: 17.01 s +2024-11-23 05:06:44.629494: +2024-11-23 05:06:44.629713: Epoch 7772 +2024-11-23 05:06:44.629827: Current learning rate: 0.00041 +2024-11-23 05:07:02.997527: train_loss -0.8382 +2024-11-23 05:07:03.002954: val_loss -0.7509 +2024-11-23 05:07:03.003083: Pseudo dice [0.8357] +2024-11-23 05:07:03.003177: Epoch time: 18.37 s +2024-11-23 05:07:04.111792: +2024-11-23 05:07:04.112014: Epoch 7773 +2024-11-23 05:07:04.112125: Current learning rate: 0.00041 +2024-11-23 05:07:23.197071: train_loss -0.8379 +2024-11-23 05:07:23.197283: val_loss -0.7697 +2024-11-23 05:07:23.197357: Pseudo dice [0.8377] +2024-11-23 05:07:23.197432: Epoch time: 19.09 s +2024-11-23 05:07:24.229980: +2024-11-23 05:07:24.230279: Epoch 7774 +2024-11-23 05:07:24.230395: Current learning rate: 0.0004 +2024-11-23 05:07:43.379955: train_loss -0.8406 +2024-11-23 05:07:43.380180: val_loss -0.7725 +2024-11-23 05:07:43.380251: Pseudo dice [0.8428] +2024-11-23 05:07:43.380327: Epoch time: 19.15 s +2024-11-23 05:07:44.327411: +2024-11-23 05:07:44.327619: Epoch 7775 +2024-11-23 05:07:44.327729: Current learning rate: 0.0004 +2024-11-23 05:08:03.499807: train_loss -0.8449 +2024-11-23 05:08:03.500019: val_loss -0.7644 +2024-11-23 05:08:03.500091: Pseudo dice [0.8456] +2024-11-23 05:08:03.500166: Epoch time: 19.17 s +2024-11-23 05:08:04.432195: +2024-11-23 05:08:04.432420: Epoch 7776 +2024-11-23 05:08:04.432537: Current learning rate: 0.0004 +2024-11-23 05:08:22.915790: train_loss -0.8422 +2024-11-23 05:08:22.916090: val_loss -0.7687 +2024-11-23 05:08:22.916163: Pseudo dice [0.8387] +2024-11-23 05:08:22.916249: Epoch time: 18.48 s +2024-11-23 05:08:23.855771: +2024-11-23 05:08:23.855999: Epoch 7777 +2024-11-23 05:08:23.856111: Current learning rate: 0.0004 +2024-11-23 05:08:41.850339: train_loss -0.8411 +2024-11-23 05:08:41.850548: val_loss -0.7577 +2024-11-23 05:08:41.850626: Pseudo dice [0.8443] +2024-11-23 05:08:41.850704: Epoch time: 18.0 s +2024-11-23 05:08:42.783846: +2024-11-23 05:08:42.784110: Epoch 7778 +2024-11-23 05:08:42.784225: Current learning rate: 0.0004 +2024-11-23 05:09:00.408514: train_loss -0.8419 +2024-11-23 05:09:00.408798: val_loss -0.7493 +2024-11-23 05:09:00.408873: Pseudo dice [0.8337] +2024-11-23 05:09:00.408949: Epoch time: 17.63 s +2024-11-23 05:09:01.343627: +2024-11-23 05:09:01.343830: Epoch 7779 +2024-11-23 05:09:01.343947: Current learning rate: 0.0004 +2024-11-23 05:09:18.928751: train_loss -0.8427 +2024-11-23 05:09:18.928975: val_loss -0.7741 +2024-11-23 05:09:18.944539: Pseudo dice [0.842] +2024-11-23 05:09:18.944650: Epoch time: 17.59 s +2024-11-23 05:09:19.872312: +2024-11-23 05:09:19.872507: Epoch 7780 +2024-11-23 05:09:19.872618: Current learning rate: 0.00039 +2024-11-23 05:09:38.278978: train_loss -0.8441 +2024-11-23 05:09:38.279218: val_loss -0.7585 +2024-11-23 05:09:38.279294: Pseudo dice [0.833] +2024-11-23 05:09:38.279381: Epoch time: 18.41 s +2024-11-23 05:09:39.212326: +2024-11-23 05:09:39.212708: Epoch 7781 +2024-11-23 05:09:39.212820: Current learning rate: 0.00039 +2024-11-23 05:09:58.814702: train_loss -0.8422 +2024-11-23 05:09:58.814932: val_loss -0.7747 +2024-11-23 05:09:58.815011: Pseudo dice [0.8361] +2024-11-23 05:09:58.815091: Epoch time: 19.6 s +2024-11-23 05:09:59.770240: +2024-11-23 05:09:59.770643: Epoch 7782 +2024-11-23 05:09:59.770775: Current learning rate: 0.00039 +2024-11-23 05:10:18.791716: train_loss -0.8413 +2024-11-23 05:10:18.791938: val_loss -0.7498 +2024-11-23 05:10:18.792021: Pseudo dice [0.8292] +2024-11-23 05:10:18.792100: Epoch time: 19.02 s +2024-11-23 05:10:20.197656: +2024-11-23 05:10:20.197873: Epoch 7783 +2024-11-23 05:10:20.197984: Current learning rate: 0.00039 +2024-11-23 05:10:38.881107: train_loss -0.8321 +2024-11-23 05:10:38.881339: val_loss -0.7657 +2024-11-23 05:10:38.883632: Pseudo dice [0.8289] +2024-11-23 05:10:38.883767: Epoch time: 18.68 s +2024-11-23 05:10:39.842694: +2024-11-23 05:10:39.842903: Epoch 7784 +2024-11-23 05:10:39.843025: Current learning rate: 0.00039 +2024-11-23 05:10:58.746585: train_loss -0.8394 +2024-11-23 05:10:58.746812: val_loss -0.7712 +2024-11-23 05:10:58.746888: Pseudo dice [0.8327] +2024-11-23 05:10:58.746968: Epoch time: 18.9 s +2024-11-23 05:10:59.684659: +2024-11-23 05:10:59.684979: Epoch 7785 +2024-11-23 05:10:59.685101: Current learning rate: 0.00039 +2024-11-23 05:11:18.771923: train_loss -0.8373 +2024-11-23 05:11:18.772151: val_loss -0.7684 +2024-11-23 05:11:18.772227: Pseudo dice [0.8478] +2024-11-23 05:11:18.772305: Epoch time: 19.09 s +2024-11-23 05:11:19.710981: +2024-11-23 05:11:19.711182: Epoch 7786 +2024-11-23 05:11:19.711299: Current learning rate: 0.00038 +2024-11-23 05:11:38.296208: train_loss -0.8421 +2024-11-23 05:11:38.296437: val_loss -0.7557 +2024-11-23 05:11:38.296519: Pseudo dice [0.8435] +2024-11-23 05:11:38.296600: Epoch time: 18.59 s +2024-11-23 05:11:39.227135: +2024-11-23 05:11:39.227371: Epoch 7787 +2024-11-23 05:11:39.227491: Current learning rate: 0.00038 +2024-11-23 05:11:57.926149: train_loss -0.8445 +2024-11-23 05:11:57.928528: val_loss -0.7437 +2024-11-23 05:11:57.928620: Pseudo dice [0.8442] +2024-11-23 05:11:57.928702: Epoch time: 18.7 s +2024-11-23 05:11:58.890233: +2024-11-23 05:11:58.890433: Epoch 7788 +2024-11-23 05:11:58.890545: Current learning rate: 0.00038 +2024-11-23 05:12:17.354325: train_loss -0.8401 +2024-11-23 05:12:17.354609: val_loss -0.7593 +2024-11-23 05:12:17.354688: Pseudo dice [0.8333] +2024-11-23 05:12:17.354769: Epoch time: 18.46 s +2024-11-23 05:12:18.289900: +2024-11-23 05:12:18.290120: Epoch 7789 +2024-11-23 05:12:18.290240: Current learning rate: 0.00038 +2024-11-23 05:12:36.536109: train_loss -0.8443 +2024-11-23 05:12:36.536333: val_loss -0.7531 +2024-11-23 05:12:36.536409: Pseudo dice [0.8492] +2024-11-23 05:12:36.536487: Epoch time: 18.25 s +2024-11-23 05:12:37.469530: +2024-11-23 05:12:37.469754: Epoch 7790 +2024-11-23 05:12:37.469870: Current learning rate: 0.00038 +2024-11-23 05:12:56.536226: train_loss -0.8382 +2024-11-23 05:12:56.536466: val_loss -0.772 +2024-11-23 05:12:56.536540: Pseudo dice [0.8428] +2024-11-23 05:12:56.536621: Epoch time: 19.07 s +2024-11-23 05:12:57.473143: +2024-11-23 05:12:57.473356: Epoch 7791 +2024-11-23 05:12:57.473468: Current learning rate: 0.00038 +2024-11-23 05:13:15.522313: train_loss -0.8462 +2024-11-23 05:13:15.522529: val_loss -0.7742 +2024-11-23 05:13:15.522602: Pseudo dice [0.8438] +2024-11-23 05:13:15.522677: Epoch time: 18.05 s +2024-11-23 05:13:16.463807: +2024-11-23 05:13:16.464063: Epoch 7792 +2024-11-23 05:13:16.464180: Current learning rate: 0.00037 +2024-11-23 05:13:35.744424: train_loss -0.8383 +2024-11-23 05:13:35.744665: val_loss -0.7617 +2024-11-23 05:13:35.744741: Pseudo dice [0.8368] +2024-11-23 05:13:35.744819: Epoch time: 19.28 s +2024-11-23 05:13:36.674209: +2024-11-23 05:13:36.674428: Epoch 7793 +2024-11-23 05:13:36.674546: Current learning rate: 0.00037 +2024-11-23 05:13:55.093286: train_loss -0.8397 +2024-11-23 05:13:55.093509: val_loss -0.7901 +2024-11-23 05:13:55.093585: Pseudo dice [0.8511] +2024-11-23 05:13:55.093663: Epoch time: 18.42 s +2024-11-23 05:13:56.417966: +2024-11-23 05:13:56.418192: Epoch 7794 +2024-11-23 05:13:56.418304: Current learning rate: 0.00037 +2024-11-23 05:14:15.167881: train_loss -0.8441 +2024-11-23 05:14:15.168128: val_loss -0.7123 +2024-11-23 05:14:15.168247: Pseudo dice [0.8182] +2024-11-23 05:14:15.168359: Epoch time: 18.75 s +2024-11-23 05:14:16.162483: +2024-11-23 05:14:16.162781: Epoch 7795 +2024-11-23 05:14:16.162894: Current learning rate: 0.00037 +2024-11-23 05:14:34.698496: train_loss -0.8387 +2024-11-23 05:14:34.698720: val_loss -0.7386 +2024-11-23 05:14:34.698797: Pseudo dice [0.839] +2024-11-23 05:14:34.698874: Epoch time: 18.54 s +2024-11-23 05:14:35.627732: +2024-11-23 05:14:35.627989: Epoch 7796 +2024-11-23 05:14:35.628109: Current learning rate: 0.00037 +2024-11-23 05:14:53.965926: train_loss -0.8407 +2024-11-23 05:14:53.966151: val_loss -0.7816 +2024-11-23 05:14:53.966225: Pseudo dice [0.8609] +2024-11-23 05:14:53.968396: Epoch time: 18.34 s +2024-11-23 05:14:54.905878: +2024-11-23 05:14:54.906086: Epoch 7797 +2024-11-23 05:14:54.906198: Current learning rate: 0.00037 +2024-11-23 05:15:14.514611: train_loss -0.8374 +2024-11-23 05:15:14.514890: val_loss -0.7657 +2024-11-23 05:15:14.514966: Pseudo dice [0.8349] +2024-11-23 05:15:14.515056: Epoch time: 19.61 s +2024-11-23 05:15:15.456094: +2024-11-23 05:15:15.456300: Epoch 7798 +2024-11-23 05:15:15.456413: Current learning rate: 0.00036 +2024-11-23 05:15:34.230642: train_loss -0.834 +2024-11-23 05:15:34.230877: val_loss -0.7376 +2024-11-23 05:15:34.230951: Pseudo dice [0.826] +2024-11-23 05:15:34.231036: Epoch time: 18.78 s +2024-11-23 05:15:35.162996: +2024-11-23 05:15:35.163193: Epoch 7799 +2024-11-23 05:15:35.163303: Current learning rate: 0.00036 +2024-11-23 05:15:53.518414: train_loss -0.8414 +2024-11-23 05:15:53.518625: val_loss -0.7752 +2024-11-23 05:15:53.518694: Pseudo dice [0.8327] +2024-11-23 05:15:53.518769: Epoch time: 18.36 s +2024-11-23 05:15:54.789974: +2024-11-23 05:15:54.790173: Epoch 7800 +2024-11-23 05:15:54.790282: Current learning rate: 0.00036 +2024-11-23 05:16:14.242826: train_loss -0.8444 +2024-11-23 05:16:14.245294: val_loss -0.773 +2024-11-23 05:16:14.245380: Pseudo dice [0.8549] +2024-11-23 05:16:14.245461: Epoch time: 19.45 s +2024-11-23 05:16:15.244704: +2024-11-23 05:16:15.244989: Epoch 7801 +2024-11-23 05:16:15.245111: Current learning rate: 0.00036 +2024-11-23 05:16:34.569895: train_loss -0.8309 +2024-11-23 05:16:34.570151: val_loss -0.7648 +2024-11-23 05:16:34.570226: Pseudo dice [0.8586] +2024-11-23 05:16:34.570345: Epoch time: 19.33 s +2024-11-23 05:16:35.510701: +2024-11-23 05:16:35.510916: Epoch 7802 +2024-11-23 05:16:35.511032: Current learning rate: 0.00036 +2024-11-23 05:16:54.743303: train_loss -0.8431 +2024-11-23 05:16:54.743520: val_loss -0.7684 +2024-11-23 05:16:54.743598: Pseudo dice [0.8381] +2024-11-23 05:16:54.743674: Epoch time: 19.23 s +2024-11-23 05:16:55.689421: +2024-11-23 05:16:55.689626: Epoch 7803 +2024-11-23 05:16:55.689741: Current learning rate: 0.00036 +2024-11-23 05:17:13.257368: train_loss -0.8371 +2024-11-23 05:17:13.257591: val_loss -0.7657 +2024-11-23 05:17:13.257666: Pseudo dice [0.8388] +2024-11-23 05:17:13.257741: Epoch time: 17.57 s +2024-11-23 05:17:14.200622: +2024-11-23 05:17:14.200958: Epoch 7804 +2024-11-23 05:17:14.201076: Current learning rate: 0.00036 +2024-11-23 05:17:32.791178: train_loss -0.8372 +2024-11-23 05:17:32.791435: val_loss -0.7183 +2024-11-23 05:17:32.791512: Pseudo dice [0.8275] +2024-11-23 05:17:32.791597: Epoch time: 18.59 s +2024-11-23 05:17:33.733889: +2024-11-23 05:17:33.734222: Epoch 7805 +2024-11-23 05:17:33.734341: Current learning rate: 0.00035 +2024-11-23 05:17:52.412707: train_loss -0.8477 +2024-11-23 05:17:52.413689: val_loss -0.7464 +2024-11-23 05:17:52.413819: Pseudo dice [0.8378] +2024-11-23 05:17:52.413899: Epoch time: 18.68 s +2024-11-23 05:17:53.346790: +2024-11-23 05:17:53.346997: Epoch 7806 +2024-11-23 05:17:53.347109: Current learning rate: 0.00035 +2024-11-23 05:18:12.850903: train_loss -0.8333 +2024-11-23 05:18:12.851139: val_loss -0.7589 +2024-11-23 05:18:12.851226: Pseudo dice [0.84] +2024-11-23 05:18:12.851312: Epoch time: 19.5 s +2024-11-23 05:18:13.783796: +2024-11-23 05:18:13.784033: Epoch 7807 +2024-11-23 05:18:13.784149: Current learning rate: 0.00035 +2024-11-23 05:18:32.652503: train_loss -0.8374 +2024-11-23 05:18:32.652738: val_loss -0.7667 +2024-11-23 05:18:32.652815: Pseudo dice [0.8409] +2024-11-23 05:18:32.652929: Epoch time: 18.87 s +2024-11-23 05:18:33.585875: +2024-11-23 05:18:33.586117: Epoch 7808 +2024-11-23 05:18:33.586230: Current learning rate: 0.00035 +2024-11-23 05:18:52.068839: train_loss -0.8369 +2024-11-23 05:18:52.069054: val_loss -0.7515 +2024-11-23 05:18:52.069127: Pseudo dice [0.8284] +2024-11-23 05:18:52.069347: Epoch time: 18.48 s +2024-11-23 05:18:53.005373: +2024-11-23 05:18:53.005686: Epoch 7809 +2024-11-23 05:18:53.005805: Current learning rate: 0.00035 +2024-11-23 05:19:11.452236: train_loss -0.8413 +2024-11-23 05:19:11.452455: val_loss -0.7617 +2024-11-23 05:19:11.452530: Pseudo dice [0.8339] +2024-11-23 05:19:11.452607: Epoch time: 18.45 s +2024-11-23 05:19:12.387237: +2024-11-23 05:19:12.387450: Epoch 7810 +2024-11-23 05:19:12.387560: Current learning rate: 0.00035 +2024-11-23 05:19:30.819023: train_loss -0.8421 +2024-11-23 05:19:30.819242: val_loss -0.784 +2024-11-23 05:19:30.819378: Pseudo dice [0.859] +2024-11-23 05:19:30.819457: Epoch time: 18.43 s +2024-11-23 05:19:31.753689: +2024-11-23 05:19:31.753897: Epoch 7811 +2024-11-23 05:19:31.754014: Current learning rate: 0.00034 +2024-11-23 05:19:49.962066: train_loss -0.8423 +2024-11-23 05:19:49.962307: val_loss -0.7609 +2024-11-23 05:19:49.962385: Pseudo dice [0.839] +2024-11-23 05:19:49.962467: Epoch time: 18.21 s +2024-11-23 05:19:50.894551: +2024-11-23 05:19:50.894762: Epoch 7812 +2024-11-23 05:19:50.894877: Current learning rate: 0.00034 +2024-11-23 05:20:10.016631: train_loss -0.8408 +2024-11-23 05:20:10.016845: val_loss -0.7789 +2024-11-23 05:20:10.016921: Pseudo dice [0.8512] +2024-11-23 05:20:10.017008: Epoch time: 19.12 s +2024-11-23 05:20:10.944181: +2024-11-23 05:20:10.944409: Epoch 7813 +2024-11-23 05:20:10.944524: Current learning rate: 0.00034 +2024-11-23 05:20:29.587130: train_loss -0.8373 +2024-11-23 05:20:29.587364: val_loss -0.7924 +2024-11-23 05:20:29.587440: Pseudo dice [0.8413] +2024-11-23 05:20:29.587571: Epoch time: 18.64 s +2024-11-23 05:20:30.581425: +2024-11-23 05:20:30.581650: Epoch 7814 +2024-11-23 05:20:30.581763: Current learning rate: 0.00034 +2024-11-23 05:20:49.208760: train_loss -0.8404 +2024-11-23 05:20:49.208984: val_loss -0.7637 +2024-11-23 05:20:49.209066: Pseudo dice [0.8345] +2024-11-23 05:20:49.209146: Epoch time: 18.63 s +2024-11-23 05:20:50.207395: +2024-11-23 05:20:50.207600: Epoch 7815 +2024-11-23 05:20:50.207711: Current learning rate: 0.00034 +2024-11-23 05:21:09.268092: train_loss -0.8399 +2024-11-23 05:21:09.270481: val_loss -0.7623 +2024-11-23 05:21:09.270591: Pseudo dice [0.8371] +2024-11-23 05:21:09.270679: Epoch time: 19.06 s +2024-11-23 05:21:10.225179: +2024-11-23 05:21:10.225378: Epoch 7816 +2024-11-23 05:21:10.225490: Current learning rate: 0.00034 +2024-11-23 05:21:28.977435: train_loss -0.8439 +2024-11-23 05:21:28.977649: val_loss -0.769 +2024-11-23 05:21:28.977728: Pseudo dice [0.8371] +2024-11-23 05:21:28.977807: Epoch time: 18.75 s +2024-11-23 05:21:29.905760: +2024-11-23 05:21:29.905961: Epoch 7817 +2024-11-23 05:21:29.906079: Current learning rate: 0.00033 +2024-11-23 05:21:48.047638: train_loss -0.8425 +2024-11-23 05:21:48.047861: val_loss -0.775 +2024-11-23 05:21:48.047942: Pseudo dice [0.8435] +2024-11-23 05:21:48.048030: Epoch time: 18.14 s +2024-11-23 05:21:48.980980: +2024-11-23 05:21:48.981227: Epoch 7818 +2024-11-23 05:21:48.981346: Current learning rate: 0.00033 +2024-11-23 05:22:07.078153: train_loss -0.8427 +2024-11-23 05:22:07.078719: val_loss -0.7665 +2024-11-23 05:22:07.078794: Pseudo dice [0.8547] +2024-11-23 05:22:07.078879: Epoch time: 18.1 s +2024-11-23 05:22:08.009863: +2024-11-23 05:22:08.010095: Epoch 7819 +2024-11-23 05:22:08.010207: Current learning rate: 0.00033 +2024-11-23 05:22:26.439234: train_loss -0.8425 +2024-11-23 05:22:26.439438: val_loss -0.7688 +2024-11-23 05:22:26.439512: Pseudo dice [0.8408] +2024-11-23 05:22:26.439591: Epoch time: 18.43 s +2024-11-23 05:22:27.369631: +2024-11-23 05:22:27.369838: Epoch 7820 +2024-11-23 05:22:27.369953: Current learning rate: 0.00033 +2024-11-23 05:22:45.842208: train_loss -0.8442 +2024-11-23 05:22:45.842421: val_loss -0.7701 +2024-11-23 05:22:45.842494: Pseudo dice [0.8423] +2024-11-23 05:22:45.847801: Epoch time: 18.47 s +2024-11-23 05:22:46.879581: +2024-11-23 05:22:46.879814: Epoch 7821 +2024-11-23 05:22:46.879930: Current learning rate: 0.00033 +2024-11-23 05:23:05.465188: train_loss -0.8432 +2024-11-23 05:23:05.465411: val_loss -0.7608 +2024-11-23 05:23:05.465488: Pseudo dice [0.8376] +2024-11-23 05:23:05.465569: Epoch time: 18.59 s +2024-11-23 05:23:06.502047: +2024-11-23 05:23:06.502348: Epoch 7822 +2024-11-23 05:23:06.502464: Current learning rate: 0.00033 +2024-11-23 05:23:24.698443: train_loss -0.8386 +2024-11-23 05:23:24.698675: val_loss -0.75 +2024-11-23 05:23:24.698748: Pseudo dice [0.8332] +2024-11-23 05:23:24.698829: Epoch time: 18.2 s +2024-11-23 05:23:25.661483: +2024-11-23 05:23:25.661677: Epoch 7823 +2024-11-23 05:23:25.661792: Current learning rate: 0.00032 +2024-11-23 05:23:44.061482: train_loss -0.8399 +2024-11-23 05:23:44.061692: val_loss -0.757 +2024-11-23 05:23:44.061768: Pseudo dice [0.8265] +2024-11-23 05:23:44.061845: Epoch time: 18.4 s +2024-11-23 05:23:44.991678: +2024-11-23 05:23:44.991887: Epoch 7824 +2024-11-23 05:23:44.992007: Current learning rate: 0.00032 +2024-11-23 05:24:03.660988: train_loss -0.844 +2024-11-23 05:24:03.661224: val_loss -0.7726 +2024-11-23 05:24:03.661319: Pseudo dice [0.8446] +2024-11-23 05:24:03.661454: Epoch time: 18.67 s +2024-11-23 05:24:04.859564: +2024-11-23 05:24:04.859767: Epoch 7825 +2024-11-23 05:24:04.859886: Current learning rate: 0.00032 +2024-11-23 05:24:24.145661: train_loss -0.8391 +2024-11-23 05:24:24.145897: val_loss -0.7836 +2024-11-23 05:24:24.145972: Pseudo dice [0.8392] +2024-11-23 05:24:24.146062: Epoch time: 19.29 s +2024-11-23 05:24:25.137760: +2024-11-23 05:24:25.137967: Epoch 7826 +2024-11-23 05:24:25.138090: Current learning rate: 0.00032 +2024-11-23 05:24:43.220826: train_loss -0.8393 +2024-11-23 05:24:43.221057: val_loss -0.7804 +2024-11-23 05:24:43.223357: Pseudo dice [0.8533] +2024-11-23 05:24:43.223453: Epoch time: 18.08 s +2024-11-23 05:24:44.191065: +2024-11-23 05:24:44.191290: Epoch 7827 +2024-11-23 05:24:44.191406: Current learning rate: 0.00032 +2024-11-23 05:25:03.258472: train_loss -0.8404 +2024-11-23 05:25:03.258698: val_loss -0.7498 +2024-11-23 05:25:03.258776: Pseudo dice [0.844] +2024-11-23 05:25:03.258855: Epoch time: 19.07 s +2024-11-23 05:25:04.194019: +2024-11-23 05:25:04.194350: Epoch 7828 +2024-11-23 05:25:04.194464: Current learning rate: 0.00032 +2024-11-23 05:25:21.873153: train_loss -0.8452 +2024-11-23 05:25:21.873380: val_loss -0.7609 +2024-11-23 05:25:21.873458: Pseudo dice [0.8364] +2024-11-23 05:25:21.873538: Epoch time: 17.68 s +2024-11-23 05:25:22.801317: +2024-11-23 05:25:22.801527: Epoch 7829 +2024-11-23 05:25:22.801638: Current learning rate: 0.00031 +2024-11-23 05:25:42.387473: train_loss -0.8371 +2024-11-23 05:25:42.387689: val_loss -0.7771 +2024-11-23 05:25:42.387759: Pseudo dice [0.8502] +2024-11-23 05:25:42.387837: Epoch time: 19.59 s +2024-11-23 05:25:43.323951: +2024-11-23 05:25:43.324169: Epoch 7830 +2024-11-23 05:25:43.324286: Current learning rate: 0.00031 +2024-11-23 05:26:02.338170: train_loss -0.8422 +2024-11-23 05:26:02.339858: val_loss -0.7517 +2024-11-23 05:26:02.339967: Pseudo dice [0.842] +2024-11-23 05:26:02.340055: Epoch time: 19.02 s +2024-11-23 05:26:03.442461: +2024-11-23 05:26:03.442683: Epoch 7831 +2024-11-23 05:26:03.442803: Current learning rate: 0.00031 +2024-11-23 05:26:22.066975: train_loss -0.8395 +2024-11-23 05:26:22.067207: val_loss -0.7777 +2024-11-23 05:26:22.067286: Pseudo dice [0.8407] +2024-11-23 05:26:22.067364: Epoch time: 18.63 s +2024-11-23 05:26:22.999055: +2024-11-23 05:26:22.999282: Epoch 7832 +2024-11-23 05:26:22.999400: Current learning rate: 0.00031 +2024-11-23 05:26:42.798194: train_loss -0.8424 +2024-11-23 05:26:42.798409: val_loss -0.7826 +2024-11-23 05:26:42.798482: Pseudo dice [0.8404] +2024-11-23 05:26:42.798558: Epoch time: 19.8 s +2024-11-23 05:26:43.728865: +2024-11-23 05:26:43.729086: Epoch 7833 +2024-11-23 05:26:43.729199: Current learning rate: 0.00031 +2024-11-23 05:27:03.745337: train_loss -0.8361 +2024-11-23 05:27:03.745571: val_loss -0.7477 +2024-11-23 05:27:03.745646: Pseudo dice [0.8524] +2024-11-23 05:27:03.745728: Epoch time: 20.02 s +2024-11-23 05:27:04.685490: +2024-11-23 05:27:04.685707: Epoch 7834 +2024-11-23 05:27:04.685822: Current learning rate: 0.00031 +2024-11-23 05:27:22.791623: train_loss -0.8388 +2024-11-23 05:27:22.791842: val_loss -0.7662 +2024-11-23 05:27:22.791918: Pseudo dice [0.8425] +2024-11-23 05:27:22.792123: Epoch time: 18.11 s +2024-11-23 05:27:23.917544: +2024-11-23 05:27:23.917800: Epoch 7835 +2024-11-23 05:27:23.917912: Current learning rate: 0.0003 +2024-11-23 05:27:42.969005: train_loss -0.8409 +2024-11-23 05:27:42.969228: val_loss -0.7757 +2024-11-23 05:27:42.969302: Pseudo dice [0.8488] +2024-11-23 05:27:42.969378: Epoch time: 19.05 s +2024-11-23 05:27:44.005383: +2024-11-23 05:27:44.005585: Epoch 7836 +2024-11-23 05:27:44.005697: Current learning rate: 0.0003 +2024-11-23 05:28:02.011488: train_loss -0.843 +2024-11-23 05:28:02.011726: val_loss -0.7614 +2024-11-23 05:28:02.011801: Pseudo dice [0.8632] +2024-11-23 05:28:02.011885: Epoch time: 18.01 s +2024-11-23 05:28:02.011949: Yayy! New best EMA pseudo Dice: 0.8452 +2024-11-23 05:28:03.288357: +2024-11-23 05:28:03.288557: Epoch 7837 +2024-11-23 05:28:03.288669: Current learning rate: 0.0003 +2024-11-23 05:28:22.586153: train_loss -0.8415 +2024-11-23 05:28:22.586373: val_loss -0.794 +2024-11-23 05:28:22.586447: Pseudo dice [0.8357] +2024-11-23 05:28:22.586522: Epoch time: 19.3 s +2024-11-23 05:28:23.513284: +2024-11-23 05:28:23.513479: Epoch 7838 +2024-11-23 05:28:23.513590: Current learning rate: 0.0003 +2024-11-23 05:28:42.735191: train_loss -0.8403 +2024-11-23 05:28:42.735421: val_loss -0.7576 +2024-11-23 05:28:42.735564: Pseudo dice [0.8519] +2024-11-23 05:28:42.735644: Epoch time: 19.22 s +2024-11-23 05:28:43.664959: +2024-11-23 05:28:43.665183: Epoch 7839 +2024-11-23 05:28:43.665296: Current learning rate: 0.0003 +2024-11-23 05:29:02.283291: train_loss -0.8362 +2024-11-23 05:29:02.283605: val_loss -0.7604 +2024-11-23 05:29:02.283690: Pseudo dice [0.8256] +2024-11-23 05:29:02.283776: Epoch time: 18.62 s +2024-11-23 05:29:03.321571: +2024-11-23 05:29:03.321789: Epoch 7840 +2024-11-23 05:29:03.321909: Current learning rate: 0.0003 +2024-11-23 05:29:22.444286: train_loss -0.8405 +2024-11-23 05:29:22.444512: val_loss -0.7575 +2024-11-23 05:29:22.444603: Pseudo dice [0.8413] +2024-11-23 05:29:22.444686: Epoch time: 19.12 s +2024-11-23 05:29:23.367671: +2024-11-23 05:29:23.367880: Epoch 7841 +2024-11-23 05:29:23.367999: Current learning rate: 0.00029 +2024-11-23 05:29:41.247633: train_loss -0.8423 +2024-11-23 05:29:41.248865: val_loss -0.7481 +2024-11-23 05:29:41.248985: Pseudo dice [0.8568] +2024-11-23 05:29:41.249074: Epoch time: 17.88 s +2024-11-23 05:29:42.283382: +2024-11-23 05:29:42.283601: Epoch 7842 +2024-11-23 05:29:42.283717: Current learning rate: 0.00029 +2024-11-23 05:30:00.621004: train_loss -0.8366 +2024-11-23 05:30:00.621243: val_loss -0.7608 +2024-11-23 05:30:00.621320: Pseudo dice [0.8424] +2024-11-23 05:30:00.621403: Epoch time: 18.34 s +2024-11-23 05:30:01.556118: +2024-11-23 05:30:01.556331: Epoch 7843 +2024-11-23 05:30:01.556443: Current learning rate: 0.00029 +2024-11-23 05:30:19.680886: train_loss -0.8423 +2024-11-23 05:30:19.681141: val_loss -0.7569 +2024-11-23 05:30:19.681219: Pseudo dice [0.8357] +2024-11-23 05:30:19.681298: Epoch time: 18.13 s +2024-11-23 05:30:20.645337: +2024-11-23 05:30:20.645564: Epoch 7844 +2024-11-23 05:30:20.645671: Current learning rate: 0.00029 +2024-11-23 05:30:40.189167: train_loss -0.8411 +2024-11-23 05:30:40.189385: val_loss -0.7295 +2024-11-23 05:30:40.189461: Pseudo dice [0.8241] +2024-11-23 05:30:40.189534: Epoch time: 19.54 s +2024-11-23 05:30:41.096850: +2024-11-23 05:30:41.097070: Epoch 7845 +2024-11-23 05:30:41.097180: Current learning rate: 0.00029 +2024-11-23 05:30:59.684317: train_loss -0.8391 +2024-11-23 05:30:59.684535: val_loss -0.7733 +2024-11-23 05:30:59.684611: Pseudo dice [0.8573] +2024-11-23 05:30:59.684687: Epoch time: 18.59 s +2024-11-23 05:31:00.609976: +2024-11-23 05:31:00.610206: Epoch 7846 +2024-11-23 05:31:00.610326: Current learning rate: 0.00029 +2024-11-23 05:31:19.118814: train_loss -0.8418 +2024-11-23 05:31:19.119089: val_loss -0.7675 +2024-11-23 05:31:19.119172: Pseudo dice [0.8364] +2024-11-23 05:31:19.119251: Epoch time: 18.51 s +2024-11-23 05:31:20.139434: +2024-11-23 05:31:20.139610: Epoch 7847 +2024-11-23 05:31:20.139717: Current learning rate: 0.00028 +2024-11-23 05:31:40.277998: train_loss -0.845 +2024-11-23 05:31:40.278288: val_loss -0.7751 +2024-11-23 05:31:40.278364: Pseudo dice [0.8522] +2024-11-23 05:31:40.278444: Epoch time: 20.14 s +2024-11-23 05:31:41.243968: +2024-11-23 05:31:41.244220: Epoch 7848 +2024-11-23 05:31:41.244330: Current learning rate: 0.00028 +2024-11-23 05:31:59.224226: train_loss -0.8416 +2024-11-23 05:31:59.224498: val_loss -0.75 +2024-11-23 05:31:59.224574: Pseudo dice [0.823] +2024-11-23 05:31:59.224648: Epoch time: 17.98 s +2024-11-23 05:32:00.154461: +2024-11-23 05:32:00.154671: Epoch 7849 +2024-11-23 05:32:00.154783: Current learning rate: 0.00028 +2024-11-23 05:32:18.556097: train_loss -0.8433 +2024-11-23 05:32:18.556335: val_loss -0.7581 +2024-11-23 05:32:18.556411: Pseudo dice [0.8141] +2024-11-23 05:32:18.556489: Epoch time: 18.4 s +2024-11-23 05:32:19.846817: +2024-11-23 05:32:19.847037: Epoch 7850 +2024-11-23 05:32:19.847149: Current learning rate: 0.00028 +2024-11-23 05:32:37.784893: train_loss -0.8435 +2024-11-23 05:32:37.785139: val_loss -0.7432 +2024-11-23 05:32:37.785214: Pseudo dice [0.833] +2024-11-23 05:32:37.785297: Epoch time: 17.94 s +2024-11-23 05:32:38.714402: +2024-11-23 05:32:38.714650: Epoch 7851 +2024-11-23 05:32:38.714763: Current learning rate: 0.00028 +2024-11-23 05:32:56.453667: train_loss -0.8461 +2024-11-23 05:32:56.453883: val_loss -0.7574 +2024-11-23 05:32:56.453956: Pseudo dice [0.8469] +2024-11-23 05:32:56.454040: Epoch time: 17.74 s +2024-11-23 05:32:57.407289: +2024-11-23 05:32:57.407568: Epoch 7852 +2024-11-23 05:32:57.407682: Current learning rate: 0.00028 +2024-11-23 05:33:15.625654: train_loss -0.8418 +2024-11-23 05:33:15.625871: val_loss -0.7679 +2024-11-23 05:33:15.625946: Pseudo dice [0.8442] +2024-11-23 05:33:15.626026: Epoch time: 18.22 s +2024-11-23 05:33:16.550052: +2024-11-23 05:33:16.550268: Epoch 7853 +2024-11-23 05:33:16.550388: Current learning rate: 0.00027 +2024-11-23 05:33:35.461302: train_loss -0.8402 +2024-11-23 05:33:35.461538: val_loss -0.7761 +2024-11-23 05:33:35.461615: Pseudo dice [0.8322] +2024-11-23 05:33:35.461699: Epoch time: 18.91 s +2024-11-23 05:33:36.383652: +2024-11-23 05:33:36.383835: Epoch 7854 +2024-11-23 05:33:36.383945: Current learning rate: 0.00027 +2024-11-23 05:33:55.411638: train_loss -0.8385 +2024-11-23 05:33:55.411915: val_loss -0.7646 +2024-11-23 05:33:55.412003: Pseudo dice [0.8359] +2024-11-23 05:33:55.412084: Epoch time: 19.03 s +2024-11-23 05:33:56.345569: +2024-11-23 05:33:56.345775: Epoch 7855 +2024-11-23 05:33:56.345889: Current learning rate: 0.00027 +2024-11-23 05:34:15.382088: train_loss -0.8434 +2024-11-23 05:34:15.382318: val_loss -0.7765 +2024-11-23 05:34:15.383112: Pseudo dice [0.8415] +2024-11-23 05:34:15.383236: Epoch time: 19.04 s +2024-11-23 05:34:16.438052: +2024-11-23 05:34:16.438266: Epoch 7856 +2024-11-23 05:34:16.438381: Current learning rate: 0.00027 +2024-11-23 05:34:35.364915: train_loss -0.8428 +2024-11-23 05:34:35.365135: val_loss -0.7692 +2024-11-23 05:34:35.365206: Pseudo dice [0.8581] +2024-11-23 05:34:35.365282: Epoch time: 18.93 s +2024-11-23 05:34:36.274637: +2024-11-23 05:34:36.274824: Epoch 7857 +2024-11-23 05:34:36.274937: Current learning rate: 0.00027 +2024-11-23 05:34:54.401459: train_loss -0.8386 +2024-11-23 05:34:54.401698: val_loss -0.7593 +2024-11-23 05:34:54.401774: Pseudo dice [0.8227] +2024-11-23 05:34:54.401859: Epoch time: 18.13 s +2024-11-23 05:34:55.320691: +2024-11-23 05:34:55.320891: Epoch 7858 +2024-11-23 05:34:55.321006: Current learning rate: 0.00027 +2024-11-23 05:35:13.060845: train_loss -0.8441 +2024-11-23 05:35:13.061076: val_loss -0.7841 +2024-11-23 05:35:13.061154: Pseudo dice [0.8514] +2024-11-23 05:35:13.061235: Epoch time: 17.74 s +2024-11-23 05:35:14.034654: +2024-11-23 05:35:14.034875: Epoch 7859 +2024-11-23 05:35:14.034984: Current learning rate: 0.00026 +2024-11-23 05:35:33.484346: train_loss -0.8443 +2024-11-23 05:35:33.484567: val_loss -0.7644 +2024-11-23 05:35:33.484640: Pseudo dice [0.8409] +2024-11-23 05:35:33.484715: Epoch time: 19.45 s +2024-11-23 05:35:34.792376: +2024-11-23 05:35:34.792580: Epoch 7860 +2024-11-23 05:35:34.792688: Current learning rate: 0.00026 +2024-11-23 05:35:54.441557: train_loss -0.8493 +2024-11-23 05:35:54.447134: val_loss -0.7619 +2024-11-23 05:35:54.447297: Pseudo dice [0.8536] +2024-11-23 05:35:54.447392: Epoch time: 19.65 s +2024-11-23 05:35:55.476931: +2024-11-23 05:35:55.477192: Epoch 7861 +2024-11-23 05:35:55.477307: Current learning rate: 0.00026 +2024-11-23 05:36:12.755927: train_loss -0.8467 +2024-11-23 05:36:12.756176: val_loss -0.767 +2024-11-23 05:36:12.756247: Pseudo dice [0.8546] +2024-11-23 05:36:12.756324: Epoch time: 17.28 s +2024-11-23 05:36:13.921298: +2024-11-23 05:36:13.921508: Epoch 7862 +2024-11-23 05:36:13.921619: Current learning rate: 0.00026 +2024-11-23 05:36:32.182389: train_loss -0.8405 +2024-11-23 05:36:32.182616: val_loss -0.7754 +2024-11-23 05:36:32.182706: Pseudo dice [0.8371] +2024-11-23 05:36:32.182786: Epoch time: 18.26 s +2024-11-23 05:36:33.112408: +2024-11-23 05:36:33.112690: Epoch 7863 +2024-11-23 05:36:33.112810: Current learning rate: 0.00026 +2024-11-23 05:36:51.598084: train_loss -0.8441 +2024-11-23 05:36:51.598311: val_loss -0.7563 +2024-11-23 05:36:51.598386: Pseudo dice [0.8485] +2024-11-23 05:36:51.598463: Epoch time: 18.49 s +2024-11-23 05:36:52.530555: +2024-11-23 05:36:52.530781: Epoch 7864 +2024-11-23 05:36:52.530939: Current learning rate: 0.00026 +2024-11-23 05:37:11.294821: train_loss -0.8424 +2024-11-23 05:37:11.295129: val_loss -0.7455 +2024-11-23 05:37:11.295218: Pseudo dice [0.8541] +2024-11-23 05:37:11.295321: Epoch time: 18.77 s +2024-11-23 05:37:12.231220: +2024-11-23 05:37:12.231485: Epoch 7865 +2024-11-23 05:37:12.231599: Current learning rate: 0.00025 +2024-11-23 05:37:30.991286: train_loss -0.8415 +2024-11-23 05:37:30.991523: val_loss -0.7672 +2024-11-23 05:37:30.991600: Pseudo dice [0.8582] +2024-11-23 05:37:30.991676: Epoch time: 18.76 s +2024-11-23 05:37:30.991737: Yayy! New best EMA pseudo Dice: 0.8454 +2024-11-23 05:37:32.318822: +2024-11-23 05:37:32.319059: Epoch 7866 +2024-11-23 05:37:32.319171: Current learning rate: 0.00025 +2024-11-23 05:37:51.821802: train_loss -0.8419 +2024-11-23 05:37:51.822087: val_loss -0.7561 +2024-11-23 05:37:51.822169: Pseudo dice [0.8257] +2024-11-23 05:37:51.822248: Epoch time: 19.5 s +2024-11-23 05:37:52.751931: +2024-11-23 05:37:52.752134: Epoch 7867 +2024-11-23 05:37:52.752245: Current learning rate: 0.00025 +2024-11-23 05:38:11.964767: train_loss -0.8442 +2024-11-23 05:38:11.964983: val_loss -0.747 +2024-11-23 05:38:11.965068: Pseudo dice [0.8419] +2024-11-23 05:38:11.965145: Epoch time: 19.21 s +2024-11-23 05:38:12.897274: +2024-11-23 05:38:12.897487: Epoch 7868 +2024-11-23 05:38:12.898209: Current learning rate: 0.00025 +2024-11-23 05:38:31.060927: train_loss -0.845 +2024-11-23 05:38:31.061159: val_loss -0.7512 +2024-11-23 05:38:31.061236: Pseudo dice [0.8256] +2024-11-23 05:38:31.061317: Epoch time: 18.16 s +2024-11-23 05:38:32.003799: +2024-11-23 05:38:32.004007: Epoch 7869 +2024-11-23 05:38:32.004125: Current learning rate: 0.00025 +2024-11-23 05:38:49.551214: train_loss -0.8466 +2024-11-23 05:38:49.551460: val_loss -0.7692 +2024-11-23 05:38:49.551540: Pseudo dice [0.8628] +2024-11-23 05:38:49.551619: Epoch time: 17.55 s +2024-11-23 05:38:50.483038: +2024-11-23 05:38:50.483258: Epoch 7870 +2024-11-23 05:38:50.483377: Current learning rate: 0.00025 +2024-11-23 05:39:08.146880: train_loss -0.8454 +2024-11-23 05:39:08.147096: val_loss -0.7421 +2024-11-23 05:39:08.147171: Pseudo dice [0.831] +2024-11-23 05:39:08.147247: Epoch time: 17.66 s +2024-11-23 05:39:09.081846: +2024-11-23 05:39:09.082080: Epoch 7871 +2024-11-23 05:39:09.082195: Current learning rate: 0.00024 +2024-11-23 05:39:27.909326: train_loss -0.8378 +2024-11-23 05:39:27.909566: val_loss -0.759 +2024-11-23 05:39:27.909639: Pseudo dice [0.8361] +2024-11-23 05:39:27.909718: Epoch time: 18.83 s +2024-11-23 05:39:28.937125: +2024-11-23 05:39:28.937359: Epoch 7872 +2024-11-23 05:39:28.937472: Current learning rate: 0.00024 +2024-11-23 05:39:47.830204: train_loss -0.8326 +2024-11-23 05:39:47.830450: val_loss -0.7331 +2024-11-23 05:39:47.830525: Pseudo dice [0.8253] +2024-11-23 05:39:47.835208: Epoch time: 18.89 s +2024-11-23 05:39:48.940977: +2024-11-23 05:39:48.941236: Epoch 7873 +2024-11-23 05:39:48.941352: Current learning rate: 0.00024 +2024-11-23 05:40:07.590005: train_loss -0.8452 +2024-11-23 05:40:07.590240: val_loss -0.7739 +2024-11-23 05:40:07.590319: Pseudo dice [0.8371] +2024-11-23 05:40:07.590403: Epoch time: 18.65 s +2024-11-23 05:40:08.523353: +2024-11-23 05:40:08.523588: Epoch 7874 +2024-11-23 05:40:08.523698: Current learning rate: 0.00024 +2024-11-23 05:40:26.878930: train_loss -0.8418 +2024-11-23 05:40:26.879185: val_loss -0.7715 +2024-11-23 05:40:26.879262: Pseudo dice [0.8292] +2024-11-23 05:40:26.879349: Epoch time: 18.36 s +2024-11-23 05:40:27.808212: +2024-11-23 05:40:27.808439: Epoch 7875 +2024-11-23 05:40:27.808547: Current learning rate: 0.00024 +2024-11-23 05:40:45.961613: train_loss -0.848 +2024-11-23 05:40:45.961830: val_loss -0.7507 +2024-11-23 05:40:45.961904: Pseudo dice [0.8367] +2024-11-23 05:40:45.961980: Epoch time: 18.15 s +2024-11-23 05:40:46.901253: +2024-11-23 05:40:46.901471: Epoch 7876 +2024-11-23 05:40:46.901581: Current learning rate: 0.00024 +2024-11-23 05:41:06.625504: train_loss -0.8453 +2024-11-23 05:41:06.627903: val_loss -0.7618 +2024-11-23 05:41:06.628006: Pseudo dice [0.8271] +2024-11-23 05:41:06.628085: Epoch time: 19.73 s +2024-11-23 05:41:07.678079: +2024-11-23 05:41:07.678299: Epoch 7877 +2024-11-23 05:41:07.678409: Current learning rate: 0.00023 +2024-11-23 05:41:26.559012: train_loss -0.8463 +2024-11-23 05:41:26.559239: val_loss -0.7594 +2024-11-23 05:41:26.559314: Pseudo dice [0.8346] +2024-11-23 05:41:26.559390: Epoch time: 18.88 s +2024-11-23 05:41:27.575660: +2024-11-23 05:41:27.575872: Epoch 7878 +2024-11-23 05:41:27.575994: Current learning rate: 0.00023 +2024-11-23 05:41:45.868211: train_loss -0.8412 +2024-11-23 05:41:45.868481: val_loss -0.7439 +2024-11-23 05:41:45.868560: Pseudo dice [0.8169] +2024-11-23 05:41:45.868639: Epoch time: 18.29 s +2024-11-23 05:41:46.976108: +2024-11-23 05:41:46.976310: Epoch 7879 +2024-11-23 05:41:46.976418: Current learning rate: 0.00023 +2024-11-23 05:42:05.760523: train_loss -0.8404 +2024-11-23 05:42:05.760733: val_loss -0.7715 +2024-11-23 05:42:05.760808: Pseudo dice [0.8452] +2024-11-23 05:42:05.760882: Epoch time: 18.79 s +2024-11-23 05:42:06.701776: +2024-11-23 05:42:06.701977: Epoch 7880 +2024-11-23 05:42:06.702092: Current learning rate: 0.00023 +2024-11-23 05:42:24.910521: train_loss -0.8442 +2024-11-23 05:42:24.910758: val_loss -0.7624 +2024-11-23 05:42:24.910837: Pseudo dice [0.85] +2024-11-23 05:42:24.921442: Epoch time: 18.21 s +2024-11-23 05:42:25.871788: +2024-11-23 05:42:25.872015: Epoch 7881 +2024-11-23 05:42:25.872127: Current learning rate: 0.00023 +2024-11-23 05:42:43.348022: train_loss -0.8407 +2024-11-23 05:42:43.348231: val_loss -0.7556 +2024-11-23 05:42:43.348307: Pseudo dice [0.8455] +2024-11-23 05:42:43.348389: Epoch time: 17.48 s +2024-11-23 05:42:44.279334: +2024-11-23 05:42:44.279597: Epoch 7882 +2024-11-23 05:42:44.279711: Current learning rate: 0.00022 +2024-11-23 05:43:03.657628: train_loss -0.8399 +2024-11-23 05:43:03.657861: val_loss -0.7596 +2024-11-23 05:43:03.657942: Pseudo dice [0.8493] +2024-11-23 05:43:03.658031: Epoch time: 19.38 s +2024-11-23 05:43:04.589576: +2024-11-23 05:43:04.589769: Epoch 7883 +2024-11-23 05:43:04.589892: Current learning rate: 0.00022 +2024-11-23 05:43:23.498235: train_loss -0.8477 +2024-11-23 05:43:23.498469: val_loss -0.7858 +2024-11-23 05:43:23.498548: Pseudo dice [0.8385] +2024-11-23 05:43:23.498628: Epoch time: 18.91 s +2024-11-23 05:43:24.541378: +2024-11-23 05:43:24.541620: Epoch 7884 +2024-11-23 05:43:24.541743: Current learning rate: 0.00022 +2024-11-23 05:43:44.034191: train_loss -0.8344 +2024-11-23 05:43:44.034441: val_loss -0.7648 +2024-11-23 05:43:44.034518: Pseudo dice [0.8447] +2024-11-23 05:43:44.034607: Epoch time: 19.49 s +2024-11-23 05:43:44.973431: +2024-11-23 05:43:44.973647: Epoch 7885 +2024-11-23 05:43:44.973760: Current learning rate: 0.00022 +2024-11-23 05:44:03.869551: train_loss -0.8404 +2024-11-23 05:44:03.869776: val_loss -0.7654 +2024-11-23 05:44:03.875066: Pseudo dice [0.8344] +2024-11-23 05:44:03.875190: Epoch time: 18.9 s +2024-11-23 05:44:05.025125: +2024-11-23 05:44:05.025328: Epoch 7886 +2024-11-23 05:44:05.025581: Current learning rate: 0.00022 +2024-11-23 05:44:24.659425: train_loss -0.8431 +2024-11-23 05:44:24.661821: val_loss -0.7479 +2024-11-23 05:44:24.661917: Pseudo dice [0.8316] +2024-11-23 05:44:24.662004: Epoch time: 19.64 s +2024-11-23 05:44:25.651203: +2024-11-23 05:44:25.651408: Epoch 7887 +2024-11-23 05:44:25.651519: Current learning rate: 0.00022 +2024-11-23 05:44:45.077674: train_loss -0.843 +2024-11-23 05:44:45.077899: val_loss -0.769 +2024-11-23 05:44:45.077974: Pseudo dice [0.8475] +2024-11-23 05:44:45.078055: Epoch time: 19.43 s +2024-11-23 05:44:46.111659: +2024-11-23 05:44:46.111896: Epoch 7888 +2024-11-23 05:44:46.112017: Current learning rate: 0.00021 +2024-11-23 05:45:05.286491: train_loss -0.8478 +2024-11-23 05:45:05.286732: val_loss -0.7883 +2024-11-23 05:45:05.286805: Pseudo dice [0.854] +2024-11-23 05:45:05.286894: Epoch time: 19.18 s +2024-11-23 05:45:06.196794: +2024-11-23 05:45:06.197021: Epoch 7889 +2024-11-23 05:45:06.197138: Current learning rate: 0.00021 +2024-11-23 05:45:24.177913: train_loss -0.8487 +2024-11-23 05:45:24.178187: val_loss -0.7706 +2024-11-23 05:45:24.178261: Pseudo dice [0.8561] +2024-11-23 05:45:24.178340: Epoch time: 17.98 s +2024-11-23 05:45:25.108524: +2024-11-23 05:45:25.108727: Epoch 7890 +2024-11-23 05:45:25.108834: Current learning rate: 0.00021 +2024-11-23 05:45:43.006948: train_loss -0.8404 +2024-11-23 05:45:43.007167: val_loss -0.7908 +2024-11-23 05:45:43.007248: Pseudo dice [0.8384] +2024-11-23 05:45:43.007325: Epoch time: 17.9 s +2024-11-23 05:45:43.934278: +2024-11-23 05:45:43.934493: Epoch 7891 +2024-11-23 05:45:43.934604: Current learning rate: 0.00021 +2024-11-23 05:46:02.705513: train_loss -0.8416 +2024-11-23 05:46:02.705729: val_loss -0.7872 +2024-11-23 05:46:02.705803: Pseudo dice [0.8392] +2024-11-23 05:46:02.705876: Epoch time: 18.77 s +2024-11-23 05:46:03.645934: +2024-11-23 05:46:03.646157: Epoch 7892 +2024-11-23 05:46:03.646265: Current learning rate: 0.00021 +2024-11-23 05:46:22.324379: train_loss -0.8494 +2024-11-23 05:46:22.324602: val_loss -0.7586 +2024-11-23 05:46:22.324679: Pseudo dice [0.8367] +2024-11-23 05:46:22.324766: Epoch time: 18.68 s +2024-11-23 05:46:23.396705: +2024-11-23 05:46:23.396992: Epoch 7893 +2024-11-23 05:46:23.397110: Current learning rate: 0.00021 +2024-11-23 05:46:42.336762: train_loss -0.8438 +2024-11-23 05:46:42.369127: val_loss -0.7266 +2024-11-23 05:46:42.369309: Pseudo dice [0.809] +2024-11-23 05:46:42.369402: Epoch time: 18.94 s +2024-11-23 05:46:43.299353: +2024-11-23 05:46:43.299577: Epoch 7894 +2024-11-23 05:46:43.299690: Current learning rate: 0.0002 +2024-11-23 05:47:02.313147: train_loss -0.8458 +2024-11-23 05:47:02.322827: val_loss -0.76 +2024-11-23 05:47:02.322976: Pseudo dice [0.8331] +2024-11-23 05:47:02.323066: Epoch time: 19.01 s +2024-11-23 05:47:03.301602: +2024-11-23 05:47:03.301857: Epoch 7895 +2024-11-23 05:47:03.301972: Current learning rate: 0.0002 +2024-11-23 05:47:22.310257: train_loss -0.8436 +2024-11-23 05:47:22.311193: val_loss -0.7395 +2024-11-23 05:47:22.311287: Pseudo dice [0.8376] +2024-11-23 05:47:22.311378: Epoch time: 19.01 s +2024-11-23 05:47:23.284172: +2024-11-23 05:47:23.284379: Epoch 7896 +2024-11-23 05:47:23.284495: Current learning rate: 0.0002 +2024-11-23 05:47:41.916227: train_loss -0.8454 +2024-11-23 05:47:41.916430: val_loss -0.7613 +2024-11-23 05:47:41.916504: Pseudo dice [0.8308] +2024-11-23 05:47:41.916578: Epoch time: 18.63 s +2024-11-23 05:47:42.875285: +2024-11-23 05:47:42.875499: Epoch 7897 +2024-11-23 05:47:42.875611: Current learning rate: 0.0002 +2024-11-23 05:48:00.779375: train_loss -0.8485 +2024-11-23 05:48:00.779599: val_loss -0.7426 +2024-11-23 05:48:00.779677: Pseudo dice [0.8315] +2024-11-23 05:48:00.779752: Epoch time: 17.9 s +2024-11-23 05:48:01.708447: +2024-11-23 05:48:01.708654: Epoch 7898 +2024-11-23 05:48:01.708768: Current learning rate: 0.0002 +2024-11-23 05:48:20.829172: train_loss -0.843 +2024-11-23 05:48:20.829394: val_loss -0.7625 +2024-11-23 05:48:20.829468: Pseudo dice [0.835] +2024-11-23 05:48:20.829544: Epoch time: 19.12 s +2024-11-23 05:48:21.762186: +2024-11-23 05:48:21.762367: Epoch 7899 +2024-11-23 05:48:21.762481: Current learning rate: 0.0002 +2024-11-23 05:48:39.981019: train_loss -0.8452 +2024-11-23 05:48:39.987196: val_loss -0.7366 +2024-11-23 05:48:39.987337: Pseudo dice [0.85] +2024-11-23 05:48:39.987436: Epoch time: 18.22 s +2024-11-23 05:48:41.555030: +2024-11-23 05:48:41.555227: Epoch 7900 +2024-11-23 05:48:41.555337: Current learning rate: 0.00019 +2024-11-23 05:49:00.268171: train_loss -0.8417 +2024-11-23 05:49:00.268808: val_loss -0.7865 +2024-11-23 05:49:00.268885: Pseudo dice [0.8513] +2024-11-23 05:49:00.268960: Epoch time: 18.71 s +2024-11-23 05:49:01.198087: +2024-11-23 05:49:01.198307: Epoch 7901 +2024-11-23 05:49:01.198431: Current learning rate: 0.00019 +2024-11-23 05:49:19.385091: train_loss -0.8494 +2024-11-23 05:49:19.386496: val_loss -0.7686 +2024-11-23 05:49:19.386588: Pseudo dice [0.845] +2024-11-23 05:49:19.386667: Epoch time: 18.19 s +2024-11-23 05:49:20.468757: +2024-11-23 05:49:20.468954: Epoch 7902 +2024-11-23 05:49:20.469068: Current learning rate: 0.00019 +2024-11-23 05:49:38.670491: train_loss -0.8464 +2024-11-23 05:49:38.670701: val_loss -0.7434 +2024-11-23 05:49:38.670780: Pseudo dice [0.8565] +2024-11-23 05:49:38.670860: Epoch time: 18.2 s +2024-11-23 05:49:39.716698: +2024-11-23 05:49:39.716887: Epoch 7903 +2024-11-23 05:49:39.717004: Current learning rate: 0.00019 +2024-11-23 05:49:57.433300: train_loss -0.8481 +2024-11-23 05:49:57.433520: val_loss -0.7648 +2024-11-23 05:49:57.433595: Pseudo dice [0.8543] +2024-11-23 05:49:57.433712: Epoch time: 17.72 s +2024-11-23 05:49:58.736830: +2024-11-23 05:49:58.737069: Epoch 7904 +2024-11-23 05:49:58.737178: Current learning rate: 0.00019 +2024-11-23 05:50:16.808725: train_loss -0.8439 +2024-11-23 05:50:16.808927: val_loss -0.7566 +2024-11-23 05:50:16.809008: Pseudo dice [0.8159] +2024-11-23 05:50:16.809085: Epoch time: 18.07 s +2024-11-23 05:50:17.745502: +2024-11-23 05:50:17.745741: Epoch 7905 +2024-11-23 05:50:17.745846: Current learning rate: 0.00018 +2024-11-23 05:50:35.948271: train_loss -0.8467 +2024-11-23 05:50:35.948478: val_loss -0.7847 +2024-11-23 05:50:35.948549: Pseudo dice [0.8541] +2024-11-23 05:50:35.948625: Epoch time: 18.2 s +2024-11-23 05:50:36.885963: +2024-11-23 05:50:36.886178: Epoch 7906 +2024-11-23 05:50:36.886288: Current learning rate: 0.00018 +2024-11-23 05:50:55.559827: train_loss -0.8424 +2024-11-23 05:50:55.560090: val_loss -0.7441 +2024-11-23 05:50:55.560166: Pseudo dice [0.8452] +2024-11-23 05:50:55.560249: Epoch time: 18.67 s +2024-11-23 05:50:56.619918: +2024-11-23 05:50:56.620127: Epoch 7907 +2024-11-23 05:50:56.620239: Current learning rate: 0.00018 +2024-11-23 05:51:15.625896: train_loss -0.8405 +2024-11-23 05:51:15.626113: val_loss -0.777 +2024-11-23 05:51:15.628374: Pseudo dice [0.854] +2024-11-23 05:51:15.628504: Epoch time: 19.01 s +2024-11-23 05:51:16.764534: +2024-11-23 05:51:16.764741: Epoch 7908 +2024-11-23 05:51:16.764851: Current learning rate: 0.00018 +2024-11-23 05:51:36.087853: train_loss -0.8454 +2024-11-23 05:51:36.088109: val_loss -0.7557 +2024-11-23 05:51:36.088186: Pseudo dice [0.8419] +2024-11-23 05:51:36.088263: Epoch time: 19.32 s +2024-11-23 05:51:37.024692: +2024-11-23 05:51:37.024885: Epoch 7909 +2024-11-23 05:51:37.024997: Current learning rate: 0.00018 +2024-11-23 05:51:55.709764: train_loss -0.846 +2024-11-23 05:51:55.709979: val_loss -0.7547 +2024-11-23 05:51:55.710061: Pseudo dice [0.8299] +2024-11-23 05:51:55.710143: Epoch time: 18.69 s +2024-11-23 05:51:56.710016: +2024-11-23 05:51:56.710273: Epoch 7910 +2024-11-23 05:51:56.710397: Current learning rate: 0.00018 +2024-11-23 05:52:15.387725: train_loss -0.8446 +2024-11-23 05:52:15.387962: val_loss -0.768 +2024-11-23 05:52:15.388042: Pseudo dice [0.843] +2024-11-23 05:52:15.388121: Epoch time: 18.68 s +2024-11-23 05:52:16.320681: +2024-11-23 05:52:16.320914: Epoch 7911 +2024-11-23 05:52:16.321038: Current learning rate: 0.00017 +2024-11-23 05:52:34.565827: train_loss -0.8434 +2024-11-23 05:52:34.566049: val_loss -0.7594 +2024-11-23 05:52:34.566127: Pseudo dice [0.839] +2024-11-23 05:52:34.566204: Epoch time: 18.25 s +2024-11-23 05:52:35.503411: +2024-11-23 05:52:35.503638: Epoch 7912 +2024-11-23 05:52:35.503870: Current learning rate: 0.00017 +2024-11-23 05:52:52.234550: train_loss -0.8486 +2024-11-23 05:52:52.234762: val_loss -0.7827 +2024-11-23 05:52:52.234841: Pseudo dice [0.8435] +2024-11-23 05:52:52.234917: Epoch time: 16.73 s +2024-11-23 05:52:53.162979: +2024-11-23 05:52:53.163205: Epoch 7913 +2024-11-23 05:52:53.163317: Current learning rate: 0.00017 +2024-11-23 05:53:11.296339: train_loss -0.8487 +2024-11-23 05:53:11.296565: val_loss -0.7752 +2024-11-23 05:53:11.296638: Pseudo dice [0.8264] +2024-11-23 05:53:11.296716: Epoch time: 18.13 s +2024-11-23 05:53:12.348509: +2024-11-23 05:53:12.348714: Epoch 7914 +2024-11-23 05:53:12.348829: Current learning rate: 0.00017 +2024-11-23 05:53:30.890584: train_loss -0.8446 +2024-11-23 05:53:30.890806: val_loss -0.762 +2024-11-23 05:53:30.890883: Pseudo dice [0.8379] +2024-11-23 05:53:30.890958: Epoch time: 18.54 s +2024-11-23 05:53:31.821834: +2024-11-23 05:53:31.822244: Epoch 7915 +2024-11-23 05:53:31.822381: Current learning rate: 0.00017 +2024-11-23 05:53:49.851942: train_loss -0.8437 +2024-11-23 05:53:49.852169: val_loss -0.7547 +2024-11-23 05:53:49.852243: Pseudo dice [0.8291] +2024-11-23 05:53:49.852319: Epoch time: 18.03 s +2024-11-23 05:53:51.228918: +2024-11-23 05:53:51.229149: Epoch 7916 +2024-11-23 05:53:51.229269: Current learning rate: 0.00017 +2024-11-23 05:54:09.730102: train_loss -0.8466 +2024-11-23 05:54:09.730341: val_loss -0.7628 +2024-11-23 05:54:09.730416: Pseudo dice [0.8352] +2024-11-23 05:54:09.730498: Epoch time: 18.5 s +2024-11-23 05:54:10.663866: +2024-11-23 05:54:10.664068: Epoch 7917 +2024-11-23 05:54:10.664181: Current learning rate: 0.00016 +2024-11-23 05:54:29.827364: train_loss -0.8463 +2024-11-23 05:54:29.827590: val_loss -0.7711 +2024-11-23 05:54:29.827668: Pseudo dice [0.8315] +2024-11-23 05:54:29.827745: Epoch time: 19.16 s +2024-11-23 05:54:30.759037: +2024-11-23 05:54:30.759274: Epoch 7918 +2024-11-23 05:54:30.759386: Current learning rate: 0.00016 +2024-11-23 05:54:48.623915: train_loss -0.8473 +2024-11-23 05:54:48.624187: val_loss -0.768 +2024-11-23 05:54:48.624266: Pseudo dice [0.8399] +2024-11-23 05:54:48.624341: Epoch time: 17.87 s +2024-11-23 05:54:49.575515: +2024-11-23 05:54:49.575731: Epoch 7919 +2024-11-23 05:54:49.575847: Current learning rate: 0.00016 +2024-11-23 05:55:07.411720: train_loss -0.8455 +2024-11-23 05:55:07.411931: val_loss -0.749 +2024-11-23 05:55:07.412013: Pseudo dice [0.8505] +2024-11-23 05:55:07.412091: Epoch time: 17.84 s +2024-11-23 05:55:08.341722: +2024-11-23 05:55:08.341926: Epoch 7920 +2024-11-23 05:55:08.342046: Current learning rate: 0.00016 +2024-11-23 05:55:26.497430: train_loss -0.8488 +2024-11-23 05:55:26.497671: val_loss -0.7457 +2024-11-23 05:55:26.497747: Pseudo dice [0.8301] +2024-11-23 05:55:26.497829: Epoch time: 18.16 s +2024-11-23 05:55:27.435827: +2024-11-23 05:55:27.436062: Epoch 7921 +2024-11-23 05:55:27.436171: Current learning rate: 0.00016 +2024-11-23 05:55:46.810132: train_loss -0.8475 +2024-11-23 05:55:46.810350: val_loss -0.7644 +2024-11-23 05:55:46.810424: Pseudo dice [0.8293] +2024-11-23 05:55:46.810498: Epoch time: 19.38 s +2024-11-23 05:55:47.811656: +2024-11-23 05:55:47.811901: Epoch 7922 +2024-11-23 05:55:47.812017: Current learning rate: 0.00015 +2024-11-23 05:56:07.105521: train_loss -0.8386 +2024-11-23 05:56:07.105762: val_loss -0.7554 +2024-11-23 05:56:07.105852: Pseudo dice [0.838] +2024-11-23 05:56:07.105979: Epoch time: 19.29 s +2024-11-23 05:56:08.041457: +2024-11-23 05:56:08.041666: Epoch 7923 +2024-11-23 05:56:08.041775: Current learning rate: 0.00015 +2024-11-23 05:56:27.380528: train_loss -0.8402 +2024-11-23 05:56:27.380735: val_loss -0.7731 +2024-11-23 05:56:27.380811: Pseudo dice [0.8519] +2024-11-23 05:56:27.380891: Epoch time: 19.34 s +2024-11-23 05:56:28.315589: +2024-11-23 05:56:28.315822: Epoch 7924 +2024-11-23 05:56:28.315933: Current learning rate: 0.00015 +2024-11-23 05:56:45.905542: train_loss -0.8395 +2024-11-23 05:56:45.905771: val_loss -0.7758 +2024-11-23 05:56:45.905844: Pseudo dice [0.8474] +2024-11-23 05:56:45.905923: Epoch time: 17.59 s +2024-11-23 05:56:46.844351: +2024-11-23 05:56:46.844545: Epoch 7925 +2024-11-23 05:56:46.844657: Current learning rate: 0.00015 +2024-11-23 05:57:04.587677: train_loss -0.8467 +2024-11-23 05:57:04.593115: val_loss -0.7552 +2024-11-23 05:57:04.593282: Pseudo dice [0.8442] +2024-11-23 05:57:04.593366: Epoch time: 17.74 s +2024-11-23 05:57:05.708349: +2024-11-23 05:57:05.708563: Epoch 7926 +2024-11-23 05:57:05.708676: Current learning rate: 0.00015 +2024-11-23 05:57:24.372011: train_loss -0.845 +2024-11-23 05:57:24.372226: val_loss -0.769 +2024-11-23 05:57:24.372303: Pseudo dice [0.8489] +2024-11-23 05:57:24.372383: Epoch time: 18.66 s +2024-11-23 05:57:25.746204: +2024-11-23 05:57:25.746413: Epoch 7927 +2024-11-23 05:57:25.746527: Current learning rate: 0.00015 +2024-11-23 05:57:45.437395: train_loss -0.8476 +2024-11-23 05:57:45.437639: val_loss -0.7484 +2024-11-23 05:57:45.437727: Pseudo dice [0.829] +2024-11-23 05:57:45.437816: Epoch time: 19.69 s +2024-11-23 05:57:46.371424: +2024-11-23 05:57:46.371636: Epoch 7928 +2024-11-23 05:57:46.371748: Current learning rate: 0.00014 +2024-11-23 05:58:04.304446: train_loss -0.8538 +2024-11-23 05:58:04.304662: val_loss -0.7733 +2024-11-23 05:58:04.304736: Pseudo dice [0.8454] +2024-11-23 05:58:04.304812: Epoch time: 17.93 s +2024-11-23 05:58:05.240297: +2024-11-23 05:58:05.240517: Epoch 7929 +2024-11-23 05:58:05.240630: Current learning rate: 0.00014 +2024-11-23 05:58:22.132063: train_loss -0.8493 +2024-11-23 05:58:22.132280: val_loss -0.7524 +2024-11-23 05:58:22.132356: Pseudo dice [0.8373] +2024-11-23 05:58:22.132434: Epoch time: 16.89 s +2024-11-23 05:58:23.202615: +2024-11-23 05:58:23.202857: Epoch 7930 +2024-11-23 05:58:23.202972: Current learning rate: 0.00014 +2024-11-23 05:58:40.769549: train_loss -0.8437 +2024-11-23 05:58:40.769761: val_loss -0.7645 +2024-11-23 05:58:40.769836: Pseudo dice [0.8184] +2024-11-23 05:58:40.769916: Epoch time: 17.57 s +2024-11-23 05:58:41.708800: +2024-11-23 05:58:41.709032: Epoch 7931 +2024-11-23 05:58:41.709153: Current learning rate: 0.00014 +2024-11-23 05:58:59.552499: train_loss -0.8486 +2024-11-23 05:58:59.552746: val_loss -0.7567 +2024-11-23 05:58:59.573653: Pseudo dice [0.8545] +2024-11-23 05:58:59.573810: Epoch time: 17.84 s +2024-11-23 05:59:00.644343: +2024-11-23 05:59:00.644620: Epoch 7932 +2024-11-23 05:59:00.644736: Current learning rate: 0.00014 +2024-11-23 05:59:19.665811: train_loss -0.8375 +2024-11-23 05:59:19.666136: val_loss -0.7689 +2024-11-23 05:59:19.666218: Pseudo dice [0.8426] +2024-11-23 05:59:19.666302: Epoch time: 19.02 s +2024-11-23 05:59:20.599446: +2024-11-23 05:59:20.599670: Epoch 7933 +2024-11-23 05:59:20.599786: Current learning rate: 0.00014 +2024-11-23 05:59:39.795182: train_loss -0.8475 +2024-11-23 05:59:39.795399: val_loss -0.7436 +2024-11-23 05:59:39.795472: Pseudo dice [0.8372] +2024-11-23 05:59:39.795548: Epoch time: 19.2 s +2024-11-23 05:59:40.912698: +2024-11-23 05:59:40.912903: Epoch 7934 +2024-11-23 05:59:40.913016: Current learning rate: 0.00013 +2024-11-23 05:59:59.169360: train_loss -0.84 +2024-11-23 05:59:59.169592: val_loss -0.7513 +2024-11-23 05:59:59.169669: Pseudo dice [0.8241] +2024-11-23 05:59:59.169789: Epoch time: 18.26 s +2024-11-23 06:00:00.106722: +2024-11-23 06:00:00.106910: Epoch 7935 +2024-11-23 06:00:00.107031: Current learning rate: 0.00013 +2024-11-23 06:00:18.864179: train_loss -0.8423 +2024-11-23 06:00:18.864394: val_loss -0.7709 +2024-11-23 06:00:18.864466: Pseudo dice [0.8614] +2024-11-23 06:00:18.864542: Epoch time: 18.76 s +2024-11-23 06:00:19.960975: +2024-11-23 06:00:19.961222: Epoch 7936 +2024-11-23 06:00:19.961333: Current learning rate: 0.00013 +2024-11-23 06:00:38.088660: train_loss -0.8483 +2024-11-23 06:00:38.088882: val_loss -0.75 +2024-11-23 06:00:38.088958: Pseudo dice [0.856] +2024-11-23 06:00:38.089041: Epoch time: 18.13 s +2024-11-23 06:00:39.023937: +2024-11-23 06:00:39.024167: Epoch 7937 +2024-11-23 06:00:39.024282: Current learning rate: 0.00013 +2024-11-23 06:00:56.998501: train_loss -0.846 +2024-11-23 06:00:56.998732: val_loss -0.772 +2024-11-23 06:00:56.998808: Pseudo dice [0.8436] +2024-11-23 06:00:56.998883: Epoch time: 17.98 s +2024-11-23 06:00:57.933808: +2024-11-23 06:00:57.934539: Epoch 7938 +2024-11-23 06:00:57.934691: Current learning rate: 0.00013 +2024-11-23 06:01:17.737331: train_loss -0.8463 +2024-11-23 06:01:17.737566: val_loss -0.7786 +2024-11-23 06:01:17.740285: Pseudo dice [0.8326] +2024-11-23 06:01:17.740440: Epoch time: 19.8 s +2024-11-23 06:01:19.086601: +2024-11-23 06:01:19.086812: Epoch 7939 +2024-11-23 06:01:19.086926: Current learning rate: 0.00012 +2024-11-23 06:01:36.674203: train_loss -0.846 +2024-11-23 06:01:36.674410: val_loss -0.7815 +2024-11-23 06:01:36.674486: Pseudo dice [0.852] +2024-11-23 06:01:36.674562: Epoch time: 17.59 s +2024-11-23 06:01:37.601944: +2024-11-23 06:01:37.602210: Epoch 7940 +2024-11-23 06:01:37.602325: Current learning rate: 0.00012 +2024-11-23 06:01:57.188863: train_loss -0.8463 +2024-11-23 06:01:57.189146: val_loss -0.7751 +2024-11-23 06:01:57.189227: Pseudo dice [0.8419] +2024-11-23 06:01:57.189305: Epoch time: 19.59 s +2024-11-23 06:01:58.129642: +2024-11-23 06:01:58.129861: Epoch 7941 +2024-11-23 06:01:58.129976: Current learning rate: 0.00012 +2024-11-23 06:02:17.134405: train_loss -0.84 +2024-11-23 06:02:17.134644: val_loss -0.7704 +2024-11-23 06:02:17.134722: Pseudo dice [0.8485] +2024-11-23 06:02:17.134811: Epoch time: 19.01 s +2024-11-23 06:02:18.071430: +2024-11-23 06:02:18.071725: Epoch 7942 +2024-11-23 06:02:18.071836: Current learning rate: 0.00012 +2024-11-23 06:02:36.331048: train_loss -0.845 +2024-11-23 06:02:36.331259: val_loss -0.7875 +2024-11-23 06:02:36.331332: Pseudo dice [0.8347] +2024-11-23 06:02:36.331406: Epoch time: 18.26 s +2024-11-23 06:02:37.266800: +2024-11-23 06:02:37.267015: Epoch 7943 +2024-11-23 06:02:37.267133: Current learning rate: 0.00012 +2024-11-23 06:02:56.084596: train_loss -0.8427 +2024-11-23 06:02:56.084814: val_loss -0.7691 +2024-11-23 06:02:56.084890: Pseudo dice [0.8452] +2024-11-23 06:02:56.084967: Epoch time: 18.82 s +2024-11-23 06:02:57.023000: +2024-11-23 06:02:57.023247: Epoch 7944 +2024-11-23 06:02:57.023360: Current learning rate: 0.00011 +2024-11-23 06:03:15.748480: train_loss -0.8415 +2024-11-23 06:03:15.748695: val_loss -0.7615 +2024-11-23 06:03:15.748771: Pseudo dice [0.8378] +2024-11-23 06:03:15.748851: Epoch time: 18.73 s +2024-11-23 06:03:16.686750: +2024-11-23 06:03:16.686955: Epoch 7945 +2024-11-23 06:03:16.687069: Current learning rate: 0.00011 +2024-11-23 06:03:33.750152: train_loss -0.8486 +2024-11-23 06:03:33.750379: val_loss -0.7467 +2024-11-23 06:03:33.750454: Pseudo dice [0.8376] +2024-11-23 06:03:33.750539: Epoch time: 17.06 s +2024-11-23 06:03:34.687614: +2024-11-23 06:03:34.687854: Epoch 7946 +2024-11-23 06:03:34.687970: Current learning rate: 0.00011 +2024-11-23 06:03:53.449411: train_loss -0.8427 +2024-11-23 06:03:53.449622: val_loss -0.7591 +2024-11-23 06:03:53.449697: Pseudo dice [0.8286] +2024-11-23 06:03:53.449772: Epoch time: 18.76 s +2024-11-23 06:03:54.557676: +2024-11-23 06:03:54.557892: Epoch 7947 +2024-11-23 06:03:54.558011: Current learning rate: 0.00011 +2024-11-23 06:04:12.991678: train_loss -0.8478 +2024-11-23 06:04:12.991899: val_loss -0.7632 +2024-11-23 06:04:12.991975: Pseudo dice [0.8496] +2024-11-23 06:04:12.992059: Epoch time: 18.43 s +2024-11-23 06:04:14.031078: +2024-11-23 06:04:14.031294: Epoch 7948 +2024-11-23 06:04:14.031407: Current learning rate: 0.00011 +2024-11-23 06:04:31.311536: train_loss -0.8473 +2024-11-23 06:04:31.311781: val_loss -0.7489 +2024-11-23 06:04:31.311854: Pseudo dice [0.8319] +2024-11-23 06:04:31.311939: Epoch time: 17.28 s +2024-11-23 06:04:32.246727: +2024-11-23 06:04:32.246932: Epoch 7949 +2024-11-23 06:04:32.247059: Current learning rate: 0.00011 +2024-11-23 06:04:50.617517: train_loss -0.8396 +2024-11-23 06:04:50.617726: val_loss -0.7568 +2024-11-23 06:04:50.617803: Pseudo dice [0.839] +2024-11-23 06:04:50.620040: Epoch time: 18.37 s +2024-11-23 06:04:52.328845: +2024-11-23 06:04:52.329052: Epoch 7950 +2024-11-23 06:04:52.329162: Current learning rate: 0.0001 +2024-11-23 06:05:10.635529: train_loss -0.8487 +2024-11-23 06:05:10.635765: val_loss -0.7718 +2024-11-23 06:05:10.635842: Pseudo dice [0.8609] +2024-11-23 06:05:10.635917: Epoch time: 18.31 s +2024-11-23 06:05:11.571867: +2024-11-23 06:05:11.572111: Epoch 7951 +2024-11-23 06:05:11.572222: Current learning rate: 0.0001 +2024-11-23 06:05:30.368530: train_loss -0.8477 +2024-11-23 06:05:30.368761: val_loss -0.7626 +2024-11-23 06:05:30.368837: Pseudo dice [0.8458] +2024-11-23 06:05:30.368915: Epoch time: 18.8 s +2024-11-23 06:05:31.326266: +2024-11-23 06:05:31.326512: Epoch 7952 +2024-11-23 06:05:31.326627: Current learning rate: 0.0001 +2024-11-23 06:05:48.252668: train_loss -0.8517 +2024-11-23 06:05:48.252907: val_loss -0.7657 +2024-11-23 06:05:48.252980: Pseudo dice [0.8406] +2024-11-23 06:05:48.253071: Epoch time: 16.93 s +2024-11-23 06:05:49.188901: +2024-11-23 06:05:49.189128: Epoch 7953 +2024-11-23 06:05:49.189241: Current learning rate: 0.0001 +2024-11-23 06:06:07.577816: train_loss -0.8452 +2024-11-23 06:06:07.578045: val_loss -0.7652 +2024-11-23 06:06:07.578129: Pseudo dice [0.8364] +2024-11-23 06:06:07.578206: Epoch time: 18.39 s +2024-11-23 06:06:08.623355: +2024-11-23 06:06:08.623579: Epoch 7954 +2024-11-23 06:06:08.623693: Current learning rate: 0.0001 +2024-11-23 06:06:27.812960: train_loss -0.847 +2024-11-23 06:06:27.813191: val_loss -0.7681 +2024-11-23 06:06:27.813264: Pseudo dice [0.8381] +2024-11-23 06:06:27.813338: Epoch time: 19.19 s +2024-11-23 06:06:28.742919: +2024-11-23 06:06:28.743149: Epoch 7955 +2024-11-23 06:06:28.743289: Current learning rate: 9e-05 +2024-11-23 06:06:47.128638: train_loss -0.8469 +2024-11-23 06:06:47.128877: val_loss -0.7586 +2024-11-23 06:06:47.128952: Pseudo dice [0.8412] +2024-11-23 06:06:47.129045: Epoch time: 18.39 s +2024-11-23 06:06:48.065765: +2024-11-23 06:06:48.065985: Epoch 7956 +2024-11-23 06:06:48.066100: Current learning rate: 9e-05 +2024-11-23 06:07:06.373803: train_loss -0.8448 +2024-11-23 06:07:06.374021: val_loss -0.775 +2024-11-23 06:07:06.374096: Pseudo dice [0.8468] +2024-11-23 06:07:06.374172: Epoch time: 18.31 s +2024-11-23 06:07:07.306230: +2024-11-23 06:07:07.306576: Epoch 7957 +2024-11-23 06:07:07.321438: Current learning rate: 9e-05 +2024-11-23 06:07:26.701746: train_loss -0.8444 +2024-11-23 06:07:26.701965: val_loss -0.7482 +2024-11-23 06:07:26.702049: Pseudo dice [0.8245] +2024-11-23 06:07:26.702126: Epoch time: 19.4 s +2024-11-23 06:07:27.634449: +2024-11-23 06:07:27.634661: Epoch 7958 +2024-11-23 06:07:27.634780: Current learning rate: 9e-05 +2024-11-23 06:07:46.002245: train_loss -0.8402 +2024-11-23 06:07:46.002455: val_loss -0.7909 +2024-11-23 06:07:46.002534: Pseudo dice [0.8526] +2024-11-23 06:07:46.002612: Epoch time: 18.37 s +2024-11-23 06:07:46.938172: +2024-11-23 06:07:46.938374: Epoch 7959 +2024-11-23 06:07:46.938487: Current learning rate: 9e-05 +2024-11-23 06:08:05.088324: train_loss -0.8496 +2024-11-23 06:08:05.088562: val_loss -0.7817 +2024-11-23 06:08:05.088638: Pseudo dice [0.8619] +2024-11-23 06:08:05.088727: Epoch time: 18.15 s +2024-11-23 06:08:06.020195: +2024-11-23 06:08:06.020425: Epoch 7960 +2024-11-23 06:08:06.020537: Current learning rate: 8e-05 +2024-11-23 06:08:24.530325: train_loss -0.8468 +2024-11-23 06:08:24.530539: val_loss -0.7565 +2024-11-23 06:08:24.530612: Pseudo dice [0.842] +2024-11-23 06:08:24.530710: Epoch time: 18.51 s +2024-11-23 06:08:25.867805: +2024-11-23 06:08:25.868031: Epoch 7961 +2024-11-23 06:08:25.868146: Current learning rate: 8e-05 +2024-11-23 06:08:44.509909: train_loss -0.8474 +2024-11-23 06:08:44.510135: val_loss -0.769 +2024-11-23 06:08:44.510209: Pseudo dice [0.8286] +2024-11-23 06:08:44.510284: Epoch time: 18.64 s +2024-11-23 06:08:45.439852: +2024-11-23 06:08:45.440068: Epoch 7962 +2024-11-23 06:08:45.440184: Current learning rate: 8e-05 +2024-11-23 06:09:03.672201: train_loss -0.8442 +2024-11-23 06:09:03.672440: val_loss -0.7735 +2024-11-23 06:09:03.672514: Pseudo dice [0.8435] +2024-11-23 06:09:03.672601: Epoch time: 18.23 s +2024-11-23 06:09:04.671310: +2024-11-23 06:09:04.671523: Epoch 7963 +2024-11-23 06:09:04.671635: Current learning rate: 8e-05 +2024-11-23 06:09:24.106869: train_loss -0.8412 +2024-11-23 06:09:24.107095: val_loss -0.7643 +2024-11-23 06:09:24.107168: Pseudo dice [0.8416] +2024-11-23 06:09:24.107244: Epoch time: 19.44 s +2024-11-23 06:09:25.165423: +2024-11-23 06:09:25.165778: Epoch 7964 +2024-11-23 06:09:25.165902: Current learning rate: 8e-05 +2024-11-23 06:09:43.637263: train_loss -0.8467 +2024-11-23 06:09:43.642408: val_loss -0.7419 +2024-11-23 06:09:43.642512: Pseudo dice [0.8243] +2024-11-23 06:09:43.642592: Epoch time: 18.47 s +2024-11-23 06:09:44.612313: +2024-11-23 06:09:44.612551: Epoch 7965 +2024-11-23 06:09:44.612665: Current learning rate: 8e-05 +2024-11-23 06:10:02.858690: train_loss -0.8401 +2024-11-23 06:10:02.858906: val_loss -0.7236 +2024-11-23 06:10:02.858986: Pseudo dice [0.8322] +2024-11-23 06:10:02.859073: Epoch time: 18.25 s +2024-11-23 06:10:03.796715: +2024-11-23 06:10:03.796935: Epoch 7966 +2024-11-23 06:10:03.797046: Current learning rate: 7e-05 +2024-11-23 06:10:22.828803: train_loss -0.8502 +2024-11-23 06:10:22.829028: val_loss -0.7815 +2024-11-23 06:10:22.829104: Pseudo dice [0.8486] +2024-11-23 06:10:22.829184: Epoch time: 19.03 s +2024-11-23 06:10:23.765210: +2024-11-23 06:10:23.765405: Epoch 7967 +2024-11-23 06:10:23.765512: Current learning rate: 7e-05 +2024-11-23 06:10:43.181303: train_loss -0.8437 +2024-11-23 06:10:43.181504: val_loss -0.7614 +2024-11-23 06:10:43.181577: Pseudo dice [0.8326] +2024-11-23 06:10:43.181654: Epoch time: 19.42 s +2024-11-23 06:10:44.219806: +2024-11-23 06:10:44.220019: Epoch 7968 +2024-11-23 06:10:44.220129: Current learning rate: 7e-05 +2024-11-23 06:11:03.395433: train_loss -0.8358 +2024-11-23 06:11:03.395643: val_loss -0.7748 +2024-11-23 06:11:03.395718: Pseudo dice [0.8324] +2024-11-23 06:11:03.395792: Epoch time: 19.18 s +2024-11-23 06:11:04.332733: +2024-11-23 06:11:04.332965: Epoch 7969 +2024-11-23 06:11:04.333079: Current learning rate: 7e-05 +2024-11-23 06:11:23.425138: train_loss -0.8462 +2024-11-23 06:11:23.425381: val_loss -0.7453 +2024-11-23 06:11:23.425462: Pseudo dice [0.8405] +2024-11-23 06:11:23.425549: Epoch time: 19.09 s +2024-11-23 06:11:24.355295: +2024-11-23 06:11:24.355499: Epoch 7970 +2024-11-23 06:11:24.355618: Current learning rate: 7e-05 +2024-11-23 06:11:42.110713: train_loss -0.8482 +2024-11-23 06:11:42.110920: val_loss -0.7609 +2024-11-23 06:11:42.111030: Pseudo dice [0.8295] +2024-11-23 06:11:42.111109: Epoch time: 17.76 s +2024-11-23 06:11:43.039919: +2024-11-23 06:11:43.040341: Epoch 7971 +2024-11-23 06:11:43.040481: Current learning rate: 6e-05 +2024-11-23 06:12:02.039447: train_loss -0.8423 +2024-11-23 06:12:02.039667: val_loss -0.7826 +2024-11-23 06:12:02.039738: Pseudo dice [0.8586] +2024-11-23 06:12:02.039812: Epoch time: 19.0 s +2024-11-23 06:12:03.024436: +2024-11-23 06:12:03.024666: Epoch 7972 +2024-11-23 06:12:03.024784: Current learning rate: 6e-05 +2024-11-23 06:12:21.939202: train_loss -0.8493 +2024-11-23 06:12:21.939417: val_loss -0.7703 +2024-11-23 06:12:21.939492: Pseudo dice [0.8407] +2024-11-23 06:12:21.939584: Epoch time: 18.92 s +2024-11-23 06:12:23.278201: +2024-11-23 06:12:23.278429: Epoch 7973 +2024-11-23 06:12:23.278547: Current learning rate: 6e-05 +2024-11-23 06:12:41.537174: train_loss -0.8511 +2024-11-23 06:12:41.537475: val_loss -0.7726 +2024-11-23 06:12:41.537552: Pseudo dice [0.8367] +2024-11-23 06:12:41.537633: Epoch time: 18.26 s +2024-11-23 06:12:42.481508: +2024-11-23 06:12:42.481705: Epoch 7974 +2024-11-23 06:12:42.481817: Current learning rate: 6e-05 +2024-11-23 06:13:00.155925: train_loss -0.8496 +2024-11-23 06:13:00.159391: val_loss -0.7631 +2024-11-23 06:13:00.159475: Pseudo dice [0.8412] +2024-11-23 06:13:00.159553: Epoch time: 17.68 s +2024-11-23 06:13:01.179521: +2024-11-23 06:13:01.179773: Epoch 7975 +2024-11-23 06:13:01.179885: Current learning rate: 6e-05 +2024-11-23 06:13:19.588757: train_loss -0.8464 +2024-11-23 06:13:19.588974: val_loss -0.7656 +2024-11-23 06:13:19.589054: Pseudo dice [0.82] +2024-11-23 06:13:19.589131: Epoch time: 18.41 s +2024-11-23 06:13:20.632563: +2024-11-23 06:13:20.632772: Epoch 7976 +2024-11-23 06:13:20.632887: Current learning rate: 5e-05 +2024-11-23 06:13:38.594059: train_loss -0.8462 +2024-11-23 06:13:38.594295: val_loss -0.7869 +2024-11-23 06:13:38.594368: Pseudo dice [0.8618] +2024-11-23 06:13:38.594450: Epoch time: 17.96 s +2024-11-23 06:13:39.533755: +2024-11-23 06:13:39.533955: Epoch 7977 +2024-11-23 06:13:39.534076: Current learning rate: 5e-05 +2024-11-23 06:13:57.877634: train_loss -0.8475 +2024-11-23 06:13:57.877844: val_loss -0.7737 +2024-11-23 06:13:57.877917: Pseudo dice [0.856] +2024-11-23 06:13:57.877999: Epoch time: 18.34 s +2024-11-23 06:13:58.813675: +2024-11-23 06:13:58.813889: Epoch 7978 +2024-11-23 06:13:58.814005: Current learning rate: 5e-05 +2024-11-23 06:14:17.468708: train_loss -0.8433 +2024-11-23 06:14:17.468922: val_loss -0.7831 +2024-11-23 06:14:17.469005: Pseudo dice [0.8388] +2024-11-23 06:14:17.469083: Epoch time: 18.66 s +2024-11-23 06:14:18.422711: +2024-11-23 06:14:18.422962: Epoch 7979 +2024-11-23 06:14:18.423084: Current learning rate: 5e-05 +2024-11-23 06:14:37.082357: train_loss -0.8453 +2024-11-23 06:14:37.082623: val_loss -0.7571 +2024-11-23 06:14:37.082699: Pseudo dice [0.845] +2024-11-23 06:14:37.082781: Epoch time: 18.66 s +2024-11-23 06:14:38.018506: +2024-11-23 06:14:38.018770: Epoch 7980 +2024-11-23 06:14:38.018888: Current learning rate: 5e-05 +2024-11-23 06:14:56.457776: train_loss -0.8429 +2024-11-23 06:14:56.458009: val_loss -0.7404 +2024-11-23 06:14:56.458086: Pseudo dice [0.849] +2024-11-23 06:14:56.458165: Epoch time: 18.44 s +2024-11-23 06:14:57.392118: +2024-11-23 06:14:57.392413: Epoch 7981 +2024-11-23 06:14:57.392525: Current learning rate: 4e-05 +2024-11-23 06:15:15.794855: train_loss -0.842 +2024-11-23 06:15:15.795079: val_loss -0.7444 +2024-11-23 06:15:15.795153: Pseudo dice [0.8269] +2024-11-23 06:15:15.795227: Epoch time: 18.4 s +2024-11-23 06:15:16.790776: +2024-11-23 06:15:16.790966: Epoch 7982 +2024-11-23 06:15:16.791079: Current learning rate: 4e-05 +2024-11-23 06:15:35.267738: train_loss -0.85 +2024-11-23 06:15:35.267973: val_loss -0.7659 +2024-11-23 06:15:35.280489: Pseudo dice [0.8513] +2024-11-23 06:15:35.280737: Epoch time: 18.48 s +2024-11-23 06:15:36.213243: +2024-11-23 06:15:36.213447: Epoch 7983 +2024-11-23 06:15:36.213557: Current learning rate: 4e-05 +2024-11-23 06:15:54.714798: train_loss -0.8464 +2024-11-23 06:15:54.715064: val_loss -0.7726 +2024-11-23 06:15:54.715147: Pseudo dice [0.8397] +2024-11-23 06:15:54.715303: Epoch time: 18.5 s +2024-11-23 06:15:56.041626: +2024-11-23 06:15:56.041836: Epoch 7984 +2024-11-23 06:15:56.041951: Current learning rate: 4e-05 +2024-11-23 06:16:15.026923: train_loss -0.8489 +2024-11-23 06:16:15.029265: val_loss -0.7834 +2024-11-23 06:16:15.029384: Pseudo dice [0.8488] +2024-11-23 06:16:15.029464: Epoch time: 18.99 s +2024-11-23 06:16:16.046289: +2024-11-23 06:16:16.046547: Epoch 7985 +2024-11-23 06:16:16.046661: Current learning rate: 4e-05 +2024-11-23 06:16:35.280211: train_loss -0.8488 +2024-11-23 06:16:35.280445: val_loss -0.7748 +2024-11-23 06:16:35.280519: Pseudo dice [0.8451] +2024-11-23 06:16:35.280596: Epoch time: 19.23 s +2024-11-23 06:16:36.369581: +2024-11-23 06:16:36.369812: Epoch 7986 +2024-11-23 06:16:36.369927: Current learning rate: 3e-05 +2024-11-23 06:16:55.317030: train_loss -0.8415 +2024-11-23 06:16:55.317248: val_loss -0.7585 +2024-11-23 06:16:55.317323: Pseudo dice [0.8508] +2024-11-23 06:16:55.317400: Epoch time: 18.95 s +2024-11-23 06:16:56.356245: +2024-11-23 06:16:56.356452: Epoch 7987 +2024-11-23 06:16:56.356570: Current learning rate: 3e-05 +2024-11-23 06:17:14.673384: train_loss -0.8456 +2024-11-23 06:17:14.673618: val_loss -0.7552 +2024-11-23 06:17:14.673696: Pseudo dice [0.8436] +2024-11-23 06:17:14.673778: Epoch time: 18.32 s +2024-11-23 06:17:15.615462: +2024-11-23 06:17:15.615686: Epoch 7988 +2024-11-23 06:17:15.615805: Current learning rate: 3e-05 +2024-11-23 06:17:33.725476: train_loss -0.8446 +2024-11-23 06:17:33.725692: val_loss -0.7768 +2024-11-23 06:17:33.725767: Pseudo dice [0.8367] +2024-11-23 06:17:33.725846: Epoch time: 18.11 s +2024-11-23 06:17:34.746812: +2024-11-23 06:17:34.747022: Epoch 7989 +2024-11-23 06:17:34.747142: Current learning rate: 3e-05 +2024-11-23 06:17:53.486706: train_loss -0.8465 +2024-11-23 06:17:53.486936: val_loss -0.7768 +2024-11-23 06:17:53.487018: Pseudo dice [0.8399] +2024-11-23 06:17:53.487096: Epoch time: 18.74 s +2024-11-23 06:17:54.422437: +2024-11-23 06:17:54.422642: Epoch 7990 +2024-11-23 06:17:54.422894: Current learning rate: 2e-05 +2024-11-23 06:18:13.441974: train_loss -0.8437 +2024-11-23 06:18:13.442197: val_loss -0.7469 +2024-11-23 06:18:13.442273: Pseudo dice [0.8372] +2024-11-23 06:18:13.442351: Epoch time: 19.02 s +2024-11-23 06:18:14.377497: +2024-11-23 06:18:14.377704: Epoch 7991 +2024-11-23 06:18:14.377824: Current learning rate: 2e-05 +2024-11-23 06:18:32.982058: train_loss -0.8471 +2024-11-23 06:18:32.982291: val_loss -0.7717 +2024-11-23 06:18:32.982367: Pseudo dice [0.8528] +2024-11-23 06:18:32.982452: Epoch time: 18.61 s +2024-11-23 06:18:34.001971: +2024-11-23 06:18:34.002171: Epoch 7992 +2024-11-23 06:18:34.002285: Current learning rate: 2e-05 +2024-11-23 06:18:52.206724: train_loss -0.851 +2024-11-23 06:18:52.206939: val_loss -0.7691 +2024-11-23 06:18:52.207019: Pseudo dice [0.8449] +2024-11-23 06:18:52.207094: Epoch time: 18.21 s +2024-11-23 06:18:53.246723: +2024-11-23 06:18:53.246964: Epoch 7993 +2024-11-23 06:18:53.247086: Current learning rate: 2e-05 +2024-11-23 06:19:11.248286: train_loss -0.8417 +2024-11-23 06:19:11.248505: val_loss -0.7484 +2024-11-23 06:19:11.248578: Pseudo dice [0.8507] +2024-11-23 06:19:11.248650: Epoch time: 18.0 s +2024-11-23 06:19:12.310714: +2024-11-23 06:19:12.310934: Epoch 7994 +2024-11-23 06:19:12.311050: Current learning rate: 2e-05 +2024-11-23 06:19:29.965623: train_loss -0.8462 +2024-11-23 06:19:29.965865: val_loss -0.754 +2024-11-23 06:19:29.965945: Pseudo dice [0.8452] +2024-11-23 06:19:29.966047: Epoch time: 17.66 s +2024-11-23 06:19:31.298681: +2024-11-23 06:19:31.299148: Epoch 7995 +2024-11-23 06:19:31.299282: Current learning rate: 1e-05 +2024-11-23 06:19:50.721755: train_loss -0.8433 +2024-11-23 06:19:50.755625: val_loss -0.768 +2024-11-23 06:19:50.755786: Pseudo dice [0.8412] +2024-11-23 06:19:50.755872: Epoch time: 19.42 s +2024-11-23 06:19:52.131173: +2024-11-23 06:19:52.131433: Epoch 7996 +2024-11-23 06:19:52.131549: Current learning rate: 1e-05 +2024-11-23 06:20:09.784013: train_loss -0.8491 +2024-11-23 06:20:09.784253: val_loss -0.7775 +2024-11-23 06:20:09.784334: Pseudo dice [0.8636] +2024-11-23 06:20:09.784410: Epoch time: 17.65 s +2024-11-23 06:20:09.784470: Yayy! New best EMA pseudo Dice: 0.8458 +2024-11-23 06:20:11.062391: +2024-11-23 06:20:11.062589: Epoch 7997 +2024-11-23 06:20:11.062701: Current learning rate: 1e-05 +2024-11-23 06:20:29.897875: train_loss -0.8421 +2024-11-23 06:20:29.898114: val_loss -0.7888 +2024-11-23 06:20:29.898252: Pseudo dice [0.8488] +2024-11-23 06:20:29.898337: Epoch time: 18.84 s +2024-11-23 06:20:29.898398: Yayy! New best EMA pseudo Dice: 0.8461 +2024-11-23 06:20:31.175656: +2024-11-23 06:20:31.175892: Epoch 7998 +2024-11-23 06:20:31.176049: Current learning rate: 1e-05 +2024-11-23 06:20:50.328565: train_loss -0.8419 +2024-11-23 06:20:50.328789: val_loss -0.7796 +2024-11-23 06:20:50.328865: Pseudo dice [0.8358] +2024-11-23 06:20:50.328944: Epoch time: 19.15 s +2024-11-23 06:20:51.263111: +2024-11-23 06:20:51.263346: Epoch 7999 +2024-11-23 06:20:51.263455: Current learning rate: 0.0 +2024-11-23 06:21:09.070490: train_loss -0.8471 +2024-11-23 06:21:09.072878: val_loss -0.7869 +2024-11-23 06:21:09.073008: Pseudo dice [0.8392] +2024-11-23 06:21:09.073087: Epoch time: 17.81 s +2024-11-23 06:21:10.577187: Training done. +2024-11-23 06:21:10.590244: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-23 06:21:10.599412: The split file contains 5 splits. +2024-11-23 06:21:10.599540: Desired fold for training: 1 +2024-11-23 06:21:10.599598: This split has 534 training and 134 validation cases. +2024-11-23 06:21:10.600544: predicting FLAIR_003 +2024-11-23 06:21:10.607351: FLAIR_003, shape torch.Size([1, 136, 147, 190]), rank 0 +2024-11-23 06:21:17.812585: predicting FLAIR_004 +2024-11-23 06:21:17.821543: FLAIR_004, shape torch.Size([1, 132, 153, 191]), rank 0 +2024-11-23 06:21:18.392641: predicting FLAIR_010 +2024-11-23 06:21:18.400094: FLAIR_010, shape torch.Size([1, 132, 139, 190]), rank 0 +2024-11-23 06:21:18.970008: predicting FLAIR_012 +2024-11-23 06:21:18.983572: FLAIR_012, shape torch.Size([1, 131, 147, 203]), rank 0 +2024-11-23 06:21:19.563512: predicting FLAIR_019 +2024-11-23 06:21:19.572536: FLAIR_019, shape torch.Size([1, 129, 146, 192]), rank 0 +2024-11-23 06:21:20.142388: predicting FLAIR_021 +2024-11-23 06:21:20.154374: FLAIR_021, shape torch.Size([1, 132, 134, 173]), rank 0 +2024-11-23 06:21:20.729114: predicting FLAIR_025 +2024-11-23 06:21:20.742237: FLAIR_025, shape torch.Size([1, 133, 140, 184]), rank 0 +2024-11-23 06:21:21.318361: predicting FLAIR_026 +2024-11-23 06:21:21.416846: FLAIR_026, shape torch.Size([1, 129, 144, 186]), rank 0 +2024-11-23 06:21:21.995053: predicting FLAIR_028 +2024-11-23 06:21:22.004623: FLAIR_028, shape torch.Size([1, 137, 157, 211]), rank 0 +2024-11-23 06:21:22.576735: predicting FLAIR_029 +2024-11-23 06:21:22.616728: FLAIR_029, shape torch.Size([1, 139, 149, 197]), rank 0 +2024-11-23 06:21:39.835822: predicting FLAIR_034 +2024-11-23 06:21:39.862733: FLAIR_034, shape torch.Size([1, 144, 152, 206]), rank 0 +2024-11-23 06:21:40.450591: predicting FLAIR_036 +2024-11-23 06:21:40.488374: FLAIR_036, shape torch.Size([1, 137, 144, 193]), rank 0 +2024-11-23 06:21:41.086977: predicting FLAIR_041 +2024-11-23 06:21:41.118547: FLAIR_041, shape torch.Size([1, 126, 147, 187]), rank 0 +2024-11-23 06:21:41.700028: predicting FLAIR_053 +2024-11-23 06:21:41.720272: FLAIR_053, shape torch.Size([1, 127, 143, 179]), rank 0 +2024-11-23 06:21:42.302686: predicting FLAIR_063 +2024-11-23 06:21:42.380508: FLAIR_063, shape torch.Size([1, 131, 148, 192]), rank 0 +2024-11-23 06:21:42.959640: predicting FLAIR_066 +2024-11-23 06:21:42.973710: FLAIR_066, shape torch.Size([1, 134, 148, 190]), rank 0 +2024-11-23 06:21:43.559691: predicting FLAIR_067 +2024-11-23 06:21:43.603488: FLAIR_067, shape torch.Size([1, 137, 153, 200]), rank 0 +2024-11-23 06:21:44.194399: predicting FLAIR_069 +2024-11-23 06:21:44.232682: FLAIR_069, shape torch.Size([1, 132, 148, 184]), rank 0 +2024-11-23 06:21:44.827986: predicting FLAIR_071 +2024-11-23 06:21:44.846668: FLAIR_071, shape torch.Size([1, 143, 165, 183]), rank 0 +2024-11-23 06:21:45.434024: predicting FLAIR_075 +2024-11-23 06:21:45.444487: FLAIR_075, shape torch.Size([1, 132, 158, 186]), rank 0 +2024-11-23 06:21:46.015645: predicting FLAIR_076 +2024-11-23 06:21:46.022516: FLAIR_076, shape torch.Size([1, 125, 156, 181]), rank 0 +2024-11-23 06:21:46.598926: predicting FLAIR_085 +2024-11-23 06:21:46.647922: FLAIR_085, shape torch.Size([1, 128, 141, 189]), rank 0 +2024-11-23 06:21:47.243205: predicting FLAIR_086 +2024-11-23 06:21:47.270294: FLAIR_086, shape torch.Size([1, 138, 141, 184]), rank 0 +2024-11-23 06:21:47.874551: predicting FLAIR_090 +2024-11-23 06:21:47.894533: FLAIR_090, shape torch.Size([1, 142, 141, 188]), rank 0 +2024-11-23 06:21:48.472476: predicting FLAIR_098 +2024-11-23 06:21:48.481069: FLAIR_098, shape torch.Size([1, 134, 142, 185]), rank 0 +2024-11-23 06:21:49.058297: predicting FLAIR_100 +2024-11-23 06:21:49.205271: FLAIR_100, shape torch.Size([1, 126, 144, 196]), rank 0 +2024-11-23 06:21:49.817139: predicting FLAIR_101 +2024-11-23 06:21:49.836185: FLAIR_101, shape torch.Size([1, 135, 142, 181]), rank 0 +2024-11-23 06:21:50.470021: predicting FLAIR_102 +2024-11-23 06:21:50.491533: FLAIR_102, shape torch.Size([1, 131, 131, 196]), rank 0 +2024-11-23 06:21:51.098192: predicting FLAIR_107 +2024-11-23 06:21:51.122473: FLAIR_107, shape torch.Size([1, 134, 149, 199]), rank 0 +2024-11-23 06:21:51.718845: predicting FLAIR_110 +2024-11-23 06:21:51.743194: FLAIR_110, shape torch.Size([1, 125, 153, 185]), rank 0 +2024-11-23 06:21:52.345444: predicting FLAIR_113 +2024-11-23 06:21:52.363509: FLAIR_113, shape torch.Size([1, 133, 155, 201]), rank 0 +2024-11-23 06:21:52.957230: predicting FLAIR_121 +2024-11-23 06:21:52.984512: FLAIR_121, shape torch.Size([1, 124, 146, 176]), rank 0 +2024-11-23 06:21:53.570072: predicting FLAIR_131 +2024-11-23 06:21:53.590167: FLAIR_131, shape torch.Size([1, 131, 150, 179]), rank 0 +2024-11-23 06:21:54.192499: predicting FLAIR_145 +2024-11-23 06:21:54.218836: FLAIR_145, shape torch.Size([1, 131, 146, 175]), rank 0 +2024-11-23 06:21:54.842075: predicting FLAIR_148 +2024-11-23 06:21:54.881479: FLAIR_148, shape torch.Size([1, 145, 150, 200]), rank 0 +2024-11-23 06:21:55.580500: predicting FLAIR_149 +2024-11-23 06:21:55.587802: FLAIR_149, shape torch.Size([1, 141, 151, 189]), rank 0 +2024-11-23 06:21:56.507605: predicting FLAIR_154 +2024-11-23 06:21:56.529163: FLAIR_154, shape torch.Size([1, 134, 149, 199]), rank 0 +2024-11-23 06:21:57.432468: predicting FLAIR_157 +2024-11-23 06:21:57.439636: FLAIR_157, shape torch.Size([1, 134, 147, 195]), rank 0 +2024-11-23 06:21:58.151002: predicting FLAIR_160 +2024-11-23 06:21:58.182523: FLAIR_160, shape torch.Size([1, 146, 162, 179]), rank 0 +2024-11-23 06:21:58.793380: predicting FLAIR_163 +2024-11-23 06:21:58.816951: FLAIR_163, shape torch.Size([1, 135, 152, 192]), rank 0 +2024-11-23 06:21:59.408907: predicting FLAIR_165 +2024-11-23 06:21:59.448818: FLAIR_165, shape torch.Size([1, 143, 153, 197]), rank 0 +2024-11-23 06:22:00.051453: predicting FLAIR_176 +2024-11-23 06:22:00.075563: FLAIR_176, shape torch.Size([1, 138, 156, 193]), rank 0 +2024-11-23 06:22:00.694095: predicting FLAIR_179 +2024-11-23 06:22:00.763508: FLAIR_179, shape torch.Size([1, 127, 149, 190]), rank 0 +2024-11-23 06:22:01.412087: predicting FLAIR_180 +2024-11-23 06:22:01.490097: FLAIR_180, shape torch.Size([1, 135, 151, 191]), rank 0 +2024-11-23 06:22:02.096180: predicting FLAIR_182 +2024-11-23 06:22:02.146284: FLAIR_182, shape torch.Size([1, 125, 194, 157]), rank 0 +2024-11-23 06:22:02.653061: predicting FLAIR_184 +2024-11-23 06:22:02.680008: FLAIR_184, shape torch.Size([1, 133, 180, 154]), rank 0 +2024-11-23 06:22:03.039094: predicting FLAIR_187 +2024-11-23 06:22:03.054092: FLAIR_187, shape torch.Size([1, 131, 197, 153]), rank 0 +2024-11-23 06:22:03.538097: predicting FLAIR_189 +2024-11-23 06:22:03.570552: FLAIR_189, shape torch.Size([1, 144, 178, 163]), rank 0 +2024-11-23 06:22:04.222401: predicting FLAIR_192 +2024-11-23 06:22:04.249083: FLAIR_192, shape torch.Size([1, 136, 199, 157]), rank 0 +2024-11-23 06:22:04.718591: predicting FLAIR_200 +2024-11-23 06:22:04.736583: FLAIR_200, shape torch.Size([1, 127, 188, 148]), rank 0 +2024-11-23 06:22:05.044595: predicting FLAIR_204 +2024-11-23 06:22:05.052410: FLAIR_204, shape torch.Size([1, 141, 197, 156]), rank 0 +2024-11-23 06:22:05.511099: predicting FLAIR_214 +2024-11-23 06:22:05.546433: FLAIR_214, shape torch.Size([1, 129, 189, 143]), rank 0 +2024-11-23 06:22:05.886703: predicting FLAIR_221 +2024-11-23 06:22:05.894043: FLAIR_221, shape torch.Size([1, 127, 151, 196]), rank 0 +2024-11-23 06:22:06.471441: predicting FLAIR_222 +2024-11-23 06:22:06.478370: FLAIR_222, shape torch.Size([1, 124, 188, 150]), rank 0 +2024-11-23 06:22:06.772535: predicting FLAIR_224 +2024-11-23 06:22:06.809918: FLAIR_224, shape torch.Size([1, 147, 187, 162]), rank 0 +2024-11-23 06:22:07.409315: predicting FLAIR_234 +2024-11-23 06:22:07.418004: FLAIR_234, shape torch.Size([1, 127, 152, 190]), rank 0 +2024-11-23 06:22:07.995514: predicting FLAIR_240 +2024-11-23 06:22:08.024776: FLAIR_240, shape torch.Size([1, 132, 194, 156]), rank 0 +2024-11-23 06:22:08.473752: predicting FLAIR_241 +2024-11-23 06:22:08.508002: FLAIR_241, shape torch.Size([1, 134, 197, 154]), rank 0 +2024-11-23 06:22:08.963998: predicting FLAIR_254 +2024-11-23 06:22:08.989423: FLAIR_254, shape torch.Size([1, 131, 199, 160]), rank 0 +2024-11-23 06:22:09.431643: predicting FLAIR_255 +2024-11-23 06:22:09.438196: FLAIR_255, shape torch.Size([1, 132, 189, 146]), rank 0 +2024-11-23 06:22:09.755728: predicting FLAIR_259 +2024-11-23 06:22:09.766150: FLAIR_259, shape torch.Size([1, 133, 186, 149]), rank 0 +2024-11-23 06:22:10.087918: predicting FLAIR_276 +2024-11-23 06:22:10.155039: FLAIR_276, shape torch.Size([1, 130, 191, 150]), rank 0 +2024-11-23 06:22:10.478090: predicting FLAIR_281 +2024-11-23 06:22:10.494579: FLAIR_281, shape torch.Size([1, 141, 202, 163]), rank 0 +2024-11-23 06:22:11.359519: predicting FLAIR_282 +2024-11-23 06:22:11.370048: FLAIR_282, shape torch.Size([1, 143, 206, 160]), rank 0 +2024-11-23 06:22:11.812084: predicting FLAIR_284 +2024-11-23 06:22:11.829641: FLAIR_284, shape torch.Size([1, 143, 177, 156]), rank 0 +2024-11-23 06:22:12.152976: predicting FLAIR_285 +2024-11-23 06:22:12.177286: FLAIR_285, shape torch.Size([1, 139, 203, 164]), rank 0 +2024-11-23 06:22:13.029859: predicting FLAIR_292 +2024-11-23 06:22:13.037825: FLAIR_292, shape torch.Size([1, 126, 144, 192]), rank 0 +2024-11-23 06:22:13.615288: predicting FLAIR_304 +2024-11-23 06:22:13.625481: FLAIR_304, shape torch.Size([1, 124, 184, 141]), rank 0 +2024-11-23 06:22:13.919727: predicting FLAIR_318 +2024-11-23 06:22:13.927102: FLAIR_318, shape torch.Size([1, 131, 148, 178]), rank 0 +2024-11-23 06:22:14.497188: predicting FLAIR_323 +2024-11-23 06:22:14.507329: FLAIR_323, shape torch.Size([1, 150, 154, 194]), rank 0 +2024-11-23 06:22:15.079106: predicting FLAIR_325 +2024-11-23 06:22:15.088356: FLAIR_325, shape torch.Size([1, 131, 193, 150]), rank 0 +2024-11-23 06:22:15.531545: predicting FLAIR_330 +2024-11-23 06:22:15.557599: FLAIR_330, shape torch.Size([1, 130, 199, 150]), rank 0 +2024-11-23 06:22:16.049107: predicting FLAIR_335 +2024-11-23 06:22:16.079529: FLAIR_335, shape torch.Size([1, 137, 158, 198]), rank 0 +2024-11-23 06:22:16.681112: predicting FLAIR_342 +2024-11-23 06:22:16.697076: FLAIR_342, shape torch.Size([1, 129, 158, 186]), rank 0 +2024-11-23 06:22:17.288079: predicting FLAIR_351 +2024-11-23 06:22:17.308001: FLAIR_351, shape torch.Size([1, 131, 150, 181]), rank 0 +2024-11-23 06:22:17.895083: predicting FLAIR_356 +2024-11-23 06:22:17.902343: FLAIR_356, shape torch.Size([1, 128, 147, 191]), rank 0 +2024-11-23 06:22:18.496089: predicting FLAIR_360 +2024-11-23 06:22:18.502931: FLAIR_360, shape torch.Size([1, 128, 153, 187]), rank 0 +2024-11-23 06:22:19.080873: predicting FLAIR_401 +2024-11-23 06:22:19.091271: FLAIR_401, shape torch.Size([1, 132, 149, 190]), rank 0 +2024-11-23 06:22:19.675897: predicting FLAIR_404 +2024-11-23 06:22:19.698952: FLAIR_404, shape torch.Size([1, 125, 194, 156]), rank 0 +2024-11-23 06:22:20.165464: predicting FLAIR_405 +2024-11-23 06:22:20.181598: FLAIR_405, shape torch.Size([1, 133, 180, 153]), rank 0 +2024-11-23 06:22:20.497829: predicting FLAIR_412 +2024-11-23 06:22:20.508971: FLAIR_412, shape torch.Size([1, 126, 179, 153]), rank 0 +2024-11-23 06:22:20.825114: predicting FLAIR_414 +2024-11-23 06:22:20.856683: FLAIR_414, shape torch.Size([1, 142, 197, 154]), rank 0 +2024-11-23 06:22:21.336094: predicting FLAIR_428 +2024-11-23 06:22:21.343382: FLAIR_428, shape torch.Size([1, 126, 188, 152]), rank 0 +2024-11-23 06:22:21.637491: predicting FLAIR_436 +2024-11-23 06:22:21.645031: FLAIR_436, shape torch.Size([1, 130, 151, 191]), rank 0 +2024-11-23 06:22:22.228015: predicting FLAIR_444 +2024-11-23 06:22:22.266076: FLAIR_444, shape torch.Size([1, 126, 191, 156]), rank 0 +2024-11-23 06:22:22.568800: predicting FLAIR_454 +2024-11-23 06:22:22.576684: FLAIR_454, shape torch.Size([1, 134, 188, 150]), rank 0 +2024-11-23 06:22:22.880440: predicting FLAIR_456 +2024-11-23 06:22:22.903930: FLAIR_456, shape torch.Size([1, 126, 183, 148]), rank 0 +2024-11-23 06:22:23.231394: predicting FLAIR_476 +2024-11-23 06:22:23.257836: FLAIR_476, shape torch.Size([1, 130, 155, 195]), rank 0 +2024-11-23 06:22:23.905120: predicting FLAIR_487 +2024-11-23 06:22:23.929080: FLAIR_487, shape torch.Size([1, 134, 155, 192]), rank 0 +2024-11-23 06:22:24.500010: predicting FLAIR_492 +2024-11-23 06:22:24.507628: FLAIR_492, shape torch.Size([1, 125, 143, 191]), rank 0 +2024-11-23 06:22:25.077794: predicting FLAIR_495 +2024-11-23 06:22:25.086041: FLAIR_495, shape torch.Size([1, 133, 154, 195]), rank 0 +2024-11-23 06:22:25.659984: predicting FLAIR_502 +2024-11-23 06:22:25.670518: FLAIR_502, shape torch.Size([1, 130, 151, 189]), rank 0 +2024-11-23 06:22:26.261125: predicting FLAIR_507 +2024-11-23 06:22:26.282308: FLAIR_507, shape torch.Size([1, 128, 151, 191]), rank 0 +2024-11-23 06:22:26.899133: predicting FLAIR_511 +2024-11-23 06:22:26.918644: FLAIR_511, shape torch.Size([1, 129, 145, 185]), rank 0 +2024-11-23 06:22:27.552136: predicting FLAIR_512 +2024-11-23 06:22:27.578450: FLAIR_512, shape torch.Size([1, 134, 145, 180]), rank 0 +2024-11-23 06:22:28.217127: predicting FLAIR_514 +2024-11-23 06:22:28.240987: FLAIR_514, shape torch.Size([1, 132, 149, 183]), rank 0 +2024-11-23 06:22:28.984770: predicting FLAIR_516 +2024-11-23 06:22:29.000586: FLAIR_516, shape torch.Size([1, 133, 149, 186]), rank 0 +2024-11-23 06:22:29.874474: predicting FLAIR_517 +2024-11-23 06:22:29.929741: FLAIR_517, shape torch.Size([1, 144, 161, 211]), rank 0 +2024-11-23 06:22:30.546113: predicting FLAIR_524 +2024-11-23 06:22:30.553291: FLAIR_524, shape torch.Size([1, 133, 145, 185]), rank 0 +2024-11-23 06:22:31.214286: predicting FLAIR_528 +2024-11-23 06:22:31.248200: FLAIR_528, shape torch.Size([1, 136, 153, 197]), rank 0 +2024-11-23 06:22:31.859010: predicting FLAIR_531 +2024-11-23 06:22:31.884560: FLAIR_531, shape torch.Size([1, 134, 148, 186]), rank 0 +2024-11-23 06:22:33.988535: predicting FLAIR_534 +2024-11-23 06:22:33.995544: FLAIR_534, shape torch.Size([1, 136, 149, 196]), rank 0 +2024-11-23 06:22:34.654765: predicting FLAIR_540 +2024-11-23 06:22:34.671629: FLAIR_540, shape torch.Size([1, 138, 149, 191]), rank 0 +2024-11-23 06:22:35.274566: predicting FLAIR_545 +2024-11-23 06:22:35.290565: FLAIR_545, shape torch.Size([1, 132, 154, 190]), rank 0 +2024-11-23 06:22:35.883697: predicting FLAIR_548 +2024-11-23 06:22:35.900556: FLAIR_548, shape torch.Size([1, 145, 160, 201]), rank 0 +2024-11-23 06:22:36.997515: predicting FLAIR_557 +2024-11-23 06:22:37.004604: FLAIR_557, shape torch.Size([1, 130, 148, 185]), rank 0 +2024-11-23 06:22:37.999843: predicting FLAIR_560 +2024-11-23 06:22:38.006862: FLAIR_560, shape torch.Size([1, 136, 145, 191]), rank 0 +2024-11-23 06:22:39.487128: predicting FLAIR_564 +2024-11-23 06:22:39.505257: FLAIR_564, shape torch.Size([1, 136, 146, 196]), rank 0 +2024-11-23 06:22:40.431521: predicting FLAIR_569 +2024-11-23 06:22:40.531856: FLAIR_569, shape torch.Size([1, 138, 148, 197]), rank 0 +2024-11-23 06:22:41.173759: predicting FLAIR_570 +2024-11-23 06:22:41.205564: FLAIR_570, shape torch.Size([1, 133, 144, 185]), rank 0 +2024-11-23 06:22:43.234062: predicting FLAIR_584 +2024-11-23 06:22:43.241758: FLAIR_584, shape torch.Size([1, 131, 155, 192]), rank 0 +2024-11-23 06:22:43.862364: predicting FLAIR_586 +2024-11-23 06:22:43.897504: FLAIR_586, shape torch.Size([1, 131, 148, 192]), rank 0 +2024-11-23 06:22:44.596811: predicting FLAIR_589 +2024-11-23 06:22:44.614539: FLAIR_589, shape torch.Size([1, 135, 154, 195]), rank 0 +2024-11-23 06:22:45.222114: predicting FLAIR_591 +2024-11-23 06:22:45.253532: FLAIR_591, shape torch.Size([1, 122, 147, 179]), rank 0 +2024-11-23 06:22:46.754070: predicting FLAIR_598 +2024-11-23 06:22:46.761138: FLAIR_598, shape torch.Size([1, 139, 143, 183]), rank 0 +2024-11-23 06:22:48.240371: predicting FLAIR_600 +2024-11-23 06:22:48.258537: FLAIR_600, shape torch.Size([1, 123, 142, 184]), rank 0 +2024-11-23 06:22:48.837481: predicting FLAIR_602 +2024-11-23 06:22:48.861008: FLAIR_602, shape torch.Size([1, 138, 158, 191]), rank 0 +2024-11-23 06:22:49.470444: predicting FLAIR_604 +2024-11-23 06:22:49.497088: FLAIR_604, shape torch.Size([1, 137, 146, 195]), rank 0 +2024-11-23 06:22:51.204790: predicting FLAIR_605 +2024-11-23 06:22:51.227123: FLAIR_605, shape torch.Size([1, 140, 143, 200]), rank 0 +2024-11-23 06:22:51.822907: predicting FLAIR_609 +2024-11-23 06:22:51.843108: FLAIR_609, shape torch.Size([1, 137, 154, 202]), rank 0 +2024-11-23 06:22:53.143633: predicting FLAIR_613 +2024-11-23 06:22:53.171546: FLAIR_613, shape torch.Size([1, 133, 146, 191]), rank 0 +2024-11-23 06:22:53.783443: predicting FLAIR_620 +2024-11-23 06:22:53.801238: FLAIR_620, shape torch.Size([1, 138, 161, 197]), rank 0 +2024-11-23 06:22:54.612506: predicting FLAIR_626 +2024-11-23 06:22:54.624468: FLAIR_626, shape torch.Size([1, 141, 155, 204]), rank 0 +2024-11-23 06:22:55.564651: predicting FLAIR_631 +2024-11-23 06:22:55.570845: FLAIR_631, shape torch.Size([1, 113, 140, 174]), rank 0 +2024-11-23 06:22:57.469271: predicting FLAIR_634 +2024-11-23 06:22:57.480107: FLAIR_634, shape torch.Size([1, 130, 151, 199]), rank 0 +2024-11-23 06:22:58.375304: predicting FLAIR_637 +2024-11-23 06:22:58.388253: FLAIR_637, shape torch.Size([1, 125, 154, 186]), rank 0 +2024-11-23 06:22:58.998325: predicting FLAIR_638 +2024-11-23 06:22:59.029476: FLAIR_638, shape torch.Size([1, 136, 150, 185]), rank 0 +2024-11-23 06:22:59.725492: predicting FLAIR_639 +2024-11-23 06:22:59.742037: FLAIR_639, shape torch.Size([1, 142, 152, 189]), rank 0 +2024-11-23 06:23:01.054056: predicting FLAIR_640 +2024-11-23 06:23:01.066498: FLAIR_640, shape torch.Size([1, 134, 161, 195]), rank 0 +2024-11-23 06:23:02.447093: predicting FLAIR_645 +2024-11-23 06:23:02.454102: FLAIR_645, shape torch.Size([1, 134, 153, 176]), rank 0 +2024-11-23 06:23:03.048102: predicting FLAIR_650 +2024-11-23 06:23:03.072466: FLAIR_650, shape torch.Size([1, 140, 154, 201]), rank 0 +2024-11-23 06:23:03.748153: predicting FLAIR_652 +2024-11-23 06:23:03.787688: FLAIR_652, shape torch.Size([1, 136, 148, 196]), rank 0 +2024-11-23 06:23:04.468480: predicting FLAIR_653 +2024-11-23 06:23:04.507527: FLAIR_653, shape torch.Size([1, 137, 165, 205]), rank 0 +2024-11-23 06:23:06.549137: predicting FLAIR_665 +2024-11-23 06:23:06.556011: FLAIR_665, shape torch.Size([1, 130, 136, 186]), rank 0 +2024-11-23 06:23:39.989245: Validation complete +2024-11-23 06:23:39.990201: Mean Validation Dice: 0.7813705943269879 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/checkpoint_best.pth b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/checkpoint_best.pth new file mode 100644 index 0000000000000000000000000000000000000000..5c4be14749bf5c3b1009f273be8c02c1c9a2de10 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/checkpoint_best.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b9c04fe42868196821c655453af654505d74370d266a2010326b95108dc2f395 +size 249222946 diff --git 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OptimizedModule(\n (_orig_mod): MemoryEfficientSoftDiceLoss()\n )\n )\n)", + "lr_scheduler": "", + "my_init_kwargs": "{'plans': {'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 106, 'patch_size': [160, 192], 'median_image_size_in_voxels': [154.0, 185.0], 'spacing': [0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 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'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}", + "preprocessed_dataset_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/nnUNetPlans_3d_fullres", + "preprocessed_dataset_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML", + "save_every": "50", + "torch_version": "2.1.2+cu121", + "unpack_dataset": "True", + "was_initialized": "True", + "weight_decay": "3e-05" +} \ No newline at end of file diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/progress.png b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/progress.png new file mode 100644 index 0000000000000000000000000000000000000000..ec0b1d673dd683950ed5a549bee7a518f9f17501 Binary files /dev/null and b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/progress.png differ diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/training_log_2024_11_21_10_39_47.txt b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/training_log_2024_11_21_10_39_47.txt new file mode 100644 index 0000000000000000000000000000000000000000..ba20a4aee61004a06065d7f3b92822e2fadaf574 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_2/training_log_2024_11_21_10_39_47.txt @@ -0,0 +1,56390 @@ + +####################################################################### +Please cite the following paper when using nnU-Net: +Isensee, F., Jaeger, P. F., Kohl, S. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 18(2), 203-211. +####################################################################### + +2024-11-21 10:39:47.870745: do_dummy_2d_data_aug: False +2024-11-21 10:39:47.873523: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-21 10:39:47.874338: The split file contains 5 splits. +2024-11-21 10:39:47.874403: Desired fold for training: 2 +2024-11-21 10:39:47.874451: This split has 534 training and 134 validation cases. +2024-11-21 10:39:53.229070: Using torch.compile... + +This is the configuration used by this training: +Configuration name: 3d_fullres + {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False} + +These are the global plan.json settings: + {'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}} + +2024-11-21 10:39:54.610160: unpacking dataset... +2024-11-21 10:40:03.746789: unpacking done... +2024-11-21 10:40:03.756651: Unable to plot network architecture: nnUNet_compile is enabled! +2024-11-21 10:40:03.765555: +2024-11-21 10:40:03.765695: Epoch 0 +2024-11-21 10:40:03.765851: Current learning rate: 0.01 +2024-11-21 10:40:59.363248: train_loss -0.2756 +2024-11-21 10:40:59.365600: val_loss -0.4914 +2024-11-21 10:40:59.365689: Pseudo dice [0.5264] +2024-11-21 10:40:59.365772: Epoch time: 55.6 s +2024-11-21 10:40:59.365843: Yayy! New best EMA pseudo Dice: 0.5264 +2024-11-21 10:41:00.185274: +2024-11-21 10:41:00.185469: Epoch 1 +2024-11-21 10:41:00.185583: Current learning rate: 0.01 +2024-11-21 10:41:19.923456: train_loss -0.5417 +2024-11-21 10:41:19.923700: val_loss -0.6045 +2024-11-21 10:41:19.923820: Pseudo dice [0.7492] +2024-11-21 10:41:19.923908: Epoch time: 19.74 s +2024-11-21 10:41:19.923980: Yayy! New best EMA pseudo Dice: 0.5487 +2024-11-21 10:41:20.884182: +2024-11-21 10:41:20.884400: Epoch 2 +2024-11-21 10:41:20.884519: Current learning rate: 0.01 +2024-11-21 10:41:39.888757: train_loss -0.5917 +2024-11-21 10:41:39.888985: val_loss -0.5977 +2024-11-21 10:41:39.889066: Pseudo dice [0.7228] +2024-11-21 10:41:39.889146: Epoch time: 19.01 s +2024-11-21 10:41:39.889207: Yayy! New best EMA pseudo Dice: 0.5661 +2024-11-21 10:41:40.885559: +2024-11-21 10:41:40.885777: Epoch 3 +2024-11-21 10:41:40.885890: Current learning rate: 0.01 +2024-11-21 10:42:00.111592: train_loss -0.6225 +2024-11-21 10:42:00.111812: val_loss -0.6214 +2024-11-21 10:42:00.111885: Pseudo dice [0.7767] +2024-11-21 10:42:00.111966: Epoch time: 19.23 s +2024-11-21 10:42:00.112035: Yayy! New best EMA pseudo Dice: 0.5872 +2024-11-21 10:42:01.091199: +2024-11-21 10:42:01.091403: Epoch 4 +2024-11-21 10:42:01.091512: Current learning rate: 0.01 +2024-11-21 10:42:20.531866: train_loss -0.6378 +2024-11-21 10:42:20.535627: val_loss -0.6779 +2024-11-21 10:42:20.535854: Pseudo dice [0.7942] +2024-11-21 10:42:20.535947: Epoch time: 19.44 s +2024-11-21 10:42:20.536032: Yayy! New best EMA pseudo Dice: 0.6079 +2024-11-21 10:42:21.549376: +2024-11-21 10:42:21.549577: Epoch 5 +2024-11-21 10:42:21.549695: Current learning rate: 0.00999 +2024-11-21 10:42:41.162689: train_loss -0.6495 +2024-11-21 10:42:41.162900: val_loss -0.6628 +2024-11-21 10:42:41.162974: Pseudo dice [0.7649] +2024-11-21 10:42:41.165225: Epoch time: 19.61 s +2024-11-21 10:42:41.165298: Yayy! New best EMA pseudo Dice: 0.6236 +2024-11-21 10:42:42.155967: +2024-11-21 10:42:42.156182: Epoch 6 +2024-11-21 10:42:42.156303: Current learning rate: 0.00999 +2024-11-21 10:43:01.114362: train_loss -0.6457 +2024-11-21 10:43:01.114645: val_loss -0.6633 +2024-11-21 10:43:01.114725: Pseudo dice [0.7824] +2024-11-21 10:43:01.114804: Epoch time: 18.96 s +2024-11-21 10:43:01.114865: Yayy! New best EMA pseudo Dice: 0.6394 +2024-11-21 10:43:02.106942: +2024-11-21 10:43:02.107156: Epoch 7 +2024-11-21 10:43:02.107273: Current learning rate: 0.00999 +2024-11-21 10:43:21.285148: train_loss -0.6522 +2024-11-21 10:43:21.285384: val_loss -0.6468 +2024-11-21 10:43:21.285461: Pseudo dice [0.7809] +2024-11-21 10:43:21.287717: Epoch time: 19.18 s +2024-11-21 10:43:21.287875: Yayy! New best EMA pseudo Dice: 0.6536 +2024-11-21 10:43:22.284191: +2024-11-21 10:43:22.284409: Epoch 8 +2024-11-21 10:43:22.284532: Current learning rate: 0.00999 +2024-11-21 10:43:42.003881: train_loss -0.6668 +2024-11-21 10:43:42.004100: val_loss -0.6776 +2024-11-21 10:43:42.004173: Pseudo dice [0.8154] +2024-11-21 10:43:42.004249: Epoch time: 19.72 s +2024-11-21 10:43:42.004310: Yayy! New best EMA pseudo Dice: 0.6698 +2024-11-21 10:43:43.004264: +2024-11-21 10:43:43.004460: Epoch 9 +2024-11-21 10:43:43.004575: Current learning rate: 0.00999 +2024-11-21 10:44:02.248194: train_loss -0.6601 +2024-11-21 10:44:02.248464: val_loss -0.6803 +2024-11-21 10:44:02.248540: Pseudo dice [0.7902] +2024-11-21 10:44:02.248615: Epoch time: 19.24 s +2024-11-21 10:44:02.248677: Yayy! New best EMA pseudo Dice: 0.6818 +2024-11-21 10:44:03.224831: +2024-11-21 10:44:03.225049: Epoch 10 +2024-11-21 10:44:03.225167: Current learning rate: 0.00999 +2024-11-21 10:44:21.524336: train_loss -0.6639 +2024-11-21 10:44:21.524606: val_loss -0.6804 +2024-11-21 10:44:21.524686: Pseudo dice [0.7952] +2024-11-21 10:44:21.524774: Epoch time: 18.3 s +2024-11-21 10:44:21.524837: Yayy! New best EMA pseudo Dice: 0.6932 +2024-11-21 10:44:22.482837: +2024-11-21 10:44:22.483031: Epoch 11 +2024-11-21 10:44:22.483143: Current learning rate: 0.00999 +2024-11-21 10:44:42.369719: train_loss -0.6746 +2024-11-21 10:44:42.370014: val_loss -0.6914 +2024-11-21 10:44:42.370097: Pseudo dice [0.7881] +2024-11-21 10:44:42.370174: Epoch time: 19.89 s +2024-11-21 10:44:42.370237: Yayy! New best EMA pseudo Dice: 0.7026 +2024-11-21 10:44:43.370777: +2024-11-21 10:44:43.371066: Epoch 12 +2024-11-21 10:44:43.371189: Current learning rate: 0.00999 +2024-11-21 10:45:01.816480: train_loss -0.6886 +2024-11-21 10:45:01.816691: val_loss -0.7137 +2024-11-21 10:45:01.816766: Pseudo dice [0.8166] +2024-11-21 10:45:01.816842: Epoch time: 18.45 s +2024-11-21 10:45:01.816904: Yayy! New best EMA pseudo Dice: 0.714 +2024-11-21 10:45:02.796573: +2024-11-21 10:45:02.796788: Epoch 13 +2024-11-21 10:45:02.796904: Current learning rate: 0.00999 +2024-11-21 10:45:20.229613: train_loss -0.6843 +2024-11-21 10:45:20.229829: val_loss -0.6607 +2024-11-21 10:45:20.229905: Pseudo dice [0.793] +2024-11-21 10:45:20.229981: Epoch time: 17.43 s +2024-11-21 10:45:20.230052: Yayy! New best EMA pseudo Dice: 0.7219 +2024-11-21 10:45:21.189670: +2024-11-21 10:45:21.189933: Epoch 14 +2024-11-21 10:45:21.190069: Current learning rate: 0.00998 +2024-11-21 10:45:39.515671: train_loss -0.6978 +2024-11-21 10:45:39.515898: val_loss -0.6886 +2024-11-21 10:45:39.515972: Pseudo dice [0.8105] +2024-11-21 10:45:39.516053: Epoch time: 18.33 s +2024-11-21 10:45:39.516137: Yayy! New best EMA pseudo Dice: 0.7308 +2024-11-21 10:45:40.588043: +2024-11-21 10:45:40.588258: Epoch 15 +2024-11-21 10:45:40.588370: Current learning rate: 0.00998 +2024-11-21 10:45:57.766813: train_loss -0.7001 +2024-11-21 10:45:57.767028: val_loss -0.7008 +2024-11-21 10:45:57.767102: Pseudo dice [0.794] +2024-11-21 10:45:57.767176: Epoch time: 17.18 s +2024-11-21 10:45:57.767236: Yayy! New best EMA pseudo Dice: 0.7371 +2024-11-21 10:45:58.798432: +2024-11-21 10:45:58.798684: Epoch 16 +2024-11-21 10:45:58.798796: Current learning rate: 0.00998 +2024-11-21 10:46:17.535995: train_loss -0.6892 +2024-11-21 10:46:17.536211: val_loss -0.6761 +2024-11-21 10:46:17.536284: Pseudo dice [0.7811] +2024-11-21 10:46:17.536357: Epoch time: 18.74 s +2024-11-21 10:46:17.536417: Yayy! New best EMA pseudo Dice: 0.7415 +2024-11-21 10:46:18.649546: +2024-11-21 10:46:18.649819: Epoch 17 +2024-11-21 10:46:18.649931: Current learning rate: 0.00998 +2024-11-21 10:46:37.353123: train_loss -0.6815 +2024-11-21 10:46:37.353364: val_loss -0.6657 +2024-11-21 10:46:37.353441: Pseudo dice [0.7743] +2024-11-21 10:46:37.353523: Epoch time: 18.7 s +2024-11-21 10:46:37.353585: Yayy! New best EMA pseudo Dice: 0.7448 +2024-11-21 10:46:38.342319: +2024-11-21 10:46:38.342535: Epoch 18 +2024-11-21 10:46:38.342647: Current learning rate: 0.00998 +2024-11-21 10:46:57.277920: train_loss -0.684 +2024-11-21 10:46:57.278164: val_loss -0.6991 +2024-11-21 10:46:57.278238: Pseudo dice [0.7962] +2024-11-21 10:46:57.278314: Epoch time: 18.94 s +2024-11-21 10:46:57.278374: Yayy! New best EMA pseudo Dice: 0.7499 +2024-11-21 10:46:58.273113: +2024-11-21 10:46:58.273331: Epoch 19 +2024-11-21 10:46:58.273451: Current learning rate: 0.00998 +2024-11-21 10:47:17.418209: train_loss -0.7051 +2024-11-21 10:47:17.418417: val_loss -0.7196 +2024-11-21 10:47:17.418489: Pseudo dice [0.8226] +2024-11-21 10:47:17.418564: Epoch time: 19.15 s +2024-11-21 10:47:17.418625: Yayy! New best EMA pseudo Dice: 0.7572 +2024-11-21 10:47:18.384109: +2024-11-21 10:47:18.384301: Epoch 20 +2024-11-21 10:47:18.384417: Current learning rate: 0.00998 +2024-11-21 10:47:36.669506: train_loss -0.716 +2024-11-21 10:47:36.669717: val_loss -0.7123 +2024-11-21 10:47:36.669789: Pseudo dice [0.8155] +2024-11-21 10:47:36.669863: Epoch time: 18.29 s +2024-11-21 10:47:36.669924: Yayy! New best EMA pseudo Dice: 0.763 +2024-11-21 10:47:37.660880: +2024-11-21 10:47:37.661089: Epoch 21 +2024-11-21 10:47:37.661204: Current learning rate: 0.00998 +2024-11-21 10:47:56.301350: train_loss -0.7167 +2024-11-21 10:47:56.303807: val_loss -0.7094 +2024-11-21 10:47:56.303947: Pseudo dice [0.8168] +2024-11-21 10:47:56.304040: Epoch time: 18.64 s +2024-11-21 10:47:56.304106: Yayy! New best EMA pseudo Dice: 0.7684 +2024-11-21 10:47:57.277481: +2024-11-21 10:47:57.277695: Epoch 22 +2024-11-21 10:47:57.277813: Current learning rate: 0.00998 +2024-11-21 10:48:15.414920: train_loss -0.7035 +2024-11-21 10:48:15.417320: val_loss -0.7448 +2024-11-21 10:48:15.417419: Pseudo dice [0.8211] +2024-11-21 10:48:15.417499: Epoch time: 18.14 s +2024-11-21 10:48:15.417560: Yayy! New best EMA pseudo Dice: 0.7737 +2024-11-21 10:48:16.478012: +2024-11-21 10:48:16.478267: Epoch 23 +2024-11-21 10:48:16.478379: Current learning rate: 0.00997 +2024-11-21 10:48:35.312341: train_loss -0.6929 +2024-11-21 10:48:35.312587: val_loss -0.7015 +2024-11-21 10:48:35.312663: Pseudo dice [0.7928] +2024-11-21 10:48:35.317885: Epoch time: 18.84 s +2024-11-21 10:48:35.318083: Yayy! New best EMA pseudo Dice: 0.7756 +2024-11-21 10:48:36.276861: +2024-11-21 10:48:36.277060: Epoch 24 +2024-11-21 10:48:36.277171: Current learning rate: 0.00997 +2024-11-21 10:48:54.184647: train_loss -0.7063 +2024-11-21 10:48:54.184867: val_loss -0.6837 +2024-11-21 10:48:54.184946: Pseudo dice [0.805] +2024-11-21 10:48:54.185031: Epoch time: 17.91 s +2024-11-21 10:48:54.185094: Yayy! New best EMA pseudo Dice: 0.7785 +2024-11-21 10:48:55.151535: +2024-11-21 10:48:55.151747: Epoch 25 +2024-11-21 10:48:55.151859: Current learning rate: 0.00997 +2024-11-21 10:49:13.206545: train_loss -0.7101 +2024-11-21 10:49:13.206794: val_loss -0.6801 +2024-11-21 10:49:13.206869: Pseudo dice [0.7943] +2024-11-21 10:49:13.206952: Epoch time: 18.06 s +2024-11-21 10:49:13.207025: Yayy! New best EMA pseudo Dice: 0.7801 +2024-11-21 10:49:14.753942: +2024-11-21 10:49:14.754142: Epoch 26 +2024-11-21 10:49:14.754259: Current learning rate: 0.00997 +2024-11-21 10:49:32.603901: train_loss -0.71 +2024-11-21 10:49:32.604129: val_loss -0.6801 +2024-11-21 10:49:32.604204: Pseudo dice [0.8086] +2024-11-21 10:49:32.604282: Epoch time: 17.85 s +2024-11-21 10:49:32.604344: Yayy! New best EMA pseudo Dice: 0.783 +2024-11-21 10:49:33.597530: +2024-11-21 10:49:33.597736: Epoch 27 +2024-11-21 10:49:33.597852: Current learning rate: 0.00997 +2024-11-21 10:49:52.624948: train_loss -0.7011 +2024-11-21 10:49:52.625175: val_loss -0.7185 +2024-11-21 10:49:52.625254: Pseudo dice [0.8046] +2024-11-21 10:49:52.625333: Epoch time: 19.03 s +2024-11-21 10:49:52.625394: Yayy! New best EMA pseudo Dice: 0.7851 +2024-11-21 10:49:53.588049: +2024-11-21 10:49:53.588343: Epoch 28 +2024-11-21 10:49:53.588456: Current learning rate: 0.00997 +2024-11-21 10:50:13.945925: train_loss -0.7205 +2024-11-21 10:50:13.946170: val_loss -0.7123 +2024-11-21 10:50:13.946245: Pseudo dice [0.8113] +2024-11-21 10:50:13.946347: Epoch time: 20.36 s +2024-11-21 10:50:13.946413: Yayy! New best EMA pseudo Dice: 0.7877 +2024-11-21 10:50:14.936581: +2024-11-21 10:50:14.936776: Epoch 29 +2024-11-21 10:50:14.936883: Current learning rate: 0.00997 +2024-11-21 10:50:33.479359: train_loss -0.7144 +2024-11-21 10:50:33.479567: val_loss -0.7069 +2024-11-21 10:50:33.479643: Pseudo dice [0.8167] +2024-11-21 10:50:33.479779: Epoch time: 18.54 s +2024-11-21 10:50:33.479841: Yayy! New best EMA pseudo Dice: 0.7906 +2024-11-21 10:50:34.453854: +2024-11-21 10:50:34.454081: Epoch 30 +2024-11-21 10:50:34.454196: Current learning rate: 0.00997 +2024-11-21 10:50:52.103172: train_loss -0.7146 +2024-11-21 10:50:52.103381: val_loss -0.7104 +2024-11-21 10:50:52.103455: Pseudo dice [0.8324] +2024-11-21 10:50:52.103529: Epoch time: 17.65 s +2024-11-21 10:50:52.103589: Yayy! New best EMA pseudo Dice: 0.7948 +2024-11-21 10:50:53.075127: +2024-11-21 10:50:53.075324: Epoch 31 +2024-11-21 10:50:53.075440: Current learning rate: 0.00997 +2024-11-21 10:51:11.555269: train_loss -0.7178 +2024-11-21 10:51:11.555478: val_loss -0.7518 +2024-11-21 10:51:11.555551: Pseudo dice [0.8456] +2024-11-21 10:51:11.555628: Epoch time: 18.48 s +2024-11-21 10:51:11.555688: Yayy! New best EMA pseudo Dice: 0.7999 +2024-11-21 10:51:12.641727: +2024-11-21 10:51:12.642020: Epoch 32 +2024-11-21 10:51:12.642153: Current learning rate: 0.00996 +2024-11-21 10:51:29.800292: train_loss -0.7257 +2024-11-21 10:51:29.800550: val_loss -0.706 +2024-11-21 10:51:29.800625: Pseudo dice [0.8453] +2024-11-21 10:51:29.800704: Epoch time: 17.16 s +2024-11-21 10:51:29.800763: Yayy! New best EMA pseudo Dice: 0.8044 +2024-11-21 10:51:30.757872: +2024-11-21 10:51:30.758131: Epoch 33 +2024-11-21 10:51:30.758247: Current learning rate: 0.00996 +2024-11-21 10:51:49.894373: train_loss -0.7278 +2024-11-21 10:51:49.894587: val_loss -0.7248 +2024-11-21 10:51:49.894669: Pseudo dice [0.8417] +2024-11-21 10:51:49.894748: Epoch time: 19.14 s +2024-11-21 10:51:49.894810: Yayy! New best EMA pseudo Dice: 0.8082 +2024-11-21 10:51:50.854590: +2024-11-21 10:51:50.854843: Epoch 34 +2024-11-21 10:51:50.854956: Current learning rate: 0.00996 +2024-11-21 10:52:10.215422: train_loss -0.727 +2024-11-21 10:52:10.215638: val_loss -0.7633 +2024-11-21 10:52:10.215729: Pseudo dice [0.8361] +2024-11-21 10:52:10.215810: Epoch time: 19.36 s +2024-11-21 10:52:10.215873: Yayy! New best EMA pseudo Dice: 0.811 +2024-11-21 10:52:11.196023: +2024-11-21 10:52:11.196252: Epoch 35 +2024-11-21 10:52:11.196368: Current learning rate: 0.00996 +2024-11-21 10:52:30.442916: train_loss -0.7131 +2024-11-21 10:52:30.443180: val_loss -0.7257 +2024-11-21 10:52:30.443291: Pseudo dice [0.7994] +2024-11-21 10:52:30.443377: Epoch time: 19.25 s +2024-11-21 10:52:31.225006: +2024-11-21 10:52:31.225196: Epoch 36 +2024-11-21 10:52:31.225309: Current learning rate: 0.00996 +2024-11-21 10:52:49.956485: train_loss -0.7213 +2024-11-21 10:52:49.956734: val_loss -0.714 +2024-11-21 10:52:49.956810: Pseudo dice [0.8181] +2024-11-21 10:52:49.956897: Epoch time: 18.73 s +2024-11-21 10:52:51.109660: +2024-11-21 10:52:51.109858: Epoch 37 +2024-11-21 10:52:51.109973: Current learning rate: 0.00996 +2024-11-21 10:53:10.015910: train_loss -0.7193 +2024-11-21 10:53:10.016149: val_loss -0.7228 +2024-11-21 10:53:10.016227: Pseudo dice [0.8082] +2024-11-21 10:53:10.016306: Epoch time: 18.91 s +2024-11-21 10:53:10.888329: +2024-11-21 10:53:10.888560: Epoch 38 +2024-11-21 10:53:10.888677: Current learning rate: 0.00996 +2024-11-21 10:53:29.177485: train_loss -0.7325 +2024-11-21 10:53:29.177714: val_loss -0.7061 +2024-11-21 10:53:29.177797: Pseudo dice [0.8391] +2024-11-21 10:53:29.177879: Epoch time: 18.29 s +2024-11-21 10:53:29.177942: Yayy! New best EMA pseudo Dice: 0.8133 +2024-11-21 10:53:30.180460: +2024-11-21 10:53:30.180655: Epoch 39 +2024-11-21 10:53:30.180769: Current learning rate: 0.00996 +2024-11-21 10:53:48.666802: train_loss -0.7256 +2024-11-21 10:53:48.667044: val_loss -0.7211 +2024-11-21 10:53:48.667115: Pseudo dice [0.823] +2024-11-21 10:53:48.667192: Epoch time: 18.49 s +2024-11-21 10:53:48.667258: Yayy! New best EMA pseudo Dice: 0.8142 +2024-11-21 10:53:49.651295: +2024-11-21 10:53:49.651499: Epoch 40 +2024-11-21 10:53:49.651611: Current learning rate: 0.00995 +2024-11-21 10:54:08.267874: train_loss -0.7122 +2024-11-21 10:54:08.268144: val_loss -0.7215 +2024-11-21 10:54:08.268218: Pseudo dice [0.8057] +2024-11-21 10:54:08.268293: Epoch time: 18.62 s +2024-11-21 10:54:09.143845: +2024-11-21 10:54:09.144048: Epoch 41 +2024-11-21 10:54:09.144160: Current learning rate: 0.00995 +2024-11-21 10:54:27.790757: train_loss -0.7072 +2024-11-21 10:54:27.790979: val_loss -0.7277 +2024-11-21 10:54:27.791061: Pseudo dice [0.8246] +2024-11-21 10:54:27.791143: Epoch time: 18.65 s +2024-11-21 10:54:27.791206: Yayy! New best EMA pseudo Dice: 0.8145 +2024-11-21 10:54:28.752490: +2024-11-21 10:54:28.752689: Epoch 42 +2024-11-21 10:54:28.752802: Current learning rate: 0.00995 +2024-11-21 10:54:48.204470: train_loss -0.728 +2024-11-21 10:54:48.204671: val_loss -0.71 +2024-11-21 10:54:48.204747: Pseudo dice [0.8465] +2024-11-21 10:54:48.204823: Epoch time: 19.45 s +2024-11-21 10:54:48.204884: Yayy! New best EMA pseudo Dice: 0.8177 +2024-11-21 10:54:49.151625: +2024-11-21 10:54:49.151821: Epoch 43 +2024-11-21 10:54:49.151931: Current learning rate: 0.00995 +2024-11-21 10:55:08.245694: train_loss -0.7264 +2024-11-21 10:55:08.246293: val_loss -0.713 +2024-11-21 10:55:08.246381: Pseudo dice [0.8106] +2024-11-21 10:55:08.246467: Epoch time: 19.09 s +2024-11-21 10:55:09.020597: +2024-11-21 10:55:09.020864: Epoch 44 +2024-11-21 10:55:09.020979: Current learning rate: 0.00995 +2024-11-21 10:55:28.500598: train_loss -0.7252 +2024-11-21 10:55:28.500806: val_loss -0.7491 +2024-11-21 10:55:28.500879: Pseudo dice [0.8378] +2024-11-21 10:55:28.500954: Epoch time: 19.48 s +2024-11-21 10:55:28.501021: Yayy! New best EMA pseudo Dice: 0.8191 +2024-11-21 10:55:29.444119: +2024-11-21 10:55:29.444334: Epoch 45 +2024-11-21 10:55:29.444450: Current learning rate: 0.00995 +2024-11-21 10:55:48.244602: train_loss -0.7208 +2024-11-21 10:55:48.244809: val_loss -0.7151 +2024-11-21 10:55:48.244885: Pseudo dice [0.8198] +2024-11-21 10:55:48.244961: Epoch time: 18.8 s +2024-11-21 10:55:48.245030: Yayy! New best EMA pseudo Dice: 0.8192 +2024-11-21 10:55:49.250376: +2024-11-21 10:55:49.250571: Epoch 46 +2024-11-21 10:55:49.250686: Current learning rate: 0.00995 +2024-11-21 10:56:07.764964: train_loss -0.7241 +2024-11-21 10:56:07.765182: val_loss -0.7032 +2024-11-21 10:56:07.765258: Pseudo dice [0.8328] +2024-11-21 10:56:07.765335: Epoch time: 18.52 s +2024-11-21 10:56:07.765401: Yayy! New best EMA pseudo Dice: 0.8205 +2024-11-21 10:56:08.723855: +2024-11-21 10:56:08.724053: Epoch 47 +2024-11-21 10:56:08.724166: Current learning rate: 0.00995 +2024-11-21 10:56:26.694872: train_loss -0.7157 +2024-11-21 10:56:26.695158: val_loss -0.6969 +2024-11-21 10:56:26.695242: Pseudo dice [0.8082] +2024-11-21 10:56:26.695334: Epoch time: 17.97 s +2024-11-21 10:56:27.476156: +2024-11-21 10:56:27.476368: Epoch 48 +2024-11-21 10:56:27.476487: Current learning rate: 0.00995 +2024-11-21 10:56:46.095093: train_loss -0.7176 +2024-11-21 10:56:46.095303: val_loss -0.7116 +2024-11-21 10:56:46.095384: Pseudo dice [0.8436] +2024-11-21 10:56:46.095478: Epoch time: 18.62 s +2024-11-21 10:56:46.095546: Yayy! New best EMA pseudo Dice: 0.8217 +2024-11-21 10:56:47.476370: +2024-11-21 10:56:47.476573: Epoch 49 +2024-11-21 10:56:47.476684: Current learning rate: 0.00994 +2024-11-21 10:57:06.287423: train_loss -0.7295 +2024-11-21 10:57:06.287660: val_loss -0.6981 +2024-11-21 10:57:06.287795: Pseudo dice [0.7898] +2024-11-21 10:57:06.287876: Epoch time: 18.81 s +2024-11-21 10:57:07.389756: +2024-11-21 10:57:07.389963: Epoch 50 +2024-11-21 10:57:07.390094: Current learning rate: 0.00994 +2024-11-21 10:57:26.687258: train_loss -0.7089 +2024-11-21 10:57:26.687505: val_loss -0.6742 +2024-11-21 10:57:26.687582: Pseudo dice [0.7965] +2024-11-21 10:57:26.687666: Epoch time: 19.3 s +2024-11-21 10:57:27.447479: +2024-11-21 10:57:27.447696: Epoch 51 +2024-11-21 10:57:27.447811: Current learning rate: 0.00994 +2024-11-21 10:57:45.976642: train_loss -0.7335 +2024-11-21 10:57:45.976861: val_loss -0.7416 +2024-11-21 10:57:45.976938: Pseudo dice [0.8063] +2024-11-21 10:57:45.977024: Epoch time: 18.53 s +2024-11-21 10:57:46.744382: +2024-11-21 10:57:46.744612: Epoch 52 +2024-11-21 10:57:46.744729: Current learning rate: 0.00994 +2024-11-21 10:58:05.419405: train_loss -0.7286 +2024-11-21 10:58:05.421816: val_loss -0.7089 +2024-11-21 10:58:05.421951: Pseudo dice [0.8209] +2024-11-21 10:58:05.422041: Epoch time: 18.68 s +2024-11-21 10:58:06.218804: +2024-11-21 10:58:06.219090: Epoch 53 +2024-11-21 10:58:06.219208: Current learning rate: 0.00994 +2024-11-21 10:58:24.502585: train_loss -0.7278 +2024-11-21 10:58:24.502798: val_loss -0.7329 +2024-11-21 10:58:24.502868: Pseudo dice [0.8192] +2024-11-21 10:58:24.502947: Epoch time: 18.28 s +2024-11-21 10:58:25.269166: +2024-11-21 10:58:25.269463: Epoch 54 +2024-11-21 10:58:25.269578: Current learning rate: 0.00994 +2024-11-21 10:58:44.291060: train_loss -0.7248 +2024-11-21 10:58:44.291320: val_loss -0.7255 +2024-11-21 10:58:44.291398: Pseudo dice [0.8129] +2024-11-21 10:58:44.291485: Epoch time: 19.02 s +2024-11-21 10:58:45.062940: +2024-11-21 10:58:45.063218: Epoch 55 +2024-11-21 10:58:45.063339: Current learning rate: 0.00994 +2024-11-21 10:59:03.301820: train_loss -0.7261 +2024-11-21 10:59:03.302032: val_loss -0.6864 +2024-11-21 10:59:03.302108: Pseudo dice [0.824] +2024-11-21 10:59:03.302184: Epoch time: 18.24 s +2024-11-21 10:59:04.167078: +2024-11-21 10:59:04.167274: Epoch 56 +2024-11-21 10:59:04.167393: Current learning rate: 0.00994 +2024-11-21 10:59:23.323700: train_loss -0.7261 +2024-11-21 10:59:23.323913: val_loss -0.7132 +2024-11-21 10:59:23.323998: Pseudo dice [0.805] +2024-11-21 10:59:23.324075: Epoch time: 19.16 s +2024-11-21 10:59:24.086317: +2024-11-21 10:59:24.086517: Epoch 57 +2024-11-21 10:59:24.086628: Current learning rate: 0.00994 +2024-11-21 10:59:43.238415: train_loss -0.7298 +2024-11-21 10:59:43.238633: val_loss -0.7274 +2024-11-21 10:59:43.238709: Pseudo dice [0.8114] +2024-11-21 10:59:43.238789: Epoch time: 19.15 s +2024-11-21 10:59:44.014549: +2024-11-21 10:59:44.014748: Epoch 58 +2024-11-21 10:59:44.014864: Current learning rate: 0.00993 +2024-11-21 11:00:01.968788: train_loss -0.7385 +2024-11-21 11:00:01.969036: val_loss -0.7259 +2024-11-21 11:00:01.969110: Pseudo dice [0.8238] +2024-11-21 11:00:01.969192: Epoch time: 17.96 s +2024-11-21 11:00:02.744209: +2024-11-21 11:00:02.744407: Epoch 59 +2024-11-21 11:00:02.744521: Current learning rate: 0.00993 +2024-11-21 11:00:21.161782: train_loss -0.7338 +2024-11-21 11:00:21.162011: val_loss -0.7169 +2024-11-21 11:00:21.162088: Pseudo dice [0.8088] +2024-11-21 11:00:21.162166: Epoch time: 18.42 s +2024-11-21 11:00:21.934907: +2024-11-21 11:00:21.935126: Epoch 60 +2024-11-21 11:00:21.935238: Current learning rate: 0.00993 +2024-11-21 11:00:39.987053: train_loss -0.7458 +2024-11-21 11:00:39.987320: val_loss -0.7565 +2024-11-21 11:00:39.987394: Pseudo dice [0.842] +2024-11-21 11:00:39.987476: Epoch time: 18.05 s +2024-11-21 11:00:40.753484: +2024-11-21 11:00:40.753705: Epoch 61 +2024-11-21 11:00:40.753815: Current learning rate: 0.00993 +2024-11-21 11:01:00.377627: train_loss -0.723 +2024-11-21 11:01:00.377835: val_loss -0.7231 +2024-11-21 11:01:00.377911: Pseudo dice [0.8329] +2024-11-21 11:01:00.377988: Epoch time: 19.63 s +2024-11-21 11:01:01.139048: +2024-11-21 11:01:01.139342: Epoch 62 +2024-11-21 11:01:01.139456: Current learning rate: 0.00993 +2024-11-21 11:01:20.384261: train_loss -0.7338 +2024-11-21 11:01:20.384539: val_loss -0.719 +2024-11-21 11:01:20.384620: Pseudo dice [0.8257] +2024-11-21 11:01:20.384699: Epoch time: 19.25 s +2024-11-21 11:01:21.151814: +2024-11-21 11:01:21.152032: Epoch 63 +2024-11-21 11:01:21.152145: Current learning rate: 0.00993 +2024-11-21 11:01:38.954011: train_loss -0.7317 +2024-11-21 11:01:38.954250: val_loss -0.7262 +2024-11-21 11:01:38.954323: Pseudo dice [0.8113] +2024-11-21 11:01:38.954403: Epoch time: 17.8 s +2024-11-21 11:01:39.804069: +2024-11-21 11:01:39.804310: Epoch 64 +2024-11-21 11:01:39.804469: Current learning rate: 0.00993 +2024-11-21 11:01:58.541825: train_loss -0.7409 +2024-11-21 11:01:58.542049: val_loss -0.7066 +2024-11-21 11:01:58.542127: Pseudo dice [0.8172] +2024-11-21 11:01:58.542211: Epoch time: 18.74 s +2024-11-21 11:01:59.327595: +2024-11-21 11:01:59.327799: Epoch 65 +2024-11-21 11:01:59.327912: Current learning rate: 0.00993 +2024-11-21 11:02:17.990825: train_loss -0.7352 +2024-11-21 11:02:17.991044: val_loss -0.717 +2024-11-21 11:02:17.991119: Pseudo dice [0.8361] +2024-11-21 11:02:17.991195: Epoch time: 18.66 s +2024-11-21 11:02:18.768520: +2024-11-21 11:02:18.768806: Epoch 66 +2024-11-21 11:02:18.768922: Current learning rate: 0.00993 +2024-11-21 11:02:38.265777: train_loss -0.7217 +2024-11-21 11:02:38.266056: val_loss -0.7368 +2024-11-21 11:02:38.266132: Pseudo dice [0.8033] +2024-11-21 11:02:38.266207: Epoch time: 19.5 s +2024-11-21 11:02:39.051129: +2024-11-21 11:02:39.051343: Epoch 67 +2024-11-21 11:02:39.051455: Current learning rate: 0.00992 +2024-11-21 11:02:57.486872: train_loss -0.7408 +2024-11-21 11:02:57.487160: val_loss -0.7147 +2024-11-21 11:02:57.487267: Pseudo dice [0.7947] +2024-11-21 11:02:57.487349: Epoch time: 18.44 s +2024-11-21 11:02:58.269144: +2024-11-21 11:02:58.269344: Epoch 68 +2024-11-21 11:02:58.269462: Current learning rate: 0.00992 +2024-11-21 11:03:17.916739: train_loss -0.7339 +2024-11-21 11:03:17.916982: val_loss -0.7078 +2024-11-21 11:03:17.917064: Pseudo dice [0.813] +2024-11-21 11:03:17.917406: Epoch time: 19.65 s +2024-11-21 11:03:18.709174: +2024-11-21 11:03:18.709363: Epoch 69 +2024-11-21 11:03:18.709475: Current learning rate: 0.00992 +2024-11-21 11:03:36.875726: train_loss -0.7278 +2024-11-21 11:03:36.875941: val_loss -0.7261 +2024-11-21 11:03:36.876027: Pseudo dice [0.8222] +2024-11-21 11:03:36.876110: Epoch time: 18.17 s +2024-11-21 11:03:37.656850: +2024-11-21 11:03:37.657057: Epoch 70 +2024-11-21 11:03:37.657169: Current learning rate: 0.00992 +2024-11-21 11:03:56.298624: train_loss -0.7261 +2024-11-21 11:03:56.298860: val_loss -0.7118 +2024-11-21 11:03:56.298934: Pseudo dice [0.8277] +2024-11-21 11:03:56.299014: Epoch time: 18.64 s +2024-11-21 11:03:57.090583: +2024-11-21 11:03:57.090889: Epoch 71 +2024-11-21 11:03:57.091007: Current learning rate: 0.00992 +2024-11-21 11:04:17.374647: train_loss -0.7366 +2024-11-21 11:04:17.374939: val_loss -0.7158 +2024-11-21 11:04:17.375023: Pseudo dice [0.8221] +2024-11-21 11:04:17.375103: Epoch time: 20.29 s +2024-11-21 11:04:18.144676: +2024-11-21 11:04:18.144869: Epoch 72 +2024-11-21 11:04:18.144979: Current learning rate: 0.00992 +2024-11-21 11:04:37.455724: train_loss -0.7269 +2024-11-21 11:04:37.455937: val_loss -0.7247 +2024-11-21 11:04:37.456016: Pseudo dice [0.8419] +2024-11-21 11:04:37.456091: Epoch time: 19.31 s +2024-11-21 11:04:38.256052: +2024-11-21 11:04:38.256265: Epoch 73 +2024-11-21 11:04:38.256383: Current learning rate: 0.00992 +2024-11-21 11:04:56.071397: train_loss -0.7341 +2024-11-21 11:04:56.071618: val_loss -0.7351 +2024-11-21 11:04:56.071696: Pseudo dice [0.8261] +2024-11-21 11:04:56.071776: Epoch time: 17.82 s +2024-11-21 11:04:56.860231: +2024-11-21 11:04:56.860455: Epoch 74 +2024-11-21 11:04:56.860571: Current learning rate: 0.00992 +2024-11-21 11:05:15.016632: train_loss -0.731 +2024-11-21 11:05:15.016891: val_loss -0.7087 +2024-11-21 11:05:15.016968: Pseudo dice [0.8199] +2024-11-21 11:05:15.017060: Epoch time: 18.16 s +2024-11-21 11:05:15.889165: +2024-11-21 11:05:15.889367: Epoch 75 +2024-11-21 11:05:15.889474: Current learning rate: 0.00992 +2024-11-21 11:05:34.551459: train_loss -0.7362 +2024-11-21 11:05:34.552816: val_loss -0.7468 +2024-11-21 11:05:34.552902: Pseudo dice [0.8134] +2024-11-21 11:05:34.552980: Epoch time: 18.66 s +2024-11-21 11:05:35.336149: +2024-11-21 11:05:35.336379: Epoch 76 +2024-11-21 11:05:35.336492: Current learning rate: 0.00991 +2024-11-21 11:05:53.970578: train_loss -0.7351 +2024-11-21 11:05:53.970796: val_loss -0.7311 +2024-11-21 11:05:53.970873: Pseudo dice [0.8241] +2024-11-21 11:05:53.970951: Epoch time: 18.64 s +2024-11-21 11:05:54.767490: +2024-11-21 11:05:54.767707: Epoch 77 +2024-11-21 11:05:54.767821: Current learning rate: 0.00991 +2024-11-21 11:06:13.466631: train_loss -0.7352 +2024-11-21 11:06:13.466842: val_loss -0.7189 +2024-11-21 11:06:13.466918: Pseudo dice [0.823] +2024-11-21 11:06:13.467000: Epoch time: 18.7 s +2024-11-21 11:06:14.248052: +2024-11-21 11:06:14.248251: Epoch 78 +2024-11-21 11:06:14.248370: Current learning rate: 0.00991 +2024-11-21 11:06:33.258166: train_loss -0.7426 +2024-11-21 11:06:33.258433: val_loss -0.7317 +2024-11-21 11:06:33.258507: Pseudo dice [0.8275] +2024-11-21 11:06:33.258593: Epoch time: 19.01 s +2024-11-21 11:06:34.043533: +2024-11-21 11:06:34.043738: Epoch 79 +2024-11-21 11:06:34.043853: Current learning rate: 0.00991 +2024-11-21 11:06:52.536058: train_loss -0.7348 +2024-11-21 11:06:52.536265: val_loss -0.7303 +2024-11-21 11:06:52.536338: Pseudo dice [0.787] +2024-11-21 11:06:52.536414: Epoch time: 18.49 s +2024-11-21 11:06:53.313458: +2024-11-21 11:06:53.313680: Epoch 80 +2024-11-21 11:06:53.313800: Current learning rate: 0.00991 +2024-11-21 11:07:11.746260: train_loss -0.7435 +2024-11-21 11:07:11.746476: val_loss -0.7174 +2024-11-21 11:07:11.746551: Pseudo dice [0.8169] +2024-11-21 11:07:11.746629: Epoch time: 18.43 s +2024-11-21 11:07:12.527789: +2024-11-21 11:07:12.528077: Epoch 81 +2024-11-21 11:07:12.528193: Current learning rate: 0.00991 +2024-11-21 11:07:30.151109: train_loss -0.7164 +2024-11-21 11:07:30.151320: val_loss -0.7105 +2024-11-21 11:07:30.151397: Pseudo dice [0.8003] +2024-11-21 11:07:30.151475: Epoch time: 17.62 s +2024-11-21 11:07:31.478976: +2024-11-21 11:07:31.479154: Epoch 82 +2024-11-21 11:07:31.479267: Current learning rate: 0.00991 +2024-11-21 11:07:51.190122: train_loss -0.7107 +2024-11-21 11:07:51.195584: val_loss -0.7112 +2024-11-21 11:07:51.195673: Pseudo dice [0.8215] +2024-11-21 11:07:51.195765: Epoch time: 19.71 s +2024-11-21 11:07:52.219019: +2024-11-21 11:07:52.219232: Epoch 83 +2024-11-21 11:07:52.219349: Current learning rate: 0.00991 +2024-11-21 11:08:11.599260: train_loss -0.7207 +2024-11-21 11:08:11.599475: val_loss -0.7169 +2024-11-21 11:08:11.599546: Pseudo dice [0.8059] +2024-11-21 11:08:11.599620: Epoch time: 19.38 s +2024-11-21 11:08:12.359462: +2024-11-21 11:08:12.359664: Epoch 84 +2024-11-21 11:08:12.359776: Current learning rate: 0.00991 +2024-11-21 11:08:31.892267: train_loss -0.742 +2024-11-21 11:08:31.892484: val_loss -0.74 +2024-11-21 11:08:31.892559: Pseudo dice [0.8299] +2024-11-21 11:08:31.892637: Epoch time: 19.53 s +2024-11-21 11:08:32.648948: +2024-11-21 11:08:32.649161: Epoch 85 +2024-11-21 11:08:32.649272: Current learning rate: 0.0099 +2024-11-21 11:08:50.223453: train_loss -0.7349 +2024-11-21 11:08:50.223664: val_loss -0.7597 +2024-11-21 11:08:50.223735: Pseudo dice [0.8434] +2024-11-21 11:08:50.223810: Epoch time: 17.58 s +2024-11-21 11:08:51.016738: +2024-11-21 11:08:51.016963: Epoch 86 +2024-11-21 11:08:51.017097: Current learning rate: 0.0099 +2024-11-21 11:09:09.991084: train_loss -0.7397 +2024-11-21 11:09:09.991338: val_loss -0.6969 +2024-11-21 11:09:09.991412: Pseudo dice [0.8157] +2024-11-21 11:09:09.991495: Epoch time: 18.98 s +2024-11-21 11:09:10.759837: +2024-11-21 11:09:10.760045: Epoch 87 +2024-11-21 11:09:10.760157: Current learning rate: 0.0099 +2024-11-21 11:09:29.559810: train_loss -0.7416 +2024-11-21 11:09:29.560033: val_loss -0.7164 +2024-11-21 11:09:29.560109: Pseudo dice [0.8284] +2024-11-21 11:09:29.560186: Epoch time: 18.8 s +2024-11-21 11:09:30.322941: +2024-11-21 11:09:30.323156: Epoch 88 +2024-11-21 11:09:30.323271: Current learning rate: 0.0099 +2024-11-21 11:09:49.114272: train_loss -0.7314 +2024-11-21 11:09:49.114490: val_loss -0.7036 +2024-11-21 11:09:49.114565: Pseudo dice [0.8541] +2024-11-21 11:09:49.114641: Epoch time: 18.79 s +2024-11-21 11:09:49.114700: Yayy! New best EMA pseudo Dice: 0.8236 +2024-11-21 11:09:50.100247: +2024-11-21 11:09:50.100445: Epoch 89 +2024-11-21 11:09:50.100556: Current learning rate: 0.0099 +2024-11-21 11:10:09.575068: train_loss -0.733 +2024-11-21 11:10:09.575291: val_loss -0.7342 +2024-11-21 11:10:09.575368: Pseudo dice [0.8222] +2024-11-21 11:10:09.575445: Epoch time: 19.48 s +2024-11-21 11:10:10.343808: +2024-11-21 11:10:10.344019: Epoch 90 +2024-11-21 11:10:10.344133: Current learning rate: 0.0099 +2024-11-21 11:10:28.293752: train_loss -0.7409 +2024-11-21 11:10:28.294051: val_loss -0.7419 +2024-11-21 11:10:28.294150: Pseudo dice [0.8231] +2024-11-21 11:10:28.294235: Epoch time: 17.95 s +2024-11-21 11:10:29.331885: +2024-11-21 11:10:29.332092: Epoch 91 +2024-11-21 11:10:29.332206: Current learning rate: 0.0099 +2024-11-21 11:10:47.736865: train_loss -0.7414 +2024-11-21 11:10:47.737081: val_loss -0.7446 +2024-11-21 11:10:47.737158: Pseudo dice [0.8393] +2024-11-21 11:10:47.737236: Epoch time: 18.41 s +2024-11-21 11:10:47.737299: Yayy! New best EMA pseudo Dice: 0.825 +2024-11-21 11:10:48.743341: +2024-11-21 11:10:48.743556: Epoch 92 +2024-11-21 11:10:48.743667: Current learning rate: 0.0099 +2024-11-21 11:11:07.228859: train_loss -0.7369 +2024-11-21 11:11:07.229086: val_loss -0.7287 +2024-11-21 11:11:07.229162: Pseudo dice [0.8155] +2024-11-21 11:11:07.229239: Epoch time: 18.49 s +2024-11-21 11:11:08.102169: +2024-11-21 11:11:08.102398: Epoch 93 +2024-11-21 11:11:08.102516: Current learning rate: 0.0099 +2024-11-21 11:11:27.280482: train_loss -0.7139 +2024-11-21 11:11:27.280741: val_loss -0.7193 +2024-11-21 11:11:27.280813: Pseudo dice [0.8235] +2024-11-21 11:11:27.280894: Epoch time: 19.18 s +2024-11-21 11:11:28.037287: +2024-11-21 11:11:28.037498: Epoch 94 +2024-11-21 11:11:28.037612: Current learning rate: 0.00989 +2024-11-21 11:11:46.105497: train_loss -0.7309 +2024-11-21 11:11:46.106327: val_loss -0.7404 +2024-11-21 11:11:46.106460: Pseudo dice [0.8171] +2024-11-21 11:11:46.106541: Epoch time: 18.07 s +2024-11-21 11:11:46.864167: +2024-11-21 11:11:46.864365: Epoch 95 +2024-11-21 11:11:46.864474: Current learning rate: 0.00989 +2024-11-21 11:12:05.496469: train_loss -0.7423 +2024-11-21 11:12:05.496686: val_loss -0.7204 +2024-11-21 11:12:05.496760: Pseudo dice [0.8019] +2024-11-21 11:12:05.496835: Epoch time: 18.63 s +2024-11-21 11:12:06.265345: +2024-11-21 11:12:06.265553: Epoch 96 +2024-11-21 11:12:06.265670: Current learning rate: 0.00989 +2024-11-21 11:12:24.021718: train_loss -0.7297 +2024-11-21 11:12:24.021968: val_loss -0.731 +2024-11-21 11:12:24.022048: Pseudo dice [0.8318] +2024-11-21 11:12:24.022132: Epoch time: 17.76 s +2024-11-21 11:12:24.877977: +2024-11-21 11:12:24.878216: Epoch 97 +2024-11-21 11:12:24.878341: Current learning rate: 0.00989 +2024-11-21 11:12:44.744158: train_loss -0.7136 +2024-11-21 11:12:44.744390: val_loss -0.6987 +2024-11-21 11:12:44.744471: Pseudo dice [0.8174] +2024-11-21 11:12:44.744550: Epoch time: 19.87 s +2024-11-21 11:12:45.513743: +2024-11-21 11:12:45.513984: Epoch 98 +2024-11-21 11:12:45.514109: Current learning rate: 0.00989 +2024-11-21 11:13:04.809866: train_loss -0.7213 +2024-11-21 11:13:04.810083: val_loss -0.7076 +2024-11-21 11:13:04.810157: Pseudo dice [0.8175] +2024-11-21 11:13:04.810236: Epoch time: 19.3 s +2024-11-21 11:13:05.587662: +2024-11-21 11:13:05.587856: Epoch 99 +2024-11-21 11:13:05.587968: Current learning rate: 0.00989 +2024-11-21 11:13:23.512427: train_loss -0.7253 +2024-11-21 11:13:23.512643: val_loss -0.7387 +2024-11-21 11:13:23.512717: Pseudo dice [0.809] +2024-11-21 11:13:23.512791: Epoch time: 17.93 s +2024-11-21 11:13:24.517169: +2024-11-21 11:13:24.517372: Epoch 100 +2024-11-21 11:13:24.517488: Current learning rate: 0.00989 +2024-11-21 11:13:44.583567: train_loss -0.7338 +2024-11-21 11:13:44.583781: val_loss -0.7455 +2024-11-21 11:13:44.583855: Pseudo dice [0.8109] +2024-11-21 11:13:44.583934: Epoch time: 20.07 s +2024-11-21 11:13:45.354562: +2024-11-21 11:13:45.354774: Epoch 101 +2024-11-21 11:13:45.354887: Current learning rate: 0.00989 +2024-11-21 11:14:03.033272: train_loss -0.7501 +2024-11-21 11:14:03.033503: val_loss -0.7264 +2024-11-21 11:14:03.033578: Pseudo dice [0.8043] +2024-11-21 11:14:03.033659: Epoch time: 17.68 s +2024-11-21 11:14:03.795897: +2024-11-21 11:14:03.796095: Epoch 102 +2024-11-21 11:14:03.796209: Current learning rate: 0.00989 +2024-11-21 11:14:23.103514: train_loss -0.7299 +2024-11-21 11:14:23.103713: val_loss -0.7163 +2024-11-21 11:14:23.103784: Pseudo dice [0.7985] +2024-11-21 11:14:23.103860: Epoch time: 19.31 s +2024-11-21 11:14:24.076980: +2024-11-21 11:14:24.077188: Epoch 103 +2024-11-21 11:14:24.077302: Current learning rate: 0.00988 +2024-11-21 11:14:43.409389: train_loss -0.7406 +2024-11-21 11:14:43.409611: val_loss -0.7336 +2024-11-21 11:14:43.411785: Pseudo dice [0.843] +2024-11-21 11:14:43.411965: Epoch time: 19.33 s +2024-11-21 11:14:44.230222: +2024-11-21 11:14:44.230481: Epoch 104 +2024-11-21 11:14:44.230603: Current learning rate: 0.00988 +2024-11-21 11:15:02.422255: train_loss -0.7489 +2024-11-21 11:15:02.422507: val_loss -0.7307 +2024-11-21 11:15:02.422588: Pseudo dice [0.8329] +2024-11-21 11:15:02.422678: Epoch time: 18.19 s +2024-11-21 11:15:03.197152: +2024-11-21 11:15:03.197350: Epoch 105 +2024-11-21 11:15:03.197465: Current learning rate: 0.00988 +2024-11-21 11:15:22.710463: train_loss -0.7341 +2024-11-21 11:15:22.710666: val_loss -0.712 +2024-11-21 11:15:22.710769: Pseudo dice [0.829] +2024-11-21 11:15:22.710881: Epoch time: 19.51 s +2024-11-21 11:15:23.904493: +2024-11-21 11:15:23.904764: Epoch 106 +2024-11-21 11:15:23.904881: Current learning rate: 0.00988 +2024-11-21 11:15:41.213048: train_loss -0.7408 +2024-11-21 11:15:41.213259: val_loss -0.6979 +2024-11-21 11:15:41.213333: Pseudo dice [0.8278] +2024-11-21 11:15:41.213407: Epoch time: 17.31 s +2024-11-21 11:15:41.986717: +2024-11-21 11:15:41.986932: Epoch 107 +2024-11-21 11:15:41.987048: Current learning rate: 0.00988 +2024-11-21 11:15:59.731642: train_loss -0.7334 +2024-11-21 11:15:59.731892: val_loss -0.7194 +2024-11-21 11:15:59.731965: Pseudo dice [0.8291] +2024-11-21 11:15:59.732060: Epoch time: 17.75 s +2024-11-21 11:16:00.503134: +2024-11-21 11:16:00.503356: Epoch 108 +2024-11-21 11:16:00.503473: Current learning rate: 0.00988 +2024-11-21 11:16:19.248886: train_loss -0.7318 +2024-11-21 11:16:19.249086: val_loss -0.7301 +2024-11-21 11:16:19.249160: Pseudo dice [0.83] +2024-11-21 11:16:19.249237: Epoch time: 18.75 s +2024-11-21 11:16:20.027766: +2024-11-21 11:16:20.028021: Epoch 109 +2024-11-21 11:16:20.028136: Current learning rate: 0.00988 +2024-11-21 11:16:39.645867: train_loss -0.7322 +2024-11-21 11:16:39.646089: val_loss -0.7238 +2024-11-21 11:16:39.646166: Pseudo dice [0.8349] +2024-11-21 11:16:39.646242: Epoch time: 19.62 s +2024-11-21 11:16:40.417506: +2024-11-21 11:16:40.417706: Epoch 110 +2024-11-21 11:16:40.417823: Current learning rate: 0.00988 +2024-11-21 11:16:59.078832: train_loss -0.7319 +2024-11-21 11:16:59.079069: val_loss -0.7281 +2024-11-21 11:16:59.079181: Pseudo dice [0.8246] +2024-11-21 11:16:59.079263: Epoch time: 18.66 s +2024-11-21 11:16:59.864625: +2024-11-21 11:16:59.864892: Epoch 111 +2024-11-21 11:16:59.865010: Current learning rate: 0.00988 +2024-11-21 11:17:17.027265: train_loss -0.7455 +2024-11-21 11:17:17.027517: val_loss -0.6953 +2024-11-21 11:17:17.027608: Pseudo dice [0.8524] +2024-11-21 11:17:17.027692: Epoch time: 17.16 s +2024-11-21 11:17:17.028002: Yayy! New best EMA pseudo Dice: 0.8271 +2024-11-21 11:17:18.161293: +2024-11-21 11:17:18.161512: Epoch 112 +2024-11-21 11:17:18.161623: Current learning rate: 0.00987 +2024-11-21 11:17:36.896207: train_loss -0.7452 +2024-11-21 11:17:36.896418: val_loss -0.7194 +2024-11-21 11:17:36.896502: Pseudo dice [0.8479] +2024-11-21 11:17:36.911094: Epoch time: 18.74 s +2024-11-21 11:17:36.911202: Yayy! New best EMA pseudo Dice: 0.8292 +2024-11-21 11:17:37.965754: +2024-11-21 11:17:37.966022: Epoch 113 +2024-11-21 11:17:37.966135: Current learning rate: 0.00987 +2024-11-21 11:17:57.656600: train_loss -0.7493 +2024-11-21 11:17:57.656816: val_loss -0.7244 +2024-11-21 11:17:57.656895: Pseudo dice [0.821] +2024-11-21 11:17:57.656978: Epoch time: 19.69 s +2024-11-21 11:17:58.423073: +2024-11-21 11:17:58.423288: Epoch 114 +2024-11-21 11:17:58.423407: Current learning rate: 0.00987 +2024-11-21 11:18:16.028235: train_loss -0.7371 +2024-11-21 11:18:16.029110: val_loss -0.7268 +2024-11-21 11:18:16.029192: Pseudo dice [0.8369] +2024-11-21 11:18:16.029275: Epoch time: 17.61 s +2024-11-21 11:18:16.029337: Yayy! New best EMA pseudo Dice: 0.8292 +2024-11-21 11:18:17.068879: +2024-11-21 11:18:17.069089: Epoch 115 +2024-11-21 11:18:17.069203: Current learning rate: 0.00987 +2024-11-21 11:18:34.653866: train_loss -0.7498 +2024-11-21 11:18:34.654076: val_loss -0.7576 +2024-11-21 11:18:34.654148: Pseudo dice [0.8301] +2024-11-21 11:18:34.654222: Epoch time: 17.59 s +2024-11-21 11:18:34.654321: Yayy! New best EMA pseudo Dice: 0.8293 +2024-11-21 11:18:35.642053: +2024-11-21 11:18:35.642268: Epoch 116 +2024-11-21 11:18:35.642385: Current learning rate: 0.00987 +2024-11-21 11:18:55.049958: train_loss -0.7606 +2024-11-21 11:18:55.050179: val_loss -0.754 +2024-11-21 11:18:55.050253: Pseudo dice [0.8601] +2024-11-21 11:18:55.050329: Epoch time: 19.41 s +2024-11-21 11:18:55.050390: Yayy! New best EMA pseudo Dice: 0.8324 +2024-11-21 11:18:56.074711: +2024-11-21 11:18:56.075062: Epoch 117 +2024-11-21 11:18:56.075178: Current learning rate: 0.00987 +2024-11-21 11:19:15.530723: train_loss -0.7366 +2024-11-21 11:19:15.530997: val_loss -0.7437 +2024-11-21 11:19:15.531075: Pseudo dice [0.8365] +2024-11-21 11:19:15.531156: Epoch time: 19.46 s +2024-11-21 11:19:15.531220: Yayy! New best EMA pseudo Dice: 0.8328 +2024-11-21 11:19:16.912261: +2024-11-21 11:19:16.912550: Epoch 118 +2024-11-21 11:19:16.912666: Current learning rate: 0.00987 +2024-11-21 11:19:36.016380: train_loss -0.7461 +2024-11-21 11:19:36.020054: val_loss -0.7186 +2024-11-21 11:19:36.020178: Pseudo dice [0.8264] +2024-11-21 11:19:36.020268: Epoch time: 19.1 s +2024-11-21 11:19:36.812578: +2024-11-21 11:19:36.812785: Epoch 119 +2024-11-21 11:19:36.812960: Current learning rate: 0.00987 +2024-11-21 11:19:54.968472: train_loss -0.7488 +2024-11-21 11:19:54.970878: val_loss -0.7214 +2024-11-21 11:19:54.970967: Pseudo dice [0.8138] +2024-11-21 11:19:54.971052: Epoch time: 18.16 s +2024-11-21 11:19:55.775015: +2024-11-21 11:19:55.775249: Epoch 120 +2024-11-21 11:19:55.775361: Current learning rate: 0.00986 +2024-11-21 11:20:13.615014: train_loss -0.7408 +2024-11-21 11:20:13.615222: val_loss -0.7281 +2024-11-21 11:20:13.615299: Pseudo dice [0.8343] +2024-11-21 11:20:13.615378: Epoch time: 17.84 s +2024-11-21 11:20:14.392126: +2024-11-21 11:20:14.392336: Epoch 121 +2024-11-21 11:20:14.392445: Current learning rate: 0.00986 +2024-11-21 11:20:32.311050: train_loss -0.7432 +2024-11-21 11:20:32.311309: val_loss -0.7395 +2024-11-21 11:20:32.311390: Pseudo dice [0.8329] +2024-11-21 11:20:32.315778: Epoch time: 17.92 s +2024-11-21 11:20:33.268337: +2024-11-21 11:20:33.268535: Epoch 122 +2024-11-21 11:20:33.268647: Current learning rate: 0.00986 +2024-11-21 11:20:51.887923: train_loss -0.7387 +2024-11-21 11:20:51.888144: val_loss -0.7317 +2024-11-21 11:20:51.888218: Pseudo dice [0.8094] +2024-11-21 11:20:51.888294: Epoch time: 18.62 s +2024-11-21 11:20:52.848495: +2024-11-21 11:20:52.848702: Epoch 123 +2024-11-21 11:20:52.848818: Current learning rate: 0.00986 +2024-11-21 11:21:11.155964: train_loss -0.7363 +2024-11-21 11:21:11.156191: val_loss -0.751 +2024-11-21 11:21:11.156271: Pseudo dice [0.8246] +2024-11-21 11:21:11.156347: Epoch time: 18.31 s +2024-11-21 11:21:12.043402: +2024-11-21 11:21:12.043589: Epoch 124 +2024-11-21 11:21:12.043701: Current learning rate: 0.00986 +2024-11-21 11:21:31.240309: train_loss -0.7402 +2024-11-21 11:21:31.240533: val_loss -0.7114 +2024-11-21 11:21:31.240608: Pseudo dice [0.8184] +2024-11-21 11:21:31.240688: Epoch time: 19.2 s +2024-11-21 11:21:32.022499: +2024-11-21 11:21:32.022733: Epoch 125 +2024-11-21 11:21:32.022855: Current learning rate: 0.00986 +2024-11-21 11:21:51.765394: train_loss -0.7483 +2024-11-21 11:21:51.765634: val_loss -0.7308 +2024-11-21 11:21:51.765707: Pseudo dice [0.8402] +2024-11-21 11:21:51.765788: Epoch time: 19.74 s +2024-11-21 11:21:52.544057: +2024-11-21 11:21:52.544256: Epoch 126 +2024-11-21 11:21:52.544365: Current learning rate: 0.00986 +2024-11-21 11:22:11.091686: train_loss -0.7461 +2024-11-21 11:22:11.091907: val_loss -0.7538 +2024-11-21 11:22:11.091983: Pseudo dice [0.839] +2024-11-21 11:22:11.092067: Epoch time: 18.55 s +2024-11-21 11:22:11.869853: +2024-11-21 11:22:11.870045: Epoch 127 +2024-11-21 11:22:11.870161: Current learning rate: 0.00986 +2024-11-21 11:22:30.894314: train_loss -0.7481 +2024-11-21 11:22:30.894536: val_loss -0.7486 +2024-11-21 11:22:30.894612: Pseudo dice [0.8246] +2024-11-21 11:22:30.894689: Epoch time: 19.03 s +2024-11-21 11:22:31.674306: +2024-11-21 11:22:31.674486: Epoch 128 +2024-11-21 11:22:31.674596: Current learning rate: 0.00986 +2024-11-21 11:22:49.430703: train_loss -0.7401 +2024-11-21 11:22:49.430939: val_loss -0.7296 +2024-11-21 11:22:49.431021: Pseudo dice [0.8362] +2024-11-21 11:22:49.431106: Epoch time: 17.76 s +2024-11-21 11:22:50.640276: +2024-11-21 11:22:50.640501: Epoch 129 +2024-11-21 11:22:50.640615: Current learning rate: 0.00985 +2024-11-21 11:23:10.380579: train_loss -0.7398 +2024-11-21 11:23:10.380798: val_loss -0.7295 +2024-11-21 11:23:10.380875: Pseudo dice [0.8186] +2024-11-21 11:23:10.380950: Epoch time: 19.74 s +2024-11-21 11:23:11.160818: +2024-11-21 11:23:11.161043: Epoch 130 +2024-11-21 11:23:11.161157: Current learning rate: 0.00985 +2024-11-21 11:23:30.104739: train_loss -0.7393 +2024-11-21 11:23:30.104960: val_loss -0.729 +2024-11-21 11:23:30.105051: Pseudo dice [0.8399] +2024-11-21 11:23:30.105135: Epoch time: 18.94 s +2024-11-21 11:23:30.957727: +2024-11-21 11:23:30.957962: Epoch 131 +2024-11-21 11:23:30.958091: Current learning rate: 0.00985 +2024-11-21 11:23:50.287862: train_loss -0.7499 +2024-11-21 11:23:50.288085: val_loss -0.7388 +2024-11-21 11:23:50.288160: Pseudo dice [0.825] +2024-11-21 11:23:50.288239: Epoch time: 19.33 s +2024-11-21 11:23:51.068095: +2024-11-21 11:23:51.068331: Epoch 132 +2024-11-21 11:23:51.068446: Current learning rate: 0.00985 +2024-11-21 11:24:10.579003: train_loss -0.76 +2024-11-21 11:24:10.579265: val_loss -0.7284 +2024-11-21 11:24:10.579342: Pseudo dice [0.8152] +2024-11-21 11:24:10.579426: Epoch time: 19.51 s +2024-11-21 11:24:11.506881: +2024-11-21 11:24:11.507139: Epoch 133 +2024-11-21 11:24:11.507254: Current learning rate: 0.00985 +2024-11-21 11:24:30.929374: train_loss -0.7466 +2024-11-21 11:24:30.929633: val_loss -0.737 +2024-11-21 11:24:30.929722: Pseudo dice [0.8164] +2024-11-21 11:24:30.929804: Epoch time: 19.42 s +2024-11-21 11:24:31.708939: +2024-11-21 11:24:31.709157: Epoch 134 +2024-11-21 11:24:31.709273: Current learning rate: 0.00985 +2024-11-21 11:24:49.445438: train_loss -0.7573 +2024-11-21 11:24:49.445624: val_loss -0.7425 +2024-11-21 11:24:49.445698: Pseudo dice [0.8417] +2024-11-21 11:24:49.445776: Epoch time: 17.74 s +2024-11-21 11:24:50.240281: +2024-11-21 11:24:50.240498: Epoch 135 +2024-11-21 11:24:50.240608: Current learning rate: 0.00985 +2024-11-21 11:25:10.329698: train_loss -0.7447 +2024-11-21 11:25:10.329938: val_loss -0.724 +2024-11-21 11:25:10.330018: Pseudo dice [0.8408] +2024-11-21 11:25:10.330094: Epoch time: 20.09 s +2024-11-21 11:25:11.124247: +2024-11-21 11:25:11.124460: Epoch 136 +2024-11-21 11:25:11.124573: Current learning rate: 0.00985 +2024-11-21 11:25:29.670533: train_loss -0.7421 +2024-11-21 11:25:29.670767: val_loss -0.7335 +2024-11-21 11:25:29.670842: Pseudo dice [0.8381] +2024-11-21 11:25:29.670921: Epoch time: 18.55 s +2024-11-21 11:25:30.556459: +2024-11-21 11:25:30.556655: Epoch 137 +2024-11-21 11:25:30.556768: Current learning rate: 0.00985 +2024-11-21 11:25:48.819292: train_loss -0.7471 +2024-11-21 11:25:48.819504: val_loss -0.7085 +2024-11-21 11:25:48.819578: Pseudo dice [0.8303] +2024-11-21 11:25:48.819653: Epoch time: 18.26 s +2024-11-21 11:25:49.599652: +2024-11-21 11:25:49.599858: Epoch 138 +2024-11-21 11:25:49.599968: Current learning rate: 0.00984 +2024-11-21 11:26:07.520761: train_loss -0.7551 +2024-11-21 11:26:07.523134: val_loss -0.706 +2024-11-21 11:26:07.534192: Pseudo dice [0.8042] +2024-11-21 11:26:07.534289: Epoch time: 17.92 s +2024-11-21 11:26:08.386836: +2024-11-21 11:26:08.387054: Epoch 139 +2024-11-21 11:26:08.387169: Current learning rate: 0.00984 +2024-11-21 11:26:27.938677: train_loss -0.7409 +2024-11-21 11:26:27.944083: val_loss -0.7318 +2024-11-21 11:26:27.944245: Pseudo dice [0.8052] +2024-11-21 11:26:27.944341: Epoch time: 19.55 s +2024-11-21 11:26:29.062452: +2024-11-21 11:26:29.062638: Epoch 140 +2024-11-21 11:26:29.062754: Current learning rate: 0.00984 +2024-11-21 11:26:47.507852: train_loss -0.7486 +2024-11-21 11:26:47.508077: val_loss -0.7231 +2024-11-21 11:26:47.508149: Pseudo dice [0.8054] +2024-11-21 11:26:47.508221: Epoch time: 18.45 s +2024-11-21 11:26:48.371965: +2024-11-21 11:26:48.372191: Epoch 141 +2024-11-21 11:26:48.372304: Current learning rate: 0.00984 +2024-11-21 11:27:07.445062: train_loss -0.7395 +2024-11-21 11:27:07.445282: val_loss -0.6819 +2024-11-21 11:27:07.445355: Pseudo dice [0.797] +2024-11-21 11:27:07.445434: Epoch time: 19.07 s +2024-11-21 11:27:08.325532: +2024-11-21 11:27:08.325756: Epoch 142 +2024-11-21 11:27:08.325879: Current learning rate: 0.00984 +2024-11-21 11:27:27.079711: train_loss -0.7264 +2024-11-21 11:27:27.079960: val_loss -0.7327 +2024-11-21 11:27:27.080042: Pseudo dice [0.8041] +2024-11-21 11:27:27.080125: Epoch time: 18.75 s +2024-11-21 11:27:27.868923: +2024-11-21 11:27:27.869114: Epoch 143 +2024-11-21 11:27:27.869220: Current learning rate: 0.00984 +2024-11-21 11:27:46.531373: train_loss -0.7343 +2024-11-21 11:27:46.531584: val_loss -0.718 +2024-11-21 11:27:46.531660: Pseudo dice [0.8303] +2024-11-21 11:27:46.531736: Epoch time: 18.66 s +2024-11-21 11:27:47.312693: +2024-11-21 11:27:47.312881: Epoch 144 +2024-11-21 11:27:47.312989: Current learning rate: 0.00984 +2024-11-21 11:28:06.420739: train_loss -0.7442 +2024-11-21 11:28:06.420948: val_loss -0.7511 +2024-11-21 11:28:06.421030: Pseudo dice [0.8268] +2024-11-21 11:28:06.421108: Epoch time: 19.11 s +2024-11-21 11:28:07.228596: +2024-11-21 11:28:07.228903: Epoch 145 +2024-11-21 11:28:07.229020: Current learning rate: 0.00984 +2024-11-21 11:28:25.209946: train_loss -0.7405 +2024-11-21 11:28:25.210155: val_loss -0.7449 +2024-11-21 11:28:25.210229: Pseudo dice [0.8528] +2024-11-21 11:28:25.210304: Epoch time: 17.98 s +2024-11-21 11:28:25.982381: +2024-11-21 11:28:25.982584: Epoch 146 +2024-11-21 11:28:25.982695: Current learning rate: 0.00984 +2024-11-21 11:28:44.639377: train_loss -0.7501 +2024-11-21 11:28:44.639624: val_loss -0.7469 +2024-11-21 11:28:44.639694: Pseudo dice [0.8186] +2024-11-21 11:28:44.639777: Epoch time: 18.66 s +2024-11-21 11:28:45.419333: +2024-11-21 11:28:45.419537: Epoch 147 +2024-11-21 11:28:45.419652: Current learning rate: 0.00983 +2024-11-21 11:29:04.236627: train_loss -0.7465 +2024-11-21 11:29:04.236835: val_loss -0.744 +2024-11-21 11:29:04.236929: Pseudo dice [0.8303] +2024-11-21 11:29:04.237013: Epoch time: 18.82 s +2024-11-21 11:29:05.013391: +2024-11-21 11:29:05.013585: Epoch 148 +2024-11-21 11:29:05.013700: Current learning rate: 0.00983 +2024-11-21 11:29:23.429107: train_loss -0.7318 +2024-11-21 11:29:23.429389: val_loss -0.7009 +2024-11-21 11:29:23.429476: Pseudo dice [0.8075] +2024-11-21 11:29:23.429554: Epoch time: 18.42 s +2024-11-21 11:29:24.218740: +2024-11-21 11:29:24.218932: Epoch 149 +2024-11-21 11:29:24.219260: Current learning rate: 0.00983 +2024-11-21 11:29:42.609555: train_loss -0.7321 +2024-11-21 11:29:42.609768: val_loss -0.7099 +2024-11-21 11:29:42.609844: Pseudo dice [0.8033] +2024-11-21 11:29:42.609924: Epoch time: 18.39 s +2024-11-21 11:29:43.606282: +2024-11-21 11:29:43.606489: Epoch 150 +2024-11-21 11:29:43.606604: Current learning rate: 0.00983 +2024-11-21 11:30:02.028727: train_loss -0.735 +2024-11-21 11:30:02.028974: val_loss -0.7078 +2024-11-21 11:30:02.029060: Pseudo dice [0.8249] +2024-11-21 11:30:02.029143: Epoch time: 18.42 s +2024-11-21 11:30:02.816256: +2024-11-21 11:30:02.816445: Epoch 151 +2024-11-21 11:30:02.816555: Current learning rate: 0.00983 +2024-11-21 11:30:22.007350: train_loss -0.7366 +2024-11-21 11:30:22.007571: val_loss -0.7358 +2024-11-21 11:30:22.007644: Pseudo dice [0.8366] +2024-11-21 11:30:22.007720: Epoch time: 19.19 s +2024-11-21 11:30:23.319139: +2024-11-21 11:30:23.319360: Epoch 152 +2024-11-21 11:30:23.319480: Current learning rate: 0.00983 +2024-11-21 11:30:41.375881: train_loss -0.741 +2024-11-21 11:30:41.376106: val_loss -0.7186 +2024-11-21 11:30:41.376179: Pseudo dice [0.826] +2024-11-21 11:30:41.376254: Epoch time: 18.06 s +2024-11-21 11:30:42.159097: +2024-11-21 11:30:42.159303: Epoch 153 +2024-11-21 11:30:42.159422: Current learning rate: 0.00983 +2024-11-21 11:31:00.902943: train_loss -0.7471 +2024-11-21 11:31:00.903229: val_loss -0.7234 +2024-11-21 11:31:00.903313: Pseudo dice [0.8182] +2024-11-21 11:31:00.903401: Epoch time: 18.74 s +2024-11-21 11:31:01.698868: +2024-11-21 11:31:01.699068: Epoch 154 +2024-11-21 11:31:01.699185: Current learning rate: 0.00983 +2024-11-21 11:31:21.039175: train_loss -0.7436 +2024-11-21 11:31:21.039386: val_loss -0.7305 +2024-11-21 11:31:21.039458: Pseudo dice [0.8357] +2024-11-21 11:31:21.039534: Epoch time: 19.34 s +2024-11-21 11:31:21.840136: +2024-11-21 11:31:21.840351: Epoch 155 +2024-11-21 11:31:21.840463: Current learning rate: 0.00983 +2024-11-21 11:31:40.447395: train_loss -0.7391 +2024-11-21 11:31:40.447605: val_loss -0.7254 +2024-11-21 11:31:40.447680: Pseudo dice [0.8326] +2024-11-21 11:31:40.447756: Epoch time: 18.61 s +2024-11-21 11:31:41.239723: +2024-11-21 11:31:41.239926: Epoch 156 +2024-11-21 11:31:41.240047: Current learning rate: 0.00982 +2024-11-21 11:31:58.930039: train_loss -0.738 +2024-11-21 11:31:58.930242: val_loss -0.7374 +2024-11-21 11:31:58.930313: Pseudo dice [0.8183] +2024-11-21 11:31:58.930387: Epoch time: 17.69 s +2024-11-21 11:31:59.720107: +2024-11-21 11:31:59.720298: Epoch 157 +2024-11-21 11:31:59.720406: Current learning rate: 0.00982 +2024-11-21 11:32:17.743705: train_loss -0.745 +2024-11-21 11:32:17.743940: val_loss -0.7299 +2024-11-21 11:32:17.744021: Pseudo dice [0.8409] +2024-11-21 11:32:17.744105: Epoch time: 18.02 s +2024-11-21 11:32:18.556736: +2024-11-21 11:32:18.556978: Epoch 158 +2024-11-21 11:32:18.557103: Current learning rate: 0.00982 +2024-11-21 11:32:37.941853: train_loss -0.7432 +2024-11-21 11:32:37.942065: val_loss -0.7524 +2024-11-21 11:32:37.942140: Pseudo dice [0.8258] +2024-11-21 11:32:37.942214: Epoch time: 19.39 s +2024-11-21 11:32:38.726896: +2024-11-21 11:32:38.727116: Epoch 159 +2024-11-21 11:32:38.727232: Current learning rate: 0.00982 +2024-11-21 11:32:56.890965: train_loss -0.7556 +2024-11-21 11:32:56.891175: val_loss -0.7518 +2024-11-21 11:32:56.891250: Pseudo dice [0.8441] +2024-11-21 11:32:56.891326: Epoch time: 18.16 s +2024-11-21 11:32:57.685937: +2024-11-21 11:32:57.686140: Epoch 160 +2024-11-21 11:32:57.686249: Current learning rate: 0.00982 +2024-11-21 11:33:15.939660: train_loss -0.7489 +2024-11-21 11:33:15.939924: val_loss -0.7103 +2024-11-21 11:33:15.940009: Pseudo dice [0.8036] +2024-11-21 11:33:15.940089: Epoch time: 18.25 s +2024-11-21 11:33:16.736823: +2024-11-21 11:33:16.737042: Epoch 161 +2024-11-21 11:33:16.737146: Current learning rate: 0.00982 +2024-11-21 11:33:36.160265: train_loss -0.7381 +2024-11-21 11:33:36.160495: val_loss -0.7154 +2024-11-21 11:33:36.160574: Pseudo dice [0.7978] +2024-11-21 11:33:36.160654: Epoch time: 19.42 s +2024-11-21 11:33:36.952320: +2024-11-21 11:33:36.952535: Epoch 162 +2024-11-21 11:33:36.952656: Current learning rate: 0.00982 +2024-11-21 11:33:56.158825: train_loss -0.749 +2024-11-21 11:33:56.159047: val_loss -0.7277 +2024-11-21 11:33:56.159124: Pseudo dice [0.8291] +2024-11-21 11:33:56.159199: Epoch time: 19.21 s +2024-11-21 11:33:57.274835: +2024-11-21 11:33:57.275062: Epoch 163 +2024-11-21 11:33:57.275176: Current learning rate: 0.00982 +2024-11-21 11:34:15.555779: train_loss -0.746 +2024-11-21 11:34:15.556012: val_loss -0.7099 +2024-11-21 11:34:15.556090: Pseudo dice [0.8452] +2024-11-21 11:34:15.556167: Epoch time: 18.28 s +2024-11-21 11:34:16.346647: +2024-11-21 11:34:16.346859: Epoch 164 +2024-11-21 11:34:16.346974: Current learning rate: 0.00982 +2024-11-21 11:34:34.811449: train_loss -0.7424 +2024-11-21 11:34:34.811688: val_loss -0.7259 +2024-11-21 11:34:34.811763: Pseudo dice [0.8261] +2024-11-21 11:34:34.811845: Epoch time: 18.47 s +2024-11-21 11:34:35.606606: +2024-11-21 11:34:35.606814: Epoch 165 +2024-11-21 11:34:35.606926: Current learning rate: 0.00981 +2024-11-21 11:34:54.182525: train_loss -0.7433 +2024-11-21 11:34:54.182737: val_loss -0.746 +2024-11-21 11:34:54.182810: Pseudo dice [0.8353] +2024-11-21 11:34:54.182887: Epoch time: 18.58 s +2024-11-21 11:34:54.966574: +2024-11-21 11:34:54.966788: Epoch 166 +2024-11-21 11:34:54.966894: Current learning rate: 0.00981 +2024-11-21 11:35:13.376951: train_loss -0.7571 +2024-11-21 11:35:13.377167: val_loss -0.736 +2024-11-21 11:35:13.377244: Pseudo dice [0.8216] +2024-11-21 11:35:13.377319: Epoch time: 18.41 s +2024-11-21 11:35:14.161715: +2024-11-21 11:35:14.161931: Epoch 167 +2024-11-21 11:35:14.162050: Current learning rate: 0.00981 +2024-11-21 11:35:32.929113: train_loss -0.7529 +2024-11-21 11:35:32.929325: val_loss -0.7339 +2024-11-21 11:35:32.929401: Pseudo dice [0.8466] +2024-11-21 11:35:32.929474: Epoch time: 18.77 s +2024-11-21 11:35:33.734171: +2024-11-21 11:35:33.734391: Epoch 168 +2024-11-21 11:35:33.734508: Current learning rate: 0.00981 +2024-11-21 11:35:52.219448: train_loss -0.7489 +2024-11-21 11:35:52.219740: val_loss -0.6935 +2024-11-21 11:35:52.219816: Pseudo dice [0.808] +2024-11-21 11:35:52.219899: Epoch time: 18.49 s +2024-11-21 11:35:53.029918: +2024-11-21 11:35:53.030129: Epoch 169 +2024-11-21 11:35:53.030242: Current learning rate: 0.00981 +2024-11-21 11:36:11.833194: train_loss -0.7435 +2024-11-21 11:36:11.833412: val_loss -0.7217 +2024-11-21 11:36:11.833488: Pseudo dice [0.8064] +2024-11-21 11:36:11.833566: Epoch time: 18.8 s +2024-11-21 11:36:12.618208: +2024-11-21 11:36:12.618559: Epoch 170 +2024-11-21 11:36:12.618679: Current learning rate: 0.00981 +2024-11-21 11:36:31.535842: train_loss -0.7538 +2024-11-21 11:36:31.541304: val_loss -0.7268 +2024-11-21 11:36:31.541445: Pseudo dice [0.8158] +2024-11-21 11:36:31.541526: Epoch time: 18.92 s +2024-11-21 11:36:32.368319: +2024-11-21 11:36:32.368501: Epoch 171 +2024-11-21 11:36:32.368609: Current learning rate: 0.00981 +2024-11-21 11:36:50.387299: train_loss -0.7426 +2024-11-21 11:36:50.387514: val_loss -0.7291 +2024-11-21 11:36:50.387588: Pseudo dice [0.844] +2024-11-21 11:36:50.387662: Epoch time: 18.02 s +2024-11-21 11:36:51.187820: +2024-11-21 11:36:51.188025: Epoch 172 +2024-11-21 11:36:51.188141: Current learning rate: 0.00981 +2024-11-21 11:37:10.268922: train_loss -0.7305 +2024-11-21 11:37:10.269164: val_loss -0.7545 +2024-11-21 11:37:10.269240: Pseudo dice [0.8271] +2024-11-21 11:37:10.269322: Epoch time: 19.08 s +2024-11-21 11:37:11.077826: +2024-11-21 11:37:11.078079: Epoch 173 +2024-11-21 11:37:11.078191: Current learning rate: 0.00981 +2024-11-21 11:37:30.282645: train_loss -0.7446 +2024-11-21 11:37:30.282857: val_loss -0.7509 +2024-11-21 11:37:30.282931: Pseudo dice [0.8298] +2024-11-21 11:37:30.283013: Epoch time: 19.21 s +2024-11-21 11:37:31.666847: +2024-11-21 11:37:31.667050: Epoch 174 +2024-11-21 11:37:31.667152: Current learning rate: 0.0098 +2024-11-21 11:37:49.222494: train_loss -0.7547 +2024-11-21 11:37:49.222734: val_loss -0.7283 +2024-11-21 11:37:49.222809: Pseudo dice [0.8359] +2024-11-21 11:37:49.222885: Epoch time: 17.56 s +2024-11-21 11:37:50.017960: +2024-11-21 11:37:50.018198: Epoch 175 +2024-11-21 11:37:50.018311: Current learning rate: 0.0098 +2024-11-21 11:38:08.747236: train_loss -0.7474 +2024-11-21 11:38:08.747471: val_loss -0.7318 +2024-11-21 11:38:08.747547: Pseudo dice [0.8413] +2024-11-21 11:38:08.747629: Epoch time: 18.73 s +2024-11-21 11:38:09.543077: +2024-11-21 11:38:09.543305: Epoch 176 +2024-11-21 11:38:09.543419: Current learning rate: 0.0098 +2024-11-21 11:38:27.964482: train_loss -0.7516 +2024-11-21 11:38:27.964688: val_loss -0.7481 +2024-11-21 11:38:27.964760: Pseudo dice [0.8427] +2024-11-21 11:38:27.965823: Epoch time: 18.42 s +2024-11-21 11:38:28.754075: +2024-11-21 11:38:28.754290: Epoch 177 +2024-11-21 11:38:28.754410: Current learning rate: 0.0098 +2024-11-21 11:38:47.723348: train_loss -0.7357 +2024-11-21 11:38:47.723563: val_loss -0.7282 +2024-11-21 11:38:47.723641: Pseudo dice [0.8444] +2024-11-21 11:38:47.723717: Epoch time: 18.97 s +2024-11-21 11:38:48.516512: +2024-11-21 11:38:48.516716: Epoch 178 +2024-11-21 11:38:48.516829: Current learning rate: 0.0098 +2024-11-21 11:39:06.153031: train_loss -0.7408 +2024-11-21 11:39:06.153250: val_loss -0.7216 +2024-11-21 11:39:06.153349: Pseudo dice [0.8167] +2024-11-21 11:39:06.153428: Epoch time: 17.64 s +2024-11-21 11:39:06.949013: +2024-11-21 11:39:06.949208: Epoch 179 +2024-11-21 11:39:06.949317: Current learning rate: 0.0098 +2024-11-21 11:39:26.229024: train_loss -0.7344 +2024-11-21 11:39:26.231744: val_loss -0.7282 +2024-11-21 11:39:26.231842: Pseudo dice [0.8265] +2024-11-21 11:39:26.231930: Epoch time: 19.28 s +2024-11-21 11:39:27.036603: +2024-11-21 11:39:27.036794: Epoch 180 +2024-11-21 11:39:27.036900: Current learning rate: 0.0098 +2024-11-21 11:39:45.702750: train_loss -0.7357 +2024-11-21 11:39:45.702967: val_loss -0.7264 +2024-11-21 11:39:45.703045: Pseudo dice [0.8084] +2024-11-21 11:39:45.703124: Epoch time: 18.67 s +2024-11-21 11:39:46.497126: +2024-11-21 11:39:46.497314: Epoch 181 +2024-11-21 11:39:46.497425: Current learning rate: 0.0098 +2024-11-21 11:40:04.810714: train_loss -0.7288 +2024-11-21 11:40:04.810928: val_loss -0.7518 +2024-11-21 11:40:04.811011: Pseudo dice [0.8594] +2024-11-21 11:40:04.811088: Epoch time: 18.31 s +2024-11-21 11:40:05.604764: +2024-11-21 11:40:05.604947: Epoch 182 +2024-11-21 11:40:05.605070: Current learning rate: 0.0098 +2024-11-21 11:40:23.674465: train_loss -0.7395 +2024-11-21 11:40:23.674668: val_loss -0.7551 +2024-11-21 11:40:23.676966: Pseudo dice [0.8444] +2024-11-21 11:40:23.677105: Epoch time: 18.07 s +2024-11-21 11:40:24.460096: +2024-11-21 11:40:24.460335: Epoch 183 +2024-11-21 11:40:24.460450: Current learning rate: 0.00979 +2024-11-21 11:40:42.640774: train_loss -0.7486 +2024-11-21 11:40:42.641036: val_loss -0.7217 +2024-11-21 11:40:42.641113: Pseudo dice [0.8303] +2024-11-21 11:40:42.641194: Epoch time: 18.18 s +2024-11-21 11:40:43.427291: +2024-11-21 11:40:43.427469: Epoch 184 +2024-11-21 11:40:43.427580: Current learning rate: 0.00979 +2024-11-21 11:41:02.195024: train_loss -0.7445 +2024-11-21 11:41:02.195237: val_loss -0.7286 +2024-11-21 11:41:02.195315: Pseudo dice [0.8484] +2024-11-21 11:41:02.195396: Epoch time: 18.77 s +2024-11-21 11:41:02.197534: Yayy! New best EMA pseudo Dice: 0.8334 +2024-11-21 11:41:03.227920: +2024-11-21 11:41:03.228131: Epoch 185 +2024-11-21 11:41:03.228244: Current learning rate: 0.00979 +2024-11-21 11:41:21.567127: train_loss -0.7573 +2024-11-21 11:41:21.567347: val_loss -0.7417 +2024-11-21 11:41:21.567422: Pseudo dice [0.8223] +2024-11-21 11:41:21.567495: Epoch time: 18.34 s +2024-11-21 11:41:22.753829: +2024-11-21 11:41:22.754057: Epoch 186 +2024-11-21 11:41:22.754171: Current learning rate: 0.00979 +2024-11-21 11:41:41.828036: train_loss -0.7452 +2024-11-21 11:41:41.828340: val_loss -0.7021 +2024-11-21 11:41:41.828420: Pseudo dice [0.8175] +2024-11-21 11:41:41.828509: Epoch time: 19.07 s +2024-11-21 11:41:42.700154: +2024-11-21 11:41:42.700437: Epoch 187 +2024-11-21 11:41:42.700551: Current learning rate: 0.00979 +2024-11-21 11:42:02.406289: train_loss -0.7494 +2024-11-21 11:42:02.406505: val_loss -0.7484 +2024-11-21 11:42:02.406579: Pseudo dice [0.8403] +2024-11-21 11:42:02.406657: Epoch time: 19.71 s +2024-11-21 11:42:03.209319: +2024-11-21 11:42:03.209526: Epoch 188 +2024-11-21 11:42:03.209637: Current learning rate: 0.00979 +2024-11-21 11:42:21.811972: train_loss -0.7486 +2024-11-21 11:42:21.812191: val_loss -0.7253 +2024-11-21 11:42:21.812266: Pseudo dice [0.818] +2024-11-21 11:42:21.812343: Epoch time: 18.6 s +2024-11-21 11:42:22.610306: +2024-11-21 11:42:22.610515: Epoch 189 +2024-11-21 11:42:22.610626: Current learning rate: 0.00979 +2024-11-21 11:42:41.041275: train_loss -0.7404 +2024-11-21 11:42:41.041515: val_loss -0.7221 +2024-11-21 11:42:41.041589: Pseudo dice [0.8486] +2024-11-21 11:42:41.041672: Epoch time: 18.43 s +2024-11-21 11:42:41.968798: +2024-11-21 11:42:41.969011: Epoch 190 +2024-11-21 11:42:41.969131: Current learning rate: 0.00979 +2024-11-21 11:42:59.565518: train_loss -0.7438 +2024-11-21 11:42:59.565730: val_loss -0.7397 +2024-11-21 11:42:59.565848: Pseudo dice [0.8354] +2024-11-21 11:42:59.565925: Epoch time: 17.6 s +2024-11-21 11:43:00.352077: +2024-11-21 11:43:00.352333: Epoch 191 +2024-11-21 11:43:00.352449: Current learning rate: 0.00978 +2024-11-21 11:43:19.617634: train_loss -0.7371 +2024-11-21 11:43:19.617850: val_loss -0.7396 +2024-11-21 11:43:19.617924: Pseudo dice [0.8369] +2024-11-21 11:43:19.618006: Epoch time: 19.27 s +2024-11-21 11:43:20.407218: +2024-11-21 11:43:20.407416: Epoch 192 +2024-11-21 11:43:20.407533: Current learning rate: 0.00978 +2024-11-21 11:43:39.629948: train_loss -0.7327 +2024-11-21 11:43:39.630230: val_loss -0.739 +2024-11-21 11:43:39.630304: Pseudo dice [0.8245] +2024-11-21 11:43:39.630378: Epoch time: 19.22 s +2024-11-21 11:43:40.447558: +2024-11-21 11:43:40.447764: Epoch 193 +2024-11-21 11:43:40.447879: Current learning rate: 0.00978 +2024-11-21 11:43:58.979206: train_loss -0.7372 +2024-11-21 11:43:58.979453: val_loss -0.7567 +2024-11-21 11:43:58.979592: Pseudo dice [0.8427] +2024-11-21 11:43:58.979680: Epoch time: 18.53 s +2024-11-21 11:43:59.771004: +2024-11-21 11:43:59.771207: Epoch 194 +2024-11-21 11:43:59.771322: Current learning rate: 0.00978 +2024-11-21 11:44:18.102522: train_loss -0.7396 +2024-11-21 11:44:18.102827: val_loss -0.7434 +2024-11-21 11:44:18.102907: Pseudo dice [0.8345] +2024-11-21 11:44:18.102983: Epoch time: 18.33 s +2024-11-21 11:44:18.892812: +2024-11-21 11:44:18.893047: Epoch 195 +2024-11-21 11:44:18.893162: Current learning rate: 0.00978 +2024-11-21 11:44:36.891654: train_loss -0.7453 +2024-11-21 11:44:36.891861: val_loss -0.7664 +2024-11-21 11:44:36.891940: Pseudo dice [0.8527] +2024-11-21 11:44:36.892022: Epoch time: 18.0 s +2024-11-21 11:44:36.892088: Yayy! New best EMA pseudo Dice: 0.8352 +2024-11-21 11:44:37.878986: +2024-11-21 11:44:37.879304: Epoch 196 +2024-11-21 11:44:37.879420: Current learning rate: 0.00978 +2024-11-21 11:44:56.658784: train_loss -0.7558 +2024-11-21 11:44:56.659002: val_loss -0.7203 +2024-11-21 11:44:56.659078: Pseudo dice [0.8194] +2024-11-21 11:44:56.659341: Epoch time: 18.78 s +2024-11-21 11:44:57.516123: +2024-11-21 11:44:57.516348: Epoch 197 +2024-11-21 11:44:57.516478: Current learning rate: 0.00978 +2024-11-21 11:45:15.429117: train_loss -0.7511 +2024-11-21 11:45:15.429340: val_loss -0.7507 +2024-11-21 11:45:15.429415: Pseudo dice [0.8552] +2024-11-21 11:45:15.429491: Epoch time: 17.91 s +2024-11-21 11:45:15.429550: Yayy! New best EMA pseudo Dice: 0.8358 +2024-11-21 11:45:16.511658: +2024-11-21 11:45:16.511873: Epoch 198 +2024-11-21 11:45:16.511987: Current learning rate: 0.00978 +2024-11-21 11:45:35.378637: train_loss -0.7451 +2024-11-21 11:45:35.379426: val_loss -0.724 +2024-11-21 11:45:35.379518: Pseudo dice [0.8278] +2024-11-21 11:45:35.379592: Epoch time: 18.87 s +2024-11-21 11:45:36.175019: +2024-11-21 11:45:36.175280: Epoch 199 +2024-11-21 11:45:36.175398: Current learning rate: 0.00978 +2024-11-21 11:45:54.486504: train_loss -0.7502 +2024-11-21 11:45:54.486714: val_loss -0.7542 +2024-11-21 11:45:54.486784: Pseudo dice [0.829] +2024-11-21 11:45:54.486863: Epoch time: 18.31 s +2024-11-21 11:45:55.486834: +2024-11-21 11:45:55.487037: Epoch 200 +2024-11-21 11:45:55.487152: Current learning rate: 0.00977 +2024-11-21 11:46:14.185834: train_loss -0.7494 +2024-11-21 11:46:14.188204: val_loss -0.7224 +2024-11-21 11:46:14.188299: Pseudo dice [0.8252] +2024-11-21 11:46:14.188385: Epoch time: 18.7 s +2024-11-21 11:46:15.189422: +2024-11-21 11:46:15.189642: Epoch 201 +2024-11-21 11:46:15.189762: Current learning rate: 0.00977 +2024-11-21 11:46:33.346344: train_loss -0.7424 +2024-11-21 11:46:33.346601: val_loss -0.7465 +2024-11-21 11:46:33.346676: Pseudo dice [0.8306] +2024-11-21 11:46:33.346754: Epoch time: 18.16 s +2024-11-21 11:46:34.135146: +2024-11-21 11:46:34.135358: Epoch 202 +2024-11-21 11:46:34.135473: Current learning rate: 0.00977 +2024-11-21 11:46:53.142931: train_loss -0.7496 +2024-11-21 11:46:53.143143: val_loss -0.7443 +2024-11-21 11:46:53.143217: Pseudo dice [0.8305] +2024-11-21 11:46:53.144399: Epoch time: 19.01 s +2024-11-21 11:46:53.990740: +2024-11-21 11:46:53.990968: Epoch 203 +2024-11-21 11:46:53.991097: Current learning rate: 0.00977 +2024-11-21 11:47:12.411765: train_loss -0.7543 +2024-11-21 11:47:12.411973: val_loss -0.7291 +2024-11-21 11:47:12.412055: Pseudo dice [0.8166] +2024-11-21 11:47:12.412137: Epoch time: 18.42 s +2024-11-21 11:47:13.265777: +2024-11-21 11:47:13.265966: Epoch 204 +2024-11-21 11:47:13.266085: Current learning rate: 0.00977 +2024-11-21 11:47:32.686565: train_loss -0.7461 +2024-11-21 11:47:32.686801: val_loss -0.7077 +2024-11-21 11:47:32.686875: Pseudo dice [0.8288] +2024-11-21 11:47:32.686957: Epoch time: 19.42 s +2024-11-21 11:47:33.480510: +2024-11-21 11:47:33.480731: Epoch 205 +2024-11-21 11:47:33.480847: Current learning rate: 0.00977 +2024-11-21 11:47:52.425105: train_loss -0.7486 +2024-11-21 11:47:52.425325: val_loss -0.6936 +2024-11-21 11:47:52.425403: Pseudo dice [0.8152] +2024-11-21 11:47:52.425485: Epoch time: 18.95 s +2024-11-21 11:47:53.207392: +2024-11-21 11:47:53.207607: Epoch 206 +2024-11-21 11:47:53.207727: Current learning rate: 0.00977 +2024-11-21 11:48:11.781309: train_loss -0.7545 +2024-11-21 11:48:11.781533: val_loss -0.7467 +2024-11-21 11:48:11.781607: Pseudo dice [0.8191] +2024-11-21 11:48:11.781685: Epoch time: 18.57 s +2024-11-21 11:48:12.545513: +2024-11-21 11:48:12.545725: Epoch 207 +2024-11-21 11:48:12.545834: Current learning rate: 0.00977 +2024-11-21 11:48:30.728061: train_loss -0.7504 +2024-11-21 11:48:30.728271: val_loss -0.7368 +2024-11-21 11:48:30.728345: Pseudo dice [0.8366] +2024-11-21 11:48:30.728422: Epoch time: 18.18 s +2024-11-21 11:48:31.489723: +2024-11-21 11:48:31.489936: Epoch 208 +2024-11-21 11:48:31.490050: Current learning rate: 0.00977 +2024-11-21 11:48:48.966841: train_loss -0.7568 +2024-11-21 11:48:48.967088: val_loss -0.7329 +2024-11-21 11:48:48.967169: Pseudo dice [0.8096] +2024-11-21 11:48:48.967246: Epoch time: 17.48 s +2024-11-21 11:48:49.880358: +2024-11-21 11:48:49.880663: Epoch 209 +2024-11-21 11:48:49.880784: Current learning rate: 0.00976 +2024-11-21 11:49:08.302670: train_loss -0.7508 +2024-11-21 11:49:08.302888: val_loss -0.7431 +2024-11-21 11:49:08.302965: Pseudo dice [0.8332] +2024-11-21 11:49:08.303060: Epoch time: 18.42 s +2024-11-21 11:49:09.064133: +2024-11-21 11:49:09.064408: Epoch 210 +2024-11-21 11:49:09.064523: Current learning rate: 0.00976 +2024-11-21 11:49:27.413183: train_loss -0.7587 +2024-11-21 11:49:27.413423: val_loss -0.7628 +2024-11-21 11:49:27.413495: Pseudo dice [0.8299] +2024-11-21 11:49:27.413575: Epoch time: 18.35 s +2024-11-21 11:49:28.260378: +2024-11-21 11:49:28.260597: Epoch 211 +2024-11-21 11:49:28.260715: Current learning rate: 0.00976 +2024-11-21 11:49:47.063125: train_loss -0.7434 +2024-11-21 11:49:47.063453: val_loss -0.716 +2024-11-21 11:49:47.063531: Pseudo dice [0.8106] +2024-11-21 11:49:47.063625: Epoch time: 18.8 s +2024-11-21 11:49:47.908650: +2024-11-21 11:49:47.908914: Epoch 212 +2024-11-21 11:49:47.909038: Current learning rate: 0.00976 +2024-11-21 11:50:06.464494: train_loss -0.7556 +2024-11-21 11:50:06.464710: val_loss -0.7457 +2024-11-21 11:50:06.464782: Pseudo dice [0.8115] +2024-11-21 11:50:06.464859: Epoch time: 18.56 s +2024-11-21 11:50:07.259903: +2024-11-21 11:50:07.260131: Epoch 213 +2024-11-21 11:50:07.260246: Current learning rate: 0.00976 +2024-11-21 11:50:26.529838: train_loss -0.7529 +2024-11-21 11:50:26.530060: val_loss -0.735 +2024-11-21 11:50:26.530133: Pseudo dice [0.8241] +2024-11-21 11:50:26.530207: Epoch time: 19.27 s +2024-11-21 11:50:27.294897: +2024-11-21 11:50:27.295124: Epoch 214 +2024-11-21 11:50:27.295238: Current learning rate: 0.00976 +2024-11-21 11:50:45.857435: train_loss -0.7545 +2024-11-21 11:50:45.857639: val_loss -0.7215 +2024-11-21 11:50:45.857710: Pseudo dice [0.8104] +2024-11-21 11:50:45.857785: Epoch time: 18.56 s +2024-11-21 11:50:46.726338: +2024-11-21 11:50:46.726551: Epoch 215 +2024-11-21 11:50:46.726664: Current learning rate: 0.00976 +2024-11-21 11:51:05.272075: train_loss -0.7509 +2024-11-21 11:51:05.272337: val_loss -0.7458 +2024-11-21 11:51:05.272413: Pseudo dice [0.8394] +2024-11-21 11:51:05.272500: Epoch time: 18.55 s +2024-11-21 11:51:06.252773: +2024-11-21 11:51:06.252965: Epoch 216 +2024-11-21 11:51:06.253082: Current learning rate: 0.00976 +2024-11-21 11:51:24.717206: train_loss -0.7356 +2024-11-21 11:51:24.717416: val_loss -0.7187 +2024-11-21 11:51:24.717490: Pseudo dice [0.8396] +2024-11-21 11:51:24.717563: Epoch time: 18.47 s +2024-11-21 11:51:25.486759: +2024-11-21 11:51:25.486973: Epoch 217 +2024-11-21 11:51:25.487092: Current learning rate: 0.00976 +2024-11-21 11:51:44.975884: train_loss -0.747 +2024-11-21 11:51:44.976138: val_loss -0.7184 +2024-11-21 11:51:44.976218: Pseudo dice [0.807] +2024-11-21 11:51:44.976300: Epoch time: 19.49 s +2024-11-21 11:51:45.925010: +2024-11-21 11:51:45.925246: Epoch 218 +2024-11-21 11:51:45.925364: Current learning rate: 0.00975 +2024-11-21 11:52:05.209533: train_loss -0.7433 +2024-11-21 11:52:05.209742: val_loss -0.7416 +2024-11-21 11:52:05.209813: Pseudo dice [0.8345] +2024-11-21 11:52:05.209887: Epoch time: 19.29 s +2024-11-21 11:52:06.064347: +2024-11-21 11:52:06.064579: Epoch 219 +2024-11-21 11:52:06.064698: Current learning rate: 0.00975 +2024-11-21 11:52:25.295637: train_loss -0.7421 +2024-11-21 11:52:25.295896: val_loss -0.7313 +2024-11-21 11:52:25.295972: Pseudo dice [0.8374] +2024-11-21 11:52:25.296064: Epoch time: 19.23 s +2024-11-21 11:52:26.257860: +2024-11-21 11:52:26.258070: Epoch 220 +2024-11-21 11:52:26.258180: Current learning rate: 0.00975 +2024-11-21 11:52:45.565848: train_loss -0.7433 +2024-11-21 11:52:45.569651: val_loss -0.7542 +2024-11-21 11:52:45.569777: Pseudo dice [0.8387] +2024-11-21 11:52:45.569858: Epoch time: 19.31 s +2024-11-21 11:52:46.360245: +2024-11-21 11:52:46.360467: Epoch 221 +2024-11-21 11:52:46.360584: Current learning rate: 0.00975 +2024-11-21 11:53:04.178865: train_loss -0.7513 +2024-11-21 11:53:04.179083: val_loss -0.7453 +2024-11-21 11:53:04.179164: Pseudo dice [0.8498] +2024-11-21 11:53:04.179240: Epoch time: 17.82 s +2024-11-21 11:53:04.942285: +2024-11-21 11:53:04.942512: Epoch 222 +2024-11-21 11:53:04.942629: Current learning rate: 0.00975 +2024-11-21 11:53:23.468582: train_loss -0.7502 +2024-11-21 11:53:23.468796: val_loss -0.7186 +2024-11-21 11:53:23.469177: Pseudo dice [0.814] +2024-11-21 11:53:23.469327: Epoch time: 18.53 s +2024-11-21 11:53:24.238894: +2024-11-21 11:53:24.239158: Epoch 223 +2024-11-21 11:53:24.239326: Current learning rate: 0.00975 +2024-11-21 11:53:42.837490: train_loss -0.7486 +2024-11-21 11:53:42.837725: val_loss -0.7453 +2024-11-21 11:53:42.837812: Pseudo dice [0.8155] +2024-11-21 11:53:42.837923: Epoch time: 18.6 s +2024-11-21 11:53:43.607815: +2024-11-21 11:53:43.608041: Epoch 224 +2024-11-21 11:53:43.608156: Current learning rate: 0.00975 +2024-11-21 11:54:02.492887: train_loss -0.7452 +2024-11-21 11:54:02.494709: val_loss -0.7326 +2024-11-21 11:54:02.494796: Pseudo dice [0.8253] +2024-11-21 11:54:02.494873: Epoch time: 18.89 s +2024-11-21 11:54:03.296805: +2024-11-21 11:54:03.297046: Epoch 225 +2024-11-21 11:54:03.297162: Current learning rate: 0.00975 +2024-11-21 11:54:21.055327: train_loss -0.7417 +2024-11-21 11:54:21.055534: val_loss -0.711 +2024-11-21 11:54:21.055604: Pseudo dice [0.8033] +2024-11-21 11:54:21.055680: Epoch time: 17.76 s +2024-11-21 11:54:21.823338: +2024-11-21 11:54:21.823554: Epoch 226 +2024-11-21 11:54:21.823682: Current learning rate: 0.00975 +2024-11-21 11:54:41.821295: train_loss -0.7481 +2024-11-21 11:54:41.826692: val_loss -0.7389 +2024-11-21 11:54:41.826806: Pseudo dice [0.8345] +2024-11-21 11:54:41.826887: Epoch time: 20.0 s +2024-11-21 11:54:42.613567: +2024-11-21 11:54:42.613856: Epoch 227 +2024-11-21 11:54:42.613975: Current learning rate: 0.00974 +2024-11-21 11:55:00.939078: train_loss -0.7556 +2024-11-21 11:55:00.939314: val_loss -0.7586 +2024-11-21 11:55:00.939388: Pseudo dice [0.8472] +2024-11-21 11:55:00.939467: Epoch time: 18.33 s +2024-11-21 11:55:01.716164: +2024-11-21 11:55:01.716475: Epoch 228 +2024-11-21 11:55:01.716592: Current learning rate: 0.00974 +2024-11-21 11:55:20.382850: train_loss -0.7557 +2024-11-21 11:55:20.383068: val_loss -0.7161 +2024-11-21 11:55:20.383143: Pseudo dice [0.8341] +2024-11-21 11:55:20.383221: Epoch time: 18.67 s +2024-11-21 11:55:21.153688: +2024-11-21 11:55:21.153888: Epoch 229 +2024-11-21 11:55:21.154004: Current learning rate: 0.00974 +2024-11-21 11:55:39.718124: train_loss -0.7567 +2024-11-21 11:55:39.718333: val_loss -0.7173 +2024-11-21 11:55:39.718412: Pseudo dice [0.7976] +2024-11-21 11:55:39.718491: Epoch time: 18.57 s +2024-11-21 11:55:40.483970: +2024-11-21 11:55:40.484180: Epoch 230 +2024-11-21 11:55:40.484292: Current learning rate: 0.00974 +2024-11-21 11:55:59.777073: train_loss -0.7562 +2024-11-21 11:55:59.777285: val_loss -0.7301 +2024-11-21 11:55:59.777382: Pseudo dice [0.8171] +2024-11-21 11:55:59.777464: Epoch time: 19.29 s +2024-11-21 11:56:00.546475: +2024-11-21 11:56:00.546780: Epoch 231 +2024-11-21 11:56:00.546891: Current learning rate: 0.00974 +2024-11-21 11:56:18.980889: train_loss -0.7591 +2024-11-21 11:56:18.981131: val_loss -0.7288 +2024-11-21 11:56:18.981208: Pseudo dice [0.8382] +2024-11-21 11:56:18.981293: Epoch time: 18.44 s +2024-11-21 11:56:19.745660: +2024-11-21 11:56:19.745864: Epoch 232 +2024-11-21 11:56:19.745980: Current learning rate: 0.00974 +2024-11-21 11:56:39.055460: train_loss -0.7529 +2024-11-21 11:56:39.055678: val_loss -0.7202 +2024-11-21 11:56:39.055752: Pseudo dice [0.805] +2024-11-21 11:56:39.055827: Epoch time: 19.31 s +2024-11-21 11:56:39.813697: +2024-11-21 11:56:39.813915: Epoch 233 +2024-11-21 11:56:39.814050: Current learning rate: 0.00974 +2024-11-21 11:56:58.009616: train_loss -0.7441 +2024-11-21 11:56:58.009826: val_loss -0.7338 +2024-11-21 11:56:58.009898: Pseudo dice [0.8405] +2024-11-21 11:56:58.009979: Epoch time: 18.2 s +2024-11-21 11:56:58.801971: +2024-11-21 11:56:58.802189: Epoch 234 +2024-11-21 11:56:58.802300: Current learning rate: 0.00974 +2024-11-21 11:57:17.390770: train_loss -0.7414 +2024-11-21 11:57:17.391030: val_loss -0.7098 +2024-11-21 11:57:17.391118: Pseudo dice [0.8405] +2024-11-21 11:57:17.391200: Epoch time: 18.59 s +2024-11-21 11:57:18.158646: +2024-11-21 11:57:18.158857: Epoch 235 +2024-11-21 11:57:18.158968: Current learning rate: 0.00974 +2024-11-21 11:57:36.514513: train_loss -0.7452 +2024-11-21 11:57:36.514740: val_loss -0.7536 +2024-11-21 11:57:36.516989: Pseudo dice [0.8259] +2024-11-21 11:57:36.517105: Epoch time: 18.36 s +2024-11-21 11:57:37.415013: +2024-11-21 11:57:37.415308: Epoch 236 +2024-11-21 11:57:37.415425: Current learning rate: 0.00973 +2024-11-21 11:57:55.418841: train_loss -0.7411 +2024-11-21 11:57:55.419071: val_loss -0.7268 +2024-11-21 11:57:55.419146: Pseudo dice [0.849] +2024-11-21 11:57:55.419219: Epoch time: 18.0 s +2024-11-21 11:57:56.413368: +2024-11-21 11:57:56.413577: Epoch 237 +2024-11-21 11:57:56.413692: Current learning rate: 0.00973 +2024-11-21 11:58:14.970699: train_loss -0.759 +2024-11-21 11:58:14.970919: val_loss -0.7154 +2024-11-21 11:58:14.970998: Pseudo dice [0.8113] +2024-11-21 11:58:14.976147: Epoch time: 18.56 s +2024-11-21 11:58:15.745441: +2024-11-21 11:58:15.745658: Epoch 238 +2024-11-21 11:58:15.745777: Current learning rate: 0.00973 +2024-11-21 11:58:34.933268: train_loss -0.7493 +2024-11-21 11:58:34.933571: val_loss -0.7485 +2024-11-21 11:58:34.933650: Pseudo dice [0.8372] +2024-11-21 11:58:34.933733: Epoch time: 19.19 s +2024-11-21 11:58:35.703417: +2024-11-21 11:58:35.703632: Epoch 239 +2024-11-21 11:58:35.703746: Current learning rate: 0.00973 +2024-11-21 11:58:53.942165: train_loss -0.7577 +2024-11-21 11:58:53.942371: val_loss -0.7168 +2024-11-21 11:58:53.942443: Pseudo dice [0.8219] +2024-11-21 11:58:53.942517: Epoch time: 18.24 s +2024-11-21 11:58:54.717751: +2024-11-21 11:58:54.717987: Epoch 240 +2024-11-21 11:58:54.718101: Current learning rate: 0.00973 +2024-11-21 11:59:14.431701: train_loss -0.747 +2024-11-21 11:59:14.431902: val_loss -0.7411 +2024-11-21 11:59:14.431976: Pseudo dice [0.8297] +2024-11-21 11:59:14.432060: Epoch time: 19.71 s +2024-11-21 11:59:15.305166: +2024-11-21 11:59:15.305370: Epoch 241 +2024-11-21 11:59:15.305480: Current learning rate: 0.00973 +2024-11-21 11:59:34.637089: train_loss -0.7599 +2024-11-21 11:59:34.637312: val_loss -0.7503 +2024-11-21 11:59:34.637385: Pseudo dice [0.8445] +2024-11-21 11:59:34.637466: Epoch time: 19.33 s +2024-11-21 11:59:35.410357: +2024-11-21 11:59:35.410551: Epoch 242 +2024-11-21 11:59:35.410663: Current learning rate: 0.00973 +2024-11-21 11:59:53.582787: train_loss -0.7547 +2024-11-21 11:59:53.583038: val_loss -0.7362 +2024-11-21 11:59:53.583117: Pseudo dice [0.8508] +2024-11-21 11:59:53.583204: Epoch time: 18.17 s +2024-11-21 11:59:54.359674: +2024-11-21 11:59:54.359897: Epoch 243 +2024-11-21 11:59:54.360024: Current learning rate: 0.00973 +2024-11-21 12:00:12.608396: train_loss -0.7547 +2024-11-21 12:00:12.608608: val_loss -0.7426 +2024-11-21 12:00:12.608685: Pseudo dice [0.8327] +2024-11-21 12:00:12.608764: Epoch time: 18.25 s +2024-11-21 12:00:13.388141: +2024-11-21 12:00:13.388381: Epoch 244 +2024-11-21 12:00:13.388493: Current learning rate: 0.00973 +2024-11-21 12:00:32.206710: train_loss -0.7563 +2024-11-21 12:00:32.206939: val_loss -0.7325 +2024-11-21 12:00:32.207023: Pseudo dice [0.8384] +2024-11-21 12:00:32.207108: Epoch time: 18.82 s +2024-11-21 12:00:33.001546: +2024-11-21 12:00:33.001765: Epoch 245 +2024-11-21 12:00:33.001873: Current learning rate: 0.00972 +2024-11-21 12:00:51.358193: train_loss -0.752 +2024-11-21 12:00:51.358432: val_loss -0.7446 +2024-11-21 12:00:51.358508: Pseudo dice [0.8292] +2024-11-21 12:00:51.358588: Epoch time: 18.36 s +2024-11-21 12:00:52.133245: +2024-11-21 12:00:52.133444: Epoch 246 +2024-11-21 12:00:52.133558: Current learning rate: 0.00972 +2024-11-21 12:01:10.951554: train_loss -0.7591 +2024-11-21 12:01:10.951756: val_loss -0.7346 +2024-11-21 12:01:10.951829: Pseudo dice [0.8318] +2024-11-21 12:01:10.951906: Epoch time: 18.82 s +2024-11-21 12:01:11.724285: +2024-11-21 12:01:11.724497: Epoch 247 +2024-11-21 12:01:11.724626: Current learning rate: 0.00972 +2024-11-21 12:01:29.488742: train_loss -0.7538 +2024-11-21 12:01:29.488959: val_loss -0.699 +2024-11-21 12:01:29.489043: Pseudo dice [0.8275] +2024-11-21 12:01:29.489120: Epoch time: 17.77 s +2024-11-21 12:01:30.397038: +2024-11-21 12:01:30.397321: Epoch 248 +2024-11-21 12:01:30.397431: Current learning rate: 0.00972 +2024-11-21 12:01:49.730105: train_loss -0.7569 +2024-11-21 12:01:49.733215: val_loss -0.722 +2024-11-21 12:01:49.733592: Pseudo dice [0.822] +2024-11-21 12:01:49.733692: Epoch time: 19.33 s +2024-11-21 12:01:50.549859: +2024-11-21 12:01:50.550220: Epoch 249 +2024-11-21 12:01:50.550340: Current learning rate: 0.00972 +2024-11-21 12:02:09.546637: train_loss -0.7481 +2024-11-21 12:02:09.546848: val_loss -0.7549 +2024-11-21 12:02:09.547275: Pseudo dice [0.8316] +2024-11-21 12:02:09.547361: Epoch time: 19.0 s +2024-11-21 12:02:10.630358: +2024-11-21 12:02:10.630572: Epoch 250 +2024-11-21 12:02:10.630688: Current learning rate: 0.00972 +2024-11-21 12:02:30.015013: train_loss -0.752 +2024-11-21 12:02:30.015225: val_loss -0.7444 +2024-11-21 12:02:30.015302: Pseudo dice [0.8349] +2024-11-21 12:02:30.015384: Epoch time: 19.39 s +2024-11-21 12:02:30.818154: +2024-11-21 12:02:30.818354: Epoch 251 +2024-11-21 12:02:30.818468: Current learning rate: 0.00972 +2024-11-21 12:02:49.509120: train_loss -0.7574 +2024-11-21 12:02:49.509335: val_loss -0.7382 +2024-11-21 12:02:49.509410: Pseudo dice [0.8311] +2024-11-21 12:02:49.509509: Epoch time: 18.69 s +2024-11-21 12:02:50.329013: +2024-11-21 12:02:50.329305: Epoch 252 +2024-11-21 12:02:50.329419: Current learning rate: 0.00972 +2024-11-21 12:03:09.010276: train_loss -0.757 +2024-11-21 12:03:09.012713: val_loss -0.7222 +2024-11-21 12:03:09.012802: Pseudo dice [0.8316] +2024-11-21 12:03:09.012884: Epoch time: 18.68 s +2024-11-21 12:03:09.788598: +2024-11-21 12:03:09.788818: Epoch 253 +2024-11-21 12:03:09.788931: Current learning rate: 0.00971 +2024-11-21 12:03:30.381592: train_loss -0.7556 +2024-11-21 12:03:30.383974: val_loss -0.729 +2024-11-21 12:03:30.384064: Pseudo dice [0.817] +2024-11-21 12:03:30.384144: Epoch time: 20.59 s +2024-11-21 12:03:31.210233: +2024-11-21 12:03:31.210439: Epoch 254 +2024-11-21 12:03:31.210555: Current learning rate: 0.00971 +2024-11-21 12:03:50.417549: train_loss -0.7564 +2024-11-21 12:03:50.417804: val_loss -0.7441 +2024-11-21 12:03:50.417881: Pseudo dice [0.8247] +2024-11-21 12:03:50.417956: Epoch time: 19.21 s +2024-11-21 12:03:51.211389: +2024-11-21 12:03:51.211602: Epoch 255 +2024-11-21 12:03:51.211713: Current learning rate: 0.00971 +2024-11-21 12:04:09.581943: train_loss -0.746 +2024-11-21 12:04:09.582198: val_loss -0.7552 +2024-11-21 12:04:09.582273: Pseudo dice [0.8426] +2024-11-21 12:04:09.582357: Epoch time: 18.37 s +2024-11-21 12:04:10.899066: +2024-11-21 12:04:10.899284: Epoch 256 +2024-11-21 12:04:10.899397: Current learning rate: 0.00971 +2024-11-21 12:04:29.249124: train_loss -0.7525 +2024-11-21 12:04:29.251531: val_loss -0.7414 +2024-11-21 12:04:29.251681: Pseudo dice [0.821] +2024-11-21 12:04:29.251760: Epoch time: 18.35 s +2024-11-21 12:04:30.187604: +2024-11-21 12:04:30.187833: Epoch 257 +2024-11-21 12:04:30.187948: Current learning rate: 0.00971 +2024-11-21 12:04:47.773155: train_loss -0.7475 +2024-11-21 12:04:47.773376: val_loss -0.7209 +2024-11-21 12:04:47.773450: Pseudo dice [0.822] +2024-11-21 12:04:47.773528: Epoch time: 17.59 s +2024-11-21 12:04:48.563812: +2024-11-21 12:04:48.564023: Epoch 258 +2024-11-21 12:04:48.564137: Current learning rate: 0.00971 +2024-11-21 12:05:07.359729: train_loss -0.7478 +2024-11-21 12:05:07.359982: val_loss -0.7015 +2024-11-21 12:05:07.360068: Pseudo dice [0.783] +2024-11-21 12:05:07.360152: Epoch time: 18.8 s +2024-11-21 12:05:08.154480: +2024-11-21 12:05:08.154707: Epoch 259 +2024-11-21 12:05:08.154819: Current learning rate: 0.00971 +2024-11-21 12:05:26.923639: train_loss -0.7537 +2024-11-21 12:05:26.923846: val_loss -0.7278 +2024-11-21 12:05:26.923920: Pseudo dice [0.8211] +2024-11-21 12:05:26.924005: Epoch time: 18.77 s +2024-11-21 12:05:27.713514: +2024-11-21 12:05:27.713794: Epoch 260 +2024-11-21 12:05:27.713909: Current learning rate: 0.00971 +2024-11-21 12:05:46.440716: train_loss -0.7545 +2024-11-21 12:05:46.440925: val_loss -0.7414 +2024-11-21 12:05:46.441003: Pseudo dice [0.8402] +2024-11-21 12:05:46.441078: Epoch time: 18.73 s +2024-11-21 12:05:47.269573: +2024-11-21 12:05:47.269781: Epoch 261 +2024-11-21 12:05:47.269890: Current learning rate: 0.00971 +2024-11-21 12:06:06.162152: train_loss -0.7342 +2024-11-21 12:06:06.162362: val_loss -0.7406 +2024-11-21 12:06:06.162457: Pseudo dice [0.8236] +2024-11-21 12:06:06.162579: Epoch time: 18.89 s +2024-11-21 12:06:06.961857: +2024-11-21 12:06:06.962101: Epoch 262 +2024-11-21 12:06:06.962243: Current learning rate: 0.0097 +2024-11-21 12:06:24.758042: train_loss -0.7612 +2024-11-21 12:06:24.758285: val_loss -0.7262 +2024-11-21 12:06:24.758362: Pseudo dice [0.8332] +2024-11-21 12:06:24.758444: Epoch time: 17.8 s +2024-11-21 12:06:25.552602: +2024-11-21 12:06:25.552823: Epoch 263 +2024-11-21 12:06:25.552939: Current learning rate: 0.0097 +2024-11-21 12:06:44.105597: train_loss -0.7474 +2024-11-21 12:06:44.105809: val_loss -0.7375 +2024-11-21 12:06:44.105883: Pseudo dice [0.8288] +2024-11-21 12:06:44.105961: Epoch time: 18.55 s +2024-11-21 12:06:44.883061: +2024-11-21 12:06:44.883283: Epoch 264 +2024-11-21 12:06:44.883401: Current learning rate: 0.0097 +2024-11-21 12:07:03.766228: train_loss -0.7601 +2024-11-21 12:07:03.766442: val_loss -0.7475 +2024-11-21 12:07:03.766515: Pseudo dice [0.8244] +2024-11-21 12:07:03.766590: Epoch time: 18.88 s +2024-11-21 12:07:04.544857: +2024-11-21 12:07:04.545067: Epoch 265 +2024-11-21 12:07:04.545180: Current learning rate: 0.0097 +2024-11-21 12:07:22.951684: train_loss -0.7506 +2024-11-21 12:07:22.951897: val_loss -0.741 +2024-11-21 12:07:22.951971: Pseudo dice [0.8482] +2024-11-21 12:07:22.952058: Epoch time: 18.41 s +2024-11-21 12:07:23.724494: +2024-11-21 12:07:23.724684: Epoch 266 +2024-11-21 12:07:23.724795: Current learning rate: 0.0097 +2024-11-21 12:07:41.922719: train_loss -0.756 +2024-11-21 12:07:41.922959: val_loss -0.7288 +2024-11-21 12:07:41.923044: Pseudo dice [0.824] +2024-11-21 12:07:41.923126: Epoch time: 18.2 s +2024-11-21 12:07:42.714390: +2024-11-21 12:07:42.714581: Epoch 267 +2024-11-21 12:07:42.714693: Current learning rate: 0.0097 +2024-11-21 12:08:01.544751: train_loss -0.738 +2024-11-21 12:08:01.544968: val_loss -0.7244 +2024-11-21 12:08:01.545050: Pseudo dice [0.8331] +2024-11-21 12:08:01.545126: Epoch time: 18.83 s +2024-11-21 12:08:02.741154: +2024-11-21 12:08:02.741393: Epoch 268 +2024-11-21 12:08:02.741507: Current learning rate: 0.0097 +2024-11-21 12:08:21.411733: train_loss -0.7427 +2024-11-21 12:08:21.411952: val_loss -0.7457 +2024-11-21 12:08:21.412036: Pseudo dice [0.8366] +2024-11-21 12:08:21.412194: Epoch time: 18.67 s +2024-11-21 12:08:22.321780: +2024-11-21 12:08:22.322029: Epoch 269 +2024-11-21 12:08:22.322186: Current learning rate: 0.0097 +2024-11-21 12:08:42.087173: train_loss -0.7432 +2024-11-21 12:08:42.087384: val_loss -0.7256 +2024-11-21 12:08:42.087456: Pseudo dice [0.8413] +2024-11-21 12:08:42.087531: Epoch time: 19.77 s +2024-11-21 12:08:43.106436: +2024-11-21 12:08:43.106683: Epoch 270 +2024-11-21 12:08:43.106800: Current learning rate: 0.0097 +2024-11-21 12:09:01.615634: train_loss -0.7463 +2024-11-21 12:09:01.615844: val_loss -0.7369 +2024-11-21 12:09:01.615921: Pseudo dice [0.8387] +2024-11-21 12:09:01.616004: Epoch time: 18.51 s +2024-11-21 12:09:02.480275: +2024-11-21 12:09:02.480505: Epoch 271 +2024-11-21 12:09:02.480618: Current learning rate: 0.00969 +2024-11-21 12:09:20.884579: train_loss -0.7583 +2024-11-21 12:09:20.884794: val_loss -0.727 +2024-11-21 12:09:20.884867: Pseudo dice [0.82] +2024-11-21 12:09:20.884941: Epoch time: 18.41 s +2024-11-21 12:09:21.754101: +2024-11-21 12:09:21.754344: Epoch 272 +2024-11-21 12:09:21.754463: Current learning rate: 0.00969 +2024-11-21 12:09:39.813682: train_loss -0.7589 +2024-11-21 12:09:39.813940: val_loss -0.7393 +2024-11-21 12:09:39.814074: Pseudo dice [0.8339] +2024-11-21 12:09:39.814163: Epoch time: 18.06 s +2024-11-21 12:09:40.607763: +2024-11-21 12:09:40.607972: Epoch 273 +2024-11-21 12:09:40.608084: Current learning rate: 0.00969 +2024-11-21 12:09:59.024931: train_loss -0.7568 +2024-11-21 12:09:59.025163: val_loss -0.7127 +2024-11-21 12:09:59.025238: Pseudo dice [0.8338] +2024-11-21 12:09:59.025316: Epoch time: 18.42 s +2024-11-21 12:09:59.806571: +2024-11-21 12:09:59.806778: Epoch 274 +2024-11-21 12:09:59.806891: Current learning rate: 0.00969 +2024-11-21 12:10:19.110450: train_loss -0.7677 +2024-11-21 12:10:19.110690: val_loss -0.7557 +2024-11-21 12:10:19.110768: Pseudo dice [0.8472] +2024-11-21 12:10:19.111076: Epoch time: 19.3 s +2024-11-21 12:10:19.905149: +2024-11-21 12:10:19.905350: Epoch 275 +2024-11-21 12:10:19.905462: Current learning rate: 0.00969 +2024-11-21 12:10:39.309201: train_loss -0.7567 +2024-11-21 12:10:39.309423: val_loss -0.7592 +2024-11-21 12:10:39.309501: Pseudo dice [0.8383] +2024-11-21 12:10:39.311777: Epoch time: 19.4 s +2024-11-21 12:10:40.124948: +2024-11-21 12:10:40.125173: Epoch 276 +2024-11-21 12:10:40.125290: Current learning rate: 0.00969 +2024-11-21 12:10:59.287532: train_loss -0.7601 +2024-11-21 12:10:59.287775: val_loss -0.7295 +2024-11-21 12:10:59.287859: Pseudo dice [0.8309] +2024-11-21 12:10:59.287941: Epoch time: 19.16 s +2024-11-21 12:11:00.066956: +2024-11-21 12:11:00.067228: Epoch 277 +2024-11-21 12:11:00.067348: Current learning rate: 0.00969 +2024-11-21 12:11:18.067895: train_loss -0.761 +2024-11-21 12:11:18.068219: val_loss -0.7206 +2024-11-21 12:11:18.068300: Pseudo dice [0.8407] +2024-11-21 12:11:18.068376: Epoch time: 18.0 s +2024-11-21 12:11:18.880490: +2024-11-21 12:11:18.880715: Epoch 278 +2024-11-21 12:11:18.880827: Current learning rate: 0.00969 +2024-11-21 12:11:37.806247: train_loss -0.76 +2024-11-21 12:11:37.806454: val_loss -0.7298 +2024-11-21 12:11:37.806529: Pseudo dice [0.8244] +2024-11-21 12:11:37.806604: Epoch time: 18.93 s +2024-11-21 12:11:38.692192: +2024-11-21 12:11:38.692425: Epoch 279 +2024-11-21 12:11:38.692541: Current learning rate: 0.00969 +2024-11-21 12:11:56.696508: train_loss -0.7638 +2024-11-21 12:11:56.696718: val_loss -0.7205 +2024-11-21 12:11:56.696793: Pseudo dice [0.8412] +2024-11-21 12:11:56.696874: Epoch time: 18.01 s +2024-11-21 12:11:57.882006: +2024-11-21 12:11:57.882300: Epoch 280 +2024-11-21 12:11:57.882412: Current learning rate: 0.00968 +2024-11-21 12:12:16.678430: train_loss -0.7551 +2024-11-21 12:12:16.678678: val_loss -0.747 +2024-11-21 12:12:16.678753: Pseudo dice [0.8281] +2024-11-21 12:12:16.678832: Epoch time: 18.8 s +2024-11-21 12:12:17.478231: +2024-11-21 12:12:17.478460: Epoch 281 +2024-11-21 12:12:17.478574: Current learning rate: 0.00968 +2024-11-21 12:12:36.207568: train_loss -0.7507 +2024-11-21 12:12:36.207792: val_loss -0.7431 +2024-11-21 12:12:36.207875: Pseudo dice [0.8171] +2024-11-21 12:12:36.208045: Epoch time: 18.73 s +2024-11-21 12:12:36.993317: +2024-11-21 12:12:36.993572: Epoch 282 +2024-11-21 12:12:36.993686: Current learning rate: 0.00968 +2024-11-21 12:12:55.247048: train_loss -0.7616 +2024-11-21 12:12:55.247306: val_loss -0.7626 +2024-11-21 12:12:55.247384: Pseudo dice [0.8318] +2024-11-21 12:12:55.247468: Epoch time: 18.25 s +2024-11-21 12:12:56.050730: +2024-11-21 12:12:56.050925: Epoch 283 +2024-11-21 12:12:56.051042: Current learning rate: 0.00968 +2024-11-21 12:13:15.102757: train_loss -0.7525 +2024-11-21 12:13:15.102966: val_loss -0.7265 +2024-11-21 12:13:15.103047: Pseudo dice [0.8458] +2024-11-21 12:13:15.103124: Epoch time: 19.05 s +2024-11-21 12:13:15.891697: +2024-11-21 12:13:15.891916: Epoch 284 +2024-11-21 12:13:15.892031: Current learning rate: 0.00968 +2024-11-21 12:13:34.341363: train_loss -0.751 +2024-11-21 12:13:34.341581: val_loss -0.7145 +2024-11-21 12:13:34.341658: Pseudo dice [0.8128] +2024-11-21 12:13:34.341736: Epoch time: 18.45 s +2024-11-21 12:13:35.121849: +2024-11-21 12:13:35.122064: Epoch 285 +2024-11-21 12:13:35.122181: Current learning rate: 0.00968 +2024-11-21 12:13:52.910028: train_loss -0.7429 +2024-11-21 12:13:52.910238: val_loss -0.7383 +2024-11-21 12:13:52.910314: Pseudo dice [0.8279] +2024-11-21 12:13:52.910388: Epoch time: 17.79 s +2024-11-21 12:13:53.693322: +2024-11-21 12:13:53.693529: Epoch 286 +2024-11-21 12:13:53.693644: Current learning rate: 0.00968 +2024-11-21 12:14:11.473411: train_loss -0.7522 +2024-11-21 12:14:11.473652: val_loss -0.7406 +2024-11-21 12:14:11.473727: Pseudo dice [0.8509] +2024-11-21 12:14:11.473809: Epoch time: 17.78 s +2024-11-21 12:14:12.549910: +2024-11-21 12:14:12.550147: Epoch 287 +2024-11-21 12:14:12.550268: Current learning rate: 0.00968 +2024-11-21 12:14:30.551811: train_loss -0.7504 +2024-11-21 12:14:30.552026: val_loss -0.7487 +2024-11-21 12:14:30.552100: Pseudo dice [0.8648] +2024-11-21 12:14:30.552175: Epoch time: 18.0 s +2024-11-21 12:14:30.552236: Yayy! New best EMA pseudo Dice: 0.8358 +2024-11-21 12:14:31.560421: +2024-11-21 12:14:31.560642: Epoch 288 +2024-11-21 12:14:31.560755: Current learning rate: 0.00968 +2024-11-21 12:14:49.436907: train_loss -0.7618 +2024-11-21 12:14:49.437119: val_loss -0.7261 +2024-11-21 12:14:49.437193: Pseudo dice [0.8486] +2024-11-21 12:14:49.437268: Epoch time: 17.88 s +2024-11-21 12:14:49.437327: Yayy! New best EMA pseudo Dice: 0.8371 +2024-11-21 12:14:50.444686: +2024-11-21 12:14:50.444890: Epoch 289 +2024-11-21 12:14:50.445011: Current learning rate: 0.00967 +2024-11-21 12:15:10.374967: train_loss -0.7501 +2024-11-21 12:15:10.375196: val_loss -0.7336 +2024-11-21 12:15:10.375268: Pseudo dice [0.8181] +2024-11-21 12:15:10.375350: Epoch time: 19.93 s +2024-11-21 12:15:11.164460: +2024-11-21 12:15:11.164673: Epoch 290 +2024-11-21 12:15:11.164798: Current learning rate: 0.00967 +2024-11-21 12:15:30.989460: train_loss -0.7557 +2024-11-21 12:15:30.989698: val_loss -0.7371 +2024-11-21 12:15:30.989772: Pseudo dice [0.8028] +2024-11-21 12:15:30.989859: Epoch time: 19.83 s +2024-11-21 12:15:31.773686: +2024-11-21 12:15:31.773907: Epoch 291 +2024-11-21 12:15:31.774026: Current learning rate: 0.00967 +2024-11-21 12:15:50.778457: train_loss -0.7539 +2024-11-21 12:15:50.778672: val_loss -0.7105 +2024-11-21 12:15:50.778751: Pseudo dice [0.8249] +2024-11-21 12:15:50.778827: Epoch time: 19.01 s +2024-11-21 12:15:51.612455: +2024-11-21 12:15:51.612673: Epoch 292 +2024-11-21 12:15:51.612784: Current learning rate: 0.00967 +2024-11-21 12:16:09.573718: train_loss -0.7491 +2024-11-21 12:16:09.573936: val_loss -0.7351 +2024-11-21 12:16:09.574016: Pseudo dice [0.828] +2024-11-21 12:16:09.574093: Epoch time: 17.96 s +2024-11-21 12:16:10.353481: +2024-11-21 12:16:10.353725: Epoch 293 +2024-11-21 12:16:10.353843: Current learning rate: 0.00967 +2024-11-21 12:16:29.297420: train_loss -0.7596 +2024-11-21 12:16:29.297665: val_loss -0.7333 +2024-11-21 12:16:29.297738: Pseudo dice [0.7959] +2024-11-21 12:16:29.297824: Epoch time: 18.94 s +2024-11-21 12:16:30.089560: +2024-11-21 12:16:30.089778: Epoch 294 +2024-11-21 12:16:30.089892: Current learning rate: 0.00967 +2024-11-21 12:16:48.560714: train_loss -0.7601 +2024-11-21 12:16:48.560924: val_loss -0.739 +2024-11-21 12:16:48.561005: Pseudo dice [0.8398] +2024-11-21 12:16:48.561080: Epoch time: 18.47 s +2024-11-21 12:16:49.339937: +2024-11-21 12:16:49.340131: Epoch 295 +2024-11-21 12:16:49.340241: Current learning rate: 0.00967 +2024-11-21 12:17:09.023427: train_loss -0.75 +2024-11-21 12:17:09.023641: val_loss -0.7152 +2024-11-21 12:17:09.023717: Pseudo dice [0.8457] +2024-11-21 12:17:09.023792: Epoch time: 19.68 s +2024-11-21 12:17:09.809317: +2024-11-21 12:17:09.809529: Epoch 296 +2024-11-21 12:17:09.809647: Current learning rate: 0.00967 +2024-11-21 12:17:29.564282: train_loss -0.7578 +2024-11-21 12:17:29.564532: val_loss -0.7342 +2024-11-21 12:17:29.564608: Pseudo dice [0.8635] +2024-11-21 12:17:29.564689: Epoch time: 19.76 s +2024-11-21 12:17:30.374655: +2024-11-21 12:17:30.374885: Epoch 297 +2024-11-21 12:17:30.375005: Current learning rate: 0.00967 +2024-11-21 12:17:48.767628: train_loss -0.7294 +2024-11-21 12:17:48.767877: val_loss -0.7453 +2024-11-21 12:17:48.767957: Pseudo dice [0.8391] +2024-11-21 12:17:48.768051: Epoch time: 18.39 s +2024-11-21 12:17:49.586861: +2024-11-21 12:17:49.587079: Epoch 298 +2024-11-21 12:17:49.587197: Current learning rate: 0.00966 +2024-11-21 12:18:08.888051: train_loss -0.7423 +2024-11-21 12:18:08.888265: val_loss -0.7379 +2024-11-21 12:18:08.888336: Pseudo dice [0.823] +2024-11-21 12:18:08.888413: Epoch time: 19.3 s +2024-11-21 12:18:09.712797: +2024-11-21 12:18:09.713078: Epoch 299 +2024-11-21 12:18:09.713196: Current learning rate: 0.00966 +2024-11-21 12:18:27.364444: train_loss -0.7515 +2024-11-21 12:18:27.364668: val_loss -0.7266 +2024-11-21 12:18:27.364745: Pseudo dice [0.8254] +2024-11-21 12:18:27.364825: Epoch time: 17.65 s +2024-11-21 12:18:28.391535: +2024-11-21 12:18:28.391841: Epoch 300 +2024-11-21 12:18:28.391961: Current learning rate: 0.00966 +2024-11-21 12:18:47.504513: train_loss -0.7588 +2024-11-21 12:18:47.504723: val_loss -0.6988 +2024-11-21 12:18:47.504805: Pseudo dice [0.8182] +2024-11-21 12:18:47.504882: Epoch time: 19.11 s +2024-11-21 12:18:48.303563: +2024-11-21 12:18:48.303771: Epoch 301 +2024-11-21 12:18:48.303885: Current learning rate: 0.00966 +2024-11-21 12:19:06.600925: train_loss -0.7622 +2024-11-21 12:19:06.601168: val_loss -0.7455 +2024-11-21 12:19:06.601246: Pseudo dice [0.8274] +2024-11-21 12:19:06.601331: Epoch time: 18.3 s +2024-11-21 12:19:07.411541: +2024-11-21 12:19:07.411724: Epoch 302 +2024-11-21 12:19:07.411847: Current learning rate: 0.00966 +2024-11-21 12:19:26.255327: train_loss -0.753 +2024-11-21 12:19:26.255550: val_loss -0.7715 +2024-11-21 12:19:26.255627: Pseudo dice [0.8462] +2024-11-21 12:19:26.255702: Epoch time: 18.84 s +2024-11-21 12:19:27.208406: +2024-11-21 12:19:27.208611: Epoch 303 +2024-11-21 12:19:27.208723: Current learning rate: 0.00966 +2024-11-21 12:19:45.471579: train_loss -0.7577 +2024-11-21 12:19:45.471792: val_loss -0.7351 +2024-11-21 12:19:45.471876: Pseudo dice [0.8541] +2024-11-21 12:19:45.471955: Epoch time: 18.26 s +2024-11-21 12:19:46.256836: +2024-11-21 12:19:46.257061: Epoch 304 +2024-11-21 12:19:46.257183: Current learning rate: 0.00966 +2024-11-21 12:20:05.572895: train_loss -0.7553 +2024-11-21 12:20:05.573160: val_loss -0.7225 +2024-11-21 12:20:05.573241: Pseudo dice [0.8433] +2024-11-21 12:20:05.573329: Epoch time: 19.32 s +2024-11-21 12:20:06.550630: +2024-11-21 12:20:06.550827: Epoch 305 +2024-11-21 12:20:06.550937: Current learning rate: 0.00966 +2024-11-21 12:20:24.161975: train_loss -0.7614 +2024-11-21 12:20:24.162190: val_loss -0.7323 +2024-11-21 12:20:24.162267: Pseudo dice [0.825] +2024-11-21 12:20:24.162344: Epoch time: 17.61 s +2024-11-21 12:20:24.959772: +2024-11-21 12:20:24.960113: Epoch 306 +2024-11-21 12:20:24.960229: Current learning rate: 0.00966 +2024-11-21 12:20:44.635926: train_loss -0.7546 +2024-11-21 12:20:44.636136: val_loss -0.7217 +2024-11-21 12:20:44.636214: Pseudo dice [0.8298] +2024-11-21 12:20:44.636292: Epoch time: 19.68 s +2024-11-21 12:20:45.436833: +2024-11-21 12:20:45.437035: Epoch 307 +2024-11-21 12:20:45.437150: Current learning rate: 0.00965 +2024-11-21 12:21:05.684706: train_loss -0.7508 +2024-11-21 12:21:05.684917: val_loss -0.7309 +2024-11-21 12:21:05.684996: Pseudo dice [0.8268] +2024-11-21 12:21:05.685070: Epoch time: 20.25 s +2024-11-21 12:21:06.480782: +2024-11-21 12:21:06.481013: Epoch 308 +2024-11-21 12:21:06.481126: Current learning rate: 0.00965 +2024-11-21 12:21:25.246342: train_loss -0.7606 +2024-11-21 12:21:25.246541: val_loss -0.7269 +2024-11-21 12:21:25.246615: Pseudo dice [0.8552] +2024-11-21 12:21:25.246694: Epoch time: 18.77 s +2024-11-21 12:21:26.069020: +2024-11-21 12:21:26.069466: Epoch 309 +2024-11-21 12:21:26.069580: Current learning rate: 0.00965 +2024-11-21 12:21:44.601470: train_loss -0.7528 +2024-11-21 12:21:44.601718: val_loss -0.7312 +2024-11-21 12:21:44.601798: Pseudo dice [0.8267] +2024-11-21 12:21:44.604060: Epoch time: 18.53 s +2024-11-21 12:21:45.398259: +2024-11-21 12:21:45.398460: Epoch 310 +2024-11-21 12:21:45.398576: Current learning rate: 0.00965 +2024-11-21 12:22:03.652493: train_loss -0.75 +2024-11-21 12:22:03.652724: val_loss -0.7363 +2024-11-21 12:22:03.652804: Pseudo dice [0.8233] +2024-11-21 12:22:03.652882: Epoch time: 18.26 s +2024-11-21 12:22:04.538876: +2024-11-21 12:22:04.539103: Epoch 311 +2024-11-21 12:22:04.539219: Current learning rate: 0.00965 +2024-11-21 12:22:22.791611: train_loss -0.7497 +2024-11-21 12:22:22.791817: val_loss -0.7272 +2024-11-21 12:22:22.791892: Pseudo dice [0.7965] +2024-11-21 12:22:22.791970: Epoch time: 18.25 s +2024-11-21 12:22:23.585016: +2024-11-21 12:22:23.585281: Epoch 312 +2024-11-21 12:22:23.585392: Current learning rate: 0.00965 +2024-11-21 12:22:41.910575: train_loss -0.7511 +2024-11-21 12:22:41.910820: val_loss -0.7293 +2024-11-21 12:22:41.910898: Pseudo dice [0.8293] +2024-11-21 12:22:41.910981: Epoch time: 18.33 s +2024-11-21 12:22:42.703357: +2024-11-21 12:22:42.703574: Epoch 313 +2024-11-21 12:22:42.703691: Current learning rate: 0.00965 +2024-11-21 12:23:02.406931: train_loss -0.7443 +2024-11-21 12:23:02.407145: val_loss -0.7356 +2024-11-21 12:23:02.407219: Pseudo dice [0.843] +2024-11-21 12:23:02.407293: Epoch time: 19.7 s +2024-11-21 12:23:03.593884: +2024-11-21 12:23:03.594091: Epoch 314 +2024-11-21 12:23:03.594204: Current learning rate: 0.00965 +2024-11-21 12:23:22.237035: train_loss -0.7609 +2024-11-21 12:23:22.237270: val_loss -0.729 +2024-11-21 12:23:22.237346: Pseudo dice [0.8128] +2024-11-21 12:23:22.237423: Epoch time: 18.64 s +2024-11-21 12:23:23.038829: +2024-11-21 12:23:23.039039: Epoch 315 +2024-11-21 12:23:23.039157: Current learning rate: 0.00964 +2024-11-21 12:23:42.641804: train_loss -0.7623 +2024-11-21 12:23:42.642087: val_loss -0.7328 +2024-11-21 12:23:42.642164: Pseudo dice [0.8345] +2024-11-21 12:23:42.642247: Epoch time: 19.6 s +2024-11-21 12:23:43.436495: +2024-11-21 12:23:43.436704: Epoch 316 +2024-11-21 12:23:43.436815: Current learning rate: 0.00964 +2024-11-21 12:24:02.233815: train_loss -0.7554 +2024-11-21 12:24:02.234042: val_loss -0.7472 +2024-11-21 12:24:02.234115: Pseudo dice [0.8538] +2024-11-21 12:24:02.234194: Epoch time: 18.8 s +2024-11-21 12:24:03.038061: +2024-11-21 12:24:03.038281: Epoch 317 +2024-11-21 12:24:03.038399: Current learning rate: 0.00964 +2024-11-21 12:24:22.250179: train_loss -0.7655 +2024-11-21 12:24:22.250383: val_loss -0.7285 +2024-11-21 12:24:22.250458: Pseudo dice [0.822] +2024-11-21 12:24:22.250536: Epoch time: 19.21 s +2024-11-21 12:24:23.112519: +2024-11-21 12:24:23.112722: Epoch 318 +2024-11-21 12:24:23.112836: Current learning rate: 0.00964 +2024-11-21 12:24:41.650368: train_loss -0.7541 +2024-11-21 12:24:41.650570: val_loss -0.7459 +2024-11-21 12:24:41.650642: Pseudo dice [0.865] +2024-11-21 12:24:41.650746: Epoch time: 18.54 s +2024-11-21 12:24:42.443972: +2024-11-21 12:24:42.444199: Epoch 319 +2024-11-21 12:24:42.444315: Current learning rate: 0.00964 +2024-11-21 12:25:00.809579: train_loss -0.7649 +2024-11-21 12:25:00.809827: val_loss -0.7342 +2024-11-21 12:25:00.809901: Pseudo dice [0.827] +2024-11-21 12:25:00.813527: Epoch time: 18.37 s +2024-11-21 12:25:01.642753: +2024-11-21 12:25:01.643008: Epoch 320 +2024-11-21 12:25:01.643123: Current learning rate: 0.00964 +2024-11-21 12:25:20.297204: train_loss -0.7457 +2024-11-21 12:25:20.299595: val_loss -0.7375 +2024-11-21 12:25:20.299698: Pseudo dice [0.8421] +2024-11-21 12:25:20.299784: Epoch time: 18.66 s +2024-11-21 12:25:21.336613: +2024-11-21 12:25:21.336964: Epoch 321 +2024-11-21 12:25:21.337079: Current learning rate: 0.00964 +2024-11-21 12:25:40.746597: train_loss -0.7481 +2024-11-21 12:25:40.747509: val_loss -0.7392 +2024-11-21 12:25:40.747590: Pseudo dice [0.8339] +2024-11-21 12:25:40.747666: Epoch time: 19.41 s +2024-11-21 12:25:41.534397: +2024-11-21 12:25:41.534608: Epoch 322 +2024-11-21 12:25:41.534723: Current learning rate: 0.00964 +2024-11-21 12:26:00.756011: train_loss -0.7368 +2024-11-21 12:26:00.756224: val_loss -0.7248 +2024-11-21 12:26:00.756303: Pseudo dice [0.8173] +2024-11-21 12:26:00.756376: Epoch time: 19.22 s +2024-11-21 12:26:01.542866: +2024-11-21 12:26:01.543066: Epoch 323 +2024-11-21 12:26:01.543178: Current learning rate: 0.00964 +2024-11-21 12:26:20.614723: train_loss -0.7485 +2024-11-21 12:26:20.614956: val_loss -0.7319 +2024-11-21 12:26:20.615034: Pseudo dice [0.7963] +2024-11-21 12:26:20.615115: Epoch time: 19.07 s +2024-11-21 12:26:21.405515: +2024-11-21 12:26:21.405719: Epoch 324 +2024-11-21 12:26:21.405829: Current learning rate: 0.00963 +2024-11-21 12:26:39.311914: train_loss -0.7478 +2024-11-21 12:26:39.312853: val_loss -0.7344 +2024-11-21 12:26:39.312933: Pseudo dice [0.8515] +2024-11-21 12:26:39.313016: Epoch time: 17.91 s +2024-11-21 12:26:40.097337: +2024-11-21 12:26:40.097546: Epoch 325 +2024-11-21 12:26:40.097658: Current learning rate: 0.00963 +2024-11-21 12:26:59.780507: train_loss -0.7559 +2024-11-21 12:26:59.780788: val_loss -0.7529 +2024-11-21 12:26:59.780862: Pseudo dice [0.8276] +2024-11-21 12:26:59.780937: Epoch time: 19.68 s +2024-11-21 12:27:00.633438: +2024-11-21 12:27:00.633897: Epoch 326 +2024-11-21 12:27:00.634037: Current learning rate: 0.00963 +2024-11-21 12:27:19.861906: train_loss -0.7394 +2024-11-21 12:27:19.862153: val_loss -0.7104 +2024-11-21 12:27:19.862224: Pseudo dice [0.8062] +2024-11-21 12:27:19.862311: Epoch time: 19.23 s +2024-11-21 12:27:20.662489: +2024-11-21 12:27:20.662922: Epoch 327 +2024-11-21 12:27:20.663056: Current learning rate: 0.00963 +2024-11-21 12:27:39.065620: train_loss -0.7343 +2024-11-21 12:27:39.065847: val_loss -0.7438 +2024-11-21 12:27:39.065922: Pseudo dice [0.8406] +2024-11-21 12:27:39.066004: Epoch time: 18.4 s +2024-11-21 12:27:39.912448: +2024-11-21 12:27:39.912906: Epoch 328 +2024-11-21 12:27:39.913047: Current learning rate: 0.00963 +2024-11-21 12:27:59.217717: train_loss -0.7462 +2024-11-21 12:27:59.220313: val_loss -0.7294 +2024-11-21 12:27:59.220407: Pseudo dice [0.8431] +2024-11-21 12:27:59.220483: Epoch time: 19.31 s +2024-11-21 12:28:00.005974: +2024-11-21 12:28:00.006400: Epoch 329 +2024-11-21 12:28:00.006534: Current learning rate: 0.00963 +2024-11-21 12:28:18.613050: train_loss -0.7623 +2024-11-21 12:28:18.613297: val_loss -0.6851 +2024-11-21 12:28:18.613373: Pseudo dice [0.8417] +2024-11-21 12:28:18.613457: Epoch time: 18.61 s +2024-11-21 12:28:19.492811: +2024-11-21 12:28:19.493245: Epoch 330 +2024-11-21 12:28:19.493379: Current learning rate: 0.00963 +2024-11-21 12:28:37.807433: train_loss -0.7558 +2024-11-21 12:28:37.807639: val_loss -0.7361 +2024-11-21 12:28:37.807715: Pseudo dice [0.8284] +2024-11-21 12:28:37.807943: Epoch time: 18.32 s +2024-11-21 12:28:38.757268: +2024-11-21 12:28:38.757662: Epoch 331 +2024-11-21 12:28:38.757809: Current learning rate: 0.00963 +2024-11-21 12:28:58.721260: train_loss -0.7586 +2024-11-21 12:28:58.721487: val_loss -0.7401 +2024-11-21 12:28:58.721566: Pseudo dice [0.812] +2024-11-21 12:28:58.721645: Epoch time: 19.96 s +2024-11-21 12:28:59.521687: +2024-11-21 12:28:59.522124: Epoch 332 +2024-11-21 12:28:59.522266: Current learning rate: 0.00963 +2024-11-21 12:29:17.909782: train_loss -0.7573 +2024-11-21 12:29:17.909996: val_loss -0.7275 +2024-11-21 12:29:17.910073: Pseudo dice [0.8384] +2024-11-21 12:29:17.910150: Epoch time: 18.39 s +2024-11-21 12:29:18.701747: +2024-11-21 12:29:18.702224: Epoch 333 +2024-11-21 12:29:18.702372: Current learning rate: 0.00962 +2024-11-21 12:29:37.826718: train_loss -0.7522 +2024-11-21 12:29:37.826960: val_loss -0.7272 +2024-11-21 12:29:37.827043: Pseudo dice [0.8412] +2024-11-21 12:29:37.827124: Epoch time: 19.13 s +2024-11-21 12:29:38.619424: +2024-11-21 12:29:38.619849: Epoch 334 +2024-11-21 12:29:38.619997: Current learning rate: 0.00962 +2024-11-21 12:29:57.772323: train_loss -0.7388 +2024-11-21 12:29:57.772546: val_loss -0.7412 +2024-11-21 12:29:57.772623: Pseudo dice [0.8468] +2024-11-21 12:29:57.772700: Epoch time: 19.15 s +2024-11-21 12:29:58.567706: +2024-11-21 12:29:58.568168: Epoch 335 +2024-11-21 12:29:58.568311: Current learning rate: 0.00962 +2024-11-21 12:30:15.823378: train_loss -0.7496 +2024-11-21 12:30:15.823672: val_loss -0.7627 +2024-11-21 12:30:15.823750: Pseudo dice [0.8511] +2024-11-21 12:30:15.823828: Epoch time: 17.26 s +2024-11-21 12:30:16.622359: +2024-11-21 12:30:16.622762: Epoch 336 +2024-11-21 12:30:16.622892: Current learning rate: 0.00962 +2024-11-21 12:30:35.512779: train_loss -0.7545 +2024-11-21 12:30:35.513025: val_loss -0.7236 +2024-11-21 12:30:35.513101: Pseudo dice [0.8366] +2024-11-21 12:30:35.513185: Epoch time: 18.89 s +2024-11-21 12:30:36.724024: +2024-11-21 12:30:36.724497: Epoch 337 +2024-11-21 12:30:36.724643: Current learning rate: 0.00962 +2024-11-21 12:30:55.904790: train_loss -0.7536 +2024-11-21 12:30:55.905057: val_loss -0.7282 +2024-11-21 12:30:55.905135: Pseudo dice [0.8481] +2024-11-21 12:30:55.905209: Epoch time: 19.18 s +2024-11-21 12:30:56.750772: +2024-11-21 12:30:56.751271: Epoch 338 +2024-11-21 12:30:56.751411: Current learning rate: 0.00962 +2024-11-21 12:31:14.685458: train_loss -0.7653 +2024-11-21 12:31:14.687878: val_loss -0.7191 +2024-11-21 12:31:14.687973: Pseudo dice [0.8138] +2024-11-21 12:31:14.688057: Epoch time: 17.94 s +2024-11-21 12:31:15.759000: +2024-11-21 12:31:15.759454: Epoch 339 +2024-11-21 12:31:15.759602: Current learning rate: 0.00962 +2024-11-21 12:31:33.332458: train_loss -0.7596 +2024-11-21 12:31:33.332669: val_loss -0.7026 +2024-11-21 12:31:33.332742: Pseudo dice [0.8134] +2024-11-21 12:31:33.332819: Epoch time: 17.57 s +2024-11-21 12:31:34.186162: +2024-11-21 12:31:34.186646: Epoch 340 +2024-11-21 12:31:34.186833: Current learning rate: 0.00962 +2024-11-21 12:31:52.964908: train_loss -0.7563 +2024-11-21 12:31:52.965122: val_loss -0.744 +2024-11-21 12:31:52.965196: Pseudo dice [0.8353] +2024-11-21 12:31:52.965273: Epoch time: 18.78 s +2024-11-21 12:31:53.760092: +2024-11-21 12:31:53.760502: Epoch 341 +2024-11-21 12:31:53.760632: Current learning rate: 0.00962 +2024-11-21 12:32:12.861586: train_loss -0.7609 +2024-11-21 12:32:12.861785: val_loss -0.7123 +2024-11-21 12:32:12.861860: Pseudo dice [0.8085] +2024-11-21 12:32:12.861936: Epoch time: 19.1 s +2024-11-21 12:32:13.671023: +2024-11-21 12:32:13.671453: Epoch 342 +2024-11-21 12:32:13.671592: Current learning rate: 0.00961 +2024-11-21 12:32:31.719482: train_loss -0.7625 +2024-11-21 12:32:31.719738: val_loss -0.7422 +2024-11-21 12:32:31.719812: Pseudo dice [0.8266] +2024-11-21 12:32:31.719887: Epoch time: 18.05 s +2024-11-21 12:32:32.515940: +2024-11-21 12:32:32.516414: Epoch 343 +2024-11-21 12:32:32.516552: Current learning rate: 0.00961 +2024-11-21 12:32:51.116249: train_loss -0.7532 +2024-11-21 12:32:51.116463: val_loss -0.725 +2024-11-21 12:32:51.118869: Pseudo dice [0.8263] +2024-11-21 12:32:51.119002: Epoch time: 18.6 s +2024-11-21 12:32:52.108767: +2024-11-21 12:32:52.109191: Epoch 344 +2024-11-21 12:32:52.109319: Current learning rate: 0.00961 +2024-11-21 12:33:11.520540: train_loss -0.7494 +2024-11-21 12:33:11.520792: val_loss -0.7528 +2024-11-21 12:33:11.520887: Pseudo dice [0.8544] +2024-11-21 12:33:11.520982: Epoch time: 19.41 s +2024-11-21 12:33:12.321619: +2024-11-21 12:33:12.322065: Epoch 345 +2024-11-21 12:33:12.322218: Current learning rate: 0.00961 +2024-11-21 12:33:30.703815: train_loss -0.7557 +2024-11-21 12:33:30.704031: val_loss -0.7441 +2024-11-21 12:33:30.704183: Pseudo dice [0.8188] +2024-11-21 12:33:30.704266: Epoch time: 18.38 s +2024-11-21 12:33:31.505692: +2024-11-21 12:33:31.506094: Epoch 346 +2024-11-21 12:33:31.506228: Current learning rate: 0.00961 +2024-11-21 12:33:50.426468: train_loss -0.7695 +2024-11-21 12:33:50.426679: val_loss -0.746 +2024-11-21 12:33:50.426758: Pseudo dice [0.8486] +2024-11-21 12:33:50.426840: Epoch time: 18.92 s +2024-11-21 12:33:51.228378: +2024-11-21 12:33:51.228818: Epoch 347 +2024-11-21 12:33:51.228965: Current learning rate: 0.00961 +2024-11-21 12:34:09.674311: train_loss -0.7585 +2024-11-21 12:34:09.674558: val_loss -0.6904 +2024-11-21 12:34:09.674636: Pseudo dice [0.8282] +2024-11-21 12:34:09.674723: Epoch time: 18.45 s +2024-11-21 12:34:11.027704: +2024-11-21 12:34:11.028154: Epoch 348 +2024-11-21 12:34:11.028286: Current learning rate: 0.00961 +2024-11-21 12:34:29.558491: train_loss -0.7507 +2024-11-21 12:34:29.558787: val_loss -0.7173 +2024-11-21 12:34:29.558867: Pseudo dice [0.8312] +2024-11-21 12:34:29.558947: Epoch time: 18.53 s +2024-11-21 12:34:30.357908: +2024-11-21 12:34:30.358434: Epoch 349 +2024-11-21 12:34:30.358575: Current learning rate: 0.00961 +2024-11-21 12:34:49.125808: train_loss -0.7343 +2024-11-21 12:34:49.126034: val_loss -0.701 +2024-11-21 12:34:49.126109: Pseudo dice [0.839] +2024-11-21 12:34:49.126184: Epoch time: 18.77 s +2024-11-21 12:34:50.307924: +2024-11-21 12:34:50.308366: Epoch 350 +2024-11-21 12:34:50.308499: Current learning rate: 0.00961 +2024-11-21 12:35:09.297501: train_loss -0.7494 +2024-11-21 12:35:09.297805: val_loss -0.7346 +2024-11-21 12:35:09.297891: Pseudo dice [0.843] +2024-11-21 12:35:09.298007: Epoch time: 18.99 s +2024-11-21 12:35:10.200582: +2024-11-21 12:35:10.201077: Epoch 351 +2024-11-21 12:35:10.201214: Current learning rate: 0.0096 +2024-11-21 12:35:30.066452: train_loss -0.7506 +2024-11-21 12:35:30.066660: val_loss -0.7629 +2024-11-21 12:35:30.066741: Pseudo dice [0.8418] +2024-11-21 12:35:30.066817: Epoch time: 19.87 s +2024-11-21 12:35:30.865335: +2024-11-21 12:35:30.865749: Epoch 352 +2024-11-21 12:35:30.865887: Current learning rate: 0.0096 +2024-11-21 12:35:48.454390: train_loss -0.7615 +2024-11-21 12:35:48.454606: val_loss -0.7426 +2024-11-21 12:35:48.454684: Pseudo dice [0.826] +2024-11-21 12:35:48.454761: Epoch time: 17.59 s +2024-11-21 12:35:49.254694: +2024-11-21 12:35:49.255146: Epoch 353 +2024-11-21 12:35:49.255280: Current learning rate: 0.0096 +2024-11-21 12:36:07.596806: train_loss -0.7466 +2024-11-21 12:36:07.602220: val_loss -0.7356 +2024-11-21 12:36:07.602336: Pseudo dice [0.828] +2024-11-21 12:36:07.602415: Epoch time: 18.34 s +2024-11-21 12:36:08.526462: +2024-11-21 12:36:08.526902: Epoch 354 +2024-11-21 12:36:08.527053: Current learning rate: 0.0096 +2024-11-21 12:36:26.480764: train_loss -0.7438 +2024-11-21 12:36:26.481032: val_loss -0.7176 +2024-11-21 12:36:26.481107: Pseudo dice [0.7988] +2024-11-21 12:36:26.481233: Epoch time: 17.96 s +2024-11-21 12:36:27.299930: +2024-11-21 12:36:27.300378: Epoch 355 +2024-11-21 12:36:27.300517: Current learning rate: 0.0096 +2024-11-21 12:36:45.749089: train_loss -0.7387 +2024-11-21 12:36:45.749314: val_loss -0.7469 +2024-11-21 12:36:45.749390: Pseudo dice [0.8399] +2024-11-21 12:36:45.749465: Epoch time: 18.45 s +2024-11-21 12:36:46.603651: +2024-11-21 12:36:46.604064: Epoch 356 +2024-11-21 12:36:46.604206: Current learning rate: 0.0096 +2024-11-21 12:37:05.592851: train_loss -0.7511 +2024-11-21 12:37:05.593076: val_loss -0.7238 +2024-11-21 12:37:05.593158: Pseudo dice [0.8303] +2024-11-21 12:37:05.593238: Epoch time: 18.99 s +2024-11-21 12:37:06.390577: +2024-11-21 12:37:06.390997: Epoch 357 +2024-11-21 12:37:06.391137: Current learning rate: 0.0096 +2024-11-21 12:37:26.543544: train_loss -0.7479 +2024-11-21 12:37:26.543755: val_loss -0.7473 +2024-11-21 12:37:26.543839: Pseudo dice [0.8421] +2024-11-21 12:37:26.543918: Epoch time: 20.15 s +2024-11-21 12:37:27.361742: +2024-11-21 12:37:27.362164: Epoch 358 +2024-11-21 12:37:27.362301: Current learning rate: 0.0096 +2024-11-21 12:37:44.864448: train_loss -0.7502 +2024-11-21 12:37:44.864688: val_loss -0.7268 +2024-11-21 12:37:44.864766: Pseudo dice [0.8254] +2024-11-21 12:37:44.864851: Epoch time: 17.5 s +2024-11-21 12:37:46.101451: +2024-11-21 12:37:46.102010: Epoch 359 +2024-11-21 12:37:46.102156: Current learning rate: 0.0096 +2024-11-21 12:38:04.801984: train_loss -0.7586 +2024-11-21 12:38:04.802199: val_loss -0.7292 +2024-11-21 12:38:04.802272: Pseudo dice [0.8376] +2024-11-21 12:38:04.802349: Epoch time: 18.7 s +2024-11-21 12:38:05.595368: +2024-11-21 12:38:05.595781: Epoch 360 +2024-11-21 12:38:05.595914: Current learning rate: 0.00959 +2024-11-21 12:38:23.183254: train_loss -0.761 +2024-11-21 12:38:23.183934: val_loss -0.7484 +2024-11-21 12:38:23.184042: Pseudo dice [0.8271] +2024-11-21 12:38:23.184119: Epoch time: 17.59 s +2024-11-21 12:38:24.167269: +2024-11-21 12:38:24.167753: Epoch 361 +2024-11-21 12:38:24.167894: Current learning rate: 0.00959 +2024-11-21 12:38:43.227547: train_loss -0.7597 +2024-11-21 12:38:43.227795: val_loss -0.7342 +2024-11-21 12:38:43.227868: Pseudo dice [0.8346] +2024-11-21 12:38:43.227952: Epoch time: 19.06 s +2024-11-21 12:38:44.033004: +2024-11-21 12:38:44.033484: Epoch 362 +2024-11-21 12:38:44.033615: Current learning rate: 0.00959 +2024-11-21 12:39:02.971001: train_loss -0.7643 +2024-11-21 12:39:02.971214: val_loss -0.7268 +2024-11-21 12:39:02.971293: Pseudo dice [0.8394] +2024-11-21 12:39:02.971371: Epoch time: 18.94 s +2024-11-21 12:39:03.773491: +2024-11-21 12:39:03.773936: Epoch 363 +2024-11-21 12:39:03.774082: Current learning rate: 0.00959 +2024-11-21 12:39:22.628394: train_loss -0.7642 +2024-11-21 12:39:22.628663: val_loss -0.7262 +2024-11-21 12:39:22.628739: Pseudo dice [0.8353] +2024-11-21 12:39:22.628814: Epoch time: 18.86 s +2024-11-21 12:39:23.434907: +2024-11-21 12:39:23.435342: Epoch 364 +2024-11-21 12:39:23.435495: Current learning rate: 0.00959 +2024-11-21 12:39:41.822337: train_loss -0.7705 +2024-11-21 12:39:41.822553: val_loss -0.7294 +2024-11-21 12:39:41.822626: Pseudo dice [0.8381] +2024-11-21 12:39:41.822703: Epoch time: 18.39 s +2024-11-21 12:39:42.636378: +2024-11-21 12:39:42.636814: Epoch 365 +2024-11-21 12:39:42.636948: Current learning rate: 0.00959 +2024-11-21 12:40:01.140487: train_loss -0.7552 +2024-11-21 12:40:01.145924: val_loss -0.741 +2024-11-21 12:40:01.146049: Pseudo dice [0.8414] +2024-11-21 12:40:01.146138: Epoch time: 18.5 s +2024-11-21 12:40:02.080094: +2024-11-21 12:40:02.080612: Epoch 366 +2024-11-21 12:40:02.080779: Current learning rate: 0.00959 +2024-11-21 12:40:20.977153: train_loss -0.7528 +2024-11-21 12:40:20.977369: val_loss -0.7478 +2024-11-21 12:40:20.977469: Pseudo dice [0.8264] +2024-11-21 12:40:20.977551: Epoch time: 18.9 s +2024-11-21 12:40:21.776802: +2024-11-21 12:40:21.777282: Epoch 367 +2024-11-21 12:40:21.777421: Current learning rate: 0.00959 +2024-11-21 12:40:40.794943: train_loss -0.7582 +2024-11-21 12:40:40.795159: val_loss -0.7485 +2024-11-21 12:40:40.795234: Pseudo dice [0.8437] +2024-11-21 12:40:40.795308: Epoch time: 19.02 s +2024-11-21 12:40:41.586223: +2024-11-21 12:40:41.586706: Epoch 368 +2024-11-21 12:40:41.586842: Current learning rate: 0.00959 +2024-11-21 12:41:01.190287: train_loss -0.7623 +2024-11-21 12:41:01.190496: val_loss -0.7399 +2024-11-21 12:41:01.190569: Pseudo dice [0.825] +2024-11-21 12:41:01.190649: Epoch time: 19.6 s +2024-11-21 12:41:01.984492: +2024-11-21 12:41:01.984790: Epoch 369 +2024-11-21 12:41:01.984949: Current learning rate: 0.00958 +2024-11-21 12:41:19.738798: train_loss -0.7627 +2024-11-21 12:41:19.739014: val_loss -0.7088 +2024-11-21 12:41:19.739088: Pseudo dice [0.8261] +2024-11-21 12:41:19.739168: Epoch time: 17.76 s +2024-11-21 12:41:20.526798: +2024-11-21 12:41:20.526996: Epoch 370 +2024-11-21 12:41:20.527107: Current learning rate: 0.00958 +2024-11-21 12:41:39.503530: train_loss -0.7691 +2024-11-21 12:41:39.503749: val_loss -0.7472 +2024-11-21 12:41:39.503821: Pseudo dice [0.8254] +2024-11-21 12:41:39.503893: Epoch time: 18.98 s +2024-11-21 12:41:40.299072: +2024-11-21 12:41:40.299289: Epoch 371 +2024-11-21 12:41:40.299404: Current learning rate: 0.00958 +2024-11-21 12:41:58.702124: train_loss -0.7533 +2024-11-21 12:41:58.702363: val_loss -0.729 +2024-11-21 12:41:58.702438: Pseudo dice [0.8504] +2024-11-21 12:41:58.702521: Epoch time: 18.4 s +2024-11-21 12:41:59.497525: +2024-11-21 12:41:59.497805: Epoch 372 +2024-11-21 12:41:59.497919: Current learning rate: 0.00958 +2024-11-21 12:42:18.087702: train_loss -0.753 +2024-11-21 12:42:18.087913: val_loss -0.7271 +2024-11-21 12:42:18.087985: Pseudo dice [0.8096] +2024-11-21 12:42:18.088068: Epoch time: 18.59 s +2024-11-21 12:42:18.881671: +2024-11-21 12:42:18.881928: Epoch 373 +2024-11-21 12:42:18.882050: Current learning rate: 0.00958 +2024-11-21 12:42:39.283147: train_loss -0.7553 +2024-11-21 12:42:39.283347: val_loss -0.7289 +2024-11-21 12:42:39.283420: Pseudo dice [0.8442] +2024-11-21 12:42:39.283494: Epoch time: 20.4 s +2024-11-21 12:42:40.080754: +2024-11-21 12:42:40.081046: Epoch 374 +2024-11-21 12:42:40.081160: Current learning rate: 0.00958 +2024-11-21 12:42:58.650632: train_loss -0.7496 +2024-11-21 12:42:58.650846: val_loss -0.7333 +2024-11-21 12:42:58.650919: Pseudo dice [0.8307] +2024-11-21 12:42:58.651004: Epoch time: 18.57 s +2024-11-21 12:42:59.448789: +2024-11-21 12:42:59.448997: Epoch 375 +2024-11-21 12:42:59.449114: Current learning rate: 0.00958 +2024-11-21 12:43:18.087917: train_loss -0.754 +2024-11-21 12:43:18.088142: val_loss -0.7365 +2024-11-21 12:43:18.088216: Pseudo dice [0.8177] +2024-11-21 12:43:18.088299: Epoch time: 18.64 s +2024-11-21 12:43:18.927083: +2024-11-21 12:43:18.927283: Epoch 376 +2024-11-21 12:43:18.927398: Current learning rate: 0.00958 +2024-11-21 12:43:37.107318: train_loss -0.7673 +2024-11-21 12:43:37.107550: val_loss -0.7373 +2024-11-21 12:43:37.112850: Pseudo dice [0.8469] +2024-11-21 12:43:37.112949: Epoch time: 18.18 s +2024-11-21 12:43:37.912998: +2024-11-21 12:43:37.913202: Epoch 377 +2024-11-21 12:43:37.913315: Current learning rate: 0.00957 +2024-11-21 12:43:57.105824: train_loss -0.7621 +2024-11-21 12:43:57.106047: val_loss -0.753 +2024-11-21 12:43:57.106139: Pseudo dice [0.8493] +2024-11-21 12:43:57.106254: Epoch time: 19.19 s +2024-11-21 12:43:57.905275: +2024-11-21 12:43:57.905486: Epoch 378 +2024-11-21 12:43:57.905612: Current learning rate: 0.00957 +2024-11-21 12:44:16.651019: train_loss -0.7587 +2024-11-21 12:44:16.651318: val_loss -0.7351 +2024-11-21 12:44:16.651403: Pseudo dice [0.8394] +2024-11-21 12:44:16.651482: Epoch time: 18.75 s +2024-11-21 12:44:17.445807: +2024-11-21 12:44:17.446072: Epoch 379 +2024-11-21 12:44:17.446188: Current learning rate: 0.00957 +2024-11-21 12:44:36.853528: train_loss -0.7629 +2024-11-21 12:44:36.853769: val_loss -0.7479 +2024-11-21 12:44:36.853843: Pseudo dice [0.8412] +2024-11-21 12:44:36.853960: Epoch time: 19.41 s +2024-11-21 12:44:37.645692: +2024-11-21 12:44:37.645916: Epoch 380 +2024-11-21 12:44:37.646043: Current learning rate: 0.00957 +2024-11-21 12:44:55.552150: train_loss -0.7543 +2024-11-21 12:44:55.552436: val_loss -0.7639 +2024-11-21 12:44:55.552512: Pseudo dice [0.8285] +2024-11-21 12:44:55.552587: Epoch time: 17.91 s +2024-11-21 12:44:56.343635: +2024-11-21 12:44:56.343924: Epoch 381 +2024-11-21 12:44:56.344042: Current learning rate: 0.00957 +2024-11-21 12:45:14.870732: train_loss -0.7587 +2024-11-21 12:45:14.870966: val_loss -0.7235 +2024-11-21 12:45:14.871055: Pseudo dice [0.8209] +2024-11-21 12:45:14.871133: Epoch time: 18.53 s +2024-11-21 12:45:16.067986: +2024-11-21 12:45:16.068272: Epoch 382 +2024-11-21 12:45:16.068384: Current learning rate: 0.00957 +2024-11-21 12:45:35.073157: train_loss -0.7578 +2024-11-21 12:45:35.073429: val_loss -0.7418 +2024-11-21 12:45:35.073564: Pseudo dice [0.8442] +2024-11-21 12:45:35.073678: Epoch time: 19.01 s +2024-11-21 12:45:35.879305: +2024-11-21 12:45:35.879690: Epoch 383 +2024-11-21 12:45:35.879839: Current learning rate: 0.00957 +2024-11-21 12:45:55.231652: train_loss -0.7525 +2024-11-21 12:45:55.231879: val_loss -0.7297 +2024-11-21 12:45:55.231955: Pseudo dice [0.806] +2024-11-21 12:45:55.232105: Epoch time: 19.35 s +2024-11-21 12:45:56.031987: +2024-11-21 12:45:56.032214: Epoch 384 +2024-11-21 12:45:56.032329: Current learning rate: 0.00957 +2024-11-21 12:46:15.398935: train_loss -0.7651 +2024-11-21 12:46:15.399156: val_loss -0.7291 +2024-11-21 12:46:15.399231: Pseudo dice [0.8517] +2024-11-21 12:46:15.399307: Epoch time: 19.37 s +2024-11-21 12:46:16.199316: +2024-11-21 12:46:16.199535: Epoch 385 +2024-11-21 12:46:16.199650: Current learning rate: 0.00957 +2024-11-21 12:46:35.560143: train_loss -0.7559 +2024-11-21 12:46:35.564562: val_loss -0.7421 +2024-11-21 12:46:35.564745: Pseudo dice [0.838] +2024-11-21 12:46:35.564843: Epoch time: 19.36 s +2024-11-21 12:46:36.375755: +2024-11-21 12:46:36.375960: Epoch 386 +2024-11-21 12:46:36.376087: Current learning rate: 0.00956 +2024-11-21 12:46:54.138130: train_loss -0.7571 +2024-11-21 12:46:54.138339: val_loss -0.7515 +2024-11-21 12:46:54.138415: Pseudo dice [0.8389] +2024-11-21 12:46:54.138491: Epoch time: 17.76 s +2024-11-21 12:46:54.924049: +2024-11-21 12:46:54.924231: Epoch 387 +2024-11-21 12:46:54.924325: Current learning rate: 0.00956 +2024-11-21 12:47:13.978612: train_loss -0.7599 +2024-11-21 12:47:13.978833: val_loss -0.7109 +2024-11-21 12:47:13.978909: Pseudo dice [0.8256] +2024-11-21 12:47:13.978997: Epoch time: 19.06 s +2024-11-21 12:47:14.973709: +2024-11-21 12:47:14.974012: Epoch 388 +2024-11-21 12:47:14.974128: Current learning rate: 0.00956 +2024-11-21 12:47:33.440951: train_loss -0.7524 +2024-11-21 12:47:33.441177: val_loss -0.7062 +2024-11-21 12:47:33.441252: Pseudo dice [0.8311] +2024-11-21 12:47:33.441327: Epoch time: 18.47 s +2024-11-21 12:47:34.257433: +2024-11-21 12:47:34.257649: Epoch 389 +2024-11-21 12:47:34.257767: Current learning rate: 0.00956 +2024-11-21 12:47:52.553405: train_loss -0.7496 +2024-11-21 12:47:52.553623: val_loss -0.7333 +2024-11-21 12:47:52.553699: Pseudo dice [0.7954] +2024-11-21 12:47:52.553779: Epoch time: 18.3 s +2024-11-21 12:47:53.353988: +2024-11-21 12:47:53.354270: Epoch 390 +2024-11-21 12:47:53.354385: Current learning rate: 0.00956 +2024-11-21 12:48:11.791932: train_loss -0.739 +2024-11-21 12:48:11.797364: val_loss -0.6811 +2024-11-21 12:48:11.797472: Pseudo dice [0.7637] +2024-11-21 12:48:11.797560: Epoch time: 18.44 s +2024-11-21 12:48:12.813270: +2024-11-21 12:48:12.813495: Epoch 391 +2024-11-21 12:48:12.813608: Current learning rate: 0.00956 +2024-11-21 12:48:30.765283: train_loss -0.753 +2024-11-21 12:48:30.765490: val_loss -0.7209 +2024-11-21 12:48:30.765565: Pseudo dice [0.8068] +2024-11-21 12:48:30.765644: Epoch time: 17.95 s +2024-11-21 12:48:31.571975: +2024-11-21 12:48:31.572366: Epoch 392 +2024-11-21 12:48:31.572482: Current learning rate: 0.00956 +2024-11-21 12:48:49.446985: train_loss -0.7407 +2024-11-21 12:48:49.447203: val_loss -0.7227 +2024-11-21 12:48:49.447275: Pseudo dice [0.8334] +2024-11-21 12:48:49.447349: Epoch time: 17.88 s +2024-11-21 12:48:50.650270: +2024-11-21 12:48:50.650463: Epoch 393 +2024-11-21 12:48:50.650572: Current learning rate: 0.00956 +2024-11-21 12:49:09.259048: train_loss -0.7579 +2024-11-21 12:49:09.259302: val_loss -0.7558 +2024-11-21 12:49:09.259382: Pseudo dice [0.8255] +2024-11-21 12:49:09.259472: Epoch time: 18.61 s +2024-11-21 12:49:10.092450: +2024-11-21 12:49:10.092662: Epoch 394 +2024-11-21 12:49:10.092772: Current learning rate: 0.00956 +2024-11-21 12:49:29.015309: train_loss -0.7563 +2024-11-21 12:49:29.015569: val_loss -0.7476 +2024-11-21 12:49:29.015647: Pseudo dice [0.8488] +2024-11-21 12:49:29.015723: Epoch time: 18.92 s +2024-11-21 12:49:29.821653: +2024-11-21 12:49:29.821894: Epoch 395 +2024-11-21 12:49:29.822008: Current learning rate: 0.00955 +2024-11-21 12:49:48.607645: train_loss -0.7537 +2024-11-21 12:49:48.607873: val_loss -0.7167 +2024-11-21 12:49:48.607947: Pseudo dice [0.8482] +2024-11-21 12:49:48.608034: Epoch time: 18.79 s +2024-11-21 12:49:49.703306: +2024-11-21 12:49:49.703542: Epoch 396 +2024-11-21 12:49:49.703669: Current learning rate: 0.00955 +2024-11-21 12:50:07.325413: train_loss -0.7503 +2024-11-21 12:50:07.325641: val_loss -0.7268 +2024-11-21 12:50:07.325718: Pseudo dice [0.841] +2024-11-21 12:50:07.325801: Epoch time: 17.62 s +2024-11-21 12:50:08.156392: +2024-11-21 12:50:08.156757: Epoch 397 +2024-11-21 12:50:08.156872: Current learning rate: 0.00955 +2024-11-21 12:50:25.690617: train_loss -0.7589 +2024-11-21 12:50:25.690846: val_loss -0.7518 +2024-11-21 12:50:25.690918: Pseudo dice [0.8463] +2024-11-21 12:50:25.691002: Epoch time: 17.54 s +2024-11-21 12:50:26.535447: +2024-11-21 12:50:26.535664: Epoch 398 +2024-11-21 12:50:26.535776: Current learning rate: 0.00955 +2024-11-21 12:50:45.783737: train_loss -0.7507 +2024-11-21 12:50:45.783944: val_loss -0.7291 +2024-11-21 12:50:45.784030: Pseudo dice [0.8257] +2024-11-21 12:50:45.784132: Epoch time: 19.25 s +2024-11-21 12:50:46.592674: +2024-11-21 12:50:46.592916: Epoch 399 +2024-11-21 12:50:46.593037: Current learning rate: 0.00955 +2024-11-21 12:51:05.681586: train_loss -0.7569 +2024-11-21 12:51:05.681805: val_loss -0.7246 +2024-11-21 12:51:05.681880: Pseudo dice [0.8071] +2024-11-21 12:51:05.681959: Epoch time: 19.09 s +2024-11-21 12:51:06.690206: +2024-11-21 12:51:06.690426: Epoch 400 +2024-11-21 12:51:06.690541: Current learning rate: 0.00955 +2024-11-21 12:51:25.048859: train_loss -0.7433 +2024-11-21 12:51:25.049112: val_loss -0.7241 +2024-11-21 12:51:25.049192: Pseudo dice [0.8165] +2024-11-21 12:51:25.049276: Epoch time: 18.36 s +2024-11-21 12:51:25.853645: +2024-11-21 12:51:25.853985: Epoch 401 +2024-11-21 12:51:25.854098: Current learning rate: 0.00955 +2024-11-21 12:51:44.359458: train_loss -0.7612 +2024-11-21 12:51:44.364841: val_loss -0.7459 +2024-11-21 12:51:44.364960: Pseudo dice [0.8337] +2024-11-21 12:51:44.365042: Epoch time: 18.51 s +2024-11-21 12:51:45.279806: +2024-11-21 12:51:45.280005: Epoch 402 +2024-11-21 12:51:45.280116: Current learning rate: 0.00955 +2024-11-21 12:52:03.438253: train_loss -0.7518 +2024-11-21 12:52:03.438468: val_loss -0.7425 +2024-11-21 12:52:03.438542: Pseudo dice [0.8221] +2024-11-21 12:52:03.438615: Epoch time: 18.16 s +2024-11-21 12:52:04.247558: +2024-11-21 12:52:04.247779: Epoch 403 +2024-11-21 12:52:04.247892: Current learning rate: 0.00955 +2024-11-21 12:52:22.593571: train_loss -0.7499 +2024-11-21 12:52:22.593783: val_loss -0.7181 +2024-11-21 12:52:22.593861: Pseudo dice [0.8255] +2024-11-21 12:52:22.593940: Epoch time: 18.35 s +2024-11-21 12:52:23.802131: +2024-11-21 12:52:23.802347: Epoch 404 +2024-11-21 12:52:23.802456: Current learning rate: 0.00954 +2024-11-21 12:52:43.133297: train_loss -0.7537 +2024-11-21 12:52:43.133530: val_loss -0.7535 +2024-11-21 12:52:43.133604: Pseudo dice [0.8438] +2024-11-21 12:52:43.133681: Epoch time: 19.33 s +2024-11-21 12:52:44.125391: +2024-11-21 12:52:44.125637: Epoch 405 +2024-11-21 12:52:44.125753: Current learning rate: 0.00954 +2024-11-21 12:53:02.709260: train_loss -0.7518 +2024-11-21 12:53:02.709467: val_loss -0.7363 +2024-11-21 12:53:02.709538: Pseudo dice [0.8608] +2024-11-21 12:53:02.709616: Epoch time: 18.58 s +2024-11-21 12:53:03.512336: +2024-11-21 12:53:03.512553: Epoch 406 +2024-11-21 12:53:03.512667: Current learning rate: 0.00954 +2024-11-21 12:53:21.936603: train_loss -0.7554 +2024-11-21 12:53:21.950317: val_loss -0.7428 +2024-11-21 12:53:21.950412: Pseudo dice [0.8457] +2024-11-21 12:53:21.950491: Epoch time: 18.43 s +2024-11-21 12:53:22.907914: +2024-11-21 12:53:22.908130: Epoch 407 +2024-11-21 12:53:22.908245: Current learning rate: 0.00954 +2024-11-21 12:53:41.637489: train_loss -0.7465 +2024-11-21 12:53:41.637699: val_loss -0.7342 +2024-11-21 12:53:41.637774: Pseudo dice [0.8331] +2024-11-21 12:53:41.637856: Epoch time: 18.73 s +2024-11-21 12:53:42.492681: +2024-11-21 12:53:42.492921: Epoch 408 +2024-11-21 12:53:42.493042: Current learning rate: 0.00954 +2024-11-21 12:54:01.563728: train_loss -0.7594 +2024-11-21 12:54:01.563950: val_loss -0.7597 +2024-11-21 12:54:01.564032: Pseudo dice [0.8612] +2024-11-21 12:54:01.564109: Epoch time: 19.07 s +2024-11-21 12:54:02.356964: +2024-11-21 12:54:02.357183: Epoch 409 +2024-11-21 12:54:02.357302: Current learning rate: 0.00954 +2024-11-21 12:54:20.916914: train_loss -0.7617 +2024-11-21 12:54:20.917134: val_loss -0.6893 +2024-11-21 12:54:20.917208: Pseudo dice [0.8025] +2024-11-21 12:54:20.917284: Epoch time: 18.56 s +2024-11-21 12:54:21.726921: +2024-11-21 12:54:21.727123: Epoch 410 +2024-11-21 12:54:21.727237: Current learning rate: 0.00954 +2024-11-21 12:54:39.629420: train_loss -0.7505 +2024-11-21 12:54:39.629641: val_loss -0.7231 +2024-11-21 12:54:39.629716: Pseudo dice [0.8391] +2024-11-21 12:54:39.629790: Epoch time: 17.9 s +2024-11-21 12:54:40.508757: +2024-11-21 12:54:40.508989: Epoch 411 +2024-11-21 12:54:40.509101: Current learning rate: 0.00954 +2024-11-21 12:54:59.172697: train_loss -0.7612 +2024-11-21 12:54:59.172943: val_loss -0.7404 +2024-11-21 12:54:59.173027: Pseudo dice [0.822] +2024-11-21 12:54:59.173108: Epoch time: 18.66 s +2024-11-21 12:55:00.178760: +2024-11-21 12:55:00.178996: Epoch 412 +2024-11-21 12:55:00.179112: Current learning rate: 0.00954 +2024-11-21 12:55:19.916688: train_loss -0.7443 +2024-11-21 12:55:19.916890: val_loss -0.7097 +2024-11-21 12:55:19.916962: Pseudo dice [0.8046] +2024-11-21 12:55:19.917040: Epoch time: 19.74 s +2024-11-21 12:55:20.839052: +2024-11-21 12:55:20.839282: Epoch 413 +2024-11-21 12:55:20.839397: Current learning rate: 0.00953 +2024-11-21 12:55:39.747697: train_loss -0.7502 +2024-11-21 12:55:39.747913: val_loss -0.7232 +2024-11-21 12:55:39.747987: Pseudo dice [0.8145] +2024-11-21 12:55:39.748069: Epoch time: 18.91 s +2024-11-21 12:55:40.521761: +2024-11-21 12:55:40.521964: Epoch 414 +2024-11-21 12:55:40.522081: Current learning rate: 0.00953 +2024-11-21 12:55:58.758054: train_loss -0.753 +2024-11-21 12:55:58.758264: val_loss -0.7257 +2024-11-21 12:55:58.758341: Pseudo dice [0.8321] +2024-11-21 12:55:58.758417: Epoch time: 18.24 s +2024-11-21 12:55:59.536728: +2024-11-21 12:55:59.537007: Epoch 415 +2024-11-21 12:55:59.537135: Current learning rate: 0.00953 +2024-11-21 12:56:18.234925: train_loss -0.7639 +2024-11-21 12:56:18.235252: val_loss -0.7402 +2024-11-21 12:56:18.235334: Pseudo dice [0.8359] +2024-11-21 12:56:18.235414: Epoch time: 18.7 s +2024-11-21 12:56:19.449052: +2024-11-21 12:56:19.449259: Epoch 416 +2024-11-21 12:56:19.449372: Current learning rate: 0.00953 +2024-11-21 12:56:38.323254: train_loss -0.7613 +2024-11-21 12:56:38.323463: val_loss -0.7456 +2024-11-21 12:56:38.323537: Pseudo dice [0.8249] +2024-11-21 12:56:38.323612: Epoch time: 18.87 s +2024-11-21 12:56:39.106479: +2024-11-21 12:56:39.106674: Epoch 417 +2024-11-21 12:56:39.106786: Current learning rate: 0.00953 +2024-11-21 12:56:57.603730: train_loss -0.7622 +2024-11-21 12:56:57.603961: val_loss -0.7465 +2024-11-21 12:56:57.604042: Pseudo dice [0.831] +2024-11-21 12:56:57.604121: Epoch time: 18.5 s +2024-11-21 12:56:58.432492: +2024-11-21 12:56:58.432779: Epoch 418 +2024-11-21 12:56:58.432900: Current learning rate: 0.00953 +2024-11-21 12:57:17.378627: train_loss -0.7582 +2024-11-21 12:57:17.378874: val_loss -0.7658 +2024-11-21 12:57:17.378947: Pseudo dice [0.8328] +2024-11-21 12:57:17.379035: Epoch time: 18.95 s +2024-11-21 12:57:18.314435: +2024-11-21 12:57:18.314659: Epoch 419 +2024-11-21 12:57:18.314776: Current learning rate: 0.00953 +2024-11-21 12:57:36.668874: train_loss -0.7454 +2024-11-21 12:57:36.669087: val_loss -0.7303 +2024-11-21 12:57:36.669161: Pseudo dice [0.8408] +2024-11-21 12:57:36.669236: Epoch time: 18.36 s +2024-11-21 12:57:37.447380: +2024-11-21 12:57:37.447582: Epoch 420 +2024-11-21 12:57:37.447694: Current learning rate: 0.00953 +2024-11-21 12:57:55.632248: train_loss -0.7536 +2024-11-21 12:57:55.632469: val_loss -0.741 +2024-11-21 12:57:55.632544: Pseudo dice [0.8215] +2024-11-21 12:57:55.632619: Epoch time: 18.19 s +2024-11-21 12:57:56.562595: +2024-11-21 12:57:56.562812: Epoch 421 +2024-11-21 12:57:56.562926: Current learning rate: 0.00953 +2024-11-21 12:58:14.683586: train_loss -0.7618 +2024-11-21 12:58:14.688983: val_loss -0.7409 +2024-11-21 12:58:14.689114: Pseudo dice [0.8235] +2024-11-21 12:58:14.689200: Epoch time: 18.12 s +2024-11-21 12:58:15.497454: +2024-11-21 12:58:15.497684: Epoch 422 +2024-11-21 12:58:15.497801: Current learning rate: 0.00952 +2024-11-21 12:58:33.563288: train_loss -0.7549 +2024-11-21 12:58:33.563525: val_loss -0.721 +2024-11-21 12:58:33.563598: Pseudo dice [0.8263] +2024-11-21 12:58:33.563676: Epoch time: 18.07 s +2024-11-21 12:58:34.336905: +2024-11-21 12:58:34.337132: Epoch 423 +2024-11-21 12:58:34.337249: Current learning rate: 0.00952 +2024-11-21 12:58:52.370645: train_loss -0.7584 +2024-11-21 12:58:52.370861: val_loss -0.7256 +2024-11-21 12:58:52.370936: Pseudo dice [0.8083] +2024-11-21 12:58:52.373188: Epoch time: 18.03 s +2024-11-21 12:58:53.172625: +2024-11-21 12:58:53.172905: Epoch 424 +2024-11-21 12:58:53.173030: Current learning rate: 0.00952 +2024-11-21 12:59:10.892249: train_loss -0.748 +2024-11-21 12:59:10.892461: val_loss -0.7465 +2024-11-21 12:59:10.892534: Pseudo dice [0.8338] +2024-11-21 12:59:10.892610: Epoch time: 17.72 s +2024-11-21 12:59:11.671794: +2024-11-21 12:59:11.671998: Epoch 425 +2024-11-21 12:59:11.672106: Current learning rate: 0.00952 +2024-11-21 12:59:30.635198: train_loss -0.7647 +2024-11-21 12:59:30.635412: val_loss -0.7344 +2024-11-21 12:59:30.635486: Pseudo dice [0.8304] +2024-11-21 12:59:30.635566: Epoch time: 18.96 s +2024-11-21 12:59:31.463907: +2024-11-21 12:59:31.464268: Epoch 426 +2024-11-21 12:59:31.464386: Current learning rate: 0.00952 +2024-11-21 12:59:49.893219: train_loss -0.7595 +2024-11-21 12:59:49.893455: val_loss -0.7525 +2024-11-21 12:59:49.893541: Pseudo dice [0.8304] +2024-11-21 12:59:49.893623: Epoch time: 18.43 s +2024-11-21 12:59:50.675118: +2024-11-21 12:59:50.675788: Epoch 427 +2024-11-21 12:59:50.675927: Current learning rate: 0.00952 +2024-11-21 13:00:10.546369: train_loss -0.7543 +2024-11-21 13:00:10.546579: val_loss -0.7285 +2024-11-21 13:00:10.546652: Pseudo dice [0.8317] +2024-11-21 13:00:10.546728: Epoch time: 19.87 s +2024-11-21 13:00:11.705467: +2024-11-21 13:00:11.705924: Epoch 428 +2024-11-21 13:00:11.706064: Current learning rate: 0.00952 +2024-11-21 13:00:31.018210: train_loss -0.7529 +2024-11-21 13:00:31.018444: val_loss -0.7393 +2024-11-21 13:00:31.018522: Pseudo dice [0.8538] +2024-11-21 13:00:31.018603: Epoch time: 19.31 s +2024-11-21 13:00:31.796641: +2024-11-21 13:00:31.797066: Epoch 429 +2024-11-21 13:00:31.797199: Current learning rate: 0.00952 +2024-11-21 13:00:50.373111: train_loss -0.7659 +2024-11-21 13:00:50.373351: val_loss -0.7683 +2024-11-21 13:00:50.373429: Pseudo dice [0.8377] +2024-11-21 13:00:50.373509: Epoch time: 18.58 s +2024-11-21 13:00:51.159908: +2024-11-21 13:00:51.160359: Epoch 430 +2024-11-21 13:00:51.160493: Current learning rate: 0.00951 +2024-11-21 13:01:09.342386: train_loss -0.7662 +2024-11-21 13:01:09.342601: val_loss -0.7286 +2024-11-21 13:01:09.342680: Pseudo dice [0.815] +2024-11-21 13:01:09.342753: Epoch time: 18.18 s +2024-11-21 13:01:10.123330: +2024-11-21 13:01:10.123818: Epoch 431 +2024-11-21 13:01:10.123958: Current learning rate: 0.00951 +2024-11-21 13:01:28.532995: train_loss -0.7596 +2024-11-21 13:01:28.533210: val_loss -0.7445 +2024-11-21 13:01:28.533284: Pseudo dice [0.8234] +2024-11-21 13:01:28.533363: Epoch time: 18.41 s +2024-11-21 13:01:29.317908: +2024-11-21 13:01:29.318337: Epoch 432 +2024-11-21 13:01:29.318474: Current learning rate: 0.00951 +2024-11-21 13:01:48.197559: train_loss -0.7524 +2024-11-21 13:01:48.197789: val_loss -0.7568 +2024-11-21 13:01:48.197865: Pseudo dice [0.8446] +2024-11-21 13:01:48.197947: Epoch time: 18.88 s +2024-11-21 13:01:48.982868: +2024-11-21 13:01:48.983303: Epoch 433 +2024-11-21 13:01:48.983442: Current learning rate: 0.00951 +2024-11-21 13:02:08.280329: train_loss -0.7481 +2024-11-21 13:02:08.280575: val_loss -0.7532 +2024-11-21 13:02:08.280650: Pseudo dice [0.8158] +2024-11-21 13:02:08.280728: Epoch time: 19.3 s +2024-11-21 13:02:09.064309: +2024-11-21 13:02:09.064787: Epoch 434 +2024-11-21 13:02:09.064931: Current learning rate: 0.00951 +2024-11-21 13:02:27.999421: train_loss -0.7544 +2024-11-21 13:02:27.999628: val_loss -0.73 +2024-11-21 13:02:27.999707: Pseudo dice [0.8239] +2024-11-21 13:02:27.999782: Epoch time: 18.94 s +2024-11-21 13:02:28.794020: +2024-11-21 13:02:28.794296: Epoch 435 +2024-11-21 13:02:28.794410: Current learning rate: 0.00951 +2024-11-21 13:02:48.850244: train_loss -0.7562 +2024-11-21 13:02:48.851903: val_loss -0.7122 +2024-11-21 13:02:48.852052: Pseudo dice [0.8213] +2024-11-21 13:02:48.852184: Epoch time: 20.06 s +2024-11-21 13:02:49.632995: +2024-11-21 13:02:49.633193: Epoch 436 +2024-11-21 13:02:49.633306: Current learning rate: 0.00951 +2024-11-21 13:03:08.377089: train_loss -0.7621 +2024-11-21 13:03:08.377325: val_loss -0.7324 +2024-11-21 13:03:08.382612: Pseudo dice [0.8342] +2024-11-21 13:03:08.382735: Epoch time: 18.74 s +2024-11-21 13:03:09.310838: +2024-11-21 13:03:09.311055: Epoch 437 +2024-11-21 13:03:09.311173: Current learning rate: 0.00951 +2024-11-21 13:03:27.213419: train_loss -0.7644 +2024-11-21 13:03:27.213681: val_loss -0.7285 +2024-11-21 13:03:27.213793: Pseudo dice [0.8421] +2024-11-21 13:03:27.213893: Epoch time: 17.9 s +2024-11-21 13:03:27.992377: +2024-11-21 13:03:27.992569: Epoch 438 +2024-11-21 13:03:27.992681: Current learning rate: 0.00951 +2024-11-21 13:03:46.288035: train_loss -0.7658 +2024-11-21 13:03:46.288228: val_loss -0.7345 +2024-11-21 13:03:46.288299: Pseudo dice [0.8433] +2024-11-21 13:03:46.288372: Epoch time: 18.3 s +2024-11-21 13:03:47.104614: +2024-11-21 13:03:47.105104: Epoch 439 +2024-11-21 13:03:47.105240: Current learning rate: 0.0095 +2024-11-21 13:04:05.576278: train_loss -0.7584 +2024-11-21 13:04:05.576528: val_loss -0.7233 +2024-11-21 13:04:05.576609: Pseudo dice [0.835] +2024-11-21 13:04:05.576710: Epoch time: 18.47 s +2024-11-21 13:04:06.757740: +2024-11-21 13:04:06.758262: Epoch 440 +2024-11-21 13:04:06.758402: Current learning rate: 0.0095 +2024-11-21 13:04:24.344314: train_loss -0.7507 +2024-11-21 13:04:24.344574: val_loss -0.6844 +2024-11-21 13:04:24.344654: Pseudo dice [0.7752] +2024-11-21 13:04:24.359085: Epoch time: 17.59 s +2024-11-21 13:04:25.155849: +2024-11-21 13:04:25.156282: Epoch 441 +2024-11-21 13:04:25.156415: Current learning rate: 0.0095 +2024-11-21 13:04:43.761310: train_loss -0.7596 +2024-11-21 13:04:43.761535: val_loss -0.7405 +2024-11-21 13:04:43.761674: Pseudo dice [0.8352] +2024-11-21 13:04:43.761753: Epoch time: 18.61 s +2024-11-21 13:04:44.542648: +2024-11-21 13:04:44.543103: Epoch 442 +2024-11-21 13:04:44.543241: Current learning rate: 0.0095 +2024-11-21 13:05:02.765155: train_loss -0.7586 +2024-11-21 13:05:02.765379: val_loss -0.7424 +2024-11-21 13:05:02.770600: Pseudo dice [0.8506] +2024-11-21 13:05:02.770793: Epoch time: 18.22 s +2024-11-21 13:05:03.701674: +2024-11-21 13:05:03.702173: Epoch 443 +2024-11-21 13:05:03.702312: Current learning rate: 0.0095 +2024-11-21 13:05:23.571310: train_loss -0.7485 +2024-11-21 13:05:23.571531: val_loss -0.711 +2024-11-21 13:05:23.571609: Pseudo dice [0.8374] +2024-11-21 13:05:23.571688: Epoch time: 19.87 s +2024-11-21 13:05:24.539962: +2024-11-21 13:05:24.540512: Epoch 444 +2024-11-21 13:05:24.540684: Current learning rate: 0.0095 +2024-11-21 13:05:42.920983: train_loss -0.751 +2024-11-21 13:05:42.921220: val_loss -0.7459 +2024-11-21 13:05:42.926450: Pseudo dice [0.8355] +2024-11-21 13:05:42.926654: Epoch time: 18.38 s +2024-11-21 13:05:43.735379: +2024-11-21 13:05:43.735846: Epoch 445 +2024-11-21 13:05:43.735986: Current learning rate: 0.0095 +2024-11-21 13:06:02.759737: train_loss -0.7593 +2024-11-21 13:06:02.759951: val_loss -0.7551 +2024-11-21 13:06:02.760032: Pseudo dice [0.8615] +2024-11-21 13:06:02.760109: Epoch time: 19.03 s +2024-11-21 13:06:03.568329: +2024-11-21 13:06:03.568789: Epoch 446 +2024-11-21 13:06:03.568936: Current learning rate: 0.0095 +2024-11-21 13:06:22.331106: train_loss -0.76 +2024-11-21 13:06:22.331318: val_loss -0.7271 +2024-11-21 13:06:22.331389: Pseudo dice [0.8357] +2024-11-21 13:06:22.331464: Epoch time: 18.76 s +2024-11-21 13:06:23.149687: +2024-11-21 13:06:23.149916: Epoch 447 +2024-11-21 13:06:23.150030: Current learning rate: 0.0095 +2024-11-21 13:06:42.026797: train_loss -0.7603 +2024-11-21 13:06:42.027010: val_loss -0.7124 +2024-11-21 13:06:42.027088: Pseudo dice [0.8368] +2024-11-21 13:06:42.027165: Epoch time: 18.88 s +2024-11-21 13:06:42.796921: +2024-11-21 13:06:42.797180: Epoch 448 +2024-11-21 13:06:42.797299: Current learning rate: 0.00949 +2024-11-21 13:07:00.342630: train_loss -0.7647 +2024-11-21 13:07:00.342862: val_loss -0.7236 +2024-11-21 13:07:00.342935: Pseudo dice [0.8111] +2024-11-21 13:07:00.343024: Epoch time: 17.55 s +2024-11-21 13:07:01.185524: +2024-11-21 13:07:01.185719: Epoch 449 +2024-11-21 13:07:01.185833: Current learning rate: 0.00949 +2024-11-21 13:07:20.538096: train_loss -0.7552 +2024-11-21 13:07:20.538308: val_loss -0.7594 +2024-11-21 13:07:20.538385: Pseudo dice [0.851] +2024-11-21 13:07:20.538463: Epoch time: 19.35 s +2024-11-21 13:07:21.561210: +2024-11-21 13:07:21.561445: Epoch 450 +2024-11-21 13:07:21.561563: Current learning rate: 0.00949 +2024-11-21 13:07:40.240572: train_loss -0.7606 +2024-11-21 13:07:40.240780: val_loss -0.7392 +2024-11-21 13:07:40.240852: Pseudo dice [0.8445] +2024-11-21 13:07:40.240927: Epoch time: 18.68 s +2024-11-21 13:07:41.163718: +2024-11-21 13:07:41.164228: Epoch 451 +2024-11-21 13:07:41.164356: Current learning rate: 0.00949 +2024-11-21 13:08:01.137860: train_loss -0.749 +2024-11-21 13:08:01.138110: val_loss -0.7312 +2024-11-21 13:08:01.138186: Pseudo dice [0.8417] +2024-11-21 13:08:01.138272: Epoch time: 19.97 s +2024-11-21 13:08:02.247006: +2024-11-21 13:08:02.247433: Epoch 452 +2024-11-21 13:08:02.247566: Current learning rate: 0.00949 +2024-11-21 13:08:21.642683: train_loss -0.746 +2024-11-21 13:08:21.642891: val_loss -0.7223 +2024-11-21 13:08:21.642966: Pseudo dice [0.7997] +2024-11-21 13:08:21.643047: Epoch time: 19.4 s +2024-11-21 13:08:22.405489: +2024-11-21 13:08:22.405965: Epoch 453 +2024-11-21 13:08:22.406114: Current learning rate: 0.00949 +2024-11-21 13:08:41.253503: train_loss -0.7593 +2024-11-21 13:08:41.253744: val_loss -0.7483 +2024-11-21 13:08:41.253821: Pseudo dice [0.8202] +2024-11-21 13:08:41.253897: Epoch time: 18.85 s +2024-11-21 13:08:42.042980: +2024-11-21 13:08:42.043426: Epoch 454 +2024-11-21 13:08:42.043561: Current learning rate: 0.00949 +2024-11-21 13:09:01.379890: train_loss -0.7551 +2024-11-21 13:09:01.380146: val_loss -0.7315 +2024-11-21 13:09:01.380221: Pseudo dice [0.8299] +2024-11-21 13:09:01.380309: Epoch time: 19.34 s +2024-11-21 13:09:02.370683: +2024-11-21 13:09:02.371093: Epoch 455 +2024-11-21 13:09:02.371223: Current learning rate: 0.00949 +2024-11-21 13:09:21.716360: train_loss -0.7642 +2024-11-21 13:09:21.716581: val_loss -0.7652 +2024-11-21 13:09:21.716663: Pseudo dice [0.8365] +2024-11-21 13:09:21.716742: Epoch time: 19.35 s +2024-11-21 13:09:22.497180: +2024-11-21 13:09:22.497598: Epoch 456 +2024-11-21 13:09:22.497747: Current learning rate: 0.00949 +2024-11-21 13:09:41.757936: train_loss -0.7647 +2024-11-21 13:09:41.758225: val_loss -0.722 +2024-11-21 13:09:41.758307: Pseudo dice [0.8298] +2024-11-21 13:09:41.758386: Epoch time: 19.26 s +2024-11-21 13:09:42.544367: +2024-11-21 13:09:42.544886: Epoch 457 +2024-11-21 13:09:42.545019: Current learning rate: 0.00948 +2024-11-21 13:10:01.702213: train_loss -0.7541 +2024-11-21 13:10:01.702430: val_loss -0.7328 +2024-11-21 13:10:01.702508: Pseudo dice [0.8476] +2024-11-21 13:10:01.702588: Epoch time: 19.16 s +2024-11-21 13:10:02.487830: +2024-11-21 13:10:02.488300: Epoch 458 +2024-11-21 13:10:02.488458: Current learning rate: 0.00948 +2024-11-21 13:10:21.748002: train_loss -0.762 +2024-11-21 13:10:21.748242: val_loss -0.7354 +2024-11-21 13:10:21.748317: Pseudo dice [0.8657] +2024-11-21 13:10:21.748399: Epoch time: 19.26 s +2024-11-21 13:10:22.528057: +2024-11-21 13:10:22.528516: Epoch 459 +2024-11-21 13:10:22.528652: Current learning rate: 0.00948 +2024-11-21 13:10:41.444708: train_loss -0.7584 +2024-11-21 13:10:41.444916: val_loss -0.7461 +2024-11-21 13:10:41.444997: Pseudo dice [0.8299] +2024-11-21 13:10:41.445073: Epoch time: 18.92 s +2024-11-21 13:10:42.224485: +2024-11-21 13:10:42.224695: Epoch 460 +2024-11-21 13:10:42.224809: Current learning rate: 0.00948 +2024-11-21 13:11:00.327493: train_loss -0.7587 +2024-11-21 13:11:00.327715: val_loss -0.7137 +2024-11-21 13:11:00.327790: Pseudo dice [0.8221] +2024-11-21 13:11:00.327869: Epoch time: 18.1 s +2024-11-21 13:11:01.108721: +2024-11-21 13:11:01.109030: Epoch 461 +2024-11-21 13:11:01.109146: Current learning rate: 0.00948 +2024-11-21 13:11:19.632705: train_loss -0.7571 +2024-11-21 13:11:19.632926: val_loss -0.7416 +2024-11-21 13:11:19.633050: Pseudo dice [0.8399] +2024-11-21 13:11:19.633135: Epoch time: 18.52 s +2024-11-21 13:11:20.421066: +2024-11-21 13:11:20.421269: Epoch 462 +2024-11-21 13:11:20.421387: Current learning rate: 0.00948 +2024-11-21 13:11:39.648594: train_loss -0.7577 +2024-11-21 13:11:39.654025: val_loss -0.7135 +2024-11-21 13:11:39.654160: Pseudo dice [0.8143] +2024-11-21 13:11:39.654246: Epoch time: 19.23 s +2024-11-21 13:11:40.536917: +2024-11-21 13:11:40.537119: Epoch 463 +2024-11-21 13:11:40.537250: Current learning rate: 0.00948 +2024-11-21 13:11:57.743749: train_loss -0.76 +2024-11-21 13:11:57.743949: val_loss -0.7439 +2024-11-21 13:11:57.744032: Pseudo dice [0.8358] +2024-11-21 13:11:57.744108: Epoch time: 17.21 s +2024-11-21 13:11:58.883737: +2024-11-21 13:11:58.883971: Epoch 464 +2024-11-21 13:11:58.884092: Current learning rate: 0.00948 +2024-11-21 13:12:17.366704: train_loss -0.7685 +2024-11-21 13:12:17.366918: val_loss -0.7352 +2024-11-21 13:12:17.372128: Pseudo dice [0.8452] +2024-11-21 13:12:17.372289: Epoch time: 18.48 s +2024-11-21 13:12:18.322384: +2024-11-21 13:12:18.322634: Epoch 465 +2024-11-21 13:12:18.322763: Current learning rate: 0.00948 +2024-11-21 13:12:36.949349: train_loss -0.7536 +2024-11-21 13:12:36.949580: val_loss -0.7138 +2024-11-21 13:12:36.949653: Pseudo dice [0.8426] +2024-11-21 13:12:36.949731: Epoch time: 18.63 s +2024-11-21 13:12:37.731301: +2024-11-21 13:12:37.731547: Epoch 466 +2024-11-21 13:12:37.731667: Current learning rate: 0.00947 +2024-11-21 13:12:55.840338: train_loss -0.7612 +2024-11-21 13:12:55.840546: val_loss -0.7152 +2024-11-21 13:12:55.840619: Pseudo dice [0.822] +2024-11-21 13:12:55.842915: Epoch time: 18.11 s +2024-11-21 13:12:56.628783: +2024-11-21 13:12:56.629006: Epoch 467 +2024-11-21 13:12:56.629119: Current learning rate: 0.00947 +2024-11-21 13:13:14.367688: train_loss -0.7626 +2024-11-21 13:13:14.367892: val_loss -0.733 +2024-11-21 13:13:14.367967: Pseudo dice [0.8408] +2024-11-21 13:13:14.368050: Epoch time: 17.74 s +2024-11-21 13:13:15.375670: +2024-11-21 13:13:15.375953: Epoch 468 +2024-11-21 13:13:15.376069: Current learning rate: 0.00947 +2024-11-21 13:13:34.684234: train_loss -0.7581 +2024-11-21 13:13:34.684451: val_loss -0.7469 +2024-11-21 13:13:34.684522: Pseudo dice [0.8434] +2024-11-21 13:13:34.684602: Epoch time: 19.31 s +2024-11-21 13:13:35.467685: +2024-11-21 13:13:35.467884: Epoch 469 +2024-11-21 13:13:35.468003: Current learning rate: 0.00947 +2024-11-21 13:13:54.248595: train_loss -0.7685 +2024-11-21 13:13:54.248833: val_loss -0.7357 +2024-11-21 13:13:54.248912: Pseudo dice [0.8553] +2024-11-21 13:13:54.262054: Epoch time: 18.78 s +2024-11-21 13:13:54.262248: Yayy! New best EMA pseudo Dice: 0.8373 +2024-11-21 13:13:55.323027: +2024-11-21 13:13:55.323245: Epoch 470 +2024-11-21 13:13:55.323356: Current learning rate: 0.00947 +2024-11-21 13:14:14.429578: train_loss -0.7511 +2024-11-21 13:14:14.429791: val_loss -0.7554 +2024-11-21 13:14:14.429867: Pseudo dice [0.8181] +2024-11-21 13:14:14.429945: Epoch time: 19.11 s +2024-11-21 13:14:15.315932: +2024-11-21 13:14:15.316162: Epoch 471 +2024-11-21 13:14:15.316276: Current learning rate: 0.00947 +2024-11-21 13:14:34.393371: train_loss -0.7576 +2024-11-21 13:14:34.393651: val_loss -0.7379 +2024-11-21 13:14:34.393730: Pseudo dice [0.8385] +2024-11-21 13:14:34.393806: Epoch time: 19.08 s +2024-11-21 13:14:35.192439: +2024-11-21 13:14:35.192652: Epoch 472 +2024-11-21 13:14:35.192763: Current learning rate: 0.00947 +2024-11-21 13:14:53.477170: train_loss -0.7621 +2024-11-21 13:14:53.477383: val_loss -0.7395 +2024-11-21 13:14:53.477539: Pseudo dice [0.824] +2024-11-21 13:14:53.477621: Epoch time: 18.29 s +2024-11-21 13:14:54.270618: +2024-11-21 13:14:54.270871: Epoch 473 +2024-11-21 13:14:54.270984: Current learning rate: 0.00947 +2024-11-21 13:15:11.774689: train_loss -0.7637 +2024-11-21 13:15:11.774927: val_loss -0.6917 +2024-11-21 13:15:11.775032: Pseudo dice [0.8009] +2024-11-21 13:15:11.775167: Epoch time: 17.5 s +2024-11-21 13:15:12.560245: +2024-11-21 13:15:12.560443: Epoch 474 +2024-11-21 13:15:12.560556: Current learning rate: 0.00947 +2024-11-21 13:15:31.031989: train_loss -0.7642 +2024-11-21 13:15:31.034359: val_loss -0.7446 +2024-11-21 13:15:31.034458: Pseudo dice [0.8315] +2024-11-21 13:15:31.034540: Epoch time: 18.47 s +2024-11-21 13:15:31.815671: +2024-11-21 13:15:31.816070: Epoch 475 +2024-11-21 13:15:31.816199: Current learning rate: 0.00946 +2024-11-21 13:15:50.397385: train_loss -0.7575 +2024-11-21 13:15:50.397655: val_loss -0.7394 +2024-11-21 13:15:50.397733: Pseudo dice [0.8365] +2024-11-21 13:15:50.397809: Epoch time: 18.58 s +2024-11-21 13:15:51.576384: +2024-11-21 13:15:51.576665: Epoch 476 +2024-11-21 13:15:51.576797: Current learning rate: 0.00946 +2024-11-21 13:16:11.238347: train_loss -0.7601 +2024-11-21 13:16:11.238595: val_loss -0.7509 +2024-11-21 13:16:11.238666: Pseudo dice [0.8509] +2024-11-21 13:16:11.240945: Epoch time: 19.66 s +2024-11-21 13:16:12.044385: +2024-11-21 13:16:12.044682: Epoch 477 +2024-11-21 13:16:12.044797: Current learning rate: 0.00946 +2024-11-21 13:16:30.959135: train_loss -0.7542 +2024-11-21 13:16:30.959337: val_loss -0.6773 +2024-11-21 13:16:30.959413: Pseudo dice [0.8386] +2024-11-21 13:16:30.959511: Epoch time: 18.92 s +2024-11-21 13:16:31.741774: +2024-11-21 13:16:31.742015: Epoch 478 +2024-11-21 13:16:31.742131: Current learning rate: 0.00946 +2024-11-21 13:16:50.115659: train_loss -0.7454 +2024-11-21 13:16:50.115901: val_loss -0.7394 +2024-11-21 13:16:50.115983: Pseudo dice [0.817] +2024-11-21 13:16:50.116069: Epoch time: 18.37 s +2024-11-21 13:16:50.910148: +2024-11-21 13:16:50.910357: Epoch 479 +2024-11-21 13:16:50.910476: Current learning rate: 0.00946 +2024-11-21 13:17:09.695796: train_loss -0.7542 +2024-11-21 13:17:09.696052: val_loss -0.7497 +2024-11-21 13:17:09.696128: Pseudo dice [0.8573] +2024-11-21 13:17:09.696211: Epoch time: 18.79 s +2024-11-21 13:17:10.513899: +2024-11-21 13:17:10.514110: Epoch 480 +2024-11-21 13:17:10.514225: Current learning rate: 0.00946 +2024-11-21 13:17:28.778681: train_loss -0.7557 +2024-11-21 13:17:28.778929: val_loss -0.7283 +2024-11-21 13:17:28.779008: Pseudo dice [0.8257] +2024-11-21 13:17:28.779085: Epoch time: 18.27 s +2024-11-21 13:17:29.595805: +2024-11-21 13:17:29.596014: Epoch 481 +2024-11-21 13:17:29.596125: Current learning rate: 0.00946 +2024-11-21 13:17:48.614816: train_loss -0.7574 +2024-11-21 13:17:48.615034: val_loss -0.75 +2024-11-21 13:17:48.615107: Pseudo dice [0.8606] +2024-11-21 13:17:48.615182: Epoch time: 19.02 s +2024-11-21 13:17:49.511067: +2024-11-21 13:17:49.511281: Epoch 482 +2024-11-21 13:17:49.511605: Current learning rate: 0.00946 +2024-11-21 13:18:09.383325: train_loss -0.7624 +2024-11-21 13:18:09.383536: val_loss -0.7224 +2024-11-21 13:18:09.383609: Pseudo dice [0.8391] +2024-11-21 13:18:09.383686: Epoch time: 19.87 s +2024-11-21 13:18:10.177551: +2024-11-21 13:18:10.177748: Epoch 483 +2024-11-21 13:18:10.177861: Current learning rate: 0.00945 +2024-11-21 13:18:30.070255: train_loss -0.7687 +2024-11-21 13:18:30.070498: val_loss -0.719 +2024-11-21 13:18:30.070576: Pseudo dice [0.8302] +2024-11-21 13:18:30.070657: Epoch time: 19.89 s +2024-11-21 13:18:30.889137: +2024-11-21 13:18:30.889414: Epoch 484 +2024-11-21 13:18:30.889532: Current learning rate: 0.00945 +2024-11-21 13:18:48.319976: train_loss -0.7592 +2024-11-21 13:18:48.320195: val_loss -0.7403 +2024-11-21 13:18:48.320267: Pseudo dice [0.8412] +2024-11-21 13:18:48.320345: Epoch time: 17.43 s +2024-11-21 13:18:49.109948: +2024-11-21 13:18:49.110210: Epoch 485 +2024-11-21 13:18:49.110321: Current learning rate: 0.00945 +2024-11-21 13:19:08.276646: train_loss -0.7725 +2024-11-21 13:19:08.276906: val_loss -0.7355 +2024-11-21 13:19:08.276986: Pseudo dice [0.8231] +2024-11-21 13:19:08.277069: Epoch time: 19.17 s +2024-11-21 13:19:09.063707: +2024-11-21 13:19:09.063913: Epoch 486 +2024-11-21 13:19:09.064030: Current learning rate: 0.00945 +2024-11-21 13:19:28.544963: train_loss -0.7618 +2024-11-21 13:19:28.545202: val_loss -0.719 +2024-11-21 13:19:28.545275: Pseudo dice [0.8078] +2024-11-21 13:19:28.545349: Epoch time: 19.48 s +2024-11-21 13:19:29.336054: +2024-11-21 13:19:29.336389: Epoch 487 +2024-11-21 13:19:29.336504: Current learning rate: 0.00945 +2024-11-21 13:19:48.896693: train_loss -0.7454 +2024-11-21 13:19:48.896928: val_loss -0.7349 +2024-11-21 13:19:48.897009: Pseudo dice [0.8375] +2024-11-21 13:19:48.897171: Epoch time: 19.56 s +2024-11-21 13:19:50.099381: +2024-11-21 13:19:50.099604: Epoch 488 +2024-11-21 13:19:50.099715: Current learning rate: 0.00945 +2024-11-21 13:20:08.450214: train_loss -0.752 +2024-11-21 13:20:08.450423: val_loss -0.7319 +2024-11-21 13:20:08.450564: Pseudo dice [0.8371] +2024-11-21 13:20:08.450639: Epoch time: 18.35 s +2024-11-21 13:20:09.239894: +2024-11-21 13:20:09.240196: Epoch 489 +2024-11-21 13:20:09.240308: Current learning rate: 0.00945 +2024-11-21 13:20:28.028779: train_loss -0.7599 +2024-11-21 13:20:28.029063: val_loss -0.7606 +2024-11-21 13:20:28.029145: Pseudo dice [0.8343] +2024-11-21 13:20:28.029245: Epoch time: 18.79 s +2024-11-21 13:20:28.812987: +2024-11-21 13:20:28.813248: Epoch 490 +2024-11-21 13:20:28.813365: Current learning rate: 0.00945 +2024-11-21 13:20:47.745114: train_loss -0.7487 +2024-11-21 13:20:47.745350: val_loss -0.6885 +2024-11-21 13:20:47.745425: Pseudo dice [0.7905] +2024-11-21 13:20:47.745510: Epoch time: 18.93 s +2024-11-21 13:20:48.536088: +2024-11-21 13:20:48.536309: Epoch 491 +2024-11-21 13:20:48.536424: Current learning rate: 0.00945 +2024-11-21 13:21:06.930880: train_loss -0.7549 +2024-11-21 13:21:06.931089: val_loss -0.7096 +2024-11-21 13:21:06.931165: Pseudo dice [0.8107] +2024-11-21 13:21:06.931299: Epoch time: 18.4 s +2024-11-21 13:21:07.712220: +2024-11-21 13:21:07.712430: Epoch 492 +2024-11-21 13:21:07.712541: Current learning rate: 0.00944 +2024-11-21 13:21:25.116685: train_loss -0.7636 +2024-11-21 13:21:25.116910: val_loss -0.7115 +2024-11-21 13:21:25.116986: Pseudo dice [0.8421] +2024-11-21 13:21:25.117070: Epoch time: 17.41 s +2024-11-21 13:21:25.912064: +2024-11-21 13:21:25.912282: Epoch 493 +2024-11-21 13:21:25.912400: Current learning rate: 0.00944 +2024-11-21 13:21:44.533955: train_loss -0.7639 +2024-11-21 13:21:44.534172: val_loss -0.7477 +2024-11-21 13:21:44.534246: Pseudo dice [0.8323] +2024-11-21 13:21:44.534321: Epoch time: 18.62 s +2024-11-21 13:21:45.326291: +2024-11-21 13:21:45.326531: Epoch 494 +2024-11-21 13:21:45.326645: Current learning rate: 0.00944 +2024-11-21 13:22:04.583886: train_loss -0.772 +2024-11-21 13:22:04.584136: val_loss -0.7337 +2024-11-21 13:22:04.584211: Pseudo dice [0.8272] +2024-11-21 13:22:04.584315: Epoch time: 19.26 s +2024-11-21 13:22:05.379321: +2024-11-21 13:22:05.379511: Epoch 495 +2024-11-21 13:22:05.379624: Current learning rate: 0.00944 +2024-11-21 13:22:23.846718: train_loss -0.7753 +2024-11-21 13:22:23.846925: val_loss -0.7606 +2024-11-21 13:22:23.847006: Pseudo dice [0.8522] +2024-11-21 13:22:23.847081: Epoch time: 18.47 s +2024-11-21 13:22:24.639019: +2024-11-21 13:22:24.639291: Epoch 496 +2024-11-21 13:22:24.639403: Current learning rate: 0.00944 +2024-11-21 13:22:44.016778: train_loss -0.7614 +2024-11-21 13:22:44.016998: val_loss -0.7262 +2024-11-21 13:22:44.017075: Pseudo dice [0.8373] +2024-11-21 13:22:44.017149: Epoch time: 19.38 s +2024-11-21 13:22:44.805269: +2024-11-21 13:22:44.805493: Epoch 497 +2024-11-21 13:22:44.805619: Current learning rate: 0.00944 +2024-11-21 13:23:03.972656: train_loss -0.7477 +2024-11-21 13:23:03.972863: val_loss -0.7215 +2024-11-21 13:23:03.972939: Pseudo dice [0.8228] +2024-11-21 13:23:03.973027: Epoch time: 19.17 s +2024-11-21 13:23:04.768571: +2024-11-21 13:23:04.768775: Epoch 498 +2024-11-21 13:23:04.768890: Current learning rate: 0.00944 +2024-11-21 13:23:23.959450: train_loss -0.757 +2024-11-21 13:23:23.959681: val_loss -0.7084 +2024-11-21 13:23:23.959753: Pseudo dice [0.7962] +2024-11-21 13:23:23.959831: Epoch time: 19.19 s +2024-11-21 13:23:24.754531: +2024-11-21 13:23:24.754718: Epoch 499 +2024-11-21 13:23:24.754865: Current learning rate: 0.00944 +2024-11-21 13:23:43.150218: train_loss -0.7535 +2024-11-21 13:23:43.150451: val_loss -0.7595 +2024-11-21 13:23:43.150532: Pseudo dice [0.8409] +2024-11-21 13:23:43.150616: Epoch time: 18.4 s +2024-11-21 13:23:44.557631: +2024-11-21 13:23:44.557909: Epoch 500 +2024-11-21 13:23:44.558029: Current learning rate: 0.00944 +2024-11-21 13:24:03.153398: train_loss -0.7616 +2024-11-21 13:24:03.153632: val_loss -0.7415 +2024-11-21 13:24:03.153707: Pseudo dice [0.8297] +2024-11-21 13:24:03.153781: Epoch time: 18.6 s +2024-11-21 13:24:04.003576: +2024-11-21 13:24:04.003785: Epoch 501 +2024-11-21 13:24:04.003896: Current learning rate: 0.00943 +2024-11-21 13:24:21.474028: train_loss -0.7435 +2024-11-21 13:24:21.474264: val_loss -0.7445 +2024-11-21 13:24:21.474338: Pseudo dice [0.845] +2024-11-21 13:24:21.474417: Epoch time: 17.47 s +2024-11-21 13:24:22.260531: +2024-11-21 13:24:22.260753: Epoch 502 +2024-11-21 13:24:22.260871: Current learning rate: 0.00943 +2024-11-21 13:24:41.835550: train_loss -0.757 +2024-11-21 13:24:41.835787: val_loss -0.7274 +2024-11-21 13:24:41.835863: Pseudo dice [0.8369] +2024-11-21 13:24:41.835941: Epoch time: 19.58 s +2024-11-21 13:24:42.622444: +2024-11-21 13:24:42.622656: Epoch 503 +2024-11-21 13:24:42.622773: Current learning rate: 0.00943 +2024-11-21 13:25:01.215794: train_loss -0.7482 +2024-11-21 13:25:01.216011: val_loss -0.7343 +2024-11-21 13:25:01.216085: Pseudo dice [0.8181] +2024-11-21 13:25:01.216159: Epoch time: 18.59 s +2024-11-21 13:25:02.012132: +2024-11-21 13:25:02.012359: Epoch 504 +2024-11-21 13:25:02.012471: Current learning rate: 0.00943 +2024-11-21 13:25:19.954346: train_loss -0.7556 +2024-11-21 13:25:19.954562: val_loss -0.6984 +2024-11-21 13:25:19.954637: Pseudo dice [0.8463] +2024-11-21 13:25:19.956907: Epoch time: 17.94 s +2024-11-21 13:25:20.900358: +2024-11-21 13:25:20.900620: Epoch 505 +2024-11-21 13:25:20.900730: Current learning rate: 0.00943 +2024-11-21 13:25:40.334130: train_loss -0.7435 +2024-11-21 13:25:40.334372: val_loss -0.7428 +2024-11-21 13:25:40.334448: Pseudo dice [0.8419] +2024-11-21 13:25:40.334538: Epoch time: 19.43 s +2024-11-21 13:25:41.132771: +2024-11-21 13:25:41.132986: Epoch 506 +2024-11-21 13:25:41.133104: Current learning rate: 0.00943 +2024-11-21 13:26:00.229698: train_loss -0.7662 +2024-11-21 13:26:00.229915: val_loss -0.7575 +2024-11-21 13:26:00.229999: Pseudo dice [0.8254] +2024-11-21 13:26:00.230076: Epoch time: 19.1 s +2024-11-21 13:26:01.028291: +2024-11-21 13:26:01.028559: Epoch 507 +2024-11-21 13:26:01.028673: Current learning rate: 0.00943 +2024-11-21 13:26:20.395395: train_loss -0.7624 +2024-11-21 13:26:20.395620: val_loss -0.7069 +2024-11-21 13:26:20.395699: Pseudo dice [0.8419] +2024-11-21 13:26:20.395778: Epoch time: 19.37 s +2024-11-21 13:26:21.193293: +2024-11-21 13:26:21.193521: Epoch 508 +2024-11-21 13:26:21.193825: Current learning rate: 0.00943 +2024-11-21 13:26:40.827793: train_loss -0.7596 +2024-11-21 13:26:40.828013: val_loss -0.7323 +2024-11-21 13:26:40.828089: Pseudo dice [0.847] +2024-11-21 13:26:40.828167: Epoch time: 19.64 s +2024-11-21 13:26:41.652670: +2024-11-21 13:26:41.652879: Epoch 509 +2024-11-21 13:26:41.653002: Current learning rate: 0.00943 +2024-11-21 13:27:00.014950: train_loss -0.7629 +2024-11-21 13:27:00.015185: val_loss -0.716 +2024-11-21 13:27:00.015257: Pseudo dice [0.8365] +2024-11-21 13:27:00.015337: Epoch time: 18.36 s +2024-11-21 13:27:00.813781: +2024-11-21 13:27:00.814008: Epoch 510 +2024-11-21 13:27:00.814121: Current learning rate: 0.00942 +2024-11-21 13:27:18.888833: train_loss -0.7604 +2024-11-21 13:27:18.889136: val_loss -0.7137 +2024-11-21 13:27:18.889215: Pseudo dice [0.8428] +2024-11-21 13:27:18.889290: Epoch time: 18.08 s +2024-11-21 13:27:20.035534: +2024-11-21 13:27:20.035755: Epoch 511 +2024-11-21 13:27:20.035864: Current learning rate: 0.00942 +2024-11-21 13:27:38.303565: train_loss -0.7719 +2024-11-21 13:27:38.303828: val_loss -0.7322 +2024-11-21 13:27:38.303904: Pseudo dice [0.8327] +2024-11-21 13:27:38.303979: Epoch time: 18.27 s +2024-11-21 13:27:39.101452: +2024-11-21 13:27:39.101833: Epoch 512 +2024-11-21 13:27:39.101945: Current learning rate: 0.00942 +2024-11-21 13:27:58.189160: train_loss -0.766 +2024-11-21 13:27:58.189406: val_loss -0.7525 +2024-11-21 13:27:58.189482: Pseudo dice [0.8371] +2024-11-21 13:27:58.189566: Epoch time: 19.09 s +2024-11-21 13:27:58.987270: +2024-11-21 13:27:58.987488: Epoch 513 +2024-11-21 13:27:58.987601: Current learning rate: 0.00942 +2024-11-21 13:28:18.107566: train_loss -0.7584 +2024-11-21 13:28:18.107781: val_loss -0.7182 +2024-11-21 13:28:18.107864: Pseudo dice [0.84] +2024-11-21 13:28:18.107947: Epoch time: 19.12 s +2024-11-21 13:28:18.899184: +2024-11-21 13:28:18.899411: Epoch 514 +2024-11-21 13:28:18.899523: Current learning rate: 0.00942 +2024-11-21 13:28:37.797539: train_loss -0.7562 +2024-11-21 13:28:37.797764: val_loss -0.7399 +2024-11-21 13:28:37.797837: Pseudo dice [0.8396] +2024-11-21 13:28:37.797936: Epoch time: 18.9 s +2024-11-21 13:28:38.597552: +2024-11-21 13:28:38.597776: Epoch 515 +2024-11-21 13:28:38.597889: Current learning rate: 0.00942 +2024-11-21 13:28:57.405073: train_loss -0.7467 +2024-11-21 13:28:57.405275: val_loss -0.7044 +2024-11-21 13:28:57.405349: Pseudo dice [0.8157] +2024-11-21 13:28:57.405426: Epoch time: 18.81 s +2024-11-21 13:28:58.204419: +2024-11-21 13:28:58.204718: Epoch 516 +2024-11-21 13:28:58.204833: Current learning rate: 0.00942 +2024-11-21 13:29:16.777034: train_loss -0.7699 +2024-11-21 13:29:16.777351: val_loss -0.7342 +2024-11-21 13:29:16.777428: Pseudo dice [0.8396] +2024-11-21 13:29:16.777513: Epoch time: 18.57 s +2024-11-21 13:29:17.582835: +2024-11-21 13:29:17.583034: Epoch 517 +2024-11-21 13:29:17.583145: Current learning rate: 0.00942 +2024-11-21 13:29:37.136352: train_loss -0.732 +2024-11-21 13:29:37.136567: val_loss -0.724 +2024-11-21 13:29:37.136642: Pseudo dice [0.8359] +2024-11-21 13:29:37.136719: Epoch time: 19.55 s +2024-11-21 13:29:38.065305: +2024-11-21 13:29:38.065526: Epoch 518 +2024-11-21 13:29:38.065641: Current learning rate: 0.00942 +2024-11-21 13:29:55.650320: train_loss -0.7476 +2024-11-21 13:29:55.650540: val_loss -0.7196 +2024-11-21 13:29:55.650617: Pseudo dice [0.8303] +2024-11-21 13:29:55.650699: Epoch time: 17.59 s +2024-11-21 13:29:56.485711: +2024-11-21 13:29:56.485926: Epoch 519 +2024-11-21 13:29:56.486045: Current learning rate: 0.00941 +2024-11-21 13:30:15.618880: train_loss -0.7463 +2024-11-21 13:30:15.619098: val_loss -0.7019 +2024-11-21 13:30:15.619170: Pseudo dice [0.807] +2024-11-21 13:30:15.619246: Epoch time: 19.13 s +2024-11-21 13:30:16.421064: +2024-11-21 13:30:16.421287: Epoch 520 +2024-11-21 13:30:16.421410: Current learning rate: 0.00941 +2024-11-21 13:30:35.419641: train_loss -0.7512 +2024-11-21 13:30:35.419969: val_loss -0.7476 +2024-11-21 13:30:35.420049: Pseudo dice [0.8249] +2024-11-21 13:30:35.420132: Epoch time: 19.0 s +2024-11-21 13:30:36.223891: +2024-11-21 13:30:36.224323: Epoch 521 +2024-11-21 13:30:36.224436: Current learning rate: 0.00941 +2024-11-21 13:30:55.537786: train_loss -0.767 +2024-11-21 13:30:55.537997: val_loss -0.7357 +2024-11-21 13:30:55.538076: Pseudo dice [0.8432] +2024-11-21 13:30:55.538153: Epoch time: 19.31 s +2024-11-21 13:30:56.332490: +2024-11-21 13:30:56.332764: Epoch 522 +2024-11-21 13:30:56.332877: Current learning rate: 0.00941 +2024-11-21 13:31:15.807426: train_loss -0.764 +2024-11-21 13:31:15.807647: val_loss -0.7126 +2024-11-21 13:31:15.807717: Pseudo dice [0.8415] +2024-11-21 13:31:15.807799: Epoch time: 19.48 s +2024-11-21 13:31:16.646131: +2024-11-21 13:31:16.646366: Epoch 523 +2024-11-21 13:31:16.646477: Current learning rate: 0.00941 +2024-11-21 13:31:35.417809: train_loss -0.7646 +2024-11-21 13:31:35.418048: val_loss -0.7234 +2024-11-21 13:31:35.418123: Pseudo dice [0.8079] +2024-11-21 13:31:35.423337: Epoch time: 18.77 s +2024-11-21 13:31:36.364719: +2024-11-21 13:31:36.364949: Epoch 524 +2024-11-21 13:31:36.365064: Current learning rate: 0.00941 +2024-11-21 13:31:55.718734: train_loss -0.757 +2024-11-21 13:31:55.718945: val_loss -0.7406 +2024-11-21 13:31:55.719030: Pseudo dice [0.8398] +2024-11-21 13:31:55.719110: Epoch time: 19.35 s +2024-11-21 13:31:56.517853: +2024-11-21 13:31:56.518077: Epoch 525 +2024-11-21 13:31:56.518188: Current learning rate: 0.00941 +2024-11-21 13:32:15.474783: train_loss -0.7631 +2024-11-21 13:32:15.475008: val_loss -0.7466 +2024-11-21 13:32:15.475084: Pseudo dice [0.8314] +2024-11-21 13:32:15.475167: Epoch time: 18.96 s +2024-11-21 13:32:16.322126: +2024-11-21 13:32:16.322356: Epoch 526 +2024-11-21 13:32:16.322470: Current learning rate: 0.00941 +2024-11-21 13:32:35.240583: train_loss -0.7671 +2024-11-21 13:32:35.240830: val_loss -0.7122 +2024-11-21 13:32:35.243148: Pseudo dice [0.8056] +2024-11-21 13:32:35.243252: Epoch time: 18.92 s +2024-11-21 13:32:36.058963: +2024-11-21 13:32:36.059253: Epoch 527 +2024-11-21 13:32:36.059368: Current learning rate: 0.00941 +2024-11-21 13:32:54.995258: train_loss -0.7636 +2024-11-21 13:32:54.995467: val_loss -0.7379 +2024-11-21 13:32:54.995540: Pseudo dice [0.8355] +2024-11-21 13:32:54.995614: Epoch time: 18.94 s +2024-11-21 13:32:55.902001: +2024-11-21 13:32:55.902212: Epoch 528 +2024-11-21 13:32:55.902324: Current learning rate: 0.0094 +2024-11-21 13:33:14.375346: train_loss -0.7323 +2024-11-21 13:33:14.375554: val_loss -0.7335 +2024-11-21 13:33:14.375631: Pseudo dice [0.8324] +2024-11-21 13:33:14.375719: Epoch time: 18.47 s +2024-11-21 13:33:15.174195: +2024-11-21 13:33:15.174429: Epoch 529 +2024-11-21 13:33:15.174544: Current learning rate: 0.0094 +2024-11-21 13:33:32.898011: train_loss -0.758 +2024-11-21 13:33:32.898228: val_loss -0.7355 +2024-11-21 13:33:32.898304: Pseudo dice [0.8229] +2024-11-21 13:33:32.898381: Epoch time: 17.72 s +2024-11-21 13:33:33.693154: +2024-11-21 13:33:33.693365: Epoch 530 +2024-11-21 13:33:33.693474: Current learning rate: 0.0094 +2024-11-21 13:33:52.626885: train_loss -0.7552 +2024-11-21 13:33:52.631021: val_loss -0.72 +2024-11-21 13:33:52.631220: Pseudo dice [0.8267] +2024-11-21 13:33:52.631316: Epoch time: 18.93 s +2024-11-21 13:33:53.433857: +2024-11-21 13:33:53.434103: Epoch 531 +2024-11-21 13:33:53.434213: Current learning rate: 0.0094 +2024-11-21 13:34:12.713117: train_loss -0.7471 +2024-11-21 13:34:12.713329: val_loss -0.7067 +2024-11-21 13:34:12.713403: Pseudo dice [0.8244] +2024-11-21 13:34:12.713481: Epoch time: 19.28 s +2024-11-21 13:34:13.512821: +2024-11-21 13:34:13.513255: Epoch 532 +2024-11-21 13:34:13.513366: Current learning rate: 0.0094 +2024-11-21 13:34:32.533781: train_loss -0.7508 +2024-11-21 13:34:32.534035: val_loss -0.749 +2024-11-21 13:34:32.534110: Pseudo dice [0.8189] +2024-11-21 13:34:32.534188: Epoch time: 19.02 s +2024-11-21 13:34:33.370447: +2024-11-21 13:34:33.370703: Epoch 533 +2024-11-21 13:34:33.370816: Current learning rate: 0.0094 +2024-11-21 13:34:51.849696: train_loss -0.7599 +2024-11-21 13:34:51.849908: val_loss -0.7611 +2024-11-21 13:34:51.849983: Pseudo dice [0.8553] +2024-11-21 13:34:51.850067: Epoch time: 18.48 s +2024-11-21 13:34:53.054901: +2024-11-21 13:34:53.055124: Epoch 534 +2024-11-21 13:34:53.055314: Current learning rate: 0.0094 +2024-11-21 13:35:10.727165: train_loss -0.7503 +2024-11-21 13:35:10.727416: val_loss -0.7241 +2024-11-21 13:35:10.727490: Pseudo dice [0.822] +2024-11-21 13:35:10.727578: Epoch time: 17.67 s +2024-11-21 13:35:11.568245: +2024-11-21 13:35:11.568455: Epoch 535 +2024-11-21 13:35:11.568569: Current learning rate: 0.0094 +2024-11-21 13:35:29.926868: train_loss -0.7504 +2024-11-21 13:35:29.927131: val_loss -0.716 +2024-11-21 13:35:29.927215: Pseudo dice [0.8149] +2024-11-21 13:35:29.927298: Epoch time: 18.36 s +2024-11-21 13:35:30.778434: +2024-11-21 13:35:30.778674: Epoch 536 +2024-11-21 13:35:30.778788: Current learning rate: 0.00939 +2024-11-21 13:35:48.776826: train_loss -0.7506 +2024-11-21 13:35:48.777059: val_loss -0.7548 +2024-11-21 13:35:48.777136: Pseudo dice [0.8578] +2024-11-21 13:35:48.777211: Epoch time: 18.0 s +2024-11-21 13:35:49.724550: +2024-11-21 13:35:49.724800: Epoch 537 +2024-11-21 13:35:49.724918: Current learning rate: 0.00939 +2024-11-21 13:36:08.110208: train_loss -0.7491 +2024-11-21 13:36:08.110457: val_loss -0.7535 +2024-11-21 13:36:08.110532: Pseudo dice [0.8394] +2024-11-21 13:36:08.110617: Epoch time: 18.39 s +2024-11-21 13:36:08.968470: +2024-11-21 13:36:08.968774: Epoch 538 +2024-11-21 13:36:08.968890: Current learning rate: 0.00939 +2024-11-21 13:36:28.165611: train_loss -0.7395 +2024-11-21 13:36:28.165824: val_loss -0.6884 +2024-11-21 13:36:28.165916: Pseudo dice [0.8183] +2024-11-21 13:36:28.166000: Epoch time: 19.2 s +2024-11-21 13:36:28.960777: +2024-11-21 13:36:28.961057: Epoch 539 +2024-11-21 13:36:28.961169: Current learning rate: 0.00939 +2024-11-21 13:36:47.549126: train_loss -0.746 +2024-11-21 13:36:47.549334: val_loss -0.749 +2024-11-21 13:36:47.549410: Pseudo dice [0.8404] +2024-11-21 13:36:47.549489: Epoch time: 18.59 s +2024-11-21 13:36:48.345840: +2024-11-21 13:36:48.346049: Epoch 540 +2024-11-21 13:36:48.346161: Current learning rate: 0.00939 +2024-11-21 13:37:07.650434: train_loss -0.7507 +2024-11-21 13:37:07.650651: val_loss -0.7284 +2024-11-21 13:37:07.650764: Pseudo dice [0.8198] +2024-11-21 13:37:07.650856: Epoch time: 19.31 s +2024-11-21 13:37:08.461228: +2024-11-21 13:37:08.461431: Epoch 541 +2024-11-21 13:37:08.461543: Current learning rate: 0.00939 +2024-11-21 13:37:27.176431: train_loss -0.747 +2024-11-21 13:37:27.176653: val_loss -0.7492 +2024-11-21 13:37:27.176728: Pseudo dice [0.8429] +2024-11-21 13:37:27.176807: Epoch time: 18.72 s +2024-11-21 13:37:27.979749: +2024-11-21 13:37:27.979988: Epoch 542 +2024-11-21 13:37:27.980149: Current learning rate: 0.00939 +2024-11-21 13:37:46.643198: train_loss -0.7661 +2024-11-21 13:37:46.643410: val_loss -0.7297 +2024-11-21 13:37:46.643487: Pseudo dice [0.8135] +2024-11-21 13:37:46.643566: Epoch time: 18.66 s +2024-11-21 13:37:47.441589: +2024-11-21 13:37:47.441768: Epoch 543 +2024-11-21 13:37:47.441881: Current learning rate: 0.00939 +2024-11-21 13:38:05.573197: train_loss -0.7571 +2024-11-21 13:38:05.573423: val_loss -0.7363 +2024-11-21 13:38:05.573499: Pseudo dice [0.8386] +2024-11-21 13:38:05.573576: Epoch time: 18.13 s +2024-11-21 13:38:06.373510: +2024-11-21 13:38:06.373772: Epoch 544 +2024-11-21 13:38:06.373885: Current learning rate: 0.00939 +2024-11-21 13:38:24.553154: train_loss -0.7773 +2024-11-21 13:38:24.553357: val_loss -0.7558 +2024-11-21 13:38:24.553430: Pseudo dice [0.8303] +2024-11-21 13:38:24.553504: Epoch time: 18.18 s +2024-11-21 13:38:25.371393: +2024-11-21 13:38:25.371601: Epoch 545 +2024-11-21 13:38:25.371715: Current learning rate: 0.00938 +2024-11-21 13:38:44.439412: train_loss -0.7715 +2024-11-21 13:38:44.439639: val_loss -0.734 +2024-11-21 13:38:44.439715: Pseudo dice [0.8252] +2024-11-21 13:38:44.439796: Epoch time: 19.07 s +2024-11-21 13:38:45.285675: +2024-11-21 13:38:45.285890: Epoch 546 +2024-11-21 13:38:45.286009: Current learning rate: 0.00938 +2024-11-21 13:39:04.029561: train_loss -0.7604 +2024-11-21 13:39:04.029770: val_loss -0.7535 +2024-11-21 13:39:04.029848: Pseudo dice [0.8562] +2024-11-21 13:39:04.029927: Epoch time: 18.74 s +2024-11-21 13:39:04.861062: +2024-11-21 13:39:04.861273: Epoch 547 +2024-11-21 13:39:04.861392: Current learning rate: 0.00938 +2024-11-21 13:39:23.598754: train_loss -0.7693 +2024-11-21 13:39:23.598974: val_loss -0.7326 +2024-11-21 13:39:23.599056: Pseudo dice [0.8416] +2024-11-21 13:39:23.599132: Epoch time: 18.74 s +2024-11-21 13:39:24.498841: +2024-11-21 13:39:24.499136: Epoch 548 +2024-11-21 13:39:24.499256: Current learning rate: 0.00938 +2024-11-21 13:39:42.140540: train_loss -0.7527 +2024-11-21 13:39:42.140782: val_loss -0.748 +2024-11-21 13:39:42.140858: Pseudo dice [0.8388] +2024-11-21 13:39:42.140943: Epoch time: 17.64 s +2024-11-21 13:39:42.939192: +2024-11-21 13:39:42.939418: Epoch 549 +2024-11-21 13:39:42.939533: Current learning rate: 0.00938 +2024-11-21 13:40:01.648253: train_loss -0.7615 +2024-11-21 13:40:01.648466: val_loss -0.7065 +2024-11-21 13:40:01.648540: Pseudo dice [0.8185] +2024-11-21 13:40:01.648615: Epoch time: 18.71 s +2024-11-21 13:40:02.671675: +2024-11-21 13:40:02.672028: Epoch 550 +2024-11-21 13:40:02.672139: Current learning rate: 0.00938 +2024-11-21 13:40:20.162471: train_loss -0.765 +2024-11-21 13:40:20.162712: val_loss -0.7351 +2024-11-21 13:40:20.162788: Pseudo dice [0.833] +2024-11-21 13:40:20.162898: Epoch time: 17.49 s +2024-11-21 13:40:20.962834: +2024-11-21 13:40:20.963063: Epoch 551 +2024-11-21 13:40:20.963177: Current learning rate: 0.00938 +2024-11-21 13:40:39.719281: train_loss -0.7663 +2024-11-21 13:40:39.719520: val_loss -0.7595 +2024-11-21 13:40:39.719596: Pseudo dice [0.8476] +2024-11-21 13:40:39.719676: Epoch time: 18.76 s +2024-11-21 13:40:40.526342: +2024-11-21 13:40:40.526695: Epoch 552 +2024-11-21 13:40:40.526810: Current learning rate: 0.00938 +2024-11-21 13:40:58.933874: train_loss -0.7605 +2024-11-21 13:40:58.934128: val_loss -0.723 +2024-11-21 13:40:58.934204: Pseudo dice [0.8224] +2024-11-21 13:40:58.934284: Epoch time: 18.41 s +2024-11-21 13:40:59.731016: +2024-11-21 13:40:59.731219: Epoch 553 +2024-11-21 13:40:59.731334: Current learning rate: 0.00938 +2024-11-21 13:41:17.753589: train_loss -0.7632 +2024-11-21 13:41:17.753797: val_loss -0.7552 +2024-11-21 13:41:17.753868: Pseudo dice [0.8225] +2024-11-21 13:41:17.756131: Epoch time: 18.02 s +2024-11-21 13:41:18.678343: +2024-11-21 13:41:18.678534: Epoch 554 +2024-11-21 13:41:18.678651: Current learning rate: 0.00937 +2024-11-21 13:41:36.394353: train_loss -0.7703 +2024-11-21 13:41:36.394563: val_loss -0.7572 +2024-11-21 13:41:36.394638: Pseudo dice [0.8545] +2024-11-21 13:41:36.394713: Epoch time: 17.72 s +2024-11-21 13:41:37.209760: +2024-11-21 13:41:37.210036: Epoch 555 +2024-11-21 13:41:37.210147: Current learning rate: 0.00937 +2024-11-21 13:41:56.735522: train_loss -0.7641 +2024-11-21 13:41:56.735733: val_loss -0.7237 +2024-11-21 13:41:56.735809: Pseudo dice [0.8354] +2024-11-21 13:41:56.735890: Epoch time: 19.53 s +2024-11-21 13:41:57.586451: +2024-11-21 13:41:57.586664: Epoch 556 +2024-11-21 13:41:57.586777: Current learning rate: 0.00937 +2024-11-21 13:42:17.509239: train_loss -0.7637 +2024-11-21 13:42:17.509474: val_loss -0.7266 +2024-11-21 13:42:17.509547: Pseudo dice [0.8315] +2024-11-21 13:42:17.509626: Epoch time: 19.92 s +2024-11-21 13:42:18.666484: +2024-11-21 13:42:18.666696: Epoch 557 +2024-11-21 13:42:18.666807: Current learning rate: 0.00937 +2024-11-21 13:42:37.723804: train_loss -0.7619 +2024-11-21 13:42:37.724025: val_loss -0.7365 +2024-11-21 13:42:37.724102: Pseudo dice [0.8274] +2024-11-21 13:42:37.724175: Epoch time: 19.06 s +2024-11-21 13:42:38.520727: +2024-11-21 13:42:38.520963: Epoch 558 +2024-11-21 13:42:38.521083: Current learning rate: 0.00937 +2024-11-21 13:42:57.391074: train_loss -0.7689 +2024-11-21 13:42:57.391285: val_loss -0.7128 +2024-11-21 13:42:57.391358: Pseudo dice [0.7987] +2024-11-21 13:42:57.393625: Epoch time: 18.87 s +2024-11-21 13:42:58.362687: +2024-11-21 13:42:58.362968: Epoch 559 +2024-11-21 13:42:58.363090: Current learning rate: 0.00937 +2024-11-21 13:43:16.819541: train_loss -0.7632 +2024-11-21 13:43:16.819782: val_loss -0.7412 +2024-11-21 13:43:16.819857: Pseudo dice [0.8494] +2024-11-21 13:43:16.820014: Epoch time: 18.46 s +2024-11-21 13:43:17.620785: +2024-11-21 13:43:17.620995: Epoch 560 +2024-11-21 13:43:17.621377: Current learning rate: 0.00937 +2024-11-21 13:43:36.639109: train_loss -0.76 +2024-11-21 13:43:36.639325: val_loss -0.711 +2024-11-21 13:43:36.639402: Pseudo dice [0.8211] +2024-11-21 13:43:36.639478: Epoch time: 19.02 s +2024-11-21 13:43:37.437755: +2024-11-21 13:43:37.438003: Epoch 561 +2024-11-21 13:43:37.438116: Current learning rate: 0.00937 +2024-11-21 13:43:55.588095: train_loss -0.7686 +2024-11-21 13:43:55.588317: val_loss -0.7249 +2024-11-21 13:43:55.588396: Pseudo dice [0.8183] +2024-11-21 13:43:55.588475: Epoch time: 18.15 s +2024-11-21 13:43:56.387302: +2024-11-21 13:43:56.387523: Epoch 562 +2024-11-21 13:43:56.387636: Current learning rate: 0.00937 +2024-11-21 13:44:14.868684: train_loss -0.773 +2024-11-21 13:44:14.868905: val_loss -0.733 +2024-11-21 13:44:14.868984: Pseudo dice [0.8184] +2024-11-21 13:44:14.869074: Epoch time: 18.48 s +2024-11-21 13:44:15.669187: +2024-11-21 13:44:15.669411: Epoch 563 +2024-11-21 13:44:15.669540: Current learning rate: 0.00936 +2024-11-21 13:44:34.687374: train_loss -0.7604 +2024-11-21 13:44:34.687621: val_loss -0.7413 +2024-11-21 13:44:34.687693: Pseudo dice [0.8264] +2024-11-21 13:44:34.687774: Epoch time: 19.02 s +2024-11-21 13:44:35.487093: +2024-11-21 13:44:35.487378: Epoch 564 +2024-11-21 13:44:35.487489: Current learning rate: 0.00936 +2024-11-21 13:44:54.410615: train_loss -0.7529 +2024-11-21 13:44:54.410826: val_loss -0.7164 +2024-11-21 13:44:54.410915: Pseudo dice [0.8301] +2024-11-21 13:44:54.411004: Epoch time: 18.92 s +2024-11-21 13:44:55.210411: +2024-11-21 13:44:55.210598: Epoch 565 +2024-11-21 13:44:55.210711: Current learning rate: 0.00936 +2024-11-21 13:45:14.227704: train_loss -0.7493 +2024-11-21 13:45:14.227928: val_loss -0.706 +2024-11-21 13:45:14.228009: Pseudo dice [0.8026] +2024-11-21 13:45:14.228084: Epoch time: 19.02 s +2024-11-21 13:45:15.119647: +2024-11-21 13:45:15.119845: Epoch 566 +2024-11-21 13:45:15.119962: Current learning rate: 0.00936 +2024-11-21 13:45:33.565877: train_loss -0.7445 +2024-11-21 13:45:33.566099: val_loss -0.7373 +2024-11-21 13:45:33.566176: Pseudo dice [0.8478] +2024-11-21 13:45:33.566256: Epoch time: 18.45 s +2024-11-21 13:45:34.363945: +2024-11-21 13:45:34.364208: Epoch 567 +2024-11-21 13:45:34.364325: Current learning rate: 0.00936 +2024-11-21 13:45:53.517053: train_loss -0.7586 +2024-11-21 13:45:53.517292: val_loss -0.7516 +2024-11-21 13:45:53.517365: Pseudo dice [0.8405] +2024-11-21 13:45:53.517445: Epoch time: 19.15 s +2024-11-21 13:45:54.320681: +2024-11-21 13:45:54.320865: Epoch 568 +2024-11-21 13:45:54.320976: Current learning rate: 0.00936 +2024-11-21 13:46:12.512996: train_loss -0.7585 +2024-11-21 13:46:12.513289: val_loss -0.7328 +2024-11-21 13:46:12.513365: Pseudo dice [0.8069] +2024-11-21 13:46:12.513443: Epoch time: 18.19 s +2024-11-21 13:46:13.317704: +2024-11-21 13:46:13.317926: Epoch 569 +2024-11-21 13:46:13.318054: Current learning rate: 0.00936 +2024-11-21 13:46:32.316254: train_loss -0.7417 +2024-11-21 13:46:32.316493: val_loss -0.7111 +2024-11-21 13:46:32.316568: Pseudo dice [0.8177] +2024-11-21 13:46:32.316645: Epoch time: 19.0 s +2024-11-21 13:46:33.115947: +2024-11-21 13:46:33.116255: Epoch 570 +2024-11-21 13:46:33.116370: Current learning rate: 0.00936 +2024-11-21 13:46:53.397309: train_loss -0.7566 +2024-11-21 13:46:53.397590: val_loss -0.7486 +2024-11-21 13:46:53.397673: Pseudo dice [0.8305] +2024-11-21 13:46:53.397754: Epoch time: 20.28 s +2024-11-21 13:46:54.198025: +2024-11-21 13:46:54.198268: Epoch 571 +2024-11-21 13:46:54.198396: Current learning rate: 0.00936 +2024-11-21 13:47:12.368751: train_loss -0.7563 +2024-11-21 13:47:12.368969: val_loss -0.693 +2024-11-21 13:47:12.369050: Pseudo dice [0.7981] +2024-11-21 13:47:12.369128: Epoch time: 18.17 s +2024-11-21 13:47:13.172377: +2024-11-21 13:47:13.172612: Epoch 572 +2024-11-21 13:47:13.172728: Current learning rate: 0.00935 +2024-11-21 13:47:31.657798: train_loss -0.7715 +2024-11-21 13:47:31.658032: val_loss -0.7541 +2024-11-21 13:47:31.658177: Pseudo dice [0.8551] +2024-11-21 13:47:31.658256: Epoch time: 18.49 s +2024-11-21 13:47:32.468352: +2024-11-21 13:47:32.468566: Epoch 573 +2024-11-21 13:47:32.468679: Current learning rate: 0.00935 +2024-11-21 13:47:51.890707: train_loss -0.7658 +2024-11-21 13:47:51.891026: val_loss -0.7359 +2024-11-21 13:47:51.891106: Pseudo dice [0.818] +2024-11-21 13:47:51.891186: Epoch time: 19.42 s +2024-11-21 13:47:52.698809: +2024-11-21 13:47:52.699017: Epoch 574 +2024-11-21 13:47:52.699137: Current learning rate: 0.00935 +2024-11-21 13:48:10.735997: train_loss -0.7614 +2024-11-21 13:48:10.741407: val_loss -0.7218 +2024-11-21 13:48:10.741520: Pseudo dice [0.808] +2024-11-21 13:48:10.741605: Epoch time: 18.04 s +2024-11-21 13:48:11.756093: +2024-11-21 13:48:11.756346: Epoch 575 +2024-11-21 13:48:11.756463: Current learning rate: 0.00935 +2024-11-21 13:48:30.141726: train_loss -0.7634 +2024-11-21 13:48:30.141953: val_loss -0.7267 +2024-11-21 13:48:30.142033: Pseudo dice [0.8123] +2024-11-21 13:48:30.142112: Epoch time: 18.39 s +2024-11-21 13:48:31.089716: +2024-11-21 13:48:31.089989: Epoch 576 +2024-11-21 13:48:31.090107: Current learning rate: 0.00935 +2024-11-21 13:48:48.457834: train_loss -0.7639 +2024-11-21 13:48:48.458059: val_loss -0.7165 +2024-11-21 13:48:48.458133: Pseudo dice [0.8212] +2024-11-21 13:48:48.458211: Epoch time: 17.37 s +2024-11-21 13:48:49.267381: +2024-11-21 13:48:49.267604: Epoch 577 +2024-11-21 13:48:49.267756: Current learning rate: 0.00935 +2024-11-21 13:49:07.956022: train_loss -0.7661 +2024-11-21 13:49:07.956247: val_loss -0.7213 +2024-11-21 13:49:07.956330: Pseudo dice [0.8405] +2024-11-21 13:49:07.956410: Epoch time: 18.69 s +2024-11-21 13:49:08.765680: +2024-11-21 13:49:08.765903: Epoch 578 +2024-11-21 13:49:08.766025: Current learning rate: 0.00935 +2024-11-21 13:49:26.685626: train_loss -0.7525 +2024-11-21 13:49:26.685851: val_loss -0.7239 +2024-11-21 13:49:26.685926: Pseudo dice [0.8357] +2024-11-21 13:49:26.686018: Epoch time: 17.92 s +2024-11-21 13:49:27.510512: +2024-11-21 13:49:27.510696: Epoch 579 +2024-11-21 13:49:27.510838: Current learning rate: 0.00935 +2024-11-21 13:49:46.855696: train_loss -0.7591 +2024-11-21 13:49:46.855910: val_loss -0.7385 +2024-11-21 13:49:46.855985: Pseudo dice [0.8206] +2024-11-21 13:49:46.856065: Epoch time: 19.35 s +2024-11-21 13:49:48.058309: +2024-11-21 13:49:48.058520: Epoch 580 +2024-11-21 13:49:48.058626: Current learning rate: 0.00935 +2024-11-21 13:50:06.763061: train_loss -0.7622 +2024-11-21 13:50:06.763287: val_loss -0.7368 +2024-11-21 13:50:06.763361: Pseudo dice [0.8342] +2024-11-21 13:50:06.763441: Epoch time: 18.71 s +2024-11-21 13:50:07.674690: +2024-11-21 13:50:07.674937: Epoch 581 +2024-11-21 13:50:07.675060: Current learning rate: 0.00934 +2024-11-21 13:50:26.185363: train_loss -0.7409 +2024-11-21 13:50:26.185578: val_loss -0.6631 +2024-11-21 13:50:26.185652: Pseudo dice [0.7815] +2024-11-21 13:50:26.185729: Epoch time: 18.51 s +2024-11-21 13:50:26.993910: +2024-11-21 13:50:26.994135: Epoch 582 +2024-11-21 13:50:26.994251: Current learning rate: 0.00934 +2024-11-21 13:50:44.401318: train_loss -0.738 +2024-11-21 13:50:44.401525: val_loss -0.7186 +2024-11-21 13:50:44.401602: Pseudo dice [0.8102] +2024-11-21 13:50:44.401677: Epoch time: 17.41 s +2024-11-21 13:50:45.193712: +2024-11-21 13:50:45.194109: Epoch 583 +2024-11-21 13:50:45.194257: Current learning rate: 0.00934 +2024-11-21 13:51:03.970737: train_loss -0.7471 +2024-11-21 13:51:03.970962: val_loss -0.7439 +2024-11-21 13:51:03.971041: Pseudo dice [0.834] +2024-11-21 13:51:03.971118: Epoch time: 18.78 s +2024-11-21 13:51:04.988997: +2024-11-21 13:51:04.989203: Epoch 584 +2024-11-21 13:51:04.989318: Current learning rate: 0.00934 +2024-11-21 13:51:22.717380: train_loss -0.7562 +2024-11-21 13:51:22.717619: val_loss -0.7457 +2024-11-21 13:51:22.717696: Pseudo dice [0.8481] +2024-11-21 13:51:22.717782: Epoch time: 17.73 s +2024-11-21 13:51:23.525245: +2024-11-21 13:51:23.525459: Epoch 585 +2024-11-21 13:51:23.525572: Current learning rate: 0.00934 +2024-11-21 13:51:42.228152: train_loss -0.7599 +2024-11-21 13:51:42.228359: val_loss -0.7282 +2024-11-21 13:51:42.228431: Pseudo dice [0.8459] +2024-11-21 13:51:42.228508: Epoch time: 18.7 s +2024-11-21 13:51:43.030813: +2024-11-21 13:51:43.031026: Epoch 586 +2024-11-21 13:51:43.031351: Current learning rate: 0.00934 +2024-11-21 13:52:01.934409: train_loss -0.746 +2024-11-21 13:52:01.934626: val_loss -0.736 +2024-11-21 13:52:01.934701: Pseudo dice [0.8322] +2024-11-21 13:52:01.934776: Epoch time: 18.9 s +2024-11-21 13:52:02.748897: +2024-11-21 13:52:02.749268: Epoch 587 +2024-11-21 13:52:02.749381: Current learning rate: 0.00934 +2024-11-21 13:52:21.524166: train_loss -0.7615 +2024-11-21 13:52:21.524366: val_loss -0.7398 +2024-11-21 13:52:21.524436: Pseudo dice [0.831] +2024-11-21 13:52:21.524514: Epoch time: 18.78 s +2024-11-21 13:52:22.366452: +2024-11-21 13:52:22.366666: Epoch 588 +2024-11-21 13:52:22.366772: Current learning rate: 0.00934 +2024-11-21 13:52:39.685709: train_loss -0.7541 +2024-11-21 13:52:39.685978: val_loss -0.7311 +2024-11-21 13:52:39.686063: Pseudo dice [0.8285] +2024-11-21 13:52:39.686146: Epoch time: 17.32 s +2024-11-21 13:52:40.495844: +2024-11-21 13:52:40.496052: Epoch 589 +2024-11-21 13:52:40.498379: Current learning rate: 0.00933 +2024-11-21 13:53:00.160471: train_loss -0.7563 +2024-11-21 13:53:00.160681: val_loss -0.7268 +2024-11-21 13:53:00.160756: Pseudo dice [0.8394] +2024-11-21 13:53:00.160833: Epoch time: 19.67 s +2024-11-21 13:53:00.969909: +2024-11-21 13:53:00.970207: Epoch 590 +2024-11-21 13:53:00.970321: Current learning rate: 0.00933 +2024-11-21 13:53:19.034556: train_loss -0.7592 +2024-11-21 13:53:19.034782: val_loss -0.7447 +2024-11-21 13:53:19.034855: Pseudo dice [0.8529] +2024-11-21 13:53:19.034933: Epoch time: 18.07 s +2024-11-21 13:53:19.851055: +2024-11-21 13:53:19.851263: Epoch 591 +2024-11-21 13:53:19.851374: Current learning rate: 0.00933 +2024-11-21 13:53:38.122854: train_loss -0.7557 +2024-11-21 13:53:38.123098: val_loss -0.7009 +2024-11-21 13:53:38.123173: Pseudo dice [0.834] +2024-11-21 13:53:38.125432: Epoch time: 18.27 s +2024-11-21 13:53:38.966015: +2024-11-21 13:53:38.966228: Epoch 592 +2024-11-21 13:53:38.966339: Current learning rate: 0.00933 +2024-11-21 13:53:58.163583: train_loss -0.7626 +2024-11-21 13:53:58.163839: val_loss -0.7334 +2024-11-21 13:53:58.163917: Pseudo dice [0.8396] +2024-11-21 13:53:58.163999: Epoch time: 19.2 s +2024-11-21 13:53:58.973426: +2024-11-21 13:53:58.973639: Epoch 593 +2024-11-21 13:53:58.973752: Current learning rate: 0.00933 +2024-11-21 13:54:19.112825: train_loss -0.7544 +2024-11-21 13:54:19.113043: val_loss -0.7553 +2024-11-21 13:54:19.113119: Pseudo dice [0.839] +2024-11-21 13:54:19.113197: Epoch time: 20.14 s +2024-11-21 13:54:19.927926: +2024-11-21 13:54:19.928145: Epoch 594 +2024-11-21 13:54:19.928265: Current learning rate: 0.00933 +2024-11-21 13:54:38.610712: train_loss -0.7531 +2024-11-21 13:54:38.610964: val_loss -0.716 +2024-11-21 13:54:38.611050: Pseudo dice [0.8232] +2024-11-21 13:54:38.611159: Epoch time: 18.68 s +2024-11-21 13:54:39.428648: +2024-11-21 13:54:39.428837: Epoch 595 +2024-11-21 13:54:39.428945: Current learning rate: 0.00933 +2024-11-21 13:54:57.946179: train_loss -0.7572 +2024-11-21 13:54:57.946391: val_loss -0.7284 +2024-11-21 13:54:57.946462: Pseudo dice [0.8336] +2024-11-21 13:54:57.946536: Epoch time: 18.52 s +2024-11-21 13:54:58.759115: +2024-11-21 13:54:58.759328: Epoch 596 +2024-11-21 13:54:58.759443: Current learning rate: 0.00933 +2024-11-21 13:55:17.530091: train_loss -0.76 +2024-11-21 13:55:17.530307: val_loss -0.7469 +2024-11-21 13:55:17.530388: Pseudo dice [0.8336] +2024-11-21 13:55:17.530464: Epoch time: 18.77 s +2024-11-21 13:55:18.342588: +2024-11-21 13:55:18.342814: Epoch 597 +2024-11-21 13:55:18.342924: Current learning rate: 0.00933 +2024-11-21 13:55:37.421908: train_loss -0.7597 +2024-11-21 13:55:37.422124: val_loss -0.7511 +2024-11-21 13:55:37.422241: Pseudo dice [0.8248] +2024-11-21 13:55:37.422315: Epoch time: 19.08 s +2024-11-21 13:55:38.230120: +2024-11-21 13:55:38.230323: Epoch 598 +2024-11-21 13:55:38.230442: Current learning rate: 0.00932 +2024-11-21 13:55:56.357662: train_loss -0.7635 +2024-11-21 13:55:56.357904: val_loss -0.735 +2024-11-21 13:55:56.357978: Pseudo dice [0.8683] +2024-11-21 13:55:56.358064: Epoch time: 18.13 s +2024-11-21 13:55:57.173606: +2024-11-21 13:55:57.173822: Epoch 599 +2024-11-21 13:55:57.173937: Current learning rate: 0.00932 +2024-11-21 13:56:14.917727: train_loss -0.7655 +2024-11-21 13:56:14.917943: val_loss -0.7481 +2024-11-21 13:56:14.918025: Pseudo dice [0.8443] +2024-11-21 13:56:14.918102: Epoch time: 17.74 s +2024-11-21 13:56:16.223289: +2024-11-21 13:56:16.223509: Epoch 600 +2024-11-21 13:56:16.223621: Current learning rate: 0.00932 +2024-11-21 13:56:34.880431: train_loss -0.7637 +2024-11-21 13:56:34.880645: val_loss -0.7062 +2024-11-21 13:56:34.880720: Pseudo dice [0.8352] +2024-11-21 13:56:34.880795: Epoch time: 18.66 s +2024-11-21 13:56:35.695460: +2024-11-21 13:56:35.695652: Epoch 601 +2024-11-21 13:56:35.695780: Current learning rate: 0.00932 +2024-11-21 13:56:55.298516: train_loss -0.7611 +2024-11-21 13:56:55.298775: val_loss -0.7277 +2024-11-21 13:56:55.298853: Pseudo dice [0.8291] +2024-11-21 13:56:55.298970: Epoch time: 19.6 s +2024-11-21 13:56:56.112145: +2024-11-21 13:56:56.112359: Epoch 602 +2024-11-21 13:56:56.112466: Current learning rate: 0.00932 +2024-11-21 13:57:14.147909: train_loss -0.759 +2024-11-21 13:57:14.148143: val_loss -0.7124 +2024-11-21 13:57:14.148218: Pseudo dice [0.8276] +2024-11-21 13:57:14.148293: Epoch time: 18.04 s +2024-11-21 13:57:14.959132: +2024-11-21 13:57:14.959360: Epoch 603 +2024-11-21 13:57:14.959479: Current learning rate: 0.00932 +2024-11-21 13:57:34.515594: train_loss -0.7508 +2024-11-21 13:57:34.515810: val_loss -0.7303 +2024-11-21 13:57:34.515883: Pseudo dice [0.8469] +2024-11-21 13:57:34.515958: Epoch time: 19.56 s +2024-11-21 13:57:35.357394: +2024-11-21 13:57:35.357627: Epoch 604 +2024-11-21 13:57:35.357743: Current learning rate: 0.00932 +2024-11-21 13:57:53.924090: train_loss -0.7519 +2024-11-21 13:57:53.924295: val_loss -0.7264 +2024-11-21 13:57:53.924371: Pseudo dice [0.8217] +2024-11-21 13:57:53.924449: Epoch time: 18.57 s +2024-11-21 13:57:54.736571: +2024-11-21 13:57:54.736798: Epoch 605 +2024-11-21 13:57:54.736926: Current learning rate: 0.00932 +2024-11-21 13:58:13.626054: train_loss -0.7579 +2024-11-21 13:58:13.626314: val_loss -0.738 +2024-11-21 13:58:13.626395: Pseudo dice [0.8482] +2024-11-21 13:58:13.626477: Epoch time: 18.89 s +2024-11-21 13:58:14.644657: +2024-11-21 13:58:14.644861: Epoch 606 +2024-11-21 13:58:14.644970: Current learning rate: 0.00932 +2024-11-21 13:58:33.093815: train_loss -0.7662 +2024-11-21 13:58:33.094035: val_loss -0.7353 +2024-11-21 13:58:33.094110: Pseudo dice [0.8502] +2024-11-21 13:58:33.094187: Epoch time: 18.45 s +2024-11-21 13:58:33.936750: +2024-11-21 13:58:33.936996: Epoch 607 +2024-11-21 13:58:33.937119: Current learning rate: 0.00931 +2024-11-21 13:58:52.360642: train_loss -0.7637 +2024-11-21 13:58:52.360850: val_loss -0.7454 +2024-11-21 13:58:52.360923: Pseudo dice [0.8261] +2024-11-21 13:58:52.361010: Epoch time: 18.42 s +2024-11-21 13:58:53.387859: +2024-11-21 13:58:53.388088: Epoch 608 +2024-11-21 13:58:53.388202: Current learning rate: 0.00931 +2024-11-21 13:59:11.479615: train_loss -0.7694 +2024-11-21 13:59:11.479830: val_loss -0.7547 +2024-11-21 13:59:11.479902: Pseudo dice [0.8477] +2024-11-21 13:59:11.480016: Epoch time: 18.09 s +2024-11-21 13:59:12.285244: +2024-11-21 13:59:12.285426: Epoch 609 +2024-11-21 13:59:12.285541: Current learning rate: 0.00931 +2024-11-21 13:59:31.793387: train_loss -0.7536 +2024-11-21 13:59:31.793664: val_loss -0.6691 +2024-11-21 13:59:31.793744: Pseudo dice [0.7744] +2024-11-21 13:59:31.793838: Epoch time: 19.51 s +2024-11-21 13:59:32.604179: +2024-11-21 13:59:32.604363: Epoch 610 +2024-11-21 13:59:32.604475: Current learning rate: 0.00931 +2024-11-21 13:59:50.204682: train_loss -0.7546 +2024-11-21 13:59:50.204890: val_loss -0.7066 +2024-11-21 13:59:50.204965: Pseudo dice [0.8281] +2024-11-21 13:59:50.205050: Epoch time: 17.6 s +2024-11-21 13:59:51.120670: +2024-11-21 13:59:51.120909: Epoch 611 +2024-11-21 13:59:51.121032: Current learning rate: 0.00931 +2024-11-21 14:00:09.521104: train_loss -0.7586 +2024-11-21 14:00:09.521313: val_loss -0.7624 +2024-11-21 14:00:09.521388: Pseudo dice [0.8336] +2024-11-21 14:00:09.521463: Epoch time: 18.4 s +2024-11-21 14:00:10.353288: +2024-11-21 14:00:10.353501: Epoch 612 +2024-11-21 14:00:10.353754: Current learning rate: 0.00931 +2024-11-21 14:00:29.122516: train_loss -0.7624 +2024-11-21 14:00:29.122750: val_loss -0.7083 +2024-11-21 14:00:29.122824: Pseudo dice [0.8338] +2024-11-21 14:00:29.122906: Epoch time: 18.77 s +2024-11-21 14:00:29.921360: +2024-11-21 14:00:29.921552: Epoch 613 +2024-11-21 14:00:29.921664: Current learning rate: 0.00931 +2024-11-21 14:00:49.781359: train_loss -0.762 +2024-11-21 14:00:49.781579: val_loss -0.7282 +2024-11-21 14:00:49.781653: Pseudo dice [0.8124] +2024-11-21 14:00:49.781730: Epoch time: 19.86 s +2024-11-21 14:00:50.993675: +2024-11-21 14:00:50.993905: Epoch 614 +2024-11-21 14:00:50.994034: Current learning rate: 0.00931 +2024-11-21 14:01:09.183039: train_loss -0.7645 +2024-11-21 14:01:09.183998: val_loss -0.7292 +2024-11-21 14:01:09.184082: Pseudo dice [0.8145] +2024-11-21 14:01:09.184158: Epoch time: 18.19 s +2024-11-21 14:01:10.152769: +2024-11-21 14:01:10.153008: Epoch 615 +2024-11-21 14:01:10.153123: Current learning rate: 0.00931 +2024-11-21 14:01:28.876482: train_loss -0.7675 +2024-11-21 14:01:28.876692: val_loss -0.7358 +2024-11-21 14:01:28.876766: Pseudo dice [0.8214] +2024-11-21 14:01:28.876845: Epoch time: 18.72 s +2024-11-21 14:01:29.738600: +2024-11-21 14:01:29.738847: Epoch 616 +2024-11-21 14:01:29.739012: Current learning rate: 0.0093 +2024-11-21 14:01:48.725763: train_loss -0.7603 +2024-11-21 14:01:48.725974: val_loss -0.7489 +2024-11-21 14:01:48.726061: Pseudo dice [0.8554] +2024-11-21 14:01:48.726141: Epoch time: 18.99 s +2024-11-21 14:01:49.537150: +2024-11-21 14:01:49.537406: Epoch 617 +2024-11-21 14:01:49.537524: Current learning rate: 0.0093 +2024-11-21 14:02:08.265795: train_loss -0.7636 +2024-11-21 14:02:08.266027: val_loss -0.7427 +2024-11-21 14:02:08.266107: Pseudo dice [0.8338] +2024-11-21 14:02:08.266187: Epoch time: 18.73 s +2024-11-21 14:02:09.255040: +2024-11-21 14:02:09.255265: Epoch 618 +2024-11-21 14:02:09.255377: Current learning rate: 0.0093 +2024-11-21 14:02:26.888003: train_loss -0.7519 +2024-11-21 14:02:26.888208: val_loss -0.7078 +2024-11-21 14:02:26.888280: Pseudo dice [0.7876] +2024-11-21 14:02:26.888358: Epoch time: 17.63 s +2024-11-21 14:02:27.703079: +2024-11-21 14:02:27.703334: Epoch 619 +2024-11-21 14:02:27.703447: Current learning rate: 0.0093 +2024-11-21 14:02:46.212761: train_loss -0.7396 +2024-11-21 14:02:46.213006: val_loss -0.72 +2024-11-21 14:02:46.213079: Pseudo dice [0.8239] +2024-11-21 14:02:46.213160: Epoch time: 18.51 s +2024-11-21 14:02:47.055405: +2024-11-21 14:02:47.055618: Epoch 620 +2024-11-21 14:02:47.055732: Current learning rate: 0.0093 +2024-11-21 14:03:05.034262: train_loss -0.75 +2024-11-21 14:03:05.034469: val_loss -0.7612 +2024-11-21 14:03:05.034546: Pseudo dice [0.8397] +2024-11-21 14:03:05.034621: Epoch time: 17.98 s +2024-11-21 14:03:05.848528: +2024-11-21 14:03:05.848748: Epoch 621 +2024-11-21 14:03:05.848857: Current learning rate: 0.0093 +2024-11-21 14:03:23.981617: train_loss -0.762 +2024-11-21 14:03:23.981829: val_loss -0.7421 +2024-11-21 14:03:23.981906: Pseudo dice [0.8254] +2024-11-21 14:03:23.981986: Epoch time: 18.13 s +2024-11-21 14:03:24.871357: +2024-11-21 14:03:24.871578: Epoch 622 +2024-11-21 14:03:24.871693: Current learning rate: 0.0093 +2024-11-21 14:03:43.421802: train_loss -0.7535 +2024-11-21 14:03:43.422010: val_loss -0.7419 +2024-11-21 14:03:43.422087: Pseudo dice [0.8542] +2024-11-21 14:03:43.422164: Epoch time: 18.55 s +2024-11-21 14:03:44.231793: +2024-11-21 14:03:44.232000: Epoch 623 +2024-11-21 14:03:44.232116: Current learning rate: 0.0093 +2024-11-21 14:04:02.481409: train_loss -0.7586 +2024-11-21 14:04:02.481659: val_loss -0.7376 +2024-11-21 14:04:02.481775: Pseudo dice [0.8137] +2024-11-21 14:04:02.481860: Epoch time: 18.25 s +2024-11-21 14:04:03.293679: +2024-11-21 14:04:03.293901: Epoch 624 +2024-11-21 14:04:03.294019: Current learning rate: 0.0093 +2024-11-21 14:04:21.375698: train_loss -0.7491 +2024-11-21 14:04:21.375914: val_loss -0.7163 +2024-11-21 14:04:21.375988: Pseudo dice [0.8284] +2024-11-21 14:04:21.376072: Epoch time: 18.08 s +2024-11-21 14:04:22.184571: +2024-11-21 14:04:22.184787: Epoch 625 +2024-11-21 14:04:22.184906: Current learning rate: 0.00929 +2024-11-21 14:04:40.709213: train_loss -0.758 +2024-11-21 14:04:40.709630: val_loss -0.7438 +2024-11-21 14:04:40.709711: Pseudo dice [0.8376] +2024-11-21 14:04:40.709791: Epoch time: 18.52 s +2024-11-21 14:04:41.521540: +2024-11-21 14:04:41.521747: Epoch 626 +2024-11-21 14:04:41.521864: Current learning rate: 0.00929 +2024-11-21 14:05:00.493406: train_loss -0.7626 +2024-11-21 14:05:00.493645: val_loss -0.7365 +2024-11-21 14:05:00.493718: Pseudo dice [0.843] +2024-11-21 14:05:00.493803: Epoch time: 18.97 s +2024-11-21 14:05:01.314070: +2024-11-21 14:05:01.314305: Epoch 627 +2024-11-21 14:05:01.314419: Current learning rate: 0.00929 +2024-11-21 14:05:21.910800: train_loss -0.7663 +2024-11-21 14:05:21.911025: val_loss -0.7555 +2024-11-21 14:05:21.911100: Pseudo dice [0.8369] +2024-11-21 14:05:21.911182: Epoch time: 20.6 s +2024-11-21 14:05:22.741134: +2024-11-21 14:05:22.741333: Epoch 628 +2024-11-21 14:05:22.741446: Current learning rate: 0.00929 +2024-11-21 14:05:41.553202: train_loss -0.7627 +2024-11-21 14:05:41.553421: val_loss -0.7519 +2024-11-21 14:05:41.553512: Pseudo dice [0.8294] +2024-11-21 14:05:41.553587: Epoch time: 18.81 s +2024-11-21 14:05:42.362722: +2024-11-21 14:05:42.362984: Epoch 629 +2024-11-21 14:05:42.363107: Current learning rate: 0.00929 +2024-11-21 14:06:00.944436: train_loss -0.7614 +2024-11-21 14:06:00.944688: val_loss -0.7483 +2024-11-21 14:06:00.944765: Pseudo dice [0.8404] +2024-11-21 14:06:00.944856: Epoch time: 18.58 s +2024-11-21 14:06:01.821271: +2024-11-21 14:06:01.821489: Epoch 630 +2024-11-21 14:06:01.821606: Current learning rate: 0.00929 +2024-11-21 14:06:20.128890: train_loss -0.7554 +2024-11-21 14:06:20.129107: val_loss -0.7432 +2024-11-21 14:06:20.129181: Pseudo dice [0.8465] +2024-11-21 14:06:20.129263: Epoch time: 18.31 s +2024-11-21 14:06:20.934900: +2024-11-21 14:06:20.935125: Epoch 631 +2024-11-21 14:06:20.935244: Current learning rate: 0.00929 +2024-11-21 14:06:38.993311: train_loss -0.7649 +2024-11-21 14:06:38.993532: val_loss -0.764 +2024-11-21 14:06:38.993612: Pseudo dice [0.827] +2024-11-21 14:06:38.993694: Epoch time: 18.06 s +2024-11-21 14:06:39.811065: +2024-11-21 14:06:39.811281: Epoch 632 +2024-11-21 14:06:39.811392: Current learning rate: 0.00929 +2024-11-21 14:06:58.933127: train_loss -0.772 +2024-11-21 14:06:58.933349: val_loss -0.7466 +2024-11-21 14:06:58.933421: Pseudo dice [0.8299] +2024-11-21 14:06:58.933497: Epoch time: 19.12 s +2024-11-21 14:06:59.742655: +2024-11-21 14:06:59.742888: Epoch 633 +2024-11-21 14:06:59.743010: Current learning rate: 0.00928 +2024-11-21 14:07:17.945274: train_loss -0.7679 +2024-11-21 14:07:17.945520: val_loss -0.7353 +2024-11-21 14:07:17.945598: Pseudo dice [0.8526] +2024-11-21 14:07:17.945682: Epoch time: 18.2 s +2024-11-21 14:07:18.755444: +2024-11-21 14:07:18.755641: Epoch 634 +2024-11-21 14:07:18.755756: Current learning rate: 0.00928 +2024-11-21 14:07:36.931211: train_loss -0.7652 +2024-11-21 14:07:36.931477: val_loss -0.7368 +2024-11-21 14:07:36.931553: Pseudo dice [0.8576] +2024-11-21 14:07:36.931632: Epoch time: 18.18 s +2024-11-21 14:07:37.743579: +2024-11-21 14:07:37.743773: Epoch 635 +2024-11-21 14:07:37.743887: Current learning rate: 0.00928 +2024-11-21 14:07:54.973240: train_loss -0.7542 +2024-11-21 14:07:54.973458: val_loss -0.754 +2024-11-21 14:07:54.973533: Pseudo dice [0.8375] +2024-11-21 14:07:54.973609: Epoch time: 17.23 s +2024-11-21 14:07:55.788968: +2024-11-21 14:07:55.789193: Epoch 636 +2024-11-21 14:07:55.789309: Current learning rate: 0.00928 +2024-11-21 14:08:13.433568: train_loss -0.7662 +2024-11-21 14:08:13.433800: val_loss -0.7421 +2024-11-21 14:08:13.433877: Pseudo dice [0.8423] +2024-11-21 14:08:13.433954: Epoch time: 17.65 s +2024-11-21 14:08:13.434024: Yayy! New best EMA pseudo Dice: 0.8374 +2024-11-21 14:08:14.519876: +2024-11-21 14:08:14.520114: Epoch 637 +2024-11-21 14:08:14.520230: Current learning rate: 0.00928 +2024-11-21 14:08:32.860019: train_loss -0.7601 +2024-11-21 14:08:32.860248: val_loss -0.7181 +2024-11-21 14:08:32.860322: Pseudo dice [0.8288] +2024-11-21 14:08:32.860400: Epoch time: 18.34 s +2024-11-21 14:08:33.685838: +2024-11-21 14:08:33.686075: Epoch 638 +2024-11-21 14:08:33.686198: Current learning rate: 0.00928 +2024-11-21 14:08:52.087956: train_loss -0.7751 +2024-11-21 14:08:52.088187: val_loss -0.7551 +2024-11-21 14:08:52.088272: Pseudo dice [0.8458] +2024-11-21 14:08:52.088353: Epoch time: 18.4 s +2024-11-21 14:08:52.088418: Yayy! New best EMA pseudo Dice: 0.8375 +2024-11-21 14:08:53.145277: +2024-11-21 14:08:53.145505: Epoch 639 +2024-11-21 14:08:53.145622: Current learning rate: 0.00928 +2024-11-21 14:09:12.004315: train_loss -0.7576 +2024-11-21 14:09:12.004571: val_loss -0.7708 +2024-11-21 14:09:12.004653: Pseudo dice [0.846] +2024-11-21 14:09:12.004729: Epoch time: 18.86 s +2024-11-21 14:09:12.004786: Yayy! New best EMA pseudo Dice: 0.8383 +2024-11-21 14:09:13.037524: +2024-11-21 14:09:13.037729: Epoch 640 +2024-11-21 14:09:13.037846: Current learning rate: 0.00928 +2024-11-21 14:09:31.188739: train_loss -0.7719 +2024-11-21 14:09:31.188987: val_loss -0.712 +2024-11-21 14:09:31.189069: Pseudo dice [0.8285] +2024-11-21 14:09:31.189153: Epoch time: 18.15 s +2024-11-21 14:09:32.003896: +2024-11-21 14:09:32.004143: Epoch 641 +2024-11-21 14:09:32.004260: Current learning rate: 0.00928 +2024-11-21 14:09:50.163978: train_loss -0.7631 +2024-11-21 14:09:50.165123: val_loss -0.7613 +2024-11-21 14:09:50.165220: Pseudo dice [0.8383] +2024-11-21 14:09:50.165303: Epoch time: 18.16 s +2024-11-21 14:09:50.979921: +2024-11-21 14:09:50.980134: Epoch 642 +2024-11-21 14:09:50.980246: Current learning rate: 0.00927 +2024-11-21 14:10:08.226299: train_loss -0.762 +2024-11-21 14:10:08.226519: val_loss -0.7383 +2024-11-21 14:10:08.226595: Pseudo dice [0.8348] +2024-11-21 14:10:08.226675: Epoch time: 17.25 s +2024-11-21 14:10:09.071295: +2024-11-21 14:10:09.071543: Epoch 643 +2024-11-21 14:10:09.071658: Current learning rate: 0.00927 +2024-11-21 14:10:27.424546: train_loss -0.755 +2024-11-21 14:10:27.424772: val_loss -0.7479 +2024-11-21 14:10:27.424851: Pseudo dice [0.8243] +2024-11-21 14:10:27.424931: Epoch time: 18.35 s +2024-11-21 14:10:28.241457: +2024-11-21 14:10:28.241650: Epoch 644 +2024-11-21 14:10:28.241761: Current learning rate: 0.00927 +2024-11-21 14:10:46.555569: train_loss -0.758 +2024-11-21 14:10:46.555833: val_loss -0.7257 +2024-11-21 14:10:46.555916: Pseudo dice [0.8081] +2024-11-21 14:10:46.556006: Epoch time: 18.32 s +2024-11-21 14:10:47.368689: +2024-11-21 14:10:47.368917: Epoch 645 +2024-11-21 14:10:47.369045: Current learning rate: 0.00927 +2024-11-21 14:11:06.446813: train_loss -0.7657 +2024-11-21 14:11:06.447031: val_loss -0.748 +2024-11-21 14:11:06.452346: Pseudo dice [0.8152] +2024-11-21 14:11:06.452469: Epoch time: 19.08 s +2024-11-21 14:11:07.283464: +2024-11-21 14:11:07.283659: Epoch 646 +2024-11-21 14:11:07.283778: Current learning rate: 0.00927 +2024-11-21 14:11:25.705872: train_loss -0.7687 +2024-11-21 14:11:25.706096: val_loss -0.7233 +2024-11-21 14:11:25.706191: Pseudo dice [0.8386] +2024-11-21 14:11:25.706269: Epoch time: 18.42 s +2024-11-21 14:11:26.869233: +2024-11-21 14:11:26.869487: Epoch 647 +2024-11-21 14:11:26.869600: Current learning rate: 0.00927 +2024-11-21 14:11:46.197097: train_loss -0.7575 +2024-11-21 14:11:46.197368: val_loss -0.7317 +2024-11-21 14:11:46.197446: Pseudo dice [0.8322] +2024-11-21 14:11:46.197579: Epoch time: 19.33 s +2024-11-21 14:11:47.008838: +2024-11-21 14:11:47.009084: Epoch 648 +2024-11-21 14:11:47.009197: Current learning rate: 0.00927 +2024-11-21 14:12:04.651288: train_loss -0.7658 +2024-11-21 14:12:04.653671: val_loss -0.7519 +2024-11-21 14:12:04.653755: Pseudo dice [0.8364] +2024-11-21 14:12:04.653835: Epoch time: 17.64 s +2024-11-21 14:12:05.611421: +2024-11-21 14:12:05.611659: Epoch 649 +2024-11-21 14:12:05.611776: Current learning rate: 0.00927 +2024-11-21 14:12:23.574814: train_loss -0.7624 +2024-11-21 14:12:23.575053: val_loss -0.74 +2024-11-21 14:12:23.575149: Pseudo dice [0.8186] +2024-11-21 14:12:23.575234: Epoch time: 17.96 s +2024-11-21 14:12:24.661244: +2024-11-21 14:12:24.661438: Epoch 650 +2024-11-21 14:12:24.661556: Current learning rate: 0.00927 +2024-11-21 14:12:42.639052: train_loss -0.7638 +2024-11-21 14:12:42.639297: val_loss -0.7535 +2024-11-21 14:12:42.639374: Pseudo dice [0.8436] +2024-11-21 14:12:42.639459: Epoch time: 17.98 s +2024-11-21 14:12:43.455901: +2024-11-21 14:12:43.456124: Epoch 651 +2024-11-21 14:12:43.456241: Current learning rate: 0.00926 +2024-11-21 14:13:02.548540: train_loss -0.7664 +2024-11-21 14:13:02.548756: val_loss -0.7511 +2024-11-21 14:13:02.548832: Pseudo dice [0.847] +2024-11-21 14:13:02.548908: Epoch time: 19.09 s +2024-11-21 14:13:03.613626: +2024-11-21 14:13:03.613844: Epoch 652 +2024-11-21 14:13:03.613960: Current learning rate: 0.00926 +2024-11-21 14:13:21.964617: train_loss -0.7673 +2024-11-21 14:13:21.964826: val_loss -0.746 +2024-11-21 14:13:21.964900: Pseudo dice [0.8085] +2024-11-21 14:13:21.964978: Epoch time: 18.35 s +2024-11-21 14:13:22.777054: +2024-11-21 14:13:22.777437: Epoch 653 +2024-11-21 14:13:22.777551: Current learning rate: 0.00926 +2024-11-21 14:13:41.304721: train_loss -0.7694 +2024-11-21 14:13:41.304935: val_loss -0.7672 +2024-11-21 14:13:41.305017: Pseudo dice [0.8471] +2024-11-21 14:13:41.305094: Epoch time: 18.53 s +2024-11-21 14:13:42.112043: +2024-11-21 14:13:42.112254: Epoch 654 +2024-11-21 14:13:42.112384: Current learning rate: 0.00926 +2024-11-21 14:14:01.275222: train_loss -0.7809 +2024-11-21 14:14:01.277624: val_loss -0.7621 +2024-11-21 14:14:01.277715: Pseudo dice [0.8406] +2024-11-21 14:14:01.277799: Epoch time: 19.16 s +2024-11-21 14:14:02.242245: +2024-11-21 14:14:02.242443: Epoch 655 +2024-11-21 14:14:02.242562: Current learning rate: 0.00926 +2024-11-21 14:14:21.238786: train_loss -0.7743 +2024-11-21 14:14:21.239043: val_loss -0.7405 +2024-11-21 14:14:21.239136: Pseudo dice [0.8182] +2024-11-21 14:14:21.239215: Epoch time: 19.0 s +2024-11-21 14:14:22.041948: +2024-11-21 14:14:22.042164: Epoch 656 +2024-11-21 14:14:22.042281: Current learning rate: 0.00926 +2024-11-21 14:14:41.379430: train_loss -0.7618 +2024-11-21 14:14:41.379637: val_loss -0.7745 +2024-11-21 14:14:41.379712: Pseudo dice [0.8453] +2024-11-21 14:14:41.379787: Epoch time: 19.34 s +2024-11-21 14:14:42.188324: +2024-11-21 14:14:42.188569: Epoch 657 +2024-11-21 14:14:42.188686: Current learning rate: 0.00926 +2024-11-21 14:15:01.253345: train_loss -0.7549 +2024-11-21 14:15:01.253586: val_loss -0.7291 +2024-11-21 14:15:01.253658: Pseudo dice [0.8193] +2024-11-21 14:15:01.253739: Epoch time: 19.07 s +2024-11-21 14:15:02.649956: +2024-11-21 14:15:02.650235: Epoch 658 +2024-11-21 14:15:02.650344: Current learning rate: 0.00926 +2024-11-21 14:15:20.602641: train_loss -0.7624 +2024-11-21 14:15:20.602863: val_loss -0.7267 +2024-11-21 14:15:20.602937: Pseudo dice [0.8363] +2024-11-21 14:15:20.603022: Epoch time: 17.95 s +2024-11-21 14:15:21.425036: +2024-11-21 14:15:21.425235: Epoch 659 +2024-11-21 14:15:21.425347: Current learning rate: 0.00926 +2024-11-21 14:15:40.058378: train_loss -0.7636 +2024-11-21 14:15:40.058595: val_loss -0.7225 +2024-11-21 14:15:40.058698: Pseudo dice [0.8379] +2024-11-21 14:15:40.058807: Epoch time: 18.63 s +2024-11-21 14:15:40.881880: +2024-11-21 14:15:40.882111: Epoch 660 +2024-11-21 14:15:40.882224: Current learning rate: 0.00925 +2024-11-21 14:15:58.917638: train_loss -0.7428 +2024-11-21 14:15:58.917854: val_loss -0.7305 +2024-11-21 14:15:58.917927: Pseudo dice [0.8126] +2024-11-21 14:15:58.918013: Epoch time: 18.04 s +2024-11-21 14:15:59.724969: +2024-11-21 14:15:59.725247: Epoch 661 +2024-11-21 14:15:59.725354: Current learning rate: 0.00925 +2024-11-21 14:16:18.779503: train_loss -0.7587 +2024-11-21 14:16:18.779806: val_loss -0.7272 +2024-11-21 14:16:18.779881: Pseudo dice [0.8251] +2024-11-21 14:16:18.779962: Epoch time: 19.06 s +2024-11-21 14:16:19.601464: +2024-11-21 14:16:19.601729: Epoch 662 +2024-11-21 14:16:19.601843: Current learning rate: 0.00925 +2024-11-21 14:16:38.319627: train_loss -0.7524 +2024-11-21 14:16:38.319832: val_loss -0.7045 +2024-11-21 14:16:38.319907: Pseudo dice [0.8321] +2024-11-21 14:16:38.319981: Epoch time: 18.72 s +2024-11-21 14:16:39.125029: +2024-11-21 14:16:39.125248: Epoch 663 +2024-11-21 14:16:39.125364: Current learning rate: 0.00925 +2024-11-21 14:16:57.815808: train_loss -0.7644 +2024-11-21 14:16:57.816036: val_loss -0.7236 +2024-11-21 14:16:57.816329: Pseudo dice [0.831] +2024-11-21 14:16:57.816407: Epoch time: 18.69 s +2024-11-21 14:16:58.625185: +2024-11-21 14:16:58.625424: Epoch 664 +2024-11-21 14:16:58.625546: Current learning rate: 0.00925 +2024-11-21 14:17:17.509000: train_loss -0.7677 +2024-11-21 14:17:17.511448: val_loss -0.7272 +2024-11-21 14:17:17.511575: Pseudo dice [0.8402] +2024-11-21 14:17:17.511669: Epoch time: 18.88 s +2024-11-21 14:17:18.389398: +2024-11-21 14:17:18.389624: Epoch 665 +2024-11-21 14:17:18.389729: Current learning rate: 0.00925 +2024-11-21 14:17:38.008749: train_loss -0.7637 +2024-11-21 14:17:38.011142: val_loss -0.7278 +2024-11-21 14:17:38.011235: Pseudo dice [0.8419] +2024-11-21 14:17:38.011314: Epoch time: 19.62 s +2024-11-21 14:17:38.888296: +2024-11-21 14:17:38.888496: Epoch 666 +2024-11-21 14:17:38.888608: Current learning rate: 0.00925 +2024-11-21 14:17:56.700639: train_loss -0.7619 +2024-11-21 14:17:56.700876: val_loss -0.7455 +2024-11-21 14:17:56.700954: Pseudo dice [0.8393] +2024-11-21 14:17:56.701040: Epoch time: 17.81 s +2024-11-21 14:17:57.532331: +2024-11-21 14:17:57.532518: Epoch 667 +2024-11-21 14:17:57.532632: Current learning rate: 0.00925 +2024-11-21 14:18:15.165932: train_loss -0.7614 +2024-11-21 14:18:15.166152: val_loss -0.7449 +2024-11-21 14:18:15.166229: Pseudo dice [0.8306] +2024-11-21 14:18:15.166310: Epoch time: 17.63 s +2024-11-21 14:18:15.979927: +2024-11-21 14:18:15.980122: Epoch 668 +2024-11-21 14:18:15.980233: Current learning rate: 0.00925 +2024-11-21 14:18:34.971638: train_loss -0.762 +2024-11-21 14:18:34.974071: val_loss -0.7125 +2024-11-21 14:18:34.974193: Pseudo dice [0.8261] +2024-11-21 14:18:34.974280: Epoch time: 18.99 s +2024-11-21 14:18:36.241687: +2024-11-21 14:18:36.241891: Epoch 669 +2024-11-21 14:18:36.242011: Current learning rate: 0.00924 +2024-11-21 14:18:56.141684: train_loss -0.761 +2024-11-21 14:18:56.141904: val_loss -0.7331 +2024-11-21 14:18:56.142007: Pseudo dice [0.8306] +2024-11-21 14:18:56.142091: Epoch time: 19.9 s +2024-11-21 14:18:56.959537: +2024-11-21 14:18:56.959765: Epoch 670 +2024-11-21 14:18:56.959876: Current learning rate: 0.00924 +2024-11-21 14:19:15.628225: train_loss -0.7623 +2024-11-21 14:19:15.628459: val_loss -0.7571 +2024-11-21 14:19:15.628592: Pseudo dice [0.8326] +2024-11-21 14:19:15.628674: Epoch time: 18.67 s +2024-11-21 14:19:16.482354: +2024-11-21 14:19:16.482891: Epoch 671 +2024-11-21 14:19:16.483010: Current learning rate: 0.00924 +2024-11-21 14:19:35.277115: train_loss -0.7648 +2024-11-21 14:19:35.277359: val_loss -0.7442 +2024-11-21 14:19:35.277437: Pseudo dice [0.8321] +2024-11-21 14:19:35.277522: Epoch time: 18.8 s +2024-11-21 14:19:36.100811: +2024-11-21 14:19:36.101014: Epoch 672 +2024-11-21 14:19:36.101126: Current learning rate: 0.00924 +2024-11-21 14:19:54.968770: train_loss -0.7678 +2024-11-21 14:19:54.968986: val_loss -0.7451 +2024-11-21 14:19:54.969069: Pseudo dice [0.8413] +2024-11-21 14:19:54.969146: Epoch time: 18.87 s +2024-11-21 14:19:55.841603: +2024-11-21 14:19:55.841810: Epoch 673 +2024-11-21 14:19:55.841921: Current learning rate: 0.00924 +2024-11-21 14:20:13.795235: train_loss -0.7709 +2024-11-21 14:20:13.795455: val_loss -0.7387 +2024-11-21 14:20:13.795547: Pseudo dice [0.8405] +2024-11-21 14:20:13.795624: Epoch time: 17.95 s +2024-11-21 14:20:14.616681: +2024-11-21 14:20:14.616899: Epoch 674 +2024-11-21 14:20:14.617015: Current learning rate: 0.00924 +2024-11-21 14:20:32.687817: train_loss -0.7692 +2024-11-21 14:20:32.688056: val_loss -0.7304 +2024-11-21 14:20:32.688146: Pseudo dice [0.8318] +2024-11-21 14:20:32.688228: Epoch time: 18.07 s +2024-11-21 14:20:33.508822: +2024-11-21 14:20:33.509024: Epoch 675 +2024-11-21 14:20:33.509143: Current learning rate: 0.00924 +2024-11-21 14:20:52.430920: train_loss -0.7626 +2024-11-21 14:20:52.431155: val_loss -0.712 +2024-11-21 14:20:52.431228: Pseudo dice [0.8265] +2024-11-21 14:20:52.431307: Epoch time: 18.92 s +2024-11-21 14:20:53.253609: +2024-11-21 14:20:53.253834: Epoch 676 +2024-11-21 14:20:53.253946: Current learning rate: 0.00924 +2024-11-21 14:21:11.809112: train_loss -0.7563 +2024-11-21 14:21:11.814480: val_loss -0.7228 +2024-11-21 14:21:11.814593: Pseudo dice [0.8133] +2024-11-21 14:21:11.814672: Epoch time: 18.56 s +2024-11-21 14:21:12.662630: +2024-11-21 14:21:12.662939: Epoch 677 +2024-11-21 14:21:12.663064: Current learning rate: 0.00924 +2024-11-21 14:21:31.379633: train_loss -0.7578 +2024-11-21 14:21:31.379851: val_loss -0.7554 +2024-11-21 14:21:31.379927: Pseudo dice [0.836] +2024-11-21 14:21:31.380020: Epoch time: 18.72 s +2024-11-21 14:21:32.208652: +2024-11-21 14:21:32.208880: Epoch 678 +2024-11-21 14:21:32.209005: Current learning rate: 0.00923 +2024-11-21 14:21:50.883205: train_loss -0.7543 +2024-11-21 14:21:50.883486: val_loss -0.7403 +2024-11-21 14:21:50.883563: Pseudo dice [0.8137] +2024-11-21 14:21:50.883646: Epoch time: 18.68 s +2024-11-21 14:21:51.784781: +2024-11-21 14:21:51.785262: Epoch 679 +2024-11-21 14:21:51.785397: Current learning rate: 0.00923 +2024-11-21 14:22:09.918746: train_loss -0.7514 +2024-11-21 14:22:09.918963: val_loss -0.7281 +2024-11-21 14:22:09.919045: Pseudo dice [0.8447] +2024-11-21 14:22:09.919120: Epoch time: 18.13 s +2024-11-21 14:22:10.741573: +2024-11-21 14:22:10.741767: Epoch 680 +2024-11-21 14:22:10.741876: Current learning rate: 0.00923 +2024-11-21 14:22:29.062884: train_loss -0.7578 +2024-11-21 14:22:29.063115: val_loss -0.7041 +2024-11-21 14:22:29.063190: Pseudo dice [0.8149] +2024-11-21 14:22:29.063270: Epoch time: 18.32 s +2024-11-21 14:22:29.884659: +2024-11-21 14:22:29.884997: Epoch 681 +2024-11-21 14:22:29.885156: Current learning rate: 0.00923 +2024-11-21 14:22:48.188711: train_loss -0.7688 +2024-11-21 14:22:48.188924: val_loss -0.7419 +2024-11-21 14:22:48.189005: Pseudo dice [0.8377] +2024-11-21 14:22:48.189083: Epoch time: 18.3 s +2024-11-21 14:22:49.011458: +2024-11-21 14:22:49.011669: Epoch 682 +2024-11-21 14:22:49.011779: Current learning rate: 0.00923 +2024-11-21 14:23:08.204519: train_loss -0.7661 +2024-11-21 14:23:08.204717: val_loss -0.7328 +2024-11-21 14:23:08.204790: Pseudo dice [0.8514] +2024-11-21 14:23:08.204865: Epoch time: 19.19 s +2024-11-21 14:23:09.068638: +2024-11-21 14:23:09.068850: Epoch 683 +2024-11-21 14:23:09.068962: Current learning rate: 0.00923 +2024-11-21 14:23:27.316945: train_loss -0.7635 +2024-11-21 14:23:27.317233: val_loss -0.7129 +2024-11-21 14:23:27.317312: Pseudo dice [0.8195] +2024-11-21 14:23:27.317390: Epoch time: 18.25 s +2024-11-21 14:23:28.142667: +2024-11-21 14:23:28.142875: Epoch 684 +2024-11-21 14:23:28.142986: Current learning rate: 0.00923 +2024-11-21 14:23:48.435916: train_loss -0.7606 +2024-11-21 14:23:48.436177: val_loss -0.7384 +2024-11-21 14:23:48.436250: Pseudo dice [0.8381] +2024-11-21 14:23:48.436336: Epoch time: 20.29 s +2024-11-21 14:23:49.266907: +2024-11-21 14:23:49.267120: Epoch 685 +2024-11-21 14:23:49.267238: Current learning rate: 0.00923 +2024-11-21 14:24:07.633567: train_loss -0.7609 +2024-11-21 14:24:07.633785: val_loss -0.7417 +2024-11-21 14:24:07.633863: Pseudo dice [0.846] +2024-11-21 14:24:07.633942: Epoch time: 18.37 s +2024-11-21 14:24:08.447443: +2024-11-21 14:24:08.447656: Epoch 686 +2024-11-21 14:24:08.447768: Current learning rate: 0.00922 +2024-11-21 14:24:26.771684: train_loss -0.7659 +2024-11-21 14:24:26.771896: val_loss -0.7201 +2024-11-21 14:24:26.771970: Pseudo dice [0.8349] +2024-11-21 14:24:26.772059: Epoch time: 18.33 s +2024-11-21 14:24:27.596479: +2024-11-21 14:24:27.596729: Epoch 687 +2024-11-21 14:24:27.596847: Current learning rate: 0.00922 +2024-11-21 14:24:46.098933: train_loss -0.76 +2024-11-21 14:24:46.099164: val_loss -0.7391 +2024-11-21 14:24:46.099242: Pseudo dice [0.8322] +2024-11-21 14:24:46.099323: Epoch time: 18.5 s +2024-11-21 14:24:46.926955: +2024-11-21 14:24:46.927175: Epoch 688 +2024-11-21 14:24:46.927286: Current learning rate: 0.00922 +2024-11-21 14:25:05.969970: train_loss -0.7663 +2024-11-21 14:25:05.970226: val_loss -0.744 +2024-11-21 14:25:05.970300: Pseudo dice [0.8469] +2024-11-21 14:25:05.970385: Epoch time: 19.04 s +2024-11-21 14:25:06.843276: +2024-11-21 14:25:06.843467: Epoch 689 +2024-11-21 14:25:06.843577: Current learning rate: 0.00922 +2024-11-21 14:25:25.792005: train_loss -0.7812 +2024-11-21 14:25:25.792224: val_loss -0.7516 +2024-11-21 14:25:25.792499: Pseudo dice [0.8564] +2024-11-21 14:25:25.792587: Epoch time: 18.95 s +2024-11-21 14:25:26.608140: +2024-11-21 14:25:26.608353: Epoch 690 +2024-11-21 14:25:26.608469: Current learning rate: 0.00922 +2024-11-21 14:25:44.680918: train_loss -0.7662 +2024-11-21 14:25:44.683382: val_loss -0.7255 +2024-11-21 14:25:44.683473: Pseudo dice [0.8068] +2024-11-21 14:25:44.683552: Epoch time: 18.07 s +2024-11-21 14:25:45.871862: +2024-11-21 14:25:45.872051: Epoch 691 +2024-11-21 14:25:45.872164: Current learning rate: 0.00922 +2024-11-21 14:26:05.507236: train_loss -0.7587 +2024-11-21 14:26:05.507508: val_loss -0.7346 +2024-11-21 14:26:05.507585: Pseudo dice [0.8309] +2024-11-21 14:26:05.507672: Epoch time: 19.64 s +2024-11-21 14:26:06.422744: +2024-11-21 14:26:06.423047: Epoch 692 +2024-11-21 14:26:06.423162: Current learning rate: 0.00922 +2024-11-21 14:26:25.239109: train_loss -0.7637 +2024-11-21 14:26:25.239320: val_loss -0.7312 +2024-11-21 14:26:25.239398: Pseudo dice [0.822] +2024-11-21 14:26:25.239476: Epoch time: 18.82 s +2024-11-21 14:26:26.056290: +2024-11-21 14:26:26.056514: Epoch 693 +2024-11-21 14:26:26.056626: Current learning rate: 0.00922 +2024-11-21 14:26:45.476089: train_loss -0.7646 +2024-11-21 14:26:45.476306: val_loss -0.7426 +2024-11-21 14:26:45.476381: Pseudo dice [0.8395] +2024-11-21 14:26:45.476459: Epoch time: 19.42 s +2024-11-21 14:26:46.294661: +2024-11-21 14:26:46.294872: Epoch 694 +2024-11-21 14:26:46.294987: Current learning rate: 0.00922 +2024-11-21 14:27:05.003103: train_loss -0.7696 +2024-11-21 14:27:05.003325: val_loss -0.757 +2024-11-21 14:27:05.003400: Pseudo dice [0.8458] +2024-11-21 14:27:05.003481: Epoch time: 18.71 s +2024-11-21 14:27:05.831350: +2024-11-21 14:27:05.831567: Epoch 695 +2024-11-21 14:27:05.831677: Current learning rate: 0.00921 +2024-11-21 14:27:24.295450: train_loss -0.7683 +2024-11-21 14:27:24.295685: val_loss -0.7309 +2024-11-21 14:27:24.295762: Pseudo dice [0.8384] +2024-11-21 14:27:24.295841: Epoch time: 18.46 s +2024-11-21 14:27:25.152755: +2024-11-21 14:27:25.152956: Epoch 696 +2024-11-21 14:27:25.153079: Current learning rate: 0.00921 +2024-11-21 14:27:45.572990: train_loss -0.757 +2024-11-21 14:27:45.573204: val_loss -0.7559 +2024-11-21 14:27:45.578435: Pseudo dice [0.8679] +2024-11-21 14:27:45.578591: Epoch time: 20.42 s +2024-11-21 14:27:46.491654: +2024-11-21 14:27:46.491862: Epoch 697 +2024-11-21 14:27:46.491971: Current learning rate: 0.00921 +2024-11-21 14:28:04.703149: train_loss -0.7669 +2024-11-21 14:28:04.703382: val_loss -0.7373 +2024-11-21 14:28:04.703458: Pseudo dice [0.8439] +2024-11-21 14:28:04.703536: Epoch time: 18.21 s +2024-11-21 14:28:04.703596: Yayy! New best EMA pseudo Dice: 0.8387 +2024-11-21 14:28:05.810744: +2024-11-21 14:28:05.811002: Epoch 698 +2024-11-21 14:28:05.811118: Current learning rate: 0.00921 +2024-11-21 14:28:24.658040: train_loss -0.7706 +2024-11-21 14:28:24.658265: val_loss -0.7317 +2024-11-21 14:28:24.658341: Pseudo dice [0.8622] +2024-11-21 14:28:24.658422: Epoch time: 18.85 s +2024-11-21 14:28:24.658485: Yayy! New best EMA pseudo Dice: 0.841 +2024-11-21 14:28:25.736076: +2024-11-21 14:28:25.736308: Epoch 699 +2024-11-21 14:28:25.736425: Current learning rate: 0.00921 +2024-11-21 14:28:43.817845: train_loss -0.7684 +2024-11-21 14:28:43.818119: val_loss -0.7449 +2024-11-21 14:28:43.818197: Pseudo dice [0.8342] +2024-11-21 14:28:43.818281: Epoch time: 18.08 s +2024-11-21 14:28:44.944891: +2024-11-21 14:28:44.945091: Epoch 700 +2024-11-21 14:28:44.945204: Current learning rate: 0.00921 +2024-11-21 14:29:03.030536: train_loss -0.7614 +2024-11-21 14:29:03.035944: val_loss -0.7448 +2024-11-21 14:29:03.036040: Pseudo dice [0.8567] +2024-11-21 14:29:03.036120: Epoch time: 18.09 s +2024-11-21 14:29:03.036182: Yayy! New best EMA pseudo Dice: 0.842 +2024-11-21 14:29:04.269793: +2024-11-21 14:29:04.270213: Epoch 701 +2024-11-21 14:29:04.270327: Current learning rate: 0.00921 +2024-11-21 14:29:22.182702: train_loss -0.7607 +2024-11-21 14:29:22.182916: val_loss -0.7386 +2024-11-21 14:29:22.182990: Pseudo dice [0.8656] +2024-11-21 14:29:22.183077: Epoch time: 17.91 s +2024-11-21 14:29:22.183139: Yayy! New best EMA pseudo Dice: 0.8443 +2024-11-21 14:29:23.610652: +2024-11-21 14:29:23.610867: Epoch 702 +2024-11-21 14:29:23.610980: Current learning rate: 0.00921 +2024-11-21 14:29:42.441835: train_loss -0.7572 +2024-11-21 14:29:42.442090: val_loss -0.739 +2024-11-21 14:29:42.442172: Pseudo dice [0.8415] +2024-11-21 14:29:42.442255: Epoch time: 18.83 s +2024-11-21 14:29:43.304211: +2024-11-21 14:29:43.304441: Epoch 703 +2024-11-21 14:29:43.304555: Current learning rate: 0.00921 +2024-11-21 14:30:01.331450: train_loss -0.7495 +2024-11-21 14:30:01.331665: val_loss -0.736 +2024-11-21 14:30:01.331739: Pseudo dice [0.8302] +2024-11-21 14:30:01.331817: Epoch time: 18.03 s +2024-11-21 14:30:02.150437: +2024-11-21 14:30:02.150649: Epoch 704 +2024-11-21 14:30:02.150768: Current learning rate: 0.0092 +2024-11-21 14:30:20.840558: train_loss -0.7678 +2024-11-21 14:30:20.840771: val_loss -0.7311 +2024-11-21 14:30:20.840850: Pseudo dice [0.8302] +2024-11-21 14:30:20.840929: Epoch time: 18.69 s +2024-11-21 14:30:21.775124: +2024-11-21 14:30:21.775318: Epoch 705 +2024-11-21 14:30:21.775434: Current learning rate: 0.0092 +2024-11-21 14:30:40.461397: train_loss -0.7658 +2024-11-21 14:30:40.461650: val_loss -0.7583 +2024-11-21 14:30:40.461724: Pseudo dice [0.8339] +2024-11-21 14:30:40.461810: Epoch time: 18.69 s +2024-11-21 14:30:41.285623: +2024-11-21 14:30:41.285904: Epoch 706 +2024-11-21 14:30:41.286024: Current learning rate: 0.0092 +2024-11-21 14:31:00.734052: train_loss -0.7546 +2024-11-21 14:31:00.734281: val_loss -0.7329 +2024-11-21 14:31:00.734362: Pseudo dice [0.818] +2024-11-21 14:31:00.734442: Epoch time: 19.45 s +2024-11-21 14:31:01.554735: +2024-11-21 14:31:01.554938: Epoch 707 +2024-11-21 14:31:01.555060: Current learning rate: 0.0092 +2024-11-21 14:31:20.556874: train_loss -0.7685 +2024-11-21 14:31:20.557088: val_loss -0.75 +2024-11-21 14:31:20.557162: Pseudo dice [0.821] +2024-11-21 14:31:20.557241: Epoch time: 19.0 s +2024-11-21 14:31:21.374184: +2024-11-21 14:31:21.374393: Epoch 708 +2024-11-21 14:31:21.374510: Current learning rate: 0.0092 +2024-11-21 14:31:40.168548: train_loss -0.7626 +2024-11-21 14:31:40.168761: val_loss -0.7305 +2024-11-21 14:31:40.168836: Pseudo dice [0.8404] +2024-11-21 14:31:40.168916: Epoch time: 18.8 s +2024-11-21 14:31:41.148183: +2024-11-21 14:31:41.148393: Epoch 709 +2024-11-21 14:31:41.148509: Current learning rate: 0.0092 +2024-11-21 14:31:59.554954: train_loss -0.7739 +2024-11-21 14:31:59.555166: val_loss -0.7241 +2024-11-21 14:31:59.555239: Pseudo dice [0.8359] +2024-11-21 14:31:59.555314: Epoch time: 18.41 s +2024-11-21 14:32:00.376057: +2024-11-21 14:32:00.376245: Epoch 710 +2024-11-21 14:32:00.376356: Current learning rate: 0.0092 +2024-11-21 14:32:19.174476: train_loss -0.7742 +2024-11-21 14:32:19.174710: val_loss -0.7505 +2024-11-21 14:32:19.174788: Pseudo dice [0.8542] +2024-11-21 14:32:19.174874: Epoch time: 18.8 s +2024-11-21 14:32:19.996349: +2024-11-21 14:32:19.996555: Epoch 711 +2024-11-21 14:32:19.996674: Current learning rate: 0.0092 +2024-11-21 14:32:37.828237: train_loss -0.7724 +2024-11-21 14:32:37.828470: val_loss -0.7456 +2024-11-21 14:32:37.828547: Pseudo dice [0.8514] +2024-11-21 14:32:37.828675: Epoch time: 17.83 s +2024-11-21 14:32:39.136813: +2024-11-21 14:32:39.137042: Epoch 712 +2024-11-21 14:32:39.137155: Current learning rate: 0.0092 +2024-11-21 14:32:57.710297: train_loss -0.7678 +2024-11-21 14:32:57.712739: val_loss -0.7418 +2024-11-21 14:32:57.712872: Pseudo dice [0.8431] +2024-11-21 14:32:57.712958: Epoch time: 18.57 s +2024-11-21 14:32:58.679628: +2024-11-21 14:32:58.679839: Epoch 713 +2024-11-21 14:32:58.679955: Current learning rate: 0.00919 +2024-11-21 14:33:17.318070: train_loss -0.7525 +2024-11-21 14:33:17.318336: val_loss -0.7371 +2024-11-21 14:33:17.318409: Pseudo dice [0.8042] +2024-11-21 14:33:17.318491: Epoch time: 18.64 s +2024-11-21 14:33:18.294774: +2024-11-21 14:33:18.295001: Epoch 714 +2024-11-21 14:33:18.295117: Current learning rate: 0.00919 +2024-11-21 14:33:36.871723: train_loss -0.7595 +2024-11-21 14:33:36.871950: val_loss -0.7123 +2024-11-21 14:33:36.872036: Pseudo dice [0.8058] +2024-11-21 14:33:36.872342: Epoch time: 18.58 s +2024-11-21 14:33:38.017342: +2024-11-21 14:33:38.017573: Epoch 715 +2024-11-21 14:33:38.017687: Current learning rate: 0.00919 +2024-11-21 14:33:56.878585: train_loss -0.7649 +2024-11-21 14:33:56.878797: val_loss -0.7647 +2024-11-21 14:33:56.878873: Pseudo dice [0.8319] +2024-11-21 14:33:56.878950: Epoch time: 18.86 s +2024-11-21 14:33:57.700344: +2024-11-21 14:33:57.700549: Epoch 716 +2024-11-21 14:33:57.700666: Current learning rate: 0.00919 +2024-11-21 14:34:15.671500: train_loss -0.7584 +2024-11-21 14:34:15.671756: val_loss -0.659 +2024-11-21 14:34:15.671832: Pseudo dice [0.8031] +2024-11-21 14:34:15.671913: Epoch time: 17.97 s +2024-11-21 14:34:16.506380: +2024-11-21 14:34:16.506600: Epoch 717 +2024-11-21 14:34:16.506711: Current learning rate: 0.00919 +2024-11-21 14:34:35.107538: train_loss -0.764 +2024-11-21 14:34:35.107821: val_loss -0.7182 +2024-11-21 14:34:35.107899: Pseudo dice [0.8387] +2024-11-21 14:34:35.107982: Epoch time: 18.6 s +2024-11-21 14:34:35.932683: +2024-11-21 14:34:35.932919: Epoch 718 +2024-11-21 14:34:35.933043: Current learning rate: 0.00919 +2024-11-21 14:34:55.182110: train_loss -0.7664 +2024-11-21 14:34:55.184490: val_loss -0.7403 +2024-11-21 14:34:55.184609: Pseudo dice [0.8463] +2024-11-21 14:34:55.184716: Epoch time: 19.25 s +2024-11-21 14:34:56.020629: +2024-11-21 14:34:56.020900: Epoch 719 +2024-11-21 14:34:56.021029: Current learning rate: 0.00919 +2024-11-21 14:35:14.627275: train_loss -0.7708 +2024-11-21 14:35:14.629655: val_loss -0.727 +2024-11-21 14:35:14.629768: Pseudo dice [0.8359] +2024-11-21 14:35:14.629854: Epoch time: 18.61 s +2024-11-21 14:35:15.611030: +2024-11-21 14:35:15.611237: Epoch 720 +2024-11-21 14:35:15.611350: Current learning rate: 0.00919 +2024-11-21 14:35:34.336291: train_loss -0.7597 +2024-11-21 14:35:34.336531: val_loss -0.7437 +2024-11-21 14:35:34.336607: Pseudo dice [0.8279] +2024-11-21 14:35:34.336686: Epoch time: 18.73 s +2024-11-21 14:35:35.222473: +2024-11-21 14:35:35.222671: Epoch 721 +2024-11-21 14:35:35.222781: Current learning rate: 0.00919 +2024-11-21 14:35:54.372096: train_loss -0.7662 +2024-11-21 14:35:54.372296: val_loss -0.7477 +2024-11-21 14:35:54.372370: Pseudo dice [0.8421] +2024-11-21 14:35:54.372446: Epoch time: 19.15 s +2024-11-21 14:35:55.203103: +2024-11-21 14:35:55.203463: Epoch 722 +2024-11-21 14:35:55.203579: Current learning rate: 0.00918 +2024-11-21 14:36:14.216911: train_loss -0.7608 +2024-11-21 14:36:14.217126: val_loss -0.7155 +2024-11-21 14:36:14.217205: Pseudo dice [0.8282] +2024-11-21 14:36:14.217283: Epoch time: 19.01 s +2024-11-21 14:36:15.036314: +2024-11-21 14:36:15.036504: Epoch 723 +2024-11-21 14:36:15.036614: Current learning rate: 0.00918 +2024-11-21 14:36:33.773123: train_loss -0.76 +2024-11-21 14:36:33.773365: val_loss -0.7315 +2024-11-21 14:36:33.773452: Pseudo dice [0.8276] +2024-11-21 14:36:33.773539: Epoch time: 18.74 s +2024-11-21 14:36:34.592513: +2024-11-21 14:36:34.592729: Epoch 724 +2024-11-21 14:36:34.592845: Current learning rate: 0.00918 +2024-11-21 14:36:53.408732: train_loss -0.7655 +2024-11-21 14:36:53.408942: val_loss -0.7524 +2024-11-21 14:36:53.409020: Pseudo dice [0.8566] +2024-11-21 14:36:53.409105: Epoch time: 18.82 s +2024-11-21 14:36:54.226467: +2024-11-21 14:36:54.226673: Epoch 725 +2024-11-21 14:36:54.226788: Current learning rate: 0.00918 +2024-11-21 14:37:13.350400: train_loss -0.7711 +2024-11-21 14:37:13.350614: val_loss -0.6925 +2024-11-21 14:37:13.350687: Pseudo dice [0.837] +2024-11-21 14:37:13.350764: Epoch time: 19.12 s +2024-11-21 14:37:14.274437: +2024-11-21 14:37:14.274656: Epoch 726 +2024-11-21 14:37:14.274777: Current learning rate: 0.00918 +2024-11-21 14:37:33.520655: train_loss -0.7777 +2024-11-21 14:37:33.523519: val_loss -0.75 +2024-11-21 14:37:33.523616: Pseudo dice [0.8217] +2024-11-21 14:37:33.523694: Epoch time: 19.25 s +2024-11-21 14:37:34.390784: +2024-11-21 14:37:34.391024: Epoch 727 +2024-11-21 14:37:34.391143: Current learning rate: 0.00918 +2024-11-21 14:37:54.634586: train_loss -0.7522 +2024-11-21 14:37:54.634901: val_loss -0.7347 +2024-11-21 14:37:54.634980: Pseudo dice [0.8406] +2024-11-21 14:37:54.635070: Epoch time: 20.24 s +2024-11-21 14:37:55.452742: +2024-11-21 14:37:55.452949: Epoch 728 +2024-11-21 14:37:55.453064: Current learning rate: 0.00918 +2024-11-21 14:38:14.412093: train_loss -0.748 +2024-11-21 14:38:14.412309: val_loss -0.7387 +2024-11-21 14:38:14.412384: Pseudo dice [0.847] +2024-11-21 14:38:14.412460: Epoch time: 18.96 s +2024-11-21 14:38:15.231986: +2024-11-21 14:38:15.232195: Epoch 729 +2024-11-21 14:38:15.232312: Current learning rate: 0.00918 +2024-11-21 14:38:33.701982: train_loss -0.7367 +2024-11-21 14:38:33.702206: val_loss -0.6916 +2024-11-21 14:38:33.702284: Pseudo dice [0.8306] +2024-11-21 14:38:33.702361: Epoch time: 18.47 s +2024-11-21 14:38:34.518034: +2024-11-21 14:38:34.518338: Epoch 730 +2024-11-21 14:38:34.518452: Current learning rate: 0.00917 +2024-11-21 14:38:53.150870: train_loss -0.7608 +2024-11-21 14:38:53.151088: val_loss -0.7331 +2024-11-21 14:38:53.151191: Pseudo dice [0.8383] +2024-11-21 14:38:53.151278: Epoch time: 18.63 s +2024-11-21 14:38:53.962337: +2024-11-21 14:38:53.962630: Epoch 731 +2024-11-21 14:38:53.962744: Current learning rate: 0.00917 +2024-11-21 14:39:11.691783: train_loss -0.7564 +2024-11-21 14:39:11.692030: val_loss -0.7222 +2024-11-21 14:39:11.692103: Pseudo dice [0.825] +2024-11-21 14:39:11.692185: Epoch time: 17.73 s +2024-11-21 14:39:12.504739: +2024-11-21 14:39:12.504945: Epoch 732 +2024-11-21 14:39:12.505066: Current learning rate: 0.00917 +2024-11-21 14:39:30.962899: train_loss -0.7504 +2024-11-21 14:39:30.963120: val_loss -0.7167 +2024-11-21 14:39:30.963195: Pseudo dice [0.8429] +2024-11-21 14:39:30.963271: Epoch time: 18.46 s +2024-11-21 14:39:31.776348: +2024-11-21 14:39:31.776549: Epoch 733 +2024-11-21 14:39:31.776667: Current learning rate: 0.00917 +2024-11-21 14:39:50.551526: train_loss -0.7633 +2024-11-21 14:39:50.551739: val_loss -0.7656 +2024-11-21 14:39:50.551813: Pseudo dice [0.841] +2024-11-21 14:39:50.554082: Epoch time: 18.78 s +2024-11-21 14:39:51.476115: +2024-11-21 14:39:51.476412: Epoch 734 +2024-11-21 14:39:51.476526: Current learning rate: 0.00917 +2024-11-21 14:40:09.301867: train_loss -0.7593 +2024-11-21 14:40:09.302117: val_loss -0.7026 +2024-11-21 14:40:09.302196: Pseudo dice [0.8187] +2024-11-21 14:40:09.302279: Epoch time: 17.83 s +2024-11-21 14:40:10.113110: +2024-11-21 14:40:10.113329: Epoch 735 +2024-11-21 14:40:10.113451: Current learning rate: 0.00917 +2024-11-21 14:40:29.122757: train_loss -0.7533 +2024-11-21 14:40:29.122978: val_loss -0.7252 +2024-11-21 14:40:29.123058: Pseudo dice [0.8199] +2024-11-21 14:40:29.123135: Epoch time: 19.01 s +2024-11-21 14:40:29.937432: +2024-11-21 14:40:29.937644: Epoch 736 +2024-11-21 14:40:29.937755: Current learning rate: 0.00917 +2024-11-21 14:40:48.947342: train_loss -0.7654 +2024-11-21 14:40:48.947569: val_loss -0.7374 +2024-11-21 14:40:48.947645: Pseudo dice [0.8382] +2024-11-21 14:40:48.947719: Epoch time: 19.01 s +2024-11-21 14:40:49.760724: +2024-11-21 14:40:49.760958: Epoch 737 +2024-11-21 14:40:49.761087: Current learning rate: 0.00917 +2024-11-21 14:41:08.401348: train_loss -0.7638 +2024-11-21 14:41:08.401590: val_loss -0.7521 +2024-11-21 14:41:08.401665: Pseudo dice [0.8294] +2024-11-21 14:41:08.401751: Epoch time: 18.64 s +2024-11-21 14:41:09.222600: +2024-11-21 14:41:09.222812: Epoch 738 +2024-11-21 14:41:09.222929: Current learning rate: 0.00917 +2024-11-21 14:41:28.880673: train_loss -0.7541 +2024-11-21 14:41:28.880888: val_loss -0.7614 +2024-11-21 14:41:28.880963: Pseudo dice [0.8348] +2024-11-21 14:41:28.881043: Epoch time: 19.66 s +2024-11-21 14:41:29.692117: +2024-11-21 14:41:29.692323: Epoch 739 +2024-11-21 14:41:29.692436: Current learning rate: 0.00916 +2024-11-21 14:41:48.186265: train_loss -0.7481 +2024-11-21 14:41:48.186478: val_loss -0.7212 +2024-11-21 14:41:48.186552: Pseudo dice [0.8539] +2024-11-21 14:41:48.186625: Epoch time: 18.49 s +2024-11-21 14:41:49.331123: +2024-11-21 14:41:49.331340: Epoch 740 +2024-11-21 14:41:49.331456: Current learning rate: 0.00916 +2024-11-21 14:42:08.216640: train_loss -0.7649 +2024-11-21 14:42:08.216856: val_loss -0.738 +2024-11-21 14:42:08.216931: Pseudo dice [0.8549] +2024-11-21 14:42:08.217612: Epoch time: 18.89 s +2024-11-21 14:42:09.028905: +2024-11-21 14:42:09.029126: Epoch 741 +2024-11-21 14:42:09.029235: Current learning rate: 0.00916 +2024-11-21 14:42:28.305269: train_loss -0.7715 +2024-11-21 14:42:28.305517: val_loss -0.733 +2024-11-21 14:42:28.305590: Pseudo dice [0.8283] +2024-11-21 14:42:28.305678: Epoch time: 19.28 s +2024-11-21 14:42:29.236053: +2024-11-21 14:42:29.236261: Epoch 742 +2024-11-21 14:42:29.236378: Current learning rate: 0.00916 +2024-11-21 14:42:48.448711: train_loss -0.758 +2024-11-21 14:42:48.448929: val_loss -0.7197 +2024-11-21 14:42:48.449008: Pseudo dice [0.816] +2024-11-21 14:42:48.449082: Epoch time: 19.21 s +2024-11-21 14:42:49.260858: +2024-11-21 14:42:49.261068: Epoch 743 +2024-11-21 14:42:49.261182: Current learning rate: 0.00916 +2024-11-21 14:43:07.378735: train_loss -0.76 +2024-11-21 14:43:07.380456: val_loss -0.7743 +2024-11-21 14:43:07.380552: Pseudo dice [0.8456] +2024-11-21 14:43:07.380631: Epoch time: 18.12 s +2024-11-21 14:43:08.263947: +2024-11-21 14:43:08.264158: Epoch 744 +2024-11-21 14:43:08.264279: Current learning rate: 0.00916 +2024-11-21 14:43:26.329382: train_loss -0.7616 +2024-11-21 14:43:26.329584: val_loss -0.7348 +2024-11-21 14:43:26.329661: Pseudo dice [0.8446] +2024-11-21 14:43:26.331982: Epoch time: 18.07 s +2024-11-21 14:43:27.283619: +2024-11-21 14:43:27.283918: Epoch 745 +2024-11-21 14:43:27.284044: Current learning rate: 0.00916 +2024-11-21 14:43:45.924593: train_loss -0.7695 +2024-11-21 14:43:45.924819: val_loss -0.7381 +2024-11-21 14:43:45.924892: Pseudo dice [0.8086] +2024-11-21 14:43:45.924970: Epoch time: 18.64 s +2024-11-21 14:43:46.743311: +2024-11-21 14:43:46.743541: Epoch 746 +2024-11-21 14:43:46.743655: Current learning rate: 0.00916 +2024-11-21 14:44:05.674269: train_loss -0.7699 +2024-11-21 14:44:05.674482: val_loss -0.7337 +2024-11-21 14:44:05.674552: Pseudo dice [0.8375] +2024-11-21 14:44:05.674629: Epoch time: 18.93 s +2024-11-21 14:44:06.601476: +2024-11-21 14:44:06.601730: Epoch 747 +2024-11-21 14:44:06.601848: Current learning rate: 0.00916 +2024-11-21 14:44:24.618956: train_loss -0.7622 +2024-11-21 14:44:24.619218: val_loss -0.7281 +2024-11-21 14:44:24.619296: Pseudo dice [0.8312] +2024-11-21 14:44:24.619374: Epoch time: 18.02 s +2024-11-21 14:44:25.650726: +2024-11-21 14:44:25.650974: Epoch 748 +2024-11-21 14:44:25.651101: Current learning rate: 0.00915 +2024-11-21 14:44:44.624779: train_loss -0.7539 +2024-11-21 14:44:44.625028: val_loss -0.7393 +2024-11-21 14:44:44.625103: Pseudo dice [0.8403] +2024-11-21 14:44:44.625185: Epoch time: 18.98 s +2024-11-21 14:44:45.464819: +2024-11-21 14:44:45.465039: Epoch 749 +2024-11-21 14:44:45.465154: Current learning rate: 0.00915 +2024-11-21 14:45:04.928069: train_loss -0.7722 +2024-11-21 14:45:04.928320: val_loss -0.7168 +2024-11-21 14:45:04.928393: Pseudo dice [0.8147] +2024-11-21 14:45:04.928471: Epoch time: 19.46 s +2024-11-21 14:45:05.969667: +2024-11-21 14:45:05.969909: Epoch 750 +2024-11-21 14:45:05.970036: Current learning rate: 0.00915 +2024-11-21 14:45:25.300780: train_loss -0.7626 +2024-11-21 14:45:25.301003: val_loss -0.7325 +2024-11-21 14:45:25.306290: Pseudo dice [0.828] +2024-11-21 14:45:25.306412: Epoch time: 19.33 s +2024-11-21 14:45:26.320428: +2024-11-21 14:45:26.320675: Epoch 751 +2024-11-21 14:45:26.320789: Current learning rate: 0.00915 +2024-11-21 14:45:45.590403: train_loss -0.7694 +2024-11-21 14:45:45.590621: val_loss -0.7465 +2024-11-21 14:45:45.590695: Pseudo dice [0.8464] +2024-11-21 14:45:45.590774: Epoch time: 19.27 s +2024-11-21 14:45:46.409155: +2024-11-21 14:45:46.409412: Epoch 752 +2024-11-21 14:45:46.409531: Current learning rate: 0.00915 +2024-11-21 14:46:04.781002: train_loss -0.7615 +2024-11-21 14:46:04.781216: val_loss -0.7525 +2024-11-21 14:46:04.781291: Pseudo dice [0.844] +2024-11-21 14:46:04.781370: Epoch time: 18.37 s +2024-11-21 14:46:05.599447: +2024-11-21 14:46:05.599686: Epoch 753 +2024-11-21 14:46:05.599799: Current learning rate: 0.00915 +2024-11-21 14:46:24.124949: train_loss -0.7563 +2024-11-21 14:46:24.125208: val_loss -0.7326 +2024-11-21 14:46:24.125285: Pseudo dice [0.8368] +2024-11-21 14:46:24.125362: Epoch time: 18.53 s +2024-11-21 14:46:24.937362: +2024-11-21 14:46:24.937629: Epoch 754 +2024-11-21 14:46:24.937745: Current learning rate: 0.00915 +2024-11-21 14:46:42.834687: train_loss -0.7705 +2024-11-21 14:46:42.834902: val_loss -0.7478 +2024-11-21 14:46:42.834975: Pseudo dice [0.8162] +2024-11-21 14:46:42.835058: Epoch time: 17.9 s +2024-11-21 14:46:43.657130: +2024-11-21 14:46:43.657360: Epoch 755 +2024-11-21 14:46:43.657485: Current learning rate: 0.00915 +2024-11-21 14:47:02.083321: train_loss -0.767 +2024-11-21 14:47:02.083662: val_loss -0.7623 +2024-11-21 14:47:02.083740: Pseudo dice [0.8248] +2024-11-21 14:47:02.083818: Epoch time: 18.43 s +2024-11-21 14:47:03.282736: +2024-11-21 14:47:03.282959: Epoch 756 +2024-11-21 14:47:03.283088: Current learning rate: 0.00915 +2024-11-21 14:47:21.674277: train_loss -0.7674 +2024-11-21 14:47:21.674494: val_loss -0.7046 +2024-11-21 14:47:21.674567: Pseudo dice [0.8069] +2024-11-21 14:47:21.674644: Epoch time: 18.39 s +2024-11-21 14:47:22.485710: +2024-11-21 14:47:22.485918: Epoch 757 +2024-11-21 14:47:22.486030: Current learning rate: 0.00914 +2024-11-21 14:47:41.501144: train_loss -0.7629 +2024-11-21 14:47:41.501356: val_loss -0.7287 +2024-11-21 14:47:41.501429: Pseudo dice [0.8351] +2024-11-21 14:47:41.501505: Epoch time: 19.02 s +2024-11-21 14:47:42.316763: +2024-11-21 14:47:42.317030: Epoch 758 +2024-11-21 14:47:42.317144: Current learning rate: 0.00914 +2024-11-21 14:48:00.503498: train_loss -0.7735 +2024-11-21 14:48:00.503732: val_loss -0.7295 +2024-11-21 14:48:00.503806: Pseudo dice [0.8106] +2024-11-21 14:48:00.503889: Epoch time: 18.19 s +2024-11-21 14:48:01.321643: +2024-11-21 14:48:01.321863: Epoch 759 +2024-11-21 14:48:01.321985: Current learning rate: 0.00914 +2024-11-21 14:48:19.921791: train_loss -0.7704 +2024-11-21 14:48:19.922043: val_loss -0.7551 +2024-11-21 14:48:19.922119: Pseudo dice [0.8425] +2024-11-21 14:48:19.922196: Epoch time: 18.6 s +2024-11-21 14:48:20.740271: +2024-11-21 14:48:20.740479: Epoch 760 +2024-11-21 14:48:20.740596: Current learning rate: 0.00914 +2024-11-21 14:48:39.078195: train_loss -0.764 +2024-11-21 14:48:39.078405: val_loss -0.7091 +2024-11-21 14:48:39.078488: Pseudo dice [0.8292] +2024-11-21 14:48:39.078565: Epoch time: 18.34 s +2024-11-21 14:48:39.897885: +2024-11-21 14:48:39.898103: Epoch 761 +2024-11-21 14:48:39.898220: Current learning rate: 0.00914 +2024-11-21 14:48:58.285796: train_loss -0.767 +2024-11-21 14:48:58.286010: val_loss -0.7609 +2024-11-21 14:48:58.286084: Pseudo dice [0.8495] +2024-11-21 14:48:58.286160: Epoch time: 18.39 s +2024-11-21 14:48:59.102658: +2024-11-21 14:48:59.102938: Epoch 762 +2024-11-21 14:48:59.103059: Current learning rate: 0.00914 +2024-11-21 14:49:18.620364: train_loss -0.7731 +2024-11-21 14:49:18.620621: val_loss -0.7433 +2024-11-21 14:49:18.620697: Pseudo dice [0.8218] +2024-11-21 14:49:18.620782: Epoch time: 19.52 s +2024-11-21 14:49:19.456601: +2024-11-21 14:49:19.456802: Epoch 763 +2024-11-21 14:49:19.456918: Current learning rate: 0.00914 +2024-11-21 14:49:39.081912: train_loss -0.776 +2024-11-21 14:49:39.082136: val_loss -0.7453 +2024-11-21 14:49:39.082219: Pseudo dice [0.8126] +2024-11-21 14:49:39.082295: Epoch time: 19.63 s +2024-11-21 14:49:39.908343: +2024-11-21 14:49:39.908542: Epoch 764 +2024-11-21 14:49:39.908655: Current learning rate: 0.00914 +2024-11-21 14:49:59.225873: train_loss -0.7635 +2024-11-21 14:49:59.226090: val_loss -0.7332 +2024-11-21 14:49:59.226163: Pseudo dice [0.8052] +2024-11-21 14:49:59.226237: Epoch time: 19.32 s +2024-11-21 14:50:00.047727: +2024-11-21 14:50:00.047926: Epoch 765 +2024-11-21 14:50:00.048054: Current learning rate: 0.00914 +2024-11-21 14:50:18.667973: train_loss -0.7654 +2024-11-21 14:50:18.668203: val_loss -0.7557 +2024-11-21 14:50:18.668280: Pseudo dice [0.844] +2024-11-21 14:50:18.668364: Epoch time: 18.62 s +2024-11-21 14:50:19.491594: +2024-11-21 14:50:19.491821: Epoch 766 +2024-11-21 14:50:19.491942: Current learning rate: 0.00913 +2024-11-21 14:50:38.137947: train_loss -0.7622 +2024-11-21 14:50:38.138216: val_loss -0.7505 +2024-11-21 14:50:38.138291: Pseudo dice [0.8266] +2024-11-21 14:50:38.138371: Epoch time: 18.65 s +2024-11-21 14:50:38.978487: +2024-11-21 14:50:38.978681: Epoch 767 +2024-11-21 14:50:38.978791: Current learning rate: 0.00913 +2024-11-21 14:50:58.417767: train_loss -0.7614 +2024-11-21 14:50:58.417975: val_loss -0.7312 +2024-11-21 14:50:58.418061: Pseudo dice [0.8136] +2024-11-21 14:50:58.418139: Epoch time: 19.44 s +2024-11-21 14:50:59.616350: +2024-11-21 14:50:59.616562: Epoch 768 +2024-11-21 14:50:59.616677: Current learning rate: 0.00913 +2024-11-21 14:51:17.929001: train_loss -0.7772 +2024-11-21 14:51:17.929224: val_loss -0.7544 +2024-11-21 14:51:17.929327: Pseudo dice [0.8342] +2024-11-21 14:51:17.929405: Epoch time: 18.31 s +2024-11-21 14:51:18.771037: +2024-11-21 14:51:18.771311: Epoch 769 +2024-11-21 14:51:18.771425: Current learning rate: 0.00913 +2024-11-21 14:51:37.226072: train_loss -0.7643 +2024-11-21 14:51:37.226313: val_loss -0.7181 +2024-11-21 14:51:37.226393: Pseudo dice [0.8051] +2024-11-21 14:51:37.226474: Epoch time: 18.46 s +2024-11-21 14:51:38.088586: +2024-11-21 14:51:38.088807: Epoch 770 +2024-11-21 14:51:38.088925: Current learning rate: 0.00913 +2024-11-21 14:51:56.809517: train_loss -0.7692 +2024-11-21 14:51:56.809734: val_loss -0.7237 +2024-11-21 14:51:56.809808: Pseudo dice [0.8346] +2024-11-21 14:51:56.809885: Epoch time: 18.72 s +2024-11-21 14:51:57.630204: +2024-11-21 14:51:57.630440: Epoch 771 +2024-11-21 14:51:57.630554: Current learning rate: 0.00913 +2024-11-21 14:52:16.389372: train_loss -0.7643 +2024-11-21 14:52:16.389572: val_loss -0.7037 +2024-11-21 14:52:16.389662: Pseudo dice [0.8329] +2024-11-21 14:52:16.389741: Epoch time: 18.76 s +2024-11-21 14:52:17.216169: +2024-11-21 14:52:17.216377: Epoch 772 +2024-11-21 14:52:17.216490: Current learning rate: 0.00913 +2024-11-21 14:52:35.726165: train_loss -0.7612 +2024-11-21 14:52:35.726409: val_loss -0.7421 +2024-11-21 14:52:35.726487: Pseudo dice [0.8294] +2024-11-21 14:52:35.726573: Epoch time: 18.51 s +2024-11-21 14:52:36.554294: +2024-11-21 14:52:36.554515: Epoch 773 +2024-11-21 14:52:36.554628: Current learning rate: 0.00913 +2024-11-21 14:52:54.875806: train_loss -0.7736 +2024-11-21 14:52:54.876025: val_loss -0.7523 +2024-11-21 14:52:54.876099: Pseudo dice [0.8428] +2024-11-21 14:52:54.876177: Epoch time: 18.32 s +2024-11-21 14:52:55.701190: +2024-11-21 14:52:55.701414: Epoch 774 +2024-11-21 14:52:55.701535: Current learning rate: 0.00912 +2024-11-21 14:53:14.759362: train_loss -0.7651 +2024-11-21 14:53:14.759581: val_loss -0.7419 +2024-11-21 14:53:14.759654: Pseudo dice [0.84] +2024-11-21 14:53:14.759731: Epoch time: 19.06 s +2024-11-21 14:53:15.585886: +2024-11-21 14:53:15.586138: Epoch 775 +2024-11-21 14:53:15.586253: Current learning rate: 0.00912 +2024-11-21 14:53:34.168026: train_loss -0.7732 +2024-11-21 14:53:34.168239: val_loss -0.7228 +2024-11-21 14:53:34.168314: Pseudo dice [0.8366] +2024-11-21 14:53:34.168410: Epoch time: 18.58 s +2024-11-21 14:53:34.993484: +2024-11-21 14:53:34.993674: Epoch 776 +2024-11-21 14:53:34.993787: Current learning rate: 0.00912 +2024-11-21 14:53:53.088143: train_loss -0.7588 +2024-11-21 14:53:53.088382: val_loss -0.7305 +2024-11-21 14:53:53.088455: Pseudo dice [0.8374] +2024-11-21 14:53:53.088547: Epoch time: 18.1 s +2024-11-21 14:53:53.916960: +2024-11-21 14:53:53.917163: Epoch 777 +2024-11-21 14:53:53.917280: Current learning rate: 0.00912 +2024-11-21 14:54:12.581671: train_loss -0.7673 +2024-11-21 14:54:12.581964: val_loss -0.7416 +2024-11-21 14:54:12.582051: Pseudo dice [0.8218] +2024-11-21 14:54:12.582128: Epoch time: 18.67 s +2024-11-21 14:54:13.408524: +2024-11-21 14:54:13.408728: Epoch 778 +2024-11-21 14:54:13.408843: Current learning rate: 0.00912 +2024-11-21 14:54:32.025909: train_loss -0.7627 +2024-11-21 14:54:32.026119: val_loss -0.7432 +2024-11-21 14:54:32.026193: Pseudo dice [0.8079] +2024-11-21 14:54:32.026269: Epoch time: 18.62 s +2024-11-21 14:54:33.216167: +2024-11-21 14:54:33.216372: Epoch 779 +2024-11-21 14:54:33.216491: Current learning rate: 0.00912 +2024-11-21 14:54:51.309997: train_loss -0.7656 +2024-11-21 14:54:51.310255: val_loss -0.7586 +2024-11-21 14:54:51.310332: Pseudo dice [0.8189] +2024-11-21 14:54:51.310413: Epoch time: 18.09 s +2024-11-21 14:54:52.131613: +2024-11-21 14:54:52.131904: Epoch 780 +2024-11-21 14:54:52.132024: Current learning rate: 0.00912 +2024-11-21 14:55:10.159898: train_loss -0.7723 +2024-11-21 14:55:10.160140: val_loss -0.7446 +2024-11-21 14:55:10.160213: Pseudo dice [0.8417] +2024-11-21 14:55:10.160289: Epoch time: 18.03 s +2024-11-21 14:55:11.110215: +2024-11-21 14:55:11.110457: Epoch 781 +2024-11-21 14:55:11.110571: Current learning rate: 0.00912 +2024-11-21 14:55:29.271440: train_loss -0.7743 +2024-11-21 14:55:29.271657: val_loss -0.7474 +2024-11-21 14:55:29.271731: Pseudo dice [0.8365] +2024-11-21 14:55:29.271806: Epoch time: 18.16 s +2024-11-21 14:55:30.125595: +2024-11-21 14:55:30.125806: Epoch 782 +2024-11-21 14:55:30.125918: Current learning rate: 0.00912 +2024-11-21 14:55:48.747687: train_loss -0.7457 +2024-11-21 14:55:48.749507: val_loss -0.726 +2024-11-21 14:55:48.749651: Pseudo dice [0.7902] +2024-11-21 14:55:48.749738: Epoch time: 18.62 s +2024-11-21 14:55:49.583401: +2024-11-21 14:55:49.583605: Epoch 783 +2024-11-21 14:55:49.583718: Current learning rate: 0.00911 +2024-11-21 14:56:08.098249: train_loss -0.764 +2024-11-21 14:56:08.098457: val_loss -0.7027 +2024-11-21 14:56:08.098529: Pseudo dice [0.8423] +2024-11-21 14:56:08.098604: Epoch time: 18.52 s +2024-11-21 14:56:09.084121: +2024-11-21 14:56:09.084465: Epoch 784 +2024-11-21 14:56:09.084586: Current learning rate: 0.00911 +2024-11-21 14:56:28.184343: train_loss -0.762 +2024-11-21 14:56:28.184547: val_loss -0.7672 +2024-11-21 14:56:28.184636: Pseudo dice [0.8598] +2024-11-21 14:56:28.184769: Epoch time: 19.1 s +2024-11-21 14:56:29.006256: +2024-11-21 14:56:29.006503: Epoch 785 +2024-11-21 14:56:29.006614: Current learning rate: 0.00911 +2024-11-21 14:56:46.318202: train_loss -0.7591 +2024-11-21 14:56:46.318420: val_loss -0.757 +2024-11-21 14:56:46.318497: Pseudo dice [0.8166] +2024-11-21 14:56:46.318573: Epoch time: 17.31 s +2024-11-21 14:56:47.143868: +2024-11-21 14:56:47.144077: Epoch 786 +2024-11-21 14:56:47.144192: Current learning rate: 0.00911 +2024-11-21 14:57:04.958982: train_loss -0.7669 +2024-11-21 14:57:04.959240: val_loss -0.7388 +2024-11-21 14:57:04.959318: Pseudo dice [0.834] +2024-11-21 14:57:04.959400: Epoch time: 17.82 s +2024-11-21 14:57:05.789008: +2024-11-21 14:57:05.789199: Epoch 787 +2024-11-21 14:57:05.789311: Current learning rate: 0.00911 +2024-11-21 14:57:23.945408: train_loss -0.7589 +2024-11-21 14:57:23.945608: val_loss -0.7413 +2024-11-21 14:57:23.945681: Pseudo dice [0.8226] +2024-11-21 14:57:23.945755: Epoch time: 18.16 s +2024-11-21 14:57:24.765106: +2024-11-21 14:57:24.765318: Epoch 788 +2024-11-21 14:57:24.765434: Current learning rate: 0.00911 +2024-11-21 14:57:42.862888: train_loss -0.7617 +2024-11-21 14:57:42.863123: val_loss -0.73 +2024-11-21 14:57:42.863202: Pseudo dice [0.8281] +2024-11-21 14:57:42.863286: Epoch time: 18.1 s +2024-11-21 14:57:43.691100: +2024-11-21 14:57:43.691307: Epoch 789 +2024-11-21 14:57:43.691428: Current learning rate: 0.00911 +2024-11-21 14:58:01.627705: train_loss -0.7467 +2024-11-21 14:58:01.627925: val_loss -0.7091 +2024-11-21 14:58:01.628006: Pseudo dice [0.8207] +2024-11-21 14:58:01.628085: Epoch time: 17.94 s +2024-11-21 14:58:02.832422: +2024-11-21 14:58:02.832661: Epoch 790 +2024-11-21 14:58:02.832785: Current learning rate: 0.00911 +2024-11-21 14:58:21.422398: train_loss -0.7583 +2024-11-21 14:58:21.422640: val_loss -0.7307 +2024-11-21 14:58:21.422716: Pseudo dice [0.8373] +2024-11-21 14:58:21.422795: Epoch time: 18.59 s +2024-11-21 14:58:22.243553: +2024-11-21 14:58:22.243788: Epoch 791 +2024-11-21 14:58:22.243906: Current learning rate: 0.00911 +2024-11-21 14:58:39.888594: train_loss -0.7582 +2024-11-21 14:58:39.888811: val_loss -0.7349 +2024-11-21 14:58:39.891729: Pseudo dice [0.8491] +2024-11-21 14:58:39.891881: Epoch time: 17.65 s +2024-11-21 14:58:40.842041: +2024-11-21 14:58:40.842268: Epoch 792 +2024-11-21 14:58:40.842388: Current learning rate: 0.0091 +2024-11-21 14:58:59.408806: train_loss -0.7647 +2024-11-21 14:58:59.409079: val_loss -0.7585 +2024-11-21 14:58:59.409163: Pseudo dice [0.8355] +2024-11-21 14:58:59.409268: Epoch time: 18.57 s +2024-11-21 14:59:00.230968: +2024-11-21 14:59:00.231181: Epoch 793 +2024-11-21 14:59:00.231292: Current learning rate: 0.0091 +2024-11-21 14:59:18.671580: train_loss -0.7659 +2024-11-21 14:59:18.676977: val_loss -0.7478 +2024-11-21 14:59:18.677158: Pseudo dice [0.8237] +2024-11-21 14:59:18.677252: Epoch time: 18.44 s +2024-11-21 14:59:19.672288: +2024-11-21 14:59:19.672644: Epoch 794 +2024-11-21 14:59:19.672762: Current learning rate: 0.0091 +2024-11-21 14:59:38.164607: train_loss -0.7646 +2024-11-21 14:59:38.164823: val_loss -0.7341 +2024-11-21 14:59:38.164900: Pseudo dice [0.828] +2024-11-21 14:59:38.165001: Epoch time: 18.49 s +2024-11-21 14:59:38.984960: +2024-11-21 14:59:38.985177: Epoch 795 +2024-11-21 14:59:38.985291: Current learning rate: 0.0091 +2024-11-21 14:59:57.590665: train_loss -0.7464 +2024-11-21 14:59:57.590873: val_loss -0.7226 +2024-11-21 14:59:57.590952: Pseudo dice [0.8413] +2024-11-21 14:59:57.591038: Epoch time: 18.61 s +2024-11-21 14:59:58.414658: +2024-11-21 14:59:58.414895: Epoch 796 +2024-11-21 14:59:58.415022: Current learning rate: 0.0091 +2024-11-21 15:00:17.356599: train_loss -0.7554 +2024-11-21 15:00:17.356817: val_loss -0.714 +2024-11-21 15:00:17.356895: Pseudo dice [0.8419] +2024-11-21 15:00:17.356973: Epoch time: 18.94 s +2024-11-21 15:00:18.220894: +2024-11-21 15:00:18.221115: Epoch 797 +2024-11-21 15:00:18.221232: Current learning rate: 0.0091 +2024-11-21 15:00:36.779284: train_loss -0.7557 +2024-11-21 15:00:36.779594: val_loss -0.7122 +2024-11-21 15:00:36.779670: Pseudo dice [0.8197] +2024-11-21 15:00:36.779752: Epoch time: 18.56 s +2024-11-21 15:00:37.607686: +2024-11-21 15:00:37.607890: Epoch 798 +2024-11-21 15:00:37.608009: Current learning rate: 0.0091 +2024-11-21 15:00:55.776654: train_loss -0.7556 +2024-11-21 15:00:55.776873: val_loss -0.7249 +2024-11-21 15:00:55.776948: Pseudo dice [0.84] +2024-11-21 15:00:55.777125: Epoch time: 18.17 s +2024-11-21 15:00:56.597516: +2024-11-21 15:00:56.597701: Epoch 799 +2024-11-21 15:00:56.597812: Current learning rate: 0.0091 +2024-11-21 15:01:15.215746: train_loss -0.7647 +2024-11-21 15:01:15.215967: val_loss -0.7575 +2024-11-21 15:01:15.216052: Pseudo dice [0.8587] +2024-11-21 15:01:15.216133: Epoch time: 18.62 s +2024-11-21 15:01:16.266113: +2024-11-21 15:01:16.266333: Epoch 800 +2024-11-21 15:01:16.266451: Current learning rate: 0.0091 +2024-11-21 15:01:34.728579: train_loss -0.7734 +2024-11-21 15:01:34.728789: val_loss -0.7588 +2024-11-21 15:01:34.728866: Pseudo dice [0.8286] +2024-11-21 15:01:34.728946: Epoch time: 18.46 s +2024-11-21 15:01:35.958878: +2024-11-21 15:01:35.959107: Epoch 801 +2024-11-21 15:01:35.959224: Current learning rate: 0.00909 +2024-11-21 15:01:54.197820: train_loss -0.7616 +2024-11-21 15:01:54.198075: val_loss -0.7377 +2024-11-21 15:01:54.198148: Pseudo dice [0.845] +2024-11-21 15:01:54.198229: Epoch time: 18.24 s +2024-11-21 15:01:55.016101: +2024-11-21 15:01:55.016336: Epoch 802 +2024-11-21 15:01:55.016444: Current learning rate: 0.00909 +2024-11-21 15:02:14.140640: train_loss -0.7669 +2024-11-21 15:02:14.140865: val_loss -0.7463 +2024-11-21 15:02:14.140949: Pseudo dice [0.8331] +2024-11-21 15:02:14.141042: Epoch time: 19.13 s +2024-11-21 15:02:14.968907: +2024-11-21 15:02:14.969139: Epoch 803 +2024-11-21 15:02:14.969256: Current learning rate: 0.00909 +2024-11-21 15:02:33.399504: train_loss -0.7606 +2024-11-21 15:02:33.399771: val_loss -0.7282 +2024-11-21 15:02:33.399845: Pseudo dice [0.8251] +2024-11-21 15:02:33.399927: Epoch time: 18.43 s +2024-11-21 15:02:34.394112: +2024-11-21 15:02:34.394318: Epoch 804 +2024-11-21 15:02:34.394433: Current learning rate: 0.00909 +2024-11-21 15:02:52.784090: train_loss -0.7527 +2024-11-21 15:02:52.789470: val_loss -0.7253 +2024-11-21 15:02:52.789592: Pseudo dice [0.8411] +2024-11-21 15:02:52.789671: Epoch time: 18.39 s +2024-11-21 15:02:53.623115: +2024-11-21 15:02:53.623321: Epoch 805 +2024-11-21 15:02:53.623435: Current learning rate: 0.00909 +2024-11-21 15:03:12.441392: train_loss -0.7554 +2024-11-21 15:03:12.441601: val_loss -0.7574 +2024-11-21 15:03:12.441675: Pseudo dice [0.839] +2024-11-21 15:03:12.441750: Epoch time: 18.82 s +2024-11-21 15:03:13.267041: +2024-11-21 15:03:13.267255: Epoch 806 +2024-11-21 15:03:13.267370: Current learning rate: 0.00909 +2024-11-21 15:03:31.709728: train_loss -0.7556 +2024-11-21 15:03:31.710003: val_loss -0.7281 +2024-11-21 15:03:31.710081: Pseudo dice [0.8414] +2024-11-21 15:03:31.710161: Epoch time: 18.44 s +2024-11-21 15:03:32.538185: +2024-11-21 15:03:32.538406: Epoch 807 +2024-11-21 15:03:32.538521: Current learning rate: 0.00909 +2024-11-21 15:03:50.639608: train_loss -0.762 +2024-11-21 15:03:50.639857: val_loss -0.7491 +2024-11-21 15:03:50.639933: Pseudo dice [0.8459] +2024-11-21 15:03:50.640019: Epoch time: 18.1 s +2024-11-21 15:03:51.461967: +2024-11-21 15:03:51.462187: Epoch 808 +2024-11-21 15:03:51.462303: Current learning rate: 0.00909 +2024-11-21 15:04:11.360732: train_loss -0.7717 +2024-11-21 15:04:11.361010: val_loss -0.7437 +2024-11-21 15:04:11.361090: Pseudo dice [0.8532] +2024-11-21 15:04:11.361170: Epoch time: 19.9 s +2024-11-21 15:04:12.186050: +2024-11-21 15:04:12.186242: Epoch 809 +2024-11-21 15:04:12.186354: Current learning rate: 0.00909 +2024-11-21 15:04:30.966133: train_loss -0.766 +2024-11-21 15:04:30.966357: val_loss -0.7439 +2024-11-21 15:04:30.966436: Pseudo dice [0.8476] +2024-11-21 15:04:30.966516: Epoch time: 18.78 s +2024-11-21 15:04:31.792152: +2024-11-21 15:04:31.792367: Epoch 810 +2024-11-21 15:04:31.792480: Current learning rate: 0.00908 +2024-11-21 15:04:50.791497: train_loss -0.7621 +2024-11-21 15:04:50.791699: val_loss -0.7084 +2024-11-21 15:04:50.791773: Pseudo dice [0.795] +2024-11-21 15:04:50.791851: Epoch time: 19.0 s +2024-11-21 15:04:51.667516: +2024-11-21 15:04:51.667763: Epoch 811 +2024-11-21 15:04:51.667921: Current learning rate: 0.00908 +2024-11-21 15:05:10.654834: train_loss -0.764 +2024-11-21 15:05:10.655055: val_loss -0.7336 +2024-11-21 15:05:10.655133: Pseudo dice [0.8436] +2024-11-21 15:05:10.655214: Epoch time: 18.99 s +2024-11-21 15:05:11.911825: +2024-11-21 15:05:11.912062: Epoch 812 +2024-11-21 15:05:11.912181: Current learning rate: 0.00908 +2024-11-21 15:05:30.186528: train_loss -0.7594 +2024-11-21 15:05:30.186761: val_loss -0.7569 +2024-11-21 15:05:30.186842: Pseudo dice [0.8327] +2024-11-21 15:05:30.186920: Epoch time: 18.28 s +2024-11-21 15:05:31.007553: +2024-11-21 15:05:31.007777: Epoch 813 +2024-11-21 15:05:31.007888: Current learning rate: 0.00908 +2024-11-21 15:05:50.026383: train_loss -0.7569 +2024-11-21 15:05:50.026603: val_loss -0.7411 +2024-11-21 15:05:50.026678: Pseudo dice [0.84] +2024-11-21 15:05:50.026759: Epoch time: 19.02 s +2024-11-21 15:05:50.855140: +2024-11-21 15:05:50.855390: Epoch 814 +2024-11-21 15:05:50.855502: Current learning rate: 0.00908 +2024-11-21 15:06:10.127327: train_loss -0.7569 +2024-11-21 15:06:10.127560: val_loss -0.7466 +2024-11-21 15:06:10.127632: Pseudo dice [0.8243] +2024-11-21 15:06:10.127710: Epoch time: 19.27 s +2024-11-21 15:06:10.957081: +2024-11-21 15:06:10.957294: Epoch 815 +2024-11-21 15:06:10.957403: Current learning rate: 0.00908 +2024-11-21 15:06:29.382987: train_loss -0.7664 +2024-11-21 15:06:29.383211: val_loss -0.7195 +2024-11-21 15:06:29.383286: Pseudo dice [0.8279] +2024-11-21 15:06:29.383363: Epoch time: 18.43 s +2024-11-21 15:06:30.206343: +2024-11-21 15:06:30.206593: Epoch 816 +2024-11-21 15:06:30.206704: Current learning rate: 0.00908 +2024-11-21 15:06:47.886401: train_loss -0.7679 +2024-11-21 15:06:47.886613: val_loss -0.7209 +2024-11-21 15:06:47.886686: Pseudo dice [0.8362] +2024-11-21 15:06:47.886762: Epoch time: 17.68 s +2024-11-21 15:06:48.713020: +2024-11-21 15:06:48.713220: Epoch 817 +2024-11-21 15:06:48.713339: Current learning rate: 0.00908 +2024-11-21 15:07:06.693630: train_loss -0.7784 +2024-11-21 15:07:06.693877: val_loss -0.7575 +2024-11-21 15:07:06.693950: Pseudo dice [0.8356] +2024-11-21 15:07:06.694043: Epoch time: 17.98 s +2024-11-21 15:07:07.535631: +2024-11-21 15:07:07.535895: Epoch 818 +2024-11-21 15:07:07.536024: Current learning rate: 0.00907 +2024-11-21 15:07:26.028772: train_loss -0.7685 +2024-11-21 15:07:26.033295: val_loss -0.7329 +2024-11-21 15:07:26.033408: Pseudo dice [0.81] +2024-11-21 15:07:26.033494: Epoch time: 18.49 s +2024-11-21 15:07:26.887675: +2024-11-21 15:07:26.887872: Epoch 819 +2024-11-21 15:07:26.887987: Current learning rate: 0.00907 +2024-11-21 15:07:45.907170: train_loss -0.7692 +2024-11-21 15:07:45.907381: val_loss -0.7245 +2024-11-21 15:07:45.907454: Pseudo dice [0.8443] +2024-11-21 15:07:45.907555: Epoch time: 19.02 s +2024-11-21 15:07:46.708801: +2024-11-21 15:07:46.709020: Epoch 820 +2024-11-21 15:07:46.709134: Current learning rate: 0.00907 +2024-11-21 15:08:05.904032: train_loss -0.7687 +2024-11-21 15:08:05.904260: val_loss -0.7306 +2024-11-21 15:08:05.904334: Pseudo dice [0.8358] +2024-11-21 15:08:05.904420: Epoch time: 19.2 s +2024-11-21 15:08:06.739717: +2024-11-21 15:08:06.739932: Epoch 821 +2024-11-21 15:08:06.740060: Current learning rate: 0.00907 +2024-11-21 15:08:25.206886: train_loss -0.7705 +2024-11-21 15:08:25.207146: val_loss -0.7477 +2024-11-21 15:08:25.207224: Pseudo dice [0.8434] +2024-11-21 15:08:25.207304: Epoch time: 18.47 s +2024-11-21 15:08:26.002349: +2024-11-21 15:08:26.002564: Epoch 822 +2024-11-21 15:08:26.002681: Current learning rate: 0.00907 +2024-11-21 15:08:43.826895: train_loss -0.7677 +2024-11-21 15:08:43.827106: val_loss -0.728 +2024-11-21 15:08:43.827183: Pseudo dice [0.8312] +2024-11-21 15:08:43.827259: Epoch time: 17.83 s +2024-11-21 15:08:44.621285: +2024-11-21 15:08:44.621489: Epoch 823 +2024-11-21 15:08:44.621600: Current learning rate: 0.00907 +2024-11-21 15:09:03.828712: train_loss -0.766 +2024-11-21 15:09:03.828935: val_loss -0.7303 +2024-11-21 15:09:03.829018: Pseudo dice [0.8284] +2024-11-21 15:09:03.829096: Epoch time: 19.21 s +2024-11-21 15:09:05.022394: +2024-11-21 15:09:05.022599: Epoch 824 +2024-11-21 15:09:05.022715: Current learning rate: 0.00907 +2024-11-21 15:09:23.803820: train_loss -0.7564 +2024-11-21 15:09:23.804074: val_loss -0.693 +2024-11-21 15:09:23.804147: Pseudo dice [0.8277] +2024-11-21 15:09:23.809376: Epoch time: 18.78 s +2024-11-21 15:09:24.708568: +2024-11-21 15:09:24.708827: Epoch 825 +2024-11-21 15:09:24.708937: Current learning rate: 0.00907 +2024-11-21 15:09:42.860350: train_loss -0.7575 +2024-11-21 15:09:42.860573: val_loss -0.7389 +2024-11-21 15:09:42.860650: Pseudo dice [0.8483] +2024-11-21 15:09:42.860728: Epoch time: 18.15 s +2024-11-21 15:09:43.660969: +2024-11-21 15:09:43.661278: Epoch 826 +2024-11-21 15:09:43.661396: Current learning rate: 0.00907 +2024-11-21 15:10:01.367045: train_loss -0.7612 +2024-11-21 15:10:01.367255: val_loss -0.7374 +2024-11-21 15:10:01.367326: Pseudo dice [0.8364] +2024-11-21 15:10:01.367402: Epoch time: 17.71 s +2024-11-21 15:10:02.230336: +2024-11-21 15:10:02.230578: Epoch 827 +2024-11-21 15:10:02.230699: Current learning rate: 0.00906 +2024-11-21 15:10:21.582802: train_loss -0.7651 +2024-11-21 15:10:21.583079: val_loss -0.7403 +2024-11-21 15:10:21.583154: Pseudo dice [0.8345] +2024-11-21 15:10:21.583235: Epoch time: 19.35 s +2024-11-21 15:10:22.387693: +2024-11-21 15:10:22.387902: Epoch 828 +2024-11-21 15:10:22.388026: Current learning rate: 0.00906 +2024-11-21 15:10:41.743776: train_loss -0.7447 +2024-11-21 15:10:41.743995: val_loss -0.7188 +2024-11-21 15:10:41.744071: Pseudo dice [0.8338] +2024-11-21 15:10:41.744148: Epoch time: 19.36 s +2024-11-21 15:10:42.552445: +2024-11-21 15:10:42.552706: Epoch 829 +2024-11-21 15:10:42.552824: Current learning rate: 0.00906 +2024-11-21 15:11:00.907402: train_loss -0.7499 +2024-11-21 15:11:00.907676: val_loss -0.7535 +2024-11-21 15:11:00.907752: Pseudo dice [0.8488] +2024-11-21 15:11:00.907828: Epoch time: 18.36 s +2024-11-21 15:11:01.710240: +2024-11-21 15:11:01.710456: Epoch 830 +2024-11-21 15:11:01.710565: Current learning rate: 0.00906 +2024-11-21 15:11:20.760664: train_loss -0.7557 +2024-11-21 15:11:20.760872: val_loss -0.7692 +2024-11-21 15:11:20.760954: Pseudo dice [0.8376] +2024-11-21 15:11:20.761036: Epoch time: 19.05 s +2024-11-21 15:11:21.562658: +2024-11-21 15:11:21.562894: Epoch 831 +2024-11-21 15:11:21.563008: Current learning rate: 0.00906 +2024-11-21 15:11:41.529202: train_loss -0.7601 +2024-11-21 15:11:41.530103: val_loss -0.7239 +2024-11-21 15:11:41.530181: Pseudo dice [0.8149] +2024-11-21 15:11:41.530262: Epoch time: 19.97 s +2024-11-21 15:11:42.329804: +2024-11-21 15:11:42.330063: Epoch 832 +2024-11-21 15:11:42.330174: Current learning rate: 0.00906 +2024-11-21 15:12:00.171644: train_loss -0.7472 +2024-11-21 15:12:00.171853: val_loss -0.7268 +2024-11-21 15:12:00.171972: Pseudo dice [0.8268] +2024-11-21 15:12:00.172055: Epoch time: 17.84 s +2024-11-21 15:12:00.992319: +2024-11-21 15:12:00.992547: Epoch 833 +2024-11-21 15:12:00.992671: Current learning rate: 0.00906 +2024-11-21 15:12:19.360655: train_loss -0.7599 +2024-11-21 15:12:19.360877: val_loss -0.7516 +2024-11-21 15:12:19.360953: Pseudo dice [0.8325] +2024-11-21 15:12:19.361033: Epoch time: 18.37 s +2024-11-21 15:12:20.170826: +2024-11-21 15:12:20.171018: Epoch 834 +2024-11-21 15:12:20.171131: Current learning rate: 0.00906 +2024-11-21 15:12:38.450276: train_loss -0.7567 +2024-11-21 15:12:38.450486: val_loss -0.7309 +2024-11-21 15:12:38.450559: Pseudo dice [0.8451] +2024-11-21 15:12:38.450639: Epoch time: 18.28 s +2024-11-21 15:12:39.255023: +2024-11-21 15:12:39.255212: Epoch 835 +2024-11-21 15:12:39.255324: Current learning rate: 0.00906 +2024-11-21 15:12:58.742940: train_loss -0.7595 +2024-11-21 15:12:58.743219: val_loss -0.7466 +2024-11-21 15:12:58.743293: Pseudo dice [0.846] +2024-11-21 15:12:58.743375: Epoch time: 19.49 s +2024-11-21 15:12:59.968661: +2024-11-21 15:12:59.968865: Epoch 836 +2024-11-21 15:12:59.968978: Current learning rate: 0.00905 +2024-11-21 15:13:18.382967: train_loss -0.7607 +2024-11-21 15:13:18.383205: val_loss -0.7415 +2024-11-21 15:13:18.383280: Pseudo dice [0.8314] +2024-11-21 15:13:18.383356: Epoch time: 18.42 s +2024-11-21 15:13:19.178097: +2024-11-21 15:13:19.178318: Epoch 837 +2024-11-21 15:13:19.178431: Current learning rate: 0.00905 +2024-11-21 15:13:38.437020: train_loss -0.7721 +2024-11-21 15:13:38.439859: val_loss -0.7251 +2024-11-21 15:13:38.439989: Pseudo dice [0.8221] +2024-11-21 15:13:38.440083: Epoch time: 19.26 s +2024-11-21 15:13:39.264417: +2024-11-21 15:13:39.264764: Epoch 838 +2024-11-21 15:13:39.264882: Current learning rate: 0.00905 +2024-11-21 15:13:57.902590: train_loss -0.7619 +2024-11-21 15:13:57.902819: val_loss -0.7323 +2024-11-21 15:13:57.902896: Pseudo dice [0.8284] +2024-11-21 15:13:57.902978: Epoch time: 18.64 s +2024-11-21 15:13:58.699712: +2024-11-21 15:13:58.699948: Epoch 839 +2024-11-21 15:13:58.700064: Current learning rate: 0.00905 +2024-11-21 15:14:16.596298: train_loss -0.7653 +2024-11-21 15:14:16.596499: val_loss -0.7383 +2024-11-21 15:14:16.596572: Pseudo dice [0.8347] +2024-11-21 15:14:16.596647: Epoch time: 17.9 s +2024-11-21 15:14:17.385248: +2024-11-21 15:14:17.385468: Epoch 840 +2024-11-21 15:14:17.385580: Current learning rate: 0.00905 +2024-11-21 15:14:36.758332: train_loss -0.7719 +2024-11-21 15:14:36.758536: val_loss -0.7593 +2024-11-21 15:14:36.758611: Pseudo dice [0.8587] +2024-11-21 15:14:36.758687: Epoch time: 19.37 s +2024-11-21 15:14:37.562667: +2024-11-21 15:14:37.562883: Epoch 841 +2024-11-21 15:14:37.563000: Current learning rate: 0.00905 +2024-11-21 15:14:57.018888: train_loss -0.7601 +2024-11-21 15:14:57.019131: val_loss -0.7018 +2024-11-21 15:14:57.019206: Pseudo dice [0.81] +2024-11-21 15:14:57.019287: Epoch time: 19.46 s +2024-11-21 15:14:57.822273: +2024-11-21 15:14:57.822517: Epoch 842 +2024-11-21 15:14:57.822633: Current learning rate: 0.00905 +2024-11-21 15:15:15.961513: train_loss -0.7554 +2024-11-21 15:15:15.961729: val_loss -0.7445 +2024-11-21 15:15:15.961801: Pseudo dice [0.8467] +2024-11-21 15:15:15.961878: Epoch time: 18.14 s +2024-11-21 15:15:16.768996: +2024-11-21 15:15:16.769206: Epoch 843 +2024-11-21 15:15:16.769320: Current learning rate: 0.00905 +2024-11-21 15:15:36.363765: train_loss -0.7518 +2024-11-21 15:15:36.363973: val_loss -0.7394 +2024-11-21 15:15:36.364056: Pseudo dice [0.8278] +2024-11-21 15:15:36.364137: Epoch time: 19.6 s +2024-11-21 15:15:37.171463: +2024-11-21 15:15:37.171650: Epoch 844 +2024-11-21 15:15:37.171758: Current learning rate: 0.00905 +2024-11-21 15:15:56.452430: train_loss -0.7728 +2024-11-21 15:15:56.452640: val_loss -0.7557 +2024-11-21 15:15:56.452713: Pseudo dice [0.8481] +2024-11-21 15:15:56.452789: Epoch time: 19.28 s +2024-11-21 15:15:57.285408: +2024-11-21 15:15:57.285807: Epoch 845 +2024-11-21 15:15:57.285934: Current learning rate: 0.00904 +2024-11-21 15:16:16.959844: train_loss -0.7582 +2024-11-21 15:16:16.960105: val_loss -0.6949 +2024-11-21 15:16:16.960180: Pseudo dice [0.8475] +2024-11-21 15:16:16.960261: Epoch time: 19.68 s +2024-11-21 15:16:17.755825: +2024-11-21 15:16:17.756036: Epoch 846 +2024-11-21 15:16:17.756150: Current learning rate: 0.00904 +2024-11-21 15:16:36.057464: train_loss -0.7628 +2024-11-21 15:16:36.057698: val_loss -0.7009 +2024-11-21 15:16:36.057805: Pseudo dice [0.8197] +2024-11-21 15:16:36.057911: Epoch time: 18.3 s +2024-11-21 15:16:36.851296: +2024-11-21 15:16:36.851502: Epoch 847 +2024-11-21 15:16:36.851614: Current learning rate: 0.00904 +2024-11-21 15:16:55.298070: train_loss -0.7605 +2024-11-21 15:16:55.298272: val_loss -0.7145 +2024-11-21 15:16:55.298345: Pseudo dice [0.817] +2024-11-21 15:16:55.298420: Epoch time: 18.45 s +2024-11-21 15:16:56.477559: +2024-11-21 15:16:56.477762: Epoch 848 +2024-11-21 15:16:56.477875: Current learning rate: 0.00904 +2024-11-21 15:17:14.751630: train_loss -0.747 +2024-11-21 15:17:14.751875: val_loss -0.7538 +2024-11-21 15:17:14.751970: Pseudo dice [0.8419] +2024-11-21 15:17:14.752062: Epoch time: 18.27 s +2024-11-21 15:17:15.544335: +2024-11-21 15:17:15.544559: Epoch 849 +2024-11-21 15:17:15.544674: Current learning rate: 0.00904 +2024-11-21 15:17:34.875352: train_loss -0.7565 +2024-11-21 15:17:34.875555: val_loss -0.7511 +2024-11-21 15:17:34.875628: Pseudo dice [0.8233] +2024-11-21 15:17:34.875701: Epoch time: 19.33 s +2024-11-21 15:17:35.970212: +2024-11-21 15:17:35.970435: Epoch 850 +2024-11-21 15:17:35.970552: Current learning rate: 0.00904 +2024-11-21 15:17:54.103870: train_loss -0.7573 +2024-11-21 15:17:54.104765: val_loss -0.7424 +2024-11-21 15:17:54.104849: Pseudo dice [0.8222] +2024-11-21 15:17:54.104928: Epoch time: 18.13 s +2024-11-21 15:17:54.907176: +2024-11-21 15:17:54.907404: Epoch 851 +2024-11-21 15:17:54.907511: Current learning rate: 0.00904 +2024-11-21 15:18:13.662792: train_loss -0.7606 +2024-11-21 15:18:13.665242: val_loss -0.721 +2024-11-21 15:18:13.665340: Pseudo dice [0.8444] +2024-11-21 15:18:13.665428: Epoch time: 18.76 s +2024-11-21 15:18:14.475985: +2024-11-21 15:18:14.476234: Epoch 852 +2024-11-21 15:18:14.476350: Current learning rate: 0.00904 +2024-11-21 15:18:32.219272: train_loss -0.7631 +2024-11-21 15:18:32.219480: val_loss -0.7331 +2024-11-21 15:18:32.219555: Pseudo dice [0.8343] +2024-11-21 15:18:32.219635: Epoch time: 17.74 s +2024-11-21 15:18:33.053982: +2024-11-21 15:18:33.054210: Epoch 853 +2024-11-21 15:18:33.054364: Current learning rate: 0.00904 +2024-11-21 15:18:51.550568: train_loss -0.7632 +2024-11-21 15:18:51.550775: val_loss -0.7393 +2024-11-21 15:18:51.550849: Pseudo dice [0.8204] +2024-11-21 15:18:51.550924: Epoch time: 18.5 s +2024-11-21 15:18:52.348671: +2024-11-21 15:18:52.348886: Epoch 854 +2024-11-21 15:18:52.349008: Current learning rate: 0.00903 +2024-11-21 15:19:10.509037: train_loss -0.7688 +2024-11-21 15:19:10.509241: val_loss -0.743 +2024-11-21 15:19:10.509316: Pseudo dice [0.8355] +2024-11-21 15:19:10.509394: Epoch time: 18.16 s +2024-11-21 15:19:11.296021: +2024-11-21 15:19:11.296218: Epoch 855 +2024-11-21 15:19:11.296328: Current learning rate: 0.00903 +2024-11-21 15:19:29.180189: train_loss -0.7736 +2024-11-21 15:19:29.180427: val_loss -0.7442 +2024-11-21 15:19:29.180564: Pseudo dice [0.8413] +2024-11-21 15:19:29.180647: Epoch time: 17.88 s +2024-11-21 15:19:30.079820: +2024-11-21 15:19:30.080024: Epoch 856 +2024-11-21 15:19:30.080138: Current learning rate: 0.00903 +2024-11-21 15:19:49.413942: train_loss -0.7676 +2024-11-21 15:19:49.414183: val_loss -0.7508 +2024-11-21 15:19:49.414255: Pseudo dice [0.8497] +2024-11-21 15:19:49.414334: Epoch time: 19.33 s +2024-11-21 15:19:50.217710: +2024-11-21 15:19:50.217911: Epoch 857 +2024-11-21 15:19:50.218031: Current learning rate: 0.00903 +2024-11-21 15:20:09.477085: train_loss -0.7683 +2024-11-21 15:20:09.477300: val_loss -0.7315 +2024-11-21 15:20:09.477396: Pseudo dice [0.823] +2024-11-21 15:20:09.477476: Epoch time: 19.26 s +2024-11-21 15:20:10.280366: +2024-11-21 15:20:10.280566: Epoch 858 +2024-11-21 15:20:10.280674: Current learning rate: 0.00903 +2024-11-21 15:20:28.700101: train_loss -0.7608 +2024-11-21 15:20:28.700370: val_loss -0.7357 +2024-11-21 15:20:28.700447: Pseudo dice [0.8474] +2024-11-21 15:20:28.700522: Epoch time: 18.42 s +2024-11-21 15:20:29.503044: +2024-11-21 15:20:29.503246: Epoch 859 +2024-11-21 15:20:29.503357: Current learning rate: 0.00903 +2024-11-21 15:20:48.347008: train_loss -0.7593 +2024-11-21 15:20:48.347262: val_loss -0.7559 +2024-11-21 15:20:48.347335: Pseudo dice [0.8584] +2024-11-21 15:20:48.347420: Epoch time: 18.84 s +2024-11-21 15:20:49.545274: +2024-11-21 15:20:49.545485: Epoch 860 +2024-11-21 15:20:49.545595: Current learning rate: 0.00903 +2024-11-21 15:21:09.140956: train_loss -0.761 +2024-11-21 15:21:09.141244: val_loss -0.7146 +2024-11-21 15:21:09.141328: Pseudo dice [0.8384] +2024-11-21 15:21:09.141404: Epoch time: 19.6 s +2024-11-21 15:21:09.944433: +2024-11-21 15:21:09.944633: Epoch 861 +2024-11-21 15:21:09.944747: Current learning rate: 0.00903 +2024-11-21 15:21:28.896673: train_loss -0.7662 +2024-11-21 15:21:28.896886: val_loss -0.7458 +2024-11-21 15:21:28.896960: Pseudo dice [0.8328] +2024-11-21 15:21:28.897046: Epoch time: 18.95 s +2024-11-21 15:21:29.696340: +2024-11-21 15:21:29.696548: Epoch 862 +2024-11-21 15:21:29.696666: Current learning rate: 0.00902 +2024-11-21 15:21:47.748936: train_loss -0.7633 +2024-11-21 15:21:47.749187: val_loss -0.7339 +2024-11-21 15:21:47.749266: Pseudo dice [0.8301] +2024-11-21 15:21:47.749350: Epoch time: 18.05 s +2024-11-21 15:21:48.567968: +2024-11-21 15:21:48.568204: Epoch 863 +2024-11-21 15:21:48.568323: Current learning rate: 0.00902 +2024-11-21 15:22:06.453406: train_loss -0.7677 +2024-11-21 15:22:06.453624: val_loss -0.734 +2024-11-21 15:22:06.453699: Pseudo dice [0.8441] +2024-11-21 15:22:06.453775: Epoch time: 17.89 s +2024-11-21 15:22:07.354669: +2024-11-21 15:22:07.354864: Epoch 864 +2024-11-21 15:22:07.354975: Current learning rate: 0.00902 +2024-11-21 15:22:26.389725: train_loss -0.7527 +2024-11-21 15:22:26.389946: val_loss -0.6847 +2024-11-21 15:22:26.392116: Pseudo dice [0.8113] +2024-11-21 15:22:26.392208: Epoch time: 19.04 s +2024-11-21 15:22:27.225155: +2024-11-21 15:22:27.225384: Epoch 865 +2024-11-21 15:22:27.225497: Current learning rate: 0.00902 +2024-11-21 15:22:45.365110: train_loss -0.7676 +2024-11-21 15:22:45.365320: val_loss -0.755 +2024-11-21 15:22:45.365396: Pseudo dice [0.8277] +2024-11-21 15:22:45.365473: Epoch time: 18.14 s +2024-11-21 15:22:46.179594: +2024-11-21 15:22:46.179811: Epoch 866 +2024-11-21 15:22:46.179924: Current learning rate: 0.00902 +2024-11-21 15:23:05.326591: train_loss -0.7552 +2024-11-21 15:23:05.326831: val_loss -0.7422 +2024-11-21 15:23:05.326929: Pseudo dice [0.8589] +2024-11-21 15:23:05.327022: Epoch time: 19.15 s +2024-11-21 15:23:06.130575: +2024-11-21 15:23:06.130791: Epoch 867 +2024-11-21 15:23:06.130908: Current learning rate: 0.00902 +2024-11-21 15:23:25.224232: train_loss -0.7694 +2024-11-21 15:23:25.224433: val_loss -0.7534 +2024-11-21 15:23:25.224506: Pseudo dice [0.831] +2024-11-21 15:23:25.224580: Epoch time: 19.09 s +2024-11-21 15:23:26.029159: +2024-11-21 15:23:26.029380: Epoch 868 +2024-11-21 15:23:26.029490: Current learning rate: 0.00902 +2024-11-21 15:23:44.873067: train_loss -0.7637 +2024-11-21 15:23:44.873277: val_loss -0.749 +2024-11-21 15:23:44.878561: Pseudo dice [0.8356] +2024-11-21 15:23:44.878694: Epoch time: 18.84 s +2024-11-21 15:23:45.741596: +2024-11-21 15:23:45.741820: Epoch 869 +2024-11-21 15:23:45.741937: Current learning rate: 0.00902 +2024-11-21 15:24:05.508544: train_loss -0.7715 +2024-11-21 15:24:05.508763: val_loss -0.707 +2024-11-21 15:24:05.508838: Pseudo dice [0.8365] +2024-11-21 15:24:05.508919: Epoch time: 19.77 s +2024-11-21 15:24:06.315228: +2024-11-21 15:24:06.315467: Epoch 870 +2024-11-21 15:24:06.315620: Current learning rate: 0.00902 +2024-11-21 15:24:25.988922: train_loss -0.7678 +2024-11-21 15:24:25.989145: val_loss -0.738 +2024-11-21 15:24:25.989221: Pseudo dice [0.8375] +2024-11-21 15:24:25.989297: Epoch time: 19.67 s +2024-11-21 15:24:26.791713: +2024-11-21 15:24:26.791903: Epoch 871 +2024-11-21 15:24:26.792021: Current learning rate: 0.00901 +2024-11-21 15:24:44.707026: train_loss -0.768 +2024-11-21 15:24:44.707301: val_loss -0.7359 +2024-11-21 15:24:44.707383: Pseudo dice [0.8541] +2024-11-21 15:24:44.707462: Epoch time: 17.92 s +2024-11-21 15:24:45.922814: +2024-11-21 15:24:45.923045: Epoch 872 +2024-11-21 15:24:45.923156: Current learning rate: 0.00901 +2024-11-21 15:25:05.446192: train_loss -0.7642 +2024-11-21 15:25:05.446492: val_loss -0.7495 +2024-11-21 15:25:05.446571: Pseudo dice [0.8269] +2024-11-21 15:25:05.446689: Epoch time: 19.52 s +2024-11-21 15:25:06.255694: +2024-11-21 15:25:06.255924: Epoch 873 +2024-11-21 15:25:06.256045: Current learning rate: 0.00901 +2024-11-21 15:25:24.640280: train_loss -0.7632 +2024-11-21 15:25:24.640492: val_loss -0.7508 +2024-11-21 15:25:24.640565: Pseudo dice [0.8553] +2024-11-21 15:25:24.640641: Epoch time: 18.39 s +2024-11-21 15:25:25.501419: +2024-11-21 15:25:25.501703: Epoch 874 +2024-11-21 15:25:25.501816: Current learning rate: 0.00901 +2024-11-21 15:25:43.708223: train_loss -0.7629 +2024-11-21 15:25:43.708438: val_loss -0.7158 +2024-11-21 15:25:43.708520: Pseudo dice [0.8238] +2024-11-21 15:25:43.708597: Epoch time: 18.21 s +2024-11-21 15:25:44.511232: +2024-11-21 15:25:44.511447: Epoch 875 +2024-11-21 15:25:44.511574: Current learning rate: 0.00901 +2024-11-21 15:26:02.878078: train_loss -0.7672 +2024-11-21 15:26:02.878311: val_loss -0.6948 +2024-11-21 15:26:02.878386: Pseudo dice [0.8191] +2024-11-21 15:26:02.878467: Epoch time: 18.37 s +2024-11-21 15:26:03.683042: +2024-11-21 15:26:03.683251: Epoch 876 +2024-11-21 15:26:03.683370: Current learning rate: 0.00901 +2024-11-21 15:26:22.537218: train_loss -0.7639 +2024-11-21 15:26:22.539645: val_loss -0.7169 +2024-11-21 15:26:22.539742: Pseudo dice [0.8213] +2024-11-21 15:26:22.539824: Epoch time: 18.86 s +2024-11-21 15:26:23.343957: +2024-11-21 15:26:23.344167: Epoch 877 +2024-11-21 15:26:23.344281: Current learning rate: 0.00901 +2024-11-21 15:26:42.098594: train_loss -0.7525 +2024-11-21 15:26:42.098806: val_loss -0.7219 +2024-11-21 15:26:42.098881: Pseudo dice [0.8396] +2024-11-21 15:26:42.098960: Epoch time: 18.76 s +2024-11-21 15:26:42.916540: +2024-11-21 15:26:42.916770: Epoch 878 +2024-11-21 15:26:42.916900: Current learning rate: 0.00901 +2024-11-21 15:27:00.962810: train_loss -0.7653 +2024-11-21 15:27:00.963025: val_loss -0.7203 +2024-11-21 15:27:00.963099: Pseudo dice [0.8536] +2024-11-21 15:27:00.963176: Epoch time: 18.05 s +2024-11-21 15:27:01.788058: +2024-11-21 15:27:01.788284: Epoch 879 +2024-11-21 15:27:01.788402: Current learning rate: 0.00901 +2024-11-21 15:27:20.238309: train_loss -0.7548 +2024-11-21 15:27:20.238557: val_loss -0.7282 +2024-11-21 15:27:20.238628: Pseudo dice [0.821] +2024-11-21 15:27:20.238709: Epoch time: 18.45 s +2024-11-21 15:27:21.162503: +2024-11-21 15:27:21.162719: Epoch 880 +2024-11-21 15:27:21.162835: Current learning rate: 0.009 +2024-11-21 15:27:40.044812: train_loss -0.7668 +2024-11-21 15:27:40.045031: val_loss -0.7369 +2024-11-21 15:27:40.045106: Pseudo dice [0.8372] +2024-11-21 15:27:40.045182: Epoch time: 18.88 s +2024-11-21 15:27:40.857888: +2024-11-21 15:27:40.858119: Epoch 881 +2024-11-21 15:27:40.858233: Current learning rate: 0.009 +2024-11-21 15:27:59.740263: train_loss -0.7669 +2024-11-21 15:27:59.740476: val_loss -0.7366 +2024-11-21 15:27:59.740550: Pseudo dice [0.8361] +2024-11-21 15:27:59.740626: Epoch time: 18.88 s +2024-11-21 15:28:00.542354: +2024-11-21 15:28:00.542651: Epoch 882 +2024-11-21 15:28:00.542768: Current learning rate: 0.009 +2024-11-21 15:28:19.250149: train_loss -0.7579 +2024-11-21 15:28:19.250364: val_loss -0.7135 +2024-11-21 15:28:19.250438: Pseudo dice [0.8303] +2024-11-21 15:28:19.250516: Epoch time: 18.71 s +2024-11-21 15:28:20.053409: +2024-11-21 15:28:20.053631: Epoch 883 +2024-11-21 15:28:20.053745: Current learning rate: 0.009 +2024-11-21 15:28:38.350596: train_loss -0.7607 +2024-11-21 15:28:38.350829: val_loss -0.7285 +2024-11-21 15:28:38.350902: Pseudo dice [0.84] +2024-11-21 15:28:38.350981: Epoch time: 18.3 s +2024-11-21 15:28:39.581960: +2024-11-21 15:28:39.582182: Epoch 884 +2024-11-21 15:28:39.582294: Current learning rate: 0.009 +2024-11-21 15:28:58.360720: train_loss -0.7707 +2024-11-21 15:28:58.360954: val_loss -0.7388 +2024-11-21 15:28:58.361037: Pseudo dice [0.8527] +2024-11-21 15:28:58.361112: Epoch time: 18.78 s +2024-11-21 15:28:59.165447: +2024-11-21 15:28:59.165709: Epoch 885 +2024-11-21 15:28:59.165823: Current learning rate: 0.009 +2024-11-21 15:29:17.129045: train_loss -0.7677 +2024-11-21 15:29:17.129274: val_loss -0.7467 +2024-11-21 15:29:17.129347: Pseudo dice [0.8568] +2024-11-21 15:29:17.129426: Epoch time: 17.96 s +2024-11-21 15:29:17.933411: +2024-11-21 15:29:17.933627: Epoch 886 +2024-11-21 15:29:17.933738: Current learning rate: 0.009 +2024-11-21 15:29:36.066422: train_loss -0.7697 +2024-11-21 15:29:36.066731: val_loss -0.733 +2024-11-21 15:29:36.066810: Pseudo dice [0.8407] +2024-11-21 15:29:36.066891: Epoch time: 18.13 s +2024-11-21 15:29:36.882283: +2024-11-21 15:29:36.882510: Epoch 887 +2024-11-21 15:29:36.882630: Current learning rate: 0.009 +2024-11-21 15:29:55.811766: train_loss -0.7703 +2024-11-21 15:29:55.811971: val_loss -0.7177 +2024-11-21 15:29:55.812052: Pseudo dice [0.83] +2024-11-21 15:29:55.812130: Epoch time: 18.93 s +2024-11-21 15:29:56.614522: +2024-11-21 15:29:56.614762: Epoch 888 +2024-11-21 15:29:56.614879: Current learning rate: 0.009 +2024-11-21 15:30:17.055688: train_loss -0.7681 +2024-11-21 15:30:17.055934: val_loss -0.7371 +2024-11-21 15:30:17.056020: Pseudo dice [0.8112] +2024-11-21 15:30:17.056102: Epoch time: 20.44 s +2024-11-21 15:30:17.901500: +2024-11-21 15:30:17.901706: Epoch 889 +2024-11-21 15:30:17.901816: Current learning rate: 0.00899 +2024-11-21 15:30:36.234498: train_loss -0.7738 +2024-11-21 15:30:36.234717: val_loss -0.7502 +2024-11-21 15:30:36.234791: Pseudo dice [0.8408] +2024-11-21 15:30:36.234873: Epoch time: 18.33 s +2024-11-21 15:30:37.043645: +2024-11-21 15:30:37.043902: Epoch 890 +2024-11-21 15:30:37.044041: Current learning rate: 0.00899 +2024-11-21 15:30:56.421414: train_loss -0.7645 +2024-11-21 15:30:56.421629: val_loss -0.7575 +2024-11-21 15:30:56.421704: Pseudo dice [0.8444] +2024-11-21 15:30:56.421783: Epoch time: 19.38 s +2024-11-21 15:30:57.270374: +2024-11-21 15:30:57.270571: Epoch 891 +2024-11-21 15:30:57.270688: Current learning rate: 0.00899 +2024-11-21 15:31:15.770449: train_loss -0.78 +2024-11-21 15:31:15.770673: val_loss -0.7288 +2024-11-21 15:31:15.770749: Pseudo dice [0.832] +2024-11-21 15:31:15.776054: Epoch time: 18.5 s +2024-11-21 15:31:16.668229: +2024-11-21 15:31:16.668646: Epoch 892 +2024-11-21 15:31:16.668763: Current learning rate: 0.00899 +2024-11-21 15:31:35.555337: train_loss -0.761 +2024-11-21 15:31:35.555555: val_loss -0.743 +2024-11-21 15:31:35.555628: Pseudo dice [0.8355] +2024-11-21 15:31:35.555716: Epoch time: 18.89 s +2024-11-21 15:31:36.357473: +2024-11-21 15:31:36.357748: Epoch 893 +2024-11-21 15:31:36.357870: Current learning rate: 0.00899 +2024-11-21 15:31:55.352823: train_loss -0.7751 +2024-11-21 15:31:55.353108: val_loss -0.7386 +2024-11-21 15:31:55.355497: Pseudo dice [0.8436] +2024-11-21 15:31:55.355598: Epoch time: 19.0 s +2024-11-21 15:31:56.165943: +2024-11-21 15:31:56.166161: Epoch 894 +2024-11-21 15:31:56.166275: Current learning rate: 0.00899 +2024-11-21 15:32:15.633384: train_loss -0.7735 +2024-11-21 15:32:15.633600: val_loss -0.7374 +2024-11-21 15:32:15.633674: Pseudo dice [0.8238] +2024-11-21 15:32:15.633750: Epoch time: 19.47 s +2024-11-21 15:32:16.637552: +2024-11-21 15:32:16.637773: Epoch 895 +2024-11-21 15:32:16.637887: Current learning rate: 0.00899 +2024-11-21 15:32:35.088427: train_loss -0.7795 +2024-11-21 15:32:35.088640: val_loss -0.7168 +2024-11-21 15:32:35.088717: Pseudo dice [0.8412] +2024-11-21 15:32:35.088794: Epoch time: 18.45 s +2024-11-21 15:32:36.277139: +2024-11-21 15:32:36.277486: Epoch 896 +2024-11-21 15:32:36.277607: Current learning rate: 0.00899 +2024-11-21 15:32:55.003740: train_loss -0.7679 +2024-11-21 15:32:55.003988: val_loss -0.7342 +2024-11-21 15:32:55.004071: Pseudo dice [0.8346] +2024-11-21 15:32:55.004155: Epoch time: 18.73 s +2024-11-21 15:32:55.912087: +2024-11-21 15:32:55.912587: Epoch 897 +2024-11-21 15:32:55.912716: Current learning rate: 0.00898 +2024-11-21 15:33:15.072313: train_loss -0.7739 +2024-11-21 15:33:15.072529: val_loss -0.6769 +2024-11-21 15:33:15.072660: Pseudo dice [0.8167] +2024-11-21 15:33:15.072746: Epoch time: 19.16 s +2024-11-21 15:33:15.874709: +2024-11-21 15:33:15.874915: Epoch 898 +2024-11-21 15:33:15.875034: Current learning rate: 0.00898 +2024-11-21 15:33:33.643455: train_loss -0.7733 +2024-11-21 15:33:33.643774: val_loss -0.7343 +2024-11-21 15:33:33.643858: Pseudo dice [0.8383] +2024-11-21 15:33:33.643936: Epoch time: 17.77 s +2024-11-21 15:33:34.446424: +2024-11-21 15:33:34.446745: Epoch 899 +2024-11-21 15:33:34.446863: Current learning rate: 0.00898 +2024-11-21 15:33:52.692963: train_loss -0.766 +2024-11-21 15:33:52.693217: val_loss -0.728 +2024-11-21 15:33:52.693294: Pseudo dice [0.8371] +2024-11-21 15:33:52.693384: Epoch time: 18.25 s +2024-11-21 15:33:53.733540: +2024-11-21 15:33:53.733744: Epoch 900 +2024-11-21 15:33:53.733863: Current learning rate: 0.00898 +2024-11-21 15:34:13.046123: train_loss -0.7649 +2024-11-21 15:34:13.046339: val_loss -0.743 +2024-11-21 15:34:13.046415: Pseudo dice [0.857] +2024-11-21 15:34:13.046499: Epoch time: 19.31 s +2024-11-21 15:34:13.846795: +2024-11-21 15:34:13.847052: Epoch 901 +2024-11-21 15:34:13.847167: Current learning rate: 0.00898 +2024-11-21 15:34:33.642772: train_loss -0.7725 +2024-11-21 15:34:33.642987: val_loss -0.7407 +2024-11-21 15:34:33.643074: Pseudo dice [0.8238] +2024-11-21 15:34:33.643173: Epoch time: 19.8 s +2024-11-21 15:34:34.446872: +2024-11-21 15:34:34.447129: Epoch 902 +2024-11-21 15:34:34.447245: Current learning rate: 0.00898 +2024-11-21 15:34:51.654933: train_loss -0.7746 +2024-11-21 15:34:51.655164: val_loss -0.7214 +2024-11-21 15:34:51.655240: Pseudo dice [0.8468] +2024-11-21 15:34:51.655315: Epoch time: 17.21 s +2024-11-21 15:34:52.460408: +2024-11-21 15:34:52.460626: Epoch 903 +2024-11-21 15:34:52.460747: Current learning rate: 0.00898 +2024-11-21 15:35:10.960464: train_loss -0.7644 +2024-11-21 15:35:10.960674: val_loss -0.7365 +2024-11-21 15:35:10.960746: Pseudo dice [0.8451] +2024-11-21 15:35:10.960823: Epoch time: 18.5 s +2024-11-21 15:35:11.972017: +2024-11-21 15:35:11.972270: Epoch 904 +2024-11-21 15:35:11.972418: Current learning rate: 0.00898 +2024-11-21 15:35:31.763943: train_loss -0.7538 +2024-11-21 15:35:31.764197: val_loss -0.7317 +2024-11-21 15:35:31.764272: Pseudo dice [0.8387] +2024-11-21 15:35:31.764349: Epoch time: 19.79 s +2024-11-21 15:35:32.568526: +2024-11-21 15:35:32.568726: Epoch 905 +2024-11-21 15:35:32.568838: Current learning rate: 0.00898 +2024-11-21 15:35:51.618962: train_loss -0.7575 +2024-11-21 15:35:51.619226: val_loss -0.7069 +2024-11-21 15:35:51.619308: Pseudo dice [0.8051] +2024-11-21 15:35:51.619384: Epoch time: 19.05 s +2024-11-21 15:35:52.419613: +2024-11-21 15:35:52.419827: Epoch 906 +2024-11-21 15:35:52.419942: Current learning rate: 0.00897 +2024-11-21 15:36:11.169167: train_loss -0.7627 +2024-11-21 15:36:11.169379: val_loss -0.7088 +2024-11-21 15:36:11.169455: Pseudo dice [0.8396] +2024-11-21 15:36:11.169531: Epoch time: 18.75 s +2024-11-21 15:36:11.977505: +2024-11-21 15:36:11.977738: Epoch 907 +2024-11-21 15:36:11.977862: Current learning rate: 0.00897 +2024-11-21 15:36:30.137389: train_loss -0.7692 +2024-11-21 15:36:30.137650: val_loss -0.749 +2024-11-21 15:36:30.137725: Pseudo dice [0.8393] +2024-11-21 15:36:30.137807: Epoch time: 18.16 s +2024-11-21 15:36:31.360131: +2024-11-21 15:36:31.360350: Epoch 908 +2024-11-21 15:36:31.360462: Current learning rate: 0.00897 +2024-11-21 15:36:49.270533: train_loss -0.7709 +2024-11-21 15:36:49.270755: val_loss -0.7626 +2024-11-21 15:36:49.270831: Pseudo dice [0.8427] +2024-11-21 15:36:49.270911: Epoch time: 17.91 s +2024-11-21 15:36:50.073168: +2024-11-21 15:36:50.073393: Epoch 909 +2024-11-21 15:36:50.073508: Current learning rate: 0.00897 +2024-11-21 15:37:08.272107: train_loss -0.7657 +2024-11-21 15:37:08.272355: val_loss -0.7306 +2024-11-21 15:37:08.272434: Pseudo dice [0.8192] +2024-11-21 15:37:08.272516: Epoch time: 18.19 s +2024-11-21 15:37:09.111357: +2024-11-21 15:37:09.111650: Epoch 910 +2024-11-21 15:37:09.111771: Current learning rate: 0.00897 +2024-11-21 15:37:27.768224: train_loss -0.7653 +2024-11-21 15:37:27.773693: val_loss -0.741 +2024-11-21 15:37:27.773811: Pseudo dice [0.8442] +2024-11-21 15:37:27.773931: Epoch time: 18.66 s +2024-11-21 15:37:28.673333: +2024-11-21 15:37:28.673525: Epoch 911 +2024-11-21 15:37:28.673634: Current learning rate: 0.00897 +2024-11-21 15:37:46.911870: train_loss -0.7613 +2024-11-21 15:37:46.912084: val_loss -0.7484 +2024-11-21 15:37:46.914405: Pseudo dice [0.845] +2024-11-21 15:37:46.914496: Epoch time: 18.24 s +2024-11-21 15:37:47.740517: +2024-11-21 15:37:47.740739: Epoch 912 +2024-11-21 15:37:47.740852: Current learning rate: 0.00897 +2024-11-21 15:38:06.685147: train_loss -0.7684 +2024-11-21 15:38:06.685357: val_loss -0.7257 +2024-11-21 15:38:06.685431: Pseudo dice [0.8302] +2024-11-21 15:38:06.685506: Epoch time: 18.95 s +2024-11-21 15:38:07.615455: +2024-11-21 15:38:07.615662: Epoch 913 +2024-11-21 15:38:07.615775: Current learning rate: 0.00897 +2024-11-21 15:38:27.963698: train_loss -0.7587 +2024-11-21 15:38:27.963984: val_loss -0.7345 +2024-11-21 15:38:27.964064: Pseudo dice [0.8491] +2024-11-21 15:38:27.964144: Epoch time: 20.35 s +2024-11-21 15:38:28.771534: +2024-11-21 15:38:28.771752: Epoch 914 +2024-11-21 15:38:28.771871: Current learning rate: 0.00897 +2024-11-21 15:38:47.294338: train_loss -0.7704 +2024-11-21 15:38:47.294583: val_loss -0.7659 +2024-11-21 15:38:47.294657: Pseudo dice [0.8538] +2024-11-21 15:38:47.294740: Epoch time: 18.52 s +2024-11-21 15:38:48.113364: +2024-11-21 15:38:48.113583: Epoch 915 +2024-11-21 15:38:48.113703: Current learning rate: 0.00896 +2024-11-21 15:39:07.410210: train_loss -0.7648 +2024-11-21 15:39:07.410422: val_loss -0.7319 +2024-11-21 15:39:07.410498: Pseudo dice [0.8412] +2024-11-21 15:39:07.410600: Epoch time: 19.3 s +2024-11-21 15:39:08.282029: +2024-11-21 15:39:08.282233: Epoch 916 +2024-11-21 15:39:08.282346: Current learning rate: 0.00896 +2024-11-21 15:39:27.709155: train_loss -0.7586 +2024-11-21 15:39:27.709383: val_loss -0.7205 +2024-11-21 15:39:27.709460: Pseudo dice [0.8429] +2024-11-21 15:39:27.709547: Epoch time: 19.43 s +2024-11-21 15:39:28.512810: +2024-11-21 15:39:28.513065: Epoch 917 +2024-11-21 15:39:28.513179: Current learning rate: 0.00896 +2024-11-21 15:39:47.810057: train_loss -0.7607 +2024-11-21 15:39:47.810299: val_loss -0.7134 +2024-11-21 15:39:47.810373: Pseudo dice [0.797] +2024-11-21 15:39:47.810456: Epoch time: 19.3 s +2024-11-21 15:39:48.624286: +2024-11-21 15:39:48.624535: Epoch 918 +2024-11-21 15:39:48.624647: Current learning rate: 0.00896 +2024-11-21 15:40:07.060659: train_loss -0.7714 +2024-11-21 15:40:07.060864: val_loss -0.7182 +2024-11-21 15:40:07.060939: Pseudo dice [0.8374] +2024-11-21 15:40:07.061122: Epoch time: 18.44 s +2024-11-21 15:40:07.865124: +2024-11-21 15:40:07.865336: Epoch 919 +2024-11-21 15:40:07.865450: Current learning rate: 0.00896 +2024-11-21 15:40:27.505705: train_loss -0.7684 +2024-11-21 15:40:27.505989: val_loss -0.7529 +2024-11-21 15:40:27.506073: Pseudo dice [0.8497] +2024-11-21 15:40:27.506150: Epoch time: 19.64 s +2024-11-21 15:40:28.716218: +2024-11-21 15:40:28.716452: Epoch 920 +2024-11-21 15:40:28.716568: Current learning rate: 0.00896 +2024-11-21 15:40:47.837783: train_loss -0.7588 +2024-11-21 15:40:47.838056: val_loss -0.7508 +2024-11-21 15:40:47.840371: Pseudo dice [0.8437] +2024-11-21 15:40:47.840489: Epoch time: 19.12 s +2024-11-21 15:40:48.746700: +2024-11-21 15:40:48.746913: Epoch 921 +2024-11-21 15:40:48.747040: Current learning rate: 0.00896 +2024-11-21 15:41:07.756563: train_loss -0.7649 +2024-11-21 15:41:07.756776: val_loss -0.7384 +2024-11-21 15:41:07.756852: Pseudo dice [0.8566] +2024-11-21 15:41:07.756928: Epoch time: 19.01 s +2024-11-21 15:41:08.575050: +2024-11-21 15:41:08.575288: Epoch 922 +2024-11-21 15:41:08.575402: Current learning rate: 0.00896 +2024-11-21 15:41:28.527735: train_loss -0.7686 +2024-11-21 15:41:28.527945: val_loss -0.7435 +2024-11-21 15:41:28.528026: Pseudo dice [0.8355] +2024-11-21 15:41:28.528106: Epoch time: 19.95 s +2024-11-21 15:41:29.338169: +2024-11-21 15:41:29.338593: Epoch 923 +2024-11-21 15:41:29.338714: Current learning rate: 0.00896 +2024-11-21 15:41:47.721791: train_loss -0.7786 +2024-11-21 15:41:47.722010: val_loss -0.7183 +2024-11-21 15:41:47.722089: Pseudo dice [0.8285] +2024-11-21 15:41:47.722167: Epoch time: 18.38 s +2024-11-21 15:41:48.525970: +2024-11-21 15:41:48.526194: Epoch 924 +2024-11-21 15:41:48.526306: Current learning rate: 0.00895 +2024-11-21 15:42:07.407703: train_loss -0.7697 +2024-11-21 15:42:07.407945: val_loss -0.7165 +2024-11-21 15:42:07.408025: Pseudo dice [0.8154] +2024-11-21 15:42:07.408109: Epoch time: 18.88 s +2024-11-21 15:42:08.247245: +2024-11-21 15:42:08.247598: Epoch 925 +2024-11-21 15:42:08.247716: Current learning rate: 0.00895 +2024-11-21 15:42:26.760444: train_loss -0.7643 +2024-11-21 15:42:26.760660: val_loss -0.7342 +2024-11-21 15:42:26.760734: Pseudo dice [0.8172] +2024-11-21 15:42:26.760809: Epoch time: 18.51 s +2024-11-21 15:42:27.718374: +2024-11-21 15:42:27.718607: Epoch 926 +2024-11-21 15:42:27.718727: Current learning rate: 0.00895 +2024-11-21 15:42:46.763642: train_loss -0.7614 +2024-11-21 15:42:46.763909: val_loss -0.7278 +2024-11-21 15:42:46.763985: Pseudo dice [0.8218] +2024-11-21 15:42:46.764066: Epoch time: 19.05 s +2024-11-21 15:42:47.569633: +2024-11-21 15:42:47.569868: Epoch 927 +2024-11-21 15:42:47.569988: Current learning rate: 0.00895 +2024-11-21 15:43:05.606106: train_loss -0.7733 +2024-11-21 15:43:05.606328: val_loss -0.7385 +2024-11-21 15:43:05.606402: Pseudo dice [0.8369] +2024-11-21 15:43:05.606484: Epoch time: 18.04 s +2024-11-21 15:43:06.412929: +2024-11-21 15:43:06.413163: Epoch 928 +2024-11-21 15:43:06.413278: Current learning rate: 0.00895 +2024-11-21 15:43:24.445765: train_loss -0.7503 +2024-11-21 15:43:24.451172: val_loss -0.7067 +2024-11-21 15:43:24.451291: Pseudo dice [0.8214] +2024-11-21 15:43:24.451379: Epoch time: 18.03 s +2024-11-21 15:43:25.359406: +2024-11-21 15:43:25.359676: Epoch 929 +2024-11-21 15:43:25.359788: Current learning rate: 0.00895 +2024-11-21 15:43:43.998366: train_loss -0.7562 +2024-11-21 15:43:43.998587: val_loss -0.7365 +2024-11-21 15:43:43.998663: Pseudo dice [0.8151] +2024-11-21 15:43:43.998739: Epoch time: 18.64 s +2024-11-21 15:43:44.831195: +2024-11-21 15:43:44.831410: Epoch 930 +2024-11-21 15:43:44.831522: Current learning rate: 0.00895 +2024-11-21 15:44:03.492125: train_loss -0.7699 +2024-11-21 15:44:03.492326: val_loss -0.7563 +2024-11-21 15:44:03.492399: Pseudo dice [0.8391] +2024-11-21 15:44:03.492474: Epoch time: 18.66 s +2024-11-21 15:44:04.306304: +2024-11-21 15:44:04.306613: Epoch 931 +2024-11-21 15:44:04.306731: Current learning rate: 0.00895 +2024-11-21 15:44:22.725184: train_loss -0.7728 +2024-11-21 15:44:22.725456: val_loss -0.727 +2024-11-21 15:44:22.725539: Pseudo dice [0.816] +2024-11-21 15:44:22.725623: Epoch time: 18.42 s +2024-11-21 15:44:24.019337: +2024-11-21 15:44:24.019559: Epoch 932 +2024-11-21 15:44:24.019674: Current learning rate: 0.00895 +2024-11-21 15:44:42.738750: train_loss -0.7651 +2024-11-21 15:44:42.738979: val_loss -0.7494 +2024-11-21 15:44:42.739060: Pseudo dice [0.8426] +2024-11-21 15:44:42.739187: Epoch time: 18.72 s +2024-11-21 15:44:43.547155: +2024-11-21 15:44:43.547392: Epoch 933 +2024-11-21 15:44:43.547514: Current learning rate: 0.00894 +2024-11-21 15:45:02.191628: train_loss -0.7691 +2024-11-21 15:45:02.191850: val_loss -0.7199 +2024-11-21 15:45:02.191923: Pseudo dice [0.8551] +2024-11-21 15:45:02.192009: Epoch time: 18.65 s +2024-11-21 15:45:02.999176: +2024-11-21 15:45:02.999405: Epoch 934 +2024-11-21 15:45:02.999516: Current learning rate: 0.00894 +2024-11-21 15:45:21.569752: train_loss -0.7665 +2024-11-21 15:45:21.570010: val_loss -0.7342 +2024-11-21 15:45:21.570087: Pseudo dice [0.8239] +2024-11-21 15:45:21.570168: Epoch time: 18.57 s +2024-11-21 15:45:22.385692: +2024-11-21 15:45:22.385894: Epoch 935 +2024-11-21 15:45:22.386018: Current learning rate: 0.00894 +2024-11-21 15:45:42.623649: train_loss -0.7652 +2024-11-21 15:45:42.623855: val_loss -0.7527 +2024-11-21 15:45:42.623931: Pseudo dice [0.8211] +2024-11-21 15:45:42.624015: Epoch time: 20.24 s +2024-11-21 15:45:43.432724: +2024-11-21 15:45:43.432933: Epoch 936 +2024-11-21 15:45:43.433056: Current learning rate: 0.00894 +2024-11-21 15:46:02.701593: train_loss -0.7566 +2024-11-21 15:46:02.701802: val_loss -0.7174 +2024-11-21 15:46:02.701874: Pseudo dice [0.8314] +2024-11-21 15:46:02.701953: Epoch time: 19.27 s +2024-11-21 15:46:03.722268: +2024-11-21 15:46:03.722492: Epoch 937 +2024-11-21 15:46:03.722610: Current learning rate: 0.00894 +2024-11-21 15:46:23.657559: train_loss -0.7514 +2024-11-21 15:46:23.657772: val_loss -0.724 +2024-11-21 15:46:23.657845: Pseudo dice [0.8346] +2024-11-21 15:46:23.657938: Epoch time: 19.94 s +2024-11-21 15:46:24.463536: +2024-11-21 15:46:24.463746: Epoch 938 +2024-11-21 15:46:24.463861: Current learning rate: 0.00894 +2024-11-21 15:46:43.238463: train_loss -0.7635 +2024-11-21 15:46:43.238710: val_loss -0.7308 +2024-11-21 15:46:43.238785: Pseudo dice [0.8273] +2024-11-21 15:46:43.238863: Epoch time: 18.78 s +2024-11-21 15:46:44.039120: +2024-11-21 15:46:44.039364: Epoch 939 +2024-11-21 15:46:44.039485: Current learning rate: 0.00894 +2024-11-21 15:47:03.507079: train_loss -0.7727 +2024-11-21 15:47:03.507285: val_loss -0.7357 +2024-11-21 15:47:03.507358: Pseudo dice [0.8464] +2024-11-21 15:47:03.507434: Epoch time: 19.47 s +2024-11-21 15:47:04.315356: +2024-11-21 15:47:04.315670: Epoch 940 +2024-11-21 15:47:04.315784: Current learning rate: 0.00894 +2024-11-21 15:47:23.463758: train_loss -0.7667 +2024-11-21 15:47:23.463976: val_loss -0.6966 +2024-11-21 15:47:23.464058: Pseudo dice [0.801] +2024-11-21 15:47:23.464136: Epoch time: 19.15 s +2024-11-21 15:47:24.272601: +2024-11-21 15:47:24.272804: Epoch 941 +2024-11-21 15:47:24.272914: Current learning rate: 0.00893 +2024-11-21 15:47:43.399927: train_loss -0.7744 +2024-11-21 15:47:43.400178: val_loss -0.6912 +2024-11-21 15:47:43.400256: Pseudo dice [0.8202] +2024-11-21 15:47:43.400352: Epoch time: 19.13 s +2024-11-21 15:47:44.209708: +2024-11-21 15:47:44.209916: Epoch 942 +2024-11-21 15:47:44.210036: Current learning rate: 0.00893 +2024-11-21 15:48:02.762266: train_loss -0.7313 +2024-11-21 15:48:02.762478: val_loss -0.738 +2024-11-21 15:48:02.762551: Pseudo dice [0.846] +2024-11-21 15:48:02.762629: Epoch time: 18.55 s +2024-11-21 15:48:03.604602: +2024-11-21 15:48:03.604813: Epoch 943 +2024-11-21 15:48:03.604929: Current learning rate: 0.00893 +2024-11-21 15:48:22.569603: train_loss -0.7353 +2024-11-21 15:48:22.569821: val_loss -0.7141 +2024-11-21 15:48:22.569896: Pseudo dice [0.8311] +2024-11-21 15:48:22.569971: Epoch time: 18.97 s +2024-11-21 15:48:23.775945: +2024-11-21 15:48:23.776174: Epoch 944 +2024-11-21 15:48:23.776288: Current learning rate: 0.00893 +2024-11-21 15:48:44.268318: train_loss -0.7502 +2024-11-21 15:48:44.268562: val_loss -0.7383 +2024-11-21 15:48:44.268636: Pseudo dice [0.8129] +2024-11-21 15:48:44.268730: Epoch time: 20.49 s +2024-11-21 15:48:45.075786: +2024-11-21 15:48:45.076003: Epoch 945 +2024-11-21 15:48:45.076116: Current learning rate: 0.00893 +2024-11-21 15:49:04.689607: train_loss -0.7598 +2024-11-21 15:49:04.689830: val_loss -0.7348 +2024-11-21 15:49:04.692147: Pseudo dice [0.8285] +2024-11-21 15:49:04.692260: Epoch time: 19.61 s +2024-11-21 15:49:05.513565: +2024-11-21 15:49:05.513805: Epoch 946 +2024-11-21 15:49:05.513918: Current learning rate: 0.00893 +2024-11-21 15:49:23.800870: train_loss -0.7671 +2024-11-21 15:49:23.801088: val_loss -0.75 +2024-11-21 15:49:23.801166: Pseudo dice [0.8374] +2024-11-21 15:49:23.801288: Epoch time: 18.29 s +2024-11-21 15:49:24.604433: +2024-11-21 15:49:24.604658: Epoch 947 +2024-11-21 15:49:24.604776: Current learning rate: 0.00893 +2024-11-21 15:49:42.959785: train_loss -0.7626 +2024-11-21 15:49:42.960031: val_loss -0.7257 +2024-11-21 15:49:42.960106: Pseudo dice [0.8075] +2024-11-21 15:49:42.960188: Epoch time: 18.36 s +2024-11-21 15:49:43.771246: +2024-11-21 15:49:43.771453: Epoch 948 +2024-11-21 15:49:43.771568: Current learning rate: 0.00893 +2024-11-21 15:50:02.003627: train_loss -0.753 +2024-11-21 15:50:02.003836: val_loss -0.7249 +2024-11-21 15:50:02.003908: Pseudo dice [0.8091] +2024-11-21 15:50:02.003982: Epoch time: 18.23 s +2024-11-21 15:50:02.810271: +2024-11-21 15:50:02.810720: Epoch 949 +2024-11-21 15:50:02.810841: Current learning rate: 0.00893 +2024-11-21 15:50:22.140059: train_loss -0.7622 +2024-11-21 15:50:22.140265: val_loss -0.721 +2024-11-21 15:50:22.140337: Pseudo dice [0.837] +2024-11-21 15:50:22.140411: Epoch time: 19.33 s +2024-11-21 15:50:23.286738: +2024-11-21 15:50:23.286956: Epoch 950 +2024-11-21 15:50:23.287074: Current learning rate: 0.00892 +2024-11-21 15:50:42.034589: train_loss -0.7613 +2024-11-21 15:50:42.034801: val_loss -0.7614 +2024-11-21 15:50:42.034875: Pseudo dice [0.8469] +2024-11-21 15:50:42.034954: Epoch time: 18.75 s +2024-11-21 15:50:42.844337: +2024-11-21 15:50:42.844544: Epoch 951 +2024-11-21 15:50:42.844658: Current learning rate: 0.00892 +2024-11-21 15:51:00.650540: train_loss -0.7624 +2024-11-21 15:51:00.650772: val_loss -0.7377 +2024-11-21 15:51:00.650848: Pseudo dice [0.8296] +2024-11-21 15:51:00.650927: Epoch time: 17.81 s +2024-11-21 15:51:01.610996: +2024-11-21 15:51:01.611251: Epoch 952 +2024-11-21 15:51:01.611365: Current learning rate: 0.00892 +2024-11-21 15:51:19.615184: train_loss -0.7623 +2024-11-21 15:51:19.615431: val_loss -0.7496 +2024-11-21 15:51:19.615566: Pseudo dice [0.8395] +2024-11-21 15:51:19.615651: Epoch time: 18.01 s +2024-11-21 15:51:20.474676: +2024-11-21 15:51:20.474866: Epoch 953 +2024-11-21 15:51:20.474978: Current learning rate: 0.00892 +2024-11-21 15:51:39.516408: train_loss -0.7542 +2024-11-21 15:51:39.516671: val_loss -0.7142 +2024-11-21 15:51:39.516750: Pseudo dice [0.8229] +2024-11-21 15:51:39.516830: Epoch time: 19.04 s +2024-11-21 15:51:40.395018: +2024-11-21 15:51:40.395276: Epoch 954 +2024-11-21 15:51:40.395397: Current learning rate: 0.00892 +2024-11-21 15:51:59.401522: train_loss -0.7554 +2024-11-21 15:51:59.401722: val_loss -0.7419 +2024-11-21 15:51:59.401833: Pseudo dice [0.8384] +2024-11-21 15:51:59.401912: Epoch time: 19.01 s +2024-11-21 15:52:00.225614: +2024-11-21 15:52:00.225806: Epoch 955 +2024-11-21 15:52:00.225944: Current learning rate: 0.00892 +2024-11-21 15:52:18.269346: train_loss -0.7637 +2024-11-21 15:52:18.269643: val_loss -0.7442 +2024-11-21 15:52:18.269719: Pseudo dice [0.8215] +2024-11-21 15:52:18.269804: Epoch time: 18.04 s +2024-11-21 15:52:19.494950: +2024-11-21 15:52:19.495156: Epoch 956 +2024-11-21 15:52:19.495266: Current learning rate: 0.00892 +2024-11-21 15:52:39.434616: train_loss -0.749 +2024-11-21 15:52:39.434930: val_loss -0.7211 +2024-11-21 15:52:39.435018: Pseudo dice [0.8525] +2024-11-21 15:52:39.435099: Epoch time: 19.94 s +2024-11-21 15:52:40.289948: +2024-11-21 15:52:40.290174: Epoch 957 +2024-11-21 15:52:40.290289: Current learning rate: 0.00892 +2024-11-21 15:52:59.582815: train_loss -0.7633 +2024-11-21 15:52:59.583034: val_loss -0.7605 +2024-11-21 15:52:59.583112: Pseudo dice [0.8599] +2024-11-21 15:52:59.583189: Epoch time: 19.29 s +2024-11-21 15:53:00.395606: +2024-11-21 15:53:00.395821: Epoch 958 +2024-11-21 15:53:00.395937: Current learning rate: 0.00892 +2024-11-21 15:53:18.497175: train_loss -0.7732 +2024-11-21 15:53:18.497471: val_loss -0.7242 +2024-11-21 15:53:18.497546: Pseudo dice [0.8411] +2024-11-21 15:53:18.497628: Epoch time: 18.1 s +2024-11-21 15:53:19.315485: +2024-11-21 15:53:19.315717: Epoch 959 +2024-11-21 15:53:19.315838: Current learning rate: 0.00891 +2024-11-21 15:53:38.084529: train_loss -0.77 +2024-11-21 15:53:38.084742: val_loss -0.7122 +2024-11-21 15:53:38.084814: Pseudo dice [0.8271] +2024-11-21 15:53:38.084889: Epoch time: 18.77 s +2024-11-21 15:53:38.909509: +2024-11-21 15:53:38.909757: Epoch 960 +2024-11-21 15:53:38.909872: Current learning rate: 0.00891 +2024-11-21 15:53:58.064576: train_loss -0.7684 +2024-11-21 15:53:58.064788: val_loss -0.7358 +2024-11-21 15:53:58.064867: Pseudo dice [0.8533] +2024-11-21 15:53:58.064948: Epoch time: 19.16 s +2024-11-21 15:53:58.880021: +2024-11-21 15:53:58.880245: Epoch 961 +2024-11-21 15:53:58.880358: Current learning rate: 0.00891 +2024-11-21 15:54:17.852018: train_loss -0.783 +2024-11-21 15:54:17.852231: val_loss -0.7685 +2024-11-21 15:54:17.852313: Pseudo dice [0.8326] +2024-11-21 15:54:17.852399: Epoch time: 18.97 s +2024-11-21 15:54:18.694376: +2024-11-21 15:54:18.694618: Epoch 962 +2024-11-21 15:54:18.694728: Current learning rate: 0.00891 +2024-11-21 15:54:37.566594: train_loss -0.7663 +2024-11-21 15:54:37.566846: val_loss -0.7671 +2024-11-21 15:54:37.566959: Pseudo dice [0.8268] +2024-11-21 15:54:37.567071: Epoch time: 18.87 s +2024-11-21 15:54:38.380203: +2024-11-21 15:54:38.380439: Epoch 963 +2024-11-21 15:54:38.380553: Current learning rate: 0.00891 +2024-11-21 15:54:56.217599: train_loss -0.7679 +2024-11-21 15:54:56.217808: val_loss -0.754 +2024-11-21 15:54:56.217883: Pseudo dice [0.8396] +2024-11-21 15:54:56.217963: Epoch time: 17.84 s +2024-11-21 15:54:57.027106: +2024-11-21 15:54:57.027368: Epoch 964 +2024-11-21 15:54:57.027487: Current learning rate: 0.00891 +2024-11-21 15:55:15.704999: train_loss -0.7608 +2024-11-21 15:55:15.705210: val_loss -0.7455 +2024-11-21 15:55:15.705287: Pseudo dice [0.853] +2024-11-21 15:55:15.705364: Epoch time: 18.68 s +2024-11-21 15:55:16.515073: +2024-11-21 15:55:16.515285: Epoch 965 +2024-11-21 15:55:16.515398: Current learning rate: 0.00891 +2024-11-21 15:55:35.201656: train_loss -0.7633 +2024-11-21 15:55:35.201891: val_loss -0.7365 +2024-11-21 15:55:35.201965: Pseudo dice [0.8308] +2024-11-21 15:55:35.202058: Epoch time: 18.69 s +2024-11-21 15:55:36.084805: +2024-11-21 15:55:36.085071: Epoch 966 +2024-11-21 15:55:36.085186: Current learning rate: 0.00891 +2024-11-21 15:55:55.410099: train_loss -0.7566 +2024-11-21 15:55:55.411237: val_loss -0.7269 +2024-11-21 15:55:55.411330: Pseudo dice [0.8129] +2024-11-21 15:55:55.411410: Epoch time: 19.33 s +2024-11-21 15:55:56.251640: +2024-11-21 15:55:56.251849: Epoch 967 +2024-11-21 15:55:56.251961: Current learning rate: 0.00891 +2024-11-21 15:56:15.043963: train_loss -0.7614 +2024-11-21 15:56:15.044258: val_loss -0.6927 +2024-11-21 15:56:15.044336: Pseudo dice [0.8176] +2024-11-21 15:56:15.044414: Epoch time: 18.79 s +2024-11-21 15:56:16.273669: +2024-11-21 15:56:16.273889: Epoch 968 +2024-11-21 15:56:16.274007: Current learning rate: 0.0089 +2024-11-21 15:56:35.601786: train_loss -0.7717 +2024-11-21 15:56:35.602044: val_loss -0.7396 +2024-11-21 15:56:35.602121: Pseudo dice [0.836] +2024-11-21 15:56:35.602207: Epoch time: 19.33 s +2024-11-21 15:56:36.417024: +2024-11-21 15:56:36.417329: Epoch 969 +2024-11-21 15:56:36.417505: Current learning rate: 0.0089 +2024-11-21 15:56:53.236580: train_loss -0.7683 +2024-11-21 15:56:53.236816: val_loss -0.7144 +2024-11-21 15:56:53.236901: Pseudo dice [0.8277] +2024-11-21 15:56:53.236982: Epoch time: 16.82 s +2024-11-21 15:56:54.048826: +2024-11-21 15:56:54.049077: Epoch 970 +2024-11-21 15:56:54.049194: Current learning rate: 0.0089 +2024-11-21 15:57:12.834082: train_loss -0.7711 +2024-11-21 15:57:12.834297: val_loss -0.7288 +2024-11-21 15:57:12.834378: Pseudo dice [0.8148] +2024-11-21 15:57:12.834458: Epoch time: 18.79 s +2024-11-21 15:57:13.644515: +2024-11-21 15:57:13.644813: Epoch 971 +2024-11-21 15:57:13.644928: Current learning rate: 0.0089 +2024-11-21 15:57:32.637957: train_loss -0.7787 +2024-11-21 15:57:32.638212: val_loss -0.7465 +2024-11-21 15:57:32.638286: Pseudo dice [0.8263] +2024-11-21 15:57:32.638374: Epoch time: 18.99 s +2024-11-21 15:57:33.461521: +2024-11-21 15:57:33.461737: Epoch 972 +2024-11-21 15:57:33.461848: Current learning rate: 0.0089 +2024-11-21 15:57:53.644716: train_loss -0.7742 +2024-11-21 15:57:53.644926: val_loss -0.7505 +2024-11-21 15:57:53.645041: Pseudo dice [0.8457] +2024-11-21 15:57:53.645119: Epoch time: 20.18 s +2024-11-21 15:57:54.463012: +2024-11-21 15:57:54.463221: Epoch 973 +2024-11-21 15:57:54.463335: Current learning rate: 0.0089 +2024-11-21 15:58:12.528851: train_loss -0.7769 +2024-11-21 15:58:12.529059: val_loss -0.7284 +2024-11-21 15:58:12.529130: Pseudo dice [0.8465] +2024-11-21 15:58:12.529205: Epoch time: 18.07 s +2024-11-21 15:58:13.344656: +2024-11-21 15:58:13.344892: Epoch 974 +2024-11-21 15:58:13.345019: Current learning rate: 0.0089 +2024-11-21 15:58:31.552340: train_loss -0.7684 +2024-11-21 15:58:31.552560: val_loss -0.727 +2024-11-21 15:58:31.552635: Pseudo dice [0.819] +2024-11-21 15:58:31.552711: Epoch time: 18.21 s +2024-11-21 15:58:32.368185: +2024-11-21 15:58:32.368581: Epoch 975 +2024-11-21 15:58:32.368701: Current learning rate: 0.0089 +2024-11-21 15:58:50.376127: train_loss -0.7629 +2024-11-21 15:58:50.376351: val_loss -0.7213 +2024-11-21 15:58:50.380700: Pseudo dice [0.7943] +2024-11-21 15:58:50.380805: Epoch time: 18.01 s +2024-11-21 15:58:51.363460: +2024-11-21 15:58:51.363789: Epoch 976 +2024-11-21 15:58:51.363947: Current learning rate: 0.00889 +2024-11-21 15:59:09.672915: train_loss -0.7683 +2024-11-21 15:59:09.673139: val_loss -0.7243 +2024-11-21 15:59:09.673217: Pseudo dice [0.8242] +2024-11-21 15:59:09.673295: Epoch time: 18.31 s +2024-11-21 15:59:10.485893: +2024-11-21 15:59:10.486096: Epoch 977 +2024-11-21 15:59:10.486209: Current learning rate: 0.00889 +2024-11-21 15:59:28.952449: train_loss -0.7759 +2024-11-21 15:59:28.952668: val_loss -0.7651 +2024-11-21 15:59:28.952745: Pseudo dice [0.8481] +2024-11-21 15:59:28.952824: Epoch time: 18.47 s +2024-11-21 15:59:29.774439: +2024-11-21 15:59:29.774719: Epoch 978 +2024-11-21 15:59:29.774838: Current learning rate: 0.00889 +2024-11-21 15:59:49.383219: train_loss -0.7642 +2024-11-21 15:59:49.384156: val_loss -0.7219 +2024-11-21 15:59:49.384235: Pseudo dice [0.821] +2024-11-21 15:59:49.384314: Epoch time: 19.61 s +2024-11-21 15:59:50.207852: +2024-11-21 15:59:50.208062: Epoch 979 +2024-11-21 15:59:50.208173: Current learning rate: 0.00889 +2024-11-21 16:00:07.828463: train_loss -0.7694 +2024-11-21 16:00:07.828721: val_loss -0.738 +2024-11-21 16:00:07.828798: Pseudo dice [0.8392] +2024-11-21 16:00:07.828882: Epoch time: 17.62 s +2024-11-21 16:00:09.132640: +2024-11-21 16:00:09.132848: Epoch 980 +2024-11-21 16:00:09.132965: Current learning rate: 0.00889 +2024-11-21 16:00:27.689098: train_loss -0.773 +2024-11-21 16:00:27.689387: val_loss -0.7466 +2024-11-21 16:00:27.689463: Pseudo dice [0.8517] +2024-11-21 16:00:27.689540: Epoch time: 18.56 s +2024-11-21 16:00:28.519240: +2024-11-21 16:00:28.519466: Epoch 981 +2024-11-21 16:00:28.519580: Current learning rate: 0.00889 +2024-11-21 16:00:47.445003: train_loss -0.7501 +2024-11-21 16:00:47.445237: val_loss -0.7129 +2024-11-21 16:00:47.445314: Pseudo dice [0.8171] +2024-11-21 16:00:47.445396: Epoch time: 18.93 s +2024-11-21 16:00:48.258566: +2024-11-21 16:00:48.258841: Epoch 982 +2024-11-21 16:00:48.258962: Current learning rate: 0.00889 +2024-11-21 16:01:06.917157: train_loss -0.7639 +2024-11-21 16:01:06.917410: val_loss -0.7475 +2024-11-21 16:01:06.917491: Pseudo dice [0.818] +2024-11-21 16:01:06.917579: Epoch time: 18.66 s +2024-11-21 16:01:07.737840: +2024-11-21 16:01:07.738038: Epoch 983 +2024-11-21 16:01:07.738150: Current learning rate: 0.00889 +2024-11-21 16:01:25.897393: train_loss -0.7678 +2024-11-21 16:01:25.897610: val_loss -0.7327 +2024-11-21 16:01:25.897681: Pseudo dice [0.82] +2024-11-21 16:01:25.897755: Epoch time: 18.16 s +2024-11-21 16:01:26.748057: +2024-11-21 16:01:26.748308: Epoch 984 +2024-11-21 16:01:26.748427: Current learning rate: 0.00889 +2024-11-21 16:01:45.778095: train_loss -0.7666 +2024-11-21 16:01:45.778322: val_loss -0.7437 +2024-11-21 16:01:45.778458: Pseudo dice [0.8532] +2024-11-21 16:01:45.778537: Epoch time: 19.03 s +2024-11-21 16:01:46.599050: +2024-11-21 16:01:46.599274: Epoch 985 +2024-11-21 16:01:46.599386: Current learning rate: 0.00888 +2024-11-21 16:02:05.445325: train_loss -0.7738 +2024-11-21 16:02:05.445598: val_loss -0.7338 +2024-11-21 16:02:05.445675: Pseudo dice [0.8398] +2024-11-21 16:02:05.445756: Epoch time: 18.85 s +2024-11-21 16:02:06.269563: +2024-11-21 16:02:06.269780: Epoch 986 +2024-11-21 16:02:06.269895: Current learning rate: 0.00888 +2024-11-21 16:02:24.298638: train_loss -0.7621 +2024-11-21 16:02:24.301007: val_loss -0.7243 +2024-11-21 16:02:24.301114: Pseudo dice [0.8231] +2024-11-21 16:02:24.301197: Epoch time: 18.03 s +2024-11-21 16:02:25.117751: +2024-11-21 16:02:25.118024: Epoch 987 +2024-11-21 16:02:25.118136: Current learning rate: 0.00888 +2024-11-21 16:02:43.731655: train_loss -0.7635 +2024-11-21 16:02:43.731867: val_loss -0.7447 +2024-11-21 16:02:43.731953: Pseudo dice [0.846] +2024-11-21 16:02:43.732038: Epoch time: 18.61 s +2024-11-21 16:02:44.562215: +2024-11-21 16:02:44.562450: Epoch 988 +2024-11-21 16:02:44.562564: Current learning rate: 0.00888 +2024-11-21 16:03:03.405508: train_loss -0.7711 +2024-11-21 16:03:03.405731: val_loss -0.7329 +2024-11-21 16:03:03.405806: Pseudo dice [0.8334] +2024-11-21 16:03:03.405883: Epoch time: 18.84 s +2024-11-21 16:03:04.222910: +2024-11-21 16:03:04.223126: Epoch 989 +2024-11-21 16:03:04.223244: Current learning rate: 0.00888 +2024-11-21 16:03:23.461078: train_loss -0.7713 +2024-11-21 16:03:23.461315: val_loss -0.7203 +2024-11-21 16:03:23.461389: Pseudo dice [0.8183] +2024-11-21 16:03:23.461476: Epoch time: 19.24 s +2024-11-21 16:03:24.275552: +2024-11-21 16:03:24.275735: Epoch 990 +2024-11-21 16:03:24.275851: Current learning rate: 0.00888 +2024-11-21 16:03:43.047239: train_loss -0.7631 +2024-11-21 16:03:43.047455: val_loss -0.7477 +2024-11-21 16:03:43.047529: Pseudo dice [0.8189] +2024-11-21 16:03:43.047606: Epoch time: 18.77 s +2024-11-21 16:03:43.861719: +2024-11-21 16:03:43.861919: Epoch 991 +2024-11-21 16:03:43.862038: Current learning rate: 0.00888 +2024-11-21 16:04:01.992851: train_loss -0.7648 +2024-11-21 16:04:01.993067: val_loss -0.7371 +2024-11-21 16:04:01.993144: Pseudo dice [0.8302] +2024-11-21 16:04:01.993220: Epoch time: 18.13 s +2024-11-21 16:04:03.219205: +2024-11-21 16:04:03.219413: Epoch 992 +2024-11-21 16:04:03.219522: Current learning rate: 0.00888 +2024-11-21 16:04:21.921538: train_loss -0.7481 +2024-11-21 16:04:21.921776: val_loss -0.6829 +2024-11-21 16:04:21.921915: Pseudo dice [0.8122] +2024-11-21 16:04:21.922005: Epoch time: 18.7 s +2024-11-21 16:04:22.838895: +2024-11-21 16:04:22.839137: Epoch 993 +2024-11-21 16:04:22.839253: Current learning rate: 0.00888 +2024-11-21 16:04:41.876780: train_loss -0.7496 +2024-11-21 16:04:41.877020: val_loss -0.7415 +2024-11-21 16:04:41.877099: Pseudo dice [0.8309] +2024-11-21 16:04:41.877178: Epoch time: 19.04 s +2024-11-21 16:04:42.803151: +2024-11-21 16:04:42.803369: Epoch 994 +2024-11-21 16:04:42.803483: Current learning rate: 0.00887 +2024-11-21 16:05:02.351763: train_loss -0.7646 +2024-11-21 16:05:02.351971: val_loss -0.7428 +2024-11-21 16:05:02.352056: Pseudo dice [0.8146] +2024-11-21 16:05:02.352136: Epoch time: 19.55 s +2024-11-21 16:05:03.162335: +2024-11-21 16:05:03.162546: Epoch 995 +2024-11-21 16:05:03.162660: Current learning rate: 0.00887 +2024-11-21 16:05:22.492226: train_loss -0.7604 +2024-11-21 16:05:22.504296: val_loss -0.7444 +2024-11-21 16:05:22.504460: Pseudo dice [0.8319] +2024-11-21 16:05:22.504554: Epoch time: 19.33 s +2024-11-21 16:05:23.336287: +2024-11-21 16:05:23.336496: Epoch 996 +2024-11-21 16:05:23.336614: Current learning rate: 0.00887 +2024-11-21 16:05:43.091446: train_loss -0.7604 +2024-11-21 16:05:43.091680: val_loss -0.7448 +2024-11-21 16:05:43.091759: Pseudo dice [0.8393] +2024-11-21 16:05:43.091834: Epoch time: 19.76 s +2024-11-21 16:05:43.905534: +2024-11-21 16:05:43.905755: Epoch 997 +2024-11-21 16:05:43.905871: Current learning rate: 0.00887 +2024-11-21 16:06:02.937710: train_loss -0.7589 +2024-11-21 16:06:02.937934: val_loss -0.7413 +2024-11-21 16:06:02.943604: Pseudo dice [0.8246] +2024-11-21 16:06:02.943696: Epoch time: 19.03 s +2024-11-21 16:06:03.933166: +2024-11-21 16:06:03.933356: Epoch 998 +2024-11-21 16:06:03.933475: Current learning rate: 0.00887 +2024-11-21 16:06:20.760964: train_loss -0.7498 +2024-11-21 16:06:20.761180: val_loss -0.7535 +2024-11-21 16:06:20.761256: Pseudo dice [0.8546] +2024-11-21 16:06:20.761334: Epoch time: 16.83 s +2024-11-21 16:06:21.683676: +2024-11-21 16:06:21.683893: Epoch 999 +2024-11-21 16:06:21.684012: Current learning rate: 0.00887 +2024-11-21 16:06:40.395589: train_loss -0.7683 +2024-11-21 16:06:40.395812: val_loss -0.7452 +2024-11-21 16:06:40.395886: Pseudo dice [0.8406] +2024-11-21 16:06:40.395967: Epoch time: 18.71 s +2024-11-21 16:06:41.438330: +2024-11-21 16:06:41.438592: Epoch 1000 +2024-11-21 16:06:41.438752: Current learning rate: 0.00887 +2024-11-21 16:07:00.262789: train_loss -0.7712 +2024-11-21 16:07:00.263077: val_loss -0.7157 +2024-11-21 16:07:00.263151: Pseudo dice [0.8251] +2024-11-21 16:07:00.263229: Epoch time: 18.83 s +2024-11-21 16:07:01.075672: +2024-11-21 16:07:01.076050: Epoch 1001 +2024-11-21 16:07:01.076169: Current learning rate: 0.00887 +2024-11-21 16:07:19.375034: train_loss -0.7713 +2024-11-21 16:07:19.375246: val_loss -0.7415 +2024-11-21 16:07:19.375322: Pseudo dice [0.8396] +2024-11-21 16:07:19.375397: Epoch time: 18.3 s +2024-11-21 16:07:20.206072: +2024-11-21 16:07:20.206275: Epoch 1002 +2024-11-21 16:07:20.206390: Current learning rate: 0.00887 +2024-11-21 16:07:38.317155: train_loss -0.7722 +2024-11-21 16:07:38.317361: val_loss -0.7592 +2024-11-21 16:07:38.317435: Pseudo dice [0.8369] +2024-11-21 16:07:38.317513: Epoch time: 18.11 s +2024-11-21 16:07:39.131951: +2024-11-21 16:07:39.132178: Epoch 1003 +2024-11-21 16:07:39.132305: Current learning rate: 0.00886 +2024-11-21 16:07:57.972176: train_loss -0.7677 +2024-11-21 16:07:57.972405: val_loss -0.7447 +2024-11-21 16:07:57.972488: Pseudo dice [0.8158] +2024-11-21 16:07:57.972569: Epoch time: 18.84 s +2024-11-21 16:07:58.783749: +2024-11-21 16:07:58.784047: Epoch 1004 +2024-11-21 16:07:58.784172: Current learning rate: 0.00886 +2024-11-21 16:08:17.107985: train_loss -0.7601 +2024-11-21 16:08:17.108212: val_loss -0.7497 +2024-11-21 16:08:17.108293: Pseudo dice [0.8143] +2024-11-21 16:08:17.108392: Epoch time: 18.33 s +2024-11-21 16:08:17.926708: +2024-11-21 16:08:17.926940: Epoch 1005 +2024-11-21 16:08:17.927075: Current learning rate: 0.00886 +2024-11-21 16:08:36.871354: train_loss -0.758 +2024-11-21 16:08:36.871568: val_loss -0.7424 +2024-11-21 16:08:36.871643: Pseudo dice [0.8519] +2024-11-21 16:08:36.871719: Epoch time: 18.95 s +2024-11-21 16:08:37.693027: +2024-11-21 16:08:37.693360: Epoch 1006 +2024-11-21 16:08:37.693488: Current learning rate: 0.00886 +2024-11-21 16:08:56.274073: train_loss -0.7739 +2024-11-21 16:08:56.274308: val_loss -0.7647 +2024-11-21 16:08:56.274450: Pseudo dice [0.8354] +2024-11-21 16:08:56.274534: Epoch time: 18.58 s +2024-11-21 16:08:57.099274: +2024-11-21 16:08:57.099516: Epoch 1007 +2024-11-21 16:08:57.099627: Current learning rate: 0.00886 +2024-11-21 16:09:15.082366: train_loss -0.7725 +2024-11-21 16:09:15.087749: val_loss -0.7257 +2024-11-21 16:09:15.087860: Pseudo dice [0.8499] +2024-11-21 16:09:15.087942: Epoch time: 17.98 s +2024-11-21 16:09:16.083122: +2024-11-21 16:09:16.083346: Epoch 1008 +2024-11-21 16:09:16.083457: Current learning rate: 0.00886 +2024-11-21 16:09:35.251487: train_loss -0.7691 +2024-11-21 16:09:35.251701: val_loss -0.7335 +2024-11-21 16:09:35.251772: Pseudo dice [0.8495] +2024-11-21 16:09:35.251850: Epoch time: 19.17 s +2024-11-21 16:09:36.072051: +2024-11-21 16:09:36.072267: Epoch 1009 +2024-11-21 16:09:36.072380: Current learning rate: 0.00886 +2024-11-21 16:09:54.397427: train_loss -0.7695 +2024-11-21 16:09:54.397649: val_loss -0.7019 +2024-11-21 16:09:54.397724: Pseudo dice [0.8235] +2024-11-21 16:09:54.397805: Epoch time: 18.33 s +2024-11-21 16:09:55.301389: +2024-11-21 16:09:55.301613: Epoch 1010 +2024-11-21 16:09:55.301730: Current learning rate: 0.00886 +2024-11-21 16:10:12.602181: train_loss -0.7798 +2024-11-21 16:10:12.602441: val_loss -0.7208 +2024-11-21 16:10:12.602519: Pseudo dice [0.8341] +2024-11-21 16:10:12.602603: Epoch time: 17.3 s +2024-11-21 16:10:13.423731: +2024-11-21 16:10:13.424003: Epoch 1011 +2024-11-21 16:10:13.424123: Current learning rate: 0.00886 +2024-11-21 16:10:31.422694: train_loss -0.7646 +2024-11-21 16:10:31.422916: val_loss -0.7584 +2024-11-21 16:10:31.422994: Pseudo dice [0.8366] +2024-11-21 16:10:31.423082: Epoch time: 18.0 s +2024-11-21 16:10:32.244560: +2024-11-21 16:10:32.244779: Epoch 1012 +2024-11-21 16:10:32.244896: Current learning rate: 0.00885 +2024-11-21 16:10:51.613367: train_loss -0.7775 +2024-11-21 16:10:51.613572: val_loss -0.7308 +2024-11-21 16:10:51.613643: Pseudo dice [0.8474] +2024-11-21 16:10:51.613719: Epoch time: 19.37 s +2024-11-21 16:10:52.563747: +2024-11-21 16:10:52.563933: Epoch 1013 +2024-11-21 16:10:52.564053: Current learning rate: 0.00885 +2024-11-21 16:11:09.719516: train_loss -0.7686 +2024-11-21 16:11:09.719795: val_loss -0.742 +2024-11-21 16:11:09.719870: Pseudo dice [0.8424] +2024-11-21 16:11:09.719959: Epoch time: 17.15 s +2024-11-21 16:11:10.538470: +2024-11-21 16:11:10.538657: Epoch 1014 +2024-11-21 16:11:10.538773: Current learning rate: 0.00885 +2024-11-21 16:11:29.573260: train_loss -0.7633 +2024-11-21 16:11:29.575427: val_loss -0.7156 +2024-11-21 16:11:29.577435: Pseudo dice [0.7843] +2024-11-21 16:11:29.577533: Epoch time: 19.04 s +2024-11-21 16:11:30.793608: +2024-11-21 16:11:30.793885: Epoch 1015 +2024-11-21 16:11:30.794006: Current learning rate: 0.00885 +2024-11-21 16:11:49.683088: train_loss -0.7475 +2024-11-21 16:11:49.683386: val_loss -0.6982 +2024-11-21 16:11:49.683467: Pseudo dice [0.8369] +2024-11-21 16:11:49.683545: Epoch time: 18.89 s +2024-11-21 16:11:50.503632: +2024-11-21 16:11:50.503868: Epoch 1016 +2024-11-21 16:11:50.503982: Current learning rate: 0.00885 +2024-11-21 16:12:08.735231: train_loss -0.756 +2024-11-21 16:12:08.735475: val_loss -0.7066 +2024-11-21 16:12:08.735552: Pseudo dice [0.8509] +2024-11-21 16:12:08.735701: Epoch time: 18.23 s +2024-11-21 16:12:09.556231: +2024-11-21 16:12:09.556445: Epoch 1017 +2024-11-21 16:12:09.556560: Current learning rate: 0.00885 +2024-11-21 16:12:27.693527: train_loss -0.7738 +2024-11-21 16:12:27.693752: val_loss -0.7304 +2024-11-21 16:12:27.693831: Pseudo dice [0.8209] +2024-11-21 16:12:27.693908: Epoch time: 18.14 s +2024-11-21 16:12:28.660701: +2024-11-21 16:12:28.660905: Epoch 1018 +2024-11-21 16:12:28.661030: Current learning rate: 0.00885 +2024-11-21 16:12:47.656101: train_loss -0.7627 +2024-11-21 16:12:47.656319: val_loss -0.7256 +2024-11-21 16:12:47.656397: Pseudo dice [0.842] +2024-11-21 16:12:47.656475: Epoch time: 19.0 s +2024-11-21 16:12:48.512481: +2024-11-21 16:12:48.512688: Epoch 1019 +2024-11-21 16:12:48.512802: Current learning rate: 0.00885 +2024-11-21 16:13:07.161643: train_loss -0.7659 +2024-11-21 16:13:07.161855: val_loss -0.7273 +2024-11-21 16:13:07.161934: Pseudo dice [0.8531] +2024-11-21 16:13:07.162017: Epoch time: 18.65 s +2024-11-21 16:13:07.988392: +2024-11-21 16:13:07.988698: Epoch 1020 +2024-11-21 16:13:07.988810: Current learning rate: 0.00884 +2024-11-21 16:13:26.497858: train_loss -0.7678 +2024-11-21 16:13:26.498129: val_loss -0.7306 +2024-11-21 16:13:26.498205: Pseudo dice [0.8184] +2024-11-21 16:13:26.498352: Epoch time: 18.51 s +2024-11-21 16:13:27.324412: +2024-11-21 16:13:27.324605: Epoch 1021 +2024-11-21 16:13:27.324717: Current learning rate: 0.00884 +2024-11-21 16:13:46.449972: train_loss -0.7715 +2024-11-21 16:13:46.450193: val_loss -0.7311 +2024-11-21 16:13:46.450265: Pseudo dice [0.8309] +2024-11-21 16:13:46.450339: Epoch time: 19.13 s +2024-11-21 16:13:47.319140: +2024-11-21 16:13:47.319347: Epoch 1022 +2024-11-21 16:13:47.319487: Current learning rate: 0.00884 +2024-11-21 16:14:06.167916: train_loss -0.7633 +2024-11-21 16:14:06.168133: val_loss -0.774 +2024-11-21 16:14:06.168205: Pseudo dice [0.8636] +2024-11-21 16:14:06.168284: Epoch time: 18.85 s +2024-11-21 16:14:06.987302: +2024-11-21 16:14:06.987514: Epoch 1023 +2024-11-21 16:14:06.987626: Current learning rate: 0.00884 +2024-11-21 16:14:25.767196: train_loss -0.7586 +2024-11-21 16:14:25.767411: val_loss -0.7113 +2024-11-21 16:14:25.767487: Pseudo dice [0.8372] +2024-11-21 16:14:25.767571: Epoch time: 18.78 s +2024-11-21 16:14:26.588736: +2024-11-21 16:14:26.588989: Epoch 1024 +2024-11-21 16:14:26.589104: Current learning rate: 0.00884 +2024-11-21 16:14:44.738600: train_loss -0.77 +2024-11-21 16:14:44.738890: val_loss -0.7386 +2024-11-21 16:14:44.738977: Pseudo dice [0.8471] +2024-11-21 16:14:44.739069: Epoch time: 18.15 s +2024-11-21 16:14:45.555790: +2024-11-21 16:14:45.556057: Epoch 1025 +2024-11-21 16:14:45.556173: Current learning rate: 0.00884 +2024-11-21 16:15:04.227733: train_loss -0.77 +2024-11-21 16:15:04.227943: val_loss -0.7423 +2024-11-21 16:15:04.228024: Pseudo dice [0.8389] +2024-11-21 16:15:04.228100: Epoch time: 18.67 s +2024-11-21 16:15:05.049241: +2024-11-21 16:15:05.049598: Epoch 1026 +2024-11-21 16:15:05.049719: Current learning rate: 0.00884 +2024-11-21 16:15:24.509238: train_loss -0.7408 +2024-11-21 16:15:24.509471: val_loss -0.7474 +2024-11-21 16:15:24.509548: Pseudo dice [0.8262] +2024-11-21 16:15:24.509628: Epoch time: 19.46 s +2024-11-21 16:15:25.334691: +2024-11-21 16:15:25.334921: Epoch 1027 +2024-11-21 16:15:25.335041: Current learning rate: 0.00884 +2024-11-21 16:15:44.061786: train_loss -0.7651 +2024-11-21 16:15:44.062057: val_loss -0.755 +2024-11-21 16:15:44.062138: Pseudo dice [0.8248] +2024-11-21 16:15:44.062224: Epoch time: 18.73 s +2024-11-21 16:15:44.885143: +2024-11-21 16:15:44.885529: Epoch 1028 +2024-11-21 16:15:44.885649: Current learning rate: 0.00884 +2024-11-21 16:16:02.987229: train_loss -0.7635 +2024-11-21 16:16:02.987447: val_loss -0.7428 +2024-11-21 16:16:02.987522: Pseudo dice [0.8221] +2024-11-21 16:16:02.987621: Epoch time: 18.1 s +2024-11-21 16:16:03.811449: +2024-11-21 16:16:03.811691: Epoch 1029 +2024-11-21 16:16:03.811812: Current learning rate: 0.00883 +2024-11-21 16:16:22.087086: train_loss -0.7722 +2024-11-21 16:16:22.087309: val_loss -0.7482 +2024-11-21 16:16:22.087384: Pseudo dice [0.859] +2024-11-21 16:16:22.087468: Epoch time: 18.28 s +2024-11-21 16:16:23.067714: +2024-11-21 16:16:23.067957: Epoch 1030 +2024-11-21 16:16:23.068083: Current learning rate: 0.00883 +2024-11-21 16:16:40.830686: train_loss -0.752 +2024-11-21 16:16:40.830930: val_loss -0.7473 +2024-11-21 16:16:40.831008: Pseudo dice [0.8394] +2024-11-21 16:16:40.831108: Epoch time: 17.76 s +2024-11-21 16:16:41.655139: +2024-11-21 16:16:41.655362: Epoch 1031 +2024-11-21 16:16:41.655473: Current learning rate: 0.00883 +2024-11-21 16:17:00.766503: train_loss -0.7573 +2024-11-21 16:17:00.766717: val_loss -0.7179 +2024-11-21 16:17:00.766815: Pseudo dice [0.8323] +2024-11-21 16:17:00.766895: Epoch time: 19.11 s +2024-11-21 16:17:01.589862: +2024-11-21 16:17:01.590114: Epoch 1032 +2024-11-21 16:17:01.590231: Current learning rate: 0.00883 +2024-11-21 16:17:20.428315: train_loss -0.7729 +2024-11-21 16:17:20.428522: val_loss -0.7324 +2024-11-21 16:17:20.428594: Pseudo dice [0.8093] +2024-11-21 16:17:20.428670: Epoch time: 18.84 s +2024-11-21 16:17:21.248623: +2024-11-21 16:17:21.248856: Epoch 1033 +2024-11-21 16:17:21.248970: Current learning rate: 0.00883 +2024-11-21 16:17:38.825484: train_loss -0.7767 +2024-11-21 16:17:38.825769: val_loss -0.7474 +2024-11-21 16:17:38.825847: Pseudo dice [0.8236] +2024-11-21 16:17:38.825926: Epoch time: 17.58 s +2024-11-21 16:17:39.656806: +2024-11-21 16:17:39.657047: Epoch 1034 +2024-11-21 16:17:39.657157: Current learning rate: 0.00883 +2024-11-21 16:17:58.245611: train_loss -0.7675 +2024-11-21 16:17:58.245841: val_loss -0.7704 +2024-11-21 16:17:58.245915: Pseudo dice [0.8297] +2024-11-21 16:17:58.246003: Epoch time: 18.59 s +2024-11-21 16:17:59.067169: +2024-11-21 16:17:59.067415: Epoch 1035 +2024-11-21 16:17:59.067532: Current learning rate: 0.00883 +2024-11-21 16:18:17.615828: train_loss -0.7734 +2024-11-21 16:18:17.616056: val_loss -0.7364 +2024-11-21 16:18:17.616160: Pseudo dice [0.8352] +2024-11-21 16:18:17.616239: Epoch time: 18.55 s +2024-11-21 16:18:18.439151: +2024-11-21 16:18:18.439384: Epoch 1036 +2024-11-21 16:18:18.439501: Current learning rate: 0.00883 +2024-11-21 16:18:38.503750: train_loss -0.7719 +2024-11-21 16:18:38.503968: val_loss -0.7505 +2024-11-21 16:18:38.504047: Pseudo dice [0.8569] +2024-11-21 16:18:38.504123: Epoch time: 20.07 s +2024-11-21 16:18:39.321817: +2024-11-21 16:18:39.322108: Epoch 1037 +2024-11-21 16:18:39.322218: Current learning rate: 0.00883 +2024-11-21 16:18:58.336121: train_loss -0.7685 +2024-11-21 16:18:58.336379: val_loss -0.7367 +2024-11-21 16:18:58.336462: Pseudo dice [0.8303] +2024-11-21 16:18:58.336559: Epoch time: 19.02 s +2024-11-21 16:18:59.546101: +2024-11-21 16:18:59.546326: Epoch 1038 +2024-11-21 16:18:59.546434: Current learning rate: 0.00882 +2024-11-21 16:19:18.326806: train_loss -0.7807 +2024-11-21 16:19:18.327027: val_loss -0.7383 +2024-11-21 16:19:18.327103: Pseudo dice [0.8297] +2024-11-21 16:19:18.327181: Epoch time: 18.78 s +2024-11-21 16:19:19.151944: +2024-11-21 16:19:19.152212: Epoch 1039 +2024-11-21 16:19:19.152329: Current learning rate: 0.00882 +2024-11-21 16:19:37.342287: train_loss -0.7643 +2024-11-21 16:19:37.342507: val_loss -0.7329 +2024-11-21 16:19:37.344828: Pseudo dice [0.8566] +2024-11-21 16:19:37.344945: Epoch time: 18.19 s +2024-11-21 16:19:38.280257: +2024-11-21 16:19:38.280499: Epoch 1040 +2024-11-21 16:19:38.280613: Current learning rate: 0.00882 +2024-11-21 16:19:57.159381: train_loss -0.7632 +2024-11-21 16:19:57.159624: val_loss -0.7341 +2024-11-21 16:19:57.159700: Pseudo dice [0.838] +2024-11-21 16:19:57.159787: Epoch time: 18.88 s +2024-11-21 16:19:57.984931: +2024-11-21 16:19:57.985127: Epoch 1041 +2024-11-21 16:19:57.985233: Current learning rate: 0.00882 +2024-11-21 16:20:16.287844: train_loss -0.7596 +2024-11-21 16:20:16.288071: val_loss -0.7154 +2024-11-21 16:20:16.288147: Pseudo dice [0.8291] +2024-11-21 16:20:16.288224: Epoch time: 18.3 s +2024-11-21 16:20:17.107405: +2024-11-21 16:20:17.107631: Epoch 1042 +2024-11-21 16:20:17.107744: Current learning rate: 0.00882 +2024-11-21 16:20:36.216343: train_loss -0.7698 +2024-11-21 16:20:36.216567: val_loss -0.7445 +2024-11-21 16:20:36.216650: Pseudo dice [0.8423] +2024-11-21 16:20:36.216725: Epoch time: 19.11 s +2024-11-21 16:20:37.077898: +2024-11-21 16:20:37.078125: Epoch 1043 +2024-11-21 16:20:37.078235: Current learning rate: 0.00882 +2024-11-21 16:20:55.763748: train_loss -0.7574 +2024-11-21 16:20:55.763969: val_loss -0.7429 +2024-11-21 16:20:55.764051: Pseudo dice [0.8416] +2024-11-21 16:20:55.764128: Epoch time: 18.69 s +2024-11-21 16:20:56.595827: +2024-11-21 16:20:56.596072: Epoch 1044 +2024-11-21 16:20:56.596195: Current learning rate: 0.00882 +2024-11-21 16:21:15.188509: train_loss -0.7759 +2024-11-21 16:21:15.188787: val_loss -0.758 +2024-11-21 16:21:15.188863: Pseudo dice [0.8489] +2024-11-21 16:21:15.188940: Epoch time: 18.59 s +2024-11-21 16:21:16.013995: +2024-11-21 16:21:16.014229: Epoch 1045 +2024-11-21 16:21:16.014348: Current learning rate: 0.00882 +2024-11-21 16:21:34.787869: train_loss -0.7721 +2024-11-21 16:21:34.788112: val_loss -0.7426 +2024-11-21 16:21:34.788189: Pseudo dice [0.8483] +2024-11-21 16:21:34.788263: Epoch time: 18.77 s +2024-11-21 16:21:35.607001: +2024-11-21 16:21:35.607348: Epoch 1046 +2024-11-21 16:21:35.607460: Current learning rate: 0.00882 +2024-11-21 16:21:54.169345: train_loss -0.7577 +2024-11-21 16:21:54.169559: val_loss -0.7446 +2024-11-21 16:21:54.169633: Pseudo dice [0.8276] +2024-11-21 16:21:54.169709: Epoch time: 18.56 s +2024-11-21 16:21:55.213424: +2024-11-21 16:21:55.213615: Epoch 1047 +2024-11-21 16:21:55.213725: Current learning rate: 0.00881 +2024-11-21 16:22:13.493359: train_loss -0.7717 +2024-11-21 16:22:13.493629: val_loss -0.7415 +2024-11-21 16:22:13.493706: Pseudo dice [0.8323] +2024-11-21 16:22:13.493790: Epoch time: 18.28 s +2024-11-21 16:22:14.322641: +2024-11-21 16:22:14.322844: Epoch 1048 +2024-11-21 16:22:14.322954: Current learning rate: 0.00881 +2024-11-21 16:22:33.420258: train_loss -0.7777 +2024-11-21 16:22:33.420479: val_loss -0.7711 +2024-11-21 16:22:33.420553: Pseudo dice [0.8377] +2024-11-21 16:22:33.420629: Epoch time: 19.1 s +2024-11-21 16:22:34.391859: +2024-11-21 16:22:34.392066: Epoch 1049 +2024-11-21 16:22:34.392176: Current learning rate: 0.00881 +2024-11-21 16:22:53.676279: train_loss -0.7602 +2024-11-21 16:22:53.676534: val_loss -0.732 +2024-11-21 16:22:53.676608: Pseudo dice [0.8467] +2024-11-21 16:22:53.676682: Epoch time: 19.29 s +2024-11-21 16:22:54.765390: +2024-11-21 16:22:54.765817: Epoch 1050 +2024-11-21 16:22:54.765949: Current learning rate: 0.00881 +2024-11-21 16:23:13.508576: train_loss -0.7594 +2024-11-21 16:23:13.508795: val_loss -0.7459 +2024-11-21 16:23:13.508869: Pseudo dice [0.8331] +2024-11-21 16:23:13.508950: Epoch time: 18.74 s +2024-11-21 16:23:14.332240: +2024-11-21 16:23:14.332688: Epoch 1051 +2024-11-21 16:23:14.332859: Current learning rate: 0.00881 +2024-11-21 16:23:34.381945: train_loss -0.7656 +2024-11-21 16:23:34.382165: val_loss -0.7378 +2024-11-21 16:23:34.382237: Pseudo dice [0.8424] +2024-11-21 16:23:34.382316: Epoch time: 20.05 s +2024-11-21 16:23:35.201595: +2024-11-21 16:23:35.202024: Epoch 1052 +2024-11-21 16:23:35.202161: Current learning rate: 0.00881 +2024-11-21 16:23:54.810777: train_loss -0.7693 +2024-11-21 16:23:54.811001: val_loss -0.7428 +2024-11-21 16:23:54.811076: Pseudo dice [0.8047] +2024-11-21 16:23:54.811153: Epoch time: 19.61 s +2024-11-21 16:23:55.631632: +2024-11-21 16:23:55.632065: Epoch 1053 +2024-11-21 16:23:55.632201: Current learning rate: 0.00881 +2024-11-21 16:24:14.316788: train_loss -0.763 +2024-11-21 16:24:14.317038: val_loss -0.7329 +2024-11-21 16:24:14.317118: Pseudo dice [0.8222] +2024-11-21 16:24:14.317199: Epoch time: 18.69 s +2024-11-21 16:24:15.139487: +2024-11-21 16:24:15.139942: Epoch 1054 +2024-11-21 16:24:15.140110: Current learning rate: 0.00881 +2024-11-21 16:24:34.996039: train_loss -0.7655 +2024-11-21 16:24:34.996284: val_loss -0.7499 +2024-11-21 16:24:34.996362: Pseudo dice [0.8202] +2024-11-21 16:24:34.996440: Epoch time: 19.86 s +2024-11-21 16:24:35.819906: +2024-11-21 16:24:35.820346: Epoch 1055 +2024-11-21 16:24:35.820497: Current learning rate: 0.0088 +2024-11-21 16:24:54.145843: train_loss -0.765 +2024-11-21 16:24:54.146102: val_loss -0.7396 +2024-11-21 16:24:54.146178: Pseudo dice [0.8257] +2024-11-21 16:24:54.146255: Epoch time: 18.33 s +2024-11-21 16:24:54.966578: +2024-11-21 16:24:54.967004: Epoch 1056 +2024-11-21 16:24:54.967144: Current learning rate: 0.0088 +2024-11-21 16:25:14.345784: train_loss -0.7624 +2024-11-21 16:25:14.346012: val_loss -0.7247 +2024-11-21 16:25:14.346094: Pseudo dice [0.812] +2024-11-21 16:25:14.351357: Epoch time: 19.38 s +2024-11-21 16:25:15.249058: +2024-11-21 16:25:15.249463: Epoch 1057 +2024-11-21 16:25:15.249602: Current learning rate: 0.0088 +2024-11-21 16:25:34.158297: train_loss -0.76 +2024-11-21 16:25:34.158513: val_loss -0.7251 +2024-11-21 16:25:34.158592: Pseudo dice [0.822] +2024-11-21 16:25:34.158673: Epoch time: 18.91 s +2024-11-21 16:25:34.986636: +2024-11-21 16:25:34.987071: Epoch 1058 +2024-11-21 16:25:34.987205: Current learning rate: 0.0088 +2024-11-21 16:25:54.152461: train_loss -0.7619 +2024-11-21 16:25:54.152675: val_loss -0.7496 +2024-11-21 16:25:54.152761: Pseudo dice [0.8513] +2024-11-21 16:25:54.152902: Epoch time: 19.17 s +2024-11-21 16:25:54.975414: +2024-11-21 16:25:54.975806: Epoch 1059 +2024-11-21 16:25:54.975937: Current learning rate: 0.0088 +2024-11-21 16:26:13.515162: train_loss -0.7695 +2024-11-21 16:26:13.515394: val_loss -0.7169 +2024-11-21 16:26:13.515473: Pseudo dice [0.8294] +2024-11-21 16:26:13.515555: Epoch time: 18.54 s +2024-11-21 16:26:14.364329: +2024-11-21 16:26:14.364745: Epoch 1060 +2024-11-21 16:26:14.364883: Current learning rate: 0.0088 +2024-11-21 16:26:32.889642: train_loss -0.7606 +2024-11-21 16:26:32.889865: val_loss -0.7255 +2024-11-21 16:26:32.889937: Pseudo dice [0.8542] +2024-11-21 16:26:32.890023: Epoch time: 18.53 s +2024-11-21 16:26:34.110806: +2024-11-21 16:26:34.111247: Epoch 1061 +2024-11-21 16:26:34.111376: Current learning rate: 0.0088 +2024-11-21 16:26:53.027907: train_loss -0.7675 +2024-11-21 16:26:53.028156: val_loss -0.7512 +2024-11-21 16:26:53.028232: Pseudo dice [0.841] +2024-11-21 16:26:53.028322: Epoch time: 18.92 s +2024-11-21 16:26:53.842214: +2024-11-21 16:26:53.842725: Epoch 1062 +2024-11-21 16:26:53.842860: Current learning rate: 0.0088 +2024-11-21 16:27:12.500649: train_loss -0.7645 +2024-11-21 16:27:12.500864: val_loss -0.7518 +2024-11-21 16:27:12.500940: Pseudo dice [0.8094] +2024-11-21 16:27:12.501022: Epoch time: 18.66 s +2024-11-21 16:27:13.315711: +2024-11-21 16:27:13.316161: Epoch 1063 +2024-11-21 16:27:13.316296: Current learning rate: 0.0088 +2024-11-21 16:27:32.159088: train_loss -0.767 +2024-11-21 16:27:32.159303: val_loss -0.7602 +2024-11-21 16:27:32.159379: Pseudo dice [0.8296] +2024-11-21 16:27:32.159457: Epoch time: 18.84 s +2024-11-21 16:27:33.077927: +2024-11-21 16:27:33.078361: Epoch 1064 +2024-11-21 16:27:33.078501: Current learning rate: 0.00879 +2024-11-21 16:27:52.349117: train_loss -0.7427 +2024-11-21 16:27:52.351128: val_loss -0.7339 +2024-11-21 16:27:52.351220: Pseudo dice [0.827] +2024-11-21 16:27:52.351308: Epoch time: 19.27 s +2024-11-21 16:27:53.209096: +2024-11-21 16:27:53.209510: Epoch 1065 +2024-11-21 16:27:53.209646: Current learning rate: 0.00879 +2024-11-21 16:28:11.958724: train_loss -0.7395 +2024-11-21 16:28:11.958980: val_loss -0.7467 +2024-11-21 16:28:11.959075: Pseudo dice [0.8421] +2024-11-21 16:28:11.959159: Epoch time: 18.75 s +2024-11-21 16:28:12.778123: +2024-11-21 16:28:12.778647: Epoch 1066 +2024-11-21 16:28:12.778785: Current learning rate: 0.00879 +2024-11-21 16:28:30.819894: train_loss -0.752 +2024-11-21 16:28:30.820120: val_loss -0.7485 +2024-11-21 16:28:30.820201: Pseudo dice [0.8207] +2024-11-21 16:28:30.820283: Epoch time: 18.04 s +2024-11-21 16:28:31.642044: +2024-11-21 16:28:31.642507: Epoch 1067 +2024-11-21 16:28:31.642650: Current learning rate: 0.00879 +2024-11-21 16:28:50.586576: train_loss -0.7552 +2024-11-21 16:28:50.589049: val_loss -0.7371 +2024-11-21 16:28:50.589144: Pseudo dice [0.8247] +2024-11-21 16:28:50.589223: Epoch time: 18.95 s +2024-11-21 16:28:51.446508: +2024-11-21 16:28:51.446954: Epoch 1068 +2024-11-21 16:28:51.447096: Current learning rate: 0.00879 +2024-11-21 16:29:10.435467: train_loss -0.7614 +2024-11-21 16:29:10.435723: val_loss -0.7218 +2024-11-21 16:29:10.435799: Pseudo dice [0.8321] +2024-11-21 16:29:10.435888: Epoch time: 18.99 s +2024-11-21 16:29:11.257250: +2024-11-21 16:29:11.257702: Epoch 1069 +2024-11-21 16:29:11.257838: Current learning rate: 0.00879 +2024-11-21 16:29:29.689267: train_loss -0.7564 +2024-11-21 16:29:29.689485: val_loss -0.7067 +2024-11-21 16:29:29.689564: Pseudo dice [0.8358] +2024-11-21 16:29:29.689669: Epoch time: 18.43 s +2024-11-21 16:29:30.509848: +2024-11-21 16:29:30.510305: Epoch 1070 +2024-11-21 16:29:30.510441: Current learning rate: 0.00879 +2024-11-21 16:29:48.542192: train_loss -0.7611 +2024-11-21 16:29:48.542401: val_loss -0.7381 +2024-11-21 16:29:48.542482: Pseudo dice [0.8234] +2024-11-21 16:29:48.542559: Epoch time: 18.03 s +2024-11-21 16:29:49.356058: +2024-11-21 16:29:49.356504: Epoch 1071 +2024-11-21 16:29:49.356656: Current learning rate: 0.00879 +2024-11-21 16:30:07.079500: train_loss -0.7635 +2024-11-21 16:30:07.079739: val_loss -0.7196 +2024-11-21 16:30:07.079815: Pseudo dice [0.8475] +2024-11-21 16:30:07.079896: Epoch time: 17.72 s +2024-11-21 16:30:07.903410: +2024-11-21 16:30:07.903738: Epoch 1072 +2024-11-21 16:30:07.903847: Current learning rate: 0.00879 +2024-11-21 16:30:27.166821: train_loss -0.7424 +2024-11-21 16:30:27.167056: val_loss -0.7608 +2024-11-21 16:30:27.167136: Pseudo dice [0.8609] +2024-11-21 16:30:27.167216: Epoch time: 19.26 s +2024-11-21 16:30:27.983847: +2024-11-21 16:30:27.984085: Epoch 1073 +2024-11-21 16:30:27.984199: Current learning rate: 0.00878 +2024-11-21 16:30:47.037414: train_loss -0.7482 +2024-11-21 16:30:47.037631: val_loss -0.7269 +2024-11-21 16:30:47.037706: Pseudo dice [0.8262] +2024-11-21 16:30:47.037784: Epoch time: 19.05 s +2024-11-21 16:30:47.863299: +2024-11-21 16:30:47.863502: Epoch 1074 +2024-11-21 16:30:47.863615: Current learning rate: 0.00878 +2024-11-21 16:31:06.345063: train_loss -0.7563 +2024-11-21 16:31:06.345390: val_loss -0.7283 +2024-11-21 16:31:06.345469: Pseudo dice [0.8197] +2024-11-21 16:31:06.345551: Epoch time: 18.48 s +2024-11-21 16:31:07.170374: +2024-11-21 16:31:07.170589: Epoch 1075 +2024-11-21 16:31:07.170702: Current learning rate: 0.00878 +2024-11-21 16:31:26.784807: train_loss -0.7434 +2024-11-21 16:31:26.785031: val_loss -0.7253 +2024-11-21 16:31:26.785108: Pseudo dice [0.8314] +2024-11-21 16:31:26.785186: Epoch time: 19.62 s +2024-11-21 16:31:27.604733: +2024-11-21 16:31:27.604962: Epoch 1076 +2024-11-21 16:31:27.605081: Current learning rate: 0.00878 +2024-11-21 16:31:45.297005: train_loss -0.7619 +2024-11-21 16:31:45.299349: val_loss -0.7163 +2024-11-21 16:31:45.299437: Pseudo dice [0.8233] +2024-11-21 16:31:45.299553: Epoch time: 17.69 s +2024-11-21 16:31:46.165305: +2024-11-21 16:31:46.165526: Epoch 1077 +2024-11-21 16:31:46.165636: Current learning rate: 0.00878 +2024-11-21 16:32:05.644763: train_loss -0.7607 +2024-11-21 16:32:05.644985: val_loss -0.7162 +2024-11-21 16:32:05.645069: Pseudo dice [0.8257] +2024-11-21 16:32:05.645147: Epoch time: 19.48 s +2024-11-21 16:32:06.534571: +2024-11-21 16:32:06.534795: Epoch 1078 +2024-11-21 16:32:06.534907: Current learning rate: 0.00878 +2024-11-21 16:32:24.997187: train_loss -0.7639 +2024-11-21 16:32:24.997442: val_loss -0.7402 +2024-11-21 16:32:24.997518: Pseudo dice [0.8242] +2024-11-21 16:32:24.998312: Epoch time: 18.46 s +2024-11-21 16:32:25.986588: +2024-11-21 16:32:25.986804: Epoch 1079 +2024-11-21 16:32:25.986917: Current learning rate: 0.00878 +2024-11-21 16:32:44.419073: train_loss -0.7554 +2024-11-21 16:32:44.419278: val_loss -0.7395 +2024-11-21 16:32:44.419353: Pseudo dice [0.8181] +2024-11-21 16:32:44.419428: Epoch time: 18.43 s +2024-11-21 16:32:45.249460: +2024-11-21 16:32:45.249655: Epoch 1080 +2024-11-21 16:32:45.249765: Current learning rate: 0.00878 +2024-11-21 16:33:03.208143: train_loss -0.7556 +2024-11-21 16:33:03.208360: val_loss -0.6971 +2024-11-21 16:33:03.208434: Pseudo dice [0.8195] +2024-11-21 16:33:03.208511: Epoch time: 17.96 s +2024-11-21 16:33:04.023565: +2024-11-21 16:33:04.023845: Epoch 1081 +2024-11-21 16:33:04.023959: Current learning rate: 0.00878 +2024-11-21 16:33:23.106914: train_loss -0.7453 +2024-11-21 16:33:23.107143: val_loss -0.7495 +2024-11-21 16:33:23.107219: Pseudo dice [0.8396] +2024-11-21 16:33:23.107297: Epoch time: 19.08 s +2024-11-21 16:33:23.926021: +2024-11-21 16:33:23.926227: Epoch 1082 +2024-11-21 16:33:23.926346: Current learning rate: 0.00877 +2024-11-21 16:33:42.334009: train_loss -0.7285 +2024-11-21 16:33:42.334242: val_loss -0.7323 +2024-11-21 16:33:42.336528: Pseudo dice [0.8285] +2024-11-21 16:33:42.336641: Epoch time: 18.41 s +2024-11-21 16:33:43.207847: +2024-11-21 16:33:43.208036: Epoch 1083 +2024-11-21 16:33:43.208145: Current learning rate: 0.00877 +2024-11-21 16:34:01.899037: train_loss -0.76 +2024-11-21 16:34:01.899252: val_loss -0.7415 +2024-11-21 16:34:01.899328: Pseudo dice [0.8435] +2024-11-21 16:34:01.899404: Epoch time: 18.69 s +2024-11-21 16:34:03.136815: +2024-11-21 16:34:03.137227: Epoch 1084 +2024-11-21 16:34:03.137338: Current learning rate: 0.00877 +2024-11-21 16:34:21.562069: train_loss -0.7551 +2024-11-21 16:34:21.562290: val_loss -0.7192 +2024-11-21 16:34:21.562364: Pseudo dice [0.818] +2024-11-21 16:34:21.562443: Epoch time: 18.43 s +2024-11-21 16:34:22.368011: +2024-11-21 16:34:22.368227: Epoch 1085 +2024-11-21 16:34:22.368337: Current learning rate: 0.00877 +2024-11-21 16:34:40.877578: train_loss -0.7643 +2024-11-21 16:34:40.877824: val_loss -0.7485 +2024-11-21 16:34:40.877899: Pseudo dice [0.8393] +2024-11-21 16:34:40.883183: Epoch time: 18.51 s +2024-11-21 16:34:41.858464: +2024-11-21 16:34:41.858678: Epoch 1086 +2024-11-21 16:34:41.858788: Current learning rate: 0.00877 +2024-11-21 16:34:59.647229: train_loss -0.7761 +2024-11-21 16:34:59.647434: val_loss -0.7518 +2024-11-21 16:34:59.647508: Pseudo dice [0.8385] +2024-11-21 16:34:59.647584: Epoch time: 17.79 s +2024-11-21 16:35:00.466237: +2024-11-21 16:35:00.466455: Epoch 1087 +2024-11-21 16:35:00.466570: Current learning rate: 0.00877 +2024-11-21 16:35:18.089538: train_loss -0.7679 +2024-11-21 16:35:18.089778: val_loss -0.7411 +2024-11-21 16:35:18.089856: Pseudo dice [0.8329] +2024-11-21 16:35:18.089943: Epoch time: 17.62 s +2024-11-21 16:35:18.933002: +2024-11-21 16:35:18.933220: Epoch 1088 +2024-11-21 16:35:18.933329: Current learning rate: 0.00877 +2024-11-21 16:35:38.028787: train_loss -0.7588 +2024-11-21 16:35:38.029005: val_loss -0.7138 +2024-11-21 16:35:38.029079: Pseudo dice [0.8248] +2024-11-21 16:35:38.029155: Epoch time: 19.1 s +2024-11-21 16:35:38.860502: +2024-11-21 16:35:38.860717: Epoch 1089 +2024-11-21 16:35:38.860828: Current learning rate: 0.00877 +2024-11-21 16:35:57.436416: train_loss -0.7541 +2024-11-21 16:35:57.436657: val_loss -0.7403 +2024-11-21 16:35:57.436736: Pseudo dice [0.8448] +2024-11-21 16:35:57.436818: Epoch time: 18.58 s +2024-11-21 16:35:58.365194: +2024-11-21 16:35:58.365418: Epoch 1090 +2024-11-21 16:35:58.365536: Current learning rate: 0.00876 +2024-11-21 16:36:16.318391: train_loss -0.7657 +2024-11-21 16:36:16.318668: val_loss -0.7551 +2024-11-21 16:36:16.318747: Pseudo dice [0.8745] +2024-11-21 16:36:16.318823: Epoch time: 17.95 s +2024-11-21 16:36:17.137469: +2024-11-21 16:36:17.137704: Epoch 1091 +2024-11-21 16:36:17.137818: Current learning rate: 0.00876 +2024-11-21 16:36:35.546692: train_loss -0.7539 +2024-11-21 16:36:35.546909: val_loss -0.7645 +2024-11-21 16:36:35.546987: Pseudo dice [0.8553] +2024-11-21 16:36:35.547070: Epoch time: 18.41 s +2024-11-21 16:36:36.367289: +2024-11-21 16:36:36.367476: Epoch 1092 +2024-11-21 16:36:36.367591: Current learning rate: 0.00876 +2024-11-21 16:36:55.013194: train_loss -0.7574 +2024-11-21 16:36:55.013428: val_loss -0.7106 +2024-11-21 16:36:55.013509: Pseudo dice [0.8254] +2024-11-21 16:36:55.013605: Epoch time: 18.65 s +2024-11-21 16:36:55.840229: +2024-11-21 16:36:55.840413: Epoch 1093 +2024-11-21 16:36:55.840543: Current learning rate: 0.00876 +2024-11-21 16:37:14.052852: train_loss -0.7773 +2024-11-21 16:37:14.053092: val_loss -0.7416 +2024-11-21 16:37:14.053165: Pseudo dice [0.8392] +2024-11-21 16:37:14.053243: Epoch time: 18.21 s +2024-11-21 16:37:14.874562: +2024-11-21 16:37:14.874794: Epoch 1094 +2024-11-21 16:37:14.874912: Current learning rate: 0.00876 +2024-11-21 16:37:32.269900: train_loss -0.7719 +2024-11-21 16:37:32.272252: val_loss -0.7403 +2024-11-21 16:37:32.272348: Pseudo dice [0.824] +2024-11-21 16:37:32.272423: Epoch time: 17.4 s +2024-11-21 16:37:33.086868: +2024-11-21 16:37:33.087342: Epoch 1095 +2024-11-21 16:37:33.087481: Current learning rate: 0.00876 +2024-11-21 16:37:52.699338: train_loss -0.7655 +2024-11-21 16:37:52.699572: val_loss -0.7277 +2024-11-21 16:37:52.699648: Pseudo dice [0.843] +2024-11-21 16:37:52.701814: Epoch time: 19.61 s +2024-11-21 16:37:53.659236: +2024-11-21 16:37:53.659687: Epoch 1096 +2024-11-21 16:37:53.659820: Current learning rate: 0.00876 +2024-11-21 16:38:11.669940: train_loss -0.7733 +2024-11-21 16:38:11.670187: val_loss -0.7379 +2024-11-21 16:38:11.670265: Pseudo dice [0.8343] +2024-11-21 16:38:11.670347: Epoch time: 18.01 s +2024-11-21 16:38:12.481321: +2024-11-21 16:38:12.481777: Epoch 1097 +2024-11-21 16:38:12.484008: Current learning rate: 0.00876 +2024-11-21 16:38:30.560002: train_loss -0.7702 +2024-11-21 16:38:30.561021: val_loss -0.7218 +2024-11-21 16:38:30.561101: Pseudo dice [0.8416] +2024-11-21 16:38:30.561193: Epoch time: 18.08 s +2024-11-21 16:38:31.381687: +2024-11-21 16:38:31.382135: Epoch 1098 +2024-11-21 16:38:31.382266: Current learning rate: 0.00876 +2024-11-21 16:38:50.638716: train_loss -0.7712 +2024-11-21 16:38:50.638940: val_loss -0.6955 +2024-11-21 16:38:50.639025: Pseudo dice [0.8117] +2024-11-21 16:38:50.639103: Epoch time: 19.26 s +2024-11-21 16:38:51.640452: +2024-11-21 16:38:51.640861: Epoch 1099 +2024-11-21 16:38:51.640998: Current learning rate: 0.00875 +2024-11-21 16:39:10.563754: train_loss -0.7814 +2024-11-21 16:39:10.568275: val_loss -0.7452 +2024-11-21 16:39:10.568351: Pseudo dice [0.8477] +2024-11-21 16:39:10.568437: Epoch time: 18.92 s +2024-11-21 16:39:11.662423: +2024-11-21 16:39:11.662845: Epoch 1100 +2024-11-21 16:39:11.662974: Current learning rate: 0.00875 +2024-11-21 16:39:30.973639: train_loss -0.7643 +2024-11-21 16:39:30.973845: val_loss -0.7391 +2024-11-21 16:39:30.973921: Pseudo dice [0.8376] +2024-11-21 16:39:30.974015: Epoch time: 19.31 s +2024-11-21 16:39:31.785108: +2024-11-21 16:39:31.785603: Epoch 1101 +2024-11-21 16:39:31.785739: Current learning rate: 0.00875 +2024-11-21 16:39:49.646908: train_loss -0.7721 +2024-11-21 16:39:49.647124: val_loss -0.7211 +2024-11-21 16:39:49.647200: Pseudo dice [0.8515] +2024-11-21 16:39:49.647279: Epoch time: 17.86 s +2024-11-21 16:39:50.471402: +2024-11-21 16:39:50.471892: Epoch 1102 +2024-11-21 16:39:50.472030: Current learning rate: 0.00875 +2024-11-21 16:40:10.340580: train_loss -0.7508 +2024-11-21 16:40:10.340787: val_loss -0.7499 +2024-11-21 16:40:10.340858: Pseudo dice [0.8357] +2024-11-21 16:40:10.340933: Epoch time: 19.87 s +2024-11-21 16:40:11.159286: +2024-11-21 16:40:11.159693: Epoch 1103 +2024-11-21 16:40:11.159830: Current learning rate: 0.00875 +2024-11-21 16:40:29.503131: train_loss -0.7654 +2024-11-21 16:40:29.503372: val_loss -0.713 +2024-11-21 16:40:29.503447: Pseudo dice [0.8334] +2024-11-21 16:40:29.503532: Epoch time: 18.34 s +2024-11-21 16:40:30.324456: +2024-11-21 16:40:30.324862: Epoch 1104 +2024-11-21 16:40:30.325009: Current learning rate: 0.00875 +2024-11-21 16:40:49.051069: train_loss -0.7703 +2024-11-21 16:40:49.051285: val_loss -0.7342 +2024-11-21 16:40:49.051363: Pseudo dice [0.8293] +2024-11-21 16:40:49.051656: Epoch time: 18.73 s +2024-11-21 16:40:49.861425: +2024-11-21 16:40:49.861973: Epoch 1105 +2024-11-21 16:40:49.862125: Current learning rate: 0.00875 +2024-11-21 16:41:08.791652: train_loss -0.7628 +2024-11-21 16:41:08.791856: val_loss -0.7491 +2024-11-21 16:41:08.791942: Pseudo dice [0.8264] +2024-11-21 16:41:08.792034: Epoch time: 18.93 s +2024-11-21 16:41:09.607717: +2024-11-21 16:41:09.607901: Epoch 1106 +2024-11-21 16:41:09.608019: Current learning rate: 0.00875 +2024-11-21 16:41:27.870574: train_loss -0.7681 +2024-11-21 16:41:27.870795: val_loss -0.7279 +2024-11-21 16:41:27.870872: Pseudo dice [0.84] +2024-11-21 16:41:27.870953: Epoch time: 18.26 s +2024-11-21 16:41:29.083036: +2024-11-21 16:41:29.083471: Epoch 1107 +2024-11-21 16:41:29.083602: Current learning rate: 0.00875 +2024-11-21 16:41:48.465860: train_loss -0.7713 +2024-11-21 16:41:48.466113: val_loss -0.7553 +2024-11-21 16:41:48.466188: Pseudo dice [0.8209] +2024-11-21 16:41:48.466268: Epoch time: 19.38 s +2024-11-21 16:41:49.283863: +2024-11-21 16:41:49.284308: Epoch 1108 +2024-11-21 16:41:49.284444: Current learning rate: 0.00874 +2024-11-21 16:42:07.897276: train_loss -0.7661 +2024-11-21 16:42:07.897495: val_loss -0.7435 +2024-11-21 16:42:07.897568: Pseudo dice [0.8494] +2024-11-21 16:42:07.897642: Epoch time: 18.61 s +2024-11-21 16:42:08.714495: +2024-11-21 16:42:08.714920: Epoch 1109 +2024-11-21 16:42:08.715060: Current learning rate: 0.00874 +2024-11-21 16:42:28.440549: train_loss -0.7624 +2024-11-21 16:42:28.440849: val_loss -0.7329 +2024-11-21 16:42:28.440926: Pseudo dice [0.8536] +2024-11-21 16:42:28.441011: Epoch time: 19.73 s +2024-11-21 16:42:29.266204: +2024-11-21 16:42:29.266659: Epoch 1110 +2024-11-21 16:42:29.266793: Current learning rate: 0.00874 +2024-11-21 16:42:48.527800: train_loss -0.7654 +2024-11-21 16:42:48.528070: val_loss -0.7524 +2024-11-21 16:42:48.528155: Pseudo dice [0.8423] +2024-11-21 16:42:48.528239: Epoch time: 19.26 s +2024-11-21 16:42:49.350579: +2024-11-21 16:42:49.351025: Epoch 1111 +2024-11-21 16:42:49.351162: Current learning rate: 0.00874 +2024-11-21 16:43:07.930461: train_loss -0.7486 +2024-11-21 16:43:07.930668: val_loss -0.754 +2024-11-21 16:43:07.930748: Pseudo dice [0.8489] +2024-11-21 16:43:07.930825: Epoch time: 18.58 s +2024-11-21 16:43:08.751791: +2024-11-21 16:43:08.752260: Epoch 1112 +2024-11-21 16:43:08.752401: Current learning rate: 0.00874 +2024-11-21 16:43:28.025205: train_loss -0.7495 +2024-11-21 16:43:28.025435: val_loss -0.7222 +2024-11-21 16:43:28.025515: Pseudo dice [0.8078] +2024-11-21 16:43:28.025597: Epoch time: 19.27 s +2024-11-21 16:43:28.849940: +2024-11-21 16:43:28.850383: Epoch 1113 +2024-11-21 16:43:28.850520: Current learning rate: 0.00874 +2024-11-21 16:43:48.494152: train_loss -0.7591 +2024-11-21 16:43:48.494397: val_loss -0.7207 +2024-11-21 16:43:48.494473: Pseudo dice [0.8425] +2024-11-21 16:43:48.494559: Epoch time: 19.65 s +2024-11-21 16:43:49.410625: +2024-11-21 16:43:49.411061: Epoch 1114 +2024-11-21 16:43:49.411204: Current learning rate: 0.00874 +2024-11-21 16:44:07.866952: train_loss -0.7547 +2024-11-21 16:44:07.867169: val_loss -0.7483 +2024-11-21 16:44:07.867244: Pseudo dice [0.8372] +2024-11-21 16:44:07.867320: Epoch time: 18.46 s +2024-11-21 16:44:08.871748: +2024-11-21 16:44:08.872175: Epoch 1115 +2024-11-21 16:44:08.872308: Current learning rate: 0.00874 +2024-11-21 16:44:27.483875: train_loss -0.7657 +2024-11-21 16:44:27.484099: val_loss -0.7394 +2024-11-21 16:44:27.484170: Pseudo dice [0.8521] +2024-11-21 16:44:27.484248: Epoch time: 18.61 s +2024-11-21 16:44:28.323074: +2024-11-21 16:44:28.323481: Epoch 1116 +2024-11-21 16:44:28.323614: Current learning rate: 0.00874 +2024-11-21 16:44:47.131526: train_loss -0.7621 +2024-11-21 16:44:47.131775: val_loss -0.7108 +2024-11-21 16:44:47.131851: Pseudo dice [0.8191] +2024-11-21 16:44:47.131934: Epoch time: 18.81 s +2024-11-21 16:44:47.952434: +2024-11-21 16:44:47.952853: Epoch 1117 +2024-11-21 16:44:47.952988: Current learning rate: 0.00873 +2024-11-21 16:45:06.811578: train_loss -0.7588 +2024-11-21 16:45:06.811873: val_loss -0.7671 +2024-11-21 16:45:06.811958: Pseudo dice [0.8553] +2024-11-21 16:45:06.812045: Epoch time: 18.86 s +2024-11-21 16:45:07.635715: +2024-11-21 16:45:07.635909: Epoch 1118 +2024-11-21 16:45:07.636038: Current learning rate: 0.00873 +2024-11-21 16:45:25.729439: train_loss -0.7569 +2024-11-21 16:45:25.729660: val_loss -0.7254 +2024-11-21 16:45:25.729735: Pseudo dice [0.8292] +2024-11-21 16:45:25.729810: Epoch time: 18.09 s +2024-11-21 16:45:27.312527: +2024-11-21 16:45:27.312753: Epoch 1119 +2024-11-21 16:45:27.312865: Current learning rate: 0.00873 +2024-11-21 16:45:46.945074: train_loss -0.7603 +2024-11-21 16:45:46.945334: val_loss -0.7077 +2024-11-21 16:45:46.945413: Pseudo dice [0.8066] +2024-11-21 16:45:46.945496: Epoch time: 19.63 s +2024-11-21 16:45:47.922135: +2024-11-21 16:45:47.922334: Epoch 1120 +2024-11-21 16:45:47.922442: Current learning rate: 0.00873 +2024-11-21 16:46:08.142906: train_loss -0.7647 +2024-11-21 16:46:08.143142: val_loss -0.7428 +2024-11-21 16:46:08.143218: Pseudo dice [0.8455] +2024-11-21 16:46:08.143296: Epoch time: 20.22 s +2024-11-21 16:46:08.979669: +2024-11-21 16:46:08.979869: Epoch 1121 +2024-11-21 16:46:08.979976: Current learning rate: 0.00873 +2024-11-21 16:46:26.951593: train_loss -0.7704 +2024-11-21 16:46:26.951817: val_loss -0.7047 +2024-11-21 16:46:26.951893: Pseudo dice [0.8419] +2024-11-21 16:46:26.951968: Epoch time: 17.97 s +2024-11-21 16:46:27.781558: +2024-11-21 16:46:27.781769: Epoch 1122 +2024-11-21 16:46:27.781886: Current learning rate: 0.00873 +2024-11-21 16:46:45.677899: train_loss -0.7795 +2024-11-21 16:46:45.678154: val_loss -0.7746 +2024-11-21 16:46:45.678228: Pseudo dice [0.8472] +2024-11-21 16:46:45.678312: Epoch time: 17.9 s +2024-11-21 16:46:46.502209: +2024-11-21 16:46:46.502432: Epoch 1123 +2024-11-21 16:46:46.502546: Current learning rate: 0.00873 +2024-11-21 16:47:05.751794: train_loss -0.7591 +2024-11-21 16:47:05.752103: val_loss -0.7283 +2024-11-21 16:47:05.752179: Pseudo dice [0.8347] +2024-11-21 16:47:05.752254: Epoch time: 19.25 s +2024-11-21 16:47:06.679060: +2024-11-21 16:47:06.679276: Epoch 1124 +2024-11-21 16:47:06.679387: Current learning rate: 0.00873 +2024-11-21 16:47:26.380638: train_loss -0.7665 +2024-11-21 16:47:26.380861: val_loss -0.7561 +2024-11-21 16:47:26.380933: Pseudo dice [0.8598] +2024-11-21 16:47:26.381014: Epoch time: 19.7 s +2024-11-21 16:47:27.200524: +2024-11-21 16:47:27.200733: Epoch 1125 +2024-11-21 16:47:27.200852: Current learning rate: 0.00872 +2024-11-21 16:47:46.564439: train_loss -0.7675 +2024-11-21 16:47:46.564656: val_loss -0.755 +2024-11-21 16:47:46.564731: Pseudo dice [0.8306] +2024-11-21 16:47:46.564808: Epoch time: 19.36 s +2024-11-21 16:47:47.389464: +2024-11-21 16:47:47.389681: Epoch 1126 +2024-11-21 16:47:47.389794: Current learning rate: 0.00872 +2024-11-21 16:48:06.765081: train_loss -0.7694 +2024-11-21 16:48:06.765316: val_loss -0.732 +2024-11-21 16:48:06.767550: Pseudo dice [0.8191] +2024-11-21 16:48:06.767667: Epoch time: 19.38 s +2024-11-21 16:48:07.726734: +2024-11-21 16:48:07.727103: Epoch 1127 +2024-11-21 16:48:07.727221: Current learning rate: 0.00872 +2024-11-21 16:48:26.136252: train_loss -0.7788 +2024-11-21 16:48:26.136457: val_loss -0.7411 +2024-11-21 16:48:26.138741: Pseudo dice [0.8557] +2024-11-21 16:48:26.138830: Epoch time: 18.41 s +2024-11-21 16:48:26.971565: +2024-11-21 16:48:26.971764: Epoch 1128 +2024-11-21 16:48:26.971878: Current learning rate: 0.00872 +2024-11-21 16:48:45.475174: train_loss -0.7668 +2024-11-21 16:48:45.475385: val_loss -0.7594 +2024-11-21 16:48:45.475459: Pseudo dice [0.8458] +2024-11-21 16:48:45.475536: Epoch time: 18.5 s +2024-11-21 16:48:46.295611: +2024-11-21 16:48:46.295863: Epoch 1129 +2024-11-21 16:48:46.295972: Current learning rate: 0.00872 +2024-11-21 16:49:04.986000: train_loss -0.7723 +2024-11-21 16:49:04.986205: val_loss -0.7307 +2024-11-21 16:49:04.986278: Pseudo dice [0.8231] +2024-11-21 16:49:04.986356: Epoch time: 18.69 s +2024-11-21 16:49:05.873213: +2024-11-21 16:49:05.873457: Epoch 1130 +2024-11-21 16:49:05.873612: Current learning rate: 0.00872 +2024-11-21 16:49:24.283461: train_loss -0.7594 +2024-11-21 16:49:24.283710: val_loss -0.7362 +2024-11-21 16:49:24.283865: Pseudo dice [0.8234] +2024-11-21 16:49:24.283947: Epoch time: 18.41 s +2024-11-21 16:49:25.099279: +2024-11-21 16:49:25.099524: Epoch 1131 +2024-11-21 16:49:25.099641: Current learning rate: 0.00872 +2024-11-21 16:49:42.868944: train_loss -0.7707 +2024-11-21 16:49:42.869183: val_loss -0.7177 +2024-11-21 16:49:42.869259: Pseudo dice [0.8123] +2024-11-21 16:49:42.869334: Epoch time: 17.77 s +2024-11-21 16:49:43.683951: +2024-11-21 16:49:43.684213: Epoch 1132 +2024-11-21 16:49:43.684338: Current learning rate: 0.00872 +2024-11-21 16:50:01.535810: train_loss -0.7629 +2024-11-21 16:50:01.536094: val_loss -0.734 +2024-11-21 16:50:01.536177: Pseudo dice [0.832] +2024-11-21 16:50:01.536260: Epoch time: 17.85 s +2024-11-21 16:50:02.364048: +2024-11-21 16:50:02.364393: Epoch 1133 +2024-11-21 16:50:02.364509: Current learning rate: 0.00872 +2024-11-21 16:50:21.303191: train_loss -0.757 +2024-11-21 16:50:21.303449: val_loss -0.7402 +2024-11-21 16:50:21.303526: Pseudo dice [0.8198] +2024-11-21 16:50:21.303620: Epoch time: 18.94 s +2024-11-21 16:50:22.127249: +2024-11-21 16:50:22.127461: Epoch 1134 +2024-11-21 16:50:22.127576: Current learning rate: 0.00871 +2024-11-21 16:50:40.529283: train_loss -0.7632 +2024-11-21 16:50:40.529497: val_loss -0.7242 +2024-11-21 16:50:40.529570: Pseudo dice [0.8323] +2024-11-21 16:50:40.529647: Epoch time: 18.4 s +2024-11-21 16:50:41.355502: +2024-11-21 16:50:41.355725: Epoch 1135 +2024-11-21 16:50:41.355834: Current learning rate: 0.00871 +2024-11-21 16:51:00.246403: train_loss -0.7665 +2024-11-21 16:51:00.246632: val_loss -0.7438 +2024-11-21 16:51:00.246714: Pseudo dice [0.8426] +2024-11-21 16:51:00.246794: Epoch time: 18.89 s +2024-11-21 16:51:01.130650: +2024-11-21 16:51:01.130899: Epoch 1136 +2024-11-21 16:51:01.131017: Current learning rate: 0.00871 +2024-11-21 16:51:20.498149: train_loss -0.7591 +2024-11-21 16:51:20.498404: val_loss -0.7469 +2024-11-21 16:51:20.498483: Pseudo dice [0.8427] +2024-11-21 16:51:20.503719: Epoch time: 19.37 s +2024-11-21 16:51:21.489214: +2024-11-21 16:51:21.489442: Epoch 1137 +2024-11-21 16:51:21.489553: Current learning rate: 0.00871 +2024-11-21 16:51:41.483500: train_loss -0.7719 +2024-11-21 16:51:41.483741: val_loss -0.7282 +2024-11-21 16:51:41.483817: Pseudo dice [0.8332] +2024-11-21 16:51:41.483891: Epoch time: 20.0 s +2024-11-21 16:51:42.323287: +2024-11-21 16:51:42.323529: Epoch 1138 +2024-11-21 16:51:42.323653: Current learning rate: 0.00871 +2024-11-21 16:52:01.412800: train_loss -0.7628 +2024-11-21 16:52:01.413017: val_loss -0.7514 +2024-11-21 16:52:01.413091: Pseudo dice [0.8409] +2024-11-21 16:52:01.413168: Epoch time: 19.09 s +2024-11-21 16:52:02.234308: +2024-11-21 16:52:02.234528: Epoch 1139 +2024-11-21 16:52:02.234636: Current learning rate: 0.00871 +2024-11-21 16:52:21.438580: train_loss -0.7674 +2024-11-21 16:52:21.438859: val_loss -0.7465 +2024-11-21 16:52:21.438942: Pseudo dice [0.8254] +2024-11-21 16:52:21.439039: Epoch time: 19.21 s +2024-11-21 16:52:22.255573: +2024-11-21 16:52:22.255760: Epoch 1140 +2024-11-21 16:52:22.255878: Current learning rate: 0.00871 +2024-11-21 16:52:41.125455: train_loss -0.7621 +2024-11-21 16:52:41.125696: val_loss -0.7539 +2024-11-21 16:52:41.125770: Pseudo dice [0.8416] +2024-11-21 16:52:41.125852: Epoch time: 18.87 s +2024-11-21 16:52:41.975022: +2024-11-21 16:52:41.975271: Epoch 1141 +2024-11-21 16:52:41.975386: Current learning rate: 0.00871 +2024-11-21 16:53:00.158579: train_loss -0.7752 +2024-11-21 16:53:00.158787: val_loss -0.7371 +2024-11-21 16:53:00.158861: Pseudo dice [0.8306] +2024-11-21 16:53:00.158934: Epoch time: 18.18 s +2024-11-21 16:53:01.398406: +2024-11-21 16:53:01.398641: Epoch 1142 +2024-11-21 16:53:01.398754: Current learning rate: 0.00871 +2024-11-21 16:53:21.229081: train_loss -0.7703 +2024-11-21 16:53:21.229325: val_loss -0.7512 +2024-11-21 16:53:21.229404: Pseudo dice [0.8198] +2024-11-21 16:53:21.229481: Epoch time: 19.83 s +2024-11-21 16:53:22.047230: +2024-11-21 16:53:22.047499: Epoch 1143 +2024-11-21 16:53:22.047608: Current learning rate: 0.0087 +2024-11-21 16:53:41.152224: train_loss -0.7644 +2024-11-21 16:53:41.152522: val_loss -0.7289 +2024-11-21 16:53:41.152598: Pseudo dice [0.8136] +2024-11-21 16:53:41.152680: Epoch time: 19.11 s +2024-11-21 16:53:41.985565: +2024-11-21 16:53:41.985793: Epoch 1144 +2024-11-21 16:53:41.985906: Current learning rate: 0.0087 +2024-11-21 16:54:00.605540: train_loss -0.7671 +2024-11-21 16:54:00.605749: val_loss -0.7443 +2024-11-21 16:54:00.605827: Pseudo dice [0.8377] +2024-11-21 16:54:00.605901: Epoch time: 18.62 s +2024-11-21 16:54:01.447767: +2024-11-21 16:54:01.448010: Epoch 1145 +2024-11-21 16:54:01.448127: Current learning rate: 0.0087 +2024-11-21 16:54:20.332237: train_loss -0.7616 +2024-11-21 16:54:20.332448: val_loss -0.7292 +2024-11-21 16:54:20.332523: Pseudo dice [0.8298] +2024-11-21 16:54:20.332600: Epoch time: 18.89 s +2024-11-21 16:54:21.162639: +2024-11-21 16:54:21.162860: Epoch 1146 +2024-11-21 16:54:21.162972: Current learning rate: 0.0087 +2024-11-21 16:54:40.338876: train_loss -0.7672 +2024-11-21 16:54:40.339088: val_loss -0.7367 +2024-11-21 16:54:40.339164: Pseudo dice [0.8248] +2024-11-21 16:54:40.339241: Epoch time: 19.18 s +2024-11-21 16:54:41.168282: +2024-11-21 16:54:41.168478: Epoch 1147 +2024-11-21 16:54:41.168591: Current learning rate: 0.0087 +2024-11-21 16:55:00.304063: train_loss -0.7764 +2024-11-21 16:55:00.304312: val_loss -0.7473 +2024-11-21 16:55:00.304387: Pseudo dice [0.8417] +2024-11-21 16:55:00.304471: Epoch time: 19.14 s +2024-11-21 16:55:01.135715: +2024-11-21 16:55:01.135982: Epoch 1148 +2024-11-21 16:55:01.136099: Current learning rate: 0.0087 +2024-11-21 16:55:20.778160: train_loss -0.7666 +2024-11-21 16:55:20.778375: val_loss -0.7406 +2024-11-21 16:55:20.778457: Pseudo dice [0.8245] +2024-11-21 16:55:20.778534: Epoch time: 19.64 s +2024-11-21 16:55:21.608945: +2024-11-21 16:55:21.609281: Epoch 1149 +2024-11-21 16:55:21.609404: Current learning rate: 0.0087 +2024-11-21 16:55:40.283321: train_loss -0.769 +2024-11-21 16:55:40.288734: val_loss -0.7777 +2024-11-21 16:55:40.288862: Pseudo dice [0.8595] +2024-11-21 16:55:40.288946: Epoch time: 18.68 s +2024-11-21 16:55:41.371397: +2024-11-21 16:55:41.371596: Epoch 1150 +2024-11-21 16:55:41.371708: Current learning rate: 0.0087 +2024-11-21 16:55:59.819043: train_loss -0.7677 +2024-11-21 16:55:59.819254: val_loss -0.7307 +2024-11-21 16:55:59.819330: Pseudo dice [0.8215] +2024-11-21 16:55:59.819407: Epoch time: 18.45 s +2024-11-21 16:56:00.656269: +2024-11-21 16:56:00.656483: Epoch 1151 +2024-11-21 16:56:00.656595: Current learning rate: 0.0087 +2024-11-21 16:56:19.433117: train_loss -0.7677 +2024-11-21 16:56:19.433362: val_loss -0.7238 +2024-11-21 16:56:19.433437: Pseudo dice [0.8323] +2024-11-21 16:56:19.433519: Epoch time: 18.78 s +2024-11-21 16:56:20.298893: +2024-11-21 16:56:20.299092: Epoch 1152 +2024-11-21 16:56:20.299204: Current learning rate: 0.00869 +2024-11-21 16:56:39.017798: train_loss -0.765 +2024-11-21 16:56:39.018028: val_loss -0.7718 +2024-11-21 16:56:39.018104: Pseudo dice [0.8454] +2024-11-21 16:56:39.018180: Epoch time: 18.72 s +2024-11-21 16:56:39.848527: +2024-11-21 16:56:39.848749: Epoch 1153 +2024-11-21 16:56:39.848864: Current learning rate: 0.00869 +2024-11-21 16:56:58.787832: train_loss -0.7624 +2024-11-21 16:56:58.788074: val_loss -0.759 +2024-11-21 16:56:58.788151: Pseudo dice [0.837] +2024-11-21 16:56:58.788231: Epoch time: 18.94 s +2024-11-21 16:56:59.614527: +2024-11-21 16:56:59.614786: Epoch 1154 +2024-11-21 16:56:59.614909: Current learning rate: 0.00869 +2024-11-21 16:57:18.333574: train_loss -0.7568 +2024-11-21 16:57:18.334779: val_loss -0.7288 +2024-11-21 16:57:18.334856: Pseudo dice [0.8474] +2024-11-21 16:57:18.334940: Epoch time: 18.72 s +2024-11-21 16:57:19.170625: +2024-11-21 16:57:19.170860: Epoch 1155 +2024-11-21 16:57:19.170982: Current learning rate: 0.00869 +2024-11-21 16:57:37.443101: train_loss -0.7537 +2024-11-21 16:57:37.443313: val_loss -0.7099 +2024-11-21 16:57:37.443465: Pseudo dice [0.8305] +2024-11-21 16:57:37.443542: Epoch time: 18.27 s +2024-11-21 16:57:38.291856: +2024-11-21 16:57:38.292111: Epoch 1156 +2024-11-21 16:57:38.292224: Current learning rate: 0.00869 +2024-11-21 16:57:56.703014: train_loss -0.7646 +2024-11-21 16:57:56.703234: val_loss -0.715 +2024-11-21 16:57:56.708800: Pseudo dice [0.8314] +2024-11-21 16:57:56.709000: Epoch time: 18.41 s +2024-11-21 16:57:57.708589: +2024-11-21 16:57:57.708804: Epoch 1157 +2024-11-21 16:57:57.708921: Current learning rate: 0.00869 +2024-11-21 16:58:16.385275: train_loss -0.7545 +2024-11-21 16:58:16.385517: val_loss -0.7545 +2024-11-21 16:58:16.385590: Pseudo dice [0.8471] +2024-11-21 16:58:16.385669: Epoch time: 18.68 s +2024-11-21 16:58:17.219296: +2024-11-21 16:58:17.219615: Epoch 1158 +2024-11-21 16:58:17.219730: Current learning rate: 0.00869 +2024-11-21 16:58:36.884043: train_loss -0.7558 +2024-11-21 16:58:36.884255: val_loss -0.7261 +2024-11-21 16:58:36.884329: Pseudo dice [0.8141] +2024-11-21 16:58:36.884432: Epoch time: 19.67 s +2024-11-21 16:58:37.715526: +2024-11-21 16:58:37.715741: Epoch 1159 +2024-11-21 16:58:37.715853: Current learning rate: 0.00869 +2024-11-21 16:58:56.381786: train_loss -0.7646 +2024-11-21 16:58:56.383329: val_loss -0.7456 +2024-11-21 16:58:56.383547: Pseudo dice [0.8564] +2024-11-21 16:58:56.383632: Epoch time: 18.67 s +2024-11-21 16:58:57.219722: +2024-11-21 16:58:57.219990: Epoch 1160 +2024-11-21 16:58:57.220108: Current learning rate: 0.00868 +2024-11-21 16:59:17.133970: train_loss -0.7547 +2024-11-21 16:59:17.134183: val_loss -0.7331 +2024-11-21 16:59:17.134258: Pseudo dice [0.854] +2024-11-21 16:59:17.134331: Epoch time: 19.92 s +2024-11-21 16:59:18.001034: +2024-11-21 16:59:18.001312: Epoch 1161 +2024-11-21 16:59:18.001434: Current learning rate: 0.00868 +2024-11-21 16:59:36.686908: train_loss -0.7722 +2024-11-21 16:59:36.687140: val_loss -0.7505 +2024-11-21 16:59:36.687214: Pseudo dice [0.8268] +2024-11-21 16:59:36.687295: Epoch time: 18.69 s +2024-11-21 16:59:37.556292: +2024-11-21 16:59:37.556551: Epoch 1162 +2024-11-21 16:59:37.556664: Current learning rate: 0.00868 +2024-11-21 16:59:55.144585: train_loss -0.7793 +2024-11-21 16:59:55.144793: val_loss -0.7481 +2024-11-21 16:59:55.144868: Pseudo dice [0.8526] +2024-11-21 16:59:55.144940: Epoch time: 17.59 s +2024-11-21 16:59:56.071037: +2024-11-21 16:59:56.071299: Epoch 1163 +2024-11-21 16:59:56.071413: Current learning rate: 0.00868 +2024-11-21 17:00:14.938531: train_loss -0.7633 +2024-11-21 17:00:14.938744: val_loss -0.7465 +2024-11-21 17:00:14.938817: Pseudo dice [0.8398] +2024-11-21 17:00:14.938893: Epoch time: 18.87 s +2024-11-21 17:00:15.767825: +2024-11-21 17:00:15.768038: Epoch 1164 +2024-11-21 17:00:15.768151: Current learning rate: 0.00868 +2024-11-21 17:00:35.563634: train_loss -0.7642 +2024-11-21 17:00:35.566121: val_loss -0.7448 +2024-11-21 17:00:35.566215: Pseudo dice [0.8437] +2024-11-21 17:00:35.566301: Epoch time: 19.8 s +2024-11-21 17:00:36.928501: +2024-11-21 17:00:36.928729: Epoch 1165 +2024-11-21 17:00:36.928836: Current learning rate: 0.00868 +2024-11-21 17:00:55.348793: train_loss -0.7632 +2024-11-21 17:00:55.349027: val_loss -0.7274 +2024-11-21 17:00:55.349106: Pseudo dice [0.8485] +2024-11-21 17:00:55.349185: Epoch time: 18.42 s +2024-11-21 17:00:56.182412: +2024-11-21 17:00:56.182623: Epoch 1166 +2024-11-21 17:00:56.182734: Current learning rate: 0.00868 +2024-11-21 17:01:13.987878: train_loss -0.7727 +2024-11-21 17:01:13.988096: val_loss -0.7262 +2024-11-21 17:01:13.988171: Pseudo dice [0.8562] +2024-11-21 17:01:13.988248: Epoch time: 17.81 s +2024-11-21 17:01:14.816725: +2024-11-21 17:01:14.816962: Epoch 1167 +2024-11-21 17:01:14.817084: Current learning rate: 0.00868 +2024-11-21 17:01:33.126323: train_loss -0.7688 +2024-11-21 17:01:33.126534: val_loss -0.7166 +2024-11-21 17:01:33.126632: Pseudo dice [0.8205] +2024-11-21 17:01:33.126712: Epoch time: 18.31 s +2024-11-21 17:01:33.955667: +2024-11-21 17:01:33.955876: Epoch 1168 +2024-11-21 17:01:33.955989: Current learning rate: 0.00868 +2024-11-21 17:01:52.185741: train_loss -0.7619 +2024-11-21 17:01:52.186039: val_loss -0.7652 +2024-11-21 17:01:52.186118: Pseudo dice [0.8517] +2024-11-21 17:01:52.186203: Epoch time: 18.23 s +2024-11-21 17:01:53.025067: +2024-11-21 17:01:53.025359: Epoch 1169 +2024-11-21 17:01:53.025476: Current learning rate: 0.00867 +2024-11-21 17:02:11.145956: train_loss -0.7701 +2024-11-21 17:02:11.146226: val_loss -0.7288 +2024-11-21 17:02:11.146305: Pseudo dice [0.8636] +2024-11-21 17:02:11.146381: Epoch time: 18.12 s +2024-11-21 17:02:11.976629: +2024-11-21 17:02:11.976839: Epoch 1170 +2024-11-21 17:02:11.976953: Current learning rate: 0.00867 +2024-11-21 17:02:30.472476: train_loss -0.78 +2024-11-21 17:02:30.472694: val_loss -0.7319 +2024-11-21 17:02:30.472769: Pseudo dice [0.8178] +2024-11-21 17:02:30.474278: Epoch time: 18.5 s +2024-11-21 17:02:31.470840: +2024-11-21 17:02:31.471070: Epoch 1171 +2024-11-21 17:02:31.471190: Current learning rate: 0.00867 +2024-11-21 17:02:50.510344: train_loss -0.7707 +2024-11-21 17:02:50.510559: val_loss -0.736 +2024-11-21 17:02:50.510638: Pseudo dice [0.8331] +2024-11-21 17:02:50.510719: Epoch time: 19.04 s +2024-11-21 17:02:51.343712: +2024-11-21 17:02:51.343940: Epoch 1172 +2024-11-21 17:02:51.344065: Current learning rate: 0.00867 +2024-11-21 17:03:10.461951: train_loss -0.7643 +2024-11-21 17:03:10.462204: val_loss -0.736 +2024-11-21 17:03:10.462283: Pseudo dice [0.8406] +2024-11-21 17:03:10.462365: Epoch time: 19.12 s +2024-11-21 17:03:11.295480: +2024-11-21 17:03:11.295712: Epoch 1173 +2024-11-21 17:03:11.295830: Current learning rate: 0.00867 +2024-11-21 17:03:31.110907: train_loss -0.7733 +2024-11-21 17:03:31.111124: val_loss -0.7376 +2024-11-21 17:03:31.111198: Pseudo dice [0.8442] +2024-11-21 17:03:31.116421: Epoch time: 19.82 s +2024-11-21 17:03:31.981308: +2024-11-21 17:03:31.981521: Epoch 1174 +2024-11-21 17:03:31.981629: Current learning rate: 0.00867 +2024-11-21 17:03:51.059477: train_loss -0.7802 +2024-11-21 17:03:51.059686: val_loss -0.7758 +2024-11-21 17:03:51.059761: Pseudo dice [0.8607] +2024-11-21 17:03:51.059836: Epoch time: 19.08 s +2024-11-21 17:03:51.891392: +2024-11-21 17:03:51.891587: Epoch 1175 +2024-11-21 17:03:51.891698: Current learning rate: 0.00867 +2024-11-21 17:04:10.922721: train_loss -0.7638 +2024-11-21 17:04:10.922968: val_loss -0.7428 +2024-11-21 17:04:10.923049: Pseudo dice [0.8316] +2024-11-21 17:04:10.923132: Epoch time: 19.03 s +2024-11-21 17:04:11.753564: +2024-11-21 17:04:11.753866: Epoch 1176 +2024-11-21 17:04:11.753982: Current learning rate: 0.00867 +2024-11-21 17:04:30.211574: train_loss -0.7694 +2024-11-21 17:04:30.211791: val_loss -0.7437 +2024-11-21 17:04:30.211863: Pseudo dice [0.8336] +2024-11-21 17:04:30.211938: Epoch time: 18.46 s +2024-11-21 17:04:31.037151: +2024-11-21 17:04:31.037459: Epoch 1177 +2024-11-21 17:04:31.037582: Current learning rate: 0.00867 +2024-11-21 17:04:49.523903: train_loss -0.7511 +2024-11-21 17:04:49.524131: val_loss -0.7156 +2024-11-21 17:04:49.524203: Pseudo dice [0.7945] +2024-11-21 17:04:49.524277: Epoch time: 18.49 s +2024-11-21 17:04:50.354715: +2024-11-21 17:04:50.355030: Epoch 1178 +2024-11-21 17:04:50.355145: Current learning rate: 0.00866 +2024-11-21 17:05:08.932534: train_loss -0.745 +2024-11-21 17:05:08.932749: val_loss -0.7731 +2024-11-21 17:05:08.932823: Pseudo dice [0.8358] +2024-11-21 17:05:08.932904: Epoch time: 18.58 s +2024-11-21 17:05:09.771068: +2024-11-21 17:05:09.771321: Epoch 1179 +2024-11-21 17:05:09.771481: Current learning rate: 0.00866 +2024-11-21 17:05:27.839293: train_loss -0.7542 +2024-11-21 17:05:27.839522: val_loss -0.7284 +2024-11-21 17:05:27.839617: Pseudo dice [0.8362] +2024-11-21 17:05:27.839698: Epoch time: 18.07 s +2024-11-21 17:05:28.677494: +2024-11-21 17:05:28.677712: Epoch 1180 +2024-11-21 17:05:28.677830: Current learning rate: 0.00866 +2024-11-21 17:05:48.262320: train_loss -0.7741 +2024-11-21 17:05:48.262528: val_loss -0.7626 +2024-11-21 17:05:48.262603: Pseudo dice [0.8438] +2024-11-21 17:05:48.262677: Epoch time: 19.59 s +2024-11-21 17:05:49.098574: +2024-11-21 17:05:49.098776: Epoch 1181 +2024-11-21 17:05:49.098886: Current learning rate: 0.00866 +2024-11-21 17:06:09.645101: train_loss -0.7607 +2024-11-21 17:06:09.645310: val_loss -0.7465 +2024-11-21 17:06:09.645388: Pseudo dice [0.8423] +2024-11-21 17:06:09.645474: Epoch time: 20.55 s +2024-11-21 17:06:10.478970: +2024-11-21 17:06:10.479172: Epoch 1182 +2024-11-21 17:06:10.479284: Current learning rate: 0.00866 +2024-11-21 17:06:30.458665: train_loss -0.7565 +2024-11-21 17:06:30.459313: val_loss -0.7598 +2024-11-21 17:06:30.459413: Pseudo dice [0.8491] +2024-11-21 17:06:30.459500: Epoch time: 19.98 s +2024-11-21 17:06:31.299649: +2024-11-21 17:06:31.299917: Epoch 1183 +2024-11-21 17:06:31.300035: Current learning rate: 0.00866 +2024-11-21 17:06:49.467903: train_loss -0.7649 +2024-11-21 17:06:49.468134: val_loss -0.7176 +2024-11-21 17:06:49.468216: Pseudo dice [0.8279] +2024-11-21 17:06:49.468297: Epoch time: 18.17 s +2024-11-21 17:06:50.296592: +2024-11-21 17:06:50.296796: Epoch 1184 +2024-11-21 17:06:50.296912: Current learning rate: 0.00866 +2024-11-21 17:07:08.603411: train_loss -0.7683 +2024-11-21 17:07:08.603615: val_loss -0.7598 +2024-11-21 17:07:08.603689: Pseudo dice [0.8366] +2024-11-21 17:07:08.603765: Epoch time: 18.31 s +2024-11-21 17:07:09.438495: +2024-11-21 17:07:09.438757: Epoch 1185 +2024-11-21 17:07:09.438874: Current learning rate: 0.00866 +2024-11-21 17:07:27.891809: train_loss -0.7606 +2024-11-21 17:07:27.892044: val_loss -0.7298 +2024-11-21 17:07:27.892124: Pseudo dice [0.8203] +2024-11-21 17:07:27.897417: Epoch time: 18.45 s +2024-11-21 17:07:28.963291: +2024-11-21 17:07:28.963496: Epoch 1186 +2024-11-21 17:07:28.963612: Current learning rate: 0.00866 +2024-11-21 17:07:48.121758: train_loss -0.7626 +2024-11-21 17:07:48.122001: val_loss -0.7551 +2024-11-21 17:07:48.122078: Pseudo dice [0.8448] +2024-11-21 17:07:48.124779: Epoch time: 19.16 s +2024-11-21 17:07:48.968493: +2024-11-21 17:07:48.968687: Epoch 1187 +2024-11-21 17:07:48.968801: Current learning rate: 0.00865 +2024-11-21 17:08:07.630374: train_loss -0.7742 +2024-11-21 17:08:07.630595: val_loss -0.7647 +2024-11-21 17:08:07.630681: Pseudo dice [0.8526] +2024-11-21 17:08:07.630756: Epoch time: 18.66 s +2024-11-21 17:08:08.851038: +2024-11-21 17:08:08.851262: Epoch 1188 +2024-11-21 17:08:08.851376: Current learning rate: 0.00865 +2024-11-21 17:08:27.822921: train_loss -0.7671 +2024-11-21 17:08:27.823159: val_loss -0.7398 +2024-11-21 17:08:27.823237: Pseudo dice [0.8268] +2024-11-21 17:08:27.823315: Epoch time: 18.97 s +2024-11-21 17:08:28.709390: +2024-11-21 17:08:28.709651: Epoch 1189 +2024-11-21 17:08:28.709765: Current learning rate: 0.00865 +2024-11-21 17:08:48.171726: train_loss -0.7528 +2024-11-21 17:08:48.171971: val_loss -0.7515 +2024-11-21 17:08:48.172051: Pseudo dice [0.8339] +2024-11-21 17:08:48.172189: Epoch time: 19.46 s +2024-11-21 17:08:49.040339: +2024-11-21 17:08:49.040586: Epoch 1190 +2024-11-21 17:08:49.040700: Current learning rate: 0.00865 +2024-11-21 17:09:07.031164: train_loss -0.7658 +2024-11-21 17:09:07.031392: val_loss -0.757 +2024-11-21 17:09:07.031472: Pseudo dice [0.8318] +2024-11-21 17:09:07.031552: Epoch time: 17.99 s +2024-11-21 17:09:07.864361: +2024-11-21 17:09:07.864557: Epoch 1191 +2024-11-21 17:09:07.864671: Current learning rate: 0.00865 +2024-11-21 17:09:26.001438: train_loss -0.7731 +2024-11-21 17:09:26.001649: val_loss -0.7436 +2024-11-21 17:09:26.001722: Pseudo dice [0.8613] +2024-11-21 17:09:26.001859: Epoch time: 18.14 s +2024-11-21 17:09:26.837709: +2024-11-21 17:09:26.837920: Epoch 1192 +2024-11-21 17:09:26.838036: Current learning rate: 0.00865 +2024-11-21 17:09:44.965050: train_loss -0.7596 +2024-11-21 17:09:44.970514: val_loss -0.7372 +2024-11-21 17:09:44.970602: Pseudo dice [0.8307] +2024-11-21 17:09:44.970691: Epoch time: 18.13 s +2024-11-21 17:09:45.866256: +2024-11-21 17:09:45.866482: Epoch 1193 +2024-11-21 17:09:45.866599: Current learning rate: 0.00865 +2024-11-21 17:10:04.103747: train_loss -0.75 +2024-11-21 17:10:04.103967: val_loss -0.7477 +2024-11-21 17:10:04.104049: Pseudo dice [0.8366] +2024-11-21 17:10:04.104128: Epoch time: 18.24 s +2024-11-21 17:10:05.153589: +2024-11-21 17:10:05.153824: Epoch 1194 +2024-11-21 17:10:05.153938: Current learning rate: 0.00865 +2024-11-21 17:10:23.468528: train_loss -0.7583 +2024-11-21 17:10:23.468745: val_loss -0.7547 +2024-11-21 17:10:23.468817: Pseudo dice [0.8418] +2024-11-21 17:10:23.468893: Epoch time: 18.32 s +2024-11-21 17:10:24.331695: +2024-11-21 17:10:24.331909: Epoch 1195 +2024-11-21 17:10:24.332024: Current learning rate: 0.00864 +2024-11-21 17:10:42.258196: train_loss -0.7705 +2024-11-21 17:10:42.258406: val_loss -0.7628 +2024-11-21 17:10:42.260726: Pseudo dice [0.8343] +2024-11-21 17:10:42.260829: Epoch time: 17.93 s +2024-11-21 17:10:43.138379: +2024-11-21 17:10:43.138594: Epoch 1196 +2024-11-21 17:10:43.138717: Current learning rate: 0.00864 +2024-11-21 17:11:01.616099: train_loss -0.7615 +2024-11-21 17:11:01.616339: val_loss -0.731 +2024-11-21 17:11:01.616417: Pseudo dice [0.8308] +2024-11-21 17:11:01.616497: Epoch time: 18.48 s +2024-11-21 17:11:02.459665: +2024-11-21 17:11:02.459854: Epoch 1197 +2024-11-21 17:11:02.459965: Current learning rate: 0.00864 +2024-11-21 17:11:21.583397: train_loss -0.7662 +2024-11-21 17:11:21.583604: val_loss -0.7168 +2024-11-21 17:11:21.583682: Pseudo dice [0.8129] +2024-11-21 17:11:21.583763: Epoch time: 19.12 s +2024-11-21 17:11:22.407365: +2024-11-21 17:11:22.407558: Epoch 1198 +2024-11-21 17:11:22.407665: Current learning rate: 0.00864 +2024-11-21 17:11:40.639760: train_loss -0.7778 +2024-11-21 17:11:40.639969: val_loss -0.7414 +2024-11-21 17:11:40.640057: Pseudo dice [0.8392] +2024-11-21 17:11:40.641920: Epoch time: 18.23 s +2024-11-21 17:11:41.482528: +2024-11-21 17:11:41.482710: Epoch 1199 +2024-11-21 17:11:41.482819: Current learning rate: 0.00864 +2024-11-21 17:11:59.610739: train_loss -0.7603 +2024-11-21 17:11:59.611013: val_loss -0.7384 +2024-11-21 17:11:59.611091: Pseudo dice [0.8325] +2024-11-21 17:11:59.611177: Epoch time: 18.13 s +2024-11-21 17:12:00.669727: +2024-11-21 17:12:00.669926: Epoch 1200 +2024-11-21 17:12:00.670044: Current learning rate: 0.00864 +2024-11-21 17:12:18.462697: train_loss -0.768 +2024-11-21 17:12:18.463033: val_loss -0.7128 +2024-11-21 17:12:18.463116: Pseudo dice [0.837] +2024-11-21 17:12:18.463194: Epoch time: 17.79 s +2024-11-21 17:12:19.297211: +2024-11-21 17:12:19.297432: Epoch 1201 +2024-11-21 17:12:19.297549: Current learning rate: 0.00864 +2024-11-21 17:12:37.778724: train_loss -0.7672 +2024-11-21 17:12:37.778989: val_loss -0.7582 +2024-11-21 17:12:37.779073: Pseudo dice [0.8382] +2024-11-21 17:12:37.779157: Epoch time: 18.48 s +2024-11-21 17:12:38.650406: +2024-11-21 17:12:38.650624: Epoch 1202 +2024-11-21 17:12:38.650744: Current learning rate: 0.00864 +2024-11-21 17:12:57.065500: train_loss -0.7642 +2024-11-21 17:12:57.065745: val_loss -0.73 +2024-11-21 17:12:57.065819: Pseudo dice [0.8354] +2024-11-21 17:12:57.065907: Epoch time: 18.42 s +2024-11-21 17:12:57.903874: +2024-11-21 17:12:57.904255: Epoch 1203 +2024-11-21 17:12:57.904366: Current learning rate: 0.00864 +2024-11-21 17:13:16.703865: train_loss -0.7679 +2024-11-21 17:13:16.704091: val_loss -0.718 +2024-11-21 17:13:16.704165: Pseudo dice [0.8445] +2024-11-21 17:13:16.704245: Epoch time: 18.8 s +2024-11-21 17:13:17.709802: +2024-11-21 17:13:17.710031: Epoch 1204 +2024-11-21 17:13:17.710147: Current learning rate: 0.00863 +2024-11-21 17:13:36.374889: train_loss -0.7726 +2024-11-21 17:13:36.375145: val_loss -0.7408 +2024-11-21 17:13:36.375221: Pseudo dice [0.8447] +2024-11-21 17:13:36.375308: Epoch time: 18.67 s +2024-11-21 17:13:37.205912: +2024-11-21 17:13:37.206167: Epoch 1205 +2024-11-21 17:13:37.206277: Current learning rate: 0.00863 +2024-11-21 17:13:56.640445: train_loss -0.7631 +2024-11-21 17:13:56.640685: val_loss -0.7486 +2024-11-21 17:13:56.640766: Pseudo dice [0.8294] +2024-11-21 17:13:56.640842: Epoch time: 19.44 s +2024-11-21 17:13:57.585530: +2024-11-21 17:13:57.585741: Epoch 1206 +2024-11-21 17:13:57.585853: Current learning rate: 0.00863 +2024-11-21 17:14:17.010133: train_loss -0.7665 +2024-11-21 17:14:17.010375: val_loss -0.7451 +2024-11-21 17:14:17.010453: Pseudo dice [0.8244] +2024-11-21 17:14:17.010535: Epoch time: 19.43 s +2024-11-21 17:14:17.847435: +2024-11-21 17:14:17.847642: Epoch 1207 +2024-11-21 17:14:17.847753: Current learning rate: 0.00863 +2024-11-21 17:14:37.665070: train_loss -0.7694 +2024-11-21 17:14:37.665276: val_loss -0.7171 +2024-11-21 17:14:37.665350: Pseudo dice [0.8513] +2024-11-21 17:14:37.665426: Epoch time: 19.82 s +2024-11-21 17:14:38.500244: +2024-11-21 17:14:38.500440: Epoch 1208 +2024-11-21 17:14:38.500550: Current learning rate: 0.00863 +2024-11-21 17:14:57.120344: train_loss -0.765 +2024-11-21 17:14:57.120777: val_loss -0.7285 +2024-11-21 17:14:57.120865: Pseudo dice [0.8252] +2024-11-21 17:14:57.120940: Epoch time: 18.62 s +2024-11-21 17:14:57.959470: +2024-11-21 17:14:57.959758: Epoch 1209 +2024-11-21 17:14:57.959873: Current learning rate: 0.00863 +2024-11-21 17:15:16.119202: train_loss -0.7614 +2024-11-21 17:15:16.119423: val_loss -0.7272 +2024-11-21 17:15:16.119505: Pseudo dice [0.8112] +2024-11-21 17:15:16.119592: Epoch time: 18.16 s +2024-11-21 17:15:17.435624: +2024-11-21 17:15:17.435832: Epoch 1210 +2024-11-21 17:15:17.435951: Current learning rate: 0.00863 +2024-11-21 17:15:35.826530: train_loss -0.7745 +2024-11-21 17:15:35.826788: val_loss -0.7548 +2024-11-21 17:15:35.826864: Pseudo dice [0.84] +2024-11-21 17:15:35.826945: Epoch time: 18.39 s +2024-11-21 17:15:36.653329: +2024-11-21 17:15:36.653542: Epoch 1211 +2024-11-21 17:15:36.653655: Current learning rate: 0.00863 +2024-11-21 17:15:56.124801: train_loss -0.7703 +2024-11-21 17:15:56.127226: val_loss -0.7599 +2024-11-21 17:15:56.127377: Pseudo dice [0.8501] +2024-11-21 17:15:56.127477: Epoch time: 19.47 s +2024-11-21 17:15:57.042298: +2024-11-21 17:15:57.042569: Epoch 1212 +2024-11-21 17:15:57.042686: Current learning rate: 0.00863 +2024-11-21 17:16:15.672146: train_loss -0.7691 +2024-11-21 17:16:15.672367: val_loss -0.7416 +2024-11-21 17:16:15.672446: Pseudo dice [0.8241] +2024-11-21 17:16:15.672550: Epoch time: 18.63 s +2024-11-21 17:16:16.513547: +2024-11-21 17:16:16.513744: Epoch 1213 +2024-11-21 17:16:16.513867: Current learning rate: 0.00862 +2024-11-21 17:16:35.129306: train_loss -0.7681 +2024-11-21 17:16:35.129550: val_loss -0.7247 +2024-11-21 17:16:35.129624: Pseudo dice [0.8323] +2024-11-21 17:16:35.129706: Epoch time: 18.62 s +2024-11-21 17:16:35.971210: +2024-11-21 17:16:35.971424: Epoch 1214 +2024-11-21 17:16:35.971537: Current learning rate: 0.00862 +2024-11-21 17:16:53.632958: train_loss -0.7604 +2024-11-21 17:16:53.633179: val_loss -0.739 +2024-11-21 17:16:53.633316: Pseudo dice [0.8345] +2024-11-21 17:16:53.633393: Epoch time: 17.66 s +2024-11-21 17:16:54.488998: +2024-11-21 17:16:54.489213: Epoch 1215 +2024-11-21 17:16:54.489327: Current learning rate: 0.00862 +2024-11-21 17:17:15.356142: train_loss -0.773 +2024-11-21 17:17:15.356356: val_loss -0.7269 +2024-11-21 17:17:15.356430: Pseudo dice [0.8512] +2024-11-21 17:17:15.356504: Epoch time: 20.87 s +2024-11-21 17:17:16.198306: +2024-11-21 17:17:16.198524: Epoch 1216 +2024-11-21 17:17:16.198636: Current learning rate: 0.00862 +2024-11-21 17:17:34.527923: train_loss -0.7696 +2024-11-21 17:17:34.533319: val_loss -0.724 +2024-11-21 17:17:34.533475: Pseudo dice [0.8231] +2024-11-21 17:17:34.533560: Epoch time: 18.33 s +2024-11-21 17:17:35.385318: +2024-11-21 17:17:35.385550: Epoch 1217 +2024-11-21 17:17:35.385667: Current learning rate: 0.00862 +2024-11-21 17:17:53.884489: train_loss -0.7704 +2024-11-21 17:17:53.884727: val_loss -0.7505 +2024-11-21 17:17:53.884803: Pseudo dice [0.8335] +2024-11-21 17:17:53.884884: Epoch time: 18.5 s +2024-11-21 17:17:54.731111: +2024-11-21 17:17:54.731302: Epoch 1218 +2024-11-21 17:17:54.731412: Current learning rate: 0.00862 +2024-11-21 17:18:13.831555: train_loss -0.7605 +2024-11-21 17:18:13.831763: val_loss -0.7061 +2024-11-21 17:18:13.831836: Pseudo dice [0.7942] +2024-11-21 17:18:13.831912: Epoch time: 19.1 s +2024-11-21 17:18:14.687496: +2024-11-21 17:18:14.687701: Epoch 1219 +2024-11-21 17:18:14.687813: Current learning rate: 0.00862 +2024-11-21 17:18:33.860340: train_loss -0.7336 +2024-11-21 17:18:33.860552: val_loss -0.7 +2024-11-21 17:18:33.860624: Pseudo dice [0.8144] +2024-11-21 17:18:33.860699: Epoch time: 19.17 s +2024-11-21 17:18:34.694830: +2024-11-21 17:18:34.695081: Epoch 1220 +2024-11-21 17:18:34.695198: Current learning rate: 0.00862 +2024-11-21 17:18:53.029402: train_loss -0.7676 +2024-11-21 17:18:53.029623: val_loss -0.7065 +2024-11-21 17:18:53.029699: Pseudo dice [0.8176] +2024-11-21 17:18:53.029777: Epoch time: 18.34 s +2024-11-21 17:18:53.932123: +2024-11-21 17:18:53.932365: Epoch 1221 +2024-11-21 17:18:53.932521: Current learning rate: 0.00862 +2024-11-21 17:19:12.962757: train_loss -0.7531 +2024-11-21 17:19:12.963039: val_loss -0.7276 +2024-11-21 17:19:12.963116: Pseudo dice [0.8125] +2024-11-21 17:19:12.963197: Epoch time: 19.03 s +2024-11-21 17:19:14.230355: +2024-11-21 17:19:14.230568: Epoch 1222 +2024-11-21 17:19:14.230681: Current learning rate: 0.00861 +2024-11-21 17:19:31.954924: train_loss -0.7539 +2024-11-21 17:19:31.955141: val_loss -0.7081 +2024-11-21 17:19:31.955215: Pseudo dice [0.8292] +2024-11-21 17:19:31.955291: Epoch time: 17.73 s +2024-11-21 17:19:32.786689: +2024-11-21 17:19:32.786997: Epoch 1223 +2024-11-21 17:19:32.787113: Current learning rate: 0.00861 +2024-11-21 17:19:52.548870: train_loss -0.7543 +2024-11-21 17:19:52.549098: val_loss -0.6996 +2024-11-21 17:19:52.549174: Pseudo dice [0.8135] +2024-11-21 17:19:52.549254: Epoch time: 19.76 s +2024-11-21 17:19:53.390271: +2024-11-21 17:19:53.390528: Epoch 1224 +2024-11-21 17:19:53.390642: Current learning rate: 0.00861 +2024-11-21 17:20:12.552153: train_loss -0.7581 +2024-11-21 17:20:12.552385: val_loss -0.7483 +2024-11-21 17:20:12.552458: Pseudo dice [0.845] +2024-11-21 17:20:12.552536: Epoch time: 19.16 s +2024-11-21 17:20:13.415370: +2024-11-21 17:20:13.415571: Epoch 1225 +2024-11-21 17:20:13.415680: Current learning rate: 0.00861 +2024-11-21 17:20:32.646073: train_loss -0.7731 +2024-11-21 17:20:32.646290: val_loss -0.7621 +2024-11-21 17:20:32.646362: Pseudo dice [0.8532] +2024-11-21 17:20:32.646447: Epoch time: 19.23 s +2024-11-21 17:20:33.479921: +2024-11-21 17:20:33.480134: Epoch 1226 +2024-11-21 17:20:33.480249: Current learning rate: 0.00861 +2024-11-21 17:20:51.819594: train_loss -0.7784 +2024-11-21 17:20:51.819806: val_loss -0.7229 +2024-11-21 17:20:51.819880: Pseudo dice [0.8362] +2024-11-21 17:20:51.819953: Epoch time: 18.34 s +2024-11-21 17:20:52.733003: +2024-11-21 17:20:52.733273: Epoch 1227 +2024-11-21 17:20:52.733388: Current learning rate: 0.00861 +2024-11-21 17:21:11.351372: train_loss -0.7609 +2024-11-21 17:21:11.353979: val_loss -0.7632 +2024-11-21 17:21:11.354080: Pseudo dice [0.8267] +2024-11-21 17:21:11.354167: Epoch time: 18.62 s +2024-11-21 17:21:12.293532: +2024-11-21 17:21:12.293756: Epoch 1228 +2024-11-21 17:21:12.293873: Current learning rate: 0.00861 +2024-11-21 17:21:31.414807: train_loss -0.7513 +2024-11-21 17:21:31.415028: val_loss -0.7103 +2024-11-21 17:21:31.415104: Pseudo dice [0.8264] +2024-11-21 17:21:31.415182: Epoch time: 19.12 s +2024-11-21 17:21:32.524110: +2024-11-21 17:21:32.524328: Epoch 1229 +2024-11-21 17:21:32.524439: Current learning rate: 0.00861 +2024-11-21 17:21:51.482213: train_loss -0.7584 +2024-11-21 17:21:51.482501: val_loss -0.7421 +2024-11-21 17:21:51.482585: Pseudo dice [0.8111] +2024-11-21 17:21:51.482664: Epoch time: 18.96 s +2024-11-21 17:21:52.321704: +2024-11-21 17:21:52.321937: Epoch 1230 +2024-11-21 17:21:52.322059: Current learning rate: 0.0086 +2024-11-21 17:22:11.180014: train_loss -0.7642 +2024-11-21 17:22:11.180264: val_loss -0.7032 +2024-11-21 17:22:11.180347: Pseudo dice [0.8227] +2024-11-21 17:22:11.180433: Epoch time: 18.86 s +2024-11-21 17:22:12.016396: +2024-11-21 17:22:12.016594: Epoch 1231 +2024-11-21 17:22:12.016702: Current learning rate: 0.0086 +2024-11-21 17:22:31.954494: train_loss -0.7617 +2024-11-21 17:22:31.959956: val_loss -0.7183 +2024-11-21 17:22:31.960076: Pseudo dice [0.8208] +2024-11-21 17:22:31.960165: Epoch time: 19.94 s +2024-11-21 17:22:33.054786: +2024-11-21 17:22:33.055017: Epoch 1232 +2024-11-21 17:22:33.055146: Current learning rate: 0.0086 +2024-11-21 17:22:51.603760: train_loss -0.7593 +2024-11-21 17:22:51.603979: val_loss -0.7171 +2024-11-21 17:22:51.604060: Pseudo dice [0.8215] +2024-11-21 17:22:51.604136: Epoch time: 18.55 s +2024-11-21 17:22:52.436453: +2024-11-21 17:22:52.436864: Epoch 1233 +2024-11-21 17:22:52.436998: Current learning rate: 0.0086 +2024-11-21 17:23:11.481975: train_loss -0.7706 +2024-11-21 17:23:11.482217: val_loss -0.7613 +2024-11-21 17:23:11.482317: Pseudo dice [0.8469] +2024-11-21 17:23:11.482503: Epoch time: 19.05 s +2024-11-21 17:23:12.330708: +2024-11-21 17:23:12.330920: Epoch 1234 +2024-11-21 17:23:12.331039: Current learning rate: 0.0086 +2024-11-21 17:23:31.888482: train_loss -0.7659 +2024-11-21 17:23:31.890870: val_loss -0.7389 +2024-11-21 17:23:31.890998: Pseudo dice [0.8458] +2024-11-21 17:23:31.891083: Epoch time: 19.56 s +2024-11-21 17:23:32.740958: +2024-11-21 17:23:32.741164: Epoch 1235 +2024-11-21 17:23:32.741280: Current learning rate: 0.0086 +2024-11-21 17:23:52.403248: train_loss -0.7677 +2024-11-21 17:23:52.403462: val_loss -0.7041 +2024-11-21 17:23:52.405732: Pseudo dice [0.8197] +2024-11-21 17:23:52.405836: Epoch time: 19.66 s +2024-11-21 17:23:53.294124: +2024-11-21 17:23:53.294394: Epoch 1236 +2024-11-21 17:23:53.294508: Current learning rate: 0.0086 +2024-11-21 17:24:12.162298: train_loss -0.769 +2024-11-21 17:24:12.162510: val_loss -0.7462 +2024-11-21 17:24:12.162582: Pseudo dice [0.8493] +2024-11-21 17:24:12.162658: Epoch time: 18.87 s +2024-11-21 17:24:12.998968: +2024-11-21 17:24:12.999190: Epoch 1237 +2024-11-21 17:24:12.999301: Current learning rate: 0.0086 +2024-11-21 17:24:31.553584: train_loss -0.7749 +2024-11-21 17:24:31.553828: val_loss -0.746 +2024-11-21 17:24:31.553912: Pseudo dice [0.8205] +2024-11-21 17:24:31.554044: Epoch time: 18.56 s +2024-11-21 17:24:32.544764: +2024-11-21 17:24:32.544978: Epoch 1238 +2024-11-21 17:24:32.545099: Current learning rate: 0.0086 +2024-11-21 17:24:52.279718: train_loss -0.7681 +2024-11-21 17:24:52.279937: val_loss -0.7275 +2024-11-21 17:24:52.280028: Pseudo dice [0.8238] +2024-11-21 17:24:52.280105: Epoch time: 19.74 s +2024-11-21 17:24:53.112238: +2024-11-21 17:24:53.112442: Epoch 1239 +2024-11-21 17:24:53.112556: Current learning rate: 0.00859 +2024-11-21 17:25:11.210005: train_loss -0.7789 +2024-11-21 17:25:11.210222: val_loss -0.7318 +2024-11-21 17:25:11.210299: Pseudo dice [0.8406] +2024-11-21 17:25:11.210377: Epoch time: 18.1 s +2024-11-21 17:25:12.046901: +2024-11-21 17:25:12.047117: Epoch 1240 +2024-11-21 17:25:12.047231: Current learning rate: 0.00859 +2024-11-21 17:25:31.472621: train_loss -0.7644 +2024-11-21 17:25:31.472836: val_loss -0.7218 +2024-11-21 17:25:31.472912: Pseudo dice [0.8207] +2024-11-21 17:25:31.472998: Epoch time: 19.43 s +2024-11-21 17:25:32.307279: +2024-11-21 17:25:32.307474: Epoch 1241 +2024-11-21 17:25:32.307587: Current learning rate: 0.00859 +2024-11-21 17:25:50.595345: train_loss -0.7716 +2024-11-21 17:25:50.599162: val_loss -0.7208 +2024-11-21 17:25:50.599368: Pseudo dice [0.8423] +2024-11-21 17:25:50.599457: Epoch time: 18.29 s +2024-11-21 17:25:51.552694: +2024-11-21 17:25:51.552977: Epoch 1242 +2024-11-21 17:25:51.553140: Current learning rate: 0.00859 +2024-11-21 17:26:09.870082: train_loss -0.7551 +2024-11-21 17:26:09.870307: val_loss -0.7313 +2024-11-21 17:26:09.870381: Pseudo dice [0.8331] +2024-11-21 17:26:09.870459: Epoch time: 18.32 s +2024-11-21 17:26:10.712019: +2024-11-21 17:26:10.712225: Epoch 1243 +2024-11-21 17:26:10.712336: Current learning rate: 0.00859 +2024-11-21 17:26:28.634405: train_loss -0.7658 +2024-11-21 17:26:28.634615: val_loss -0.7376 +2024-11-21 17:26:28.634691: Pseudo dice [0.8223] +2024-11-21 17:26:28.634766: Epoch time: 17.92 s +2024-11-21 17:26:29.472034: +2024-11-21 17:26:29.472229: Epoch 1244 +2024-11-21 17:26:29.472341: Current learning rate: 0.00859 +2024-11-21 17:26:47.555228: train_loss -0.7732 +2024-11-21 17:26:47.555421: val_loss -0.7341 +2024-11-21 17:26:47.555504: Pseudo dice [0.8362] +2024-11-21 17:26:47.555583: Epoch time: 18.08 s +2024-11-21 17:26:48.749267: +2024-11-21 17:26:48.749536: Epoch 1245 +2024-11-21 17:26:48.749658: Current learning rate: 0.00859 +2024-11-21 17:27:08.602378: train_loss -0.7709 +2024-11-21 17:27:08.602608: val_loss -0.7687 +2024-11-21 17:27:08.602682: Pseudo dice [0.8603] +2024-11-21 17:27:08.602767: Epoch time: 19.85 s +2024-11-21 17:27:09.468744: +2024-11-21 17:27:09.468967: Epoch 1246 +2024-11-21 17:27:09.469084: Current learning rate: 0.00859 +2024-11-21 17:27:27.967590: train_loss -0.7637 +2024-11-21 17:27:27.967816: val_loss -0.7125 +2024-11-21 17:27:27.967893: Pseudo dice [0.8395] +2024-11-21 17:27:27.967974: Epoch time: 18.5 s +2024-11-21 17:27:28.810782: +2024-11-21 17:27:28.811001: Epoch 1247 +2024-11-21 17:27:28.811116: Current learning rate: 0.00859 +2024-11-21 17:27:47.515101: train_loss -0.7692 +2024-11-21 17:27:47.515316: val_loss -0.7502 +2024-11-21 17:27:47.515392: Pseudo dice [0.8648] +2024-11-21 17:27:47.515472: Epoch time: 18.71 s +2024-11-21 17:27:48.348034: +2024-11-21 17:27:48.348400: Epoch 1248 +2024-11-21 17:27:48.348517: Current learning rate: 0.00858 +2024-11-21 17:28:05.776889: train_loss -0.7774 +2024-11-21 17:28:05.777153: val_loss -0.7433 +2024-11-21 17:28:05.777238: Pseudo dice [0.8442] +2024-11-21 17:28:05.777340: Epoch time: 17.43 s +2024-11-21 17:28:06.616786: +2024-11-21 17:28:06.616998: Epoch 1249 +2024-11-21 17:28:06.617110: Current learning rate: 0.00858 +2024-11-21 17:28:24.797354: train_loss -0.7747 +2024-11-21 17:28:24.797569: val_loss -0.7231 +2024-11-21 17:28:24.797646: Pseudo dice [0.8474] +2024-11-21 17:28:24.797721: Epoch time: 18.18 s +2024-11-21 17:28:25.872115: +2024-11-21 17:28:25.872331: Epoch 1250 +2024-11-21 17:28:25.872443: Current learning rate: 0.00858 +2024-11-21 17:28:43.884728: train_loss -0.7735 +2024-11-21 17:28:43.884938: val_loss -0.736 +2024-11-21 17:28:43.885020: Pseudo dice [0.815] +2024-11-21 17:28:43.885097: Epoch time: 18.01 s +2024-11-21 17:28:44.714663: +2024-11-21 17:28:44.714879: Epoch 1251 +2024-11-21 17:28:44.714990: Current learning rate: 0.00858 +2024-11-21 17:29:03.370096: train_loss -0.7823 +2024-11-21 17:29:03.370315: val_loss -0.759 +2024-11-21 17:29:03.370392: Pseudo dice [0.8209] +2024-11-21 17:29:03.370477: Epoch time: 18.66 s +2024-11-21 17:29:04.208580: +2024-11-21 17:29:04.208791: Epoch 1252 +2024-11-21 17:29:04.208897: Current learning rate: 0.00858 +2024-11-21 17:29:23.943839: train_loss -0.7794 +2024-11-21 17:29:23.944082: val_loss -0.7312 +2024-11-21 17:29:23.944161: Pseudo dice [0.8665] +2024-11-21 17:29:23.944240: Epoch time: 19.74 s +2024-11-21 17:29:24.772517: +2024-11-21 17:29:24.772710: Epoch 1253 +2024-11-21 17:29:24.772819: Current learning rate: 0.00858 +2024-11-21 17:29:43.288714: train_loss -0.7773 +2024-11-21 17:29:43.288920: val_loss -0.7318 +2024-11-21 17:29:43.289003: Pseudo dice [0.8412] +2024-11-21 17:29:43.289078: Epoch time: 18.52 s +2024-11-21 17:29:44.119070: +2024-11-21 17:29:44.119277: Epoch 1254 +2024-11-21 17:29:44.119388: Current learning rate: 0.00858 +2024-11-21 17:30:03.605491: train_loss -0.7734 +2024-11-21 17:30:03.605681: val_loss -0.7514 +2024-11-21 17:30:03.605755: Pseudo dice [0.846] +2024-11-21 17:30:03.605886: Epoch time: 19.49 s +2024-11-21 17:30:04.437945: +2024-11-21 17:30:04.438202: Epoch 1255 +2024-11-21 17:30:04.438313: Current learning rate: 0.00858 +2024-11-21 17:30:22.861082: train_loss -0.7601 +2024-11-21 17:30:22.861314: val_loss -0.7442 +2024-11-21 17:30:22.861388: Pseudo dice [0.8327] +2024-11-21 17:30:22.861468: Epoch time: 18.42 s +2024-11-21 17:30:23.968410: +2024-11-21 17:30:23.968620: Epoch 1256 +2024-11-21 17:30:23.968732: Current learning rate: 0.00858 +2024-11-21 17:30:43.146023: train_loss -0.7533 +2024-11-21 17:30:43.146225: val_loss -0.7489 +2024-11-21 17:30:43.146304: Pseudo dice [0.83] +2024-11-21 17:30:43.146381: Epoch time: 19.18 s +2024-11-21 17:30:43.979708: +2024-11-21 17:30:43.979908: Epoch 1257 +2024-11-21 17:30:43.980026: Current learning rate: 0.00857 +2024-11-21 17:31:02.284440: train_loss -0.7643 +2024-11-21 17:31:02.284655: val_loss -0.7426 +2024-11-21 17:31:02.284731: Pseudo dice [0.838] +2024-11-21 17:31:02.284807: Epoch time: 18.31 s +2024-11-21 17:31:03.118399: +2024-11-21 17:31:03.118627: Epoch 1258 +2024-11-21 17:31:03.118735: Current learning rate: 0.00857 +2024-11-21 17:31:20.766398: train_loss -0.7804 +2024-11-21 17:31:20.766637: val_loss -0.7704 +2024-11-21 17:31:20.768915: Pseudo dice [0.8382] +2024-11-21 17:31:20.769031: Epoch time: 17.65 s +2024-11-21 17:31:21.689249: +2024-11-21 17:31:21.689450: Epoch 1259 +2024-11-21 17:31:21.689559: Current learning rate: 0.00857 +2024-11-21 17:31:41.057601: train_loss -0.7735 +2024-11-21 17:31:41.057811: val_loss -0.7362 +2024-11-21 17:31:41.057974: Pseudo dice [0.8262] +2024-11-21 17:31:41.058059: Epoch time: 19.37 s +2024-11-21 17:31:41.901682: +2024-11-21 17:31:41.901899: Epoch 1260 +2024-11-21 17:31:41.902020: Current learning rate: 0.00857 +2024-11-21 17:32:01.044425: train_loss -0.7674 +2024-11-21 17:32:01.044702: val_loss -0.749 +2024-11-21 17:32:01.044779: Pseudo dice [0.848] +2024-11-21 17:32:01.044854: Epoch time: 19.14 s +2024-11-21 17:32:01.874165: +2024-11-21 17:32:01.874366: Epoch 1261 +2024-11-21 17:32:01.874478: Current learning rate: 0.00857 +2024-11-21 17:32:18.960113: train_loss -0.7702 +2024-11-21 17:32:18.960333: val_loss -0.7481 +2024-11-21 17:32:18.960409: Pseudo dice [0.8282] +2024-11-21 17:32:18.960507: Epoch time: 17.09 s +2024-11-21 17:32:19.936475: +2024-11-21 17:32:19.936683: Epoch 1262 +2024-11-21 17:32:19.936796: Current learning rate: 0.00857 +2024-11-21 17:32:37.570396: train_loss -0.7718 +2024-11-21 17:32:37.570648: val_loss -0.7507 +2024-11-21 17:32:37.570724: Pseudo dice [0.8551] +2024-11-21 17:32:37.570807: Epoch time: 17.63 s +2024-11-21 17:32:38.406869: +2024-11-21 17:32:38.407102: Epoch 1263 +2024-11-21 17:32:38.407220: Current learning rate: 0.00857 +2024-11-21 17:32:56.624908: train_loss -0.7528 +2024-11-21 17:32:56.625170: val_loss -0.731 +2024-11-21 17:32:56.625247: Pseudo dice [0.8315] +2024-11-21 17:32:56.625327: Epoch time: 18.21 s +2024-11-21 17:32:57.660303: +2024-11-21 17:32:57.660513: Epoch 1264 +2024-11-21 17:32:57.660633: Current learning rate: 0.00857 +2024-11-21 17:33:16.891817: train_loss -0.7567 +2024-11-21 17:33:16.892045: val_loss -0.7337 +2024-11-21 17:33:16.892123: Pseudo dice [0.8325] +2024-11-21 17:33:16.892199: Epoch time: 19.23 s +2024-11-21 17:33:17.723584: +2024-11-21 17:33:17.723853: Epoch 1265 +2024-11-21 17:33:17.723988: Current learning rate: 0.00856 +2024-11-21 17:33:36.310156: train_loss -0.7668 +2024-11-21 17:33:36.310368: val_loss -0.7328 +2024-11-21 17:33:36.310442: Pseudo dice [0.8214] +2024-11-21 17:33:36.310519: Epoch time: 18.59 s +2024-11-21 17:33:37.146690: +2024-11-21 17:33:37.146908: Epoch 1266 +2024-11-21 17:33:37.147026: Current learning rate: 0.00856 +2024-11-21 17:33:56.353844: train_loss -0.7556 +2024-11-21 17:33:56.359233: val_loss -0.7307 +2024-11-21 17:33:56.359348: Pseudo dice [0.8321] +2024-11-21 17:33:56.359430: Epoch time: 19.21 s +2024-11-21 17:33:57.685277: +2024-11-21 17:33:57.685462: Epoch 1267 +2024-11-21 17:33:57.685573: Current learning rate: 0.00856 +2024-11-21 17:34:16.378217: train_loss -0.7699 +2024-11-21 17:34:16.380141: val_loss -0.7664 +2024-11-21 17:34:16.380246: Pseudo dice [0.8268] +2024-11-21 17:34:16.380322: Epoch time: 18.69 s +2024-11-21 17:34:17.221151: +2024-11-21 17:34:17.221370: Epoch 1268 +2024-11-21 17:34:17.221483: Current learning rate: 0.00856 +2024-11-21 17:34:35.950578: train_loss -0.7674 +2024-11-21 17:34:35.950849: val_loss -0.7248 +2024-11-21 17:34:35.950924: Pseudo dice [0.8363] +2024-11-21 17:34:35.951008: Epoch time: 18.73 s +2024-11-21 17:34:36.785897: +2024-11-21 17:34:36.786123: Epoch 1269 +2024-11-21 17:34:36.786241: Current learning rate: 0.00856 +2024-11-21 17:34:54.856748: train_loss -0.7587 +2024-11-21 17:34:54.857023: val_loss -0.7296 +2024-11-21 17:34:54.857103: Pseudo dice [0.8318] +2024-11-21 17:34:54.857187: Epoch time: 18.07 s +2024-11-21 17:34:55.767571: +2024-11-21 17:34:55.767819: Epoch 1270 +2024-11-21 17:34:55.767933: Current learning rate: 0.00856 +2024-11-21 17:35:14.108513: train_loss -0.7648 +2024-11-21 17:35:14.108731: val_loss -0.7375 +2024-11-21 17:35:14.108810: Pseudo dice [0.8403] +2024-11-21 17:35:14.108888: Epoch time: 18.34 s +2024-11-21 17:35:14.945360: +2024-11-21 17:35:14.945584: Epoch 1271 +2024-11-21 17:35:14.945701: Current learning rate: 0.00856 +2024-11-21 17:35:34.295975: train_loss -0.7494 +2024-11-21 17:35:34.296191: val_loss -0.7404 +2024-11-21 17:35:34.296268: Pseudo dice [0.8505] +2024-11-21 17:35:34.296346: Epoch time: 19.35 s +2024-11-21 17:35:35.134291: +2024-11-21 17:35:35.134500: Epoch 1272 +2024-11-21 17:35:35.134612: Current learning rate: 0.00856 +2024-11-21 17:35:53.695987: train_loss -0.7637 +2024-11-21 17:35:53.701415: val_loss -0.7301 +2024-11-21 17:35:53.701496: Pseudo dice [0.83] +2024-11-21 17:35:53.701581: Epoch time: 18.56 s +2024-11-21 17:35:54.668923: +2024-11-21 17:35:54.669155: Epoch 1273 +2024-11-21 17:35:54.669286: Current learning rate: 0.00856 +2024-11-21 17:36:12.851019: train_loss -0.7671 +2024-11-21 17:36:12.851236: val_loss -0.7244 +2024-11-21 17:36:12.851311: Pseudo dice [0.8233] +2024-11-21 17:36:12.851386: Epoch time: 18.18 s +2024-11-21 17:36:13.680854: +2024-11-21 17:36:13.681134: Epoch 1274 +2024-11-21 17:36:13.681252: Current learning rate: 0.00855 +2024-11-21 17:36:32.980971: train_loss -0.7704 +2024-11-21 17:36:32.981193: val_loss -0.7361 +2024-11-21 17:36:32.981270: Pseudo dice [0.836] +2024-11-21 17:36:32.981347: Epoch time: 19.3 s +2024-11-21 17:36:33.958921: +2024-11-21 17:36:33.959131: Epoch 1275 +2024-11-21 17:36:33.959243: Current learning rate: 0.00855 +2024-11-21 17:36:51.945122: train_loss -0.7507 +2024-11-21 17:36:51.945344: val_loss -0.7404 +2024-11-21 17:36:51.945426: Pseudo dice [0.8461] +2024-11-21 17:36:51.945502: Epoch time: 17.99 s +2024-11-21 17:36:52.781577: +2024-11-21 17:36:52.781765: Epoch 1276 +2024-11-21 17:36:52.781877: Current learning rate: 0.00855 +2024-11-21 17:37:10.764740: train_loss -0.7614 +2024-11-21 17:37:10.764987: val_loss -0.7697 +2024-11-21 17:37:10.765070: Pseudo dice [0.859] +2024-11-21 17:37:10.765157: Epoch time: 17.98 s +2024-11-21 17:37:11.617250: +2024-11-21 17:37:11.617517: Epoch 1277 +2024-11-21 17:37:11.617633: Current learning rate: 0.00855 +2024-11-21 17:37:29.190690: train_loss -0.7673 +2024-11-21 17:37:29.190908: val_loss -0.729 +2024-11-21 17:37:29.190986: Pseudo dice [0.8516] +2024-11-21 17:37:29.191071: Epoch time: 17.57 s +2024-11-21 17:37:30.024916: +2024-11-21 17:37:30.025153: Epoch 1278 +2024-11-21 17:37:30.025271: Current learning rate: 0.00855 +2024-11-21 17:37:48.126184: train_loss -0.7664 +2024-11-21 17:37:48.126432: val_loss -0.7689 +2024-11-21 17:37:48.126509: Pseudo dice [0.8396] +2024-11-21 17:37:48.126585: Epoch time: 18.1 s +2024-11-21 17:37:49.382707: +2024-11-21 17:37:49.382938: Epoch 1279 +2024-11-21 17:37:49.383055: Current learning rate: 0.00855 +2024-11-21 17:38:08.189114: train_loss -0.7814 +2024-11-21 17:38:08.189371: val_loss -0.7401 +2024-11-21 17:38:08.189447: Pseudo dice [0.8144] +2024-11-21 17:38:08.189533: Epoch time: 18.81 s +2024-11-21 17:38:09.032928: +2024-11-21 17:38:09.033320: Epoch 1280 +2024-11-21 17:38:09.033437: Current learning rate: 0.00855 +2024-11-21 17:38:27.091142: train_loss -0.787 +2024-11-21 17:38:27.091353: val_loss -0.7558 +2024-11-21 17:38:27.091424: Pseudo dice [0.8512] +2024-11-21 17:38:27.091520: Epoch time: 18.06 s +2024-11-21 17:38:27.923017: +2024-11-21 17:38:27.923243: Epoch 1281 +2024-11-21 17:38:27.923356: Current learning rate: 0.00855 +2024-11-21 17:38:47.070230: train_loss -0.7758 +2024-11-21 17:38:47.070442: val_loss -0.7357 +2024-11-21 17:38:47.070515: Pseudo dice [0.847] +2024-11-21 17:38:47.075843: Epoch time: 19.15 s +2024-11-21 17:38:48.094831: +2024-11-21 17:38:48.095054: Epoch 1282 +2024-11-21 17:38:48.095168: Current learning rate: 0.00855 +2024-11-21 17:39:06.826902: train_loss -0.7712 +2024-11-21 17:39:06.827175: val_loss -0.7245 +2024-11-21 17:39:06.827253: Pseudo dice [0.8431] +2024-11-21 17:39:06.827335: Epoch time: 18.73 s +2024-11-21 17:39:07.665760: +2024-11-21 17:39:07.665983: Epoch 1283 +2024-11-21 17:39:07.666102: Current learning rate: 0.00854 +2024-11-21 17:39:26.242108: train_loss -0.7748 +2024-11-21 17:39:26.242324: val_loss -0.7212 +2024-11-21 17:39:26.242459: Pseudo dice [0.8366] +2024-11-21 17:39:26.242542: Epoch time: 18.58 s +2024-11-21 17:39:27.159038: +2024-11-21 17:39:27.159251: Epoch 1284 +2024-11-21 17:39:27.159363: Current learning rate: 0.00854 +2024-11-21 17:39:44.680182: train_loss -0.7722 +2024-11-21 17:39:44.680398: val_loss -0.759 +2024-11-21 17:39:44.680487: Pseudo dice [0.8266] +2024-11-21 17:39:44.680619: Epoch time: 17.52 s +2024-11-21 17:39:45.513328: +2024-11-21 17:39:45.513547: Epoch 1285 +2024-11-21 17:39:45.513659: Current learning rate: 0.00854 +2024-11-21 17:40:03.519128: train_loss -0.7668 +2024-11-21 17:40:03.519359: val_loss -0.742 +2024-11-21 17:40:03.519441: Pseudo dice [0.8342] +2024-11-21 17:40:03.519521: Epoch time: 18.01 s +2024-11-21 17:40:04.363714: +2024-11-21 17:40:04.363910: Epoch 1286 +2024-11-21 17:40:04.364546: Current learning rate: 0.00854 +2024-11-21 17:40:23.709860: train_loss -0.7618 +2024-11-21 17:40:23.710112: val_loss -0.726 +2024-11-21 17:40:23.710188: Pseudo dice [0.8249] +2024-11-21 17:40:23.710267: Epoch time: 19.35 s +2024-11-21 17:40:24.544939: +2024-11-21 17:40:24.545136: Epoch 1287 +2024-11-21 17:40:24.545247: Current learning rate: 0.00854 +2024-11-21 17:40:43.423970: train_loss -0.761 +2024-11-21 17:40:43.424248: val_loss -0.7237 +2024-11-21 17:40:43.424326: Pseudo dice [0.814] +2024-11-21 17:40:43.424402: Epoch time: 18.88 s +2024-11-21 17:40:44.355440: +2024-11-21 17:40:44.355705: Epoch 1288 +2024-11-21 17:40:44.355821: Current learning rate: 0.00854 +2024-11-21 17:41:02.219239: train_loss -0.7687 +2024-11-21 17:41:02.219446: val_loss -0.731 +2024-11-21 17:41:02.219520: Pseudo dice [0.8347] +2024-11-21 17:41:02.219597: Epoch time: 17.86 s +2024-11-21 17:41:03.087501: +2024-11-21 17:41:03.087772: Epoch 1289 +2024-11-21 17:41:03.087887: Current learning rate: 0.00854 +2024-11-21 17:41:20.927277: train_loss -0.7651 +2024-11-21 17:41:20.927520: val_loss -0.7342 +2024-11-21 17:41:20.927596: Pseudo dice [0.8326] +2024-11-21 17:41:20.927677: Epoch time: 17.84 s +2024-11-21 17:41:21.868019: +2024-11-21 17:41:21.868227: Epoch 1290 +2024-11-21 17:41:21.868344: Current learning rate: 0.00854 +2024-11-21 17:41:40.422494: train_loss -0.7835 +2024-11-21 17:41:40.422714: val_loss -0.7478 +2024-11-21 17:41:40.422792: Pseudo dice [0.8216] +2024-11-21 17:41:40.422885: Epoch time: 18.56 s +2024-11-21 17:41:41.252097: +2024-11-21 17:41:41.252327: Epoch 1291 +2024-11-21 17:41:41.252443: Current learning rate: 0.00854 +2024-11-21 17:41:59.316552: train_loss -0.7701 +2024-11-21 17:41:59.316772: val_loss -0.7335 +2024-11-21 17:41:59.316849: Pseudo dice [0.8339] +2024-11-21 17:41:59.316937: Epoch time: 18.07 s +2024-11-21 17:42:00.154012: +2024-11-21 17:42:00.154227: Epoch 1292 +2024-11-21 17:42:00.154340: Current learning rate: 0.00853 +2024-11-21 17:42:19.181819: train_loss -0.7601 +2024-11-21 17:42:19.182092: val_loss -0.6967 +2024-11-21 17:42:19.182170: Pseudo dice [0.8063] +2024-11-21 17:42:19.182254: Epoch time: 19.03 s +2024-11-21 17:42:20.010155: +2024-11-21 17:42:20.010419: Epoch 1293 +2024-11-21 17:42:20.010534: Current learning rate: 0.00853 +2024-11-21 17:42:38.681622: train_loss -0.7468 +2024-11-21 17:42:38.681846: val_loss -0.7167 +2024-11-21 17:42:38.681919: Pseudo dice [0.8258] +2024-11-21 17:42:38.682001: Epoch time: 18.67 s +2024-11-21 17:42:39.690174: +2024-11-21 17:42:39.690429: Epoch 1294 +2024-11-21 17:42:39.690544: Current learning rate: 0.00853 +2024-11-21 17:42:57.920189: train_loss -0.7388 +2024-11-21 17:42:57.920404: val_loss -0.718 +2024-11-21 17:42:57.920481: Pseudo dice [0.8369] +2024-11-21 17:42:57.920562: Epoch time: 18.23 s +2024-11-21 17:42:58.767049: +2024-11-21 17:42:58.767282: Epoch 1295 +2024-11-21 17:42:58.767400: Current learning rate: 0.00853 +2024-11-21 17:43:16.186836: train_loss -0.7674 +2024-11-21 17:43:16.187070: val_loss -0.7428 +2024-11-21 17:43:16.187148: Pseudo dice [0.8341] +2024-11-21 17:43:16.187231: Epoch time: 17.42 s +2024-11-21 17:43:17.056487: +2024-11-21 17:43:17.056690: Epoch 1296 +2024-11-21 17:43:17.056801: Current learning rate: 0.00853 +2024-11-21 17:43:35.658506: train_loss -0.7697 +2024-11-21 17:43:35.658751: val_loss -0.73 +2024-11-21 17:43:35.658829: Pseudo dice [0.8242] +2024-11-21 17:43:35.658929: Epoch time: 18.6 s +2024-11-21 17:43:36.495925: +2024-11-21 17:43:36.496144: Epoch 1297 +2024-11-21 17:43:36.496258: Current learning rate: 0.00853 +2024-11-21 17:43:54.849955: train_loss -0.7736 +2024-11-21 17:43:54.850179: val_loss -0.7629 +2024-11-21 17:43:54.850269: Pseudo dice [0.8305] +2024-11-21 17:43:54.850404: Epoch time: 18.35 s +2024-11-21 17:43:55.685246: +2024-11-21 17:43:55.685454: Epoch 1298 +2024-11-21 17:43:55.685567: Current learning rate: 0.00853 +2024-11-21 17:44:14.330447: train_loss -0.7624 +2024-11-21 17:44:14.330672: val_loss -0.7212 +2024-11-21 17:44:14.330747: Pseudo dice [0.8326] +2024-11-21 17:44:14.330825: Epoch time: 18.65 s +2024-11-21 17:44:15.161567: +2024-11-21 17:44:15.161759: Epoch 1299 +2024-11-21 17:44:15.161872: Current learning rate: 0.00853 +2024-11-21 17:44:33.325925: train_loss -0.7567 +2024-11-21 17:44:33.326145: val_loss -0.7177 +2024-11-21 17:44:33.326222: Pseudo dice [0.831] +2024-11-21 17:44:33.326298: Epoch time: 18.17 s +2024-11-21 17:44:34.349099: +2024-11-21 17:44:34.349347: Epoch 1300 +2024-11-21 17:44:34.349472: Current learning rate: 0.00852 +2024-11-21 17:44:53.262019: train_loss -0.7661 +2024-11-21 17:44:53.262287: val_loss -0.7385 +2024-11-21 17:44:53.262366: Pseudo dice [0.8196] +2024-11-21 17:44:53.262449: Epoch time: 18.91 s +2024-11-21 17:44:54.101866: +2024-11-21 17:44:54.102141: Epoch 1301 +2024-11-21 17:44:54.102256: Current learning rate: 0.00852 +2024-11-21 17:45:12.240198: train_loss -0.7775 +2024-11-21 17:45:12.240422: val_loss -0.7647 +2024-11-21 17:45:12.240494: Pseudo dice [0.8433] +2024-11-21 17:45:12.240567: Epoch time: 18.14 s +2024-11-21 17:45:13.079511: +2024-11-21 17:45:13.079729: Epoch 1302 +2024-11-21 17:45:13.079838: Current learning rate: 0.00852 +2024-11-21 17:45:32.575034: train_loss -0.7354 +2024-11-21 17:45:32.575253: val_loss -0.7133 +2024-11-21 17:45:32.575325: Pseudo dice [0.8143] +2024-11-21 17:45:32.575400: Epoch time: 19.5 s +2024-11-21 17:45:33.514601: +2024-11-21 17:45:33.514825: Epoch 1303 +2024-11-21 17:45:33.514936: Current learning rate: 0.00852 +2024-11-21 17:45:52.914915: train_loss -0.7425 +2024-11-21 17:45:52.915215: val_loss -0.74 +2024-11-21 17:45:52.915298: Pseudo dice [0.8194] +2024-11-21 17:45:52.915383: Epoch time: 19.4 s +2024-11-21 17:45:53.755624: +2024-11-21 17:45:53.755855: Epoch 1304 +2024-11-21 17:45:53.755968: Current learning rate: 0.00852 +2024-11-21 17:46:11.710615: train_loss -0.7527 +2024-11-21 17:46:11.710819: val_loss -0.7462 +2024-11-21 17:46:11.710894: Pseudo dice [0.8451] +2024-11-21 17:46:11.710967: Epoch time: 17.96 s +2024-11-21 17:46:12.554115: +2024-11-21 17:46:12.554350: Epoch 1305 +2024-11-21 17:46:12.554464: Current learning rate: 0.00852 +2024-11-21 17:46:31.110301: train_loss -0.76 +2024-11-21 17:46:31.110524: val_loss -0.7225 +2024-11-21 17:46:31.110597: Pseudo dice [0.7979] +2024-11-21 17:46:31.110811: Epoch time: 18.56 s +2024-11-21 17:46:31.948837: +2024-11-21 17:46:31.949055: Epoch 1306 +2024-11-21 17:46:31.949170: Current learning rate: 0.00852 +2024-11-21 17:46:52.044102: train_loss -0.7496 +2024-11-21 17:46:52.044315: val_loss -0.7375 +2024-11-21 17:46:52.044388: Pseudo dice [0.8231] +2024-11-21 17:46:52.044465: Epoch time: 20.1 s +2024-11-21 17:46:52.948548: +2024-11-21 17:46:52.948772: Epoch 1307 +2024-11-21 17:46:52.948897: Current learning rate: 0.00852 +2024-11-21 17:47:12.048780: train_loss -0.758 +2024-11-21 17:47:12.049037: val_loss -0.7221 +2024-11-21 17:47:12.049116: Pseudo dice [0.8325] +2024-11-21 17:47:12.049203: Epoch time: 19.1 s +2024-11-21 17:47:12.892320: +2024-11-21 17:47:12.892523: Epoch 1308 +2024-11-21 17:47:12.892634: Current learning rate: 0.00852 +2024-11-21 17:47:31.215820: train_loss -0.7718 +2024-11-21 17:47:31.216089: val_loss -0.7385 +2024-11-21 17:47:31.216167: Pseudo dice [0.832] +2024-11-21 17:47:31.216245: Epoch time: 18.32 s +2024-11-21 17:47:32.055893: +2024-11-21 17:47:32.056112: Epoch 1309 +2024-11-21 17:47:32.056228: Current learning rate: 0.00851 +2024-11-21 17:47:51.627820: train_loss -0.7616 +2024-11-21 17:47:51.628037: val_loss -0.7145 +2024-11-21 17:47:51.628111: Pseudo dice [0.8211] +2024-11-21 17:47:51.628188: Epoch time: 19.57 s +2024-11-21 17:47:52.468720: +2024-11-21 17:47:52.468929: Epoch 1310 +2024-11-21 17:47:52.469050: Current learning rate: 0.00851 +2024-11-21 17:48:12.119267: train_loss -0.7585 +2024-11-21 17:48:12.119491: val_loss -0.7451 +2024-11-21 17:48:12.119569: Pseudo dice [0.825] +2024-11-21 17:48:12.119649: Epoch time: 19.65 s +2024-11-21 17:48:13.000491: +2024-11-21 17:48:13.000706: Epoch 1311 +2024-11-21 17:48:13.000817: Current learning rate: 0.00851 +2024-11-21 17:48:31.920616: train_loss -0.7651 +2024-11-21 17:48:31.920858: val_loss -0.7464 +2024-11-21 17:48:31.920932: Pseudo dice [0.8468] +2024-11-21 17:48:31.921018: Epoch time: 18.92 s +2024-11-21 17:48:32.756254: +2024-11-21 17:48:32.756476: Epoch 1312 +2024-11-21 17:48:32.756761: Current learning rate: 0.00851 +2024-11-21 17:48:52.695972: train_loss -0.7608 +2024-11-21 17:48:52.696185: val_loss -0.7593 +2024-11-21 17:48:52.696263: Pseudo dice [0.8274] +2024-11-21 17:48:52.696340: Epoch time: 19.94 s +2024-11-21 17:48:53.909723: +2024-11-21 17:48:53.909968: Epoch 1313 +2024-11-21 17:48:53.910091: Current learning rate: 0.00851 +2024-11-21 17:49:12.503058: train_loss -0.7746 +2024-11-21 17:49:12.503283: val_loss -0.7504 +2024-11-21 17:49:12.503367: Pseudo dice [0.844] +2024-11-21 17:49:12.503460: Epoch time: 18.59 s +2024-11-21 17:49:13.343207: +2024-11-21 17:49:13.343421: Epoch 1314 +2024-11-21 17:49:13.343532: Current learning rate: 0.00851 +2024-11-21 17:49:32.836622: train_loss -0.7709 +2024-11-21 17:49:32.836899: val_loss -0.7122 +2024-11-21 17:49:32.836974: Pseudo dice [0.8179] +2024-11-21 17:49:32.837062: Epoch time: 19.49 s +2024-11-21 17:49:33.672092: +2024-11-21 17:49:33.672389: Epoch 1315 +2024-11-21 17:49:33.672508: Current learning rate: 0.00851 +2024-11-21 17:49:52.317815: train_loss -0.7757 +2024-11-21 17:49:52.318047: val_loss -0.7455 +2024-11-21 17:49:52.318125: Pseudo dice [0.8456] +2024-11-21 17:49:52.318202: Epoch time: 18.65 s +2024-11-21 17:49:53.163205: +2024-11-21 17:49:53.163413: Epoch 1316 +2024-11-21 17:49:53.163520: Current learning rate: 0.00851 +2024-11-21 17:50:12.629238: train_loss -0.7784 +2024-11-21 17:50:12.629450: val_loss -0.7325 +2024-11-21 17:50:12.629522: Pseudo dice [0.8288] +2024-11-21 17:50:12.629598: Epoch time: 19.47 s +2024-11-21 17:50:13.494237: +2024-11-21 17:50:13.494466: Epoch 1317 +2024-11-21 17:50:13.494584: Current learning rate: 0.00851 +2024-11-21 17:50:32.594507: train_loss -0.766 +2024-11-21 17:50:32.594709: val_loss -0.7373 +2024-11-21 17:50:32.594784: Pseudo dice [0.8364] +2024-11-21 17:50:32.594861: Epoch time: 19.1 s +2024-11-21 17:50:33.429071: +2024-11-21 17:50:33.429378: Epoch 1318 +2024-11-21 17:50:33.429495: Current learning rate: 0.0085 +2024-11-21 17:50:52.594111: train_loss -0.7717 +2024-11-21 17:50:52.594348: val_loss -0.7408 +2024-11-21 17:50:52.594423: Pseudo dice [0.8267] +2024-11-21 17:50:52.594503: Epoch time: 19.17 s +2024-11-21 17:50:53.533834: +2024-11-21 17:50:53.534063: Epoch 1319 +2024-11-21 17:50:53.534181: Current learning rate: 0.0085 +2024-11-21 17:51:12.019499: train_loss -0.7728 +2024-11-21 17:51:12.019701: val_loss -0.7407 +2024-11-21 17:51:12.019775: Pseudo dice [0.8353] +2024-11-21 17:51:12.019848: Epoch time: 18.49 s +2024-11-21 17:51:12.852330: +2024-11-21 17:51:12.852597: Epoch 1320 +2024-11-21 17:51:12.852710: Current learning rate: 0.0085 +2024-11-21 17:51:31.609881: train_loss -0.7658 +2024-11-21 17:51:31.610121: val_loss -0.7542 +2024-11-21 17:51:31.610192: Pseudo dice [0.8321] +2024-11-21 17:51:31.610269: Epoch time: 18.76 s +2024-11-21 17:51:32.447690: +2024-11-21 17:51:32.447889: Epoch 1321 +2024-11-21 17:51:32.448010: Current learning rate: 0.0085 +2024-11-21 17:51:51.267605: train_loss -0.766 +2024-11-21 17:51:51.267815: val_loss -0.7422 +2024-11-21 17:51:51.267950: Pseudo dice [0.8534] +2024-11-21 17:51:51.268035: Epoch time: 18.82 s +2024-11-21 17:51:52.207956: +2024-11-21 17:51:52.208184: Epoch 1322 +2024-11-21 17:51:52.208311: Current learning rate: 0.0085 +2024-11-21 17:52:11.505573: train_loss -0.7663 +2024-11-21 17:52:11.505835: val_loss -0.7282 +2024-11-21 17:52:11.505911: Pseudo dice [0.8221] +2024-11-21 17:52:11.506059: Epoch time: 19.3 s +2024-11-21 17:52:12.375839: +2024-11-21 17:52:12.376053: Epoch 1323 +2024-11-21 17:52:12.376169: Current learning rate: 0.0085 +2024-11-21 17:52:30.986811: train_loss -0.7633 +2024-11-21 17:52:30.987034: val_loss -0.7413 +2024-11-21 17:52:30.987116: Pseudo dice [0.8566] +2024-11-21 17:52:30.987193: Epoch time: 18.61 s +2024-11-21 17:52:32.234496: +2024-11-21 17:52:32.234683: Epoch 1324 +2024-11-21 17:52:32.234790: Current learning rate: 0.0085 +2024-11-21 17:52:51.285378: train_loss -0.7662 +2024-11-21 17:52:51.285587: val_loss -0.7323 +2024-11-21 17:52:51.285664: Pseudo dice [0.8522] +2024-11-21 17:52:51.285739: Epoch time: 19.05 s +2024-11-21 17:52:52.117739: +2024-11-21 17:52:52.117940: Epoch 1325 +2024-11-21 17:52:52.118054: Current learning rate: 0.0085 +2024-11-21 17:53:11.289724: train_loss -0.7521 +2024-11-21 17:53:11.289968: val_loss -0.7207 +2024-11-21 17:53:11.290050: Pseudo dice [0.8412] +2024-11-21 17:53:11.290138: Epoch time: 19.17 s +2024-11-21 17:53:12.143036: +2024-11-21 17:53:12.143274: Epoch 1326 +2024-11-21 17:53:12.143388: Current learning rate: 0.0085 +2024-11-21 17:53:32.383607: train_loss -0.7766 +2024-11-21 17:53:32.383820: val_loss -0.7417 +2024-11-21 17:53:32.383899: Pseudo dice [0.8413] +2024-11-21 17:53:32.383977: Epoch time: 20.24 s +2024-11-21 17:53:33.219530: +2024-11-21 17:53:33.219757: Epoch 1327 +2024-11-21 17:53:33.219867: Current learning rate: 0.00849 +2024-11-21 17:53:52.913072: train_loss -0.7677 +2024-11-21 17:53:52.913286: val_loss -0.7478 +2024-11-21 17:53:52.913361: Pseudo dice [0.8158] +2024-11-21 17:53:52.913440: Epoch time: 19.69 s +2024-11-21 17:53:53.776977: +2024-11-21 17:53:53.777219: Epoch 1328 +2024-11-21 17:53:53.777338: Current learning rate: 0.00849 +2024-11-21 17:54:11.982120: train_loss -0.7693 +2024-11-21 17:54:11.982337: val_loss -0.7118 +2024-11-21 17:54:11.982410: Pseudo dice [0.8239] +2024-11-21 17:54:11.982489: Epoch time: 18.21 s +2024-11-21 17:54:12.818392: +2024-11-21 17:54:12.818605: Epoch 1329 +2024-11-21 17:54:12.818714: Current learning rate: 0.00849 +2024-11-21 17:54:32.273715: train_loss -0.7681 +2024-11-21 17:54:32.273966: val_loss -0.7321 +2024-11-21 17:54:32.274050: Pseudo dice [0.8293] +2024-11-21 17:54:32.274135: Epoch time: 19.46 s +2024-11-21 17:54:33.117204: +2024-11-21 17:54:33.117507: Epoch 1330 +2024-11-21 17:54:33.117620: Current learning rate: 0.00849 +2024-11-21 17:54:52.630593: train_loss -0.7751 +2024-11-21 17:54:52.630795: val_loss -0.7524 +2024-11-21 17:54:52.630872: Pseudo dice [0.8281] +2024-11-21 17:54:52.630947: Epoch time: 19.51 s +2024-11-21 17:54:53.518037: +2024-11-21 17:54:53.518250: Epoch 1331 +2024-11-21 17:54:53.518363: Current learning rate: 0.00849 +2024-11-21 17:55:11.973779: train_loss -0.7756 +2024-11-21 17:55:11.974034: val_loss -0.729 +2024-11-21 17:55:11.974155: Pseudo dice [0.837] +2024-11-21 17:55:11.974235: Epoch time: 18.46 s +2024-11-21 17:55:12.813939: +2024-11-21 17:55:12.814154: Epoch 1332 +2024-11-21 17:55:12.814265: Current learning rate: 0.00849 +2024-11-21 17:55:31.295503: train_loss -0.7687 +2024-11-21 17:55:31.295732: val_loss -0.7462 +2024-11-21 17:55:31.295819: Pseudo dice [0.8279] +2024-11-21 17:55:31.295902: Epoch time: 18.48 s +2024-11-21 17:55:32.132705: +2024-11-21 17:55:32.132998: Epoch 1333 +2024-11-21 17:55:32.133111: Current learning rate: 0.00849 +2024-11-21 17:55:51.533259: train_loss -0.7717 +2024-11-21 17:55:51.533514: val_loss -0.7373 +2024-11-21 17:55:51.533591: Pseudo dice [0.8583] +2024-11-21 17:55:51.533675: Epoch time: 19.4 s +2024-11-21 17:55:52.378456: +2024-11-21 17:55:52.378790: Epoch 1334 +2024-11-21 17:55:52.378909: Current learning rate: 0.00849 +2024-11-21 17:56:10.564438: train_loss -0.7679 +2024-11-21 17:56:10.564652: val_loss -0.7524 +2024-11-21 17:56:10.564727: Pseudo dice [0.849] +2024-11-21 17:56:10.564802: Epoch time: 18.19 s +2024-11-21 17:56:11.516627: +2024-11-21 17:56:11.516837: Epoch 1335 +2024-11-21 17:56:11.516949: Current learning rate: 0.00848 +2024-11-21 17:56:30.578572: train_loss -0.7691 +2024-11-21 17:56:30.578773: val_loss -0.7582 +2024-11-21 17:56:30.578848: Pseudo dice [0.8639] +2024-11-21 17:56:30.578928: Epoch time: 19.06 s +2024-11-21 17:56:31.733899: +2024-11-21 17:56:31.734140: Epoch 1336 +2024-11-21 17:56:31.734274: Current learning rate: 0.00848 +2024-11-21 17:56:51.238404: train_loss -0.778 +2024-11-21 17:56:51.238659: val_loss -0.7714 +2024-11-21 17:56:51.238740: Pseudo dice [0.8461] +2024-11-21 17:56:51.238819: Epoch time: 19.51 s +2024-11-21 17:56:52.075381: +2024-11-21 17:56:52.075597: Epoch 1337 +2024-11-21 17:56:52.075708: Current learning rate: 0.00848 +2024-11-21 17:57:10.277547: train_loss -0.772 +2024-11-21 17:57:10.277749: val_loss -0.7106 +2024-11-21 17:57:10.277826: Pseudo dice [0.8316] +2024-11-21 17:57:10.277903: Epoch time: 18.2 s +2024-11-21 17:57:11.096558: +2024-11-21 17:57:11.096982: Epoch 1338 +2024-11-21 17:57:11.097108: Current learning rate: 0.00848 +2024-11-21 17:57:29.298724: train_loss -0.76 +2024-11-21 17:57:29.298943: val_loss -0.7273 +2024-11-21 17:57:29.299025: Pseudo dice [0.8313] +2024-11-21 17:57:29.299101: Epoch time: 18.2 s +2024-11-21 17:57:30.124125: +2024-11-21 17:57:30.124331: Epoch 1339 +2024-11-21 17:57:30.124443: Current learning rate: 0.00848 +2024-11-21 17:57:49.071187: train_loss -0.7559 +2024-11-21 17:57:49.071422: val_loss -0.727 +2024-11-21 17:57:49.071510: Pseudo dice [0.817] +2024-11-21 17:57:49.071594: Epoch time: 18.95 s +2024-11-21 17:57:49.908511: +2024-11-21 17:57:49.908728: Epoch 1340 +2024-11-21 17:57:49.908842: Current learning rate: 0.00848 +2024-11-21 17:58:08.982954: train_loss -0.7561 +2024-11-21 17:58:08.983197: val_loss -0.7459 +2024-11-21 17:58:08.983270: Pseudo dice [0.8365] +2024-11-21 17:58:08.983344: Epoch time: 19.08 s +2024-11-21 17:58:09.844158: +2024-11-21 17:58:09.844371: Epoch 1341 +2024-11-21 17:58:09.844481: Current learning rate: 0.00848 +2024-11-21 17:58:28.708988: train_loss -0.7699 +2024-11-21 17:58:28.709200: val_loss -0.7308 +2024-11-21 17:58:28.709276: Pseudo dice [0.8507] +2024-11-21 17:58:28.709355: Epoch time: 18.87 s +2024-11-21 17:58:29.541948: +2024-11-21 17:58:29.542155: Epoch 1342 +2024-11-21 17:58:29.542268: Current learning rate: 0.00848 +2024-11-21 17:58:48.098492: train_loss -0.7725 +2024-11-21 17:58:48.098714: val_loss -0.7432 +2024-11-21 17:58:48.098791: Pseudo dice [0.8296] +2024-11-21 17:58:48.098866: Epoch time: 18.56 s +2024-11-21 17:58:48.920586: +2024-11-21 17:58:48.920786: Epoch 1343 +2024-11-21 17:58:48.920899: Current learning rate: 0.00848 +2024-11-21 17:59:06.506448: train_loss -0.7796 +2024-11-21 17:59:06.506692: val_loss -0.76 +2024-11-21 17:59:06.506767: Pseudo dice [0.828] +2024-11-21 17:59:06.506852: Epoch time: 17.59 s +2024-11-21 17:59:07.355879: +2024-11-21 17:59:07.356080: Epoch 1344 +2024-11-21 17:59:07.356190: Current learning rate: 0.00847 +2024-11-21 17:59:25.939059: train_loss -0.7626 +2024-11-21 17:59:25.939288: val_loss -0.7324 +2024-11-21 17:59:25.939371: Pseudo dice [0.8291] +2024-11-21 17:59:25.939452: Epoch time: 18.58 s +2024-11-21 17:59:26.792814: +2024-11-21 17:59:26.793008: Epoch 1345 +2024-11-21 17:59:26.793111: Current learning rate: 0.00847 +2024-11-21 17:59:46.536156: train_loss -0.7656 +2024-11-21 17:59:46.536357: val_loss -0.7446 +2024-11-21 17:59:46.536429: Pseudo dice [0.8386] +2024-11-21 17:59:46.536505: Epoch time: 19.74 s +2024-11-21 17:59:47.412031: +2024-11-21 17:59:47.412239: Epoch 1346 +2024-11-21 17:59:47.412350: Current learning rate: 0.00847 +2024-11-21 18:00:05.695030: train_loss -0.7725 +2024-11-21 18:00:05.695251: val_loss -0.7395 +2024-11-21 18:00:05.695325: Pseudo dice [0.7981] +2024-11-21 18:00:05.695407: Epoch time: 18.28 s +2024-11-21 18:00:06.966446: +2024-11-21 18:00:06.966677: Epoch 1347 +2024-11-21 18:00:06.966793: Current learning rate: 0.00847 +2024-11-21 18:00:25.687094: train_loss -0.7731 +2024-11-21 18:00:25.687332: val_loss -0.747 +2024-11-21 18:00:25.687407: Pseudo dice [0.83] +2024-11-21 18:00:25.687493: Epoch time: 18.72 s +2024-11-21 18:00:26.576861: +2024-11-21 18:00:26.577127: Epoch 1348 +2024-11-21 18:00:26.577243: Current learning rate: 0.00847 +2024-11-21 18:00:46.095835: train_loss -0.7601 +2024-11-21 18:00:46.096061: val_loss -0.7638 +2024-11-21 18:00:46.096137: Pseudo dice [0.8446] +2024-11-21 18:00:46.096213: Epoch time: 19.52 s +2024-11-21 18:00:46.946793: +2024-11-21 18:00:46.947001: Epoch 1349 +2024-11-21 18:00:46.947109: Current learning rate: 0.00847 +2024-11-21 18:01:06.010601: train_loss -0.7665 +2024-11-21 18:01:06.010815: val_loss -0.7544 +2024-11-21 18:01:06.010890: Pseudo dice [0.856] +2024-11-21 18:01:06.010965: Epoch time: 19.06 s +2024-11-21 18:01:07.092810: +2024-11-21 18:01:07.093047: Epoch 1350 +2024-11-21 18:01:07.093152: Current learning rate: 0.00847 +2024-11-21 18:01:26.507793: train_loss -0.776 +2024-11-21 18:01:26.508046: val_loss -0.724 +2024-11-21 18:01:26.508120: Pseudo dice [0.8191] +2024-11-21 18:01:26.508204: Epoch time: 19.42 s +2024-11-21 18:01:27.380945: +2024-11-21 18:01:27.381162: Epoch 1351 +2024-11-21 18:01:27.381276: Current learning rate: 0.00847 +2024-11-21 18:01:46.050851: train_loss -0.7674 +2024-11-21 18:01:46.051088: val_loss -0.7539 +2024-11-21 18:01:46.051165: Pseudo dice [0.8287] +2024-11-21 18:01:46.051240: Epoch time: 18.67 s +2024-11-21 18:01:46.893683: +2024-11-21 18:01:46.893898: Epoch 1352 +2024-11-21 18:01:46.894010: Current learning rate: 0.00847 +2024-11-21 18:02:05.743037: train_loss -0.7785 +2024-11-21 18:02:05.745410: val_loss -0.7305 +2024-11-21 18:02:05.745499: Pseudo dice [0.8158] +2024-11-21 18:02:05.745580: Epoch time: 18.85 s +2024-11-21 18:02:06.660296: +2024-11-21 18:02:06.660511: Epoch 1353 +2024-11-21 18:02:06.660615: Current learning rate: 0.00846 +2024-11-21 18:02:25.838756: train_loss -0.7741 +2024-11-21 18:02:25.838964: val_loss -0.742 +2024-11-21 18:02:25.839046: Pseudo dice [0.8335] +2024-11-21 18:02:25.839118: Epoch time: 19.18 s +2024-11-21 18:02:26.696280: +2024-11-21 18:02:26.696487: Epoch 1354 +2024-11-21 18:02:26.696594: Current learning rate: 0.00846 +2024-11-21 18:02:45.434714: train_loss -0.7742 +2024-11-21 18:02:45.434955: val_loss -0.7323 +2024-11-21 18:02:45.435040: Pseudo dice [0.8385] +2024-11-21 18:02:45.435122: Epoch time: 18.74 s +2024-11-21 18:02:46.372945: +2024-11-21 18:02:46.373165: Epoch 1355 +2024-11-21 18:02:46.373276: Current learning rate: 0.00846 +2024-11-21 18:03:06.189370: train_loss -0.7607 +2024-11-21 18:03:06.189676: val_loss -0.7247 +2024-11-21 18:03:06.189755: Pseudo dice [0.8337] +2024-11-21 18:03:06.189837: Epoch time: 19.82 s +2024-11-21 18:03:07.057808: +2024-11-21 18:03:07.058037: Epoch 1356 +2024-11-21 18:03:07.058158: Current learning rate: 0.00846 +2024-11-21 18:03:24.721020: train_loss -0.7678 +2024-11-21 18:03:24.721247: val_loss -0.7334 +2024-11-21 18:03:24.721323: Pseudo dice [0.8243] +2024-11-21 18:03:24.721405: Epoch time: 17.66 s +2024-11-21 18:03:25.602952: +2024-11-21 18:03:25.603155: Epoch 1357 +2024-11-21 18:03:25.603269: Current learning rate: 0.00846 +2024-11-21 18:03:43.777675: train_loss -0.7727 +2024-11-21 18:03:43.777884: val_loss -0.7342 +2024-11-21 18:03:43.777961: Pseudo dice [0.8284] +2024-11-21 18:03:43.778056: Epoch time: 18.18 s +2024-11-21 18:03:45.035728: +2024-11-21 18:03:45.035986: Epoch 1358 +2024-11-21 18:03:45.036150: Current learning rate: 0.00846 +2024-11-21 18:04:03.837519: train_loss -0.7793 +2024-11-21 18:04:03.837761: val_loss -0.7354 +2024-11-21 18:04:03.837834: Pseudo dice [0.8046] +2024-11-21 18:04:03.837912: Epoch time: 18.8 s +2024-11-21 18:04:04.685183: +2024-11-21 18:04:04.685403: Epoch 1359 +2024-11-21 18:04:04.685513: Current learning rate: 0.00846 +2024-11-21 18:04:23.246180: train_loss -0.762 +2024-11-21 18:04:23.246425: val_loss -0.7275 +2024-11-21 18:04:23.246502: Pseudo dice [0.8241] +2024-11-21 18:04:23.246580: Epoch time: 18.56 s +2024-11-21 18:04:24.092102: +2024-11-21 18:04:24.092348: Epoch 1360 +2024-11-21 18:04:24.092465: Current learning rate: 0.00846 +2024-11-21 18:04:43.263670: train_loss -0.7591 +2024-11-21 18:04:43.263896: val_loss -0.7428 +2024-11-21 18:04:43.263973: Pseudo dice [0.8577] +2024-11-21 18:04:43.264055: Epoch time: 19.17 s +2024-11-21 18:04:44.133339: +2024-11-21 18:04:44.133561: Epoch 1361 +2024-11-21 18:04:44.133674: Current learning rate: 0.00845 +2024-11-21 18:05:01.687510: train_loss -0.7768 +2024-11-21 18:05:01.687758: val_loss -0.7509 +2024-11-21 18:05:01.687836: Pseudo dice [0.8467] +2024-11-21 18:05:01.687922: Epoch time: 17.55 s +2024-11-21 18:05:02.539928: +2024-11-21 18:05:02.540140: Epoch 1362 +2024-11-21 18:05:02.540250: Current learning rate: 0.00845 +2024-11-21 18:05:22.416382: train_loss -0.7736 +2024-11-21 18:05:22.416591: val_loss -0.7703 +2024-11-21 18:05:22.416670: Pseudo dice [0.8542] +2024-11-21 18:05:22.416744: Epoch time: 19.88 s +2024-11-21 18:05:23.262343: +2024-11-21 18:05:23.262557: Epoch 1363 +2024-11-21 18:05:23.262678: Current learning rate: 0.00845 +2024-11-21 18:05:41.861945: train_loss -0.7564 +2024-11-21 18:05:41.862160: val_loss -0.7222 +2024-11-21 18:05:41.862237: Pseudo dice [0.8082] +2024-11-21 18:05:41.862317: Epoch time: 18.6 s +2024-11-21 18:05:42.863885: +2024-11-21 18:05:42.864122: Epoch 1364 +2024-11-21 18:05:42.864238: Current learning rate: 0.00845 +2024-11-21 18:06:00.853371: train_loss -0.7654 +2024-11-21 18:06:00.853587: val_loss -0.7259 +2024-11-21 18:06:00.853669: Pseudo dice [0.8396] +2024-11-21 18:06:00.853754: Epoch time: 17.99 s +2024-11-21 18:06:01.699389: +2024-11-21 18:06:01.699713: Epoch 1365 +2024-11-21 18:06:01.699849: Current learning rate: 0.00845 +2024-11-21 18:06:21.200703: train_loss -0.7693 +2024-11-21 18:06:21.200945: val_loss -0.7416 +2024-11-21 18:06:21.201026: Pseudo dice [0.8232] +2024-11-21 18:06:21.201107: Epoch time: 19.5 s +2024-11-21 18:06:22.151817: +2024-11-21 18:06:22.152081: Epoch 1366 +2024-11-21 18:06:22.152200: Current learning rate: 0.00845 +2024-11-21 18:06:40.327356: train_loss -0.7717 +2024-11-21 18:06:40.327574: val_loss -0.7591 +2024-11-21 18:06:40.327650: Pseudo dice [0.8514] +2024-11-21 18:06:40.327727: Epoch time: 18.18 s +2024-11-21 18:06:41.173522: +2024-11-21 18:06:41.173779: Epoch 1367 +2024-11-21 18:06:41.173894: Current learning rate: 0.00845 +2024-11-21 18:07:00.084168: train_loss -0.7713 +2024-11-21 18:07:00.084389: val_loss -0.7255 +2024-11-21 18:07:00.084466: Pseudo dice [0.827] +2024-11-21 18:07:00.089776: Epoch time: 18.91 s +2024-11-21 18:07:00.996713: +2024-11-21 18:07:00.996984: Epoch 1368 +2024-11-21 18:07:00.997102: Current learning rate: 0.00845 +2024-11-21 18:07:21.194775: train_loss -0.7747 +2024-11-21 18:07:21.195004: val_loss -0.7342 +2024-11-21 18:07:21.195080: Pseudo dice [0.8011] +2024-11-21 18:07:21.195159: Epoch time: 20.2 s +2024-11-21 18:07:22.527205: +2024-11-21 18:07:22.527457: Epoch 1369 +2024-11-21 18:07:22.527575: Current learning rate: 0.00845 +2024-11-21 18:07:41.153609: train_loss -0.7711 +2024-11-21 18:07:41.153847: val_loss -0.732 +2024-11-21 18:07:41.153920: Pseudo dice [0.847] +2024-11-21 18:07:41.154042: Epoch time: 18.63 s +2024-11-21 18:07:41.994365: +2024-11-21 18:07:41.994585: Epoch 1370 +2024-11-21 18:07:41.994700: Current learning rate: 0.00844 +2024-11-21 18:08:00.718444: train_loss -0.7804 +2024-11-21 18:08:00.718654: val_loss -0.7684 +2024-11-21 18:08:00.718728: Pseudo dice [0.8487] +2024-11-21 18:08:00.718803: Epoch time: 18.72 s +2024-11-21 18:08:01.564539: +2024-11-21 18:08:01.564747: Epoch 1371 +2024-11-21 18:08:01.564855: Current learning rate: 0.00844 +2024-11-21 18:08:20.337777: train_loss -0.776 +2024-11-21 18:08:20.337986: val_loss -0.7388 +2024-11-21 18:08:20.338071: Pseudo dice [0.8159] +2024-11-21 18:08:20.338151: Epoch time: 18.77 s +2024-11-21 18:08:21.178766: +2024-11-21 18:08:21.178963: Epoch 1372 +2024-11-21 18:08:21.179079: Current learning rate: 0.00844 +2024-11-21 18:08:40.916936: train_loss -0.7678 +2024-11-21 18:08:40.917177: val_loss -0.7316 +2024-11-21 18:08:40.917266: Pseudo dice [0.8155] +2024-11-21 18:08:40.917403: Epoch time: 19.74 s +2024-11-21 18:08:41.755800: +2024-11-21 18:08:41.756021: Epoch 1373 +2024-11-21 18:08:41.756133: Current learning rate: 0.00844 +2024-11-21 18:08:59.767787: train_loss -0.7849 +2024-11-21 18:08:59.767996: val_loss -0.7461 +2024-11-21 18:08:59.768071: Pseudo dice [0.8526] +2024-11-21 18:08:59.768141: Epoch time: 18.01 s +2024-11-21 18:09:00.593628: +2024-11-21 18:09:00.593862: Epoch 1374 +2024-11-21 18:09:00.593972: Current learning rate: 0.00844 +2024-11-21 18:09:20.321044: train_loss -0.7854 +2024-11-21 18:09:20.321264: val_loss -0.7508 +2024-11-21 18:09:20.321340: Pseudo dice [0.8601] +2024-11-21 18:09:20.321418: Epoch time: 19.73 s +2024-11-21 18:09:21.162751: +2024-11-21 18:09:21.163077: Epoch 1375 +2024-11-21 18:09:21.163187: Current learning rate: 0.00844 +2024-11-21 18:09:39.943025: train_loss -0.7787 +2024-11-21 18:09:39.943268: val_loss -0.7338 +2024-11-21 18:09:39.943344: Pseudo dice [0.8355] +2024-11-21 18:09:39.943427: Epoch time: 18.78 s +2024-11-21 18:09:40.792413: +2024-11-21 18:09:40.792609: Epoch 1376 +2024-11-21 18:09:40.792723: Current learning rate: 0.00844 +2024-11-21 18:09:59.398393: train_loss -0.7675 +2024-11-21 18:09:59.398596: val_loss -0.7364 +2024-11-21 18:09:59.398669: Pseudo dice [0.8455] +2024-11-21 18:09:59.398748: Epoch time: 18.61 s +2024-11-21 18:10:00.240728: +2024-11-21 18:10:00.241003: Epoch 1377 +2024-11-21 18:10:00.241115: Current learning rate: 0.00844 +2024-11-21 18:10:19.053967: train_loss -0.7604 +2024-11-21 18:10:19.059376: val_loss -0.7578 +2024-11-21 18:10:19.059465: Pseudo dice [0.8245] +2024-11-21 18:10:19.059553: Epoch time: 18.81 s +2024-11-21 18:10:20.062622: +2024-11-21 18:10:20.062834: Epoch 1378 +2024-11-21 18:10:20.062950: Current learning rate: 0.00844 +2024-11-21 18:10:39.398048: train_loss -0.7688 +2024-11-21 18:10:39.398341: val_loss -0.7368 +2024-11-21 18:10:39.398421: Pseudo dice [0.8369] +2024-11-21 18:10:39.398502: Epoch time: 19.34 s +2024-11-21 18:10:40.249649: +2024-11-21 18:10:40.249919: Epoch 1379 +2024-11-21 18:10:40.250042: Current learning rate: 0.00843 +2024-11-21 18:10:58.694664: train_loss -0.7692 +2024-11-21 18:10:58.694972: val_loss -0.7368 +2024-11-21 18:10:58.695055: Pseudo dice [0.8403] +2024-11-21 18:10:58.695136: Epoch time: 18.45 s +2024-11-21 18:10:59.927084: +2024-11-21 18:10:59.927311: Epoch 1380 +2024-11-21 18:10:59.927425: Current learning rate: 0.00843 +2024-11-21 18:11:19.254016: train_loss -0.7751 +2024-11-21 18:11:19.254231: val_loss -0.7482 +2024-11-21 18:11:19.254305: Pseudo dice [0.8246] +2024-11-21 18:11:19.254382: Epoch time: 19.33 s +2024-11-21 18:11:20.098210: +2024-11-21 18:11:20.098509: Epoch 1381 +2024-11-21 18:11:20.098620: Current learning rate: 0.00843 +2024-11-21 18:11:39.271278: train_loss -0.7706 +2024-11-21 18:11:39.271566: val_loss -0.7524 +2024-11-21 18:11:39.271640: Pseudo dice [0.8501] +2024-11-21 18:11:39.271728: Epoch time: 19.17 s +2024-11-21 18:11:40.117919: +2024-11-21 18:11:40.118157: Epoch 1382 +2024-11-21 18:11:40.118273: Current learning rate: 0.00843 +2024-11-21 18:11:57.930025: train_loss -0.7835 +2024-11-21 18:11:57.930228: val_loss -0.7364 +2024-11-21 18:11:57.930304: Pseudo dice [0.8338] +2024-11-21 18:11:57.930385: Epoch time: 17.81 s +2024-11-21 18:11:58.760301: +2024-11-21 18:11:58.760513: Epoch 1383 +2024-11-21 18:11:58.760624: Current learning rate: 0.00843 +2024-11-21 18:12:18.214018: train_loss -0.778 +2024-11-21 18:12:18.214232: val_loss -0.7376 +2024-11-21 18:12:18.214309: Pseudo dice [0.8422] +2024-11-21 18:12:18.214392: Epoch time: 19.45 s +2024-11-21 18:12:19.085904: +2024-11-21 18:12:19.086167: Epoch 1384 +2024-11-21 18:12:19.086277: Current learning rate: 0.00843 +2024-11-21 18:12:37.055037: train_loss -0.7748 +2024-11-21 18:12:37.055248: val_loss -0.738 +2024-11-21 18:12:37.055321: Pseudo dice [0.8204] +2024-11-21 18:12:37.055419: Epoch time: 17.97 s +2024-11-21 18:12:37.896948: +2024-11-21 18:12:37.897219: Epoch 1385 +2024-11-21 18:12:37.897330: Current learning rate: 0.00843 +2024-11-21 18:12:55.827793: train_loss -0.7761 +2024-11-21 18:12:55.828047: val_loss -0.7492 +2024-11-21 18:12:55.828125: Pseudo dice [0.8461] +2024-11-21 18:12:55.828211: Epoch time: 17.93 s +2024-11-21 18:12:56.803506: +2024-11-21 18:12:56.803724: Epoch 1386 +2024-11-21 18:12:56.803836: Current learning rate: 0.00843 +2024-11-21 18:13:15.719678: train_loss -0.7708 +2024-11-21 18:13:15.719895: val_loss -0.7562 +2024-11-21 18:13:15.719971: Pseudo dice [0.8393] +2024-11-21 18:13:15.720061: Epoch time: 18.92 s +2024-11-21 18:13:16.714313: +2024-11-21 18:13:16.714524: Epoch 1387 +2024-11-21 18:13:16.714633: Current learning rate: 0.00843 +2024-11-21 18:13:34.722262: train_loss -0.7754 +2024-11-21 18:13:34.722472: val_loss -0.7367 +2024-11-21 18:13:34.722547: Pseudo dice [0.8188] +2024-11-21 18:13:34.722628: Epoch time: 18.01 s +2024-11-21 18:13:35.568672: +2024-11-21 18:13:35.568886: Epoch 1388 +2024-11-21 18:13:35.569006: Current learning rate: 0.00842 +2024-11-21 18:13:54.601229: train_loss -0.7722 +2024-11-21 18:13:54.601425: val_loss -0.7321 +2024-11-21 18:13:54.601498: Pseudo dice [0.829] +2024-11-21 18:13:54.601572: Epoch time: 19.03 s +2024-11-21 18:13:55.418564: +2024-11-21 18:13:55.418760: Epoch 1389 +2024-11-21 18:13:55.418871: Current learning rate: 0.00842 +2024-11-21 18:14:14.607421: train_loss -0.7786 +2024-11-21 18:14:14.607673: val_loss -0.7205 +2024-11-21 18:14:14.607749: Pseudo dice [0.8326] +2024-11-21 18:14:14.607829: Epoch time: 19.19 s +2024-11-21 18:14:15.445642: +2024-11-21 18:14:15.445823: Epoch 1390 +2024-11-21 18:14:15.445930: Current learning rate: 0.00842 +2024-11-21 18:14:33.500209: train_loss -0.7725 +2024-11-21 18:14:33.500417: val_loss -0.7547 +2024-11-21 18:14:33.500492: Pseudo dice [0.8472] +2024-11-21 18:14:33.500567: Epoch time: 18.06 s +2024-11-21 18:14:34.724366: +2024-11-21 18:14:34.724585: Epoch 1391 +2024-11-21 18:14:34.724699: Current learning rate: 0.00842 +2024-11-21 18:14:54.442118: train_loss -0.7734 +2024-11-21 18:14:54.442320: val_loss -0.7433 +2024-11-21 18:14:54.447554: Pseudo dice [0.8005] +2024-11-21 18:14:54.447648: Epoch time: 19.72 s +2024-11-21 18:14:55.308309: +2024-11-21 18:14:55.308528: Epoch 1392 +2024-11-21 18:14:55.308643: Current learning rate: 0.00842 +2024-11-21 18:15:14.420534: train_loss -0.7709 +2024-11-21 18:15:14.424346: val_loss -0.7492 +2024-11-21 18:15:14.424548: Pseudo dice [0.84] +2024-11-21 18:15:14.424640: Epoch time: 19.11 s +2024-11-21 18:15:15.271259: +2024-11-21 18:15:15.271500: Epoch 1393 +2024-11-21 18:15:15.271612: Current learning rate: 0.00842 +2024-11-21 18:15:33.515813: train_loss -0.7629 +2024-11-21 18:15:33.516040: val_loss -0.7431 +2024-11-21 18:15:33.516119: Pseudo dice [0.8348] +2024-11-21 18:15:33.516212: Epoch time: 18.25 s +2024-11-21 18:15:34.351820: +2024-11-21 18:15:34.352038: Epoch 1394 +2024-11-21 18:15:34.352147: Current learning rate: 0.00842 +2024-11-21 18:15:51.505476: train_loss -0.7671 +2024-11-21 18:15:51.505684: val_loss -0.7379 +2024-11-21 18:15:51.505758: Pseudo dice [0.8291] +2024-11-21 18:15:51.505834: Epoch time: 17.15 s +2024-11-21 18:15:52.356033: +2024-11-21 18:15:52.356244: Epoch 1395 +2024-11-21 18:15:52.356354: Current learning rate: 0.00842 +2024-11-21 18:16:10.758262: train_loss -0.7613 +2024-11-21 18:16:10.761265: val_loss -0.7488 +2024-11-21 18:16:10.761372: Pseudo dice [0.8307] +2024-11-21 18:16:10.761454: Epoch time: 18.4 s +2024-11-21 18:16:11.626054: +2024-11-21 18:16:11.626247: Epoch 1396 +2024-11-21 18:16:11.626358: Current learning rate: 0.00841 +2024-11-21 18:16:29.962160: train_loss -0.7741 +2024-11-21 18:16:29.962457: val_loss -0.7561 +2024-11-21 18:16:29.962534: Pseudo dice [0.8333] +2024-11-21 18:16:29.962617: Epoch time: 18.34 s +2024-11-21 18:16:30.814235: +2024-11-21 18:16:30.814520: Epoch 1397 +2024-11-21 18:16:30.814644: Current learning rate: 0.00841 +2024-11-21 18:16:48.838938: train_loss -0.7755 +2024-11-21 18:16:48.839162: val_loss -0.76 +2024-11-21 18:16:48.839259: Pseudo dice [0.8275] +2024-11-21 18:16:48.839336: Epoch time: 18.03 s +2024-11-21 18:16:49.682641: +2024-11-21 18:16:49.682830: Epoch 1398 +2024-11-21 18:16:49.682942: Current learning rate: 0.00841 +2024-11-21 18:17:08.220896: train_loss -0.7706 +2024-11-21 18:17:08.221114: val_loss -0.744 +2024-11-21 18:17:08.221196: Pseudo dice [0.8294] +2024-11-21 18:17:08.221269: Epoch time: 18.54 s +2024-11-21 18:17:09.063983: +2024-11-21 18:17:09.064179: Epoch 1399 +2024-11-21 18:17:09.064290: Current learning rate: 0.00841 +2024-11-21 18:17:28.733625: train_loss -0.7797 +2024-11-21 18:17:28.733833: val_loss -0.7321 +2024-11-21 18:17:28.733903: Pseudo dice [0.8411] +2024-11-21 18:17:28.733979: Epoch time: 19.67 s +2024-11-21 18:17:29.776280: +2024-11-21 18:17:29.776577: Epoch 1400 +2024-11-21 18:17:29.776694: Current learning rate: 0.00841 +2024-11-21 18:17:48.934459: train_loss -0.7716 +2024-11-21 18:17:48.934694: val_loss -0.7195 +2024-11-21 18:17:48.934770: Pseudo dice [0.8208] +2024-11-21 18:17:48.934848: Epoch time: 19.16 s +2024-11-21 18:17:49.791959: +2024-11-21 18:17:49.792154: Epoch 1401 +2024-11-21 18:17:49.792269: Current learning rate: 0.00841 +2024-11-21 18:18:07.910507: train_loss -0.7812 +2024-11-21 18:18:07.910724: val_loss -0.7372 +2024-11-21 18:18:07.910811: Pseudo dice [0.8389] +2024-11-21 18:18:07.916074: Epoch time: 18.12 s +2024-11-21 18:18:09.265693: +2024-11-21 18:18:09.268079: Epoch 1402 +2024-11-21 18:18:09.268208: Current learning rate: 0.00841 +2024-11-21 18:18:27.850270: train_loss -0.7769 +2024-11-21 18:18:27.850486: val_loss -0.7442 +2024-11-21 18:18:27.850562: Pseudo dice [0.8315] +2024-11-21 18:18:27.850650: Epoch time: 18.59 s +2024-11-21 18:18:28.725123: +2024-11-21 18:18:28.725332: Epoch 1403 +2024-11-21 18:18:28.725444: Current learning rate: 0.00841 +2024-11-21 18:18:47.556327: train_loss -0.7776 +2024-11-21 18:18:47.561750: val_loss -0.7535 +2024-11-21 18:18:47.561922: Pseudo dice [0.846] +2024-11-21 18:18:47.562036: Epoch time: 18.83 s +2024-11-21 18:18:48.438183: +2024-11-21 18:18:48.438395: Epoch 1404 +2024-11-21 18:18:48.438506: Current learning rate: 0.00841 +2024-11-21 18:19:07.003292: train_loss -0.7744 +2024-11-21 18:19:07.003499: val_loss -0.7347 +2024-11-21 18:19:07.003571: Pseudo dice [0.839] +2024-11-21 18:19:07.003645: Epoch time: 18.57 s +2024-11-21 18:19:07.848097: +2024-11-21 18:19:07.848314: Epoch 1405 +2024-11-21 18:19:07.848429: Current learning rate: 0.0084 +2024-11-21 18:19:26.118184: train_loss -0.7705 +2024-11-21 18:19:26.118407: val_loss -0.7482 +2024-11-21 18:19:26.118482: Pseudo dice [0.8334] +2024-11-21 18:19:26.118558: Epoch time: 18.27 s +2024-11-21 18:19:26.973137: +2024-11-21 18:19:26.973348: Epoch 1406 +2024-11-21 18:19:26.973458: Current learning rate: 0.0084 +2024-11-21 18:19:46.048852: train_loss -0.759 +2024-11-21 18:19:46.049095: val_loss -0.7444 +2024-11-21 18:19:46.049170: Pseudo dice [0.8219] +2024-11-21 18:19:46.049270: Epoch time: 19.08 s +2024-11-21 18:19:46.895708: +2024-11-21 18:19:46.895916: Epoch 1407 +2024-11-21 18:19:46.896029: Current learning rate: 0.0084 +2024-11-21 18:20:05.904507: train_loss -0.7619 +2024-11-21 18:20:05.904766: val_loss -0.7463 +2024-11-21 18:20:05.904842: Pseudo dice [0.8421] +2024-11-21 18:20:05.904924: Epoch time: 19.01 s +2024-11-21 18:20:06.953283: +2024-11-21 18:20:06.953521: Epoch 1408 +2024-11-21 18:20:06.953637: Current learning rate: 0.0084 +2024-11-21 18:20:25.711553: train_loss -0.7705 +2024-11-21 18:20:25.711770: val_loss -0.7588 +2024-11-21 18:20:25.711850: Pseudo dice [0.8168] +2024-11-21 18:20:25.711926: Epoch time: 18.76 s +2024-11-21 18:20:26.556566: +2024-11-21 18:20:26.556757: Epoch 1409 +2024-11-21 18:20:26.556868: Current learning rate: 0.0084 +2024-11-21 18:20:45.761340: train_loss -0.7682 +2024-11-21 18:20:45.761557: val_loss -0.7039 +2024-11-21 18:20:45.761634: Pseudo dice [0.8346] +2024-11-21 18:20:45.761712: Epoch time: 19.21 s +2024-11-21 18:20:46.605659: +2024-11-21 18:20:46.605962: Epoch 1410 +2024-11-21 18:20:46.606085: Current learning rate: 0.0084 +2024-11-21 18:21:04.112853: train_loss -0.7623 +2024-11-21 18:21:04.113121: val_loss -0.7496 +2024-11-21 18:21:04.113200: Pseudo dice [0.8493] +2024-11-21 18:21:04.113276: Epoch time: 17.51 s +2024-11-21 18:21:04.971016: +2024-11-21 18:21:04.971348: Epoch 1411 +2024-11-21 18:21:04.971474: Current learning rate: 0.0084 +2024-11-21 18:21:24.937397: train_loss -0.777 +2024-11-21 18:21:24.937642: val_loss -0.7379 +2024-11-21 18:21:24.937716: Pseudo dice [0.8368] +2024-11-21 18:21:24.937810: Epoch time: 19.97 s +2024-11-21 18:21:25.796400: +2024-11-21 18:21:25.796628: Epoch 1412 +2024-11-21 18:21:25.796747: Current learning rate: 0.0084 +2024-11-21 18:21:45.092208: train_loss -0.7623 +2024-11-21 18:21:45.092414: val_loss -0.7478 +2024-11-21 18:21:45.092489: Pseudo dice [0.8317] +2024-11-21 18:21:45.092563: Epoch time: 19.3 s +2024-11-21 18:21:46.339594: +2024-11-21 18:21:46.339816: Epoch 1413 +2024-11-21 18:21:46.339930: Current learning rate: 0.0084 +2024-11-21 18:22:04.579287: train_loss -0.7582 +2024-11-21 18:22:04.579513: val_loss -0.7434 +2024-11-21 18:22:04.579594: Pseudo dice [0.8363] +2024-11-21 18:22:04.579670: Epoch time: 18.24 s +2024-11-21 18:22:05.426685: +2024-11-21 18:22:05.426911: Epoch 1414 +2024-11-21 18:22:05.427033: Current learning rate: 0.00839 +2024-11-21 18:22:24.568977: train_loss -0.7602 +2024-11-21 18:22:24.570096: val_loss -0.7438 +2024-11-21 18:22:24.570174: Pseudo dice [0.8572] +2024-11-21 18:22:24.570259: Epoch time: 19.14 s +2024-11-21 18:22:25.458613: +2024-11-21 18:22:25.458833: Epoch 1415 +2024-11-21 18:22:25.458950: Current learning rate: 0.00839 +2024-11-21 18:22:43.165079: train_loss -0.7706 +2024-11-21 18:22:43.165306: val_loss -0.7347 +2024-11-21 18:22:43.165386: Pseudo dice [0.8449] +2024-11-21 18:22:43.166535: Epoch time: 17.71 s +2024-11-21 18:22:44.129059: +2024-11-21 18:22:44.129321: Epoch 1416 +2024-11-21 18:22:44.129435: Current learning rate: 0.00839 +2024-11-21 18:23:02.744576: train_loss -0.7647 +2024-11-21 18:23:02.744799: val_loss -0.7154 +2024-11-21 18:23:02.744874: Pseudo dice [0.8369] +2024-11-21 18:23:02.744949: Epoch time: 18.62 s +2024-11-21 18:23:03.598420: +2024-11-21 18:23:03.598660: Epoch 1417 +2024-11-21 18:23:03.598778: Current learning rate: 0.00839 +2024-11-21 18:23:22.550630: train_loss -0.7716 +2024-11-21 18:23:22.550853: val_loss -0.7349 +2024-11-21 18:23:22.551040: Pseudo dice [0.8563] +2024-11-21 18:23:22.551123: Epoch time: 18.95 s +2024-11-21 18:23:23.398566: +2024-11-21 18:23:23.398802: Epoch 1418 +2024-11-21 18:23:23.398918: Current learning rate: 0.00839 +2024-11-21 18:23:41.421842: train_loss -0.7712 +2024-11-21 18:23:41.422104: val_loss -0.746 +2024-11-21 18:23:41.422184: Pseudo dice [0.8224] +2024-11-21 18:23:41.422268: Epoch time: 18.02 s +2024-11-21 18:23:42.486911: +2024-11-21 18:23:42.487150: Epoch 1419 +2024-11-21 18:23:42.487267: Current learning rate: 0.00839 +2024-11-21 18:24:01.152275: train_loss -0.7502 +2024-11-21 18:24:01.152492: val_loss -0.7155 +2024-11-21 18:24:01.152569: Pseudo dice [0.8337] +2024-11-21 18:24:01.152647: Epoch time: 18.67 s +2024-11-21 18:24:01.995978: +2024-11-21 18:24:01.996193: Epoch 1420 +2024-11-21 18:24:01.996303: Current learning rate: 0.00839 +2024-11-21 18:24:19.916956: train_loss -0.7576 +2024-11-21 18:24:19.917181: val_loss -0.7282 +2024-11-21 18:24:19.917258: Pseudo dice [0.8527] +2024-11-21 18:24:19.917335: Epoch time: 17.92 s +2024-11-21 18:24:20.762799: +2024-11-21 18:24:20.763068: Epoch 1421 +2024-11-21 18:24:20.763182: Current learning rate: 0.00839 +2024-11-21 18:24:39.690048: train_loss -0.7566 +2024-11-21 18:24:39.690278: val_loss -0.7318 +2024-11-21 18:24:39.690368: Pseudo dice [0.8459] +2024-11-21 18:24:39.690448: Epoch time: 18.93 s +2024-11-21 18:24:40.579731: +2024-11-21 18:24:40.579954: Epoch 1422 +2024-11-21 18:24:40.580101: Current learning rate: 0.00839 +2024-11-21 18:24:59.691662: train_loss -0.7578 +2024-11-21 18:24:59.691931: val_loss -0.7459 +2024-11-21 18:24:59.692021: Pseudo dice [0.8303] +2024-11-21 18:24:59.692101: Epoch time: 19.11 s +2024-11-21 18:25:00.539655: +2024-11-21 18:25:00.539870: Epoch 1423 +2024-11-21 18:25:00.539982: Current learning rate: 0.00838 +2024-11-21 18:25:19.439417: train_loss -0.7758 +2024-11-21 18:25:19.439633: val_loss -0.7415 +2024-11-21 18:25:19.439711: Pseudo dice [0.8316] +2024-11-21 18:25:19.439790: Epoch time: 18.9 s +2024-11-21 18:25:20.924446: +2024-11-21 18:25:20.924671: Epoch 1424 +2024-11-21 18:25:20.924784: Current learning rate: 0.00838 +2024-11-21 18:25:38.989598: train_loss -0.782 +2024-11-21 18:25:38.989803: val_loss -0.7285 +2024-11-21 18:25:38.989875: Pseudo dice [0.8483] +2024-11-21 18:25:38.989952: Epoch time: 18.07 s +2024-11-21 18:25:39.843045: +2024-11-21 18:25:39.843298: Epoch 1425 +2024-11-21 18:25:39.843415: Current learning rate: 0.00838 +2024-11-21 18:25:57.322642: train_loss -0.7879 +2024-11-21 18:25:57.322936: val_loss -0.7592 +2024-11-21 18:25:57.323026: Pseudo dice [0.8455] +2024-11-21 18:25:57.323112: Epoch time: 17.48 s +2024-11-21 18:25:58.173377: +2024-11-21 18:25:58.173830: Epoch 1426 +2024-11-21 18:25:58.173952: Current learning rate: 0.00838 +2024-11-21 18:26:16.289030: train_loss -0.7789 +2024-11-21 18:26:16.289240: val_loss -0.7477 +2024-11-21 18:26:16.289313: Pseudo dice [0.8291] +2024-11-21 18:26:16.289386: Epoch time: 18.12 s +2024-11-21 18:26:17.163701: +2024-11-21 18:26:17.163903: Epoch 1427 +2024-11-21 18:26:17.164020: Current learning rate: 0.00838 +2024-11-21 18:26:35.828335: train_loss -0.7667 +2024-11-21 18:26:35.828547: val_loss -0.7457 +2024-11-21 18:26:35.828622: Pseudo dice [0.8415] +2024-11-21 18:26:35.828698: Epoch time: 18.67 s +2024-11-21 18:26:36.671979: +2024-11-21 18:26:36.672214: Epoch 1428 +2024-11-21 18:26:36.672335: Current learning rate: 0.00838 +2024-11-21 18:26:55.454324: train_loss -0.7685 +2024-11-21 18:26:55.454536: val_loss -0.7097 +2024-11-21 18:26:55.454614: Pseudo dice [0.8375] +2024-11-21 18:26:55.456856: Epoch time: 18.78 s +2024-11-21 18:26:56.334240: +2024-11-21 18:26:56.334474: Epoch 1429 +2024-11-21 18:26:56.334597: Current learning rate: 0.00838 +2024-11-21 18:27:15.928699: train_loss -0.7615 +2024-11-21 18:27:15.929006: val_loss -0.7182 +2024-11-21 18:27:15.929083: Pseudo dice [0.8161] +2024-11-21 18:27:15.929161: Epoch time: 19.6 s +2024-11-21 18:27:16.779751: +2024-11-21 18:27:16.779946: Epoch 1430 +2024-11-21 18:27:16.780067: Current learning rate: 0.00838 +2024-11-21 18:27:33.652749: train_loss -0.7653 +2024-11-21 18:27:33.652980: val_loss -0.7361 +2024-11-21 18:27:33.653068: Pseudo dice [0.8429] +2024-11-21 18:27:33.653142: Epoch time: 16.87 s +2024-11-21 18:27:34.502103: +2024-11-21 18:27:34.502295: Epoch 1431 +2024-11-21 18:27:34.502409: Current learning rate: 0.00837 +2024-11-21 18:27:53.054083: train_loss -0.7595 +2024-11-21 18:27:53.054302: val_loss -0.7632 +2024-11-21 18:27:53.054374: Pseudo dice [0.8414] +2024-11-21 18:27:53.054448: Epoch time: 18.55 s +2024-11-21 18:27:53.899915: +2024-11-21 18:27:53.900157: Epoch 1432 +2024-11-21 18:27:53.900266: Current learning rate: 0.00837 +2024-11-21 18:28:13.103601: train_loss -0.7676 +2024-11-21 18:28:13.103822: val_loss -0.734 +2024-11-21 18:28:13.103925: Pseudo dice [0.8332] +2024-11-21 18:28:13.104027: Epoch time: 19.2 s +2024-11-21 18:28:14.090126: +2024-11-21 18:28:14.090341: Epoch 1433 +2024-11-21 18:28:14.090455: Current learning rate: 0.00837 +2024-11-21 18:28:33.503527: train_loss -0.7597 +2024-11-21 18:28:33.503761: val_loss -0.7605 +2024-11-21 18:28:33.503833: Pseudo dice [0.8555] +2024-11-21 18:28:33.503910: Epoch time: 19.41 s +2024-11-21 18:28:34.351181: +2024-11-21 18:28:34.351403: Epoch 1434 +2024-11-21 18:28:34.351520: Current learning rate: 0.00837 +2024-11-21 18:28:52.586801: train_loss -0.7606 +2024-11-21 18:28:52.587030: val_loss -0.7397 +2024-11-21 18:28:52.587109: Pseudo dice [0.8474] +2024-11-21 18:28:52.587191: Epoch time: 18.24 s +2024-11-21 18:28:53.860962: +2024-11-21 18:28:53.861170: Epoch 1435 +2024-11-21 18:28:53.861283: Current learning rate: 0.00837 +2024-11-21 18:29:11.283382: train_loss -0.7595 +2024-11-21 18:29:11.283611: val_loss -0.7464 +2024-11-21 18:29:11.283687: Pseudo dice [0.8279] +2024-11-21 18:29:11.283766: Epoch time: 17.42 s +2024-11-21 18:29:12.130577: +2024-11-21 18:29:12.130804: Epoch 1436 +2024-11-21 18:29:12.130929: Current learning rate: 0.00837 +2024-11-21 18:29:30.919480: train_loss -0.7635 +2024-11-21 18:29:30.920819: val_loss -0.7349 +2024-11-21 18:29:30.920917: Pseudo dice [0.8052] +2024-11-21 18:29:30.921008: Epoch time: 18.79 s +2024-11-21 18:29:31.873852: +2024-11-21 18:29:31.874090: Epoch 1437 +2024-11-21 18:29:31.874200: Current learning rate: 0.00837 +2024-11-21 18:29:50.702314: train_loss -0.7666 +2024-11-21 18:29:50.702526: val_loss -0.7433 +2024-11-21 18:29:50.702601: Pseudo dice [0.8318] +2024-11-21 18:29:50.702674: Epoch time: 18.83 s +2024-11-21 18:29:51.546070: +2024-11-21 18:29:51.546268: Epoch 1438 +2024-11-21 18:29:51.546384: Current learning rate: 0.00837 +2024-11-21 18:30:08.688719: train_loss -0.7702 +2024-11-21 18:30:08.688925: val_loss -0.7146 +2024-11-21 18:30:08.689008: Pseudo dice [0.8236] +2024-11-21 18:30:08.689085: Epoch time: 17.14 s +2024-11-21 18:30:09.529951: +2024-11-21 18:30:09.530174: Epoch 1439 +2024-11-21 18:30:09.530290: Current learning rate: 0.00837 +2024-11-21 18:30:28.291325: train_loss -0.7681 +2024-11-21 18:30:28.291561: val_loss -0.7119 +2024-11-21 18:30:28.291707: Pseudo dice [0.8089] +2024-11-21 18:30:28.291789: Epoch time: 18.76 s +2024-11-21 18:30:29.141662: +2024-11-21 18:30:29.141868: Epoch 1440 +2024-11-21 18:30:29.141990: Current learning rate: 0.00836 +2024-11-21 18:30:48.371159: train_loss -0.7435 +2024-11-21 18:30:48.371367: val_loss -0.7196 +2024-11-21 18:30:48.371460: Pseudo dice [0.8393] +2024-11-21 18:30:48.371536: Epoch time: 19.23 s +2024-11-21 18:30:49.256868: +2024-11-21 18:30:49.257077: Epoch 1441 +2024-11-21 18:30:49.257187: Current learning rate: 0.00836 +2024-11-21 18:31:08.019685: train_loss -0.7632 +2024-11-21 18:31:08.019899: val_loss -0.7774 +2024-11-21 18:31:08.019973: Pseudo dice [0.8638] +2024-11-21 18:31:08.020282: Epoch time: 18.76 s +2024-11-21 18:31:08.860133: +2024-11-21 18:31:08.860357: Epoch 1442 +2024-11-21 18:31:08.860468: Current learning rate: 0.00836 +2024-11-21 18:31:27.044655: train_loss -0.7649 +2024-11-21 18:31:27.044881: val_loss -0.7003 +2024-11-21 18:31:27.044957: Pseudo dice [0.7996] +2024-11-21 18:31:27.045043: Epoch time: 18.19 s +2024-11-21 18:31:27.885396: +2024-11-21 18:31:27.885597: Epoch 1443 +2024-11-21 18:31:27.885714: Current learning rate: 0.00836 +2024-11-21 18:31:46.279158: train_loss -0.7548 +2024-11-21 18:31:46.279403: val_loss -0.7207 +2024-11-21 18:31:46.279480: Pseudo dice [0.8174] +2024-11-21 18:31:46.279562: Epoch time: 18.39 s +2024-11-21 18:31:47.119393: +2024-11-21 18:31:47.119592: Epoch 1444 +2024-11-21 18:31:47.119704: Current learning rate: 0.00836 +2024-11-21 18:32:04.723050: train_loss -0.7634 +2024-11-21 18:32:04.723260: val_loss -0.7437 +2024-11-21 18:32:04.723334: Pseudo dice [0.8314] +2024-11-21 18:32:04.723411: Epoch time: 17.6 s +2024-11-21 18:32:05.567398: +2024-11-21 18:32:05.567621: Epoch 1445 +2024-11-21 18:32:05.567736: Current learning rate: 0.00836 +2024-11-21 18:32:23.778491: train_loss -0.7672 +2024-11-21 18:32:23.778704: val_loss -0.743 +2024-11-21 18:32:23.778779: Pseudo dice [0.844] +2024-11-21 18:32:23.778857: Epoch time: 18.21 s +2024-11-21 18:32:25.029422: +2024-11-21 18:32:25.029662: Epoch 1446 +2024-11-21 18:32:25.029789: Current learning rate: 0.00836 +2024-11-21 18:32:43.405904: train_loss -0.7719 +2024-11-21 18:32:43.406151: val_loss -0.7321 +2024-11-21 18:32:43.406225: Pseudo dice [0.8652] +2024-11-21 18:32:43.411463: Epoch time: 18.38 s +2024-11-21 18:32:44.294857: +2024-11-21 18:32:44.295178: Epoch 1447 +2024-11-21 18:32:44.295301: Current learning rate: 0.00836 +2024-11-21 18:33:03.397806: train_loss -0.7747 +2024-11-21 18:33:03.398020: val_loss -0.7556 +2024-11-21 18:33:03.398097: Pseudo dice [0.8266] +2024-11-21 18:33:03.398174: Epoch time: 19.1 s +2024-11-21 18:33:04.238267: +2024-11-21 18:33:04.238499: Epoch 1448 +2024-11-21 18:33:04.238612: Current learning rate: 0.00836 +2024-11-21 18:33:21.863707: train_loss -0.7644 +2024-11-21 18:33:21.863916: val_loss -0.7385 +2024-11-21 18:33:21.864010: Pseudo dice [0.8496] +2024-11-21 18:33:21.864090: Epoch time: 17.63 s +2024-11-21 18:33:22.709437: +2024-11-21 18:33:22.709718: Epoch 1449 +2024-11-21 18:33:22.709836: Current learning rate: 0.00835 +2024-11-21 18:33:41.055162: train_loss -0.7686 +2024-11-21 18:33:41.055413: val_loss -0.7535 +2024-11-21 18:33:41.055489: Pseudo dice [0.8319] +2024-11-21 18:33:41.055577: Epoch time: 18.35 s +2024-11-21 18:33:42.093209: +2024-11-21 18:33:42.093444: Epoch 1450 +2024-11-21 18:33:42.093558: Current learning rate: 0.00835 +2024-11-21 18:33:59.808520: train_loss -0.7648 +2024-11-21 18:33:59.808732: val_loss -0.7683 +2024-11-21 18:33:59.808816: Pseudo dice [0.8601] +2024-11-21 18:33:59.808898: Epoch time: 17.72 s +2024-11-21 18:34:00.645790: +2024-11-21 18:34:00.646018: Epoch 1451 +2024-11-21 18:34:00.646136: Current learning rate: 0.00835 +2024-11-21 18:34:19.074403: train_loss -0.7724 +2024-11-21 18:34:19.074616: val_loss -0.7388 +2024-11-21 18:34:19.074692: Pseudo dice [0.8427] +2024-11-21 18:34:19.074771: Epoch time: 18.43 s +2024-11-21 18:34:19.963778: +2024-11-21 18:34:19.964020: Epoch 1452 +2024-11-21 18:34:19.964139: Current learning rate: 0.00835 +2024-11-21 18:34:38.736441: train_loss -0.7812 +2024-11-21 18:34:38.741829: val_loss -0.7618 +2024-11-21 18:34:38.742013: Pseudo dice [0.866] +2024-11-21 18:34:38.742093: Epoch time: 18.77 s +2024-11-21 18:34:39.601378: +2024-11-21 18:34:39.601569: Epoch 1453 +2024-11-21 18:34:39.601680: Current learning rate: 0.00835 +2024-11-21 18:34:57.956424: train_loss -0.77 +2024-11-21 18:34:57.956671: val_loss -0.745 +2024-11-21 18:34:57.956747: Pseudo dice [0.8249] +2024-11-21 18:34:57.956831: Epoch time: 18.36 s +2024-11-21 18:34:58.921717: +2024-11-21 18:34:58.921901: Epoch 1454 +2024-11-21 18:34:58.922015: Current learning rate: 0.00835 +2024-11-21 18:35:17.659486: train_loss -0.7755 +2024-11-21 18:35:17.659696: val_loss -0.7739 +2024-11-21 18:35:17.659773: Pseudo dice [0.8495] +2024-11-21 18:35:17.659851: Epoch time: 18.74 s +2024-11-21 18:35:18.500870: +2024-11-21 18:35:18.501087: Epoch 1455 +2024-11-21 18:35:18.501206: Current learning rate: 0.00835 +2024-11-21 18:35:37.532809: train_loss -0.7719 +2024-11-21 18:35:37.539589: val_loss -0.6938 +2024-11-21 18:35:37.539687: Pseudo dice [0.8327] +2024-11-21 18:35:37.539770: Epoch time: 19.03 s +2024-11-21 18:35:38.409479: +2024-11-21 18:35:38.409697: Epoch 1456 +2024-11-21 18:35:38.409817: Current learning rate: 0.00835 +2024-11-21 18:35:57.134867: train_loss -0.7722 +2024-11-21 18:35:57.135087: val_loss -0.73 +2024-11-21 18:35:57.135160: Pseudo dice [0.8337] +2024-11-21 18:35:57.135254: Epoch time: 18.73 s +2024-11-21 18:35:58.359088: +2024-11-21 18:35:58.359304: Epoch 1457 +2024-11-21 18:35:58.359416: Current learning rate: 0.00834 +2024-11-21 18:36:17.043533: train_loss -0.7725 +2024-11-21 18:36:17.043781: val_loss -0.7189 +2024-11-21 18:36:17.043855: Pseudo dice [0.8402] +2024-11-21 18:36:17.043934: Epoch time: 18.69 s +2024-11-21 18:36:17.884508: +2024-11-21 18:36:17.884731: Epoch 1458 +2024-11-21 18:36:17.884845: Current learning rate: 0.00834 +2024-11-21 18:36:36.543770: train_loss -0.7771 +2024-11-21 18:36:36.543989: val_loss -0.7457 +2024-11-21 18:36:36.544069: Pseudo dice [0.8368] +2024-11-21 18:36:36.544146: Epoch time: 18.66 s +2024-11-21 18:36:37.384807: +2024-11-21 18:36:37.385116: Epoch 1459 +2024-11-21 18:36:37.385236: Current learning rate: 0.00834 +2024-11-21 18:36:56.078365: train_loss -0.7699 +2024-11-21 18:36:56.078572: val_loss -0.7174 +2024-11-21 18:36:56.078646: Pseudo dice [0.815] +2024-11-21 18:36:56.078720: Epoch time: 18.69 s +2024-11-21 18:36:56.913327: +2024-11-21 18:36:56.913551: Epoch 1460 +2024-11-21 18:36:56.913688: Current learning rate: 0.00834 +2024-11-21 18:37:15.515442: train_loss -0.7752 +2024-11-21 18:37:15.515732: val_loss -0.7514 +2024-11-21 18:37:15.515814: Pseudo dice [0.8551] +2024-11-21 18:37:15.515896: Epoch time: 18.6 s +2024-11-21 18:37:16.367269: +2024-11-21 18:37:16.367482: Epoch 1461 +2024-11-21 18:37:16.367596: Current learning rate: 0.00834 +2024-11-21 18:37:35.413909: train_loss -0.7724 +2024-11-21 18:37:35.414130: val_loss -0.716 +2024-11-21 18:37:35.414207: Pseudo dice [0.7919] +2024-11-21 18:37:35.414283: Epoch time: 19.05 s +2024-11-21 18:37:36.253192: +2024-11-21 18:37:36.253393: Epoch 1462 +2024-11-21 18:37:36.253501: Current learning rate: 0.00834 +2024-11-21 18:37:54.644344: train_loss -0.7718 +2024-11-21 18:37:54.644563: val_loss -0.7373 +2024-11-21 18:37:54.644647: Pseudo dice [0.8288] +2024-11-21 18:37:54.644730: Epoch time: 18.39 s +2024-11-21 18:37:55.487279: +2024-11-21 18:37:55.487491: Epoch 1463 +2024-11-21 18:37:55.487602: Current learning rate: 0.00834 +2024-11-21 18:38:15.001379: train_loss -0.7697 +2024-11-21 18:38:15.001600: val_loss -0.7052 +2024-11-21 18:38:15.001674: Pseudo dice [0.825] +2024-11-21 18:38:15.001753: Epoch time: 19.51 s +2024-11-21 18:38:15.910575: +2024-11-21 18:38:15.910913: Epoch 1464 +2024-11-21 18:38:15.911035: Current learning rate: 0.00834 +2024-11-21 18:38:36.075813: train_loss -0.7726 +2024-11-21 18:38:36.076069: val_loss -0.7373 +2024-11-21 18:38:36.076148: Pseudo dice [0.8354] +2024-11-21 18:38:36.076235: Epoch time: 20.17 s +2024-11-21 18:38:36.937633: +2024-11-21 18:38:36.937858: Epoch 1465 +2024-11-21 18:38:36.937973: Current learning rate: 0.00834 +2024-11-21 18:38:56.155319: train_loss -0.7685 +2024-11-21 18:38:56.155577: val_loss -0.7226 +2024-11-21 18:38:56.155651: Pseudo dice [0.8446] +2024-11-21 18:38:56.155731: Epoch time: 19.22 s +2024-11-21 18:38:57.018260: +2024-11-21 18:38:57.018509: Epoch 1466 +2024-11-21 18:38:57.018619: Current learning rate: 0.00833 +2024-11-21 18:39:14.884508: train_loss -0.7642 +2024-11-21 18:39:14.884719: val_loss -0.7491 +2024-11-21 18:39:14.884793: Pseudo dice [0.8416] +2024-11-21 18:39:14.884869: Epoch time: 17.87 s +2024-11-21 18:39:15.720931: +2024-11-21 18:39:15.721209: Epoch 1467 +2024-11-21 18:39:15.721326: Current learning rate: 0.00833 +2024-11-21 18:39:34.396481: train_loss -0.7648 +2024-11-21 18:39:34.396702: val_loss -0.7097 +2024-11-21 18:39:34.397037: Pseudo dice [0.8304] +2024-11-21 18:39:34.397121: Epoch time: 18.68 s +2024-11-21 18:39:35.616438: +2024-11-21 18:39:35.616756: Epoch 1468 +2024-11-21 18:39:35.616873: Current learning rate: 0.00833 +2024-11-21 18:39:54.238248: train_loss -0.7723 +2024-11-21 18:39:54.244305: val_loss -0.7606 +2024-11-21 18:39:54.244399: Pseudo dice [0.8406] +2024-11-21 18:39:54.244488: Epoch time: 18.62 s +2024-11-21 18:39:55.089369: +2024-11-21 18:39:55.089605: Epoch 1469 +2024-11-21 18:39:55.089719: Current learning rate: 0.00833 +2024-11-21 18:40:13.638793: train_loss -0.7742 +2024-11-21 18:40:13.639015: val_loss -0.7413 +2024-11-21 18:40:13.639090: Pseudo dice [0.8288] +2024-11-21 18:40:13.639168: Epoch time: 18.55 s +2024-11-21 18:40:14.485979: +2024-11-21 18:40:14.486196: Epoch 1470 +2024-11-21 18:40:14.486309: Current learning rate: 0.00833 +2024-11-21 18:40:33.661191: train_loss -0.7825 +2024-11-21 18:40:33.661405: val_loss -0.7312 +2024-11-21 18:40:33.661480: Pseudo dice [0.8096] +2024-11-21 18:40:33.661559: Epoch time: 19.18 s +2024-11-21 18:40:34.602682: +2024-11-21 18:40:34.602878: Epoch 1471 +2024-11-21 18:40:34.602985: Current learning rate: 0.00833 +2024-11-21 18:40:53.168566: train_loss -0.7758 +2024-11-21 18:40:53.168811: val_loss -0.7554 +2024-11-21 18:40:53.168887: Pseudo dice [0.8603] +2024-11-21 18:40:53.168974: Epoch time: 18.57 s +2024-11-21 18:40:54.034882: +2024-11-21 18:40:54.035092: Epoch 1472 +2024-11-21 18:40:54.035202: Current learning rate: 0.00833 +2024-11-21 18:41:12.067251: train_loss -0.7647 +2024-11-21 18:41:12.067472: val_loss -0.7034 +2024-11-21 18:41:12.067554: Pseudo dice [0.8386] +2024-11-21 18:41:12.067632: Epoch time: 18.03 s +2024-11-21 18:41:12.917426: +2024-11-21 18:41:12.917651: Epoch 1473 +2024-11-21 18:41:12.917762: Current learning rate: 0.00833 +2024-11-21 18:41:30.309947: train_loss -0.7792 +2024-11-21 18:41:30.310180: val_loss -0.7321 +2024-11-21 18:41:30.310275: Pseudo dice [0.8425] +2024-11-21 18:41:30.310355: Epoch time: 17.39 s +2024-11-21 18:41:31.187175: +2024-11-21 18:41:31.187383: Epoch 1474 +2024-11-21 18:41:31.187494: Current learning rate: 0.00833 +2024-11-21 18:41:50.902000: train_loss -0.7654 +2024-11-21 18:41:50.902217: val_loss -0.744 +2024-11-21 18:41:50.902295: Pseudo dice [0.8303] +2024-11-21 18:41:50.902374: Epoch time: 19.72 s +2024-11-21 18:41:51.844612: +2024-11-21 18:41:51.844834: Epoch 1475 +2024-11-21 18:41:51.844945: Current learning rate: 0.00832 +2024-11-21 18:42:10.208146: train_loss -0.7635 +2024-11-21 18:42:10.208389: val_loss -0.7441 +2024-11-21 18:42:10.208509: Pseudo dice [0.8286] +2024-11-21 18:42:10.208599: Epoch time: 18.36 s +2024-11-21 18:42:11.054779: +2024-11-21 18:42:11.054986: Epoch 1476 +2024-11-21 18:42:11.055107: Current learning rate: 0.00832 +2024-11-21 18:42:29.700835: train_loss -0.7687 +2024-11-21 18:42:29.701046: val_loss -0.6968 +2024-11-21 18:42:29.701124: Pseudo dice [0.8059] +2024-11-21 18:42:29.701198: Epoch time: 18.65 s +2024-11-21 18:42:30.541109: +2024-11-21 18:42:30.541363: Epoch 1477 +2024-11-21 18:42:30.541471: Current learning rate: 0.00832 +2024-11-21 18:42:48.471644: train_loss -0.7732 +2024-11-21 18:42:48.471854: val_loss -0.7334 +2024-11-21 18:42:48.471927: Pseudo dice [0.8498] +2024-11-21 18:42:48.474287: Epoch time: 17.93 s +2024-11-21 18:42:49.332977: +2024-11-21 18:42:49.333185: Epoch 1478 +2024-11-21 18:42:49.333297: Current learning rate: 0.00832 +2024-11-21 18:43:08.587142: train_loss -0.7828 +2024-11-21 18:43:08.587352: val_loss -0.7629 +2024-11-21 18:43:08.587425: Pseudo dice [0.8383] +2024-11-21 18:43:08.587505: Epoch time: 19.25 s +2024-11-21 18:43:09.433561: +2024-11-21 18:43:09.433765: Epoch 1479 +2024-11-21 18:43:09.433878: Current learning rate: 0.00832 +2024-11-21 18:43:27.558145: train_loss -0.7744 +2024-11-21 18:43:27.558388: val_loss -0.7731 +2024-11-21 18:43:27.558460: Pseudo dice [0.8353] +2024-11-21 18:43:27.558538: Epoch time: 18.13 s +2024-11-21 18:43:28.796660: +2024-11-21 18:43:28.796947: Epoch 1480 +2024-11-21 18:43:28.797063: Current learning rate: 0.00832 +2024-11-21 18:43:46.768951: train_loss -0.7637 +2024-11-21 18:43:46.769181: val_loss -0.7452 +2024-11-21 18:43:46.769258: Pseudo dice [0.8548] +2024-11-21 18:43:46.769338: Epoch time: 17.97 s +2024-11-21 18:43:47.613849: +2024-11-21 18:43:47.614065: Epoch 1481 +2024-11-21 18:43:47.614177: Current learning rate: 0.00832 +2024-11-21 18:44:06.292013: train_loss -0.7775 +2024-11-21 18:44:06.292230: val_loss -0.7167 +2024-11-21 18:44:06.292310: Pseudo dice [0.8249] +2024-11-21 18:44:06.292407: Epoch time: 18.68 s +2024-11-21 18:44:07.142261: +2024-11-21 18:44:07.142561: Epoch 1482 +2024-11-21 18:44:07.142674: Current learning rate: 0.00832 +2024-11-21 18:44:26.280261: train_loss -0.7703 +2024-11-21 18:44:26.280502: val_loss -0.7234 +2024-11-21 18:44:26.280575: Pseudo dice [0.8278] +2024-11-21 18:44:26.280655: Epoch time: 19.14 s +2024-11-21 18:44:27.292240: +2024-11-21 18:44:27.292443: Epoch 1483 +2024-11-21 18:44:27.292557: Current learning rate: 0.00831 +2024-11-21 18:44:45.779274: train_loss -0.7571 +2024-11-21 18:44:45.779489: val_loss -0.7216 +2024-11-21 18:44:45.779561: Pseudo dice [0.8186] +2024-11-21 18:44:45.779642: Epoch time: 18.49 s +2024-11-21 18:44:46.675756: +2024-11-21 18:44:46.676038: Epoch 1484 +2024-11-21 18:44:46.676151: Current learning rate: 0.00831 +2024-11-21 18:45:04.726597: train_loss -0.7549 +2024-11-21 18:45:04.726812: val_loss -0.71 +2024-11-21 18:45:04.726885: Pseudo dice [0.8073] +2024-11-21 18:45:04.726961: Epoch time: 18.05 s +2024-11-21 18:45:05.594155: +2024-11-21 18:45:05.594356: Epoch 1485 +2024-11-21 18:45:05.594471: Current learning rate: 0.00831 +2024-11-21 18:45:23.752602: train_loss -0.7623 +2024-11-21 18:45:23.752848: val_loss -0.7017 +2024-11-21 18:45:23.752932: Pseudo dice [0.8201] +2024-11-21 18:45:23.753024: Epoch time: 18.16 s +2024-11-21 18:45:24.599458: +2024-11-21 18:45:24.599662: Epoch 1486 +2024-11-21 18:45:24.599774: Current learning rate: 0.00831 +2024-11-21 18:45:42.650145: train_loss -0.7731 +2024-11-21 18:45:42.650365: val_loss -0.7313 +2024-11-21 18:45:42.650439: Pseudo dice [0.8237] +2024-11-21 18:45:42.650516: Epoch time: 18.05 s +2024-11-21 18:45:43.756145: +2024-11-21 18:45:43.756365: Epoch 1487 +2024-11-21 18:45:43.756481: Current learning rate: 0.00831 +2024-11-21 18:46:02.225887: train_loss -0.7701 +2024-11-21 18:46:02.226104: val_loss -0.7483 +2024-11-21 18:46:02.226191: Pseudo dice [0.8547] +2024-11-21 18:46:02.226274: Epoch time: 18.47 s +2024-11-21 18:46:03.068328: +2024-11-21 18:46:03.068603: Epoch 1488 +2024-11-21 18:46:03.068714: Current learning rate: 0.00831 +2024-11-21 18:46:22.208887: train_loss -0.773 +2024-11-21 18:46:22.209098: val_loss -0.721 +2024-11-21 18:46:22.209175: Pseudo dice [0.842] +2024-11-21 18:46:22.209252: Epoch time: 19.14 s +2024-11-21 18:46:23.047790: +2024-11-21 18:46:23.048292: Epoch 1489 +2024-11-21 18:46:23.048407: Current learning rate: 0.00831 +2024-11-21 18:46:41.451722: train_loss -0.7825 +2024-11-21 18:46:41.451960: val_loss -0.7217 +2024-11-21 18:46:41.452042: Pseudo dice [0.841] +2024-11-21 18:46:41.452125: Epoch time: 18.4 s +2024-11-21 18:46:42.298168: +2024-11-21 18:46:42.298388: Epoch 1490 +2024-11-21 18:46:42.298499: Current learning rate: 0.00831 +2024-11-21 18:47:01.773243: train_loss -0.7675 +2024-11-21 18:47:01.773447: val_loss -0.7602 +2024-11-21 18:47:01.773521: Pseudo dice [0.8239] +2024-11-21 18:47:01.773597: Epoch time: 19.48 s +2024-11-21 18:47:02.980445: +2024-11-21 18:47:02.980648: Epoch 1491 +2024-11-21 18:47:02.980756: Current learning rate: 0.00831 +2024-11-21 18:47:20.791820: train_loss -0.7723 +2024-11-21 18:47:20.792047: val_loss -0.7685 +2024-11-21 18:47:20.792124: Pseudo dice [0.8453] +2024-11-21 18:47:20.792202: Epoch time: 17.81 s +2024-11-21 18:47:21.639142: +2024-11-21 18:47:21.639602: Epoch 1492 +2024-11-21 18:47:21.639716: Current learning rate: 0.0083 +2024-11-21 18:47:40.482683: train_loss -0.768 +2024-11-21 18:47:40.482931: val_loss -0.7423 +2024-11-21 18:47:40.483013: Pseudo dice [0.8567] +2024-11-21 18:47:40.483111: Epoch time: 18.84 s +2024-11-21 18:47:41.326306: +2024-11-21 18:47:41.326524: Epoch 1493 +2024-11-21 18:47:41.326637: Current learning rate: 0.0083 +2024-11-21 18:48:00.213037: train_loss -0.7708 +2024-11-21 18:48:00.213250: val_loss -0.7356 +2024-11-21 18:48:00.213624: Pseudo dice [0.8507] +2024-11-21 18:48:00.213735: Epoch time: 18.89 s +2024-11-21 18:48:01.078141: +2024-11-21 18:48:01.078360: Epoch 1494 +2024-11-21 18:48:01.078474: Current learning rate: 0.0083 +2024-11-21 18:48:19.568225: train_loss -0.7715 +2024-11-21 18:48:19.568435: val_loss -0.7492 +2024-11-21 18:48:19.568508: Pseudo dice [0.8484] +2024-11-21 18:48:19.568584: Epoch time: 18.49 s +2024-11-21 18:48:20.436867: +2024-11-21 18:48:20.437086: Epoch 1495 +2024-11-21 18:48:20.437195: Current learning rate: 0.0083 +2024-11-21 18:48:39.871742: train_loss -0.7697 +2024-11-21 18:48:39.871946: val_loss -0.7237 +2024-11-21 18:48:39.872027: Pseudo dice [0.8253] +2024-11-21 18:48:39.872105: Epoch time: 19.44 s +2024-11-21 18:48:40.717107: +2024-11-21 18:48:40.717453: Epoch 1496 +2024-11-21 18:48:40.717566: Current learning rate: 0.0083 +2024-11-21 18:48:58.764556: train_loss -0.7793 +2024-11-21 18:48:58.764804: val_loss -0.7339 +2024-11-21 18:48:58.764880: Pseudo dice [0.8336] +2024-11-21 18:48:58.764964: Epoch time: 18.05 s +2024-11-21 18:48:59.691396: +2024-11-21 18:48:59.691583: Epoch 1497 +2024-11-21 18:48:59.691695: Current learning rate: 0.0083 +2024-11-21 18:49:19.072611: train_loss -0.7722 +2024-11-21 18:49:19.072828: val_loss -0.7468 +2024-11-21 18:49:19.072901: Pseudo dice [0.8485] +2024-11-21 18:49:19.072974: Epoch time: 19.38 s +2024-11-21 18:49:20.014738: +2024-11-21 18:49:20.014948: Epoch 1498 +2024-11-21 18:49:20.015071: Current learning rate: 0.0083 +2024-11-21 18:49:38.178306: train_loss -0.7696 +2024-11-21 18:49:38.183718: val_loss -0.729 +2024-11-21 18:49:38.183851: Pseudo dice [0.825] +2024-11-21 18:49:38.183940: Epoch time: 18.16 s +2024-11-21 18:49:39.066306: +2024-11-21 18:49:39.066607: Epoch 1499 +2024-11-21 18:49:39.066718: Current learning rate: 0.0083 +2024-11-21 18:49:57.535523: train_loss -0.7645 +2024-11-21 18:49:57.535736: val_loss -0.7514 +2024-11-21 18:49:57.535815: Pseudo dice [0.8423] +2024-11-21 18:49:57.535893: Epoch time: 18.47 s +2024-11-21 18:49:58.566032: +2024-11-21 18:49:58.566234: Epoch 1500 +2024-11-21 18:49:58.566346: Current learning rate: 0.0083 +2024-11-21 18:50:17.478402: train_loss -0.7481 +2024-11-21 18:50:17.478642: val_loss -0.7428 +2024-11-21 18:50:17.478716: Pseudo dice [0.8245] +2024-11-21 18:50:17.478796: Epoch time: 18.91 s +2024-11-21 18:50:18.325622: +2024-11-21 18:50:18.325824: Epoch 1501 +2024-11-21 18:50:18.325940: Current learning rate: 0.00829 +2024-11-21 18:50:36.704561: train_loss -0.7607 +2024-11-21 18:50:36.704774: val_loss -0.7459 +2024-11-21 18:50:36.704851: Pseudo dice [0.8436] +2024-11-21 18:50:36.704926: Epoch time: 18.38 s +2024-11-21 18:50:37.936402: +2024-11-21 18:50:37.936683: Epoch 1502 +2024-11-21 18:50:37.936795: Current learning rate: 0.00829 +2024-11-21 18:50:57.140143: train_loss -0.7663 +2024-11-21 18:50:57.140364: val_loss -0.7338 +2024-11-21 18:50:57.140443: Pseudo dice [0.8376] +2024-11-21 18:50:57.145753: Epoch time: 19.2 s +2024-11-21 18:50:58.190210: +2024-11-21 18:50:58.190439: Epoch 1503 +2024-11-21 18:50:58.190551: Current learning rate: 0.00829 +2024-11-21 18:51:15.758529: train_loss -0.7613 +2024-11-21 18:51:15.758779: val_loss -0.7458 +2024-11-21 18:51:15.760858: Pseudo dice [0.854] +2024-11-21 18:51:15.760965: Epoch time: 17.57 s +2024-11-21 18:51:16.610918: +2024-11-21 18:51:16.611146: Epoch 1504 +2024-11-21 18:51:16.611260: Current learning rate: 0.00829 +2024-11-21 18:51:34.971272: train_loss -0.774 +2024-11-21 18:51:34.971484: val_loss -0.7571 +2024-11-21 18:51:34.971557: Pseudo dice [0.8595] +2024-11-21 18:51:34.971631: Epoch time: 18.36 s +2024-11-21 18:51:35.812925: +2024-11-21 18:51:35.813134: Epoch 1505 +2024-11-21 18:51:35.813243: Current learning rate: 0.00829 +2024-11-21 18:51:54.187165: train_loss -0.7778 +2024-11-21 18:51:54.187378: val_loss -0.7278 +2024-11-21 18:51:54.187454: Pseudo dice [0.8478] +2024-11-21 18:51:54.187530: Epoch time: 18.38 s +2024-11-21 18:51:55.068315: +2024-11-21 18:51:55.068516: Epoch 1506 +2024-11-21 18:51:55.068629: Current learning rate: 0.00829 +2024-11-21 18:52:12.447980: train_loss -0.7667 +2024-11-21 18:52:12.448192: val_loss -0.7374 +2024-11-21 18:52:12.448266: Pseudo dice [0.8322] +2024-11-21 18:52:12.448354: Epoch time: 17.38 s +2024-11-21 18:52:13.288887: +2024-11-21 18:52:13.289285: Epoch 1507 +2024-11-21 18:52:13.289398: Current learning rate: 0.00829 +2024-11-21 18:52:31.691514: train_loss -0.7609 +2024-11-21 18:52:31.691756: val_loss -0.7447 +2024-11-21 18:52:31.691831: Pseudo dice [0.829] +2024-11-21 18:52:31.691915: Epoch time: 18.4 s +2024-11-21 18:52:32.529498: +2024-11-21 18:52:32.529723: Epoch 1508 +2024-11-21 18:52:32.529835: Current learning rate: 0.00829 +2024-11-21 18:52:51.527667: train_loss -0.768 +2024-11-21 18:52:51.527912: val_loss -0.7572 +2024-11-21 18:52:51.528004: Pseudo dice [0.8439] +2024-11-21 18:52:51.528138: Epoch time: 19.0 s +2024-11-21 18:52:52.431700: +2024-11-21 18:52:52.431923: Epoch 1509 +2024-11-21 18:52:52.432041: Current learning rate: 0.00829 +2024-11-21 18:53:10.255174: train_loss -0.7693 +2024-11-21 18:53:10.255382: val_loss -0.7541 +2024-11-21 18:53:10.255453: Pseudo dice [0.8271] +2024-11-21 18:53:10.255528: Epoch time: 17.82 s +2024-11-21 18:53:11.090971: +2024-11-21 18:53:11.091171: Epoch 1510 +2024-11-21 18:53:11.091283: Current learning rate: 0.00828 +2024-11-21 18:53:28.698517: train_loss -0.7627 +2024-11-21 18:53:28.702654: val_loss -0.7231 +2024-11-21 18:53:28.702760: Pseudo dice [0.8166] +2024-11-21 18:53:28.702849: Epoch time: 17.61 s +2024-11-21 18:53:29.563254: +2024-11-21 18:53:29.563470: Epoch 1511 +2024-11-21 18:53:29.563583: Current learning rate: 0.00828 +2024-11-21 18:53:50.091483: train_loss -0.7536 +2024-11-21 18:53:50.091730: val_loss -0.7502 +2024-11-21 18:53:50.091813: Pseudo dice [0.8379] +2024-11-21 18:53:50.091897: Epoch time: 20.53 s +2024-11-21 18:53:50.952239: +2024-11-21 18:53:50.952442: Epoch 1512 +2024-11-21 18:53:50.952552: Current learning rate: 0.00828 +2024-11-21 18:54:09.349827: train_loss -0.7527 +2024-11-21 18:54:09.350052: val_loss -0.7256 +2024-11-21 18:54:09.350130: Pseudo dice [0.8339] +2024-11-21 18:54:09.350206: Epoch time: 18.4 s +2024-11-21 18:54:10.598336: +2024-11-21 18:54:10.598544: Epoch 1513 +2024-11-21 18:54:10.598654: Current learning rate: 0.00828 +2024-11-21 18:54:28.930961: train_loss -0.7522 +2024-11-21 18:54:28.931164: val_loss -0.68 +2024-11-21 18:54:28.931237: Pseudo dice [0.8314] +2024-11-21 18:54:28.931311: Epoch time: 18.33 s +2024-11-21 18:54:29.766073: +2024-11-21 18:54:29.766299: Epoch 1514 +2024-11-21 18:54:29.766421: Current learning rate: 0.00828 +2024-11-21 18:54:48.670906: train_loss -0.7706 +2024-11-21 18:54:48.671154: val_loss -0.7507 +2024-11-21 18:54:48.671231: Pseudo dice [0.8387] +2024-11-21 18:54:48.671310: Epoch time: 18.91 s +2024-11-21 18:54:49.517539: +2024-11-21 18:54:49.517754: Epoch 1515 +2024-11-21 18:54:49.517869: Current learning rate: 0.00828 +2024-11-21 18:55:07.201462: train_loss -0.7764 +2024-11-21 18:55:07.203815: val_loss -0.7432 +2024-11-21 18:55:07.203926: Pseudo dice [0.8334] +2024-11-21 18:55:07.204010: Epoch time: 17.68 s +2024-11-21 18:55:08.266110: +2024-11-21 18:55:08.266334: Epoch 1516 +2024-11-21 18:55:08.266446: Current learning rate: 0.00828 +2024-11-21 18:55:27.090487: train_loss -0.775 +2024-11-21 18:55:27.090700: val_loss -0.757 +2024-11-21 18:55:27.096001: Pseudo dice [0.8517] +2024-11-21 18:55:27.096090: Epoch time: 18.83 s +2024-11-21 18:55:27.936226: +2024-11-21 18:55:27.936419: Epoch 1517 +2024-11-21 18:55:27.936525: Current learning rate: 0.00828 +2024-11-21 18:55:46.692668: train_loss -0.7873 +2024-11-21 18:55:46.692898: val_loss -0.7472 +2024-11-21 18:55:46.692977: Pseudo dice [0.8386] +2024-11-21 18:55:46.693090: Epoch time: 18.76 s +2024-11-21 18:55:47.539768: +2024-11-21 18:55:47.539997: Epoch 1518 +2024-11-21 18:55:47.540099: Current learning rate: 0.00827 +2024-11-21 18:56:06.685766: train_loss -0.7779 +2024-11-21 18:56:06.686001: val_loss -0.7462 +2024-11-21 18:56:06.686077: Pseudo dice [0.8298] +2024-11-21 18:56:06.686157: Epoch time: 19.15 s +2024-11-21 18:56:07.529580: +2024-11-21 18:56:07.529814: Epoch 1519 +2024-11-21 18:56:07.529927: Current learning rate: 0.00827 +2024-11-21 18:56:26.176821: train_loss -0.7795 +2024-11-21 18:56:26.177267: val_loss -0.7378 +2024-11-21 18:56:26.179476: Pseudo dice [0.835] +2024-11-21 18:56:26.179691: Epoch time: 18.65 s +2024-11-21 18:56:27.134857: +2024-11-21 18:56:27.135090: Epoch 1520 +2024-11-21 18:56:27.135200: Current learning rate: 0.00827 +2024-11-21 18:56:46.548968: train_loss -0.7769 +2024-11-21 18:56:46.549183: val_loss -0.7315 +2024-11-21 18:56:46.549255: Pseudo dice [0.8328] +2024-11-21 18:56:46.549330: Epoch time: 19.41 s +2024-11-21 18:56:47.433697: +2024-11-21 18:56:47.433905: Epoch 1521 +2024-11-21 18:56:47.434024: Current learning rate: 0.00827 +2024-11-21 18:57:06.663440: train_loss -0.7801 +2024-11-21 18:57:06.663660: val_loss -0.7728 +2024-11-21 18:57:06.663738: Pseudo dice [0.8561] +2024-11-21 18:57:06.663819: Epoch time: 19.23 s +2024-11-21 18:57:07.507488: +2024-11-21 18:57:07.507685: Epoch 1522 +2024-11-21 18:57:07.507795: Current learning rate: 0.00827 +2024-11-21 18:57:26.667240: train_loss -0.7774 +2024-11-21 18:57:26.667475: val_loss -0.7616 +2024-11-21 18:57:26.667551: Pseudo dice [0.8619] +2024-11-21 18:57:26.667632: Epoch time: 19.16 s +2024-11-21 18:57:27.510213: +2024-11-21 18:57:27.510398: Epoch 1523 +2024-11-21 18:57:27.510506: Current learning rate: 0.00827 +2024-11-21 18:57:45.379428: train_loss -0.7805 +2024-11-21 18:57:45.379640: val_loss -0.7618 +2024-11-21 18:57:45.379717: Pseudo dice [0.8344] +2024-11-21 18:57:45.379793: Epoch time: 17.87 s +2024-11-21 18:57:46.599879: +2024-11-21 18:57:46.600093: Epoch 1524 +2024-11-21 18:57:46.600206: Current learning rate: 0.00827 +2024-11-21 18:58:06.287207: train_loss -0.7696 +2024-11-21 18:58:06.287428: val_loss -0.7573 +2024-11-21 18:58:06.287508: Pseudo dice [0.8285] +2024-11-21 18:58:06.287585: Epoch time: 19.69 s +2024-11-21 18:58:07.131513: +2024-11-21 18:58:07.131729: Epoch 1525 +2024-11-21 18:58:07.131840: Current learning rate: 0.00827 +2024-11-21 18:58:24.455343: train_loss -0.772 +2024-11-21 18:58:24.455581: val_loss -0.751 +2024-11-21 18:58:24.455655: Pseudo dice [0.8527] +2024-11-21 18:58:24.455735: Epoch time: 17.32 s +2024-11-21 18:58:25.298486: +2024-11-21 18:58:25.298695: Epoch 1526 +2024-11-21 18:58:25.298804: Current learning rate: 0.00827 +2024-11-21 18:58:44.292592: train_loss -0.7767 +2024-11-21 18:58:44.294986: val_loss -0.7318 +2024-11-21 18:58:44.295091: Pseudo dice [0.8074] +2024-11-21 18:58:44.295174: Epoch time: 18.99 s +2024-11-21 18:58:45.332064: +2024-11-21 18:58:45.332282: Epoch 1527 +2024-11-21 18:58:45.332399: Current learning rate: 0.00826 +2024-11-21 18:59:03.712770: train_loss -0.7673 +2024-11-21 18:59:03.712986: val_loss -0.7585 +2024-11-21 18:59:03.713070: Pseudo dice [0.8164] +2024-11-21 18:59:03.713146: Epoch time: 18.38 s +2024-11-21 18:59:04.565014: +2024-11-21 18:59:04.565222: Epoch 1528 +2024-11-21 18:59:04.565335: Current learning rate: 0.00826 +2024-11-21 18:59:23.394164: train_loss -0.7737 +2024-11-21 18:59:23.394403: val_loss -0.7428 +2024-11-21 18:59:23.394485: Pseudo dice [0.8406] +2024-11-21 18:59:23.394573: Epoch time: 18.83 s +2024-11-21 18:59:24.259242: +2024-11-21 18:59:24.259466: Epoch 1529 +2024-11-21 18:59:24.259577: Current learning rate: 0.00826 +2024-11-21 18:59:43.197384: train_loss -0.7803 +2024-11-21 18:59:43.197628: val_loss -0.733 +2024-11-21 18:59:43.197702: Pseudo dice [0.8389] +2024-11-21 18:59:43.197783: Epoch time: 18.94 s +2024-11-21 18:59:44.177279: +2024-11-21 18:59:44.177506: Epoch 1530 +2024-11-21 18:59:44.177622: Current learning rate: 0.00826 +2024-11-21 19:00:03.356253: train_loss -0.7711 +2024-11-21 19:00:03.356472: val_loss -0.7123 +2024-11-21 19:00:03.356549: Pseudo dice [0.8369] +2024-11-21 19:00:03.356623: Epoch time: 19.18 s +2024-11-21 19:00:04.200796: +2024-11-21 19:00:04.201057: Epoch 1531 +2024-11-21 19:00:04.201167: Current learning rate: 0.00826 +2024-11-21 19:00:22.942453: train_loss -0.7714 +2024-11-21 19:00:22.942693: val_loss -0.7434 +2024-11-21 19:00:22.942765: Pseudo dice [0.8348] +2024-11-21 19:00:22.942841: Epoch time: 18.74 s +2024-11-21 19:00:23.792963: +2024-11-21 19:00:23.793156: Epoch 1532 +2024-11-21 19:00:23.793274: Current learning rate: 0.00826 +2024-11-21 19:00:42.210483: train_loss -0.7775 +2024-11-21 19:00:42.210695: val_loss -0.7367 +2024-11-21 19:00:42.210768: Pseudo dice [0.8349] +2024-11-21 19:00:42.210847: Epoch time: 18.42 s +2024-11-21 19:00:43.064472: +2024-11-21 19:00:43.064706: Epoch 1533 +2024-11-21 19:00:43.064822: Current learning rate: 0.00826 +2024-11-21 19:01:01.785990: train_loss -0.7808 +2024-11-21 19:01:01.786241: val_loss -0.7308 +2024-11-21 19:01:01.786314: Pseudo dice [0.8323] +2024-11-21 19:01:01.786394: Epoch time: 18.72 s +2024-11-21 19:01:02.636213: +2024-11-21 19:01:02.636402: Epoch 1534 +2024-11-21 19:01:02.636515: Current learning rate: 0.00826 +2024-11-21 19:01:21.323675: train_loss -0.7781 +2024-11-21 19:01:21.323888: val_loss -0.7661 +2024-11-21 19:01:21.323966: Pseudo dice [0.8481] +2024-11-21 19:01:21.326247: Epoch time: 18.69 s +2024-11-21 19:01:22.644720: +2024-11-21 19:01:22.644988: Epoch 1535 +2024-11-21 19:01:22.645106: Current learning rate: 0.00826 +2024-11-21 19:01:42.522190: train_loss -0.775 +2024-11-21 19:01:42.522411: val_loss -0.7409 +2024-11-21 19:01:42.522490: Pseudo dice [0.832] +2024-11-21 19:01:42.522566: Epoch time: 19.88 s +2024-11-21 19:01:43.379207: +2024-11-21 19:01:43.379415: Epoch 1536 +2024-11-21 19:01:43.379526: Current learning rate: 0.00825 +2024-11-21 19:02:01.300444: train_loss -0.755 +2024-11-21 19:02:01.300687: val_loss -0.6942 +2024-11-21 19:02:01.300768: Pseudo dice [0.8271] +2024-11-21 19:02:01.300851: Epoch time: 17.92 s +2024-11-21 19:02:02.149683: +2024-11-21 19:02:02.149911: Epoch 1537 +2024-11-21 19:02:02.150038: Current learning rate: 0.00825 +2024-11-21 19:02:20.561192: train_loss -0.7538 +2024-11-21 19:02:20.563590: val_loss -0.7266 +2024-11-21 19:02:20.563679: Pseudo dice [0.8239] +2024-11-21 19:02:20.563758: Epoch time: 18.41 s +2024-11-21 19:02:21.567933: +2024-11-21 19:02:21.568214: Epoch 1538 +2024-11-21 19:02:21.568332: Current learning rate: 0.00825 +2024-11-21 19:02:39.785772: train_loss -0.7713 +2024-11-21 19:02:39.785978: val_loss -0.7093 +2024-11-21 19:02:39.786057: Pseudo dice [0.8262] +2024-11-21 19:02:39.786132: Epoch time: 18.22 s +2024-11-21 19:02:40.652461: +2024-11-21 19:02:40.652661: Epoch 1539 +2024-11-21 19:02:40.652771: Current learning rate: 0.00825 +2024-11-21 19:02:59.336390: train_loss -0.7639 +2024-11-21 19:02:59.336636: val_loss -0.7342 +2024-11-21 19:02:59.336715: Pseudo dice [0.8126] +2024-11-21 19:02:59.336800: Epoch time: 18.68 s +2024-11-21 19:03:00.247418: +2024-11-21 19:03:00.247623: Epoch 1540 +2024-11-21 19:03:00.247735: Current learning rate: 0.00825 +2024-11-21 19:03:18.848946: train_loss -0.7757 +2024-11-21 19:03:18.849165: val_loss -0.7217 +2024-11-21 19:03:18.849245: Pseudo dice [0.8335] +2024-11-21 19:03:18.849320: Epoch time: 18.6 s +2024-11-21 19:03:19.695234: +2024-11-21 19:03:19.695456: Epoch 1541 +2024-11-21 19:03:19.695570: Current learning rate: 0.00825 +2024-11-21 19:03:38.116406: train_loss -0.7691 +2024-11-21 19:03:38.116632: val_loss -0.7317 +2024-11-21 19:03:38.116706: Pseudo dice [0.8264] +2024-11-21 19:03:38.116786: Epoch time: 18.42 s +2024-11-21 19:03:38.972867: +2024-11-21 19:03:38.973057: Epoch 1542 +2024-11-21 19:03:38.973166: Current learning rate: 0.00825 +2024-11-21 19:03:58.434694: train_loss -0.7719 +2024-11-21 19:03:58.434911: val_loss -0.7312 +2024-11-21 19:03:58.434985: Pseudo dice [0.8528] +2024-11-21 19:03:58.435073: Epoch time: 19.46 s +2024-11-21 19:03:59.288841: +2024-11-21 19:03:59.289126: Epoch 1543 +2024-11-21 19:03:59.289243: Current learning rate: 0.00825 +2024-11-21 19:04:17.510862: train_loss -0.7694 +2024-11-21 19:04:17.511141: val_loss -0.7141 +2024-11-21 19:04:17.511219: Pseudo dice [0.8335] +2024-11-21 19:04:17.511304: Epoch time: 18.22 s +2024-11-21 19:04:18.421021: +2024-11-21 19:04:18.421417: Epoch 1544 +2024-11-21 19:04:18.421546: Current learning rate: 0.00824 +2024-11-21 19:04:36.501860: train_loss -0.7701 +2024-11-21 19:04:36.502083: val_loss -0.7214 +2024-11-21 19:04:36.502159: Pseudo dice [0.8188] +2024-11-21 19:04:36.502295: Epoch time: 18.08 s +2024-11-21 19:04:37.348599: +2024-11-21 19:04:37.348795: Epoch 1545 +2024-11-21 19:04:37.348912: Current learning rate: 0.00824 +2024-11-21 19:04:56.040547: train_loss -0.7584 +2024-11-21 19:04:56.040963: val_loss -0.7442 +2024-11-21 19:04:56.041058: Pseudo dice [0.8348] +2024-11-21 19:04:56.041140: Epoch time: 18.69 s +2024-11-21 19:04:57.333240: +2024-11-21 19:04:57.333469: Epoch 1546 +2024-11-21 19:04:57.333590: Current learning rate: 0.00824 +2024-11-21 19:05:15.875594: train_loss -0.7602 +2024-11-21 19:05:15.875842: val_loss -0.7146 +2024-11-21 19:05:15.875918: Pseudo dice [0.8313] +2024-11-21 19:05:15.876009: Epoch time: 18.54 s +2024-11-21 19:05:16.728981: +2024-11-21 19:05:16.729254: Epoch 1547 +2024-11-21 19:05:16.729372: Current learning rate: 0.00824 +2024-11-21 19:05:35.045275: train_loss -0.7636 +2024-11-21 19:05:35.045488: val_loss -0.737 +2024-11-21 19:05:35.045563: Pseudo dice [0.8496] +2024-11-21 19:05:35.045638: Epoch time: 18.32 s +2024-11-21 19:05:35.891112: +2024-11-21 19:05:35.891328: Epoch 1548 +2024-11-21 19:05:35.891446: Current learning rate: 0.00824 +2024-11-21 19:05:54.308936: train_loss -0.7638 +2024-11-21 19:05:54.309174: val_loss -0.7532 +2024-11-21 19:05:54.309250: Pseudo dice [0.8394] +2024-11-21 19:05:54.309330: Epoch time: 18.42 s +2024-11-21 19:05:55.175237: +2024-11-21 19:05:55.175462: Epoch 1549 +2024-11-21 19:05:55.175578: Current learning rate: 0.00824 +2024-11-21 19:06:14.161345: train_loss -0.7715 +2024-11-21 19:06:14.161597: val_loss -0.727 +2024-11-21 19:06:14.161718: Pseudo dice [0.8501] +2024-11-21 19:06:14.161810: Epoch time: 18.99 s +2024-11-21 19:06:15.213434: +2024-11-21 19:06:15.213644: Epoch 1550 +2024-11-21 19:06:15.213758: Current learning rate: 0.00824 +2024-11-21 19:06:33.583163: train_loss -0.7634 +2024-11-21 19:06:33.583376: val_loss -0.7602 +2024-11-21 19:06:33.583450: Pseudo dice [0.8449] +2024-11-21 19:06:33.583525: Epoch time: 18.37 s +2024-11-21 19:06:34.432373: +2024-11-21 19:06:34.432587: Epoch 1551 +2024-11-21 19:06:34.432701: Current learning rate: 0.00824 +2024-11-21 19:06:53.114308: train_loss -0.7686 +2024-11-21 19:06:53.119704: val_loss -0.7073 +2024-11-21 19:06:53.119864: Pseudo dice [0.8298] +2024-11-21 19:06:53.119947: Epoch time: 18.68 s +2024-11-21 19:06:54.036310: +2024-11-21 19:06:54.036666: Epoch 1552 +2024-11-21 19:06:54.036791: Current learning rate: 0.00824 +2024-11-21 19:07:12.579500: train_loss -0.7663 +2024-11-21 19:07:12.579710: val_loss -0.7282 +2024-11-21 19:07:12.579783: Pseudo dice [0.8405] +2024-11-21 19:07:12.579875: Epoch time: 18.54 s +2024-11-21 19:07:13.491143: +2024-11-21 19:07:13.491355: Epoch 1553 +2024-11-21 19:07:13.491472: Current learning rate: 0.00823 +2024-11-21 19:07:31.603204: train_loss -0.7658 +2024-11-21 19:07:31.603430: val_loss -0.7365 +2024-11-21 19:07:31.603507: Pseudo dice [0.8323] +2024-11-21 19:07:31.603634: Epoch time: 18.11 s +2024-11-21 19:07:32.463010: +2024-11-21 19:07:32.463243: Epoch 1554 +2024-11-21 19:07:32.463353: Current learning rate: 0.00823 +2024-11-21 19:07:51.028426: train_loss -0.7568 +2024-11-21 19:07:51.028671: val_loss -0.7311 +2024-11-21 19:07:51.028747: Pseudo dice [0.8435] +2024-11-21 19:07:51.028828: Epoch time: 18.57 s +2024-11-21 19:07:51.882779: +2024-11-21 19:07:51.883003: Epoch 1555 +2024-11-21 19:07:51.883112: Current learning rate: 0.00823 +2024-11-21 19:08:10.464864: train_loss -0.7711 +2024-11-21 19:08:10.465083: val_loss -0.7599 +2024-11-21 19:08:10.465164: Pseudo dice [0.8424] +2024-11-21 19:08:10.465248: Epoch time: 18.58 s +2024-11-21 19:08:11.321772: +2024-11-21 19:08:11.321964: Epoch 1556 +2024-11-21 19:08:11.322072: Current learning rate: 0.00823 +2024-11-21 19:08:30.616975: train_loss -0.7626 +2024-11-21 19:08:30.617177: val_loss -0.7428 +2024-11-21 19:08:30.617251: Pseudo dice [0.8505] +2024-11-21 19:08:30.617323: Epoch time: 19.3 s +2024-11-21 19:08:31.849917: +2024-11-21 19:08:31.850125: Epoch 1557 +2024-11-21 19:08:31.850236: Current learning rate: 0.00823 +2024-11-21 19:08:51.905452: train_loss -0.7659 +2024-11-21 19:08:51.905702: val_loss -0.7422 +2024-11-21 19:08:51.905778: Pseudo dice [0.8421] +2024-11-21 19:08:51.905861: Epoch time: 20.06 s +2024-11-21 19:08:52.757732: +2024-11-21 19:08:52.757941: Epoch 1558 +2024-11-21 19:08:52.758058: Current learning rate: 0.00823 +2024-11-21 19:09:11.783238: train_loss -0.7686 +2024-11-21 19:09:11.783458: val_loss -0.7516 +2024-11-21 19:09:11.783533: Pseudo dice [0.8202] +2024-11-21 19:09:11.783617: Epoch time: 19.03 s +2024-11-21 19:09:12.813313: +2024-11-21 19:09:12.813590: Epoch 1559 +2024-11-21 19:09:12.813701: Current learning rate: 0.00823 +2024-11-21 19:09:32.003381: train_loss -0.7732 +2024-11-21 19:09:32.003593: val_loss -0.757 +2024-11-21 19:09:32.003665: Pseudo dice [0.8432] +2024-11-21 19:09:32.003741: Epoch time: 19.19 s +2024-11-21 19:09:32.860789: +2024-11-21 19:09:32.861012: Epoch 1560 +2024-11-21 19:09:32.861125: Current learning rate: 0.00823 +2024-11-21 19:09:50.564840: train_loss -0.7588 +2024-11-21 19:09:50.565098: val_loss -0.7515 +2024-11-21 19:09:50.565176: Pseudo dice [0.8308] +2024-11-21 19:09:50.565262: Epoch time: 17.7 s +2024-11-21 19:09:51.426389: +2024-11-21 19:09:51.426603: Epoch 1561 +2024-11-21 19:09:51.426714: Current learning rate: 0.00823 +2024-11-21 19:10:10.029528: train_loss -0.7691 +2024-11-21 19:10:10.029794: val_loss -0.753 +2024-11-21 19:10:10.029870: Pseudo dice [0.8376] +2024-11-21 19:10:10.029947: Epoch time: 18.6 s +2024-11-21 19:10:10.958489: +2024-11-21 19:10:10.958682: Epoch 1562 +2024-11-21 19:10:10.958796: Current learning rate: 0.00822 +2024-11-21 19:10:29.940742: train_loss -0.7607 +2024-11-21 19:10:29.940946: val_loss -0.7451 +2024-11-21 19:10:29.941031: Pseudo dice [0.8355] +2024-11-21 19:10:29.941111: Epoch time: 18.98 s +2024-11-21 19:10:30.791126: +2024-11-21 19:10:30.791355: Epoch 1563 +2024-11-21 19:10:30.791476: Current learning rate: 0.00822 +2024-11-21 19:10:49.723570: train_loss -0.7696 +2024-11-21 19:10:49.723781: val_loss -0.7489 +2024-11-21 19:10:49.723856: Pseudo dice [0.8647] +2024-11-21 19:10:49.723953: Epoch time: 18.93 s +2024-11-21 19:10:50.586676: +2024-11-21 19:10:50.586872: Epoch 1564 +2024-11-21 19:10:50.586983: Current learning rate: 0.00822 +2024-11-21 19:11:09.362013: train_loss -0.7567 +2024-11-21 19:11:09.362232: val_loss -0.7409 +2024-11-21 19:11:09.362363: Pseudo dice [0.8177] +2024-11-21 19:11:09.362448: Epoch time: 18.78 s +2024-11-21 19:11:10.324039: +2024-11-21 19:11:10.324295: Epoch 1565 +2024-11-21 19:11:10.324412: Current learning rate: 0.00822 +2024-11-21 19:11:29.184847: train_loss -0.7703 +2024-11-21 19:11:29.185093: val_loss -0.7208 +2024-11-21 19:11:29.185170: Pseudo dice [0.8319] +2024-11-21 19:11:29.185249: Epoch time: 18.86 s +2024-11-21 19:11:30.036406: +2024-11-21 19:11:30.036652: Epoch 1566 +2024-11-21 19:11:30.036764: Current learning rate: 0.00822 +2024-11-21 19:11:49.605834: train_loss -0.7662 +2024-11-21 19:11:49.606054: val_loss -0.7284 +2024-11-21 19:11:49.606133: Pseudo dice [0.8334] +2024-11-21 19:11:49.606217: Epoch time: 19.57 s +2024-11-21 19:11:50.460080: +2024-11-21 19:11:50.460316: Epoch 1567 +2024-11-21 19:11:50.460426: Current learning rate: 0.00822 +2024-11-21 19:12:09.398601: train_loss -0.7712 +2024-11-21 19:12:09.398841: val_loss -0.7745 +2024-11-21 19:12:09.398917: Pseudo dice [0.8619] +2024-11-21 19:12:09.399011: Epoch time: 18.93 s +2024-11-21 19:12:10.754735: +2024-11-21 19:12:10.754966: Epoch 1568 +2024-11-21 19:12:10.755082: Current learning rate: 0.00822 +2024-11-21 19:12:28.411665: train_loss -0.7654 +2024-11-21 19:12:28.417115: val_loss -0.7083 +2024-11-21 19:12:28.417251: Pseudo dice [0.8045] +2024-11-21 19:12:28.417346: Epoch time: 17.66 s +2024-11-21 19:12:29.483658: +2024-11-21 19:12:29.483875: Epoch 1569 +2024-11-21 19:12:29.483984: Current learning rate: 0.00822 +2024-11-21 19:12:47.114461: train_loss -0.7646 +2024-11-21 19:12:47.114687: val_loss -0.7398 +2024-11-21 19:12:47.114765: Pseudo dice [0.8413] +2024-11-21 19:12:47.114842: Epoch time: 17.63 s +2024-11-21 19:12:47.961607: +2024-11-21 19:12:47.961830: Epoch 1570 +2024-11-21 19:12:47.961942: Current learning rate: 0.00822 +2024-11-21 19:13:06.826554: train_loss -0.7689 +2024-11-21 19:13:06.826771: val_loss -0.7443 +2024-11-21 19:13:06.826851: Pseudo dice [0.8243] +2024-11-21 19:13:06.826934: Epoch time: 18.87 s +2024-11-21 19:13:07.718492: +2024-11-21 19:13:07.718701: Epoch 1571 +2024-11-21 19:13:07.718822: Current learning rate: 0.00821 +2024-11-21 19:13:26.374555: train_loss -0.7797 +2024-11-21 19:13:26.374824: val_loss -0.7122 +2024-11-21 19:13:26.374899: Pseudo dice [0.8215] +2024-11-21 19:13:26.374984: Epoch time: 18.66 s +2024-11-21 19:13:27.225353: +2024-11-21 19:13:27.225561: Epoch 1572 +2024-11-21 19:13:27.225670: Current learning rate: 0.00821 +2024-11-21 19:13:46.386053: train_loss -0.7693 +2024-11-21 19:13:46.386326: val_loss -0.7386 +2024-11-21 19:13:46.386401: Pseudo dice [0.8454] +2024-11-21 19:13:46.386478: Epoch time: 19.16 s +2024-11-21 19:13:47.253543: +2024-11-21 19:13:47.253734: Epoch 1573 +2024-11-21 19:13:47.253842: Current learning rate: 0.00821 +2024-11-21 19:14:05.000403: train_loss -0.7675 +2024-11-21 19:14:05.000617: val_loss -0.7213 +2024-11-21 19:14:05.000692: Pseudo dice [0.8315] +2024-11-21 19:14:05.000839: Epoch time: 17.75 s +2024-11-21 19:14:05.853720: +2024-11-21 19:14:05.853981: Epoch 1574 +2024-11-21 19:14:05.854103: Current learning rate: 0.00821 +2024-11-21 19:14:24.287686: train_loss -0.7694 +2024-11-21 19:14:24.287890: val_loss -0.7544 +2024-11-21 19:14:24.287963: Pseudo dice [0.85] +2024-11-21 19:14:24.288043: Epoch time: 18.43 s +2024-11-21 19:14:25.211962: +2024-11-21 19:14:25.212157: Epoch 1575 +2024-11-21 19:14:25.212281: Current learning rate: 0.00821 +2024-11-21 19:14:44.437039: train_loss -0.7736 +2024-11-21 19:14:44.437283: val_loss -0.7166 +2024-11-21 19:14:44.437360: Pseudo dice [0.8151] +2024-11-21 19:14:44.437446: Epoch time: 19.23 s +2024-11-21 19:14:45.282573: +2024-11-21 19:14:45.282783: Epoch 1576 +2024-11-21 19:14:45.282897: Current learning rate: 0.00821 +2024-11-21 19:15:04.626465: train_loss -0.7645 +2024-11-21 19:15:04.626707: val_loss -0.742 +2024-11-21 19:15:04.626787: Pseudo dice [0.8371] +2024-11-21 19:15:04.626863: Epoch time: 19.34 s +2024-11-21 19:15:05.478824: +2024-11-21 19:15:05.479029: Epoch 1577 +2024-11-21 19:15:05.479145: Current learning rate: 0.00821 +2024-11-21 19:15:24.416440: train_loss -0.7761 +2024-11-21 19:15:24.416650: val_loss -0.7538 +2024-11-21 19:15:24.416741: Pseudo dice [0.8201] +2024-11-21 19:15:24.416821: Epoch time: 18.94 s +2024-11-21 19:15:25.268470: +2024-11-21 19:15:25.268686: Epoch 1578 +2024-11-21 19:15:25.268807: Current learning rate: 0.00821 +2024-11-21 19:15:44.624535: train_loss -0.7724 +2024-11-21 19:15:44.624750: val_loss -0.7551 +2024-11-21 19:15:44.624829: Pseudo dice [0.8131] +2024-11-21 19:15:44.624914: Epoch time: 19.36 s +2024-11-21 19:15:45.881973: +2024-11-21 19:15:45.882199: Epoch 1579 +2024-11-21 19:15:45.882325: Current learning rate: 0.0082 +2024-11-21 19:16:04.219963: train_loss -0.7647 +2024-11-21 19:16:04.220231: val_loss -0.7201 +2024-11-21 19:16:04.220308: Pseudo dice [0.8459] +2024-11-21 19:16:04.220394: Epoch time: 18.34 s +2024-11-21 19:16:05.072963: +2024-11-21 19:16:05.073347: Epoch 1580 +2024-11-21 19:16:05.073461: Current learning rate: 0.0082 +2024-11-21 19:16:23.946655: train_loss -0.7627 +2024-11-21 19:16:23.946869: val_loss -0.7442 +2024-11-21 19:16:23.946947: Pseudo dice [0.8358] +2024-11-21 19:16:23.947034: Epoch time: 18.87 s +2024-11-21 19:16:24.843313: +2024-11-21 19:16:24.843524: Epoch 1581 +2024-11-21 19:16:24.843632: Current learning rate: 0.0082 +2024-11-21 19:16:43.844510: train_loss -0.7554 +2024-11-21 19:16:43.844727: val_loss -0.7329 +2024-11-21 19:16:43.844807: Pseudo dice [0.8274] +2024-11-21 19:16:43.844886: Epoch time: 19.0 s +2024-11-21 19:16:44.757669: +2024-11-21 19:16:44.757882: Epoch 1582 +2024-11-21 19:16:44.757999: Current learning rate: 0.0082 +2024-11-21 19:17:03.415749: train_loss -0.7654 +2024-11-21 19:17:03.416054: val_loss -0.7539 +2024-11-21 19:17:03.416139: Pseudo dice [0.8287] +2024-11-21 19:17:03.416240: Epoch time: 18.66 s +2024-11-21 19:17:04.271651: +2024-11-21 19:17:04.271869: Epoch 1583 +2024-11-21 19:17:04.271988: Current learning rate: 0.0082 +2024-11-21 19:17:22.405887: train_loss -0.7739 +2024-11-21 19:17:22.406110: val_loss -0.7407 +2024-11-21 19:17:22.406187: Pseudo dice [0.8208] +2024-11-21 19:17:22.406265: Epoch time: 18.14 s +2024-11-21 19:17:23.258220: +2024-11-21 19:17:23.258430: Epoch 1584 +2024-11-21 19:17:23.258543: Current learning rate: 0.0082 +2024-11-21 19:17:42.528853: train_loss -0.7804 +2024-11-21 19:17:42.529068: val_loss -0.7169 +2024-11-21 19:17:42.529143: Pseudo dice [0.8282] +2024-11-21 19:17:42.529223: Epoch time: 19.27 s +2024-11-21 19:17:43.489331: +2024-11-21 19:17:43.489539: Epoch 1585 +2024-11-21 19:17:43.489658: Current learning rate: 0.0082 +2024-11-21 19:18:02.085043: train_loss -0.7786 +2024-11-21 19:18:02.085262: val_loss -0.7099 +2024-11-21 19:18:02.085336: Pseudo dice [0.8331] +2024-11-21 19:18:02.090614: Epoch time: 18.6 s +2024-11-21 19:18:03.061325: +2024-11-21 19:18:03.061532: Epoch 1586 +2024-11-21 19:18:03.061646: Current learning rate: 0.0082 +2024-11-21 19:18:21.657104: train_loss -0.7672 +2024-11-21 19:18:21.657315: val_loss -0.746 +2024-11-21 19:18:21.657400: Pseudo dice [0.8373] +2024-11-21 19:18:21.658936: Epoch time: 18.6 s +2024-11-21 19:18:22.549119: +2024-11-21 19:18:22.549332: Epoch 1587 +2024-11-21 19:18:22.549482: Current learning rate: 0.0082 +2024-11-21 19:18:41.423210: train_loss -0.7741 +2024-11-21 19:18:41.423949: val_loss -0.7423 +2024-11-21 19:18:41.424033: Pseudo dice [0.8192] +2024-11-21 19:18:41.424111: Epoch time: 18.87 s +2024-11-21 19:18:42.278704: +2024-11-21 19:18:42.278925: Epoch 1588 +2024-11-21 19:18:42.279047: Current learning rate: 0.00819 +2024-11-21 19:19:00.734326: train_loss -0.7781 +2024-11-21 19:19:00.734537: val_loss -0.7406 +2024-11-21 19:19:00.734612: Pseudo dice [0.8402] +2024-11-21 19:19:00.734691: Epoch time: 18.46 s +2024-11-21 19:19:01.586452: +2024-11-21 19:19:01.586644: Epoch 1589 +2024-11-21 19:19:01.586756: Current learning rate: 0.00819 +2024-11-21 19:19:19.150933: train_loss -0.7716 +2024-11-21 19:19:19.151153: val_loss -0.7366 +2024-11-21 19:19:19.151226: Pseudo dice [0.849] +2024-11-21 19:19:19.151302: Epoch time: 17.57 s +2024-11-21 19:19:20.411051: +2024-11-21 19:19:20.411277: Epoch 1590 +2024-11-21 19:19:20.411390: Current learning rate: 0.00819 +2024-11-21 19:19:39.124824: train_loss -0.7284 +2024-11-21 19:19:39.125091: val_loss -0.7022 +2024-11-21 19:19:39.125191: Pseudo dice [0.8307] +2024-11-21 19:19:39.125275: Epoch time: 18.71 s +2024-11-21 19:19:39.978379: +2024-11-21 19:19:39.978585: Epoch 1591 +2024-11-21 19:19:39.978695: Current learning rate: 0.00819 +2024-11-21 19:19:58.957293: train_loss -0.76 +2024-11-21 19:19:58.957505: val_loss -0.74 +2024-11-21 19:19:58.957588: Pseudo dice [0.856] +2024-11-21 19:19:58.957667: Epoch time: 18.98 s +2024-11-21 19:19:59.847027: +2024-11-21 19:19:59.847231: Epoch 1592 +2024-11-21 19:19:59.847341: Current learning rate: 0.00819 +2024-11-21 19:20:18.484361: train_loss -0.7703 +2024-11-21 19:20:18.484584: val_loss -0.7547 +2024-11-21 19:20:18.484661: Pseudo dice [0.8335] +2024-11-21 19:20:18.484742: Epoch time: 18.64 s +2024-11-21 19:20:19.337445: +2024-11-21 19:20:19.337645: Epoch 1593 +2024-11-21 19:20:19.337757: Current learning rate: 0.00819 +2024-11-21 19:20:39.133783: train_loss -0.763 +2024-11-21 19:20:39.134047: val_loss -0.7409 +2024-11-21 19:20:39.134122: Pseudo dice [0.849] +2024-11-21 19:20:39.134209: Epoch time: 19.8 s +2024-11-21 19:20:39.997051: +2024-11-21 19:20:39.997421: Epoch 1594 +2024-11-21 19:20:39.997537: Current learning rate: 0.00819 +2024-11-21 19:20:59.412143: train_loss -0.767 +2024-11-21 19:20:59.412686: val_loss -0.7295 +2024-11-21 19:20:59.412769: Pseudo dice [0.8158] +2024-11-21 19:20:59.412849: Epoch time: 19.42 s +2024-11-21 19:21:00.267636: +2024-11-21 19:21:00.267848: Epoch 1595 +2024-11-21 19:21:00.267957: Current learning rate: 0.00819 +2024-11-21 19:21:17.889923: train_loss -0.7656 +2024-11-21 19:21:17.890164: val_loss -0.7168 +2024-11-21 19:21:17.890242: Pseudo dice [0.8408] +2024-11-21 19:21:17.890319: Epoch time: 17.62 s +2024-11-21 19:21:18.741594: +2024-11-21 19:21:18.741872: Epoch 1596 +2024-11-21 19:21:18.741997: Current learning rate: 0.00819 +2024-11-21 19:21:36.803739: train_loss -0.7669 +2024-11-21 19:21:36.803958: val_loss -0.7484 +2024-11-21 19:21:36.804093: Pseudo dice [0.8302] +2024-11-21 19:21:36.804205: Epoch time: 18.06 s +2024-11-21 19:21:37.755674: +2024-11-21 19:21:37.755878: Epoch 1597 +2024-11-21 19:21:37.755989: Current learning rate: 0.00818 +2024-11-21 19:21:55.832536: train_loss -0.7789 +2024-11-21 19:21:55.832837: val_loss -0.7386 +2024-11-21 19:21:55.832914: Pseudo dice [0.8457] +2024-11-21 19:21:55.833005: Epoch time: 18.08 s +2024-11-21 19:21:56.686966: +2024-11-21 19:21:56.687178: Epoch 1598 +2024-11-21 19:21:56.687304: Current learning rate: 0.00818 +2024-11-21 19:22:14.316339: train_loss -0.7771 +2024-11-21 19:22:14.316602: val_loss -0.7563 +2024-11-21 19:22:14.316678: Pseudo dice [0.8398] +2024-11-21 19:22:14.316756: Epoch time: 17.63 s +2024-11-21 19:22:15.172356: +2024-11-21 19:22:15.172577: Epoch 1599 +2024-11-21 19:22:15.172697: Current learning rate: 0.00818 +2024-11-21 19:22:33.455288: train_loss -0.7633 +2024-11-21 19:22:33.455504: val_loss -0.7523 +2024-11-21 19:22:33.455598: Pseudo dice [0.8521] +2024-11-21 19:22:33.455676: Epoch time: 18.28 s +2024-11-21 19:22:34.500177: +2024-11-21 19:22:34.500377: Epoch 1600 +2024-11-21 19:22:34.500487: Current learning rate: 0.00818 +2024-11-21 19:22:53.025149: train_loss -0.7714 +2024-11-21 19:22:53.025403: val_loss -0.7099 +2024-11-21 19:22:53.025481: Pseudo dice [0.8332] +2024-11-21 19:22:53.025567: Epoch time: 18.53 s +2024-11-21 19:22:54.301665: +2024-11-21 19:22:54.301889: Epoch 1601 +2024-11-21 19:22:54.302005: Current learning rate: 0.00818 +2024-11-21 19:23:13.712592: train_loss -0.7573 +2024-11-21 19:23:13.712834: val_loss -0.7063 +2024-11-21 19:23:13.712911: Pseudo dice [0.8287] +2024-11-21 19:23:13.713025: Epoch time: 19.41 s +2024-11-21 19:23:14.563546: +2024-11-21 19:23:14.563785: Epoch 1602 +2024-11-21 19:23:14.563899: Current learning rate: 0.00818 +2024-11-21 19:23:33.114811: train_loss -0.7682 +2024-11-21 19:23:33.115039: val_loss -0.7561 +2024-11-21 19:23:33.115116: Pseudo dice [0.852] +2024-11-21 19:23:33.115192: Epoch time: 18.55 s +2024-11-21 19:23:33.968359: +2024-11-21 19:23:33.968724: Epoch 1603 +2024-11-21 19:23:33.968833: Current learning rate: 0.00818 +2024-11-21 19:23:52.284780: train_loss -0.7759 +2024-11-21 19:23:52.290199: val_loss -0.7744 +2024-11-21 19:23:52.290286: Pseudo dice [0.8486] +2024-11-21 19:23:52.290370: Epoch time: 18.32 s +2024-11-21 19:23:53.166806: +2024-11-21 19:23:53.167295: Epoch 1604 +2024-11-21 19:23:53.167417: Current learning rate: 0.00818 +2024-11-21 19:24:12.078558: train_loss -0.7729 +2024-11-21 19:24:12.078796: val_loss -0.7273 +2024-11-21 19:24:12.078872: Pseudo dice [0.8529] +2024-11-21 19:24:12.078955: Epoch time: 18.91 s +2024-11-21 19:24:12.936864: +2024-11-21 19:24:12.937101: Epoch 1605 +2024-11-21 19:24:12.937218: Current learning rate: 0.00817 +2024-11-21 19:24:30.859509: train_loss -0.7745 +2024-11-21 19:24:30.859733: val_loss -0.7157 +2024-11-21 19:24:30.859818: Pseudo dice [0.8239] +2024-11-21 19:24:30.859905: Epoch time: 17.92 s +2024-11-21 19:24:31.712391: +2024-11-21 19:24:31.712620: Epoch 1606 +2024-11-21 19:24:31.712732: Current learning rate: 0.00817 +2024-11-21 19:24:50.582044: train_loss -0.7781 +2024-11-21 19:24:50.582261: val_loss -0.7288 +2024-11-21 19:24:50.582336: Pseudo dice [0.8462] +2024-11-21 19:24:50.582414: Epoch time: 18.87 s +2024-11-21 19:24:51.591102: +2024-11-21 19:24:51.591299: Epoch 1607 +2024-11-21 19:24:51.591408: Current learning rate: 0.00817 +2024-11-21 19:25:10.984792: train_loss -0.7853 +2024-11-21 19:25:10.985044: val_loss -0.743 +2024-11-21 19:25:10.985124: Pseudo dice [0.8245] +2024-11-21 19:25:10.985204: Epoch time: 19.39 s +2024-11-21 19:25:11.857541: +2024-11-21 19:25:11.857767: Epoch 1608 +2024-11-21 19:25:11.857878: Current learning rate: 0.00817 +2024-11-21 19:25:30.678148: train_loss -0.778 +2024-11-21 19:25:30.678425: val_loss -0.7634 +2024-11-21 19:25:30.678501: Pseudo dice [0.838] +2024-11-21 19:25:30.678596: Epoch time: 18.82 s +2024-11-21 19:25:31.535841: +2024-11-21 19:25:31.536046: Epoch 1609 +2024-11-21 19:25:31.536157: Current learning rate: 0.00817 +2024-11-21 19:25:49.568285: train_loss -0.7658 +2024-11-21 19:25:49.568515: val_loss -0.7441 +2024-11-21 19:25:49.568595: Pseudo dice [0.8413] +2024-11-21 19:25:49.568671: Epoch time: 18.03 s +2024-11-21 19:25:50.413700: +2024-11-21 19:25:50.413918: Epoch 1610 +2024-11-21 19:25:50.414036: Current learning rate: 0.00817 +2024-11-21 19:26:09.216998: train_loss -0.7724 +2024-11-21 19:26:09.217209: val_loss -0.7477 +2024-11-21 19:26:09.217289: Pseudo dice [0.8549] +2024-11-21 19:26:09.217369: Epoch time: 18.8 s +2024-11-21 19:26:10.064891: +2024-11-21 19:26:10.065237: Epoch 1611 +2024-11-21 19:26:10.065352: Current learning rate: 0.00817 +2024-11-21 19:26:29.451110: train_loss -0.7805 +2024-11-21 19:26:29.451853: val_loss -0.765 +2024-11-21 19:26:29.451930: Pseudo dice [0.8477] +2024-11-21 19:26:29.452017: Epoch time: 19.39 s +2024-11-21 19:26:30.694966: +2024-11-21 19:26:30.695231: Epoch 1612 +2024-11-21 19:26:30.695379: Current learning rate: 0.00817 +2024-11-21 19:26:48.968710: train_loss -0.7804 +2024-11-21 19:26:48.968976: val_loss -0.7583 +2024-11-21 19:26:48.969063: Pseudo dice [0.8347] +2024-11-21 19:26:48.969146: Epoch time: 18.27 s +2024-11-21 19:26:49.845462: +2024-11-21 19:26:49.845719: Epoch 1613 +2024-11-21 19:26:49.845837: Current learning rate: 0.00817 +2024-11-21 19:27:07.867720: train_loss -0.7732 +2024-11-21 19:27:07.867939: val_loss -0.7416 +2024-11-21 19:27:07.868023: Pseudo dice [0.8628] +2024-11-21 19:27:07.868102: Epoch time: 18.02 s +2024-11-21 19:27:08.722262: +2024-11-21 19:27:08.722503: Epoch 1614 +2024-11-21 19:27:08.722617: Current learning rate: 0.00816 +2024-11-21 19:27:27.109986: train_loss -0.7688 +2024-11-21 19:27:27.110703: val_loss -0.7563 +2024-11-21 19:27:27.110782: Pseudo dice [0.8601] +2024-11-21 19:27:27.110875: Epoch time: 18.39 s +2024-11-21 19:27:27.964113: +2024-11-21 19:27:27.964348: Epoch 1615 +2024-11-21 19:27:27.964468: Current learning rate: 0.00816 +2024-11-21 19:27:46.501968: train_loss -0.7653 +2024-11-21 19:27:46.502228: val_loss -0.7245 +2024-11-21 19:27:46.502311: Pseudo dice [0.8279] +2024-11-21 19:27:46.502397: Epoch time: 18.54 s +2024-11-21 19:27:47.365191: +2024-11-21 19:27:47.365389: Epoch 1616 +2024-11-21 19:27:47.365498: Current learning rate: 0.00816 +2024-11-21 19:28:06.957578: train_loss -0.7657 +2024-11-21 19:28:06.957792: val_loss -0.7335 +2024-11-21 19:28:06.957868: Pseudo dice [0.8325] +2024-11-21 19:28:06.957944: Epoch time: 19.59 s +2024-11-21 19:28:07.811527: +2024-11-21 19:28:07.811741: Epoch 1617 +2024-11-21 19:28:07.811858: Current learning rate: 0.00816 +2024-11-21 19:28:25.538486: train_loss -0.7717 +2024-11-21 19:28:25.538698: val_loss -0.7555 +2024-11-21 19:28:25.538778: Pseudo dice [0.8536] +2024-11-21 19:28:25.538852: Epoch time: 17.73 s +2024-11-21 19:28:26.398539: +2024-11-21 19:28:26.398835: Epoch 1618 +2024-11-21 19:28:26.398951: Current learning rate: 0.00816 +2024-11-21 19:28:44.462038: train_loss -0.7696 +2024-11-21 19:28:44.462262: val_loss -0.7239 +2024-11-21 19:28:44.464567: Pseudo dice [0.8227] +2024-11-21 19:28:44.464684: Epoch time: 18.06 s +2024-11-21 19:28:45.394643: +2024-11-21 19:28:45.394847: Epoch 1619 +2024-11-21 19:28:45.394962: Current learning rate: 0.00816 +2024-11-21 19:29:03.842039: train_loss -0.7736 +2024-11-21 19:29:03.842290: val_loss -0.7297 +2024-11-21 19:29:03.842367: Pseudo dice [0.8142] +2024-11-21 19:29:03.842453: Epoch time: 18.45 s +2024-11-21 19:29:04.689050: +2024-11-21 19:29:04.689301: Epoch 1620 +2024-11-21 19:29:04.689415: Current learning rate: 0.00816 +2024-11-21 19:29:22.226155: train_loss -0.7697 +2024-11-21 19:29:22.226365: val_loss -0.7384 +2024-11-21 19:29:22.226440: Pseudo dice [0.8454] +2024-11-21 19:29:22.226516: Epoch time: 17.54 s +2024-11-21 19:29:23.075111: +2024-11-21 19:29:23.075327: Epoch 1621 +2024-11-21 19:29:23.075442: Current learning rate: 0.00816 +2024-11-21 19:29:40.645628: train_loss -0.7766 +2024-11-21 19:29:40.645855: val_loss -0.7312 +2024-11-21 19:29:40.645934: Pseudo dice [0.8417] +2024-11-21 19:29:40.646018: Epoch time: 17.57 s +2024-11-21 19:29:41.532955: +2024-11-21 19:29:41.533367: Epoch 1622 +2024-11-21 19:29:41.533505: Current learning rate: 0.00816 +2024-11-21 19:30:00.663324: train_loss -0.7795 +2024-11-21 19:30:00.663594: val_loss -0.74 +2024-11-21 19:30:00.663677: Pseudo dice [0.8381] +2024-11-21 19:30:00.663767: Epoch time: 19.13 s +2024-11-21 19:30:01.958194: +2024-11-21 19:30:01.958402: Epoch 1623 +2024-11-21 19:30:01.958516: Current learning rate: 0.00815 +2024-11-21 19:30:20.191542: train_loss -0.7818 +2024-11-21 19:30:20.191762: val_loss -0.73 +2024-11-21 19:30:20.191835: Pseudo dice [0.8079] +2024-11-21 19:30:20.191911: Epoch time: 18.23 s +2024-11-21 19:30:21.043286: +2024-11-21 19:30:21.043514: Epoch 1624 +2024-11-21 19:30:21.043633: Current learning rate: 0.00815 +2024-11-21 19:30:40.313160: train_loss -0.7689 +2024-11-21 19:30:40.313385: val_loss -0.741 +2024-11-21 19:30:40.313458: Pseudo dice [0.8403] +2024-11-21 19:30:40.313534: Epoch time: 19.27 s +2024-11-21 19:30:41.164105: +2024-11-21 19:30:41.164318: Epoch 1625 +2024-11-21 19:30:41.164431: Current learning rate: 0.00815 +2024-11-21 19:31:00.213515: train_loss -0.7815 +2024-11-21 19:31:00.213770: val_loss -0.7507 +2024-11-21 19:31:00.213851: Pseudo dice [0.8545] +2024-11-21 19:31:00.213938: Epoch time: 19.05 s +2024-11-21 19:31:01.072896: +2024-11-21 19:31:01.073113: Epoch 1626 +2024-11-21 19:31:01.073225: Current learning rate: 0.00815 +2024-11-21 19:31:20.281782: train_loss -0.7809 +2024-11-21 19:31:20.282049: val_loss -0.7495 +2024-11-21 19:31:20.282125: Pseudo dice [0.8301] +2024-11-21 19:31:20.282200: Epoch time: 19.21 s +2024-11-21 19:31:21.141045: +2024-11-21 19:31:21.141265: Epoch 1627 +2024-11-21 19:31:21.141377: Current learning rate: 0.00815 +2024-11-21 19:31:39.474066: train_loss -0.7728 +2024-11-21 19:31:39.474314: val_loss -0.7511 +2024-11-21 19:31:39.474397: Pseudo dice [0.8416] +2024-11-21 19:31:39.474475: Epoch time: 18.33 s +2024-11-21 19:31:40.428976: +2024-11-21 19:31:40.429290: Epoch 1628 +2024-11-21 19:31:40.429404: Current learning rate: 0.00815 +2024-11-21 19:31:58.908252: train_loss -0.7786 +2024-11-21 19:31:58.908481: val_loss -0.7538 +2024-11-21 19:31:58.908555: Pseudo dice [0.8275] +2024-11-21 19:31:58.908632: Epoch time: 18.48 s +2024-11-21 19:31:59.823952: +2024-11-21 19:31:59.824236: Epoch 1629 +2024-11-21 19:31:59.824352: Current learning rate: 0.00815 +2024-11-21 19:32:17.596711: train_loss -0.7773 +2024-11-21 19:32:17.596952: val_loss -0.7378 +2024-11-21 19:32:17.597036: Pseudo dice [0.836] +2024-11-21 19:32:17.597121: Epoch time: 17.77 s +2024-11-21 19:32:18.451886: +2024-11-21 19:32:18.452213: Epoch 1630 +2024-11-21 19:32:18.452332: Current learning rate: 0.00815 +2024-11-21 19:32:36.834301: train_loss -0.7685 +2024-11-21 19:32:36.834591: val_loss -0.7214 +2024-11-21 19:32:36.834671: Pseudo dice [0.8374] +2024-11-21 19:32:36.834745: Epoch time: 18.38 s +2024-11-21 19:32:37.684822: +2024-11-21 19:32:37.685059: Epoch 1631 +2024-11-21 19:32:37.685178: Current learning rate: 0.00814 +2024-11-21 19:32:56.997719: train_loss -0.7694 +2024-11-21 19:32:56.997937: val_loss -0.7721 +2024-11-21 19:32:56.998022: Pseudo dice [0.852] +2024-11-21 19:32:57.000281: Epoch time: 19.31 s +2024-11-21 19:32:57.873795: +2024-11-21 19:32:57.874005: Epoch 1632 +2024-11-21 19:32:57.874126: Current learning rate: 0.00814 +2024-11-21 19:33:16.065853: train_loss -0.7824 +2024-11-21 19:33:16.066130: val_loss -0.7519 +2024-11-21 19:33:16.066212: Pseudo dice [0.8413] +2024-11-21 19:33:16.066292: Epoch time: 18.19 s +2024-11-21 19:33:16.925144: +2024-11-21 19:33:16.925364: Epoch 1633 +2024-11-21 19:33:16.925478: Current learning rate: 0.00814 +2024-11-21 19:33:36.391292: train_loss -0.7799 +2024-11-21 19:33:36.391534: val_loss -0.7081 +2024-11-21 19:33:36.391616: Pseudo dice [0.8389] +2024-11-21 19:33:36.391744: Epoch time: 19.47 s +2024-11-21 19:33:37.646572: +2024-11-21 19:33:37.647033: Epoch 1634 +2024-11-21 19:33:37.647167: Current learning rate: 0.00814 +2024-11-21 19:33:56.295112: train_loss -0.7709 +2024-11-21 19:33:56.295331: val_loss -0.7259 +2024-11-21 19:33:56.295407: Pseudo dice [0.8418] +2024-11-21 19:33:56.295483: Epoch time: 18.65 s +2024-11-21 19:33:57.150976: +2024-11-21 19:33:57.151422: Epoch 1635 +2024-11-21 19:33:57.151553: Current learning rate: 0.00814 +2024-11-21 19:34:15.247576: train_loss -0.7776 +2024-11-21 19:34:15.247793: val_loss -0.7488 +2024-11-21 19:34:15.250084: Pseudo dice [0.8326] +2024-11-21 19:34:15.250195: Epoch time: 18.1 s +2024-11-21 19:34:16.217372: +2024-11-21 19:34:16.217831: Epoch 1636 +2024-11-21 19:34:16.217970: Current learning rate: 0.00814 +2024-11-21 19:34:34.476951: train_loss -0.7728 +2024-11-21 19:34:34.477200: val_loss -0.7586 +2024-11-21 19:34:34.477276: Pseudo dice [0.8451] +2024-11-21 19:34:34.477355: Epoch time: 18.26 s +2024-11-21 19:34:35.494497: +2024-11-21 19:34:35.494983: Epoch 1637 +2024-11-21 19:34:35.495121: Current learning rate: 0.00814 +2024-11-21 19:34:54.897476: train_loss -0.7666 +2024-11-21 19:34:54.897725: val_loss -0.7584 +2024-11-21 19:34:54.897800: Pseudo dice [0.8432] +2024-11-21 19:34:54.897876: Epoch time: 19.4 s +2024-11-21 19:34:55.736329: +2024-11-21 19:34:55.736758: Epoch 1638 +2024-11-21 19:34:55.736893: Current learning rate: 0.00814 +2024-11-21 19:35:14.337597: train_loss -0.7666 +2024-11-21 19:35:14.337819: val_loss -0.7305 +2024-11-21 19:35:14.337896: Pseudo dice [0.8273] +2024-11-21 19:35:14.337974: Epoch time: 18.6 s +2024-11-21 19:35:15.343448: +2024-11-21 19:35:15.343918: Epoch 1639 +2024-11-21 19:35:15.344064: Current learning rate: 0.00814 +2024-11-21 19:35:34.721743: train_loss -0.7626 +2024-11-21 19:35:34.722038: val_loss -0.7255 +2024-11-21 19:35:34.722117: Pseudo dice [0.8388] +2024-11-21 19:35:34.722203: Epoch time: 19.38 s +2024-11-21 19:35:35.565164: +2024-11-21 19:35:35.565648: Epoch 1640 +2024-11-21 19:35:35.565787: Current learning rate: 0.00813 +2024-11-21 19:35:54.397717: train_loss -0.776 +2024-11-21 19:35:54.397939: val_loss -0.7103 +2024-11-21 19:35:54.398025: Pseudo dice [0.8411] +2024-11-21 19:35:54.398104: Epoch time: 18.83 s +2024-11-21 19:35:55.235955: +2024-11-21 19:35:55.236385: Epoch 1641 +2024-11-21 19:35:55.236526: Current learning rate: 0.00813 +2024-11-21 19:36:14.450393: train_loss -0.7726 +2024-11-21 19:36:14.450618: val_loss -0.7328 +2024-11-21 19:36:14.450696: Pseudo dice [0.819] +2024-11-21 19:36:14.450773: Epoch time: 19.22 s +2024-11-21 19:36:15.286437: +2024-11-21 19:36:15.286869: Epoch 1642 +2024-11-21 19:36:15.287015: Current learning rate: 0.00813 +2024-11-21 19:36:34.380530: train_loss -0.7696 +2024-11-21 19:36:34.380744: val_loss -0.7067 +2024-11-21 19:36:34.380818: Pseudo dice [0.8337] +2024-11-21 19:36:34.380891: Epoch time: 19.09 s +2024-11-21 19:36:35.224731: +2024-11-21 19:36:35.225214: Epoch 1643 +2024-11-21 19:36:35.225352: Current learning rate: 0.00813 +2024-11-21 19:36:54.893921: train_loss -0.7653 +2024-11-21 19:36:54.894249: val_loss -0.7518 +2024-11-21 19:36:54.894326: Pseudo dice [0.8505] +2024-11-21 19:36:54.894416: Epoch time: 19.67 s +2024-11-21 19:36:55.821430: +2024-11-21 19:36:55.821636: Epoch 1644 +2024-11-21 19:36:55.821752: Current learning rate: 0.00813 +2024-11-21 19:37:15.084465: train_loss -0.7783 +2024-11-21 19:37:15.084683: val_loss -0.7466 +2024-11-21 19:37:15.084758: Pseudo dice [0.8335] +2024-11-21 19:37:15.084835: Epoch time: 19.26 s +2024-11-21 19:37:15.925732: +2024-11-21 19:37:15.925925: Epoch 1645 +2024-11-21 19:37:15.926038: Current learning rate: 0.00813 +2024-11-21 19:37:34.046026: train_loss -0.771 +2024-11-21 19:37:34.046257: val_loss -0.7308 +2024-11-21 19:37:34.046340: Pseudo dice [0.8389] +2024-11-21 19:37:34.046427: Epoch time: 18.12 s +2024-11-21 19:37:34.876972: +2024-11-21 19:37:34.877275: Epoch 1646 +2024-11-21 19:37:34.877389: Current learning rate: 0.00813 +2024-11-21 19:37:54.376752: train_loss -0.7626 +2024-11-21 19:37:54.379234: val_loss -0.7533 +2024-11-21 19:37:54.379339: Pseudo dice [0.8311] +2024-11-21 19:37:54.379430: Epoch time: 19.5 s +2024-11-21 19:37:55.227776: +2024-11-21 19:37:55.228145: Epoch 1647 +2024-11-21 19:37:55.228256: Current learning rate: 0.00813 +2024-11-21 19:38:14.257228: train_loss -0.7679 +2024-11-21 19:38:14.257439: val_loss -0.7319 +2024-11-21 19:38:14.257513: Pseudo dice [0.8332] +2024-11-21 19:38:14.257588: Epoch time: 19.03 s +2024-11-21 19:38:15.102887: +2024-11-21 19:38:15.103144: Epoch 1648 +2024-11-21 19:38:15.103263: Current learning rate: 0.00813 +2024-11-21 19:38:34.619097: train_loss -0.767 +2024-11-21 19:38:34.619314: val_loss -0.6786 +2024-11-21 19:38:34.619395: Pseudo dice [0.8405] +2024-11-21 19:38:34.619485: Epoch time: 19.52 s +2024-11-21 19:38:35.459445: +2024-11-21 19:38:35.459651: Epoch 1649 +2024-11-21 19:38:35.460018: Current learning rate: 0.00812 +2024-11-21 19:38:53.665454: train_loss -0.7646 +2024-11-21 19:38:53.665728: val_loss -0.7397 +2024-11-21 19:38:53.665804: Pseudo dice [0.8179] +2024-11-21 19:38:53.666563: Epoch time: 18.21 s +2024-11-21 19:38:54.901363: +2024-11-21 19:38:54.901570: Epoch 1650 +2024-11-21 19:38:54.901682: Current learning rate: 0.00812 +2024-11-21 19:39:14.045811: train_loss -0.7663 +2024-11-21 19:39:14.046049: val_loss -0.7337 +2024-11-21 19:39:14.046124: Pseudo dice [0.8657] +2024-11-21 19:39:14.046203: Epoch time: 19.15 s +2024-11-21 19:39:14.989658: +2024-11-21 19:39:14.989870: Epoch 1651 +2024-11-21 19:39:14.989989: Current learning rate: 0.00812 +2024-11-21 19:39:33.821567: train_loss -0.7694 +2024-11-21 19:39:33.821790: val_loss -0.7415 +2024-11-21 19:39:33.821867: Pseudo dice [0.8207] +2024-11-21 19:39:33.821944: Epoch time: 18.83 s +2024-11-21 19:39:34.681108: +2024-11-21 19:39:34.681308: Epoch 1652 +2024-11-21 19:39:34.681418: Current learning rate: 0.00812 +2024-11-21 19:39:54.077892: train_loss -0.7641 +2024-11-21 19:39:54.083302: val_loss -0.7513 +2024-11-21 19:39:54.083408: Pseudo dice [0.8408] +2024-11-21 19:39:54.083487: Epoch time: 19.4 s +2024-11-21 19:39:55.044389: +2024-11-21 19:39:55.044610: Epoch 1653 +2024-11-21 19:39:55.044720: Current learning rate: 0.00812 +2024-11-21 19:40:13.503575: train_loss -0.7682 +2024-11-21 19:40:13.503870: val_loss -0.7336 +2024-11-21 19:40:13.503946: Pseudo dice [0.8687] +2024-11-21 19:40:13.504038: Epoch time: 18.46 s +2024-11-21 19:40:14.348510: +2024-11-21 19:40:14.348790: Epoch 1654 +2024-11-21 19:40:14.348904: Current learning rate: 0.00812 +2024-11-21 19:40:32.720783: train_loss -0.7746 +2024-11-21 19:40:32.721010: val_loss -0.7466 +2024-11-21 19:40:32.721090: Pseudo dice [0.8372] +2024-11-21 19:40:32.721166: Epoch time: 18.37 s +2024-11-21 19:40:33.572099: +2024-11-21 19:40:33.572308: Epoch 1655 +2024-11-21 19:40:33.572425: Current learning rate: 0.00812 +2024-11-21 19:40:53.057446: train_loss -0.7728 +2024-11-21 19:40:53.057654: val_loss -0.7287 +2024-11-21 19:40:53.057728: Pseudo dice [0.814] +2024-11-21 19:40:53.057804: Epoch time: 19.49 s +2024-11-21 19:40:53.929039: +2024-11-21 19:40:53.929243: Epoch 1656 +2024-11-21 19:40:53.929356: Current learning rate: 0.00812 +2024-11-21 19:41:11.901988: train_loss -0.7695 +2024-11-21 19:41:11.902239: val_loss -0.7147 +2024-11-21 19:41:11.902319: Pseudo dice [0.8169] +2024-11-21 19:41:11.902400: Epoch time: 17.97 s +2024-11-21 19:41:12.743891: +2024-11-21 19:41:12.744258: Epoch 1657 +2024-11-21 19:41:12.744409: Current learning rate: 0.00811 +2024-11-21 19:41:31.601119: train_loss -0.7711 +2024-11-21 19:41:31.601340: val_loss -0.7161 +2024-11-21 19:41:31.601413: Pseudo dice [0.821] +2024-11-21 19:41:31.601490: Epoch time: 18.86 s +2024-11-21 19:41:32.441378: +2024-11-21 19:41:32.441595: Epoch 1658 +2024-11-21 19:41:32.441705: Current learning rate: 0.00811 +2024-11-21 19:41:50.881028: train_loss -0.7771 +2024-11-21 19:41:50.881242: val_loss -0.7514 +2024-11-21 19:41:50.881318: Pseudo dice [0.829] +2024-11-21 19:41:50.881393: Epoch time: 18.44 s +2024-11-21 19:41:51.718828: +2024-11-21 19:41:51.719119: Epoch 1659 +2024-11-21 19:41:51.719234: Current learning rate: 0.00811 +2024-11-21 19:42:11.480051: train_loss -0.7675 +2024-11-21 19:42:11.480320: val_loss -0.7254 +2024-11-21 19:42:11.480397: Pseudo dice [0.8492] +2024-11-21 19:42:11.480473: Epoch time: 19.76 s +2024-11-21 19:42:12.397578: +2024-11-21 19:42:12.397879: Epoch 1660 +2024-11-21 19:42:12.397998: Current learning rate: 0.00811 +2024-11-21 19:42:31.279467: train_loss -0.7689 +2024-11-21 19:42:31.279732: val_loss -0.7101 +2024-11-21 19:42:31.279808: Pseudo dice [0.8356] +2024-11-21 19:42:31.279893: Epoch time: 18.88 s +2024-11-21 19:42:32.136919: +2024-11-21 19:42:32.137214: Epoch 1661 +2024-11-21 19:42:32.137329: Current learning rate: 0.00811 +2024-11-21 19:42:49.925799: train_loss -0.7676 +2024-11-21 19:42:49.926017: val_loss -0.7248 +2024-11-21 19:42:49.926106: Pseudo dice [0.8236] +2024-11-21 19:42:49.926187: Epoch time: 17.79 s +2024-11-21 19:42:50.766662: +2024-11-21 19:42:50.766880: Epoch 1662 +2024-11-21 19:42:50.767005: Current learning rate: 0.00811 +2024-11-21 19:43:09.933209: train_loss -0.765 +2024-11-21 19:43:09.933433: val_loss -0.724 +2024-11-21 19:43:09.933512: Pseudo dice [0.8048] +2024-11-21 19:43:09.933589: Epoch time: 19.17 s +2024-11-21 19:43:10.776752: +2024-11-21 19:43:10.777049: Epoch 1663 +2024-11-21 19:43:10.777170: Current learning rate: 0.00811 +2024-11-21 19:43:29.261030: train_loss -0.7747 +2024-11-21 19:43:29.261264: val_loss -0.7325 +2024-11-21 19:43:29.261363: Pseudo dice [0.8358] +2024-11-21 19:43:29.261512: Epoch time: 18.49 s +2024-11-21 19:43:30.107690: +2024-11-21 19:43:30.107979: Epoch 1664 +2024-11-21 19:43:30.108099: Current learning rate: 0.00811 +2024-11-21 19:43:48.659095: train_loss -0.7692 +2024-11-21 19:43:48.659338: val_loss -0.7286 +2024-11-21 19:43:48.659416: Pseudo dice [0.8362] +2024-11-21 19:43:48.659496: Epoch time: 18.55 s +2024-11-21 19:43:49.496703: +2024-11-21 19:43:49.496896: Epoch 1665 +2024-11-21 19:43:49.497033: Current learning rate: 0.00811 +2024-11-21 19:44:09.523366: train_loss -0.7651 +2024-11-21 19:44:09.523595: val_loss -0.7599 +2024-11-21 19:44:09.523673: Pseudo dice [0.8331] +2024-11-21 19:44:09.523770: Epoch time: 20.03 s +2024-11-21 19:44:10.359069: +2024-11-21 19:44:10.359280: Epoch 1666 +2024-11-21 19:44:10.359395: Current learning rate: 0.0081 +2024-11-21 19:44:28.945462: train_loss -0.7672 +2024-11-21 19:44:28.945686: val_loss -0.7445 +2024-11-21 19:44:28.945765: Pseudo dice [0.8332] +2024-11-21 19:44:28.945842: Epoch time: 18.59 s +2024-11-21 19:44:29.787347: +2024-11-21 19:44:29.787545: Epoch 1667 +2024-11-21 19:44:29.787657: Current learning rate: 0.0081 +2024-11-21 19:44:48.527440: train_loss -0.756 +2024-11-21 19:44:48.527692: val_loss -0.7442 +2024-11-21 19:44:48.527766: Pseudo dice [0.8302] +2024-11-21 19:44:48.527848: Epoch time: 18.74 s +2024-11-21 19:44:49.775112: +2024-11-21 19:44:49.775339: Epoch 1668 +2024-11-21 19:44:49.775449: Current learning rate: 0.0081 +2024-11-21 19:45:08.112899: train_loss -0.7626 +2024-11-21 19:45:08.113122: val_loss -0.7514 +2024-11-21 19:45:08.113200: Pseudo dice [0.8284] +2024-11-21 19:45:08.113276: Epoch time: 18.34 s +2024-11-21 19:45:08.957849: +2024-11-21 19:45:08.958165: Epoch 1669 +2024-11-21 19:45:08.958282: Current learning rate: 0.0081 +2024-11-21 19:45:27.316929: train_loss -0.7755 +2024-11-21 19:45:27.317184: val_loss -0.7414 +2024-11-21 19:45:27.317268: Pseudo dice [0.8474] +2024-11-21 19:45:27.317349: Epoch time: 18.36 s +2024-11-21 19:45:28.167827: +2024-11-21 19:45:28.168081: Epoch 1670 +2024-11-21 19:45:28.168203: Current learning rate: 0.0081 +2024-11-21 19:45:46.855432: train_loss -0.77 +2024-11-21 19:45:46.855692: val_loss -0.7433 +2024-11-21 19:45:46.855784: Pseudo dice [0.8483] +2024-11-21 19:45:46.855879: Epoch time: 18.69 s +2024-11-21 19:45:47.706324: +2024-11-21 19:45:47.706525: Epoch 1671 +2024-11-21 19:45:47.706634: Current learning rate: 0.0081 +2024-11-21 19:46:06.946311: train_loss -0.7795 +2024-11-21 19:46:06.946552: val_loss -0.7294 +2024-11-21 19:46:06.946635: Pseudo dice [0.8152] +2024-11-21 19:46:06.946713: Epoch time: 19.24 s +2024-11-21 19:46:07.798513: +2024-11-21 19:46:07.798743: Epoch 1672 +2024-11-21 19:46:07.798856: Current learning rate: 0.0081 +2024-11-21 19:46:26.765874: train_loss -0.7783 +2024-11-21 19:46:26.766086: val_loss -0.7313 +2024-11-21 19:46:26.766175: Pseudo dice [0.8336] +2024-11-21 19:46:26.766273: Epoch time: 18.97 s +2024-11-21 19:46:27.614847: +2024-11-21 19:46:27.615059: Epoch 1673 +2024-11-21 19:46:27.615170: Current learning rate: 0.0081 +2024-11-21 19:46:44.969342: train_loss -0.781 +2024-11-21 19:46:44.969560: val_loss -0.7546 +2024-11-21 19:46:44.969635: Pseudo dice [0.8387] +2024-11-21 19:46:44.969713: Epoch time: 17.36 s +2024-11-21 19:46:45.817966: +2024-11-21 19:46:45.818160: Epoch 1674 +2024-11-21 19:46:45.818276: Current learning rate: 0.0081 +2024-11-21 19:47:04.845134: train_loss -0.7674 +2024-11-21 19:47:04.845358: val_loss -0.716 +2024-11-21 19:47:04.845433: Pseudo dice [0.821] +2024-11-21 19:47:04.845511: Epoch time: 19.03 s +2024-11-21 19:47:05.697085: +2024-11-21 19:47:05.697285: Epoch 1675 +2024-11-21 19:47:05.697644: Current learning rate: 0.00809 +2024-11-21 19:47:24.114806: train_loss -0.7766 +2024-11-21 19:47:24.115059: val_loss -0.7365 +2024-11-21 19:47:24.115143: Pseudo dice [0.8415] +2024-11-21 19:47:24.115252: Epoch time: 18.42 s +2024-11-21 19:47:24.972118: +2024-11-21 19:47:24.972308: Epoch 1676 +2024-11-21 19:47:24.972418: Current learning rate: 0.00809 +2024-11-21 19:47:43.316313: train_loss -0.7742 +2024-11-21 19:47:43.318729: val_loss -0.735 +2024-11-21 19:47:43.318829: Pseudo dice [0.8416] +2024-11-21 19:47:43.318915: Epoch time: 18.34 s +2024-11-21 19:47:44.282544: +2024-11-21 19:47:44.282770: Epoch 1677 +2024-11-21 19:47:44.282883: Current learning rate: 0.00809 +2024-11-21 19:48:02.784167: train_loss -0.7647 +2024-11-21 19:48:02.786451: val_loss -0.7136 +2024-11-21 19:48:02.786578: Pseudo dice [0.8443] +2024-11-21 19:48:02.786659: Epoch time: 18.5 s +2024-11-21 19:48:03.638058: +2024-11-21 19:48:03.638271: Epoch 1678 +2024-11-21 19:48:03.638384: Current learning rate: 0.00809 +2024-11-21 19:48:22.807379: train_loss -0.7549 +2024-11-21 19:48:22.807633: val_loss -0.6944 +2024-11-21 19:48:22.807723: Pseudo dice [0.7924] +2024-11-21 19:48:22.807811: Epoch time: 19.17 s +2024-11-21 19:48:24.114665: +2024-11-21 19:48:24.114868: Epoch 1679 +2024-11-21 19:48:24.114981: Current learning rate: 0.00809 +2024-11-21 19:48:42.558284: train_loss -0.7667 +2024-11-21 19:48:42.558517: val_loss -0.742 +2024-11-21 19:48:42.558593: Pseudo dice [0.8332] +2024-11-21 19:48:42.558731: Epoch time: 18.44 s +2024-11-21 19:48:43.403374: +2024-11-21 19:48:43.403580: Epoch 1680 +2024-11-21 19:48:43.403691: Current learning rate: 0.00809 +2024-11-21 19:49:02.314449: train_loss -0.7638 +2024-11-21 19:49:02.319847: val_loss -0.721 +2024-11-21 19:49:02.319953: Pseudo dice [0.8174] +2024-11-21 19:49:02.320043: Epoch time: 18.91 s +2024-11-21 19:49:03.424931: +2024-11-21 19:49:03.425168: Epoch 1681 +2024-11-21 19:49:03.425284: Current learning rate: 0.00809 +2024-11-21 19:49:21.993882: train_loss -0.7623 +2024-11-21 19:49:21.994132: val_loss -0.7211 +2024-11-21 19:49:21.994208: Pseudo dice [0.8324] +2024-11-21 19:49:21.994293: Epoch time: 18.57 s +2024-11-21 19:49:22.852766: +2024-11-21 19:49:22.853006: Epoch 1682 +2024-11-21 19:49:22.853118: Current learning rate: 0.00809 +2024-11-21 19:49:41.897382: train_loss -0.7566 +2024-11-21 19:49:41.897600: val_loss -0.7365 +2024-11-21 19:49:41.897677: Pseudo dice [0.83] +2024-11-21 19:49:41.897755: Epoch time: 19.05 s +2024-11-21 19:49:42.743031: +2024-11-21 19:49:42.743299: Epoch 1683 +2024-11-21 19:49:42.743413: Current learning rate: 0.00808 +2024-11-21 19:50:01.570772: train_loss -0.7716 +2024-11-21 19:50:01.576167: val_loss -0.7261 +2024-11-21 19:50:01.576251: Pseudo dice [0.8374] +2024-11-21 19:50:01.576329: Epoch time: 18.83 s +2024-11-21 19:50:02.452502: +2024-11-21 19:50:02.452714: Epoch 1684 +2024-11-21 19:50:02.452835: Current learning rate: 0.00808 +2024-11-21 19:50:21.315895: train_loss -0.7741 +2024-11-21 19:50:21.318297: val_loss -0.763 +2024-11-21 19:50:21.318388: Pseudo dice [0.845] +2024-11-21 19:50:21.318468: Epoch time: 18.86 s +2024-11-21 19:50:22.190915: +2024-11-21 19:50:22.191132: Epoch 1685 +2024-11-21 19:50:22.191252: Current learning rate: 0.00808 +2024-11-21 19:50:41.212101: train_loss -0.7753 +2024-11-21 19:50:41.212337: val_loss -0.7418 +2024-11-21 19:50:41.213974: Pseudo dice [0.8394] +2024-11-21 19:50:41.214094: Epoch time: 19.02 s +2024-11-21 19:50:42.085750: +2024-11-21 19:50:42.086002: Epoch 1686 +2024-11-21 19:50:42.086123: Current learning rate: 0.00808 +2024-11-21 19:51:00.037241: train_loss -0.7678 +2024-11-21 19:51:00.037460: val_loss -0.7569 +2024-11-21 19:51:00.037534: Pseudo dice [0.8451] +2024-11-21 19:51:00.037609: Epoch time: 17.95 s +2024-11-21 19:51:00.887458: +2024-11-21 19:51:00.887664: Epoch 1687 +2024-11-21 19:51:00.887778: Current learning rate: 0.00808 +2024-11-21 19:51:20.434467: train_loss -0.7821 +2024-11-21 19:51:20.434684: val_loss -0.7483 +2024-11-21 19:51:20.434768: Pseudo dice [0.8496] +2024-11-21 19:51:20.434846: Epoch time: 19.55 s +2024-11-21 19:51:21.279869: +2024-11-21 19:51:21.280179: Epoch 1688 +2024-11-21 19:51:21.280291: Current learning rate: 0.00808 +2024-11-21 19:51:40.725269: train_loss -0.7701 +2024-11-21 19:51:40.725486: val_loss -0.7491 +2024-11-21 19:51:40.725565: Pseudo dice [0.8294] +2024-11-21 19:51:40.725641: Epoch time: 19.45 s +2024-11-21 19:51:41.728814: +2024-11-21 19:51:41.729024: Epoch 1689 +2024-11-21 19:51:41.729144: Current learning rate: 0.00808 +2024-11-21 19:52:00.403625: train_loss -0.7686 +2024-11-21 19:52:00.403875: val_loss -0.729 +2024-11-21 19:52:00.403957: Pseudo dice [0.8195] +2024-11-21 19:52:00.404051: Epoch time: 18.68 s +2024-11-21 19:52:01.254958: +2024-11-21 19:52:01.255178: Epoch 1690 +2024-11-21 19:52:01.255294: Current learning rate: 0.00808 +2024-11-21 19:52:19.837792: train_loss -0.7718 +2024-11-21 19:52:19.838023: val_loss -0.7293 +2024-11-21 19:52:19.838102: Pseudo dice [0.8303] +2024-11-21 19:52:19.838181: Epoch time: 18.58 s +2024-11-21 19:52:20.687420: +2024-11-21 19:52:20.687639: Epoch 1691 +2024-11-21 19:52:20.687757: Current learning rate: 0.00808 +2024-11-21 19:52:39.299260: train_loss -0.7825 +2024-11-21 19:52:39.299492: val_loss -0.7526 +2024-11-21 19:52:39.299569: Pseudo dice [0.8225] +2024-11-21 19:52:39.299645: Epoch time: 18.61 s +2024-11-21 19:52:40.155923: +2024-11-21 19:52:40.156224: Epoch 1692 +2024-11-21 19:52:40.156353: Current learning rate: 0.00807 +2024-11-21 19:52:59.472230: train_loss -0.7666 +2024-11-21 19:52:59.472486: val_loss -0.7408 +2024-11-21 19:52:59.472564: Pseudo dice [0.83] +2024-11-21 19:52:59.472653: Epoch time: 19.32 s +2024-11-21 19:53:00.332324: +2024-11-21 19:53:00.332558: Epoch 1693 +2024-11-21 19:53:00.332670: Current learning rate: 0.00807 +2024-11-21 19:53:19.535855: train_loss -0.7591 +2024-11-21 19:53:19.536084: val_loss -0.7356 +2024-11-21 19:53:19.536167: Pseudo dice [0.8461] +2024-11-21 19:53:19.536243: Epoch time: 19.2 s +2024-11-21 19:53:20.391140: +2024-11-21 19:53:20.391355: Epoch 1694 +2024-11-21 19:53:20.391469: Current learning rate: 0.00807 +2024-11-21 19:53:38.993186: train_loss -0.7655 +2024-11-21 19:53:38.993400: val_loss -0.7322 +2024-11-21 19:53:38.993472: Pseudo dice [0.8361] +2024-11-21 19:53:38.993549: Epoch time: 18.6 s +2024-11-21 19:53:39.844517: +2024-11-21 19:53:39.844793: Epoch 1695 +2024-11-21 19:53:39.844912: Current learning rate: 0.00807 +2024-11-21 19:53:57.672256: train_loss -0.7587 +2024-11-21 19:53:57.672492: val_loss -0.7539 +2024-11-21 19:53:57.672571: Pseudo dice [0.8373] +2024-11-21 19:53:57.672654: Epoch time: 17.83 s +2024-11-21 19:53:58.533570: +2024-11-21 19:53:58.533765: Epoch 1696 +2024-11-21 19:53:58.533878: Current learning rate: 0.00807 +2024-11-21 19:54:17.286859: train_loss -0.7731 +2024-11-21 19:54:17.292234: val_loss -0.7234 +2024-11-21 19:54:17.292348: Pseudo dice [0.837] +2024-11-21 19:54:17.292429: Epoch time: 18.75 s +2024-11-21 19:54:18.262489: +2024-11-21 19:54:18.262693: Epoch 1697 +2024-11-21 19:54:18.262803: Current learning rate: 0.00807 +2024-11-21 19:54:36.979569: train_loss -0.7675 +2024-11-21 19:54:36.979784: val_loss -0.7465 +2024-11-21 19:54:36.979859: Pseudo dice [0.8399] +2024-11-21 19:54:36.979964: Epoch time: 18.72 s +2024-11-21 19:54:37.823679: +2024-11-21 19:54:37.823873: Epoch 1698 +2024-11-21 19:54:37.823988: Current learning rate: 0.00807 +2024-11-21 19:54:57.523854: train_loss -0.7755 +2024-11-21 19:54:57.524082: val_loss -0.7274 +2024-11-21 19:54:57.524158: Pseudo dice [0.8418] +2024-11-21 19:54:57.524233: Epoch time: 19.7 s +2024-11-21 19:54:58.432583: +2024-11-21 19:54:58.432805: Epoch 1699 +2024-11-21 19:54:58.432917: Current learning rate: 0.00807 +2024-11-21 19:55:17.724463: train_loss -0.7817 +2024-11-21 19:55:17.724708: val_loss -0.7639 +2024-11-21 19:55:17.724784: Pseudo dice [0.8509] +2024-11-21 19:55:17.724865: Epoch time: 19.29 s +2024-11-21 19:55:18.785692: +2024-11-21 19:55:18.785902: Epoch 1700 +2024-11-21 19:55:18.786022: Current learning rate: 0.00807 +2024-11-21 19:55:37.445507: train_loss -0.7669 +2024-11-21 19:55:37.445759: val_loss -0.7432 +2024-11-21 19:55:37.445836: Pseudo dice [0.7937] +2024-11-21 19:55:37.445919: Epoch time: 18.66 s +2024-11-21 19:55:38.297535: +2024-11-21 19:55:38.297915: Epoch 1701 +2024-11-21 19:55:38.298040: Current learning rate: 0.00806 +2024-11-21 19:55:56.170478: train_loss -0.7664 +2024-11-21 19:55:56.172905: val_loss -0.7439 +2024-11-21 19:55:56.173005: Pseudo dice [0.8258] +2024-11-21 19:55:56.173084: Epoch time: 17.87 s +2024-11-21 19:55:57.167506: +2024-11-21 19:55:57.167753: Epoch 1702 +2024-11-21 19:55:57.167874: Current learning rate: 0.00806 +2024-11-21 19:56:15.672224: train_loss -0.7801 +2024-11-21 19:56:15.672474: val_loss -0.7451 +2024-11-21 19:56:15.672564: Pseudo dice [0.8219] +2024-11-21 19:56:15.672649: Epoch time: 18.51 s +2024-11-21 19:56:16.519258: +2024-11-21 19:56:16.519467: Epoch 1703 +2024-11-21 19:56:16.519581: Current learning rate: 0.00806 +2024-11-21 19:56:34.461469: train_loss -0.7796 +2024-11-21 19:56:34.461684: val_loss -0.7544 +2024-11-21 19:56:34.461756: Pseudo dice [0.8507] +2024-11-21 19:56:34.461833: Epoch time: 17.94 s +2024-11-21 19:56:35.311491: +2024-11-21 19:56:35.311724: Epoch 1704 +2024-11-21 19:56:35.311841: Current learning rate: 0.00806 +2024-11-21 19:56:54.147882: train_loss -0.7743 +2024-11-21 19:56:54.148106: val_loss -0.7777 +2024-11-21 19:56:54.148187: Pseudo dice [0.849] +2024-11-21 19:56:54.148266: Epoch time: 18.84 s +2024-11-21 19:56:55.001140: +2024-11-21 19:56:55.001373: Epoch 1705 +2024-11-21 19:56:55.001490: Current learning rate: 0.00806 +2024-11-21 19:57:13.505476: train_loss -0.7784 +2024-11-21 19:57:13.505731: val_loss -0.7221 +2024-11-21 19:57:13.505807: Pseudo dice [0.8371] +2024-11-21 19:57:13.511103: Epoch time: 18.51 s +2024-11-21 19:57:14.534894: +2024-11-21 19:57:14.535167: Epoch 1706 +2024-11-21 19:57:14.535281: Current learning rate: 0.00806 +2024-11-21 19:57:32.986518: train_loss -0.7737 +2024-11-21 19:57:32.986787: val_loss -0.7416 +2024-11-21 19:57:32.986862: Pseudo dice [0.807] +2024-11-21 19:57:32.986940: Epoch time: 18.45 s +2024-11-21 19:57:33.848916: +2024-11-21 19:57:33.849132: Epoch 1707 +2024-11-21 19:57:33.849247: Current learning rate: 0.00806 +2024-11-21 19:57:52.531487: train_loss -0.7748 +2024-11-21 19:57:52.531706: val_loss -0.7272 +2024-11-21 19:57:52.531779: Pseudo dice [0.8382] +2024-11-21 19:57:52.531856: Epoch time: 18.68 s +2024-11-21 19:57:53.383768: +2024-11-21 19:57:53.383986: Epoch 1708 +2024-11-21 19:57:53.384118: Current learning rate: 0.00806 +2024-11-21 19:58:10.921291: train_loss -0.7736 +2024-11-21 19:58:10.921499: val_loss -0.7513 +2024-11-21 19:58:10.921573: Pseudo dice [0.8372] +2024-11-21 19:58:10.921647: Epoch time: 17.54 s +2024-11-21 19:58:11.872265: +2024-11-21 19:58:11.872465: Epoch 1709 +2024-11-21 19:58:11.872573: Current learning rate: 0.00806 +2024-11-21 19:58:30.005483: train_loss -0.7729 +2024-11-21 19:58:30.005735: val_loss -0.7497 +2024-11-21 19:58:30.005814: Pseudo dice [0.8459] +2024-11-21 19:58:30.005898: Epoch time: 18.13 s +2024-11-21 19:58:30.858166: +2024-11-21 19:58:30.858358: Epoch 1710 +2024-11-21 19:58:30.858469: Current learning rate: 0.00805 +2024-11-21 19:58:50.141969: train_loss -0.7838 +2024-11-21 19:58:50.142184: val_loss -0.7399 +2024-11-21 19:58:50.142255: Pseudo dice [0.817] +2024-11-21 19:58:50.142331: Epoch time: 19.28 s +2024-11-21 19:58:50.995508: +2024-11-21 19:58:50.995709: Epoch 1711 +2024-11-21 19:58:50.995820: Current learning rate: 0.00805 +2024-11-21 19:59:10.354856: train_loss -0.7807 +2024-11-21 19:59:10.355096: val_loss -0.7522 +2024-11-21 19:59:10.357359: Pseudo dice [0.8654] +2024-11-21 19:59:10.359392: Epoch time: 19.36 s +2024-11-21 19:59:11.655060: +2024-11-21 19:59:11.655251: Epoch 1712 +2024-11-21 19:59:11.655361: Current learning rate: 0.00805 +2024-11-21 19:59:30.585876: train_loss -0.7678 +2024-11-21 19:59:30.591326: val_loss -0.7406 +2024-11-21 19:59:30.591455: Pseudo dice [0.8388] +2024-11-21 19:59:30.591546: Epoch time: 18.93 s +2024-11-21 19:59:31.582945: +2024-11-21 19:59:31.583162: Epoch 1713 +2024-11-21 19:59:31.583272: Current learning rate: 0.00805 +2024-11-21 19:59:50.018264: train_loss -0.7692 +2024-11-21 19:59:50.018480: val_loss -0.6896 +2024-11-21 19:59:50.018555: Pseudo dice [0.815] +2024-11-21 19:59:50.018631: Epoch time: 18.44 s +2024-11-21 19:59:50.866804: +2024-11-21 19:59:50.867035: Epoch 1714 +2024-11-21 19:59:50.867152: Current learning rate: 0.00805 +2024-11-21 20:00:11.083293: train_loss -0.7646 +2024-11-21 20:00:11.083517: val_loss -0.7175 +2024-11-21 20:00:11.083591: Pseudo dice [0.8258] +2024-11-21 20:00:11.083667: Epoch time: 20.22 s +2024-11-21 20:00:11.936277: +2024-11-21 20:00:11.936573: Epoch 1715 +2024-11-21 20:00:11.936686: Current learning rate: 0.00805 +2024-11-21 20:00:30.604696: train_loss -0.7686 +2024-11-21 20:00:30.604920: val_loss -0.7251 +2024-11-21 20:00:30.605000: Pseudo dice [0.8425] +2024-11-21 20:00:30.605078: Epoch time: 18.67 s +2024-11-21 20:00:31.457450: +2024-11-21 20:00:31.457663: Epoch 1716 +2024-11-21 20:00:31.457779: Current learning rate: 0.00805 +2024-11-21 20:00:50.314120: train_loss -0.7702 +2024-11-21 20:00:50.314367: val_loss -0.7364 +2024-11-21 20:00:50.314445: Pseudo dice [0.835] +2024-11-21 20:00:50.314531: Epoch time: 18.86 s +2024-11-21 20:00:51.166212: +2024-11-21 20:00:51.166442: Epoch 1717 +2024-11-21 20:00:51.166556: Current learning rate: 0.00805 +2024-11-21 20:01:09.802662: train_loss -0.7646 +2024-11-21 20:01:09.802888: val_loss -0.6844 +2024-11-21 20:01:09.802963: Pseudo dice [0.8] +2024-11-21 20:01:09.803052: Epoch time: 18.64 s +2024-11-21 20:01:10.654621: +2024-11-21 20:01:10.654814: Epoch 1718 +2024-11-21 20:01:10.654924: Current learning rate: 0.00804 +2024-11-21 20:01:29.952554: train_loss -0.7713 +2024-11-21 20:01:29.952768: val_loss -0.7443 +2024-11-21 20:01:29.952845: Pseudo dice [0.8401] +2024-11-21 20:01:29.952922: Epoch time: 19.3 s +2024-11-21 20:01:30.818136: +2024-11-21 20:01:30.818329: Epoch 1719 +2024-11-21 20:01:30.818444: Current learning rate: 0.00804 +2024-11-21 20:01:49.587322: train_loss -0.7698 +2024-11-21 20:01:49.587554: val_loss -0.7293 +2024-11-21 20:01:49.587637: Pseudo dice [0.836] +2024-11-21 20:01:49.587718: Epoch time: 18.77 s +2024-11-21 20:01:50.448457: +2024-11-21 20:01:50.448652: Epoch 1720 +2024-11-21 20:01:50.448771: Current learning rate: 0.00804 +2024-11-21 20:02:08.533738: train_loss -0.7784 +2024-11-21 20:02:08.533983: val_loss -0.7297 +2024-11-21 20:02:08.534066: Pseudo dice [0.8538] +2024-11-21 20:02:08.534150: Epoch time: 18.09 s +2024-11-21 20:02:09.386407: +2024-11-21 20:02:09.386618: Epoch 1721 +2024-11-21 20:02:09.386744: Current learning rate: 0.00804 +2024-11-21 20:02:28.287388: train_loss -0.7736 +2024-11-21 20:02:28.287600: val_loss -0.7385 +2024-11-21 20:02:28.287676: Pseudo dice [0.8301] +2024-11-21 20:02:28.287752: Epoch time: 18.9 s +2024-11-21 20:02:29.131124: +2024-11-21 20:02:29.131321: Epoch 1722 +2024-11-21 20:02:29.131437: Current learning rate: 0.00804 +2024-11-21 20:02:48.353147: train_loss -0.7681 +2024-11-21 20:02:48.353360: val_loss -0.7679 +2024-11-21 20:02:48.353432: Pseudo dice [0.8563] +2024-11-21 20:02:48.353506: Epoch time: 19.22 s +2024-11-21 20:02:49.203089: +2024-11-21 20:02:49.203376: Epoch 1723 +2024-11-21 20:02:49.203495: Current learning rate: 0.00804 +2024-11-21 20:03:07.162868: train_loss -0.7741 +2024-11-21 20:03:07.163147: val_loss -0.7352 +2024-11-21 20:03:07.163226: Pseudo dice [0.8487] +2024-11-21 20:03:07.163309: Epoch time: 17.96 s +2024-11-21 20:03:08.034766: +2024-11-21 20:03:08.035012: Epoch 1724 +2024-11-21 20:03:08.035129: Current learning rate: 0.00804 +2024-11-21 20:03:27.459201: train_loss -0.777 +2024-11-21 20:03:27.459455: val_loss -0.7278 +2024-11-21 20:03:27.459532: Pseudo dice [0.8466] +2024-11-21 20:03:27.459616: Epoch time: 19.43 s +2024-11-21 20:03:28.348897: +2024-11-21 20:03:28.349105: Epoch 1725 +2024-11-21 20:03:28.349221: Current learning rate: 0.00804 +2024-11-21 20:03:45.287435: train_loss -0.7758 +2024-11-21 20:03:45.287658: val_loss -0.7375 +2024-11-21 20:03:45.287741: Pseudo dice [0.8264] +2024-11-21 20:03:45.287838: Epoch time: 16.94 s +2024-11-21 20:03:46.133042: +2024-11-21 20:03:46.133250: Epoch 1726 +2024-11-21 20:03:46.133362: Current learning rate: 0.00804 +2024-11-21 20:04:06.038853: train_loss -0.7839 +2024-11-21 20:04:06.039075: val_loss -0.7349 +2024-11-21 20:04:06.039166: Pseudo dice [0.8445] +2024-11-21 20:04:06.039303: Epoch time: 19.91 s +2024-11-21 20:04:06.888409: +2024-11-21 20:04:06.888635: Epoch 1727 +2024-11-21 20:04:06.888750: Current learning rate: 0.00803 +2024-11-21 20:04:25.154336: train_loss -0.7776 +2024-11-21 20:04:25.154584: val_loss -0.7261 +2024-11-21 20:04:25.154661: Pseudo dice [0.8449] +2024-11-21 20:04:25.154747: Epoch time: 18.27 s +2024-11-21 20:04:26.021043: +2024-11-21 20:04:26.021275: Epoch 1728 +2024-11-21 20:04:26.021391: Current learning rate: 0.00803 +2024-11-21 20:04:45.277649: train_loss -0.7677 +2024-11-21 20:04:45.277872: val_loss -0.7132 +2024-11-21 20:04:45.277951: Pseudo dice [0.8657] +2024-11-21 20:04:45.278043: Epoch time: 19.26 s +2024-11-21 20:04:46.129106: +2024-11-21 20:04:46.129324: Epoch 1729 +2024-11-21 20:04:46.129447: Current learning rate: 0.00803 +2024-11-21 20:05:04.439704: train_loss -0.7705 +2024-11-21 20:05:04.439935: val_loss -0.7232 +2024-11-21 20:05:04.440026: Pseudo dice [0.8214] +2024-11-21 20:05:04.440105: Epoch time: 18.31 s +2024-11-21 20:05:05.290026: +2024-11-21 20:05:05.290290: Epoch 1730 +2024-11-21 20:05:05.290407: Current learning rate: 0.00803 +2024-11-21 20:05:23.527110: train_loss -0.7595 +2024-11-21 20:05:23.527328: val_loss -0.7228 +2024-11-21 20:05:23.527401: Pseudo dice [0.8154] +2024-11-21 20:05:23.532620: Epoch time: 18.24 s +2024-11-21 20:05:24.409606: +2024-11-21 20:05:24.409891: Epoch 1731 +2024-11-21 20:05:24.410015: Current learning rate: 0.00803 +2024-11-21 20:05:43.788276: train_loss -0.7686 +2024-11-21 20:05:43.788517: val_loss -0.7491 +2024-11-21 20:05:43.788596: Pseudo dice [0.8384] +2024-11-21 20:05:43.788682: Epoch time: 19.38 s +2024-11-21 20:05:44.657419: +2024-11-21 20:05:44.657631: Epoch 1732 +2024-11-21 20:05:44.657744: Current learning rate: 0.00803 +2024-11-21 20:06:04.156388: train_loss -0.7649 +2024-11-21 20:06:04.158811: val_loss -0.7345 +2024-11-21 20:06:04.158946: Pseudo dice [0.8357] +2024-11-21 20:06:04.159030: Epoch time: 19.5 s +2024-11-21 20:06:05.045263: +2024-11-21 20:06:05.045480: Epoch 1733 +2024-11-21 20:06:05.045595: Current learning rate: 0.00803 +2024-11-21 20:06:23.036953: train_loss -0.7594 +2024-11-21 20:06:23.037177: val_loss -0.7338 +2024-11-21 20:06:23.037256: Pseudo dice [0.8451] +2024-11-21 20:06:23.037331: Epoch time: 17.99 s +2024-11-21 20:06:24.286846: +2024-11-21 20:06:24.287055: Epoch 1734 +2024-11-21 20:06:24.287170: Current learning rate: 0.00803 +2024-11-21 20:06:42.239965: train_loss -0.7656 +2024-11-21 20:06:42.240279: val_loss -0.7452 +2024-11-21 20:06:42.240358: Pseudo dice [0.8486] +2024-11-21 20:06:42.240444: Epoch time: 17.95 s +2024-11-21 20:06:43.092849: +2024-11-21 20:06:43.093089: Epoch 1735 +2024-11-21 20:06:43.093201: Current learning rate: 0.00803 +2024-11-21 20:07:01.567886: train_loss -0.7615 +2024-11-21 20:07:01.568118: val_loss -0.7375 +2024-11-21 20:07:01.568197: Pseudo dice [0.8503] +2024-11-21 20:07:01.568278: Epoch time: 18.48 s +2024-11-21 20:07:02.433286: +2024-11-21 20:07:02.433552: Epoch 1736 +2024-11-21 20:07:02.433666: Current learning rate: 0.00802 +2024-11-21 20:07:21.264728: train_loss -0.7753 +2024-11-21 20:07:21.264968: val_loss -0.7699 +2024-11-21 20:07:21.265114: Pseudo dice [0.8574] +2024-11-21 20:07:21.265195: Epoch time: 18.83 s +2024-11-21 20:07:22.125863: +2024-11-21 20:07:22.126104: Epoch 1737 +2024-11-21 20:07:22.126225: Current learning rate: 0.00802 +2024-11-21 20:07:40.479585: train_loss -0.7787 +2024-11-21 20:07:40.479836: val_loss -0.7603 +2024-11-21 20:07:40.479914: Pseudo dice [0.8283] +2024-11-21 20:07:40.480008: Epoch time: 18.35 s +2024-11-21 20:07:41.359983: +2024-11-21 20:07:41.360190: Epoch 1738 +2024-11-21 20:07:41.360298: Current learning rate: 0.00802 +2024-11-21 20:08:00.006154: train_loss -0.7651 +2024-11-21 20:08:00.006397: val_loss -0.7269 +2024-11-21 20:08:00.006517: Pseudo dice [0.8281] +2024-11-21 20:08:00.006600: Epoch time: 18.65 s +2024-11-21 20:08:00.859444: +2024-11-21 20:08:00.859685: Epoch 1739 +2024-11-21 20:08:00.859801: Current learning rate: 0.00802 +2024-11-21 20:08:20.068397: train_loss -0.7676 +2024-11-21 20:08:20.068655: val_loss -0.7428 +2024-11-21 20:08:20.068735: Pseudo dice [0.8437] +2024-11-21 20:08:20.068812: Epoch time: 19.21 s +2024-11-21 20:08:21.033790: +2024-11-21 20:08:21.033997: Epoch 1740 +2024-11-21 20:08:21.034107: Current learning rate: 0.00802 +2024-11-21 20:08:39.795767: train_loss -0.7799 +2024-11-21 20:08:39.796069: val_loss -0.7754 +2024-11-21 20:08:39.796149: Pseudo dice [0.8536] +2024-11-21 20:08:39.796229: Epoch time: 18.76 s +2024-11-21 20:08:40.646767: +2024-11-21 20:08:40.646977: Epoch 1741 +2024-11-21 20:08:40.647103: Current learning rate: 0.00802 +2024-11-21 20:08:58.791975: train_loss -0.7804 +2024-11-21 20:08:58.792194: val_loss -0.7237 +2024-11-21 20:08:58.792276: Pseudo dice [0.8206] +2024-11-21 20:08:58.792358: Epoch time: 18.15 s +2024-11-21 20:08:59.642094: +2024-11-21 20:08:59.642342: Epoch 1742 +2024-11-21 20:08:59.642497: Current learning rate: 0.00802 +2024-11-21 20:09:19.680101: train_loss -0.779 +2024-11-21 20:09:19.680319: val_loss -0.748 +2024-11-21 20:09:19.680393: Pseudo dice [0.8319] +2024-11-21 20:09:19.680496: Epoch time: 20.04 s +2024-11-21 20:09:20.537389: +2024-11-21 20:09:20.537601: Epoch 1743 +2024-11-21 20:09:20.537714: Current learning rate: 0.00802 +2024-11-21 20:09:39.455551: train_loss -0.7692 +2024-11-21 20:09:39.455833: val_loss -0.7463 +2024-11-21 20:09:39.455913: Pseudo dice [0.8465] +2024-11-21 20:09:39.455989: Epoch time: 18.92 s +2024-11-21 20:09:40.329980: +2024-11-21 20:09:40.330191: Epoch 1744 +2024-11-21 20:09:40.330307: Current learning rate: 0.00801 +2024-11-21 20:09:58.376189: train_loss -0.7845 +2024-11-21 20:09:58.376418: val_loss -0.7296 +2024-11-21 20:09:58.376491: Pseudo dice [0.8283] +2024-11-21 20:09:58.376567: Epoch time: 18.05 s +2024-11-21 20:09:59.224321: +2024-11-21 20:09:59.224554: Epoch 1745 +2024-11-21 20:09:59.224678: Current learning rate: 0.00801 +2024-11-21 20:10:17.705424: train_loss -0.7694 +2024-11-21 20:10:17.705660: val_loss -0.7219 +2024-11-21 20:10:17.705735: Pseudo dice [0.835] +2024-11-21 20:10:17.705812: Epoch time: 18.48 s +2024-11-21 20:10:18.553611: +2024-11-21 20:10:18.553825: Epoch 1746 +2024-11-21 20:10:18.553941: Current learning rate: 0.00801 +2024-11-21 20:10:37.565204: train_loss -0.7806 +2024-11-21 20:10:37.565409: val_loss -0.7323 +2024-11-21 20:10:37.565485: Pseudo dice [0.8393] +2024-11-21 20:10:37.565561: Epoch time: 19.01 s +2024-11-21 20:10:38.415954: +2024-11-21 20:10:38.416217: Epoch 1747 +2024-11-21 20:10:38.416329: Current learning rate: 0.00801 +2024-11-21 20:10:57.136484: train_loss -0.7626 +2024-11-21 20:10:57.136701: val_loss -0.7492 +2024-11-21 20:10:57.136774: Pseudo dice [0.8273] +2024-11-21 20:10:57.136847: Epoch time: 18.72 s +2024-11-21 20:10:58.029835: +2024-11-21 20:10:58.030056: Epoch 1748 +2024-11-21 20:10:58.030166: Current learning rate: 0.00801 +2024-11-21 20:11:16.455225: train_loss -0.7735 +2024-11-21 20:11:16.455471: val_loss -0.7449 +2024-11-21 20:11:16.455546: Pseudo dice [0.8262] +2024-11-21 20:11:16.455626: Epoch time: 18.43 s +2024-11-21 20:11:17.306603: +2024-11-21 20:11:17.306806: Epoch 1749 +2024-11-21 20:11:17.306924: Current learning rate: 0.00801 +2024-11-21 20:11:36.337203: train_loss -0.7788 +2024-11-21 20:11:36.337413: val_loss -0.738 +2024-11-21 20:11:36.342677: Pseudo dice [0.8294] +2024-11-21 20:11:36.342871: Epoch time: 19.03 s +2024-11-21 20:11:37.586805: +2024-11-21 20:11:37.587024: Epoch 1750 +2024-11-21 20:11:37.587134: Current learning rate: 0.00801 +2024-11-21 20:11:55.360528: train_loss -0.7704 +2024-11-21 20:11:55.360748: val_loss -0.7278 +2024-11-21 20:11:55.360823: Pseudo dice [0.826] +2024-11-21 20:11:55.360898: Epoch time: 17.77 s +2024-11-21 20:11:56.230633: +2024-11-21 20:11:56.230852: Epoch 1751 +2024-11-21 20:11:56.230969: Current learning rate: 0.00801 +2024-11-21 20:12:14.400883: train_loss -0.7768 +2024-11-21 20:12:14.401107: val_loss -0.729 +2024-11-21 20:12:14.401183: Pseudo dice [0.8056] +2024-11-21 20:12:14.401262: Epoch time: 18.17 s +2024-11-21 20:12:15.250732: +2024-11-21 20:12:15.250920: Epoch 1752 +2024-11-21 20:12:15.251033: Current learning rate: 0.00801 +2024-11-21 20:12:33.802489: train_loss -0.7839 +2024-11-21 20:12:33.802708: val_loss -0.7262 +2024-11-21 20:12:33.802780: Pseudo dice [0.8537] +2024-11-21 20:12:33.802861: Epoch time: 18.55 s +2024-11-21 20:12:34.678395: +2024-11-21 20:12:34.678743: Epoch 1753 +2024-11-21 20:12:34.678857: Current learning rate: 0.008 +2024-11-21 20:12:53.719040: train_loss -0.7756 +2024-11-21 20:12:53.719295: val_loss -0.7537 +2024-11-21 20:12:53.719371: Pseudo dice [0.8343] +2024-11-21 20:12:53.719450: Epoch time: 19.04 s +2024-11-21 20:12:54.577072: +2024-11-21 20:12:54.577268: Epoch 1754 +2024-11-21 20:12:54.577381: Current learning rate: 0.008 +2024-11-21 20:13:13.047498: train_loss -0.7729 +2024-11-21 20:13:13.047713: val_loss -0.712 +2024-11-21 20:13:13.047788: Pseudo dice [0.8414] +2024-11-21 20:13:13.047862: Epoch time: 18.47 s +2024-11-21 20:13:13.902129: +2024-11-21 20:13:13.902383: Epoch 1755 +2024-11-21 20:13:13.902500: Current learning rate: 0.008 +2024-11-21 20:13:31.997797: train_loss -0.7717 +2024-11-21 20:13:31.998118: val_loss -0.7637 +2024-11-21 20:13:31.998198: Pseudo dice [0.8503] +2024-11-21 20:13:31.998275: Epoch time: 18.1 s +2024-11-21 20:13:33.221754: +2024-11-21 20:13:33.222053: Epoch 1756 +2024-11-21 20:13:33.222176: Current learning rate: 0.008 +2024-11-21 20:13:52.182290: train_loss -0.7844 +2024-11-21 20:13:52.182564: val_loss -0.7418 +2024-11-21 20:13:52.182646: Pseudo dice [0.8509] +2024-11-21 20:13:52.182728: Epoch time: 18.96 s +2024-11-21 20:13:53.035020: +2024-11-21 20:13:53.035274: Epoch 1757 +2024-11-21 20:13:53.035392: Current learning rate: 0.008 +2024-11-21 20:14:11.807367: train_loss -0.7784 +2024-11-21 20:14:11.807576: val_loss -0.7404 +2024-11-21 20:14:11.807651: Pseudo dice [0.8495] +2024-11-21 20:14:11.807726: Epoch time: 18.77 s +2024-11-21 20:14:12.655912: +2024-11-21 20:14:12.656148: Epoch 1758 +2024-11-21 20:14:12.656258: Current learning rate: 0.008 +2024-11-21 20:14:32.470023: train_loss -0.7736 +2024-11-21 20:14:32.470260: val_loss -0.7356 +2024-11-21 20:14:32.470334: Pseudo dice [0.8406] +2024-11-21 20:14:32.470451: Epoch time: 19.81 s +2024-11-21 20:14:33.319269: +2024-11-21 20:14:33.319490: Epoch 1759 +2024-11-21 20:14:33.319601: Current learning rate: 0.008 +2024-11-21 20:14:51.084852: train_loss -0.7791 +2024-11-21 20:14:51.086612: val_loss -0.7476 +2024-11-21 20:14:51.086700: Pseudo dice [0.8541] +2024-11-21 20:14:51.086787: Epoch time: 17.77 s +2024-11-21 20:14:52.003705: +2024-11-21 20:14:52.004007: Epoch 1760 +2024-11-21 20:14:52.004124: Current learning rate: 0.008 +2024-11-21 20:15:09.784841: train_loss -0.7843 +2024-11-21 20:15:09.785077: val_loss -0.7293 +2024-11-21 20:15:09.785153: Pseudo dice [0.8409] +2024-11-21 20:15:09.785230: Epoch time: 17.78 s +2024-11-21 20:15:10.638744: +2024-11-21 20:15:10.638942: Epoch 1761 +2024-11-21 20:15:10.639057: Current learning rate: 0.008 +2024-11-21 20:15:28.853971: train_loss -0.7796 +2024-11-21 20:15:28.854197: val_loss -0.7219 +2024-11-21 20:15:28.854275: Pseudo dice [0.8298] +2024-11-21 20:15:28.856254: Epoch time: 18.22 s +2024-11-21 20:15:29.717118: +2024-11-21 20:15:29.717324: Epoch 1762 +2024-11-21 20:15:29.717442: Current learning rate: 0.00799 +2024-11-21 20:15:48.097413: train_loss -0.7773 +2024-11-21 20:15:48.101111: val_loss -0.7182 +2024-11-21 20:15:48.101206: Pseudo dice [0.8298] +2024-11-21 20:15:48.101284: Epoch time: 18.38 s +2024-11-21 20:15:49.135998: +2024-11-21 20:15:49.136307: Epoch 1763 +2024-11-21 20:15:49.136420: Current learning rate: 0.00799 +2024-11-21 20:16:07.955649: train_loss -0.7799 +2024-11-21 20:16:07.955890: val_loss -0.7422 +2024-11-21 20:16:07.955964: Pseudo dice [0.8462] +2024-11-21 20:16:07.956054: Epoch time: 18.82 s +2024-11-21 20:16:08.883866: +2024-11-21 20:16:08.884111: Epoch 1764 +2024-11-21 20:16:08.884223: Current learning rate: 0.00799 +2024-11-21 20:16:27.996570: train_loss -0.7734 +2024-11-21 20:16:27.996812: val_loss -0.7429 +2024-11-21 20:16:27.996890: Pseudo dice [0.8618] +2024-11-21 20:16:27.997035: Epoch time: 19.11 s +2024-11-21 20:16:28.848812: +2024-11-21 20:16:28.849042: Epoch 1765 +2024-11-21 20:16:28.849157: Current learning rate: 0.00799 +2024-11-21 20:16:47.435987: train_loss -0.7733 +2024-11-21 20:16:47.436213: val_loss -0.7223 +2024-11-21 20:16:47.436288: Pseudo dice [0.8352] +2024-11-21 20:16:47.436363: Epoch time: 18.59 s +2024-11-21 20:16:48.286897: +2024-11-21 20:16:48.287096: Epoch 1766 +2024-11-21 20:16:48.287208: Current learning rate: 0.00799 +2024-11-21 20:17:06.675956: train_loss -0.7734 +2024-11-21 20:17:06.676180: val_loss -0.7138 +2024-11-21 20:17:06.676259: Pseudo dice [0.8478] +2024-11-21 20:17:06.676338: Epoch time: 18.39 s +2024-11-21 20:17:07.533458: +2024-11-21 20:17:07.533690: Epoch 1767 +2024-11-21 20:17:07.533805: Current learning rate: 0.00799 +2024-11-21 20:17:27.200375: train_loss -0.7677 +2024-11-21 20:17:27.200691: val_loss -0.7003 +2024-11-21 20:17:27.200770: Pseudo dice [0.8336] +2024-11-21 20:17:27.200850: Epoch time: 19.67 s +2024-11-21 20:17:28.105839: +2024-11-21 20:17:28.106053: Epoch 1768 +2024-11-21 20:17:28.106164: Current learning rate: 0.00799 +2024-11-21 20:17:46.224404: train_loss -0.7741 +2024-11-21 20:17:46.224619: val_loss -0.723 +2024-11-21 20:17:46.224693: Pseudo dice [0.8226] +2024-11-21 20:17:46.224773: Epoch time: 18.12 s +2024-11-21 20:17:47.088399: +2024-11-21 20:17:47.088610: Epoch 1769 +2024-11-21 20:17:47.088724: Current learning rate: 0.00799 +2024-11-21 20:18:06.391101: train_loss -0.7718 +2024-11-21 20:18:06.391319: val_loss -0.7253 +2024-11-21 20:18:06.391392: Pseudo dice [0.8258] +2024-11-21 20:18:06.391469: Epoch time: 19.3 s +2024-11-21 20:18:07.350280: +2024-11-21 20:18:07.350519: Epoch 1770 +2024-11-21 20:18:07.350637: Current learning rate: 0.00798 +2024-11-21 20:18:24.627470: train_loss -0.7656 +2024-11-21 20:18:24.627712: val_loss -0.7046 +2024-11-21 20:18:24.627813: Pseudo dice [0.8167] +2024-11-21 20:18:24.627893: Epoch time: 17.28 s +2024-11-21 20:18:25.473609: +2024-11-21 20:18:25.473804: Epoch 1771 +2024-11-21 20:18:25.473917: Current learning rate: 0.00798 +2024-11-21 20:18:44.785748: train_loss -0.7596 +2024-11-21 20:18:44.785958: val_loss -0.7221 +2024-11-21 20:18:44.786046: Pseudo dice [0.8326] +2024-11-21 20:18:44.786123: Epoch time: 19.31 s +2024-11-21 20:18:45.850106: +2024-11-21 20:18:45.850343: Epoch 1772 +2024-11-21 20:18:45.850462: Current learning rate: 0.00798 +2024-11-21 20:19:03.554995: train_loss -0.7744 +2024-11-21 20:19:03.555203: val_loss -0.729 +2024-11-21 20:19:03.555281: Pseudo dice [0.8512] +2024-11-21 20:19:03.555356: Epoch time: 17.71 s +2024-11-21 20:19:04.394513: +2024-11-21 20:19:04.394725: Epoch 1773 +2024-11-21 20:19:04.394837: Current learning rate: 0.00798 +2024-11-21 20:19:23.241337: train_loss -0.7805 +2024-11-21 20:19:23.241566: val_loss -0.6976 +2024-11-21 20:19:23.241642: Pseudo dice [0.7983] +2024-11-21 20:19:23.241724: Epoch time: 18.85 s +2024-11-21 20:19:24.172719: +2024-11-21 20:19:24.172941: Epoch 1774 +2024-11-21 20:19:24.173063: Current learning rate: 0.00798 +2024-11-21 20:19:44.654810: train_loss -0.7636 +2024-11-21 20:19:44.655073: val_loss -0.7178 +2024-11-21 20:19:44.655150: Pseudo dice [0.8193] +2024-11-21 20:19:44.655234: Epoch time: 20.48 s +2024-11-21 20:19:45.513102: +2024-11-21 20:19:45.513293: Epoch 1775 +2024-11-21 20:19:45.513404: Current learning rate: 0.00798 +2024-11-21 20:20:05.141115: train_loss -0.7512 +2024-11-21 20:20:05.148673: val_loss -0.751 +2024-11-21 20:20:05.148845: Pseudo dice [0.8505] +2024-11-21 20:20:05.148935: Epoch time: 19.63 s +2024-11-21 20:20:06.014227: +2024-11-21 20:20:06.014425: Epoch 1776 +2024-11-21 20:20:06.014537: Current learning rate: 0.00798 +2024-11-21 20:20:25.935226: train_loss -0.7731 +2024-11-21 20:20:25.940606: val_loss -0.7293 +2024-11-21 20:20:25.940716: Pseudo dice [0.8531] +2024-11-21 20:20:25.940795: Epoch time: 19.92 s +2024-11-21 20:20:26.975461: +2024-11-21 20:20:26.975730: Epoch 1777 +2024-11-21 20:20:26.975846: Current learning rate: 0.00798 +2024-11-21 20:20:45.724412: train_loss -0.7524 +2024-11-21 20:20:45.724694: val_loss -0.7231 +2024-11-21 20:20:45.724770: Pseudo dice [0.8422] +2024-11-21 20:20:45.724855: Epoch time: 18.75 s +2024-11-21 20:20:46.960440: +2024-11-21 20:20:46.960658: Epoch 1778 +2024-11-21 20:20:46.960771: Current learning rate: 0.00798 +2024-11-21 20:21:04.850219: train_loss -0.7758 +2024-11-21 20:21:04.850444: val_loss -0.7541 +2024-11-21 20:21:04.850518: Pseudo dice [0.8464] +2024-11-21 20:21:04.850666: Epoch time: 17.89 s +2024-11-21 20:21:05.686669: +2024-11-21 20:21:05.686895: Epoch 1779 +2024-11-21 20:21:05.687011: Current learning rate: 0.00797 +2024-11-21 20:21:24.564114: train_loss -0.7714 +2024-11-21 20:21:24.564310: val_loss -0.7395 +2024-11-21 20:21:24.564385: Pseudo dice [0.8374] +2024-11-21 20:21:24.564459: Epoch time: 18.88 s +2024-11-21 20:21:25.411940: +2024-11-21 20:21:25.412154: Epoch 1780 +2024-11-21 20:21:25.412271: Current learning rate: 0.00797 +2024-11-21 20:21:43.109091: train_loss -0.769 +2024-11-21 20:21:43.109353: val_loss -0.7491 +2024-11-21 20:21:43.109434: Pseudo dice [0.8574] +2024-11-21 20:21:43.109530: Epoch time: 17.7 s +2024-11-21 20:21:43.961943: +2024-11-21 20:21:43.962154: Epoch 1781 +2024-11-21 20:21:43.962264: Current learning rate: 0.00797 +2024-11-21 20:22:02.368897: train_loss -0.7712 +2024-11-21 20:22:02.369122: val_loss -0.7118 +2024-11-21 20:22:02.369197: Pseudo dice [0.8118] +2024-11-21 20:22:02.369275: Epoch time: 18.41 s +2024-11-21 20:22:03.225188: +2024-11-21 20:22:03.225424: Epoch 1782 +2024-11-21 20:22:03.225543: Current learning rate: 0.00797 +2024-11-21 20:22:22.432894: train_loss -0.7711 +2024-11-21 20:22:22.433110: val_loss -0.7331 +2024-11-21 20:22:22.433189: Pseudo dice [0.848] +2024-11-21 20:22:22.433265: Epoch time: 19.21 s +2024-11-21 20:22:23.287621: +2024-11-21 20:22:23.287838: Epoch 1783 +2024-11-21 20:22:23.287947: Current learning rate: 0.00797 +2024-11-21 20:22:42.243623: train_loss -0.7676 +2024-11-21 20:22:42.243850: val_loss -0.7514 +2024-11-21 20:22:42.243951: Pseudo dice [0.8367] +2024-11-21 20:22:42.244040: Epoch time: 18.96 s +2024-11-21 20:22:43.102698: +2024-11-21 20:22:43.103056: Epoch 1784 +2024-11-21 20:22:43.103171: Current learning rate: 0.00797 +2024-11-21 20:23:01.770819: train_loss -0.7829 +2024-11-21 20:23:01.772575: val_loss -0.7269 +2024-11-21 20:23:01.772690: Pseudo dice [0.8398] +2024-11-21 20:23:01.772774: Epoch time: 18.67 s +2024-11-21 20:23:02.676443: +2024-11-21 20:23:02.676652: Epoch 1785 +2024-11-21 20:23:02.676776: Current learning rate: 0.00797 +2024-11-21 20:23:21.074383: train_loss -0.7742 +2024-11-21 20:23:21.074630: val_loss -0.7373 +2024-11-21 20:23:21.074711: Pseudo dice [0.83] +2024-11-21 20:23:21.074795: Epoch time: 18.4 s +2024-11-21 20:23:21.931058: +2024-11-21 20:23:21.931267: Epoch 1786 +2024-11-21 20:23:21.931380: Current learning rate: 0.00797 +2024-11-21 20:23:39.401276: train_loss -0.7829 +2024-11-21 20:23:39.401490: val_loss -0.7412 +2024-11-21 20:23:39.401567: Pseudo dice [0.8265] +2024-11-21 20:23:39.401641: Epoch time: 17.47 s +2024-11-21 20:23:40.250938: +2024-11-21 20:23:40.251201: Epoch 1787 +2024-11-21 20:23:40.251315: Current learning rate: 0.00797 +2024-11-21 20:23:59.057811: train_loss -0.7899 +2024-11-21 20:23:59.058031: val_loss -0.7439 +2024-11-21 20:23:59.058106: Pseudo dice [0.8278] +2024-11-21 20:23:59.058182: Epoch time: 18.81 s +2024-11-21 20:23:59.907060: +2024-11-21 20:23:59.907291: Epoch 1788 +2024-11-21 20:23:59.907409: Current learning rate: 0.00796 +2024-11-21 20:24:18.451456: train_loss -0.7789 +2024-11-21 20:24:18.451751: val_loss -0.7499 +2024-11-21 20:24:18.451833: Pseudo dice [0.8227] +2024-11-21 20:24:18.451952: Epoch time: 18.55 s +2024-11-21 20:24:19.413339: +2024-11-21 20:24:19.413594: Epoch 1789 +2024-11-21 20:24:19.413707: Current learning rate: 0.00796 +2024-11-21 20:24:37.652644: train_loss -0.7788 +2024-11-21 20:24:37.652886: val_loss -0.7474 +2024-11-21 20:24:37.653005: Pseudo dice [0.8399] +2024-11-21 20:24:37.653086: Epoch time: 18.24 s +2024-11-21 20:24:38.494348: +2024-11-21 20:24:38.494568: Epoch 1790 +2024-11-21 20:24:38.494682: Current learning rate: 0.00796 +2024-11-21 20:24:57.827996: train_loss -0.7753 +2024-11-21 20:24:57.828215: val_loss -0.7212 +2024-11-21 20:24:57.828294: Pseudo dice [0.8273] +2024-11-21 20:24:57.828372: Epoch time: 19.33 s +2024-11-21 20:24:58.723233: +2024-11-21 20:24:58.723457: Epoch 1791 +2024-11-21 20:24:58.723569: Current learning rate: 0.00796 +2024-11-21 20:25:17.355698: train_loss -0.7777 +2024-11-21 20:25:17.355939: val_loss -0.7264 +2024-11-21 20:25:17.356024: Pseudo dice [0.8256] +2024-11-21 20:25:17.356109: Epoch time: 18.63 s +2024-11-21 20:25:18.225214: +2024-11-21 20:25:18.225439: Epoch 1792 +2024-11-21 20:25:18.225554: Current learning rate: 0.00796 +2024-11-21 20:25:35.919247: train_loss -0.7622 +2024-11-21 20:25:35.919462: val_loss -0.7321 +2024-11-21 20:25:35.919537: Pseudo dice [0.8432] +2024-11-21 20:25:35.919614: Epoch time: 17.69 s +2024-11-21 20:25:36.776887: +2024-11-21 20:25:36.777119: Epoch 1793 +2024-11-21 20:25:36.777238: Current learning rate: 0.00796 +2024-11-21 20:25:55.080616: train_loss -0.7644 +2024-11-21 20:25:55.080914: val_loss -0.695 +2024-11-21 20:25:55.081001: Pseudo dice [0.8186] +2024-11-21 20:25:55.081079: Epoch time: 18.3 s +2024-11-21 20:25:55.974978: +2024-11-21 20:25:55.975287: Epoch 1794 +2024-11-21 20:25:55.975403: Current learning rate: 0.00796 +2024-11-21 20:26:14.821029: train_loss -0.775 +2024-11-21 20:26:14.821258: val_loss -0.735 +2024-11-21 20:26:14.821337: Pseudo dice [0.8448] +2024-11-21 20:26:14.821416: Epoch time: 18.85 s +2024-11-21 20:26:15.673638: +2024-11-21 20:26:15.673844: Epoch 1795 +2024-11-21 20:26:15.673958: Current learning rate: 0.00796 +2024-11-21 20:26:34.259341: train_loss -0.7818 +2024-11-21 20:26:34.259581: val_loss -0.7187 +2024-11-21 20:26:34.259654: Pseudo dice [0.8133] +2024-11-21 20:26:34.259733: Epoch time: 18.59 s +2024-11-21 20:26:35.114577: +2024-11-21 20:26:35.114836: Epoch 1796 +2024-11-21 20:26:35.114957: Current learning rate: 0.00795 +2024-11-21 20:26:52.668848: train_loss -0.7861 +2024-11-21 20:26:52.669071: val_loss -0.7466 +2024-11-21 20:26:52.669160: Pseudo dice [0.8358] +2024-11-21 20:26:52.669239: Epoch time: 17.56 s +2024-11-21 20:26:53.571981: +2024-11-21 20:26:53.572224: Epoch 1797 +2024-11-21 20:26:53.572340: Current learning rate: 0.00795 +2024-11-21 20:27:12.958905: train_loss -0.7666 +2024-11-21 20:27:12.959137: val_loss -0.7597 +2024-11-21 20:27:12.959211: Pseudo dice [0.8605] +2024-11-21 20:27:12.959289: Epoch time: 19.39 s +2024-11-21 20:27:13.808660: +2024-11-21 20:27:13.808851: Epoch 1798 +2024-11-21 20:27:13.809021: Current learning rate: 0.00795 +2024-11-21 20:27:32.955499: train_loss -0.7725 +2024-11-21 20:27:32.955726: val_loss -0.7371 +2024-11-21 20:27:32.955806: Pseudo dice [0.8339] +2024-11-21 20:27:32.955887: Epoch time: 19.15 s +2024-11-21 20:27:33.811202: +2024-11-21 20:27:33.811415: Epoch 1799 +2024-11-21 20:27:33.811542: Current learning rate: 0.00795 +2024-11-21 20:27:52.540438: train_loss -0.7549 +2024-11-21 20:27:52.540673: val_loss -0.7363 +2024-11-21 20:27:52.540746: Pseudo dice [0.8005] +2024-11-21 20:27:52.540826: Epoch time: 18.73 s +2024-11-21 20:27:54.001733: +2024-11-21 20:27:54.001951: Epoch 1800 +2024-11-21 20:27:54.002069: Current learning rate: 0.00795 +2024-11-21 20:28:12.519649: train_loss -0.7631 +2024-11-21 20:28:12.519902: val_loss -0.7697 +2024-11-21 20:28:12.519982: Pseudo dice [0.8405] +2024-11-21 20:28:12.520065: Epoch time: 18.52 s +2024-11-21 20:28:13.370300: +2024-11-21 20:28:13.370542: Epoch 1801 +2024-11-21 20:28:13.370657: Current learning rate: 0.00795 +2024-11-21 20:28:31.850935: train_loss -0.7679 +2024-11-21 20:28:31.851166: val_loss -0.7324 +2024-11-21 20:28:31.853436: Pseudo dice [0.8199] +2024-11-21 20:28:31.853589: Epoch time: 18.48 s +2024-11-21 20:28:32.782194: +2024-11-21 20:28:32.782421: Epoch 1802 +2024-11-21 20:28:32.782534: Current learning rate: 0.00795 +2024-11-21 20:28:50.973781: train_loss -0.7802 +2024-11-21 20:28:50.974041: val_loss -0.7247 +2024-11-21 20:28:50.974117: Pseudo dice [0.8304] +2024-11-21 20:28:50.974200: Epoch time: 18.19 s +2024-11-21 20:28:52.084175: +2024-11-21 20:28:52.084464: Epoch 1803 +2024-11-21 20:28:52.084582: Current learning rate: 0.00795 +2024-11-21 20:29:10.712490: train_loss -0.7595 +2024-11-21 20:29:10.712704: val_loss -0.6934 +2024-11-21 20:29:10.712780: Pseudo dice [0.7947] +2024-11-21 20:29:10.712855: Epoch time: 18.63 s +2024-11-21 20:29:11.556907: +2024-11-21 20:29:11.557168: Epoch 1804 +2024-11-21 20:29:11.557286: Current learning rate: 0.00795 +2024-11-21 20:29:30.008389: train_loss -0.7499 +2024-11-21 20:29:30.008613: val_loss -0.7272 +2024-11-21 20:29:30.008692: Pseudo dice [0.8141] +2024-11-21 20:29:30.009022: Epoch time: 18.45 s +2024-11-21 20:29:30.908262: +2024-11-21 20:29:30.908495: Epoch 1805 +2024-11-21 20:29:30.908610: Current learning rate: 0.00794 +2024-11-21 20:29:51.268450: train_loss -0.75 +2024-11-21 20:29:51.268733: val_loss -0.7019 +2024-11-21 20:29:51.268812: Pseudo dice [0.8241] +2024-11-21 20:29:51.268890: Epoch time: 20.36 s +2024-11-21 20:29:52.122193: +2024-11-21 20:29:52.122413: Epoch 1806 +2024-11-21 20:29:52.122527: Current learning rate: 0.00794 +2024-11-21 20:30:10.781346: train_loss -0.7538 +2024-11-21 20:30:10.781595: val_loss -0.7293 +2024-11-21 20:30:10.781668: Pseudo dice [0.8307] +2024-11-21 20:30:10.781749: Epoch time: 18.66 s +2024-11-21 20:30:11.644733: +2024-11-21 20:30:11.644950: Epoch 1807 +2024-11-21 20:30:11.645071: Current learning rate: 0.00794 +2024-11-21 20:30:29.306627: train_loss -0.757 +2024-11-21 20:30:29.306841: val_loss -0.7384 +2024-11-21 20:30:29.306923: Pseudo dice [0.8476] +2024-11-21 20:30:29.307005: Epoch time: 17.66 s +2024-11-21 20:30:30.259114: +2024-11-21 20:30:30.259324: Epoch 1808 +2024-11-21 20:30:30.259437: Current learning rate: 0.00794 +2024-11-21 20:30:49.179944: train_loss -0.7684 +2024-11-21 20:30:49.181962: val_loss -0.7433 +2024-11-21 20:30:49.182069: Pseudo dice [0.8318] +2024-11-21 20:30:49.182150: Epoch time: 18.92 s +2024-11-21 20:30:50.032881: +2024-11-21 20:30:50.033102: Epoch 1809 +2024-11-21 20:30:50.033230: Current learning rate: 0.00794 +2024-11-21 20:31:07.137211: train_loss -0.759 +2024-11-21 20:31:07.137465: val_loss -0.7418 +2024-11-21 20:31:07.137542: Pseudo dice [0.8381] +2024-11-21 20:31:07.137639: Epoch time: 17.11 s +2024-11-21 20:31:08.117854: +2024-11-21 20:31:08.118246: Epoch 1810 +2024-11-21 20:31:08.118360: Current learning rate: 0.00794 +2024-11-21 20:31:27.121957: train_loss -0.7642 +2024-11-21 20:31:27.122187: val_loss -0.7229 +2024-11-21 20:31:27.124393: Pseudo dice [0.8174] +2024-11-21 20:31:27.124542: Epoch time: 19.0 s +2024-11-21 20:31:28.122935: +2024-11-21 20:31:28.123154: Epoch 1811 +2024-11-21 20:31:28.123268: Current learning rate: 0.00794 +2024-11-21 20:31:46.830209: train_loss -0.7597 +2024-11-21 20:31:46.830444: val_loss -0.7486 +2024-11-21 20:31:46.830519: Pseudo dice [0.8345] +2024-11-21 20:31:46.830599: Epoch time: 18.71 s +2024-11-21 20:31:47.674850: +2024-11-21 20:31:47.675075: Epoch 1812 +2024-11-21 20:31:47.675200: Current learning rate: 0.00794 +2024-11-21 20:32:07.194205: train_loss -0.7545 +2024-11-21 20:32:07.194449: val_loss -0.7409 +2024-11-21 20:32:07.194528: Pseudo dice [0.8245] +2024-11-21 20:32:07.194609: Epoch time: 19.52 s +2024-11-21 20:32:08.043224: +2024-11-21 20:32:08.043447: Epoch 1813 +2024-11-21 20:32:08.043561: Current learning rate: 0.00794 +2024-11-21 20:32:25.902963: train_loss -0.7606 +2024-11-21 20:32:25.903200: val_loss -0.7627 +2024-11-21 20:32:25.903276: Pseudo dice [0.8526] +2024-11-21 20:32:25.903372: Epoch time: 17.86 s +2024-11-21 20:32:26.757351: +2024-11-21 20:32:26.757591: Epoch 1814 +2024-11-21 20:32:26.757704: Current learning rate: 0.00793 +2024-11-21 20:32:44.432292: train_loss -0.7607 +2024-11-21 20:32:44.433394: val_loss -0.7438 +2024-11-21 20:32:44.433485: Pseudo dice [0.8315] +2024-11-21 20:32:44.433562: Epoch time: 17.68 s +2024-11-21 20:32:45.306854: +2024-11-21 20:32:45.307076: Epoch 1815 +2024-11-21 20:32:45.307188: Current learning rate: 0.00793 +2024-11-21 20:33:04.136415: train_loss -0.7611 +2024-11-21 20:33:04.136651: val_loss -0.7548 +2024-11-21 20:33:04.136828: Pseudo dice [0.8484] +2024-11-21 20:33:04.136972: Epoch time: 18.83 s +2024-11-21 20:33:04.986491: +2024-11-21 20:33:04.986689: Epoch 1816 +2024-11-21 20:33:04.986804: Current learning rate: 0.00793 +2024-11-21 20:33:23.585134: train_loss -0.7615 +2024-11-21 20:33:23.585348: val_loss -0.7546 +2024-11-21 20:33:23.585427: Pseudo dice [0.8315] +2024-11-21 20:33:23.585503: Epoch time: 18.6 s +2024-11-21 20:33:24.435048: +2024-11-21 20:33:24.435244: Epoch 1817 +2024-11-21 20:33:24.435357: Current learning rate: 0.00793 +2024-11-21 20:33:44.082582: train_loss -0.7767 +2024-11-21 20:33:44.082803: val_loss -0.7448 +2024-11-21 20:33:44.082881: Pseudo dice [0.8336] +2024-11-21 20:33:44.082960: Epoch time: 19.65 s +2024-11-21 20:33:44.935318: +2024-11-21 20:33:44.935518: Epoch 1818 +2024-11-21 20:33:44.935638: Current learning rate: 0.00793 +2024-11-21 20:34:03.568792: train_loss -0.7618 +2024-11-21 20:34:03.569024: val_loss -0.7368 +2024-11-21 20:34:03.569101: Pseudo dice [0.8366] +2024-11-21 20:34:03.569265: Epoch time: 18.63 s +2024-11-21 20:34:04.411233: +2024-11-21 20:34:04.411490: Epoch 1819 +2024-11-21 20:34:04.411603: Current learning rate: 0.00793 +2024-11-21 20:34:21.718894: train_loss -0.7649 +2024-11-21 20:34:21.719147: val_loss -0.7019 +2024-11-21 20:34:21.719224: Pseudo dice [0.8072] +2024-11-21 20:34:21.719305: Epoch time: 17.31 s +2024-11-21 20:34:22.570340: +2024-11-21 20:34:22.570555: Epoch 1820 +2024-11-21 20:34:22.570678: Current learning rate: 0.00793 +2024-11-21 20:34:41.399182: train_loss -0.7715 +2024-11-21 20:34:41.399452: val_loss -0.7486 +2024-11-21 20:34:41.399534: Pseudo dice [0.8515] +2024-11-21 20:34:41.399613: Epoch time: 18.83 s +2024-11-21 20:34:42.318765: +2024-11-21 20:34:42.318953: Epoch 1821 +2024-11-21 20:34:42.319062: Current learning rate: 0.00793 +2024-11-21 20:35:01.919878: train_loss -0.7664 +2024-11-21 20:35:01.925291: val_loss -0.7225 +2024-11-21 20:35:01.925406: Pseudo dice [0.8251] +2024-11-21 20:35:01.925489: Epoch time: 19.6 s +2024-11-21 20:35:02.779443: +2024-11-21 20:35:02.779644: Epoch 1822 +2024-11-21 20:35:02.779763: Current learning rate: 0.00792 +2024-11-21 20:35:21.402286: train_loss -0.7607 +2024-11-21 20:35:21.402534: val_loss -0.7241 +2024-11-21 20:35:21.402609: Pseudo dice [0.8378] +2024-11-21 20:35:21.402689: Epoch time: 18.62 s +2024-11-21 20:35:22.642499: +2024-11-21 20:35:22.642706: Epoch 1823 +2024-11-21 20:35:22.642813: Current learning rate: 0.00792 +2024-11-21 20:35:42.128439: train_loss -0.7705 +2024-11-21 20:35:42.128660: val_loss -0.7441 +2024-11-21 20:35:42.128733: Pseudo dice [0.8286] +2024-11-21 20:35:42.128808: Epoch time: 19.49 s +2024-11-21 20:35:42.979332: +2024-11-21 20:35:42.979550: Epoch 1824 +2024-11-21 20:35:42.979671: Current learning rate: 0.00792 +2024-11-21 20:36:02.669653: train_loss -0.7677 +2024-11-21 20:36:02.669870: val_loss -0.7403 +2024-11-21 20:36:02.669947: Pseudo dice [0.8384] +2024-11-21 20:36:02.670028: Epoch time: 19.69 s +2024-11-21 20:36:03.616171: +2024-11-21 20:36:03.616415: Epoch 1825 +2024-11-21 20:36:03.616531: Current learning rate: 0.00792 +2024-11-21 20:36:22.327375: train_loss -0.766 +2024-11-21 20:36:22.327595: val_loss -0.7515 +2024-11-21 20:36:22.327671: Pseudo dice [0.8306] +2024-11-21 20:36:22.327748: Epoch time: 18.71 s +2024-11-21 20:36:23.176973: +2024-11-21 20:36:23.177202: Epoch 1826 +2024-11-21 20:36:23.177314: Current learning rate: 0.00792 +2024-11-21 20:36:42.477190: train_loss -0.7763 +2024-11-21 20:36:42.477439: val_loss -0.7473 +2024-11-21 20:36:42.477519: Pseudo dice [0.8361] +2024-11-21 20:36:42.477599: Epoch time: 19.3 s +2024-11-21 20:36:43.329401: +2024-11-21 20:36:43.329597: Epoch 1827 +2024-11-21 20:36:43.329711: Current learning rate: 0.00792 +2024-11-21 20:37:01.691087: train_loss -0.7761 +2024-11-21 20:37:01.691305: val_loss -0.7203 +2024-11-21 20:37:01.691386: Pseudo dice [0.8205] +2024-11-21 20:37:01.691468: Epoch time: 18.36 s +2024-11-21 20:37:02.537691: +2024-11-21 20:37:02.537896: Epoch 1828 +2024-11-21 20:37:02.538022: Current learning rate: 0.00792 +2024-11-21 20:37:22.098728: train_loss -0.7691 +2024-11-21 20:37:22.098945: val_loss -0.7317 +2024-11-21 20:37:22.099029: Pseudo dice [0.8198] +2024-11-21 20:37:22.099105: Epoch time: 19.56 s +2024-11-21 20:37:22.946629: +2024-11-21 20:37:22.946913: Epoch 1829 +2024-11-21 20:37:22.947042: Current learning rate: 0.00792 +2024-11-21 20:37:41.696379: train_loss -0.7781 +2024-11-21 20:37:41.696607: val_loss -0.7478 +2024-11-21 20:37:41.696686: Pseudo dice [0.8549] +2024-11-21 20:37:41.696768: Epoch time: 18.75 s +2024-11-21 20:37:42.539808: +2024-11-21 20:37:42.540015: Epoch 1830 +2024-11-21 20:37:42.540133: Current learning rate: 0.00792 +2024-11-21 20:38:00.900586: train_loss -0.7733 +2024-11-21 20:38:00.900849: val_loss -0.7459 +2024-11-21 20:38:00.900929: Pseudo dice [0.8678] +2024-11-21 20:38:00.901246: Epoch time: 18.36 s +2024-11-21 20:38:01.746270: +2024-11-21 20:38:01.746560: Epoch 1831 +2024-11-21 20:38:01.746685: Current learning rate: 0.00791 +2024-11-21 20:38:20.315830: train_loss -0.7762 +2024-11-21 20:38:20.316048: val_loss -0.7562 +2024-11-21 20:38:20.316125: Pseudo dice [0.8333] +2024-11-21 20:38:20.316201: Epoch time: 18.57 s +2024-11-21 20:38:21.239699: +2024-11-21 20:38:21.239914: Epoch 1832 +2024-11-21 20:38:21.240032: Current learning rate: 0.00791 +2024-11-21 20:38:39.781327: train_loss -0.7726 +2024-11-21 20:38:39.781562: val_loss -0.7342 +2024-11-21 20:38:39.781639: Pseudo dice [0.8387] +2024-11-21 20:38:39.781717: Epoch time: 18.54 s +2024-11-21 20:38:40.778912: +2024-11-21 20:38:40.779144: Epoch 1833 +2024-11-21 20:38:40.779266: Current learning rate: 0.00791 +2024-11-21 20:38:59.709888: train_loss -0.7704 +2024-11-21 20:38:59.710156: val_loss -0.7285 +2024-11-21 20:38:59.710235: Pseudo dice [0.8499] +2024-11-21 20:38:59.710315: Epoch time: 18.93 s +2024-11-21 20:39:00.964943: +2024-11-21 20:39:00.965179: Epoch 1834 +2024-11-21 20:39:00.965298: Current learning rate: 0.00791 +2024-11-21 20:39:20.068161: train_loss -0.7709 +2024-11-21 20:39:20.068428: val_loss -0.7255 +2024-11-21 20:39:20.068505: Pseudo dice [0.8305] +2024-11-21 20:39:20.068583: Epoch time: 19.1 s +2024-11-21 20:39:21.124170: +2024-11-21 20:39:21.124373: Epoch 1835 +2024-11-21 20:39:21.124484: Current learning rate: 0.00791 +2024-11-21 20:39:41.044542: train_loss -0.7746 +2024-11-21 20:39:41.044768: val_loss -0.7385 +2024-11-21 20:39:41.044847: Pseudo dice [0.8493] +2024-11-21 20:39:41.050097: Epoch time: 19.92 s +2024-11-21 20:39:42.017305: +2024-11-21 20:39:42.017518: Epoch 1836 +2024-11-21 20:39:42.017630: Current learning rate: 0.00791 +2024-11-21 20:40:00.215758: train_loss -0.768 +2024-11-21 20:40:00.215986: val_loss -0.7362 +2024-11-21 20:40:00.216075: Pseudo dice [0.841] +2024-11-21 20:40:00.216153: Epoch time: 18.2 s +2024-11-21 20:40:01.075836: +2024-11-21 20:40:01.076079: Epoch 1837 +2024-11-21 20:40:01.076194: Current learning rate: 0.00791 +2024-11-21 20:40:20.592205: train_loss -0.7816 +2024-11-21 20:40:20.592450: val_loss -0.7558 +2024-11-21 20:40:20.597764: Pseudo dice [0.8271] +2024-11-21 20:40:20.597869: Epoch time: 19.52 s +2024-11-21 20:40:21.576441: +2024-11-21 20:40:21.576648: Epoch 1838 +2024-11-21 20:40:21.576766: Current learning rate: 0.00791 +2024-11-21 20:40:40.295935: train_loss -0.774 +2024-11-21 20:40:40.296158: val_loss -0.7379 +2024-11-21 20:40:40.296236: Pseudo dice [0.831] +2024-11-21 20:40:40.296311: Epoch time: 18.72 s +2024-11-21 20:40:41.143135: +2024-11-21 20:40:41.143323: Epoch 1839 +2024-11-21 20:40:41.143431: Current learning rate: 0.00791 +2024-11-21 20:40:59.501916: train_loss -0.7741 +2024-11-21 20:40:59.502135: val_loss -0.7211 +2024-11-21 20:40:59.502208: Pseudo dice [0.8229] +2024-11-21 20:40:59.502285: Epoch time: 18.36 s +2024-11-21 20:41:00.352456: +2024-11-21 20:41:00.352763: Epoch 1840 +2024-11-21 20:41:00.352877: Current learning rate: 0.0079 +2024-11-21 20:41:19.669947: train_loss -0.78 +2024-11-21 20:41:19.670161: val_loss -0.7261 +2024-11-21 20:41:19.670236: Pseudo dice [0.8202] +2024-11-21 20:41:19.670310: Epoch time: 19.32 s +2024-11-21 20:41:20.599945: +2024-11-21 20:41:20.600155: Epoch 1841 +2024-11-21 20:41:20.600267: Current learning rate: 0.0079 +2024-11-21 20:41:39.903657: train_loss -0.7754 +2024-11-21 20:41:39.903899: val_loss -0.7369 +2024-11-21 20:41:39.903979: Pseudo dice [0.8246] +2024-11-21 20:41:39.904068: Epoch time: 19.3 s +2024-11-21 20:41:40.753987: +2024-11-21 20:41:40.754174: Epoch 1842 +2024-11-21 20:41:40.754368: Current learning rate: 0.0079 +2024-11-21 20:41:59.064739: train_loss -0.7675 +2024-11-21 20:41:59.064947: val_loss -0.7313 +2024-11-21 20:41:59.065028: Pseudo dice [0.814] +2024-11-21 20:41:59.065103: Epoch time: 18.31 s +2024-11-21 20:41:59.911920: +2024-11-21 20:41:59.912137: Epoch 1843 +2024-11-21 20:41:59.912252: Current learning rate: 0.0079 +2024-11-21 20:42:19.278846: train_loss -0.7625 +2024-11-21 20:42:19.279187: val_loss -0.6932 +2024-11-21 20:42:19.279271: Pseudo dice [0.8136] +2024-11-21 20:42:19.279346: Epoch time: 19.37 s +2024-11-21 20:42:20.135586: +2024-11-21 20:42:20.136035: Epoch 1844 +2024-11-21 20:42:20.136172: Current learning rate: 0.0079 +2024-11-21 20:42:38.654298: train_loss -0.7686 +2024-11-21 20:42:38.654522: val_loss -0.7094 +2024-11-21 20:42:38.654595: Pseudo dice [0.8311] +2024-11-21 20:42:38.654672: Epoch time: 18.52 s +2024-11-21 20:42:39.505695: +2024-11-21 20:42:39.505914: Epoch 1845 +2024-11-21 20:42:39.506071: Current learning rate: 0.0079 +2024-11-21 20:42:57.467811: train_loss -0.7733 +2024-11-21 20:42:57.468029: val_loss -0.752 +2024-11-21 20:42:57.468106: Pseudo dice [0.8404] +2024-11-21 20:42:57.468184: Epoch time: 17.96 s +2024-11-21 20:42:58.712374: +2024-11-21 20:42:58.712576: Epoch 1846 +2024-11-21 20:42:58.712692: Current learning rate: 0.0079 +2024-11-21 20:43:17.983061: train_loss -0.7782 +2024-11-21 20:43:17.983280: val_loss -0.7557 +2024-11-21 20:43:17.983358: Pseudo dice [0.849] +2024-11-21 20:43:17.983440: Epoch time: 19.27 s +2024-11-21 20:43:18.824450: +2024-11-21 20:43:18.824674: Epoch 1847 +2024-11-21 20:43:18.824786: Current learning rate: 0.0079 +2024-11-21 20:43:37.889831: train_loss -0.7728 +2024-11-21 20:43:37.890137: val_loss -0.7339 +2024-11-21 20:43:37.890219: Pseudo dice [0.8466] +2024-11-21 20:43:37.890299: Epoch time: 19.07 s +2024-11-21 20:43:38.737761: +2024-11-21 20:43:38.738003: Epoch 1848 +2024-11-21 20:43:38.738114: Current learning rate: 0.00789 +2024-11-21 20:43:56.891713: train_loss -0.7831 +2024-11-21 20:43:56.892025: val_loss -0.7649 +2024-11-21 20:43:56.892102: Pseudo dice [0.8607] +2024-11-21 20:43:56.892224: Epoch time: 18.15 s +2024-11-21 20:43:57.749225: +2024-11-21 20:43:57.749568: Epoch 1849 +2024-11-21 20:43:57.749682: Current learning rate: 0.00789 +2024-11-21 20:44:17.131648: train_loss -0.7747 +2024-11-21 20:44:17.131863: val_loss -0.7427 +2024-11-21 20:44:17.131936: Pseudo dice [0.8393] +2024-11-21 20:44:17.132019: Epoch time: 19.38 s +2024-11-21 20:44:18.179115: +2024-11-21 20:44:18.179311: Epoch 1850 +2024-11-21 20:44:18.179427: Current learning rate: 0.00789 +2024-11-21 20:44:37.454436: train_loss -0.7676 +2024-11-21 20:44:37.454719: val_loss -0.7597 +2024-11-21 20:44:37.454799: Pseudo dice [0.8558] +2024-11-21 20:44:37.454880: Epoch time: 19.28 s +2024-11-21 20:44:38.303513: +2024-11-21 20:44:38.303734: Epoch 1851 +2024-11-21 20:44:38.303845: Current learning rate: 0.00789 +2024-11-21 20:44:56.441679: train_loss -0.78 +2024-11-21 20:44:56.441906: val_loss -0.7491 +2024-11-21 20:44:56.441986: Pseudo dice [0.8221] +2024-11-21 20:44:56.447214: Epoch time: 18.14 s +2024-11-21 20:44:57.312420: +2024-11-21 20:44:57.312656: Epoch 1852 +2024-11-21 20:44:57.312781: Current learning rate: 0.00789 +2024-11-21 20:45:15.970050: train_loss -0.778 +2024-11-21 20:45:15.970299: val_loss -0.7597 +2024-11-21 20:45:15.970380: Pseudo dice [0.831] +2024-11-21 20:45:15.970470: Epoch time: 18.66 s +2024-11-21 20:45:16.818905: +2024-11-21 20:45:16.819122: Epoch 1853 +2024-11-21 20:45:16.819234: Current learning rate: 0.00789 +2024-11-21 20:45:34.996346: train_loss -0.7747 +2024-11-21 20:45:34.996582: val_loss -0.7373 +2024-11-21 20:45:34.996658: Pseudo dice [0.8524] +2024-11-21 20:45:34.996735: Epoch time: 18.18 s +2024-11-21 20:45:35.849361: +2024-11-21 20:45:35.849649: Epoch 1854 +2024-11-21 20:45:35.849764: Current learning rate: 0.00789 +2024-11-21 20:45:53.939838: train_loss -0.7859 +2024-11-21 20:45:53.940059: val_loss -0.7753 +2024-11-21 20:45:53.940133: Pseudo dice [0.8483] +2024-11-21 20:45:53.940208: Epoch time: 18.09 s +2024-11-21 20:45:54.789760: +2024-11-21 20:45:54.790012: Epoch 1855 +2024-11-21 20:45:54.790134: Current learning rate: 0.00789 +2024-11-21 20:46:13.430875: train_loss -0.7756 +2024-11-21 20:46:13.431123: val_loss -0.7564 +2024-11-21 20:46:13.431198: Pseudo dice [0.8261] +2024-11-21 20:46:13.431281: Epoch time: 18.64 s +2024-11-21 20:46:14.316483: +2024-11-21 20:46:14.316676: Epoch 1856 +2024-11-21 20:46:14.316789: Current learning rate: 0.00789 +2024-11-21 20:46:32.855541: train_loss -0.7757 +2024-11-21 20:46:32.865765: val_loss -0.7273 +2024-11-21 20:46:32.866146: Pseudo dice [0.8383] +2024-11-21 20:46:32.866237: Epoch time: 18.54 s +2024-11-21 20:46:33.718193: +2024-11-21 20:46:33.718412: Epoch 1857 +2024-11-21 20:46:33.718524: Current learning rate: 0.00788 +2024-11-21 20:46:52.796205: train_loss -0.7642 +2024-11-21 20:46:52.796441: val_loss -0.7451 +2024-11-21 20:46:52.796517: Pseudo dice [0.8428] +2024-11-21 20:46:52.796593: Epoch time: 19.08 s +2024-11-21 20:46:53.674155: +2024-11-21 20:46:53.674405: Epoch 1858 +2024-11-21 20:46:53.674527: Current learning rate: 0.00788 +2024-11-21 20:47:12.634256: train_loss -0.7773 +2024-11-21 20:47:12.634515: val_loss -0.7516 +2024-11-21 20:47:12.634637: Pseudo dice [0.833] +2024-11-21 20:47:12.634729: Epoch time: 18.96 s +2024-11-21 20:47:13.485152: +2024-11-21 20:47:13.485351: Epoch 1859 +2024-11-21 20:47:13.485459: Current learning rate: 0.00788 +2024-11-21 20:47:32.218713: train_loss -0.7746 +2024-11-21 20:47:32.218946: val_loss -0.7535 +2024-11-21 20:47:32.219045: Pseudo dice [0.8513] +2024-11-21 20:47:32.219123: Epoch time: 18.73 s +2024-11-21 20:47:33.064564: +2024-11-21 20:47:33.064790: Epoch 1860 +2024-11-21 20:47:33.064901: Current learning rate: 0.00788 +2024-11-21 20:47:51.915824: train_loss -0.7705 +2024-11-21 20:47:51.916063: val_loss -0.7518 +2024-11-21 20:47:51.916141: Pseudo dice [0.851] +2024-11-21 20:47:51.916218: Epoch time: 18.85 s +2024-11-21 20:47:52.780932: +2024-11-21 20:47:52.781160: Epoch 1861 +2024-11-21 20:47:52.781276: Current learning rate: 0.00788 +2024-11-21 20:48:11.947859: train_loss -0.7705 +2024-11-21 20:48:11.948151: val_loss -0.742 +2024-11-21 20:48:11.948230: Pseudo dice [0.8453] +2024-11-21 20:48:11.948306: Epoch time: 19.17 s +2024-11-21 20:48:12.797054: +2024-11-21 20:48:12.797264: Epoch 1862 +2024-11-21 20:48:12.797375: Current learning rate: 0.00788 +2024-11-21 20:48:31.956352: train_loss -0.774 +2024-11-21 20:48:31.956678: val_loss -0.7214 +2024-11-21 20:48:31.956765: Pseudo dice [0.8265] +2024-11-21 20:48:31.956851: Epoch time: 19.16 s +2024-11-21 20:48:32.808611: +2024-11-21 20:48:32.808841: Epoch 1863 +2024-11-21 20:48:32.808960: Current learning rate: 0.00788 +2024-11-21 20:48:52.606461: train_loss -0.7809 +2024-11-21 20:48:52.606678: val_loss -0.7585 +2024-11-21 20:48:52.606751: Pseudo dice [0.844] +2024-11-21 20:48:52.606830: Epoch time: 19.8 s +2024-11-21 20:48:53.456687: +2024-11-21 20:48:53.456894: Epoch 1864 +2024-11-21 20:48:53.457013: Current learning rate: 0.00788 +2024-11-21 20:49:12.526670: train_loss -0.7746 +2024-11-21 20:49:12.526893: val_loss -0.7539 +2024-11-21 20:49:12.526968: Pseudo dice [0.8462] +2024-11-21 20:49:12.527053: Epoch time: 19.07 s +2024-11-21 20:49:13.379078: +2024-11-21 20:49:13.379358: Epoch 1865 +2024-11-21 20:49:13.379467: Current learning rate: 0.00788 +2024-11-21 20:49:32.017116: train_loss -0.7741 +2024-11-21 20:49:32.017337: val_loss -0.7207 +2024-11-21 20:49:32.017411: Pseudo dice [0.8179] +2024-11-21 20:49:32.017487: Epoch time: 18.64 s +2024-11-21 20:49:32.909211: +2024-11-21 20:49:32.909438: Epoch 1866 +2024-11-21 20:49:32.909551: Current learning rate: 0.00787 +2024-11-21 20:49:51.030265: train_loss -0.7689 +2024-11-21 20:49:51.030513: val_loss -0.7397 +2024-11-21 20:49:51.030670: Pseudo dice [0.8422] +2024-11-21 20:49:51.030755: Epoch time: 18.12 s +2024-11-21 20:49:51.879396: +2024-11-21 20:49:51.879629: Epoch 1867 +2024-11-21 20:49:51.879740: Current learning rate: 0.00787 +2024-11-21 20:50:11.032181: train_loss -0.7808 +2024-11-21 20:50:11.032406: val_loss -0.749 +2024-11-21 20:50:11.032483: Pseudo dice [0.8443] +2024-11-21 20:50:11.034730: Epoch time: 19.15 s +2024-11-21 20:50:12.045877: +2024-11-21 20:50:12.046083: Epoch 1868 +2024-11-21 20:50:12.046193: Current learning rate: 0.00787 +2024-11-21 20:50:31.179136: train_loss -0.7766 +2024-11-21 20:50:31.179356: val_loss -0.751 +2024-11-21 20:50:31.179431: Pseudo dice [0.8368] +2024-11-21 20:50:31.179506: Epoch time: 19.13 s +2024-11-21 20:50:32.423374: +2024-11-21 20:50:32.423569: Epoch 1869 +2024-11-21 20:50:32.423679: Current learning rate: 0.00787 +2024-11-21 20:50:51.366196: train_loss -0.7854 +2024-11-21 20:50:51.366461: val_loss -0.7551 +2024-11-21 20:50:51.366540: Pseudo dice [0.8594] +2024-11-21 20:50:51.366658: Epoch time: 18.94 s +2024-11-21 20:50:52.217815: +2024-11-21 20:50:52.218057: Epoch 1870 +2024-11-21 20:50:52.218181: Current learning rate: 0.00787 +2024-11-21 20:51:10.817365: train_loss -0.7612 +2024-11-21 20:51:10.817589: val_loss -0.7295 +2024-11-21 20:51:10.817669: Pseudo dice [0.8355] +2024-11-21 20:51:10.817745: Epoch time: 18.6 s +2024-11-21 20:51:11.666810: +2024-11-21 20:51:11.667037: Epoch 1871 +2024-11-21 20:51:11.667153: Current learning rate: 0.00787 +2024-11-21 20:51:30.390627: train_loss -0.7701 +2024-11-21 20:51:30.390910: val_loss -0.7417 +2024-11-21 20:51:30.390988: Pseudo dice [0.831] +2024-11-21 20:51:30.391070: Epoch time: 18.72 s +2024-11-21 20:51:31.244909: +2024-11-21 20:51:31.245140: Epoch 1872 +2024-11-21 20:51:31.245256: Current learning rate: 0.00787 +2024-11-21 20:51:49.694311: train_loss -0.7766 +2024-11-21 20:51:49.694560: val_loss -0.7415 +2024-11-21 20:51:49.694637: Pseudo dice [0.8209] +2024-11-21 20:51:49.694720: Epoch time: 18.45 s +2024-11-21 20:51:50.548571: +2024-11-21 20:51:50.548791: Epoch 1873 +2024-11-21 20:51:50.548910: Current learning rate: 0.00787 +2024-11-21 20:52:10.073219: train_loss -0.7712 +2024-11-21 20:52:10.073437: val_loss -0.7465 +2024-11-21 20:52:10.073511: Pseudo dice [0.8289] +2024-11-21 20:52:10.073587: Epoch time: 19.53 s +2024-11-21 20:52:10.921425: +2024-11-21 20:52:10.921633: Epoch 1874 +2024-11-21 20:52:10.921753: Current learning rate: 0.00786 +2024-11-21 20:52:28.756891: train_loss -0.7657 +2024-11-21 20:52:28.757619: val_loss -0.7654 +2024-11-21 20:52:28.757707: Pseudo dice [0.8437] +2024-11-21 20:52:28.757789: Epoch time: 17.84 s +2024-11-21 20:52:29.607122: +2024-11-21 20:52:29.607348: Epoch 1875 +2024-11-21 20:52:29.607466: Current learning rate: 0.00786 +2024-11-21 20:52:48.375263: train_loss -0.7703 +2024-11-21 20:52:48.375474: val_loss -0.7203 +2024-11-21 20:52:48.375549: Pseudo dice [0.8135] +2024-11-21 20:52:48.375627: Epoch time: 18.77 s +2024-11-21 20:52:49.223100: +2024-11-21 20:52:49.223304: Epoch 1876 +2024-11-21 20:52:49.223416: Current learning rate: 0.00786 +2024-11-21 20:53:07.877156: train_loss -0.7659 +2024-11-21 20:53:07.877424: val_loss -0.7482 +2024-11-21 20:53:07.877503: Pseudo dice [0.8321] +2024-11-21 20:53:07.877589: Epoch time: 18.65 s +2024-11-21 20:53:08.738151: +2024-11-21 20:53:08.738351: Epoch 1877 +2024-11-21 20:53:08.738458: Current learning rate: 0.00786 +2024-11-21 20:53:26.496117: train_loss -0.7754 +2024-11-21 20:53:26.496326: val_loss -0.7332 +2024-11-21 20:53:26.496405: Pseudo dice [0.8655] +2024-11-21 20:53:26.496488: Epoch time: 17.76 s +2024-11-21 20:53:27.346557: +2024-11-21 20:53:27.346770: Epoch 1878 +2024-11-21 20:53:27.346883: Current learning rate: 0.00786 +2024-11-21 20:53:45.992924: train_loss -0.773 +2024-11-21 20:53:45.993160: val_loss -0.7406 +2024-11-21 20:53:45.993237: Pseudo dice [0.8228] +2024-11-21 20:53:45.993317: Epoch time: 18.65 s +2024-11-21 20:53:46.844753: +2024-11-21 20:53:46.844989: Epoch 1879 +2024-11-21 20:53:46.845118: Current learning rate: 0.00786 +2024-11-21 20:54:04.420348: train_loss -0.7787 +2024-11-21 20:54:04.420598: val_loss -0.714 +2024-11-21 20:54:04.420729: Pseudo dice [0.8088] +2024-11-21 20:54:04.420817: Epoch time: 17.58 s +2024-11-21 20:54:05.376722: +2024-11-21 20:54:05.376925: Epoch 1880 +2024-11-21 20:54:05.377045: Current learning rate: 0.00786 +2024-11-21 20:54:24.222400: train_loss -0.7551 +2024-11-21 20:54:24.222661: val_loss -0.7253 +2024-11-21 20:54:24.222735: Pseudo dice [0.8365] +2024-11-21 20:54:24.222812: Epoch time: 18.85 s +2024-11-21 20:54:25.216971: +2024-11-21 20:54:25.217191: Epoch 1881 +2024-11-21 20:54:25.217304: Current learning rate: 0.00786 +2024-11-21 20:54:44.253595: train_loss -0.7523 +2024-11-21 20:54:44.256036: val_loss -0.7303 +2024-11-21 20:54:44.256170: Pseudo dice [0.8236] +2024-11-21 20:54:44.256249: Epoch time: 19.04 s +2024-11-21 20:54:45.211278: +2024-11-21 20:54:45.211496: Epoch 1882 +2024-11-21 20:54:45.211611: Current learning rate: 0.00786 +2024-11-21 20:55:05.699660: train_loss -0.771 +2024-11-21 20:55:05.699899: val_loss -0.7402 +2024-11-21 20:55:05.700298: Pseudo dice [0.8417] +2024-11-21 20:55:05.700394: Epoch time: 20.49 s +2024-11-21 20:55:06.552601: +2024-11-21 20:55:06.552814: Epoch 1883 +2024-11-21 20:55:06.552925: Current learning rate: 0.00785 +2024-11-21 20:55:25.348209: train_loss -0.7692 +2024-11-21 20:55:25.348448: val_loss -0.7349 +2024-11-21 20:55:25.348527: Pseudo dice [0.8391] +2024-11-21 20:55:25.348606: Epoch time: 18.8 s +2024-11-21 20:55:26.202168: +2024-11-21 20:55:26.202487: Epoch 1884 +2024-11-21 20:55:26.202605: Current learning rate: 0.00785 +2024-11-21 20:55:44.261820: train_loss -0.7509 +2024-11-21 20:55:44.262113: val_loss -0.6871 +2024-11-21 20:55:44.262195: Pseudo dice [0.8166] +2024-11-21 20:55:44.262276: Epoch time: 18.06 s +2024-11-21 20:55:45.115916: +2024-11-21 20:55:45.116142: Epoch 1885 +2024-11-21 20:55:45.116256: Current learning rate: 0.00785 +2024-11-21 20:56:04.213914: train_loss -0.7583 +2024-11-21 20:56:04.216267: val_loss -0.7191 +2024-11-21 20:56:04.216363: Pseudo dice [0.8183] +2024-11-21 20:56:04.216443: Epoch time: 19.1 s +2024-11-21 20:56:05.158365: +2024-11-21 20:56:05.158595: Epoch 1886 +2024-11-21 20:56:05.158712: Current learning rate: 0.00785 +2024-11-21 20:56:23.790887: train_loss -0.7489 +2024-11-21 20:56:23.796334: val_loss -0.7223 +2024-11-21 20:56:23.796425: Pseudo dice [0.8144] +2024-11-21 20:56:23.796514: Epoch time: 18.63 s +2024-11-21 20:56:24.770865: +2024-11-21 20:56:24.771105: Epoch 1887 +2024-11-21 20:56:24.771219: Current learning rate: 0.00785 +2024-11-21 20:56:43.924604: train_loss -0.7483 +2024-11-21 20:56:43.924880: val_loss -0.7597 +2024-11-21 20:56:43.924961: Pseudo dice [0.8464] +2024-11-21 20:56:43.925048: Epoch time: 19.15 s +2024-11-21 20:56:44.778940: +2024-11-21 20:56:44.779187: Epoch 1888 +2024-11-21 20:56:44.779296: Current learning rate: 0.00785 +2024-11-21 20:57:03.268712: train_loss -0.7596 +2024-11-21 20:57:03.268942: val_loss -0.7199 +2024-11-21 20:57:03.269024: Pseudo dice [0.8287] +2024-11-21 20:57:03.269104: Epoch time: 18.49 s +2024-11-21 20:57:04.113067: +2024-11-21 20:57:04.113286: Epoch 1889 +2024-11-21 20:57:04.113398: Current learning rate: 0.00785 +2024-11-21 20:57:21.933999: train_loss -0.7749 +2024-11-21 20:57:21.934227: val_loss -0.7208 +2024-11-21 20:57:21.934304: Pseudo dice [0.8281] +2024-11-21 20:57:21.934381: Epoch time: 17.82 s +2024-11-21 20:57:22.788111: +2024-11-21 20:57:22.788321: Epoch 1890 +2024-11-21 20:57:22.788462: Current learning rate: 0.00785 +2024-11-21 20:57:41.924304: train_loss -0.7732 +2024-11-21 20:57:41.924559: val_loss -0.7402 +2024-11-21 20:57:41.924639: Pseudo dice [0.8335] +2024-11-21 20:57:41.924721: Epoch time: 19.14 s +2024-11-21 20:57:42.781780: +2024-11-21 20:57:42.781984: Epoch 1891 +2024-11-21 20:57:42.782098: Current learning rate: 0.00784 +2024-11-21 20:58:01.714391: train_loss -0.7672 +2024-11-21 20:58:01.714606: val_loss -0.7582 +2024-11-21 20:58:01.714683: Pseudo dice [0.8537] +2024-11-21 20:58:01.714758: Epoch time: 18.93 s +2024-11-21 20:58:02.956352: +2024-11-21 20:58:02.956566: Epoch 1892 +2024-11-21 20:58:02.956679: Current learning rate: 0.00784 +2024-11-21 20:58:23.302293: train_loss -0.774 +2024-11-21 20:58:23.303655: val_loss -0.7377 +2024-11-21 20:58:23.303752: Pseudo dice [0.8332] +2024-11-21 20:58:23.303835: Epoch time: 20.35 s +2024-11-21 20:58:24.172747: +2024-11-21 20:58:24.172978: Epoch 1893 +2024-11-21 20:58:24.173102: Current learning rate: 0.00784 +2024-11-21 20:58:42.778154: train_loss -0.7763 +2024-11-21 20:58:42.778484: val_loss -0.7385 +2024-11-21 20:58:42.778562: Pseudo dice [0.8332] +2024-11-21 20:58:42.778646: Epoch time: 18.61 s +2024-11-21 20:58:43.818463: +2024-11-21 20:58:43.818694: Epoch 1894 +2024-11-21 20:58:43.818805: Current learning rate: 0.00784 +2024-11-21 20:59:01.886462: train_loss -0.7665 +2024-11-21 20:59:01.886679: val_loss -0.7241 +2024-11-21 20:59:01.886756: Pseudo dice [0.8322] +2024-11-21 20:59:01.886920: Epoch time: 18.07 s +2024-11-21 20:59:02.756486: +2024-11-21 20:59:02.756745: Epoch 1895 +2024-11-21 20:59:02.756858: Current learning rate: 0.00784 +2024-11-21 20:59:21.767918: train_loss -0.7638 +2024-11-21 20:59:21.768141: val_loss -0.7179 +2024-11-21 20:59:21.768252: Pseudo dice [0.8398] +2024-11-21 20:59:21.768327: Epoch time: 19.01 s +2024-11-21 20:59:22.693678: +2024-11-21 20:59:22.693898: Epoch 1896 +2024-11-21 20:59:22.694013: Current learning rate: 0.00784 +2024-11-21 20:59:41.628052: train_loss -0.7808 +2024-11-21 20:59:41.628270: val_loss -0.7598 +2024-11-21 20:59:41.628382: Pseudo dice [0.8344] +2024-11-21 20:59:41.628463: Epoch time: 18.94 s +2024-11-21 20:59:42.478875: +2024-11-21 20:59:42.479178: Epoch 1897 +2024-11-21 20:59:42.479293: Current learning rate: 0.00784 +2024-11-21 21:00:00.532231: train_loss -0.7716 +2024-11-21 21:00:00.532483: val_loss -0.7448 +2024-11-21 21:00:00.532559: Pseudo dice [0.8538] +2024-11-21 21:00:00.532645: Epoch time: 18.05 s +2024-11-21 21:00:01.481020: +2024-11-21 21:00:01.481212: Epoch 1898 +2024-11-21 21:00:01.481325: Current learning rate: 0.00784 +2024-11-21 21:00:20.154182: train_loss -0.7805 +2024-11-21 21:00:20.154468: val_loss -0.7469 +2024-11-21 21:00:20.154548: Pseudo dice [0.8312] +2024-11-21 21:00:20.154624: Epoch time: 18.67 s +2024-11-21 21:00:21.103712: +2024-11-21 21:00:21.103915: Epoch 1899 +2024-11-21 21:00:21.104033: Current learning rate: 0.00784 +2024-11-21 21:00:40.037048: train_loss -0.7808 +2024-11-21 21:00:40.037331: val_loss -0.7336 +2024-11-21 21:00:40.037409: Pseudo dice [0.8412] +2024-11-21 21:00:40.037485: Epoch time: 18.93 s +2024-11-21 21:00:41.094188: +2024-11-21 21:00:41.094386: Epoch 1900 +2024-11-21 21:00:41.094497: Current learning rate: 0.00783 +2024-11-21 21:00:59.392275: train_loss -0.7802 +2024-11-21 21:00:59.392536: val_loss -0.7479 +2024-11-21 21:00:59.392613: Pseudo dice [0.8484] +2024-11-21 21:00:59.392690: Epoch time: 18.3 s +2024-11-21 21:01:00.245688: +2024-11-21 21:01:00.245915: Epoch 1901 +2024-11-21 21:01:00.246052: Current learning rate: 0.00783 +2024-11-21 21:01:20.763756: train_loss -0.7783 +2024-11-21 21:01:20.764006: val_loss -0.7706 +2024-11-21 21:01:20.764082: Pseudo dice [0.8554] +2024-11-21 21:01:20.764162: Epoch time: 20.52 s +2024-11-21 21:01:21.616340: +2024-11-21 21:01:21.616557: Epoch 1902 +2024-11-21 21:01:21.616671: Current learning rate: 0.00783 +2024-11-21 21:01:40.913415: train_loss -0.7801 +2024-11-21 21:01:40.913640: val_loss -0.7527 +2024-11-21 21:01:40.913724: Pseudo dice [0.8382] +2024-11-21 21:01:40.913808: Epoch time: 19.3 s +2024-11-21 21:01:41.757492: +2024-11-21 21:01:41.757680: Epoch 1903 +2024-11-21 21:01:41.757795: Current learning rate: 0.00783 +2024-11-21 21:02:00.857957: train_loss -0.7632 +2024-11-21 21:02:00.858206: val_loss -0.7369 +2024-11-21 21:02:00.860471: Pseudo dice [0.8314] +2024-11-21 21:02:00.860569: Epoch time: 19.1 s +2024-11-21 21:02:01.767296: +2024-11-21 21:02:01.767516: Epoch 1904 +2024-11-21 21:02:01.767627: Current learning rate: 0.00783 +2024-11-21 21:02:20.624306: train_loss -0.7614 +2024-11-21 21:02:20.624608: val_loss -0.7237 +2024-11-21 21:02:20.624705: Pseudo dice [0.8447] +2024-11-21 21:02:20.624789: Epoch time: 18.86 s +2024-11-21 21:02:21.471864: +2024-11-21 21:02:21.472086: Epoch 1905 +2024-11-21 21:02:21.472203: Current learning rate: 0.00783 +2024-11-21 21:02:40.735582: train_loss -0.7841 +2024-11-21 21:02:40.735778: val_loss -0.7285 +2024-11-21 21:02:40.735852: Pseudo dice [0.8237] +2024-11-21 21:02:40.737434: Epoch time: 19.26 s +2024-11-21 21:02:41.612700: +2024-11-21 21:02:41.612956: Epoch 1906 +2024-11-21 21:02:41.613078: Current learning rate: 0.00783 +2024-11-21 21:02:59.615467: train_loss -0.7831 +2024-11-21 21:02:59.615695: val_loss -0.745 +2024-11-21 21:02:59.615777: Pseudo dice [0.8323] +2024-11-21 21:02:59.615854: Epoch time: 18.0 s +2024-11-21 21:03:00.467651: +2024-11-21 21:03:00.467856: Epoch 1907 +2024-11-21 21:03:00.467964: Current learning rate: 0.00783 +2024-11-21 21:03:19.436805: train_loss -0.7803 +2024-11-21 21:03:19.437089: val_loss -0.7386 +2024-11-21 21:03:19.437206: Pseudo dice [0.8443] +2024-11-21 21:03:19.437292: Epoch time: 18.97 s +2024-11-21 21:03:20.324739: +2024-11-21 21:03:20.324947: Epoch 1908 +2024-11-21 21:03:20.325068: Current learning rate: 0.00783 +2024-11-21 21:03:38.996987: train_loss -0.7711 +2024-11-21 21:03:38.997215: val_loss -0.7356 +2024-11-21 21:03:38.997555: Pseudo dice [0.8371] +2024-11-21 21:03:38.997662: Epoch time: 18.67 s +2024-11-21 21:03:39.852592: +2024-11-21 21:03:39.852983: Epoch 1909 +2024-11-21 21:03:39.853102: Current learning rate: 0.00782 +2024-11-21 21:03:59.924823: train_loss -0.7677 +2024-11-21 21:03:59.925037: val_loss -0.7285 +2024-11-21 21:03:59.925114: Pseudo dice [0.8379] +2024-11-21 21:03:59.925189: Epoch time: 20.07 s +2024-11-21 21:04:00.761471: +2024-11-21 21:04:00.761660: Epoch 1910 +2024-11-21 21:04:00.763508: Current learning rate: 0.00782 +2024-11-21 21:04:19.161079: train_loss -0.7749 +2024-11-21 21:04:19.161354: val_loss -0.75 +2024-11-21 21:04:19.161432: Pseudo dice [0.8141] +2024-11-21 21:04:19.161510: Epoch time: 18.4 s +2024-11-21 21:04:20.007822: +2024-11-21 21:04:20.008047: Epoch 1911 +2024-11-21 21:04:20.008165: Current learning rate: 0.00782 +2024-11-21 21:04:38.447860: train_loss -0.7715 +2024-11-21 21:04:38.448123: val_loss -0.7572 +2024-11-21 21:04:38.448200: Pseudo dice [0.8491] +2024-11-21 21:04:38.448288: Epoch time: 18.44 s +2024-11-21 21:04:39.303309: +2024-11-21 21:04:39.303524: Epoch 1912 +2024-11-21 21:04:39.303631: Current learning rate: 0.00782 +2024-11-21 21:04:57.723852: train_loss -0.7756 +2024-11-21 21:04:57.724071: val_loss -0.7187 +2024-11-21 21:04:57.724146: Pseudo dice [0.8048] +2024-11-21 21:04:57.724222: Epoch time: 18.42 s +2024-11-21 21:04:58.629773: +2024-11-21 21:04:58.630014: Epoch 1913 +2024-11-21 21:04:58.630126: Current learning rate: 0.00782 +2024-11-21 21:05:18.871373: train_loss -0.7628 +2024-11-21 21:05:18.871593: val_loss -0.7327 +2024-11-21 21:05:18.871671: Pseudo dice [0.8404] +2024-11-21 21:05:18.871749: Epoch time: 20.24 s +2024-11-21 21:05:19.729856: +2024-11-21 21:05:19.730084: Epoch 1914 +2024-11-21 21:05:19.730202: Current learning rate: 0.00782 +2024-11-21 21:05:38.005505: train_loss -0.767 +2024-11-21 21:05:38.005754: val_loss -0.7556 +2024-11-21 21:05:38.005833: Pseudo dice [0.842] +2024-11-21 21:05:38.005915: Epoch time: 18.28 s +2024-11-21 21:05:38.992216: +2024-11-21 21:05:38.992422: Epoch 1915 +2024-11-21 21:05:38.992535: Current learning rate: 0.00782 +2024-11-21 21:05:57.437936: train_loss -0.7723 +2024-11-21 21:05:57.438828: val_loss -0.7334 +2024-11-21 21:05:57.438919: Pseudo dice [0.8427] +2024-11-21 21:05:57.439005: Epoch time: 18.45 s +2024-11-21 21:05:58.349997: +2024-11-21 21:05:58.350258: Epoch 1916 +2024-11-21 21:05:58.350375: Current learning rate: 0.00782 +2024-11-21 21:06:17.578897: train_loss -0.7635 +2024-11-21 21:06:17.579143: val_loss -0.7414 +2024-11-21 21:06:17.579300: Pseudo dice [0.8163] +2024-11-21 21:06:17.579389: Epoch time: 19.23 s +2024-11-21 21:06:18.434026: +2024-11-21 21:06:18.434237: Epoch 1917 +2024-11-21 21:06:18.434355: Current learning rate: 0.00781 +2024-11-21 21:06:37.397261: train_loss -0.7668 +2024-11-21 21:06:37.397544: val_loss -0.7541 +2024-11-21 21:06:37.397625: Pseudo dice [0.8242] +2024-11-21 21:06:37.397704: Epoch time: 18.96 s +2024-11-21 21:06:38.257179: +2024-11-21 21:06:38.257416: Epoch 1918 +2024-11-21 21:06:38.257533: Current learning rate: 0.00781 +2024-11-21 21:06:56.621670: train_loss -0.7642 +2024-11-21 21:06:56.621957: val_loss -0.7188 +2024-11-21 21:06:56.622044: Pseudo dice [0.8138] +2024-11-21 21:06:56.622136: Epoch time: 18.36 s +2024-11-21 21:06:57.504604: +2024-11-21 21:06:57.504803: Epoch 1919 +2024-11-21 21:06:57.504913: Current learning rate: 0.00781 +2024-11-21 21:07:16.820532: train_loss -0.7687 +2024-11-21 21:07:16.820756: val_loss -0.7388 +2024-11-21 21:07:16.820830: Pseudo dice [0.8471] +2024-11-21 21:07:16.820904: Epoch time: 19.32 s +2024-11-21 21:07:17.707582: +2024-11-21 21:07:17.707840: Epoch 1920 +2024-11-21 21:07:17.707956: Current learning rate: 0.00781 +2024-11-21 21:07:37.396309: train_loss -0.7664 +2024-11-21 21:07:37.396548: val_loss -0.7493 +2024-11-21 21:07:37.396624: Pseudo dice [0.8248] +2024-11-21 21:07:37.396699: Epoch time: 19.69 s +2024-11-21 21:07:38.505816: +2024-11-21 21:07:38.506042: Epoch 1921 +2024-11-21 21:07:38.506160: Current learning rate: 0.00781 +2024-11-21 21:07:56.676756: train_loss -0.7796 +2024-11-21 21:07:56.677017: val_loss -0.742 +2024-11-21 21:07:56.677097: Pseudo dice [0.834] +2024-11-21 21:07:56.677177: Epoch time: 18.17 s +2024-11-21 21:07:57.645886: +2024-11-21 21:07:57.646091: Epoch 1922 +2024-11-21 21:07:57.646202: Current learning rate: 0.00781 +2024-11-21 21:08:16.129671: train_loss -0.7703 +2024-11-21 21:08:16.129919: val_loss -0.7234 +2024-11-21 21:08:16.130001: Pseudo dice [0.8426] +2024-11-21 21:08:16.130083: Epoch time: 18.48 s +2024-11-21 21:08:17.088774: +2024-11-21 21:08:17.088986: Epoch 1923 +2024-11-21 21:08:17.089104: Current learning rate: 0.00781 +2024-11-21 21:08:35.544537: train_loss -0.7753 +2024-11-21 21:08:35.544751: val_loss -0.7029 +2024-11-21 21:08:35.544827: Pseudo dice [0.8339] +2024-11-21 21:08:35.544905: Epoch time: 18.46 s +2024-11-21 21:08:36.394383: +2024-11-21 21:08:36.394600: Epoch 1924 +2024-11-21 21:08:36.394717: Current learning rate: 0.00781 +2024-11-21 21:08:54.005442: train_loss -0.7824 +2024-11-21 21:08:54.005654: val_loss -0.7401 +2024-11-21 21:08:54.005727: Pseudo dice [0.8503] +2024-11-21 21:08:54.005805: Epoch time: 17.61 s +2024-11-21 21:08:54.861020: +2024-11-21 21:08:54.861232: Epoch 1925 +2024-11-21 21:08:54.861347: Current learning rate: 0.00781 +2024-11-21 21:09:14.086066: train_loss -0.7832 +2024-11-21 21:09:14.086318: val_loss -0.7381 +2024-11-21 21:09:14.086393: Pseudo dice [0.8432] +2024-11-21 21:09:14.086475: Epoch time: 19.23 s +2024-11-21 21:09:14.940267: +2024-11-21 21:09:14.940489: Epoch 1926 +2024-11-21 21:09:14.940602: Current learning rate: 0.0078 +2024-11-21 21:09:34.860908: train_loss -0.7672 +2024-11-21 21:09:34.861124: val_loss -0.7626 +2024-11-21 21:09:34.861199: Pseudo dice [0.845] +2024-11-21 21:09:34.861275: Epoch time: 19.92 s +2024-11-21 21:09:35.711682: +2024-11-21 21:09:35.711909: Epoch 1927 +2024-11-21 21:09:35.712026: Current learning rate: 0.0078 +2024-11-21 21:09:53.061398: train_loss -0.7722 +2024-11-21 21:09:53.061625: val_loss -0.7279 +2024-11-21 21:09:53.061701: Pseudo dice [0.831] +2024-11-21 21:09:53.061776: Epoch time: 17.35 s +2024-11-21 21:09:53.921822: +2024-11-21 21:09:53.922026: Epoch 1928 +2024-11-21 21:09:53.922136: Current learning rate: 0.0078 +2024-11-21 21:10:12.894851: train_loss -0.7762 +2024-11-21 21:10:12.895100: val_loss -0.7494 +2024-11-21 21:10:12.895187: Pseudo dice [0.8635] +2024-11-21 21:10:12.895270: Epoch time: 18.97 s +2024-11-21 21:10:13.754580: +2024-11-21 21:10:13.754791: Epoch 1929 +2024-11-21 21:10:13.754903: Current learning rate: 0.0078 +2024-11-21 21:10:32.227354: train_loss -0.7806 +2024-11-21 21:10:32.227572: val_loss -0.758 +2024-11-21 21:10:32.227682: Pseudo dice [0.8416] +2024-11-21 21:10:32.227800: Epoch time: 18.47 s +2024-11-21 21:10:33.085607: +2024-11-21 21:10:33.085838: Epoch 1930 +2024-11-21 21:10:33.085948: Current learning rate: 0.0078 +2024-11-21 21:10:52.523478: train_loss -0.772 +2024-11-21 21:10:52.523700: val_loss -0.695 +2024-11-21 21:10:52.523774: Pseudo dice [0.8244] +2024-11-21 21:10:52.523851: Epoch time: 19.44 s +2024-11-21 21:10:53.429711: +2024-11-21 21:10:53.429919: Epoch 1931 +2024-11-21 21:10:53.430036: Current learning rate: 0.0078 +2024-11-21 21:11:12.218129: train_loss -0.7628 +2024-11-21 21:11:12.218355: val_loss -0.725 +2024-11-21 21:11:12.218431: Pseudo dice [0.8482] +2024-11-21 21:11:12.218508: Epoch time: 18.79 s +2024-11-21 21:11:13.079252: +2024-11-21 21:11:13.079458: Epoch 1932 +2024-11-21 21:11:13.079571: Current learning rate: 0.0078 +2024-11-21 21:11:30.516964: train_loss -0.7704 +2024-11-21 21:11:30.517213: val_loss -0.723 +2024-11-21 21:11:30.517291: Pseudo dice [0.8319] +2024-11-21 21:11:30.517376: Epoch time: 17.44 s +2024-11-21 21:11:31.376283: +2024-11-21 21:11:31.376489: Epoch 1933 +2024-11-21 21:11:31.376602: Current learning rate: 0.0078 +2024-11-21 21:11:49.273126: train_loss -0.7772 +2024-11-21 21:11:49.278507: val_loss -0.7342 +2024-11-21 21:11:49.278598: Pseudo dice [0.8229] +2024-11-21 21:11:49.278685: Epoch time: 17.9 s +2024-11-21 21:11:50.150603: +2024-11-21 21:11:50.150886: Epoch 1934 +2024-11-21 21:11:50.151002: Current learning rate: 0.0078 +2024-11-21 21:12:09.667059: train_loss -0.761 +2024-11-21 21:12:09.667288: val_loss -0.7463 +2024-11-21 21:12:09.667568: Pseudo dice [0.8417] +2024-11-21 21:12:09.667651: Epoch time: 19.52 s +2024-11-21 21:12:10.693770: +2024-11-21 21:12:10.694003: Epoch 1935 +2024-11-21 21:12:10.694120: Current learning rate: 0.00779 +2024-11-21 21:12:29.014321: train_loss -0.7627 +2024-11-21 21:12:29.014534: val_loss -0.7064 +2024-11-21 21:12:29.014610: Pseudo dice [0.8327] +2024-11-21 21:12:29.014693: Epoch time: 18.32 s +2024-11-21 21:12:30.226879: +2024-11-21 21:12:30.227097: Epoch 1936 +2024-11-21 21:12:30.227209: Current learning rate: 0.00779 +2024-11-21 21:12:48.894215: train_loss -0.7735 +2024-11-21 21:12:48.894476: val_loss -0.7543 +2024-11-21 21:12:48.894549: Pseudo dice [0.8393] +2024-11-21 21:12:48.894630: Epoch time: 18.67 s +2024-11-21 21:12:49.750047: +2024-11-21 21:12:49.750287: Epoch 1937 +2024-11-21 21:12:49.750403: Current learning rate: 0.00779 +2024-11-21 21:13:08.312109: train_loss -0.7755 +2024-11-21 21:13:08.312326: val_loss -0.7315 +2024-11-21 21:13:08.312407: Pseudo dice [0.8182] +2024-11-21 21:13:08.312487: Epoch time: 18.56 s +2024-11-21 21:13:09.172748: +2024-11-21 21:13:09.172975: Epoch 1938 +2024-11-21 21:13:09.173094: Current learning rate: 0.00779 +2024-11-21 21:13:27.311419: train_loss -0.7654 +2024-11-21 21:13:27.311627: val_loss -0.7479 +2024-11-21 21:13:27.311702: Pseudo dice [0.8097] +2024-11-21 21:13:27.311777: Epoch time: 18.14 s +2024-11-21 21:13:28.169470: +2024-11-21 21:13:28.169672: Epoch 1939 +2024-11-21 21:13:28.169781: Current learning rate: 0.00779 +2024-11-21 21:13:46.804842: train_loss -0.779 +2024-11-21 21:13:46.805111: val_loss -0.7553 +2024-11-21 21:13:46.805192: Pseudo dice [0.8225] +2024-11-21 21:13:46.805275: Epoch time: 18.64 s +2024-11-21 21:13:47.670163: +2024-11-21 21:13:47.670467: Epoch 1940 +2024-11-21 21:13:47.670580: Current learning rate: 0.00779 +2024-11-21 21:14:06.491407: train_loss -0.7698 +2024-11-21 21:14:06.491644: val_loss -0.7459 +2024-11-21 21:14:06.491721: Pseudo dice [0.8342] +2024-11-21 21:14:06.491798: Epoch time: 18.82 s +2024-11-21 21:14:07.415751: +2024-11-21 21:14:07.415974: Epoch 1941 +2024-11-21 21:14:07.416092: Current learning rate: 0.00779 +2024-11-21 21:14:26.443998: train_loss -0.7767 +2024-11-21 21:14:26.444217: val_loss -0.7485 +2024-11-21 21:14:26.444293: Pseudo dice [0.8516] +2024-11-21 21:14:26.444369: Epoch time: 19.03 s +2024-11-21 21:14:27.309526: +2024-11-21 21:14:27.309719: Epoch 1942 +2024-11-21 21:14:27.309830: Current learning rate: 0.00779 +2024-11-21 21:14:46.509726: train_loss -0.7757 +2024-11-21 21:14:46.509953: val_loss -0.7502 +2024-11-21 21:14:46.512254: Pseudo dice [0.8259] +2024-11-21 21:14:46.512337: Epoch time: 19.2 s +2024-11-21 21:14:47.442594: +2024-11-21 21:14:47.442789: Epoch 1943 +2024-11-21 21:14:47.442904: Current learning rate: 0.00778 +2024-11-21 21:15:06.683640: train_loss -0.7613 +2024-11-21 21:15:06.683861: val_loss -0.7228 +2024-11-21 21:15:06.683936: Pseudo dice [0.8277] +2024-11-21 21:15:06.684025: Epoch time: 19.24 s +2024-11-21 21:15:07.543082: +2024-11-21 21:15:07.543288: Epoch 1944 +2024-11-21 21:15:07.543405: Current learning rate: 0.00778 +2024-11-21 21:15:25.482004: train_loss -0.7695 +2024-11-21 21:15:25.482251: val_loss -0.7461 +2024-11-21 21:15:25.482329: Pseudo dice [0.8411] +2024-11-21 21:15:25.482410: Epoch time: 17.94 s +2024-11-21 21:15:26.333405: +2024-11-21 21:15:26.333836: Epoch 1945 +2024-11-21 21:15:26.333974: Current learning rate: 0.00778 +2024-11-21 21:15:43.953625: train_loss -0.7739 +2024-11-21 21:15:43.953838: val_loss -0.7325 +2024-11-21 21:15:43.953916: Pseudo dice [0.8193] +2024-11-21 21:15:43.953999: Epoch time: 17.62 s +2024-11-21 21:15:44.810198: +2024-11-21 21:15:44.810404: Epoch 1946 +2024-11-21 21:15:44.810516: Current learning rate: 0.00778 +2024-11-21 21:16:03.992304: train_loss -0.7624 +2024-11-21 21:16:03.992534: val_loss -0.7156 +2024-11-21 21:16:03.992612: Pseudo dice [0.8277] +2024-11-21 21:16:03.992692: Epoch time: 19.18 s +2024-11-21 21:16:04.850400: +2024-11-21 21:16:04.850668: Epoch 1947 +2024-11-21 21:16:04.850785: Current learning rate: 0.00778 +2024-11-21 21:16:23.716748: train_loss -0.7575 +2024-11-21 21:16:23.717002: val_loss -0.7218 +2024-11-21 21:16:23.717079: Pseudo dice [0.8155] +2024-11-21 21:16:23.717160: Epoch time: 18.87 s +2024-11-21 21:16:24.969508: +2024-11-21 21:16:24.969744: Epoch 1948 +2024-11-21 21:16:24.969860: Current learning rate: 0.00778 +2024-11-21 21:16:44.910138: train_loss -0.7502 +2024-11-21 21:16:44.910350: val_loss -0.7442 +2024-11-21 21:16:44.910429: Pseudo dice [0.8571] +2024-11-21 21:16:44.910549: Epoch time: 19.94 s +2024-11-21 21:16:45.765858: +2024-11-21 21:16:45.766184: Epoch 1949 +2024-11-21 21:16:45.766294: Current learning rate: 0.00778 +2024-11-21 21:17:04.227550: train_loss -0.7658 +2024-11-21 21:17:04.227765: val_loss -0.7244 +2024-11-21 21:17:04.227844: Pseudo dice [0.8487] +2024-11-21 21:17:04.227921: Epoch time: 18.46 s +2024-11-21 21:17:05.308646: +2024-11-21 21:17:05.308865: Epoch 1950 +2024-11-21 21:17:05.308979: Current learning rate: 0.00778 +2024-11-21 21:17:25.054316: train_loss -0.7733 +2024-11-21 21:17:25.054568: val_loss -0.7337 +2024-11-21 21:17:25.054645: Pseudo dice [0.8306] +2024-11-21 21:17:25.054727: Epoch time: 19.75 s +2024-11-21 21:17:25.916883: +2024-11-21 21:17:25.917141: Epoch 1951 +2024-11-21 21:17:25.917253: Current learning rate: 0.00778 +2024-11-21 21:17:44.661798: train_loss -0.7736 +2024-11-21 21:17:44.662026: val_loss -0.7339 +2024-11-21 21:17:44.662098: Pseudo dice [0.8247] +2024-11-21 21:17:44.662176: Epoch time: 18.75 s +2024-11-21 21:17:45.516031: +2024-11-21 21:17:45.516260: Epoch 1952 +2024-11-21 21:17:45.516381: Current learning rate: 0.00777 +2024-11-21 21:18:03.720077: train_loss -0.782 +2024-11-21 21:18:03.720296: val_loss -0.764 +2024-11-21 21:18:03.720371: Pseudo dice [0.8341] +2024-11-21 21:18:03.720446: Epoch time: 18.2 s +2024-11-21 21:18:04.574939: +2024-11-21 21:18:04.575156: Epoch 1953 +2024-11-21 21:18:04.575271: Current learning rate: 0.00777 +2024-11-21 21:18:22.223709: train_loss -0.7747 +2024-11-21 21:18:22.223955: val_loss -0.7471 +2024-11-21 21:18:22.224048: Pseudo dice [0.8514] +2024-11-21 21:18:22.224172: Epoch time: 17.65 s +2024-11-21 21:18:23.082336: +2024-11-21 21:18:23.082572: Epoch 1954 +2024-11-21 21:18:23.082700: Current learning rate: 0.00777 +2024-11-21 21:18:41.241819: train_loss -0.7812 +2024-11-21 21:18:41.242075: val_loss -0.7399 +2024-11-21 21:18:41.242151: Pseudo dice [0.8375] +2024-11-21 21:18:41.242235: Epoch time: 18.16 s +2024-11-21 21:18:42.101276: +2024-11-21 21:18:42.101482: Epoch 1955 +2024-11-21 21:18:42.101595: Current learning rate: 0.00777 +2024-11-21 21:19:01.050659: train_loss -0.7754 +2024-11-21 21:19:01.050872: val_loss -0.7537 +2024-11-21 21:19:01.050949: Pseudo dice [0.8226] +2024-11-21 21:19:01.051032: Epoch time: 18.95 s +2024-11-21 21:19:01.907891: +2024-11-21 21:19:01.908177: Epoch 1956 +2024-11-21 21:19:01.908289: Current learning rate: 0.00777 +2024-11-21 21:19:19.111325: train_loss -0.7753 +2024-11-21 21:19:19.111546: val_loss -0.7414 +2024-11-21 21:19:19.111619: Pseudo dice [0.8252] +2024-11-21 21:19:19.111695: Epoch time: 17.2 s +2024-11-21 21:19:20.019845: +2024-11-21 21:19:20.020061: Epoch 1957 +2024-11-21 21:19:20.020174: Current learning rate: 0.00777 +2024-11-21 21:19:37.869564: train_loss -0.7731 +2024-11-21 21:19:37.872030: val_loss -0.7304 +2024-11-21 21:19:37.872120: Pseudo dice [0.8472] +2024-11-21 21:19:37.872207: Epoch time: 17.85 s +2024-11-21 21:19:38.738657: +2024-11-21 21:19:38.738864: Epoch 1958 +2024-11-21 21:19:38.738975: Current learning rate: 0.00777 +2024-11-21 21:19:57.735634: train_loss -0.7722 +2024-11-21 21:19:57.735846: val_loss -0.7152 +2024-11-21 21:19:57.735925: Pseudo dice [0.8459] +2024-11-21 21:19:57.736006: Epoch time: 19.0 s +2024-11-21 21:19:58.953119: +2024-11-21 21:19:58.953374: Epoch 1959 +2024-11-21 21:19:58.953494: Current learning rate: 0.00777 +2024-11-21 21:20:18.940581: train_loss -0.7756 +2024-11-21 21:20:18.940804: val_loss -0.7469 +2024-11-21 21:20:18.940876: Pseudo dice [0.8402] +2024-11-21 21:20:18.940954: Epoch time: 19.99 s +2024-11-21 21:20:19.793080: +2024-11-21 21:20:19.793314: Epoch 1960 +2024-11-21 21:20:19.793426: Current learning rate: 0.00777 +2024-11-21 21:20:38.668586: train_loss -0.7792 +2024-11-21 21:20:38.669172: val_loss -0.719 +2024-11-21 21:20:38.669268: Pseudo dice [0.8575] +2024-11-21 21:20:38.669350: Epoch time: 18.88 s +2024-11-21 21:20:39.522041: +2024-11-21 21:20:39.522263: Epoch 1961 +2024-11-21 21:20:39.522374: Current learning rate: 0.00776 +2024-11-21 21:20:57.642568: train_loss -0.7773 +2024-11-21 21:20:57.642795: val_loss -0.7512 +2024-11-21 21:20:57.642873: Pseudo dice [0.8389] +2024-11-21 21:20:57.642951: Epoch time: 18.12 s +2024-11-21 21:20:58.535946: +2024-11-21 21:20:58.536152: Epoch 1962 +2024-11-21 21:20:58.536260: Current learning rate: 0.00776 +2024-11-21 21:21:17.689277: train_loss -0.7774 +2024-11-21 21:21:17.689500: val_loss -0.7435 +2024-11-21 21:21:17.689578: Pseudo dice [0.8656] +2024-11-21 21:21:17.689657: Epoch time: 19.15 s +2024-11-21 21:21:18.546555: +2024-11-21 21:21:18.546784: Epoch 1963 +2024-11-21 21:21:18.546905: Current learning rate: 0.00776 +2024-11-21 21:21:37.863120: train_loss -0.7688 +2024-11-21 21:21:37.863357: val_loss -0.7482 +2024-11-21 21:21:37.863441: Pseudo dice [0.8508] +2024-11-21 21:21:37.863523: Epoch time: 19.32 s +2024-11-21 21:21:38.749669: +2024-11-21 21:21:38.749884: Epoch 1964 +2024-11-21 21:21:38.750012: Current learning rate: 0.00776 +2024-11-21 21:21:58.851382: train_loss -0.7646 +2024-11-21 21:21:58.851686: val_loss -0.7058 +2024-11-21 21:21:58.851799: Pseudo dice [0.7989] +2024-11-21 21:21:58.851889: Epoch time: 20.1 s +2024-11-21 21:21:59.711679: +2024-11-21 21:21:59.711880: Epoch 1965 +2024-11-21 21:21:59.711999: Current learning rate: 0.00776 +2024-11-21 21:22:19.027655: train_loss -0.768 +2024-11-21 21:22:19.027909: val_loss -0.7688 +2024-11-21 21:22:19.027986: Pseudo dice [0.8482] +2024-11-21 21:22:19.028067: Epoch time: 19.32 s +2024-11-21 21:22:19.903277: +2024-11-21 21:22:19.903473: Epoch 1966 +2024-11-21 21:22:19.903584: Current learning rate: 0.00776 +2024-11-21 21:22:37.971847: train_loss -0.7757 +2024-11-21 21:22:37.972068: val_loss -0.7611 +2024-11-21 21:22:37.972156: Pseudo dice [0.8453] +2024-11-21 21:22:37.972231: Epoch time: 18.07 s +2024-11-21 21:22:38.848342: +2024-11-21 21:22:38.848559: Epoch 1967 +2024-11-21 21:22:38.848674: Current learning rate: 0.00776 +2024-11-21 21:22:57.782370: train_loss -0.7662 +2024-11-21 21:22:57.787744: val_loss -0.7216 +2024-11-21 21:22:57.787894: Pseudo dice [0.8227] +2024-11-21 21:22:57.787974: Epoch time: 18.93 s +2024-11-21 21:22:58.672134: +2024-11-21 21:22:58.672340: Epoch 1968 +2024-11-21 21:22:58.672454: Current learning rate: 0.00776 +2024-11-21 21:23:17.303040: train_loss -0.7697 +2024-11-21 21:23:17.303280: val_loss -0.7201 +2024-11-21 21:23:17.303354: Pseudo dice [0.8306] +2024-11-21 21:23:17.303439: Epoch time: 18.63 s +2024-11-21 21:23:18.164996: +2024-11-21 21:23:18.165483: Epoch 1969 +2024-11-21 21:23:18.165602: Current learning rate: 0.00775 +2024-11-21 21:23:37.330264: train_loss -0.7612 +2024-11-21 21:23:37.330484: val_loss -0.7377 +2024-11-21 21:23:37.330560: Pseudo dice [0.833] +2024-11-21 21:23:37.330636: Epoch time: 19.17 s +2024-11-21 21:23:38.589463: +2024-11-21 21:23:38.589681: Epoch 1970 +2024-11-21 21:23:38.589797: Current learning rate: 0.00775 +2024-11-21 21:23:57.627432: train_loss -0.7716 +2024-11-21 21:23:57.627666: val_loss -0.7152 +2024-11-21 21:23:57.627742: Pseudo dice [0.8289] +2024-11-21 21:23:57.627820: Epoch time: 19.04 s +2024-11-21 21:23:58.487021: +2024-11-21 21:23:58.487334: Epoch 1971 +2024-11-21 21:23:58.487451: Current learning rate: 0.00775 +2024-11-21 21:24:16.115052: train_loss -0.7762 +2024-11-21 21:24:16.115350: val_loss -0.7309 +2024-11-21 21:24:16.115426: Pseudo dice [0.8097] +2024-11-21 21:24:16.115511: Epoch time: 17.63 s +2024-11-21 21:24:16.986240: +2024-11-21 21:24:16.986498: Epoch 1972 +2024-11-21 21:24:16.986625: Current learning rate: 0.00775 +2024-11-21 21:24:36.286538: train_loss -0.7741 +2024-11-21 21:24:36.286761: val_loss -0.7329 +2024-11-21 21:24:36.286836: Pseudo dice [0.8349] +2024-11-21 21:24:36.286911: Epoch time: 19.3 s +2024-11-21 21:24:37.146036: +2024-11-21 21:24:37.146376: Epoch 1973 +2024-11-21 21:24:37.146496: Current learning rate: 0.00775 +2024-11-21 21:24:56.313323: train_loss -0.764 +2024-11-21 21:24:56.313550: val_loss -0.7268 +2024-11-21 21:24:56.313629: Pseudo dice [0.8522] +2024-11-21 21:24:56.313713: Epoch time: 19.17 s +2024-11-21 21:24:57.172214: +2024-11-21 21:24:57.172427: Epoch 1974 +2024-11-21 21:24:57.172548: Current learning rate: 0.00775 +2024-11-21 21:25:16.530322: train_loss -0.768 +2024-11-21 21:25:16.530549: val_loss -0.7194 +2024-11-21 21:25:16.530623: Pseudo dice [0.8244] +2024-11-21 21:25:16.530702: Epoch time: 19.36 s +2024-11-21 21:25:17.392399: +2024-11-21 21:25:17.392632: Epoch 1975 +2024-11-21 21:25:17.392754: Current learning rate: 0.00775 +2024-11-21 21:25:36.083907: train_loss -0.7797 +2024-11-21 21:25:36.084225: val_loss -0.738 +2024-11-21 21:25:36.084299: Pseudo dice [0.8368] +2024-11-21 21:25:36.084387: Epoch time: 18.69 s +2024-11-21 21:25:36.942786: +2024-11-21 21:25:36.942984: Epoch 1976 +2024-11-21 21:25:36.943103: Current learning rate: 0.00775 +2024-11-21 21:25:55.310506: train_loss -0.7728 +2024-11-21 21:25:55.310726: val_loss -0.7264 +2024-11-21 21:25:55.310800: Pseudo dice [0.8268] +2024-11-21 21:25:55.310879: Epoch time: 18.37 s +2024-11-21 21:25:56.177233: +2024-11-21 21:25:56.177424: Epoch 1977 +2024-11-21 21:25:56.177535: Current learning rate: 0.00775 +2024-11-21 21:26:14.074881: train_loss -0.7696 +2024-11-21 21:26:14.075112: val_loss -0.7413 +2024-11-21 21:26:14.077425: Pseudo dice [0.8532] +2024-11-21 21:26:14.077528: Epoch time: 17.9 s +2024-11-21 21:26:14.962746: +2024-11-21 21:26:14.962941: Epoch 1978 +2024-11-21 21:26:14.963063: Current learning rate: 0.00774 +2024-11-21 21:26:33.208219: train_loss -0.7669 +2024-11-21 21:26:33.208437: val_loss -0.7465 +2024-11-21 21:26:33.208513: Pseudo dice [0.8469] +2024-11-21 21:26:33.208592: Epoch time: 18.25 s +2024-11-21 21:26:34.071099: +2024-11-21 21:26:34.071302: Epoch 1979 +2024-11-21 21:26:34.071412: Current learning rate: 0.00774 +2024-11-21 21:26:54.153018: train_loss -0.7786 +2024-11-21 21:26:54.155502: val_loss -0.7528 +2024-11-21 21:26:54.155598: Pseudo dice [0.8337] +2024-11-21 21:26:54.155680: Epoch time: 20.08 s +2024-11-21 21:26:55.062132: +2024-11-21 21:26:55.062369: Epoch 1980 +2024-11-21 21:26:55.062488: Current learning rate: 0.00774 +2024-11-21 21:27:13.838502: train_loss -0.7695 +2024-11-21 21:27:13.838717: val_loss -0.728 +2024-11-21 21:27:13.838793: Pseudo dice [0.8406] +2024-11-21 21:27:13.838872: Epoch time: 18.78 s +2024-11-21 21:27:15.146962: +2024-11-21 21:27:15.147184: Epoch 1981 +2024-11-21 21:27:15.147300: Current learning rate: 0.00774 +2024-11-21 21:27:34.582580: train_loss -0.7661 +2024-11-21 21:27:34.582797: val_loss -0.7419 +2024-11-21 21:27:34.582871: Pseudo dice [0.8639] +2024-11-21 21:27:34.582951: Epoch time: 19.44 s +2024-11-21 21:27:35.594504: +2024-11-21 21:27:35.594736: Epoch 1982 +2024-11-21 21:27:35.594848: Current learning rate: 0.00774 +2024-11-21 21:27:53.768232: train_loss -0.7743 +2024-11-21 21:27:53.768477: val_loss -0.6946 +2024-11-21 21:27:53.768560: Pseudo dice [0.8319] +2024-11-21 21:27:53.768649: Epoch time: 18.17 s +2024-11-21 21:27:54.623476: +2024-11-21 21:27:54.623776: Epoch 1983 +2024-11-21 21:27:54.623888: Current learning rate: 0.00774 +2024-11-21 21:28:13.488910: train_loss -0.7792 +2024-11-21 21:28:13.489137: val_loss -0.7401 +2024-11-21 21:28:13.489210: Pseudo dice [0.8288] +2024-11-21 21:28:13.489286: Epoch time: 18.87 s +2024-11-21 21:28:14.348816: +2024-11-21 21:28:14.349138: Epoch 1984 +2024-11-21 21:28:14.349251: Current learning rate: 0.00774 +2024-11-21 21:28:33.929451: train_loss -0.7787 +2024-11-21 21:28:33.929672: val_loss -0.7378 +2024-11-21 21:28:33.929744: Pseudo dice [0.8493] +2024-11-21 21:28:33.929821: Epoch time: 19.58 s +2024-11-21 21:28:34.813310: +2024-11-21 21:28:34.813529: Epoch 1985 +2024-11-21 21:28:34.813646: Current learning rate: 0.00774 +2024-11-21 21:28:53.665135: train_loss -0.7754 +2024-11-21 21:28:53.665351: val_loss -0.7258 +2024-11-21 21:28:53.665424: Pseudo dice [0.8382] +2024-11-21 21:28:53.665500: Epoch time: 18.85 s +2024-11-21 21:28:54.521716: +2024-11-21 21:28:54.521916: Epoch 1986 +2024-11-21 21:28:54.522033: Current learning rate: 0.00774 +2024-11-21 21:29:13.308035: train_loss -0.7734 +2024-11-21 21:29:13.308640: val_loss -0.7219 +2024-11-21 21:29:13.308726: Pseudo dice [0.8416] +2024-11-21 21:29:13.308811: Epoch time: 18.79 s +2024-11-21 21:29:14.168320: +2024-11-21 21:29:14.168536: Epoch 1987 +2024-11-21 21:29:14.168652: Current learning rate: 0.00773 +2024-11-21 21:29:32.300511: train_loss -0.7646 +2024-11-21 21:29:32.300724: val_loss -0.7451 +2024-11-21 21:29:32.303034: Pseudo dice [0.8331] +2024-11-21 21:29:32.303131: Epoch time: 18.13 s +2024-11-21 21:29:33.184770: +2024-11-21 21:29:33.185001: Epoch 1988 +2024-11-21 21:29:33.185122: Current learning rate: 0.00773 +2024-11-21 21:29:53.186294: train_loss -0.7768 +2024-11-21 21:29:53.186520: val_loss -0.7487 +2024-11-21 21:29:53.186602: Pseudo dice [0.8303] +2024-11-21 21:29:53.186678: Epoch time: 20.0 s +2024-11-21 21:29:54.065150: +2024-11-21 21:29:54.065433: Epoch 1989 +2024-11-21 21:29:54.065545: Current learning rate: 0.00773 +2024-11-21 21:30:11.336218: train_loss -0.765 +2024-11-21 21:30:11.336444: val_loss -0.7449 +2024-11-21 21:30:11.336521: Pseudo dice [0.8293] +2024-11-21 21:30:11.336603: Epoch time: 17.27 s +2024-11-21 21:30:12.198301: +2024-11-21 21:30:12.198504: Epoch 1990 +2024-11-21 21:30:12.198621: Current learning rate: 0.00773 +2024-11-21 21:30:30.259078: train_loss -0.7744 +2024-11-21 21:30:30.259325: val_loss -0.7495 +2024-11-21 21:30:30.259404: Pseudo dice [0.8494] +2024-11-21 21:30:30.259492: Epoch time: 18.06 s +2024-11-21 21:30:31.115331: +2024-11-21 21:30:31.115554: Epoch 1991 +2024-11-21 21:30:31.115672: Current learning rate: 0.00773 +2024-11-21 21:30:50.206131: train_loss -0.7743 +2024-11-21 21:30:50.206340: val_loss -0.7464 +2024-11-21 21:30:50.206415: Pseudo dice [0.8562] +2024-11-21 21:30:50.206491: Epoch time: 19.09 s +2024-11-21 21:30:51.476195: +2024-11-21 21:30:51.476430: Epoch 1992 +2024-11-21 21:30:51.476545: Current learning rate: 0.00773 +2024-11-21 21:31:09.549371: train_loss -0.7801 +2024-11-21 21:31:09.549610: val_loss -0.7299 +2024-11-21 21:31:09.549687: Pseudo dice [0.8311] +2024-11-21 21:31:09.549764: Epoch time: 18.07 s +2024-11-21 21:31:10.565306: +2024-11-21 21:31:10.565511: Epoch 1993 +2024-11-21 21:31:10.565622: Current learning rate: 0.00773 +2024-11-21 21:31:29.517494: train_loss -0.7887 +2024-11-21 21:31:29.517791: val_loss -0.7301 +2024-11-21 21:31:29.517871: Pseudo dice [0.8268] +2024-11-21 21:31:29.517958: Epoch time: 18.95 s +2024-11-21 21:31:30.407834: +2024-11-21 21:31:30.408056: Epoch 1994 +2024-11-21 21:31:30.408165: Current learning rate: 0.00773 +2024-11-21 21:31:49.740099: train_loss -0.7769 +2024-11-21 21:31:49.740319: val_loss -0.7175 +2024-11-21 21:31:49.740396: Pseudo dice [0.8415] +2024-11-21 21:31:49.740473: Epoch time: 19.33 s +2024-11-21 21:31:50.607031: +2024-11-21 21:31:50.607285: Epoch 1995 +2024-11-21 21:31:50.607400: Current learning rate: 0.00772 +2024-11-21 21:32:08.797694: train_loss -0.7704 +2024-11-21 21:32:08.797948: val_loss -0.7541 +2024-11-21 21:32:08.798038: Pseudo dice [0.8311] +2024-11-21 21:32:08.798113: Epoch time: 18.19 s +2024-11-21 21:32:09.655802: +2024-11-21 21:32:09.656019: Epoch 1996 +2024-11-21 21:32:09.656134: Current learning rate: 0.00772 +2024-11-21 21:32:27.243257: train_loss -0.7809 +2024-11-21 21:32:27.243483: val_loss -0.7695 +2024-11-21 21:32:27.245731: Pseudo dice [0.8509] +2024-11-21 21:32:27.245831: Epoch time: 17.59 s +2024-11-21 21:32:28.261392: +2024-11-21 21:32:28.261684: Epoch 1997 +2024-11-21 21:32:28.261797: Current learning rate: 0.00772 +2024-11-21 21:32:47.615115: train_loss -0.7767 +2024-11-21 21:32:47.615388: val_loss -0.7575 +2024-11-21 21:32:47.615467: Pseudo dice [0.8596] +2024-11-21 21:32:47.615549: Epoch time: 19.35 s +2024-11-21 21:32:48.479281: +2024-11-21 21:32:48.479486: Epoch 1998 +2024-11-21 21:32:48.479597: Current learning rate: 0.00772 +2024-11-21 21:33:07.724381: train_loss -0.7781 +2024-11-21 21:33:07.724605: val_loss -0.745 +2024-11-21 21:33:07.724681: Pseudo dice [0.8657] +2024-11-21 21:33:07.724760: Epoch time: 19.25 s +2024-11-21 21:33:08.582675: +2024-11-21 21:33:08.582883: Epoch 1999 +2024-11-21 21:33:08.583003: Current learning rate: 0.00772 +2024-11-21 21:33:27.689489: train_loss -0.7753 +2024-11-21 21:33:27.689717: val_loss -0.7683 +2024-11-21 21:33:27.689795: Pseudo dice [0.8473] +2024-11-21 21:33:27.695045: Epoch time: 19.11 s +2024-11-21 21:33:28.791263: +2024-11-21 21:33:28.791525: Epoch 2000 +2024-11-21 21:33:28.791641: Current learning rate: 0.00772 +2024-11-21 21:33:47.128082: train_loss -0.7787 +2024-11-21 21:33:47.128308: val_loss -0.7291 +2024-11-21 21:33:47.128386: Pseudo dice [0.8173] +2024-11-21 21:33:47.130379: Epoch time: 18.34 s +2024-11-21 21:33:47.999334: +2024-11-21 21:33:47.999614: Epoch 2001 +2024-11-21 21:33:47.999723: Current learning rate: 0.00772 +2024-11-21 21:34:05.677186: train_loss -0.7668 +2024-11-21 21:34:05.677425: val_loss -0.7224 +2024-11-21 21:34:05.677501: Pseudo dice [0.823] +2024-11-21 21:34:05.677578: Epoch time: 17.68 s +2024-11-21 21:34:06.643536: +2024-11-21 21:34:06.643747: Epoch 2002 +2024-11-21 21:34:06.643855: Current learning rate: 0.00772 +2024-11-21 21:34:26.640940: train_loss -0.7701 +2024-11-21 21:34:26.641167: val_loss -0.7293 +2024-11-21 21:34:26.641244: Pseudo dice [0.7981] +2024-11-21 21:34:26.641320: Epoch time: 20.0 s +2024-11-21 21:34:27.886743: +2024-11-21 21:34:27.886966: Epoch 2003 +2024-11-21 21:34:27.887085: Current learning rate: 0.00772 +2024-11-21 21:34:45.980862: train_loss -0.7833 +2024-11-21 21:34:45.981093: val_loss -0.7492 +2024-11-21 21:34:45.981214: Pseudo dice [0.843] +2024-11-21 21:34:45.981301: Epoch time: 18.09 s +2024-11-21 21:34:46.841084: +2024-11-21 21:34:46.841325: Epoch 2004 +2024-11-21 21:34:46.841474: Current learning rate: 0.00771 +2024-11-21 21:35:06.080323: train_loss -0.7809 +2024-11-21 21:35:06.080630: val_loss -0.7377 +2024-11-21 21:35:06.080712: Pseudo dice [0.84] +2024-11-21 21:35:06.080796: Epoch time: 19.24 s +2024-11-21 21:35:06.953817: +2024-11-21 21:35:06.954062: Epoch 2005 +2024-11-21 21:35:06.954178: Current learning rate: 0.00771 +2024-11-21 21:35:24.638036: train_loss -0.7821 +2024-11-21 21:35:24.638255: val_loss -0.7452 +2024-11-21 21:35:24.638330: Pseudo dice [0.861] +2024-11-21 21:35:24.643642: Epoch time: 17.69 s +2024-11-21 21:35:25.530026: +2024-11-21 21:35:25.530262: Epoch 2006 +2024-11-21 21:35:25.530373: Current learning rate: 0.00771 +2024-11-21 21:35:45.084144: train_loss -0.7784 +2024-11-21 21:35:45.084365: val_loss -0.7475 +2024-11-21 21:35:45.084438: Pseudo dice [0.8365] +2024-11-21 21:35:45.084516: Epoch time: 19.55 s +2024-11-21 21:35:45.940819: +2024-11-21 21:35:45.941083: Epoch 2007 +2024-11-21 21:35:45.941203: Current learning rate: 0.00771 +2024-11-21 21:36:04.593584: train_loss -0.7749 +2024-11-21 21:36:04.593824: val_loss -0.7296 +2024-11-21 21:36:04.593899: Pseudo dice [0.8275] +2024-11-21 21:36:04.593981: Epoch time: 18.65 s +2024-11-21 21:36:05.634357: +2024-11-21 21:36:05.634558: Epoch 2008 +2024-11-21 21:36:05.634670: Current learning rate: 0.00771 +2024-11-21 21:36:24.263164: train_loss -0.7722 +2024-11-21 21:36:24.263418: val_loss -0.7418 +2024-11-21 21:36:24.263502: Pseudo dice [0.8404] +2024-11-21 21:36:24.263588: Epoch time: 18.63 s +2024-11-21 21:36:25.135730: +2024-11-21 21:36:25.135951: Epoch 2009 +2024-11-21 21:36:25.136066: Current learning rate: 0.00771 +2024-11-21 21:36:44.667425: train_loss -0.7797 +2024-11-21 21:36:44.667647: val_loss -0.7554 +2024-11-21 21:36:44.667725: Pseudo dice [0.8138] +2024-11-21 21:36:44.667804: Epoch time: 19.53 s +2024-11-21 21:36:45.523097: +2024-11-21 21:36:45.523288: Epoch 2010 +2024-11-21 21:36:45.523405: Current learning rate: 0.00771 +2024-11-21 21:37:03.101113: train_loss -0.7616 +2024-11-21 21:37:03.101342: val_loss -0.7282 +2024-11-21 21:37:03.101416: Pseudo dice [0.8183] +2024-11-21 21:37:03.101496: Epoch time: 17.58 s +2024-11-21 21:37:03.960637: +2024-11-21 21:37:03.960848: Epoch 2011 +2024-11-21 21:37:03.960965: Current learning rate: 0.00771 +2024-11-21 21:37:22.313510: train_loss -0.7584 +2024-11-21 21:37:22.313745: val_loss -0.7605 +2024-11-21 21:37:22.313825: Pseudo dice [0.8376] +2024-11-21 21:37:22.315770: Epoch time: 18.35 s +2024-11-21 21:37:23.175831: +2024-11-21 21:37:23.176063: Epoch 2012 +2024-11-21 21:37:23.176188: Current learning rate: 0.0077 +2024-11-21 21:37:42.567211: train_loss -0.7634 +2024-11-21 21:37:42.567453: val_loss -0.7417 +2024-11-21 21:37:42.567527: Pseudo dice [0.8317] +2024-11-21 21:37:42.567606: Epoch time: 19.39 s +2024-11-21 21:37:43.439546: +2024-11-21 21:37:43.439769: Epoch 2013 +2024-11-21 21:37:43.439882: Current learning rate: 0.0077 +2024-11-21 21:38:03.164758: train_loss -0.7783 +2024-11-21 21:38:03.164972: val_loss -0.7265 +2024-11-21 21:38:03.165057: Pseudo dice [0.8333] +2024-11-21 21:38:03.167496: Epoch time: 19.73 s +2024-11-21 21:38:04.423586: +2024-11-21 21:38:04.423780: Epoch 2014 +2024-11-21 21:38:04.423895: Current learning rate: 0.0077 +2024-11-21 21:38:23.453775: train_loss -0.7803 +2024-11-21 21:38:23.454025: val_loss -0.742 +2024-11-21 21:38:23.454105: Pseudo dice [0.8543] +2024-11-21 21:38:23.454186: Epoch time: 19.03 s +2024-11-21 21:38:24.462927: +2024-11-21 21:38:24.463167: Epoch 2015 +2024-11-21 21:38:24.463285: Current learning rate: 0.0077 +2024-11-21 21:38:42.296905: train_loss -0.7704 +2024-11-21 21:38:42.297156: val_loss -0.7384 +2024-11-21 21:38:42.297232: Pseudo dice [0.8272] +2024-11-21 21:38:42.297315: Epoch time: 17.83 s +2024-11-21 21:38:43.155912: +2024-11-21 21:38:43.156139: Epoch 2016 +2024-11-21 21:38:43.156259: Current learning rate: 0.0077 +2024-11-21 21:39:01.316394: train_loss -0.7771 +2024-11-21 21:39:01.316604: val_loss -0.7446 +2024-11-21 21:39:01.316681: Pseudo dice [0.8452] +2024-11-21 21:39:01.316757: Epoch time: 18.16 s +2024-11-21 21:39:02.173223: +2024-11-21 21:39:02.173443: Epoch 2017 +2024-11-21 21:39:02.173555: Current learning rate: 0.0077 +2024-11-21 21:39:21.107755: train_loss -0.7797 +2024-11-21 21:39:21.107982: val_loss -0.7265 +2024-11-21 21:39:21.108067: Pseudo dice [0.8245] +2024-11-21 21:39:21.108142: Epoch time: 18.94 s +2024-11-21 21:39:21.965056: +2024-11-21 21:39:21.965263: Epoch 2018 +2024-11-21 21:39:21.965376: Current learning rate: 0.0077 +2024-11-21 21:39:40.523525: train_loss -0.7681 +2024-11-21 21:39:40.525939: val_loss -0.7594 +2024-11-21 21:39:40.526035: Pseudo dice [0.871] +2024-11-21 21:39:40.526119: Epoch time: 18.56 s +2024-11-21 21:39:41.552382: +2024-11-21 21:39:41.552612: Epoch 2019 +2024-11-21 21:39:41.552726: Current learning rate: 0.0077 +2024-11-21 21:39:59.923691: train_loss -0.7748 +2024-11-21 21:39:59.923918: val_loss -0.7461 +2024-11-21 21:39:59.923999: Pseudo dice [0.8312] +2024-11-21 21:39:59.924076: Epoch time: 18.37 s +2024-11-21 21:40:00.779583: +2024-11-21 21:40:00.779804: Epoch 2020 +2024-11-21 21:40:00.779920: Current learning rate: 0.0077 +2024-11-21 21:40:20.136547: train_loss -0.7762 +2024-11-21 21:40:20.136769: val_loss -0.7545 +2024-11-21 21:40:20.136843: Pseudo dice [0.8434] +2024-11-21 21:40:20.136919: Epoch time: 19.36 s +2024-11-21 21:40:20.991519: +2024-11-21 21:40:20.991724: Epoch 2021 +2024-11-21 21:40:20.991838: Current learning rate: 0.00769 +2024-11-21 21:40:39.146742: train_loss -0.7792 +2024-11-21 21:40:39.146952: val_loss -0.7554 +2024-11-21 21:40:39.147032: Pseudo dice [0.8363] +2024-11-21 21:40:39.147108: Epoch time: 18.16 s +2024-11-21 21:40:40.031689: +2024-11-21 21:40:40.032000: Epoch 2022 +2024-11-21 21:40:40.032109: Current learning rate: 0.00769 +2024-11-21 21:40:58.498161: train_loss -0.7767 +2024-11-21 21:40:58.498414: val_loss -0.7501 +2024-11-21 21:40:58.498492: Pseudo dice [0.8731] +2024-11-21 21:40:58.498577: Epoch time: 18.47 s +2024-11-21 21:40:59.361102: +2024-11-21 21:40:59.361298: Epoch 2023 +2024-11-21 21:40:59.361413: Current learning rate: 0.00769 +2024-11-21 21:41:18.034608: train_loss -0.7772 +2024-11-21 21:41:18.034859: val_loss -0.7562 +2024-11-21 21:41:18.034939: Pseudo dice [0.8383] +2024-11-21 21:41:18.035034: Epoch time: 18.67 s +2024-11-21 21:41:18.889722: +2024-11-21 21:41:18.889919: Epoch 2024 +2024-11-21 21:41:18.890035: Current learning rate: 0.00769 +2024-11-21 21:41:37.676427: train_loss -0.7815 +2024-11-21 21:41:37.676647: val_loss -0.7421 +2024-11-21 21:41:37.676723: Pseudo dice [0.8438] +2024-11-21 21:41:37.676799: Epoch time: 18.79 s +2024-11-21 21:41:38.528767: +2024-11-21 21:41:38.529059: Epoch 2025 +2024-11-21 21:41:38.529173: Current learning rate: 0.00769 +2024-11-21 21:41:55.911536: train_loss -0.7769 +2024-11-21 21:41:55.911843: val_loss -0.7407 +2024-11-21 21:41:55.911931: Pseudo dice [0.8304] +2024-11-21 21:41:55.912017: Epoch time: 17.38 s +2024-11-21 21:41:56.766312: +2024-11-21 21:41:56.766517: Epoch 2026 +2024-11-21 21:41:56.766628: Current learning rate: 0.00769 +2024-11-21 21:42:14.811663: train_loss -0.7701 +2024-11-21 21:42:14.811925: val_loss -0.7533 +2024-11-21 21:42:14.812012: Pseudo dice [0.8527] +2024-11-21 21:42:14.812095: Epoch time: 18.05 s +2024-11-21 21:42:15.674318: +2024-11-21 21:42:15.674530: Epoch 2027 +2024-11-21 21:42:15.674641: Current learning rate: 0.00769 +2024-11-21 21:42:32.839477: train_loss -0.7742 +2024-11-21 21:42:32.839693: val_loss -0.7329 +2024-11-21 21:42:32.839769: Pseudo dice [0.838] +2024-11-21 21:42:32.839847: Epoch time: 17.17 s +2024-11-21 21:42:33.858657: +2024-11-21 21:42:33.858898: Epoch 2028 +2024-11-21 21:42:33.859020: Current learning rate: 0.00769 +2024-11-21 21:42:51.626257: train_loss -0.7763 +2024-11-21 21:42:51.626476: val_loss -0.7457 +2024-11-21 21:42:51.628760: Pseudo dice [0.8237] +2024-11-21 21:42:51.628861: Epoch time: 17.77 s +2024-11-21 21:42:52.773501: +2024-11-21 21:42:52.773726: Epoch 2029 +2024-11-21 21:42:52.773841: Current learning rate: 0.00769 +2024-11-21 21:43:11.243728: train_loss -0.7741 +2024-11-21 21:43:11.243978: val_loss -0.7493 +2024-11-21 21:43:11.244062: Pseudo dice [0.8444] +2024-11-21 21:43:11.253192: Epoch time: 18.47 s +2024-11-21 21:43:12.115765: +2024-11-21 21:43:12.115997: Epoch 2030 +2024-11-21 21:43:12.116114: Current learning rate: 0.00768 +2024-11-21 21:43:31.307645: train_loss -0.7725 +2024-11-21 21:43:31.307927: val_loss -0.7434 +2024-11-21 21:43:31.308052: Pseudo dice [0.8398] +2024-11-21 21:43:31.308130: Epoch time: 19.19 s +2024-11-21 21:43:32.170378: +2024-11-21 21:43:32.170583: Epoch 2031 +2024-11-21 21:43:32.170699: Current learning rate: 0.00768 +2024-11-21 21:43:52.046187: train_loss -0.7758 +2024-11-21 21:43:52.046401: val_loss -0.7302 +2024-11-21 21:43:52.046475: Pseudo dice [0.8173] +2024-11-21 21:43:52.046551: Epoch time: 19.88 s +2024-11-21 21:43:52.916867: +2024-11-21 21:43:52.917161: Epoch 2032 +2024-11-21 21:43:52.917289: Current learning rate: 0.00768 +2024-11-21 21:44:11.833405: train_loss -0.7744 +2024-11-21 21:44:11.833659: val_loss -0.7565 +2024-11-21 21:44:11.833735: Pseudo dice [0.8467] +2024-11-21 21:44:11.833816: Epoch time: 18.92 s +2024-11-21 21:44:12.786929: +2024-11-21 21:44:12.787139: Epoch 2033 +2024-11-21 21:44:12.787252: Current learning rate: 0.00768 +2024-11-21 21:44:31.312832: train_loss -0.7821 +2024-11-21 21:44:31.313086: val_loss -0.753 +2024-11-21 21:44:31.313159: Pseudo dice [0.852] +2024-11-21 21:44:31.313238: Epoch time: 18.53 s +2024-11-21 21:44:32.170342: +2024-11-21 21:44:32.170578: Epoch 2034 +2024-11-21 21:44:32.170693: Current learning rate: 0.00768 +2024-11-21 21:44:51.957277: train_loss -0.7773 +2024-11-21 21:44:51.957499: val_loss -0.7465 +2024-11-21 21:44:51.957580: Pseudo dice [0.8384] +2024-11-21 21:44:51.957658: Epoch time: 19.79 s +2024-11-21 21:44:52.824715: +2024-11-21 21:44:52.824929: Epoch 2035 +2024-11-21 21:44:52.825050: Current learning rate: 0.00768 +2024-11-21 21:45:11.760507: train_loss -0.7586 +2024-11-21 21:45:11.760726: val_loss -0.7411 +2024-11-21 21:45:11.760801: Pseudo dice [0.8453] +2024-11-21 21:45:11.760882: Epoch time: 18.94 s +2024-11-21 21:45:12.998837: +2024-11-21 21:45:12.999031: Epoch 2036 +2024-11-21 21:45:12.999141: Current learning rate: 0.00768 +2024-11-21 21:45:30.745385: train_loss -0.7758 +2024-11-21 21:45:30.745664: val_loss -0.7501 +2024-11-21 21:45:30.745750: Pseudo dice [0.8191] +2024-11-21 21:45:30.745839: Epoch time: 17.75 s +2024-11-21 21:45:31.890984: +2024-11-21 21:45:31.891210: Epoch 2037 +2024-11-21 21:45:31.891324: Current learning rate: 0.00768 +2024-11-21 21:45:50.160730: train_loss -0.7697 +2024-11-21 21:45:50.160963: val_loss -0.7205 +2024-11-21 21:45:50.161047: Pseudo dice [0.78] +2024-11-21 21:45:50.161125: Epoch time: 18.27 s +2024-11-21 21:45:51.230437: +2024-11-21 21:45:51.230698: Epoch 2038 +2024-11-21 21:45:51.230813: Current learning rate: 0.00767 +2024-11-21 21:46:09.337535: train_loss -0.7743 +2024-11-21 21:46:09.337758: val_loss -0.7143 +2024-11-21 21:46:09.337832: Pseudo dice [0.8147] +2024-11-21 21:46:09.337909: Epoch time: 18.11 s +2024-11-21 21:46:10.197432: +2024-11-21 21:46:10.197639: Epoch 2039 +2024-11-21 21:46:10.197752: Current learning rate: 0.00767 +2024-11-21 21:46:29.296867: train_loss -0.7827 +2024-11-21 21:46:29.297108: val_loss -0.7147 +2024-11-21 21:46:29.297188: Pseudo dice [0.8416] +2024-11-21 21:46:29.297270: Epoch time: 19.1 s +2024-11-21 21:46:30.157346: +2024-11-21 21:46:30.157579: Epoch 2040 +2024-11-21 21:46:30.157692: Current learning rate: 0.00767 +2024-11-21 21:46:47.956801: train_loss -0.7759 +2024-11-21 21:46:47.957054: val_loss -0.7289 +2024-11-21 21:46:47.957130: Pseudo dice [0.8242] +2024-11-21 21:46:47.957211: Epoch time: 17.8 s +2024-11-21 21:46:48.819792: +2024-11-21 21:46:48.819996: Epoch 2041 +2024-11-21 21:46:48.820110: Current learning rate: 0.00767 +2024-11-21 21:47:07.577301: train_loss -0.784 +2024-11-21 21:47:07.577520: val_loss -0.7221 +2024-11-21 21:47:07.577598: Pseudo dice [0.8267] +2024-11-21 21:47:07.577674: Epoch time: 18.76 s +2024-11-21 21:47:08.433943: +2024-11-21 21:47:08.434142: Epoch 2042 +2024-11-21 21:47:08.434255: Current learning rate: 0.00767 +2024-11-21 21:47:27.131995: train_loss -0.7835 +2024-11-21 21:47:27.132207: val_loss -0.7193 +2024-11-21 21:47:27.132284: Pseudo dice [0.8223] +2024-11-21 21:47:27.132360: Epoch time: 18.7 s +2024-11-21 21:47:27.990782: +2024-11-21 21:47:27.991046: Epoch 2043 +2024-11-21 21:47:27.991160: Current learning rate: 0.00767 +2024-11-21 21:47:45.908250: train_loss -0.7769 +2024-11-21 21:47:45.908499: val_loss -0.7448 +2024-11-21 21:47:45.908576: Pseudo dice [0.8324] +2024-11-21 21:47:45.908688: Epoch time: 17.92 s +2024-11-21 21:47:46.771379: +2024-11-21 21:47:46.771587: Epoch 2044 +2024-11-21 21:47:46.771700: Current learning rate: 0.00767 +2024-11-21 21:48:06.178988: train_loss -0.7704 +2024-11-21 21:48:06.179213: val_loss -0.746 +2024-11-21 21:48:06.179287: Pseudo dice [0.8549] +2024-11-21 21:48:06.179364: Epoch time: 19.41 s +2024-11-21 21:48:07.036747: +2024-11-21 21:48:07.036941: Epoch 2045 +2024-11-21 21:48:07.037061: Current learning rate: 0.00767 +2024-11-21 21:48:26.117680: train_loss -0.7782 +2024-11-21 21:48:26.117883: val_loss -0.7495 +2024-11-21 21:48:26.117958: Pseudo dice [0.832] +2024-11-21 21:48:26.118040: Epoch time: 19.08 s +2024-11-21 21:48:26.975888: +2024-11-21 21:48:26.976449: Epoch 2046 +2024-11-21 21:48:26.976586: Current learning rate: 0.00767 +2024-11-21 21:48:45.773707: train_loss -0.7734 +2024-11-21 21:48:45.773947: val_loss -0.7398 +2024-11-21 21:48:45.774030: Pseudo dice [0.8246] +2024-11-21 21:48:45.774106: Epoch time: 18.8 s +2024-11-21 21:48:46.608445: +2024-11-21 21:48:46.608758: Epoch 2047 +2024-11-21 21:48:46.608878: Current learning rate: 0.00766 +2024-11-21 21:49:05.919940: train_loss -0.7754 +2024-11-21 21:49:05.920644: val_loss -0.7475 +2024-11-21 21:49:05.920720: Pseudo dice [0.8527] +2024-11-21 21:49:05.920802: Epoch time: 19.31 s +2024-11-21 21:49:07.144657: +2024-11-21 21:49:07.144898: Epoch 2048 +2024-11-21 21:49:07.145021: Current learning rate: 0.00766 +2024-11-21 21:49:26.048813: train_loss -0.7674 +2024-11-21 21:49:26.049030: val_loss -0.7176 +2024-11-21 21:49:26.049105: Pseudo dice [0.8233] +2024-11-21 21:49:26.049177: Epoch time: 18.9 s +2024-11-21 21:49:26.918311: +2024-11-21 21:49:26.918529: Epoch 2049 +2024-11-21 21:49:26.918640: Current learning rate: 0.00766 +2024-11-21 21:49:46.440147: train_loss -0.7667 +2024-11-21 21:49:46.440364: val_loss -0.727 +2024-11-21 21:49:46.440453: Pseudo dice [0.8252] +2024-11-21 21:49:46.440529: Epoch time: 19.52 s +2024-11-21 21:49:47.579099: +2024-11-21 21:49:47.579326: Epoch 2050 +2024-11-21 21:49:47.579439: Current learning rate: 0.00766 +2024-11-21 21:50:05.640908: train_loss -0.7749 +2024-11-21 21:50:05.641168: val_loss -0.7475 +2024-11-21 21:50:05.641244: Pseudo dice [0.8522] +2024-11-21 21:50:05.641327: Epoch time: 18.06 s +2024-11-21 21:50:06.470982: +2024-11-21 21:50:06.471223: Epoch 2051 +2024-11-21 21:50:06.471335: Current learning rate: 0.00766 +2024-11-21 21:50:24.835868: train_loss -0.7815 +2024-11-21 21:50:24.836107: val_loss -0.7188 +2024-11-21 21:50:24.836184: Pseudo dice [0.8254] +2024-11-21 21:50:24.836317: Epoch time: 18.37 s +2024-11-21 21:50:25.667426: +2024-11-21 21:50:25.667669: Epoch 2052 +2024-11-21 21:50:25.667796: Current learning rate: 0.00766 +2024-11-21 21:50:43.827451: train_loss -0.7871 +2024-11-21 21:50:43.827668: val_loss -0.7589 +2024-11-21 21:50:43.827744: Pseudo dice [0.8408] +2024-11-21 21:50:43.827819: Epoch time: 18.16 s +2024-11-21 21:50:44.704239: +2024-11-21 21:50:44.704449: Epoch 2053 +2024-11-21 21:50:44.704562: Current learning rate: 0.00766 +2024-11-21 21:51:02.912163: train_loss -0.7747 +2024-11-21 21:51:02.912385: val_loss -0.7405 +2024-11-21 21:51:02.912461: Pseudo dice [0.8394] +2024-11-21 21:51:02.912537: Epoch time: 18.21 s +2024-11-21 21:51:03.742711: +2024-11-21 21:51:03.742913: Epoch 2054 +2024-11-21 21:51:03.743036: Current learning rate: 0.00766 +2024-11-21 21:51:23.470920: train_loss -0.7745 +2024-11-21 21:51:23.471178: val_loss -0.7522 +2024-11-21 21:51:23.471254: Pseudo dice [0.8344] +2024-11-21 21:51:23.471341: Epoch time: 19.73 s +2024-11-21 21:51:24.304082: +2024-11-21 21:51:24.304296: Epoch 2055 +2024-11-21 21:51:24.304410: Current learning rate: 0.00766 +2024-11-21 21:51:42.452635: train_loss -0.7666 +2024-11-21 21:51:42.452909: val_loss -0.7536 +2024-11-21 21:51:42.452982: Pseudo dice [0.8536] +2024-11-21 21:51:42.453065: Epoch time: 18.15 s +2024-11-21 21:51:43.289429: +2024-11-21 21:51:43.289638: Epoch 2056 +2024-11-21 21:51:43.289754: Current learning rate: 0.00765 +2024-11-21 21:52:01.628592: train_loss -0.7802 +2024-11-21 21:52:01.630969: val_loss -0.7165 +2024-11-21 21:52:01.631072: Pseudo dice [0.847] +2024-11-21 21:52:01.631151: Epoch time: 18.34 s +2024-11-21 21:52:02.510191: +2024-11-21 21:52:02.510639: Epoch 2057 +2024-11-21 21:52:02.510753: Current learning rate: 0.00765 +2024-11-21 21:52:21.555743: train_loss -0.7872 +2024-11-21 21:52:21.555960: val_loss -0.7397 +2024-11-21 21:52:21.556046: Pseudo dice [0.8474] +2024-11-21 21:52:21.556125: Epoch time: 19.05 s +2024-11-21 21:52:22.388978: +2024-11-21 21:52:22.389432: Epoch 2058 +2024-11-21 21:52:22.389566: Current learning rate: 0.00765 +2024-11-21 21:52:40.602107: train_loss -0.7863 +2024-11-21 21:52:40.602350: val_loss -0.7378 +2024-11-21 21:52:40.602430: Pseudo dice [0.8432] +2024-11-21 21:52:40.602508: Epoch time: 18.21 s +2024-11-21 21:52:41.432647: +2024-11-21 21:52:41.432852: Epoch 2059 +2024-11-21 21:52:41.432963: Current learning rate: 0.00765 +2024-11-21 21:52:59.886764: train_loss -0.7847 +2024-11-21 21:52:59.887041: val_loss -0.7566 +2024-11-21 21:52:59.887119: Pseudo dice [0.8482] +2024-11-21 21:52:59.887194: Epoch time: 18.45 s +2024-11-21 21:53:01.149636: +2024-11-21 21:53:01.149858: Epoch 2060 +2024-11-21 21:53:01.149968: Current learning rate: 0.00765 +2024-11-21 21:53:21.128093: train_loss -0.7758 +2024-11-21 21:53:21.128315: val_loss -0.7639 +2024-11-21 21:53:21.128392: Pseudo dice [0.8486] +2024-11-21 21:53:21.128472: Epoch time: 19.98 s +2024-11-21 21:53:21.958256: +2024-11-21 21:53:21.958560: Epoch 2061 +2024-11-21 21:53:21.958706: Current learning rate: 0.00765 +2024-11-21 21:53:40.348199: train_loss -0.7794 +2024-11-21 21:53:40.348420: val_loss -0.7432 +2024-11-21 21:53:40.348491: Pseudo dice [0.8498] +2024-11-21 21:53:40.348567: Epoch time: 18.39 s +2024-11-21 21:53:41.242000: +2024-11-21 21:53:41.242248: Epoch 2062 +2024-11-21 21:53:41.242364: Current learning rate: 0.00765 +2024-11-21 21:54:00.388499: train_loss -0.7756 +2024-11-21 21:54:00.388720: val_loss -0.748 +2024-11-21 21:54:00.390964: Pseudo dice [0.839] +2024-11-21 21:54:00.391774: Epoch time: 19.15 s +2024-11-21 21:54:01.223968: +2024-11-21 21:54:01.224263: Epoch 2063 +2024-11-21 21:54:01.224396: Current learning rate: 0.00765 +2024-11-21 21:54:21.389154: train_loss -0.775 +2024-11-21 21:54:21.389380: val_loss -0.7365 +2024-11-21 21:54:21.389457: Pseudo dice [0.8222] +2024-11-21 21:54:21.389532: Epoch time: 20.17 s +2024-11-21 21:54:22.246427: +2024-11-21 21:54:22.246668: Epoch 2064 +2024-11-21 21:54:22.247001: Current learning rate: 0.00764 +2024-11-21 21:54:41.024628: train_loss -0.7742 +2024-11-21 21:54:41.024909: val_loss -0.7398 +2024-11-21 21:54:41.025000: Pseudo dice [0.8555] +2024-11-21 21:54:41.025085: Epoch time: 18.78 s +2024-11-21 21:54:41.870600: +2024-11-21 21:54:41.870905: Epoch 2065 +2024-11-21 21:54:41.871032: Current learning rate: 0.00764 +2024-11-21 21:55:01.239105: train_loss -0.7522 +2024-11-21 21:55:01.239396: val_loss -0.7209 +2024-11-21 21:55:01.239475: Pseudo dice [0.8087] +2024-11-21 21:55:01.239574: Epoch time: 19.37 s +2024-11-21 21:55:02.072767: +2024-11-21 21:55:02.072983: Epoch 2066 +2024-11-21 21:55:02.073100: Current learning rate: 0.00764 +2024-11-21 21:55:20.196794: train_loss -0.7564 +2024-11-21 21:55:20.197038: val_loss -0.717 +2024-11-21 21:55:20.197117: Pseudo dice [0.8185] +2024-11-21 21:55:20.197195: Epoch time: 18.12 s +2024-11-21 21:55:21.031189: +2024-11-21 21:55:21.031419: Epoch 2067 +2024-11-21 21:55:21.031533: Current learning rate: 0.00764 +2024-11-21 21:55:39.698685: train_loss -0.7739 +2024-11-21 21:55:39.699373: val_loss -0.7338 +2024-11-21 21:55:39.699458: Pseudo dice [0.8203] +2024-11-21 21:55:39.699539: Epoch time: 18.67 s +2024-11-21 21:55:40.703131: +2024-11-21 21:55:40.703386: Epoch 2068 +2024-11-21 21:55:40.703499: Current learning rate: 0.00764 +2024-11-21 21:55:58.728268: train_loss -0.7725 +2024-11-21 21:55:58.728506: val_loss -0.7365 +2024-11-21 21:55:58.728582: Pseudo dice [0.8336] +2024-11-21 21:55:58.728663: Epoch time: 18.03 s +2024-11-21 21:55:59.558688: +2024-11-21 21:55:59.558951: Epoch 2069 +2024-11-21 21:55:59.559070: Current learning rate: 0.00764 +2024-11-21 21:56:18.107564: train_loss -0.777 +2024-11-21 21:56:18.107810: val_loss -0.721 +2024-11-21 21:56:18.107887: Pseudo dice [0.8255] +2024-11-21 21:56:18.107963: Epoch time: 18.55 s +2024-11-21 21:56:18.936923: +2024-11-21 21:56:18.937378: Epoch 2070 +2024-11-21 21:56:18.937520: Current learning rate: 0.00764 +2024-11-21 21:56:38.001502: train_loss -0.776 +2024-11-21 21:56:38.001729: val_loss -0.7507 +2024-11-21 21:56:38.001815: Pseudo dice [0.8511] +2024-11-21 21:56:38.001891: Epoch time: 19.07 s +2024-11-21 21:56:38.830976: +2024-11-21 21:56:38.831182: Epoch 2071 +2024-11-21 21:56:38.831293: Current learning rate: 0.00764 +2024-11-21 21:56:57.374185: train_loss -0.7863 +2024-11-21 21:56:57.374430: val_loss -0.75 +2024-11-21 21:56:57.374512: Pseudo dice [0.849] +2024-11-21 21:56:57.374604: Epoch time: 18.54 s +2024-11-21 21:56:58.597463: +2024-11-21 21:56:58.597692: Epoch 2072 +2024-11-21 21:56:58.597804: Current learning rate: 0.00764 +2024-11-21 21:57:17.501902: train_loss -0.7806 +2024-11-21 21:57:17.502127: val_loss -0.7695 +2024-11-21 21:57:17.502200: Pseudo dice [0.8435] +2024-11-21 21:57:17.502273: Epoch time: 18.91 s +2024-11-21 21:57:18.330446: +2024-11-21 21:57:18.330682: Epoch 2073 +2024-11-21 21:57:18.330803: Current learning rate: 0.00763 +2024-11-21 21:57:37.105173: train_loss -0.7671 +2024-11-21 21:57:37.105428: val_loss -0.7291 +2024-11-21 21:57:37.105507: Pseudo dice [0.8304] +2024-11-21 21:57:37.105583: Epoch time: 18.78 s +2024-11-21 21:57:37.932365: +2024-11-21 21:57:37.932587: Epoch 2074 +2024-11-21 21:57:37.932698: Current learning rate: 0.00763 +2024-11-21 21:57:57.257188: train_loss -0.7697 +2024-11-21 21:57:57.259580: val_loss -0.7263 +2024-11-21 21:57:57.259668: Pseudo dice [0.8086] +2024-11-21 21:57:57.259751: Epoch time: 19.33 s +2024-11-21 21:57:58.253457: +2024-11-21 21:57:58.253676: Epoch 2075 +2024-11-21 21:57:58.253788: Current learning rate: 0.00763 +2024-11-21 21:58:16.823351: train_loss -0.777 +2024-11-21 21:58:16.823575: val_loss -0.7238 +2024-11-21 21:58:16.823665: Pseudo dice [0.8265] +2024-11-21 21:58:16.823748: Epoch time: 18.57 s +2024-11-21 21:58:17.659539: +2024-11-21 21:58:17.659761: Epoch 2076 +2024-11-21 21:58:17.659876: Current learning rate: 0.00763 +2024-11-21 21:58:36.599304: train_loss -0.7755 +2024-11-21 21:58:36.601714: val_loss -0.7358 +2024-11-21 21:58:36.601807: Pseudo dice [0.8326] +2024-11-21 21:58:36.601885: Epoch time: 18.94 s +2024-11-21 21:58:37.447236: +2024-11-21 21:58:37.447440: Epoch 2077 +2024-11-21 21:58:37.447552: Current learning rate: 0.00763 +2024-11-21 21:58:55.937093: train_loss -0.7792 +2024-11-21 21:58:55.937315: val_loss -0.7576 +2024-11-21 21:58:55.937388: Pseudo dice [0.8579] +2024-11-21 21:58:55.937464: Epoch time: 18.49 s +2024-11-21 21:58:56.766925: +2024-11-21 21:58:56.767140: Epoch 2078 +2024-11-21 21:58:56.767253: Current learning rate: 0.00763 +2024-11-21 21:59:15.364777: train_loss -0.7759 +2024-11-21 21:59:15.365005: val_loss -0.7442 +2024-11-21 21:59:15.365081: Pseudo dice [0.8298] +2024-11-21 21:59:15.365161: Epoch time: 18.6 s +2024-11-21 21:59:16.199209: +2024-11-21 21:59:16.199412: Epoch 2079 +2024-11-21 21:59:16.199530: Current learning rate: 0.00763 +2024-11-21 21:59:36.060715: train_loss -0.76 +2024-11-21 21:59:36.060963: val_loss -0.7371 +2024-11-21 21:59:36.061042: Pseudo dice [0.8447] +2024-11-21 21:59:36.061122: Epoch time: 19.86 s +2024-11-21 21:59:36.969344: +2024-11-21 21:59:36.969641: Epoch 2080 +2024-11-21 21:59:36.969758: Current learning rate: 0.00763 +2024-11-21 21:59:54.857730: train_loss -0.7715 +2024-11-21 21:59:54.857962: val_loss -0.73 +2024-11-21 21:59:54.858047: Pseudo dice [0.8406] +2024-11-21 21:59:54.858127: Epoch time: 17.89 s +2024-11-21 21:59:55.897270: +2024-11-21 21:59:55.897494: Epoch 2081 +2024-11-21 21:59:55.897609: Current learning rate: 0.00763 +2024-11-21 22:00:14.742950: train_loss -0.7782 +2024-11-21 22:00:14.743171: val_loss -0.7408 +2024-11-21 22:00:14.743250: Pseudo dice [0.8212] +2024-11-21 22:00:14.743332: Epoch time: 18.85 s +2024-11-21 22:00:15.571504: +2024-11-21 22:00:15.571712: Epoch 2082 +2024-11-21 22:00:15.571824: Current learning rate: 0.00762 +2024-11-21 22:00:34.019134: train_loss -0.7867 +2024-11-21 22:00:34.019384: val_loss -0.7291 +2024-11-21 22:00:34.019463: Pseudo dice [0.8418] +2024-11-21 22:00:34.019548: Epoch time: 18.45 s +2024-11-21 22:00:34.851842: +2024-11-21 22:00:34.852057: Epoch 2083 +2024-11-21 22:00:34.852172: Current learning rate: 0.00762 +2024-11-21 22:00:54.037932: train_loss -0.7708 +2024-11-21 22:00:54.038227: val_loss -0.7587 +2024-11-21 22:00:54.038306: Pseudo dice [0.857] +2024-11-21 22:00:54.038382: Epoch time: 19.19 s +2024-11-21 22:00:55.275343: +2024-11-21 22:00:55.275553: Epoch 2084 +2024-11-21 22:00:55.275662: Current learning rate: 0.00762 +2024-11-21 22:01:13.543416: train_loss -0.7753 +2024-11-21 22:01:13.543643: val_loss -0.7538 +2024-11-21 22:01:13.543719: Pseudo dice [0.847] +2024-11-21 22:01:13.543795: Epoch time: 18.27 s +2024-11-21 22:01:14.439568: +2024-11-21 22:01:14.439775: Epoch 2085 +2024-11-21 22:01:14.439885: Current learning rate: 0.00762 +2024-11-21 22:01:33.752289: train_loss -0.7691 +2024-11-21 22:01:33.752547: val_loss -0.7333 +2024-11-21 22:01:33.752625: Pseudo dice [0.8388] +2024-11-21 22:01:33.752706: Epoch time: 19.31 s +2024-11-21 22:01:34.584914: +2024-11-21 22:01:34.585115: Epoch 2086 +2024-11-21 22:01:34.585228: Current learning rate: 0.00762 +2024-11-21 22:01:54.268556: train_loss -0.7731 +2024-11-21 22:01:54.268768: val_loss -0.7402 +2024-11-21 22:01:54.268850: Pseudo dice [0.8399] +2024-11-21 22:01:54.268929: Epoch time: 19.68 s +2024-11-21 22:01:55.097461: +2024-11-21 22:01:55.097670: Epoch 2087 +2024-11-21 22:01:55.097783: Current learning rate: 0.00762 +2024-11-21 22:02:13.629934: train_loss -0.7757 +2024-11-21 22:02:13.630171: val_loss -0.7611 +2024-11-21 22:02:13.630252: Pseudo dice [0.8552] +2024-11-21 22:02:13.630328: Epoch time: 18.53 s +2024-11-21 22:02:14.513770: +2024-11-21 22:02:14.514012: Epoch 2088 +2024-11-21 22:02:14.514129: Current learning rate: 0.00762 +2024-11-21 22:02:33.557329: train_loss -0.7671 +2024-11-21 22:02:33.557539: val_loss -0.7085 +2024-11-21 22:02:33.557611: Pseudo dice [0.8344] +2024-11-21 22:02:33.557687: Epoch time: 19.04 s +2024-11-21 22:02:34.410734: +2024-11-21 22:02:34.410980: Epoch 2089 +2024-11-21 22:02:34.411093: Current learning rate: 0.00762 +2024-11-21 22:02:52.295742: train_loss -0.7743 +2024-11-21 22:02:52.295988: val_loss -0.7264 +2024-11-21 22:02:52.296072: Pseudo dice [0.8179] +2024-11-21 22:02:52.296156: Epoch time: 17.89 s +2024-11-21 22:02:53.145296: +2024-11-21 22:02:53.145500: Epoch 2090 +2024-11-21 22:02:53.145854: Current learning rate: 0.00761 +2024-11-21 22:03:12.251875: train_loss -0.7727 +2024-11-21 22:03:12.252098: val_loss -0.7369 +2024-11-21 22:03:12.252172: Pseudo dice [0.8205] +2024-11-21 22:03:12.252248: Epoch time: 19.11 s +2024-11-21 22:03:13.079173: +2024-11-21 22:03:13.079375: Epoch 2091 +2024-11-21 22:03:13.079485: Current learning rate: 0.00761 +2024-11-21 22:03:30.940852: train_loss -0.7721 +2024-11-21 22:03:30.941091: val_loss -0.696 +2024-11-21 22:03:30.941175: Pseudo dice [0.8421] +2024-11-21 22:03:30.941259: Epoch time: 17.86 s +2024-11-21 22:03:31.777917: +2024-11-21 22:03:31.778133: Epoch 2092 +2024-11-21 22:03:31.778246: Current learning rate: 0.00761 +2024-11-21 22:03:49.780476: train_loss -0.7646 +2024-11-21 22:03:49.780720: val_loss -0.7562 +2024-11-21 22:03:49.780799: Pseudo dice [0.8513] +2024-11-21 22:03:49.780883: Epoch time: 18.0 s +2024-11-21 22:03:50.621691: +2024-11-21 22:03:50.621891: Epoch 2093 +2024-11-21 22:03:50.622010: Current learning rate: 0.00761 +2024-11-21 22:04:08.905544: train_loss -0.7755 +2024-11-21 22:04:08.905798: val_loss -0.7407 +2024-11-21 22:04:08.905880: Pseudo dice [0.8439] +2024-11-21 22:04:08.905964: Epoch time: 18.28 s +2024-11-21 22:04:09.738135: +2024-11-21 22:04:09.738348: Epoch 2094 +2024-11-21 22:04:09.738466: Current learning rate: 0.00761 +2024-11-21 22:04:27.936302: train_loss -0.7759 +2024-11-21 22:04:27.936516: val_loss -0.7011 +2024-11-21 22:04:27.936589: Pseudo dice [0.8426] +2024-11-21 22:04:27.936664: Epoch time: 18.2 s +2024-11-21 22:04:28.769631: +2024-11-21 22:04:28.769854: Epoch 2095 +2024-11-21 22:04:28.769973: Current learning rate: 0.00761 +2024-11-21 22:04:46.731807: train_loss -0.7776 +2024-11-21 22:04:46.732067: val_loss -0.7552 +2024-11-21 22:04:46.732145: Pseudo dice [0.8365] +2024-11-21 22:04:46.732221: Epoch time: 17.96 s +2024-11-21 22:04:47.961224: +2024-11-21 22:04:47.961673: Epoch 2096 +2024-11-21 22:04:47.961808: Current learning rate: 0.00761 +2024-11-21 22:05:06.601191: train_loss -0.7817 +2024-11-21 22:05:06.601435: val_loss -0.7499 +2024-11-21 22:05:06.601513: Pseudo dice [0.8581] +2024-11-21 22:05:06.601594: Epoch time: 18.64 s +2024-11-21 22:05:07.432637: +2024-11-21 22:05:07.432854: Epoch 2097 +2024-11-21 22:05:07.432998: Current learning rate: 0.00761 +2024-11-21 22:05:25.762114: train_loss -0.7799 +2024-11-21 22:05:25.762343: val_loss -0.7463 +2024-11-21 22:05:25.762421: Pseudo dice [0.808] +2024-11-21 22:05:25.762498: Epoch time: 18.33 s +2024-11-21 22:05:26.593663: +2024-11-21 22:05:26.593883: Epoch 2098 +2024-11-21 22:05:26.594000: Current learning rate: 0.00761 +2024-11-21 22:05:45.855574: train_loss -0.7817 +2024-11-21 22:05:45.855845: val_loss -0.7439 +2024-11-21 22:05:45.855923: Pseudo dice [0.8538] +2024-11-21 22:05:45.856006: Epoch time: 19.26 s +2024-11-21 22:05:46.736286: +2024-11-21 22:05:46.736504: Epoch 2099 +2024-11-21 22:05:46.736625: Current learning rate: 0.0076 +2024-11-21 22:06:04.741411: train_loss -0.774 +2024-11-21 22:06:04.741657: val_loss -0.7305 +2024-11-21 22:06:04.741754: Pseudo dice [0.8529] +2024-11-21 22:06:04.741844: Epoch time: 18.01 s +2024-11-21 22:06:05.849750: +2024-11-21 22:06:05.849989: Epoch 2100 +2024-11-21 22:06:05.850105: Current learning rate: 0.0076 +2024-11-21 22:06:23.939429: train_loss -0.7808 +2024-11-21 22:06:23.939655: val_loss -0.7327 +2024-11-21 22:06:23.939734: Pseudo dice [0.8463] +2024-11-21 22:06:23.939831: Epoch time: 18.09 s +2024-11-21 22:06:24.773482: +2024-11-21 22:06:24.773682: Epoch 2101 +2024-11-21 22:06:24.773791: Current learning rate: 0.0076 +2024-11-21 22:06:43.039597: train_loss -0.7707 +2024-11-21 22:06:43.039816: val_loss -0.738 +2024-11-21 22:06:43.039892: Pseudo dice [0.8386] +2024-11-21 22:06:43.039970: Epoch time: 18.27 s +2024-11-21 22:06:43.979754: +2024-11-21 22:06:43.979954: Epoch 2102 +2024-11-21 22:06:43.980071: Current learning rate: 0.0076 +2024-11-21 22:07:03.175450: train_loss -0.7672 +2024-11-21 22:07:03.175673: val_loss -0.7303 +2024-11-21 22:07:03.175749: Pseudo dice [0.8092] +2024-11-21 22:07:03.175827: Epoch time: 19.2 s +2024-11-21 22:07:04.024479: +2024-11-21 22:07:04.024700: Epoch 2103 +2024-11-21 22:07:04.024811: Current learning rate: 0.0076 +2024-11-21 22:07:22.688006: train_loss -0.7754 +2024-11-21 22:07:22.688273: val_loss -0.7438 +2024-11-21 22:07:22.688353: Pseudo dice [0.8482] +2024-11-21 22:07:22.688500: Epoch time: 18.66 s +2024-11-21 22:07:23.540375: +2024-11-21 22:07:23.540586: Epoch 2104 +2024-11-21 22:07:23.540702: Current learning rate: 0.0076 +2024-11-21 22:07:42.448889: train_loss -0.7638 +2024-11-21 22:07:42.449180: val_loss -0.7376 +2024-11-21 22:07:42.449260: Pseudo dice [0.8366] +2024-11-21 22:07:42.449337: Epoch time: 18.91 s +2024-11-21 22:07:43.283299: +2024-11-21 22:07:43.283504: Epoch 2105 +2024-11-21 22:07:43.283616: Current learning rate: 0.0076 +2024-11-21 22:08:01.179436: train_loss -0.7649 +2024-11-21 22:08:01.179659: val_loss -0.7186 +2024-11-21 22:08:01.179791: Pseudo dice [0.8342] +2024-11-21 22:08:01.179869: Epoch time: 17.9 s +2024-11-21 22:08:02.025106: +2024-11-21 22:08:02.025310: Epoch 2106 +2024-11-21 22:08:02.025426: Current learning rate: 0.0076 +2024-11-21 22:08:20.217242: train_loss -0.7538 +2024-11-21 22:08:20.217481: val_loss -0.7279 +2024-11-21 22:08:20.217557: Pseudo dice [0.8443] +2024-11-21 22:08:20.217640: Epoch time: 18.19 s +2024-11-21 22:08:21.072407: +2024-11-21 22:08:21.072933: Epoch 2107 +2024-11-21 22:08:21.073077: Current learning rate: 0.00759 +2024-11-21 22:08:41.488986: train_loss -0.7599 +2024-11-21 22:08:41.489227: val_loss -0.7307 +2024-11-21 22:08:41.489302: Pseudo dice [0.8284] +2024-11-21 22:08:41.489383: Epoch time: 20.42 s +2024-11-21 22:08:42.833741: +2024-11-21 22:08:42.833972: Epoch 2108 +2024-11-21 22:08:42.834092: Current learning rate: 0.00759 +2024-11-21 22:08:59.841612: train_loss -0.7745 +2024-11-21 22:08:59.841860: val_loss -0.7292 +2024-11-21 22:08:59.841938: Pseudo dice [0.815] +2024-11-21 22:08:59.842017: Epoch time: 17.01 s +2024-11-21 22:09:00.685590: +2024-11-21 22:09:00.685821: Epoch 2109 +2024-11-21 22:09:00.685933: Current learning rate: 0.00759 +2024-11-21 22:09:19.254806: train_loss -0.7699 +2024-11-21 22:09:19.255033: val_loss -0.722 +2024-11-21 22:09:19.255109: Pseudo dice [0.8305] +2024-11-21 22:09:19.255189: Epoch time: 18.57 s +2024-11-21 22:09:20.092189: +2024-11-21 22:09:20.092417: Epoch 2110 +2024-11-21 22:09:20.092533: Current learning rate: 0.00759 +2024-11-21 22:09:38.931854: train_loss -0.7654 +2024-11-21 22:09:38.932908: val_loss -0.7168 +2024-11-21 22:09:38.933145: Pseudo dice [0.8259] +2024-11-21 22:09:38.933229: Epoch time: 18.84 s +2024-11-21 22:09:39.764129: +2024-11-21 22:09:39.764354: Epoch 2111 +2024-11-21 22:09:39.764469: Current learning rate: 0.00759 +2024-11-21 22:09:58.893618: train_loss -0.7625 +2024-11-21 22:09:58.893833: val_loss -0.7519 +2024-11-21 22:09:58.893909: Pseudo dice [0.8179] +2024-11-21 22:09:58.893986: Epoch time: 19.13 s +2024-11-21 22:09:59.759713: +2024-11-21 22:09:59.759950: Epoch 2112 +2024-11-21 22:09:59.760074: Current learning rate: 0.00759 +2024-11-21 22:10:18.552118: train_loss -0.7834 +2024-11-21 22:10:18.552351: val_loss -0.7246 +2024-11-21 22:10:18.552427: Pseudo dice [0.8333] +2024-11-21 22:10:18.552505: Epoch time: 18.79 s +2024-11-21 22:10:19.397630: +2024-11-21 22:10:19.397880: Epoch 2113 +2024-11-21 22:10:19.398000: Current learning rate: 0.00759 +2024-11-21 22:10:37.798114: train_loss -0.7697 +2024-11-21 22:10:37.798329: val_loss -0.7295 +2024-11-21 22:10:37.798404: Pseudo dice [0.822] +2024-11-21 22:10:37.798479: Epoch time: 18.4 s +2024-11-21 22:10:38.636641: +2024-11-21 22:10:38.636873: Epoch 2114 +2024-11-21 22:10:38.637003: Current learning rate: 0.00759 +2024-11-21 22:10:56.498841: train_loss -0.774 +2024-11-21 22:10:56.499097: val_loss -0.7353 +2024-11-21 22:10:56.499185: Pseudo dice [0.8375] +2024-11-21 22:10:56.499276: Epoch time: 17.86 s +2024-11-21 22:10:57.316839: +2024-11-21 22:10:57.317040: Epoch 2115 +2024-11-21 22:10:57.317160: Current learning rate: 0.00759 +2024-11-21 22:11:15.378481: train_loss -0.7722 +2024-11-21 22:11:15.378698: val_loss -0.7478 +2024-11-21 22:11:15.378776: Pseudo dice [0.8397] +2024-11-21 22:11:15.378855: Epoch time: 18.06 s +2024-11-21 22:11:16.305342: +2024-11-21 22:11:16.305829: Epoch 2116 +2024-11-21 22:11:16.305952: Current learning rate: 0.00758 +2024-11-21 22:11:34.642324: train_loss -0.7653 +2024-11-21 22:11:34.644724: val_loss -0.727 +2024-11-21 22:11:34.644846: Pseudo dice [0.8573] +2024-11-21 22:11:34.644925: Epoch time: 18.34 s +2024-11-21 22:11:35.668320: +2024-11-21 22:11:35.668520: Epoch 2117 +2024-11-21 22:11:35.668636: Current learning rate: 0.00758 +2024-11-21 22:11:54.492664: train_loss -0.7742 +2024-11-21 22:11:54.492918: val_loss -0.7394 +2024-11-21 22:11:54.493001: Pseudo dice [0.8268] +2024-11-21 22:11:54.493113: Epoch time: 18.83 s +2024-11-21 22:11:55.333753: +2024-11-21 22:11:55.333954: Epoch 2118 +2024-11-21 22:11:55.334067: Current learning rate: 0.00758 +2024-11-21 22:12:13.828658: train_loss -0.7753 +2024-11-21 22:12:13.828865: val_loss -0.7326 +2024-11-21 22:12:13.828939: Pseudo dice [0.8405] +2024-11-21 22:12:13.829025: Epoch time: 18.5 s +2024-11-21 22:12:14.697047: +2024-11-21 22:12:14.697267: Epoch 2119 +2024-11-21 22:12:14.697371: Current learning rate: 0.00758 +2024-11-21 22:12:33.729384: train_loss -0.7803 +2024-11-21 22:12:33.729612: val_loss -0.7045 +2024-11-21 22:12:33.729690: Pseudo dice [0.8203] +2024-11-21 22:12:33.729773: Epoch time: 19.03 s +2024-11-21 22:12:34.993511: +2024-11-21 22:12:34.993786: Epoch 2120 +2024-11-21 22:12:34.993896: Current learning rate: 0.00758 +2024-11-21 22:12:53.568927: train_loss -0.7773 +2024-11-21 22:12:53.569194: val_loss -0.7587 +2024-11-21 22:12:53.569269: Pseudo dice [0.8419] +2024-11-21 22:12:53.569355: Epoch time: 18.58 s +2024-11-21 22:12:54.410444: +2024-11-21 22:12:54.410661: Epoch 2121 +2024-11-21 22:12:54.410780: Current learning rate: 0.00758 +2024-11-21 22:13:13.978100: train_loss -0.7751 +2024-11-21 22:13:13.978320: val_loss -0.7237 +2024-11-21 22:13:13.978393: Pseudo dice [0.83] +2024-11-21 22:13:13.978470: Epoch time: 19.57 s +2024-11-21 22:13:14.839754: +2024-11-21 22:13:14.839975: Epoch 2122 +2024-11-21 22:13:14.840111: Current learning rate: 0.00758 +2024-11-21 22:13:33.599680: train_loss -0.7744 +2024-11-21 22:13:33.599902: val_loss -0.7514 +2024-11-21 22:13:33.599978: Pseudo dice [0.8421] +2024-11-21 22:13:33.600061: Epoch time: 18.76 s +2024-11-21 22:13:34.439212: +2024-11-21 22:13:34.439405: Epoch 2123 +2024-11-21 22:13:34.439512: Current learning rate: 0.00758 +2024-11-21 22:13:52.952769: train_loss -0.7661 +2024-11-21 22:13:52.953027: val_loss -0.7429 +2024-11-21 22:13:52.953103: Pseudo dice [0.8608] +2024-11-21 22:13:52.953183: Epoch time: 18.51 s +2024-11-21 22:13:53.792641: +2024-11-21 22:13:53.792875: Epoch 2124 +2024-11-21 22:13:53.792986: Current learning rate: 0.00758 +2024-11-21 22:14:12.031976: train_loss -0.7803 +2024-11-21 22:14:12.032216: val_loss -0.7387 +2024-11-21 22:14:12.032310: Pseudo dice [0.8418] +2024-11-21 22:14:12.032389: Epoch time: 18.24 s +2024-11-21 22:14:13.025279: +2024-11-21 22:14:13.025466: Epoch 2125 +2024-11-21 22:14:13.025578: Current learning rate: 0.00757 +2024-11-21 22:14:32.541788: train_loss -0.7772 +2024-11-21 22:14:32.542059: val_loss -0.7421 +2024-11-21 22:14:32.542137: Pseudo dice [0.8385] +2024-11-21 22:14:32.542212: Epoch time: 19.52 s +2024-11-21 22:14:33.375481: +2024-11-21 22:14:33.375666: Epoch 2126 +2024-11-21 22:14:33.375777: Current learning rate: 0.00757 +2024-11-21 22:14:53.032342: train_loss -0.7718 +2024-11-21 22:14:53.032560: val_loss -0.7367 +2024-11-21 22:14:53.032636: Pseudo dice [0.837] +2024-11-21 22:14:53.032714: Epoch time: 19.66 s +2024-11-21 22:14:53.871795: +2024-11-21 22:14:53.872009: Epoch 2127 +2024-11-21 22:14:53.872123: Current learning rate: 0.00757 +2024-11-21 22:15:13.250954: train_loss -0.782 +2024-11-21 22:15:13.251183: val_loss -0.7554 +2024-11-21 22:15:13.251258: Pseudo dice [0.8205] +2024-11-21 22:15:13.251343: Epoch time: 19.38 s +2024-11-21 22:15:14.123976: +2024-11-21 22:15:14.124200: Epoch 2128 +2024-11-21 22:15:14.124326: Current learning rate: 0.00757 +2024-11-21 22:15:32.037598: train_loss -0.7673 +2024-11-21 22:15:32.037833: val_loss -0.7207 +2024-11-21 22:15:32.037911: Pseudo dice [0.8332] +2024-11-21 22:15:32.038039: Epoch time: 17.91 s +2024-11-21 22:15:32.868440: +2024-11-21 22:15:32.868646: Epoch 2129 +2024-11-21 22:15:32.868757: Current learning rate: 0.00757 +2024-11-21 22:15:50.678652: train_loss -0.7756 +2024-11-21 22:15:50.678874: val_loss -0.7334 +2024-11-21 22:15:50.678949: Pseudo dice [0.8248] +2024-11-21 22:15:50.679033: Epoch time: 17.81 s +2024-11-21 22:15:51.547652: +2024-11-21 22:15:51.547880: Epoch 2130 +2024-11-21 22:15:51.548000: Current learning rate: 0.00757 +2024-11-21 22:16:09.666958: train_loss -0.7792 +2024-11-21 22:16:09.667228: val_loss -0.7663 +2024-11-21 22:16:09.667312: Pseudo dice [0.8399] +2024-11-21 22:16:09.667391: Epoch time: 18.12 s +2024-11-21 22:16:10.503003: +2024-11-21 22:16:10.503205: Epoch 2131 +2024-11-21 22:16:10.503309: Current learning rate: 0.00757 +2024-11-21 22:16:29.941710: train_loss -0.7847 +2024-11-21 22:16:29.941943: val_loss -0.75 +2024-11-21 22:16:29.942022: Pseudo dice [0.8389] +2024-11-21 22:16:29.942104: Epoch time: 19.44 s +2024-11-21 22:16:31.026287: +2024-11-21 22:16:31.026516: Epoch 2132 +2024-11-21 22:16:31.026631: Current learning rate: 0.00757 +2024-11-21 22:16:50.662367: train_loss -0.785 +2024-11-21 22:16:50.662591: val_loss -0.746 +2024-11-21 22:16:50.662668: Pseudo dice [0.8389] +2024-11-21 22:16:50.662744: Epoch time: 19.64 s +2024-11-21 22:16:51.513672: +2024-11-21 22:16:51.513869: Epoch 2133 +2024-11-21 22:16:51.513984: Current learning rate: 0.00756 +2024-11-21 22:17:09.355324: train_loss -0.779 +2024-11-21 22:17:09.355554: val_loss -0.694 +2024-11-21 22:17:09.355634: Pseudo dice [0.8373] +2024-11-21 22:17:09.355714: Epoch time: 17.84 s +2024-11-21 22:17:10.187510: +2024-11-21 22:17:10.187731: Epoch 2134 +2024-11-21 22:17:10.187840: Current learning rate: 0.00756 +2024-11-21 22:17:28.155600: train_loss -0.7819 +2024-11-21 22:17:28.155843: val_loss -0.7321 +2024-11-21 22:17:28.155917: Pseudo dice [0.8222] +2024-11-21 22:17:28.156034: Epoch time: 17.97 s +2024-11-21 22:17:28.995663: +2024-11-21 22:17:28.995890: Epoch 2135 +2024-11-21 22:17:28.996012: Current learning rate: 0.00756 +2024-11-21 22:17:47.848986: train_loss -0.7817 +2024-11-21 22:17:47.849278: val_loss -0.7391 +2024-11-21 22:17:47.849361: Pseudo dice [0.8434] +2024-11-21 22:17:47.849437: Epoch time: 18.85 s +2024-11-21 22:17:48.671860: +2024-11-21 22:17:48.672082: Epoch 2136 +2024-11-21 22:17:48.672190: Current learning rate: 0.00756 +2024-11-21 22:18:06.997748: train_loss -0.7724 +2024-11-21 22:18:06.997985: val_loss -0.7409 +2024-11-21 22:18:06.998072: Pseudo dice [0.8492] +2024-11-21 22:18:06.998150: Epoch time: 18.33 s +2024-11-21 22:18:07.835516: +2024-11-21 22:18:07.835740: Epoch 2137 +2024-11-21 22:18:07.835854: Current learning rate: 0.00756 +2024-11-21 22:18:27.680219: train_loss -0.7882 +2024-11-21 22:18:27.680431: val_loss -0.7456 +2024-11-21 22:18:27.680503: Pseudo dice [0.8246] +2024-11-21 22:18:27.680581: Epoch time: 19.85 s +2024-11-21 22:18:28.512297: +2024-11-21 22:18:28.512603: Epoch 2138 +2024-11-21 22:18:28.512716: Current learning rate: 0.00756 +2024-11-21 22:18:47.313602: train_loss -0.7739 +2024-11-21 22:18:47.313865: val_loss -0.7584 +2024-11-21 22:18:47.313940: Pseudo dice [0.8442] +2024-11-21 22:18:47.314034: Epoch time: 18.8 s +2024-11-21 22:18:48.150112: +2024-11-21 22:18:48.150309: Epoch 2139 +2024-11-21 22:18:48.150420: Current learning rate: 0.00756 +2024-11-21 22:19:06.867813: train_loss -0.781 +2024-11-21 22:19:06.868029: val_loss -0.7497 +2024-11-21 22:19:06.868104: Pseudo dice [0.8392] +2024-11-21 22:19:06.868179: Epoch time: 18.72 s +2024-11-21 22:19:07.704983: +2024-11-21 22:19:07.705196: Epoch 2140 +2024-11-21 22:19:07.705310: Current learning rate: 0.00756 +2024-11-21 22:19:27.175657: train_loss -0.7664 +2024-11-21 22:19:27.175877: val_loss -0.6879 +2024-11-21 22:19:27.175953: Pseudo dice [0.7887] +2024-11-21 22:19:27.176042: Epoch time: 19.47 s +2024-11-21 22:19:28.011595: +2024-11-21 22:19:28.011798: Epoch 2141 +2024-11-21 22:19:28.011909: Current learning rate: 0.00756 +2024-11-21 22:19:48.405913: train_loss -0.7694 +2024-11-21 22:19:48.406141: val_loss -0.7427 +2024-11-21 22:19:48.406213: Pseudo dice [0.8521] +2024-11-21 22:19:48.406289: Epoch time: 20.4 s +2024-11-21 22:19:49.245329: +2024-11-21 22:19:49.245572: Epoch 2142 +2024-11-21 22:19:49.245689: Current learning rate: 0.00755 +2024-11-21 22:20:07.749212: train_loss -0.7771 +2024-11-21 22:20:07.749461: val_loss -0.748 +2024-11-21 22:20:07.749534: Pseudo dice [0.8447] +2024-11-21 22:20:07.749615: Epoch time: 18.5 s +2024-11-21 22:20:08.602698: +2024-11-21 22:20:08.602903: Epoch 2143 +2024-11-21 22:20:08.603016: Current learning rate: 0.00755 +2024-11-21 22:20:28.005196: train_loss -0.7743 +2024-11-21 22:20:28.005428: val_loss -0.7548 +2024-11-21 22:20:28.005508: Pseudo dice [0.8379] +2024-11-21 22:20:28.005586: Epoch time: 19.4 s +2024-11-21 22:20:29.234190: +2024-11-21 22:20:29.234416: Epoch 2144 +2024-11-21 22:20:29.234530: Current learning rate: 0.00755 +2024-11-21 22:20:47.037490: train_loss -0.7744 +2024-11-21 22:20:47.037715: val_loss -0.7547 +2024-11-21 22:20:47.037794: Pseudo dice [0.8405] +2024-11-21 22:20:47.037874: Epoch time: 17.8 s +2024-11-21 22:20:47.949214: +2024-11-21 22:20:47.949477: Epoch 2145 +2024-11-21 22:20:47.949613: Current learning rate: 0.00755 +2024-11-21 22:21:06.269034: train_loss -0.78 +2024-11-21 22:21:06.269273: val_loss -0.7323 +2024-11-21 22:21:06.269347: Pseudo dice [0.808] +2024-11-21 22:21:06.269431: Epoch time: 18.32 s +2024-11-21 22:21:07.106644: +2024-11-21 22:21:07.106968: Epoch 2146 +2024-11-21 22:21:07.107083: Current learning rate: 0.00755 +2024-11-21 22:21:25.560768: train_loss -0.7665 +2024-11-21 22:21:25.560982: val_loss -0.7397 +2024-11-21 22:21:25.561067: Pseudo dice [0.8317] +2024-11-21 22:21:25.561147: Epoch time: 18.45 s +2024-11-21 22:21:26.397424: +2024-11-21 22:21:26.397775: Epoch 2147 +2024-11-21 22:21:26.397893: Current learning rate: 0.00755 +2024-11-21 22:21:45.977461: train_loss -0.7675 +2024-11-21 22:21:45.977747: val_loss -0.7342 +2024-11-21 22:21:45.977830: Pseudo dice [0.8267] +2024-11-21 22:21:45.977915: Epoch time: 19.58 s +2024-11-21 22:21:46.817740: +2024-11-21 22:21:46.817966: Epoch 2148 +2024-11-21 22:21:46.818087: Current learning rate: 0.00755 +2024-11-21 22:22:05.605397: train_loss -0.7717 +2024-11-21 22:22:05.605614: val_loss -0.7196 +2024-11-21 22:22:05.605689: Pseudo dice [0.8347] +2024-11-21 22:22:05.605766: Epoch time: 18.79 s +2024-11-21 22:22:06.495671: +2024-11-21 22:22:06.495915: Epoch 2149 +2024-11-21 22:22:06.496062: Current learning rate: 0.00755 +2024-11-21 22:22:24.633368: train_loss -0.7671 +2024-11-21 22:22:24.633607: val_loss -0.7108 +2024-11-21 22:22:24.633682: Pseudo dice [0.8078] +2024-11-21 22:22:24.633772: Epoch time: 18.14 s +2024-11-21 22:22:25.689245: +2024-11-21 22:22:25.689453: Epoch 2150 +2024-11-21 22:22:25.689564: Current learning rate: 0.00755 +2024-11-21 22:22:43.003233: train_loss -0.7646 +2024-11-21 22:22:43.003450: val_loss -0.7459 +2024-11-21 22:22:43.003525: Pseudo dice [0.8419] +2024-11-21 22:22:43.003600: Epoch time: 17.31 s +2024-11-21 22:22:43.839271: +2024-11-21 22:22:43.839475: Epoch 2151 +2024-11-21 22:22:43.839589: Current learning rate: 0.00754 +2024-11-21 22:23:01.382487: train_loss -0.7777 +2024-11-21 22:23:01.382706: val_loss -0.7448 +2024-11-21 22:23:01.382781: Pseudo dice [0.8362] +2024-11-21 22:23:01.382862: Epoch time: 17.54 s +2024-11-21 22:23:02.359002: +2024-11-21 22:23:02.359238: Epoch 2152 +2024-11-21 22:23:02.359356: Current learning rate: 0.00754 +2024-11-21 22:23:21.011689: train_loss -0.7789 +2024-11-21 22:23:21.011900: val_loss -0.7386 +2024-11-21 22:23:21.011975: Pseudo dice [0.8243] +2024-11-21 22:23:21.012057: Epoch time: 18.65 s +2024-11-21 22:23:21.952175: +2024-11-21 22:23:21.952400: Epoch 2153 +2024-11-21 22:23:21.952514: Current learning rate: 0.00754 +2024-11-21 22:23:40.663049: train_loss -0.7758 +2024-11-21 22:23:40.663290: val_loss -0.741 +2024-11-21 22:23:40.663368: Pseudo dice [0.8359] +2024-11-21 22:23:40.663452: Epoch time: 18.71 s +2024-11-21 22:23:41.492687: +2024-11-21 22:23:41.492894: Epoch 2154 +2024-11-21 22:23:41.493016: Current learning rate: 0.00754 +2024-11-21 22:23:58.318975: train_loss -0.7775 +2024-11-21 22:23:58.323334: val_loss -0.7426 +2024-11-21 22:23:58.323426: Pseudo dice [0.8332] +2024-11-21 22:23:58.323505: Epoch time: 16.83 s +2024-11-21 22:23:59.189496: +2024-11-21 22:23:59.189700: Epoch 2155 +2024-11-21 22:23:59.189806: Current learning rate: 0.00754 +2024-11-21 22:24:18.067474: train_loss -0.7739 +2024-11-21 22:24:18.067707: val_loss -0.6953 +2024-11-21 22:24:18.067782: Pseudo dice [0.8153] +2024-11-21 22:24:18.067858: Epoch time: 18.88 s +2024-11-21 22:24:19.354429: +2024-11-21 22:24:19.354662: Epoch 2156 +2024-11-21 22:24:19.354780: Current learning rate: 0.00754 +2024-11-21 22:24:38.822779: train_loss -0.7594 +2024-11-21 22:24:38.823049: val_loss -0.7152 +2024-11-21 22:24:38.823128: Pseudo dice [0.8083] +2024-11-21 22:24:38.823207: Epoch time: 19.47 s +2024-11-21 22:24:39.666120: +2024-11-21 22:24:39.666335: Epoch 2157 +2024-11-21 22:24:39.666447: Current learning rate: 0.00754 +2024-11-21 22:24:58.843701: train_loss -0.7621 +2024-11-21 22:24:58.843929: val_loss -0.7609 +2024-11-21 22:24:58.844014: Pseudo dice [0.8339] +2024-11-21 22:24:58.844090: Epoch time: 19.18 s +2024-11-21 22:24:59.681020: +2024-11-21 22:24:59.681259: Epoch 2158 +2024-11-21 22:24:59.681374: Current learning rate: 0.00754 +2024-11-21 22:25:18.042887: train_loss -0.7792 +2024-11-21 22:25:18.043113: val_loss -0.7545 +2024-11-21 22:25:18.043188: Pseudo dice [0.8332] +2024-11-21 22:25:18.043284: Epoch time: 18.36 s +2024-11-21 22:25:18.883981: +2024-11-21 22:25:18.884258: Epoch 2159 +2024-11-21 22:25:18.884371: Current learning rate: 0.00753 +2024-11-21 22:25:38.767580: train_loss -0.7762 +2024-11-21 22:25:38.767827: val_loss -0.7375 +2024-11-21 22:25:38.767902: Pseudo dice [0.8466] +2024-11-21 22:25:38.767988: Epoch time: 19.88 s +2024-11-21 22:25:39.613427: +2024-11-21 22:25:39.613617: Epoch 2160 +2024-11-21 22:25:39.613730: Current learning rate: 0.00753 +2024-11-21 22:25:58.860606: train_loss -0.791 +2024-11-21 22:25:58.860832: val_loss -0.753 +2024-11-21 22:25:58.860915: Pseudo dice [0.8392] +2024-11-21 22:25:58.861002: Epoch time: 19.25 s +2024-11-21 22:25:59.699528: +2024-11-21 22:25:59.699811: Epoch 2161 +2024-11-21 22:25:59.699935: Current learning rate: 0.00753 +2024-11-21 22:26:17.984587: train_loss -0.7753 +2024-11-21 22:26:17.984811: val_loss -0.7466 +2024-11-21 22:26:17.984889: Pseudo dice [0.8057] +2024-11-21 22:26:17.984970: Epoch time: 18.29 s +2024-11-21 22:26:18.826639: +2024-11-21 22:26:18.826860: Epoch 2162 +2024-11-21 22:26:18.826981: Current learning rate: 0.00753 +2024-11-21 22:26:37.324323: train_loss -0.7721 +2024-11-21 22:26:37.326811: val_loss -0.7594 +2024-11-21 22:26:37.326980: Pseudo dice [0.8491] +2024-11-21 22:26:37.327077: Epoch time: 18.5 s +2024-11-21 22:26:38.183763: +2024-11-21 22:26:38.184031: Epoch 2163 +2024-11-21 22:26:38.184145: Current learning rate: 0.00753 +2024-11-21 22:26:56.112261: train_loss -0.7779 +2024-11-21 22:26:56.112581: val_loss -0.7615 +2024-11-21 22:26:56.112666: Pseudo dice [0.8501] +2024-11-21 22:26:56.112748: Epoch time: 17.93 s +2024-11-21 22:26:56.955784: +2024-11-21 22:26:56.956075: Epoch 2164 +2024-11-21 22:26:56.956188: Current learning rate: 0.00753 +2024-11-21 22:27:15.582766: train_loss -0.7737 +2024-11-21 22:27:15.583003: val_loss -0.738 +2024-11-21 22:27:15.583079: Pseudo dice [0.8435] +2024-11-21 22:27:15.583156: Epoch time: 18.63 s +2024-11-21 22:27:16.419340: +2024-11-21 22:27:16.419550: Epoch 2165 +2024-11-21 22:27:16.419662: Current learning rate: 0.00753 +2024-11-21 22:27:35.443614: train_loss -0.78 +2024-11-21 22:27:35.443832: val_loss -0.7424 +2024-11-21 22:27:35.443907: Pseudo dice [0.8287] +2024-11-21 22:27:35.443982: Epoch time: 19.03 s +2024-11-21 22:27:36.383592: +2024-11-21 22:27:36.383851: Epoch 2166 +2024-11-21 22:27:36.383967: Current learning rate: 0.00753 +2024-11-21 22:27:54.151812: train_loss -0.7866 +2024-11-21 22:27:54.152038: val_loss -0.7428 +2024-11-21 22:27:54.152115: Pseudo dice [0.808] +2024-11-21 22:27:54.152260: Epoch time: 17.77 s +2024-11-21 22:27:54.989836: +2024-11-21 22:27:54.990050: Epoch 2167 +2024-11-21 22:27:54.990160: Current learning rate: 0.00753 +2024-11-21 22:28:13.838606: train_loss -0.7768 +2024-11-21 22:28:13.838856: val_loss -0.7209 +2024-11-21 22:28:13.838933: Pseudo dice [0.8434] +2024-11-21 22:28:13.839022: Epoch time: 18.85 s +2024-11-21 22:28:15.100606: +2024-11-21 22:28:15.100821: Epoch 2168 +2024-11-21 22:28:15.100932: Current learning rate: 0.00752 +2024-11-21 22:28:34.250436: train_loss -0.781 +2024-11-21 22:28:34.250659: val_loss -0.7287 +2024-11-21 22:28:34.250737: Pseudo dice [0.831] +2024-11-21 22:28:34.250815: Epoch time: 19.15 s +2024-11-21 22:28:35.090889: +2024-11-21 22:28:35.091112: Epoch 2169 +2024-11-21 22:28:35.091228: Current learning rate: 0.00752 +2024-11-21 22:28:53.687715: train_loss -0.7813 +2024-11-21 22:28:53.693129: val_loss -0.7156 +2024-11-21 22:28:53.693211: Pseudo dice [0.8269] +2024-11-21 22:28:53.693294: Epoch time: 18.6 s +2024-11-21 22:28:54.765944: +2024-11-21 22:28:54.766187: Epoch 2170 +2024-11-21 22:28:54.766301: Current learning rate: 0.00752 +2024-11-21 22:29:14.484006: train_loss -0.7772 +2024-11-21 22:29:14.484270: val_loss -0.752 +2024-11-21 22:29:14.484350: Pseudo dice [0.8438] +2024-11-21 22:29:14.484432: Epoch time: 19.72 s +2024-11-21 22:29:15.320455: +2024-11-21 22:29:15.320765: Epoch 2171 +2024-11-21 22:29:15.320877: Current learning rate: 0.00752 +2024-11-21 22:29:34.334130: train_loss -0.7833 +2024-11-21 22:29:34.334342: val_loss -0.7624 +2024-11-21 22:29:34.334416: Pseudo dice [0.8381] +2024-11-21 22:29:34.334494: Epoch time: 19.01 s +2024-11-21 22:29:35.169060: +2024-11-21 22:29:35.169272: Epoch 2172 +2024-11-21 22:29:35.169389: Current learning rate: 0.00752 +2024-11-21 22:29:53.206236: train_loss -0.7794 +2024-11-21 22:29:53.206456: val_loss -0.7625 +2024-11-21 22:29:53.206532: Pseudo dice [0.8414] +2024-11-21 22:29:53.206608: Epoch time: 18.04 s +2024-11-21 22:29:54.048144: +2024-11-21 22:29:54.048350: Epoch 2173 +2024-11-21 22:29:54.048457: Current learning rate: 0.00752 +2024-11-21 22:30:12.504739: train_loss -0.7807 +2024-11-21 22:30:12.504968: val_loss -0.7238 +2024-11-21 22:30:12.505055: Pseudo dice [0.8496] +2024-11-21 22:30:12.505137: Epoch time: 18.46 s +2024-11-21 22:30:13.349126: +2024-11-21 22:30:13.349320: Epoch 2174 +2024-11-21 22:30:13.349437: Current learning rate: 0.00752 +2024-11-21 22:30:32.383610: train_loss -0.78 +2024-11-21 22:30:32.383838: val_loss -0.7355 +2024-11-21 22:30:32.383913: Pseudo dice [0.8379] +2024-11-21 22:30:32.383999: Epoch time: 19.04 s +2024-11-21 22:30:33.219760: +2024-11-21 22:30:33.220052: Epoch 2175 +2024-11-21 22:30:33.220165: Current learning rate: 0.00752 +2024-11-21 22:30:52.701285: train_loss -0.7804 +2024-11-21 22:30:52.701493: val_loss -0.7502 +2024-11-21 22:30:52.701568: Pseudo dice [0.8417] +2024-11-21 22:30:52.706851: Epoch time: 19.48 s +2024-11-21 22:30:53.601883: +2024-11-21 22:30:53.602092: Epoch 2176 +2024-11-21 22:30:53.602204: Current learning rate: 0.00751 +2024-11-21 22:31:12.818332: train_loss -0.7745 +2024-11-21 22:31:12.818544: val_loss -0.7534 +2024-11-21 22:31:12.818621: Pseudo dice [0.8475] +2024-11-21 22:31:12.818697: Epoch time: 19.22 s +2024-11-21 22:31:13.725018: +2024-11-21 22:31:13.725262: Epoch 2177 +2024-11-21 22:31:13.725378: Current learning rate: 0.00751 +2024-11-21 22:31:32.073288: train_loss -0.7608 +2024-11-21 22:31:32.073529: val_loss -0.7376 +2024-11-21 22:31:32.073603: Pseudo dice [0.8417] +2024-11-21 22:31:32.073689: Epoch time: 18.35 s +2024-11-21 22:31:32.915878: +2024-11-21 22:31:32.916093: Epoch 2178 +2024-11-21 22:31:32.916205: Current learning rate: 0.00751 +2024-11-21 22:31:52.214351: train_loss -0.7683 +2024-11-21 22:31:52.214568: val_loss -0.7362 +2024-11-21 22:31:52.214702: Pseudo dice [0.8255] +2024-11-21 22:31:52.214782: Epoch time: 19.3 s +2024-11-21 22:31:53.050324: +2024-11-21 22:31:53.050527: Epoch 2179 +2024-11-21 22:31:53.050639: Current learning rate: 0.00751 +2024-11-21 22:32:11.924046: train_loss -0.7703 +2024-11-21 22:32:11.924264: val_loss -0.7134 +2024-11-21 22:32:11.924350: Pseudo dice [0.8337] +2024-11-21 22:32:11.924429: Epoch time: 18.87 s +2024-11-21 22:32:13.163539: +2024-11-21 22:32:13.163747: Epoch 2180 +2024-11-21 22:32:13.163857: Current learning rate: 0.00751 +2024-11-21 22:32:31.594649: train_loss -0.7669 +2024-11-21 22:32:31.594909: val_loss -0.7447 +2024-11-21 22:32:31.594987: Pseudo dice [0.8434] +2024-11-21 22:32:31.595083: Epoch time: 18.43 s +2024-11-21 22:32:32.429345: +2024-11-21 22:32:32.429567: Epoch 2181 +2024-11-21 22:32:32.429681: Current learning rate: 0.00751 +2024-11-21 22:32:51.054042: train_loss -0.791 +2024-11-21 22:32:51.054262: val_loss -0.7472 +2024-11-21 22:32:51.054337: Pseudo dice [0.8444] +2024-11-21 22:32:51.054411: Epoch time: 18.63 s +2024-11-21 22:32:51.889760: +2024-11-21 22:32:51.889969: Epoch 2182 +2024-11-21 22:32:51.890083: Current learning rate: 0.00751 +2024-11-21 22:33:10.502516: train_loss -0.7835 +2024-11-21 22:33:10.502757: val_loss -0.7498 +2024-11-21 22:33:10.502839: Pseudo dice [0.8555] +2024-11-21 22:33:10.502918: Epoch time: 18.61 s +2024-11-21 22:33:11.494753: +2024-11-21 22:33:11.495028: Epoch 2183 +2024-11-21 22:33:11.495145: Current learning rate: 0.00751 +2024-11-21 22:33:30.788632: train_loss -0.7746 +2024-11-21 22:33:30.788882: val_loss -0.7571 +2024-11-21 22:33:30.788956: Pseudo dice [0.8461] +2024-11-21 22:33:30.789051: Epoch time: 19.29 s +2024-11-21 22:33:31.732851: +2024-11-21 22:33:31.733063: Epoch 2184 +2024-11-21 22:33:31.733174: Current learning rate: 0.00751 +2024-11-21 22:33:50.791726: train_loss -0.781 +2024-11-21 22:33:50.791948: val_loss -0.7212 +2024-11-21 22:33:50.792032: Pseudo dice [0.8236] +2024-11-21 22:33:50.792111: Epoch time: 19.06 s +2024-11-21 22:33:51.626903: +2024-11-21 22:33:51.627313: Epoch 2185 +2024-11-21 22:33:51.627429: Current learning rate: 0.0075 +2024-11-21 22:34:09.882942: train_loss -0.7697 +2024-11-21 22:34:09.883195: val_loss -0.7416 +2024-11-21 22:34:09.883283: Pseudo dice [0.8205] +2024-11-21 22:34:09.883363: Epoch time: 18.26 s +2024-11-21 22:34:10.723159: +2024-11-21 22:34:10.723431: Epoch 2186 +2024-11-21 22:34:10.723546: Current learning rate: 0.0075 +2024-11-21 22:34:29.706835: train_loss -0.7833 +2024-11-21 22:34:29.707110: val_loss -0.7282 +2024-11-21 22:34:29.707184: Pseudo dice [0.8324] +2024-11-21 22:34:29.707261: Epoch time: 18.98 s +2024-11-21 22:34:30.542469: +2024-11-21 22:34:30.542692: Epoch 2187 +2024-11-21 22:34:30.542802: Current learning rate: 0.0075 +2024-11-21 22:34:49.729116: train_loss -0.7715 +2024-11-21 22:34:49.729342: val_loss -0.7635 +2024-11-21 22:34:49.729428: Pseudo dice [0.8351] +2024-11-21 22:34:49.729517: Epoch time: 19.19 s +2024-11-21 22:34:50.571309: +2024-11-21 22:34:50.571549: Epoch 2188 +2024-11-21 22:34:50.571699: Current learning rate: 0.0075 +2024-11-21 22:35:09.565129: train_loss -0.7421 +2024-11-21 22:35:09.565352: val_loss -0.7488 +2024-11-21 22:35:09.565426: Pseudo dice [0.8509] +2024-11-21 22:35:09.565503: Epoch time: 18.99 s +2024-11-21 22:35:10.398077: +2024-11-21 22:35:10.398319: Epoch 2189 +2024-11-21 22:35:10.398431: Current learning rate: 0.0075 +2024-11-21 22:35:30.661557: train_loss -0.7698 +2024-11-21 22:35:30.661776: val_loss -0.7565 +2024-11-21 22:35:30.661849: Pseudo dice [0.8104] +2024-11-21 22:35:30.661928: Epoch time: 20.26 s +2024-11-21 22:35:31.624661: +2024-11-21 22:35:31.624997: Epoch 2190 +2024-11-21 22:35:31.625110: Current learning rate: 0.0075 +2024-11-21 22:35:50.314673: train_loss -0.7623 +2024-11-21 22:35:50.314966: val_loss -0.7286 +2024-11-21 22:35:50.315054: Pseudo dice [0.8315] +2024-11-21 22:35:50.315142: Epoch time: 18.69 s +2024-11-21 22:35:51.154033: +2024-11-21 22:35:51.154351: Epoch 2191 +2024-11-21 22:35:51.154503: Current learning rate: 0.0075 +2024-11-21 22:36:09.731861: train_loss -0.773 +2024-11-21 22:36:09.732075: val_loss -0.7431 +2024-11-21 22:36:09.732147: Pseudo dice [0.8417] +2024-11-21 22:36:09.732223: Epoch time: 18.58 s +2024-11-21 22:36:10.983619: +2024-11-21 22:36:10.983836: Epoch 2192 +2024-11-21 22:36:10.983946: Current learning rate: 0.0075 +2024-11-21 22:36:29.730422: train_loss -0.7719 +2024-11-21 22:36:29.730648: val_loss -0.7283 +2024-11-21 22:36:29.730731: Pseudo dice [0.8509] +2024-11-21 22:36:29.730805: Epoch time: 18.75 s +2024-11-21 22:36:30.560387: +2024-11-21 22:36:30.560594: Epoch 2193 +2024-11-21 22:36:30.560715: Current learning rate: 0.0075 +2024-11-21 22:36:48.632524: train_loss -0.7743 +2024-11-21 22:36:48.632759: val_loss -0.7205 +2024-11-21 22:36:48.635062: Pseudo dice [0.8276] +2024-11-21 22:36:48.635492: Epoch time: 18.07 s +2024-11-21 22:36:49.488984: +2024-11-21 22:36:49.489258: Epoch 2194 +2024-11-21 22:36:49.489369: Current learning rate: 0.00749 +2024-11-21 22:37:07.621383: train_loss -0.7608 +2024-11-21 22:37:07.621634: val_loss -0.7009 +2024-11-21 22:37:07.621778: Pseudo dice [0.8024] +2024-11-21 22:37:07.621859: Epoch time: 18.13 s +2024-11-21 22:37:08.460143: +2024-11-21 22:37:08.460380: Epoch 2195 +2024-11-21 22:37:08.460491: Current learning rate: 0.00749 +2024-11-21 22:37:26.393806: train_loss -0.7719 +2024-11-21 22:37:26.394067: val_loss -0.7525 +2024-11-21 22:37:26.394145: Pseudo dice [0.8531] +2024-11-21 22:37:26.394223: Epoch time: 17.93 s +2024-11-21 22:37:27.236526: +2024-11-21 22:37:27.236747: Epoch 2196 +2024-11-21 22:37:27.236857: Current learning rate: 0.00749 +2024-11-21 22:37:46.061412: train_loss -0.7728 +2024-11-21 22:37:46.061663: val_loss -0.7376 +2024-11-21 22:37:46.061743: Pseudo dice [0.848] +2024-11-21 22:37:46.061840: Epoch time: 18.83 s +2024-11-21 22:37:47.065225: +2024-11-21 22:37:47.065418: Epoch 2197 +2024-11-21 22:37:47.065531: Current learning rate: 0.00749 +2024-11-21 22:38:07.149859: train_loss -0.7709 +2024-11-21 22:38:07.150115: val_loss -0.7288 +2024-11-21 22:38:07.150197: Pseudo dice [0.8303] +2024-11-21 22:38:07.150281: Epoch time: 20.09 s +2024-11-21 22:38:07.986926: +2024-11-21 22:38:07.987146: Epoch 2198 +2024-11-21 22:38:07.987258: Current learning rate: 0.00749 +2024-11-21 22:38:26.024236: train_loss -0.7691 +2024-11-21 22:38:26.024448: val_loss -0.732 +2024-11-21 22:38:26.024523: Pseudo dice [0.8282] +2024-11-21 22:38:26.024598: Epoch time: 18.04 s +2024-11-21 22:38:26.854281: +2024-11-21 22:38:26.854471: Epoch 2199 +2024-11-21 22:38:26.854580: Current learning rate: 0.00749 +2024-11-21 22:38:45.381194: train_loss -0.7727 +2024-11-21 22:38:45.381430: val_loss -0.7198 +2024-11-21 22:38:45.381509: Pseudo dice [0.8375] +2024-11-21 22:38:45.381588: Epoch time: 18.53 s +2024-11-21 22:38:46.437943: +2024-11-21 22:38:46.438162: Epoch 2200 +2024-11-21 22:38:46.438276: Current learning rate: 0.00749 +2024-11-21 22:39:04.398678: train_loss -0.7813 +2024-11-21 22:39:04.398944: val_loss -0.7481 +2024-11-21 22:39:04.399032: Pseudo dice [0.8507] +2024-11-21 22:39:04.399119: Epoch time: 17.96 s +2024-11-21 22:39:05.304852: +2024-11-21 22:39:05.305117: Epoch 2201 +2024-11-21 22:39:05.305228: Current learning rate: 0.00749 +2024-11-21 22:39:23.148394: train_loss -0.774 +2024-11-21 22:39:23.148625: val_loss -0.7358 +2024-11-21 22:39:23.148704: Pseudo dice [0.8301] +2024-11-21 22:39:23.148785: Epoch time: 17.84 s +2024-11-21 22:39:24.001190: +2024-11-21 22:39:24.001574: Epoch 2202 +2024-11-21 22:39:24.001686: Current learning rate: 0.00748 +2024-11-21 22:39:42.864975: train_loss -0.7673 +2024-11-21 22:39:42.865197: val_loss -0.7362 +2024-11-21 22:39:42.865271: Pseudo dice [0.8463] +2024-11-21 22:39:42.865345: Epoch time: 18.86 s +2024-11-21 22:39:43.803334: +2024-11-21 22:39:43.803555: Epoch 2203 +2024-11-21 22:39:43.803667: Current learning rate: 0.00748 +2024-11-21 22:40:01.123626: train_loss -0.7896 +2024-11-21 22:40:01.123847: val_loss -0.7501 +2024-11-21 22:40:01.123922: Pseudo dice [0.8597] +2024-11-21 22:40:01.124033: Epoch time: 17.32 s +2024-11-21 22:40:02.327505: +2024-11-21 22:40:02.327782: Epoch 2204 +2024-11-21 22:40:02.327901: Current learning rate: 0.00748 +2024-11-21 22:40:21.257405: train_loss -0.7664 +2024-11-21 22:40:21.257652: val_loss -0.7239 +2024-11-21 22:40:21.257727: Pseudo dice [0.8481] +2024-11-21 22:40:21.257806: Epoch time: 18.93 s +2024-11-21 22:40:22.092138: +2024-11-21 22:40:22.092342: Epoch 2205 +2024-11-21 22:40:22.092454: Current learning rate: 0.00748 +2024-11-21 22:40:41.217467: train_loss -0.7741 +2024-11-21 22:40:41.217688: val_loss -0.7355 +2024-11-21 22:40:41.217766: Pseudo dice [0.84] +2024-11-21 22:40:41.217843: Epoch time: 19.13 s +2024-11-21 22:40:42.054521: +2024-11-21 22:40:42.054737: Epoch 2206 +2024-11-21 22:40:42.054848: Current learning rate: 0.00748 +2024-11-21 22:41:01.111090: train_loss -0.762 +2024-11-21 22:41:01.111325: val_loss -0.7291 +2024-11-21 22:41:01.111399: Pseudo dice [0.8452] +2024-11-21 22:41:01.111479: Epoch time: 19.06 s +2024-11-21 22:41:02.136439: +2024-11-21 22:41:02.136652: Epoch 2207 +2024-11-21 22:41:02.136763: Current learning rate: 0.00748 +2024-11-21 22:41:20.689891: train_loss -0.7727 +2024-11-21 22:41:20.690142: val_loss -0.7312 +2024-11-21 22:41:20.690227: Pseudo dice [0.8298] +2024-11-21 22:41:20.690311: Epoch time: 18.55 s +2024-11-21 22:41:21.528102: +2024-11-21 22:41:21.528321: Epoch 2208 +2024-11-21 22:41:21.528435: Current learning rate: 0.00748 +2024-11-21 22:41:41.340203: train_loss -0.7682 +2024-11-21 22:41:41.340423: val_loss -0.733 +2024-11-21 22:41:41.340505: Pseudo dice [0.8477] +2024-11-21 22:41:41.340583: Epoch time: 19.81 s +2024-11-21 22:41:42.180913: +2024-11-21 22:41:42.181152: Epoch 2209 +2024-11-21 22:41:42.181267: Current learning rate: 0.00748 +2024-11-21 22:42:01.036689: train_loss -0.7753 +2024-11-21 22:42:01.036910: val_loss -0.7271 +2024-11-21 22:42:01.036986: Pseudo dice [0.835] +2024-11-21 22:42:01.037068: Epoch time: 18.86 s +2024-11-21 22:42:01.871704: +2024-11-21 22:42:01.871905: Epoch 2210 +2024-11-21 22:42:01.872026: Current learning rate: 0.00748 +2024-11-21 22:42:20.438076: train_loss -0.7815 +2024-11-21 22:42:20.438292: val_loss -0.7423 +2024-11-21 22:42:20.438369: Pseudo dice [0.827] +2024-11-21 22:42:20.438446: Epoch time: 18.57 s +2024-11-21 22:42:21.274096: +2024-11-21 22:42:21.274314: Epoch 2211 +2024-11-21 22:42:21.274432: Current learning rate: 0.00747 +2024-11-21 22:42:39.141925: train_loss -0.7762 +2024-11-21 22:42:39.142185: val_loss -0.7501 +2024-11-21 22:42:39.142265: Pseudo dice [0.8314] +2024-11-21 22:42:39.142350: Epoch time: 17.87 s +2024-11-21 22:42:39.983581: +2024-11-21 22:42:39.983829: Epoch 2212 +2024-11-21 22:42:39.983943: Current learning rate: 0.00747 +2024-11-21 22:42:57.731071: train_loss -0.7826 +2024-11-21 22:42:57.731286: val_loss -0.7173 +2024-11-21 22:42:57.731365: Pseudo dice [0.8331] +2024-11-21 22:42:57.731443: Epoch time: 17.75 s +2024-11-21 22:42:58.584471: +2024-11-21 22:42:58.584682: Epoch 2213 +2024-11-21 22:42:58.584792: Current learning rate: 0.00747 +2024-11-21 22:43:17.651745: train_loss -0.7687 +2024-11-21 22:43:17.651976: val_loss -0.7232 +2024-11-21 22:43:17.652065: Pseudo dice [0.8305] +2024-11-21 22:43:17.652147: Epoch time: 19.07 s +2024-11-21 22:43:18.638921: +2024-11-21 22:43:18.639186: Epoch 2214 +2024-11-21 22:43:18.639301: Current learning rate: 0.00747 +2024-11-21 22:43:36.439182: train_loss -0.7801 +2024-11-21 22:43:36.439443: val_loss -0.7239 +2024-11-21 22:43:36.439524: Pseudo dice [0.8387] +2024-11-21 22:43:36.439607: Epoch time: 17.8 s +2024-11-21 22:43:37.280172: +2024-11-21 22:43:37.280366: Epoch 2215 +2024-11-21 22:43:37.280476: Current learning rate: 0.00747 +2024-11-21 22:43:56.663117: train_loss -0.7761 +2024-11-21 22:43:56.664465: val_loss -0.7251 +2024-11-21 22:43:56.664564: Pseudo dice [0.8246] +2024-11-21 22:43:56.664649: Epoch time: 19.38 s +2024-11-21 22:43:57.899738: +2024-11-21 22:43:57.899975: Epoch 2216 +2024-11-21 22:43:57.900100: Current learning rate: 0.00747 +2024-11-21 22:44:16.478080: train_loss -0.7707 +2024-11-21 22:44:16.478306: val_loss -0.7516 +2024-11-21 22:44:16.478382: Pseudo dice [0.8371] +2024-11-21 22:44:16.478460: Epoch time: 18.58 s +2024-11-21 22:44:17.367497: +2024-11-21 22:44:17.367784: Epoch 2217 +2024-11-21 22:44:17.367896: Current learning rate: 0.00747 +2024-11-21 22:44:35.413860: train_loss -0.7804 +2024-11-21 22:44:35.414111: val_loss -0.7262 +2024-11-21 22:44:35.414200: Pseudo dice [0.8187] +2024-11-21 22:44:35.414291: Epoch time: 18.05 s +2024-11-21 22:44:36.250185: +2024-11-21 22:44:36.250400: Epoch 2218 +2024-11-21 22:44:36.250507: Current learning rate: 0.00747 +2024-11-21 22:44:55.145292: train_loss -0.7821 +2024-11-21 22:44:55.145515: val_loss -0.7574 +2024-11-21 22:44:55.145596: Pseudo dice [0.8254] +2024-11-21 22:44:55.145674: Epoch time: 18.9 s +2024-11-21 22:44:56.081300: +2024-11-21 22:44:56.081504: Epoch 2219 +2024-11-21 22:44:56.081618: Current learning rate: 0.00746 +2024-11-21 22:45:14.836353: train_loss -0.7678 +2024-11-21 22:45:14.836580: val_loss -0.7236 +2024-11-21 22:45:14.836655: Pseudo dice [0.8137] +2024-11-21 22:45:14.837013: Epoch time: 18.76 s +2024-11-21 22:45:15.744246: +2024-11-21 22:45:15.744503: Epoch 2220 +2024-11-21 22:45:15.744614: Current learning rate: 0.00746 +2024-11-21 22:45:34.311947: train_loss -0.7727 +2024-11-21 22:45:34.326029: val_loss -0.7446 +2024-11-21 22:45:34.326171: Pseudo dice [0.8407] +2024-11-21 22:45:34.326259: Epoch time: 18.57 s +2024-11-21 22:45:35.199267: +2024-11-21 22:45:35.199463: Epoch 2221 +2024-11-21 22:45:35.199574: Current learning rate: 0.00746 +2024-11-21 22:45:53.277375: train_loss -0.7855 +2024-11-21 22:45:53.277620: val_loss -0.7621 +2024-11-21 22:45:53.277695: Pseudo dice [0.8527] +2024-11-21 22:45:53.277777: Epoch time: 18.08 s +2024-11-21 22:45:54.115138: +2024-11-21 22:45:54.115397: Epoch 2222 +2024-11-21 22:45:54.115510: Current learning rate: 0.00746 +2024-11-21 22:46:13.263272: train_loss -0.7791 +2024-11-21 22:46:13.263494: val_loss -0.7347 +2024-11-21 22:46:13.263570: Pseudo dice [0.82] +2024-11-21 22:46:13.263646: Epoch time: 19.15 s +2024-11-21 22:46:14.094879: +2024-11-21 22:46:14.095084: Epoch 2223 +2024-11-21 22:46:14.095195: Current learning rate: 0.00746 +2024-11-21 22:46:33.452429: train_loss -0.7807 +2024-11-21 22:46:33.452662: val_loss -0.739 +2024-11-21 22:46:33.452737: Pseudo dice [0.8614] +2024-11-21 22:46:33.452811: Epoch time: 19.36 s +2024-11-21 22:46:34.295584: +2024-11-21 22:46:34.295792: Epoch 2224 +2024-11-21 22:46:34.295912: Current learning rate: 0.00746 +2024-11-21 22:46:51.634514: train_loss -0.77 +2024-11-21 22:46:51.634737: val_loss -0.7618 +2024-11-21 22:46:51.634809: Pseudo dice [0.8495] +2024-11-21 22:46:51.634892: Epoch time: 17.34 s +2024-11-21 22:46:52.525722: +2024-11-21 22:46:52.525989: Epoch 2225 +2024-11-21 22:46:52.526147: Current learning rate: 0.00746 +2024-11-21 22:47:10.520379: train_loss -0.7636 +2024-11-21 22:47:10.520595: val_loss -0.7299 +2024-11-21 22:47:10.522852: Pseudo dice [0.839] +2024-11-21 22:47:10.522944: Epoch time: 18.0 s +2024-11-21 22:47:11.473326: +2024-11-21 22:47:11.473519: Epoch 2226 +2024-11-21 22:47:11.473629: Current learning rate: 0.00746 +2024-11-21 22:47:30.561135: train_loss -0.7569 +2024-11-21 22:47:30.561362: val_loss -0.7317 +2024-11-21 22:47:30.561445: Pseudo dice [0.8272] +2024-11-21 22:47:30.561526: Epoch time: 19.09 s +2024-11-21 22:47:31.403376: +2024-11-21 22:47:31.403658: Epoch 2227 +2024-11-21 22:47:31.403773: Current learning rate: 0.00746 +2024-11-21 22:47:49.597666: train_loss -0.7597 +2024-11-21 22:47:49.597882: val_loss -0.7336 +2024-11-21 22:47:49.597957: Pseudo dice [0.8251] +2024-11-21 22:47:49.598040: Epoch time: 18.2 s +2024-11-21 22:47:50.817071: +2024-11-21 22:47:50.817604: Epoch 2228 +2024-11-21 22:47:50.817752: Current learning rate: 0.00745 +2024-11-21 22:48:09.215883: train_loss -0.7746 +2024-11-21 22:48:09.218353: val_loss -0.7399 +2024-11-21 22:48:09.218472: Pseudo dice [0.8482] +2024-11-21 22:48:09.218559: Epoch time: 18.4 s +2024-11-21 22:48:10.203199: +2024-11-21 22:48:10.203627: Epoch 2229 +2024-11-21 22:48:10.203758: Current learning rate: 0.00745 +2024-11-21 22:48:27.846054: train_loss -0.7528 +2024-11-21 22:48:27.846277: val_loss -0.7424 +2024-11-21 22:48:27.846352: Pseudo dice [0.8349] +2024-11-21 22:48:27.846430: Epoch time: 17.64 s +2024-11-21 22:48:28.682121: +2024-11-21 22:48:28.682586: Epoch 2230 +2024-11-21 22:48:28.682724: Current learning rate: 0.00745 +2024-11-21 22:48:47.075827: train_loss -0.7692 +2024-11-21 22:48:47.076129: val_loss -0.7536 +2024-11-21 22:48:47.076216: Pseudo dice [0.8442] +2024-11-21 22:48:47.076301: Epoch time: 18.39 s +2024-11-21 22:48:47.909516: +2024-11-21 22:48:47.910190: Epoch 2231 +2024-11-21 22:48:47.910327: Current learning rate: 0.00745 +2024-11-21 22:49:07.072851: train_loss -0.7728 +2024-11-21 22:49:07.073108: val_loss -0.7563 +2024-11-21 22:49:07.073184: Pseudo dice [0.8492] +2024-11-21 22:49:07.073270: Epoch time: 19.16 s +2024-11-21 22:49:07.907591: +2024-11-21 22:49:07.908028: Epoch 2232 +2024-11-21 22:49:07.908163: Current learning rate: 0.00745 +2024-11-21 22:49:25.813416: train_loss -0.7793 +2024-11-21 22:49:25.813630: val_loss -0.7667 +2024-11-21 22:49:25.813701: Pseudo dice [0.8542] +2024-11-21 22:49:25.813778: Epoch time: 17.91 s +2024-11-21 22:49:26.685649: +2024-11-21 22:49:26.686078: Epoch 2233 +2024-11-21 22:49:26.686217: Current learning rate: 0.00745 +2024-11-21 22:49:45.226458: train_loss -0.7816 +2024-11-21 22:49:45.226671: val_loss -0.7293 +2024-11-21 22:49:45.226745: Pseudo dice [0.8377] +2024-11-21 22:49:45.226822: Epoch time: 18.54 s +2024-11-21 22:49:46.061140: +2024-11-21 22:49:46.061582: Epoch 2234 +2024-11-21 22:49:46.061714: Current learning rate: 0.00745 +2024-11-21 22:50:03.843426: train_loss -0.7777 +2024-11-21 22:50:03.843641: val_loss -0.7434 +2024-11-21 22:50:03.843714: Pseudo dice [0.8242] +2024-11-21 22:50:03.843791: Epoch time: 17.78 s +2024-11-21 22:50:04.675034: +2024-11-21 22:50:04.675540: Epoch 2235 +2024-11-21 22:50:04.675677: Current learning rate: 0.00745 +2024-11-21 22:50:23.187392: train_loss -0.7845 +2024-11-21 22:50:23.187638: val_loss -0.751 +2024-11-21 22:50:23.187714: Pseudo dice [0.8589] +2024-11-21 22:50:23.187798: Epoch time: 18.51 s +2024-11-21 22:50:24.042733: +2024-11-21 22:50:24.043171: Epoch 2236 +2024-11-21 22:50:24.043313: Current learning rate: 0.00745 +2024-11-21 22:50:41.563006: train_loss -0.7844 +2024-11-21 22:50:41.563274: val_loss -0.7468 +2024-11-21 22:50:41.563355: Pseudo dice [0.822] +2024-11-21 22:50:41.563430: Epoch time: 17.52 s +2024-11-21 22:50:42.389689: +2024-11-21 22:50:42.390163: Epoch 2237 +2024-11-21 22:50:42.390300: Current learning rate: 0.00744 +2024-11-21 22:51:00.692069: train_loss -0.7824 +2024-11-21 22:51:00.692286: val_loss -0.7208 +2024-11-21 22:51:00.692360: Pseudo dice [0.8167] +2024-11-21 22:51:00.692435: Epoch time: 18.3 s +2024-11-21 22:51:01.517035: +2024-11-21 22:51:01.517454: Epoch 2238 +2024-11-21 22:51:01.517583: Current learning rate: 0.00744 +2024-11-21 22:51:20.112367: train_loss -0.786 +2024-11-21 22:51:20.112623: val_loss -0.7335 +2024-11-21 22:51:20.112699: Pseudo dice [0.8429] +2024-11-21 22:51:20.112780: Epoch time: 18.6 s +2024-11-21 22:51:20.942103: +2024-11-21 22:51:20.942305: Epoch 2239 +2024-11-21 22:51:20.942419: Current learning rate: 0.00744 +2024-11-21 22:51:39.434191: train_loss -0.7764 +2024-11-21 22:51:39.434415: val_loss -0.7521 +2024-11-21 22:51:39.434491: Pseudo dice [0.8388] +2024-11-21 22:51:39.434566: Epoch time: 18.49 s +2024-11-21 22:51:40.759736: +2024-11-21 22:51:40.759972: Epoch 2240 +2024-11-21 22:51:40.760100: Current learning rate: 0.00744 +2024-11-21 22:51:59.279825: train_loss -0.7833 +2024-11-21 22:51:59.280056: val_loss -0.7579 +2024-11-21 22:51:59.280130: Pseudo dice [0.8361] +2024-11-21 22:51:59.280207: Epoch time: 18.52 s +2024-11-21 22:52:00.170546: +2024-11-21 22:52:00.170776: Epoch 2241 +2024-11-21 22:52:00.170892: Current learning rate: 0.00744 +2024-11-21 22:52:18.982208: train_loss -0.7778 +2024-11-21 22:52:18.984219: val_loss -0.7427 +2024-11-21 22:52:18.984314: Pseudo dice [0.8404] +2024-11-21 22:52:18.984404: Epoch time: 18.81 s +2024-11-21 22:52:19.880025: +2024-11-21 22:52:19.880260: Epoch 2242 +2024-11-21 22:52:19.880374: Current learning rate: 0.00744 +2024-11-21 22:52:38.807406: train_loss -0.7783 +2024-11-21 22:52:38.807618: val_loss -0.7514 +2024-11-21 22:52:38.812860: Pseudo dice [0.8498] +2024-11-21 22:52:38.813081: Epoch time: 18.93 s +2024-11-21 22:52:39.663902: +2024-11-21 22:52:39.664143: Epoch 2243 +2024-11-21 22:52:39.664260: Current learning rate: 0.00744 +2024-11-21 22:52:57.017275: train_loss -0.788 +2024-11-21 22:52:57.017499: val_loss -0.7456 +2024-11-21 22:52:57.017637: Pseudo dice [0.8266] +2024-11-21 22:52:57.017719: Epoch time: 17.35 s +2024-11-21 22:52:57.858676: +2024-11-21 22:52:57.858877: Epoch 2244 +2024-11-21 22:52:57.858988: Current learning rate: 0.00744 +2024-11-21 22:53:16.012689: train_loss -0.7809 +2024-11-21 22:53:16.012998: val_loss -0.7383 +2024-11-21 22:53:16.013078: Pseudo dice [0.8242] +2024-11-21 22:53:16.013158: Epoch time: 18.15 s +2024-11-21 22:53:16.858978: +2024-11-21 22:53:16.859244: Epoch 2245 +2024-11-21 22:53:16.859355: Current learning rate: 0.00743 +2024-11-21 22:53:35.958517: train_loss -0.7797 +2024-11-21 22:53:35.958748: val_loss -0.7103 +2024-11-21 22:53:35.958823: Pseudo dice [0.8223] +2024-11-21 22:53:35.959137: Epoch time: 19.1 s +2024-11-21 22:53:36.802910: +2024-11-21 22:53:36.803122: Epoch 2246 +2024-11-21 22:53:36.803241: Current learning rate: 0.00743 +2024-11-21 22:53:55.423455: train_loss -0.7788 +2024-11-21 22:53:55.426124: val_loss -0.7108 +2024-11-21 22:53:55.426224: Pseudo dice [0.8344] +2024-11-21 22:53:55.426305: Epoch time: 18.62 s +2024-11-21 22:53:56.432003: +2024-11-21 22:53:56.432258: Epoch 2247 +2024-11-21 22:53:56.432370: Current learning rate: 0.00743 +2024-11-21 22:54:15.664194: train_loss -0.7783 +2024-11-21 22:54:15.664410: val_loss -0.7317 +2024-11-21 22:54:15.664563: Pseudo dice [0.8325] +2024-11-21 22:54:15.664643: Epoch time: 19.23 s +2024-11-21 22:54:16.494640: +2024-11-21 22:54:16.494851: Epoch 2248 +2024-11-21 22:54:16.494963: Current learning rate: 0.00743 +2024-11-21 22:54:34.728964: train_loss -0.7797 +2024-11-21 22:54:34.729224: val_loss -0.7028 +2024-11-21 22:54:34.729300: Pseudo dice [0.827] +2024-11-21 22:54:34.729384: Epoch time: 18.24 s +2024-11-21 22:54:35.569214: +2024-11-21 22:54:35.569537: Epoch 2249 +2024-11-21 22:54:35.569660: Current learning rate: 0.00743 +2024-11-21 22:54:54.698771: train_loss -0.7788 +2024-11-21 22:54:54.698982: val_loss -0.7465 +2024-11-21 22:54:54.699062: Pseudo dice [0.8337] +2024-11-21 22:54:54.699136: Epoch time: 19.13 s +2024-11-21 22:54:55.747276: +2024-11-21 22:54:55.747491: Epoch 2250 +2024-11-21 22:54:55.747607: Current learning rate: 0.00743 +2024-11-21 22:55:14.132773: train_loss -0.7832 +2024-11-21 22:55:14.132988: val_loss -0.7219 +2024-11-21 22:55:14.133076: Pseudo dice [0.8406] +2024-11-21 22:55:14.138310: Epoch time: 18.39 s +2024-11-21 22:55:14.982456: +2024-11-21 22:55:14.982653: Epoch 2251 +2024-11-21 22:55:14.982767: Current learning rate: 0.00743 +2024-11-21 22:55:33.480839: train_loss -0.7765 +2024-11-21 22:55:33.481064: val_loss -0.7128 +2024-11-21 22:55:33.481145: Pseudo dice [0.8216] +2024-11-21 22:55:33.481226: Epoch time: 18.5 s +2024-11-21 22:55:34.708111: +2024-11-21 22:55:34.708343: Epoch 2252 +2024-11-21 22:55:34.708455: Current learning rate: 0.00743 +2024-11-21 22:55:52.157468: train_loss -0.7804 +2024-11-21 22:55:52.157723: val_loss -0.7397 +2024-11-21 22:55:52.157801: Pseudo dice [0.8395] +2024-11-21 22:55:52.157887: Epoch time: 17.45 s +2024-11-21 22:55:52.990646: +2024-11-21 22:55:52.990857: Epoch 2253 +2024-11-21 22:55:52.990970: Current learning rate: 0.00743 +2024-11-21 22:56:11.629340: train_loss -0.7752 +2024-11-21 22:56:11.629567: val_loss -0.7567 +2024-11-21 22:56:11.629646: Pseudo dice [0.8346] +2024-11-21 22:56:11.629724: Epoch time: 18.64 s +2024-11-21 22:56:12.467672: +2024-11-21 22:56:12.467886: Epoch 2254 +2024-11-21 22:56:12.468004: Current learning rate: 0.00742 +2024-11-21 22:56:30.547826: train_loss -0.7876 +2024-11-21 22:56:30.548073: val_loss -0.7095 +2024-11-21 22:56:30.548153: Pseudo dice [0.824] +2024-11-21 22:56:30.548234: Epoch time: 18.08 s +2024-11-21 22:56:31.392661: +2024-11-21 22:56:31.392886: Epoch 2255 +2024-11-21 22:56:31.393006: Current learning rate: 0.00742 +2024-11-21 22:56:50.754887: train_loss -0.7872 +2024-11-21 22:56:50.755196: val_loss -0.7383 +2024-11-21 22:56:50.755274: Pseudo dice [0.8341] +2024-11-21 22:56:50.755363: Epoch time: 19.36 s +2024-11-21 22:56:51.608107: +2024-11-21 22:56:51.608309: Epoch 2256 +2024-11-21 22:56:51.608427: Current learning rate: 0.00742 +2024-11-21 22:57:10.351430: train_loss -0.7929 +2024-11-21 22:57:10.351652: val_loss -0.7524 +2024-11-21 22:57:10.351730: Pseudo dice [0.8384] +2024-11-21 22:57:10.351808: Epoch time: 18.74 s +2024-11-21 22:57:11.295178: +2024-11-21 22:57:11.295378: Epoch 2257 +2024-11-21 22:57:11.295496: Current learning rate: 0.00742 +2024-11-21 22:57:29.528390: train_loss -0.7829 +2024-11-21 22:57:29.528613: val_loss -0.7283 +2024-11-21 22:57:29.528723: Pseudo dice [0.8436] +2024-11-21 22:57:29.528802: Epoch time: 18.23 s +2024-11-21 22:57:30.369560: +2024-11-21 22:57:30.369841: Epoch 2258 +2024-11-21 22:57:30.369954: Current learning rate: 0.00742 +2024-11-21 22:57:49.649912: train_loss -0.7814 +2024-11-21 22:57:49.650177: val_loss -0.7474 +2024-11-21 22:57:49.650315: Pseudo dice [0.8385] +2024-11-21 22:57:49.650393: Epoch time: 19.28 s +2024-11-21 22:57:50.490769: +2024-11-21 22:57:50.490987: Epoch 2259 +2024-11-21 22:57:50.491106: Current learning rate: 0.00742 +2024-11-21 22:58:09.266541: train_loss -0.7786 +2024-11-21 22:58:09.266824: val_loss -0.7372 +2024-11-21 22:58:09.266947: Pseudo dice [0.8405] +2024-11-21 22:58:09.267045: Epoch time: 18.78 s +2024-11-21 22:58:10.108647: +2024-11-21 22:58:10.108850: Epoch 2260 +2024-11-21 22:58:10.108965: Current learning rate: 0.00742 +2024-11-21 22:58:29.707215: train_loss -0.7462 +2024-11-21 22:58:29.707428: val_loss -0.6981 +2024-11-21 22:58:29.707506: Pseudo dice [0.8252] +2024-11-21 22:58:29.707579: Epoch time: 19.6 s +2024-11-21 22:58:30.544107: +2024-11-21 22:58:30.544540: Epoch 2261 +2024-11-21 22:58:30.544675: Current learning rate: 0.00742 +2024-11-21 22:58:50.040100: train_loss -0.7358 +2024-11-21 22:58:50.040322: val_loss -0.7238 +2024-11-21 22:58:50.040396: Pseudo dice [0.8222] +2024-11-21 22:58:50.040474: Epoch time: 19.5 s +2024-11-21 22:58:50.877749: +2024-11-21 22:58:50.877961: Epoch 2262 +2024-11-21 22:58:50.878082: Current learning rate: 0.00741 +2024-11-21 22:59:09.415086: train_loss -0.7593 +2024-11-21 22:59:09.415412: val_loss -0.7377 +2024-11-21 22:59:09.415492: Pseudo dice [0.8475] +2024-11-21 22:59:09.415586: Epoch time: 18.54 s +2024-11-21 22:59:10.302093: +2024-11-21 22:59:10.302347: Epoch 2263 +2024-11-21 22:59:10.302462: Current learning rate: 0.00741 +2024-11-21 22:59:28.612427: train_loss -0.7692 +2024-11-21 22:59:28.612728: val_loss -0.7381 +2024-11-21 22:59:28.612811: Pseudo dice [0.8518] +2024-11-21 22:59:28.612891: Epoch time: 18.31 s +2024-11-21 22:59:29.837593: +2024-11-21 22:59:29.837815: Epoch 2264 +2024-11-21 22:59:29.837929: Current learning rate: 0.00741 +2024-11-21 22:59:48.224226: train_loss -0.7797 +2024-11-21 22:59:48.224480: val_loss -0.7557 +2024-11-21 22:59:48.224559: Pseudo dice [0.8381] +2024-11-21 22:59:48.224636: Epoch time: 18.39 s +2024-11-21 22:59:49.062502: +2024-11-21 22:59:49.062714: Epoch 2265 +2024-11-21 22:59:49.062827: Current learning rate: 0.00741 +2024-11-21 23:00:07.864040: train_loss -0.7783 +2024-11-21 23:00:07.864293: val_loss -0.7613 +2024-11-21 23:00:07.864375: Pseudo dice [0.8362] +2024-11-21 23:00:07.864456: Epoch time: 18.8 s +2024-11-21 23:00:08.699545: +2024-11-21 23:00:08.699792: Epoch 2266 +2024-11-21 23:00:08.699908: Current learning rate: 0.00741 +2024-11-21 23:00:27.129167: train_loss -0.7536 +2024-11-21 23:00:27.129379: val_loss -0.7287 +2024-11-21 23:00:27.129451: Pseudo dice [0.8309] +2024-11-21 23:00:27.129525: Epoch time: 18.43 s +2024-11-21 23:00:27.964186: +2024-11-21 23:00:27.964437: Epoch 2267 +2024-11-21 23:00:27.964546: Current learning rate: 0.00741 +2024-11-21 23:00:48.506125: train_loss -0.7474 +2024-11-21 23:00:48.506351: val_loss -0.7449 +2024-11-21 23:00:48.506431: Pseudo dice [0.8622] +2024-11-21 23:00:48.506511: Epoch time: 20.54 s +2024-11-21 23:00:49.506846: +2024-11-21 23:00:49.507058: Epoch 2268 +2024-11-21 23:00:49.507169: Current learning rate: 0.00741 +2024-11-21 23:01:08.079053: train_loss -0.759 +2024-11-21 23:01:08.081985: val_loss -0.7329 +2024-11-21 23:01:08.082094: Pseudo dice [0.838] +2024-11-21 23:01:08.082175: Epoch time: 18.57 s +2024-11-21 23:01:08.933298: +2024-11-21 23:01:08.933502: Epoch 2269 +2024-11-21 23:01:08.933618: Current learning rate: 0.00741 +2024-11-21 23:01:26.939299: train_loss -0.7658 +2024-11-21 23:01:26.939546: val_loss -0.7173 +2024-11-21 23:01:26.939626: Pseudo dice [0.8461] +2024-11-21 23:01:26.939711: Epoch time: 18.01 s +2024-11-21 23:01:27.784970: +2024-11-21 23:01:27.785210: Epoch 2270 +2024-11-21 23:01:27.785321: Current learning rate: 0.00741 +2024-11-21 23:01:46.495686: train_loss -0.7726 +2024-11-21 23:01:46.495906: val_loss -0.7455 +2024-11-21 23:01:46.495984: Pseudo dice [0.8272] +2024-11-21 23:01:46.496068: Epoch time: 18.71 s +2024-11-21 23:01:47.334223: +2024-11-21 23:01:47.334421: Epoch 2271 +2024-11-21 23:01:47.334539: Current learning rate: 0.0074 +2024-11-21 23:02:07.324061: train_loss -0.7663 +2024-11-21 23:02:07.324291: val_loss -0.7436 +2024-11-21 23:02:07.324604: Pseudo dice [0.8307] +2024-11-21 23:02:07.324685: Epoch time: 19.99 s +2024-11-21 23:02:08.309159: +2024-11-21 23:02:08.309446: Epoch 2272 +2024-11-21 23:02:08.309560: Current learning rate: 0.0074 +2024-11-21 23:02:27.186105: train_loss -0.7618 +2024-11-21 23:02:27.186328: val_loss -0.7182 +2024-11-21 23:02:27.186406: Pseudo dice [0.8423] +2024-11-21 23:02:27.186492: Epoch time: 18.88 s +2024-11-21 23:02:28.028598: +2024-11-21 23:02:28.028828: Epoch 2273 +2024-11-21 23:02:28.028935: Current learning rate: 0.0074 +2024-11-21 23:02:46.011287: train_loss -0.7595 +2024-11-21 23:02:46.011532: val_loss -0.7441 +2024-11-21 23:02:46.011608: Pseudo dice [0.848] +2024-11-21 23:02:46.011689: Epoch time: 17.98 s +2024-11-21 23:02:46.851296: +2024-11-21 23:02:46.851708: Epoch 2274 +2024-11-21 23:02:46.851840: Current learning rate: 0.0074 +2024-11-21 23:03:05.662608: train_loss -0.771 +2024-11-21 23:03:05.662831: val_loss -0.6767 +2024-11-21 23:03:05.662909: Pseudo dice [0.8079] +2024-11-21 23:03:05.662989: Epoch time: 18.81 s +2024-11-21 23:03:06.504465: +2024-11-21 23:03:06.504666: Epoch 2275 +2024-11-21 23:03:06.504776: Current learning rate: 0.0074 +2024-11-21 23:03:25.769495: train_loss -0.7584 +2024-11-21 23:03:25.769710: val_loss -0.7125 +2024-11-21 23:03:25.769785: Pseudo dice [0.8355] +2024-11-21 23:03:25.775057: Epoch time: 19.27 s +2024-11-21 23:03:27.061433: +2024-11-21 23:03:27.061720: Epoch 2276 +2024-11-21 23:03:27.061839: Current learning rate: 0.0074 +2024-11-21 23:03:44.131892: train_loss -0.7677 +2024-11-21 23:03:44.132169: val_loss -0.7218 +2024-11-21 23:03:44.132252: Pseudo dice [0.8183] +2024-11-21 23:03:44.132340: Epoch time: 17.07 s +2024-11-21 23:03:44.968815: +2024-11-21 23:03:44.969058: Epoch 2277 +2024-11-21 23:03:44.969180: Current learning rate: 0.0074 +2024-11-21 23:04:03.625237: train_loss -0.7649 +2024-11-21 23:04:03.625461: val_loss -0.725 +2024-11-21 23:04:03.625535: Pseudo dice [0.8503] +2024-11-21 23:04:03.625609: Epoch time: 18.66 s +2024-11-21 23:04:04.462896: +2024-11-21 23:04:04.463213: Epoch 2278 +2024-11-21 23:04:04.463327: Current learning rate: 0.0074 +2024-11-21 23:04:23.396842: train_loss -0.7745 +2024-11-21 23:04:23.397076: val_loss -0.7432 +2024-11-21 23:04:23.397154: Pseudo dice [0.8516] +2024-11-21 23:04:23.397229: Epoch time: 18.93 s +2024-11-21 23:04:24.265457: +2024-11-21 23:04:24.265703: Epoch 2279 +2024-11-21 23:04:24.265818: Current learning rate: 0.0074 +2024-11-21 23:04:41.164334: train_loss -0.7741 +2024-11-21 23:04:41.164588: val_loss -0.7193 +2024-11-21 23:04:41.164665: Pseudo dice [0.8235] +2024-11-21 23:04:41.164753: Epoch time: 16.9 s +2024-11-21 23:04:42.044783: +2024-11-21 23:04:42.045007: Epoch 2280 +2024-11-21 23:04:42.045119: Current learning rate: 0.00739 +2024-11-21 23:05:00.651451: train_loss -0.7788 +2024-11-21 23:05:00.651670: val_loss -0.7299 +2024-11-21 23:05:00.651782: Pseudo dice [0.8372] +2024-11-21 23:05:00.651913: Epoch time: 18.61 s +2024-11-21 23:05:01.501041: +2024-11-21 23:05:01.501271: Epoch 2281 +2024-11-21 23:05:01.501386: Current learning rate: 0.00739 +2024-11-21 23:05:20.685811: train_loss -0.7564 +2024-11-21 23:05:20.691197: val_loss -0.7435 +2024-11-21 23:05:20.691323: Pseudo dice [0.8216] +2024-11-21 23:05:20.691403: Epoch time: 19.19 s +2024-11-21 23:05:21.691149: +2024-11-21 23:05:21.691341: Epoch 2282 +2024-11-21 23:05:21.691453: Current learning rate: 0.00739 +2024-11-21 23:05:40.217040: train_loss -0.7647 +2024-11-21 23:05:40.217258: val_loss -0.7208 +2024-11-21 23:05:40.217334: Pseudo dice [0.8058] +2024-11-21 23:05:40.217411: Epoch time: 18.53 s +2024-11-21 23:05:41.152670: +2024-11-21 23:05:41.152875: Epoch 2283 +2024-11-21 23:05:41.152986: Current learning rate: 0.00739 +2024-11-21 23:06:00.739916: train_loss -0.7605 +2024-11-21 23:06:00.740160: val_loss -0.7447 +2024-11-21 23:06:00.740240: Pseudo dice [0.8318] +2024-11-21 23:06:00.740322: Epoch time: 19.59 s +2024-11-21 23:06:01.604158: +2024-11-21 23:06:01.604402: Epoch 2284 +2024-11-21 23:06:01.604559: Current learning rate: 0.00739 +2024-11-21 23:06:20.929674: train_loss -0.7721 +2024-11-21 23:06:20.929888: val_loss -0.7397 +2024-11-21 23:06:20.932111: Pseudo dice [0.8461] +2024-11-21 23:06:20.932207: Epoch time: 19.33 s +2024-11-21 23:06:21.878352: +2024-11-21 23:06:21.878574: Epoch 2285 +2024-11-21 23:06:21.878685: Current learning rate: 0.00739 +2024-11-21 23:06:39.793501: train_loss -0.7781 +2024-11-21 23:06:39.793722: val_loss -0.7222 +2024-11-21 23:06:39.793799: Pseudo dice [0.8422] +2024-11-21 23:06:39.793875: Epoch time: 17.92 s +2024-11-21 23:06:40.631802: +2024-11-21 23:06:40.632016: Epoch 2286 +2024-11-21 23:06:40.632131: Current learning rate: 0.00739 +2024-11-21 23:06:59.416951: train_loss -0.778 +2024-11-21 23:06:59.417181: val_loss -0.7464 +2024-11-21 23:06:59.418688: Pseudo dice [0.8278] +2024-11-21 23:06:59.418792: Epoch time: 18.79 s +2024-11-21 23:07:00.261443: +2024-11-21 23:07:00.261665: Epoch 2287 +2024-11-21 23:07:00.261781: Current learning rate: 0.00739 +2024-11-21 23:07:19.455154: train_loss -0.774 +2024-11-21 23:07:19.455392: val_loss -0.744 +2024-11-21 23:07:19.455467: Pseudo dice [0.8349] +2024-11-21 23:07:19.455549: Epoch time: 19.19 s +2024-11-21 23:07:20.696135: +2024-11-21 23:07:20.696567: Epoch 2288 +2024-11-21 23:07:20.696701: Current learning rate: 0.00738 +2024-11-21 23:07:39.778797: train_loss -0.7769 +2024-11-21 23:07:39.779019: val_loss -0.7358 +2024-11-21 23:07:39.779097: Pseudo dice [0.8439] +2024-11-21 23:07:39.779176: Epoch time: 19.08 s +2024-11-21 23:07:40.616376: +2024-11-21 23:07:40.616816: Epoch 2289 +2024-11-21 23:07:40.616959: Current learning rate: 0.00738 +2024-11-21 23:07:58.515799: train_loss -0.7776 +2024-11-21 23:07:58.516019: val_loss -0.7578 +2024-11-21 23:07:58.516093: Pseudo dice [0.8618] +2024-11-21 23:07:58.516167: Epoch time: 17.9 s +2024-11-21 23:07:59.356801: +2024-11-21 23:07:59.357252: Epoch 2290 +2024-11-21 23:07:59.357389: Current learning rate: 0.00738 +2024-11-21 23:08:18.629378: train_loss -0.7682 +2024-11-21 23:08:18.631773: val_loss -0.7532 +2024-11-21 23:08:18.631871: Pseudo dice [0.8359] +2024-11-21 23:08:18.631955: Epoch time: 19.27 s +2024-11-21 23:08:19.475281: +2024-11-21 23:08:19.475698: Epoch 2291 +2024-11-21 23:08:19.475831: Current learning rate: 0.00738 +2024-11-21 23:08:37.812712: train_loss -0.7692 +2024-11-21 23:08:37.812936: val_loss -0.7338 +2024-11-21 23:08:37.813026: Pseudo dice [0.8531] +2024-11-21 23:08:37.813103: Epoch time: 18.34 s +2024-11-21 23:08:38.648787: +2024-11-21 23:08:38.649226: Epoch 2292 +2024-11-21 23:08:38.649360: Current learning rate: 0.00738 +2024-11-21 23:08:56.901829: train_loss -0.7742 +2024-11-21 23:08:56.902052: val_loss -0.7276 +2024-11-21 23:08:56.902131: Pseudo dice [0.8385] +2024-11-21 23:08:56.902209: Epoch time: 18.25 s +2024-11-21 23:08:57.745719: +2024-11-21 23:08:57.746172: Epoch 2293 +2024-11-21 23:08:57.746308: Current learning rate: 0.00738 +2024-11-21 23:09:16.675652: train_loss -0.77 +2024-11-21 23:09:16.675869: val_loss -0.7355 +2024-11-21 23:09:16.675944: Pseudo dice [0.8305] +2024-11-21 23:09:16.676028: Epoch time: 18.93 s +2024-11-21 23:09:17.626646: +2024-11-21 23:09:17.627076: Epoch 2294 +2024-11-21 23:09:17.627206: Current learning rate: 0.00738 +2024-11-21 23:09:37.196256: train_loss -0.7882 +2024-11-21 23:09:37.196509: val_loss -0.7341 +2024-11-21 23:09:37.196626: Pseudo dice [0.8301] +2024-11-21 23:09:37.196715: Epoch time: 19.57 s +2024-11-21 23:09:38.036220: +2024-11-21 23:09:38.036629: Epoch 2295 +2024-11-21 23:09:38.036764: Current learning rate: 0.00738 +2024-11-21 23:09:57.916446: train_loss -0.7739 +2024-11-21 23:09:57.916670: val_loss -0.7165 +2024-11-21 23:09:57.916745: Pseudo dice [0.8167] +2024-11-21 23:09:57.916822: Epoch time: 19.88 s +2024-11-21 23:09:58.911256: +2024-11-21 23:09:58.911658: Epoch 2296 +2024-11-21 23:09:58.911790: Current learning rate: 0.00738 +2024-11-21 23:10:17.848792: train_loss -0.7753 +2024-11-21 23:10:17.849025: val_loss -0.7678 +2024-11-21 23:10:17.849105: Pseudo dice [0.8555] +2024-11-21 23:10:17.849184: Epoch time: 18.94 s +2024-11-21 23:10:18.856680: +2024-11-21 23:10:18.857115: Epoch 2297 +2024-11-21 23:10:18.857245: Current learning rate: 0.00737 +2024-11-21 23:10:36.910618: train_loss -0.7777 +2024-11-21 23:10:36.911567: val_loss -0.7073 +2024-11-21 23:10:36.911918: Pseudo dice [0.8373] +2024-11-21 23:10:36.912012: Epoch time: 18.05 s +2024-11-21 23:10:38.008573: +2024-11-21 23:10:38.009008: Epoch 2298 +2024-11-21 23:10:38.009143: Current learning rate: 0.00737 +2024-11-21 23:10:56.837337: train_loss -0.7785 +2024-11-21 23:10:56.839765: val_loss -0.7481 +2024-11-21 23:10:56.839887: Pseudo dice [0.8501] +2024-11-21 23:10:56.839975: Epoch time: 18.83 s +2024-11-21 23:10:57.681158: +2024-11-21 23:10:57.681393: Epoch 2299 +2024-11-21 23:10:57.681505: Current learning rate: 0.00737 +2024-11-21 23:11:16.792944: train_loss -0.7903 +2024-11-21 23:11:16.793220: val_loss -0.7248 +2024-11-21 23:11:16.793295: Pseudo dice [0.8417] +2024-11-21 23:11:16.793397: Epoch time: 19.11 s +2024-11-21 23:11:18.312466: +2024-11-21 23:11:18.312677: Epoch 2300 +2024-11-21 23:11:18.312790: Current learning rate: 0.00737 +2024-11-21 23:11:36.784153: train_loss -0.7856 +2024-11-21 23:11:36.789597: val_loss -0.7502 +2024-11-21 23:11:36.789708: Pseudo dice [0.8391] +2024-11-21 23:11:36.789806: Epoch time: 18.47 s +2024-11-21 23:11:37.774863: +2024-11-21 23:11:37.775073: Epoch 2301 +2024-11-21 23:11:37.775184: Current learning rate: 0.00737 +2024-11-21 23:11:57.066480: train_loss -0.7715 +2024-11-21 23:11:57.066722: val_loss -0.7345 +2024-11-21 23:11:57.066799: Pseudo dice [0.8441] +2024-11-21 23:11:57.066876: Epoch time: 19.29 s +2024-11-21 23:11:57.926793: +2024-11-21 23:11:57.927073: Epoch 2302 +2024-11-21 23:11:57.927187: Current learning rate: 0.00737 +2024-11-21 23:12:16.658368: train_loss -0.7844 +2024-11-21 23:12:16.658598: val_loss -0.7428 +2024-11-21 23:12:16.658677: Pseudo dice [0.824] +2024-11-21 23:12:16.658757: Epoch time: 18.73 s +2024-11-21 23:12:17.538662: +2024-11-21 23:12:17.538913: Epoch 2303 +2024-11-21 23:12:17.539030: Current learning rate: 0.00737 +2024-11-21 23:12:36.012462: train_loss -0.7651 +2024-11-21 23:12:36.012678: val_loss -0.7587 +2024-11-21 23:12:36.012755: Pseudo dice [0.859] +2024-11-21 23:12:36.014912: Epoch time: 18.47 s +2024-11-21 23:12:37.018517: +2024-11-21 23:12:37.018729: Epoch 2304 +2024-11-21 23:12:37.018840: Current learning rate: 0.00737 +2024-11-21 23:12:56.276181: train_loss -0.7803 +2024-11-21 23:12:56.276446: val_loss -0.7304 +2024-11-21 23:12:56.276525: Pseudo dice [0.8349] +2024-11-21 23:12:56.276614: Epoch time: 19.26 s +2024-11-21 23:12:57.119853: +2024-11-21 23:12:57.120078: Epoch 2305 +2024-11-21 23:12:57.120197: Current learning rate: 0.00736 +2024-11-21 23:13:15.198956: train_loss -0.781 +2024-11-21 23:13:15.199175: val_loss -0.7475 +2024-11-21 23:13:15.199249: Pseudo dice [0.8536] +2024-11-21 23:13:15.199328: Epoch time: 18.08 s +2024-11-21 23:13:16.033124: +2024-11-21 23:13:16.033346: Epoch 2306 +2024-11-21 23:13:16.033460: Current learning rate: 0.00736 +2024-11-21 23:13:34.190166: train_loss -0.7833 +2024-11-21 23:13:34.190452: val_loss -0.7342 +2024-11-21 23:13:34.190534: Pseudo dice [0.8314] +2024-11-21 23:13:34.190616: Epoch time: 18.16 s +2024-11-21 23:13:35.034043: +2024-11-21 23:13:35.034255: Epoch 2307 +2024-11-21 23:13:35.034372: Current learning rate: 0.00736 +2024-11-21 23:13:53.297414: train_loss -0.7792 +2024-11-21 23:13:53.297628: val_loss -0.7276 +2024-11-21 23:13:53.297704: Pseudo dice [0.8283] +2024-11-21 23:13:53.297783: Epoch time: 18.26 s +2024-11-21 23:13:54.133084: +2024-11-21 23:13:54.133312: Epoch 2308 +2024-11-21 23:13:54.133430: Current learning rate: 0.00736 +2024-11-21 23:14:12.069482: train_loss -0.7827 +2024-11-21 23:14:12.071925: val_loss -0.7486 +2024-11-21 23:14:12.072061: Pseudo dice [0.8351] +2024-11-21 23:14:12.072148: Epoch time: 17.94 s +2024-11-21 23:14:12.927569: +2024-11-21 23:14:12.927765: Epoch 2309 +2024-11-21 23:14:12.927874: Current learning rate: 0.00736 +2024-11-21 23:14:31.194407: train_loss -0.7882 +2024-11-21 23:14:31.194680: val_loss -0.7428 +2024-11-21 23:14:31.194756: Pseudo dice [0.8223] +2024-11-21 23:14:31.194832: Epoch time: 18.27 s +2024-11-21 23:14:32.026070: +2024-11-21 23:14:32.026265: Epoch 2310 +2024-11-21 23:14:32.026383: Current learning rate: 0.00736 +2024-11-21 23:14:50.955949: train_loss -0.7918 +2024-11-21 23:14:50.958363: val_loss -0.7606 +2024-11-21 23:14:50.958455: Pseudo dice [0.84] +2024-11-21 23:14:50.958542: Epoch time: 18.93 s +2024-11-21 23:14:51.832157: +2024-11-21 23:14:51.832366: Epoch 2311 +2024-11-21 23:14:51.832485: Current learning rate: 0.00736 +2024-11-21 23:15:11.205983: train_loss -0.7877 +2024-11-21 23:15:11.206237: val_loss -0.7376 +2024-11-21 23:15:11.206316: Pseudo dice [0.8344] +2024-11-21 23:15:11.206400: Epoch time: 19.37 s +2024-11-21 23:15:12.409538: +2024-11-21 23:15:12.409758: Epoch 2312 +2024-11-21 23:15:12.409870: Current learning rate: 0.00736 +2024-11-21 23:15:31.323020: train_loss -0.7866 +2024-11-21 23:15:31.323241: val_loss -0.7407 +2024-11-21 23:15:31.323314: Pseudo dice [0.8345] +2024-11-21 23:15:31.323389: Epoch time: 18.91 s +2024-11-21 23:15:32.173863: +2024-11-21 23:15:32.174078: Epoch 2313 +2024-11-21 23:15:32.174194: Current learning rate: 0.00736 +2024-11-21 23:15:50.486669: train_loss -0.7764 +2024-11-21 23:15:50.486897: val_loss -0.7664 +2024-11-21 23:15:50.486979: Pseudo dice [0.8475] +2024-11-21 23:15:50.487064: Epoch time: 18.31 s +2024-11-21 23:15:51.425275: +2024-11-21 23:15:51.425479: Epoch 2314 +2024-11-21 23:15:51.425590: Current learning rate: 0.00735 +2024-11-21 23:16:09.927268: train_loss -0.7696 +2024-11-21 23:16:09.929678: val_loss -0.7276 +2024-11-21 23:16:09.929804: Pseudo dice [0.8292] +2024-11-21 23:16:09.929892: Epoch time: 18.5 s +2024-11-21 23:16:10.811726: +2024-11-21 23:16:10.811936: Epoch 2315 +2024-11-21 23:16:10.812050: Current learning rate: 0.00735 +2024-11-21 23:16:29.443694: train_loss -0.778 +2024-11-21 23:16:29.443912: val_loss -0.7122 +2024-11-21 23:16:29.444015: Pseudo dice [0.8153] +2024-11-21 23:16:29.444098: Epoch time: 18.63 s +2024-11-21 23:16:30.286598: +2024-11-21 23:16:30.286787: Epoch 2316 +2024-11-21 23:16:30.286896: Current learning rate: 0.00735 +2024-11-21 23:16:49.077299: train_loss -0.7799 +2024-11-21 23:16:49.077536: val_loss -0.748 +2024-11-21 23:16:49.079680: Pseudo dice [0.8396] +2024-11-21 23:16:49.079788: Epoch time: 18.79 s +2024-11-21 23:16:49.968533: +2024-11-21 23:16:49.968754: Epoch 2317 +2024-11-21 23:16:49.968868: Current learning rate: 0.00735 +2024-11-21 23:17:09.486040: train_loss -0.7786 +2024-11-21 23:17:09.486253: val_loss -0.736 +2024-11-21 23:17:09.486326: Pseudo dice [0.8319] +2024-11-21 23:17:09.486402: Epoch time: 19.52 s +2024-11-21 23:17:10.327775: +2024-11-21 23:17:10.327984: Epoch 2318 +2024-11-21 23:17:10.328100: Current learning rate: 0.00735 +2024-11-21 23:17:28.617107: train_loss -0.7786 +2024-11-21 23:17:28.617332: val_loss -0.739 +2024-11-21 23:17:28.617412: Pseudo dice [0.8356] +2024-11-21 23:17:28.617496: Epoch time: 18.29 s +2024-11-21 23:17:29.460386: +2024-11-21 23:17:29.460591: Epoch 2319 +2024-11-21 23:17:29.460702: Current learning rate: 0.00735 +2024-11-21 23:17:48.087168: train_loss -0.7739 +2024-11-21 23:17:48.087421: val_loss -0.7262 +2024-11-21 23:17:48.087496: Pseudo dice [0.8462] +2024-11-21 23:17:48.087576: Epoch time: 18.63 s +2024-11-21 23:17:48.929868: +2024-11-21 23:17:48.930092: Epoch 2320 +2024-11-21 23:17:48.930205: Current learning rate: 0.00735 +2024-11-21 23:18:08.078535: train_loss -0.7685 +2024-11-21 23:18:08.078748: val_loss -0.7565 +2024-11-21 23:18:08.078825: Pseudo dice [0.8433] +2024-11-21 23:18:08.078902: Epoch time: 19.15 s +2024-11-21 23:18:08.921122: +2024-11-21 23:18:08.921318: Epoch 2321 +2024-11-21 23:18:08.921427: Current learning rate: 0.00735 +2024-11-21 23:18:27.602327: train_loss -0.7772 +2024-11-21 23:18:27.602545: val_loss -0.7286 +2024-11-21 23:18:27.602621: Pseudo dice [0.8318] +2024-11-21 23:18:27.602696: Epoch time: 18.68 s +2024-11-21 23:18:28.459417: +2024-11-21 23:18:28.459681: Epoch 2322 +2024-11-21 23:18:28.459793: Current learning rate: 0.00735 +2024-11-21 23:18:46.215388: train_loss -0.7716 +2024-11-21 23:18:46.215668: val_loss -0.7223 +2024-11-21 23:18:46.215746: Pseudo dice [0.8369] +2024-11-21 23:18:46.215836: Epoch time: 17.76 s +2024-11-21 23:18:47.057169: +2024-11-21 23:18:47.057364: Epoch 2323 +2024-11-21 23:18:47.057475: Current learning rate: 0.00734 +2024-11-21 23:19:05.798498: train_loss -0.7735 +2024-11-21 23:19:05.798959: val_loss -0.7144 +2024-11-21 23:19:05.799053: Pseudo dice [0.842] +2024-11-21 23:19:05.799129: Epoch time: 18.74 s +2024-11-21 23:19:07.109246: +2024-11-21 23:19:07.109514: Epoch 2324 +2024-11-21 23:19:07.109629: Current learning rate: 0.00734 +2024-11-21 23:19:25.205474: train_loss -0.7752 +2024-11-21 23:19:25.205718: val_loss -0.7236 +2024-11-21 23:19:25.205802: Pseudo dice [0.8315] +2024-11-21 23:19:25.205889: Epoch time: 18.1 s +2024-11-21 23:19:26.038235: +2024-11-21 23:19:26.038455: Epoch 2325 +2024-11-21 23:19:26.038571: Current learning rate: 0.00734 +2024-11-21 23:19:45.486954: train_loss -0.7848 +2024-11-21 23:19:45.487207: val_loss -0.7491 +2024-11-21 23:19:45.487284: Pseudo dice [0.8569] +2024-11-21 23:19:45.487367: Epoch time: 19.45 s +2024-11-21 23:19:46.331400: +2024-11-21 23:19:46.331606: Epoch 2326 +2024-11-21 23:19:46.331720: Current learning rate: 0.00734 +2024-11-21 23:20:05.748680: train_loss -0.7746 +2024-11-21 23:20:05.748901: val_loss -0.7153 +2024-11-21 23:20:05.748981: Pseudo dice [0.8206] +2024-11-21 23:20:05.751207: Epoch time: 19.42 s +2024-11-21 23:20:06.687435: +2024-11-21 23:20:06.687627: Epoch 2327 +2024-11-21 23:20:06.687740: Current learning rate: 0.00734 +2024-11-21 23:20:23.767671: train_loss -0.7818 +2024-11-21 23:20:23.767929: val_loss -0.7461 +2024-11-21 23:20:23.768012: Pseudo dice [0.8346] +2024-11-21 23:20:23.768090: Epoch time: 17.08 s +2024-11-21 23:20:24.608043: +2024-11-21 23:20:24.608242: Epoch 2328 +2024-11-21 23:20:24.608353: Current learning rate: 0.00734 +2024-11-21 23:20:43.398759: train_loss -0.7739 +2024-11-21 23:20:43.398981: val_loss -0.7152 +2024-11-21 23:20:43.399063: Pseudo dice [0.8398] +2024-11-21 23:20:43.399143: Epoch time: 18.79 s +2024-11-21 23:20:44.304802: +2024-11-21 23:20:44.305022: Epoch 2329 +2024-11-21 23:20:44.305131: Current learning rate: 0.00734 +2024-11-21 23:21:01.835019: train_loss -0.7669 +2024-11-21 23:21:01.835328: val_loss -0.7627 +2024-11-21 23:21:01.835406: Pseudo dice [0.8228] +2024-11-21 23:21:01.835486: Epoch time: 17.53 s +2024-11-21 23:21:02.677055: +2024-11-21 23:21:02.677261: Epoch 2330 +2024-11-21 23:21:02.677376: Current learning rate: 0.00734 +2024-11-21 23:21:21.147861: train_loss -0.7638 +2024-11-21 23:21:21.148118: val_loss -0.723 +2024-11-21 23:21:21.148191: Pseudo dice [0.81] +2024-11-21 23:21:21.148265: Epoch time: 18.47 s +2024-11-21 23:21:21.990676: +2024-11-21 23:21:21.990877: Epoch 2331 +2024-11-21 23:21:21.990988: Current learning rate: 0.00733 +2024-11-21 23:21:40.962878: train_loss -0.7721 +2024-11-21 23:21:40.963106: val_loss -0.7359 +2024-11-21 23:21:40.963183: Pseudo dice [0.8227] +2024-11-21 23:21:40.963263: Epoch time: 18.97 s +2024-11-21 23:21:41.798691: +2024-11-21 23:21:41.798925: Epoch 2332 +2024-11-21 23:21:41.799048: Current learning rate: 0.00733 +2024-11-21 23:22:00.842262: train_loss -0.7841 +2024-11-21 23:22:00.842494: val_loss -0.7383 +2024-11-21 23:22:00.842570: Pseudo dice [0.8179] +2024-11-21 23:22:00.842650: Epoch time: 19.04 s +2024-11-21 23:22:01.680542: +2024-11-21 23:22:01.680757: Epoch 2333 +2024-11-21 23:22:01.680869: Current learning rate: 0.00733 +2024-11-21 23:22:21.158365: train_loss -0.7729 +2024-11-21 23:22:21.158616: val_loss -0.7391 +2024-11-21 23:22:21.158693: Pseudo dice [0.8269] +2024-11-21 23:22:21.158776: Epoch time: 19.48 s +2024-11-21 23:22:21.998578: +2024-11-21 23:22:21.998770: Epoch 2334 +2024-11-21 23:22:21.998878: Current learning rate: 0.00733 +2024-11-21 23:22:41.368158: train_loss -0.7777 +2024-11-21 23:22:41.368381: val_loss -0.7472 +2024-11-21 23:22:41.368460: Pseudo dice [0.8315] +2024-11-21 23:22:41.368539: Epoch time: 19.37 s +2024-11-21 23:22:42.202524: +2024-11-21 23:22:42.202737: Epoch 2335 +2024-11-21 23:22:42.202850: Current learning rate: 0.00733 +2024-11-21 23:23:01.844551: train_loss -0.7727 +2024-11-21 23:23:01.849924: val_loss -0.7296 +2024-11-21 23:23:01.850008: Pseudo dice [0.8284] +2024-11-21 23:23:01.850089: Epoch time: 19.64 s +2024-11-21 23:23:03.157254: +2024-11-21 23:23:03.157495: Epoch 2336 +2024-11-21 23:23:03.157613: Current learning rate: 0.00733 +2024-11-21 23:23:22.579904: train_loss -0.7665 +2024-11-21 23:23:22.585352: val_loss -0.7552 +2024-11-21 23:23:22.585470: Pseudo dice [0.8481] +2024-11-21 23:23:22.585563: Epoch time: 19.42 s +2024-11-21 23:23:23.526717: +2024-11-21 23:23:23.526925: Epoch 2337 +2024-11-21 23:23:23.527040: Current learning rate: 0.00733 +2024-11-21 23:23:42.834309: train_loss -0.7729 +2024-11-21 23:23:42.834533: val_loss -0.7234 +2024-11-21 23:23:42.834610: Pseudo dice [0.8238] +2024-11-21 23:23:42.834687: Epoch time: 19.31 s +2024-11-21 23:23:43.803045: +2024-11-21 23:23:43.803324: Epoch 2338 +2024-11-21 23:23:43.803441: Current learning rate: 0.00733 +2024-11-21 23:24:02.949670: train_loss -0.7842 +2024-11-21 23:24:02.949964: val_loss -0.7292 +2024-11-21 23:24:02.950044: Pseudo dice [0.8377] +2024-11-21 23:24:02.950123: Epoch time: 19.15 s +2024-11-21 23:24:03.891433: +2024-11-21 23:24:03.891661: Epoch 2339 +2024-11-21 23:24:03.891774: Current learning rate: 0.00733 +2024-11-21 23:24:21.994545: train_loss -0.7807 +2024-11-21 23:24:21.994799: val_loss -0.743 +2024-11-21 23:24:21.994876: Pseudo dice [0.8182] +2024-11-21 23:24:21.994963: Epoch time: 18.1 s +2024-11-21 23:24:22.847706: +2024-11-21 23:24:22.847943: Epoch 2340 +2024-11-21 23:24:22.848069: Current learning rate: 0.00732 +2024-11-21 23:24:41.607612: train_loss -0.7851 +2024-11-21 23:24:41.607825: val_loss -0.727 +2024-11-21 23:24:41.607899: Pseudo dice [0.8587] +2024-11-21 23:24:41.607977: Epoch time: 18.76 s +2024-11-21 23:24:42.448569: +2024-11-21 23:24:42.448789: Epoch 2341 +2024-11-21 23:24:42.448902: Current learning rate: 0.00732 +2024-11-21 23:25:01.317127: train_loss -0.782 +2024-11-21 23:25:01.317336: val_loss -0.7203 +2024-11-21 23:25:01.317414: Pseudo dice [0.8353] +2024-11-21 23:25:01.317491: Epoch time: 18.87 s +2024-11-21 23:25:02.153641: +2024-11-21 23:25:02.153852: Epoch 2342 +2024-11-21 23:25:02.153967: Current learning rate: 0.00732 +2024-11-21 23:25:20.882319: train_loss -0.7811 +2024-11-21 23:25:20.882540: val_loss -0.7445 +2024-11-21 23:25:20.882616: Pseudo dice [0.8305] +2024-11-21 23:25:20.882693: Epoch time: 18.73 s +2024-11-21 23:25:21.913293: +2024-11-21 23:25:21.913578: Epoch 2343 +2024-11-21 23:25:21.913689: Current learning rate: 0.00732 +2024-11-21 23:25:40.200887: train_loss -0.7742 +2024-11-21 23:25:40.201787: val_loss -0.7547 +2024-11-21 23:25:40.201867: Pseudo dice [0.8412] +2024-11-21 23:25:40.201952: Epoch time: 18.29 s +2024-11-21 23:25:41.039767: +2024-11-21 23:25:41.040009: Epoch 2344 +2024-11-21 23:25:41.040144: Current learning rate: 0.00732 +2024-11-21 23:26:00.549303: train_loss -0.777 +2024-11-21 23:26:00.553025: val_loss -0.7115 +2024-11-21 23:26:00.553121: Pseudo dice [0.8358] +2024-11-21 23:26:00.553212: Epoch time: 19.51 s +2024-11-21 23:26:01.419705: +2024-11-21 23:26:01.420027: Epoch 2345 +2024-11-21 23:26:01.420145: Current learning rate: 0.00732 +2024-11-21 23:26:19.209072: train_loss -0.778 +2024-11-21 23:26:19.209349: val_loss -0.7402 +2024-11-21 23:26:19.209439: Pseudo dice [0.8372] +2024-11-21 23:26:19.209521: Epoch time: 17.79 s +2024-11-21 23:26:20.051394: +2024-11-21 23:26:20.051701: Epoch 2346 +2024-11-21 23:26:20.051819: Current learning rate: 0.00732 +2024-11-21 23:26:39.275544: train_loss -0.7631 +2024-11-21 23:26:39.275768: val_loss -0.7496 +2024-11-21 23:26:39.275845: Pseudo dice [0.8406] +2024-11-21 23:26:39.275926: Epoch time: 19.22 s +2024-11-21 23:26:40.296201: +2024-11-21 23:26:40.296423: Epoch 2347 +2024-11-21 23:26:40.296539: Current learning rate: 0.00732 +2024-11-21 23:26:59.016807: train_loss -0.7801 +2024-11-21 23:26:59.017064: val_loss -0.7463 +2024-11-21 23:26:59.017143: Pseudo dice [0.8255] +2024-11-21 23:26:59.017223: Epoch time: 18.72 s +2024-11-21 23:27:00.252537: +2024-11-21 23:27:00.252778: Epoch 2348 +2024-11-21 23:27:00.252895: Current learning rate: 0.00731 +2024-11-21 23:27:17.962156: train_loss -0.7759 +2024-11-21 23:27:17.962385: val_loss -0.7198 +2024-11-21 23:27:17.962463: Pseudo dice [0.8432] +2024-11-21 23:27:17.962540: Epoch time: 17.71 s +2024-11-21 23:27:18.806486: +2024-11-21 23:27:18.806693: Epoch 2349 +2024-11-21 23:27:18.806809: Current learning rate: 0.00731 +2024-11-21 23:27:37.403619: train_loss -0.779 +2024-11-21 23:27:37.403930: val_loss -0.7344 +2024-11-21 23:27:37.404031: Pseudo dice [0.8308] +2024-11-21 23:27:37.404109: Epoch time: 18.6 s +2024-11-21 23:27:38.473573: +2024-11-21 23:27:38.473802: Epoch 2350 +2024-11-21 23:27:38.473917: Current learning rate: 0.00731 +2024-11-21 23:27:57.457378: train_loss -0.7785 +2024-11-21 23:27:57.457625: val_loss -0.7228 +2024-11-21 23:27:57.457767: Pseudo dice [0.8498] +2024-11-21 23:27:57.457848: Epoch time: 18.98 s +2024-11-21 23:27:58.298053: +2024-11-21 23:27:58.298311: Epoch 2351 +2024-11-21 23:27:58.298424: Current learning rate: 0.00731 +2024-11-21 23:28:16.751869: train_loss -0.7772 +2024-11-21 23:28:16.752098: val_loss -0.7495 +2024-11-21 23:28:16.752176: Pseudo dice [0.8309] +2024-11-21 23:28:16.752252: Epoch time: 18.45 s +2024-11-21 23:28:17.586029: +2024-11-21 23:28:17.586243: Epoch 2352 +2024-11-21 23:28:17.586354: Current learning rate: 0.00731 +2024-11-21 23:28:35.230123: train_loss -0.7808 +2024-11-21 23:28:35.230340: val_loss -0.7419 +2024-11-21 23:28:35.230418: Pseudo dice [0.8479] +2024-11-21 23:28:35.230494: Epoch time: 17.64 s +2024-11-21 23:28:36.069605: +2024-11-21 23:28:36.069815: Epoch 2353 +2024-11-21 23:28:36.069929: Current learning rate: 0.00731 +2024-11-21 23:28:55.006894: train_loss -0.772 +2024-11-21 23:28:55.009297: val_loss -0.7437 +2024-11-21 23:28:55.009404: Pseudo dice [0.8034] +2024-11-21 23:28:55.009497: Epoch time: 18.94 s +2024-11-21 23:28:56.118930: +2024-11-21 23:28:56.119133: Epoch 2354 +2024-11-21 23:28:56.119248: Current learning rate: 0.00731 +2024-11-21 23:29:14.707475: train_loss -0.7844 +2024-11-21 23:29:14.707723: val_loss -0.7488 +2024-11-21 23:29:14.707799: Pseudo dice [0.8322] +2024-11-21 23:29:14.707882: Epoch time: 18.59 s +2024-11-21 23:29:15.589858: +2024-11-21 23:29:15.590094: Epoch 2355 +2024-11-21 23:29:15.590205: Current learning rate: 0.00731 +2024-11-21 23:29:33.888646: train_loss -0.7873 +2024-11-21 23:29:33.889487: val_loss -0.7326 +2024-11-21 23:29:33.889620: Pseudo dice [0.8278] +2024-11-21 23:29:33.889705: Epoch time: 18.3 s +2024-11-21 23:29:34.931355: +2024-11-21 23:29:34.931633: Epoch 2356 +2024-11-21 23:29:34.931750: Current learning rate: 0.00731 +2024-11-21 23:29:52.844985: train_loss -0.7795 +2024-11-21 23:29:52.845210: val_loss -0.756 +2024-11-21 23:29:52.845288: Pseudo dice [0.838] +2024-11-21 23:29:52.845382: Epoch time: 17.91 s +2024-11-21 23:29:53.690430: +2024-11-21 23:29:53.690633: Epoch 2357 +2024-11-21 23:29:53.690743: Current learning rate: 0.0073 +2024-11-21 23:30:12.566848: train_loss -0.776 +2024-11-21 23:30:12.567099: val_loss -0.7458 +2024-11-21 23:30:12.567172: Pseudo dice [0.8289] +2024-11-21 23:30:12.567253: Epoch time: 18.88 s +2024-11-21 23:30:13.405499: +2024-11-21 23:30:13.405781: Epoch 2358 +2024-11-21 23:30:13.405896: Current learning rate: 0.0073 +2024-11-21 23:30:31.391256: train_loss -0.7673 +2024-11-21 23:30:31.391471: val_loss -0.7495 +2024-11-21 23:30:31.391546: Pseudo dice [0.8368] +2024-11-21 23:30:31.391621: Epoch time: 17.99 s +2024-11-21 23:30:32.222160: +2024-11-21 23:30:32.222601: Epoch 2359 +2024-11-21 23:30:32.222734: Current learning rate: 0.0073 +2024-11-21 23:30:51.177862: train_loss -0.7712 +2024-11-21 23:30:51.178096: val_loss -0.7631 +2024-11-21 23:30:51.178172: Pseudo dice [0.8462] +2024-11-21 23:30:51.178329: Epoch time: 18.96 s +2024-11-21 23:30:52.447559: +2024-11-21 23:30:52.447777: Epoch 2360 +2024-11-21 23:30:52.447891: Current learning rate: 0.0073 +2024-11-21 23:31:10.410668: train_loss -0.772 +2024-11-21 23:31:10.411009: val_loss -0.7441 +2024-11-21 23:31:10.411087: Pseudo dice [0.845] +2024-11-21 23:31:10.411170: Epoch time: 17.96 s +2024-11-21 23:31:11.256064: +2024-11-21 23:31:11.256286: Epoch 2361 +2024-11-21 23:31:11.256400: Current learning rate: 0.0073 +2024-11-21 23:31:28.410648: train_loss -0.7806 +2024-11-21 23:31:28.410872: val_loss -0.7319 +2024-11-21 23:31:28.410950: Pseudo dice [0.8335] +2024-11-21 23:31:28.411035: Epoch time: 17.16 s +2024-11-21 23:31:29.248818: +2024-11-21 23:31:29.249105: Epoch 2362 +2024-11-21 23:31:29.249216: Current learning rate: 0.0073 +2024-11-21 23:31:46.854643: train_loss -0.7879 +2024-11-21 23:31:46.854882: val_loss -0.7259 +2024-11-21 23:31:46.854961: Pseudo dice [0.8218] +2024-11-21 23:31:46.855059: Epoch time: 17.61 s +2024-11-21 23:31:47.689743: +2024-11-21 23:31:47.689970: Epoch 2363 +2024-11-21 23:31:47.690092: Current learning rate: 0.0073 +2024-11-21 23:32:06.410080: train_loss -0.7767 +2024-11-21 23:32:06.410332: val_loss -0.7563 +2024-11-21 23:32:06.410409: Pseudo dice [0.8409] +2024-11-21 23:32:06.410491: Epoch time: 18.72 s +2024-11-21 23:32:07.264610: +2024-11-21 23:32:07.264821: Epoch 2364 +2024-11-21 23:32:07.264935: Current learning rate: 0.0073 +2024-11-21 23:32:26.950598: train_loss -0.779 +2024-11-21 23:32:26.950814: val_loss -0.7142 +2024-11-21 23:32:26.950887: Pseudo dice [0.8197] +2024-11-21 23:32:26.950962: Epoch time: 19.69 s +2024-11-21 23:32:27.790461: +2024-11-21 23:32:27.790689: Epoch 2365 +2024-11-21 23:32:27.790803: Current learning rate: 0.00729 +2024-11-21 23:32:47.032543: train_loss -0.7577 +2024-11-21 23:32:47.032758: val_loss -0.7343 +2024-11-21 23:32:47.032838: Pseudo dice [0.8529] +2024-11-21 23:32:47.032915: Epoch time: 19.24 s +2024-11-21 23:32:47.866138: +2024-11-21 23:32:47.866337: Epoch 2366 +2024-11-21 23:32:47.866449: Current learning rate: 0.00729 +2024-11-21 23:33:07.147221: train_loss -0.7564 +2024-11-21 23:33:07.148002: val_loss -0.7317 +2024-11-21 23:33:07.148086: Pseudo dice [0.8468] +2024-11-21 23:33:07.148166: Epoch time: 19.28 s +2024-11-21 23:33:07.991855: +2024-11-21 23:33:07.992135: Epoch 2367 +2024-11-21 23:33:07.992243: Current learning rate: 0.00729 +2024-11-21 23:33:28.219358: train_loss -0.7517 +2024-11-21 23:33:28.219608: val_loss -0.7298 +2024-11-21 23:33:28.219687: Pseudo dice [0.822] +2024-11-21 23:33:28.219771: Epoch time: 20.23 s +2024-11-21 23:33:29.061176: +2024-11-21 23:33:29.061397: Epoch 2368 +2024-11-21 23:33:29.061514: Current learning rate: 0.00729 +2024-11-21 23:33:48.434203: train_loss -0.7451 +2024-11-21 23:33:48.434426: val_loss -0.7596 +2024-11-21 23:33:48.434500: Pseudo dice [0.8408] +2024-11-21 23:33:48.439792: Epoch time: 19.37 s +2024-11-21 23:33:49.278580: +2024-11-21 23:33:49.278795: Epoch 2369 +2024-11-21 23:33:49.278909: Current learning rate: 0.00729 +2024-11-21 23:34:06.721490: train_loss -0.7607 +2024-11-21 23:34:06.721704: val_loss -0.7461 +2024-11-21 23:34:06.721817: Pseudo dice [0.8226] +2024-11-21 23:34:06.721899: Epoch time: 17.44 s +2024-11-21 23:34:07.561543: +2024-11-21 23:34:07.561827: Epoch 2370 +2024-11-21 23:34:07.561942: Current learning rate: 0.00729 +2024-11-21 23:34:25.685078: train_loss -0.7744 +2024-11-21 23:34:25.685289: val_loss -0.7427 +2024-11-21 23:34:25.685364: Pseudo dice [0.8295] +2024-11-21 23:34:25.685440: Epoch time: 18.12 s +2024-11-21 23:34:26.519255: +2024-11-21 23:34:26.519472: Epoch 2371 +2024-11-21 23:34:26.519582: Current learning rate: 0.00729 +2024-11-21 23:34:44.816482: train_loss -0.7611 +2024-11-21 23:34:44.816742: val_loss -0.757 +2024-11-21 23:34:44.816817: Pseudo dice [0.8296] +2024-11-21 23:34:44.816900: Epoch time: 18.3 s +2024-11-21 23:34:46.130532: +2024-11-21 23:34:46.130857: Epoch 2372 +2024-11-21 23:34:46.130971: Current learning rate: 0.00729 +2024-11-21 23:35:04.666126: train_loss -0.7733 +2024-11-21 23:35:04.666356: val_loss -0.7408 +2024-11-21 23:35:04.666431: Pseudo dice [0.8303] +2024-11-21 23:35:04.666505: Epoch time: 18.54 s +2024-11-21 23:35:05.504191: +2024-11-21 23:35:05.504409: Epoch 2373 +2024-11-21 23:35:05.504521: Current learning rate: 0.00729 +2024-11-21 23:35:23.960551: train_loss -0.7679 +2024-11-21 23:35:23.960768: val_loss -0.7309 +2024-11-21 23:35:23.960842: Pseudo dice [0.8342] +2024-11-21 23:35:23.960918: Epoch time: 18.46 s +2024-11-21 23:35:24.803919: +2024-11-21 23:35:24.804156: Epoch 2374 +2024-11-21 23:35:24.804272: Current learning rate: 0.00728 +2024-11-21 23:35:43.824235: train_loss -0.7707 +2024-11-21 23:35:43.824488: val_loss -0.7361 +2024-11-21 23:35:43.824569: Pseudo dice [0.8394] +2024-11-21 23:35:43.824655: Epoch time: 19.02 s +2024-11-21 23:35:44.664379: +2024-11-21 23:35:44.664601: Epoch 2375 +2024-11-21 23:35:44.664713: Current learning rate: 0.00728 +2024-11-21 23:36:04.022302: train_loss -0.772 +2024-11-21 23:36:04.022515: val_loss -0.7379 +2024-11-21 23:36:04.022626: Pseudo dice [0.8156] +2024-11-21 23:36:04.022756: Epoch time: 19.36 s +2024-11-21 23:36:04.864885: +2024-11-21 23:36:04.865169: Epoch 2376 +2024-11-21 23:36:04.865287: Current learning rate: 0.00728 +2024-11-21 23:36:24.704698: train_loss -0.7705 +2024-11-21 23:36:24.704933: val_loss -0.7281 +2024-11-21 23:36:24.705015: Pseudo dice [0.8378] +2024-11-21 23:36:24.705095: Epoch time: 19.84 s +2024-11-21 23:36:25.587421: +2024-11-21 23:36:25.587626: Epoch 2377 +2024-11-21 23:36:25.587740: Current learning rate: 0.00728 +2024-11-21 23:36:43.782674: train_loss -0.7685 +2024-11-21 23:36:43.782901: val_loss -0.7545 +2024-11-21 23:36:43.782978: Pseudo dice [0.8381] +2024-11-21 23:36:43.783063: Epoch time: 18.2 s +2024-11-21 23:36:44.723615: +2024-11-21 23:36:44.723819: Epoch 2378 +2024-11-21 23:36:44.723934: Current learning rate: 0.00728 +2024-11-21 23:37:02.663860: train_loss -0.7806 +2024-11-21 23:37:02.664117: val_loss -0.7548 +2024-11-21 23:37:02.664195: Pseudo dice [0.8665] +2024-11-21 23:37:02.664283: Epoch time: 17.94 s +2024-11-21 23:37:03.497062: +2024-11-21 23:37:03.497257: Epoch 2379 +2024-11-21 23:37:03.497372: Current learning rate: 0.00728 +2024-11-21 23:37:22.805634: train_loss -0.775 +2024-11-21 23:37:22.805846: val_loss -0.7478 +2024-11-21 23:37:22.805921: Pseudo dice [0.8149] +2024-11-21 23:37:22.806006: Epoch time: 19.31 s +2024-11-21 23:37:23.635863: +2024-11-21 23:37:23.636070: Epoch 2380 +2024-11-21 23:37:23.636180: Current learning rate: 0.00728 +2024-11-21 23:37:42.960874: train_loss -0.7736 +2024-11-21 23:37:42.961095: val_loss -0.7425 +2024-11-21 23:37:42.961170: Pseudo dice [0.8703] +2024-11-21 23:37:42.961263: Epoch time: 19.33 s +2024-11-21 23:37:43.792977: +2024-11-21 23:37:43.793225: Epoch 2381 +2024-11-21 23:37:43.793338: Current learning rate: 0.00728 +2024-11-21 23:38:02.033802: train_loss -0.7734 +2024-11-21 23:38:02.039213: val_loss -0.7383 +2024-11-21 23:38:02.039339: Pseudo dice [0.8272] +2024-11-21 23:38:02.039420: Epoch time: 18.24 s +2024-11-21 23:38:02.952874: +2024-11-21 23:38:02.953114: Epoch 2382 +2024-11-21 23:38:02.953244: Current learning rate: 0.00728 +2024-11-21 23:38:22.297721: train_loss -0.7734 +2024-11-21 23:38:22.297962: val_loss -0.7364 +2024-11-21 23:38:22.298046: Pseudo dice [0.8559] +2024-11-21 23:38:22.298129: Epoch time: 19.35 s +2024-11-21 23:38:23.145560: +2024-11-21 23:38:23.145765: Epoch 2383 +2024-11-21 23:38:23.145880: Current learning rate: 0.00727 +2024-11-21 23:38:42.292675: train_loss -0.7801 +2024-11-21 23:38:42.292888: val_loss -0.7232 +2024-11-21 23:38:42.292962: Pseudo dice [0.8468] +2024-11-21 23:38:42.293046: Epoch time: 19.15 s +2024-11-21 23:38:43.547735: +2024-11-21 23:38:43.547970: Epoch 2384 +2024-11-21 23:38:43.548086: Current learning rate: 0.00727 +2024-11-21 23:39:02.493534: train_loss -0.7653 +2024-11-21 23:39:02.493756: val_loss -0.7394 +2024-11-21 23:39:02.493839: Pseudo dice [0.8518] +2024-11-21 23:39:02.496086: Epoch time: 18.95 s +2024-11-21 23:39:03.395563: +2024-11-21 23:39:03.395763: Epoch 2385 +2024-11-21 23:39:03.395879: Current learning rate: 0.00727 +2024-11-21 23:39:21.602509: train_loss -0.7847 +2024-11-21 23:39:21.602780: val_loss -0.7255 +2024-11-21 23:39:21.602864: Pseudo dice [0.8518] +2024-11-21 23:39:21.602961: Epoch time: 18.21 s +2024-11-21 23:39:22.484318: +2024-11-21 23:39:22.494198: Epoch 2386 +2024-11-21 23:39:22.494323: Current learning rate: 0.00727 +2024-11-21 23:39:41.910752: train_loss -0.7632 +2024-11-21 23:39:41.910968: val_loss -0.7316 +2024-11-21 23:39:41.911072: Pseudo dice [0.8435] +2024-11-21 23:39:41.911157: Epoch time: 19.43 s +2024-11-21 23:39:42.754400: +2024-11-21 23:39:42.754643: Epoch 2387 +2024-11-21 23:39:42.754756: Current learning rate: 0.00727 +2024-11-21 23:40:01.699198: train_loss -0.7706 +2024-11-21 23:40:01.699411: val_loss -0.7192 +2024-11-21 23:40:01.699489: Pseudo dice [0.8272] +2024-11-21 23:40:01.699570: Epoch time: 18.95 s +2024-11-21 23:40:02.562350: +2024-11-21 23:40:02.562550: Epoch 2388 +2024-11-21 23:40:02.562681: Current learning rate: 0.00727 +2024-11-21 23:40:21.028504: train_loss -0.7723 +2024-11-21 23:40:21.028722: val_loss -0.7255 +2024-11-21 23:40:21.028800: Pseudo dice [0.8532] +2024-11-21 23:40:21.028880: Epoch time: 18.47 s +2024-11-21 23:40:22.014334: +2024-11-21 23:40:22.014597: Epoch 2389 +2024-11-21 23:40:22.014710: Current learning rate: 0.00727 +2024-11-21 23:40:40.332927: train_loss -0.7802 +2024-11-21 23:40:40.333183: val_loss -0.741 +2024-11-21 23:40:40.333260: Pseudo dice [0.8106] +2024-11-21 23:40:40.333344: Epoch time: 18.32 s +2024-11-21 23:40:41.185515: +2024-11-21 23:40:41.185715: Epoch 2390 +2024-11-21 23:40:41.185828: Current learning rate: 0.00727 +2024-11-21 23:41:00.009850: train_loss -0.7764 +2024-11-21 23:41:00.010079: val_loss -0.7392 +2024-11-21 23:41:00.015316: Pseudo dice [0.8466] +2024-11-21 23:41:00.015467: Epoch time: 18.83 s +2024-11-21 23:41:00.875090: +2024-11-21 23:41:00.875289: Epoch 2391 +2024-11-21 23:41:00.875398: Current learning rate: 0.00726 +2024-11-21 23:41:18.524013: train_loss -0.7785 +2024-11-21 23:41:18.524223: val_loss -0.7541 +2024-11-21 23:41:18.524298: Pseudo dice [0.817] +2024-11-21 23:41:18.524376: Epoch time: 17.65 s +2024-11-21 23:41:19.371165: +2024-11-21 23:41:19.371394: Epoch 2392 +2024-11-21 23:41:19.371506: Current learning rate: 0.00726 +2024-11-21 23:41:39.469521: train_loss -0.7742 +2024-11-21 23:41:39.469749: val_loss -0.74 +2024-11-21 23:41:39.469830: Pseudo dice [0.8552] +2024-11-21 23:41:39.469914: Epoch time: 20.1 s +2024-11-21 23:41:40.314755: +2024-11-21 23:41:40.314945: Epoch 2393 +2024-11-21 23:41:40.315084: Current learning rate: 0.00726 +2024-11-21 23:41:58.782817: train_loss -0.7904 +2024-11-21 23:41:58.785252: val_loss -0.7618 +2024-11-21 23:41:58.785341: Pseudo dice [0.8532] +2024-11-21 23:41:58.785421: Epoch time: 18.47 s +2024-11-21 23:41:59.746846: +2024-11-21 23:41:59.747105: Epoch 2394 +2024-11-21 23:41:59.747220: Current learning rate: 0.00726 +2024-11-21 23:42:18.299058: train_loss -0.7803 +2024-11-21 23:42:18.299279: val_loss -0.7313 +2024-11-21 23:42:18.299365: Pseudo dice [0.8426] +2024-11-21 23:42:18.299443: Epoch time: 18.55 s +2024-11-21 23:42:19.141390: +2024-11-21 23:42:19.141586: Epoch 2395 +2024-11-21 23:42:19.141695: Current learning rate: 0.00726 +2024-11-21 23:42:38.135304: train_loss -0.7743 +2024-11-21 23:42:38.135526: val_loss -0.7413 +2024-11-21 23:42:38.135603: Pseudo dice [0.8281] +2024-11-21 23:42:38.135681: Epoch time: 18.99 s +2024-11-21 23:42:39.360955: +2024-11-21 23:42:39.361397: Epoch 2396 +2024-11-21 23:42:39.361530: Current learning rate: 0.00726 +2024-11-21 23:42:58.593203: train_loss -0.7803 +2024-11-21 23:42:58.593461: val_loss -0.7567 +2024-11-21 23:42:58.593537: Pseudo dice [0.8331] +2024-11-21 23:42:58.593622: Epoch time: 19.23 s +2024-11-21 23:42:59.448434: +2024-11-21 23:42:59.448916: Epoch 2397 +2024-11-21 23:42:59.449051: Current learning rate: 0.00726 +2024-11-21 23:43:18.692547: train_loss -0.7811 +2024-11-21 23:43:18.692783: val_loss -0.7331 +2024-11-21 23:43:18.692876: Pseudo dice [0.83] +2024-11-21 23:43:18.692971: Epoch time: 19.24 s +2024-11-21 23:43:19.534294: +2024-11-21 23:43:19.534819: Epoch 2398 +2024-11-21 23:43:19.534955: Current learning rate: 0.00726 +2024-11-21 23:43:38.518616: train_loss -0.7796 +2024-11-21 23:43:38.518837: val_loss -0.7399 +2024-11-21 23:43:38.518909: Pseudo dice [0.8276] +2024-11-21 23:43:38.521108: Epoch time: 18.99 s +2024-11-21 23:43:39.450943: +2024-11-21 23:43:39.451427: Epoch 2399 +2024-11-21 23:43:39.451561: Current learning rate: 0.00726 +2024-11-21 23:43:58.299093: train_loss -0.7708 +2024-11-21 23:43:58.299338: val_loss -0.7489 +2024-11-21 23:43:58.299413: Pseudo dice [0.8085] +2024-11-21 23:43:58.299542: Epoch time: 18.85 s +2024-11-21 23:43:59.361315: +2024-11-21 23:43:59.361744: Epoch 2400 +2024-11-21 23:43:59.361882: Current learning rate: 0.00725 +2024-11-21 23:44:18.441098: train_loss -0.7794 +2024-11-21 23:44:18.441319: val_loss -0.7439 +2024-11-21 23:44:18.441401: Pseudo dice [0.8518] +2024-11-21 23:44:18.441501: Epoch time: 19.08 s +2024-11-21 23:44:19.284437: +2024-11-21 23:44:19.284850: Epoch 2401 +2024-11-21 23:44:19.284978: Current learning rate: 0.00725 +2024-11-21 23:44:38.826261: train_loss -0.7829 +2024-11-21 23:44:38.826469: val_loss -0.7358 +2024-11-21 23:44:38.826545: Pseudo dice [0.821] +2024-11-21 23:44:38.826620: Epoch time: 19.54 s +2024-11-21 23:44:39.671600: +2024-11-21 23:44:39.672024: Epoch 2402 +2024-11-21 23:44:39.672163: Current learning rate: 0.00725 +2024-11-21 23:44:57.527704: train_loss -0.7801 +2024-11-21 23:44:57.530077: val_loss -0.7344 +2024-11-21 23:44:57.530169: Pseudo dice [0.8298] +2024-11-21 23:44:57.530246: Epoch time: 17.86 s +2024-11-21 23:44:58.546006: +2024-11-21 23:44:58.546456: Epoch 2403 +2024-11-21 23:44:58.546595: Current learning rate: 0.00725 +2024-11-21 23:45:17.714470: train_loss -0.7822 +2024-11-21 23:45:17.714730: val_loss -0.7579 +2024-11-21 23:45:17.714804: Pseudo dice [0.8381] +2024-11-21 23:45:17.714889: Epoch time: 19.17 s +2024-11-21 23:45:18.573608: +2024-11-21 23:45:18.574070: Epoch 2404 +2024-11-21 23:45:18.574203: Current learning rate: 0.00725 +2024-11-21 23:45:36.724044: train_loss -0.7854 +2024-11-21 23:45:36.724265: val_loss -0.693 +2024-11-21 23:45:36.724350: Pseudo dice [0.8382] +2024-11-21 23:45:36.724431: Epoch time: 18.15 s +2024-11-21 23:45:37.570648: +2024-11-21 23:45:37.571078: Epoch 2405 +2024-11-21 23:45:37.571214: Current learning rate: 0.00725 +2024-11-21 23:45:56.587610: train_loss -0.7835 +2024-11-21 23:45:56.587837: val_loss -0.7447 +2024-11-21 23:45:56.587919: Pseudo dice [0.8256] +2024-11-21 23:45:56.588007: Epoch time: 19.02 s +2024-11-21 23:45:57.503688: +2024-11-21 23:45:57.504133: Epoch 2406 +2024-11-21 23:45:57.504265: Current learning rate: 0.00725 +2024-11-21 23:46:16.244096: train_loss -0.7782 +2024-11-21 23:46:16.244319: val_loss -0.7281 +2024-11-21 23:46:16.244392: Pseudo dice [0.8176] +2024-11-21 23:46:16.244534: Epoch time: 18.74 s +2024-11-21 23:46:17.089629: +2024-11-21 23:46:17.090043: Epoch 2407 +2024-11-21 23:46:17.090179: Current learning rate: 0.00725 +2024-11-21 23:46:36.094398: train_loss -0.7796 +2024-11-21 23:46:36.094630: val_loss -0.71 +2024-11-21 23:46:36.094705: Pseudo dice [0.817] +2024-11-21 23:46:36.094800: Epoch time: 19.01 s +2024-11-21 23:46:36.939085: +2024-11-21 23:46:36.939373: Epoch 2408 +2024-11-21 23:46:36.939485: Current learning rate: 0.00724 +2024-11-21 23:46:54.846873: train_loss -0.7761 +2024-11-21 23:46:54.847101: val_loss -0.7351 +2024-11-21 23:46:54.847176: Pseudo dice [0.8473] +2024-11-21 23:46:54.847250: Epoch time: 17.91 s +2024-11-21 23:46:55.691670: +2024-11-21 23:46:55.691887: Epoch 2409 +2024-11-21 23:46:55.692010: Current learning rate: 0.00724 +2024-11-21 23:47:14.255046: train_loss -0.7793 +2024-11-21 23:47:14.255267: val_loss -0.7219 +2024-11-21 23:47:14.257720: Pseudo dice [0.8518] +2024-11-21 23:47:14.257813: Epoch time: 18.56 s +2024-11-21 23:47:15.089636: +2024-11-21 23:47:15.089865: Epoch 2410 +2024-11-21 23:47:15.089989: Current learning rate: 0.00724 +2024-11-21 23:47:35.362401: train_loss -0.7695 +2024-11-21 23:47:35.362659: val_loss -0.7526 +2024-11-21 23:47:35.362741: Pseudo dice [0.8229] +2024-11-21 23:47:35.362823: Epoch time: 20.27 s +2024-11-21 23:47:36.209679: +2024-11-21 23:47:36.209894: Epoch 2411 +2024-11-21 23:47:36.210006: Current learning rate: 0.00724 +2024-11-21 23:47:54.446480: train_loss -0.7713 +2024-11-21 23:47:54.446713: val_loss -0.7237 +2024-11-21 23:47:54.446791: Pseudo dice [0.8101] +2024-11-21 23:47:54.446876: Epoch time: 18.24 s +2024-11-21 23:47:55.295840: +2024-11-21 23:47:55.296056: Epoch 2412 +2024-11-21 23:47:55.296168: Current learning rate: 0.00724 +2024-11-21 23:48:12.612545: train_loss -0.7717 +2024-11-21 23:48:12.612761: val_loss -0.7272 +2024-11-21 23:48:12.612835: Pseudo dice [0.8082] +2024-11-21 23:48:12.612911: Epoch time: 17.32 s +2024-11-21 23:48:13.481838: +2024-11-21 23:48:13.482063: Epoch 2413 +2024-11-21 23:48:13.482173: Current learning rate: 0.00724 +2024-11-21 23:48:32.159571: train_loss -0.7745 +2024-11-21 23:48:32.159798: val_loss -0.7529 +2024-11-21 23:48:32.159877: Pseudo dice [0.8399] +2024-11-21 23:48:32.159955: Epoch time: 18.68 s +2024-11-21 23:48:33.011406: +2024-11-21 23:48:33.011596: Epoch 2414 +2024-11-21 23:48:33.011704: Current learning rate: 0.00724 +2024-11-21 23:48:50.709939: train_loss -0.7708 +2024-11-21 23:48:50.710192: val_loss -0.7371 +2024-11-21 23:48:50.710274: Pseudo dice [0.8074] +2024-11-21 23:48:50.710363: Epoch time: 17.7 s +2024-11-21 23:48:51.562311: +2024-11-21 23:48:51.562518: Epoch 2415 +2024-11-21 23:48:51.562627: Current learning rate: 0.00724 +2024-11-21 23:49:10.238198: train_loss -0.7764 +2024-11-21 23:49:10.238403: val_loss -0.7454 +2024-11-21 23:49:10.238476: Pseudo dice [0.8464] +2024-11-21 23:49:10.238551: Epoch time: 18.68 s +2024-11-21 23:49:11.084784: +2024-11-21 23:49:11.085164: Epoch 2416 +2024-11-21 23:49:11.085274: Current learning rate: 0.00724 +2024-11-21 23:49:29.767260: train_loss -0.7765 +2024-11-21 23:49:29.767532: val_loss -0.7355 +2024-11-21 23:49:29.767614: Pseudo dice [0.8551] +2024-11-21 23:49:29.767696: Epoch time: 18.68 s +2024-11-21 23:49:30.620779: +2024-11-21 23:49:30.621069: Epoch 2417 +2024-11-21 23:49:30.621187: Current learning rate: 0.00723 +2024-11-21 23:49:48.404015: train_loss -0.7721 +2024-11-21 23:49:48.404227: val_loss -0.7291 +2024-11-21 23:49:48.404303: Pseudo dice [0.8452] +2024-11-21 23:49:48.404384: Epoch time: 17.78 s +2024-11-21 23:49:49.254286: +2024-11-21 23:49:49.254494: Epoch 2418 +2024-11-21 23:49:49.256329: Current learning rate: 0.00723 +2024-11-21 23:50:08.088923: train_loss -0.7732 +2024-11-21 23:50:08.089205: val_loss -0.7372 +2024-11-21 23:50:08.089285: Pseudo dice [0.8323] +2024-11-21 23:50:08.089370: Epoch time: 18.84 s +2024-11-21 23:50:09.371319: +2024-11-21 23:50:09.371556: Epoch 2419 +2024-11-21 23:50:09.371674: Current learning rate: 0.00723 +2024-11-21 23:50:27.528798: train_loss -0.7811 +2024-11-21 23:50:27.529037: val_loss -0.7543 +2024-11-21 23:50:27.529114: Pseudo dice [0.8345] +2024-11-21 23:50:27.529189: Epoch time: 18.16 s +2024-11-21 23:50:28.373272: +2024-11-21 23:50:28.373479: Epoch 2420 +2024-11-21 23:50:28.373592: Current learning rate: 0.00723 +2024-11-21 23:50:47.222406: train_loss -0.7766 +2024-11-21 23:50:47.222690: val_loss -0.7346 +2024-11-21 23:50:47.222767: Pseudo dice [0.8247] +2024-11-21 23:50:47.222845: Epoch time: 18.85 s +2024-11-21 23:50:48.083370: +2024-11-21 23:50:48.083588: Epoch 2421 +2024-11-21 23:50:48.083698: Current learning rate: 0.00723 +2024-11-21 23:51:06.824767: train_loss -0.7694 +2024-11-21 23:51:06.825026: val_loss -0.7342 +2024-11-21 23:51:06.825122: Pseudo dice [0.8413] +2024-11-21 23:51:06.843228: Epoch time: 18.74 s +2024-11-21 23:51:07.695210: +2024-11-21 23:51:07.695416: Epoch 2422 +2024-11-21 23:51:07.695534: Current learning rate: 0.00723 +2024-11-21 23:51:25.361451: train_loss -0.7803 +2024-11-21 23:51:25.361672: val_loss -0.7487 +2024-11-21 23:51:25.361744: Pseudo dice [0.8416] +2024-11-21 23:51:25.364073: Epoch time: 17.67 s +2024-11-21 23:51:26.238746: +2024-11-21 23:51:26.238966: Epoch 2423 +2024-11-21 23:51:26.239082: Current learning rate: 0.00723 +2024-11-21 23:51:44.407417: train_loss -0.7811 +2024-11-21 23:51:44.407642: val_loss -0.7552 +2024-11-21 23:51:44.407723: Pseudo dice [0.8462] +2024-11-21 23:51:44.407805: Epoch time: 18.17 s +2024-11-21 23:51:45.305039: +2024-11-21 23:51:45.305230: Epoch 2424 +2024-11-21 23:51:45.305345: Current learning rate: 0.00723 +2024-11-21 23:52:04.835863: train_loss -0.7793 +2024-11-21 23:52:04.836083: val_loss -0.7261 +2024-11-21 23:52:04.836157: Pseudo dice [0.8363] +2024-11-21 23:52:04.836234: Epoch time: 19.53 s +2024-11-21 23:52:05.686244: +2024-11-21 23:52:05.686450: Epoch 2425 +2024-11-21 23:52:05.686564: Current learning rate: 0.00723 +2024-11-21 23:52:25.402021: train_loss -0.7697 +2024-11-21 23:52:25.402271: val_loss -0.7383 +2024-11-21 23:52:25.404503: Pseudo dice [0.8329] +2024-11-21 23:52:25.404637: Epoch time: 19.72 s +2024-11-21 23:52:26.367418: +2024-11-21 23:52:26.367656: Epoch 2426 +2024-11-21 23:52:26.367773: Current learning rate: 0.00722 +2024-11-21 23:52:45.703625: train_loss -0.7684 +2024-11-21 23:52:45.703856: val_loss -0.7535 +2024-11-21 23:52:45.703938: Pseudo dice [0.8432] +2024-11-21 23:52:45.704018: Epoch time: 19.34 s +2024-11-21 23:52:46.544846: +2024-11-21 23:52:46.545065: Epoch 2427 +2024-11-21 23:52:46.545680: Current learning rate: 0.00722 +2024-11-21 23:53:05.704500: train_loss -0.7742 +2024-11-21 23:53:05.708999: val_loss -0.7588 +2024-11-21 23:53:05.709111: Pseudo dice [0.8383] +2024-11-21 23:53:05.709190: Epoch time: 19.16 s +2024-11-21 23:53:06.591415: +2024-11-21 23:53:06.591619: Epoch 2428 +2024-11-21 23:53:06.591734: Current learning rate: 0.00722 +2024-11-21 23:53:25.260613: train_loss -0.7747 +2024-11-21 23:53:25.260840: val_loss -0.7485 +2024-11-21 23:53:25.263168: Pseudo dice [0.824] +2024-11-21 23:53:25.263305: Epoch time: 18.67 s +2024-11-21 23:53:26.131024: +2024-11-21 23:53:26.131253: Epoch 2429 +2024-11-21 23:53:26.131367: Current learning rate: 0.00722 +2024-11-21 23:53:45.113419: train_loss -0.774 +2024-11-21 23:53:45.113731: val_loss -0.7537 +2024-11-21 23:53:45.113810: Pseudo dice [0.8419] +2024-11-21 23:53:45.113889: Epoch time: 18.98 s +2024-11-21 23:53:45.957057: +2024-11-21 23:53:45.957491: Epoch 2430 +2024-11-21 23:53:45.957625: Current learning rate: 0.00722 +2024-11-21 23:54:03.472642: train_loss -0.7741 +2024-11-21 23:54:03.475061: val_loss -0.7117 +2024-11-21 23:54:03.475200: Pseudo dice [0.8438] +2024-11-21 23:54:03.475281: Epoch time: 17.52 s +2024-11-21 23:54:04.821375: +2024-11-21 23:54:04.821573: Epoch 2431 +2024-11-21 23:54:04.821682: Current learning rate: 0.00722 +2024-11-21 23:54:23.585841: train_loss -0.7772 +2024-11-21 23:54:23.586078: val_loss -0.7743 +2024-11-21 23:54:23.586273: Pseudo dice [0.854] +2024-11-21 23:54:23.586357: Epoch time: 18.77 s +2024-11-21 23:54:24.433249: +2024-11-21 23:54:24.433476: Epoch 2432 +2024-11-21 23:54:24.433587: Current learning rate: 0.00722 +2024-11-21 23:54:43.277107: train_loss -0.7769 +2024-11-21 23:54:43.277334: val_loss -0.727 +2024-11-21 23:54:43.277410: Pseudo dice [0.8392] +2024-11-21 23:54:43.281836: Epoch time: 18.84 s +2024-11-21 23:54:44.257165: +2024-11-21 23:54:44.257380: Epoch 2433 +2024-11-21 23:54:44.257499: Current learning rate: 0.00722 +2024-11-21 23:55:03.899757: train_loss -0.7759 +2024-11-21 23:55:03.899980: val_loss -0.7474 +2024-11-21 23:55:03.900066: Pseudo dice [0.8231] +2024-11-21 23:55:03.900147: Epoch time: 19.64 s +2024-11-21 23:55:04.746373: +2024-11-21 23:55:04.746575: Epoch 2434 +2024-11-21 23:55:04.746693: Current learning rate: 0.00721 +2024-11-21 23:55:23.977126: train_loss -0.7834 +2024-11-21 23:55:23.977357: val_loss -0.7164 +2024-11-21 23:55:23.977432: Pseudo dice [0.8439] +2024-11-21 23:55:23.977511: Epoch time: 19.23 s +2024-11-21 23:55:24.857431: +2024-11-21 23:55:24.857660: Epoch 2435 +2024-11-21 23:55:24.857779: Current learning rate: 0.00721 +2024-11-21 23:55:43.264298: train_loss -0.7716 +2024-11-21 23:55:43.264552: val_loss -0.7435 +2024-11-21 23:55:43.266788: Pseudo dice [0.8434] +2024-11-21 23:55:43.266913: Epoch time: 18.41 s +2024-11-21 23:55:44.144094: +2024-11-21 23:55:44.144288: Epoch 2436 +2024-11-21 23:55:44.144399: Current learning rate: 0.00721 +2024-11-21 23:56:02.683965: train_loss -0.7681 +2024-11-21 23:56:02.684229: val_loss -0.7474 +2024-11-21 23:56:02.684311: Pseudo dice [0.8567] +2024-11-21 23:56:02.684395: Epoch time: 18.54 s +2024-11-21 23:56:03.533245: +2024-11-21 23:56:03.533588: Epoch 2437 +2024-11-21 23:56:03.533703: Current learning rate: 0.00721 +2024-11-21 23:56:21.947099: train_loss -0.7575 +2024-11-21 23:56:21.947328: val_loss -0.7541 +2024-11-21 23:56:21.947401: Pseudo dice [0.8456] +2024-11-21 23:56:21.947479: Epoch time: 18.41 s +2024-11-21 23:56:22.794518: +2024-11-21 23:56:22.794708: Epoch 2438 +2024-11-21 23:56:22.794820: Current learning rate: 0.00721 +2024-11-21 23:56:41.823313: train_loss -0.7721 +2024-11-21 23:56:41.823567: val_loss -0.7068 +2024-11-21 23:56:41.823645: Pseudo dice [0.8157] +2024-11-21 23:56:41.823729: Epoch time: 19.03 s +2024-11-21 23:56:42.677933: +2024-11-21 23:56:42.678150: Epoch 2439 +2024-11-21 23:56:42.678267: Current learning rate: 0.00721 +2024-11-21 23:57:00.306931: train_loss -0.7733 +2024-11-21 23:57:00.307176: val_loss -0.7359 +2024-11-21 23:57:00.319387: Pseudo dice [0.8283] +2024-11-21 23:57:00.319496: Epoch time: 17.63 s +2024-11-21 23:57:01.300252: +2024-11-21 23:57:01.300485: Epoch 2440 +2024-11-21 23:57:01.300605: Current learning rate: 0.00721 +2024-11-21 23:57:19.013189: train_loss -0.7751 +2024-11-21 23:57:19.018613: val_loss -0.7568 +2024-11-21 23:57:19.018705: Pseudo dice [0.8378] +2024-11-21 23:57:19.018785: Epoch time: 17.71 s +2024-11-21 23:57:20.040536: +2024-11-21 23:57:20.040735: Epoch 2441 +2024-11-21 23:57:20.040853: Current learning rate: 0.00721 +2024-11-21 23:57:39.256604: train_loss -0.7735 +2024-11-21 23:57:39.256821: val_loss -0.7344 +2024-11-21 23:57:39.256896: Pseudo dice [0.8224] +2024-11-21 23:57:39.256973: Epoch time: 19.22 s +2024-11-21 23:57:40.120060: +2024-11-21 23:57:40.120277: Epoch 2442 +2024-11-21 23:57:40.120400: Current learning rate: 0.00721 +2024-11-21 23:57:58.145734: train_loss -0.7738 +2024-11-21 23:57:58.145959: val_loss -0.7246 +2024-11-21 23:57:58.146042: Pseudo dice [0.8329] +2024-11-21 23:57:58.146122: Epoch time: 18.03 s +2024-11-21 23:57:59.400167: +2024-11-21 23:57:59.400442: Epoch 2443 +2024-11-21 23:57:59.400562: Current learning rate: 0.0072 +2024-11-21 23:58:18.464252: train_loss -0.7759 +2024-11-21 23:58:18.465020: val_loss -0.7226 +2024-11-21 23:58:18.465111: Pseudo dice [0.8263] +2024-11-21 23:58:18.465191: Epoch time: 19.06 s +2024-11-21 23:58:19.314418: +2024-11-21 23:58:19.314646: Epoch 2444 +2024-11-21 23:58:19.314762: Current learning rate: 0.0072 +2024-11-21 23:58:37.485028: train_loss -0.7773 +2024-11-21 23:58:37.487400: val_loss -0.7428 +2024-11-21 23:58:37.487486: Pseudo dice [0.8296] +2024-11-21 23:58:37.487567: Epoch time: 18.17 s +2024-11-21 23:58:38.384212: +2024-11-21 23:58:38.384432: Epoch 2445 +2024-11-21 23:58:38.384546: Current learning rate: 0.0072 +2024-11-21 23:58:57.465508: train_loss -0.782 +2024-11-21 23:58:57.465726: val_loss -0.7441 +2024-11-21 23:58:57.465803: Pseudo dice [0.8428] +2024-11-21 23:58:57.465879: Epoch time: 19.08 s +2024-11-21 23:58:58.418195: +2024-11-21 23:58:58.418385: Epoch 2446 +2024-11-21 23:58:58.418502: Current learning rate: 0.0072 +2024-11-21 23:59:17.326531: train_loss -0.7756 +2024-11-21 23:59:17.326846: val_loss -0.7407 +2024-11-21 23:59:17.326924: Pseudo dice [0.8395] +2024-11-21 23:59:17.327021: Epoch time: 18.91 s +2024-11-21 23:59:18.177070: +2024-11-21 23:59:18.177275: Epoch 2447 +2024-11-21 23:59:18.177384: Current learning rate: 0.0072 +2024-11-21 23:59:36.752730: train_loss -0.7793 +2024-11-21 23:59:36.752940: val_loss -0.7506 +2024-11-21 23:59:36.753020: Pseudo dice [0.8431] +2024-11-21 23:59:36.753097: Epoch time: 18.58 s +2024-11-21 23:59:37.619300: +2024-11-21 23:59:37.619502: Epoch 2448 +2024-11-21 23:59:37.619618: Current learning rate: 0.0072 +2024-11-21 23:59:56.355158: train_loss -0.7824 +2024-11-21 23:59:56.355403: val_loss -0.7315 +2024-11-21 23:59:56.355483: Pseudo dice [0.8355] +2024-11-21 23:59:56.355562: Epoch time: 18.74 s +2024-11-21 23:59:57.344043: +2024-11-21 23:59:57.344270: Epoch 2449 +2024-11-21 23:59:57.344385: Current learning rate: 0.0072 +2024-11-22 00:00:17.079824: train_loss -0.7748 +2024-11-22 00:00:17.080117: val_loss -0.7421 +2024-11-22 00:00:17.080200: Pseudo dice [0.831] +2024-11-22 00:00:17.080286: Epoch time: 19.74 s +2024-11-22 00:00:18.154178: +2024-11-22 00:00:18.154398: Epoch 2450 +2024-11-22 00:00:18.154518: Current learning rate: 0.0072 +2024-11-22 00:00:36.286635: train_loss -0.7778 +2024-11-22 00:00:36.286939: val_loss -0.7456 +2024-11-22 00:00:36.287026: Pseudo dice [0.8276] +2024-11-22 00:00:36.287108: Epoch time: 18.13 s +2024-11-22 00:00:37.137240: +2024-11-22 00:00:37.137500: Epoch 2451 +2024-11-22 00:00:37.137615: Current learning rate: 0.00719 +2024-11-22 00:00:56.340841: train_loss -0.7767 +2024-11-22 00:00:56.346235: val_loss -0.749 +2024-11-22 00:00:56.346344: Pseudo dice [0.8421] +2024-11-22 00:00:56.346432: Epoch time: 19.2 s +2024-11-22 00:00:57.210837: +2024-11-22 00:00:57.211075: Epoch 2452 +2024-11-22 00:00:57.211187: Current learning rate: 0.00719 +2024-11-22 00:01:16.009477: train_loss -0.7838 +2024-11-22 00:01:16.009700: val_loss -0.7445 +2024-11-22 00:01:16.009775: Pseudo dice [0.8375] +2024-11-22 00:01:16.009852: Epoch time: 18.8 s +2024-11-22 00:01:16.849745: +2024-11-22 00:01:16.850074: Epoch 2453 +2024-11-22 00:01:16.850195: Current learning rate: 0.00719 +2024-11-22 00:01:35.268550: train_loss -0.7829 +2024-11-22 00:01:35.273998: val_loss -0.7045 +2024-11-22 00:01:35.274123: Pseudo dice [0.8486] +2024-11-22 00:01:35.274215: Epoch time: 18.42 s +2024-11-22 00:01:36.244406: +2024-11-22 00:01:36.244610: Epoch 2454 +2024-11-22 00:01:36.244724: Current learning rate: 0.00719 +2024-11-22 00:01:55.373505: train_loss -0.7793 +2024-11-22 00:01:55.373728: val_loss -0.7336 +2024-11-22 00:01:55.373808: Pseudo dice [0.8489] +2024-11-22 00:01:55.373883: Epoch time: 19.13 s +2024-11-22 00:01:56.213124: +2024-11-22 00:01:56.213339: Epoch 2455 +2024-11-22 00:01:56.213450: Current learning rate: 0.00719 +2024-11-22 00:02:14.443701: train_loss -0.7867 +2024-11-22 00:02:14.443995: val_loss -0.7581 +2024-11-22 00:02:14.444084: Pseudo dice [0.8318] +2024-11-22 00:02:14.444164: Epoch time: 18.23 s +2024-11-22 00:02:15.291500: +2024-11-22 00:02:15.291728: Epoch 2456 +2024-11-22 00:02:15.291843: Current learning rate: 0.00719 +2024-11-22 00:02:33.508436: train_loss -0.7819 +2024-11-22 00:02:33.508659: val_loss -0.741 +2024-11-22 00:02:33.508735: Pseudo dice [0.8155] +2024-11-22 00:02:33.508817: Epoch time: 18.22 s +2024-11-22 00:02:34.360854: +2024-11-22 00:02:34.361099: Epoch 2457 +2024-11-22 00:02:34.361255: Current learning rate: 0.00719 +2024-11-22 00:02:53.421192: train_loss -0.7703 +2024-11-22 00:02:53.421425: val_loss -0.7181 +2024-11-22 00:02:53.421502: Pseudo dice [0.8384] +2024-11-22 00:02:53.421578: Epoch time: 19.06 s +2024-11-22 00:02:54.270277: +2024-11-22 00:02:54.270497: Epoch 2458 +2024-11-22 00:02:54.270610: Current learning rate: 0.00719 +2024-11-22 00:03:12.824180: train_loss -0.7649 +2024-11-22 00:03:12.824434: val_loss -0.7232 +2024-11-22 00:03:12.824518: Pseudo dice [0.827] +2024-11-22 00:03:12.824601: Epoch time: 18.55 s +2024-11-22 00:03:13.673981: +2024-11-22 00:03:13.674285: Epoch 2459 +2024-11-22 00:03:13.674406: Current learning rate: 0.00719 +2024-11-22 00:03:31.514529: train_loss -0.7654 +2024-11-22 00:03:31.514745: val_loss -0.7271 +2024-11-22 00:03:31.514840: Pseudo dice [0.8319] +2024-11-22 00:03:31.514925: Epoch time: 17.84 s +2024-11-22 00:03:32.364685: +2024-11-22 00:03:32.364936: Epoch 2460 +2024-11-22 00:03:32.365056: Current learning rate: 0.00718 +2024-11-22 00:03:51.203224: train_loss -0.7655 +2024-11-22 00:03:51.203456: val_loss -0.7271 +2024-11-22 00:03:51.203541: Pseudo dice [0.8222] +2024-11-22 00:03:51.203619: Epoch time: 18.84 s +2024-11-22 00:03:52.048223: +2024-11-22 00:03:52.048437: Epoch 2461 +2024-11-22 00:03:52.048556: Current learning rate: 0.00718 +2024-11-22 00:04:10.228644: train_loss -0.7662 +2024-11-22 00:04:10.228895: val_loss -0.7392 +2024-11-22 00:04:10.228972: Pseudo dice [0.8544] +2024-11-22 00:04:10.229062: Epoch time: 18.18 s +2024-11-22 00:04:11.075679: +2024-11-22 00:04:11.075961: Epoch 2462 +2024-11-22 00:04:11.076082: Current learning rate: 0.00718 +2024-11-22 00:04:30.706555: train_loss -0.773 +2024-11-22 00:04:30.706777: val_loss -0.7382 +2024-11-22 00:04:30.706853: Pseudo dice [0.8222] +2024-11-22 00:04:30.706930: Epoch time: 19.63 s +2024-11-22 00:04:31.560059: +2024-11-22 00:04:31.560319: Epoch 2463 +2024-11-22 00:04:31.560433: Current learning rate: 0.00718 +2024-11-22 00:04:50.417012: train_loss -0.7609 +2024-11-22 00:04:50.417228: val_loss -0.7155 +2024-11-22 00:04:50.417304: Pseudo dice [0.8278] +2024-11-22 00:04:50.417379: Epoch time: 18.86 s +2024-11-22 00:04:51.268297: +2024-11-22 00:04:51.268574: Epoch 2464 +2024-11-22 00:04:51.268686: Current learning rate: 0.00718 +2024-11-22 00:05:10.423125: train_loss -0.757 +2024-11-22 00:05:10.423383: val_loss -0.7352 +2024-11-22 00:05:10.423459: Pseudo dice [0.8475] +2024-11-22 00:05:10.423546: Epoch time: 19.16 s +2024-11-22 00:05:11.271379: +2024-11-22 00:05:11.271568: Epoch 2465 +2024-11-22 00:05:11.271680: Current learning rate: 0.00718 +2024-11-22 00:05:29.509376: train_loss -0.7719 +2024-11-22 00:05:29.509590: val_loss -0.7552 +2024-11-22 00:05:29.509665: Pseudo dice [0.8457] +2024-11-22 00:05:29.509758: Epoch time: 18.24 s +2024-11-22 00:05:30.748263: +2024-11-22 00:05:30.748503: Epoch 2466 +2024-11-22 00:05:30.748622: Current learning rate: 0.00718 +2024-11-22 00:05:49.056162: train_loss -0.7883 +2024-11-22 00:05:49.056384: val_loss -0.7563 +2024-11-22 00:05:49.056463: Pseudo dice [0.8305] +2024-11-22 00:05:49.056548: Epoch time: 18.31 s +2024-11-22 00:05:49.898355: +2024-11-22 00:05:49.898576: Epoch 2467 +2024-11-22 00:05:49.898686: Current learning rate: 0.00718 +2024-11-22 00:06:09.678699: train_loss -0.7735 +2024-11-22 00:06:09.678949: val_loss -0.7526 +2024-11-22 00:06:09.679037: Pseudo dice [0.823] +2024-11-22 00:06:09.679154: Epoch time: 19.78 s +2024-11-22 00:06:10.527556: +2024-11-22 00:06:10.527859: Epoch 2468 +2024-11-22 00:06:10.527974: Current learning rate: 0.00717 +2024-11-22 00:06:29.635578: train_loss -0.7756 +2024-11-22 00:06:29.635854: val_loss -0.7546 +2024-11-22 00:06:29.635931: Pseudo dice [0.8462] +2024-11-22 00:06:29.636013: Epoch time: 19.11 s +2024-11-22 00:06:30.482544: +2024-11-22 00:06:30.482740: Epoch 2469 +2024-11-22 00:06:30.482854: Current learning rate: 0.00717 +2024-11-22 00:06:49.760807: train_loss -0.7861 +2024-11-22 00:06:49.761029: val_loss -0.7495 +2024-11-22 00:06:49.761105: Pseudo dice [0.8256] +2024-11-22 00:06:49.761181: Epoch time: 19.28 s +2024-11-22 00:06:50.610371: +2024-11-22 00:06:50.610646: Epoch 2470 +2024-11-22 00:06:50.610770: Current learning rate: 0.00717 +2024-11-22 00:07:09.292000: train_loss -0.7836 +2024-11-22 00:07:09.292235: val_loss -0.7498 +2024-11-22 00:07:09.292317: Pseudo dice [0.8344] +2024-11-22 00:07:09.292395: Epoch time: 18.68 s +2024-11-22 00:07:10.145014: +2024-11-22 00:07:10.145226: Epoch 2471 +2024-11-22 00:07:10.145338: Current learning rate: 0.00717 +2024-11-22 00:07:29.475702: train_loss -0.7762 +2024-11-22 00:07:29.475957: val_loss -0.7449 +2024-11-22 00:07:29.476054: Pseudo dice [0.8392] +2024-11-22 00:07:29.476140: Epoch time: 19.33 s +2024-11-22 00:07:30.328907: +2024-11-22 00:07:30.329127: Epoch 2472 +2024-11-22 00:07:30.329240: Current learning rate: 0.00717 +2024-11-22 00:07:49.529106: train_loss -0.7854 +2024-11-22 00:07:49.529331: val_loss -0.727 +2024-11-22 00:07:49.529409: Pseudo dice [0.8212] +2024-11-22 00:07:49.534623: Epoch time: 19.2 s +2024-11-22 00:07:50.404783: +2024-11-22 00:07:50.404979: Epoch 2473 +2024-11-22 00:07:50.405097: Current learning rate: 0.00717 +2024-11-22 00:08:08.613653: train_loss -0.7767 +2024-11-22 00:08:08.613884: val_loss -0.7308 +2024-11-22 00:08:08.613961: Pseudo dice [0.8378] +2024-11-22 00:08:08.614045: Epoch time: 18.21 s +2024-11-22 00:08:09.459660: +2024-11-22 00:08:09.459847: Epoch 2474 +2024-11-22 00:08:09.459958: Current learning rate: 0.00717 +2024-11-22 00:08:28.977648: train_loss -0.7782 +2024-11-22 00:08:28.977911: val_loss -0.7462 +2024-11-22 00:08:28.977987: Pseudo dice [0.8362] +2024-11-22 00:08:28.978084: Epoch time: 19.52 s +2024-11-22 00:08:29.844595: +2024-11-22 00:08:29.844832: Epoch 2475 +2024-11-22 00:08:29.844941: Current learning rate: 0.00717 +2024-11-22 00:08:48.254685: train_loss -0.7843 +2024-11-22 00:08:48.254935: val_loss -0.7357 +2024-11-22 00:08:48.255030: Pseudo dice [0.836] +2024-11-22 00:08:48.255114: Epoch time: 18.41 s +2024-11-22 00:08:49.105438: +2024-11-22 00:08:49.105660: Epoch 2476 +2024-11-22 00:08:49.105779: Current learning rate: 0.00717 +2024-11-22 00:09:08.761090: train_loss -0.7777 +2024-11-22 00:09:08.761339: val_loss -0.7524 +2024-11-22 00:09:08.761429: Pseudo dice [0.8078] +2024-11-22 00:09:08.761510: Epoch time: 19.66 s +2024-11-22 00:09:09.608214: +2024-11-22 00:09:09.608415: Epoch 2477 +2024-11-22 00:09:09.608524: Current learning rate: 0.00716 +2024-11-22 00:09:28.139533: train_loss -0.7762 +2024-11-22 00:09:28.139756: val_loss -0.7614 +2024-11-22 00:09:28.139829: Pseudo dice [0.8382] +2024-11-22 00:09:28.139905: Epoch time: 18.53 s +2024-11-22 00:09:29.401721: +2024-11-22 00:09:29.401975: Epoch 2478 +2024-11-22 00:09:29.402094: Current learning rate: 0.00716 +2024-11-22 00:09:48.897161: train_loss -0.7793 +2024-11-22 00:09:48.898103: val_loss -0.7133 +2024-11-22 00:09:48.898194: Pseudo dice [0.8136] +2024-11-22 00:09:48.898281: Epoch time: 19.5 s +2024-11-22 00:09:49.751397: +2024-11-22 00:09:49.751640: Epoch 2479 +2024-11-22 00:09:49.751750: Current learning rate: 0.00716 +2024-11-22 00:10:07.284570: train_loss -0.7827 +2024-11-22 00:10:07.284869: val_loss -0.7608 +2024-11-22 00:10:07.284953: Pseudo dice [0.8512] +2024-11-22 00:10:07.285039: Epoch time: 17.53 s +2024-11-22 00:10:08.131459: +2024-11-22 00:10:08.131696: Epoch 2480 +2024-11-22 00:10:08.131814: Current learning rate: 0.00716 +2024-11-22 00:10:26.463640: train_loss -0.7851 +2024-11-22 00:10:26.463869: val_loss -0.7408 +2024-11-22 00:10:26.463943: Pseudo dice [0.8322] +2024-11-22 00:10:26.464032: Epoch time: 18.33 s +2024-11-22 00:10:27.306348: +2024-11-22 00:10:27.306621: Epoch 2481 +2024-11-22 00:10:27.306734: Current learning rate: 0.00716 +2024-11-22 00:10:46.700903: train_loss -0.7826 +2024-11-22 00:10:46.701169: val_loss -0.7193 +2024-11-22 00:10:46.701244: Pseudo dice [0.8306] +2024-11-22 00:10:46.701329: Epoch time: 19.4 s +2024-11-22 00:10:47.552770: +2024-11-22 00:10:47.552970: Epoch 2482 +2024-11-22 00:10:47.553091: Current learning rate: 0.00716 +2024-11-22 00:11:05.303633: train_loss -0.7817 +2024-11-22 00:11:05.303916: val_loss -0.7365 +2024-11-22 00:11:05.304003: Pseudo dice [0.8292] +2024-11-22 00:11:05.304088: Epoch time: 17.75 s +2024-11-22 00:11:06.153832: +2024-11-22 00:11:06.154040: Epoch 2483 +2024-11-22 00:11:06.154150: Current learning rate: 0.00716 +2024-11-22 00:11:24.262500: train_loss -0.783 +2024-11-22 00:11:24.262717: val_loss -0.7307 +2024-11-22 00:11:24.262793: Pseudo dice [0.8342] +2024-11-22 00:11:24.262871: Epoch time: 18.11 s +2024-11-22 00:11:25.107543: +2024-11-22 00:11:25.107776: Epoch 2484 +2024-11-22 00:11:25.107890: Current learning rate: 0.00716 +2024-11-22 00:11:44.015882: train_loss -0.7885 +2024-11-22 00:11:44.016115: val_loss -0.758 +2024-11-22 00:11:44.016212: Pseudo dice [0.8618] +2024-11-22 00:11:44.016292: Epoch time: 18.91 s +2024-11-22 00:11:44.863608: +2024-11-22 00:11:44.863802: Epoch 2485 +2024-11-22 00:11:44.863910: Current learning rate: 0.00716 +2024-11-22 00:12:04.164409: train_loss -0.7736 +2024-11-22 00:12:04.164667: val_loss -0.7643 +2024-11-22 00:12:04.164781: Pseudo dice [0.8424] +2024-11-22 00:12:04.164871: Epoch time: 19.3 s +2024-11-22 00:12:05.015284: +2024-11-22 00:12:05.015483: Epoch 2486 +2024-11-22 00:12:05.015593: Current learning rate: 0.00715 +2024-11-22 00:12:24.372176: train_loss -0.7722 +2024-11-22 00:12:24.374195: val_loss -0.733 +2024-11-22 00:12:24.374284: Pseudo dice [0.802] +2024-11-22 00:12:24.374363: Epoch time: 19.36 s +2024-11-22 00:12:25.230600: +2024-11-22 00:12:25.230792: Epoch 2487 +2024-11-22 00:12:25.230903: Current learning rate: 0.00715 +2024-11-22 00:12:44.113164: train_loss -0.7734 +2024-11-22 00:12:44.113454: val_loss -0.741 +2024-11-22 00:12:44.113534: Pseudo dice [0.8541] +2024-11-22 00:12:44.113611: Epoch time: 18.88 s +2024-11-22 00:12:44.988184: +2024-11-22 00:12:44.988548: Epoch 2488 +2024-11-22 00:12:44.988666: Current learning rate: 0.00715 +2024-11-22 00:13:03.774276: train_loss -0.7662 +2024-11-22 00:13:03.774508: val_loss -0.7518 +2024-11-22 00:13:03.774588: Pseudo dice [0.8414] +2024-11-22 00:13:03.774670: Epoch time: 18.79 s +2024-11-22 00:13:04.625852: +2024-11-22 00:13:04.626076: Epoch 2489 +2024-11-22 00:13:04.626196: Current learning rate: 0.00715 +2024-11-22 00:13:23.790702: train_loss -0.7758 +2024-11-22 00:13:23.790951: val_loss -0.7247 +2024-11-22 00:13:23.791967: Pseudo dice [0.8361] +2024-11-22 00:13:23.792089: Epoch time: 19.17 s +2024-11-22 00:13:25.055157: +2024-11-22 00:13:25.055414: Epoch 2490 +2024-11-22 00:13:25.055525: Current learning rate: 0.00715 +2024-11-22 00:13:43.856478: train_loss -0.7833 +2024-11-22 00:13:43.856703: val_loss -0.7447 +2024-11-22 00:13:43.856775: Pseudo dice [0.8443] +2024-11-22 00:13:43.856851: Epoch time: 18.8 s +2024-11-22 00:13:44.816628: +2024-11-22 00:13:44.816871: Epoch 2491 +2024-11-22 00:13:44.816984: Current learning rate: 0.00715 +2024-11-22 00:14:04.515833: train_loss -0.7774 +2024-11-22 00:14:04.516087: val_loss -0.719 +2024-11-22 00:14:04.516165: Pseudo dice [0.843] +2024-11-22 00:14:04.516242: Epoch time: 19.7 s +2024-11-22 00:14:05.348200: +2024-11-22 00:14:05.348448: Epoch 2492 +2024-11-22 00:14:05.348562: Current learning rate: 0.00715 +2024-11-22 00:14:23.848139: train_loss -0.7898 +2024-11-22 00:14:23.848389: val_loss -0.7267 +2024-11-22 00:14:23.848466: Pseudo dice [0.843] +2024-11-22 00:14:23.848550: Epoch time: 18.5 s +2024-11-22 00:14:24.688959: +2024-11-22 00:14:24.689203: Epoch 2493 +2024-11-22 00:14:24.689317: Current learning rate: 0.00715 +2024-11-22 00:14:44.356891: train_loss -0.7761 +2024-11-22 00:14:44.357118: val_loss -0.7374 +2024-11-22 00:14:44.357196: Pseudo dice [0.8274] +2024-11-22 00:14:44.357270: Epoch time: 19.67 s +2024-11-22 00:14:45.328519: +2024-11-22 00:14:45.328728: Epoch 2494 +2024-11-22 00:14:45.328844: Current learning rate: 0.00714 +2024-11-22 00:15:03.898264: train_loss -0.773 +2024-11-22 00:15:03.898476: val_loss -0.7352 +2024-11-22 00:15:03.898551: Pseudo dice [0.8517] +2024-11-22 00:15:03.898626: Epoch time: 18.57 s +2024-11-22 00:15:04.970014: +2024-11-22 00:15:04.970214: Epoch 2495 +2024-11-22 00:15:04.970331: Current learning rate: 0.00714 +2024-11-22 00:15:23.418258: train_loss -0.7819 +2024-11-22 00:15:23.418470: val_loss -0.7352 +2024-11-22 00:15:23.418543: Pseudo dice [0.8385] +2024-11-22 00:15:23.418619: Epoch time: 18.45 s +2024-11-22 00:15:24.266767: +2024-11-22 00:15:24.267002: Epoch 2496 +2024-11-22 00:15:24.267110: Current learning rate: 0.00714 +2024-11-22 00:15:42.883869: train_loss -0.7807 +2024-11-22 00:15:42.884101: val_loss -0.7597 +2024-11-22 00:15:42.886346: Pseudo dice [0.8448] +2024-11-22 00:15:42.886482: Epoch time: 18.62 s +2024-11-22 00:15:43.768405: +2024-11-22 00:15:43.768616: Epoch 2497 +2024-11-22 00:15:43.768723: Current learning rate: 0.00714 +2024-11-22 00:16:02.141129: train_loss -0.7733 +2024-11-22 00:16:02.141368: val_loss -0.7314 +2024-11-22 00:16:02.141447: Pseudo dice [0.8405] +2024-11-22 00:16:02.141590: Epoch time: 18.37 s +2024-11-22 00:16:02.995743: +2024-11-22 00:16:02.996061: Epoch 2498 +2024-11-22 00:16:02.996177: Current learning rate: 0.00714 +2024-11-22 00:16:21.961444: train_loss -0.7863 +2024-11-22 00:16:21.961659: val_loss -0.7423 +2024-11-22 00:16:21.961736: Pseudo dice [0.8448] +2024-11-22 00:16:21.961819: Epoch time: 18.97 s +2024-11-22 00:16:22.808375: +2024-11-22 00:16:22.808623: Epoch 2499 +2024-11-22 00:16:22.808734: Current learning rate: 0.00714 +2024-11-22 00:16:42.790882: train_loss -0.7768 +2024-11-22 00:16:42.791101: val_loss -0.7444 +2024-11-22 00:16:42.791178: Pseudo dice [0.8361] +2024-11-22 00:16:42.791257: Epoch time: 19.98 s +2024-11-22 00:16:43.845661: +2024-11-22 00:16:43.845879: Epoch 2500 +2024-11-22 00:16:43.845996: Current learning rate: 0.00714 +2024-11-22 00:17:01.828522: train_loss -0.7769 +2024-11-22 00:17:01.828852: val_loss -0.7274 +2024-11-22 00:17:01.828932: Pseudo dice [0.8234] +2024-11-22 00:17:01.829026: Epoch time: 17.98 s +2024-11-22 00:17:02.741621: +2024-11-22 00:17:02.741872: Epoch 2501 +2024-11-22 00:17:02.741979: Current learning rate: 0.00714 +2024-11-22 00:17:21.592655: train_loss -0.7787 +2024-11-22 00:17:21.592887: val_loss -0.7587 +2024-11-22 00:17:21.592964: Pseudo dice [0.829] +2024-11-22 00:17:21.593047: Epoch time: 18.85 s +2024-11-22 00:17:22.439752: +2024-11-22 00:17:22.439970: Epoch 2502 +2024-11-22 00:17:22.440090: Current learning rate: 0.00714 +2024-11-22 00:17:41.117408: train_loss -0.7772 +2024-11-22 00:17:41.117708: val_loss -0.7403 +2024-11-22 00:17:41.117789: Pseudo dice [0.8021] +2024-11-22 00:17:41.117867: Epoch time: 18.68 s +2024-11-22 00:17:41.962342: +2024-11-22 00:17:41.962586: Epoch 2503 +2024-11-22 00:17:41.962705: Current learning rate: 0.00713 +2024-11-22 00:18:01.915204: train_loss -0.7779 +2024-11-22 00:18:01.915938: val_loss -0.727 +2024-11-22 00:18:01.916027: Pseudo dice [0.8193] +2024-11-22 00:18:01.916112: Epoch time: 19.95 s +2024-11-22 00:18:02.765136: +2024-11-22 00:18:02.765365: Epoch 2504 +2024-11-22 00:18:02.765482: Current learning rate: 0.00713 +2024-11-22 00:18:21.262791: train_loss -0.7843 +2024-11-22 00:18:21.263013: val_loss -0.736 +2024-11-22 00:18:21.263089: Pseudo dice [0.8326] +2024-11-22 00:18:21.263164: Epoch time: 18.5 s +2024-11-22 00:18:22.149396: +2024-11-22 00:18:22.149623: Epoch 2505 +2024-11-22 00:18:22.149730: Current learning rate: 0.00713 +2024-11-22 00:18:41.319523: train_loss -0.7846 +2024-11-22 00:18:41.319741: val_loss -0.7512 +2024-11-22 00:18:41.319818: Pseudo dice [0.8415] +2024-11-22 00:18:41.319911: Epoch time: 19.17 s +2024-11-22 00:18:42.174722: +2024-11-22 00:18:42.174925: Epoch 2506 +2024-11-22 00:18:42.175038: Current learning rate: 0.00713 +2024-11-22 00:19:00.864391: train_loss -0.7839 +2024-11-22 00:19:00.864602: val_loss -0.7448 +2024-11-22 00:19:00.864679: Pseudo dice [0.8393] +2024-11-22 00:19:00.864756: Epoch time: 18.69 s +2024-11-22 00:19:01.714966: +2024-11-22 00:19:01.715158: Epoch 2507 +2024-11-22 00:19:01.715271: Current learning rate: 0.00713 +2024-11-22 00:19:20.181317: train_loss -0.7864 +2024-11-22 00:19:20.181563: val_loss -0.7566 +2024-11-22 00:19:20.181641: Pseudo dice [0.8428] +2024-11-22 00:19:20.181773: Epoch time: 18.47 s +2024-11-22 00:19:21.040388: +2024-11-22 00:19:21.040587: Epoch 2508 +2024-11-22 00:19:21.040700: Current learning rate: 0.00713 +2024-11-22 00:19:39.764086: train_loss -0.7821 +2024-11-22 00:19:39.764299: val_loss -0.7481 +2024-11-22 00:19:39.764380: Pseudo dice [0.8179] +2024-11-22 00:19:39.764454: Epoch time: 18.72 s +2024-11-22 00:19:40.613389: +2024-11-22 00:19:40.613604: Epoch 2509 +2024-11-22 00:19:40.613720: Current learning rate: 0.00713 +2024-11-22 00:19:59.299812: train_loss -0.7786 +2024-11-22 00:19:59.300036: val_loss -0.749 +2024-11-22 00:19:59.300111: Pseudo dice [0.8461] +2024-11-22 00:19:59.300184: Epoch time: 18.69 s +2024-11-22 00:20:00.189907: +2024-11-22 00:20:00.190110: Epoch 2510 +2024-11-22 00:20:00.190228: Current learning rate: 0.00713 +2024-11-22 00:20:18.112381: train_loss -0.7937 +2024-11-22 00:20:18.112611: val_loss -0.7403 +2024-11-22 00:20:18.112703: Pseudo dice [0.8552] +2024-11-22 00:20:18.112789: Epoch time: 17.92 s +2024-11-22 00:20:18.965814: +2024-11-22 00:20:18.966035: Epoch 2511 +2024-11-22 00:20:18.966145: Current learning rate: 0.00712 +2024-11-22 00:20:37.732033: train_loss -0.7864 +2024-11-22 00:20:37.732279: val_loss -0.7555 +2024-11-22 00:20:37.732353: Pseudo dice [0.8347] +2024-11-22 00:20:37.732433: Epoch time: 18.77 s +2024-11-22 00:20:38.585128: +2024-11-22 00:20:38.585375: Epoch 2512 +2024-11-22 00:20:38.585484: Current learning rate: 0.00712 +2024-11-22 00:20:58.328518: train_loss -0.7714 +2024-11-22 00:20:58.328740: val_loss -0.714 +2024-11-22 00:20:58.328820: Pseudo dice [0.8155] +2024-11-22 00:20:58.328902: Epoch time: 19.74 s +2024-11-22 00:20:59.558358: +2024-11-22 00:20:59.558658: Epoch 2513 +2024-11-22 00:20:59.558772: Current learning rate: 0.00712 +2024-11-22 00:21:17.732814: train_loss -0.7788 +2024-11-22 00:21:17.733349: val_loss -0.7628 +2024-11-22 00:21:17.733452: Pseudo dice [0.8192] +2024-11-22 00:21:17.733538: Epoch time: 18.18 s +2024-11-22 00:21:18.587410: +2024-11-22 00:21:18.587627: Epoch 2514 +2024-11-22 00:21:18.587740: Current learning rate: 0.00712 +2024-11-22 00:21:37.339998: train_loss -0.7837 +2024-11-22 00:21:37.340310: val_loss -0.7409 +2024-11-22 00:21:37.340390: Pseudo dice [0.8369] +2024-11-22 00:21:37.340472: Epoch time: 18.75 s +2024-11-22 00:21:38.189238: +2024-11-22 00:21:38.189448: Epoch 2515 +2024-11-22 00:21:38.189559: Current learning rate: 0.00712 +2024-11-22 00:21:56.155933: train_loss -0.7866 +2024-11-22 00:21:56.156153: val_loss -0.7533 +2024-11-22 00:21:56.156232: Pseudo dice [0.8406] +2024-11-22 00:21:56.156313: Epoch time: 17.97 s +2024-11-22 00:21:57.008853: +2024-11-22 00:21:57.009072: Epoch 2516 +2024-11-22 00:21:57.009193: Current learning rate: 0.00712 +2024-11-22 00:22:15.188348: train_loss -0.782 +2024-11-22 00:22:15.188571: val_loss -0.7629 +2024-11-22 00:22:15.188648: Pseudo dice [0.8155] +2024-11-22 00:22:15.188726: Epoch time: 18.18 s +2024-11-22 00:22:16.040245: +2024-11-22 00:22:16.040467: Epoch 2517 +2024-11-22 00:22:16.040585: Current learning rate: 0.00712 +2024-11-22 00:22:33.907330: train_loss -0.7919 +2024-11-22 00:22:33.907590: val_loss -0.7281 +2024-11-22 00:22:33.907666: Pseudo dice [0.8468] +2024-11-22 00:22:33.907749: Epoch time: 17.87 s +2024-11-22 00:22:34.861320: +2024-11-22 00:22:34.861540: Epoch 2518 +2024-11-22 00:22:34.861653: Current learning rate: 0.00712 +2024-11-22 00:22:53.183065: train_loss -0.8012 +2024-11-22 00:22:53.183341: val_loss -0.7491 +2024-11-22 00:22:53.183420: Pseudo dice [0.8384] +2024-11-22 00:22:53.183495: Epoch time: 18.32 s +2024-11-22 00:22:54.033949: +2024-11-22 00:22:54.034168: Epoch 2519 +2024-11-22 00:22:54.034281: Current learning rate: 0.00712 +2024-11-22 00:23:12.304543: train_loss -0.7736 +2024-11-22 00:23:12.304791: val_loss -0.7028 +2024-11-22 00:23:12.304869: Pseudo dice [0.8381] +2024-11-22 00:23:12.306778: Epoch time: 18.27 s +2024-11-22 00:23:13.150383: +2024-11-22 00:23:13.150646: Epoch 2520 +2024-11-22 00:23:13.150762: Current learning rate: 0.00711 +2024-11-22 00:23:32.155797: train_loss -0.7799 +2024-11-22 00:23:32.161210: val_loss -0.7606 +2024-11-22 00:23:32.161367: Pseudo dice [0.8406] +2024-11-22 00:23:32.161450: Epoch time: 19.01 s +2024-11-22 00:23:33.026610: +2024-11-22 00:23:33.026834: Epoch 2521 +2024-11-22 00:23:33.026959: Current learning rate: 0.00711 +2024-11-22 00:23:52.366214: train_loss -0.7828 +2024-11-22 00:23:52.366472: val_loss -0.7617 +2024-11-22 00:23:52.366554: Pseudo dice [0.8342] +2024-11-22 00:23:52.366656: Epoch time: 19.34 s +2024-11-22 00:23:53.218905: +2024-11-22 00:23:53.219108: Epoch 2522 +2024-11-22 00:23:53.219219: Current learning rate: 0.00711 +2024-11-22 00:24:12.730495: train_loss -0.7774 +2024-11-22 00:24:12.730729: val_loss -0.7359 +2024-11-22 00:24:12.730811: Pseudo dice [0.8435] +2024-11-22 00:24:12.730891: Epoch time: 19.51 s +2024-11-22 00:24:13.578951: +2024-11-22 00:24:13.579156: Epoch 2523 +2024-11-22 00:24:13.579272: Current learning rate: 0.00711 +2024-11-22 00:24:32.995811: train_loss -0.7764 +2024-11-22 00:24:32.996043: val_loss -0.7309 +2024-11-22 00:24:32.996123: Pseudo dice [0.8521] +2024-11-22 00:24:32.996202: Epoch time: 19.42 s +2024-11-22 00:24:33.842710: +2024-11-22 00:24:33.842972: Epoch 2524 +2024-11-22 00:24:33.843088: Current learning rate: 0.00711 +2024-11-22 00:24:53.429547: train_loss -0.7759 +2024-11-22 00:24:53.429783: val_loss -0.7473 +2024-11-22 00:24:53.429861: Pseudo dice [0.8335] +2024-11-22 00:24:53.429945: Epoch time: 19.59 s +2024-11-22 00:24:54.279924: +2024-11-22 00:24:54.280148: Epoch 2525 +2024-11-22 00:24:54.280267: Current learning rate: 0.00711 +2024-11-22 00:25:12.293082: train_loss -0.7762 +2024-11-22 00:25:12.293390: val_loss -0.7408 +2024-11-22 00:25:12.293470: Pseudo dice [0.834] +2024-11-22 00:25:12.293553: Epoch time: 18.01 s +2024-11-22 00:25:13.141143: +2024-11-22 00:25:13.141386: Epoch 2526 +2024-11-22 00:25:13.141499: Current learning rate: 0.00711 +2024-11-22 00:25:32.289603: train_loss -0.7728 +2024-11-22 00:25:32.289824: val_loss -0.7585 +2024-11-22 00:25:32.289905: Pseudo dice [0.8393] +2024-11-22 00:25:32.289982: Epoch time: 19.15 s +2024-11-22 00:25:33.139138: +2024-11-22 00:25:33.139345: Epoch 2527 +2024-11-22 00:25:33.139454: Current learning rate: 0.00711 +2024-11-22 00:25:51.952853: train_loss -0.7707 +2024-11-22 00:25:51.953079: val_loss -0.7507 +2024-11-22 00:25:51.953155: Pseudo dice [0.8302] +2024-11-22 00:25:51.953234: Epoch time: 18.81 s +2024-11-22 00:25:52.860537: +2024-11-22 00:25:52.860759: Epoch 2528 +2024-11-22 00:25:52.860871: Current learning rate: 0.0071 +2024-11-22 00:26:11.368377: train_loss -0.779 +2024-11-22 00:26:11.368697: val_loss -0.7656 +2024-11-22 00:26:11.368782: Pseudo dice [0.8347] +2024-11-22 00:26:11.368869: Epoch time: 18.51 s +2024-11-22 00:26:12.223997: +2024-11-22 00:26:12.224200: Epoch 2529 +2024-11-22 00:26:12.224308: Current learning rate: 0.0071 +2024-11-22 00:26:30.625968: train_loss -0.7843 +2024-11-22 00:26:30.626187: val_loss -0.7428 +2024-11-22 00:26:30.626261: Pseudo dice [0.8323] +2024-11-22 00:26:30.626335: Epoch time: 18.4 s +2024-11-22 00:26:31.483724: +2024-11-22 00:26:31.483980: Epoch 2530 +2024-11-22 00:26:31.484094: Current learning rate: 0.0071 +2024-11-22 00:26:49.582792: train_loss -0.7727 +2024-11-22 00:26:49.583040: val_loss -0.7567 +2024-11-22 00:26:49.583119: Pseudo dice [0.8477] +2024-11-22 00:26:49.583494: Epoch time: 18.1 s +2024-11-22 00:26:50.442212: +2024-11-22 00:26:50.442468: Epoch 2531 +2024-11-22 00:26:50.442604: Current learning rate: 0.0071 +2024-11-22 00:27:08.769207: train_loss -0.781 +2024-11-22 00:27:08.769424: val_loss -0.7362 +2024-11-22 00:27:08.769502: Pseudo dice [0.8351] +2024-11-22 00:27:08.769580: Epoch time: 18.33 s +2024-11-22 00:27:09.618839: +2024-11-22 00:27:09.619050: Epoch 2532 +2024-11-22 00:27:09.619159: Current learning rate: 0.0071 +2024-11-22 00:27:28.210763: train_loss -0.7749 +2024-11-22 00:27:28.211026: val_loss -0.744 +2024-11-22 00:27:28.211142: Pseudo dice [0.8294] +2024-11-22 00:27:28.211273: Epoch time: 18.59 s +2024-11-22 00:27:29.059290: +2024-11-22 00:27:29.059499: Epoch 2533 +2024-11-22 00:27:29.059609: Current learning rate: 0.0071 +2024-11-22 00:27:47.701403: train_loss -0.7807 +2024-11-22 00:27:47.701611: val_loss -0.7408 +2024-11-22 00:27:47.701685: Pseudo dice [0.8381] +2024-11-22 00:27:47.701762: Epoch time: 18.64 s +2024-11-22 00:27:48.543849: +2024-11-22 00:27:48.544059: Epoch 2534 +2024-11-22 00:27:48.544175: Current learning rate: 0.0071 +2024-11-22 00:28:07.201840: train_loss -0.7756 +2024-11-22 00:28:07.202068: val_loss -0.7683 +2024-11-22 00:28:07.202150: Pseudo dice [0.8446] +2024-11-22 00:28:07.202227: Epoch time: 18.66 s +2024-11-22 00:28:08.233999: +2024-11-22 00:28:08.234252: Epoch 2535 +2024-11-22 00:28:08.234370: Current learning rate: 0.0071 +2024-11-22 00:28:26.861691: train_loss -0.7707 +2024-11-22 00:28:26.861909: val_loss -0.7324 +2024-11-22 00:28:26.861986: Pseudo dice [0.8027] +2024-11-22 00:28:26.862074: Epoch time: 18.63 s +2024-11-22 00:28:28.083589: +2024-11-22 00:28:28.083834: Epoch 2536 +2024-11-22 00:28:28.083949: Current learning rate: 0.0071 +2024-11-22 00:28:48.005322: train_loss -0.7705 +2024-11-22 00:28:48.005576: val_loss -0.7495 +2024-11-22 00:28:48.005655: Pseudo dice [0.8391] +2024-11-22 00:28:48.005735: Epoch time: 19.92 s +2024-11-22 00:28:48.857090: +2024-11-22 00:28:48.857288: Epoch 2537 +2024-11-22 00:28:48.857398: Current learning rate: 0.00709 +2024-11-22 00:29:07.276533: train_loss -0.7748 +2024-11-22 00:29:07.276763: val_loss -0.7474 +2024-11-22 00:29:07.276837: Pseudo dice [0.8324] +2024-11-22 00:29:07.276914: Epoch time: 18.42 s +2024-11-22 00:29:08.123547: +2024-11-22 00:29:08.123791: Epoch 2538 +2024-11-22 00:29:08.123899: Current learning rate: 0.00709 +2024-11-22 00:29:26.951356: train_loss -0.7817 +2024-11-22 00:29:26.951616: val_loss -0.7215 +2024-11-22 00:29:26.951694: Pseudo dice [0.8528] +2024-11-22 00:29:26.951787: Epoch time: 18.83 s +2024-11-22 00:29:27.802777: +2024-11-22 00:29:27.803168: Epoch 2539 +2024-11-22 00:29:27.803279: Current learning rate: 0.00709 +2024-11-22 00:29:46.664304: train_loss -0.7885 +2024-11-22 00:29:46.664561: val_loss -0.7588 +2024-11-22 00:29:46.664634: Pseudo dice [0.8504] +2024-11-22 00:29:46.664721: Epoch time: 18.86 s +2024-11-22 00:29:47.521196: +2024-11-22 00:29:47.521403: Epoch 2540 +2024-11-22 00:29:47.521519: Current learning rate: 0.00709 +2024-11-22 00:30:06.843487: train_loss -0.7792 +2024-11-22 00:30:06.843721: val_loss -0.713 +2024-11-22 00:30:06.843798: Pseudo dice [0.8241] +2024-11-22 00:30:06.843872: Epoch time: 19.32 s +2024-11-22 00:30:07.693414: +2024-11-22 00:30:07.693617: Epoch 2541 +2024-11-22 00:30:07.693735: Current learning rate: 0.00709 +2024-11-22 00:30:27.729949: train_loss -0.7817 +2024-11-22 00:30:27.730176: val_loss -0.7335 +2024-11-22 00:30:27.730258: Pseudo dice [0.8197] +2024-11-22 00:30:27.730335: Epoch time: 20.04 s +2024-11-22 00:30:28.580641: +2024-11-22 00:30:28.580837: Epoch 2542 +2024-11-22 00:30:28.580951: Current learning rate: 0.00709 +2024-11-22 00:30:46.851505: train_loss -0.7815 +2024-11-22 00:30:46.851718: val_loss -0.7582 +2024-11-22 00:30:46.851798: Pseudo dice [0.8633] +2024-11-22 00:30:46.851872: Epoch time: 18.27 s +2024-11-22 00:30:47.705717: +2024-11-22 00:30:47.705912: Epoch 2543 +2024-11-22 00:30:47.706032: Current learning rate: 0.00709 +2024-11-22 00:31:06.633224: train_loss -0.7715 +2024-11-22 00:31:06.633472: val_loss -0.7529 +2024-11-22 00:31:06.633548: Pseudo dice [0.84] +2024-11-22 00:31:06.633631: Epoch time: 18.93 s +2024-11-22 00:31:07.487071: +2024-11-22 00:31:07.487272: Epoch 2544 +2024-11-22 00:31:07.487385: Current learning rate: 0.00709 +2024-11-22 00:31:26.289850: train_loss -0.7709 +2024-11-22 00:31:26.291422: val_loss -0.7509 +2024-11-22 00:31:26.291657: Pseudo dice [0.8266] +2024-11-22 00:31:26.291751: Epoch time: 18.8 s +2024-11-22 00:31:27.147367: +2024-11-22 00:31:27.147572: Epoch 2545 +2024-11-22 00:31:27.147685: Current learning rate: 0.00708 +2024-11-22 00:31:46.098147: train_loss -0.7731 +2024-11-22 00:31:46.098371: val_loss -0.734 +2024-11-22 00:31:46.098446: Pseudo dice [0.8389] +2024-11-22 00:31:46.098522: Epoch time: 18.95 s +2024-11-22 00:31:46.952892: +2024-11-22 00:31:46.953100: Epoch 2546 +2024-11-22 00:31:46.953212: Current learning rate: 0.00708 +2024-11-22 00:32:06.089892: train_loss -0.7819 +2024-11-22 00:32:06.090119: val_loss -0.7598 +2024-11-22 00:32:06.090197: Pseudo dice [0.8242] +2024-11-22 00:32:06.090278: Epoch time: 19.14 s +2024-11-22 00:32:06.947080: +2024-11-22 00:32:06.947327: Epoch 2547 +2024-11-22 00:32:06.947437: Current learning rate: 0.00708 +2024-11-22 00:32:25.770911: train_loss -0.7755 +2024-11-22 00:32:25.771158: val_loss -0.7237 +2024-11-22 00:32:25.771232: Pseudo dice [0.8375] +2024-11-22 00:32:25.771312: Epoch time: 18.82 s +2024-11-22 00:32:27.034331: +2024-11-22 00:32:27.034552: Epoch 2548 +2024-11-22 00:32:27.034662: Current learning rate: 0.00708 +2024-11-22 00:32:46.497136: train_loss -0.7856 +2024-11-22 00:32:46.497360: val_loss -0.7536 +2024-11-22 00:32:46.497435: Pseudo dice [0.8441] +2024-11-22 00:32:46.497512: Epoch time: 19.46 s +2024-11-22 00:32:47.334522: +2024-11-22 00:32:47.334729: Epoch 2549 +2024-11-22 00:32:47.334840: Current learning rate: 0.00708 +2024-11-22 00:33:07.629494: train_loss -0.7765 +2024-11-22 00:33:07.629802: val_loss -0.7503 +2024-11-22 00:33:07.629898: Pseudo dice [0.8428] +2024-11-22 00:33:07.629983: Epoch time: 20.3 s +2024-11-22 00:33:08.729280: +2024-11-22 00:33:08.729497: Epoch 2550 +2024-11-22 00:33:08.729608: Current learning rate: 0.00708 +2024-11-22 00:33:27.120676: train_loss -0.7859 +2024-11-22 00:33:27.123082: val_loss -0.7403 +2024-11-22 00:33:27.123186: Pseudo dice [0.841] +2024-11-22 00:33:27.123271: Epoch time: 18.39 s +2024-11-22 00:33:28.120425: +2024-11-22 00:33:28.120661: Epoch 2551 +2024-11-22 00:33:28.120773: Current learning rate: 0.00708 +2024-11-22 00:33:47.045387: train_loss -0.7907 +2024-11-22 00:33:47.045608: val_loss -0.7216 +2024-11-22 00:33:47.045684: Pseudo dice [0.8614] +2024-11-22 00:33:47.045763: Epoch time: 18.93 s +2024-11-22 00:33:47.902532: +2024-11-22 00:33:47.902812: Epoch 2552 +2024-11-22 00:33:47.902920: Current learning rate: 0.00708 +2024-11-22 00:34:06.597117: train_loss -0.7768 +2024-11-22 00:34:06.597333: val_loss -0.724 +2024-11-22 00:34:06.597407: Pseudo dice [0.837] +2024-11-22 00:34:06.597482: Epoch time: 18.7 s +2024-11-22 00:34:07.452223: +2024-11-22 00:34:07.452436: Epoch 2553 +2024-11-22 00:34:07.452548: Current learning rate: 0.00708 +2024-11-22 00:34:26.856133: train_loss -0.7802 +2024-11-22 00:34:26.856336: val_loss -0.7387 +2024-11-22 00:34:26.856406: Pseudo dice [0.808] +2024-11-22 00:34:26.856483: Epoch time: 19.4 s +2024-11-22 00:34:27.715921: +2024-11-22 00:34:27.716136: Epoch 2554 +2024-11-22 00:34:27.716254: Current learning rate: 0.00707 +2024-11-22 00:34:46.627579: train_loss -0.7822 +2024-11-22 00:34:46.627897: val_loss -0.7437 +2024-11-22 00:34:46.627980: Pseudo dice [0.8378] +2024-11-22 00:34:46.628069: Epoch time: 18.91 s +2024-11-22 00:34:47.494746: +2024-11-22 00:34:47.495047: Epoch 2555 +2024-11-22 00:34:47.495163: Current learning rate: 0.00707 +2024-11-22 00:35:06.509094: train_loss -0.7849 +2024-11-22 00:35:06.509315: val_loss -0.771 +2024-11-22 00:35:06.509387: Pseudo dice [0.8534] +2024-11-22 00:35:06.509461: Epoch time: 19.02 s +2024-11-22 00:35:07.354810: +2024-11-22 00:35:07.355048: Epoch 2556 +2024-11-22 00:35:07.355165: Current learning rate: 0.00707 +2024-11-22 00:35:25.683191: train_loss -0.7878 +2024-11-22 00:35:25.683885: val_loss -0.76 +2024-11-22 00:35:25.683972: Pseudo dice [0.8514] +2024-11-22 00:35:25.684261: Epoch time: 18.33 s +2024-11-22 00:35:26.567049: +2024-11-22 00:35:26.567244: Epoch 2557 +2024-11-22 00:35:26.567355: Current learning rate: 0.00707 +2024-11-22 00:35:44.592587: train_loss -0.7889 +2024-11-22 00:35:44.592846: val_loss -0.7449 +2024-11-22 00:35:44.592980: Pseudo dice [0.8345] +2024-11-22 00:35:44.593074: Epoch time: 18.03 s +2024-11-22 00:35:45.481566: +2024-11-22 00:35:45.481798: Epoch 2558 +2024-11-22 00:35:45.481947: Current learning rate: 0.00707 +2024-11-22 00:36:04.688805: train_loss -0.7708 +2024-11-22 00:36:04.689035: val_loss -0.7694 +2024-11-22 00:36:04.689112: Pseudo dice [0.8322] +2024-11-22 00:36:04.689194: Epoch time: 19.21 s +2024-11-22 00:36:05.580974: +2024-11-22 00:36:05.581193: Epoch 2559 +2024-11-22 00:36:05.581305: Current learning rate: 0.00707 +2024-11-22 00:36:23.656406: train_loss -0.7727 +2024-11-22 00:36:23.656635: val_loss -0.7352 +2024-11-22 00:36:23.656709: Pseudo dice [0.8272] +2024-11-22 00:36:23.656786: Epoch time: 18.08 s +2024-11-22 00:36:24.513497: +2024-11-22 00:36:24.513732: Epoch 2560 +2024-11-22 00:36:24.513850: Current learning rate: 0.00707 +2024-11-22 00:36:43.029858: train_loss -0.7684 +2024-11-22 00:36:43.030073: val_loss -0.7293 +2024-11-22 00:36:43.030150: Pseudo dice [0.8366] +2024-11-22 00:36:43.030231: Epoch time: 18.52 s +2024-11-22 00:36:43.965741: +2024-11-22 00:36:43.966003: Epoch 2561 +2024-11-22 00:36:43.966159: Current learning rate: 0.00707 +2024-11-22 00:37:03.041432: train_loss -0.78 +2024-11-22 00:37:03.041667: val_loss -0.7284 +2024-11-22 00:37:03.041744: Pseudo dice [0.8078] +2024-11-22 00:37:03.041824: Epoch time: 19.08 s +2024-11-22 00:37:03.887245: +2024-11-22 00:37:03.887463: Epoch 2562 +2024-11-22 00:37:03.887570: Current learning rate: 0.00707 +2024-11-22 00:37:23.563330: train_loss -0.7758 +2024-11-22 00:37:23.563540: val_loss -0.75 +2024-11-22 00:37:23.563649: Pseudo dice [0.8366] +2024-11-22 00:37:23.563747: Epoch time: 19.68 s +2024-11-22 00:37:24.443065: +2024-11-22 00:37:24.443379: Epoch 2563 +2024-11-22 00:37:24.443492: Current learning rate: 0.00706 +2024-11-22 00:37:43.017899: train_loss -0.7793 +2024-11-22 00:37:43.018168: val_loss -0.7445 +2024-11-22 00:37:43.018246: Pseudo dice [0.8377] +2024-11-22 00:37:43.018332: Epoch time: 18.58 s +2024-11-22 00:37:43.872217: +2024-11-22 00:37:43.872427: Epoch 2564 +2024-11-22 00:37:43.872537: Current learning rate: 0.00706 +2024-11-22 00:38:02.458506: train_loss -0.7806 +2024-11-22 00:38:02.458740: val_loss -0.748 +2024-11-22 00:38:02.458816: Pseudo dice [0.8245] +2024-11-22 00:38:02.458902: Epoch time: 18.59 s +2024-11-22 00:38:03.346900: +2024-11-22 00:38:03.347115: Epoch 2565 +2024-11-22 00:38:03.347232: Current learning rate: 0.00706 +2024-11-22 00:38:22.464310: train_loss -0.7734 +2024-11-22 00:38:22.464554: val_loss -0.7326 +2024-11-22 00:38:22.464630: Pseudo dice [0.8351] +2024-11-22 00:38:22.464708: Epoch time: 19.12 s +2024-11-22 00:38:23.417124: +2024-11-22 00:38:23.417317: Epoch 2566 +2024-11-22 00:38:23.417453: Current learning rate: 0.00706 +2024-11-22 00:38:42.303862: train_loss -0.7643 +2024-11-22 00:38:42.304093: val_loss -0.7326 +2024-11-22 00:38:42.304174: Pseudo dice [0.844] +2024-11-22 00:38:42.304255: Epoch time: 18.89 s +2024-11-22 00:38:43.160103: +2024-11-22 00:38:43.160344: Epoch 2567 +2024-11-22 00:38:43.160460: Current learning rate: 0.00706 +2024-11-22 00:39:02.512594: train_loss -0.7713 +2024-11-22 00:39:02.513205: val_loss -0.7526 +2024-11-22 00:39:02.513287: Pseudo dice [0.8167] +2024-11-22 00:39:02.513390: Epoch time: 19.35 s +2024-11-22 00:39:03.366315: +2024-11-22 00:39:03.366527: Epoch 2568 +2024-11-22 00:39:03.366644: Current learning rate: 0.00706 +2024-11-22 00:39:22.768273: train_loss -0.776 +2024-11-22 00:39:22.768519: val_loss -0.7083 +2024-11-22 00:39:22.768600: Pseudo dice [0.834] +2024-11-22 00:39:22.768687: Epoch time: 19.4 s +2024-11-22 00:39:23.626940: +2024-11-22 00:39:23.627228: Epoch 2569 +2024-11-22 00:39:23.627347: Current learning rate: 0.00706 +2024-11-22 00:39:42.923551: train_loss -0.7568 +2024-11-22 00:39:42.923766: val_loss -0.7094 +2024-11-22 00:39:42.923840: Pseudo dice [0.8385] +2024-11-22 00:39:42.923915: Epoch time: 19.3 s +2024-11-22 00:39:43.922349: +2024-11-22 00:39:43.922546: Epoch 2570 +2024-11-22 00:39:43.922663: Current learning rate: 0.00706 +2024-11-22 00:40:02.705913: train_loss -0.7656 +2024-11-22 00:40:02.706135: val_loss -0.7367 +2024-11-22 00:40:02.706216: Pseudo dice [0.8476] +2024-11-22 00:40:02.706294: Epoch time: 18.78 s +2024-11-22 00:40:03.955263: +2024-11-22 00:40:03.955491: Epoch 2571 +2024-11-22 00:40:03.955603: Current learning rate: 0.00705 +2024-11-22 00:40:22.000782: train_loss -0.7841 +2024-11-22 00:40:22.001050: val_loss -0.7245 +2024-11-22 00:40:22.001141: Pseudo dice [0.8352] +2024-11-22 00:40:22.001236: Epoch time: 18.05 s +2024-11-22 00:40:22.854725: +2024-11-22 00:40:22.855070: Epoch 2572 +2024-11-22 00:40:22.855188: Current learning rate: 0.00705 +2024-11-22 00:40:40.862903: train_loss -0.7832 +2024-11-22 00:40:40.863131: val_loss -0.7424 +2024-11-22 00:40:40.863206: Pseudo dice [0.831] +2024-11-22 00:40:40.863282: Epoch time: 18.01 s +2024-11-22 00:40:41.710909: +2024-11-22 00:40:41.711234: Epoch 2573 +2024-11-22 00:40:41.711344: Current learning rate: 0.00705 +2024-11-22 00:41:01.148835: train_loss -0.7735 +2024-11-22 00:41:01.149075: val_loss -0.7549 +2024-11-22 00:41:01.149155: Pseudo dice [0.8578] +2024-11-22 00:41:01.149242: Epoch time: 19.44 s +2024-11-22 00:41:02.323141: +2024-11-22 00:41:02.323347: Epoch 2574 +2024-11-22 00:41:02.323462: Current learning rate: 0.00705 +2024-11-22 00:41:22.317790: train_loss -0.7816 +2024-11-22 00:41:22.318045: val_loss -0.7459 +2024-11-22 00:41:22.318127: Pseudo dice [0.8581] +2024-11-22 00:41:22.318212: Epoch time: 20.0 s +2024-11-22 00:41:23.170302: +2024-11-22 00:41:23.170500: Epoch 2575 +2024-11-22 00:41:23.170612: Current learning rate: 0.00705 +2024-11-22 00:41:42.695745: train_loss -0.7817 +2024-11-22 00:41:42.695959: val_loss -0.7597 +2024-11-22 00:41:42.696040: Pseudo dice [0.8539] +2024-11-22 00:41:42.696119: Epoch time: 19.53 s +2024-11-22 00:41:43.619499: +2024-11-22 00:41:43.619695: Epoch 2576 +2024-11-22 00:41:43.619809: Current learning rate: 0.00705 +2024-11-22 00:42:01.744712: train_loss -0.7851 +2024-11-22 00:42:01.744963: val_loss -0.7332 +2024-11-22 00:42:01.745059: Pseudo dice [0.8457] +2024-11-22 00:42:01.745141: Epoch time: 18.13 s +2024-11-22 00:42:02.592000: +2024-11-22 00:42:02.592213: Epoch 2577 +2024-11-22 00:42:02.592325: Current learning rate: 0.00705 +2024-11-22 00:42:21.859199: train_loss -0.7647 +2024-11-22 00:42:21.859427: val_loss -0.761 +2024-11-22 00:42:21.859502: Pseudo dice [0.8507] +2024-11-22 00:42:21.861756: Epoch time: 19.27 s +2024-11-22 00:42:22.872979: +2024-11-22 00:42:22.873258: Epoch 2578 +2024-11-22 00:42:22.873375: Current learning rate: 0.00705 +2024-11-22 00:42:41.288783: train_loss -0.7782 +2024-11-22 00:42:41.289088: val_loss -0.7528 +2024-11-22 00:42:41.289167: Pseudo dice [0.8565] +2024-11-22 00:42:41.289246: Epoch time: 18.42 s +2024-11-22 00:42:42.141063: +2024-11-22 00:42:42.141254: Epoch 2579 +2024-11-22 00:42:42.141408: Current learning rate: 0.00705 +2024-11-22 00:43:00.553204: train_loss -0.771 +2024-11-22 00:43:00.553448: val_loss -0.7402 +2024-11-22 00:43:00.553523: Pseudo dice [0.8411] +2024-11-22 00:43:00.553602: Epoch time: 18.41 s +2024-11-22 00:43:01.403893: +2024-11-22 00:43:01.404131: Epoch 2580 +2024-11-22 00:43:01.404242: Current learning rate: 0.00704 +2024-11-22 00:43:19.403394: train_loss -0.7724 +2024-11-22 00:43:19.403613: val_loss -0.7392 +2024-11-22 00:43:19.403690: Pseudo dice [0.8299] +2024-11-22 00:43:19.403765: Epoch time: 18.0 s +2024-11-22 00:43:20.400594: +2024-11-22 00:43:20.400786: Epoch 2581 +2024-11-22 00:43:20.400896: Current learning rate: 0.00704 +2024-11-22 00:43:40.486233: train_loss -0.7745 +2024-11-22 00:43:40.486453: val_loss -0.7033 +2024-11-22 00:43:40.486527: Pseudo dice [0.8389] +2024-11-22 00:43:40.486605: Epoch time: 20.09 s +2024-11-22 00:43:41.337920: +2024-11-22 00:43:41.338479: Epoch 2582 +2024-11-22 00:43:41.338638: Current learning rate: 0.00704 +2024-11-22 00:44:00.784839: train_loss -0.7686 +2024-11-22 00:44:00.786941: val_loss -0.7502 +2024-11-22 00:44:00.787061: Pseudo dice [0.8173] +2024-11-22 00:44:00.787383: Epoch time: 19.45 s +2024-11-22 00:44:02.079493: +2024-11-22 00:44:02.079708: Epoch 2583 +2024-11-22 00:44:02.079822: Current learning rate: 0.00704 +2024-11-22 00:44:20.193263: train_loss -0.778 +2024-11-22 00:44:20.193497: val_loss -0.7604 +2024-11-22 00:44:20.193574: Pseudo dice [0.8337] +2024-11-22 00:44:20.193649: Epoch time: 18.11 s +2024-11-22 00:44:21.042381: +2024-11-22 00:44:21.042790: Epoch 2584 +2024-11-22 00:44:21.042910: Current learning rate: 0.00704 +2024-11-22 00:44:39.971771: train_loss -0.7824 +2024-11-22 00:44:39.971987: val_loss -0.7491 +2024-11-22 00:44:39.972072: Pseudo dice [0.8251] +2024-11-22 00:44:39.972147: Epoch time: 18.93 s +2024-11-22 00:44:40.852376: +2024-11-22 00:44:40.852648: Epoch 2585 +2024-11-22 00:44:40.852768: Current learning rate: 0.00704 +2024-11-22 00:44:59.288471: train_loss -0.7822 +2024-11-22 00:44:59.288734: val_loss -0.7082 +2024-11-22 00:44:59.288811: Pseudo dice [0.8088] +2024-11-22 00:44:59.288894: Epoch time: 18.44 s +2024-11-22 00:45:00.145165: +2024-11-22 00:45:00.145378: Epoch 2586 +2024-11-22 00:45:00.145491: Current learning rate: 0.00704 +2024-11-22 00:45:19.197501: train_loss -0.7493 +2024-11-22 00:45:19.197720: val_loss -0.7218 +2024-11-22 00:45:19.197796: Pseudo dice [0.8175] +2024-11-22 00:45:19.197869: Epoch time: 19.05 s +2024-11-22 00:45:20.046445: +2024-11-22 00:45:20.046645: Epoch 2587 +2024-11-22 00:45:20.046759: Current learning rate: 0.00704 +2024-11-22 00:45:38.854761: train_loss -0.7745 +2024-11-22 00:45:38.860178: val_loss -0.7344 +2024-11-22 00:45:38.860305: Pseudo dice [0.8079] +2024-11-22 00:45:38.860384: Epoch time: 18.81 s +2024-11-22 00:45:39.765278: +2024-11-22 00:45:39.765493: Epoch 2588 +2024-11-22 00:45:39.765608: Current learning rate: 0.00703 +2024-11-22 00:45:58.639768: train_loss -0.7716 +2024-11-22 00:45:58.639999: val_loss -0.7374 +2024-11-22 00:45:58.640082: Pseudo dice [0.8263] +2024-11-22 00:45:58.640163: Epoch time: 18.88 s +2024-11-22 00:45:59.492987: +2024-11-22 00:45:59.493210: Epoch 2589 +2024-11-22 00:45:59.493322: Current learning rate: 0.00703 +2024-11-22 00:46:18.682293: train_loss -0.7739 +2024-11-22 00:46:18.682522: val_loss -0.712 +2024-11-22 00:46:18.682598: Pseudo dice [0.8131] +2024-11-22 00:46:18.682680: Epoch time: 19.19 s +2024-11-22 00:46:19.617484: +2024-11-22 00:46:19.617691: Epoch 2590 +2024-11-22 00:46:19.617806: Current learning rate: 0.00703 +2024-11-22 00:46:37.225741: train_loss -0.7716 +2024-11-22 00:46:37.225998: val_loss -0.7435 +2024-11-22 00:46:37.226075: Pseudo dice [0.8563] +2024-11-22 00:46:37.226156: Epoch time: 17.61 s +2024-11-22 00:46:38.073380: +2024-11-22 00:46:38.073581: Epoch 2591 +2024-11-22 00:46:38.073690: Current learning rate: 0.00703 +2024-11-22 00:46:57.410625: train_loss -0.7742 +2024-11-22 00:46:57.410874: val_loss -0.7203 +2024-11-22 00:46:57.410953: Pseudo dice [0.8222] +2024-11-22 00:46:57.411035: Epoch time: 19.34 s +2024-11-22 00:46:58.262651: +2024-11-22 00:46:58.262886: Epoch 2592 +2024-11-22 00:46:58.263013: Current learning rate: 0.00703 +2024-11-22 00:47:16.353084: train_loss -0.7864 +2024-11-22 00:47:16.353314: val_loss -0.7139 +2024-11-22 00:47:16.353393: Pseudo dice [0.8267] +2024-11-22 00:47:16.353479: Epoch time: 18.09 s +2024-11-22 00:47:17.214447: +2024-11-22 00:47:17.214640: Epoch 2593 +2024-11-22 00:47:17.214759: Current learning rate: 0.00703 +2024-11-22 00:47:37.494368: train_loss -0.7777 +2024-11-22 00:47:37.494612: val_loss -0.7488 +2024-11-22 00:47:37.494686: Pseudo dice [0.8382] +2024-11-22 00:47:37.494765: Epoch time: 20.28 s +2024-11-22 00:47:38.345982: +2024-11-22 00:47:38.346236: Epoch 2594 +2024-11-22 00:47:38.346355: Current learning rate: 0.00703 +2024-11-22 00:47:57.188695: train_loss -0.7793 +2024-11-22 00:47:57.191109: val_loss -0.734 +2024-11-22 00:47:57.191240: Pseudo dice [0.8268] +2024-11-22 00:47:57.191319: Epoch time: 18.84 s +2024-11-22 00:47:58.614026: +2024-11-22 00:47:58.614473: Epoch 2595 +2024-11-22 00:47:58.614614: Current learning rate: 0.00703 +2024-11-22 00:48:17.034844: train_loss -0.7825 +2024-11-22 00:48:17.035083: val_loss -0.7098 +2024-11-22 00:48:17.035157: Pseudo dice [0.8286] +2024-11-22 00:48:17.035234: Epoch time: 18.42 s +2024-11-22 00:48:17.883215: +2024-11-22 00:48:17.883704: Epoch 2596 +2024-11-22 00:48:17.883846: Current learning rate: 0.00703 +2024-11-22 00:48:36.280374: train_loss -0.791 +2024-11-22 00:48:36.280602: val_loss -0.7414 +2024-11-22 00:48:36.280679: Pseudo dice [0.8588] +2024-11-22 00:48:36.280757: Epoch time: 18.4 s +2024-11-22 00:48:37.130062: +2024-11-22 00:48:37.130474: Epoch 2597 +2024-11-22 00:48:37.130606: Current learning rate: 0.00702 +2024-11-22 00:48:56.056276: train_loss -0.7855 +2024-11-22 00:48:56.056505: val_loss -0.75 +2024-11-22 00:48:56.056581: Pseudo dice [0.8404] +2024-11-22 00:48:56.056656: Epoch time: 18.93 s +2024-11-22 00:48:56.904305: +2024-11-22 00:48:56.904798: Epoch 2598 +2024-11-22 00:48:56.904937: Current learning rate: 0.00702 +2024-11-22 00:49:15.475544: train_loss -0.7797 +2024-11-22 00:49:15.475852: val_loss -0.7514 +2024-11-22 00:49:15.475928: Pseudo dice [0.8206] +2024-11-22 00:49:15.476016: Epoch time: 18.57 s +2024-11-22 00:49:16.350273: +2024-11-22 00:49:16.350694: Epoch 2599 +2024-11-22 00:49:16.350832: Current learning rate: 0.00702 +2024-11-22 00:49:35.280195: train_loss -0.7734 +2024-11-22 00:49:35.280412: val_loss -0.7352 +2024-11-22 00:49:35.280490: Pseudo dice [0.8274] +2024-11-22 00:49:35.280565: Epoch time: 18.93 s +2024-11-22 00:49:36.413058: +2024-11-22 00:49:36.413515: Epoch 2600 +2024-11-22 00:49:36.413654: Current learning rate: 0.00702 +2024-11-22 00:49:54.401217: train_loss -0.7882 +2024-11-22 00:49:54.401488: val_loss -0.7634 +2024-11-22 00:49:54.401570: Pseudo dice [0.8564] +2024-11-22 00:49:54.401647: Epoch time: 17.99 s +2024-11-22 00:49:55.255355: +2024-11-22 00:49:55.255802: Epoch 2601 +2024-11-22 00:49:55.255935: Current learning rate: 0.00702 +2024-11-22 00:50:13.919089: train_loss -0.785 +2024-11-22 00:50:13.919311: val_loss -0.7396 +2024-11-22 00:50:13.919387: Pseudo dice [0.8285] +2024-11-22 00:50:13.919465: Epoch time: 18.66 s +2024-11-22 00:50:14.772935: +2024-11-22 00:50:14.773342: Epoch 2602 +2024-11-22 00:50:14.773478: Current learning rate: 0.00702 +2024-11-22 00:50:34.000870: train_loss -0.7779 +2024-11-22 00:50:34.001141: val_loss -0.7207 +2024-11-22 00:50:34.001228: Pseudo dice [0.8359] +2024-11-22 00:50:34.001311: Epoch time: 19.23 s +2024-11-22 00:50:34.852875: +2024-11-22 00:50:34.853299: Epoch 2603 +2024-11-22 00:50:34.853429: Current learning rate: 0.00702 +2024-11-22 00:50:53.789257: train_loss -0.7779 +2024-11-22 00:50:53.789502: val_loss -0.7192 +2024-11-22 00:50:53.789581: Pseudo dice [0.8397] +2024-11-22 00:50:53.789658: Epoch time: 18.94 s +2024-11-22 00:50:54.649123: +2024-11-22 00:50:54.649525: Epoch 2604 +2024-11-22 00:50:54.649657: Current learning rate: 0.00702 +2024-11-22 00:51:13.482247: train_loss -0.7802 +2024-11-22 00:51:13.482462: val_loss -0.7371 +2024-11-22 00:51:13.482539: Pseudo dice [0.8264] +2024-11-22 00:51:13.482617: Epoch time: 18.83 s +2024-11-22 00:51:14.329452: +2024-11-22 00:51:14.329850: Epoch 2605 +2024-11-22 00:51:14.329981: Current learning rate: 0.00701 +2024-11-22 00:51:33.343305: train_loss -0.7804 +2024-11-22 00:51:33.343536: val_loss -0.7472 +2024-11-22 00:51:33.343615: Pseudo dice [0.8392] +2024-11-22 00:51:33.343717: Epoch time: 19.01 s +2024-11-22 00:51:34.284798: +2024-11-22 00:51:34.285016: Epoch 2606 +2024-11-22 00:51:34.285126: Current learning rate: 0.00701 +2024-11-22 00:51:53.759871: train_loss -0.7883 +2024-11-22 00:51:53.760118: val_loss -0.7443 +2024-11-22 00:51:53.760226: Pseudo dice [0.8417] +2024-11-22 00:51:53.760306: Epoch time: 19.48 s +2024-11-22 00:51:54.605101: +2024-11-22 00:51:54.605517: Epoch 2607 +2024-11-22 00:51:54.605650: Current learning rate: 0.00701 +2024-11-22 00:52:14.402090: train_loss -0.7773 +2024-11-22 00:52:14.402308: val_loss -0.7364 +2024-11-22 00:52:14.402387: Pseudo dice [0.8168] +2024-11-22 00:52:14.402468: Epoch time: 19.8 s +2024-11-22 00:52:15.247666: +2024-11-22 00:52:15.248103: Epoch 2608 +2024-11-22 00:52:15.248241: Current learning rate: 0.00701 +2024-11-22 00:52:34.586277: train_loss -0.7809 +2024-11-22 00:52:34.586495: val_loss -0.7625 +2024-11-22 00:52:34.586652: Pseudo dice [0.8457] +2024-11-22 00:52:34.586734: Epoch time: 19.34 s +2024-11-22 00:52:35.437478: +2024-11-22 00:52:35.437896: Epoch 2609 +2024-11-22 00:52:35.438039: Current learning rate: 0.00701 +2024-11-22 00:52:54.404183: train_loss -0.7823 +2024-11-22 00:52:54.404452: val_loss -0.738 +2024-11-22 00:52:54.404529: Pseudo dice [0.8423] +2024-11-22 00:52:54.404614: Epoch time: 18.97 s +2024-11-22 00:52:55.251808: +2024-11-22 00:52:55.252237: Epoch 2610 +2024-11-22 00:52:55.252372: Current learning rate: 0.00701 +2024-11-22 00:53:13.759248: train_loss -0.791 +2024-11-22 00:53:13.761638: val_loss -0.7601 +2024-11-22 00:53:13.761724: Pseudo dice [0.8526] +2024-11-22 00:53:13.761802: Epoch time: 18.51 s +2024-11-22 00:53:14.727966: +2024-11-22 00:53:14.728397: Epoch 2611 +2024-11-22 00:53:14.728529: Current learning rate: 0.00701 +2024-11-22 00:53:33.315202: train_loss -0.7916 +2024-11-22 00:53:33.320612: val_loss -0.7271 +2024-11-22 00:53:33.320731: Pseudo dice [0.8019] +2024-11-22 00:53:33.320818: Epoch time: 18.59 s +2024-11-22 00:53:34.439757: +2024-11-22 00:53:34.440179: Epoch 2612 +2024-11-22 00:53:34.440314: Current learning rate: 0.00701 +2024-11-22 00:53:52.307268: train_loss -0.7789 +2024-11-22 00:53:52.307497: val_loss -0.7155 +2024-11-22 00:53:52.307573: Pseudo dice [0.8068] +2024-11-22 00:53:52.307651: Epoch time: 17.87 s +2024-11-22 00:53:53.155286: +2024-11-22 00:53:53.155707: Epoch 2613 +2024-11-22 00:53:53.155843: Current learning rate: 0.00701 +2024-11-22 00:54:12.545668: train_loss -0.7716 +2024-11-22 00:54:12.545934: val_loss -0.7412 +2024-11-22 00:54:12.546025: Pseudo dice [0.8382] +2024-11-22 00:54:12.546110: Epoch time: 19.39 s +2024-11-22 00:54:13.401587: +2024-11-22 00:54:13.402056: Epoch 2614 +2024-11-22 00:54:13.402194: Current learning rate: 0.007 +2024-11-22 00:54:31.923910: train_loss -0.7738 +2024-11-22 00:54:31.924139: val_loss -0.6997 +2024-11-22 00:54:31.924214: Pseudo dice [0.8415] +2024-11-22 00:54:31.924291: Epoch time: 18.52 s +2024-11-22 00:54:32.779677: +2024-11-22 00:54:32.780091: Epoch 2615 +2024-11-22 00:54:32.780226: Current learning rate: 0.007 +2024-11-22 00:54:51.963732: train_loss -0.7825 +2024-11-22 00:54:51.963964: val_loss -0.7536 +2024-11-22 00:54:51.964048: Pseudo dice [0.8342] +2024-11-22 00:54:51.964132: Epoch time: 19.18 s +2024-11-22 00:54:52.871070: +2024-11-22 00:54:52.871543: Epoch 2616 +2024-11-22 00:54:52.871677: Current learning rate: 0.007 +2024-11-22 00:55:12.573645: train_loss -0.7895 +2024-11-22 00:55:12.573870: val_loss -0.7462 +2024-11-22 00:55:12.573945: Pseudo dice [0.8443] +2024-11-22 00:55:12.574026: Epoch time: 19.7 s +2024-11-22 00:55:13.518447: +2024-11-22 00:55:13.518883: Epoch 2617 +2024-11-22 00:55:13.519022: Current learning rate: 0.007 +2024-11-22 00:55:31.447567: train_loss -0.7731 +2024-11-22 00:55:31.447811: val_loss -0.7432 +2024-11-22 00:55:31.447886: Pseudo dice [0.8403] +2024-11-22 00:55:31.447968: Epoch time: 17.93 s +2024-11-22 00:55:32.707196: +2024-11-22 00:55:32.707638: Epoch 2618 +2024-11-22 00:55:32.707781: Current learning rate: 0.007 +2024-11-22 00:55:50.233822: train_loss -0.7702 +2024-11-22 00:55:50.234044: val_loss -0.73 +2024-11-22 00:55:50.234119: Pseudo dice [0.8268] +2024-11-22 00:55:50.234195: Epoch time: 17.53 s +2024-11-22 00:55:51.084809: +2024-11-22 00:55:51.085229: Epoch 2619 +2024-11-22 00:55:51.085357: Current learning rate: 0.007 +2024-11-22 00:56:09.939351: train_loss -0.7757 +2024-11-22 00:56:09.939566: val_loss -0.7424 +2024-11-22 00:56:09.939646: Pseudo dice [0.8461] +2024-11-22 00:56:09.939723: Epoch time: 18.86 s +2024-11-22 00:56:10.787198: +2024-11-22 00:56:10.787703: Epoch 2620 +2024-11-22 00:56:10.787843: Current learning rate: 0.007 +2024-11-22 00:56:29.710103: train_loss -0.7811 +2024-11-22 00:56:29.710361: val_loss -0.7445 +2024-11-22 00:56:29.710439: Pseudo dice [0.8554] +2024-11-22 00:56:29.710526: Epoch time: 18.92 s +2024-11-22 00:56:30.619798: +2024-11-22 00:56:30.620253: Epoch 2621 +2024-11-22 00:56:30.620389: Current learning rate: 0.007 +2024-11-22 00:56:50.707933: train_loss -0.7763 +2024-11-22 00:56:50.710797: val_loss -0.7337 +2024-11-22 00:56:50.710938: Pseudo dice [0.8349] +2024-11-22 00:56:50.711030: Epoch time: 20.09 s +2024-11-22 00:56:51.564080: +2024-11-22 00:56:51.564525: Epoch 2622 +2024-11-22 00:56:51.564668: Current learning rate: 0.00699 +2024-11-22 00:57:11.057962: train_loss -0.7784 +2024-11-22 00:57:11.058216: val_loss -0.7341 +2024-11-22 00:57:11.058290: Pseudo dice [0.8433] +2024-11-22 00:57:11.058364: Epoch time: 19.49 s +2024-11-22 00:57:11.977923: +2024-11-22 00:57:11.978368: Epoch 2623 +2024-11-22 00:57:11.978500: Current learning rate: 0.00699 +2024-11-22 00:57:31.091466: train_loss -0.7654 +2024-11-22 00:57:31.091688: val_loss -0.7221 +2024-11-22 00:57:31.091762: Pseudo dice [0.8319] +2024-11-22 00:57:31.091838: Epoch time: 19.11 s +2024-11-22 00:57:31.946965: +2024-11-22 00:57:31.947399: Epoch 2624 +2024-11-22 00:57:31.947531: Current learning rate: 0.00699 +2024-11-22 00:57:50.418540: train_loss -0.7794 +2024-11-22 00:57:50.418792: val_loss -0.7394 +2024-11-22 00:57:50.418867: Pseudo dice [0.8394] +2024-11-22 00:57:50.418947: Epoch time: 18.47 s +2024-11-22 00:57:51.269510: +2024-11-22 00:57:51.269924: Epoch 2625 +2024-11-22 00:57:51.270060: Current learning rate: 0.00699 +2024-11-22 00:58:10.223116: train_loss -0.7733 +2024-11-22 00:58:10.223337: val_loss -0.7276 +2024-11-22 00:58:10.223412: Pseudo dice [0.8416] +2024-11-22 00:58:10.223488: Epoch time: 18.95 s +2024-11-22 00:58:11.072129: +2024-11-22 00:58:11.072535: Epoch 2626 +2024-11-22 00:58:11.072669: Current learning rate: 0.00699 +2024-11-22 00:58:29.361628: train_loss -0.7707 +2024-11-22 00:58:29.361846: val_loss -0.764 +2024-11-22 00:58:29.361920: Pseudo dice [0.8526] +2024-11-22 00:58:29.362004: Epoch time: 18.29 s +2024-11-22 00:58:30.214380: +2024-11-22 00:58:30.214876: Epoch 2627 +2024-11-22 00:58:30.215022: Current learning rate: 0.00699 +2024-11-22 00:58:49.057563: train_loss -0.7819 +2024-11-22 00:58:49.057792: val_loss -0.7459 +2024-11-22 00:58:49.057870: Pseudo dice [0.8616] +2024-11-22 00:58:49.057950: Epoch time: 18.84 s +2024-11-22 00:58:49.910570: +2024-11-22 00:58:49.910985: Epoch 2628 +2024-11-22 00:58:49.911125: Current learning rate: 0.00699 +2024-11-22 00:59:08.803016: train_loss -0.7781 +2024-11-22 00:59:08.806676: val_loss -0.7313 +2024-11-22 00:59:08.806763: Pseudo dice [0.8328] +2024-11-22 00:59:08.806849: Epoch time: 18.89 s +2024-11-22 00:59:09.665871: +2024-11-22 00:59:09.666097: Epoch 2629 +2024-11-22 00:59:09.666210: Current learning rate: 0.00699 +2024-11-22 00:59:27.365083: train_loss -0.7846 +2024-11-22 00:59:27.365299: val_loss -0.7546 +2024-11-22 00:59:27.365372: Pseudo dice [0.8186] +2024-11-22 00:59:27.365446: Epoch time: 17.7 s +2024-11-22 00:59:28.682105: +2024-11-22 00:59:28.682317: Epoch 2630 +2024-11-22 00:59:28.682429: Current learning rate: 0.00699 +2024-11-22 00:59:46.831018: train_loss -0.779 +2024-11-22 00:59:46.831239: val_loss -0.7681 +2024-11-22 00:59:46.831316: Pseudo dice [0.84] +2024-11-22 00:59:46.831394: Epoch time: 18.15 s +2024-11-22 00:59:47.684362: +2024-11-22 00:59:47.684578: Epoch 2631 +2024-11-22 00:59:47.684699: Current learning rate: 0.00698 +2024-11-22 01:00:06.831963: train_loss -0.7747 +2024-11-22 01:00:06.832222: val_loss -0.7402 +2024-11-22 01:00:06.832300: Pseudo dice [0.8355] +2024-11-22 01:00:06.832381: Epoch time: 19.15 s +2024-11-22 01:00:07.680833: +2024-11-22 01:00:07.681068: Epoch 2632 +2024-11-22 01:00:07.681180: Current learning rate: 0.00698 +2024-11-22 01:00:25.600760: train_loss -0.7739 +2024-11-22 01:00:25.601009: val_loss -0.7342 +2024-11-22 01:00:25.601083: Pseudo dice [0.8439] +2024-11-22 01:00:25.601213: Epoch time: 17.92 s +2024-11-22 01:00:26.453687: +2024-11-22 01:00:26.453886: Epoch 2633 +2024-11-22 01:00:26.454004: Current learning rate: 0.00698 +2024-11-22 01:00:45.509530: train_loss -0.7709 +2024-11-22 01:00:45.509750: val_loss -0.7596 +2024-11-22 01:00:45.509824: Pseudo dice [0.8413] +2024-11-22 01:00:45.509901: Epoch time: 19.06 s +2024-11-22 01:00:46.383532: +2024-11-22 01:00:46.383748: Epoch 2634 +2024-11-22 01:00:46.383858: Current learning rate: 0.00698 +2024-11-22 01:01:04.353631: train_loss -0.7836 +2024-11-22 01:01:04.359076: val_loss -0.7651 +2024-11-22 01:01:04.359478: Pseudo dice [0.8597] +2024-11-22 01:01:04.359572: Epoch time: 17.97 s +2024-11-22 01:01:05.381120: +2024-11-22 01:01:05.381329: Epoch 2635 +2024-11-22 01:01:05.381443: Current learning rate: 0.00698 +2024-11-22 01:01:24.073327: train_loss -0.7813 +2024-11-22 01:01:24.073543: val_loss -0.7465 +2024-11-22 01:01:24.073618: Pseudo dice [0.8177] +2024-11-22 01:01:24.073692: Epoch time: 18.69 s +2024-11-22 01:01:24.924177: +2024-11-22 01:01:24.924381: Epoch 2636 +2024-11-22 01:01:24.924491: Current learning rate: 0.00698 +2024-11-22 01:01:42.630802: train_loss -0.7844 +2024-11-22 01:01:42.631027: val_loss -0.7453 +2024-11-22 01:01:42.631101: Pseudo dice [0.8371] +2024-11-22 01:01:42.631178: Epoch time: 17.71 s +2024-11-22 01:01:43.482090: +2024-11-22 01:01:43.482282: Epoch 2637 +2024-11-22 01:01:43.482392: Current learning rate: 0.00698 +2024-11-22 01:02:01.247626: train_loss -0.7853 +2024-11-22 01:02:01.247861: val_loss -0.7497 +2024-11-22 01:02:01.247945: Pseudo dice [0.8557] +2024-11-22 01:02:01.248033: Epoch time: 17.77 s +2024-11-22 01:02:02.119573: +2024-11-22 01:02:02.119783: Epoch 2638 +2024-11-22 01:02:02.119898: Current learning rate: 0.00698 +2024-11-22 01:02:20.726191: train_loss -0.7831 +2024-11-22 01:02:20.726435: val_loss -0.736 +2024-11-22 01:02:20.726510: Pseudo dice [0.8441] +2024-11-22 01:02:20.731768: Epoch time: 18.61 s +2024-11-22 01:02:21.716466: +2024-11-22 01:02:21.716679: Epoch 2639 +2024-11-22 01:02:21.716794: Current learning rate: 0.00697 +2024-11-22 01:02:40.959285: train_loss -0.7801 +2024-11-22 01:02:40.959508: val_loss -0.7447 +2024-11-22 01:02:40.959592: Pseudo dice [0.8303] +2024-11-22 01:02:40.959716: Epoch time: 19.24 s +2024-11-22 01:02:41.816220: +2024-11-22 01:02:41.816448: Epoch 2640 +2024-11-22 01:02:41.816559: Current learning rate: 0.00697 +2024-11-22 01:03:01.068449: train_loss -0.7721 +2024-11-22 01:03:01.068671: val_loss -0.745 +2024-11-22 01:03:01.068746: Pseudo dice [0.8338] +2024-11-22 01:03:01.068822: Epoch time: 19.25 s +2024-11-22 01:03:01.923435: +2024-11-22 01:03:01.923637: Epoch 2641 +2024-11-22 01:03:01.923750: Current learning rate: 0.00697 +2024-11-22 01:03:20.841464: train_loss -0.7712 +2024-11-22 01:03:20.841697: val_loss -0.7258 +2024-11-22 01:03:20.841774: Pseudo dice [0.8532] +2024-11-22 01:03:20.841857: Epoch time: 18.92 s +2024-11-22 01:03:22.112625: +2024-11-22 01:03:22.112875: Epoch 2642 +2024-11-22 01:03:22.113031: Current learning rate: 0.00697 +2024-11-22 01:03:40.733876: train_loss -0.77 +2024-11-22 01:03:40.734102: val_loss -0.7203 +2024-11-22 01:03:40.734179: Pseudo dice [0.8171] +2024-11-22 01:03:40.734258: Epoch time: 18.62 s +2024-11-22 01:03:41.622493: +2024-11-22 01:03:41.622726: Epoch 2643 +2024-11-22 01:03:41.622842: Current learning rate: 0.00697 +2024-11-22 01:04:00.593305: train_loss -0.7736 +2024-11-22 01:04:00.593532: val_loss -0.7298 +2024-11-22 01:04:00.593607: Pseudo dice [0.8229] +2024-11-22 01:04:00.593683: Epoch time: 18.97 s +2024-11-22 01:04:01.447095: +2024-11-22 01:04:01.447301: Epoch 2644 +2024-11-22 01:04:01.447412: Current learning rate: 0.00697 +2024-11-22 01:04:19.820526: train_loss -0.7797 +2024-11-22 01:04:19.820764: val_loss -0.7567 +2024-11-22 01:04:19.820847: Pseudo dice [0.8175] +2024-11-22 01:04:19.820926: Epoch time: 18.37 s +2024-11-22 01:04:20.715380: +2024-11-22 01:04:20.715711: Epoch 2645 +2024-11-22 01:04:20.715828: Current learning rate: 0.00697 +2024-11-22 01:04:39.158634: train_loss -0.7838 +2024-11-22 01:04:39.158943: val_loss -0.7484 +2024-11-22 01:04:39.159035: Pseudo dice [0.8303] +2024-11-22 01:04:39.159125: Epoch time: 18.44 s +2024-11-22 01:04:40.014262: +2024-11-22 01:04:40.014491: Epoch 2646 +2024-11-22 01:04:40.014606: Current learning rate: 0.00697 +2024-11-22 01:04:58.938518: train_loss -0.7817 +2024-11-22 01:04:58.938731: val_loss -0.7153 +2024-11-22 01:04:58.938809: Pseudo dice [0.8414] +2024-11-22 01:04:58.938888: Epoch time: 18.93 s +2024-11-22 01:04:59.863495: +2024-11-22 01:04:59.863725: Epoch 2647 +2024-11-22 01:04:59.863838: Current learning rate: 0.00697 +2024-11-22 01:05:19.019285: train_loss -0.7818 +2024-11-22 01:05:19.019498: val_loss -0.7165 +2024-11-22 01:05:19.019575: Pseudo dice [0.8294] +2024-11-22 01:05:19.019652: Epoch time: 19.16 s +2024-11-22 01:05:19.869496: +2024-11-22 01:05:19.869691: Epoch 2648 +2024-11-22 01:05:19.869799: Current learning rate: 0.00696 +2024-11-22 01:05:38.043338: train_loss -0.7915 +2024-11-22 01:05:38.043602: val_loss -0.7578 +2024-11-22 01:05:38.043679: Pseudo dice [0.8412] +2024-11-22 01:05:38.043756: Epoch time: 18.17 s +2024-11-22 01:05:38.898516: +2024-11-22 01:05:38.898745: Epoch 2649 +2024-11-22 01:05:38.898870: Current learning rate: 0.00696 +2024-11-22 01:05:56.283318: train_loss -0.7769 +2024-11-22 01:05:56.283554: val_loss -0.7506 +2024-11-22 01:05:56.283628: Pseudo dice [0.8497] +2024-11-22 01:05:56.283704: Epoch time: 17.39 s +2024-11-22 01:05:57.373047: +2024-11-22 01:05:57.373336: Epoch 2650 +2024-11-22 01:05:57.373451: Current learning rate: 0.00696 +2024-11-22 01:06:17.124320: train_loss -0.777 +2024-11-22 01:06:17.124540: val_loss -0.7206 +2024-11-22 01:06:17.124612: Pseudo dice [0.8432] +2024-11-22 01:06:17.124688: Epoch time: 19.75 s +2024-11-22 01:06:18.058166: +2024-11-22 01:06:18.058380: Epoch 2651 +2024-11-22 01:06:18.058494: Current learning rate: 0.00696 +2024-11-22 01:06:37.232857: train_loss -0.7596 +2024-11-22 01:06:37.233096: val_loss -0.7109 +2024-11-22 01:06:37.233174: Pseudo dice [0.8051] +2024-11-22 01:06:37.233251: Epoch time: 19.18 s +2024-11-22 01:06:38.240899: +2024-11-22 01:06:38.241138: Epoch 2652 +2024-11-22 01:06:38.241258: Current learning rate: 0.00696 +2024-11-22 01:06:56.141846: train_loss -0.7546 +2024-11-22 01:06:56.142123: val_loss -0.735 +2024-11-22 01:06:56.142204: Pseudo dice [0.8405] +2024-11-22 01:06:56.142317: Epoch time: 17.9 s +2024-11-22 01:06:56.995533: +2024-11-22 01:06:56.995742: Epoch 2653 +2024-11-22 01:06:56.995866: Current learning rate: 0.00696 +2024-11-22 01:07:15.850930: train_loss -0.7637 +2024-11-22 01:07:15.851170: val_loss -0.7248 +2024-11-22 01:07:15.851247: Pseudo dice [0.8257] +2024-11-22 01:07:15.851327: Epoch time: 18.86 s +2024-11-22 01:07:16.696827: +2024-11-22 01:07:16.697067: Epoch 2654 +2024-11-22 01:07:16.697185: Current learning rate: 0.00696 +2024-11-22 01:07:36.302890: train_loss -0.7744 +2024-11-22 01:07:36.303123: val_loss -0.749 +2024-11-22 01:07:36.303202: Pseudo dice [0.8306] +2024-11-22 01:07:36.303282: Epoch time: 19.61 s +2024-11-22 01:07:37.166912: +2024-11-22 01:07:37.167161: Epoch 2655 +2024-11-22 01:07:37.167280: Current learning rate: 0.00696 +2024-11-22 01:07:56.021051: train_loss -0.7739 +2024-11-22 01:07:56.021319: val_loss -0.7442 +2024-11-22 01:07:56.021397: Pseudo dice [0.8203] +2024-11-22 01:07:56.021486: Epoch time: 18.85 s +2024-11-22 01:07:56.875359: +2024-11-22 01:07:56.875583: Epoch 2656 +2024-11-22 01:07:56.875698: Current learning rate: 0.00696 +2024-11-22 01:08:16.738006: train_loss -0.7729 +2024-11-22 01:08:16.738226: val_loss -0.7437 +2024-11-22 01:08:16.738303: Pseudo dice [0.8381] +2024-11-22 01:08:16.738379: Epoch time: 19.86 s +2024-11-22 01:08:17.584509: +2024-11-22 01:08:17.584725: Epoch 2657 +2024-11-22 01:08:17.584837: Current learning rate: 0.00695 +2024-11-22 01:08:36.233387: train_loss -0.7591 +2024-11-22 01:08:36.233631: val_loss -0.7409 +2024-11-22 01:08:36.233708: Pseudo dice [0.8244] +2024-11-22 01:08:36.233786: Epoch time: 18.64 s +2024-11-22 01:08:37.103110: +2024-11-22 01:08:37.103350: Epoch 2658 +2024-11-22 01:08:37.103463: Current learning rate: 0.00695 +2024-11-22 01:08:55.747370: train_loss -0.7646 +2024-11-22 01:08:55.747594: val_loss -0.6998 +2024-11-22 01:08:55.747669: Pseudo dice [0.8383] +2024-11-22 01:08:55.747744: Epoch time: 18.65 s +2024-11-22 01:08:56.597641: +2024-11-22 01:08:56.597876: Epoch 2659 +2024-11-22 01:08:56.597986: Current learning rate: 0.00695 +2024-11-22 01:09:15.864310: train_loss -0.7665 +2024-11-22 01:09:15.864541: val_loss -0.7486 +2024-11-22 01:09:15.864618: Pseudo dice [0.8367] +2024-11-22 01:09:15.864702: Epoch time: 19.27 s +2024-11-22 01:09:16.715813: +2024-11-22 01:09:16.716125: Epoch 2660 +2024-11-22 01:09:16.716235: Current learning rate: 0.00695 +2024-11-22 01:09:35.154814: train_loss -0.7781 +2024-11-22 01:09:35.155078: val_loss -0.7661 +2024-11-22 01:09:35.155770: Pseudo dice [0.8274] +2024-11-22 01:09:35.155877: Epoch time: 18.44 s +2024-11-22 01:09:36.027713: +2024-11-22 01:09:36.027984: Epoch 2661 +2024-11-22 01:09:36.028100: Current learning rate: 0.00695 +2024-11-22 01:09:55.198141: train_loss -0.7816 +2024-11-22 01:09:55.198365: val_loss -0.754 +2024-11-22 01:09:55.198444: Pseudo dice [0.8372] +2024-11-22 01:09:55.198522: Epoch time: 19.17 s +2024-11-22 01:09:56.047768: +2024-11-22 01:09:56.047985: Epoch 2662 +2024-11-22 01:09:56.048103: Current learning rate: 0.00695 +2024-11-22 01:10:14.330760: train_loss -0.7792 +2024-11-22 01:10:14.330985: val_loss -0.7146 +2024-11-22 01:10:14.331075: Pseudo dice [0.8408] +2024-11-22 01:10:14.331169: Epoch time: 18.28 s +2024-11-22 01:10:15.180981: +2024-11-22 01:10:15.181199: Epoch 2663 +2024-11-22 01:10:15.181312: Current learning rate: 0.00695 +2024-11-22 01:10:34.091487: train_loss -0.7727 +2024-11-22 01:10:34.091739: val_loss -0.6937 +2024-11-22 01:10:34.091812: Pseudo dice [0.8119] +2024-11-22 01:10:34.091895: Epoch time: 18.91 s +2024-11-22 01:10:34.945390: +2024-11-22 01:10:34.945629: Epoch 2664 +2024-11-22 01:10:34.945745: Current learning rate: 0.00695 +2024-11-22 01:10:52.949413: train_loss -0.7729 +2024-11-22 01:10:52.949647: val_loss -0.7424 +2024-11-22 01:10:52.949727: Pseudo dice [0.8391] +2024-11-22 01:10:52.949804: Epoch time: 18.0 s +2024-11-22 01:10:54.202880: +2024-11-22 01:10:54.203103: Epoch 2665 +2024-11-22 01:10:54.203219: Current learning rate: 0.00694 +2024-11-22 01:11:12.325301: train_loss -0.7788 +2024-11-22 01:11:12.325535: val_loss -0.7416 +2024-11-22 01:11:12.325685: Pseudo dice [0.8472] +2024-11-22 01:11:12.325764: Epoch time: 18.12 s +2024-11-22 01:11:13.188118: +2024-11-22 01:11:13.188323: Epoch 2666 +2024-11-22 01:11:13.188436: Current learning rate: 0.00694 +2024-11-22 01:11:33.093482: train_loss -0.7815 +2024-11-22 01:11:33.093784: val_loss -0.7469 +2024-11-22 01:11:33.093865: Pseudo dice [0.8505] +2024-11-22 01:11:33.093956: Epoch time: 19.91 s +2024-11-22 01:11:33.994347: +2024-11-22 01:11:33.994542: Epoch 2667 +2024-11-22 01:11:33.994650: Current learning rate: 0.00694 +2024-11-22 01:11:53.236766: train_loss -0.7799 +2024-11-22 01:11:53.236983: val_loss -0.7459 +2024-11-22 01:11:53.237067: Pseudo dice [0.8475] +2024-11-22 01:11:53.237140: Epoch time: 19.24 s +2024-11-22 01:11:54.083480: +2024-11-22 01:11:54.083703: Epoch 2668 +2024-11-22 01:11:54.083815: Current learning rate: 0.00694 +2024-11-22 01:12:13.736442: train_loss -0.7701 +2024-11-22 01:12:13.736676: val_loss -0.727 +2024-11-22 01:12:13.736753: Pseudo dice [0.8291] +2024-11-22 01:12:13.736830: Epoch time: 19.65 s +2024-11-22 01:12:14.588848: +2024-11-22 01:12:14.589056: Epoch 2669 +2024-11-22 01:12:14.589168: Current learning rate: 0.00694 +2024-11-22 01:12:33.348752: train_loss -0.7764 +2024-11-22 01:12:33.349012: val_loss -0.7403 +2024-11-22 01:12:33.349092: Pseudo dice [0.8234] +2024-11-22 01:12:33.354326: Epoch time: 18.76 s +2024-11-22 01:12:34.372529: +2024-11-22 01:12:34.372743: Epoch 2670 +2024-11-22 01:12:34.372859: Current learning rate: 0.00694 +2024-11-22 01:12:52.558920: train_loss -0.7833 +2024-11-22 01:12:52.559147: val_loss -0.7472 +2024-11-22 01:12:52.559225: Pseudo dice [0.8519] +2024-11-22 01:12:52.559304: Epoch time: 18.19 s +2024-11-22 01:12:53.466746: +2024-11-22 01:12:53.466954: Epoch 2671 +2024-11-22 01:12:53.467069: Current learning rate: 0.00694 +2024-11-22 01:13:12.797184: train_loss -0.7863 +2024-11-22 01:13:12.797398: val_loss -0.7347 +2024-11-22 01:13:12.797473: Pseudo dice [0.8426] +2024-11-22 01:13:12.797548: Epoch time: 19.33 s +2024-11-22 01:13:13.647539: +2024-11-22 01:13:13.647743: Epoch 2672 +2024-11-22 01:13:13.647853: Current learning rate: 0.00694 +2024-11-22 01:13:31.865596: train_loss -0.7777 +2024-11-22 01:13:31.865813: val_loss -0.7198 +2024-11-22 01:13:31.865891: Pseudo dice [0.8127] +2024-11-22 01:13:31.865965: Epoch time: 18.22 s +2024-11-22 01:13:32.718356: +2024-11-22 01:13:32.718584: Epoch 2673 +2024-11-22 01:13:32.718695: Current learning rate: 0.00694 +2024-11-22 01:13:50.726707: train_loss -0.7764 +2024-11-22 01:13:50.726962: val_loss -0.7123 +2024-11-22 01:13:50.727046: Pseudo dice [0.7958] +2024-11-22 01:13:50.727130: Epoch time: 18.01 s +2024-11-22 01:13:51.582905: +2024-11-22 01:13:51.583185: Epoch 2674 +2024-11-22 01:13:51.583296: Current learning rate: 0.00693 +2024-11-22 01:14:10.507723: train_loss -0.7743 +2024-11-22 01:14:10.508744: val_loss -0.7383 +2024-11-22 01:14:10.508837: Pseudo dice [0.8519] +2024-11-22 01:14:10.508915: Epoch time: 18.93 s +2024-11-22 01:14:11.373337: +2024-11-22 01:14:11.373630: Epoch 2675 +2024-11-22 01:14:11.373743: Current learning rate: 0.00693 +2024-11-22 01:14:30.600641: train_loss -0.7764 +2024-11-22 01:14:30.600876: val_loss -0.7524 +2024-11-22 01:14:30.600963: Pseudo dice [0.8403] +2024-11-22 01:14:30.601055: Epoch time: 19.23 s +2024-11-22 01:14:31.454188: +2024-11-22 01:14:31.454440: Epoch 2676 +2024-11-22 01:14:31.454553: Current learning rate: 0.00693 +2024-11-22 01:14:49.120615: train_loss -0.7789 +2024-11-22 01:14:49.120849: val_loss -0.7575 +2024-11-22 01:14:49.120933: Pseudo dice [0.821] +2024-11-22 01:14:49.121024: Epoch time: 17.67 s +2024-11-22 01:14:50.379222: +2024-11-22 01:14:50.379580: Epoch 2677 +2024-11-22 01:14:50.379734: Current learning rate: 0.00693 +2024-11-22 01:15:08.938955: train_loss -0.7715 +2024-11-22 01:15:08.939231: val_loss -0.7535 +2024-11-22 01:15:08.939306: Pseudo dice [0.8166] +2024-11-22 01:15:08.939386: Epoch time: 18.56 s +2024-11-22 01:15:09.789113: +2024-11-22 01:15:09.789358: Epoch 2678 +2024-11-22 01:15:09.789474: Current learning rate: 0.00693 +2024-11-22 01:15:28.060776: train_loss -0.7813 +2024-11-22 01:15:28.061005: val_loss -0.7299 +2024-11-22 01:15:28.061081: Pseudo dice [0.84] +2024-11-22 01:15:28.061157: Epoch time: 18.27 s +2024-11-22 01:15:28.912009: +2024-11-22 01:15:28.912210: Epoch 2679 +2024-11-22 01:15:28.912320: Current learning rate: 0.00693 +2024-11-22 01:15:48.645322: train_loss -0.7715 +2024-11-22 01:15:48.645545: val_loss -0.7528 +2024-11-22 01:15:48.645621: Pseudo dice [0.8346] +2024-11-22 01:15:48.645710: Epoch time: 19.73 s +2024-11-22 01:15:49.502799: +2024-11-22 01:15:49.503011: Epoch 2680 +2024-11-22 01:15:49.503122: Current learning rate: 0.00693 +2024-11-22 01:16:08.387614: train_loss -0.782 +2024-11-22 01:16:08.387877: val_loss -0.7325 +2024-11-22 01:16:08.387958: Pseudo dice [0.8232] +2024-11-22 01:16:08.388093: Epoch time: 18.89 s +2024-11-22 01:16:09.243122: +2024-11-22 01:16:09.243327: Epoch 2681 +2024-11-22 01:16:09.243443: Current learning rate: 0.00693 +2024-11-22 01:16:28.250202: train_loss -0.7756 +2024-11-22 01:16:28.250423: val_loss -0.7329 +2024-11-22 01:16:28.250500: Pseudo dice [0.822] +2024-11-22 01:16:28.250579: Epoch time: 19.01 s +2024-11-22 01:16:29.195544: +2024-11-22 01:16:29.195752: Epoch 2682 +2024-11-22 01:16:29.195866: Current learning rate: 0.00692 +2024-11-22 01:16:47.629942: train_loss -0.7808 +2024-11-22 01:16:47.630169: val_loss -0.7591 +2024-11-22 01:16:47.630243: Pseudo dice [0.8552] +2024-11-22 01:16:47.630318: Epoch time: 18.44 s +2024-11-22 01:16:48.480824: +2024-11-22 01:16:48.481069: Epoch 2683 +2024-11-22 01:16:48.481183: Current learning rate: 0.00692 +2024-11-22 01:17:08.590786: train_loss -0.7812 +2024-11-22 01:17:08.591054: val_loss -0.7508 +2024-11-22 01:17:08.591139: Pseudo dice [0.8354] +2024-11-22 01:17:08.591222: Epoch time: 20.11 s +2024-11-22 01:17:09.446335: +2024-11-22 01:17:09.446563: Epoch 2684 +2024-11-22 01:17:09.446674: Current learning rate: 0.00692 +2024-11-22 01:17:27.146124: train_loss -0.7616 +2024-11-22 01:17:27.146370: val_loss -0.7552 +2024-11-22 01:17:27.146446: Pseudo dice [0.8526] +2024-11-22 01:17:27.146524: Epoch time: 17.7 s +2024-11-22 01:17:27.995642: +2024-11-22 01:17:27.995849: Epoch 2685 +2024-11-22 01:17:27.995959: Current learning rate: 0.00692 +2024-11-22 01:17:46.784951: train_loss -0.7738 +2024-11-22 01:17:46.785175: val_loss -0.7458 +2024-11-22 01:17:46.785249: Pseudo dice [0.8693] +2024-11-22 01:17:46.785326: Epoch time: 18.79 s +2024-11-22 01:17:47.636094: +2024-11-22 01:17:47.636390: Epoch 2686 +2024-11-22 01:17:47.636503: Current learning rate: 0.00692 +2024-11-22 01:18:05.459160: train_loss -0.7782 +2024-11-22 01:18:05.459591: val_loss -0.7404 +2024-11-22 01:18:05.459677: Pseudo dice [0.8168] +2024-11-22 01:18:05.459752: Epoch time: 17.82 s +2024-11-22 01:18:06.313337: +2024-11-22 01:18:06.313550: Epoch 2687 +2024-11-22 01:18:06.313664: Current learning rate: 0.00692 +2024-11-22 01:18:23.511929: train_loss -0.7804 +2024-11-22 01:18:23.517369: val_loss -0.7431 +2024-11-22 01:18:23.517459: Pseudo dice [0.8246] +2024-11-22 01:18:23.517546: Epoch time: 17.2 s +2024-11-22 01:18:24.593926: +2024-11-22 01:18:24.594241: Epoch 2688 +2024-11-22 01:18:24.594359: Current learning rate: 0.00692 +2024-11-22 01:18:42.262094: train_loss -0.7834 +2024-11-22 01:18:42.262305: val_loss -0.7611 +2024-11-22 01:18:42.262380: Pseudo dice [0.8163] +2024-11-22 01:18:42.262459: Epoch time: 17.67 s +2024-11-22 01:18:43.529316: +2024-11-22 01:18:43.529565: Epoch 2689 +2024-11-22 01:18:43.529682: Current learning rate: 0.00692 +2024-11-22 01:19:02.985928: train_loss -0.7653 +2024-11-22 01:19:02.988339: val_loss -0.7073 +2024-11-22 01:19:02.988501: Pseudo dice [0.8416] +2024-11-22 01:19:02.988583: Epoch time: 19.46 s +2024-11-22 01:19:03.869598: +2024-11-22 01:19:03.869801: Epoch 2690 +2024-11-22 01:19:03.869914: Current learning rate: 0.00692 +2024-11-22 01:19:23.601336: train_loss -0.7739 +2024-11-22 01:19:23.601609: val_loss -0.7328 +2024-11-22 01:19:23.601686: Pseudo dice [0.839] +2024-11-22 01:19:23.601772: Epoch time: 19.73 s +2024-11-22 01:19:24.471629: +2024-11-22 01:19:24.471828: Epoch 2691 +2024-11-22 01:19:24.471941: Current learning rate: 0.00691 +2024-11-22 01:19:43.591853: train_loss -0.7701 +2024-11-22 01:19:43.592123: val_loss -0.7547 +2024-11-22 01:19:43.592201: Pseudo dice [0.8242] +2024-11-22 01:19:43.592277: Epoch time: 19.12 s +2024-11-22 01:19:44.490793: +2024-11-22 01:19:44.491002: Epoch 2692 +2024-11-22 01:19:44.491112: Current learning rate: 0.00691 +2024-11-22 01:20:03.313529: train_loss -0.7786 +2024-11-22 01:20:03.313751: val_loss -0.7694 +2024-11-22 01:20:03.313833: Pseudo dice [0.837] +2024-11-22 01:20:03.313910: Epoch time: 18.82 s +2024-11-22 01:20:04.174436: +2024-11-22 01:20:04.174662: Epoch 2693 +2024-11-22 01:20:04.174775: Current learning rate: 0.00691 +2024-11-22 01:20:23.153361: train_loss -0.7863 +2024-11-22 01:20:23.153579: val_loss -0.7542 +2024-11-22 01:20:23.153653: Pseudo dice [0.8613] +2024-11-22 01:20:23.153729: Epoch time: 18.98 s +2024-11-22 01:20:24.093493: +2024-11-22 01:20:24.093713: Epoch 2694 +2024-11-22 01:20:24.093829: Current learning rate: 0.00691 +2024-11-22 01:20:43.894949: train_loss -0.7803 +2024-11-22 01:20:43.897412: val_loss -0.7529 +2024-11-22 01:20:43.897506: Pseudo dice [0.8516] +2024-11-22 01:20:43.897591: Epoch time: 19.8 s +2024-11-22 01:20:44.793825: +2024-11-22 01:20:44.800285: Epoch 2695 +2024-11-22 01:20:44.800410: Current learning rate: 0.00691 +2024-11-22 01:21:03.735370: train_loss -0.7836 +2024-11-22 01:21:03.735587: val_loss -0.7725 +2024-11-22 01:21:03.735662: Pseudo dice [0.8646] +2024-11-22 01:21:03.735738: Epoch time: 18.94 s +2024-11-22 01:21:04.588550: +2024-11-22 01:21:04.588767: Epoch 2696 +2024-11-22 01:21:04.588879: Current learning rate: 0.00691 +2024-11-22 01:21:22.977594: train_loss -0.7883 +2024-11-22 01:21:22.977810: val_loss -0.7352 +2024-11-22 01:21:22.977889: Pseudo dice [0.8416] +2024-11-22 01:21:22.977967: Epoch time: 18.39 s +2024-11-22 01:21:23.831821: +2024-11-22 01:21:23.832029: Epoch 2697 +2024-11-22 01:21:23.832143: Current learning rate: 0.00691 +2024-11-22 01:21:42.083147: train_loss -0.7775 +2024-11-22 01:21:42.083383: val_loss -0.7357 +2024-11-22 01:21:42.083459: Pseudo dice [0.812] +2024-11-22 01:21:42.083540: Epoch time: 18.25 s +2024-11-22 01:21:42.938721: +2024-11-22 01:21:42.938927: Epoch 2698 +2024-11-22 01:21:42.939043: Current learning rate: 0.00691 +2024-11-22 01:22:00.718060: train_loss -0.7802 +2024-11-22 01:22:00.720632: val_loss -0.7501 +2024-11-22 01:22:00.720725: Pseudo dice [0.8307] +2024-11-22 01:22:00.720810: Epoch time: 17.78 s +2024-11-22 01:22:01.674582: +2024-11-22 01:22:01.674780: Epoch 2699 +2024-11-22 01:22:01.674899: Current learning rate: 0.0069 +2024-11-22 01:22:20.321555: train_loss -0.7851 +2024-11-22 01:22:20.321820: val_loss -0.7552 +2024-11-22 01:22:20.321899: Pseudo dice [0.8283] +2024-11-22 01:22:20.321978: Epoch time: 18.65 s +2024-11-22 01:22:21.395121: +2024-11-22 01:22:21.395577: Epoch 2700 +2024-11-22 01:22:21.395707: Current learning rate: 0.0069 +2024-11-22 01:22:40.236606: train_loss -0.7855 +2024-11-22 01:22:40.236851: val_loss -0.7414 +2024-11-22 01:22:40.236928: Pseudo dice [0.834] +2024-11-22 01:22:40.237014: Epoch time: 18.84 s +2024-11-22 01:22:41.084215: +2024-11-22 01:22:41.084425: Epoch 2701 +2024-11-22 01:22:41.084537: Current learning rate: 0.0069 +2024-11-22 01:22:59.961664: train_loss -0.7776 +2024-11-22 01:22:59.961911: val_loss -0.7643 +2024-11-22 01:22:59.961987: Pseudo dice [0.847] +2024-11-22 01:22:59.962077: Epoch time: 18.88 s +2024-11-22 01:23:00.820737: +2024-11-22 01:23:00.820954: Epoch 2702 +2024-11-22 01:23:00.821076: Current learning rate: 0.0069 +2024-11-22 01:23:20.186779: train_loss -0.7887 +2024-11-22 01:23:20.187011: val_loss -0.7398 +2024-11-22 01:23:20.187089: Pseudo dice [0.8344] +2024-11-22 01:23:20.187165: Epoch time: 19.37 s +2024-11-22 01:23:21.207247: +2024-11-22 01:23:21.207469: Epoch 2703 +2024-11-22 01:23:21.207586: Current learning rate: 0.0069 +2024-11-22 01:23:40.072263: train_loss -0.7789 +2024-11-22 01:23:40.072529: val_loss -0.7441 +2024-11-22 01:23:40.072607: Pseudo dice [0.8451] +2024-11-22 01:23:40.072722: Epoch time: 18.87 s +2024-11-22 01:23:41.028997: +2024-11-22 01:23:41.029207: Epoch 2704 +2024-11-22 01:23:41.029324: Current learning rate: 0.0069 +2024-11-22 01:24:00.805636: train_loss -0.776 +2024-11-22 01:24:00.805853: val_loss -0.747 +2024-11-22 01:24:00.808101: Pseudo dice [0.8492] +2024-11-22 01:24:00.808195: Epoch time: 19.78 s +2024-11-22 01:24:01.651101: +2024-11-22 01:24:01.651306: Epoch 2705 +2024-11-22 01:24:01.651417: Current learning rate: 0.0069 +2024-11-22 01:24:20.843672: train_loss -0.7846 +2024-11-22 01:24:20.845814: val_loss -0.7405 +2024-11-22 01:24:20.845925: Pseudo dice [0.8386] +2024-11-22 01:24:20.846010: Epoch time: 19.19 s +2024-11-22 01:24:21.726915: +2024-11-22 01:24:21.727230: Epoch 2706 +2024-11-22 01:24:21.727343: Current learning rate: 0.0069 +2024-11-22 01:24:39.969781: train_loss -0.7819 +2024-11-22 01:24:39.970018: val_loss -0.7542 +2024-11-22 01:24:39.970097: Pseudo dice [0.8451] +2024-11-22 01:24:39.970176: Epoch time: 18.24 s +2024-11-22 01:24:40.815630: +2024-11-22 01:24:40.815842: Epoch 2707 +2024-11-22 01:24:40.815957: Current learning rate: 0.0069 +2024-11-22 01:25:00.418630: train_loss -0.7783 +2024-11-22 01:25:00.418843: val_loss -0.7483 +2024-11-22 01:25:00.418918: Pseudo dice [0.8284] +2024-11-22 01:25:00.419001: Epoch time: 19.6 s +2024-11-22 01:25:01.273060: +2024-11-22 01:25:01.273263: Epoch 2708 +2024-11-22 01:25:01.273375: Current learning rate: 0.00689 +2024-11-22 01:25:20.149103: train_loss -0.7807 +2024-11-22 01:25:20.149345: val_loss -0.7417 +2024-11-22 01:25:20.149423: Pseudo dice [0.8182] +2024-11-22 01:25:20.149507: Epoch time: 18.88 s +2024-11-22 01:25:20.988731: +2024-11-22 01:25:20.988929: Epoch 2709 +2024-11-22 01:25:20.989043: Current learning rate: 0.00689 +2024-11-22 01:25:39.423392: train_loss -0.7857 +2024-11-22 01:25:39.423586: val_loss -0.7284 +2024-11-22 01:25:39.423663: Pseudo dice [0.8485] +2024-11-22 01:25:39.423737: Epoch time: 18.44 s +2024-11-22 01:25:40.268835: +2024-11-22 01:25:40.269057: Epoch 2710 +2024-11-22 01:25:40.269169: Current learning rate: 0.00689 +2024-11-22 01:25:58.908668: train_loss -0.797 +2024-11-22 01:25:58.908890: val_loss -0.755 +2024-11-22 01:25:58.909010: Pseudo dice [0.8308] +2024-11-22 01:25:58.909085: Epoch time: 18.64 s +2024-11-22 01:25:59.753841: +2024-11-22 01:25:59.754032: Epoch 2711 +2024-11-22 01:25:59.754142: Current learning rate: 0.00689 +2024-11-22 01:26:18.204383: train_loss -0.7924 +2024-11-22 01:26:18.204628: val_loss -0.7178 +2024-11-22 01:26:18.204705: Pseudo dice [0.83] +2024-11-22 01:26:18.204792: Epoch time: 18.45 s +2024-11-22 01:26:19.410473: +2024-11-22 01:26:19.410681: Epoch 2712 +2024-11-22 01:26:19.410802: Current learning rate: 0.00689 +2024-11-22 01:26:39.429801: train_loss -0.786 +2024-11-22 01:26:39.430118: val_loss -0.7592 +2024-11-22 01:26:39.430207: Pseudo dice [0.8376] +2024-11-22 01:26:39.430286: Epoch time: 20.02 s +2024-11-22 01:26:40.348681: +2024-11-22 01:26:40.348920: Epoch 2713 +2024-11-22 01:26:40.349042: Current learning rate: 0.00689 +2024-11-22 01:26:59.257318: train_loss -0.7771 +2024-11-22 01:26:59.257538: val_loss -0.7419 +2024-11-22 01:26:59.257612: Pseudo dice [0.8337] +2024-11-22 01:26:59.257686: Epoch time: 18.91 s +2024-11-22 01:27:00.103217: +2024-11-22 01:27:00.103429: Epoch 2714 +2024-11-22 01:27:00.103540: Current learning rate: 0.00689 +2024-11-22 01:27:18.993724: train_loss -0.7852 +2024-11-22 01:27:18.993965: val_loss -0.7503 +2024-11-22 01:27:18.994109: Pseudo dice [0.8458] +2024-11-22 01:27:18.994195: Epoch time: 18.89 s +2024-11-22 01:27:19.849882: +2024-11-22 01:27:19.850113: Epoch 2715 +2024-11-22 01:27:19.850227: Current learning rate: 0.00689 +2024-11-22 01:27:38.919484: train_loss -0.7843 +2024-11-22 01:27:38.919696: val_loss -0.7516 +2024-11-22 01:27:38.919771: Pseudo dice [0.8517] +2024-11-22 01:27:38.919846: Epoch time: 19.07 s +2024-11-22 01:27:39.754317: +2024-11-22 01:27:39.754511: Epoch 2716 +2024-11-22 01:27:39.754625: Current learning rate: 0.00688 +2024-11-22 01:27:58.219248: train_loss -0.7811 +2024-11-22 01:27:58.219475: val_loss -0.7616 +2024-11-22 01:27:58.219550: Pseudo dice [0.8467] +2024-11-22 01:27:58.219629: Epoch time: 18.47 s +2024-11-22 01:27:59.069879: +2024-11-22 01:27:59.070110: Epoch 2717 +2024-11-22 01:27:59.070227: Current learning rate: 0.00688 +2024-11-22 01:28:17.688473: train_loss -0.789 +2024-11-22 01:28:17.688703: val_loss -0.7096 +2024-11-22 01:28:17.688781: Pseudo dice [0.823] +2024-11-22 01:28:17.688858: Epoch time: 18.62 s +2024-11-22 01:28:18.610741: +2024-11-22 01:28:18.610952: Epoch 2718 +2024-11-22 01:28:18.611067: Current learning rate: 0.00688 +2024-11-22 01:28:37.700879: train_loss -0.7835 +2024-11-22 01:28:37.701151: val_loss -0.7285 +2024-11-22 01:28:37.701236: Pseudo dice [0.845] +2024-11-22 01:28:37.701316: Epoch time: 19.09 s +2024-11-22 01:28:38.551816: +2024-11-22 01:28:38.552032: Epoch 2719 +2024-11-22 01:28:38.552150: Current learning rate: 0.00688 +2024-11-22 01:28:57.885613: train_loss -0.7852 +2024-11-22 01:28:57.885848: val_loss -0.7628 +2024-11-22 01:28:57.885928: Pseudo dice [0.8354] +2024-11-22 01:28:57.886016: Epoch time: 19.33 s +2024-11-22 01:28:58.728684: +2024-11-22 01:28:58.728945: Epoch 2720 +2024-11-22 01:28:58.729075: Current learning rate: 0.00688 +2024-11-22 01:29:17.151737: train_loss -0.783 +2024-11-22 01:29:17.157153: val_loss -0.7457 +2024-11-22 01:29:17.157272: Pseudo dice [0.847] +2024-11-22 01:29:17.157357: Epoch time: 18.42 s +2024-11-22 01:29:18.009841: +2024-11-22 01:29:18.010138: Epoch 2721 +2024-11-22 01:29:18.010246: Current learning rate: 0.00688 +2024-11-22 01:29:36.077121: train_loss -0.7846 +2024-11-22 01:29:36.077358: val_loss -0.7221 +2024-11-22 01:29:36.077434: Pseudo dice [0.82] +2024-11-22 01:29:36.077509: Epoch time: 18.07 s +2024-11-22 01:29:36.932591: +2024-11-22 01:29:36.932842: Epoch 2722 +2024-11-22 01:29:36.932962: Current learning rate: 0.00688 +2024-11-22 01:29:54.900806: train_loss -0.7877 +2024-11-22 01:29:54.901054: val_loss -0.7291 +2024-11-22 01:29:54.901130: Pseudo dice [0.8438] +2024-11-22 01:29:54.901214: Epoch time: 17.97 s +2024-11-22 01:29:55.756785: +2024-11-22 01:29:55.757005: Epoch 2723 +2024-11-22 01:29:55.758809: Current learning rate: 0.00688 +2024-11-22 01:30:14.852426: train_loss -0.7796 +2024-11-22 01:30:14.852650: val_loss -0.7752 +2024-11-22 01:30:14.852727: Pseudo dice [0.841] +2024-11-22 01:30:14.852803: Epoch time: 19.1 s +2024-11-22 01:30:16.187325: +2024-11-22 01:30:16.187573: Epoch 2724 +2024-11-22 01:30:16.187689: Current learning rate: 0.00688 +2024-11-22 01:30:35.340647: train_loss -0.7884 +2024-11-22 01:30:35.340927: val_loss -0.7441 +2024-11-22 01:30:35.341015: Pseudo dice [0.8306] +2024-11-22 01:30:35.341089: Epoch time: 19.15 s +2024-11-22 01:30:36.197956: +2024-11-22 01:30:36.198208: Epoch 2725 +2024-11-22 01:30:36.198322: Current learning rate: 0.00687 +2024-11-22 01:30:55.280872: train_loss -0.7811 +2024-11-22 01:30:55.281136: val_loss -0.7657 +2024-11-22 01:30:55.281219: Pseudo dice [0.8609] +2024-11-22 01:30:55.281305: Epoch time: 19.08 s +2024-11-22 01:30:56.129539: +2024-11-22 01:30:56.129777: Epoch 2726 +2024-11-22 01:30:56.129890: Current learning rate: 0.00687 +2024-11-22 01:31:15.926254: train_loss -0.7768 +2024-11-22 01:31:15.926465: val_loss -0.7418 +2024-11-22 01:31:15.926539: Pseudo dice [0.8339] +2024-11-22 01:31:15.926614: Epoch time: 19.8 s +2024-11-22 01:31:16.780378: +2024-11-22 01:31:16.780591: Epoch 2727 +2024-11-22 01:31:16.780702: Current learning rate: 0.00687 +2024-11-22 01:31:35.634936: train_loss -0.7492 +2024-11-22 01:31:35.635238: val_loss -0.6915 +2024-11-22 01:31:35.635317: Pseudo dice [0.8059] +2024-11-22 01:31:35.635393: Epoch time: 18.86 s +2024-11-22 01:31:36.492465: +2024-11-22 01:31:36.492675: Epoch 2728 +2024-11-22 01:31:36.492787: Current learning rate: 0.00687 +2024-11-22 01:31:55.746045: train_loss -0.7565 +2024-11-22 01:31:55.746276: val_loss -0.7508 +2024-11-22 01:31:55.746356: Pseudo dice [0.844] +2024-11-22 01:31:55.746438: Epoch time: 19.25 s +2024-11-22 01:31:56.708139: +2024-11-22 01:31:56.708379: Epoch 2729 +2024-11-22 01:31:56.708493: Current learning rate: 0.00687 +2024-11-22 01:32:15.178854: train_loss -0.7655 +2024-11-22 01:32:15.179110: val_loss -0.7282 +2024-11-22 01:32:15.179188: Pseudo dice [0.8085] +2024-11-22 01:32:15.179283: Epoch time: 18.47 s +2024-11-22 01:32:16.205466: +2024-11-22 01:32:16.205661: Epoch 2730 +2024-11-22 01:32:16.205774: Current learning rate: 0.00687 +2024-11-22 01:32:35.163400: train_loss -0.7356 +2024-11-22 01:32:35.163622: val_loss -0.7278 +2024-11-22 01:32:35.163702: Pseudo dice [0.8443] +2024-11-22 01:32:35.163775: Epoch time: 18.96 s +2024-11-22 01:32:36.232346: +2024-11-22 01:32:36.232552: Epoch 2731 +2024-11-22 01:32:36.232666: Current learning rate: 0.00687 +2024-11-22 01:32:55.185779: train_loss -0.7596 +2024-11-22 01:32:55.186104: val_loss -0.7311 +2024-11-22 01:32:55.186193: Pseudo dice [0.8354] +2024-11-22 01:32:55.186276: Epoch time: 18.95 s +2024-11-22 01:32:56.042409: +2024-11-22 01:32:56.042603: Epoch 2732 +2024-11-22 01:32:56.042717: Current learning rate: 0.00687 +2024-11-22 01:33:14.440434: train_loss -0.7717 +2024-11-22 01:33:14.440712: val_loss -0.7213 +2024-11-22 01:33:14.440793: Pseudo dice [0.8423] +2024-11-22 01:33:14.440876: Epoch time: 18.4 s +2024-11-22 01:33:15.306426: +2024-11-22 01:33:15.306726: Epoch 2733 +2024-11-22 01:33:15.306844: Current learning rate: 0.00686 +2024-11-22 01:33:34.115055: train_loss -0.7638 +2024-11-22 01:33:34.115284: val_loss -0.755 +2024-11-22 01:33:34.115361: Pseudo dice [0.8523] +2024-11-22 01:33:34.115440: Epoch time: 18.81 s +2024-11-22 01:33:35.074881: +2024-11-22 01:33:35.075091: Epoch 2734 +2024-11-22 01:33:35.075207: Current learning rate: 0.00686 +2024-11-22 01:33:52.702891: train_loss -0.7729 +2024-11-22 01:33:52.703156: val_loss -0.7244 +2024-11-22 01:33:52.703234: Pseudo dice [0.8339] +2024-11-22 01:33:52.703344: Epoch time: 17.63 s +2024-11-22 01:33:53.576781: +2024-11-22 01:33:53.577136: Epoch 2735 +2024-11-22 01:33:53.577251: Current learning rate: 0.00686 +2024-11-22 01:34:12.254065: train_loss -0.7719 +2024-11-22 01:34:12.254290: val_loss -0.7128 +2024-11-22 01:34:12.254366: Pseudo dice [0.8314] +2024-11-22 01:34:12.254442: Epoch time: 18.68 s +2024-11-22 01:34:13.538424: +2024-11-22 01:34:13.538651: Epoch 2736 +2024-11-22 01:34:13.538762: Current learning rate: 0.00686 +2024-11-22 01:34:32.711587: train_loss -0.7733 +2024-11-22 01:34:32.711828: val_loss -0.7448 +2024-11-22 01:34:32.711908: Pseudo dice [0.84] +2024-11-22 01:34:32.711988: Epoch time: 19.17 s +2024-11-22 01:34:33.563084: +2024-11-22 01:34:33.563292: Epoch 2737 +2024-11-22 01:34:33.563403: Current learning rate: 0.00686 +2024-11-22 01:34:51.904385: train_loss -0.7715 +2024-11-22 01:34:51.904614: val_loss -0.7454 +2024-11-22 01:34:51.904696: Pseudo dice [0.8208] +2024-11-22 01:34:51.904773: Epoch time: 18.34 s +2024-11-22 01:34:52.814068: +2024-11-22 01:34:52.814368: Epoch 2738 +2024-11-22 01:34:52.814483: Current learning rate: 0.00686 +2024-11-22 01:35:11.833889: train_loss -0.7747 +2024-11-22 01:35:11.839401: val_loss -0.7598 +2024-11-22 01:35:11.839521: Pseudo dice [0.8378] +2024-11-22 01:35:11.839603: Epoch time: 19.02 s +2024-11-22 01:35:12.706843: +2024-11-22 01:35:12.707057: Epoch 2739 +2024-11-22 01:35:12.707167: Current learning rate: 0.00686 +2024-11-22 01:35:31.016883: train_loss -0.7684 +2024-11-22 01:35:31.017147: val_loss -0.753 +2024-11-22 01:35:31.017347: Pseudo dice [0.8418] +2024-11-22 01:35:31.017432: Epoch time: 18.31 s +2024-11-22 01:35:31.872605: +2024-11-22 01:35:31.872861: Epoch 2740 +2024-11-22 01:35:31.873001: Current learning rate: 0.00686 +2024-11-22 01:35:50.374865: train_loss -0.7695 +2024-11-22 01:35:50.375090: val_loss -0.7323 +2024-11-22 01:35:50.375162: Pseudo dice [0.838] +2024-11-22 01:35:50.375235: Epoch time: 18.5 s +2024-11-22 01:35:51.249881: +2024-11-22 01:35:51.250096: Epoch 2741 +2024-11-22 01:35:51.250214: Current learning rate: 0.00686 +2024-11-22 01:36:10.181186: train_loss -0.776 +2024-11-22 01:36:10.181409: val_loss -0.7447 +2024-11-22 01:36:10.181486: Pseudo dice [0.84] +2024-11-22 01:36:10.181563: Epoch time: 18.93 s +2024-11-22 01:36:11.034199: +2024-11-22 01:36:11.034778: Epoch 2742 +2024-11-22 01:36:11.034899: Current learning rate: 0.00685 +2024-11-22 01:36:28.987565: train_loss -0.7732 +2024-11-22 01:36:28.989974: val_loss -0.7407 +2024-11-22 01:36:28.990080: Pseudo dice [0.8421] +2024-11-22 01:36:28.990159: Epoch time: 17.95 s +2024-11-22 01:36:29.854349: +2024-11-22 01:36:29.854567: Epoch 2743 +2024-11-22 01:36:29.854683: Current learning rate: 0.00685 +2024-11-22 01:36:48.538297: train_loss -0.7778 +2024-11-22 01:36:48.538543: val_loss -0.7517 +2024-11-22 01:36:48.538621: Pseudo dice [0.8352] +2024-11-22 01:36:48.538704: Epoch time: 18.68 s +2024-11-22 01:36:49.387560: +2024-11-22 01:36:49.387756: Epoch 2744 +2024-11-22 01:36:49.387869: Current learning rate: 0.00685 +2024-11-22 01:37:07.305739: train_loss -0.7822 +2024-11-22 01:37:07.305980: val_loss -0.7545 +2024-11-22 01:37:07.306064: Pseudo dice [0.8309] +2024-11-22 01:37:07.306141: Epoch time: 17.92 s +2024-11-22 01:37:08.171233: +2024-11-22 01:37:08.171460: Epoch 2745 +2024-11-22 01:37:08.171579: Current learning rate: 0.00685 +2024-11-22 01:37:26.483635: train_loss -0.7849 +2024-11-22 01:37:26.483855: val_loss -0.7463 +2024-11-22 01:37:26.483929: Pseudo dice [0.8273] +2024-11-22 01:37:26.484011: Epoch time: 18.31 s +2024-11-22 01:37:27.336558: +2024-11-22 01:37:27.336826: Epoch 2746 +2024-11-22 01:37:27.336939: Current learning rate: 0.00685 +2024-11-22 01:37:46.103410: train_loss -0.7865 +2024-11-22 01:37:46.106185: val_loss -0.7522 +2024-11-22 01:37:46.106285: Pseudo dice [0.847] +2024-11-22 01:37:46.106367: Epoch time: 18.77 s +2024-11-22 01:37:47.062767: +2024-11-22 01:37:47.062967: Epoch 2747 +2024-11-22 01:37:47.063108: Current learning rate: 0.00685 +2024-11-22 01:38:05.045583: train_loss -0.7799 +2024-11-22 01:38:05.045830: val_loss -0.7668 +2024-11-22 01:38:05.045928: Pseudo dice [0.8476] +2024-11-22 01:38:05.046018: Epoch time: 17.98 s +2024-11-22 01:38:06.270431: +2024-11-22 01:38:06.270672: Epoch 2748 +2024-11-22 01:38:06.270786: Current learning rate: 0.00685 +2024-11-22 01:38:24.281688: train_loss -0.7915 +2024-11-22 01:38:24.281933: val_loss -0.7648 +2024-11-22 01:38:24.282015: Pseudo dice [0.8434] +2024-11-22 01:38:24.282099: Epoch time: 18.01 s +2024-11-22 01:38:25.194989: +2024-11-22 01:38:25.195312: Epoch 2749 +2024-11-22 01:38:25.195428: Current learning rate: 0.00685 +2024-11-22 01:38:45.330515: train_loss -0.7872 +2024-11-22 01:38:45.330727: val_loss -0.7699 +2024-11-22 01:38:45.330804: Pseudo dice [0.8394] +2024-11-22 01:38:45.330888: Epoch time: 20.14 s +2024-11-22 01:38:46.547540: +2024-11-22 01:38:46.547844: Epoch 2750 +2024-11-22 01:38:46.547959: Current learning rate: 0.00684 +2024-11-22 01:39:05.477943: train_loss -0.7873 +2024-11-22 01:39:05.478203: val_loss -0.7468 +2024-11-22 01:39:05.478284: Pseudo dice [0.8529] +2024-11-22 01:39:05.478366: Epoch time: 18.93 s +2024-11-22 01:39:06.358322: +2024-11-22 01:39:06.358544: Epoch 2751 +2024-11-22 01:39:06.358659: Current learning rate: 0.00684 +2024-11-22 01:39:24.906058: train_loss -0.7891 +2024-11-22 01:39:24.906286: val_loss -0.7653 +2024-11-22 01:39:24.906364: Pseudo dice [0.8563] +2024-11-22 01:39:24.906444: Epoch time: 18.55 s +2024-11-22 01:39:25.860821: +2024-11-22 01:39:25.861040: Epoch 2752 +2024-11-22 01:39:25.861149: Current learning rate: 0.00684 +2024-11-22 01:39:43.712117: train_loss -0.7834 +2024-11-22 01:39:43.712341: val_loss -0.7501 +2024-11-22 01:39:43.712416: Pseudo dice [0.8524] +2024-11-22 01:39:43.712492: Epoch time: 17.85 s +2024-11-22 01:39:44.561594: +2024-11-22 01:39:44.561799: Epoch 2753 +2024-11-22 01:39:44.561908: Current learning rate: 0.00684 +2024-11-22 01:40:04.156878: train_loss -0.788 +2024-11-22 01:40:04.158187: val_loss -0.7449 +2024-11-22 01:40:04.158441: Pseudo dice [0.8172] +2024-11-22 01:40:04.158524: Epoch time: 19.6 s +2024-11-22 01:40:05.180227: +2024-11-22 01:40:05.180407: Epoch 2754 +2024-11-22 01:40:05.180518: Current learning rate: 0.00684 +2024-11-22 01:40:24.139916: train_loss -0.792 +2024-11-22 01:40:24.140177: val_loss -0.7443 +2024-11-22 01:40:24.140257: Pseudo dice [0.8475] +2024-11-22 01:40:24.140342: Epoch time: 18.96 s +2024-11-22 01:40:25.001587: +2024-11-22 01:40:25.001868: Epoch 2755 +2024-11-22 01:40:25.001984: Current learning rate: 0.00684 +2024-11-22 01:40:42.927930: train_loss -0.7687 +2024-11-22 01:40:42.928188: val_loss -0.7451 +2024-11-22 01:40:42.928267: Pseudo dice [0.8442] +2024-11-22 01:40:42.928344: Epoch time: 17.93 s +2024-11-22 01:40:43.787730: +2024-11-22 01:40:43.787947: Epoch 2756 +2024-11-22 01:40:43.788066: Current learning rate: 0.00684 +2024-11-22 01:41:02.311200: train_loss -0.7724 +2024-11-22 01:41:02.311484: val_loss -0.738 +2024-11-22 01:41:02.311562: Pseudo dice [0.8524] +2024-11-22 01:41:02.311641: Epoch time: 18.52 s +2024-11-22 01:41:03.163646: +2024-11-22 01:41:03.163884: Epoch 2757 +2024-11-22 01:41:03.164005: Current learning rate: 0.00684 +2024-11-22 01:41:22.009536: train_loss -0.776 +2024-11-22 01:41:22.009755: val_loss -0.7192 +2024-11-22 01:41:22.009832: Pseudo dice [0.8249] +2024-11-22 01:41:22.009913: Epoch time: 18.85 s +2024-11-22 01:41:22.867130: +2024-11-22 01:41:22.867326: Epoch 2758 +2024-11-22 01:41:22.867442: Current learning rate: 0.00684 +2024-11-22 01:41:41.759802: train_loss -0.7823 +2024-11-22 01:41:41.760058: val_loss -0.7533 +2024-11-22 01:41:41.760133: Pseudo dice [0.8496] +2024-11-22 01:41:41.760211: Epoch time: 18.89 s +2024-11-22 01:41:42.615731: +2024-11-22 01:41:42.615951: Epoch 2759 +2024-11-22 01:41:42.616074: Current learning rate: 0.00683 +2024-11-22 01:42:01.455452: train_loss -0.7899 +2024-11-22 01:42:01.455700: val_loss -0.7484 +2024-11-22 01:42:01.455778: Pseudo dice [0.826] +2024-11-22 01:42:01.455853: Epoch time: 18.84 s +2024-11-22 01:42:02.307709: +2024-11-22 01:42:02.308039: Epoch 2760 +2024-11-22 01:42:02.308153: Current learning rate: 0.00683 +2024-11-22 01:42:22.058270: train_loss -0.7729 +2024-11-22 01:42:22.058533: val_loss -0.7283 +2024-11-22 01:42:22.058609: Pseudo dice [0.83] +2024-11-22 01:42:22.063890: Epoch time: 19.75 s +2024-11-22 01:42:23.114442: +2024-11-22 01:42:23.114701: Epoch 2761 +2024-11-22 01:42:23.114821: Current learning rate: 0.00683 +2024-11-22 01:42:41.382844: train_loss -0.7853 +2024-11-22 01:42:41.383075: val_loss -0.7579 +2024-11-22 01:42:41.383151: Pseudo dice [0.821] +2024-11-22 01:42:41.383227: Epoch time: 18.27 s +2024-11-22 01:42:42.244958: +2024-11-22 01:42:42.245251: Epoch 2762 +2024-11-22 01:42:42.245373: Current learning rate: 0.00683 +2024-11-22 01:42:59.817499: train_loss -0.7814 +2024-11-22 01:42:59.817719: val_loss -0.7415 +2024-11-22 01:42:59.817791: Pseudo dice [0.8473] +2024-11-22 01:42:59.817870: Epoch time: 17.57 s +2024-11-22 01:43:00.832375: +2024-11-22 01:43:00.832586: Epoch 2763 +2024-11-22 01:43:00.832702: Current learning rate: 0.00683 +2024-11-22 01:43:19.355769: train_loss -0.783 +2024-11-22 01:43:19.356058: val_loss -0.7577 +2024-11-22 01:43:19.356147: Pseudo dice [0.8446] +2024-11-22 01:43:19.356232: Epoch time: 18.52 s +2024-11-22 01:43:20.219101: +2024-11-22 01:43:20.219320: Epoch 2764 +2024-11-22 01:43:20.219432: Current learning rate: 0.00683 +2024-11-22 01:43:37.928173: train_loss -0.7789 +2024-11-22 01:43:37.928389: val_loss -0.7451 +2024-11-22 01:43:37.928466: Pseudo dice [0.8239] +2024-11-22 01:43:37.928542: Epoch time: 17.71 s +2024-11-22 01:43:38.779400: +2024-11-22 01:43:38.779608: Epoch 2765 +2024-11-22 01:43:38.779722: Current learning rate: 0.00683 +2024-11-22 01:43:57.435809: train_loss -0.7806 +2024-11-22 01:43:57.436053: val_loss -0.7316 +2024-11-22 01:43:57.437331: Pseudo dice [0.8279] +2024-11-22 01:43:57.437428: Epoch time: 18.66 s +2024-11-22 01:43:58.315235: +2024-11-22 01:43:58.315425: Epoch 2766 +2024-11-22 01:43:58.315566: Current learning rate: 0.00683 +2024-11-22 01:44:17.448176: train_loss -0.7807 +2024-11-22 01:44:17.448398: val_loss -0.7247 +2024-11-22 01:44:17.448474: Pseudo dice [0.8642] +2024-11-22 01:44:17.448548: Epoch time: 19.13 s +2024-11-22 01:44:18.297452: +2024-11-22 01:44:18.297660: Epoch 2767 +2024-11-22 01:44:18.297769: Current learning rate: 0.00682 +2024-11-22 01:44:36.899070: train_loss -0.7863 +2024-11-22 01:44:36.899328: val_loss -0.7425 +2024-11-22 01:44:36.899404: Pseudo dice [0.8431] +2024-11-22 01:44:36.899488: Epoch time: 18.6 s +2024-11-22 01:44:37.758028: +2024-11-22 01:44:37.758335: Epoch 2768 +2024-11-22 01:44:37.758449: Current learning rate: 0.00682 +2024-11-22 01:44:56.632696: train_loss -0.7653 +2024-11-22 01:44:56.632916: val_loss -0.7041 +2024-11-22 01:44:56.633000: Pseudo dice [0.8392] +2024-11-22 01:44:56.633077: Epoch time: 18.88 s +2024-11-22 01:44:57.483498: +2024-11-22 01:44:57.483719: Epoch 2769 +2024-11-22 01:44:57.483835: Current learning rate: 0.00682 +2024-11-22 01:45:15.782520: train_loss -0.7765 +2024-11-22 01:45:15.782744: val_loss -0.7579 +2024-11-22 01:45:15.782821: Pseudo dice [0.8208] +2024-11-22 01:45:15.782894: Epoch time: 18.3 s +2024-11-22 01:45:16.645758: +2024-11-22 01:45:16.645974: Epoch 2770 +2024-11-22 01:45:16.646094: Current learning rate: 0.00682 +2024-11-22 01:45:35.042465: train_loss -0.7657 +2024-11-22 01:45:35.042687: val_loss -0.7116 +2024-11-22 01:45:35.044976: Pseudo dice [0.7962] +2024-11-22 01:45:35.045077: Epoch time: 18.4 s +2024-11-22 01:45:36.368182: +2024-11-22 01:45:36.368387: Epoch 2771 +2024-11-22 01:45:36.368501: Current learning rate: 0.00682 +2024-11-22 01:45:55.407298: train_loss -0.7801 +2024-11-22 01:45:55.407559: val_loss -0.7222 +2024-11-22 01:45:55.407637: Pseudo dice [0.8508] +2024-11-22 01:45:55.407723: Epoch time: 19.04 s +2024-11-22 01:45:56.262060: +2024-11-22 01:45:56.262266: Epoch 2772 +2024-11-22 01:45:56.262378: Current learning rate: 0.00682 +2024-11-22 01:46:13.913595: train_loss -0.7712 +2024-11-22 01:46:13.913828: val_loss -0.7287 +2024-11-22 01:46:13.913905: Pseudo dice [0.8372] +2024-11-22 01:46:13.913983: Epoch time: 17.65 s +2024-11-22 01:46:14.766588: +2024-11-22 01:46:14.766821: Epoch 2773 +2024-11-22 01:46:14.766934: Current learning rate: 0.00682 +2024-11-22 01:46:33.488281: train_loss -0.7764 +2024-11-22 01:46:33.489089: val_loss -0.743 +2024-11-22 01:46:33.489194: Pseudo dice [0.8519] +2024-11-22 01:46:33.489280: Epoch time: 18.72 s +2024-11-22 01:46:34.343343: +2024-11-22 01:46:34.343672: Epoch 2774 +2024-11-22 01:46:34.343786: Current learning rate: 0.00682 +2024-11-22 01:46:52.929672: train_loss -0.782 +2024-11-22 01:46:52.929917: val_loss -0.6842 +2024-11-22 01:46:52.929999: Pseudo dice [0.8226] +2024-11-22 01:46:52.930082: Epoch time: 18.59 s +2024-11-22 01:46:53.782855: +2024-11-22 01:46:53.783102: Epoch 2775 +2024-11-22 01:46:53.783213: Current learning rate: 0.00682 +2024-11-22 01:47:12.064933: train_loss -0.7674 +2024-11-22 01:47:12.065153: val_loss -0.7242 +2024-11-22 01:47:12.065228: Pseudo dice [0.8447] +2024-11-22 01:47:12.065301: Epoch time: 18.28 s +2024-11-22 01:47:12.919290: +2024-11-22 01:47:12.919596: Epoch 2776 +2024-11-22 01:47:12.919714: Current learning rate: 0.00681 +2024-11-22 01:47:32.304332: train_loss -0.774 +2024-11-22 01:47:32.304559: val_loss -0.7176 +2024-11-22 01:47:32.309797: Pseudo dice [0.845] +2024-11-22 01:47:32.309972: Epoch time: 19.39 s +2024-11-22 01:47:33.267732: +2024-11-22 01:47:33.268044: Epoch 2777 +2024-11-22 01:47:33.268158: Current learning rate: 0.00681 +2024-11-22 01:47:52.331339: train_loss -0.7843 +2024-11-22 01:47:52.331568: val_loss -0.7161 +2024-11-22 01:47:52.331644: Pseudo dice [0.8352] +2024-11-22 01:47:52.331724: Epoch time: 19.06 s +2024-11-22 01:47:53.191382: +2024-11-22 01:47:53.191609: Epoch 2778 +2024-11-22 01:47:53.191736: Current learning rate: 0.00681 +2024-11-22 01:48:11.575080: train_loss -0.7863 +2024-11-22 01:48:11.575341: val_loss -0.7597 +2024-11-22 01:48:11.575420: Pseudo dice [0.8302] +2024-11-22 01:48:11.575508: Epoch time: 18.38 s +2024-11-22 01:48:12.434204: +2024-11-22 01:48:12.434434: Epoch 2779 +2024-11-22 01:48:12.434551: Current learning rate: 0.00681 +2024-11-22 01:48:31.468410: train_loss -0.779 +2024-11-22 01:48:31.468628: val_loss -0.744 +2024-11-22 01:48:31.468709: Pseudo dice [0.8495] +2024-11-22 01:48:31.468789: Epoch time: 19.04 s +2024-11-22 01:48:32.321499: +2024-11-22 01:48:32.321717: Epoch 2780 +2024-11-22 01:48:32.321830: Current learning rate: 0.00681 +2024-11-22 01:48:51.765603: train_loss -0.7872 +2024-11-22 01:48:51.765826: val_loss -0.7396 +2024-11-22 01:48:51.765903: Pseudo dice [0.8477] +2024-11-22 01:48:51.766049: Epoch time: 19.44 s +2024-11-22 01:48:52.637983: +2024-11-22 01:48:52.638256: Epoch 2781 +2024-11-22 01:48:52.638367: Current learning rate: 0.00681 +2024-11-22 01:49:12.008029: train_loss -0.7847 +2024-11-22 01:49:12.008244: val_loss -0.7335 +2024-11-22 01:49:12.008317: Pseudo dice [0.8441] +2024-11-22 01:49:12.008401: Epoch time: 19.37 s +2024-11-22 01:49:12.899242: +2024-11-22 01:49:12.899483: Epoch 2782 +2024-11-22 01:49:12.899593: Current learning rate: 0.00681 +2024-11-22 01:49:30.560029: train_loss -0.7872 +2024-11-22 01:49:30.560295: val_loss -0.7324 +2024-11-22 01:49:30.560370: Pseudo dice [0.8459] +2024-11-22 01:49:30.560450: Epoch time: 17.66 s +2024-11-22 01:49:31.844228: +2024-11-22 01:49:31.844440: Epoch 2783 +2024-11-22 01:49:31.844553: Current learning rate: 0.00681 +2024-11-22 01:49:49.994804: train_loss -0.7822 +2024-11-22 01:49:49.995036: val_loss -0.7463 +2024-11-22 01:49:49.995149: Pseudo dice [0.8356] +2024-11-22 01:49:49.995227: Epoch time: 18.15 s +2024-11-22 01:49:50.850378: +2024-11-22 01:49:50.850621: Epoch 2784 +2024-11-22 01:49:50.850741: Current learning rate: 0.0068 +2024-11-22 01:50:09.745827: train_loss -0.7779 +2024-11-22 01:50:09.746055: val_loss -0.7384 +2024-11-22 01:50:09.746131: Pseudo dice [0.8479] +2024-11-22 01:50:09.746212: Epoch time: 18.9 s +2024-11-22 01:50:10.603428: +2024-11-22 01:50:10.603663: Epoch 2785 +2024-11-22 01:50:10.603775: Current learning rate: 0.0068 +2024-11-22 01:50:28.883682: train_loss -0.7864 +2024-11-22 01:50:28.883922: val_loss -0.7428 +2024-11-22 01:50:28.884047: Pseudo dice [0.8575] +2024-11-22 01:50:28.884136: Epoch time: 18.28 s +2024-11-22 01:50:29.737565: +2024-11-22 01:50:29.737767: Epoch 2786 +2024-11-22 01:50:29.737879: Current learning rate: 0.0068 +2024-11-22 01:50:47.961075: train_loss -0.788 +2024-11-22 01:50:47.961296: val_loss -0.7462 +2024-11-22 01:50:47.961379: Pseudo dice [0.841] +2024-11-22 01:50:47.961457: Epoch time: 18.22 s +2024-11-22 01:50:49.073535: +2024-11-22 01:50:49.073882: Epoch 2787 +2024-11-22 01:50:49.073997: Current learning rate: 0.0068 +2024-11-22 01:51:08.329305: train_loss -0.7828 +2024-11-22 01:51:08.329531: val_loss -0.7362 +2024-11-22 01:51:08.329627: Pseudo dice [0.8184] +2024-11-22 01:51:08.329765: Epoch time: 19.26 s +2024-11-22 01:51:09.189960: +2024-11-22 01:51:09.190178: Epoch 2788 +2024-11-22 01:51:09.190297: Current learning rate: 0.0068 +2024-11-22 01:51:27.683482: train_loss -0.7899 +2024-11-22 01:51:27.683716: val_loss -0.726 +2024-11-22 01:51:27.683792: Pseudo dice [0.8447] +2024-11-22 01:51:27.683872: Epoch time: 18.49 s +2024-11-22 01:51:28.538398: +2024-11-22 01:51:28.538680: Epoch 2789 +2024-11-22 01:51:28.538799: Current learning rate: 0.0068 +2024-11-22 01:51:47.734016: train_loss -0.7892 +2024-11-22 01:51:47.734336: val_loss -0.7429 +2024-11-22 01:51:47.734420: Pseudo dice [0.8555] +2024-11-22 01:51:47.734505: Epoch time: 19.2 s +2024-11-22 01:51:48.591774: +2024-11-22 01:51:48.591979: Epoch 2790 +2024-11-22 01:51:48.592097: Current learning rate: 0.0068 +2024-11-22 01:52:06.349125: train_loss -0.7818 +2024-11-22 01:52:06.349355: val_loss -0.7307 +2024-11-22 01:52:06.349489: Pseudo dice [0.8137] +2024-11-22 01:52:06.349569: Epoch time: 17.76 s +2024-11-22 01:52:07.202556: +2024-11-22 01:52:07.202923: Epoch 2791 +2024-11-22 01:52:07.203043: Current learning rate: 0.0068 +2024-11-22 01:52:25.966097: train_loss -0.7686 +2024-11-22 01:52:25.966323: val_loss -0.7519 +2024-11-22 01:52:25.966405: Pseudo dice [0.848] +2024-11-22 01:52:25.966485: Epoch time: 18.76 s +2024-11-22 01:52:26.818569: +2024-11-22 01:52:26.818789: Epoch 2792 +2024-11-22 01:52:26.818905: Current learning rate: 0.0068 +2024-11-22 01:52:45.718009: train_loss -0.7715 +2024-11-22 01:52:45.718265: val_loss -0.7267 +2024-11-22 01:52:45.718343: Pseudo dice [0.8217] +2024-11-22 01:52:45.718428: Epoch time: 18.9 s +2024-11-22 01:52:46.583551: +2024-11-22 01:52:46.583806: Epoch 2793 +2024-11-22 01:52:46.583921: Current learning rate: 0.00679 +2024-11-22 01:53:04.855344: train_loss -0.7829 +2024-11-22 01:53:04.855564: val_loss -0.7405 +2024-11-22 01:53:04.855641: Pseudo dice [0.8325] +2024-11-22 01:53:04.855718: Epoch time: 18.27 s +2024-11-22 01:53:05.705626: +2024-11-22 01:53:05.705876: Epoch 2794 +2024-11-22 01:53:05.705987: Current learning rate: 0.00679 +2024-11-22 01:53:23.622585: train_loss -0.7798 +2024-11-22 01:53:23.622811: val_loss -0.7351 +2024-11-22 01:53:23.622892: Pseudo dice [0.831] +2024-11-22 01:53:23.622972: Epoch time: 17.92 s +2024-11-22 01:53:24.898664: +2024-11-22 01:53:24.899120: Epoch 2795 +2024-11-22 01:53:24.899256: Current learning rate: 0.00679 +2024-11-22 01:53:44.293142: train_loss -0.7842 +2024-11-22 01:53:44.293462: val_loss -0.7499 +2024-11-22 01:53:44.293539: Pseudo dice [0.8412] +2024-11-22 01:53:44.293624: Epoch time: 19.4 s +2024-11-22 01:53:45.152312: +2024-11-22 01:53:45.152797: Epoch 2796 +2024-11-22 01:53:45.152931: Current learning rate: 0.00679 +2024-11-22 01:54:03.870129: train_loss -0.7796 +2024-11-22 01:54:03.870357: val_loss -0.7355 +2024-11-22 01:54:03.870434: Pseudo dice [0.8471] +2024-11-22 01:54:03.870516: Epoch time: 18.72 s +2024-11-22 01:54:04.726712: +2024-11-22 01:54:04.727157: Epoch 2797 +2024-11-22 01:54:04.727287: Current learning rate: 0.00679 +2024-11-22 01:54:22.268163: train_loss -0.767 +2024-11-22 01:54:22.268385: val_loss -0.7546 +2024-11-22 01:54:22.268459: Pseudo dice [0.8623] +2024-11-22 01:54:22.268536: Epoch time: 17.54 s +2024-11-22 01:54:23.147258: +2024-11-22 01:54:23.147747: Epoch 2798 +2024-11-22 01:54:23.147896: Current learning rate: 0.00679 +2024-11-22 01:54:41.832398: train_loss -0.7597 +2024-11-22 01:54:41.832656: val_loss -0.7427 +2024-11-22 01:54:41.832737: Pseudo dice [0.8474] +2024-11-22 01:54:41.832825: Epoch time: 18.69 s +2024-11-22 01:54:42.758551: +2024-11-22 01:54:42.758971: Epoch 2799 +2024-11-22 01:54:42.759111: Current learning rate: 0.00679 +2024-11-22 01:55:00.809042: train_loss -0.7652 +2024-11-22 01:55:00.809264: val_loss -0.7258 +2024-11-22 01:55:00.809338: Pseudo dice [0.8446] +2024-11-22 01:55:00.809413: Epoch time: 18.05 s +2024-11-22 01:55:01.909551: +2024-11-22 01:55:01.910042: Epoch 2800 +2024-11-22 01:55:01.910175: Current learning rate: 0.00679 +2024-11-22 01:55:21.539382: train_loss -0.7575 +2024-11-22 01:55:21.539606: val_loss -0.7561 +2024-11-22 01:55:21.539683: Pseudo dice [0.8424] +2024-11-22 01:55:21.539757: Epoch time: 19.63 s +2024-11-22 01:55:22.393712: +2024-11-22 01:55:22.394169: Epoch 2801 +2024-11-22 01:55:22.394303: Current learning rate: 0.00678 +2024-11-22 01:55:41.091754: train_loss -0.7627 +2024-11-22 01:55:41.091975: val_loss -0.7249 +2024-11-22 01:55:41.092061: Pseudo dice [0.8286] +2024-11-22 01:55:41.092141: Epoch time: 18.7 s +2024-11-22 01:55:41.955347: +2024-11-22 01:55:41.955839: Epoch 2802 +2024-11-22 01:55:41.956003: Current learning rate: 0.00678 +2024-11-22 01:56:01.549315: train_loss -0.7677 +2024-11-22 01:56:01.549560: val_loss -0.7644 +2024-11-22 01:56:01.549639: Pseudo dice [0.8389] +2024-11-22 01:56:01.549719: Epoch time: 19.6 s +2024-11-22 01:56:02.401725: +2024-11-22 01:56:02.402283: Epoch 2803 +2024-11-22 01:56:02.402420: Current learning rate: 0.00678 +2024-11-22 01:56:21.665590: train_loss -0.7794 +2024-11-22 01:56:21.665785: val_loss -0.7214 +2024-11-22 01:56:21.665859: Pseudo dice [0.8404] +2024-11-22 01:56:21.665935: Epoch time: 19.26 s +2024-11-22 01:56:22.530462: +2024-11-22 01:56:22.530899: Epoch 2804 +2024-11-22 01:56:22.531046: Current learning rate: 0.00678 +2024-11-22 01:56:40.456662: train_loss -0.7735 +2024-11-22 01:56:40.456882: val_loss -0.737 +2024-11-22 01:56:40.456955: Pseudo dice [0.8488] +2024-11-22 01:56:40.457041: Epoch time: 17.93 s +2024-11-22 01:56:41.312208: +2024-11-22 01:56:41.312408: Epoch 2805 +2024-11-22 01:56:41.312517: Current learning rate: 0.00678 +2024-11-22 01:56:59.277799: train_loss -0.7714 +2024-11-22 01:56:59.283243: val_loss -0.7495 +2024-11-22 01:56:59.283336: Pseudo dice [0.8368] +2024-11-22 01:56:59.283427: Epoch time: 17.97 s +2024-11-22 01:57:00.251958: +2024-11-22 01:57:00.252212: Epoch 2806 +2024-11-22 01:57:00.252328: Current learning rate: 0.00678 +2024-11-22 01:57:18.877048: train_loss -0.7794 +2024-11-22 01:57:18.877293: val_loss -0.7391 +2024-11-22 01:57:18.877372: Pseudo dice [0.8283] +2024-11-22 01:57:18.877451: Epoch time: 18.63 s +2024-11-22 01:57:19.728956: +2024-11-22 01:57:19.729303: Epoch 2807 +2024-11-22 01:57:19.729426: Current learning rate: 0.00678 +2024-11-22 01:57:38.850229: train_loss -0.776 +2024-11-22 01:57:38.850456: val_loss -0.741 +2024-11-22 01:57:38.850535: Pseudo dice [0.8552] +2024-11-22 01:57:38.850618: Epoch time: 19.12 s +2024-11-22 01:57:39.706038: +2024-11-22 01:57:39.706248: Epoch 2808 +2024-11-22 01:57:39.706358: Current learning rate: 0.00678 +2024-11-22 01:57:58.629041: train_loss -0.7824 +2024-11-22 01:57:58.634436: val_loss -0.7352 +2024-11-22 01:57:58.634526: Pseudo dice [0.8224] +2024-11-22 01:57:58.634610: Epoch time: 18.92 s +2024-11-22 01:57:59.539664: +2024-11-22 01:57:59.539932: Epoch 2809 +2024-11-22 01:57:59.540054: Current learning rate: 0.00678 +2024-11-22 01:58:19.422842: train_loss -0.7803 +2024-11-22 01:58:19.423063: val_loss -0.7512 +2024-11-22 01:58:19.423138: Pseudo dice [0.8335] +2024-11-22 01:58:19.423214: Epoch time: 19.88 s +2024-11-22 01:58:20.276602: +2024-11-22 01:58:20.276812: Epoch 2810 +2024-11-22 01:58:20.276934: Current learning rate: 0.00677 +2024-11-22 01:58:39.356179: train_loss -0.7845 +2024-11-22 01:58:39.356396: val_loss -0.7122 +2024-11-22 01:58:39.356472: Pseudo dice [0.7955] +2024-11-22 01:58:39.356561: Epoch time: 19.08 s +2024-11-22 01:58:40.238884: +2024-11-22 01:58:40.239119: Epoch 2811 +2024-11-22 01:58:40.239231: Current learning rate: 0.00677 +2024-11-22 01:58:59.737896: train_loss -0.7765 +2024-11-22 01:58:59.738122: val_loss -0.7356 +2024-11-22 01:58:59.738198: Pseudo dice [0.8366] +2024-11-22 01:58:59.738273: Epoch time: 19.5 s +2024-11-22 01:59:00.697587: +2024-11-22 01:59:00.697801: Epoch 2812 +2024-11-22 01:59:00.697916: Current learning rate: 0.00677 +2024-11-22 01:59:19.837931: train_loss -0.7889 +2024-11-22 01:59:19.838158: val_loss -0.7615 +2024-11-22 01:59:19.838238: Pseudo dice [0.8287] +2024-11-22 01:59:19.838317: Epoch time: 19.14 s +2024-11-22 01:59:20.695740: +2024-11-22 01:59:20.695955: Epoch 2813 +2024-11-22 01:59:20.696074: Current learning rate: 0.00677 +2024-11-22 01:59:39.823709: train_loss -0.781 +2024-11-22 01:59:39.824037: val_loss -0.7621 +2024-11-22 01:59:39.824131: Pseudo dice [0.8443] +2024-11-22 01:59:39.824217: Epoch time: 19.13 s +2024-11-22 01:59:40.684713: +2024-11-22 01:59:40.685008: Epoch 2814 +2024-11-22 01:59:40.685117: Current learning rate: 0.00677 +2024-11-22 01:59:59.676485: train_loss -0.7827 +2024-11-22 01:59:59.676707: val_loss -0.7399 +2024-11-22 01:59:59.679096: Pseudo dice [0.8248] +2024-11-22 01:59:59.679225: Epoch time: 18.99 s +2024-11-22 02:00:00.568367: +2024-11-22 02:00:00.568595: Epoch 2815 +2024-11-22 02:00:00.568709: Current learning rate: 0.00677 +2024-11-22 02:00:19.553971: train_loss -0.7766 +2024-11-22 02:00:19.554202: val_loss -0.7351 +2024-11-22 02:00:19.554282: Pseudo dice [0.8294] +2024-11-22 02:00:19.554359: Epoch time: 18.99 s +2024-11-22 02:00:20.611069: +2024-11-22 02:00:20.611282: Epoch 2816 +2024-11-22 02:00:20.611567: Current learning rate: 0.00677 +2024-11-22 02:00:38.930959: train_loss -0.767 +2024-11-22 02:00:38.931224: val_loss -0.7554 +2024-11-22 02:00:38.931299: Pseudo dice [0.854] +2024-11-22 02:00:38.931384: Epoch time: 18.32 s +2024-11-22 02:00:39.796439: +2024-11-22 02:00:39.796707: Epoch 2817 +2024-11-22 02:00:39.796823: Current learning rate: 0.00677 +2024-11-22 02:00:58.786163: train_loss -0.7821 +2024-11-22 02:00:58.789044: val_loss -0.7458 +2024-11-22 02:00:58.789136: Pseudo dice [0.8371] +2024-11-22 02:00:58.789215: Epoch time: 18.99 s +2024-11-22 02:01:00.392787: +2024-11-22 02:01:00.393004: Epoch 2818 +2024-11-22 02:01:00.393114: Current learning rate: 0.00676 +2024-11-22 02:01:19.765522: train_loss -0.7718 +2024-11-22 02:01:19.765751: val_loss -0.7568 +2024-11-22 02:01:19.765826: Pseudo dice [0.8316] +2024-11-22 02:01:19.765904: Epoch time: 19.37 s +2024-11-22 02:01:20.625124: +2024-11-22 02:01:20.625338: Epoch 2819 +2024-11-22 02:01:20.625453: Current learning rate: 0.00676 +2024-11-22 02:01:38.418356: train_loss -0.7572 +2024-11-22 02:01:38.418604: val_loss -0.7165 +2024-11-22 02:01:38.418685: Pseudo dice [0.837] +2024-11-22 02:01:38.418768: Epoch time: 17.79 s +2024-11-22 02:01:39.274406: +2024-11-22 02:01:39.274643: Epoch 2820 +2024-11-22 02:01:39.274754: Current learning rate: 0.00676 +2024-11-22 02:01:58.296010: train_loss -0.7678 +2024-11-22 02:01:58.296225: val_loss -0.7387 +2024-11-22 02:01:58.296301: Pseudo dice [0.8094] +2024-11-22 02:01:58.296447: Epoch time: 19.02 s +2024-11-22 02:01:59.162266: +2024-11-22 02:01:59.162480: Epoch 2821 +2024-11-22 02:01:59.162597: Current learning rate: 0.00676 +2024-11-22 02:02:17.385977: train_loss -0.764 +2024-11-22 02:02:17.386193: val_loss -0.7106 +2024-11-22 02:02:17.386285: Pseudo dice [0.8221] +2024-11-22 02:02:17.386361: Epoch time: 18.22 s +2024-11-22 02:02:18.244881: +2024-11-22 02:02:18.245092: Epoch 2822 +2024-11-22 02:02:18.245208: Current learning rate: 0.00676 +2024-11-22 02:02:36.898143: train_loss -0.7594 +2024-11-22 02:02:36.898376: val_loss -0.736 +2024-11-22 02:02:36.898452: Pseudo dice [0.7946] +2024-11-22 02:02:36.898531: Epoch time: 18.65 s +2024-11-22 02:02:37.752395: +2024-11-22 02:02:37.752652: Epoch 2823 +2024-11-22 02:02:37.752769: Current learning rate: 0.00676 +2024-11-22 02:02:56.087721: train_loss -0.7694 +2024-11-22 02:02:56.087965: val_loss -0.756 +2024-11-22 02:02:56.088048: Pseudo dice [0.8449] +2024-11-22 02:02:56.088132: Epoch time: 18.34 s +2024-11-22 02:02:56.944227: +2024-11-22 02:02:56.944468: Epoch 2824 +2024-11-22 02:02:56.944581: Current learning rate: 0.00676 +2024-11-22 02:03:15.591155: train_loss -0.7779 +2024-11-22 02:03:15.591372: val_loss -0.6917 +2024-11-22 02:03:15.591446: Pseudo dice [0.8288] +2024-11-22 02:03:15.593979: Epoch time: 18.65 s +2024-11-22 02:03:16.451303: +2024-11-22 02:03:16.451495: Epoch 2825 +2024-11-22 02:03:16.451605: Current learning rate: 0.00676 +2024-11-22 02:03:35.059907: train_loss -0.7823 +2024-11-22 02:03:35.060196: val_loss -0.7344 +2024-11-22 02:03:35.060276: Pseudo dice [0.863] +2024-11-22 02:03:35.060357: Epoch time: 18.61 s +2024-11-22 02:03:35.916175: +2024-11-22 02:03:35.916381: Epoch 2826 +2024-11-22 02:03:35.916502: Current learning rate: 0.00676 +2024-11-22 02:03:54.550578: train_loss -0.785 +2024-11-22 02:03:54.550795: val_loss -0.7234 +2024-11-22 02:03:54.553125: Pseudo dice [0.8163] +2024-11-22 02:03:54.553235: Epoch time: 18.64 s +2024-11-22 02:03:55.420477: +2024-11-22 02:03:55.420688: Epoch 2827 +2024-11-22 02:03:55.420799: Current learning rate: 0.00675 +2024-11-22 02:04:13.965580: train_loss -0.7844 +2024-11-22 02:04:13.965841: val_loss -0.7297 +2024-11-22 02:04:13.965939: Pseudo dice [0.8277] +2024-11-22 02:04:13.966039: Epoch time: 18.55 s +2024-11-22 02:04:14.818642: +2024-11-22 02:04:14.818872: Epoch 2828 +2024-11-22 02:04:14.819000: Current learning rate: 0.00675 +2024-11-22 02:04:32.867248: train_loss -0.7722 +2024-11-22 02:04:32.867482: val_loss -0.7554 +2024-11-22 02:04:32.867562: Pseudo dice [0.8482] +2024-11-22 02:04:32.867642: Epoch time: 18.05 s +2024-11-22 02:04:33.717973: +2024-11-22 02:04:33.718166: Epoch 2829 +2024-11-22 02:04:33.718276: Current learning rate: 0.00675 +2024-11-22 02:04:52.415591: train_loss -0.7782 +2024-11-22 02:04:52.415869: val_loss -0.7209 +2024-11-22 02:04:52.415949: Pseudo dice [0.8358] +2024-11-22 02:04:52.416090: Epoch time: 18.7 s +2024-11-22 02:04:53.696916: +2024-11-22 02:04:53.697132: Epoch 2830 +2024-11-22 02:04:53.697243: Current learning rate: 0.00675 +2024-11-22 02:05:11.813284: train_loss -0.771 +2024-11-22 02:05:11.815728: val_loss -0.7397 +2024-11-22 02:05:11.815852: Pseudo dice [0.8545] +2024-11-22 02:05:11.815937: Epoch time: 18.12 s +2024-11-22 02:05:12.686217: +2024-11-22 02:05:12.686509: Epoch 2831 +2024-11-22 02:05:12.686621: Current learning rate: 0.00675 +2024-11-22 02:05:32.442900: train_loss -0.7827 +2024-11-22 02:05:32.443132: val_loss -0.7145 +2024-11-22 02:05:32.443210: Pseudo dice [0.8113] +2024-11-22 02:05:32.443286: Epoch time: 19.76 s +2024-11-22 02:05:33.294350: +2024-11-22 02:05:33.294618: Epoch 2832 +2024-11-22 02:05:33.294729: Current learning rate: 0.00675 +2024-11-22 02:05:52.368369: train_loss -0.7827 +2024-11-22 02:05:52.368575: val_loss -0.7359 +2024-11-22 02:05:52.368688: Pseudo dice [0.8437] +2024-11-22 02:05:52.368770: Epoch time: 19.07 s +2024-11-22 02:05:53.255869: +2024-11-22 02:05:53.256082: Epoch 2833 +2024-11-22 02:05:53.256196: Current learning rate: 0.00675 +2024-11-22 02:06:11.650211: train_loss -0.786 +2024-11-22 02:06:11.650461: val_loss -0.7442 +2024-11-22 02:06:11.650539: Pseudo dice [0.8483] +2024-11-22 02:06:11.650629: Epoch time: 18.4 s +2024-11-22 02:06:12.541225: +2024-11-22 02:06:12.541426: Epoch 2834 +2024-11-22 02:06:12.541538: Current learning rate: 0.00675 +2024-11-22 02:06:31.028918: train_loss -0.7681 +2024-11-22 02:06:31.029225: val_loss -0.7306 +2024-11-22 02:06:31.029306: Pseudo dice [0.8374] +2024-11-22 02:06:31.029385: Epoch time: 18.49 s +2024-11-22 02:06:31.893741: +2024-11-22 02:06:31.894004: Epoch 2835 +2024-11-22 02:06:31.894120: Current learning rate: 0.00675 +2024-11-22 02:06:49.719153: train_loss -0.7748 +2024-11-22 02:06:49.719373: val_loss -0.7426 +2024-11-22 02:06:49.719460: Pseudo dice [0.8529] +2024-11-22 02:06:49.719541: Epoch time: 17.83 s +2024-11-22 02:06:50.642665: +2024-11-22 02:06:50.642868: Epoch 2836 +2024-11-22 02:06:50.642997: Current learning rate: 0.00674 +2024-11-22 02:07:08.774706: train_loss -0.7826 +2024-11-22 02:07:08.774930: val_loss -0.7574 +2024-11-22 02:07:08.775011: Pseudo dice [0.8306] +2024-11-22 02:07:08.775088: Epoch time: 18.13 s +2024-11-22 02:07:09.627784: +2024-11-22 02:07:09.627998: Epoch 2837 +2024-11-22 02:07:09.628114: Current learning rate: 0.00674 +2024-11-22 02:07:29.123363: train_loss -0.772 +2024-11-22 02:07:29.123616: val_loss -0.7579 +2024-11-22 02:07:29.123692: Pseudo dice [0.8471] +2024-11-22 02:07:29.123804: Epoch time: 19.5 s +2024-11-22 02:07:30.003243: +2024-11-22 02:07:30.003455: Epoch 2838 +2024-11-22 02:07:30.003565: Current learning rate: 0.00674 +2024-11-22 02:07:48.742140: train_loss -0.7755 +2024-11-22 02:07:48.742364: val_loss -0.7571 +2024-11-22 02:07:48.742460: Pseudo dice [0.8372] +2024-11-22 02:07:48.742544: Epoch time: 18.74 s +2024-11-22 02:07:49.599336: +2024-11-22 02:07:49.599593: Epoch 2839 +2024-11-22 02:07:49.599746: Current learning rate: 0.00674 +2024-11-22 02:08:08.566399: train_loss -0.7788 +2024-11-22 02:08:08.566619: val_loss -0.7203 +2024-11-22 02:08:08.566697: Pseudo dice [0.8405] +2024-11-22 02:08:08.566776: Epoch time: 18.97 s +2024-11-22 02:08:09.424860: +2024-11-22 02:08:09.425293: Epoch 2840 +2024-11-22 02:08:09.425423: Current learning rate: 0.00674 +2024-11-22 02:08:27.594032: train_loss -0.7692 +2024-11-22 02:08:27.594256: val_loss -0.7257 +2024-11-22 02:08:27.594334: Pseudo dice [0.8595] +2024-11-22 02:08:27.594413: Epoch time: 18.17 s +2024-11-22 02:08:28.452045: +2024-11-22 02:08:28.452229: Epoch 2841 +2024-11-22 02:08:28.452339: Current learning rate: 0.00674 +2024-11-22 02:08:46.157492: train_loss -0.7845 +2024-11-22 02:08:46.157755: val_loss -0.7617 +2024-11-22 02:08:46.157831: Pseudo dice [0.8427] +2024-11-22 02:08:46.157919: Epoch time: 17.71 s +2024-11-22 02:08:47.431228: +2024-11-22 02:08:47.431560: Epoch 2842 +2024-11-22 02:08:47.431745: Current learning rate: 0.00674 +2024-11-22 02:09:05.342266: train_loss -0.7807 +2024-11-22 02:09:05.342525: val_loss -0.761 +2024-11-22 02:09:05.344851: Pseudo dice [0.8401] +2024-11-22 02:09:05.344945: Epoch time: 17.91 s +2024-11-22 02:09:06.393518: +2024-11-22 02:09:06.393731: Epoch 2843 +2024-11-22 02:09:06.393844: Current learning rate: 0.00674 +2024-11-22 02:09:26.020162: train_loss -0.7777 +2024-11-22 02:09:26.020473: val_loss -0.734 +2024-11-22 02:09:26.020551: Pseudo dice [0.8297] +2024-11-22 02:09:26.020635: Epoch time: 19.63 s +2024-11-22 02:09:26.875172: +2024-11-22 02:09:26.875462: Epoch 2844 +2024-11-22 02:09:26.875575: Current learning rate: 0.00673 +2024-11-22 02:09:45.071472: train_loss -0.7788 +2024-11-22 02:09:45.071686: val_loss -0.7421 +2024-11-22 02:09:45.071861: Pseudo dice [0.8119] +2024-11-22 02:09:45.071945: Epoch time: 18.2 s +2024-11-22 02:09:45.924786: +2024-11-22 02:09:45.925000: Epoch 2845 +2024-11-22 02:09:45.925114: Current learning rate: 0.00673 +2024-11-22 02:10:05.121227: train_loss -0.7824 +2024-11-22 02:10:05.132510: val_loss -0.7566 +2024-11-22 02:10:05.132624: Pseudo dice [0.8474] +2024-11-22 02:10:05.132715: Epoch time: 19.2 s +2024-11-22 02:10:06.032857: +2024-11-22 02:10:06.033060: Epoch 2846 +2024-11-22 02:10:06.033169: Current learning rate: 0.00673 +2024-11-22 02:10:25.649574: train_loss -0.7854 +2024-11-22 02:10:25.649793: val_loss -0.7097 +2024-11-22 02:10:25.649869: Pseudo dice [0.8121] +2024-11-22 02:10:25.649944: Epoch time: 19.62 s +2024-11-22 02:10:26.509741: +2024-11-22 02:10:26.509939: Epoch 2847 +2024-11-22 02:10:26.510060: Current learning rate: 0.00673 +2024-11-22 02:10:45.676106: train_loss -0.7852 +2024-11-22 02:10:45.676329: val_loss -0.731 +2024-11-22 02:10:45.676404: Pseudo dice [0.8294] +2024-11-22 02:10:45.676486: Epoch time: 19.17 s +2024-11-22 02:10:46.536420: +2024-11-22 02:10:46.536685: Epoch 2848 +2024-11-22 02:10:46.536799: Current learning rate: 0.00673 +2024-11-22 02:11:06.622772: train_loss -0.7892 +2024-11-22 02:11:06.623027: val_loss -0.7617 +2024-11-22 02:11:06.623105: Pseudo dice [0.8552] +2024-11-22 02:11:06.623185: Epoch time: 20.09 s +2024-11-22 02:11:07.480458: +2024-11-22 02:11:07.480696: Epoch 2849 +2024-11-22 02:11:07.480817: Current learning rate: 0.00673 +2024-11-22 02:11:25.924643: train_loss -0.7809 +2024-11-22 02:11:25.924851: val_loss -0.7668 +2024-11-22 02:11:25.924948: Pseudo dice [0.8453] +2024-11-22 02:11:25.925059: Epoch time: 18.45 s +2024-11-22 02:11:27.012537: +2024-11-22 02:11:27.012763: Epoch 2850 +2024-11-22 02:11:27.012881: Current learning rate: 0.00673 +2024-11-22 02:11:46.197820: train_loss -0.7846 +2024-11-22 02:11:46.198049: val_loss -0.7606 +2024-11-22 02:11:46.198129: Pseudo dice [0.8616] +2024-11-22 02:11:46.198205: Epoch time: 19.19 s +2024-11-22 02:11:47.053981: +2024-11-22 02:11:47.054222: Epoch 2851 +2024-11-22 02:11:47.054334: Current learning rate: 0.00673 +2024-11-22 02:12:05.617061: train_loss -0.7909 +2024-11-22 02:12:05.619485: val_loss -0.7491 +2024-11-22 02:12:05.619581: Pseudo dice [0.8596] +2024-11-22 02:12:05.619664: Epoch time: 18.56 s +2024-11-22 02:12:06.685720: +2024-11-22 02:12:06.685930: Epoch 2852 +2024-11-22 02:12:06.686046: Current learning rate: 0.00673 +2024-11-22 02:12:25.290897: train_loss -0.7912 +2024-11-22 02:12:25.291124: val_loss -0.7403 +2024-11-22 02:12:25.291204: Pseudo dice [0.8526] +2024-11-22 02:12:25.291283: Epoch time: 18.61 s +2024-11-22 02:12:26.144659: +2024-11-22 02:12:26.144898: Epoch 2853 +2024-11-22 02:12:26.145018: Current learning rate: 0.00672 +2024-11-22 02:12:45.417595: train_loss -0.7798 +2024-11-22 02:12:45.417838: val_loss -0.7641 +2024-11-22 02:12:45.417915: Pseudo dice [0.8488] +2024-11-22 02:12:45.418035: Epoch time: 19.27 s +2024-11-22 02:12:46.268308: +2024-11-22 02:12:46.268627: Epoch 2854 +2024-11-22 02:12:46.268778: Current learning rate: 0.00672 +2024-11-22 02:13:04.605782: train_loss -0.7768 +2024-11-22 02:13:04.606016: val_loss -0.7653 +2024-11-22 02:13:04.606092: Pseudo dice [0.8263] +2024-11-22 02:13:04.606170: Epoch time: 18.34 s +2024-11-22 02:13:05.518550: +2024-11-22 02:13:05.519166: Epoch 2855 +2024-11-22 02:13:05.519299: Current learning rate: 0.00672 +2024-11-22 02:13:24.339161: train_loss -0.7823 +2024-11-22 02:13:24.339382: val_loss -0.7427 +2024-11-22 02:13:24.339458: Pseudo dice [0.8336] +2024-11-22 02:13:24.339535: Epoch time: 18.82 s +2024-11-22 02:13:25.199665: +2024-11-22 02:13:25.200115: Epoch 2856 +2024-11-22 02:13:25.200259: Current learning rate: 0.00672 +2024-11-22 02:13:45.467954: train_loss -0.7884 +2024-11-22 02:13:45.468176: val_loss -0.7382 +2024-11-22 02:13:45.468260: Pseudo dice [0.8423] +2024-11-22 02:13:45.468337: Epoch time: 20.27 s +2024-11-22 02:13:46.326028: +2024-11-22 02:13:46.326465: Epoch 2857 +2024-11-22 02:13:46.326602: Current learning rate: 0.00672 +2024-11-22 02:14:05.064346: train_loss -0.7917 +2024-11-22 02:14:05.064595: val_loss -0.7718 +2024-11-22 02:14:05.064674: Pseudo dice [0.847] +2024-11-22 02:14:05.064834: Epoch time: 18.74 s +2024-11-22 02:14:05.921372: +2024-11-22 02:14:05.921870: Epoch 2858 +2024-11-22 02:14:05.922000: Current learning rate: 0.00672 +2024-11-22 02:14:23.782193: train_loss -0.7913 +2024-11-22 02:14:23.782405: val_loss -0.7128 +2024-11-22 02:14:23.782480: Pseudo dice [0.8097] +2024-11-22 02:14:23.782557: Epoch time: 17.86 s +2024-11-22 02:14:24.642740: +2024-11-22 02:14:24.643169: Epoch 2859 +2024-11-22 02:14:24.643328: Current learning rate: 0.00672 +2024-11-22 02:14:43.392167: train_loss -0.7835 +2024-11-22 02:14:43.397578: val_loss -0.7294 +2024-11-22 02:14:43.397695: Pseudo dice [0.849] +2024-11-22 02:14:43.397779: Epoch time: 18.75 s +2024-11-22 02:14:44.411507: +2024-11-22 02:14:44.411957: Epoch 2860 +2024-11-22 02:14:44.412097: Current learning rate: 0.00672 +2024-11-22 02:15:02.985460: train_loss -0.7717 +2024-11-22 02:15:02.985676: val_loss -0.7489 +2024-11-22 02:15:02.985751: Pseudo dice [0.856] +2024-11-22 02:15:02.985831: Epoch time: 18.57 s +2024-11-22 02:15:03.841063: +2024-11-22 02:15:03.841463: Epoch 2861 +2024-11-22 02:15:03.841593: Current learning rate: 0.00671 +2024-11-22 02:15:23.308523: train_loss -0.7773 +2024-11-22 02:15:23.308770: val_loss -0.7066 +2024-11-22 02:15:23.308848: Pseudo dice [0.8211] +2024-11-22 02:15:23.308928: Epoch time: 19.47 s +2024-11-22 02:15:24.198987: +2024-11-22 02:15:24.199488: Epoch 2862 +2024-11-22 02:15:24.199620: Current learning rate: 0.00671 +2024-11-22 02:15:42.769203: train_loss -0.7826 +2024-11-22 02:15:42.769424: val_loss -0.7611 +2024-11-22 02:15:42.769499: Pseudo dice [0.8433] +2024-11-22 02:15:42.769590: Epoch time: 18.57 s +2024-11-22 02:15:43.628653: +2024-11-22 02:15:43.629073: Epoch 2863 +2024-11-22 02:15:43.629206: Current learning rate: 0.00671 +2024-11-22 02:16:02.328968: train_loss -0.7844 +2024-11-22 02:16:02.329209: val_loss -0.7383 +2024-11-22 02:16:02.329285: Pseudo dice [0.8535] +2024-11-22 02:16:02.329361: Epoch time: 18.7 s +2024-11-22 02:16:03.309207: +2024-11-22 02:16:03.309611: Epoch 2864 +2024-11-22 02:16:03.309751: Current learning rate: 0.00671 +2024-11-22 02:16:21.556886: train_loss -0.7869 +2024-11-22 02:16:21.562371: val_loss -0.7469 +2024-11-22 02:16:21.562491: Pseudo dice [0.8434] +2024-11-22 02:16:21.562583: Epoch time: 18.25 s +2024-11-22 02:16:22.844256: +2024-11-22 02:16:22.844681: Epoch 2865 +2024-11-22 02:16:22.844810: Current learning rate: 0.00671 +2024-11-22 02:16:41.503423: train_loss -0.7859 +2024-11-22 02:16:41.503667: val_loss -0.7584 +2024-11-22 02:16:41.503743: Pseudo dice [0.8628] +2024-11-22 02:16:41.503822: Epoch time: 18.66 s +2024-11-22 02:16:42.383737: +2024-11-22 02:16:42.384195: Epoch 2866 +2024-11-22 02:16:42.384338: Current learning rate: 0.00671 +2024-11-22 02:17:01.898690: train_loss -0.7796 +2024-11-22 02:17:01.898933: val_loss -0.7711 +2024-11-22 02:17:01.899013: Pseudo dice [0.8443] +2024-11-22 02:17:01.899089: Epoch time: 19.52 s +2024-11-22 02:17:02.764855: +2024-11-22 02:17:02.765277: Epoch 2867 +2024-11-22 02:17:02.765409: Current learning rate: 0.00671 +2024-11-22 02:17:22.340268: train_loss -0.786 +2024-11-22 02:17:22.340536: val_loss -0.7383 +2024-11-22 02:17:22.340614: Pseudo dice [0.8424] +2024-11-22 02:17:22.340701: Epoch time: 19.58 s +2024-11-22 02:17:23.254734: +2024-11-22 02:17:23.255422: Epoch 2868 +2024-11-22 02:17:23.255568: Current learning rate: 0.00671 +2024-11-22 02:17:40.760152: train_loss -0.7873 +2024-11-22 02:17:40.760384: val_loss -0.7447 +2024-11-22 02:17:40.760469: Pseudo dice [0.8492] +2024-11-22 02:17:40.760545: Epoch time: 17.51 s +2024-11-22 02:17:41.623315: +2024-11-22 02:17:41.623798: Epoch 2869 +2024-11-22 02:17:41.623938: Current learning rate: 0.00671 +2024-11-22 02:18:00.450284: train_loss -0.7862 +2024-11-22 02:18:00.450499: val_loss -0.7487 +2024-11-22 02:18:00.450575: Pseudo dice [0.8321] +2024-11-22 02:18:00.450652: Epoch time: 18.83 s +2024-11-22 02:18:01.314733: +2024-11-22 02:18:01.315145: Epoch 2870 +2024-11-22 02:18:01.315279: Current learning rate: 0.0067 +2024-11-22 02:18:20.063457: train_loss -0.7756 +2024-11-22 02:18:20.063688: val_loss -0.7111 +2024-11-22 02:18:20.063767: Pseudo dice [0.8108] +2024-11-22 02:18:20.063845: Epoch time: 18.75 s +2024-11-22 02:18:20.927957: +2024-11-22 02:18:20.928635: Epoch 2871 +2024-11-22 02:18:20.928771: Current learning rate: 0.0067 +2024-11-22 02:18:39.501074: train_loss -0.7763 +2024-11-22 02:18:39.501298: val_loss -0.7425 +2024-11-22 02:18:39.501373: Pseudo dice [0.8406] +2024-11-22 02:18:39.501454: Epoch time: 18.57 s +2024-11-22 02:18:40.366563: +2024-11-22 02:18:40.367023: Epoch 2872 +2024-11-22 02:18:40.367159: Current learning rate: 0.0067 +2024-11-22 02:18:57.667763: train_loss -0.7804 +2024-11-22 02:18:57.668049: val_loss -0.7495 +2024-11-22 02:18:57.668128: Pseudo dice [0.8523] +2024-11-22 02:18:57.668204: Epoch time: 17.3 s +2024-11-22 02:18:58.598065: +2024-11-22 02:18:58.598523: Epoch 2873 +2024-11-22 02:18:58.598660: Current learning rate: 0.0067 +2024-11-22 02:19:15.634717: train_loss -0.7817 +2024-11-22 02:19:15.634937: val_loss -0.7302 +2024-11-22 02:19:15.635022: Pseudo dice [0.8295] +2024-11-22 02:19:15.635167: Epoch time: 17.04 s +2024-11-22 02:19:16.518986: +2024-11-22 02:19:16.519450: Epoch 2874 +2024-11-22 02:19:16.519589: Current learning rate: 0.0067 +2024-11-22 02:19:35.937535: train_loss -0.7797 +2024-11-22 02:19:35.937756: val_loss -0.7394 +2024-11-22 02:19:35.937832: Pseudo dice [0.8113] +2024-11-22 02:19:35.937911: Epoch time: 19.42 s +2024-11-22 02:19:36.797360: +2024-11-22 02:19:36.797751: Epoch 2875 +2024-11-22 02:19:36.797882: Current learning rate: 0.0067 +2024-11-22 02:19:55.635426: train_loss -0.7827 +2024-11-22 02:19:55.635672: val_loss -0.769 +2024-11-22 02:19:55.635754: Pseudo dice [0.8519] +2024-11-22 02:19:55.635833: Epoch time: 18.84 s +2024-11-22 02:19:56.494117: +2024-11-22 02:19:56.494318: Epoch 2876 +2024-11-22 02:19:56.494430: Current learning rate: 0.0067 +2024-11-22 02:20:16.045171: train_loss -0.7731 +2024-11-22 02:20:16.045411: val_loss -0.7546 +2024-11-22 02:20:16.045489: Pseudo dice [0.8339] +2024-11-22 02:20:16.045565: Epoch time: 19.55 s +2024-11-22 02:20:16.902220: +2024-11-22 02:20:16.902627: Epoch 2877 +2024-11-22 02:20:16.902759: Current learning rate: 0.0067 +2024-11-22 02:20:35.050032: train_loss -0.7813 +2024-11-22 02:20:35.050256: val_loss -0.7582 +2024-11-22 02:20:35.050334: Pseudo dice [0.8512] +2024-11-22 02:20:35.050411: Epoch time: 18.15 s +2024-11-22 02:20:36.015410: +2024-11-22 02:20:36.015841: Epoch 2878 +2024-11-22 02:20:36.015976: Current learning rate: 0.00669 +2024-11-22 02:20:54.385386: train_loss -0.7777 +2024-11-22 02:20:54.385720: val_loss -0.7245 +2024-11-22 02:20:54.385798: Pseudo dice [0.8509] +2024-11-22 02:20:54.385879: Epoch time: 18.37 s +2024-11-22 02:20:55.249702: +2024-11-22 02:20:55.250138: Epoch 2879 +2024-11-22 02:20:55.250269: Current learning rate: 0.00669 +2024-11-22 02:21:14.476400: train_loss -0.7839 +2024-11-22 02:21:14.476611: val_loss -0.727 +2024-11-22 02:21:14.476682: Pseudo dice [0.8422] +2024-11-22 02:21:14.476757: Epoch time: 19.23 s +2024-11-22 02:21:15.341100: +2024-11-22 02:21:15.341532: Epoch 2880 +2024-11-22 02:21:15.341674: Current learning rate: 0.00669 +2024-11-22 02:21:33.617319: train_loss -0.7799 +2024-11-22 02:21:33.617592: val_loss -0.7535 +2024-11-22 02:21:33.617672: Pseudo dice [0.8455] +2024-11-22 02:21:33.617748: Epoch time: 18.28 s +2024-11-22 02:21:34.486582: +2024-11-22 02:21:34.486987: Epoch 2881 +2024-11-22 02:21:34.487121: Current learning rate: 0.00669 +2024-11-22 02:21:53.107626: train_loss -0.7813 +2024-11-22 02:21:53.107888: val_loss -0.7255 +2024-11-22 02:21:53.107970: Pseudo dice [0.8255] +2024-11-22 02:21:53.108061: Epoch time: 18.62 s +2024-11-22 02:21:53.982202: +2024-11-22 02:21:53.982611: Epoch 2882 +2024-11-22 02:21:53.982747: Current learning rate: 0.00669 +2024-11-22 02:22:12.444366: train_loss -0.7886 +2024-11-22 02:22:12.444650: val_loss -0.751 +2024-11-22 02:22:12.444723: Pseudo dice [0.8485] +2024-11-22 02:22:12.444803: Epoch time: 18.46 s +2024-11-22 02:22:13.314466: +2024-11-22 02:22:13.314901: Epoch 2883 +2024-11-22 02:22:13.315040: Current learning rate: 0.00669 +2024-11-22 02:22:32.416441: train_loss -0.7873 +2024-11-22 02:22:32.416755: val_loss -0.751 +2024-11-22 02:22:32.416832: Pseudo dice [0.845] +2024-11-22 02:22:32.416909: Epoch time: 19.1 s +2024-11-22 02:22:33.275911: +2024-11-22 02:22:33.276327: Epoch 2884 +2024-11-22 02:22:33.276466: Current learning rate: 0.00669 +2024-11-22 02:22:51.730610: train_loss -0.789 +2024-11-22 02:22:51.730834: val_loss -0.7548 +2024-11-22 02:22:51.730913: Pseudo dice [0.8442] +2024-11-22 02:22:51.730999: Epoch time: 18.46 s +2024-11-22 02:22:52.587833: +2024-11-22 02:22:52.588361: Epoch 2885 +2024-11-22 02:22:52.588510: Current learning rate: 0.00669 +2024-11-22 02:23:11.729004: train_loss -0.7797 +2024-11-22 02:23:11.729261: val_loss -0.7621 +2024-11-22 02:23:11.729339: Pseudo dice [0.8576] +2024-11-22 02:23:11.729422: Epoch time: 19.14 s +2024-11-22 02:23:12.600091: +2024-11-22 02:23:12.600495: Epoch 2886 +2024-11-22 02:23:12.600627: Current learning rate: 0.00669 +2024-11-22 02:23:31.310115: train_loss -0.7837 +2024-11-22 02:23:31.310330: val_loss -0.7377 +2024-11-22 02:23:31.310403: Pseudo dice [0.8595] +2024-11-22 02:23:31.310477: Epoch time: 18.71 s +2024-11-22 02:23:31.310539: Yayy! New best EMA pseudo Dice: 0.8445 +2024-11-22 02:23:32.414459: +2024-11-22 02:23:32.414919: Epoch 2887 +2024-11-22 02:23:32.415065: Current learning rate: 0.00668 +2024-11-22 02:23:51.361540: train_loss -0.7885 +2024-11-22 02:23:51.361792: val_loss -0.7161 +2024-11-22 02:23:51.361872: Pseudo dice [0.8142] +2024-11-22 02:23:51.361951: Epoch time: 18.95 s +2024-11-22 02:23:52.440147: +2024-11-22 02:23:52.440575: Epoch 2888 +2024-11-22 02:23:52.440712: Current learning rate: 0.00668 +2024-11-22 02:24:10.645996: train_loss -0.7902 +2024-11-22 02:24:10.646243: val_loss -0.7595 +2024-11-22 02:24:10.646319: Pseudo dice [0.8357] +2024-11-22 02:24:10.646401: Epoch time: 18.21 s +2024-11-22 02:24:11.503982: +2024-11-22 02:24:11.504403: Epoch 2889 +2024-11-22 02:24:11.504539: Current learning rate: 0.00668 +2024-11-22 02:24:30.270424: train_loss -0.7815 +2024-11-22 02:24:30.270658: val_loss -0.7495 +2024-11-22 02:24:30.270778: Pseudo dice [0.8247] +2024-11-22 02:24:30.270860: Epoch time: 18.77 s +2024-11-22 02:24:31.131284: +2024-11-22 02:24:31.131699: Epoch 2890 +2024-11-22 02:24:31.131834: Current learning rate: 0.00668 +2024-11-22 02:24:49.476764: train_loss -0.7871 +2024-11-22 02:24:49.476980: val_loss -0.7514 +2024-11-22 02:24:49.477066: Pseudo dice [0.8439] +2024-11-22 02:24:49.477146: Epoch time: 18.35 s +2024-11-22 02:24:50.340179: +2024-11-22 02:24:50.340638: Epoch 2891 +2024-11-22 02:24:50.340773: Current learning rate: 0.00668 +2024-11-22 02:25:09.634752: train_loss -0.7779 +2024-11-22 02:25:09.635024: val_loss -0.7538 +2024-11-22 02:25:09.635110: Pseudo dice [0.8392] +2024-11-22 02:25:09.635201: Epoch time: 19.3 s +2024-11-22 02:25:10.498163: +2024-11-22 02:25:10.498616: Epoch 2892 +2024-11-22 02:25:10.498751: Current learning rate: 0.00668 +2024-11-22 02:25:29.533592: train_loss -0.7844 +2024-11-22 02:25:29.533815: val_loss -0.7419 +2024-11-22 02:25:29.533889: Pseudo dice [0.8603] +2024-11-22 02:25:29.533964: Epoch time: 19.04 s +2024-11-22 02:25:30.586134: +2024-11-22 02:25:30.586557: Epoch 2893 +2024-11-22 02:25:30.586689: Current learning rate: 0.00668 +2024-11-22 02:25:49.574789: train_loss -0.7834 +2024-11-22 02:25:49.575015: val_loss -0.7334 +2024-11-22 02:25:49.575094: Pseudo dice [0.8335] +2024-11-22 02:25:49.575998: Epoch time: 18.99 s +2024-11-22 02:25:50.436546: +2024-11-22 02:25:50.437028: Epoch 2894 +2024-11-22 02:25:50.437164: Current learning rate: 0.00668 +2024-11-22 02:26:08.977914: train_loss -0.7797 +2024-11-22 02:26:08.978139: val_loss -0.7403 +2024-11-22 02:26:08.978213: Pseudo dice [0.844] +2024-11-22 02:26:08.978290: Epoch time: 18.54 s +2024-11-22 02:26:09.884132: +2024-11-22 02:26:09.884572: Epoch 2895 +2024-11-22 02:26:09.884705: Current learning rate: 0.00667 +2024-11-22 02:26:27.721761: train_loss -0.7809 +2024-11-22 02:26:27.722022: val_loss -0.7491 +2024-11-22 02:26:27.722102: Pseudo dice [0.8471] +2024-11-22 02:26:27.722184: Epoch time: 17.84 s +2024-11-22 02:26:28.710189: +2024-11-22 02:26:28.710754: Epoch 2896 +2024-11-22 02:26:28.710890: Current learning rate: 0.00667 +2024-11-22 02:26:48.977974: train_loss -0.7732 +2024-11-22 02:26:48.979110: val_loss -0.7668 +2024-11-22 02:26:48.979206: Pseudo dice [0.8209] +2024-11-22 02:26:48.979296: Epoch time: 20.27 s +2024-11-22 02:26:49.890320: +2024-11-22 02:26:49.890721: Epoch 2897 +2024-11-22 02:26:49.890849: Current learning rate: 0.00667 +2024-11-22 02:27:09.796217: train_loss -0.7808 +2024-11-22 02:27:09.796441: val_loss -0.7466 +2024-11-22 02:27:09.796515: Pseudo dice [0.8358] +2024-11-22 02:27:09.796591: Epoch time: 19.91 s +2024-11-22 02:27:10.663431: +2024-11-22 02:27:10.663915: Epoch 2898 +2024-11-22 02:27:10.664057: Current learning rate: 0.00667 +2024-11-22 02:27:28.494455: train_loss -0.7744 +2024-11-22 02:27:28.494704: val_loss -0.7278 +2024-11-22 02:27:28.494780: Pseudo dice [0.7962] +2024-11-22 02:27:28.494866: Epoch time: 17.83 s +2024-11-22 02:27:29.716321: +2024-11-22 02:27:29.716745: Epoch 2899 +2024-11-22 02:27:29.716878: Current learning rate: 0.00667 +2024-11-22 02:27:48.656003: train_loss -0.7702 +2024-11-22 02:27:48.656240: val_loss -0.7203 +2024-11-22 02:27:48.656319: Pseudo dice [0.8292] +2024-11-22 02:27:48.656398: Epoch time: 18.94 s +2024-11-22 02:27:49.746593: +2024-11-22 02:27:49.747096: Epoch 2900 +2024-11-22 02:27:49.747231: Current learning rate: 0.00667 +2024-11-22 02:28:08.485862: train_loss -0.7749 +2024-11-22 02:28:08.486087: val_loss -0.7321 +2024-11-22 02:28:08.486164: Pseudo dice [0.8116] +2024-11-22 02:28:08.486241: Epoch time: 18.74 s +2024-11-22 02:28:09.344231: +2024-11-22 02:28:09.344667: Epoch 2901 +2024-11-22 02:28:09.344804: Current learning rate: 0.00667 +2024-11-22 02:28:27.635468: train_loss -0.7938 +2024-11-22 02:28:27.639188: val_loss -0.7588 +2024-11-22 02:28:27.639277: Pseudo dice [0.8507] +2024-11-22 02:28:27.639364: Epoch time: 18.29 s +2024-11-22 02:28:28.536831: +2024-11-22 02:28:28.537306: Epoch 2902 +2024-11-22 02:28:28.537446: Current learning rate: 0.00667 +2024-11-22 02:28:46.545425: train_loss -0.7828 +2024-11-22 02:28:46.545636: val_loss -0.7267 +2024-11-22 02:28:46.545709: Pseudo dice [0.8395] +2024-11-22 02:28:46.545787: Epoch time: 18.01 s +2024-11-22 02:28:47.408076: +2024-11-22 02:28:47.408490: Epoch 2903 +2024-11-22 02:28:47.408625: Current learning rate: 0.00667 +2024-11-22 02:29:07.512577: train_loss -0.7716 +2024-11-22 02:29:07.512793: val_loss -0.7147 +2024-11-22 02:29:07.512868: Pseudo dice [0.8394] +2024-11-22 02:29:07.512946: Epoch time: 20.11 s +2024-11-22 02:29:08.376343: +2024-11-22 02:29:08.376785: Epoch 2904 +2024-11-22 02:29:08.376927: Current learning rate: 0.00666 +2024-11-22 02:29:27.151100: train_loss -0.7852 +2024-11-22 02:29:27.151320: val_loss -0.7388 +2024-11-22 02:29:27.151396: Pseudo dice [0.8324] +2024-11-22 02:29:27.151472: Epoch time: 18.78 s +2024-11-22 02:29:28.013175: +2024-11-22 02:29:28.013645: Epoch 2905 +2024-11-22 02:29:28.013779: Current learning rate: 0.00666 +2024-11-22 02:29:46.400289: train_loss -0.7739 +2024-11-22 02:29:46.400537: val_loss -0.7323 +2024-11-22 02:29:46.400611: Pseudo dice [0.848] +2024-11-22 02:29:46.402889: Epoch time: 18.39 s +2024-11-22 02:29:47.393453: +2024-11-22 02:29:47.393882: Epoch 2906 +2024-11-22 02:29:47.394024: Current learning rate: 0.00666 +2024-11-22 02:30:05.738796: train_loss -0.7857 +2024-11-22 02:30:05.739044: val_loss -0.739 +2024-11-22 02:30:05.739123: Pseudo dice [0.8558] +2024-11-22 02:30:05.739203: Epoch time: 18.35 s +2024-11-22 02:30:06.602973: +2024-11-22 02:30:06.603402: Epoch 2907 +2024-11-22 02:30:06.603540: Current learning rate: 0.00666 +2024-11-22 02:30:26.092102: train_loss -0.7765 +2024-11-22 02:30:26.092332: val_loss -0.7661 +2024-11-22 02:30:26.092409: Pseudo dice [0.822] +2024-11-22 02:30:26.092492: Epoch time: 19.49 s +2024-11-22 02:30:26.957643: +2024-11-22 02:30:26.958067: Epoch 2908 +2024-11-22 02:30:26.958249: Current learning rate: 0.00666 +2024-11-22 02:30:44.974848: train_loss -0.7842 +2024-11-22 02:30:44.975074: val_loss -0.744 +2024-11-22 02:30:44.975150: Pseudo dice [0.8501] +2024-11-22 02:30:44.975226: Epoch time: 18.02 s +2024-11-22 02:30:45.840605: +2024-11-22 02:30:45.841059: Epoch 2909 +2024-11-22 02:30:45.841203: Current learning rate: 0.00666 +2024-11-22 02:31:04.012395: train_loss -0.7793 +2024-11-22 02:31:04.013297: val_loss -0.7301 +2024-11-22 02:31:04.013376: Pseudo dice [0.8506] +2024-11-22 02:31:04.013460: Epoch time: 18.17 s +2024-11-22 02:31:05.283096: +2024-11-22 02:31:05.283295: Epoch 2910 +2024-11-22 02:31:05.283406: Current learning rate: 0.00666 +2024-11-22 02:31:24.752320: train_loss -0.7875 +2024-11-22 02:31:24.752559: val_loss -0.7617 +2024-11-22 02:31:24.752636: Pseudo dice [0.8517] +2024-11-22 02:31:24.752711: Epoch time: 19.47 s +2024-11-22 02:31:25.718988: +2024-11-22 02:31:25.719413: Epoch 2911 +2024-11-22 02:31:25.719549: Current learning rate: 0.00666 +2024-11-22 02:31:45.309659: train_loss -0.7812 +2024-11-22 02:31:45.309877: val_loss -0.7287 +2024-11-22 02:31:45.309951: Pseudo dice [0.8279] +2024-11-22 02:31:45.310029: Epoch time: 19.59 s +2024-11-22 02:31:46.261211: +2024-11-22 02:31:46.261642: Epoch 2912 +2024-11-22 02:31:46.261773: Current learning rate: 0.00665 +2024-11-22 02:32:04.888775: train_loss -0.7749 +2024-11-22 02:32:04.889038: val_loss -0.7296 +2024-11-22 02:32:04.889125: Pseudo dice [0.8285] +2024-11-22 02:32:04.889277: Epoch time: 18.63 s +2024-11-22 02:32:05.757792: +2024-11-22 02:32:05.758237: Epoch 2913 +2024-11-22 02:32:05.758369: Current learning rate: 0.00665 +2024-11-22 02:32:23.975469: train_loss -0.7852 +2024-11-22 02:32:23.975693: val_loss -0.7424 +2024-11-22 02:32:23.975773: Pseudo dice [0.8297] +2024-11-22 02:32:23.975854: Epoch time: 18.22 s +2024-11-22 02:32:24.842428: +2024-11-22 02:32:24.842837: Epoch 2914 +2024-11-22 02:32:24.842971: Current learning rate: 0.00665 +2024-11-22 02:32:42.367420: train_loss -0.7854 +2024-11-22 02:32:42.367640: val_loss -0.7461 +2024-11-22 02:32:42.367719: Pseudo dice [0.847] +2024-11-22 02:32:42.367798: Epoch time: 17.53 s +2024-11-22 02:32:43.233427: +2024-11-22 02:32:43.233871: Epoch 2915 +2024-11-22 02:32:43.234011: Current learning rate: 0.00665 +2024-11-22 02:33:01.453445: train_loss -0.7894 +2024-11-22 02:33:01.454258: val_loss -0.7443 +2024-11-22 02:33:01.454355: Pseudo dice [0.8315] +2024-11-22 02:33:01.454436: Epoch time: 18.22 s +2024-11-22 02:33:02.335591: +2024-11-22 02:33:02.336036: Epoch 2916 +2024-11-22 02:33:02.336174: Current learning rate: 0.00665 +2024-11-22 02:33:20.439484: train_loss -0.7825 +2024-11-22 02:33:20.439740: val_loss -0.7484 +2024-11-22 02:33:20.439816: Pseudo dice [0.8508] +2024-11-22 02:33:20.439899: Epoch time: 18.1 s +2024-11-22 02:33:21.394638: +2024-11-22 02:33:21.395070: Epoch 2917 +2024-11-22 02:33:21.395203: Current learning rate: 0.00665 +2024-11-22 02:33:40.518190: train_loss -0.7838 +2024-11-22 02:33:40.519007: val_loss -0.7701 +2024-11-22 02:33:40.519090: Pseudo dice [0.8431] +2024-11-22 02:33:40.519167: Epoch time: 19.12 s +2024-11-22 02:33:41.579570: +2024-11-22 02:33:41.579986: Epoch 2918 +2024-11-22 02:33:41.580128: Current learning rate: 0.00665 +2024-11-22 02:34:00.468500: train_loss -0.7882 +2024-11-22 02:34:00.468728: val_loss -0.7396 +2024-11-22 02:34:00.468805: Pseudo dice [0.8423] +2024-11-22 02:34:00.468882: Epoch time: 18.89 s +2024-11-22 02:34:01.364605: +2024-11-22 02:34:01.365134: Epoch 2919 +2024-11-22 02:34:01.365274: Current learning rate: 0.00665 +2024-11-22 02:34:19.253867: train_loss -0.7903 +2024-11-22 02:34:19.254104: val_loss -0.7313 +2024-11-22 02:34:19.254432: Pseudo dice [0.8564] +2024-11-22 02:34:19.254521: Epoch time: 17.89 s +2024-11-22 02:34:20.116651: +2024-11-22 02:34:20.117086: Epoch 2920 +2024-11-22 02:34:20.117222: Current learning rate: 0.00665 +2024-11-22 02:34:38.753649: train_loss -0.7901 +2024-11-22 02:34:38.753882: val_loss -0.7477 +2024-11-22 02:34:38.753959: Pseudo dice [0.8424] +2024-11-22 02:34:38.754045: Epoch time: 18.64 s +2024-11-22 02:34:39.647364: +2024-11-22 02:34:39.647840: Epoch 2921 +2024-11-22 02:34:39.647969: Current learning rate: 0.00664 +2024-11-22 02:34:58.142798: train_loss -0.7815 +2024-11-22 02:34:58.143155: val_loss -0.7327 +2024-11-22 02:34:58.143240: Pseudo dice [0.8318] +2024-11-22 02:34:58.143321: Epoch time: 18.5 s +2024-11-22 02:34:59.419325: +2024-11-22 02:34:59.419768: Epoch 2922 +2024-11-22 02:34:59.419904: Current learning rate: 0.00664 +2024-11-22 02:35:18.143599: train_loss -0.7833 +2024-11-22 02:35:18.143876: val_loss -0.7664 +2024-11-22 02:35:18.143953: Pseudo dice [0.8387] +2024-11-22 02:35:18.144051: Epoch time: 18.73 s +2024-11-22 02:35:19.389143: +2024-11-22 02:35:19.389696: Epoch 2923 +2024-11-22 02:35:19.389833: Current learning rate: 0.00664 +2024-11-22 02:35:38.129002: train_loss -0.7913 +2024-11-22 02:35:38.129388: val_loss -0.7448 +2024-11-22 02:35:38.129483: Pseudo dice [0.8497] +2024-11-22 02:35:38.129563: Epoch time: 18.74 s +2024-11-22 02:35:38.994393: +2024-11-22 02:35:38.994843: Epoch 2924 +2024-11-22 02:35:38.994978: Current learning rate: 0.00664 +2024-11-22 02:35:56.240140: train_loss -0.7835 +2024-11-22 02:35:56.240353: val_loss -0.7699 +2024-11-22 02:35:56.240431: Pseudo dice [0.8347] +2024-11-22 02:35:56.240510: Epoch time: 17.25 s +2024-11-22 02:35:57.116718: +2024-11-22 02:35:57.117140: Epoch 2925 +2024-11-22 02:35:57.117278: Current learning rate: 0.00664 +2024-11-22 02:36:15.250989: train_loss -0.7809 +2024-11-22 02:36:15.251260: val_loss -0.7916 +2024-11-22 02:36:15.251338: Pseudo dice [0.8697] +2024-11-22 02:36:15.251422: Epoch time: 18.14 s +2024-11-22 02:36:16.123877: +2024-11-22 02:36:16.124319: Epoch 2926 +2024-11-22 02:36:16.126172: Current learning rate: 0.00664 +2024-11-22 02:36:35.172343: train_loss -0.787 +2024-11-22 02:36:35.172570: val_loss -0.7265 +2024-11-22 02:36:35.172646: Pseudo dice [0.8482] +2024-11-22 02:36:35.172765: Epoch time: 19.05 s +2024-11-22 02:36:36.030821: +2024-11-22 02:36:36.031242: Epoch 2927 +2024-11-22 02:36:36.031377: Current learning rate: 0.00664 +2024-11-22 02:36:54.362005: train_loss -0.789 +2024-11-22 02:36:54.362247: val_loss -0.7443 +2024-11-22 02:36:54.362329: Pseudo dice [0.8437] +2024-11-22 02:36:54.362455: Epoch time: 18.33 s +2024-11-22 02:36:55.244955: +2024-11-22 02:36:55.245399: Epoch 2928 +2024-11-22 02:36:55.245536: Current learning rate: 0.00664 +2024-11-22 02:37:13.953156: train_loss -0.7818 +2024-11-22 02:37:13.953384: val_loss -0.7367 +2024-11-22 02:37:13.953464: Pseudo dice [0.8438] +2024-11-22 02:37:13.953543: Epoch time: 18.71 s +2024-11-22 02:37:14.835250: +2024-11-22 02:37:14.835707: Epoch 2929 +2024-11-22 02:37:14.835846: Current learning rate: 0.00663 +2024-11-22 02:37:32.178687: train_loss -0.7909 +2024-11-22 02:37:32.178931: val_loss -0.7397 +2024-11-22 02:37:32.179015: Pseudo dice [0.8254] +2024-11-22 02:37:32.179160: Epoch time: 17.34 s +2024-11-22 02:37:33.056733: +2024-11-22 02:37:33.057187: Epoch 2930 +2024-11-22 02:37:33.057319: Current learning rate: 0.00663 +2024-11-22 02:37:51.495279: train_loss -0.7903 +2024-11-22 02:37:51.495525: val_loss -0.7662 +2024-11-22 02:37:51.495606: Pseudo dice [0.8484] +2024-11-22 02:37:51.495689: Epoch time: 18.44 s +2024-11-22 02:37:52.357574: +2024-11-22 02:37:52.357997: Epoch 2931 +2024-11-22 02:37:52.358132: Current learning rate: 0.00663 +2024-11-22 02:38:12.287478: train_loss -0.7829 +2024-11-22 02:38:12.287701: val_loss -0.7464 +2024-11-22 02:38:12.287780: Pseudo dice [0.8322] +2024-11-22 02:38:12.287863: Epoch time: 19.93 s +2024-11-22 02:38:13.157901: +2024-11-22 02:38:13.158309: Epoch 2932 +2024-11-22 02:38:13.158437: Current learning rate: 0.00663 +2024-11-22 02:38:32.061289: train_loss -0.7813 +2024-11-22 02:38:32.061518: val_loss -0.7588 +2024-11-22 02:38:32.061602: Pseudo dice [0.8522] +2024-11-22 02:38:32.061685: Epoch time: 18.9 s +2024-11-22 02:38:32.921380: +2024-11-22 02:38:32.921807: Epoch 2933 +2024-11-22 02:38:32.921939: Current learning rate: 0.00663 +2024-11-22 02:38:51.749959: train_loss -0.7836 +2024-11-22 02:38:51.750206: val_loss -0.7277 +2024-11-22 02:38:51.750281: Pseudo dice [0.8305] +2024-11-22 02:38:51.750357: Epoch time: 18.83 s +2024-11-22 02:38:52.610264: +2024-11-22 02:38:52.610707: Epoch 2934 +2024-11-22 02:38:52.610842: Current learning rate: 0.00663 +2024-11-22 02:39:11.010041: train_loss -0.7861 +2024-11-22 02:39:11.010270: val_loss -0.7395 +2024-11-22 02:39:11.010352: Pseudo dice [0.8552] +2024-11-22 02:39:11.010429: Epoch time: 18.4 s +2024-11-22 02:39:11.912767: +2024-11-22 02:39:11.913256: Epoch 2935 +2024-11-22 02:39:11.913393: Current learning rate: 0.00663 +2024-11-22 02:39:31.202557: train_loss -0.775 +2024-11-22 02:39:31.202850: val_loss -0.7417 +2024-11-22 02:39:31.202929: Pseudo dice [0.8305] +2024-11-22 02:39:31.203011: Epoch time: 19.29 s +2024-11-22 02:39:32.091094: +2024-11-22 02:39:32.091554: Epoch 2936 +2024-11-22 02:39:32.091688: Current learning rate: 0.00663 +2024-11-22 02:39:51.520787: train_loss -0.7754 +2024-11-22 02:39:51.521071: val_loss -0.7447 +2024-11-22 02:39:51.521154: Pseudo dice [0.8461] +2024-11-22 02:39:51.521291: Epoch time: 19.43 s +2024-11-22 02:39:52.392285: +2024-11-22 02:39:52.392710: Epoch 2937 +2024-11-22 02:39:52.392853: Current learning rate: 0.00663 +2024-11-22 02:40:10.855840: train_loss -0.7814 +2024-11-22 02:40:10.856068: val_loss -0.7582 +2024-11-22 02:40:10.856143: Pseudo dice [0.8453] +2024-11-22 02:40:10.856221: Epoch time: 18.46 s +2024-11-22 02:40:11.718978: +2024-11-22 02:40:11.719398: Epoch 2938 +2024-11-22 02:40:11.719532: Current learning rate: 0.00662 +2024-11-22 02:40:30.571717: train_loss -0.7839 +2024-11-22 02:40:30.571946: val_loss -0.7341 +2024-11-22 02:40:30.572030: Pseudo dice [0.8413] +2024-11-22 02:40:30.572109: Epoch time: 18.85 s +2024-11-22 02:40:31.439486: +2024-11-22 02:40:31.439900: Epoch 2939 +2024-11-22 02:40:31.440045: Current learning rate: 0.00662 +2024-11-22 02:40:50.820716: train_loss -0.7898 +2024-11-22 02:40:50.820977: val_loss -0.7273 +2024-11-22 02:40:50.821091: Pseudo dice [0.837] +2024-11-22 02:40:50.821171: Epoch time: 19.38 s +2024-11-22 02:40:51.682559: +2024-11-22 02:40:51.683016: Epoch 2940 +2024-11-22 02:40:51.683160: Current learning rate: 0.00662 +2024-11-22 02:41:10.837602: train_loss -0.7862 +2024-11-22 02:41:10.837822: val_loss -0.7043 +2024-11-22 02:41:10.837897: Pseudo dice [0.8024] +2024-11-22 02:41:10.837981: Epoch time: 19.16 s +2024-11-22 02:41:11.698713: +2024-11-22 02:41:11.699143: Epoch 2941 +2024-11-22 02:41:11.699283: Current learning rate: 0.00662 +2024-11-22 02:41:31.093807: train_loss -0.7765 +2024-11-22 02:41:31.094051: val_loss -0.7445 +2024-11-22 02:41:31.094130: Pseudo dice [0.8353] +2024-11-22 02:41:31.094216: Epoch time: 19.4 s +2024-11-22 02:41:31.957982: +2024-11-22 02:41:31.958401: Epoch 2942 +2024-11-22 02:41:31.958535: Current learning rate: 0.00662 +2024-11-22 02:41:50.146312: train_loss -0.7875 +2024-11-22 02:41:50.146535: val_loss -0.7414 +2024-11-22 02:41:50.146609: Pseudo dice [0.8336] +2024-11-22 02:41:50.146688: Epoch time: 18.19 s +2024-11-22 02:41:51.006159: +2024-11-22 02:41:51.006577: Epoch 2943 +2024-11-22 02:41:51.006706: Current learning rate: 0.00662 +2024-11-22 02:42:09.384123: train_loss -0.7851 +2024-11-22 02:42:09.384355: val_loss -0.7525 +2024-11-22 02:42:09.384430: Pseudo dice [0.8288] +2024-11-22 02:42:09.384507: Epoch time: 18.38 s +2024-11-22 02:42:10.247211: +2024-11-22 02:42:10.247635: Epoch 2944 +2024-11-22 02:42:10.247769: Current learning rate: 0.00662 +2024-11-22 02:42:30.064878: train_loss -0.7879 +2024-11-22 02:42:30.065136: val_loss -0.7727 +2024-11-22 02:42:30.065222: Pseudo dice [0.8502] +2024-11-22 02:42:30.065307: Epoch time: 19.82 s +2024-11-22 02:42:31.335709: +2024-11-22 02:42:31.336111: Epoch 2945 +2024-11-22 02:42:31.336239: Current learning rate: 0.00662 +2024-11-22 02:42:50.964645: train_loss -0.7701 +2024-11-22 02:42:50.967040: val_loss -0.7194 +2024-11-22 02:42:50.967269: Pseudo dice [0.8459] +2024-11-22 02:42:50.967368: Epoch time: 19.63 s +2024-11-22 02:42:51.864002: +2024-11-22 02:42:51.864493: Epoch 2946 +2024-11-22 02:42:51.864640: Current learning rate: 0.00661 +2024-11-22 02:43:10.621639: train_loss -0.7703 +2024-11-22 02:43:10.621858: val_loss -0.7388 +2024-11-22 02:43:10.627113: Pseudo dice [0.8244] +2024-11-22 02:43:10.627302: Epoch time: 18.76 s +2024-11-22 02:43:11.517799: +2024-11-22 02:43:11.518300: Epoch 2947 +2024-11-22 02:43:11.518432: Current learning rate: 0.00661 +2024-11-22 02:43:30.737606: train_loss -0.773 +2024-11-22 02:43:30.737868: val_loss -0.7297 +2024-11-22 02:43:30.737949: Pseudo dice [0.8299] +2024-11-22 02:43:30.738042: Epoch time: 19.22 s +2024-11-22 02:43:31.606582: +2024-11-22 02:43:31.607059: Epoch 2948 +2024-11-22 02:43:31.607198: Current learning rate: 0.00661 +2024-11-22 02:43:49.793786: train_loss -0.7826 +2024-11-22 02:43:49.794013: val_loss -0.7631 +2024-11-22 02:43:49.794088: Pseudo dice [0.8598] +2024-11-22 02:43:49.794167: Epoch time: 18.19 s +2024-11-22 02:43:50.661140: +2024-11-22 02:43:50.661561: Epoch 2949 +2024-11-22 02:43:50.661696: Current learning rate: 0.00661 +2024-11-22 02:44:08.769071: train_loss -0.7951 +2024-11-22 02:44:08.769292: val_loss -0.7122 +2024-11-22 02:44:08.769367: Pseudo dice [0.8211] +2024-11-22 02:44:08.769506: Epoch time: 18.11 s +2024-11-22 02:44:09.878426: +2024-11-22 02:44:09.878871: Epoch 2950 +2024-11-22 02:44:09.879012: Current learning rate: 0.00661 +2024-11-22 02:44:28.142814: train_loss -0.7929 +2024-11-22 02:44:28.143043: val_loss -0.7093 +2024-11-22 02:44:28.143126: Pseudo dice [0.8226] +2024-11-22 02:44:28.143202: Epoch time: 18.27 s +2024-11-22 02:44:29.008176: +2024-11-22 02:44:29.008597: Epoch 2951 +2024-11-22 02:44:29.008731: Current learning rate: 0.00661 +2024-11-22 02:44:49.623987: train_loss -0.7843 +2024-11-22 02:44:49.624282: val_loss -0.7208 +2024-11-22 02:44:49.624361: Pseudo dice [0.8213] +2024-11-22 02:44:49.624443: Epoch time: 20.62 s +2024-11-22 02:44:50.496287: +2024-11-22 02:44:50.496700: Epoch 2952 +2024-11-22 02:44:50.496831: Current learning rate: 0.00661 +2024-11-22 02:45:09.086519: train_loss -0.7873 +2024-11-22 02:45:09.086741: val_loss -0.7693 +2024-11-22 02:45:09.086818: Pseudo dice [0.8458] +2024-11-22 02:45:09.086895: Epoch time: 18.59 s +2024-11-22 02:45:09.951383: +2024-11-22 02:45:09.951781: Epoch 2953 +2024-11-22 02:45:09.951913: Current learning rate: 0.00661 +2024-11-22 02:45:28.611973: train_loss -0.7847 +2024-11-22 02:45:28.612193: val_loss -0.7402 +2024-11-22 02:45:28.612267: Pseudo dice [0.8324] +2024-11-22 02:45:28.612342: Epoch time: 18.66 s +2024-11-22 02:45:29.494297: +2024-11-22 02:45:29.494719: Epoch 2954 +2024-11-22 02:45:29.494850: Current learning rate: 0.0066 +2024-11-22 02:45:48.068748: train_loss -0.7811 +2024-11-22 02:45:48.069001: val_loss -0.7313 +2024-11-22 02:45:48.069080: Pseudo dice [0.8467] +2024-11-22 02:45:48.069164: Epoch time: 18.58 s +2024-11-22 02:45:49.024606: +2024-11-22 02:45:49.025128: Epoch 2955 +2024-11-22 02:45:49.025260: Current learning rate: 0.0066 +2024-11-22 02:46:07.361909: train_loss -0.7765 +2024-11-22 02:46:07.362156: val_loss -0.7158 +2024-11-22 02:46:07.362231: Pseudo dice [0.8445] +2024-11-22 02:46:07.362312: Epoch time: 18.34 s +2024-11-22 02:46:08.620177: +2024-11-22 02:46:08.620377: Epoch 2956 +2024-11-22 02:46:08.620487: Current learning rate: 0.0066 +2024-11-22 02:46:27.470262: train_loss -0.7773 +2024-11-22 02:46:27.470496: val_loss -0.7451 +2024-11-22 02:46:27.470574: Pseudo dice [0.8468] +2024-11-22 02:46:27.470652: Epoch time: 18.85 s +2024-11-22 02:46:28.326097: +2024-11-22 02:46:28.326597: Epoch 2957 +2024-11-22 02:46:28.326735: Current learning rate: 0.0066 +2024-11-22 02:46:47.196375: train_loss -0.7803 +2024-11-22 02:46:47.201802: val_loss -0.7254 +2024-11-22 02:46:47.201914: Pseudo dice [0.8419] +2024-11-22 02:46:47.202010: Epoch time: 18.87 s +2024-11-22 02:46:48.073154: +2024-11-22 02:46:48.073579: Epoch 2958 +2024-11-22 02:46:48.073709: Current learning rate: 0.0066 +2024-11-22 02:47:07.853460: train_loss -0.7766 +2024-11-22 02:47:07.853709: val_loss -0.7411 +2024-11-22 02:47:07.853782: Pseudo dice [0.8432] +2024-11-22 02:47:07.853864: Epoch time: 19.78 s +2024-11-22 02:47:08.725712: +2024-11-22 02:47:08.726174: Epoch 2959 +2024-11-22 02:47:08.726312: Current learning rate: 0.0066 +2024-11-22 02:47:28.256779: train_loss -0.7831 +2024-11-22 02:47:28.257007: val_loss -0.7354 +2024-11-22 02:47:28.257088: Pseudo dice [0.8571] +2024-11-22 02:47:28.257178: Epoch time: 19.53 s +2024-11-22 02:47:29.123177: +2024-11-22 02:47:29.123640: Epoch 2960 +2024-11-22 02:47:29.123779: Current learning rate: 0.0066 +2024-11-22 02:47:49.412601: train_loss -0.777 +2024-11-22 02:47:49.412832: val_loss -0.7471 +2024-11-22 02:47:49.412923: Pseudo dice [0.8218] +2024-11-22 02:47:49.413010: Epoch time: 20.29 s +2024-11-22 02:47:50.277904: +2024-11-22 02:47:50.278321: Epoch 2961 +2024-11-22 02:47:50.278458: Current learning rate: 0.0066 +2024-11-22 02:48:09.401622: train_loss -0.7714 +2024-11-22 02:48:09.401832: val_loss -0.7571 +2024-11-22 02:48:09.401904: Pseudo dice [0.854] +2024-11-22 02:48:09.401978: Epoch time: 19.12 s +2024-11-22 02:48:10.262301: +2024-11-22 02:48:10.262728: Epoch 2962 +2024-11-22 02:48:10.262871: Current learning rate: 0.0066 +2024-11-22 02:48:29.306528: train_loss -0.7872 +2024-11-22 02:48:29.306845: val_loss -0.758 +2024-11-22 02:48:29.306923: Pseudo dice [0.8476] +2024-11-22 02:48:29.307016: Epoch time: 19.04 s +2024-11-22 02:48:30.276253: +2024-11-22 02:48:30.276680: Epoch 2963 +2024-11-22 02:48:30.276834: Current learning rate: 0.00659 +2024-11-22 02:48:48.629812: train_loss -0.7737 +2024-11-22 02:48:48.630043: val_loss -0.7478 +2024-11-22 02:48:48.635370: Pseudo dice [0.8434] +2024-11-22 02:48:48.635466: Epoch time: 18.35 s +2024-11-22 02:48:49.736275: +2024-11-22 02:48:49.736717: Epoch 2964 +2024-11-22 02:48:49.736863: Current learning rate: 0.00659 +2024-11-22 02:49:08.667458: train_loss -0.7873 +2024-11-22 02:49:08.667670: val_loss -0.7339 +2024-11-22 02:49:08.667745: Pseudo dice [0.8389] +2024-11-22 02:49:08.667822: Epoch time: 18.93 s +2024-11-22 02:49:09.520415: +2024-11-22 02:49:09.520751: Epoch 2965 +2024-11-22 02:49:09.520871: Current learning rate: 0.00659 +2024-11-22 02:49:28.630103: train_loss -0.7877 +2024-11-22 02:49:28.630327: val_loss -0.7585 +2024-11-22 02:49:28.630403: Pseudo dice [0.8483] +2024-11-22 02:49:28.630484: Epoch time: 19.11 s +2024-11-22 02:49:29.472985: +2024-11-22 02:49:29.473416: Epoch 2966 +2024-11-22 02:49:29.473552: Current learning rate: 0.00659 +2024-11-22 02:49:49.341820: train_loss -0.7792 +2024-11-22 02:49:49.342064: val_loss -0.7335 +2024-11-22 02:49:49.342140: Pseudo dice [0.8555] +2024-11-22 02:49:49.342222: Epoch time: 19.87 s +2024-11-22 02:49:50.206876: +2024-11-22 02:49:50.207307: Epoch 2967 +2024-11-22 02:49:50.207441: Current learning rate: 0.00659 +2024-11-22 02:50:08.865510: train_loss -0.7877 +2024-11-22 02:50:08.865725: val_loss -0.7421 +2024-11-22 02:50:08.865798: Pseudo dice [0.8506] +2024-11-22 02:50:08.865875: Epoch time: 18.66 s +2024-11-22 02:50:10.111029: +2024-11-22 02:50:10.111435: Epoch 2968 +2024-11-22 02:50:10.111565: Current learning rate: 0.00659 +2024-11-22 02:50:29.444262: train_loss -0.7962 +2024-11-22 02:50:29.444469: val_loss -0.7303 +2024-11-22 02:50:29.444546: Pseudo dice [0.8269] +2024-11-22 02:50:29.444624: Epoch time: 19.33 s +2024-11-22 02:50:30.305901: +2024-11-22 02:50:30.306340: Epoch 2969 +2024-11-22 02:50:30.306479: Current learning rate: 0.00659 +2024-11-22 02:50:48.604138: train_loss -0.7893 +2024-11-22 02:50:48.604357: val_loss -0.7294 +2024-11-22 02:50:48.604435: Pseudo dice [0.8257] +2024-11-22 02:50:48.604525: Epoch time: 18.3 s +2024-11-22 02:50:49.446973: +2024-11-22 02:50:49.447403: Epoch 2970 +2024-11-22 02:50:49.447537: Current learning rate: 0.00659 +2024-11-22 02:51:08.308927: train_loss -0.7773 +2024-11-22 02:51:08.311339: val_loss -0.7318 +2024-11-22 02:51:08.311454: Pseudo dice [0.8301] +2024-11-22 02:51:08.311540: Epoch time: 18.86 s +2024-11-22 02:51:09.321865: +2024-11-22 02:51:09.322286: Epoch 2971 +2024-11-22 02:51:09.322418: Current learning rate: 0.00658 +2024-11-22 02:51:27.946989: train_loss -0.775 +2024-11-22 02:51:27.947587: val_loss -0.7431 +2024-11-22 02:51:27.947676: Pseudo dice [0.8461] +2024-11-22 02:51:27.947758: Epoch time: 18.63 s +2024-11-22 02:51:28.814807: +2024-11-22 02:51:28.815228: Epoch 2972 +2024-11-22 02:51:28.815362: Current learning rate: 0.00658 +2024-11-22 02:51:47.804534: train_loss -0.7756 +2024-11-22 02:51:47.804746: val_loss -0.732 +2024-11-22 02:51:47.804821: Pseudo dice [0.8179] +2024-11-22 02:51:47.804897: Epoch time: 18.99 s +2024-11-22 02:51:48.672915: +2024-11-22 02:51:48.673412: Epoch 2973 +2024-11-22 02:51:48.673548: Current learning rate: 0.00658 +2024-11-22 02:52:06.416895: train_loss -0.7748 +2024-11-22 02:52:06.417170: val_loss -0.7154 +2024-11-22 02:52:06.417250: Pseudo dice [0.803] +2024-11-22 02:52:06.417328: Epoch time: 17.74 s +2024-11-22 02:52:07.276811: +2024-11-22 02:52:07.277220: Epoch 2974 +2024-11-22 02:52:07.277352: Current learning rate: 0.00658 +2024-11-22 02:52:26.102787: train_loss -0.7773 +2024-11-22 02:52:26.103008: val_loss -0.743 +2024-11-22 02:52:26.103081: Pseudo dice [0.8602] +2024-11-22 02:52:26.103155: Epoch time: 18.83 s +2024-11-22 02:52:27.160038: +2024-11-22 02:52:27.160467: Epoch 2975 +2024-11-22 02:52:27.160601: Current learning rate: 0.00658 +2024-11-22 02:52:45.733533: train_loss -0.7796 +2024-11-22 02:52:45.733764: val_loss -0.7336 +2024-11-22 02:52:45.733839: Pseudo dice [0.8388] +2024-11-22 02:52:45.733923: Epoch time: 18.57 s +2024-11-22 02:52:46.692883: +2024-11-22 02:52:46.693304: Epoch 2976 +2024-11-22 02:52:46.693436: Current learning rate: 0.00658 +2024-11-22 02:53:06.841650: train_loss -0.7725 +2024-11-22 02:53:06.841868: val_loss -0.7551 +2024-11-22 02:53:06.841942: Pseudo dice [0.8305] +2024-11-22 02:53:06.842026: Epoch time: 20.15 s +2024-11-22 02:53:07.703945: +2024-11-22 02:53:07.704348: Epoch 2977 +2024-11-22 02:53:07.704480: Current learning rate: 0.00658 +2024-11-22 02:53:27.344261: train_loss -0.7793 +2024-11-22 02:53:27.344563: val_loss -0.7123 +2024-11-22 02:53:27.344650: Pseudo dice [0.8405] +2024-11-22 02:53:27.344744: Epoch time: 19.64 s +2024-11-22 02:53:28.209244: +2024-11-22 02:53:28.209676: Epoch 2978 +2024-11-22 02:53:28.209815: Current learning rate: 0.00658 +2024-11-22 02:53:46.596041: train_loss -0.7697 +2024-11-22 02:53:46.596265: val_loss -0.7668 +2024-11-22 02:53:46.596341: Pseudo dice [0.8353] +2024-11-22 02:53:46.596424: Epoch time: 18.39 s +2024-11-22 02:53:47.467832: +2024-11-22 02:53:47.468295: Epoch 2979 +2024-11-22 02:53:47.468476: Current learning rate: 0.00658 +2024-11-22 02:54:06.934703: train_loss -0.7873 +2024-11-22 02:54:06.935344: val_loss -0.7781 +2024-11-22 02:54:06.935425: Pseudo dice [0.8493] +2024-11-22 02:54:06.935499: Epoch time: 19.47 s +2024-11-22 02:54:07.795755: +2024-11-22 02:54:07.796216: Epoch 2980 +2024-11-22 02:54:07.796353: Current learning rate: 0.00657 +2024-11-22 02:54:25.387593: train_loss -0.7827 +2024-11-22 02:54:25.387817: val_loss -0.7356 +2024-11-22 02:54:25.387902: Pseudo dice [0.8447] +2024-11-22 02:54:25.387984: Epoch time: 17.59 s +2024-11-22 02:54:26.247064: +2024-11-22 02:54:26.247524: Epoch 2981 +2024-11-22 02:54:26.247663: Current learning rate: 0.00657 +2024-11-22 02:54:45.644619: train_loss -0.7865 +2024-11-22 02:54:45.644843: val_loss -0.7269 +2024-11-22 02:54:45.644919: Pseudo dice [0.8383] +2024-11-22 02:54:45.645012: Epoch time: 19.4 s +2024-11-22 02:54:46.569207: +2024-11-22 02:54:46.569656: Epoch 2982 +2024-11-22 02:54:46.569837: Current learning rate: 0.00657 +2024-11-22 02:55:04.838791: train_loss -0.7762 +2024-11-22 02:55:04.844244: val_loss -0.7247 +2024-11-22 02:55:04.844378: Pseudo dice [0.8235] +2024-11-22 02:55:04.844463: Epoch time: 18.27 s +2024-11-22 02:55:05.793372: +2024-11-22 02:55:05.793831: Epoch 2983 +2024-11-22 02:55:05.793978: Current learning rate: 0.00657 +2024-11-22 02:55:23.321718: train_loss -0.7586 +2024-11-22 02:55:23.321930: val_loss -0.713 +2024-11-22 02:55:23.322013: Pseudo dice [0.8281] +2024-11-22 02:55:23.322092: Epoch time: 17.53 s +2024-11-22 02:55:24.193903: +2024-11-22 02:55:24.194325: Epoch 2984 +2024-11-22 02:55:24.194460: Current learning rate: 0.00657 +2024-11-22 02:55:43.235956: train_loss -0.778 +2024-11-22 02:55:43.236248: val_loss -0.7533 +2024-11-22 02:55:43.236323: Pseudo dice [0.8623] +2024-11-22 02:55:43.236402: Epoch time: 19.04 s +2024-11-22 02:55:44.107511: +2024-11-22 02:55:44.107917: Epoch 2985 +2024-11-22 02:55:44.108059: Current learning rate: 0.00657 +2024-11-22 02:56:03.331028: train_loss -0.7847 +2024-11-22 02:56:03.331267: val_loss -0.7414 +2024-11-22 02:56:03.331353: Pseudo dice [0.8163] +2024-11-22 02:56:03.331435: Epoch time: 19.22 s +2024-11-22 02:56:04.212482: +2024-11-22 02:56:04.212914: Epoch 2986 +2024-11-22 02:56:04.213058: Current learning rate: 0.00657 +2024-11-22 02:56:23.758671: train_loss -0.7784 +2024-11-22 02:56:23.758914: val_loss -0.7382 +2024-11-22 02:56:23.758987: Pseudo dice [0.83] +2024-11-22 02:56:23.759082: Epoch time: 19.55 s +2024-11-22 02:56:24.620976: +2024-11-22 02:56:24.621400: Epoch 2987 +2024-11-22 02:56:24.621530: Current learning rate: 0.00657 +2024-11-22 02:56:42.362249: train_loss -0.7738 +2024-11-22 02:56:42.362465: val_loss -0.7431 +2024-11-22 02:56:42.362539: Pseudo dice [0.8411] +2024-11-22 02:56:42.362615: Epoch time: 17.74 s +2024-11-22 02:56:43.267245: +2024-11-22 02:56:43.267669: Epoch 2988 +2024-11-22 02:56:43.267802: Current learning rate: 0.00656 +2024-11-22 02:57:01.745653: train_loss -0.7786 +2024-11-22 02:57:01.745872: val_loss -0.7355 +2024-11-22 02:57:01.745954: Pseudo dice [0.846] +2024-11-22 02:57:01.746044: Epoch time: 18.48 s +2024-11-22 02:57:02.608678: +2024-11-22 02:57:02.609085: Epoch 2989 +2024-11-22 02:57:02.609212: Current learning rate: 0.00656 +2024-11-22 02:57:21.301008: train_loss -0.781 +2024-11-22 02:57:21.301265: val_loss -0.7242 +2024-11-22 02:57:21.301343: Pseudo dice [0.8303] +2024-11-22 02:57:21.301424: Epoch time: 18.69 s +2024-11-22 02:57:22.166137: +2024-11-22 02:57:22.166595: Epoch 2990 +2024-11-22 02:57:22.166729: Current learning rate: 0.00656 +2024-11-22 02:57:41.254956: train_loss -0.78 +2024-11-22 02:57:41.255268: val_loss -0.7485 +2024-11-22 02:57:41.255347: Pseudo dice [0.835] +2024-11-22 02:57:41.255428: Epoch time: 19.09 s +2024-11-22 02:57:42.510196: +2024-11-22 02:57:42.510612: Epoch 2991 +2024-11-22 02:57:42.510788: Current learning rate: 0.00656 +2024-11-22 02:58:01.463729: train_loss -0.778 +2024-11-22 02:58:01.463969: val_loss -0.7504 +2024-11-22 02:58:01.464051: Pseudo dice [0.8573] +2024-11-22 02:58:01.464131: Epoch time: 18.95 s +2024-11-22 02:58:02.459564: +2024-11-22 02:58:02.459986: Epoch 2992 +2024-11-22 02:58:02.460121: Current learning rate: 0.00656 +2024-11-22 02:58:22.411226: train_loss -0.7822 +2024-11-22 02:58:22.411475: val_loss -0.7249 +2024-11-22 02:58:22.411678: Pseudo dice [0.8369] +2024-11-22 02:58:22.411762: Epoch time: 19.95 s +2024-11-22 02:58:23.283789: +2024-11-22 02:58:23.284235: Epoch 2993 +2024-11-22 02:58:23.284367: Current learning rate: 0.00656 +2024-11-22 02:58:42.544570: train_loss -0.7731 +2024-11-22 02:58:42.544856: val_loss -0.7345 +2024-11-22 02:58:42.544960: Pseudo dice [0.8392] +2024-11-22 02:58:42.545044: Epoch time: 19.26 s +2024-11-22 02:58:43.511691: +2024-11-22 02:58:43.512112: Epoch 2994 +2024-11-22 02:58:43.512245: Current learning rate: 0.00656 +2024-11-22 02:59:01.796314: train_loss -0.7791 +2024-11-22 02:59:01.796525: val_loss -0.7189 +2024-11-22 02:59:01.796598: Pseudo dice [0.8227] +2024-11-22 02:59:01.796673: Epoch time: 18.29 s +2024-11-22 02:59:02.659206: +2024-11-22 02:59:02.659620: Epoch 2995 +2024-11-22 02:59:02.659754: Current learning rate: 0.00656 +2024-11-22 02:59:22.144692: train_loss -0.7815 +2024-11-22 02:59:22.144933: val_loss -0.75 +2024-11-22 02:59:22.145030: Pseudo dice [0.8441] +2024-11-22 02:59:22.145116: Epoch time: 19.49 s +2024-11-22 02:59:23.175673: +2024-11-22 02:59:23.176113: Epoch 2996 +2024-11-22 02:59:23.176252: Current learning rate: 0.00656 +2024-11-22 02:59:41.763537: train_loss -0.7835 +2024-11-22 02:59:41.763754: val_loss -0.7581 +2024-11-22 02:59:41.763831: Pseudo dice [0.854] +2024-11-22 02:59:41.763910: Epoch time: 18.59 s +2024-11-22 02:59:42.627985: +2024-11-22 02:59:42.628448: Epoch 2997 +2024-11-22 02:59:42.628594: Current learning rate: 0.00655 +2024-11-22 03:00:01.239472: train_loss -0.7858 +2024-11-22 03:00:01.239913: val_loss -0.7758 +2024-11-22 03:00:01.240007: Pseudo dice [0.8294] +2024-11-22 03:00:01.240087: Epoch time: 18.61 s +2024-11-22 03:00:02.102605: +2024-11-22 03:00:02.103104: Epoch 2998 +2024-11-22 03:00:02.103248: Current learning rate: 0.00655 +2024-11-22 03:00:20.858716: train_loss -0.788 +2024-11-22 03:00:20.858937: val_loss -0.7393 +2024-11-22 03:00:20.859019: Pseudo dice [0.8169] +2024-11-22 03:00:20.861127: Epoch time: 18.76 s +2024-11-22 03:00:21.835721: +2024-11-22 03:00:21.836290: Epoch 2999 +2024-11-22 03:00:21.836445: Current learning rate: 0.00655 +2024-11-22 03:00:40.224658: train_loss -0.7886 +2024-11-22 03:00:40.224899: val_loss -0.7672 +2024-11-22 03:00:40.224973: Pseudo dice [0.8488] +2024-11-22 03:00:40.225063: Epoch time: 18.39 s +2024-11-22 03:00:41.368979: +2024-11-22 03:00:41.369395: Epoch 3000 +2024-11-22 03:00:41.369525: Current learning rate: 0.00655 +2024-11-22 03:01:00.197822: train_loss -0.7813 +2024-11-22 03:01:00.198041: val_loss -0.7238 +2024-11-22 03:01:00.198120: Pseudo dice [0.8303] +2024-11-22 03:01:00.198201: Epoch time: 18.83 s +2024-11-22 03:01:01.065573: +2024-11-22 03:01:01.066011: Epoch 3001 +2024-11-22 03:01:01.066152: Current learning rate: 0.00655 +2024-11-22 03:01:19.025945: train_loss -0.788 +2024-11-22 03:01:19.026175: val_loss -0.7477 +2024-11-22 03:01:19.026251: Pseudo dice [0.8381] +2024-11-22 03:01:19.026333: Epoch time: 17.96 s +2024-11-22 03:01:20.289910: +2024-11-22 03:01:20.290352: Epoch 3002 +2024-11-22 03:01:20.290512: Current learning rate: 0.00655 +2024-11-22 03:01:38.119751: train_loss -0.7862 +2024-11-22 03:01:38.120003: val_loss -0.7271 +2024-11-22 03:01:38.120079: Pseudo dice [0.822] +2024-11-22 03:01:38.120161: Epoch time: 17.83 s +2024-11-22 03:01:38.986025: +2024-11-22 03:01:38.986454: Epoch 3003 +2024-11-22 03:01:38.986582: Current learning rate: 0.00655 +2024-11-22 03:01:57.655727: train_loss -0.7811 +2024-11-22 03:01:57.655948: val_loss -0.7373 +2024-11-22 03:01:57.656044: Pseudo dice [0.855] +2024-11-22 03:01:57.656125: Epoch time: 18.67 s +2024-11-22 03:01:58.524505: +2024-11-22 03:01:58.524948: Epoch 3004 +2024-11-22 03:01:58.525089: Current learning rate: 0.00655 +2024-11-22 03:02:17.232667: train_loss -0.7885 +2024-11-22 03:02:17.232948: val_loss -0.7559 +2024-11-22 03:02:17.233038: Pseudo dice [0.8367] +2024-11-22 03:02:17.233117: Epoch time: 18.71 s +2024-11-22 03:02:18.096711: +2024-11-22 03:02:18.097139: Epoch 3005 +2024-11-22 03:02:18.097270: Current learning rate: 0.00654 +2024-11-22 03:02:36.374874: train_loss -0.7838 +2024-11-22 03:02:36.377240: val_loss -0.7294 +2024-11-22 03:02:36.377332: Pseudo dice [0.8223] +2024-11-22 03:02:36.377410: Epoch time: 18.28 s +2024-11-22 03:02:37.275715: +2024-11-22 03:02:37.276255: Epoch 3006 +2024-11-22 03:02:37.276429: Current learning rate: 0.00654 +2024-11-22 03:02:56.114927: train_loss -0.7813 +2024-11-22 03:02:56.115187: val_loss -0.7226 +2024-11-22 03:02:56.115268: Pseudo dice [0.8129] +2024-11-22 03:02:56.115353: Epoch time: 18.84 s +2024-11-22 03:02:57.011149: +2024-11-22 03:02:57.011624: Epoch 3007 +2024-11-22 03:02:57.011769: Current learning rate: 0.00654 +2024-11-22 03:03:15.679781: train_loss -0.7892 +2024-11-22 03:03:15.680009: val_loss -0.7065 +2024-11-22 03:03:15.680087: Pseudo dice [0.8211] +2024-11-22 03:03:15.680187: Epoch time: 18.67 s +2024-11-22 03:03:16.546128: +2024-11-22 03:03:16.546541: Epoch 3008 +2024-11-22 03:03:16.546678: Current learning rate: 0.00654 +2024-11-22 03:03:34.183380: train_loss -0.7851 +2024-11-22 03:03:34.183609: val_loss -0.765 +2024-11-22 03:03:34.183687: Pseudo dice [0.8421] +2024-11-22 03:03:34.183776: Epoch time: 17.64 s +2024-11-22 03:03:35.047806: +2024-11-22 03:03:35.048235: Epoch 3009 +2024-11-22 03:03:35.048373: Current learning rate: 0.00654 +2024-11-22 03:03:53.916080: train_loss -0.7737 +2024-11-22 03:03:53.916326: val_loss -0.7258 +2024-11-22 03:03:53.916404: Pseudo dice [0.8462] +2024-11-22 03:03:53.916485: Epoch time: 18.87 s +2024-11-22 03:03:54.817904: +2024-11-22 03:03:54.818323: Epoch 3010 +2024-11-22 03:03:54.818456: Current learning rate: 0.00654 +2024-11-22 03:04:13.494467: train_loss -0.779 +2024-11-22 03:04:13.494754: val_loss -0.7411 +2024-11-22 03:04:13.494831: Pseudo dice [0.837] +2024-11-22 03:04:13.494911: Epoch time: 18.68 s +2024-11-22 03:04:14.356179: +2024-11-22 03:04:14.356596: Epoch 3011 +2024-11-22 03:04:14.356727: Current learning rate: 0.00654 +2024-11-22 03:04:33.699830: train_loss -0.7741 +2024-11-22 03:04:33.700057: val_loss -0.7479 +2024-11-22 03:04:33.700135: Pseudo dice [0.834] +2024-11-22 03:04:33.700211: Epoch time: 19.34 s +2024-11-22 03:04:34.566711: +2024-11-22 03:04:34.567165: Epoch 3012 +2024-11-22 03:04:34.567297: Current learning rate: 0.00654 +2024-11-22 03:04:53.902894: train_loss -0.7769 +2024-11-22 03:04:53.903124: val_loss -0.738 +2024-11-22 03:04:53.903203: Pseudo dice [0.8294] +2024-11-22 03:04:53.903283: Epoch time: 19.34 s +2024-11-22 03:04:54.807398: +2024-11-22 03:04:54.807631: Epoch 3013 +2024-11-22 03:04:54.807750: Current learning rate: 0.00654 +2024-11-22 03:05:14.803592: train_loss -0.788 +2024-11-22 03:05:14.803850: val_loss -0.7596 +2024-11-22 03:05:14.804001: Pseudo dice [0.8333] +2024-11-22 03:05:14.804085: Epoch time: 20.0 s +2024-11-22 03:05:15.680380: +2024-11-22 03:05:15.680820: Epoch 3014 +2024-11-22 03:05:15.680952: Current learning rate: 0.00653 +2024-11-22 03:05:35.095923: train_loss -0.7755 +2024-11-22 03:05:35.096138: val_loss -0.7521 +2024-11-22 03:05:35.096220: Pseudo dice [0.824] +2024-11-22 03:05:35.096314: Epoch time: 19.42 s +2024-11-22 03:05:35.997553: +2024-11-22 03:05:35.997967: Epoch 3015 +2024-11-22 03:05:35.998107: Current learning rate: 0.00653 +2024-11-22 03:05:55.641629: train_loss -0.7752 +2024-11-22 03:05:55.641854: val_loss -0.7024 +2024-11-22 03:05:55.641929: Pseudo dice [0.8433] +2024-11-22 03:05:55.642015: Epoch time: 19.64 s +2024-11-22 03:05:56.510165: +2024-11-22 03:05:56.510573: Epoch 3016 +2024-11-22 03:05:56.510706: Current learning rate: 0.00653 +2024-11-22 03:06:16.129075: train_loss -0.7737 +2024-11-22 03:06:16.129338: val_loss -0.7287 +2024-11-22 03:06:16.129414: Pseudo dice [0.8306] +2024-11-22 03:06:16.129499: Epoch time: 19.62 s +2024-11-22 03:06:16.990192: +2024-11-22 03:06:16.990641: Epoch 3017 +2024-11-22 03:06:16.990780: Current learning rate: 0.00653 +2024-11-22 03:06:34.939765: train_loss -0.7715 +2024-11-22 03:06:34.939977: val_loss -0.7299 +2024-11-22 03:06:34.940061: Pseudo dice [0.8223] +2024-11-22 03:06:34.940140: Epoch time: 17.95 s +2024-11-22 03:06:35.807737: +2024-11-22 03:06:35.808161: Epoch 3018 +2024-11-22 03:06:35.808302: Current learning rate: 0.00653 +2024-11-22 03:06:55.270206: train_loss -0.7489 +2024-11-22 03:06:55.270425: val_loss -0.7508 +2024-11-22 03:06:55.270499: Pseudo dice [0.8321] +2024-11-22 03:06:55.270578: Epoch time: 19.46 s +2024-11-22 03:06:56.269862: +2024-11-22 03:06:56.270282: Epoch 3019 +2024-11-22 03:06:56.270422: Current learning rate: 0.00653 +2024-11-22 03:07:14.699921: train_loss -0.7434 +2024-11-22 03:07:14.700190: val_loss -0.744 +2024-11-22 03:07:14.700268: Pseudo dice [0.8306] +2024-11-22 03:07:14.700345: Epoch time: 18.43 s +2024-11-22 03:07:15.571543: +2024-11-22 03:07:15.571984: Epoch 3020 +2024-11-22 03:07:15.572121: Current learning rate: 0.00653 +2024-11-22 03:07:34.527546: train_loss -0.7548 +2024-11-22 03:07:34.527823: val_loss -0.7094 +2024-11-22 03:07:34.527903: Pseudo dice [0.8471] +2024-11-22 03:07:34.527984: Epoch time: 18.96 s +2024-11-22 03:07:35.421473: +2024-11-22 03:07:35.421906: Epoch 3021 +2024-11-22 03:07:35.422047: Current learning rate: 0.00653 +2024-11-22 03:07:53.229515: train_loss -0.7767 +2024-11-22 03:07:53.229824: val_loss -0.75 +2024-11-22 03:07:53.229899: Pseudo dice [0.8386] +2024-11-22 03:07:53.229979: Epoch time: 17.81 s +2024-11-22 03:07:54.092834: +2024-11-22 03:07:54.093277: Epoch 3022 +2024-11-22 03:07:54.093417: Current learning rate: 0.00652 +2024-11-22 03:08:13.506756: train_loss -0.7762 +2024-11-22 03:08:13.506970: val_loss -0.7609 +2024-11-22 03:08:13.507058: Pseudo dice [0.8432] +2024-11-22 03:08:13.507136: Epoch time: 19.41 s +2024-11-22 03:08:14.374460: +2024-11-22 03:08:14.374890: Epoch 3023 +2024-11-22 03:08:14.375034: Current learning rate: 0.00652 +2024-11-22 03:08:33.284590: train_loss -0.7701 +2024-11-22 03:08:33.284840: val_loss -0.742 +2024-11-22 03:08:33.284921: Pseudo dice [0.8461] +2024-11-22 03:08:33.285009: Epoch time: 18.91 s +2024-11-22 03:08:34.180475: +2024-11-22 03:08:34.180984: Epoch 3024 +2024-11-22 03:08:34.181126: Current learning rate: 0.00652 +2024-11-22 03:08:54.446486: train_loss -0.7752 +2024-11-22 03:08:54.446731: val_loss -0.7196 +2024-11-22 03:08:54.446806: Pseudo dice [0.7998] +2024-11-22 03:08:54.446887: Epoch time: 20.27 s +2024-11-22 03:08:55.705234: +2024-11-22 03:08:55.705671: Epoch 3025 +2024-11-22 03:08:55.705806: Current learning rate: 0.00652 +2024-11-22 03:09:14.254467: train_loss -0.7804 +2024-11-22 03:09:14.254686: val_loss -0.755 +2024-11-22 03:09:14.254767: Pseudo dice [0.8214] +2024-11-22 03:09:14.254846: Epoch time: 18.55 s +2024-11-22 03:09:15.122109: +2024-11-22 03:09:15.122540: Epoch 3026 +2024-11-22 03:09:15.122679: Current learning rate: 0.00652 +2024-11-22 03:09:33.988700: train_loss -0.7811 +2024-11-22 03:09:33.988912: val_loss -0.7452 +2024-11-22 03:09:33.988984: Pseudo dice [0.8234] +2024-11-22 03:09:33.989066: Epoch time: 18.87 s +2024-11-22 03:09:34.850934: +2024-11-22 03:09:34.851378: Epoch 3027 +2024-11-22 03:09:34.851509: Current learning rate: 0.00652 +2024-11-22 03:09:53.218955: train_loss -0.7792 +2024-11-22 03:09:53.219222: val_loss -0.7323 +2024-11-22 03:09:53.219305: Pseudo dice [0.8438] +2024-11-22 03:09:53.222816: Epoch time: 18.37 s +2024-11-22 03:09:54.094816: +2024-11-22 03:09:54.095246: Epoch 3028 +2024-11-22 03:09:54.095379: Current learning rate: 0.00652 +2024-11-22 03:10:12.384734: train_loss -0.7755 +2024-11-22 03:10:12.384968: val_loss -0.7624 +2024-11-22 03:10:12.385053: Pseudo dice [0.8382] +2024-11-22 03:10:12.385135: Epoch time: 18.29 s +2024-11-22 03:10:13.288732: +2024-11-22 03:10:13.289150: Epoch 3029 +2024-11-22 03:10:13.289287: Current learning rate: 0.00652 +2024-11-22 03:10:32.303179: train_loss -0.7734 +2024-11-22 03:10:32.303397: val_loss -0.7405 +2024-11-22 03:10:32.303471: Pseudo dice [0.8366] +2024-11-22 03:10:32.303549: Epoch time: 19.02 s +2024-11-22 03:10:33.182142: +2024-11-22 03:10:33.182569: Epoch 3030 +2024-11-22 03:10:33.182703: Current learning rate: 0.00652 +2024-11-22 03:10:52.300097: train_loss -0.7667 +2024-11-22 03:10:52.302452: val_loss -0.7351 +2024-11-22 03:10:52.302632: Pseudo dice [0.8495] +2024-11-22 03:10:52.302720: Epoch time: 19.12 s +2024-11-22 03:10:53.181891: +2024-11-22 03:10:53.182338: Epoch 3031 +2024-11-22 03:10:53.182481: Current learning rate: 0.00651 +2024-11-22 03:11:11.835929: train_loss -0.7788 +2024-11-22 03:11:11.836157: val_loss -0.7315 +2024-11-22 03:11:11.836234: Pseudo dice [0.8396] +2024-11-22 03:11:11.836312: Epoch time: 18.65 s +2024-11-22 03:11:12.924067: +2024-11-22 03:11:12.924477: Epoch 3032 +2024-11-22 03:11:12.924618: Current learning rate: 0.00651 +2024-11-22 03:11:30.963735: train_loss -0.7846 +2024-11-22 03:11:30.963972: val_loss -0.7448 +2024-11-22 03:11:30.964053: Pseudo dice [0.8283] +2024-11-22 03:11:30.964133: Epoch time: 18.04 s +2024-11-22 03:11:31.854778: +2024-11-22 03:11:31.855247: Epoch 3033 +2024-11-22 03:11:31.855380: Current learning rate: 0.00651 +2024-11-22 03:11:49.817845: train_loss -0.7857 +2024-11-22 03:11:49.818075: val_loss -0.7395 +2024-11-22 03:11:49.818153: Pseudo dice [0.8342] +2024-11-22 03:11:49.818233: Epoch time: 17.96 s +2024-11-22 03:11:50.686831: +2024-11-22 03:11:50.687271: Epoch 3034 +2024-11-22 03:11:50.687405: Current learning rate: 0.00651 +2024-11-22 03:12:09.527071: train_loss -0.7877 +2024-11-22 03:12:09.527286: val_loss -0.7311 +2024-11-22 03:12:09.527362: Pseudo dice [0.8315] +2024-11-22 03:12:09.529602: Epoch time: 18.84 s +2024-11-22 03:12:10.565619: +2024-11-22 03:12:10.566082: Epoch 3035 +2024-11-22 03:12:10.566222: Current learning rate: 0.00651 +2024-11-22 03:12:30.279605: train_loss -0.7898 +2024-11-22 03:12:30.279860: val_loss -0.7503 +2024-11-22 03:12:30.279933: Pseudo dice [0.8434] +2024-11-22 03:12:30.281884: Epoch time: 19.71 s +2024-11-22 03:12:31.249914: +2024-11-22 03:12:31.250186: Epoch 3036 +2024-11-22 03:12:31.250301: Current learning rate: 0.00651 +2024-11-22 03:12:49.891617: train_loss -0.7824 +2024-11-22 03:12:49.891853: val_loss -0.7545 +2024-11-22 03:12:49.891931: Pseudo dice [0.8599] +2024-11-22 03:12:49.892018: Epoch time: 18.64 s +2024-11-22 03:12:50.757997: +2024-11-22 03:12:50.758452: Epoch 3037 +2024-11-22 03:12:50.758588: Current learning rate: 0.00651 +2024-11-22 03:13:10.152296: train_loss -0.7827 +2024-11-22 03:13:10.152514: val_loss -0.7183 +2024-11-22 03:13:10.152589: Pseudo dice [0.8255] +2024-11-22 03:13:10.152668: Epoch time: 19.4 s +2024-11-22 03:13:11.036673: +2024-11-22 03:13:11.037089: Epoch 3038 +2024-11-22 03:13:11.037223: Current learning rate: 0.00651 +2024-11-22 03:13:30.008464: train_loss -0.7901 +2024-11-22 03:13:30.008762: val_loss -0.7666 +2024-11-22 03:13:30.008843: Pseudo dice [0.8587] +2024-11-22 03:13:30.008926: Epoch time: 18.97 s +2024-11-22 03:13:30.873569: +2024-11-22 03:13:30.874065: Epoch 3039 +2024-11-22 03:13:30.874201: Current learning rate: 0.0065 +2024-11-22 03:13:50.254416: train_loss -0.782 +2024-11-22 03:13:50.254629: val_loss -0.7321 +2024-11-22 03:13:50.254705: Pseudo dice [0.8418] +2024-11-22 03:13:50.259979: Epoch time: 19.38 s +2024-11-22 03:13:51.225849: +2024-11-22 03:13:51.226309: Epoch 3040 +2024-11-22 03:13:51.226453: Current learning rate: 0.0065 +2024-11-22 03:14:09.752736: train_loss -0.7797 +2024-11-22 03:14:09.752955: val_loss -0.7152 +2024-11-22 03:14:09.753039: Pseudo dice [0.8326] +2024-11-22 03:14:09.753118: Epoch time: 18.53 s +2024-11-22 03:14:10.625681: +2024-11-22 03:14:10.626108: Epoch 3041 +2024-11-22 03:14:10.626240: Current learning rate: 0.0065 +2024-11-22 03:14:29.249460: train_loss -0.7831 +2024-11-22 03:14:29.249691: val_loss -0.7479 +2024-11-22 03:14:29.249793: Pseudo dice [0.8481] +2024-11-22 03:14:29.249880: Epoch time: 18.62 s +2024-11-22 03:14:30.119822: +2024-11-22 03:14:30.120254: Epoch 3042 +2024-11-22 03:14:30.120391: Current learning rate: 0.0065 +2024-11-22 03:14:49.225627: train_loss -0.7855 +2024-11-22 03:14:49.225899: val_loss -0.7237 +2024-11-22 03:14:49.225978: Pseudo dice [0.8175] +2024-11-22 03:14:49.226064: Epoch time: 19.11 s +2024-11-22 03:14:50.097738: +2024-11-22 03:14:50.098168: Epoch 3043 +2024-11-22 03:14:50.098307: Current learning rate: 0.0065 +2024-11-22 03:15:09.299913: train_loss -0.7804 +2024-11-22 03:15:09.300140: val_loss -0.7301 +2024-11-22 03:15:09.300214: Pseudo dice [0.8316] +2024-11-22 03:15:09.300292: Epoch time: 19.2 s +2024-11-22 03:15:10.166311: +2024-11-22 03:15:10.166743: Epoch 3044 +2024-11-22 03:15:10.166877: Current learning rate: 0.0065 +2024-11-22 03:15:29.253453: train_loss -0.7863 +2024-11-22 03:15:29.254069: val_loss -0.7256 +2024-11-22 03:15:29.254150: Pseudo dice [0.8488] +2024-11-22 03:15:29.254231: Epoch time: 19.09 s +2024-11-22 03:15:30.123275: +2024-11-22 03:15:30.123690: Epoch 3045 +2024-11-22 03:15:30.123824: Current learning rate: 0.0065 +2024-11-22 03:15:47.793657: train_loss -0.7836 +2024-11-22 03:15:47.793931: val_loss -0.7496 +2024-11-22 03:15:47.794023: Pseudo dice [0.8624] +2024-11-22 03:15:47.794108: Epoch time: 17.67 s +2024-11-22 03:15:48.887899: +2024-11-22 03:15:48.888336: Epoch 3046 +2024-11-22 03:15:48.888471: Current learning rate: 0.0065 +2024-11-22 03:16:08.275984: train_loss -0.7825 +2024-11-22 03:16:08.276210: val_loss -0.7486 +2024-11-22 03:16:08.276289: Pseudo dice [0.8305] +2024-11-22 03:16:08.276367: Epoch time: 19.39 s +2024-11-22 03:16:09.142706: +2024-11-22 03:16:09.143132: Epoch 3047 +2024-11-22 03:16:09.143268: Current learning rate: 0.0065 +2024-11-22 03:16:27.174925: train_loss -0.7845 +2024-11-22 03:16:27.175151: val_loss -0.7334 +2024-11-22 03:16:27.175225: Pseudo dice [0.8452] +2024-11-22 03:16:27.175304: Epoch time: 18.03 s +2024-11-22 03:16:28.420333: +2024-11-22 03:16:28.420807: Epoch 3048 +2024-11-22 03:16:28.420956: Current learning rate: 0.00649 +2024-11-22 03:16:47.362350: train_loss -0.7952 +2024-11-22 03:16:47.362676: val_loss -0.7543 +2024-11-22 03:16:47.362756: Pseudo dice [0.8498] +2024-11-22 03:16:47.362842: Epoch time: 18.94 s +2024-11-22 03:16:48.249544: +2024-11-22 03:16:48.250000: Epoch 3049 +2024-11-22 03:16:48.250138: Current learning rate: 0.00649 +2024-11-22 03:17:07.866508: train_loss -0.7764 +2024-11-22 03:17:07.866731: val_loss -0.7492 +2024-11-22 03:17:07.866812: Pseudo dice [0.8534] +2024-11-22 03:17:07.866893: Epoch time: 19.62 s +2024-11-22 03:17:08.964369: +2024-11-22 03:17:08.964808: Epoch 3050 +2024-11-22 03:17:08.964945: Current learning rate: 0.00649 +2024-11-22 03:17:27.798151: train_loss -0.7784 +2024-11-22 03:17:27.798373: val_loss -0.75 +2024-11-22 03:17:27.798449: Pseudo dice [0.8504] +2024-11-22 03:17:27.798527: Epoch time: 18.83 s +2024-11-22 03:17:28.675007: +2024-11-22 03:17:28.675483: Epoch 3051 +2024-11-22 03:17:28.675631: Current learning rate: 0.00649 +2024-11-22 03:17:47.479752: train_loss -0.7819 +2024-11-22 03:17:47.480000: val_loss -0.755 +2024-11-22 03:17:47.480078: Pseudo dice [0.842] +2024-11-22 03:17:47.480161: Epoch time: 18.81 s +2024-11-22 03:17:48.350007: +2024-11-22 03:17:48.350452: Epoch 3052 +2024-11-22 03:17:48.350591: Current learning rate: 0.00649 +2024-11-22 03:18:08.121152: train_loss -0.7855 +2024-11-22 03:18:08.121363: val_loss -0.7136 +2024-11-22 03:18:08.121436: Pseudo dice [0.8202] +2024-11-22 03:18:08.121511: Epoch time: 19.77 s +2024-11-22 03:18:09.030525: +2024-11-22 03:18:09.031042: Epoch 3053 +2024-11-22 03:18:09.031185: Current learning rate: 0.00649 +2024-11-22 03:18:27.708294: train_loss -0.7874 +2024-11-22 03:18:27.708507: val_loss -0.7352 +2024-11-22 03:18:27.708583: Pseudo dice [0.8344] +2024-11-22 03:18:27.708658: Epoch time: 18.68 s +2024-11-22 03:18:28.680681: +2024-11-22 03:18:28.681199: Epoch 3054 +2024-11-22 03:18:28.681339: Current learning rate: 0.00649 +2024-11-22 03:18:47.386796: train_loss -0.7875 +2024-11-22 03:18:47.387014: val_loss -0.7442 +2024-11-22 03:18:47.387088: Pseudo dice [0.8519] +2024-11-22 03:18:47.387165: Epoch time: 18.71 s +2024-11-22 03:18:48.255648: +2024-11-22 03:18:48.256067: Epoch 3055 +2024-11-22 03:18:48.256202: Current learning rate: 0.00649 +2024-11-22 03:19:07.712679: train_loss -0.7862 +2024-11-22 03:19:07.712970: val_loss -0.7427 +2024-11-22 03:19:07.713058: Pseudo dice [0.8372] +2024-11-22 03:19:07.713142: Epoch time: 19.46 s +2024-11-22 03:19:08.615186: +2024-11-22 03:19:08.615665: Epoch 3056 +2024-11-22 03:19:08.615806: Current learning rate: 0.00648 +2024-11-22 03:19:27.254748: train_loss -0.7884 +2024-11-22 03:19:27.254977: val_loss -0.7436 +2024-11-22 03:19:27.255057: Pseudo dice [0.8396] +2024-11-22 03:19:27.255136: Epoch time: 18.64 s +2024-11-22 03:19:28.246920: +2024-11-22 03:19:28.247339: Epoch 3057 +2024-11-22 03:19:28.247478: Current learning rate: 0.00648 +2024-11-22 03:19:46.214418: train_loss -0.7823 +2024-11-22 03:19:46.214659: val_loss -0.7428 +2024-11-22 03:19:46.214736: Pseudo dice [0.8311] +2024-11-22 03:19:46.214813: Epoch time: 17.97 s +2024-11-22 03:19:47.085281: +2024-11-22 03:19:47.085689: Epoch 3058 +2024-11-22 03:19:47.085824: Current learning rate: 0.00648 +2024-11-22 03:20:06.075467: train_loss -0.7892 +2024-11-22 03:20:06.075684: val_loss -0.7413 +2024-11-22 03:20:06.075759: Pseudo dice [0.8644] +2024-11-22 03:20:06.075837: Epoch time: 18.99 s +2024-11-22 03:20:07.330762: +2024-11-22 03:20:07.331190: Epoch 3059 +2024-11-22 03:20:07.331322: Current learning rate: 0.00648 +2024-11-22 03:20:26.337101: train_loss -0.7879 +2024-11-22 03:20:26.337377: val_loss -0.745 +2024-11-22 03:20:26.337454: Pseudo dice [0.8083] +2024-11-22 03:20:26.337545: Epoch time: 19.01 s +2024-11-22 03:20:27.201870: +2024-11-22 03:20:27.202288: Epoch 3060 +2024-11-22 03:20:27.202420: Current learning rate: 0.00648 +2024-11-22 03:20:46.014132: train_loss -0.7812 +2024-11-22 03:20:46.014354: val_loss -0.744 +2024-11-22 03:20:46.014430: Pseudo dice [0.828] +2024-11-22 03:20:46.014509: Epoch time: 18.81 s +2024-11-22 03:20:46.882636: +2024-11-22 03:20:46.883140: Epoch 3061 +2024-11-22 03:20:46.883276: Current learning rate: 0.00648 +2024-11-22 03:21:06.571435: train_loss -0.784 +2024-11-22 03:21:06.571716: val_loss -0.7496 +2024-11-22 03:21:06.571797: Pseudo dice [0.8579] +2024-11-22 03:21:06.571878: Epoch time: 19.69 s +2024-11-22 03:21:07.439626: +2024-11-22 03:21:07.440073: Epoch 3062 +2024-11-22 03:21:07.440211: Current learning rate: 0.00648 +2024-11-22 03:21:26.280899: train_loss -0.7891 +2024-11-22 03:21:26.281162: val_loss -0.7668 +2024-11-22 03:21:26.281239: Pseudo dice [0.8315] +2024-11-22 03:21:26.281327: Epoch time: 18.84 s +2024-11-22 03:21:27.154378: +2024-11-22 03:21:27.154810: Epoch 3063 +2024-11-22 03:21:27.154945: Current learning rate: 0.00648 +2024-11-22 03:21:45.534412: train_loss -0.7855 +2024-11-22 03:21:45.534635: val_loss -0.7167 +2024-11-22 03:21:45.534714: Pseudo dice [0.8355] +2024-11-22 03:21:45.534793: Epoch time: 18.38 s +2024-11-22 03:21:46.425142: +2024-11-22 03:21:46.425538: Epoch 3064 +2024-11-22 03:21:46.425663: Current learning rate: 0.00648 +2024-11-22 03:22:05.351666: train_loss -0.7751 +2024-11-22 03:22:05.351888: val_loss -0.7295 +2024-11-22 03:22:05.351979: Pseudo dice [0.8357] +2024-11-22 03:22:05.352123: Epoch time: 18.93 s +2024-11-22 03:22:06.216582: +2024-11-22 03:22:06.216998: Epoch 3065 +2024-11-22 03:22:06.217131: Current learning rate: 0.00647 +2024-11-22 03:22:25.941240: train_loss -0.7887 +2024-11-22 03:22:25.941462: val_loss -0.7533 +2024-11-22 03:22:25.941540: Pseudo dice [0.8443] +2024-11-22 03:22:25.941614: Epoch time: 19.73 s +2024-11-22 03:22:27.038378: +2024-11-22 03:22:27.038797: Epoch 3066 +2024-11-22 03:22:27.038933: Current learning rate: 0.00647 +2024-11-22 03:22:45.274725: train_loss -0.79 +2024-11-22 03:22:45.275019: val_loss -0.733 +2024-11-22 03:22:45.275106: Pseudo dice [0.8434] +2024-11-22 03:22:45.275210: Epoch time: 18.24 s +2024-11-22 03:22:46.143851: +2024-11-22 03:22:46.144396: Epoch 3067 +2024-11-22 03:22:46.144541: Current learning rate: 0.00647 +2024-11-22 03:23:05.271183: train_loss -0.7838 +2024-11-22 03:23:05.271393: val_loss -0.6975 +2024-11-22 03:23:05.271467: Pseudo dice [0.8458] +2024-11-22 03:23:05.271543: Epoch time: 19.13 s +2024-11-22 03:23:06.152544: +2024-11-22 03:23:06.153005: Epoch 3068 +2024-11-22 03:23:06.153152: Current learning rate: 0.00647 +2024-11-22 03:23:25.540227: train_loss -0.7878 +2024-11-22 03:23:25.540459: val_loss -0.7427 +2024-11-22 03:23:25.540541: Pseudo dice [0.8285] +2024-11-22 03:23:25.540619: Epoch time: 19.39 s +2024-11-22 03:23:26.407392: +2024-11-22 03:23:26.407910: Epoch 3069 +2024-11-22 03:23:26.408054: Current learning rate: 0.00647 +2024-11-22 03:23:44.172593: train_loss -0.7849 +2024-11-22 03:23:44.172829: val_loss -0.7452 +2024-11-22 03:23:44.172905: Pseudo dice [0.8603] +2024-11-22 03:23:44.172986: Epoch time: 17.77 s +2024-11-22 03:23:45.143418: +2024-11-22 03:23:45.143705: Epoch 3070 +2024-11-22 03:23:45.143821: Current learning rate: 0.00647 +2024-11-22 03:24:03.862271: train_loss -0.7865 +2024-11-22 03:24:03.862510: val_loss -0.7153 +2024-11-22 03:24:03.862602: Pseudo dice [0.8423] +2024-11-22 03:24:03.862682: Epoch time: 18.72 s +2024-11-22 03:24:04.719215: +2024-11-22 03:24:04.719689: Epoch 3071 +2024-11-22 03:24:04.719830: Current learning rate: 0.00647 +2024-11-22 03:24:23.179445: train_loss -0.7815 +2024-11-22 03:24:23.181775: val_loss -0.762 +2024-11-22 03:24:23.181879: Pseudo dice [0.8406] +2024-11-22 03:24:23.181964: Epoch time: 18.46 s +2024-11-22 03:24:24.127739: +2024-11-22 03:24:24.128205: Epoch 3072 +2024-11-22 03:24:24.128343: Current learning rate: 0.00647 +2024-11-22 03:24:42.708535: train_loss -0.7863 +2024-11-22 03:24:42.708769: val_loss -0.7536 +2024-11-22 03:24:42.714011: Pseudo dice [0.8358] +2024-11-22 03:24:42.714213: Epoch time: 18.58 s +2024-11-22 03:24:43.607138: +2024-11-22 03:24:43.607588: Epoch 3073 +2024-11-22 03:24:43.607721: Current learning rate: 0.00646 +2024-11-22 03:25:01.822182: train_loss -0.784 +2024-11-22 03:25:01.822438: val_loss -0.7748 +2024-11-22 03:25:01.822513: Pseudo dice [0.8598] +2024-11-22 03:25:01.822599: Epoch time: 18.22 s +2024-11-22 03:25:02.691487: +2024-11-22 03:25:02.691906: Epoch 3074 +2024-11-22 03:25:02.692048: Current learning rate: 0.00646 +2024-11-22 03:25:21.292816: train_loss -0.7814 +2024-11-22 03:25:21.293055: val_loss -0.7495 +2024-11-22 03:25:21.293133: Pseudo dice [0.8292] +2024-11-22 03:25:21.293213: Epoch time: 18.6 s +2024-11-22 03:25:22.285395: +2024-11-22 03:25:22.285816: Epoch 3075 +2024-11-22 03:25:22.286199: Current learning rate: 0.00646 +2024-11-22 03:25:40.327674: train_loss -0.7799 +2024-11-22 03:25:40.327896: val_loss -0.711 +2024-11-22 03:25:40.327974: Pseudo dice [0.8323] +2024-11-22 03:25:40.328056: Epoch time: 18.04 s +2024-11-22 03:25:41.221999: +2024-11-22 03:25:41.222504: Epoch 3076 +2024-11-22 03:25:41.222646: Current learning rate: 0.00646 +2024-11-22 03:25:59.693553: train_loss -0.7827 +2024-11-22 03:25:59.693787: val_loss -0.7233 +2024-11-22 03:25:59.693925: Pseudo dice [0.8111] +2024-11-22 03:25:59.694011: Epoch time: 18.47 s +2024-11-22 03:26:00.598727: +2024-11-22 03:26:00.599155: Epoch 3077 +2024-11-22 03:26:00.599290: Current learning rate: 0.00646 +2024-11-22 03:26:18.497021: train_loss -0.7731 +2024-11-22 03:26:18.497242: val_loss -0.7421 +2024-11-22 03:26:18.497321: Pseudo dice [0.8407] +2024-11-22 03:26:18.497399: Epoch time: 17.9 s +2024-11-22 03:26:19.361695: +2024-11-22 03:26:19.362206: Epoch 3078 +2024-11-22 03:26:19.362347: Current learning rate: 0.00646 +2024-11-22 03:26:38.167690: train_loss -0.788 +2024-11-22 03:26:38.167936: val_loss -0.7427 +2024-11-22 03:26:38.168020: Pseudo dice [0.8373] +2024-11-22 03:26:38.168099: Epoch time: 18.81 s +2024-11-22 03:26:39.032304: +2024-11-22 03:26:39.032757: Epoch 3079 +2024-11-22 03:26:39.032899: Current learning rate: 0.00646 +2024-11-22 03:26:58.186160: train_loss -0.7761 +2024-11-22 03:26:58.186423: val_loss -0.7605 +2024-11-22 03:26:58.186503: Pseudo dice [0.851] +2024-11-22 03:26:58.186580: Epoch time: 19.15 s +2024-11-22 03:26:59.055140: +2024-11-22 03:26:59.055555: Epoch 3080 +2024-11-22 03:26:59.055687: Current learning rate: 0.00646 +2024-11-22 03:27:18.429925: train_loss -0.7823 +2024-11-22 03:27:18.430149: val_loss -0.757 +2024-11-22 03:27:18.430225: Pseudo dice [0.8375] +2024-11-22 03:27:18.430300: Epoch time: 19.38 s +2024-11-22 03:27:19.295660: +2024-11-22 03:27:19.296088: Epoch 3081 +2024-11-22 03:27:19.296225: Current learning rate: 0.00646 +2024-11-22 03:27:38.428529: train_loss -0.7808 +2024-11-22 03:27:38.428793: val_loss -0.7494 +2024-11-22 03:27:38.428871: Pseudo dice [0.8462] +2024-11-22 03:27:38.428955: Epoch time: 19.13 s +2024-11-22 03:27:39.691569: +2024-11-22 03:27:39.692034: Epoch 3082 +2024-11-22 03:27:39.692183: Current learning rate: 0.00645 +2024-11-22 03:27:58.750935: train_loss -0.7861 +2024-11-22 03:27:58.751586: val_loss -0.7284 +2024-11-22 03:27:58.751669: Pseudo dice [0.8312] +2024-11-22 03:27:58.751746: Epoch time: 19.06 s +2024-11-22 03:27:59.638381: +2024-11-22 03:27:59.638820: Epoch 3083 +2024-11-22 03:27:59.638951: Current learning rate: 0.00645 +2024-11-22 03:28:18.170451: train_loss -0.7905 +2024-11-22 03:28:18.170683: val_loss -0.7623 +2024-11-22 03:28:18.170759: Pseudo dice [0.8422] +2024-11-22 03:28:18.172995: Epoch time: 18.53 s +2024-11-22 03:28:19.237140: +2024-11-22 03:28:19.237686: Epoch 3084 +2024-11-22 03:28:19.237821: Current learning rate: 0.00645 +2024-11-22 03:28:37.803493: train_loss -0.7862 +2024-11-22 03:28:37.805372: val_loss -0.7442 +2024-11-22 03:28:37.805458: Pseudo dice [0.8242] +2024-11-22 03:28:37.805543: Epoch time: 18.57 s +2024-11-22 03:28:38.824351: +2024-11-22 03:28:38.824774: Epoch 3085 +2024-11-22 03:28:38.824914: Current learning rate: 0.00645 +2024-11-22 03:28:57.595272: train_loss -0.7833 +2024-11-22 03:28:57.595501: val_loss -0.7439 +2024-11-22 03:28:57.595586: Pseudo dice [0.8212] +2024-11-22 03:28:57.595663: Epoch time: 18.77 s +2024-11-22 03:28:58.460323: +2024-11-22 03:28:58.460747: Epoch 3086 +2024-11-22 03:28:58.460880: Current learning rate: 0.00645 +2024-11-22 03:29:17.712837: train_loss -0.7747 +2024-11-22 03:29:17.713138: val_loss -0.7332 +2024-11-22 03:29:17.713250: Pseudo dice [0.8216] +2024-11-22 03:29:17.713330: Epoch time: 19.25 s +2024-11-22 03:29:18.587479: +2024-11-22 03:29:18.587978: Epoch 3087 +2024-11-22 03:29:18.588112: Current learning rate: 0.00645 +2024-11-22 03:29:36.844082: train_loss -0.7834 +2024-11-22 03:29:36.844295: val_loss -0.7337 +2024-11-22 03:29:36.844376: Pseudo dice [0.8344] +2024-11-22 03:29:36.844453: Epoch time: 18.26 s +2024-11-22 03:29:37.711339: +2024-11-22 03:29:37.711795: Epoch 3088 +2024-11-22 03:29:37.711936: Current learning rate: 0.00645 +2024-11-22 03:29:56.828413: train_loss -0.7869 +2024-11-22 03:29:56.833880: val_loss -0.745 +2024-11-22 03:29:56.834011: Pseudo dice [0.8433] +2024-11-22 03:29:56.834105: Epoch time: 19.12 s +2024-11-22 03:29:57.729247: +2024-11-22 03:29:57.729697: Epoch 3089 +2024-11-22 03:29:57.729847: Current learning rate: 0.00645 +2024-11-22 03:30:16.979355: train_loss -0.7795 +2024-11-22 03:30:16.979587: val_loss -0.7462 +2024-11-22 03:30:16.979663: Pseudo dice [0.8292] +2024-11-22 03:30:16.979741: Epoch time: 19.25 s +2024-11-22 03:30:18.062486: +2024-11-22 03:30:18.062928: Epoch 3090 +2024-11-22 03:30:18.063074: Current learning rate: 0.00644 +2024-11-22 03:30:37.224668: train_loss -0.785 +2024-11-22 03:30:37.224883: val_loss -0.7286 +2024-11-22 03:30:37.224960: Pseudo dice [0.8232] +2024-11-22 03:30:37.225047: Epoch time: 19.16 s +2024-11-22 03:30:38.090544: +2024-11-22 03:30:38.091047: Epoch 3091 +2024-11-22 03:30:38.091177: Current learning rate: 0.00644 +2024-11-22 03:30:57.437865: train_loss -0.7844 +2024-11-22 03:30:57.439157: val_loss -0.7446 +2024-11-22 03:30:57.439250: Pseudo dice [0.8214] +2024-11-22 03:30:57.439332: Epoch time: 19.35 s +2024-11-22 03:30:58.318603: +2024-11-22 03:30:58.319001: Epoch 3092 +2024-11-22 03:30:58.319131: Current learning rate: 0.00644 +2024-11-22 03:31:16.993918: train_loss -0.7857 +2024-11-22 03:31:16.996294: val_loss -0.7527 +2024-11-22 03:31:16.996414: Pseudo dice [0.8289] +2024-11-22 03:31:16.996499: Epoch time: 18.68 s +2024-11-22 03:31:18.370319: +2024-11-22 03:31:18.370533: Epoch 3093 +2024-11-22 03:31:18.370643: Current learning rate: 0.00644 +2024-11-22 03:31:37.122706: train_loss -0.7776 +2024-11-22 03:31:37.122942: val_loss -0.7135 +2024-11-22 03:31:37.123028: Pseudo dice [0.8406] +2024-11-22 03:31:37.125297: Epoch time: 18.75 s +2024-11-22 03:31:38.015461: +2024-11-22 03:31:38.015709: Epoch 3094 +2024-11-22 03:31:38.015823: Current learning rate: 0.00644 +2024-11-22 03:31:56.881494: train_loss -0.7696 +2024-11-22 03:31:56.881726: val_loss -0.7412 +2024-11-22 03:31:56.881806: Pseudo dice [0.8423] +2024-11-22 03:31:56.881890: Epoch time: 18.87 s +2024-11-22 03:31:57.865955: +2024-11-22 03:31:57.866282: Epoch 3095 +2024-11-22 03:31:57.866398: Current learning rate: 0.00644 +2024-11-22 03:32:16.876552: train_loss -0.7844 +2024-11-22 03:32:16.876785: val_loss -0.7313 +2024-11-22 03:32:16.876859: Pseudo dice [0.8233] +2024-11-22 03:32:16.876939: Epoch time: 19.01 s +2024-11-22 03:32:17.763425: +2024-11-22 03:32:17.763620: Epoch 3096 +2024-11-22 03:32:17.763736: Current learning rate: 0.00644 +2024-11-22 03:32:37.155683: train_loss -0.7893 +2024-11-22 03:32:37.155906: val_loss -0.7312 +2024-11-22 03:32:37.155985: Pseudo dice [0.8376] +2024-11-22 03:32:37.156069: Epoch time: 19.39 s +2024-11-22 03:32:38.126745: +2024-11-22 03:32:38.126962: Epoch 3097 +2024-11-22 03:32:38.127079: Current learning rate: 0.00644 +2024-11-22 03:32:56.488560: train_loss -0.7933 +2024-11-22 03:32:56.488790: val_loss -0.7842 +2024-11-22 03:32:56.488870: Pseudo dice [0.8484] +2024-11-22 03:32:56.488948: Epoch time: 18.36 s +2024-11-22 03:32:57.366604: +2024-11-22 03:32:57.366806: Epoch 3098 +2024-11-22 03:32:57.366916: Current learning rate: 0.00644 +2024-11-22 03:33:15.978175: train_loss -0.7911 +2024-11-22 03:33:15.978425: val_loss -0.7492 +2024-11-22 03:33:15.978503: Pseudo dice [0.8596] +2024-11-22 03:33:15.978587: Epoch time: 18.61 s +2024-11-22 03:33:17.119950: +2024-11-22 03:33:17.120166: Epoch 3099 +2024-11-22 03:33:17.120289: Current learning rate: 0.00643 +2024-11-22 03:33:35.590236: train_loss -0.7866 +2024-11-22 03:33:35.590483: val_loss -0.7347 +2024-11-22 03:33:35.590562: Pseudo dice [0.8186] +2024-11-22 03:33:35.590643: Epoch time: 18.47 s +2024-11-22 03:33:36.713637: +2024-11-22 03:33:36.713849: Epoch 3100 +2024-11-22 03:33:36.713961: Current learning rate: 0.00643 +2024-11-22 03:33:55.913118: train_loss -0.783 +2024-11-22 03:33:55.913349: val_loss -0.7383 +2024-11-22 03:33:55.913502: Pseudo dice [0.8273] +2024-11-22 03:33:55.913584: Epoch time: 19.2 s +2024-11-22 03:33:56.784151: +2024-11-22 03:33:56.784347: Epoch 3101 +2024-11-22 03:33:56.784599: Current learning rate: 0.00643 +2024-11-22 03:34:15.611503: train_loss -0.7916 +2024-11-22 03:34:15.611720: val_loss -0.7537 +2024-11-22 03:34:15.611794: Pseudo dice [0.8541] +2024-11-22 03:34:15.611871: Epoch time: 18.83 s +2024-11-22 03:34:16.473704: +2024-11-22 03:34:16.473896: Epoch 3102 +2024-11-22 03:34:16.474014: Current learning rate: 0.00643 +2024-11-22 03:34:34.547484: train_loss -0.7853 +2024-11-22 03:34:34.547737: val_loss -0.7566 +2024-11-22 03:34:34.547822: Pseudo dice [0.8487] +2024-11-22 03:34:34.547909: Epoch time: 18.07 s +2024-11-22 03:34:35.419824: +2024-11-22 03:34:35.420029: Epoch 3103 +2024-11-22 03:34:35.420138: Current learning rate: 0.00643 +2024-11-22 03:34:54.527955: train_loss -0.7929 +2024-11-22 03:34:54.528199: val_loss -0.7639 +2024-11-22 03:34:54.528279: Pseudo dice [0.8401] +2024-11-22 03:34:54.528360: Epoch time: 19.11 s +2024-11-22 03:34:55.394804: +2024-11-22 03:34:55.395088: Epoch 3104 +2024-11-22 03:34:55.395201: Current learning rate: 0.00643 +2024-11-22 03:35:14.316399: train_loss -0.7772 +2024-11-22 03:35:14.316621: val_loss -0.721 +2024-11-22 03:35:14.316695: Pseudo dice [0.8337] +2024-11-22 03:35:14.316771: Epoch time: 18.92 s +2024-11-22 03:35:15.607318: +2024-11-22 03:35:15.607762: Epoch 3105 +2024-11-22 03:35:15.607913: Current learning rate: 0.00643 +2024-11-22 03:35:34.956091: train_loss -0.7801 +2024-11-22 03:35:34.956343: val_loss -0.745 +2024-11-22 03:35:34.956418: Pseudo dice [0.8481] +2024-11-22 03:35:34.956497: Epoch time: 19.35 s +2024-11-22 03:35:35.824304: +2024-11-22 03:35:35.824777: Epoch 3106 +2024-11-22 03:35:35.824911: Current learning rate: 0.00643 +2024-11-22 03:35:54.529510: train_loss -0.7879 +2024-11-22 03:35:54.529727: val_loss -0.7541 +2024-11-22 03:35:54.529806: Pseudo dice [0.8415] +2024-11-22 03:35:54.529885: Epoch time: 18.71 s +2024-11-22 03:35:55.399499: +2024-11-22 03:35:55.400036: Epoch 3107 +2024-11-22 03:35:55.400170: Current learning rate: 0.00642 +2024-11-22 03:36:14.810613: train_loss -0.7869 +2024-11-22 03:36:14.810833: val_loss -0.7465 +2024-11-22 03:36:14.813101: Pseudo dice [0.8476] +2024-11-22 03:36:14.813187: Epoch time: 19.41 s +2024-11-22 03:36:15.691222: +2024-11-22 03:36:15.691758: Epoch 3108 +2024-11-22 03:36:15.691895: Current learning rate: 0.00642 +2024-11-22 03:36:33.515206: train_loss -0.7893 +2024-11-22 03:36:33.517131: val_loss -0.7427 +2024-11-22 03:36:33.517222: Pseudo dice [0.8609] +2024-11-22 03:36:33.517308: Epoch time: 17.82 s +2024-11-22 03:36:34.432106: +2024-11-22 03:36:34.432558: Epoch 3109 +2024-11-22 03:36:34.432689: Current learning rate: 0.00642 +2024-11-22 03:36:52.791687: train_loss -0.7873 +2024-11-22 03:36:52.791900: val_loss -0.743 +2024-11-22 03:36:52.791973: Pseudo dice [0.8372] +2024-11-22 03:36:52.792057: Epoch time: 18.36 s +2024-11-22 03:36:53.657829: +2024-11-22 03:36:53.658251: Epoch 3110 +2024-11-22 03:36:53.658388: Current learning rate: 0.00642 +2024-11-22 03:37:12.560757: train_loss -0.7894 +2024-11-22 03:37:12.560983: val_loss -0.7667 +2024-11-22 03:37:12.561065: Pseudo dice [0.8421] +2024-11-22 03:37:12.561158: Epoch time: 18.9 s +2024-11-22 03:37:13.423834: +2024-11-22 03:37:13.424281: Epoch 3111 +2024-11-22 03:37:13.424428: Current learning rate: 0.00642 +2024-11-22 03:37:32.842115: train_loss -0.789 +2024-11-22 03:37:32.842332: val_loss -0.7299 +2024-11-22 03:37:32.842406: Pseudo dice [0.8465] +2024-11-22 03:37:32.842486: Epoch time: 19.42 s +2024-11-22 03:37:33.707042: +2024-11-22 03:37:33.707536: Epoch 3112 +2024-11-22 03:37:33.707672: Current learning rate: 0.00642 +2024-11-22 03:37:52.877059: train_loss -0.7856 +2024-11-22 03:37:52.877309: val_loss -0.7622 +2024-11-22 03:37:52.877459: Pseudo dice [0.8459] +2024-11-22 03:37:52.877544: Epoch time: 19.17 s +2024-11-22 03:37:53.745391: +2024-11-22 03:37:53.745799: Epoch 3113 +2024-11-22 03:37:53.745932: Current learning rate: 0.00642 +2024-11-22 03:38:12.537782: train_loss -0.773 +2024-11-22 03:38:12.543183: val_loss -0.7244 +2024-11-22 03:38:12.543293: Pseudo dice [0.8307] +2024-11-22 03:38:12.543376: Epoch time: 18.79 s +2024-11-22 03:38:13.482870: +2024-11-22 03:38:13.483286: Epoch 3114 +2024-11-22 03:38:13.483427: Current learning rate: 0.00642 +2024-11-22 03:38:33.479166: train_loss -0.7866 +2024-11-22 03:38:33.484568: val_loss -0.785 +2024-11-22 03:38:33.484682: Pseudo dice [0.8469] +2024-11-22 03:38:33.484762: Epoch time: 20.0 s +2024-11-22 03:38:34.386194: +2024-11-22 03:38:34.386699: Epoch 3115 +2024-11-22 03:38:34.386832: Current learning rate: 0.00642 +2024-11-22 03:38:52.151427: train_loss -0.7787 +2024-11-22 03:38:52.152636: val_loss -0.7512 +2024-11-22 03:38:52.152721: Pseudo dice [0.8416] +2024-11-22 03:38:52.152805: Epoch time: 17.77 s +2024-11-22 03:38:53.034128: +2024-11-22 03:38:53.034391: Epoch 3116 +2024-11-22 03:38:53.034503: Current learning rate: 0.00641 +2024-11-22 03:39:12.410560: train_loss -0.7841 +2024-11-22 03:39:12.412941: val_loss -0.7643 +2024-11-22 03:39:12.413132: Pseudo dice [0.8392] +2024-11-22 03:39:12.413214: Epoch time: 19.38 s +2024-11-22 03:39:13.288728: +2024-11-22 03:39:13.289197: Epoch 3117 +2024-11-22 03:39:13.289328: Current learning rate: 0.00641 +2024-11-22 03:39:32.345955: train_loss -0.7776 +2024-11-22 03:39:32.346184: val_loss -0.7513 +2024-11-22 03:39:32.346257: Pseudo dice [0.8271] +2024-11-22 03:39:32.346334: Epoch time: 19.06 s +2024-11-22 03:39:33.212854: +2024-11-22 03:39:33.213274: Epoch 3118 +2024-11-22 03:39:33.213405: Current learning rate: 0.00641 +2024-11-22 03:39:50.767773: train_loss -0.7769 +2024-11-22 03:39:50.770188: val_loss -0.7456 +2024-11-22 03:39:50.770311: Pseudo dice [0.8321] +2024-11-22 03:39:50.770405: Epoch time: 17.56 s +2024-11-22 03:39:51.644340: +2024-11-22 03:39:51.644776: Epoch 3119 +2024-11-22 03:39:51.644905: Current learning rate: 0.00641 +2024-11-22 03:40:10.456405: train_loss -0.7938 +2024-11-22 03:40:10.456633: val_loss -0.7563 +2024-11-22 03:40:10.458866: Pseudo dice [0.8515] +2024-11-22 03:40:10.458984: Epoch time: 18.81 s +2024-11-22 03:40:11.492548: +2024-11-22 03:40:11.493009: Epoch 3120 +2024-11-22 03:40:11.493155: Current learning rate: 0.00641 +2024-11-22 03:40:29.848930: train_loss -0.7875 +2024-11-22 03:40:29.849156: val_loss -0.7464 +2024-11-22 03:40:29.849232: Pseudo dice [0.8499] +2024-11-22 03:40:29.849319: Epoch time: 18.36 s +2024-11-22 03:40:30.718872: +2024-11-22 03:40:30.719306: Epoch 3121 +2024-11-22 03:40:30.719452: Current learning rate: 0.00641 +2024-11-22 03:40:50.978488: train_loss -0.7817 +2024-11-22 03:40:50.983971: val_loss -0.7304 +2024-11-22 03:40:50.984106: Pseudo dice [0.8476] +2024-11-22 03:40:50.984189: Epoch time: 20.26 s +2024-11-22 03:40:51.854280: +2024-11-22 03:40:51.854727: Epoch 3122 +2024-11-22 03:40:51.854868: Current learning rate: 0.00641 +2024-11-22 03:41:11.609982: train_loss -0.7774 +2024-11-22 03:41:11.610702: val_loss -0.7485 +2024-11-22 03:41:11.610784: Pseudo dice [0.8472] +2024-11-22 03:41:11.610868: Epoch time: 19.76 s +2024-11-22 03:41:12.488318: +2024-11-22 03:41:12.488812: Epoch 3123 +2024-11-22 03:41:12.488945: Current learning rate: 0.00641 +2024-11-22 03:41:31.219836: train_loss -0.7838 +2024-11-22 03:41:31.220124: val_loss -0.7488 +2024-11-22 03:41:31.220200: Pseudo dice [0.841] +2024-11-22 03:41:31.220276: Epoch time: 18.73 s +2024-11-22 03:41:32.193918: +2024-11-22 03:41:32.194334: Epoch 3124 +2024-11-22 03:41:32.194468: Current learning rate: 0.0064 +2024-11-22 03:41:50.711039: train_loss -0.7699 +2024-11-22 03:41:50.713732: val_loss -0.7228 +2024-11-22 03:41:50.713869: Pseudo dice [0.8213] +2024-11-22 03:41:50.713951: Epoch time: 18.52 s +2024-11-22 03:41:51.612480: +2024-11-22 03:41:51.612883: Epoch 3125 +2024-11-22 03:41:51.613025: Current learning rate: 0.0064 +2024-11-22 03:42:08.634828: train_loss -0.7722 +2024-11-22 03:42:08.635056: val_loss -0.7512 +2024-11-22 03:42:08.635130: Pseudo dice [0.8183] +2024-11-22 03:42:08.635211: Epoch time: 17.02 s +2024-11-22 03:42:09.510105: +2024-11-22 03:42:09.510602: Epoch 3126 +2024-11-22 03:42:09.510751: Current learning rate: 0.0064 +2024-11-22 03:42:28.978545: train_loss -0.7792 +2024-11-22 03:42:28.978771: val_loss -0.7344 +2024-11-22 03:42:28.978850: Pseudo dice [0.8429] +2024-11-22 03:42:28.978990: Epoch time: 19.47 s +2024-11-22 03:42:29.845035: +2024-11-22 03:42:29.845654: Epoch 3127 +2024-11-22 03:42:29.845797: Current learning rate: 0.0064 +2024-11-22 03:42:48.538644: train_loss -0.7836 +2024-11-22 03:42:48.538876: val_loss -0.7186 +2024-11-22 03:42:48.538955: Pseudo dice [0.8249] +2024-11-22 03:42:48.539043: Epoch time: 18.69 s +2024-11-22 03:42:49.795928: +2024-11-22 03:42:49.796362: Epoch 3128 +2024-11-22 03:42:49.796507: Current learning rate: 0.0064 +2024-11-22 03:43:08.454238: train_loss -0.7759 +2024-11-22 03:43:08.454525: val_loss -0.7289 +2024-11-22 03:43:08.454605: Pseudo dice [0.8393] +2024-11-22 03:43:08.454690: Epoch time: 18.66 s +2024-11-22 03:43:09.326490: +2024-11-22 03:43:09.326972: Epoch 3129 +2024-11-22 03:43:09.327113: Current learning rate: 0.0064 +2024-11-22 03:43:27.970407: train_loss -0.7781 +2024-11-22 03:43:27.970631: val_loss -0.7374 +2024-11-22 03:43:27.970705: Pseudo dice [0.8043] +2024-11-22 03:43:27.970794: Epoch time: 18.64 s +2024-11-22 03:43:28.838517: +2024-11-22 03:43:28.839019: Epoch 3130 +2024-11-22 03:43:28.839159: Current learning rate: 0.0064 +2024-11-22 03:43:46.288850: train_loss -0.7754 +2024-11-22 03:43:46.289098: val_loss -0.7209 +2024-11-22 03:43:46.289176: Pseudo dice [0.8413] +2024-11-22 03:43:46.289255: Epoch time: 17.45 s +2024-11-22 03:43:47.273465: +2024-11-22 03:43:47.273887: Epoch 3131 +2024-11-22 03:43:47.274040: Current learning rate: 0.0064 +2024-11-22 03:44:05.457788: train_loss -0.7766 +2024-11-22 03:44:05.458014: val_loss -0.731 +2024-11-22 03:44:05.458118: Pseudo dice [0.8329] +2024-11-22 03:44:05.458200: Epoch time: 18.19 s +2024-11-22 03:44:06.324574: +2024-11-22 03:44:06.325086: Epoch 3132 +2024-11-22 03:44:06.325230: Current learning rate: 0.00639 +2024-11-22 03:44:25.204088: train_loss -0.7792 +2024-11-22 03:44:25.204350: val_loss -0.7501 +2024-11-22 03:44:25.204427: Pseudo dice [0.8255] +2024-11-22 03:44:25.204516: Epoch time: 18.88 s +2024-11-22 03:44:26.078296: +2024-11-22 03:44:26.078769: Epoch 3133 +2024-11-22 03:44:26.078903: Current learning rate: 0.00639 +2024-11-22 03:44:44.529480: train_loss -0.7759 +2024-11-22 03:44:44.529708: val_loss -0.7819 +2024-11-22 03:44:44.529787: Pseudo dice [0.8399] +2024-11-22 03:44:44.529869: Epoch time: 18.45 s +2024-11-22 03:44:45.403678: +2024-11-22 03:44:45.404103: Epoch 3134 +2024-11-22 03:44:45.404239: Current learning rate: 0.00639 +2024-11-22 03:45:04.322216: train_loss -0.7758 +2024-11-22 03:45:04.322434: val_loss -0.7532 +2024-11-22 03:45:04.322512: Pseudo dice [0.8397] +2024-11-22 03:45:04.322597: Epoch time: 18.92 s +2024-11-22 03:45:05.191423: +2024-11-22 03:45:05.191877: Epoch 3135 +2024-11-22 03:45:05.192015: Current learning rate: 0.00639 +2024-11-22 03:45:23.297998: train_loss -0.7773 +2024-11-22 03:45:23.298229: val_loss -0.7356 +2024-11-22 03:45:23.298306: Pseudo dice [0.8439] +2024-11-22 03:45:23.298387: Epoch time: 18.11 s +2024-11-22 03:45:24.247657: +2024-11-22 03:45:24.248106: Epoch 3136 +2024-11-22 03:45:24.248242: Current learning rate: 0.00639 +2024-11-22 03:45:43.459709: train_loss -0.7825 +2024-11-22 03:45:43.459954: val_loss -0.7673 +2024-11-22 03:45:43.460036: Pseudo dice [0.8446] +2024-11-22 03:45:43.460117: Epoch time: 19.21 s +2024-11-22 03:45:44.322584: +2024-11-22 03:45:44.323061: Epoch 3137 +2024-11-22 03:45:44.323199: Current learning rate: 0.00639 +2024-11-22 03:46:03.320673: train_loss -0.7861 +2024-11-22 03:46:03.320882: val_loss -0.7374 +2024-11-22 03:46:03.320957: Pseudo dice [0.8292] +2024-11-22 03:46:03.321043: Epoch time: 19.0 s +2024-11-22 03:46:04.185119: +2024-11-22 03:46:04.185546: Epoch 3138 +2024-11-22 03:46:04.185685: Current learning rate: 0.00639 +2024-11-22 03:46:23.629112: train_loss -0.7758 +2024-11-22 03:46:23.629332: val_loss -0.7451 +2024-11-22 03:46:23.629410: Pseudo dice [0.8438] +2024-11-22 03:46:23.629490: Epoch time: 19.44 s +2024-11-22 03:46:24.502521: +2024-11-22 03:46:24.502843: Epoch 3139 +2024-11-22 03:46:24.502964: Current learning rate: 0.00639 +2024-11-22 03:46:43.097964: train_loss -0.7841 +2024-11-22 03:46:43.098231: val_loss -0.7589 +2024-11-22 03:46:43.098307: Pseudo dice [0.8416] +2024-11-22 03:46:43.098390: Epoch time: 18.6 s +2024-11-22 03:46:43.966346: +2024-11-22 03:46:43.966759: Epoch 3140 +2024-11-22 03:46:43.966892: Current learning rate: 0.00639 +2024-11-22 03:47:03.486299: train_loss -0.7813 +2024-11-22 03:47:03.486583: val_loss -0.7488 +2024-11-22 03:47:03.486658: Pseudo dice [0.8377] +2024-11-22 03:47:03.486734: Epoch time: 19.52 s +2024-11-22 03:47:04.348017: +2024-11-22 03:47:04.348462: Epoch 3141 +2024-11-22 03:47:04.348597: Current learning rate: 0.00638 +2024-11-22 03:47:23.477576: train_loss -0.7822 +2024-11-22 03:47:23.477799: val_loss -0.7486 +2024-11-22 03:47:23.477873: Pseudo dice [0.8047] +2024-11-22 03:47:23.477951: Epoch time: 19.13 s +2024-11-22 03:47:24.341942: +2024-11-22 03:47:24.342387: Epoch 3142 +2024-11-22 03:47:24.342521: Current learning rate: 0.00638 +2024-11-22 03:47:44.386498: train_loss -0.7832 +2024-11-22 03:47:44.386806: val_loss -0.7489 +2024-11-22 03:47:44.386890: Pseudo dice [0.8433] +2024-11-22 03:47:44.386975: Epoch time: 20.05 s +2024-11-22 03:47:45.262124: +2024-11-22 03:47:45.262561: Epoch 3143 +2024-11-22 03:47:45.262690: Current learning rate: 0.00638 +2024-11-22 03:48:04.718879: train_loss -0.785 +2024-11-22 03:48:04.719137: val_loss -0.7528 +2024-11-22 03:48:04.719214: Pseudo dice [0.8396] +2024-11-22 03:48:04.719291: Epoch time: 19.46 s +2024-11-22 03:48:05.591753: +2024-11-22 03:48:05.592199: Epoch 3144 +2024-11-22 03:48:05.592347: Current learning rate: 0.00638 +2024-11-22 03:48:25.657554: train_loss -0.7721 +2024-11-22 03:48:25.657781: val_loss -0.7158 +2024-11-22 03:48:25.657860: Pseudo dice [0.8473] +2024-11-22 03:48:25.657946: Epoch time: 20.07 s +2024-11-22 03:48:26.529611: +2024-11-22 03:48:26.530020: Epoch 3145 +2024-11-22 03:48:26.530156: Current learning rate: 0.00638 +2024-11-22 03:48:44.678966: train_loss -0.7839 +2024-11-22 03:48:44.679232: val_loss -0.7539 +2024-11-22 03:48:44.679309: Pseudo dice [0.8346] +2024-11-22 03:48:44.679385: Epoch time: 18.15 s +2024-11-22 03:48:45.545764: +2024-11-22 03:48:45.546204: Epoch 3146 +2024-11-22 03:48:45.546341: Current learning rate: 0.00638 +2024-11-22 03:49:04.401657: train_loss -0.7817 +2024-11-22 03:49:04.401896: val_loss -0.7527 +2024-11-22 03:49:04.401979: Pseudo dice [0.8444] +2024-11-22 03:49:04.402078: Epoch time: 18.86 s +2024-11-22 03:49:05.272868: +2024-11-22 03:49:05.273288: Epoch 3147 +2024-11-22 03:49:05.273421: Current learning rate: 0.00638 +2024-11-22 03:49:23.702636: train_loss -0.7725 +2024-11-22 03:49:23.702858: val_loss -0.7648 +2024-11-22 03:49:23.702932: Pseudo dice [0.8454] +2024-11-22 03:49:23.703014: Epoch time: 18.43 s +2024-11-22 03:49:24.609109: +2024-11-22 03:49:24.609536: Epoch 3148 +2024-11-22 03:49:24.609695: Current learning rate: 0.00638 +2024-11-22 03:49:44.843431: train_loss -0.7753 +2024-11-22 03:49:44.843650: val_loss -0.7426 +2024-11-22 03:49:44.843726: Pseudo dice [0.8516] +2024-11-22 03:49:44.843802: Epoch time: 20.24 s +2024-11-22 03:49:45.733209: +2024-11-22 03:49:45.733624: Epoch 3149 +2024-11-22 03:49:45.733757: Current learning rate: 0.00637 +2024-11-22 03:50:04.843273: train_loss -0.7848 +2024-11-22 03:50:04.843498: val_loss -0.7041 +2024-11-22 03:50:04.843570: Pseudo dice [0.8229] +2024-11-22 03:50:04.843645: Epoch time: 19.11 s +2024-11-22 03:50:06.390290: +2024-11-22 03:50:06.390499: Epoch 3150 +2024-11-22 03:50:06.390618: Current learning rate: 0.00637 +2024-11-22 03:50:24.597464: train_loss -0.7795 +2024-11-22 03:50:24.597732: val_loss -0.7601 +2024-11-22 03:50:24.597844: Pseudo dice [0.8412] +2024-11-22 03:50:24.597933: Epoch time: 18.21 s +2024-11-22 03:50:25.473822: +2024-11-22 03:50:25.474043: Epoch 3151 +2024-11-22 03:50:25.474153: Current learning rate: 0.00637 +2024-11-22 03:50:43.496125: train_loss -0.7845 +2024-11-22 03:50:43.496346: val_loss -0.7569 +2024-11-22 03:50:43.496422: Pseudo dice [0.8425] +2024-11-22 03:50:43.496500: Epoch time: 18.02 s +2024-11-22 03:50:44.445635: +2024-11-22 03:50:44.445837: Epoch 3152 +2024-11-22 03:50:44.445949: Current learning rate: 0.00637 +2024-11-22 03:51:03.773688: train_loss -0.7836 +2024-11-22 03:51:03.773909: val_loss -0.7641 +2024-11-22 03:51:03.776154: Pseudo dice [0.847] +2024-11-22 03:51:03.776247: Epoch time: 19.33 s +2024-11-22 03:51:04.655883: +2024-11-22 03:51:04.656082: Epoch 3153 +2024-11-22 03:51:04.656194: Current learning rate: 0.00637 +2024-11-22 03:51:24.161397: train_loss -0.7823 +2024-11-22 03:51:24.161633: val_loss -0.7225 +2024-11-22 03:51:24.161708: Pseudo dice [0.8364] +2024-11-22 03:51:24.161789: Epoch time: 19.51 s +2024-11-22 03:51:25.045411: +2024-11-22 03:51:25.045626: Epoch 3154 +2024-11-22 03:51:25.045745: Current learning rate: 0.00637 +2024-11-22 03:51:43.330485: train_loss -0.7812 +2024-11-22 03:51:43.330720: val_loss -0.7296 +2024-11-22 03:51:43.330794: Pseudo dice [0.831] +2024-11-22 03:51:43.330872: Epoch time: 18.29 s +2024-11-22 03:51:44.295801: +2024-11-22 03:51:44.295987: Epoch 3155 +2024-11-22 03:51:44.296100: Current learning rate: 0.00637 +2024-11-22 03:52:02.013364: train_loss -0.7696 +2024-11-22 03:52:02.013636: val_loss -0.7485 +2024-11-22 03:52:02.013725: Pseudo dice [0.8394] +2024-11-22 03:52:02.013829: Epoch time: 17.72 s +2024-11-22 03:52:02.909317: +2024-11-22 03:52:02.909521: Epoch 3156 +2024-11-22 03:52:02.909633: Current learning rate: 0.00637 +2024-11-22 03:52:21.882044: train_loss -0.7876 +2024-11-22 03:52:21.882262: val_loss -0.7394 +2024-11-22 03:52:21.882339: Pseudo dice [0.8413] +2024-11-22 03:52:21.882416: Epoch time: 18.97 s +2024-11-22 03:52:22.757393: +2024-11-22 03:52:22.757650: Epoch 3157 +2024-11-22 03:52:22.757770: Current learning rate: 0.00637 +2024-11-22 03:52:42.348938: train_loss -0.7884 +2024-11-22 03:52:42.349239: val_loss -0.7612 +2024-11-22 03:52:42.349321: Pseudo dice [0.841] +2024-11-22 03:52:42.349441: Epoch time: 19.59 s +2024-11-22 03:52:43.223753: +2024-11-22 03:52:43.223952: Epoch 3158 +2024-11-22 03:52:43.224069: Current learning rate: 0.00636 +2024-11-22 03:53:02.168798: train_loss -0.7958 +2024-11-22 03:53:02.169019: val_loss -0.7393 +2024-11-22 03:53:02.169096: Pseudo dice [0.8172] +2024-11-22 03:53:02.169249: Epoch time: 18.95 s +2024-11-22 03:53:03.036636: +2024-11-22 03:53:03.036831: Epoch 3159 +2024-11-22 03:53:03.036943: Current learning rate: 0.00636 +2024-11-22 03:53:20.894034: train_loss -0.7807 +2024-11-22 03:53:20.894252: val_loss -0.7208 +2024-11-22 03:53:20.894388: Pseudo dice [0.829] +2024-11-22 03:53:20.894469: Epoch time: 17.86 s +2024-11-22 03:53:21.760364: +2024-11-22 03:53:21.760576: Epoch 3160 +2024-11-22 03:53:21.760688: Current learning rate: 0.00636 +2024-11-22 03:53:41.327458: train_loss -0.7917 +2024-11-22 03:53:41.327681: val_loss -0.7378 +2024-11-22 03:53:41.327761: Pseudo dice [0.817] +2024-11-22 03:53:41.327842: Epoch time: 19.57 s +2024-11-22 03:53:42.194498: +2024-11-22 03:53:42.194725: Epoch 3161 +2024-11-22 03:53:42.194836: Current learning rate: 0.00636 +2024-11-22 03:54:01.824369: train_loss -0.7941 +2024-11-22 03:54:01.824584: val_loss -0.7264 +2024-11-22 03:54:01.824663: Pseudo dice [0.7831] +2024-11-22 03:54:01.824747: Epoch time: 19.63 s +2024-11-22 03:54:03.082258: +2024-11-22 03:54:03.082700: Epoch 3162 +2024-11-22 03:54:03.082844: Current learning rate: 0.00636 +2024-11-22 03:54:21.056825: train_loss -0.7904 +2024-11-22 03:54:21.057069: val_loss -0.7588 +2024-11-22 03:54:21.057147: Pseudo dice [0.8436] +2024-11-22 03:54:21.057247: Epoch time: 17.98 s +2024-11-22 03:54:21.934546: +2024-11-22 03:54:21.934974: Epoch 3163 +2024-11-22 03:54:21.935105: Current learning rate: 0.00636 +2024-11-22 03:54:40.384149: train_loss -0.7877 +2024-11-22 03:54:40.384375: val_loss -0.7443 +2024-11-22 03:54:40.384450: Pseudo dice [0.8531] +2024-11-22 03:54:40.384550: Epoch time: 18.45 s +2024-11-22 03:54:41.253565: +2024-11-22 03:54:41.253997: Epoch 3164 +2024-11-22 03:54:41.254133: Current learning rate: 0.00636 +2024-11-22 03:54:59.796614: train_loss -0.7885 +2024-11-22 03:54:59.796916: val_loss -0.7423 +2024-11-22 03:54:59.796997: Pseudo dice [0.8202] +2024-11-22 03:54:59.797079: Epoch time: 18.54 s +2024-11-22 03:55:00.671938: +2024-11-22 03:55:00.672352: Epoch 3165 +2024-11-22 03:55:00.672482: Current learning rate: 0.00636 +2024-11-22 03:55:18.638197: train_loss -0.7934 +2024-11-22 03:55:18.638412: val_loss -0.7358 +2024-11-22 03:55:18.638488: Pseudo dice [0.8019] +2024-11-22 03:55:18.638564: Epoch time: 17.97 s +2024-11-22 03:55:19.500110: +2024-11-22 03:55:19.500551: Epoch 3166 +2024-11-22 03:55:19.500688: Current learning rate: 0.00635 +2024-11-22 03:55:38.991477: train_loss -0.7803 +2024-11-22 03:55:38.991709: val_loss -0.7267 +2024-11-22 03:55:38.991783: Pseudo dice [0.8211] +2024-11-22 03:55:38.991864: Epoch time: 19.49 s +2024-11-22 03:55:39.861542: +2024-11-22 03:55:39.861963: Epoch 3167 +2024-11-22 03:55:39.862103: Current learning rate: 0.00635 +2024-11-22 03:55:57.600091: train_loss -0.7798 +2024-11-22 03:55:57.600355: val_loss -0.7523 +2024-11-22 03:55:57.600437: Pseudo dice [0.8432] +2024-11-22 03:55:57.600520: Epoch time: 17.73 s +2024-11-22 03:55:58.586942: +2024-11-22 03:55:58.587348: Epoch 3168 +2024-11-22 03:55:58.587481: Current learning rate: 0.00635 +2024-11-22 03:56:17.290243: train_loss -0.7844 +2024-11-22 03:56:17.290480: val_loss -0.7512 +2024-11-22 03:56:17.290602: Pseudo dice [0.8351] +2024-11-22 03:56:17.290695: Epoch time: 18.7 s +2024-11-22 03:56:18.158724: +2024-11-22 03:56:18.159198: Epoch 3169 +2024-11-22 03:56:18.159332: Current learning rate: 0.00635 +2024-11-22 03:56:37.899579: train_loss -0.7851 +2024-11-22 03:56:37.899789: val_loss -0.7647 +2024-11-22 03:56:37.899863: Pseudo dice [0.8457] +2024-11-22 03:56:37.899937: Epoch time: 19.74 s +2024-11-22 03:56:38.775074: +2024-11-22 03:56:38.775518: Epoch 3170 +2024-11-22 03:56:38.775652: Current learning rate: 0.00635 +2024-11-22 03:56:57.621617: train_loss -0.7665 +2024-11-22 03:56:57.621861: val_loss -0.7384 +2024-11-22 03:56:57.621942: Pseudo dice [0.8096] +2024-11-22 03:56:57.622033: Epoch time: 18.85 s +2024-11-22 03:56:58.487217: +2024-11-22 03:56:58.487652: Epoch 3171 +2024-11-22 03:56:58.487783: Current learning rate: 0.00635 +2024-11-22 03:57:15.573041: train_loss -0.7882 +2024-11-22 03:57:15.573274: val_loss -0.709 +2024-11-22 03:57:15.573345: Pseudo dice [0.822] +2024-11-22 03:57:15.573424: Epoch time: 17.09 s +2024-11-22 03:57:16.475594: +2024-11-22 03:57:16.475802: Epoch 3172 +2024-11-22 03:57:16.475914: Current learning rate: 0.00635 +2024-11-22 03:57:35.689721: train_loss -0.7706 +2024-11-22 03:57:35.689936: val_loss -0.7614 +2024-11-22 03:57:35.690022: Pseudo dice [0.8493] +2024-11-22 03:57:35.690105: Epoch time: 19.21 s +2024-11-22 03:57:36.960785: +2024-11-22 03:57:36.960999: Epoch 3173 +2024-11-22 03:57:36.961109: Current learning rate: 0.00635 +2024-11-22 03:57:56.273347: train_loss -0.7714 +2024-11-22 03:57:56.273603: val_loss -0.7269 +2024-11-22 03:57:56.273680: Pseudo dice [0.8465] +2024-11-22 03:57:56.273759: Epoch time: 19.31 s +2024-11-22 03:57:57.138892: +2024-11-22 03:57:57.139119: Epoch 3174 +2024-11-22 03:57:57.139233: Current learning rate: 0.00635 +2024-11-22 03:58:15.878847: train_loss -0.7893 +2024-11-22 03:58:15.879114: val_loss -0.7668 +2024-11-22 03:58:15.879192: Pseudo dice [0.8548] +2024-11-22 03:58:15.879278: Epoch time: 18.74 s +2024-11-22 03:58:16.753176: +2024-11-22 03:58:16.753397: Epoch 3175 +2024-11-22 03:58:16.753509: Current learning rate: 0.00634 +2024-11-22 03:58:36.540978: train_loss -0.7809 +2024-11-22 03:58:36.541198: val_loss -0.7573 +2024-11-22 03:58:36.541336: Pseudo dice [0.8651] +2024-11-22 03:58:36.541420: Epoch time: 19.79 s +2024-11-22 03:58:37.419922: +2024-11-22 03:58:37.420219: Epoch 3176 +2024-11-22 03:58:37.420338: Current learning rate: 0.00634 +2024-11-22 03:58:55.560519: train_loss -0.7679 +2024-11-22 03:58:55.560788: val_loss -0.7361 +2024-11-22 03:58:55.560865: Pseudo dice [0.8324] +2024-11-22 03:58:55.560940: Epoch time: 18.14 s +2024-11-22 03:58:56.427795: +2024-11-22 03:58:56.428005: Epoch 3177 +2024-11-22 03:58:56.428118: Current learning rate: 0.00634 +2024-11-22 03:59:15.715599: train_loss -0.7681 +2024-11-22 03:59:15.715819: val_loss -0.7537 +2024-11-22 03:59:15.715895: Pseudo dice [0.8306] +2024-11-22 03:59:15.715971: Epoch time: 19.29 s +2024-11-22 03:59:16.586092: +2024-11-22 03:59:16.586292: Epoch 3178 +2024-11-22 03:59:16.586404: Current learning rate: 0.00634 +2024-11-22 03:59:35.219009: train_loss -0.7833 +2024-11-22 03:59:35.219233: val_loss -0.7653 +2024-11-22 03:59:35.219309: Pseudo dice [0.8397] +2024-11-22 03:59:35.219390: Epoch time: 18.63 s +2024-11-22 03:59:36.093652: +2024-11-22 03:59:36.093868: Epoch 3179 +2024-11-22 03:59:36.093985: Current learning rate: 0.00634 +2024-11-22 03:59:54.759852: train_loss -0.7826 +2024-11-22 03:59:54.760105: val_loss -0.7784 +2024-11-22 03:59:54.760182: Pseudo dice [0.8412] +2024-11-22 03:59:54.760261: Epoch time: 18.67 s +2024-11-22 03:59:55.629618: +2024-11-22 03:59:55.629825: Epoch 3180 +2024-11-22 03:59:55.629938: Current learning rate: 0.00634 +2024-11-22 04:00:14.029073: train_loss -0.7746 +2024-11-22 04:00:14.029294: val_loss -0.7478 +2024-11-22 04:00:14.029370: Pseudo dice [0.851] +2024-11-22 04:00:14.029446: Epoch time: 18.4 s +2024-11-22 04:00:15.020938: +2024-11-22 04:00:15.021188: Epoch 3181 +2024-11-22 04:00:15.021302: Current learning rate: 0.00634 +2024-11-22 04:00:33.420335: train_loss -0.7726 +2024-11-22 04:00:33.434127: val_loss -0.7271 +2024-11-22 04:00:33.434257: Pseudo dice [0.8587] +2024-11-22 04:00:33.434338: Epoch time: 18.4 s +2024-11-22 04:00:34.420516: +2024-11-22 04:00:34.420711: Epoch 3182 +2024-11-22 04:00:34.420823: Current learning rate: 0.00634 +2024-11-22 04:00:52.796653: train_loss -0.7859 +2024-11-22 04:00:52.796895: val_loss -0.7347 +2024-11-22 04:00:52.796971: Pseudo dice [0.8439] +2024-11-22 04:00:52.797060: Epoch time: 18.38 s +2024-11-22 04:00:53.665869: +2024-11-22 04:00:53.666075: Epoch 3183 +2024-11-22 04:00:53.666187: Current learning rate: 0.00633 +2024-11-22 04:01:11.791793: train_loss -0.7794 +2024-11-22 04:01:11.792015: val_loss -0.7144 +2024-11-22 04:01:11.792096: Pseudo dice [0.8432] +2024-11-22 04:01:11.792172: Epoch time: 18.13 s +2024-11-22 04:01:12.652080: +2024-11-22 04:01:12.652283: Epoch 3184 +2024-11-22 04:01:12.652394: Current learning rate: 0.00633 +2024-11-22 04:01:31.021165: train_loss -0.7889 +2024-11-22 04:01:31.021395: val_loss -0.7309 +2024-11-22 04:01:31.021501: Pseudo dice [0.8424] +2024-11-22 04:01:31.021587: Epoch time: 18.37 s +2024-11-22 04:01:32.287938: +2024-11-22 04:01:32.288346: Epoch 3185 +2024-11-22 04:01:32.288474: Current learning rate: 0.00633 +2024-11-22 04:01:50.685444: train_loss -0.7871 +2024-11-22 04:01:50.685702: val_loss -0.7399 +2024-11-22 04:01:50.685779: Pseudo dice [0.8517] +2024-11-22 04:01:50.685865: Epoch time: 18.4 s +2024-11-22 04:01:51.553389: +2024-11-22 04:01:51.553833: Epoch 3186 +2024-11-22 04:01:51.553967: Current learning rate: 0.00633 +2024-11-22 04:02:10.171642: train_loss -0.7898 +2024-11-22 04:02:10.172729: val_loss -0.7305 +2024-11-22 04:02:10.172812: Pseudo dice [0.8235] +2024-11-22 04:02:10.172890: Epoch time: 18.62 s +2024-11-22 04:02:11.044737: +2024-11-22 04:02:11.045228: Epoch 3187 +2024-11-22 04:02:11.045373: Current learning rate: 0.00633 +2024-11-22 04:02:30.371174: train_loss -0.7887 +2024-11-22 04:02:30.371396: val_loss -0.7445 +2024-11-22 04:02:30.371469: Pseudo dice [0.8563] +2024-11-22 04:02:30.371544: Epoch time: 19.33 s +2024-11-22 04:02:31.241807: +2024-11-22 04:02:31.242228: Epoch 3188 +2024-11-22 04:02:31.242361: Current learning rate: 0.00633 +2024-11-22 04:02:50.098779: train_loss -0.7891 +2024-11-22 04:02:50.099085: val_loss -0.7195 +2024-11-22 04:02:50.099165: Pseudo dice [0.8356] +2024-11-22 04:02:50.099247: Epoch time: 18.86 s +2024-11-22 04:02:50.973492: +2024-11-22 04:02:50.973950: Epoch 3189 +2024-11-22 04:02:50.974100: Current learning rate: 0.00633 +2024-11-22 04:03:09.132579: train_loss -0.79 +2024-11-22 04:03:09.132789: val_loss -0.7295 +2024-11-22 04:03:09.132866: Pseudo dice [0.8601] +2024-11-22 04:03:09.132942: Epoch time: 18.16 s +2024-11-22 04:03:10.001864: +2024-11-22 04:03:10.002272: Epoch 3190 +2024-11-22 04:03:10.002432: Current learning rate: 0.00633 +2024-11-22 04:03:28.397432: train_loss -0.7887 +2024-11-22 04:03:28.397712: val_loss -0.7439 +2024-11-22 04:03:28.397793: Pseudo dice [0.8305] +2024-11-22 04:03:28.397872: Epoch time: 18.4 s +2024-11-22 04:03:29.270064: +2024-11-22 04:03:29.270469: Epoch 3191 +2024-11-22 04:03:29.270602: Current learning rate: 0.00633 +2024-11-22 04:03:48.051147: train_loss -0.7906 +2024-11-22 04:03:48.051361: val_loss -0.7509 +2024-11-22 04:03:48.051434: Pseudo dice [0.8416] +2024-11-22 04:03:48.051514: Epoch time: 18.78 s +2024-11-22 04:03:48.918768: +2024-11-22 04:03:48.919247: Epoch 3192 +2024-11-22 04:03:48.919380: Current learning rate: 0.00632 +2024-11-22 04:04:08.414781: train_loss -0.7967 +2024-11-22 04:04:08.415037: val_loss -0.7411 +2024-11-22 04:04:08.415116: Pseudo dice [0.8521] +2024-11-22 04:04:08.415201: Epoch time: 19.5 s +2024-11-22 04:04:09.284571: +2024-11-22 04:04:09.285008: Epoch 3193 +2024-11-22 04:04:09.285146: Current learning rate: 0.00632 +2024-11-22 04:04:28.291488: train_loss -0.7848 +2024-11-22 04:04:28.291703: val_loss -0.7383 +2024-11-22 04:04:28.291781: Pseudo dice [0.8409] +2024-11-22 04:04:28.291858: Epoch time: 19.01 s +2024-11-22 04:04:29.155581: +2024-11-22 04:04:29.156035: Epoch 3194 +2024-11-22 04:04:29.156186: Current learning rate: 0.00632 +2024-11-22 04:04:46.959810: train_loss -0.7834 +2024-11-22 04:04:46.960040: val_loss -0.751 +2024-11-22 04:04:46.960149: Pseudo dice [0.8329] +2024-11-22 04:04:46.960233: Epoch time: 17.81 s +2024-11-22 04:04:47.828198: +2024-11-22 04:04:47.828397: Epoch 3195 +2024-11-22 04:04:47.828508: Current learning rate: 0.00632 +2024-11-22 04:05:06.353955: train_loss -0.7825 +2024-11-22 04:05:06.354188: val_loss -0.7467 +2024-11-22 04:05:06.354514: Pseudo dice [0.8478] +2024-11-22 04:05:06.354642: Epoch time: 18.53 s +2024-11-22 04:05:07.611231: +2024-11-22 04:05:07.611435: Epoch 3196 +2024-11-22 04:05:07.611542: Current learning rate: 0.00632 +2024-11-22 04:05:25.376951: train_loss -0.7823 +2024-11-22 04:05:25.377227: val_loss -0.746 +2024-11-22 04:05:25.377311: Pseudo dice [0.8468] +2024-11-22 04:05:25.377394: Epoch time: 17.77 s +2024-11-22 04:05:26.241733: +2024-11-22 04:05:26.241967: Epoch 3197 +2024-11-22 04:05:26.242082: Current learning rate: 0.00632 +2024-11-22 04:05:43.328008: train_loss -0.7892 +2024-11-22 04:05:43.328239: val_loss -0.743 +2024-11-22 04:05:43.328318: Pseudo dice [0.8448] +2024-11-22 04:05:43.328396: Epoch time: 17.09 s +2024-11-22 04:05:44.226927: +2024-11-22 04:05:44.227266: Epoch 3198 +2024-11-22 04:05:44.227381: Current learning rate: 0.00632 +2024-11-22 04:06:02.455632: train_loss -0.7884 +2024-11-22 04:06:02.455862: val_loss -0.7541 +2024-11-22 04:06:02.455945: Pseudo dice [0.8453] +2024-11-22 04:06:02.456035: Epoch time: 18.23 s +2024-11-22 04:06:03.325301: +2024-11-22 04:06:03.325497: Epoch 3199 +2024-11-22 04:06:03.325688: Current learning rate: 0.00632 +2024-11-22 04:06:22.244948: train_loss -0.7902 +2024-11-22 04:06:22.245201: val_loss -0.7842 +2024-11-22 04:06:22.245276: Pseudo dice [0.8675] +2024-11-22 04:06:22.245365: Epoch time: 18.92 s +2024-11-22 04:06:22.510995: Yayy! New best EMA pseudo Dice: 0.8457 +2024-11-22 04:06:23.612671: +2024-11-22 04:06:23.612872: Epoch 3200 +2024-11-22 04:06:23.612983: Current learning rate: 0.00631 +2024-11-22 04:06:42.265000: train_loss -0.7879 +2024-11-22 04:06:42.265218: val_loss -0.7295 +2024-11-22 04:06:42.265295: Pseudo dice [0.8394] +2024-11-22 04:06:42.265387: Epoch time: 18.65 s +2024-11-22 04:06:43.135421: +2024-11-22 04:06:43.135632: Epoch 3201 +2024-11-22 04:06:43.135745: Current learning rate: 0.00631 +2024-11-22 04:07:01.865578: train_loss -0.7856 +2024-11-22 04:07:01.865808: val_loss -0.7457 +2024-11-22 04:07:01.865884: Pseudo dice [0.8367] +2024-11-22 04:07:01.865973: Epoch time: 18.73 s +2024-11-22 04:07:02.729070: +2024-11-22 04:07:02.729288: Epoch 3202 +2024-11-22 04:07:02.729401: Current learning rate: 0.00631 +2024-11-22 04:07:21.703264: train_loss -0.7834 +2024-11-22 04:07:21.703547: val_loss -0.7517 +2024-11-22 04:07:21.703625: Pseudo dice [0.8507] +2024-11-22 04:07:21.703710: Epoch time: 18.97 s +2024-11-22 04:07:22.578136: +2024-11-22 04:07:22.578407: Epoch 3203 +2024-11-22 04:07:22.578524: Current learning rate: 0.00631 +2024-11-22 04:07:42.169117: train_loss -0.7831 +2024-11-22 04:07:42.169386: val_loss -0.7325 +2024-11-22 04:07:42.169461: Pseudo dice [0.8381] +2024-11-22 04:07:42.169550: Epoch time: 19.59 s +2024-11-22 04:07:43.130511: +2024-11-22 04:07:43.130754: Epoch 3204 +2024-11-22 04:07:43.130869: Current learning rate: 0.00631 +2024-11-22 04:08:01.795649: train_loss -0.7847 +2024-11-22 04:08:01.795871: val_loss -0.7579 +2024-11-22 04:08:01.796167: Pseudo dice [0.8418] +2024-11-22 04:08:01.796251: Epoch time: 18.67 s +2024-11-22 04:08:02.659827: +2024-11-22 04:08:02.660057: Epoch 3205 +2024-11-22 04:08:02.660179: Current learning rate: 0.00631 +2024-11-22 04:08:21.571249: train_loss -0.7894 +2024-11-22 04:08:21.571478: val_loss -0.7811 +2024-11-22 04:08:21.571688: Pseudo dice [0.8544] +2024-11-22 04:08:21.571770: Epoch time: 18.91 s +2024-11-22 04:08:22.444107: +2024-11-22 04:08:22.444316: Epoch 3206 +2024-11-22 04:08:22.444428: Current learning rate: 0.00631 +2024-11-22 04:08:40.159974: train_loss -0.7846 +2024-11-22 04:08:40.160191: val_loss -0.7627 +2024-11-22 04:08:40.160264: Pseudo dice [0.8503] +2024-11-22 04:08:40.160342: Epoch time: 17.72 s +2024-11-22 04:08:41.030533: +2024-11-22 04:08:41.030737: Epoch 3207 +2024-11-22 04:08:41.030859: Current learning rate: 0.00631 +2024-11-22 04:09:01.017272: train_loss -0.7852 +2024-11-22 04:09:01.017545: val_loss -0.7505 +2024-11-22 04:09:01.017622: Pseudo dice [0.8313] +2024-11-22 04:09:01.017708: Epoch time: 19.99 s +2024-11-22 04:09:01.880034: +2024-11-22 04:09:01.880442: Epoch 3208 +2024-11-22 04:09:01.880591: Current learning rate: 0.0063 +2024-11-22 04:09:20.138945: train_loss -0.7829 +2024-11-22 04:09:20.139172: val_loss -0.7437 +2024-11-22 04:09:20.139266: Pseudo dice [0.8159] +2024-11-22 04:09:20.139340: Epoch time: 18.26 s +2024-11-22 04:09:21.119101: +2024-11-22 04:09:21.119521: Epoch 3209 +2024-11-22 04:09:21.119650: Current learning rate: 0.0063 +2024-11-22 04:09:39.025389: train_loss -0.7875 +2024-11-22 04:09:39.025607: val_loss -0.7412 +2024-11-22 04:09:39.025683: Pseudo dice [0.8298] +2024-11-22 04:09:39.030982: Epoch time: 17.91 s +2024-11-22 04:09:39.937273: +2024-11-22 04:09:39.937683: Epoch 3210 +2024-11-22 04:09:39.937815: Current learning rate: 0.0063 +2024-11-22 04:10:00.071742: train_loss -0.7885 +2024-11-22 04:10:00.072004: val_loss -0.7452 +2024-11-22 04:10:00.072080: Pseudo dice [0.8439] +2024-11-22 04:10:00.072164: Epoch time: 20.14 s +2024-11-22 04:10:00.942754: +2024-11-22 04:10:00.943205: Epoch 3211 +2024-11-22 04:10:00.943341: Current learning rate: 0.0063 +2024-11-22 04:10:20.581772: train_loss -0.791 +2024-11-22 04:10:20.581998: val_loss -0.7557 +2024-11-22 04:10:20.582076: Pseudo dice [0.8619] +2024-11-22 04:10:20.582154: Epoch time: 19.64 s +2024-11-22 04:10:21.453927: +2024-11-22 04:10:21.454338: Epoch 3212 +2024-11-22 04:10:21.454472: Current learning rate: 0.0063 +2024-11-22 04:10:39.643654: train_loss -0.7916 +2024-11-22 04:10:39.643900: val_loss -0.7456 +2024-11-22 04:10:39.643977: Pseudo dice [0.8419] +2024-11-22 04:10:39.644064: Epoch time: 18.19 s +2024-11-22 04:10:40.607181: +2024-11-22 04:10:40.607649: Epoch 3213 +2024-11-22 04:10:40.607789: Current learning rate: 0.0063 +2024-11-22 04:11:00.056348: train_loss -0.7866 +2024-11-22 04:11:00.056568: val_loss -0.7493 +2024-11-22 04:11:00.056648: Pseudo dice [0.8357] +2024-11-22 04:11:00.056801: Epoch time: 19.45 s +2024-11-22 04:11:00.924397: +2024-11-22 04:11:00.924812: Epoch 3214 +2024-11-22 04:11:00.924951: Current learning rate: 0.0063 +2024-11-22 04:11:19.250544: train_loss -0.7865 +2024-11-22 04:11:19.250793: val_loss -0.7273 +2024-11-22 04:11:19.250869: Pseudo dice [0.8357] +2024-11-22 04:11:19.250950: Epoch time: 18.33 s +2024-11-22 04:11:20.127372: +2024-11-22 04:11:20.127778: Epoch 3215 +2024-11-22 04:11:20.127911: Current learning rate: 0.0063 +2024-11-22 04:11:38.876502: train_loss -0.7881 +2024-11-22 04:11:38.876719: val_loss -0.7667 +2024-11-22 04:11:38.876795: Pseudo dice [0.8405] +2024-11-22 04:11:38.876873: Epoch time: 18.75 s +2024-11-22 04:11:39.745389: +2024-11-22 04:11:39.745902: Epoch 3216 +2024-11-22 04:11:39.746042: Current learning rate: 0.0063 +2024-11-22 04:11:58.450338: train_loss -0.7867 +2024-11-22 04:11:58.450565: val_loss -0.7521 +2024-11-22 04:11:58.450641: Pseudo dice [0.848] +2024-11-22 04:11:58.450719: Epoch time: 18.71 s +2024-11-22 04:11:59.319469: +2024-11-22 04:11:59.319897: Epoch 3217 +2024-11-22 04:11:59.320045: Current learning rate: 0.00629 +2024-11-22 04:12:17.917522: train_loss -0.7843 +2024-11-22 04:12:17.917762: val_loss -0.7135 +2024-11-22 04:12:17.917841: Pseudo dice [0.8267] +2024-11-22 04:12:17.917925: Epoch time: 18.6 s +2024-11-22 04:12:18.908956: +2024-11-22 04:12:18.909183: Epoch 3218 +2024-11-22 04:12:18.909297: Current learning rate: 0.00629 +2024-11-22 04:12:38.224575: train_loss -0.7782 +2024-11-22 04:12:38.224816: val_loss -0.7202 +2024-11-22 04:12:38.224890: Pseudo dice [0.8363] +2024-11-22 04:12:38.224971: Epoch time: 19.32 s +2024-11-22 04:12:39.481840: +2024-11-22 04:12:39.482280: Epoch 3219 +2024-11-22 04:12:39.482417: Current learning rate: 0.00629 +2024-11-22 04:12:58.171618: train_loss -0.7838 +2024-11-22 04:12:58.171846: val_loss -0.7462 +2024-11-22 04:12:58.171948: Pseudo dice [0.849] +2024-11-22 04:12:58.172076: Epoch time: 18.69 s +2024-11-22 04:12:59.046775: +2024-11-22 04:12:59.047216: Epoch 3220 +2024-11-22 04:12:59.047347: Current learning rate: 0.00629 +2024-11-22 04:13:18.277436: train_loss -0.7793 +2024-11-22 04:13:18.278559: val_loss -0.731 +2024-11-22 04:13:18.278657: Pseudo dice [0.8476] +2024-11-22 04:13:18.278743: Epoch time: 19.23 s +2024-11-22 04:13:19.152420: +2024-11-22 04:13:19.152937: Epoch 3221 +2024-11-22 04:13:19.153073: Current learning rate: 0.00629 +2024-11-22 04:13:38.844913: train_loss -0.7808 +2024-11-22 04:13:38.845160: val_loss -0.7467 +2024-11-22 04:13:38.845235: Pseudo dice [0.8485] +2024-11-22 04:13:38.845321: Epoch time: 19.69 s +2024-11-22 04:13:39.718406: +2024-11-22 04:13:39.718877: Epoch 3222 +2024-11-22 04:13:39.719019: Current learning rate: 0.00629 +2024-11-22 04:13:57.116570: train_loss -0.7819 +2024-11-22 04:13:57.116786: val_loss -0.7396 +2024-11-22 04:13:57.116858: Pseudo dice [0.8475] +2024-11-22 04:13:57.116932: Epoch time: 17.4 s +2024-11-22 04:13:57.982110: +2024-11-22 04:13:57.982597: Epoch 3223 +2024-11-22 04:13:57.982733: Current learning rate: 0.00629 +2024-11-22 04:14:16.473851: train_loss -0.7818 +2024-11-22 04:14:16.474075: val_loss -0.7406 +2024-11-22 04:14:16.474152: Pseudo dice [0.8515] +2024-11-22 04:14:16.474227: Epoch time: 18.49 s +2024-11-22 04:14:17.344328: +2024-11-22 04:14:17.344737: Epoch 3224 +2024-11-22 04:14:17.344870: Current learning rate: 0.00629 +2024-11-22 04:14:36.134135: train_loss -0.7748 +2024-11-22 04:14:36.134353: val_loss -0.7358 +2024-11-22 04:14:36.134426: Pseudo dice [0.834] +2024-11-22 04:14:36.134505: Epoch time: 18.79 s +2024-11-22 04:14:37.000201: +2024-11-22 04:14:37.000641: Epoch 3225 +2024-11-22 04:14:37.000773: Current learning rate: 0.00628 +2024-11-22 04:14:55.505712: train_loss -0.7815 +2024-11-22 04:14:55.505969: val_loss -0.7376 +2024-11-22 04:14:55.506054: Pseudo dice [0.8171] +2024-11-22 04:14:55.506140: Epoch time: 18.51 s +2024-11-22 04:14:56.445816: +2024-11-22 04:14:56.446261: Epoch 3226 +2024-11-22 04:14:56.446396: Current learning rate: 0.00628 +2024-11-22 04:15:15.464857: train_loss -0.7862 +2024-11-22 04:15:15.465081: val_loss -0.7457 +2024-11-22 04:15:15.465158: Pseudo dice [0.8413] +2024-11-22 04:15:15.465237: Epoch time: 19.02 s +2024-11-22 04:15:16.335591: +2024-11-22 04:15:16.336036: Epoch 3227 +2024-11-22 04:15:16.336166: Current learning rate: 0.00628 +2024-11-22 04:15:34.939938: train_loss -0.7871 +2024-11-22 04:15:34.940174: val_loss -0.743 +2024-11-22 04:15:34.940248: Pseudo dice [0.828] +2024-11-22 04:15:34.940328: Epoch time: 18.61 s +2024-11-22 04:15:35.807033: +2024-11-22 04:15:35.807456: Epoch 3228 +2024-11-22 04:15:35.807595: Current learning rate: 0.00628 +2024-11-22 04:15:54.155689: train_loss -0.7807 +2024-11-22 04:15:54.155936: val_loss -0.7323 +2024-11-22 04:15:54.158206: Pseudo dice [0.8471] +2024-11-22 04:15:54.158368: Epoch time: 18.35 s +2024-11-22 04:15:55.113360: +2024-11-22 04:15:55.113554: Epoch 3229 +2024-11-22 04:15:55.113663: Current learning rate: 0.00628 +2024-11-22 04:16:13.960865: train_loss -0.7778 +2024-11-22 04:16:13.961080: val_loss -0.7453 +2024-11-22 04:16:13.961156: Pseudo dice [0.8414] +2024-11-22 04:16:13.961236: Epoch time: 18.85 s +2024-11-22 04:16:14.823332: +2024-11-22 04:16:14.823561: Epoch 3230 +2024-11-22 04:16:14.823678: Current learning rate: 0.00628 +2024-11-22 04:16:33.203077: train_loss -0.7846 +2024-11-22 04:16:33.205582: val_loss -0.7426 +2024-11-22 04:16:33.205725: Pseudo dice [0.839] +2024-11-22 04:16:33.209775: Epoch time: 18.38 s +2024-11-22 04:16:34.080755: +2024-11-22 04:16:34.080966: Epoch 3231 +2024-11-22 04:16:34.081087: Current learning rate: 0.00628 +2024-11-22 04:16:52.819989: train_loss -0.7896 +2024-11-22 04:16:52.820485: val_loss -0.7391 +2024-11-22 04:16:52.820586: Pseudo dice [0.8325] +2024-11-22 04:16:52.820669: Epoch time: 18.74 s +2024-11-22 04:16:53.780556: +2024-11-22 04:16:53.781002: Epoch 3232 +2024-11-22 04:16:53.781140: Current learning rate: 0.00628 +2024-11-22 04:17:11.784085: train_loss -0.7873 +2024-11-22 04:17:11.786523: val_loss -0.7582 +2024-11-22 04:17:11.786611: Pseudo dice [0.8232] +2024-11-22 04:17:11.786692: Epoch time: 18.0 s +2024-11-22 04:17:12.754397: +2024-11-22 04:17:12.754827: Epoch 3233 +2024-11-22 04:17:12.754959: Current learning rate: 0.00628 +2024-11-22 04:17:31.114032: train_loss -0.7886 +2024-11-22 04:17:31.114248: val_loss -0.7594 +2024-11-22 04:17:31.114327: Pseudo dice [0.8554] +2024-11-22 04:17:31.114403: Epoch time: 18.36 s +2024-11-22 04:17:31.982499: +2024-11-22 04:17:31.983061: Epoch 3234 +2024-11-22 04:17:31.983197: Current learning rate: 0.00627 +2024-11-22 04:17:50.415352: train_loss -0.7925 +2024-11-22 04:17:50.415568: val_loss -0.7607 +2024-11-22 04:17:50.415642: Pseudo dice [0.845] +2024-11-22 04:17:50.415720: Epoch time: 18.43 s +2024-11-22 04:17:51.287894: +2024-11-22 04:17:51.288359: Epoch 3235 +2024-11-22 04:17:51.288492: Current learning rate: 0.00627 +2024-11-22 04:18:09.792038: train_loss -0.785 +2024-11-22 04:18:09.792267: val_loss -0.7459 +2024-11-22 04:18:09.792345: Pseudo dice [0.8324] +2024-11-22 04:18:09.792429: Epoch time: 18.5 s +2024-11-22 04:18:10.737069: +2024-11-22 04:18:10.737473: Epoch 3236 +2024-11-22 04:18:10.737608: Current learning rate: 0.00627 +2024-11-22 04:18:29.000141: train_loss -0.7956 +2024-11-22 04:18:29.000459: val_loss -0.714 +2024-11-22 04:18:29.000539: Pseudo dice [0.823] +2024-11-22 04:18:29.000618: Epoch time: 18.26 s +2024-11-22 04:18:29.867093: +2024-11-22 04:18:29.867590: Epoch 3237 +2024-11-22 04:18:29.867726: Current learning rate: 0.00627 +2024-11-22 04:18:48.395171: train_loss -0.788 +2024-11-22 04:18:48.395390: val_loss -0.7217 +2024-11-22 04:18:48.395468: Pseudo dice [0.8166] +2024-11-22 04:18:48.395566: Epoch time: 18.53 s +2024-11-22 04:18:49.316059: +2024-11-22 04:18:49.316465: Epoch 3238 +2024-11-22 04:18:49.316598: Current learning rate: 0.00627 +2024-11-22 04:19:08.843568: train_loss -0.7837 +2024-11-22 04:19:08.843784: val_loss -0.7304 +2024-11-22 04:19:08.843861: Pseudo dice [0.8166] +2024-11-22 04:19:08.843936: Epoch time: 19.53 s +2024-11-22 04:19:09.719171: +2024-11-22 04:19:09.719589: Epoch 3239 +2024-11-22 04:19:09.719729: Current learning rate: 0.00627 +2024-11-22 04:19:27.878308: train_loss -0.7738 +2024-11-22 04:19:27.878569: val_loss -0.7319 +2024-11-22 04:19:27.878646: Pseudo dice [0.8296] +2024-11-22 04:19:27.878730: Epoch time: 18.16 s +2024-11-22 04:19:28.743637: +2024-11-22 04:19:28.744087: Epoch 3240 +2024-11-22 04:19:28.744232: Current learning rate: 0.00627 +2024-11-22 04:19:47.521388: train_loss -0.7898 +2024-11-22 04:19:47.521617: val_loss -0.7311 +2024-11-22 04:19:47.521697: Pseudo dice [0.8297] +2024-11-22 04:19:47.521778: Epoch time: 18.78 s +2024-11-22 04:19:48.388443: +2024-11-22 04:19:48.388879: Epoch 3241 +2024-11-22 04:19:48.389029: Current learning rate: 0.00627 +2024-11-22 04:20:07.512925: train_loss -0.7921 +2024-11-22 04:20:07.513153: val_loss -0.7284 +2024-11-22 04:20:07.513230: Pseudo dice [0.832] +2024-11-22 04:20:07.513309: Epoch time: 19.13 s +2024-11-22 04:20:08.869778: +2024-11-22 04:20:08.870231: Epoch 3242 +2024-11-22 04:20:08.870369: Current learning rate: 0.00626 +2024-11-22 04:20:27.063374: train_loss -0.7921 +2024-11-22 04:20:27.063622: val_loss -0.7467 +2024-11-22 04:20:27.063698: Pseudo dice [0.8314] +2024-11-22 04:20:27.063782: Epoch time: 18.19 s +2024-11-22 04:20:28.010434: +2024-11-22 04:20:28.010884: Epoch 3243 +2024-11-22 04:20:28.011034: Current learning rate: 0.00626 +2024-11-22 04:20:46.341712: train_loss -0.7959 +2024-11-22 04:20:46.341944: val_loss -0.7624 +2024-11-22 04:20:46.342031: Pseudo dice [0.87] +2024-11-22 04:20:46.342107: Epoch time: 18.33 s +2024-11-22 04:20:47.261279: +2024-11-22 04:20:47.261686: Epoch 3244 +2024-11-22 04:20:47.261816: Current learning rate: 0.00626 +2024-11-22 04:21:06.424616: train_loss -0.7774 +2024-11-22 04:21:06.424846: val_loss -0.7568 +2024-11-22 04:21:06.427141: Pseudo dice [0.821] +2024-11-22 04:21:06.427247: Epoch time: 19.16 s +2024-11-22 04:21:07.302246: +2024-11-22 04:21:07.302668: Epoch 3245 +2024-11-22 04:21:07.302809: Current learning rate: 0.00626 +2024-11-22 04:21:25.708482: train_loss -0.7834 +2024-11-22 04:21:25.708734: val_loss -0.737 +2024-11-22 04:21:25.708809: Pseudo dice [0.835] +2024-11-22 04:21:25.708898: Epoch time: 18.41 s +2024-11-22 04:21:26.581731: +2024-11-22 04:21:26.582166: Epoch 3246 +2024-11-22 04:21:26.582303: Current learning rate: 0.00626 +2024-11-22 04:21:45.773115: train_loss -0.7808 +2024-11-22 04:21:45.773342: val_loss -0.7383 +2024-11-22 04:21:45.773423: Pseudo dice [0.8581] +2024-11-22 04:21:45.773498: Epoch time: 19.19 s +2024-11-22 04:21:46.642775: +2024-11-22 04:21:46.643219: Epoch 3247 +2024-11-22 04:21:46.643358: Current learning rate: 0.00626 +2024-11-22 04:22:03.945451: train_loss -0.7864 +2024-11-22 04:22:03.945665: val_loss -0.7283 +2024-11-22 04:22:03.945747: Pseudo dice [0.8486] +2024-11-22 04:22:03.945828: Epoch time: 17.3 s +2024-11-22 04:22:04.815178: +2024-11-22 04:22:04.815584: Epoch 3248 +2024-11-22 04:22:04.815714: Current learning rate: 0.00626 +2024-11-22 04:22:23.699583: train_loss -0.7926 +2024-11-22 04:22:23.699804: val_loss -0.7516 +2024-11-22 04:22:23.699883: Pseudo dice [0.8437] +2024-11-22 04:22:23.699963: Epoch time: 18.89 s +2024-11-22 04:22:24.616710: +2024-11-22 04:22:24.617135: Epoch 3249 +2024-11-22 04:22:24.617270: Current learning rate: 0.00626 +2024-11-22 04:22:42.693618: train_loss -0.7843 +2024-11-22 04:22:42.693861: val_loss -0.7592 +2024-11-22 04:22:42.693940: Pseudo dice [0.8393] +2024-11-22 04:22:42.694031: Epoch time: 18.08 s +2024-11-22 04:22:43.894492: +2024-11-22 04:22:43.894892: Epoch 3250 +2024-11-22 04:22:43.895036: Current learning rate: 0.00626 +2024-11-22 04:23:02.401575: train_loss -0.7906 +2024-11-22 04:23:02.401803: val_loss -0.7436 +2024-11-22 04:23:02.401881: Pseudo dice [0.8351] +2024-11-22 04:23:02.401962: Epoch time: 18.51 s +2024-11-22 04:23:03.269792: +2024-11-22 04:23:03.270216: Epoch 3251 +2024-11-22 04:23:03.270353: Current learning rate: 0.00625 +2024-11-22 04:23:21.435154: train_loss -0.767 +2024-11-22 04:23:21.435389: val_loss -0.7267 +2024-11-22 04:23:21.435469: Pseudo dice [0.8467] +2024-11-22 04:23:21.435550: Epoch time: 18.17 s +2024-11-22 04:23:22.408926: +2024-11-22 04:23:22.409425: Epoch 3252 +2024-11-22 04:23:22.409564: Current learning rate: 0.00625 +2024-11-22 04:23:40.195065: train_loss -0.7861 +2024-11-22 04:23:40.195298: val_loss -0.7324 +2024-11-22 04:23:40.195374: Pseudo dice [0.8496] +2024-11-22 04:23:40.195464: Epoch time: 17.79 s +2024-11-22 04:23:41.456239: +2024-11-22 04:23:41.456472: Epoch 3253 +2024-11-22 04:23:41.456579: Current learning rate: 0.00625 +2024-11-22 04:23:59.538939: train_loss -0.7868 +2024-11-22 04:23:59.539196: val_loss -0.7626 +2024-11-22 04:23:59.539276: Pseudo dice [0.8465] +2024-11-22 04:23:59.539359: Epoch time: 18.08 s +2024-11-22 04:24:00.405356: +2024-11-22 04:24:00.405571: Epoch 3254 +2024-11-22 04:24:00.405686: Current learning rate: 0.00625 +2024-11-22 04:24:19.643757: train_loss -0.7902 +2024-11-22 04:24:19.643978: val_loss -0.7276 +2024-11-22 04:24:19.644061: Pseudo dice [0.8279] +2024-11-22 04:24:19.644136: Epoch time: 19.24 s +2024-11-22 04:24:20.593410: +2024-11-22 04:24:20.593607: Epoch 3255 +2024-11-22 04:24:20.593717: Current learning rate: 0.00625 +2024-11-22 04:24:39.367008: train_loss -0.7836 +2024-11-22 04:24:39.367308: val_loss -0.7823 +2024-11-22 04:24:39.367394: Pseudo dice [0.8543] +2024-11-22 04:24:39.367474: Epoch time: 18.77 s +2024-11-22 04:24:40.243156: +2024-11-22 04:24:40.243361: Epoch 3256 +2024-11-22 04:24:40.243471: Current learning rate: 0.00625 +2024-11-22 04:24:58.242245: train_loss -0.7928 +2024-11-22 04:24:58.242752: val_loss -0.7346 +2024-11-22 04:24:58.242841: Pseudo dice [0.8269] +2024-11-22 04:24:58.242921: Epoch time: 18.0 s +2024-11-22 04:24:59.221355: +2024-11-22 04:24:59.221583: Epoch 3257 +2024-11-22 04:24:59.221697: Current learning rate: 0.00625 +2024-11-22 04:25:17.662963: train_loss -0.7892 +2024-11-22 04:25:17.663237: val_loss -0.733 +2024-11-22 04:25:17.663313: Pseudo dice [0.8416] +2024-11-22 04:25:17.663390: Epoch time: 18.44 s +2024-11-22 04:25:18.542589: +2024-11-22 04:25:18.542815: Epoch 3258 +2024-11-22 04:25:18.542931: Current learning rate: 0.00625 +2024-11-22 04:25:37.753793: train_loss -0.7902 +2024-11-22 04:25:37.754020: val_loss -0.7549 +2024-11-22 04:25:37.754094: Pseudo dice [0.8542] +2024-11-22 04:25:37.754175: Epoch time: 19.21 s +2024-11-22 04:25:38.630786: +2024-11-22 04:25:38.631024: Epoch 3259 +2024-11-22 04:25:38.631139: Current learning rate: 0.00624 +2024-11-22 04:25:57.435069: train_loss -0.7895 +2024-11-22 04:25:57.435300: val_loss -0.7488 +2024-11-22 04:25:57.435381: Pseudo dice [0.8262] +2024-11-22 04:25:57.435463: Epoch time: 18.81 s +2024-11-22 04:25:58.562839: +2024-11-22 04:25:58.563066: Epoch 3260 +2024-11-22 04:25:58.563177: Current learning rate: 0.00624 +2024-11-22 04:26:17.034556: train_loss -0.7848 +2024-11-22 04:26:17.034803: val_loss -0.7283 +2024-11-22 04:26:17.034881: Pseudo dice [0.8389] +2024-11-22 04:26:17.034965: Epoch time: 18.47 s +2024-11-22 04:26:17.901291: +2024-11-22 04:26:17.901495: Epoch 3261 +2024-11-22 04:26:17.901603: Current learning rate: 0.00624 +2024-11-22 04:26:36.192869: train_loss -0.7724 +2024-11-22 04:26:36.193148: val_loss -0.7563 +2024-11-22 04:26:36.193322: Pseudo dice [0.8539] +2024-11-22 04:26:36.193408: Epoch time: 18.29 s +2024-11-22 04:26:37.158941: +2024-11-22 04:26:37.159211: Epoch 3262 +2024-11-22 04:26:37.159320: Current learning rate: 0.00624 +2024-11-22 04:26:56.397322: train_loss -0.7832 +2024-11-22 04:26:56.397552: val_loss -0.7291 +2024-11-22 04:26:56.397630: Pseudo dice [0.8392] +2024-11-22 04:26:56.397708: Epoch time: 19.24 s +2024-11-22 04:26:57.279429: +2024-11-22 04:26:57.279672: Epoch 3263 +2024-11-22 04:26:57.279782: Current learning rate: 0.00624 +2024-11-22 04:27:15.421783: train_loss -0.7835 +2024-11-22 04:27:15.423862: val_loss -0.7644 +2024-11-22 04:27:15.423949: Pseudo dice [0.8509] +2024-11-22 04:27:15.424101: Epoch time: 18.14 s +2024-11-22 04:27:16.445649: +2024-11-22 04:27:16.445856: Epoch 3264 +2024-11-22 04:27:16.445968: Current learning rate: 0.00624 +2024-11-22 04:27:34.001239: train_loss -0.7862 +2024-11-22 04:27:34.001471: val_loss -0.7669 +2024-11-22 04:27:34.001551: Pseudo dice [0.8363] +2024-11-22 04:27:34.001629: Epoch time: 17.56 s +2024-11-22 04:27:35.289983: +2024-11-22 04:27:35.290196: Epoch 3265 +2024-11-22 04:27:35.290309: Current learning rate: 0.00624 +2024-11-22 04:27:54.016756: train_loss -0.7844 +2024-11-22 04:27:54.017038: val_loss -0.7308 +2024-11-22 04:27:54.017123: Pseudo dice [0.8366] +2024-11-22 04:27:54.017204: Epoch time: 18.73 s +2024-11-22 04:27:54.881224: +2024-11-22 04:27:54.881467: Epoch 3266 +2024-11-22 04:27:54.881595: Current learning rate: 0.00624 +2024-11-22 04:28:14.168677: train_loss -0.7784 +2024-11-22 04:28:14.168932: val_loss -0.7403 +2024-11-22 04:28:14.169015: Pseudo dice [0.8472] +2024-11-22 04:28:14.169102: Epoch time: 19.29 s +2024-11-22 04:28:15.038784: +2024-11-22 04:28:15.038983: Epoch 3267 +2024-11-22 04:28:15.039098: Current learning rate: 0.00624 +2024-11-22 04:28:33.717945: train_loss -0.7911 +2024-11-22 04:28:33.718188: val_loss -0.754 +2024-11-22 04:28:33.718264: Pseudo dice [0.8235] +2024-11-22 04:28:33.718340: Epoch time: 18.68 s +2024-11-22 04:28:34.603174: +2024-11-22 04:28:34.603447: Epoch 3268 +2024-11-22 04:28:34.603563: Current learning rate: 0.00623 +2024-11-22 04:28:53.286669: train_loss -0.7887 +2024-11-22 04:28:53.286894: val_loss -0.75 +2024-11-22 04:28:53.286969: Pseudo dice [0.8314] +2024-11-22 04:28:53.287052: Epoch time: 18.68 s +2024-11-22 04:28:54.178172: +2024-11-22 04:28:54.178386: Epoch 3269 +2024-11-22 04:28:54.178494: Current learning rate: 0.00623 +2024-11-22 04:29:13.270721: train_loss -0.788 +2024-11-22 04:29:13.270962: val_loss -0.7598 +2024-11-22 04:29:13.271055: Pseudo dice [0.8463] +2024-11-22 04:29:13.271154: Epoch time: 19.09 s +2024-11-22 04:29:14.196451: +2024-11-22 04:29:14.196648: Epoch 3270 +2024-11-22 04:29:14.196762: Current learning rate: 0.00623 +2024-11-22 04:29:32.934330: train_loss -0.7821 +2024-11-22 04:29:32.934580: val_loss -0.759 +2024-11-22 04:29:32.934658: Pseudo dice [0.8499] +2024-11-22 04:29:32.936990: Epoch time: 18.74 s +2024-11-22 04:29:34.006885: +2024-11-22 04:29:34.007120: Epoch 3271 +2024-11-22 04:29:34.007231: Current learning rate: 0.00623 +2024-11-22 04:29:52.318125: train_loss -0.7841 +2024-11-22 04:29:52.318342: val_loss -0.7352 +2024-11-22 04:29:52.318418: Pseudo dice [0.8395] +2024-11-22 04:29:52.318496: Epoch time: 18.31 s +2024-11-22 04:29:53.194527: +2024-11-22 04:29:53.194740: Epoch 3272 +2024-11-22 04:29:53.194854: Current learning rate: 0.00623 +2024-11-22 04:30:11.989370: train_loss -0.7924 +2024-11-22 04:30:11.989615: val_loss -0.7306 +2024-11-22 04:30:11.989697: Pseudo dice [0.8214] +2024-11-22 04:30:11.989781: Epoch time: 18.8 s +2024-11-22 04:30:12.866196: +2024-11-22 04:30:12.866385: Epoch 3273 +2024-11-22 04:30:12.866496: Current learning rate: 0.00623 +2024-11-22 04:30:30.412754: train_loss -0.7857 +2024-11-22 04:30:30.412983: val_loss -0.7312 +2024-11-22 04:30:30.413069: Pseudo dice [0.8296] +2024-11-22 04:30:30.413156: Epoch time: 17.55 s +2024-11-22 04:30:31.287831: +2024-11-22 04:30:31.288040: Epoch 3274 +2024-11-22 04:30:31.288157: Current learning rate: 0.00623 +2024-11-22 04:30:49.162677: train_loss -0.7965 +2024-11-22 04:30:49.162935: val_loss -0.7672 +2024-11-22 04:30:49.163089: Pseudo dice [0.8433] +2024-11-22 04:30:49.163171: Epoch time: 17.88 s +2024-11-22 04:30:50.032115: +2024-11-22 04:30:50.032371: Epoch 3275 +2024-11-22 04:30:50.032483: Current learning rate: 0.00623 +2024-11-22 04:31:09.209257: train_loss -0.7942 +2024-11-22 04:31:09.209500: val_loss -0.7515 +2024-11-22 04:31:09.209579: Pseudo dice [0.8691] +2024-11-22 04:31:09.209657: Epoch time: 19.18 s +2024-11-22 04:31:10.074862: +2024-11-22 04:31:10.075284: Epoch 3276 +2024-11-22 04:31:10.075415: Current learning rate: 0.00622 +2024-11-22 04:31:28.680644: train_loss -0.7884 +2024-11-22 04:31:28.680905: val_loss -0.7468 +2024-11-22 04:31:28.680981: Pseudo dice [0.8504] +2024-11-22 04:31:28.681074: Epoch time: 18.61 s +2024-11-22 04:31:29.545468: +2024-11-22 04:31:29.545702: Epoch 3277 +2024-11-22 04:31:29.545830: Current learning rate: 0.00622 +2024-11-22 04:31:47.548886: train_loss -0.7922 +2024-11-22 04:31:47.549134: val_loss -0.7706 +2024-11-22 04:31:47.549209: Pseudo dice [0.8491] +2024-11-22 04:31:47.549285: Epoch time: 18.0 s +2024-11-22 04:31:48.423852: +2024-11-22 04:31:48.424099: Epoch 3278 +2024-11-22 04:31:48.424213: Current learning rate: 0.00622 +2024-11-22 04:32:06.053301: train_loss -0.7771 +2024-11-22 04:32:06.053525: val_loss -0.7182 +2024-11-22 04:32:06.053600: Pseudo dice [0.8228] +2024-11-22 04:32:06.053686: Epoch time: 17.63 s +2024-11-22 04:32:06.923836: +2024-11-22 04:32:06.924048: Epoch 3279 +2024-11-22 04:32:06.924164: Current learning rate: 0.00622 +2024-11-22 04:32:25.637332: train_loss -0.7914 +2024-11-22 04:32:25.637562: val_loss -0.755 +2024-11-22 04:32:25.637637: Pseudo dice [0.8439] +2024-11-22 04:32:25.637715: Epoch time: 18.71 s +2024-11-22 04:32:26.595315: +2024-11-22 04:32:26.595551: Epoch 3280 +2024-11-22 04:32:26.595674: Current learning rate: 0.00622 +2024-11-22 04:32:46.056250: train_loss -0.781 +2024-11-22 04:32:46.056477: val_loss -0.7349 +2024-11-22 04:32:46.056553: Pseudo dice [0.8376] +2024-11-22 04:32:46.061784: Epoch time: 19.46 s +2024-11-22 04:32:47.078646: +2024-11-22 04:32:47.078876: Epoch 3281 +2024-11-22 04:32:47.079001: Current learning rate: 0.00622 +2024-11-22 04:33:05.231079: train_loss -0.7828 +2024-11-22 04:33:05.231375: val_loss -0.7555 +2024-11-22 04:33:05.231454: Pseudo dice [0.8274] +2024-11-22 04:33:05.231539: Epoch time: 18.15 s +2024-11-22 04:33:06.142664: +2024-11-22 04:33:06.142898: Epoch 3282 +2024-11-22 04:33:06.143010: Current learning rate: 0.00622 +2024-11-22 04:33:25.958373: train_loss -0.7811 +2024-11-22 04:33:25.958824: val_loss -0.7389 +2024-11-22 04:33:25.958912: Pseudo dice [0.8518] +2024-11-22 04:33:25.958999: Epoch time: 19.82 s +2024-11-22 04:33:26.824814: +2024-11-22 04:33:26.825129: Epoch 3283 +2024-11-22 04:33:26.825247: Current learning rate: 0.00622 +2024-11-22 04:33:45.566037: train_loss -0.7832 +2024-11-22 04:33:45.566253: val_loss -0.7444 +2024-11-22 04:33:45.566326: Pseudo dice [0.8192] +2024-11-22 04:33:45.566407: Epoch time: 18.74 s +2024-11-22 04:33:46.438294: +2024-11-22 04:33:46.438508: Epoch 3284 +2024-11-22 04:33:46.438639: Current learning rate: 0.00621 +2024-11-22 04:34:04.937943: train_loss -0.782 +2024-11-22 04:34:04.938274: val_loss -0.7487 +2024-11-22 04:34:04.938352: Pseudo dice [0.8577] +2024-11-22 04:34:04.938437: Epoch time: 18.5 s +2024-11-22 04:34:05.910232: +2024-11-22 04:34:05.910491: Epoch 3285 +2024-11-22 04:34:05.910609: Current learning rate: 0.00621 +2024-11-22 04:34:25.588008: train_loss -0.7811 +2024-11-22 04:34:25.588226: val_loss -0.7366 +2024-11-22 04:34:25.588304: Pseudo dice [0.8369] +2024-11-22 04:34:25.588381: Epoch time: 19.68 s +2024-11-22 04:34:26.454422: +2024-11-22 04:34:26.454672: Epoch 3286 +2024-11-22 04:34:26.454794: Current learning rate: 0.00621 +2024-11-22 04:34:45.387406: train_loss -0.777 +2024-11-22 04:34:45.387630: val_loss -0.7283 +2024-11-22 04:34:45.387706: Pseudo dice [0.8306] +2024-11-22 04:34:45.387785: Epoch time: 18.93 s +2024-11-22 04:34:46.254320: +2024-11-22 04:34:46.254538: Epoch 3287 +2024-11-22 04:34:46.254650: Current learning rate: 0.00621 +2024-11-22 04:35:06.616172: train_loss -0.7713 +2024-11-22 04:35:06.616416: val_loss -0.7085 +2024-11-22 04:35:06.616492: Pseudo dice [0.8165] +2024-11-22 04:35:06.616578: Epoch time: 20.36 s +2024-11-22 04:35:07.864364: +2024-11-22 04:35:07.864586: Epoch 3288 +2024-11-22 04:35:07.864698: Current learning rate: 0.00621 +2024-11-22 04:35:27.029218: train_loss -0.7716 +2024-11-22 04:35:27.029448: val_loss -0.7289 +2024-11-22 04:35:27.029526: Pseudo dice [0.8443] +2024-11-22 04:35:27.029606: Epoch time: 19.17 s +2024-11-22 04:35:27.900774: +2024-11-22 04:35:27.901104: Epoch 3289 +2024-11-22 04:35:27.901223: Current learning rate: 0.00621 +2024-11-22 04:35:45.899652: train_loss -0.7846 +2024-11-22 04:35:45.902123: val_loss -0.7281 +2024-11-22 04:35:45.902217: Pseudo dice [0.8387] +2024-11-22 04:35:45.902294: Epoch time: 18.0 s +2024-11-22 04:35:46.888209: +2024-11-22 04:35:46.888446: Epoch 3290 +2024-11-22 04:35:46.888558: Current learning rate: 0.00621 +2024-11-22 04:36:06.222780: train_loss -0.7916 +2024-11-22 04:36:06.223100: val_loss -0.7777 +2024-11-22 04:36:06.223184: Pseudo dice [0.8482] +2024-11-22 04:36:06.223271: Epoch time: 19.34 s +2024-11-22 04:36:07.103101: +2024-11-22 04:36:07.103344: Epoch 3291 +2024-11-22 04:36:07.103466: Current learning rate: 0.00621 +2024-11-22 04:36:26.505457: train_loss -0.7605 +2024-11-22 04:36:26.505682: val_loss -0.7342 +2024-11-22 04:36:26.505755: Pseudo dice [0.8353] +2024-11-22 04:36:26.505831: Epoch time: 19.4 s +2024-11-22 04:36:27.389587: +2024-11-22 04:36:27.389927: Epoch 3292 +2024-11-22 04:36:27.390045: Current learning rate: 0.00621 +2024-11-22 04:36:46.866030: train_loss -0.7759 +2024-11-22 04:36:46.866273: val_loss -0.7335 +2024-11-22 04:36:46.866350: Pseudo dice [0.8558] +2024-11-22 04:36:46.866434: Epoch time: 19.47 s +2024-11-22 04:36:47.746829: +2024-11-22 04:36:47.747077: Epoch 3293 +2024-11-22 04:36:47.747186: Current learning rate: 0.0062 +2024-11-22 04:37:06.581858: train_loss -0.7805 +2024-11-22 04:37:06.582078: val_loss -0.7488 +2024-11-22 04:37:06.582170: Pseudo dice [0.8189] +2024-11-22 04:37:06.582249: Epoch time: 18.84 s +2024-11-22 04:37:07.429852: +2024-11-22 04:37:07.430040: Epoch 3294 +2024-11-22 04:37:07.430139: Current learning rate: 0.0062 +2024-11-22 04:37:25.982318: train_loss -0.7798 +2024-11-22 04:37:25.982540: val_loss -0.7433 +2024-11-22 04:37:25.982616: Pseudo dice [0.8384] +2024-11-22 04:37:25.982695: Epoch time: 18.55 s +2024-11-22 04:37:26.882466: +2024-11-22 04:37:26.882681: Epoch 3295 +2024-11-22 04:37:26.882785: Current learning rate: 0.0062 +2024-11-22 04:37:45.240901: train_loss -0.7757 +2024-11-22 04:37:45.241170: val_loss -0.7626 +2024-11-22 04:37:45.241246: Pseudo dice [0.838] +2024-11-22 04:37:45.241330: Epoch time: 18.36 s +2024-11-22 04:37:46.117857: +2024-11-22 04:37:46.118152: Epoch 3296 +2024-11-22 04:37:46.118263: Current learning rate: 0.0062 +2024-11-22 04:38:04.683066: train_loss -0.7709 +2024-11-22 04:38:04.683279: val_loss -0.7136 +2024-11-22 04:38:04.683355: Pseudo dice [0.8411] +2024-11-22 04:38:04.683433: Epoch time: 18.57 s +2024-11-22 04:38:05.555223: +2024-11-22 04:38:05.555449: Epoch 3297 +2024-11-22 04:38:05.555565: Current learning rate: 0.0062 +2024-11-22 04:38:24.245517: train_loss -0.7802 +2024-11-22 04:38:24.246602: val_loss -0.7422 +2024-11-22 04:38:24.246716: Pseudo dice [0.847] +2024-11-22 04:38:24.246800: Epoch time: 18.69 s +2024-11-22 04:38:25.123914: +2024-11-22 04:38:25.124129: Epoch 3298 +2024-11-22 04:38:25.124242: Current learning rate: 0.0062 +2024-11-22 04:38:44.659636: train_loss -0.7842 +2024-11-22 04:38:44.659877: val_loss -0.7346 +2024-11-22 04:38:44.659953: Pseudo dice [0.8286] +2024-11-22 04:38:44.660107: Epoch time: 19.54 s +2024-11-22 04:38:45.920816: +2024-11-22 04:38:45.921021: Epoch 3299 +2024-11-22 04:38:45.921131: Current learning rate: 0.0062 +2024-11-22 04:39:04.480064: train_loss -0.7919 +2024-11-22 04:39:04.480306: val_loss -0.7457 +2024-11-22 04:39:04.480387: Pseudo dice [0.849] +2024-11-22 04:39:04.480467: Epoch time: 18.56 s +2024-11-22 04:39:05.615212: +2024-11-22 04:39:05.615445: Epoch 3300 +2024-11-22 04:39:05.615557: Current learning rate: 0.0062 +2024-11-22 04:39:24.914824: train_loss -0.7823 +2024-11-22 04:39:24.915058: val_loss -0.7462 +2024-11-22 04:39:24.915133: Pseudo dice [0.847] +2024-11-22 04:39:24.915210: Epoch time: 19.3 s +2024-11-22 04:39:25.917055: +2024-11-22 04:39:25.917267: Epoch 3301 +2024-11-22 04:39:25.917377: Current learning rate: 0.00619 +2024-11-22 04:39:43.762936: train_loss -0.7782 +2024-11-22 04:39:43.765347: val_loss -0.7398 +2024-11-22 04:39:43.765478: Pseudo dice [0.8357] +2024-11-22 04:39:43.765569: Epoch time: 17.85 s +2024-11-22 04:39:44.790143: +2024-11-22 04:39:44.790359: Epoch 3302 +2024-11-22 04:39:44.790497: Current learning rate: 0.00619 +2024-11-22 04:40:03.247132: train_loss -0.7819 +2024-11-22 04:40:03.247341: val_loss -0.7441 +2024-11-22 04:40:03.247419: Pseudo dice [0.8618] +2024-11-22 04:40:03.247495: Epoch time: 18.46 s +2024-11-22 04:40:04.105518: +2024-11-22 04:40:04.105744: Epoch 3303 +2024-11-22 04:40:04.105854: Current learning rate: 0.00619 +2024-11-22 04:40:21.988046: train_loss -0.7681 +2024-11-22 04:40:21.988267: val_loss -0.7253 +2024-11-22 04:40:21.988358: Pseudo dice [0.822] +2024-11-22 04:40:21.988438: Epoch time: 17.88 s +2024-11-22 04:40:22.860460: +2024-11-22 04:40:22.860674: Epoch 3304 +2024-11-22 04:40:22.860784: Current learning rate: 0.00619 +2024-11-22 04:40:40.802620: train_loss -0.7857 +2024-11-22 04:40:40.802917: val_loss -0.7607 +2024-11-22 04:40:40.803006: Pseudo dice [0.8275] +2024-11-22 04:40:40.803090: Epoch time: 17.94 s +2024-11-22 04:40:41.687687: +2024-11-22 04:40:41.687882: Epoch 3305 +2024-11-22 04:40:41.688000: Current learning rate: 0.00619 +2024-11-22 04:41:01.426307: train_loss -0.7792 +2024-11-22 04:41:01.426547: val_loss -0.7338 +2024-11-22 04:41:01.426643: Pseudo dice [0.8327] +2024-11-22 04:41:01.426732: Epoch time: 19.74 s +2024-11-22 04:41:02.305617: +2024-11-22 04:41:02.305813: Epoch 3306 +2024-11-22 04:41:02.305925: Current learning rate: 0.00619 +2024-11-22 04:41:20.615787: train_loss -0.7795 +2024-11-22 04:41:20.616026: val_loss -0.7413 +2024-11-22 04:41:20.616121: Pseudo dice [0.8633] +2024-11-22 04:41:20.616198: Epoch time: 18.31 s +2024-11-22 04:41:21.481345: +2024-11-22 04:41:21.481584: Epoch 3307 +2024-11-22 04:41:21.481697: Current learning rate: 0.00619 +2024-11-22 04:41:40.480875: train_loss -0.7887 +2024-11-22 04:41:40.481178: val_loss -0.7622 +2024-11-22 04:41:40.481266: Pseudo dice [0.8352] +2024-11-22 04:41:40.481346: Epoch time: 19.0 s +2024-11-22 04:41:41.377304: +2024-11-22 04:41:41.377498: Epoch 3308 +2024-11-22 04:41:41.377609: Current learning rate: 0.00619 +2024-11-22 04:41:59.452899: train_loss -0.7917 +2024-11-22 04:41:59.453123: val_loss -0.7593 +2024-11-22 04:41:59.453200: Pseudo dice [0.8707] +2024-11-22 04:41:59.453277: Epoch time: 18.08 s +2024-11-22 04:42:00.341568: +2024-11-22 04:42:00.341760: Epoch 3309 +2024-11-22 04:42:00.341871: Current learning rate: 0.00619 +2024-11-22 04:42:19.064529: train_loss -0.7859 +2024-11-22 04:42:19.064780: val_loss -0.754 +2024-11-22 04:42:19.064856: Pseudo dice [0.8386] +2024-11-22 04:42:19.064938: Epoch time: 18.72 s +2024-11-22 04:42:19.935948: +2024-11-22 04:42:19.936155: Epoch 3310 +2024-11-22 04:42:19.936269: Current learning rate: 0.00618 +2024-11-22 04:42:39.203790: train_loss -0.784 +2024-11-22 04:42:39.204015: val_loss -0.7307 +2024-11-22 04:42:39.204093: Pseudo dice [0.8672] +2024-11-22 04:42:39.204169: Epoch time: 19.27 s +2024-11-22 04:42:40.488213: +2024-11-22 04:42:40.488437: Epoch 3311 +2024-11-22 04:42:40.488548: Current learning rate: 0.00618 +2024-11-22 04:42:59.785160: train_loss -0.789 +2024-11-22 04:42:59.785385: val_loss -0.7158 +2024-11-22 04:42:59.785462: Pseudo dice [0.8485] +2024-11-22 04:42:59.785546: Epoch time: 19.3 s +2024-11-22 04:43:00.659546: +2024-11-22 04:43:00.659764: Epoch 3312 +2024-11-22 04:43:00.659876: Current learning rate: 0.00618 +2024-11-22 04:43:19.933500: train_loss -0.7797 +2024-11-22 04:43:19.933816: val_loss -0.7559 +2024-11-22 04:43:19.933902: Pseudo dice [0.836] +2024-11-22 04:43:19.933985: Epoch time: 19.27 s +2024-11-22 04:43:20.810555: +2024-11-22 04:43:20.810789: Epoch 3313 +2024-11-22 04:43:20.810904: Current learning rate: 0.00618 +2024-11-22 04:43:39.208967: train_loss -0.785 +2024-11-22 04:43:39.209194: val_loss -0.7533 +2024-11-22 04:43:39.209268: Pseudo dice [0.8384] +2024-11-22 04:43:39.209346: Epoch time: 18.4 s +2024-11-22 04:43:40.105824: +2024-11-22 04:43:40.106045: Epoch 3314 +2024-11-22 04:43:40.106168: Current learning rate: 0.00618 +2024-11-22 04:43:58.659787: train_loss -0.7697 +2024-11-22 04:43:58.660015: val_loss -0.7252 +2024-11-22 04:43:58.660089: Pseudo dice [0.8425] +2024-11-22 04:43:58.660165: Epoch time: 18.55 s +2024-11-22 04:43:59.538320: +2024-11-22 04:43:59.538532: Epoch 3315 +2024-11-22 04:43:59.538650: Current learning rate: 0.00618 +2024-11-22 04:44:17.080781: train_loss -0.7736 +2024-11-22 04:44:17.081037: val_loss -0.7272 +2024-11-22 04:44:17.081114: Pseudo dice [0.8213] +2024-11-22 04:44:17.081197: Epoch time: 17.54 s +2024-11-22 04:44:18.005294: +2024-11-22 04:44:18.005510: Epoch 3316 +2024-11-22 04:44:18.005630: Current learning rate: 0.00618 +2024-11-22 04:44:36.875749: train_loss -0.7804 +2024-11-22 04:44:36.876003: val_loss -0.73 +2024-11-22 04:44:36.876081: Pseudo dice [0.8369] +2024-11-22 04:44:36.876157: Epoch time: 18.87 s +2024-11-22 04:44:37.773244: +2024-11-22 04:44:37.773474: Epoch 3317 +2024-11-22 04:44:37.773583: Current learning rate: 0.00618 +2024-11-22 04:44:57.673800: train_loss -0.788 +2024-11-22 04:44:57.674035: val_loss -0.7494 +2024-11-22 04:44:57.674182: Pseudo dice [0.8484] +2024-11-22 04:44:57.674265: Epoch time: 19.9 s +2024-11-22 04:44:58.560096: +2024-11-22 04:44:58.560310: Epoch 3318 +2024-11-22 04:44:58.560416: Current learning rate: 0.00617 +2024-11-22 04:45:17.356922: train_loss -0.791 +2024-11-22 04:45:17.361072: val_loss -0.7492 +2024-11-22 04:45:17.361297: Pseudo dice [0.861] +2024-11-22 04:45:17.361389: Epoch time: 18.8 s +2024-11-22 04:45:18.305223: +2024-11-22 04:45:18.305466: Epoch 3319 +2024-11-22 04:45:18.305579: Current learning rate: 0.00617 +2024-11-22 04:45:37.368011: train_loss -0.7932 +2024-11-22 04:45:37.368267: val_loss -0.7487 +2024-11-22 04:45:37.368347: Pseudo dice [0.8572] +2024-11-22 04:45:37.368428: Epoch time: 19.06 s +2024-11-22 04:45:38.322703: +2024-11-22 04:45:38.322916: Epoch 3320 +2024-11-22 04:45:38.323024: Current learning rate: 0.00617 +2024-11-22 04:45:56.756006: train_loss -0.7835 +2024-11-22 04:45:56.756226: val_loss -0.7469 +2024-11-22 04:45:56.756304: Pseudo dice [0.8355] +2024-11-22 04:45:56.756383: Epoch time: 18.43 s +2024-11-22 04:45:57.631181: +2024-11-22 04:45:57.631458: Epoch 3321 +2024-11-22 04:45:57.631566: Current learning rate: 0.00617 +2024-11-22 04:46:15.622868: train_loss -0.7825 +2024-11-22 04:46:15.623219: val_loss -0.7727 +2024-11-22 04:46:15.623305: Pseudo dice [0.8446] +2024-11-22 04:46:15.623389: Epoch time: 17.99 s +2024-11-22 04:46:16.896231: +2024-11-22 04:46:16.896507: Epoch 3322 +2024-11-22 04:46:16.896621: Current learning rate: 0.00617 +2024-11-22 04:46:35.455814: train_loss -0.7995 +2024-11-22 04:46:35.457455: val_loss -0.7666 +2024-11-22 04:46:35.457551: Pseudo dice [0.856] +2024-11-22 04:46:35.457636: Epoch time: 18.56 s +2024-11-22 04:46:36.392777: +2024-11-22 04:46:36.393003: Epoch 3323 +2024-11-22 04:46:36.393119: Current learning rate: 0.00617 +2024-11-22 04:46:55.035613: train_loss -0.787 +2024-11-22 04:46:55.035830: val_loss -0.736 +2024-11-22 04:46:55.035909: Pseudo dice [0.8404] +2024-11-22 04:46:55.035989: Epoch time: 18.64 s +2024-11-22 04:46:56.048604: +2024-11-22 04:46:56.048959: Epoch 3324 +2024-11-22 04:46:56.049095: Current learning rate: 0.00617 +2024-11-22 04:47:13.986699: train_loss -0.787 +2024-11-22 04:47:13.987562: val_loss -0.7268 +2024-11-22 04:47:13.987725: Pseudo dice [0.8193] +2024-11-22 04:47:13.987806: Epoch time: 17.94 s +2024-11-22 04:47:14.855186: +2024-11-22 04:47:14.855484: Epoch 3325 +2024-11-22 04:47:14.855597: Current learning rate: 0.00617 +2024-11-22 04:47:33.960161: train_loss -0.7933 +2024-11-22 04:47:33.960377: val_loss -0.7383 +2024-11-22 04:47:33.960451: Pseudo dice [0.8557] +2024-11-22 04:47:33.960527: Epoch time: 19.11 s +2024-11-22 04:47:34.825429: +2024-11-22 04:47:34.825641: Epoch 3326 +2024-11-22 04:47:34.825754: Current learning rate: 0.00617 +2024-11-22 04:47:53.657329: train_loss -0.7971 +2024-11-22 04:47:53.657647: val_loss -0.7191 +2024-11-22 04:47:53.657727: Pseudo dice [0.8292] +2024-11-22 04:47:53.657814: Epoch time: 18.83 s +2024-11-22 04:47:54.536774: +2024-11-22 04:47:54.536979: Epoch 3327 +2024-11-22 04:47:54.537095: Current learning rate: 0.00616 +2024-11-22 04:48:12.623894: train_loss -0.7858 +2024-11-22 04:48:12.626766: val_loss -0.7367 +2024-11-22 04:48:12.626863: Pseudo dice [0.8281] +2024-11-22 04:48:12.626945: Epoch time: 18.09 s +2024-11-22 04:48:13.590543: +2024-11-22 04:48:13.590763: Epoch 3328 +2024-11-22 04:48:13.590877: Current learning rate: 0.00616 +2024-11-22 04:48:31.695418: train_loss -0.779 +2024-11-22 04:48:31.695640: val_loss -0.7356 +2024-11-22 04:48:31.695714: Pseudo dice [0.8278] +2024-11-22 04:48:31.695790: Epoch time: 18.11 s +2024-11-22 04:48:32.572569: +2024-11-22 04:48:32.572767: Epoch 3329 +2024-11-22 04:48:32.572881: Current learning rate: 0.00616 +2024-11-22 04:48:51.591743: train_loss -0.774 +2024-11-22 04:48:51.591963: val_loss -0.7464 +2024-11-22 04:48:51.592048: Pseudo dice [0.8115] +2024-11-22 04:48:51.592125: Epoch time: 19.02 s +2024-11-22 04:48:52.461410: +2024-11-22 04:48:52.461613: Epoch 3330 +2024-11-22 04:48:52.461727: Current learning rate: 0.00616 +2024-11-22 04:49:10.666620: train_loss -0.7776 +2024-11-22 04:49:10.666876: val_loss -0.7535 +2024-11-22 04:49:10.666952: Pseudo dice [0.8472] +2024-11-22 04:49:10.667044: Epoch time: 18.21 s +2024-11-22 04:49:11.543550: +2024-11-22 04:49:11.543756: Epoch 3331 +2024-11-22 04:49:11.543868: Current learning rate: 0.00616 +2024-11-22 04:49:31.281718: train_loss -0.7819 +2024-11-22 04:49:31.281934: val_loss -0.7377 +2024-11-22 04:49:31.282014: Pseudo dice [0.8343] +2024-11-22 04:49:31.282092: Epoch time: 19.74 s +2024-11-22 04:49:32.262764: +2024-11-22 04:49:32.263018: Epoch 3332 +2024-11-22 04:49:32.263137: Current learning rate: 0.00616 +2024-11-22 04:49:51.228512: train_loss -0.7871 +2024-11-22 04:49:51.230901: val_loss -0.7142 +2024-11-22 04:49:51.230989: Pseudo dice [0.8601] +2024-11-22 04:49:51.231072: Epoch time: 18.97 s +2024-11-22 04:49:52.184256: +2024-11-22 04:49:52.184485: Epoch 3333 +2024-11-22 04:49:52.184607: Current learning rate: 0.00616 +2024-11-22 04:50:10.375546: train_loss -0.7838 +2024-11-22 04:50:10.375766: val_loss -0.7676 +2024-11-22 04:50:10.375847: Pseudo dice [0.8644] +2024-11-22 04:50:10.375926: Epoch time: 18.19 s +2024-11-22 04:50:11.647040: +2024-11-22 04:50:11.647304: Epoch 3334 +2024-11-22 04:50:11.647416: Current learning rate: 0.00616 +2024-11-22 04:50:29.564052: train_loss -0.7833 +2024-11-22 04:50:29.564301: val_loss -0.7661 +2024-11-22 04:50:29.564384: Pseudo dice [0.8546] +2024-11-22 04:50:29.564472: Epoch time: 17.92 s +2024-11-22 04:50:30.485054: +2024-11-22 04:50:30.485389: Epoch 3335 +2024-11-22 04:50:30.485504: Current learning rate: 0.00615 +2024-11-22 04:50:50.139643: train_loss -0.7825 +2024-11-22 04:50:50.140759: val_loss -0.7386 +2024-11-22 04:50:50.140836: Pseudo dice [0.8273] +2024-11-22 04:50:50.140914: Epoch time: 19.66 s +2024-11-22 04:50:51.023373: +2024-11-22 04:50:51.023590: Epoch 3336 +2024-11-22 04:50:51.023701: Current learning rate: 0.00615 +2024-11-22 04:51:08.949406: train_loss -0.7789 +2024-11-22 04:51:08.949620: val_loss -0.7429 +2024-11-22 04:51:08.949693: Pseudo dice [0.8372] +2024-11-22 04:51:08.949766: Epoch time: 17.93 s +2024-11-22 04:51:09.833077: +2024-11-22 04:51:09.833316: Epoch 3337 +2024-11-22 04:51:09.833442: Current learning rate: 0.00615 +2024-11-22 04:51:27.870666: train_loss -0.7906 +2024-11-22 04:51:27.870920: val_loss -0.723 +2024-11-22 04:51:27.871002: Pseudo dice [0.8225] +2024-11-22 04:51:27.871088: Epoch time: 18.04 s +2024-11-22 04:51:28.759209: +2024-11-22 04:51:28.759402: Epoch 3338 +2024-11-22 04:51:28.759514: Current learning rate: 0.00615 +2024-11-22 04:51:47.417117: train_loss -0.7819 +2024-11-22 04:51:47.422487: val_loss -0.7576 +2024-11-22 04:51:47.422656: Pseudo dice [0.8508] +2024-11-22 04:51:47.422743: Epoch time: 18.66 s +2024-11-22 04:51:48.470164: +2024-11-22 04:51:48.470369: Epoch 3339 +2024-11-22 04:51:48.470478: Current learning rate: 0.00615 +2024-11-22 04:52:08.137153: train_loss -0.7893 +2024-11-22 04:52:08.137374: val_loss -0.7146 +2024-11-22 04:52:08.137460: Pseudo dice [0.8259] +2024-11-22 04:52:08.137537: Epoch time: 19.67 s +2024-11-22 04:52:09.020300: +2024-11-22 04:52:09.020570: Epoch 3340 +2024-11-22 04:52:09.020687: Current learning rate: 0.00615 +2024-11-22 04:52:28.279766: train_loss -0.7835 +2024-11-22 04:52:28.280045: val_loss -0.7669 +2024-11-22 04:52:28.280123: Pseudo dice [0.8428] +2024-11-22 04:52:28.280198: Epoch time: 19.26 s +2024-11-22 04:52:29.161579: +2024-11-22 04:52:29.161844: Epoch 3341 +2024-11-22 04:52:29.161957: Current learning rate: 0.00615 +2024-11-22 04:52:46.679044: train_loss -0.7793 +2024-11-22 04:52:46.679273: val_loss -0.7211 +2024-11-22 04:52:46.679353: Pseudo dice [0.8119] +2024-11-22 04:52:46.679432: Epoch time: 17.52 s +2024-11-22 04:52:47.562411: +2024-11-22 04:52:47.562615: Epoch 3342 +2024-11-22 04:52:47.562735: Current learning rate: 0.00615 +2024-11-22 04:53:05.449965: train_loss -0.7759 +2024-11-22 04:53:05.450891: val_loss -0.7377 +2024-11-22 04:53:05.451005: Pseudo dice [0.8499] +2024-11-22 04:53:05.451093: Epoch time: 17.89 s +2024-11-22 04:53:06.438235: +2024-11-22 04:53:06.438423: Epoch 3343 +2024-11-22 04:53:06.438531: Current learning rate: 0.00614 +2024-11-22 04:53:25.716281: train_loss -0.7852 +2024-11-22 04:53:25.716516: val_loss -0.7439 +2024-11-22 04:53:25.716592: Pseudo dice [0.8341] +2024-11-22 04:53:25.716743: Epoch time: 19.28 s +2024-11-22 04:53:26.596544: +2024-11-22 04:53:26.596842: Epoch 3344 +2024-11-22 04:53:26.596954: Current learning rate: 0.00614 +2024-11-22 04:53:45.796396: train_loss -0.7734 +2024-11-22 04:53:45.796690: val_loss -0.7307 +2024-11-22 04:53:45.796770: Pseudo dice [0.8447] +2024-11-22 04:53:45.796846: Epoch time: 19.2 s +2024-11-22 04:53:47.126065: +2024-11-22 04:53:47.126268: Epoch 3345 +2024-11-22 04:53:47.126385: Current learning rate: 0.00614 +2024-11-22 04:54:05.626224: train_loss -0.7749 +2024-11-22 04:54:05.628653: val_loss -0.7372 +2024-11-22 04:54:05.628783: Pseudo dice [0.8408] +2024-11-22 04:54:05.628875: Epoch time: 18.5 s +2024-11-22 04:54:06.750084: +2024-11-22 04:54:06.750305: Epoch 3346 +2024-11-22 04:54:06.750417: Current learning rate: 0.00614 +2024-11-22 04:54:25.844147: train_loss -0.7829 +2024-11-22 04:54:25.844367: val_loss -0.7534 +2024-11-22 04:54:25.844453: Pseudo dice [0.8565] +2024-11-22 04:54:25.846752: Epoch time: 19.09 s +2024-11-22 04:54:26.728345: +2024-11-22 04:54:26.728577: Epoch 3347 +2024-11-22 04:54:26.728691: Current learning rate: 0.00614 +2024-11-22 04:54:45.182625: train_loss -0.7811 +2024-11-22 04:54:45.182849: val_loss -0.76 +2024-11-22 04:54:45.182927: Pseudo dice [0.8594] +2024-11-22 04:54:45.183011: Epoch time: 18.46 s +2024-11-22 04:54:46.070435: +2024-11-22 04:54:46.070631: Epoch 3348 +2024-11-22 04:54:46.070743: Current learning rate: 0.00614 +2024-11-22 04:55:05.139660: train_loss -0.7796 +2024-11-22 04:55:05.139923: val_loss -0.7201 +2024-11-22 04:55:05.140039: Pseudo dice [0.8507] +2024-11-22 04:55:05.140125: Epoch time: 19.07 s +2024-11-22 04:55:06.024055: +2024-11-22 04:55:06.024276: Epoch 3349 +2024-11-22 04:55:06.024390: Current learning rate: 0.00614 +2024-11-22 04:55:24.653228: train_loss -0.7817 +2024-11-22 04:55:24.653437: val_loss -0.725 +2024-11-22 04:55:24.653510: Pseudo dice [0.8289] +2024-11-22 04:55:24.653589: Epoch time: 18.63 s +2024-11-22 04:55:25.779416: +2024-11-22 04:55:25.779645: Epoch 3350 +2024-11-22 04:55:25.779763: Current learning rate: 0.00614 +2024-11-22 04:55:44.038097: train_loss -0.7732 +2024-11-22 04:55:44.038317: val_loss -0.7609 +2024-11-22 04:55:44.038397: Pseudo dice [0.8605] +2024-11-22 04:55:44.038475: Epoch time: 18.26 s +2024-11-22 04:55:44.916912: +2024-11-22 04:55:44.917128: Epoch 3351 +2024-11-22 04:55:44.917242: Current learning rate: 0.00614 +2024-11-22 04:56:02.986335: train_loss -0.783 +2024-11-22 04:56:02.986554: val_loss -0.7516 +2024-11-22 04:56:02.986630: Pseudo dice [0.848] +2024-11-22 04:56:02.986707: Epoch time: 18.07 s +2024-11-22 04:56:03.913202: +2024-11-22 04:56:03.913400: Epoch 3352 +2024-11-22 04:56:03.913518: Current learning rate: 0.00613 +2024-11-22 04:56:23.140837: train_loss -0.7867 +2024-11-22 04:56:23.141088: val_loss -0.7317 +2024-11-22 04:56:23.141166: Pseudo dice [0.836] +2024-11-22 04:56:23.141248: Epoch time: 19.23 s +2024-11-22 04:56:24.035064: +2024-11-22 04:56:24.035347: Epoch 3353 +2024-11-22 04:56:24.035457: Current learning rate: 0.00613 +2024-11-22 04:56:42.428457: train_loss -0.7929 +2024-11-22 04:56:42.428680: val_loss -0.7377 +2024-11-22 04:56:42.428757: Pseudo dice [0.8539] +2024-11-22 04:56:42.428831: Epoch time: 18.39 s +2024-11-22 04:56:43.410163: +2024-11-22 04:56:43.410365: Epoch 3354 +2024-11-22 04:56:43.410477: Current learning rate: 0.00613 +2024-11-22 04:57:01.395690: train_loss -0.7925 +2024-11-22 04:57:01.395918: val_loss -0.7471 +2024-11-22 04:57:01.396001: Pseudo dice [0.8457] +2024-11-22 04:57:01.396079: Epoch time: 17.99 s +2024-11-22 04:57:02.277927: +2024-11-22 04:57:02.278136: Epoch 3355 +2024-11-22 04:57:02.278247: Current learning rate: 0.00613 +2024-11-22 04:57:19.847555: train_loss -0.7822 +2024-11-22 04:57:19.847773: val_loss -0.755 +2024-11-22 04:57:19.847848: Pseudo dice [0.8102] +2024-11-22 04:57:19.847927: Epoch time: 17.57 s +2024-11-22 04:57:21.161750: +2024-11-22 04:57:21.161951: Epoch 3356 +2024-11-22 04:57:21.162068: Current learning rate: 0.00613 +2024-11-22 04:57:39.280650: train_loss -0.7842 +2024-11-22 04:57:39.280965: val_loss -0.7673 +2024-11-22 04:57:39.281064: Pseudo dice [0.8589] +2024-11-22 04:57:39.281156: Epoch time: 18.12 s +2024-11-22 04:57:40.161577: +2024-11-22 04:57:40.161805: Epoch 3357 +2024-11-22 04:57:40.161923: Current learning rate: 0.00613 +2024-11-22 04:57:59.721210: train_loss -0.7843 +2024-11-22 04:57:59.721437: val_loss -0.7509 +2024-11-22 04:57:59.721513: Pseudo dice [0.8255] +2024-11-22 04:57:59.721591: Epoch time: 19.56 s +2024-11-22 04:58:00.605407: +2024-11-22 04:58:00.605656: Epoch 3358 +2024-11-22 04:58:00.605773: Current learning rate: 0.00613 +2024-11-22 04:58:19.270500: train_loss -0.783 +2024-11-22 04:58:19.270724: val_loss -0.7455 +2024-11-22 04:58:19.270802: Pseudo dice [0.8395] +2024-11-22 04:58:19.270880: Epoch time: 18.67 s +2024-11-22 04:58:20.153522: +2024-11-22 04:58:20.153745: Epoch 3359 +2024-11-22 04:58:20.153859: Current learning rate: 0.00613 +2024-11-22 04:58:38.652667: train_loss -0.7899 +2024-11-22 04:58:38.655140: val_loss -0.7204 +2024-11-22 04:58:38.655235: Pseudo dice [0.8222] +2024-11-22 04:58:38.655325: Epoch time: 18.5 s +2024-11-22 04:58:39.558259: +2024-11-22 04:58:39.558533: Epoch 3360 +2024-11-22 04:58:39.558885: Current learning rate: 0.00612 +2024-11-22 04:58:58.623085: train_loss -0.7875 +2024-11-22 04:58:58.623301: val_loss -0.7614 +2024-11-22 04:58:58.623378: Pseudo dice [0.8312] +2024-11-22 04:58:58.623455: Epoch time: 19.07 s +2024-11-22 04:58:59.502589: +2024-11-22 04:58:59.502785: Epoch 3361 +2024-11-22 04:58:59.502899: Current learning rate: 0.00612 +2024-11-22 04:59:17.862402: train_loss -0.7922 +2024-11-22 04:59:17.862623: val_loss -0.767 +2024-11-22 04:59:17.862699: Pseudo dice [0.8253] +2024-11-22 04:59:17.862777: Epoch time: 18.36 s +2024-11-22 04:59:18.751080: +2024-11-22 04:59:18.751349: Epoch 3362 +2024-11-22 04:59:18.751463: Current learning rate: 0.00612 +2024-11-22 04:59:36.690479: train_loss -0.7869 +2024-11-22 04:59:36.690693: val_loss -0.7244 +2024-11-22 04:59:36.690769: Pseudo dice [0.8295] +2024-11-22 04:59:36.690844: Epoch time: 17.94 s +2024-11-22 04:59:37.569324: +2024-11-22 04:59:37.569536: Epoch 3363 +2024-11-22 04:59:37.569646: Current learning rate: 0.00612 +2024-11-22 04:59:56.358263: train_loss -0.792 +2024-11-22 04:59:56.358506: val_loss -0.7515 +2024-11-22 04:59:56.358603: Pseudo dice [0.8505] +2024-11-22 04:59:56.358746: Epoch time: 18.79 s +2024-11-22 04:59:57.243747: +2024-11-22 04:59:57.243943: Epoch 3364 +2024-11-22 04:59:57.244066: Current learning rate: 0.00612 +2024-11-22 05:00:16.511371: train_loss -0.7947 +2024-11-22 05:00:16.511595: val_loss -0.7318 +2024-11-22 05:00:16.511672: Pseudo dice [0.8604] +2024-11-22 05:00:16.511749: Epoch time: 19.27 s +2024-11-22 05:00:17.395509: +2024-11-22 05:00:17.395705: Epoch 3365 +2024-11-22 05:00:17.395815: Current learning rate: 0.00612 +2024-11-22 05:00:35.898586: train_loss -0.7928 +2024-11-22 05:00:35.898836: val_loss -0.7405 +2024-11-22 05:00:35.898913: Pseudo dice [0.8477] +2024-11-22 05:00:35.899000: Epoch time: 18.5 s +2024-11-22 05:00:36.782496: +2024-11-22 05:00:36.782757: Epoch 3366 +2024-11-22 05:00:36.782873: Current learning rate: 0.00612 +2024-11-22 05:00:55.616759: train_loss -0.7829 +2024-11-22 05:00:55.616983: val_loss -0.7522 +2024-11-22 05:00:55.617066: Pseudo dice [0.8326] +2024-11-22 05:00:55.617158: Epoch time: 18.84 s +2024-11-22 05:00:56.965824: +2024-11-22 05:00:56.966073: Epoch 3367 +2024-11-22 05:00:56.966228: Current learning rate: 0.00612 +2024-11-22 05:01:16.425520: train_loss -0.779 +2024-11-22 05:01:16.425747: val_loss -0.7392 +2024-11-22 05:01:16.425823: Pseudo dice [0.8175] +2024-11-22 05:01:16.425933: Epoch time: 19.46 s +2024-11-22 05:01:17.306453: +2024-11-22 05:01:17.306708: Epoch 3368 +2024-11-22 05:01:17.306822: Current learning rate: 0.00612 +2024-11-22 05:01:35.528433: train_loss -0.7882 +2024-11-22 05:01:35.528652: val_loss -0.7286 +2024-11-22 05:01:35.528726: Pseudo dice [0.8308] +2024-11-22 05:01:35.528803: Epoch time: 18.22 s +2024-11-22 05:01:36.406726: +2024-11-22 05:01:36.406930: Epoch 3369 +2024-11-22 05:01:36.407048: Current learning rate: 0.00611 +2024-11-22 05:01:55.462034: train_loss -0.7875 +2024-11-22 05:01:55.462253: val_loss -0.7243 +2024-11-22 05:01:55.462333: Pseudo dice [0.8244] +2024-11-22 05:01:55.462409: Epoch time: 19.06 s +2024-11-22 05:01:56.344898: +2024-11-22 05:01:56.345153: Epoch 3370 +2024-11-22 05:01:56.345266: Current learning rate: 0.00611 +2024-11-22 05:02:15.636257: train_loss -0.7921 +2024-11-22 05:02:15.636506: val_loss -0.7581 +2024-11-22 05:02:15.636582: Pseudo dice [0.8428] +2024-11-22 05:02:15.636663: Epoch time: 19.29 s +2024-11-22 05:02:16.520032: +2024-11-22 05:02:16.520244: Epoch 3371 +2024-11-22 05:02:16.520367: Current learning rate: 0.00611 +2024-11-22 05:02:35.177727: train_loss -0.7809 +2024-11-22 05:02:35.177946: val_loss -0.7383 +2024-11-22 05:02:35.178130: Pseudo dice [0.8428] +2024-11-22 05:02:35.178231: Epoch time: 18.66 s +2024-11-22 05:02:36.056929: +2024-11-22 05:02:36.057153: Epoch 3372 +2024-11-22 05:02:36.057271: Current learning rate: 0.00611 +2024-11-22 05:02:55.037662: train_loss -0.7782 +2024-11-22 05:02:55.037884: val_loss -0.7452 +2024-11-22 05:02:55.037958: Pseudo dice [0.8334] +2024-11-22 05:02:55.038046: Epoch time: 18.98 s +2024-11-22 05:02:56.068879: +2024-11-22 05:02:56.069196: Epoch 3373 +2024-11-22 05:02:56.069315: Current learning rate: 0.00611 +2024-11-22 05:03:14.673252: train_loss -0.7757 +2024-11-22 05:03:14.673478: val_loss -0.735 +2024-11-22 05:03:14.673561: Pseudo dice [0.8422] +2024-11-22 05:03:14.673644: Epoch time: 18.61 s +2024-11-22 05:03:15.652909: +2024-11-22 05:03:15.653139: Epoch 3374 +2024-11-22 05:03:15.653258: Current learning rate: 0.00611 +2024-11-22 05:03:34.143897: train_loss -0.7871 +2024-11-22 05:03:34.144174: val_loss -0.7414 +2024-11-22 05:03:34.144253: Pseudo dice [0.8437] +2024-11-22 05:03:34.144338: Epoch time: 18.49 s +2024-11-22 05:03:35.125669: +2024-11-22 05:03:35.125881: Epoch 3375 +2024-11-22 05:03:35.125997: Current learning rate: 0.00611 +2024-11-22 05:03:54.245321: train_loss -0.7775 +2024-11-22 05:03:54.245538: val_loss -0.7508 +2024-11-22 05:03:54.245614: Pseudo dice [0.8316] +2024-11-22 05:03:54.245691: Epoch time: 19.12 s +2024-11-22 05:03:55.121799: +2024-11-22 05:03:55.122013: Epoch 3376 +2024-11-22 05:03:55.122127: Current learning rate: 0.00611 +2024-11-22 05:04:13.595541: train_loss -0.7787 +2024-11-22 05:04:13.595767: val_loss -0.6998 +2024-11-22 05:04:13.595843: Pseudo dice [0.8206] +2024-11-22 05:04:13.595937: Epoch time: 18.47 s +2024-11-22 05:04:14.474444: +2024-11-22 05:04:14.474635: Epoch 3377 +2024-11-22 05:04:14.474746: Current learning rate: 0.0061 +2024-11-22 05:04:33.750180: train_loss -0.7756 +2024-11-22 05:04:33.750424: val_loss -0.7439 +2024-11-22 05:04:33.750502: Pseudo dice [0.8386] +2024-11-22 05:04:33.750585: Epoch time: 19.28 s +2024-11-22 05:04:35.021607: +2024-11-22 05:04:35.021890: Epoch 3378 +2024-11-22 05:04:35.022016: Current learning rate: 0.0061 +2024-11-22 05:04:53.627548: train_loss -0.7818 +2024-11-22 05:04:53.627774: val_loss -0.7306 +2024-11-22 05:04:53.627851: Pseudo dice [0.8548] +2024-11-22 05:04:53.627928: Epoch time: 18.61 s +2024-11-22 05:04:54.665862: +2024-11-22 05:04:54.666068: Epoch 3379 +2024-11-22 05:04:54.666183: Current learning rate: 0.0061 +2024-11-22 05:05:14.373969: train_loss -0.7773 +2024-11-22 05:05:14.374195: val_loss -0.7089 +2024-11-22 05:05:14.374273: Pseudo dice [0.8515] +2024-11-22 05:05:14.374349: Epoch time: 19.71 s +2024-11-22 05:05:15.260752: +2024-11-22 05:05:15.260988: Epoch 3380 +2024-11-22 05:05:15.261106: Current learning rate: 0.0061 +2024-11-22 05:05:34.239039: train_loss -0.7672 +2024-11-22 05:05:34.240368: val_loss -0.7179 +2024-11-22 05:05:34.240561: Pseudo dice [0.8276] +2024-11-22 05:05:34.240646: Epoch time: 18.98 s +2024-11-22 05:05:35.157651: +2024-11-22 05:05:35.157999: Epoch 3381 +2024-11-22 05:05:35.158180: Current learning rate: 0.0061 +2024-11-22 05:05:54.169665: train_loss -0.7758 +2024-11-22 05:05:54.169880: val_loss -0.7365 +2024-11-22 05:05:54.169955: Pseudo dice [0.8365] +2024-11-22 05:05:54.170040: Epoch time: 19.01 s +2024-11-22 05:05:55.065371: +2024-11-22 05:05:55.065649: Epoch 3382 +2024-11-22 05:05:55.065762: Current learning rate: 0.0061 +2024-11-22 05:06:13.375814: train_loss -0.7809 +2024-11-22 05:06:13.376051: val_loss -0.7436 +2024-11-22 05:06:13.376148: Pseudo dice [0.8374] +2024-11-22 05:06:13.376227: Epoch time: 18.31 s +2024-11-22 05:06:14.342511: +2024-11-22 05:06:14.342878: Epoch 3383 +2024-11-22 05:06:14.343001: Current learning rate: 0.0061 +2024-11-22 05:06:32.254303: train_loss -0.7658 +2024-11-22 05:06:32.254533: val_loss -0.7543 +2024-11-22 05:06:32.254610: Pseudo dice [0.8568] +2024-11-22 05:06:32.254685: Epoch time: 17.91 s +2024-11-22 05:06:33.137704: +2024-11-22 05:06:33.137921: Epoch 3384 +2024-11-22 05:06:33.138041: Current learning rate: 0.0061 +2024-11-22 05:06:51.580059: train_loss -0.7748 +2024-11-22 05:06:51.580296: val_loss -0.717 +2024-11-22 05:06:51.580411: Pseudo dice [0.83] +2024-11-22 05:06:51.580491: Epoch time: 18.44 s +2024-11-22 05:06:52.469561: +2024-11-22 05:06:52.469840: Epoch 3385 +2024-11-22 05:06:52.469951: Current learning rate: 0.00609 +2024-11-22 05:07:11.285781: train_loss -0.7835 +2024-11-22 05:07:11.286047: val_loss -0.7351 +2024-11-22 05:07:11.286124: Pseudo dice [0.84] +2024-11-22 05:07:11.286208: Epoch time: 18.82 s +2024-11-22 05:07:12.170605: +2024-11-22 05:07:12.170882: Epoch 3386 +2024-11-22 05:07:12.171215: Current learning rate: 0.00609 +2024-11-22 05:07:30.782673: train_loss -0.7761 +2024-11-22 05:07:30.782896: val_loss -0.7219 +2024-11-22 05:07:30.782973: Pseudo dice [0.8386] +2024-11-22 05:07:30.783056: Epoch time: 18.61 s +2024-11-22 05:07:31.662756: +2024-11-22 05:07:31.662955: Epoch 3387 +2024-11-22 05:07:31.663070: Current learning rate: 0.00609 +2024-11-22 05:07:50.445696: train_loss -0.7846 +2024-11-22 05:07:50.445949: val_loss -0.778 +2024-11-22 05:07:50.446033: Pseudo dice [0.8559] +2024-11-22 05:07:50.446112: Epoch time: 18.78 s +2024-11-22 05:07:51.326546: +2024-11-22 05:07:51.326772: Epoch 3388 +2024-11-22 05:07:51.326883: Current learning rate: 0.00609 +2024-11-22 05:08:09.731642: train_loss -0.7715 +2024-11-22 05:08:09.731903: val_loss -0.721 +2024-11-22 05:08:09.731981: Pseudo dice [0.8401] +2024-11-22 05:08:09.732072: Epoch time: 18.41 s +2024-11-22 05:08:11.000597: +2024-11-22 05:08:11.000846: Epoch 3389 +2024-11-22 05:08:11.000966: Current learning rate: 0.00609 +2024-11-22 05:08:30.564590: train_loss -0.7789 +2024-11-22 05:08:30.564813: val_loss -0.7366 +2024-11-22 05:08:30.564887: Pseudo dice [0.8468] +2024-11-22 05:08:30.564964: Epoch time: 19.56 s +2024-11-22 05:08:31.542973: +2024-11-22 05:08:31.543220: Epoch 3390 +2024-11-22 05:08:31.543333: Current learning rate: 0.00609 +2024-11-22 05:08:49.945069: train_loss -0.7884 +2024-11-22 05:08:49.945301: val_loss -0.7447 +2024-11-22 05:08:49.947604: Pseudo dice [0.8231] +2024-11-22 05:08:49.947726: Epoch time: 18.4 s +2024-11-22 05:08:50.916623: +2024-11-22 05:08:50.916882: Epoch 3391 +2024-11-22 05:08:50.917004: Current learning rate: 0.00609 +2024-11-22 05:09:09.715299: train_loss -0.7915 +2024-11-22 05:09:09.715538: val_loss -0.7652 +2024-11-22 05:09:09.715614: Pseudo dice [0.86] +2024-11-22 05:09:09.715695: Epoch time: 18.8 s +2024-11-22 05:09:10.599208: +2024-11-22 05:09:10.599423: Epoch 3392 +2024-11-22 05:09:10.599541: Current learning rate: 0.00609 +2024-11-22 05:09:28.613021: train_loss -0.7923 +2024-11-22 05:09:28.613246: val_loss -0.7594 +2024-11-22 05:09:28.613324: Pseudo dice [0.8485] +2024-11-22 05:09:28.613400: Epoch time: 18.01 s +2024-11-22 05:09:29.494939: +2024-11-22 05:09:29.495158: Epoch 3393 +2024-11-22 05:09:29.495271: Current learning rate: 0.00609 +2024-11-22 05:09:49.153732: train_loss -0.7926 +2024-11-22 05:09:49.153952: val_loss -0.7236 +2024-11-22 05:09:49.154097: Pseudo dice [0.8536] +2024-11-22 05:09:49.154189: Epoch time: 19.66 s +2024-11-22 05:09:50.053921: +2024-11-22 05:09:50.054154: Epoch 3394 +2024-11-22 05:09:50.054270: Current learning rate: 0.00608 +2024-11-22 05:10:09.151703: train_loss -0.7943 +2024-11-22 05:10:09.151940: val_loss -0.7562 +2024-11-22 05:10:09.152033: Pseudo dice [0.8513] +2024-11-22 05:10:09.152119: Epoch time: 19.1 s +2024-11-22 05:10:10.037554: +2024-11-22 05:10:10.037762: Epoch 3395 +2024-11-22 05:10:10.037882: Current learning rate: 0.00608 +2024-11-22 05:10:29.755057: train_loss -0.7793 +2024-11-22 05:10:29.755318: val_loss -0.746 +2024-11-22 05:10:29.755394: Pseudo dice [0.824] +2024-11-22 05:10:29.755536: Epoch time: 19.72 s +2024-11-22 05:10:30.644485: +2024-11-22 05:10:30.644683: Epoch 3396 +2024-11-22 05:10:30.644798: Current learning rate: 0.00608 +2024-11-22 05:10:49.163899: train_loss -0.795 +2024-11-22 05:10:49.166289: val_loss -0.7375 +2024-11-22 05:10:49.166378: Pseudo dice [0.831] +2024-11-22 05:10:49.166457: Epoch time: 18.52 s +2024-11-22 05:10:50.052063: +2024-11-22 05:10:50.052438: Epoch 3397 +2024-11-22 05:10:50.052554: Current learning rate: 0.00608 +2024-11-22 05:11:07.932822: train_loss -0.7916 +2024-11-22 05:11:07.933060: val_loss -0.7195 +2024-11-22 05:11:07.933137: Pseudo dice [0.835] +2024-11-22 05:11:07.933216: Epoch time: 17.88 s +2024-11-22 05:11:08.856314: +2024-11-22 05:11:08.856526: Epoch 3398 +2024-11-22 05:11:08.856640: Current learning rate: 0.00608 +2024-11-22 05:11:26.547721: train_loss -0.783 +2024-11-22 05:11:26.547947: val_loss -0.7385 +2024-11-22 05:11:26.548032: Pseudo dice [0.8333] +2024-11-22 05:11:26.548111: Epoch time: 17.69 s +2024-11-22 05:11:27.427724: +2024-11-22 05:11:27.428083: Epoch 3399 +2024-11-22 05:11:27.428197: Current learning rate: 0.00608 +2024-11-22 05:11:47.568394: train_loss -0.7762 +2024-11-22 05:11:47.570794: val_loss -0.7377 +2024-11-22 05:11:47.570886: Pseudo dice [0.8521] +2024-11-22 05:11:47.570970: Epoch time: 20.14 s +2024-11-22 05:11:49.312673: +2024-11-22 05:11:49.312914: Epoch 3400 +2024-11-22 05:11:49.313026: Current learning rate: 0.00608 +2024-11-22 05:12:08.694031: train_loss -0.7883 +2024-11-22 05:12:08.694264: val_loss -0.7544 +2024-11-22 05:12:08.694341: Pseudo dice [0.8614] +2024-11-22 05:12:08.694417: Epoch time: 19.38 s +2024-11-22 05:12:09.608197: +2024-11-22 05:12:09.608418: Epoch 3401 +2024-11-22 05:12:09.608534: Current learning rate: 0.00608 +2024-11-22 05:12:27.213260: train_loss -0.783 +2024-11-22 05:12:27.213547: val_loss -0.7387 +2024-11-22 05:12:27.213631: Pseudo dice [0.8377] +2024-11-22 05:12:27.213707: Epoch time: 17.61 s +2024-11-22 05:12:28.092924: +2024-11-22 05:12:28.093171: Epoch 3402 +2024-11-22 05:12:28.093282: Current learning rate: 0.00607 +2024-11-22 05:12:46.651810: train_loss -0.7781 +2024-11-22 05:12:46.652074: val_loss -0.7302 +2024-11-22 05:12:46.652161: Pseudo dice [0.8181] +2024-11-22 05:12:46.652244: Epoch time: 18.56 s +2024-11-22 05:12:47.537871: +2024-11-22 05:12:47.538110: Epoch 3403 +2024-11-22 05:12:47.538214: Current learning rate: 0.00607 +2024-11-22 05:13:05.835946: train_loss -0.7705 +2024-11-22 05:13:05.836169: val_loss -0.7349 +2024-11-22 05:13:05.836312: Pseudo dice [0.853] +2024-11-22 05:13:05.836394: Epoch time: 18.3 s +2024-11-22 05:13:06.725413: +2024-11-22 05:13:06.725631: Epoch 3404 +2024-11-22 05:13:06.725745: Current learning rate: 0.00607 +2024-11-22 05:13:24.834879: train_loss -0.7849 +2024-11-22 05:13:24.835106: val_loss -0.7611 +2024-11-22 05:13:24.835184: Pseudo dice [0.8647] +2024-11-22 05:13:24.835262: Epoch time: 18.11 s +2024-11-22 05:13:25.726876: +2024-11-22 05:13:25.727087: Epoch 3405 +2024-11-22 05:13:25.727204: Current learning rate: 0.00607 +2024-11-22 05:13:44.546397: train_loss -0.7902 +2024-11-22 05:13:44.548815: val_loss -0.7501 +2024-11-22 05:13:44.548906: Pseudo dice [0.8418] +2024-11-22 05:13:44.548984: Epoch time: 18.82 s +2024-11-22 05:13:45.495610: +2024-11-22 05:13:45.495819: Epoch 3406 +2024-11-22 05:13:45.495931: Current learning rate: 0.00607 +2024-11-22 05:14:02.856275: train_loss -0.7836 +2024-11-22 05:14:02.856520: val_loss -0.7331 +2024-11-22 05:14:02.856595: Pseudo dice [0.8405] +2024-11-22 05:14:02.856675: Epoch time: 17.36 s +2024-11-22 05:14:03.735508: +2024-11-22 05:14:03.735737: Epoch 3407 +2024-11-22 05:14:03.735851: Current learning rate: 0.00607 +2024-11-22 05:14:24.349010: train_loss -0.7725 +2024-11-22 05:14:24.349227: val_loss -0.7526 +2024-11-22 05:14:24.349301: Pseudo dice [0.8328] +2024-11-22 05:14:24.349378: Epoch time: 20.61 s +2024-11-22 05:14:25.232131: +2024-11-22 05:14:25.232336: Epoch 3408 +2024-11-22 05:14:25.232451: Current learning rate: 0.00607 +2024-11-22 05:14:43.623816: train_loss -0.7882 +2024-11-22 05:14:43.624053: val_loss -0.7352 +2024-11-22 05:14:43.624139: Pseudo dice [0.848] +2024-11-22 05:14:43.624226: Epoch time: 18.39 s +2024-11-22 05:14:44.511438: +2024-11-22 05:14:44.511628: Epoch 3409 +2024-11-22 05:14:44.511739: Current learning rate: 0.00607 +2024-11-22 05:15:03.003648: train_loss -0.786 +2024-11-22 05:15:03.003863: val_loss -0.7502 +2024-11-22 05:15:03.003936: Pseudo dice [0.8322] +2024-11-22 05:15:03.004018: Epoch time: 18.49 s +2024-11-22 05:15:03.881277: +2024-11-22 05:15:03.881476: Epoch 3410 +2024-11-22 05:15:03.881589: Current learning rate: 0.00607 +2024-11-22 05:15:22.060958: train_loss -0.7775 +2024-11-22 05:15:22.061212: val_loss -0.7356 +2024-11-22 05:15:22.063492: Pseudo dice [0.8365] +2024-11-22 05:15:22.063590: Epoch time: 18.18 s +2024-11-22 05:15:23.413142: +2024-11-22 05:15:23.413353: Epoch 3411 +2024-11-22 05:15:23.413466: Current learning rate: 0.00606 +2024-11-22 05:15:42.674842: train_loss -0.7923 +2024-11-22 05:15:42.675085: val_loss -0.7383 +2024-11-22 05:15:42.675167: Pseudo dice [0.8391] +2024-11-22 05:15:42.675247: Epoch time: 19.26 s +2024-11-22 05:15:43.548589: +2024-11-22 05:15:43.548876: Epoch 3412 +2024-11-22 05:15:43.549000: Current learning rate: 0.00606 +2024-11-22 05:16:02.411309: train_loss -0.7802 +2024-11-22 05:16:02.411537: val_loss -0.7326 +2024-11-22 05:16:02.411621: Pseudo dice [0.8355] +2024-11-22 05:16:02.411706: Epoch time: 18.86 s +2024-11-22 05:16:03.299229: +2024-11-22 05:16:03.299468: Epoch 3413 +2024-11-22 05:16:03.299587: Current learning rate: 0.00606 +2024-11-22 05:16:21.733421: train_loss -0.7839 +2024-11-22 05:16:21.733644: val_loss -0.7117 +2024-11-22 05:16:21.733721: Pseudo dice [0.8117] +2024-11-22 05:16:21.733841: Epoch time: 18.44 s +2024-11-22 05:16:22.622526: +2024-11-22 05:16:22.622746: Epoch 3414 +2024-11-22 05:16:22.622862: Current learning rate: 0.00606 +2024-11-22 05:16:41.466804: train_loss -0.7939 +2024-11-22 05:16:41.467024: val_loss -0.7584 +2024-11-22 05:16:41.467097: Pseudo dice [0.8475] +2024-11-22 05:16:41.467175: Epoch time: 18.85 s +2024-11-22 05:16:42.353061: +2024-11-22 05:16:42.353312: Epoch 3415 +2024-11-22 05:16:42.353431: Current learning rate: 0.00606 +2024-11-22 05:17:00.845438: train_loss -0.7934 +2024-11-22 05:17:00.845652: val_loss -0.7564 +2024-11-22 05:17:00.845724: Pseudo dice [0.8588] +2024-11-22 05:17:00.845800: Epoch time: 18.49 s +2024-11-22 05:17:01.740041: +2024-11-22 05:17:01.740259: Epoch 3416 +2024-11-22 05:17:01.740372: Current learning rate: 0.00606 +2024-11-22 05:17:19.166920: train_loss -0.7906 +2024-11-22 05:17:19.167164: val_loss -0.7216 +2024-11-22 05:17:19.167244: Pseudo dice [0.8546] +2024-11-22 05:17:19.167329: Epoch time: 17.43 s +2024-11-22 05:17:20.054996: +2024-11-22 05:17:20.055228: Epoch 3417 +2024-11-22 05:17:20.055344: Current learning rate: 0.00606 +2024-11-22 05:17:39.598340: train_loss -0.7677 +2024-11-22 05:17:39.598615: val_loss -0.746 +2024-11-22 05:17:39.598753: Pseudo dice [0.8416] +2024-11-22 05:17:39.598838: Epoch time: 19.54 s +2024-11-22 05:17:40.520791: +2024-11-22 05:17:40.521091: Epoch 3418 +2024-11-22 05:17:40.521205: Current learning rate: 0.00606 +2024-11-22 05:17:58.935215: train_loss -0.7677 +2024-11-22 05:17:58.937626: val_loss -0.7192 +2024-11-22 05:17:58.937751: Pseudo dice [0.8439] +2024-11-22 05:17:58.937839: Epoch time: 18.42 s +2024-11-22 05:17:59.895204: +2024-11-22 05:17:59.895417: Epoch 3419 +2024-11-22 05:17:59.895526: Current learning rate: 0.00605 +2024-11-22 05:18:18.546376: train_loss -0.756 +2024-11-22 05:18:18.546591: val_loss -0.739 +2024-11-22 05:18:18.546666: Pseudo dice [0.8331] +2024-11-22 05:18:18.546745: Epoch time: 18.65 s +2024-11-22 05:18:19.567333: +2024-11-22 05:18:19.567529: Epoch 3420 +2024-11-22 05:18:19.567646: Current learning rate: 0.00605 +2024-11-22 05:18:37.637741: train_loss -0.7665 +2024-11-22 05:18:37.638048: val_loss -0.7186 +2024-11-22 05:18:37.638127: Pseudo dice [0.8079] +2024-11-22 05:18:37.638211: Epoch time: 18.07 s +2024-11-22 05:18:38.522256: +2024-11-22 05:18:38.522455: Epoch 3421 +2024-11-22 05:18:38.522566: Current learning rate: 0.00605 +2024-11-22 05:18:57.531792: train_loss -0.7838 +2024-11-22 05:18:57.532018: val_loss -0.758 +2024-11-22 05:18:57.532094: Pseudo dice [0.8382] +2024-11-22 05:18:57.532171: Epoch time: 19.01 s +2024-11-22 05:18:58.413170: +2024-11-22 05:18:58.413367: Epoch 3422 +2024-11-22 05:18:58.413479: Current learning rate: 0.00605 +2024-11-22 05:19:17.546492: train_loss -0.7659 +2024-11-22 05:19:17.546734: val_loss -0.6901 +2024-11-22 05:19:17.546815: Pseudo dice [0.8352] +2024-11-22 05:19:17.546893: Epoch time: 19.13 s +2024-11-22 05:19:18.448347: +2024-11-22 05:19:18.448565: Epoch 3423 +2024-11-22 05:19:18.448676: Current learning rate: 0.00605 +2024-11-22 05:19:37.405339: train_loss -0.7805 +2024-11-22 05:19:37.405568: val_loss -0.7392 +2024-11-22 05:19:37.405643: Pseudo dice [0.8412] +2024-11-22 05:19:37.405784: Epoch time: 18.96 s +2024-11-22 05:19:38.297297: +2024-11-22 05:19:38.297540: Epoch 3424 +2024-11-22 05:19:38.297651: Current learning rate: 0.00605 +2024-11-22 05:19:56.809870: train_loss -0.7857 +2024-11-22 05:19:56.810102: val_loss -0.7342 +2024-11-22 05:19:56.810176: Pseudo dice [0.8398] +2024-11-22 05:19:56.810254: Epoch time: 18.51 s +2024-11-22 05:19:57.693588: +2024-11-22 05:19:57.693805: Epoch 3425 +2024-11-22 05:19:57.693919: Current learning rate: 0.00605 +2024-11-22 05:20:15.607971: train_loss -0.7898 +2024-11-22 05:20:15.608220: val_loss -0.7334 +2024-11-22 05:20:15.608296: Pseudo dice [0.8173] +2024-11-22 05:20:15.608374: Epoch time: 17.92 s +2024-11-22 05:20:16.489619: +2024-11-22 05:20:16.489849: Epoch 3426 +2024-11-22 05:20:16.489961: Current learning rate: 0.00605 +2024-11-22 05:20:34.758836: train_loss -0.7836 +2024-11-22 05:20:34.759065: val_loss -0.7521 +2024-11-22 05:20:34.759140: Pseudo dice [0.8508] +2024-11-22 05:20:34.759216: Epoch time: 18.27 s +2024-11-22 05:20:35.641096: +2024-11-22 05:20:35.641337: Epoch 3427 +2024-11-22 05:20:35.641446: Current learning rate: 0.00605 +2024-11-22 05:20:54.273635: train_loss -0.7761 +2024-11-22 05:20:54.273882: val_loss -0.7456 +2024-11-22 05:20:54.273959: Pseudo dice [0.8248] +2024-11-22 05:20:54.274050: Epoch time: 18.63 s +2024-11-22 05:20:55.163299: +2024-11-22 05:20:55.163620: Epoch 3428 +2024-11-22 05:20:55.163734: Current learning rate: 0.00604 +2024-11-22 05:21:13.491457: train_loss -0.7803 +2024-11-22 05:21:13.491678: val_loss -0.7596 +2024-11-22 05:21:13.491757: Pseudo dice [0.8443] +2024-11-22 05:21:13.491851: Epoch time: 18.33 s +2024-11-22 05:21:14.492020: +2024-11-22 05:21:14.492215: Epoch 3429 +2024-11-22 05:21:14.492332: Current learning rate: 0.00604 +2024-11-22 05:21:33.832827: train_loss -0.7891 +2024-11-22 05:21:33.833061: val_loss -0.7406 +2024-11-22 05:21:33.833138: Pseudo dice [0.8427] +2024-11-22 05:21:33.833215: Epoch time: 19.34 s +2024-11-22 05:21:34.724651: +2024-11-22 05:21:34.724935: Epoch 3430 +2024-11-22 05:21:34.725062: Current learning rate: 0.00604 +2024-11-22 05:21:53.632362: train_loss -0.7799 +2024-11-22 05:21:53.632619: val_loss -0.7357 +2024-11-22 05:21:53.632696: Pseudo dice [0.8326] +2024-11-22 05:21:53.632776: Epoch time: 18.91 s +2024-11-22 05:21:54.578566: +2024-11-22 05:21:54.578790: Epoch 3431 +2024-11-22 05:21:54.578902: Current learning rate: 0.00604 +2024-11-22 05:22:13.312990: train_loss -0.7685 +2024-11-22 05:22:13.313256: val_loss -0.7647 +2024-11-22 05:22:13.313331: Pseudo dice [0.8334] +2024-11-22 05:22:13.313487: Epoch time: 18.74 s +2024-11-22 05:22:14.196520: +2024-11-22 05:22:14.196713: Epoch 3432 +2024-11-22 05:22:14.196826: Current learning rate: 0.00604 +2024-11-22 05:22:32.961383: train_loss -0.7785 +2024-11-22 05:22:32.961606: val_loss -0.7338 +2024-11-22 05:22:32.961682: Pseudo dice [0.8657] +2024-11-22 05:22:32.961758: Epoch time: 18.77 s +2024-11-22 05:22:34.407758: +2024-11-22 05:22:34.407958: Epoch 3433 +2024-11-22 05:22:34.408072: Current learning rate: 0.00604 +2024-11-22 05:22:54.099725: train_loss -0.7899 +2024-11-22 05:22:54.099966: val_loss -0.745 +2024-11-22 05:22:54.100051: Pseudo dice [0.833] +2024-11-22 05:22:54.100136: Epoch time: 19.69 s +2024-11-22 05:22:54.977075: +2024-11-22 05:22:54.977333: Epoch 3434 +2024-11-22 05:22:54.977446: Current learning rate: 0.00604 +2024-11-22 05:23:13.747625: train_loss -0.7698 +2024-11-22 05:23:13.747909: val_loss -0.7338 +2024-11-22 05:23:13.748004: Pseudo dice [0.8544] +2024-11-22 05:23:13.748090: Epoch time: 18.77 s +2024-11-22 05:23:14.749001: +2024-11-22 05:23:14.749241: Epoch 3435 +2024-11-22 05:23:14.749353: Current learning rate: 0.00604 +2024-11-22 05:23:33.479537: train_loss -0.7872 +2024-11-22 05:23:33.479751: val_loss -0.742 +2024-11-22 05:23:33.479830: Pseudo dice [0.828] +2024-11-22 05:23:33.479910: Epoch time: 18.73 s +2024-11-22 05:23:34.360364: +2024-11-22 05:23:34.360607: Epoch 3436 +2024-11-22 05:23:34.360722: Current learning rate: 0.00603 +2024-11-22 05:23:53.446314: train_loss -0.7909 +2024-11-22 05:23:53.446545: val_loss -0.7574 +2024-11-22 05:23:53.446623: Pseudo dice [0.8363] +2024-11-22 05:23:53.446705: Epoch time: 19.09 s +2024-11-22 05:23:54.329143: +2024-11-22 05:23:54.329371: Epoch 3437 +2024-11-22 05:23:54.329484: Current learning rate: 0.00603 +2024-11-22 05:24:12.048365: train_loss -0.7811 +2024-11-22 05:24:12.048615: val_loss -0.7507 +2024-11-22 05:24:12.050886: Pseudo dice [0.8568] +2024-11-22 05:24:12.051050: Epoch time: 17.72 s +2024-11-22 05:24:13.105943: +2024-11-22 05:24:13.106157: Epoch 3438 +2024-11-22 05:24:13.106271: Current learning rate: 0.00603 +2024-11-22 05:24:30.997161: train_loss -0.7794 +2024-11-22 05:24:30.997380: val_loss -0.746 +2024-11-22 05:24:30.997457: Pseudo dice [0.8361] +2024-11-22 05:24:30.997534: Epoch time: 17.89 s +2024-11-22 05:24:31.882741: +2024-11-22 05:24:31.882956: Epoch 3439 +2024-11-22 05:24:31.883079: Current learning rate: 0.00603 +2024-11-22 05:24:51.200357: train_loss -0.781 +2024-11-22 05:24:51.200581: val_loss -0.7721 +2024-11-22 05:24:51.200657: Pseudo dice [0.851] +2024-11-22 05:24:51.200734: Epoch time: 19.32 s +2024-11-22 05:24:52.185971: +2024-11-22 05:24:52.186183: Epoch 3440 +2024-11-22 05:24:52.186294: Current learning rate: 0.00603 +2024-11-22 05:25:11.044552: train_loss -0.7887 +2024-11-22 05:25:11.044775: val_loss -0.7122 +2024-11-22 05:25:11.044852: Pseudo dice [0.8218] +2024-11-22 05:25:11.044931: Epoch time: 18.86 s +2024-11-22 05:25:11.924868: +2024-11-22 05:25:11.925074: Epoch 3441 +2024-11-22 05:25:11.925190: Current learning rate: 0.00603 +2024-11-22 05:25:30.566041: train_loss -0.7926 +2024-11-22 05:25:30.566303: val_loss -0.7429 +2024-11-22 05:25:30.566381: Pseudo dice [0.8273] +2024-11-22 05:25:30.566471: Epoch time: 18.64 s +2024-11-22 05:25:31.516853: +2024-11-22 05:25:31.517062: Epoch 3442 +2024-11-22 05:25:31.517169: Current learning rate: 0.00603 +2024-11-22 05:25:49.476431: train_loss -0.7899 +2024-11-22 05:25:49.476723: val_loss -0.7632 +2024-11-22 05:25:49.476825: Pseudo dice [0.8578] +2024-11-22 05:25:49.476903: Epoch time: 17.96 s +2024-11-22 05:25:50.372143: +2024-11-22 05:25:50.372365: Epoch 3443 +2024-11-22 05:25:50.372475: Current learning rate: 0.00603 +2024-11-22 05:26:09.935791: train_loss -0.7855 +2024-11-22 05:26:09.936075: val_loss -0.7412 +2024-11-22 05:26:09.936152: Pseudo dice [0.8499] +2024-11-22 05:26:09.936229: Epoch time: 19.56 s +2024-11-22 05:26:10.799239: +2024-11-22 05:26:10.799442: Epoch 3444 +2024-11-22 05:26:10.799554: Current learning rate: 0.00602 +2024-11-22 05:26:28.928138: train_loss -0.7825 +2024-11-22 05:26:28.928411: val_loss -0.7267 +2024-11-22 05:26:28.928493: Pseudo dice [0.8409] +2024-11-22 05:26:28.928582: Epoch time: 18.13 s +2024-11-22 05:26:29.796669: +2024-11-22 05:26:29.796881: Epoch 3445 +2024-11-22 05:26:29.796998: Current learning rate: 0.00602 +2024-11-22 05:26:48.154122: train_loss -0.785 +2024-11-22 05:26:48.154361: val_loss -0.7522 +2024-11-22 05:26:48.154435: Pseudo dice [0.8248] +2024-11-22 05:26:48.154514: Epoch time: 18.36 s +2024-11-22 05:26:49.077187: +2024-11-22 05:26:49.077388: Epoch 3446 +2024-11-22 05:26:49.077496: Current learning rate: 0.00602 +2024-11-22 05:27:08.818756: train_loss -0.792 +2024-11-22 05:27:08.819044: val_loss -0.757 +2024-11-22 05:27:08.819125: Pseudo dice [0.8283] +2024-11-22 05:27:08.819203: Epoch time: 19.74 s +2024-11-22 05:27:09.709514: +2024-11-22 05:27:09.709760: Epoch 3447 +2024-11-22 05:27:09.709877: Current learning rate: 0.00602 +2024-11-22 05:27:29.757769: train_loss -0.7862 +2024-11-22 05:27:29.758044: val_loss -0.7509 +2024-11-22 05:27:29.758183: Pseudo dice [0.8444] +2024-11-22 05:27:29.758268: Epoch time: 20.05 s +2024-11-22 05:27:30.655392: +2024-11-22 05:27:30.655628: Epoch 3448 +2024-11-22 05:27:30.655745: Current learning rate: 0.00602 +2024-11-22 05:27:48.741303: train_loss -0.7908 +2024-11-22 05:27:48.741544: val_loss -0.73 +2024-11-22 05:27:48.741624: Pseudo dice [0.8216] +2024-11-22 05:27:48.741717: Epoch time: 18.09 s +2024-11-22 05:27:49.636613: +2024-11-22 05:27:49.636821: Epoch 3449 +2024-11-22 05:27:49.636942: Current learning rate: 0.00602 +2024-11-22 05:28:08.029037: train_loss -0.7866 +2024-11-22 05:28:08.029255: val_loss -0.7198 +2024-11-22 05:28:08.029332: Pseudo dice [0.8271] +2024-11-22 05:28:08.029415: Epoch time: 18.39 s +2024-11-22 05:28:09.154851: +2024-11-22 05:28:09.155140: Epoch 3450 +2024-11-22 05:28:09.155253: Current learning rate: 0.00602 +2024-11-22 05:28:27.255227: train_loss -0.7844 +2024-11-22 05:28:27.255451: val_loss -0.7687 +2024-11-22 05:28:27.255525: Pseudo dice [0.841] +2024-11-22 05:28:27.255603: Epoch time: 18.1 s +2024-11-22 05:28:28.235654: +2024-11-22 05:28:28.235869: Epoch 3451 +2024-11-22 05:28:28.235979: Current learning rate: 0.00602 +2024-11-22 05:28:46.453241: train_loss -0.7897 +2024-11-22 05:28:46.453461: val_loss -0.7409 +2024-11-22 05:28:46.453541: Pseudo dice [0.8438] +2024-11-22 05:28:46.453623: Epoch time: 18.22 s +2024-11-22 05:28:47.357555: +2024-11-22 05:28:47.357785: Epoch 3452 +2024-11-22 05:28:47.357905: Current learning rate: 0.00602 +2024-11-22 05:29:05.818759: train_loss -0.7918 +2024-11-22 05:29:05.819019: val_loss -0.7403 +2024-11-22 05:29:05.819098: Pseudo dice [0.8449] +2024-11-22 05:29:05.819180: Epoch time: 18.46 s +2024-11-22 05:29:06.695613: +2024-11-22 05:29:06.695832: Epoch 3453 +2024-11-22 05:29:06.695948: Current learning rate: 0.00601 +2024-11-22 05:29:25.108736: train_loss -0.7822 +2024-11-22 05:29:25.108980: val_loss -0.7416 +2024-11-22 05:29:25.109062: Pseudo dice [0.8258] +2024-11-22 05:29:25.109139: Epoch time: 18.41 s +2024-11-22 05:29:25.995904: +2024-11-22 05:29:25.996171: Epoch 3454 +2024-11-22 05:29:25.996283: Current learning rate: 0.00601 +2024-11-22 05:29:45.356837: train_loss -0.7845 +2024-11-22 05:29:45.357052: val_loss -0.7582 +2024-11-22 05:29:45.357130: Pseudo dice [0.8598] +2024-11-22 05:29:45.357206: Epoch time: 19.36 s +2024-11-22 05:29:46.558244: +2024-11-22 05:29:46.558424: Epoch 3455 +2024-11-22 05:29:46.558522: Current learning rate: 0.00601 +2024-11-22 05:30:04.531362: train_loss -0.7926 +2024-11-22 05:30:04.531699: val_loss -0.7485 +2024-11-22 05:30:04.531777: Pseudo dice [0.8163] +2024-11-22 05:30:04.531862: Epoch time: 17.97 s +2024-11-22 05:30:05.413154: +2024-11-22 05:30:05.413362: Epoch 3456 +2024-11-22 05:30:05.413471: Current learning rate: 0.00601 +2024-11-22 05:30:22.625127: train_loss -0.7899 +2024-11-22 05:30:22.625363: val_loss -0.755 +2024-11-22 05:30:22.625442: Pseudo dice [0.8488] +2024-11-22 05:30:22.625518: Epoch time: 17.21 s +2024-11-22 05:30:23.509303: +2024-11-22 05:30:23.509592: Epoch 3457 +2024-11-22 05:30:23.509710: Current learning rate: 0.00601 +2024-11-22 05:30:43.321581: train_loss -0.7855 +2024-11-22 05:30:43.321805: val_loss -0.7182 +2024-11-22 05:30:43.321881: Pseudo dice [0.8368] +2024-11-22 05:30:43.321961: Epoch time: 19.81 s +2024-11-22 05:30:44.191871: +2024-11-22 05:30:44.192069: Epoch 3458 +2024-11-22 05:30:44.192172: Current learning rate: 0.00601 +2024-11-22 05:31:02.986746: train_loss -0.7881 +2024-11-22 05:31:02.986968: val_loss -0.7431 +2024-11-22 05:31:02.987051: Pseudo dice [0.837] +2024-11-22 05:31:02.987139: Epoch time: 18.8 s +2024-11-22 05:31:03.856553: +2024-11-22 05:31:03.856770: Epoch 3459 +2024-11-22 05:31:03.856884: Current learning rate: 0.00601 +2024-11-22 05:31:23.516670: train_loss -0.7772 +2024-11-22 05:31:23.516938: val_loss -0.7283 +2024-11-22 05:31:23.517027: Pseudo dice [0.8493] +2024-11-22 05:31:23.517113: Epoch time: 19.66 s +2024-11-22 05:31:24.423362: +2024-11-22 05:31:24.423570: Epoch 3460 +2024-11-22 05:31:24.423689: Current learning rate: 0.00601 +2024-11-22 05:31:43.468084: train_loss -0.7811 +2024-11-22 05:31:43.468344: val_loss -0.7655 +2024-11-22 05:31:43.468427: Pseudo dice [0.8386] +2024-11-22 05:31:43.468506: Epoch time: 19.04 s +2024-11-22 05:31:44.499166: +2024-11-22 05:31:44.499361: Epoch 3461 +2024-11-22 05:31:44.499473: Current learning rate: 0.006 +2024-11-22 05:32:02.398415: train_loss -0.7882 +2024-11-22 05:32:02.400788: val_loss -0.7588 +2024-11-22 05:32:02.400916: Pseudo dice [0.8505] +2024-11-22 05:32:02.401009: Epoch time: 17.9 s +2024-11-22 05:32:03.469469: +2024-11-22 05:32:03.469685: Epoch 3462 +2024-11-22 05:32:03.469801: Current learning rate: 0.006 +2024-11-22 05:32:22.350439: train_loss -0.7896 +2024-11-22 05:32:22.350651: val_loss -0.7481 +2024-11-22 05:32:22.350729: Pseudo dice [0.8424] +2024-11-22 05:32:22.350811: Epoch time: 18.88 s +2024-11-22 05:32:23.217715: +2024-11-22 05:32:23.217965: Epoch 3463 +2024-11-22 05:32:23.218086: Current learning rate: 0.006 +2024-11-22 05:32:42.577690: train_loss -0.7869 +2024-11-22 05:32:42.577900: val_loss -0.7146 +2024-11-22 05:32:42.577977: Pseudo dice [0.8492] +2024-11-22 05:32:42.578061: Epoch time: 19.36 s +2024-11-22 05:32:43.500879: +2024-11-22 05:32:43.501084: Epoch 3464 +2024-11-22 05:32:43.501199: Current learning rate: 0.006 +2024-11-22 05:33:02.710725: train_loss -0.7864 +2024-11-22 05:33:02.710918: val_loss -0.7415 +2024-11-22 05:33:02.710998: Pseudo dice [0.8428] +2024-11-22 05:33:02.711090: Epoch time: 19.21 s +2024-11-22 05:33:03.589461: +2024-11-22 05:33:03.589663: Epoch 3465 +2024-11-22 05:33:03.589780: Current learning rate: 0.006 +2024-11-22 05:33:22.774518: train_loss -0.7931 +2024-11-22 05:33:22.774740: val_loss -0.722 +2024-11-22 05:33:22.774814: Pseudo dice [0.8302] +2024-11-22 05:33:22.774891: Epoch time: 19.19 s +2024-11-22 05:33:23.639189: +2024-11-22 05:33:23.639376: Epoch 3466 +2024-11-22 05:33:23.639473: Current learning rate: 0.006 +2024-11-22 05:33:42.900043: train_loss -0.7866 +2024-11-22 05:33:42.900292: val_loss -0.735 +2024-11-22 05:33:42.905591: Pseudo dice [0.849] +2024-11-22 05:33:42.905696: Epoch time: 19.26 s +2024-11-22 05:33:44.240574: +2024-11-22 05:33:44.240797: Epoch 3467 +2024-11-22 05:33:44.240909: Current learning rate: 0.006 +2024-11-22 05:34:03.024472: train_loss -0.782 +2024-11-22 05:34:03.024731: val_loss -0.7231 +2024-11-22 05:34:03.024833: Pseudo dice [0.8297] +2024-11-22 05:34:03.024919: Epoch time: 18.78 s +2024-11-22 05:34:03.901185: +2024-11-22 05:34:03.901400: Epoch 3468 +2024-11-22 05:34:03.901503: Current learning rate: 0.006 +2024-11-22 05:34:22.844718: train_loss -0.7919 +2024-11-22 05:34:22.845003: val_loss -0.7572 +2024-11-22 05:34:22.845078: Pseudo dice [0.8221] +2024-11-22 05:34:22.845155: Epoch time: 18.94 s +2024-11-22 05:34:23.776094: +2024-11-22 05:34:23.776314: Epoch 3469 +2024-11-22 05:34:23.776425: Current learning rate: 0.006 +2024-11-22 05:34:42.646422: train_loss -0.7824 +2024-11-22 05:34:42.646692: val_loss -0.7225 +2024-11-22 05:34:42.646770: Pseudo dice [0.8328] +2024-11-22 05:34:42.646929: Epoch time: 18.87 s +2024-11-22 05:34:43.544010: +2024-11-22 05:34:43.544232: Epoch 3470 +2024-11-22 05:34:43.544344: Current learning rate: 0.00599 +2024-11-22 05:35:02.016087: train_loss -0.7939 +2024-11-22 05:35:02.016307: val_loss -0.7524 +2024-11-22 05:35:02.016383: Pseudo dice [0.8533] +2024-11-22 05:35:02.016461: Epoch time: 18.47 s +2024-11-22 05:35:02.899065: +2024-11-22 05:35:02.899279: Epoch 3471 +2024-11-22 05:35:02.899389: Current learning rate: 0.00599 +2024-11-22 05:35:21.424900: train_loss -0.7899 +2024-11-22 05:35:21.425122: val_loss -0.7656 +2024-11-22 05:35:21.425197: Pseudo dice [0.8586] +2024-11-22 05:35:21.425277: Epoch time: 18.53 s +2024-11-22 05:35:22.348122: +2024-11-22 05:35:22.348321: Epoch 3472 +2024-11-22 05:35:22.348433: Current learning rate: 0.00599 +2024-11-22 05:35:41.722400: train_loss -0.7767 +2024-11-22 05:35:41.722626: val_loss -0.7294 +2024-11-22 05:35:41.722708: Pseudo dice [0.8475] +2024-11-22 05:35:41.722845: Epoch time: 19.38 s +2024-11-22 05:35:42.611700: +2024-11-22 05:35:42.611931: Epoch 3473 +2024-11-22 05:35:42.612042: Current learning rate: 0.00599 +2024-11-22 05:36:01.882191: train_loss -0.7745 +2024-11-22 05:36:01.882431: val_loss -0.7346 +2024-11-22 05:36:01.882559: Pseudo dice [0.8278] +2024-11-22 05:36:01.882639: Epoch time: 19.27 s +2024-11-22 05:36:02.770394: +2024-11-22 05:36:02.770878: Epoch 3474 +2024-11-22 05:36:02.771038: Current learning rate: 0.00599 +2024-11-22 05:36:21.566905: train_loss -0.7932 +2024-11-22 05:36:21.567147: val_loss -0.723 +2024-11-22 05:36:21.567221: Pseudo dice [0.8291] +2024-11-22 05:36:21.567306: Epoch time: 18.8 s +2024-11-22 05:36:22.511048: +2024-11-22 05:36:22.511255: Epoch 3475 +2024-11-22 05:36:22.511363: Current learning rate: 0.00599 +2024-11-22 05:36:39.857717: train_loss -0.7926 +2024-11-22 05:36:39.857934: val_loss -0.7298 +2024-11-22 05:36:39.858020: Pseudo dice [0.8381] +2024-11-22 05:36:39.858097: Epoch time: 17.35 s +2024-11-22 05:36:40.739467: +2024-11-22 05:36:40.739676: Epoch 3476 +2024-11-22 05:36:40.739791: Current learning rate: 0.00599 +2024-11-22 05:36:59.368420: train_loss -0.7773 +2024-11-22 05:36:59.368642: val_loss -0.7005 +2024-11-22 05:36:59.368725: Pseudo dice [0.8346] +2024-11-22 05:36:59.368800: Epoch time: 18.63 s +2024-11-22 05:37:00.245666: +2024-11-22 05:37:00.245935: Epoch 3477 +2024-11-22 05:37:00.246052: Current learning rate: 0.00599 +2024-11-22 05:37:18.935277: train_loss -0.7853 +2024-11-22 05:37:18.935523: val_loss -0.7484 +2024-11-22 05:37:18.935599: Pseudo dice [0.8544] +2024-11-22 05:37:18.935680: Epoch time: 18.69 s +2024-11-22 05:37:20.208631: +2024-11-22 05:37:20.208838: Epoch 3478 +2024-11-22 05:37:20.208955: Current learning rate: 0.00598 +2024-11-22 05:37:38.157610: train_loss -0.7826 +2024-11-22 05:37:38.157887: val_loss -0.7328 +2024-11-22 05:37:38.157964: Pseudo dice [0.8406] +2024-11-22 05:37:38.158047: Epoch time: 17.95 s +2024-11-22 05:37:39.043467: +2024-11-22 05:37:39.043699: Epoch 3479 +2024-11-22 05:37:39.043815: Current learning rate: 0.00598 +2024-11-22 05:37:58.770118: train_loss -0.7836 +2024-11-22 05:37:58.770344: val_loss -0.7635 +2024-11-22 05:37:58.770423: Pseudo dice [0.8399] +2024-11-22 05:37:58.770502: Epoch time: 19.73 s +2024-11-22 05:37:59.676004: +2024-11-22 05:37:59.676347: Epoch 3480 +2024-11-22 05:37:59.676463: Current learning rate: 0.00598 +2024-11-22 05:38:18.673522: train_loss -0.7874 +2024-11-22 05:38:18.673743: val_loss -0.741 +2024-11-22 05:38:18.673820: Pseudo dice [0.8637] +2024-11-22 05:38:18.673894: Epoch time: 19.0 s +2024-11-22 05:38:19.556652: +2024-11-22 05:38:19.556878: Epoch 3481 +2024-11-22 05:38:19.556996: Current learning rate: 0.00598 +2024-11-22 05:38:38.637101: train_loss -0.7915 +2024-11-22 05:38:38.637353: val_loss -0.7803 +2024-11-22 05:38:38.637431: Pseudo dice [0.8633] +2024-11-22 05:38:38.637514: Epoch time: 19.08 s +2024-11-22 05:38:39.524747: +2024-11-22 05:38:39.524942: Epoch 3482 +2024-11-22 05:38:39.525055: Current learning rate: 0.00598 +2024-11-22 05:38:58.552948: train_loss -0.7919 +2024-11-22 05:38:58.553209: val_loss -0.7439 +2024-11-22 05:38:58.553287: Pseudo dice [0.8221] +2024-11-22 05:38:58.553366: Epoch time: 19.03 s +2024-11-22 05:38:59.441652: +2024-11-22 05:38:59.441936: Epoch 3483 +2024-11-22 05:38:59.442059: Current learning rate: 0.00598 +2024-11-22 05:39:17.508396: train_loss -0.783 +2024-11-22 05:39:17.508645: val_loss -0.7359 +2024-11-22 05:39:17.508732: Pseudo dice [0.8532] +2024-11-22 05:39:17.508811: Epoch time: 18.07 s +2024-11-22 05:39:18.388087: +2024-11-22 05:39:18.388308: Epoch 3484 +2024-11-22 05:39:18.388420: Current learning rate: 0.00598 +2024-11-22 05:39:36.871894: train_loss -0.7879 +2024-11-22 05:39:36.872116: val_loss -0.7395 +2024-11-22 05:39:36.872192: Pseudo dice [0.8612] +2024-11-22 05:39:36.872294: Epoch time: 18.48 s +2024-11-22 05:39:37.771118: +2024-11-22 05:39:37.771373: Epoch 3485 +2024-11-22 05:39:37.771488: Current learning rate: 0.00598 +2024-11-22 05:39:57.111953: train_loss -0.7847 +2024-11-22 05:39:57.112201: val_loss -0.7192 +2024-11-22 05:39:57.112277: Pseudo dice [0.8088] +2024-11-22 05:39:57.112356: Epoch time: 19.34 s +2024-11-22 05:39:57.989521: +2024-11-22 05:39:57.989722: Epoch 3486 +2024-11-22 05:39:57.989834: Current learning rate: 0.00597 +2024-11-22 05:40:16.947214: train_loss -0.7823 +2024-11-22 05:40:16.947468: val_loss -0.7669 +2024-11-22 05:40:16.947554: Pseudo dice [0.8537] +2024-11-22 05:40:16.947635: Epoch time: 18.96 s +2024-11-22 05:40:17.827442: +2024-11-22 05:40:17.827687: Epoch 3487 +2024-11-22 05:40:17.827809: Current learning rate: 0.00597 +2024-11-22 05:40:36.379430: train_loss -0.7814 +2024-11-22 05:40:36.379687: val_loss -0.7187 +2024-11-22 05:40:36.379766: Pseudo dice [0.8149] +2024-11-22 05:40:36.379886: Epoch time: 18.55 s +2024-11-22 05:40:37.272729: +2024-11-22 05:40:37.272919: Epoch 3488 +2024-11-22 05:40:37.273035: Current learning rate: 0.00597 +2024-11-22 05:40:55.814040: train_loss -0.78 +2024-11-22 05:40:55.814276: val_loss -0.7581 +2024-11-22 05:40:55.814348: Pseudo dice [0.8394] +2024-11-22 05:40:55.814431: Epoch time: 18.54 s +2024-11-22 05:40:57.194115: +2024-11-22 05:40:57.194319: Epoch 3489 +2024-11-22 05:40:57.194437: Current learning rate: 0.00597 +2024-11-22 05:41:16.194531: train_loss -0.7819 +2024-11-22 05:41:16.194752: val_loss -0.769 +2024-11-22 05:41:16.194830: Pseudo dice [0.8579] +2024-11-22 05:41:16.194984: Epoch time: 19.0 s +2024-11-22 05:41:17.099281: +2024-11-22 05:41:17.099508: Epoch 3490 +2024-11-22 05:41:17.099622: Current learning rate: 0.00597 +2024-11-22 05:41:36.343518: train_loss -0.7774 +2024-11-22 05:41:36.343716: val_loss -0.7795 +2024-11-22 05:41:36.343789: Pseudo dice [0.8487] +2024-11-22 05:41:36.343865: Epoch time: 19.25 s +2024-11-22 05:41:37.261043: +2024-11-22 05:41:37.261269: Epoch 3491 +2024-11-22 05:41:37.261382: Current learning rate: 0.00597 +2024-11-22 05:41:55.445569: train_loss -0.7855 +2024-11-22 05:41:55.445792: val_loss -0.7407 +2024-11-22 05:41:55.445868: Pseudo dice [0.8527] +2024-11-22 05:41:55.445944: Epoch time: 18.19 s +2024-11-22 05:41:56.332465: +2024-11-22 05:41:56.332697: Epoch 3492 +2024-11-22 05:41:56.332812: Current learning rate: 0.00597 +2024-11-22 05:42:15.352623: train_loss -0.7831 +2024-11-22 05:42:15.352857: val_loss -0.7462 +2024-11-22 05:42:15.352933: Pseudo dice [0.8482] +2024-11-22 05:42:15.353126: Epoch time: 19.02 s +2024-11-22 05:42:16.235531: +2024-11-22 05:42:16.235734: Epoch 3493 +2024-11-22 05:42:16.235852: Current learning rate: 0.00597 +2024-11-22 05:42:34.750187: train_loss -0.7958 +2024-11-22 05:42:34.750410: val_loss -0.739 +2024-11-22 05:42:34.753691: Pseudo dice [0.8465] +2024-11-22 05:42:34.753797: Epoch time: 18.52 s +2024-11-22 05:42:35.681976: +2024-11-22 05:42:35.682191: Epoch 3494 +2024-11-22 05:42:35.682304: Current learning rate: 0.00597 +2024-11-22 05:42:54.740655: train_loss -0.7915 +2024-11-22 05:42:54.740875: val_loss -0.7317 +2024-11-22 05:42:54.741007: Pseudo dice [0.8457] +2024-11-22 05:42:54.741096: Epoch time: 19.06 s +2024-11-22 05:42:55.627973: +2024-11-22 05:42:55.628193: Epoch 3495 +2024-11-22 05:42:55.628304: Current learning rate: 0.00596 +2024-11-22 05:43:13.791466: train_loss -0.7958 +2024-11-22 05:43:13.791693: val_loss -0.756 +2024-11-22 05:43:13.791770: Pseudo dice [0.8542] +2024-11-22 05:43:13.791853: Epoch time: 18.16 s +2024-11-22 05:43:14.675596: +2024-11-22 05:43:14.675815: Epoch 3496 +2024-11-22 05:43:14.675929: Current learning rate: 0.00596 +2024-11-22 05:43:33.769886: train_loss -0.7873 +2024-11-22 05:43:33.775329: val_loss -0.7715 +2024-11-22 05:43:33.775415: Pseudo dice [0.8497] +2024-11-22 05:43:33.775510: Epoch time: 19.1 s +2024-11-22 05:43:33.775577: Yayy! New best EMA pseudo Dice: 0.8458 +2024-11-22 05:43:34.921330: +2024-11-22 05:43:34.921545: Epoch 3497 +2024-11-22 05:43:34.921652: Current learning rate: 0.00596 +2024-11-22 05:43:53.689507: train_loss -0.7846 +2024-11-22 05:43:53.689729: val_loss -0.7646 +2024-11-22 05:43:53.689807: Pseudo dice [0.8406] +2024-11-22 05:43:53.689884: Epoch time: 18.77 s +2024-11-22 05:43:54.648984: +2024-11-22 05:43:54.649198: Epoch 3498 +2024-11-22 05:43:54.649309: Current learning rate: 0.00596 +2024-11-22 05:44:13.512561: train_loss -0.7863 +2024-11-22 05:44:13.512775: val_loss -0.7619 +2024-11-22 05:44:13.512847: Pseudo dice [0.839] +2024-11-22 05:44:13.512922: Epoch time: 18.86 s +2024-11-22 05:44:14.391641: +2024-11-22 05:44:14.391848: Epoch 3499 +2024-11-22 05:44:14.391963: Current learning rate: 0.00596 +2024-11-22 05:44:32.559518: train_loss -0.7911 +2024-11-22 05:44:32.559787: val_loss -0.739 +2024-11-22 05:44:32.559866: Pseudo dice [0.8335] +2024-11-22 05:44:32.560019: Epoch time: 18.17 s +2024-11-22 05:44:34.066988: +2024-11-22 05:44:34.067259: Epoch 3500 +2024-11-22 05:44:34.067375: Current learning rate: 0.00596 +2024-11-22 05:44:53.420154: train_loss -0.7743 +2024-11-22 05:44:53.422567: val_loss -0.7268 +2024-11-22 05:44:53.422654: Pseudo dice [0.8216] +2024-11-22 05:44:53.422736: Epoch time: 19.35 s +2024-11-22 05:44:54.443939: +2024-11-22 05:44:54.444162: Epoch 3501 +2024-11-22 05:44:54.444275: Current learning rate: 0.00596 +2024-11-22 05:45:12.363629: train_loss -0.7785 +2024-11-22 05:45:12.363860: val_loss -0.7244 +2024-11-22 05:45:12.363940: Pseudo dice [0.8192] +2024-11-22 05:45:12.364028: Epoch time: 17.92 s +2024-11-22 05:45:13.393860: +2024-11-22 05:45:13.394082: Epoch 3502 +2024-11-22 05:45:13.394199: Current learning rate: 0.00596 +2024-11-22 05:45:32.195134: train_loss -0.7819 +2024-11-22 05:45:32.195385: val_loss -0.7432 +2024-11-22 05:45:32.195461: Pseudo dice [0.8579] +2024-11-22 05:45:32.195544: Epoch time: 18.8 s +2024-11-22 05:45:33.089082: +2024-11-22 05:45:33.089414: Epoch 3503 +2024-11-22 05:45:33.089530: Current learning rate: 0.00595 +2024-11-22 05:45:51.030539: train_loss -0.7715 +2024-11-22 05:45:51.030788: val_loss -0.705 +2024-11-22 05:45:51.030909: Pseudo dice [0.8133] +2024-11-22 05:45:51.030987: Epoch time: 17.94 s +2024-11-22 05:45:51.922738: +2024-11-22 05:45:51.922972: Epoch 3504 +2024-11-22 05:45:51.923090: Current learning rate: 0.00595 +2024-11-22 05:46:10.756621: train_loss -0.7847 +2024-11-22 05:46:10.756844: val_loss -0.7443 +2024-11-22 05:46:10.756918: Pseudo dice [0.8359] +2024-11-22 05:46:10.757004: Epoch time: 18.83 s +2024-11-22 05:46:11.638692: +2024-11-22 05:46:11.638905: Epoch 3505 +2024-11-22 05:46:11.639027: Current learning rate: 0.00595 +2024-11-22 05:46:30.734442: train_loss -0.7872 +2024-11-22 05:46:30.734725: val_loss -0.7534 +2024-11-22 05:46:30.734807: Pseudo dice [0.8104] +2024-11-22 05:46:30.734894: Epoch time: 19.1 s +2024-11-22 05:46:31.617564: +2024-11-22 05:46:31.617787: Epoch 3506 +2024-11-22 05:46:31.617901: Current learning rate: 0.00595 +2024-11-22 05:46:50.829493: train_loss -0.7841 +2024-11-22 05:46:50.829753: val_loss -0.771 +2024-11-22 05:46:50.829832: Pseudo dice [0.866] +2024-11-22 05:46:50.829920: Epoch time: 19.21 s +2024-11-22 05:46:51.716009: +2024-11-22 05:46:51.716263: Epoch 3507 +2024-11-22 05:46:51.716383: Current learning rate: 0.00595 +2024-11-22 05:47:10.856899: train_loss -0.7837 +2024-11-22 05:47:10.857130: val_loss -0.7389 +2024-11-22 05:47:10.857208: Pseudo dice [0.8106] +2024-11-22 05:47:10.857285: Epoch time: 19.14 s +2024-11-22 05:47:11.750750: +2024-11-22 05:47:11.750956: Epoch 3508 +2024-11-22 05:47:11.751072: Current learning rate: 0.00595 +2024-11-22 05:47:30.504042: train_loss -0.7881 +2024-11-22 05:47:30.504283: val_loss -0.721 +2024-11-22 05:47:30.504360: Pseudo dice [0.8146] +2024-11-22 05:47:30.504436: Epoch time: 18.75 s +2024-11-22 05:47:31.382795: +2024-11-22 05:47:31.383018: Epoch 3509 +2024-11-22 05:47:31.383134: Current learning rate: 0.00595 +2024-11-22 05:47:50.233924: train_loss -0.7778 +2024-11-22 05:47:50.234143: val_loss -0.7153 +2024-11-22 05:47:50.234273: Pseudo dice [0.8101] +2024-11-22 05:47:50.234377: Epoch time: 18.85 s +2024-11-22 05:47:51.237358: +2024-11-22 05:47:51.237580: Epoch 3510 +2024-11-22 05:47:51.237689: Current learning rate: 0.00595 +2024-11-22 05:48:10.351619: train_loss -0.788 +2024-11-22 05:48:10.351873: val_loss -0.729 +2024-11-22 05:48:10.351951: Pseudo dice [0.862] +2024-11-22 05:48:10.352042: Epoch time: 19.12 s +2024-11-22 05:48:11.665952: +2024-11-22 05:48:11.666170: Epoch 3511 +2024-11-22 05:48:11.666275: Current learning rate: 0.00595 +2024-11-22 05:48:30.585546: train_loss -0.7978 +2024-11-22 05:48:30.585769: val_loss -0.7443 +2024-11-22 05:48:30.585846: Pseudo dice [0.8247] +2024-11-22 05:48:30.585922: Epoch time: 18.92 s +2024-11-22 05:48:31.604009: +2024-11-22 05:48:31.604230: Epoch 3512 +2024-11-22 05:48:31.604342: Current learning rate: 0.00594 +2024-11-22 05:48:50.562910: train_loss -0.7989 +2024-11-22 05:48:50.563130: val_loss -0.7486 +2024-11-22 05:48:50.564304: Pseudo dice [0.8387] +2024-11-22 05:48:50.564409: Epoch time: 18.96 s +2024-11-22 05:48:51.541605: +2024-11-22 05:48:51.541814: Epoch 3513 +2024-11-22 05:48:51.541924: Current learning rate: 0.00594 +2024-11-22 05:49:10.093559: train_loss -0.7855 +2024-11-22 05:49:10.093801: val_loss -0.7333 +2024-11-22 05:49:10.093875: Pseudo dice [0.8186] +2024-11-22 05:49:10.093958: Epoch time: 18.55 s +2024-11-22 05:49:10.957376: +2024-11-22 05:49:10.957589: Epoch 3514 +2024-11-22 05:49:10.957698: Current learning rate: 0.00594 +2024-11-22 05:49:29.979372: train_loss -0.7918 +2024-11-22 05:49:29.979587: val_loss -0.7178 +2024-11-22 05:49:29.984877: Pseudo dice [0.8304] +2024-11-22 05:49:29.985003: Epoch time: 19.02 s +2024-11-22 05:49:31.003361: +2024-11-22 05:49:31.003573: Epoch 3515 +2024-11-22 05:49:31.003689: Current learning rate: 0.00594 +2024-11-22 05:49:50.956186: train_loss -0.7897 +2024-11-22 05:49:50.956421: val_loss -0.7384 +2024-11-22 05:49:50.956716: Pseudo dice [0.8279] +2024-11-22 05:49:50.956799: Epoch time: 19.95 s +2024-11-22 05:49:51.833985: +2024-11-22 05:49:51.834197: Epoch 3516 +2024-11-22 05:49:51.834312: Current learning rate: 0.00594 +2024-11-22 05:50:10.324869: train_loss -0.782 +2024-11-22 05:50:10.325092: val_loss -0.7406 +2024-11-22 05:50:10.325166: Pseudo dice [0.8523] +2024-11-22 05:50:10.325243: Epoch time: 18.49 s +2024-11-22 05:50:11.199949: +2024-11-22 05:50:11.200178: Epoch 3517 +2024-11-22 05:50:11.200292: Current learning rate: 0.00594 +2024-11-22 05:50:30.219949: train_loss -0.7696 +2024-11-22 05:50:30.220222: val_loss -0.7267 +2024-11-22 05:50:30.220300: Pseudo dice [0.8393] +2024-11-22 05:50:30.220385: Epoch time: 19.02 s +2024-11-22 05:50:31.102710: +2024-11-22 05:50:31.102925: Epoch 3518 +2024-11-22 05:50:31.103039: Current learning rate: 0.00594 +2024-11-22 05:50:50.166497: train_loss -0.7551 +2024-11-22 05:50:50.166716: val_loss -0.7408 +2024-11-22 05:50:50.166790: Pseudo dice [0.8415] +2024-11-22 05:50:50.166867: Epoch time: 19.06 s +2024-11-22 05:50:51.046615: +2024-11-22 05:50:51.046818: Epoch 3519 +2024-11-22 05:50:51.046931: Current learning rate: 0.00594 +2024-11-22 05:51:09.211694: train_loss -0.7797 +2024-11-22 05:51:09.211905: val_loss -0.7328 +2024-11-22 05:51:09.211985: Pseudo dice [0.839] +2024-11-22 05:51:09.212095: Epoch time: 18.17 s +2024-11-22 05:51:10.089119: +2024-11-22 05:51:10.089327: Epoch 3520 +2024-11-22 05:51:10.089442: Current learning rate: 0.00593 +2024-11-22 05:51:28.931763: train_loss -0.7772 +2024-11-22 05:51:28.931988: val_loss -0.7121 +2024-11-22 05:51:28.932071: Pseudo dice [0.819] +2024-11-22 05:51:28.932147: Epoch time: 18.84 s +2024-11-22 05:51:29.811774: +2024-11-22 05:51:29.812004: Epoch 3521 +2024-11-22 05:51:29.812118: Current learning rate: 0.00593 +2024-11-22 05:51:47.992472: train_loss -0.7797 +2024-11-22 05:51:47.992733: val_loss -0.7489 +2024-11-22 05:51:47.992810: Pseudo dice [0.8551] +2024-11-22 05:51:47.992896: Epoch time: 18.18 s +2024-11-22 05:51:49.314481: +2024-11-22 05:51:49.314692: Epoch 3522 +2024-11-22 05:51:49.314810: Current learning rate: 0.00593 +2024-11-22 05:52:08.790376: train_loss -0.7775 +2024-11-22 05:52:08.790600: val_loss -0.7784 +2024-11-22 05:52:08.790675: Pseudo dice [0.8447] +2024-11-22 05:52:08.790752: Epoch time: 19.48 s +2024-11-22 05:52:09.867191: +2024-11-22 05:52:09.867423: Epoch 3523 +2024-11-22 05:52:09.867537: Current learning rate: 0.00593 +2024-11-22 05:52:28.049687: train_loss -0.784 +2024-11-22 05:52:28.049912: val_loss -0.7545 +2024-11-22 05:52:28.050000: Pseudo dice [0.833] +2024-11-22 05:52:28.050080: Epoch time: 18.18 s +2024-11-22 05:52:28.933554: +2024-11-22 05:52:28.933809: Epoch 3524 +2024-11-22 05:52:28.933924: Current learning rate: 0.00593 +2024-11-22 05:52:47.030637: train_loss -0.7849 +2024-11-22 05:52:47.030896: val_loss -0.7316 +2024-11-22 05:52:47.031077: Pseudo dice [0.8257] +2024-11-22 05:52:47.031171: Epoch time: 18.1 s +2024-11-22 05:52:47.919875: +2024-11-22 05:52:47.920092: Epoch 3525 +2024-11-22 05:52:47.920208: Current learning rate: 0.00593 +2024-11-22 05:53:08.225632: train_loss -0.7857 +2024-11-22 05:53:08.225844: val_loss -0.7252 +2024-11-22 05:53:08.225920: Pseudo dice [0.8213] +2024-11-22 05:53:08.226011: Epoch time: 20.31 s +2024-11-22 05:53:09.121188: +2024-11-22 05:53:09.121385: Epoch 3526 +2024-11-22 05:53:09.121494: Current learning rate: 0.00593 +2024-11-22 05:53:26.906026: train_loss -0.7886 +2024-11-22 05:53:26.906249: val_loss -0.7431 +2024-11-22 05:53:26.906326: Pseudo dice [0.8433] +2024-11-22 05:53:26.906409: Epoch time: 17.79 s +2024-11-22 05:53:27.791129: +2024-11-22 05:53:27.791346: Epoch 3527 +2024-11-22 05:53:27.791460: Current learning rate: 0.00593 +2024-11-22 05:53:46.599862: train_loss -0.7921 +2024-11-22 05:53:46.600091: val_loss -0.748 +2024-11-22 05:53:46.600163: Pseudo dice [0.8191] +2024-11-22 05:53:46.600237: Epoch time: 18.81 s +2024-11-22 05:53:47.483230: +2024-11-22 05:53:47.483444: Epoch 3528 +2024-11-22 05:53:47.483555: Current learning rate: 0.00592 +2024-11-22 05:54:06.471461: train_loss -0.7859 +2024-11-22 05:54:06.471714: val_loss -0.737 +2024-11-22 05:54:06.471790: Pseudo dice [0.8469] +2024-11-22 05:54:06.471871: Epoch time: 18.99 s +2024-11-22 05:54:07.441977: +2024-11-22 05:54:07.442184: Epoch 3529 +2024-11-22 05:54:07.442306: Current learning rate: 0.00592 +2024-11-22 05:54:25.133011: train_loss -0.7851 +2024-11-22 05:54:25.133237: val_loss -0.7111 +2024-11-22 05:54:25.133314: Pseudo dice [0.8361] +2024-11-22 05:54:25.133392: Epoch time: 17.69 s +2024-11-22 05:54:26.081308: +2024-11-22 05:54:26.081550: Epoch 3530 +2024-11-22 05:54:26.081662: Current learning rate: 0.00592 +2024-11-22 05:54:45.212829: train_loss -0.785 +2024-11-22 05:54:45.213051: val_loss -0.7398 +2024-11-22 05:54:45.213126: Pseudo dice [0.8394] +2024-11-22 05:54:45.213204: Epoch time: 19.13 s +2024-11-22 05:54:46.090277: +2024-11-22 05:54:46.090474: Epoch 3531 +2024-11-22 05:54:46.090584: Current learning rate: 0.00592 +2024-11-22 05:55:04.468312: train_loss -0.7883 +2024-11-22 05:55:04.468551: val_loss -0.7401 +2024-11-22 05:55:04.468629: Pseudo dice [0.8453] +2024-11-22 05:55:04.468706: Epoch time: 18.38 s +2024-11-22 05:55:05.363192: +2024-11-22 05:55:05.363418: Epoch 3532 +2024-11-22 05:55:05.363534: Current learning rate: 0.00592 +2024-11-22 05:55:24.039462: train_loss -0.7899 +2024-11-22 05:55:24.039708: val_loss -0.745 +2024-11-22 05:55:24.039786: Pseudo dice [0.8173] +2024-11-22 05:55:24.039877: Epoch time: 18.68 s +2024-11-22 05:55:25.331800: +2024-11-22 05:55:25.332026: Epoch 3533 +2024-11-22 05:55:25.332140: Current learning rate: 0.00592 +2024-11-22 05:55:43.323113: train_loss -0.7768 +2024-11-22 05:55:43.323623: val_loss -0.7456 +2024-11-22 05:55:43.323726: Pseudo dice [0.8424] +2024-11-22 05:55:43.323816: Epoch time: 17.99 s +2024-11-22 05:55:44.203337: +2024-11-22 05:55:44.203661: Epoch 3534 +2024-11-22 05:55:44.203773: Current learning rate: 0.00592 +2024-11-22 05:56:02.979124: train_loss -0.7902 +2024-11-22 05:56:02.979359: val_loss -0.7585 +2024-11-22 05:56:02.979437: Pseudo dice [0.8352] +2024-11-22 05:56:02.979525: Epoch time: 18.78 s +2024-11-22 05:56:03.856011: +2024-11-22 05:56:03.856293: Epoch 3535 +2024-11-22 05:56:03.856408: Current learning rate: 0.00592 +2024-11-22 05:56:23.003361: train_loss -0.7799 +2024-11-22 05:56:23.008204: val_loss -0.7464 +2024-11-22 05:56:23.008367: Pseudo dice [0.8338] +2024-11-22 05:56:23.008457: Epoch time: 19.15 s +2024-11-22 05:56:23.892615: +2024-11-22 05:56:23.892820: Epoch 3536 +2024-11-22 05:56:23.892933: Current learning rate: 0.00592 +2024-11-22 05:56:42.568935: train_loss -0.7803 +2024-11-22 05:56:42.569182: val_loss -0.721 +2024-11-22 05:56:42.569258: Pseudo dice [0.8275] +2024-11-22 05:56:42.569336: Epoch time: 18.67 s +2024-11-22 05:56:43.594100: +2024-11-22 05:56:43.594316: Epoch 3537 +2024-11-22 05:56:43.594430: Current learning rate: 0.00591 +2024-11-22 05:57:01.684725: train_loss -0.7864 +2024-11-22 05:57:01.684957: val_loss -0.7378 +2024-11-22 05:57:01.685040: Pseudo dice [0.8185] +2024-11-22 05:57:01.685120: Epoch time: 18.09 s +2024-11-22 05:57:02.575790: +2024-11-22 05:57:02.576000: Epoch 3538 +2024-11-22 05:57:02.576111: Current learning rate: 0.00591 +2024-11-22 05:57:21.172333: train_loss -0.7856 +2024-11-22 05:57:21.172553: val_loss -0.7646 +2024-11-22 05:57:21.172630: Pseudo dice [0.846] +2024-11-22 05:57:21.172707: Epoch time: 18.6 s +2024-11-22 05:57:22.052092: +2024-11-22 05:57:22.052299: Epoch 3539 +2024-11-22 05:57:22.052413: Current learning rate: 0.00591 +2024-11-22 05:57:39.775669: train_loss -0.7881 +2024-11-22 05:57:39.775909: val_loss -0.7423 +2024-11-22 05:57:39.775982: Pseudo dice [0.8211] +2024-11-22 05:57:39.776071: Epoch time: 17.72 s +2024-11-22 05:57:40.672457: +2024-11-22 05:57:40.672686: Epoch 3540 +2024-11-22 05:57:40.672799: Current learning rate: 0.00591 +2024-11-22 05:57:59.809601: train_loss -0.7739 +2024-11-22 05:57:59.809814: val_loss -0.7034 +2024-11-22 05:57:59.809888: Pseudo dice [0.8119] +2024-11-22 05:57:59.809967: Epoch time: 19.14 s +2024-11-22 05:58:00.694301: +2024-11-22 05:58:00.694506: Epoch 3541 +2024-11-22 05:58:00.694631: Current learning rate: 0.00591 +2024-11-22 05:58:20.356296: train_loss -0.7725 +2024-11-22 05:58:20.356733: val_loss -0.7417 +2024-11-22 05:58:20.356820: Pseudo dice [0.8341] +2024-11-22 05:58:20.356899: Epoch time: 19.66 s +2024-11-22 05:58:21.233985: +2024-11-22 05:58:21.234184: Epoch 3542 +2024-11-22 05:58:21.234294: Current learning rate: 0.00591 +2024-11-22 05:58:39.524843: train_loss -0.7714 +2024-11-22 05:58:39.525126: val_loss -0.7525 +2024-11-22 05:58:39.525211: Pseudo dice [0.837] +2024-11-22 05:58:39.525294: Epoch time: 18.29 s +2024-11-22 05:58:40.401365: +2024-11-22 05:58:40.401573: Epoch 3543 +2024-11-22 05:58:40.401684: Current learning rate: 0.00591 +2024-11-22 05:58:59.254895: train_loss -0.769 +2024-11-22 05:58:59.255159: val_loss -0.7279 +2024-11-22 05:58:59.255236: Pseudo dice [0.8218] +2024-11-22 05:58:59.255319: Epoch time: 18.85 s +2024-11-22 05:59:00.515380: +2024-11-22 05:59:00.515605: Epoch 3544 +2024-11-22 05:59:00.515723: Current learning rate: 0.00591 +2024-11-22 05:59:18.341705: train_loss -0.7749 +2024-11-22 05:59:18.341995: val_loss -0.694 +2024-11-22 05:59:18.342076: Pseudo dice [0.7909] +2024-11-22 05:59:18.342155: Epoch time: 17.83 s +2024-11-22 05:59:19.238004: +2024-11-22 05:59:19.238259: Epoch 3545 +2024-11-22 05:59:19.238375: Current learning rate: 0.0059 +2024-11-22 05:59:37.887129: train_loss -0.7537 +2024-11-22 05:59:37.887351: val_loss -0.7454 +2024-11-22 05:59:37.887427: Pseudo dice [0.8451] +2024-11-22 05:59:37.887507: Epoch time: 18.65 s +2024-11-22 05:59:38.763448: +2024-11-22 05:59:38.763673: Epoch 3546 +2024-11-22 05:59:38.763786: Current learning rate: 0.0059 +2024-11-22 05:59:57.417967: train_loss -0.7807 +2024-11-22 05:59:57.418264: val_loss -0.7646 +2024-11-22 05:59:57.418346: Pseudo dice [0.8586] +2024-11-22 05:59:57.418527: Epoch time: 18.66 s +2024-11-22 05:59:58.303452: +2024-11-22 05:59:58.303697: Epoch 3547 +2024-11-22 05:59:58.303811: Current learning rate: 0.0059 +2024-11-22 06:00:17.190144: train_loss -0.7782 +2024-11-22 06:00:17.190356: val_loss -0.7513 +2024-11-22 06:00:17.190431: Pseudo dice [0.8427] +2024-11-22 06:00:17.190508: Epoch time: 18.89 s +2024-11-22 06:00:18.069119: +2024-11-22 06:00:18.069334: Epoch 3548 +2024-11-22 06:00:18.069448: Current learning rate: 0.0059 +2024-11-22 06:00:37.118626: train_loss -0.7794 +2024-11-22 06:00:37.118847: val_loss -0.7214 +2024-11-22 06:00:37.118923: Pseudo dice [0.8402] +2024-11-22 06:00:37.119013: Epoch time: 19.05 s +2024-11-22 06:00:37.996111: +2024-11-22 06:00:37.996388: Epoch 3549 +2024-11-22 06:00:37.996501: Current learning rate: 0.0059 +2024-11-22 06:00:56.500309: train_loss -0.7878 +2024-11-22 06:00:56.500528: val_loss -0.7331 +2024-11-22 06:00:56.500603: Pseudo dice [0.8405] +2024-11-22 06:00:56.500686: Epoch time: 18.51 s +2024-11-22 06:00:57.616858: +2024-11-22 06:00:57.617084: Epoch 3550 +2024-11-22 06:00:57.617196: Current learning rate: 0.0059 +2024-11-22 06:01:16.584298: train_loss -0.7849 +2024-11-22 06:01:16.584538: val_loss -0.7276 +2024-11-22 06:01:16.586811: Pseudo dice [0.8076] +2024-11-22 06:01:16.586908: Epoch time: 18.97 s +2024-11-22 06:01:17.498081: +2024-11-22 06:01:17.498319: Epoch 3551 +2024-11-22 06:01:17.498430: Current learning rate: 0.0059 +2024-11-22 06:01:35.844264: train_loss -0.7832 +2024-11-22 06:01:35.844481: val_loss -0.7281 +2024-11-22 06:01:35.844563: Pseudo dice [0.8204] +2024-11-22 06:01:35.844640: Epoch time: 18.35 s +2024-11-22 06:01:36.714983: +2024-11-22 06:01:36.715178: Epoch 3552 +2024-11-22 06:01:36.715285: Current learning rate: 0.0059 +2024-11-22 06:01:56.458205: train_loss -0.7755 +2024-11-22 06:01:56.458486: val_loss -0.7355 +2024-11-22 06:01:56.458563: Pseudo dice [0.8282] +2024-11-22 06:01:56.458641: Epoch time: 19.74 s +2024-11-22 06:01:57.376287: +2024-11-22 06:01:57.376476: Epoch 3553 +2024-11-22 06:01:57.376588: Current learning rate: 0.00589 +2024-11-22 06:02:16.985741: train_loss -0.7826 +2024-11-22 06:02:16.985996: val_loss -0.774 +2024-11-22 06:02:16.986073: Pseudo dice [0.8596] +2024-11-22 06:02:16.986159: Epoch time: 19.61 s +2024-11-22 06:02:17.867517: +2024-11-22 06:02:17.867749: Epoch 3554 +2024-11-22 06:02:17.867863: Current learning rate: 0.00589 +2024-11-22 06:02:36.592209: train_loss -0.79 +2024-11-22 06:02:36.592421: val_loss -0.7255 +2024-11-22 06:02:36.592501: Pseudo dice [0.8265] +2024-11-22 06:02:36.592578: Epoch time: 18.73 s +2024-11-22 06:02:37.952577: +2024-11-22 06:02:37.952793: Epoch 3555 +2024-11-22 06:02:37.952915: Current learning rate: 0.00589 +2024-11-22 06:02:56.873926: train_loss -0.7888 +2024-11-22 06:02:56.874183: val_loss -0.7257 +2024-11-22 06:02:56.874261: Pseudo dice [0.8527] +2024-11-22 06:02:56.874341: Epoch time: 18.92 s +2024-11-22 06:02:57.756658: +2024-11-22 06:02:57.756873: Epoch 3556 +2024-11-22 06:02:57.756987: Current learning rate: 0.00589 +2024-11-22 06:03:16.434740: train_loss -0.7905 +2024-11-22 06:03:16.434964: val_loss -0.747 +2024-11-22 06:03:16.435046: Pseudo dice [0.8489] +2024-11-22 06:03:16.435124: Epoch time: 18.68 s +2024-11-22 06:03:17.316483: +2024-11-22 06:03:17.316727: Epoch 3557 +2024-11-22 06:03:17.316841: Current learning rate: 0.00589 +2024-11-22 06:03:35.162621: train_loss -0.7853 +2024-11-22 06:03:35.162849: val_loss -0.7073 +2024-11-22 06:03:35.162924: Pseudo dice [0.8201] +2024-11-22 06:03:35.163010: Epoch time: 17.85 s +2024-11-22 06:03:36.048189: +2024-11-22 06:03:36.048409: Epoch 3558 +2024-11-22 06:03:36.048515: Current learning rate: 0.00589 +2024-11-22 06:03:55.398542: train_loss -0.7753 +2024-11-22 06:03:55.398761: val_loss -0.7541 +2024-11-22 06:03:55.398838: Pseudo dice [0.8323] +2024-11-22 06:03:55.398917: Epoch time: 19.35 s +2024-11-22 06:03:56.281197: +2024-11-22 06:03:56.281430: Epoch 3559 +2024-11-22 06:03:56.281543: Current learning rate: 0.00589 +2024-11-22 06:04:14.259767: train_loss -0.7847 +2024-11-22 06:04:14.259989: val_loss -0.7482 +2024-11-22 06:04:14.260073: Pseudo dice [0.8319] +2024-11-22 06:04:14.260147: Epoch time: 17.98 s +2024-11-22 06:04:15.143630: +2024-11-22 06:04:15.143827: Epoch 3560 +2024-11-22 06:04:15.143939: Current learning rate: 0.00589 +2024-11-22 06:04:35.393063: train_loss -0.7781 +2024-11-22 06:04:35.393300: val_loss -0.721 +2024-11-22 06:04:35.393377: Pseudo dice [0.8282] +2024-11-22 06:04:35.393458: Epoch time: 20.25 s +2024-11-22 06:04:36.325538: +2024-11-22 06:04:36.325770: Epoch 3561 +2024-11-22 06:04:36.325887: Current learning rate: 0.00589 +2024-11-22 06:04:54.814882: train_loss -0.7703 +2024-11-22 06:04:54.815128: val_loss -0.7243 +2024-11-22 06:04:54.815207: Pseudo dice [0.8209] +2024-11-22 06:04:54.815300: Epoch time: 18.49 s +2024-11-22 06:04:55.692540: +2024-11-22 06:04:55.692763: Epoch 3562 +2024-11-22 06:04:55.692879: Current learning rate: 0.00588 +2024-11-22 06:05:14.739161: train_loss -0.7859 +2024-11-22 06:05:14.739383: val_loss -0.7554 +2024-11-22 06:05:14.739460: Pseudo dice [0.8515] +2024-11-22 06:05:14.739538: Epoch time: 19.05 s +2024-11-22 06:05:15.685409: +2024-11-22 06:05:15.685646: Epoch 3563 +2024-11-22 06:05:15.685767: Current learning rate: 0.00588 +2024-11-22 06:05:34.489829: train_loss -0.7894 +2024-11-22 06:05:34.490051: val_loss -0.7596 +2024-11-22 06:05:34.490130: Pseudo dice [0.8332] +2024-11-22 06:05:34.490218: Epoch time: 18.81 s +2024-11-22 06:05:35.535295: +2024-11-22 06:05:35.535527: Epoch 3564 +2024-11-22 06:05:35.535637: Current learning rate: 0.00588 +2024-11-22 06:05:54.609699: train_loss -0.7808 +2024-11-22 06:05:54.609934: val_loss -0.7494 +2024-11-22 06:05:54.610017: Pseudo dice [0.8316] +2024-11-22 06:05:54.610099: Epoch time: 19.08 s +2024-11-22 06:05:55.513667: +2024-11-22 06:05:55.513916: Epoch 3565 +2024-11-22 06:05:55.514031: Current learning rate: 0.00588 +2024-11-22 06:06:13.975293: train_loss -0.7666 +2024-11-22 06:06:13.975527: val_loss -0.7516 +2024-11-22 06:06:13.975609: Pseudo dice [0.8432] +2024-11-22 06:06:13.975692: Epoch time: 18.46 s +2024-11-22 06:06:14.841121: +2024-11-22 06:06:14.841338: Epoch 3566 +2024-11-22 06:06:14.841456: Current learning rate: 0.00588 +2024-11-22 06:06:33.897261: train_loss -0.7922 +2024-11-22 06:06:33.900150: val_loss -0.7375 +2024-11-22 06:06:33.900358: Pseudo dice [0.8519] +2024-11-22 06:06:33.900445: Epoch time: 19.06 s +2024-11-22 06:06:35.123462: +2024-11-22 06:06:35.123672: Epoch 3567 +2024-11-22 06:06:35.123782: Current learning rate: 0.00588 +2024-11-22 06:06:54.263949: train_loss -0.7902 +2024-11-22 06:06:54.264903: val_loss -0.7495 +2024-11-22 06:06:54.265043: Pseudo dice [0.8497] +2024-11-22 06:06:54.265135: Epoch time: 19.14 s +2024-11-22 06:06:55.130605: +2024-11-22 06:06:55.130814: Epoch 3568 +2024-11-22 06:06:55.130927: Current learning rate: 0.00588 +2024-11-22 06:07:13.981817: train_loss -0.7882 +2024-11-22 06:07:13.982075: val_loss -0.744 +2024-11-22 06:07:13.982149: Pseudo dice [0.8487] +2024-11-22 06:07:13.982221: Epoch time: 18.85 s +2024-11-22 06:07:14.850336: +2024-11-22 06:07:14.850617: Epoch 3569 +2024-11-22 06:07:14.850727: Current learning rate: 0.00588 +2024-11-22 06:07:33.948066: train_loss -0.7853 +2024-11-22 06:07:33.948282: val_loss -0.7393 +2024-11-22 06:07:33.948357: Pseudo dice [0.862] +2024-11-22 06:07:33.948434: Epoch time: 19.1 s +2024-11-22 06:07:34.820185: +2024-11-22 06:07:34.820427: Epoch 3570 +2024-11-22 06:07:34.820543: Current learning rate: 0.00587 +2024-11-22 06:07:52.675282: train_loss -0.7908 +2024-11-22 06:07:52.690180: val_loss -0.7629 +2024-11-22 06:07:52.690351: Pseudo dice [0.8498] +2024-11-22 06:07:52.690446: Epoch time: 17.86 s +2024-11-22 06:07:53.630913: +2024-11-22 06:07:53.631134: Epoch 3571 +2024-11-22 06:07:53.631249: Current learning rate: 0.00587 +2024-11-22 06:08:13.148479: train_loss -0.7894 +2024-11-22 06:08:13.148694: val_loss -0.7373 +2024-11-22 06:08:13.148770: Pseudo dice [0.8537] +2024-11-22 06:08:13.148849: Epoch time: 19.52 s +2024-11-22 06:08:14.025695: +2024-11-22 06:08:14.025899: Epoch 3572 +2024-11-22 06:08:14.026011: Current learning rate: 0.00587 +2024-11-22 06:08:32.309484: train_loss -0.7852 +2024-11-22 06:08:32.309712: val_loss -0.7268 +2024-11-22 06:08:32.309791: Pseudo dice [0.8375] +2024-11-22 06:08:32.309870: Epoch time: 18.28 s +2024-11-22 06:08:33.178958: +2024-11-22 06:08:33.179176: Epoch 3573 +2024-11-22 06:08:33.179286: Current learning rate: 0.00587 +2024-11-22 06:08:51.160357: train_loss -0.7855 +2024-11-22 06:08:51.160590: val_loss -0.7447 +2024-11-22 06:08:51.160669: Pseudo dice [0.8381] +2024-11-22 06:08:51.160762: Epoch time: 17.98 s +2024-11-22 06:08:52.044810: +2024-11-22 06:08:52.045022: Epoch 3574 +2024-11-22 06:08:52.045137: Current learning rate: 0.00587 +2024-11-22 06:09:10.729942: train_loss -0.7855 +2024-11-22 06:09:10.730178: val_loss -0.7587 +2024-11-22 06:09:10.730252: Pseudo dice [0.8503] +2024-11-22 06:09:10.730331: Epoch time: 18.69 s +2024-11-22 06:09:11.890411: +2024-11-22 06:09:11.890822: Epoch 3575 +2024-11-22 06:09:11.890944: Current learning rate: 0.00587 +2024-11-22 06:09:30.771863: train_loss -0.7891 +2024-11-22 06:09:30.772064: val_loss -0.7743 +2024-11-22 06:09:30.772139: Pseudo dice [0.8423] +2024-11-22 06:09:30.772219: Epoch time: 18.88 s +2024-11-22 06:09:31.666399: +2024-11-22 06:09:31.666608: Epoch 3576 +2024-11-22 06:09:31.666718: Current learning rate: 0.00587 +2024-11-22 06:09:51.388548: train_loss -0.7708 +2024-11-22 06:09:51.388770: val_loss -0.7357 +2024-11-22 06:09:51.388847: Pseudo dice [0.8404] +2024-11-22 06:09:51.394080: Epoch time: 19.72 s +2024-11-22 06:09:52.511039: +2024-11-22 06:09:52.511238: Epoch 3577 +2024-11-22 06:09:52.511349: Current learning rate: 0.00587 +2024-11-22 06:10:10.850100: train_loss -0.7868 +2024-11-22 06:10:10.850315: val_loss -0.6954 +2024-11-22 06:10:10.850388: Pseudo dice [0.8095] +2024-11-22 06:10:10.850471: Epoch time: 18.34 s +2024-11-22 06:10:12.107660: +2024-11-22 06:10:12.107855: Epoch 3578 +2024-11-22 06:10:12.108003: Current learning rate: 0.00587 +2024-11-22 06:10:31.261571: train_loss -0.7813 +2024-11-22 06:10:31.261905: val_loss -0.7209 +2024-11-22 06:10:31.261989: Pseudo dice [0.8168] +2024-11-22 06:10:31.262081: Epoch time: 19.15 s +2024-11-22 06:10:32.135392: +2024-11-22 06:10:32.135619: Epoch 3579 +2024-11-22 06:10:32.135734: Current learning rate: 0.00586 +2024-11-22 06:10:50.887613: train_loss -0.7889 +2024-11-22 06:10:50.887827: val_loss -0.7571 +2024-11-22 06:10:50.887906: Pseudo dice [0.8307] +2024-11-22 06:10:50.887983: Epoch time: 18.75 s +2024-11-22 06:10:51.829801: +2024-11-22 06:10:51.830200: Epoch 3580 +2024-11-22 06:10:51.830313: Current learning rate: 0.00586 +2024-11-22 06:11:10.815687: train_loss -0.7807 +2024-11-22 06:11:10.815905: val_loss -0.7431 +2024-11-22 06:11:10.815983: Pseudo dice [0.847] +2024-11-22 06:11:10.816070: Epoch time: 18.99 s +2024-11-22 06:11:11.699409: +2024-11-22 06:11:11.699632: Epoch 3581 +2024-11-22 06:11:11.699748: Current learning rate: 0.00586 +2024-11-22 06:11:31.394423: train_loss -0.7752 +2024-11-22 06:11:31.394651: val_loss -0.7384 +2024-11-22 06:11:31.394728: Pseudo dice [0.8157] +2024-11-22 06:11:31.394812: Epoch time: 19.7 s +2024-11-22 06:11:32.277254: +2024-11-22 06:11:32.277530: Epoch 3582 +2024-11-22 06:11:32.277642: Current learning rate: 0.00586 +2024-11-22 06:11:51.902660: train_loss -0.7756 +2024-11-22 06:11:51.902903: val_loss -0.7341 +2024-11-22 06:11:51.902976: Pseudo dice [0.8424] +2024-11-22 06:11:51.903066: Epoch time: 19.63 s +2024-11-22 06:11:52.784517: +2024-11-22 06:11:52.784732: Epoch 3583 +2024-11-22 06:11:52.784845: Current learning rate: 0.00586 +2024-11-22 06:12:11.779225: train_loss -0.7833 +2024-11-22 06:12:11.779449: val_loss -0.7387 +2024-11-22 06:12:11.779525: Pseudo dice [0.8408] +2024-11-22 06:12:11.779600: Epoch time: 19.0 s +2024-11-22 06:12:12.759909: +2024-11-22 06:12:12.760233: Epoch 3584 +2024-11-22 06:12:12.760346: Current learning rate: 0.00586 +2024-11-22 06:12:30.687739: train_loss -0.7797 +2024-11-22 06:12:30.687956: val_loss -0.7458 +2024-11-22 06:12:30.688036: Pseudo dice [0.8382] +2024-11-22 06:12:30.688122: Epoch time: 17.93 s +2024-11-22 06:12:31.678467: +2024-11-22 06:12:31.678766: Epoch 3585 +2024-11-22 06:12:31.678878: Current learning rate: 0.00586 +2024-11-22 06:12:50.275793: train_loss -0.7707 +2024-11-22 06:12:50.276042: val_loss -0.7636 +2024-11-22 06:12:50.276119: Pseudo dice [0.8512] +2024-11-22 06:12:50.276203: Epoch time: 18.6 s +2024-11-22 06:12:51.159214: +2024-11-22 06:12:51.159439: Epoch 3586 +2024-11-22 06:12:51.159548: Current learning rate: 0.00586 +2024-11-22 06:13:09.879674: train_loss -0.781 +2024-11-22 06:13:09.879885: val_loss -0.7358 +2024-11-22 06:13:09.879960: Pseudo dice [0.8438] +2024-11-22 06:13:09.880042: Epoch time: 18.72 s +2024-11-22 06:13:10.757209: +2024-11-22 06:13:10.757418: Epoch 3587 +2024-11-22 06:13:10.757535: Current learning rate: 0.00585 +2024-11-22 06:13:29.507224: train_loss -0.7818 +2024-11-22 06:13:29.507451: val_loss -0.734 +2024-11-22 06:13:29.507530: Pseudo dice [0.8398] +2024-11-22 06:13:29.507610: Epoch time: 18.75 s +2024-11-22 06:13:30.377813: +2024-11-22 06:13:30.378007: Epoch 3588 +2024-11-22 06:13:30.378117: Current learning rate: 0.00585 +2024-11-22 06:13:48.301028: train_loss -0.7875 +2024-11-22 06:13:48.301249: val_loss -0.7584 +2024-11-22 06:13:48.301327: Pseudo dice [0.8404] +2024-11-22 06:13:48.301405: Epoch time: 17.92 s +2024-11-22 06:13:49.176249: +2024-11-22 06:13:49.176466: Epoch 3589 +2024-11-22 06:13:49.176584: Current learning rate: 0.00585 +2024-11-22 06:14:07.854226: train_loss -0.7861 +2024-11-22 06:14:07.854473: val_loss -0.7569 +2024-11-22 06:14:07.854547: Pseudo dice [0.8355] +2024-11-22 06:14:07.854635: Epoch time: 18.68 s +2024-11-22 06:14:09.136303: +2024-11-22 06:14:09.136515: Epoch 3590 +2024-11-22 06:14:09.136626: Current learning rate: 0.00585 +2024-11-22 06:14:27.634113: train_loss -0.7766 +2024-11-22 06:14:27.634336: val_loss -0.7283 +2024-11-22 06:14:27.634413: Pseudo dice [0.8463] +2024-11-22 06:14:27.634492: Epoch time: 18.5 s +2024-11-22 06:14:28.513134: +2024-11-22 06:14:28.513361: Epoch 3591 +2024-11-22 06:14:28.513470: Current learning rate: 0.00585 +2024-11-22 06:14:46.555323: train_loss -0.7906 +2024-11-22 06:14:46.555558: val_loss -0.7302 +2024-11-22 06:14:46.555632: Pseudo dice [0.8453] +2024-11-22 06:14:46.555709: Epoch time: 18.04 s +2024-11-22 06:14:47.538016: +2024-11-22 06:14:47.538224: Epoch 3592 +2024-11-22 06:14:47.538338: Current learning rate: 0.00585 +2024-11-22 06:15:06.846411: train_loss -0.7896 +2024-11-22 06:15:06.846694: val_loss -0.7433 +2024-11-22 06:15:06.846778: Pseudo dice [0.8332] +2024-11-22 06:15:06.846864: Epoch time: 19.3 s +2024-11-22 06:15:07.927114: +2024-11-22 06:15:07.927357: Epoch 3593 +2024-11-22 06:15:07.927477: Current learning rate: 0.00585 +2024-11-22 06:15:26.783401: train_loss -0.7913 +2024-11-22 06:15:26.783638: val_loss -0.7328 +2024-11-22 06:15:26.783721: Pseudo dice [0.8397] +2024-11-22 06:15:26.783809: Epoch time: 18.86 s +2024-11-22 06:15:27.765332: +2024-11-22 06:15:27.765604: Epoch 3594 +2024-11-22 06:15:27.765722: Current learning rate: 0.00585 +2024-11-22 06:15:45.721152: train_loss -0.7884 +2024-11-22 06:15:45.721369: val_loss -0.7501 +2024-11-22 06:15:45.721444: Pseudo dice [0.8364] +2024-11-22 06:15:45.721521: Epoch time: 17.96 s +2024-11-22 06:15:46.748888: +2024-11-22 06:15:46.749234: Epoch 3595 +2024-11-22 06:15:46.749349: Current learning rate: 0.00584 +2024-11-22 06:16:05.438152: train_loss -0.7937 +2024-11-22 06:16:05.438439: val_loss -0.7705 +2024-11-22 06:16:05.438521: Pseudo dice [0.8498] +2024-11-22 06:16:05.438599: Epoch time: 18.69 s +2024-11-22 06:16:06.325442: +2024-11-22 06:16:06.325668: Epoch 3596 +2024-11-22 06:16:06.325780: Current learning rate: 0.00584 +2024-11-22 06:16:23.868507: train_loss -0.7885 +2024-11-22 06:16:23.868738: val_loss -0.7585 +2024-11-22 06:16:23.868814: Pseudo dice [0.846] +2024-11-22 06:16:23.868895: Epoch time: 17.54 s +2024-11-22 06:16:24.748490: +2024-11-22 06:16:24.748709: Epoch 3597 +2024-11-22 06:16:24.748821: Current learning rate: 0.00584 +2024-11-22 06:16:43.437130: train_loss -0.7864 +2024-11-22 06:16:43.437357: val_loss -0.7565 +2024-11-22 06:16:43.437433: Pseudo dice [0.863] +2024-11-22 06:16:43.437511: Epoch time: 18.69 s +2024-11-22 06:16:44.331170: +2024-11-22 06:16:44.331432: Epoch 3598 +2024-11-22 06:16:44.331547: Current learning rate: 0.00584 +2024-11-22 06:17:03.270149: train_loss -0.781 +2024-11-22 06:17:03.270375: val_loss -0.7536 +2024-11-22 06:17:03.270453: Pseudo dice [0.8522] +2024-11-22 06:17:03.270532: Epoch time: 18.94 s +2024-11-22 06:17:04.147998: +2024-11-22 06:17:04.148229: Epoch 3599 +2024-11-22 06:17:04.148345: Current learning rate: 0.00584 +2024-11-22 06:17:22.132582: train_loss -0.7819 +2024-11-22 06:17:22.132818: val_loss -0.7462 +2024-11-22 06:17:22.138062: Pseudo dice [0.8365] +2024-11-22 06:17:22.138225: Epoch time: 17.99 s +2024-11-22 06:17:23.422146: +2024-11-22 06:17:23.422550: Epoch 3600 +2024-11-22 06:17:23.422680: Current learning rate: 0.00584 +2024-11-22 06:17:42.859717: train_loss -0.7884 +2024-11-22 06:17:42.865156: val_loss -0.7424 +2024-11-22 06:17:42.865273: Pseudo dice [0.8341] +2024-11-22 06:17:42.865367: Epoch time: 19.44 s +2024-11-22 06:17:44.271405: +2024-11-22 06:17:44.271720: Epoch 3601 +2024-11-22 06:17:44.271837: Current learning rate: 0.00584 +2024-11-22 06:18:02.611890: train_loss -0.7859 +2024-11-22 06:18:02.612134: val_loss -0.7395 +2024-11-22 06:18:02.612216: Pseudo dice [0.8368] +2024-11-22 06:18:02.612292: Epoch time: 18.34 s +2024-11-22 06:18:03.495026: +2024-11-22 06:18:03.495238: Epoch 3602 +2024-11-22 06:18:03.495347: Current learning rate: 0.00584 +2024-11-22 06:18:21.858317: train_loss -0.7935 +2024-11-22 06:18:21.858543: val_loss -0.7616 +2024-11-22 06:18:21.858624: Pseudo dice [0.8313] +2024-11-22 06:18:21.858700: Epoch time: 18.36 s +2024-11-22 06:18:22.739585: +2024-11-22 06:18:22.739918: Epoch 3603 +2024-11-22 06:18:22.740035: Current learning rate: 0.00584 +2024-11-22 06:18:41.138159: train_loss -0.7922 +2024-11-22 06:18:41.138381: val_loss -0.7554 +2024-11-22 06:18:41.138459: Pseudo dice [0.8548] +2024-11-22 06:18:41.138539: Epoch time: 18.4 s +2024-11-22 06:18:42.023298: +2024-11-22 06:18:42.023518: Epoch 3604 +2024-11-22 06:18:42.023629: Current learning rate: 0.00583 +2024-11-22 06:19:00.609504: train_loss -0.7932 +2024-11-22 06:19:00.609758: val_loss -0.7382 +2024-11-22 06:19:00.609835: Pseudo dice [0.8334] +2024-11-22 06:19:00.609922: Epoch time: 18.59 s +2024-11-22 06:19:01.489852: +2024-11-22 06:19:01.490081: Epoch 3605 +2024-11-22 06:19:01.490199: Current learning rate: 0.00583 +2024-11-22 06:19:20.123557: train_loss -0.7908 +2024-11-22 06:19:20.123783: val_loss -0.7609 +2024-11-22 06:19:20.123860: Pseudo dice [0.8511] +2024-11-22 06:19:20.123938: Epoch time: 18.63 s +2024-11-22 06:19:21.069837: +2024-11-22 06:19:21.070066: Epoch 3606 +2024-11-22 06:19:21.070179: Current learning rate: 0.00583 +2024-11-22 06:19:39.372363: train_loss -0.7906 +2024-11-22 06:19:39.372577: val_loss -0.7345 +2024-11-22 06:19:39.372658: Pseudo dice [0.829] +2024-11-22 06:19:39.372733: Epoch time: 18.3 s +2024-11-22 06:19:40.272764: +2024-11-22 06:19:40.272962: Epoch 3607 +2024-11-22 06:19:40.273084: Current learning rate: 0.00583 +2024-11-22 06:19:58.407138: train_loss -0.7917 +2024-11-22 06:19:58.407356: val_loss -0.7561 +2024-11-22 06:19:58.407430: Pseudo dice [0.8513] +2024-11-22 06:19:58.407507: Epoch time: 18.14 s +2024-11-22 06:19:59.284765: +2024-11-22 06:19:59.285030: Epoch 3608 +2024-11-22 06:19:59.285147: Current learning rate: 0.00583 +2024-11-22 06:20:17.475458: train_loss -0.7852 +2024-11-22 06:20:17.475709: val_loss -0.7266 +2024-11-22 06:20:17.475789: Pseudo dice [0.8438] +2024-11-22 06:20:17.475870: Epoch time: 18.19 s +2024-11-22 06:20:18.462531: +2024-11-22 06:20:18.462740: Epoch 3609 +2024-11-22 06:20:18.462853: Current learning rate: 0.00583 +2024-11-22 06:20:37.212598: train_loss -0.7884 +2024-11-22 06:20:37.212818: val_loss -0.7482 +2024-11-22 06:20:37.212953: Pseudo dice [0.841] +2024-11-22 06:20:37.213044: Epoch time: 18.75 s +2024-11-22 06:20:38.088643: +2024-11-22 06:20:38.088864: Epoch 3610 +2024-11-22 06:20:38.088973: Current learning rate: 0.00583 +2024-11-22 06:20:57.076246: train_loss -0.7884 +2024-11-22 06:20:57.076462: val_loss -0.7592 +2024-11-22 06:20:57.076555: Pseudo dice [0.8305] +2024-11-22 06:20:57.076687: Epoch time: 18.99 s +2024-11-22 06:20:57.952760: +2024-11-22 06:20:57.952977: Epoch 3611 +2024-11-22 06:20:57.953097: Current learning rate: 0.00583 +2024-11-22 06:21:17.283092: train_loss -0.7796 +2024-11-22 06:21:17.284608: val_loss -0.7422 +2024-11-22 06:21:17.284727: Pseudo dice [0.834] +2024-11-22 06:21:17.284806: Epoch time: 19.33 s +2024-11-22 06:21:18.172893: +2024-11-22 06:21:18.173178: Epoch 3612 +2024-11-22 06:21:18.173290: Current learning rate: 0.00582 +2024-11-22 06:21:36.986748: train_loss -0.7922 +2024-11-22 06:21:36.987074: val_loss -0.7224 +2024-11-22 06:21:36.987155: Pseudo dice [0.8219] +2024-11-22 06:21:36.987234: Epoch time: 18.81 s +2024-11-22 06:21:37.857909: +2024-11-22 06:21:37.858124: Epoch 3613 +2024-11-22 06:21:37.858239: Current learning rate: 0.00582 +2024-11-22 06:21:56.214577: train_loss -0.7838 +2024-11-22 06:21:56.214777: val_loss -0.6994 +2024-11-22 06:21:56.214849: Pseudo dice [0.8264] +2024-11-22 06:21:56.214924: Epoch time: 18.36 s +2024-11-22 06:21:57.116478: +2024-11-22 06:21:57.116719: Epoch 3614 +2024-11-22 06:21:57.116832: Current learning rate: 0.00582 +2024-11-22 06:22:15.200639: train_loss -0.7872 +2024-11-22 06:22:15.200868: val_loss -0.7533 +2024-11-22 06:22:15.200945: Pseudo dice [0.8496] +2024-11-22 06:22:15.201028: Epoch time: 18.08 s +2024-11-22 06:22:16.085441: +2024-11-22 06:22:16.085657: Epoch 3615 +2024-11-22 06:22:16.085769: Current learning rate: 0.00582 +2024-11-22 06:22:33.967826: train_loss -0.7911 +2024-11-22 06:22:33.968075: val_loss -0.7703 +2024-11-22 06:22:33.968153: Pseudo dice [0.8449] +2024-11-22 06:22:33.968237: Epoch time: 17.88 s +2024-11-22 06:22:34.842394: +2024-11-22 06:22:34.842595: Epoch 3616 +2024-11-22 06:22:34.842705: Current learning rate: 0.00582 +2024-11-22 06:22:53.784220: train_loss -0.788 +2024-11-22 06:22:53.784427: val_loss -0.7402 +2024-11-22 06:22:53.786757: Pseudo dice [0.8544] +2024-11-22 06:22:53.786852: Epoch time: 18.94 s +2024-11-22 06:22:54.680755: +2024-11-22 06:22:54.680976: Epoch 3617 +2024-11-22 06:22:54.681092: Current learning rate: 0.00582 +2024-11-22 06:23:13.600235: train_loss -0.7863 +2024-11-22 06:23:13.600450: val_loss -0.7444 +2024-11-22 06:23:13.600528: Pseudo dice [0.8207] +2024-11-22 06:23:13.600604: Epoch time: 18.92 s +2024-11-22 06:23:14.476375: +2024-11-22 06:23:14.476592: Epoch 3618 +2024-11-22 06:23:14.476704: Current learning rate: 0.00582 +2024-11-22 06:23:32.820734: train_loss -0.7914 +2024-11-22 06:23:32.820956: val_loss -0.7478 +2024-11-22 06:23:32.821038: Pseudo dice [0.8461] +2024-11-22 06:23:32.821115: Epoch time: 18.35 s +2024-11-22 06:23:33.697642: +2024-11-22 06:23:33.697897: Epoch 3619 +2024-11-22 06:23:33.698018: Current learning rate: 0.00582 +2024-11-22 06:23:52.378388: train_loss -0.7819 +2024-11-22 06:23:52.378611: val_loss -0.7266 +2024-11-22 06:23:52.378687: Pseudo dice [0.8489] +2024-11-22 06:23:52.378769: Epoch time: 18.68 s +2024-11-22 06:23:53.260218: +2024-11-22 06:23:53.260454: Epoch 3620 +2024-11-22 06:23:53.260572: Current learning rate: 0.00581 +2024-11-22 06:24:11.619373: train_loss -0.8001 +2024-11-22 06:24:11.619617: val_loss -0.7499 +2024-11-22 06:24:11.619693: Pseudo dice [0.8458] +2024-11-22 06:24:11.619772: Epoch time: 18.36 s +2024-11-22 06:24:12.543845: +2024-11-22 06:24:12.544055: Epoch 3621 +2024-11-22 06:24:12.544168: Current learning rate: 0.00581 +2024-11-22 06:24:31.592373: train_loss -0.7952 +2024-11-22 06:24:31.592584: val_loss -0.7489 +2024-11-22 06:24:31.592659: Pseudo dice [0.8436] +2024-11-22 06:24:31.592734: Epoch time: 19.05 s +2024-11-22 06:24:32.658872: +2024-11-22 06:24:32.659091: Epoch 3622 +2024-11-22 06:24:32.659202: Current learning rate: 0.00581 +2024-11-22 06:24:51.071180: train_loss -0.7938 +2024-11-22 06:24:51.071411: val_loss -0.7416 +2024-11-22 06:24:51.071485: Pseudo dice [0.843] +2024-11-22 06:24:51.071562: Epoch time: 18.41 s +2024-11-22 06:24:51.991498: +2024-11-22 06:24:51.991709: Epoch 3623 +2024-11-22 06:24:51.991822: Current learning rate: 0.00581 +2024-11-22 06:25:10.534329: train_loss -0.7899 +2024-11-22 06:25:10.534554: val_loss -0.7356 +2024-11-22 06:25:10.534632: Pseudo dice [0.8412] +2024-11-22 06:25:10.534718: Epoch time: 18.54 s +2024-11-22 06:25:11.878668: +2024-11-22 06:25:11.878926: Epoch 3624 +2024-11-22 06:25:11.879077: Current learning rate: 0.00581 +2024-11-22 06:25:31.051951: train_loss -0.7809 +2024-11-22 06:25:31.052187: val_loss -0.7477 +2024-11-22 06:25:31.052264: Pseudo dice [0.8342] +2024-11-22 06:25:31.052345: Epoch time: 19.17 s +2024-11-22 06:25:31.931879: +2024-11-22 06:25:31.932102: Epoch 3625 +2024-11-22 06:25:31.932216: Current learning rate: 0.00581 +2024-11-22 06:25:50.506076: train_loss -0.7911 +2024-11-22 06:25:50.506302: val_loss -0.7193 +2024-11-22 06:25:50.506381: Pseudo dice [0.8458] +2024-11-22 06:25:50.506459: Epoch time: 18.57 s +2024-11-22 06:25:51.391718: +2024-11-22 06:25:51.391966: Epoch 3626 +2024-11-22 06:25:51.392089: Current learning rate: 0.00581 +2024-11-22 06:26:10.326728: train_loss -0.7832 +2024-11-22 06:26:10.326955: val_loss -0.7449 +2024-11-22 06:26:10.327042: Pseudo dice [0.8479] +2024-11-22 06:26:10.327130: Epoch time: 18.94 s +2024-11-22 06:26:11.190278: +2024-11-22 06:26:11.190507: Epoch 3627 +2024-11-22 06:26:11.190624: Current learning rate: 0.00581 +2024-11-22 06:26:29.968692: train_loss -0.7891 +2024-11-22 06:26:29.968968: val_loss -0.7475 +2024-11-22 06:26:29.969056: Pseudo dice [0.8494] +2024-11-22 06:26:29.969141: Epoch time: 18.78 s +2024-11-22 06:26:30.857756: +2024-11-22 06:26:30.858096: Epoch 3628 +2024-11-22 06:26:30.858213: Current learning rate: 0.00581 +2024-11-22 06:26:49.676406: train_loss -0.7899 +2024-11-22 06:26:49.676636: val_loss -0.7327 +2024-11-22 06:26:49.676790: Pseudo dice [0.8331] +2024-11-22 06:26:49.676873: Epoch time: 18.82 s +2024-11-22 06:26:50.637124: +2024-11-22 06:26:50.637352: Epoch 3629 +2024-11-22 06:26:50.637468: Current learning rate: 0.0058 +2024-11-22 06:27:09.142319: train_loss -0.7914 +2024-11-22 06:27:09.142581: val_loss -0.7501 +2024-11-22 06:27:09.142679: Pseudo dice [0.8523] +2024-11-22 06:27:09.142755: Epoch time: 18.51 s +2024-11-22 06:27:10.009564: +2024-11-22 06:27:10.009794: Epoch 3630 +2024-11-22 06:27:10.009904: Current learning rate: 0.0058 +2024-11-22 06:27:28.663260: train_loss -0.7875 +2024-11-22 06:27:28.663493: val_loss -0.7237 +2024-11-22 06:27:28.663620: Pseudo dice [0.8402] +2024-11-22 06:27:28.663696: Epoch time: 18.65 s +2024-11-22 06:27:29.537327: +2024-11-22 06:27:29.537549: Epoch 3631 +2024-11-22 06:27:29.537665: Current learning rate: 0.0058 +2024-11-22 06:27:48.092805: train_loss -0.7899 +2024-11-22 06:27:48.093153: val_loss -0.7218 +2024-11-22 06:27:48.093230: Pseudo dice [0.8276] +2024-11-22 06:27:48.093313: Epoch time: 18.56 s +2024-11-22 06:27:48.976804: +2024-11-22 06:27:48.977043: Epoch 3632 +2024-11-22 06:27:48.977163: Current learning rate: 0.0058 +2024-11-22 06:28:08.008937: train_loss -0.783 +2024-11-22 06:28:08.009161: val_loss -0.7647 +2024-11-22 06:28:08.009243: Pseudo dice [0.8445] +2024-11-22 06:28:08.009324: Epoch time: 19.03 s +2024-11-22 06:28:08.871208: +2024-11-22 06:28:08.871405: Epoch 3633 +2024-11-22 06:28:08.871512: Current learning rate: 0.0058 +2024-11-22 06:28:27.851048: train_loss -0.7953 +2024-11-22 06:28:27.851260: val_loss -0.7451 +2024-11-22 06:28:27.851332: Pseudo dice [0.8385] +2024-11-22 06:28:27.851412: Epoch time: 18.98 s +2024-11-22 06:28:28.889109: +2024-11-22 06:28:28.889535: Epoch 3634 +2024-11-22 06:28:28.889669: Current learning rate: 0.0058 +2024-11-22 06:28:48.161376: train_loss -0.7858 +2024-11-22 06:28:48.161620: val_loss -0.7384 +2024-11-22 06:28:48.161710: Pseudo dice [0.839] +2024-11-22 06:28:48.161790: Epoch time: 19.27 s +2024-11-22 06:28:49.038231: +2024-11-22 06:28:49.038459: Epoch 3635 +2024-11-22 06:28:49.038589: Current learning rate: 0.0058 +2024-11-22 06:29:07.674495: train_loss -0.7839 +2024-11-22 06:29:07.674739: val_loss -0.7491 +2024-11-22 06:29:07.674819: Pseudo dice [0.8373] +2024-11-22 06:29:07.674899: Epoch time: 18.64 s +2024-11-22 06:29:08.543950: +2024-11-22 06:29:08.544178: Epoch 3636 +2024-11-22 06:29:08.544295: Current learning rate: 0.0058 +2024-11-22 06:29:26.523924: train_loss -0.7899 +2024-11-22 06:29:26.524134: val_loss -0.7622 +2024-11-22 06:29:26.524211: Pseudo dice [0.8267] +2024-11-22 06:29:26.524290: Epoch time: 17.98 s +2024-11-22 06:29:27.390180: +2024-11-22 06:29:27.392216: Epoch 3637 +2024-11-22 06:29:27.392335: Current learning rate: 0.00579 +2024-11-22 06:29:46.865550: train_loss -0.7902 +2024-11-22 06:29:46.865772: val_loss -0.7325 +2024-11-22 06:29:46.865927: Pseudo dice [0.8341] +2024-11-22 06:29:46.866017: Epoch time: 19.48 s +2024-11-22 06:29:47.739230: +2024-11-22 06:29:47.739424: Epoch 3638 +2024-11-22 06:29:47.739533: Current learning rate: 0.00579 +2024-11-22 06:30:06.577769: train_loss -0.7895 +2024-11-22 06:30:06.577998: val_loss -0.7439 +2024-11-22 06:30:06.578074: Pseudo dice [0.8497] +2024-11-22 06:30:06.578150: Epoch time: 18.84 s +2024-11-22 06:30:07.459519: +2024-11-22 06:30:07.459845: Epoch 3639 +2024-11-22 06:30:07.460011: Current learning rate: 0.00579 +2024-11-22 06:30:26.782564: train_loss -0.7883 +2024-11-22 06:30:26.782782: val_loss -0.77 +2024-11-22 06:30:26.782859: Pseudo dice [0.8478] +2024-11-22 06:30:26.782958: Epoch time: 19.32 s +2024-11-22 06:30:27.682241: +2024-11-22 06:30:27.682451: Epoch 3640 +2024-11-22 06:30:27.682564: Current learning rate: 0.00579 +2024-11-22 06:30:46.556596: train_loss -0.7926 +2024-11-22 06:30:46.556816: val_loss -0.748 +2024-11-22 06:30:46.556893: Pseudo dice [0.8394] +2024-11-22 06:30:46.557000: Epoch time: 18.88 s +2024-11-22 06:30:47.428292: +2024-11-22 06:30:47.428490: Epoch 3641 +2024-11-22 06:30:47.428597: Current learning rate: 0.00579 +2024-11-22 06:31:06.807487: train_loss -0.7864 +2024-11-22 06:31:06.807697: val_loss -0.7489 +2024-11-22 06:31:06.807772: Pseudo dice [0.8459] +2024-11-22 06:31:06.807848: Epoch time: 19.38 s +2024-11-22 06:31:07.676572: +2024-11-22 06:31:07.676802: Epoch 3642 +2024-11-22 06:31:07.676915: Current learning rate: 0.00579 +2024-11-22 06:31:25.144635: train_loss -0.7887 +2024-11-22 06:31:25.147045: val_loss -0.7428 +2024-11-22 06:31:25.147159: Pseudo dice [0.8557] +2024-11-22 06:31:25.147247: Epoch time: 17.47 s +2024-11-22 06:31:26.187237: +2024-11-22 06:31:26.187437: Epoch 3643 +2024-11-22 06:31:26.187549: Current learning rate: 0.00579 +2024-11-22 06:31:43.976237: train_loss -0.7839 +2024-11-22 06:31:43.976466: val_loss -0.7223 +2024-11-22 06:31:43.976542: Pseudo dice [0.8309] +2024-11-22 06:31:43.976618: Epoch time: 17.79 s +2024-11-22 06:31:44.904487: +2024-11-22 06:31:44.904689: Epoch 3644 +2024-11-22 06:31:44.904796: Current learning rate: 0.00579 +2024-11-22 06:32:03.776153: train_loss -0.7935 +2024-11-22 06:32:03.776369: val_loss -0.7387 +2024-11-22 06:32:03.776447: Pseudo dice [0.8315] +2024-11-22 06:32:03.776523: Epoch time: 18.87 s +2024-11-22 06:32:04.783780: +2024-11-22 06:32:04.783973: Epoch 3645 +2024-11-22 06:32:04.784281: Current learning rate: 0.00579 +2024-11-22 06:32:23.782434: train_loss -0.7828 +2024-11-22 06:32:23.782650: val_loss -0.7312 +2024-11-22 06:32:23.782728: Pseudo dice [0.8171] +2024-11-22 06:32:23.782804: Epoch time: 19.0 s +2024-11-22 06:32:24.659405: +2024-11-22 06:32:24.659815: Epoch 3646 +2024-11-22 06:32:24.659945: Current learning rate: 0.00578 +2024-11-22 06:32:44.075224: train_loss -0.7926 +2024-11-22 06:32:44.075464: val_loss -0.7386 +2024-11-22 06:32:44.075540: Pseudo dice [0.8277] +2024-11-22 06:32:44.075624: Epoch time: 19.42 s +2024-11-22 06:32:45.289023: +2024-11-22 06:32:45.289264: Epoch 3647 +2024-11-22 06:32:45.289375: Current learning rate: 0.00578 +2024-11-22 06:33:03.968493: train_loss -0.7799 +2024-11-22 06:33:03.968698: val_loss -0.7372 +2024-11-22 06:33:03.968770: Pseudo dice [0.8457] +2024-11-22 06:33:03.968844: Epoch time: 18.68 s +2024-11-22 06:33:04.833621: +2024-11-22 06:33:04.833844: Epoch 3648 +2024-11-22 06:33:04.833953: Current learning rate: 0.00578 +2024-11-22 06:33:23.431602: train_loss -0.7819 +2024-11-22 06:33:23.431819: val_loss -0.7485 +2024-11-22 06:33:23.431894: Pseudo dice [0.82] +2024-11-22 06:33:23.432007: Epoch time: 18.6 s +2024-11-22 06:33:24.298854: +2024-11-22 06:33:24.299063: Epoch 3649 +2024-11-22 06:33:24.299173: Current learning rate: 0.00578 +2024-11-22 06:33:43.812431: train_loss -0.7777 +2024-11-22 06:33:43.812706: val_loss -0.7405 +2024-11-22 06:33:43.812787: Pseudo dice [0.8317] +2024-11-22 06:33:43.812863: Epoch time: 19.51 s +2024-11-22 06:33:44.957916: +2024-11-22 06:33:44.958150: Epoch 3650 +2024-11-22 06:33:44.958262: Current learning rate: 0.00578 +2024-11-22 06:34:02.959449: train_loss -0.7862 +2024-11-22 06:34:02.959690: val_loss -0.7447 +2024-11-22 06:34:02.959765: Pseudo dice [0.8442] +2024-11-22 06:34:02.959846: Epoch time: 18.0 s +2024-11-22 06:34:03.832541: +2024-11-22 06:34:03.832815: Epoch 3651 +2024-11-22 06:34:03.832931: Current learning rate: 0.00578 +2024-11-22 06:34:22.839902: train_loss -0.791 +2024-11-22 06:34:22.840128: val_loss -0.7233 +2024-11-22 06:34:22.840202: Pseudo dice [0.8473] +2024-11-22 06:34:22.840280: Epoch time: 19.01 s +2024-11-22 06:34:23.717600: +2024-11-22 06:34:23.717810: Epoch 3652 +2024-11-22 06:34:23.717922: Current learning rate: 0.00578 +2024-11-22 06:34:41.855448: train_loss -0.7892 +2024-11-22 06:34:41.855676: val_loss -0.7203 +2024-11-22 06:34:41.855751: Pseudo dice [0.8381] +2024-11-22 06:34:41.855832: Epoch time: 18.14 s +2024-11-22 06:34:42.734648: +2024-11-22 06:34:42.734850: Epoch 3653 +2024-11-22 06:34:42.735020: Current learning rate: 0.00578 +2024-11-22 06:35:00.941749: train_loss -0.7976 +2024-11-22 06:35:00.941972: val_loss -0.7596 +2024-11-22 06:35:00.942055: Pseudo dice [0.8525] +2024-11-22 06:35:00.942135: Epoch time: 18.21 s +2024-11-22 06:35:01.809619: +2024-11-22 06:35:01.809843: Epoch 3654 +2024-11-22 06:35:01.809963: Current learning rate: 0.00577 +2024-11-22 06:35:19.452505: train_loss -0.7894 +2024-11-22 06:35:19.452756: val_loss -0.7686 +2024-11-22 06:35:19.452835: Pseudo dice [0.8428] +2024-11-22 06:35:19.452917: Epoch time: 17.64 s +2024-11-22 06:35:20.393886: +2024-11-22 06:35:20.394106: Epoch 3655 +2024-11-22 06:35:20.394220: Current learning rate: 0.00577 +2024-11-22 06:35:39.342308: train_loss -0.7902 +2024-11-22 06:35:39.342529: val_loss -0.7451 +2024-11-22 06:35:39.342636: Pseudo dice [0.8207] +2024-11-22 06:35:39.342717: Epoch time: 18.95 s +2024-11-22 06:35:40.236803: +2024-11-22 06:35:40.237029: Epoch 3656 +2024-11-22 06:35:40.237142: Current learning rate: 0.00577 +2024-11-22 06:36:00.387407: train_loss -0.7863 +2024-11-22 06:36:00.387621: val_loss -0.739 +2024-11-22 06:36:00.387695: Pseudo dice [0.8319] +2024-11-22 06:36:00.387773: Epoch time: 20.15 s +2024-11-22 06:36:01.260722: +2024-11-22 06:36:01.260916: Epoch 3657 +2024-11-22 06:36:01.261029: Current learning rate: 0.00577 +2024-11-22 06:36:20.404526: train_loss -0.7933 +2024-11-22 06:36:20.404747: val_loss -0.7828 +2024-11-22 06:36:20.404827: Pseudo dice [0.8603] +2024-11-22 06:36:20.404916: Epoch time: 19.14 s +2024-11-22 06:36:21.277451: +2024-11-22 06:36:21.277659: Epoch 3658 +2024-11-22 06:36:21.277772: Current learning rate: 0.00577 +2024-11-22 06:36:39.754678: train_loss -0.7951 +2024-11-22 06:36:39.754926: val_loss -0.7553 +2024-11-22 06:36:39.755011: Pseudo dice [0.8442] +2024-11-22 06:36:39.755091: Epoch time: 18.48 s +2024-11-22 06:36:40.631223: +2024-11-22 06:36:40.631426: Epoch 3659 +2024-11-22 06:36:40.631532: Current learning rate: 0.00577 +2024-11-22 06:36:59.631045: train_loss -0.791 +2024-11-22 06:36:59.631278: val_loss -0.7541 +2024-11-22 06:36:59.631354: Pseudo dice [0.8268] +2024-11-22 06:36:59.631432: Epoch time: 19.0 s +2024-11-22 06:37:00.526644: +2024-11-22 06:37:00.526864: Epoch 3660 +2024-11-22 06:37:00.526978: Current learning rate: 0.00577 +2024-11-22 06:37:20.154832: train_loss -0.7936 +2024-11-22 06:37:20.155065: val_loss -0.7374 +2024-11-22 06:37:20.155138: Pseudo dice [0.8385] +2024-11-22 06:37:20.155214: Epoch time: 19.63 s +2024-11-22 06:37:21.202202: +2024-11-22 06:37:21.202416: Epoch 3661 +2024-11-22 06:37:21.202528: Current learning rate: 0.00577 +2024-11-22 06:37:39.694579: train_loss -0.7973 +2024-11-22 06:37:39.694845: val_loss -0.7293 +2024-11-22 06:37:39.694929: Pseudo dice [0.8505] +2024-11-22 06:37:39.695026: Epoch time: 18.49 s +2024-11-22 06:37:40.825685: +2024-11-22 06:37:40.825893: Epoch 3662 +2024-11-22 06:37:40.826015: Current learning rate: 0.00576 +2024-11-22 06:37:59.711998: train_loss -0.7883 +2024-11-22 06:37:59.712211: val_loss -0.7347 +2024-11-22 06:37:59.712288: Pseudo dice [0.8392] +2024-11-22 06:37:59.712363: Epoch time: 18.89 s +2024-11-22 06:38:00.741241: +2024-11-22 06:38:00.741462: Epoch 3663 +2024-11-22 06:38:00.741576: Current learning rate: 0.00576 +2024-11-22 06:38:19.986729: train_loss -0.7894 +2024-11-22 06:38:19.986948: val_loss -0.7359 +2024-11-22 06:38:19.987030: Pseudo dice [0.814] +2024-11-22 06:38:19.987108: Epoch time: 19.25 s +2024-11-22 06:38:20.968673: +2024-11-22 06:38:20.968904: Epoch 3664 +2024-11-22 06:38:20.969022: Current learning rate: 0.00576 +2024-11-22 06:38:40.798955: train_loss -0.7748 +2024-11-22 06:38:40.799860: val_loss -0.7457 +2024-11-22 06:38:40.799941: Pseudo dice [0.8273] +2024-11-22 06:38:40.800024: Epoch time: 19.83 s +2024-11-22 06:38:41.667288: +2024-11-22 06:38:41.667517: Epoch 3665 +2024-11-22 06:38:41.667629: Current learning rate: 0.00576 +2024-11-22 06:39:00.612423: train_loss -0.7816 +2024-11-22 06:39:00.612683: val_loss -0.7463 +2024-11-22 06:39:00.612764: Pseudo dice [0.8312] +2024-11-22 06:39:00.612886: Epoch time: 18.95 s +2024-11-22 06:39:01.496441: +2024-11-22 06:39:01.496755: Epoch 3666 +2024-11-22 06:39:01.496869: Current learning rate: 0.00576 +2024-11-22 06:39:20.146832: train_loss -0.793 +2024-11-22 06:39:20.147063: val_loss -0.7486 +2024-11-22 06:39:20.147193: Pseudo dice [0.8463] +2024-11-22 06:39:20.147277: Epoch time: 18.65 s +2024-11-22 06:39:21.026958: +2024-11-22 06:39:21.027149: Epoch 3667 +2024-11-22 06:39:21.027259: Current learning rate: 0.00576 +2024-11-22 06:39:40.128026: train_loss -0.7943 +2024-11-22 06:39:40.128247: val_loss -0.7397 +2024-11-22 06:39:40.128326: Pseudo dice [0.8391] +2024-11-22 06:39:40.128402: Epoch time: 19.1 s +2024-11-22 06:39:41.027312: +2024-11-22 06:39:41.027534: Epoch 3668 +2024-11-22 06:39:41.027649: Current learning rate: 0.00576 +2024-11-22 06:40:00.467489: train_loss -0.7777 +2024-11-22 06:40:00.467710: val_loss -0.7352 +2024-11-22 06:40:00.467787: Pseudo dice [0.8424] +2024-11-22 06:40:00.467867: Epoch time: 19.44 s +2024-11-22 06:40:01.345436: +2024-11-22 06:40:01.345639: Epoch 3669 +2024-11-22 06:40:01.345751: Current learning rate: 0.00576 +2024-11-22 06:40:20.353057: train_loss -0.7891 +2024-11-22 06:40:20.353302: val_loss -0.7431 +2024-11-22 06:40:20.353381: Pseudo dice [0.8341] +2024-11-22 06:40:20.353461: Epoch time: 19.01 s +2024-11-22 06:40:21.630177: +2024-11-22 06:40:21.630457: Epoch 3670 +2024-11-22 06:40:21.630567: Current learning rate: 0.00576 +2024-11-22 06:40:40.731132: train_loss -0.7936 +2024-11-22 06:40:40.731387: val_loss -0.7494 +2024-11-22 06:40:40.731466: Pseudo dice [0.8174] +2024-11-22 06:40:40.731547: Epoch time: 19.1 s +2024-11-22 06:40:41.604823: +2024-11-22 06:40:41.605152: Epoch 3671 +2024-11-22 06:40:41.605341: Current learning rate: 0.00575 +2024-11-22 06:41:00.213823: train_loss -0.7941 +2024-11-22 06:41:00.214110: val_loss -0.754 +2024-11-22 06:41:00.214193: Pseudo dice [0.8426] +2024-11-22 06:41:00.214274: Epoch time: 18.61 s +2024-11-22 06:41:01.088037: +2024-11-22 06:41:01.088338: Epoch 3672 +2024-11-22 06:41:01.088452: Current learning rate: 0.00575 +2024-11-22 06:41:19.903024: train_loss -0.7867 +2024-11-22 06:41:19.903247: val_loss -0.7129 +2024-11-22 06:41:19.903324: Pseudo dice [0.8321] +2024-11-22 06:41:19.903402: Epoch time: 18.82 s +2024-11-22 06:41:20.780138: +2024-11-22 06:41:20.780409: Epoch 3673 +2024-11-22 06:41:20.780526: Current learning rate: 0.00575 +2024-11-22 06:41:39.146971: train_loss -0.791 +2024-11-22 06:41:39.149415: val_loss -0.7427 +2024-11-22 06:41:39.149511: Pseudo dice [0.8465] +2024-11-22 06:41:39.149600: Epoch time: 18.37 s +2024-11-22 06:41:40.075027: +2024-11-22 06:41:40.075247: Epoch 3674 +2024-11-22 06:41:40.075362: Current learning rate: 0.00575 +2024-11-22 06:41:58.451244: train_loss -0.7822 +2024-11-22 06:41:58.451457: val_loss -0.7375 +2024-11-22 06:41:58.451531: Pseudo dice [0.8554] +2024-11-22 06:41:58.451607: Epoch time: 18.38 s +2024-11-22 06:41:59.328440: +2024-11-22 06:41:59.328637: Epoch 3675 +2024-11-22 06:41:59.328751: Current learning rate: 0.00575 +2024-11-22 06:42:17.520571: train_loss -0.7734 +2024-11-22 06:42:17.520798: val_loss -0.7537 +2024-11-22 06:42:17.520881: Pseudo dice [0.836] +2024-11-22 06:42:17.520958: Epoch time: 18.19 s +2024-11-22 06:42:18.397133: +2024-11-22 06:42:18.397335: Epoch 3676 +2024-11-22 06:42:18.397451: Current learning rate: 0.00575 +2024-11-22 06:42:38.044776: train_loss -0.7876 +2024-11-22 06:42:38.045002: val_loss -0.7465 +2024-11-22 06:42:38.045095: Pseudo dice [0.8242] +2024-11-22 06:42:38.045212: Epoch time: 19.65 s +2024-11-22 06:42:38.922735: +2024-11-22 06:42:38.923038: Epoch 3677 +2024-11-22 06:42:38.923150: Current learning rate: 0.00575 +2024-11-22 06:42:57.621880: train_loss -0.774 +2024-11-22 06:42:57.622129: val_loss -0.7363 +2024-11-22 06:42:57.622203: Pseudo dice [0.8261] +2024-11-22 06:42:57.622320: Epoch time: 18.7 s +2024-11-22 06:42:58.509679: +2024-11-22 06:42:58.509903: Epoch 3678 +2024-11-22 06:42:58.510029: Current learning rate: 0.00575 +2024-11-22 06:43:17.302545: train_loss -0.7778 +2024-11-22 06:43:17.302870: val_loss -0.7665 +2024-11-22 06:43:17.302952: Pseudo dice [0.8552] +2024-11-22 06:43:17.303039: Epoch time: 18.79 s +2024-11-22 06:43:18.185445: +2024-11-22 06:43:18.185682: Epoch 3679 +2024-11-22 06:43:18.185797: Current learning rate: 0.00574 +2024-11-22 06:43:36.439537: train_loss -0.7788 +2024-11-22 06:43:36.439759: val_loss -0.7525 +2024-11-22 06:43:36.439833: Pseudo dice [0.8435] +2024-11-22 06:43:36.439908: Epoch time: 18.25 s +2024-11-22 06:43:37.322027: +2024-11-22 06:43:37.322233: Epoch 3680 +2024-11-22 06:43:37.322346: Current learning rate: 0.00574 +2024-11-22 06:43:56.031817: train_loss -0.7909 +2024-11-22 06:43:56.037253: val_loss -0.7559 +2024-11-22 06:43:56.037369: Pseudo dice [0.8376] +2024-11-22 06:43:56.037451: Epoch time: 18.71 s +2024-11-22 06:43:57.334524: +2024-11-22 06:43:57.334728: Epoch 3681 +2024-11-22 06:43:57.334838: Current learning rate: 0.00574 +2024-11-22 06:44:17.035189: train_loss -0.7888 +2024-11-22 06:44:17.035475: val_loss -0.7599 +2024-11-22 06:44:17.035552: Pseudo dice [0.8676] +2024-11-22 06:44:17.035641: Epoch time: 19.7 s +2024-11-22 06:44:17.912176: +2024-11-22 06:44:17.912390: Epoch 3682 +2024-11-22 06:44:17.912502: Current learning rate: 0.00574 +2024-11-22 06:44:36.594732: train_loss -0.7997 +2024-11-22 06:44:36.594947: val_loss -0.7543 +2024-11-22 06:44:36.595029: Pseudo dice [0.8475] +2024-11-22 06:44:36.595105: Epoch time: 18.68 s +2024-11-22 06:44:37.473016: +2024-11-22 06:44:37.473234: Epoch 3683 +2024-11-22 06:44:37.473346: Current learning rate: 0.00574 +2024-11-22 06:44:56.722933: train_loss -0.7881 +2024-11-22 06:44:56.723223: val_loss -0.731 +2024-11-22 06:44:56.723301: Pseudo dice [0.8396] +2024-11-22 06:44:56.723377: Epoch time: 19.25 s +2024-11-22 06:44:57.603055: +2024-11-22 06:44:57.603329: Epoch 3684 +2024-11-22 06:44:57.603447: Current learning rate: 0.00574 +2024-11-22 06:45:16.087271: train_loss -0.7921 +2024-11-22 06:45:16.087516: val_loss -0.7626 +2024-11-22 06:45:16.087597: Pseudo dice [0.8489] +2024-11-22 06:45:16.087676: Epoch time: 18.49 s +2024-11-22 06:45:16.971145: +2024-11-22 06:45:16.971354: Epoch 3685 +2024-11-22 06:45:16.971467: Current learning rate: 0.00574 +2024-11-22 06:45:35.909828: train_loss -0.7687 +2024-11-22 06:45:35.910074: val_loss -0.7425 +2024-11-22 06:45:35.910149: Pseudo dice [0.8473] +2024-11-22 06:45:35.910235: Epoch time: 18.94 s +2024-11-22 06:45:36.797135: +2024-11-22 06:45:36.797347: Epoch 3686 +2024-11-22 06:45:36.797459: Current learning rate: 0.00574 +2024-11-22 06:45:55.506873: train_loss -0.7838 +2024-11-22 06:45:55.507095: val_loss -0.7723 +2024-11-22 06:45:55.507174: Pseudo dice [0.8599] +2024-11-22 06:45:55.507254: Epoch time: 18.71 s +2024-11-22 06:45:56.385672: +2024-11-22 06:45:56.385889: Epoch 3687 +2024-11-22 06:45:56.386007: Current learning rate: 0.00573 +2024-11-22 06:46:14.770119: train_loss -0.7797 +2024-11-22 06:46:14.770363: val_loss -0.7604 +2024-11-22 06:46:14.770447: Pseudo dice [0.8409] +2024-11-22 06:46:14.770524: Epoch time: 18.39 s +2024-11-22 06:46:15.650272: +2024-11-22 06:46:15.650468: Epoch 3688 +2024-11-22 06:46:15.650580: Current learning rate: 0.00573 +2024-11-22 06:46:34.867548: train_loss -0.777 +2024-11-22 06:46:34.869936: val_loss -0.7297 +2024-11-22 06:46:34.870063: Pseudo dice [0.8255] +2024-11-22 06:46:34.870146: Epoch time: 19.22 s +2024-11-22 06:46:35.811903: +2024-11-22 06:46:35.812131: Epoch 3689 +2024-11-22 06:46:35.812243: Current learning rate: 0.00573 +2024-11-22 06:46:53.604348: train_loss -0.7721 +2024-11-22 06:46:53.604594: val_loss -0.7639 +2024-11-22 06:46:53.604674: Pseudo dice [0.8501] +2024-11-22 06:46:53.604755: Epoch time: 17.79 s +2024-11-22 06:46:54.485234: +2024-11-22 06:46:54.485440: Epoch 3690 +2024-11-22 06:46:54.485548: Current learning rate: 0.00573 +2024-11-22 06:47:12.672199: train_loss -0.7723 +2024-11-22 06:47:12.672418: val_loss -0.7215 +2024-11-22 06:47:12.672523: Pseudo dice [0.834] +2024-11-22 06:47:12.672665: Epoch time: 18.19 s +2024-11-22 06:47:13.584770: +2024-11-22 06:47:13.585059: Epoch 3691 +2024-11-22 06:47:13.585171: Current learning rate: 0.00573 +2024-11-22 06:47:31.210999: train_loss -0.765 +2024-11-22 06:47:31.211224: val_loss -0.7313 +2024-11-22 06:47:31.211298: Pseudo dice [0.8342] +2024-11-22 06:47:31.211372: Epoch time: 17.63 s +2024-11-22 06:47:32.088536: +2024-11-22 06:47:32.088792: Epoch 3692 +2024-11-22 06:47:32.088904: Current learning rate: 0.00573 +2024-11-22 06:47:51.097881: train_loss -0.7802 +2024-11-22 06:47:51.098110: val_loss -0.7532 +2024-11-22 06:47:51.098187: Pseudo dice [0.832] +2024-11-22 06:47:51.098269: Epoch time: 19.01 s +2024-11-22 06:47:52.409783: +2024-11-22 06:47:52.410039: Epoch 3693 +2024-11-22 06:47:52.410151: Current learning rate: 0.00573 +2024-11-22 06:48:10.663507: train_loss -0.7919 +2024-11-22 06:48:10.663768: val_loss -0.7447 +2024-11-22 06:48:10.663847: Pseudo dice [0.8441] +2024-11-22 06:48:10.663971: Epoch time: 18.25 s +2024-11-22 06:48:11.541984: +2024-11-22 06:48:11.542195: Epoch 3694 +2024-11-22 06:48:11.542305: Current learning rate: 0.00573 +2024-11-22 06:48:30.128445: train_loss -0.7964 +2024-11-22 06:48:30.128674: val_loss -0.7556 +2024-11-22 06:48:30.128753: Pseudo dice [0.8608] +2024-11-22 06:48:30.128834: Epoch time: 18.59 s +2024-11-22 06:48:31.012192: +2024-11-22 06:48:31.012449: Epoch 3695 +2024-11-22 06:48:31.012564: Current learning rate: 0.00573 +2024-11-22 06:48:48.870958: train_loss -0.7995 +2024-11-22 06:48:48.871198: val_loss -0.775 +2024-11-22 06:48:48.871278: Pseudo dice [0.8438] +2024-11-22 06:48:48.871358: Epoch time: 17.86 s +2024-11-22 06:48:49.783113: +2024-11-22 06:48:49.783320: Epoch 3696 +2024-11-22 06:48:49.783432: Current learning rate: 0.00572 +2024-11-22 06:49:08.499561: train_loss -0.794 +2024-11-22 06:49:08.505014: val_loss -0.717 +2024-11-22 06:49:08.505131: Pseudo dice [0.8179] +2024-11-22 06:49:08.505220: Epoch time: 18.72 s +2024-11-22 06:49:09.561186: +2024-11-22 06:49:09.561673: Epoch 3697 +2024-11-22 06:49:09.561793: Current learning rate: 0.00572 +2024-11-22 06:49:27.149839: train_loss -0.7888 +2024-11-22 06:49:27.150093: val_loss -0.7474 +2024-11-22 06:49:27.150170: Pseudo dice [0.8588] +2024-11-22 06:49:27.150246: Epoch time: 17.59 s +2024-11-22 06:49:28.030684: +2024-11-22 06:49:28.030968: Epoch 3698 +2024-11-22 06:49:28.031091: Current learning rate: 0.00572 +2024-11-22 06:49:46.790030: train_loss -0.7831 +2024-11-22 06:49:46.790241: val_loss -0.7599 +2024-11-22 06:49:46.790314: Pseudo dice [0.8266] +2024-11-22 06:49:46.790389: Epoch time: 18.76 s +2024-11-22 06:49:47.666670: +2024-11-22 06:49:47.666950: Epoch 3699 +2024-11-22 06:49:47.667070: Current learning rate: 0.00572 +2024-11-22 06:50:07.550319: train_loss -0.7895 +2024-11-22 06:50:07.550541: val_loss -0.7329 +2024-11-22 06:50:07.550616: Pseudo dice [0.8433] +2024-11-22 06:50:07.550693: Epoch time: 19.88 s +2024-11-22 06:50:08.679161: +2024-11-22 06:50:08.679363: Epoch 3700 +2024-11-22 06:50:08.679476: Current learning rate: 0.00572 +2024-11-22 06:50:27.965071: train_loss -0.7882 +2024-11-22 06:50:27.965330: val_loss -0.7322 +2024-11-22 06:50:27.965404: Pseudo dice [0.8317] +2024-11-22 06:50:27.965490: Epoch time: 19.29 s +2024-11-22 06:50:28.848976: +2024-11-22 06:50:28.849406: Epoch 3701 +2024-11-22 06:50:28.849530: Current learning rate: 0.00572 +2024-11-22 06:50:47.401415: train_loss -0.7875 +2024-11-22 06:50:47.401637: val_loss -0.7435 +2024-11-22 06:50:47.401717: Pseudo dice [0.8446] +2024-11-22 06:50:47.401793: Epoch time: 18.55 s +2024-11-22 06:50:48.544066: +2024-11-22 06:50:48.544284: Epoch 3702 +2024-11-22 06:50:48.544401: Current learning rate: 0.00572 +2024-11-22 06:51:07.487572: train_loss -0.7809 +2024-11-22 06:51:07.487810: val_loss -0.7118 +2024-11-22 06:51:07.487885: Pseudo dice [0.8372] +2024-11-22 06:51:07.487960: Epoch time: 18.94 s +2024-11-22 06:51:08.417327: +2024-11-22 06:51:08.417521: Epoch 3703 +2024-11-22 06:51:08.417631: Current learning rate: 0.00572 +2024-11-22 06:51:26.226916: train_loss -0.7694 +2024-11-22 06:51:26.227146: val_loss -0.7139 +2024-11-22 06:51:26.227221: Pseudo dice [0.8479] +2024-11-22 06:51:26.227300: Epoch time: 17.81 s +2024-11-22 06:51:27.101323: +2024-11-22 06:51:27.101544: Epoch 3704 +2024-11-22 06:51:27.101657: Current learning rate: 0.00571 +2024-11-22 06:51:46.774018: train_loss -0.7843 +2024-11-22 06:51:46.774278: val_loss -0.7077 +2024-11-22 06:51:46.774356: Pseudo dice [0.8397] +2024-11-22 06:51:46.774438: Epoch time: 19.67 s +2024-11-22 06:51:47.648375: +2024-11-22 06:51:47.648581: Epoch 3705 +2024-11-22 06:51:47.648694: Current learning rate: 0.00571 +2024-11-22 06:52:05.822961: train_loss -0.797 +2024-11-22 06:52:05.823179: val_loss -0.7601 +2024-11-22 06:52:05.823254: Pseudo dice [0.8589] +2024-11-22 06:52:05.823329: Epoch time: 18.18 s +2024-11-22 06:52:06.693702: +2024-11-22 06:52:06.693964: Epoch 3706 +2024-11-22 06:52:06.694083: Current learning rate: 0.00571 +2024-11-22 06:52:24.995129: train_loss -0.7876 +2024-11-22 06:52:24.995357: val_loss -0.7469 +2024-11-22 06:52:24.995431: Pseudo dice [0.8539] +2024-11-22 06:52:24.995509: Epoch time: 18.3 s +2024-11-22 06:52:25.995792: +2024-11-22 06:52:25.996033: Epoch 3707 +2024-11-22 06:52:25.996152: Current learning rate: 0.00571 +2024-11-22 06:52:44.893553: train_loss -0.782 +2024-11-22 06:52:44.893804: val_loss -0.7384 +2024-11-22 06:52:44.893879: Pseudo dice [0.8337] +2024-11-22 06:52:44.893964: Epoch time: 18.9 s +2024-11-22 06:52:45.777747: +2024-11-22 06:52:45.777959: Epoch 3708 +2024-11-22 06:52:45.778076: Current learning rate: 0.00571 +2024-11-22 06:53:04.954621: train_loss -0.7888 +2024-11-22 06:53:04.954851: val_loss -0.7396 +2024-11-22 06:53:04.954930: Pseudo dice [0.8505] +2024-11-22 06:53:04.955021: Epoch time: 19.18 s +2024-11-22 06:53:05.839497: +2024-11-22 06:53:05.839760: Epoch 3709 +2024-11-22 06:53:05.839875: Current learning rate: 0.00571 +2024-11-22 06:53:23.780704: train_loss -0.7896 +2024-11-22 06:53:23.780933: val_loss -0.7419 +2024-11-22 06:53:23.781016: Pseudo dice [0.8547] +2024-11-22 06:53:23.781108: Epoch time: 17.94 s +2024-11-22 06:53:24.663944: +2024-11-22 06:53:24.664176: Epoch 3710 +2024-11-22 06:53:24.664289: Current learning rate: 0.00571 +2024-11-22 06:53:43.155255: train_loss -0.7833 +2024-11-22 06:53:43.155482: val_loss -0.7531 +2024-11-22 06:53:43.155558: Pseudo dice [0.8589] +2024-11-22 06:53:43.155633: Epoch time: 18.49 s +2024-11-22 06:53:43.155694: Yayy! New best EMA pseudo Dice: 0.8461 +2024-11-22 06:53:44.291476: +2024-11-22 06:53:44.291705: Epoch 3711 +2024-11-22 06:53:44.291815: Current learning rate: 0.00571 +2024-11-22 06:54:02.573480: train_loss -0.7929 +2024-11-22 06:54:02.573746: val_loss -0.7371 +2024-11-22 06:54:02.573823: Pseudo dice [0.825] +2024-11-22 06:54:02.573910: Epoch time: 18.28 s +2024-11-22 06:54:03.461547: +2024-11-22 06:54:03.461753: Epoch 3712 +2024-11-22 06:54:03.461864: Current learning rate: 0.0057 +2024-11-22 06:54:23.289705: train_loss -0.7936 +2024-11-22 06:54:23.289928: val_loss -0.7686 +2024-11-22 06:54:23.290039: Pseudo dice [0.8568] +2024-11-22 06:54:23.290125: Epoch time: 19.83 s +2024-11-22 06:54:24.164403: +2024-11-22 06:54:24.164614: Epoch 3713 +2024-11-22 06:54:24.164728: Current learning rate: 0.0057 +2024-11-22 06:54:44.030467: train_loss -0.79 +2024-11-22 06:54:44.030688: val_loss -0.7534 +2024-11-22 06:54:44.030766: Pseudo dice [0.8207] +2024-11-22 06:54:44.030839: Epoch time: 19.87 s +2024-11-22 06:54:44.940438: +2024-11-22 06:54:44.940639: Epoch 3714 +2024-11-22 06:54:44.940751: Current learning rate: 0.0057 +2024-11-22 06:55:03.293486: train_loss -0.7915 +2024-11-22 06:55:03.293712: val_loss -0.741 +2024-11-22 06:55:03.296003: Pseudo dice [0.8307] +2024-11-22 06:55:03.296094: Epoch time: 18.35 s +2024-11-22 06:55:04.792955: +2024-11-22 06:55:04.793208: Epoch 3715 +2024-11-22 06:55:04.793333: Current learning rate: 0.0057 +2024-11-22 06:55:22.682201: train_loss -0.7909 +2024-11-22 06:55:22.682507: val_loss -0.7456 +2024-11-22 06:55:22.682588: Pseudo dice [0.8289] +2024-11-22 06:55:22.682670: Epoch time: 17.89 s +2024-11-22 06:55:23.734011: +2024-11-22 06:55:23.734255: Epoch 3716 +2024-11-22 06:55:23.734369: Current learning rate: 0.0057 +2024-11-22 06:55:42.926874: train_loss -0.7926 +2024-11-22 06:55:42.927099: val_loss -0.7264 +2024-11-22 06:55:42.927180: Pseudo dice [0.8212] +2024-11-22 06:55:42.927262: Epoch time: 19.19 s +2024-11-22 06:55:43.805453: +2024-11-22 06:55:43.805686: Epoch 3717 +2024-11-22 06:55:43.805801: Current learning rate: 0.0057 +2024-11-22 06:56:03.270605: train_loss -0.7957 +2024-11-22 06:56:03.270822: val_loss -0.7383 +2024-11-22 06:56:03.270895: Pseudo dice [0.8187] +2024-11-22 06:56:03.270966: Epoch time: 19.47 s +2024-11-22 06:56:04.131313: +2024-11-22 06:56:04.131517: Epoch 3718 +2024-11-22 06:56:04.131629: Current learning rate: 0.0057 +2024-11-22 06:56:22.937838: train_loss -0.7984 +2024-11-22 06:56:22.938067: val_loss -0.7576 +2024-11-22 06:56:22.938147: Pseudo dice [0.8456] +2024-11-22 06:56:22.938228: Epoch time: 18.81 s +2024-11-22 06:56:23.983431: +2024-11-22 06:56:23.983642: Epoch 3719 +2024-11-22 06:56:23.983755: Current learning rate: 0.0057 +2024-11-22 06:56:42.273899: train_loss -0.786 +2024-11-22 06:56:42.274220: val_loss -0.7743 +2024-11-22 06:56:42.274303: Pseudo dice [0.8373] +2024-11-22 06:56:42.274384: Epoch time: 18.29 s +2024-11-22 06:56:43.160917: +2024-11-22 06:56:43.161134: Epoch 3720 +2024-11-22 06:56:43.161243: Current learning rate: 0.0057 +2024-11-22 06:57:01.416661: train_loss -0.7938 +2024-11-22 06:57:01.416884: val_loss -0.7548 +2024-11-22 06:57:01.416959: Pseudo dice [0.8414] +2024-11-22 06:57:01.417041: Epoch time: 18.26 s +2024-11-22 06:57:02.331098: +2024-11-22 06:57:02.331421: Epoch 3721 +2024-11-22 06:57:02.331536: Current learning rate: 0.00569 +2024-11-22 06:57:21.599912: train_loss -0.7942 +2024-11-22 06:57:21.600150: val_loss -0.7344 +2024-11-22 06:57:21.600226: Pseudo dice [0.826] +2024-11-22 06:57:21.600307: Epoch time: 19.27 s +2024-11-22 06:57:22.479108: +2024-11-22 06:57:22.479305: Epoch 3722 +2024-11-22 06:57:22.479417: Current learning rate: 0.00569 +2024-11-22 06:57:42.022964: train_loss -0.7797 +2024-11-22 06:57:42.023201: val_loss -0.7406 +2024-11-22 06:57:42.023278: Pseudo dice [0.8355] +2024-11-22 06:57:42.025820: Epoch time: 19.54 s +2024-11-22 06:57:42.922476: +2024-11-22 06:57:42.922694: Epoch 3723 +2024-11-22 06:57:42.922806: Current learning rate: 0.00569 +2024-11-22 06:58:02.085313: train_loss -0.7886 +2024-11-22 06:58:02.085548: val_loss -0.7441 +2024-11-22 06:58:02.085623: Pseudo dice [0.8723] +2024-11-22 06:58:02.085702: Epoch time: 19.16 s +2024-11-22 06:58:03.070798: +2024-11-22 06:58:03.071007: Epoch 3724 +2024-11-22 06:58:03.071120: Current learning rate: 0.00569 +2024-11-22 06:58:21.881136: train_loss -0.7904 +2024-11-22 06:58:21.881346: val_loss -0.7517 +2024-11-22 06:58:21.881426: Pseudo dice [0.82] +2024-11-22 06:58:21.881502: Epoch time: 18.81 s +2024-11-22 06:58:22.798918: +2024-11-22 06:58:22.799115: Epoch 3725 +2024-11-22 06:58:22.799226: Current learning rate: 0.00569 +2024-11-22 06:58:41.739956: train_loss -0.7864 +2024-11-22 06:58:41.740204: val_loss -0.7477 +2024-11-22 06:58:41.740285: Pseudo dice [0.8562] +2024-11-22 06:58:41.740364: Epoch time: 18.94 s +2024-11-22 06:58:42.607006: +2024-11-22 06:58:42.607212: Epoch 3726 +2024-11-22 06:58:42.607326: Current learning rate: 0.00569 +2024-11-22 06:59:00.701535: train_loss -0.783 +2024-11-22 06:59:00.701756: val_loss -0.7465 +2024-11-22 06:59:00.701840: Pseudo dice [0.8592] +2024-11-22 06:59:00.701916: Epoch time: 18.1 s +2024-11-22 06:59:01.970728: +2024-11-22 06:59:01.970935: Epoch 3727 +2024-11-22 06:59:01.971061: Current learning rate: 0.00569 +2024-11-22 06:59:20.204127: train_loss -0.7864 +2024-11-22 06:59:20.204384: val_loss -0.7329 +2024-11-22 06:59:20.204466: Pseudo dice [0.8282] +2024-11-22 06:59:20.204552: Epoch time: 18.23 s +2024-11-22 06:59:21.078259: +2024-11-22 06:59:21.078482: Epoch 3728 +2024-11-22 06:59:21.078593: Current learning rate: 0.00569 +2024-11-22 06:59:40.225561: train_loss -0.7888 +2024-11-22 06:59:40.225783: val_loss -0.7512 +2024-11-22 06:59:40.225860: Pseudo dice [0.8304] +2024-11-22 06:59:40.225938: Epoch time: 19.15 s +2024-11-22 06:59:41.096910: +2024-11-22 06:59:41.097135: Epoch 3729 +2024-11-22 06:59:41.097248: Current learning rate: 0.00568 +2024-11-22 06:59:59.422835: train_loss -0.7872 +2024-11-22 06:59:59.423053: val_loss -0.7148 +2024-11-22 06:59:59.423130: Pseudo dice [0.8447] +2024-11-22 06:59:59.423206: Epoch time: 18.33 s +2024-11-22 07:00:00.302971: +2024-11-22 07:00:00.303175: Epoch 3730 +2024-11-22 07:00:00.303288: Current learning rate: 0.00568 +2024-11-22 07:00:18.470887: train_loss -0.7864 +2024-11-22 07:00:18.472646: val_loss -0.7628 +2024-11-22 07:00:18.472735: Pseudo dice [0.8391] +2024-11-22 07:00:18.472821: Epoch time: 18.17 s +2024-11-22 07:00:19.416471: +2024-11-22 07:00:19.416679: Epoch 3731 +2024-11-22 07:00:19.416791: Current learning rate: 0.00568 +2024-11-22 07:00:38.140960: train_loss -0.7837 +2024-11-22 07:00:38.141206: val_loss -0.7406 +2024-11-22 07:00:38.141281: Pseudo dice [0.8422] +2024-11-22 07:00:38.141358: Epoch time: 18.73 s +2024-11-22 07:00:39.027508: +2024-11-22 07:00:39.027768: Epoch 3732 +2024-11-22 07:00:39.027885: Current learning rate: 0.00568 +2024-11-22 07:00:57.827871: train_loss -0.7868 +2024-11-22 07:00:57.828094: val_loss -0.7642 +2024-11-22 07:00:57.828171: Pseudo dice [0.8569] +2024-11-22 07:00:57.828248: Epoch time: 18.8 s +2024-11-22 07:00:58.704971: +2024-11-22 07:00:58.705180: Epoch 3733 +2024-11-22 07:00:58.705293: Current learning rate: 0.00568 +2024-11-22 07:01:18.475182: train_loss -0.7884 +2024-11-22 07:01:18.475403: val_loss -0.7414 +2024-11-22 07:01:18.475477: Pseudo dice [0.8553] +2024-11-22 07:01:18.475554: Epoch time: 19.77 s +2024-11-22 07:01:19.456497: +2024-11-22 07:01:19.456692: Epoch 3734 +2024-11-22 07:01:19.456804: Current learning rate: 0.00568 +2024-11-22 07:01:38.631264: train_loss -0.7971 +2024-11-22 07:01:38.631504: val_loss -0.7436 +2024-11-22 07:01:38.631581: Pseudo dice [0.8515] +2024-11-22 07:01:38.631662: Epoch time: 19.18 s +2024-11-22 07:01:39.539650: +2024-11-22 07:01:39.539863: Epoch 3735 +2024-11-22 07:01:39.539973: Current learning rate: 0.00568 +2024-11-22 07:01:58.587566: train_loss -0.7795 +2024-11-22 07:01:58.587796: val_loss -0.7574 +2024-11-22 07:01:58.587879: Pseudo dice [0.8506] +2024-11-22 07:01:58.587954: Epoch time: 19.05 s +2024-11-22 07:01:59.468208: +2024-11-22 07:01:59.468430: Epoch 3736 +2024-11-22 07:01:59.468552: Current learning rate: 0.00568 +2024-11-22 07:02:17.759399: train_loss -0.7835 +2024-11-22 07:02:17.759612: val_loss -0.7749 +2024-11-22 07:02:17.759685: Pseudo dice [0.8498] +2024-11-22 07:02:17.759761: Epoch time: 18.29 s +2024-11-22 07:02:18.795215: +2024-11-22 07:02:18.795413: Epoch 3737 +2024-11-22 07:02:18.795520: Current learning rate: 0.00567 +2024-11-22 07:02:38.193169: train_loss -0.7839 +2024-11-22 07:02:38.193379: val_loss -0.7431 +2024-11-22 07:02:38.193454: Pseudo dice [0.8306] +2024-11-22 07:02:38.193530: Epoch time: 19.4 s +2024-11-22 07:02:39.149727: +2024-11-22 07:02:39.149926: Epoch 3738 +2024-11-22 07:02:39.150044: Current learning rate: 0.00567 +2024-11-22 07:02:58.082523: train_loss -0.7913 +2024-11-22 07:02:58.084258: val_loss -0.7419 +2024-11-22 07:02:58.084368: Pseudo dice [0.85] +2024-11-22 07:02:58.084452: Epoch time: 18.93 s +2024-11-22 07:02:58.968647: +2024-11-22 07:02:58.968850: Epoch 3739 +2024-11-22 07:02:58.968964: Current learning rate: 0.00567 +2024-11-22 07:03:18.689375: train_loss -0.7826 +2024-11-22 07:03:18.689595: val_loss -0.753 +2024-11-22 07:03:18.689670: Pseudo dice [0.855] +2024-11-22 07:03:18.689747: Epoch time: 19.72 s +2024-11-22 07:03:19.569994: +2024-11-22 07:03:19.570223: Epoch 3740 +2024-11-22 07:03:19.570340: Current learning rate: 0.00567 +2024-11-22 07:03:37.584240: train_loss -0.7888 +2024-11-22 07:03:37.584452: val_loss -0.7526 +2024-11-22 07:03:37.584527: Pseudo dice [0.8568] +2024-11-22 07:03:37.584601: Epoch time: 18.02 s +2024-11-22 07:03:37.584664: Yayy! New best EMA pseudo Dice: 0.8465 +2024-11-22 07:03:38.720198: +2024-11-22 07:03:38.720416: Epoch 3741 +2024-11-22 07:03:38.720526: Current learning rate: 0.00567 +2024-11-22 07:03:56.992968: train_loss -0.7882 +2024-11-22 07:03:56.993280: val_loss -0.738 +2024-11-22 07:03:56.993358: Pseudo dice [0.829] +2024-11-22 07:03:56.993444: Epoch time: 18.27 s +2024-11-22 07:03:57.877878: +2024-11-22 07:03:57.878117: Epoch 3742 +2024-11-22 07:03:57.878230: Current learning rate: 0.00567 +2024-11-22 07:04:17.078864: train_loss -0.788 +2024-11-22 07:04:17.079098: val_loss -0.7412 +2024-11-22 07:04:17.079177: Pseudo dice [0.852] +2024-11-22 07:04:17.079254: Epoch time: 19.2 s +2024-11-22 07:04:18.165128: +2024-11-22 07:04:18.165333: Epoch 3743 +2024-11-22 07:04:18.165440: Current learning rate: 0.00567 +2024-11-22 07:04:37.216171: train_loss -0.774 +2024-11-22 07:04:37.218565: val_loss -0.737 +2024-11-22 07:04:37.218681: Pseudo dice [0.8367] +2024-11-22 07:04:37.218765: Epoch time: 19.05 s +2024-11-22 07:04:38.102223: +2024-11-22 07:04:38.102482: Epoch 3744 +2024-11-22 07:04:38.102595: Current learning rate: 0.00567 +2024-11-22 07:04:57.102532: train_loss -0.7749 +2024-11-22 07:04:57.102771: val_loss -0.7475 +2024-11-22 07:04:57.102847: Pseudo dice [0.8358] +2024-11-22 07:04:57.102928: Epoch time: 19.0 s +2024-11-22 07:04:58.047946: +2024-11-22 07:04:58.048187: Epoch 3745 +2024-11-22 07:04:58.048316: Current learning rate: 0.00567 +2024-11-22 07:05:15.935508: train_loss -0.7713 +2024-11-22 07:05:15.935802: val_loss -0.7425 +2024-11-22 07:05:15.935878: Pseudo dice [0.8348] +2024-11-22 07:05:15.935959: Epoch time: 17.89 s +2024-11-22 07:05:16.819471: +2024-11-22 07:05:16.819679: Epoch 3746 +2024-11-22 07:05:16.819793: Current learning rate: 0.00566 +2024-11-22 07:05:36.034059: train_loss -0.7772 +2024-11-22 07:05:36.034369: val_loss -0.766 +2024-11-22 07:05:36.034446: Pseudo dice [0.8704] +2024-11-22 07:05:36.034527: Epoch time: 19.22 s +2024-11-22 07:05:36.915730: +2024-11-22 07:05:36.915951: Epoch 3747 +2024-11-22 07:05:36.916073: Current learning rate: 0.00566 +2024-11-22 07:05:55.750785: train_loss -0.7888 +2024-11-22 07:05:55.751014: val_loss -0.7551 +2024-11-22 07:05:55.751112: Pseudo dice [0.8586] +2024-11-22 07:05:55.751192: Epoch time: 18.84 s +2024-11-22 07:05:55.751258: Yayy! New best EMA pseudo Dice: 0.8469 +2024-11-22 07:05:56.870778: +2024-11-22 07:05:56.871040: Epoch 3748 +2024-11-22 07:05:56.871155: Current learning rate: 0.00566 +2024-11-22 07:06:16.146683: train_loss -0.7906 +2024-11-22 07:06:16.146916: val_loss -0.7495 +2024-11-22 07:06:16.147002: Pseudo dice [0.8278] +2024-11-22 07:06:16.147087: Epoch time: 19.28 s +2024-11-22 07:06:17.021844: +2024-11-22 07:06:17.022061: Epoch 3749 +2024-11-22 07:06:17.022175: Current learning rate: 0.00566 +2024-11-22 07:06:34.838245: train_loss -0.7901 +2024-11-22 07:06:34.838510: val_loss -0.7632 +2024-11-22 07:06:34.838589: Pseudo dice [0.8458] +2024-11-22 07:06:34.838708: Epoch time: 17.82 s +2024-11-22 07:06:35.978724: +2024-11-22 07:06:35.978957: Epoch 3750 +2024-11-22 07:06:35.979078: Current learning rate: 0.00566 +2024-11-22 07:06:53.455832: train_loss -0.7745 +2024-11-22 07:06:53.456049: val_loss -0.7602 +2024-11-22 07:06:53.456124: Pseudo dice [0.8286] +2024-11-22 07:06:53.456199: Epoch time: 17.48 s +2024-11-22 07:06:54.336357: +2024-11-22 07:06:54.336594: Epoch 3751 +2024-11-22 07:06:54.336706: Current learning rate: 0.00566 +2024-11-22 07:07:13.152186: train_loss -0.7845 +2024-11-22 07:07:13.152407: val_loss -0.7419 +2024-11-22 07:07:13.152485: Pseudo dice [0.8281] +2024-11-22 07:07:13.152567: Epoch time: 18.82 s +2024-11-22 07:07:14.034643: +2024-11-22 07:07:14.034857: Epoch 3752 +2024-11-22 07:07:14.034969: Current learning rate: 0.00566 +2024-11-22 07:07:33.955880: train_loss -0.794 +2024-11-22 07:07:33.957367: val_loss -0.7384 +2024-11-22 07:07:33.957445: Pseudo dice [0.8342] +2024-11-22 07:07:33.957543: Epoch time: 19.92 s +2024-11-22 07:07:34.840410: +2024-11-22 07:07:34.840658: Epoch 3753 +2024-11-22 07:07:34.840817: Current learning rate: 0.00566 +2024-11-22 07:07:53.962338: train_loss -0.79 +2024-11-22 07:07:53.962590: val_loss -0.7487 +2024-11-22 07:07:53.962666: Pseudo dice [0.8415] +2024-11-22 07:07:53.962745: Epoch time: 19.12 s +2024-11-22 07:07:54.980330: +2024-11-22 07:07:54.980575: Epoch 3754 +2024-11-22 07:07:54.980695: Current learning rate: 0.00565 +2024-11-22 07:08:13.093166: train_loss -0.7863 +2024-11-22 07:08:13.093388: val_loss -0.737 +2024-11-22 07:08:13.093463: Pseudo dice [0.8254] +2024-11-22 07:08:13.093539: Epoch time: 18.11 s +2024-11-22 07:08:13.970798: +2024-11-22 07:08:13.971020: Epoch 3755 +2024-11-22 07:08:13.971134: Current learning rate: 0.00565 +2024-11-22 07:08:32.793782: train_loss -0.7801 +2024-11-22 07:08:32.794012: val_loss -0.7484 +2024-11-22 07:08:32.794088: Pseudo dice [0.8512] +2024-11-22 07:08:32.794166: Epoch time: 18.82 s +2024-11-22 07:08:33.780081: +2024-11-22 07:08:33.780275: Epoch 3756 +2024-11-22 07:08:33.780391: Current learning rate: 0.00565 +2024-11-22 07:08:52.578500: train_loss -0.7892 +2024-11-22 07:08:52.578796: val_loss -0.7515 +2024-11-22 07:08:52.578874: Pseudo dice [0.8236] +2024-11-22 07:08:52.578953: Epoch time: 18.8 s +2024-11-22 07:08:53.460938: +2024-11-22 07:08:53.461157: Epoch 3757 +2024-11-22 07:08:53.461271: Current learning rate: 0.00565 +2024-11-22 07:09:13.076157: train_loss -0.7889 +2024-11-22 07:09:13.076422: val_loss -0.7446 +2024-11-22 07:09:13.076501: Pseudo dice [0.8326] +2024-11-22 07:09:13.076586: Epoch time: 19.62 s +2024-11-22 07:09:13.954473: +2024-11-22 07:09:13.954678: Epoch 3758 +2024-11-22 07:09:13.954790: Current learning rate: 0.00565 +2024-11-22 07:09:31.863148: train_loss -0.7928 +2024-11-22 07:09:31.863369: val_loss -0.7619 +2024-11-22 07:09:31.863448: Pseudo dice [0.87] +2024-11-22 07:09:31.863527: Epoch time: 17.91 s +2024-11-22 07:09:32.795735: +2024-11-22 07:09:32.795950: Epoch 3759 +2024-11-22 07:09:32.796070: Current learning rate: 0.00565 +2024-11-22 07:09:50.953523: train_loss -0.7937 +2024-11-22 07:09:50.953751: val_loss -0.7755 +2024-11-22 07:09:50.953830: Pseudo dice [0.8585] +2024-11-22 07:09:50.953907: Epoch time: 18.16 s +2024-11-22 07:09:52.263015: +2024-11-22 07:09:52.263213: Epoch 3760 +2024-11-22 07:09:52.263328: Current learning rate: 0.00565 +2024-11-22 07:10:11.124784: train_loss -0.7842 +2024-11-22 07:10:11.125054: val_loss -0.7148 +2024-11-22 07:10:11.125130: Pseudo dice [0.8161] +2024-11-22 07:10:11.125214: Epoch time: 18.86 s +2024-11-22 07:10:12.021172: +2024-11-22 07:10:12.021407: Epoch 3761 +2024-11-22 07:10:12.021518: Current learning rate: 0.00565 +2024-11-22 07:10:29.632573: train_loss -0.7859 +2024-11-22 07:10:29.632804: val_loss -0.7583 +2024-11-22 07:10:29.632878: Pseudo dice [0.8369] +2024-11-22 07:10:29.632952: Epoch time: 17.61 s +2024-11-22 07:10:30.514073: +2024-11-22 07:10:30.514348: Epoch 3762 +2024-11-22 07:10:30.514459: Current learning rate: 0.00564 +2024-11-22 07:10:48.708247: train_loss -0.7756 +2024-11-22 07:10:48.708473: val_loss -0.7593 +2024-11-22 07:10:48.708548: Pseudo dice [0.8547] +2024-11-22 07:10:48.708624: Epoch time: 18.19 s +2024-11-22 07:10:49.586919: +2024-11-22 07:10:49.587203: Epoch 3763 +2024-11-22 07:10:49.587313: Current learning rate: 0.00564 +2024-11-22 07:11:08.619280: train_loss -0.7933 +2024-11-22 07:11:08.619524: val_loss -0.7422 +2024-11-22 07:11:08.619601: Pseudo dice [0.8475] +2024-11-22 07:11:08.619695: Epoch time: 19.03 s +2024-11-22 07:11:09.579932: +2024-11-22 07:11:09.580177: Epoch 3764 +2024-11-22 07:11:09.580287: Current learning rate: 0.00564 +2024-11-22 07:11:28.363327: train_loss -0.7839 +2024-11-22 07:11:28.363566: val_loss -0.7289 +2024-11-22 07:11:28.363642: Pseudo dice [0.8554] +2024-11-22 07:11:28.363722: Epoch time: 18.78 s +2024-11-22 07:11:29.240480: +2024-11-22 07:11:29.240693: Epoch 3765 +2024-11-22 07:11:29.240803: Current learning rate: 0.00564 +2024-11-22 07:11:48.826762: train_loss -0.7902 +2024-11-22 07:11:48.826988: val_loss -0.7448 +2024-11-22 07:11:48.827081: Pseudo dice [0.8489] +2024-11-22 07:11:48.827162: Epoch time: 19.59 s +2024-11-22 07:11:49.826131: +2024-11-22 07:11:49.826328: Epoch 3766 +2024-11-22 07:11:49.826438: Current learning rate: 0.00564 +2024-11-22 07:12:09.249298: train_loss -0.7873 +2024-11-22 07:12:09.249542: val_loss -0.755 +2024-11-22 07:12:09.249618: Pseudo dice [0.8328] +2024-11-22 07:12:09.249697: Epoch time: 19.42 s +2024-11-22 07:12:10.128466: +2024-11-22 07:12:10.128719: Epoch 3767 +2024-11-22 07:12:10.128832: Current learning rate: 0.00564 +2024-11-22 07:12:29.214539: train_loss -0.7858 +2024-11-22 07:12:29.214756: val_loss -0.7489 +2024-11-22 07:12:29.214832: Pseudo dice [0.8083] +2024-11-22 07:12:29.214911: Epoch time: 19.09 s +2024-11-22 07:12:30.117543: +2024-11-22 07:12:30.117749: Epoch 3768 +2024-11-22 07:12:30.117861: Current learning rate: 0.00564 +2024-11-22 07:12:47.760965: train_loss -0.7877 +2024-11-22 07:12:47.761214: val_loss -0.7408 +2024-11-22 07:12:47.761296: Pseudo dice [0.8235] +2024-11-22 07:12:47.761377: Epoch time: 17.64 s +2024-11-22 07:12:48.833726: +2024-11-22 07:12:48.833955: Epoch 3769 +2024-11-22 07:12:48.834073: Current learning rate: 0.00564 +2024-11-22 07:13:07.089144: train_loss -0.7918 +2024-11-22 07:13:07.089365: val_loss -0.7169 +2024-11-22 07:13:07.089442: Pseudo dice [0.8162] +2024-11-22 07:13:07.089521: Epoch time: 18.26 s +2024-11-22 07:13:07.974216: +2024-11-22 07:13:07.974442: Epoch 3770 +2024-11-22 07:13:07.974562: Current learning rate: 0.00564 +2024-11-22 07:13:26.195884: train_loss -0.7957 +2024-11-22 07:13:26.196169: val_loss -0.7286 +2024-11-22 07:13:26.196248: Pseudo dice [0.8623] +2024-11-22 07:13:26.196325: Epoch time: 18.22 s +2024-11-22 07:13:27.097004: +2024-11-22 07:13:27.097231: Epoch 3771 +2024-11-22 07:13:27.097347: Current learning rate: 0.00563 +2024-11-22 07:13:44.927296: train_loss -0.8031 +2024-11-22 07:13:44.932728: val_loss -0.7611 +2024-11-22 07:13:44.932852: Pseudo dice [0.843] +2024-11-22 07:13:44.932963: Epoch time: 17.83 s +2024-11-22 07:13:46.118079: +2024-11-22 07:13:46.118311: Epoch 3772 +2024-11-22 07:13:46.118426: Current learning rate: 0.00563 +2024-11-22 07:14:05.096027: train_loss -0.7947 +2024-11-22 07:14:05.096318: val_loss -0.7444 +2024-11-22 07:14:05.096398: Pseudo dice [0.8487] +2024-11-22 07:14:05.096479: Epoch time: 18.98 s +2024-11-22 07:14:05.979283: +2024-11-22 07:14:05.979515: Epoch 3773 +2024-11-22 07:14:05.979626: Current learning rate: 0.00563 +2024-11-22 07:14:24.074835: train_loss -0.7884 +2024-11-22 07:14:24.075059: val_loss -0.7646 +2024-11-22 07:14:24.075142: Pseudo dice [0.8549] +2024-11-22 07:14:24.075218: Epoch time: 18.1 s +2024-11-22 07:14:25.041711: +2024-11-22 07:14:25.041986: Epoch 3774 +2024-11-22 07:14:25.042175: Current learning rate: 0.00563 +2024-11-22 07:14:43.764153: train_loss -0.7917 +2024-11-22 07:14:43.764367: val_loss -0.7435 +2024-11-22 07:14:43.764452: Pseudo dice [0.8695] +2024-11-22 07:14:43.764534: Epoch time: 18.72 s +2024-11-22 07:14:44.629520: +2024-11-22 07:14:44.629732: Epoch 3775 +2024-11-22 07:14:44.629846: Current learning rate: 0.00563 +2024-11-22 07:15:03.502350: train_loss -0.7932 +2024-11-22 07:15:03.502595: val_loss -0.7547 +2024-11-22 07:15:03.502676: Pseudo dice [0.8444] +2024-11-22 07:15:03.502759: Epoch time: 18.87 s +2024-11-22 07:15:04.641374: +2024-11-22 07:15:04.641573: Epoch 3776 +2024-11-22 07:15:04.641682: Current learning rate: 0.00563 +2024-11-22 07:15:23.742619: train_loss -0.774 +2024-11-22 07:15:23.742893: val_loss -0.7444 +2024-11-22 07:15:23.742966: Pseudo dice [0.8143] +2024-11-22 07:15:23.743047: Epoch time: 19.1 s +2024-11-22 07:15:24.607361: +2024-11-22 07:15:24.607587: Epoch 3777 +2024-11-22 07:15:24.607706: Current learning rate: 0.00563 +2024-11-22 07:15:43.859324: train_loss -0.7848 +2024-11-22 07:15:43.859537: val_loss -0.7209 +2024-11-22 07:15:43.859616: Pseudo dice [0.8384] +2024-11-22 07:15:43.859695: Epoch time: 19.25 s +2024-11-22 07:15:44.725006: +2024-11-22 07:15:44.725227: Epoch 3778 +2024-11-22 07:15:44.725342: Current learning rate: 0.00563 +2024-11-22 07:16:02.511614: train_loss -0.7802 +2024-11-22 07:16:02.511919: val_loss -0.7558 +2024-11-22 07:16:02.512008: Pseudo dice [0.821] +2024-11-22 07:16:02.512090: Epoch time: 17.79 s +2024-11-22 07:16:03.467607: +2024-11-22 07:16:03.467825: Epoch 3779 +2024-11-22 07:16:03.467938: Current learning rate: 0.00562 +2024-11-22 07:16:22.992333: train_loss -0.7938 +2024-11-22 07:16:22.992582: val_loss -0.7305 +2024-11-22 07:16:22.992661: Pseudo dice [0.8428] +2024-11-22 07:16:22.992745: Epoch time: 19.53 s +2024-11-22 07:16:23.871714: +2024-11-22 07:16:23.871933: Epoch 3780 +2024-11-22 07:16:23.872056: Current learning rate: 0.00562 +2024-11-22 07:16:41.132411: train_loss -0.7994 +2024-11-22 07:16:41.132619: val_loss -0.7444 +2024-11-22 07:16:41.132693: Pseudo dice [0.8625] +2024-11-22 07:16:41.132767: Epoch time: 17.26 s +2024-11-22 07:16:42.166002: +2024-11-22 07:16:42.166222: Epoch 3781 +2024-11-22 07:16:42.166335: Current learning rate: 0.00562 +2024-11-22 07:17:01.267715: train_loss -0.7788 +2024-11-22 07:17:01.267946: val_loss -0.7441 +2024-11-22 07:17:01.268031: Pseudo dice [0.8133] +2024-11-22 07:17:01.270361: Epoch time: 19.1 s +2024-11-22 07:17:02.267696: +2024-11-22 07:17:02.267926: Epoch 3782 +2024-11-22 07:17:02.268048: Current learning rate: 0.00562 +2024-11-22 07:17:19.895080: train_loss -0.7915 +2024-11-22 07:17:19.895301: val_loss -0.7372 +2024-11-22 07:17:19.895380: Pseudo dice [0.8432] +2024-11-22 07:17:19.895462: Epoch time: 17.63 s +2024-11-22 07:17:20.773741: +2024-11-22 07:17:20.774164: Epoch 3783 +2024-11-22 07:17:20.774298: Current learning rate: 0.00562 +2024-11-22 07:17:39.550321: train_loss -0.7876 +2024-11-22 07:17:39.550564: val_loss -0.771 +2024-11-22 07:17:39.550643: Pseudo dice [0.8414] +2024-11-22 07:17:39.550723: Epoch time: 18.78 s +2024-11-22 07:17:40.425821: +2024-11-22 07:17:40.426031: Epoch 3784 +2024-11-22 07:17:40.426151: Current learning rate: 0.00562 +2024-11-22 07:17:59.294000: train_loss -0.7941 +2024-11-22 07:17:59.294205: val_loss -0.7502 +2024-11-22 07:17:59.294279: Pseudo dice [0.8367] +2024-11-22 07:17:59.294354: Epoch time: 18.87 s +2024-11-22 07:18:00.216071: +2024-11-22 07:18:00.216310: Epoch 3785 +2024-11-22 07:18:00.216420: Current learning rate: 0.00562 +2024-11-22 07:18:18.367008: train_loss -0.7968 +2024-11-22 07:18:18.367231: val_loss -0.7548 +2024-11-22 07:18:18.367305: Pseudo dice [0.8334] +2024-11-22 07:18:18.367381: Epoch time: 18.15 s +2024-11-22 07:18:19.250263: +2024-11-22 07:18:19.250472: Epoch 3786 +2024-11-22 07:18:19.250578: Current learning rate: 0.00562 +2024-11-22 07:18:37.820595: train_loss -0.7909 +2024-11-22 07:18:37.820878: val_loss -0.7598 +2024-11-22 07:18:37.820956: Pseudo dice [0.8476] +2024-11-22 07:18:37.821043: Epoch time: 18.57 s +2024-11-22 07:18:38.708968: +2024-11-22 07:18:38.709198: Epoch 3787 +2024-11-22 07:18:38.709313: Current learning rate: 0.00562 +2024-11-22 07:18:58.779503: train_loss -0.7753 +2024-11-22 07:18:58.779784: val_loss -0.7 +2024-11-22 07:18:58.779863: Pseudo dice [0.837] +2024-11-22 07:18:58.779946: Epoch time: 20.07 s +2024-11-22 07:18:59.661727: +2024-11-22 07:18:59.661931: Epoch 3788 +2024-11-22 07:18:59.662049: Current learning rate: 0.00561 +2024-11-22 07:19:18.032715: train_loss -0.7865 +2024-11-22 07:19:18.032957: val_loss -0.7107 +2024-11-22 07:19:18.033066: Pseudo dice [0.8159] +2024-11-22 07:19:18.033147: Epoch time: 18.37 s +2024-11-22 07:19:18.922562: +2024-11-22 07:19:18.922808: Epoch 3789 +2024-11-22 07:19:18.922918: Current learning rate: 0.00561 +2024-11-22 07:19:36.796709: train_loss -0.7857 +2024-11-22 07:19:36.796937: val_loss -0.733 +2024-11-22 07:19:36.797017: Pseudo dice [0.822] +2024-11-22 07:19:36.797094: Epoch time: 17.87 s +2024-11-22 07:19:37.679552: +2024-11-22 07:19:37.679775: Epoch 3790 +2024-11-22 07:19:37.679885: Current learning rate: 0.00561 +2024-11-22 07:19:55.573664: train_loss -0.7789 +2024-11-22 07:19:55.573887: val_loss -0.7617 +2024-11-22 07:19:55.573966: Pseudo dice [0.8272] +2024-11-22 07:19:55.574049: Epoch time: 17.89 s +2024-11-22 07:19:56.469127: +2024-11-22 07:19:56.469381: Epoch 3791 +2024-11-22 07:19:56.469535: Current learning rate: 0.00561 +2024-11-22 07:20:13.957238: train_loss -0.7929 +2024-11-22 07:20:13.957462: val_loss -0.7441 +2024-11-22 07:20:13.957538: Pseudo dice [0.8587] +2024-11-22 07:20:13.957616: Epoch time: 17.49 s +2024-11-22 07:20:14.832003: +2024-11-22 07:20:14.832197: Epoch 3792 +2024-11-22 07:20:14.832310: Current learning rate: 0.00561 +2024-11-22 07:20:33.524493: train_loss -0.7891 +2024-11-22 07:20:33.524712: val_loss -0.7366 +2024-11-22 07:20:33.524791: Pseudo dice [0.8439] +2024-11-22 07:20:33.524870: Epoch time: 18.69 s +2024-11-22 07:20:34.403651: +2024-11-22 07:20:34.403858: Epoch 3793 +2024-11-22 07:20:34.403975: Current learning rate: 0.00561 +2024-11-22 07:20:53.636268: train_loss -0.7853 +2024-11-22 07:20:53.638651: val_loss -0.6964 +2024-11-22 07:20:53.638746: Pseudo dice [0.8375] +2024-11-22 07:20:53.638824: Epoch time: 19.23 s +2024-11-22 07:20:54.565030: +2024-11-22 07:20:54.565297: Epoch 3794 +2024-11-22 07:20:54.565411: Current learning rate: 0.00561 +2024-11-22 07:21:13.395922: train_loss -0.7828 +2024-11-22 07:21:13.396194: val_loss -0.7383 +2024-11-22 07:21:13.396271: Pseudo dice [0.8393] +2024-11-22 07:21:13.396355: Epoch time: 18.83 s +2024-11-22 07:21:14.708270: +2024-11-22 07:21:14.708480: Epoch 3795 +2024-11-22 07:21:14.708592: Current learning rate: 0.00561 +2024-11-22 07:21:33.556361: train_loss -0.7866 +2024-11-22 07:21:33.556583: val_loss -0.7276 +2024-11-22 07:21:33.556658: Pseudo dice [0.8256] +2024-11-22 07:21:33.556734: Epoch time: 18.85 s +2024-11-22 07:21:34.440021: +2024-11-22 07:21:34.440264: Epoch 3796 +2024-11-22 07:21:34.440387: Current learning rate: 0.0056 +2024-11-22 07:21:53.508519: train_loss -0.7802 +2024-11-22 07:21:53.508734: val_loss -0.7374 +2024-11-22 07:21:53.508819: Pseudo dice [0.819] +2024-11-22 07:21:53.508897: Epoch time: 19.07 s +2024-11-22 07:21:54.385108: +2024-11-22 07:21:54.385334: Epoch 3797 +2024-11-22 07:21:54.385447: Current learning rate: 0.0056 +2024-11-22 07:22:11.825259: train_loss -0.7814 +2024-11-22 07:22:11.825512: val_loss -0.7399 +2024-11-22 07:22:11.825591: Pseudo dice [0.8054] +2024-11-22 07:22:11.825670: Epoch time: 17.44 s +2024-11-22 07:22:12.827193: +2024-11-22 07:22:12.827413: Epoch 3798 +2024-11-22 07:22:12.827528: Current learning rate: 0.0056 +2024-11-22 07:22:31.464572: train_loss -0.7866 +2024-11-22 07:22:31.464830: val_loss -0.7526 +2024-11-22 07:22:31.464905: Pseudo dice [0.8177] +2024-11-22 07:22:31.470151: Epoch time: 18.64 s +2024-11-22 07:22:32.527558: +2024-11-22 07:22:32.527819: Epoch 3799 +2024-11-22 07:22:32.527928: Current learning rate: 0.0056 +2024-11-22 07:22:51.697751: train_loss -0.7889 +2024-11-22 07:22:51.697974: val_loss -0.7575 +2024-11-22 07:22:51.698056: Pseudo dice [0.8572] +2024-11-22 07:22:51.698134: Epoch time: 19.17 s +2024-11-22 07:22:52.831075: +2024-11-22 07:22:52.831442: Epoch 3800 +2024-11-22 07:22:52.831562: Current learning rate: 0.0056 +2024-11-22 07:23:11.422032: train_loss -0.797 +2024-11-22 07:23:11.422258: val_loss -0.7193 +2024-11-22 07:23:11.422334: Pseudo dice [0.8334] +2024-11-22 07:23:11.422412: Epoch time: 18.59 s +2024-11-22 07:23:12.343527: +2024-11-22 07:23:12.343748: Epoch 3801 +2024-11-22 07:23:12.343861: Current learning rate: 0.0056 +2024-11-22 07:23:30.824430: train_loss -0.7884 +2024-11-22 07:23:30.824713: val_loss -0.7255 +2024-11-22 07:23:30.824793: Pseudo dice [0.8398] +2024-11-22 07:23:30.824871: Epoch time: 18.48 s +2024-11-22 07:23:31.717692: +2024-11-22 07:23:31.718132: Epoch 3802 +2024-11-22 07:23:31.718247: Current learning rate: 0.0056 +2024-11-22 07:23:51.312560: train_loss -0.7915 +2024-11-22 07:23:51.312810: val_loss -0.7506 +2024-11-22 07:23:51.312886: Pseudo dice [0.8238] +2024-11-22 07:23:51.312965: Epoch time: 19.6 s +2024-11-22 07:23:52.216379: +2024-11-22 07:23:52.216609: Epoch 3803 +2024-11-22 07:23:52.216728: Current learning rate: 0.0056 +2024-11-22 07:24:11.206449: train_loss -0.7962 +2024-11-22 07:24:11.206733: val_loss -0.726 +2024-11-22 07:24:11.206811: Pseudo dice [0.8605] +2024-11-22 07:24:11.206888: Epoch time: 18.99 s +2024-11-22 07:24:12.131752: +2024-11-22 07:24:12.131952: Epoch 3804 +2024-11-22 07:24:12.132070: Current learning rate: 0.00559 +2024-11-22 07:24:31.298321: train_loss -0.7876 +2024-11-22 07:24:31.298544: val_loss -0.7364 +2024-11-22 07:24:31.298621: Pseudo dice [0.8315] +2024-11-22 07:24:31.298698: Epoch time: 19.17 s +2024-11-22 07:24:32.178477: +2024-11-22 07:24:32.178695: Epoch 3805 +2024-11-22 07:24:32.178810: Current learning rate: 0.00559 +2024-11-22 07:24:50.986366: train_loss -0.7993 +2024-11-22 07:24:50.986591: val_loss -0.7301 +2024-11-22 07:24:50.986685: Pseudo dice [0.8489] +2024-11-22 07:24:50.986766: Epoch time: 18.81 s +2024-11-22 07:24:51.882609: +2024-11-22 07:24:51.882834: Epoch 3806 +2024-11-22 07:24:51.882972: Current learning rate: 0.00559 +2024-11-22 07:25:10.451279: train_loss -0.7801 +2024-11-22 07:25:10.451529: val_loss -0.7403 +2024-11-22 07:25:10.451605: Pseudo dice [0.8549] +2024-11-22 07:25:10.451682: Epoch time: 18.57 s +2024-11-22 07:25:11.329561: +2024-11-22 07:25:11.329806: Epoch 3807 +2024-11-22 07:25:11.329928: Current learning rate: 0.00559 +2024-11-22 07:25:30.729467: train_loss -0.7807 +2024-11-22 07:25:30.729709: val_loss -0.7647 +2024-11-22 07:25:30.729794: Pseudo dice [0.856] +2024-11-22 07:25:30.729869: Epoch time: 19.4 s +2024-11-22 07:25:31.610668: +2024-11-22 07:25:31.610931: Epoch 3808 +2024-11-22 07:25:31.611049: Current learning rate: 0.00559 +2024-11-22 07:25:50.460838: train_loss -0.7768 +2024-11-22 07:25:50.461072: val_loss -0.7492 +2024-11-22 07:25:50.461152: Pseudo dice [0.8298] +2024-11-22 07:25:50.461233: Epoch time: 18.85 s +2024-11-22 07:25:51.338326: +2024-11-22 07:25:51.338542: Epoch 3809 +2024-11-22 07:25:51.338654: Current learning rate: 0.00559 +2024-11-22 07:26:09.811948: train_loss -0.773 +2024-11-22 07:26:09.812229: val_loss -0.7403 +2024-11-22 07:26:09.812311: Pseudo dice [0.8406] +2024-11-22 07:26:09.812396: Epoch time: 18.47 s +2024-11-22 07:26:10.738462: +2024-11-22 07:26:10.738657: Epoch 3810 +2024-11-22 07:26:10.738768: Current learning rate: 0.00559 +2024-11-22 07:26:31.130589: train_loss -0.7858 +2024-11-22 07:26:31.130838: val_loss -0.7393 +2024-11-22 07:26:31.130912: Pseudo dice [0.847] +2024-11-22 07:26:31.130990: Epoch time: 20.39 s +2024-11-22 07:26:32.178954: +2024-11-22 07:26:32.179185: Epoch 3811 +2024-11-22 07:26:32.179293: Current learning rate: 0.00559 +2024-11-22 07:26:51.106560: train_loss -0.7949 +2024-11-22 07:26:51.106776: val_loss -0.7572 +2024-11-22 07:26:51.106853: Pseudo dice [0.8535] +2024-11-22 07:26:51.106934: Epoch time: 18.93 s +2024-11-22 07:26:51.993509: +2024-11-22 07:26:51.993707: Epoch 3812 +2024-11-22 07:26:51.993815: Current learning rate: 0.00559 +2024-11-22 07:27:11.118429: train_loss -0.7827 +2024-11-22 07:27:11.118646: val_loss -0.7427 +2024-11-22 07:27:11.118723: Pseudo dice [0.824] +2024-11-22 07:27:11.118800: Epoch time: 19.13 s +2024-11-22 07:27:12.104650: +2024-11-22 07:27:12.104861: Epoch 3813 +2024-11-22 07:27:12.104974: Current learning rate: 0.00558 +2024-11-22 07:27:31.533844: train_loss -0.7876 +2024-11-22 07:27:31.534063: val_loss -0.7455 +2024-11-22 07:27:31.534141: Pseudo dice [0.8715] +2024-11-22 07:27:31.534223: Epoch time: 19.43 s +2024-11-22 07:27:32.413746: +2024-11-22 07:27:32.413963: Epoch 3814 +2024-11-22 07:27:32.414081: Current learning rate: 0.00558 +2024-11-22 07:27:51.297727: train_loss -0.7847 +2024-11-22 07:27:51.297966: val_loss -0.7199 +2024-11-22 07:27:51.298046: Pseudo dice [0.8303] +2024-11-22 07:27:51.298126: Epoch time: 18.88 s +2024-11-22 07:27:52.165174: +2024-11-22 07:27:52.165377: Epoch 3815 +2024-11-22 07:27:52.165495: Current learning rate: 0.00558 +2024-11-22 07:28:11.407431: train_loss -0.7857 +2024-11-22 07:28:11.407657: val_loss -0.7364 +2024-11-22 07:28:11.407733: Pseudo dice [0.8538] +2024-11-22 07:28:11.407810: Epoch time: 19.24 s +2024-11-22 07:28:12.325291: +2024-11-22 07:28:12.325496: Epoch 3816 +2024-11-22 07:28:12.325605: Current learning rate: 0.00558 +2024-11-22 07:28:30.711957: train_loss -0.7874 +2024-11-22 07:28:30.712182: val_loss -0.7402 +2024-11-22 07:28:30.712256: Pseudo dice [0.8442] +2024-11-22 07:28:30.712332: Epoch time: 18.39 s +2024-11-22 07:28:31.973986: +2024-11-22 07:28:31.974186: Epoch 3817 +2024-11-22 07:28:31.974296: Current learning rate: 0.00558 +2024-11-22 07:28:49.742537: train_loss -0.7751 +2024-11-22 07:28:49.742809: val_loss -0.7282 +2024-11-22 07:28:49.742888: Pseudo dice [0.8354] +2024-11-22 07:28:49.748273: Epoch time: 17.77 s +2024-11-22 07:28:50.751041: +2024-11-22 07:28:50.751256: Epoch 3818 +2024-11-22 07:28:50.751368: Current learning rate: 0.00558 +2024-11-22 07:29:10.392104: train_loss -0.7794 +2024-11-22 07:29:10.392318: val_loss -0.7309 +2024-11-22 07:29:10.392391: Pseudo dice [0.8337] +2024-11-22 07:29:10.392464: Epoch time: 19.64 s +2024-11-22 07:29:11.361835: +2024-11-22 07:29:11.362252: Epoch 3819 +2024-11-22 07:29:11.362369: Current learning rate: 0.00558 +2024-11-22 07:29:30.785106: train_loss -0.7785 +2024-11-22 07:29:30.785339: val_loss -0.7322 +2024-11-22 07:29:30.785422: Pseudo dice [0.8044] +2024-11-22 07:29:30.785515: Epoch time: 19.42 s +2024-11-22 07:29:31.697778: +2024-11-22 07:29:31.698004: Epoch 3820 +2024-11-22 07:29:31.698116: Current learning rate: 0.00558 +2024-11-22 07:29:50.496517: train_loss -0.7682 +2024-11-22 07:29:50.496747: val_loss -0.7218 +2024-11-22 07:29:50.496824: Pseudo dice [0.8364] +2024-11-22 07:29:50.496901: Epoch time: 18.8 s +2024-11-22 07:29:51.400499: +2024-11-22 07:29:51.400701: Epoch 3821 +2024-11-22 07:29:51.400810: Current learning rate: 0.00557 +2024-11-22 07:30:09.913277: train_loss -0.7791 +2024-11-22 07:30:09.913516: val_loss -0.7598 +2024-11-22 07:30:09.913590: Pseudo dice [0.8607] +2024-11-22 07:30:09.913672: Epoch time: 18.51 s +2024-11-22 07:30:10.783783: +2024-11-22 07:30:10.783994: Epoch 3822 +2024-11-22 07:30:10.784105: Current learning rate: 0.00557 +2024-11-22 07:30:29.760420: train_loss -0.7886 +2024-11-22 07:30:29.760635: val_loss -0.7259 +2024-11-22 07:30:29.760715: Pseudo dice [0.8245] +2024-11-22 07:30:29.760790: Epoch time: 18.98 s +2024-11-22 07:30:30.655729: +2024-11-22 07:30:30.655949: Epoch 3823 +2024-11-22 07:30:30.656065: Current learning rate: 0.00557 +2024-11-22 07:30:49.457164: train_loss -0.7909 +2024-11-22 07:30:49.457458: val_loss -0.7549 +2024-11-22 07:30:49.457539: Pseudo dice [0.8532] +2024-11-22 07:30:49.457615: Epoch time: 18.8 s +2024-11-22 07:30:50.343096: +2024-11-22 07:30:50.343307: Epoch 3824 +2024-11-22 07:30:50.343419: Current learning rate: 0.00557 +2024-11-22 07:31:08.744582: train_loss -0.7932 +2024-11-22 07:31:08.744797: val_loss -0.7341 +2024-11-22 07:31:08.744872: Pseudo dice [0.8357] +2024-11-22 07:31:08.744950: Epoch time: 18.4 s +2024-11-22 07:31:09.628345: +2024-11-22 07:31:09.628556: Epoch 3825 +2024-11-22 07:31:09.628667: Current learning rate: 0.00557 +2024-11-22 07:31:27.923361: train_loss -0.7973 +2024-11-22 07:31:27.925808: val_loss -0.7745 +2024-11-22 07:31:27.925962: Pseudo dice [0.8548] +2024-11-22 07:31:27.926059: Epoch time: 18.3 s +2024-11-22 07:31:28.838986: +2024-11-22 07:31:28.839250: Epoch 3826 +2024-11-22 07:31:28.839367: Current learning rate: 0.00557 +2024-11-22 07:31:46.745956: train_loss -0.7859 +2024-11-22 07:31:46.746233: val_loss -0.7249 +2024-11-22 07:31:46.746311: Pseudo dice [0.8077] +2024-11-22 07:31:46.746389: Epoch time: 17.91 s +2024-11-22 07:31:47.639109: +2024-11-22 07:31:47.639295: Epoch 3827 +2024-11-22 07:31:47.639405: Current learning rate: 0.00557 +2024-11-22 07:32:05.366938: train_loss -0.7784 +2024-11-22 07:32:05.367175: val_loss -0.7435 +2024-11-22 07:32:05.367251: Pseudo dice [0.8178] +2024-11-22 07:32:05.367327: Epoch time: 17.73 s +2024-11-22 07:32:06.252947: +2024-11-22 07:32:06.253151: Epoch 3828 +2024-11-22 07:32:06.253266: Current learning rate: 0.00557 +2024-11-22 07:32:24.638060: train_loss -0.7795 +2024-11-22 07:32:24.641116: val_loss -0.7175 +2024-11-22 07:32:24.641217: Pseudo dice [0.8335] +2024-11-22 07:32:24.641300: Epoch time: 18.39 s +2024-11-22 07:32:25.963791: +2024-11-22 07:32:25.964057: Epoch 3829 +2024-11-22 07:32:25.964175: Current learning rate: 0.00556 +2024-11-22 07:32:45.756594: train_loss -0.789 +2024-11-22 07:32:45.756858: val_loss -0.7677 +2024-11-22 07:32:45.756932: Pseudo dice [0.8502] +2024-11-22 07:32:45.759199: Epoch time: 19.79 s +2024-11-22 07:32:46.689420: +2024-11-22 07:32:46.689732: Epoch 3830 +2024-11-22 07:32:46.689846: Current learning rate: 0.00556 +2024-11-22 07:33:04.451623: train_loss -0.7913 +2024-11-22 07:33:04.451844: val_loss -0.7651 +2024-11-22 07:33:04.451921: Pseudo dice [0.868] +2024-11-22 07:33:04.452004: Epoch time: 17.76 s +2024-11-22 07:33:05.335385: +2024-11-22 07:33:05.335622: Epoch 3831 +2024-11-22 07:33:05.335734: Current learning rate: 0.00556 +2024-11-22 07:33:24.383145: train_loss -0.7929 +2024-11-22 07:33:24.383394: val_loss -0.7299 +2024-11-22 07:33:24.383525: Pseudo dice [0.8315] +2024-11-22 07:33:24.383608: Epoch time: 19.05 s +2024-11-22 07:33:25.375495: +2024-11-22 07:33:25.375737: Epoch 3832 +2024-11-22 07:33:25.375850: Current learning rate: 0.00556 +2024-11-22 07:33:44.303281: train_loss -0.7808 +2024-11-22 07:33:44.303540: val_loss -0.7454 +2024-11-22 07:33:44.303619: Pseudo dice [0.824] +2024-11-22 07:33:44.303711: Epoch time: 18.93 s +2024-11-22 07:33:45.216891: +2024-11-22 07:33:45.217107: Epoch 3833 +2024-11-22 07:33:45.217219: Current learning rate: 0.00556 +2024-11-22 07:34:03.768493: train_loss -0.7891 +2024-11-22 07:34:03.768767: val_loss -0.7551 +2024-11-22 07:34:03.768855: Pseudo dice [0.8317] +2024-11-22 07:34:03.768940: Epoch time: 18.55 s +2024-11-22 07:34:04.656535: +2024-11-22 07:34:04.656791: Epoch 3834 +2024-11-22 07:34:04.656902: Current learning rate: 0.00556 +2024-11-22 07:34:25.146532: train_loss -0.7853 +2024-11-22 07:34:25.146746: val_loss -0.7587 +2024-11-22 07:34:25.146821: Pseudo dice [0.8415] +2024-11-22 07:34:25.146898: Epoch time: 20.49 s +2024-11-22 07:34:26.065418: +2024-11-22 07:34:26.065630: Epoch 3835 +2024-11-22 07:34:26.065743: Current learning rate: 0.00556 +2024-11-22 07:34:45.042791: train_loss -0.7717 +2024-11-22 07:34:45.043013: val_loss -0.7382 +2024-11-22 07:34:45.043088: Pseudo dice [0.8254] +2024-11-22 07:34:45.043163: Epoch time: 18.98 s +2024-11-22 07:34:45.985687: +2024-11-22 07:34:45.985913: Epoch 3836 +2024-11-22 07:34:45.986037: Current learning rate: 0.00556 +2024-11-22 07:35:04.586758: train_loss -0.7771 +2024-11-22 07:35:04.587011: val_loss -0.7387 +2024-11-22 07:35:04.587090: Pseudo dice [0.8372] +2024-11-22 07:35:04.587173: Epoch time: 18.6 s +2024-11-22 07:35:05.477172: +2024-11-22 07:35:05.477409: Epoch 3837 +2024-11-22 07:35:05.477524: Current learning rate: 0.00556 +2024-11-22 07:35:24.599607: train_loss -0.7839 +2024-11-22 07:35:24.600872: val_loss -0.7525 +2024-11-22 07:35:24.600954: Pseudo dice [0.8399] +2024-11-22 07:35:24.601037: Epoch time: 19.12 s +2024-11-22 07:35:25.481087: +2024-11-22 07:35:25.481302: Epoch 3838 +2024-11-22 07:35:25.481417: Current learning rate: 0.00555 +2024-11-22 07:35:45.591563: train_loss -0.7776 +2024-11-22 07:35:45.591793: val_loss -0.7649 +2024-11-22 07:35:45.591871: Pseudo dice [0.8333] +2024-11-22 07:35:45.591947: Epoch time: 20.11 s +2024-11-22 07:35:46.481412: +2024-11-22 07:35:46.481638: Epoch 3839 +2024-11-22 07:35:46.481749: Current learning rate: 0.00555 +2024-11-22 07:36:06.545139: train_loss -0.7801 +2024-11-22 07:36:06.545373: val_loss -0.7745 +2024-11-22 07:36:06.546968: Pseudo dice [0.8273] +2024-11-22 07:36:06.547060: Epoch time: 20.06 s +2024-11-22 07:36:07.799024: +2024-11-22 07:36:07.799212: Epoch 3840 +2024-11-22 07:36:07.799320: Current learning rate: 0.00555 +2024-11-22 07:36:26.297129: train_loss -0.7893 +2024-11-22 07:36:26.297395: val_loss -0.7392 +2024-11-22 07:36:26.299701: Pseudo dice [0.8568] +2024-11-22 07:36:26.299804: Epoch time: 18.5 s +2024-11-22 07:36:27.295891: +2024-11-22 07:36:27.296122: Epoch 3841 +2024-11-22 07:36:27.296240: Current learning rate: 0.00555 +2024-11-22 07:36:46.601322: train_loss -0.7866 +2024-11-22 07:36:46.601526: val_loss -0.7605 +2024-11-22 07:36:46.601598: Pseudo dice [0.8219] +2024-11-22 07:36:46.601672: Epoch time: 19.31 s +2024-11-22 07:36:47.480299: +2024-11-22 07:36:47.480531: Epoch 3842 +2024-11-22 07:36:47.480642: Current learning rate: 0.00555 +2024-11-22 07:37:06.068603: train_loss -0.7959 +2024-11-22 07:37:06.068823: val_loss -0.7338 +2024-11-22 07:37:06.068897: Pseudo dice [0.8316] +2024-11-22 07:37:06.069009: Epoch time: 18.59 s +2024-11-22 07:37:06.948476: +2024-11-22 07:37:06.948690: Epoch 3843 +2024-11-22 07:37:06.948801: Current learning rate: 0.00555 +2024-11-22 07:37:25.559574: train_loss -0.7933 +2024-11-22 07:37:25.559805: val_loss -0.7395 +2024-11-22 07:37:25.559884: Pseudo dice [0.8473] +2024-11-22 07:37:25.559965: Epoch time: 18.61 s +2024-11-22 07:37:26.446774: +2024-11-22 07:37:26.446981: Epoch 3844 +2024-11-22 07:37:26.447097: Current learning rate: 0.00555 +2024-11-22 07:37:45.570943: train_loss -0.789 +2024-11-22 07:37:45.571189: val_loss -0.7417 +2024-11-22 07:37:45.571306: Pseudo dice [0.8469] +2024-11-22 07:37:45.571435: Epoch time: 19.13 s +2024-11-22 07:37:46.464169: +2024-11-22 07:37:46.464427: Epoch 3845 +2024-11-22 07:37:46.464539: Current learning rate: 0.00555 +2024-11-22 07:38:05.143613: train_loss -0.7961 +2024-11-22 07:38:05.143849: val_loss -0.7403 +2024-11-22 07:38:05.143940: Pseudo dice [0.8579] +2024-11-22 07:38:05.144032: Epoch time: 18.68 s +2024-11-22 07:38:06.105845: +2024-11-22 07:38:06.106140: Epoch 3846 +2024-11-22 07:38:06.106257: Current learning rate: 0.00554 +2024-11-22 07:38:23.091120: train_loss -0.8001 +2024-11-22 07:38:23.091340: val_loss -0.759 +2024-11-22 07:38:23.091417: Pseudo dice [0.8634] +2024-11-22 07:38:23.091492: Epoch time: 16.99 s +2024-11-22 07:38:23.976303: +2024-11-22 07:38:23.976534: Epoch 3847 +2024-11-22 07:38:23.976640: Current learning rate: 0.00554 +2024-11-22 07:38:41.858284: train_loss -0.7991 +2024-11-22 07:38:41.858503: val_loss -0.765 +2024-11-22 07:38:41.858581: Pseudo dice [0.8494] +2024-11-22 07:38:41.858706: Epoch time: 17.88 s +2024-11-22 07:38:42.747734: +2024-11-22 07:38:42.747981: Epoch 3848 +2024-11-22 07:38:42.748135: Current learning rate: 0.00554 +2024-11-22 07:39:01.448404: train_loss -0.7909 +2024-11-22 07:39:01.448627: val_loss -0.7628 +2024-11-22 07:39:01.448701: Pseudo dice [0.8501] +2024-11-22 07:39:01.448778: Epoch time: 18.7 s +2024-11-22 07:39:02.337720: +2024-11-22 07:39:02.338009: Epoch 3849 +2024-11-22 07:39:02.338132: Current learning rate: 0.00554 +2024-11-22 07:39:20.324656: train_loss -0.7958 +2024-11-22 07:39:20.324871: val_loss -0.7447 +2024-11-22 07:39:20.324948: Pseudo dice [0.8595] +2024-11-22 07:39:20.325030: Epoch time: 17.99 s +2024-11-22 07:39:21.460356: +2024-11-22 07:39:21.460596: Epoch 3850 +2024-11-22 07:39:21.460715: Current learning rate: 0.00554 +2024-11-22 07:39:40.223117: train_loss -0.7953 +2024-11-22 07:39:40.223357: val_loss -0.7465 +2024-11-22 07:39:40.223433: Pseudo dice [0.846] +2024-11-22 07:39:40.223509: Epoch time: 18.76 s +2024-11-22 07:39:41.102922: +2024-11-22 07:39:41.103137: Epoch 3851 +2024-11-22 07:39:41.103251: Current learning rate: 0.00554 +2024-11-22 07:40:00.173219: train_loss -0.7927 +2024-11-22 07:40:00.173499: val_loss -0.7405 +2024-11-22 07:40:00.173576: Pseudo dice [0.8398] +2024-11-22 07:40:00.173655: Epoch time: 19.07 s +2024-11-22 07:40:01.054394: +2024-11-22 07:40:01.054603: Epoch 3852 +2024-11-22 07:40:01.054715: Current learning rate: 0.00554 +2024-11-22 07:40:19.625626: train_loss -0.7815 +2024-11-22 07:40:19.625849: val_loss -0.7426 +2024-11-22 07:40:19.625924: Pseudo dice [0.8503] +2024-11-22 07:40:19.631167: Epoch time: 18.57 s +2024-11-22 07:40:20.529474: +2024-11-22 07:40:20.529712: Epoch 3853 +2024-11-22 07:40:20.529824: Current learning rate: 0.00554 +2024-11-22 07:40:40.407063: train_loss -0.7913 +2024-11-22 07:40:40.407296: val_loss -0.7399 +2024-11-22 07:40:40.407372: Pseudo dice [0.8296] +2024-11-22 07:40:40.407449: Epoch time: 19.88 s +2024-11-22 07:40:41.299949: +2024-11-22 07:40:41.300174: Epoch 3854 +2024-11-22 07:40:41.300284: Current learning rate: 0.00553 +2024-11-22 07:40:59.560412: train_loss -0.7913 +2024-11-22 07:40:59.560637: val_loss -0.7629 +2024-11-22 07:40:59.560715: Pseudo dice [0.8451] +2024-11-22 07:40:59.560798: Epoch time: 18.26 s +2024-11-22 07:41:00.452661: +2024-11-22 07:41:00.452935: Epoch 3855 +2024-11-22 07:41:00.453053: Current learning rate: 0.00553 +2024-11-22 07:41:19.459292: train_loss -0.7852 +2024-11-22 07:41:19.459545: val_loss -0.7529 +2024-11-22 07:41:19.459619: Pseudo dice [0.8559] +2024-11-22 07:41:19.459702: Epoch time: 19.01 s +2024-11-22 07:41:20.354556: +2024-11-22 07:41:20.354774: Epoch 3856 +2024-11-22 07:41:20.354892: Current learning rate: 0.00553 +2024-11-22 07:41:39.358745: train_loss -0.7949 +2024-11-22 07:41:39.358972: val_loss -0.7238 +2024-11-22 07:41:39.359056: Pseudo dice [0.831] +2024-11-22 07:41:39.359135: Epoch time: 19.01 s +2024-11-22 07:41:40.248033: +2024-11-22 07:41:40.248233: Epoch 3857 +2024-11-22 07:41:40.248343: Current learning rate: 0.00553 +2024-11-22 07:41:59.089296: train_loss -0.7971 +2024-11-22 07:41:59.089519: val_loss -0.7712 +2024-11-22 07:41:59.089594: Pseudo dice [0.8476] +2024-11-22 07:41:59.089671: Epoch time: 18.84 s +2024-11-22 07:41:59.979124: +2024-11-22 07:41:59.979372: Epoch 3858 +2024-11-22 07:41:59.979486: Current learning rate: 0.00553 +2024-11-22 07:42:17.701698: train_loss -0.7872 +2024-11-22 07:42:17.711105: val_loss -0.7053 +2024-11-22 07:42:17.711275: Pseudo dice [0.8062] +2024-11-22 07:42:17.711361: Epoch time: 17.72 s +2024-11-22 07:42:18.605733: +2024-11-22 07:42:18.605950: Epoch 3859 +2024-11-22 07:42:18.606065: Current learning rate: 0.00553 +2024-11-22 07:42:37.231697: train_loss -0.7834 +2024-11-22 07:42:37.231959: val_loss -0.6904 +2024-11-22 07:42:37.232046: Pseudo dice [0.8188] +2024-11-22 07:42:37.232139: Epoch time: 18.63 s +2024-11-22 07:42:38.291028: +2024-11-22 07:42:38.291219: Epoch 3860 +2024-11-22 07:42:38.291332: Current learning rate: 0.00553 +2024-11-22 07:42:56.042249: train_loss -0.7842 +2024-11-22 07:42:56.042463: val_loss -0.7362 +2024-11-22 07:42:56.042541: Pseudo dice [0.8232] +2024-11-22 07:42:56.042623: Epoch time: 17.75 s +2024-11-22 07:42:56.923741: +2024-11-22 07:42:56.923945: Epoch 3861 +2024-11-22 07:42:56.924061: Current learning rate: 0.00553 +2024-11-22 07:43:15.309314: train_loss -0.7877 +2024-11-22 07:43:15.310139: val_loss -0.7711 +2024-11-22 07:43:15.310222: Pseudo dice [0.8517] +2024-11-22 07:43:15.310300: Epoch time: 18.39 s +2024-11-22 07:43:16.606820: +2024-11-22 07:43:16.607032: Epoch 3862 +2024-11-22 07:43:16.607145: Current learning rate: 0.00552 +2024-11-22 07:43:36.210583: train_loss -0.777 +2024-11-22 07:43:36.210828: val_loss -0.7267 +2024-11-22 07:43:36.210904: Pseudo dice [0.8215] +2024-11-22 07:43:36.210984: Epoch time: 19.6 s +2024-11-22 07:43:37.097677: +2024-11-22 07:43:37.097883: Epoch 3863 +2024-11-22 07:43:37.097998: Current learning rate: 0.00552 +2024-11-22 07:43:56.351187: train_loss -0.779 +2024-11-22 07:43:56.351506: val_loss -0.7408 +2024-11-22 07:43:56.351589: Pseudo dice [0.8492] +2024-11-22 07:43:56.351671: Epoch time: 19.25 s +2024-11-22 07:43:57.243790: +2024-11-22 07:43:57.244004: Epoch 3864 +2024-11-22 07:43:57.244111: Current learning rate: 0.00552 +2024-11-22 07:44:16.050378: train_loss -0.7846 +2024-11-22 07:44:16.050585: val_loss -0.7336 +2024-11-22 07:44:16.050660: Pseudo dice [0.8214] +2024-11-22 07:44:16.050739: Epoch time: 18.81 s +2024-11-22 07:44:16.938477: +2024-11-22 07:44:16.938687: Epoch 3865 +2024-11-22 07:44:16.938800: Current learning rate: 0.00552 +2024-11-22 07:44:34.656709: train_loss -0.7877 +2024-11-22 07:44:34.656935: val_loss -0.7439 +2024-11-22 07:44:34.657016: Pseudo dice [0.8561] +2024-11-22 07:44:34.657091: Epoch time: 17.72 s +2024-11-22 07:44:35.714483: +2024-11-22 07:44:35.714715: Epoch 3866 +2024-11-22 07:44:35.714829: Current learning rate: 0.00552 +2024-11-22 07:44:53.745319: train_loss -0.7953 +2024-11-22 07:44:53.750768: val_loss -0.7438 +2024-11-22 07:44:53.750881: Pseudo dice [0.8179] +2024-11-22 07:44:53.750981: Epoch time: 18.03 s +2024-11-22 07:44:54.673763: +2024-11-22 07:44:54.674015: Epoch 3867 +2024-11-22 07:44:54.674132: Current learning rate: 0.00552 +2024-11-22 07:45:14.714698: train_loss -0.7972 +2024-11-22 07:45:14.714948: val_loss -0.7113 +2024-11-22 07:45:14.715030: Pseudo dice [0.8051] +2024-11-22 07:45:14.715108: Epoch time: 20.04 s +2024-11-22 07:45:15.601188: +2024-11-22 07:45:15.601402: Epoch 3868 +2024-11-22 07:45:15.601514: Current learning rate: 0.00552 +2024-11-22 07:45:34.238198: train_loss -0.784 +2024-11-22 07:45:34.238410: val_loss -0.726 +2024-11-22 07:45:34.238487: Pseudo dice [0.8579] +2024-11-22 07:45:34.238564: Epoch time: 18.64 s +2024-11-22 07:45:35.126289: +2024-11-22 07:45:35.126506: Epoch 3869 +2024-11-22 07:45:35.126619: Current learning rate: 0.00552 +2024-11-22 07:45:54.095131: train_loss -0.7791 +2024-11-22 07:45:54.095345: val_loss -0.7538 +2024-11-22 07:45:54.095420: Pseudo dice [0.8503] +2024-11-22 07:45:54.095500: Epoch time: 18.97 s +2024-11-22 07:45:54.983099: +2024-11-22 07:45:54.983300: Epoch 3870 +2024-11-22 07:45:54.983412: Current learning rate: 0.00552 +2024-11-22 07:46:13.891472: train_loss -0.7815 +2024-11-22 07:46:13.891722: val_loss -0.7371 +2024-11-22 07:46:13.891877: Pseudo dice [0.8235] +2024-11-22 07:46:13.891963: Epoch time: 18.91 s +2024-11-22 07:46:14.788919: +2024-11-22 07:46:14.789202: Epoch 3871 +2024-11-22 07:46:14.789320: Current learning rate: 0.00551 +2024-11-22 07:46:33.425943: train_loss -0.7859 +2024-11-22 07:46:33.426164: val_loss -0.7535 +2024-11-22 07:46:33.426240: Pseudo dice [0.8409] +2024-11-22 07:46:33.426319: Epoch time: 18.64 s +2024-11-22 07:46:34.310500: +2024-11-22 07:46:34.310708: Epoch 3872 +2024-11-22 07:46:34.310821: Current learning rate: 0.00551 +2024-11-22 07:46:52.041379: train_loss -0.7945 +2024-11-22 07:46:52.041599: val_loss -0.7529 +2024-11-22 07:46:52.041674: Pseudo dice [0.8557] +2024-11-22 07:46:52.041751: Epoch time: 17.73 s +2024-11-22 07:46:52.931812: +2024-11-22 07:46:52.932040: Epoch 3873 +2024-11-22 07:46:52.932158: Current learning rate: 0.00551 +2024-11-22 07:47:11.051895: train_loss -0.7862 +2024-11-22 07:47:11.052132: val_loss -0.7574 +2024-11-22 07:47:11.052210: Pseudo dice [0.853] +2024-11-22 07:47:11.052297: Epoch time: 18.12 s +2024-11-22 07:47:12.379997: +2024-11-22 07:47:12.380202: Epoch 3874 +2024-11-22 07:47:12.380310: Current learning rate: 0.00551 +2024-11-22 07:47:30.881494: train_loss -0.778 +2024-11-22 07:47:30.881737: val_loss -0.745 +2024-11-22 07:47:30.881831: Pseudo dice [0.8368] +2024-11-22 07:47:30.881914: Epoch time: 18.5 s +2024-11-22 07:47:31.769714: +2024-11-22 07:47:31.769953: Epoch 3875 +2024-11-22 07:47:31.770073: Current learning rate: 0.00551 +2024-11-22 07:47:50.145761: train_loss -0.7892 +2024-11-22 07:47:50.145983: val_loss -0.7658 +2024-11-22 07:47:50.146064: Pseudo dice [0.828] +2024-11-22 07:47:50.146139: Epoch time: 18.38 s +2024-11-22 07:47:51.190940: +2024-11-22 07:47:51.191160: Epoch 3876 +2024-11-22 07:47:51.191271: Current learning rate: 0.00551 +2024-11-22 07:48:09.176816: train_loss -0.7621 +2024-11-22 07:48:09.177033: val_loss -0.7434 +2024-11-22 07:48:09.177109: Pseudo dice [0.8338] +2024-11-22 07:48:09.177185: Epoch time: 17.99 s +2024-11-22 07:48:10.065458: +2024-11-22 07:48:10.065675: Epoch 3877 +2024-11-22 07:48:10.065795: Current learning rate: 0.00551 +2024-11-22 07:48:29.099758: train_loss -0.781 +2024-11-22 07:48:29.100026: val_loss -0.7297 +2024-11-22 07:48:29.100137: Pseudo dice [0.8151] +2024-11-22 07:48:29.100539: Epoch time: 19.04 s +2024-11-22 07:48:29.987792: +2024-11-22 07:48:29.988017: Epoch 3878 +2024-11-22 07:48:29.988135: Current learning rate: 0.00551 +2024-11-22 07:48:49.165767: train_loss -0.7797 +2024-11-22 07:48:49.166008: val_loss -0.7304 +2024-11-22 07:48:49.166084: Pseudo dice [0.8319] +2024-11-22 07:48:49.166160: Epoch time: 19.18 s +2024-11-22 07:48:50.051072: +2024-11-22 07:48:50.051265: Epoch 3879 +2024-11-22 07:48:50.051373: Current learning rate: 0.0055 +2024-11-22 07:49:08.488883: train_loss -0.7935 +2024-11-22 07:49:08.489115: val_loss -0.7381 +2024-11-22 07:49:08.489196: Pseudo dice [0.8667] +2024-11-22 07:49:08.489277: Epoch time: 18.44 s +2024-11-22 07:49:09.380247: +2024-11-22 07:49:09.380463: Epoch 3880 +2024-11-22 07:49:09.380579: Current learning rate: 0.0055 +2024-11-22 07:49:28.496750: train_loss -0.7828 +2024-11-22 07:49:28.496973: val_loss -0.7614 +2024-11-22 07:49:28.497055: Pseudo dice [0.8281] +2024-11-22 07:49:28.497134: Epoch time: 19.12 s +2024-11-22 07:49:29.385261: +2024-11-22 07:49:29.385523: Epoch 3881 +2024-11-22 07:49:29.385639: Current learning rate: 0.0055 +2024-11-22 07:49:48.418412: train_loss -0.7859 +2024-11-22 07:49:48.418690: val_loss -0.707 +2024-11-22 07:49:48.418775: Pseudo dice [0.8479] +2024-11-22 07:49:48.418895: Epoch time: 19.03 s +2024-11-22 07:49:49.343227: +2024-11-22 07:49:49.343436: Epoch 3882 +2024-11-22 07:49:49.343556: Current learning rate: 0.0055 +2024-11-22 07:50:08.105942: train_loss -0.7904 +2024-11-22 07:50:08.106165: val_loss -0.7575 +2024-11-22 07:50:08.106241: Pseudo dice [0.8564] +2024-11-22 07:50:08.106397: Epoch time: 18.76 s +2024-11-22 07:50:08.995450: +2024-11-22 07:50:08.995654: Epoch 3883 +2024-11-22 07:50:08.995769: Current learning rate: 0.0055 +2024-11-22 07:50:27.246695: train_loss -0.781 +2024-11-22 07:50:27.246920: val_loss -0.7375 +2024-11-22 07:50:27.247003: Pseudo dice [0.8412] +2024-11-22 07:50:27.247080: Epoch time: 18.25 s +2024-11-22 07:50:28.131739: +2024-11-22 07:50:28.132010: Epoch 3884 +2024-11-22 07:50:28.132129: Current learning rate: 0.0055 +2024-11-22 07:50:46.488120: train_loss -0.7789 +2024-11-22 07:50:46.490520: val_loss -0.743 +2024-11-22 07:50:46.490636: Pseudo dice [0.8543] +2024-11-22 07:50:46.490717: Epoch time: 18.36 s +2024-11-22 07:50:47.834684: +2024-11-22 07:50:47.834906: Epoch 3885 +2024-11-22 07:50:47.835022: Current learning rate: 0.0055 +2024-11-22 07:51:06.412670: train_loss -0.7799 +2024-11-22 07:51:06.412941: val_loss -0.7191 +2024-11-22 07:51:06.413028: Pseudo dice [0.8374] +2024-11-22 07:51:06.413116: Epoch time: 18.58 s +2024-11-22 07:51:07.294630: +2024-11-22 07:51:07.294837: Epoch 3886 +2024-11-22 07:51:07.294946: Current learning rate: 0.0055 +2024-11-22 07:51:26.633335: train_loss -0.7767 +2024-11-22 07:51:26.633549: val_loss -0.7511 +2024-11-22 07:51:26.633625: Pseudo dice [0.8565] +2024-11-22 07:51:26.633703: Epoch time: 19.34 s +2024-11-22 07:51:27.517880: +2024-11-22 07:51:27.518101: Epoch 3887 +2024-11-22 07:51:27.518214: Current learning rate: 0.00549 +2024-11-22 07:51:45.677519: train_loss -0.8003 +2024-11-22 07:51:45.677750: val_loss -0.6968 +2024-11-22 07:51:45.677826: Pseudo dice [0.8312] +2024-11-22 07:51:45.677903: Epoch time: 18.16 s +2024-11-22 07:51:46.561076: +2024-11-22 07:51:46.561335: Epoch 3888 +2024-11-22 07:51:46.561455: Current learning rate: 0.00549 +2024-11-22 07:52:04.425364: train_loss -0.7954 +2024-11-22 07:52:04.425603: val_loss -0.7456 +2024-11-22 07:52:04.425681: Pseudo dice [0.8361] +2024-11-22 07:52:04.425766: Epoch time: 17.87 s +2024-11-22 07:52:05.319511: +2024-11-22 07:52:05.319782: Epoch 3889 +2024-11-22 07:52:05.319896: Current learning rate: 0.00549 +2024-11-22 07:52:23.630197: train_loss -0.7847 +2024-11-22 07:52:23.630457: val_loss -0.7269 +2024-11-22 07:52:23.630545: Pseudo dice [0.8141] +2024-11-22 07:52:23.630650: Epoch time: 18.31 s +2024-11-22 07:52:24.516763: +2024-11-22 07:52:24.517038: Epoch 3890 +2024-11-22 07:52:24.517147: Current learning rate: 0.00549 +2024-11-22 07:52:43.201594: train_loss -0.7887 +2024-11-22 07:52:43.201831: val_loss -0.7405 +2024-11-22 07:52:43.201913: Pseudo dice [0.8425] +2024-11-22 07:52:43.201988: Epoch time: 18.69 s +2024-11-22 07:52:44.084321: +2024-11-22 07:52:44.084542: Epoch 3891 +2024-11-22 07:52:44.084654: Current learning rate: 0.00549 +2024-11-22 07:53:03.212086: train_loss -0.794 +2024-11-22 07:53:03.212308: val_loss -0.7736 +2024-11-22 07:53:03.212401: Pseudo dice [0.8347] +2024-11-22 07:53:03.212539: Epoch time: 19.13 s +2024-11-22 07:53:04.098547: +2024-11-22 07:53:04.098765: Epoch 3892 +2024-11-22 07:53:04.098876: Current learning rate: 0.00549 +2024-11-22 07:53:22.885517: train_loss -0.781 +2024-11-22 07:53:22.885771: val_loss -0.7537 +2024-11-22 07:53:22.885850: Pseudo dice [0.8271] +2024-11-22 07:53:22.885937: Epoch time: 18.79 s +2024-11-22 07:53:23.775757: +2024-11-22 07:53:23.776082: Epoch 3893 +2024-11-22 07:53:23.776201: Current learning rate: 0.00549 +2024-11-22 07:53:43.187632: train_loss -0.7802 +2024-11-22 07:53:43.187846: val_loss -0.7316 +2024-11-22 07:53:43.187919: Pseudo dice [0.8479] +2024-11-22 07:53:43.188002: Epoch time: 19.41 s +2024-11-22 07:53:44.072954: +2024-11-22 07:53:44.073207: Epoch 3894 +2024-11-22 07:53:44.073318: Current learning rate: 0.00549 +2024-11-22 07:54:03.378530: train_loss -0.7815 +2024-11-22 07:54:03.378754: val_loss -0.7442 +2024-11-22 07:54:03.378831: Pseudo dice [0.8245] +2024-11-22 07:54:03.378911: Epoch time: 19.31 s +2024-11-22 07:54:04.271742: +2024-11-22 07:54:04.271955: Epoch 3895 +2024-11-22 07:54:04.272074: Current learning rate: 0.00549 +2024-11-22 07:54:22.927040: train_loss -0.7844 +2024-11-22 07:54:22.927260: val_loss -0.7587 +2024-11-22 07:54:22.927334: Pseudo dice [0.8568] +2024-11-22 07:54:22.927407: Epoch time: 18.66 s +2024-11-22 07:54:23.808395: +2024-11-22 07:54:23.808609: Epoch 3896 +2024-11-22 07:54:23.808712: Current learning rate: 0.00548 +2024-11-22 07:54:42.913485: train_loss -0.7981 +2024-11-22 07:54:42.914553: val_loss -0.7579 +2024-11-22 07:54:42.914635: Pseudo dice [0.8496] +2024-11-22 07:54:42.914717: Epoch time: 19.11 s +2024-11-22 07:54:44.266383: +2024-11-22 07:54:44.266610: Epoch 3897 +2024-11-22 07:54:44.266727: Current learning rate: 0.00548 +2024-11-22 07:55:01.983377: train_loss -0.791 +2024-11-22 07:55:01.983603: val_loss -0.7441 +2024-11-22 07:55:01.983685: Pseudo dice [0.8345] +2024-11-22 07:55:01.983767: Epoch time: 17.72 s +2024-11-22 07:55:02.875170: +2024-11-22 07:55:02.875381: Epoch 3898 +2024-11-22 07:55:02.875491: Current learning rate: 0.00548 +2024-11-22 07:55:22.241574: train_loss -0.7899 +2024-11-22 07:55:22.242060: val_loss -0.7631 +2024-11-22 07:55:22.242158: Pseudo dice [0.8658] +2024-11-22 07:55:22.242236: Epoch time: 19.37 s +2024-11-22 07:55:23.138110: +2024-11-22 07:55:23.138328: Epoch 3899 +2024-11-22 07:55:23.138435: Current learning rate: 0.00548 +2024-11-22 07:55:40.861759: train_loss -0.7938 +2024-11-22 07:55:40.861978: val_loss -0.7469 +2024-11-22 07:55:40.862063: Pseudo dice [0.8508] +2024-11-22 07:55:40.862197: Epoch time: 17.72 s +2024-11-22 07:55:42.048702: +2024-11-22 07:55:42.048922: Epoch 3900 +2024-11-22 07:55:42.049043: Current learning rate: 0.00548 +2024-11-22 07:56:00.707174: train_loss -0.7926 +2024-11-22 07:56:00.708164: val_loss -0.7687 +2024-11-22 07:56:00.708243: Pseudo dice [0.8583] +2024-11-22 07:56:00.708326: Epoch time: 18.66 s +2024-11-22 07:56:01.600311: +2024-11-22 07:56:01.600654: Epoch 3901 +2024-11-22 07:56:01.600776: Current learning rate: 0.00548 +2024-11-22 07:56:21.141468: train_loss -0.7825 +2024-11-22 07:56:21.141693: val_loss -0.7291 +2024-11-22 07:56:21.141771: Pseudo dice [0.845] +2024-11-22 07:56:21.141847: Epoch time: 19.54 s +2024-11-22 07:56:22.030959: +2024-11-22 07:56:22.031195: Epoch 3902 +2024-11-22 07:56:22.031308: Current learning rate: 0.00548 +2024-11-22 07:56:41.326202: train_loss -0.7937 +2024-11-22 07:56:41.326421: val_loss -0.731 +2024-11-22 07:56:41.326493: Pseudo dice [0.8371] +2024-11-22 07:56:41.326567: Epoch time: 19.3 s +2024-11-22 07:56:42.199708: +2024-11-22 07:56:42.199926: Epoch 3903 +2024-11-22 07:56:42.200044: Current learning rate: 0.00548 +2024-11-22 07:57:00.905456: train_loss -0.7877 +2024-11-22 07:57:00.905695: val_loss -0.7402 +2024-11-22 07:57:00.905772: Pseudo dice [0.8446] +2024-11-22 07:57:00.906141: Epoch time: 18.71 s +2024-11-22 07:57:01.800528: +2024-11-22 07:57:01.800754: Epoch 3904 +2024-11-22 07:57:01.800866: Current learning rate: 0.00547 +2024-11-22 07:57:20.986814: train_loss -0.7896 +2024-11-22 07:57:20.987041: val_loss -0.7347 +2024-11-22 07:57:20.987120: Pseudo dice [0.8555] +2024-11-22 07:57:20.987199: Epoch time: 19.19 s +2024-11-22 07:57:21.874892: +2024-11-22 07:57:21.875095: Epoch 3905 +2024-11-22 07:57:21.875210: Current learning rate: 0.00547 +2024-11-22 07:57:40.294597: train_loss -0.7909 +2024-11-22 07:57:40.294813: val_loss -0.7391 +2024-11-22 07:57:40.294888: Pseudo dice [0.8169] +2024-11-22 07:57:40.294963: Epoch time: 18.42 s +2024-11-22 07:57:41.181111: +2024-11-22 07:57:41.181361: Epoch 3906 +2024-11-22 07:57:41.181476: Current learning rate: 0.00547 +2024-11-22 07:57:59.411026: train_loss -0.7884 +2024-11-22 07:57:59.411246: val_loss -0.721 +2024-11-22 07:57:59.411320: Pseudo dice [0.8462] +2024-11-22 07:57:59.411397: Epoch time: 18.23 s +2024-11-22 07:58:00.294392: +2024-11-22 07:58:00.294621: Epoch 3907 +2024-11-22 07:58:00.294740: Current learning rate: 0.00547 +2024-11-22 07:58:19.653498: train_loss -0.7861 +2024-11-22 07:58:19.653744: val_loss -0.7311 +2024-11-22 07:58:19.653823: Pseudo dice [0.8496] +2024-11-22 07:58:19.653902: Epoch time: 19.36 s +2024-11-22 07:58:20.898901: +2024-11-22 07:58:20.899132: Epoch 3908 +2024-11-22 07:58:20.899258: Current learning rate: 0.00547 +2024-11-22 07:58:40.046740: train_loss -0.7882 +2024-11-22 07:58:40.046962: val_loss -0.7674 +2024-11-22 07:58:40.047044: Pseudo dice [0.8622] +2024-11-22 07:58:40.047122: Epoch time: 19.15 s +2024-11-22 07:58:40.928884: +2024-11-22 07:58:40.929100: Epoch 3909 +2024-11-22 07:58:40.929212: Current learning rate: 0.00547 +2024-11-22 07:59:00.205905: train_loss -0.7994 +2024-11-22 07:59:00.206151: val_loss -0.7256 +2024-11-22 07:59:00.206227: Pseudo dice [0.8583] +2024-11-22 07:59:00.206305: Epoch time: 19.28 s +2024-11-22 07:59:01.197204: +2024-11-22 07:59:01.197417: Epoch 3910 +2024-11-22 07:59:01.197528: Current learning rate: 0.00547 +2024-11-22 07:59:20.300798: train_loss -0.7945 +2024-11-22 07:59:20.301026: val_loss -0.7218 +2024-11-22 07:59:20.301105: Pseudo dice [0.8323] +2024-11-22 07:59:20.301182: Epoch time: 19.1 s +2024-11-22 07:59:21.254997: +2024-11-22 07:59:21.255211: Epoch 3911 +2024-11-22 07:59:21.255328: Current learning rate: 0.00547 +2024-11-22 07:59:38.904854: train_loss -0.7956 +2024-11-22 07:59:38.905100: val_loss -0.7282 +2024-11-22 07:59:38.905180: Pseudo dice [0.8505] +2024-11-22 07:59:38.905265: Epoch time: 17.65 s +2024-11-22 07:59:39.781319: +2024-11-22 07:59:39.781533: Epoch 3912 +2024-11-22 07:59:39.781641: Current learning rate: 0.00546 +2024-11-22 07:59:58.890059: train_loss -0.8004 +2024-11-22 07:59:58.890264: val_loss -0.7506 +2024-11-22 07:59:58.890379: Pseudo dice [0.8156] +2024-11-22 07:59:58.890459: Epoch time: 19.11 s +2024-11-22 07:59:59.775003: +2024-11-22 07:59:59.775248: Epoch 3913 +2024-11-22 07:59:59.775369: Current learning rate: 0.00546 +2024-11-22 08:00:17.893114: train_loss -0.8023 +2024-11-22 08:00:17.893338: val_loss -0.7746 +2024-11-22 08:00:17.893411: Pseudo dice [0.8753] +2024-11-22 08:00:17.893495: Epoch time: 18.12 s +2024-11-22 08:00:18.785917: +2024-11-22 08:00:18.786140: Epoch 3914 +2024-11-22 08:00:18.786253: Current learning rate: 0.00546 +2024-11-22 08:00:37.669724: train_loss -0.7975 +2024-11-22 08:00:37.670001: val_loss -0.7515 +2024-11-22 08:00:37.670082: Pseudo dice [0.8406] +2024-11-22 08:00:37.670161: Epoch time: 18.88 s +2024-11-22 08:00:38.595210: +2024-11-22 08:00:38.595410: Epoch 3915 +2024-11-22 08:00:38.595521: Current learning rate: 0.00546 +2024-11-22 08:00:57.041237: train_loss -0.796 +2024-11-22 08:00:57.041486: val_loss -0.776 +2024-11-22 08:00:57.041561: Pseudo dice [0.8809] +2024-11-22 08:00:57.041638: Epoch time: 18.45 s +2024-11-22 08:00:57.041698: Yayy! New best EMA pseudo Dice: 0.8489 +2024-11-22 08:00:58.194403: +2024-11-22 08:00:58.194710: Epoch 3916 +2024-11-22 08:00:58.194822: Current learning rate: 0.00546 +2024-11-22 08:01:16.536503: train_loss -0.7978 +2024-11-22 08:01:16.536726: val_loss -0.7344 +2024-11-22 08:01:16.536809: Pseudo dice [0.8212] +2024-11-22 08:01:16.536947: Epoch time: 18.34 s +2024-11-22 08:01:17.434552: +2024-11-22 08:01:17.434765: Epoch 3917 +2024-11-22 08:01:17.434878: Current learning rate: 0.00546 +2024-11-22 08:01:36.515711: train_loss -0.791 +2024-11-22 08:01:36.515927: val_loss -0.7725 +2024-11-22 08:01:36.516013: Pseudo dice [0.8407] +2024-11-22 08:01:36.516093: Epoch time: 19.08 s +2024-11-22 08:01:37.396062: +2024-11-22 08:01:37.396272: Epoch 3918 +2024-11-22 08:01:37.396381: Current learning rate: 0.00546 +2024-11-22 08:01:56.380737: train_loss -0.7894 +2024-11-22 08:01:56.380983: val_loss -0.7515 +2024-11-22 08:01:56.381074: Pseudo dice [0.8393] +2024-11-22 08:01:56.381186: Epoch time: 18.99 s +2024-11-22 08:01:57.681675: +2024-11-22 08:01:57.681898: Epoch 3919 +2024-11-22 08:01:57.682012: Current learning rate: 0.00546 +2024-11-22 08:02:16.564914: train_loss -0.7945 +2024-11-22 08:02:16.565168: val_loss -0.7615 +2024-11-22 08:02:16.565244: Pseudo dice [0.8526] +2024-11-22 08:02:16.565327: Epoch time: 18.88 s +2024-11-22 08:02:17.490390: +2024-11-22 08:02:17.490591: Epoch 3920 +2024-11-22 08:02:17.490699: Current learning rate: 0.00546 +2024-11-22 08:02:35.792719: train_loss -0.8018 +2024-11-22 08:02:35.792926: val_loss -0.7696 +2024-11-22 08:02:35.793004: Pseudo dice [0.8474] +2024-11-22 08:02:35.793082: Epoch time: 18.3 s +2024-11-22 08:02:36.658420: +2024-11-22 08:02:36.658645: Epoch 3921 +2024-11-22 08:02:36.658759: Current learning rate: 0.00545 +2024-11-22 08:02:55.374074: train_loss -0.7968 +2024-11-22 08:02:55.374274: val_loss -0.7487 +2024-11-22 08:02:55.374345: Pseudo dice [0.8246] +2024-11-22 08:02:55.374419: Epoch time: 18.72 s +2024-11-22 08:02:56.302986: +2024-11-22 08:02:56.303208: Epoch 3922 +2024-11-22 08:02:56.303322: Current learning rate: 0.00545 +2024-11-22 08:03:15.026834: train_loss -0.7986 +2024-11-22 08:03:15.027086: val_loss -0.751 +2024-11-22 08:03:15.027162: Pseudo dice [0.8379] +2024-11-22 08:03:15.027244: Epoch time: 18.72 s +2024-11-22 08:03:15.921096: +2024-11-22 08:03:15.921327: Epoch 3923 +2024-11-22 08:03:15.921437: Current learning rate: 0.00545 +2024-11-22 08:03:35.400927: train_loss -0.7939 +2024-11-22 08:03:35.401148: val_loss -0.7442 +2024-11-22 08:03:35.401222: Pseudo dice [0.8186] +2024-11-22 08:03:35.401297: Epoch time: 19.48 s +2024-11-22 08:03:36.299403: +2024-11-22 08:03:36.299636: Epoch 3924 +2024-11-22 08:03:36.299747: Current learning rate: 0.00545 +2024-11-22 08:03:55.914062: train_loss -0.791 +2024-11-22 08:03:55.914276: val_loss -0.7688 +2024-11-22 08:03:55.914351: Pseudo dice [0.8363] +2024-11-22 08:03:55.914427: Epoch time: 19.62 s +2024-11-22 08:03:56.858450: +2024-11-22 08:03:56.858664: Epoch 3925 +2024-11-22 08:03:56.858774: Current learning rate: 0.00545 +2024-11-22 08:04:15.039538: train_loss -0.7869 +2024-11-22 08:04:15.039764: val_loss -0.7648 +2024-11-22 08:04:15.039837: Pseudo dice [0.8426] +2024-11-22 08:04:15.039913: Epoch time: 18.18 s +2024-11-22 08:04:15.915504: +2024-11-22 08:04:15.915710: Epoch 3926 +2024-11-22 08:04:15.915823: Current learning rate: 0.00545 +2024-11-22 08:04:34.847084: train_loss -0.7868 +2024-11-22 08:04:34.849105: val_loss -0.7277 +2024-11-22 08:04:34.849209: Pseudo dice [0.8583] +2024-11-22 08:04:34.849293: Epoch time: 18.93 s +2024-11-22 08:04:35.755374: +2024-11-22 08:04:35.755579: Epoch 3927 +2024-11-22 08:04:35.755692: Current learning rate: 0.00545 +2024-11-22 08:04:53.184393: train_loss -0.7891 +2024-11-22 08:04:53.184612: val_loss -0.7627 +2024-11-22 08:04:53.184690: Pseudo dice [0.8418] +2024-11-22 08:04:53.184767: Epoch time: 17.43 s +2024-11-22 08:04:54.074530: +2024-11-22 08:04:54.074834: Epoch 3928 +2024-11-22 08:04:54.074950: Current learning rate: 0.00545 +2024-11-22 08:05:12.390264: train_loss -0.785 +2024-11-22 08:05:12.390479: val_loss -0.7651 +2024-11-22 08:05:12.395707: Pseudo dice [0.8498] +2024-11-22 08:05:12.395863: Epoch time: 18.32 s +2024-11-22 08:05:13.606867: +2024-11-22 08:05:13.607064: Epoch 3929 +2024-11-22 08:05:13.607180: Current learning rate: 0.00544 +2024-11-22 08:05:32.546622: train_loss -0.7691 +2024-11-22 08:05:32.549233: val_loss -0.7515 +2024-11-22 08:05:32.549377: Pseudo dice [0.8154] +2024-11-22 08:05:32.549459: Epoch time: 18.94 s +2024-11-22 08:05:33.859721: +2024-11-22 08:05:33.859952: Epoch 3930 +2024-11-22 08:05:33.860075: Current learning rate: 0.00544 +2024-11-22 08:05:53.492214: train_loss -0.7839 +2024-11-22 08:05:53.492474: val_loss -0.7334 +2024-11-22 08:05:53.492550: Pseudo dice [0.8385] +2024-11-22 08:05:53.492635: Epoch time: 19.63 s +2024-11-22 08:05:54.399375: +2024-11-22 08:05:54.399647: Epoch 3931 +2024-11-22 08:05:54.399760: Current learning rate: 0.00544 +2024-11-22 08:06:13.756969: train_loss -0.7772 +2024-11-22 08:06:13.757186: val_loss -0.7541 +2024-11-22 08:06:13.757263: Pseudo dice [0.8327] +2024-11-22 08:06:13.757340: Epoch time: 19.36 s +2024-11-22 08:06:14.641872: +2024-11-22 08:06:14.642094: Epoch 3932 +2024-11-22 08:06:14.642209: Current learning rate: 0.00544 +2024-11-22 08:06:34.274733: train_loss -0.7826 +2024-11-22 08:06:34.274955: val_loss -0.7471 +2024-11-22 08:06:34.275039: Pseudo dice [0.8584] +2024-11-22 08:06:34.275117: Epoch time: 19.63 s +2024-11-22 08:06:35.232296: +2024-11-22 08:06:35.232516: Epoch 3933 +2024-11-22 08:06:35.232631: Current learning rate: 0.00544 +2024-11-22 08:06:53.142411: train_loss -0.7836 +2024-11-22 08:06:53.142640: val_loss -0.7405 +2024-11-22 08:06:53.144942: Pseudo dice [0.841] +2024-11-22 08:06:53.145056: Epoch time: 17.91 s +2024-11-22 08:06:54.098035: +2024-11-22 08:06:54.098245: Epoch 3934 +2024-11-22 08:06:54.098353: Current learning rate: 0.00544 +2024-11-22 08:07:13.803187: train_loss -0.7845 +2024-11-22 08:07:13.803436: val_loss -0.7271 +2024-11-22 08:07:13.803516: Pseudo dice [0.8244] +2024-11-22 08:07:13.803602: Epoch time: 19.71 s +2024-11-22 08:07:14.703515: +2024-11-22 08:07:14.703728: Epoch 3935 +2024-11-22 08:07:14.703840: Current learning rate: 0.00544 +2024-11-22 08:07:33.176985: train_loss -0.796 +2024-11-22 08:07:33.177209: val_loss -0.7654 +2024-11-22 08:07:33.177292: Pseudo dice [0.8468] +2024-11-22 08:07:33.177373: Epoch time: 18.47 s +2024-11-22 08:07:34.081592: +2024-11-22 08:07:34.081808: Epoch 3936 +2024-11-22 08:07:34.081923: Current learning rate: 0.00544 +2024-11-22 08:07:52.646184: train_loss -0.7942 +2024-11-22 08:07:52.646400: val_loss -0.7505 +2024-11-22 08:07:52.646475: Pseudo dice [0.8561] +2024-11-22 08:07:52.646549: Epoch time: 18.57 s +2024-11-22 08:07:53.536663: +2024-11-22 08:07:53.536869: Epoch 3937 +2024-11-22 08:07:53.536978: Current learning rate: 0.00543 +2024-11-22 08:08:11.870910: train_loss -0.8029 +2024-11-22 08:08:11.871137: val_loss -0.7495 +2024-11-22 08:08:11.871215: Pseudo dice [0.8248] +2024-11-22 08:08:11.871291: Epoch time: 18.34 s +2024-11-22 08:08:12.759796: +2024-11-22 08:08:12.760072: Epoch 3938 +2024-11-22 08:08:12.760184: Current learning rate: 0.00543 +2024-11-22 08:08:32.734726: train_loss -0.8023 +2024-11-22 08:08:32.734970: val_loss -0.7754 +2024-11-22 08:08:32.737283: Pseudo dice [0.8584] +2024-11-22 08:08:32.737388: Epoch time: 19.98 s +2024-11-22 08:08:33.635690: +2024-11-22 08:08:33.635906: Epoch 3939 +2024-11-22 08:08:33.636030: Current learning rate: 0.00543 +2024-11-22 08:08:52.120630: train_loss -0.7977 +2024-11-22 08:08:52.120847: val_loss -0.7404 +2024-11-22 08:08:52.120925: Pseudo dice [0.8513] +2024-11-22 08:08:52.121011: Epoch time: 18.49 s +2024-11-22 08:08:53.012691: +2024-11-22 08:08:53.012944: Epoch 3940 +2024-11-22 08:08:53.013069: Current learning rate: 0.00543 +2024-11-22 08:09:12.282878: train_loss -0.7924 +2024-11-22 08:09:12.283132: val_loss -0.7668 +2024-11-22 08:09:12.283322: Pseudo dice [0.849] +2024-11-22 08:09:12.283398: Epoch time: 19.27 s +2024-11-22 08:09:13.175912: +2024-11-22 08:09:13.177597: Epoch 3941 +2024-11-22 08:09:13.177737: Current learning rate: 0.00543 +2024-11-22 08:09:32.055136: train_loss -0.7927 +2024-11-22 08:09:32.055374: val_loss -0.7854 +2024-11-22 08:09:32.055450: Pseudo dice [0.8593] +2024-11-22 08:09:32.055530: Epoch time: 18.88 s +2024-11-22 08:09:32.941520: +2024-11-22 08:09:32.941741: Epoch 3942 +2024-11-22 08:09:32.941851: Current learning rate: 0.00543 +2024-11-22 08:09:50.742589: train_loss -0.7925 +2024-11-22 08:09:50.742835: val_loss -0.7638 +2024-11-22 08:09:50.743019: Pseudo dice [0.8701] +2024-11-22 08:09:50.743100: Epoch time: 17.8 s +2024-11-22 08:09:51.626050: +2024-11-22 08:09:51.626324: Epoch 3943 +2024-11-22 08:09:51.626435: Current learning rate: 0.00543 +2024-11-22 08:10:11.211225: train_loss -0.7972 +2024-11-22 08:10:11.211449: val_loss -0.726 +2024-11-22 08:10:11.211522: Pseudo dice [0.838] +2024-11-22 08:10:11.211598: Epoch time: 19.59 s +2024-11-22 08:10:12.101716: +2024-11-22 08:10:12.101930: Epoch 3944 +2024-11-22 08:10:12.102047: Current learning rate: 0.00543 +2024-11-22 08:10:30.488888: train_loss -0.7838 +2024-11-22 08:10:30.489112: val_loss -0.7785 +2024-11-22 08:10:30.489190: Pseudo dice [0.8535] +2024-11-22 08:10:30.489272: Epoch time: 18.39 s +2024-11-22 08:10:31.382406: +2024-11-22 08:10:31.382612: Epoch 3945 +2024-11-22 08:10:31.382720: Current learning rate: 0.00543 +2024-11-22 08:10:50.781655: train_loss -0.7924 +2024-11-22 08:10:50.781966: val_loss -0.7296 +2024-11-22 08:10:50.782059: Pseudo dice [0.8318] +2024-11-22 08:10:50.782144: Epoch time: 19.4 s +2024-11-22 08:10:51.678735: +2024-11-22 08:10:51.678962: Epoch 3946 +2024-11-22 08:10:51.679074: Current learning rate: 0.00542 +2024-11-22 08:11:09.678969: train_loss -0.7802 +2024-11-22 08:11:09.679199: val_loss -0.7296 +2024-11-22 08:11:09.679280: Pseudo dice [0.8558] +2024-11-22 08:11:09.679359: Epoch time: 18.0 s +2024-11-22 08:11:10.562413: +2024-11-22 08:11:10.562645: Epoch 3947 +2024-11-22 08:11:10.562758: Current learning rate: 0.00542 +2024-11-22 08:11:28.999369: train_loss -0.7716 +2024-11-22 08:11:28.999589: val_loss -0.7529 +2024-11-22 08:11:28.999706: Pseudo dice [0.8205] +2024-11-22 08:11:28.999788: Epoch time: 18.44 s +2024-11-22 08:11:29.993738: +2024-11-22 08:11:29.993937: Epoch 3948 +2024-11-22 08:11:29.994053: Current learning rate: 0.00542 +2024-11-22 08:11:49.962533: train_loss -0.7717 +2024-11-22 08:11:49.962772: val_loss -0.737 +2024-11-22 08:11:49.962852: Pseudo dice [0.8354] +2024-11-22 08:11:49.962934: Epoch time: 19.97 s +2024-11-22 08:11:50.852510: +2024-11-22 08:11:50.852710: Epoch 3949 +2024-11-22 08:11:50.852820: Current learning rate: 0.00542 +2024-11-22 08:12:10.239910: train_loss -0.777 +2024-11-22 08:12:10.240144: val_loss -0.7446 +2024-11-22 08:12:10.240218: Pseudo dice [0.8411] +2024-11-22 08:12:10.240299: Epoch time: 19.39 s +2024-11-22 08:12:11.535301: +2024-11-22 08:12:11.535589: Epoch 3950 +2024-11-22 08:12:11.535704: Current learning rate: 0.00542 +2024-11-22 08:12:29.884298: train_loss -0.7826 +2024-11-22 08:12:29.884550: val_loss -0.7531 +2024-11-22 08:12:29.884647: Pseudo dice [0.8561] +2024-11-22 08:12:29.884730: Epoch time: 18.35 s +2024-11-22 08:12:30.768578: +2024-11-22 08:12:30.768767: Epoch 3951 +2024-11-22 08:12:30.768883: Current learning rate: 0.00542 +2024-11-22 08:12:49.511688: train_loss -0.7817 +2024-11-22 08:12:49.511956: val_loss -0.7386 +2024-11-22 08:12:49.512037: Pseudo dice [0.8345] +2024-11-22 08:12:49.512116: Epoch time: 18.74 s +2024-11-22 08:12:50.407447: +2024-11-22 08:12:50.407653: Epoch 3952 +2024-11-22 08:12:50.407763: Current learning rate: 0.00542 +2024-11-22 08:13:08.498137: train_loss -0.7944 +2024-11-22 08:13:08.498420: val_loss -0.7507 +2024-11-22 08:13:08.498501: Pseudo dice [0.8233] +2024-11-22 08:13:08.498579: Epoch time: 18.09 s +2024-11-22 08:13:09.422729: +2024-11-22 08:13:09.422946: Epoch 3953 +2024-11-22 08:13:09.423061: Current learning rate: 0.00542 +2024-11-22 08:13:28.609069: train_loss -0.8005 +2024-11-22 08:13:28.609330: val_loss -0.7595 +2024-11-22 08:13:28.609410: Pseudo dice [0.8276] +2024-11-22 08:13:28.611730: Epoch time: 19.19 s +2024-11-22 08:13:29.672531: +2024-11-22 08:13:29.672797: Epoch 3954 +2024-11-22 08:13:29.672910: Current learning rate: 0.00541 +2024-11-22 08:13:48.756275: train_loss -0.7985 +2024-11-22 08:13:48.756513: val_loss -0.7517 +2024-11-22 08:13:48.756594: Pseudo dice [0.8416] +2024-11-22 08:13:48.756679: Epoch time: 19.08 s +2024-11-22 08:13:49.788605: +2024-11-22 08:13:49.788842: Epoch 3955 +2024-11-22 08:13:49.788957: Current learning rate: 0.00541 +2024-11-22 08:14:07.715223: train_loss -0.7935 +2024-11-22 08:14:07.715442: val_loss -0.7312 +2024-11-22 08:14:07.715519: Pseudo dice [0.8307] +2024-11-22 08:14:07.715596: Epoch time: 17.93 s +2024-11-22 08:14:08.646660: +2024-11-22 08:14:08.646899: Epoch 3956 +2024-11-22 08:14:08.647019: Current learning rate: 0.00541 +2024-11-22 08:14:27.167516: train_loss -0.7949 +2024-11-22 08:14:27.169941: val_loss -0.7663 +2024-11-22 08:14:27.170049: Pseudo dice [0.8364] +2024-11-22 08:14:27.170130: Epoch time: 18.52 s +2024-11-22 08:14:28.442123: +2024-11-22 08:14:28.442382: Epoch 3957 +2024-11-22 08:14:28.442526: Current learning rate: 0.00541 +2024-11-22 08:14:47.140296: train_loss -0.7859 +2024-11-22 08:14:47.140542: val_loss -0.7495 +2024-11-22 08:14:47.140623: Pseudo dice [0.8433] +2024-11-22 08:14:47.140737: Epoch time: 18.7 s +2024-11-22 08:14:48.036053: +2024-11-22 08:14:48.036258: Epoch 3958 +2024-11-22 08:14:48.036371: Current learning rate: 0.00541 +2024-11-22 08:15:06.792576: train_loss -0.7779 +2024-11-22 08:15:06.792812: val_loss -0.7171 +2024-11-22 08:15:06.792885: Pseudo dice [0.8399] +2024-11-22 08:15:06.792963: Epoch time: 18.76 s +2024-11-22 08:15:07.805120: +2024-11-22 08:15:07.805365: Epoch 3959 +2024-11-22 08:15:07.805475: Current learning rate: 0.00541 +2024-11-22 08:15:25.355910: train_loss -0.7761 +2024-11-22 08:15:25.356136: val_loss -0.7368 +2024-11-22 08:15:25.356214: Pseudo dice [0.8488] +2024-11-22 08:15:25.356290: Epoch time: 17.55 s +2024-11-22 08:15:26.357801: +2024-11-22 08:15:26.358023: Epoch 3960 +2024-11-22 08:15:26.358135: Current learning rate: 0.00541 +2024-11-22 08:15:45.148630: train_loss -0.7889 +2024-11-22 08:15:45.148857: val_loss -0.7351 +2024-11-22 08:15:45.148939: Pseudo dice [0.8456] +2024-11-22 08:15:45.149027: Epoch time: 18.79 s +2024-11-22 08:15:46.032576: +2024-11-22 08:15:46.032782: Epoch 3961 +2024-11-22 08:15:46.032894: Current learning rate: 0.00541 +2024-11-22 08:16:05.782253: train_loss -0.7883 +2024-11-22 08:16:05.782499: val_loss -0.7226 +2024-11-22 08:16:05.782575: Pseudo dice [0.8524] +2024-11-22 08:16:05.796209: Epoch time: 19.75 s +2024-11-22 08:16:06.687353: +2024-11-22 08:16:06.687572: Epoch 3962 +2024-11-22 08:16:06.687682: Current learning rate: 0.0054 +2024-11-22 08:16:24.310769: train_loss -0.7889 +2024-11-22 08:16:24.311028: val_loss -0.7332 +2024-11-22 08:16:24.311102: Pseudo dice [0.843] +2024-11-22 08:16:24.311176: Epoch time: 17.62 s +2024-11-22 08:16:25.592444: +2024-11-22 08:16:25.592739: Epoch 3963 +2024-11-22 08:16:25.592867: Current learning rate: 0.0054 +2024-11-22 08:16:44.573953: train_loss -0.7927 +2024-11-22 08:16:44.574196: val_loss -0.761 +2024-11-22 08:16:44.574276: Pseudo dice [0.8479] +2024-11-22 08:16:44.574353: Epoch time: 18.98 s +2024-11-22 08:16:45.456299: +2024-11-22 08:16:45.456562: Epoch 3964 +2024-11-22 08:16:45.456673: Current learning rate: 0.0054 +2024-11-22 08:17:03.902669: train_loss -0.7937 +2024-11-22 08:17:03.903013: val_loss -0.76 +2024-11-22 08:17:03.903094: Pseudo dice [0.8595] +2024-11-22 08:17:03.903179: Epoch time: 18.45 s +2024-11-22 08:17:04.791410: +2024-11-22 08:17:04.791645: Epoch 3965 +2024-11-22 08:17:04.791763: Current learning rate: 0.0054 +2024-11-22 08:17:23.531518: train_loss -0.7874 +2024-11-22 08:17:23.531793: val_loss -0.7672 +2024-11-22 08:17:23.531873: Pseudo dice [0.847] +2024-11-22 08:17:23.531953: Epoch time: 18.74 s +2024-11-22 08:17:24.594627: +2024-11-22 08:17:24.594872: Epoch 3966 +2024-11-22 08:17:24.594996: Current learning rate: 0.0054 +2024-11-22 08:17:44.001796: train_loss -0.783 +2024-11-22 08:17:44.002015: val_loss -0.7519 +2024-11-22 08:17:44.002094: Pseudo dice [0.8495] +2024-11-22 08:17:44.002169: Epoch time: 19.41 s +2024-11-22 08:17:44.890966: +2024-11-22 08:17:44.891228: Epoch 3967 +2024-11-22 08:17:44.891342: Current learning rate: 0.0054 +2024-11-22 08:18:03.179032: train_loss -0.7821 +2024-11-22 08:18:03.179249: val_loss -0.7372 +2024-11-22 08:18:03.179322: Pseudo dice [0.8135] +2024-11-22 08:18:03.179394: Epoch time: 18.29 s +2024-11-22 08:18:04.069685: +2024-11-22 08:18:04.069907: Epoch 3968 +2024-11-22 08:18:04.070025: Current learning rate: 0.0054 +2024-11-22 08:18:21.753865: train_loss -0.7881 +2024-11-22 08:18:21.754124: val_loss -0.7173 +2024-11-22 08:18:21.754217: Pseudo dice [0.8232] +2024-11-22 08:18:21.754300: Epoch time: 17.68 s +2024-11-22 08:18:22.641952: +2024-11-22 08:18:22.642163: Epoch 3969 +2024-11-22 08:18:22.642271: Current learning rate: 0.0054 +2024-11-22 08:18:40.175569: train_loss -0.7901 +2024-11-22 08:18:40.175787: val_loss -0.7567 +2024-11-22 08:18:40.175863: Pseudo dice [0.8473] +2024-11-22 08:18:40.175938: Epoch time: 17.53 s +2024-11-22 08:18:41.065760: +2024-11-22 08:18:41.065959: Epoch 3970 +2024-11-22 08:18:41.066074: Current learning rate: 0.0054 +2024-11-22 08:18:59.720603: train_loss -0.7949 +2024-11-22 08:18:59.721504: val_loss -0.7576 +2024-11-22 08:18:59.721584: Pseudo dice [0.8546] +2024-11-22 08:18:59.721678: Epoch time: 18.66 s +2024-11-22 08:19:00.609847: +2024-11-22 08:19:00.610068: Epoch 3971 +2024-11-22 08:19:00.610182: Current learning rate: 0.00539 +2024-11-22 08:19:20.275138: train_loss -0.7914 +2024-11-22 08:19:20.275410: val_loss -0.7528 +2024-11-22 08:19:20.275486: Pseudo dice [0.8615] +2024-11-22 08:19:20.275565: Epoch time: 19.67 s +2024-11-22 08:19:21.164880: +2024-11-22 08:19:21.165078: Epoch 3972 +2024-11-22 08:19:21.165188: Current learning rate: 0.00539 +2024-11-22 08:19:39.570139: train_loss -0.7957 +2024-11-22 08:19:39.570421: val_loss -0.7251 +2024-11-22 08:19:39.570500: Pseudo dice [0.8384] +2024-11-22 08:19:39.570586: Epoch time: 18.41 s +2024-11-22 08:19:40.452614: +2024-11-22 08:19:40.453122: Epoch 3973 +2024-11-22 08:19:40.453255: Current learning rate: 0.00539 +2024-11-22 08:19:58.707444: train_loss -0.7928 +2024-11-22 08:19:58.707662: val_loss -0.7503 +2024-11-22 08:19:58.707736: Pseudo dice [0.836] +2024-11-22 08:19:58.707822: Epoch time: 18.26 s +2024-11-22 08:19:59.594368: +2024-11-22 08:19:59.594604: Epoch 3974 +2024-11-22 08:19:59.594714: Current learning rate: 0.00539 +2024-11-22 08:20:17.559538: train_loss -0.7935 +2024-11-22 08:20:17.559770: val_loss -0.7307 +2024-11-22 08:20:17.559845: Pseudo dice [0.8259] +2024-11-22 08:20:17.559922: Epoch time: 17.97 s +2024-11-22 08:20:18.854761: +2024-11-22 08:20:18.854969: Epoch 3975 +2024-11-22 08:20:18.855086: Current learning rate: 0.00539 +2024-11-22 08:20:38.123252: train_loss -0.7858 +2024-11-22 08:20:38.123516: val_loss -0.7506 +2024-11-22 08:20:38.123593: Pseudo dice [0.8377] +2024-11-22 08:20:38.123742: Epoch time: 19.27 s +2024-11-22 08:20:39.021334: +2024-11-22 08:20:39.021562: Epoch 3976 +2024-11-22 08:20:39.021673: Current learning rate: 0.00539 +2024-11-22 08:20:57.059170: train_loss -0.7899 +2024-11-22 08:20:57.059394: val_loss -0.7788 +2024-11-22 08:20:57.059470: Pseudo dice [0.8543] +2024-11-22 08:20:57.059547: Epoch time: 18.04 s +2024-11-22 08:20:57.989655: +2024-11-22 08:20:57.989881: Epoch 3977 +2024-11-22 08:20:57.990008: Current learning rate: 0.00539 +2024-11-22 08:21:16.922448: train_loss -0.7909 +2024-11-22 08:21:16.922670: val_loss -0.7405 +2024-11-22 08:21:16.922749: Pseudo dice [0.8515] +2024-11-22 08:21:16.922852: Epoch time: 18.93 s +2024-11-22 08:21:17.813154: +2024-11-22 08:21:17.813379: Epoch 3978 +2024-11-22 08:21:17.813492: Current learning rate: 0.00539 +2024-11-22 08:21:37.018326: train_loss -0.7864 +2024-11-22 08:21:37.018544: val_loss -0.7276 +2024-11-22 08:21:37.018619: Pseudo dice [0.8628] +2024-11-22 08:21:37.018695: Epoch time: 19.21 s +2024-11-22 08:21:37.938794: +2024-11-22 08:21:37.939008: Epoch 3979 +2024-11-22 08:21:37.939119: Current learning rate: 0.00538 +2024-11-22 08:21:56.882101: train_loss -0.7922 +2024-11-22 08:21:56.882346: val_loss -0.708 +2024-11-22 08:21:56.882421: Pseudo dice [0.818] +2024-11-22 08:21:56.882504: Epoch time: 18.94 s +2024-11-22 08:21:57.774265: +2024-11-22 08:21:57.774492: Epoch 3980 +2024-11-22 08:21:57.774601: Current learning rate: 0.00538 +2024-11-22 08:22:16.821377: train_loss -0.7895 +2024-11-22 08:22:16.821581: val_loss -0.741 +2024-11-22 08:22:16.821656: Pseudo dice [0.8414] +2024-11-22 08:22:16.821729: Epoch time: 19.05 s +2024-11-22 08:22:17.713016: +2024-11-22 08:22:17.713243: Epoch 3981 +2024-11-22 08:22:17.713357: Current learning rate: 0.00538 +2024-11-22 08:22:36.422771: train_loss -0.7858 +2024-11-22 08:22:36.423016: val_loss -0.7408 +2024-11-22 08:22:36.423090: Pseudo dice [0.8393] +2024-11-22 08:22:36.423169: Epoch time: 18.71 s +2024-11-22 08:22:37.346837: +2024-11-22 08:22:37.347062: Epoch 3982 +2024-11-22 08:22:37.347177: Current learning rate: 0.00538 +2024-11-22 08:22:57.499562: train_loss -0.7709 +2024-11-22 08:22:57.499786: val_loss -0.7245 +2024-11-22 08:22:57.499862: Pseudo dice [0.8384] +2024-11-22 08:22:57.499941: Epoch time: 20.15 s +2024-11-22 08:22:58.404303: +2024-11-22 08:22:58.404511: Epoch 3983 +2024-11-22 08:22:58.404629: Current learning rate: 0.00538 +2024-11-22 08:23:17.627356: train_loss -0.7742 +2024-11-22 08:23:17.627604: val_loss -0.7255 +2024-11-22 08:23:17.627678: Pseudo dice [0.849] +2024-11-22 08:23:17.627757: Epoch time: 19.22 s +2024-11-22 08:23:18.517700: +2024-11-22 08:23:18.517888: Epoch 3984 +2024-11-22 08:23:18.518005: Current learning rate: 0.00538 +2024-11-22 08:23:36.930134: train_loss -0.7901 +2024-11-22 08:23:36.930357: val_loss -0.756 +2024-11-22 08:23:36.930438: Pseudo dice [0.8359] +2024-11-22 08:23:36.930515: Epoch time: 18.41 s +2024-11-22 08:23:37.869038: +2024-11-22 08:23:37.869288: Epoch 3985 +2024-11-22 08:23:37.869402: Current learning rate: 0.00538 +2024-11-22 08:23:57.041341: train_loss -0.7802 +2024-11-22 08:23:57.041578: val_loss -0.7559 +2024-11-22 08:23:57.041655: Pseudo dice [0.8379] +2024-11-22 08:23:57.041731: Epoch time: 19.17 s +2024-11-22 08:23:58.346699: +2024-11-22 08:23:58.346905: Epoch 3986 +2024-11-22 08:23:58.347024: Current learning rate: 0.00538 +2024-11-22 08:24:16.454505: train_loss -0.7761 +2024-11-22 08:24:16.454759: val_loss -0.7441 +2024-11-22 08:24:16.454836: Pseudo dice [0.8433] +2024-11-22 08:24:16.454920: Epoch time: 18.11 s +2024-11-22 08:24:17.355398: +2024-11-22 08:24:17.355632: Epoch 3987 +2024-11-22 08:24:17.355744: Current learning rate: 0.00537 +2024-11-22 08:24:35.429755: train_loss -0.7873 +2024-11-22 08:24:35.429972: val_loss -0.7242 +2024-11-22 08:24:35.430054: Pseudo dice [0.8202] +2024-11-22 08:24:35.430128: Epoch time: 18.08 s +2024-11-22 08:24:36.325248: +2024-11-22 08:24:36.325478: Epoch 3988 +2024-11-22 08:24:36.325594: Current learning rate: 0.00537 +2024-11-22 08:24:54.986819: train_loss -0.7705 +2024-11-22 08:24:54.987046: val_loss -0.755 +2024-11-22 08:24:54.987121: Pseudo dice [0.8348] +2024-11-22 08:24:54.987198: Epoch time: 18.66 s +2024-11-22 08:24:55.976039: +2024-11-22 08:24:55.976261: Epoch 3989 +2024-11-22 08:24:55.976376: Current learning rate: 0.00537 +2024-11-22 08:25:14.265202: train_loss -0.7784 +2024-11-22 08:25:14.265477: val_loss -0.7518 +2024-11-22 08:25:14.265552: Pseudo dice [0.8343] +2024-11-22 08:25:14.265627: Epoch time: 18.29 s +2024-11-22 08:25:15.156018: +2024-11-22 08:25:15.156239: Epoch 3990 +2024-11-22 08:25:15.156353: Current learning rate: 0.00537 +2024-11-22 08:25:33.583143: train_loss -0.7767 +2024-11-22 08:25:33.583400: val_loss -0.7461 +2024-11-22 08:25:33.583479: Pseudo dice [0.8238] +2024-11-22 08:25:33.583562: Epoch time: 18.43 s +2024-11-22 08:25:34.474840: +2024-11-22 08:25:34.475122: Epoch 3991 +2024-11-22 08:25:34.475232: Current learning rate: 0.00537 +2024-11-22 08:25:53.255195: train_loss -0.7783 +2024-11-22 08:25:53.255412: val_loss -0.7268 +2024-11-22 08:25:53.255495: Pseudo dice [0.8413] +2024-11-22 08:25:53.255571: Epoch time: 18.78 s +2024-11-22 08:25:54.135436: +2024-11-22 08:25:54.135657: Epoch 3992 +2024-11-22 08:25:54.135770: Current learning rate: 0.00537 +2024-11-22 08:26:13.668256: train_loss -0.782 +2024-11-22 08:26:13.668566: val_loss -0.7376 +2024-11-22 08:26:13.668649: Pseudo dice [0.821] +2024-11-22 08:26:13.668730: Epoch time: 19.53 s +2024-11-22 08:26:14.560616: +2024-11-22 08:26:14.560915: Epoch 3993 +2024-11-22 08:26:14.561033: Current learning rate: 0.00537 +2024-11-22 08:26:32.262825: train_loss -0.7819 +2024-11-22 08:26:32.263051: val_loss -0.749 +2024-11-22 08:26:32.263126: Pseudo dice [0.8434] +2024-11-22 08:26:32.263207: Epoch time: 17.7 s +2024-11-22 08:26:33.255712: +2024-11-22 08:26:33.255969: Epoch 3994 +2024-11-22 08:26:33.256088: Current learning rate: 0.00537 +2024-11-22 08:26:51.377457: train_loss -0.7851 +2024-11-22 08:26:51.377706: val_loss -0.7088 +2024-11-22 08:26:51.377781: Pseudo dice [0.8352] +2024-11-22 08:26:51.377864: Epoch time: 18.12 s +2024-11-22 08:26:52.267380: +2024-11-22 08:26:52.267573: Epoch 3995 +2024-11-22 08:26:52.267682: Current learning rate: 0.00536 +2024-11-22 08:27:11.450205: train_loss -0.7831 +2024-11-22 08:27:11.450428: val_loss -0.7293 +2024-11-22 08:27:11.450504: Pseudo dice [0.844] +2024-11-22 08:27:11.450580: Epoch time: 19.18 s +2024-11-22 08:27:12.471872: +2024-11-22 08:27:12.472072: Epoch 3996 +2024-11-22 08:27:12.472182: Current learning rate: 0.00536 +2024-11-22 08:27:33.002548: train_loss -0.7748 +2024-11-22 08:27:33.002773: val_loss -0.7261 +2024-11-22 08:27:33.002849: Pseudo dice [0.81] +2024-11-22 08:27:33.002926: Epoch time: 20.53 s +2024-11-22 08:27:34.328999: +2024-11-22 08:27:34.329205: Epoch 3997 +2024-11-22 08:27:34.329317: Current learning rate: 0.00536 +2024-11-22 08:27:52.949335: train_loss -0.7825 +2024-11-22 08:27:52.949591: val_loss -0.7574 +2024-11-22 08:27:52.949669: Pseudo dice [0.855] +2024-11-22 08:27:52.954938: Epoch time: 18.62 s +2024-11-22 08:27:53.929272: +2024-11-22 08:27:53.929628: Epoch 3998 +2024-11-22 08:27:53.929745: Current learning rate: 0.00536 +2024-11-22 08:28:12.102092: train_loss -0.7917 +2024-11-22 08:28:12.107476: val_loss -0.7188 +2024-11-22 08:28:12.107586: Pseudo dice [0.8232] +2024-11-22 08:28:12.107663: Epoch time: 18.17 s +2024-11-22 08:28:13.182526: +2024-11-22 08:28:13.182739: Epoch 3999 +2024-11-22 08:28:13.182853: Current learning rate: 0.00536 +2024-11-22 08:28:32.364749: train_loss -0.7834 +2024-11-22 08:28:32.364974: val_loss -0.7518 +2024-11-22 08:28:32.365056: Pseudo dice [0.8148] +2024-11-22 08:28:32.365130: Epoch time: 19.18 s +2024-11-22 08:28:33.516474: +2024-11-22 08:28:33.516700: Epoch 4000 +2024-11-22 08:28:33.516813: Current learning rate: 0.00536 +2024-11-22 08:28:52.560287: train_loss -0.7859 +2024-11-22 08:28:52.560529: val_loss -0.7556 +2024-11-22 08:28:52.560611: Pseudo dice [0.8271] +2024-11-22 08:28:52.560694: Epoch time: 19.04 s +2024-11-22 08:28:53.450690: +2024-11-22 08:28:53.450902: Epoch 4001 +2024-11-22 08:28:53.451026: Current learning rate: 0.00536 +2024-11-22 08:29:12.576358: train_loss -0.7901 +2024-11-22 08:29:12.578767: val_loss -0.7518 +2024-11-22 08:29:12.578861: Pseudo dice [0.8476] +2024-11-22 08:29:12.578936: Epoch time: 19.13 s +2024-11-22 08:29:13.486723: +2024-11-22 08:29:13.486936: Epoch 4002 +2024-11-22 08:29:13.487062: Current learning rate: 0.00536 +2024-11-22 08:29:33.114139: train_loss -0.7892 +2024-11-22 08:29:33.114357: val_loss -0.7533 +2024-11-22 08:29:33.114433: Pseudo dice [0.8466] +2024-11-22 08:29:33.114511: Epoch time: 19.63 s +2024-11-22 08:29:34.446645: +2024-11-22 08:29:34.447028: Epoch 4003 +2024-11-22 08:29:34.447142: Current learning rate: 0.00536 +2024-11-22 08:29:51.857934: train_loss -0.7987 +2024-11-22 08:29:51.858168: val_loss -0.7373 +2024-11-22 08:29:51.858243: Pseudo dice [0.8249] +2024-11-22 08:29:51.858319: Epoch time: 17.41 s +2024-11-22 08:29:52.748260: +2024-11-22 08:29:52.748456: Epoch 4004 +2024-11-22 08:29:52.748570: Current learning rate: 0.00535 +2024-11-22 08:30:09.780089: train_loss -0.7906 +2024-11-22 08:30:09.782901: val_loss -0.7481 +2024-11-22 08:30:09.783000: Pseudo dice [0.8681] +2024-11-22 08:30:09.783085: Epoch time: 17.03 s +2024-11-22 08:30:10.814076: +2024-11-22 08:30:10.814294: Epoch 4005 +2024-11-22 08:30:10.814405: Current learning rate: 0.00535 +2024-11-22 08:30:28.607261: train_loss -0.7981 +2024-11-22 08:30:28.607484: val_loss -0.7498 +2024-11-22 08:30:28.607558: Pseudo dice [0.8486] +2024-11-22 08:30:28.607633: Epoch time: 17.79 s +2024-11-22 08:30:29.492103: +2024-11-22 08:30:29.492307: Epoch 4006 +2024-11-22 08:30:29.492419: Current learning rate: 0.00535 +2024-11-22 08:30:47.972021: train_loss -0.7791 +2024-11-22 08:30:47.972303: val_loss -0.7496 +2024-11-22 08:30:47.972386: Pseudo dice [0.8318] +2024-11-22 08:30:47.972462: Epoch time: 18.48 s +2024-11-22 08:30:48.863113: +2024-11-22 08:30:48.863317: Epoch 4007 +2024-11-22 08:30:48.864055: Current learning rate: 0.00535 +2024-11-22 08:31:08.590029: train_loss -0.7859 +2024-11-22 08:31:08.590241: val_loss -0.7644 +2024-11-22 08:31:08.590312: Pseudo dice [0.8415] +2024-11-22 08:31:08.590385: Epoch time: 19.73 s +2024-11-22 08:31:09.882003: +2024-11-22 08:31:09.882247: Epoch 4008 +2024-11-22 08:31:09.882356: Current learning rate: 0.00535 +2024-11-22 08:31:28.830246: train_loss -0.7753 +2024-11-22 08:31:28.830495: val_loss -0.7495 +2024-11-22 08:31:28.830574: Pseudo dice [0.8611] +2024-11-22 08:31:28.830660: Epoch time: 18.95 s +2024-11-22 08:31:29.728335: +2024-11-22 08:31:29.728555: Epoch 4009 +2024-11-22 08:31:29.728668: Current learning rate: 0.00535 +2024-11-22 08:31:47.998804: train_loss -0.7872 +2024-11-22 08:31:47.999091: val_loss -0.7542 +2024-11-22 08:31:47.999168: Pseudo dice [0.8421] +2024-11-22 08:31:47.999244: Epoch time: 18.27 s +2024-11-22 08:31:48.891052: +2024-11-22 08:31:48.891303: Epoch 4010 +2024-11-22 08:31:48.891419: Current learning rate: 0.00535 +2024-11-22 08:32:07.361573: train_loss -0.7847 +2024-11-22 08:32:07.361803: val_loss -0.7489 +2024-11-22 08:32:07.361878: Pseudo dice [0.8504] +2024-11-22 08:32:07.361958: Epoch time: 18.47 s +2024-11-22 08:32:08.250460: +2024-11-22 08:32:08.250674: Epoch 4011 +2024-11-22 08:32:08.250784: Current learning rate: 0.00535 +2024-11-22 08:32:27.688077: train_loss -0.7866 +2024-11-22 08:32:27.688365: val_loss -0.7503 +2024-11-22 08:32:27.688450: Pseudo dice [0.849] +2024-11-22 08:32:27.688527: Epoch time: 19.44 s +2024-11-22 08:32:28.579322: +2024-11-22 08:32:28.579539: Epoch 4012 +2024-11-22 08:32:28.579654: Current learning rate: 0.00534 +2024-11-22 08:32:46.846098: train_loss -0.7912 +2024-11-22 08:32:46.846348: val_loss -0.7655 +2024-11-22 08:32:46.846431: Pseudo dice [0.8437] +2024-11-22 08:32:46.846517: Epoch time: 18.27 s +2024-11-22 08:32:47.743822: +2024-11-22 08:32:47.744103: Epoch 4013 +2024-11-22 08:32:47.744219: Current learning rate: 0.00534 +2024-11-22 08:33:06.592426: train_loss -0.7978 +2024-11-22 08:33:06.592706: val_loss -0.7497 +2024-11-22 08:33:06.592820: Pseudo dice [0.8634] +2024-11-22 08:33:06.592902: Epoch time: 18.85 s +2024-11-22 08:33:07.483975: +2024-11-22 08:33:07.484184: Epoch 4014 +2024-11-22 08:33:07.484303: Current learning rate: 0.00534 +2024-11-22 08:33:26.664062: train_loss -0.7763 +2024-11-22 08:33:26.664351: val_loss -0.7794 +2024-11-22 08:33:26.664431: Pseudo dice [0.8308] +2024-11-22 08:33:26.664532: Epoch time: 19.18 s +2024-11-22 08:33:27.557665: +2024-11-22 08:33:27.557987: Epoch 4015 +2024-11-22 08:33:27.558116: Current learning rate: 0.00534 +2024-11-22 08:33:45.810952: train_loss -0.7798 +2024-11-22 08:33:45.811185: val_loss -0.7382 +2024-11-22 08:33:45.811262: Pseudo dice [0.8504] +2024-11-22 08:33:45.811343: Epoch time: 18.25 s +2024-11-22 08:33:46.696583: +2024-11-22 08:33:46.696827: Epoch 4016 +2024-11-22 08:33:46.696943: Current learning rate: 0.00534 +2024-11-22 08:34:06.353978: train_loss -0.7936 +2024-11-22 08:34:06.354289: val_loss -0.7745 +2024-11-22 08:34:06.354364: Pseudo dice [0.8557] +2024-11-22 08:34:06.354444: Epoch time: 19.66 s +2024-11-22 08:34:07.300532: +2024-11-22 08:34:07.300746: Epoch 4017 +2024-11-22 08:34:07.300864: Current learning rate: 0.00534 +2024-11-22 08:34:25.397008: train_loss -0.7944 +2024-11-22 08:34:25.397230: val_loss -0.7444 +2024-11-22 08:34:25.397306: Pseudo dice [0.8386] +2024-11-22 08:34:25.397384: Epoch time: 18.1 s +2024-11-22 08:34:26.285626: +2024-11-22 08:34:26.285843: Epoch 4018 +2024-11-22 08:34:26.285963: Current learning rate: 0.00534 +2024-11-22 08:34:45.178813: train_loss -0.7961 +2024-11-22 08:34:45.179091: val_loss -0.7562 +2024-11-22 08:34:45.179232: Pseudo dice [0.846] +2024-11-22 08:34:45.179313: Epoch time: 18.89 s +2024-11-22 08:34:46.452018: +2024-11-22 08:34:46.452276: Epoch 4019 +2024-11-22 08:34:46.452402: Current learning rate: 0.00534 +2024-11-22 08:35:04.689247: train_loss -0.7988 +2024-11-22 08:35:04.689515: val_loss -0.7287 +2024-11-22 08:35:04.689589: Pseudo dice [0.8189] +2024-11-22 08:35:04.689673: Epoch time: 18.24 s +2024-11-22 08:35:05.593883: +2024-11-22 08:35:05.594134: Epoch 4020 +2024-11-22 08:35:05.594244: Current learning rate: 0.00533 +2024-11-22 08:35:25.043199: train_loss -0.7893 +2024-11-22 08:35:25.043420: val_loss -0.7458 +2024-11-22 08:35:25.043502: Pseudo dice [0.8294] +2024-11-22 08:35:25.043581: Epoch time: 19.45 s +2024-11-22 08:35:25.933223: +2024-11-22 08:35:25.933466: Epoch 4021 +2024-11-22 08:35:25.933579: Current learning rate: 0.00533 +2024-11-22 08:35:44.785890: train_loss -0.7956 +2024-11-22 08:35:44.786118: val_loss -0.742 +2024-11-22 08:35:44.786194: Pseudo dice [0.8403] +2024-11-22 08:35:44.786271: Epoch time: 18.85 s +2024-11-22 08:35:45.708029: +2024-11-22 08:35:45.708302: Epoch 4022 +2024-11-22 08:35:45.708416: Current learning rate: 0.00533 +2024-11-22 08:36:04.932881: train_loss -0.7976 +2024-11-22 08:36:04.933132: val_loss -0.7746 +2024-11-22 08:36:04.933221: Pseudo dice [0.8666] +2024-11-22 08:36:04.933355: Epoch time: 19.23 s +2024-11-22 08:36:05.831603: +2024-11-22 08:36:05.831871: Epoch 4023 +2024-11-22 08:36:05.831984: Current learning rate: 0.00533 +2024-11-22 08:36:24.802745: train_loss -0.7947 +2024-11-22 08:36:24.803006: val_loss -0.7438 +2024-11-22 08:36:24.803082: Pseudo dice [0.8436] +2024-11-22 08:36:24.803165: Epoch time: 18.97 s +2024-11-22 08:36:25.695566: +2024-11-22 08:36:25.695810: Epoch 4024 +2024-11-22 08:36:25.695924: Current learning rate: 0.00533 +2024-11-22 08:36:44.310029: train_loss -0.7926 +2024-11-22 08:36:44.310240: val_loss -0.7252 +2024-11-22 08:36:44.310399: Pseudo dice [0.8664] +2024-11-22 08:36:44.310479: Epoch time: 18.62 s +2024-11-22 08:36:45.211289: +2024-11-22 08:36:45.211533: Epoch 4025 +2024-11-22 08:36:45.211648: Current learning rate: 0.00533 +2024-11-22 08:37:04.284764: train_loss -0.7985 +2024-11-22 08:37:04.287194: val_loss -0.7571 +2024-11-22 08:37:04.287284: Pseudo dice [0.833] +2024-11-22 08:37:04.287365: Epoch time: 19.07 s +2024-11-22 08:37:05.334372: +2024-11-22 08:37:05.334812: Epoch 4026 +2024-11-22 08:37:05.334922: Current learning rate: 0.00533 +2024-11-22 08:37:23.657885: train_loss -0.7938 +2024-11-22 08:37:23.658179: val_loss -0.7556 +2024-11-22 08:37:23.658256: Pseudo dice [0.8406] +2024-11-22 08:37:23.658358: Epoch time: 18.32 s +2024-11-22 08:37:24.552414: +2024-11-22 08:37:24.552715: Epoch 4027 +2024-11-22 08:37:24.552829: Current learning rate: 0.00533 +2024-11-22 08:37:42.080034: train_loss -0.7844 +2024-11-22 08:37:42.080285: val_loss -0.7399 +2024-11-22 08:37:42.080361: Pseudo dice [0.8371] +2024-11-22 08:37:42.080444: Epoch time: 17.53 s +2024-11-22 08:37:43.045307: +2024-11-22 08:37:43.045533: Epoch 4028 +2024-11-22 08:37:43.045645: Current learning rate: 0.00533 +2024-11-22 08:38:01.571074: train_loss -0.7937 +2024-11-22 08:38:01.571289: val_loss -0.7621 +2024-11-22 08:38:01.571364: Pseudo dice [0.851] +2024-11-22 08:38:01.571444: Epoch time: 18.53 s +2024-11-22 08:38:02.492532: +2024-11-22 08:38:02.492795: Epoch 4029 +2024-11-22 08:38:02.492907: Current learning rate: 0.00532 +2024-11-22 08:38:21.687924: train_loss -0.7861 +2024-11-22 08:38:21.688150: val_loss -0.7426 +2024-11-22 08:38:21.688228: Pseudo dice [0.8518] +2024-11-22 08:38:21.688303: Epoch time: 19.2 s +2024-11-22 08:38:22.573705: +2024-11-22 08:38:22.573933: Epoch 4030 +2024-11-22 08:38:22.574060: Current learning rate: 0.00532 +2024-11-22 08:38:41.976857: train_loss -0.7919 +2024-11-22 08:38:41.977118: val_loss -0.7648 +2024-11-22 08:38:41.977198: Pseudo dice [0.8438] +2024-11-22 08:38:41.977284: Epoch time: 19.4 s +2024-11-22 08:38:43.284233: +2024-11-22 08:38:43.284464: Epoch 4031 +2024-11-22 08:38:43.284580: Current learning rate: 0.00532 +2024-11-22 08:39:01.692204: train_loss -0.7984 +2024-11-22 08:39:01.692436: val_loss -0.6815 +2024-11-22 08:39:01.692512: Pseudo dice [0.8173] +2024-11-22 08:39:01.692612: Epoch time: 18.41 s +2024-11-22 08:39:02.582948: +2024-11-22 08:39:02.583155: Epoch 4032 +2024-11-22 08:39:02.583262: Current learning rate: 0.00532 +2024-11-22 08:39:21.843270: train_loss -0.7977 +2024-11-22 08:39:21.843498: val_loss -0.7433 +2024-11-22 08:39:21.843579: Pseudo dice [0.8199] +2024-11-22 08:39:21.843674: Epoch time: 19.26 s +2024-11-22 08:39:22.733691: +2024-11-22 08:39:22.734002: Epoch 4033 +2024-11-22 08:39:22.734121: Current learning rate: 0.00532 +2024-11-22 08:39:41.246934: train_loss -0.7993 +2024-11-22 08:39:41.247156: val_loss -0.7241 +2024-11-22 08:39:41.247233: Pseudo dice [0.8269] +2024-11-22 08:39:41.249549: Epoch time: 18.51 s +2024-11-22 08:39:42.159857: +2024-11-22 08:39:42.160107: Epoch 4034 +2024-11-22 08:39:42.160247: Current learning rate: 0.00532 +2024-11-22 08:40:01.811291: train_loss -0.7906 +2024-11-22 08:40:01.811535: val_loss -0.7521 +2024-11-22 08:40:01.811609: Pseudo dice [0.855] +2024-11-22 08:40:01.811691: Epoch time: 19.65 s +2024-11-22 08:40:02.792751: +2024-11-22 08:40:02.792980: Epoch 4035 +2024-11-22 08:40:02.793104: Current learning rate: 0.00532 +2024-11-22 08:40:20.944501: train_loss -0.7926 +2024-11-22 08:40:20.944722: val_loss -0.7418 +2024-11-22 08:40:20.944797: Pseudo dice [0.8462] +2024-11-22 08:40:20.944873: Epoch time: 18.15 s +2024-11-22 08:40:21.835286: +2024-11-22 08:40:21.835516: Epoch 4036 +2024-11-22 08:40:21.835649: Current learning rate: 0.00532 +2024-11-22 08:40:40.915444: train_loss -0.7979 +2024-11-22 08:40:40.915661: val_loss -0.7524 +2024-11-22 08:40:40.915737: Pseudo dice [0.8507] +2024-11-22 08:40:40.915814: Epoch time: 19.08 s +2024-11-22 08:40:41.806102: +2024-11-22 08:40:41.806304: Epoch 4037 +2024-11-22 08:40:41.806419: Current learning rate: 0.00531 +2024-11-22 08:41:00.802551: train_loss -0.7921 +2024-11-22 08:41:00.802768: val_loss -0.7555 +2024-11-22 08:41:00.802842: Pseudo dice [0.8515] +2024-11-22 08:41:00.802917: Epoch time: 19.0 s +2024-11-22 08:41:01.795457: +2024-11-22 08:41:01.795671: Epoch 4038 +2024-11-22 08:41:01.795792: Current learning rate: 0.00531 +2024-11-22 08:41:20.365065: train_loss -0.7896 +2024-11-22 08:41:20.365317: val_loss -0.699 +2024-11-22 08:41:20.365391: Pseudo dice [0.8175] +2024-11-22 08:41:20.365474: Epoch time: 18.57 s +2024-11-22 08:41:21.262140: +2024-11-22 08:41:21.262334: Epoch 4039 +2024-11-22 08:41:21.262443: Current learning rate: 0.00531 +2024-11-22 08:41:40.116462: train_loss -0.7951 +2024-11-22 08:41:40.116686: val_loss -0.7663 +2024-11-22 08:41:40.116763: Pseudo dice [0.8361] +2024-11-22 08:41:40.116846: Epoch time: 18.86 s +2024-11-22 08:41:41.004434: +2024-11-22 08:41:41.004730: Epoch 4040 +2024-11-22 08:41:41.004843: Current learning rate: 0.00531 +2024-11-22 08:42:00.986812: train_loss -0.7895 +2024-11-22 08:42:00.987040: val_loss -0.7562 +2024-11-22 08:42:00.987117: Pseudo dice [0.8473] +2024-11-22 08:42:00.987193: Epoch time: 19.98 s +2024-11-22 08:42:01.947234: +2024-11-22 08:42:01.947496: Epoch 4041 +2024-11-22 08:42:01.947608: Current learning rate: 0.00531 +2024-11-22 08:42:19.753832: train_loss -0.7888 +2024-11-22 08:42:19.754057: val_loss -0.761 +2024-11-22 08:42:19.754139: Pseudo dice [0.8505] +2024-11-22 08:42:19.754218: Epoch time: 17.81 s +2024-11-22 08:42:21.049536: +2024-11-22 08:42:21.049741: Epoch 4042 +2024-11-22 08:42:21.049855: Current learning rate: 0.00531 +2024-11-22 08:42:39.944670: train_loss -0.7923 +2024-11-22 08:42:39.947102: val_loss -0.7204 +2024-11-22 08:42:39.951241: Pseudo dice [0.8116] +2024-11-22 08:42:39.951374: Epoch time: 18.9 s +2024-11-22 08:42:40.944468: +2024-11-22 08:42:40.944757: Epoch 4043 +2024-11-22 08:42:40.944871: Current learning rate: 0.00531 +2024-11-22 08:42:59.662269: train_loss -0.7904 +2024-11-22 08:42:59.662484: val_loss -0.7434 +2024-11-22 08:42:59.662565: Pseudo dice [0.8406] +2024-11-22 08:42:59.662650: Epoch time: 18.72 s +2024-11-22 08:43:00.551416: +2024-11-22 08:43:00.551671: Epoch 4044 +2024-11-22 08:43:00.551798: Current learning rate: 0.00531 +2024-11-22 08:43:19.380998: train_loss -0.7929 +2024-11-22 08:43:19.381225: val_loss -0.6985 +2024-11-22 08:43:19.381300: Pseudo dice [0.8194] +2024-11-22 08:43:19.381380: Epoch time: 18.83 s +2024-11-22 08:43:20.271485: +2024-11-22 08:43:20.271767: Epoch 4045 +2024-11-22 08:43:20.271886: Current learning rate: 0.0053 +2024-11-22 08:43:39.736382: train_loss -0.7746 +2024-11-22 08:43:39.736609: val_loss -0.7325 +2024-11-22 08:43:39.736684: Pseudo dice [0.8214] +2024-11-22 08:43:39.736762: Epoch time: 19.47 s +2024-11-22 08:43:40.805401: +2024-11-22 08:43:40.805630: Epoch 4046 +2024-11-22 08:43:40.805745: Current learning rate: 0.0053 +2024-11-22 08:43:59.521173: train_loss -0.7858 +2024-11-22 08:43:59.521435: val_loss -0.7575 +2024-11-22 08:43:59.521518: Pseudo dice [0.8533] +2024-11-22 08:43:59.521612: Epoch time: 18.72 s +2024-11-22 08:44:00.416293: +2024-11-22 08:44:00.416517: Epoch 4047 +2024-11-22 08:44:00.416629: Current learning rate: 0.0053 +2024-11-22 08:44:18.794591: train_loss -0.7883 +2024-11-22 08:44:18.794802: val_loss -0.7561 +2024-11-22 08:44:18.794881: Pseudo dice [0.828] +2024-11-22 08:44:18.794956: Epoch time: 18.38 s +2024-11-22 08:44:19.805966: +2024-11-22 08:44:19.806272: Epoch 4048 +2024-11-22 08:44:19.806388: Current learning rate: 0.0053 +2024-11-22 08:44:38.231334: train_loss -0.7891 +2024-11-22 08:44:38.233713: val_loss -0.721 +2024-11-22 08:44:38.233799: Pseudo dice [0.8443] +2024-11-22 08:44:38.233876: Epoch time: 18.43 s +2024-11-22 08:44:39.173642: +2024-11-22 08:44:39.173883: Epoch 4049 +2024-11-22 08:44:39.174008: Current learning rate: 0.0053 +2024-11-22 08:44:57.939873: train_loss -0.7852 +2024-11-22 08:44:57.940108: val_loss -0.7334 +2024-11-22 08:44:57.940184: Pseudo dice [0.8378] +2024-11-22 08:44:57.940280: Epoch time: 18.77 s +2024-11-22 08:44:59.100074: +2024-11-22 08:44:59.100342: Epoch 4050 +2024-11-22 08:44:59.100463: Current learning rate: 0.0053 +2024-11-22 08:45:17.225782: train_loss -0.7962 +2024-11-22 08:45:17.226057: val_loss -0.7126 +2024-11-22 08:45:17.226136: Pseudo dice [0.8157] +2024-11-22 08:45:17.226217: Epoch time: 18.13 s +2024-11-22 08:45:18.113179: +2024-11-22 08:45:18.113392: Epoch 4051 +2024-11-22 08:45:18.113506: Current learning rate: 0.0053 +2024-11-22 08:45:38.307490: train_loss -0.7844 +2024-11-22 08:45:38.307706: val_loss -0.7502 +2024-11-22 08:45:38.307782: Pseudo dice [0.828] +2024-11-22 08:45:38.307858: Epoch time: 20.2 s +2024-11-22 08:45:39.201548: +2024-11-22 08:45:39.201756: Epoch 4052 +2024-11-22 08:45:39.201866: Current learning rate: 0.0053 +2024-11-22 08:45:58.426028: train_loss -0.7751 +2024-11-22 08:45:58.426238: val_loss -0.7252 +2024-11-22 08:45:58.426316: Pseudo dice [0.8453] +2024-11-22 08:45:58.426394: Epoch time: 19.23 s +2024-11-22 08:45:59.316626: +2024-11-22 08:45:59.316836: Epoch 4053 +2024-11-22 08:45:59.316952: Current learning rate: 0.00529 +2024-11-22 08:46:18.956603: train_loss -0.7874 +2024-11-22 08:46:18.959052: val_loss -0.7335 +2024-11-22 08:46:18.959144: Pseudo dice [0.8409] +2024-11-22 08:46:18.959230: Epoch time: 19.64 s +2024-11-22 08:46:19.855746: +2024-11-22 08:46:19.855969: Epoch 4054 +2024-11-22 08:46:19.856087: Current learning rate: 0.00529 +2024-11-22 08:46:38.565729: train_loss -0.7876 +2024-11-22 08:46:38.565942: val_loss -0.7448 +2024-11-22 08:46:38.566019: Pseudo dice [0.839] +2024-11-22 08:46:38.566094: Epoch time: 18.71 s +2024-11-22 08:46:39.452321: +2024-11-22 08:46:39.452551: Epoch 4055 +2024-11-22 08:46:39.452662: Current learning rate: 0.00529 +2024-11-22 08:46:58.235906: train_loss -0.7753 +2024-11-22 08:46:58.236199: val_loss -0.7426 +2024-11-22 08:46:58.236279: Pseudo dice [0.8489] +2024-11-22 08:46:58.236355: Epoch time: 18.78 s +2024-11-22 08:46:59.123484: +2024-11-22 08:46:59.123748: Epoch 4056 +2024-11-22 08:46:59.123861: Current learning rate: 0.00529 +2024-11-22 08:47:17.016375: train_loss -0.7838 +2024-11-22 08:47:17.016629: val_loss -0.7219 +2024-11-22 08:47:17.016710: Pseudo dice [0.8304] +2024-11-22 08:47:17.016791: Epoch time: 17.89 s +2024-11-22 08:47:17.918355: +2024-11-22 08:47:17.918574: Epoch 4057 +2024-11-22 08:47:17.918690: Current learning rate: 0.00529 +2024-11-22 08:47:37.146298: train_loss -0.7906 +2024-11-22 08:47:37.146514: val_loss -0.7353 +2024-11-22 08:47:37.146589: Pseudo dice [0.8497] +2024-11-22 08:47:37.146665: Epoch time: 19.23 s +2024-11-22 08:47:38.040069: +2024-11-22 08:47:38.040316: Epoch 4058 +2024-11-22 08:47:38.040434: Current learning rate: 0.00529 +2024-11-22 08:47:57.256521: train_loss -0.7924 +2024-11-22 08:47:57.256757: val_loss -0.75 +2024-11-22 08:47:57.256831: Pseudo dice [0.8587] +2024-11-22 08:47:57.256910: Epoch time: 19.22 s +2024-11-22 08:47:58.151862: +2024-11-22 08:47:58.152160: Epoch 4059 +2024-11-22 08:47:58.152277: Current learning rate: 0.00529 +2024-11-22 08:48:15.590067: train_loss -0.7914 +2024-11-22 08:48:15.590286: val_loss -0.734 +2024-11-22 08:48:15.590362: Pseudo dice [0.8691] +2024-11-22 08:48:15.590441: Epoch time: 17.44 s +2024-11-22 08:48:16.479375: +2024-11-22 08:48:16.479599: Epoch 4060 +2024-11-22 08:48:16.479716: Current learning rate: 0.00529 +2024-11-22 08:48:34.996520: train_loss -0.7819 +2024-11-22 08:48:34.996745: val_loss -0.7513 +2024-11-22 08:48:34.996822: Pseudo dice [0.8333] +2024-11-22 08:48:35.003103: Epoch time: 18.52 s +2024-11-22 08:48:35.954886: +2024-11-22 08:48:35.955113: Epoch 4061 +2024-11-22 08:48:35.955225: Current learning rate: 0.00529 +2024-11-22 08:48:56.132467: train_loss -0.7898 +2024-11-22 08:48:56.132685: val_loss -0.7692 +2024-11-22 08:48:56.132760: Pseudo dice [0.8518] +2024-11-22 08:48:56.132839: Epoch time: 20.18 s +2024-11-22 08:48:57.022096: +2024-11-22 08:48:57.022313: Epoch 4062 +2024-11-22 08:48:57.022430: Current learning rate: 0.00528 +2024-11-22 08:49:15.961760: train_loss -0.7883 +2024-11-22 08:49:15.961978: val_loss -0.754 +2024-11-22 08:49:15.962060: Pseudo dice [0.8484] +2024-11-22 08:49:15.962138: Epoch time: 18.94 s +2024-11-22 08:49:16.852009: +2024-11-22 08:49:16.852227: Epoch 4063 +2024-11-22 08:49:16.852340: Current learning rate: 0.00528 +2024-11-22 08:49:35.642668: train_loss -0.7877 +2024-11-22 08:49:35.642900: val_loss -0.6959 +2024-11-22 08:49:35.642977: Pseudo dice [0.8337] +2024-11-22 08:49:35.643061: Epoch time: 18.79 s +2024-11-22 08:49:36.904307: +2024-11-22 08:49:36.904517: Epoch 4064 +2024-11-22 08:49:36.904628: Current learning rate: 0.00528 +2024-11-22 08:49:55.402026: train_loss -0.7951 +2024-11-22 08:49:55.402306: val_loss -0.7179 +2024-11-22 08:49:55.402385: Pseudo dice [0.833] +2024-11-22 08:49:55.402472: Epoch time: 18.5 s +2024-11-22 08:49:56.294506: +2024-11-22 08:49:56.294722: Epoch 4065 +2024-11-22 08:49:56.294833: Current learning rate: 0.00528 +2024-11-22 08:50:14.512987: train_loss -0.7824 +2024-11-22 08:50:14.513206: val_loss -0.7475 +2024-11-22 08:50:14.513280: Pseudo dice [0.8508] +2024-11-22 08:50:14.513357: Epoch time: 18.22 s +2024-11-22 08:50:15.604774: +2024-11-22 08:50:15.605053: Epoch 4066 +2024-11-22 08:50:15.605167: Current learning rate: 0.00528 +2024-11-22 08:50:34.829494: train_loss -0.7883 +2024-11-22 08:50:34.829727: val_loss -0.726 +2024-11-22 08:50:34.829802: Pseudo dice [0.8302] +2024-11-22 08:50:34.829879: Epoch time: 19.23 s +2024-11-22 08:50:35.752685: +2024-11-22 08:50:35.753022: Epoch 4067 +2024-11-22 08:50:35.753139: Current learning rate: 0.00528 +2024-11-22 08:50:53.416219: train_loss -0.783 +2024-11-22 08:50:53.416431: val_loss -0.7299 +2024-11-22 08:50:53.416506: Pseudo dice [0.8333] +2024-11-22 08:50:53.416584: Epoch time: 17.66 s +2024-11-22 08:50:54.325969: +2024-11-22 08:50:54.326252: Epoch 4068 +2024-11-22 08:50:54.326367: Current learning rate: 0.00528 +2024-11-22 08:51:12.102249: train_loss -0.772 +2024-11-22 08:51:12.102567: val_loss -0.7288 +2024-11-22 08:51:12.102647: Pseudo dice [0.8075] +2024-11-22 08:51:12.102730: Epoch time: 17.78 s +2024-11-22 08:51:13.020285: +2024-11-22 08:51:13.020499: Epoch 4069 +2024-11-22 08:51:13.020620: Current learning rate: 0.00528 +2024-11-22 08:51:32.229667: train_loss -0.7802 +2024-11-22 08:51:32.229893: val_loss -0.7332 +2024-11-22 08:51:32.229968: Pseudo dice [0.8204] +2024-11-22 08:51:32.230050: Epoch time: 19.21 s +2024-11-22 08:51:33.119298: +2024-11-22 08:51:33.119521: Epoch 4070 +2024-11-22 08:51:33.119635: Current learning rate: 0.00527 +2024-11-22 08:51:52.446694: train_loss -0.7651 +2024-11-22 08:51:52.446918: val_loss -0.7516 +2024-11-22 08:51:52.446999: Pseudo dice [0.8108] +2024-11-22 08:51:52.447094: Epoch time: 19.33 s +2024-11-22 08:51:53.526087: +2024-11-22 08:51:53.526288: Epoch 4071 +2024-11-22 08:51:53.526397: Current learning rate: 0.00527 +2024-11-22 08:52:11.809797: train_loss -0.773 +2024-11-22 08:52:11.810027: val_loss -0.7475 +2024-11-22 08:52:11.810133: Pseudo dice [0.8398] +2024-11-22 08:52:11.810217: Epoch time: 18.28 s +2024-11-22 08:52:12.703823: +2024-11-22 08:52:12.704053: Epoch 4072 +2024-11-22 08:52:12.704168: Current learning rate: 0.00527 +2024-11-22 08:52:33.032363: train_loss -0.7807 +2024-11-22 08:52:33.032687: val_loss -0.7278 +2024-11-22 08:52:33.032764: Pseudo dice [0.8393] +2024-11-22 08:52:33.032846: Epoch time: 20.33 s +2024-11-22 08:52:33.917409: +2024-11-22 08:52:33.917603: Epoch 4073 +2024-11-22 08:52:33.917721: Current learning rate: 0.00527 +2024-11-22 08:52:52.187087: train_loss -0.7791 +2024-11-22 08:52:52.187300: val_loss -0.7515 +2024-11-22 08:52:52.187382: Pseudo dice [0.8362] +2024-11-22 08:52:52.187459: Epoch time: 18.27 s +2024-11-22 08:52:53.152529: +2024-11-22 08:52:53.152745: Epoch 4074 +2024-11-22 08:52:53.152862: Current learning rate: 0.00527 +2024-11-22 08:53:11.331437: train_loss -0.7875 +2024-11-22 08:53:11.336836: val_loss -0.7561 +2024-11-22 08:53:11.336957: Pseudo dice [0.836] +2024-11-22 08:53:11.337045: Epoch time: 18.18 s +2024-11-22 08:53:12.332553: +2024-11-22 08:53:12.332747: Epoch 4075 +2024-11-22 08:53:12.332859: Current learning rate: 0.00527 +2024-11-22 08:53:30.445736: train_loss -0.7923 +2024-11-22 08:53:30.445953: val_loss -0.6856 +2024-11-22 08:53:30.446035: Pseudo dice [0.8393] +2024-11-22 08:53:30.446114: Epoch time: 18.11 s +2024-11-22 08:53:31.797180: +2024-11-22 08:53:31.797399: Epoch 4076 +2024-11-22 08:53:31.797511: Current learning rate: 0.00527 +2024-11-22 08:53:51.357604: train_loss -0.7692 +2024-11-22 08:53:51.360043: val_loss -0.7188 +2024-11-22 08:53:51.360193: Pseudo dice [0.7955] +2024-11-22 08:53:51.360284: Epoch time: 19.56 s +2024-11-22 08:53:52.310859: +2024-11-22 08:53:52.311103: Epoch 4077 +2024-11-22 08:53:52.311217: Current learning rate: 0.00527 +2024-11-22 08:54:12.312216: train_loss -0.7596 +2024-11-22 08:54:12.312441: val_loss -0.7435 +2024-11-22 08:54:12.312515: Pseudo dice [0.8346] +2024-11-22 08:54:12.312590: Epoch time: 20.0 s +2024-11-22 08:54:13.206076: +2024-11-22 08:54:13.206341: Epoch 4078 +2024-11-22 08:54:13.206454: Current learning rate: 0.00526 +2024-11-22 08:54:31.339282: train_loss -0.771 +2024-11-22 08:54:31.339502: val_loss -0.7373 +2024-11-22 08:54:31.339576: Pseudo dice [0.8303] +2024-11-22 08:54:31.339654: Epoch time: 18.13 s +2024-11-22 08:54:32.235778: +2024-11-22 08:54:32.236004: Epoch 4079 +2024-11-22 08:54:32.236125: Current learning rate: 0.00526 +2024-11-22 08:54:52.051275: train_loss -0.7803 +2024-11-22 08:54:52.051521: val_loss -0.7456 +2024-11-22 08:54:52.051596: Pseudo dice [0.8259] +2024-11-22 08:54:52.051677: Epoch time: 19.82 s +2024-11-22 08:54:52.945095: +2024-11-22 08:54:52.945325: Epoch 4080 +2024-11-22 08:54:52.945440: Current learning rate: 0.00526 +2024-11-22 08:55:11.605416: train_loss -0.7847 +2024-11-22 08:55:11.605634: val_loss -0.7597 +2024-11-22 08:55:11.605707: Pseudo dice [0.8334] +2024-11-22 08:55:11.607969: Epoch time: 18.66 s +2024-11-22 08:55:12.533354: +2024-11-22 08:55:12.533572: Epoch 4081 +2024-11-22 08:55:12.533684: Current learning rate: 0.00526 +2024-11-22 08:55:31.123779: train_loss -0.7826 +2024-11-22 08:55:31.123999: val_loss -0.7669 +2024-11-22 08:55:31.124075: Pseudo dice [0.8573] +2024-11-22 08:55:31.124151: Epoch time: 18.59 s +2024-11-22 08:55:32.013622: +2024-11-22 08:55:32.013831: Epoch 4082 +2024-11-22 08:55:32.013940: Current learning rate: 0.00526 +2024-11-22 08:55:51.475832: train_loss -0.7885 +2024-11-22 08:55:51.476067: val_loss -0.755 +2024-11-22 08:55:51.476144: Pseudo dice [0.845] +2024-11-22 08:55:51.476219: Epoch time: 19.46 s +2024-11-22 08:55:52.366526: +2024-11-22 08:55:52.366736: Epoch 4083 +2024-11-22 08:55:52.366845: Current learning rate: 0.00526 +2024-11-22 08:56:10.624336: train_loss -0.7832 +2024-11-22 08:56:10.624576: val_loss -0.752 +2024-11-22 08:56:10.624654: Pseudo dice [0.8555] +2024-11-22 08:56:10.624732: Epoch time: 18.26 s +2024-11-22 08:56:11.522082: +2024-11-22 08:56:11.522302: Epoch 4084 +2024-11-22 08:56:11.522414: Current learning rate: 0.00526 +2024-11-22 08:56:30.320320: train_loss -0.7999 +2024-11-22 08:56:30.320544: val_loss -0.7611 +2024-11-22 08:56:30.320642: Pseudo dice [0.8313] +2024-11-22 08:56:30.320724: Epoch time: 18.8 s +2024-11-22 08:56:31.212293: +2024-11-22 08:56:31.212488: Epoch 4085 +2024-11-22 08:56:31.212601: Current learning rate: 0.00526 +2024-11-22 08:56:49.995526: train_loss -0.7972 +2024-11-22 08:56:49.995740: val_loss -0.7411 +2024-11-22 08:56:49.995814: Pseudo dice [0.8536] +2024-11-22 08:56:49.995911: Epoch time: 18.78 s +2024-11-22 08:56:50.886356: +2024-11-22 08:56:50.886551: Epoch 4086 +2024-11-22 08:56:50.886662: Current learning rate: 0.00526 +2024-11-22 08:57:10.519826: train_loss -0.786 +2024-11-22 08:57:10.520089: val_loss -0.7327 +2024-11-22 08:57:10.520169: Pseudo dice [0.8433] +2024-11-22 08:57:10.520292: Epoch time: 19.63 s +2024-11-22 08:57:11.803614: +2024-11-22 08:57:11.803824: Epoch 4087 +2024-11-22 08:57:11.803936: Current learning rate: 0.00525 +2024-11-22 08:57:30.689077: train_loss -0.7928 +2024-11-22 08:57:30.691238: val_loss -0.7423 +2024-11-22 08:57:30.691352: Pseudo dice [0.8462] +2024-11-22 08:57:30.691439: Epoch time: 18.89 s +2024-11-22 08:57:31.619497: +2024-11-22 08:57:31.619712: Epoch 4088 +2024-11-22 08:57:31.619826: Current learning rate: 0.00525 +2024-11-22 08:57:51.261073: train_loss -0.7917 +2024-11-22 08:57:51.261293: val_loss -0.7845 +2024-11-22 08:57:51.261370: Pseudo dice [0.8686] +2024-11-22 08:57:51.261446: Epoch time: 19.64 s +2024-11-22 08:57:52.154061: +2024-11-22 08:57:52.154283: Epoch 4089 +2024-11-22 08:57:52.154394: Current learning rate: 0.00525 +2024-11-22 08:58:11.183965: train_loss -0.798 +2024-11-22 08:58:11.184216: val_loss -0.7602 +2024-11-22 08:58:11.184303: Pseudo dice [0.8191] +2024-11-22 08:58:11.184417: Epoch time: 19.03 s +2024-11-22 08:58:12.170795: +2024-11-22 08:58:12.171008: Epoch 4090 +2024-11-22 08:58:12.171118: Current learning rate: 0.00525 +2024-11-22 08:58:30.596376: train_loss -0.7989 +2024-11-22 08:58:30.596637: val_loss -0.7128 +2024-11-22 08:58:30.596715: Pseudo dice [0.823] +2024-11-22 08:58:30.596794: Epoch time: 18.43 s +2024-11-22 08:58:31.492743: +2024-11-22 08:58:31.492959: Epoch 4091 +2024-11-22 08:58:31.493078: Current learning rate: 0.00525 +2024-11-22 08:58:51.372233: train_loss -0.7854 +2024-11-22 08:58:51.372480: val_loss -0.7689 +2024-11-22 08:58:51.372559: Pseudo dice [0.8491] +2024-11-22 08:58:51.372648: Epoch time: 19.88 s +2024-11-22 08:58:52.242812: +2024-11-22 08:58:52.243028: Epoch 4092 +2024-11-22 08:58:52.243147: Current learning rate: 0.00525 +2024-11-22 08:59:10.106749: train_loss -0.7849 +2024-11-22 08:59:10.106987: val_loss -0.7413 +2024-11-22 08:59:10.107067: Pseudo dice [0.8517] +2024-11-22 08:59:10.107143: Epoch time: 17.86 s +2024-11-22 08:59:10.992016: +2024-11-22 08:59:10.992253: Epoch 4093 +2024-11-22 08:59:10.992378: Current learning rate: 0.00525 +2024-11-22 08:59:31.146984: train_loss -0.7878 +2024-11-22 08:59:31.147228: val_loss -0.7614 +2024-11-22 08:59:31.147308: Pseudo dice [0.8223] +2024-11-22 08:59:31.147385: Epoch time: 20.16 s +2024-11-22 08:59:32.012465: +2024-11-22 08:59:32.012679: Epoch 4094 +2024-11-22 08:59:32.012789: Current learning rate: 0.00525 +2024-11-22 08:59:51.296557: train_loss -0.7916 +2024-11-22 08:59:51.296792: val_loss -0.7545 +2024-11-22 08:59:51.296871: Pseudo dice [0.8589] +2024-11-22 08:59:51.296952: Epoch time: 19.28 s +2024-11-22 08:59:52.167505: +2024-11-22 08:59:52.167737: Epoch 4095 +2024-11-22 08:59:52.167850: Current learning rate: 0.00524 +2024-11-22 09:00:10.553412: train_loss -0.787 +2024-11-22 09:00:10.553729: val_loss -0.7298 +2024-11-22 09:00:10.553807: Pseudo dice [0.8252] +2024-11-22 09:00:10.553889: Epoch time: 18.39 s +2024-11-22 09:00:11.422784: +2024-11-22 09:00:11.423015: Epoch 4096 +2024-11-22 09:00:11.423131: Current learning rate: 0.00524 +2024-11-22 09:00:31.043672: train_loss -0.7923 +2024-11-22 09:00:31.048207: val_loss -0.7622 +2024-11-22 09:00:31.048326: Pseudo dice [0.8614] +2024-11-22 09:00:31.048408: Epoch time: 19.62 s +2024-11-22 09:00:32.026804: +2024-11-22 09:00:32.027061: Epoch 4097 +2024-11-22 09:00:32.027189: Current learning rate: 0.00524 +2024-11-22 09:00:50.483829: train_loss -0.7795 +2024-11-22 09:00:50.484064: val_loss -0.7361 +2024-11-22 09:00:50.484142: Pseudo dice [0.8318] +2024-11-22 09:00:50.484220: Epoch time: 18.46 s +2024-11-22 09:00:51.348084: +2024-11-22 09:00:51.348349: Epoch 4098 +2024-11-22 09:00:51.348471: Current learning rate: 0.00524 +2024-11-22 09:01:09.775816: train_loss -0.7704 +2024-11-22 09:01:09.776037: val_loss -0.7425 +2024-11-22 09:01:09.776112: Pseudo dice [0.8401] +2024-11-22 09:01:09.776191: Epoch time: 18.43 s +2024-11-22 09:01:11.007252: +2024-11-22 09:01:11.007466: Epoch 4099 +2024-11-22 09:01:11.007577: Current learning rate: 0.00524 +2024-11-22 09:01:29.208038: train_loss -0.7842 +2024-11-22 09:01:29.208287: val_loss -0.7645 +2024-11-22 09:01:29.208402: Pseudo dice [0.8612] +2024-11-22 09:01:29.208489: Epoch time: 18.2 s +2024-11-22 09:01:30.333469: +2024-11-22 09:01:30.333692: Epoch 4100 +2024-11-22 09:01:30.333810: Current learning rate: 0.00524 +2024-11-22 09:01:48.742042: train_loss -0.7931 +2024-11-22 09:01:48.742263: val_loss -0.7414 +2024-11-22 09:01:48.742338: Pseudo dice [0.855] +2024-11-22 09:01:48.742419: Epoch time: 18.41 s +2024-11-22 09:01:49.614703: +2024-11-22 09:01:49.614915: Epoch 4101 +2024-11-22 09:01:49.615030: Current learning rate: 0.00524 +2024-11-22 09:02:08.664349: train_loss -0.79 +2024-11-22 09:02:08.664591: val_loss -0.7678 +2024-11-22 09:02:08.664671: Pseudo dice [0.8503] +2024-11-22 09:02:08.664748: Epoch time: 19.05 s +2024-11-22 09:02:09.529850: +2024-11-22 09:02:09.530089: Epoch 4102 +2024-11-22 09:02:09.530203: Current learning rate: 0.00524 +2024-11-22 09:02:27.936072: train_loss -0.7964 +2024-11-22 09:02:27.936327: val_loss -0.7371 +2024-11-22 09:02:27.936407: Pseudo dice [0.8268] +2024-11-22 09:02:27.936491: Epoch time: 18.41 s +2024-11-22 09:02:28.893929: +2024-11-22 09:02:28.894147: Epoch 4103 +2024-11-22 09:02:28.894288: Current learning rate: 0.00523 +2024-11-22 09:02:47.470397: train_loss -0.7982 +2024-11-22 09:02:47.470622: val_loss -0.7533 +2024-11-22 09:02:47.470698: Pseudo dice [0.8549] +2024-11-22 09:02:47.470777: Epoch time: 18.58 s +2024-11-22 09:02:48.333151: +2024-11-22 09:02:48.333366: Epoch 4104 +2024-11-22 09:02:48.333481: Current learning rate: 0.00523 +2024-11-22 09:03:08.097458: train_loss -0.7946 +2024-11-22 09:03:08.097676: val_loss -0.7218 +2024-11-22 09:03:08.097819: Pseudo dice [0.8487] +2024-11-22 09:03:08.097898: Epoch time: 19.77 s +2024-11-22 09:03:08.968935: +2024-11-22 09:03:08.969144: Epoch 4105 +2024-11-22 09:03:08.969264: Current learning rate: 0.00523 +2024-11-22 09:03:26.989580: train_loss -0.7934 +2024-11-22 09:03:26.989811: val_loss -0.7503 +2024-11-22 09:03:26.989974: Pseudo dice [0.8396] +2024-11-22 09:03:26.990058: Epoch time: 18.02 s +2024-11-22 09:03:27.960010: +2024-11-22 09:03:27.960215: Epoch 4106 +2024-11-22 09:03:27.960340: Current learning rate: 0.00523 +2024-11-22 09:03:47.020835: train_loss -0.7908 +2024-11-22 09:03:47.021096: val_loss -0.7392 +2024-11-22 09:03:47.021172: Pseudo dice [0.8257] +2024-11-22 09:03:47.021256: Epoch time: 19.06 s +2024-11-22 09:03:47.919762: +2024-11-22 09:03:47.919997: Epoch 4107 +2024-11-22 09:03:47.920112: Current learning rate: 0.00523 +2024-11-22 09:04:05.521061: train_loss -0.7929 +2024-11-22 09:04:05.521294: val_loss -0.7739 +2024-11-22 09:04:05.521368: Pseudo dice [0.8354] +2024-11-22 09:04:05.521444: Epoch time: 17.6 s +2024-11-22 09:04:06.388687: +2024-11-22 09:04:06.388889: Epoch 4108 +2024-11-22 09:04:06.389006: Current learning rate: 0.00523 +2024-11-22 09:04:23.676140: train_loss -0.7938 +2024-11-22 09:04:23.676361: val_loss -0.76 +2024-11-22 09:04:23.676439: Pseudo dice [0.8346] +2024-11-22 09:04:23.676518: Epoch time: 17.29 s +2024-11-22 09:04:24.540819: +2024-11-22 09:04:24.541034: Epoch 4109 +2024-11-22 09:04:24.541146: Current learning rate: 0.00523 +2024-11-22 09:04:44.167806: train_loss -0.7981 +2024-11-22 09:04:44.168031: val_loss -0.7653 +2024-11-22 09:04:44.168106: Pseudo dice [0.8591] +2024-11-22 09:04:44.168183: Epoch time: 19.63 s +2024-11-22 09:04:45.034471: +2024-11-22 09:04:45.034683: Epoch 4110 +2024-11-22 09:04:45.034804: Current learning rate: 0.00523 +2024-11-22 09:05:03.507461: train_loss -0.7971 +2024-11-22 09:05:03.507711: val_loss -0.7309 +2024-11-22 09:05:03.507786: Pseudo dice [0.801] +2024-11-22 09:05:03.508123: Epoch time: 18.47 s +2024-11-22 09:05:04.768717: +2024-11-22 09:05:04.768942: Epoch 4111 +2024-11-22 09:05:04.769063: Current learning rate: 0.00522 +2024-11-22 09:05:23.666756: train_loss -0.7976 +2024-11-22 09:05:23.667040: val_loss -0.7268 +2024-11-22 09:05:23.667119: Pseudo dice [0.819] +2024-11-22 09:05:23.667197: Epoch time: 18.9 s +2024-11-22 09:05:24.635066: +2024-11-22 09:05:24.635276: Epoch 4112 +2024-11-22 09:05:24.635387: Current learning rate: 0.00522 +2024-11-22 09:05:43.802564: train_loss -0.7925 +2024-11-22 09:05:43.802790: val_loss -0.7288 +2024-11-22 09:05:43.802864: Pseudo dice [0.8225] +2024-11-22 09:05:43.802942: Epoch time: 19.17 s +2024-11-22 09:05:44.672227: +2024-11-22 09:05:44.672451: Epoch 4113 +2024-11-22 09:05:44.672563: Current learning rate: 0.00522 +2024-11-22 09:06:04.672941: train_loss -0.7886 +2024-11-22 09:06:04.673176: val_loss -0.7381 +2024-11-22 09:06:04.673259: Pseudo dice [0.864] +2024-11-22 09:06:04.673338: Epoch time: 20.0 s +2024-11-22 09:06:05.593796: +2024-11-22 09:06:05.594102: Epoch 4114 +2024-11-22 09:06:05.594213: Current learning rate: 0.00522 +2024-11-22 09:06:25.097873: train_loss -0.7838 +2024-11-22 09:06:25.098172: val_loss -0.7361 +2024-11-22 09:06:25.098259: Pseudo dice [0.8272] +2024-11-22 09:06:25.098346: Epoch time: 19.5 s +2024-11-22 09:06:26.040870: +2024-11-22 09:06:26.041098: Epoch 4115 +2024-11-22 09:06:26.041215: Current learning rate: 0.00522 +2024-11-22 09:06:45.393929: train_loss -0.7876 +2024-11-22 09:06:45.394159: val_loss -0.7414 +2024-11-22 09:06:45.394237: Pseudo dice [0.8223] +2024-11-22 09:06:45.394315: Epoch time: 19.35 s +2024-11-22 09:06:46.311216: +2024-11-22 09:06:46.311430: Epoch 4116 +2024-11-22 09:06:46.311543: Current learning rate: 0.00522 +2024-11-22 09:07:05.368709: train_loss -0.7826 +2024-11-22 09:07:05.368933: val_loss -0.738 +2024-11-22 09:07:05.369020: Pseudo dice [0.8534] +2024-11-22 09:07:05.369101: Epoch time: 19.06 s +2024-11-22 09:07:06.400183: +2024-11-22 09:07:06.400419: Epoch 4117 +2024-11-22 09:07:06.400531: Current learning rate: 0.00522 +2024-11-22 09:07:25.231801: train_loss -0.7908 +2024-11-22 09:07:25.232043: val_loss -0.7594 +2024-11-22 09:07:25.232127: Pseudo dice [0.8552] +2024-11-22 09:07:25.232211: Epoch time: 18.83 s +2024-11-22 09:07:26.268421: +2024-11-22 09:07:26.268619: Epoch 4118 +2024-11-22 09:07:26.268734: Current learning rate: 0.00522 +2024-11-22 09:07:45.057156: train_loss -0.7909 +2024-11-22 09:07:45.057394: val_loss -0.7341 +2024-11-22 09:07:45.057471: Pseudo dice [0.8324] +2024-11-22 09:07:45.057550: Epoch time: 18.79 s +2024-11-22 09:07:45.925393: +2024-11-22 09:07:45.925605: Epoch 4119 +2024-11-22 09:07:45.925715: Current learning rate: 0.00522 +2024-11-22 09:08:05.944531: train_loss -0.7787 +2024-11-22 09:08:05.945728: val_loss -0.7592 +2024-11-22 09:08:05.945806: Pseudo dice [0.8473] +2024-11-22 09:08:05.945882: Epoch time: 20.02 s +2024-11-22 09:08:06.810847: +2024-11-22 09:08:06.811074: Epoch 4120 +2024-11-22 09:08:06.811195: Current learning rate: 0.00521 +2024-11-22 09:08:26.592775: train_loss -0.7955 +2024-11-22 09:08:26.593011: val_loss -0.7665 +2024-11-22 09:08:26.593089: Pseudo dice [0.845] +2024-11-22 09:08:26.593166: Epoch time: 19.78 s +2024-11-22 09:08:27.457907: +2024-11-22 09:08:27.458122: Epoch 4121 +2024-11-22 09:08:27.458228: Current learning rate: 0.00521 +2024-11-22 09:08:45.687978: train_loss -0.8036 +2024-11-22 09:08:45.688211: val_loss -0.7502 +2024-11-22 09:08:45.690471: Pseudo dice [0.8593] +2024-11-22 09:08:45.690631: Epoch time: 18.23 s +2024-11-22 09:08:46.633840: +2024-11-22 09:08:46.634090: Epoch 4122 +2024-11-22 09:08:46.634213: Current learning rate: 0.00521 +2024-11-22 09:09:05.017558: train_loss -0.7984 +2024-11-22 09:09:05.018922: val_loss -0.7479 +2024-11-22 09:09:05.019025: Pseudo dice [0.8463] +2024-11-22 09:09:05.019107: Epoch time: 18.38 s +2024-11-22 09:09:06.353786: +2024-11-22 09:09:06.354017: Epoch 4123 +2024-11-22 09:09:06.354128: Current learning rate: 0.00521 +2024-11-22 09:09:25.325753: train_loss -0.7922 +2024-11-22 09:09:25.325987: val_loss -0.749 +2024-11-22 09:09:25.326072: Pseudo dice [0.834] +2024-11-22 09:09:25.326150: Epoch time: 18.97 s +2024-11-22 09:09:26.187004: +2024-11-22 09:09:26.187206: Epoch 4124 +2024-11-22 09:09:26.187323: Current learning rate: 0.00521 +2024-11-22 09:09:46.135093: train_loss -0.7874 +2024-11-22 09:09:46.135344: val_loss -0.7518 +2024-11-22 09:09:46.135429: Pseudo dice [0.816] +2024-11-22 09:09:46.135564: Epoch time: 19.95 s +2024-11-22 09:09:47.021013: +2024-11-22 09:09:47.021334: Epoch 4125 +2024-11-22 09:09:47.021448: Current learning rate: 0.00521 +2024-11-22 09:10:05.321649: train_loss -0.8018 +2024-11-22 09:10:05.321859: val_loss -0.7888 +2024-11-22 09:10:05.321934: Pseudo dice [0.8613] +2024-11-22 09:10:05.322017: Epoch time: 18.3 s +2024-11-22 09:10:06.192867: +2024-11-22 09:10:06.193136: Epoch 4126 +2024-11-22 09:10:06.193256: Current learning rate: 0.00521 +2024-11-22 09:10:25.751130: train_loss -0.7957 +2024-11-22 09:10:25.751344: val_loss -0.7666 +2024-11-22 09:10:25.751419: Pseudo dice [0.8491] +2024-11-22 09:10:25.751495: Epoch time: 19.56 s +2024-11-22 09:10:26.606232: +2024-11-22 09:10:26.606439: Epoch 4127 +2024-11-22 09:10:26.606551: Current learning rate: 0.00521 +2024-11-22 09:10:46.038772: train_loss -0.7728 +2024-11-22 09:10:46.041180: val_loss -0.7301 +2024-11-22 09:10:46.041312: Pseudo dice [0.8333] +2024-11-22 09:10:46.041393: Epoch time: 19.43 s +2024-11-22 09:10:46.989678: +2024-11-22 09:10:46.989881: Epoch 4128 +2024-11-22 09:10:46.990001: Current learning rate: 0.0052 +2024-11-22 09:11:05.290550: train_loss -0.7905 +2024-11-22 09:11:05.290777: val_loss -0.7437 +2024-11-22 09:11:05.290850: Pseudo dice [0.8354] +2024-11-22 09:11:05.290927: Epoch time: 18.3 s +2024-11-22 09:11:06.272868: +2024-11-22 09:11:06.273083: Epoch 4129 +2024-11-22 09:11:06.273199: Current learning rate: 0.0052 +2024-11-22 09:11:25.375560: train_loss -0.7826 +2024-11-22 09:11:25.375816: val_loss -0.7348 +2024-11-22 09:11:25.375897: Pseudo dice [0.8397] +2024-11-22 09:11:25.375982: Epoch time: 19.1 s +2024-11-22 09:11:26.234305: +2024-11-22 09:11:26.234508: Epoch 4130 +2024-11-22 09:11:26.234617: Current learning rate: 0.0052 +2024-11-22 09:11:44.876138: train_loss -0.7918 +2024-11-22 09:11:44.876386: val_loss -0.7621 +2024-11-22 09:11:44.876468: Pseudo dice [0.8448] +2024-11-22 09:11:44.876545: Epoch time: 18.64 s +2024-11-22 09:11:45.750186: +2024-11-22 09:11:45.750396: Epoch 4131 +2024-11-22 09:11:45.750507: Current learning rate: 0.0052 +2024-11-22 09:12:04.917502: train_loss -0.7984 +2024-11-22 09:12:04.917719: val_loss -0.7483 +2024-11-22 09:12:04.917797: Pseudo dice [0.822] +2024-11-22 09:12:04.917876: Epoch time: 19.17 s +2024-11-22 09:12:05.852170: +2024-11-22 09:12:05.852363: Epoch 4132 +2024-11-22 09:12:05.852475: Current learning rate: 0.0052 +2024-11-22 09:12:24.344333: train_loss -0.7847 +2024-11-22 09:12:24.344540: val_loss -0.7363 +2024-11-22 09:12:24.344644: Pseudo dice [0.8127] +2024-11-22 09:12:24.344721: Epoch time: 18.49 s +2024-11-22 09:12:25.207526: +2024-11-22 09:12:25.207733: Epoch 4133 +2024-11-22 09:12:25.207849: Current learning rate: 0.0052 +2024-11-22 09:12:43.627165: train_loss -0.7904 +2024-11-22 09:12:43.627424: val_loss -0.7367 +2024-11-22 09:12:43.629703: Pseudo dice [0.8385] +2024-11-22 09:12:43.629803: Epoch time: 18.42 s +2024-11-22 09:12:44.690788: +2024-11-22 09:12:44.690999: Epoch 4134 +2024-11-22 09:12:44.691109: Current learning rate: 0.0052 +2024-11-22 09:13:03.178985: train_loss -0.7906 +2024-11-22 09:13:03.184360: val_loss -0.7545 +2024-11-22 09:13:03.184504: Pseudo dice [0.8532] +2024-11-22 09:13:03.184590: Epoch time: 18.49 s +2024-11-22 09:13:04.593854: +2024-11-22 09:13:04.594078: Epoch 4135 +2024-11-22 09:13:04.594186: Current learning rate: 0.0052 +2024-11-22 09:13:23.000850: train_loss -0.7992 +2024-11-22 09:13:23.006259: val_loss -0.7413 +2024-11-22 09:13:23.006383: Pseudo dice [0.8451] +2024-11-22 09:13:23.006468: Epoch time: 18.41 s +2024-11-22 09:13:23.959553: +2024-11-22 09:13:23.959773: Epoch 4136 +2024-11-22 09:13:23.959883: Current learning rate: 0.00519 +2024-11-22 09:13:41.443841: train_loss -0.7998 +2024-11-22 09:13:41.444073: val_loss -0.7026 +2024-11-22 09:13:41.444157: Pseudo dice [0.8133] +2024-11-22 09:13:41.449766: Epoch time: 17.49 s +2024-11-22 09:13:42.348898: +2024-11-22 09:13:42.349171: Epoch 4137 +2024-11-22 09:13:42.349285: Current learning rate: 0.00519 +2024-11-22 09:14:01.955709: train_loss -0.7931 +2024-11-22 09:14:01.961098: val_loss -0.7433 +2024-11-22 09:14:01.961307: Pseudo dice [0.8305] +2024-11-22 09:14:01.961405: Epoch time: 19.61 s +2024-11-22 09:14:02.866211: +2024-11-22 09:14:02.866461: Epoch 4138 +2024-11-22 09:14:02.866577: Current learning rate: 0.00519 +2024-11-22 09:14:21.836325: train_loss -0.7909 +2024-11-22 09:14:21.836548: val_loss -0.7443 +2024-11-22 09:14:21.836628: Pseudo dice [0.8481] +2024-11-22 09:14:21.836708: Epoch time: 18.97 s +2024-11-22 09:14:22.708411: +2024-11-22 09:14:22.708631: Epoch 4139 +2024-11-22 09:14:22.708742: Current learning rate: 0.00519 +2024-11-22 09:14:40.767450: train_loss -0.7867 +2024-11-22 09:14:40.767685: val_loss -0.7236 +2024-11-22 09:14:40.767761: Pseudo dice [0.8383] +2024-11-22 09:14:40.767838: Epoch time: 18.06 s +2024-11-22 09:14:41.634212: +2024-11-22 09:14:41.634427: Epoch 4140 +2024-11-22 09:14:41.634535: Current learning rate: 0.00519 +2024-11-22 09:15:00.061857: train_loss -0.7934 +2024-11-22 09:15:00.062075: val_loss -0.7743 +2024-11-22 09:15:00.062151: Pseudo dice [0.8569] +2024-11-22 09:15:00.062226: Epoch time: 18.43 s +2024-11-22 09:15:00.927739: +2024-11-22 09:15:00.927954: Epoch 4141 +2024-11-22 09:15:00.928071: Current learning rate: 0.00519 +2024-11-22 09:15:19.573661: train_loss -0.7919 +2024-11-22 09:15:19.573966: val_loss -0.7276 +2024-11-22 09:15:19.574048: Pseudo dice [0.8272] +2024-11-22 09:15:19.574169: Epoch time: 18.65 s +2024-11-22 09:15:20.453303: +2024-11-22 09:15:20.453510: Epoch 4142 +2024-11-22 09:15:20.453625: Current learning rate: 0.00519 +2024-11-22 09:15:39.338305: train_loss -0.781 +2024-11-22 09:15:39.338538: val_loss -0.7206 +2024-11-22 09:15:39.338621: Pseudo dice [0.8312] +2024-11-22 09:15:39.338707: Epoch time: 18.89 s +2024-11-22 09:15:40.206275: +2024-11-22 09:15:40.206472: Epoch 4143 +2024-11-22 09:15:40.206584: Current learning rate: 0.00519 +2024-11-22 09:15:58.627380: train_loss -0.7854 +2024-11-22 09:15:58.627606: val_loss -0.7292 +2024-11-22 09:15:58.629869: Pseudo dice [0.85] +2024-11-22 09:15:58.629978: Epoch time: 18.42 s +2024-11-22 09:15:59.533378: +2024-11-22 09:15:59.533571: Epoch 4144 +2024-11-22 09:15:59.533685: Current learning rate: 0.00518 +2024-11-22 09:16:17.939206: train_loss -0.7829 +2024-11-22 09:16:17.939422: val_loss -0.753 +2024-11-22 09:16:17.939502: Pseudo dice [0.8523] +2024-11-22 09:16:17.939579: Epoch time: 18.41 s +2024-11-22 09:16:18.838059: +2024-11-22 09:16:18.838323: Epoch 4145 +2024-11-22 09:16:18.838437: Current learning rate: 0.00518 +2024-11-22 09:16:36.841100: train_loss -0.7907 +2024-11-22 09:16:36.841353: val_loss -0.7171 +2024-11-22 09:16:36.841429: Pseudo dice [0.8414] +2024-11-22 09:16:36.841513: Epoch time: 18.0 s +2024-11-22 09:16:37.715104: +2024-11-22 09:16:37.715383: Epoch 4146 +2024-11-22 09:16:37.715503: Current learning rate: 0.00518 +2024-11-22 09:16:55.705656: train_loss -0.798 +2024-11-22 09:16:55.705893: val_loss -0.7462 +2024-11-22 09:16:55.705973: Pseudo dice [0.8526] +2024-11-22 09:16:55.706059: Epoch time: 17.99 s +2024-11-22 09:16:57.002970: +2024-11-22 09:16:57.003222: Epoch 4147 +2024-11-22 09:16:57.003327: Current learning rate: 0.00518 +2024-11-22 09:17:15.330062: train_loss -0.7898 +2024-11-22 09:17:15.330283: val_loss -0.7594 +2024-11-22 09:17:15.330359: Pseudo dice [0.8616] +2024-11-22 09:17:15.330438: Epoch time: 18.33 s +2024-11-22 09:17:16.202358: +2024-11-22 09:17:16.202567: Epoch 4148 +2024-11-22 09:17:16.202675: Current learning rate: 0.00518 +2024-11-22 09:17:35.373806: train_loss -0.7899 +2024-11-22 09:17:35.374042: val_loss -0.7039 +2024-11-22 09:17:35.374117: Pseudo dice [0.8381] +2024-11-22 09:17:35.374197: Epoch time: 19.17 s +2024-11-22 09:17:36.254436: +2024-11-22 09:17:36.254654: Epoch 4149 +2024-11-22 09:17:36.254770: Current learning rate: 0.00518 +2024-11-22 09:17:54.747481: train_loss -0.7971 +2024-11-22 09:17:54.747728: val_loss -0.7514 +2024-11-22 09:17:54.747804: Pseudo dice [0.8422] +2024-11-22 09:17:54.747898: Epoch time: 18.49 s +2024-11-22 09:17:55.881224: +2024-11-22 09:17:55.881432: Epoch 4150 +2024-11-22 09:17:55.881538: Current learning rate: 0.00518 +2024-11-22 09:18:13.993963: train_loss -0.8034 +2024-11-22 09:18:13.994188: val_loss -0.7375 +2024-11-22 09:18:13.994264: Pseudo dice [0.8495] +2024-11-22 09:18:13.994340: Epoch time: 18.11 s +2024-11-22 09:18:14.943511: +2024-11-22 09:18:14.943742: Epoch 4151 +2024-11-22 09:18:14.943849: Current learning rate: 0.00518 +2024-11-22 09:18:33.201876: train_loss -0.7996 +2024-11-22 09:18:33.202123: val_loss -0.7334 +2024-11-22 09:18:33.202209: Pseudo dice [0.854] +2024-11-22 09:18:33.202286: Epoch time: 18.26 s +2024-11-22 09:18:34.065228: +2024-11-22 09:18:34.065442: Epoch 4152 +2024-11-22 09:18:34.065546: Current learning rate: 0.00518 +2024-11-22 09:18:53.554020: train_loss -0.8037 +2024-11-22 09:18:53.554241: val_loss -0.7592 +2024-11-22 09:18:53.554317: Pseudo dice [0.8594] +2024-11-22 09:18:53.554396: Epoch time: 19.49 s +2024-11-22 09:18:54.424890: +2024-11-22 09:18:54.425119: Epoch 4153 +2024-11-22 09:18:54.425238: Current learning rate: 0.00517 +2024-11-22 09:19:13.188865: train_loss -0.7894 +2024-11-22 09:19:13.189133: val_loss -0.7545 +2024-11-22 09:19:13.189212: Pseudo dice [0.8371] +2024-11-22 09:19:13.189297: Epoch time: 18.76 s +2024-11-22 09:19:14.061296: +2024-11-22 09:19:14.061492: Epoch 4154 +2024-11-22 09:19:14.061606: Current learning rate: 0.00517 +2024-11-22 09:19:32.064783: train_loss -0.7922 +2024-11-22 09:19:32.065012: val_loss -0.7661 +2024-11-22 09:19:32.065094: Pseudo dice [0.8681] +2024-11-22 09:19:32.065171: Epoch time: 18.0 s +2024-11-22 09:19:32.934115: +2024-11-22 09:19:32.934380: Epoch 4155 +2024-11-22 09:19:32.934495: Current learning rate: 0.00517 +2024-11-22 09:19:51.409454: train_loss -0.7995 +2024-11-22 09:19:51.409686: val_loss -0.7437 +2024-11-22 09:19:51.409761: Pseudo dice [0.8415] +2024-11-22 09:19:51.409837: Epoch time: 18.48 s +2024-11-22 09:19:52.324705: +2024-11-22 09:19:52.324935: Epoch 4156 +2024-11-22 09:19:52.325051: Current learning rate: 0.00517 +2024-11-22 09:20:10.921037: train_loss -0.796 +2024-11-22 09:20:10.926421: val_loss -0.7425 +2024-11-22 09:20:10.926576: Pseudo dice [0.8403] +2024-11-22 09:20:10.926661: Epoch time: 18.6 s +2024-11-22 09:20:11.866372: +2024-11-22 09:20:11.866606: Epoch 4157 +2024-11-22 09:20:11.866716: Current learning rate: 0.00517 +2024-11-22 09:20:29.783598: train_loss -0.8036 +2024-11-22 09:20:29.783835: val_loss -0.7125 +2024-11-22 09:20:29.783914: Pseudo dice [0.8472] +2024-11-22 09:20:29.784000: Epoch time: 17.92 s +2024-11-22 09:20:30.655630: +2024-11-22 09:20:30.655822: Epoch 4158 +2024-11-22 09:20:30.655932: Current learning rate: 0.00517 +2024-11-22 09:20:49.163248: train_loss -0.7901 +2024-11-22 09:20:49.163476: val_loss -0.7029 +2024-11-22 09:20:49.163550: Pseudo dice [0.82] +2024-11-22 09:20:49.163630: Epoch time: 18.51 s +2024-11-22 09:20:50.480291: +2024-11-22 09:20:50.480513: Epoch 4159 +2024-11-22 09:20:50.480619: Current learning rate: 0.00517 +2024-11-22 09:21:09.345984: train_loss -0.805 +2024-11-22 09:21:09.346212: val_loss -0.7417 +2024-11-22 09:21:09.346286: Pseudo dice [0.8158] +2024-11-22 09:21:09.346363: Epoch time: 18.87 s +2024-11-22 09:21:10.295294: +2024-11-22 09:21:10.295526: Epoch 4160 +2024-11-22 09:21:10.295636: Current learning rate: 0.00517 +2024-11-22 09:21:27.695973: train_loss -0.7928 +2024-11-22 09:21:27.696237: val_loss -0.7427 +2024-11-22 09:21:27.698526: Pseudo dice [0.8417] +2024-11-22 09:21:27.698627: Epoch time: 17.4 s +2024-11-22 09:21:28.734519: +2024-11-22 09:21:28.734723: Epoch 4161 +2024-11-22 09:21:28.734835: Current learning rate: 0.00516 +2024-11-22 09:21:46.770998: train_loss -0.7947 +2024-11-22 09:21:46.771222: val_loss -0.7416 +2024-11-22 09:21:46.771302: Pseudo dice [0.8467] +2024-11-22 09:21:46.771377: Epoch time: 18.04 s +2024-11-22 09:21:47.641772: +2024-11-22 09:21:47.642067: Epoch 4162 +2024-11-22 09:21:47.642183: Current learning rate: 0.00516 +2024-11-22 09:22:05.998034: train_loss -0.7842 +2024-11-22 09:22:05.998269: val_loss -0.716 +2024-11-22 09:22:05.998347: Pseudo dice [0.826] +2024-11-22 09:22:05.998701: Epoch time: 18.36 s +2024-11-22 09:22:06.863970: +2024-11-22 09:22:06.864187: Epoch 4163 +2024-11-22 09:22:06.864301: Current learning rate: 0.00516 +2024-11-22 09:22:25.907368: train_loss -0.7955 +2024-11-22 09:22:25.908962: val_loss -0.7702 +2024-11-22 09:22:25.909077: Pseudo dice [0.8427] +2024-11-22 09:22:25.909162: Epoch time: 19.04 s +2024-11-22 09:22:26.781710: +2024-11-22 09:22:26.781927: Epoch 4164 +2024-11-22 09:22:26.782043: Current learning rate: 0.00516 +2024-11-22 09:22:45.258155: train_loss -0.794 +2024-11-22 09:22:45.258408: val_loss -0.7491 +2024-11-22 09:22:45.260730: Pseudo dice [0.843] +2024-11-22 09:22:45.260851: Epoch time: 18.48 s +2024-11-22 09:22:46.261838: +2024-11-22 09:22:46.262062: Epoch 4165 +2024-11-22 09:22:46.262174: Current learning rate: 0.00516 +2024-11-22 09:23:04.912750: train_loss -0.8024 +2024-11-22 09:23:04.912996: val_loss -0.761 +2024-11-22 09:23:04.913074: Pseudo dice [0.8423] +2024-11-22 09:23:04.913152: Epoch time: 18.65 s +2024-11-22 09:23:05.889210: +2024-11-22 09:23:05.889402: Epoch 4166 +2024-11-22 09:23:05.889516: Current learning rate: 0.00516 +2024-11-22 09:23:24.249319: train_loss -0.7875 +2024-11-22 09:23:24.249543: val_loss -0.7477 +2024-11-22 09:23:24.249621: Pseudo dice [0.8441] +2024-11-22 09:23:24.249702: Epoch time: 18.36 s +2024-11-22 09:23:25.120367: +2024-11-22 09:23:25.120593: Epoch 4167 +2024-11-22 09:23:25.120713: Current learning rate: 0.00516 +2024-11-22 09:23:43.966975: train_loss -0.7915 +2024-11-22 09:23:43.967229: val_loss -0.7735 +2024-11-22 09:23:43.967309: Pseudo dice [0.8517] +2024-11-22 09:23:43.967387: Epoch time: 18.85 s +2024-11-22 09:23:44.837324: +2024-11-22 09:23:44.837610: Epoch 4168 +2024-11-22 09:23:44.837723: Current learning rate: 0.00516 +2024-11-22 09:24:03.445473: train_loss -0.7943 +2024-11-22 09:24:03.445779: val_loss -0.7159 +2024-11-22 09:24:03.445858: Pseudo dice [0.8303] +2024-11-22 09:24:03.445947: Epoch time: 18.61 s +2024-11-22 09:24:04.315950: +2024-11-22 09:24:04.316151: Epoch 4169 +2024-11-22 09:24:04.316261: Current learning rate: 0.00515 +2024-11-22 09:24:23.437968: train_loss -0.791 +2024-11-22 09:24:23.438184: val_loss -0.7233 +2024-11-22 09:24:23.438260: Pseudo dice [0.8413] +2024-11-22 09:24:23.438333: Epoch time: 19.12 s +2024-11-22 09:24:24.426112: +2024-11-22 09:24:24.426317: Epoch 4170 +2024-11-22 09:24:24.426428: Current learning rate: 0.00515 +2024-11-22 09:24:43.899697: train_loss -0.7889 +2024-11-22 09:24:43.899915: val_loss -0.7493 +2024-11-22 09:24:43.900002: Pseudo dice [0.8467] +2024-11-22 09:24:43.900083: Epoch time: 19.47 s +2024-11-22 09:24:45.193876: +2024-11-22 09:24:45.194106: Epoch 4171 +2024-11-22 09:24:45.194220: Current learning rate: 0.00515 +2024-11-22 09:25:04.050876: train_loss -0.7941 +2024-11-22 09:25:04.051133: val_loss -0.7408 +2024-11-22 09:25:04.051211: Pseudo dice [0.8236] +2024-11-22 09:25:04.051358: Epoch time: 18.86 s +2024-11-22 09:25:04.928587: +2024-11-22 09:25:04.928797: Epoch 4172 +2024-11-22 09:25:04.928909: Current learning rate: 0.00515 +2024-11-22 09:25:23.344537: train_loss -0.7905 +2024-11-22 09:25:23.344761: val_loss -0.7844 +2024-11-22 09:25:23.344837: Pseudo dice [0.8559] +2024-11-22 09:25:23.344915: Epoch time: 18.42 s +2024-11-22 09:25:24.267631: +2024-11-22 09:25:24.267859: Epoch 4173 +2024-11-22 09:25:24.267971: Current learning rate: 0.00515 +2024-11-22 09:25:42.710104: train_loss -0.7956 +2024-11-22 09:25:42.710352: val_loss -0.7602 +2024-11-22 09:25:42.710431: Pseudo dice [0.8282] +2024-11-22 09:25:42.710512: Epoch time: 18.44 s +2024-11-22 09:25:43.632519: +2024-11-22 09:25:43.632749: Epoch 4174 +2024-11-22 09:25:43.632859: Current learning rate: 0.00515 +2024-11-22 09:26:03.254113: train_loss -0.7952 +2024-11-22 09:26:03.254347: val_loss -0.7158 +2024-11-22 09:26:03.254420: Pseudo dice [0.8096] +2024-11-22 09:26:03.254496: Epoch time: 19.62 s +2024-11-22 09:26:04.138401: +2024-11-22 09:26:04.138624: Epoch 4175 +2024-11-22 09:26:04.138742: Current learning rate: 0.00515 +2024-11-22 09:26:22.737629: train_loss -0.7928 +2024-11-22 09:26:22.737889: val_loss -0.7305 +2024-11-22 09:26:22.737983: Pseudo dice [0.8408] +2024-11-22 09:26:22.738127: Epoch time: 18.6 s +2024-11-22 09:26:23.692135: +2024-11-22 09:26:23.692397: Epoch 4176 +2024-11-22 09:26:23.692520: Current learning rate: 0.00515 +2024-11-22 09:26:43.123734: train_loss -0.7958 +2024-11-22 09:26:43.123946: val_loss -0.7614 +2024-11-22 09:26:43.124028: Pseudo dice [0.847] +2024-11-22 09:26:43.124106: Epoch time: 19.43 s +2024-11-22 09:26:44.188135: +2024-11-22 09:26:44.188496: Epoch 4177 +2024-11-22 09:26:44.188611: Current learning rate: 0.00514 +2024-11-22 09:27:02.780583: train_loss -0.798 +2024-11-22 09:27:02.780799: val_loss -0.7606 +2024-11-22 09:27:02.780872: Pseudo dice [0.855] +2024-11-22 09:27:02.780948: Epoch time: 18.59 s +2024-11-22 09:27:03.874225: +2024-11-22 09:27:03.874423: Epoch 4178 +2024-11-22 09:27:03.874531: Current learning rate: 0.00514 +2024-11-22 09:27:23.727254: train_loss -0.7991 +2024-11-22 09:27:23.727466: val_loss -0.7407 +2024-11-22 09:27:23.727543: Pseudo dice [0.8319] +2024-11-22 09:27:23.727618: Epoch time: 19.85 s +2024-11-22 09:27:24.592544: +2024-11-22 09:27:24.592757: Epoch 4179 +2024-11-22 09:27:24.592883: Current learning rate: 0.00514 +2024-11-22 09:27:42.824178: train_loss -0.7972 +2024-11-22 09:27:42.824435: val_loss -0.735 +2024-11-22 09:27:42.824515: Pseudo dice [0.8463] +2024-11-22 09:27:42.824597: Epoch time: 18.23 s +2024-11-22 09:27:43.704960: +2024-11-22 09:27:43.705186: Epoch 4180 +2024-11-22 09:27:43.705299: Current learning rate: 0.00514 +2024-11-22 09:28:02.486310: train_loss -0.8048 +2024-11-22 09:28:02.486529: val_loss -0.7291 +2024-11-22 09:28:02.486605: Pseudo dice [0.8155] +2024-11-22 09:28:02.486680: Epoch time: 18.78 s +2024-11-22 09:28:03.354098: +2024-11-22 09:28:03.354307: Epoch 4181 +2024-11-22 09:28:03.354419: Current learning rate: 0.00514 +2024-11-22 09:28:22.622793: train_loss -0.7791 +2024-11-22 09:28:22.623017: val_loss -0.7754 +2024-11-22 09:28:22.623095: Pseudo dice [0.8565] +2024-11-22 09:28:22.623173: Epoch time: 19.27 s +2024-11-22 09:28:23.492003: +2024-11-22 09:28:23.492207: Epoch 4182 +2024-11-22 09:28:23.492321: Current learning rate: 0.00514 +2024-11-22 09:28:43.018313: train_loss -0.7873 +2024-11-22 09:28:43.018530: val_loss -0.7648 +2024-11-22 09:28:43.020852: Pseudo dice [0.8455] +2024-11-22 09:28:43.020966: Epoch time: 19.53 s +2024-11-22 09:28:44.307084: +2024-11-22 09:28:44.307376: Epoch 4183 +2024-11-22 09:28:44.307494: Current learning rate: 0.00514 +2024-11-22 09:29:02.846591: train_loss -0.7931 +2024-11-22 09:29:02.846850: val_loss -0.7488 +2024-11-22 09:29:02.846927: Pseudo dice [0.8598] +2024-11-22 09:29:02.847052: Epoch time: 18.54 s +2024-11-22 09:29:03.833971: +2024-11-22 09:29:03.834255: Epoch 4184 +2024-11-22 09:29:03.834370: Current learning rate: 0.00514 +2024-11-22 09:29:23.665445: train_loss -0.7855 +2024-11-22 09:29:23.665671: val_loss -0.7392 +2024-11-22 09:29:23.665744: Pseudo dice [0.8604] +2024-11-22 09:29:23.665823: Epoch time: 19.83 s +2024-11-22 09:29:24.719465: +2024-11-22 09:29:24.719680: Epoch 4185 +2024-11-22 09:29:24.719795: Current learning rate: 0.00514 +2024-11-22 09:29:43.907361: train_loss -0.7879 +2024-11-22 09:29:43.907581: val_loss -0.7501 +2024-11-22 09:29:43.907655: Pseudo dice [0.8393] +2024-11-22 09:29:43.907733: Epoch time: 19.19 s +2024-11-22 09:29:44.778145: +2024-11-22 09:29:44.778378: Epoch 4186 +2024-11-22 09:29:44.778494: Current learning rate: 0.00513 +2024-11-22 09:30:02.720149: train_loss -0.7953 +2024-11-22 09:30:02.720368: val_loss -0.7525 +2024-11-22 09:30:02.720443: Pseudo dice [0.8425] +2024-11-22 09:30:02.720519: Epoch time: 17.94 s +2024-11-22 09:30:03.733622: +2024-11-22 09:30:03.733846: Epoch 4187 +2024-11-22 09:30:03.733958: Current learning rate: 0.00513 +2024-11-22 09:30:23.080541: train_loss -0.7933 +2024-11-22 09:30:23.085965: val_loss -0.761 +2024-11-22 09:30:23.086143: Pseudo dice [0.8536] +2024-11-22 09:30:23.086238: Epoch time: 19.35 s +2024-11-22 09:30:23.976151: +2024-11-22 09:30:23.976393: Epoch 4188 +2024-11-22 09:30:23.976508: Current learning rate: 0.00513 +2024-11-22 09:30:41.662605: train_loss -0.7964 +2024-11-22 09:30:41.662820: val_loss -0.747 +2024-11-22 09:30:41.663144: Pseudo dice [0.8703] +2024-11-22 09:30:41.663231: Epoch time: 17.69 s +2024-11-22 09:30:42.529006: +2024-11-22 09:30:42.529293: Epoch 4189 +2024-11-22 09:30:42.529409: Current learning rate: 0.00513 +2024-11-22 09:31:01.218020: train_loss -0.7925 +2024-11-22 09:31:01.218233: val_loss -0.7701 +2024-11-22 09:31:01.218307: Pseudo dice [0.8472] +2024-11-22 09:31:01.218383: Epoch time: 18.69 s +2024-11-22 09:31:02.144801: +2024-11-22 09:31:02.145019: Epoch 4190 +2024-11-22 09:31:02.145131: Current learning rate: 0.00513 +2024-11-22 09:31:20.084652: train_loss -0.7899 +2024-11-22 09:31:20.084874: val_loss -0.7249 +2024-11-22 09:31:20.084948: Pseudo dice [0.8354] +2024-11-22 09:31:20.085043: Epoch time: 17.94 s +2024-11-22 09:31:20.948210: +2024-11-22 09:31:20.948424: Epoch 4191 +2024-11-22 09:31:20.948539: Current learning rate: 0.00513 +2024-11-22 09:31:39.654399: train_loss -0.7799 +2024-11-22 09:31:39.654638: val_loss -0.7507 +2024-11-22 09:31:39.654716: Pseudo dice [0.8158] +2024-11-22 09:31:39.654805: Epoch time: 18.71 s +2024-11-22 09:31:40.521319: +2024-11-22 09:31:40.521554: Epoch 4192 +2024-11-22 09:31:40.521676: Current learning rate: 0.00513 +2024-11-22 09:31:58.992766: train_loss -0.7804 +2024-11-22 09:31:58.993578: val_loss -0.7682 +2024-11-22 09:31:58.993660: Pseudo dice [0.8617] +2024-11-22 09:31:58.993743: Epoch time: 18.47 s +2024-11-22 09:31:59.854374: +2024-11-22 09:31:59.854614: Epoch 4193 +2024-11-22 09:31:59.854729: Current learning rate: 0.00513 +2024-11-22 09:32:18.305617: train_loss -0.7747 +2024-11-22 09:32:18.305835: val_loss -0.712 +2024-11-22 09:32:18.305914: Pseudo dice [0.8318] +2024-11-22 09:32:18.305997: Epoch time: 18.45 s +2024-11-22 09:32:19.354871: +2024-11-22 09:32:19.355110: Epoch 4194 +2024-11-22 09:32:19.355223: Current learning rate: 0.00512 +2024-11-22 09:32:37.618204: train_loss -0.776 +2024-11-22 09:32:37.618466: val_loss -0.7106 +2024-11-22 09:32:37.618544: Pseudo dice [0.8245] +2024-11-22 09:32:37.618635: Epoch time: 18.26 s +2024-11-22 09:32:38.906789: +2024-11-22 09:32:38.907020: Epoch 4195 +2024-11-22 09:32:38.907135: Current learning rate: 0.00512 +2024-11-22 09:32:58.230755: train_loss -0.7788 +2024-11-22 09:32:58.231032: val_loss -0.7374 +2024-11-22 09:32:58.231116: Pseudo dice [0.8471] +2024-11-22 09:32:58.231196: Epoch time: 19.32 s +2024-11-22 09:32:59.094656: +2024-11-22 09:32:59.094877: Epoch 4196 +2024-11-22 09:32:59.095000: Current learning rate: 0.00512 +2024-11-22 09:33:18.320427: train_loss -0.7874 +2024-11-22 09:33:18.320656: val_loss -0.7509 +2024-11-22 09:33:18.320740: Pseudo dice [0.8478] +2024-11-22 09:33:18.320823: Epoch time: 19.23 s +2024-11-22 09:33:19.283216: +2024-11-22 09:33:19.283449: Epoch 4197 +2024-11-22 09:33:19.283566: Current learning rate: 0.00512 +2024-11-22 09:33:36.469078: train_loss -0.7839 +2024-11-22 09:33:36.469338: val_loss -0.7842 +2024-11-22 09:33:36.469419: Pseudo dice [0.8662] +2024-11-22 09:33:36.469502: Epoch time: 17.19 s +2024-11-22 09:33:37.337345: +2024-11-22 09:33:37.337611: Epoch 4198 +2024-11-22 09:33:37.337723: Current learning rate: 0.00512 +2024-11-22 09:33:56.303236: train_loss -0.7992 +2024-11-22 09:33:56.303482: val_loss -0.7416 +2024-11-22 09:33:56.303565: Pseudo dice [0.8078] +2024-11-22 09:33:56.303647: Epoch time: 18.97 s +2024-11-22 09:33:57.171838: +2024-11-22 09:33:57.172066: Epoch 4199 +2024-11-22 09:33:57.172180: Current learning rate: 0.00512 +2024-11-22 09:34:16.287073: train_loss -0.7918 +2024-11-22 09:34:16.287304: val_loss -0.7503 +2024-11-22 09:34:16.287384: Pseudo dice [0.8447] +2024-11-22 09:34:16.287463: Epoch time: 19.12 s +2024-11-22 09:34:17.439762: +2024-11-22 09:34:17.439981: Epoch 4200 +2024-11-22 09:34:17.440103: Current learning rate: 0.00512 +2024-11-22 09:34:35.758767: train_loss -0.7939 +2024-11-22 09:34:35.759014: val_loss -0.746 +2024-11-22 09:34:35.759094: Pseudo dice [0.8408] +2024-11-22 09:34:35.759177: Epoch time: 18.32 s +2024-11-22 09:34:36.628958: +2024-11-22 09:34:36.629184: Epoch 4201 +2024-11-22 09:34:36.629298: Current learning rate: 0.00512 +2024-11-22 09:34:55.458110: train_loss -0.788 +2024-11-22 09:34:55.458345: val_loss -0.7555 +2024-11-22 09:34:55.458434: Pseudo dice [0.8349] +2024-11-22 09:34:55.458518: Epoch time: 18.83 s +2024-11-22 09:34:56.332776: +2024-11-22 09:34:56.333012: Epoch 4202 +2024-11-22 09:34:56.333127: Current learning rate: 0.00511 +2024-11-22 09:35:14.690273: train_loss -0.7852 +2024-11-22 09:35:14.690518: val_loss -0.7119 +2024-11-22 09:35:14.690595: Pseudo dice [0.8289] +2024-11-22 09:35:14.690674: Epoch time: 18.36 s +2024-11-22 09:35:15.563229: +2024-11-22 09:35:15.563447: Epoch 4203 +2024-11-22 09:35:15.563560: Current learning rate: 0.00511 +2024-11-22 09:35:34.203600: train_loss -0.7737 +2024-11-22 09:35:34.203832: val_loss -0.7169 +2024-11-22 09:35:34.203909: Pseudo dice [0.8406] +2024-11-22 09:35:34.203989: Epoch time: 18.64 s +2024-11-22 09:35:35.072373: +2024-11-22 09:35:35.072608: Epoch 4204 +2024-11-22 09:35:35.072717: Current learning rate: 0.00511 +2024-11-22 09:35:53.564234: train_loss -0.7794 +2024-11-22 09:35:53.564449: val_loss -0.6969 +2024-11-22 09:35:53.564522: Pseudo dice [0.8183] +2024-11-22 09:35:53.564597: Epoch time: 18.49 s +2024-11-22 09:35:54.433563: +2024-11-22 09:35:54.433766: Epoch 4205 +2024-11-22 09:35:54.433874: Current learning rate: 0.00511 +2024-11-22 09:36:12.570050: train_loss -0.7812 +2024-11-22 09:36:12.570298: val_loss -0.754 +2024-11-22 09:36:12.570374: Pseudo dice [0.8502] +2024-11-22 09:36:12.570459: Epoch time: 18.14 s +2024-11-22 09:36:13.476734: +2024-11-22 09:36:13.476962: Epoch 4206 +2024-11-22 09:36:13.477079: Current learning rate: 0.00511 +2024-11-22 09:36:31.494044: train_loss -0.7899 +2024-11-22 09:36:31.494325: val_loss -0.7425 +2024-11-22 09:36:31.494399: Pseudo dice [0.8539] +2024-11-22 09:36:31.494480: Epoch time: 18.02 s +2024-11-22 09:36:32.782948: +2024-11-22 09:36:32.783243: Epoch 4207 +2024-11-22 09:36:32.783356: Current learning rate: 0.00511 +2024-11-22 09:36:51.592521: train_loss -0.7974 +2024-11-22 09:36:51.592742: val_loss -0.7259 +2024-11-22 09:36:51.592818: Pseudo dice [0.812] +2024-11-22 09:36:51.592896: Epoch time: 18.81 s +2024-11-22 09:36:52.465394: +2024-11-22 09:36:52.465666: Epoch 4208 +2024-11-22 09:36:52.465781: Current learning rate: 0.00511 +2024-11-22 09:37:10.627942: train_loss -0.7758 +2024-11-22 09:37:10.628180: val_loss -0.7553 +2024-11-22 09:37:10.628261: Pseudo dice [0.8305] +2024-11-22 09:37:10.628349: Epoch time: 18.16 s +2024-11-22 09:37:11.496231: +2024-11-22 09:37:11.496481: Epoch 4209 +2024-11-22 09:37:11.496593: Current learning rate: 0.00511 +2024-11-22 09:37:30.779031: train_loss -0.782 +2024-11-22 09:37:30.779274: val_loss -0.7321 +2024-11-22 09:37:30.779347: Pseudo dice [0.8188] +2024-11-22 09:37:30.779429: Epoch time: 19.28 s +2024-11-22 09:37:31.648419: +2024-11-22 09:37:31.648657: Epoch 4210 +2024-11-22 09:37:31.648767: Current learning rate: 0.0051 +2024-11-22 09:37:49.668571: train_loss -0.7953 +2024-11-22 09:37:49.668792: val_loss -0.7454 +2024-11-22 09:37:49.668865: Pseudo dice [0.8382] +2024-11-22 09:37:49.668942: Epoch time: 18.02 s +2024-11-22 09:37:50.539377: +2024-11-22 09:37:50.539608: Epoch 4211 +2024-11-22 09:37:50.539726: Current learning rate: 0.0051 +2024-11-22 09:38:08.417149: train_loss -0.7823 +2024-11-22 09:38:08.417374: val_loss -0.7646 +2024-11-22 09:38:08.417452: Pseudo dice [0.8409] +2024-11-22 09:38:08.417529: Epoch time: 17.88 s +2024-11-22 09:38:09.292289: +2024-11-22 09:38:09.292505: Epoch 4212 +2024-11-22 09:38:09.292621: Current learning rate: 0.0051 +2024-11-22 09:38:28.552198: train_loss -0.7877 +2024-11-22 09:38:28.552483: val_loss -0.7397 +2024-11-22 09:38:28.552562: Pseudo dice [0.8583] +2024-11-22 09:38:28.552639: Epoch time: 19.26 s +2024-11-22 09:38:29.514569: +2024-11-22 09:38:29.514776: Epoch 4213 +2024-11-22 09:38:29.514890: Current learning rate: 0.0051 +2024-11-22 09:38:48.311157: train_loss -0.7947 +2024-11-22 09:38:48.311403: val_loss -0.7628 +2024-11-22 09:38:48.311485: Pseudo dice [0.8413] +2024-11-22 09:38:48.311573: Epoch time: 18.8 s +2024-11-22 09:38:49.184633: +2024-11-22 09:38:49.184847: Epoch 4214 +2024-11-22 09:38:49.184963: Current learning rate: 0.0051 +2024-11-22 09:39:07.362828: train_loss -0.7991 +2024-11-22 09:39:07.363084: val_loss -0.7538 +2024-11-22 09:39:07.363405: Pseudo dice [0.8343] +2024-11-22 09:39:07.363489: Epoch time: 18.18 s +2024-11-22 09:39:08.231267: +2024-11-22 09:39:08.231490: Epoch 4215 +2024-11-22 09:39:08.231607: Current learning rate: 0.0051 +2024-11-22 09:39:26.260694: train_loss -0.7947 +2024-11-22 09:39:26.260916: val_loss -0.7549 +2024-11-22 09:39:26.261010: Pseudo dice [0.8428] +2024-11-22 09:39:26.261092: Epoch time: 18.03 s +2024-11-22 09:39:27.126435: +2024-11-22 09:39:27.126640: Epoch 4216 +2024-11-22 09:39:27.126751: Current learning rate: 0.0051 +2024-11-22 09:39:46.047100: train_loss -0.7883 +2024-11-22 09:39:46.047333: val_loss -0.7358 +2024-11-22 09:39:46.047411: Pseudo dice [0.8509] +2024-11-22 09:39:46.047491: Epoch time: 18.92 s +2024-11-22 09:39:46.912619: +2024-11-22 09:39:46.912861: Epoch 4217 +2024-11-22 09:39:46.912987: Current learning rate: 0.0051 +2024-11-22 09:40:05.919416: train_loss -0.7908 +2024-11-22 09:40:05.920405: val_loss -0.7546 +2024-11-22 09:40:05.920521: Pseudo dice [0.8535] +2024-11-22 09:40:05.920606: Epoch time: 19.01 s +2024-11-22 09:40:06.791649: +2024-11-22 09:40:06.791905: Epoch 4218 +2024-11-22 09:40:06.792026: Current learning rate: 0.0051 +2024-11-22 09:40:25.223582: train_loss -0.8031 +2024-11-22 09:40:25.223794: val_loss -0.7697 +2024-11-22 09:40:25.223871: Pseudo dice [0.8424] +2024-11-22 09:40:25.223946: Epoch time: 18.43 s +2024-11-22 09:40:26.502174: +2024-11-22 09:40:26.502403: Epoch 4219 +2024-11-22 09:40:26.502515: Current learning rate: 0.00509 +2024-11-22 09:40:45.500962: train_loss -0.788 +2024-11-22 09:40:45.501203: val_loss -0.7067 +2024-11-22 09:40:45.501279: Pseudo dice [0.8334] +2024-11-22 09:40:45.501355: Epoch time: 19.0 s +2024-11-22 09:40:46.373671: +2024-11-22 09:40:46.373900: Epoch 4220 +2024-11-22 09:40:46.374015: Current learning rate: 0.00509 +2024-11-22 09:41:06.068059: train_loss -0.783 +2024-11-22 09:41:06.068275: val_loss -0.7246 +2024-11-22 09:41:06.068351: Pseudo dice [0.8424] +2024-11-22 09:41:06.068428: Epoch time: 19.7 s +2024-11-22 09:41:07.200982: +2024-11-22 09:41:07.201241: Epoch 4221 +2024-11-22 09:41:07.201401: Current learning rate: 0.00509 +2024-11-22 09:41:25.976625: train_loss -0.7924 +2024-11-22 09:41:25.976877: val_loss -0.7088 +2024-11-22 09:41:25.976960: Pseudo dice [0.8299] +2024-11-22 09:41:25.977049: Epoch time: 18.78 s +2024-11-22 09:41:26.843709: +2024-11-22 09:41:26.843954: Epoch 4222 +2024-11-22 09:41:26.844069: Current learning rate: 0.00509 +2024-11-22 09:41:45.283315: train_loss -0.7888 +2024-11-22 09:41:45.283535: val_loss -0.7421 +2024-11-22 09:41:45.283608: Pseudo dice [0.8573] +2024-11-22 09:41:45.283684: Epoch time: 18.44 s +2024-11-22 09:41:46.155357: +2024-11-22 09:41:46.155586: Epoch 4223 +2024-11-22 09:41:46.155697: Current learning rate: 0.00509 +2024-11-22 09:42:04.800984: train_loss -0.7951 +2024-11-22 09:42:04.806402: val_loss -0.7375 +2024-11-22 09:42:04.806487: Pseudo dice [0.8262] +2024-11-22 09:42:04.806568: Epoch time: 18.65 s +2024-11-22 09:42:05.788431: +2024-11-22 09:42:05.788704: Epoch 4224 +2024-11-22 09:42:05.788822: Current learning rate: 0.00509 +2024-11-22 09:42:24.901500: train_loss -0.7767 +2024-11-22 09:42:24.901730: val_loss -0.7302 +2024-11-22 09:42:24.901812: Pseudo dice [0.8524] +2024-11-22 09:42:24.901896: Epoch time: 19.11 s +2024-11-22 09:42:25.773382: +2024-11-22 09:42:25.773681: Epoch 4225 +2024-11-22 09:42:25.773798: Current learning rate: 0.00509 +2024-11-22 09:42:44.190461: train_loss -0.7725 +2024-11-22 09:42:44.190711: val_loss -0.7266 +2024-11-22 09:42:44.190793: Pseudo dice [0.8407] +2024-11-22 09:42:44.190875: Epoch time: 18.42 s +2024-11-22 09:42:45.059925: +2024-11-22 09:42:45.060151: Epoch 4226 +2024-11-22 09:42:45.060265: Current learning rate: 0.00509 +2024-11-22 09:43:06.025319: train_loss -0.7707 +2024-11-22 09:43:06.025534: val_loss -0.7488 +2024-11-22 09:43:06.025610: Pseudo dice [0.8525] +2024-11-22 09:43:06.025689: Epoch time: 20.97 s +2024-11-22 09:43:06.998424: +2024-11-22 09:43:06.998658: Epoch 4227 +2024-11-22 09:43:06.998775: Current learning rate: 0.00508 +2024-11-22 09:43:24.781308: train_loss -0.7724 +2024-11-22 09:43:24.781535: val_loss -0.7441 +2024-11-22 09:43:24.781613: Pseudo dice [0.8504] +2024-11-22 09:43:24.781693: Epoch time: 17.78 s +2024-11-22 09:43:25.649951: +2024-11-22 09:43:25.650173: Epoch 4228 +2024-11-22 09:43:25.650289: Current learning rate: 0.00508 +2024-11-22 09:43:45.331087: train_loss -0.7798 +2024-11-22 09:43:45.331320: val_loss -0.7293 +2024-11-22 09:43:45.331397: Pseudo dice [0.839] +2024-11-22 09:43:45.331479: Epoch time: 19.68 s +2024-11-22 09:43:46.201753: +2024-11-22 09:43:46.201945: Epoch 4229 +2024-11-22 09:43:46.202055: Current learning rate: 0.00508 +2024-11-22 09:44:05.694205: train_loss -0.7735 +2024-11-22 09:44:05.694435: val_loss -0.7391 +2024-11-22 09:44:05.694512: Pseudo dice [0.8357] +2024-11-22 09:44:05.694593: Epoch time: 19.49 s +2024-11-22 09:44:06.548379: +2024-11-22 09:44:06.548584: Epoch 4230 +2024-11-22 09:44:06.548693: Current learning rate: 0.00508 +2024-11-22 09:44:24.825948: train_loss -0.78 +2024-11-22 09:44:24.826171: val_loss -0.738 +2024-11-22 09:44:24.826251: Pseudo dice [0.8298] +2024-11-22 09:44:24.826329: Epoch time: 18.28 s +2024-11-22 09:44:25.970959: +2024-11-22 09:44:25.971193: Epoch 4231 +2024-11-22 09:44:25.971304: Current learning rate: 0.00508 +2024-11-22 09:44:45.305879: train_loss -0.7903 +2024-11-22 09:44:45.306112: val_loss -0.7181 +2024-11-22 09:44:45.306185: Pseudo dice [0.8444] +2024-11-22 09:44:45.311478: Epoch time: 19.34 s +2024-11-22 09:44:46.304440: +2024-11-22 09:44:46.304659: Epoch 4232 +2024-11-22 09:44:46.304768: Current learning rate: 0.00508 +2024-11-22 09:45:05.173061: train_loss -0.7862 +2024-11-22 09:45:05.173366: val_loss -0.7567 +2024-11-22 09:45:05.173445: Pseudo dice [0.8399] +2024-11-22 09:45:05.173533: Epoch time: 18.87 s +2024-11-22 09:45:06.048637: +2024-11-22 09:45:06.048851: Epoch 4233 +2024-11-22 09:45:06.048963: Current learning rate: 0.00508 +2024-11-22 09:45:25.359679: train_loss -0.7901 +2024-11-22 09:45:25.359899: val_loss -0.7607 +2024-11-22 09:45:25.359975: Pseudo dice [0.8318] +2024-11-22 09:45:25.360058: Epoch time: 19.31 s +2024-11-22 09:45:26.287191: +2024-11-22 09:45:26.287426: Epoch 4234 +2024-11-22 09:45:26.287536: Current learning rate: 0.00508 +2024-11-22 09:45:43.999407: train_loss -0.7908 +2024-11-22 09:45:43.999656: val_loss -0.7409 +2024-11-22 09:45:43.999735: Pseudo dice [0.8557] +2024-11-22 09:45:43.999817: Epoch time: 17.71 s +2024-11-22 09:45:44.857543: +2024-11-22 09:45:44.857764: Epoch 4235 +2024-11-22 09:45:44.857873: Current learning rate: 0.00507 +2024-11-22 09:46:02.731509: train_loss -0.7917 +2024-11-22 09:46:02.731723: val_loss -0.7599 +2024-11-22 09:46:02.731800: Pseudo dice [0.8512] +2024-11-22 09:46:02.731918: Epoch time: 17.87 s +2024-11-22 09:46:03.592663: +2024-11-22 09:46:03.592900: Epoch 4236 +2024-11-22 09:46:03.593016: Current learning rate: 0.00507 +2024-11-22 09:46:23.667096: train_loss -0.7898 +2024-11-22 09:46:23.667365: val_loss -0.7305 +2024-11-22 09:46:23.667460: Pseudo dice [0.8436] +2024-11-22 09:46:23.667603: Epoch time: 20.08 s +2024-11-22 09:46:24.537818: +2024-11-22 09:46:24.538025: Epoch 4237 +2024-11-22 09:46:24.538139: Current learning rate: 0.00507 +2024-11-22 09:46:43.544287: train_loss -0.7933 +2024-11-22 09:46:43.544554: val_loss -0.7502 +2024-11-22 09:46:43.544637: Pseudo dice [0.8413] +2024-11-22 09:46:43.544713: Epoch time: 19.01 s +2024-11-22 09:46:44.405802: +2024-11-22 09:46:44.406026: Epoch 4238 +2024-11-22 09:46:44.406140: Current learning rate: 0.00507 +2024-11-22 09:47:03.901318: train_loss -0.7785 +2024-11-22 09:47:03.901523: val_loss -0.7659 +2024-11-22 09:47:03.901600: Pseudo dice [0.8519] +2024-11-22 09:47:03.901677: Epoch time: 19.5 s +2024-11-22 09:47:04.754178: +2024-11-22 09:47:04.754380: Epoch 4239 +2024-11-22 09:47:04.754494: Current learning rate: 0.00507 +2024-11-22 09:47:23.713346: train_loss -0.7881 +2024-11-22 09:47:23.713568: val_loss -0.7327 +2024-11-22 09:47:23.713640: Pseudo dice [0.8295] +2024-11-22 09:47:23.713721: Epoch time: 18.96 s +2024-11-22 09:47:24.580891: +2024-11-22 09:47:24.581123: Epoch 4240 +2024-11-22 09:47:24.581241: Current learning rate: 0.00507 +2024-11-22 09:47:43.347088: train_loss -0.7955 +2024-11-22 09:47:43.347646: val_loss -0.741 +2024-11-22 09:47:43.347738: Pseudo dice [0.8424] +2024-11-22 09:47:43.347820: Epoch time: 18.77 s +2024-11-22 09:47:44.216055: +2024-11-22 09:47:44.216259: Epoch 4241 +2024-11-22 09:47:44.216374: Current learning rate: 0.00507 +2024-11-22 09:48:03.634782: train_loss -0.7908 +2024-11-22 09:48:03.634999: val_loss -0.7563 +2024-11-22 09:48:03.635079: Pseudo dice [0.8143] +2024-11-22 09:48:03.635153: Epoch time: 19.42 s +2024-11-22 09:48:04.488642: +2024-11-22 09:48:04.488839: Epoch 4242 +2024-11-22 09:48:04.488950: Current learning rate: 0.00507 +2024-11-22 09:48:23.094102: train_loss -0.781 +2024-11-22 09:48:23.094351: val_loss -0.7589 +2024-11-22 09:48:23.094430: Pseudo dice [0.8539] +2024-11-22 09:48:23.094514: Epoch time: 18.61 s +2024-11-22 09:48:24.311352: +2024-11-22 09:48:24.311571: Epoch 4243 +2024-11-22 09:48:24.311691: Current learning rate: 0.00506 +2024-11-22 09:48:43.697072: train_loss -0.7884 +2024-11-22 09:48:43.697311: val_loss -0.752 +2024-11-22 09:48:43.697386: Pseudo dice [0.8366] +2024-11-22 09:48:43.697468: Epoch time: 19.39 s +2024-11-22 09:48:44.603506: +2024-11-22 09:48:44.603729: Epoch 4244 +2024-11-22 09:48:44.603845: Current learning rate: 0.00506 +2024-11-22 09:49:02.994066: train_loss -0.7674 +2024-11-22 09:49:02.994278: val_loss -0.7589 +2024-11-22 09:49:02.994356: Pseudo dice [0.8392] +2024-11-22 09:49:02.994436: Epoch time: 18.39 s +2024-11-22 09:49:03.881063: +2024-11-22 09:49:03.881277: Epoch 4245 +2024-11-22 09:49:03.881389: Current learning rate: 0.00506 +2024-11-22 09:49:22.308855: train_loss -0.7823 +2024-11-22 09:49:22.309082: val_loss -0.7558 +2024-11-22 09:49:22.309157: Pseudo dice [0.8406] +2024-11-22 09:49:22.311318: Epoch time: 18.43 s +2024-11-22 09:49:23.187805: +2024-11-22 09:49:23.188122: Epoch 4246 +2024-11-22 09:49:23.188234: Current learning rate: 0.00506 +2024-11-22 09:49:41.995946: train_loss -0.7886 +2024-11-22 09:49:41.996180: val_loss -0.7533 +2024-11-22 09:49:41.996255: Pseudo dice [0.8395] +2024-11-22 09:49:41.996331: Epoch time: 18.81 s +2024-11-22 09:49:42.886176: +2024-11-22 09:49:42.886406: Epoch 4247 +2024-11-22 09:49:42.886523: Current learning rate: 0.00506 +2024-11-22 09:50:02.062815: train_loss -0.7807 +2024-11-22 09:50:02.063083: val_loss -0.761 +2024-11-22 09:50:02.063161: Pseudo dice [0.828] +2024-11-22 09:50:02.063241: Epoch time: 19.18 s +2024-11-22 09:50:02.934433: +2024-11-22 09:50:02.934648: Epoch 4248 +2024-11-22 09:50:02.934757: Current learning rate: 0.00506 +2024-11-22 09:50:20.509806: train_loss -0.79 +2024-11-22 09:50:20.510024: val_loss -0.7627 +2024-11-22 09:50:20.510099: Pseudo dice [0.8501] +2024-11-22 09:50:20.510176: Epoch time: 17.58 s +2024-11-22 09:50:21.375571: +2024-11-22 09:50:21.375776: Epoch 4249 +2024-11-22 09:50:21.375881: Current learning rate: 0.00506 +2024-11-22 09:50:40.550812: train_loss -0.7837 +2024-11-22 09:50:40.551034: val_loss -0.7475 +2024-11-22 09:50:40.551109: Pseudo dice [0.8664] +2024-11-22 09:50:40.551192: Epoch time: 19.18 s +2024-11-22 09:50:41.658145: +2024-11-22 09:50:41.658438: Epoch 4250 +2024-11-22 09:50:41.658551: Current learning rate: 0.00506 +2024-11-22 09:50:59.911514: train_loss -0.7977 +2024-11-22 09:50:59.911787: val_loss -0.7377 +2024-11-22 09:50:59.911865: Pseudo dice [0.858] +2024-11-22 09:50:59.911947: Epoch time: 18.25 s +2024-11-22 09:51:00.771338: +2024-11-22 09:51:00.771563: Epoch 4251 +2024-11-22 09:51:00.771676: Current learning rate: 0.00506 +2024-11-22 09:51:18.811907: train_loss -0.7889 +2024-11-22 09:51:18.812155: val_loss -0.773 +2024-11-22 09:51:18.812229: Pseudo dice [0.8445] +2024-11-22 09:51:18.812310: Epoch time: 18.04 s +2024-11-22 09:51:19.675459: +2024-11-22 09:51:19.675673: Epoch 4252 +2024-11-22 09:51:19.675777: Current learning rate: 0.00505 +2024-11-22 09:51:39.085355: train_loss -0.7979 +2024-11-22 09:51:39.085655: val_loss -0.7572 +2024-11-22 09:51:39.085734: Pseudo dice [0.8525] +2024-11-22 09:51:39.085811: Epoch time: 19.41 s +2024-11-22 09:51:40.020126: +2024-11-22 09:51:40.020319: Epoch 4253 +2024-11-22 09:51:40.020429: Current learning rate: 0.00505 +2024-11-22 09:51:59.316851: train_loss -0.7863 +2024-11-22 09:51:59.317087: val_loss -0.7402 +2024-11-22 09:51:59.317164: Pseudo dice [0.841] +2024-11-22 09:51:59.317242: Epoch time: 19.3 s +2024-11-22 09:52:00.166317: +2024-11-22 09:52:00.166510: Epoch 4254 +2024-11-22 09:52:00.166622: Current learning rate: 0.00505 +2024-11-22 09:52:18.437253: train_loss -0.7847 +2024-11-22 09:52:18.437494: val_loss -0.7494 +2024-11-22 09:52:18.437569: Pseudo dice [0.824] +2024-11-22 09:52:18.437651: Epoch time: 18.27 s +2024-11-22 09:52:19.573664: +2024-11-22 09:52:19.573876: Epoch 4255 +2024-11-22 09:52:19.573987: Current learning rate: 0.00505 +2024-11-22 09:52:37.782718: train_loss -0.791 +2024-11-22 09:52:37.782969: val_loss -0.767 +2024-11-22 09:52:37.783055: Pseudo dice [0.8589] +2024-11-22 09:52:37.783138: Epoch time: 18.21 s +2024-11-22 09:52:38.857075: +2024-11-22 09:52:38.857378: Epoch 4256 +2024-11-22 09:52:38.857495: Current learning rate: 0.00505 +2024-11-22 09:52:57.351129: train_loss -0.7987 +2024-11-22 09:52:57.351360: val_loss -0.7385 +2024-11-22 09:52:57.351434: Pseudo dice [0.861] +2024-11-22 09:52:57.351514: Epoch time: 18.49 s +2024-11-22 09:52:58.224577: +2024-11-22 09:52:58.224952: Epoch 4257 +2024-11-22 09:52:58.225068: Current learning rate: 0.00505 +2024-11-22 09:53:17.710553: train_loss -0.793 +2024-11-22 09:53:17.710813: val_loss -0.7462 +2024-11-22 09:53:17.713119: Pseudo dice [0.8675] +2024-11-22 09:53:17.713221: Epoch time: 19.49 s +2024-11-22 09:53:18.627000: +2024-11-22 09:53:18.627210: Epoch 4258 +2024-11-22 09:53:18.627324: Current learning rate: 0.00505 +2024-11-22 09:53:38.109664: train_loss -0.7832 +2024-11-22 09:53:38.109891: val_loss -0.7426 +2024-11-22 09:53:38.109971: Pseudo dice [0.8499] +2024-11-22 09:53:38.110073: Epoch time: 19.48 s +2024-11-22 09:53:38.982346: +2024-11-22 09:53:38.982569: Epoch 4259 +2024-11-22 09:53:38.982680: Current learning rate: 0.00505 +2024-11-22 09:53:57.261334: train_loss -0.7897 +2024-11-22 09:53:57.261572: val_loss -0.7541 +2024-11-22 09:53:57.261685: Pseudo dice [0.8554] +2024-11-22 09:53:57.261767: Epoch time: 18.28 s +2024-11-22 09:53:57.261831: Yayy! New best EMA pseudo Dice: 0.849 +2024-11-22 09:53:58.434922: +2024-11-22 09:53:58.435156: Epoch 4260 +2024-11-22 09:53:58.435269: Current learning rate: 0.00504 +2024-11-22 09:54:16.903997: train_loss -0.7853 +2024-11-22 09:54:16.904248: val_loss -0.7493 +2024-11-22 09:54:16.904323: Pseudo dice [0.8393] +2024-11-22 09:54:16.904396: Epoch time: 18.47 s +2024-11-22 09:54:17.821540: +2024-11-22 09:54:17.821768: Epoch 4261 +2024-11-22 09:54:17.821879: Current learning rate: 0.00504 +2024-11-22 09:54:36.289790: train_loss -0.7847 +2024-11-22 09:54:36.290031: val_loss -0.7496 +2024-11-22 09:54:36.290107: Pseudo dice [0.8349] +2024-11-22 09:54:36.290188: Epoch time: 18.47 s +2024-11-22 09:54:37.270868: +2024-11-22 09:54:37.271101: Epoch 4262 +2024-11-22 09:54:37.271204: Current learning rate: 0.00504 +2024-11-22 09:54:55.495652: train_loss -0.7886 +2024-11-22 09:54:55.495898: val_loss -0.7486 +2024-11-22 09:54:55.501084: Pseudo dice [0.8363] +2024-11-22 09:54:55.501238: Epoch time: 18.23 s +2024-11-22 09:54:56.477760: +2024-11-22 09:54:56.478123: Epoch 4263 +2024-11-22 09:54:56.478239: Current learning rate: 0.00504 +2024-11-22 09:55:15.796529: train_loss -0.7903 +2024-11-22 09:55:15.796805: val_loss -0.7474 +2024-11-22 09:55:15.796884: Pseudo dice [0.8221] +2024-11-22 09:55:15.796963: Epoch time: 19.32 s +2024-11-22 09:55:16.670425: +2024-11-22 09:55:16.670621: Epoch 4264 +2024-11-22 09:55:16.670731: Current learning rate: 0.00504 +2024-11-22 09:55:34.905472: train_loss -0.7883 +2024-11-22 09:55:34.905699: val_loss -0.7457 +2024-11-22 09:55:34.905774: Pseudo dice [0.8628] +2024-11-22 09:55:34.905851: Epoch time: 18.24 s +2024-11-22 09:55:35.777020: +2024-11-22 09:55:35.777217: Epoch 4265 +2024-11-22 09:55:35.777344: Current learning rate: 0.00504 +2024-11-22 09:55:54.427697: train_loss -0.7794 +2024-11-22 09:55:54.427919: val_loss -0.7421 +2024-11-22 09:55:54.428005: Pseudo dice [0.8214] +2024-11-22 09:55:54.428088: Epoch time: 18.65 s +2024-11-22 09:55:55.297801: +2024-11-22 09:55:55.298021: Epoch 4266 +2024-11-22 09:55:55.298133: Current learning rate: 0.00504 +2024-11-22 09:56:13.751610: train_loss -0.7816 +2024-11-22 09:56:13.751848: val_loss -0.7419 +2024-11-22 09:56:13.751919: Pseudo dice [0.8477] +2024-11-22 09:56:13.752008: Epoch time: 18.45 s +2024-11-22 09:56:15.039658: +2024-11-22 09:56:15.039940: Epoch 4267 +2024-11-22 09:56:15.040056: Current learning rate: 0.00504 +2024-11-22 09:56:33.784394: train_loss -0.794 +2024-11-22 09:56:33.784643: val_loss -0.7415 +2024-11-22 09:56:33.784719: Pseudo dice [0.8367] +2024-11-22 09:56:33.784801: Epoch time: 18.75 s +2024-11-22 09:56:34.686805: +2024-11-22 09:56:34.687024: Epoch 4268 +2024-11-22 09:56:34.687136: Current learning rate: 0.00503 +2024-11-22 09:56:53.497437: train_loss -0.7896 +2024-11-22 09:56:53.497654: val_loss -0.7545 +2024-11-22 09:56:53.497728: Pseudo dice [0.8458] +2024-11-22 09:56:53.497805: Epoch time: 18.81 s +2024-11-22 09:56:54.375439: +2024-11-22 09:56:54.375690: Epoch 4269 +2024-11-22 09:56:54.375801: Current learning rate: 0.00503 +2024-11-22 09:57:12.942198: train_loss -0.7962 +2024-11-22 09:57:12.942468: val_loss -0.7517 +2024-11-22 09:57:12.942603: Pseudo dice [0.8418] +2024-11-22 09:57:12.942684: Epoch time: 18.57 s +2024-11-22 09:57:13.868492: +2024-11-22 09:57:13.868716: Epoch 4270 +2024-11-22 09:57:13.868827: Current learning rate: 0.00503 +2024-11-22 09:57:32.735275: train_loss -0.7899 +2024-11-22 09:57:32.735487: val_loss -0.7555 +2024-11-22 09:57:32.735563: Pseudo dice [0.8321] +2024-11-22 09:57:32.735639: Epoch time: 18.87 s +2024-11-22 09:57:33.590547: +2024-11-22 09:57:33.590770: Epoch 4271 +2024-11-22 09:57:33.590887: Current learning rate: 0.00503 +2024-11-22 09:57:52.622226: train_loss -0.7867 +2024-11-22 09:57:52.622438: val_loss -0.7443 +2024-11-22 09:57:52.622514: Pseudo dice [0.8209] +2024-11-22 09:57:52.622593: Epoch time: 19.03 s +2024-11-22 09:57:53.481070: +2024-11-22 09:57:53.481273: Epoch 4272 +2024-11-22 09:57:53.481390: Current learning rate: 0.00503 +2024-11-22 09:58:11.993408: train_loss -0.7912 +2024-11-22 09:58:11.993625: val_loss -0.7453 +2024-11-22 09:58:11.993701: Pseudo dice [0.8527] +2024-11-22 09:58:11.993778: Epoch time: 18.51 s +2024-11-22 09:58:12.851701: +2024-11-22 09:58:12.851896: Epoch 4273 +2024-11-22 09:58:12.852007: Current learning rate: 0.00503 +2024-11-22 09:58:30.855638: train_loss -0.7892 +2024-11-22 09:58:30.855875: val_loss -0.7741 +2024-11-22 09:58:30.855949: Pseudo dice [0.8476] +2024-11-22 09:58:30.856036: Epoch time: 18.0 s +2024-11-22 09:58:31.720945: +2024-11-22 09:58:31.721143: Epoch 4274 +2024-11-22 09:58:31.721274: Current learning rate: 0.00503 +2024-11-22 09:58:50.683705: train_loss -0.7914 +2024-11-22 09:58:50.683916: val_loss -0.7582 +2024-11-22 09:58:50.684004: Pseudo dice [0.8357] +2024-11-22 09:58:50.684081: Epoch time: 18.96 s +2024-11-22 09:58:51.535664: +2024-11-22 09:58:51.535867: Epoch 4275 +2024-11-22 09:58:51.535979: Current learning rate: 0.00503 +2024-11-22 09:59:10.180643: train_loss -0.7889 +2024-11-22 09:59:10.180857: val_loss -0.7315 +2024-11-22 09:59:10.180931: Pseudo dice [0.874] +2024-11-22 09:59:10.181061: Epoch time: 18.65 s +2024-11-22 09:59:11.041211: +2024-11-22 09:59:11.041413: Epoch 4276 +2024-11-22 09:59:11.041523: Current learning rate: 0.00502 +2024-11-22 09:59:30.206845: train_loss -0.8015 +2024-11-22 09:59:30.207074: val_loss -0.7695 +2024-11-22 09:59:30.207176: Pseudo dice [0.8604] +2024-11-22 09:59:30.207260: Epoch time: 19.17 s +2024-11-22 09:59:31.078038: +2024-11-22 09:59:31.078241: Epoch 4277 +2024-11-22 09:59:31.078354: Current learning rate: 0.00502 +2024-11-22 09:59:49.323376: train_loss -0.7998 +2024-11-22 09:59:49.323616: val_loss -0.755 +2024-11-22 09:59:49.323693: Pseudo dice [0.835] +2024-11-22 09:59:49.323775: Epoch time: 18.25 s +2024-11-22 09:59:50.174976: +2024-11-22 09:59:50.175180: Epoch 4278 +2024-11-22 09:59:50.175297: Current learning rate: 0.00502 +2024-11-22 10:00:10.089269: train_loss -0.7964 +2024-11-22 10:00:10.089483: val_loss -0.7453 +2024-11-22 10:00:10.089558: Pseudo dice [0.8314] +2024-11-22 10:00:10.089635: Epoch time: 19.92 s +2024-11-22 10:00:11.368686: +2024-11-22 10:00:11.368901: Epoch 4279 +2024-11-22 10:00:11.369021: Current learning rate: 0.00502 +2024-11-22 10:00:30.625022: train_loss -0.7849 +2024-11-22 10:00:30.625253: val_loss -0.7467 +2024-11-22 10:00:30.625328: Pseudo dice [0.8452] +2024-11-22 10:00:30.625406: Epoch time: 19.26 s +2024-11-22 10:00:31.496552: +2024-11-22 10:00:31.496775: Epoch 4280 +2024-11-22 10:00:31.496887: Current learning rate: 0.00502 +2024-11-22 10:00:50.588169: train_loss -0.7867 +2024-11-22 10:00:50.588387: val_loss -0.764 +2024-11-22 10:00:50.588462: Pseudo dice [0.8631] +2024-11-22 10:00:50.588542: Epoch time: 19.09 s +2024-11-22 10:00:51.454944: +2024-11-22 10:00:51.455171: Epoch 4281 +2024-11-22 10:00:51.455285: Current learning rate: 0.00502 +2024-11-22 10:01:09.334929: train_loss -0.7833 +2024-11-22 10:01:09.337343: val_loss -0.7544 +2024-11-22 10:01:09.337429: Pseudo dice [0.8678] +2024-11-22 10:01:09.337509: Epoch time: 17.88 s +2024-11-22 10:01:10.399204: +2024-11-22 10:01:10.399418: Epoch 4282 +2024-11-22 10:01:10.399533: Current learning rate: 0.00502 +2024-11-22 10:01:30.051224: train_loss -0.7893 +2024-11-22 10:01:30.051448: val_loss -0.7594 +2024-11-22 10:01:30.051530: Pseudo dice [0.8614] +2024-11-22 10:01:30.051609: Epoch time: 19.65 s +2024-11-22 10:01:30.051678: Yayy! New best EMA pseudo Dice: 0.8492 +2024-11-22 10:01:31.234424: +2024-11-22 10:01:31.234700: Epoch 4283 +2024-11-22 10:01:31.234814: Current learning rate: 0.00502 +2024-11-22 10:01:50.547592: train_loss -0.7897 +2024-11-22 10:01:50.547810: val_loss -0.7468 +2024-11-22 10:01:50.547888: Pseudo dice [0.8615] +2024-11-22 10:01:50.547966: Epoch time: 19.31 s +2024-11-22 10:01:50.548032: Yayy! New best EMA pseudo Dice: 0.8504 +2024-11-22 10:01:51.671010: +2024-11-22 10:01:51.671239: Epoch 4284 +2024-11-22 10:01:51.671354: Current learning rate: 0.00502 +2024-11-22 10:02:09.871400: train_loss -0.7899 +2024-11-22 10:02:09.871645: val_loss -0.7255 +2024-11-22 10:02:09.871724: Pseudo dice [0.8075] +2024-11-22 10:02:09.871807: Epoch time: 18.2 s +2024-11-22 10:02:10.898898: +2024-11-22 10:02:10.899128: Epoch 4285 +2024-11-22 10:02:10.899242: Current learning rate: 0.00501 +2024-11-22 10:02:28.762951: train_loss -0.7824 +2024-11-22 10:02:28.768392: val_loss -0.7253 +2024-11-22 10:02:28.768516: Pseudo dice [0.8147] +2024-11-22 10:02:28.768603: Epoch time: 17.86 s +2024-11-22 10:02:29.732839: +2024-11-22 10:02:29.733078: Epoch 4286 +2024-11-22 10:02:29.733189: Current learning rate: 0.00501 +2024-11-22 10:02:49.187537: train_loss -0.7893 +2024-11-22 10:02:49.187759: val_loss -0.738 +2024-11-22 10:02:49.187840: Pseudo dice [0.8187] +2024-11-22 10:02:49.187922: Epoch time: 19.46 s +2024-11-22 10:02:50.123053: +2024-11-22 10:02:50.123280: Epoch 4287 +2024-11-22 10:02:50.123396: Current learning rate: 0.00501 +2024-11-22 10:03:09.516863: train_loss -0.7887 +2024-11-22 10:03:09.517096: val_loss -0.7271 +2024-11-22 10:03:09.517173: Pseudo dice [0.8397] +2024-11-22 10:03:09.517250: Epoch time: 19.39 s +2024-11-22 10:03:10.437292: +2024-11-22 10:03:10.437519: Epoch 4288 +2024-11-22 10:03:10.437631: Current learning rate: 0.00501 +2024-11-22 10:03:29.055053: train_loss -0.7963 +2024-11-22 10:03:29.055296: val_loss -0.7477 +2024-11-22 10:03:29.055372: Pseudo dice [0.8354] +2024-11-22 10:03:29.055453: Epoch time: 18.62 s +2024-11-22 10:03:29.923898: +2024-11-22 10:03:29.924107: Epoch 4289 +2024-11-22 10:03:29.924227: Current learning rate: 0.00501 +2024-11-22 10:03:49.018420: train_loss -0.7684 +2024-11-22 10:03:49.018661: val_loss -0.7165 +2024-11-22 10:03:49.018735: Pseudo dice [0.8294] +2024-11-22 10:03:49.018817: Epoch time: 19.1 s +2024-11-22 10:03:49.888201: +2024-11-22 10:03:49.888416: Epoch 4290 +2024-11-22 10:03:49.888545: Current learning rate: 0.00501 +2024-11-22 10:04:09.312918: train_loss -0.7772 +2024-11-22 10:04:09.313816: val_loss -0.7296 +2024-11-22 10:04:09.313929: Pseudo dice [0.8321] +2024-11-22 10:04:09.314013: Epoch time: 19.43 s +2024-11-22 10:04:10.179950: +2024-11-22 10:04:10.180181: Epoch 4291 +2024-11-22 10:04:10.180295: Current learning rate: 0.00501 +2024-11-22 10:04:28.665924: train_loss -0.788 +2024-11-22 10:04:28.666144: val_loss -0.7447 +2024-11-22 10:04:28.666215: Pseudo dice [0.8568] +2024-11-22 10:04:28.671512: Epoch time: 18.49 s +2024-11-22 10:04:29.570507: +2024-11-22 10:04:29.570719: Epoch 4292 +2024-11-22 10:04:29.570835: Current learning rate: 0.00501 +2024-11-22 10:04:47.786546: train_loss -0.796 +2024-11-22 10:04:47.786842: val_loss -0.7558 +2024-11-22 10:04:47.786921: Pseudo dice [0.8351] +2024-11-22 10:04:47.787013: Epoch time: 18.22 s +2024-11-22 10:04:48.703157: +2024-11-22 10:04:48.703388: Epoch 4293 +2024-11-22 10:04:48.703501: Current learning rate: 0.005 +2024-11-22 10:05:08.187642: train_loss -0.7991 +2024-11-22 10:05:08.187863: val_loss -0.7053 +2024-11-22 10:05:08.187938: Pseudo dice [0.8259] +2024-11-22 10:05:08.188020: Epoch time: 19.49 s +2024-11-22 10:05:09.057206: +2024-11-22 10:05:09.057438: Epoch 4294 +2024-11-22 10:05:09.057554: Current learning rate: 0.005 +2024-11-22 10:05:27.282304: train_loss -0.7929 +2024-11-22 10:05:27.282522: val_loss -0.7443 +2024-11-22 10:05:27.286844: Pseudo dice [0.8499] +2024-11-22 10:05:27.286984: Epoch time: 18.23 s +2024-11-22 10:05:28.167386: +2024-11-22 10:05:28.167598: Epoch 4295 +2024-11-22 10:05:28.167712: Current learning rate: 0.005 +2024-11-22 10:05:46.910594: train_loss -0.7899 +2024-11-22 10:05:46.910826: val_loss -0.7548 +2024-11-22 10:05:46.910903: Pseudo dice [0.8504] +2024-11-22 10:05:46.910980: Epoch time: 18.74 s +2024-11-22 10:05:47.826203: +2024-11-22 10:05:47.826425: Epoch 4296 +2024-11-22 10:05:47.826535: Current learning rate: 0.005 +2024-11-22 10:06:06.096004: train_loss -0.7985 +2024-11-22 10:06:06.096276: val_loss -0.7649 +2024-11-22 10:06:06.096350: Pseudo dice [0.8624] +2024-11-22 10:06:06.096431: Epoch time: 18.27 s +2024-11-22 10:06:07.020699: +2024-11-22 10:06:07.020960: Epoch 4297 +2024-11-22 10:06:07.021083: Current learning rate: 0.005 +2024-11-22 10:06:25.809239: train_loss -0.7799 +2024-11-22 10:06:25.809479: val_loss -0.7248 +2024-11-22 10:06:25.809559: Pseudo dice [0.8451] +2024-11-22 10:06:25.809640: Epoch time: 18.79 s +2024-11-22 10:06:26.717297: +2024-11-22 10:06:26.717594: Epoch 4298 +2024-11-22 10:06:26.717712: Current learning rate: 0.005 +2024-11-22 10:06:45.217723: train_loss -0.7901 +2024-11-22 10:06:45.217934: val_loss -0.7628 +2024-11-22 10:06:45.218024: Pseudo dice [0.8502] +2024-11-22 10:06:45.218102: Epoch time: 18.5 s +2024-11-22 10:06:46.082084: +2024-11-22 10:06:46.082282: Epoch 4299 +2024-11-22 10:06:46.082390: Current learning rate: 0.005 +2024-11-22 10:07:05.261156: train_loss -0.7984 +2024-11-22 10:07:05.261407: val_loss -0.7563 +2024-11-22 10:07:05.261488: Pseudo dice [0.8547] +2024-11-22 10:07:05.261570: Epoch time: 19.18 s +2024-11-22 10:07:06.491191: +2024-11-22 10:07:06.491479: Epoch 4300 +2024-11-22 10:07:06.491596: Current learning rate: 0.005 +2024-11-22 10:07:25.979274: train_loss -0.7948 +2024-11-22 10:07:25.979496: val_loss -0.6965 +2024-11-22 10:07:25.979575: Pseudo dice [0.8407] +2024-11-22 10:07:25.979660: Epoch time: 19.49 s +2024-11-22 10:07:26.851268: +2024-11-22 10:07:26.851511: Epoch 4301 +2024-11-22 10:07:26.851669: Current learning rate: 0.00499 +2024-11-22 10:07:45.202015: train_loss -0.7869 +2024-11-22 10:07:45.202241: val_loss -0.7551 +2024-11-22 10:07:45.202322: Pseudo dice [0.8499] +2024-11-22 10:07:45.202402: Epoch time: 18.35 s +2024-11-22 10:07:46.478781: +2024-11-22 10:07:46.479036: Epoch 4302 +2024-11-22 10:07:46.479151: Current learning rate: 0.00499 +2024-11-22 10:08:05.131817: train_loss -0.7963 +2024-11-22 10:08:05.132120: val_loss -0.7651 +2024-11-22 10:08:05.132201: Pseudo dice [0.8547] +2024-11-22 10:08:05.132282: Epoch time: 18.65 s +2024-11-22 10:08:06.246683: +2024-11-22 10:08:06.246905: Epoch 4303 +2024-11-22 10:08:06.247031: Current learning rate: 0.00499 +2024-11-22 10:08:24.940161: train_loss -0.7922 +2024-11-22 10:08:24.942597: val_loss -0.7498 +2024-11-22 10:08:24.942693: Pseudo dice [0.8361] +2024-11-22 10:08:24.942777: Epoch time: 18.69 s +2024-11-22 10:08:25.817318: +2024-11-22 10:08:25.817620: Epoch 4304 +2024-11-22 10:08:25.817738: Current learning rate: 0.00499 +2024-11-22 10:08:45.624023: train_loss -0.7942 +2024-11-22 10:08:45.624273: val_loss -0.7865 +2024-11-22 10:08:45.624352: Pseudo dice [0.87] +2024-11-22 10:08:45.624434: Epoch time: 19.81 s +2024-11-22 10:08:46.494925: +2024-11-22 10:08:46.495144: Epoch 4305 +2024-11-22 10:08:46.495256: Current learning rate: 0.00499 +2024-11-22 10:09:04.537150: train_loss -0.7983 +2024-11-22 10:09:04.537360: val_loss -0.7362 +2024-11-22 10:09:04.537435: Pseudo dice [0.816] +2024-11-22 10:09:04.537511: Epoch time: 18.04 s +2024-11-22 10:09:05.406017: +2024-11-22 10:09:05.406260: Epoch 4306 +2024-11-22 10:09:05.406378: Current learning rate: 0.00499 +2024-11-22 10:09:24.166980: train_loss -0.7946 +2024-11-22 10:09:24.167217: val_loss -0.7732 +2024-11-22 10:09:24.167298: Pseudo dice [0.8471] +2024-11-22 10:09:24.167375: Epoch time: 18.76 s +2024-11-22 10:09:25.110965: +2024-11-22 10:09:25.111200: Epoch 4307 +2024-11-22 10:09:25.111317: Current learning rate: 0.00499 +2024-11-22 10:09:44.205765: train_loss -0.7933 +2024-11-22 10:09:44.205988: val_loss -0.7365 +2024-11-22 10:09:44.206072: Pseudo dice [0.8652] +2024-11-22 10:09:44.206149: Epoch time: 19.1 s +2024-11-22 10:09:45.074805: +2024-11-22 10:09:45.075172: Epoch 4308 +2024-11-22 10:09:45.075322: Current learning rate: 0.00499 +2024-11-22 10:10:03.874858: train_loss -0.7961 +2024-11-22 10:10:03.875108: val_loss -0.7784 +2024-11-22 10:10:03.875183: Pseudo dice [0.8475] +2024-11-22 10:10:03.875268: Epoch time: 18.8 s +2024-11-22 10:10:04.745969: +2024-11-22 10:10:04.746182: Epoch 4309 +2024-11-22 10:10:04.746296: Current learning rate: 0.00498 +2024-11-22 10:10:23.572181: train_loss -0.7911 +2024-11-22 10:10:23.572396: val_loss -0.7402 +2024-11-22 10:10:23.572474: Pseudo dice [0.8626] +2024-11-22 10:10:23.572553: Epoch time: 18.83 s +2024-11-22 10:10:24.437567: +2024-11-22 10:10:24.437778: Epoch 4310 +2024-11-22 10:10:24.437891: Current learning rate: 0.00498 +2024-11-22 10:10:43.048002: train_loss -0.7871 +2024-11-22 10:10:43.048224: val_loss -0.7372 +2024-11-22 10:10:43.048299: Pseudo dice [0.8191] +2024-11-22 10:10:43.048377: Epoch time: 18.61 s +2024-11-22 10:10:43.915059: +2024-11-22 10:10:43.915273: Epoch 4311 +2024-11-22 10:10:43.915384: Current learning rate: 0.00498 +2024-11-22 10:11:02.481879: train_loss -0.792 +2024-11-22 10:11:02.482102: val_loss -0.7633 +2024-11-22 10:11:02.482181: Pseudo dice [0.8428] +2024-11-22 10:11:02.482258: Epoch time: 18.57 s +2024-11-22 10:11:03.353169: +2024-11-22 10:11:03.353368: Epoch 4312 +2024-11-22 10:11:03.353480: Current learning rate: 0.00498 +2024-11-22 10:11:21.331580: train_loss -0.7929 +2024-11-22 10:11:21.331837: val_loss -0.7496 +2024-11-22 10:11:21.331913: Pseudo dice [0.8525] +2024-11-22 10:11:21.332023: Epoch time: 17.98 s +2024-11-22 10:11:22.199253: +2024-11-22 10:11:22.199448: Epoch 4313 +2024-11-22 10:11:22.199557: Current learning rate: 0.00498 +2024-11-22 10:11:41.805275: train_loss -0.8015 +2024-11-22 10:11:41.805493: val_loss -0.7322 +2024-11-22 10:11:41.805574: Pseudo dice [0.8587] +2024-11-22 10:11:41.805654: Epoch time: 19.61 s +2024-11-22 10:11:43.084894: +2024-11-22 10:11:43.085142: Epoch 4314 +2024-11-22 10:11:43.085259: Current learning rate: 0.00498 +2024-11-22 10:12:01.829095: train_loss -0.7944 +2024-11-22 10:12:01.829331: val_loss -0.7669 +2024-11-22 10:12:01.829412: Pseudo dice [0.8444] +2024-11-22 10:12:01.829502: Epoch time: 18.74 s +2024-11-22 10:12:02.702958: +2024-11-22 10:12:02.703194: Epoch 4315 +2024-11-22 10:12:02.703308: Current learning rate: 0.00498 +2024-11-22 10:12:20.720921: train_loss -0.7905 +2024-11-22 10:12:20.726314: val_loss -0.7737 +2024-11-22 10:12:20.726462: Pseudo dice [0.8484] +2024-11-22 10:12:20.726554: Epoch time: 18.02 s +2024-11-22 10:12:21.625408: +2024-11-22 10:12:21.625626: Epoch 4316 +2024-11-22 10:12:21.625739: Current learning rate: 0.00498 +2024-11-22 10:12:40.047266: train_loss -0.7871 +2024-11-22 10:12:40.047485: val_loss -0.6996 +2024-11-22 10:12:40.047557: Pseudo dice [0.8138] +2024-11-22 10:12:40.047638: Epoch time: 18.42 s +2024-11-22 10:12:40.950022: +2024-11-22 10:12:40.950229: Epoch 4317 +2024-11-22 10:12:40.950360: Current learning rate: 0.00498 +2024-11-22 10:12:59.368403: train_loss -0.7922 +2024-11-22 10:12:59.368620: val_loss -0.7716 +2024-11-22 10:12:59.368951: Pseudo dice [0.8544] +2024-11-22 10:12:59.369060: Epoch time: 18.42 s +2024-11-22 10:13:00.330689: +2024-11-22 10:13:00.330923: Epoch 4318 +2024-11-22 10:13:00.331044: Current learning rate: 0.00497 +2024-11-22 10:13:19.367653: train_loss -0.7866 +2024-11-22 10:13:19.367884: val_loss -0.7283 +2024-11-22 10:13:19.367962: Pseudo dice [0.8504] +2024-11-22 10:13:19.368042: Epoch time: 19.04 s +2024-11-22 10:13:20.243830: +2024-11-22 10:13:20.244065: Epoch 4319 +2024-11-22 10:13:20.244186: Current learning rate: 0.00497 +2024-11-22 10:13:39.426473: train_loss -0.7846 +2024-11-22 10:13:39.426744: val_loss -0.7535 +2024-11-22 10:13:39.426821: Pseudo dice [0.852] +2024-11-22 10:13:39.426909: Epoch time: 19.18 s +2024-11-22 10:13:40.303172: +2024-11-22 10:13:40.303373: Epoch 4320 +2024-11-22 10:13:40.303483: Current learning rate: 0.00497 +2024-11-22 10:13:59.291740: train_loss -0.7916 +2024-11-22 10:13:59.291954: val_loss -0.7268 +2024-11-22 10:13:59.292032: Pseudo dice [0.8297] +2024-11-22 10:13:59.292106: Epoch time: 18.99 s +2024-11-22 10:14:00.197404: +2024-11-22 10:14:00.197608: Epoch 4321 +2024-11-22 10:14:00.197720: Current learning rate: 0.00497 +2024-11-22 10:14:18.842398: train_loss -0.7883 +2024-11-22 10:14:18.842629: val_loss -0.7463 +2024-11-22 10:14:18.847934: Pseudo dice [0.839] +2024-11-22 10:14:18.848029: Epoch time: 18.65 s +2024-11-22 10:14:19.767196: +2024-11-22 10:14:19.767398: Epoch 4322 +2024-11-22 10:14:19.767510: Current learning rate: 0.00497 +2024-11-22 10:14:38.113827: train_loss -0.796 +2024-11-22 10:14:38.114051: val_loss -0.7252 +2024-11-22 10:14:38.114146: Pseudo dice [0.8413] +2024-11-22 10:14:38.114252: Epoch time: 18.35 s +2024-11-22 10:14:39.081589: +2024-11-22 10:14:39.081802: Epoch 4323 +2024-11-22 10:14:39.081913: Current learning rate: 0.00497 +2024-11-22 10:14:58.240153: train_loss -0.7968 +2024-11-22 10:14:58.240407: val_loss -0.7305 +2024-11-22 10:14:58.240508: Pseudo dice [0.8354] +2024-11-22 10:14:58.240595: Epoch time: 19.16 s +2024-11-22 10:14:59.139920: +2024-11-22 10:14:59.140134: Epoch 4324 +2024-11-22 10:14:59.140248: Current learning rate: 0.00497 +2024-11-22 10:15:16.994668: train_loss -0.801 +2024-11-22 10:15:16.994884: val_loss -0.7435 +2024-11-22 10:15:16.994964: Pseudo dice [0.837] +2024-11-22 10:15:16.995053: Epoch time: 17.86 s +2024-11-22 10:15:17.988784: +2024-11-22 10:15:17.989144: Epoch 4325 +2024-11-22 10:15:17.989259: Current learning rate: 0.00497 +2024-11-22 10:15:37.457112: train_loss -0.8009 +2024-11-22 10:15:37.457341: val_loss -0.7623 +2024-11-22 10:15:37.457424: Pseudo dice [0.848] +2024-11-22 10:15:37.457514: Epoch time: 19.47 s +2024-11-22 10:15:38.789224: +2024-11-22 10:15:38.789462: Epoch 4326 +2024-11-22 10:15:38.789579: Current learning rate: 0.00496 +2024-11-22 10:15:58.091838: train_loss -0.8013 +2024-11-22 10:15:58.092156: val_loss -0.7758 +2024-11-22 10:15:58.092237: Pseudo dice [0.8543] +2024-11-22 10:15:58.092323: Epoch time: 19.3 s +2024-11-22 10:15:58.963450: +2024-11-22 10:15:58.963683: Epoch 4327 +2024-11-22 10:15:58.963794: Current learning rate: 0.00496 +2024-11-22 10:16:16.311965: train_loss -0.7854 +2024-11-22 10:16:16.312188: val_loss -0.7505 +2024-11-22 10:16:16.312268: Pseudo dice [0.8244] +2024-11-22 10:16:16.312348: Epoch time: 17.35 s +2024-11-22 10:16:17.178039: +2024-11-22 10:16:17.178254: Epoch 4328 +2024-11-22 10:16:17.178366: Current learning rate: 0.00496 +2024-11-22 10:16:37.401531: train_loss -0.7808 +2024-11-22 10:16:37.401758: val_loss -0.7339 +2024-11-22 10:16:37.401841: Pseudo dice [0.854] +2024-11-22 10:16:37.401924: Epoch time: 20.22 s +2024-11-22 10:16:38.504042: +2024-11-22 10:16:38.504286: Epoch 4329 +2024-11-22 10:16:38.504411: Current learning rate: 0.00496 +2024-11-22 10:16:56.981038: train_loss -0.7885 +2024-11-22 10:16:56.981338: val_loss -0.7661 +2024-11-22 10:16:56.983980: Pseudo dice [0.85] +2024-11-22 10:16:56.984247: Epoch time: 18.48 s +2024-11-22 10:16:57.999464: +2024-11-22 10:16:57.999687: Epoch 4330 +2024-11-22 10:16:57.999808: Current learning rate: 0.00496 +2024-11-22 10:17:16.590880: train_loss -0.7972 +2024-11-22 10:17:16.591125: val_loss -0.726 +2024-11-22 10:17:16.591202: Pseudo dice [0.8221] +2024-11-22 10:17:16.591288: Epoch time: 18.59 s +2024-11-22 10:17:17.469367: +2024-11-22 10:17:17.469611: Epoch 4331 +2024-11-22 10:17:17.469745: Current learning rate: 0.00496 +2024-11-22 10:17:36.464589: train_loss -0.7834 +2024-11-22 10:17:36.464808: val_loss -0.7364 +2024-11-22 10:17:36.464885: Pseudo dice [0.8474] +2024-11-22 10:17:36.464960: Epoch time: 19.0 s +2024-11-22 10:17:37.337451: +2024-11-22 10:17:37.337708: Epoch 4332 +2024-11-22 10:17:37.337819: Current learning rate: 0.00496 +2024-11-22 10:17:54.962430: train_loss -0.7915 +2024-11-22 10:17:54.962706: val_loss -0.7584 +2024-11-22 10:17:54.962808: Pseudo dice [0.8448] +2024-11-22 10:17:54.962886: Epoch time: 17.63 s +2024-11-22 10:17:55.833867: +2024-11-22 10:17:55.834100: Epoch 4333 +2024-11-22 10:17:55.834218: Current learning rate: 0.00496 +2024-11-22 10:18:14.271862: train_loss -0.7943 +2024-11-22 10:18:14.272089: val_loss -0.7513 +2024-11-22 10:18:14.272163: Pseudo dice [0.8551] +2024-11-22 10:18:14.272238: Epoch time: 18.44 s +2024-11-22 10:18:15.142969: +2024-11-22 10:18:15.143181: Epoch 4334 +2024-11-22 10:18:15.143293: Current learning rate: 0.00495 +2024-11-22 10:18:34.158947: train_loss -0.7986 +2024-11-22 10:18:34.159274: val_loss -0.7224 +2024-11-22 10:18:34.159354: Pseudo dice [0.8616] +2024-11-22 10:18:34.159440: Epoch time: 19.02 s +2024-11-22 10:18:35.032209: +2024-11-22 10:18:35.032416: Epoch 4335 +2024-11-22 10:18:35.032529: Current learning rate: 0.00495 +2024-11-22 10:18:54.213039: train_loss -0.8007 +2024-11-22 10:18:54.213306: val_loss -0.7771 +2024-11-22 10:18:54.213383: Pseudo dice [0.8813] +2024-11-22 10:18:54.213456: Epoch time: 19.18 s +2024-11-22 10:18:55.080354: +2024-11-22 10:18:55.080763: Epoch 4336 +2024-11-22 10:18:55.080896: Current learning rate: 0.00495 +2024-11-22 10:19:13.813669: train_loss -0.7843 +2024-11-22 10:19:13.813889: val_loss -0.7578 +2024-11-22 10:19:13.813963: Pseudo dice [0.8418] +2024-11-22 10:19:13.814061: Epoch time: 18.73 s +2024-11-22 10:19:14.683122: +2024-11-22 10:19:14.683338: Epoch 4337 +2024-11-22 10:19:14.683452: Current learning rate: 0.00495 +2024-11-22 10:19:33.353477: train_loss -0.7937 +2024-11-22 10:19:33.353694: val_loss -0.7501 +2024-11-22 10:19:33.353768: Pseudo dice [0.8352] +2024-11-22 10:19:33.353844: Epoch time: 18.67 s +2024-11-22 10:19:34.599585: +2024-11-22 10:19:34.599792: Epoch 4338 +2024-11-22 10:19:34.599908: Current learning rate: 0.00495 +2024-11-22 10:19:53.043680: train_loss -0.7897 +2024-11-22 10:19:53.043928: val_loss -0.7573 +2024-11-22 10:19:53.044010: Pseudo dice [0.8542] +2024-11-22 10:19:53.044093: Epoch time: 18.44 s +2024-11-22 10:19:53.918575: +2024-11-22 10:19:53.918797: Epoch 4339 +2024-11-22 10:19:53.918913: Current learning rate: 0.00495 +2024-11-22 10:20:11.447809: train_loss -0.7877 +2024-11-22 10:20:11.448038: val_loss -0.7373 +2024-11-22 10:20:11.448113: Pseudo dice [0.8415] +2024-11-22 10:20:11.448190: Epoch time: 17.53 s +2024-11-22 10:20:12.498769: +2024-11-22 10:20:12.499043: Epoch 4340 +2024-11-22 10:20:12.499155: Current learning rate: 0.00495 +2024-11-22 10:20:31.304291: train_loss -0.7818 +2024-11-22 10:20:31.304538: val_loss -0.7341 +2024-11-22 10:20:31.304615: Pseudo dice [0.8238] +2024-11-22 10:20:31.304693: Epoch time: 18.81 s +2024-11-22 10:20:32.260607: +2024-11-22 10:20:32.260834: Epoch 4341 +2024-11-22 10:20:32.260947: Current learning rate: 0.00495 +2024-11-22 10:20:50.870578: train_loss -0.7884 +2024-11-22 10:20:50.870837: val_loss -0.7111 +2024-11-22 10:20:50.870948: Pseudo dice [0.8492] +2024-11-22 10:20:50.871041: Epoch time: 18.61 s +2024-11-22 10:20:51.746737: +2024-11-22 10:20:51.747022: Epoch 4342 +2024-11-22 10:20:51.747140: Current learning rate: 0.00494 +2024-11-22 10:21:09.739865: train_loss -0.7932 +2024-11-22 10:21:09.740168: val_loss -0.7261 +2024-11-22 10:21:09.740247: Pseudo dice [0.8356] +2024-11-22 10:21:09.740322: Epoch time: 17.99 s +2024-11-22 10:21:10.613835: +2024-11-22 10:21:10.614053: Epoch 4343 +2024-11-22 10:21:10.614169: Current learning rate: 0.00494 +2024-11-22 10:21:28.518465: train_loss -0.7992 +2024-11-22 10:21:28.518671: val_loss -0.7444 +2024-11-22 10:21:28.518983: Pseudo dice [0.8365] +2024-11-22 10:21:28.519077: Epoch time: 17.91 s +2024-11-22 10:21:29.378125: +2024-11-22 10:21:29.378342: Epoch 4344 +2024-11-22 10:21:29.378456: Current learning rate: 0.00494 +2024-11-22 10:21:47.447315: train_loss -0.7898 +2024-11-22 10:21:47.447582: val_loss -0.7347 +2024-11-22 10:21:47.447656: Pseudo dice [0.8416] +2024-11-22 10:21:47.447735: Epoch time: 18.07 s +2024-11-22 10:21:48.315687: +2024-11-22 10:21:48.315947: Epoch 4345 +2024-11-22 10:21:48.316072: Current learning rate: 0.00494 +2024-11-22 10:22:07.816712: train_loss -0.7858 +2024-11-22 10:22:07.816977: val_loss -0.7359 +2024-11-22 10:22:07.817062: Pseudo dice [0.8458] +2024-11-22 10:22:07.817146: Epoch time: 19.5 s +2024-11-22 10:22:08.720409: +2024-11-22 10:22:08.720619: Epoch 4346 +2024-11-22 10:22:08.720734: Current learning rate: 0.00494 +2024-11-22 10:22:27.534919: train_loss -0.798 +2024-11-22 10:22:27.535163: val_loss -0.7608 +2024-11-22 10:22:27.535242: Pseudo dice [0.8286] +2024-11-22 10:22:27.535323: Epoch time: 18.82 s +2024-11-22 10:22:28.418350: +2024-11-22 10:22:28.418781: Epoch 4347 +2024-11-22 10:22:28.418918: Current learning rate: 0.00494 +2024-11-22 10:22:47.346051: train_loss -0.7952 +2024-11-22 10:22:47.346269: val_loss -0.7602 +2024-11-22 10:22:47.346343: Pseudo dice [0.8442] +2024-11-22 10:22:47.346418: Epoch time: 18.93 s +2024-11-22 10:22:48.212048: +2024-11-22 10:22:48.212268: Epoch 4348 +2024-11-22 10:22:48.212382: Current learning rate: 0.00494 +2024-11-22 10:23:06.094460: train_loss -0.8005 +2024-11-22 10:23:06.094696: val_loss -0.7665 +2024-11-22 10:23:06.094776: Pseudo dice [0.853] +2024-11-22 10:23:06.094857: Epoch time: 17.88 s +2024-11-22 10:23:07.129384: +2024-11-22 10:23:07.129576: Epoch 4349 +2024-11-22 10:23:07.129687: Current learning rate: 0.00494 +2024-11-22 10:23:25.353235: train_loss -0.8013 +2024-11-22 10:23:25.353483: val_loss -0.7283 +2024-11-22 10:23:25.353563: Pseudo dice [0.8477] +2024-11-22 10:23:25.353650: Epoch time: 18.22 s +2024-11-22 10:23:26.926633: +2024-11-22 10:23:26.926904: Epoch 4350 +2024-11-22 10:23:26.927017: Current learning rate: 0.00493 +2024-11-22 10:23:45.872909: train_loss -0.795 +2024-11-22 10:23:45.873181: val_loss -0.7412 +2024-11-22 10:23:45.873263: Pseudo dice [0.8477] +2024-11-22 10:23:45.873342: Epoch time: 18.95 s +2024-11-22 10:23:46.963327: +2024-11-22 10:23:46.963541: Epoch 4351 +2024-11-22 10:23:46.963651: Current learning rate: 0.00493 +2024-11-22 10:24:06.375236: train_loss -0.7976 +2024-11-22 10:24:06.375465: val_loss -0.7545 +2024-11-22 10:24:06.375544: Pseudo dice [0.8323] +2024-11-22 10:24:06.375620: Epoch time: 19.41 s +2024-11-22 10:24:07.246793: +2024-11-22 10:24:07.247019: Epoch 4352 +2024-11-22 10:24:07.247134: Current learning rate: 0.00493 +2024-11-22 10:24:25.958550: train_loss -0.8002 +2024-11-22 10:24:25.958762: val_loss -0.7453 +2024-11-22 10:24:25.958838: Pseudo dice [0.8386] +2024-11-22 10:24:25.958915: Epoch time: 18.71 s +2024-11-22 10:24:26.843280: +2024-11-22 10:24:26.843513: Epoch 4353 +2024-11-22 10:24:26.843630: Current learning rate: 0.00493 +2024-11-22 10:24:44.925506: train_loss -0.8072 +2024-11-22 10:24:44.925768: val_loss -0.7335 +2024-11-22 10:24:44.925848: Pseudo dice [0.8434] +2024-11-22 10:24:44.925936: Epoch time: 18.08 s +2024-11-22 10:24:45.854587: +2024-11-22 10:24:45.854780: Epoch 4354 +2024-11-22 10:24:45.854889: Current learning rate: 0.00493 +2024-11-22 10:25:05.401132: train_loss -0.7944 +2024-11-22 10:25:05.401351: val_loss -0.739 +2024-11-22 10:25:05.401423: Pseudo dice [0.8391] +2024-11-22 10:25:05.401498: Epoch time: 19.55 s +2024-11-22 10:25:06.329111: +2024-11-22 10:25:06.329368: Epoch 4355 +2024-11-22 10:25:06.329479: Current learning rate: 0.00493 +2024-11-22 10:25:24.636724: train_loss -0.7904 +2024-11-22 10:25:24.637016: val_loss -0.7424 +2024-11-22 10:25:24.637099: Pseudo dice [0.8358] +2024-11-22 10:25:24.637177: Epoch time: 18.31 s +2024-11-22 10:25:25.517963: +2024-11-22 10:25:25.518165: Epoch 4356 +2024-11-22 10:25:25.518274: Current learning rate: 0.00493 +2024-11-22 10:25:44.274131: train_loss -0.7946 +2024-11-22 10:25:44.274352: val_loss -0.7282 +2024-11-22 10:25:44.274429: Pseudo dice [0.8201] +2024-11-22 10:25:44.274508: Epoch time: 18.76 s +2024-11-22 10:25:45.143116: +2024-11-22 10:25:45.143320: Epoch 4357 +2024-11-22 10:25:45.143435: Current learning rate: 0.00493 +2024-11-22 10:26:03.303030: train_loss -0.7775 +2024-11-22 10:26:03.303303: val_loss -0.7383 +2024-11-22 10:26:03.303380: Pseudo dice [0.8236] +2024-11-22 10:26:03.303465: Epoch time: 18.16 s +2024-11-22 10:26:04.179845: +2024-11-22 10:26:04.180046: Epoch 4358 +2024-11-22 10:26:04.180157: Current learning rate: 0.00493 +2024-11-22 10:26:23.544063: train_loss -0.7898 +2024-11-22 10:26:23.544279: val_loss -0.7413 +2024-11-22 10:26:23.544352: Pseudo dice [0.8297] +2024-11-22 10:26:23.544427: Epoch time: 19.37 s +2024-11-22 10:26:24.410643: +2024-11-22 10:26:24.410852: Epoch 4359 +2024-11-22 10:26:24.410966: Current learning rate: 0.00492 +2024-11-22 10:26:42.349384: train_loss -0.785 +2024-11-22 10:26:42.349609: val_loss -0.7265 +2024-11-22 10:26:42.349686: Pseudo dice [0.8273] +2024-11-22 10:26:42.349768: Epoch time: 17.94 s +2024-11-22 10:26:43.272297: +2024-11-22 10:26:43.272782: Epoch 4360 +2024-11-22 10:26:43.272911: Current learning rate: 0.00492 +2024-11-22 10:27:00.983166: train_loss -0.7864 +2024-11-22 10:27:00.983396: val_loss -0.7484 +2024-11-22 10:27:00.983480: Pseudo dice [0.8443] +2024-11-22 10:27:00.983565: Epoch time: 17.71 s +2024-11-22 10:27:01.859307: +2024-11-22 10:27:01.859558: Epoch 4361 +2024-11-22 10:27:01.859690: Current learning rate: 0.00492 +2024-11-22 10:27:20.786683: train_loss -0.7971 +2024-11-22 10:27:20.792168: val_loss -0.7341 +2024-11-22 10:27:20.792296: Pseudo dice [0.8366] +2024-11-22 10:27:20.792380: Epoch time: 18.93 s +2024-11-22 10:27:22.130112: +2024-11-22 10:27:22.130337: Epoch 4362 +2024-11-22 10:27:22.130459: Current learning rate: 0.00492 +2024-11-22 10:27:41.095202: train_loss -0.7877 +2024-11-22 10:27:41.095427: val_loss -0.7513 +2024-11-22 10:27:41.095503: Pseudo dice [0.844] +2024-11-22 10:27:41.095580: Epoch time: 18.97 s +2024-11-22 10:27:41.985682: +2024-11-22 10:27:41.985919: Epoch 4363 +2024-11-22 10:27:41.986042: Current learning rate: 0.00492 +2024-11-22 10:28:01.819954: train_loss -0.7782 +2024-11-22 10:28:01.820187: val_loss -0.7522 +2024-11-22 10:28:01.820263: Pseudo dice [0.8573] +2024-11-22 10:28:01.820338: Epoch time: 19.84 s +2024-11-22 10:28:02.759967: +2024-11-22 10:28:02.760197: Epoch 4364 +2024-11-22 10:28:02.760311: Current learning rate: 0.00492 +2024-11-22 10:28:22.192990: train_loss -0.7992 +2024-11-22 10:28:22.193290: val_loss -0.7617 +2024-11-22 10:28:22.193367: Pseudo dice [0.8499] +2024-11-22 10:28:22.193448: Epoch time: 19.43 s +2024-11-22 10:28:23.071579: +2024-11-22 10:28:23.071831: Epoch 4365 +2024-11-22 10:28:23.071939: Current learning rate: 0.00492 +2024-11-22 10:28:42.145531: train_loss -0.7994 +2024-11-22 10:28:42.145820: val_loss -0.7517 +2024-11-22 10:28:42.145900: Pseudo dice [0.8495] +2024-11-22 10:28:42.145973: Epoch time: 19.07 s +2024-11-22 10:28:43.006869: +2024-11-22 10:28:43.007082: Epoch 4366 +2024-11-22 10:28:43.007192: Current learning rate: 0.00492 +2024-11-22 10:29:01.295678: train_loss -0.7947 +2024-11-22 10:29:01.295898: val_loss -0.7739 +2024-11-22 10:29:01.295976: Pseudo dice [0.8619] +2024-11-22 10:29:01.296126: Epoch time: 18.29 s +2024-11-22 10:29:02.157175: +2024-11-22 10:29:02.157392: Epoch 4367 +2024-11-22 10:29:02.157515: Current learning rate: 0.00491 +2024-11-22 10:29:20.519612: train_loss -0.7847 +2024-11-22 10:29:20.519844: val_loss -0.7473 +2024-11-22 10:29:20.519922: Pseudo dice [0.8336] +2024-11-22 10:29:20.520007: Epoch time: 18.36 s +2024-11-22 10:29:21.390082: +2024-11-22 10:29:21.390305: Epoch 4368 +2024-11-22 10:29:21.390412: Current learning rate: 0.00491 +2024-11-22 10:29:40.266397: train_loss -0.7906 +2024-11-22 10:29:40.266630: val_loss -0.7693 +2024-11-22 10:29:40.268965: Pseudo dice [0.8488] +2024-11-22 10:29:40.269087: Epoch time: 18.88 s +2024-11-22 10:29:41.260407: +2024-11-22 10:29:41.260643: Epoch 4369 +2024-11-22 10:29:41.260756: Current learning rate: 0.00491 +2024-11-22 10:29:59.077989: train_loss -0.7913 +2024-11-22 10:29:59.078246: val_loss -0.7263 +2024-11-22 10:29:59.078535: Pseudo dice [0.8309] +2024-11-22 10:29:59.078675: Epoch time: 17.82 s +2024-11-22 10:29:59.956783: +2024-11-22 10:29:59.957147: Epoch 4370 +2024-11-22 10:29:59.957255: Current learning rate: 0.00491 +2024-11-22 10:30:18.370396: train_loss -0.7981 +2024-11-22 10:30:18.372734: val_loss -0.7438 +2024-11-22 10:30:18.372836: Pseudo dice [0.8251] +2024-11-22 10:30:18.372919: Epoch time: 18.41 s +2024-11-22 10:30:19.373069: +2024-11-22 10:30:19.373278: Epoch 4371 +2024-11-22 10:30:19.373393: Current learning rate: 0.00491 +2024-11-22 10:30:38.416683: train_loss -0.7984 +2024-11-22 10:30:38.416899: val_loss -0.743 +2024-11-22 10:30:38.416973: Pseudo dice [0.8459] +2024-11-22 10:30:38.417067: Epoch time: 19.04 s +2024-11-22 10:30:39.307063: +2024-11-22 10:30:39.307558: Epoch 4372 +2024-11-22 10:30:39.307693: Current learning rate: 0.00491 +2024-11-22 10:30:58.304603: train_loss -0.8046 +2024-11-22 10:30:58.304810: val_loss -0.7286 +2024-11-22 10:30:58.304884: Pseudo dice [0.8434] +2024-11-22 10:30:58.304964: Epoch time: 19.0 s +2024-11-22 10:30:59.173411: +2024-11-22 10:30:59.173649: Epoch 4373 +2024-11-22 10:30:59.173796: Current learning rate: 0.00491 +2024-11-22 10:31:18.915496: train_loss -0.7954 +2024-11-22 10:31:18.918207: val_loss -0.7403 +2024-11-22 10:31:18.918329: Pseudo dice [0.8327] +2024-11-22 10:31:18.918414: Epoch time: 19.74 s +2024-11-22 10:31:20.227033: +2024-11-22 10:31:20.227254: Epoch 4374 +2024-11-22 10:31:20.227365: Current learning rate: 0.00491 +2024-11-22 10:31:39.023686: train_loss -0.8031 +2024-11-22 10:31:39.023912: val_loss -0.7524 +2024-11-22 10:31:39.023986: Pseudo dice [0.8594] +2024-11-22 10:31:39.024072: Epoch time: 18.8 s +2024-11-22 10:31:39.878671: +2024-11-22 10:31:39.878901: Epoch 4375 +2024-11-22 10:31:39.879017: Current learning rate: 0.0049 +2024-11-22 10:31:57.637012: train_loss -0.8071 +2024-11-22 10:31:57.637341: val_loss -0.754 +2024-11-22 10:31:57.637432: Pseudo dice [0.8509] +2024-11-22 10:31:57.637525: Epoch time: 17.76 s +2024-11-22 10:31:58.520318: +2024-11-22 10:31:58.520523: Epoch 4376 +2024-11-22 10:31:58.520636: Current learning rate: 0.0049 +2024-11-22 10:32:16.444146: train_loss -0.794 +2024-11-22 10:32:16.444468: val_loss -0.7486 +2024-11-22 10:32:16.444546: Pseudo dice [0.8405] +2024-11-22 10:32:16.444629: Epoch time: 17.92 s +2024-11-22 10:32:17.320217: +2024-11-22 10:32:17.320448: Epoch 4377 +2024-11-22 10:32:17.320566: Current learning rate: 0.0049 +2024-11-22 10:32:36.231616: train_loss -0.7876 +2024-11-22 10:32:36.231855: val_loss -0.7483 +2024-11-22 10:32:36.231932: Pseudo dice [0.8428] +2024-11-22 10:32:36.232017: Epoch time: 18.91 s +2024-11-22 10:32:37.136195: +2024-11-22 10:32:37.136412: Epoch 4378 +2024-11-22 10:32:37.136528: Current learning rate: 0.0049 +2024-11-22 10:32:55.875013: train_loss -0.7654 +2024-11-22 10:32:55.875254: val_loss -0.7396 +2024-11-22 10:32:55.875335: Pseudo dice [0.8188] +2024-11-22 10:32:55.875413: Epoch time: 18.74 s +2024-11-22 10:32:56.839552: +2024-11-22 10:32:56.839762: Epoch 4379 +2024-11-22 10:32:56.839867: Current learning rate: 0.0049 +2024-11-22 10:33:16.363126: train_loss -0.786 +2024-11-22 10:33:16.363349: val_loss -0.73 +2024-11-22 10:33:16.363425: Pseudo dice [0.8349] +2024-11-22 10:33:16.363502: Epoch time: 19.52 s +2024-11-22 10:33:17.232612: +2024-11-22 10:33:17.232803: Epoch 4380 +2024-11-22 10:33:17.232909: Current learning rate: 0.0049 +2024-11-22 10:33:36.436109: train_loss -0.7832 +2024-11-22 10:33:36.436352: val_loss -0.7622 +2024-11-22 10:33:36.436428: Pseudo dice [0.8473] +2024-11-22 10:33:36.436511: Epoch time: 19.2 s +2024-11-22 10:33:37.308513: +2024-11-22 10:33:37.308739: Epoch 4381 +2024-11-22 10:33:37.308839: Current learning rate: 0.0049 +2024-11-22 10:33:56.475121: train_loss -0.7941 +2024-11-22 10:33:56.475349: val_loss -0.7798 +2024-11-22 10:33:56.475428: Pseudo dice [0.8493] +2024-11-22 10:33:56.475506: Epoch time: 19.17 s +2024-11-22 10:33:57.342787: +2024-11-22 10:33:57.343012: Epoch 4382 +2024-11-22 10:33:57.343120: Current learning rate: 0.0049 +2024-11-22 10:34:15.680061: train_loss -0.7842 +2024-11-22 10:34:15.680279: val_loss -0.7358 +2024-11-22 10:34:15.680412: Pseudo dice [0.8177] +2024-11-22 10:34:15.680491: Epoch time: 18.34 s +2024-11-22 10:34:16.546866: +2024-11-22 10:34:16.547104: Epoch 4383 +2024-11-22 10:34:16.547220: Current learning rate: 0.00489 +2024-11-22 10:34:36.247589: train_loss -0.7884 +2024-11-22 10:34:36.247812: val_loss -0.7243 +2024-11-22 10:34:36.247924: Pseudo dice [0.8383] +2024-11-22 10:34:36.248008: Epoch time: 19.7 s +2024-11-22 10:34:37.102596: +2024-11-22 10:34:37.102800: Epoch 4384 +2024-11-22 10:34:37.102914: Current learning rate: 0.00489 +2024-11-22 10:34:55.906824: train_loss -0.7999 +2024-11-22 10:34:55.907150: val_loss -0.7602 +2024-11-22 10:34:55.907228: Pseudo dice [0.8569] +2024-11-22 10:34:55.907319: Epoch time: 18.8 s +2024-11-22 10:34:56.894242: +2024-11-22 10:34:56.894474: Epoch 4385 +2024-11-22 10:34:56.894592: Current learning rate: 0.00489 +2024-11-22 10:35:15.157150: train_loss -0.795 +2024-11-22 10:35:15.157385: val_loss -0.7657 +2024-11-22 10:35:15.157464: Pseudo dice [0.8565] +2024-11-22 10:35:15.157544: Epoch time: 18.26 s +2024-11-22 10:35:16.467547: +2024-11-22 10:35:16.467756: Epoch 4386 +2024-11-22 10:35:16.467860: Current learning rate: 0.00489 +2024-11-22 10:35:35.495011: train_loss -0.788 +2024-11-22 10:35:35.495231: val_loss -0.7422 +2024-11-22 10:35:35.495306: Pseudo dice [0.8059] +2024-11-22 10:35:35.495380: Epoch time: 19.03 s +2024-11-22 10:35:36.454178: +2024-11-22 10:35:36.454395: Epoch 4387 +2024-11-22 10:35:36.454506: Current learning rate: 0.00489 +2024-11-22 10:35:55.421419: train_loss -0.7931 +2024-11-22 10:35:55.421629: val_loss -0.7644 +2024-11-22 10:35:55.421705: Pseudo dice [0.844] +2024-11-22 10:35:55.421782: Epoch time: 18.97 s +2024-11-22 10:35:56.294976: +2024-11-22 10:35:56.295184: Epoch 4388 +2024-11-22 10:35:56.295296: Current learning rate: 0.00489 +2024-11-22 10:36:14.989876: train_loss -0.7762 +2024-11-22 10:36:14.990126: val_loss -0.7118 +2024-11-22 10:36:14.990202: Pseudo dice [0.8391] +2024-11-22 10:36:14.990279: Epoch time: 18.7 s +2024-11-22 10:36:15.865058: +2024-11-22 10:36:15.865337: Epoch 4389 +2024-11-22 10:36:15.865455: Current learning rate: 0.00489 +2024-11-22 10:36:35.620206: train_loss -0.7695 +2024-11-22 10:36:35.621281: val_loss -0.7534 +2024-11-22 10:36:35.621364: Pseudo dice [0.8393] +2024-11-22 10:36:35.621448: Epoch time: 19.76 s +2024-11-22 10:36:36.488018: +2024-11-22 10:36:36.488232: Epoch 4390 +2024-11-22 10:36:36.488345: Current learning rate: 0.00489 +2024-11-22 10:36:54.967625: train_loss -0.7732 +2024-11-22 10:36:54.967869: val_loss -0.7157 +2024-11-22 10:36:54.967946: Pseudo dice [0.8317] +2024-11-22 10:36:54.968030: Epoch time: 18.48 s +2024-11-22 10:36:55.855165: +2024-11-22 10:36:55.855354: Epoch 4391 +2024-11-22 10:36:55.855494: Current learning rate: 0.00489 +2024-11-22 10:37:14.943338: train_loss -0.7912 +2024-11-22 10:37:14.943557: val_loss -0.7554 +2024-11-22 10:37:14.943632: Pseudo dice [0.8504] +2024-11-22 10:37:14.943709: Epoch time: 19.09 s +2024-11-22 10:37:15.807368: +2024-11-22 10:37:15.807601: Epoch 4392 +2024-11-22 10:37:15.807712: Current learning rate: 0.00488 +2024-11-22 10:37:34.288494: train_loss -0.7857 +2024-11-22 10:37:34.288747: val_loss -0.7399 +2024-11-22 10:37:34.288824: Pseudo dice [0.8355] +2024-11-22 10:37:34.288907: Epoch time: 18.48 s +2024-11-22 10:37:35.209149: +2024-11-22 10:37:35.209363: Epoch 4393 +2024-11-22 10:37:35.209480: Current learning rate: 0.00488 +2024-11-22 10:37:53.418350: train_loss -0.7848 +2024-11-22 10:37:53.418572: val_loss -0.7571 +2024-11-22 10:37:53.418650: Pseudo dice [0.8536] +2024-11-22 10:37:53.418729: Epoch time: 18.21 s +2024-11-22 10:37:54.282668: +2024-11-22 10:37:54.282903: Epoch 4394 +2024-11-22 10:37:54.283021: Current learning rate: 0.00488 +2024-11-22 10:38:13.239799: train_loss -0.7942 +2024-11-22 10:38:13.240033: val_loss -0.7702 +2024-11-22 10:38:13.240106: Pseudo dice [0.8613] +2024-11-22 10:38:13.240184: Epoch time: 18.96 s +2024-11-22 10:38:14.090286: +2024-11-22 10:38:14.090477: Epoch 4395 +2024-11-22 10:38:14.090586: Current learning rate: 0.00488 +2024-11-22 10:38:33.255367: train_loss -0.7777 +2024-11-22 10:38:33.255913: val_loss -0.7263 +2024-11-22 10:38:33.256008: Pseudo dice [0.8405] +2024-11-22 10:38:33.256085: Epoch time: 19.17 s +2024-11-22 10:38:34.104666: +2024-11-22 10:38:34.104880: Epoch 4396 +2024-11-22 10:38:34.105022: Current learning rate: 0.00488 +2024-11-22 10:38:52.332201: train_loss -0.7868 +2024-11-22 10:38:52.332483: val_loss -0.7663 +2024-11-22 10:38:52.332572: Pseudo dice [0.8448] +2024-11-22 10:38:52.332654: Epoch time: 18.23 s +2024-11-22 10:38:53.193120: +2024-11-22 10:38:53.193326: Epoch 4397 +2024-11-22 10:38:53.193434: Current learning rate: 0.00488 +2024-11-22 10:39:13.226694: train_loss -0.7791 +2024-11-22 10:39:13.226913: val_loss -0.7512 +2024-11-22 10:39:13.227000: Pseudo dice [0.8637] +2024-11-22 10:39:13.227077: Epoch time: 20.03 s +2024-11-22 10:39:14.505392: +2024-11-22 10:39:14.505645: Epoch 4398 +2024-11-22 10:39:14.505771: Current learning rate: 0.00488 +2024-11-22 10:39:33.204294: train_loss -0.7896 +2024-11-22 10:39:33.204535: val_loss -0.7544 +2024-11-22 10:39:33.204616: Pseudo dice [0.8394] +2024-11-22 10:39:33.204695: Epoch time: 18.7 s +2024-11-22 10:39:34.075162: +2024-11-22 10:39:34.075378: Epoch 4399 +2024-11-22 10:39:34.075487: Current learning rate: 0.00488 +2024-11-22 10:39:52.388315: train_loss -0.79 +2024-11-22 10:39:52.390752: val_loss -0.7358 +2024-11-22 10:39:52.390857: Pseudo dice [0.849] +2024-11-22 10:39:52.390947: Epoch time: 18.31 s +2024-11-22 10:39:53.572086: +2024-11-22 10:39:53.572304: Epoch 4400 +2024-11-22 10:39:53.572415: Current learning rate: 0.00487 +2024-11-22 10:40:11.688876: train_loss -0.7953 +2024-11-22 10:40:11.689091: val_loss -0.739 +2024-11-22 10:40:11.689171: Pseudo dice [0.8565] +2024-11-22 10:40:11.689255: Epoch time: 18.12 s +2024-11-22 10:40:12.558923: +2024-11-22 10:40:12.559144: Epoch 4401 +2024-11-22 10:40:12.559255: Current learning rate: 0.00487 +2024-11-22 10:40:32.466680: train_loss -0.7935 +2024-11-22 10:40:32.466944: val_loss -0.7547 +2024-11-22 10:40:32.467028: Pseudo dice [0.8401] +2024-11-22 10:40:32.467109: Epoch time: 19.91 s +2024-11-22 10:40:33.338623: +2024-11-22 10:40:33.338861: Epoch 4402 +2024-11-22 10:40:33.338982: Current learning rate: 0.00487 +2024-11-22 10:40:51.825701: train_loss -0.7981 +2024-11-22 10:40:51.828088: val_loss -0.744 +2024-11-22 10:40:51.828190: Pseudo dice [0.8376] +2024-11-22 10:40:51.828270: Epoch time: 18.49 s +2024-11-22 10:40:52.733972: +2024-11-22 10:40:52.734304: Epoch 4403 +2024-11-22 10:40:52.734419: Current learning rate: 0.00487 +2024-11-22 10:41:10.829139: train_loss -0.7949 +2024-11-22 10:41:10.829419: val_loss -0.7605 +2024-11-22 10:41:10.829498: Pseudo dice [0.8541] +2024-11-22 10:41:10.829580: Epoch time: 18.1 s +2024-11-22 10:41:11.702300: +2024-11-22 10:41:11.702550: Epoch 4404 +2024-11-22 10:41:11.702667: Current learning rate: 0.00487 +2024-11-22 10:41:30.428505: train_loss -0.7933 +2024-11-22 10:41:30.428736: val_loss -0.746 +2024-11-22 10:41:30.428811: Pseudo dice [0.8422] +2024-11-22 10:41:30.428895: Epoch time: 18.73 s +2024-11-22 10:41:31.295938: +2024-11-22 10:41:31.296161: Epoch 4405 +2024-11-22 10:41:31.296298: Current learning rate: 0.00487 +2024-11-22 10:41:50.813670: train_loss -0.7873 +2024-11-22 10:41:50.813882: val_loss -0.7484 +2024-11-22 10:41:50.813957: Pseudo dice [0.8601] +2024-11-22 10:41:50.814115: Epoch time: 19.52 s +2024-11-22 10:41:51.689465: +2024-11-22 10:41:51.689701: Epoch 4406 +2024-11-22 10:41:51.689809: Current learning rate: 0.00487 +2024-11-22 10:42:10.506088: train_loss -0.7973 +2024-11-22 10:42:10.506303: val_loss -0.7475 +2024-11-22 10:42:10.506380: Pseudo dice [0.8492] +2024-11-22 10:42:10.506456: Epoch time: 18.82 s +2024-11-22 10:42:11.374865: +2024-11-22 10:42:11.375083: Epoch 4407 +2024-11-22 10:42:11.375196: Current learning rate: 0.00487 +2024-11-22 10:42:30.547413: train_loss -0.7993 +2024-11-22 10:42:30.547648: val_loss -0.7538 +2024-11-22 10:42:30.547724: Pseudo dice [0.8461] +2024-11-22 10:42:30.547804: Epoch time: 19.17 s +2024-11-22 10:42:31.438246: +2024-11-22 10:42:31.438498: Epoch 4408 +2024-11-22 10:42:31.438609: Current learning rate: 0.00486 +2024-11-22 10:42:51.175635: train_loss -0.7929 +2024-11-22 10:42:51.175943: val_loss -0.7531 +2024-11-22 10:42:51.176159: Pseudo dice [0.8318] +2024-11-22 10:42:51.176247: Epoch time: 19.74 s +2024-11-22 10:42:52.047032: +2024-11-22 10:42:52.047244: Epoch 4409 +2024-11-22 10:42:52.047355: Current learning rate: 0.00486 +2024-11-22 10:43:10.621802: train_loss -0.7962 +2024-11-22 10:43:10.622023: val_loss -0.7428 +2024-11-22 10:43:10.622099: Pseudo dice [0.857] +2024-11-22 10:43:10.622186: Epoch time: 18.58 s +2024-11-22 10:43:11.881687: +2024-11-22 10:43:11.881935: Epoch 4410 +2024-11-22 10:43:11.882060: Current learning rate: 0.00486 +2024-11-22 10:43:31.327639: train_loss -0.7876 +2024-11-22 10:43:31.327875: val_loss -0.7466 +2024-11-22 10:43:31.328028: Pseudo dice [0.8431] +2024-11-22 10:43:31.328121: Epoch time: 19.45 s +2024-11-22 10:43:32.203637: +2024-11-22 10:43:32.203862: Epoch 4411 +2024-11-22 10:43:32.203970: Current learning rate: 0.00486 +2024-11-22 10:43:50.795071: train_loss -0.7983 +2024-11-22 10:43:50.795323: val_loss -0.7479 +2024-11-22 10:43:50.797583: Pseudo dice [0.8283] +2024-11-22 10:43:50.797681: Epoch time: 18.59 s +2024-11-22 10:43:51.792758: +2024-11-22 10:43:51.793080: Epoch 4412 +2024-11-22 10:43:51.793187: Current learning rate: 0.00486 +2024-11-22 10:44:11.282616: train_loss -0.7895 +2024-11-22 10:44:11.282831: val_loss -0.7156 +2024-11-22 10:44:11.282903: Pseudo dice [0.8259] +2024-11-22 10:44:11.282978: Epoch time: 19.49 s +2024-11-22 10:44:12.163110: +2024-11-22 10:44:12.163331: Epoch 4413 +2024-11-22 10:44:12.163445: Current learning rate: 0.00486 +2024-11-22 10:44:29.774266: train_loss -0.7897 +2024-11-22 10:44:29.774485: val_loss -0.7713 +2024-11-22 10:44:29.774561: Pseudo dice [0.8419] +2024-11-22 10:44:29.774640: Epoch time: 17.61 s +2024-11-22 10:44:30.646267: +2024-11-22 10:44:30.646470: Epoch 4414 +2024-11-22 10:44:30.646583: Current learning rate: 0.00486 +2024-11-22 10:44:49.889155: train_loss -0.7992 +2024-11-22 10:44:49.889428: val_loss -0.7478 +2024-11-22 10:44:49.889507: Pseudo dice [0.8577] +2024-11-22 10:44:49.889583: Epoch time: 19.24 s +2024-11-22 10:44:50.767855: +2024-11-22 10:44:50.768079: Epoch 4415 +2024-11-22 10:44:50.768198: Current learning rate: 0.00486 +2024-11-22 10:45:09.228118: train_loss -0.7977 +2024-11-22 10:45:09.228372: val_loss -0.7438 +2024-11-22 10:45:09.228450: Pseudo dice [0.8316] +2024-11-22 10:45:09.233672: Epoch time: 18.46 s +2024-11-22 10:45:10.158973: +2024-11-22 10:45:10.159209: Epoch 4416 +2024-11-22 10:45:10.159321: Current learning rate: 0.00485 +2024-11-22 10:45:28.633901: train_loss -0.8002 +2024-11-22 10:45:28.634137: val_loss -0.7335 +2024-11-22 10:45:28.634214: Pseudo dice [0.8341] +2024-11-22 10:45:28.634292: Epoch time: 18.48 s +2024-11-22 10:45:29.762570: +2024-11-22 10:45:29.762808: Epoch 4417 +2024-11-22 10:45:29.762919: Current learning rate: 0.00485 +2024-11-22 10:45:48.350941: train_loss -0.793 +2024-11-22 10:45:48.356347: val_loss -0.7652 +2024-11-22 10:45:48.356460: Pseudo dice [0.8505] +2024-11-22 10:45:48.356544: Epoch time: 18.59 s +2024-11-22 10:45:49.235663: +2024-11-22 10:45:49.235903: Epoch 4418 +2024-11-22 10:45:49.236015: Current learning rate: 0.00485 +2024-11-22 10:46:07.758319: train_loss -0.7794 +2024-11-22 10:46:07.758535: val_loss -0.7499 +2024-11-22 10:46:07.758610: Pseudo dice [0.8303] +2024-11-22 10:46:07.758689: Epoch time: 18.52 s +2024-11-22 10:46:08.626580: +2024-11-22 10:46:08.626806: Epoch 4419 +2024-11-22 10:46:08.626920: Current learning rate: 0.00485 +2024-11-22 10:46:26.552903: train_loss -0.7823 +2024-11-22 10:46:26.553175: val_loss -0.7465 +2024-11-22 10:46:26.553272: Pseudo dice [0.8249] +2024-11-22 10:46:26.553369: Epoch time: 17.93 s +2024-11-22 10:46:27.426640: +2024-11-22 10:46:27.426949: Epoch 4420 +2024-11-22 10:46:27.427067: Current learning rate: 0.00485 +2024-11-22 10:46:45.700097: train_loss -0.7902 +2024-11-22 10:46:45.700321: val_loss -0.7503 +2024-11-22 10:46:45.700396: Pseudo dice [0.8468] +2024-11-22 10:46:45.700474: Epoch time: 18.27 s +2024-11-22 10:46:46.565899: +2024-11-22 10:46:46.566133: Epoch 4421 +2024-11-22 10:46:46.566257: Current learning rate: 0.00485 +2024-11-22 10:47:05.068364: train_loss -0.7898 +2024-11-22 10:47:05.068775: val_loss -0.7501 +2024-11-22 10:47:05.068859: Pseudo dice [0.8403] +2024-11-22 10:47:05.068936: Epoch time: 18.5 s +2024-11-22 10:47:06.377409: +2024-11-22 10:47:06.377621: Epoch 4422 +2024-11-22 10:47:06.377734: Current learning rate: 0.00485 +2024-11-22 10:47:24.569125: train_loss -0.7811 +2024-11-22 10:47:24.569354: val_loss -0.7291 +2024-11-22 10:47:24.569429: Pseudo dice [0.8356] +2024-11-22 10:47:24.569506: Epoch time: 18.19 s +2024-11-22 10:47:25.503752: +2024-11-22 10:47:25.503971: Epoch 4423 +2024-11-22 10:47:25.504087: Current learning rate: 0.00485 +2024-11-22 10:47:45.161299: train_loss -0.7897 +2024-11-22 10:47:45.161561: val_loss -0.7569 +2024-11-22 10:47:45.161641: Pseudo dice [0.84] +2024-11-22 10:47:45.161731: Epoch time: 19.66 s +2024-11-22 10:47:46.054223: +2024-11-22 10:47:46.054451: Epoch 4424 +2024-11-22 10:47:46.054569: Current learning rate: 0.00484 +2024-11-22 10:48:04.568309: train_loss -0.7943 +2024-11-22 10:48:04.568529: val_loss -0.7571 +2024-11-22 10:48:04.568606: Pseudo dice [0.8369] +2024-11-22 10:48:04.568685: Epoch time: 18.51 s +2024-11-22 10:48:05.545098: +2024-11-22 10:48:05.545325: Epoch 4425 +2024-11-22 10:48:05.545439: Current learning rate: 0.00484 +2024-11-22 10:48:23.472816: train_loss -0.7868 +2024-11-22 10:48:23.473037: val_loss -0.7453 +2024-11-22 10:48:23.473141: Pseudo dice [0.8446] +2024-11-22 10:48:23.473253: Epoch time: 17.93 s +2024-11-22 10:48:24.343692: +2024-11-22 10:48:24.343905: Epoch 4426 +2024-11-22 10:48:24.344022: Current learning rate: 0.00484 +2024-11-22 10:48:43.428266: train_loss -0.7908 +2024-11-22 10:48:43.428488: val_loss -0.7419 +2024-11-22 10:48:43.428563: Pseudo dice [0.8359] +2024-11-22 10:48:43.428638: Epoch time: 19.09 s +2024-11-22 10:48:44.296593: +2024-11-22 10:48:44.296916: Epoch 4427 +2024-11-22 10:48:44.297031: Current learning rate: 0.00484 +2024-11-22 10:49:02.796034: train_loss -0.787 +2024-11-22 10:49:02.796285: val_loss -0.746 +2024-11-22 10:49:02.796364: Pseudo dice [0.8378] +2024-11-22 10:49:02.796448: Epoch time: 18.5 s +2024-11-22 10:49:03.670637: +2024-11-22 10:49:03.670968: Epoch 4428 +2024-11-22 10:49:03.671087: Current learning rate: 0.00484 +2024-11-22 10:49:22.959059: train_loss -0.7984 +2024-11-22 10:49:22.959268: val_loss -0.7491 +2024-11-22 10:49:22.959341: Pseudo dice [0.8428] +2024-11-22 10:49:22.959414: Epoch time: 19.29 s +2024-11-22 10:49:23.831428: +2024-11-22 10:49:23.831642: Epoch 4429 +2024-11-22 10:49:23.831753: Current learning rate: 0.00484 +2024-11-22 10:49:43.066790: train_loss -0.7978 +2024-11-22 10:49:43.067013: val_loss -0.7637 +2024-11-22 10:49:43.067089: Pseudo dice [0.8375] +2024-11-22 10:49:43.067167: Epoch time: 19.24 s +2024-11-22 10:49:43.941466: +2024-11-22 10:49:43.941692: Epoch 4430 +2024-11-22 10:49:43.941811: Current learning rate: 0.00484 +2024-11-22 10:50:02.878377: train_loss -0.795 +2024-11-22 10:50:02.878611: val_loss -0.7438 +2024-11-22 10:50:02.878691: Pseudo dice [0.8307] +2024-11-22 10:50:02.878772: Epoch time: 18.94 s +2024-11-22 10:50:03.753748: +2024-11-22 10:50:03.753957: Epoch 4431 +2024-11-22 10:50:03.754073: Current learning rate: 0.00484 +2024-11-22 10:50:23.147930: train_loss -0.7972 +2024-11-22 10:50:23.148268: val_loss -0.7394 +2024-11-22 10:50:23.148350: Pseudo dice [0.8424] +2024-11-22 10:50:23.148442: Epoch time: 19.39 s +2024-11-22 10:50:24.078719: +2024-11-22 10:50:24.078917: Epoch 4432 +2024-11-22 10:50:24.079035: Current learning rate: 0.00484 +2024-11-22 10:50:42.162790: train_loss -0.7925 +2024-11-22 10:50:42.163011: val_loss -0.7168 +2024-11-22 10:50:42.163089: Pseudo dice [0.8357] +2024-11-22 10:50:42.163165: Epoch time: 18.08 s +2024-11-22 10:50:43.031869: +2024-11-22 10:50:43.032088: Epoch 4433 +2024-11-22 10:50:43.032204: Current learning rate: 0.00483 +2024-11-22 10:51:02.325023: train_loss -0.7991 +2024-11-22 10:51:02.325887: val_loss -0.771 +2024-11-22 10:51:02.325962: Pseudo dice [0.8435] +2024-11-22 10:51:02.326045: Epoch time: 19.29 s +2024-11-22 10:51:03.594614: +2024-11-22 10:51:03.594823: Epoch 4434 +2024-11-22 10:51:03.594934: Current learning rate: 0.00483 +2024-11-22 10:51:22.439450: train_loss -0.8035 +2024-11-22 10:51:22.439718: val_loss -0.7409 +2024-11-22 10:51:22.439802: Pseudo dice [0.8506] +2024-11-22 10:51:22.439912: Epoch time: 18.85 s +2024-11-22 10:51:23.316524: +2024-11-22 10:51:23.316820: Epoch 4435 +2024-11-22 10:51:23.316932: Current learning rate: 0.00483 +2024-11-22 10:51:42.461296: train_loss -0.8014 +2024-11-22 10:51:42.461530: val_loss -0.7765 +2024-11-22 10:51:42.461607: Pseudo dice [0.8411] +2024-11-22 10:51:42.461683: Epoch time: 19.15 s +2024-11-22 10:51:43.332083: +2024-11-22 10:51:43.332314: Epoch 4436 +2024-11-22 10:51:43.332424: Current learning rate: 0.00483 +2024-11-22 10:52:02.390781: train_loss -0.8017 +2024-11-22 10:52:02.391014: val_loss -0.7711 +2024-11-22 10:52:02.391089: Pseudo dice [0.8633] +2024-11-22 10:52:02.391168: Epoch time: 19.06 s +2024-11-22 10:52:03.277344: +2024-11-22 10:52:03.277559: Epoch 4437 +2024-11-22 10:52:03.277673: Current learning rate: 0.00483 +2024-11-22 10:52:21.893616: train_loss -0.7943 +2024-11-22 10:52:21.893872: val_loss -0.7549 +2024-11-22 10:52:21.893953: Pseudo dice [0.8557] +2024-11-22 10:52:21.894051: Epoch time: 18.62 s +2024-11-22 10:52:22.773720: +2024-11-22 10:52:22.773942: Epoch 4438 +2024-11-22 10:52:22.774061: Current learning rate: 0.00483 +2024-11-22 10:52:42.570189: train_loss -0.7927 +2024-11-22 10:52:42.575590: val_loss -0.7396 +2024-11-22 10:52:42.575675: Pseudo dice [0.8591] +2024-11-22 10:52:42.575756: Epoch time: 19.8 s +2024-11-22 10:52:43.480777: +2024-11-22 10:52:43.481003: Epoch 4439 +2024-11-22 10:52:43.481118: Current learning rate: 0.00483 +2024-11-22 10:53:01.602829: train_loss -0.7891 +2024-11-22 10:53:01.603136: val_loss -0.7451 +2024-11-22 10:53:01.603218: Pseudo dice [0.8656] +2024-11-22 10:53:01.603297: Epoch time: 18.12 s +2024-11-22 10:53:02.479366: +2024-11-22 10:53:02.479574: Epoch 4440 +2024-11-22 10:53:02.479687: Current learning rate: 0.00483 +2024-11-22 10:53:20.319547: train_loss -0.7907 +2024-11-22 10:53:20.319792: val_loss -0.7536 +2024-11-22 10:53:20.319868: Pseudo dice [0.8561] +2024-11-22 10:53:20.319981: Epoch time: 17.84 s +2024-11-22 10:53:21.193178: +2024-11-22 10:53:21.193384: Epoch 4441 +2024-11-22 10:53:21.193494: Current learning rate: 0.00482 +2024-11-22 10:53:39.772489: train_loss -0.8054 +2024-11-22 10:53:39.772741: val_loss -0.755 +2024-11-22 10:53:39.772814: Pseudo dice [0.8662] +2024-11-22 10:53:39.772899: Epoch time: 18.58 s +2024-11-22 10:53:40.656835: +2024-11-22 10:53:40.657126: Epoch 4442 +2024-11-22 10:53:40.657238: Current learning rate: 0.00482 +2024-11-22 10:53:58.406815: train_loss -0.7971 +2024-11-22 10:53:58.407043: val_loss -0.76 +2024-11-22 10:53:58.407123: Pseudo dice [0.8431] +2024-11-22 10:53:58.407201: Epoch time: 17.75 s +2024-11-22 10:53:59.282928: +2024-11-22 10:53:59.283133: Epoch 4443 +2024-11-22 10:53:59.283243: Current learning rate: 0.00482 +2024-11-22 10:54:18.093889: train_loss -0.7912 +2024-11-22 10:54:18.094162: val_loss -0.7386 +2024-11-22 10:54:18.094240: Pseudo dice [0.8516] +2024-11-22 10:54:18.094323: Epoch time: 18.81 s +2024-11-22 10:54:18.991205: +2024-11-22 10:54:18.991399: Epoch 4444 +2024-11-22 10:54:18.991511: Current learning rate: 0.00482 +2024-11-22 10:54:37.792038: train_loss -0.7886 +2024-11-22 10:54:37.792261: val_loss -0.7338 +2024-11-22 10:54:37.792406: Pseudo dice [0.8416] +2024-11-22 10:54:37.792488: Epoch time: 18.8 s +2024-11-22 10:54:38.666473: +2024-11-22 10:54:38.666761: Epoch 4445 +2024-11-22 10:54:38.666875: Current learning rate: 0.00482 +2024-11-22 10:54:57.333083: train_loss -0.7991 +2024-11-22 10:54:57.333326: val_loss -0.727 +2024-11-22 10:54:57.333405: Pseudo dice [0.8668] +2024-11-22 10:54:57.333486: Epoch time: 18.67 s +2024-11-22 10:54:57.333546: Yayy! New best EMA pseudo Dice: 0.8507 +2024-11-22 10:54:58.875803: +2024-11-22 10:54:58.876018: Epoch 4446 +2024-11-22 10:54:58.876129: Current learning rate: 0.00482 +2024-11-22 10:55:16.968215: train_loss -0.7862 +2024-11-22 10:55:16.968493: val_loss -0.7541 +2024-11-22 10:55:16.968579: Pseudo dice [0.8396] +2024-11-22 10:55:16.968661: Epoch time: 18.09 s +2024-11-22 10:55:17.830173: +2024-11-22 10:55:17.830386: Epoch 4447 +2024-11-22 10:55:17.830497: Current learning rate: 0.00482 +2024-11-22 10:55:35.585256: train_loss -0.7928 +2024-11-22 10:55:35.585495: val_loss -0.7401 +2024-11-22 10:55:35.585572: Pseudo dice [0.8534] +2024-11-22 10:55:35.585649: Epoch time: 17.76 s +2024-11-22 10:55:36.454310: +2024-11-22 10:55:36.454539: Epoch 4448 +2024-11-22 10:55:36.454648: Current learning rate: 0.00482 +2024-11-22 10:55:54.714332: train_loss -0.7983 +2024-11-22 10:55:54.714595: val_loss -0.7549 +2024-11-22 10:55:54.714672: Pseudo dice [0.8267] +2024-11-22 10:55:54.714779: Epoch time: 18.26 s +2024-11-22 10:55:55.587568: +2024-11-22 10:55:55.587787: Epoch 4449 +2024-11-22 10:55:55.587896: Current learning rate: 0.00481 +2024-11-22 10:56:15.657926: train_loss -0.7929 +2024-11-22 10:56:15.658159: val_loss -0.776 +2024-11-22 10:56:15.658234: Pseudo dice [0.8439] +2024-11-22 10:56:15.658313: Epoch time: 20.07 s +2024-11-22 10:56:16.904314: +2024-11-22 10:56:16.904538: Epoch 4450 +2024-11-22 10:56:16.904649: Current learning rate: 0.00481 +2024-11-22 10:56:35.208282: train_loss -0.7964 +2024-11-22 10:56:35.208562: val_loss -0.7345 +2024-11-22 10:56:35.208643: Pseudo dice [0.8469] +2024-11-22 10:56:35.208719: Epoch time: 18.3 s +2024-11-22 10:56:36.081467: +2024-11-22 10:56:36.081717: Epoch 4451 +2024-11-22 10:56:36.081833: Current learning rate: 0.00481 +2024-11-22 10:56:55.020013: train_loss -0.7916 +2024-11-22 10:56:55.020234: val_loss -0.7589 +2024-11-22 10:56:55.020311: Pseudo dice [0.8531] +2024-11-22 10:56:55.020388: Epoch time: 18.94 s +2024-11-22 10:56:55.892387: +2024-11-22 10:56:55.892673: Epoch 4452 +2024-11-22 10:56:55.892790: Current learning rate: 0.00481 +2024-11-22 10:57:14.412431: train_loss -0.7951 +2024-11-22 10:57:14.412663: val_loss -0.7498 +2024-11-22 10:57:14.412736: Pseudo dice [0.8278] +2024-11-22 10:57:14.412819: Epoch time: 18.52 s +2024-11-22 10:57:15.320496: +2024-11-22 10:57:15.320718: Epoch 4453 +2024-11-22 10:57:15.320836: Current learning rate: 0.00481 +2024-11-22 10:57:34.432637: train_loss -0.7943 +2024-11-22 10:57:34.432859: val_loss -0.7252 +2024-11-22 10:57:34.432941: Pseudo dice [0.8286] +2024-11-22 10:57:34.433051: Epoch time: 19.11 s +2024-11-22 10:57:35.300415: +2024-11-22 10:57:35.300668: Epoch 4454 +2024-11-22 10:57:35.300784: Current learning rate: 0.00481 +2024-11-22 10:57:54.147020: train_loss -0.7977 +2024-11-22 10:57:54.147240: val_loss -0.7734 +2024-11-22 10:57:54.147416: Pseudo dice [0.8479] +2024-11-22 10:57:54.147497: Epoch time: 18.85 s +2024-11-22 10:57:55.014709: +2024-11-22 10:57:55.014914: Epoch 4455 +2024-11-22 10:57:55.015039: Current learning rate: 0.00481 +2024-11-22 10:58:13.959699: train_loss -0.8 +2024-11-22 10:58:13.959952: val_loss -0.7498 +2024-11-22 10:58:13.960034: Pseudo dice [0.8445] +2024-11-22 10:58:13.960111: Epoch time: 18.95 s +2024-11-22 10:58:14.829532: +2024-11-22 10:58:14.829834: Epoch 4456 +2024-11-22 10:58:14.829965: Current learning rate: 0.00481 +2024-11-22 10:58:34.349069: train_loss -0.8023 +2024-11-22 10:58:34.349324: val_loss -0.7407 +2024-11-22 10:58:34.349402: Pseudo dice [0.8356] +2024-11-22 10:58:34.349481: Epoch time: 19.52 s +2024-11-22 10:58:35.214557: +2024-11-22 10:58:35.214791: Epoch 4457 +2024-11-22 10:58:35.214904: Current learning rate: 0.0048 +2024-11-22 10:58:53.953459: train_loss -0.7914 +2024-11-22 10:58:53.953679: val_loss -0.7377 +2024-11-22 10:58:53.953762: Pseudo dice [0.8507] +2024-11-22 10:58:53.953841: Epoch time: 18.74 s +2024-11-22 10:58:55.223795: +2024-11-22 10:58:55.224016: Epoch 4458 +2024-11-22 10:58:55.224128: Current learning rate: 0.0048 +2024-11-22 10:59:14.341685: train_loss -0.7819 +2024-11-22 10:59:14.341935: val_loss -0.7542 +2024-11-22 10:59:14.344207: Pseudo dice [0.8429] +2024-11-22 10:59:14.344337: Epoch time: 19.12 s +2024-11-22 10:59:15.366185: +2024-11-22 10:59:15.366470: Epoch 4459 +2024-11-22 10:59:15.366584: Current learning rate: 0.0048 +2024-11-22 10:59:34.178696: train_loss -0.7806 +2024-11-22 10:59:34.178927: val_loss -0.7591 +2024-11-22 10:59:34.179016: Pseudo dice [0.8497] +2024-11-22 10:59:34.179099: Epoch time: 18.81 s +2024-11-22 10:59:35.055044: +2024-11-22 10:59:35.055294: Epoch 4460 +2024-11-22 10:59:35.055453: Current learning rate: 0.0048 +2024-11-22 10:59:53.696239: train_loss -0.7767 +2024-11-22 10:59:53.696455: val_loss -0.727 +2024-11-22 10:59:53.696530: Pseudo dice [0.8384] +2024-11-22 10:59:53.696609: Epoch time: 18.64 s +2024-11-22 10:59:54.564412: +2024-11-22 10:59:54.564640: Epoch 4461 +2024-11-22 10:59:54.564751: Current learning rate: 0.0048 +2024-11-22 11:00:13.662013: train_loss -0.7883 +2024-11-22 11:00:13.662234: val_loss -0.7476 +2024-11-22 11:00:13.662307: Pseudo dice [0.8491] +2024-11-22 11:00:13.662382: Epoch time: 19.1 s +2024-11-22 11:00:14.543065: +2024-11-22 11:00:14.543278: Epoch 4462 +2024-11-22 11:00:14.543387: Current learning rate: 0.0048 +2024-11-22 11:00:32.882308: train_loss -0.8003 +2024-11-22 11:00:32.882542: val_loss -0.7509 +2024-11-22 11:00:32.882633: Pseudo dice [0.8209] +2024-11-22 11:00:32.882714: Epoch time: 18.34 s +2024-11-22 11:00:33.766238: +2024-11-22 11:00:33.766454: Epoch 4463 +2024-11-22 11:00:33.766561: Current learning rate: 0.0048 +2024-11-22 11:00:52.098019: train_loss -0.7963 +2024-11-22 11:00:52.098242: val_loss -0.7648 +2024-11-22 11:00:52.098316: Pseudo dice [0.8517] +2024-11-22 11:00:52.098398: Epoch time: 18.33 s +2024-11-22 11:00:52.974258: +2024-11-22 11:00:52.974484: Epoch 4464 +2024-11-22 11:00:52.974596: Current learning rate: 0.0048 +2024-11-22 11:01:11.405942: train_loss -0.7972 +2024-11-22 11:01:11.406196: val_loss -0.742 +2024-11-22 11:01:11.406273: Pseudo dice [0.8186] +2024-11-22 11:01:11.406351: Epoch time: 18.43 s +2024-11-22 11:01:12.275315: +2024-11-22 11:01:12.275526: Epoch 4465 +2024-11-22 11:01:12.275640: Current learning rate: 0.00479 +2024-11-22 11:01:31.401883: train_loss -0.7956 +2024-11-22 11:01:31.402104: val_loss -0.726 +2024-11-22 11:01:31.402181: Pseudo dice [0.8357] +2024-11-22 11:01:31.402257: Epoch time: 19.13 s +2024-11-22 11:01:32.272447: +2024-11-22 11:01:32.272738: Epoch 4466 +2024-11-22 11:01:32.272851: Current learning rate: 0.00479 +2024-11-22 11:01:49.814491: train_loss -0.7929 +2024-11-22 11:01:49.814711: val_loss -0.738 +2024-11-22 11:01:49.814788: Pseudo dice [0.8334] +2024-11-22 11:01:49.814862: Epoch time: 17.54 s +2024-11-22 11:01:50.843811: +2024-11-22 11:01:50.844039: Epoch 4467 +2024-11-22 11:01:50.844149: Current learning rate: 0.00479 +2024-11-22 11:02:10.396503: train_loss -0.7808 +2024-11-22 11:02:10.396759: val_loss -0.7594 +2024-11-22 11:02:10.396839: Pseudo dice [0.8475] +2024-11-22 11:02:10.396921: Epoch time: 19.55 s +2024-11-22 11:02:11.269641: +2024-11-22 11:02:11.269850: Epoch 4468 +2024-11-22 11:02:11.269963: Current learning rate: 0.00479 +2024-11-22 11:02:29.171316: train_loss -0.7838 +2024-11-22 11:02:29.171536: val_loss -0.7484 +2024-11-22 11:02:29.171610: Pseudo dice [0.8478] +2024-11-22 11:02:29.171688: Epoch time: 17.9 s +2024-11-22 11:02:30.127625: +2024-11-22 11:02:30.127826: Epoch 4469 +2024-11-22 11:02:30.127937: Current learning rate: 0.00479 +2024-11-22 11:02:48.467172: train_loss -0.7912 +2024-11-22 11:02:48.467395: val_loss -0.7691 +2024-11-22 11:02:48.467471: Pseudo dice [0.8488] +2024-11-22 11:02:48.467546: Epoch time: 18.34 s +2024-11-22 11:02:49.791938: +2024-11-22 11:02:49.792174: Epoch 4470 +2024-11-22 11:02:49.792288: Current learning rate: 0.00479 +2024-11-22 11:03:08.298610: train_loss -0.7833 +2024-11-22 11:03:08.298927: val_loss -0.7415 +2024-11-22 11:03:08.299016: Pseudo dice [0.8488] +2024-11-22 11:03:08.299098: Epoch time: 18.51 s +2024-11-22 11:03:09.163735: +2024-11-22 11:03:09.164032: Epoch 4471 +2024-11-22 11:03:09.164146: Current learning rate: 0.00479 +2024-11-22 11:03:29.096881: train_loss -0.7966 +2024-11-22 11:03:29.097105: val_loss -0.7481 +2024-11-22 11:03:29.097183: Pseudo dice [0.8566] +2024-11-22 11:03:29.097260: Epoch time: 19.93 s +2024-11-22 11:03:29.968598: +2024-11-22 11:03:29.968898: Epoch 4472 +2024-11-22 11:03:29.969017: Current learning rate: 0.00479 +2024-11-22 11:03:49.287224: train_loss -0.7958 +2024-11-22 11:03:49.288560: val_loss -0.7501 +2024-11-22 11:03:49.288646: Pseudo dice [0.8382] +2024-11-22 11:03:49.288725: Epoch time: 19.32 s +2024-11-22 11:03:50.159079: +2024-11-22 11:03:50.159323: Epoch 4473 +2024-11-22 11:03:50.159643: Current learning rate: 0.00479 +2024-11-22 11:04:08.849633: train_loss -0.8063 +2024-11-22 11:04:08.849855: val_loss -0.7599 +2024-11-22 11:04:08.849929: Pseudo dice [0.8661] +2024-11-22 11:04:08.850008: Epoch time: 18.69 s +2024-11-22 11:04:09.722080: +2024-11-22 11:04:09.722383: Epoch 4474 +2024-11-22 11:04:09.722497: Current learning rate: 0.00478 +2024-11-22 11:04:30.064876: train_loss -0.7967 +2024-11-22 11:04:30.065198: val_loss -0.7687 +2024-11-22 11:04:30.065284: Pseudo dice [0.8534] +2024-11-22 11:04:30.065371: Epoch time: 20.34 s +2024-11-22 11:04:30.944344: +2024-11-22 11:04:30.944635: Epoch 4475 +2024-11-22 11:04:30.944746: Current learning rate: 0.00478 +2024-11-22 11:04:49.746367: train_loss -0.7995 +2024-11-22 11:04:49.746583: val_loss -0.7492 +2024-11-22 11:04:49.746725: Pseudo dice [0.8354] +2024-11-22 11:04:49.746805: Epoch time: 18.8 s +2024-11-22 11:04:50.620207: +2024-11-22 11:04:50.620551: Epoch 4476 +2024-11-22 11:04:50.620667: Current learning rate: 0.00478 +2024-11-22 11:05:08.656760: train_loss -0.78 +2024-11-22 11:05:08.656989: val_loss -0.7634 +2024-11-22 11:05:08.657072: Pseudo dice [0.8356] +2024-11-22 11:05:08.657148: Epoch time: 18.04 s +2024-11-22 11:05:09.555458: +2024-11-22 11:05:09.555650: Epoch 4477 +2024-11-22 11:05:09.555762: Current learning rate: 0.00478 +2024-11-22 11:05:28.222598: train_loss -0.7656 +2024-11-22 11:05:28.222817: val_loss -0.7229 +2024-11-22 11:05:28.222918: Pseudo dice [0.8301] +2024-11-22 11:05:28.223010: Epoch time: 18.67 s +2024-11-22 11:05:29.099417: +2024-11-22 11:05:29.099772: Epoch 4478 +2024-11-22 11:05:29.099884: Current learning rate: 0.00478 +2024-11-22 11:05:47.463839: train_loss -0.7847 +2024-11-22 11:05:47.464088: val_loss -0.7547 +2024-11-22 11:05:47.464164: Pseudo dice [0.8471] +2024-11-22 11:05:47.464247: Epoch time: 18.37 s +2024-11-22 11:05:48.428350: +2024-11-22 11:05:48.428558: Epoch 4479 +2024-11-22 11:05:48.428667: Current learning rate: 0.00478 +2024-11-22 11:06:08.158861: train_loss -0.7832 +2024-11-22 11:06:08.159085: val_loss -0.7638 +2024-11-22 11:06:08.159160: Pseudo dice [0.8388] +2024-11-22 11:06:08.159256: Epoch time: 19.73 s +2024-11-22 11:06:09.026266: +2024-11-22 11:06:09.026512: Epoch 4480 +2024-11-22 11:06:09.026623: Current learning rate: 0.00478 +2024-11-22 11:06:28.418912: train_loss -0.7837 +2024-11-22 11:06:28.419141: val_loss -0.741 +2024-11-22 11:06:28.419218: Pseudo dice [0.8423] +2024-11-22 11:06:28.419309: Epoch time: 19.39 s +2024-11-22 11:06:29.283928: +2024-11-22 11:06:29.284279: Epoch 4481 +2024-11-22 11:06:29.284387: Current learning rate: 0.00478 +2024-11-22 11:06:48.391138: train_loss -0.7925 +2024-11-22 11:06:48.391392: val_loss -0.708 +2024-11-22 11:06:48.391468: Pseudo dice [0.8218] +2024-11-22 11:06:48.391555: Epoch time: 19.11 s +2024-11-22 11:06:49.691567: +2024-11-22 11:06:49.691780: Epoch 4482 +2024-11-22 11:06:49.691893: Current learning rate: 0.00477 +2024-11-22 11:07:08.539884: train_loss -0.7736 +2024-11-22 11:07:08.540119: val_loss -0.7493 +2024-11-22 11:07:08.540195: Pseudo dice [0.8202] +2024-11-22 11:07:08.540269: Epoch time: 18.85 s +2024-11-22 11:07:09.429295: +2024-11-22 11:07:09.429520: Epoch 4483 +2024-11-22 11:07:09.429631: Current learning rate: 0.00477 +2024-11-22 11:07:27.923881: train_loss -0.7808 +2024-11-22 11:07:27.924111: val_loss -0.719 +2024-11-22 11:07:27.924195: Pseudo dice [0.8577] +2024-11-22 11:07:27.924298: Epoch time: 18.5 s +2024-11-22 11:07:28.801444: +2024-11-22 11:07:28.801732: Epoch 4484 +2024-11-22 11:07:28.801845: Current learning rate: 0.00477 +2024-11-22 11:07:47.563054: train_loss -0.7791 +2024-11-22 11:07:47.563304: val_loss -0.7403 +2024-11-22 11:07:47.563380: Pseudo dice [0.8453] +2024-11-22 11:07:47.563465: Epoch time: 18.76 s +2024-11-22 11:07:48.439476: +2024-11-22 11:07:48.439689: Epoch 4485 +2024-11-22 11:07:48.439799: Current learning rate: 0.00477 +2024-11-22 11:08:06.966143: train_loss -0.801 +2024-11-22 11:08:06.966358: val_loss -0.756 +2024-11-22 11:08:06.966433: Pseudo dice [0.8395] +2024-11-22 11:08:06.966511: Epoch time: 18.53 s +2024-11-22 11:08:07.841805: +2024-11-22 11:08:07.842047: Epoch 4486 +2024-11-22 11:08:07.842161: Current learning rate: 0.00477 +2024-11-22 11:08:27.552484: train_loss -0.786 +2024-11-22 11:08:27.552701: val_loss -0.7262 +2024-11-22 11:08:27.552781: Pseudo dice [0.8582] +2024-11-22 11:08:27.552870: Epoch time: 19.71 s +2024-11-22 11:08:28.424726: +2024-11-22 11:08:28.424955: Epoch 4487 +2024-11-22 11:08:28.425076: Current learning rate: 0.00477 +2024-11-22 11:08:48.036195: train_loss -0.7721 +2024-11-22 11:08:48.036416: val_loss -0.727 +2024-11-22 11:08:48.036494: Pseudo dice [0.8264] +2024-11-22 11:08:48.036572: Epoch time: 19.61 s +2024-11-22 11:08:48.906393: +2024-11-22 11:08:48.906764: Epoch 4488 +2024-11-22 11:08:48.906878: Current learning rate: 0.00477 +2024-11-22 11:09:07.699587: train_loss -0.7869 +2024-11-22 11:09:07.699832: val_loss -0.7169 +2024-11-22 11:09:07.699910: Pseudo dice [0.8319] +2024-11-22 11:09:07.700002: Epoch time: 18.79 s +2024-11-22 11:09:08.573158: +2024-11-22 11:09:08.573368: Epoch 4489 +2024-11-22 11:09:08.573480: Current learning rate: 0.00477 +2024-11-22 11:09:27.023185: train_loss -0.785 +2024-11-22 11:09:27.023409: val_loss -0.7454 +2024-11-22 11:09:27.023511: Pseudo dice [0.8227] +2024-11-22 11:09:27.023589: Epoch time: 18.45 s +2024-11-22 11:09:27.898565: +2024-11-22 11:09:27.898787: Epoch 4490 +2024-11-22 11:09:27.898900: Current learning rate: 0.00476 +2024-11-22 11:09:46.990268: train_loss -0.7819 +2024-11-22 11:09:46.990491: val_loss -0.7569 +2024-11-22 11:09:46.990567: Pseudo dice [0.849] +2024-11-22 11:09:46.990644: Epoch time: 19.09 s +2024-11-22 11:09:47.961360: +2024-11-22 11:09:47.961576: Epoch 4491 +2024-11-22 11:09:47.961692: Current learning rate: 0.00476 +2024-11-22 11:10:07.447025: train_loss -0.7764 +2024-11-22 11:10:07.447245: val_loss -0.7384 +2024-11-22 11:10:07.447320: Pseudo dice [0.8431] +2024-11-22 11:10:07.447398: Epoch time: 19.49 s +2024-11-22 11:10:08.324262: +2024-11-22 11:10:08.324487: Epoch 4492 +2024-11-22 11:10:08.324601: Current learning rate: 0.00476 +2024-11-22 11:10:27.782792: train_loss -0.7827 +2024-11-22 11:10:27.783052: val_loss -0.7333 +2024-11-22 11:10:27.783129: Pseudo dice [0.8091] +2024-11-22 11:10:27.783215: Epoch time: 19.46 s +2024-11-22 11:10:28.651864: +2024-11-22 11:10:28.652083: Epoch 4493 +2024-11-22 11:10:28.652200: Current learning rate: 0.00476 +2024-11-22 11:10:46.334458: train_loss -0.7826 +2024-11-22 11:10:46.334728: val_loss -0.7234 +2024-11-22 11:10:46.334805: Pseudo dice [0.8216] +2024-11-22 11:10:46.334878: Epoch time: 17.68 s +2024-11-22 11:10:47.646787: +2024-11-22 11:10:47.647010: Epoch 4494 +2024-11-22 11:10:47.647120: Current learning rate: 0.00476 +2024-11-22 11:11:05.838819: train_loss -0.7898 +2024-11-22 11:11:05.839057: val_loss -0.7668 +2024-11-22 11:11:05.841357: Pseudo dice [0.8389] +2024-11-22 11:11:05.841451: Epoch time: 18.19 s +2024-11-22 11:11:06.810092: +2024-11-22 11:11:06.810416: Epoch 4495 +2024-11-22 11:11:06.810527: Current learning rate: 0.00476 +2024-11-22 11:11:25.841707: train_loss -0.7882 +2024-11-22 11:11:25.841930: val_loss -0.7558 +2024-11-22 11:11:25.842014: Pseudo dice [0.8471] +2024-11-22 11:11:25.842098: Epoch time: 19.03 s +2024-11-22 11:11:26.715330: +2024-11-22 11:11:26.715589: Epoch 4496 +2024-11-22 11:11:26.715747: Current learning rate: 0.00476 +2024-11-22 11:11:44.700280: train_loss -0.7871 +2024-11-22 11:11:44.700500: val_loss -0.7452 +2024-11-22 11:11:44.700573: Pseudo dice [0.8425] +2024-11-22 11:11:44.700651: Epoch time: 17.99 s +2024-11-22 11:11:45.578080: +2024-11-22 11:11:45.578401: Epoch 4497 +2024-11-22 11:11:45.578514: Current learning rate: 0.00476 +2024-11-22 11:12:03.693938: train_loss -0.8004 +2024-11-22 11:12:03.694167: val_loss -0.7418 +2024-11-22 11:12:03.694245: Pseudo dice [0.8484] +2024-11-22 11:12:03.694324: Epoch time: 18.12 s +2024-11-22 11:12:04.568457: +2024-11-22 11:12:04.568671: Epoch 4498 +2024-11-22 11:12:04.568785: Current learning rate: 0.00475 +2024-11-22 11:12:23.767789: train_loss -0.791 +2024-11-22 11:12:23.768018: val_loss -0.7693 +2024-11-22 11:12:23.768094: Pseudo dice [0.8453] +2024-11-22 11:12:23.768171: Epoch time: 19.2 s +2024-11-22 11:12:24.640908: +2024-11-22 11:12:24.641134: Epoch 4499 +2024-11-22 11:12:24.641470: Current learning rate: 0.00475 +2024-11-22 11:12:44.015187: train_loss -0.7942 +2024-11-22 11:12:44.015414: val_loss -0.748 +2024-11-22 11:12:44.015491: Pseudo dice [0.8633] +2024-11-22 11:12:44.015575: Epoch time: 19.38 s +2024-11-22 11:12:45.159811: +2024-11-22 11:12:45.160039: Epoch 4500 +2024-11-22 11:12:45.160160: Current learning rate: 0.00475 +2024-11-22 11:13:03.402097: train_loss -0.7982 +2024-11-22 11:13:03.402347: val_loss -0.7463 +2024-11-22 11:13:03.402471: Pseudo dice [0.8371] +2024-11-22 11:13:03.402584: Epoch time: 18.24 s +2024-11-22 11:13:04.304375: +2024-11-22 11:13:04.304600: Epoch 4501 +2024-11-22 11:13:04.304716: Current learning rate: 0.00475 +2024-11-22 11:13:22.372634: train_loss -0.8025 +2024-11-22 11:13:22.372856: val_loss -0.7308 +2024-11-22 11:13:22.372931: Pseudo dice [0.8251] +2024-11-22 11:13:22.373014: Epoch time: 18.07 s +2024-11-22 11:13:23.241092: +2024-11-22 11:13:23.241374: Epoch 4502 +2024-11-22 11:13:23.241488: Current learning rate: 0.00475 +2024-11-22 11:13:41.515499: train_loss -0.7962 +2024-11-22 11:13:41.515722: val_loss -0.7698 +2024-11-22 11:13:41.515795: Pseudo dice [0.836] +2024-11-22 11:13:41.515872: Epoch time: 18.28 s +2024-11-22 11:13:42.388840: +2024-11-22 11:13:42.389046: Epoch 4503 +2024-11-22 11:13:42.389157: Current learning rate: 0.00475 +2024-11-22 11:14:00.231664: train_loss -0.7833 +2024-11-22 11:14:00.232016: val_loss -0.7194 +2024-11-22 11:14:00.232102: Pseudo dice [0.8379] +2024-11-22 11:14:00.232203: Epoch time: 17.84 s +2024-11-22 11:14:01.113471: +2024-11-22 11:14:01.113687: Epoch 4504 +2024-11-22 11:14:01.113804: Current learning rate: 0.00475 +2024-11-22 11:14:19.646130: train_loss -0.7937 +2024-11-22 11:14:19.646356: val_loss -0.7303 +2024-11-22 11:14:19.646434: Pseudo dice [0.8011] +2024-11-22 11:14:19.646510: Epoch time: 18.53 s +2024-11-22 11:14:20.519766: +2024-11-22 11:14:20.520034: Epoch 4505 +2024-11-22 11:14:20.520148: Current learning rate: 0.00475 +2024-11-22 11:14:39.619423: train_loss -0.7759 +2024-11-22 11:14:39.619642: val_loss -0.7645 +2024-11-22 11:14:39.619716: Pseudo dice [0.8368] +2024-11-22 11:14:39.619797: Epoch time: 19.1 s +2024-11-22 11:14:40.872411: +2024-11-22 11:14:40.872642: Epoch 4506 +2024-11-22 11:14:40.872754: Current learning rate: 0.00474 +2024-11-22 11:15:00.550136: train_loss -0.7962 +2024-11-22 11:15:00.550389: val_loss -0.759 +2024-11-22 11:15:00.550465: Pseudo dice [0.8306] +2024-11-22 11:15:00.550544: Epoch time: 19.68 s +2024-11-22 11:15:01.432375: +2024-11-22 11:15:01.432607: Epoch 4507 +2024-11-22 11:15:01.432728: Current learning rate: 0.00474 +2024-11-22 11:15:18.864224: train_loss -0.7928 +2024-11-22 11:15:18.869696: val_loss -0.7338 +2024-11-22 11:15:18.869788: Pseudo dice [0.8453] +2024-11-22 11:15:18.869877: Epoch time: 17.43 s +2024-11-22 11:15:19.799886: +2024-11-22 11:15:19.800099: Epoch 4508 +2024-11-22 11:15:19.800213: Current learning rate: 0.00474 +2024-11-22 11:15:38.075351: train_loss -0.7941 +2024-11-22 11:15:38.075567: val_loss -0.7334 +2024-11-22 11:15:38.075641: Pseudo dice [0.8153] +2024-11-22 11:15:38.075718: Epoch time: 18.28 s +2024-11-22 11:15:39.038383: +2024-11-22 11:15:39.038603: Epoch 4509 +2024-11-22 11:15:39.038717: Current learning rate: 0.00474 +2024-11-22 11:15:57.940649: train_loss -0.7894 +2024-11-22 11:15:57.940867: val_loss -0.7529 +2024-11-22 11:15:57.940944: Pseudo dice [0.8632] +2024-11-22 11:15:57.941026: Epoch time: 18.9 s +2024-11-22 11:15:58.816006: +2024-11-22 11:15:58.816286: Epoch 4510 +2024-11-22 11:15:58.816400: Current learning rate: 0.00474 +2024-11-22 11:16:17.507061: train_loss -0.7841 +2024-11-22 11:16:17.507299: val_loss -0.7536 +2024-11-22 11:16:17.507374: Pseudo dice [0.8479] +2024-11-22 11:16:17.507456: Epoch time: 18.69 s +2024-11-22 11:16:18.385198: +2024-11-22 11:16:18.385416: Epoch 4511 +2024-11-22 11:16:18.385531: Current learning rate: 0.00474 +2024-11-22 11:16:37.942781: train_loss -0.7807 +2024-11-22 11:16:37.943005: val_loss -0.7228 +2024-11-22 11:16:37.943087: Pseudo dice [0.824] +2024-11-22 11:16:37.943170: Epoch time: 19.56 s +2024-11-22 11:16:38.940514: +2024-11-22 11:16:38.940720: Epoch 4512 +2024-11-22 11:16:38.940830: Current learning rate: 0.00474 +2024-11-22 11:16:57.544226: train_loss -0.786 +2024-11-22 11:16:57.544455: val_loss -0.761 +2024-11-22 11:16:57.544541: Pseudo dice [0.8425] +2024-11-22 11:16:57.544623: Epoch time: 18.6 s +2024-11-22 11:16:58.499784: +2024-11-22 11:16:58.499982: Epoch 4513 +2024-11-22 11:16:58.500097: Current learning rate: 0.00474 +2024-11-22 11:17:16.822835: train_loss -0.7806 +2024-11-22 11:17:16.823069: val_loss -0.7504 +2024-11-22 11:17:16.823144: Pseudo dice [0.8465] +2024-11-22 11:17:16.823225: Epoch time: 18.32 s +2024-11-22 11:17:17.699518: +2024-11-22 11:17:17.699783: Epoch 4514 +2024-11-22 11:17:17.699896: Current learning rate: 0.00473 +2024-11-22 11:17:37.301337: train_loss -0.784 +2024-11-22 11:17:37.301577: val_loss -0.7432 +2024-11-22 11:17:37.301651: Pseudo dice [0.8583] +2024-11-22 11:17:37.301731: Epoch time: 19.6 s +2024-11-22 11:17:38.174654: +2024-11-22 11:17:38.174889: Epoch 4515 +2024-11-22 11:17:38.175008: Current learning rate: 0.00473 +2024-11-22 11:17:56.458881: train_loss -0.7659 +2024-11-22 11:17:56.459142: val_loss -0.7601 +2024-11-22 11:17:56.459260: Pseudo dice [0.8431] +2024-11-22 11:17:56.459336: Epoch time: 18.29 s +2024-11-22 11:17:57.334663: +2024-11-22 11:17:57.334908: Epoch 4516 +2024-11-22 11:17:57.335033: Current learning rate: 0.00473 +2024-11-22 11:18:15.852627: train_loss -0.7946 +2024-11-22 11:18:15.852904: val_loss -0.7506 +2024-11-22 11:18:15.852981: Pseudo dice [0.8437] +2024-11-22 11:18:15.853063: Epoch time: 18.52 s +2024-11-22 11:18:16.720346: +2024-11-22 11:18:16.720555: Epoch 4517 +2024-11-22 11:18:16.720671: Current learning rate: 0.00473 +2024-11-22 11:18:35.584912: train_loss -0.7857 +2024-11-22 11:18:35.585173: val_loss -0.751 +2024-11-22 11:18:35.585253: Pseudo dice [0.8374] +2024-11-22 11:18:35.585355: Epoch time: 18.87 s +2024-11-22 11:18:36.875276: +2024-11-22 11:18:36.875504: Epoch 4518 +2024-11-22 11:18:36.875612: Current learning rate: 0.00473 +2024-11-22 11:18:56.592458: train_loss -0.7919 +2024-11-22 11:18:56.592709: val_loss -0.7395 +2024-11-22 11:18:56.594985: Pseudo dice [0.842] +2024-11-22 11:18:56.595081: Epoch time: 19.72 s +2024-11-22 11:18:57.495947: +2024-11-22 11:18:57.496184: Epoch 4519 +2024-11-22 11:18:57.496296: Current learning rate: 0.00473 +2024-11-22 11:19:15.257977: train_loss -0.7902 +2024-11-22 11:19:15.258208: val_loss -0.7231 +2024-11-22 11:19:15.258285: Pseudo dice [0.8257] +2024-11-22 11:19:15.258366: Epoch time: 17.76 s +2024-11-22 11:19:16.151484: +2024-11-22 11:19:16.151699: Epoch 4520 +2024-11-22 11:19:16.151812: Current learning rate: 0.00473 +2024-11-22 11:19:35.399130: train_loss -0.7971 +2024-11-22 11:19:35.399357: val_loss -0.7373 +2024-11-22 11:19:35.399435: Pseudo dice [0.8646] +2024-11-22 11:19:35.399513: Epoch time: 19.25 s +2024-11-22 11:19:36.280481: +2024-11-22 11:19:36.280675: Epoch 4521 +2024-11-22 11:19:36.280784: Current learning rate: 0.00473 +2024-11-22 11:19:54.936904: train_loss -0.7965 +2024-11-22 11:19:54.937217: val_loss -0.7596 +2024-11-22 11:19:54.937299: Pseudo dice [0.8294] +2024-11-22 11:19:54.937382: Epoch time: 18.66 s +2024-11-22 11:19:55.823650: +2024-11-22 11:19:55.823947: Epoch 4522 +2024-11-22 11:19:55.824063: Current learning rate: 0.00473 +2024-11-22 11:20:15.124617: train_loss -0.7902 +2024-11-22 11:20:15.124914: val_loss -0.7387 +2024-11-22 11:20:15.125009: Pseudo dice [0.827] +2024-11-22 11:20:15.125087: Epoch time: 19.3 s +2024-11-22 11:20:16.001160: +2024-11-22 11:20:16.001390: Epoch 4523 +2024-11-22 11:20:16.001501: Current learning rate: 0.00472 +2024-11-22 11:20:34.902821: train_loss -0.7956 +2024-11-22 11:20:34.903054: val_loss -0.7547 +2024-11-22 11:20:34.903127: Pseudo dice [0.8466] +2024-11-22 11:20:34.903206: Epoch time: 18.9 s +2024-11-22 11:20:35.773617: +2024-11-22 11:20:35.773827: Epoch 4524 +2024-11-22 11:20:35.773943: Current learning rate: 0.00472 +2024-11-22 11:20:54.590393: train_loss -0.7936 +2024-11-22 11:20:54.590626: val_loss -0.7476 +2024-11-22 11:20:54.592927: Pseudo dice [0.8254] +2024-11-22 11:20:54.593051: Epoch time: 18.82 s +2024-11-22 11:20:55.528561: +2024-11-22 11:20:55.529032: Epoch 4525 +2024-11-22 11:20:55.529155: Current learning rate: 0.00472 +2024-11-22 11:21:15.093956: train_loss -0.7927 +2024-11-22 11:21:15.094179: val_loss -0.7103 +2024-11-22 11:21:15.094256: Pseudo dice [0.8237] +2024-11-22 11:21:15.094339: Epoch time: 19.57 s +2024-11-22 11:21:15.966495: +2024-11-22 11:21:15.966719: Epoch 4526 +2024-11-22 11:21:15.966833: Current learning rate: 0.00472 +2024-11-22 11:21:34.108168: train_loss -0.7955 +2024-11-22 11:21:34.108395: val_loss -0.7473 +2024-11-22 11:21:34.108475: Pseudo dice [0.829] +2024-11-22 11:21:34.108554: Epoch time: 18.14 s +2024-11-22 11:21:34.984312: +2024-11-22 11:21:34.984533: Epoch 4527 +2024-11-22 11:21:34.984647: Current learning rate: 0.00472 +2024-11-22 11:21:52.773697: train_loss -0.7986 +2024-11-22 11:21:52.773914: val_loss -0.755 +2024-11-22 11:21:52.774002: Pseudo dice [0.8278] +2024-11-22 11:21:52.774084: Epoch time: 17.79 s +2024-11-22 11:21:53.642948: +2024-11-22 11:21:53.643202: Epoch 4528 +2024-11-22 11:21:53.643316: Current learning rate: 0.00472 +2024-11-22 11:22:12.276659: train_loss -0.7951 +2024-11-22 11:22:12.276876: val_loss -0.7283 +2024-11-22 11:22:12.276962: Pseudo dice [0.8365] +2024-11-22 11:22:12.277048: Epoch time: 18.63 s +2024-11-22 11:22:13.150455: +2024-11-22 11:22:13.150660: Epoch 4529 +2024-11-22 11:22:13.150778: Current learning rate: 0.00472 +2024-11-22 11:22:31.350702: train_loss -0.797 +2024-11-22 11:22:31.350943: val_loss -0.7371 +2024-11-22 11:22:31.351025: Pseudo dice [0.8528] +2024-11-22 11:22:31.351104: Epoch time: 18.2 s +2024-11-22 11:22:32.629441: +2024-11-22 11:22:32.629694: Epoch 4530 +2024-11-22 11:22:32.629813: Current learning rate: 0.00472 +2024-11-22 11:22:51.766248: train_loss -0.792 +2024-11-22 11:22:51.766484: val_loss -0.7582 +2024-11-22 11:22:51.766560: Pseudo dice [0.8553] +2024-11-22 11:22:51.766638: Epoch time: 19.14 s +2024-11-22 11:22:52.695365: +2024-11-22 11:22:52.695586: Epoch 4531 +2024-11-22 11:22:52.695694: Current learning rate: 0.00471 +2024-11-22 11:23:11.392649: train_loss -0.8052 +2024-11-22 11:23:11.392896: val_loss -0.7639 +2024-11-22 11:23:11.392975: Pseudo dice [0.8513] +2024-11-22 11:23:11.393063: Epoch time: 18.7 s +2024-11-22 11:23:12.268296: +2024-11-22 11:23:12.268539: Epoch 4532 +2024-11-22 11:23:12.268654: Current learning rate: 0.00471 +2024-11-22 11:23:31.054329: train_loss -0.8057 +2024-11-22 11:23:31.054577: val_loss -0.7414 +2024-11-22 11:23:31.054653: Pseudo dice [0.8552] +2024-11-22 11:23:31.054734: Epoch time: 18.79 s +2024-11-22 11:23:31.931295: +2024-11-22 11:23:31.931541: Epoch 4533 +2024-11-22 11:23:31.931659: Current learning rate: 0.00471 +2024-11-22 11:23:50.832870: train_loss -0.8049 +2024-11-22 11:23:50.833094: val_loss -0.7616 +2024-11-22 11:23:50.833214: Pseudo dice [0.854] +2024-11-22 11:23:50.833292: Epoch time: 18.9 s +2024-11-22 11:23:51.707627: +2024-11-22 11:23:51.707875: Epoch 4534 +2024-11-22 11:23:51.707985: Current learning rate: 0.00471 +2024-11-22 11:24:10.686842: train_loss -0.7875 +2024-11-22 11:24:10.687071: val_loss -0.7531 +2024-11-22 11:24:10.687148: Pseudo dice [0.8535] +2024-11-22 11:24:10.687227: Epoch time: 18.98 s +2024-11-22 11:24:11.562228: +2024-11-22 11:24:11.562448: Epoch 4535 +2024-11-22 11:24:11.562562: Current learning rate: 0.00471 +2024-11-22 11:24:30.717715: train_loss -0.797 +2024-11-22 11:24:30.717946: val_loss -0.7495 +2024-11-22 11:24:30.718051: Pseudo dice [0.8536] +2024-11-22 11:24:30.718128: Epoch time: 19.16 s +2024-11-22 11:24:31.592393: +2024-11-22 11:24:31.592708: Epoch 4536 +2024-11-22 11:24:31.592835: Current learning rate: 0.00471 +2024-11-22 11:24:51.019734: train_loss -0.8012 +2024-11-22 11:24:51.019984: val_loss -0.7301 +2024-11-22 11:24:51.020068: Pseudo dice [0.8286] +2024-11-22 11:24:51.020151: Epoch time: 19.43 s +2024-11-22 11:24:51.896537: +2024-11-22 11:24:51.896827: Epoch 4537 +2024-11-22 11:24:51.896938: Current learning rate: 0.00471 +2024-11-22 11:25:11.330858: train_loss -0.7975 +2024-11-22 11:25:11.333261: val_loss -0.7552 +2024-11-22 11:25:11.333355: Pseudo dice [0.8448] +2024-11-22 11:25:11.333434: Epoch time: 19.44 s +2024-11-22 11:25:12.249796: +2024-11-22 11:25:12.250006: Epoch 4538 +2024-11-22 11:25:12.250119: Current learning rate: 0.00471 +2024-11-22 11:25:31.129793: train_loss -0.8046 +2024-11-22 11:25:31.130033: val_loss -0.7698 +2024-11-22 11:25:31.130112: Pseudo dice [0.8568] +2024-11-22 11:25:31.130193: Epoch time: 18.88 s +2024-11-22 11:25:32.009081: +2024-11-22 11:25:32.009324: Epoch 4539 +2024-11-22 11:25:32.009438: Current learning rate: 0.0047 +2024-11-22 11:25:50.742400: train_loss -0.8082 +2024-11-22 11:25:50.742621: val_loss -0.7571 +2024-11-22 11:25:50.742697: Pseudo dice [0.8383] +2024-11-22 11:25:50.742775: Epoch time: 18.73 s +2024-11-22 11:25:51.615368: +2024-11-22 11:25:51.615623: Epoch 4540 +2024-11-22 11:25:51.615734: Current learning rate: 0.0047 +2024-11-22 11:26:10.031535: train_loss -0.8112 +2024-11-22 11:26:10.031796: val_loss -0.7483 +2024-11-22 11:26:10.031873: Pseudo dice [0.8567] +2024-11-22 11:26:10.031958: Epoch time: 18.42 s +2024-11-22 11:26:10.932418: +2024-11-22 11:26:10.932684: Epoch 4541 +2024-11-22 11:26:10.932797: Current learning rate: 0.0047 +2024-11-22 11:26:30.272287: train_loss -0.7977 +2024-11-22 11:26:30.272511: val_loss -0.7034 +2024-11-22 11:26:30.272587: Pseudo dice [0.8154] +2024-11-22 11:26:30.272688: Epoch time: 19.34 s +2024-11-22 11:26:31.572069: +2024-11-22 11:26:31.572490: Epoch 4542 +2024-11-22 11:26:31.572623: Current learning rate: 0.0047 +2024-11-22 11:26:50.021940: train_loss -0.7923 +2024-11-22 11:26:50.022180: val_loss -0.74 +2024-11-22 11:26:50.022256: Pseudo dice [0.8452] +2024-11-22 11:26:50.022350: Epoch time: 18.45 s +2024-11-22 11:26:50.889604: +2024-11-22 11:26:50.890031: Epoch 4543 +2024-11-22 11:26:50.890168: Current learning rate: 0.0047 +2024-11-22 11:27:09.248438: train_loss -0.7879 +2024-11-22 11:27:09.248699: val_loss -0.7317 +2024-11-22 11:27:09.248777: Pseudo dice [0.8057] +2024-11-22 11:27:09.248865: Epoch time: 18.36 s +2024-11-22 11:27:10.119277: +2024-11-22 11:27:10.119715: Epoch 4544 +2024-11-22 11:27:10.119851: Current learning rate: 0.0047 +2024-11-22 11:27:29.535067: train_loss -0.773 +2024-11-22 11:27:29.535286: val_loss -0.765 +2024-11-22 11:27:29.535359: Pseudo dice [0.8585] +2024-11-22 11:27:29.535438: Epoch time: 19.42 s +2024-11-22 11:27:30.406056: +2024-11-22 11:27:30.406549: Epoch 4545 +2024-11-22 11:27:30.406690: Current learning rate: 0.0047 +2024-11-22 11:27:48.667333: train_loss -0.7835 +2024-11-22 11:27:48.667557: val_loss -0.7718 +2024-11-22 11:27:48.667636: Pseudo dice [0.8621] +2024-11-22 11:27:48.667737: Epoch time: 18.26 s +2024-11-22 11:27:49.542887: +2024-11-22 11:27:49.543300: Epoch 4546 +2024-11-22 11:27:49.543434: Current learning rate: 0.0047 +2024-11-22 11:28:08.943623: train_loss -0.7935 +2024-11-22 11:28:08.943840: val_loss -0.7706 +2024-11-22 11:28:08.943915: Pseudo dice [0.851] +2024-11-22 11:28:08.949130: Epoch time: 19.4 s +2024-11-22 11:28:09.978191: +2024-11-22 11:28:09.978649: Epoch 4547 +2024-11-22 11:28:09.978782: Current learning rate: 0.00469 +2024-11-22 11:28:29.250664: train_loss -0.8087 +2024-11-22 11:28:29.250949: val_loss -0.7547 +2024-11-22 11:28:29.251033: Pseudo dice [0.8403] +2024-11-22 11:28:29.251138: Epoch time: 19.27 s +2024-11-22 11:28:30.132124: +2024-11-22 11:28:30.132543: Epoch 4548 +2024-11-22 11:28:30.132676: Current learning rate: 0.00469 +2024-11-22 11:28:49.080083: train_loss -0.7925 +2024-11-22 11:28:49.080324: val_loss -0.7531 +2024-11-22 11:28:49.080398: Pseudo dice [0.8383] +2024-11-22 11:28:49.080478: Epoch time: 18.95 s +2024-11-22 11:28:49.950418: +2024-11-22 11:28:49.950835: Epoch 4549 +2024-11-22 11:28:49.950972: Current learning rate: 0.00469 +2024-11-22 11:29:08.503676: train_loss -0.8019 +2024-11-22 11:29:08.503896: val_loss -0.7201 +2024-11-22 11:29:08.503979: Pseudo dice [0.7975] +2024-11-22 11:29:08.504065: Epoch time: 18.55 s +2024-11-22 11:29:09.641693: +2024-11-22 11:29:09.643363: Epoch 4550 +2024-11-22 11:29:09.643501: Current learning rate: 0.00469 +2024-11-22 11:29:28.509837: train_loss -0.7877 +2024-11-22 11:29:28.510061: val_loss -0.7303 +2024-11-22 11:29:28.510143: Pseudo dice [0.8106] +2024-11-22 11:29:28.510224: Epoch time: 18.87 s +2024-11-22 11:29:29.383788: +2024-11-22 11:29:29.384198: Epoch 4551 +2024-11-22 11:29:29.384325: Current learning rate: 0.00469 +2024-11-22 11:29:48.304594: train_loss -0.7819 +2024-11-22 11:29:48.304856: val_loss -0.7065 +2024-11-22 11:29:48.304932: Pseudo dice [0.8249] +2024-11-22 11:29:48.305024: Epoch time: 18.92 s +2024-11-22 11:29:49.209908: +2024-11-22 11:29:49.210337: Epoch 4552 +2024-11-22 11:29:49.210470: Current learning rate: 0.00469 +2024-11-22 11:30:08.604150: train_loss -0.7706 +2024-11-22 11:30:08.604372: val_loss -0.7436 +2024-11-22 11:30:08.604448: Pseudo dice [0.8487] +2024-11-22 11:30:08.604524: Epoch time: 19.4 s +2024-11-22 11:30:09.479541: +2024-11-22 11:30:09.479784: Epoch 4553 +2024-11-22 11:30:09.479894: Current learning rate: 0.00469 +2024-11-22 11:30:28.495647: train_loss -0.7818 +2024-11-22 11:30:28.495856: val_loss -0.7444 +2024-11-22 11:30:28.495937: Pseudo dice [0.8547] +2024-11-22 11:30:28.496022: Epoch time: 19.02 s +2024-11-22 11:30:29.815821: +2024-11-22 11:30:29.816066: Epoch 4554 +2024-11-22 11:30:29.816188: Current learning rate: 0.00469 +2024-11-22 11:30:48.933975: train_loss -0.7864 +2024-11-22 11:30:48.934232: val_loss -0.7692 +2024-11-22 11:30:48.934306: Pseudo dice [0.8507] +2024-11-22 11:30:48.934385: Epoch time: 19.12 s +2024-11-22 11:30:49.816198: +2024-11-22 11:30:49.816474: Epoch 4555 +2024-11-22 11:30:49.816584: Current learning rate: 0.00468 +2024-11-22 11:31:08.630733: train_loss -0.7869 +2024-11-22 11:31:08.630986: val_loss -0.7521 +2024-11-22 11:31:08.631070: Pseudo dice [0.8365] +2024-11-22 11:31:08.631152: Epoch time: 18.82 s +2024-11-22 11:31:09.509406: +2024-11-22 11:31:09.509635: Epoch 4556 +2024-11-22 11:31:09.509745: Current learning rate: 0.00468 +2024-11-22 11:31:28.715155: train_loss -0.7888 +2024-11-22 11:31:28.715372: val_loss -0.739 +2024-11-22 11:31:28.715447: Pseudo dice [0.839] +2024-11-22 11:31:28.715523: Epoch time: 19.21 s +2024-11-22 11:31:29.597575: +2024-11-22 11:31:29.597817: Epoch 4557 +2024-11-22 11:31:29.597928: Current learning rate: 0.00468 +2024-11-22 11:31:48.315165: train_loss -0.7944 +2024-11-22 11:31:48.315375: val_loss -0.7562 +2024-11-22 11:31:48.315452: Pseudo dice [0.851] +2024-11-22 11:31:48.315530: Epoch time: 18.72 s +2024-11-22 11:31:49.179271: +2024-11-22 11:31:49.179477: Epoch 4558 +2024-11-22 11:31:49.179591: Current learning rate: 0.00468 +2024-11-22 11:32:08.281623: train_loss -0.7839 +2024-11-22 11:32:08.281832: val_loss -0.7512 +2024-11-22 11:32:08.281968: Pseudo dice [0.8338] +2024-11-22 11:32:08.282055: Epoch time: 19.1 s +2024-11-22 11:32:09.146888: +2024-11-22 11:32:09.147194: Epoch 4559 +2024-11-22 11:32:09.147308: Current learning rate: 0.00468 +2024-11-22 11:32:26.206374: train_loss -0.7913 +2024-11-22 11:32:26.206882: val_loss -0.7719 +2024-11-22 11:32:26.206971: Pseudo dice [0.8478] +2024-11-22 11:32:26.207077: Epoch time: 17.06 s +2024-11-22 11:32:27.125869: +2024-11-22 11:32:27.126101: Epoch 4560 +2024-11-22 11:32:27.126209: Current learning rate: 0.00468 +2024-11-22 11:32:45.081989: train_loss -0.7921 +2024-11-22 11:32:45.082220: val_loss -0.7764 +2024-11-22 11:32:45.082303: Pseudo dice [0.8766] +2024-11-22 11:32:45.082380: Epoch time: 17.96 s +2024-11-22 11:32:45.948739: +2024-11-22 11:32:45.948952: Epoch 4561 +2024-11-22 11:32:45.949067: Current learning rate: 0.00468 +2024-11-22 11:33:05.200794: train_loss -0.7953 +2024-11-22 11:33:05.201076: val_loss -0.7708 +2024-11-22 11:33:05.201154: Pseudo dice [0.8529] +2024-11-22 11:33:05.201231: Epoch time: 19.25 s +2024-11-22 11:33:06.078813: +2024-11-22 11:33:06.079079: Epoch 4562 +2024-11-22 11:33:06.079192: Current learning rate: 0.00468 +2024-11-22 11:33:23.596632: train_loss -0.7985 +2024-11-22 11:33:23.596840: val_loss -0.7456 +2024-11-22 11:33:23.596914: Pseudo dice [0.84] +2024-11-22 11:33:23.597004: Epoch time: 17.52 s +2024-11-22 11:33:24.470690: +2024-11-22 11:33:24.471008: Epoch 4563 +2024-11-22 11:33:24.471123: Current learning rate: 0.00467 +2024-11-22 11:33:42.830290: train_loss -0.7964 +2024-11-22 11:33:42.830526: val_loss -0.7683 +2024-11-22 11:33:42.830614: Pseudo dice [0.8612] +2024-11-22 11:33:42.830703: Epoch time: 18.36 s +2024-11-22 11:33:43.731792: +2024-11-22 11:33:43.732186: Epoch 4564 +2024-11-22 11:33:43.732301: Current learning rate: 0.00467 +2024-11-22 11:34:02.308240: train_loss -0.7934 +2024-11-22 11:34:02.308457: val_loss -0.7603 +2024-11-22 11:34:02.308534: Pseudo dice [0.8624] +2024-11-22 11:34:02.308612: Epoch time: 18.58 s +2024-11-22 11:34:03.176316: +2024-11-22 11:34:03.176590: Epoch 4565 +2024-11-22 11:34:03.176704: Current learning rate: 0.00467 +2024-11-22 11:34:21.220698: train_loss -0.8051 +2024-11-22 11:34:21.221365: val_loss -0.7607 +2024-11-22 11:34:21.221499: Pseudo dice [0.837] +2024-11-22 11:34:21.221581: Epoch time: 18.05 s +2024-11-22 11:34:22.519138: +2024-11-22 11:34:22.519356: Epoch 4566 +2024-11-22 11:34:22.519469: Current learning rate: 0.00467 +2024-11-22 11:34:39.705236: train_loss -0.8001 +2024-11-22 11:34:39.705497: val_loss -0.7589 +2024-11-22 11:34:39.705573: Pseudo dice [0.8443] +2024-11-22 11:34:39.705656: Epoch time: 17.19 s +2024-11-22 11:34:40.581457: +2024-11-22 11:34:40.581696: Epoch 4567 +2024-11-22 11:34:40.581810: Current learning rate: 0.00467 +2024-11-22 11:34:59.486360: train_loss -0.7979 +2024-11-22 11:34:59.486586: val_loss -0.7729 +2024-11-22 11:34:59.486660: Pseudo dice [0.8372] +2024-11-22 11:34:59.486738: Epoch time: 18.91 s +2024-11-22 11:35:00.356202: +2024-11-22 11:35:00.356445: Epoch 4568 +2024-11-22 11:35:00.356561: Current learning rate: 0.00467 +2024-11-22 11:35:19.780299: train_loss -0.7966 +2024-11-22 11:35:19.780547: val_loss -0.728 +2024-11-22 11:35:19.780627: Pseudo dice [0.836] +2024-11-22 11:35:19.780706: Epoch time: 19.42 s +2024-11-22 11:35:20.756129: +2024-11-22 11:35:20.756357: Epoch 4569 +2024-11-22 11:35:20.756466: Current learning rate: 0.00467 +2024-11-22 11:35:39.809921: train_loss -0.7958 +2024-11-22 11:35:39.810173: val_loss -0.7441 +2024-11-22 11:35:39.810248: Pseudo dice [0.8432] +2024-11-22 11:35:39.810332: Epoch time: 19.05 s +2024-11-22 11:35:40.688431: +2024-11-22 11:35:40.688640: Epoch 4570 +2024-11-22 11:35:40.688756: Current learning rate: 0.00467 +2024-11-22 11:35:58.814599: train_loss -0.7968 +2024-11-22 11:35:58.814896: val_loss -0.7424 +2024-11-22 11:35:58.814973: Pseudo dice [0.8582] +2024-11-22 11:35:58.815053: Epoch time: 18.13 s +2024-11-22 11:35:59.690819: +2024-11-22 11:35:59.691052: Epoch 4571 +2024-11-22 11:35:59.691164: Current learning rate: 0.00467 +2024-11-22 11:36:19.385558: train_loss -0.7937 +2024-11-22 11:36:19.385776: val_loss -0.7267 +2024-11-22 11:36:19.385854: Pseudo dice [0.8544] +2024-11-22 11:36:19.385934: Epoch time: 19.7 s +2024-11-22 11:36:20.261434: +2024-11-22 11:36:20.261670: Epoch 4572 +2024-11-22 11:36:20.261785: Current learning rate: 0.00466 +2024-11-22 11:36:37.500637: train_loss -0.769 +2024-11-22 11:36:37.500858: val_loss -0.7389 +2024-11-22 11:36:37.500932: Pseudo dice [0.8505] +2024-11-22 11:36:37.501015: Epoch time: 17.24 s +2024-11-22 11:36:38.377645: +2024-11-22 11:36:38.377933: Epoch 4573 +2024-11-22 11:36:38.378051: Current learning rate: 0.00466 +2024-11-22 11:36:56.310974: train_loss -0.7786 +2024-11-22 11:36:56.311243: val_loss -0.7405 +2024-11-22 11:36:56.311373: Pseudo dice [0.8139] +2024-11-22 11:36:56.311460: Epoch time: 17.93 s +2024-11-22 11:36:57.291179: +2024-11-22 11:36:57.291441: Epoch 4574 +2024-11-22 11:36:57.291554: Current learning rate: 0.00466 +2024-11-22 11:37:15.682184: train_loss -0.7877 +2024-11-22 11:37:15.682425: val_loss -0.7482 +2024-11-22 11:37:15.682512: Pseudo dice [0.8473] +2024-11-22 11:37:15.682594: Epoch time: 18.39 s +2024-11-22 11:37:16.553730: +2024-11-22 11:37:16.553970: Epoch 4575 +2024-11-22 11:37:16.554090: Current learning rate: 0.00466 +2024-11-22 11:37:35.482577: train_loss -0.7792 +2024-11-22 11:37:35.482816: val_loss -0.7232 +2024-11-22 11:37:35.482973: Pseudo dice [0.8509] +2024-11-22 11:37:35.483063: Epoch time: 18.93 s +2024-11-22 11:37:36.356061: +2024-11-22 11:37:36.356266: Epoch 4576 +2024-11-22 11:37:36.356376: Current learning rate: 0.00466 +2024-11-22 11:37:56.066898: train_loss -0.7897 +2024-11-22 11:37:56.067128: val_loss -0.7211 +2024-11-22 11:37:56.067208: Pseudo dice [0.841] +2024-11-22 11:37:56.067289: Epoch time: 19.71 s +2024-11-22 11:37:56.942146: +2024-11-22 11:37:56.942356: Epoch 4577 +2024-11-22 11:37:56.942470: Current learning rate: 0.00466 +2024-11-22 11:38:16.334257: train_loss -0.7907 +2024-11-22 11:38:16.334502: val_loss -0.7465 +2024-11-22 11:38:16.334579: Pseudo dice [0.8429] +2024-11-22 11:38:16.334660: Epoch time: 19.39 s +2024-11-22 11:38:17.603325: +2024-11-22 11:38:17.603599: Epoch 4578 +2024-11-22 11:38:17.603712: Current learning rate: 0.00466 +2024-11-22 11:38:35.938546: train_loss -0.7923 +2024-11-22 11:38:35.938834: val_loss -0.7147 +2024-11-22 11:38:35.938913: Pseudo dice [0.8034] +2024-11-22 11:38:35.938988: Epoch time: 18.34 s +2024-11-22 11:38:36.809810: +2024-11-22 11:38:36.810040: Epoch 4579 +2024-11-22 11:38:36.810150: Current learning rate: 0.00466 +2024-11-22 11:38:54.883061: train_loss -0.783 +2024-11-22 11:38:54.883289: val_loss -0.7503 +2024-11-22 11:38:54.883363: Pseudo dice [0.8565] +2024-11-22 11:38:54.883439: Epoch time: 18.07 s +2024-11-22 11:38:55.755709: +2024-11-22 11:38:55.756016: Epoch 4580 +2024-11-22 11:38:55.756130: Current learning rate: 0.00465 +2024-11-22 11:39:13.878417: train_loss -0.7914 +2024-11-22 11:39:13.878673: val_loss -0.7272 +2024-11-22 11:39:13.878752: Pseudo dice [0.8067] +2024-11-22 11:39:13.878835: Epoch time: 18.12 s +2024-11-22 11:39:14.762638: +2024-11-22 11:39:14.762933: Epoch 4581 +2024-11-22 11:39:14.763048: Current learning rate: 0.00465 +2024-11-22 11:39:32.631612: train_loss -0.7908 +2024-11-22 11:39:32.631865: val_loss -0.7693 +2024-11-22 11:39:32.631977: Pseudo dice [0.8573] +2024-11-22 11:39:32.632093: Epoch time: 17.87 s +2024-11-22 11:39:33.509876: +2024-11-22 11:39:33.510158: Epoch 4582 +2024-11-22 11:39:33.510269: Current learning rate: 0.00465 +2024-11-22 11:39:52.194193: train_loss -0.7882 +2024-11-22 11:39:52.194477: val_loss -0.7491 +2024-11-22 11:39:52.194557: Pseudo dice [0.846] +2024-11-22 11:39:52.194635: Epoch time: 18.69 s +2024-11-22 11:39:53.155610: +2024-11-22 11:39:53.155946: Epoch 4583 +2024-11-22 11:39:53.156062: Current learning rate: 0.00465 +2024-11-22 11:40:13.084009: train_loss -0.7816 +2024-11-22 11:40:13.084221: val_loss -0.7585 +2024-11-22 11:40:13.084339: Pseudo dice [0.8275] +2024-11-22 11:40:13.084419: Epoch time: 19.93 s +2024-11-22 11:40:13.961539: +2024-11-22 11:40:13.961770: Epoch 4584 +2024-11-22 11:40:13.961888: Current learning rate: 0.00465 +2024-11-22 11:40:31.852160: train_loss -0.7894 +2024-11-22 11:40:31.852463: val_loss -0.7095 +2024-11-22 11:40:31.852546: Pseudo dice [0.8231] +2024-11-22 11:40:31.852633: Epoch time: 17.89 s +2024-11-22 11:40:32.826901: +2024-11-22 11:40:32.827152: Epoch 4585 +2024-11-22 11:40:32.827272: Current learning rate: 0.00465 +2024-11-22 11:40:51.858330: train_loss -0.7908 +2024-11-22 11:40:51.858592: val_loss -0.7601 +2024-11-22 11:40:51.858666: Pseudo dice [0.8354] +2024-11-22 11:40:51.858750: Epoch time: 19.03 s +2024-11-22 11:40:52.837085: +2024-11-22 11:40:52.837349: Epoch 4586 +2024-11-22 11:40:52.837467: Current learning rate: 0.00465 +2024-11-22 11:41:11.978463: train_loss -0.7957 +2024-11-22 11:41:11.978693: val_loss -0.6993 +2024-11-22 11:41:11.978774: Pseudo dice [0.8473] +2024-11-22 11:41:11.978852: Epoch time: 19.14 s +2024-11-22 11:41:12.853347: +2024-11-22 11:41:12.853547: Epoch 4587 +2024-11-22 11:41:12.853660: Current learning rate: 0.00465 +2024-11-22 11:41:32.761827: train_loss -0.7951 +2024-11-22 11:41:32.762053: val_loss -0.729 +2024-11-22 11:41:32.762127: Pseudo dice [0.825] +2024-11-22 11:41:32.762201: Epoch time: 19.91 s +2024-11-22 11:41:33.634896: +2024-11-22 11:41:33.635206: Epoch 4588 +2024-11-22 11:41:33.635319: Current learning rate: 0.00464 +2024-11-22 11:41:52.553907: train_loss -0.7978 +2024-11-22 11:41:52.556374: val_loss -0.7721 +2024-11-22 11:41:52.556482: Pseudo dice [0.8458] +2024-11-22 11:41:52.556570: Epoch time: 18.92 s +2024-11-22 11:41:53.548247: +2024-11-22 11:41:53.548556: Epoch 4589 +2024-11-22 11:41:53.548692: Current learning rate: 0.00464 +2024-11-22 11:42:12.508628: train_loss -0.7707 +2024-11-22 11:42:12.509635: val_loss -0.7268 +2024-11-22 11:42:12.509720: Pseudo dice [0.8354] +2024-11-22 11:42:12.509797: Epoch time: 18.96 s +2024-11-22 11:42:13.842760: +2024-11-22 11:42:13.842989: Epoch 4590 +2024-11-22 11:42:13.843103: Current learning rate: 0.00464 +2024-11-22 11:42:31.918031: train_loss -0.7857 +2024-11-22 11:42:31.918261: val_loss -0.7269 +2024-11-22 11:42:31.918337: Pseudo dice [0.8067] +2024-11-22 11:42:31.918413: Epoch time: 18.08 s +2024-11-22 11:42:32.792407: +2024-11-22 11:42:32.792622: Epoch 4591 +2024-11-22 11:42:32.792737: Current learning rate: 0.00464 +2024-11-22 11:42:51.517283: train_loss -0.7776 +2024-11-22 11:42:51.517544: val_loss -0.7217 +2024-11-22 11:42:51.517621: Pseudo dice [0.8341] +2024-11-22 11:42:51.517701: Epoch time: 18.73 s +2024-11-22 11:42:52.435605: +2024-11-22 11:42:52.435880: Epoch 4592 +2024-11-22 11:42:52.435997: Current learning rate: 0.00464 +2024-11-22 11:43:11.267979: train_loss -0.7728 +2024-11-22 11:43:11.268245: val_loss -0.7407 +2024-11-22 11:43:11.268326: Pseudo dice [0.8573] +2024-11-22 11:43:11.268411: Epoch time: 18.83 s +2024-11-22 11:43:12.164434: +2024-11-22 11:43:12.164683: Epoch 4593 +2024-11-22 11:43:12.164798: Current learning rate: 0.00464 +2024-11-22 11:43:30.862617: train_loss -0.7711 +2024-11-22 11:43:30.862824: val_loss -0.7393 +2024-11-22 11:43:30.862898: Pseudo dice [0.8348] +2024-11-22 11:43:30.862997: Epoch time: 18.7 s +2024-11-22 11:43:31.745694: +2024-11-22 11:43:31.745950: Epoch 4594 +2024-11-22 11:43:31.746070: Current learning rate: 0.00464 +2024-11-22 11:43:50.757191: train_loss -0.781 +2024-11-22 11:43:50.757403: val_loss -0.7479 +2024-11-22 11:43:50.757478: Pseudo dice [0.842] +2024-11-22 11:43:50.757555: Epoch time: 19.01 s +2024-11-22 11:43:51.651414: +2024-11-22 11:43:51.651649: Epoch 4595 +2024-11-22 11:43:51.651765: Current learning rate: 0.00464 +2024-11-22 11:44:11.034151: train_loss -0.7963 +2024-11-22 11:44:11.034369: val_loss -0.752 +2024-11-22 11:44:11.034450: Pseudo dice [0.8537] +2024-11-22 11:44:11.034528: Epoch time: 19.38 s +2024-11-22 11:44:11.909289: +2024-11-22 11:44:11.909507: Epoch 4596 +2024-11-22 11:44:11.909623: Current learning rate: 0.00463 +2024-11-22 11:44:32.177730: train_loss -0.7751 +2024-11-22 11:44:32.177981: val_loss -0.7452 +2024-11-22 11:44:32.178065: Pseudo dice [0.8112] +2024-11-22 11:44:32.178154: Epoch time: 20.27 s +2024-11-22 11:44:33.055076: +2024-11-22 11:44:33.055370: Epoch 4597 +2024-11-22 11:44:33.055496: Current learning rate: 0.00463 +2024-11-22 11:44:51.876578: train_loss -0.762 +2024-11-22 11:44:51.876796: val_loss -0.7282 +2024-11-22 11:44:51.876872: Pseudo dice [0.8253] +2024-11-22 11:44:51.876950: Epoch time: 18.82 s +2024-11-22 11:44:52.755932: +2024-11-22 11:44:52.756197: Epoch 4598 +2024-11-22 11:44:52.756313: Current learning rate: 0.00463 +2024-11-22 11:45:11.235591: train_loss -0.7782 +2024-11-22 11:45:11.235814: val_loss -0.7405 +2024-11-22 11:45:11.235888: Pseudo dice [0.8388] +2024-11-22 11:45:11.235966: Epoch time: 18.48 s +2024-11-22 11:45:12.122670: +2024-11-22 11:45:12.122957: Epoch 4599 +2024-11-22 11:45:12.123077: Current learning rate: 0.00463 +2024-11-22 11:45:30.535035: train_loss -0.7828 +2024-11-22 11:45:30.535262: val_loss -0.7301 +2024-11-22 11:45:30.535336: Pseudo dice [0.832] +2024-11-22 11:45:30.535415: Epoch time: 18.41 s +2024-11-22 11:45:31.675292: +2024-11-22 11:45:31.675501: Epoch 4600 +2024-11-22 11:45:31.675612: Current learning rate: 0.00463 +2024-11-22 11:45:50.278315: train_loss -0.7745 +2024-11-22 11:45:50.280787: val_loss -0.7469 +2024-11-22 11:45:50.280886: Pseudo dice [0.8294] +2024-11-22 11:45:50.280976: Epoch time: 18.6 s +2024-11-22 11:45:51.226087: +2024-11-22 11:45:51.226296: Epoch 4601 +2024-11-22 11:45:51.226408: Current learning rate: 0.00463 +2024-11-22 11:46:09.790141: train_loss -0.7953 +2024-11-22 11:46:09.790363: val_loss -0.7448 +2024-11-22 11:46:09.790438: Pseudo dice [0.8291] +2024-11-22 11:46:09.790515: Epoch time: 18.56 s +2024-11-22 11:46:11.066831: +2024-11-22 11:46:11.067053: Epoch 4602 +2024-11-22 11:46:11.067170: Current learning rate: 0.00463 +2024-11-22 11:46:29.299541: train_loss -0.7892 +2024-11-22 11:46:29.299762: val_loss -0.7334 +2024-11-22 11:46:29.299834: Pseudo dice [0.8309] +2024-11-22 11:46:29.301600: Epoch time: 18.23 s +2024-11-22 11:46:30.313102: +2024-11-22 11:46:30.313324: Epoch 4603 +2024-11-22 11:46:30.313435: Current learning rate: 0.00463 +2024-11-22 11:46:48.940581: train_loss -0.7932 +2024-11-22 11:46:48.940836: val_loss -0.7372 +2024-11-22 11:46:48.946081: Pseudo dice [0.8287] +2024-11-22 11:46:48.946263: Epoch time: 18.63 s +2024-11-22 11:46:49.966079: +2024-11-22 11:46:49.966325: Epoch 4604 +2024-11-22 11:46:49.966439: Current learning rate: 0.00462 +2024-11-22 11:47:09.265648: train_loss -0.7971 +2024-11-22 11:47:09.265928: val_loss -0.7563 +2024-11-22 11:47:09.266010: Pseudo dice [0.8468] +2024-11-22 11:47:09.266088: Epoch time: 19.3 s +2024-11-22 11:47:10.145820: +2024-11-22 11:47:10.146049: Epoch 4605 +2024-11-22 11:47:10.146163: Current learning rate: 0.00462 +2024-11-22 11:47:29.018324: train_loss -0.7897 +2024-11-22 11:47:29.018548: val_loss -0.7377 +2024-11-22 11:47:29.018625: Pseudo dice [0.8606] +2024-11-22 11:47:29.018704: Epoch time: 18.87 s +2024-11-22 11:47:29.899875: +2024-11-22 11:47:29.900103: Epoch 4606 +2024-11-22 11:47:29.900219: Current learning rate: 0.00462 +2024-11-22 11:47:47.881974: train_loss -0.7985 +2024-11-22 11:47:47.882197: val_loss -0.7493 +2024-11-22 11:47:47.882272: Pseudo dice [0.8353] +2024-11-22 11:47:47.882347: Epoch time: 17.98 s +2024-11-22 11:47:48.776348: +2024-11-22 11:47:48.776720: Epoch 4607 +2024-11-22 11:47:48.776829: Current learning rate: 0.00462 +2024-11-22 11:48:07.823201: train_loss -0.7983 +2024-11-22 11:48:07.823452: val_loss -0.7225 +2024-11-22 11:48:07.823602: Pseudo dice [0.8361] +2024-11-22 11:48:07.823692: Epoch time: 19.05 s +2024-11-22 11:48:08.725395: +2024-11-22 11:48:08.725601: Epoch 4608 +2024-11-22 11:48:08.725710: Current learning rate: 0.00462 +2024-11-22 11:48:27.960593: train_loss -0.7978 +2024-11-22 11:48:27.960906: val_loss -0.7566 +2024-11-22 11:48:27.960987: Pseudo dice [0.8394] +2024-11-22 11:48:27.961072: Epoch time: 19.24 s +2024-11-22 11:48:28.837878: +2024-11-22 11:48:28.838161: Epoch 4609 +2024-11-22 11:48:28.838274: Current learning rate: 0.00462 +2024-11-22 11:48:47.185778: train_loss -0.7975 +2024-11-22 11:48:47.186008: val_loss -0.7498 +2024-11-22 11:48:47.186120: Pseudo dice [0.8593] +2024-11-22 11:48:47.186218: Epoch time: 18.35 s +2024-11-22 11:48:48.091977: +2024-11-22 11:48:48.092197: Epoch 4610 +2024-11-22 11:48:48.092308: Current learning rate: 0.00462 +2024-11-22 11:49:08.123118: train_loss -0.7942 +2024-11-22 11:49:08.123346: val_loss -0.7416 +2024-11-22 11:49:08.123419: Pseudo dice [0.8167] +2024-11-22 11:49:08.123493: Epoch time: 20.03 s +2024-11-22 11:49:09.047395: +2024-11-22 11:49:09.047623: Epoch 4611 +2024-11-22 11:49:09.047738: Current learning rate: 0.00462 +2024-11-22 11:49:27.668621: train_loss -0.7916 +2024-11-22 11:49:27.668874: val_loss -0.7373 +2024-11-22 11:49:27.668952: Pseudo dice [0.8493] +2024-11-22 11:49:27.669042: Epoch time: 18.62 s +2024-11-22 11:49:28.541411: +2024-11-22 11:49:28.541627: Epoch 4612 +2024-11-22 11:49:28.541759: Current learning rate: 0.00461 +2024-11-22 11:49:47.393268: train_loss -0.7935 +2024-11-22 11:49:47.393485: val_loss -0.7314 +2024-11-22 11:49:47.393560: Pseudo dice [0.8445] +2024-11-22 11:49:47.393636: Epoch time: 18.85 s +2024-11-22 11:49:48.293223: +2024-11-22 11:49:48.293452: Epoch 4613 +2024-11-22 11:49:48.293557: Current learning rate: 0.00461 +2024-11-22 11:50:06.732768: train_loss -0.786 +2024-11-22 11:50:06.732987: val_loss -0.7496 +2024-11-22 11:50:06.733078: Pseudo dice [0.8377] +2024-11-22 11:50:06.733155: Epoch time: 18.44 s +2024-11-22 11:50:08.115523: +2024-11-22 11:50:08.115737: Epoch 4614 +2024-11-22 11:50:08.115857: Current learning rate: 0.00461 +2024-11-22 11:50:27.037591: train_loss -0.7966 +2024-11-22 11:50:27.037846: val_loss -0.7587 +2024-11-22 11:50:27.037924: Pseudo dice [0.8545] +2024-11-22 11:50:27.038056: Epoch time: 18.92 s +2024-11-22 11:50:27.926544: +2024-11-22 11:50:27.926757: Epoch 4615 +2024-11-22 11:50:27.926868: Current learning rate: 0.00461 +2024-11-22 11:50:47.035948: train_loss -0.7962 +2024-11-22 11:50:47.037031: val_loss -0.7243 +2024-11-22 11:50:47.037127: Pseudo dice [0.8138] +2024-11-22 11:50:47.037205: Epoch time: 19.11 s +2024-11-22 11:50:47.930346: +2024-11-22 11:50:47.930614: Epoch 4616 +2024-11-22 11:50:47.930725: Current learning rate: 0.00461 +2024-11-22 11:51:07.643000: train_loss -0.7902 +2024-11-22 11:51:07.643246: val_loss -0.757 +2024-11-22 11:51:07.643322: Pseudo dice [0.841] +2024-11-22 11:51:07.643459: Epoch time: 19.71 s +2024-11-22 11:51:08.519290: +2024-11-22 11:51:08.519516: Epoch 4617 +2024-11-22 11:51:08.519630: Current learning rate: 0.00461 +2024-11-22 11:51:27.388256: train_loss -0.7903 +2024-11-22 11:51:27.388535: val_loss -0.7646 +2024-11-22 11:51:27.388612: Pseudo dice [0.8488] +2024-11-22 11:51:27.388689: Epoch time: 18.87 s +2024-11-22 11:51:28.266949: +2024-11-22 11:51:28.267177: Epoch 4618 +2024-11-22 11:51:28.267291: Current learning rate: 0.00461 +2024-11-22 11:51:46.762176: train_loss -0.792 +2024-11-22 11:51:46.762423: val_loss -0.7729 +2024-11-22 11:51:46.762497: Pseudo dice [0.8478] +2024-11-22 11:51:46.762593: Epoch time: 18.5 s +2024-11-22 11:51:47.639214: +2024-11-22 11:51:47.639453: Epoch 4619 +2024-11-22 11:51:47.639563: Current learning rate: 0.00461 +2024-11-22 11:52:06.773659: train_loss -0.7931 +2024-11-22 11:52:06.773886: val_loss -0.7178 +2024-11-22 11:52:06.773963: Pseudo dice [0.8573] +2024-11-22 11:52:06.774047: Epoch time: 19.14 s +2024-11-22 11:52:07.872461: +2024-11-22 11:52:07.872676: Epoch 4620 +2024-11-22 11:52:07.872791: Current learning rate: 0.00461 +2024-11-22 11:52:26.641977: train_loss -0.7962 +2024-11-22 11:52:26.642200: val_loss -0.7519 +2024-11-22 11:52:26.642279: Pseudo dice [0.8612] +2024-11-22 11:52:26.642359: Epoch time: 18.77 s +2024-11-22 11:52:27.610758: +2024-11-22 11:52:27.610993: Epoch 4621 +2024-11-22 11:52:27.611109: Current learning rate: 0.0046 +2024-11-22 11:52:46.280151: train_loss -0.8086 +2024-11-22 11:52:46.280373: val_loss -0.7759 +2024-11-22 11:52:46.280449: Pseudo dice [0.8548] +2024-11-22 11:52:46.280529: Epoch time: 18.67 s +2024-11-22 11:52:47.155723: +2024-11-22 11:52:47.155953: Epoch 4622 +2024-11-22 11:52:47.156071: Current learning rate: 0.0046 +2024-11-22 11:53:05.310663: train_loss -0.8054 +2024-11-22 11:53:05.310952: val_loss -0.7406 +2024-11-22 11:53:05.311048: Pseudo dice [0.8242] +2024-11-22 11:53:05.311142: Epoch time: 18.16 s +2024-11-22 11:53:06.182629: +2024-11-22 11:53:06.182848: Epoch 4623 +2024-11-22 11:53:06.182960: Current learning rate: 0.0046 +2024-11-22 11:53:23.295799: train_loss -0.8033 +2024-11-22 11:53:23.296026: val_loss -0.7305 +2024-11-22 11:53:23.296103: Pseudo dice [0.8501] +2024-11-22 11:53:23.296183: Epoch time: 17.11 s +2024-11-22 11:53:24.277131: +2024-11-22 11:53:24.277351: Epoch 4624 +2024-11-22 11:53:24.277467: Current learning rate: 0.0046 +2024-11-22 11:53:43.203359: train_loss -0.7982 +2024-11-22 11:53:43.205757: val_loss -0.7491 +2024-11-22 11:53:43.205842: Pseudo dice [0.8393] +2024-11-22 11:53:43.205921: Epoch time: 18.93 s +2024-11-22 11:53:44.095708: +2024-11-22 11:53:44.095932: Epoch 4625 +2024-11-22 11:53:44.096054: Current learning rate: 0.0046 +2024-11-22 11:54:02.640663: train_loss -0.7885 +2024-11-22 11:54:02.640957: val_loss -0.7448 +2024-11-22 11:54:02.641042: Pseudo dice [0.8503] +2024-11-22 11:54:02.641125: Epoch time: 18.55 s +2024-11-22 11:54:03.817105: +2024-11-22 11:54:03.817321: Epoch 4626 +2024-11-22 11:54:03.817433: Current learning rate: 0.0046 +2024-11-22 11:54:22.614417: train_loss -0.7888 +2024-11-22 11:54:22.614635: val_loss -0.757 +2024-11-22 11:54:22.614711: Pseudo dice [0.8423] +2024-11-22 11:54:22.614800: Epoch time: 18.8 s +2024-11-22 11:54:23.472662: +2024-11-22 11:54:23.472885: Epoch 4627 +2024-11-22 11:54:23.472999: Current learning rate: 0.0046 +2024-11-22 11:54:42.648539: train_loss -0.7975 +2024-11-22 11:54:42.648750: val_loss -0.7659 +2024-11-22 11:54:42.648825: Pseudo dice [0.8496] +2024-11-22 11:54:42.648901: Epoch time: 19.18 s +2024-11-22 11:54:43.508235: +2024-11-22 11:54:43.508464: Epoch 4628 +2024-11-22 11:54:43.508581: Current learning rate: 0.0046 +2024-11-22 11:55:01.551797: train_loss -0.808 +2024-11-22 11:55:01.557228: val_loss -0.7424 +2024-11-22 11:55:01.557355: Pseudo dice [0.8546] +2024-11-22 11:55:01.558108: Epoch time: 18.04 s +2024-11-22 11:55:02.590317: +2024-11-22 11:55:02.590539: Epoch 4629 +2024-11-22 11:55:02.590652: Current learning rate: 0.00459 +2024-11-22 11:55:21.518958: train_loss -0.7978 +2024-11-22 11:55:21.519174: val_loss -0.7346 +2024-11-22 11:55:21.519249: Pseudo dice [0.8509] +2024-11-22 11:55:21.519323: Epoch time: 18.93 s +2024-11-22 11:55:22.392439: +2024-11-22 11:55:22.392658: Epoch 4630 +2024-11-22 11:55:22.392765: Current learning rate: 0.00459 +2024-11-22 11:55:41.223822: train_loss -0.7979 +2024-11-22 11:55:41.224035: val_loss -0.7454 +2024-11-22 11:55:41.224108: Pseudo dice [0.8554] +2024-11-22 11:55:41.224185: Epoch time: 18.83 s +2024-11-22 11:55:42.185295: +2024-11-22 11:55:42.185560: Epoch 4631 +2024-11-22 11:55:42.185667: Current learning rate: 0.00459 +2024-11-22 11:56:00.143302: train_loss -0.7985 +2024-11-22 11:56:00.143526: val_loss -0.7531 +2024-11-22 11:56:00.143603: Pseudo dice [0.8459] +2024-11-22 11:56:00.143681: Epoch time: 17.96 s +2024-11-22 11:56:01.148157: +2024-11-22 11:56:01.148368: Epoch 4632 +2024-11-22 11:56:01.148482: Current learning rate: 0.00459 +2024-11-22 11:56:19.736996: train_loss -0.8027 +2024-11-22 11:56:19.737216: val_loss -0.7158 +2024-11-22 11:56:19.737293: Pseudo dice [0.8376] +2024-11-22 11:56:19.737372: Epoch time: 18.59 s +2024-11-22 11:56:20.629298: +2024-11-22 11:56:20.629529: Epoch 4633 +2024-11-22 11:56:20.629642: Current learning rate: 0.00459 +2024-11-22 11:56:37.951825: train_loss -0.7988 +2024-11-22 11:56:37.952059: val_loss -0.729 +2024-11-22 11:56:37.952135: Pseudo dice [0.8523] +2024-11-22 11:56:37.957451: Epoch time: 17.32 s +2024-11-22 11:56:38.877421: +2024-11-22 11:56:38.877625: Epoch 4634 +2024-11-22 11:56:38.877737: Current learning rate: 0.00459 +2024-11-22 11:56:59.017195: train_loss -0.8011 +2024-11-22 11:56:59.017532: val_loss -0.7457 +2024-11-22 11:56:59.017620: Pseudo dice [0.8436] +2024-11-22 11:56:59.017701: Epoch time: 20.14 s +2024-11-22 11:57:00.110486: +2024-11-22 11:57:00.110821: Epoch 4635 +2024-11-22 11:57:00.110933: Current learning rate: 0.00459 +2024-11-22 11:57:18.805957: train_loss -0.8049 +2024-11-22 11:57:18.806186: val_loss -0.7413 +2024-11-22 11:57:18.806262: Pseudo dice [0.854] +2024-11-22 11:57:18.806337: Epoch time: 18.7 s +2024-11-22 11:57:19.780076: +2024-11-22 11:57:19.780496: Epoch 4636 +2024-11-22 11:57:19.780623: Current learning rate: 0.00459 +2024-11-22 11:57:38.160179: train_loss -0.7881 +2024-11-22 11:57:38.160402: val_loss -0.7372 +2024-11-22 11:57:38.160477: Pseudo dice [0.8415] +2024-11-22 11:57:38.160556: Epoch time: 18.38 s +2024-11-22 11:57:39.034730: +2024-11-22 11:57:39.035051: Epoch 4637 +2024-11-22 11:57:39.035171: Current learning rate: 0.00458 +2024-11-22 11:57:56.737170: train_loss -0.8054 +2024-11-22 11:57:56.737418: val_loss -0.7471 +2024-11-22 11:57:56.737495: Pseudo dice [0.8375] +2024-11-22 11:57:56.737577: Epoch time: 17.7 s +2024-11-22 11:57:58.015548: +2024-11-22 11:57:58.015799: Epoch 4638 +2024-11-22 11:57:58.015919: Current learning rate: 0.00458 +2024-11-22 11:58:16.087542: train_loss -0.7972 +2024-11-22 11:58:16.087785: val_loss -0.7618 +2024-11-22 11:58:16.087860: Pseudo dice [0.8482] +2024-11-22 11:58:16.087936: Epoch time: 18.07 s +2024-11-22 11:58:16.968673: +2024-11-22 11:58:16.968898: Epoch 4639 +2024-11-22 11:58:16.969020: Current learning rate: 0.00458 +2024-11-22 11:58:35.098494: train_loss -0.7955 +2024-11-22 11:58:35.098710: val_loss -0.7498 +2024-11-22 11:58:35.098786: Pseudo dice [0.8499] +2024-11-22 11:58:35.098881: Epoch time: 18.13 s +2024-11-22 11:58:35.968336: +2024-11-22 11:58:35.968633: Epoch 4640 +2024-11-22 11:58:35.968756: Current learning rate: 0.00458 +2024-11-22 11:58:55.761362: train_loss -0.8004 +2024-11-22 11:58:55.761604: val_loss -0.7462 +2024-11-22 11:58:55.761679: Pseudo dice [0.8396] +2024-11-22 11:58:55.761760: Epoch time: 19.79 s +2024-11-22 11:58:56.637243: +2024-11-22 11:58:56.637458: Epoch 4641 +2024-11-22 11:58:56.637572: Current learning rate: 0.00458 +2024-11-22 11:59:15.232583: train_loss -0.8005 +2024-11-22 11:59:15.233688: val_loss -0.7642 +2024-11-22 11:59:15.233780: Pseudo dice [0.8515] +2024-11-22 11:59:15.233859: Epoch time: 18.6 s +2024-11-22 11:59:16.114142: +2024-11-22 11:59:16.114343: Epoch 4642 +2024-11-22 11:59:16.114458: Current learning rate: 0.00458 +2024-11-22 11:59:34.580848: train_loss -0.7923 +2024-11-22 11:59:34.581078: val_loss -0.7406 +2024-11-22 11:59:34.581174: Pseudo dice [0.8413] +2024-11-22 11:59:34.581255: Epoch time: 18.47 s +2024-11-22 11:59:35.455270: +2024-11-22 11:59:35.455478: Epoch 4643 +2024-11-22 11:59:35.455591: Current learning rate: 0.00458 +2024-11-22 11:59:53.555253: train_loss -0.7942 +2024-11-22 11:59:53.555545: val_loss -0.7557 +2024-11-22 11:59:53.555624: Pseudo dice [0.8582] +2024-11-22 11:59:53.555705: Epoch time: 18.1 s +2024-11-22 11:59:54.441429: +2024-11-22 11:59:54.441639: Epoch 4644 +2024-11-22 11:59:54.441757: Current learning rate: 0.00458 +2024-11-22 12:00:12.067658: train_loss -0.7978 +2024-11-22 12:00:12.067904: val_loss -0.7498 +2024-11-22 12:00:12.067978: Pseudo dice [0.8513] +2024-11-22 12:00:12.068072: Epoch time: 17.63 s +2024-11-22 12:00:12.940094: +2024-11-22 12:00:12.940296: Epoch 4645 +2024-11-22 12:00:12.940414: Current learning rate: 0.00457 +2024-11-22 12:00:32.096286: train_loss -0.7984 +2024-11-22 12:00:32.096500: val_loss -0.7188 +2024-11-22 12:00:32.096575: Pseudo dice [0.8492] +2024-11-22 12:00:32.096650: Epoch time: 19.16 s +2024-11-22 12:00:32.968281: +2024-11-22 12:00:32.968481: Epoch 4646 +2024-11-22 12:00:32.968595: Current learning rate: 0.00457 +2024-11-22 12:00:52.297578: train_loss -0.8101 +2024-11-22 12:00:52.297811: val_loss -0.7447 +2024-11-22 12:00:52.297893: Pseudo dice [0.8736] +2024-11-22 12:00:52.297972: Epoch time: 19.33 s +2024-11-22 12:00:53.196489: +2024-11-22 12:00:53.196685: Epoch 4647 +2024-11-22 12:00:53.196794: Current learning rate: 0.00457 +2024-11-22 12:01:11.446815: train_loss -0.7949 +2024-11-22 12:01:11.447048: val_loss -0.7375 +2024-11-22 12:01:11.447134: Pseudo dice [0.8383] +2024-11-22 12:01:11.447237: Epoch time: 18.25 s +2024-11-22 12:01:12.321400: +2024-11-22 12:01:12.321660: Epoch 4648 +2024-11-22 12:01:12.321770: Current learning rate: 0.00457 +2024-11-22 12:01:31.269189: train_loss -0.8026 +2024-11-22 12:01:31.269433: val_loss -0.7616 +2024-11-22 12:01:31.269513: Pseudo dice [0.8515] +2024-11-22 12:01:31.269593: Epoch time: 18.95 s +2024-11-22 12:01:32.140704: +2024-11-22 12:01:32.140914: Epoch 4649 +2024-11-22 12:01:32.141033: Current learning rate: 0.00457 +2024-11-22 12:01:49.880887: train_loss -0.7956 +2024-11-22 12:01:49.881110: val_loss -0.7472 +2024-11-22 12:01:49.881189: Pseudo dice [0.8487] +2024-11-22 12:01:49.881271: Epoch time: 17.74 s +2024-11-22 12:01:51.443552: +2024-11-22 12:01:51.443851: Epoch 4650 +2024-11-22 12:01:51.443966: Current learning rate: 0.00457 +2024-11-22 12:02:09.627986: train_loss -0.8016 +2024-11-22 12:02:09.628244: val_loss -0.7523 +2024-11-22 12:02:09.628321: Pseudo dice [0.8466] +2024-11-22 12:02:09.628403: Epoch time: 18.19 s +2024-11-22 12:02:10.519646: +2024-11-22 12:02:10.519886: Epoch 4651 +2024-11-22 12:02:10.520010: Current learning rate: 0.00457 +2024-11-22 12:02:29.543607: train_loss -0.8066 +2024-11-22 12:02:29.543906: val_loss -0.7488 +2024-11-22 12:02:29.546621: Pseudo dice [0.8395] +2024-11-22 12:02:29.546771: Epoch time: 19.02 s +2024-11-22 12:02:30.430912: +2024-11-22 12:02:30.431228: Epoch 4652 +2024-11-22 12:02:30.431343: Current learning rate: 0.00457 +2024-11-22 12:02:48.668118: train_loss -0.7969 +2024-11-22 12:02:48.668365: val_loss -0.7739 +2024-11-22 12:02:48.668445: Pseudo dice [0.8634] +2024-11-22 12:02:48.668527: Epoch time: 18.23 s +2024-11-22 12:02:49.570578: +2024-11-22 12:02:49.570798: Epoch 4653 +2024-11-22 12:02:49.570911: Current learning rate: 0.00456 +2024-11-22 12:03:07.958888: train_loss -0.8007 +2024-11-22 12:03:07.959124: val_loss -0.756 +2024-11-22 12:03:07.959200: Pseudo dice [0.8443] +2024-11-22 12:03:07.959281: Epoch time: 18.39 s +2024-11-22 12:03:08.928446: +2024-11-22 12:03:08.928759: Epoch 4654 +2024-11-22 12:03:08.928881: Current learning rate: 0.00456 +2024-11-22 12:03:27.396242: train_loss -0.7918 +2024-11-22 12:03:27.396473: val_loss -0.7596 +2024-11-22 12:03:27.396549: Pseudo dice [0.8699] +2024-11-22 12:03:27.396841: Epoch time: 18.47 s +2024-11-22 12:03:27.396909: Yayy! New best EMA pseudo Dice: 0.8511 +2024-11-22 12:03:28.720666: +2024-11-22 12:03:28.720872: Epoch 4655 +2024-11-22 12:03:28.720983: Current learning rate: 0.00456 +2024-11-22 12:03:47.014060: train_loss -0.802 +2024-11-22 12:03:47.019457: val_loss -0.722 +2024-11-22 12:03:47.019633: Pseudo dice [0.8125] +2024-11-22 12:03:47.019733: Epoch time: 18.29 s +2024-11-22 12:03:48.021469: +2024-11-22 12:03:48.021719: Epoch 4656 +2024-11-22 12:03:48.021835: Current learning rate: 0.00456 +2024-11-22 12:04:06.908176: train_loss -0.8056 +2024-11-22 12:04:06.908398: val_loss -0.7367 +2024-11-22 12:04:06.908478: Pseudo dice [0.8455] +2024-11-22 12:04:06.908558: Epoch time: 18.89 s +2024-11-22 12:04:07.784776: +2024-11-22 12:04:07.785033: Epoch 4657 +2024-11-22 12:04:07.785147: Current learning rate: 0.00456 +2024-11-22 12:04:26.802566: train_loss -0.7986 +2024-11-22 12:04:26.802784: val_loss -0.7418 +2024-11-22 12:04:26.802860: Pseudo dice [0.8255] +2024-11-22 12:04:26.802942: Epoch time: 19.02 s +2024-11-22 12:04:27.690389: +2024-11-22 12:04:27.690588: Epoch 4658 +2024-11-22 12:04:27.690697: Current learning rate: 0.00456 +2024-11-22 12:04:45.455112: train_loss -0.8027 +2024-11-22 12:04:45.455327: val_loss -0.7523 +2024-11-22 12:04:45.455401: Pseudo dice [0.8513] +2024-11-22 12:04:45.455507: Epoch time: 17.77 s +2024-11-22 12:04:46.337403: +2024-11-22 12:04:46.337599: Epoch 4659 +2024-11-22 12:04:46.337710: Current learning rate: 0.00456 +2024-11-22 12:05:04.941842: train_loss -0.7933 +2024-11-22 12:05:04.942165: val_loss -0.7444 +2024-11-22 12:05:04.942254: Pseudo dice [0.8576] +2024-11-22 12:05:04.942342: Epoch time: 18.61 s +2024-11-22 12:05:05.826559: +2024-11-22 12:05:05.826768: Epoch 4660 +2024-11-22 12:05:05.826882: Current learning rate: 0.00456 +2024-11-22 12:05:25.017782: train_loss -0.7994 +2024-11-22 12:05:25.018006: val_loss -0.7639 +2024-11-22 12:05:25.018086: Pseudo dice [0.8463] +2024-11-22 12:05:25.018162: Epoch time: 19.19 s +2024-11-22 12:05:25.890867: +2024-11-22 12:05:25.891155: Epoch 4661 +2024-11-22 12:05:25.891270: Current learning rate: 0.00455 +2024-11-22 12:05:44.197969: train_loss -0.8051 +2024-11-22 12:05:44.198189: val_loss -0.7745 +2024-11-22 12:05:44.198263: Pseudo dice [0.8558] +2024-11-22 12:05:44.198337: Epoch time: 18.31 s +2024-11-22 12:05:45.440271: +2024-11-22 12:05:45.440547: Epoch 4662 +2024-11-22 12:05:45.440659: Current learning rate: 0.00455 +2024-11-22 12:06:04.713256: train_loss -0.8086 +2024-11-22 12:06:04.713512: val_loss -0.7401 +2024-11-22 12:06:04.713588: Pseudo dice [0.8437] +2024-11-22 12:06:04.713677: Epoch time: 19.27 s +2024-11-22 12:06:05.695067: +2024-11-22 12:06:05.695286: Epoch 4663 +2024-11-22 12:06:05.695400: Current learning rate: 0.00455 +2024-11-22 12:06:24.596856: train_loss -0.7991 +2024-11-22 12:06:24.599229: val_loss -0.7269 +2024-11-22 12:06:24.599324: Pseudo dice [0.8515] +2024-11-22 12:06:24.599401: Epoch time: 18.9 s +2024-11-22 12:06:25.513956: +2024-11-22 12:06:25.514196: Epoch 4664 +2024-11-22 12:06:25.514307: Current learning rate: 0.00455 +2024-11-22 12:06:44.500133: train_loss -0.7943 +2024-11-22 12:06:44.500350: val_loss -0.7588 +2024-11-22 12:06:44.500424: Pseudo dice [0.8632] +2024-11-22 12:06:44.500499: Epoch time: 18.99 s +2024-11-22 12:06:45.386631: +2024-11-22 12:06:45.386886: Epoch 4665 +2024-11-22 12:06:45.387010: Current learning rate: 0.00455 +2024-11-22 12:07:03.128388: train_loss -0.8004 +2024-11-22 12:07:03.128604: val_loss -0.763 +2024-11-22 12:07:03.128685: Pseudo dice [0.8316] +2024-11-22 12:07:03.128764: Epoch time: 17.74 s +2024-11-22 12:07:04.009248: +2024-11-22 12:07:04.009474: Epoch 4666 +2024-11-22 12:07:04.009593: Current learning rate: 0.00455 +2024-11-22 12:07:21.492696: train_loss -0.8072 +2024-11-22 12:07:21.492934: val_loss -0.7476 +2024-11-22 12:07:21.493016: Pseudo dice [0.8572] +2024-11-22 12:07:21.493098: Epoch time: 17.48 s +2024-11-22 12:07:22.375877: +2024-11-22 12:07:22.376126: Epoch 4667 +2024-11-22 12:07:22.376251: Current learning rate: 0.00455 +2024-11-22 12:07:40.895696: train_loss -0.7963 +2024-11-22 12:07:40.895920: val_loss -0.7829 +2024-11-22 12:07:40.896001: Pseudo dice [0.8677] +2024-11-22 12:07:40.896141: Epoch time: 18.52 s +2024-11-22 12:07:41.778660: +2024-11-22 12:07:41.778875: Epoch 4668 +2024-11-22 12:07:41.778995: Current learning rate: 0.00455 +2024-11-22 12:08:00.863750: train_loss -0.7962 +2024-11-22 12:08:00.863978: val_loss -0.7535 +2024-11-22 12:08:00.864062: Pseudo dice [0.8291] +2024-11-22 12:08:00.864140: Epoch time: 19.09 s +2024-11-22 12:08:01.746505: +2024-11-22 12:08:01.746751: Epoch 4669 +2024-11-22 12:08:01.746867: Current learning rate: 0.00455 +2024-11-22 12:08:21.288350: train_loss -0.8005 +2024-11-22 12:08:21.288613: val_loss -0.7639 +2024-11-22 12:08:21.288693: Pseudo dice [0.8416] +2024-11-22 12:08:21.288778: Epoch time: 19.54 s +2024-11-22 12:08:22.283985: +2024-11-22 12:08:22.284265: Epoch 4670 +2024-11-22 12:08:22.284376: Current learning rate: 0.00454 +2024-11-22 12:08:41.826929: train_loss -0.7963 +2024-11-22 12:08:41.827157: val_loss -0.7634 +2024-11-22 12:08:41.832523: Pseudo dice [0.8442] +2024-11-22 12:08:41.832621: Epoch time: 19.54 s +2024-11-22 12:08:42.734437: +2024-11-22 12:08:42.734652: Epoch 4671 +2024-11-22 12:08:42.734764: Current learning rate: 0.00454 +2024-11-22 12:09:01.414960: train_loss -0.7963 +2024-11-22 12:09:01.415184: val_loss -0.7312 +2024-11-22 12:09:01.415262: Pseudo dice [0.8495] +2024-11-22 12:09:01.415343: Epoch time: 18.68 s +2024-11-22 12:09:02.287246: +2024-11-22 12:09:02.287437: Epoch 4672 +2024-11-22 12:09:02.287548: Current learning rate: 0.00454 +2024-11-22 12:09:20.773170: train_loss -0.7831 +2024-11-22 12:09:20.773401: val_loss -0.7618 +2024-11-22 12:09:20.773477: Pseudo dice [0.8482] +2024-11-22 12:09:20.773554: Epoch time: 18.49 s +2024-11-22 12:09:21.852337: +2024-11-22 12:09:21.852578: Epoch 4673 +2024-11-22 12:09:21.852698: Current learning rate: 0.00454 +2024-11-22 12:09:40.870115: train_loss -0.7966 +2024-11-22 12:09:40.870361: val_loss -0.7368 +2024-11-22 12:09:40.870435: Pseudo dice [0.8306] +2024-11-22 12:09:40.870518: Epoch time: 19.02 s +2024-11-22 12:09:42.207913: +2024-11-22 12:09:42.208140: Epoch 4674 +2024-11-22 12:09:42.208252: Current learning rate: 0.00454 +2024-11-22 12:10:01.215816: train_loss -0.782 +2024-11-22 12:10:01.216044: val_loss -0.7325 +2024-11-22 12:10:01.216119: Pseudo dice [0.8383] +2024-11-22 12:10:01.216195: Epoch time: 19.01 s +2024-11-22 12:10:02.115126: +2024-11-22 12:10:02.115346: Epoch 4675 +2024-11-22 12:10:02.115491: Current learning rate: 0.00454 +2024-11-22 12:10:22.323537: train_loss -0.7812 +2024-11-22 12:10:22.323765: val_loss -0.7478 +2024-11-22 12:10:22.323839: Pseudo dice [0.8549] +2024-11-22 12:10:22.323917: Epoch time: 20.21 s +2024-11-22 12:10:23.206868: +2024-11-22 12:10:23.207078: Epoch 4676 +2024-11-22 12:10:23.207186: Current learning rate: 0.00454 +2024-11-22 12:10:41.488198: train_loss -0.7921 +2024-11-22 12:10:41.488418: val_loss -0.7258 +2024-11-22 12:10:41.488497: Pseudo dice [0.8349] +2024-11-22 12:10:41.488577: Epoch time: 18.28 s +2024-11-22 12:10:42.410627: +2024-11-22 12:10:42.410916: Epoch 4677 +2024-11-22 12:10:42.411037: Current learning rate: 0.00454 +2024-11-22 12:11:01.888585: train_loss -0.7956 +2024-11-22 12:11:01.888861: val_loss -0.7381 +2024-11-22 12:11:01.888937: Pseudo dice [0.8439] +2024-11-22 12:11:01.889032: Epoch time: 19.48 s +2024-11-22 12:11:02.801718: +2024-11-22 12:11:02.801924: Epoch 4678 +2024-11-22 12:11:02.802038: Current learning rate: 0.00453 +2024-11-22 12:11:22.031965: train_loss -0.7923 +2024-11-22 12:11:22.032192: val_loss -0.7258 +2024-11-22 12:11:22.032266: Pseudo dice [0.8207] +2024-11-22 12:11:22.032343: Epoch time: 19.23 s +2024-11-22 12:11:22.918283: +2024-11-22 12:11:22.918511: Epoch 4679 +2024-11-22 12:11:22.918624: Current learning rate: 0.00453 +2024-11-22 12:11:41.898960: train_loss -0.786 +2024-11-22 12:11:41.899182: val_loss -0.7599 +2024-11-22 12:11:41.899261: Pseudo dice [0.8368] +2024-11-22 12:11:41.899339: Epoch time: 18.98 s +2024-11-22 12:11:42.797081: +2024-11-22 12:11:42.797395: Epoch 4680 +2024-11-22 12:11:42.797513: Current learning rate: 0.00453 +2024-11-22 12:12:01.628352: train_loss -0.7919 +2024-11-22 12:12:01.628808: val_loss -0.772 +2024-11-22 12:12:01.628896: Pseudo dice [0.8334] +2024-11-22 12:12:01.628975: Epoch time: 18.83 s +2024-11-22 12:12:02.525366: +2024-11-22 12:12:02.525624: Epoch 4681 +2024-11-22 12:12:02.525739: Current learning rate: 0.00453 +2024-11-22 12:12:21.203787: train_loss -0.7962 +2024-11-22 12:12:21.204035: val_loss -0.7439 +2024-11-22 12:12:21.204110: Pseudo dice [0.8461] +2024-11-22 12:12:21.204191: Epoch time: 18.68 s +2024-11-22 12:12:22.081403: +2024-11-22 12:12:22.081677: Epoch 4682 +2024-11-22 12:12:22.081792: Current learning rate: 0.00453 +2024-11-22 12:12:40.227887: train_loss -0.793 +2024-11-22 12:12:40.228109: val_loss -0.7494 +2024-11-22 12:12:40.228185: Pseudo dice [0.8529] +2024-11-22 12:12:40.228262: Epoch time: 18.15 s +2024-11-22 12:12:41.102506: +2024-11-22 12:12:41.102757: Epoch 4683 +2024-11-22 12:12:41.102874: Current learning rate: 0.00453 +2024-11-22 12:12:59.881536: train_loss -0.803 +2024-11-22 12:12:59.881761: val_loss -0.7618 +2024-11-22 12:12:59.881834: Pseudo dice [0.8438] +2024-11-22 12:12:59.881911: Epoch time: 18.78 s +2024-11-22 12:13:00.785569: +2024-11-22 12:13:00.785777: Epoch 4684 +2024-11-22 12:13:00.785891: Current learning rate: 0.00453 +2024-11-22 12:13:19.937825: train_loss -0.8015 +2024-11-22 12:13:19.940209: val_loss -0.7563 +2024-11-22 12:13:19.940331: Pseudo dice [0.8365] +2024-11-22 12:13:19.940414: Epoch time: 19.15 s +2024-11-22 12:13:20.854550: +2024-11-22 12:13:20.854758: Epoch 4685 +2024-11-22 12:13:20.854870: Current learning rate: 0.00453 +2024-11-22 12:13:39.174481: train_loss -0.7997 +2024-11-22 12:13:39.174734: val_loss -0.7569 +2024-11-22 12:13:39.174809: Pseudo dice [0.8573] +2024-11-22 12:13:39.174968: Epoch time: 18.32 s +2024-11-22 12:13:40.472977: +2024-11-22 12:13:40.473199: Epoch 4686 +2024-11-22 12:13:40.473313: Current learning rate: 0.00452 +2024-11-22 12:14:00.249813: train_loss -0.7927 +2024-11-22 12:14:00.250050: val_loss -0.7228 +2024-11-22 12:14:00.250125: Pseudo dice [0.834] +2024-11-22 12:14:00.252432: Epoch time: 19.78 s +2024-11-22 12:14:01.306641: +2024-11-22 12:14:01.306884: Epoch 4687 +2024-11-22 12:14:01.307003: Current learning rate: 0.00452 +2024-11-22 12:14:20.175533: train_loss -0.7987 +2024-11-22 12:14:20.175754: val_loss -0.7469 +2024-11-22 12:14:20.175829: Pseudo dice [0.8471] +2024-11-22 12:14:20.175904: Epoch time: 18.87 s +2024-11-22 12:14:21.052672: +2024-11-22 12:14:21.052883: Epoch 4688 +2024-11-22 12:14:21.053003: Current learning rate: 0.00452 +2024-11-22 12:14:39.146789: train_loss -0.7854 +2024-11-22 12:14:39.147011: val_loss -0.7582 +2024-11-22 12:14:39.147094: Pseudo dice [0.8572] +2024-11-22 12:14:39.147185: Epoch time: 18.09 s +2024-11-22 12:14:40.026791: +2024-11-22 12:14:40.027032: Epoch 4689 +2024-11-22 12:14:40.027152: Current learning rate: 0.00452 +2024-11-22 12:14:58.877650: train_loss -0.7869 +2024-11-22 12:14:58.877909: val_loss -0.7748 +2024-11-22 12:14:58.877995: Pseudo dice [0.8459] +2024-11-22 12:14:58.878085: Epoch time: 18.85 s +2024-11-22 12:14:59.758606: +2024-11-22 12:14:59.758849: Epoch 4690 +2024-11-22 12:14:59.758969: Current learning rate: 0.00452 +2024-11-22 12:15:18.017843: train_loss -0.7953 +2024-11-22 12:15:18.018081: val_loss -0.7309 +2024-11-22 12:15:18.018160: Pseudo dice [0.8511] +2024-11-22 12:15:18.018242: Epoch time: 18.26 s +2024-11-22 12:15:18.909966: +2024-11-22 12:15:18.910190: Epoch 4691 +2024-11-22 12:15:18.910306: Current learning rate: 0.00452 +2024-11-22 12:15:37.800471: train_loss -0.7791 +2024-11-22 12:15:37.800682: val_loss -0.7439 +2024-11-22 12:15:37.800758: Pseudo dice [0.8309] +2024-11-22 12:15:37.800895: Epoch time: 18.89 s +2024-11-22 12:15:38.678937: +2024-11-22 12:15:38.679167: Epoch 4692 +2024-11-22 12:15:38.679283: Current learning rate: 0.00452 +2024-11-22 12:15:57.119594: train_loss -0.774 +2024-11-22 12:15:57.119875: val_loss -0.7377 +2024-11-22 12:15:57.119953: Pseudo dice [0.845] +2024-11-22 12:15:57.120044: Epoch time: 18.44 s +2024-11-22 12:15:58.011144: +2024-11-22 12:15:58.011375: Epoch 4693 +2024-11-22 12:15:58.011492: Current learning rate: 0.00452 +2024-11-22 12:16:17.495869: train_loss -0.7838 +2024-11-22 12:16:17.496124: val_loss -0.7377 +2024-11-22 12:16:17.496198: Pseudo dice [0.8049] +2024-11-22 12:16:17.496278: Epoch time: 19.49 s +2024-11-22 12:16:18.367784: +2024-11-22 12:16:18.368007: Epoch 4694 +2024-11-22 12:16:18.368121: Current learning rate: 0.00451 +2024-11-22 12:16:36.417016: train_loss -0.7848 +2024-11-22 12:16:36.417232: val_loss -0.7201 +2024-11-22 12:16:36.417311: Pseudo dice [0.832] +2024-11-22 12:16:36.417389: Epoch time: 18.05 s +2024-11-22 12:16:37.293877: +2024-11-22 12:16:37.294116: Epoch 4695 +2024-11-22 12:16:37.294242: Current learning rate: 0.00451 +2024-11-22 12:16:57.457217: train_loss -0.7938 +2024-11-22 12:16:57.457443: val_loss -0.7046 +2024-11-22 12:16:57.457521: Pseudo dice [0.8418] +2024-11-22 12:16:57.457600: Epoch time: 20.16 s +2024-11-22 12:16:58.323078: +2024-11-22 12:16:58.323311: Epoch 4696 +2024-11-22 12:16:58.323424: Current learning rate: 0.00451 +2024-11-22 12:17:16.708474: train_loss -0.7936 +2024-11-22 12:17:16.708697: val_loss -0.7156 +2024-11-22 12:17:16.708783: Pseudo dice [0.8145] +2024-11-22 12:17:16.708868: Epoch time: 18.39 s +2024-11-22 12:17:17.597251: +2024-11-22 12:17:17.597454: Epoch 4697 +2024-11-22 12:17:17.597571: Current learning rate: 0.00451 +2024-11-22 12:17:36.536901: train_loss -0.7729 +2024-11-22 12:17:36.537157: val_loss -0.7638 +2024-11-22 12:17:36.537231: Pseudo dice [0.8368] +2024-11-22 12:17:36.537315: Epoch time: 18.94 s +2024-11-22 12:17:37.830027: +2024-11-22 12:17:37.830241: Epoch 4698 +2024-11-22 12:17:37.830351: Current learning rate: 0.00451 +2024-11-22 12:17:57.246585: train_loss -0.7792 +2024-11-22 12:17:57.251981: val_loss -0.7399 +2024-11-22 12:17:57.252112: Pseudo dice [0.8404] +2024-11-22 12:17:57.252200: Epoch time: 19.42 s +2024-11-22 12:17:58.268199: +2024-11-22 12:17:58.268428: Epoch 4699 +2024-11-22 12:17:58.268539: Current learning rate: 0.00451 +2024-11-22 12:18:17.461381: train_loss -0.7891 +2024-11-22 12:18:17.461627: val_loss -0.7162 +2024-11-22 12:18:17.461709: Pseudo dice [0.8206] +2024-11-22 12:18:17.461788: Epoch time: 19.19 s +2024-11-22 12:18:18.657240: +2024-11-22 12:18:18.657456: Epoch 4700 +2024-11-22 12:18:18.657565: Current learning rate: 0.00451 +2024-11-22 12:18:37.271636: train_loss -0.7827 +2024-11-22 12:18:37.271877: val_loss -0.7379 +2024-11-22 12:18:37.271955: Pseudo dice [0.8478] +2024-11-22 12:18:37.272042: Epoch time: 18.62 s +2024-11-22 12:18:38.143687: +2024-11-22 12:18:38.143903: Epoch 4701 +2024-11-22 12:18:38.144018: Current learning rate: 0.00451 +2024-11-22 12:18:56.245062: train_loss -0.7936 +2024-11-22 12:18:56.245281: val_loss -0.7108 +2024-11-22 12:18:56.245425: Pseudo dice [0.8636] +2024-11-22 12:18:56.245507: Epoch time: 18.1 s +2024-11-22 12:18:57.136724: +2024-11-22 12:18:57.136950: Epoch 4702 +2024-11-22 12:18:57.137070: Current learning rate: 0.0045 +2024-11-22 12:19:15.590114: train_loss -0.7905 +2024-11-22 12:19:15.590324: val_loss -0.7365 +2024-11-22 12:19:15.590398: Pseudo dice [0.8397] +2024-11-22 12:19:15.590474: Epoch time: 18.45 s +2024-11-22 12:19:16.474876: +2024-11-22 12:19:16.475100: Epoch 4703 +2024-11-22 12:19:16.475211: Current learning rate: 0.0045 +2024-11-22 12:19:35.968909: train_loss -0.7869 +2024-11-22 12:19:35.969144: val_loss -0.7593 +2024-11-22 12:19:35.969221: Pseudo dice [0.8417] +2024-11-22 12:19:35.969298: Epoch time: 19.49 s +2024-11-22 12:19:36.838940: +2024-11-22 12:19:36.839156: Epoch 4704 +2024-11-22 12:19:36.839268: Current learning rate: 0.0045 +2024-11-22 12:19:56.127972: train_loss -0.7861 +2024-11-22 12:19:56.128197: val_loss -0.784 +2024-11-22 12:19:56.128272: Pseudo dice [0.8598] +2024-11-22 12:19:56.128367: Epoch time: 19.29 s +2024-11-22 12:19:56.995170: +2024-11-22 12:19:56.995394: Epoch 4705 +2024-11-22 12:19:56.995540: Current learning rate: 0.0045 +2024-11-22 12:20:16.440571: train_loss -0.7893 +2024-11-22 12:20:16.440793: val_loss -0.7454 +2024-11-22 12:20:16.440872: Pseudo dice [0.8496] +2024-11-22 12:20:16.440955: Epoch time: 19.45 s +2024-11-22 12:20:17.321567: +2024-11-22 12:20:17.321775: Epoch 4706 +2024-11-22 12:20:17.321889: Current learning rate: 0.0045 +2024-11-22 12:20:36.587917: train_loss -0.7876 +2024-11-22 12:20:36.588164: val_loss -0.757 +2024-11-22 12:20:36.588294: Pseudo dice [0.8468] +2024-11-22 12:20:36.588373: Epoch time: 19.27 s +2024-11-22 12:20:37.468315: +2024-11-22 12:20:37.468581: Epoch 4707 +2024-11-22 12:20:37.468694: Current learning rate: 0.0045 +2024-11-22 12:20:56.074758: train_loss -0.7968 +2024-11-22 12:20:56.074975: val_loss -0.7556 +2024-11-22 12:20:56.075055: Pseudo dice [0.8425] +2024-11-22 12:20:56.075130: Epoch time: 18.61 s +2024-11-22 12:20:56.938832: +2024-11-22 12:20:56.939035: Epoch 4708 +2024-11-22 12:20:56.939148: Current learning rate: 0.0045 +2024-11-22 12:21:15.282818: train_loss -0.7875 +2024-11-22 12:21:15.283045: val_loss -0.7513 +2024-11-22 12:21:15.283122: Pseudo dice [0.8484] +2024-11-22 12:21:15.283201: Epoch time: 18.34 s +2024-11-22 12:21:16.166893: +2024-11-22 12:21:16.167128: Epoch 4709 +2024-11-22 12:21:16.167235: Current learning rate: 0.0045 +2024-11-22 12:21:35.241796: train_loss -0.7939 +2024-11-22 12:21:35.242031: val_loss -0.7269 +2024-11-22 12:21:35.242108: Pseudo dice [0.8307] +2024-11-22 12:21:35.242188: Epoch time: 19.08 s +2024-11-22 12:21:36.592678: +2024-11-22 12:21:36.592914: Epoch 4710 +2024-11-22 12:21:36.593024: Current learning rate: 0.00449 +2024-11-22 12:21:55.458525: train_loss -0.7938 +2024-11-22 12:21:55.458747: val_loss -0.7308 +2024-11-22 12:21:55.458822: Pseudo dice [0.8539] +2024-11-22 12:21:55.458899: Epoch time: 18.87 s +2024-11-22 12:21:56.430879: +2024-11-22 12:21:56.431103: Epoch 4711 +2024-11-22 12:21:56.431212: Current learning rate: 0.00449 +2024-11-22 12:22:14.995621: train_loss -0.7868 +2024-11-22 12:22:14.995853: val_loss -0.755 +2024-11-22 12:22:14.995956: Pseudo dice [0.8688] +2024-11-22 12:22:14.996046: Epoch time: 18.57 s +2024-11-22 12:22:15.890213: +2024-11-22 12:22:15.890448: Epoch 4712 +2024-11-22 12:22:15.890565: Current learning rate: 0.00449 +2024-11-22 12:22:34.651039: train_loss -0.7682 +2024-11-22 12:22:34.651320: val_loss -0.7577 +2024-11-22 12:22:34.651451: Pseudo dice [0.8219] +2024-11-22 12:22:34.651537: Epoch time: 18.76 s +2024-11-22 12:22:35.515885: +2024-11-22 12:22:35.516081: Epoch 4713 +2024-11-22 12:22:35.516181: Current learning rate: 0.00449 +2024-11-22 12:22:54.485155: train_loss -0.7754 +2024-11-22 12:22:54.485368: val_loss -0.7497 +2024-11-22 12:22:54.485443: Pseudo dice [0.858] +2024-11-22 12:22:54.485519: Epoch time: 18.97 s +2024-11-22 12:22:55.338975: +2024-11-22 12:22:55.339256: Epoch 4714 +2024-11-22 12:22:55.339369: Current learning rate: 0.00449 +2024-11-22 12:23:13.068296: train_loss -0.7921 +2024-11-22 12:23:13.068534: val_loss -0.738 +2024-11-22 12:23:13.068607: Pseudo dice [0.8441] +2024-11-22 12:23:13.068682: Epoch time: 17.73 s +2024-11-22 12:23:14.081758: +2024-11-22 12:23:14.081959: Epoch 4715 +2024-11-22 12:23:14.082074: Current learning rate: 0.00449 +2024-11-22 12:23:33.302183: train_loss -0.7917 +2024-11-22 12:23:33.302396: val_loss -0.7303 +2024-11-22 12:23:33.302472: Pseudo dice [0.8273] +2024-11-22 12:23:33.302551: Epoch time: 19.22 s +2024-11-22 12:23:34.169130: +2024-11-22 12:23:34.169358: Epoch 4716 +2024-11-22 12:23:34.169473: Current learning rate: 0.00449 +2024-11-22 12:23:51.780996: train_loss -0.784 +2024-11-22 12:23:51.781247: val_loss -0.7641 +2024-11-22 12:23:51.781325: Pseudo dice [0.8408] +2024-11-22 12:23:51.781408: Epoch time: 17.61 s +2024-11-22 12:23:52.657997: +2024-11-22 12:23:52.658242: Epoch 4717 +2024-11-22 12:23:52.658356: Current learning rate: 0.00449 +2024-11-22 12:24:11.448523: train_loss -0.7918 +2024-11-22 12:24:11.448735: val_loss -0.7412 +2024-11-22 12:24:11.448809: Pseudo dice [0.8339] +2024-11-22 12:24:11.448883: Epoch time: 18.79 s +2024-11-22 12:24:12.459862: +2024-11-22 12:24:12.460081: Epoch 4718 +2024-11-22 12:24:12.460191: Current learning rate: 0.00448 +2024-11-22 12:24:33.241497: train_loss -0.7913 +2024-11-22 12:24:33.241711: val_loss -0.7644 +2024-11-22 12:24:33.241786: Pseudo dice [0.8393] +2024-11-22 12:24:33.241862: Epoch time: 20.78 s +2024-11-22 12:24:34.120361: +2024-11-22 12:24:34.120600: Epoch 4719 +2024-11-22 12:24:34.120720: Current learning rate: 0.00448 +2024-11-22 12:24:53.606756: train_loss -0.7874 +2024-11-22 12:24:53.606972: val_loss -0.7505 +2024-11-22 12:24:53.607054: Pseudo dice [0.8664] +2024-11-22 12:24:53.607137: Epoch time: 19.49 s +2024-11-22 12:24:54.616215: +2024-11-22 12:24:54.616423: Epoch 4720 +2024-11-22 12:24:54.616536: Current learning rate: 0.00448 +2024-11-22 12:25:13.302608: train_loss -0.792 +2024-11-22 12:25:13.302874: val_loss -0.7415 +2024-11-22 12:25:13.302953: Pseudo dice [0.8492] +2024-11-22 12:25:13.303038: Epoch time: 18.69 s +2024-11-22 12:25:14.323010: +2024-11-22 12:25:14.323232: Epoch 4721 +2024-11-22 12:25:14.323341: Current learning rate: 0.00448 +2024-11-22 12:25:32.168119: train_loss -0.7951 +2024-11-22 12:25:32.168409: val_loss -0.7494 +2024-11-22 12:25:32.168491: Pseudo dice [0.8555] +2024-11-22 12:25:32.168569: Epoch time: 17.85 s +2024-11-22 12:25:33.465141: +2024-11-22 12:25:33.465384: Epoch 4722 +2024-11-22 12:25:33.465495: Current learning rate: 0.00448 +2024-11-22 12:25:51.611623: train_loss -0.8068 +2024-11-22 12:25:51.611841: val_loss -0.7467 +2024-11-22 12:25:51.611915: Pseudo dice [0.8684] +2024-11-22 12:25:51.611988: Epoch time: 18.15 s +2024-11-22 12:25:52.576030: +2024-11-22 12:25:52.576273: Epoch 4723 +2024-11-22 12:25:52.576385: Current learning rate: 0.00448 +2024-11-22 12:26:11.542585: train_loss -0.7984 +2024-11-22 12:26:11.542850: val_loss -0.7401 +2024-11-22 12:26:11.542930: Pseudo dice [0.8457] +2024-11-22 12:26:11.545182: Epoch time: 18.97 s +2024-11-22 12:26:12.424300: +2024-11-22 12:26:12.424531: Epoch 4724 +2024-11-22 12:26:12.424641: Current learning rate: 0.00448 +2024-11-22 12:26:31.201417: train_loss -0.7951 +2024-11-22 12:26:31.201638: val_loss -0.7601 +2024-11-22 12:26:31.201715: Pseudo dice [0.8584] +2024-11-22 12:26:31.201792: Epoch time: 18.78 s +2024-11-22 12:26:32.092181: +2024-11-22 12:26:32.092419: Epoch 4725 +2024-11-22 12:26:32.092530: Current learning rate: 0.00448 +2024-11-22 12:26:51.090779: train_loss -0.7952 +2024-11-22 12:26:51.091017: val_loss -0.7471 +2024-11-22 12:26:51.091097: Pseudo dice [0.8493] +2024-11-22 12:26:51.091175: Epoch time: 19.0 s +2024-11-22 12:26:51.994862: +2024-11-22 12:26:51.995089: Epoch 4726 +2024-11-22 12:26:51.995215: Current learning rate: 0.00447 +2024-11-22 12:27:09.931685: train_loss -0.7948 +2024-11-22 12:27:09.931911: val_loss -0.7603 +2024-11-22 12:27:09.931987: Pseudo dice [0.8504] +2024-11-22 12:27:09.932072: Epoch time: 17.94 s +2024-11-22 12:27:10.816354: +2024-11-22 12:27:10.816628: Epoch 4727 +2024-11-22 12:27:10.816739: Current learning rate: 0.00447 +2024-11-22 12:27:29.692612: train_loss -0.7888 +2024-11-22 12:27:29.692934: val_loss -0.765 +2024-11-22 12:27:29.693016: Pseudo dice [0.8649] +2024-11-22 12:27:29.693103: Epoch time: 18.88 s +2024-11-22 12:27:30.586453: +2024-11-22 12:27:30.586674: Epoch 4728 +2024-11-22 12:27:30.586791: Current learning rate: 0.00447 +2024-11-22 12:27:50.090842: train_loss -0.794 +2024-11-22 12:27:50.091060: val_loss -0.7448 +2024-11-22 12:27:50.091140: Pseudo dice [0.8479] +2024-11-22 12:27:50.091217: Epoch time: 19.51 s +2024-11-22 12:27:50.974063: +2024-11-22 12:27:50.974280: Epoch 4729 +2024-11-22 12:27:50.974390: Current learning rate: 0.00447 +2024-11-22 12:28:09.992534: train_loss -0.8031 +2024-11-22 12:28:09.992754: val_loss -0.7748 +2024-11-22 12:28:09.992831: Pseudo dice [0.8512] +2024-11-22 12:28:09.992904: Epoch time: 19.02 s +2024-11-22 12:28:10.909687: +2024-11-22 12:28:10.909883: Epoch 4730 +2024-11-22 12:28:10.910004: Current learning rate: 0.00447 +2024-11-22 12:28:30.128660: train_loss -0.7882 +2024-11-22 12:28:30.128877: val_loss -0.7505 +2024-11-22 12:28:30.128953: Pseudo dice [0.853] +2024-11-22 12:28:30.129039: Epoch time: 19.22 s +2024-11-22 12:28:31.011242: +2024-11-22 12:28:31.011479: Epoch 4731 +2024-11-22 12:28:31.011597: Current learning rate: 0.00447 +2024-11-22 12:28:49.413626: train_loss -0.7866 +2024-11-22 12:28:49.413869: val_loss -0.7269 +2024-11-22 12:28:49.413952: Pseudo dice [0.8477] +2024-11-22 12:28:49.414044: Epoch time: 18.4 s +2024-11-22 12:28:50.330732: +2024-11-22 12:28:50.331207: Epoch 4732 +2024-11-22 12:28:50.331324: Current learning rate: 0.00447 +2024-11-22 12:29:08.689517: train_loss -0.7831 +2024-11-22 12:29:08.689743: val_loss -0.7592 +2024-11-22 12:29:08.689883: Pseudo dice [0.8542] +2024-11-22 12:29:08.689962: Epoch time: 18.36 s +2024-11-22 12:29:09.598984: +2024-11-22 12:29:09.599192: Epoch 4733 +2024-11-22 12:29:09.599305: Current learning rate: 0.00447 +2024-11-22 12:29:27.936764: train_loss -0.791 +2024-11-22 12:29:27.937019: val_loss -0.7518 +2024-11-22 12:29:27.937098: Pseudo dice [0.8675] +2024-11-22 12:29:27.937173: Epoch time: 18.34 s +2024-11-22 12:29:27.937233: Yayy! New best EMA pseudo Dice: 0.8524 +2024-11-22 12:29:29.491704: +2024-11-22 12:29:29.491920: Epoch 4734 +2024-11-22 12:29:29.492041: Current learning rate: 0.00447 +2024-11-22 12:29:48.268613: train_loss -0.7955 +2024-11-22 12:29:48.268845: val_loss -0.7471 +2024-11-22 12:29:48.268923: Pseudo dice [0.8572] +2024-11-22 12:29:48.269013: Epoch time: 18.78 s +2024-11-22 12:29:48.269075: Yayy! New best EMA pseudo Dice: 0.8529 +2024-11-22 12:29:49.455252: +2024-11-22 12:29:49.455502: Epoch 4735 +2024-11-22 12:29:49.455654: Current learning rate: 0.00446 +2024-11-22 12:30:08.890620: train_loss -0.7903 +2024-11-22 12:30:08.892676: val_loss -0.7626 +2024-11-22 12:30:08.892771: Pseudo dice [0.8523] +2024-11-22 12:30:08.892853: Epoch time: 19.44 s +2024-11-22 12:30:09.773887: +2024-11-22 12:30:09.774119: Epoch 4736 +2024-11-22 12:30:09.774234: Current learning rate: 0.00446 +2024-11-22 12:30:29.583351: train_loss -0.8007 +2024-11-22 12:30:29.583576: val_loss -0.7561 +2024-11-22 12:30:29.583706: Pseudo dice [0.8583] +2024-11-22 12:30:29.583784: Epoch time: 19.81 s +2024-11-22 12:30:29.583846: Yayy! New best EMA pseudo Dice: 0.8534 +2024-11-22 12:30:30.788978: +2024-11-22 12:30:30.789191: Epoch 4737 +2024-11-22 12:30:30.789308: Current learning rate: 0.00446 +2024-11-22 12:30:49.262054: train_loss -0.7925 +2024-11-22 12:30:49.262277: val_loss -0.7687 +2024-11-22 12:30:49.262349: Pseudo dice [0.8658] +2024-11-22 12:30:49.262428: Epoch time: 18.47 s +2024-11-22 12:30:49.262489: Yayy! New best EMA pseudo Dice: 0.8546 +2024-11-22 12:30:50.636540: +2024-11-22 12:30:50.636776: Epoch 4738 +2024-11-22 12:30:50.636889: Current learning rate: 0.00446 +2024-11-22 12:31:08.245884: train_loss -0.7907 +2024-11-22 12:31:08.246204: val_loss -0.763 +2024-11-22 12:31:08.246286: Pseudo dice [0.8344] +2024-11-22 12:31:08.246372: Epoch time: 17.61 s +2024-11-22 12:31:09.163167: +2024-11-22 12:31:09.163384: Epoch 4739 +2024-11-22 12:31:09.163498: Current learning rate: 0.00446 +2024-11-22 12:31:28.336643: train_loss -0.7888 +2024-11-22 12:31:28.336860: val_loss -0.7565 +2024-11-22 12:31:28.336934: Pseudo dice [0.8515] +2024-11-22 12:31:28.337016: Epoch time: 19.17 s +2024-11-22 12:31:29.204742: +2024-11-22 12:31:29.204944: Epoch 4740 +2024-11-22 12:31:29.205072: Current learning rate: 0.00446 +2024-11-22 12:31:48.483636: train_loss -0.7846 +2024-11-22 12:31:48.483858: val_loss -0.7444 +2024-11-22 12:31:48.483937: Pseudo dice [0.8169] +2024-11-22 12:31:48.484026: Epoch time: 19.28 s +2024-11-22 12:31:49.363682: +2024-11-22 12:31:49.363904: Epoch 4741 +2024-11-22 12:31:49.364021: Current learning rate: 0.00446 +2024-11-22 12:32:07.598830: train_loss -0.7713 +2024-11-22 12:32:07.599141: val_loss -0.7129 +2024-11-22 12:32:07.599226: Pseudo dice [0.8306] +2024-11-22 12:32:07.599310: Epoch time: 18.24 s +2024-11-22 12:32:08.499635: +2024-11-22 12:32:08.499918: Epoch 4742 +2024-11-22 12:32:08.500034: Current learning rate: 0.00446 +2024-11-22 12:32:27.780716: train_loss -0.783 +2024-11-22 12:32:27.780966: val_loss -0.7308 +2024-11-22 12:32:27.781047: Pseudo dice [0.8199] +2024-11-22 12:32:27.781130: Epoch time: 19.28 s +2024-11-22 12:32:28.661543: +2024-11-22 12:32:28.661778: Epoch 4743 +2024-11-22 12:32:28.661892: Current learning rate: 0.00445 +2024-11-22 12:32:47.172279: train_loss -0.7833 +2024-11-22 12:32:47.172492: val_loss -0.7536 +2024-11-22 12:32:47.172633: Pseudo dice [0.8433] +2024-11-22 12:32:47.172709: Epoch time: 18.51 s +2024-11-22 12:32:48.049459: +2024-11-22 12:32:48.049680: Epoch 4744 +2024-11-22 12:32:48.049793: Current learning rate: 0.00445 +2024-11-22 12:33:06.311723: train_loss -0.7907 +2024-11-22 12:33:06.311957: val_loss -0.7295 +2024-11-22 12:33:06.312039: Pseudo dice [0.833] +2024-11-22 12:33:06.312117: Epoch time: 18.26 s +2024-11-22 12:33:07.206219: +2024-11-22 12:33:07.206495: Epoch 4745 +2024-11-22 12:33:07.206609: Current learning rate: 0.00445 +2024-11-22 12:33:25.281882: train_loss -0.7867 +2024-11-22 12:33:25.282161: val_loss -0.7473 +2024-11-22 12:33:25.282239: Pseudo dice [0.8438] +2024-11-22 12:33:25.282325: Epoch time: 18.08 s +2024-11-22 12:33:26.158816: +2024-11-22 12:33:26.159103: Epoch 4746 +2024-11-22 12:33:26.159220: Current learning rate: 0.00445 +2024-11-22 12:33:44.726624: train_loss -0.7769 +2024-11-22 12:33:44.726842: val_loss -0.7425 +2024-11-22 12:33:44.726915: Pseudo dice [0.833] +2024-11-22 12:33:44.726990: Epoch time: 18.57 s +2024-11-22 12:33:45.618915: +2024-11-22 12:33:45.619133: Epoch 4747 +2024-11-22 12:33:45.619259: Current learning rate: 0.00445 +2024-11-22 12:34:03.978181: train_loss -0.7851 +2024-11-22 12:34:03.978407: val_loss -0.7421 +2024-11-22 12:34:03.978497: Pseudo dice [0.8351] +2024-11-22 12:34:03.980938: Epoch time: 18.36 s +2024-11-22 12:34:05.025714: +2024-11-22 12:34:05.025928: Epoch 4748 +2024-11-22 12:34:05.026046: Current learning rate: 0.00445 +2024-11-22 12:34:24.100498: train_loss -0.7796 +2024-11-22 12:34:24.100795: val_loss -0.7364 +2024-11-22 12:34:24.100875: Pseudo dice [0.824] +2024-11-22 12:34:24.100955: Epoch time: 19.08 s +2024-11-22 12:34:24.974494: +2024-11-22 12:34:24.974729: Epoch 4749 +2024-11-22 12:34:24.974849: Current learning rate: 0.00445 +2024-11-22 12:34:45.080323: train_loss -0.788 +2024-11-22 12:34:45.080588: val_loss -0.7545 +2024-11-22 12:34:45.080664: Pseudo dice [0.8295] +2024-11-22 12:34:45.080755: Epoch time: 20.11 s +2024-11-22 12:34:46.517124: +2024-11-22 12:34:46.517331: Epoch 4750 +2024-11-22 12:34:46.517441: Current learning rate: 0.00445 +2024-11-22 12:35:05.929516: train_loss -0.7894 +2024-11-22 12:35:05.929728: val_loss -0.7368 +2024-11-22 12:35:05.929801: Pseudo dice [0.8122] +2024-11-22 12:35:05.929874: Epoch time: 19.41 s +2024-11-22 12:35:06.816683: +2024-11-22 12:35:06.816926: Epoch 4751 +2024-11-22 12:35:06.817049: Current learning rate: 0.00444 +2024-11-22 12:35:25.747061: train_loss -0.8009 +2024-11-22 12:35:25.747284: val_loss -0.7225 +2024-11-22 12:35:25.747389: Pseudo dice [0.8275] +2024-11-22 12:35:25.747501: Epoch time: 18.93 s +2024-11-22 12:35:26.651652: +2024-11-22 12:35:26.651855: Epoch 4752 +2024-11-22 12:35:26.653219: Current learning rate: 0.00444 +2024-11-22 12:35:46.257359: train_loss -0.796 +2024-11-22 12:35:46.257573: val_loss -0.7555 +2024-11-22 12:35:46.257645: Pseudo dice [0.8467] +2024-11-22 12:35:46.257720: Epoch time: 19.61 s +2024-11-22 12:35:47.153259: +2024-11-22 12:35:47.153474: Epoch 4753 +2024-11-22 12:35:47.153593: Current learning rate: 0.00444 +2024-11-22 12:36:05.767194: train_loss -0.7889 +2024-11-22 12:36:05.767465: val_loss -0.751 +2024-11-22 12:36:05.767540: Pseudo dice [0.8363] +2024-11-22 12:36:05.767624: Epoch time: 18.61 s +2024-11-22 12:36:06.974756: +2024-11-22 12:36:06.974989: Epoch 4754 +2024-11-22 12:36:06.975114: Current learning rate: 0.00444 +2024-11-22 12:36:25.982344: train_loss -0.7968 +2024-11-22 12:36:25.982563: val_loss -0.742 +2024-11-22 12:36:25.982640: Pseudo dice [0.864] +2024-11-22 12:36:25.982715: Epoch time: 19.01 s +2024-11-22 12:36:26.878288: +2024-11-22 12:36:26.878597: Epoch 4755 +2024-11-22 12:36:26.878714: Current learning rate: 0.00444 +2024-11-22 12:36:45.503508: train_loss -0.7943 +2024-11-22 12:36:45.503736: val_loss -0.7758 +2024-11-22 12:36:45.503811: Pseudo dice [0.8325] +2024-11-22 12:36:45.503888: Epoch time: 18.63 s +2024-11-22 12:36:46.546467: +2024-11-22 12:36:46.546690: Epoch 4756 +2024-11-22 12:36:46.546802: Current learning rate: 0.00444 +2024-11-22 12:37:06.131691: train_loss -0.8031 +2024-11-22 12:37:06.131917: val_loss -0.7495 +2024-11-22 12:37:06.132014: Pseudo dice [0.8266] +2024-11-22 12:37:06.132097: Epoch time: 19.59 s +2024-11-22 12:37:07.010766: +2024-11-22 12:37:07.011018: Epoch 4757 +2024-11-22 12:37:07.011144: Current learning rate: 0.00444 +2024-11-22 12:37:26.325330: train_loss -0.7815 +2024-11-22 12:37:26.325593: val_loss -0.7278 +2024-11-22 12:37:26.325704: Pseudo dice [0.8289] +2024-11-22 12:37:26.325797: Epoch time: 19.32 s +2024-11-22 12:37:27.220956: +2024-11-22 12:37:27.221197: Epoch 4758 +2024-11-22 12:37:27.221321: Current learning rate: 0.00444 +2024-11-22 12:37:45.465397: train_loss -0.7995 +2024-11-22 12:37:45.465629: val_loss -0.7425 +2024-11-22 12:37:45.465703: Pseudo dice [0.8506] +2024-11-22 12:37:45.465782: Epoch time: 18.25 s +2024-11-22 12:37:46.353379: +2024-11-22 12:37:46.353604: Epoch 4759 +2024-11-22 12:37:46.353722: Current learning rate: 0.00443 +2024-11-22 12:38:05.458269: train_loss -0.7849 +2024-11-22 12:38:05.458496: val_loss -0.7351 +2024-11-22 12:38:05.458571: Pseudo dice [0.8414] +2024-11-22 12:38:05.458656: Epoch time: 19.11 s +2024-11-22 12:38:06.346493: +2024-11-22 12:38:06.346709: Epoch 4760 +2024-11-22 12:38:06.346823: Current learning rate: 0.00443 +2024-11-22 12:38:25.339492: train_loss -0.7937 +2024-11-22 12:38:25.339795: val_loss -0.7386 +2024-11-22 12:38:25.339879: Pseudo dice [0.8101] +2024-11-22 12:38:25.339959: Epoch time: 18.99 s +2024-11-22 12:38:26.254051: +2024-11-22 12:38:26.254314: Epoch 4761 +2024-11-22 12:38:26.254432: Current learning rate: 0.00443 +2024-11-22 12:38:45.815891: train_loss -0.7828 +2024-11-22 12:38:45.816135: val_loss -0.7587 +2024-11-22 12:38:45.816222: Pseudo dice [0.8628] +2024-11-22 12:38:45.816311: Epoch time: 19.56 s +2024-11-22 12:38:46.704483: +2024-11-22 12:38:46.704691: Epoch 4762 +2024-11-22 12:38:46.704809: Current learning rate: 0.00443 +2024-11-22 12:39:04.236304: train_loss -0.7825 +2024-11-22 12:39:04.236526: val_loss -0.7399 +2024-11-22 12:39:04.236604: Pseudo dice [0.8442] +2024-11-22 12:39:04.236682: Epoch time: 17.53 s +2024-11-22 12:39:05.314643: +2024-11-22 12:39:05.314897: Epoch 4763 +2024-11-22 12:39:05.315024: Current learning rate: 0.00443 +2024-11-22 12:39:23.966686: train_loss -0.7988 +2024-11-22 12:39:23.966912: val_loss -0.7587 +2024-11-22 12:39:23.966986: Pseudo dice [0.8417] +2024-11-22 12:39:23.967073: Epoch time: 18.65 s +2024-11-22 12:39:24.851003: +2024-11-22 12:39:24.851228: Epoch 4764 +2024-11-22 12:39:24.851346: Current learning rate: 0.00443 +2024-11-22 12:39:42.825989: train_loss -0.7918 +2024-11-22 12:39:42.826230: val_loss -0.7696 +2024-11-22 12:39:42.826372: Pseudo dice [0.8218] +2024-11-22 12:39:42.826463: Epoch time: 17.98 s +2024-11-22 12:39:43.716511: +2024-11-22 12:39:43.716704: Epoch 4765 +2024-11-22 12:39:43.716820: Current learning rate: 0.00443 +2024-11-22 12:40:03.029949: train_loss -0.7945 +2024-11-22 12:40:03.030197: val_loss -0.75 +2024-11-22 12:40:03.030275: Pseudo dice [0.8403] +2024-11-22 12:40:03.030358: Epoch time: 19.31 s +2024-11-22 12:40:03.918085: +2024-11-22 12:40:03.918302: Epoch 4766 +2024-11-22 12:40:03.918414: Current learning rate: 0.00443 +2024-11-22 12:40:22.304348: train_loss -0.7957 +2024-11-22 12:40:22.304572: val_loss -0.7705 +2024-11-22 12:40:22.304651: Pseudo dice [0.8528] +2024-11-22 12:40:22.304729: Epoch time: 18.39 s +2024-11-22 12:40:23.199824: +2024-11-22 12:40:23.200039: Epoch 4767 +2024-11-22 12:40:23.200150: Current learning rate: 0.00442 +2024-11-22 12:40:42.129645: train_loss -0.7898 +2024-11-22 12:40:42.129867: val_loss -0.7654 +2024-11-22 12:40:42.129945: Pseudo dice [0.8464] +2024-11-22 12:40:42.130068: Epoch time: 18.93 s +2024-11-22 12:40:43.023609: +2024-11-22 12:40:43.023809: Epoch 4768 +2024-11-22 12:40:43.023922: Current learning rate: 0.00442 +2024-11-22 12:41:02.328084: train_loss -0.7915 +2024-11-22 12:41:02.328307: val_loss -0.7519 +2024-11-22 12:41:02.328383: Pseudo dice [0.8477] +2024-11-22 12:41:02.328462: Epoch time: 19.31 s +2024-11-22 12:41:03.615932: +2024-11-22 12:41:03.616183: Epoch 4769 +2024-11-22 12:41:03.616298: Current learning rate: 0.00442 +2024-11-22 12:41:22.411158: train_loss -0.7912 +2024-11-22 12:41:22.411395: val_loss -0.7504 +2024-11-22 12:41:22.411472: Pseudo dice [0.8497] +2024-11-22 12:41:22.416042: Epoch time: 18.8 s +2024-11-22 12:41:23.314075: +2024-11-22 12:41:23.314315: Epoch 4770 +2024-11-22 12:41:23.314427: Current learning rate: 0.00442 +2024-11-22 12:41:41.898618: train_loss -0.7883 +2024-11-22 12:41:41.898835: val_loss -0.755 +2024-11-22 12:41:41.898910: Pseudo dice [0.8276] +2024-11-22 12:41:41.898988: Epoch time: 18.59 s +2024-11-22 12:41:42.781005: +2024-11-22 12:41:42.781225: Epoch 4771 +2024-11-22 12:41:42.781334: Current learning rate: 0.00442 +2024-11-22 12:42:01.394156: train_loss -0.7799 +2024-11-22 12:42:01.394384: val_loss -0.7488 +2024-11-22 12:42:01.394464: Pseudo dice [0.8278] +2024-11-22 12:42:01.399726: Epoch time: 18.61 s +2024-11-22 12:42:02.401783: +2024-11-22 12:42:02.402029: Epoch 4772 +2024-11-22 12:42:02.402141: Current learning rate: 0.00442 +2024-11-22 12:42:21.701477: train_loss -0.7998 +2024-11-22 12:42:21.701739: val_loss -0.7468 +2024-11-22 12:42:21.701822: Pseudo dice [0.83] +2024-11-22 12:42:21.701948: Epoch time: 19.3 s +2024-11-22 12:42:22.611206: +2024-11-22 12:42:22.611437: Epoch 4773 +2024-11-22 12:42:22.611548: Current learning rate: 0.00442 +2024-11-22 12:42:40.556880: train_loss -0.8021 +2024-11-22 12:42:40.557170: val_loss -0.7509 +2024-11-22 12:42:40.557247: Pseudo dice [0.8521] +2024-11-22 12:42:40.557323: Epoch time: 17.95 s +2024-11-22 12:42:41.456595: +2024-11-22 12:42:41.456908: Epoch 4774 +2024-11-22 12:42:41.457031: Current learning rate: 0.00442 +2024-11-22 12:43:00.586464: train_loss -0.7924 +2024-11-22 12:43:00.586694: val_loss -0.7661 +2024-11-22 12:43:00.586769: Pseudo dice [0.8562] +2024-11-22 12:43:00.586847: Epoch time: 19.13 s +2024-11-22 12:43:01.485715: +2024-11-22 12:43:01.485999: Epoch 4775 +2024-11-22 12:43:01.486110: Current learning rate: 0.00441 +2024-11-22 12:43:20.076427: train_loss -0.7997 +2024-11-22 12:43:20.076641: val_loss -0.7635 +2024-11-22 12:43:20.076716: Pseudo dice [0.8679] +2024-11-22 12:43:20.076791: Epoch time: 18.59 s +2024-11-22 12:43:20.967446: +2024-11-22 12:43:20.967649: Epoch 4776 +2024-11-22 12:43:20.967766: Current learning rate: 0.00441 +2024-11-22 12:43:40.977212: train_loss -0.8038 +2024-11-22 12:43:40.982656: val_loss -0.7545 +2024-11-22 12:43:40.982817: Pseudo dice [0.8467] +2024-11-22 12:43:40.982907: Epoch time: 20.01 s +2024-11-22 12:43:41.877415: +2024-11-22 12:43:41.877670: Epoch 4777 +2024-11-22 12:43:41.877785: Current learning rate: 0.00441 +2024-11-22 12:44:00.819389: train_loss -0.7962 +2024-11-22 12:44:00.819619: val_loss -0.7601 +2024-11-22 12:44:00.819707: Pseudo dice [0.8456] +2024-11-22 12:44:00.819797: Epoch time: 18.94 s +2024-11-22 12:44:01.708110: +2024-11-22 12:44:01.708321: Epoch 4778 +2024-11-22 12:44:01.708433: Current learning rate: 0.00441 +2024-11-22 12:44:21.787373: train_loss -0.8014 +2024-11-22 12:44:21.787654: val_loss -0.7357 +2024-11-22 12:44:21.787730: Pseudo dice [0.8379] +2024-11-22 12:44:21.787808: Epoch time: 20.08 s +2024-11-22 12:44:22.675635: +2024-11-22 12:44:22.675831: Epoch 4779 +2024-11-22 12:44:22.675944: Current learning rate: 0.00441 +2024-11-22 12:44:41.748450: train_loss -0.8025 +2024-11-22 12:44:41.748671: val_loss -0.7548 +2024-11-22 12:44:41.748746: Pseudo dice [0.8336] +2024-11-22 12:44:41.748822: Epoch time: 19.07 s +2024-11-22 12:44:42.668842: +2024-11-22 12:44:42.669072: Epoch 4780 +2024-11-22 12:44:42.669184: Current learning rate: 0.00441 +2024-11-22 12:45:01.495020: train_loss -0.799 +2024-11-22 12:45:01.495265: val_loss -0.7369 +2024-11-22 12:45:01.495340: Pseudo dice [0.853] +2024-11-22 12:45:01.495421: Epoch time: 18.83 s +2024-11-22 12:45:02.790434: +2024-11-22 12:45:02.790735: Epoch 4781 +2024-11-22 12:45:02.790851: Current learning rate: 0.00441 +2024-11-22 12:45:21.335192: train_loss -0.7958 +2024-11-22 12:45:21.335423: val_loss -0.7147 +2024-11-22 12:45:21.335500: Pseudo dice [0.8369] +2024-11-22 12:45:21.335582: Epoch time: 18.55 s +2024-11-22 12:45:22.227601: +2024-11-22 12:45:22.227805: Epoch 4782 +2024-11-22 12:45:22.227916: Current learning rate: 0.00441 +2024-11-22 12:45:41.230715: train_loss -0.8015 +2024-11-22 12:45:41.230988: val_loss -0.7751 +2024-11-22 12:45:41.231069: Pseudo dice [0.854] +2024-11-22 12:45:41.231163: Epoch time: 19.0 s +2024-11-22 12:45:42.109314: +2024-11-22 12:45:42.109581: Epoch 4783 +2024-11-22 12:45:42.109693: Current learning rate: 0.0044 +2024-11-22 12:46:00.566136: train_loss -0.8045 +2024-11-22 12:46:00.566429: val_loss -0.7853 +2024-11-22 12:46:00.566508: Pseudo dice [0.8446] +2024-11-22 12:46:00.566597: Epoch time: 18.46 s +2024-11-22 12:46:01.455438: +2024-11-22 12:46:01.455652: Epoch 4784 +2024-11-22 12:46:01.455775: Current learning rate: 0.0044 +2024-11-22 12:46:20.568295: train_loss -0.7968 +2024-11-22 12:46:20.568518: val_loss -0.7375 +2024-11-22 12:46:20.568610: Pseudo dice [0.798] +2024-11-22 12:46:20.568690: Epoch time: 19.11 s +2024-11-22 12:46:21.474525: +2024-11-22 12:46:21.474727: Epoch 4785 +2024-11-22 12:46:21.474843: Current learning rate: 0.0044 +2024-11-22 12:46:40.341393: train_loss -0.7976 +2024-11-22 12:46:40.341615: val_loss -0.766 +2024-11-22 12:46:40.341751: Pseudo dice [0.8571] +2024-11-22 12:46:40.341829: Epoch time: 18.87 s +2024-11-22 12:46:41.230315: +2024-11-22 12:46:41.230549: Epoch 4786 +2024-11-22 12:46:41.230665: Current learning rate: 0.0044 +2024-11-22 12:46:59.895145: train_loss -0.7993 +2024-11-22 12:46:59.895379: val_loss -0.7706 +2024-11-22 12:46:59.895456: Pseudo dice [0.8316] +2024-11-22 12:46:59.895533: Epoch time: 18.67 s +2024-11-22 12:47:00.779487: +2024-11-22 12:47:00.779728: Epoch 4787 +2024-11-22 12:47:00.779857: Current learning rate: 0.0044 +2024-11-22 12:47:19.292123: train_loss -0.7983 +2024-11-22 12:47:19.292361: val_loss -0.7384 +2024-11-22 12:47:19.292446: Pseudo dice [0.8444] +2024-11-22 12:47:19.292532: Epoch time: 18.51 s +2024-11-22 12:47:20.173962: +2024-11-22 12:47:20.174265: Epoch 4788 +2024-11-22 12:47:20.174377: Current learning rate: 0.0044 +2024-11-22 12:47:39.167597: train_loss -0.7988 +2024-11-22 12:47:39.167850: val_loss -0.7421 +2024-11-22 12:47:39.167950: Pseudo dice [0.83] +2024-11-22 12:47:39.168043: Epoch time: 18.99 s +2024-11-22 12:47:40.057416: +2024-11-22 12:47:40.057604: Epoch 4789 +2024-11-22 12:47:40.057720: Current learning rate: 0.0044 +2024-11-22 12:47:59.447859: train_loss -0.7643 +2024-11-22 12:47:59.448093: val_loss -0.7564 +2024-11-22 12:47:59.448169: Pseudo dice [0.8525] +2024-11-22 12:47:59.448246: Epoch time: 19.39 s +2024-11-22 12:48:00.505085: +2024-11-22 12:48:00.505298: Epoch 4790 +2024-11-22 12:48:00.505410: Current learning rate: 0.0044 +2024-11-22 12:48:19.735857: train_loss -0.7699 +2024-11-22 12:48:19.736073: val_loss -0.7478 +2024-11-22 12:48:19.736151: Pseudo dice [0.81] +2024-11-22 12:48:19.736228: Epoch time: 19.23 s +2024-11-22 12:48:20.646831: +2024-11-22 12:48:20.647028: Epoch 4791 +2024-11-22 12:48:20.647164: Current learning rate: 0.00439 +2024-11-22 12:48:39.143212: train_loss -0.7919 +2024-11-22 12:48:39.143445: val_loss -0.7302 +2024-11-22 12:48:39.143521: Pseudo dice [0.8277] +2024-11-22 12:48:39.143599: Epoch time: 18.5 s +2024-11-22 12:48:40.070449: +2024-11-22 12:48:40.070647: Epoch 4792 +2024-11-22 12:48:40.070764: Current learning rate: 0.00439 +2024-11-22 12:48:59.106003: train_loss -0.7865 +2024-11-22 12:48:59.106241: val_loss -0.733 +2024-11-22 12:48:59.106318: Pseudo dice [0.8482] +2024-11-22 12:48:59.106438: Epoch time: 19.04 s +2024-11-22 12:49:00.399762: +2024-11-22 12:49:00.400015: Epoch 4793 +2024-11-22 12:49:00.400126: Current learning rate: 0.00439 +2024-11-22 12:49:19.349849: train_loss -0.7902 +2024-11-22 12:49:19.350096: val_loss -0.7461 +2024-11-22 12:49:19.350176: Pseudo dice [0.8482] +2024-11-22 12:49:19.350252: Epoch time: 18.95 s +2024-11-22 12:49:20.261158: +2024-11-22 12:49:20.261374: Epoch 4794 +2024-11-22 12:49:20.261486: Current learning rate: 0.00439 +2024-11-22 12:49:38.251130: train_loss -0.7785 +2024-11-22 12:49:38.251359: val_loss -0.7454 +2024-11-22 12:49:38.251432: Pseudo dice [0.8422] +2024-11-22 12:49:38.251509: Epoch time: 17.99 s +2024-11-22 12:49:39.135557: +2024-11-22 12:49:39.135859: Epoch 4795 +2024-11-22 12:49:39.135972: Current learning rate: 0.00439 +2024-11-22 12:49:58.302780: train_loss -0.7864 +2024-11-22 12:49:58.303041: val_loss -0.7618 +2024-11-22 12:49:58.303123: Pseudo dice [0.8482] +2024-11-22 12:49:58.303208: Epoch time: 19.17 s +2024-11-22 12:49:59.190288: +2024-11-22 12:49:59.190498: Epoch 4796 +2024-11-22 12:49:59.190607: Current learning rate: 0.00439 +2024-11-22 12:50:17.062003: train_loss -0.7966 +2024-11-22 12:50:17.062291: val_loss -0.7513 +2024-11-22 12:50:17.062370: Pseudo dice [0.8539] +2024-11-22 12:50:17.062451: Epoch time: 17.87 s +2024-11-22 12:50:17.945352: +2024-11-22 12:50:17.945580: Epoch 4797 +2024-11-22 12:50:17.945702: Current learning rate: 0.00439 +2024-11-22 12:50:36.273255: train_loss -0.804 +2024-11-22 12:50:36.273479: val_loss -0.7575 +2024-11-22 12:50:36.273552: Pseudo dice [0.8408] +2024-11-22 12:50:36.273629: Epoch time: 18.33 s +2024-11-22 12:50:37.188331: +2024-11-22 12:50:37.188554: Epoch 4798 +2024-11-22 12:50:37.188667: Current learning rate: 0.00439 +2024-11-22 12:50:55.669768: train_loss -0.7939 +2024-11-22 12:50:55.669981: val_loss -0.7301 +2024-11-22 12:50:55.670067: Pseudo dice [0.8274] +2024-11-22 12:50:55.670144: Epoch time: 18.48 s +2024-11-22 12:50:56.554549: +2024-11-22 12:50:56.554743: Epoch 4799 +2024-11-22 12:50:56.554871: Current learning rate: 0.00439 +2024-11-22 12:51:15.589854: train_loss -0.7944 +2024-11-22 12:51:15.590124: val_loss -0.7465 +2024-11-22 12:51:15.590213: Pseudo dice [0.8412] +2024-11-22 12:51:15.590297: Epoch time: 19.04 s +2024-11-22 12:51:16.774735: +2024-11-22 12:51:16.774954: Epoch 4800 +2024-11-22 12:51:16.775074: Current learning rate: 0.00438 +2024-11-22 12:51:35.545381: train_loss -0.7919 +2024-11-22 12:51:35.545594: val_loss -0.7294 +2024-11-22 12:51:35.545670: Pseudo dice [0.8306] +2024-11-22 12:51:35.550966: Epoch time: 18.77 s +2024-11-22 12:51:36.510566: +2024-11-22 12:51:36.510827: Epoch 4801 +2024-11-22 12:51:36.510938: Current learning rate: 0.00438 +2024-11-22 12:51:55.128157: train_loss -0.7998 +2024-11-22 12:51:55.128389: val_loss -0.7489 +2024-11-22 12:51:55.128464: Pseudo dice [0.8723] +2024-11-22 12:51:55.128546: Epoch time: 18.62 s +2024-11-22 12:51:56.054416: +2024-11-22 12:51:56.054626: Epoch 4802 +2024-11-22 12:51:56.054740: Current learning rate: 0.00438 +2024-11-22 12:52:14.994605: train_loss -0.7967 +2024-11-22 12:52:14.994823: val_loss -0.748 +2024-11-22 12:52:14.994905: Pseudo dice [0.8454] +2024-11-22 12:52:14.994986: Epoch time: 18.94 s +2024-11-22 12:52:15.980058: +2024-11-22 12:52:15.980294: Epoch 4803 +2024-11-22 12:52:15.980421: Current learning rate: 0.00438 +2024-11-22 12:52:35.210311: train_loss -0.7874 +2024-11-22 12:52:35.210557: val_loss -0.7614 +2024-11-22 12:52:35.210638: Pseudo dice [0.8174] +2024-11-22 12:52:35.210802: Epoch time: 19.23 s +2024-11-22 12:52:36.092930: +2024-11-22 12:52:36.093153: Epoch 4804 +2024-11-22 12:52:36.093262: Current learning rate: 0.00438 +2024-11-22 12:52:55.475796: train_loss -0.7926 +2024-11-22 12:52:55.476078: val_loss -0.741 +2024-11-22 12:52:55.476160: Pseudo dice [0.8308] +2024-11-22 12:52:55.476238: Epoch time: 19.38 s +2024-11-22 12:52:56.356234: +2024-11-22 12:52:56.356453: Epoch 4805 +2024-11-22 12:52:56.356568: Current learning rate: 0.00438 +2024-11-22 12:53:14.823154: train_loss -0.7983 +2024-11-22 12:53:14.823370: val_loss -0.7736 +2024-11-22 12:53:14.823444: Pseudo dice [0.8458] +2024-11-22 12:53:14.823520: Epoch time: 18.47 s +2024-11-22 12:53:15.704106: +2024-11-22 12:53:15.704349: Epoch 4806 +2024-11-22 12:53:15.704480: Current learning rate: 0.00438 +2024-11-22 12:53:33.706760: train_loss -0.7952 +2024-11-22 12:53:33.707068: val_loss -0.7092 +2024-11-22 12:53:33.707149: Pseudo dice [0.8285] +2024-11-22 12:53:33.707229: Epoch time: 18.0 s +2024-11-22 12:53:34.590659: +2024-11-22 12:53:34.590929: Epoch 4807 +2024-11-22 12:53:34.591049: Current learning rate: 0.00438 +2024-11-22 12:53:53.421355: train_loss -0.8058 +2024-11-22 12:53:53.421573: val_loss -0.7497 +2024-11-22 12:53:53.421647: Pseudo dice [0.847] +2024-11-22 12:53:53.421723: Epoch time: 18.83 s +2024-11-22 12:53:54.614856: +2024-11-22 12:53:54.615052: Epoch 4808 +2024-11-22 12:53:54.615167: Current learning rate: 0.00437 +2024-11-22 12:54:13.061638: train_loss -0.798 +2024-11-22 12:54:13.061860: val_loss -0.736 +2024-11-22 12:54:13.061937: Pseudo dice [0.8127] +2024-11-22 12:54:13.062026: Epoch time: 18.45 s +2024-11-22 12:54:13.957009: +2024-11-22 12:54:13.957236: Epoch 4809 +2024-11-22 12:54:13.957998: Current learning rate: 0.00437 +2024-11-22 12:54:32.032581: train_loss -0.7986 +2024-11-22 12:54:32.032821: val_loss -0.7782 +2024-11-22 12:54:32.032898: Pseudo dice [0.8353] +2024-11-22 12:54:32.032975: Epoch time: 18.08 s +2024-11-22 12:54:32.920394: +2024-11-22 12:54:32.920676: Epoch 4810 +2024-11-22 12:54:32.920786: Current learning rate: 0.00437 +2024-11-22 12:54:50.826533: train_loss -0.8003 +2024-11-22 12:54:50.826843: val_loss -0.7482 +2024-11-22 12:54:50.826922: Pseudo dice [0.8419] +2024-11-22 12:54:50.827014: Epoch time: 17.91 s +2024-11-22 12:54:51.717938: +2024-11-22 12:54:51.718140: Epoch 4811 +2024-11-22 12:54:51.718251: Current learning rate: 0.00437 +2024-11-22 12:55:10.831680: train_loss -0.7945 +2024-11-22 12:55:10.831907: val_loss -0.7176 +2024-11-22 12:55:10.831980: Pseudo dice [0.8222] +2024-11-22 12:55:10.832063: Epoch time: 19.11 s +2024-11-22 12:55:11.744818: +2024-11-22 12:55:11.745029: Epoch 4812 +2024-11-22 12:55:11.745147: Current learning rate: 0.00437 +2024-11-22 12:55:30.608344: train_loss -0.8016 +2024-11-22 12:55:30.608583: val_loss -0.7552 +2024-11-22 12:55:30.608658: Pseudo dice [0.8494] +2024-11-22 12:55:30.608737: Epoch time: 18.86 s +2024-11-22 12:55:31.548922: +2024-11-22 12:55:31.549120: Epoch 4813 +2024-11-22 12:55:31.549238: Current learning rate: 0.00437 +2024-11-22 12:55:51.176405: train_loss -0.7951 +2024-11-22 12:55:51.176615: val_loss -0.7764 +2024-11-22 12:55:51.176688: Pseudo dice [0.8586] +2024-11-22 12:55:51.176763: Epoch time: 19.63 s +2024-11-22 12:55:52.061575: +2024-11-22 12:55:52.061793: Epoch 4814 +2024-11-22 12:55:52.061903: Current learning rate: 0.00437 +2024-11-22 12:56:10.907064: train_loss -0.8053 +2024-11-22 12:56:10.907299: val_loss -0.7452 +2024-11-22 12:56:10.907417: Pseudo dice [0.844] +2024-11-22 12:56:10.907504: Epoch time: 18.85 s +2024-11-22 12:56:11.778628: +2024-11-22 12:56:11.778820: Epoch 4815 +2024-11-22 12:56:11.778937: Current learning rate: 0.00437 +2024-11-22 12:56:30.047068: train_loss -0.8032 +2024-11-22 12:56:30.047285: val_loss -0.7117 +2024-11-22 12:56:30.047359: Pseudo dice [0.8148] +2024-11-22 12:56:30.047493: Epoch time: 18.27 s +2024-11-22 12:56:31.346411: +2024-11-22 12:56:31.346663: Epoch 4816 +2024-11-22 12:56:31.346778: Current learning rate: 0.00436 +2024-11-22 12:56:50.434796: train_loss -0.7881 +2024-11-22 12:56:50.437741: val_loss -0.7695 +2024-11-22 12:56:50.437838: Pseudo dice [0.8491] +2024-11-22 12:56:50.437917: Epoch time: 19.09 s +2024-11-22 12:56:51.346538: +2024-11-22 12:56:51.346861: Epoch 4817 +2024-11-22 12:56:51.346979: Current learning rate: 0.00436 +2024-11-22 12:57:10.071188: train_loss -0.8025 +2024-11-22 12:57:10.071417: val_loss -0.7414 +2024-11-22 12:57:10.071496: Pseudo dice [0.8371] +2024-11-22 12:57:10.071576: Epoch time: 18.73 s +2024-11-22 12:57:10.979770: +2024-11-22 12:57:10.980003: Epoch 4818 +2024-11-22 12:57:10.980116: Current learning rate: 0.00436 +2024-11-22 12:57:30.532285: train_loss -0.8034 +2024-11-22 12:57:30.532533: val_loss -0.7475 +2024-11-22 12:57:30.532609: Pseudo dice [0.8441] +2024-11-22 12:57:30.532689: Epoch time: 19.55 s +2024-11-22 12:57:31.419341: +2024-11-22 12:57:31.419557: Epoch 4819 +2024-11-22 12:57:31.419670: Current learning rate: 0.00436 +2024-11-22 12:57:50.008317: train_loss -0.793 +2024-11-22 12:57:50.008556: val_loss -0.7419 +2024-11-22 12:57:50.008634: Pseudo dice [0.857] +2024-11-22 12:57:50.008712: Epoch time: 18.59 s +2024-11-22 12:57:51.069326: +2024-11-22 12:57:51.069524: Epoch 4820 +2024-11-22 12:57:51.069632: Current learning rate: 0.00436 +2024-11-22 12:58:09.918979: train_loss -0.8046 +2024-11-22 12:58:09.919980: val_loss -0.7716 +2024-11-22 12:58:09.920068: Pseudo dice [0.8555] +2024-11-22 12:58:09.920147: Epoch time: 18.85 s +2024-11-22 12:58:10.843595: +2024-11-22 12:58:10.843807: Epoch 4821 +2024-11-22 12:58:10.843920: Current learning rate: 0.00436 +2024-11-22 12:58:29.743853: train_loss -0.7991 +2024-11-22 12:58:29.744089: val_loss -0.7462 +2024-11-22 12:58:29.744167: Pseudo dice [0.8508] +2024-11-22 12:58:29.744250: Epoch time: 18.9 s +2024-11-22 12:58:30.832995: +2024-11-22 12:58:30.833210: Epoch 4822 +2024-11-22 12:58:30.833319: Current learning rate: 0.00436 +2024-11-22 12:58:49.716945: train_loss -0.8035 +2024-11-22 12:58:49.717252: val_loss -0.7557 +2024-11-22 12:58:49.717330: Pseudo dice [0.853] +2024-11-22 12:58:49.717410: Epoch time: 18.88 s +2024-11-22 12:58:50.600082: +2024-11-22 12:58:50.600285: Epoch 4823 +2024-11-22 12:58:50.600402: Current learning rate: 0.00436 +2024-11-22 12:59:08.709558: train_loss -0.7949 +2024-11-22 12:59:08.712276: val_loss -0.7326 +2024-11-22 12:59:08.712382: Pseudo dice [0.842] +2024-11-22 12:59:08.712464: Epoch time: 18.11 s +2024-11-22 12:59:09.589782: +2024-11-22 12:59:09.590020: Epoch 4824 +2024-11-22 12:59:09.590143: Current learning rate: 0.00435 +2024-11-22 12:59:28.885203: train_loss -0.7895 +2024-11-22 12:59:28.885423: val_loss -0.7357 +2024-11-22 12:59:28.885498: Pseudo dice [0.825] +2024-11-22 12:59:28.885576: Epoch time: 19.3 s +2024-11-22 12:59:29.764598: +2024-11-22 12:59:29.764807: Epoch 4825 +2024-11-22 12:59:29.764920: Current learning rate: 0.00435 +2024-11-22 12:59:48.695266: train_loss -0.8019 +2024-11-22 12:59:48.695487: val_loss -0.752 +2024-11-22 12:59:48.695567: Pseudo dice [0.8438] +2024-11-22 12:59:48.695651: Epoch time: 18.93 s +2024-11-22 12:59:49.601288: +2024-11-22 12:59:49.601482: Epoch 4826 +2024-11-22 12:59:49.601587: Current learning rate: 0.00435 +2024-11-22 13:00:08.280354: train_loss -0.8038 +2024-11-22 13:00:08.280617: val_loss -0.7562 +2024-11-22 13:00:08.280694: Pseudo dice [0.8463] +2024-11-22 13:00:08.285911: Epoch time: 18.68 s +2024-11-22 13:00:09.361078: +2024-11-22 13:00:09.361299: Epoch 4827 +2024-11-22 13:00:09.361416: Current learning rate: 0.00435 +2024-11-22 13:00:28.814767: train_loss -0.8 +2024-11-22 13:00:28.814986: val_loss -0.7542 +2024-11-22 13:00:28.815086: Pseudo dice [0.8506] +2024-11-22 13:00:28.815164: Epoch time: 19.45 s +2024-11-22 13:00:30.096690: +2024-11-22 13:00:30.096925: Epoch 4828 +2024-11-22 13:00:30.097046: Current learning rate: 0.00435 +2024-11-22 13:00:48.205020: train_loss -0.8015 +2024-11-22 13:00:48.205235: val_loss -0.7594 +2024-11-22 13:00:48.205314: Pseudo dice [0.858] +2024-11-22 13:00:48.205386: Epoch time: 18.11 s +2024-11-22 13:00:49.080855: +2024-11-22 13:00:49.081074: Epoch 4829 +2024-11-22 13:00:49.081187: Current learning rate: 0.00435 +2024-11-22 13:01:08.903730: train_loss -0.7914 +2024-11-22 13:01:08.903971: val_loss -0.7176 +2024-11-22 13:01:08.904055: Pseudo dice [0.8351] +2024-11-22 13:01:08.904148: Epoch time: 19.82 s +2024-11-22 13:01:09.787599: +2024-11-22 13:01:09.787836: Epoch 4830 +2024-11-22 13:01:09.787952: Current learning rate: 0.00435 +2024-11-22 13:01:28.443936: train_loss -0.7895 +2024-11-22 13:01:28.444166: val_loss -0.7524 +2024-11-22 13:01:28.444242: Pseudo dice [0.8217] +2024-11-22 13:01:28.444319: Epoch time: 18.66 s +2024-11-22 13:01:29.426097: +2024-11-22 13:01:29.426335: Epoch 4831 +2024-11-22 13:01:29.426444: Current learning rate: 0.00435 +2024-11-22 13:01:48.483273: train_loss -0.7919 +2024-11-22 13:01:48.483552: val_loss -0.7669 +2024-11-22 13:01:48.483633: Pseudo dice [0.8466] +2024-11-22 13:01:48.483709: Epoch time: 19.06 s +2024-11-22 13:01:49.372534: +2024-11-22 13:01:49.372785: Epoch 4832 +2024-11-22 13:01:49.372905: Current learning rate: 0.00434 +2024-11-22 13:02:08.003055: train_loss -0.7895 +2024-11-22 13:02:08.003274: val_loss -0.745 +2024-11-22 13:02:08.003345: Pseudo dice [0.8566] +2024-11-22 13:02:08.003422: Epoch time: 18.63 s +2024-11-22 13:02:08.907897: +2024-11-22 13:02:08.908114: Epoch 4833 +2024-11-22 13:02:08.908233: Current learning rate: 0.00434 +2024-11-22 13:02:28.113088: train_loss -0.7998 +2024-11-22 13:02:28.113354: val_loss -0.7549 +2024-11-22 13:02:28.113431: Pseudo dice [0.8606] +2024-11-22 13:02:28.113514: Epoch time: 19.21 s +2024-11-22 13:02:29.174166: +2024-11-22 13:02:29.174356: Epoch 4834 +2024-11-22 13:02:29.174467: Current learning rate: 0.00434 +2024-11-22 13:02:47.132975: train_loss -0.7997 +2024-11-22 13:02:47.133204: val_loss -0.7353 +2024-11-22 13:02:47.133279: Pseudo dice [0.8202] +2024-11-22 13:02:47.133356: Epoch time: 17.96 s +2024-11-22 13:02:48.015171: +2024-11-22 13:02:48.015375: Epoch 4835 +2024-11-22 13:02:48.015726: Current learning rate: 0.00434 +2024-11-22 13:03:05.773760: train_loss -0.8033 +2024-11-22 13:03:05.773975: val_loss -0.7437 +2024-11-22 13:03:05.774064: Pseudo dice [0.8536] +2024-11-22 13:03:05.774143: Epoch time: 17.76 s +2024-11-22 13:03:06.664764: +2024-11-22 13:03:06.664974: Epoch 4836 +2024-11-22 13:03:06.665091: Current learning rate: 0.00434 +2024-11-22 13:03:26.070302: train_loss -0.7946 +2024-11-22 13:03:26.070529: val_loss -0.7372 +2024-11-22 13:03:26.070607: Pseudo dice [0.8365] +2024-11-22 13:03:26.070688: Epoch time: 19.41 s +2024-11-22 13:03:26.959200: +2024-11-22 13:03:26.959419: Epoch 4837 +2024-11-22 13:03:26.959534: Current learning rate: 0.00434 +2024-11-22 13:03:45.826099: train_loss -0.7927 +2024-11-22 13:03:45.826352: val_loss -0.7456 +2024-11-22 13:03:45.826483: Pseudo dice [0.8736] +2024-11-22 13:03:45.826568: Epoch time: 18.87 s +2024-11-22 13:03:46.717868: +2024-11-22 13:03:46.718075: Epoch 4838 +2024-11-22 13:03:46.718186: Current learning rate: 0.00434 +2024-11-22 13:04:05.229378: train_loss -0.799 +2024-11-22 13:04:05.229599: val_loss -0.7493 +2024-11-22 13:04:05.229676: Pseudo dice [0.8377] +2024-11-22 13:04:05.229756: Epoch time: 18.51 s +2024-11-22 13:04:06.218040: +2024-11-22 13:04:06.218257: Epoch 4839 +2024-11-22 13:04:06.218364: Current learning rate: 0.00434 +2024-11-22 13:04:25.728803: train_loss -0.8014 +2024-11-22 13:04:25.729028: val_loss -0.7709 +2024-11-22 13:04:25.729107: Pseudo dice [0.8613] +2024-11-22 13:04:25.729187: Epoch time: 19.51 s +2024-11-22 13:04:27.011686: +2024-11-22 13:04:27.011908: Epoch 4840 +2024-11-22 13:04:27.012026: Current learning rate: 0.00433 +2024-11-22 13:04:45.562335: train_loss -0.8017 +2024-11-22 13:04:45.562584: val_loss -0.762 +2024-11-22 13:04:45.562732: Pseudo dice [0.8655] +2024-11-22 13:04:45.562819: Epoch time: 18.55 s +2024-11-22 13:04:46.446907: +2024-11-22 13:04:46.447128: Epoch 4841 +2024-11-22 13:04:46.447239: Current learning rate: 0.00433 +2024-11-22 13:05:06.236206: train_loss -0.8013 +2024-11-22 13:05:06.236425: val_loss -0.7771 +2024-11-22 13:05:06.236524: Pseudo dice [0.8481] +2024-11-22 13:05:06.236600: Epoch time: 19.79 s +2024-11-22 13:05:07.119320: +2024-11-22 13:05:07.119601: Epoch 4842 +2024-11-22 13:05:07.119713: Current learning rate: 0.00433 +2024-11-22 13:05:24.804172: train_loss -0.8014 +2024-11-22 13:05:24.804381: val_loss -0.7244 +2024-11-22 13:05:24.804457: Pseudo dice [0.8485] +2024-11-22 13:05:24.804531: Epoch time: 17.69 s +2024-11-22 13:05:25.674429: +2024-11-22 13:05:25.674635: Epoch 4843 +2024-11-22 13:05:25.674746: Current learning rate: 0.00433 +2024-11-22 13:05:45.471067: train_loss -0.7979 +2024-11-22 13:05:45.471292: val_loss -0.7316 +2024-11-22 13:05:45.471372: Pseudo dice [0.8339] +2024-11-22 13:05:45.471453: Epoch time: 19.8 s +2024-11-22 13:05:46.491208: +2024-11-22 13:05:46.491424: Epoch 4844 +2024-11-22 13:05:46.491534: Current learning rate: 0.00433 +2024-11-22 13:06:06.003731: train_loss -0.7978 +2024-11-22 13:06:06.003977: val_loss -0.7357 +2024-11-22 13:06:06.004064: Pseudo dice [0.8591] +2024-11-22 13:06:06.004143: Epoch time: 19.51 s +2024-11-22 13:06:06.888659: +2024-11-22 13:06:06.888873: Epoch 4845 +2024-11-22 13:06:06.888985: Current learning rate: 0.00433 +2024-11-22 13:06:25.504688: train_loss -0.806 +2024-11-22 13:06:25.504908: val_loss -0.7226 +2024-11-22 13:06:25.504982: Pseudo dice [0.8607] +2024-11-22 13:06:25.505065: Epoch time: 18.62 s +2024-11-22 13:06:26.449349: +2024-11-22 13:06:26.449635: Epoch 4846 +2024-11-22 13:06:26.449749: Current learning rate: 0.00433 +2024-11-22 13:06:45.368922: train_loss -0.7915 +2024-11-22 13:06:45.369153: val_loss -0.7368 +2024-11-22 13:06:45.369227: Pseudo dice [0.8361] +2024-11-22 13:06:45.369304: Epoch time: 18.92 s +2024-11-22 13:06:46.355311: +2024-11-22 13:06:46.355509: Epoch 4847 +2024-11-22 13:06:46.355623: Current learning rate: 0.00433 +2024-11-22 13:07:05.981747: train_loss -0.7935 +2024-11-22 13:07:05.982006: val_loss -0.7702 +2024-11-22 13:07:05.982081: Pseudo dice [0.8421] +2024-11-22 13:07:05.982183: Epoch time: 19.63 s +2024-11-22 13:07:06.866089: +2024-11-22 13:07:06.866289: Epoch 4848 +2024-11-22 13:07:06.866401: Current learning rate: 0.00432 +2024-11-22 13:07:25.457330: train_loss -0.7892 +2024-11-22 13:07:25.457556: val_loss -0.7663 +2024-11-22 13:07:25.457631: Pseudo dice [0.838] +2024-11-22 13:07:25.457708: Epoch time: 18.59 s +2024-11-22 13:07:26.423415: +2024-11-22 13:07:26.423743: Epoch 4849 +2024-11-22 13:07:26.423856: Current learning rate: 0.00432 +2024-11-22 13:07:45.546594: train_loss -0.7919 +2024-11-22 13:07:45.546824: val_loss -0.7371 +2024-11-22 13:07:45.546914: Pseudo dice [0.8251] +2024-11-22 13:07:45.547000: Epoch time: 19.12 s +2024-11-22 13:07:46.770474: +2024-11-22 13:07:46.770708: Epoch 4850 +2024-11-22 13:07:46.770822: Current learning rate: 0.00432 +2024-11-22 13:08:04.009050: train_loss -0.8006 +2024-11-22 13:08:04.011474: val_loss -0.7431 +2024-11-22 13:08:04.011613: Pseudo dice [0.8537] +2024-11-22 13:08:04.011706: Epoch time: 17.24 s +2024-11-22 13:08:04.941514: +2024-11-22 13:08:04.941751: Epoch 4851 +2024-11-22 13:08:04.941876: Current learning rate: 0.00432 +2024-11-22 13:08:23.939033: train_loss -0.7936 +2024-11-22 13:08:23.939336: val_loss -0.7426 +2024-11-22 13:08:23.939417: Pseudo dice [0.8393] +2024-11-22 13:08:23.939500: Epoch time: 19.0 s +2024-11-22 13:08:24.824071: +2024-11-22 13:08:24.824276: Epoch 4852 +2024-11-22 13:08:24.824392: Current learning rate: 0.00432 +2024-11-22 13:08:44.182948: train_loss -0.7973 +2024-11-22 13:08:44.185376: val_loss -0.7557 +2024-11-22 13:08:44.185472: Pseudo dice [0.8413] +2024-11-22 13:08:44.185551: Epoch time: 19.36 s +2024-11-22 13:08:45.078863: +2024-11-22 13:08:45.079077: Epoch 4853 +2024-11-22 13:08:45.079193: Current learning rate: 0.00432 +2024-11-22 13:09:03.569506: train_loss -0.8042 +2024-11-22 13:09:03.569731: val_loss -0.75 +2024-11-22 13:09:03.569807: Pseudo dice [0.8385] +2024-11-22 13:09:03.571479: Epoch time: 18.49 s +2024-11-22 13:09:04.457099: +2024-11-22 13:09:04.457327: Epoch 4854 +2024-11-22 13:09:04.457442: Current learning rate: 0.00432 +2024-11-22 13:09:23.094936: train_loss -0.7985 +2024-11-22 13:09:23.095198: val_loss -0.7435 +2024-11-22 13:09:23.095274: Pseudo dice [0.8684] +2024-11-22 13:09:23.095361: Epoch time: 18.64 s +2024-11-22 13:09:23.976949: +2024-11-22 13:09:23.977163: Epoch 4855 +2024-11-22 13:09:23.977274: Current learning rate: 0.00432 +2024-11-22 13:09:41.811652: train_loss -0.7972 +2024-11-22 13:09:41.811877: val_loss -0.7706 +2024-11-22 13:09:41.811949: Pseudo dice [0.8529] +2024-11-22 13:09:41.812028: Epoch time: 17.84 s +2024-11-22 13:09:42.685209: +2024-11-22 13:09:42.685420: Epoch 4856 +2024-11-22 13:09:42.685528: Current learning rate: 0.00431 +2024-11-22 13:10:00.566174: train_loss -0.8093 +2024-11-22 13:10:00.566384: val_loss -0.7435 +2024-11-22 13:10:00.566457: Pseudo dice [0.8473] +2024-11-22 13:10:00.566530: Epoch time: 17.88 s +2024-11-22 13:10:01.617629: +2024-11-22 13:10:01.617838: Epoch 4857 +2024-11-22 13:10:01.617947: Current learning rate: 0.00431 +2024-11-22 13:10:21.950477: train_loss -0.7897 +2024-11-22 13:10:21.950698: val_loss -0.7734 +2024-11-22 13:10:21.950776: Pseudo dice [0.8484] +2024-11-22 13:10:21.950875: Epoch time: 20.33 s +2024-11-22 13:10:22.818996: +2024-11-22 13:10:22.819206: Epoch 4858 +2024-11-22 13:10:22.819319: Current learning rate: 0.00431 +2024-11-22 13:10:41.751007: train_loss -0.8019 +2024-11-22 13:10:41.751222: val_loss -0.7397 +2024-11-22 13:10:41.751300: Pseudo dice [0.8642] +2024-11-22 13:10:41.751379: Epoch time: 18.93 s +2024-11-22 13:10:42.722531: +2024-11-22 13:10:42.722732: Epoch 4859 +2024-11-22 13:10:42.722843: Current learning rate: 0.00431 +2024-11-22 13:11:02.278454: train_loss -0.7946 +2024-11-22 13:11:02.279514: val_loss -0.7717 +2024-11-22 13:11:02.279598: Pseudo dice [0.8533] +2024-11-22 13:11:02.279681: Epoch time: 19.56 s +2024-11-22 13:11:03.169215: +2024-11-22 13:11:03.169427: Epoch 4860 +2024-11-22 13:11:03.169540: Current learning rate: 0.00431 +2024-11-22 13:11:21.808026: train_loss -0.797 +2024-11-22 13:11:21.808250: val_loss -0.743 +2024-11-22 13:11:21.808332: Pseudo dice [0.8316] +2024-11-22 13:11:21.808418: Epoch time: 18.64 s +2024-11-22 13:11:22.683817: +2024-11-22 13:11:22.684032: Epoch 4861 +2024-11-22 13:11:22.684321: Current learning rate: 0.00431 +2024-11-22 13:11:40.898722: train_loss -0.7927 +2024-11-22 13:11:40.898937: val_loss -0.757 +2024-11-22 13:11:40.899083: Pseudo dice [0.8235] +2024-11-22 13:11:40.899159: Epoch time: 18.22 s +2024-11-22 13:11:41.763730: +2024-11-22 13:11:41.763965: Epoch 4862 +2024-11-22 13:11:41.764083: Current learning rate: 0.00431 +2024-11-22 13:12:00.653662: train_loss -0.797 +2024-11-22 13:12:00.653889: val_loss -0.7506 +2024-11-22 13:12:00.653969: Pseudo dice [0.8459] +2024-11-22 13:12:00.654059: Epoch time: 18.89 s +2024-11-22 13:12:01.979828: +2024-11-22 13:12:01.980132: Epoch 4863 +2024-11-22 13:12:01.980248: Current learning rate: 0.00431 +2024-11-22 13:12:21.917402: train_loss -0.8102 +2024-11-22 13:12:21.918196: val_loss -0.7199 +2024-11-22 13:12:21.918279: Pseudo dice [0.8468] +2024-11-22 13:12:21.918364: Epoch time: 19.94 s +2024-11-22 13:12:22.798523: +2024-11-22 13:12:22.798738: Epoch 4864 +2024-11-22 13:12:22.798847: Current learning rate: 0.0043 +2024-11-22 13:12:41.239528: train_loss -0.795 +2024-11-22 13:12:41.239789: val_loss -0.736 +2024-11-22 13:12:41.239873: Pseudo dice [0.8427] +2024-11-22 13:12:41.239961: Epoch time: 18.44 s +2024-11-22 13:12:42.125095: +2024-11-22 13:12:42.125378: Epoch 4865 +2024-11-22 13:12:42.125490: Current learning rate: 0.0043 +2024-11-22 13:13:00.868204: train_loss -0.7993 +2024-11-22 13:13:00.868443: val_loss -0.7551 +2024-11-22 13:13:00.868522: Pseudo dice [0.8553] +2024-11-22 13:13:00.868600: Epoch time: 18.74 s +2024-11-22 13:13:01.892036: +2024-11-22 13:13:01.892343: Epoch 4866 +2024-11-22 13:13:01.892461: Current learning rate: 0.0043 +2024-11-22 13:13:20.615375: train_loss -0.8005 +2024-11-22 13:13:20.615657: val_loss -0.7363 +2024-11-22 13:13:20.615735: Pseudo dice [0.8247] +2024-11-22 13:13:20.615818: Epoch time: 18.72 s +2024-11-22 13:13:21.504140: +2024-11-22 13:13:21.504364: Epoch 4867 +2024-11-22 13:13:21.504478: Current learning rate: 0.0043 +2024-11-22 13:13:39.874401: train_loss -0.8034 +2024-11-22 13:13:39.874612: val_loss -0.7675 +2024-11-22 13:13:39.874688: Pseudo dice [0.8572] +2024-11-22 13:13:39.874765: Epoch time: 18.37 s +2024-11-22 13:13:40.859234: +2024-11-22 13:13:40.859452: Epoch 4868 +2024-11-22 13:13:40.859563: Current learning rate: 0.0043 +2024-11-22 13:13:58.630776: train_loss -0.8072 +2024-11-22 13:13:58.631000: val_loss -0.7749 +2024-11-22 13:13:58.631078: Pseudo dice [0.8342] +2024-11-22 13:13:58.631155: Epoch time: 17.77 s +2024-11-22 13:13:59.601069: +2024-11-22 13:13:59.601282: Epoch 4869 +2024-11-22 13:13:59.601397: Current learning rate: 0.0043 +2024-11-22 13:14:18.347202: train_loss -0.8043 +2024-11-22 13:14:18.347429: val_loss -0.7769 +2024-11-22 13:14:18.347518: Pseudo dice [0.8586] +2024-11-22 13:14:18.347602: Epoch time: 18.75 s +2024-11-22 13:14:19.231882: +2024-11-22 13:14:19.232105: Epoch 4870 +2024-11-22 13:14:19.232227: Current learning rate: 0.0043 +2024-11-22 13:14:37.564113: train_loss -0.7957 +2024-11-22 13:14:37.564351: val_loss -0.7537 +2024-11-22 13:14:37.564431: Pseudo dice [0.8583] +2024-11-22 13:14:37.564513: Epoch time: 18.33 s +2024-11-22 13:14:38.452378: +2024-11-22 13:14:38.452576: Epoch 4871 +2024-11-22 13:14:38.452687: Current learning rate: 0.0043 +2024-11-22 13:14:57.594385: train_loss -0.7975 +2024-11-22 13:14:57.594609: val_loss -0.7546 +2024-11-22 13:14:57.594684: Pseudo dice [0.8636] +2024-11-22 13:14:57.594760: Epoch time: 19.14 s +2024-11-22 13:14:58.481094: +2024-11-22 13:14:58.481297: Epoch 4872 +2024-11-22 13:14:58.481408: Current learning rate: 0.00429 +2024-11-22 13:15:17.633293: train_loss -0.7985 +2024-11-22 13:15:17.633528: val_loss -0.7365 +2024-11-22 13:15:17.633608: Pseudo dice [0.8654] +2024-11-22 13:15:17.633686: Epoch time: 19.15 s +2024-11-22 13:15:18.518648: +2024-11-22 13:15:18.518858: Epoch 4873 +2024-11-22 13:15:18.518975: Current learning rate: 0.00429 +2024-11-22 13:15:38.407784: train_loss -0.7994 +2024-11-22 13:15:38.408020: val_loss -0.7528 +2024-11-22 13:15:38.408169: Pseudo dice [0.8517] +2024-11-22 13:15:38.408255: Epoch time: 19.89 s +2024-11-22 13:15:39.292730: +2024-11-22 13:15:39.292933: Epoch 4874 +2024-11-22 13:15:39.293061: Current learning rate: 0.00429 +2024-11-22 13:15:57.959496: train_loss -0.7983 +2024-11-22 13:15:57.959783: val_loss -0.7572 +2024-11-22 13:15:57.959864: Pseudo dice [0.8576] +2024-11-22 13:15:57.959948: Epoch time: 18.67 s +2024-11-22 13:15:59.240901: +2024-11-22 13:15:59.241153: Epoch 4875 +2024-11-22 13:15:59.241271: Current learning rate: 0.00429 +2024-11-22 13:16:17.791078: train_loss -0.8047 +2024-11-22 13:16:17.791296: val_loss -0.7314 +2024-11-22 13:16:17.791371: Pseudo dice [0.8261] +2024-11-22 13:16:17.791449: Epoch time: 18.55 s +2024-11-22 13:16:18.671260: +2024-11-22 13:16:18.671500: Epoch 4876 +2024-11-22 13:16:18.671611: Current learning rate: 0.00429 +2024-11-22 13:16:37.636423: train_loss -0.8 +2024-11-22 13:16:37.636648: val_loss -0.7503 +2024-11-22 13:16:37.636727: Pseudo dice [0.8382] +2024-11-22 13:16:37.636804: Epoch time: 18.97 s +2024-11-22 13:16:38.601649: +2024-11-22 13:16:38.601871: Epoch 4877 +2024-11-22 13:16:38.601982: Current learning rate: 0.00429 +2024-11-22 13:16:58.329824: train_loss -0.7923 +2024-11-22 13:16:58.330668: val_loss -0.7383 +2024-11-22 13:16:58.330779: Pseudo dice [0.8405] +2024-11-22 13:16:58.330868: Epoch time: 19.73 s +2024-11-22 13:16:59.217985: +2024-11-22 13:16:59.218205: Epoch 4878 +2024-11-22 13:16:59.218320: Current learning rate: 0.00429 +2024-11-22 13:17:18.288699: train_loss -0.7969 +2024-11-22 13:17:18.288920: val_loss -0.7623 +2024-11-22 13:17:18.289078: Pseudo dice [0.8589] +2024-11-22 13:17:18.289155: Epoch time: 19.07 s +2024-11-22 13:17:19.178940: +2024-11-22 13:17:19.179148: Epoch 4879 +2024-11-22 13:17:19.179262: Current learning rate: 0.00429 +2024-11-22 13:17:37.165020: train_loss -0.7996 +2024-11-22 13:17:37.165240: val_loss -0.7764 +2024-11-22 13:17:37.165315: Pseudo dice [0.8455] +2024-11-22 13:17:37.165390: Epoch time: 17.99 s +2024-11-22 13:17:38.051571: +2024-11-22 13:17:38.051806: Epoch 4880 +2024-11-22 13:17:38.051920: Current learning rate: 0.00429 +2024-11-22 13:17:55.872597: train_loss -0.8004 +2024-11-22 13:17:55.872812: val_loss -0.7797 +2024-11-22 13:17:55.872914: Pseudo dice [0.8433] +2024-11-22 13:17:55.873017: Epoch time: 17.82 s +2024-11-22 13:17:56.764439: +2024-11-22 13:17:56.764718: Epoch 4881 +2024-11-22 13:17:56.764836: Current learning rate: 0.00428 +2024-11-22 13:18:15.901288: train_loss -0.7983 +2024-11-22 13:18:15.901510: val_loss -0.7524 +2024-11-22 13:18:15.901605: Pseudo dice [0.8434] +2024-11-22 13:18:15.901692: Epoch time: 19.14 s +2024-11-22 13:18:16.800437: +2024-11-22 13:18:16.800686: Epoch 4882 +2024-11-22 13:18:16.800801: Current learning rate: 0.00428 +2024-11-22 13:18:36.312861: train_loss -0.7915 +2024-11-22 13:18:36.313111: val_loss -0.7781 +2024-11-22 13:18:36.313196: Pseudo dice [0.8767] +2024-11-22 13:18:36.313280: Epoch time: 19.51 s +2024-11-22 13:18:37.238065: +2024-11-22 13:18:37.238286: Epoch 4883 +2024-11-22 13:18:37.238398: Current learning rate: 0.00428 +2024-11-22 13:18:56.587519: train_loss -0.7893 +2024-11-22 13:18:56.587741: val_loss -0.7576 +2024-11-22 13:18:56.587814: Pseudo dice [0.8431] +2024-11-22 13:18:56.587888: Epoch time: 19.35 s +2024-11-22 13:18:57.677837: +2024-11-22 13:18:57.678059: Epoch 4884 +2024-11-22 13:18:57.678175: Current learning rate: 0.00428 +2024-11-22 13:19:16.772859: train_loss -0.7943 +2024-11-22 13:19:16.773150: val_loss -0.7355 +2024-11-22 13:19:16.773248: Pseudo dice [0.8289] +2024-11-22 13:19:16.773330: Epoch time: 19.1 s +2024-11-22 13:19:17.660551: +2024-11-22 13:19:17.660750: Epoch 4885 +2024-11-22 13:19:17.660870: Current learning rate: 0.00428 +2024-11-22 13:19:37.057105: train_loss -0.7948 +2024-11-22 13:19:37.058017: val_loss -0.7363 +2024-11-22 13:19:37.058111: Pseudo dice [0.8477] +2024-11-22 13:19:37.058195: Epoch time: 19.4 s +2024-11-22 13:19:37.941680: +2024-11-22 13:19:37.941884: Epoch 4886 +2024-11-22 13:19:37.942004: Current learning rate: 0.00428 +2024-11-22 13:19:56.411124: train_loss -0.787 +2024-11-22 13:19:56.411371: val_loss -0.7487 +2024-11-22 13:19:56.411443: Pseudo dice [0.8418] +2024-11-22 13:19:56.411522: Epoch time: 18.47 s +2024-11-22 13:19:57.728823: +2024-11-22 13:19:57.729105: Epoch 4887 +2024-11-22 13:19:57.729227: Current learning rate: 0.00428 +2024-11-22 13:20:17.542009: train_loss -0.7876 +2024-11-22 13:20:17.543743: val_loss -0.7042 +2024-11-22 13:20:17.543837: Pseudo dice [0.8218] +2024-11-22 13:20:17.543916: Epoch time: 19.81 s +2024-11-22 13:20:18.449505: +2024-11-22 13:20:18.449720: Epoch 4888 +2024-11-22 13:20:18.449833: Current learning rate: 0.00428 +2024-11-22 13:20:36.914739: train_loss -0.7924 +2024-11-22 13:20:36.914954: val_loss -0.7534 +2024-11-22 13:20:36.915060: Pseudo dice [0.8013] +2024-11-22 13:20:36.915141: Epoch time: 18.47 s +2024-11-22 13:20:37.805638: +2024-11-22 13:20:37.805867: Epoch 4889 +2024-11-22 13:20:37.805983: Current learning rate: 0.00427 +2024-11-22 13:20:57.487348: train_loss -0.7884 +2024-11-22 13:20:57.487606: val_loss -0.7638 +2024-11-22 13:20:57.487682: Pseudo dice [0.8369] +2024-11-22 13:20:57.487771: Epoch time: 19.68 s +2024-11-22 13:20:58.520340: +2024-11-22 13:20:58.520589: Epoch 4890 +2024-11-22 13:20:58.520713: Current learning rate: 0.00427 +2024-11-22 13:21:16.993962: train_loss -0.8002 +2024-11-22 13:21:16.994192: val_loss -0.7635 +2024-11-22 13:21:16.994268: Pseudo dice [0.8559] +2024-11-22 13:21:16.994346: Epoch time: 18.47 s +2024-11-22 13:21:17.889699: +2024-11-22 13:21:17.889941: Epoch 4891 +2024-11-22 13:21:17.890069: Current learning rate: 0.00427 +2024-11-22 13:21:35.842027: train_loss -0.7935 +2024-11-22 13:21:35.842244: val_loss -0.7493 +2024-11-22 13:21:35.842322: Pseudo dice [0.8455] +2024-11-22 13:21:35.842397: Epoch time: 17.95 s +2024-11-22 13:21:36.733696: +2024-11-22 13:21:36.733964: Epoch 4892 +2024-11-22 13:21:36.734082: Current learning rate: 0.00427 +2024-11-22 13:21:55.711622: train_loss -0.7928 +2024-11-22 13:21:55.711842: val_loss -0.7799 +2024-11-22 13:21:55.717098: Pseudo dice [0.8619] +2024-11-22 13:21:55.717271: Epoch time: 18.98 s +2024-11-22 13:21:56.786185: +2024-11-22 13:21:56.786399: Epoch 4893 +2024-11-22 13:21:56.786514: Current learning rate: 0.00427 +2024-11-22 13:22:15.684015: train_loss -0.7978 +2024-11-22 13:22:15.684272: val_loss -0.7586 +2024-11-22 13:22:15.684386: Pseudo dice [0.8703] +2024-11-22 13:22:15.684489: Epoch time: 18.9 s +2024-11-22 13:22:16.589984: +2024-11-22 13:22:16.590191: Epoch 4894 +2024-11-22 13:22:16.590304: Current learning rate: 0.00427 +2024-11-22 13:22:34.760378: train_loss -0.7968 +2024-11-22 13:22:34.760604: val_loss -0.7437 +2024-11-22 13:22:34.760678: Pseudo dice [0.841] +2024-11-22 13:22:34.760754: Epoch time: 18.17 s +2024-11-22 13:22:35.655155: +2024-11-22 13:22:35.655385: Epoch 4895 +2024-11-22 13:22:35.655501: Current learning rate: 0.00427 +2024-11-22 13:22:54.779788: train_loss -0.7974 +2024-11-22 13:22:54.780012: val_loss -0.7484 +2024-11-22 13:22:54.780086: Pseudo dice [0.8249] +2024-11-22 13:22:54.780163: Epoch time: 19.13 s +2024-11-22 13:22:55.670514: +2024-11-22 13:22:55.670717: Epoch 4896 +2024-11-22 13:22:55.670828: Current learning rate: 0.00427 +2024-11-22 13:23:14.212895: train_loss -0.8033 +2024-11-22 13:23:14.213206: val_loss -0.7637 +2024-11-22 13:23:14.213282: Pseudo dice [0.8548] +2024-11-22 13:23:14.213358: Epoch time: 18.54 s +2024-11-22 13:23:15.098391: +2024-11-22 13:23:15.098619: Epoch 4897 +2024-11-22 13:23:15.098734: Current learning rate: 0.00426 +2024-11-22 13:23:32.687038: train_loss -0.8068 +2024-11-22 13:23:32.687339: val_loss -0.7495 +2024-11-22 13:23:32.687415: Pseudo dice [0.8489] +2024-11-22 13:23:32.687499: Epoch time: 17.59 s +2024-11-22 13:23:33.575208: +2024-11-22 13:23:33.575646: Epoch 4898 +2024-11-22 13:23:33.575782: Current learning rate: 0.00426 +2024-11-22 13:23:52.316042: train_loss -0.8027 +2024-11-22 13:23:52.321528: val_loss -0.7587 +2024-11-22 13:23:52.321723: Pseudo dice [0.8531] +2024-11-22 13:23:52.321815: Epoch time: 18.74 s +2024-11-22 13:23:53.597312: +2024-11-22 13:23:53.597527: Epoch 4899 +2024-11-22 13:23:53.597639: Current learning rate: 0.00426 +2024-11-22 13:24:12.519243: train_loss -0.8011 +2024-11-22 13:24:12.519475: val_loss -0.7512 +2024-11-22 13:24:12.519551: Pseudo dice [0.8519] +2024-11-22 13:24:12.519627: Epoch time: 18.92 s +2024-11-22 13:24:13.765409: +2024-11-22 13:24:13.765649: Epoch 4900 +2024-11-22 13:24:13.765760: Current learning rate: 0.00426 +2024-11-22 13:24:32.352379: train_loss -0.7972 +2024-11-22 13:24:32.352604: val_loss -0.7533 +2024-11-22 13:24:32.352681: Pseudo dice [0.8391] +2024-11-22 13:24:32.354954: Epoch time: 18.59 s +2024-11-22 13:24:33.279563: +2024-11-22 13:24:33.279781: Epoch 4901 +2024-11-22 13:24:33.279904: Current learning rate: 0.00426 +2024-11-22 13:24:51.906574: train_loss -0.7901 +2024-11-22 13:24:51.906821: val_loss -0.751 +2024-11-22 13:24:51.906901: Pseudo dice [0.8245] +2024-11-22 13:24:51.906983: Epoch time: 18.63 s +2024-11-22 13:24:52.799872: +2024-11-22 13:24:52.800100: Epoch 4902 +2024-11-22 13:24:52.800220: Current learning rate: 0.00426 +2024-11-22 13:25:11.335495: train_loss -0.8016 +2024-11-22 13:25:11.335717: val_loss -0.7336 +2024-11-22 13:25:11.335791: Pseudo dice [0.8158] +2024-11-22 13:25:11.335870: Epoch time: 18.54 s +2024-11-22 13:25:12.255771: +2024-11-22 13:25:12.256022: Epoch 4903 +2024-11-22 13:25:12.256139: Current learning rate: 0.00426 +2024-11-22 13:25:31.798325: train_loss -0.7976 +2024-11-22 13:25:31.798565: val_loss -0.7122 +2024-11-22 13:25:31.798644: Pseudo dice [0.8216] +2024-11-22 13:25:31.798723: Epoch time: 19.54 s +2024-11-22 13:25:32.690066: +2024-11-22 13:25:32.690288: Epoch 4904 +2024-11-22 13:25:32.690404: Current learning rate: 0.00426 +2024-11-22 13:25:50.787872: train_loss -0.7805 +2024-11-22 13:25:50.788116: val_loss -0.7272 +2024-11-22 13:25:50.788192: Pseudo dice [0.8549] +2024-11-22 13:25:50.788275: Epoch time: 18.1 s +2024-11-22 13:25:51.704082: +2024-11-22 13:25:51.704294: Epoch 4905 +2024-11-22 13:25:51.704406: Current learning rate: 0.00425 +2024-11-22 13:26:10.724074: train_loss -0.7849 +2024-11-22 13:26:10.724322: val_loss -0.7305 +2024-11-22 13:26:10.724396: Pseudo dice [0.8399] +2024-11-22 13:26:10.724479: Epoch time: 19.02 s +2024-11-22 13:26:11.616102: +2024-11-22 13:26:11.616363: Epoch 4906 +2024-11-22 13:26:11.616478: Current learning rate: 0.00425 +2024-11-22 13:26:30.112722: train_loss -0.7932 +2024-11-22 13:26:30.112931: val_loss -0.77 +2024-11-22 13:26:30.113008: Pseudo dice [0.8435] +2024-11-22 13:26:30.113086: Epoch time: 18.5 s +2024-11-22 13:26:30.997030: +2024-11-22 13:26:30.997251: Epoch 4907 +2024-11-22 13:26:30.997375: Current learning rate: 0.00425 +2024-11-22 13:26:49.962596: train_loss -0.789 +2024-11-22 13:26:49.962887: val_loss -0.7781 +2024-11-22 13:26:49.962968: Pseudo dice [0.8666] +2024-11-22 13:26:49.963052: Epoch time: 18.97 s +2024-11-22 13:26:50.856488: +2024-11-22 13:26:50.856683: Epoch 4908 +2024-11-22 13:26:50.856795: Current learning rate: 0.00425 +2024-11-22 13:27:10.269083: train_loss -0.7871 +2024-11-22 13:27:10.269301: val_loss -0.7395 +2024-11-22 13:27:10.269385: Pseudo dice [0.8191] +2024-11-22 13:27:10.269464: Epoch time: 19.41 s +2024-11-22 13:27:11.153781: +2024-11-22 13:27:11.153996: Epoch 4909 +2024-11-22 13:27:11.154111: Current learning rate: 0.00425 +2024-11-22 13:27:29.558246: train_loss -0.7951 +2024-11-22 13:27:29.558563: val_loss -0.7544 +2024-11-22 13:27:29.558645: Pseudo dice [0.8354] +2024-11-22 13:27:29.558729: Epoch time: 18.41 s +2024-11-22 13:27:30.493446: +2024-11-22 13:27:30.493640: Epoch 4910 +2024-11-22 13:27:30.493756: Current learning rate: 0.00425 +2024-11-22 13:27:49.079031: train_loss -0.7952 +2024-11-22 13:27:49.079291: val_loss -0.7526 +2024-11-22 13:27:49.079371: Pseudo dice [0.8448] +2024-11-22 13:27:49.079448: Epoch time: 18.59 s +2024-11-22 13:27:50.124326: +2024-11-22 13:27:50.124653: Epoch 4911 +2024-11-22 13:27:50.124772: Current learning rate: 0.00425 +2024-11-22 13:28:09.238376: train_loss -0.7924 +2024-11-22 13:28:09.238593: val_loss -0.7267 +2024-11-22 13:28:09.238668: Pseudo dice [0.8326] +2024-11-22 13:28:09.238745: Epoch time: 19.11 s +2024-11-22 13:28:10.220119: +2024-11-22 13:28:10.220324: Epoch 4912 +2024-11-22 13:28:10.220433: Current learning rate: 0.00425 +2024-11-22 13:28:28.948405: train_loss -0.7958 +2024-11-22 13:28:28.948656: val_loss -0.7412 +2024-11-22 13:28:28.948733: Pseudo dice [0.8392] +2024-11-22 13:28:28.948819: Epoch time: 18.73 s +2024-11-22 13:28:29.845831: +2024-11-22 13:28:29.846060: Epoch 4913 +2024-11-22 13:28:29.846178: Current learning rate: 0.00424 +2024-11-22 13:28:49.040508: train_loss -0.7855 +2024-11-22 13:28:49.040726: val_loss -0.7777 +2024-11-22 13:28:49.040839: Pseudo dice [0.8461] +2024-11-22 13:28:49.040918: Epoch time: 19.2 s +2024-11-22 13:28:49.932519: +2024-11-22 13:28:49.932793: Epoch 4914 +2024-11-22 13:28:49.932905: Current learning rate: 0.00424 +2024-11-22 13:29:08.602376: train_loss -0.7854 +2024-11-22 13:29:08.604783: val_loss -0.7217 +2024-11-22 13:29:08.604910: Pseudo dice [0.847] +2024-11-22 13:29:08.604990: Epoch time: 18.67 s +2024-11-22 13:29:09.678339: +2024-11-22 13:29:09.678563: Epoch 4915 +2024-11-22 13:29:09.678679: Current learning rate: 0.00424 +2024-11-22 13:29:28.755662: train_loss -0.789 +2024-11-22 13:29:28.755886: val_loss -0.7294 +2024-11-22 13:29:28.755965: Pseudo dice [0.8058] +2024-11-22 13:29:28.756052: Epoch time: 19.08 s +2024-11-22 13:29:29.684052: +2024-11-22 13:29:29.684256: Epoch 4916 +2024-11-22 13:29:29.684405: Current learning rate: 0.00424 +2024-11-22 13:29:48.698273: train_loss -0.8016 +2024-11-22 13:29:48.698504: val_loss -0.7363 +2024-11-22 13:29:48.698580: Pseudo dice [0.8562] +2024-11-22 13:29:48.701191: Epoch time: 19.02 s +2024-11-22 13:29:49.630795: +2024-11-22 13:29:49.631085: Epoch 4917 +2024-11-22 13:29:49.631199: Current learning rate: 0.00424 +2024-11-22 13:30:08.500444: train_loss -0.7957 +2024-11-22 13:30:08.500704: val_loss -0.7239 +2024-11-22 13:30:08.500778: Pseudo dice [0.8332] +2024-11-22 13:30:08.500863: Epoch time: 18.87 s +2024-11-22 13:30:09.445188: +2024-11-22 13:30:09.445388: Epoch 4918 +2024-11-22 13:30:09.445502: Current learning rate: 0.00424 +2024-11-22 13:30:27.997723: train_loss -0.8023 +2024-11-22 13:30:27.997929: val_loss -0.7747 +2024-11-22 13:30:27.998011: Pseudo dice [0.8494] +2024-11-22 13:30:27.998090: Epoch time: 18.55 s +2024-11-22 13:30:28.892781: +2024-11-22 13:30:28.892983: Epoch 4919 +2024-11-22 13:30:28.893095: Current learning rate: 0.00424 +2024-11-22 13:30:47.833411: train_loss -0.801 +2024-11-22 13:30:47.833633: val_loss -0.7569 +2024-11-22 13:30:47.833706: Pseudo dice [0.8431] +2024-11-22 13:30:47.833782: Epoch time: 18.94 s +2024-11-22 13:30:48.774298: +2024-11-22 13:30:48.774505: Epoch 4920 +2024-11-22 13:30:48.774619: Current learning rate: 0.00424 +2024-11-22 13:31:08.317315: train_loss -0.7892 +2024-11-22 13:31:08.327900: val_loss -0.7549 +2024-11-22 13:31:08.328022: Pseudo dice [0.848] +2024-11-22 13:31:08.328122: Epoch time: 19.54 s +2024-11-22 13:31:09.393104: +2024-11-22 13:31:09.393446: Epoch 4921 +2024-11-22 13:31:09.393560: Current learning rate: 0.00423 +2024-11-22 13:31:28.519539: train_loss -0.8004 +2024-11-22 13:31:28.519758: val_loss -0.7613 +2024-11-22 13:31:28.519834: Pseudo dice [0.8384] +2024-11-22 13:31:28.519913: Epoch time: 19.13 s +2024-11-22 13:31:29.817683: +2024-11-22 13:31:29.817986: Epoch 4922 +2024-11-22 13:31:29.818105: Current learning rate: 0.00423 +2024-11-22 13:31:49.101018: train_loss -0.7998 +2024-11-22 13:31:49.101242: val_loss -0.7556 +2024-11-22 13:31:49.103502: Pseudo dice [0.8457] +2024-11-22 13:31:49.103595: Epoch time: 19.28 s +2024-11-22 13:31:50.025366: +2024-11-22 13:31:50.025593: Epoch 4923 +2024-11-22 13:31:50.025711: Current learning rate: 0.00423 +2024-11-22 13:32:08.127735: train_loss -0.7901 +2024-11-22 13:32:08.127979: val_loss -0.7254 +2024-11-22 13:32:08.128064: Pseudo dice [0.8314] +2024-11-22 13:32:08.128145: Epoch time: 18.1 s +2024-11-22 13:32:09.220945: +2024-11-22 13:32:09.221239: Epoch 4924 +2024-11-22 13:32:09.221352: Current learning rate: 0.00423 +2024-11-22 13:32:28.128316: train_loss -0.7847 +2024-11-22 13:32:28.128572: val_loss -0.7556 +2024-11-22 13:32:28.128647: Pseudo dice [0.8445] +2024-11-22 13:32:28.128734: Epoch time: 18.91 s +2024-11-22 13:32:29.025378: +2024-11-22 13:32:29.025588: Epoch 4925 +2024-11-22 13:32:29.025697: Current learning rate: 0.00423 +2024-11-22 13:32:47.495337: train_loss -0.7769 +2024-11-22 13:32:47.495624: val_loss -0.759 +2024-11-22 13:32:47.495714: Pseudo dice [0.8459] +2024-11-22 13:32:47.495804: Epoch time: 18.47 s +2024-11-22 13:32:48.387738: +2024-11-22 13:32:48.387960: Epoch 4926 +2024-11-22 13:32:48.388077: Current learning rate: 0.00423 +2024-11-22 13:33:07.350033: train_loss -0.7735 +2024-11-22 13:33:07.350253: val_loss -0.7162 +2024-11-22 13:33:07.350330: Pseudo dice [0.8564] +2024-11-22 13:33:07.350404: Epoch time: 18.96 s +2024-11-22 13:33:08.240637: +2024-11-22 13:33:08.240837: Epoch 4927 +2024-11-22 13:33:08.240952: Current learning rate: 0.00423 +2024-11-22 13:33:26.745270: train_loss -0.7904 +2024-11-22 13:33:26.745496: val_loss -0.7542 +2024-11-22 13:33:26.745572: Pseudo dice [0.8383] +2024-11-22 13:33:26.745656: Epoch time: 18.51 s +2024-11-22 13:33:27.642614: +2024-11-22 13:33:27.642828: Epoch 4928 +2024-11-22 13:33:27.642940: Current learning rate: 0.00423 +2024-11-22 13:33:45.551157: train_loss -0.7978 +2024-11-22 13:33:45.551436: val_loss -0.7582 +2024-11-22 13:33:45.551514: Pseudo dice [0.8428] +2024-11-22 13:33:45.551599: Epoch time: 17.91 s +2024-11-22 13:33:46.445031: +2024-11-22 13:33:46.445240: Epoch 4929 +2024-11-22 13:33:46.445353: Current learning rate: 0.00422 +2024-11-22 13:34:04.613137: train_loss -0.7953 +2024-11-22 13:34:04.613345: val_loss -0.7215 +2024-11-22 13:34:04.613469: Pseudo dice [0.8543] +2024-11-22 13:34:04.613647: Epoch time: 18.17 s +2024-11-22 13:34:05.505190: +2024-11-22 13:34:05.505395: Epoch 4930 +2024-11-22 13:34:05.505511: Current learning rate: 0.00422 +2024-11-22 13:34:24.276603: train_loss -0.7868 +2024-11-22 13:34:24.276842: val_loss -0.7524 +2024-11-22 13:34:24.276919: Pseudo dice [0.8376] +2024-11-22 13:34:24.277005: Epoch time: 18.77 s +2024-11-22 13:34:25.164987: +2024-11-22 13:34:25.165189: Epoch 4931 +2024-11-22 13:34:25.165302: Current learning rate: 0.00422 +2024-11-22 13:34:44.626828: train_loss -0.7877 +2024-11-22 13:34:44.627054: val_loss -0.7509 +2024-11-22 13:34:44.627131: Pseudo dice [0.8444] +2024-11-22 13:34:44.627212: Epoch time: 19.46 s +2024-11-22 13:34:45.616420: +2024-11-22 13:34:45.616614: Epoch 4932 +2024-11-22 13:34:45.616722: Current learning rate: 0.00422 +2024-11-22 13:35:04.564167: train_loss -0.7942 +2024-11-22 13:35:04.564413: val_loss -0.7598 +2024-11-22 13:35:04.564489: Pseudo dice [0.8383] +2024-11-22 13:35:04.564572: Epoch time: 18.95 s +2024-11-22 13:35:05.454674: +2024-11-22 13:35:05.454909: Epoch 4933 +2024-11-22 13:35:05.455030: Current learning rate: 0.00422 +2024-11-22 13:35:24.804929: train_loss -0.7922 +2024-11-22 13:35:24.805148: val_loss -0.7193 +2024-11-22 13:35:24.805224: Pseudo dice [0.8388] +2024-11-22 13:35:24.805300: Epoch time: 19.35 s +2024-11-22 13:35:26.114375: +2024-11-22 13:35:26.114669: Epoch 4934 +2024-11-22 13:35:26.114777: Current learning rate: 0.00422 +2024-11-22 13:35:45.818479: train_loss -0.7962 +2024-11-22 13:35:45.818740: val_loss -0.7347 +2024-11-22 13:35:45.818889: Pseudo dice [0.8332] +2024-11-22 13:35:45.818970: Epoch time: 19.7 s +2024-11-22 13:35:46.705688: +2024-11-22 13:35:46.705900: Epoch 4935 +2024-11-22 13:35:46.706017: Current learning rate: 0.00422 +2024-11-22 13:36:05.122898: train_loss -0.7785 +2024-11-22 13:36:05.123164: val_loss -0.7106 +2024-11-22 13:36:05.123240: Pseudo dice [0.8185] +2024-11-22 13:36:05.123399: Epoch time: 18.42 s +2024-11-22 13:36:06.016504: +2024-11-22 13:36:06.016733: Epoch 4936 +2024-11-22 13:36:06.016849: Current learning rate: 0.00422 +2024-11-22 13:36:24.999312: train_loss -0.7774 +2024-11-22 13:36:24.999540: val_loss -0.7554 +2024-11-22 13:36:25.001210: Pseudo dice [0.8339] +2024-11-22 13:36:25.001317: Epoch time: 18.98 s +2024-11-22 13:36:25.896892: +2024-11-22 13:36:25.897134: Epoch 4937 +2024-11-22 13:36:25.897258: Current learning rate: 0.00421 +2024-11-22 13:36:45.999896: train_loss -0.7841 +2024-11-22 13:36:46.000122: val_loss -0.7456 +2024-11-22 13:36:46.000197: Pseudo dice [0.8374] +2024-11-22 13:36:46.000274: Epoch time: 20.1 s +2024-11-22 13:36:46.892355: +2024-11-22 13:36:46.892558: Epoch 4938 +2024-11-22 13:36:46.892666: Current learning rate: 0.00421 +2024-11-22 13:37:05.110373: train_loss -0.7975 +2024-11-22 13:37:05.110601: val_loss -0.7681 +2024-11-22 13:37:05.110677: Pseudo dice [0.8222] +2024-11-22 13:37:05.110752: Epoch time: 18.22 s +2024-11-22 13:37:06.106665: +2024-11-22 13:37:06.106952: Epoch 4939 +2024-11-22 13:37:06.107077: Current learning rate: 0.00421 +2024-11-22 13:37:25.727970: train_loss -0.796 +2024-11-22 13:37:25.728217: val_loss -0.7558 +2024-11-22 13:37:25.728356: Pseudo dice [0.8713] +2024-11-22 13:37:25.728439: Epoch time: 19.62 s +2024-11-22 13:37:26.621774: +2024-11-22 13:37:26.622032: Epoch 4940 +2024-11-22 13:37:26.622191: Current learning rate: 0.00421 +2024-11-22 13:37:44.816988: train_loss -0.7953 +2024-11-22 13:37:44.817227: val_loss -0.765 +2024-11-22 13:37:44.817304: Pseudo dice [0.8564] +2024-11-22 13:37:44.817403: Epoch time: 18.2 s +2024-11-22 13:37:45.703479: +2024-11-22 13:37:45.703682: Epoch 4941 +2024-11-22 13:37:45.703798: Current learning rate: 0.00421 +2024-11-22 13:38:03.872000: train_loss -0.8032 +2024-11-22 13:38:03.872212: val_loss -0.7407 +2024-11-22 13:38:03.872295: Pseudo dice [0.8237] +2024-11-22 13:38:03.872375: Epoch time: 18.17 s +2024-11-22 13:38:04.765204: +2024-11-22 13:38:04.765488: Epoch 4942 +2024-11-22 13:38:04.765606: Current learning rate: 0.00421 +2024-11-22 13:38:24.088246: train_loss -0.7935 +2024-11-22 13:38:24.088474: val_loss -0.7428 +2024-11-22 13:38:24.088549: Pseudo dice [0.8281] +2024-11-22 13:38:24.088624: Epoch time: 19.32 s +2024-11-22 13:38:25.077000: +2024-11-22 13:38:25.077212: Epoch 4943 +2024-11-22 13:38:25.077324: Current learning rate: 0.00421 +2024-11-22 13:38:44.055156: train_loss -0.7977 +2024-11-22 13:38:44.055403: val_loss -0.7449 +2024-11-22 13:38:44.055480: Pseudo dice [0.8272] +2024-11-22 13:38:44.055565: Epoch time: 18.98 s +2024-11-22 13:38:44.939656: +2024-11-22 13:38:44.939844: Epoch 4944 +2024-11-22 13:38:44.939953: Current learning rate: 0.00421 +2024-11-22 13:39:03.037479: train_loss -0.8036 +2024-11-22 13:39:03.037707: val_loss -0.7711 +2024-11-22 13:39:03.037785: Pseudo dice [0.8513] +2024-11-22 13:39:03.037863: Epoch time: 18.1 s +2024-11-22 13:39:03.936415: +2024-11-22 13:39:03.936688: Epoch 4945 +2024-11-22 13:39:03.936805: Current learning rate: 0.0042 +2024-11-22 13:39:22.199872: train_loss -0.8014 +2024-11-22 13:39:22.205257: val_loss -0.773 +2024-11-22 13:39:22.205368: Pseudo dice [0.8563] +2024-11-22 13:39:22.205454: Epoch time: 18.26 s +2024-11-22 13:39:23.540245: +2024-11-22 13:39:23.540466: Epoch 4946 +2024-11-22 13:39:23.540577: Current learning rate: 0.0042 +2024-11-22 13:39:43.073618: train_loss -0.7987 +2024-11-22 13:39:43.073867: val_loss -0.7662 +2024-11-22 13:39:43.073942: Pseudo dice [0.858] +2024-11-22 13:39:43.074032: Epoch time: 19.53 s +2024-11-22 13:39:43.971403: +2024-11-22 13:39:43.971596: Epoch 4947 +2024-11-22 13:39:43.971703: Current learning rate: 0.0042 +2024-11-22 13:40:02.153520: train_loss -0.8011 +2024-11-22 13:40:02.153756: val_loss -0.7671 +2024-11-22 13:40:02.153836: Pseudo dice [0.8489] +2024-11-22 13:40:02.153912: Epoch time: 18.18 s +2024-11-22 13:40:03.044985: +2024-11-22 13:40:03.045211: Epoch 4948 +2024-11-22 13:40:03.045327: Current learning rate: 0.0042 +2024-11-22 13:40:21.766624: train_loss -0.8083 +2024-11-22 13:40:21.766901: val_loss -0.7446 +2024-11-22 13:40:21.766978: Pseudo dice [0.8422] +2024-11-22 13:40:21.767062: Epoch time: 18.72 s +2024-11-22 13:40:22.658078: +2024-11-22 13:40:22.658295: Epoch 4949 +2024-11-22 13:40:22.658408: Current learning rate: 0.0042 +2024-11-22 13:40:42.020272: train_loss -0.8022 +2024-11-22 13:40:42.020493: val_loss -0.7482 +2024-11-22 13:40:42.020585: Pseudo dice [0.8316] +2024-11-22 13:40:42.020662: Epoch time: 19.36 s +2024-11-22 13:40:43.201864: +2024-11-22 13:40:43.202069: Epoch 4950 +2024-11-22 13:40:43.202181: Current learning rate: 0.0042 +2024-11-22 13:41:02.493436: train_loss -0.7967 +2024-11-22 13:41:02.493689: val_loss -0.7513 +2024-11-22 13:41:02.493769: Pseudo dice [0.8395] +2024-11-22 13:41:02.493860: Epoch time: 19.29 s +2024-11-22 13:41:03.575425: +2024-11-22 13:41:03.575646: Epoch 4951 +2024-11-22 13:41:03.575757: Current learning rate: 0.0042 +2024-11-22 13:41:22.466265: train_loss -0.7832 +2024-11-22 13:41:22.466493: val_loss -0.7339 +2024-11-22 13:41:22.466569: Pseudo dice [0.818] +2024-11-22 13:41:22.466645: Epoch time: 18.89 s +2024-11-22 13:41:23.362216: +2024-11-22 13:41:23.362457: Epoch 4952 +2024-11-22 13:41:23.362580: Current learning rate: 0.0042 +2024-11-22 13:41:42.687658: train_loss -0.7987 +2024-11-22 13:41:42.687948: val_loss -0.749 +2024-11-22 13:41:42.688049: Pseudo dice [0.8393] +2024-11-22 13:41:42.688135: Epoch time: 19.33 s +2024-11-22 13:41:43.587960: +2024-11-22 13:41:43.588194: Epoch 4953 +2024-11-22 13:41:43.588313: Current learning rate: 0.00419 +2024-11-22 13:42:02.288129: train_loss -0.7949 +2024-11-22 13:42:02.288357: val_loss -0.7286 +2024-11-22 13:42:02.288436: Pseudo dice [0.8373] +2024-11-22 13:42:02.288531: Epoch time: 18.7 s +2024-11-22 13:42:03.176325: +2024-11-22 13:42:03.176537: Epoch 4954 +2024-11-22 13:42:03.176650: Current learning rate: 0.00419 +2024-11-22 13:42:22.123609: train_loss -0.7909 +2024-11-22 13:42:22.129067: val_loss -0.717 +2024-11-22 13:42:22.129202: Pseudo dice [0.8436] +2024-11-22 13:42:22.129290: Epoch time: 18.95 s +2024-11-22 13:42:23.051876: +2024-11-22 13:42:23.052078: Epoch 4955 +2024-11-22 13:42:23.052194: Current learning rate: 0.00419 +2024-11-22 13:42:41.446905: train_loss -0.7979 +2024-11-22 13:42:41.447128: val_loss -0.7732 +2024-11-22 13:42:41.447220: Pseudo dice [0.8479] +2024-11-22 13:42:41.447299: Epoch time: 18.4 s +2024-11-22 13:42:42.341881: +2024-11-22 13:42:42.342083: Epoch 4956 +2024-11-22 13:42:42.342194: Current learning rate: 0.00419 +2024-11-22 13:43:01.511674: train_loss -0.7929 +2024-11-22 13:43:01.511890: val_loss -0.7518 +2024-11-22 13:43:01.511961: Pseudo dice [0.8323] +2024-11-22 13:43:01.512046: Epoch time: 19.17 s +2024-11-22 13:43:02.406602: +2024-11-22 13:43:02.406808: Epoch 4957 +2024-11-22 13:43:02.406919: Current learning rate: 0.00419 +2024-11-22 13:43:22.146632: train_loss -0.798 +2024-11-22 13:43:22.146948: val_loss -0.7257 +2024-11-22 13:43:22.147032: Pseudo dice [0.8424] +2024-11-22 13:43:22.147115: Epoch time: 19.74 s +2024-11-22 13:43:23.035725: +2024-11-22 13:43:23.035933: Epoch 4958 +2024-11-22 13:43:23.036055: Current learning rate: 0.00419 +2024-11-22 13:43:41.470794: train_loss -0.795 +2024-11-22 13:43:41.471100: val_loss -0.7397 +2024-11-22 13:43:41.471178: Pseudo dice [0.8508] +2024-11-22 13:43:41.471257: Epoch time: 18.44 s +2024-11-22 13:43:42.434138: +2024-11-22 13:43:42.434477: Epoch 4959 +2024-11-22 13:43:42.434593: Current learning rate: 0.00419 +2024-11-22 13:44:01.754862: train_loss -0.7955 +2024-11-22 13:44:01.755092: val_loss -0.7394 +2024-11-22 13:44:01.755167: Pseudo dice [0.8085] +2024-11-22 13:44:01.755258: Epoch time: 19.32 s +2024-11-22 13:44:02.647955: +2024-11-22 13:44:02.648169: Epoch 4960 +2024-11-22 13:44:02.648283: Current learning rate: 0.00419 +2024-11-22 13:44:22.644793: train_loss -0.803 +2024-11-22 13:44:22.645024: val_loss -0.7458 +2024-11-22 13:44:22.645103: Pseudo dice [0.8472] +2024-11-22 13:44:22.645178: Epoch time: 20.0 s +2024-11-22 13:44:23.543979: +2024-11-22 13:44:23.544189: Epoch 4961 +2024-11-22 13:44:23.544299: Current learning rate: 0.00418 +2024-11-22 13:44:42.467293: train_loss -0.7994 +2024-11-22 13:44:42.467544: val_loss -0.7562 +2024-11-22 13:44:42.467688: Pseudo dice [0.8402] +2024-11-22 13:44:42.467775: Epoch time: 18.92 s +2024-11-22 13:44:43.365434: +2024-11-22 13:44:43.365773: Epoch 4962 +2024-11-22 13:44:43.365888: Current learning rate: 0.00418 +2024-11-22 13:45:03.032328: train_loss -0.806 +2024-11-22 13:45:03.035462: val_loss -0.7735 +2024-11-22 13:45:03.035691: Pseudo dice [0.8523] +2024-11-22 13:45:03.035781: Epoch time: 19.67 s +2024-11-22 13:45:03.956193: +2024-11-22 13:45:03.956477: Epoch 4963 +2024-11-22 13:45:03.956591: Current learning rate: 0.00418 +2024-11-22 13:45:22.699370: train_loss -0.8027 +2024-11-22 13:45:22.699588: val_loss -0.7623 +2024-11-22 13:45:22.699667: Pseudo dice [0.8666] +2024-11-22 13:45:22.699743: Epoch time: 18.74 s +2024-11-22 13:45:23.596658: +2024-11-22 13:45:23.596912: Epoch 4964 +2024-11-22 13:45:23.597038: Current learning rate: 0.00418 +2024-11-22 13:45:42.555304: train_loss -0.7953 +2024-11-22 13:45:42.560717: val_loss -0.7592 +2024-11-22 13:45:42.560849: Pseudo dice [0.8545] +2024-11-22 13:45:42.561135: Epoch time: 18.96 s +2024-11-22 13:45:43.628722: +2024-11-22 13:45:43.628963: Epoch 4965 +2024-11-22 13:45:43.629083: Current learning rate: 0.00418 +2024-11-22 13:46:02.862802: train_loss -0.806 +2024-11-22 13:46:02.863109: val_loss -0.764 +2024-11-22 13:46:02.863189: Pseudo dice [0.8475] +2024-11-22 13:46:02.863276: Epoch time: 19.23 s +2024-11-22 13:46:03.767909: +2024-11-22 13:46:03.768129: Epoch 4966 +2024-11-22 13:46:03.768241: Current learning rate: 0.00418 +2024-11-22 13:46:21.463887: train_loss -0.7897 +2024-11-22 13:46:21.464113: val_loss -0.7353 +2024-11-22 13:46:21.466357: Pseudo dice [0.8188] +2024-11-22 13:46:21.466473: Epoch time: 17.7 s +2024-11-22 13:46:22.549320: +2024-11-22 13:46:22.549609: Epoch 4967 +2024-11-22 13:46:22.549726: Current learning rate: 0.00418 +2024-11-22 13:46:41.596245: train_loss -0.788 +2024-11-22 13:46:41.596473: val_loss -0.7487 +2024-11-22 13:46:41.596554: Pseudo dice [0.8475] +2024-11-22 13:46:41.596635: Epoch time: 19.05 s +2024-11-22 13:46:42.669251: +2024-11-22 13:46:42.669456: Epoch 4968 +2024-11-22 13:46:42.669567: Current learning rate: 0.00418 +2024-11-22 13:47:01.682713: train_loss -0.7868 +2024-11-22 13:47:01.682943: val_loss -0.7307 +2024-11-22 13:47:01.683030: Pseudo dice [0.8196] +2024-11-22 13:47:01.683114: Epoch time: 19.01 s +2024-11-22 13:47:02.964455: +2024-11-22 13:47:02.964663: Epoch 4969 +2024-11-22 13:47:02.964777: Current learning rate: 0.00417 +2024-11-22 13:47:21.772448: train_loss -0.7897 +2024-11-22 13:47:21.772691: val_loss -0.7404 +2024-11-22 13:47:21.772765: Pseudo dice [0.8309] +2024-11-22 13:47:21.772842: Epoch time: 18.81 s +2024-11-22 13:47:22.679986: +2024-11-22 13:47:22.680201: Epoch 4970 +2024-11-22 13:47:22.680310: Current learning rate: 0.00417 +2024-11-22 13:47:41.093505: train_loss -0.7966 +2024-11-22 13:47:41.093728: val_loss -0.7411 +2024-11-22 13:47:41.093803: Pseudo dice [0.8259] +2024-11-22 13:47:41.093881: Epoch time: 18.41 s +2024-11-22 13:47:41.979325: +2024-11-22 13:47:41.979553: Epoch 4971 +2024-11-22 13:47:41.979664: Current learning rate: 0.00417 +2024-11-22 13:48:00.257795: train_loss -0.7911 +2024-11-22 13:48:00.258676: val_loss -0.7295 +2024-11-22 13:48:00.258786: Pseudo dice [0.8274] +2024-11-22 13:48:00.258868: Epoch time: 18.28 s +2024-11-22 13:48:01.169576: +2024-11-22 13:48:01.169785: Epoch 4972 +2024-11-22 13:48:01.169900: Current learning rate: 0.00417 +2024-11-22 13:48:18.677392: train_loss -0.7798 +2024-11-22 13:48:18.677649: val_loss -0.7415 +2024-11-22 13:48:18.677728: Pseudo dice [0.8577] +2024-11-22 13:48:18.677815: Epoch time: 17.51 s +2024-11-22 13:48:19.569031: +2024-11-22 13:48:19.569248: Epoch 4973 +2024-11-22 13:48:19.569361: Current learning rate: 0.00417 +2024-11-22 13:48:38.118330: train_loss -0.7974 +2024-11-22 13:48:38.118554: val_loss -0.7531 +2024-11-22 13:48:38.118635: Pseudo dice [0.8391] +2024-11-22 13:48:38.118712: Epoch time: 18.55 s +2024-11-22 13:48:39.008354: +2024-11-22 13:48:39.008587: Epoch 4974 +2024-11-22 13:48:39.008708: Current learning rate: 0.00417 +2024-11-22 13:48:58.024514: train_loss -0.7861 +2024-11-22 13:48:58.024734: val_loss -0.7183 +2024-11-22 13:48:58.024811: Pseudo dice [0.8381] +2024-11-22 13:48:58.024885: Epoch time: 19.02 s +2024-11-22 13:48:58.909075: +2024-11-22 13:48:58.909271: Epoch 4975 +2024-11-22 13:48:58.909384: Current learning rate: 0.00417 +2024-11-22 13:49:17.205334: train_loss -0.7727 +2024-11-22 13:49:17.205598: val_loss -0.7376 +2024-11-22 13:49:17.205676: Pseudo dice [0.8218] +2024-11-22 13:49:17.205751: Epoch time: 18.3 s +2024-11-22 13:49:18.091218: +2024-11-22 13:49:18.091419: Epoch 4976 +2024-11-22 13:49:18.091533: Current learning rate: 0.00417 +2024-11-22 13:49:36.057822: train_loss -0.7833 +2024-11-22 13:49:36.058083: val_loss -0.7588 +2024-11-22 13:49:36.058167: Pseudo dice [0.8272] +2024-11-22 13:49:36.058252: Epoch time: 17.97 s +2024-11-22 13:49:36.950255: +2024-11-22 13:49:36.950518: Epoch 4977 +2024-11-22 13:49:36.950632: Current learning rate: 0.00416 +2024-11-22 13:49:56.294859: train_loss -0.7925 +2024-11-22 13:49:56.295088: val_loss -0.769 +2024-11-22 13:49:56.295171: Pseudo dice [0.8587] +2024-11-22 13:49:56.295249: Epoch time: 19.35 s +2024-11-22 13:49:57.222349: +2024-11-22 13:49:57.222575: Epoch 4978 +2024-11-22 13:49:57.222694: Current learning rate: 0.00416 +2024-11-22 13:50:15.863585: train_loss -0.7951 +2024-11-22 13:50:15.863811: val_loss -0.7746 +2024-11-22 13:50:15.863883: Pseudo dice [0.871] +2024-11-22 13:50:15.863963: Epoch time: 18.64 s +2024-11-22 13:50:16.756183: +2024-11-22 13:50:16.756425: Epoch 4979 +2024-11-22 13:50:16.756538: Current learning rate: 0.00416 +2024-11-22 13:50:35.603806: train_loss -0.7922 +2024-11-22 13:50:35.604039: val_loss -0.7664 +2024-11-22 13:50:35.604123: Pseudo dice [0.8475] +2024-11-22 13:50:35.604205: Epoch time: 18.85 s +2024-11-22 13:50:36.497999: +2024-11-22 13:50:36.498225: Epoch 4980 +2024-11-22 13:50:36.498361: Current learning rate: 0.00416 +2024-11-22 13:50:55.379942: train_loss -0.8014 +2024-11-22 13:50:55.380210: val_loss -0.7325 +2024-11-22 13:50:55.380283: Pseudo dice [0.8219] +2024-11-22 13:50:55.380368: Epoch time: 18.88 s +2024-11-22 13:50:56.854375: +2024-11-22 13:50:56.854594: Epoch 4981 +2024-11-22 13:50:56.854711: Current learning rate: 0.00416 +2024-11-22 13:51:14.608837: train_loss -0.7996 +2024-11-22 13:51:14.609149: val_loss -0.7645 +2024-11-22 13:51:14.609225: Pseudo dice [0.8339] +2024-11-22 13:51:14.609304: Epoch time: 17.76 s +2024-11-22 13:51:15.497660: +2024-11-22 13:51:15.497943: Epoch 4982 +2024-11-22 13:51:15.498057: Current learning rate: 0.00416 +2024-11-22 13:51:34.831871: train_loss -0.8028 +2024-11-22 13:51:34.832139: val_loss -0.7156 +2024-11-22 13:51:34.832214: Pseudo dice [0.843] +2024-11-22 13:51:34.832290: Epoch time: 19.34 s +2024-11-22 13:51:35.762212: +2024-11-22 13:51:35.762431: Epoch 4983 +2024-11-22 13:51:35.762541: Current learning rate: 0.00416 +2024-11-22 13:51:53.663480: train_loss -0.8009 +2024-11-22 13:51:53.663734: val_loss -0.7549 +2024-11-22 13:51:53.663819: Pseudo dice [0.8543] +2024-11-22 13:51:53.669126: Epoch time: 17.9 s +2024-11-22 13:51:54.562079: +2024-11-22 13:51:54.562362: Epoch 4984 +2024-11-22 13:51:54.562474: Current learning rate: 0.00416 +2024-11-22 13:52:12.975872: train_loss -0.7936 +2024-11-22 13:52:12.976094: val_loss -0.7303 +2024-11-22 13:52:12.976172: Pseudo dice [0.8334] +2024-11-22 13:52:12.976251: Epoch time: 18.41 s +2024-11-22 13:52:13.871381: +2024-11-22 13:52:13.871593: Epoch 4985 +2024-11-22 13:52:13.871707: Current learning rate: 0.00416 +2024-11-22 13:52:32.310306: train_loss -0.803 +2024-11-22 13:52:32.310549: val_loss -0.7469 +2024-11-22 13:52:32.310627: Pseudo dice [0.8562] +2024-11-22 13:52:32.310705: Epoch time: 18.44 s +2024-11-22 13:52:33.206344: +2024-11-22 13:52:33.206616: Epoch 4986 +2024-11-22 13:52:33.206733: Current learning rate: 0.00415 +2024-11-22 13:52:52.192679: train_loss -0.7962 +2024-11-22 13:52:52.192902: val_loss -0.7587 +2024-11-22 13:52:52.193030: Pseudo dice [0.848] +2024-11-22 13:52:52.193107: Epoch time: 18.99 s +2024-11-22 13:52:53.086194: +2024-11-22 13:52:53.086456: Epoch 4987 +2024-11-22 13:52:53.086586: Current learning rate: 0.00415 +2024-11-22 13:53:12.810035: train_loss -0.8028 +2024-11-22 13:53:12.810286: val_loss -0.7387 +2024-11-22 13:53:12.810362: Pseudo dice [0.8394] +2024-11-22 13:53:12.810447: Epoch time: 19.72 s +2024-11-22 13:53:13.699029: +2024-11-22 13:53:13.699205: Epoch 4988 +2024-11-22 13:53:13.699318: Current learning rate: 0.00415 +2024-11-22 13:53:32.700142: train_loss -0.8015 +2024-11-22 13:53:32.700360: val_loss -0.7521 +2024-11-22 13:53:32.700436: Pseudo dice [0.8648] +2024-11-22 13:53:32.700509: Epoch time: 19.0 s +2024-11-22 13:53:33.588341: +2024-11-22 13:53:33.588614: Epoch 4989 +2024-11-22 13:53:33.588724: Current learning rate: 0.00415 +2024-11-22 13:53:53.857256: train_loss -0.7817 +2024-11-22 13:53:53.857482: val_loss -0.7479 +2024-11-22 13:53:53.857560: Pseudo dice [0.8338] +2024-11-22 13:53:53.857699: Epoch time: 20.27 s +2024-11-22 13:53:54.757044: +2024-11-22 13:53:54.757231: Epoch 4990 +2024-11-22 13:53:54.757343: Current learning rate: 0.00415 +2024-11-22 13:54:13.135032: train_loss -0.7977 +2024-11-22 13:54:13.135265: val_loss -0.7371 +2024-11-22 13:54:13.135339: Pseudo dice [0.8443] +2024-11-22 13:54:13.140842: Epoch time: 18.38 s +2024-11-22 13:54:14.221219: +2024-11-22 13:54:14.221422: Epoch 4991 +2024-11-22 13:54:14.221529: Current learning rate: 0.00415 +2024-11-22 13:54:33.510204: train_loss -0.7935 +2024-11-22 13:54:33.510525: val_loss -0.7352 +2024-11-22 13:54:33.510605: Pseudo dice [0.8204] +2024-11-22 13:54:33.510689: Epoch time: 19.29 s +2024-11-22 13:54:34.409584: +2024-11-22 13:54:34.409790: Epoch 4992 +2024-11-22 13:54:34.409905: Current learning rate: 0.00415 +2024-11-22 13:54:53.079645: train_loss -0.8098 +2024-11-22 13:54:53.079862: val_loss -0.7268 +2024-11-22 13:54:53.079939: Pseudo dice [0.8395] +2024-11-22 13:54:53.080024: Epoch time: 18.67 s +2024-11-22 13:54:54.401805: +2024-11-22 13:54:54.402035: Epoch 4993 +2024-11-22 13:54:54.402148: Current learning rate: 0.00415 +2024-11-22 13:55:12.206384: train_loss -0.7851 +2024-11-22 13:55:12.206641: val_loss -0.7542 +2024-11-22 13:55:12.206722: Pseudo dice [0.8373] +2024-11-22 13:55:12.206803: Epoch time: 17.81 s +2024-11-22 13:55:13.104052: +2024-11-22 13:55:13.104264: Epoch 4994 +2024-11-22 13:55:13.104373: Current learning rate: 0.00414 +2024-11-22 13:55:31.654967: train_loss -0.7897 +2024-11-22 13:55:31.655190: val_loss -0.7738 +2024-11-22 13:55:31.655276: Pseudo dice [0.8519] +2024-11-22 13:55:31.655361: Epoch time: 18.55 s +2024-11-22 13:55:32.548158: +2024-11-22 13:55:32.548360: Epoch 4995 +2024-11-22 13:55:32.548470: Current learning rate: 0.00414 +2024-11-22 13:55:51.255779: train_loss -0.7909 +2024-11-22 13:55:51.256043: val_loss -0.7607 +2024-11-22 13:55:51.256118: Pseudo dice [0.8526] +2024-11-22 13:55:51.256201: Epoch time: 18.71 s +2024-11-22 13:55:52.304362: +2024-11-22 13:55:52.304627: Epoch 4996 +2024-11-22 13:55:52.304743: Current learning rate: 0.00414 +2024-11-22 13:56:11.977005: train_loss -0.7953 +2024-11-22 13:56:11.977283: val_loss -0.717 +2024-11-22 13:56:11.977366: Pseudo dice [0.8512] +2024-11-22 13:56:11.977448: Epoch time: 19.67 s +2024-11-22 13:56:12.864871: +2024-11-22 13:56:12.865294: Epoch 4997 +2024-11-22 13:56:12.865409: Current learning rate: 0.00414 +2024-11-22 13:56:31.819225: train_loss -0.7993 +2024-11-22 13:56:31.819440: val_loss -0.7346 +2024-11-22 13:56:31.819519: Pseudo dice [0.7959] +2024-11-22 13:56:31.819595: Epoch time: 18.96 s +2024-11-22 13:56:32.708996: +2024-11-22 13:56:32.709189: Epoch 4998 +2024-11-22 13:56:32.709299: Current learning rate: 0.00414 +2024-11-22 13:56:51.075252: train_loss -0.8 +2024-11-22 13:56:51.075498: val_loss -0.7283 +2024-11-22 13:56:51.075585: Pseudo dice [0.8256] +2024-11-22 13:56:51.075666: Epoch time: 18.37 s +2024-11-22 13:56:52.197277: +2024-11-22 13:56:52.197488: Epoch 4999 +2024-11-22 13:56:52.197600: Current learning rate: 0.00414 +2024-11-22 13:57:09.408981: train_loss -0.8023 +2024-11-22 13:57:09.409254: val_loss -0.7143 +2024-11-22 13:57:09.409331: Pseudo dice [0.8194] +2024-11-22 13:57:09.409419: Epoch time: 17.21 s +2024-11-22 13:57:10.589644: +2024-11-22 13:57:10.589859: Epoch 5000 +2024-11-22 13:57:10.589969: Current learning rate: 0.00414 +2024-11-22 13:57:29.464832: train_loss -0.8063 +2024-11-22 13:57:29.465083: val_loss -0.7384 +2024-11-22 13:57:29.465162: Pseudo dice [0.849] +2024-11-22 13:57:29.465240: Epoch time: 18.88 s +2024-11-22 13:57:30.445683: +2024-11-22 13:57:30.445950: Epoch 5001 +2024-11-22 13:57:30.446070: Current learning rate: 0.00414 +2024-11-22 13:57:49.210290: train_loss -0.7993 +2024-11-22 13:57:49.210506: val_loss -0.736 +2024-11-22 13:57:49.210581: Pseudo dice [0.8336] +2024-11-22 13:57:49.210713: Epoch time: 18.77 s +2024-11-22 13:57:50.095284: +2024-11-22 13:57:50.095511: Epoch 5002 +2024-11-22 13:57:50.095624: Current learning rate: 0.00413 +2024-11-22 13:58:08.728533: train_loss -0.7923 +2024-11-22 13:58:08.729286: val_loss -0.7463 +2024-11-22 13:58:08.729454: Pseudo dice [0.8607] +2024-11-22 13:58:08.729539: Epoch time: 18.63 s +2024-11-22 13:58:09.616353: +2024-11-22 13:58:09.616561: Epoch 5003 +2024-11-22 13:58:09.616673: Current learning rate: 0.00413 +2024-11-22 13:58:28.675199: train_loss -0.7992 +2024-11-22 13:58:28.675442: val_loss -0.7492 +2024-11-22 13:58:28.675518: Pseudo dice [0.8583] +2024-11-22 13:58:28.675602: Epoch time: 19.06 s +2024-11-22 13:58:29.557443: +2024-11-22 13:58:29.557802: Epoch 5004 +2024-11-22 13:58:29.557920: Current learning rate: 0.00413 +2024-11-22 13:58:48.111515: train_loss -0.7969 +2024-11-22 13:58:48.111775: val_loss -0.7157 +2024-11-22 13:58:48.114089: Pseudo dice [0.84] +2024-11-22 13:58:48.114188: Epoch time: 18.55 s +2024-11-22 13:58:49.021352: +2024-11-22 13:58:49.021698: Epoch 5005 +2024-11-22 13:58:49.021811: Current learning rate: 0.00413 +2024-11-22 13:59:07.883498: train_loss -0.8039 +2024-11-22 13:59:07.883736: val_loss -0.7375 +2024-11-22 13:59:07.883815: Pseudo dice [0.8332] +2024-11-22 13:59:07.883891: Epoch time: 18.86 s +2024-11-22 13:59:08.776268: +2024-11-22 13:59:08.776508: Epoch 5006 +2024-11-22 13:59:08.776619: Current learning rate: 0.00413 +2024-11-22 13:59:28.186821: train_loss -0.8039 +2024-11-22 13:59:28.187051: val_loss -0.7654 +2024-11-22 13:59:28.187135: Pseudo dice [0.8496] +2024-11-22 13:59:28.187218: Epoch time: 19.41 s +2024-11-22 13:59:29.083349: +2024-11-22 13:59:29.083603: Epoch 5007 +2024-11-22 13:59:29.083762: Current learning rate: 0.00413 +2024-11-22 13:59:48.684862: train_loss -0.8003 +2024-11-22 13:59:48.685152: val_loss -0.7803 +2024-11-22 13:59:48.685230: Pseudo dice [0.8362] +2024-11-22 13:59:48.685312: Epoch time: 19.6 s +2024-11-22 13:59:49.644774: +2024-11-22 13:59:49.644981: Epoch 5008 +2024-11-22 13:59:49.645098: Current learning rate: 0.00413 +2024-11-22 14:00:08.038735: train_loss -0.7938 +2024-11-22 14:00:08.038955: val_loss -0.7177 +2024-11-22 14:00:08.039037: Pseudo dice [0.8536] +2024-11-22 14:00:08.039111: Epoch time: 18.39 s +2024-11-22 14:00:09.031173: +2024-11-22 14:00:09.031386: Epoch 5009 +2024-11-22 14:00:09.031512: Current learning rate: 0.00413 +2024-11-22 14:00:29.112273: train_loss -0.8006 +2024-11-22 14:00:29.112511: val_loss -0.7395 +2024-11-22 14:00:29.112591: Pseudo dice [0.8513] +2024-11-22 14:00:29.112666: Epoch time: 20.08 s +2024-11-22 14:00:30.005655: +2024-11-22 14:00:30.005874: Epoch 5010 +2024-11-22 14:00:30.005996: Current learning rate: 0.00412 +2024-11-22 14:00:49.106576: train_loss -0.8043 +2024-11-22 14:00:49.106827: val_loss -0.7605 +2024-11-22 14:00:49.106946: Pseudo dice [0.8503] +2024-11-22 14:00:49.107033: Epoch time: 19.1 s +2024-11-22 14:00:50.005109: +2024-11-22 14:00:50.005372: Epoch 5011 +2024-11-22 14:00:50.005495: Current learning rate: 0.00412 +2024-11-22 14:01:08.504271: train_loss -0.7967 +2024-11-22 14:01:08.504542: val_loss -0.7259 +2024-11-22 14:01:08.504627: Pseudo dice [0.8599] +2024-11-22 14:01:08.504707: Epoch time: 18.5 s +2024-11-22 14:01:09.406938: +2024-11-22 14:01:09.407260: Epoch 5012 +2024-11-22 14:01:09.407372: Current learning rate: 0.00412 +2024-11-22 14:01:28.427491: train_loss -0.8006 +2024-11-22 14:01:28.427754: val_loss -0.7534 +2024-11-22 14:01:28.427832: Pseudo dice [0.8494] +2024-11-22 14:01:28.427906: Epoch time: 19.02 s +2024-11-22 14:01:29.317716: +2024-11-22 14:01:29.318145: Epoch 5013 +2024-11-22 14:01:29.318287: Current learning rate: 0.00412 +2024-11-22 14:01:47.345475: train_loss -0.8041 +2024-11-22 14:01:47.345695: val_loss -0.7611 +2024-11-22 14:01:47.345773: Pseudo dice [0.8702] +2024-11-22 14:01:47.345854: Epoch time: 18.03 s +2024-11-22 14:01:48.236476: +2024-11-22 14:01:48.236890: Epoch 5014 +2024-11-22 14:01:48.237030: Current learning rate: 0.00412 +2024-11-22 14:02:06.933024: train_loss -0.7942 +2024-11-22 14:02:06.933264: val_loss -0.7622 +2024-11-22 14:02:06.933346: Pseudo dice [0.8558] +2024-11-22 14:02:06.933432: Epoch time: 18.7 s +2024-11-22 14:02:07.821351: +2024-11-22 14:02:07.821763: Epoch 5015 +2024-11-22 14:02:07.821902: Current learning rate: 0.00412 +2024-11-22 14:02:27.001194: train_loss -0.7933 +2024-11-22 14:02:27.001450: val_loss -0.7676 +2024-11-22 14:02:27.001522: Pseudo dice [0.8607] +2024-11-22 14:02:27.001601: Epoch time: 19.18 s +2024-11-22 14:02:28.294111: +2024-11-22 14:02:28.294625: Epoch 5016 +2024-11-22 14:02:28.294760: Current learning rate: 0.00412 +2024-11-22 14:02:47.301264: train_loss -0.7973 +2024-11-22 14:02:47.301483: val_loss -0.768 +2024-11-22 14:02:47.301557: Pseudo dice [0.8688] +2024-11-22 14:02:47.302387: Epoch time: 19.01 s +2024-11-22 14:02:48.186335: +2024-11-22 14:02:48.186779: Epoch 5017 +2024-11-22 14:02:48.186913: Current learning rate: 0.00412 +2024-11-22 14:03:06.469513: train_loss -0.7963 +2024-11-22 14:03:06.470204: val_loss -0.7505 +2024-11-22 14:03:06.470286: Pseudo dice [0.8356] +2024-11-22 14:03:06.470365: Epoch time: 18.28 s +2024-11-22 14:03:07.357795: +2024-11-22 14:03:07.358243: Epoch 5018 +2024-11-22 14:03:07.358384: Current learning rate: 0.00411 +2024-11-22 14:03:26.802215: train_loss -0.7941 +2024-11-22 14:03:26.802469: val_loss -0.7486 +2024-11-22 14:03:26.802550: Pseudo dice [0.8311] +2024-11-22 14:03:26.802752: Epoch time: 19.45 s +2024-11-22 14:03:27.694211: +2024-11-22 14:03:27.694655: Epoch 5019 +2024-11-22 14:03:27.694794: Current learning rate: 0.00411 +2024-11-22 14:03:47.451585: train_loss -0.798 +2024-11-22 14:03:47.451812: val_loss -0.7347 +2024-11-22 14:03:47.451891: Pseudo dice [0.8309] +2024-11-22 14:03:47.451966: Epoch time: 19.76 s +2024-11-22 14:03:48.334084: +2024-11-22 14:03:48.334557: Epoch 5020 +2024-11-22 14:03:48.334694: Current learning rate: 0.00411 +2024-11-22 14:04:06.857331: train_loss -0.7966 +2024-11-22 14:04:06.857556: val_loss -0.7305 +2024-11-22 14:04:06.857631: Pseudo dice [0.8376] +2024-11-22 14:04:06.857708: Epoch time: 18.52 s +2024-11-22 14:04:07.745130: +2024-11-22 14:04:07.745584: Epoch 5021 +2024-11-22 14:04:07.745719: Current learning rate: 0.00411 +2024-11-22 14:04:26.307709: train_loss -0.7895 +2024-11-22 14:04:26.307932: val_loss -0.7706 +2024-11-22 14:04:26.308011: Pseudo dice [0.8421] +2024-11-22 14:04:26.308089: Epoch time: 18.56 s +2024-11-22 14:04:27.378277: +2024-11-22 14:04:27.378686: Epoch 5022 +2024-11-22 14:04:27.378819: Current learning rate: 0.00411 +2024-11-22 14:04:45.900537: train_loss -0.798 +2024-11-22 14:04:45.900785: val_loss -0.7578 +2024-11-22 14:04:45.900866: Pseudo dice [0.8607] +2024-11-22 14:04:45.900958: Epoch time: 18.52 s +2024-11-22 14:04:46.794360: +2024-11-22 14:04:46.794812: Epoch 5023 +2024-11-22 14:04:46.794948: Current learning rate: 0.00411 +2024-11-22 14:05:06.850420: train_loss -0.8021 +2024-11-22 14:05:06.850640: val_loss -0.7453 +2024-11-22 14:05:06.850716: Pseudo dice [0.8444] +2024-11-22 14:05:06.850792: Epoch time: 20.06 s +2024-11-22 14:05:07.855325: +2024-11-22 14:05:07.855742: Epoch 5024 +2024-11-22 14:05:07.855875: Current learning rate: 0.00411 +2024-11-22 14:05:26.380381: train_loss -0.8038 +2024-11-22 14:05:26.380599: val_loss -0.7418 +2024-11-22 14:05:26.380678: Pseudo dice [0.8542] +2024-11-22 14:05:26.380754: Epoch time: 18.53 s +2024-11-22 14:05:27.262022: +2024-11-22 14:05:27.262411: Epoch 5025 +2024-11-22 14:05:27.262541: Current learning rate: 0.00411 +2024-11-22 14:05:47.721431: train_loss -0.8073 +2024-11-22 14:05:47.721653: val_loss -0.7716 +2024-11-22 14:05:47.721726: Pseudo dice [0.8224] +2024-11-22 14:05:47.721805: Epoch time: 20.46 s +2024-11-22 14:05:48.615143: +2024-11-22 14:05:48.615546: Epoch 5026 +2024-11-22 14:05:48.615678: Current learning rate: 0.0041 +2024-11-22 14:06:07.778889: train_loss -0.8089 +2024-11-22 14:06:07.779166: val_loss -0.7346 +2024-11-22 14:06:07.779244: Pseudo dice [0.8433] +2024-11-22 14:06:07.779397: Epoch time: 19.16 s +2024-11-22 14:06:08.668027: +2024-11-22 14:06:08.668475: Epoch 5027 +2024-11-22 14:06:08.668618: Current learning rate: 0.0041 +2024-11-22 14:06:26.747599: train_loss -0.8025 +2024-11-22 14:06:26.747817: val_loss -0.7396 +2024-11-22 14:06:26.747894: Pseudo dice [0.8305] +2024-11-22 14:06:26.747973: Epoch time: 18.08 s +2024-11-22 14:06:28.074347: +2024-11-22 14:06:28.074584: Epoch 5028 +2024-11-22 14:06:28.074695: Current learning rate: 0.0041 +2024-11-22 14:06:46.692885: train_loss -0.8002 +2024-11-22 14:06:46.693116: val_loss -0.7357 +2024-11-22 14:06:46.693219: Pseudo dice [0.8523] +2024-11-22 14:06:46.693297: Epoch time: 18.62 s +2024-11-22 14:06:47.576448: +2024-11-22 14:06:47.576728: Epoch 5029 +2024-11-22 14:06:47.576839: Current learning rate: 0.0041 +2024-11-22 14:07:06.298368: train_loss -0.8056 +2024-11-22 14:07:06.298585: val_loss -0.7579 +2024-11-22 14:07:06.298734: Pseudo dice [0.846] +2024-11-22 14:07:06.298812: Epoch time: 18.72 s +2024-11-22 14:07:07.185514: +2024-11-22 14:07:07.185760: Epoch 5030 +2024-11-22 14:07:07.185871: Current learning rate: 0.0041 +2024-11-22 14:07:26.167965: train_loss -0.8007 +2024-11-22 14:07:26.168295: val_loss -0.7305 +2024-11-22 14:07:26.168377: Pseudo dice [0.8283] +2024-11-22 14:07:26.168458: Epoch time: 18.98 s +2024-11-22 14:07:27.056215: +2024-11-22 14:07:27.056428: Epoch 5031 +2024-11-22 14:07:27.056541: Current learning rate: 0.0041 +2024-11-22 14:07:46.578899: train_loss -0.7941 +2024-11-22 14:07:46.579122: val_loss -0.735 +2024-11-22 14:07:46.579198: Pseudo dice [0.8434] +2024-11-22 14:07:46.579273: Epoch time: 19.52 s +2024-11-22 14:07:47.510834: +2024-11-22 14:07:47.511051: Epoch 5032 +2024-11-22 14:07:47.511170: Current learning rate: 0.0041 +2024-11-22 14:08:06.250432: train_loss -0.7943 +2024-11-22 14:08:06.250670: val_loss -0.753 +2024-11-22 14:08:06.250747: Pseudo dice [0.8508] +2024-11-22 14:08:06.250870: Epoch time: 18.74 s +2024-11-22 14:08:07.144760: +2024-11-22 14:08:07.144979: Epoch 5033 +2024-11-22 14:08:07.145098: Current learning rate: 0.0041 +2024-11-22 14:08:26.445822: train_loss -0.7969 +2024-11-22 14:08:26.446047: val_loss -0.7396 +2024-11-22 14:08:26.446124: Pseudo dice [0.8386] +2024-11-22 14:08:26.446274: Epoch time: 19.3 s +2024-11-22 14:08:27.341398: +2024-11-22 14:08:27.341613: Epoch 5034 +2024-11-22 14:08:27.341729: Current learning rate: 0.00409 +2024-11-22 14:08:45.926308: train_loss -0.7966 +2024-11-22 14:08:45.926555: val_loss -0.7542 +2024-11-22 14:08:45.926630: Pseudo dice [0.8585] +2024-11-22 14:08:45.926713: Epoch time: 18.59 s +2024-11-22 14:08:46.826041: +2024-11-22 14:08:46.826259: Epoch 5035 +2024-11-22 14:08:46.826370: Current learning rate: 0.00409 +2024-11-22 14:09:04.534523: train_loss -0.8056 +2024-11-22 14:09:04.534739: val_loss -0.7059 +2024-11-22 14:09:04.534816: Pseudo dice [0.838] +2024-11-22 14:09:04.534894: Epoch time: 17.71 s +2024-11-22 14:09:05.424486: +2024-11-22 14:09:05.424765: Epoch 5036 +2024-11-22 14:09:05.424880: Current learning rate: 0.00409 +2024-11-22 14:09:23.375517: train_loss -0.8029 +2024-11-22 14:09:23.375738: val_loss -0.7472 +2024-11-22 14:09:23.375816: Pseudo dice [0.8392] +2024-11-22 14:09:23.375891: Epoch time: 17.95 s +2024-11-22 14:09:24.276578: +2024-11-22 14:09:24.276775: Epoch 5037 +2024-11-22 14:09:24.276889: Current learning rate: 0.00409 +2024-11-22 14:09:43.186925: train_loss -0.7985 +2024-11-22 14:09:43.187155: val_loss -0.7557 +2024-11-22 14:09:43.189412: Pseudo dice [0.8454] +2024-11-22 14:09:43.189570: Epoch time: 18.91 s +2024-11-22 14:09:44.104890: +2024-11-22 14:09:44.105112: Epoch 5038 +2024-11-22 14:09:44.105228: Current learning rate: 0.00409 +2024-11-22 14:10:01.657974: train_loss -0.8021 +2024-11-22 14:10:01.658257: val_loss -0.7384 +2024-11-22 14:10:01.658334: Pseudo dice [0.8389] +2024-11-22 14:10:01.658423: Epoch time: 17.55 s +2024-11-22 14:10:02.742539: +2024-11-22 14:10:02.742758: Epoch 5039 +2024-11-22 14:10:02.742867: Current learning rate: 0.00409 +2024-11-22 14:10:21.083618: train_loss -0.8076 +2024-11-22 14:10:21.083827: val_loss -0.7504 +2024-11-22 14:10:21.083901: Pseudo dice [0.8638] +2024-11-22 14:10:21.083976: Epoch time: 18.34 s +2024-11-22 14:10:22.410172: +2024-11-22 14:10:22.410412: Epoch 5040 +2024-11-22 14:10:22.410526: Current learning rate: 0.00409 +2024-11-22 14:10:41.270649: train_loss -0.8006 +2024-11-22 14:10:41.270875: val_loss -0.7627 +2024-11-22 14:10:41.270952: Pseudo dice [0.8539] +2024-11-22 14:10:41.271050: Epoch time: 18.86 s +2024-11-22 14:10:42.154456: +2024-11-22 14:10:42.154750: Epoch 5041 +2024-11-22 14:10:42.154863: Current learning rate: 0.00409 +2024-11-22 14:11:00.874818: train_loss -0.8007 +2024-11-22 14:11:00.875141: val_loss -0.7489 +2024-11-22 14:11:00.875225: Pseudo dice [0.8251] +2024-11-22 14:11:00.875314: Epoch time: 18.72 s +2024-11-22 14:11:01.770271: +2024-11-22 14:11:01.770483: Epoch 5042 +2024-11-22 14:11:01.770598: Current learning rate: 0.00408 +2024-11-22 14:11:20.851027: train_loss -0.7932 +2024-11-22 14:11:20.851296: val_loss -0.7286 +2024-11-22 14:11:20.851659: Pseudo dice [0.8365] +2024-11-22 14:11:20.851745: Epoch time: 19.08 s +2024-11-22 14:11:21.736335: +2024-11-22 14:11:21.736599: Epoch 5043 +2024-11-22 14:11:21.736713: Current learning rate: 0.00408 +2024-11-22 14:11:41.281516: train_loss -0.806 +2024-11-22 14:11:41.281734: val_loss -0.7757 +2024-11-22 14:11:41.281810: Pseudo dice [0.8471] +2024-11-22 14:11:41.281885: Epoch time: 19.55 s +2024-11-22 14:11:42.172453: +2024-11-22 14:11:42.172686: Epoch 5044 +2024-11-22 14:11:42.172802: Current learning rate: 0.00408 +2024-11-22 14:12:00.712628: train_loss -0.7912 +2024-11-22 14:12:00.712859: val_loss -0.7609 +2024-11-22 14:12:00.712932: Pseudo dice [0.8318] +2024-11-22 14:12:00.713016: Epoch time: 18.54 s +2024-11-22 14:12:01.606855: +2024-11-22 14:12:01.607222: Epoch 5045 +2024-11-22 14:12:01.607339: Current learning rate: 0.00408 +2024-11-22 14:12:19.628245: train_loss -0.7999 +2024-11-22 14:12:19.628466: val_loss -0.7312 +2024-11-22 14:12:19.628542: Pseudo dice [0.8385] +2024-11-22 14:12:19.628621: Epoch time: 18.02 s +2024-11-22 14:12:20.518284: +2024-11-22 14:12:20.518483: Epoch 5046 +2024-11-22 14:12:20.518596: Current learning rate: 0.00408 +2024-11-22 14:12:39.001959: train_loss -0.7987 +2024-11-22 14:12:39.002306: val_loss -0.7587 +2024-11-22 14:12:39.002397: Pseudo dice [0.8367] +2024-11-22 14:12:39.002493: Epoch time: 18.48 s +2024-11-22 14:12:39.905754: +2024-11-22 14:12:39.905963: Epoch 5047 +2024-11-22 14:12:39.906082: Current learning rate: 0.00408 +2024-11-22 14:12:58.517510: train_loss -0.8005 +2024-11-22 14:12:58.517717: val_loss -0.7689 +2024-11-22 14:12:58.517795: Pseudo dice [0.8545] +2024-11-22 14:12:58.517870: Epoch time: 18.61 s +2024-11-22 14:12:59.499388: +2024-11-22 14:12:59.499617: Epoch 5048 +2024-11-22 14:12:59.499732: Current learning rate: 0.00408 +2024-11-22 14:13:17.633074: train_loss -0.7996 +2024-11-22 14:13:17.633347: val_loss -0.765 +2024-11-22 14:13:17.633455: Pseudo dice [0.8714] +2024-11-22 14:13:17.633533: Epoch time: 18.13 s +2024-11-22 14:13:18.529241: +2024-11-22 14:13:18.529459: Epoch 5049 +2024-11-22 14:13:18.529573: Current learning rate: 0.00408 +2024-11-22 14:13:37.385293: train_loss -0.8003 +2024-11-22 14:13:37.385512: val_loss -0.7463 +2024-11-22 14:13:37.385585: Pseudo dice [0.8301] +2024-11-22 14:13:37.385664: Epoch time: 18.86 s +2024-11-22 14:13:38.545664: +2024-11-22 14:13:38.545876: Epoch 5050 +2024-11-22 14:13:38.545998: Current learning rate: 0.00407 +2024-11-22 14:13:57.789557: train_loss -0.806 +2024-11-22 14:13:57.789797: val_loss -0.7478 +2024-11-22 14:13:57.789871: Pseudo dice [0.8577] +2024-11-22 14:13:57.789950: Epoch time: 19.24 s +2024-11-22 14:13:58.671451: +2024-11-22 14:13:58.671736: Epoch 5051 +2024-11-22 14:13:58.671855: Current learning rate: 0.00407 +2024-11-22 14:14:16.143349: train_loss -0.7989 +2024-11-22 14:14:16.143582: val_loss -0.7703 +2024-11-22 14:14:16.143661: Pseudo dice [0.8685] +2024-11-22 14:14:16.143736: Epoch time: 17.47 s +2024-11-22 14:14:17.017326: +2024-11-22 14:14:17.017535: Epoch 5052 +2024-11-22 14:14:17.017650: Current learning rate: 0.00407 +2024-11-22 14:14:35.731138: train_loss -0.7987 +2024-11-22 14:14:35.731366: val_loss -0.7718 +2024-11-22 14:14:35.731442: Pseudo dice [0.8543] +2024-11-22 14:14:35.731522: Epoch time: 18.71 s +2024-11-22 14:14:36.627445: +2024-11-22 14:14:36.627650: Epoch 5053 +2024-11-22 14:14:36.627759: Current learning rate: 0.00407 +2024-11-22 14:14:56.250206: train_loss -0.8006 +2024-11-22 14:14:56.250516: val_loss -0.7635 +2024-11-22 14:14:56.250598: Pseudo dice [0.8372] +2024-11-22 14:14:56.250681: Epoch time: 19.62 s +2024-11-22 14:14:57.165626: +2024-11-22 14:14:57.165848: Epoch 5054 +2024-11-22 14:14:57.165963: Current learning rate: 0.00407 +2024-11-22 14:15:15.306143: train_loss -0.794 +2024-11-22 14:15:15.306368: val_loss -0.7538 +2024-11-22 14:15:15.306506: Pseudo dice [0.8465] +2024-11-22 14:15:15.306587: Epoch time: 18.14 s +2024-11-22 14:15:16.198392: +2024-11-22 14:15:16.198599: Epoch 5055 +2024-11-22 14:15:16.198714: Current learning rate: 0.00407 +2024-11-22 14:15:35.101169: train_loss -0.7473 +2024-11-22 14:15:35.101398: val_loss -0.7126 +2024-11-22 14:15:35.101482: Pseudo dice [0.8272] +2024-11-22 14:15:35.101560: Epoch time: 18.9 s +2024-11-22 14:15:35.994528: +2024-11-22 14:15:35.994756: Epoch 5056 +2024-11-22 14:15:35.994873: Current learning rate: 0.00407 +2024-11-22 14:15:56.116299: train_loss -0.759 +2024-11-22 14:15:56.116521: val_loss -0.7233 +2024-11-22 14:15:56.121734: Pseudo dice [0.8397] +2024-11-22 14:15:56.121916: Epoch time: 20.12 s +2024-11-22 14:15:57.074669: +2024-11-22 14:15:57.074888: Epoch 5057 +2024-11-22 14:15:57.075008: Current learning rate: 0.00407 +2024-11-22 14:16:17.456497: train_loss -0.7634 +2024-11-22 14:16:17.456752: val_loss -0.7615 +2024-11-22 14:16:17.456830: Pseudo dice [0.8403] +2024-11-22 14:16:17.462170: Epoch time: 20.38 s +2024-11-22 14:16:18.549877: +2024-11-22 14:16:18.550104: Epoch 5058 +2024-11-22 14:16:18.550221: Current learning rate: 0.00406 +2024-11-22 14:16:36.874920: train_loss -0.7704 +2024-11-22 14:16:36.875148: val_loss -0.7442 +2024-11-22 14:16:36.875224: Pseudo dice [0.8364] +2024-11-22 14:16:36.875299: Epoch time: 18.33 s +2024-11-22 14:16:37.853775: +2024-11-22 14:16:37.853971: Epoch 5059 +2024-11-22 14:16:37.854092: Current learning rate: 0.00406 +2024-11-22 14:16:56.170050: train_loss -0.7803 +2024-11-22 14:16:56.172481: val_loss -0.7542 +2024-11-22 14:16:56.172618: Pseudo dice [0.856] +2024-11-22 14:16:56.172698: Epoch time: 18.32 s +2024-11-22 14:16:57.281356: +2024-11-22 14:16:57.281565: Epoch 5060 +2024-11-22 14:16:57.281679: Current learning rate: 0.00406 +2024-11-22 14:17:15.644908: train_loss -0.7998 +2024-11-22 14:17:15.645188: val_loss -0.7724 +2024-11-22 14:17:15.645268: Pseudo dice [0.8473] +2024-11-22 14:17:15.645349: Epoch time: 18.36 s +2024-11-22 14:17:16.548111: +2024-11-22 14:17:16.548429: Epoch 5061 +2024-11-22 14:17:16.548546: Current learning rate: 0.00406 +2024-11-22 14:17:35.665730: train_loss -0.797 +2024-11-22 14:17:35.666000: val_loss -0.7792 +2024-11-22 14:17:35.666076: Pseudo dice [0.8548] +2024-11-22 14:17:35.666160: Epoch time: 19.12 s +2024-11-22 14:17:36.665363: +2024-11-22 14:17:36.665601: Epoch 5062 +2024-11-22 14:17:36.665718: Current learning rate: 0.00406 +2024-11-22 14:17:55.512068: train_loss -0.7721 +2024-11-22 14:17:55.512360: val_loss -0.7585 +2024-11-22 14:17:55.512440: Pseudo dice [0.8103] +2024-11-22 14:17:55.512516: Epoch time: 18.85 s +2024-11-22 14:17:56.785615: +2024-11-22 14:17:56.785888: Epoch 5063 +2024-11-22 14:17:56.786005: Current learning rate: 0.00406 +2024-11-22 14:18:15.954165: train_loss -0.7853 +2024-11-22 14:18:15.954393: val_loss -0.7564 +2024-11-22 14:18:15.954469: Pseudo dice [0.846] +2024-11-22 14:18:15.954549: Epoch time: 19.17 s +2024-11-22 14:18:16.847233: +2024-11-22 14:18:16.847468: Epoch 5064 +2024-11-22 14:18:16.847581: Current learning rate: 0.00406 +2024-11-22 14:18:35.835251: train_loss -0.7937 +2024-11-22 14:18:35.835490: val_loss -0.7643 +2024-11-22 14:18:35.835567: Pseudo dice [0.8468] +2024-11-22 14:18:35.835647: Epoch time: 18.99 s +2024-11-22 14:18:36.762471: +2024-11-22 14:18:36.762731: Epoch 5065 +2024-11-22 14:18:36.762894: Current learning rate: 0.00406 +2024-11-22 14:18:55.659776: train_loss -0.795 +2024-11-22 14:18:55.660032: val_loss -0.7466 +2024-11-22 14:18:55.660114: Pseudo dice [0.8186] +2024-11-22 14:18:55.660195: Epoch time: 18.9 s +2024-11-22 14:18:56.552056: +2024-11-22 14:18:56.552319: Epoch 5066 +2024-11-22 14:18:56.552433: Current learning rate: 0.00405 +2024-11-22 14:19:15.347784: train_loss -0.7715 +2024-11-22 14:19:15.348017: val_loss -0.7538 +2024-11-22 14:19:15.348094: Pseudo dice [0.8458] +2024-11-22 14:19:15.348174: Epoch time: 18.8 s +2024-11-22 14:19:16.248518: +2024-11-22 14:19:16.248745: Epoch 5067 +2024-11-22 14:19:16.248855: Current learning rate: 0.00405 +2024-11-22 14:19:34.128917: train_loss -0.7918 +2024-11-22 14:19:34.129148: val_loss -0.7686 +2024-11-22 14:19:34.129224: Pseudo dice [0.8485] +2024-11-22 14:19:34.129307: Epoch time: 17.88 s +2024-11-22 14:19:35.024598: +2024-11-22 14:19:35.024805: Epoch 5068 +2024-11-22 14:19:35.024922: Current learning rate: 0.00405 +2024-11-22 14:19:53.823979: train_loss -0.7922 +2024-11-22 14:19:53.824214: val_loss -0.7497 +2024-11-22 14:19:53.824658: Pseudo dice [0.8257] +2024-11-22 14:19:53.824752: Epoch time: 18.8 s +2024-11-22 14:19:54.721342: +2024-11-22 14:19:54.721565: Epoch 5069 +2024-11-22 14:19:54.721690: Current learning rate: 0.00405 +2024-11-22 14:20:13.428026: train_loss -0.8028 +2024-11-22 14:20:13.428276: val_loss -0.7405 +2024-11-22 14:20:13.428349: Pseudo dice [0.8506] +2024-11-22 14:20:13.428429: Epoch time: 18.71 s +2024-11-22 14:20:14.320890: +2024-11-22 14:20:14.321155: Epoch 5070 +2024-11-22 14:20:14.321267: Current learning rate: 0.00405 +2024-11-22 14:20:33.597738: train_loss -0.794 +2024-11-22 14:20:33.597957: val_loss -0.7714 +2024-11-22 14:20:33.598047: Pseudo dice [0.8682] +2024-11-22 14:20:33.598128: Epoch time: 19.28 s +2024-11-22 14:20:34.602261: +2024-11-22 14:20:34.602484: Epoch 5071 +2024-11-22 14:20:34.602599: Current learning rate: 0.00405 +2024-11-22 14:20:53.250974: train_loss -0.796 +2024-11-22 14:20:53.251207: val_loss -0.7438 +2024-11-22 14:20:53.251283: Pseudo dice [0.8381] +2024-11-22 14:20:53.251359: Epoch time: 18.65 s +2024-11-22 14:20:54.144486: +2024-11-22 14:20:54.144680: Epoch 5072 +2024-11-22 14:20:54.144786: Current learning rate: 0.00405 +2024-11-22 14:21:12.268258: train_loss -0.8021 +2024-11-22 14:21:12.268476: val_loss -0.7426 +2024-11-22 14:21:12.268549: Pseudo dice [0.8362] +2024-11-22 14:21:12.268629: Epoch time: 18.12 s +2024-11-22 14:21:13.198813: +2024-11-22 14:21:13.199015: Epoch 5073 +2024-11-22 14:21:13.199133: Current learning rate: 0.00405 +2024-11-22 14:21:31.363563: train_loss -0.7943 +2024-11-22 14:21:31.363802: val_loss -0.7533 +2024-11-22 14:21:31.363880: Pseudo dice [0.8333] +2024-11-22 14:21:31.363965: Epoch time: 18.17 s +2024-11-22 14:21:32.251026: +2024-11-22 14:21:32.251225: Epoch 5074 +2024-11-22 14:21:32.251336: Current learning rate: 0.00404 +2024-11-22 14:21:50.346509: train_loss -0.7922 +2024-11-22 14:21:50.346744: val_loss -0.73 +2024-11-22 14:21:50.346823: Pseudo dice [0.8403] +2024-11-22 14:21:50.346905: Epoch time: 18.1 s +2024-11-22 14:21:51.664389: +2024-11-22 14:21:51.664810: Epoch 5075 +2024-11-22 14:21:51.664942: Current learning rate: 0.00404 +2024-11-22 14:22:10.824084: train_loss -0.7915 +2024-11-22 14:22:10.824341: val_loss -0.7472 +2024-11-22 14:22:10.824418: Pseudo dice [0.854] +2024-11-22 14:22:10.824502: Epoch time: 19.16 s +2024-11-22 14:22:11.714226: +2024-11-22 14:22:11.714658: Epoch 5076 +2024-11-22 14:22:11.714787: Current learning rate: 0.00404 +2024-11-22 14:22:30.691527: train_loss -0.8024 +2024-11-22 14:22:30.691781: val_loss -0.7605 +2024-11-22 14:22:30.691861: Pseudo dice [0.8498] +2024-11-22 14:22:30.691957: Epoch time: 18.98 s +2024-11-22 14:22:31.683788: +2024-11-22 14:22:31.684273: Epoch 5077 +2024-11-22 14:22:31.684402: Current learning rate: 0.00404 +2024-11-22 14:22:49.802189: train_loss -0.7944 +2024-11-22 14:22:49.802418: val_loss -0.7454 +2024-11-22 14:22:49.802500: Pseudo dice [0.8168] +2024-11-22 14:22:49.802577: Epoch time: 18.12 s +2024-11-22 14:22:50.730267: +2024-11-22 14:22:50.730735: Epoch 5078 +2024-11-22 14:22:50.730867: Current learning rate: 0.00404 +2024-11-22 14:23:08.979866: train_loss -0.7876 +2024-11-22 14:23:08.980101: val_loss -0.7603 +2024-11-22 14:23:08.980178: Pseudo dice [0.8314] +2024-11-22 14:23:08.980255: Epoch time: 18.25 s +2024-11-22 14:23:09.873223: +2024-11-22 14:23:09.873709: Epoch 5079 +2024-11-22 14:23:09.873848: Current learning rate: 0.00404 +2024-11-22 14:23:28.375478: train_loss -0.8023 +2024-11-22 14:23:28.375691: val_loss -0.7323 +2024-11-22 14:23:28.375763: Pseudo dice [0.8343] +2024-11-22 14:23:28.375837: Epoch time: 18.5 s +2024-11-22 14:23:29.272717: +2024-11-22 14:23:29.273141: Epoch 5080 +2024-11-22 14:23:29.273270: Current learning rate: 0.00404 +2024-11-22 14:23:48.632601: train_loss -0.7977 +2024-11-22 14:23:48.635077: val_loss -0.766 +2024-11-22 14:23:48.635210: Pseudo dice [0.8546] +2024-11-22 14:23:48.635299: Epoch time: 19.36 s +2024-11-22 14:23:49.641010: +2024-11-22 14:23:49.641430: Epoch 5081 +2024-11-22 14:23:49.641564: Current learning rate: 0.00404 +2024-11-22 14:24:09.033534: train_loss -0.8001 +2024-11-22 14:24:09.033775: val_loss -0.7568 +2024-11-22 14:24:09.033853: Pseudo dice [0.8435] +2024-11-22 14:24:09.033977: Epoch time: 19.39 s +2024-11-22 14:24:09.921216: +2024-11-22 14:24:09.921678: Epoch 5082 +2024-11-22 14:24:09.921813: Current learning rate: 0.00403 +2024-11-22 14:24:28.225384: train_loss -0.8073 +2024-11-22 14:24:28.225592: val_loss -0.7627 +2024-11-22 14:24:28.225666: Pseudo dice [0.8571] +2024-11-22 14:24:28.225738: Epoch time: 18.3 s +2024-11-22 14:24:29.114231: +2024-11-22 14:24:29.114652: Epoch 5083 +2024-11-22 14:24:29.114789: Current learning rate: 0.00403 +2024-11-22 14:24:49.103080: train_loss -0.804 +2024-11-22 14:24:49.103296: val_loss -0.742 +2024-11-22 14:24:49.103368: Pseudo dice [0.8594] +2024-11-22 14:24:49.103445: Epoch time: 19.99 s +2024-11-22 14:24:49.995943: +2024-11-22 14:24:49.996361: Epoch 5084 +2024-11-22 14:24:49.996494: Current learning rate: 0.00403 +2024-11-22 14:25:07.305473: train_loss -0.8079 +2024-11-22 14:25:07.305724: val_loss -0.7475 +2024-11-22 14:25:07.305802: Pseudo dice [0.8338] +2024-11-22 14:25:07.305887: Epoch time: 17.31 s +2024-11-22 14:25:08.200937: +2024-11-22 14:25:08.201383: Epoch 5085 +2024-11-22 14:25:08.201518: Current learning rate: 0.00403 +2024-11-22 14:25:26.162642: train_loss -0.798 +2024-11-22 14:25:26.162874: val_loss -0.7771 +2024-11-22 14:25:26.162951: Pseudo dice [0.8463] +2024-11-22 14:25:26.163039: Epoch time: 17.96 s +2024-11-22 14:25:27.053114: +2024-11-22 14:25:27.053324: Epoch 5086 +2024-11-22 14:25:27.053439: Current learning rate: 0.00403 +2024-11-22 14:25:45.700214: train_loss -0.8002 +2024-11-22 14:25:45.700459: val_loss -0.7562 +2024-11-22 14:25:45.700536: Pseudo dice [0.8217] +2024-11-22 14:25:45.700621: Epoch time: 18.65 s +2024-11-22 14:25:47.035988: +2024-11-22 14:25:47.036209: Epoch 5087 +2024-11-22 14:25:47.036321: Current learning rate: 0.00403 +2024-11-22 14:26:07.003067: train_loss -0.8068 +2024-11-22 14:26:07.003320: val_loss -0.7416 +2024-11-22 14:26:07.003408: Pseudo dice [0.8331] +2024-11-22 14:26:07.003499: Epoch time: 19.97 s +2024-11-22 14:26:07.893958: +2024-11-22 14:26:07.894248: Epoch 5088 +2024-11-22 14:26:07.894365: Current learning rate: 0.00403 +2024-11-22 14:26:27.444150: train_loss -0.7789 +2024-11-22 14:26:27.444372: val_loss -0.7363 +2024-11-22 14:26:27.444447: Pseudo dice [0.8374] +2024-11-22 14:26:27.444530: Epoch time: 19.55 s +2024-11-22 14:26:28.333483: +2024-11-22 14:26:28.333698: Epoch 5089 +2024-11-22 14:26:28.333812: Current learning rate: 0.00403 +2024-11-22 14:26:47.445625: train_loss -0.7544 +2024-11-22 14:26:47.445859: val_loss -0.7157 +2024-11-22 14:26:47.445937: Pseudo dice [0.8212] +2024-11-22 14:26:47.446020: Epoch time: 19.11 s +2024-11-22 14:26:48.364799: +2024-11-22 14:26:48.365015: Epoch 5090 +2024-11-22 14:26:48.365124: Current learning rate: 0.00402 +2024-11-22 14:27:06.550135: train_loss -0.7817 +2024-11-22 14:27:06.550385: val_loss -0.7653 +2024-11-22 14:27:06.550465: Pseudo dice [0.8529] +2024-11-22 14:27:06.550550: Epoch time: 18.19 s +2024-11-22 14:27:07.442016: +2024-11-22 14:27:07.442239: Epoch 5091 +2024-11-22 14:27:07.442354: Current learning rate: 0.00402 +2024-11-22 14:27:24.792213: train_loss -0.787 +2024-11-22 14:27:24.792434: val_loss -0.72 +2024-11-22 14:27:24.792513: Pseudo dice [0.8474] +2024-11-22 14:27:24.792592: Epoch time: 17.35 s +2024-11-22 14:27:25.697175: +2024-11-22 14:27:25.697397: Epoch 5092 +2024-11-22 14:27:25.697513: Current learning rate: 0.00402 +2024-11-22 14:27:44.388816: train_loss -0.8005 +2024-11-22 14:27:44.389043: val_loss -0.7693 +2024-11-22 14:27:44.389121: Pseudo dice [0.8478] +2024-11-22 14:27:44.389199: Epoch time: 18.69 s +2024-11-22 14:27:45.283688: +2024-11-22 14:27:45.283908: Epoch 5093 +2024-11-22 14:27:45.284024: Current learning rate: 0.00402 +2024-11-22 14:28:04.648044: train_loss -0.795 +2024-11-22 14:28:04.648259: val_loss -0.7336 +2024-11-22 14:28:04.648334: Pseudo dice [0.8469] +2024-11-22 14:28:04.648412: Epoch time: 19.37 s +2024-11-22 14:28:05.545271: +2024-11-22 14:28:05.545462: Epoch 5094 +2024-11-22 14:28:05.545574: Current learning rate: 0.00402 +2024-11-22 14:28:25.981266: train_loss -0.7974 +2024-11-22 14:28:25.981814: val_loss -0.7386 +2024-11-22 14:28:25.981905: Pseudo dice [0.8402] +2024-11-22 14:28:25.982023: Epoch time: 20.44 s +2024-11-22 14:28:26.880301: +2024-11-22 14:28:26.880495: Epoch 5095 +2024-11-22 14:28:26.880607: Current learning rate: 0.00402 +2024-11-22 14:28:44.931059: train_loss -0.7962 +2024-11-22 14:28:44.931315: val_loss -0.7537 +2024-11-22 14:28:44.931403: Pseudo dice [0.832] +2024-11-22 14:28:44.931479: Epoch time: 18.05 s +2024-11-22 14:28:45.824582: +2024-11-22 14:28:45.824864: Epoch 5096 +2024-11-22 14:28:45.824978: Current learning rate: 0.00402 +2024-11-22 14:29:03.860805: train_loss -0.795 +2024-11-22 14:29:03.861021: val_loss -0.7594 +2024-11-22 14:29:03.861094: Pseudo dice [0.8621] +2024-11-22 14:29:03.861169: Epoch time: 18.04 s +2024-11-22 14:29:04.906588: +2024-11-22 14:29:04.906802: Epoch 5097 +2024-11-22 14:29:04.906921: Current learning rate: 0.00402 +2024-11-22 14:29:23.607260: train_loss -0.803 +2024-11-22 14:29:23.607472: val_loss -0.7545 +2024-11-22 14:29:23.607549: Pseudo dice [0.8566] +2024-11-22 14:29:23.607629: Epoch time: 18.7 s +2024-11-22 14:29:24.484927: +2024-11-22 14:29:24.485160: Epoch 5098 +2024-11-22 14:29:24.485282: Current learning rate: 0.00401 +2024-11-22 14:29:42.932889: train_loss -0.8081 +2024-11-22 14:29:42.938350: val_loss -0.7577 +2024-11-22 14:29:42.938492: Pseudo dice [0.8236] +2024-11-22 14:29:42.938591: Epoch time: 18.45 s +2024-11-22 14:29:44.272798: +2024-11-22 14:29:44.273022: Epoch 5099 +2024-11-22 14:29:44.273137: Current learning rate: 0.00401 +2024-11-22 14:30:02.682760: train_loss -0.8052 +2024-11-22 14:30:02.685188: val_loss -0.7396 +2024-11-22 14:30:02.685316: Pseudo dice [0.8361] +2024-11-22 14:30:02.685398: Epoch time: 18.41 s +2024-11-22 14:30:03.914958: +2024-11-22 14:30:03.915178: Epoch 5100 +2024-11-22 14:30:03.915287: Current learning rate: 0.00401 +2024-11-22 14:30:22.008867: train_loss -0.8069 +2024-11-22 14:30:22.009095: val_loss -0.7559 +2024-11-22 14:30:22.009172: Pseudo dice [0.8428] +2024-11-22 14:30:22.009250: Epoch time: 18.09 s +2024-11-22 14:30:22.895878: +2024-11-22 14:30:22.896149: Epoch 5101 +2024-11-22 14:30:22.896262: Current learning rate: 0.00401 +2024-11-22 14:30:42.308693: train_loss -0.7851 +2024-11-22 14:30:42.308946: val_loss -0.7188 +2024-11-22 14:30:42.309029: Pseudo dice [0.8194] +2024-11-22 14:30:42.309143: Epoch time: 19.41 s +2024-11-22 14:30:43.203271: +2024-11-22 14:30:43.203490: Epoch 5102 +2024-11-22 14:30:43.203603: Current learning rate: 0.00401 +2024-11-22 14:31:02.360690: train_loss -0.7983 +2024-11-22 14:31:02.360912: val_loss -0.77 +2024-11-22 14:31:02.360987: Pseudo dice [0.861] +2024-11-22 14:31:02.361070: Epoch time: 19.16 s +2024-11-22 14:31:03.249896: +2024-11-22 14:31:03.250197: Epoch 5103 +2024-11-22 14:31:03.250385: Current learning rate: 0.00401 +2024-11-22 14:31:22.672340: train_loss -0.7962 +2024-11-22 14:31:22.672575: val_loss -0.73 +2024-11-22 14:31:22.672657: Pseudo dice [0.8419] +2024-11-22 14:31:22.672739: Epoch time: 19.42 s +2024-11-22 14:31:23.629882: +2024-11-22 14:31:23.630099: Epoch 5104 +2024-11-22 14:31:23.630232: Current learning rate: 0.00401 +2024-11-22 14:31:42.632518: train_loss -0.7931 +2024-11-22 14:31:42.632748: val_loss -0.7543 +2024-11-22 14:31:42.635062: Pseudo dice [0.8388] +2024-11-22 14:31:42.635173: Epoch time: 19.0 s +2024-11-22 14:31:43.545382: +2024-11-22 14:31:43.545588: Epoch 5105 +2024-11-22 14:31:43.545702: Current learning rate: 0.00401 +2024-11-22 14:32:02.822150: train_loss -0.796 +2024-11-22 14:32:02.824504: val_loss -0.774 +2024-11-22 14:32:02.824699: Pseudo dice [0.8317] +2024-11-22 14:32:02.824788: Epoch time: 19.28 s +2024-11-22 14:32:03.733086: +2024-11-22 14:32:03.733345: Epoch 5106 +2024-11-22 14:32:03.733461: Current learning rate: 0.004 +2024-11-22 14:32:22.500109: train_loss -0.7939 +2024-11-22 14:32:22.500363: val_loss -0.7514 +2024-11-22 14:32:22.500444: Pseudo dice [0.848] +2024-11-22 14:32:22.500525: Epoch time: 18.77 s +2024-11-22 14:32:23.394918: +2024-11-22 14:32:23.395158: Epoch 5107 +2024-11-22 14:32:23.395273: Current learning rate: 0.004 +2024-11-22 14:32:42.769375: train_loss -0.7994 +2024-11-22 14:32:42.769593: val_loss -0.7449 +2024-11-22 14:32:42.769672: Pseudo dice [0.8496] +2024-11-22 14:32:42.769754: Epoch time: 19.38 s +2024-11-22 14:32:43.717325: +2024-11-22 14:32:43.717577: Epoch 5108 +2024-11-22 14:32:43.717690: Current learning rate: 0.004 +2024-11-22 14:33:02.722233: train_loss -0.7887 +2024-11-22 14:33:02.722476: val_loss -0.7364 +2024-11-22 14:33:02.722557: Pseudo dice [0.8463] +2024-11-22 14:33:02.722639: Epoch time: 19.01 s +2024-11-22 14:33:03.614830: +2024-11-22 14:33:03.615045: Epoch 5109 +2024-11-22 14:33:03.615159: Current learning rate: 0.004 +2024-11-22 14:33:22.598630: train_loss -0.7867 +2024-11-22 14:33:22.601068: val_loss -0.722 +2024-11-22 14:33:22.601169: Pseudo dice [0.815] +2024-11-22 14:33:22.601253: Epoch time: 18.98 s +2024-11-22 14:33:23.736681: +2024-11-22 14:33:23.736907: Epoch 5110 +2024-11-22 14:33:23.737023: Current learning rate: 0.004 +2024-11-22 14:33:42.359846: train_loss -0.7936 +2024-11-22 14:33:42.362238: val_loss -0.7568 +2024-11-22 14:33:42.362342: Pseudo dice [0.8332] +2024-11-22 14:33:42.362424: Epoch time: 18.62 s +2024-11-22 14:33:43.281503: +2024-11-22 14:33:43.281703: Epoch 5111 +2024-11-22 14:33:43.281817: Current learning rate: 0.004 +2024-11-22 14:34:02.427783: train_loss -0.7968 +2024-11-22 14:34:02.428008: val_loss -0.7229 +2024-11-22 14:34:02.428083: Pseudo dice [0.8193] +2024-11-22 14:34:02.428159: Epoch time: 19.15 s +2024-11-22 14:34:03.317842: +2024-11-22 14:34:03.318091: Epoch 5112 +2024-11-22 14:34:03.318206: Current learning rate: 0.004 +2024-11-22 14:34:22.444214: train_loss -0.8007 +2024-11-22 14:34:22.444435: val_loss -0.7607 +2024-11-22 14:34:22.444513: Pseudo dice [0.851] +2024-11-22 14:34:22.444591: Epoch time: 19.13 s +2024-11-22 14:34:23.340069: +2024-11-22 14:34:23.340306: Epoch 5113 +2024-11-22 14:34:23.340421: Current learning rate: 0.004 +2024-11-22 14:34:43.169766: train_loss -0.7928 +2024-11-22 14:34:43.170034: val_loss -0.7385 +2024-11-22 14:34:43.170111: Pseudo dice [0.8479] +2024-11-22 14:34:43.170222: Epoch time: 19.83 s +2024-11-22 14:34:44.065102: +2024-11-22 14:34:44.065308: Epoch 5114 +2024-11-22 14:34:44.065419: Current learning rate: 0.00399 +2024-11-22 14:35:03.959806: train_loss -0.7891 +2024-11-22 14:35:03.960037: val_loss -0.7566 +2024-11-22 14:35:03.960109: Pseudo dice [0.8487] +2024-11-22 14:35:03.960186: Epoch time: 19.9 s +2024-11-22 14:35:04.851605: +2024-11-22 14:35:04.851862: Epoch 5115 +2024-11-22 14:35:04.851988: Current learning rate: 0.00399 +2024-11-22 14:35:23.115236: train_loss -0.7968 +2024-11-22 14:35:23.115448: val_loss -0.763 +2024-11-22 14:35:23.115526: Pseudo dice [0.8505] +2024-11-22 14:35:23.115601: Epoch time: 18.26 s +2024-11-22 14:35:24.004100: +2024-11-22 14:35:24.004444: Epoch 5116 +2024-11-22 14:35:24.004561: Current learning rate: 0.00399 +2024-11-22 14:35:43.393482: train_loss -0.7953 +2024-11-22 14:35:43.393711: val_loss -0.7532 +2024-11-22 14:35:43.399044: Pseudo dice [0.8608] +2024-11-22 14:35:43.399142: Epoch time: 19.39 s +2024-11-22 14:35:44.449591: +2024-11-22 14:35:44.449818: Epoch 5117 +2024-11-22 14:35:44.449931: Current learning rate: 0.00399 +2024-11-22 14:36:02.270634: train_loss -0.7983 +2024-11-22 14:36:02.270865: val_loss -0.7458 +2024-11-22 14:36:02.270938: Pseudo dice [0.8537] +2024-11-22 14:36:02.276182: Epoch time: 17.82 s +2024-11-22 14:36:03.381357: +2024-11-22 14:36:03.381569: Epoch 5118 +2024-11-22 14:36:03.381683: Current learning rate: 0.00399 +2024-11-22 14:36:22.119632: train_loss -0.8046 +2024-11-22 14:36:22.119885: val_loss -0.7632 +2024-11-22 14:36:22.119963: Pseudo dice [0.8378] +2024-11-22 14:36:22.120050: Epoch time: 18.74 s +2024-11-22 14:36:23.004233: +2024-11-22 14:36:23.004430: Epoch 5119 +2024-11-22 14:36:23.004540: Current learning rate: 0.00399 +2024-11-22 14:36:41.614435: train_loss -0.8052 +2024-11-22 14:36:41.614655: val_loss -0.759 +2024-11-22 14:36:41.614729: Pseudo dice [0.8394] +2024-11-22 14:36:41.614810: Epoch time: 18.61 s +2024-11-22 14:36:42.497027: +2024-11-22 14:36:42.497215: Epoch 5120 +2024-11-22 14:36:42.497342: Current learning rate: 0.00399 +2024-11-22 14:37:00.919022: train_loss -0.8007 +2024-11-22 14:37:00.919256: val_loss -0.774 +2024-11-22 14:37:00.924695: Pseudo dice [0.8485] +2024-11-22 14:37:00.924854: Epoch time: 18.42 s +2024-11-22 14:37:01.924619: +2024-11-22 14:37:01.924890: Epoch 5121 +2024-11-22 14:37:01.925010: Current learning rate: 0.00399 +2024-11-22 14:37:20.827849: train_loss -0.7969 +2024-11-22 14:37:20.828075: val_loss -0.7404 +2024-11-22 14:37:20.828153: Pseudo dice [0.845] +2024-11-22 14:37:20.828232: Epoch time: 18.9 s +2024-11-22 14:37:22.125369: +2024-11-22 14:37:22.125685: Epoch 5122 +2024-11-22 14:37:22.125798: Current learning rate: 0.00398 +2024-11-22 14:37:41.305320: train_loss -0.8004 +2024-11-22 14:37:41.305580: val_loss -0.7384 +2024-11-22 14:37:41.305679: Pseudo dice [0.8354] +2024-11-22 14:37:41.305776: Epoch time: 19.18 s +2024-11-22 14:37:42.200168: +2024-11-22 14:37:42.200417: Epoch 5123 +2024-11-22 14:37:42.200527: Current learning rate: 0.00398 +2024-11-22 14:38:01.342189: train_loss -0.7907 +2024-11-22 14:38:01.342438: val_loss -0.734 +2024-11-22 14:38:01.342515: Pseudo dice [0.8291] +2024-11-22 14:38:01.342594: Epoch time: 19.14 s +2024-11-22 14:38:02.239730: +2024-11-22 14:38:02.239964: Epoch 5124 +2024-11-22 14:38:02.240077: Current learning rate: 0.00398 +2024-11-22 14:38:20.757249: train_loss -0.8054 +2024-11-22 14:38:20.757474: val_loss -0.7759 +2024-11-22 14:38:20.757553: Pseudo dice [0.8733] +2024-11-22 14:38:20.757632: Epoch time: 18.52 s +2024-11-22 14:38:21.654890: +2024-11-22 14:38:21.655103: Epoch 5125 +2024-11-22 14:38:21.655212: Current learning rate: 0.00398 +2024-11-22 14:38:39.520592: train_loss -0.8064 +2024-11-22 14:38:39.520858: val_loss -0.7288 +2024-11-22 14:38:39.520951: Pseudo dice [0.8482] +2024-11-22 14:38:39.521077: Epoch time: 17.87 s +2024-11-22 14:38:40.410546: +2024-11-22 14:38:40.410753: Epoch 5126 +2024-11-22 14:38:40.410865: Current learning rate: 0.00398 +2024-11-22 14:38:58.834873: train_loss -0.804 +2024-11-22 14:38:58.835114: val_loss -0.7237 +2024-11-22 14:38:58.835193: Pseudo dice [0.8441] +2024-11-22 14:38:58.835273: Epoch time: 18.43 s +2024-11-22 14:38:59.730320: +2024-11-22 14:38:59.730599: Epoch 5127 +2024-11-22 14:38:59.730706: Current learning rate: 0.00398 +2024-11-22 14:39:19.422601: train_loss -0.8079 +2024-11-22 14:39:19.422822: val_loss -0.7459 +2024-11-22 14:39:19.422897: Pseudo dice [0.8472] +2024-11-22 14:39:19.422972: Epoch time: 19.69 s +2024-11-22 14:39:20.316797: +2024-11-22 14:39:20.317038: Epoch 5128 +2024-11-22 14:39:20.317151: Current learning rate: 0.00398 +2024-11-22 14:39:39.077724: train_loss -0.7977 +2024-11-22 14:39:39.077934: val_loss -0.7443 +2024-11-22 14:39:39.078014: Pseudo dice [0.8637] +2024-11-22 14:39:39.078089: Epoch time: 18.76 s +2024-11-22 14:39:39.954552: +2024-11-22 14:39:39.954782: Epoch 5129 +2024-11-22 14:39:39.954894: Current learning rate: 0.00398 +2024-11-22 14:39:59.185417: train_loss -0.8046 +2024-11-22 14:39:59.185651: val_loss -0.7649 +2024-11-22 14:39:59.185725: Pseudo dice [0.8599] +2024-11-22 14:39:59.185809: Epoch time: 19.23 s +2024-11-22 14:40:00.078501: +2024-11-22 14:40:00.078765: Epoch 5130 +2024-11-22 14:40:00.078882: Current learning rate: 0.00397 +2024-11-22 14:40:19.168286: train_loss -0.8039 +2024-11-22 14:40:19.168555: val_loss -0.7373 +2024-11-22 14:40:19.168636: Pseudo dice [0.8527] +2024-11-22 14:40:19.168716: Epoch time: 19.09 s +2024-11-22 14:40:20.060741: +2024-11-22 14:40:20.061003: Epoch 5131 +2024-11-22 14:40:20.061115: Current learning rate: 0.00397 +2024-11-22 14:40:39.249229: train_loss -0.805 +2024-11-22 14:40:39.249452: val_loss -0.7482 +2024-11-22 14:40:39.249525: Pseudo dice [0.8514] +2024-11-22 14:40:39.249602: Epoch time: 19.19 s +2024-11-22 14:40:40.138489: +2024-11-22 14:40:40.138693: Epoch 5132 +2024-11-22 14:40:40.138805: Current learning rate: 0.00397 +2024-11-22 14:40:59.207591: train_loss -0.7989 +2024-11-22 14:40:59.207818: val_loss -0.749 +2024-11-22 14:40:59.207897: Pseudo dice [0.8426] +2024-11-22 14:40:59.207973: Epoch time: 19.07 s +2024-11-22 14:41:00.097327: +2024-11-22 14:41:00.097522: Epoch 5133 +2024-11-22 14:41:00.097637: Current learning rate: 0.00397 +2024-11-22 14:41:18.484776: train_loss -0.8027 +2024-11-22 14:41:18.485023: val_loss -0.7631 +2024-11-22 14:41:18.485105: Pseudo dice [0.8568] +2024-11-22 14:41:18.485197: Epoch time: 18.39 s +2024-11-22 14:41:19.771316: +2024-11-22 14:41:19.771749: Epoch 5134 +2024-11-22 14:41:19.771881: Current learning rate: 0.00397 +2024-11-22 14:41:37.436535: train_loss -0.7981 +2024-11-22 14:41:37.436744: val_loss -0.7557 +2024-11-22 14:41:37.436820: Pseudo dice [0.8434] +2024-11-22 14:41:37.436896: Epoch time: 17.67 s +2024-11-22 14:41:38.316826: +2024-11-22 14:41:38.317263: Epoch 5135 +2024-11-22 14:41:38.317399: Current learning rate: 0.00397 +2024-11-22 14:41:57.571564: train_loss -0.8044 +2024-11-22 14:41:57.571792: val_loss -0.7665 +2024-11-22 14:41:57.571871: Pseudo dice [0.8756] +2024-11-22 14:41:57.571947: Epoch time: 19.26 s +2024-11-22 14:41:58.467927: +2024-11-22 14:41:58.468543: Epoch 5136 +2024-11-22 14:41:58.468677: Current learning rate: 0.00397 +2024-11-22 14:42:17.921494: train_loss -0.8069 +2024-11-22 14:42:17.921719: val_loss -0.7406 +2024-11-22 14:42:17.921797: Pseudo dice [0.8504] +2024-11-22 14:42:17.921872: Epoch time: 19.45 s +2024-11-22 14:42:18.807155: +2024-11-22 14:42:18.807571: Epoch 5137 +2024-11-22 14:42:18.807703: Current learning rate: 0.00397 +2024-11-22 14:42:37.199329: train_loss -0.8005 +2024-11-22 14:42:37.199580: val_loss -0.7339 +2024-11-22 14:42:37.199656: Pseudo dice [0.8326] +2024-11-22 14:42:37.199741: Epoch time: 18.39 s +2024-11-22 14:42:38.096190: +2024-11-22 14:42:38.096625: Epoch 5138 +2024-11-22 14:42:38.096767: Current learning rate: 0.00396 +2024-11-22 14:42:57.420717: train_loss -0.7975 +2024-11-22 14:42:57.420956: val_loss -0.754 +2024-11-22 14:42:57.421041: Pseudo dice [0.871] +2024-11-22 14:42:57.421118: Epoch time: 19.33 s +2024-11-22 14:42:58.412493: +2024-11-22 14:42:58.412940: Epoch 5139 +2024-11-22 14:42:58.413088: Current learning rate: 0.00396 +2024-11-22 14:43:16.658297: train_loss -0.7985 +2024-11-22 14:43:16.658586: val_loss -0.7521 +2024-11-22 14:43:16.658666: Pseudo dice [0.8659] +2024-11-22 14:43:16.658744: Epoch time: 18.25 s +2024-11-22 14:43:17.648787: +2024-11-22 14:43:17.649224: Epoch 5140 +2024-11-22 14:43:17.649386: Current learning rate: 0.00396 +2024-11-22 14:43:37.137415: train_loss -0.7987 +2024-11-22 14:43:37.137661: val_loss -0.7372 +2024-11-22 14:43:37.137739: Pseudo dice [0.8371] +2024-11-22 14:43:37.137818: Epoch time: 19.49 s +2024-11-22 14:43:38.024239: +2024-11-22 14:43:38.024650: Epoch 5141 +2024-11-22 14:43:38.024786: Current learning rate: 0.00396 +2024-11-22 14:43:56.598296: train_loss -0.7928 +2024-11-22 14:43:56.598539: val_loss -0.7129 +2024-11-22 14:43:56.598611: Pseudo dice [0.8548] +2024-11-22 14:43:56.598692: Epoch time: 18.58 s +2024-11-22 14:43:57.485263: +2024-11-22 14:43:57.485707: Epoch 5142 +2024-11-22 14:43:57.485857: Current learning rate: 0.00396 +2024-11-22 14:44:16.223930: train_loss -0.7956 +2024-11-22 14:44:16.224153: val_loss -0.7313 +2024-11-22 14:44:16.224231: Pseudo dice [0.8543] +2024-11-22 14:44:16.226409: Epoch time: 18.74 s +2024-11-22 14:44:17.163634: +2024-11-22 14:44:17.164032: Epoch 5143 +2024-11-22 14:44:17.164161: Current learning rate: 0.00396 +2024-11-22 14:44:36.128532: train_loss -0.802 +2024-11-22 14:44:36.128748: val_loss -0.7335 +2024-11-22 14:44:36.128821: Pseudo dice [0.8379] +2024-11-22 14:44:36.128897: Epoch time: 18.97 s +2024-11-22 14:44:37.017538: +2024-11-22 14:44:37.017962: Epoch 5144 +2024-11-22 14:44:37.018102: Current learning rate: 0.00396 +2024-11-22 14:44:56.946972: train_loss -0.8074 +2024-11-22 14:44:56.947210: val_loss -0.75 +2024-11-22 14:44:56.947289: Pseudo dice [0.8344] +2024-11-22 14:44:56.947368: Epoch time: 19.93 s +2024-11-22 14:44:57.828498: +2024-11-22 14:44:57.828912: Epoch 5145 +2024-11-22 14:44:57.829050: Current learning rate: 0.00396 +2024-11-22 14:45:16.742856: train_loss -0.7977 +2024-11-22 14:45:16.743191: val_loss -0.7641 +2024-11-22 14:45:16.743271: Pseudo dice [0.8471] +2024-11-22 14:45:16.743361: Epoch time: 18.92 s +2024-11-22 14:45:18.021703: +2024-11-22 14:45:18.021978: Epoch 5146 +2024-11-22 14:45:18.022107: Current learning rate: 0.00395 +2024-11-22 14:45:35.814490: train_loss -0.8014 +2024-11-22 14:45:35.814795: val_loss -0.7636 +2024-11-22 14:45:35.814886: Pseudo dice [0.859] +2024-11-22 14:45:35.814963: Epoch time: 17.79 s +2024-11-22 14:45:36.705458: +2024-11-22 14:45:36.705680: Epoch 5147 +2024-11-22 14:45:36.705795: Current learning rate: 0.00395 +2024-11-22 14:45:55.061652: train_loss -0.8041 +2024-11-22 14:45:55.061887: val_loss -0.7427 +2024-11-22 14:45:55.061964: Pseudo dice [0.836] +2024-11-22 14:45:55.062044: Epoch time: 18.36 s +2024-11-22 14:45:55.954382: +2024-11-22 14:45:55.954589: Epoch 5148 +2024-11-22 14:45:55.954700: Current learning rate: 0.00395 +2024-11-22 14:46:14.689086: train_loss -0.7921 +2024-11-22 14:46:14.689338: val_loss -0.7437 +2024-11-22 14:46:14.689420: Pseudo dice [0.8567] +2024-11-22 14:46:14.689506: Epoch time: 18.74 s +2024-11-22 14:46:15.586533: +2024-11-22 14:46:15.586769: Epoch 5149 +2024-11-22 14:46:15.586887: Current learning rate: 0.00395 +2024-11-22 14:46:34.658306: train_loss -0.8042 +2024-11-22 14:46:34.658518: val_loss -0.7537 +2024-11-22 14:46:34.658595: Pseudo dice [0.8576] +2024-11-22 14:46:34.658672: Epoch time: 19.07 s +2024-11-22 14:46:35.856480: +2024-11-22 14:46:35.856750: Epoch 5150 +2024-11-22 14:46:35.856866: Current learning rate: 0.00395 +2024-11-22 14:46:54.316307: train_loss -0.7948 +2024-11-22 14:46:54.316530: val_loss -0.7317 +2024-11-22 14:46:54.316697: Pseudo dice [0.8367] +2024-11-22 14:46:54.316782: Epoch time: 18.46 s +2024-11-22 14:46:55.205097: +2024-11-22 14:46:55.205301: Epoch 5151 +2024-11-22 14:46:55.205417: Current learning rate: 0.00395 +2024-11-22 14:47:12.506974: train_loss -0.8013 +2024-11-22 14:47:12.507210: val_loss -0.736 +2024-11-22 14:47:12.507289: Pseudo dice [0.8347] +2024-11-22 14:47:12.507380: Epoch time: 17.3 s +2024-11-22 14:47:13.394035: +2024-11-22 14:47:13.394361: Epoch 5152 +2024-11-22 14:47:13.394473: Current learning rate: 0.00395 +2024-11-22 14:47:31.458806: train_loss -0.8008 +2024-11-22 14:47:31.459031: val_loss -0.7345 +2024-11-22 14:47:31.459109: Pseudo dice [0.831] +2024-11-22 14:47:31.459188: Epoch time: 18.07 s +2024-11-22 14:47:32.381495: +2024-11-22 14:47:32.381734: Epoch 5153 +2024-11-22 14:47:32.381847: Current learning rate: 0.00395 +2024-11-22 14:47:51.908068: train_loss -0.7926 +2024-11-22 14:47:51.908294: val_loss -0.7571 +2024-11-22 14:47:51.908367: Pseudo dice [0.8521] +2024-11-22 14:47:51.908448: Epoch time: 19.53 s +2024-11-22 14:47:52.834386: +2024-11-22 14:47:52.834602: Epoch 5154 +2024-11-22 14:47:52.834714: Current learning rate: 0.00394 +2024-11-22 14:48:11.734039: train_loss -0.8044 +2024-11-22 14:48:11.734255: val_loss -0.7616 +2024-11-22 14:48:11.734329: Pseudo dice [0.8356] +2024-11-22 14:48:11.734405: Epoch time: 18.9 s +2024-11-22 14:48:12.624871: +2024-11-22 14:48:12.625067: Epoch 5155 +2024-11-22 14:48:12.625188: Current learning rate: 0.00394 +2024-11-22 14:48:30.868788: train_loss -0.8013 +2024-11-22 14:48:30.869024: val_loss -0.762 +2024-11-22 14:48:30.869099: Pseudo dice [0.8712] +2024-11-22 14:48:30.869175: Epoch time: 18.24 s +2024-11-22 14:48:31.815289: +2024-11-22 14:48:31.815485: Epoch 5156 +2024-11-22 14:48:31.815596: Current learning rate: 0.00394 +2024-11-22 14:48:50.062104: train_loss -0.8013 +2024-11-22 14:48:50.062412: val_loss -0.75 +2024-11-22 14:48:50.062492: Pseudo dice [0.8354] +2024-11-22 14:48:50.062583: Epoch time: 18.25 s +2024-11-22 14:48:50.956484: +2024-11-22 14:48:50.956672: Epoch 5157 +2024-11-22 14:48:50.956785: Current learning rate: 0.00394 +2024-11-22 14:49:09.653471: train_loss -0.7943 +2024-11-22 14:49:09.653722: val_loss -0.758 +2024-11-22 14:49:09.653799: Pseudo dice [0.8588] +2024-11-22 14:49:09.653877: Epoch time: 18.7 s +2024-11-22 14:49:10.642497: +2024-11-22 14:49:10.642749: Epoch 5158 +2024-11-22 14:49:10.642861: Current learning rate: 0.00394 +2024-11-22 14:49:29.212471: train_loss -0.7961 +2024-11-22 14:49:29.212689: val_loss -0.7551 +2024-11-22 14:49:29.212761: Pseudo dice [0.8476] +2024-11-22 14:49:29.215363: Epoch time: 18.57 s +2024-11-22 14:49:30.283317: +2024-11-22 14:49:30.283550: Epoch 5159 +2024-11-22 14:49:30.283667: Current learning rate: 0.00394 +2024-11-22 14:49:48.823382: train_loss -0.786 +2024-11-22 14:49:48.823596: val_loss -0.7465 +2024-11-22 14:49:48.823668: Pseudo dice [0.8377] +2024-11-22 14:49:48.823752: Epoch time: 18.54 s +2024-11-22 14:49:49.713590: +2024-11-22 14:49:49.713811: Epoch 5160 +2024-11-22 14:49:49.713924: Current learning rate: 0.00394 +2024-11-22 14:50:08.337020: train_loss -0.7975 +2024-11-22 14:50:08.337280: val_loss -0.7168 +2024-11-22 14:50:08.337357: Pseudo dice [0.806] +2024-11-22 14:50:08.337437: Epoch time: 18.62 s +2024-11-22 14:50:09.228166: +2024-11-22 14:50:09.228382: Epoch 5161 +2024-11-22 14:50:09.228499: Current learning rate: 0.00394 +2024-11-22 14:50:28.700774: train_loss -0.7904 +2024-11-22 14:50:28.700985: val_loss -0.7489 +2024-11-22 14:50:28.701070: Pseudo dice [0.8493] +2024-11-22 14:50:28.701150: Epoch time: 19.47 s +2024-11-22 14:50:29.719895: +2024-11-22 14:50:29.720137: Epoch 5162 +2024-11-22 14:50:29.720251: Current learning rate: 0.00393 +2024-11-22 14:50:48.771880: train_loss -0.8011 +2024-11-22 14:50:48.772142: val_loss -0.7956 +2024-11-22 14:50:48.772218: Pseudo dice [0.8604] +2024-11-22 14:50:48.772297: Epoch time: 19.05 s +2024-11-22 14:50:49.658486: +2024-11-22 14:50:49.658778: Epoch 5163 +2024-11-22 14:50:49.658890: Current learning rate: 0.00393 +2024-11-22 14:51:08.458694: train_loss -0.8043 +2024-11-22 14:51:08.458995: val_loss -0.7692 +2024-11-22 14:51:08.459075: Pseudo dice [0.8451] +2024-11-22 14:51:08.459153: Epoch time: 18.8 s +2024-11-22 14:51:09.332620: +2024-11-22 14:51:09.332827: Epoch 5164 +2024-11-22 14:51:09.332938: Current learning rate: 0.00393 +2024-11-22 14:51:28.249167: train_loss -0.8054 +2024-11-22 14:51:28.249421: val_loss -0.7348 +2024-11-22 14:51:28.249496: Pseudo dice [0.8354] +2024-11-22 14:51:28.249578: Epoch time: 18.92 s +2024-11-22 14:51:29.207762: +2024-11-22 14:51:29.207954: Epoch 5165 +2024-11-22 14:51:29.208074: Current learning rate: 0.00393 +2024-11-22 14:51:49.002386: train_loss -0.7914 +2024-11-22 14:51:49.002596: val_loss -0.7364 +2024-11-22 14:51:49.002674: Pseudo dice [0.8576] +2024-11-22 14:51:49.002752: Epoch time: 19.8 s +2024-11-22 14:51:49.905122: +2024-11-22 14:51:49.905352: Epoch 5166 +2024-11-22 14:51:49.905465: Current learning rate: 0.00393 +2024-11-22 14:52:08.154983: train_loss -0.7889 +2024-11-22 14:52:08.155211: val_loss -0.7403 +2024-11-22 14:52:08.155287: Pseudo dice [0.8194] +2024-11-22 14:52:08.155363: Epoch time: 18.25 s +2024-11-22 14:52:09.186787: +2024-11-22 14:52:09.187013: Epoch 5167 +2024-11-22 14:52:09.187125: Current learning rate: 0.00393 +2024-11-22 14:52:28.594977: train_loss -0.7893 +2024-11-22 14:52:28.595193: val_loss -0.7348 +2024-11-22 14:52:28.595271: Pseudo dice [0.8425] +2024-11-22 14:52:28.595374: Epoch time: 19.41 s +2024-11-22 14:52:29.483230: +2024-11-22 14:52:29.483421: Epoch 5168 +2024-11-22 14:52:29.483533: Current learning rate: 0.00393 +2024-11-22 14:52:48.528260: train_loss -0.7919 +2024-11-22 14:52:48.528501: val_loss -0.7212 +2024-11-22 14:52:48.528575: Pseudo dice [0.8171] +2024-11-22 14:52:48.528665: Epoch time: 19.05 s +2024-11-22 14:52:49.830971: +2024-11-22 14:52:49.831198: Epoch 5169 +2024-11-22 14:52:49.831316: Current learning rate: 0.00393 +2024-11-22 14:53:08.474893: train_loss -0.7982 +2024-11-22 14:53:08.475111: val_loss -0.7373 +2024-11-22 14:53:08.475185: Pseudo dice [0.8504] +2024-11-22 14:53:08.475262: Epoch time: 18.64 s +2024-11-22 14:53:09.345033: +2024-11-22 14:53:09.345243: Epoch 5170 +2024-11-22 14:53:09.345354: Current learning rate: 0.00392 +2024-11-22 14:53:28.449749: train_loss -0.7944 +2024-11-22 14:53:28.449972: val_loss -0.7436 +2024-11-22 14:53:28.450059: Pseudo dice [0.8335] +2024-11-22 14:53:28.450137: Epoch time: 19.11 s +2024-11-22 14:53:29.349552: +2024-11-22 14:53:29.349784: Epoch 5171 +2024-11-22 14:53:29.349902: Current learning rate: 0.00392 +2024-11-22 14:53:47.826650: train_loss -0.8071 +2024-11-22 14:53:47.826900: val_loss -0.7357 +2024-11-22 14:53:47.826977: Pseudo dice [0.8249] +2024-11-22 14:53:47.827068: Epoch time: 18.48 s +2024-11-22 14:53:48.726473: +2024-11-22 14:53:48.726689: Epoch 5172 +2024-11-22 14:53:48.726797: Current learning rate: 0.00392 +2024-11-22 14:54:06.029847: train_loss -0.8007 +2024-11-22 14:54:06.033068: val_loss -0.7532 +2024-11-22 14:54:06.033174: Pseudo dice [0.8356] +2024-11-22 14:54:06.033253: Epoch time: 17.3 s +2024-11-22 14:54:06.934923: +2024-11-22 14:54:06.935150: Epoch 5173 +2024-11-22 14:54:06.935270: Current learning rate: 0.00392 +2024-11-22 14:54:25.590494: train_loss -0.8084 +2024-11-22 14:54:25.590710: val_loss -0.7481 +2024-11-22 14:54:25.590785: Pseudo dice [0.8566] +2024-11-22 14:54:25.590859: Epoch time: 18.66 s +2024-11-22 14:54:26.881960: +2024-11-22 14:54:26.882237: Epoch 5174 +2024-11-22 14:54:26.882348: Current learning rate: 0.00392 +2024-11-22 14:54:46.160094: train_loss -0.807 +2024-11-22 14:54:46.160324: val_loss -0.7194 +2024-11-22 14:54:46.160402: Pseudo dice [0.8516] +2024-11-22 14:54:46.160481: Epoch time: 19.28 s +2024-11-22 14:54:47.063692: +2024-11-22 14:54:47.063946: Epoch 5175 +2024-11-22 14:54:47.064063: Current learning rate: 0.00392 +2024-11-22 14:55:05.526225: train_loss -0.8004 +2024-11-22 14:55:05.526480: val_loss -0.74 +2024-11-22 14:55:05.526567: Pseudo dice [0.8393] +2024-11-22 14:55:05.526651: Epoch time: 18.46 s +2024-11-22 14:55:06.472318: +2024-11-22 14:55:06.472514: Epoch 5176 +2024-11-22 14:55:06.472626: Current learning rate: 0.00392 +2024-11-22 14:55:24.669010: train_loss -0.7955 +2024-11-22 14:55:24.669265: val_loss -0.7456 +2024-11-22 14:55:24.669389: Pseudo dice [0.8225] +2024-11-22 14:55:24.669502: Epoch time: 18.2 s +2024-11-22 14:55:25.565987: +2024-11-22 14:55:25.566186: Epoch 5177 +2024-11-22 14:55:25.566297: Current learning rate: 0.00392 +2024-11-22 14:55:45.250029: train_loss -0.7964 +2024-11-22 14:55:45.250254: val_loss -0.7677 +2024-11-22 14:55:45.250331: Pseudo dice [0.8188] +2024-11-22 14:55:45.250410: Epoch time: 19.68 s +2024-11-22 14:55:46.130553: +2024-11-22 14:55:46.130760: Epoch 5178 +2024-11-22 14:55:46.130869: Current learning rate: 0.00391 +2024-11-22 14:56:05.087754: train_loss -0.7943 +2024-11-22 14:56:05.090261: val_loss -0.7562 +2024-11-22 14:56:05.090353: Pseudo dice [0.8518] +2024-11-22 14:56:05.090429: Epoch time: 18.96 s +2024-11-22 14:56:06.129285: +2024-11-22 14:56:06.129477: Epoch 5179 +2024-11-22 14:56:06.129590: Current learning rate: 0.00391 +2024-11-22 14:56:25.101907: train_loss -0.7964 +2024-11-22 14:56:25.104311: val_loss -0.7273 +2024-11-22 14:56:25.104404: Pseudo dice [0.8495] +2024-11-22 14:56:25.104487: Epoch time: 18.97 s +2024-11-22 14:56:26.000360: +2024-11-22 14:56:26.000562: Epoch 5180 +2024-11-22 14:56:26.000672: Current learning rate: 0.00391 +2024-11-22 14:56:44.808227: train_loss -0.8084 +2024-11-22 14:56:44.808461: val_loss -0.7479 +2024-11-22 14:56:44.808536: Pseudo dice [0.8494] +2024-11-22 14:56:44.808618: Epoch time: 18.81 s +2024-11-22 14:56:46.049913: +2024-11-22 14:56:46.050151: Epoch 5181 +2024-11-22 14:56:46.050265: Current learning rate: 0.00391 +2024-11-22 14:57:05.265117: train_loss -0.7996 +2024-11-22 14:57:05.265328: val_loss -0.7451 +2024-11-22 14:57:05.265402: Pseudo dice [0.8579] +2024-11-22 14:57:05.265476: Epoch time: 19.22 s +2024-11-22 14:57:06.343620: +2024-11-22 14:57:06.343838: Epoch 5182 +2024-11-22 14:57:06.343953: Current learning rate: 0.00391 +2024-11-22 14:57:25.191205: train_loss -0.8008 +2024-11-22 14:57:25.191424: val_loss -0.7378 +2024-11-22 14:57:25.191501: Pseudo dice [0.8424] +2024-11-22 14:57:25.191583: Epoch time: 18.85 s +2024-11-22 14:57:26.074800: +2024-11-22 14:57:26.075077: Epoch 5183 +2024-11-22 14:57:26.075194: Current learning rate: 0.00391 +2024-11-22 14:57:43.714469: train_loss -0.8026 +2024-11-22 14:57:43.715390: val_loss -0.7032 +2024-11-22 14:57:43.715484: Pseudo dice [0.8153] +2024-11-22 14:57:43.715568: Epoch time: 17.64 s +2024-11-22 14:57:44.623977: +2024-11-22 14:57:44.624194: Epoch 5184 +2024-11-22 14:57:44.624307: Current learning rate: 0.00391 +2024-11-22 14:58:03.516235: train_loss -0.8039 +2024-11-22 14:58:03.516449: val_loss -0.7726 +2024-11-22 14:58:03.516527: Pseudo dice [0.8493] +2024-11-22 14:58:03.516637: Epoch time: 18.89 s +2024-11-22 14:58:04.398017: +2024-11-22 14:58:04.398237: Epoch 5185 +2024-11-22 14:58:04.398350: Current learning rate: 0.00391 +2024-11-22 14:58:23.288866: train_loss -0.7997 +2024-11-22 14:58:23.289093: val_loss -0.7563 +2024-11-22 14:58:23.289171: Pseudo dice [0.8421] +2024-11-22 14:58:23.289251: Epoch time: 18.89 s +2024-11-22 14:58:24.171850: +2024-11-22 14:58:24.172075: Epoch 5186 +2024-11-22 14:58:24.172198: Current learning rate: 0.0039 +2024-11-22 14:58:43.614034: train_loss -0.7969 +2024-11-22 14:58:43.614252: val_loss -0.7335 +2024-11-22 14:58:43.614328: Pseudo dice [0.8422] +2024-11-22 14:58:43.614407: Epoch time: 19.44 s +2024-11-22 14:58:44.509704: +2024-11-22 14:58:44.509910: Epoch 5187 +2024-11-22 14:58:44.510024: Current learning rate: 0.0039 +2024-11-22 14:59:03.146217: train_loss -0.7955 +2024-11-22 14:59:03.146466: val_loss -0.7704 +2024-11-22 14:59:03.146546: Pseudo dice [0.8486] +2024-11-22 14:59:03.146630: Epoch time: 18.64 s +2024-11-22 14:59:04.039561: +2024-11-22 14:59:04.039765: Epoch 5188 +2024-11-22 14:59:04.039873: Current learning rate: 0.0039 +2024-11-22 14:59:23.555981: train_loss -0.8021 +2024-11-22 14:59:23.556214: val_loss -0.7371 +2024-11-22 14:59:23.556300: Pseudo dice [0.8442] +2024-11-22 14:59:23.556383: Epoch time: 19.52 s +2024-11-22 14:59:24.447579: +2024-11-22 14:59:24.447780: Epoch 5189 +2024-11-22 14:59:24.447892: Current learning rate: 0.0039 +2024-11-22 14:59:43.662865: train_loss -0.8005 +2024-11-22 14:59:43.663099: val_loss -0.7562 +2024-11-22 14:59:43.663173: Pseudo dice [0.838] +2024-11-22 14:59:43.668462: Epoch time: 19.22 s +2024-11-22 14:59:44.595230: +2024-11-22 14:59:44.595422: Epoch 5190 +2024-11-22 14:59:44.595536: Current learning rate: 0.0039 +2024-11-22 15:00:02.837928: train_loss -0.8017 +2024-11-22 15:00:02.838211: val_loss -0.7436 +2024-11-22 15:00:02.838291: Pseudo dice [0.8557] +2024-11-22 15:00:02.838371: Epoch time: 18.24 s +2024-11-22 15:00:03.732073: +2024-11-22 15:00:03.732282: Epoch 5191 +2024-11-22 15:00:03.732393: Current learning rate: 0.0039 +2024-11-22 15:00:22.138398: train_loss -0.8 +2024-11-22 15:00:22.138637: val_loss -0.7516 +2024-11-22 15:00:22.138712: Pseudo dice [0.851] +2024-11-22 15:00:22.138852: Epoch time: 18.41 s +2024-11-22 15:00:23.027911: +2024-11-22 15:00:23.028113: Epoch 5192 +2024-11-22 15:00:23.028226: Current learning rate: 0.0039 +2024-11-22 15:00:41.556570: train_loss -0.7952 +2024-11-22 15:00:41.556779: val_loss -0.7697 +2024-11-22 15:00:41.556853: Pseudo dice [0.847] +2024-11-22 15:00:41.556927: Epoch time: 18.53 s +2024-11-22 15:00:42.832651: +2024-11-22 15:00:42.832865: Epoch 5193 +2024-11-22 15:00:42.832978: Current learning rate: 0.0039 +2024-11-22 15:01:01.399876: train_loss -0.7954 +2024-11-22 15:01:01.400103: val_loss -0.7385 +2024-11-22 15:01:01.400245: Pseudo dice [0.858] +2024-11-22 15:01:01.400324: Epoch time: 18.57 s +2024-11-22 15:01:02.288921: +2024-11-22 15:01:02.289146: Epoch 5194 +2024-11-22 15:01:02.289258: Current learning rate: 0.00389 +2024-11-22 15:01:20.624320: train_loss -0.7985 +2024-11-22 15:01:20.624584: val_loss -0.731 +2024-11-22 15:01:20.624660: Pseudo dice [0.8003] +2024-11-22 15:01:20.624747: Epoch time: 18.34 s +2024-11-22 15:01:21.513769: +2024-11-22 15:01:21.514061: Epoch 5195 +2024-11-22 15:01:21.514176: Current learning rate: 0.00389 +2024-11-22 15:01:40.562161: train_loss -0.7881 +2024-11-22 15:01:40.562375: val_loss -0.756 +2024-11-22 15:01:40.562451: Pseudo dice [0.8675] +2024-11-22 15:01:40.562528: Epoch time: 19.05 s +2024-11-22 15:01:41.479945: +2024-11-22 15:01:41.480150: Epoch 5196 +2024-11-22 15:01:41.480293: Current learning rate: 0.00389 +2024-11-22 15:02:01.441458: train_loss -0.7944 +2024-11-22 15:02:01.441681: val_loss -0.7667 +2024-11-22 15:02:01.441758: Pseudo dice [0.8563] +2024-11-22 15:02:01.441878: Epoch time: 19.96 s +2024-11-22 15:02:02.332640: +2024-11-22 15:02:02.332859: Epoch 5197 +2024-11-22 15:02:02.332976: Current learning rate: 0.00389 +2024-11-22 15:02:19.987919: train_loss -0.8078 +2024-11-22 15:02:19.988152: val_loss -0.7039 +2024-11-22 15:02:19.988228: Pseudo dice [0.8057] +2024-11-22 15:02:19.988306: Epoch time: 17.66 s +2024-11-22 15:02:20.878662: +2024-11-22 15:02:20.878856: Epoch 5198 +2024-11-22 15:02:20.878971: Current learning rate: 0.00389 +2024-11-22 15:02:39.497684: train_loss -0.8054 +2024-11-22 15:02:39.497923: val_loss -0.7735 +2024-11-22 15:02:39.498007: Pseudo dice [0.8439] +2024-11-22 15:02:39.498119: Epoch time: 18.62 s +2024-11-22 15:02:40.399340: +2024-11-22 15:02:40.399549: Epoch 5199 +2024-11-22 15:02:40.399663: Current learning rate: 0.00389 +2024-11-22 15:02:59.412277: train_loss -0.7986 +2024-11-22 15:02:59.412524: val_loss -0.7609 +2024-11-22 15:02:59.412603: Pseudo dice [0.8413] +2024-11-22 15:02:59.414874: Epoch time: 19.01 s +2024-11-22 15:03:00.609483: +2024-11-22 15:03:00.609700: Epoch 5200 +2024-11-22 15:03:00.609811: Current learning rate: 0.00389 +2024-11-22 15:03:20.559742: train_loss -0.806 +2024-11-22 15:03:20.559955: val_loss -0.7225 +2024-11-22 15:03:20.560076: Pseudo dice [0.8353] +2024-11-22 15:03:20.560176: Epoch time: 19.95 s +2024-11-22 15:03:21.444351: +2024-11-22 15:03:21.444556: Epoch 5201 +2024-11-22 15:03:21.444670: Current learning rate: 0.00389 +2024-11-22 15:03:39.379305: train_loss -0.8059 +2024-11-22 15:03:39.379528: val_loss -0.7659 +2024-11-22 15:03:39.379609: Pseudo dice [0.8682] +2024-11-22 15:03:39.379732: Epoch time: 17.94 s +2024-11-22 15:03:40.269413: +2024-11-22 15:03:40.269631: Epoch 5202 +2024-11-22 15:03:40.269741: Current learning rate: 0.00388 +2024-11-22 15:03:59.195977: train_loss -0.8017 +2024-11-22 15:03:59.196237: val_loss -0.7744 +2024-11-22 15:03:59.196318: Pseudo dice [0.8484] +2024-11-22 15:03:59.196400: Epoch time: 18.93 s +2024-11-22 15:04:00.120874: +2024-11-22 15:04:00.121094: Epoch 5203 +2024-11-22 15:04:00.121209: Current learning rate: 0.00388 +2024-11-22 15:04:18.772914: train_loss -0.806 +2024-11-22 15:04:18.773129: val_loss -0.7727 +2024-11-22 15:04:18.773205: Pseudo dice [0.8676] +2024-11-22 15:04:18.773279: Epoch time: 18.65 s +2024-11-22 15:04:19.653677: +2024-11-22 15:04:19.653943: Epoch 5204 +2024-11-22 15:04:19.654062: Current learning rate: 0.00388 +2024-11-22 15:04:38.621886: train_loss -0.8059 +2024-11-22 15:04:38.622133: val_loss -0.7563 +2024-11-22 15:04:38.622210: Pseudo dice [0.8647] +2024-11-22 15:04:38.622285: Epoch time: 18.97 s +2024-11-22 15:04:39.508573: +2024-11-22 15:04:39.508873: Epoch 5205 +2024-11-22 15:04:39.508998: Current learning rate: 0.00388 +2024-11-22 15:04:57.948224: train_loss -0.8031 +2024-11-22 15:04:57.948476: val_loss -0.7561 +2024-11-22 15:04:57.948555: Pseudo dice [0.8214] +2024-11-22 15:04:57.948632: Epoch time: 18.44 s +2024-11-22 15:04:58.832120: +2024-11-22 15:04:58.832382: Epoch 5206 +2024-11-22 15:04:58.832515: Current learning rate: 0.00388 +2024-11-22 15:05:17.734599: train_loss -0.8072 +2024-11-22 15:05:17.734848: val_loss -0.7678 +2024-11-22 15:05:17.734922: Pseudo dice [0.8532] +2024-11-22 15:05:17.735013: Epoch time: 18.9 s +2024-11-22 15:05:18.629355: +2024-11-22 15:05:18.629562: Epoch 5207 +2024-11-22 15:05:18.629677: Current learning rate: 0.00388 +2024-11-22 15:05:38.373963: train_loss -0.8062 +2024-11-22 15:05:38.374204: val_loss -0.7488 +2024-11-22 15:05:38.374279: Pseudo dice [0.8435] +2024-11-22 15:05:38.374356: Epoch time: 19.75 s +2024-11-22 15:05:39.270679: +2024-11-22 15:05:39.270886: Epoch 5208 +2024-11-22 15:05:39.271009: Current learning rate: 0.00388 +2024-11-22 15:05:57.901734: train_loss -0.8059 +2024-11-22 15:05:57.901966: val_loss -0.7581 +2024-11-22 15:05:57.902063: Pseudo dice [0.8589] +2024-11-22 15:05:57.902142: Epoch time: 18.63 s +2024-11-22 15:05:58.792806: +2024-11-22 15:05:58.793031: Epoch 5209 +2024-11-22 15:05:58.793164: Current learning rate: 0.00388 +2024-11-22 15:06:16.384679: train_loss -0.8069 +2024-11-22 15:06:16.384913: val_loss -0.7846 +2024-11-22 15:06:16.384997: Pseudo dice [0.8511] +2024-11-22 15:06:16.385074: Epoch time: 17.59 s +2024-11-22 15:06:17.281622: +2024-11-22 15:06:17.281838: Epoch 5210 +2024-11-22 15:06:17.281957: Current learning rate: 0.00387 +2024-11-22 15:06:36.215291: train_loss -0.7903 +2024-11-22 15:06:36.215537: val_loss -0.7488 +2024-11-22 15:06:36.215612: Pseudo dice [0.8355] +2024-11-22 15:06:36.215696: Epoch time: 18.93 s +2024-11-22 15:06:37.115924: +2024-11-22 15:06:37.116139: Epoch 5211 +2024-11-22 15:06:37.116252: Current learning rate: 0.00387 +2024-11-22 15:06:56.187612: train_loss -0.803 +2024-11-22 15:06:56.187914: val_loss -0.7355 +2024-11-22 15:06:56.187999: Pseudo dice [0.8204] +2024-11-22 15:06:56.188083: Epoch time: 19.07 s +2024-11-22 15:06:57.085481: +2024-11-22 15:06:57.085693: Epoch 5212 +2024-11-22 15:06:57.085805: Current learning rate: 0.00387 +2024-11-22 15:07:16.756111: train_loss -0.8011 +2024-11-22 15:07:16.756342: val_loss -0.739 +2024-11-22 15:07:16.756419: Pseudo dice [0.8481] +2024-11-22 15:07:16.756497: Epoch time: 19.67 s +2024-11-22 15:07:17.650227: +2024-11-22 15:07:17.650505: Epoch 5213 +2024-11-22 15:07:17.650619: Current learning rate: 0.00387 +2024-11-22 15:07:36.322932: train_loss -0.8066 +2024-11-22 15:07:36.323157: val_loss -0.7726 +2024-11-22 15:07:36.323252: Pseudo dice [0.8471] +2024-11-22 15:07:36.323356: Epoch time: 18.67 s +2024-11-22 15:07:37.326435: +2024-11-22 15:07:37.326648: Epoch 5214 +2024-11-22 15:07:37.326763: Current learning rate: 0.00387 +2024-11-22 15:07:55.950585: train_loss -0.7969 +2024-11-22 15:07:55.950894: val_loss -0.6992 +2024-11-22 15:07:55.950972: Pseudo dice [0.7909] +2024-11-22 15:07:55.951061: Epoch time: 18.62 s +2024-11-22 15:07:56.846221: +2024-11-22 15:07:56.846472: Epoch 5215 +2024-11-22 15:07:56.846588: Current learning rate: 0.00387 +2024-11-22 15:08:15.169266: train_loss -0.8014 +2024-11-22 15:08:15.169561: val_loss -0.7403 +2024-11-22 15:08:15.169638: Pseudo dice [0.8408] +2024-11-22 15:08:15.169719: Epoch time: 18.32 s +2024-11-22 15:08:16.622653: +2024-11-22 15:08:16.622922: Epoch 5216 +2024-11-22 15:08:16.623042: Current learning rate: 0.00387 +2024-11-22 15:08:35.471562: train_loss -0.8079 +2024-11-22 15:08:35.471793: val_loss -0.7675 +2024-11-22 15:08:35.471866: Pseudo dice [0.8204] +2024-11-22 15:08:35.471942: Epoch time: 18.85 s +2024-11-22 15:08:36.386427: +2024-11-22 15:08:36.386703: Epoch 5217 +2024-11-22 15:08:36.386817: Current learning rate: 0.00387 +2024-11-22 15:08:55.995041: train_loss -0.8068 +2024-11-22 15:08:55.995275: val_loss -0.7445 +2024-11-22 15:08:55.995361: Pseudo dice [0.8362] +2024-11-22 15:08:55.995450: Epoch time: 19.61 s +2024-11-22 15:08:56.895898: +2024-11-22 15:08:56.896217: Epoch 5218 +2024-11-22 15:08:56.896380: Current learning rate: 0.00386 +2024-11-22 15:09:15.508049: train_loss -0.8072 +2024-11-22 15:09:15.508326: val_loss -0.764 +2024-11-22 15:09:15.508408: Pseudo dice [0.8668] +2024-11-22 15:09:15.508488: Epoch time: 18.61 s +2024-11-22 15:09:16.416156: +2024-11-22 15:09:16.416442: Epoch 5219 +2024-11-22 15:09:16.416556: Current learning rate: 0.00386 +2024-11-22 15:09:35.215262: train_loss -0.8075 +2024-11-22 15:09:35.215477: val_loss -0.76 +2024-11-22 15:09:35.215550: Pseudo dice [0.8594] +2024-11-22 15:09:35.215658: Epoch time: 18.8 s +2024-11-22 15:09:36.110022: +2024-11-22 15:09:36.110213: Epoch 5220 +2024-11-22 15:09:36.110350: Current learning rate: 0.00386 +2024-11-22 15:09:55.031964: train_loss -0.7988 +2024-11-22 15:09:55.032266: val_loss -0.7554 +2024-11-22 15:09:55.032354: Pseudo dice [0.8683] +2024-11-22 15:09:55.032441: Epoch time: 18.92 s +2024-11-22 15:09:55.925490: +2024-11-22 15:09:55.925716: Epoch 5221 +2024-11-22 15:09:55.925835: Current learning rate: 0.00386 +2024-11-22 15:10:14.758260: train_loss -0.8007 +2024-11-22 15:10:14.758490: val_loss -0.7515 +2024-11-22 15:10:14.758570: Pseudo dice [0.8381] +2024-11-22 15:10:14.758654: Epoch time: 18.83 s +2024-11-22 15:10:15.679481: +2024-11-22 15:10:15.679844: Epoch 5222 +2024-11-22 15:10:15.679955: Current learning rate: 0.00386 +2024-11-22 15:10:34.165313: train_loss -0.7992 +2024-11-22 15:10:34.165625: val_loss -0.7482 +2024-11-22 15:10:34.165710: Pseudo dice [0.8285] +2024-11-22 15:10:34.165796: Epoch time: 18.47 s +2024-11-22 15:10:35.210167: +2024-11-22 15:10:35.210355: Epoch 5223 +2024-11-22 15:10:35.210469: Current learning rate: 0.00386 +2024-11-22 15:10:54.578058: train_loss -0.8025 +2024-11-22 15:10:54.578287: val_loss -0.7412 +2024-11-22 15:10:54.578377: Pseudo dice [0.8507] +2024-11-22 15:10:54.578465: Epoch time: 19.37 s +2024-11-22 15:10:55.507925: +2024-11-22 15:10:55.508122: Epoch 5224 +2024-11-22 15:10:55.508236: Current learning rate: 0.00386 +2024-11-22 15:11:13.677652: train_loss -0.7938 +2024-11-22 15:11:13.677880: val_loss -0.7431 +2024-11-22 15:11:13.677956: Pseudo dice [0.8267] +2024-11-22 15:11:13.678037: Epoch time: 18.17 s +2024-11-22 15:11:14.671810: +2024-11-22 15:11:14.672019: Epoch 5225 +2024-11-22 15:11:14.672132: Current learning rate: 0.00386 +2024-11-22 15:11:33.600635: train_loss -0.806 +2024-11-22 15:11:33.600874: val_loss -0.732 +2024-11-22 15:11:33.600948: Pseudo dice [0.8322] +2024-11-22 15:11:33.601070: Epoch time: 18.93 s +2024-11-22 15:11:34.493771: +2024-11-22 15:11:34.494023: Epoch 5226 +2024-11-22 15:11:34.494144: Current learning rate: 0.00385 +2024-11-22 15:11:52.625520: train_loss -0.7984 +2024-11-22 15:11:52.625730: val_loss -0.7402 +2024-11-22 15:11:52.625817: Pseudo dice [0.8586] +2024-11-22 15:11:52.625892: Epoch time: 18.13 s +2024-11-22 15:11:53.507013: +2024-11-22 15:11:53.507217: Epoch 5227 +2024-11-22 15:11:53.507332: Current learning rate: 0.00385 +2024-11-22 15:12:12.478683: train_loss -0.7923 +2024-11-22 15:12:12.478914: val_loss -0.7525 +2024-11-22 15:12:12.478988: Pseudo dice [0.8513] +2024-11-22 15:12:12.479069: Epoch time: 18.97 s +2024-11-22 15:12:13.821559: +2024-11-22 15:12:13.821768: Epoch 5228 +2024-11-22 15:12:13.821883: Current learning rate: 0.00385 +2024-11-22 15:12:33.096514: train_loss -0.8029 +2024-11-22 15:12:33.096751: val_loss -0.766 +2024-11-22 15:12:33.096836: Pseudo dice [0.8354] +2024-11-22 15:12:33.096928: Epoch time: 19.28 s +2024-11-22 15:12:33.996342: +2024-11-22 15:12:33.996570: Epoch 5229 +2024-11-22 15:12:33.996681: Current learning rate: 0.00385 +2024-11-22 15:12:53.645677: train_loss -0.8008 +2024-11-22 15:12:53.645915: val_loss -0.7551 +2024-11-22 15:12:53.645987: Pseudo dice [0.8483] +2024-11-22 15:12:53.646071: Epoch time: 19.65 s +2024-11-22 15:12:54.648548: +2024-11-22 15:12:54.648776: Epoch 5230 +2024-11-22 15:12:54.648895: Current learning rate: 0.00385 +2024-11-22 15:13:13.426543: train_loss -0.804 +2024-11-22 15:13:13.426759: val_loss -0.7507 +2024-11-22 15:13:13.426831: Pseudo dice [0.8322] +2024-11-22 15:13:13.426908: Epoch time: 18.78 s +2024-11-22 15:13:14.319618: +2024-11-22 15:13:14.319834: Epoch 5231 +2024-11-22 15:13:14.319947: Current learning rate: 0.00385 +2024-11-22 15:13:34.550905: train_loss -0.8052 +2024-11-22 15:13:34.551144: val_loss -0.7425 +2024-11-22 15:13:34.551224: Pseudo dice [0.8292] +2024-11-22 15:13:34.551303: Epoch time: 20.23 s +2024-11-22 15:13:35.450608: +2024-11-22 15:13:35.450807: Epoch 5232 +2024-11-22 15:13:35.450918: Current learning rate: 0.00385 +2024-11-22 15:13:54.872132: train_loss -0.7978 +2024-11-22 15:13:54.872382: val_loss -0.7229 +2024-11-22 15:13:54.874718: Pseudo dice [0.8415] +2024-11-22 15:13:54.874830: Epoch time: 19.42 s +2024-11-22 15:13:55.831622: +2024-11-22 15:13:55.831820: Epoch 5233 +2024-11-22 15:13:55.831933: Current learning rate: 0.00385 +2024-11-22 15:14:14.699325: train_loss -0.8053 +2024-11-22 15:14:14.699547: val_loss -0.7618 +2024-11-22 15:14:14.699621: Pseudo dice [0.8768] +2024-11-22 15:14:14.699696: Epoch time: 18.87 s +2024-11-22 15:14:15.612925: +2024-11-22 15:14:15.613152: Epoch 5234 +2024-11-22 15:14:15.613268: Current learning rate: 0.00384 +2024-11-22 15:14:34.482338: train_loss -0.8074 +2024-11-22 15:14:34.482561: val_loss -0.7495 +2024-11-22 15:14:34.482637: Pseudo dice [0.8451] +2024-11-22 15:14:34.482714: Epoch time: 18.87 s +2024-11-22 15:14:35.387733: +2024-11-22 15:14:35.388002: Epoch 5235 +2024-11-22 15:14:35.388119: Current learning rate: 0.00384 +2024-11-22 15:14:54.360259: train_loss -0.7977 +2024-11-22 15:14:54.360523: val_loss -0.7261 +2024-11-22 15:14:54.360596: Pseudo dice [0.8572] +2024-11-22 15:14:54.360676: Epoch time: 18.97 s +2024-11-22 15:14:55.258771: +2024-11-22 15:14:55.258960: Epoch 5236 +2024-11-22 15:14:55.259101: Current learning rate: 0.00384 +2024-11-22 15:15:13.855627: train_loss -0.7937 +2024-11-22 15:15:13.860129: val_loss -0.7541 +2024-11-22 15:15:13.860268: Pseudo dice [0.865] +2024-11-22 15:15:13.860353: Epoch time: 18.6 s +2024-11-22 15:15:14.886812: +2024-11-22 15:15:14.887028: Epoch 5237 +2024-11-22 15:15:14.887143: Current learning rate: 0.00384 +2024-11-22 15:15:34.634060: train_loss -0.7976 +2024-11-22 15:15:34.634286: val_loss -0.7457 +2024-11-22 15:15:34.634367: Pseudo dice [0.8473] +2024-11-22 15:15:34.634447: Epoch time: 19.75 s +2024-11-22 15:15:35.540311: +2024-11-22 15:15:35.540516: Epoch 5238 +2024-11-22 15:15:35.540632: Current learning rate: 0.00384 +2024-11-22 15:15:53.517580: train_loss -0.787 +2024-11-22 15:15:53.517808: val_loss -0.7474 +2024-11-22 15:15:53.520092: Pseudo dice [0.8319] +2024-11-22 15:15:53.520183: Epoch time: 17.98 s +2024-11-22 15:15:54.430631: +2024-11-22 15:15:54.430820: Epoch 5239 +2024-11-22 15:15:54.430930: Current learning rate: 0.00384 +2024-11-22 15:16:13.464573: train_loss -0.7975 +2024-11-22 15:16:13.470006: val_loss -0.7232 +2024-11-22 15:16:13.470130: Pseudo dice [0.8235] +2024-11-22 15:16:13.470226: Epoch time: 19.03 s +2024-11-22 15:16:14.910894: +2024-11-22 15:16:14.911123: Epoch 5240 +2024-11-22 15:16:14.911234: Current learning rate: 0.00384 +2024-11-22 15:16:33.791902: train_loss -0.7988 +2024-11-22 15:16:33.792133: val_loss -0.749 +2024-11-22 15:16:33.792218: Pseudo dice [0.8234] +2024-11-22 15:16:33.792296: Epoch time: 18.88 s +2024-11-22 15:16:34.679431: +2024-11-22 15:16:34.679648: Epoch 5241 +2024-11-22 15:16:34.679760: Current learning rate: 0.00384 +2024-11-22 15:16:54.114112: train_loss -0.8022 +2024-11-22 15:16:54.114405: val_loss -0.7309 +2024-11-22 15:16:54.114487: Pseudo dice [0.8331] +2024-11-22 15:16:54.114567: Epoch time: 19.44 s +2024-11-22 15:16:55.004498: +2024-11-22 15:16:55.004728: Epoch 5242 +2024-11-22 15:16:55.004841: Current learning rate: 0.00383 +2024-11-22 15:17:14.180628: train_loss -0.7999 +2024-11-22 15:17:14.180850: val_loss -0.768 +2024-11-22 15:17:14.180924: Pseudo dice [0.8469] +2024-11-22 15:17:14.181007: Epoch time: 19.18 s +2024-11-22 15:17:15.080095: +2024-11-22 15:17:15.080323: Epoch 5243 +2024-11-22 15:17:15.080433: Current learning rate: 0.00383 +2024-11-22 15:17:33.630442: train_loss -0.8051 +2024-11-22 15:17:33.631154: val_loss -0.7735 +2024-11-22 15:17:33.631243: Pseudo dice [0.8545] +2024-11-22 15:17:33.631347: Epoch time: 18.55 s +2024-11-22 15:17:34.531412: +2024-11-22 15:17:34.531616: Epoch 5244 +2024-11-22 15:17:34.531732: Current learning rate: 0.00383 +2024-11-22 15:17:53.747665: train_loss -0.798 +2024-11-22 15:17:53.747882: val_loss -0.737 +2024-11-22 15:17:53.753174: Pseudo dice [0.8285] +2024-11-22 15:17:53.753284: Epoch time: 19.22 s +2024-11-22 15:17:54.914793: +2024-11-22 15:17:54.915027: Epoch 5245 +2024-11-22 15:17:54.915145: Current learning rate: 0.00383 +2024-11-22 15:18:14.317685: train_loss -0.8008 +2024-11-22 15:18:14.317912: val_loss -0.7289 +2024-11-22 15:18:14.317986: Pseudo dice [0.8547] +2024-11-22 15:18:14.318071: Epoch time: 19.4 s +2024-11-22 15:18:15.210177: +2024-11-22 15:18:15.210370: Epoch 5246 +2024-11-22 15:18:15.210482: Current learning rate: 0.00383 +2024-11-22 15:18:34.670919: train_loss -0.8023 +2024-11-22 15:18:34.671137: val_loss -0.7615 +2024-11-22 15:18:34.671217: Pseudo dice [0.8508] +2024-11-22 15:18:34.671293: Epoch time: 19.46 s +2024-11-22 15:18:35.784626: +2024-11-22 15:18:35.784859: Epoch 5247 +2024-11-22 15:18:35.784986: Current learning rate: 0.00383 +2024-11-22 15:18:53.192327: train_loss -0.804 +2024-11-22 15:18:53.192574: val_loss -0.7446 +2024-11-22 15:18:53.192650: Pseudo dice [0.842] +2024-11-22 15:18:53.192731: Epoch time: 17.41 s +2024-11-22 15:18:54.167072: +2024-11-22 15:18:54.167287: Epoch 5248 +2024-11-22 15:18:54.167400: Current learning rate: 0.00383 +2024-11-22 15:19:12.073073: train_loss -0.8041 +2024-11-22 15:19:12.073291: val_loss -0.7337 +2024-11-22 15:19:12.073369: Pseudo dice [0.8533] +2024-11-22 15:19:12.073457: Epoch time: 17.91 s +2024-11-22 15:19:12.971478: +2024-11-22 15:19:12.971672: Epoch 5249 +2024-11-22 15:19:12.971782: Current learning rate: 0.00383 +2024-11-22 15:19:31.246098: train_loss -0.7994 +2024-11-22 15:19:31.246368: val_loss -0.7558 +2024-11-22 15:19:31.246446: Pseudo dice [0.8601] +2024-11-22 15:19:31.246527: Epoch time: 18.28 s +2024-11-22 15:19:32.439216: +2024-11-22 15:19:32.439441: Epoch 5250 +2024-11-22 15:19:32.439695: Current learning rate: 0.00382 +2024-11-22 15:19:52.615535: train_loss -0.8021 +2024-11-22 15:19:52.615854: val_loss -0.7402 +2024-11-22 15:19:52.615936: Pseudo dice [0.8193] +2024-11-22 15:19:52.616030: Epoch time: 20.18 s +2024-11-22 15:19:53.511998: +2024-11-22 15:19:53.512205: Epoch 5251 +2024-11-22 15:19:53.512318: Current learning rate: 0.00382 +2024-11-22 15:20:13.190778: train_loss -0.8041 +2024-11-22 15:20:13.193221: val_loss -0.772 +2024-11-22 15:20:13.193314: Pseudo dice [0.8739] +2024-11-22 15:20:13.193397: Epoch time: 19.68 s +2024-11-22 15:20:14.128615: +2024-11-22 15:20:14.128813: Epoch 5252 +2024-11-22 15:20:14.128928: Current learning rate: 0.00382 +2024-11-22 15:20:32.951631: train_loss -0.7821 +2024-11-22 15:20:32.951906: val_loss -0.7588 +2024-11-22 15:20:32.951984: Pseudo dice [0.8574] +2024-11-22 15:20:32.952068: Epoch time: 18.82 s +2024-11-22 15:20:33.842422: +2024-11-22 15:20:33.842660: Epoch 5253 +2024-11-22 15:20:33.842773: Current learning rate: 0.00382 +2024-11-22 15:20:53.151545: train_loss -0.7971 +2024-11-22 15:20:53.151776: val_loss -0.7478 +2024-11-22 15:20:53.151853: Pseudo dice [0.8313] +2024-11-22 15:20:53.151930: Epoch time: 19.31 s +2024-11-22 15:20:54.048944: +2024-11-22 15:20:54.049174: Epoch 5254 +2024-11-22 15:20:54.049289: Current learning rate: 0.00382 +2024-11-22 15:21:12.392648: train_loss -0.7933 +2024-11-22 15:21:12.392933: val_loss -0.7409 +2024-11-22 15:21:12.393020: Pseudo dice [0.845] +2024-11-22 15:21:12.393111: Epoch time: 18.34 s +2024-11-22 15:21:13.328400: +2024-11-22 15:21:13.328627: Epoch 5255 +2024-11-22 15:21:13.328743: Current learning rate: 0.00382 +2024-11-22 15:21:32.309779: train_loss -0.7916 +2024-11-22 15:21:32.310018: val_loss -0.7802 +2024-11-22 15:21:32.310097: Pseudo dice [0.8528] +2024-11-22 15:21:32.310183: Epoch time: 18.98 s +2024-11-22 15:21:33.323879: +2024-11-22 15:21:33.324085: Epoch 5256 +2024-11-22 15:21:33.324204: Current learning rate: 0.00382 +2024-11-22 15:21:51.282260: train_loss -0.8004 +2024-11-22 15:21:51.282474: val_loss -0.7528 +2024-11-22 15:21:51.282552: Pseudo dice [0.8304] +2024-11-22 15:21:51.282657: Epoch time: 17.96 s +2024-11-22 15:21:52.177145: +2024-11-22 15:21:52.177360: Epoch 5257 +2024-11-22 15:21:52.177480: Current learning rate: 0.00382 +2024-11-22 15:22:10.681309: train_loss -0.804 +2024-11-22 15:22:10.681540: val_loss -0.7494 +2024-11-22 15:22:10.681629: Pseudo dice [0.8446] +2024-11-22 15:22:10.681710: Epoch time: 18.5 s +2024-11-22 15:22:11.576890: +2024-11-22 15:22:11.577078: Epoch 5258 +2024-11-22 15:22:11.577190: Current learning rate: 0.00381 +2024-11-22 15:22:30.851013: train_loss -0.794 +2024-11-22 15:22:30.851238: val_loss -0.7381 +2024-11-22 15:22:30.851314: Pseudo dice [0.8433] +2024-11-22 15:22:30.851395: Epoch time: 19.27 s +2024-11-22 15:22:31.744280: +2024-11-22 15:22:31.744621: Epoch 5259 +2024-11-22 15:22:31.744738: Current learning rate: 0.00381 +2024-11-22 15:22:51.518548: train_loss -0.7933 +2024-11-22 15:22:51.518781: val_loss -0.7731 +2024-11-22 15:22:51.518864: Pseudo dice [0.8562] +2024-11-22 15:22:51.518951: Epoch time: 19.78 s +2024-11-22 15:22:52.514961: +2024-11-22 15:22:52.515198: Epoch 5260 +2024-11-22 15:22:52.515314: Current learning rate: 0.00381 +2024-11-22 15:23:12.194263: train_loss -0.8031 +2024-11-22 15:23:12.194486: val_loss -0.7675 +2024-11-22 15:23:12.194562: Pseudo dice [0.8633] +2024-11-22 15:23:12.194639: Epoch time: 19.68 s +2024-11-22 15:23:13.113636: +2024-11-22 15:23:13.113870: Epoch 5261 +2024-11-22 15:23:13.113983: Current learning rate: 0.00381 +2024-11-22 15:23:32.005413: train_loss -0.7989 +2024-11-22 15:23:32.006102: val_loss -0.7539 +2024-11-22 15:23:32.006226: Pseudo dice [0.8381] +2024-11-22 15:23:32.006315: Epoch time: 18.89 s +2024-11-22 15:23:32.906603: +2024-11-22 15:23:32.906816: Epoch 5262 +2024-11-22 15:23:32.906929: Current learning rate: 0.00381 +2024-11-22 15:23:52.338693: train_loss -0.802 +2024-11-22 15:23:52.338944: val_loss -0.7372 +2024-11-22 15:23:52.339035: Pseudo dice [0.8746] +2024-11-22 15:23:52.339129: Epoch time: 19.43 s +2024-11-22 15:23:53.632464: +2024-11-22 15:23:53.632674: Epoch 5263 +2024-11-22 15:23:53.632788: Current learning rate: 0.00381 +2024-11-22 15:24:13.636684: train_loss -0.7903 +2024-11-22 15:24:13.636901: val_loss -0.7195 +2024-11-22 15:24:13.636975: Pseudo dice [0.837] +2024-11-22 15:24:13.637053: Epoch time: 20.01 s +2024-11-22 15:24:14.530542: +2024-11-22 15:24:14.530761: Epoch 5264 +2024-11-22 15:24:14.530874: Current learning rate: 0.00381 +2024-11-22 15:24:33.069484: train_loss -0.8052 +2024-11-22 15:24:33.069701: val_loss -0.7545 +2024-11-22 15:24:33.069781: Pseudo dice [0.8457] +2024-11-22 15:24:33.069859: Epoch time: 18.54 s +2024-11-22 15:24:33.954165: +2024-11-22 15:24:33.954384: Epoch 5265 +2024-11-22 15:24:33.954498: Current learning rate: 0.00381 +2024-11-22 15:24:52.498932: train_loss -0.8016 +2024-11-22 15:24:52.499153: val_loss -0.7376 +2024-11-22 15:24:52.499225: Pseudo dice [0.8453] +2024-11-22 15:24:52.499299: Epoch time: 18.55 s +2024-11-22 15:24:53.399248: +2024-11-22 15:24:53.399481: Epoch 5266 +2024-11-22 15:24:53.399594: Current learning rate: 0.0038 +2024-11-22 15:25:11.723076: train_loss -0.8026 +2024-11-22 15:25:11.723314: val_loss -0.7798 +2024-11-22 15:25:11.723389: Pseudo dice [0.8665] +2024-11-22 15:25:11.723474: Epoch time: 18.32 s +2024-11-22 15:25:12.616364: +2024-11-22 15:25:12.616616: Epoch 5267 +2024-11-22 15:25:12.616731: Current learning rate: 0.0038 +2024-11-22 15:25:31.122162: train_loss -0.8011 +2024-11-22 15:25:31.122365: val_loss -0.7521 +2024-11-22 15:25:31.122438: Pseudo dice [0.8464] +2024-11-22 15:25:31.122515: Epoch time: 18.51 s +2024-11-22 15:25:32.098119: +2024-11-22 15:25:32.098333: Epoch 5268 +2024-11-22 15:25:32.098447: Current learning rate: 0.0038 +2024-11-22 15:25:50.393186: train_loss -0.798 +2024-11-22 15:25:50.395581: val_loss -0.7369 +2024-11-22 15:25:50.395679: Pseudo dice [0.8471] +2024-11-22 15:25:50.395760: Epoch time: 18.3 s +2024-11-22 15:25:51.353348: +2024-11-22 15:25:51.353570: Epoch 5269 +2024-11-22 15:25:51.353677: Current learning rate: 0.0038 +2024-11-22 15:26:10.769232: train_loss -0.8009 +2024-11-22 15:26:10.769460: val_loss -0.7645 +2024-11-22 15:26:10.769537: Pseudo dice [0.8602] +2024-11-22 15:26:10.769617: Epoch time: 19.42 s +2024-11-22 15:26:11.743198: +2024-11-22 15:26:11.743406: Epoch 5270 +2024-11-22 15:26:11.743510: Current learning rate: 0.0038 +2024-11-22 15:26:29.394293: train_loss -0.79 +2024-11-22 15:26:29.394545: val_loss -0.7258 +2024-11-22 15:26:29.394621: Pseudo dice [0.8481] +2024-11-22 15:26:29.394701: Epoch time: 17.65 s +2024-11-22 15:26:30.306530: +2024-11-22 15:26:30.306892: Epoch 5271 +2024-11-22 15:26:30.307012: Current learning rate: 0.0038 +2024-11-22 15:26:49.240680: train_loss -0.8001 +2024-11-22 15:26:49.240892: val_loss -0.769 +2024-11-22 15:26:49.240965: Pseudo dice [0.8478] +2024-11-22 15:26:49.241046: Epoch time: 18.93 s +2024-11-22 15:26:50.132892: +2024-11-22 15:26:50.133093: Epoch 5272 +2024-11-22 15:26:50.133207: Current learning rate: 0.0038 +2024-11-22 15:27:09.193467: train_loss -0.7999 +2024-11-22 15:27:09.193686: val_loss -0.7486 +2024-11-22 15:27:09.193765: Pseudo dice [0.8556] +2024-11-22 15:27:09.193841: Epoch time: 19.06 s +2024-11-22 15:27:10.220582: +2024-11-22 15:27:10.220863: Epoch 5273 +2024-11-22 15:27:10.220976: Current learning rate: 0.0038 +2024-11-22 15:27:27.724779: train_loss -0.7959 +2024-11-22 15:27:27.725005: val_loss -0.7569 +2024-11-22 15:27:27.725080: Pseudo dice [0.8538] +2024-11-22 15:27:27.725157: Epoch time: 17.5 s +2024-11-22 15:27:28.620700: +2024-11-22 15:27:28.620931: Epoch 5274 +2024-11-22 15:27:28.621049: Current learning rate: 0.00379 +2024-11-22 15:27:46.999555: train_loss -0.8021 +2024-11-22 15:27:46.999802: val_loss -0.755 +2024-11-22 15:27:46.999874: Pseudo dice [0.8363] +2024-11-22 15:27:46.999955: Epoch time: 18.38 s +2024-11-22 15:27:48.357850: +2024-11-22 15:27:48.358294: Epoch 5275 +2024-11-22 15:27:48.358418: Current learning rate: 0.00379 +2024-11-22 15:28:07.500828: train_loss -0.7807 +2024-11-22 15:28:07.501093: val_loss -0.7448 +2024-11-22 15:28:07.501169: Pseudo dice [0.8422] +2024-11-22 15:28:07.501246: Epoch time: 19.14 s +2024-11-22 15:28:08.395385: +2024-11-22 15:28:08.395840: Epoch 5276 +2024-11-22 15:28:08.396054: Current learning rate: 0.00379 +2024-11-22 15:28:26.928772: train_loss -0.7977 +2024-11-22 15:28:26.930097: val_loss -0.7171 +2024-11-22 15:28:26.930171: Pseudo dice [0.8488] +2024-11-22 15:28:26.930247: Epoch time: 18.53 s +2024-11-22 15:28:27.817207: +2024-11-22 15:28:27.817692: Epoch 5277 +2024-11-22 15:28:27.817825: Current learning rate: 0.00379 +2024-11-22 15:28:46.691076: train_loss -0.7988 +2024-11-22 15:28:46.691348: val_loss -0.7241 +2024-11-22 15:28:46.691432: Pseudo dice [0.8332] +2024-11-22 15:28:46.691516: Epoch time: 18.87 s +2024-11-22 15:28:47.593786: +2024-11-22 15:28:47.594249: Epoch 5278 +2024-11-22 15:28:47.594386: Current learning rate: 0.00379 +2024-11-22 15:29:05.962276: train_loss -0.7905 +2024-11-22 15:29:05.962566: val_loss -0.7186 +2024-11-22 15:29:05.962644: Pseudo dice [0.8371] +2024-11-22 15:29:05.962723: Epoch time: 18.37 s +2024-11-22 15:29:06.861547: +2024-11-22 15:29:06.862018: Epoch 5279 +2024-11-22 15:29:06.862152: Current learning rate: 0.00379 +2024-11-22 15:29:25.829725: train_loss -0.7973 +2024-11-22 15:29:25.829952: val_loss -0.7805 +2024-11-22 15:29:25.830038: Pseudo dice [0.8487] +2024-11-22 15:29:25.830116: Epoch time: 18.97 s +2024-11-22 15:29:26.718279: +2024-11-22 15:29:26.718713: Epoch 5280 +2024-11-22 15:29:26.718845: Current learning rate: 0.00379 +2024-11-22 15:29:45.596514: train_loss -0.8097 +2024-11-22 15:29:45.596769: val_loss -0.7362 +2024-11-22 15:29:45.596843: Pseudo dice [0.8337] +2024-11-22 15:29:45.596920: Epoch time: 18.88 s +2024-11-22 15:29:46.490052: +2024-11-22 15:29:46.490478: Epoch 5281 +2024-11-22 15:29:46.490614: Current learning rate: 0.00379 +2024-11-22 15:30:04.977874: train_loss -0.7989 +2024-11-22 15:30:04.982166: val_loss -0.7309 +2024-11-22 15:30:04.982276: Pseudo dice [0.8429] +2024-11-22 15:30:04.982364: Epoch time: 18.49 s +2024-11-22 15:30:05.878864: +2024-11-22 15:30:05.879279: Epoch 5282 +2024-11-22 15:30:05.879414: Current learning rate: 0.00378 +2024-11-22 15:30:25.785535: train_loss -0.8018 +2024-11-22 15:30:25.785760: val_loss -0.7671 +2024-11-22 15:30:25.785838: Pseudo dice [0.8688] +2024-11-22 15:30:25.785915: Epoch time: 19.91 s +2024-11-22 15:30:26.682833: +2024-11-22 15:30:26.683263: Epoch 5283 +2024-11-22 15:30:26.683397: Current learning rate: 0.00378 +2024-11-22 15:30:44.833166: train_loss -0.7998 +2024-11-22 15:30:44.833386: val_loss -0.764 +2024-11-22 15:30:44.833466: Pseudo dice [0.8643] +2024-11-22 15:30:44.833548: Epoch time: 18.15 s +2024-11-22 15:30:45.725607: +2024-11-22 15:30:45.726030: Epoch 5284 +2024-11-22 15:30:45.726165: Current learning rate: 0.00378 +2024-11-22 15:31:03.672615: train_loss -0.7829 +2024-11-22 15:31:03.672831: val_loss -0.7536 +2024-11-22 15:31:03.672901: Pseudo dice [0.8386] +2024-11-22 15:31:03.672975: Epoch time: 17.95 s +2024-11-22 15:31:04.568002: +2024-11-22 15:31:04.568426: Epoch 5285 +2024-11-22 15:31:04.568568: Current learning rate: 0.00378 +2024-11-22 15:31:22.775204: train_loss -0.7866 +2024-11-22 15:31:22.775453: val_loss -0.74 +2024-11-22 15:31:22.775529: Pseudo dice [0.8264] +2024-11-22 15:31:22.775614: Epoch time: 18.21 s +2024-11-22 15:31:23.672586: +2024-11-22 15:31:23.672793: Epoch 5286 +2024-11-22 15:31:23.672906: Current learning rate: 0.00378 +2024-11-22 15:31:42.398162: train_loss -0.7999 +2024-11-22 15:31:42.398942: val_loss -0.7404 +2024-11-22 15:31:42.399035: Pseudo dice [0.8345] +2024-11-22 15:31:42.399115: Epoch time: 18.73 s +2024-11-22 15:31:43.672440: +2024-11-22 15:31:43.672656: Epoch 5287 +2024-11-22 15:31:43.672769: Current learning rate: 0.00378 +2024-11-22 15:32:02.028731: train_loss -0.7889 +2024-11-22 15:32:02.028965: val_loss -0.7296 +2024-11-22 15:32:02.029047: Pseudo dice [0.8547] +2024-11-22 15:32:02.029123: Epoch time: 18.36 s +2024-11-22 15:32:02.924648: +2024-11-22 15:32:02.924888: Epoch 5288 +2024-11-22 15:32:02.925011: Current learning rate: 0.00378 +2024-11-22 15:32:21.364082: train_loss -0.7992 +2024-11-22 15:32:21.364313: val_loss -0.7256 +2024-11-22 15:32:21.364391: Pseudo dice [0.8543] +2024-11-22 15:32:21.364475: Epoch time: 18.44 s +2024-11-22 15:32:22.310255: +2024-11-22 15:32:22.310492: Epoch 5289 +2024-11-22 15:32:22.310603: Current learning rate: 0.00378 +2024-11-22 15:32:40.374757: train_loss -0.797 +2024-11-22 15:32:40.375035: val_loss -0.7333 +2024-11-22 15:32:40.375117: Pseudo dice [0.8305] +2024-11-22 15:32:40.375201: Epoch time: 18.07 s +2024-11-22 15:32:41.272640: +2024-11-22 15:32:41.272846: Epoch 5290 +2024-11-22 15:32:41.272962: Current learning rate: 0.00377 +2024-11-22 15:33:00.072097: train_loss -0.7858 +2024-11-22 15:33:00.072404: val_loss -0.7308 +2024-11-22 15:33:00.072480: Pseudo dice [0.8425] +2024-11-22 15:33:00.072558: Epoch time: 18.8 s +2024-11-22 15:33:00.969470: +2024-11-22 15:33:00.969695: Epoch 5291 +2024-11-22 15:33:00.969809: Current learning rate: 0.00377 +2024-11-22 15:33:19.867783: train_loss -0.8003 +2024-11-22 15:33:19.868000: val_loss -0.715 +2024-11-22 15:33:19.868074: Pseudo dice [0.8274] +2024-11-22 15:33:19.868148: Epoch time: 18.9 s +2024-11-22 15:33:20.931090: +2024-11-22 15:33:20.931364: Epoch 5292 +2024-11-22 15:33:20.931477: Current learning rate: 0.00377 +2024-11-22 15:33:38.915697: train_loss -0.7927 +2024-11-22 15:33:38.915958: val_loss -0.7413 +2024-11-22 15:33:38.916049: Pseudo dice [0.842] +2024-11-22 15:33:38.916141: Epoch time: 17.99 s +2024-11-22 15:33:39.815922: +2024-11-22 15:33:39.816133: Epoch 5293 +2024-11-22 15:33:39.816245: Current learning rate: 0.00377 +2024-11-22 15:33:57.783937: train_loss -0.8017 +2024-11-22 15:33:57.784200: val_loss -0.7532 +2024-11-22 15:33:57.784277: Pseudo dice [0.8442] +2024-11-22 15:33:57.784361: Epoch time: 17.97 s +2024-11-22 15:33:58.736110: +2024-11-22 15:33:58.736411: Epoch 5294 +2024-11-22 15:33:58.736530: Current learning rate: 0.00377 +2024-11-22 15:34:18.406298: train_loss -0.7977 +2024-11-22 15:34:18.406511: val_loss -0.7541 +2024-11-22 15:34:18.406648: Pseudo dice [0.8394] +2024-11-22 15:34:18.406726: Epoch time: 19.67 s +2024-11-22 15:34:19.304506: +2024-11-22 15:34:19.304697: Epoch 5295 +2024-11-22 15:34:19.304812: Current learning rate: 0.00377 +2024-11-22 15:34:39.248973: train_loss -0.8051 +2024-11-22 15:34:39.249193: val_loss -0.7604 +2024-11-22 15:34:39.249271: Pseudo dice [0.8494] +2024-11-22 15:34:39.249349: Epoch time: 19.95 s +2024-11-22 15:34:40.150162: +2024-11-22 15:34:40.150413: Epoch 5296 +2024-11-22 15:34:40.150524: Current learning rate: 0.00377 +2024-11-22 15:34:58.411069: train_loss -0.8077 +2024-11-22 15:34:58.411321: val_loss -0.759 +2024-11-22 15:34:58.411404: Pseudo dice [0.8481] +2024-11-22 15:34:58.411487: Epoch time: 18.26 s +2024-11-22 15:34:59.301935: +2024-11-22 15:34:59.302141: Epoch 5297 +2024-11-22 15:34:59.302253: Current learning rate: 0.00377 +2024-11-22 15:35:17.635118: train_loss -0.7849 +2024-11-22 15:35:17.635366: val_loss -0.7388 +2024-11-22 15:35:17.635442: Pseudo dice [0.858] +2024-11-22 15:35:17.635559: Epoch time: 18.33 s +2024-11-22 15:35:18.521657: +2024-11-22 15:35:18.521867: Epoch 5298 +2024-11-22 15:35:18.521981: Current learning rate: 0.00376 +2024-11-22 15:35:38.955052: train_loss -0.7876 +2024-11-22 15:35:38.955343: val_loss -0.7514 +2024-11-22 15:35:38.955425: Pseudo dice [0.824] +2024-11-22 15:35:38.955505: Epoch time: 20.43 s +2024-11-22 15:35:40.263732: +2024-11-22 15:35:40.263968: Epoch 5299 +2024-11-22 15:35:40.264122: Current learning rate: 0.00376 +2024-11-22 15:35:58.994806: train_loss -0.7966 +2024-11-22 15:35:58.995089: val_loss -0.7277 +2024-11-22 15:35:58.995174: Pseudo dice [0.8497] +2024-11-22 15:35:58.995255: Epoch time: 18.73 s +2024-11-22 15:36:00.200111: +2024-11-22 15:36:00.200327: Epoch 5300 +2024-11-22 15:36:00.200437: Current learning rate: 0.00376 +2024-11-22 15:36:17.614493: train_loss -0.8092 +2024-11-22 15:36:17.614744: val_loss -0.7615 +2024-11-22 15:36:17.614820: Pseudo dice [0.8358] +2024-11-22 15:36:17.614903: Epoch time: 17.42 s +2024-11-22 15:36:18.512908: +2024-11-22 15:36:18.513132: Epoch 5301 +2024-11-22 15:36:18.513243: Current learning rate: 0.00376 +2024-11-22 15:36:37.546943: train_loss -0.8059 +2024-11-22 15:36:37.548166: val_loss -0.7567 +2024-11-22 15:36:37.548265: Pseudo dice [0.8545] +2024-11-22 15:36:37.548352: Epoch time: 19.03 s +2024-11-22 15:36:38.518515: +2024-11-22 15:36:38.518985: Epoch 5302 +2024-11-22 15:36:38.519112: Current learning rate: 0.00376 +2024-11-22 15:36:56.448188: train_loss -0.7959 +2024-11-22 15:36:56.448436: val_loss -0.7358 +2024-11-22 15:36:56.448521: Pseudo dice [0.8343] +2024-11-22 15:36:56.448599: Epoch time: 17.93 s +2024-11-22 15:36:57.342278: +2024-11-22 15:36:57.342516: Epoch 5303 +2024-11-22 15:36:57.342631: Current learning rate: 0.00376 +2024-11-22 15:37:15.573766: train_loss -0.8062 +2024-11-22 15:37:15.574067: val_loss -0.7153 +2024-11-22 15:37:15.574147: Pseudo dice [0.8445] +2024-11-22 15:37:15.574226: Epoch time: 18.23 s +2024-11-22 15:37:16.505349: +2024-11-22 15:37:16.505551: Epoch 5304 +2024-11-22 15:37:16.505662: Current learning rate: 0.00376 +2024-11-22 15:37:36.104436: train_loss -0.7945 +2024-11-22 15:37:36.109851: val_loss -0.7588 +2024-11-22 15:37:36.109977: Pseudo dice [0.8509] +2024-11-22 15:37:36.110089: Epoch time: 19.6 s +2024-11-22 15:37:37.061481: +2024-11-22 15:37:37.061694: Epoch 5305 +2024-11-22 15:37:37.061810: Current learning rate: 0.00376 +2024-11-22 15:37:55.264535: train_loss -0.8018 +2024-11-22 15:37:55.269983: val_loss -0.7689 +2024-11-22 15:37:55.270107: Pseudo dice [0.8553] +2024-11-22 15:37:55.270195: Epoch time: 18.2 s +2024-11-22 15:37:56.334219: +2024-11-22 15:37:56.334445: Epoch 5306 +2024-11-22 15:37:56.334562: Current learning rate: 0.00375 +2024-11-22 15:38:14.686786: train_loss -0.7954 +2024-11-22 15:38:14.687080: val_loss -0.743 +2024-11-22 15:38:14.687158: Pseudo dice [0.8574] +2024-11-22 15:38:14.687237: Epoch time: 18.35 s +2024-11-22 15:38:15.583633: +2024-11-22 15:38:15.583849: Epoch 5307 +2024-11-22 15:38:15.583962: Current learning rate: 0.00375 +2024-11-22 15:38:33.312711: train_loss -0.7963 +2024-11-22 15:38:33.312932: val_loss -0.736 +2024-11-22 15:38:33.313019: Pseudo dice [0.8296] +2024-11-22 15:38:33.313105: Epoch time: 17.73 s +2024-11-22 15:38:34.223118: +2024-11-22 15:38:34.223326: Epoch 5308 +2024-11-22 15:38:34.223440: Current learning rate: 0.00375 +2024-11-22 15:38:53.363493: train_loss -0.7923 +2024-11-22 15:38:53.363749: val_loss -0.7339 +2024-11-22 15:38:53.363826: Pseudo dice [0.8424] +2024-11-22 15:38:53.363914: Epoch time: 19.14 s +2024-11-22 15:38:54.257417: +2024-11-22 15:38:54.257637: Epoch 5309 +2024-11-22 15:38:54.257745: Current learning rate: 0.00375 +2024-11-22 15:39:11.511135: train_loss -0.7858 +2024-11-22 15:39:11.511358: val_loss -0.7545 +2024-11-22 15:39:11.511436: Pseudo dice [0.8303] +2024-11-22 15:39:11.511516: Epoch time: 17.25 s +2024-11-22 15:39:12.400656: +2024-11-22 15:39:12.400864: Epoch 5310 +2024-11-22 15:39:12.400977: Current learning rate: 0.00375 +2024-11-22 15:39:30.829781: train_loss -0.7908 +2024-11-22 15:39:30.830048: val_loss -0.7439 +2024-11-22 15:39:30.830126: Pseudo dice [0.8355] +2024-11-22 15:39:30.830208: Epoch time: 18.43 s +2024-11-22 15:39:31.734635: +2024-11-22 15:39:31.734975: Epoch 5311 +2024-11-22 15:39:31.735116: Current learning rate: 0.00375 +2024-11-22 15:39:50.279135: train_loss -0.7919 +2024-11-22 15:39:50.279355: val_loss -0.7571 +2024-11-22 15:39:50.279430: Pseudo dice [0.8392] +2024-11-22 15:39:50.279513: Epoch time: 18.55 s +2024-11-22 15:39:51.170757: +2024-11-22 15:39:51.170977: Epoch 5312 +2024-11-22 15:39:51.171087: Current learning rate: 0.00375 +2024-11-22 15:40:09.592546: train_loss -0.7996 +2024-11-22 15:40:09.592802: val_loss -0.7449 +2024-11-22 15:40:09.592881: Pseudo dice [0.8505] +2024-11-22 15:40:09.592968: Epoch time: 18.42 s +2024-11-22 15:40:10.486059: +2024-11-22 15:40:10.486280: Epoch 5313 +2024-11-22 15:40:10.486393: Current learning rate: 0.00375 +2024-11-22 15:40:30.304976: train_loss -0.7888 +2024-11-22 15:40:30.305207: val_loss -0.7259 +2024-11-22 15:40:30.305291: Pseudo dice [0.8439] +2024-11-22 15:40:30.305373: Epoch time: 19.82 s +2024-11-22 15:40:31.371789: +2024-11-22 15:40:31.372022: Epoch 5314 +2024-11-22 15:40:31.372132: Current learning rate: 0.00374 +2024-11-22 15:40:50.060886: train_loss -0.7922 +2024-11-22 15:40:50.061165: val_loss -0.7558 +2024-11-22 15:40:50.061242: Pseudo dice [0.84] +2024-11-22 15:40:50.061318: Epoch time: 18.69 s +2024-11-22 15:40:50.969733: +2024-11-22 15:40:50.970060: Epoch 5315 +2024-11-22 15:40:50.970179: Current learning rate: 0.00374 +2024-11-22 15:41:09.373471: train_loss -0.8017 +2024-11-22 15:41:09.373742: val_loss -0.7784 +2024-11-22 15:41:09.373824: Pseudo dice [0.8767] +2024-11-22 15:41:09.373901: Epoch time: 18.4 s +2024-11-22 15:41:10.303515: +2024-11-22 15:41:10.303712: Epoch 5316 +2024-11-22 15:41:10.303824: Current learning rate: 0.00374 +2024-11-22 15:41:29.005591: train_loss -0.8041 +2024-11-22 15:41:29.005860: val_loss -0.7419 +2024-11-22 15:41:29.005935: Pseudo dice [0.825] +2024-11-22 15:41:29.006029: Epoch time: 18.7 s +2024-11-22 15:41:29.903226: +2024-11-22 15:41:29.903428: Epoch 5317 +2024-11-22 15:41:29.903538: Current learning rate: 0.00374 +2024-11-22 15:41:48.162616: train_loss -0.8025 +2024-11-22 15:41:48.162841: val_loss -0.7695 +2024-11-22 15:41:48.162917: Pseudo dice [0.8595] +2024-11-22 15:41:48.163002: Epoch time: 18.26 s +2024-11-22 15:41:49.101282: +2024-11-22 15:41:49.101586: Epoch 5318 +2024-11-22 15:41:49.101696: Current learning rate: 0.00374 +2024-11-22 15:42:07.500425: train_loss -0.7984 +2024-11-22 15:42:07.505822: val_loss -0.7407 +2024-11-22 15:42:07.505968: Pseudo dice [0.8149] +2024-11-22 15:42:07.506060: Epoch time: 18.4 s +2024-11-22 15:42:08.733193: +2024-11-22 15:42:08.733466: Epoch 5319 +2024-11-22 15:42:08.733583: Current learning rate: 0.00374 +2024-11-22 15:42:28.083467: train_loss -0.8019 +2024-11-22 15:42:28.083783: val_loss -0.7673 +2024-11-22 15:42:28.083862: Pseudo dice [0.8472] +2024-11-22 15:42:28.083945: Epoch time: 19.35 s +2024-11-22 15:42:28.978748: +2024-11-22 15:42:28.979028: Epoch 5320 +2024-11-22 15:42:28.979143: Current learning rate: 0.00374 +2024-11-22 15:42:48.292536: train_loss -0.8031 +2024-11-22 15:42:48.294929: val_loss -0.7568 +2024-11-22 15:42:48.295047: Pseudo dice [0.8409] +2024-11-22 15:42:48.295132: Epoch time: 19.31 s +2024-11-22 15:42:49.319816: +2024-11-22 15:42:49.320125: Epoch 5321 +2024-11-22 15:42:49.320236: Current learning rate: 0.00374 +2024-11-22 15:43:07.687683: train_loss -0.8053 +2024-11-22 15:43:07.687900: val_loss -0.7696 +2024-11-22 15:43:07.687977: Pseudo dice [0.8518] +2024-11-22 15:43:07.688063: Epoch time: 18.37 s +2024-11-22 15:43:09.012937: +2024-11-22 15:43:09.013170: Epoch 5322 +2024-11-22 15:43:09.013285: Current learning rate: 0.00373 +2024-11-22 15:43:26.614843: train_loss -0.8067 +2024-11-22 15:43:26.615087: val_loss -0.7517 +2024-11-22 15:43:26.615165: Pseudo dice [0.8412] +2024-11-22 15:43:26.615243: Epoch time: 17.6 s +2024-11-22 15:43:27.617547: +2024-11-22 15:43:27.617759: Epoch 5323 +2024-11-22 15:43:27.617875: Current learning rate: 0.00373 +2024-11-22 15:43:47.883104: train_loss -0.798 +2024-11-22 15:43:47.883421: val_loss -0.7676 +2024-11-22 15:43:47.883504: Pseudo dice [0.8337] +2024-11-22 15:43:47.883591: Epoch time: 20.27 s +2024-11-22 15:43:48.782548: +2024-11-22 15:43:48.782827: Epoch 5324 +2024-11-22 15:43:48.782942: Current learning rate: 0.00373 +2024-11-22 15:44:08.026541: train_loss -0.8064 +2024-11-22 15:44:08.026764: val_loss -0.7375 +2024-11-22 15:44:08.026879: Pseudo dice [0.8585] +2024-11-22 15:44:08.026971: Epoch time: 19.24 s +2024-11-22 15:44:09.024863: +2024-11-22 15:44:09.025088: Epoch 5325 +2024-11-22 15:44:09.025201: Current learning rate: 0.00373 +2024-11-22 15:44:29.709074: train_loss -0.8021 +2024-11-22 15:44:29.709287: val_loss -0.7598 +2024-11-22 15:44:29.709364: Pseudo dice [0.8559] +2024-11-22 15:44:29.709446: Epoch time: 20.69 s +2024-11-22 15:44:30.599725: +2024-11-22 15:44:30.599927: Epoch 5326 +2024-11-22 15:44:30.600048: Current learning rate: 0.00373 +2024-11-22 15:44:49.710253: train_loss -0.7939 +2024-11-22 15:44:49.710475: val_loss -0.7308 +2024-11-22 15:44:49.710555: Pseudo dice [0.8352] +2024-11-22 15:44:49.710633: Epoch time: 19.11 s +2024-11-22 15:44:50.603559: +2024-11-22 15:44:50.603772: Epoch 5327 +2024-11-22 15:44:50.603883: Current learning rate: 0.00373 +2024-11-22 15:45:08.575678: train_loss -0.7967 +2024-11-22 15:45:08.575923: val_loss -0.7642 +2024-11-22 15:45:08.576008: Pseudo dice [0.8513] +2024-11-22 15:45:08.576091: Epoch time: 17.97 s +2024-11-22 15:45:09.476881: +2024-11-22 15:45:09.477079: Epoch 5328 +2024-11-22 15:45:09.477191: Current learning rate: 0.00373 +2024-11-22 15:45:28.115585: train_loss -0.7974 +2024-11-22 15:45:28.115830: val_loss -0.7511 +2024-11-22 15:45:28.115910: Pseudo dice [0.8683] +2024-11-22 15:45:28.115988: Epoch time: 18.64 s +2024-11-22 15:45:29.033995: +2024-11-22 15:45:29.034202: Epoch 5329 +2024-11-22 15:45:29.034327: Current learning rate: 0.00373 +2024-11-22 15:45:47.384598: train_loss -0.796 +2024-11-22 15:45:47.384807: val_loss -0.7317 +2024-11-22 15:45:47.384885: Pseudo dice [0.8474] +2024-11-22 15:45:47.384962: Epoch time: 18.35 s +2024-11-22 15:45:48.277257: +2024-11-22 15:45:48.277462: Epoch 5330 +2024-11-22 15:45:48.277576: Current learning rate: 0.00372 +2024-11-22 15:46:06.967588: train_loss -0.7905 +2024-11-22 15:46:06.970025: val_loss -0.7632 +2024-11-22 15:46:06.970125: Pseudo dice [0.8502] +2024-11-22 15:46:06.970211: Epoch time: 18.69 s +2024-11-22 15:46:07.964711: +2024-11-22 15:46:07.964893: Epoch 5331 +2024-11-22 15:46:07.965012: Current learning rate: 0.00372 +2024-11-22 15:46:25.482428: train_loss -0.8088 +2024-11-22 15:46:25.482671: val_loss -0.7783 +2024-11-22 15:46:25.482744: Pseudo dice [0.8607] +2024-11-22 15:46:25.482830: Epoch time: 17.52 s +2024-11-22 15:46:26.375112: +2024-11-22 15:46:26.375300: Epoch 5332 +2024-11-22 15:46:26.375411: Current learning rate: 0.00372 +2024-11-22 15:46:45.089390: train_loss -0.7992 +2024-11-22 15:46:45.089601: val_loss -0.7886 +2024-11-22 15:46:45.089679: Pseudo dice [0.8508] +2024-11-22 15:46:45.089754: Epoch time: 18.72 s +2024-11-22 15:46:45.978030: +2024-11-22 15:46:45.978245: Epoch 5333 +2024-11-22 15:46:45.978359: Current learning rate: 0.00372 +2024-11-22 15:47:04.150387: train_loss -0.8063 +2024-11-22 15:47:04.150609: val_loss -0.7645 +2024-11-22 15:47:04.150711: Pseudo dice [0.8439] +2024-11-22 15:47:04.150791: Epoch time: 18.17 s +2024-11-22 15:47:05.447782: +2024-11-22 15:47:05.448017: Epoch 5334 +2024-11-22 15:47:05.448128: Current learning rate: 0.00372 +2024-11-22 15:47:23.710594: train_loss -0.801 +2024-11-22 15:47:23.710853: val_loss -0.732 +2024-11-22 15:47:23.710998: Pseudo dice [0.8341] +2024-11-22 15:47:23.711088: Epoch time: 18.26 s +2024-11-22 15:47:24.603511: +2024-11-22 15:47:24.603727: Epoch 5335 +2024-11-22 15:47:24.603846: Current learning rate: 0.00372 +2024-11-22 15:47:42.809887: train_loss -0.7987 +2024-11-22 15:47:42.810121: val_loss -0.7529 +2024-11-22 15:47:42.810198: Pseudo dice [0.8521] +2024-11-22 15:47:42.813521: Epoch time: 18.21 s +2024-11-22 15:47:43.727646: +2024-11-22 15:47:43.727860: Epoch 5336 +2024-11-22 15:47:43.727971: Current learning rate: 0.00372 +2024-11-22 15:48:03.249777: train_loss -0.8073 +2024-11-22 15:48:03.250006: val_loss -0.7261 +2024-11-22 15:48:03.250081: Pseudo dice [0.817] +2024-11-22 15:48:03.250154: Epoch time: 19.52 s +2024-11-22 15:48:04.143997: +2024-11-22 15:48:04.144220: Epoch 5337 +2024-11-22 15:48:04.144338: Current learning rate: 0.00372 +2024-11-22 15:48:22.806040: train_loss -0.7941 +2024-11-22 15:48:22.806268: val_loss -0.7441 +2024-11-22 15:48:22.806343: Pseudo dice [0.8428] +2024-11-22 15:48:22.806424: Epoch time: 18.66 s +2024-11-22 15:48:23.698506: +2024-11-22 15:48:23.698709: Epoch 5338 +2024-11-22 15:48:23.698822: Current learning rate: 0.00371 +2024-11-22 15:48:43.269276: train_loss -0.8016 +2024-11-22 15:48:43.271620: val_loss -0.7617 +2024-11-22 15:48:43.271712: Pseudo dice [0.8444] +2024-11-22 15:48:43.271793: Epoch time: 19.57 s +2024-11-22 15:48:44.315080: +2024-11-22 15:48:44.315309: Epoch 5339 +2024-11-22 15:48:44.315424: Current learning rate: 0.00371 +2024-11-22 15:49:04.314280: train_loss -0.7965 +2024-11-22 15:49:04.314494: val_loss -0.7234 +2024-11-22 15:49:04.314572: Pseudo dice [0.841] +2024-11-22 15:49:04.314649: Epoch time: 20.0 s +2024-11-22 15:49:05.205603: +2024-11-22 15:49:05.205805: Epoch 5340 +2024-11-22 15:49:05.205933: Current learning rate: 0.00371 +2024-11-22 15:49:25.246099: train_loss -0.8057 +2024-11-22 15:49:25.246321: val_loss -0.7163 +2024-11-22 15:49:25.251530: Pseudo dice [0.8427] +2024-11-22 15:49:25.251740: Epoch time: 20.04 s +2024-11-22 15:49:26.157966: +2024-11-22 15:49:26.158187: Epoch 5341 +2024-11-22 15:49:26.158303: Current learning rate: 0.00371 +2024-11-22 15:49:45.001497: train_loss -0.8059 +2024-11-22 15:49:45.001758: val_loss -0.7864 +2024-11-22 15:49:45.001847: Pseudo dice [0.8612] +2024-11-22 15:49:45.001932: Epoch time: 18.84 s +2024-11-22 15:49:45.898858: +2024-11-22 15:49:45.899079: Epoch 5342 +2024-11-22 15:49:45.899192: Current learning rate: 0.00371 +2024-11-22 15:50:03.763999: train_loss -0.8116 +2024-11-22 15:50:03.764219: val_loss -0.7444 +2024-11-22 15:50:03.764295: Pseudo dice [0.8568] +2024-11-22 15:50:03.764374: Epoch time: 17.87 s +2024-11-22 15:50:04.652642: +2024-11-22 15:50:04.652842: Epoch 5343 +2024-11-22 15:50:04.652956: Current learning rate: 0.00371 +2024-11-22 15:50:23.310865: train_loss -0.8037 +2024-11-22 15:50:23.311095: val_loss -0.7424 +2024-11-22 15:50:23.311172: Pseudo dice [0.8457] +2024-11-22 15:50:23.311248: Epoch time: 18.66 s +2024-11-22 15:50:24.199988: +2024-11-22 15:50:24.200203: Epoch 5344 +2024-11-22 15:50:24.200319: Current learning rate: 0.00371 +2024-11-22 15:50:43.218098: train_loss -0.8056 +2024-11-22 15:50:43.218328: val_loss -0.7749 +2024-11-22 15:50:43.218404: Pseudo dice [0.8509] +2024-11-22 15:50:43.218479: Epoch time: 19.02 s +2024-11-22 15:50:44.108140: +2024-11-22 15:50:44.108341: Epoch 5345 +2024-11-22 15:50:44.108454: Current learning rate: 0.00371 +2024-11-22 15:51:03.098272: train_loss -0.7989 +2024-11-22 15:51:03.098526: val_loss -0.7411 +2024-11-22 15:51:03.098605: Pseudo dice [0.8418] +2024-11-22 15:51:03.098689: Epoch time: 18.99 s +2024-11-22 15:51:04.441028: +2024-11-22 15:51:04.441265: Epoch 5346 +2024-11-22 15:51:04.441389: Current learning rate: 0.0037 +2024-11-22 15:51:22.843533: train_loss -0.8 +2024-11-22 15:51:22.848953: val_loss -0.7474 +2024-11-22 15:51:22.849072: Pseudo dice [0.8403] +2024-11-22 15:51:22.849150: Epoch time: 18.4 s +2024-11-22 15:51:23.773999: +2024-11-22 15:51:23.774219: Epoch 5347 +2024-11-22 15:51:23.774330: Current learning rate: 0.0037 +2024-11-22 15:51:43.442045: train_loss -0.7989 +2024-11-22 15:51:43.447478: val_loss -0.735 +2024-11-22 15:51:43.447565: Pseudo dice [0.8359] +2024-11-22 15:51:43.447654: Epoch time: 19.67 s +2024-11-22 15:51:44.505651: +2024-11-22 15:51:44.505850: Epoch 5348 +2024-11-22 15:51:44.505975: Current learning rate: 0.0037 +2024-11-22 15:52:02.761850: train_loss -0.8021 +2024-11-22 15:52:02.762092: val_loss -0.769 +2024-11-22 15:52:02.762201: Pseudo dice [0.8433] +2024-11-22 15:52:02.762331: Epoch time: 18.26 s +2024-11-22 15:52:03.655856: +2024-11-22 15:52:03.656093: Epoch 5349 +2024-11-22 15:52:03.656207: Current learning rate: 0.0037 +2024-11-22 15:52:22.822284: train_loss -0.7952 +2024-11-22 15:52:22.822529: val_loss -0.7619 +2024-11-22 15:52:22.822602: Pseudo dice [0.8559] +2024-11-22 15:52:22.822685: Epoch time: 19.17 s +2024-11-22 15:52:24.111042: +2024-11-22 15:52:24.111277: Epoch 5350 +2024-11-22 15:52:24.111390: Current learning rate: 0.0037 +2024-11-22 15:52:42.276840: train_loss -0.81 +2024-11-22 15:52:42.277063: val_loss -0.756 +2024-11-22 15:52:42.277139: Pseudo dice [0.8429] +2024-11-22 15:52:42.277219: Epoch time: 18.17 s +2024-11-22 15:52:43.269674: +2024-11-22 15:52:43.269917: Epoch 5351 +2024-11-22 15:52:43.270034: Current learning rate: 0.0037 +2024-11-22 15:53:02.041139: train_loss -0.8007 +2024-11-22 15:53:02.041424: val_loss -0.7568 +2024-11-22 15:53:02.041512: Pseudo dice [0.8588] +2024-11-22 15:53:02.041594: Epoch time: 18.77 s +2024-11-22 15:53:02.954214: +2024-11-22 15:53:02.954421: Epoch 5352 +2024-11-22 15:53:02.954530: Current learning rate: 0.0037 +2024-11-22 15:53:21.937453: train_loss -0.8081 +2024-11-22 15:53:21.937685: val_loss -0.7327 +2024-11-22 15:53:21.937761: Pseudo dice [0.8405] +2024-11-22 15:53:21.937841: Epoch time: 18.98 s +2024-11-22 15:53:22.834563: +2024-11-22 15:53:22.834785: Epoch 5353 +2024-11-22 15:53:22.834898: Current learning rate: 0.0037 +2024-11-22 15:53:41.224381: train_loss -0.8072 +2024-11-22 15:53:41.224632: val_loss -0.7716 +2024-11-22 15:53:41.224710: Pseudo dice [0.8547] +2024-11-22 15:53:41.224793: Epoch time: 18.39 s +2024-11-22 15:53:42.124106: +2024-11-22 15:53:42.124314: Epoch 5354 +2024-11-22 15:53:42.124427: Current learning rate: 0.00369 +2024-11-22 15:54:01.034815: train_loss -0.808 +2024-11-22 15:54:01.035038: val_loss -0.7423 +2024-11-22 15:54:01.035115: Pseudo dice [0.8409] +2024-11-22 15:54:01.035192: Epoch time: 18.91 s +2024-11-22 15:54:01.926433: +2024-11-22 15:54:01.926627: Epoch 5355 +2024-11-22 15:54:01.926738: Current learning rate: 0.00369 +2024-11-22 15:54:20.343398: train_loss -0.8103 +2024-11-22 15:54:20.343644: val_loss -0.7326 +2024-11-22 15:54:20.343724: Pseudo dice [0.8426] +2024-11-22 15:54:20.343803: Epoch time: 18.42 s +2024-11-22 15:54:21.234503: +2024-11-22 15:54:21.234691: Epoch 5356 +2024-11-22 15:54:21.234807: Current learning rate: 0.00369 +2024-11-22 15:54:39.996138: train_loss -0.7996 +2024-11-22 15:54:39.996368: val_loss -0.7608 +2024-11-22 15:54:39.996448: Pseudo dice [0.8383] +2024-11-22 15:54:39.996531: Epoch time: 18.76 s +2024-11-22 15:54:40.885242: +2024-11-22 15:54:40.885472: Epoch 5357 +2024-11-22 15:54:40.885593: Current learning rate: 0.00369 +2024-11-22 15:54:59.472686: train_loss -0.8036 +2024-11-22 15:54:59.472949: val_loss -0.7647 +2024-11-22 15:54:59.473033: Pseudo dice [0.8638] +2024-11-22 15:54:59.473119: Epoch time: 18.59 s +2024-11-22 15:55:00.368973: +2024-11-22 15:55:00.369191: Epoch 5358 +2024-11-22 15:55:00.369303: Current learning rate: 0.00369 +2024-11-22 15:55:19.415376: train_loss -0.8014 +2024-11-22 15:55:19.415597: val_loss -0.7581 +2024-11-22 15:55:19.415677: Pseudo dice [0.8495] +2024-11-22 15:55:19.415768: Epoch time: 19.05 s +2024-11-22 15:55:20.314957: +2024-11-22 15:55:20.315161: Epoch 5359 +2024-11-22 15:55:20.315269: Current learning rate: 0.00369 +2024-11-22 15:55:39.393280: train_loss -0.7909 +2024-11-22 15:55:39.393508: val_loss -0.7603 +2024-11-22 15:55:39.393587: Pseudo dice [0.8668] +2024-11-22 15:55:39.393669: Epoch time: 19.08 s +2024-11-22 15:55:40.433756: +2024-11-22 15:55:40.434044: Epoch 5360 +2024-11-22 15:55:40.434157: Current learning rate: 0.00369 +2024-11-22 15:55:59.220870: train_loss -0.8042 +2024-11-22 15:55:59.221130: val_loss -0.7421 +2024-11-22 15:55:59.221206: Pseudo dice [0.8356] +2024-11-22 15:55:59.221293: Epoch time: 18.79 s +2024-11-22 15:56:00.118894: +2024-11-22 15:56:00.119174: Epoch 5361 +2024-11-22 15:56:00.119293: Current learning rate: 0.00369 +2024-11-22 15:56:18.734951: train_loss -0.8032 +2024-11-22 15:56:18.735224: val_loss -0.7423 +2024-11-22 15:56:18.735300: Pseudo dice [0.861] +2024-11-22 15:56:18.735376: Epoch time: 18.62 s +2024-11-22 15:56:19.636967: +2024-11-22 15:56:19.637161: Epoch 5362 +2024-11-22 15:56:19.637273: Current learning rate: 0.00368 +2024-11-22 15:56:37.454455: train_loss -0.8047 +2024-11-22 15:56:37.454732: val_loss -0.7377 +2024-11-22 15:56:37.454811: Pseudo dice [0.87] +2024-11-22 15:56:37.454897: Epoch time: 17.82 s +2024-11-22 15:56:38.383403: +2024-11-22 15:56:38.383617: Epoch 5363 +2024-11-22 15:56:38.383733: Current learning rate: 0.00368 +2024-11-22 15:56:57.431371: train_loss -0.7949 +2024-11-22 15:56:57.431616: val_loss -0.7493 +2024-11-22 15:56:57.431693: Pseudo dice [0.8139] +2024-11-22 15:56:57.431773: Epoch time: 19.05 s +2024-11-22 15:56:58.338936: +2024-11-22 15:56:58.339134: Epoch 5364 +2024-11-22 15:56:58.339247: Current learning rate: 0.00368 +2024-11-22 15:57:16.612709: train_loss -0.7994 +2024-11-22 15:57:16.612972: val_loss -0.7702 +2024-11-22 15:57:16.613059: Pseudo dice [0.8636] +2024-11-22 15:57:16.613150: Epoch time: 18.27 s +2024-11-22 15:57:17.697971: +2024-11-22 15:57:17.698186: Epoch 5365 +2024-11-22 15:57:17.698300: Current learning rate: 0.00368 +2024-11-22 15:57:36.194367: train_loss -0.8051 +2024-11-22 15:57:36.194594: val_loss -0.7368 +2024-11-22 15:57:36.199923: Pseudo dice [0.8528] +2024-11-22 15:57:36.200022: Epoch time: 18.5 s +2024-11-22 15:57:37.244450: +2024-11-22 15:57:37.244820: Epoch 5366 +2024-11-22 15:57:37.244933: Current learning rate: 0.00368 +2024-11-22 15:57:55.562600: train_loss -0.8038 +2024-11-22 15:57:55.562815: val_loss -0.7284 +2024-11-22 15:57:55.562889: Pseudo dice [0.8644] +2024-11-22 15:57:55.562963: Epoch time: 18.32 s +2024-11-22 15:57:56.457357: +2024-11-22 15:57:56.457580: Epoch 5367 +2024-11-22 15:57:56.457699: Current learning rate: 0.00368 +2024-11-22 15:58:14.228301: train_loss -0.7908 +2024-11-22 15:58:14.228526: val_loss -0.74 +2024-11-22 15:58:14.228604: Pseudo dice [0.8438] +2024-11-22 15:58:14.228683: Epoch time: 17.77 s +2024-11-22 15:58:15.121802: +2024-11-22 15:58:15.122079: Epoch 5368 +2024-11-22 15:58:15.122204: Current learning rate: 0.00368 +2024-11-22 15:58:34.256048: train_loss -0.7655 +2024-11-22 15:58:34.256358: val_loss -0.7367 +2024-11-22 15:58:34.256435: Pseudo dice [0.8522] +2024-11-22 15:58:34.256518: Epoch time: 19.13 s +2024-11-22 15:58:35.545340: +2024-11-22 15:58:35.545551: Epoch 5369 +2024-11-22 15:58:35.545672: Current learning rate: 0.00368 +2024-11-22 15:58:54.462753: train_loss -0.7832 +2024-11-22 15:58:54.462975: val_loss -0.7172 +2024-11-22 15:58:54.463061: Pseudo dice [0.8422] +2024-11-22 15:58:54.463140: Epoch time: 18.92 s +2024-11-22 15:58:55.545914: +2024-11-22 15:58:55.546143: Epoch 5370 +2024-11-22 15:58:55.546260: Current learning rate: 0.00367 +2024-11-22 15:59:14.435751: train_loss -0.7938 +2024-11-22 15:59:14.435974: val_loss -0.7437 +2024-11-22 15:59:14.436058: Pseudo dice [0.8622] +2024-11-22 15:59:14.436138: Epoch time: 18.89 s +2024-11-22 15:59:15.328329: +2024-11-22 15:59:15.328554: Epoch 5371 +2024-11-22 15:59:15.328668: Current learning rate: 0.00367 +2024-11-22 15:59:34.304662: train_loss -0.8019 +2024-11-22 15:59:34.304912: val_loss -0.7769 +2024-11-22 15:59:34.304998: Pseudo dice [0.837] +2024-11-22 15:59:34.305090: Epoch time: 18.98 s +2024-11-22 15:59:35.204256: +2024-11-22 15:59:35.204554: Epoch 5372 +2024-11-22 15:59:35.204667: Current learning rate: 0.00367 +2024-11-22 15:59:53.522830: train_loss -0.8039 +2024-11-22 15:59:53.523058: val_loss -0.7265 +2024-11-22 15:59:53.523135: Pseudo dice [0.8574] +2024-11-22 15:59:53.523212: Epoch time: 18.32 s +2024-11-22 15:59:54.409889: +2024-11-22 15:59:54.410106: Epoch 5373 +2024-11-22 15:59:54.410222: Current learning rate: 0.00367 +2024-11-22 16:00:13.046619: train_loss -0.7951 +2024-11-22 16:00:13.046835: val_loss -0.7502 +2024-11-22 16:00:13.046910: Pseudo dice [0.8478] +2024-11-22 16:00:13.046987: Epoch time: 18.64 s +2024-11-22 16:00:13.941989: +2024-11-22 16:00:13.942214: Epoch 5374 +2024-11-22 16:00:13.942344: Current learning rate: 0.00367 +2024-11-22 16:00:33.402965: train_loss -0.7909 +2024-11-22 16:00:33.403198: val_loss -0.7629 +2024-11-22 16:00:33.403287: Pseudo dice [0.8435] +2024-11-22 16:00:33.403366: Epoch time: 19.46 s +2024-11-22 16:00:34.299021: +2024-11-22 16:00:34.299225: Epoch 5375 +2024-11-22 16:00:34.299338: Current learning rate: 0.00367 +2024-11-22 16:00:53.022032: train_loss -0.7909 +2024-11-22 16:00:53.022261: val_loss -0.7201 +2024-11-22 16:00:53.022338: Pseudo dice [0.8127] +2024-11-22 16:00:53.022417: Epoch time: 18.72 s +2024-11-22 16:00:53.919439: +2024-11-22 16:00:53.919657: Epoch 5376 +2024-11-22 16:00:53.919771: Current learning rate: 0.00367 +2024-11-22 16:01:12.809274: train_loss -0.8041 +2024-11-22 16:01:12.809494: val_loss -0.7486 +2024-11-22 16:01:12.809565: Pseudo dice [0.8347] +2024-11-22 16:01:12.814824: Epoch time: 18.89 s +2024-11-22 16:01:13.801759: +2024-11-22 16:01:13.801968: Epoch 5377 +2024-11-22 16:01:13.802088: Current learning rate: 0.00367 +2024-11-22 16:01:32.097519: train_loss -0.8034 +2024-11-22 16:01:32.097741: val_loss -0.7473 +2024-11-22 16:01:32.097820: Pseudo dice [0.86] +2024-11-22 16:01:32.097898: Epoch time: 18.3 s +2024-11-22 16:01:33.000816: +2024-11-22 16:01:33.001041: Epoch 5378 +2024-11-22 16:01:33.001166: Current learning rate: 0.00366 +2024-11-22 16:01:52.227190: train_loss -0.7978 +2024-11-22 16:01:52.227413: val_loss -0.7439 +2024-11-22 16:01:52.227547: Pseudo dice [0.8464] +2024-11-22 16:01:52.227648: Epoch time: 19.23 s +2024-11-22 16:01:53.141011: +2024-11-22 16:01:53.141234: Epoch 5379 +2024-11-22 16:01:53.141354: Current learning rate: 0.00366 +2024-11-22 16:02:12.387747: train_loss -0.7878 +2024-11-22 16:02:12.388005: val_loss -0.7833 +2024-11-22 16:02:12.388083: Pseudo dice [0.8569] +2024-11-22 16:02:12.388166: Epoch time: 19.25 s +2024-11-22 16:02:13.358872: +2024-11-22 16:02:13.359144: Epoch 5380 +2024-11-22 16:02:13.359261: Current learning rate: 0.00366 +2024-11-22 16:02:32.400026: train_loss -0.7871 +2024-11-22 16:02:32.400254: val_loss -0.7674 +2024-11-22 16:02:32.400332: Pseudo dice [0.841] +2024-11-22 16:02:32.400410: Epoch time: 19.04 s +2024-11-22 16:02:33.744687: +2024-11-22 16:02:33.744919: Epoch 5381 +2024-11-22 16:02:33.745037: Current learning rate: 0.00366 +2024-11-22 16:02:53.077077: train_loss -0.7883 +2024-11-22 16:02:53.077326: val_loss -0.7595 +2024-11-22 16:02:53.077407: Pseudo dice [0.8617] +2024-11-22 16:02:53.077486: Epoch time: 19.33 s +2024-11-22 16:02:53.965064: +2024-11-22 16:02:53.965289: Epoch 5382 +2024-11-22 16:02:53.965401: Current learning rate: 0.00366 +2024-11-22 16:03:11.866690: train_loss -0.7861 +2024-11-22 16:03:11.866939: val_loss -0.7381 +2024-11-22 16:03:11.867026: Pseudo dice [0.8522] +2024-11-22 16:03:11.867110: Epoch time: 17.9 s +2024-11-22 16:03:12.847218: +2024-11-22 16:03:12.847425: Epoch 5383 +2024-11-22 16:03:12.847539: Current learning rate: 0.00366 +2024-11-22 16:03:31.699189: train_loss -0.7884 +2024-11-22 16:03:31.699439: val_loss -0.7109 +2024-11-22 16:03:31.699518: Pseudo dice [0.8422] +2024-11-22 16:03:31.699600: Epoch time: 18.85 s +2024-11-22 16:03:32.601722: +2024-11-22 16:03:32.601948: Epoch 5384 +2024-11-22 16:03:32.602066: Current learning rate: 0.00366 +2024-11-22 16:03:51.513111: train_loss -0.7827 +2024-11-22 16:03:51.513337: val_loss -0.7411 +2024-11-22 16:03:51.513410: Pseudo dice [0.8564] +2024-11-22 16:03:51.513484: Epoch time: 18.91 s +2024-11-22 16:03:52.416771: +2024-11-22 16:03:52.416982: Epoch 5385 +2024-11-22 16:03:52.417104: Current learning rate: 0.00366 +2024-11-22 16:04:10.852087: train_loss -0.7905 +2024-11-22 16:04:10.852312: val_loss -0.747 +2024-11-22 16:04:10.852386: Pseudo dice [0.8255] +2024-11-22 16:04:10.852467: Epoch time: 18.44 s +2024-11-22 16:04:11.769971: +2024-11-22 16:04:11.770178: Epoch 5386 +2024-11-22 16:04:11.770298: Current learning rate: 0.00365 +2024-11-22 16:04:28.729537: train_loss -0.7943 +2024-11-22 16:04:28.729755: val_loss -0.7714 +2024-11-22 16:04:28.729828: Pseudo dice [0.8694] +2024-11-22 16:04:28.729903: Epoch time: 16.96 s +2024-11-22 16:04:29.619601: +2024-11-22 16:04:29.619821: Epoch 5387 +2024-11-22 16:04:29.619939: Current learning rate: 0.00365 +2024-11-22 16:04:48.179893: train_loss -0.7868 +2024-11-22 16:04:48.185344: val_loss -0.7349 +2024-11-22 16:04:48.185474: Pseudo dice [0.8353] +2024-11-22 16:04:48.185565: Epoch time: 18.56 s +2024-11-22 16:04:49.262049: +2024-11-22 16:04:49.262256: Epoch 5388 +2024-11-22 16:04:49.262371: Current learning rate: 0.00365 +2024-11-22 16:05:07.420807: train_loss -0.7965 +2024-11-22 16:05:07.421038: val_loss -0.7323 +2024-11-22 16:05:07.421112: Pseudo dice [0.8594] +2024-11-22 16:05:07.421187: Epoch time: 18.16 s +2024-11-22 16:05:08.368903: +2024-11-22 16:05:08.369112: Epoch 5389 +2024-11-22 16:05:08.369223: Current learning rate: 0.00365 +2024-11-22 16:05:28.246048: train_loss -0.7922 +2024-11-22 16:05:28.246273: val_loss -0.7671 +2024-11-22 16:05:28.246356: Pseudo dice [0.8615] +2024-11-22 16:05:28.246437: Epoch time: 19.88 s +2024-11-22 16:05:29.139191: +2024-11-22 16:05:29.139412: Epoch 5390 +2024-11-22 16:05:29.139530: Current learning rate: 0.00365 +2024-11-22 16:05:46.517101: train_loss -0.8007 +2024-11-22 16:05:46.517362: val_loss -0.7567 +2024-11-22 16:05:46.517440: Pseudo dice [0.8326] +2024-11-22 16:05:46.517518: Epoch time: 17.38 s +2024-11-22 16:05:47.409809: +2024-11-22 16:05:47.410085: Epoch 5391 +2024-11-22 16:05:47.410192: Current learning rate: 0.00365 +2024-11-22 16:06:06.168238: train_loss -0.7887 +2024-11-22 16:06:06.168484: val_loss -0.7601 +2024-11-22 16:06:06.168570: Pseudo dice [0.8556] +2024-11-22 16:06:06.168653: Epoch time: 18.76 s +2024-11-22 16:06:07.057096: +2024-11-22 16:06:07.057372: Epoch 5392 +2024-11-22 16:06:07.057491: Current learning rate: 0.00365 +2024-11-22 16:06:26.192458: train_loss -0.7865 +2024-11-22 16:06:26.192674: val_loss -0.745 +2024-11-22 16:06:26.192753: Pseudo dice [0.8304] +2024-11-22 16:06:26.192835: Epoch time: 19.14 s +2024-11-22 16:06:27.487829: +2024-11-22 16:06:27.488106: Epoch 5393 +2024-11-22 16:06:27.488220: Current learning rate: 0.00365 +2024-11-22 16:06:47.446277: train_loss -0.8048 +2024-11-22 16:06:47.446510: val_loss -0.7376 +2024-11-22 16:06:47.446586: Pseudo dice [0.8359] +2024-11-22 16:06:47.446662: Epoch time: 19.96 s +2024-11-22 16:06:48.338973: +2024-11-22 16:06:48.339186: Epoch 5394 +2024-11-22 16:06:48.339298: Current learning rate: 0.00364 +2024-11-22 16:07:07.012854: train_loss -0.7965 +2024-11-22 16:07:07.013101: val_loss -0.7369 +2024-11-22 16:07:07.013182: Pseudo dice [0.8221] +2024-11-22 16:07:07.013262: Epoch time: 18.67 s +2024-11-22 16:07:07.904496: +2024-11-22 16:07:07.904726: Epoch 5395 +2024-11-22 16:07:07.904843: Current learning rate: 0.00364 +2024-11-22 16:07:26.957824: train_loss -0.8011 +2024-11-22 16:07:26.958136: val_loss -0.735 +2024-11-22 16:07:26.958212: Pseudo dice [0.8529] +2024-11-22 16:07:26.958292: Epoch time: 19.05 s +2024-11-22 16:07:27.855339: +2024-11-22 16:07:27.855553: Epoch 5396 +2024-11-22 16:07:27.855674: Current learning rate: 0.00364 +2024-11-22 16:07:46.823956: train_loss -0.797 +2024-11-22 16:07:46.824182: val_loss -0.7605 +2024-11-22 16:07:46.824257: Pseudo dice [0.848] +2024-11-22 16:07:46.824330: Epoch time: 18.97 s +2024-11-22 16:07:47.724236: +2024-11-22 16:07:47.724478: Epoch 5397 +2024-11-22 16:07:47.724591: Current learning rate: 0.00364 +2024-11-22 16:08:06.494543: train_loss -0.8037 +2024-11-22 16:08:06.494759: val_loss -0.7369 +2024-11-22 16:08:06.494836: Pseudo dice [0.8347] +2024-11-22 16:08:06.494911: Epoch time: 18.77 s +2024-11-22 16:08:07.387017: +2024-11-22 16:08:07.387227: Epoch 5398 +2024-11-22 16:08:07.387344: Current learning rate: 0.00364 +2024-11-22 16:08:25.896258: train_loss -0.8037 +2024-11-22 16:08:25.896585: val_loss -0.7613 +2024-11-22 16:08:25.896662: Pseudo dice [0.8647] +2024-11-22 16:08:25.896748: Epoch time: 18.51 s +2024-11-22 16:08:26.794047: +2024-11-22 16:08:26.794243: Epoch 5399 +2024-11-22 16:08:26.794355: Current learning rate: 0.00364 +2024-11-22 16:08:45.078139: train_loss -0.8033 +2024-11-22 16:08:45.078372: val_loss -0.7714 +2024-11-22 16:08:45.078453: Pseudo dice [0.8338] +2024-11-22 16:08:45.078530: Epoch time: 18.28 s +2024-11-22 16:08:46.284592: +2024-11-22 16:08:46.284798: Epoch 5400 +2024-11-22 16:08:46.284909: Current learning rate: 0.00364 +2024-11-22 16:09:06.110349: train_loss -0.8012 +2024-11-22 16:09:06.110566: val_loss -0.7583 +2024-11-22 16:09:06.110643: Pseudo dice [0.8515] +2024-11-22 16:09:06.110719: Epoch time: 19.83 s +2024-11-22 16:09:07.005440: +2024-11-22 16:09:07.005632: Epoch 5401 +2024-11-22 16:09:07.005744: Current learning rate: 0.00364 +2024-11-22 16:09:25.425085: train_loss -0.8022 +2024-11-22 16:09:25.425358: val_loss -0.7435 +2024-11-22 16:09:25.425463: Pseudo dice [0.8317] +2024-11-22 16:09:25.425542: Epoch time: 18.42 s +2024-11-22 16:09:26.323260: +2024-11-22 16:09:26.323454: Epoch 5402 +2024-11-22 16:09:26.323566: Current learning rate: 0.00363 +2024-11-22 16:09:45.645809: train_loss -0.8032 +2024-11-22 16:09:45.647216: val_loss -0.7482 +2024-11-22 16:09:45.647348: Pseudo dice [0.8533] +2024-11-22 16:09:45.647439: Epoch time: 19.32 s +2024-11-22 16:09:46.550285: +2024-11-22 16:09:46.550472: Epoch 5403 +2024-11-22 16:09:46.550588: Current learning rate: 0.00363 +2024-11-22 16:10:05.629565: train_loss -0.81 +2024-11-22 16:10:05.629778: val_loss -0.7583 +2024-11-22 16:10:05.629912: Pseudo dice [0.8688] +2024-11-22 16:10:05.629996: Epoch time: 19.08 s +2024-11-22 16:10:06.516844: +2024-11-22 16:10:06.517101: Epoch 5404 +2024-11-22 16:10:06.517212: Current learning rate: 0.00363 +2024-11-22 16:10:24.087738: train_loss -0.8076 +2024-11-22 16:10:24.087987: val_loss -0.7789 +2024-11-22 16:10:24.088072: Pseudo dice [0.8457] +2024-11-22 16:10:24.088148: Epoch time: 17.57 s +2024-11-22 16:10:24.972824: +2024-11-22 16:10:24.973054: Epoch 5405 +2024-11-22 16:10:24.973170: Current learning rate: 0.00363 +2024-11-22 16:10:42.857653: train_loss -0.8046 +2024-11-22 16:10:42.857886: val_loss -0.727 +2024-11-22 16:10:42.857967: Pseudo dice [0.8376] +2024-11-22 16:10:42.858399: Epoch time: 17.89 s +2024-11-22 16:10:43.747659: +2024-11-22 16:10:43.747946: Epoch 5406 +2024-11-22 16:10:43.748067: Current learning rate: 0.00363 +2024-11-22 16:11:01.044145: train_loss -0.7864 +2024-11-22 16:11:01.044385: val_loss -0.746 +2024-11-22 16:11:01.044460: Pseudo dice [0.8449] +2024-11-22 16:11:01.044539: Epoch time: 17.3 s +2024-11-22 16:11:01.938273: +2024-11-22 16:11:01.938512: Epoch 5407 +2024-11-22 16:11:01.938624: Current learning rate: 0.00363 +2024-11-22 16:11:21.074735: train_loss -0.7968 +2024-11-22 16:11:21.074961: val_loss -0.7361 +2024-11-22 16:11:21.075042: Pseudo dice [0.838] +2024-11-22 16:11:21.075120: Epoch time: 19.14 s +2024-11-22 16:11:21.976313: +2024-11-22 16:11:21.976517: Epoch 5408 +2024-11-22 16:11:21.976619: Current learning rate: 0.00363 +2024-11-22 16:11:40.638019: train_loss -0.8088 +2024-11-22 16:11:40.638247: val_loss -0.7718 +2024-11-22 16:11:40.638328: Pseudo dice [0.8584] +2024-11-22 16:11:40.638405: Epoch time: 18.66 s +2024-11-22 16:11:41.541626: +2024-11-22 16:11:41.541811: Epoch 5409 +2024-11-22 16:11:41.541919: Current learning rate: 0.00363 +2024-11-22 16:11:58.828599: train_loss -0.8138 +2024-11-22 16:11:58.828822: val_loss -0.7485 +2024-11-22 16:11:58.828897: Pseudo dice [0.8385] +2024-11-22 16:11:58.828977: Epoch time: 17.29 s +2024-11-22 16:11:59.729327: +2024-11-22 16:11:59.729517: Epoch 5410 +2024-11-22 16:11:59.729632: Current learning rate: 0.00362 +2024-11-22 16:12:19.503607: train_loss -0.8005 +2024-11-22 16:12:19.503849: val_loss -0.7284 +2024-11-22 16:12:19.503925: Pseudo dice [0.8418] +2024-11-22 16:12:19.506199: Epoch time: 19.78 s +2024-11-22 16:12:20.424690: +2024-11-22 16:12:20.424916: Epoch 5411 +2024-11-22 16:12:20.425042: Current learning rate: 0.00362 +2024-11-22 16:12:38.846442: train_loss -0.7987 +2024-11-22 16:12:38.849184: val_loss -0.7497 +2024-11-22 16:12:38.849281: Pseudo dice [0.8407] +2024-11-22 16:12:38.849360: Epoch time: 18.42 s +2024-11-22 16:12:39.753517: +2024-11-22 16:12:39.753849: Epoch 5412 +2024-11-22 16:12:39.753961: Current learning rate: 0.00362 +2024-11-22 16:12:57.003129: train_loss -0.8046 +2024-11-22 16:12:57.003347: val_loss -0.7414 +2024-11-22 16:12:57.003424: Pseudo dice [0.8153] +2024-11-22 16:12:57.003502: Epoch time: 17.25 s +2024-11-22 16:12:57.902345: +2024-11-22 16:12:57.902556: Epoch 5413 +2024-11-22 16:12:57.902664: Current learning rate: 0.00362 +2024-11-22 16:13:16.447106: train_loss -0.7999 +2024-11-22 16:13:16.447334: val_loss -0.7475 +2024-11-22 16:13:16.447410: Pseudo dice [0.8399] +2024-11-22 16:13:16.447493: Epoch time: 18.55 s +2024-11-22 16:13:17.383427: +2024-11-22 16:13:17.383653: Epoch 5414 +2024-11-22 16:13:17.383769: Current learning rate: 0.00362 +2024-11-22 16:13:36.308647: train_loss -0.7868 +2024-11-22 16:13:36.308873: val_loss -0.7124 +2024-11-22 16:13:36.308949: Pseudo dice [0.8228] +2024-11-22 16:13:36.309037: Epoch time: 18.93 s +2024-11-22 16:13:37.211210: +2024-11-22 16:13:37.211422: Epoch 5415 +2024-11-22 16:13:37.211537: Current learning rate: 0.00362 +2024-11-22 16:13:56.265019: train_loss -0.7886 +2024-11-22 16:13:56.265238: val_loss -0.7448 +2024-11-22 16:13:56.265315: Pseudo dice [0.8398] +2024-11-22 16:13:56.265389: Epoch time: 19.05 s +2024-11-22 16:13:57.550078: +2024-11-22 16:13:57.550302: Epoch 5416 +2024-11-22 16:13:57.550434: Current learning rate: 0.00362 +2024-11-22 16:14:16.649542: train_loss -0.7956 +2024-11-22 16:14:16.649772: val_loss -0.7667 +2024-11-22 16:14:16.649846: Pseudo dice [0.8336] +2024-11-22 16:14:16.649926: Epoch time: 19.1 s +2024-11-22 16:14:17.548767: +2024-11-22 16:14:17.549014: Epoch 5417 +2024-11-22 16:14:17.549127: Current learning rate: 0.00362 +2024-11-22 16:14:36.394737: train_loss -0.7864 +2024-11-22 16:14:36.394960: val_loss -0.779 +2024-11-22 16:14:36.395056: Pseudo dice [0.8438] +2024-11-22 16:14:36.395136: Epoch time: 18.85 s +2024-11-22 16:14:37.288837: +2024-11-22 16:14:37.289243: Epoch 5418 +2024-11-22 16:14:37.289363: Current learning rate: 0.00361 +2024-11-22 16:14:55.305173: train_loss -0.8036 +2024-11-22 16:14:55.305399: val_loss -0.7573 +2024-11-22 16:14:55.305476: Pseudo dice [0.8601] +2024-11-22 16:14:55.305553: Epoch time: 18.02 s +2024-11-22 16:14:56.436685: +2024-11-22 16:14:56.436904: Epoch 5419 +2024-11-22 16:14:56.437025: Current learning rate: 0.00361 +2024-11-22 16:15:15.639268: train_loss -0.7991 +2024-11-22 16:15:15.639491: val_loss -0.7579 +2024-11-22 16:15:15.639571: Pseudo dice [0.8482] +2024-11-22 16:15:15.639649: Epoch time: 19.2 s +2024-11-22 16:15:16.658450: +2024-11-22 16:15:16.658672: Epoch 5420 +2024-11-22 16:15:16.658786: Current learning rate: 0.00361 +2024-11-22 16:15:35.477041: train_loss -0.8013 +2024-11-22 16:15:35.477306: val_loss -0.7476 +2024-11-22 16:15:35.477384: Pseudo dice [0.8503] +2024-11-22 16:15:35.477473: Epoch time: 18.82 s +2024-11-22 16:15:36.384030: +2024-11-22 16:15:36.384299: Epoch 5421 +2024-11-22 16:15:36.384421: Current learning rate: 0.00361 +2024-11-22 16:15:54.972522: train_loss -0.794 +2024-11-22 16:15:54.973086: val_loss -0.7495 +2024-11-22 16:15:54.973163: Pseudo dice [0.8425] +2024-11-22 16:15:54.973240: Epoch time: 18.59 s +2024-11-22 16:15:55.865501: +2024-11-22 16:15:55.865712: Epoch 5422 +2024-11-22 16:15:55.865835: Current learning rate: 0.00361 +2024-11-22 16:16:15.425472: train_loss -0.7964 +2024-11-22 16:16:15.425746: val_loss -0.7477 +2024-11-22 16:16:15.425828: Pseudo dice [0.8109] +2024-11-22 16:16:15.425922: Epoch time: 19.56 s +2024-11-22 16:16:16.325005: +2024-11-22 16:16:16.325209: Epoch 5423 +2024-11-22 16:16:16.325329: Current learning rate: 0.00361 +2024-11-22 16:16:34.245443: train_loss -0.7947 +2024-11-22 16:16:34.247859: val_loss -0.7164 +2024-11-22 16:16:34.247951: Pseudo dice [0.8244] +2024-11-22 16:16:34.248039: Epoch time: 17.92 s +2024-11-22 16:16:35.413682: +2024-11-22 16:16:35.413915: Epoch 5424 +2024-11-22 16:16:35.414036: Current learning rate: 0.00361 +2024-11-22 16:16:54.659449: train_loss -0.793 +2024-11-22 16:16:54.659700: val_loss -0.7574 +2024-11-22 16:16:54.659779: Pseudo dice [0.864] +2024-11-22 16:16:54.659859: Epoch time: 19.25 s +2024-11-22 16:16:55.605153: +2024-11-22 16:16:55.605356: Epoch 5425 +2024-11-22 16:16:55.605470: Current learning rate: 0.00361 +2024-11-22 16:17:14.431720: train_loss -0.7978 +2024-11-22 16:17:14.431939: val_loss -0.7468 +2024-11-22 16:17:14.432024: Pseudo dice [0.8379] +2024-11-22 16:17:14.432102: Epoch time: 18.83 s +2024-11-22 16:17:15.331528: +2024-11-22 16:17:15.331747: Epoch 5426 +2024-11-22 16:17:15.331865: Current learning rate: 0.0036 +2024-11-22 16:17:33.905722: train_loss -0.7969 +2024-11-22 16:17:33.905946: val_loss -0.7764 +2024-11-22 16:17:33.906029: Pseudo dice [0.8377] +2024-11-22 16:17:33.906106: Epoch time: 18.58 s +2024-11-22 16:17:34.799736: +2024-11-22 16:17:34.799957: Epoch 5427 +2024-11-22 16:17:34.800074: Current learning rate: 0.0036 +2024-11-22 16:17:52.563365: train_loss -0.8048 +2024-11-22 16:17:52.563608: val_loss -0.7593 +2024-11-22 16:17:52.563685: Pseudo dice [0.8589] +2024-11-22 16:17:52.563766: Epoch time: 17.76 s +2024-11-22 16:17:53.871404: +2024-11-22 16:17:53.871603: Epoch 5428 +2024-11-22 16:17:53.871716: Current learning rate: 0.0036 +2024-11-22 16:18:13.390306: train_loss -0.8063 +2024-11-22 16:18:13.390527: val_loss -0.7557 +2024-11-22 16:18:13.390605: Pseudo dice [0.8594] +2024-11-22 16:18:13.390683: Epoch time: 19.52 s +2024-11-22 16:18:14.285893: +2024-11-22 16:18:14.286113: Epoch 5429 +2024-11-22 16:18:14.286225: Current learning rate: 0.0036 +2024-11-22 16:18:32.870083: train_loss -0.8024 +2024-11-22 16:18:32.870301: val_loss -0.7762 +2024-11-22 16:18:32.870375: Pseudo dice [0.8576] +2024-11-22 16:18:32.870452: Epoch time: 18.58 s +2024-11-22 16:18:33.804606: +2024-11-22 16:18:33.804885: Epoch 5430 +2024-11-22 16:18:33.805007: Current learning rate: 0.0036 +2024-11-22 16:18:52.290275: train_loss -0.8065 +2024-11-22 16:18:52.290551: val_loss -0.7344 +2024-11-22 16:18:52.290629: Pseudo dice [0.8265] +2024-11-22 16:18:52.290707: Epoch time: 18.49 s +2024-11-22 16:18:53.292852: +2024-11-22 16:18:53.293126: Epoch 5431 +2024-11-22 16:18:53.293242: Current learning rate: 0.0036 +2024-11-22 16:19:12.921731: train_loss -0.799 +2024-11-22 16:19:12.927176: val_loss -0.7586 +2024-11-22 16:19:12.927304: Pseudo dice [0.8468] +2024-11-22 16:19:12.927707: Epoch time: 19.63 s +2024-11-22 16:19:14.188697: +2024-11-22 16:19:14.188969: Epoch 5432 +2024-11-22 16:19:14.189090: Current learning rate: 0.0036 +2024-11-22 16:19:32.840572: train_loss -0.8075 +2024-11-22 16:19:32.840845: val_loss -0.7552 +2024-11-22 16:19:32.840925: Pseudo dice [0.8327] +2024-11-22 16:19:32.841018: Epoch time: 18.65 s +2024-11-22 16:19:33.741720: +2024-11-22 16:19:33.741943: Epoch 5433 +2024-11-22 16:19:33.742053: Current learning rate: 0.0036 +2024-11-22 16:19:52.508621: train_loss -0.8028 +2024-11-22 16:19:52.508851: val_loss -0.7591 +2024-11-22 16:19:52.508974: Pseudo dice [0.8583] +2024-11-22 16:19:52.509056: Epoch time: 18.77 s +2024-11-22 16:19:53.508378: +2024-11-22 16:19:53.508599: Epoch 5434 +2024-11-22 16:19:53.508711: Current learning rate: 0.00359 +2024-11-22 16:20:13.176276: train_loss -0.7987 +2024-11-22 16:20:13.176494: val_loss -0.7716 +2024-11-22 16:20:13.176617: Pseudo dice [0.8373] +2024-11-22 16:20:13.176696: Epoch time: 19.67 s +2024-11-22 16:20:14.070440: +2024-11-22 16:20:14.070673: Epoch 5435 +2024-11-22 16:20:14.070805: Current learning rate: 0.00359 +2024-11-22 16:20:32.574597: train_loss -0.7976 +2024-11-22 16:20:32.574839: val_loss -0.7476 +2024-11-22 16:20:32.574916: Pseudo dice [0.8444] +2024-11-22 16:20:32.575006: Epoch time: 18.51 s +2024-11-22 16:20:33.450248: +2024-11-22 16:20:33.450525: Epoch 5436 +2024-11-22 16:20:33.450639: Current learning rate: 0.00359 +2024-11-22 16:20:52.387980: train_loss -0.802 +2024-11-22 16:20:52.388225: val_loss -0.7513 +2024-11-22 16:20:52.388304: Pseudo dice [0.8252] +2024-11-22 16:20:52.388382: Epoch time: 18.94 s +2024-11-22 16:20:53.272939: +2024-11-22 16:20:53.273132: Epoch 5437 +2024-11-22 16:20:53.273242: Current learning rate: 0.00359 +2024-11-22 16:21:12.394359: train_loss -0.7986 +2024-11-22 16:21:12.394677: val_loss -0.7783 +2024-11-22 16:21:12.394761: Pseudo dice [0.8433] +2024-11-22 16:21:12.394836: Epoch time: 19.12 s +2024-11-22 16:21:13.284704: +2024-11-22 16:21:13.284920: Epoch 5438 +2024-11-22 16:21:13.285046: Current learning rate: 0.00359 +2024-11-22 16:21:32.227727: train_loss -0.8037 +2024-11-22 16:21:32.227948: val_loss -0.7517 +2024-11-22 16:21:32.228031: Pseudo dice [0.8397] +2024-11-22 16:21:32.228110: Epoch time: 18.94 s +2024-11-22 16:21:33.155194: +2024-11-22 16:21:33.155396: Epoch 5439 +2024-11-22 16:21:33.155509: Current learning rate: 0.00359 +2024-11-22 16:21:51.854631: train_loss -0.8135 +2024-11-22 16:21:51.854896: val_loss -0.7623 +2024-11-22 16:21:51.854978: Pseudo dice [0.8507] +2024-11-22 16:21:51.855077: Epoch time: 18.7 s +2024-11-22 16:21:53.158455: +2024-11-22 16:21:53.158668: Epoch 5440 +2024-11-22 16:21:53.158777: Current learning rate: 0.00359 +2024-11-22 16:22:11.935240: train_loss -0.8054 +2024-11-22 16:22:11.935470: val_loss -0.7652 +2024-11-22 16:22:11.935547: Pseudo dice [0.849] +2024-11-22 16:22:11.935626: Epoch time: 18.78 s +2024-11-22 16:22:12.829612: +2024-11-22 16:22:12.829856: Epoch 5441 +2024-11-22 16:22:12.829973: Current learning rate: 0.00358 +2024-11-22 16:22:31.300110: train_loss -0.8088 +2024-11-22 16:22:31.300326: val_loss -0.7308 +2024-11-22 16:22:31.300399: Pseudo dice [0.8314] +2024-11-22 16:22:31.300473: Epoch time: 18.47 s +2024-11-22 16:22:32.218519: +2024-11-22 16:22:32.218736: Epoch 5442 +2024-11-22 16:22:32.218845: Current learning rate: 0.00358 +2024-11-22 16:22:50.620258: train_loss -0.8032 +2024-11-22 16:22:50.621931: val_loss -0.7545 +2024-11-22 16:22:50.622036: Pseudo dice [0.8311] +2024-11-22 16:22:50.622126: Epoch time: 18.4 s +2024-11-22 16:22:51.546335: +2024-11-22 16:22:51.546728: Epoch 5443 +2024-11-22 16:22:51.546843: Current learning rate: 0.00358 +2024-11-22 16:23:09.814701: train_loss -0.7941 +2024-11-22 16:23:09.814948: val_loss -0.7393 +2024-11-22 16:23:09.815034: Pseudo dice [0.8615] +2024-11-22 16:23:09.815112: Epoch time: 18.27 s +2024-11-22 16:23:10.731905: +2024-11-22 16:23:10.732125: Epoch 5444 +2024-11-22 16:23:10.732239: Current learning rate: 0.00358 +2024-11-22 16:23:29.058287: train_loss -0.7972 +2024-11-22 16:23:29.058510: val_loss -0.7461 +2024-11-22 16:23:29.058589: Pseudo dice [0.8366] +2024-11-22 16:23:29.058666: Epoch time: 18.33 s +2024-11-22 16:23:29.952161: +2024-11-22 16:23:29.952402: Epoch 5445 +2024-11-22 16:23:29.952518: Current learning rate: 0.00358 +2024-11-22 16:23:49.444723: train_loss -0.8028 +2024-11-22 16:23:49.444969: val_loss -0.7456 +2024-11-22 16:23:49.445060: Pseudo dice [0.8353] +2024-11-22 16:23:49.445139: Epoch time: 19.49 s +2024-11-22 16:23:50.440576: +2024-11-22 16:23:50.440795: Epoch 5446 +2024-11-22 16:23:50.440916: Current learning rate: 0.00358 +2024-11-22 16:24:08.520775: train_loss -0.8066 +2024-11-22 16:24:08.521956: val_loss -0.759 +2024-11-22 16:24:08.522061: Pseudo dice [0.8504] +2024-11-22 16:24:08.522145: Epoch time: 18.08 s +2024-11-22 16:24:09.447714: +2024-11-22 16:24:09.448052: Epoch 5447 +2024-11-22 16:24:09.448216: Current learning rate: 0.00358 +2024-11-22 16:24:28.824891: train_loss -0.8024 +2024-11-22 16:24:28.825149: val_loss -0.7576 +2024-11-22 16:24:28.825234: Pseudo dice [0.8241] +2024-11-22 16:24:28.825320: Epoch time: 19.38 s +2024-11-22 16:24:29.836857: +2024-11-22 16:24:29.837080: Epoch 5448 +2024-11-22 16:24:29.837194: Current learning rate: 0.00358 +2024-11-22 16:24:48.118076: train_loss -0.806 +2024-11-22 16:24:48.118305: val_loss -0.7738 +2024-11-22 16:24:48.118382: Pseudo dice [0.8524] +2024-11-22 16:24:48.118457: Epoch time: 18.28 s +2024-11-22 16:24:49.017901: +2024-11-22 16:24:49.018118: Epoch 5449 +2024-11-22 16:24:49.018241: Current learning rate: 0.00357 +2024-11-22 16:25:06.823683: train_loss -0.8103 +2024-11-22 16:25:06.823977: val_loss -0.7501 +2024-11-22 16:25:06.824058: Pseudo dice [0.8362] +2024-11-22 16:25:06.824138: Epoch time: 17.81 s +2024-11-22 16:25:08.004401: +2024-11-22 16:25:08.004607: Epoch 5450 +2024-11-22 16:25:08.004718: Current learning rate: 0.00357 +2024-11-22 16:25:26.952053: train_loss -0.8123 +2024-11-22 16:25:26.952305: val_loss -0.7508 +2024-11-22 16:25:26.952382: Pseudo dice [0.8592] +2024-11-22 16:25:26.952464: Epoch time: 18.95 s +2024-11-22 16:25:27.851542: +2024-11-22 16:25:27.851807: Epoch 5451 +2024-11-22 16:25:27.851925: Current learning rate: 0.00357 +2024-11-22 16:25:47.072860: train_loss -0.8096 +2024-11-22 16:25:47.073118: val_loss -0.7322 +2024-11-22 16:25:47.073199: Pseudo dice [0.8649] +2024-11-22 16:25:47.073279: Epoch time: 19.22 s +2024-11-22 16:25:47.962282: +2024-11-22 16:25:47.962490: Epoch 5452 +2024-11-22 16:25:47.962602: Current learning rate: 0.00357 +2024-11-22 16:26:06.070219: train_loss -0.8068 +2024-11-22 16:26:06.070434: val_loss -0.7527 +2024-11-22 16:26:06.070508: Pseudo dice [0.8346] +2024-11-22 16:26:06.070584: Epoch time: 18.11 s +2024-11-22 16:26:06.971519: +2024-11-22 16:26:06.971777: Epoch 5453 +2024-11-22 16:26:06.971901: Current learning rate: 0.00357 +2024-11-22 16:26:24.859083: train_loss -0.8099 +2024-11-22 16:26:24.859305: val_loss -0.7404 +2024-11-22 16:26:24.859383: Pseudo dice [0.8427] +2024-11-22 16:26:24.859463: Epoch time: 17.89 s +2024-11-22 16:26:25.755260: +2024-11-22 16:26:25.755475: Epoch 5454 +2024-11-22 16:26:25.755587: Current learning rate: 0.00357 +2024-11-22 16:26:45.294255: train_loss -0.7978 +2024-11-22 16:26:45.294501: val_loss -0.7492 +2024-11-22 16:26:45.294577: Pseudo dice [0.8515] +2024-11-22 16:26:45.294658: Epoch time: 19.54 s +2024-11-22 16:26:46.389917: +2024-11-22 16:26:46.390152: Epoch 5455 +2024-11-22 16:26:46.390264: Current learning rate: 0.00357 +2024-11-22 16:27:04.876019: train_loss -0.8028 +2024-11-22 16:27:04.876235: val_loss -0.7425 +2024-11-22 16:27:04.876308: Pseudo dice [0.8445] +2024-11-22 16:27:04.876384: Epoch time: 18.49 s +2024-11-22 16:27:05.771764: +2024-11-22 16:27:05.771984: Epoch 5456 +2024-11-22 16:27:05.772104: Current learning rate: 0.00357 +2024-11-22 16:27:23.334457: train_loss -0.8013 +2024-11-22 16:27:23.334682: val_loss -0.7548 +2024-11-22 16:27:23.334758: Pseudo dice [0.8519] +2024-11-22 16:27:23.334835: Epoch time: 17.56 s +2024-11-22 16:27:24.299091: +2024-11-22 16:27:24.299339: Epoch 5457 +2024-11-22 16:27:24.299460: Current learning rate: 0.00356 +2024-11-22 16:27:42.320397: train_loss -0.802 +2024-11-22 16:27:42.320615: val_loss -0.7552 +2024-11-22 16:27:42.320969: Pseudo dice [0.8421] +2024-11-22 16:27:42.321058: Epoch time: 18.02 s +2024-11-22 16:27:43.235412: +2024-11-22 16:27:43.235634: Epoch 5458 +2024-11-22 16:27:43.235754: Current learning rate: 0.00356 +2024-11-22 16:28:01.867388: train_loss -0.8076 +2024-11-22 16:28:01.867635: val_loss -0.7654 +2024-11-22 16:28:01.867712: Pseudo dice [0.8576] +2024-11-22 16:28:01.867796: Epoch time: 18.63 s +2024-11-22 16:28:02.763956: +2024-11-22 16:28:02.764234: Epoch 5459 +2024-11-22 16:28:02.764355: Current learning rate: 0.00356 +2024-11-22 16:28:21.042670: train_loss -0.8069 +2024-11-22 16:28:21.042897: val_loss -0.7681 +2024-11-22 16:28:21.042975: Pseudo dice [0.852] +2024-11-22 16:28:21.043064: Epoch time: 18.28 s +2024-11-22 16:28:22.042566: +2024-11-22 16:28:22.042768: Epoch 5460 +2024-11-22 16:28:22.042877: Current learning rate: 0.00356 +2024-11-22 16:28:41.075686: train_loss -0.7966 +2024-11-22 16:28:41.075904: val_loss -0.7546 +2024-11-22 16:28:41.075976: Pseudo dice [0.8467] +2024-11-22 16:28:41.076061: Epoch time: 19.03 s +2024-11-22 16:28:42.004570: +2024-11-22 16:28:42.004770: Epoch 5461 +2024-11-22 16:28:42.004879: Current learning rate: 0.00356 +2024-11-22 16:29:01.206096: train_loss -0.807 +2024-11-22 16:29:01.206311: val_loss -0.765 +2024-11-22 16:29:01.206385: Pseudo dice [0.8404] +2024-11-22 16:29:01.206460: Epoch time: 19.2 s +2024-11-22 16:29:02.109702: +2024-11-22 16:29:02.109936: Epoch 5462 +2024-11-22 16:29:02.110061: Current learning rate: 0.00356 +2024-11-22 16:29:20.621013: train_loss -0.8052 +2024-11-22 16:29:20.621256: val_loss -0.7561 +2024-11-22 16:29:20.621330: Pseudo dice [0.8653] +2024-11-22 16:29:20.621409: Epoch time: 18.51 s +2024-11-22 16:29:21.914421: +2024-11-22 16:29:21.914653: Epoch 5463 +2024-11-22 16:29:21.914767: Current learning rate: 0.00356 +2024-11-22 16:29:40.742558: train_loss -0.8046 +2024-11-22 16:29:40.742819: val_loss -0.7394 +2024-11-22 16:29:40.744327: Pseudo dice [0.8283] +2024-11-22 16:29:40.744415: Epoch time: 18.83 s +2024-11-22 16:29:41.649129: +2024-11-22 16:29:41.649353: Epoch 5464 +2024-11-22 16:29:41.649469: Current learning rate: 0.00356 +2024-11-22 16:30:01.388520: train_loss -0.8097 +2024-11-22 16:30:01.388751: val_loss -0.754 +2024-11-22 16:30:01.388830: Pseudo dice [0.8379] +2024-11-22 16:30:01.388909: Epoch time: 19.74 s +2024-11-22 16:30:02.283311: +2024-11-22 16:30:02.283582: Epoch 5465 +2024-11-22 16:30:02.283704: Current learning rate: 0.00355 +2024-11-22 16:30:20.226048: train_loss -0.8092 +2024-11-22 16:30:20.226371: val_loss -0.7568 +2024-11-22 16:30:20.226449: Pseudo dice [0.8606] +2024-11-22 16:30:20.226532: Epoch time: 17.94 s +2024-11-22 16:30:21.121193: +2024-11-22 16:30:21.121413: Epoch 5466 +2024-11-22 16:30:21.121526: Current learning rate: 0.00355 +2024-11-22 16:30:40.999278: train_loss -0.8125 +2024-11-22 16:30:40.999486: val_loss -0.7521 +2024-11-22 16:30:40.999563: Pseudo dice [0.8296] +2024-11-22 16:30:40.999640: Epoch time: 19.88 s +2024-11-22 16:30:41.892739: +2024-11-22 16:30:41.892937: Epoch 5467 +2024-11-22 16:30:41.893056: Current learning rate: 0.00355 +2024-11-22 16:31:00.800362: train_loss -0.7991 +2024-11-22 16:31:00.800590: val_loss -0.7569 +2024-11-22 16:31:00.800666: Pseudo dice [0.8235] +2024-11-22 16:31:00.800744: Epoch time: 18.91 s +2024-11-22 16:31:01.721921: +2024-11-22 16:31:01.722125: Epoch 5468 +2024-11-22 16:31:01.722237: Current learning rate: 0.00355 +2024-11-22 16:31:20.073730: train_loss -0.787 +2024-11-22 16:31:20.073961: val_loss -0.7345 +2024-11-22 16:31:20.074044: Pseudo dice [0.8402] +2024-11-22 16:31:20.074121: Epoch time: 18.35 s +2024-11-22 16:31:21.032552: +2024-11-22 16:31:21.032768: Epoch 5469 +2024-11-22 16:31:21.032881: Current learning rate: 0.00355 +2024-11-22 16:31:40.052354: train_loss -0.7915 +2024-11-22 16:31:40.052580: val_loss -0.7495 +2024-11-22 16:31:40.057830: Pseudo dice [0.8446] +2024-11-22 16:31:40.058022: Epoch time: 19.02 s +2024-11-22 16:31:41.096967: +2024-11-22 16:31:41.097199: Epoch 5470 +2024-11-22 16:31:41.097314: Current learning rate: 0.00355 +2024-11-22 16:32:00.335873: train_loss -0.7923 +2024-11-22 16:32:00.336181: val_loss -0.7222 +2024-11-22 16:32:00.336268: Pseudo dice [0.8291] +2024-11-22 16:32:00.336349: Epoch time: 19.24 s +2024-11-22 16:32:01.230302: +2024-11-22 16:32:01.230511: Epoch 5471 +2024-11-22 16:32:01.230630: Current learning rate: 0.00355 +2024-11-22 16:32:19.493622: train_loss -0.8018 +2024-11-22 16:32:19.493903: val_loss -0.7649 +2024-11-22 16:32:19.493980: Pseudo dice [0.8425] +2024-11-22 16:32:19.494063: Epoch time: 18.26 s +2024-11-22 16:32:20.390031: +2024-11-22 16:32:20.390252: Epoch 5472 +2024-11-22 16:32:20.390367: Current learning rate: 0.00355 +2024-11-22 16:32:39.777599: train_loss -0.7846 +2024-11-22 16:32:39.777831: val_loss -0.7503 +2024-11-22 16:32:39.777924: Pseudo dice [0.8456] +2024-11-22 16:32:39.783228: Epoch time: 19.39 s +2024-11-22 16:32:40.775468: +2024-11-22 16:32:40.775677: Epoch 5473 +2024-11-22 16:32:40.775795: Current learning rate: 0.00354 +2024-11-22 16:32:59.283539: train_loss -0.7669 +2024-11-22 16:32:59.283826: val_loss -0.7523 +2024-11-22 16:32:59.283910: Pseudo dice [0.8509] +2024-11-22 16:32:59.284002: Epoch time: 18.51 s +2024-11-22 16:33:00.180765: +2024-11-22 16:33:00.180973: Epoch 5474 +2024-11-22 16:33:00.181091: Current learning rate: 0.00354 +2024-11-22 16:33:18.682505: train_loss -0.7742 +2024-11-22 16:33:18.684902: val_loss -0.7531 +2024-11-22 16:33:18.685015: Pseudo dice [0.8363] +2024-11-22 16:33:18.685100: Epoch time: 18.5 s +2024-11-22 16:33:20.137633: +2024-11-22 16:33:20.137880: Epoch 5475 +2024-11-22 16:33:20.138017: Current learning rate: 0.00354 +2024-11-22 16:33:39.969953: train_loss -0.7893 +2024-11-22 16:33:39.970180: val_loss -0.7388 +2024-11-22 16:33:39.970257: Pseudo dice [0.8423] +2024-11-22 16:33:39.970336: Epoch time: 19.83 s +2024-11-22 16:33:40.864660: +2024-11-22 16:33:40.864891: Epoch 5476 +2024-11-22 16:33:40.865016: Current learning rate: 0.00354 +2024-11-22 16:33:58.232355: train_loss -0.7936 +2024-11-22 16:33:58.232592: val_loss -0.733 +2024-11-22 16:33:58.232674: Pseudo dice [0.8363] +2024-11-22 16:33:58.232762: Epoch time: 17.37 s +2024-11-22 16:33:59.124748: +2024-11-22 16:33:59.124957: Epoch 5477 +2024-11-22 16:33:59.125077: Current learning rate: 0.00354 +2024-11-22 16:34:16.445086: train_loss -0.7998 +2024-11-22 16:34:16.445343: val_loss -0.7569 +2024-11-22 16:34:16.445426: Pseudo dice [0.852] +2024-11-22 16:34:16.445510: Epoch time: 17.32 s +2024-11-22 16:34:17.347522: +2024-11-22 16:34:17.347773: Epoch 5478 +2024-11-22 16:34:17.347887: Current learning rate: 0.00354 +2024-11-22 16:34:35.087913: train_loss -0.795 +2024-11-22 16:34:35.088135: val_loss -0.7079 +2024-11-22 16:34:35.088209: Pseudo dice [0.8305] +2024-11-22 16:34:35.088286: Epoch time: 17.74 s +2024-11-22 16:34:35.984890: +2024-11-22 16:34:35.985111: Epoch 5479 +2024-11-22 16:34:35.985222: Current learning rate: 0.00354 +2024-11-22 16:34:54.811758: train_loss -0.7967 +2024-11-22 16:34:54.811972: val_loss -0.7482 +2024-11-22 16:34:54.812052: Pseudo dice [0.8358] +2024-11-22 16:34:54.812133: Epoch time: 18.83 s +2024-11-22 16:34:55.709011: +2024-11-22 16:34:55.709214: Epoch 5480 +2024-11-22 16:34:55.709354: Current learning rate: 0.00354 +2024-11-22 16:35:15.173342: train_loss -0.8012 +2024-11-22 16:35:15.173614: val_loss -0.7353 +2024-11-22 16:35:15.173689: Pseudo dice [0.8514] +2024-11-22 16:35:15.173766: Epoch time: 19.47 s +2024-11-22 16:35:16.069890: +2024-11-22 16:35:16.070128: Epoch 5481 +2024-11-22 16:35:16.070253: Current learning rate: 0.00353 +2024-11-22 16:35:35.230551: train_loss -0.7899 +2024-11-22 16:35:35.230805: val_loss -0.7619 +2024-11-22 16:35:35.230882: Pseudo dice [0.8466] +2024-11-22 16:35:35.230964: Epoch time: 19.16 s +2024-11-22 16:35:36.132053: +2024-11-22 16:35:36.132336: Epoch 5482 +2024-11-22 16:35:36.132452: Current learning rate: 0.00353 +2024-11-22 16:35:54.826976: train_loss -0.8084 +2024-11-22 16:35:54.827199: val_loss -0.7448 +2024-11-22 16:35:54.827273: Pseudo dice [0.8417] +2024-11-22 16:35:54.827349: Epoch time: 18.7 s +2024-11-22 16:35:55.722688: +2024-11-22 16:35:55.722892: Epoch 5483 +2024-11-22 16:35:55.723015: Current learning rate: 0.00353 +2024-11-22 16:36:14.541691: train_loss -0.8027 +2024-11-22 16:36:14.541909: val_loss -0.7691 +2024-11-22 16:36:14.542839: Pseudo dice [0.8427] +2024-11-22 16:36:14.542964: Epoch time: 18.82 s +2024-11-22 16:36:15.453207: +2024-11-22 16:36:15.453434: Epoch 5484 +2024-11-22 16:36:15.453557: Current learning rate: 0.00353 +2024-11-22 16:36:34.173335: train_loss -0.803 +2024-11-22 16:36:34.173640: val_loss -0.7592 +2024-11-22 16:36:34.173724: Pseudo dice [0.8541] +2024-11-22 16:36:34.173804: Epoch time: 18.72 s +2024-11-22 16:36:35.126136: +2024-11-22 16:36:35.126436: Epoch 5485 +2024-11-22 16:36:35.126551: Current learning rate: 0.00353 +2024-11-22 16:36:53.680053: train_loss -0.8039 +2024-11-22 16:36:53.680320: val_loss -0.7704 +2024-11-22 16:36:53.680397: Pseudo dice [0.8423] +2024-11-22 16:36:53.680479: Epoch time: 18.55 s +2024-11-22 16:36:54.576265: +2024-11-22 16:36:54.576485: Epoch 5486 +2024-11-22 16:36:54.576601: Current learning rate: 0.00353 +2024-11-22 16:37:14.424011: train_loss -0.7991 +2024-11-22 16:37:14.424230: val_loss -0.7634 +2024-11-22 16:37:14.424305: Pseudo dice [0.8391] +2024-11-22 16:37:14.424381: Epoch time: 19.85 s +2024-11-22 16:37:15.761365: +2024-11-22 16:37:15.761583: Epoch 5487 +2024-11-22 16:37:15.761695: Current learning rate: 0.00353 +2024-11-22 16:37:33.369250: train_loss -0.804 +2024-11-22 16:37:33.369469: val_loss -0.7754 +2024-11-22 16:37:33.369544: Pseudo dice [0.8364] +2024-11-22 16:37:33.369622: Epoch time: 17.61 s +2024-11-22 16:37:34.260479: +2024-11-22 16:37:34.260692: Epoch 5488 +2024-11-22 16:37:34.260806: Current learning rate: 0.00353 +2024-11-22 16:37:53.639866: train_loss -0.8133 +2024-11-22 16:37:53.640111: val_loss -0.7584 +2024-11-22 16:37:53.640188: Pseudo dice [0.8591] +2024-11-22 16:37:53.640272: Epoch time: 19.38 s +2024-11-22 16:37:54.803810: +2024-11-22 16:37:54.804054: Epoch 5489 +2024-11-22 16:37:54.804175: Current learning rate: 0.00352 +2024-11-22 16:38:14.166289: train_loss -0.8012 +2024-11-22 16:38:14.166512: val_loss -0.7528 +2024-11-22 16:38:14.166587: Pseudo dice [0.8637] +2024-11-22 16:38:14.166663: Epoch time: 19.36 s +2024-11-22 16:38:15.064230: +2024-11-22 16:38:15.064463: Epoch 5490 +2024-11-22 16:38:15.064576: Current learning rate: 0.00352 +2024-11-22 16:38:33.564610: train_loss -0.8057 +2024-11-22 16:38:33.564845: val_loss -0.7776 +2024-11-22 16:38:33.564922: Pseudo dice [0.8638] +2024-11-22 16:38:33.565005: Epoch time: 18.5 s +2024-11-22 16:38:34.461099: +2024-11-22 16:38:34.461311: Epoch 5491 +2024-11-22 16:38:34.461421: Current learning rate: 0.00352 +2024-11-22 16:38:51.832406: train_loss -0.8035 +2024-11-22 16:38:51.832632: val_loss -0.7573 +2024-11-22 16:38:51.832709: Pseudo dice [0.8622] +2024-11-22 16:38:51.832786: Epoch time: 17.37 s +2024-11-22 16:38:52.727586: +2024-11-22 16:38:52.727810: Epoch 5492 +2024-11-22 16:38:52.727923: Current learning rate: 0.00352 +2024-11-22 16:39:11.530286: train_loss -0.8036 +2024-11-22 16:39:11.532423: val_loss -0.7492 +2024-11-22 16:39:11.532523: Pseudo dice [0.8246] +2024-11-22 16:39:11.532610: Epoch time: 18.8 s +2024-11-22 16:39:12.433505: +2024-11-22 16:39:12.433700: Epoch 5493 +2024-11-22 16:39:12.433817: Current learning rate: 0.00352 +2024-11-22 16:39:31.348144: train_loss -0.8095 +2024-11-22 16:39:31.348391: val_loss -0.7758 +2024-11-22 16:39:31.348466: Pseudo dice [0.8351] +2024-11-22 16:39:31.348545: Epoch time: 18.92 s +2024-11-22 16:39:32.258931: +2024-11-22 16:39:32.259131: Epoch 5494 +2024-11-22 16:39:32.259242: Current learning rate: 0.00352 +2024-11-22 16:39:51.444468: train_loss -0.8083 +2024-11-22 16:39:51.444715: val_loss -0.7434 +2024-11-22 16:39:51.444794: Pseudo dice [0.8618] +2024-11-22 16:39:51.444872: Epoch time: 19.19 s +2024-11-22 16:39:52.347243: +2024-11-22 16:39:52.347438: Epoch 5495 +2024-11-22 16:39:52.347554: Current learning rate: 0.00352 +2024-11-22 16:40:10.369838: train_loss -0.8102 +2024-11-22 16:40:10.370070: val_loss -0.7564 +2024-11-22 16:40:10.370146: Pseudo dice [0.8655] +2024-11-22 16:40:10.370223: Epoch time: 18.02 s +2024-11-22 16:40:11.387655: +2024-11-22 16:40:11.387855: Epoch 5496 +2024-11-22 16:40:11.387968: Current learning rate: 0.00352 +2024-11-22 16:40:30.893587: train_loss -0.8046 +2024-11-22 16:40:30.893831: val_loss -0.7527 +2024-11-22 16:40:30.893909: Pseudo dice [0.8296] +2024-11-22 16:40:30.894004: Epoch time: 19.51 s +2024-11-22 16:40:31.788123: +2024-11-22 16:40:31.788340: Epoch 5497 +2024-11-22 16:40:31.788457: Current learning rate: 0.00351 +2024-11-22 16:40:50.132680: train_loss -0.8055 +2024-11-22 16:40:50.132900: val_loss -0.7439 +2024-11-22 16:40:50.132974: Pseudo dice [0.8342] +2024-11-22 16:40:50.133092: Epoch time: 18.35 s +2024-11-22 16:40:51.031336: +2024-11-22 16:40:51.031552: Epoch 5498 +2024-11-22 16:40:51.031663: Current learning rate: 0.00351 +2024-11-22 16:41:09.861017: train_loss -0.8077 +2024-11-22 16:41:09.861273: val_loss -0.7572 +2024-11-22 16:41:09.861412: Pseudo dice [0.8405] +2024-11-22 16:41:09.861491: Epoch time: 18.83 s +2024-11-22 16:41:11.204665: +2024-11-22 16:41:11.204880: Epoch 5499 +2024-11-22 16:41:11.205004: Current learning rate: 0.00351 +2024-11-22 16:41:29.012418: train_loss -0.7789 +2024-11-22 16:41:29.012650: val_loss -0.7399 +2024-11-22 16:41:29.012726: Pseudo dice [0.8576] +2024-11-22 16:41:29.012807: Epoch time: 17.81 s +2024-11-22 16:41:30.219561: +2024-11-22 16:41:30.219845: Epoch 5500 +2024-11-22 16:41:30.220008: Current learning rate: 0.00351 +2024-11-22 16:41:49.458757: train_loss -0.7999 +2024-11-22 16:41:49.458987: val_loss -0.7566 +2024-11-22 16:41:49.459069: Pseudo dice [0.8638] +2024-11-22 16:41:49.459147: Epoch time: 19.24 s +2024-11-22 16:41:50.353664: +2024-11-22 16:41:50.353878: Epoch 5501 +2024-11-22 16:41:50.353990: Current learning rate: 0.00351 +2024-11-22 16:42:08.745903: train_loss -0.7977 +2024-11-22 16:42:08.746131: val_loss -0.7786 +2024-11-22 16:42:08.746207: Pseudo dice [0.8466] +2024-11-22 16:42:08.746288: Epoch time: 18.39 s +2024-11-22 16:42:09.637872: +2024-11-22 16:42:09.638106: Epoch 5502 +2024-11-22 16:42:09.638224: Current learning rate: 0.00351 +2024-11-22 16:42:28.088620: train_loss -0.8097 +2024-11-22 16:42:28.088841: val_loss -0.7595 +2024-11-22 16:42:28.088916: Pseudo dice [0.8543] +2024-11-22 16:42:28.089000: Epoch time: 18.45 s +2024-11-22 16:42:28.983296: +2024-11-22 16:42:28.983497: Epoch 5503 +2024-11-22 16:42:28.983614: Current learning rate: 0.00351 +2024-11-22 16:42:47.958380: train_loss -0.805 +2024-11-22 16:42:47.958668: val_loss -0.771 +2024-11-22 16:42:47.958746: Pseudo dice [0.8624] +2024-11-22 16:42:47.958835: Epoch time: 18.98 s +2024-11-22 16:42:48.862597: +2024-11-22 16:42:48.862823: Epoch 5504 +2024-11-22 16:42:48.862945: Current learning rate: 0.00351 +2024-11-22 16:43:08.797191: train_loss -0.7989 +2024-11-22 16:43:08.802585: val_loss -0.7546 +2024-11-22 16:43:08.802673: Pseudo dice [0.8683] +2024-11-22 16:43:08.802753: Epoch time: 19.94 s +2024-11-22 16:43:09.846525: +2024-11-22 16:43:09.846769: Epoch 5505 +2024-11-22 16:43:09.846881: Current learning rate: 0.0035 +2024-11-22 16:43:29.209514: train_loss -0.8025 +2024-11-22 16:43:29.209744: val_loss -0.7426 +2024-11-22 16:43:29.209824: Pseudo dice [0.843] +2024-11-22 16:43:29.209903: Epoch time: 19.36 s +2024-11-22 16:43:30.220107: +2024-11-22 16:43:30.220302: Epoch 5506 +2024-11-22 16:43:30.220417: Current learning rate: 0.0035 +2024-11-22 16:43:50.010879: train_loss -0.8061 +2024-11-22 16:43:50.011145: val_loss -0.7574 +2024-11-22 16:43:50.011223: Pseudo dice [0.8522] +2024-11-22 16:43:50.011335: Epoch time: 19.79 s +2024-11-22 16:43:50.925946: +2024-11-22 16:43:50.926306: Epoch 5507 +2024-11-22 16:43:50.926435: Current learning rate: 0.0035 +2024-11-22 16:44:08.909328: train_loss -0.8091 +2024-11-22 16:44:08.909577: val_loss -0.7284 +2024-11-22 16:44:08.909651: Pseudo dice [0.8317] +2024-11-22 16:44:08.909733: Epoch time: 17.98 s +2024-11-22 16:44:09.917401: +2024-11-22 16:44:09.917595: Epoch 5508 +2024-11-22 16:44:09.917707: Current learning rate: 0.0035 +2024-11-22 16:44:28.996123: train_loss -0.8029 +2024-11-22 16:44:28.996343: val_loss -0.7516 +2024-11-22 16:44:28.996421: Pseudo dice [0.8523] +2024-11-22 16:44:28.996498: Epoch time: 19.08 s +2024-11-22 16:44:29.890665: +2024-11-22 16:44:29.890870: Epoch 5509 +2024-11-22 16:44:29.890982: Current learning rate: 0.0035 +2024-11-22 16:44:48.147598: train_loss -0.8011 +2024-11-22 16:44:48.148048: val_loss -0.7508 +2024-11-22 16:44:48.148139: Pseudo dice [0.8427] +2024-11-22 16:44:48.148220: Epoch time: 18.26 s +2024-11-22 16:44:49.039893: +2024-11-22 16:44:49.040199: Epoch 5510 +2024-11-22 16:44:49.040326: Current learning rate: 0.0035 +2024-11-22 16:45:08.476278: train_loss -0.8007 +2024-11-22 16:45:08.476565: val_loss -0.7551 +2024-11-22 16:45:08.476646: Pseudo dice [0.8439] +2024-11-22 16:45:08.476727: Epoch time: 19.44 s +2024-11-22 16:45:09.382123: +2024-11-22 16:45:09.382412: Epoch 5511 +2024-11-22 16:45:09.382523: Current learning rate: 0.0035 +2024-11-22 16:45:28.217894: train_loss -0.8117 +2024-11-22 16:45:28.218118: val_loss -0.7706 +2024-11-22 16:45:28.218194: Pseudo dice [0.8523] +2024-11-22 16:45:28.218270: Epoch time: 18.84 s +2024-11-22 16:45:29.119542: +2024-11-22 16:45:29.119746: Epoch 5512 +2024-11-22 16:45:29.119862: Current learning rate: 0.0035 +2024-11-22 16:45:48.594739: train_loss -0.8084 +2024-11-22 16:45:48.594973: val_loss -0.7473 +2024-11-22 16:45:48.595057: Pseudo dice [0.8573] +2024-11-22 16:45:48.595134: Epoch time: 19.48 s +2024-11-22 16:45:49.517004: +2024-11-22 16:45:49.517212: Epoch 5513 +2024-11-22 16:45:49.517326: Current learning rate: 0.00349 +2024-11-22 16:46:08.485428: train_loss -0.8082 +2024-11-22 16:46:08.485656: val_loss -0.7609 +2024-11-22 16:46:08.485735: Pseudo dice [0.8635] +2024-11-22 16:46:08.485816: Epoch time: 18.97 s +2024-11-22 16:46:09.519818: +2024-11-22 16:46:09.520024: Epoch 5514 +2024-11-22 16:46:09.520139: Current learning rate: 0.00349 +2024-11-22 16:46:28.013980: train_loss -0.8069 +2024-11-22 16:46:28.014248: val_loss -0.7428 +2024-11-22 16:46:28.014324: Pseudo dice [0.8365] +2024-11-22 16:46:28.014407: Epoch time: 18.49 s +2024-11-22 16:46:28.905480: +2024-11-22 16:46:28.905692: Epoch 5515 +2024-11-22 16:46:28.905805: Current learning rate: 0.00349 +2024-11-22 16:46:47.455358: train_loss -0.8104 +2024-11-22 16:46:47.455582: val_loss -0.7606 +2024-11-22 16:46:47.455660: Pseudo dice [0.8554] +2024-11-22 16:46:47.455741: Epoch time: 18.55 s +2024-11-22 16:46:48.354271: +2024-11-22 16:46:48.354477: Epoch 5516 +2024-11-22 16:46:48.354592: Current learning rate: 0.00349 +2024-11-22 16:47:06.576678: train_loss -0.8062 +2024-11-22 16:47:06.576926: val_loss -0.7371 +2024-11-22 16:47:06.577011: Pseudo dice [0.8125] +2024-11-22 16:47:06.577090: Epoch time: 18.22 s +2024-11-22 16:47:07.473021: +2024-11-22 16:47:07.473289: Epoch 5517 +2024-11-22 16:47:07.473404: Current learning rate: 0.00349 +2024-11-22 16:47:25.378945: train_loss -0.809 +2024-11-22 16:47:25.379168: val_loss -0.7554 +2024-11-22 16:47:25.379245: Pseudo dice [0.8645] +2024-11-22 16:47:25.379321: Epoch time: 17.91 s +2024-11-22 16:47:26.277578: +2024-11-22 16:47:26.277788: Epoch 5518 +2024-11-22 16:47:26.277900: Current learning rate: 0.00349 +2024-11-22 16:47:46.184753: train_loss -0.8001 +2024-11-22 16:47:46.185019: val_loss -0.7322 +2024-11-22 16:47:46.185100: Pseudo dice [0.8337] +2024-11-22 16:47:46.185184: Epoch time: 19.91 s +2024-11-22 16:47:47.079950: +2024-11-22 16:47:47.080150: Epoch 5519 +2024-11-22 16:47:47.080263: Current learning rate: 0.00349 +2024-11-22 16:48:07.091080: train_loss -0.7855 +2024-11-22 16:48:07.098061: val_loss -0.7381 +2024-11-22 16:48:07.098208: Pseudo dice [0.8505] +2024-11-22 16:48:07.098292: Epoch time: 20.01 s +2024-11-22 16:48:08.115053: +2024-11-22 16:48:08.115252: Epoch 5520 +2024-11-22 16:48:08.115362: Current learning rate: 0.00349 +2024-11-22 16:48:27.942959: train_loss -0.797 +2024-11-22 16:48:27.943187: val_loss -0.7533 +2024-11-22 16:48:27.943262: Pseudo dice [0.832] +2024-11-22 16:48:27.943337: Epoch time: 19.83 s +2024-11-22 16:48:28.870706: +2024-11-22 16:48:28.871187: Epoch 5521 +2024-11-22 16:48:28.871334: Current learning rate: 0.00348 +2024-11-22 16:48:48.166937: train_loss -0.8059 +2024-11-22 16:48:48.167164: val_loss -0.741 +2024-11-22 16:48:48.167238: Pseudo dice [0.8426] +2024-11-22 16:48:48.167315: Epoch time: 19.3 s +2024-11-22 16:48:49.474487: +2024-11-22 16:48:49.474775: Epoch 5522 +2024-11-22 16:48:49.474900: Current learning rate: 0.00348 +2024-11-22 16:49:06.757845: train_loss -0.8061 +2024-11-22 16:49:06.758107: val_loss -0.7496 +2024-11-22 16:49:06.758182: Pseudo dice [0.8489] +2024-11-22 16:49:06.758264: Epoch time: 17.28 s +2024-11-22 16:49:07.659596: +2024-11-22 16:49:07.659943: Epoch 5523 +2024-11-22 16:49:07.660059: Current learning rate: 0.00348 +2024-11-22 16:49:26.668808: train_loss -0.8118 +2024-11-22 16:49:26.669065: val_loss -0.7467 +2024-11-22 16:49:26.669141: Pseudo dice [0.8363] +2024-11-22 16:49:26.669215: Epoch time: 19.01 s +2024-11-22 16:49:27.597362: +2024-11-22 16:49:27.597571: Epoch 5524 +2024-11-22 16:49:27.597681: Current learning rate: 0.00348 +2024-11-22 16:49:47.200249: train_loss -0.8038 +2024-11-22 16:49:47.200471: val_loss -0.7441 +2024-11-22 16:49:47.200547: Pseudo dice [0.8387] +2024-11-22 16:49:47.200628: Epoch time: 19.6 s +2024-11-22 16:49:48.102301: +2024-11-22 16:49:48.102509: Epoch 5525 +2024-11-22 16:49:48.102622: Current learning rate: 0.00348 +2024-11-22 16:50:07.442879: train_loss -0.7984 +2024-11-22 16:50:07.443220: val_loss -0.7819 +2024-11-22 16:50:07.443305: Pseudo dice [0.8571] +2024-11-22 16:50:07.443390: Epoch time: 19.34 s +2024-11-22 16:50:08.342525: +2024-11-22 16:50:08.342716: Epoch 5526 +2024-11-22 16:50:08.342829: Current learning rate: 0.00348 +2024-11-22 16:50:27.051099: train_loss -0.803 +2024-11-22 16:50:27.051323: val_loss -0.7447 +2024-11-22 16:50:27.051401: Pseudo dice [0.8533] +2024-11-22 16:50:27.051478: Epoch time: 18.71 s +2024-11-22 16:50:27.975391: +2024-11-22 16:50:27.975648: Epoch 5527 +2024-11-22 16:50:27.975760: Current learning rate: 0.00348 +2024-11-22 16:50:46.520828: train_loss -0.8084 +2024-11-22 16:50:46.523223: val_loss -0.7449 +2024-11-22 16:50:46.523342: Pseudo dice [0.8552] +2024-11-22 16:50:46.523425: Epoch time: 18.55 s +2024-11-22 16:50:47.447551: +2024-11-22 16:50:47.447744: Epoch 5528 +2024-11-22 16:50:47.447850: Current learning rate: 0.00348 +2024-11-22 16:51:06.291233: train_loss -0.7999 +2024-11-22 16:51:06.291449: val_loss -0.7399 +2024-11-22 16:51:06.293747: Pseudo dice [0.8441] +2024-11-22 16:51:06.293858: Epoch time: 18.84 s +2024-11-22 16:51:07.211931: +2024-11-22 16:51:07.212124: Epoch 5529 +2024-11-22 16:51:07.212237: Current learning rate: 0.00347 +2024-11-22 16:51:25.360043: train_loss -0.8058 +2024-11-22 16:51:25.360292: val_loss -0.7601 +2024-11-22 16:51:25.360370: Pseudo dice [0.8298] +2024-11-22 16:51:25.360454: Epoch time: 18.15 s +2024-11-22 16:51:26.347442: +2024-11-22 16:51:26.347732: Epoch 5530 +2024-11-22 16:51:26.347845: Current learning rate: 0.00347 +2024-11-22 16:51:45.952796: train_loss -0.7972 +2024-11-22 16:51:45.953018: val_loss -0.7598 +2024-11-22 16:51:45.953098: Pseudo dice [0.8304] +2024-11-22 16:51:45.953179: Epoch time: 19.61 s +2024-11-22 16:51:47.065454: +2024-11-22 16:51:47.065746: Epoch 5531 +2024-11-22 16:51:47.065860: Current learning rate: 0.00347 +2024-11-22 16:52:05.181938: train_loss -0.8005 +2024-11-22 16:52:05.182173: val_loss -0.7465 +2024-11-22 16:52:05.182247: Pseudo dice [0.8673] +2024-11-22 16:52:05.182325: Epoch time: 18.12 s +2024-11-22 16:52:06.078686: +2024-11-22 16:52:06.079102: Epoch 5532 +2024-11-22 16:52:06.079231: Current learning rate: 0.00347 +2024-11-22 16:52:24.833479: train_loss -0.8137 +2024-11-22 16:52:24.833702: val_loss -0.7596 +2024-11-22 16:52:24.833777: Pseudo dice [0.8285] +2024-11-22 16:52:24.833855: Epoch time: 18.76 s +2024-11-22 16:52:25.725195: +2024-11-22 16:52:25.725665: Epoch 5533 +2024-11-22 16:52:25.725801: Current learning rate: 0.00347 +2024-11-22 16:52:45.411665: train_loss -0.8098 +2024-11-22 16:52:45.411911: val_loss -0.7778 +2024-11-22 16:52:45.411984: Pseudo dice [0.8575] +2024-11-22 16:52:45.412068: Epoch time: 19.69 s +2024-11-22 16:52:46.734298: +2024-11-22 16:52:46.734514: Epoch 5534 +2024-11-22 16:52:46.734624: Current learning rate: 0.00347 +2024-11-22 16:53:05.624833: train_loss -0.8164 +2024-11-22 16:53:05.625064: val_loss -0.7672 +2024-11-22 16:53:05.625138: Pseudo dice [0.8503] +2024-11-22 16:53:05.625221: Epoch time: 18.89 s +2024-11-22 16:53:06.519696: +2024-11-22 16:53:06.519940: Epoch 5535 +2024-11-22 16:53:06.520057: Current learning rate: 0.00347 +2024-11-22 16:53:25.276284: train_loss -0.8092 +2024-11-22 16:53:25.276574: val_loss -0.7447 +2024-11-22 16:53:25.276662: Pseudo dice [0.8519] +2024-11-22 16:53:25.276740: Epoch time: 18.76 s +2024-11-22 16:53:26.169544: +2024-11-22 16:53:26.169755: Epoch 5536 +2024-11-22 16:53:26.169867: Current learning rate: 0.00346 +2024-11-22 16:53:45.475275: train_loss -0.8122 +2024-11-22 16:53:45.475532: val_loss -0.7533 +2024-11-22 16:53:45.475670: Pseudo dice [0.8497] +2024-11-22 16:53:45.475760: Epoch time: 19.31 s +2024-11-22 16:53:46.372304: +2024-11-22 16:53:46.372509: Epoch 5537 +2024-11-22 16:53:46.372624: Current learning rate: 0.00346 +2024-11-22 16:54:05.876023: train_loss -0.8095 +2024-11-22 16:54:05.876256: val_loss -0.7503 +2024-11-22 16:54:05.876337: Pseudo dice [0.8542] +2024-11-22 16:54:05.876415: Epoch time: 19.5 s +2024-11-22 16:54:06.781595: +2024-11-22 16:54:06.781816: Epoch 5538 +2024-11-22 16:54:06.781930: Current learning rate: 0.00346 +2024-11-22 16:54:25.902359: train_loss -0.8108 +2024-11-22 16:54:25.902649: val_loss -0.7562 +2024-11-22 16:54:25.902734: Pseudo dice [0.8515] +2024-11-22 16:54:25.902812: Epoch time: 19.12 s +2024-11-22 16:54:26.805411: +2024-11-22 16:54:26.805643: Epoch 5539 +2024-11-22 16:54:26.805752: Current learning rate: 0.00346 +2024-11-22 16:54:45.208097: train_loss -0.8119 +2024-11-22 16:54:45.208326: val_loss -0.7769 +2024-11-22 16:54:45.208401: Pseudo dice [0.8545] +2024-11-22 16:54:45.208478: Epoch time: 18.4 s +2024-11-22 16:54:46.107851: +2024-11-22 16:54:46.108079: Epoch 5540 +2024-11-22 16:54:46.108190: Current learning rate: 0.00346 +2024-11-22 16:55:05.418568: train_loss -0.8114 +2024-11-22 16:55:05.418849: val_loss -0.7694 +2024-11-22 16:55:05.418932: Pseudo dice [0.8609] +2024-11-22 16:55:05.419019: Epoch time: 19.31 s +2024-11-22 16:55:06.327369: +2024-11-22 16:55:06.327594: Epoch 5541 +2024-11-22 16:55:06.327711: Current learning rate: 0.00346 +2024-11-22 16:55:25.208684: train_loss -0.8065 +2024-11-22 16:55:25.208934: val_loss -0.7277 +2024-11-22 16:55:25.209014: Pseudo dice [0.8331] +2024-11-22 16:55:25.209174: Epoch time: 18.88 s +2024-11-22 16:55:26.125087: +2024-11-22 16:55:26.125308: Epoch 5542 +2024-11-22 16:55:26.125418: Current learning rate: 0.00346 +2024-11-22 16:55:44.506919: train_loss -0.8081 +2024-11-22 16:55:44.507146: val_loss -0.7458 +2024-11-22 16:55:44.507227: Pseudo dice [0.8552] +2024-11-22 16:55:44.507307: Epoch time: 18.38 s +2024-11-22 16:55:45.410252: +2024-11-22 16:55:45.410473: Epoch 5543 +2024-11-22 16:55:45.410590: Current learning rate: 0.00346 +2024-11-22 16:56:05.287345: train_loss -0.8081 +2024-11-22 16:56:05.287578: val_loss -0.7638 +2024-11-22 16:56:05.287653: Pseudo dice [0.864] +2024-11-22 16:56:05.287728: Epoch time: 19.88 s +2024-11-22 16:56:06.378990: +2024-11-22 16:56:06.379216: Epoch 5544 +2024-11-22 16:56:06.379330: Current learning rate: 0.00345 +2024-11-22 16:56:23.749454: train_loss -0.8006 +2024-11-22 16:56:23.749724: val_loss -0.7671 +2024-11-22 16:56:23.749835: Pseudo dice [0.8506] +2024-11-22 16:56:23.749919: Epoch time: 17.37 s +2024-11-22 16:56:24.710850: +2024-11-22 16:56:24.711454: Epoch 5545 +2024-11-22 16:56:24.711631: Current learning rate: 0.00345 +2024-11-22 16:56:43.238014: train_loss -0.7994 +2024-11-22 16:56:43.238291: val_loss -0.7422 +2024-11-22 16:56:43.238367: Pseudo dice [0.8343] +2024-11-22 16:56:43.238448: Epoch time: 18.53 s +2024-11-22 16:56:44.517367: +2024-11-22 16:56:44.517640: Epoch 5546 +2024-11-22 16:56:44.517759: Current learning rate: 0.00345 +2024-11-22 16:57:03.939781: train_loss -0.8015 +2024-11-22 16:57:03.940045: val_loss -0.715 +2024-11-22 16:57:03.940121: Pseudo dice [0.8425] +2024-11-22 16:57:03.940202: Epoch time: 19.42 s +2024-11-22 16:57:04.960392: +2024-11-22 16:57:04.960600: Epoch 5547 +2024-11-22 16:57:04.960715: Current learning rate: 0.00345 +2024-11-22 16:57:23.699851: train_loss -0.8123 +2024-11-22 16:57:23.700089: val_loss -0.7281 +2024-11-22 16:57:23.700183: Pseudo dice [0.8506] +2024-11-22 16:57:23.700270: Epoch time: 18.74 s +2024-11-22 16:57:24.600561: +2024-11-22 16:57:24.600764: Epoch 5548 +2024-11-22 16:57:24.600878: Current learning rate: 0.00345 +2024-11-22 16:57:44.808246: train_loss -0.8051 +2024-11-22 16:57:44.808495: val_loss -0.7606 +2024-11-22 16:57:44.808651: Pseudo dice [0.8602] +2024-11-22 16:57:44.808739: Epoch time: 20.21 s +2024-11-22 16:57:45.718682: +2024-11-22 16:57:45.718917: Epoch 5549 +2024-11-22 16:57:45.719029: Current learning rate: 0.00345 +2024-11-22 16:58:04.815481: train_loss -0.8066 +2024-11-22 16:58:04.815695: val_loss -0.7593 +2024-11-22 16:58:04.815771: Pseudo dice [0.8632] +2024-11-22 16:58:04.815847: Epoch time: 19.1 s +2024-11-22 16:58:06.006432: +2024-11-22 16:58:06.006665: Epoch 5550 +2024-11-22 16:58:06.006780: Current learning rate: 0.00345 +2024-11-22 16:58:25.333527: train_loss -0.8108 +2024-11-22 16:58:25.333740: val_loss -0.7317 +2024-11-22 16:58:25.333815: Pseudo dice [0.8505] +2024-11-22 16:58:25.333889: Epoch time: 19.33 s +2024-11-22 16:58:26.205467: +2024-11-22 16:58:26.205694: Epoch 5551 +2024-11-22 16:58:26.205804: Current learning rate: 0.00345 +2024-11-22 16:58:46.707003: train_loss -0.8099 +2024-11-22 16:58:46.707216: val_loss -0.7665 +2024-11-22 16:58:46.707288: Pseudo dice [0.8639] +2024-11-22 16:58:46.707363: Epoch time: 20.5 s +2024-11-22 16:58:47.641948: +2024-11-22 16:58:47.642194: Epoch 5552 +2024-11-22 16:58:47.642324: Current learning rate: 0.00344 +2024-11-22 16:59:06.938237: train_loss -0.7983 +2024-11-22 16:59:06.938482: val_loss -0.7574 +2024-11-22 16:59:06.938561: Pseudo dice [0.8416] +2024-11-22 16:59:06.938646: Epoch time: 19.3 s +2024-11-22 16:59:07.838872: +2024-11-22 16:59:07.839068: Epoch 5553 +2024-11-22 16:59:07.839180: Current learning rate: 0.00344 +2024-11-22 16:59:25.987447: train_loss -0.8074 +2024-11-22 16:59:25.987669: val_loss -0.7424 +2024-11-22 16:59:25.987745: Pseudo dice [0.8547] +2024-11-22 16:59:25.987823: Epoch time: 18.15 s +2024-11-22 16:59:26.901569: +2024-11-22 16:59:26.901792: Epoch 5554 +2024-11-22 16:59:26.901902: Current learning rate: 0.00344 +2024-11-22 16:59:45.429745: train_loss -0.8114 +2024-11-22 16:59:45.430472: val_loss -0.7661 +2024-11-22 16:59:45.430555: Pseudo dice [0.8291] +2024-11-22 16:59:45.430638: Epoch time: 18.53 s +2024-11-22 16:59:46.334339: +2024-11-22 16:59:46.334532: Epoch 5555 +2024-11-22 16:59:46.334651: Current learning rate: 0.00344 +2024-11-22 17:00:04.141332: train_loss -0.8116 +2024-11-22 17:00:04.141581: val_loss -0.7403 +2024-11-22 17:00:04.141655: Pseudo dice [0.8449] +2024-11-22 17:00:04.141737: Epoch time: 17.81 s +2024-11-22 17:00:05.184420: +2024-11-22 17:00:05.184827: Epoch 5556 +2024-11-22 17:00:05.184963: Current learning rate: 0.00344 +2024-11-22 17:00:23.910590: train_loss -0.8113 +2024-11-22 17:00:23.911593: val_loss -0.7417 +2024-11-22 17:00:23.911729: Pseudo dice [0.8449] +2024-11-22 17:00:23.911815: Epoch time: 18.73 s +2024-11-22 17:00:24.809302: +2024-11-22 17:00:24.809638: Epoch 5557 +2024-11-22 17:00:24.809769: Current learning rate: 0.00344 +2024-11-22 17:00:42.915277: train_loss -0.804 +2024-11-22 17:00:42.915516: val_loss -0.7686 +2024-11-22 17:00:42.915597: Pseudo dice [0.8341] +2024-11-22 17:00:42.915678: Epoch time: 18.11 s +2024-11-22 17:00:43.860126: +2024-11-22 17:00:43.860333: Epoch 5558 +2024-11-22 17:00:43.860445: Current learning rate: 0.00344 +2024-11-22 17:01:03.324386: train_loss -0.8074 +2024-11-22 17:01:03.324616: val_loss -0.7417 +2024-11-22 17:01:03.324695: Pseudo dice [0.8416] +2024-11-22 17:01:03.324780: Epoch time: 19.47 s +2024-11-22 17:01:04.469317: +2024-11-22 17:01:04.469533: Epoch 5559 +2024-11-22 17:01:04.469645: Current learning rate: 0.00344 +2024-11-22 17:01:24.251611: train_loss -0.8059 +2024-11-22 17:01:24.251883: val_loss -0.7537 +2024-11-22 17:01:24.251964: Pseudo dice [0.852] +2024-11-22 17:01:24.252075: Epoch time: 19.78 s +2024-11-22 17:01:25.158506: +2024-11-22 17:01:25.158743: Epoch 5560 +2024-11-22 17:01:25.158857: Current learning rate: 0.00343 +2024-11-22 17:01:42.829800: train_loss -0.8131 +2024-11-22 17:01:42.830029: val_loss -0.7697 +2024-11-22 17:01:42.830107: Pseudo dice [0.8467] +2024-11-22 17:01:42.830185: Epoch time: 17.67 s +2024-11-22 17:01:43.731469: +2024-11-22 17:01:43.731686: Epoch 5561 +2024-11-22 17:01:43.731797: Current learning rate: 0.00343 +2024-11-22 17:02:02.222070: train_loss -0.804 +2024-11-22 17:02:02.222336: val_loss -0.759 +2024-11-22 17:02:02.222412: Pseudo dice [0.8479] +2024-11-22 17:02:02.222489: Epoch time: 18.49 s +2024-11-22 17:02:03.154273: +2024-11-22 17:02:03.154490: Epoch 5562 +2024-11-22 17:02:03.154603: Current learning rate: 0.00343 +2024-11-22 17:02:21.217540: train_loss -0.8111 +2024-11-22 17:02:21.217774: val_loss -0.7708 +2024-11-22 17:02:21.217853: Pseudo dice [0.8545] +2024-11-22 17:02:21.217955: Epoch time: 18.06 s +2024-11-22 17:02:22.147816: +2024-11-22 17:02:22.148070: Epoch 5563 +2024-11-22 17:02:22.148182: Current learning rate: 0.00343 +2024-11-22 17:02:40.841629: train_loss -0.8043 +2024-11-22 17:02:40.841927: val_loss -0.7597 +2024-11-22 17:02:40.842010: Pseudo dice [0.865] +2024-11-22 17:02:40.842145: Epoch time: 18.69 s +2024-11-22 17:02:41.743762: +2024-11-22 17:02:41.744010: Epoch 5564 +2024-11-22 17:02:41.744126: Current learning rate: 0.00343 +2024-11-22 17:03:00.021430: train_loss -0.8092 +2024-11-22 17:03:00.021669: val_loss -0.7494 +2024-11-22 17:03:00.021746: Pseudo dice [0.8393] +2024-11-22 17:03:00.021866: Epoch time: 18.28 s +2024-11-22 17:03:00.922129: +2024-11-22 17:03:00.922367: Epoch 5565 +2024-11-22 17:03:00.923704: Current learning rate: 0.00343 +2024-11-22 17:03:19.072129: train_loss -0.805 +2024-11-22 17:03:19.072352: val_loss -0.7422 +2024-11-22 17:03:19.072432: Pseudo dice [0.8501] +2024-11-22 17:03:19.072512: Epoch time: 18.15 s +2024-11-22 17:03:20.067425: +2024-11-22 17:03:20.067703: Epoch 5566 +2024-11-22 17:03:20.067813: Current learning rate: 0.00343 +2024-11-22 17:03:38.777031: train_loss -0.8082 +2024-11-22 17:03:38.777268: val_loss -0.748 +2024-11-22 17:03:38.777345: Pseudo dice [0.861] +2024-11-22 17:03:38.777422: Epoch time: 18.71 s +2024-11-22 17:03:39.670610: +2024-11-22 17:03:39.670852: Epoch 5567 +2024-11-22 17:03:39.670968: Current learning rate: 0.00343 +2024-11-22 17:03:58.670796: train_loss -0.8079 +2024-11-22 17:03:58.671052: val_loss -0.723 +2024-11-22 17:03:58.671130: Pseudo dice [0.829] +2024-11-22 17:03:58.671215: Epoch time: 19.0 s +2024-11-22 17:03:59.568983: +2024-11-22 17:03:59.569180: Epoch 5568 +2024-11-22 17:03:59.569290: Current learning rate: 0.00342 +2024-11-22 17:04:18.036417: train_loss -0.8043 +2024-11-22 17:04:18.037120: val_loss -0.7728 +2024-11-22 17:04:18.037194: Pseudo dice [0.8333] +2024-11-22 17:04:18.037271: Epoch time: 18.47 s +2024-11-22 17:04:19.313226: +2024-11-22 17:04:19.313473: Epoch 5569 +2024-11-22 17:04:19.313598: Current learning rate: 0.00342 +2024-11-22 17:04:37.893123: train_loss -0.7988 +2024-11-22 17:04:37.895530: val_loss -0.7492 +2024-11-22 17:04:37.895616: Pseudo dice [0.8509] +2024-11-22 17:04:37.895694: Epoch time: 18.58 s +2024-11-22 17:04:38.815144: +2024-11-22 17:04:38.815448: Epoch 5570 +2024-11-22 17:04:38.815565: Current learning rate: 0.00342 +2024-11-22 17:04:57.705681: train_loss -0.8043 +2024-11-22 17:04:57.705932: val_loss -0.776 +2024-11-22 17:04:57.706015: Pseudo dice [0.8364] +2024-11-22 17:04:57.706096: Epoch time: 18.89 s +2024-11-22 17:04:58.610246: +2024-11-22 17:04:58.610464: Epoch 5571 +2024-11-22 17:04:58.610577: Current learning rate: 0.00342 +2024-11-22 17:05:17.710225: train_loss -0.7965 +2024-11-22 17:05:17.710472: val_loss -0.7425 +2024-11-22 17:05:17.710549: Pseudo dice [0.8622] +2024-11-22 17:05:17.710628: Epoch time: 19.1 s +2024-11-22 17:05:18.609784: +2024-11-22 17:05:18.609980: Epoch 5572 +2024-11-22 17:05:18.610096: Current learning rate: 0.00342 +2024-11-22 17:05:36.128747: train_loss -0.8098 +2024-11-22 17:05:36.131153: val_loss -0.7726 +2024-11-22 17:05:36.131244: Pseudo dice [0.8468] +2024-11-22 17:05:36.131320: Epoch time: 17.52 s +2024-11-22 17:05:37.158110: +2024-11-22 17:05:37.158320: Epoch 5573 +2024-11-22 17:05:37.158434: Current learning rate: 0.00342 +2024-11-22 17:05:55.979354: train_loss -0.7931 +2024-11-22 17:05:55.979578: val_loss -0.7541 +2024-11-22 17:05:55.979655: Pseudo dice [0.8475] +2024-11-22 17:05:55.979732: Epoch time: 18.82 s +2024-11-22 17:05:56.910759: +2024-11-22 17:05:56.910955: Epoch 5574 +2024-11-22 17:05:56.911074: Current learning rate: 0.00342 +2024-11-22 17:06:17.232350: train_loss -0.782 +2024-11-22 17:06:17.232569: val_loss -0.7496 +2024-11-22 17:06:17.232648: Pseudo dice [0.8643] +2024-11-22 17:06:17.232732: Epoch time: 20.32 s +2024-11-22 17:06:18.132075: +2024-11-22 17:06:18.132281: Epoch 5575 +2024-11-22 17:06:18.132391: Current learning rate: 0.00342 +2024-11-22 17:06:37.918569: train_loss -0.7842 +2024-11-22 17:06:37.918869: val_loss -0.7543 +2024-11-22 17:06:37.918951: Pseudo dice [0.8481] +2024-11-22 17:06:37.919044: Epoch time: 19.79 s +2024-11-22 17:06:38.819936: +2024-11-22 17:06:38.820152: Epoch 5576 +2024-11-22 17:06:38.820266: Current learning rate: 0.00341 +2024-11-22 17:06:57.543675: train_loss -0.7948 +2024-11-22 17:06:57.543891: val_loss -0.7587 +2024-11-22 17:06:57.543965: Pseudo dice [0.8483] +2024-11-22 17:06:57.544047: Epoch time: 18.72 s +2024-11-22 17:06:58.609917: +2024-11-22 17:06:58.610133: Epoch 5577 +2024-11-22 17:06:58.610250: Current learning rate: 0.00341 +2024-11-22 17:07:18.663857: train_loss -0.7924 +2024-11-22 17:07:18.664117: val_loss -0.7628 +2024-11-22 17:07:18.664195: Pseudo dice [0.8519] +2024-11-22 17:07:18.664274: Epoch time: 20.05 s +2024-11-22 17:07:19.561589: +2024-11-22 17:07:19.561794: Epoch 5578 +2024-11-22 17:07:19.561911: Current learning rate: 0.00341 +2024-11-22 17:07:38.829017: train_loss -0.7984 +2024-11-22 17:07:38.829272: val_loss -0.7396 +2024-11-22 17:07:38.829351: Pseudo dice [0.8435] +2024-11-22 17:07:38.829429: Epoch time: 19.27 s +2024-11-22 17:07:39.736442: +2024-11-22 17:07:39.736716: Epoch 5579 +2024-11-22 17:07:39.736830: Current learning rate: 0.00341 +2024-11-22 17:07:57.643490: train_loss -0.8079 +2024-11-22 17:07:57.643734: val_loss -0.7494 +2024-11-22 17:07:57.643811: Pseudo dice [0.8636] +2024-11-22 17:07:57.643898: Epoch time: 17.91 s +2024-11-22 17:07:58.538711: +2024-11-22 17:07:58.538897: Epoch 5580 +2024-11-22 17:07:58.539018: Current learning rate: 0.00341 +2024-11-22 17:08:16.944940: train_loss -0.8053 +2024-11-22 17:08:16.945167: val_loss -0.7546 +2024-11-22 17:08:16.945244: Pseudo dice [0.8792] +2024-11-22 17:08:16.945323: Epoch time: 18.41 s +2024-11-22 17:08:18.273894: +2024-11-22 17:08:18.274128: Epoch 5581 +2024-11-22 17:08:18.274246: Current learning rate: 0.00341 +2024-11-22 17:08:38.035819: train_loss -0.7951 +2024-11-22 17:08:38.036061: val_loss -0.7516 +2024-11-22 17:08:38.036138: Pseudo dice [0.848] +2024-11-22 17:08:38.036215: Epoch time: 19.76 s +2024-11-22 17:08:38.942644: +2024-11-22 17:08:38.942865: Epoch 5582 +2024-11-22 17:08:38.942976: Current learning rate: 0.00341 +2024-11-22 17:08:57.528843: train_loss -0.7975 +2024-11-22 17:08:57.529091: val_loss -0.7703 +2024-11-22 17:08:57.529168: Pseudo dice [0.8362] +2024-11-22 17:08:57.529247: Epoch time: 18.59 s +2024-11-22 17:08:58.439206: +2024-11-22 17:08:58.439420: Epoch 5583 +2024-11-22 17:08:58.439530: Current learning rate: 0.00341 +2024-11-22 17:09:16.237977: train_loss -0.8021 +2024-11-22 17:09:16.238230: val_loss -0.7441 +2024-11-22 17:09:16.238313: Pseudo dice [0.8562] +2024-11-22 17:09:16.238410: Epoch time: 17.8 s +2024-11-22 17:09:17.135446: +2024-11-22 17:09:17.135674: Epoch 5584 +2024-11-22 17:09:17.135784: Current learning rate: 0.0034 +2024-11-22 17:09:36.724847: train_loss -0.7964 +2024-11-22 17:09:36.725079: val_loss -0.7607 +2024-11-22 17:09:36.725152: Pseudo dice [0.8584] +2024-11-22 17:09:36.725227: Epoch time: 19.59 s +2024-11-22 17:09:37.624935: +2024-11-22 17:09:37.625142: Epoch 5585 +2024-11-22 17:09:37.625266: Current learning rate: 0.0034 +2024-11-22 17:09:56.583676: train_loss -0.8052 +2024-11-22 17:09:56.585720: val_loss -0.7645 +2024-11-22 17:09:56.585809: Pseudo dice [0.8501] +2024-11-22 17:09:56.585886: Epoch time: 18.96 s +2024-11-22 17:09:57.482978: +2024-11-22 17:09:57.483204: Epoch 5586 +2024-11-22 17:09:57.483321: Current learning rate: 0.0034 +2024-11-22 17:10:15.965295: train_loss -0.8109 +2024-11-22 17:10:15.965508: val_loss -0.7755 +2024-11-22 17:10:15.965592: Pseudo dice [0.8405] +2024-11-22 17:10:15.965671: Epoch time: 18.48 s +2024-11-22 17:10:16.868202: +2024-11-22 17:10:16.868418: Epoch 5587 +2024-11-22 17:10:16.868528: Current learning rate: 0.0034 +2024-11-22 17:10:35.857238: train_loss -0.7998 +2024-11-22 17:10:35.857494: val_loss -0.7407 +2024-11-22 17:10:35.857569: Pseudo dice [0.8242] +2024-11-22 17:10:35.857648: Epoch time: 18.99 s +2024-11-22 17:10:36.757550: +2024-11-22 17:10:36.757824: Epoch 5588 +2024-11-22 17:10:36.757939: Current learning rate: 0.0034 +2024-11-22 17:10:55.613602: train_loss -0.7969 +2024-11-22 17:10:55.613832: val_loss -0.7477 +2024-11-22 17:10:55.613915: Pseudo dice [0.8302] +2024-11-22 17:10:55.614001: Epoch time: 18.86 s +2024-11-22 17:10:56.511155: +2024-11-22 17:10:56.511348: Epoch 5589 +2024-11-22 17:10:56.511458: Current learning rate: 0.0034 +2024-11-22 17:11:14.490305: train_loss -0.8006 +2024-11-22 17:11:14.490598: val_loss -0.756 +2024-11-22 17:11:14.490679: Pseudo dice [0.848] +2024-11-22 17:11:14.490757: Epoch time: 17.98 s +2024-11-22 17:11:15.379449: +2024-11-22 17:11:15.379656: Epoch 5590 +2024-11-22 17:11:15.379777: Current learning rate: 0.0034 +2024-11-22 17:11:33.175725: train_loss -0.7904 +2024-11-22 17:11:33.175935: val_loss -0.7656 +2024-11-22 17:11:33.176014: Pseudo dice [0.8528] +2024-11-22 17:11:33.176090: Epoch time: 17.8 s +2024-11-22 17:11:34.076814: +2024-11-22 17:11:34.077071: Epoch 5591 +2024-11-22 17:11:34.077188: Current learning rate: 0.0034 +2024-11-22 17:11:52.316495: train_loss -0.7902 +2024-11-22 17:11:52.316737: val_loss -0.7245 +2024-11-22 17:11:52.316813: Pseudo dice [0.8625] +2024-11-22 17:11:52.316895: Epoch time: 18.24 s +2024-11-22 17:11:53.271839: +2024-11-22 17:11:53.272055: Epoch 5592 +2024-11-22 17:11:53.272175: Current learning rate: 0.00339 +2024-11-22 17:12:12.838894: train_loss -0.7995 +2024-11-22 17:12:12.839128: val_loss -0.769 +2024-11-22 17:12:12.839200: Pseudo dice [0.8561] +2024-11-22 17:12:12.839278: Epoch time: 19.57 s +2024-11-22 17:12:14.149558: +2024-11-22 17:12:14.149765: Epoch 5593 +2024-11-22 17:12:14.149881: Current learning rate: 0.00339 +2024-11-22 17:12:32.813477: train_loss -0.7993 +2024-11-22 17:12:32.813701: val_loss -0.7564 +2024-11-22 17:12:32.813777: Pseudo dice [0.8333] +2024-11-22 17:12:32.813853: Epoch time: 18.66 s +2024-11-22 17:12:33.707910: +2024-11-22 17:12:33.708129: Epoch 5594 +2024-11-22 17:12:33.708240: Current learning rate: 0.00339 +2024-11-22 17:12:52.539659: train_loss -0.7985 +2024-11-22 17:12:52.539932: val_loss -0.776 +2024-11-22 17:12:52.540015: Pseudo dice [0.8692] +2024-11-22 17:12:52.540108: Epoch time: 18.83 s +2024-11-22 17:12:53.462172: +2024-11-22 17:12:53.462448: Epoch 5595 +2024-11-22 17:12:53.462566: Current learning rate: 0.00339 +2024-11-22 17:13:12.582395: train_loss -0.8055 +2024-11-22 17:13:12.582630: val_loss -0.7472 +2024-11-22 17:13:12.582707: Pseudo dice [0.8465] +2024-11-22 17:13:12.582785: Epoch time: 19.12 s +2024-11-22 17:13:13.483343: +2024-11-22 17:13:13.483584: Epoch 5596 +2024-11-22 17:13:13.483703: Current learning rate: 0.00339 +2024-11-22 17:13:31.834148: train_loss -0.795 +2024-11-22 17:13:31.834396: val_loss -0.7488 +2024-11-22 17:13:31.834476: Pseudo dice [0.834] +2024-11-22 17:13:31.834556: Epoch time: 18.35 s +2024-11-22 17:13:32.735107: +2024-11-22 17:13:32.735324: Epoch 5597 +2024-11-22 17:13:32.735435: Current learning rate: 0.00339 +2024-11-22 17:13:52.229365: train_loss -0.7976 +2024-11-22 17:13:52.229586: val_loss -0.7584 +2024-11-22 17:13:52.229666: Pseudo dice [0.8277] +2024-11-22 17:13:52.229848: Epoch time: 19.5 s +2024-11-22 17:13:53.126089: +2024-11-22 17:13:53.126292: Epoch 5598 +2024-11-22 17:13:53.126405: Current learning rate: 0.00339 +2024-11-22 17:14:10.773795: train_loss -0.7958 +2024-11-22 17:14:10.774028: val_loss -0.7442 +2024-11-22 17:14:10.774106: Pseudo dice [0.8267] +2024-11-22 17:14:10.774185: Epoch time: 17.65 s +2024-11-22 17:14:11.668325: +2024-11-22 17:14:11.668522: Epoch 5599 +2024-11-22 17:14:11.668632: Current learning rate: 0.00339 +2024-11-22 17:14:30.767059: train_loss -0.7822 +2024-11-22 17:14:30.768669: val_loss -0.7398 +2024-11-22 17:14:30.768761: Pseudo dice [0.8376] +2024-11-22 17:14:30.768842: Epoch time: 19.1 s +2024-11-22 17:14:31.974760: +2024-11-22 17:14:31.974976: Epoch 5600 +2024-11-22 17:14:31.975115: Current learning rate: 0.00338 +2024-11-22 17:14:50.594274: train_loss -0.7832 +2024-11-22 17:14:50.594490: val_loss -0.7362 +2024-11-22 17:14:50.594570: Pseudo dice [0.8259] +2024-11-22 17:14:50.594648: Epoch time: 18.62 s +2024-11-22 17:14:51.594591: +2024-11-22 17:14:51.594813: Epoch 5601 +2024-11-22 17:14:51.594929: Current learning rate: 0.00338 +2024-11-22 17:15:10.546687: train_loss -0.791 +2024-11-22 17:15:10.546913: val_loss -0.7631 +2024-11-22 17:15:10.546986: Pseudo dice [0.8485] +2024-11-22 17:15:10.547067: Epoch time: 18.95 s +2024-11-22 17:15:11.464519: +2024-11-22 17:15:11.464752: Epoch 5602 +2024-11-22 17:15:11.464865: Current learning rate: 0.00338 +2024-11-22 17:15:31.331940: train_loss -0.8004 +2024-11-22 17:15:31.332167: val_loss -0.7422 +2024-11-22 17:15:31.332241: Pseudo dice [0.8448] +2024-11-22 17:15:31.332315: Epoch time: 19.87 s +2024-11-22 17:15:32.236449: +2024-11-22 17:15:32.236674: Epoch 5603 +2024-11-22 17:15:32.236786: Current learning rate: 0.00338 +2024-11-22 17:15:51.374860: train_loss -0.8019 +2024-11-22 17:15:51.375097: val_loss -0.7766 +2024-11-22 17:15:51.375173: Pseudo dice [0.8529] +2024-11-22 17:15:51.375252: Epoch time: 19.14 s +2024-11-22 17:15:52.272896: +2024-11-22 17:15:52.273129: Epoch 5604 +2024-11-22 17:15:52.273250: Current learning rate: 0.00338 +2024-11-22 17:16:12.107010: train_loss -0.7904 +2024-11-22 17:16:12.107256: val_loss -0.7615 +2024-11-22 17:16:12.107335: Pseudo dice [0.8496] +2024-11-22 17:16:12.107414: Epoch time: 19.83 s +2024-11-22 17:16:12.996351: +2024-11-22 17:16:12.996741: Epoch 5605 +2024-11-22 17:16:12.996861: Current learning rate: 0.00338 +2024-11-22 17:16:32.346244: train_loss -0.7962 +2024-11-22 17:16:32.347203: val_loss -0.7198 +2024-11-22 17:16:32.347287: Pseudo dice [0.8225] +2024-11-22 17:16:32.347368: Epoch time: 19.35 s +2024-11-22 17:16:33.250365: +2024-11-22 17:16:33.250619: Epoch 5606 +2024-11-22 17:16:33.250731: Current learning rate: 0.00338 +2024-11-22 17:16:51.582530: train_loss -0.7973 +2024-11-22 17:16:51.582786: val_loss -0.745 +2024-11-22 17:16:51.582870: Pseudo dice [0.8435] +2024-11-22 17:16:51.582951: Epoch time: 18.33 s +2024-11-22 17:16:52.480259: +2024-11-22 17:16:52.480473: Epoch 5607 +2024-11-22 17:16:52.480593: Current learning rate: 0.00337 +2024-11-22 17:17:11.927877: train_loss -0.8018 +2024-11-22 17:17:11.928101: val_loss -0.7629 +2024-11-22 17:17:11.928178: Pseudo dice [0.8309] +2024-11-22 17:17:11.928254: Epoch time: 19.45 s +2024-11-22 17:17:12.819338: +2024-11-22 17:17:12.819543: Epoch 5608 +2024-11-22 17:17:12.819655: Current learning rate: 0.00337 +2024-11-22 17:17:32.106787: train_loss -0.8039 +2024-11-22 17:17:32.107013: val_loss -0.7202 +2024-11-22 17:17:32.107090: Pseudo dice [0.8354] +2024-11-22 17:17:32.107193: Epoch time: 19.29 s +2024-11-22 17:17:33.007590: +2024-11-22 17:17:33.007833: Epoch 5609 +2024-11-22 17:17:33.007953: Current learning rate: 0.00337 +2024-11-22 17:17:53.287515: train_loss -0.7953 +2024-11-22 17:17:53.287728: val_loss -0.7599 +2024-11-22 17:17:53.287895: Pseudo dice [0.8494] +2024-11-22 17:17:53.287977: Epoch time: 20.28 s +2024-11-22 17:17:54.193701: +2024-11-22 17:17:54.193918: Epoch 5610 +2024-11-22 17:17:54.194050: Current learning rate: 0.00337 +2024-11-22 17:18:13.933405: train_loss -0.7999 +2024-11-22 17:18:13.933705: val_loss -0.7738 +2024-11-22 17:18:13.933786: Pseudo dice [0.8453] +2024-11-22 17:18:13.933879: Epoch time: 19.74 s +2024-11-22 17:18:14.840959: +2024-11-22 17:18:14.841162: Epoch 5611 +2024-11-22 17:18:14.841303: Current learning rate: 0.00337 +2024-11-22 17:18:33.296464: train_loss -0.8025 +2024-11-22 17:18:33.296685: val_loss -0.7593 +2024-11-22 17:18:33.296757: Pseudo dice [0.8527] +2024-11-22 17:18:33.296833: Epoch time: 18.46 s +2024-11-22 17:18:34.201249: +2024-11-22 17:18:34.201444: Epoch 5612 +2024-11-22 17:18:34.201551: Current learning rate: 0.00337 +2024-11-22 17:18:52.224721: train_loss -0.8005 +2024-11-22 17:18:52.224946: val_loss -0.757 +2024-11-22 17:18:52.225037: Pseudo dice [0.8411] +2024-11-22 17:18:52.225120: Epoch time: 18.02 s +2024-11-22 17:18:53.121188: +2024-11-22 17:18:53.121484: Epoch 5613 +2024-11-22 17:18:53.121780: Current learning rate: 0.00337 +2024-11-22 17:19:11.899460: train_loss -0.8037 +2024-11-22 17:19:11.899686: val_loss -0.7397 +2024-11-22 17:19:11.899765: Pseudo dice [0.8665] +2024-11-22 17:19:11.899845: Epoch time: 18.78 s +2024-11-22 17:19:12.814198: +2024-11-22 17:19:12.814417: Epoch 5614 +2024-11-22 17:19:12.814530: Current learning rate: 0.00337 +2024-11-22 17:19:33.555644: train_loss -0.7999 +2024-11-22 17:19:33.555893: val_loss -0.7394 +2024-11-22 17:19:33.555977: Pseudo dice [0.8509] +2024-11-22 17:19:33.556067: Epoch time: 20.74 s +2024-11-22 17:19:34.451624: +2024-11-22 17:19:34.451819: Epoch 5615 +2024-11-22 17:19:34.451929: Current learning rate: 0.00336 +2024-11-22 17:19:54.658971: train_loss -0.8048 +2024-11-22 17:19:54.659204: val_loss -0.7634 +2024-11-22 17:19:54.659312: Pseudo dice [0.8528] +2024-11-22 17:19:54.659453: Epoch time: 20.21 s +2024-11-22 17:19:55.949679: +2024-11-22 17:19:55.949896: Epoch 5616 +2024-11-22 17:19:55.950013: Current learning rate: 0.00336 +2024-11-22 17:20:15.213677: train_loss -0.7993 +2024-11-22 17:20:15.213909: val_loss -0.7726 +2024-11-22 17:20:15.214000: Pseudo dice [0.8545] +2024-11-22 17:20:15.214087: Epoch time: 19.26 s +2024-11-22 17:20:16.118952: +2024-11-22 17:20:16.119197: Epoch 5617 +2024-11-22 17:20:16.119309: Current learning rate: 0.00336 +2024-11-22 17:20:34.774083: train_loss -0.8014 +2024-11-22 17:20:34.774351: val_loss -0.7647 +2024-11-22 17:20:34.774430: Pseudo dice [0.8672] +2024-11-22 17:20:34.774576: Epoch time: 18.66 s +2024-11-22 17:20:35.679379: +2024-11-22 17:20:35.679616: Epoch 5618 +2024-11-22 17:20:35.679726: Current learning rate: 0.00336 +2024-11-22 17:20:55.114890: train_loss -0.8063 +2024-11-22 17:20:55.115116: val_loss -0.7569 +2024-11-22 17:20:55.115188: Pseudo dice [0.8449] +2024-11-22 17:20:55.115263: Epoch time: 19.44 s +2024-11-22 17:20:56.053788: +2024-11-22 17:20:56.054029: Epoch 5619 +2024-11-22 17:20:56.054138: Current learning rate: 0.00336 +2024-11-22 17:21:15.605085: train_loss -0.8047 +2024-11-22 17:21:15.605319: val_loss -0.7432 +2024-11-22 17:21:15.605397: Pseudo dice [0.8427] +2024-11-22 17:21:15.605474: Epoch time: 19.55 s +2024-11-22 17:21:16.600438: +2024-11-22 17:21:16.600655: Epoch 5620 +2024-11-22 17:21:16.600769: Current learning rate: 0.00336 +2024-11-22 17:21:35.643888: train_loss -0.8101 +2024-11-22 17:21:35.644112: val_loss -0.7547 +2024-11-22 17:21:35.644189: Pseudo dice [0.8639] +2024-11-22 17:21:35.644265: Epoch time: 19.04 s +2024-11-22 17:21:36.529805: +2024-11-22 17:21:36.530022: Epoch 5621 +2024-11-22 17:21:36.530138: Current learning rate: 0.00336 +2024-11-22 17:21:55.621425: train_loss -0.8109 +2024-11-22 17:21:55.621649: val_loss -0.7465 +2024-11-22 17:21:55.621727: Pseudo dice [0.85] +2024-11-22 17:21:55.621809: Epoch time: 19.09 s +2024-11-22 17:21:56.529575: +2024-11-22 17:21:56.529791: Epoch 5622 +2024-11-22 17:21:56.529899: Current learning rate: 0.00336 +2024-11-22 17:22:15.461081: train_loss -0.8026 +2024-11-22 17:22:15.461334: val_loss -0.7325 +2024-11-22 17:22:15.461412: Pseudo dice [0.8187] +2024-11-22 17:22:15.461494: Epoch time: 18.93 s +2024-11-22 17:22:16.371587: +2024-11-22 17:22:16.371789: Epoch 5623 +2024-11-22 17:22:16.371898: Current learning rate: 0.00335 +2024-11-22 17:22:35.483237: train_loss -0.7975 +2024-11-22 17:22:35.483457: val_loss -0.7548 +2024-11-22 17:22:35.483543: Pseudo dice [0.832] +2024-11-22 17:22:35.483622: Epoch time: 19.11 s +2024-11-22 17:22:36.367665: +2024-11-22 17:22:36.367857: Epoch 5624 +2024-11-22 17:22:36.367971: Current learning rate: 0.00335 +2024-11-22 17:22:55.567822: train_loss -0.8051 +2024-11-22 17:22:55.568051: val_loss -0.7616 +2024-11-22 17:22:55.568126: Pseudo dice [0.8544] +2024-11-22 17:22:55.568214: Epoch time: 19.2 s +2024-11-22 17:22:56.458017: +2024-11-22 17:22:56.458220: Epoch 5625 +2024-11-22 17:22:56.458337: Current learning rate: 0.00335 +2024-11-22 17:23:14.616581: train_loss -0.8006 +2024-11-22 17:23:14.616806: val_loss -0.74 +2024-11-22 17:23:14.616885: Pseudo dice [0.8413] +2024-11-22 17:23:14.616976: Epoch time: 18.16 s +2024-11-22 17:23:15.505666: +2024-11-22 17:23:15.505874: Epoch 5626 +2024-11-22 17:23:15.505982: Current learning rate: 0.00335 +2024-11-22 17:23:35.016534: train_loss -0.8005 +2024-11-22 17:23:35.016775: val_loss -0.7572 +2024-11-22 17:23:35.016854: Pseudo dice [0.814] +2024-11-22 17:23:35.016932: Epoch time: 19.51 s +2024-11-22 17:23:35.894006: +2024-11-22 17:23:35.894228: Epoch 5627 +2024-11-22 17:23:35.894336: Current learning rate: 0.00335 +2024-11-22 17:23:54.569782: train_loss -0.805 +2024-11-22 17:23:54.570003: val_loss -0.7391 +2024-11-22 17:23:54.570081: Pseudo dice [0.8393] +2024-11-22 17:23:54.570157: Epoch time: 18.68 s +2024-11-22 17:23:55.835762: +2024-11-22 17:23:55.836074: Epoch 5628 +2024-11-22 17:23:55.836188: Current learning rate: 0.00335 +2024-11-22 17:24:15.563298: train_loss -0.7949 +2024-11-22 17:24:15.563579: val_loss -0.7377 +2024-11-22 17:24:15.563658: Pseudo dice [0.852] +2024-11-22 17:24:15.563733: Epoch time: 19.73 s +2024-11-22 17:24:16.461678: +2024-11-22 17:24:16.461903: Epoch 5629 +2024-11-22 17:24:16.462022: Current learning rate: 0.00335 +2024-11-22 17:24:34.190620: train_loss -0.8021 +2024-11-22 17:24:34.190859: val_loss -0.7126 +2024-11-22 17:24:34.190938: Pseudo dice [0.8385] +2024-11-22 17:24:34.191031: Epoch time: 17.73 s +2024-11-22 17:24:35.085645: +2024-11-22 17:24:35.085913: Epoch 5630 +2024-11-22 17:24:35.086037: Current learning rate: 0.00335 +2024-11-22 17:24:53.764263: train_loss -0.7997 +2024-11-22 17:24:53.764483: val_loss -0.7469 +2024-11-22 17:24:53.764560: Pseudo dice [0.8266] +2024-11-22 17:24:53.764638: Epoch time: 18.68 s +2024-11-22 17:24:54.657755: +2024-11-22 17:24:54.657981: Epoch 5631 +2024-11-22 17:24:54.658098: Current learning rate: 0.00334 +2024-11-22 17:25:13.000263: train_loss -0.8062 +2024-11-22 17:25:13.000480: val_loss -0.7698 +2024-11-22 17:25:13.000587: Pseudo dice [0.8313] +2024-11-22 17:25:13.000673: Epoch time: 18.34 s +2024-11-22 17:25:13.886855: +2024-11-22 17:25:13.887059: Epoch 5632 +2024-11-22 17:25:13.887168: Current learning rate: 0.00334 +2024-11-22 17:25:32.497673: train_loss -0.8116 +2024-11-22 17:25:32.497883: val_loss -0.7381 +2024-11-22 17:25:32.497957: Pseudo dice [0.8297] +2024-11-22 17:25:32.498039: Epoch time: 18.61 s +2024-11-22 17:25:33.378798: +2024-11-22 17:25:33.379028: Epoch 5633 +2024-11-22 17:25:33.379144: Current learning rate: 0.00334 +2024-11-22 17:25:53.420699: train_loss -0.7997 +2024-11-22 17:25:53.420945: val_loss -0.7568 +2024-11-22 17:25:53.421031: Pseudo dice [0.8423] +2024-11-22 17:25:53.421114: Epoch time: 20.04 s +2024-11-22 17:25:54.323147: +2024-11-22 17:25:54.323348: Epoch 5634 +2024-11-22 17:25:54.323456: Current learning rate: 0.00334 +2024-11-22 17:26:12.925960: train_loss -0.813 +2024-11-22 17:26:12.926180: val_loss -0.7756 +2024-11-22 17:26:12.926254: Pseudo dice [0.8593] +2024-11-22 17:26:12.926329: Epoch time: 18.6 s +2024-11-22 17:26:13.823849: +2024-11-22 17:26:13.824066: Epoch 5635 +2024-11-22 17:26:13.824183: Current learning rate: 0.00334 +2024-11-22 17:26:32.913764: train_loss -0.8178 +2024-11-22 17:26:32.914030: val_loss -0.7539 +2024-11-22 17:26:32.914114: Pseudo dice [0.8654] +2024-11-22 17:26:32.914194: Epoch time: 19.09 s +2024-11-22 17:26:33.811247: +2024-11-22 17:26:33.811471: Epoch 5636 +2024-11-22 17:26:33.811585: Current learning rate: 0.00334 +2024-11-22 17:26:52.738440: train_loss -0.8094 +2024-11-22 17:26:52.738666: val_loss -0.7877 +2024-11-22 17:26:52.738739: Pseudo dice [0.8662] +2024-11-22 17:26:52.738813: Epoch time: 18.93 s +2024-11-22 17:26:53.636434: +2024-11-22 17:26:53.636655: Epoch 5637 +2024-11-22 17:26:53.636765: Current learning rate: 0.00334 +2024-11-22 17:27:11.268294: train_loss -0.8075 +2024-11-22 17:27:11.268553: val_loss -0.7459 +2024-11-22 17:27:11.268629: Pseudo dice [0.8421] +2024-11-22 17:27:11.268714: Epoch time: 17.63 s +2024-11-22 17:27:12.267505: +2024-11-22 17:27:12.267751: Epoch 5638 +2024-11-22 17:27:12.267868: Current learning rate: 0.00334 +2024-11-22 17:27:30.093171: train_loss -0.806 +2024-11-22 17:27:30.093438: val_loss -0.7273 +2024-11-22 17:27:30.093520: Pseudo dice [0.8469] +2024-11-22 17:27:30.093600: Epoch time: 17.83 s +2024-11-22 17:27:30.985861: +2024-11-22 17:27:30.986082: Epoch 5639 +2024-11-22 17:27:30.986388: Current learning rate: 0.00333 +2024-11-22 17:27:49.840173: train_loss -0.8111 +2024-11-22 17:27:49.840392: val_loss -0.756 +2024-11-22 17:27:49.840472: Pseudo dice [0.8331] +2024-11-22 17:27:49.840555: Epoch time: 18.86 s +2024-11-22 17:27:51.142149: +2024-11-22 17:27:51.142347: Epoch 5640 +2024-11-22 17:27:51.142450: Current learning rate: 0.00333 +2024-11-22 17:28:09.711266: train_loss -0.8022 +2024-11-22 17:28:09.711510: val_loss -0.7558 +2024-11-22 17:28:09.711585: Pseudo dice [0.8449] +2024-11-22 17:28:09.711668: Epoch time: 18.57 s +2024-11-22 17:28:10.624303: +2024-11-22 17:28:10.624523: Epoch 5641 +2024-11-22 17:28:10.624630: Current learning rate: 0.00333 +2024-11-22 17:28:27.999052: train_loss -0.8013 +2024-11-22 17:28:27.999278: val_loss -0.7403 +2024-11-22 17:28:27.999354: Pseudo dice [0.8508] +2024-11-22 17:28:27.999430: Epoch time: 17.38 s +2024-11-22 17:28:28.897713: +2024-11-22 17:28:28.897968: Epoch 5642 +2024-11-22 17:28:28.898083: Current learning rate: 0.00333 +2024-11-22 17:28:48.170421: train_loss -0.797 +2024-11-22 17:28:48.170636: val_loss -0.7588 +2024-11-22 17:28:48.170712: Pseudo dice [0.853] +2024-11-22 17:28:48.170791: Epoch time: 19.27 s +2024-11-22 17:28:49.073348: +2024-11-22 17:28:49.073557: Epoch 5643 +2024-11-22 17:28:49.073667: Current learning rate: 0.00333 +2024-11-22 17:29:07.858122: train_loss -0.8058 +2024-11-22 17:29:07.858352: val_loss -0.7649 +2024-11-22 17:29:07.858428: Pseudo dice [0.8629] +2024-11-22 17:29:07.858511: Epoch time: 18.79 s +2024-11-22 17:29:08.765561: +2024-11-22 17:29:08.765780: Epoch 5644 +2024-11-22 17:29:08.765892: Current learning rate: 0.00333 +2024-11-22 17:29:28.623331: train_loss -0.8032 +2024-11-22 17:29:28.623638: val_loss -0.7588 +2024-11-22 17:29:28.623724: Pseudo dice [0.845] +2024-11-22 17:29:28.623802: Epoch time: 19.86 s +2024-11-22 17:29:29.529366: +2024-11-22 17:29:29.529570: Epoch 5645 +2024-11-22 17:29:29.529685: Current learning rate: 0.00333 +2024-11-22 17:29:48.016344: train_loss -0.8116 +2024-11-22 17:29:48.016591: val_loss -0.7476 +2024-11-22 17:29:48.016716: Pseudo dice [0.8374] +2024-11-22 17:29:48.016797: Epoch time: 18.49 s +2024-11-22 17:29:48.931012: +2024-11-22 17:29:48.931271: Epoch 5646 +2024-11-22 17:29:48.931385: Current learning rate: 0.00333 +2024-11-22 17:30:08.460409: train_loss -0.8071 +2024-11-22 17:30:08.460625: val_loss -0.7657 +2024-11-22 17:30:08.460701: Pseudo dice [0.8401] +2024-11-22 17:30:08.460776: Epoch time: 19.53 s +2024-11-22 17:30:09.365559: +2024-11-22 17:30:09.365812: Epoch 5647 +2024-11-22 17:30:09.365931: Current learning rate: 0.00332 +2024-11-22 17:30:28.398569: train_loss -0.8123 +2024-11-22 17:30:28.398836: val_loss -0.7899 +2024-11-22 17:30:28.398915: Pseudo dice [0.8499] +2024-11-22 17:30:28.399008: Epoch time: 19.03 s +2024-11-22 17:30:29.298224: +2024-11-22 17:30:29.298432: Epoch 5648 +2024-11-22 17:30:29.298548: Current learning rate: 0.00332 +2024-11-22 17:30:48.575415: train_loss -0.8108 +2024-11-22 17:30:48.575635: val_loss -0.7426 +2024-11-22 17:30:48.575710: Pseudo dice [0.8518] +2024-11-22 17:30:48.575786: Epoch time: 19.28 s +2024-11-22 17:30:49.482565: +2024-11-22 17:30:49.482861: Epoch 5649 +2024-11-22 17:30:49.482976: Current learning rate: 0.00332 +2024-11-22 17:31:07.814140: train_loss -0.8084 +2024-11-22 17:31:07.814371: val_loss -0.7653 +2024-11-22 17:31:07.814446: Pseudo dice [0.8386] +2024-11-22 17:31:07.814523: Epoch time: 18.33 s +2024-11-22 17:31:09.018626: +2024-11-22 17:31:09.018829: Epoch 5650 +2024-11-22 17:31:09.018944: Current learning rate: 0.00332 +2024-11-22 17:31:27.811595: train_loss -0.8037 +2024-11-22 17:31:27.811813: val_loss -0.7416 +2024-11-22 17:31:27.811900: Pseudo dice [0.8443] +2024-11-22 17:31:27.811982: Epoch time: 18.79 s +2024-11-22 17:31:28.714951: +2024-11-22 17:31:28.715164: Epoch 5651 +2024-11-22 17:31:28.715279: Current learning rate: 0.00332 +2024-11-22 17:31:47.087716: train_loss -0.8002 +2024-11-22 17:31:47.087972: val_loss -0.7681 +2024-11-22 17:31:47.088060: Pseudo dice [0.8558] +2024-11-22 17:31:47.088136: Epoch time: 18.37 s +2024-11-22 17:31:47.986484: +2024-11-22 17:31:47.986986: Epoch 5652 +2024-11-22 17:31:47.987127: Current learning rate: 0.00332 +2024-11-22 17:32:06.667507: train_loss -0.7973 +2024-11-22 17:32:06.667742: val_loss -0.7021 +2024-11-22 17:32:06.667879: Pseudo dice [0.8375] +2024-11-22 17:32:06.667958: Epoch time: 18.68 s +2024-11-22 17:32:07.562721: +2024-11-22 17:32:07.563223: Epoch 5653 +2024-11-22 17:32:07.563364: Current learning rate: 0.00332 +2024-11-22 17:32:26.990420: train_loss -0.7767 +2024-11-22 17:32:26.990640: val_loss -0.727 +2024-11-22 17:32:26.990719: Pseudo dice [0.8392] +2024-11-22 17:32:26.990797: Epoch time: 19.43 s +2024-11-22 17:32:27.895845: +2024-11-22 17:32:27.896334: Epoch 5654 +2024-11-22 17:32:27.896465: Current learning rate: 0.00332 +2024-11-22 17:32:46.804374: train_loss -0.7914 +2024-11-22 17:32:46.804623: val_loss -0.7432 +2024-11-22 17:32:46.804698: Pseudo dice [0.8466] +2024-11-22 17:32:46.804780: Epoch time: 18.91 s +2024-11-22 17:32:47.706944: +2024-11-22 17:32:47.707373: Epoch 5655 +2024-11-22 17:32:47.707509: Current learning rate: 0.00331 +2024-11-22 17:33:06.679701: train_loss -0.8011 +2024-11-22 17:33:06.679926: val_loss -0.7349 +2024-11-22 17:33:06.680008: Pseudo dice [0.8117] +2024-11-22 17:33:06.680086: Epoch time: 18.97 s +2024-11-22 17:33:07.586635: +2024-11-22 17:33:07.587065: Epoch 5656 +2024-11-22 17:33:07.587204: Current learning rate: 0.00331 +2024-11-22 17:33:26.505710: train_loss -0.7991 +2024-11-22 17:33:26.505925: val_loss -0.7479 +2024-11-22 17:33:26.506010: Pseudo dice [0.8358] +2024-11-22 17:33:26.506087: Epoch time: 18.92 s +2024-11-22 17:33:27.409614: +2024-11-22 17:33:27.410092: Epoch 5657 +2024-11-22 17:33:27.410233: Current learning rate: 0.00331 +2024-11-22 17:33:46.958287: train_loss -0.7939 +2024-11-22 17:33:46.958518: val_loss -0.7569 +2024-11-22 17:33:46.958593: Pseudo dice [0.8578] +2024-11-22 17:33:46.958668: Epoch time: 19.55 s +2024-11-22 17:33:47.856237: +2024-11-22 17:33:47.856642: Epoch 5658 +2024-11-22 17:33:47.856769: Current learning rate: 0.00331 +2024-11-22 17:34:08.115927: train_loss -0.8013 +2024-11-22 17:34:08.116178: val_loss -0.7523 +2024-11-22 17:34:08.116252: Pseudo dice [0.8293] +2024-11-22 17:34:08.116333: Epoch time: 20.26 s +2024-11-22 17:34:09.015932: +2024-11-22 17:34:09.016356: Epoch 5659 +2024-11-22 17:34:09.016492: Current learning rate: 0.00331 +2024-11-22 17:34:27.804612: train_loss -0.8055 +2024-11-22 17:34:27.805699: val_loss -0.7403 +2024-11-22 17:34:27.805790: Pseudo dice [0.8212] +2024-11-22 17:34:27.805870: Epoch time: 18.79 s +2024-11-22 17:34:28.715620: +2024-11-22 17:34:28.716037: Epoch 5660 +2024-11-22 17:34:28.716179: Current learning rate: 0.00331 +2024-11-22 17:34:48.298982: train_loss -0.8007 +2024-11-22 17:34:48.299207: val_loss -0.7432 +2024-11-22 17:34:48.299284: Pseudo dice [0.8268] +2024-11-22 17:34:48.299363: Epoch time: 19.58 s +2024-11-22 17:34:49.195744: +2024-11-22 17:34:49.196189: Epoch 5661 +2024-11-22 17:34:49.196325: Current learning rate: 0.00331 +2024-11-22 17:35:08.428762: train_loss -0.8054 +2024-11-22 17:35:08.429006: val_loss -0.7354 +2024-11-22 17:35:08.429087: Pseudo dice [0.8582] +2024-11-22 17:35:08.429163: Epoch time: 19.23 s +2024-11-22 17:35:09.325409: +2024-11-22 17:35:09.325830: Epoch 5662 +2024-11-22 17:35:09.325959: Current learning rate: 0.00331 +2024-11-22 17:35:27.853671: train_loss -0.8053 +2024-11-22 17:35:27.853926: val_loss -0.7504 +2024-11-22 17:35:27.854008: Pseudo dice [0.8549] +2024-11-22 17:35:27.854090: Epoch time: 18.53 s +2024-11-22 17:35:29.127513: +2024-11-22 17:35:29.127907: Epoch 5663 +2024-11-22 17:35:29.128053: Current learning rate: 0.0033 +2024-11-22 17:35:49.231220: train_loss -0.806 +2024-11-22 17:35:49.231440: val_loss -0.7551 +2024-11-22 17:35:49.231517: Pseudo dice [0.8371] +2024-11-22 17:35:49.231634: Epoch time: 20.1 s +2024-11-22 17:35:50.136959: +2024-11-22 17:35:50.137424: Epoch 5664 +2024-11-22 17:35:50.137554: Current learning rate: 0.0033 +2024-11-22 17:36:08.225790: train_loss -0.8113 +2024-11-22 17:36:08.226029: val_loss -0.7505 +2024-11-22 17:36:08.226113: Pseudo dice [0.8328] +2024-11-22 17:36:08.226193: Epoch time: 18.09 s +2024-11-22 17:36:09.128768: +2024-11-22 17:36:09.129295: Epoch 5665 +2024-11-22 17:36:09.129436: Current learning rate: 0.0033 +2024-11-22 17:36:27.720104: train_loss -0.808 +2024-11-22 17:36:27.720329: val_loss -0.7423 +2024-11-22 17:36:27.720405: Pseudo dice [0.8515] +2024-11-22 17:36:27.720483: Epoch time: 18.59 s +2024-11-22 17:36:28.620710: +2024-11-22 17:36:28.621233: Epoch 5666 +2024-11-22 17:36:28.621369: Current learning rate: 0.0033 +2024-11-22 17:36:46.347328: train_loss -0.8021 +2024-11-22 17:36:46.347627: val_loss -0.7293 +2024-11-22 17:36:46.347706: Pseudo dice [0.835] +2024-11-22 17:36:46.349111: Epoch time: 17.73 s +2024-11-22 17:36:47.252231: +2024-11-22 17:36:47.252640: Epoch 5667 +2024-11-22 17:36:47.252770: Current learning rate: 0.0033 +2024-11-22 17:37:06.380735: train_loss -0.7985 +2024-11-22 17:37:06.380938: val_loss -0.7443 +2024-11-22 17:37:06.381016: Pseudo dice [0.8575] +2024-11-22 17:37:06.381092: Epoch time: 19.13 s +2024-11-22 17:37:07.279389: +2024-11-22 17:37:07.279851: Epoch 5668 +2024-11-22 17:37:07.279997: Current learning rate: 0.0033 +2024-11-22 17:37:26.417886: train_loss -0.8013 +2024-11-22 17:37:26.418184: val_loss -0.7435 +2024-11-22 17:37:26.418259: Pseudo dice [0.8406] +2024-11-22 17:37:26.418341: Epoch time: 19.14 s +2024-11-22 17:37:27.428268: +2024-11-22 17:37:27.428705: Epoch 5669 +2024-11-22 17:37:27.428862: Current learning rate: 0.0033 +2024-11-22 17:37:46.249659: train_loss -0.7932 +2024-11-22 17:37:46.249912: val_loss -0.7531 +2024-11-22 17:37:46.249995: Pseudo dice [0.848] +2024-11-22 17:37:46.250075: Epoch time: 18.82 s +2024-11-22 17:37:47.153319: +2024-11-22 17:37:47.153775: Epoch 5670 +2024-11-22 17:37:47.153917: Current learning rate: 0.00329 +2024-11-22 17:38:07.386134: train_loss -0.8041 +2024-11-22 17:38:07.386373: val_loss -0.7413 +2024-11-22 17:38:07.386447: Pseudo dice [0.8696] +2024-11-22 17:38:07.386525: Epoch time: 20.23 s +2024-11-22 17:38:08.399279: +2024-11-22 17:38:08.399679: Epoch 5671 +2024-11-22 17:38:08.399814: Current learning rate: 0.00329 +2024-11-22 17:38:26.832851: train_loss -0.8004 +2024-11-22 17:38:26.833080: val_loss -0.7372 +2024-11-22 17:38:26.833163: Pseudo dice [0.8507] +2024-11-22 17:38:26.833242: Epoch time: 18.43 s +2024-11-22 17:38:27.733329: +2024-11-22 17:38:27.733750: Epoch 5672 +2024-11-22 17:38:27.733881: Current learning rate: 0.00329 +2024-11-22 17:38:47.106019: train_loss -0.7873 +2024-11-22 17:38:47.106246: val_loss -0.7309 +2024-11-22 17:38:47.106319: Pseudo dice [0.8473] +2024-11-22 17:38:47.106393: Epoch time: 19.37 s +2024-11-22 17:38:48.081490: +2024-11-22 17:38:48.081986: Epoch 5673 +2024-11-22 17:38:48.082131: Current learning rate: 0.00329 +2024-11-22 17:39:06.806378: train_loss -0.7977 +2024-11-22 17:39:06.806599: val_loss -0.7456 +2024-11-22 17:39:06.806678: Pseudo dice [0.8357] +2024-11-22 17:39:06.806760: Epoch time: 18.73 s +2024-11-22 17:39:07.707227: +2024-11-22 17:39:07.707429: Epoch 5674 +2024-11-22 17:39:07.707541: Current learning rate: 0.00329 +2024-11-22 17:39:25.540259: train_loss -0.7885 +2024-11-22 17:39:25.540533: val_loss -0.7389 +2024-11-22 17:39:25.540612: Pseudo dice [0.8446] +2024-11-22 17:39:25.540690: Epoch time: 17.83 s +2024-11-22 17:39:26.445484: +2024-11-22 17:39:26.445937: Epoch 5675 +2024-11-22 17:39:26.446079: Current learning rate: 0.00329 +2024-11-22 17:39:44.660300: train_loss -0.8084 +2024-11-22 17:39:44.660519: val_loss -0.7759 +2024-11-22 17:39:44.660594: Pseudo dice [0.8266] +2024-11-22 17:39:44.660671: Epoch time: 18.22 s +2024-11-22 17:39:45.560766: +2024-11-22 17:39:45.561193: Epoch 5676 +2024-11-22 17:39:45.561321: Current learning rate: 0.00329 +2024-11-22 17:40:05.018571: train_loss -0.8003 +2024-11-22 17:40:05.018868: val_loss -0.7408 +2024-11-22 17:40:05.018945: Pseudo dice [0.8342] +2024-11-22 17:40:05.019033: Epoch time: 19.46 s +2024-11-22 17:40:05.922960: +2024-11-22 17:40:05.923482: Epoch 5677 +2024-11-22 17:40:05.923618: Current learning rate: 0.00329 +2024-11-22 17:40:24.012532: train_loss -0.8046 +2024-11-22 17:40:24.012778: val_loss -0.7391 +2024-11-22 17:40:24.012851: Pseudo dice [0.8309] +2024-11-22 17:40:24.012931: Epoch time: 18.09 s +2024-11-22 17:40:24.988634: +2024-11-22 17:40:24.989063: Epoch 5678 +2024-11-22 17:40:24.989196: Current learning rate: 0.00328 +2024-11-22 17:40:45.568599: train_loss -0.7928 +2024-11-22 17:40:45.568820: val_loss -0.7342 +2024-11-22 17:40:45.574077: Pseudo dice [0.8464] +2024-11-22 17:40:45.574264: Epoch time: 20.58 s +2024-11-22 17:40:46.487559: +2024-11-22 17:40:46.488000: Epoch 5679 +2024-11-22 17:40:46.488131: Current learning rate: 0.00328 +2024-11-22 17:41:05.346182: train_loss -0.8044 +2024-11-22 17:41:05.346410: val_loss -0.7355 +2024-11-22 17:41:05.346485: Pseudo dice [0.8317] +2024-11-22 17:41:05.348799: Epoch time: 18.86 s +2024-11-22 17:41:06.249898: +2024-11-22 17:41:06.250336: Epoch 5680 +2024-11-22 17:41:06.250467: Current learning rate: 0.00328 +2024-11-22 17:41:25.748890: train_loss -0.7925 +2024-11-22 17:41:25.749123: val_loss -0.7426 +2024-11-22 17:41:25.749203: Pseudo dice [0.8518] +2024-11-22 17:41:25.749285: Epoch time: 19.5 s +2024-11-22 17:41:26.650907: +2024-11-22 17:41:26.651322: Epoch 5681 +2024-11-22 17:41:26.651449: Current learning rate: 0.00328 +2024-11-22 17:41:45.664909: train_loss -0.8053 +2024-11-22 17:41:45.665162: val_loss -0.7559 +2024-11-22 17:41:45.665239: Pseudo dice [0.8414] +2024-11-22 17:41:45.665325: Epoch time: 19.01 s +2024-11-22 17:41:46.560266: +2024-11-22 17:41:46.560688: Epoch 5682 +2024-11-22 17:41:46.560822: Current learning rate: 0.00328 +2024-11-22 17:42:04.592697: train_loss -0.7988 +2024-11-22 17:42:04.592926: val_loss -0.7564 +2024-11-22 17:42:04.593014: Pseudo dice [0.8539] +2024-11-22 17:42:04.593094: Epoch time: 18.03 s +2024-11-22 17:42:05.493577: +2024-11-22 17:42:05.494010: Epoch 5683 +2024-11-22 17:42:05.494147: Current learning rate: 0.00328 +2024-11-22 17:42:23.999575: train_loss -0.7974 +2024-11-22 17:42:23.999804: val_loss -0.7618 +2024-11-22 17:42:23.999883: Pseudo dice [0.8677] +2024-11-22 17:42:23.999962: Epoch time: 18.51 s +2024-11-22 17:42:24.906229: +2024-11-22 17:42:24.906664: Epoch 5684 +2024-11-22 17:42:24.906805: Current learning rate: 0.00328 +2024-11-22 17:42:43.904311: train_loss -0.7922 +2024-11-22 17:42:43.904539: val_loss -0.7377 +2024-11-22 17:42:43.904614: Pseudo dice [0.8276] +2024-11-22 17:42:43.904694: Epoch time: 19.0 s +2024-11-22 17:42:44.807347: +2024-11-22 17:42:44.807758: Epoch 5685 +2024-11-22 17:42:44.807888: Current learning rate: 0.00328 +2024-11-22 17:43:03.701516: train_loss -0.809 +2024-11-22 17:43:03.701763: val_loss -0.7705 +2024-11-22 17:43:03.701837: Pseudo dice [0.846] +2024-11-22 17:43:03.701926: Epoch time: 18.89 s +2024-11-22 17:43:05.011173: +2024-11-22 17:43:05.011381: Epoch 5686 +2024-11-22 17:43:05.011518: Current learning rate: 0.00327 +2024-11-22 17:43:23.516771: train_loss -0.8083 +2024-11-22 17:43:23.517004: val_loss -0.764 +2024-11-22 17:43:23.517082: Pseudo dice [0.8376] +2024-11-22 17:43:23.517161: Epoch time: 18.51 s +2024-11-22 17:43:24.410719: +2024-11-22 17:43:24.411036: Epoch 5687 +2024-11-22 17:43:24.411148: Current learning rate: 0.00327 +2024-11-22 17:43:42.780669: train_loss -0.7982 +2024-11-22 17:43:42.780899: val_loss -0.7513 +2024-11-22 17:43:42.780976: Pseudo dice [0.8318] +2024-11-22 17:43:42.781062: Epoch time: 18.37 s +2024-11-22 17:43:43.680243: +2024-11-22 17:43:43.680460: Epoch 5688 +2024-11-22 17:43:43.680575: Current learning rate: 0.00327 +2024-11-22 17:44:01.226516: train_loss -0.8023 +2024-11-22 17:44:01.226764: val_loss -0.7526 +2024-11-22 17:44:01.226840: Pseudo dice [0.8456] +2024-11-22 17:44:01.226923: Epoch time: 17.55 s +2024-11-22 17:44:02.131274: +2024-11-22 17:44:02.131482: Epoch 5689 +2024-11-22 17:44:02.131593: Current learning rate: 0.00327 +2024-11-22 17:44:21.372677: train_loss -0.8043 +2024-11-22 17:44:21.372889: val_loss -0.7514 +2024-11-22 17:44:21.372964: Pseudo dice [0.8354] +2024-11-22 17:44:21.373046: Epoch time: 19.24 s +2024-11-22 17:44:22.272059: +2024-11-22 17:44:22.272330: Epoch 5690 +2024-11-22 17:44:22.272447: Current learning rate: 0.00327 +2024-11-22 17:44:41.086320: train_loss -0.8021 +2024-11-22 17:44:41.086535: val_loss -0.7382 +2024-11-22 17:44:41.086611: Pseudo dice [0.8574] +2024-11-22 17:44:41.086686: Epoch time: 18.82 s +2024-11-22 17:44:41.994943: +2024-11-22 17:44:41.995167: Epoch 5691 +2024-11-22 17:44:41.995281: Current learning rate: 0.00327 +2024-11-22 17:45:01.215244: train_loss -0.8112 +2024-11-22 17:45:01.215466: val_loss -0.768 +2024-11-22 17:45:01.215540: Pseudo dice [0.8565] +2024-11-22 17:45:01.219936: Epoch time: 19.22 s +2024-11-22 17:45:02.188533: +2024-11-22 17:45:02.188742: Epoch 5692 +2024-11-22 17:45:02.188857: Current learning rate: 0.00327 +2024-11-22 17:45:21.140373: train_loss -0.8021 +2024-11-22 17:45:21.140641: val_loss -0.7628 +2024-11-22 17:45:21.140720: Pseudo dice [0.8411] +2024-11-22 17:45:21.140806: Epoch time: 18.95 s +2024-11-22 17:45:22.081222: +2024-11-22 17:45:22.081438: Epoch 5693 +2024-11-22 17:45:22.081552: Current learning rate: 0.00327 +2024-11-22 17:45:41.715718: train_loss -0.8047 +2024-11-22 17:45:41.715989: val_loss -0.7594 +2024-11-22 17:45:41.716073: Pseudo dice [0.8359] +2024-11-22 17:45:41.716150: Epoch time: 19.64 s +2024-11-22 17:45:42.626185: +2024-11-22 17:45:42.626413: Epoch 5694 +2024-11-22 17:45:42.626529: Current learning rate: 0.00326 +2024-11-22 17:46:01.282597: train_loss -0.8107 +2024-11-22 17:46:01.282816: val_loss -0.7813 +2024-11-22 17:46:01.282891: Pseudo dice [0.8549] +2024-11-22 17:46:01.282968: Epoch time: 18.66 s +2024-11-22 17:46:02.178845: +2024-11-22 17:46:02.179057: Epoch 5695 +2024-11-22 17:46:02.179176: Current learning rate: 0.00326 +2024-11-22 17:46:22.637463: train_loss -0.8159 +2024-11-22 17:46:22.637687: val_loss -0.7513 +2024-11-22 17:46:22.637763: Pseudo dice [0.8424] +2024-11-22 17:46:22.637846: Epoch time: 20.46 s +2024-11-22 17:46:23.580160: +2024-11-22 17:46:23.580380: Epoch 5696 +2024-11-22 17:46:23.580490: Current learning rate: 0.00326 +2024-11-22 17:46:42.595884: train_loss -0.8059 +2024-11-22 17:46:42.596139: val_loss -0.7524 +2024-11-22 17:46:42.596217: Pseudo dice [0.8446] +2024-11-22 17:46:42.596304: Epoch time: 19.02 s +2024-11-22 17:46:43.516210: +2024-11-22 17:46:43.516405: Epoch 5697 +2024-11-22 17:46:43.516517: Current learning rate: 0.00326 +2024-11-22 17:47:01.969207: train_loss -0.8044 +2024-11-22 17:47:01.969460: val_loss -0.7577 +2024-11-22 17:47:01.969541: Pseudo dice [0.8601] +2024-11-22 17:47:01.969620: Epoch time: 18.45 s +2024-11-22 17:47:02.870218: +2024-11-22 17:47:02.870500: Epoch 5698 +2024-11-22 17:47:02.870614: Current learning rate: 0.00326 +2024-11-22 17:47:20.288370: train_loss -0.7967 +2024-11-22 17:47:20.288595: val_loss -0.7751 +2024-11-22 17:47:20.288671: Pseudo dice [0.8495] +2024-11-22 17:47:20.288751: Epoch time: 17.42 s +2024-11-22 17:47:21.186389: +2024-11-22 17:47:21.186664: Epoch 5699 +2024-11-22 17:47:21.186773: Current learning rate: 0.00326 +2024-11-22 17:47:40.306672: train_loss -0.8048 +2024-11-22 17:47:40.306951: val_loss -0.7588 +2024-11-22 17:47:40.307033: Pseudo dice [0.8398] +2024-11-22 17:47:40.307119: Epoch time: 19.12 s +2024-11-22 17:47:41.598346: +2024-11-22 17:47:41.598574: Epoch 5700 +2024-11-22 17:47:41.598691: Current learning rate: 0.00326 +2024-11-22 17:48:00.458287: train_loss -0.8058 +2024-11-22 17:48:00.458510: val_loss -0.7313 +2024-11-22 17:48:00.458605: Pseudo dice [0.8511] +2024-11-22 17:48:00.458682: Epoch time: 18.86 s +2024-11-22 17:48:01.366384: +2024-11-22 17:48:01.366592: Epoch 5701 +2024-11-22 17:48:01.366709: Current learning rate: 0.00326 +2024-11-22 17:48:20.514855: train_loss -0.8089 +2024-11-22 17:48:20.515142: val_loss -0.7574 +2024-11-22 17:48:20.515221: Pseudo dice [0.8579] +2024-11-22 17:48:20.515298: Epoch time: 19.15 s +2024-11-22 17:48:21.452866: +2024-11-22 17:48:21.453077: Epoch 5702 +2024-11-22 17:48:21.453217: Current learning rate: 0.00325 +2024-11-22 17:48:40.763246: train_loss -0.8091 +2024-11-22 17:48:40.763528: val_loss -0.7501 +2024-11-22 17:48:40.763603: Pseudo dice [0.8619] +2024-11-22 17:48:40.763680: Epoch time: 19.31 s +2024-11-22 17:48:41.662335: +2024-11-22 17:48:41.662688: Epoch 5703 +2024-11-22 17:48:41.662800: Current learning rate: 0.00325 +2024-11-22 17:49:00.325332: train_loss -0.8102 +2024-11-22 17:49:00.325585: val_loss -0.756 +2024-11-22 17:49:00.325666: Pseudo dice [0.8395] +2024-11-22 17:49:00.325870: Epoch time: 18.66 s +2024-11-22 17:49:01.232037: +2024-11-22 17:49:01.232451: Epoch 5704 +2024-11-22 17:49:01.232611: Current learning rate: 0.00325 +2024-11-22 17:49:19.416803: train_loss -0.808 +2024-11-22 17:49:19.417030: val_loss -0.7746 +2024-11-22 17:49:19.417104: Pseudo dice [0.8399] +2024-11-22 17:49:19.417181: Epoch time: 18.19 s +2024-11-22 17:49:20.424567: +2024-11-22 17:49:20.424773: Epoch 5705 +2024-11-22 17:49:20.424888: Current learning rate: 0.00325 +2024-11-22 17:49:39.747699: train_loss -0.8106 +2024-11-22 17:49:39.747922: val_loss -0.7728 +2024-11-22 17:49:39.748006: Pseudo dice [0.8561] +2024-11-22 17:49:39.748083: Epoch time: 19.32 s +2024-11-22 17:49:40.651348: +2024-11-22 17:49:40.651754: Epoch 5706 +2024-11-22 17:49:40.651871: Current learning rate: 0.00325 +2024-11-22 17:49:59.473197: train_loss -0.8051 +2024-11-22 17:49:59.473418: val_loss -0.7698 +2024-11-22 17:49:59.473492: Pseudo dice [0.8478] +2024-11-22 17:49:59.473578: Epoch time: 18.82 s +2024-11-22 17:50:00.369084: +2024-11-22 17:50:00.369293: Epoch 5707 +2024-11-22 17:50:00.369405: Current learning rate: 0.00325 +2024-11-22 17:50:20.297354: train_loss -0.794 +2024-11-22 17:50:20.297612: val_loss -0.7617 +2024-11-22 17:50:20.297691: Pseudo dice [0.8321] +2024-11-22 17:50:20.297774: Epoch time: 19.93 s +2024-11-22 17:50:21.196161: +2024-11-22 17:50:21.196382: Epoch 5708 +2024-11-22 17:50:21.196494: Current learning rate: 0.00325 +2024-11-22 17:50:40.543188: train_loss -0.7999 +2024-11-22 17:50:40.543416: val_loss -0.7543 +2024-11-22 17:50:40.543492: Pseudo dice [0.8601] +2024-11-22 17:50:40.543574: Epoch time: 19.35 s +2024-11-22 17:50:41.943331: +2024-11-22 17:50:41.943535: Epoch 5709 +2024-11-22 17:50:41.943670: Current learning rate: 0.00325 +2024-11-22 17:51:00.477776: train_loss -0.8045 +2024-11-22 17:51:00.478022: val_loss -0.7623 +2024-11-22 17:51:00.478099: Pseudo dice [0.8599] +2024-11-22 17:51:00.478177: Epoch time: 18.54 s +2024-11-22 17:51:01.394312: +2024-11-22 17:51:01.394631: Epoch 5710 +2024-11-22 17:51:01.394748: Current learning rate: 0.00324 +2024-11-22 17:51:19.387231: train_loss -0.8067 +2024-11-22 17:51:19.387534: val_loss -0.7463 +2024-11-22 17:51:19.387611: Pseudo dice [0.8515] +2024-11-22 17:51:19.387694: Epoch time: 17.99 s +2024-11-22 17:51:20.295761: +2024-11-22 17:51:20.295989: Epoch 5711 +2024-11-22 17:51:20.296105: Current learning rate: 0.00324 +2024-11-22 17:51:38.648764: train_loss -0.7978 +2024-11-22 17:51:38.649029: val_loss -0.7401 +2024-11-22 17:51:38.649107: Pseudo dice [0.825] +2024-11-22 17:51:38.649190: Epoch time: 18.35 s +2024-11-22 17:51:39.558982: +2024-11-22 17:51:39.559226: Epoch 5712 +2024-11-22 17:51:39.559336: Current learning rate: 0.00324 +2024-11-22 17:51:57.108915: train_loss -0.7989 +2024-11-22 17:51:57.109145: val_loss -0.7598 +2024-11-22 17:51:57.109223: Pseudo dice [0.865] +2024-11-22 17:51:57.109302: Epoch time: 17.55 s +2024-11-22 17:51:58.044883: +2024-11-22 17:51:58.045080: Epoch 5713 +2024-11-22 17:51:58.045192: Current learning rate: 0.00324 +2024-11-22 17:52:16.373438: train_loss -0.7983 +2024-11-22 17:52:16.373686: val_loss -0.7685 +2024-11-22 17:52:16.373764: Pseudo dice [0.8535] +2024-11-22 17:52:16.373839: Epoch time: 18.33 s +2024-11-22 17:52:17.274439: +2024-11-22 17:52:17.274657: Epoch 5714 +2024-11-22 17:52:17.274767: Current learning rate: 0.00324 +2024-11-22 17:52:36.229196: train_loss -0.8034 +2024-11-22 17:52:36.229478: val_loss -0.7374 +2024-11-22 17:52:36.229558: Pseudo dice [0.8508] +2024-11-22 17:52:36.229640: Epoch time: 18.96 s +2024-11-22 17:52:37.135023: +2024-11-22 17:52:37.135238: Epoch 5715 +2024-11-22 17:52:37.135353: Current learning rate: 0.00324 +2024-11-22 17:52:55.418200: train_loss -0.8115 +2024-11-22 17:52:55.418432: val_loss -0.7556 +2024-11-22 17:52:55.418508: Pseudo dice [0.8574] +2024-11-22 17:52:55.418588: Epoch time: 18.28 s +2024-11-22 17:52:56.324658: +2024-11-22 17:52:56.324869: Epoch 5716 +2024-11-22 17:52:56.324981: Current learning rate: 0.00324 +2024-11-22 17:53:14.397478: train_loss -0.8065 +2024-11-22 17:53:14.397698: val_loss -0.7377 +2024-11-22 17:53:14.397778: Pseudo dice [0.848] +2024-11-22 17:53:14.397859: Epoch time: 18.07 s +2024-11-22 17:53:15.331000: +2024-11-22 17:53:15.331273: Epoch 5717 +2024-11-22 17:53:15.331387: Current learning rate: 0.00324 +2024-11-22 17:53:33.220349: train_loss -0.7961 +2024-11-22 17:53:33.220571: val_loss -0.7771 +2024-11-22 17:53:33.220643: Pseudo dice [0.8621] +2024-11-22 17:53:33.220718: Epoch time: 17.89 s +2024-11-22 17:53:34.149361: +2024-11-22 17:53:34.149659: Epoch 5718 +2024-11-22 17:53:34.149776: Current learning rate: 0.00323 +2024-11-22 17:53:53.687756: train_loss -0.8083 +2024-11-22 17:53:53.687986: val_loss -0.73 +2024-11-22 17:53:53.688072: Pseudo dice [0.8474] +2024-11-22 17:53:53.688151: Epoch time: 19.54 s +2024-11-22 17:53:54.600973: +2024-11-22 17:53:54.601185: Epoch 5719 +2024-11-22 17:53:54.601298: Current learning rate: 0.00323 +2024-11-22 17:54:13.184098: train_loss -0.8072 +2024-11-22 17:54:13.184345: val_loss -0.7641 +2024-11-22 17:54:13.184419: Pseudo dice [0.8278] +2024-11-22 17:54:13.184496: Epoch time: 18.58 s +2024-11-22 17:54:14.090930: +2024-11-22 17:54:14.091188: Epoch 5720 +2024-11-22 17:54:14.091306: Current learning rate: 0.00323 +2024-11-22 17:54:32.570324: train_loss -0.8113 +2024-11-22 17:54:32.570597: val_loss -0.7458 +2024-11-22 17:54:32.570684: Pseudo dice [0.8605] +2024-11-22 17:54:32.570765: Epoch time: 18.48 s +2024-11-22 17:54:33.468323: +2024-11-22 17:54:33.468614: Epoch 5721 +2024-11-22 17:54:33.468730: Current learning rate: 0.00323 +2024-11-22 17:54:52.653519: train_loss -0.799 +2024-11-22 17:54:52.653749: val_loss -0.766 +2024-11-22 17:54:52.653825: Pseudo dice [0.8549] +2024-11-22 17:54:52.653902: Epoch time: 19.19 s +2024-11-22 17:54:53.669407: +2024-11-22 17:54:53.669622: Epoch 5722 +2024-11-22 17:54:53.669735: Current learning rate: 0.00323 +2024-11-22 17:55:12.653887: train_loss -0.7969 +2024-11-22 17:55:12.654197: val_loss -0.7552 +2024-11-22 17:55:12.654272: Pseudo dice [0.8645] +2024-11-22 17:55:12.654358: Epoch time: 18.99 s +2024-11-22 17:55:13.681046: +2024-11-22 17:55:13.681254: Epoch 5723 +2024-11-22 17:55:13.681368: Current learning rate: 0.00323 +2024-11-22 17:55:31.863519: train_loss -0.8076 +2024-11-22 17:55:31.863749: val_loss -0.7645 +2024-11-22 17:55:31.863822: Pseudo dice [0.8568] +2024-11-22 17:55:31.863901: Epoch time: 18.18 s +2024-11-22 17:55:32.793820: +2024-11-22 17:55:32.794099: Epoch 5724 +2024-11-22 17:55:32.794218: Current learning rate: 0.00323 +2024-11-22 17:55:51.571537: train_loss -0.8054 +2024-11-22 17:55:51.571749: val_loss -0.7363 +2024-11-22 17:55:51.571824: Pseudo dice [0.8702] +2024-11-22 17:55:51.571906: Epoch time: 18.78 s +2024-11-22 17:55:52.475619: +2024-11-22 17:55:52.475829: Epoch 5725 +2024-11-22 17:55:52.475942: Current learning rate: 0.00322 +2024-11-22 17:56:10.695586: train_loss -0.8108 +2024-11-22 17:56:10.695810: val_loss -0.7512 +2024-11-22 17:56:10.701056: Pseudo dice [0.8165] +2024-11-22 17:56:10.701169: Epoch time: 18.22 s +2024-11-22 17:56:11.628435: +2024-11-22 17:56:11.628648: Epoch 5726 +2024-11-22 17:56:11.628762: Current learning rate: 0.00322 +2024-11-22 17:56:29.414594: train_loss -0.8104 +2024-11-22 17:56:29.414810: val_loss -0.7578 +2024-11-22 17:56:29.414885: Pseudo dice [0.8308] +2024-11-22 17:56:29.414966: Epoch time: 17.79 s +2024-11-22 17:56:30.326485: +2024-11-22 17:56:30.326710: Epoch 5727 +2024-11-22 17:56:30.326859: Current learning rate: 0.00322 +2024-11-22 17:56:49.681769: train_loss -0.8039 +2024-11-22 17:56:49.682074: val_loss -0.7525 +2024-11-22 17:56:49.682154: Pseudo dice [0.8495] +2024-11-22 17:56:49.682236: Epoch time: 19.36 s +2024-11-22 17:56:50.718397: +2024-11-22 17:56:50.718666: Epoch 5728 +2024-11-22 17:56:50.718784: Current learning rate: 0.00322 +2024-11-22 17:57:08.813463: train_loss -0.7983 +2024-11-22 17:57:08.813679: val_loss -0.7209 +2024-11-22 17:57:08.813765: Pseudo dice [0.8477] +2024-11-22 17:57:08.813841: Epoch time: 18.1 s +2024-11-22 17:57:09.760074: +2024-11-22 17:57:09.760270: Epoch 5729 +2024-11-22 17:57:09.760379: Current learning rate: 0.00322 +2024-11-22 17:57:27.924150: train_loss -0.8067 +2024-11-22 17:57:27.926499: val_loss -0.7533 +2024-11-22 17:57:27.928439: Pseudo dice [0.8349] +2024-11-22 17:57:27.928555: Epoch time: 18.16 s +2024-11-22 17:57:28.932611: +2024-11-22 17:57:28.932821: Epoch 5730 +2024-11-22 17:57:28.932934: Current learning rate: 0.00322 +2024-11-22 17:57:48.450071: train_loss -0.8045 +2024-11-22 17:57:48.450322: val_loss -0.7503 +2024-11-22 17:57:48.450399: Pseudo dice [0.8544] +2024-11-22 17:57:48.450492: Epoch time: 19.52 s +2024-11-22 17:57:49.366819: +2024-11-22 17:57:49.367075: Epoch 5731 +2024-11-22 17:57:49.367189: Current learning rate: 0.00322 +2024-11-22 17:58:08.358528: train_loss -0.8052 +2024-11-22 17:58:08.358749: val_loss -0.7348 +2024-11-22 17:58:08.358824: Pseudo dice [0.8335] +2024-11-22 17:58:08.358902: Epoch time: 18.99 s +2024-11-22 17:58:09.746943: +2024-11-22 17:58:09.747195: Epoch 5732 +2024-11-22 17:58:09.747319: Current learning rate: 0.00322 +2024-11-22 17:58:28.026522: train_loss -0.8126 +2024-11-22 17:58:28.026743: val_loss -0.7506 +2024-11-22 17:58:28.026824: Pseudo dice [0.8572] +2024-11-22 17:58:28.026910: Epoch time: 18.28 s +2024-11-22 17:58:28.931502: +2024-11-22 17:58:28.931727: Epoch 5733 +2024-11-22 17:58:28.931842: Current learning rate: 0.00321 +2024-11-22 17:58:46.952703: train_loss -0.8144 +2024-11-22 17:58:46.952959: val_loss -0.761 +2024-11-22 17:58:46.953075: Pseudo dice [0.8541] +2024-11-22 17:58:46.953155: Epoch time: 18.02 s +2024-11-22 17:58:48.004610: +2024-11-22 17:58:48.004872: Epoch 5734 +2024-11-22 17:58:48.004990: Current learning rate: 0.00321 +2024-11-22 17:59:07.095280: train_loss -0.8097 +2024-11-22 17:59:07.095550: val_loss -0.7523 +2024-11-22 17:59:07.095627: Pseudo dice [0.8531] +2024-11-22 17:59:07.095710: Epoch time: 19.09 s +2024-11-22 17:59:08.001772: +2024-11-22 17:59:08.001976: Epoch 5735 +2024-11-22 17:59:08.002097: Current learning rate: 0.00321 +2024-11-22 17:59:26.986742: train_loss -0.8059 +2024-11-22 17:59:26.986956: val_loss -0.786 +2024-11-22 17:59:26.987034: Pseudo dice [0.8566] +2024-11-22 17:59:26.987110: Epoch time: 18.99 s +2024-11-22 17:59:27.899017: +2024-11-22 17:59:27.899307: Epoch 5736 +2024-11-22 17:59:27.899420: Current learning rate: 0.00321 +2024-11-22 17:59:46.558039: train_loss -0.8032 +2024-11-22 17:59:46.558259: val_loss -0.754 +2024-11-22 17:59:46.558338: Pseudo dice [0.8613] +2024-11-22 17:59:46.558416: Epoch time: 18.66 s +2024-11-22 17:59:47.459589: +2024-11-22 17:59:47.459800: Epoch 5737 +2024-11-22 17:59:47.459911: Current learning rate: 0.00321 +2024-11-22 18:00:06.895810: train_loss -0.7966 +2024-11-22 18:00:06.896042: val_loss -0.7357 +2024-11-22 18:00:06.896120: Pseudo dice [0.8272] +2024-11-22 18:00:06.896198: Epoch time: 19.44 s +2024-11-22 18:00:07.814518: +2024-11-22 18:00:07.814741: Epoch 5738 +2024-11-22 18:00:07.814860: Current learning rate: 0.00321 +2024-11-22 18:00:27.779809: train_loss -0.7985 +2024-11-22 18:00:27.780061: val_loss -0.7672 +2024-11-22 18:00:27.780136: Pseudo dice [0.8262] +2024-11-22 18:00:27.780220: Epoch time: 19.97 s +2024-11-22 18:00:28.699449: +2024-11-22 18:00:28.699703: Epoch 5739 +2024-11-22 18:00:28.699815: Current learning rate: 0.00321 +2024-11-22 18:00:47.014308: train_loss -0.804 +2024-11-22 18:00:47.014523: val_loss -0.7219 +2024-11-22 18:00:47.014596: Pseudo dice [0.8174] +2024-11-22 18:00:47.014672: Epoch time: 18.32 s +2024-11-22 18:00:47.926909: +2024-11-22 18:00:47.927220: Epoch 5740 +2024-11-22 18:00:47.927332: Current learning rate: 0.00321 +2024-11-22 18:01:06.062635: train_loss -0.8054 +2024-11-22 18:01:06.062869: val_loss -0.7314 +2024-11-22 18:01:06.062946: Pseudo dice [0.846] +2024-11-22 18:01:06.063090: Epoch time: 18.14 s +2024-11-22 18:01:07.072317: +2024-11-22 18:01:07.072537: Epoch 5741 +2024-11-22 18:01:07.072657: Current learning rate: 0.0032 +2024-11-22 18:01:26.324164: train_loss -0.7948 +2024-11-22 18:01:26.324384: val_loss -0.7863 +2024-11-22 18:01:26.324456: Pseudo dice [0.8614] +2024-11-22 18:01:26.324533: Epoch time: 19.25 s +2024-11-22 18:01:27.444189: +2024-11-22 18:01:27.444517: Epoch 5742 +2024-11-22 18:01:27.444632: Current learning rate: 0.0032 +2024-11-22 18:01:45.475466: train_loss -0.8087 +2024-11-22 18:01:45.475721: val_loss -0.7528 +2024-11-22 18:01:45.475800: Pseudo dice [0.8467] +2024-11-22 18:01:45.476144: Epoch time: 18.03 s +2024-11-22 18:01:46.385088: +2024-11-22 18:01:46.385306: Epoch 5743 +2024-11-22 18:01:46.385416: Current learning rate: 0.0032 +2024-11-22 18:02:04.516896: train_loss -0.807 +2024-11-22 18:02:04.522354: val_loss -0.7507 +2024-11-22 18:02:04.522496: Pseudo dice [0.8655] +2024-11-22 18:02:04.522576: Epoch time: 18.13 s +2024-11-22 18:02:05.475008: +2024-11-22 18:02:05.475234: Epoch 5744 +2024-11-22 18:02:05.475353: Current learning rate: 0.0032 +2024-11-22 18:02:24.085203: train_loss -0.8095 +2024-11-22 18:02:24.085457: val_loss -0.7721 +2024-11-22 18:02:24.085585: Pseudo dice [0.8613] +2024-11-22 18:02:24.085668: Epoch time: 18.61 s +2024-11-22 18:02:24.994137: +2024-11-22 18:02:24.994393: Epoch 5745 +2024-11-22 18:02:24.994505: Current learning rate: 0.0032 +2024-11-22 18:02:42.985374: train_loss -0.7996 +2024-11-22 18:02:42.985608: val_loss -0.7556 +2024-11-22 18:02:42.985684: Pseudo dice [0.8229] +2024-11-22 18:02:42.985773: Epoch time: 17.99 s +2024-11-22 18:02:43.903236: +2024-11-22 18:02:43.903480: Epoch 5746 +2024-11-22 18:02:43.903595: Current learning rate: 0.0032 +2024-11-22 18:03:02.383358: train_loss -0.7945 +2024-11-22 18:03:02.383589: val_loss -0.7427 +2024-11-22 18:03:02.383666: Pseudo dice [0.8714] +2024-11-22 18:03:02.383747: Epoch time: 18.48 s +2024-11-22 18:03:03.292592: +2024-11-22 18:03:03.292873: Epoch 5747 +2024-11-22 18:03:03.292987: Current learning rate: 0.0032 +2024-11-22 18:03:22.779004: train_loss -0.8059 +2024-11-22 18:03:22.779223: val_loss -0.7782 +2024-11-22 18:03:22.779300: Pseudo dice [0.8499] +2024-11-22 18:03:22.779382: Epoch time: 19.49 s +2024-11-22 18:03:23.814842: +2024-11-22 18:03:23.815094: Epoch 5748 +2024-11-22 18:03:23.815209: Current learning rate: 0.0032 +2024-11-22 18:03:42.089261: train_loss -0.7982 +2024-11-22 18:03:42.089485: val_loss -0.7389 +2024-11-22 18:03:42.089562: Pseudo dice [0.869] +2024-11-22 18:03:42.089641: Epoch time: 18.28 s +2024-11-22 18:03:42.991627: +2024-11-22 18:03:42.991828: Epoch 5749 +2024-11-22 18:03:42.991940: Current learning rate: 0.00319 +2024-11-22 18:04:01.792539: train_loss -0.8066 +2024-11-22 18:04:01.797932: val_loss -0.7615 +2024-11-22 18:04:01.798052: Pseudo dice [0.8489] +2024-11-22 18:04:01.798141: Epoch time: 18.8 s +2024-11-22 18:04:03.184709: +2024-11-22 18:04:03.184927: Epoch 5750 +2024-11-22 18:04:03.185046: Current learning rate: 0.00319 +2024-11-22 18:04:21.656372: train_loss -0.8103 +2024-11-22 18:04:21.656615: val_loss -0.7417 +2024-11-22 18:04:21.656691: Pseudo dice [0.8435] +2024-11-22 18:04:21.656772: Epoch time: 18.47 s +2024-11-22 18:04:22.556556: +2024-11-22 18:04:22.556763: Epoch 5751 +2024-11-22 18:04:22.556874: Current learning rate: 0.00319 +2024-11-22 18:04:40.942684: train_loss -0.808 +2024-11-22 18:04:40.942915: val_loss -0.7689 +2024-11-22 18:04:40.947425: Pseudo dice [0.8412] +2024-11-22 18:04:40.947571: Epoch time: 18.39 s +2024-11-22 18:04:41.856027: +2024-11-22 18:04:41.856214: Epoch 5752 +2024-11-22 18:04:41.856351: Current learning rate: 0.00319 +2024-11-22 18:05:00.386932: train_loss -0.8105 +2024-11-22 18:05:00.387167: val_loss -0.7665 +2024-11-22 18:05:00.392440: Pseudo dice [0.8485] +2024-11-22 18:05:00.392549: Epoch time: 18.53 s +2024-11-22 18:05:01.397604: +2024-11-22 18:05:01.397805: Epoch 5753 +2024-11-22 18:05:01.397917: Current learning rate: 0.00319 +2024-11-22 18:05:19.772373: train_loss -0.8125 +2024-11-22 18:05:19.772600: val_loss -0.7702 +2024-11-22 18:05:19.772685: Pseudo dice [0.8375] +2024-11-22 18:05:19.772773: Epoch time: 18.38 s +2024-11-22 18:05:20.690269: +2024-11-22 18:05:20.690505: Epoch 5754 +2024-11-22 18:05:20.690621: Current learning rate: 0.00319 +2024-11-22 18:05:39.929111: train_loss -0.8074 +2024-11-22 18:05:39.929353: val_loss -0.7225 +2024-11-22 18:05:39.929435: Pseudo dice [0.8443] +2024-11-22 18:05:39.929513: Epoch time: 19.24 s +2024-11-22 18:05:40.831068: +2024-11-22 18:05:40.831299: Epoch 5755 +2024-11-22 18:05:40.831420: Current learning rate: 0.00319 +2024-11-22 18:05:59.157643: train_loss -0.7933 +2024-11-22 18:05:59.157854: val_loss -0.7362 +2024-11-22 18:05:59.157932: Pseudo dice [0.8482] +2024-11-22 18:05:59.158014: Epoch time: 18.33 s +2024-11-22 18:06:00.126188: +2024-11-22 18:06:00.126401: Epoch 5756 +2024-11-22 18:06:00.126516: Current learning rate: 0.00319 +2024-11-22 18:06:18.901008: train_loss -0.798 +2024-11-22 18:06:18.901235: val_loss -0.7554 +2024-11-22 18:06:18.901314: Pseudo dice [0.8474] +2024-11-22 18:06:18.901394: Epoch time: 18.78 s +2024-11-22 18:06:19.808196: +2024-11-22 18:06:19.808409: Epoch 5757 +2024-11-22 18:06:19.808522: Current learning rate: 0.00318 +2024-11-22 18:06:38.597772: train_loss -0.7999 +2024-11-22 18:06:38.598013: val_loss -0.7372 +2024-11-22 18:06:38.598087: Pseudo dice [0.8342] +2024-11-22 18:06:38.598170: Epoch time: 18.79 s +2024-11-22 18:06:39.501769: +2024-11-22 18:06:39.501985: Epoch 5758 +2024-11-22 18:06:39.502108: Current learning rate: 0.00318 +2024-11-22 18:06:57.634207: train_loss -0.8065 +2024-11-22 18:06:57.634425: val_loss -0.7677 +2024-11-22 18:06:57.634502: Pseudo dice [0.8538] +2024-11-22 18:06:57.634579: Epoch time: 18.13 s +2024-11-22 18:06:58.529126: +2024-11-22 18:06:58.529331: Epoch 5759 +2024-11-22 18:06:58.529444: Current learning rate: 0.00318 +2024-11-22 18:07:16.922420: train_loss -0.8044 +2024-11-22 18:07:16.922639: val_loss -0.7556 +2024-11-22 18:07:16.922712: Pseudo dice [0.859] +2024-11-22 18:07:16.922788: Epoch time: 18.39 s +2024-11-22 18:07:17.828910: +2024-11-22 18:07:17.829118: Epoch 5760 +2024-11-22 18:07:17.829228: Current learning rate: 0.00318 +2024-11-22 18:07:35.369741: train_loss -0.8073 +2024-11-22 18:07:35.369953: val_loss -0.7499 +2024-11-22 18:07:35.370042: Pseudo dice [0.8409] +2024-11-22 18:07:35.370119: Epoch time: 17.54 s +2024-11-22 18:07:36.283634: +2024-11-22 18:07:36.283839: Epoch 5761 +2024-11-22 18:07:36.283951: Current learning rate: 0.00318 +2024-11-22 18:07:53.915813: train_loss -0.8065 +2024-11-22 18:07:53.916065: val_loss -0.7627 +2024-11-22 18:07:53.916142: Pseudo dice [0.857] +2024-11-22 18:07:53.916227: Epoch time: 17.63 s +2024-11-22 18:07:54.822420: +2024-11-22 18:07:54.822804: Epoch 5762 +2024-11-22 18:07:54.822920: Current learning rate: 0.00318 +2024-11-22 18:08:14.641147: train_loss -0.8066 +2024-11-22 18:08:14.641393: val_loss -0.759 +2024-11-22 18:08:14.641481: Pseudo dice [0.8461] +2024-11-22 18:08:14.641558: Epoch time: 19.82 s +2024-11-22 18:08:15.658831: +2024-11-22 18:08:15.659024: Epoch 5763 +2024-11-22 18:08:15.659137: Current learning rate: 0.00318 +2024-11-22 18:08:33.797952: train_loss -0.8073 +2024-11-22 18:08:33.798179: val_loss -0.7681 +2024-11-22 18:08:33.798280: Pseudo dice [0.8589] +2024-11-22 18:08:33.798360: Epoch time: 18.14 s +2024-11-22 18:08:34.702479: +2024-11-22 18:08:34.702681: Epoch 5764 +2024-11-22 18:08:34.702791: Current learning rate: 0.00317 +2024-11-22 18:08:53.775871: train_loss -0.8066 +2024-11-22 18:08:53.776159: val_loss -0.7705 +2024-11-22 18:08:53.776236: Pseudo dice [0.8441] +2024-11-22 18:08:53.776315: Epoch time: 19.07 s +2024-11-22 18:08:54.681441: +2024-11-22 18:08:54.681663: Epoch 5765 +2024-11-22 18:08:54.681777: Current learning rate: 0.00317 +2024-11-22 18:09:13.784683: train_loss -0.8029 +2024-11-22 18:09:13.784937: val_loss -0.7477 +2024-11-22 18:09:13.785020: Pseudo dice [0.8531] +2024-11-22 18:09:13.785103: Epoch time: 19.1 s +2024-11-22 18:09:15.108130: +2024-11-22 18:09:15.108357: Epoch 5766 +2024-11-22 18:09:15.108470: Current learning rate: 0.00317 +2024-11-22 18:09:34.659046: train_loss -0.8056 +2024-11-22 18:09:34.659268: val_loss -0.7323 +2024-11-22 18:09:34.659344: Pseudo dice [0.8471] +2024-11-22 18:09:34.659419: Epoch time: 19.55 s +2024-11-22 18:09:35.576115: +2024-11-22 18:09:35.576324: Epoch 5767 +2024-11-22 18:09:35.576436: Current learning rate: 0.00317 +2024-11-22 18:09:55.135668: train_loss -0.8036 +2024-11-22 18:09:55.135896: val_loss -0.7357 +2024-11-22 18:09:55.135972: Pseudo dice [0.8179] +2024-11-22 18:09:55.136054: Epoch time: 19.56 s +2024-11-22 18:09:56.026930: +2024-11-22 18:09:56.027193: Epoch 5768 +2024-11-22 18:09:56.027311: Current learning rate: 0.00317 +2024-11-22 18:10:14.652965: train_loss -0.8096 +2024-11-22 18:10:14.653191: val_loss -0.7574 +2024-11-22 18:10:14.653266: Pseudo dice [0.8282] +2024-11-22 18:10:14.653602: Epoch time: 18.63 s +2024-11-22 18:10:15.576819: +2024-11-22 18:10:15.577093: Epoch 5769 +2024-11-22 18:10:15.577253: Current learning rate: 0.00317 +2024-11-22 18:10:35.174463: train_loss -0.8081 +2024-11-22 18:10:35.174681: val_loss -0.7356 +2024-11-22 18:10:35.174753: Pseudo dice [0.8541] +2024-11-22 18:10:35.174901: Epoch time: 19.6 s +2024-11-22 18:10:36.108231: +2024-11-22 18:10:36.108443: Epoch 5770 +2024-11-22 18:10:36.108554: Current learning rate: 0.00317 +2024-11-22 18:10:54.386703: train_loss -0.8144 +2024-11-22 18:10:54.386929: val_loss -0.7372 +2024-11-22 18:10:54.387017: Pseudo dice [0.8697] +2024-11-22 18:10:54.387093: Epoch time: 18.28 s +2024-11-22 18:10:55.305758: +2024-11-22 18:10:55.305948: Epoch 5771 +2024-11-22 18:10:55.306067: Current learning rate: 0.00317 +2024-11-22 18:11:15.080506: train_loss -0.8022 +2024-11-22 18:11:15.080739: val_loss -0.7702 +2024-11-22 18:11:15.080819: Pseudo dice [0.8483] +2024-11-22 18:11:15.080901: Epoch time: 19.78 s +2024-11-22 18:11:15.990580: +2024-11-22 18:11:15.990782: Epoch 5772 +2024-11-22 18:11:15.990887: Current learning rate: 0.00316 +2024-11-22 18:11:33.963638: train_loss -0.8044 +2024-11-22 18:11:33.963868: val_loss -0.7434 +2024-11-22 18:11:33.966161: Pseudo dice [0.8231] +2024-11-22 18:11:33.966257: Epoch time: 17.97 s +2024-11-22 18:11:34.927417: +2024-11-22 18:11:34.927657: Epoch 5773 +2024-11-22 18:11:34.927764: Current learning rate: 0.00316 +2024-11-22 18:11:53.488227: train_loss -0.807 +2024-11-22 18:11:53.488474: val_loss -0.7618 +2024-11-22 18:11:53.488550: Pseudo dice [0.8295] +2024-11-22 18:11:53.488631: Epoch time: 18.56 s +2024-11-22 18:11:54.446413: +2024-11-22 18:11:54.446638: Epoch 5774 +2024-11-22 18:11:54.446762: Current learning rate: 0.00316 +2024-11-22 18:12:12.536497: train_loss -0.8038 +2024-11-22 18:12:12.536715: val_loss -0.7606 +2024-11-22 18:12:12.536796: Pseudo dice [0.8612] +2024-11-22 18:12:12.536876: Epoch time: 18.09 s +2024-11-22 18:12:13.447780: +2024-11-22 18:12:13.448031: Epoch 5775 +2024-11-22 18:12:13.448144: Current learning rate: 0.00316 +2024-11-22 18:12:31.145118: train_loss -0.8085 +2024-11-22 18:12:31.145351: val_loss -0.7495 +2024-11-22 18:12:31.145432: Pseudo dice [0.8439] +2024-11-22 18:12:31.145508: Epoch time: 17.7 s +2024-11-22 18:12:32.055455: +2024-11-22 18:12:32.055678: Epoch 5776 +2024-11-22 18:12:32.055796: Current learning rate: 0.00316 +2024-11-22 18:12:50.939826: train_loss -0.8137 +2024-11-22 18:12:50.940058: val_loss -0.7611 +2024-11-22 18:12:50.940150: Pseudo dice [0.8506] +2024-11-22 18:12:50.940288: Epoch time: 18.89 s +2024-11-22 18:12:51.849260: +2024-11-22 18:12:51.849473: Epoch 5777 +2024-11-22 18:12:51.849585: Current learning rate: 0.00316 +2024-11-22 18:13:10.455983: train_loss -0.8142 +2024-11-22 18:13:10.456337: val_loss -0.7443 +2024-11-22 18:13:10.456420: Pseudo dice [0.8339] +2024-11-22 18:13:10.456502: Epoch time: 18.61 s +2024-11-22 18:13:11.371684: +2024-11-22 18:13:11.371895: Epoch 5778 +2024-11-22 18:13:11.372018: Current learning rate: 0.00316 +2024-11-22 18:13:31.645916: train_loss -0.8105 +2024-11-22 18:13:31.646150: val_loss -0.7614 +2024-11-22 18:13:31.646234: Pseudo dice [0.8534] +2024-11-22 18:13:31.646321: Epoch time: 20.28 s +2024-11-22 18:13:32.547268: +2024-11-22 18:13:32.547477: Epoch 5779 +2024-11-22 18:13:32.547591: Current learning rate: 0.00316 +2024-11-22 18:13:51.766937: train_loss -0.8054 +2024-11-22 18:13:51.767164: val_loss -0.736 +2024-11-22 18:13:51.767241: Pseudo dice [0.8193] +2024-11-22 18:13:51.767321: Epoch time: 19.22 s +2024-11-22 18:13:52.677712: +2024-11-22 18:13:52.677947: Epoch 5780 +2024-11-22 18:13:52.678067: Current learning rate: 0.00315 +2024-11-22 18:14:11.189813: train_loss -0.8083 +2024-11-22 18:14:11.190098: val_loss -0.7443 +2024-11-22 18:14:11.190227: Pseudo dice [0.8421] +2024-11-22 18:14:11.190316: Epoch time: 18.51 s +2024-11-22 18:14:12.197502: +2024-11-22 18:14:12.197722: Epoch 5781 +2024-11-22 18:14:12.197845: Current learning rate: 0.00315 +2024-11-22 18:14:31.373476: train_loss -0.8062 +2024-11-22 18:14:31.373692: val_loss -0.727 +2024-11-22 18:14:31.373766: Pseudo dice [0.8514] +2024-11-22 18:14:31.373841: Epoch time: 19.18 s +2024-11-22 18:14:32.280115: +2024-11-22 18:14:32.280333: Epoch 5782 +2024-11-22 18:14:32.280448: Current learning rate: 0.00315 +2024-11-22 18:14:51.684614: train_loss -0.8032 +2024-11-22 18:14:51.684834: val_loss -0.7215 +2024-11-22 18:14:51.684914: Pseudo dice [0.8292] +2024-11-22 18:14:51.687195: Epoch time: 19.41 s +2024-11-22 18:14:52.881147: +2024-11-22 18:14:52.881377: Epoch 5783 +2024-11-22 18:14:52.881500: Current learning rate: 0.00315 +2024-11-22 18:15:12.124507: train_loss -0.8065 +2024-11-22 18:15:12.129911: val_loss -0.769 +2024-11-22 18:15:12.130004: Pseudo dice [0.8605] +2024-11-22 18:15:12.130083: Epoch time: 19.24 s +2024-11-22 18:15:13.298140: +2024-11-22 18:15:13.298331: Epoch 5784 +2024-11-22 18:15:13.298443: Current learning rate: 0.00315 +2024-11-22 18:15:32.117588: train_loss -0.8037 +2024-11-22 18:15:32.117841: val_loss -0.7639 +2024-11-22 18:15:32.117916: Pseudo dice [0.8572] +2024-11-22 18:15:32.118005: Epoch time: 18.82 s +2024-11-22 18:15:33.123238: +2024-11-22 18:15:33.123507: Epoch 5785 +2024-11-22 18:15:33.123623: Current learning rate: 0.00315 +2024-11-22 18:15:52.293384: train_loss -0.8024 +2024-11-22 18:15:52.293636: val_loss -0.7368 +2024-11-22 18:15:52.293719: Pseudo dice [0.854] +2024-11-22 18:15:52.293793: Epoch time: 19.17 s +2024-11-22 18:15:53.204865: +2024-11-22 18:15:53.205075: Epoch 5786 +2024-11-22 18:15:53.205186: Current learning rate: 0.00315 +2024-11-22 18:16:11.840434: train_loss -0.7918 +2024-11-22 18:16:11.840652: val_loss -0.7659 +2024-11-22 18:16:11.840727: Pseudo dice [0.8108] +2024-11-22 18:16:11.840803: Epoch time: 18.64 s +2024-11-22 18:16:12.744809: +2024-11-22 18:16:12.745081: Epoch 5787 +2024-11-22 18:16:12.745198: Current learning rate: 0.00315 +2024-11-22 18:16:31.836883: train_loss -0.8111 +2024-11-22 18:16:31.837116: val_loss -0.7431 +2024-11-22 18:16:31.837197: Pseudo dice [0.8565] +2024-11-22 18:16:31.837285: Epoch time: 19.09 s +2024-11-22 18:16:32.748955: +2024-11-22 18:16:32.749164: Epoch 5788 +2024-11-22 18:16:32.749282: Current learning rate: 0.00314 +2024-11-22 18:16:51.341001: train_loss -0.8046 +2024-11-22 18:16:51.341251: val_loss -0.7235 +2024-11-22 18:16:51.341331: Pseudo dice [0.86] +2024-11-22 18:16:51.341414: Epoch time: 18.59 s +2024-11-22 18:16:52.661592: +2024-11-22 18:16:52.661801: Epoch 5789 +2024-11-22 18:16:52.661911: Current learning rate: 0.00314 +2024-11-22 18:17:10.312407: train_loss -0.809 +2024-11-22 18:17:10.312642: val_loss -0.7512 +2024-11-22 18:17:10.312726: Pseudo dice [0.8385] +2024-11-22 18:17:10.312816: Epoch time: 17.65 s +2024-11-22 18:17:11.396062: +2024-11-22 18:17:11.396269: Epoch 5790 +2024-11-22 18:17:11.396391: Current learning rate: 0.00314 +2024-11-22 18:17:30.672676: train_loss -0.8057 +2024-11-22 18:17:30.672897: val_loss -0.7426 +2024-11-22 18:17:30.672971: Pseudo dice [0.8343] +2024-11-22 18:17:30.673052: Epoch time: 19.28 s +2024-11-22 18:17:31.582271: +2024-11-22 18:17:31.582496: Epoch 5791 +2024-11-22 18:17:31.582610: Current learning rate: 0.00314 +2024-11-22 18:17:50.694659: train_loss -0.8055 +2024-11-22 18:17:50.694917: val_loss -0.7528 +2024-11-22 18:17:50.694999: Pseudo dice [0.8292] +2024-11-22 18:17:50.695088: Epoch time: 19.11 s +2024-11-22 18:17:51.636502: +2024-11-22 18:17:51.636752: Epoch 5792 +2024-11-22 18:17:51.636869: Current learning rate: 0.00314 +2024-11-22 18:18:11.577192: train_loss -0.8085 +2024-11-22 18:18:11.577412: val_loss -0.7768 +2024-11-22 18:18:11.579006: Pseudo dice [0.8565] +2024-11-22 18:18:11.579102: Epoch time: 19.94 s +2024-11-22 18:18:12.589437: +2024-11-22 18:18:12.589659: Epoch 5793 +2024-11-22 18:18:12.589773: Current learning rate: 0.00314 +2024-11-22 18:18:31.365116: train_loss -0.8103 +2024-11-22 18:18:31.365343: val_loss -0.7408 +2024-11-22 18:18:31.365422: Pseudo dice [0.8504] +2024-11-22 18:18:31.365509: Epoch time: 18.78 s +2024-11-22 18:18:32.281998: +2024-11-22 18:18:32.282205: Epoch 5794 +2024-11-22 18:18:32.282316: Current learning rate: 0.00314 +2024-11-22 18:18:51.556637: train_loss -0.8002 +2024-11-22 18:18:51.556852: val_loss -0.7517 +2024-11-22 18:18:51.557132: Pseudo dice [0.8508] +2024-11-22 18:18:51.557218: Epoch time: 19.28 s +2024-11-22 18:18:52.513208: +2024-11-22 18:18:52.513396: Epoch 5795 +2024-11-22 18:18:52.513508: Current learning rate: 0.00314 +2024-11-22 18:19:11.841142: train_loss -0.8132 +2024-11-22 18:19:11.843560: val_loss -0.7513 +2024-11-22 18:19:11.843719: Pseudo dice [0.8176] +2024-11-22 18:19:11.843811: Epoch time: 19.33 s +2024-11-22 18:19:12.771063: +2024-11-22 18:19:12.771266: Epoch 5796 +2024-11-22 18:19:12.771376: Current learning rate: 0.00313 +2024-11-22 18:19:32.989669: train_loss -0.7996 +2024-11-22 18:19:32.989900: val_loss -0.7519 +2024-11-22 18:19:32.989974: Pseudo dice [0.8362] +2024-11-22 18:19:32.990057: Epoch time: 20.22 s +2024-11-22 18:19:33.906049: +2024-11-22 18:19:33.906348: Epoch 5797 +2024-11-22 18:19:33.906462: Current learning rate: 0.00313 +2024-11-22 18:19:53.662578: train_loss -0.8043 +2024-11-22 18:19:53.662802: val_loss -0.7662 +2024-11-22 18:19:53.662882: Pseudo dice [0.8645] +2024-11-22 18:19:53.662961: Epoch time: 19.76 s +2024-11-22 18:19:54.760453: +2024-11-22 18:19:54.760728: Epoch 5798 +2024-11-22 18:19:54.760849: Current learning rate: 0.00313 +2024-11-22 18:20:14.462143: train_loss -0.8101 +2024-11-22 18:20:14.462369: val_loss -0.7494 +2024-11-22 18:20:14.462444: Pseudo dice [0.8413] +2024-11-22 18:20:14.462523: Epoch time: 19.7 s +2024-11-22 18:20:15.480931: +2024-11-22 18:20:15.481166: Epoch 5799 +2024-11-22 18:20:15.481282: Current learning rate: 0.00313 +2024-11-22 18:20:33.825617: train_loss -0.8096 +2024-11-22 18:20:33.825876: val_loss -0.7479 +2024-11-22 18:20:33.825960: Pseudo dice [0.8496] +2024-11-22 18:20:33.826054: Epoch time: 18.35 s +2024-11-22 18:20:35.455439: +2024-11-22 18:20:35.455665: Epoch 5800 +2024-11-22 18:20:35.455776: Current learning rate: 0.00313 +2024-11-22 18:20:54.131077: train_loss -0.8042 +2024-11-22 18:20:54.131328: val_loss -0.7397 +2024-11-22 18:20:54.131404: Pseudo dice [0.8405] +2024-11-22 18:20:54.131479: Epoch time: 18.68 s +2024-11-22 18:20:55.035624: +2024-11-22 18:20:55.035833: Epoch 5801 +2024-11-22 18:20:55.035944: Current learning rate: 0.00313 +2024-11-22 18:21:13.559889: train_loss -0.8071 +2024-11-22 18:21:13.560119: val_loss -0.7406 +2024-11-22 18:21:13.560193: Pseudo dice [0.8571] +2024-11-22 18:21:13.560268: Epoch time: 18.53 s +2024-11-22 18:21:14.464782: +2024-11-22 18:21:14.464998: Epoch 5802 +2024-11-22 18:21:14.465111: Current learning rate: 0.00313 +2024-11-22 18:21:32.702607: train_loss -0.7987 +2024-11-22 18:21:32.702926: val_loss -0.7562 +2024-11-22 18:21:32.703011: Pseudo dice [0.8438] +2024-11-22 18:21:32.703099: Epoch time: 18.24 s +2024-11-22 18:21:33.624459: +2024-11-22 18:21:33.624674: Epoch 5803 +2024-11-22 18:21:33.624786: Current learning rate: 0.00313 +2024-11-22 18:21:51.760556: train_loss -0.8088 +2024-11-22 18:21:51.760771: val_loss -0.7228 +2024-11-22 18:21:51.760895: Pseudo dice [0.8184] +2024-11-22 18:21:51.760971: Epoch time: 18.14 s +2024-11-22 18:21:52.673936: +2024-11-22 18:21:52.674156: Epoch 5804 +2024-11-22 18:21:52.674267: Current learning rate: 0.00312 +2024-11-22 18:22:10.280016: train_loss -0.8077 +2024-11-22 18:22:10.280221: val_loss -0.7441 +2024-11-22 18:22:10.280295: Pseudo dice [0.8508] +2024-11-22 18:22:10.280372: Epoch time: 17.61 s +2024-11-22 18:22:11.227113: +2024-11-22 18:22:11.227347: Epoch 5805 +2024-11-22 18:22:11.227457: Current learning rate: 0.00312 +2024-11-22 18:22:30.744330: train_loss -0.81 +2024-11-22 18:22:30.744553: val_loss -0.7797 +2024-11-22 18:22:30.744627: Pseudo dice [0.853] +2024-11-22 18:22:30.744704: Epoch time: 19.52 s +2024-11-22 18:22:31.653354: +2024-11-22 18:22:31.653633: Epoch 5806 +2024-11-22 18:22:31.653748: Current learning rate: 0.00312 +2024-11-22 18:22:51.199694: train_loss -0.8112 +2024-11-22 18:22:51.199967: val_loss -0.7476 +2024-11-22 18:22:51.200051: Pseudo dice [0.8477] +2024-11-22 18:22:51.200133: Epoch time: 19.55 s +2024-11-22 18:22:52.121216: +2024-11-22 18:22:52.121413: Epoch 5807 +2024-11-22 18:22:52.121526: Current learning rate: 0.00312 +2024-11-22 18:23:10.102318: train_loss -0.8094 +2024-11-22 18:23:10.102553: val_loss -0.7632 +2024-11-22 18:23:10.102629: Pseudo dice [0.8475] +2024-11-22 18:23:10.102710: Epoch time: 17.98 s +2024-11-22 18:23:11.015564: +2024-11-22 18:23:11.015758: Epoch 5808 +2024-11-22 18:23:11.015871: Current learning rate: 0.00312 +2024-11-22 18:23:29.546006: train_loss -0.8171 +2024-11-22 18:23:29.546252: val_loss -0.7526 +2024-11-22 18:23:29.546336: Pseudo dice [0.8553] +2024-11-22 18:23:29.546416: Epoch time: 18.53 s +2024-11-22 18:23:30.457242: +2024-11-22 18:23:30.457446: Epoch 5809 +2024-11-22 18:23:30.457562: Current learning rate: 0.00312 +2024-11-22 18:23:49.338330: train_loss -0.8115 +2024-11-22 18:23:49.338560: val_loss -0.7669 +2024-11-22 18:23:49.338637: Pseudo dice [0.8486] +2024-11-22 18:23:49.338797: Epoch time: 18.88 s +2024-11-22 18:23:50.243511: +2024-11-22 18:23:50.243704: Epoch 5810 +2024-11-22 18:23:50.243812: Current learning rate: 0.00312 +2024-11-22 18:24:09.048620: train_loss -0.811 +2024-11-22 18:24:09.048886: val_loss -0.7439 +2024-11-22 18:24:09.048969: Pseudo dice [0.8428] +2024-11-22 18:24:09.049064: Epoch time: 18.81 s +2024-11-22 18:24:09.957495: +2024-11-22 18:24:09.957712: Epoch 5811 +2024-11-22 18:24:09.957821: Current learning rate: 0.00311 +2024-11-22 18:24:28.266856: train_loss -0.8008 +2024-11-22 18:24:28.267080: val_loss -0.7585 +2024-11-22 18:24:28.267164: Pseudo dice [0.8452] +2024-11-22 18:24:28.267246: Epoch time: 18.31 s +2024-11-22 18:24:29.569476: +2024-11-22 18:24:29.569731: Epoch 5812 +2024-11-22 18:24:29.569847: Current learning rate: 0.00311 +2024-11-22 18:24:48.252434: train_loss -0.8048 +2024-11-22 18:24:48.252653: val_loss -0.7761 +2024-11-22 18:24:48.252727: Pseudo dice [0.8575] +2024-11-22 18:24:48.252803: Epoch time: 18.68 s +2024-11-22 18:24:49.196600: +2024-11-22 18:24:49.196908: Epoch 5813 +2024-11-22 18:24:49.197032: Current learning rate: 0.00311 +2024-11-22 18:25:08.239697: train_loss -0.8055 +2024-11-22 18:25:08.239941: val_loss -0.7494 +2024-11-22 18:25:08.240026: Pseudo dice [0.8286] +2024-11-22 18:25:08.240110: Epoch time: 19.04 s +2024-11-22 18:25:09.163284: +2024-11-22 18:25:09.163501: Epoch 5814 +2024-11-22 18:25:09.163614: Current learning rate: 0.00311 +2024-11-22 18:25:27.498126: train_loss -0.8017 +2024-11-22 18:25:27.498376: val_loss -0.7625 +2024-11-22 18:25:27.498452: Pseudo dice [0.8528] +2024-11-22 18:25:27.498534: Epoch time: 18.34 s +2024-11-22 18:25:28.409030: +2024-11-22 18:25:28.409230: Epoch 5815 +2024-11-22 18:25:28.409341: Current learning rate: 0.00311 +2024-11-22 18:25:47.521970: train_loss -0.814 +2024-11-22 18:25:47.522194: val_loss -0.7323 +2024-11-22 18:25:47.522269: Pseudo dice [0.8378] +2024-11-22 18:25:47.522387: Epoch time: 19.11 s +2024-11-22 18:25:48.438978: +2024-11-22 18:25:48.439201: Epoch 5816 +2024-11-22 18:25:48.439313: Current learning rate: 0.00311 +2024-11-22 18:26:07.259674: train_loss -0.8076 +2024-11-22 18:26:07.259905: val_loss -0.7673 +2024-11-22 18:26:07.259979: Pseudo dice [0.856] +2024-11-22 18:26:07.260063: Epoch time: 18.82 s +2024-11-22 18:26:08.276098: +2024-11-22 18:26:08.276388: Epoch 5817 +2024-11-22 18:26:08.276504: Current learning rate: 0.00311 +2024-11-22 18:26:27.721623: train_loss -0.8004 +2024-11-22 18:26:27.721843: val_loss -0.7489 +2024-11-22 18:26:27.721919: Pseudo dice [0.8366] +2024-11-22 18:26:27.722003: Epoch time: 19.45 s +2024-11-22 18:26:28.634462: +2024-11-22 18:26:28.634691: Epoch 5818 +2024-11-22 18:26:28.634808: Current learning rate: 0.00311 +2024-11-22 18:26:46.938650: train_loss -0.8092 +2024-11-22 18:26:46.938974: val_loss -0.7602 +2024-11-22 18:26:46.939064: Pseudo dice [0.821] +2024-11-22 18:26:46.939148: Epoch time: 18.3 s +2024-11-22 18:26:47.859534: +2024-11-22 18:26:47.859726: Epoch 5819 +2024-11-22 18:26:47.859838: Current learning rate: 0.0031 +2024-11-22 18:27:06.989507: train_loss -0.8078 +2024-11-22 18:27:06.989727: val_loss -0.7779 +2024-11-22 18:27:06.989805: Pseudo dice [0.8676] +2024-11-22 18:27:06.989882: Epoch time: 19.13 s +2024-11-22 18:27:07.899275: +2024-11-22 18:27:07.899466: Epoch 5820 +2024-11-22 18:27:07.899576: Current learning rate: 0.0031 +2024-11-22 18:27:26.517812: train_loss -0.8024 +2024-11-22 18:27:26.518041: val_loss -0.75 +2024-11-22 18:27:26.518855: Pseudo dice [0.8292] +2024-11-22 18:27:26.518979: Epoch time: 18.62 s +2024-11-22 18:27:27.437470: +2024-11-22 18:27:27.437682: Epoch 5821 +2024-11-22 18:27:27.437798: Current learning rate: 0.0031 +2024-11-22 18:27:45.200349: train_loss -0.8017 +2024-11-22 18:27:45.200567: val_loss -0.7477 +2024-11-22 18:27:45.200647: Pseudo dice [0.8464] +2024-11-22 18:27:45.200727: Epoch time: 17.76 s +2024-11-22 18:27:46.111670: +2024-11-22 18:27:46.111923: Epoch 5822 +2024-11-22 18:27:46.112046: Current learning rate: 0.0031 +2024-11-22 18:28:04.156925: train_loss -0.7964 +2024-11-22 18:28:04.157237: val_loss -0.728 +2024-11-22 18:28:04.157329: Pseudo dice [0.843] +2024-11-22 18:28:04.157420: Epoch time: 18.05 s +2024-11-22 18:28:05.065844: +2024-11-22 18:28:05.066049: Epoch 5823 +2024-11-22 18:28:05.066163: Current learning rate: 0.0031 +2024-11-22 18:28:23.065400: train_loss -0.7907 +2024-11-22 18:28:23.065695: val_loss -0.7453 +2024-11-22 18:28:23.065773: Pseudo dice [0.8481] +2024-11-22 18:28:23.065850: Epoch time: 18.0 s +2024-11-22 18:28:23.965962: +2024-11-22 18:28:23.966277: Epoch 5824 +2024-11-22 18:28:23.966392: Current learning rate: 0.0031 +2024-11-22 18:28:41.771330: train_loss -0.7957 +2024-11-22 18:28:41.771602: val_loss -0.7502 +2024-11-22 18:28:41.771679: Pseudo dice [0.8368] +2024-11-22 18:28:41.771755: Epoch time: 17.81 s +2024-11-22 18:28:42.749242: +2024-11-22 18:28:42.749509: Epoch 5825 +2024-11-22 18:28:42.749624: Current learning rate: 0.0031 +2024-11-22 18:29:01.102733: train_loss -0.8113 +2024-11-22 18:29:01.102984: val_loss -0.7407 +2024-11-22 18:29:01.103069: Pseudo dice [0.849] +2024-11-22 18:29:01.103153: Epoch time: 18.35 s +2024-11-22 18:29:02.015485: +2024-11-22 18:29:02.015704: Epoch 5826 +2024-11-22 18:29:02.015819: Current learning rate: 0.0031 +2024-11-22 18:29:20.418725: train_loss -0.8081 +2024-11-22 18:29:20.418954: val_loss -0.7403 +2024-11-22 18:29:20.419080: Pseudo dice [0.8492] +2024-11-22 18:29:20.419161: Epoch time: 18.4 s +2024-11-22 18:29:21.328854: +2024-11-22 18:29:21.329129: Epoch 5827 +2024-11-22 18:29:21.329244: Current learning rate: 0.00309 +2024-11-22 18:29:39.802287: train_loss -0.7938 +2024-11-22 18:29:39.802556: val_loss -0.7299 +2024-11-22 18:29:39.802634: Pseudo dice [0.8187] +2024-11-22 18:29:39.802715: Epoch time: 18.47 s +2024-11-22 18:29:41.055928: +2024-11-22 18:29:41.056155: Epoch 5828 +2024-11-22 18:29:41.056268: Current learning rate: 0.00309 +2024-11-22 18:29:59.647536: train_loss -0.8054 +2024-11-22 18:29:59.647757: val_loss -0.7351 +2024-11-22 18:29:59.647833: Pseudo dice [0.8466] +2024-11-22 18:29:59.647909: Epoch time: 18.59 s +2024-11-22 18:30:00.729267: +2024-11-22 18:30:00.729495: Epoch 5829 +2024-11-22 18:30:00.729612: Current learning rate: 0.00309 +2024-11-22 18:30:21.182490: train_loss -0.7986 +2024-11-22 18:30:21.182782: val_loss -0.765 +2024-11-22 18:30:21.182865: Pseudo dice [0.8363] +2024-11-22 18:30:21.182950: Epoch time: 20.45 s +2024-11-22 18:30:22.099535: +2024-11-22 18:30:22.099752: Epoch 5830 +2024-11-22 18:30:22.099870: Current learning rate: 0.00309 +2024-11-22 18:30:40.005364: train_loss -0.8047 +2024-11-22 18:30:40.005621: val_loss -0.7551 +2024-11-22 18:30:40.005698: Pseudo dice [0.8442] +2024-11-22 18:30:40.005781: Epoch time: 17.91 s +2024-11-22 18:30:40.912235: +2024-11-22 18:30:40.912431: Epoch 5831 +2024-11-22 18:30:40.912545: Current learning rate: 0.00309 +2024-11-22 18:31:00.375881: train_loss -0.7997 +2024-11-22 18:31:00.376104: val_loss -0.7607 +2024-11-22 18:31:00.376180: Pseudo dice [0.8445] +2024-11-22 18:31:00.377138: Epoch time: 19.46 s +2024-11-22 18:31:01.315032: +2024-11-22 18:31:01.315247: Epoch 5832 +2024-11-22 18:31:01.315364: Current learning rate: 0.00309 +2024-11-22 18:31:19.175110: train_loss -0.805 +2024-11-22 18:31:19.175323: val_loss -0.7655 +2024-11-22 18:31:19.175397: Pseudo dice [0.8474] +2024-11-22 18:31:19.175472: Epoch time: 17.86 s +2024-11-22 18:31:20.082739: +2024-11-22 18:31:20.083039: Epoch 5833 +2024-11-22 18:31:20.083157: Current learning rate: 0.00309 +2024-11-22 18:31:38.311207: train_loss -0.7907 +2024-11-22 18:31:38.311431: val_loss -0.7891 +2024-11-22 18:31:38.311566: Pseudo dice [0.8562] +2024-11-22 18:31:38.311654: Epoch time: 18.23 s +2024-11-22 18:31:39.219536: +2024-11-22 18:31:39.219797: Epoch 5834 +2024-11-22 18:31:39.219913: Current learning rate: 0.00309 +2024-11-22 18:31:59.175901: train_loss -0.7943 +2024-11-22 18:31:59.176133: val_loss -0.7556 +2024-11-22 18:31:59.178364: Pseudo dice [0.8459] +2024-11-22 18:31:59.178509: Epoch time: 19.96 s +2024-11-22 18:32:00.584065: +2024-11-22 18:32:00.584269: Epoch 5835 +2024-11-22 18:32:00.584382: Current learning rate: 0.00308 +2024-11-22 18:32:19.203650: train_loss -0.8034 +2024-11-22 18:32:19.203875: val_loss -0.7403 +2024-11-22 18:32:19.203949: Pseudo dice [0.8584] +2024-11-22 18:32:19.204035: Epoch time: 18.62 s +2024-11-22 18:32:20.110525: +2024-11-22 18:32:20.110747: Epoch 5836 +2024-11-22 18:32:20.110858: Current learning rate: 0.00308 +2024-11-22 18:32:39.539680: train_loss -0.8005 +2024-11-22 18:32:39.539904: val_loss -0.7622 +2024-11-22 18:32:39.539979: Pseudo dice [0.8596] +2024-11-22 18:32:39.540064: Epoch time: 19.43 s +2024-11-22 18:32:40.501632: +2024-11-22 18:32:40.502029: Epoch 5837 +2024-11-22 18:32:40.502146: Current learning rate: 0.00308 +2024-11-22 18:32:59.345228: train_loss -0.7971 +2024-11-22 18:32:59.345485: val_loss -0.7483 +2024-11-22 18:32:59.345559: Pseudo dice [0.8207] +2024-11-22 18:32:59.345644: Epoch time: 18.84 s +2024-11-22 18:33:00.260849: +2024-11-22 18:33:00.261056: Epoch 5838 +2024-11-22 18:33:00.261262: Current learning rate: 0.00308 +2024-11-22 18:33:18.689790: train_loss -0.8087 +2024-11-22 18:33:18.690070: val_loss -0.7505 +2024-11-22 18:33:18.690144: Pseudo dice [0.8165] +2024-11-22 18:33:18.690219: Epoch time: 18.43 s +2024-11-22 18:33:19.603520: +2024-11-22 18:33:19.603739: Epoch 5839 +2024-11-22 18:33:19.603851: Current learning rate: 0.00308 +2024-11-22 18:33:38.892520: train_loss -0.8018 +2024-11-22 18:33:38.892744: val_loss -0.7463 +2024-11-22 18:33:38.892827: Pseudo dice [0.8513] +2024-11-22 18:33:38.892904: Epoch time: 19.29 s +2024-11-22 18:33:39.809716: +2024-11-22 18:33:39.809925: Epoch 5840 +2024-11-22 18:33:39.810046: Current learning rate: 0.00308 +2024-11-22 18:33:59.243015: train_loss -0.8039 +2024-11-22 18:33:59.243233: val_loss -0.7651 +2024-11-22 18:33:59.243333: Pseudo dice [0.8722] +2024-11-22 18:33:59.243411: Epoch time: 19.43 s +2024-11-22 18:34:00.155664: +2024-11-22 18:34:00.156068: Epoch 5841 +2024-11-22 18:34:00.156183: Current learning rate: 0.00308 +2024-11-22 18:34:18.879019: train_loss -0.8071 +2024-11-22 18:34:18.879276: val_loss -0.7602 +2024-11-22 18:34:18.879351: Pseudo dice [0.8437] +2024-11-22 18:34:18.879436: Epoch time: 18.72 s +2024-11-22 18:34:19.808478: +2024-11-22 18:34:19.808698: Epoch 5842 +2024-11-22 18:34:19.808811: Current learning rate: 0.00308 +2024-11-22 18:34:39.352670: train_loss -0.8075 +2024-11-22 18:34:39.352899: val_loss -0.7706 +2024-11-22 18:34:39.353007: Pseudo dice [0.852] +2024-11-22 18:34:39.353095: Epoch time: 19.55 s +2024-11-22 18:34:40.326547: +2024-11-22 18:34:40.326766: Epoch 5843 +2024-11-22 18:34:40.326880: Current learning rate: 0.00307 +2024-11-22 18:34:58.546114: train_loss -0.8078 +2024-11-22 18:34:58.546394: val_loss -0.7491 +2024-11-22 18:34:58.546471: Pseudo dice [0.8625] +2024-11-22 18:34:58.546549: Epoch time: 18.22 s +2024-11-22 18:34:59.488011: +2024-11-22 18:34:59.488262: Epoch 5844 +2024-11-22 18:34:59.488385: Current learning rate: 0.00307 +2024-11-22 18:35:17.497635: train_loss -0.8137 +2024-11-22 18:35:17.498418: val_loss -0.7644 +2024-11-22 18:35:17.498499: Pseudo dice [0.8519] +2024-11-22 18:35:17.498575: Epoch time: 18.01 s +2024-11-22 18:35:18.402230: +2024-11-22 18:35:18.402425: Epoch 5845 +2024-11-22 18:35:18.402539: Current learning rate: 0.00307 +2024-11-22 18:35:37.739529: train_loss -0.8098 +2024-11-22 18:35:37.739782: val_loss -0.7517 +2024-11-22 18:35:37.739857: Pseudo dice [0.8339] +2024-11-22 18:35:37.739943: Epoch time: 19.34 s +2024-11-22 18:35:39.037536: +2024-11-22 18:35:39.037749: Epoch 5846 +2024-11-22 18:35:39.037859: Current learning rate: 0.00307 +2024-11-22 18:35:57.656279: train_loss -0.8139 +2024-11-22 18:35:57.656611: val_loss -0.772 +2024-11-22 18:35:57.656700: Pseudo dice [0.8554] +2024-11-22 18:35:57.656780: Epoch time: 18.62 s +2024-11-22 18:35:58.723247: +2024-11-22 18:35:58.723465: Epoch 5847 +2024-11-22 18:35:58.723580: Current learning rate: 0.00307 +2024-11-22 18:36:18.282347: train_loss -0.8078 +2024-11-22 18:36:18.282568: val_loss -0.7603 +2024-11-22 18:36:18.282644: Pseudo dice [0.8289] +2024-11-22 18:36:18.282719: Epoch time: 19.56 s +2024-11-22 18:36:19.479104: +2024-11-22 18:36:19.479338: Epoch 5848 +2024-11-22 18:36:19.479450: Current learning rate: 0.00307 +2024-11-22 18:36:39.239184: train_loss -0.811 +2024-11-22 18:36:39.239448: val_loss -0.7889 +2024-11-22 18:36:39.239527: Pseudo dice [0.861] +2024-11-22 18:36:39.239615: Epoch time: 19.76 s +2024-11-22 18:36:40.157523: +2024-11-22 18:36:40.157745: Epoch 5849 +2024-11-22 18:36:40.157866: Current learning rate: 0.00307 +2024-11-22 18:36:58.129294: train_loss -0.8167 +2024-11-22 18:36:58.129554: val_loss -0.7274 +2024-11-22 18:36:58.129634: Pseudo dice [0.8552] +2024-11-22 18:36:58.129713: Epoch time: 17.97 s +2024-11-22 18:36:59.343078: +2024-11-22 18:36:59.343294: Epoch 5850 +2024-11-22 18:36:59.343407: Current learning rate: 0.00306 +2024-11-22 18:37:18.066932: train_loss -0.8093 +2024-11-22 18:37:18.067156: val_loss -0.7163 +2024-11-22 18:37:18.067230: Pseudo dice [0.8251] +2024-11-22 18:37:18.067307: Epoch time: 18.72 s +2024-11-22 18:37:19.005877: +2024-11-22 18:37:19.006134: Epoch 5851 +2024-11-22 18:37:19.006256: Current learning rate: 0.00306 +2024-11-22 18:37:37.116265: train_loss -0.8082 +2024-11-22 18:37:37.116480: val_loss -0.7702 +2024-11-22 18:37:37.116561: Pseudo dice [0.8355] +2024-11-22 18:37:37.116639: Epoch time: 18.11 s +2024-11-22 18:37:38.017767: +2024-11-22 18:37:38.017999: Epoch 5852 +2024-11-22 18:37:38.018107: Current learning rate: 0.00306 +2024-11-22 18:37:56.567870: train_loss -0.8084 +2024-11-22 18:37:56.568103: val_loss -0.7639 +2024-11-22 18:37:56.568177: Pseudo dice [0.8556] +2024-11-22 18:37:56.568256: Epoch time: 18.55 s +2024-11-22 18:37:57.511194: +2024-11-22 18:37:57.511426: Epoch 5853 +2024-11-22 18:37:57.511543: Current learning rate: 0.00306 +2024-11-22 18:38:15.831042: train_loss -0.8164 +2024-11-22 18:38:15.831282: val_loss -0.7468 +2024-11-22 18:38:15.831360: Pseudo dice [0.8181] +2024-11-22 18:38:15.831440: Epoch time: 18.32 s +2024-11-22 18:38:16.742535: +2024-11-22 18:38:16.742823: Epoch 5854 +2024-11-22 18:38:16.742934: Current learning rate: 0.00306 +2024-11-22 18:38:34.889971: train_loss -0.8134 +2024-11-22 18:38:34.890237: val_loss -0.7751 +2024-11-22 18:38:34.890316: Pseudo dice [0.8441] +2024-11-22 18:38:34.890394: Epoch time: 18.15 s +2024-11-22 18:38:35.830623: +2024-11-22 18:38:35.830833: Epoch 5855 +2024-11-22 18:38:35.830947: Current learning rate: 0.00306 +2024-11-22 18:38:54.727590: train_loss -0.8111 +2024-11-22 18:38:54.727824: val_loss -0.7635 +2024-11-22 18:38:54.727904: Pseudo dice [0.849] +2024-11-22 18:38:54.727981: Epoch time: 18.9 s +2024-11-22 18:38:55.650697: +2024-11-22 18:38:55.650889: Epoch 5856 +2024-11-22 18:38:55.651008: Current learning rate: 0.00306 +2024-11-22 18:39:15.076897: train_loss -0.8085 +2024-11-22 18:39:15.077184: val_loss -0.714 +2024-11-22 18:39:15.077279: Pseudo dice [0.8456] +2024-11-22 18:39:15.077362: Epoch time: 19.43 s +2024-11-22 18:39:15.984874: +2024-11-22 18:39:15.985079: Epoch 5857 +2024-11-22 18:39:15.985189: Current learning rate: 0.00306 +2024-11-22 18:39:35.578975: train_loss -0.8097 +2024-11-22 18:39:35.580065: val_loss -0.7803 +2024-11-22 18:39:35.580145: Pseudo dice [0.8549] +2024-11-22 18:39:35.580227: Epoch time: 19.59 s +2024-11-22 18:39:36.891392: +2024-11-22 18:39:36.891607: Epoch 5858 +2024-11-22 18:39:36.891714: Current learning rate: 0.00305 +2024-11-22 18:39:56.010738: train_loss -0.7999 +2024-11-22 18:39:56.010968: val_loss -0.7586 +2024-11-22 18:39:56.011046: Pseudo dice [0.8407] +2024-11-22 18:39:56.011127: Epoch time: 19.12 s +2024-11-22 18:39:56.926142: +2024-11-22 18:39:56.926419: Epoch 5859 +2024-11-22 18:39:56.926530: Current learning rate: 0.00305 +2024-11-22 18:40:15.535845: train_loss -0.8083 +2024-11-22 18:40:15.548721: val_loss -0.7664 +2024-11-22 18:40:15.548876: Pseudo dice [0.852] +2024-11-22 18:40:15.549142: Epoch time: 18.61 s +2024-11-22 18:40:16.534478: +2024-11-22 18:40:16.534736: Epoch 5860 +2024-11-22 18:40:16.534856: Current learning rate: 0.00305 +2024-11-22 18:40:35.336558: train_loss -0.8109 +2024-11-22 18:40:35.336821: val_loss -0.7312 +2024-11-22 18:40:35.336901: Pseudo dice [0.8382] +2024-11-22 18:40:35.336984: Epoch time: 18.8 s +2024-11-22 18:40:36.248891: +2024-11-22 18:40:36.249148: Epoch 5861 +2024-11-22 18:40:36.249266: Current learning rate: 0.00305 +2024-11-22 18:40:55.479568: train_loss -0.8085 +2024-11-22 18:40:55.479788: val_loss -0.7508 +2024-11-22 18:40:55.479868: Pseudo dice [0.8602] +2024-11-22 18:40:55.479949: Epoch time: 19.23 s +2024-11-22 18:40:56.393022: +2024-11-22 18:40:56.393304: Epoch 5862 +2024-11-22 18:40:56.393424: Current learning rate: 0.00305 +2024-11-22 18:41:15.640609: train_loss -0.803 +2024-11-22 18:41:15.640825: val_loss -0.7412 +2024-11-22 18:41:15.640905: Pseudo dice [0.8294] +2024-11-22 18:41:15.640984: Epoch time: 19.25 s +2024-11-22 18:41:16.547888: +2024-11-22 18:41:16.548099: Epoch 5863 +2024-11-22 18:41:16.548212: Current learning rate: 0.00305 +2024-11-22 18:41:34.976088: train_loss -0.8085 +2024-11-22 18:41:34.976323: val_loss -0.7572 +2024-11-22 18:41:34.976399: Pseudo dice [0.8409] +2024-11-22 18:41:34.976475: Epoch time: 18.43 s +2024-11-22 18:41:35.883053: +2024-11-22 18:41:35.883257: Epoch 5864 +2024-11-22 18:41:35.883375: Current learning rate: 0.00305 +2024-11-22 18:41:53.755889: train_loss -0.8104 +2024-11-22 18:41:53.756123: val_loss -0.7426 +2024-11-22 18:41:53.756204: Pseudo dice [0.8476] +2024-11-22 18:41:53.756283: Epoch time: 17.87 s +2024-11-22 18:41:54.695518: +2024-11-22 18:41:54.695784: Epoch 5865 +2024-11-22 18:41:54.695939: Current learning rate: 0.00305 +2024-11-22 18:42:14.601306: train_loss -0.8103 +2024-11-22 18:42:14.601533: val_loss -0.72 +2024-11-22 18:42:14.601607: Pseudo dice [0.8196] +2024-11-22 18:42:14.601745: Epoch time: 19.91 s +2024-11-22 18:42:15.516592: +2024-11-22 18:42:15.516890: Epoch 5866 +2024-11-22 18:42:15.517005: Current learning rate: 0.00304 +2024-11-22 18:42:33.825285: train_loss -0.8108 +2024-11-22 18:42:33.825500: val_loss -0.7406 +2024-11-22 18:42:33.825583: Pseudo dice [0.8382] +2024-11-22 18:42:33.825666: Epoch time: 18.31 s +2024-11-22 18:42:34.736032: +2024-11-22 18:42:34.736230: Epoch 5867 +2024-11-22 18:42:34.736342: Current learning rate: 0.00304 +2024-11-22 18:42:52.362006: train_loss -0.8124 +2024-11-22 18:42:52.362230: val_loss -0.745 +2024-11-22 18:42:52.362307: Pseudo dice [0.822] +2024-11-22 18:42:52.362383: Epoch time: 17.63 s +2024-11-22 18:42:53.267057: +2024-11-22 18:42:53.267263: Epoch 5868 +2024-11-22 18:42:53.267379: Current learning rate: 0.00304 +2024-11-22 18:43:12.222304: train_loss -0.8019 +2024-11-22 18:43:12.227746: val_loss -0.7248 +2024-11-22 18:43:12.227826: Pseudo dice [0.8478] +2024-11-22 18:43:12.227916: Epoch time: 18.96 s +2024-11-22 18:43:13.189358: +2024-11-22 18:43:13.189572: Epoch 5869 +2024-11-22 18:43:13.189690: Current learning rate: 0.00304 +2024-11-22 18:43:32.345281: train_loss -0.8055 +2024-11-22 18:43:32.345533: val_loss -0.7447 +2024-11-22 18:43:32.345635: Pseudo dice [0.8618] +2024-11-22 18:43:32.345714: Epoch time: 19.16 s +2024-11-22 18:43:33.251149: +2024-11-22 18:43:33.251409: Epoch 5870 +2024-11-22 18:43:33.251524: Current learning rate: 0.00304 +2024-11-22 18:43:51.639039: train_loss -0.8039 +2024-11-22 18:43:51.639260: val_loss -0.7449 +2024-11-22 18:43:51.639336: Pseudo dice [0.8382] +2024-11-22 18:43:51.639414: Epoch time: 18.39 s +2024-11-22 18:43:52.545859: +2024-11-22 18:43:52.546107: Epoch 5871 +2024-11-22 18:43:52.546230: Current learning rate: 0.00304 +2024-11-22 18:44:11.185508: train_loss -0.7967 +2024-11-22 18:44:11.185731: val_loss -0.7619 +2024-11-22 18:44:11.186909: Pseudo dice [0.8431] +2024-11-22 18:44:11.187052: Epoch time: 18.64 s +2024-11-22 18:44:12.108033: +2024-11-22 18:44:12.108266: Epoch 5872 +2024-11-22 18:44:12.108378: Current learning rate: 0.00304 +2024-11-22 18:44:31.460429: train_loss -0.8063 +2024-11-22 18:44:31.465147: val_loss -0.7254 +2024-11-22 18:44:31.465289: Pseudo dice [0.8187] +2024-11-22 18:44:31.465426: Epoch time: 19.35 s +2024-11-22 18:44:32.379005: +2024-11-22 18:44:32.379205: Epoch 5873 +2024-11-22 18:44:32.379318: Current learning rate: 0.00304 +2024-11-22 18:44:51.281391: train_loss -0.8141 +2024-11-22 18:44:51.281703: val_loss -0.774 +2024-11-22 18:44:51.281783: Pseudo dice [0.8596] +2024-11-22 18:44:51.281862: Epoch time: 18.9 s +2024-11-22 18:44:52.196900: +2024-11-22 18:44:52.197118: Epoch 5874 +2024-11-22 18:44:52.197233: Current learning rate: 0.00303 +2024-11-22 18:45:11.266174: train_loss -0.7966 +2024-11-22 18:45:11.266392: val_loss -0.7219 +2024-11-22 18:45:11.266466: Pseudo dice [0.8385] +2024-11-22 18:45:11.266543: Epoch time: 19.07 s +2024-11-22 18:45:12.324414: +2024-11-22 18:45:12.324665: Epoch 5875 +2024-11-22 18:45:12.324783: Current learning rate: 0.00303 +2024-11-22 18:45:31.236967: train_loss -0.798 +2024-11-22 18:45:31.237188: val_loss -0.7464 +2024-11-22 18:45:31.237263: Pseudo dice [0.8552] +2024-11-22 18:45:31.237338: Epoch time: 18.91 s +2024-11-22 18:45:32.169900: +2024-11-22 18:45:32.170108: Epoch 5876 +2024-11-22 18:45:32.170223: Current learning rate: 0.00303 +2024-11-22 18:45:49.526713: train_loss -0.7984 +2024-11-22 18:45:49.529129: val_loss -0.7406 +2024-11-22 18:45:49.529222: Pseudo dice [0.8402] +2024-11-22 18:45:49.529311: Epoch time: 17.36 s +2024-11-22 18:45:50.574377: +2024-11-22 18:45:50.574620: Epoch 5877 +2024-11-22 18:45:50.574735: Current learning rate: 0.00303 +2024-11-22 18:46:09.180629: train_loss -0.8094 +2024-11-22 18:46:09.180857: val_loss -0.7629 +2024-11-22 18:46:09.180934: Pseudo dice [0.8467] +2024-11-22 18:46:09.181019: Epoch time: 18.61 s +2024-11-22 18:46:10.099955: +2024-11-22 18:46:10.100252: Epoch 5878 +2024-11-22 18:46:10.100363: Current learning rate: 0.00303 +2024-11-22 18:46:27.895476: train_loss -0.7966 +2024-11-22 18:46:27.895715: val_loss -0.7744 +2024-11-22 18:46:27.895820: Pseudo dice [0.8396] +2024-11-22 18:46:27.895901: Epoch time: 17.8 s +2024-11-22 18:46:28.807010: +2024-11-22 18:46:28.807222: Epoch 5879 +2024-11-22 18:46:28.807334: Current learning rate: 0.00303 +2024-11-22 18:46:48.548428: train_loss -0.8005 +2024-11-22 18:46:48.548688: val_loss -0.744 +2024-11-22 18:46:48.548766: Pseudo dice [0.8661] +2024-11-22 18:46:48.548848: Epoch time: 19.74 s +2024-11-22 18:46:49.515500: +2024-11-22 18:46:49.515721: Epoch 5880 +2024-11-22 18:46:49.515836: Current learning rate: 0.00303 +2024-11-22 18:47:09.317207: train_loss -0.7945 +2024-11-22 18:47:09.322627: val_loss -0.7372 +2024-11-22 18:47:09.322771: Pseudo dice [0.8306] +2024-11-22 18:47:09.322858: Epoch time: 19.8 s +2024-11-22 18:47:10.762325: +2024-11-22 18:47:10.762543: Epoch 5881 +2024-11-22 18:47:10.762656: Current learning rate: 0.00303 +2024-11-22 18:47:29.300601: train_loss -0.7962 +2024-11-22 18:47:29.300823: val_loss -0.7764 +2024-11-22 18:47:29.300907: Pseudo dice [0.8586] +2024-11-22 18:47:29.301058: Epoch time: 18.54 s +2024-11-22 18:47:30.218076: +2024-11-22 18:47:30.218363: Epoch 5882 +2024-11-22 18:47:30.218479: Current learning rate: 0.00302 +2024-11-22 18:47:48.661245: train_loss -0.8082 +2024-11-22 18:47:48.661478: val_loss -0.7757 +2024-11-22 18:47:48.661553: Pseudo dice [0.8376] +2024-11-22 18:47:48.661631: Epoch time: 18.44 s +2024-11-22 18:47:49.581462: +2024-11-22 18:47:49.581764: Epoch 5883 +2024-11-22 18:47:49.581884: Current learning rate: 0.00302 +2024-11-22 18:48:10.046876: train_loss -0.8048 +2024-11-22 18:48:10.047202: val_loss -0.7544 +2024-11-22 18:48:10.047285: Pseudo dice [0.8339] +2024-11-22 18:48:10.047370: Epoch time: 20.47 s +2024-11-22 18:48:10.982935: +2024-11-22 18:48:10.983157: Epoch 5884 +2024-11-22 18:48:10.983270: Current learning rate: 0.00302 +2024-11-22 18:48:28.936232: train_loss -0.8041 +2024-11-22 18:48:28.936455: val_loss -0.7696 +2024-11-22 18:48:28.936536: Pseudo dice [0.8726] +2024-11-22 18:48:28.936620: Epoch time: 17.95 s +2024-11-22 18:48:29.849321: +2024-11-22 18:48:29.849535: Epoch 5885 +2024-11-22 18:48:29.849653: Current learning rate: 0.00302 +2024-11-22 18:48:49.250123: train_loss -0.7949 +2024-11-22 18:48:49.250345: val_loss -0.7023 +2024-11-22 18:48:49.250424: Pseudo dice [0.8189] +2024-11-22 18:48:49.255640: Epoch time: 19.4 s +2024-11-22 18:48:50.209522: +2024-11-22 18:48:50.209821: Epoch 5886 +2024-11-22 18:48:50.209939: Current learning rate: 0.00302 +2024-11-22 18:49:08.267150: train_loss -0.7971 +2024-11-22 18:49:08.267364: val_loss -0.7322 +2024-11-22 18:49:08.267437: Pseudo dice [0.8522] +2024-11-22 18:49:08.267513: Epoch time: 18.06 s +2024-11-22 18:49:09.181432: +2024-11-22 18:49:09.181661: Epoch 5887 +2024-11-22 18:49:09.181776: Current learning rate: 0.00302 +2024-11-22 18:49:28.058789: train_loss -0.802 +2024-11-22 18:49:28.059072: val_loss -0.7815 +2024-11-22 18:49:28.059157: Pseudo dice [0.8551] +2024-11-22 18:49:28.059238: Epoch time: 18.88 s +2024-11-22 18:49:28.973473: +2024-11-22 18:49:28.973780: Epoch 5888 +2024-11-22 18:49:28.973893: Current learning rate: 0.00302 +2024-11-22 18:49:48.330585: train_loss -0.8017 +2024-11-22 18:49:48.330802: val_loss -0.7488 +2024-11-22 18:49:48.330875: Pseudo dice [0.8628] +2024-11-22 18:49:48.330955: Epoch time: 19.36 s +2024-11-22 18:49:49.336099: +2024-11-22 18:49:49.336301: Epoch 5889 +2024-11-22 18:49:49.336417: Current learning rate: 0.00301 +2024-11-22 18:50:07.581269: train_loss -0.812 +2024-11-22 18:50:07.583638: val_loss -0.7505 +2024-11-22 18:50:07.583735: Pseudo dice [0.8502] +2024-11-22 18:50:07.583819: Epoch time: 18.25 s +2024-11-22 18:50:08.504088: +2024-11-22 18:50:08.504323: Epoch 5890 +2024-11-22 18:50:08.504447: Current learning rate: 0.00301 +2024-11-22 18:50:26.798865: train_loss -0.7977 +2024-11-22 18:50:26.799103: val_loss -0.7421 +2024-11-22 18:50:26.799179: Pseudo dice [0.8247] +2024-11-22 18:50:26.799269: Epoch time: 18.3 s +2024-11-22 18:50:27.701842: +2024-11-22 18:50:27.702066: Epoch 5891 +2024-11-22 18:50:27.702179: Current learning rate: 0.00301 +2024-11-22 18:50:45.948322: train_loss -0.8076 +2024-11-22 18:50:45.948574: val_loss -0.7453 +2024-11-22 18:50:45.948652: Pseudo dice [0.8191] +2024-11-22 18:50:45.948737: Epoch time: 18.25 s +2024-11-22 18:50:46.857156: +2024-11-22 18:50:46.857491: Epoch 5892 +2024-11-22 18:50:46.857614: Current learning rate: 0.00301 +2024-11-22 18:51:05.885030: train_loss -0.8094 +2024-11-22 18:51:05.885288: val_loss -0.7469 +2024-11-22 18:51:05.885367: Pseudo dice [0.8577] +2024-11-22 18:51:05.885444: Epoch time: 19.03 s +2024-11-22 18:51:06.795563: +2024-11-22 18:51:06.795808: Epoch 5893 +2024-11-22 18:51:06.795930: Current learning rate: 0.00301 +2024-11-22 18:51:24.887309: train_loss -0.8098 +2024-11-22 18:51:24.887533: val_loss -0.7474 +2024-11-22 18:51:24.887610: Pseudo dice [0.8474] +2024-11-22 18:51:24.887689: Epoch time: 18.09 s +2024-11-22 18:51:25.795587: +2024-11-22 18:51:25.795803: Epoch 5894 +2024-11-22 18:51:25.795912: Current learning rate: 0.00301 +2024-11-22 18:51:44.662703: train_loss -0.8072 +2024-11-22 18:51:44.662927: val_loss -0.7598 +2024-11-22 18:51:44.663012: Pseudo dice [0.8574] +2024-11-22 18:51:44.663102: Epoch time: 18.87 s +2024-11-22 18:51:45.586311: +2024-11-22 18:51:45.586550: Epoch 5895 +2024-11-22 18:51:45.586669: Current learning rate: 0.00301 +2024-11-22 18:52:04.178508: train_loss -0.8059 +2024-11-22 18:52:04.178771: val_loss -0.7538 +2024-11-22 18:52:04.178846: Pseudo dice [0.8485] +2024-11-22 18:52:04.178927: Epoch time: 18.59 s +2024-11-22 18:52:05.340474: +2024-11-22 18:52:05.340688: Epoch 5896 +2024-11-22 18:52:05.340798: Current learning rate: 0.00301 +2024-11-22 18:52:24.385003: train_loss -0.8111 +2024-11-22 18:52:24.385220: val_loss -0.73 +2024-11-22 18:52:24.385295: Pseudo dice [0.8444] +2024-11-22 18:52:24.385373: Epoch time: 19.05 s +2024-11-22 18:52:25.295675: +2024-11-22 18:52:25.295913: Epoch 5897 +2024-11-22 18:52:25.296038: Current learning rate: 0.003 +2024-11-22 18:52:44.106551: train_loss -0.8177 +2024-11-22 18:52:44.106781: val_loss -0.7334 +2024-11-22 18:52:44.106860: Pseudo dice [0.8489] +2024-11-22 18:52:44.106942: Epoch time: 18.81 s +2024-11-22 18:52:45.018796: +2024-11-22 18:52:45.019000: Epoch 5898 +2024-11-22 18:52:45.019112: Current learning rate: 0.003 +2024-11-22 18:53:04.033514: train_loss -0.8101 +2024-11-22 18:53:04.036132: val_loss -0.7355 +2024-11-22 18:53:04.036243: Pseudo dice [0.8527] +2024-11-22 18:53:04.036324: Epoch time: 19.02 s +2024-11-22 18:53:04.952462: +2024-11-22 18:53:04.952663: Epoch 5899 +2024-11-22 18:53:04.952774: Current learning rate: 0.003 +2024-11-22 18:53:23.833363: train_loss -0.8023 +2024-11-22 18:53:23.833681: val_loss -0.758 +2024-11-22 18:53:23.833758: Pseudo dice [0.8549] +2024-11-22 18:53:23.833841: Epoch time: 18.88 s +2024-11-22 18:53:25.066332: +2024-11-22 18:53:25.066560: Epoch 5900 +2024-11-22 18:53:25.066673: Current learning rate: 0.003 +2024-11-22 18:53:44.049056: train_loss -0.81 +2024-11-22 18:53:44.049300: val_loss -0.746 +2024-11-22 18:53:44.049379: Pseudo dice [0.832] +2024-11-22 18:53:44.049455: Epoch time: 18.98 s +2024-11-22 18:53:44.959478: +2024-11-22 18:53:44.959686: Epoch 5901 +2024-11-22 18:53:44.959805: Current learning rate: 0.003 +2024-11-22 18:54:03.667120: train_loss -0.8138 +2024-11-22 18:54:03.667345: val_loss -0.7797 +2024-11-22 18:54:03.667424: Pseudo dice [0.8499] +2024-11-22 18:54:03.667503: Epoch time: 18.71 s +2024-11-22 18:54:04.582541: +2024-11-22 18:54:04.582765: Epoch 5902 +2024-11-22 18:54:04.582884: Current learning rate: 0.003 +2024-11-22 18:54:23.969801: train_loss -0.8075 +2024-11-22 18:54:23.970032: val_loss -0.7581 +2024-11-22 18:54:23.970174: Pseudo dice [0.8458] +2024-11-22 18:54:23.970254: Epoch time: 19.39 s +2024-11-22 18:54:25.262396: +2024-11-22 18:54:25.262614: Epoch 5903 +2024-11-22 18:54:25.262724: Current learning rate: 0.003 +2024-11-22 18:54:43.490565: train_loss -0.8143 +2024-11-22 18:54:43.490845: val_loss -0.7323 +2024-11-22 18:54:43.490922: Pseudo dice [0.8427] +2024-11-22 18:54:43.491011: Epoch time: 18.23 s +2024-11-22 18:54:44.398856: +2024-11-22 18:54:44.399088: Epoch 5904 +2024-11-22 18:54:44.399203: Current learning rate: 0.003 +2024-11-22 18:55:02.875097: train_loss -0.8092 +2024-11-22 18:55:02.875312: val_loss -0.7372 +2024-11-22 18:55:02.875387: Pseudo dice [0.8498] +2024-11-22 18:55:02.875460: Epoch time: 18.48 s +2024-11-22 18:55:03.785486: +2024-11-22 18:55:03.785721: Epoch 5905 +2024-11-22 18:55:03.785836: Current learning rate: 0.00299 +2024-11-22 18:55:22.608976: train_loss -0.8122 +2024-11-22 18:55:22.609209: val_loss -0.7592 +2024-11-22 18:55:22.609285: Pseudo dice [0.8632] +2024-11-22 18:55:22.609363: Epoch time: 18.82 s +2024-11-22 18:55:23.612387: +2024-11-22 18:55:23.612592: Epoch 5906 +2024-11-22 18:55:23.612704: Current learning rate: 0.00299 +2024-11-22 18:55:41.844559: train_loss -0.8017 +2024-11-22 18:55:41.844788: val_loss -0.7447 +2024-11-22 18:55:41.844865: Pseudo dice [0.8654] +2024-11-22 18:55:41.844943: Epoch time: 18.23 s +2024-11-22 18:55:42.761035: +2024-11-22 18:55:42.761245: Epoch 5907 +2024-11-22 18:55:42.761359: Current learning rate: 0.00299 +2024-11-22 18:56:02.014918: train_loss -0.7998 +2024-11-22 18:56:02.015169: val_loss -0.776 +2024-11-22 18:56:02.017443: Pseudo dice [0.8671] +2024-11-22 18:56:02.017540: Epoch time: 19.25 s +2024-11-22 18:56:02.930654: +2024-11-22 18:56:02.930871: Epoch 5908 +2024-11-22 18:56:02.931028: Current learning rate: 0.00299 +2024-11-22 18:56:22.142397: train_loss -0.8044 +2024-11-22 18:56:22.142589: val_loss -0.7878 +2024-11-22 18:56:22.142660: Pseudo dice [0.8503] +2024-11-22 18:56:22.142736: Epoch time: 19.21 s +2024-11-22 18:56:23.108401: +2024-11-22 18:56:23.108606: Epoch 5909 +2024-11-22 18:56:23.108718: Current learning rate: 0.00299 +2024-11-22 18:56:43.127602: train_loss -0.8077 +2024-11-22 18:56:43.127824: val_loss -0.7765 +2024-11-22 18:56:43.127915: Pseudo dice [0.852] +2024-11-22 18:56:43.128003: Epoch time: 20.02 s +2024-11-22 18:56:44.040185: +2024-11-22 18:56:44.040411: Epoch 5910 +2024-11-22 18:56:44.040525: Current learning rate: 0.00299 +2024-11-22 18:57:02.410543: train_loss -0.8065 +2024-11-22 18:57:02.410788: val_loss -0.7387 +2024-11-22 18:57:02.410863: Pseudo dice [0.8369] +2024-11-22 18:57:02.410949: Epoch time: 18.37 s +2024-11-22 18:57:03.351913: +2024-11-22 18:57:03.352126: Epoch 5911 +2024-11-22 18:57:03.352244: Current learning rate: 0.00299 +2024-11-22 18:57:22.154367: train_loss -0.8013 +2024-11-22 18:57:22.154591: val_loss -0.7622 +2024-11-22 18:57:22.154665: Pseudo dice [0.8603] +2024-11-22 18:57:22.154743: Epoch time: 18.8 s +2024-11-22 18:57:23.059588: +2024-11-22 18:57:23.059871: Epoch 5912 +2024-11-22 18:57:23.059983: Current learning rate: 0.00299 +2024-11-22 18:57:41.931502: train_loss -0.8111 +2024-11-22 18:57:41.931717: val_loss -0.7335 +2024-11-22 18:57:41.931790: Pseudo dice [0.8571] +2024-11-22 18:57:41.931865: Epoch time: 18.87 s +2024-11-22 18:57:42.838479: +2024-11-22 18:57:42.839001: Epoch 5913 +2024-11-22 18:57:42.839136: Current learning rate: 0.00298 +2024-11-22 18:58:02.275724: train_loss -0.7997 +2024-11-22 18:58:02.275945: val_loss -0.743 +2024-11-22 18:58:02.276037: Pseudo dice [0.8452] +2024-11-22 18:58:02.276128: Epoch time: 19.44 s +2024-11-22 18:58:03.185572: +2024-11-22 18:58:03.185832: Epoch 5914 +2024-11-22 18:58:03.185948: Current learning rate: 0.00298 +2024-11-22 18:58:20.995776: train_loss -0.8116 +2024-11-22 18:58:20.998198: val_loss -0.7433 +2024-11-22 18:58:20.998283: Pseudo dice [0.849] +2024-11-22 18:58:20.998367: Epoch time: 17.81 s +2024-11-22 18:58:22.466741: +2024-11-22 18:58:22.466967: Epoch 5915 +2024-11-22 18:58:22.467086: Current learning rate: 0.00298 +2024-11-22 18:58:41.856294: train_loss -0.816 +2024-11-22 18:58:41.856537: val_loss -0.7716 +2024-11-22 18:58:41.856613: Pseudo dice [0.8373] +2024-11-22 18:58:41.856696: Epoch time: 19.39 s +2024-11-22 18:58:42.882548: +2024-11-22 18:58:42.882763: Epoch 5916 +2024-11-22 18:58:42.882873: Current learning rate: 0.00298 +2024-11-22 18:59:02.294925: train_loss -0.8118 +2024-11-22 18:59:02.297302: val_loss -0.7234 +2024-11-22 18:59:02.297429: Pseudo dice [0.8447] +2024-11-22 18:59:02.297513: Epoch time: 19.41 s +2024-11-22 18:59:03.248299: +2024-11-22 18:59:03.248517: Epoch 5917 +2024-11-22 18:59:03.248631: Current learning rate: 0.00298 +2024-11-22 18:59:21.433512: train_loss -0.8103 +2024-11-22 18:59:21.433734: val_loss -0.7437 +2024-11-22 18:59:21.433808: Pseudo dice [0.8628] +2024-11-22 18:59:21.433885: Epoch time: 18.19 s +2024-11-22 18:59:22.343186: +2024-11-22 18:59:22.343406: Epoch 5918 +2024-11-22 18:59:22.343524: Current learning rate: 0.00298 +2024-11-22 18:59:41.592157: train_loss -0.8075 +2024-11-22 18:59:41.597601: val_loss -0.7525 +2024-11-22 18:59:41.597714: Pseudo dice [0.8367] +2024-11-22 18:59:41.597802: Epoch time: 19.25 s +2024-11-22 18:59:42.676724: +2024-11-22 18:59:42.676935: Epoch 5919 +2024-11-22 18:59:42.677055: Current learning rate: 0.00298 +2024-11-22 19:00:00.607833: train_loss -0.8044 +2024-11-22 19:00:00.608057: val_loss -0.7454 +2024-11-22 19:00:00.608131: Pseudo dice [0.8454] +2024-11-22 19:00:00.608208: Epoch time: 17.93 s +2024-11-22 19:00:01.524551: +2024-11-22 19:00:01.524766: Epoch 5920 +2024-11-22 19:00:01.524879: Current learning rate: 0.00297 +2024-11-22 19:00:18.753986: train_loss -0.8129 +2024-11-22 19:00:18.754263: val_loss -0.75 +2024-11-22 19:00:18.754339: Pseudo dice [0.8614] +2024-11-22 19:00:18.754418: Epoch time: 17.23 s +2024-11-22 19:00:19.664907: +2024-11-22 19:00:19.665139: Epoch 5921 +2024-11-22 19:00:19.665257: Current learning rate: 0.00297 +2024-11-22 19:00:39.483595: train_loss -0.8061 +2024-11-22 19:00:39.483819: val_loss -0.7279 +2024-11-22 19:00:39.483896: Pseudo dice [0.8391] +2024-11-22 19:00:39.483976: Epoch time: 19.82 s +2024-11-22 19:00:40.513784: +2024-11-22 19:00:40.514022: Epoch 5922 +2024-11-22 19:00:40.514139: Current learning rate: 0.00297 +2024-11-22 19:00:59.312803: train_loss -0.8016 +2024-11-22 19:00:59.313059: val_loss -0.7498 +2024-11-22 19:00:59.313138: Pseudo dice [0.8456] +2024-11-22 19:00:59.313223: Epoch time: 18.8 s +2024-11-22 19:01:00.237009: +2024-11-22 19:01:00.237228: Epoch 5923 +2024-11-22 19:01:00.237345: Current learning rate: 0.00297 +2024-11-22 19:01:19.643789: train_loss -0.7992 +2024-11-22 19:01:19.644019: val_loss -0.7137 +2024-11-22 19:01:19.644102: Pseudo dice [0.8288] +2024-11-22 19:01:19.644178: Epoch time: 19.41 s +2024-11-22 19:01:20.556720: +2024-11-22 19:01:20.556925: Epoch 5924 +2024-11-22 19:01:20.557046: Current learning rate: 0.00297 +2024-11-22 19:01:38.917718: train_loss -0.7884 +2024-11-22 19:01:38.918144: val_loss -0.7255 +2024-11-22 19:01:38.918230: Pseudo dice [0.8122] +2024-11-22 19:01:38.918306: Epoch time: 18.36 s +2024-11-22 19:01:39.909418: +2024-11-22 19:01:39.909623: Epoch 5925 +2024-11-22 19:01:39.909732: Current learning rate: 0.00297 +2024-11-22 19:01:59.007637: train_loss -0.8004 +2024-11-22 19:01:59.007870: val_loss -0.7678 +2024-11-22 19:01:59.007948: Pseudo dice [0.8404] +2024-11-22 19:01:59.008040: Epoch time: 19.1 s +2024-11-22 19:01:59.912495: +2024-11-22 19:01:59.912770: Epoch 5926 +2024-11-22 19:01:59.912886: Current learning rate: 0.00297 +2024-11-22 19:02:19.723095: train_loss -0.8026 +2024-11-22 19:02:19.723347: val_loss -0.763 +2024-11-22 19:02:19.723428: Pseudo dice [0.8465] +2024-11-22 19:02:19.723509: Epoch time: 19.81 s +2024-11-22 19:02:20.626276: +2024-11-22 19:02:20.626494: Epoch 5927 +2024-11-22 19:02:20.626605: Current learning rate: 0.00297 +2024-11-22 19:02:40.724308: train_loss -0.808 +2024-11-22 19:02:40.724528: val_loss -0.7673 +2024-11-22 19:02:40.724604: Pseudo dice [0.8655] +2024-11-22 19:02:40.724682: Epoch time: 20.1 s +2024-11-22 19:02:41.630548: +2024-11-22 19:02:41.630758: Epoch 5928 +2024-11-22 19:02:41.630868: Current learning rate: 0.00296 +2024-11-22 19:02:59.910959: train_loss -0.8118 +2024-11-22 19:02:59.911212: val_loss -0.7448 +2024-11-22 19:02:59.911290: Pseudo dice [0.8276] +2024-11-22 19:02:59.911373: Epoch time: 18.28 s +2024-11-22 19:03:00.819193: +2024-11-22 19:03:00.819431: Epoch 5929 +2024-11-22 19:03:00.819543: Current learning rate: 0.00296 +2024-11-22 19:03:18.894279: train_loss -0.8062 +2024-11-22 19:03:18.894561: val_loss -0.7829 +2024-11-22 19:03:18.894637: Pseudo dice [0.8662] +2024-11-22 19:03:18.894722: Epoch time: 18.08 s +2024-11-22 19:03:19.811904: +2024-11-22 19:03:19.812108: Epoch 5930 +2024-11-22 19:03:19.812219: Current learning rate: 0.00296 +2024-11-22 19:03:39.285472: train_loss -0.8111 +2024-11-22 19:03:39.285720: val_loss -0.7467 +2024-11-22 19:03:39.285798: Pseudo dice [0.8385] +2024-11-22 19:03:39.285885: Epoch time: 19.47 s +2024-11-22 19:03:40.196007: +2024-11-22 19:03:40.196210: Epoch 5931 +2024-11-22 19:03:40.196325: Current learning rate: 0.00296 +2024-11-22 19:03:58.909471: train_loss -0.8093 +2024-11-22 19:03:58.909694: val_loss -0.7439 +2024-11-22 19:03:58.909795: Pseudo dice [0.8581] +2024-11-22 19:03:58.909875: Epoch time: 18.71 s +2024-11-22 19:03:59.834518: +2024-11-22 19:03:59.834747: Epoch 5932 +2024-11-22 19:03:59.834865: Current learning rate: 0.00296 +2024-11-22 19:04:18.328341: train_loss -0.8082 +2024-11-22 19:04:18.328561: val_loss -0.7608 +2024-11-22 19:04:18.328640: Pseudo dice [0.8325] +2024-11-22 19:04:18.328779: Epoch time: 18.49 s +2024-11-22 19:04:19.253179: +2024-11-22 19:04:19.253384: Epoch 5933 +2024-11-22 19:04:19.253500: Current learning rate: 0.00296 +2024-11-22 19:04:37.779083: train_loss -0.808 +2024-11-22 19:04:37.779348: val_loss -0.7446 +2024-11-22 19:04:37.779465: Pseudo dice [0.8607] +2024-11-22 19:04:37.779552: Epoch time: 18.53 s +2024-11-22 19:04:38.698963: +2024-11-22 19:04:38.699186: Epoch 5934 +2024-11-22 19:04:38.699300: Current learning rate: 0.00296 +2024-11-22 19:04:57.883200: train_loss -0.7919 +2024-11-22 19:04:57.883414: val_loss -0.7514 +2024-11-22 19:04:57.883489: Pseudo dice [0.8531] +2024-11-22 19:04:57.883564: Epoch time: 19.19 s +2024-11-22 19:04:58.797223: +2024-11-22 19:04:58.797441: Epoch 5935 +2024-11-22 19:04:58.797554: Current learning rate: 0.00296 +2024-11-22 19:05:17.350855: train_loss -0.807 +2024-11-22 19:05:17.351079: val_loss -0.7636 +2024-11-22 19:05:17.351154: Pseudo dice [0.8512] +2024-11-22 19:05:17.351231: Epoch time: 18.55 s +2024-11-22 19:05:18.263059: +2024-11-22 19:05:18.263255: Epoch 5936 +2024-11-22 19:05:18.263373: Current learning rate: 0.00295 +2024-11-22 19:05:37.881358: train_loss -0.7888 +2024-11-22 19:05:37.881568: val_loss -0.7481 +2024-11-22 19:05:37.881643: Pseudo dice [0.8402] +2024-11-22 19:05:37.881717: Epoch time: 19.62 s +2024-11-22 19:05:38.829030: +2024-11-22 19:05:38.829478: Epoch 5937 +2024-11-22 19:05:38.829614: Current learning rate: 0.00295 +2024-11-22 19:05:56.970270: train_loss -0.7878 +2024-11-22 19:05:56.970512: val_loss -0.752 +2024-11-22 19:05:56.970587: Pseudo dice [0.8217] +2024-11-22 19:05:56.970672: Epoch time: 18.14 s +2024-11-22 19:05:58.281021: +2024-11-22 19:05:58.281232: Epoch 5938 +2024-11-22 19:05:58.281347: Current learning rate: 0.00295 +2024-11-22 19:06:16.288542: train_loss -0.7923 +2024-11-22 19:06:16.288775: val_loss -0.7415 +2024-11-22 19:06:16.288856: Pseudo dice [0.8466] +2024-11-22 19:06:16.288934: Epoch time: 18.01 s +2024-11-22 19:06:17.193321: +2024-11-22 19:06:17.193558: Epoch 5939 +2024-11-22 19:06:17.193676: Current learning rate: 0.00295 +2024-11-22 19:06:35.324717: train_loss -0.7975 +2024-11-22 19:06:35.324949: val_loss -0.7503 +2024-11-22 19:06:35.325033: Pseudo dice [0.8448] +2024-11-22 19:06:35.325116: Epoch time: 18.13 s +2024-11-22 19:06:36.365296: +2024-11-22 19:06:36.365531: Epoch 5940 +2024-11-22 19:06:36.365646: Current learning rate: 0.00295 +2024-11-22 19:06:56.499974: train_loss -0.7975 +2024-11-22 19:06:56.500199: val_loss -0.7602 +2024-11-22 19:06:56.500272: Pseudo dice [0.8671] +2024-11-22 19:06:56.500348: Epoch time: 20.14 s +2024-11-22 19:06:57.434695: +2024-11-22 19:06:57.434936: Epoch 5941 +2024-11-22 19:06:57.435066: Current learning rate: 0.00295 +2024-11-22 19:07:15.428847: train_loss -0.7947 +2024-11-22 19:07:15.429093: val_loss -0.7298 +2024-11-22 19:07:15.429168: Pseudo dice [0.8537] +2024-11-22 19:07:15.429252: Epoch time: 17.99 s +2024-11-22 19:07:16.335828: +2024-11-22 19:07:16.336032: Epoch 5942 +2024-11-22 19:07:16.336145: Current learning rate: 0.00295 +2024-11-22 19:07:33.716972: train_loss -0.8107 +2024-11-22 19:07:33.717211: val_loss -0.7512 +2024-11-22 19:07:33.717289: Pseudo dice [0.8479] +2024-11-22 19:07:33.717364: Epoch time: 17.38 s +2024-11-22 19:07:34.745150: +2024-11-22 19:07:34.745384: Epoch 5943 +2024-11-22 19:07:34.745496: Current learning rate: 0.00295 +2024-11-22 19:07:53.279607: train_loss -0.7968 +2024-11-22 19:07:53.279827: val_loss -0.7802 +2024-11-22 19:07:53.279900: Pseudo dice [0.8615] +2024-11-22 19:07:53.279976: Epoch time: 18.54 s +2024-11-22 19:07:54.194116: +2024-11-22 19:07:54.194336: Epoch 5944 +2024-11-22 19:07:54.194454: Current learning rate: 0.00294 +2024-11-22 19:08:12.195428: train_loss -0.8071 +2024-11-22 19:08:12.195662: val_loss -0.7212 +2024-11-22 19:08:12.195739: Pseudo dice [0.8393] +2024-11-22 19:08:12.195818: Epoch time: 18.0 s +2024-11-22 19:08:13.111969: +2024-11-22 19:08:13.112194: Epoch 5945 +2024-11-22 19:08:13.112308: Current learning rate: 0.00294 +2024-11-22 19:08:30.541044: train_loss -0.7991 +2024-11-22 19:08:30.541299: val_loss -0.7549 +2024-11-22 19:08:30.541374: Pseudo dice [0.8464] +2024-11-22 19:08:30.541456: Epoch time: 17.43 s +2024-11-22 19:08:31.468683: +2024-11-22 19:08:31.468913: Epoch 5946 +2024-11-22 19:08:31.469038: Current learning rate: 0.00294 +2024-11-22 19:08:49.221867: train_loss -0.7975 +2024-11-22 19:08:49.222100: val_loss -0.7504 +2024-11-22 19:08:49.222179: Pseudo dice [0.8693] +2024-11-22 19:08:49.222335: Epoch time: 17.75 s +2024-11-22 19:08:50.135801: +2024-11-22 19:08:50.136030: Epoch 5947 +2024-11-22 19:08:50.136154: Current learning rate: 0.00294 +2024-11-22 19:09:09.942402: train_loss -0.7989 +2024-11-22 19:09:09.942621: val_loss -0.7134 +2024-11-22 19:09:09.942696: Pseudo dice [0.8203] +2024-11-22 19:09:09.942774: Epoch time: 19.81 s +2024-11-22 19:09:10.843568: +2024-11-22 19:09:10.843971: Epoch 5948 +2024-11-22 19:09:10.844110: Current learning rate: 0.00294 +2024-11-22 19:09:29.637818: train_loss -0.8033 +2024-11-22 19:09:29.638057: val_loss -0.7408 +2024-11-22 19:09:29.638136: Pseudo dice [0.8553] +2024-11-22 19:09:29.638218: Epoch time: 18.8 s +2024-11-22 19:09:30.978074: +2024-11-22 19:09:30.978426: Epoch 5949 +2024-11-22 19:09:30.978542: Current learning rate: 0.00294 +2024-11-22 19:09:49.847228: train_loss -0.7943 +2024-11-22 19:09:49.847503: val_loss -0.7568 +2024-11-22 19:09:49.847657: Pseudo dice [0.8618] +2024-11-22 19:09:49.847745: Epoch time: 18.87 s +2024-11-22 19:09:51.367167: +2024-11-22 19:09:51.367430: Epoch 5950 +2024-11-22 19:09:51.367543: Current learning rate: 0.00294 +2024-11-22 19:10:10.808483: train_loss -0.8069 +2024-11-22 19:10:10.808698: val_loss -0.7204 +2024-11-22 19:10:10.808778: Pseudo dice [0.8523] +2024-11-22 19:10:10.808855: Epoch time: 19.44 s +2024-11-22 19:10:11.726724: +2024-11-22 19:10:11.726955: Epoch 5951 +2024-11-22 19:10:11.727076: Current learning rate: 0.00293 +2024-11-22 19:10:29.608663: train_loss -0.7944 +2024-11-22 19:10:29.608899: val_loss -0.7476 +2024-11-22 19:10:29.608979: Pseudo dice [0.8574] +2024-11-22 19:10:29.609067: Epoch time: 17.88 s +2024-11-22 19:10:30.520699: +2024-11-22 19:10:30.520916: Epoch 5952 +2024-11-22 19:10:30.521032: Current learning rate: 0.00293 +2024-11-22 19:10:48.396061: train_loss -0.7948 +2024-11-22 19:10:48.396356: val_loss -0.7765 +2024-11-22 19:10:48.396434: Pseudo dice [0.8433] +2024-11-22 19:10:48.396518: Epoch time: 17.88 s +2024-11-22 19:10:49.316008: +2024-11-22 19:10:49.316233: Epoch 5953 +2024-11-22 19:10:49.316346: Current learning rate: 0.00293 +2024-11-22 19:11:07.784302: train_loss -0.7904 +2024-11-22 19:11:07.784523: val_loss -0.7229 +2024-11-22 19:11:07.784599: Pseudo dice [0.8611] +2024-11-22 19:11:07.784677: Epoch time: 18.47 s +2024-11-22 19:11:08.696354: +2024-11-22 19:11:08.696565: Epoch 5954 +2024-11-22 19:11:08.696674: Current learning rate: 0.00293 +2024-11-22 19:11:27.385897: train_loss -0.7978 +2024-11-22 19:11:27.386128: val_loss -0.762 +2024-11-22 19:11:27.386208: Pseudo dice [0.8593] +2024-11-22 19:11:27.386288: Epoch time: 18.69 s +2024-11-22 19:11:28.318403: +2024-11-22 19:11:28.318649: Epoch 5955 +2024-11-22 19:11:28.318774: Current learning rate: 0.00293 +2024-11-22 19:11:47.290507: train_loss -0.7953 +2024-11-22 19:11:47.290746: val_loss -0.7423 +2024-11-22 19:11:47.290823: Pseudo dice [0.8516] +2024-11-22 19:11:47.290902: Epoch time: 18.97 s +2024-11-22 19:11:48.200839: +2024-11-22 19:11:48.201058: Epoch 5956 +2024-11-22 19:11:48.201174: Current learning rate: 0.00293 +2024-11-22 19:12:07.730524: train_loss -0.8051 +2024-11-22 19:12:07.730768: val_loss -0.7465 +2024-11-22 19:12:07.733060: Pseudo dice [0.8277] +2024-11-22 19:12:07.733167: Epoch time: 19.53 s +2024-11-22 19:12:08.844895: +2024-11-22 19:12:08.845119: Epoch 5957 +2024-11-22 19:12:08.845235: Current learning rate: 0.00293 +2024-11-22 19:12:27.601758: train_loss -0.8076 +2024-11-22 19:12:27.601980: val_loss -0.7577 +2024-11-22 19:12:27.602090: Pseudo dice [0.8554] +2024-11-22 19:12:27.602169: Epoch time: 18.76 s +2024-11-22 19:12:28.508509: +2024-11-22 19:12:28.508702: Epoch 5958 +2024-11-22 19:12:28.508815: Current learning rate: 0.00293 +2024-11-22 19:12:47.137041: train_loss -0.7949 +2024-11-22 19:12:47.137258: val_loss -0.7508 +2024-11-22 19:12:47.137333: Pseudo dice [0.8631] +2024-11-22 19:12:47.137411: Epoch time: 18.63 s +2024-11-22 19:12:48.051832: +2024-11-22 19:12:48.052048: Epoch 5959 +2024-11-22 19:12:48.052164: Current learning rate: 0.00292 +2024-11-22 19:13:06.858387: train_loss -0.8118 +2024-11-22 19:13:06.858608: val_loss -0.7707 +2024-11-22 19:13:06.858686: Pseudo dice [0.8571] +2024-11-22 19:13:06.858764: Epoch time: 18.81 s +2024-11-22 19:13:07.769151: +2024-11-22 19:13:07.769362: Epoch 5960 +2024-11-22 19:13:07.769479: Current learning rate: 0.00292 +2024-11-22 19:13:26.735065: train_loss -0.8123 +2024-11-22 19:13:26.735319: val_loss -0.7604 +2024-11-22 19:13:26.735396: Pseudo dice [0.8535] +2024-11-22 19:13:26.735482: Epoch time: 18.97 s +2024-11-22 19:13:28.074795: +2024-11-22 19:13:28.075022: Epoch 5961 +2024-11-22 19:13:28.075136: Current learning rate: 0.00292 +2024-11-22 19:13:47.525819: train_loss -0.8111 +2024-11-22 19:13:47.528234: val_loss -0.7657 +2024-11-22 19:13:47.528372: Pseudo dice [0.8397] +2024-11-22 19:13:47.528454: Epoch time: 19.45 s +2024-11-22 19:13:48.488530: +2024-11-22 19:13:48.488746: Epoch 5962 +2024-11-22 19:13:48.488860: Current learning rate: 0.00292 +2024-11-22 19:14:07.612911: train_loss -0.8059 +2024-11-22 19:14:07.613219: val_loss -0.7484 +2024-11-22 19:14:07.613300: Pseudo dice [0.8528] +2024-11-22 19:14:07.613379: Epoch time: 19.13 s +2024-11-22 19:14:08.523119: +2024-11-22 19:14:08.523339: Epoch 5963 +2024-11-22 19:14:08.523450: Current learning rate: 0.00292 +2024-11-22 19:14:27.364743: train_loss -0.8021 +2024-11-22 19:14:27.365041: val_loss -0.7385 +2024-11-22 19:14:27.365124: Pseudo dice [0.8144] +2024-11-22 19:14:27.365203: Epoch time: 18.84 s +2024-11-22 19:14:28.276208: +2024-11-22 19:14:28.276421: Epoch 5964 +2024-11-22 19:14:28.276530: Current learning rate: 0.00292 +2024-11-22 19:14:47.541908: train_loss -0.8093 +2024-11-22 19:14:47.542224: val_loss -0.7425 +2024-11-22 19:14:47.542300: Pseudo dice [0.8085] +2024-11-22 19:14:47.542383: Epoch time: 19.27 s +2024-11-22 19:14:48.455719: +2024-11-22 19:14:48.455964: Epoch 5965 +2024-11-22 19:14:48.456085: Current learning rate: 0.00292 +2024-11-22 19:15:06.480347: train_loss -0.8128 +2024-11-22 19:15:06.480574: val_loss -0.7356 +2024-11-22 19:15:06.480649: Pseudo dice [0.8266] +2024-11-22 19:15:06.480725: Epoch time: 18.03 s +2024-11-22 19:15:07.395747: +2024-11-22 19:15:07.395953: Epoch 5966 +2024-11-22 19:15:07.396078: Current learning rate: 0.00292 +2024-11-22 19:15:27.067463: train_loss -0.8091 +2024-11-22 19:15:27.067686: val_loss -0.7777 +2024-11-22 19:15:27.067764: Pseudo dice [0.8483] +2024-11-22 19:15:27.067841: Epoch time: 19.67 s +2024-11-22 19:15:27.982816: +2024-11-22 19:15:27.983018: Epoch 5967 +2024-11-22 19:15:27.983132: Current learning rate: 0.00291 +2024-11-22 19:15:46.577624: train_loss -0.8066 +2024-11-22 19:15:46.578552: val_loss -0.7436 +2024-11-22 19:15:46.578727: Pseudo dice [0.8628] +2024-11-22 19:15:46.578816: Epoch time: 18.6 s +2024-11-22 19:15:47.490994: +2024-11-22 19:15:47.491204: Epoch 5968 +2024-11-22 19:15:47.491317: Current learning rate: 0.00291 +2024-11-22 19:16:05.258829: train_loss -0.8055 +2024-11-22 19:16:05.259087: val_loss -0.7821 +2024-11-22 19:16:05.259160: Pseudo dice [0.8728] +2024-11-22 19:16:05.259243: Epoch time: 17.77 s +2024-11-22 19:16:06.349048: +2024-11-22 19:16:06.349258: Epoch 5969 +2024-11-22 19:16:06.349372: Current learning rate: 0.00291 +2024-11-22 19:16:24.924015: train_loss -0.8076 +2024-11-22 19:16:24.924230: val_loss -0.7508 +2024-11-22 19:16:24.924307: Pseudo dice [0.8388] +2024-11-22 19:16:24.924387: Epoch time: 18.58 s +2024-11-22 19:16:26.045878: +2024-11-22 19:16:26.046153: Epoch 5970 +2024-11-22 19:16:26.046265: Current learning rate: 0.00291 +2024-11-22 19:16:43.995400: train_loss -0.8079 +2024-11-22 19:16:43.995618: val_loss -0.7662 +2024-11-22 19:16:43.995695: Pseudo dice [0.8504] +2024-11-22 19:16:43.995770: Epoch time: 17.95 s +2024-11-22 19:16:44.912747: +2024-11-22 19:16:44.913000: Epoch 5971 +2024-11-22 19:16:44.913120: Current learning rate: 0.00291 +2024-11-22 19:17:03.983654: train_loss -0.8097 +2024-11-22 19:17:03.983892: val_loss -0.7716 +2024-11-22 19:17:03.986444: Pseudo dice [0.8622] +2024-11-22 19:17:03.986599: Epoch time: 19.07 s +2024-11-22 19:17:04.918120: +2024-11-22 19:17:04.918320: Epoch 5972 +2024-11-22 19:17:04.918437: Current learning rate: 0.00291 +2024-11-22 19:17:23.336064: train_loss -0.8113 +2024-11-22 19:17:23.336321: val_loss -0.756 +2024-11-22 19:17:23.336398: Pseudo dice [0.8574] +2024-11-22 19:17:23.336479: Epoch time: 18.42 s +2024-11-22 19:17:24.262693: +2024-11-22 19:17:24.262914: Epoch 5973 +2024-11-22 19:17:24.263038: Current learning rate: 0.00291 +2024-11-22 19:17:43.793586: train_loss -0.8061 +2024-11-22 19:17:43.793797: val_loss -0.7829 +2024-11-22 19:17:43.793869: Pseudo dice [0.8627] +2024-11-22 19:17:43.793946: Epoch time: 19.53 s +2024-11-22 19:17:44.703343: +2024-11-22 19:17:44.703563: Epoch 5974 +2024-11-22 19:17:44.703676: Current learning rate: 0.00291 +2024-11-22 19:18:03.599645: train_loss -0.8095 +2024-11-22 19:18:03.599869: val_loss -0.7545 +2024-11-22 19:18:03.599944: Pseudo dice [0.8377] +2024-11-22 19:18:03.600028: Epoch time: 18.9 s +2024-11-22 19:18:04.512577: +2024-11-22 19:18:04.512834: Epoch 5975 +2024-11-22 19:18:04.512953: Current learning rate: 0.0029 +2024-11-22 19:18:22.695096: train_loss -0.8167 +2024-11-22 19:18:22.695349: val_loss -0.7447 +2024-11-22 19:18:22.695429: Pseudo dice [0.8483] +2024-11-22 19:18:22.695509: Epoch time: 18.18 s +2024-11-22 19:18:23.610208: +2024-11-22 19:18:23.610430: Epoch 5976 +2024-11-22 19:18:23.610542: Current learning rate: 0.0029 +2024-11-22 19:18:42.264165: train_loss -0.8108 +2024-11-22 19:18:42.264385: val_loss -0.7603 +2024-11-22 19:18:42.264460: Pseudo dice [0.8583] +2024-11-22 19:18:42.264536: Epoch time: 18.65 s +2024-11-22 19:18:43.368670: +2024-11-22 19:18:43.368891: Epoch 5977 +2024-11-22 19:18:43.369014: Current learning rate: 0.0029 +2024-11-22 19:19:01.881977: train_loss -0.8043 +2024-11-22 19:19:01.882200: val_loss -0.7698 +2024-11-22 19:19:01.882283: Pseudo dice [0.8586] +2024-11-22 19:19:01.882365: Epoch time: 18.51 s +2024-11-22 19:19:02.789164: +2024-11-22 19:19:02.789376: Epoch 5978 +2024-11-22 19:19:02.789491: Current learning rate: 0.0029 +2024-11-22 19:19:20.575197: train_loss -0.8114 +2024-11-22 19:19:20.575428: val_loss -0.765 +2024-11-22 19:19:20.575509: Pseudo dice [0.8569] +2024-11-22 19:19:20.575588: Epoch time: 17.79 s +2024-11-22 19:19:21.481019: +2024-11-22 19:19:21.481296: Epoch 5979 +2024-11-22 19:19:21.481411: Current learning rate: 0.0029 +2024-11-22 19:19:40.018331: train_loss -0.8107 +2024-11-22 19:19:40.018604: val_loss -0.7715 +2024-11-22 19:19:40.018689: Pseudo dice [0.8556] +2024-11-22 19:19:40.018770: Epoch time: 18.54 s +2024-11-22 19:19:40.929312: +2024-11-22 19:19:40.929533: Epoch 5980 +2024-11-22 19:19:40.929647: Current learning rate: 0.0029 +2024-11-22 19:20:00.106473: train_loss -0.8128 +2024-11-22 19:20:00.106699: val_loss -0.7572 +2024-11-22 19:20:00.106780: Pseudo dice [0.8353] +2024-11-22 19:20:00.106864: Epoch time: 19.18 s +2024-11-22 19:20:01.064690: +2024-11-22 19:20:01.064891: Epoch 5981 +2024-11-22 19:20:01.065006: Current learning rate: 0.0029 +2024-11-22 19:20:18.213798: train_loss -0.801 +2024-11-22 19:20:18.214022: val_loss -0.7625 +2024-11-22 19:20:18.214097: Pseudo dice [0.8405] +2024-11-22 19:20:18.214176: Epoch time: 17.15 s +2024-11-22 19:20:19.122577: +2024-11-22 19:20:19.122776: Epoch 5982 +2024-11-22 19:20:19.122892: Current learning rate: 0.00289 +2024-11-22 19:20:36.704843: train_loss -0.8046 +2024-11-22 19:20:36.705079: val_loss -0.7682 +2024-11-22 19:20:36.705158: Pseudo dice [0.8392] +2024-11-22 19:20:36.705238: Epoch time: 17.58 s +2024-11-22 19:20:37.595034: +2024-11-22 19:20:37.595485: Epoch 5983 +2024-11-22 19:20:37.595666: Current learning rate: 0.00289 +2024-11-22 19:20:55.934791: train_loss -0.8126 +2024-11-22 19:20:55.937216: val_loss -0.7592 +2024-11-22 19:20:55.937310: Pseudo dice [0.8662] +2024-11-22 19:20:55.937394: Epoch time: 18.34 s +2024-11-22 19:20:57.186796: +2024-11-22 19:20:57.187012: Epoch 5984 +2024-11-22 19:20:57.187122: Current learning rate: 0.00289 +2024-11-22 19:21:16.137895: train_loss -0.8085 +2024-11-22 19:21:16.138368: val_loss -0.7419 +2024-11-22 19:21:16.138467: Pseudo dice [0.8639] +2024-11-22 19:21:16.138546: Epoch time: 18.95 s +2024-11-22 19:21:17.045332: +2024-11-22 19:21:17.045553: Epoch 5985 +2024-11-22 19:21:17.045665: Current learning rate: 0.00289 +2024-11-22 19:21:35.425529: train_loss -0.8092 +2024-11-22 19:21:35.425749: val_loss -0.7754 +2024-11-22 19:21:35.425824: Pseudo dice [0.8519] +2024-11-22 19:21:35.425906: Epoch time: 18.38 s +2024-11-22 19:21:36.326683: +2024-11-22 19:21:36.326900: Epoch 5986 +2024-11-22 19:21:36.327019: Current learning rate: 0.00289 +2024-11-22 19:21:55.100896: train_loss -0.8131 +2024-11-22 19:21:55.101227: val_loss -0.7373 +2024-11-22 19:21:55.101308: Pseudo dice [0.8486] +2024-11-22 19:21:55.101391: Epoch time: 18.78 s +2024-11-22 19:21:56.007565: +2024-11-22 19:21:56.007770: Epoch 5987 +2024-11-22 19:21:56.007877: Current learning rate: 0.00289 +2024-11-22 19:22:15.068970: train_loss -0.812 +2024-11-22 19:22:15.069191: val_loss -0.7436 +2024-11-22 19:22:15.069264: Pseudo dice [0.8429] +2024-11-22 19:22:15.069350: Epoch time: 19.06 s +2024-11-22 19:22:16.006653: +2024-11-22 19:22:16.006859: Epoch 5988 +2024-11-22 19:22:16.006972: Current learning rate: 0.00289 +2024-11-22 19:22:34.965835: train_loss -0.8171 +2024-11-22 19:22:34.966070: val_loss -0.7459 +2024-11-22 19:22:34.966147: Pseudo dice [0.8483] +2024-11-22 19:22:34.966225: Epoch time: 18.96 s +2024-11-22 19:22:35.886032: +2024-11-22 19:22:35.886244: Epoch 5989 +2024-11-22 19:22:35.886353: Current learning rate: 0.00289 +2024-11-22 19:22:55.873645: train_loss -0.806 +2024-11-22 19:22:55.873930: val_loss -0.774 +2024-11-22 19:22:55.874016: Pseudo dice [0.8594] +2024-11-22 19:22:55.874097: Epoch time: 19.99 s +2024-11-22 19:22:56.784677: +2024-11-22 19:22:56.784887: Epoch 5990 +2024-11-22 19:22:56.785017: Current learning rate: 0.00288 +2024-11-22 19:23:17.624372: train_loss -0.8008 +2024-11-22 19:23:17.624676: val_loss -0.7547 +2024-11-22 19:23:17.624751: Pseudo dice [0.8506] +2024-11-22 19:23:17.624827: Epoch time: 20.84 s +2024-11-22 19:23:18.532863: +2024-11-22 19:23:18.533067: Epoch 5991 +2024-11-22 19:23:18.533180: Current learning rate: 0.00288 +2024-11-22 19:23:37.632528: train_loss -0.7996 +2024-11-22 19:23:37.632745: val_loss -0.7445 +2024-11-22 19:23:37.632821: Pseudo dice [0.8484] +2024-11-22 19:23:37.632897: Epoch time: 19.1 s +2024-11-22 19:23:38.538705: +2024-11-22 19:23:38.539033: Epoch 5992 +2024-11-22 19:23:38.539150: Current learning rate: 0.00288 +2024-11-22 19:23:57.913162: train_loss -0.7947 +2024-11-22 19:23:57.913375: val_loss -0.7325 +2024-11-22 19:23:57.913450: Pseudo dice [0.8277] +2024-11-22 19:23:57.913529: Epoch time: 19.38 s +2024-11-22 19:23:58.820091: +2024-11-22 19:23:58.820294: Epoch 5993 +2024-11-22 19:23:58.820409: Current learning rate: 0.00288 +2024-11-22 19:24:17.541272: train_loss -0.8121 +2024-11-22 19:24:17.541521: val_loss -0.75 +2024-11-22 19:24:17.541598: Pseudo dice [0.8561] +2024-11-22 19:24:17.541683: Epoch time: 18.72 s +2024-11-22 19:24:18.453344: +2024-11-22 19:24:18.453541: Epoch 5994 +2024-11-22 19:24:18.453655: Current learning rate: 0.00288 +2024-11-22 19:24:36.307596: train_loss -0.8092 +2024-11-22 19:24:36.307790: val_loss -0.7656 +2024-11-22 19:24:36.307867: Pseudo dice [0.8552] +2024-11-22 19:24:36.307947: Epoch time: 17.86 s +2024-11-22 19:24:37.242971: +2024-11-22 19:24:37.243188: Epoch 5995 +2024-11-22 19:24:37.243304: Current learning rate: 0.00288 +2024-11-22 19:24:56.520778: train_loss -0.8136 +2024-11-22 19:24:56.521030: val_loss -0.7797 +2024-11-22 19:24:56.521107: Pseudo dice [0.8318] +2024-11-22 19:24:56.521183: Epoch time: 19.28 s +2024-11-22 19:24:57.430261: +2024-11-22 19:24:57.430505: Epoch 5996 +2024-11-22 19:24:57.430620: Current learning rate: 0.00288 +2024-11-22 19:25:16.583859: train_loss -0.8082 +2024-11-22 19:25:16.584104: val_loss -0.7267 +2024-11-22 19:25:16.584190: Pseudo dice [0.8273] +2024-11-22 19:25:16.584276: Epoch time: 19.15 s +2024-11-22 19:25:17.537860: +2024-11-22 19:25:17.538071: Epoch 5997 +2024-11-22 19:25:17.538184: Current learning rate: 0.00288 +2024-11-22 19:25:36.187623: train_loss -0.796 +2024-11-22 19:25:36.187873: val_loss -0.7554 +2024-11-22 19:25:36.187952: Pseudo dice [0.8502] +2024-11-22 19:25:36.188038: Epoch time: 18.65 s +2024-11-22 19:25:37.103886: +2024-11-22 19:25:37.104118: Epoch 5998 +2024-11-22 19:25:37.104229: Current learning rate: 0.00287 +2024-11-22 19:25:56.291802: train_loss -0.7994 +2024-11-22 19:25:56.292039: val_loss -0.7397 +2024-11-22 19:25:56.292118: Pseudo dice [0.8296] +2024-11-22 19:25:56.292195: Epoch time: 19.19 s +2024-11-22 19:25:57.209363: +2024-11-22 19:25:57.209570: Epoch 5999 +2024-11-22 19:25:57.209685: Current learning rate: 0.00287 +2024-11-22 19:26:16.008259: train_loss -0.8038 +2024-11-22 19:26:16.008488: val_loss -0.7297 +2024-11-22 19:26:16.008562: Pseudo dice [0.8289] +2024-11-22 19:26:16.008636: Epoch time: 18.8 s +2024-11-22 19:26:17.225311: +2024-11-22 19:26:17.225540: Epoch 6000 +2024-11-22 19:26:17.225655: Current learning rate: 0.00287 +2024-11-22 19:26:36.442271: train_loss -0.8024 +2024-11-22 19:26:36.442498: val_loss -0.7444 +2024-11-22 19:26:36.442572: Pseudo dice [0.8382] +2024-11-22 19:26:36.442654: Epoch time: 19.22 s +2024-11-22 19:26:37.349431: +2024-11-22 19:26:37.349653: Epoch 6001 +2024-11-22 19:26:37.349768: Current learning rate: 0.00287 +2024-11-22 19:26:55.926582: train_loss -0.8026 +2024-11-22 19:26:55.926872: val_loss -0.7491 +2024-11-22 19:26:55.926953: Pseudo dice [0.8275] +2024-11-22 19:26:55.927041: Epoch time: 18.58 s +2024-11-22 19:26:56.840008: +2024-11-22 19:26:56.840197: Epoch 6002 +2024-11-22 19:26:56.840515: Current learning rate: 0.00287 +2024-11-22 19:27:15.338267: train_loss -0.796 +2024-11-22 19:27:15.338493: val_loss -0.7418 +2024-11-22 19:27:15.338572: Pseudo dice [0.8352] +2024-11-22 19:27:15.338649: Epoch time: 18.5 s +2024-11-22 19:27:16.247653: +2024-11-22 19:27:16.247867: Epoch 6003 +2024-11-22 19:27:16.247980: Current learning rate: 0.00287 +2024-11-22 19:27:34.881176: train_loss -0.8108 +2024-11-22 19:27:34.883555: val_loss -0.7644 +2024-11-22 19:27:34.883741: Pseudo dice [0.859] +2024-11-22 19:27:34.883824: Epoch time: 18.63 s +2024-11-22 19:27:35.856640: +2024-11-22 19:27:35.856947: Epoch 6004 +2024-11-22 19:27:35.857082: Current learning rate: 0.00287 +2024-11-22 19:27:54.880561: train_loss -0.8182 +2024-11-22 19:27:54.880816: val_loss -0.7481 +2024-11-22 19:27:54.880894: Pseudo dice [0.8579] +2024-11-22 19:27:54.886125: Epoch time: 19.02 s +2024-11-22 19:27:55.966471: +2024-11-22 19:27:55.966825: Epoch 6005 +2024-11-22 19:27:55.966937: Current learning rate: 0.00287 +2024-11-22 19:28:15.899133: train_loss -0.8032 +2024-11-22 19:28:15.899348: val_loss -0.7584 +2024-11-22 19:28:15.899428: Pseudo dice [0.8389] +2024-11-22 19:28:15.899505: Epoch time: 19.93 s +2024-11-22 19:28:17.198017: +2024-11-22 19:28:17.198227: Epoch 6006 +2024-11-22 19:28:17.198344: Current learning rate: 0.00286 +2024-11-22 19:28:35.209834: train_loss -0.7977 +2024-11-22 19:28:35.210094: val_loss -0.7203 +2024-11-22 19:28:35.210173: Pseudo dice [0.8249] +2024-11-22 19:28:35.210253: Epoch time: 18.01 s +2024-11-22 19:28:36.114386: +2024-11-22 19:28:36.114607: Epoch 6007 +2024-11-22 19:28:36.114719: Current learning rate: 0.00286 +2024-11-22 19:28:54.495288: train_loss -0.8053 +2024-11-22 19:28:54.495503: val_loss -0.7329 +2024-11-22 19:28:54.495578: Pseudo dice [0.8578] +2024-11-22 19:28:54.495656: Epoch time: 18.38 s +2024-11-22 19:28:55.407407: +2024-11-22 19:28:55.407650: Epoch 6008 +2024-11-22 19:28:55.407767: Current learning rate: 0.00286 +2024-11-22 19:29:13.216133: train_loss -0.8124 +2024-11-22 19:29:13.221558: val_loss -0.7675 +2024-11-22 19:29:13.221683: Pseudo dice [0.8442] +2024-11-22 19:29:13.221768: Epoch time: 17.81 s +2024-11-22 19:29:14.475514: +2024-11-22 19:29:14.475733: Epoch 6009 +2024-11-22 19:29:14.475853: Current learning rate: 0.00286 +2024-11-22 19:29:32.277778: train_loss -0.8068 +2024-11-22 19:29:32.278002: val_loss -0.7623 +2024-11-22 19:29:32.278077: Pseudo dice [0.833] +2024-11-22 19:29:32.278153: Epoch time: 17.8 s +2024-11-22 19:29:33.201205: +2024-11-22 19:29:33.201526: Epoch 6010 +2024-11-22 19:29:33.201644: Current learning rate: 0.00286 +2024-11-22 19:29:50.947399: train_loss -0.8107 +2024-11-22 19:29:50.947645: val_loss -0.7484 +2024-11-22 19:29:50.947720: Pseudo dice [0.8455] +2024-11-22 19:29:50.947799: Epoch time: 17.75 s +2024-11-22 19:29:51.874701: +2024-11-22 19:29:51.874902: Epoch 6011 +2024-11-22 19:29:51.875023: Current learning rate: 0.00286 +2024-11-22 19:30:10.706679: train_loss -0.8086 +2024-11-22 19:30:10.706903: val_loss -0.7428 +2024-11-22 19:30:10.706979: Pseudo dice [0.8404] +2024-11-22 19:30:10.707067: Epoch time: 18.83 s +2024-11-22 19:30:11.627937: +2024-11-22 19:30:11.628222: Epoch 6012 +2024-11-22 19:30:11.628340: Current learning rate: 0.00286 +2024-11-22 19:30:30.550653: train_loss -0.7993 +2024-11-22 19:30:30.550898: val_loss -0.7602 +2024-11-22 19:30:30.550978: Pseudo dice [0.8466] +2024-11-22 19:30:30.551068: Epoch time: 18.92 s +2024-11-22 19:30:31.466831: +2024-11-22 19:30:31.467036: Epoch 6013 +2024-11-22 19:30:31.467146: Current learning rate: 0.00285 +2024-11-22 19:30:50.519129: train_loss -0.7998 +2024-11-22 19:30:50.519390: val_loss -0.7333 +2024-11-22 19:30:50.519469: Pseudo dice [0.8571] +2024-11-22 19:30:50.519547: Epoch time: 19.05 s +2024-11-22 19:30:51.457799: +2024-11-22 19:30:51.457997: Epoch 6014 +2024-11-22 19:30:51.458108: Current learning rate: 0.00285 +2024-11-22 19:31:10.392531: train_loss -0.8014 +2024-11-22 19:31:10.392751: val_loss -0.7639 +2024-11-22 19:31:10.392827: Pseudo dice [0.8395] +2024-11-22 19:31:10.392903: Epoch time: 18.94 s +2024-11-22 19:31:11.310380: +2024-11-22 19:31:11.310573: Epoch 6015 +2024-11-22 19:31:11.310686: Current learning rate: 0.00285 +2024-11-22 19:31:30.588785: train_loss -0.7983 +2024-11-22 19:31:30.589052: val_loss -0.7638 +2024-11-22 19:31:30.594338: Pseudo dice [0.8484] +2024-11-22 19:31:30.594432: Epoch time: 19.28 s +2024-11-22 19:31:31.560845: +2024-11-22 19:31:31.561044: Epoch 6016 +2024-11-22 19:31:31.561155: Current learning rate: 0.00285 +2024-11-22 19:31:50.000381: train_loss -0.8003 +2024-11-22 19:31:50.000607: val_loss -0.749 +2024-11-22 19:31:50.000680: Pseudo dice [0.8611] +2024-11-22 19:31:50.000757: Epoch time: 18.44 s +2024-11-22 19:31:50.920056: +2024-11-22 19:31:50.920253: Epoch 6017 +2024-11-22 19:31:50.920368: Current learning rate: 0.00285 +2024-11-22 19:32:10.223738: train_loss -0.8078 +2024-11-22 19:32:10.223968: val_loss -0.752 +2024-11-22 19:32:10.224051: Pseudo dice [0.8236] +2024-11-22 19:32:10.224131: Epoch time: 19.3 s +2024-11-22 19:32:11.525949: +2024-11-22 19:32:11.526178: Epoch 6018 +2024-11-22 19:32:11.526293: Current learning rate: 0.00285 +2024-11-22 19:32:31.253341: train_loss -0.8081 +2024-11-22 19:32:31.253596: val_loss -0.7568 +2024-11-22 19:32:31.258909: Pseudo dice [0.8622] +2024-11-22 19:32:31.259044: Epoch time: 19.73 s +2024-11-22 19:32:32.182498: +2024-11-22 19:32:32.182733: Epoch 6019 +2024-11-22 19:32:32.182848: Current learning rate: 0.00285 +2024-11-22 19:32:51.383689: train_loss -0.8076 +2024-11-22 19:32:51.383909: val_loss -0.7372 +2024-11-22 19:32:51.383984: Pseudo dice [0.8447] +2024-11-22 19:32:51.384067: Epoch time: 19.2 s +2024-11-22 19:32:52.353000: +2024-11-22 19:32:52.353201: Epoch 6020 +2024-11-22 19:32:52.353312: Current learning rate: 0.00285 +2024-11-22 19:33:11.694657: train_loss -0.8086 +2024-11-22 19:33:11.694862: val_loss -0.7274 +2024-11-22 19:33:11.695057: Pseudo dice [0.828] +2024-11-22 19:33:11.695136: Epoch time: 19.34 s +2024-11-22 19:33:12.685550: +2024-11-22 19:33:12.685751: Epoch 6021 +2024-11-22 19:33:12.685862: Current learning rate: 0.00284 +2024-11-22 19:33:32.136956: train_loss -0.807 +2024-11-22 19:33:32.137182: val_loss -0.7611 +2024-11-22 19:33:32.137254: Pseudo dice [0.8408] +2024-11-22 19:33:32.137328: Epoch time: 19.45 s +2024-11-22 19:33:33.087253: +2024-11-22 19:33:33.087591: Epoch 6022 +2024-11-22 19:33:33.087703: Current learning rate: 0.00284 +2024-11-22 19:33:51.882588: train_loss -0.8026 +2024-11-22 19:33:51.888048: val_loss -0.7395 +2024-11-22 19:33:51.888167: Pseudo dice [0.8338] +2024-11-22 19:33:51.888262: Epoch time: 18.8 s +2024-11-22 19:33:52.992683: +2024-11-22 19:33:52.992869: Epoch 6023 +2024-11-22 19:33:52.992981: Current learning rate: 0.00284 +2024-11-22 19:34:11.235075: train_loss -0.8226 +2024-11-22 19:34:11.235295: val_loss -0.7517 +2024-11-22 19:34:11.235371: Pseudo dice [0.8324] +2024-11-22 19:34:11.235447: Epoch time: 18.24 s +2024-11-22 19:34:12.149798: +2024-11-22 19:34:12.150009: Epoch 6024 +2024-11-22 19:34:12.150121: Current learning rate: 0.00284 +2024-11-22 19:34:29.852755: train_loss -0.8157 +2024-11-22 19:34:29.852983: val_loss -0.7397 +2024-11-22 19:34:29.853072: Pseudo dice [0.8405] +2024-11-22 19:34:29.853149: Epoch time: 17.7 s +2024-11-22 19:34:30.768064: +2024-11-22 19:34:30.768287: Epoch 6025 +2024-11-22 19:34:30.768401: Current learning rate: 0.00284 +2024-11-22 19:34:49.732115: train_loss -0.8028 +2024-11-22 19:34:49.732326: val_loss -0.7267 +2024-11-22 19:34:49.732402: Pseudo dice [0.8497] +2024-11-22 19:34:49.732480: Epoch time: 18.96 s +2024-11-22 19:34:50.642712: +2024-11-22 19:34:50.642945: Epoch 6026 +2024-11-22 19:34:50.643076: Current learning rate: 0.00284 +2024-11-22 19:35:08.710040: train_loss -0.8069 +2024-11-22 19:35:08.710306: val_loss -0.7725 +2024-11-22 19:35:08.710389: Pseudo dice [0.865] +2024-11-22 19:35:08.710474: Epoch time: 18.07 s +2024-11-22 19:35:09.620968: +2024-11-22 19:35:09.621215: Epoch 6027 +2024-11-22 19:35:09.621325: Current learning rate: 0.00284 +2024-11-22 19:35:27.914163: train_loss -0.8063 +2024-11-22 19:35:27.914392: val_loss -0.7541 +2024-11-22 19:35:27.916704: Pseudo dice [0.8651] +2024-11-22 19:35:27.916811: Epoch time: 18.29 s +2024-11-22 19:35:29.199342: +2024-11-22 19:35:29.199536: Epoch 6028 +2024-11-22 19:35:29.199843: Current learning rate: 0.00284 +2024-11-22 19:35:47.054394: train_loss -0.8005 +2024-11-22 19:35:47.054646: val_loss -0.7606 +2024-11-22 19:35:47.054719: Pseudo dice [0.8489] +2024-11-22 19:35:47.054798: Epoch time: 17.86 s +2024-11-22 19:35:47.979884: +2024-11-22 19:35:47.980167: Epoch 6029 +2024-11-22 19:35:47.980283: Current learning rate: 0.00283 +2024-11-22 19:36:06.783631: train_loss -0.8095 +2024-11-22 19:36:06.783876: val_loss -0.732 +2024-11-22 19:36:06.783953: Pseudo dice [0.857] +2024-11-22 19:36:06.784040: Epoch time: 18.8 s +2024-11-22 19:36:07.683511: +2024-11-22 19:36:07.683775: Epoch 6030 +2024-11-22 19:36:07.683929: Current learning rate: 0.00283 +2024-11-22 19:36:27.979693: train_loss -0.8117 +2024-11-22 19:36:27.979915: val_loss -0.7581 +2024-11-22 19:36:27.979999: Pseudo dice [0.8551] +2024-11-22 19:36:27.980083: Epoch time: 20.3 s +2024-11-22 19:36:28.884743: +2024-11-22 19:36:28.884953: Epoch 6031 +2024-11-22 19:36:28.885072: Current learning rate: 0.00283 +2024-11-22 19:36:48.168020: train_loss -0.8098 +2024-11-22 19:36:48.168239: val_loss -0.7368 +2024-11-22 19:36:48.168318: Pseudo dice [0.8551] +2024-11-22 19:36:48.170554: Epoch time: 19.28 s +2024-11-22 19:36:49.170983: +2024-11-22 19:36:49.171225: Epoch 6032 +2024-11-22 19:36:49.171347: Current learning rate: 0.00283 +2024-11-22 19:37:08.083960: train_loss -0.8179 +2024-11-22 19:37:08.084187: val_loss -0.7489 +2024-11-22 19:37:08.084264: Pseudo dice [0.8407] +2024-11-22 19:37:08.086231: Epoch time: 18.91 s +2024-11-22 19:37:09.113586: +2024-11-22 19:37:09.113796: Epoch 6033 +2024-11-22 19:37:09.113916: Current learning rate: 0.00283 +2024-11-22 19:37:27.325119: train_loss -0.805 +2024-11-22 19:37:27.325370: val_loss -0.759 +2024-11-22 19:37:27.325457: Pseudo dice [0.84] +2024-11-22 19:37:27.325543: Epoch time: 18.21 s +2024-11-22 19:37:28.302609: +2024-11-22 19:37:28.302832: Epoch 6034 +2024-11-22 19:37:28.302947: Current learning rate: 0.00283 +2024-11-22 19:37:47.589007: train_loss -0.8089 +2024-11-22 19:37:47.589228: val_loss -0.771 +2024-11-22 19:37:47.589308: Pseudo dice [0.8531] +2024-11-22 19:37:47.589387: Epoch time: 19.29 s +2024-11-22 19:37:48.542343: +2024-11-22 19:37:48.542592: Epoch 6035 +2024-11-22 19:37:48.542711: Current learning rate: 0.00283 +2024-11-22 19:38:06.730356: train_loss -0.807 +2024-11-22 19:38:06.730571: val_loss -0.7467 +2024-11-22 19:38:06.730643: Pseudo dice [0.825] +2024-11-22 19:38:06.730719: Epoch time: 18.19 s +2024-11-22 19:38:07.651249: +2024-11-22 19:38:07.651520: Epoch 6036 +2024-11-22 19:38:07.651632: Current learning rate: 0.00283 +2024-11-22 19:38:26.338398: train_loss -0.8052 +2024-11-22 19:38:26.338614: val_loss -0.7577 +2024-11-22 19:38:26.338691: Pseudo dice [0.8571] +2024-11-22 19:38:26.338770: Epoch time: 18.69 s +2024-11-22 19:38:27.246013: +2024-11-22 19:38:27.246226: Epoch 6037 +2024-11-22 19:38:27.246344: Current learning rate: 0.00282 +2024-11-22 19:38:45.251084: train_loss -0.8113 +2024-11-22 19:38:45.251331: val_loss -0.7528 +2024-11-22 19:38:45.251405: Pseudo dice [0.8473] +2024-11-22 19:38:45.251488: Epoch time: 18.01 s +2024-11-22 19:38:46.147764: +2024-11-22 19:38:46.147982: Epoch 6038 +2024-11-22 19:38:46.148099: Current learning rate: 0.00282 +2024-11-22 19:39:04.682752: train_loss -0.7922 +2024-11-22 19:39:04.682979: val_loss -0.728 +2024-11-22 19:39:04.683060: Pseudo dice [0.8419] +2024-11-22 19:39:04.683136: Epoch time: 18.54 s +2024-11-22 19:39:05.754002: +2024-11-22 19:39:05.754214: Epoch 6039 +2024-11-22 19:39:05.754330: Current learning rate: 0.00282 +2024-11-22 19:39:24.120998: train_loss -0.8022 +2024-11-22 19:39:24.121217: val_loss -0.7332 +2024-11-22 19:39:24.121292: Pseudo dice [0.8539] +2024-11-22 19:39:24.121368: Epoch time: 18.37 s +2024-11-22 19:39:25.048751: +2024-11-22 19:39:25.048951: Epoch 6040 +2024-11-22 19:39:25.049065: Current learning rate: 0.00282 +2024-11-22 19:39:44.714633: train_loss -0.8015 +2024-11-22 19:39:44.714853: val_loss -0.7431 +2024-11-22 19:39:44.714928: Pseudo dice [0.8251] +2024-11-22 19:39:44.715019: Epoch time: 19.67 s +2024-11-22 19:39:46.039508: +2024-11-22 19:39:46.039774: Epoch 6041 +2024-11-22 19:39:46.039905: Current learning rate: 0.00282 +2024-11-22 19:40:04.797973: train_loss -0.8138 +2024-11-22 19:40:04.798221: val_loss -0.7755 +2024-11-22 19:40:04.798303: Pseudo dice [0.8555] +2024-11-22 19:40:04.798383: Epoch time: 18.76 s +2024-11-22 19:40:05.691655: +2024-11-22 19:40:05.691873: Epoch 6042 +2024-11-22 19:40:05.691987: Current learning rate: 0.00282 +2024-11-22 19:40:23.409041: train_loss -0.8068 +2024-11-22 19:40:23.409268: val_loss -0.7738 +2024-11-22 19:40:23.409344: Pseudo dice [0.8581] +2024-11-22 19:40:23.409424: Epoch time: 17.72 s +2024-11-22 19:40:24.323714: +2024-11-22 19:40:24.323957: Epoch 6043 +2024-11-22 19:40:24.324078: Current learning rate: 0.00282 +2024-11-22 19:40:43.333031: train_loss -0.8066 +2024-11-22 19:40:43.333290: val_loss -0.7478 +2024-11-22 19:40:43.333371: Pseudo dice [0.8502] +2024-11-22 19:40:43.333464: Epoch time: 19.01 s +2024-11-22 19:40:44.264444: +2024-11-22 19:40:44.264691: Epoch 6044 +2024-11-22 19:40:44.264805: Current learning rate: 0.00281 +2024-11-22 19:41:03.088033: train_loss -0.8061 +2024-11-22 19:41:03.088287: val_loss -0.7384 +2024-11-22 19:41:03.088370: Pseudo dice [0.8296] +2024-11-22 19:41:03.088453: Epoch time: 18.82 s +2024-11-22 19:41:04.011446: +2024-11-22 19:41:04.011672: Epoch 6045 +2024-11-22 19:41:04.011783: Current learning rate: 0.00281 +2024-11-22 19:41:22.300146: train_loss -0.7911 +2024-11-22 19:41:22.300367: val_loss -0.7337 +2024-11-22 19:41:22.300449: Pseudo dice [0.8508] +2024-11-22 19:41:22.300535: Epoch time: 18.29 s +2024-11-22 19:41:23.219185: +2024-11-22 19:41:23.219478: Epoch 6046 +2024-11-22 19:41:23.219594: Current learning rate: 0.00281 +2024-11-22 19:41:40.146154: train_loss -0.7971 +2024-11-22 19:41:40.151546: val_loss -0.7776 +2024-11-22 19:41:40.151657: Pseudo dice [0.8484] +2024-11-22 19:41:40.151741: Epoch time: 16.93 s +2024-11-22 19:41:41.438835: +2024-11-22 19:41:41.439058: Epoch 6047 +2024-11-22 19:41:41.439171: Current learning rate: 0.00281 +2024-11-22 19:42:00.331374: train_loss -0.7812 +2024-11-22 19:42:00.331597: val_loss -0.7594 +2024-11-22 19:42:00.331668: Pseudo dice [0.853] +2024-11-22 19:42:00.331745: Epoch time: 18.89 s +2024-11-22 19:42:01.322662: +2024-11-22 19:42:01.322925: Epoch 6048 +2024-11-22 19:42:01.323046: Current learning rate: 0.00281 +2024-11-22 19:42:20.301614: train_loss -0.7937 +2024-11-22 19:42:20.301870: val_loss -0.7358 +2024-11-22 19:42:20.301948: Pseudo dice [0.8352] +2024-11-22 19:42:20.307209: Epoch time: 18.98 s +2024-11-22 19:42:21.335670: +2024-11-22 19:42:21.335901: Epoch 6049 +2024-11-22 19:42:21.336020: Current learning rate: 0.00281 +2024-11-22 19:42:40.270848: train_loss -0.8047 +2024-11-22 19:42:40.271078: val_loss -0.761 +2024-11-22 19:42:40.271158: Pseudo dice [0.8616] +2024-11-22 19:42:40.271233: Epoch time: 18.94 s +2024-11-22 19:42:41.513313: +2024-11-22 19:42:41.513525: Epoch 6050 +2024-11-22 19:42:41.513640: Current learning rate: 0.00281 +2024-11-22 19:42:59.967361: train_loss -0.8094 +2024-11-22 19:42:59.967590: val_loss -0.7362 +2024-11-22 19:42:59.967669: Pseudo dice [0.8474] +2024-11-22 19:42:59.967747: Epoch time: 18.45 s +2024-11-22 19:43:00.872305: +2024-11-22 19:43:00.872581: Epoch 6051 +2024-11-22 19:43:00.872695: Current learning rate: 0.00281 +2024-11-22 19:43:20.439508: train_loss -0.805 +2024-11-22 19:43:20.439778: val_loss -0.7594 +2024-11-22 19:43:20.439877: Pseudo dice [0.8474] +2024-11-22 19:43:20.439961: Epoch time: 19.57 s +2024-11-22 19:43:21.345293: +2024-11-22 19:43:21.345507: Epoch 6052 +2024-11-22 19:43:21.345623: Current learning rate: 0.0028 +2024-11-22 19:43:39.885637: train_loss -0.8021 +2024-11-22 19:43:39.891107: val_loss -0.7666 +2024-11-22 19:43:39.891272: Pseudo dice [0.8459] +2024-11-22 19:43:39.891356: Epoch time: 18.54 s +2024-11-22 19:43:40.837250: +2024-11-22 19:43:40.837472: Epoch 6053 +2024-11-22 19:43:40.837585: Current learning rate: 0.0028 +2024-11-22 19:43:59.191624: train_loss -0.8052 +2024-11-22 19:43:59.191854: val_loss -0.744 +2024-11-22 19:43:59.191929: Pseudo dice [0.8382] +2024-11-22 19:43:59.192017: Epoch time: 18.36 s +2024-11-22 19:44:00.101850: +2024-11-22 19:44:00.102167: Epoch 6054 +2024-11-22 19:44:00.102291: Current learning rate: 0.0028 +2024-11-22 19:44:19.104262: train_loss -0.8043 +2024-11-22 19:44:19.104486: val_loss -0.7585 +2024-11-22 19:44:19.104563: Pseudo dice [0.8396] +2024-11-22 19:44:19.104642: Epoch time: 19.0 s +2024-11-22 19:44:20.045692: +2024-11-22 19:44:20.046013: Epoch 6055 +2024-11-22 19:44:20.046126: Current learning rate: 0.0028 +2024-11-22 19:44:39.343482: train_loss -0.804 +2024-11-22 19:44:39.343731: val_loss -0.7701 +2024-11-22 19:44:39.343810: Pseudo dice [0.8364] +2024-11-22 19:44:39.343893: Epoch time: 19.3 s +2024-11-22 19:44:40.257532: +2024-11-22 19:44:40.257743: Epoch 6056 +2024-11-22 19:44:40.257857: Current learning rate: 0.0028 +2024-11-22 19:44:58.354731: train_loss -0.8097 +2024-11-22 19:44:58.354958: val_loss -0.7639 +2024-11-22 19:44:58.355044: Pseudo dice [0.8628] +2024-11-22 19:44:58.355124: Epoch time: 18.1 s +2024-11-22 19:44:59.266145: +2024-11-22 19:44:59.266357: Epoch 6057 +2024-11-22 19:44:59.266467: Current learning rate: 0.0028 +2024-11-22 19:45:17.056010: train_loss -0.8073 +2024-11-22 19:45:17.056270: val_loss -0.7517 +2024-11-22 19:45:17.056347: Pseudo dice [0.8492] +2024-11-22 19:45:17.056453: Epoch time: 17.79 s +2024-11-22 19:45:18.271018: +2024-11-22 19:45:18.271313: Epoch 6058 +2024-11-22 19:45:18.271430: Current learning rate: 0.0028 +2024-11-22 19:45:37.049622: train_loss -0.8087 +2024-11-22 19:45:37.049829: val_loss -0.7535 +2024-11-22 19:45:37.049904: Pseudo dice [0.841] +2024-11-22 19:45:37.052137: Epoch time: 18.78 s +2024-11-22 19:45:38.124026: +2024-11-22 19:45:38.124217: Epoch 6059 +2024-11-22 19:45:38.124328: Current learning rate: 0.0028 +2024-11-22 19:45:56.771949: train_loss -0.8166 +2024-11-22 19:45:56.772199: val_loss -0.7559 +2024-11-22 19:45:56.772274: Pseudo dice [0.8611] +2024-11-22 19:45:56.772359: Epoch time: 18.65 s +2024-11-22 19:45:57.698588: +2024-11-22 19:45:57.698835: Epoch 6060 +2024-11-22 19:45:57.698947: Current learning rate: 0.00279 +2024-11-22 19:46:16.098014: train_loss -0.8039 +2024-11-22 19:46:16.098233: val_loss -0.7745 +2024-11-22 19:46:16.098371: Pseudo dice [0.8663] +2024-11-22 19:46:16.098450: Epoch time: 18.4 s +2024-11-22 19:46:17.042725: +2024-11-22 19:46:17.042936: Epoch 6061 +2024-11-22 19:46:17.043054: Current learning rate: 0.00279 +2024-11-22 19:46:35.437164: train_loss -0.8078 +2024-11-22 19:46:35.437383: val_loss -0.7671 +2024-11-22 19:46:35.437458: Pseudo dice [0.8579] +2024-11-22 19:46:35.437533: Epoch time: 18.4 s +2024-11-22 19:46:36.347078: +2024-11-22 19:46:36.347290: Epoch 6062 +2024-11-22 19:46:36.347410: Current learning rate: 0.00279 +2024-11-22 19:46:55.239399: train_loss -0.8092 +2024-11-22 19:46:55.239615: val_loss -0.7303 +2024-11-22 19:46:55.239690: Pseudo dice [0.8272] +2024-11-22 19:46:55.239764: Epoch time: 18.89 s +2024-11-22 19:46:56.147485: +2024-11-22 19:46:56.147694: Epoch 6063 +2024-11-22 19:46:56.147803: Current learning rate: 0.00279 +2024-11-22 19:47:15.708962: train_loss -0.8014 +2024-11-22 19:47:15.709266: val_loss -0.7457 +2024-11-22 19:47:15.709343: Pseudo dice [0.8399] +2024-11-22 19:47:15.709425: Epoch time: 19.56 s +2024-11-22 19:47:17.061073: +2024-11-22 19:47:17.061278: Epoch 6064 +2024-11-22 19:47:17.061391: Current learning rate: 0.00279 +2024-11-22 19:47:36.115783: train_loss -0.8074 +2024-11-22 19:47:36.116014: val_loss -0.7554 +2024-11-22 19:47:36.116090: Pseudo dice [0.8455] +2024-11-22 19:47:36.116164: Epoch time: 19.06 s +2024-11-22 19:47:37.034007: +2024-11-22 19:47:37.034387: Epoch 6065 +2024-11-22 19:47:37.034503: Current learning rate: 0.00279 +2024-11-22 19:47:55.967715: train_loss -0.8116 +2024-11-22 19:47:55.970118: val_loss -0.77 +2024-11-22 19:47:55.970256: Pseudo dice [0.8644] +2024-11-22 19:47:55.970335: Epoch time: 18.93 s +2024-11-22 19:47:56.908269: +2024-11-22 19:47:56.908531: Epoch 6066 +2024-11-22 19:47:56.908645: Current learning rate: 0.00279 +2024-11-22 19:48:16.049451: train_loss -0.7978 +2024-11-22 19:48:16.049679: val_loss -0.7567 +2024-11-22 19:48:16.049779: Pseudo dice [0.8634] +2024-11-22 19:48:16.049872: Epoch time: 19.14 s +2024-11-22 19:48:16.963813: +2024-11-22 19:48:16.964041: Epoch 6067 +2024-11-22 19:48:16.964159: Current learning rate: 0.00279 +2024-11-22 19:48:34.791317: train_loss -0.8092 +2024-11-22 19:48:34.791560: val_loss -0.7646 +2024-11-22 19:48:34.791637: Pseudo dice [0.8503] +2024-11-22 19:48:34.791722: Epoch time: 17.83 s +2024-11-22 19:48:35.712673: +2024-11-22 19:48:35.713052: Epoch 6068 +2024-11-22 19:48:35.713169: Current learning rate: 0.00278 +2024-11-22 19:48:54.807184: train_loss -0.8157 +2024-11-22 19:48:54.807409: val_loss -0.7465 +2024-11-22 19:48:54.807485: Pseudo dice [0.8464] +2024-11-22 19:48:54.807566: Epoch time: 19.1 s +2024-11-22 19:48:55.756720: +2024-11-22 19:48:55.756932: Epoch 6069 +2024-11-22 19:48:55.757051: Current learning rate: 0.00278 +2024-11-22 19:49:15.336486: train_loss -0.8089 +2024-11-22 19:49:15.336700: val_loss -0.7655 +2024-11-22 19:49:15.336776: Pseudo dice [0.8458] +2024-11-22 19:49:15.336882: Epoch time: 19.58 s +2024-11-22 19:49:16.254107: +2024-11-22 19:49:16.254311: Epoch 6070 +2024-11-22 19:49:16.254416: Current learning rate: 0.00278 +2024-11-22 19:49:35.635259: train_loss -0.8043 +2024-11-22 19:49:35.635493: val_loss -0.7596 +2024-11-22 19:49:35.637675: Pseudo dice [0.8525] +2024-11-22 19:49:35.637891: Epoch time: 19.38 s +2024-11-22 19:49:36.582485: +2024-11-22 19:49:36.582701: Epoch 6071 +2024-11-22 19:49:36.582810: Current learning rate: 0.00278 +2024-11-22 19:49:55.889190: train_loss -0.8042 +2024-11-22 19:49:55.889462: val_loss -0.7573 +2024-11-22 19:49:55.889539: Pseudo dice [0.8646] +2024-11-22 19:49:55.889622: Epoch time: 19.31 s +2024-11-22 19:49:56.821287: +2024-11-22 19:49:56.821492: Epoch 6072 +2024-11-22 19:49:56.821603: Current learning rate: 0.00278 +2024-11-22 19:50:14.691565: train_loss -0.817 +2024-11-22 19:50:14.691800: val_loss -0.7487 +2024-11-22 19:50:14.691878: Pseudo dice [0.8478] +2024-11-22 19:50:14.691957: Epoch time: 17.87 s +2024-11-22 19:50:15.768343: +2024-11-22 19:50:15.768547: Epoch 6073 +2024-11-22 19:50:15.768660: Current learning rate: 0.00278 +2024-11-22 19:50:35.151631: train_loss -0.7963 +2024-11-22 19:50:35.151852: val_loss -0.7426 +2024-11-22 19:50:35.151934: Pseudo dice [0.8377] +2024-11-22 19:50:35.152024: Epoch time: 19.38 s +2024-11-22 19:50:36.063257: +2024-11-22 19:50:36.063454: Epoch 6074 +2024-11-22 19:50:36.063560: Current learning rate: 0.00278 +2024-11-22 19:50:56.092890: train_loss -0.8052 +2024-11-22 19:50:56.093119: val_loss -0.7606 +2024-11-22 19:50:56.093194: Pseudo dice [0.8307] +2024-11-22 19:50:56.093274: Epoch time: 20.03 s +2024-11-22 19:50:57.003731: +2024-11-22 19:50:57.003942: Epoch 6075 +2024-11-22 19:50:57.004058: Current learning rate: 0.00277 +2024-11-22 19:51:15.771720: train_loss -0.8087 +2024-11-22 19:51:15.772014: val_loss -0.7642 +2024-11-22 19:51:15.772095: Pseudo dice [0.8506] +2024-11-22 19:51:15.772175: Epoch time: 18.77 s +2024-11-22 19:51:16.679234: +2024-11-22 19:51:16.679458: Epoch 6076 +2024-11-22 19:51:16.679569: Current learning rate: 0.00277 +2024-11-22 19:51:34.960050: train_loss -0.8186 +2024-11-22 19:51:34.960274: val_loss -0.7587 +2024-11-22 19:51:34.960354: Pseudo dice [0.8477] +2024-11-22 19:51:34.960431: Epoch time: 18.28 s +2024-11-22 19:51:35.869757: +2024-11-22 19:51:35.869958: Epoch 6077 +2024-11-22 19:51:35.870074: Current learning rate: 0.00277 +2024-11-22 19:51:54.076160: train_loss -0.8153 +2024-11-22 19:51:54.076446: val_loss -0.7785 +2024-11-22 19:51:54.076522: Pseudo dice [0.842] +2024-11-22 19:51:54.076599: Epoch time: 18.21 s +2024-11-22 19:51:55.043877: +2024-11-22 19:51:55.044149: Epoch 6078 +2024-11-22 19:51:55.044262: Current learning rate: 0.00277 +2024-11-22 19:52:14.183852: train_loss -0.8079 +2024-11-22 19:52:14.184137: val_loss -0.7669 +2024-11-22 19:52:14.184215: Pseudo dice [0.8558] +2024-11-22 19:52:14.184300: Epoch time: 19.14 s +2024-11-22 19:52:15.095972: +2024-11-22 19:52:15.096185: Epoch 6079 +2024-11-22 19:52:15.096297: Current learning rate: 0.00277 +2024-11-22 19:52:34.271310: train_loss -0.8064 +2024-11-22 19:52:34.271585: val_loss -0.7727 +2024-11-22 19:52:34.271665: Pseudo dice [0.855] +2024-11-22 19:52:34.271746: Epoch time: 19.18 s +2024-11-22 19:52:35.288841: +2024-11-22 19:52:35.289052: Epoch 6080 +2024-11-22 19:52:35.289161: Current learning rate: 0.00277 +2024-11-22 19:52:53.536260: train_loss -0.8105 +2024-11-22 19:52:53.536538: val_loss -0.765 +2024-11-22 19:52:53.536619: Pseudo dice [0.8581] +2024-11-22 19:52:53.536699: Epoch time: 18.25 s +2024-11-22 19:52:54.448852: +2024-11-22 19:52:54.449111: Epoch 6081 +2024-11-22 19:52:54.449229: Current learning rate: 0.00277 +2024-11-22 19:53:13.161793: train_loss -0.8153 +2024-11-22 19:53:13.162025: val_loss -0.7396 +2024-11-22 19:53:13.162100: Pseudo dice [0.8122] +2024-11-22 19:53:13.162178: Epoch time: 18.71 s +2024-11-22 19:53:14.084446: +2024-11-22 19:53:14.084693: Epoch 6082 +2024-11-22 19:53:14.084804: Current learning rate: 0.00277 +2024-11-22 19:53:33.205250: train_loss -0.8112 +2024-11-22 19:53:33.205495: val_loss -0.7378 +2024-11-22 19:53:33.205572: Pseudo dice [0.8165] +2024-11-22 19:53:33.205658: Epoch time: 19.12 s +2024-11-22 19:53:34.171977: +2024-11-22 19:53:34.172186: Epoch 6083 +2024-11-22 19:53:34.172300: Current learning rate: 0.00276 +2024-11-22 19:53:52.500262: train_loss -0.8161 +2024-11-22 19:53:52.500538: val_loss -0.7259 +2024-11-22 19:53:52.500614: Pseudo dice [0.8633] +2024-11-22 19:53:52.500692: Epoch time: 18.33 s +2024-11-22 19:53:53.414451: +2024-11-22 19:53:53.414663: Epoch 6084 +2024-11-22 19:53:53.414777: Current learning rate: 0.00276 +2024-11-22 19:54:11.831645: train_loss -0.8184 +2024-11-22 19:54:11.831870: val_loss -0.7456 +2024-11-22 19:54:11.831947: Pseudo dice [0.8103] +2024-11-22 19:54:11.832029: Epoch time: 18.42 s +2024-11-22 19:54:12.928377: +2024-11-22 19:54:12.928575: Epoch 6085 +2024-11-22 19:54:12.928688: Current learning rate: 0.00276 +2024-11-22 19:54:32.247260: train_loss -0.8106 +2024-11-22 19:54:32.247487: val_loss -0.7564 +2024-11-22 19:54:32.247565: Pseudo dice [0.8502] +2024-11-22 19:54:32.247650: Epoch time: 19.32 s +2024-11-22 19:54:33.164017: +2024-11-22 19:54:33.164233: Epoch 6086 +2024-11-22 19:54:33.164357: Current learning rate: 0.00276 +2024-11-22 19:54:51.242603: train_loss -0.8055 +2024-11-22 19:54:51.242851: val_loss -0.7525 +2024-11-22 19:54:51.242930: Pseudo dice [0.8517] +2024-11-22 19:54:51.243021: Epoch time: 18.08 s +2024-11-22 19:54:52.462508: +2024-11-22 19:54:52.462773: Epoch 6087 +2024-11-22 19:54:52.462884: Current learning rate: 0.00276 +2024-11-22 19:55:12.228446: train_loss -0.8086 +2024-11-22 19:55:12.228649: val_loss -0.7532 +2024-11-22 19:55:12.228725: Pseudo dice [0.8516] +2024-11-22 19:55:12.230351: Epoch time: 19.77 s +2024-11-22 19:55:13.153609: +2024-11-22 19:55:13.153832: Epoch 6088 +2024-11-22 19:55:13.153943: Current learning rate: 0.00276 +2024-11-22 19:55:32.242812: train_loss -0.8092 +2024-11-22 19:55:32.243039: val_loss -0.7167 +2024-11-22 19:55:32.243116: Pseudo dice [0.8154] +2024-11-22 19:55:32.243194: Epoch time: 19.09 s +2024-11-22 19:55:33.153037: +2024-11-22 19:55:33.153304: Epoch 6089 +2024-11-22 19:55:33.153419: Current learning rate: 0.00276 +2024-11-22 19:55:50.615481: train_loss -0.819 +2024-11-22 19:55:50.615728: val_loss -0.7491 +2024-11-22 19:55:50.615808: Pseudo dice [0.8539] +2024-11-22 19:55:50.615946: Epoch time: 17.46 s +2024-11-22 19:55:51.504885: +2024-11-22 19:55:51.505081: Epoch 6090 +2024-11-22 19:55:51.505177: Current learning rate: 0.00276 +2024-11-22 19:56:09.835041: train_loss -0.808 +2024-11-22 19:56:09.835263: val_loss -0.7672 +2024-11-22 19:56:09.835341: Pseudo dice [0.8548] +2024-11-22 19:56:09.835418: Epoch time: 18.33 s +2024-11-22 19:56:11.004681: +2024-11-22 19:56:11.004907: Epoch 6091 +2024-11-22 19:56:11.005038: Current learning rate: 0.00275 +2024-11-22 19:56:29.608648: train_loss -0.8069 +2024-11-22 19:56:29.608858: val_loss -0.7509 +2024-11-22 19:56:29.608932: Pseudo dice [0.8674] +2024-11-22 19:56:29.609047: Epoch time: 18.6 s +2024-11-22 19:56:30.522239: +2024-11-22 19:56:30.522431: Epoch 6092 +2024-11-22 19:56:30.522555: Current learning rate: 0.00275 +2024-11-22 19:56:49.840669: train_loss -0.8071 +2024-11-22 19:56:49.840890: val_loss -0.7442 +2024-11-22 19:56:49.840964: Pseudo dice [0.8666] +2024-11-22 19:56:49.841052: Epoch time: 19.32 s +2024-11-22 19:56:50.753778: +2024-11-22 19:56:50.754011: Epoch 6093 +2024-11-22 19:56:50.754118: Current learning rate: 0.00275 +2024-11-22 19:57:08.459938: train_loss -0.8117 +2024-11-22 19:57:08.460211: val_loss -0.777 +2024-11-22 19:57:08.460287: Pseudo dice [0.8369] +2024-11-22 19:57:08.460372: Epoch time: 17.71 s +2024-11-22 19:57:09.407907: +2024-11-22 19:57:09.408148: Epoch 6094 +2024-11-22 19:57:09.408264: Current learning rate: 0.00275 +2024-11-22 19:57:27.495786: train_loss -0.8174 +2024-11-22 19:57:27.496010: val_loss -0.7627 +2024-11-22 19:57:27.496083: Pseudo dice [0.8572] +2024-11-22 19:57:27.496158: Epoch time: 18.09 s +2024-11-22 19:57:28.399150: +2024-11-22 19:57:28.399353: Epoch 6095 +2024-11-22 19:57:28.399459: Current learning rate: 0.00275 +2024-11-22 19:57:48.567603: train_loss -0.8115 +2024-11-22 19:57:48.567816: val_loss -0.7507 +2024-11-22 19:57:48.567888: Pseudo dice [0.8567] +2024-11-22 19:57:48.567964: Epoch time: 20.17 s +2024-11-22 19:57:49.473883: +2024-11-22 19:57:49.474108: Epoch 6096 +2024-11-22 19:57:49.474222: Current learning rate: 0.00275 +2024-11-22 19:58:09.140514: train_loss -0.8208 +2024-11-22 19:58:09.140725: val_loss -0.7533 +2024-11-22 19:58:09.140797: Pseudo dice [0.8345] +2024-11-22 19:58:09.140872: Epoch time: 19.67 s +2024-11-22 19:58:10.055945: +2024-11-22 19:58:10.056198: Epoch 6097 +2024-11-22 19:58:10.056306: Current learning rate: 0.00275 +2024-11-22 19:58:28.584085: train_loss -0.8134 +2024-11-22 19:58:28.584332: val_loss -0.7589 +2024-11-22 19:58:28.584404: Pseudo dice [0.8567] +2024-11-22 19:58:28.584488: Epoch time: 18.53 s +2024-11-22 19:58:29.472258: +2024-11-22 19:58:29.472460: Epoch 6098 +2024-11-22 19:58:29.472573: Current learning rate: 0.00274 +2024-11-22 19:58:48.815278: train_loss -0.8118 +2024-11-22 19:58:48.815501: val_loss -0.7608 +2024-11-22 19:58:48.815574: Pseudo dice [0.8364] +2024-11-22 19:58:48.815649: Epoch time: 19.34 s +2024-11-22 19:58:49.796252: +2024-11-22 19:58:49.796459: Epoch 6099 +2024-11-22 19:58:49.796571: Current learning rate: 0.00274 +2024-11-22 19:59:08.795374: train_loss -0.8117 +2024-11-22 19:59:08.795590: val_loss -0.7453 +2024-11-22 19:59:08.795666: Pseudo dice [0.8536] +2024-11-22 19:59:08.795742: Epoch time: 19.0 s +2024-11-22 19:59:10.015382: +2024-11-22 19:59:10.015588: Epoch 6100 +2024-11-22 19:59:10.015702: Current learning rate: 0.00274 +2024-11-22 19:59:27.695827: train_loss -0.7996 +2024-11-22 19:59:27.696054: val_loss -0.7641 +2024-11-22 19:59:27.696131: Pseudo dice [0.8488] +2024-11-22 19:59:27.696211: Epoch time: 17.68 s +2024-11-22 19:59:28.605332: +2024-11-22 19:59:28.605581: Epoch 6101 +2024-11-22 19:59:28.605740: Current learning rate: 0.00274 +2024-11-22 19:59:47.565458: train_loss -0.8068 +2024-11-22 19:59:47.565675: val_loss -0.7419 +2024-11-22 19:59:47.565751: Pseudo dice [0.8386] +2024-11-22 19:59:47.565829: Epoch time: 18.96 s +2024-11-22 19:59:48.475171: +2024-11-22 19:59:48.475430: Epoch 6102 +2024-11-22 19:59:48.475544: Current learning rate: 0.00274 +2024-11-22 20:00:08.070427: train_loss -0.8044 +2024-11-22 20:00:08.070649: val_loss -0.7524 +2024-11-22 20:00:08.070727: Pseudo dice [0.8352] +2024-11-22 20:00:08.070864: Epoch time: 19.6 s +2024-11-22 20:00:08.979132: +2024-11-22 20:00:08.979328: Epoch 6103 +2024-11-22 20:00:08.979438: Current learning rate: 0.00274 +2024-11-22 20:00:26.725725: train_loss -0.8086 +2024-11-22 20:00:26.726000: val_loss -0.7557 +2024-11-22 20:00:26.726079: Pseudo dice [0.8478] +2024-11-22 20:00:26.726155: Epoch time: 17.75 s +2024-11-22 20:00:27.636703: +2024-11-22 20:00:27.637001: Epoch 6104 +2024-11-22 20:00:27.637114: Current learning rate: 0.00274 +2024-11-22 20:00:46.251872: train_loss -0.8142 +2024-11-22 20:00:46.252098: val_loss -0.7602 +2024-11-22 20:00:46.252174: Pseudo dice [0.8405] +2024-11-22 20:00:46.252249: Epoch time: 18.62 s +2024-11-22 20:00:47.167603: +2024-11-22 20:00:47.167839: Epoch 6105 +2024-11-22 20:00:47.167955: Current learning rate: 0.00274 +2024-11-22 20:01:05.235629: train_loss -0.8088 +2024-11-22 20:01:05.235846: val_loss -0.7415 +2024-11-22 20:01:05.235921: Pseudo dice [0.8427] +2024-11-22 20:01:05.236078: Epoch time: 18.07 s +2024-11-22 20:01:06.138416: +2024-11-22 20:01:06.138642: Epoch 6106 +2024-11-22 20:01:06.138756: Current learning rate: 0.00273 +2024-11-22 20:01:24.890805: train_loss -0.8035 +2024-11-22 20:01:24.891020: val_loss -0.7702 +2024-11-22 20:01:24.891097: Pseudo dice [0.8548] +2024-11-22 20:01:24.891172: Epoch time: 18.75 s +2024-11-22 20:01:25.784015: +2024-11-22 20:01:25.784217: Epoch 6107 +2024-11-22 20:01:25.784332: Current learning rate: 0.00273 +2024-11-22 20:01:43.755107: train_loss -0.8094 +2024-11-22 20:01:43.755335: val_loss -0.7528 +2024-11-22 20:01:43.755417: Pseudo dice [0.8498] +2024-11-22 20:01:43.755497: Epoch time: 17.97 s +2024-11-22 20:01:44.668376: +2024-11-22 20:01:44.668603: Epoch 6108 +2024-11-22 20:01:44.668714: Current learning rate: 0.00273 +2024-11-22 20:02:04.343648: train_loss -0.8125 +2024-11-22 20:02:04.343907: val_loss -0.747 +2024-11-22 20:02:04.343984: Pseudo dice [0.8495] +2024-11-22 20:02:04.344075: Epoch time: 19.68 s +2024-11-22 20:02:05.242911: +2024-11-22 20:02:05.243111: Epoch 6109 +2024-11-22 20:02:05.243219: Current learning rate: 0.00273 +2024-11-22 20:02:24.487025: train_loss -0.8186 +2024-11-22 20:02:24.487278: val_loss -0.7436 +2024-11-22 20:02:24.487356: Pseudo dice [0.8401] +2024-11-22 20:02:24.487438: Epoch time: 19.24 s +2024-11-22 20:02:25.378231: +2024-11-22 20:02:25.378438: Epoch 6110 +2024-11-22 20:02:25.378550: Current learning rate: 0.00273 +2024-11-22 20:02:44.097467: train_loss -0.8132 +2024-11-22 20:02:44.097681: val_loss -0.7576 +2024-11-22 20:02:44.097754: Pseudo dice [0.8424] +2024-11-22 20:02:44.097830: Epoch time: 18.72 s +2024-11-22 20:02:44.991797: +2024-11-22 20:02:44.992264: Epoch 6111 +2024-11-22 20:02:44.992402: Current learning rate: 0.00273 +2024-11-22 20:03:03.879715: train_loss -0.8173 +2024-11-22 20:03:03.885142: val_loss -0.7567 +2024-11-22 20:03:03.885275: Pseudo dice [0.8597] +2024-11-22 20:03:03.885361: Epoch time: 18.89 s +2024-11-22 20:03:04.907826: +2024-11-22 20:03:04.908270: Epoch 6112 +2024-11-22 20:03:04.908403: Current learning rate: 0.00273 +2024-11-22 20:03:23.708706: train_loss -0.8119 +2024-11-22 20:03:23.708942: val_loss -0.7283 +2024-11-22 20:03:23.709020: Pseudo dice [0.8302] +2024-11-22 20:03:23.709100: Epoch time: 18.8 s +2024-11-22 20:03:24.720027: +2024-11-22 20:03:24.720452: Epoch 6113 +2024-11-22 20:03:24.720583: Current learning rate: 0.00273 +2024-11-22 20:03:43.555583: train_loss -0.8083 +2024-11-22 20:03:43.555796: val_loss -0.7681 +2024-11-22 20:03:43.555870: Pseudo dice [0.8619] +2024-11-22 20:03:43.555944: Epoch time: 18.84 s +2024-11-22 20:03:44.437840: +2024-11-22 20:03:44.438296: Epoch 6114 +2024-11-22 20:03:44.438433: Current learning rate: 0.00272 +2024-11-22 20:04:03.824739: train_loss -0.8189 +2024-11-22 20:04:03.825005: val_loss -0.7603 +2024-11-22 20:04:03.825089: Pseudo dice [0.846] +2024-11-22 20:04:03.825175: Epoch time: 19.39 s +2024-11-22 20:04:04.731462: +2024-11-22 20:04:04.731876: Epoch 6115 +2024-11-22 20:04:04.732018: Current learning rate: 0.00272 +2024-11-22 20:04:23.701750: train_loss -0.8072 +2024-11-22 20:04:23.701969: val_loss -0.7737 +2024-11-22 20:04:23.702072: Pseudo dice [0.8715] +2024-11-22 20:04:23.702149: Epoch time: 18.97 s +2024-11-22 20:04:24.604140: +2024-11-22 20:04:24.604552: Epoch 6116 +2024-11-22 20:04:24.604687: Current learning rate: 0.00272 +2024-11-22 20:04:42.778433: train_loss -0.8173 +2024-11-22 20:04:42.778692: val_loss -0.7444 +2024-11-22 20:04:42.778770: Pseudo dice [0.8664] +2024-11-22 20:04:42.778854: Epoch time: 18.18 s +2024-11-22 20:04:43.690763: +2024-11-22 20:04:43.691203: Epoch 6117 +2024-11-22 20:04:43.691339: Current learning rate: 0.00272 +2024-11-22 20:05:03.550005: train_loss -0.8086 +2024-11-22 20:05:03.550219: val_loss -0.75 +2024-11-22 20:05:03.550308: Pseudo dice [0.8511] +2024-11-22 20:05:03.550385: Epoch time: 19.86 s +2024-11-22 20:05:04.455282: +2024-11-22 20:05:04.455707: Epoch 6118 +2024-11-22 20:05:04.455845: Current learning rate: 0.00272 +2024-11-22 20:05:23.018111: train_loss -0.8144 +2024-11-22 20:05:23.018329: val_loss -0.7647 +2024-11-22 20:05:23.018409: Pseudo dice [0.8429] +2024-11-22 20:05:23.018496: Epoch time: 18.56 s +2024-11-22 20:05:23.921885: +2024-11-22 20:05:23.922306: Epoch 6119 +2024-11-22 20:05:23.922445: Current learning rate: 0.00272 +2024-11-22 20:05:42.968117: train_loss -0.8081 +2024-11-22 20:05:42.968329: val_loss -0.7514 +2024-11-22 20:05:42.968407: Pseudo dice [0.8454] +2024-11-22 20:05:42.973624: Epoch time: 19.05 s +2024-11-22 20:05:43.990385: +2024-11-22 20:05:43.990636: Epoch 6120 +2024-11-22 20:05:43.990746: Current learning rate: 0.00272 +2024-11-22 20:06:02.344622: train_loss -0.8075 +2024-11-22 20:06:02.344870: val_loss -0.7621 +2024-11-22 20:06:02.344944: Pseudo dice [0.8267] +2024-11-22 20:06:02.345035: Epoch time: 18.36 s +2024-11-22 20:06:03.653984: +2024-11-22 20:06:03.654462: Epoch 6121 +2024-11-22 20:06:03.654602: Current learning rate: 0.00271 +2024-11-22 20:06:22.323654: train_loss -0.7932 +2024-11-22 20:06:22.323884: val_loss -0.7545 +2024-11-22 20:06:22.323960: Pseudo dice [0.8584] +2024-11-22 20:06:22.324045: Epoch time: 18.67 s +2024-11-22 20:06:23.235155: +2024-11-22 20:06:23.235584: Epoch 6122 +2024-11-22 20:06:23.235728: Current learning rate: 0.00271 +2024-11-22 20:06:41.861360: train_loss -0.8069 +2024-11-22 20:06:41.861579: val_loss -0.7734 +2024-11-22 20:06:41.861652: Pseudo dice [0.8633] +2024-11-22 20:06:41.861727: Epoch time: 18.63 s +2024-11-22 20:06:42.770883: +2024-11-22 20:06:42.771320: Epoch 6123 +2024-11-22 20:06:42.771451: Current learning rate: 0.00271 +2024-11-22 20:07:01.759738: train_loss -0.8061 +2024-11-22 20:07:01.760590: val_loss -0.7528 +2024-11-22 20:07:01.760668: Pseudo dice [0.8295] +2024-11-22 20:07:01.760753: Epoch time: 18.99 s +2024-11-22 20:07:02.665767: +2024-11-22 20:07:02.666193: Epoch 6124 +2024-11-22 20:07:02.666331: Current learning rate: 0.00271 +2024-11-22 20:07:22.404441: train_loss -0.8054 +2024-11-22 20:07:22.404674: val_loss -0.787 +2024-11-22 20:07:22.404754: Pseudo dice [0.8697] +2024-11-22 20:07:22.404851: Epoch time: 19.74 s +2024-11-22 20:07:23.311309: +2024-11-22 20:07:23.311732: Epoch 6125 +2024-11-22 20:07:23.311865: Current learning rate: 0.00271 +2024-11-22 20:07:42.034755: train_loss -0.7975 +2024-11-22 20:07:42.034976: val_loss -0.7607 +2024-11-22 20:07:42.035062: Pseudo dice [0.831] +2024-11-22 20:07:42.035156: Epoch time: 18.72 s +2024-11-22 20:07:42.941653: +2024-11-22 20:07:42.942101: Epoch 6126 +2024-11-22 20:07:42.942243: Current learning rate: 0.00271 +2024-11-22 20:08:00.963286: train_loss -0.7817 +2024-11-22 20:08:00.963517: val_loss -0.7711 +2024-11-22 20:08:00.963592: Pseudo dice [0.8504] +2024-11-22 20:08:00.963670: Epoch time: 18.02 s +2024-11-22 20:08:01.877119: +2024-11-22 20:08:01.877534: Epoch 6127 +2024-11-22 20:08:01.877661: Current learning rate: 0.00271 +2024-11-22 20:08:20.517591: train_loss -0.7974 +2024-11-22 20:08:20.518307: val_loss -0.7484 +2024-11-22 20:08:20.518384: Pseudo dice [0.8531] +2024-11-22 20:08:20.518469: Epoch time: 18.64 s +2024-11-22 20:08:21.420468: +2024-11-22 20:08:21.420929: Epoch 6128 +2024-11-22 20:08:21.421075: Current learning rate: 0.00271 +2024-11-22 20:08:40.430025: train_loss -0.7926 +2024-11-22 20:08:40.430247: val_loss -0.745 +2024-11-22 20:08:40.430323: Pseudo dice [0.8521] +2024-11-22 20:08:40.430398: Epoch time: 19.01 s +2024-11-22 20:08:41.346253: +2024-11-22 20:08:41.346683: Epoch 6129 +2024-11-22 20:08:41.346818: Current learning rate: 0.0027 +2024-11-22 20:08:59.279867: train_loss -0.8086 +2024-11-22 20:08:59.280088: val_loss -0.7674 +2024-11-22 20:08:59.280162: Pseudo dice [0.8506] +2024-11-22 20:08:59.280238: Epoch time: 17.93 s +2024-11-22 20:09:00.179744: +2024-11-22 20:09:00.180240: Epoch 6130 +2024-11-22 20:09:00.180373: Current learning rate: 0.0027 +2024-11-22 20:09:18.232653: train_loss -0.8106 +2024-11-22 20:09:18.232924: val_loss -0.7438 +2024-11-22 20:09:18.233012: Pseudo dice [0.8477] +2024-11-22 20:09:18.233096: Epoch time: 18.05 s +2024-11-22 20:09:19.187099: +2024-11-22 20:09:19.187292: Epoch 6131 +2024-11-22 20:09:19.187405: Current learning rate: 0.0027 +2024-11-22 20:09:37.202067: train_loss -0.8115 +2024-11-22 20:09:37.202312: val_loss -0.7505 +2024-11-22 20:09:37.202387: Pseudo dice [0.8441] +2024-11-22 20:09:37.202582: Epoch time: 18.02 s +2024-11-22 20:09:38.466212: +2024-11-22 20:09:38.466442: Epoch 6132 +2024-11-22 20:09:38.466561: Current learning rate: 0.0027 +2024-11-22 20:09:56.222851: train_loss -0.806 +2024-11-22 20:09:56.223122: val_loss -0.774 +2024-11-22 20:09:56.223204: Pseudo dice [0.8631] +2024-11-22 20:09:56.223283: Epoch time: 17.76 s +2024-11-22 20:09:57.124959: +2024-11-22 20:09:57.125179: Epoch 6133 +2024-11-22 20:09:57.125290: Current learning rate: 0.0027 +2024-11-22 20:10:15.592757: train_loss -0.7998 +2024-11-22 20:10:15.593083: val_loss -0.7596 +2024-11-22 20:10:15.593162: Pseudo dice [0.8335] +2024-11-22 20:10:15.593242: Epoch time: 18.47 s +2024-11-22 20:10:16.562327: +2024-11-22 20:10:16.562568: Epoch 6134 +2024-11-22 20:10:16.562686: Current learning rate: 0.0027 +2024-11-22 20:10:34.404383: train_loss -0.802 +2024-11-22 20:10:34.404661: val_loss -0.7236 +2024-11-22 20:10:34.404737: Pseudo dice [0.8372] +2024-11-22 20:10:34.404818: Epoch time: 17.84 s +2024-11-22 20:10:35.292580: +2024-11-22 20:10:35.292781: Epoch 6135 +2024-11-22 20:10:35.292897: Current learning rate: 0.0027 +2024-11-22 20:10:53.626103: train_loss -0.7946 +2024-11-22 20:10:53.626356: val_loss -0.7498 +2024-11-22 20:10:53.626433: Pseudo dice [0.8326] +2024-11-22 20:10:53.626511: Epoch time: 18.33 s +2024-11-22 20:10:54.527065: +2024-11-22 20:10:54.527252: Epoch 6136 +2024-11-22 20:10:54.527379: Current learning rate: 0.0027 +2024-11-22 20:11:13.638817: train_loss -0.804 +2024-11-22 20:11:13.639039: val_loss -0.7731 +2024-11-22 20:11:13.639122: Pseudo dice [0.8348] +2024-11-22 20:11:13.639199: Epoch time: 19.11 s +2024-11-22 20:11:14.529550: +2024-11-22 20:11:14.529756: Epoch 6137 +2024-11-22 20:11:14.529865: Current learning rate: 0.00269 +2024-11-22 20:11:33.938736: train_loss -0.7943 +2024-11-22 20:11:33.938956: val_loss -0.7573 +2024-11-22 20:11:33.939039: Pseudo dice [0.8515] +2024-11-22 20:11:33.939120: Epoch time: 19.41 s +2024-11-22 20:11:34.931604: +2024-11-22 20:11:34.931820: Epoch 6138 +2024-11-22 20:11:34.931934: Current learning rate: 0.00269 +2024-11-22 20:11:53.575800: train_loss -0.7972 +2024-11-22 20:11:53.576043: val_loss -0.7708 +2024-11-22 20:11:53.576146: Pseudo dice [0.8716] +2024-11-22 20:11:53.576229: Epoch time: 18.65 s +2024-11-22 20:11:54.484677: +2024-11-22 20:11:54.485027: Epoch 6139 +2024-11-22 20:11:54.485141: Current learning rate: 0.00269 +2024-11-22 20:12:13.289919: train_loss -0.8015 +2024-11-22 20:12:13.290145: val_loss -0.7683 +2024-11-22 20:12:13.290222: Pseudo dice [0.8368] +2024-11-22 20:12:13.290300: Epoch time: 18.81 s +2024-11-22 20:12:14.192186: +2024-11-22 20:12:14.192391: Epoch 6140 +2024-11-22 20:12:14.192505: Current learning rate: 0.00269 +2024-11-22 20:12:33.884425: train_loss -0.812 +2024-11-22 20:12:33.884653: val_loss -0.7275 +2024-11-22 20:12:33.884724: Pseudo dice [0.8476] +2024-11-22 20:12:33.884802: Epoch time: 19.69 s +2024-11-22 20:12:34.806096: +2024-11-22 20:12:34.806311: Epoch 6141 +2024-11-22 20:12:34.806423: Current learning rate: 0.00269 +2024-11-22 20:12:53.762522: train_loss -0.8099 +2024-11-22 20:12:53.762737: val_loss -0.7621 +2024-11-22 20:12:53.762811: Pseudo dice [0.8491] +2024-11-22 20:12:53.762889: Epoch time: 18.96 s +2024-11-22 20:12:54.706551: +2024-11-22 20:12:54.706842: Epoch 6142 +2024-11-22 20:12:54.706957: Current learning rate: 0.00269 +2024-11-22 20:13:12.990326: train_loss -0.8059 +2024-11-22 20:13:12.990551: val_loss -0.7202 +2024-11-22 20:13:12.990631: Pseudo dice [0.8144] +2024-11-22 20:13:12.990714: Epoch time: 18.28 s +2024-11-22 20:13:13.992331: +2024-11-22 20:13:13.992552: Epoch 6143 +2024-11-22 20:13:13.992666: Current learning rate: 0.00269 +2024-11-22 20:13:31.206398: train_loss -0.802 +2024-11-22 20:13:31.206610: val_loss -0.7374 +2024-11-22 20:13:31.206690: Pseudo dice [0.8331] +2024-11-22 20:13:31.206767: Epoch time: 17.21 s +2024-11-22 20:13:32.515242: +2024-11-22 20:13:32.515486: Epoch 6144 +2024-11-22 20:13:32.515596: Current learning rate: 0.00268 +2024-11-22 20:13:51.249363: train_loss -0.8112 +2024-11-22 20:13:51.249580: val_loss -0.7616 +2024-11-22 20:13:51.249689: Pseudo dice [0.8642] +2024-11-22 20:13:51.249774: Epoch time: 18.73 s +2024-11-22 20:13:52.155900: +2024-11-22 20:13:52.156108: Epoch 6145 +2024-11-22 20:13:52.156223: Current learning rate: 0.00268 +2024-11-22 20:14:10.042343: train_loss -0.8013 +2024-11-22 20:14:10.042611: val_loss -0.7775 +2024-11-22 20:14:10.042689: Pseudo dice [0.8633] +2024-11-22 20:14:10.042767: Epoch time: 17.89 s +2024-11-22 20:14:10.950805: +2024-11-22 20:14:10.951043: Epoch 6146 +2024-11-22 20:14:10.951172: Current learning rate: 0.00268 +2024-11-22 20:14:30.385088: train_loss -0.8044 +2024-11-22 20:14:30.390484: val_loss -0.7798 +2024-11-22 20:14:30.390661: Pseudo dice [0.8752] +2024-11-22 20:14:30.390745: Epoch time: 19.44 s +2024-11-22 20:14:31.325414: +2024-11-22 20:14:31.325620: Epoch 6147 +2024-11-22 20:14:31.325731: Current learning rate: 0.00268 +2024-11-22 20:14:50.074587: train_loss -0.8136 +2024-11-22 20:14:50.074804: val_loss -0.7529 +2024-11-22 20:14:50.074879: Pseudo dice [0.8434] +2024-11-22 20:14:50.074957: Epoch time: 18.75 s +2024-11-22 20:14:50.978848: +2024-11-22 20:14:50.979065: Epoch 6148 +2024-11-22 20:14:50.979182: Current learning rate: 0.00268 +2024-11-22 20:15:09.531955: train_loss -0.8045 +2024-11-22 20:15:09.532186: val_loss -0.7465 +2024-11-22 20:15:09.532261: Pseudo dice [0.842] +2024-11-22 20:15:09.532340: Epoch time: 18.55 s +2024-11-22 20:15:10.566561: +2024-11-22 20:15:10.566780: Epoch 6149 +2024-11-22 20:15:10.566900: Current learning rate: 0.00268 +2024-11-22 20:15:30.410168: train_loss -0.8032 +2024-11-22 20:15:30.410432: val_loss -0.7187 +2024-11-22 20:15:30.410510: Pseudo dice [0.8371] +2024-11-22 20:15:30.412527: Epoch time: 19.84 s +2024-11-22 20:15:31.644144: +2024-11-22 20:15:31.644340: Epoch 6150 +2024-11-22 20:15:31.644452: Current learning rate: 0.00268 +2024-11-22 20:15:51.699979: train_loss -0.8008 +2024-11-22 20:15:51.700197: val_loss -0.7756 +2024-11-22 20:15:51.700269: Pseudo dice [0.8606] +2024-11-22 20:15:51.700342: Epoch time: 20.06 s +2024-11-22 20:15:52.602752: +2024-11-22 20:15:52.602958: Epoch 6151 +2024-11-22 20:15:52.603072: Current learning rate: 0.00268 +2024-11-22 20:16:11.066175: train_loss -0.8123 +2024-11-22 20:16:11.066389: val_loss -0.7377 +2024-11-22 20:16:11.066466: Pseudo dice [0.8506] +2024-11-22 20:16:11.066542: Epoch time: 18.46 s +2024-11-22 20:16:11.982367: +2024-11-22 20:16:11.982567: Epoch 6152 +2024-11-22 20:16:11.982681: Current learning rate: 0.00267 +2024-11-22 20:16:30.841034: train_loss -0.805 +2024-11-22 20:16:30.841255: val_loss -0.7693 +2024-11-22 20:16:30.841329: Pseudo dice [0.8437] +2024-11-22 20:16:30.841486: Epoch time: 18.86 s +2024-11-22 20:16:31.752690: +2024-11-22 20:16:31.752912: Epoch 6153 +2024-11-22 20:16:31.753029: Current learning rate: 0.00267 +2024-11-22 20:16:51.168214: train_loss -0.7919 +2024-11-22 20:16:51.168520: val_loss -0.7432 +2024-11-22 20:16:51.168600: Pseudo dice [0.8591] +2024-11-22 20:16:51.168683: Epoch time: 19.42 s +2024-11-22 20:16:52.074278: +2024-11-22 20:16:52.074700: Epoch 6154 +2024-11-22 20:16:52.074836: Current learning rate: 0.00267 +2024-11-22 20:17:11.425605: train_loss -0.8058 +2024-11-22 20:17:11.425819: val_loss -0.7519 +2024-11-22 20:17:11.425897: Pseudo dice [0.8559] +2024-11-22 20:17:11.425973: Epoch time: 19.35 s +2024-11-22 20:17:12.698115: +2024-11-22 20:17:12.698334: Epoch 6155 +2024-11-22 20:17:12.698451: Current learning rate: 0.00267 +2024-11-22 20:17:31.877827: train_loss -0.8055 +2024-11-22 20:17:31.878099: val_loss -0.7507 +2024-11-22 20:17:31.878176: Pseudo dice [0.8509] +2024-11-22 20:17:31.878252: Epoch time: 19.18 s +2024-11-22 20:17:32.827772: +2024-11-22 20:17:32.828189: Epoch 6156 +2024-11-22 20:17:32.828317: Current learning rate: 0.00267 +2024-11-22 20:17:51.377495: train_loss -0.8066 +2024-11-22 20:17:51.377715: val_loss -0.7597 +2024-11-22 20:17:51.377790: Pseudo dice [0.8388] +2024-11-22 20:17:51.377868: Epoch time: 18.55 s +2024-11-22 20:17:52.384526: +2024-11-22 20:17:52.384961: Epoch 6157 +2024-11-22 20:17:52.385103: Current learning rate: 0.00267 +2024-11-22 20:18:10.916043: train_loss -0.8014 +2024-11-22 20:18:10.916308: val_loss -0.765 +2024-11-22 20:18:10.916386: Pseudo dice [0.8509] +2024-11-22 20:18:10.916631: Epoch time: 18.53 s +2024-11-22 20:18:11.828905: +2024-11-22 20:18:11.829334: Epoch 6158 +2024-11-22 20:18:11.829464: Current learning rate: 0.00267 +2024-11-22 20:18:31.037596: train_loss -0.8115 +2024-11-22 20:18:31.037819: val_loss -0.7527 +2024-11-22 20:18:31.037896: Pseudo dice [0.8616] +2024-11-22 20:18:31.037970: Epoch time: 19.21 s +2024-11-22 20:18:31.946141: +2024-11-22 20:18:31.946539: Epoch 6159 +2024-11-22 20:18:31.946668: Current learning rate: 0.00267 +2024-11-22 20:18:50.526028: train_loss -0.8048 +2024-11-22 20:18:50.526243: val_loss -0.7584 +2024-11-22 20:18:50.526317: Pseudo dice [0.8573] +2024-11-22 20:18:50.526394: Epoch time: 18.58 s +2024-11-22 20:18:51.432426: +2024-11-22 20:18:51.432936: Epoch 6160 +2024-11-22 20:18:51.433076: Current learning rate: 0.00266 +2024-11-22 20:19:10.058879: train_loss -0.8003 +2024-11-22 20:19:10.059109: val_loss -0.7391 +2024-11-22 20:19:10.059181: Pseudo dice [0.8541] +2024-11-22 20:19:10.059260: Epoch time: 18.63 s +2024-11-22 20:19:10.962341: +2024-11-22 20:19:10.962775: Epoch 6161 +2024-11-22 20:19:10.962919: Current learning rate: 0.00266 +2024-11-22 20:19:30.290743: train_loss -0.8104 +2024-11-22 20:19:30.291004: val_loss -0.7345 +2024-11-22 20:19:30.291082: Pseudo dice [0.8513] +2024-11-22 20:19:30.291163: Epoch time: 19.33 s +2024-11-22 20:19:31.228445: +2024-11-22 20:19:31.228870: Epoch 6162 +2024-11-22 20:19:31.229013: Current learning rate: 0.00266 +2024-11-22 20:19:49.919612: train_loss -0.8195 +2024-11-22 20:19:49.919825: val_loss -0.7667 +2024-11-22 20:19:49.919899: Pseudo dice [0.8822] +2024-11-22 20:19:49.919978: Epoch time: 18.69 s +2024-11-22 20:19:50.830881: +2024-11-22 20:19:50.831317: Epoch 6163 +2024-11-22 20:19:50.831454: Current learning rate: 0.00266 +2024-11-22 20:20:09.004860: train_loss -0.8101 +2024-11-22 20:20:09.005090: val_loss -0.7715 +2024-11-22 20:20:09.005170: Pseudo dice [0.8595] +2024-11-22 20:20:09.005298: Epoch time: 18.17 s +2024-11-22 20:20:09.005361: Yayy! New best EMA pseudo Dice: 0.855 +2024-11-22 20:20:10.215280: +2024-11-22 20:20:10.215695: Epoch 6164 +2024-11-22 20:20:10.215828: Current learning rate: 0.00266 +2024-11-22 20:20:29.618206: train_loss -0.8076 +2024-11-22 20:20:29.618453: val_loss -0.7559 +2024-11-22 20:20:29.618528: Pseudo dice [0.8666] +2024-11-22 20:20:29.618614: Epoch time: 19.4 s +2024-11-22 20:20:29.618675: Yayy! New best EMA pseudo Dice: 0.8561 +2024-11-22 20:20:30.818417: +2024-11-22 20:20:30.818869: Epoch 6165 +2024-11-22 20:20:30.819011: Current learning rate: 0.00266 +2024-11-22 20:20:50.165053: train_loss -0.8121 +2024-11-22 20:20:50.165332: val_loss -0.7934 +2024-11-22 20:20:50.165414: Pseudo dice [0.8402] +2024-11-22 20:20:50.165506: Epoch time: 19.35 s +2024-11-22 20:20:51.096575: +2024-11-22 20:20:51.097087: Epoch 6166 +2024-11-22 20:20:51.097222: Current learning rate: 0.00266 +2024-11-22 20:21:09.874287: train_loss -0.8138 +2024-11-22 20:21:09.874547: val_loss -0.7653 +2024-11-22 20:21:09.874627: Pseudo dice [0.8542] +2024-11-22 20:21:09.874707: Epoch time: 18.78 s +2024-11-22 20:21:10.779895: +2024-11-22 20:21:10.780370: Epoch 6167 +2024-11-22 20:21:10.780513: Current learning rate: 0.00266 +2024-11-22 20:21:29.609420: train_loss -0.8134 +2024-11-22 20:21:29.609639: val_loss -0.7724 +2024-11-22 20:21:29.609713: Pseudo dice [0.8698] +2024-11-22 20:21:29.609797: Epoch time: 18.83 s +2024-11-22 20:21:30.523308: +2024-11-22 20:21:30.523741: Epoch 6168 +2024-11-22 20:21:30.523865: Current learning rate: 0.00265 +2024-11-22 20:21:49.215335: train_loss -0.8146 +2024-11-22 20:21:49.215585: val_loss -0.7647 +2024-11-22 20:21:49.215677: Pseudo dice [0.8427] +2024-11-22 20:21:49.215755: Epoch time: 18.69 s +2024-11-22 20:21:50.121189: +2024-11-22 20:21:50.121678: Epoch 6169 +2024-11-22 20:21:50.121816: Current learning rate: 0.00265 +2024-11-22 20:22:08.529503: train_loss -0.8139 +2024-11-22 20:22:08.529784: val_loss -0.7625 +2024-11-22 20:22:08.529861: Pseudo dice [0.8339] +2024-11-22 20:22:08.529937: Epoch time: 18.41 s +2024-11-22 20:22:09.441393: +2024-11-22 20:22:09.441817: Epoch 6170 +2024-11-22 20:22:09.441951: Current learning rate: 0.00265 +2024-11-22 20:22:27.915620: train_loss -0.8129 +2024-11-22 20:22:27.915836: val_loss -0.7427 +2024-11-22 20:22:27.915907: Pseudo dice [0.8587] +2024-11-22 20:22:27.915982: Epoch time: 18.48 s +2024-11-22 20:22:28.822477: +2024-11-22 20:22:28.822874: Epoch 6171 +2024-11-22 20:22:28.823010: Current learning rate: 0.00265 +2024-11-22 20:22:47.289724: train_loss -0.8185 +2024-11-22 20:22:47.289941: val_loss -0.7177 +2024-11-22 20:22:47.290020: Pseudo dice [0.8241] +2024-11-22 20:22:47.290097: Epoch time: 18.47 s +2024-11-22 20:22:48.197819: +2024-11-22 20:22:48.198244: Epoch 6172 +2024-11-22 20:22:48.198377: Current learning rate: 0.00265 +2024-11-22 20:23:07.280182: train_loss -0.803 +2024-11-22 20:23:07.280441: val_loss -0.7217 +2024-11-22 20:23:07.280527: Pseudo dice [0.8326] +2024-11-22 20:23:07.280617: Epoch time: 19.08 s +2024-11-22 20:23:08.198395: +2024-11-22 20:23:08.198871: Epoch 6173 +2024-11-22 20:23:08.199016: Current learning rate: 0.00265 +2024-11-22 20:23:26.973946: train_loss -0.7863 +2024-11-22 20:23:26.974172: val_loss -0.7608 +2024-11-22 20:23:26.974247: Pseudo dice [0.8569] +2024-11-22 20:23:26.974324: Epoch time: 18.78 s +2024-11-22 20:23:27.955428: +2024-11-22 20:23:27.955905: Epoch 6174 +2024-11-22 20:23:27.956047: Current learning rate: 0.00265 +2024-11-22 20:23:46.786427: train_loss -0.7943 +2024-11-22 20:23:46.786650: val_loss -0.7648 +2024-11-22 20:23:46.786724: Pseudo dice [0.8327] +2024-11-22 20:23:46.786801: Epoch time: 18.83 s +2024-11-22 20:23:47.735491: +2024-11-22 20:23:47.735906: Epoch 6175 +2024-11-22 20:23:47.736045: Current learning rate: 0.00264 +2024-11-22 20:24:05.715883: train_loss -0.8075 +2024-11-22 20:24:05.716115: val_loss -0.7513 +2024-11-22 20:24:05.716191: Pseudo dice [0.8627] +2024-11-22 20:24:05.716271: Epoch time: 17.98 s +2024-11-22 20:24:06.633550: +2024-11-22 20:24:06.633976: Epoch 6176 +2024-11-22 20:24:06.634114: Current learning rate: 0.00264 +2024-11-22 20:24:25.341694: train_loss -0.8055 +2024-11-22 20:24:25.341999: val_loss -0.7585 +2024-11-22 20:24:25.342079: Pseudo dice [0.8611] +2024-11-22 20:24:25.342161: Epoch time: 18.71 s +2024-11-22 20:24:26.253878: +2024-11-22 20:24:26.254317: Epoch 6177 +2024-11-22 20:24:26.254450: Current learning rate: 0.00264 +2024-11-22 20:24:45.316258: train_loss -0.8083 +2024-11-22 20:24:45.316471: val_loss -0.7342 +2024-11-22 20:24:45.316550: Pseudo dice [0.8557] +2024-11-22 20:24:45.316633: Epoch time: 19.06 s +2024-11-22 20:24:46.585691: +2024-11-22 20:24:46.586153: Epoch 6178 +2024-11-22 20:24:46.586287: Current learning rate: 0.00264 +2024-11-22 20:25:05.155090: train_loss -0.8069 +2024-11-22 20:25:05.155597: val_loss -0.7674 +2024-11-22 20:25:05.155694: Pseudo dice [0.8601] +2024-11-22 20:25:05.155774: Epoch time: 18.57 s +2024-11-22 20:25:06.055604: +2024-11-22 20:25:06.055863: Epoch 6179 +2024-11-22 20:25:06.055973: Current learning rate: 0.00264 +2024-11-22 20:25:24.466246: train_loss -0.8099 +2024-11-22 20:25:24.466507: val_loss -0.7812 +2024-11-22 20:25:24.466597: Pseudo dice [0.8475] +2024-11-22 20:25:24.466687: Epoch time: 18.41 s +2024-11-22 20:25:25.375803: +2024-11-22 20:25:25.376029: Epoch 6180 +2024-11-22 20:25:25.376140: Current learning rate: 0.00264 +2024-11-22 20:25:43.634904: train_loss -0.8088 +2024-11-22 20:25:43.635134: val_loss -0.7601 +2024-11-22 20:25:43.635209: Pseudo dice [0.8307] +2024-11-22 20:25:43.635284: Epoch time: 18.26 s +2024-11-22 20:25:44.544787: +2024-11-22 20:25:44.545012: Epoch 6181 +2024-11-22 20:25:44.545127: Current learning rate: 0.00264 +2024-11-22 20:26:02.895787: train_loss -0.8053 +2024-11-22 20:26:02.896036: val_loss -0.7292 +2024-11-22 20:26:02.896118: Pseudo dice [0.8489] +2024-11-22 20:26:02.896203: Epoch time: 18.35 s +2024-11-22 20:26:03.804207: +2024-11-22 20:26:03.804427: Epoch 6182 +2024-11-22 20:26:03.804538: Current learning rate: 0.00264 +2024-11-22 20:26:21.686361: train_loss -0.8158 +2024-11-22 20:26:21.686582: val_loss -0.7438 +2024-11-22 20:26:21.686658: Pseudo dice [0.8485] +2024-11-22 20:26:21.686743: Epoch time: 17.88 s +2024-11-22 20:26:22.587943: +2024-11-22 20:26:22.588169: Epoch 6183 +2024-11-22 20:26:22.588432: Current learning rate: 0.00263 +2024-11-22 20:26:40.932475: train_loss -0.8116 +2024-11-22 20:26:40.932690: val_loss -0.7085 +2024-11-22 20:26:40.932765: Pseudo dice [0.8389] +2024-11-22 20:26:40.932843: Epoch time: 18.35 s +2024-11-22 20:26:41.848555: +2024-11-22 20:26:41.848789: Epoch 6184 +2024-11-22 20:26:41.848896: Current learning rate: 0.00263 +2024-11-22 20:27:00.375610: train_loss -0.807 +2024-11-22 20:27:00.375906: val_loss -0.7482 +2024-11-22 20:27:00.376014: Pseudo dice [0.8465] +2024-11-22 20:27:00.376097: Epoch time: 18.53 s +2024-11-22 20:27:01.300025: +2024-11-22 20:27:01.300218: Epoch 6185 +2024-11-22 20:27:01.300319: Current learning rate: 0.00263 +2024-11-22 20:27:19.678433: train_loss -0.7982 +2024-11-22 20:27:19.678640: val_loss -0.7539 +2024-11-22 20:27:19.678717: Pseudo dice [0.8529] +2024-11-22 20:27:19.678792: Epoch time: 18.38 s +2024-11-22 20:27:20.597167: +2024-11-22 20:27:20.597428: Epoch 6186 +2024-11-22 20:27:20.597544: Current learning rate: 0.00263 +2024-11-22 20:27:38.487682: train_loss -0.816 +2024-11-22 20:27:38.487915: val_loss -0.7664 +2024-11-22 20:27:38.493266: Pseudo dice [0.8662] +2024-11-22 20:27:38.493366: Epoch time: 17.89 s +2024-11-22 20:27:39.505164: +2024-11-22 20:27:39.505357: Epoch 6187 +2024-11-22 20:27:39.505466: Current learning rate: 0.00263 +2024-11-22 20:27:58.448309: train_loss -0.8074 +2024-11-22 20:27:58.448558: val_loss -0.7838 +2024-11-22 20:27:58.448636: Pseudo dice [0.8542] +2024-11-22 20:27:58.448722: Epoch time: 18.94 s +2024-11-22 20:27:59.359176: +2024-11-22 20:27:59.359390: Epoch 6188 +2024-11-22 20:27:59.359501: Current learning rate: 0.00263 +2024-11-22 20:28:19.397574: train_loss -0.8125 +2024-11-22 20:28:19.397792: val_loss -0.7352 +2024-11-22 20:28:19.397867: Pseudo dice [0.859] +2024-11-22 20:28:19.397942: Epoch time: 20.04 s +2024-11-22 20:28:20.662179: +2024-11-22 20:28:20.662374: Epoch 6189 +2024-11-22 20:28:20.662482: Current learning rate: 0.00263 +2024-11-22 20:28:39.320218: train_loss -0.8152 +2024-11-22 20:28:39.320473: val_loss -0.7726 +2024-11-22 20:28:39.320548: Pseudo dice [0.8485] +2024-11-22 20:28:39.320627: Epoch time: 18.66 s +2024-11-22 20:28:40.235305: +2024-11-22 20:28:40.235516: Epoch 6190 +2024-11-22 20:28:40.235627: Current learning rate: 0.00263 +2024-11-22 20:29:00.227674: train_loss -0.8124 +2024-11-22 20:29:00.227902: val_loss -0.774 +2024-11-22 20:29:00.227985: Pseudo dice [0.8467] +2024-11-22 20:29:00.228074: Epoch time: 19.99 s +2024-11-22 20:29:01.136361: +2024-11-22 20:29:01.136575: Epoch 6191 +2024-11-22 20:29:01.136685: Current learning rate: 0.00262 +2024-11-22 20:29:19.919595: train_loss -0.8075 +2024-11-22 20:29:19.919831: val_loss -0.7648 +2024-11-22 20:29:19.919903: Pseudo dice [0.8678] +2024-11-22 20:29:19.919984: Epoch time: 18.78 s +2024-11-22 20:29:20.827564: +2024-11-22 20:29:20.827772: Epoch 6192 +2024-11-22 20:29:20.827888: Current learning rate: 0.00262 +2024-11-22 20:29:38.222093: train_loss -0.8099 +2024-11-22 20:29:38.224481: val_loss -0.7608 +2024-11-22 20:29:38.224618: Pseudo dice [0.8396] +2024-11-22 20:29:38.224700: Epoch time: 17.4 s +2024-11-22 20:29:39.313394: +2024-11-22 20:29:39.313618: Epoch 6193 +2024-11-22 20:29:39.313731: Current learning rate: 0.00262 +2024-11-22 20:29:58.084300: train_loss -0.814 +2024-11-22 20:29:58.084574: val_loss -0.7473 +2024-11-22 20:29:58.084654: Pseudo dice [0.8412] +2024-11-22 20:29:58.084730: Epoch time: 18.77 s +2024-11-22 20:29:59.085621: +2024-11-22 20:29:59.085835: Epoch 6194 +2024-11-22 20:29:59.085945: Current learning rate: 0.00262 +2024-11-22 20:30:17.595284: train_loss -0.8146 +2024-11-22 20:30:17.595512: val_loss -0.7389 +2024-11-22 20:30:17.595586: Pseudo dice [0.8395] +2024-11-22 20:30:17.595666: Epoch time: 18.51 s +2024-11-22 20:30:18.495064: +2024-11-22 20:30:18.495270: Epoch 6195 +2024-11-22 20:30:18.495376: Current learning rate: 0.00262 +2024-11-22 20:30:36.932561: train_loss -0.8185 +2024-11-22 20:30:36.932792: val_loss -0.7691 +2024-11-22 20:30:36.932865: Pseudo dice [0.8551] +2024-11-22 20:30:36.932976: Epoch time: 18.44 s +2024-11-22 20:30:37.828972: +2024-11-22 20:30:37.829185: Epoch 6196 +2024-11-22 20:30:37.829296: Current learning rate: 0.00262 +2024-11-22 20:30:56.153615: train_loss -0.8072 +2024-11-22 20:30:56.153839: val_loss -0.7853 +2024-11-22 20:30:56.153918: Pseudo dice [0.8548] +2024-11-22 20:30:56.154003: Epoch time: 18.33 s +2024-11-22 20:30:57.051893: +2024-11-22 20:30:57.052094: Epoch 6197 +2024-11-22 20:30:57.052206: Current learning rate: 0.00262 +2024-11-22 20:31:16.170707: train_loss -0.8075 +2024-11-22 20:31:16.170930: val_loss -0.7331 +2024-11-22 20:31:16.171011: Pseudo dice [0.8349] +2024-11-22 20:31:16.176251: Epoch time: 19.12 s +2024-11-22 20:31:17.080358: +2024-11-22 20:31:17.080568: Epoch 6198 +2024-11-22 20:31:17.080678: Current learning rate: 0.00261 +2024-11-22 20:31:37.260623: train_loss -0.808 +2024-11-22 20:31:37.260875: val_loss -0.7317 +2024-11-22 20:31:37.260959: Pseudo dice [0.8595] +2024-11-22 20:31:37.261049: Epoch time: 20.18 s +2024-11-22 20:31:38.169144: +2024-11-22 20:31:38.169442: Epoch 6199 +2024-11-22 20:31:38.169556: Current learning rate: 0.00261 +2024-11-22 20:31:56.878043: train_loss -0.8127 +2024-11-22 20:31:56.878277: val_loss -0.7665 +2024-11-22 20:31:56.878351: Pseudo dice [0.8446] +2024-11-22 20:31:56.880683: Epoch time: 18.71 s +2024-11-22 20:31:58.135442: +2024-11-22 20:31:58.135697: Epoch 6200 +2024-11-22 20:31:58.135807: Current learning rate: 0.00261 +2024-11-22 20:32:15.930350: train_loss -0.8202 +2024-11-22 20:32:15.930569: val_loss -0.7429 +2024-11-22 20:32:15.930648: Pseudo dice [0.8478] +2024-11-22 20:32:15.930724: Epoch time: 17.8 s +2024-11-22 20:32:17.295149: +2024-11-22 20:32:17.295367: Epoch 6201 +2024-11-22 20:32:17.295479: Current learning rate: 0.00261 +2024-11-22 20:32:35.495847: train_loss -0.8101 +2024-11-22 20:32:35.496094: val_loss -0.7653 +2024-11-22 20:32:35.496186: Pseudo dice [0.8574] +2024-11-22 20:32:35.496264: Epoch time: 18.2 s +2024-11-22 20:32:36.521899: +2024-11-22 20:32:36.522160: Epoch 6202 +2024-11-22 20:32:36.522284: Current learning rate: 0.00261 +2024-11-22 20:32:55.271235: train_loss -0.8075 +2024-11-22 20:32:55.276680: val_loss -0.7388 +2024-11-22 20:32:55.276770: Pseudo dice [0.8547] +2024-11-22 20:32:55.276860: Epoch time: 18.75 s +2024-11-22 20:32:56.423816: +2024-11-22 20:32:56.424097: Epoch 6203 +2024-11-22 20:32:56.424208: Current learning rate: 0.00261 +2024-11-22 20:33:15.607702: train_loss -0.8144 +2024-11-22 20:33:15.607920: val_loss -0.7251 +2024-11-22 20:33:15.608000: Pseudo dice [0.8491] +2024-11-22 20:33:15.608075: Epoch time: 19.18 s +2024-11-22 20:33:16.514777: +2024-11-22 20:33:16.514986: Epoch 6204 +2024-11-22 20:33:16.515101: Current learning rate: 0.00261 +2024-11-22 20:33:34.954184: train_loss -0.8137 +2024-11-22 20:33:34.954388: val_loss -0.7729 +2024-11-22 20:33:34.954461: Pseudo dice [0.8452] +2024-11-22 20:33:34.954536: Epoch time: 18.44 s +2024-11-22 20:33:35.856094: +2024-11-22 20:33:35.856311: Epoch 6205 +2024-11-22 20:33:35.856421: Current learning rate: 0.00261 +2024-11-22 20:33:54.860380: train_loss -0.8116 +2024-11-22 20:33:54.860600: val_loss -0.7551 +2024-11-22 20:33:54.860672: Pseudo dice [0.8551] +2024-11-22 20:33:54.860748: Epoch time: 19.01 s +2024-11-22 20:33:55.766190: +2024-11-22 20:33:55.766400: Epoch 6206 +2024-11-22 20:33:55.766514: Current learning rate: 0.0026 +2024-11-22 20:34:14.088175: train_loss -0.8175 +2024-11-22 20:34:14.088427: val_loss -0.7502 +2024-11-22 20:34:14.088591: Pseudo dice [0.8609] +2024-11-22 20:34:14.088676: Epoch time: 18.32 s +2024-11-22 20:34:14.998620: +2024-11-22 20:34:14.998845: Epoch 6207 +2024-11-22 20:34:14.998962: Current learning rate: 0.0026 +2024-11-22 20:34:34.562564: train_loss -0.8119 +2024-11-22 20:34:34.562793: val_loss -0.776 +2024-11-22 20:34:34.562869: Pseudo dice [0.8454] +2024-11-22 20:34:34.562947: Epoch time: 19.56 s +2024-11-22 20:34:35.473676: +2024-11-22 20:34:35.473959: Epoch 6208 +2024-11-22 20:34:35.474082: Current learning rate: 0.0026 +2024-11-22 20:34:53.941493: train_loss -0.813 +2024-11-22 20:34:53.941716: val_loss -0.7297 +2024-11-22 20:34:53.941791: Pseudo dice [0.8384] +2024-11-22 20:34:53.941882: Epoch time: 18.47 s +2024-11-22 20:34:54.851598: +2024-11-22 20:34:54.851831: Epoch 6209 +2024-11-22 20:34:54.852087: Current learning rate: 0.0026 +2024-11-22 20:35:13.404475: train_loss -0.8177 +2024-11-22 20:35:13.404698: val_loss -0.7747 +2024-11-22 20:35:13.404773: Pseudo dice [0.8693] +2024-11-22 20:35:13.404849: Epoch time: 18.55 s +2024-11-22 20:35:14.315053: +2024-11-22 20:35:14.315263: Epoch 6210 +2024-11-22 20:35:14.315372: Current learning rate: 0.0026 +2024-11-22 20:35:31.826435: train_loss -0.8173 +2024-11-22 20:35:31.826707: val_loss -0.7429 +2024-11-22 20:35:31.826831: Pseudo dice [0.8354] +2024-11-22 20:35:31.826916: Epoch time: 17.51 s +2024-11-22 20:35:32.738234: +2024-11-22 20:35:32.738446: Epoch 6211 +2024-11-22 20:35:32.738549: Current learning rate: 0.0026 +2024-11-22 20:35:51.166616: train_loss -0.8163 +2024-11-22 20:35:51.166837: val_loss -0.7669 +2024-11-22 20:35:51.166911: Pseudo dice [0.8477] +2024-11-22 20:35:51.166988: Epoch time: 18.43 s +2024-11-22 20:35:52.902570: +2024-11-22 20:35:52.902793: Epoch 6212 +2024-11-22 20:35:52.902909: Current learning rate: 0.0026 +2024-11-22 20:36:11.123226: train_loss -0.8154 +2024-11-22 20:36:11.123473: val_loss -0.7651 +2024-11-22 20:36:11.123547: Pseudo dice [0.8378] +2024-11-22 20:36:11.123620: Epoch time: 18.22 s +2024-11-22 20:36:12.066778: +2024-11-22 20:36:12.067007: Epoch 6213 +2024-11-22 20:36:12.067118: Current learning rate: 0.00259 +2024-11-22 20:36:30.272740: train_loss -0.8142 +2024-11-22 20:36:30.274841: val_loss -0.7654 +2024-11-22 20:36:30.274944: Pseudo dice [0.8536] +2024-11-22 20:36:30.275056: Epoch time: 18.21 s +2024-11-22 20:36:31.287568: +2024-11-22 20:36:31.287777: Epoch 6214 +2024-11-22 20:36:31.287890: Current learning rate: 0.00259 +2024-11-22 20:36:50.615286: train_loss -0.8091 +2024-11-22 20:36:50.615499: val_loss -0.7346 +2024-11-22 20:36:50.615574: Pseudo dice [0.8154] +2024-11-22 20:36:50.615649: Epoch time: 19.33 s +2024-11-22 20:36:51.527044: +2024-11-22 20:36:51.527250: Epoch 6215 +2024-11-22 20:36:51.527365: Current learning rate: 0.00259 +2024-11-22 20:37:11.041490: train_loss -0.8136 +2024-11-22 20:37:11.041711: val_loss -0.7507 +2024-11-22 20:37:11.041784: Pseudo dice [0.8506] +2024-11-22 20:37:11.041860: Epoch time: 19.52 s +2024-11-22 20:37:12.041698: +2024-11-22 20:37:12.041901: Epoch 6216 +2024-11-22 20:37:12.042042: Current learning rate: 0.00259 +2024-11-22 20:37:31.456493: train_loss -0.8008 +2024-11-22 20:37:31.456777: val_loss -0.7402 +2024-11-22 20:37:31.456853: Pseudo dice [0.8548] +2024-11-22 20:37:31.456931: Epoch time: 19.42 s +2024-11-22 20:37:32.412108: +2024-11-22 20:37:32.412346: Epoch 6217 +2024-11-22 20:37:32.412462: Current learning rate: 0.00259 +2024-11-22 20:37:50.598143: train_loss -0.8106 +2024-11-22 20:37:50.598371: val_loss -0.7451 +2024-11-22 20:37:50.598447: Pseudo dice [0.8538] +2024-11-22 20:37:50.598534: Epoch time: 18.19 s +2024-11-22 20:37:51.514638: +2024-11-22 20:37:51.514871: Epoch 6218 +2024-11-22 20:37:51.514979: Current learning rate: 0.00259 +2024-11-22 20:38:09.929750: train_loss -0.8156 +2024-11-22 20:38:09.930001: val_loss -0.7637 +2024-11-22 20:38:09.930078: Pseudo dice [0.8474] +2024-11-22 20:38:09.930156: Epoch time: 18.42 s +2024-11-22 20:38:10.838855: +2024-11-22 20:38:10.839048: Epoch 6219 +2024-11-22 20:38:10.839158: Current learning rate: 0.00259 +2024-11-22 20:38:29.033545: train_loss -0.8145 +2024-11-22 20:38:29.033772: val_loss -0.7609 +2024-11-22 20:38:29.033852: Pseudo dice [0.8717] +2024-11-22 20:38:29.033928: Epoch time: 18.2 s +2024-11-22 20:38:29.939534: +2024-11-22 20:38:29.939740: Epoch 6220 +2024-11-22 20:38:29.939850: Current learning rate: 0.00259 +2024-11-22 20:38:48.611381: train_loss -0.8083 +2024-11-22 20:38:48.611605: val_loss -0.7427 +2024-11-22 20:38:48.611678: Pseudo dice [0.857] +2024-11-22 20:38:48.611752: Epoch time: 18.67 s +2024-11-22 20:38:49.562387: +2024-11-22 20:38:49.562592: Epoch 6221 +2024-11-22 20:38:49.562707: Current learning rate: 0.00258 +2024-11-22 20:39:08.525505: train_loss -0.8156 +2024-11-22 20:39:08.525845: val_loss -0.764 +2024-11-22 20:39:08.525926: Pseudo dice [0.8306] +2024-11-22 20:39:08.526015: Epoch time: 18.96 s +2024-11-22 20:39:09.441026: +2024-11-22 20:39:09.441219: Epoch 6222 +2024-11-22 20:39:09.441336: Current learning rate: 0.00258 +2024-11-22 20:39:27.582115: train_loss -0.8152 +2024-11-22 20:39:27.582333: val_loss -0.7382 +2024-11-22 20:39:27.582418: Pseudo dice [0.8515] +2024-11-22 20:39:27.582495: Epoch time: 18.14 s +2024-11-22 20:39:28.493458: +2024-11-22 20:39:28.493680: Epoch 6223 +2024-11-22 20:39:28.493788: Current learning rate: 0.00258 +2024-11-22 20:39:47.117045: train_loss -0.8102 +2024-11-22 20:39:47.117340: val_loss -0.7423 +2024-11-22 20:39:47.117424: Pseudo dice [0.8511] +2024-11-22 20:39:47.117503: Epoch time: 18.62 s +2024-11-22 20:39:48.436141: +2024-11-22 20:39:48.436377: Epoch 6224 +2024-11-22 20:39:48.436486: Current learning rate: 0.00258 +2024-11-22 20:40:07.902305: train_loss -0.82 +2024-11-22 20:40:07.902534: val_loss -0.7633 +2024-11-22 20:40:07.902616: Pseudo dice [0.8682] +2024-11-22 20:40:07.902709: Epoch time: 19.47 s +2024-11-22 20:40:08.821706: +2024-11-22 20:40:08.821963: Epoch 6225 +2024-11-22 20:40:08.822113: Current learning rate: 0.00258 +2024-11-22 20:40:27.279141: train_loss -0.8143 +2024-11-22 20:40:27.279361: val_loss -0.7434 +2024-11-22 20:40:27.279437: Pseudo dice [0.8331] +2024-11-22 20:40:27.279516: Epoch time: 18.46 s +2024-11-22 20:40:28.192542: +2024-11-22 20:40:28.193004: Epoch 6226 +2024-11-22 20:40:28.193115: Current learning rate: 0.00258 +2024-11-22 20:40:47.452581: train_loss -0.8046 +2024-11-22 20:40:47.452830: val_loss -0.7621 +2024-11-22 20:40:47.452907: Pseudo dice [0.8487] +2024-11-22 20:40:47.452983: Epoch time: 19.26 s +2024-11-22 20:40:48.455051: +2024-11-22 20:40:48.455267: Epoch 6227 +2024-11-22 20:40:48.455383: Current learning rate: 0.00258 +2024-11-22 20:41:07.414701: train_loss -0.8083 +2024-11-22 20:41:07.414923: val_loss -0.7419 +2024-11-22 20:41:07.415005: Pseudo dice [0.8353] +2024-11-22 20:41:07.415079: Epoch time: 18.96 s +2024-11-22 20:41:08.325082: +2024-11-22 20:41:08.325282: Epoch 6228 +2024-11-22 20:41:08.325390: Current learning rate: 0.00258 +2024-11-22 20:41:27.812068: train_loss -0.8139 +2024-11-22 20:41:27.812312: val_loss -0.7524 +2024-11-22 20:41:27.812444: Pseudo dice [0.8606] +2024-11-22 20:41:27.812530: Epoch time: 19.49 s +2024-11-22 20:41:28.726652: +2024-11-22 20:41:28.726905: Epoch 6229 +2024-11-22 20:41:28.727017: Current learning rate: 0.00257 +2024-11-22 20:41:47.460742: train_loss -0.8159 +2024-11-22 20:41:47.460980: val_loss -0.7581 +2024-11-22 20:41:47.461062: Pseudo dice [0.8553] +2024-11-22 20:41:47.461138: Epoch time: 18.73 s +2024-11-22 20:41:48.376693: +2024-11-22 20:41:48.376924: Epoch 6230 +2024-11-22 20:41:48.377038: Current learning rate: 0.00257 +2024-11-22 20:42:06.867844: train_loss -0.8146 +2024-11-22 20:42:06.868082: val_loss -0.7656 +2024-11-22 20:42:06.868159: Pseudo dice [0.8458] +2024-11-22 20:42:06.868234: Epoch time: 18.49 s +2024-11-22 20:42:07.792404: +2024-11-22 20:42:07.792621: Epoch 6231 +2024-11-22 20:42:07.792733: Current learning rate: 0.00257 +2024-11-22 20:42:26.788776: train_loss -0.8124 +2024-11-22 20:42:26.789004: val_loss -0.7537 +2024-11-22 20:42:26.789082: Pseudo dice [0.8528] +2024-11-22 20:42:26.789167: Epoch time: 19.0 s +2024-11-22 20:42:27.697024: +2024-11-22 20:42:27.697242: Epoch 6232 +2024-11-22 20:42:27.697354: Current learning rate: 0.00257 +2024-11-22 20:42:46.471964: train_loss -0.8152 +2024-11-22 20:42:46.472237: val_loss -0.7167 +2024-11-22 20:42:46.472311: Pseudo dice [0.8504] +2024-11-22 20:42:46.472397: Epoch time: 18.78 s +2024-11-22 20:42:47.383127: +2024-11-22 20:42:47.383347: Epoch 6233 +2024-11-22 20:42:47.383473: Current learning rate: 0.00257 +2024-11-22 20:43:06.193983: train_loss -0.805 +2024-11-22 20:43:06.196361: val_loss -0.7769 +2024-11-22 20:43:06.196450: Pseudo dice [0.8689] +2024-11-22 20:43:06.196527: Epoch time: 18.81 s +2024-11-22 20:43:07.302325: +2024-11-22 20:43:07.302529: Epoch 6234 +2024-11-22 20:43:07.302637: Current learning rate: 0.00257 +2024-11-22 20:43:25.518538: train_loss -0.8188 +2024-11-22 20:43:25.518775: val_loss -0.7532 +2024-11-22 20:43:25.518855: Pseudo dice [0.8442] +2024-11-22 20:43:25.518938: Epoch time: 18.22 s +2024-11-22 20:43:26.795343: +2024-11-22 20:43:26.795610: Epoch 6235 +2024-11-22 20:43:26.795726: Current learning rate: 0.00257 +2024-11-22 20:43:45.929606: train_loss -0.813 +2024-11-22 20:43:45.929929: val_loss -0.7643 +2024-11-22 20:43:45.930024: Pseudo dice [0.8502] +2024-11-22 20:43:45.930109: Epoch time: 19.14 s +2024-11-22 20:43:46.842105: +2024-11-22 20:43:46.842338: Epoch 6236 +2024-11-22 20:43:46.842450: Current learning rate: 0.00256 +2024-11-22 20:44:04.911045: train_loss -0.8164 +2024-11-22 20:44:04.913429: val_loss -0.7251 +2024-11-22 20:44:04.913526: Pseudo dice [0.8264] +2024-11-22 20:44:04.913605: Epoch time: 18.07 s +2024-11-22 20:44:05.866134: +2024-11-22 20:44:05.866352: Epoch 6237 +2024-11-22 20:44:05.866463: Current learning rate: 0.00256 +2024-11-22 20:44:23.731747: train_loss -0.8183 +2024-11-22 20:44:23.731966: val_loss -0.7481 +2024-11-22 20:44:23.732049: Pseudo dice [0.8333] +2024-11-22 20:44:23.732126: Epoch time: 17.87 s +2024-11-22 20:44:24.633384: +2024-11-22 20:44:24.633594: Epoch 6238 +2024-11-22 20:44:24.633705: Current learning rate: 0.00256 +2024-11-22 20:44:44.255076: train_loss -0.8186 +2024-11-22 20:44:44.255303: val_loss -0.7799 +2024-11-22 20:44:44.255379: Pseudo dice [0.8646] +2024-11-22 20:44:44.255461: Epoch time: 19.62 s +2024-11-22 20:44:45.169497: +2024-11-22 20:44:45.169762: Epoch 6239 +2024-11-22 20:44:45.169914: Current learning rate: 0.00256 +2024-11-22 20:45:03.700204: train_loss -0.809 +2024-11-22 20:45:03.700428: val_loss -0.7346 +2024-11-22 20:45:03.700503: Pseudo dice [0.8519] +2024-11-22 20:45:03.700583: Epoch time: 18.53 s +2024-11-22 20:45:04.616793: +2024-11-22 20:45:04.617107: Epoch 6240 +2024-11-22 20:45:04.617232: Current learning rate: 0.00256 +2024-11-22 20:45:22.333360: train_loss -0.8193 +2024-11-22 20:45:22.333583: val_loss -0.7515 +2024-11-22 20:45:22.333661: Pseudo dice [0.8609] +2024-11-22 20:45:22.333739: Epoch time: 17.72 s +2024-11-22 20:45:23.244766: +2024-11-22 20:45:23.244970: Epoch 6241 +2024-11-22 20:45:23.245092: Current learning rate: 0.00256 +2024-11-22 20:45:41.159513: train_loss -0.8147 +2024-11-22 20:45:41.160826: val_loss -0.7479 +2024-11-22 20:45:41.160902: Pseudo dice [0.843] +2024-11-22 20:45:41.160980: Epoch time: 17.92 s +2024-11-22 20:45:42.066588: +2024-11-22 20:45:42.066826: Epoch 6242 +2024-11-22 20:45:42.066939: Current learning rate: 0.00256 +2024-11-22 20:46:01.900787: train_loss -0.8136 +2024-11-22 20:46:01.901042: val_loss -0.7535 +2024-11-22 20:46:01.901118: Pseudo dice [0.8464] +2024-11-22 20:46:01.901202: Epoch time: 19.83 s +2024-11-22 20:46:02.814057: +2024-11-22 20:46:02.814282: Epoch 6243 +2024-11-22 20:46:02.814399: Current learning rate: 0.00256 +2024-11-22 20:46:21.771610: train_loss -0.8096 +2024-11-22 20:46:21.771842: val_loss -0.7526 +2024-11-22 20:46:21.771950: Pseudo dice [0.8681] +2024-11-22 20:46:21.772033: Epoch time: 18.96 s +2024-11-22 20:46:22.679847: +2024-11-22 20:46:22.680063: Epoch 6244 +2024-11-22 20:46:22.680176: Current learning rate: 0.00255 +2024-11-22 20:46:41.621396: train_loss -0.8119 +2024-11-22 20:46:41.621624: val_loss -0.7546 +2024-11-22 20:46:41.621700: Pseudo dice [0.8665] +2024-11-22 20:46:41.621775: Epoch time: 18.94 s +2024-11-22 20:46:42.538690: +2024-11-22 20:46:42.538893: Epoch 6245 +2024-11-22 20:46:42.539007: Current learning rate: 0.00255 +2024-11-22 20:47:01.933227: train_loss -0.822 +2024-11-22 20:47:01.933450: val_loss -0.7672 +2024-11-22 20:47:01.933528: Pseudo dice [0.8626] +2024-11-22 20:47:01.933623: Epoch time: 19.4 s +2024-11-22 20:47:02.842191: +2024-11-22 20:47:02.842395: Epoch 6246 +2024-11-22 20:47:02.842505: Current learning rate: 0.00255 +2024-11-22 20:47:22.736814: train_loss -0.8075 +2024-11-22 20:47:22.737102: val_loss -0.7316 +2024-11-22 20:47:22.737177: Pseudo dice [0.8365] +2024-11-22 20:47:22.737263: Epoch time: 19.9 s +2024-11-22 20:47:24.081398: +2024-11-22 20:47:24.081613: Epoch 6247 +2024-11-22 20:47:24.081728: Current learning rate: 0.00255 +2024-11-22 20:47:43.279486: train_loss -0.811 +2024-11-22 20:47:43.279708: val_loss -0.734 +2024-11-22 20:47:43.279858: Pseudo dice [0.8314] +2024-11-22 20:47:43.279941: Epoch time: 19.2 s +2024-11-22 20:47:44.200191: +2024-11-22 20:47:44.200397: Epoch 6248 +2024-11-22 20:47:44.200507: Current learning rate: 0.00255 +2024-11-22 20:48:01.999999: train_loss -0.8007 +2024-11-22 20:48:02.000220: val_loss -0.748 +2024-11-22 20:48:02.000294: Pseudo dice [0.8542] +2024-11-22 20:48:02.000373: Epoch time: 17.8 s +2024-11-22 20:48:02.918263: +2024-11-22 20:48:02.918481: Epoch 6249 +2024-11-22 20:48:02.918593: Current learning rate: 0.00255 +2024-11-22 20:48:22.754966: train_loss -0.8066 +2024-11-22 20:48:22.755216: val_loss -0.7524 +2024-11-22 20:48:22.755291: Pseudo dice [0.8321] +2024-11-22 20:48:22.755373: Epoch time: 19.84 s +2024-11-22 20:48:23.972190: +2024-11-22 20:48:23.972394: Epoch 6250 +2024-11-22 20:48:23.972505: Current learning rate: 0.00255 +2024-11-22 20:48:42.894393: train_loss -0.8089 +2024-11-22 20:48:42.894620: val_loss -0.7427 +2024-11-22 20:48:42.894697: Pseudo dice [0.8533] +2024-11-22 20:48:42.894774: Epoch time: 18.92 s +2024-11-22 20:48:43.810328: +2024-11-22 20:48:43.810557: Epoch 6251 +2024-11-22 20:48:43.810672: Current learning rate: 0.00255 +2024-11-22 20:49:02.797935: train_loss -0.8049 +2024-11-22 20:49:02.798155: val_loss -0.7803 +2024-11-22 20:49:02.798234: Pseudo dice [0.8631] +2024-11-22 20:49:02.798312: Epoch time: 18.99 s +2024-11-22 20:49:03.697432: +2024-11-22 20:49:03.697623: Epoch 6252 +2024-11-22 20:49:03.697736: Current learning rate: 0.00254 +2024-11-22 20:49:21.557587: train_loss -0.7915 +2024-11-22 20:49:21.557807: val_loss -0.7366 +2024-11-22 20:49:21.557885: Pseudo dice [0.8505] +2024-11-22 20:49:21.557979: Epoch time: 17.86 s +2024-11-22 20:49:22.468059: +2024-11-22 20:49:22.468286: Epoch 6253 +2024-11-22 20:49:22.468391: Current learning rate: 0.00254 +2024-11-22 20:49:41.434463: train_loss -0.8037 +2024-11-22 20:49:41.434714: val_loss -0.7698 +2024-11-22 20:49:41.434794: Pseudo dice [0.8681] +2024-11-22 20:49:41.434876: Epoch time: 18.97 s +2024-11-22 20:49:42.327380: +2024-11-22 20:49:42.327591: Epoch 6254 +2024-11-22 20:49:42.327706: Current learning rate: 0.00254 +2024-11-22 20:50:01.758363: train_loss -0.8062 +2024-11-22 20:50:01.758651: val_loss -0.7409 +2024-11-22 20:50:01.758732: Pseudo dice [0.8308] +2024-11-22 20:50:01.758814: Epoch time: 19.43 s +2024-11-22 20:50:02.664478: +2024-11-22 20:50:02.664702: Epoch 6255 +2024-11-22 20:50:02.664821: Current learning rate: 0.00254 +2024-11-22 20:50:22.556896: train_loss -0.8074 +2024-11-22 20:50:22.557116: val_loss -0.741 +2024-11-22 20:50:22.557188: Pseudo dice [0.8335] +2024-11-22 20:50:22.557264: Epoch time: 19.89 s +2024-11-22 20:50:23.650741: +2024-11-22 20:50:23.650970: Epoch 6256 +2024-11-22 20:50:23.651095: Current learning rate: 0.00254 +2024-11-22 20:50:42.798030: train_loss -0.7973 +2024-11-22 20:50:42.798244: val_loss -0.7369 +2024-11-22 20:50:42.798318: Pseudo dice [0.8517] +2024-11-22 20:50:42.803604: Epoch time: 19.15 s +2024-11-22 20:50:43.849585: +2024-11-22 20:50:43.849788: Epoch 6257 +2024-11-22 20:50:43.849901: Current learning rate: 0.00254 +2024-11-22 20:51:03.256749: train_loss -0.8097 +2024-11-22 20:51:03.257022: val_loss -0.7656 +2024-11-22 20:51:03.257131: Pseudo dice [0.8473] +2024-11-22 20:51:03.257248: Epoch time: 19.41 s +2024-11-22 20:51:04.588011: +2024-11-22 20:51:04.588222: Epoch 6258 +2024-11-22 20:51:04.588340: Current learning rate: 0.00254 +2024-11-22 20:51:23.625707: train_loss -0.805 +2024-11-22 20:51:23.626032: val_loss -0.7265 +2024-11-22 20:51:23.626115: Pseudo dice [0.8547] +2024-11-22 20:51:23.626189: Epoch time: 19.04 s +2024-11-22 20:51:24.536210: +2024-11-22 20:51:24.536643: Epoch 6259 +2024-11-22 20:51:24.536776: Current learning rate: 0.00253 +2024-11-22 20:51:43.933918: train_loss -0.8111 +2024-11-22 20:51:43.934154: val_loss -0.7582 +2024-11-22 20:51:43.934235: Pseudo dice [0.8379] +2024-11-22 20:51:43.934317: Epoch time: 19.4 s +2024-11-22 20:51:44.845809: +2024-11-22 20:51:44.846233: Epoch 6260 +2024-11-22 20:51:44.846362: Current learning rate: 0.00253 +2024-11-22 20:52:04.211483: train_loss -0.8131 +2024-11-22 20:52:04.211734: val_loss -0.7379 +2024-11-22 20:52:04.211809: Pseudo dice [0.8263] +2024-11-22 20:52:04.211891: Epoch time: 19.37 s +2024-11-22 20:52:05.146246: +2024-11-22 20:52:05.146693: Epoch 6261 +2024-11-22 20:52:05.146828: Current learning rate: 0.00253 +2024-11-22 20:52:23.806558: train_loss -0.8102 +2024-11-22 20:52:23.806784: val_loss -0.7582 +2024-11-22 20:52:23.806858: Pseudo dice [0.8444] +2024-11-22 20:52:23.806931: Epoch time: 18.66 s +2024-11-22 20:52:24.713665: +2024-11-22 20:52:24.714133: Epoch 6262 +2024-11-22 20:52:24.714282: Current learning rate: 0.00253 +2024-11-22 20:52:43.417978: train_loss -0.8145 +2024-11-22 20:52:43.418242: val_loss -0.7508 +2024-11-22 20:52:43.418317: Pseudo dice [0.8663] +2024-11-22 20:52:43.418393: Epoch time: 18.71 s +2024-11-22 20:52:44.326425: +2024-11-22 20:52:44.326874: Epoch 6263 +2024-11-22 20:52:44.327013: Current learning rate: 0.00253 +2024-11-22 20:53:02.372745: train_loss -0.8162 +2024-11-22 20:53:02.372979: val_loss -0.7549 +2024-11-22 20:53:02.373065: Pseudo dice [0.8683] +2024-11-22 20:53:02.373149: Epoch time: 18.05 s +2024-11-22 20:53:03.295409: +2024-11-22 20:53:03.295849: Epoch 6264 +2024-11-22 20:53:03.295995: Current learning rate: 0.00253 +2024-11-22 20:53:21.857256: train_loss -0.816 +2024-11-22 20:53:21.861381: val_loss -0.7286 +2024-11-22 20:53:21.861633: Pseudo dice [0.8438] +2024-11-22 20:53:21.861728: Epoch time: 18.56 s +2024-11-22 20:53:22.778800: +2024-11-22 20:53:22.779221: Epoch 6265 +2024-11-22 20:53:22.779363: Current learning rate: 0.00253 +2024-11-22 20:53:41.320820: train_loss -0.8146 +2024-11-22 20:53:41.321043: val_loss -0.7639 +2024-11-22 20:53:41.321120: Pseudo dice [0.8195] +2024-11-22 20:53:41.321194: Epoch time: 18.54 s +2024-11-22 20:53:42.232373: +2024-11-22 20:53:42.232779: Epoch 6266 +2024-11-22 20:53:42.232926: Current learning rate: 0.00253 +2024-11-22 20:54:01.309644: train_loss -0.8162 +2024-11-22 20:54:01.309860: val_loss -0.7697 +2024-11-22 20:54:01.309940: Pseudo dice [0.8423] +2024-11-22 20:54:01.310029: Epoch time: 19.08 s +2024-11-22 20:54:02.217660: +2024-11-22 20:54:02.218102: Epoch 6267 +2024-11-22 20:54:02.218236: Current learning rate: 0.00252 +2024-11-22 20:54:21.198192: train_loss -0.8125 +2024-11-22 20:54:21.198418: val_loss -0.7514 +2024-11-22 20:54:21.198495: Pseudo dice [0.8548] +2024-11-22 20:54:21.198576: Epoch time: 18.98 s +2024-11-22 20:54:22.215041: +2024-11-22 20:54:22.215483: Epoch 6268 +2024-11-22 20:54:22.215660: Current learning rate: 0.00252 +2024-11-22 20:54:40.504391: train_loss -0.8147 +2024-11-22 20:54:40.504653: val_loss -0.7625 +2024-11-22 20:54:40.504734: Pseudo dice [0.8671] +2024-11-22 20:54:40.504854: Epoch time: 18.29 s +2024-11-22 20:54:41.410576: +2024-11-22 20:54:41.410784: Epoch 6269 +2024-11-22 20:54:41.410894: Current learning rate: 0.00252 +2024-11-22 20:54:59.208233: train_loss -0.8136 +2024-11-22 20:54:59.208452: val_loss -0.7569 +2024-11-22 20:54:59.208531: Pseudo dice [0.8537] +2024-11-22 20:54:59.208615: Epoch time: 17.8 s +2024-11-22 20:55:00.542509: +2024-11-22 20:55:00.542758: Epoch 6270 +2024-11-22 20:55:00.542883: Current learning rate: 0.00252 +2024-11-22 20:55:19.157112: train_loss -0.8145 +2024-11-22 20:55:19.157346: val_loss -0.7553 +2024-11-22 20:55:19.157454: Pseudo dice [0.8474] +2024-11-22 20:55:19.157539: Epoch time: 18.62 s +2024-11-22 20:55:20.091490: +2024-11-22 20:55:20.091736: Epoch 6271 +2024-11-22 20:55:20.091852: Current learning rate: 0.00252 +2024-11-22 20:55:38.789016: train_loss -0.8071 +2024-11-22 20:55:38.789265: val_loss -0.7841 +2024-11-22 20:55:38.789339: Pseudo dice [0.8558] +2024-11-22 20:55:38.789418: Epoch time: 18.7 s +2024-11-22 20:55:39.706920: +2024-11-22 20:55:39.707461: Epoch 6272 +2024-11-22 20:55:39.707576: Current learning rate: 0.00252 +2024-11-22 20:55:58.613416: train_loss -0.8113 +2024-11-22 20:55:58.613711: val_loss -0.7615 +2024-11-22 20:55:58.613786: Pseudo dice [0.8646] +2024-11-22 20:55:58.613864: Epoch time: 18.91 s +2024-11-22 20:55:59.528431: +2024-11-22 20:55:59.528644: Epoch 6273 +2024-11-22 20:55:59.528758: Current learning rate: 0.00252 +2024-11-22 20:56:18.313289: train_loss -0.8148 +2024-11-22 20:56:18.313520: val_loss -0.7667 +2024-11-22 20:56:18.313595: Pseudo dice [0.8463] +2024-11-22 20:56:18.313677: Epoch time: 18.79 s +2024-11-22 20:56:19.227480: +2024-11-22 20:56:19.227720: Epoch 6274 +2024-11-22 20:56:19.227836: Current learning rate: 0.00252 +2024-11-22 20:56:37.762558: train_loss -0.8015 +2024-11-22 20:56:37.762794: val_loss -0.7673 +2024-11-22 20:56:37.762873: Pseudo dice [0.8544] +2024-11-22 20:56:37.762954: Epoch time: 18.54 s +2024-11-22 20:56:38.727448: +2024-11-22 20:56:38.727653: Epoch 6275 +2024-11-22 20:56:38.727765: Current learning rate: 0.00251 +2024-11-22 20:56:57.301095: train_loss -0.7975 +2024-11-22 20:56:57.301340: val_loss -0.7463 +2024-11-22 20:56:57.301416: Pseudo dice [0.8404] +2024-11-22 20:56:57.301498: Epoch time: 18.57 s +2024-11-22 20:56:58.224772: +2024-11-22 20:56:58.224969: Epoch 6276 +2024-11-22 20:56:58.225087: Current learning rate: 0.00251 +2024-11-22 20:57:17.970787: train_loss -0.8066 +2024-11-22 20:57:17.971026: val_loss -0.7365 +2024-11-22 20:57:17.971106: Pseudo dice [0.8446] +2024-11-22 20:57:17.971197: Epoch time: 19.75 s +2024-11-22 20:57:18.879812: +2024-11-22 20:57:18.880007: Epoch 6277 +2024-11-22 20:57:18.880116: Current learning rate: 0.00251 +2024-11-22 20:57:37.397963: train_loss -0.8146 +2024-11-22 20:57:37.398199: val_loss -0.7634 +2024-11-22 20:57:37.398273: Pseudo dice [0.8665] +2024-11-22 20:57:37.398350: Epoch time: 18.52 s +2024-11-22 20:57:38.340379: +2024-11-22 20:57:38.340582: Epoch 6278 +2024-11-22 20:57:38.340690: Current learning rate: 0.00251 +2024-11-22 20:57:56.833760: train_loss -0.8047 +2024-11-22 20:57:56.836111: val_loss -0.7357 +2024-11-22 20:57:56.836326: Pseudo dice [0.8327] +2024-11-22 20:57:56.836418: Epoch time: 18.49 s +2024-11-22 20:57:57.765822: +2024-11-22 20:57:57.766051: Epoch 6279 +2024-11-22 20:57:57.766161: Current learning rate: 0.00251 +2024-11-22 20:58:15.829557: train_loss -0.8112 +2024-11-22 20:58:15.829796: val_loss -0.7544 +2024-11-22 20:58:15.829870: Pseudo dice [0.8436] +2024-11-22 20:58:15.829951: Epoch time: 18.06 s +2024-11-22 20:58:16.898126: +2024-11-22 20:58:16.898328: Epoch 6280 +2024-11-22 20:58:16.898438: Current learning rate: 0.00251 +2024-11-22 20:58:35.608221: train_loss -0.7962 +2024-11-22 20:58:35.608442: val_loss -0.7504 +2024-11-22 20:58:35.608519: Pseudo dice [0.8382] +2024-11-22 20:58:35.608597: Epoch time: 18.71 s +2024-11-22 20:58:36.908498: +2024-11-22 20:58:36.908704: Epoch 6281 +2024-11-22 20:58:36.908819: Current learning rate: 0.00251 +2024-11-22 20:58:55.346102: train_loss -0.8182 +2024-11-22 20:58:55.351541: val_loss -0.7411 +2024-11-22 20:58:55.351681: Pseudo dice [0.8263] +2024-11-22 20:58:55.351764: Epoch time: 18.44 s +2024-11-22 20:58:56.269416: +2024-11-22 20:58:56.269669: Epoch 6282 +2024-11-22 20:58:56.269783: Current learning rate: 0.0025 +2024-11-22 20:59:14.745436: train_loss -0.815 +2024-11-22 20:59:14.746832: val_loss -0.7293 +2024-11-22 20:59:14.746937: Pseudo dice [0.8655] +2024-11-22 20:59:14.747031: Epoch time: 18.48 s +2024-11-22 20:59:15.661337: +2024-11-22 20:59:15.661579: Epoch 6283 +2024-11-22 20:59:15.661688: Current learning rate: 0.0025 +2024-11-22 20:59:33.323230: train_loss -0.8222 +2024-11-22 20:59:33.323452: val_loss -0.758 +2024-11-22 20:59:33.323549: Pseudo dice [0.8579] +2024-11-22 20:59:33.323635: Epoch time: 17.66 s +2024-11-22 20:59:34.234439: +2024-11-22 20:59:34.234641: Epoch 6284 +2024-11-22 20:59:34.234778: Current learning rate: 0.0025 +2024-11-22 20:59:52.086133: train_loss -0.818 +2024-11-22 20:59:52.086380: val_loss -0.7635 +2024-11-22 20:59:52.086457: Pseudo dice [0.8383] +2024-11-22 20:59:52.086537: Epoch time: 17.85 s +2024-11-22 20:59:53.020742: +2024-11-22 20:59:53.020983: Epoch 6285 +2024-11-22 20:59:53.021108: Current learning rate: 0.0025 +2024-11-22 21:00:11.490925: train_loss -0.8151 +2024-11-22 21:00:11.491151: val_loss -0.7587 +2024-11-22 21:00:11.491225: Pseudo dice [0.8336] +2024-11-22 21:00:11.491302: Epoch time: 18.47 s +2024-11-22 21:00:12.420358: +2024-11-22 21:00:12.420587: Epoch 6286 +2024-11-22 21:00:12.420705: Current learning rate: 0.0025 +2024-11-22 21:00:31.513086: train_loss -0.8114 +2024-11-22 21:00:31.513352: val_loss -0.7333 +2024-11-22 21:00:31.513428: Pseudo dice [0.8626] +2024-11-22 21:00:31.513514: Epoch time: 19.09 s +2024-11-22 21:00:32.430354: +2024-11-22 21:00:32.430566: Epoch 6287 +2024-11-22 21:00:32.430678: Current learning rate: 0.0025 +2024-11-22 21:00:50.702497: train_loss -0.8095 +2024-11-22 21:00:50.702701: val_loss -0.7615 +2024-11-22 21:00:50.702772: Pseudo dice [0.8602] +2024-11-22 21:00:50.702848: Epoch time: 18.27 s +2024-11-22 21:00:51.636100: +2024-11-22 21:00:51.636301: Epoch 6288 +2024-11-22 21:00:51.636412: Current learning rate: 0.0025 +2024-11-22 21:01:09.819221: train_loss -0.7989 +2024-11-22 21:01:09.819437: val_loss -0.7569 +2024-11-22 21:01:09.819516: Pseudo dice [0.8466] +2024-11-22 21:01:09.819595: Epoch time: 18.18 s +2024-11-22 21:01:10.807108: +2024-11-22 21:01:10.807314: Epoch 6289 +2024-11-22 21:01:10.807438: Current learning rate: 0.0025 +2024-11-22 21:01:29.352813: train_loss -0.7946 +2024-11-22 21:01:29.355048: val_loss -0.7473 +2024-11-22 21:01:29.355132: Pseudo dice [0.8216] +2024-11-22 21:01:29.355212: Epoch time: 18.55 s +2024-11-22 21:01:30.286721: +2024-11-22 21:01:30.286935: Epoch 6290 +2024-11-22 21:01:30.287052: Current learning rate: 0.00249 +2024-11-22 21:01:48.237402: train_loss -0.789 +2024-11-22 21:01:48.237654: val_loss -0.7619 +2024-11-22 21:01:48.237728: Pseudo dice [0.8416] +2024-11-22 21:01:48.237806: Epoch time: 17.95 s +2024-11-22 21:01:49.175936: +2024-11-22 21:01:49.176132: Epoch 6291 +2024-11-22 21:01:49.176242: Current learning rate: 0.00249 +2024-11-22 21:02:08.360505: train_loss -0.8119 +2024-11-22 21:02:08.360716: val_loss -0.7305 +2024-11-22 21:02:08.360789: Pseudo dice [0.8272] +2024-11-22 21:02:08.360870: Epoch time: 19.19 s +2024-11-22 21:02:09.270624: +2024-11-22 21:02:09.270823: Epoch 6292 +2024-11-22 21:02:09.270941: Current learning rate: 0.00249 +2024-11-22 21:02:27.582238: train_loss -0.8081 +2024-11-22 21:02:27.582465: val_loss -0.7475 +2024-11-22 21:02:27.582544: Pseudo dice [0.8656] +2024-11-22 21:02:27.582621: Epoch time: 18.31 s +2024-11-22 21:02:28.828463: +2024-11-22 21:02:28.828744: Epoch 6293 +2024-11-22 21:02:28.828862: Current learning rate: 0.00249 +2024-11-22 21:02:48.200193: train_loss -0.8091 +2024-11-22 21:02:48.200480: val_loss -0.7476 +2024-11-22 21:02:48.200619: Pseudo dice [0.8503] +2024-11-22 21:02:48.200709: Epoch time: 19.37 s +2024-11-22 21:02:49.114749: +2024-11-22 21:02:49.115006: Epoch 6294 +2024-11-22 21:02:49.115121: Current learning rate: 0.00249 +2024-11-22 21:03:08.109221: train_loss -0.8066 +2024-11-22 21:03:08.109445: val_loss -0.7636 +2024-11-22 21:03:08.109516: Pseudo dice [0.8355] +2024-11-22 21:03:08.109594: Epoch time: 19.0 s +2024-11-22 21:03:09.018361: +2024-11-22 21:03:09.018660: Epoch 6295 +2024-11-22 21:03:09.018773: Current learning rate: 0.00249 +2024-11-22 21:03:29.298333: train_loss -0.7975 +2024-11-22 21:03:29.298568: val_loss -0.7427 +2024-11-22 21:03:29.298643: Pseudo dice [0.8556] +2024-11-22 21:03:29.298743: Epoch time: 20.28 s +2024-11-22 21:03:30.211697: +2024-11-22 21:03:30.211896: Epoch 6296 +2024-11-22 21:03:30.212016: Current learning rate: 0.00249 +2024-11-22 21:03:49.375815: train_loss -0.802 +2024-11-22 21:03:49.376058: val_loss -0.7621 +2024-11-22 21:03:49.376133: Pseudo dice [0.8515] +2024-11-22 21:03:49.376213: Epoch time: 19.16 s +2024-11-22 21:03:50.287443: +2024-11-22 21:03:50.287806: Epoch 6297 +2024-11-22 21:03:50.287921: Current learning rate: 0.00248 +2024-11-22 21:04:08.627511: train_loss -0.8071 +2024-11-22 21:04:08.627759: val_loss -0.7861 +2024-11-22 21:04:08.627837: Pseudo dice [0.8698] +2024-11-22 21:04:08.627916: Epoch time: 18.34 s +2024-11-22 21:04:09.531358: +2024-11-22 21:04:09.531617: Epoch 6298 +2024-11-22 21:04:09.531736: Current learning rate: 0.00248 +2024-11-22 21:04:27.781398: train_loss -0.8067 +2024-11-22 21:04:27.781617: val_loss -0.7578 +2024-11-22 21:04:27.781708: Pseudo dice [0.8386] +2024-11-22 21:04:27.781783: Epoch time: 18.25 s +2024-11-22 21:04:28.697736: +2024-11-22 21:04:28.697936: Epoch 6299 +2024-11-22 21:04:28.698054: Current learning rate: 0.00248 +2024-11-22 21:04:48.137544: train_loss -0.8049 +2024-11-22 21:04:48.137764: val_loss -0.7645 +2024-11-22 21:04:48.137837: Pseudo dice [0.8505] +2024-11-22 21:04:48.137911: Epoch time: 19.44 s +2024-11-22 21:04:49.386395: +2024-11-22 21:04:49.386593: Epoch 6300 +2024-11-22 21:04:49.386699: Current learning rate: 0.00248 +2024-11-22 21:05:08.950964: train_loss -0.8033 +2024-11-22 21:05:08.951197: val_loss -0.7241 +2024-11-22 21:05:08.951272: Pseudo dice [0.8543] +2024-11-22 21:05:08.951352: Epoch time: 19.57 s +2024-11-22 21:05:09.884688: +2024-11-22 21:05:09.885162: Epoch 6301 +2024-11-22 21:05:09.885279: Current learning rate: 0.00248 +2024-11-22 21:05:28.564738: train_loss -0.8177 +2024-11-22 21:05:28.564985: val_loss -0.7671 +2024-11-22 21:05:28.570199: Pseudo dice [0.8663] +2024-11-22 21:05:28.570370: Epoch time: 18.68 s +2024-11-22 21:05:29.513313: +2024-11-22 21:05:29.513519: Epoch 6302 +2024-11-22 21:05:29.513631: Current learning rate: 0.00248 +2024-11-22 21:05:47.174148: train_loss -0.8113 +2024-11-22 21:05:47.174362: val_loss -0.7637 +2024-11-22 21:05:47.174438: Pseudo dice [0.8519] +2024-11-22 21:05:47.174515: Epoch time: 17.66 s +2024-11-22 21:05:48.079363: +2024-11-22 21:05:48.079563: Epoch 6303 +2024-11-22 21:05:48.079677: Current learning rate: 0.00248 +2024-11-22 21:06:06.562461: train_loss -0.8141 +2024-11-22 21:06:06.563264: val_loss -0.7476 +2024-11-22 21:06:06.563381: Pseudo dice [0.8678] +2024-11-22 21:06:06.563460: Epoch time: 18.48 s +2024-11-22 21:06:07.887859: +2024-11-22 21:06:07.888095: Epoch 6304 +2024-11-22 21:06:07.888219: Current learning rate: 0.00248 +2024-11-22 21:06:27.181507: train_loss -0.8151 +2024-11-22 21:06:27.181772: val_loss -0.7576 +2024-11-22 21:06:27.181848: Pseudo dice [0.8503] +2024-11-22 21:06:27.181928: Epoch time: 19.29 s +2024-11-22 21:06:28.092891: +2024-11-22 21:06:28.093102: Epoch 6305 +2024-11-22 21:06:28.093211: Current learning rate: 0.00247 +2024-11-22 21:06:46.133701: train_loss -0.8146 +2024-11-22 21:06:46.133943: val_loss -0.7361 +2024-11-22 21:06:46.134025: Pseudo dice [0.8563] +2024-11-22 21:06:46.134104: Epoch time: 18.04 s +2024-11-22 21:06:47.093937: +2024-11-22 21:06:47.094153: Epoch 6306 +2024-11-22 21:06:47.094268: Current learning rate: 0.00247 +2024-11-22 21:07:06.239918: train_loss -0.8112 +2024-11-22 21:07:06.240222: val_loss -0.7615 +2024-11-22 21:07:06.240308: Pseudo dice [0.8515] +2024-11-22 21:07:06.240401: Epoch time: 19.15 s +2024-11-22 21:07:07.150552: +2024-11-22 21:07:07.150839: Epoch 6307 +2024-11-22 21:07:07.150954: Current learning rate: 0.00247 +2024-11-22 21:07:24.635073: train_loss -0.8127 +2024-11-22 21:07:24.635311: val_loss -0.776 +2024-11-22 21:07:24.635388: Pseudo dice [0.8591] +2024-11-22 21:07:24.635472: Epoch time: 17.49 s +2024-11-22 21:07:25.544600: +2024-11-22 21:07:25.544837: Epoch 6308 +2024-11-22 21:07:25.544952: Current learning rate: 0.00247 +2024-11-22 21:07:44.252113: train_loss -0.8143 +2024-11-22 21:07:44.252359: val_loss -0.7693 +2024-11-22 21:07:44.252434: Pseudo dice [0.8621] +2024-11-22 21:07:44.252513: Epoch time: 18.71 s +2024-11-22 21:07:45.278676: +2024-11-22 21:07:45.278870: Epoch 6309 +2024-11-22 21:07:45.278982: Current learning rate: 0.00247 +2024-11-22 21:08:04.718181: train_loss -0.8132 +2024-11-22 21:08:04.718392: val_loss -0.7184 +2024-11-22 21:08:04.718467: Pseudo dice [0.8201] +2024-11-22 21:08:04.718547: Epoch time: 19.44 s +2024-11-22 21:08:05.635944: +2024-11-22 21:08:05.636160: Epoch 6310 +2024-11-22 21:08:05.636272: Current learning rate: 0.00247 +2024-11-22 21:08:25.538122: train_loss -0.7993 +2024-11-22 21:08:25.538345: val_loss -0.7489 +2024-11-22 21:08:25.538418: Pseudo dice [0.8778] +2024-11-22 21:08:25.538496: Epoch time: 19.9 s +2024-11-22 21:08:26.633899: +2024-11-22 21:08:26.634087: Epoch 6311 +2024-11-22 21:08:26.634195: Current learning rate: 0.00247 +2024-11-22 21:08:45.406470: train_loss -0.81 +2024-11-22 21:08:45.406727: val_loss -0.7537 +2024-11-22 21:08:45.406803: Pseudo dice [0.8362] +2024-11-22 21:08:45.406889: Epoch time: 18.77 s +2024-11-22 21:08:46.315973: +2024-11-22 21:08:46.316172: Epoch 6312 +2024-11-22 21:08:46.316288: Current learning rate: 0.00247 +2024-11-22 21:09:05.089058: train_loss -0.8099 +2024-11-22 21:09:05.089279: val_loss -0.742 +2024-11-22 21:09:05.089356: Pseudo dice [0.8442] +2024-11-22 21:09:05.089608: Epoch time: 18.77 s +2024-11-22 21:09:05.997202: +2024-11-22 21:09:05.997434: Epoch 6313 +2024-11-22 21:09:05.997545: Current learning rate: 0.00246 +2024-11-22 21:09:24.307533: train_loss -0.8071 +2024-11-22 21:09:24.307806: val_loss -0.7427 +2024-11-22 21:09:24.307925: Pseudo dice [0.8267] +2024-11-22 21:09:24.308012: Epoch time: 18.31 s +2024-11-22 21:09:25.218274: +2024-11-22 21:09:25.218470: Epoch 6314 +2024-11-22 21:09:25.218585: Current learning rate: 0.00246 +2024-11-22 21:09:43.360961: train_loss -0.8082 +2024-11-22 21:09:43.361202: val_loss -0.7617 +2024-11-22 21:09:43.361279: Pseudo dice [0.8626] +2024-11-22 21:09:43.361359: Epoch time: 18.14 s +2024-11-22 21:09:44.263429: +2024-11-22 21:09:44.263640: Epoch 6315 +2024-11-22 21:09:44.263753: Current learning rate: 0.00246 +2024-11-22 21:10:03.795887: train_loss -0.8041 +2024-11-22 21:10:03.796186: val_loss -0.7692 +2024-11-22 21:10:03.796266: Pseudo dice [0.8627] +2024-11-22 21:10:03.796347: Epoch time: 19.53 s +2024-11-22 21:10:05.119281: +2024-11-22 21:10:05.119493: Epoch 6316 +2024-11-22 21:10:05.119606: Current learning rate: 0.00246 +2024-11-22 21:10:23.898598: train_loss -0.8112 +2024-11-22 21:10:23.898824: val_loss -0.7589 +2024-11-22 21:10:23.898899: Pseudo dice [0.846] +2024-11-22 21:10:23.898974: Epoch time: 18.78 s +2024-11-22 21:10:24.814017: +2024-11-22 21:10:24.814239: Epoch 6317 +2024-11-22 21:10:24.814351: Current learning rate: 0.00246 +2024-11-22 21:10:43.321159: train_loss -0.808 +2024-11-22 21:10:43.321395: val_loss -0.7476 +2024-11-22 21:10:43.321473: Pseudo dice [0.8531] +2024-11-22 21:10:43.321552: Epoch time: 18.51 s +2024-11-22 21:10:44.236597: +2024-11-22 21:10:44.236816: Epoch 6318 +2024-11-22 21:10:44.236926: Current learning rate: 0.00246 +2024-11-22 21:11:02.641251: train_loss -0.8139 +2024-11-22 21:11:02.641506: val_loss -0.7415 +2024-11-22 21:11:02.641585: Pseudo dice [0.8431] +2024-11-22 21:11:02.641670: Epoch time: 18.41 s +2024-11-22 21:11:03.582132: +2024-11-22 21:11:03.582522: Epoch 6319 +2024-11-22 21:11:03.582637: Current learning rate: 0.00246 +2024-11-22 21:11:22.171167: train_loss -0.811 +2024-11-22 21:11:22.171471: val_loss -0.7699 +2024-11-22 21:11:22.171550: Pseudo dice [0.8587] +2024-11-22 21:11:22.171629: Epoch time: 18.59 s +2024-11-22 21:11:23.084666: +2024-11-22 21:11:23.084984: Epoch 6320 +2024-11-22 21:11:23.085111: Current learning rate: 0.00245 +2024-11-22 21:11:41.394593: train_loss -0.8127 +2024-11-22 21:11:41.394807: val_loss -0.7686 +2024-11-22 21:11:41.394885: Pseudo dice [0.8533] +2024-11-22 21:11:41.394959: Epoch time: 18.31 s +2024-11-22 21:11:42.318972: +2024-11-22 21:11:42.319176: Epoch 6321 +2024-11-22 21:11:42.319285: Current learning rate: 0.00245 +2024-11-22 21:12:01.515350: train_loss -0.8008 +2024-11-22 21:12:01.515564: val_loss -0.7586 +2024-11-22 21:12:01.515637: Pseudo dice [0.8591] +2024-11-22 21:12:01.515715: Epoch time: 19.2 s +2024-11-22 21:12:02.423538: +2024-11-22 21:12:02.423809: Epoch 6322 +2024-11-22 21:12:02.423923: Current learning rate: 0.00245 +2024-11-22 21:12:21.778496: train_loss -0.8215 +2024-11-22 21:12:21.778738: val_loss -0.7311 +2024-11-22 21:12:21.778811: Pseudo dice [0.8191] +2024-11-22 21:12:21.778891: Epoch time: 19.36 s +2024-11-22 21:12:22.686746: +2024-11-22 21:12:22.686981: Epoch 6323 +2024-11-22 21:12:22.687105: Current learning rate: 0.00245 +2024-11-22 21:12:40.596866: train_loss -0.8145 +2024-11-22 21:12:40.597080: val_loss -0.737 +2024-11-22 21:12:40.597155: Pseudo dice [0.8364] +2024-11-22 21:12:40.597235: Epoch time: 17.91 s +2024-11-22 21:12:41.541707: +2024-11-22 21:12:41.541916: Epoch 6324 +2024-11-22 21:12:41.542037: Current learning rate: 0.00245 +2024-11-22 21:13:00.903272: train_loss -0.8086 +2024-11-22 21:13:00.903495: val_loss -0.7635 +2024-11-22 21:13:00.903571: Pseudo dice [0.8674] +2024-11-22 21:13:00.903647: Epoch time: 19.36 s +2024-11-22 21:13:01.808932: +2024-11-22 21:13:01.809136: Epoch 6325 +2024-11-22 21:13:01.809249: Current learning rate: 0.00245 +2024-11-22 21:13:19.802770: train_loss -0.8209 +2024-11-22 21:13:19.802979: val_loss -0.7746 +2024-11-22 21:13:19.803066: Pseudo dice [0.8357] +2024-11-22 21:13:19.803144: Epoch time: 17.99 s +2024-11-22 21:13:20.714448: +2024-11-22 21:13:20.714669: Epoch 6326 +2024-11-22 21:13:20.714781: Current learning rate: 0.00245 +2024-11-22 21:13:39.403816: train_loss -0.8179 +2024-11-22 21:13:39.404089: val_loss -0.7489 +2024-11-22 21:13:39.404164: Pseudo dice [0.8301] +2024-11-22 21:13:39.404241: Epoch time: 18.69 s +2024-11-22 21:13:40.680736: +2024-11-22 21:13:40.680941: Epoch 6327 +2024-11-22 21:13:40.681062: Current learning rate: 0.00245 +2024-11-22 21:14:00.553609: train_loss -0.8078 +2024-11-22 21:14:00.565714: val_loss -0.7506 +2024-11-22 21:14:00.565809: Pseudo dice [0.8596] +2024-11-22 21:14:00.565890: Epoch time: 19.87 s +2024-11-22 21:14:01.554257: +2024-11-22 21:14:01.554502: Epoch 6328 +2024-11-22 21:14:01.554614: Current learning rate: 0.00244 +2024-11-22 21:14:19.482642: train_loss -0.8061 +2024-11-22 21:14:19.482860: val_loss -0.7601 +2024-11-22 21:14:19.482934: Pseudo dice [0.8368] +2024-11-22 21:14:19.483023: Epoch time: 17.93 s +2024-11-22 21:14:20.391549: +2024-11-22 21:14:20.391770: Epoch 6329 +2024-11-22 21:14:20.391881: Current learning rate: 0.00244 +2024-11-22 21:14:39.242909: train_loss -0.8136 +2024-11-22 21:14:39.243195: val_loss -0.7484 +2024-11-22 21:14:39.243270: Pseudo dice [0.8471] +2024-11-22 21:14:39.243351: Epoch time: 18.85 s +2024-11-22 21:14:40.159710: +2024-11-22 21:14:40.159929: Epoch 6330 +2024-11-22 21:14:40.160047: Current learning rate: 0.00244 +2024-11-22 21:14:59.745860: train_loss -0.8193 +2024-11-22 21:14:59.746146: val_loss -0.7587 +2024-11-22 21:14:59.746224: Pseudo dice [0.8554] +2024-11-22 21:14:59.746300: Epoch time: 19.59 s +2024-11-22 21:15:00.657200: +2024-11-22 21:15:00.657415: Epoch 6331 +2024-11-22 21:15:00.657534: Current learning rate: 0.00244 +2024-11-22 21:15:18.309140: train_loss -0.8188 +2024-11-22 21:15:18.311515: val_loss -0.7738 +2024-11-22 21:15:18.311600: Pseudo dice [0.8501] +2024-11-22 21:15:18.311678: Epoch time: 17.65 s +2024-11-22 21:15:19.348629: +2024-11-22 21:15:19.348928: Epoch 6332 +2024-11-22 21:15:19.349056: Current learning rate: 0.00244 +2024-11-22 21:15:38.703206: train_loss -0.814 +2024-11-22 21:15:38.703418: val_loss -0.7531 +2024-11-22 21:15:38.703497: Pseudo dice [0.8527] +2024-11-22 21:15:38.703571: Epoch time: 19.36 s +2024-11-22 21:15:39.621800: +2024-11-22 21:15:39.622009: Epoch 6333 +2024-11-22 21:15:39.622122: Current learning rate: 0.00244 +2024-11-22 21:15:59.096584: train_loss -0.8106 +2024-11-22 21:15:59.096857: val_loss -0.732 +2024-11-22 21:15:59.096932: Pseudo dice [0.8276] +2024-11-22 21:15:59.097030: Epoch time: 19.48 s +2024-11-22 21:16:00.017214: +2024-11-22 21:16:00.017444: Epoch 6334 +2024-11-22 21:16:00.017566: Current learning rate: 0.00244 +2024-11-22 21:16:16.994484: train_loss -0.8121 +2024-11-22 21:16:16.994703: val_loss -0.747 +2024-11-22 21:16:16.994778: Pseudo dice [0.8507] +2024-11-22 21:16:16.994851: Epoch time: 16.98 s +2024-11-22 21:16:17.935656: +2024-11-22 21:16:17.935855: Epoch 6335 +2024-11-22 21:16:17.935971: Current learning rate: 0.00243 +2024-11-22 21:16:36.490514: train_loss -0.8161 +2024-11-22 21:16:36.490727: val_loss -0.7486 +2024-11-22 21:16:36.490800: Pseudo dice [0.8613] +2024-11-22 21:16:36.490879: Epoch time: 18.56 s +2024-11-22 21:16:37.403476: +2024-11-22 21:16:37.403695: Epoch 6336 +2024-11-22 21:16:37.403809: Current learning rate: 0.00243 +2024-11-22 21:16:56.223379: train_loss -0.8141 +2024-11-22 21:16:56.223598: val_loss -0.712 +2024-11-22 21:16:56.223671: Pseudo dice [0.8538] +2024-11-22 21:16:56.223747: Epoch time: 18.82 s +2024-11-22 21:16:57.129580: +2024-11-22 21:16:57.129860: Epoch 6337 +2024-11-22 21:16:57.129975: Current learning rate: 0.00243 +2024-11-22 21:17:16.740278: train_loss -0.8125 +2024-11-22 21:17:16.740525: val_loss -0.7559 +2024-11-22 21:17:16.740601: Pseudo dice [0.8441] +2024-11-22 21:17:16.740685: Epoch time: 19.61 s +2024-11-22 21:17:17.653641: +2024-11-22 21:17:17.653879: Epoch 6338 +2024-11-22 21:17:17.653994: Current learning rate: 0.00243 +2024-11-22 21:17:36.637927: train_loss -0.8179 +2024-11-22 21:17:36.638132: val_loss -0.7416 +2024-11-22 21:17:36.638206: Pseudo dice [0.8502] +2024-11-22 21:17:36.638406: Epoch time: 18.99 s +2024-11-22 21:17:37.928446: +2024-11-22 21:17:37.928666: Epoch 6339 +2024-11-22 21:17:37.928776: Current learning rate: 0.00243 +2024-11-22 21:17:57.823310: train_loss -0.8164 +2024-11-22 21:17:57.823539: val_loss -0.7441 +2024-11-22 21:17:57.823613: Pseudo dice [0.8299] +2024-11-22 21:17:57.823687: Epoch time: 19.9 s +2024-11-22 21:17:58.736152: +2024-11-22 21:17:58.736356: Epoch 6340 +2024-11-22 21:17:58.736467: Current learning rate: 0.00243 +2024-11-22 21:18:17.232243: train_loss -0.8099 +2024-11-22 21:18:17.232468: val_loss -0.7553 +2024-11-22 21:18:17.232547: Pseudo dice [0.8636] +2024-11-22 21:18:17.232627: Epoch time: 18.5 s +2024-11-22 21:18:18.141346: +2024-11-22 21:18:18.141554: Epoch 6341 +2024-11-22 21:18:18.141671: Current learning rate: 0.00243 +2024-11-22 21:18:36.935358: train_loss -0.8111 +2024-11-22 21:18:36.935622: val_loss -0.7464 +2024-11-22 21:18:36.935702: Pseudo dice [0.8421] +2024-11-22 21:18:36.935788: Epoch time: 18.79 s +2024-11-22 21:18:37.859618: +2024-11-22 21:18:37.859843: Epoch 6342 +2024-11-22 21:18:37.859953: Current learning rate: 0.00243 +2024-11-22 21:18:56.553274: train_loss -0.8064 +2024-11-22 21:18:56.553492: val_loss -0.769 +2024-11-22 21:18:56.553563: Pseudo dice [0.8504] +2024-11-22 21:18:56.553639: Epoch time: 18.69 s +2024-11-22 21:18:57.510638: +2024-11-22 21:18:57.510859: Epoch 6343 +2024-11-22 21:18:57.510974: Current learning rate: 0.00242 +2024-11-22 21:19:15.403274: train_loss -0.8209 +2024-11-22 21:19:15.403504: val_loss -0.762 +2024-11-22 21:19:15.403581: Pseudo dice [0.8523] +2024-11-22 21:19:15.403663: Epoch time: 17.89 s +2024-11-22 21:19:16.322345: +2024-11-22 21:19:16.322815: Epoch 6344 +2024-11-22 21:19:16.322930: Current learning rate: 0.00242 +2024-11-22 21:19:35.065885: train_loss -0.8118 +2024-11-22 21:19:35.066159: val_loss -0.7611 +2024-11-22 21:19:35.066237: Pseudo dice [0.8496] +2024-11-22 21:19:35.066320: Epoch time: 18.74 s +2024-11-22 21:19:36.086473: +2024-11-22 21:19:36.086688: Epoch 6345 +2024-11-22 21:19:36.086797: Current learning rate: 0.00242 +2024-11-22 21:19:54.777607: train_loss -0.8181 +2024-11-22 21:19:54.777863: val_loss -0.7639 +2024-11-22 21:19:54.777939: Pseudo dice [0.865] +2024-11-22 21:19:54.778068: Epoch time: 18.69 s +2024-11-22 21:19:55.695425: +2024-11-22 21:19:55.695619: Epoch 6346 +2024-11-22 21:19:55.695729: Current learning rate: 0.00242 +2024-11-22 21:20:14.322789: train_loss -0.8113 +2024-11-22 21:20:14.323009: val_loss -0.7322 +2024-11-22 21:20:14.323085: Pseudo dice [0.842] +2024-11-22 21:20:14.323195: Epoch time: 18.63 s +2024-11-22 21:20:15.338476: +2024-11-22 21:20:15.338666: Epoch 6347 +2024-11-22 21:20:15.338792: Current learning rate: 0.00242 +2024-11-22 21:20:34.811400: train_loss -0.8149 +2024-11-22 21:20:34.811621: val_loss -0.7428 +2024-11-22 21:20:34.811693: Pseudo dice [0.8484] +2024-11-22 21:20:34.811769: Epoch time: 19.47 s +2024-11-22 21:20:35.727479: +2024-11-22 21:20:35.727685: Epoch 6348 +2024-11-22 21:20:35.727801: Current learning rate: 0.00242 +2024-11-22 21:20:54.141289: train_loss -0.8165 +2024-11-22 21:20:54.141515: val_loss -0.7406 +2024-11-22 21:20:54.141588: Pseudo dice [0.8264] +2024-11-22 21:20:54.141669: Epoch time: 18.41 s +2024-11-22 21:20:55.055450: +2024-11-22 21:20:55.055648: Epoch 6349 +2024-11-22 21:20:55.055761: Current learning rate: 0.00242 +2024-11-22 21:21:13.252721: train_loss -0.8106 +2024-11-22 21:21:13.252966: val_loss -0.7683 +2024-11-22 21:21:13.253049: Pseudo dice [0.8608] +2024-11-22 21:21:13.253130: Epoch time: 18.2 s +2024-11-22 21:21:14.859772: +2024-11-22 21:21:14.859984: Epoch 6350 +2024-11-22 21:21:14.860096: Current learning rate: 0.00242 +2024-11-22 21:21:34.099322: train_loss -0.8098 +2024-11-22 21:21:34.099562: val_loss -0.7696 +2024-11-22 21:21:34.099656: Pseudo dice [0.8577] +2024-11-22 21:21:34.099797: Epoch time: 19.24 s +2024-11-22 21:21:35.011405: +2024-11-22 21:21:35.011673: Epoch 6351 +2024-11-22 21:21:35.011785: Current learning rate: 0.00241 +2024-11-22 21:21:53.399314: train_loss -0.8061 +2024-11-22 21:21:53.399563: val_loss -0.7363 +2024-11-22 21:21:53.399638: Pseudo dice [0.8381] +2024-11-22 21:21:53.399712: Epoch time: 18.39 s +2024-11-22 21:21:54.305756: +2024-11-22 21:21:54.305966: Epoch 6352 +2024-11-22 21:21:54.306087: Current learning rate: 0.00241 +2024-11-22 21:22:13.475768: train_loss -0.8065 +2024-11-22 21:22:13.476009: val_loss -0.7287 +2024-11-22 21:22:13.476084: Pseudo dice [0.8527] +2024-11-22 21:22:13.476164: Epoch time: 19.17 s +2024-11-22 21:22:14.396473: +2024-11-22 21:22:14.396739: Epoch 6353 +2024-11-22 21:22:14.396853: Current learning rate: 0.00241 +2024-11-22 21:22:33.800009: train_loss -0.8168 +2024-11-22 21:22:33.800229: val_loss -0.7229 +2024-11-22 21:22:33.800304: Pseudo dice [0.8539] +2024-11-22 21:22:33.800380: Epoch time: 19.4 s +2024-11-22 21:22:34.717204: +2024-11-22 21:22:34.717418: Epoch 6354 +2024-11-22 21:22:34.717553: Current learning rate: 0.00241 +2024-11-22 21:22:53.526349: train_loss -0.8156 +2024-11-22 21:22:53.526572: val_loss -0.7476 +2024-11-22 21:22:53.526648: Pseudo dice [0.8311] +2024-11-22 21:22:53.526725: Epoch time: 18.81 s +2024-11-22 21:22:54.433197: +2024-11-22 21:22:54.433418: Epoch 6355 +2024-11-22 21:22:54.433527: Current learning rate: 0.00241 +2024-11-22 21:23:13.615257: train_loss -0.8073 +2024-11-22 21:23:13.615474: val_loss -0.7449 +2024-11-22 21:23:13.615551: Pseudo dice [0.8773] +2024-11-22 21:23:13.615632: Epoch time: 19.18 s +2024-11-22 21:23:14.548429: +2024-11-22 21:23:14.548773: Epoch 6356 +2024-11-22 21:23:14.548888: Current learning rate: 0.00241 +2024-11-22 21:23:33.128027: train_loss -0.8182 +2024-11-22 21:23:33.128313: val_loss -0.7467 +2024-11-22 21:23:33.128392: Pseudo dice [0.8409] +2024-11-22 21:23:33.128473: Epoch time: 18.58 s +2024-11-22 21:23:34.051756: +2024-11-22 21:23:34.051951: Epoch 6357 +2024-11-22 21:23:34.052066: Current learning rate: 0.00241 +2024-11-22 21:23:52.900151: train_loss -0.8221 +2024-11-22 21:23:52.900369: val_loss -0.754 +2024-11-22 21:23:52.900502: Pseudo dice [0.842] +2024-11-22 21:23:52.900583: Epoch time: 18.85 s +2024-11-22 21:23:53.812566: +2024-11-22 21:23:53.812773: Epoch 6358 +2024-11-22 21:23:53.812879: Current learning rate: 0.0024 +2024-11-22 21:24:12.217710: train_loss -0.8098 +2024-11-22 21:24:12.218247: val_loss -0.7357 +2024-11-22 21:24:12.218348: Pseudo dice [0.8351] +2024-11-22 21:24:12.218424: Epoch time: 18.41 s +2024-11-22 21:24:13.238607: +2024-11-22 21:24:13.238798: Epoch 6359 +2024-11-22 21:24:13.238910: Current learning rate: 0.0024 +2024-11-22 21:24:31.728419: train_loss -0.8105 +2024-11-22 21:24:31.728691: val_loss -0.7791 +2024-11-22 21:24:31.728767: Pseudo dice [0.8512] +2024-11-22 21:24:31.728847: Epoch time: 18.49 s +2024-11-22 21:24:32.679785: +2024-11-22 21:24:32.679979: Epoch 6360 +2024-11-22 21:24:32.680114: Current learning rate: 0.0024 +2024-11-22 21:24:51.400219: train_loss -0.8054 +2024-11-22 21:24:51.400470: val_loss -0.7401 +2024-11-22 21:24:51.400546: Pseudo dice [0.8536] +2024-11-22 21:24:51.400626: Epoch time: 18.72 s +2024-11-22 21:24:52.680626: +2024-11-22 21:24:52.680861: Epoch 6361 +2024-11-22 21:24:52.680975: Current learning rate: 0.0024 +2024-11-22 21:25:11.848823: train_loss -0.8075 +2024-11-22 21:25:11.849086: val_loss -0.7563 +2024-11-22 21:25:11.849223: Pseudo dice [0.8347] +2024-11-22 21:25:11.849302: Epoch time: 19.17 s +2024-11-22 21:25:12.756943: +2024-11-22 21:25:12.757159: Epoch 6362 +2024-11-22 21:25:12.757267: Current learning rate: 0.0024 +2024-11-22 21:25:30.279606: train_loss -0.8122 +2024-11-22 21:25:30.279825: val_loss -0.7234 +2024-11-22 21:25:30.279899: Pseudo dice [0.8326] +2024-11-22 21:25:30.279974: Epoch time: 17.52 s +2024-11-22 21:25:31.199326: +2024-11-22 21:25:31.199533: Epoch 6363 +2024-11-22 21:25:31.199644: Current learning rate: 0.0024 +2024-11-22 21:25:49.173277: train_loss -0.8161 +2024-11-22 21:25:49.178722: val_loss -0.7626 +2024-11-22 21:25:49.178805: Pseudo dice [0.8248] +2024-11-22 21:25:49.178896: Epoch time: 17.97 s +2024-11-22 21:25:50.124001: +2024-11-22 21:25:50.124207: Epoch 6364 +2024-11-22 21:25:50.124318: Current learning rate: 0.0024 +2024-11-22 21:26:09.824556: train_loss -0.8143 +2024-11-22 21:26:09.825162: val_loss -0.7412 +2024-11-22 21:26:09.825393: Pseudo dice [0.8368] +2024-11-22 21:26:09.825480: Epoch time: 19.7 s +2024-11-22 21:26:10.738930: +2024-11-22 21:26:10.739163: Epoch 6365 +2024-11-22 21:26:10.739275: Current learning rate: 0.0024 +2024-11-22 21:26:29.548842: train_loss -0.8128 +2024-11-22 21:26:29.549070: val_loss -0.7513 +2024-11-22 21:26:29.549147: Pseudo dice [0.8654] +2024-11-22 21:26:29.549226: Epoch time: 18.81 s +2024-11-22 21:26:30.459852: +2024-11-22 21:26:30.460074: Epoch 6366 +2024-11-22 21:26:30.460191: Current learning rate: 0.00239 +2024-11-22 21:26:48.147288: train_loss -0.8152 +2024-11-22 21:26:48.147517: val_loss -0.7854 +2024-11-22 21:26:48.147650: Pseudo dice [0.8724] +2024-11-22 21:26:48.147733: Epoch time: 17.69 s +2024-11-22 21:26:49.062248: +2024-11-22 21:26:49.062491: Epoch 6367 +2024-11-22 21:26:49.062602: Current learning rate: 0.00239 +2024-11-22 21:27:07.110677: train_loss -0.8138 +2024-11-22 21:27:07.110930: val_loss -0.7797 +2024-11-22 21:27:07.111013: Pseudo dice [0.8675] +2024-11-22 21:27:07.111097: Epoch time: 18.05 s +2024-11-22 21:27:08.025361: +2024-11-22 21:27:08.025566: Epoch 6368 +2024-11-22 21:27:08.025674: Current learning rate: 0.00239 +2024-11-22 21:27:27.708720: train_loss -0.8186 +2024-11-22 21:27:27.708935: val_loss -0.7665 +2024-11-22 21:27:27.709066: Pseudo dice [0.8614] +2024-11-22 21:27:27.709143: Epoch time: 19.68 s +2024-11-22 21:27:28.726475: +2024-11-22 21:27:28.726671: Epoch 6369 +2024-11-22 21:27:28.726780: Current learning rate: 0.00239 +2024-11-22 21:27:47.852022: train_loss -0.803 +2024-11-22 21:27:47.852329: val_loss -0.7674 +2024-11-22 21:27:47.852407: Pseudo dice [0.838] +2024-11-22 21:27:47.852489: Epoch time: 19.13 s +2024-11-22 21:27:48.766644: +2024-11-22 21:27:48.766883: Epoch 6370 +2024-11-22 21:27:48.767003: Current learning rate: 0.00239 +2024-11-22 21:28:07.958154: train_loss -0.8171 +2024-11-22 21:28:07.958372: val_loss -0.7637 +2024-11-22 21:28:07.958447: Pseudo dice [0.843] +2024-11-22 21:28:07.958521: Epoch time: 19.19 s +2024-11-22 21:28:08.873097: +2024-11-22 21:28:08.873338: Epoch 6371 +2024-11-22 21:28:08.873457: Current learning rate: 0.00239 +2024-11-22 21:28:27.547109: train_loss -0.8076 +2024-11-22 21:28:27.547398: val_loss -0.7549 +2024-11-22 21:28:27.547534: Pseudo dice [0.8559] +2024-11-22 21:28:27.547620: Epoch time: 18.67 s +2024-11-22 21:28:28.461015: +2024-11-22 21:28:28.461222: Epoch 6372 +2024-11-22 21:28:28.461341: Current learning rate: 0.00239 +2024-11-22 21:28:47.275208: train_loss -0.8165 +2024-11-22 21:28:47.275417: val_loss -0.7486 +2024-11-22 21:28:47.275522: Pseudo dice [0.86] +2024-11-22 21:28:47.275626: Epoch time: 18.81 s +2024-11-22 21:28:48.584360: +2024-11-22 21:28:48.584592: Epoch 6373 +2024-11-22 21:28:48.584708: Current learning rate: 0.00238 +2024-11-22 21:29:07.229872: train_loss -0.8184 +2024-11-22 21:29:07.230139: val_loss -0.7557 +2024-11-22 21:29:07.230216: Pseudo dice [0.8649] +2024-11-22 21:29:07.230293: Epoch time: 18.65 s +2024-11-22 21:29:08.141568: +2024-11-22 21:29:08.141810: Epoch 6374 +2024-11-22 21:29:08.141927: Current learning rate: 0.00238 +2024-11-22 21:29:26.116927: train_loss -0.8157 +2024-11-22 21:29:26.117173: val_loss -0.7684 +2024-11-22 21:29:26.117246: Pseudo dice [0.8469] +2024-11-22 21:29:26.117327: Epoch time: 17.98 s +2024-11-22 21:29:27.064430: +2024-11-22 21:29:27.064696: Epoch 6375 +2024-11-22 21:29:27.064811: Current learning rate: 0.00238 +2024-11-22 21:29:46.457549: train_loss -0.8171 +2024-11-22 21:29:46.457776: val_loss -0.7566 +2024-11-22 21:29:46.457852: Pseudo dice [0.8538] +2024-11-22 21:29:46.457946: Epoch time: 19.39 s +2024-11-22 21:29:47.476892: +2024-11-22 21:29:47.477112: Epoch 6376 +2024-11-22 21:29:47.477222: Current learning rate: 0.00238 +2024-11-22 21:30:07.252620: train_loss -0.8111 +2024-11-22 21:30:07.258020: val_loss -0.7621 +2024-11-22 21:30:07.258142: Pseudo dice [0.8714] +2024-11-22 21:30:07.258223: Epoch time: 19.78 s +2024-11-22 21:30:08.341126: +2024-11-22 21:30:08.341335: Epoch 6377 +2024-11-22 21:30:08.341451: Current learning rate: 0.00238 +2024-11-22 21:30:25.856436: train_loss -0.8223 +2024-11-22 21:30:25.861161: val_loss -0.754 +2024-11-22 21:30:25.861301: Pseudo dice [0.8444] +2024-11-22 21:30:25.861382: Epoch time: 17.52 s +2024-11-22 21:30:26.949448: +2024-11-22 21:30:26.949682: Epoch 6378 +2024-11-22 21:30:26.949795: Current learning rate: 0.00238 +2024-11-22 21:30:45.069745: train_loss -0.814 +2024-11-22 21:30:45.070053: val_loss -0.7508 +2024-11-22 21:30:45.070137: Pseudo dice [0.8584] +2024-11-22 21:30:45.070217: Epoch time: 18.12 s +2024-11-22 21:30:45.985478: +2024-11-22 21:30:45.985687: Epoch 6379 +2024-11-22 21:30:45.985800: Current learning rate: 0.00238 +2024-11-22 21:31:04.200304: train_loss -0.8198 +2024-11-22 21:31:04.204811: val_loss -0.738 +2024-11-22 21:31:04.210063: Pseudo dice [0.8548] +2024-11-22 21:31:04.210212: Epoch time: 18.22 s +2024-11-22 21:31:05.159569: +2024-11-22 21:31:05.159777: Epoch 6380 +2024-11-22 21:31:05.159888: Current learning rate: 0.00238 +2024-11-22 21:31:24.316600: train_loss -0.8104 +2024-11-22 21:31:24.316934: val_loss -0.7648 +2024-11-22 21:31:24.317025: Pseudo dice [0.8564] +2024-11-22 21:31:24.317107: Epoch time: 19.15 s +2024-11-22 21:31:25.330334: +2024-11-22 21:31:25.330552: Epoch 6381 +2024-11-22 21:31:25.330667: Current learning rate: 0.00237 +2024-11-22 21:31:43.742114: train_loss -0.8214 +2024-11-22 21:31:43.742337: val_loss -0.7461 +2024-11-22 21:31:43.742417: Pseudo dice [0.8527] +2024-11-22 21:31:43.742499: Epoch time: 18.41 s +2024-11-22 21:31:44.657137: +2024-11-22 21:31:44.657333: Epoch 6382 +2024-11-22 21:31:44.657445: Current learning rate: 0.00237 +2024-11-22 21:32:02.558666: train_loss -0.8219 +2024-11-22 21:32:02.558884: val_loss -0.7747 +2024-11-22 21:32:02.558956: Pseudo dice [0.8634] +2024-11-22 21:32:02.561302: Epoch time: 17.9 s +2024-11-22 21:32:03.595809: +2024-11-22 21:32:03.596008: Epoch 6383 +2024-11-22 21:32:03.596117: Current learning rate: 0.00237 +2024-11-22 21:32:22.813908: train_loss -0.8125 +2024-11-22 21:32:22.814149: val_loss -0.7575 +2024-11-22 21:32:22.814226: Pseudo dice [0.861] +2024-11-22 21:32:22.814304: Epoch time: 19.22 s +2024-11-22 21:32:24.307313: +2024-11-22 21:32:24.307527: Epoch 6384 +2024-11-22 21:32:24.307643: Current learning rate: 0.00237 +2024-11-22 21:32:43.067430: train_loss -0.8017 +2024-11-22 21:32:43.067669: val_loss -0.7682 +2024-11-22 21:32:43.067758: Pseudo dice [0.8552] +2024-11-22 21:32:43.067833: Epoch time: 18.76 s +2024-11-22 21:32:43.975338: +2024-11-22 21:32:43.975563: Epoch 6385 +2024-11-22 21:32:43.975678: Current learning rate: 0.00237 +2024-11-22 21:33:02.416673: train_loss -0.8157 +2024-11-22 21:33:02.416915: val_loss -0.7477 +2024-11-22 21:33:02.417005: Pseudo dice [0.8285] +2024-11-22 21:33:02.417089: Epoch time: 18.44 s +2024-11-22 21:33:03.325973: +2024-11-22 21:33:03.326276: Epoch 6386 +2024-11-22 21:33:03.326391: Current learning rate: 0.00237 +2024-11-22 21:33:22.635663: train_loss -0.8116 +2024-11-22 21:33:22.635917: val_loss -0.7521 +2024-11-22 21:33:22.636004: Pseudo dice [0.8413] +2024-11-22 21:33:22.636089: Epoch time: 19.31 s +2024-11-22 21:33:23.585041: +2024-11-22 21:33:23.585259: Epoch 6387 +2024-11-22 21:33:23.585379: Current learning rate: 0.00237 +2024-11-22 21:33:42.152478: train_loss -0.8175 +2024-11-22 21:33:42.152701: val_loss -0.7561 +2024-11-22 21:33:42.152775: Pseudo dice [0.8363] +2024-11-22 21:33:42.152855: Epoch time: 18.57 s +2024-11-22 21:33:43.068862: +2024-11-22 21:33:43.069071: Epoch 6388 +2024-11-22 21:33:43.069183: Current learning rate: 0.00237 +2024-11-22 21:34:02.297882: train_loss -0.8113 +2024-11-22 21:34:02.298180: val_loss -0.7596 +2024-11-22 21:34:02.298253: Pseudo dice [0.861] +2024-11-22 21:34:02.298335: Epoch time: 19.23 s +2024-11-22 21:34:03.376963: +2024-11-22 21:34:03.377178: Epoch 6389 +2024-11-22 21:34:03.377290: Current learning rate: 0.00236 +2024-11-22 21:34:23.296803: train_loss -0.8147 +2024-11-22 21:34:23.297023: val_loss -0.7452 +2024-11-22 21:34:23.297094: Pseudo dice [0.8273] +2024-11-22 21:34:23.297168: Epoch time: 19.92 s +2024-11-22 21:34:24.242442: +2024-11-22 21:34:24.242688: Epoch 6390 +2024-11-22 21:34:24.242803: Current learning rate: 0.00236 +2024-11-22 21:34:43.746958: train_loss -0.8186 +2024-11-22 21:34:43.747220: val_loss -0.7368 +2024-11-22 21:34:43.747459: Pseudo dice [0.8671] +2024-11-22 21:34:43.747552: Epoch time: 19.51 s +2024-11-22 21:34:44.668799: +2024-11-22 21:34:44.669069: Epoch 6391 +2024-11-22 21:34:44.669185: Current learning rate: 0.00236 +2024-11-22 21:35:04.793393: train_loss -0.8175 +2024-11-22 21:35:04.793608: val_loss -0.7711 +2024-11-22 21:35:04.793688: Pseudo dice [0.8669] +2024-11-22 21:35:04.793765: Epoch time: 20.13 s +2024-11-22 21:35:05.709383: +2024-11-22 21:35:05.709588: Epoch 6392 +2024-11-22 21:35:05.709699: Current learning rate: 0.00236 +2024-11-22 21:35:25.377997: train_loss -0.8151 +2024-11-22 21:35:25.378224: val_loss -0.7211 +2024-11-22 21:35:25.378301: Pseudo dice [0.8573] +2024-11-22 21:35:25.378379: Epoch time: 19.67 s +2024-11-22 21:35:26.306389: +2024-11-22 21:35:26.306609: Epoch 6393 +2024-11-22 21:35:26.306737: Current learning rate: 0.00236 +2024-11-22 21:35:46.535625: train_loss -0.8228 +2024-11-22 21:35:46.535857: val_loss -0.7596 +2024-11-22 21:35:46.535930: Pseudo dice [0.8352] +2024-11-22 21:35:46.536013: Epoch time: 20.23 s +2024-11-22 21:35:47.460136: +2024-11-22 21:35:47.460330: Epoch 6394 +2024-11-22 21:35:47.460439: Current learning rate: 0.00236 +2024-11-22 21:36:05.752059: train_loss -0.8103 +2024-11-22 21:36:05.752301: val_loss -0.7683 +2024-11-22 21:36:05.752373: Pseudo dice [0.8503] +2024-11-22 21:36:05.752457: Epoch time: 18.29 s +2024-11-22 21:36:06.670975: +2024-11-22 21:36:06.671180: Epoch 6395 +2024-11-22 21:36:06.671293: Current learning rate: 0.00236 +2024-11-22 21:36:26.113343: train_loss -0.8131 +2024-11-22 21:36:26.113568: val_loss -0.7625 +2024-11-22 21:36:26.113651: Pseudo dice [0.8562] +2024-11-22 21:36:26.113728: Epoch time: 19.44 s +2024-11-22 21:36:27.419786: +2024-11-22 21:36:27.419980: Epoch 6396 +2024-11-22 21:36:27.420094: Current learning rate: 0.00235 +2024-11-22 21:36:45.372245: train_loss -0.8172 +2024-11-22 21:36:45.372468: val_loss -0.744 +2024-11-22 21:36:45.372548: Pseudo dice [0.8262] +2024-11-22 21:36:45.372624: Epoch time: 17.95 s +2024-11-22 21:36:46.291261: +2024-11-22 21:36:46.291544: Epoch 6397 +2024-11-22 21:36:46.291653: Current learning rate: 0.00235 +2024-11-22 21:37:05.118670: train_loss -0.8124 +2024-11-22 21:37:05.118890: val_loss -0.7466 +2024-11-22 21:37:05.119035: Pseudo dice [0.8517] +2024-11-22 21:37:05.119118: Epoch time: 18.83 s +2024-11-22 21:37:06.104179: +2024-11-22 21:37:06.104396: Epoch 6398 +2024-11-22 21:37:06.104506: Current learning rate: 0.00235 +2024-11-22 21:37:24.800416: train_loss -0.8108 +2024-11-22 21:37:24.800677: val_loss -0.7677 +2024-11-22 21:37:24.800752: Pseudo dice [0.8542] +2024-11-22 21:37:24.800833: Epoch time: 18.7 s +2024-11-22 21:37:25.835409: +2024-11-22 21:37:25.835641: Epoch 6399 +2024-11-22 21:37:25.835769: Current learning rate: 0.00235 +2024-11-22 21:37:44.827432: train_loss -0.8114 +2024-11-22 21:37:44.827652: val_loss -0.7444 +2024-11-22 21:37:44.827824: Pseudo dice [0.8526] +2024-11-22 21:37:44.827905: Epoch time: 18.99 s +2024-11-22 21:37:46.052227: +2024-11-22 21:37:46.052432: Epoch 6400 +2024-11-22 21:37:46.052546: Current learning rate: 0.00235 +2024-11-22 21:38:05.965912: train_loss -0.8136 +2024-11-22 21:38:05.967136: val_loss -0.7444 +2024-11-22 21:38:05.967235: Pseudo dice [0.8228] +2024-11-22 21:38:05.967313: Epoch time: 19.91 s +2024-11-22 21:38:06.893504: +2024-11-22 21:38:06.893760: Epoch 6401 +2024-11-22 21:38:06.893871: Current learning rate: 0.00235 +2024-11-22 21:38:25.436026: train_loss -0.8108 +2024-11-22 21:38:25.436247: val_loss -0.7376 +2024-11-22 21:38:25.436321: Pseudo dice [0.8596] +2024-11-22 21:38:25.436398: Epoch time: 18.54 s +2024-11-22 21:38:26.349303: +2024-11-22 21:38:26.349500: Epoch 6402 +2024-11-22 21:38:26.349612: Current learning rate: 0.00235 +2024-11-22 21:38:45.590205: train_loss -0.8168 +2024-11-22 21:38:45.590456: val_loss -0.789 +2024-11-22 21:38:45.590531: Pseudo dice [0.8703] +2024-11-22 21:38:45.590612: Epoch time: 19.24 s +2024-11-22 21:38:46.588832: +2024-11-22 21:38:46.589040: Epoch 6403 +2024-11-22 21:38:46.589159: Current learning rate: 0.00235 +2024-11-22 21:39:04.744182: train_loss -0.817 +2024-11-22 21:39:04.744402: val_loss -0.7642 +2024-11-22 21:39:04.744481: Pseudo dice [0.843] +2024-11-22 21:39:04.744559: Epoch time: 18.16 s +2024-11-22 21:39:05.656703: +2024-11-22 21:39:05.656979: Epoch 6404 +2024-11-22 21:39:05.657093: Current learning rate: 0.00234 +2024-11-22 21:39:24.743261: train_loss -0.8166 +2024-11-22 21:39:24.743484: val_loss -0.7623 +2024-11-22 21:39:24.743556: Pseudo dice [0.8606] +2024-11-22 21:39:24.743631: Epoch time: 19.09 s +2024-11-22 21:39:25.656827: +2024-11-22 21:39:25.657033: Epoch 6405 +2024-11-22 21:39:25.657147: Current learning rate: 0.00234 +2024-11-22 21:39:44.565019: train_loss -0.8043 +2024-11-22 21:39:44.565250: val_loss -0.7813 +2024-11-22 21:39:44.565326: Pseudo dice [0.8546] +2024-11-22 21:39:44.565410: Epoch time: 18.91 s +2024-11-22 21:39:45.490704: +2024-11-22 21:39:45.490923: Epoch 6406 +2024-11-22 21:39:45.491038: Current learning rate: 0.00234 +2024-11-22 21:40:03.999443: train_loss -0.8188 +2024-11-22 21:40:04.001878: val_loss -0.7256 +2024-11-22 21:40:04.002005: Pseudo dice [0.8466] +2024-11-22 21:40:04.002091: Epoch time: 18.51 s +2024-11-22 21:40:05.586088: +2024-11-22 21:40:05.586277: Epoch 6407 +2024-11-22 21:40:05.586383: Current learning rate: 0.00234 +2024-11-22 21:40:23.688829: train_loss -0.8071 +2024-11-22 21:40:23.689055: val_loss -0.7433 +2024-11-22 21:40:23.689128: Pseudo dice [0.8211] +2024-11-22 21:40:23.689208: Epoch time: 18.1 s +2024-11-22 21:40:24.611626: +2024-11-22 21:40:24.611856: Epoch 6408 +2024-11-22 21:40:24.611962: Current learning rate: 0.00234 +2024-11-22 21:40:44.064074: train_loss -0.811 +2024-11-22 21:40:44.064293: val_loss -0.7645 +2024-11-22 21:40:44.064368: Pseudo dice [0.8501] +2024-11-22 21:40:44.064447: Epoch time: 19.45 s +2024-11-22 21:40:44.979110: +2024-11-22 21:40:44.979326: Epoch 6409 +2024-11-22 21:40:44.979436: Current learning rate: 0.00234 +2024-11-22 21:41:04.872425: train_loss -0.8107 +2024-11-22 21:41:04.872669: val_loss -0.7159 +2024-11-22 21:41:04.872743: Pseudo dice [0.8455] +2024-11-22 21:41:04.872820: Epoch time: 19.89 s +2024-11-22 21:41:05.777369: +2024-11-22 21:41:05.777570: Epoch 6410 +2024-11-22 21:41:05.777680: Current learning rate: 0.00234 +2024-11-22 21:41:24.438062: train_loss -0.8103 +2024-11-22 21:41:24.438269: val_loss -0.7439 +2024-11-22 21:41:24.438341: Pseudo dice [0.857] +2024-11-22 21:41:24.438413: Epoch time: 18.66 s +2024-11-22 21:41:25.329683: +2024-11-22 21:41:25.329885: Epoch 6411 +2024-11-22 21:41:25.330003: Current learning rate: 0.00233 +2024-11-22 21:41:43.861813: train_loss -0.8143 +2024-11-22 21:41:43.862039: val_loss -0.7409 +2024-11-22 21:41:43.862114: Pseudo dice [0.8551] +2024-11-22 21:41:43.862190: Epoch time: 18.53 s +2024-11-22 21:41:44.820746: +2024-11-22 21:41:44.820950: Epoch 6412 +2024-11-22 21:41:44.821069: Current learning rate: 0.00233 +2024-11-22 21:42:05.359947: train_loss -0.8091 +2024-11-22 21:42:05.360164: val_loss -0.7294 +2024-11-22 21:42:05.360239: Pseudo dice [0.8424] +2024-11-22 21:42:05.360315: Epoch time: 20.54 s +2024-11-22 21:42:06.341947: +2024-11-22 21:42:06.342175: Epoch 6413 +2024-11-22 21:42:06.342297: Current learning rate: 0.00233 +2024-11-22 21:42:24.745825: train_loss -0.8132 +2024-11-22 21:42:24.746080: val_loss -0.7554 +2024-11-22 21:42:24.746155: Pseudo dice [0.8477] +2024-11-22 21:42:24.746236: Epoch time: 18.4 s +2024-11-22 21:42:25.657072: +2024-11-22 21:42:25.657395: Epoch 6414 +2024-11-22 21:42:25.657511: Current learning rate: 0.00233 +2024-11-22 21:42:44.578351: train_loss -0.8105 +2024-11-22 21:42:44.578632: val_loss -0.7475 +2024-11-22 21:42:44.578709: Pseudo dice [0.8658] +2024-11-22 21:42:44.578784: Epoch time: 18.92 s +2024-11-22 21:42:45.510524: +2024-11-22 21:42:45.510731: Epoch 6415 +2024-11-22 21:42:45.510841: Current learning rate: 0.00233 +2024-11-22 21:43:04.505494: train_loss -0.8114 +2024-11-22 21:43:04.505715: val_loss -0.745 +2024-11-22 21:43:04.505790: Pseudo dice [0.8518] +2024-11-22 21:43:04.505871: Epoch time: 19.0 s +2024-11-22 21:43:05.559982: +2024-11-22 21:43:05.560265: Epoch 6416 +2024-11-22 21:43:05.560373: Current learning rate: 0.00233 +2024-11-22 21:43:24.182880: train_loss -0.8174 +2024-11-22 21:43:24.183234: val_loss -0.7729 +2024-11-22 21:43:24.183321: Pseudo dice [0.8581] +2024-11-22 21:43:24.183401: Epoch time: 18.62 s +2024-11-22 21:43:25.096036: +2024-11-22 21:43:25.096339: Epoch 6417 +2024-11-22 21:43:25.096461: Current learning rate: 0.00233 +2024-11-22 21:43:43.656947: train_loss -0.8094 +2024-11-22 21:43:43.657192: val_loss -0.7643 +2024-11-22 21:43:43.657269: Pseudo dice [0.8579] +2024-11-22 21:43:43.657348: Epoch time: 18.56 s +2024-11-22 21:43:44.954866: +2024-11-22 21:43:44.955101: Epoch 6418 +2024-11-22 21:43:44.955218: Current learning rate: 0.00233 +2024-11-22 21:44:03.642528: train_loss -0.7961 +2024-11-22 21:44:03.642768: val_loss -0.7376 +2024-11-22 21:44:03.642846: Pseudo dice [0.8505] +2024-11-22 21:44:03.642925: Epoch time: 18.69 s +2024-11-22 21:44:04.552209: +2024-11-22 21:44:04.552433: Epoch 6419 +2024-11-22 21:44:04.552547: Current learning rate: 0.00232 +2024-11-22 21:44:23.332985: train_loss -0.8007 +2024-11-22 21:44:23.333292: val_loss -0.7529 +2024-11-22 21:44:23.333374: Pseudo dice [0.831] +2024-11-22 21:44:23.333451: Epoch time: 18.78 s +2024-11-22 21:44:24.243666: +2024-11-22 21:44:24.243864: Epoch 6420 +2024-11-22 21:44:24.243977: Current learning rate: 0.00232 +2024-11-22 21:44:43.629610: train_loss -0.8185 +2024-11-22 21:44:43.629867: val_loss -0.7312 +2024-11-22 21:44:43.629941: Pseudo dice [0.8168] +2024-11-22 21:44:43.630067: Epoch time: 19.39 s +2024-11-22 21:44:44.544155: +2024-11-22 21:44:44.544356: Epoch 6421 +2024-11-22 21:44:44.544464: Current learning rate: 0.00232 +2024-11-22 21:45:02.776437: train_loss -0.8087 +2024-11-22 21:45:02.776645: val_loss -0.7556 +2024-11-22 21:45:02.776718: Pseudo dice [0.8406] +2024-11-22 21:45:02.778970: Epoch time: 18.23 s +2024-11-22 21:45:03.778808: +2024-11-22 21:45:03.779026: Epoch 6422 +2024-11-22 21:45:03.779139: Current learning rate: 0.00232 +2024-11-22 21:45:22.996740: train_loss -0.8178 +2024-11-22 21:45:22.996955: val_loss -0.7611 +2024-11-22 21:45:22.997036: Pseudo dice [0.8569] +2024-11-22 21:45:22.997110: Epoch time: 19.22 s +2024-11-22 21:45:23.913789: +2024-11-22 21:45:23.914081: Epoch 6423 +2024-11-22 21:45:23.914193: Current learning rate: 0.00232 +2024-11-22 21:45:43.849619: train_loss -0.8053 +2024-11-22 21:45:43.849836: val_loss -0.7514 +2024-11-22 21:45:43.849911: Pseudo dice [0.8452] +2024-11-22 21:45:43.850052: Epoch time: 19.94 s +2024-11-22 21:45:44.767942: +2024-11-22 21:45:44.768145: Epoch 6424 +2024-11-22 21:45:44.768259: Current learning rate: 0.00232 +2024-11-22 21:46:03.092105: train_loss -0.8091 +2024-11-22 21:46:03.092356: val_loss -0.7631 +2024-11-22 21:46:03.092430: Pseudo dice [0.8541] +2024-11-22 21:46:03.092510: Epoch time: 18.32 s +2024-11-22 21:46:04.008539: +2024-11-22 21:46:04.008753: Epoch 6425 +2024-11-22 21:46:04.008866: Current learning rate: 0.00232 +2024-11-22 21:46:22.191399: train_loss -0.8182 +2024-11-22 21:46:22.191624: val_loss -0.7494 +2024-11-22 21:46:22.191700: Pseudo dice [0.8432] +2024-11-22 21:46:22.191774: Epoch time: 18.18 s +2024-11-22 21:46:23.107394: +2024-11-22 21:46:23.107599: Epoch 6426 +2024-11-22 21:46:23.107710: Current learning rate: 0.00231 +2024-11-22 21:46:41.458522: train_loss -0.8054 +2024-11-22 21:46:41.458743: val_loss -0.7695 +2024-11-22 21:46:41.460133: Pseudo dice [0.8466] +2024-11-22 21:46:41.460243: Epoch time: 18.35 s +2024-11-22 21:46:42.396130: +2024-11-22 21:46:42.396326: Epoch 6427 +2024-11-22 21:46:42.396440: Current learning rate: 0.00231 +2024-11-22 21:47:01.897465: train_loss -0.8168 +2024-11-22 21:47:01.897682: val_loss -0.7613 +2024-11-22 21:47:01.897765: Pseudo dice [0.8586] +2024-11-22 21:47:01.897841: Epoch time: 19.5 s +2024-11-22 21:47:02.815447: +2024-11-22 21:47:02.815674: Epoch 6428 +2024-11-22 21:47:02.815805: Current learning rate: 0.00231 +2024-11-22 21:47:21.496989: train_loss -0.8081 +2024-11-22 21:47:21.497248: val_loss -0.751 +2024-11-22 21:47:21.497325: Pseudo dice [0.8537] +2024-11-22 21:47:21.497408: Epoch time: 18.68 s +2024-11-22 21:47:22.413691: +2024-11-22 21:47:22.413888: Epoch 6429 +2024-11-22 21:47:22.414009: Current learning rate: 0.00231 +2024-11-22 21:47:40.546129: train_loss -0.8119 +2024-11-22 21:47:40.546339: val_loss -0.7576 +2024-11-22 21:47:40.546415: Pseudo dice [0.8605] +2024-11-22 21:47:40.546491: Epoch time: 18.13 s +2024-11-22 21:47:41.833824: +2024-11-22 21:47:41.834063: Epoch 6430 +2024-11-22 21:47:41.834173: Current learning rate: 0.00231 +2024-11-22 21:47:59.186125: train_loss -0.8104 +2024-11-22 21:47:59.186345: val_loss -0.7366 +2024-11-22 21:47:59.186418: Pseudo dice [0.8386] +2024-11-22 21:47:59.186492: Epoch time: 17.35 s +2024-11-22 21:48:00.088249: +2024-11-22 21:48:00.088439: Epoch 6431 +2024-11-22 21:48:00.088534: Current learning rate: 0.00231 +2024-11-22 21:48:19.293211: train_loss -0.7948 +2024-11-22 21:48:19.293465: val_loss -0.7757 +2024-11-22 21:48:19.293538: Pseudo dice [0.8548] +2024-11-22 21:48:19.293622: Epoch time: 19.21 s +2024-11-22 21:48:20.203563: +2024-11-22 21:48:20.203776: Epoch 6432 +2024-11-22 21:48:20.203885: Current learning rate: 0.00231 +2024-11-22 21:48:38.495749: train_loss -0.7957 +2024-11-22 21:48:38.496009: val_loss -0.7207 +2024-11-22 21:48:38.496088: Pseudo dice [0.845] +2024-11-22 21:48:38.496166: Epoch time: 18.29 s +2024-11-22 21:48:39.390735: +2024-11-22 21:48:39.391020: Epoch 6433 +2024-11-22 21:48:39.391139: Current learning rate: 0.00231 +2024-11-22 21:48:57.854772: train_loss -0.8056 +2024-11-22 21:48:57.854979: val_loss -0.7354 +2024-11-22 21:48:57.855059: Pseudo dice [0.8535] +2024-11-22 21:48:57.855138: Epoch time: 18.46 s +2024-11-22 21:48:58.757167: +2024-11-22 21:48:58.757364: Epoch 6434 +2024-11-22 21:48:58.757464: Current learning rate: 0.0023 +2024-11-22 21:49:16.488080: train_loss -0.8059 +2024-11-22 21:49:16.488313: val_loss -0.7475 +2024-11-22 21:49:16.488388: Pseudo dice [0.8546] +2024-11-22 21:49:16.488465: Epoch time: 17.73 s +2024-11-22 21:49:17.401393: +2024-11-22 21:49:17.401644: Epoch 6435 +2024-11-22 21:49:17.401759: Current learning rate: 0.0023 +2024-11-22 21:49:37.471644: train_loss -0.8066 +2024-11-22 21:49:37.471866: val_loss -0.7385 +2024-11-22 21:49:37.471962: Pseudo dice [0.8361] +2024-11-22 21:49:37.472052: Epoch time: 20.07 s +2024-11-22 21:49:38.391744: +2024-11-22 21:49:38.392008: Epoch 6436 +2024-11-22 21:49:38.392124: Current learning rate: 0.0023 +2024-11-22 21:49:57.082500: train_loss -0.8143 +2024-11-22 21:49:57.082721: val_loss -0.7735 +2024-11-22 21:49:57.082799: Pseudo dice [0.8628] +2024-11-22 21:49:57.082881: Epoch time: 18.69 s +2024-11-22 21:49:58.011269: +2024-11-22 21:49:58.011462: Epoch 6437 +2024-11-22 21:49:58.011573: Current learning rate: 0.0023 +2024-11-22 21:50:17.071824: train_loss -0.8085 +2024-11-22 21:50:17.072043: val_loss -0.7573 +2024-11-22 21:50:17.072122: Pseudo dice [0.8522] +2024-11-22 21:50:17.072202: Epoch time: 19.06 s +2024-11-22 21:50:18.012036: +2024-11-22 21:50:18.012233: Epoch 6438 +2024-11-22 21:50:18.012344: Current learning rate: 0.0023 +2024-11-22 21:50:37.408831: train_loss -0.8135 +2024-11-22 21:50:37.409050: val_loss -0.7678 +2024-11-22 21:50:37.409135: Pseudo dice [0.8493] +2024-11-22 21:50:37.409212: Epoch time: 19.4 s +2024-11-22 21:50:38.319269: +2024-11-22 21:50:38.319504: Epoch 6439 +2024-11-22 21:50:38.319631: Current learning rate: 0.0023 +2024-11-22 21:50:57.061471: train_loss -0.8126 +2024-11-22 21:50:57.061728: val_loss -0.7622 +2024-11-22 21:50:57.061807: Pseudo dice [0.8629] +2024-11-22 21:50:57.061891: Epoch time: 18.74 s +2024-11-22 21:50:57.997728: +2024-11-22 21:50:57.997930: Epoch 6440 +2024-11-22 21:50:57.998048: Current learning rate: 0.0023 +2024-11-22 21:51:16.942355: train_loss -0.8094 +2024-11-22 21:51:16.942575: val_loss -0.7741 +2024-11-22 21:51:16.942653: Pseudo dice [0.8553] +2024-11-22 21:51:16.942755: Epoch time: 18.95 s +2024-11-22 21:51:18.275048: +2024-11-22 21:51:18.275254: Epoch 6441 +2024-11-22 21:51:18.275367: Current learning rate: 0.00229 +2024-11-22 21:51:37.185133: train_loss -0.8087 +2024-11-22 21:51:37.185369: val_loss -0.7427 +2024-11-22 21:51:37.185445: Pseudo dice [0.8596] +2024-11-22 21:51:37.190666: Epoch time: 18.91 s +2024-11-22 21:51:38.178643: +2024-11-22 21:51:38.178864: Epoch 6442 +2024-11-22 21:51:38.178976: Current learning rate: 0.00229 +2024-11-22 21:51:56.975866: train_loss -0.8129 +2024-11-22 21:51:56.976276: val_loss -0.765 +2024-11-22 21:51:56.976400: Pseudo dice [0.8594] +2024-11-22 21:51:56.976481: Epoch time: 18.8 s +2024-11-22 21:51:57.896195: +2024-11-22 21:51:57.896419: Epoch 6443 +2024-11-22 21:51:57.896527: Current learning rate: 0.00229 +2024-11-22 21:52:16.812278: train_loss -0.8228 +2024-11-22 21:52:16.812530: val_loss -0.7696 +2024-11-22 21:52:16.812604: Pseudo dice [0.8557] +2024-11-22 21:52:16.812685: Epoch time: 18.92 s +2024-11-22 21:52:17.723117: +2024-11-22 21:52:17.723330: Epoch 6444 +2024-11-22 21:52:17.723444: Current learning rate: 0.00229 +2024-11-22 21:52:37.120869: train_loss -0.8171 +2024-11-22 21:52:37.121155: val_loss -0.7224 +2024-11-22 21:52:37.121233: Pseudo dice [0.8449] +2024-11-22 21:52:37.121310: Epoch time: 19.4 s +2024-11-22 21:52:38.035806: +2024-11-22 21:52:38.036019: Epoch 6445 +2024-11-22 21:52:38.036134: Current learning rate: 0.00229 +2024-11-22 21:52:56.741901: train_loss -0.8147 +2024-11-22 21:52:56.742136: val_loss -0.7807 +2024-11-22 21:52:56.742217: Pseudo dice [0.8512] +2024-11-22 21:52:56.742294: Epoch time: 18.71 s +2024-11-22 21:52:57.665708: +2024-11-22 21:52:57.665946: Epoch 6446 +2024-11-22 21:52:57.666061: Current learning rate: 0.00229 +2024-11-22 21:53:16.352862: train_loss -0.8106 +2024-11-22 21:53:16.353113: val_loss -0.7435 +2024-11-22 21:53:16.353194: Pseudo dice [0.8472] +2024-11-22 21:53:16.353284: Epoch time: 18.69 s +2024-11-22 21:53:17.409166: +2024-11-22 21:53:17.409406: Epoch 6447 +2024-11-22 21:53:17.409517: Current learning rate: 0.00229 +2024-11-22 21:53:35.026050: train_loss -0.8075 +2024-11-22 21:53:35.026289: val_loss -0.7554 +2024-11-22 21:53:35.026368: Pseudo dice [0.8525] +2024-11-22 21:53:35.026455: Epoch time: 17.62 s +2024-11-22 21:53:35.940345: +2024-11-22 21:53:35.940538: Epoch 6448 +2024-11-22 21:53:35.940651: Current learning rate: 0.00229 +2024-11-22 21:53:53.699378: train_loss -0.8162 +2024-11-22 21:53:53.699598: val_loss -0.7462 +2024-11-22 21:53:53.699672: Pseudo dice [0.8539] +2024-11-22 21:53:53.699749: Epoch time: 17.76 s +2024-11-22 21:53:54.832365: +2024-11-22 21:53:54.832574: Epoch 6449 +2024-11-22 21:53:54.832689: Current learning rate: 0.00228 +2024-11-22 21:54:12.414341: train_loss -0.8147 +2024-11-22 21:54:12.414566: val_loss -0.7676 +2024-11-22 21:54:12.414641: Pseudo dice [0.8551] +2024-11-22 21:54:12.414719: Epoch time: 17.58 s +2024-11-22 21:54:13.643366: +2024-11-22 21:54:13.643568: Epoch 6450 +2024-11-22 21:54:13.643677: Current learning rate: 0.00228 +2024-11-22 21:54:32.577342: train_loss -0.8042 +2024-11-22 21:54:32.577581: val_loss -0.7405 +2024-11-22 21:54:32.577657: Pseudo dice [0.853] +2024-11-22 21:54:32.577737: Epoch time: 18.93 s +2024-11-22 21:54:33.492733: +2024-11-22 21:54:33.492935: Epoch 6451 +2024-11-22 21:54:33.493054: Current learning rate: 0.00228 +2024-11-22 21:54:51.642024: train_loss -0.8178 +2024-11-22 21:54:51.642247: val_loss -0.7739 +2024-11-22 21:54:51.642326: Pseudo dice [0.8684] +2024-11-22 21:54:51.642404: Epoch time: 18.15 s +2024-11-22 21:54:52.601047: +2024-11-22 21:54:52.601237: Epoch 6452 +2024-11-22 21:54:52.601368: Current learning rate: 0.00228 +2024-11-22 21:55:11.462503: train_loss -0.8071 +2024-11-22 21:55:11.462724: val_loss -0.7877 +2024-11-22 21:55:11.462803: Pseudo dice [0.8751] +2024-11-22 21:55:11.462886: Epoch time: 18.86 s +2024-11-22 21:55:11.462948: Yayy! New best EMA pseudo Dice: 0.8562 +2024-11-22 21:55:13.063679: +2024-11-22 21:55:13.063900: Epoch 6453 +2024-11-22 21:55:13.064017: Current learning rate: 0.00228 +2024-11-22 21:55:31.584270: train_loss -0.8102 +2024-11-22 21:55:31.584548: val_loss -0.7618 +2024-11-22 21:55:31.584624: Pseudo dice [0.8476] +2024-11-22 21:55:31.584710: Epoch time: 18.52 s +2024-11-22 21:55:32.607248: +2024-11-22 21:55:32.607485: Epoch 6454 +2024-11-22 21:55:32.607604: Current learning rate: 0.00228 +2024-11-22 21:55:51.497370: train_loss -0.8099 +2024-11-22 21:55:51.497577: val_loss -0.7331 +2024-11-22 21:55:51.497653: Pseudo dice [0.8238] +2024-11-22 21:55:51.497730: Epoch time: 18.89 s +2024-11-22 21:55:52.410134: +2024-11-22 21:55:52.410343: Epoch 6455 +2024-11-22 21:55:52.410453: Current learning rate: 0.00228 +2024-11-22 21:56:11.076138: train_loss -0.8166 +2024-11-22 21:56:11.076358: val_loss -0.7592 +2024-11-22 21:56:11.076439: Pseudo dice [0.8673] +2024-11-22 21:56:11.076533: Epoch time: 18.67 s +2024-11-22 21:56:12.100607: +2024-11-22 21:56:12.100835: Epoch 6456 +2024-11-22 21:56:12.100946: Current learning rate: 0.00228 +2024-11-22 21:56:31.240788: train_loss -0.8143 +2024-11-22 21:56:31.241004: val_loss -0.7616 +2024-11-22 21:56:31.241077: Pseudo dice [0.8328] +2024-11-22 21:56:31.241160: Epoch time: 19.14 s +2024-11-22 21:56:32.146426: +2024-11-22 21:56:32.146638: Epoch 6457 +2024-11-22 21:56:32.146748: Current learning rate: 0.00227 +2024-11-22 21:56:51.235096: train_loss -0.8198 +2024-11-22 21:56:51.235413: val_loss -0.7494 +2024-11-22 21:56:51.235519: Pseudo dice [0.822] +2024-11-22 21:56:51.235613: Epoch time: 19.09 s +2024-11-22 21:56:52.151479: +2024-11-22 21:56:52.151692: Epoch 6458 +2024-11-22 21:56:52.151801: Current learning rate: 0.00227 +2024-11-22 21:57:11.274057: train_loss -0.8119 +2024-11-22 21:57:11.274282: val_loss -0.7314 +2024-11-22 21:57:11.274357: Pseudo dice [0.8397] +2024-11-22 21:57:11.274517: Epoch time: 19.12 s +2024-11-22 21:57:12.193097: +2024-11-22 21:57:12.193308: Epoch 6459 +2024-11-22 21:57:12.193422: Current learning rate: 0.00227 +2024-11-22 21:57:31.963908: train_loss -0.8124 +2024-11-22 21:57:31.964134: val_loss -0.7682 +2024-11-22 21:57:31.964214: Pseudo dice [0.8704] +2024-11-22 21:57:31.964291: Epoch time: 19.77 s +2024-11-22 21:57:32.878977: +2024-11-22 21:57:32.879199: Epoch 6460 +2024-11-22 21:57:32.879305: Current learning rate: 0.00227 +2024-11-22 21:57:51.599248: train_loss -0.8083 +2024-11-22 21:57:51.599471: val_loss -0.7554 +2024-11-22 21:57:51.599545: Pseudo dice [0.8425] +2024-11-22 21:57:51.599621: Epoch time: 18.72 s +2024-11-22 21:57:52.613872: +2024-11-22 21:57:52.614176: Epoch 6461 +2024-11-22 21:57:52.614293: Current learning rate: 0.00227 +2024-11-22 21:58:12.058697: train_loss -0.8067 +2024-11-22 21:58:12.058944: val_loss -0.7658 +2024-11-22 21:58:12.059023: Pseudo dice [0.8392] +2024-11-22 21:58:12.059106: Epoch time: 19.45 s +2024-11-22 21:58:12.978179: +2024-11-22 21:58:12.978392: Epoch 6462 +2024-11-22 21:58:12.978512: Current learning rate: 0.00227 +2024-11-22 21:58:30.966678: train_loss -0.8072 +2024-11-22 21:58:30.966892: val_loss -0.7609 +2024-11-22 21:58:30.966968: Pseudo dice [0.8385] +2024-11-22 21:58:30.967053: Epoch time: 17.99 s +2024-11-22 21:58:31.876128: +2024-11-22 21:58:31.876360: Epoch 6463 +2024-11-22 21:58:31.876477: Current learning rate: 0.00227 +2024-11-22 21:58:49.389566: train_loss -0.8128 +2024-11-22 21:58:49.400064: val_loss -0.7644 +2024-11-22 21:58:49.400167: Pseudo dice [0.8611] +2024-11-22 21:58:49.400248: Epoch time: 17.51 s +2024-11-22 21:58:50.712001: +2024-11-22 21:58:50.712215: Epoch 6464 +2024-11-22 21:58:50.712326: Current learning rate: 0.00226 +2024-11-22 21:59:08.925928: train_loss -0.8149 +2024-11-22 21:59:08.926553: val_loss -0.7483 +2024-11-22 21:59:08.926662: Pseudo dice [0.8468] +2024-11-22 21:59:08.926750: Epoch time: 18.21 s +2024-11-22 21:59:09.853709: +2024-11-22 21:59:09.853920: Epoch 6465 +2024-11-22 21:59:09.854034: Current learning rate: 0.00226 +2024-11-22 21:59:29.433456: train_loss -0.81 +2024-11-22 21:59:29.433672: val_loss -0.7538 +2024-11-22 21:59:29.433747: Pseudo dice [0.8445] +2024-11-22 21:59:29.433823: Epoch time: 19.58 s +2024-11-22 21:59:30.343130: +2024-11-22 21:59:30.343346: Epoch 6466 +2024-11-22 21:59:30.343460: Current learning rate: 0.00226 +2024-11-22 21:59:50.424469: train_loss -0.8098 +2024-11-22 21:59:50.424696: val_loss -0.7671 +2024-11-22 21:59:50.424771: Pseudo dice [0.8525] +2024-11-22 21:59:50.424845: Epoch time: 20.08 s +2024-11-22 21:59:51.476170: +2024-11-22 21:59:51.476401: Epoch 6467 +2024-11-22 21:59:51.476511: Current learning rate: 0.00226 +2024-11-22 22:00:10.403657: train_loss -0.8087 +2024-11-22 22:00:10.403895: val_loss -0.7392 +2024-11-22 22:00:10.403971: Pseudo dice [0.8307] +2024-11-22 22:00:10.404062: Epoch time: 18.93 s +2024-11-22 22:00:11.322332: +2024-11-22 22:00:11.322542: Epoch 6468 +2024-11-22 22:00:11.322795: Current learning rate: 0.00226 +2024-11-22 22:00:29.877092: train_loss -0.813 +2024-11-22 22:00:29.877311: val_loss -0.7336 +2024-11-22 22:00:29.877384: Pseudo dice [0.8226] +2024-11-22 22:00:29.877459: Epoch time: 18.56 s +2024-11-22 22:00:30.777785: +2024-11-22 22:00:30.778006: Epoch 6469 +2024-11-22 22:00:30.778118: Current learning rate: 0.00226 +2024-11-22 22:00:48.765412: train_loss -0.8171 +2024-11-22 22:00:48.765634: val_loss -0.7769 +2024-11-22 22:00:48.765710: Pseudo dice [0.8743] +2024-11-22 22:00:48.765786: Epoch time: 17.99 s +2024-11-22 22:00:49.677053: +2024-11-22 22:00:49.677266: Epoch 6470 +2024-11-22 22:00:49.677380: Current learning rate: 0.00226 +2024-11-22 22:01:07.392924: train_loss -0.8186 +2024-11-22 22:01:07.393225: val_loss -0.7383 +2024-11-22 22:01:07.393299: Pseudo dice [0.8255] +2024-11-22 22:01:07.393380: Epoch time: 17.72 s +2024-11-22 22:01:08.310304: +2024-11-22 22:01:08.310512: Epoch 6471 +2024-11-22 22:01:08.310624: Current learning rate: 0.00226 +2024-11-22 22:01:26.837501: train_loss -0.8193 +2024-11-22 22:01:26.838876: val_loss -0.7684 +2024-11-22 22:01:26.838973: Pseudo dice [0.8633] +2024-11-22 22:01:26.839068: Epoch time: 18.53 s +2024-11-22 22:01:27.764953: +2024-11-22 22:01:27.765253: Epoch 6472 +2024-11-22 22:01:27.765367: Current learning rate: 0.00225 +2024-11-22 22:01:46.232142: train_loss -0.8189 +2024-11-22 22:01:46.232363: val_loss -0.7497 +2024-11-22 22:01:46.232440: Pseudo dice [0.8588] +2024-11-22 22:01:46.232516: Epoch time: 18.47 s +2024-11-22 22:01:47.146913: +2024-11-22 22:01:47.147122: Epoch 6473 +2024-11-22 22:01:47.147236: Current learning rate: 0.00225 +2024-11-22 22:02:06.135608: train_loss -0.8096 +2024-11-22 22:02:06.135872: val_loss -0.7438 +2024-11-22 22:02:06.135947: Pseudo dice [0.856] +2024-11-22 22:02:06.136029: Epoch time: 18.99 s +2024-11-22 22:02:07.152083: +2024-11-22 22:02:07.152302: Epoch 6474 +2024-11-22 22:02:07.152416: Current learning rate: 0.00225 +2024-11-22 22:02:25.267351: train_loss -0.8078 +2024-11-22 22:02:25.267646: val_loss -0.7579 +2024-11-22 22:02:25.267725: Pseudo dice [0.8536] +2024-11-22 22:02:25.267810: Epoch time: 18.12 s +2024-11-22 22:02:26.518344: +2024-11-22 22:02:26.518544: Epoch 6475 +2024-11-22 22:02:26.518652: Current learning rate: 0.00225 +2024-11-22 22:02:46.498941: train_loss -0.8176 +2024-11-22 22:02:46.499204: val_loss -0.7535 +2024-11-22 22:02:46.499281: Pseudo dice [0.8603] +2024-11-22 22:02:46.499358: Epoch time: 19.98 s +2024-11-22 22:02:47.410251: +2024-11-22 22:02:47.410450: Epoch 6476 +2024-11-22 22:02:47.410559: Current learning rate: 0.00225 +2024-11-22 22:03:06.170915: train_loss -0.8191 +2024-11-22 22:03:06.171149: val_loss -0.7543 +2024-11-22 22:03:06.171224: Pseudo dice [0.8564] +2024-11-22 22:03:06.171300: Epoch time: 18.76 s +2024-11-22 22:03:07.193343: +2024-11-22 22:03:07.193556: Epoch 6477 +2024-11-22 22:03:07.193673: Current learning rate: 0.00225 +2024-11-22 22:03:24.920480: train_loss -0.8112 +2024-11-22 22:03:24.920715: val_loss -0.7651 +2024-11-22 22:03:24.920789: Pseudo dice [0.8649] +2024-11-22 22:03:24.920880: Epoch time: 17.73 s +2024-11-22 22:03:25.837237: +2024-11-22 22:03:25.837441: Epoch 6478 +2024-11-22 22:03:25.837555: Current learning rate: 0.00225 +2024-11-22 22:03:44.331591: train_loss -0.81 +2024-11-22 22:03:44.331818: val_loss -0.7524 +2024-11-22 22:03:44.331892: Pseudo dice [0.8753] +2024-11-22 22:03:44.331967: Epoch time: 18.5 s +2024-11-22 22:03:45.289200: +2024-11-22 22:03:45.289395: Epoch 6479 +2024-11-22 22:03:45.289508: Current learning rate: 0.00224 +2024-11-22 22:04:03.288983: train_loss -0.817 +2024-11-22 22:04:03.289210: val_loss -0.746 +2024-11-22 22:04:03.289287: Pseudo dice [0.853] +2024-11-22 22:04:03.289385: Epoch time: 18.0 s +2024-11-22 22:04:04.257147: +2024-11-22 22:04:04.257359: Epoch 6480 +2024-11-22 22:04:04.257468: Current learning rate: 0.00224 +2024-11-22 22:04:23.530953: train_loss -0.8156 +2024-11-22 22:04:23.531181: val_loss -0.7278 +2024-11-22 22:04:23.531257: Pseudo dice [0.8528] +2024-11-22 22:04:23.531334: Epoch time: 19.27 s +2024-11-22 22:04:24.456363: +2024-11-22 22:04:24.456605: Epoch 6481 +2024-11-22 22:04:24.456722: Current learning rate: 0.00224 +2024-11-22 22:04:43.379086: train_loss -0.8163 +2024-11-22 22:04:43.379346: val_loss -0.7406 +2024-11-22 22:04:43.379418: Pseudo dice [0.8349] +2024-11-22 22:04:43.379501: Epoch time: 18.92 s +2024-11-22 22:04:44.361135: +2024-11-22 22:04:44.361366: Epoch 6482 +2024-11-22 22:04:44.361477: Current learning rate: 0.00224 +2024-11-22 22:05:03.059407: train_loss -0.8133 +2024-11-22 22:05:03.059697: val_loss -0.7324 +2024-11-22 22:05:03.059783: Pseudo dice [0.8525] +2024-11-22 22:05:03.059863: Epoch time: 18.7 s +2024-11-22 22:05:03.974389: +2024-11-22 22:05:03.974618: Epoch 6483 +2024-11-22 22:05:03.974730: Current learning rate: 0.00224 +2024-11-22 22:05:23.358262: train_loss -0.7968 +2024-11-22 22:05:23.358477: val_loss -0.7566 +2024-11-22 22:05:23.358552: Pseudo dice [0.84] +2024-11-22 22:05:23.358627: Epoch time: 19.38 s +2024-11-22 22:05:24.298970: +2024-11-22 22:05:24.299240: Epoch 6484 +2024-11-22 22:05:24.299356: Current learning rate: 0.00224 +2024-11-22 22:05:41.711527: train_loss -0.8094 +2024-11-22 22:05:41.712352: val_loss -0.7789 +2024-11-22 22:05:41.712438: Pseudo dice [0.8547] +2024-11-22 22:05:41.712513: Epoch time: 17.41 s +2024-11-22 22:05:42.628130: +2024-11-22 22:05:42.628337: Epoch 6485 +2024-11-22 22:05:42.628455: Current learning rate: 0.00224 +2024-11-22 22:06:01.218629: train_loss -0.8168 +2024-11-22 22:06:01.218959: val_loss -0.7541 +2024-11-22 22:06:01.219045: Pseudo dice [0.8645] +2024-11-22 22:06:01.219135: Epoch time: 18.59 s +2024-11-22 22:06:02.149711: +2024-11-22 22:06:02.149920: Epoch 6486 +2024-11-22 22:06:02.150035: Current learning rate: 0.00224 +2024-11-22 22:06:20.475664: train_loss -0.8225 +2024-11-22 22:06:20.475957: val_loss -0.7546 +2024-11-22 22:06:20.476047: Pseudo dice [0.8666] +2024-11-22 22:06:20.476126: Epoch time: 18.33 s +2024-11-22 22:06:21.851014: +2024-11-22 22:06:21.851433: Epoch 6487 +2024-11-22 22:06:21.851571: Current learning rate: 0.00223 +2024-11-22 22:06:40.618509: train_loss -0.816 +2024-11-22 22:06:40.618732: val_loss -0.78 +2024-11-22 22:06:40.618806: Pseudo dice [0.8626] +2024-11-22 22:06:40.618887: Epoch time: 18.77 s +2024-11-22 22:06:41.532951: +2024-11-22 22:06:41.533386: Epoch 6488 +2024-11-22 22:06:41.533519: Current learning rate: 0.00223 +2024-11-22 22:07:00.440124: train_loss -0.8076 +2024-11-22 22:07:00.441362: val_loss -0.7364 +2024-11-22 22:07:00.441473: Pseudo dice [0.8485] +2024-11-22 22:07:00.441564: Epoch time: 18.91 s +2024-11-22 22:07:01.363990: +2024-11-22 22:07:01.364431: Epoch 6489 +2024-11-22 22:07:01.364564: Current learning rate: 0.00223 +2024-11-22 22:07:21.052644: train_loss -0.804 +2024-11-22 22:07:21.052866: val_loss -0.7452 +2024-11-22 22:07:21.052967: Pseudo dice [0.8166] +2024-11-22 22:07:21.053055: Epoch time: 19.69 s +2024-11-22 22:07:21.963317: +2024-11-22 22:07:21.963825: Epoch 6490 +2024-11-22 22:07:21.963964: Current learning rate: 0.00223 +2024-11-22 22:07:40.021111: train_loss -0.8115 +2024-11-22 22:07:40.021328: val_loss -0.7751 +2024-11-22 22:07:40.021418: Pseudo dice [0.8299] +2024-11-22 22:07:40.021498: Epoch time: 18.06 s +2024-11-22 22:07:40.936953: +2024-11-22 22:07:40.937401: Epoch 6491 +2024-11-22 22:07:40.937535: Current learning rate: 0.00223 +2024-11-22 22:07:59.507916: train_loss -0.811 +2024-11-22 22:07:59.508142: val_loss -0.7446 +2024-11-22 22:07:59.508215: Pseudo dice [0.8489] +2024-11-22 22:07:59.508338: Epoch time: 18.57 s +2024-11-22 22:08:00.424339: +2024-11-22 22:08:00.424807: Epoch 6492 +2024-11-22 22:08:00.424946: Current learning rate: 0.00223 +2024-11-22 22:08:19.138628: train_loss -0.8087 +2024-11-22 22:08:19.138845: val_loss -0.7451 +2024-11-22 22:08:19.138921: Pseudo dice [0.8351] +2024-11-22 22:08:19.139008: Epoch time: 18.72 s +2024-11-22 22:08:20.284870: +2024-11-22 22:08:20.285302: Epoch 6493 +2024-11-22 22:08:20.285434: Current learning rate: 0.00223 +2024-11-22 22:08:38.785234: train_loss -0.8157 +2024-11-22 22:08:38.785498: val_loss -0.785 +2024-11-22 22:08:38.785576: Pseudo dice [0.8396] +2024-11-22 22:08:38.785658: Epoch time: 18.5 s +2024-11-22 22:08:39.867998: +2024-11-22 22:08:39.869163: Epoch 6494 +2024-11-22 22:08:39.869325: Current learning rate: 0.00222 +2024-11-22 22:08:59.053220: train_loss -0.8188 +2024-11-22 22:08:59.053443: val_loss -0.7517 +2024-11-22 22:08:59.053545: Pseudo dice [0.8482] +2024-11-22 22:08:59.053629: Epoch time: 19.19 s +2024-11-22 22:08:59.973643: +2024-11-22 22:08:59.974097: Epoch 6495 +2024-11-22 22:08:59.974224: Current learning rate: 0.00222 +2024-11-22 22:09:18.298139: train_loss -0.8183 +2024-11-22 22:09:18.298391: val_loss -0.7415 +2024-11-22 22:09:18.298464: Pseudo dice [0.8274] +2024-11-22 22:09:18.298541: Epoch time: 18.33 s +2024-11-22 22:09:19.242290: +2024-11-22 22:09:19.242755: Epoch 6496 +2024-11-22 22:09:19.242888: Current learning rate: 0.00222 +2024-11-22 22:09:37.379559: train_loss -0.8131 +2024-11-22 22:09:37.379787: val_loss -0.732 +2024-11-22 22:09:37.379863: Pseudo dice [0.8303] +2024-11-22 22:09:37.379947: Epoch time: 18.14 s +2024-11-22 22:09:38.294945: +2024-11-22 22:09:38.295370: Epoch 6497 +2024-11-22 22:09:38.295510: Current learning rate: 0.00222 +2024-11-22 22:09:56.257420: train_loss -0.815 +2024-11-22 22:09:56.257664: val_loss -0.7453 +2024-11-22 22:09:56.257739: Pseudo dice [0.8672] +2024-11-22 22:09:56.257821: Epoch time: 17.96 s +2024-11-22 22:09:57.576385: +2024-11-22 22:09:57.576612: Epoch 6498 +2024-11-22 22:09:57.576724: Current learning rate: 0.00222 +2024-11-22 22:10:16.745125: train_loss -0.8133 +2024-11-22 22:10:16.745378: val_loss -0.7508 +2024-11-22 22:10:16.745456: Pseudo dice [0.8387] +2024-11-22 22:10:16.745537: Epoch time: 19.17 s +2024-11-22 22:10:17.656710: +2024-11-22 22:10:17.656934: Epoch 6499 +2024-11-22 22:10:17.657052: Current learning rate: 0.00222 +2024-11-22 22:10:35.786054: train_loss -0.8195 +2024-11-22 22:10:35.786277: val_loss -0.7499 +2024-11-22 22:10:35.786353: Pseudo dice [0.8356] +2024-11-22 22:10:35.786429: Epoch time: 18.13 s +2024-11-22 22:10:37.014863: +2024-11-22 22:10:37.015081: Epoch 6500 +2024-11-22 22:10:37.015192: Current learning rate: 0.00222 +2024-11-22 22:10:56.197511: train_loss -0.8157 +2024-11-22 22:10:56.197834: val_loss -0.7627 +2024-11-22 22:10:56.197914: Pseudo dice [0.8448] +2024-11-22 22:10:56.198005: Epoch time: 19.18 s +2024-11-22 22:10:57.162343: +2024-11-22 22:10:57.162570: Epoch 6501 +2024-11-22 22:10:57.162683: Current learning rate: 0.00222 +2024-11-22 22:11:15.774017: train_loss -0.8131 +2024-11-22 22:11:15.774271: val_loss -0.7729 +2024-11-22 22:11:15.774347: Pseudo dice [0.8628] +2024-11-22 22:11:15.774422: Epoch time: 18.61 s +2024-11-22 22:11:16.684896: +2024-11-22 22:11:16.685094: Epoch 6502 +2024-11-22 22:11:16.685201: Current learning rate: 0.00221 +2024-11-22 22:11:36.305125: train_loss -0.8122 +2024-11-22 22:11:36.305359: val_loss -0.7379 +2024-11-22 22:11:36.305436: Pseudo dice [0.8354] +2024-11-22 22:11:36.305508: Epoch time: 19.62 s +2024-11-22 22:11:37.224437: +2024-11-22 22:11:37.224710: Epoch 6503 +2024-11-22 22:11:37.224838: Current learning rate: 0.00221 +2024-11-22 22:11:55.543679: train_loss -0.8076 +2024-11-22 22:11:55.546090: val_loss -0.7457 +2024-11-22 22:11:55.546225: Pseudo dice [0.8529] +2024-11-22 22:11:55.546304: Epoch time: 18.32 s +2024-11-22 22:11:56.473983: +2024-11-22 22:11:56.474233: Epoch 6504 +2024-11-22 22:11:56.474348: Current learning rate: 0.00221 +2024-11-22 22:12:15.371242: train_loss -0.8055 +2024-11-22 22:12:15.371505: val_loss -0.741 +2024-11-22 22:12:15.371581: Pseudo dice [0.856] +2024-11-22 22:12:15.371667: Epoch time: 18.9 s +2024-11-22 22:12:16.288674: +2024-11-22 22:12:16.288898: Epoch 6505 +2024-11-22 22:12:16.289016: Current learning rate: 0.00221 +2024-11-22 22:12:35.187738: train_loss -0.8175 +2024-11-22 22:12:35.187962: val_loss -0.7526 +2024-11-22 22:12:35.188046: Pseudo dice [0.842] +2024-11-22 22:12:35.188123: Epoch time: 18.9 s +2024-11-22 22:12:36.105434: +2024-11-22 22:12:36.105644: Epoch 6506 +2024-11-22 22:12:36.105757: Current learning rate: 0.00221 +2024-11-22 22:12:55.588735: train_loss -0.8186 +2024-11-22 22:12:55.588953: val_loss -0.7642 +2024-11-22 22:12:55.589033: Pseudo dice [0.844] +2024-11-22 22:12:55.589113: Epoch time: 19.48 s +2024-11-22 22:12:56.596858: +2024-11-22 22:12:56.597104: Epoch 6507 +2024-11-22 22:12:56.597231: Current learning rate: 0.00221 +2024-11-22 22:13:15.960649: train_loss -0.8187 +2024-11-22 22:13:15.960874: val_loss -0.7099 +2024-11-22 22:13:15.960948: Pseudo dice [0.8202] +2024-11-22 22:13:15.961035: Epoch time: 19.36 s +2024-11-22 22:13:16.973696: +2024-11-22 22:13:16.973905: Epoch 6508 +2024-11-22 22:13:16.974027: Current learning rate: 0.00221 +2024-11-22 22:13:35.418338: train_loss -0.8215 +2024-11-22 22:13:35.418571: val_loss -0.7315 +2024-11-22 22:13:35.418643: Pseudo dice [0.8374] +2024-11-22 22:13:35.418724: Epoch time: 18.45 s +2024-11-22 22:13:36.343286: +2024-11-22 22:13:36.343702: Epoch 6509 +2024-11-22 22:13:36.343836: Current learning rate: 0.0022 +2024-11-22 22:13:55.513829: train_loss -0.8217 +2024-11-22 22:13:55.514092: val_loss -0.7154 +2024-11-22 22:13:55.514175: Pseudo dice [0.8302] +2024-11-22 22:13:55.514259: Epoch time: 19.17 s +2024-11-22 22:13:56.426680: +2024-11-22 22:13:56.426900: Epoch 6510 +2024-11-22 22:13:56.427027: Current learning rate: 0.0022 +2024-11-22 22:14:15.629292: train_loss -0.8149 +2024-11-22 22:14:15.629529: val_loss -0.7508 +2024-11-22 22:14:15.629605: Pseudo dice [0.8339] +2024-11-22 22:14:15.629679: Epoch time: 19.2 s +2024-11-22 22:14:16.535670: +2024-11-22 22:14:16.536040: Epoch 6511 +2024-11-22 22:14:16.536150: Current learning rate: 0.0022 +2024-11-22 22:14:35.745946: train_loss -0.8114 +2024-11-22 22:14:35.746221: val_loss -0.7711 +2024-11-22 22:14:35.746301: Pseudo dice [0.8445] +2024-11-22 22:14:35.746389: Epoch time: 19.21 s +2024-11-22 22:14:36.673894: +2024-11-22 22:14:36.674102: Epoch 6512 +2024-11-22 22:14:36.674209: Current learning rate: 0.0022 +2024-11-22 22:14:55.091470: train_loss -0.8184 +2024-11-22 22:14:55.091706: val_loss -0.7512 +2024-11-22 22:14:55.091786: Pseudo dice [0.8304] +2024-11-22 22:14:55.091867: Epoch time: 18.42 s +2024-11-22 22:14:56.025569: +2024-11-22 22:14:56.025860: Epoch 6513 +2024-11-22 22:14:56.025975: Current learning rate: 0.0022 +2024-11-22 22:15:14.711942: train_loss -0.8183 +2024-11-22 22:15:14.712187: val_loss -0.7955 +2024-11-22 22:15:14.712263: Pseudo dice [0.8685] +2024-11-22 22:15:14.712342: Epoch time: 18.69 s +2024-11-22 22:15:15.630650: +2024-11-22 22:15:15.630865: Epoch 6514 +2024-11-22 22:15:15.630982: Current learning rate: 0.0022 +2024-11-22 22:15:34.563636: train_loss -0.8117 +2024-11-22 22:15:34.563877: val_loss -0.7237 +2024-11-22 22:15:34.563958: Pseudo dice [0.8311] +2024-11-22 22:15:34.564050: Epoch time: 18.93 s +2024-11-22 22:15:35.541259: +2024-11-22 22:15:35.541468: Epoch 6515 +2024-11-22 22:15:35.541577: Current learning rate: 0.0022 +2024-11-22 22:15:53.643769: train_loss -0.8187 +2024-11-22 22:15:53.644028: val_loss -0.7689 +2024-11-22 22:15:53.644107: Pseudo dice [0.8344] +2024-11-22 22:15:53.644186: Epoch time: 18.1 s +2024-11-22 22:15:54.560596: +2024-11-22 22:15:54.560783: Epoch 6516 +2024-11-22 22:15:54.560893: Current learning rate: 0.0022 +2024-11-22 22:16:13.170352: train_loss -0.8185 +2024-11-22 22:16:13.170608: val_loss -0.7477 +2024-11-22 22:16:13.170753: Pseudo dice [0.8549] +2024-11-22 22:16:13.170838: Epoch time: 18.61 s +2024-11-22 22:16:14.091365: +2024-11-22 22:16:14.091567: Epoch 6517 +2024-11-22 22:16:14.091673: Current learning rate: 0.00219 +2024-11-22 22:16:32.484335: train_loss -0.8161 +2024-11-22 22:16:32.484562: val_loss -0.7744 +2024-11-22 22:16:32.484684: Pseudo dice [0.854] +2024-11-22 22:16:32.484763: Epoch time: 18.39 s +2024-11-22 22:16:33.409948: +2024-11-22 22:16:33.410156: Epoch 6518 +2024-11-22 22:16:33.410268: Current learning rate: 0.00219 +2024-11-22 22:16:52.109629: train_loss -0.8136 +2024-11-22 22:16:52.109861: val_loss -0.7488 +2024-11-22 22:16:52.109937: Pseudo dice [0.838] +2024-11-22 22:16:52.110022: Epoch time: 18.7 s +2024-11-22 22:16:53.029509: +2024-11-22 22:16:53.029688: Epoch 6519 +2024-11-22 22:16:53.029822: Current learning rate: 0.00219 +2024-11-22 22:17:11.869963: train_loss -0.8221 +2024-11-22 22:17:11.870195: val_loss -0.7282 +2024-11-22 22:17:11.870272: Pseudo dice [0.8325] +2024-11-22 22:17:11.870353: Epoch time: 18.84 s +2024-11-22 22:17:12.788761: +2024-11-22 22:17:12.788986: Epoch 6520 +2024-11-22 22:17:12.789102: Current learning rate: 0.00219 +2024-11-22 22:17:31.943392: train_loss -0.8135 +2024-11-22 22:17:31.943647: val_loss -0.7329 +2024-11-22 22:17:31.943741: Pseudo dice [0.8326] +2024-11-22 22:17:31.943899: Epoch time: 19.16 s +2024-11-22 22:17:32.857530: +2024-11-22 22:17:32.857736: Epoch 6521 +2024-11-22 22:17:32.857846: Current learning rate: 0.00219 +2024-11-22 22:17:50.668604: train_loss -0.8054 +2024-11-22 22:17:50.668846: val_loss -0.738 +2024-11-22 22:17:50.668927: Pseudo dice [0.8502] +2024-11-22 22:17:50.669019: Epoch time: 17.81 s +2024-11-22 22:17:51.583001: +2024-11-22 22:17:51.583230: Epoch 6522 +2024-11-22 22:17:51.583340: Current learning rate: 0.00219 +2024-11-22 22:18:10.657369: train_loss -0.8028 +2024-11-22 22:18:10.657603: val_loss -0.7608 +2024-11-22 22:18:10.657683: Pseudo dice [0.859] +2024-11-22 22:18:10.657759: Epoch time: 19.08 s +2024-11-22 22:18:11.571142: +2024-11-22 22:18:11.571416: Epoch 6523 +2024-11-22 22:18:11.571531: Current learning rate: 0.00219 +2024-11-22 22:18:30.263875: train_loss -0.8101 +2024-11-22 22:18:30.264152: val_loss -0.7568 +2024-11-22 22:18:30.264231: Pseudo dice [0.8573] +2024-11-22 22:18:30.264314: Epoch time: 18.69 s +2024-11-22 22:18:31.181906: +2024-11-22 22:18:31.182171: Epoch 6524 +2024-11-22 22:18:31.182288: Current learning rate: 0.00218 +2024-11-22 22:18:49.232774: train_loss -0.7997 +2024-11-22 22:18:49.233021: val_loss -0.7763 +2024-11-22 22:18:49.233195: Pseudo dice [0.8604] +2024-11-22 22:18:49.233275: Epoch time: 18.05 s +2024-11-22 22:18:50.150763: +2024-11-22 22:18:50.150985: Epoch 6525 +2024-11-22 22:18:50.151107: Current learning rate: 0.00218 +2024-11-22 22:19:08.729043: train_loss -0.7981 +2024-11-22 22:19:08.729257: val_loss -0.7626 +2024-11-22 22:19:08.729331: Pseudo dice [0.8398] +2024-11-22 22:19:08.730779: Epoch time: 18.58 s +2024-11-22 22:19:09.684850: +2024-11-22 22:19:09.685093: Epoch 6526 +2024-11-22 22:19:09.685210: Current learning rate: 0.00218 +2024-11-22 22:19:27.675336: train_loss -0.8067 +2024-11-22 22:19:27.675561: val_loss -0.7364 +2024-11-22 22:19:27.675639: Pseudo dice [0.8454] +2024-11-22 22:19:27.675719: Epoch time: 17.99 s +2024-11-22 22:19:28.594078: +2024-11-22 22:19:28.594271: Epoch 6527 +2024-11-22 22:19:28.594386: Current learning rate: 0.00218 +2024-11-22 22:19:48.372147: train_loss -0.8089 +2024-11-22 22:19:48.372403: val_loss -0.7541 +2024-11-22 22:19:48.372481: Pseudo dice [0.8392] +2024-11-22 22:19:48.372590: Epoch time: 19.78 s +2024-11-22 22:19:49.287848: +2024-11-22 22:19:49.288065: Epoch 6528 +2024-11-22 22:19:49.288186: Current learning rate: 0.00218 +2024-11-22 22:20:08.388044: train_loss -0.8112 +2024-11-22 22:20:08.388260: val_loss -0.7334 +2024-11-22 22:20:08.388334: Pseudo dice [0.8202] +2024-11-22 22:20:08.388407: Epoch time: 19.1 s +2024-11-22 22:20:09.318236: +2024-11-22 22:20:09.318474: Epoch 6529 +2024-11-22 22:20:09.318591: Current learning rate: 0.00218 +2024-11-22 22:20:29.349368: train_loss -0.812 +2024-11-22 22:20:29.349585: val_loss -0.7648 +2024-11-22 22:20:29.349733: Pseudo dice [0.8476] +2024-11-22 22:20:29.349812: Epoch time: 20.03 s +2024-11-22 22:20:30.275517: +2024-11-22 22:20:30.275711: Epoch 6530 +2024-11-22 22:20:30.275821: Current learning rate: 0.00218 +2024-11-22 22:20:48.810016: train_loss -0.8222 +2024-11-22 22:20:48.810243: val_loss -0.7742 +2024-11-22 22:20:48.810372: Pseudo dice [0.853] +2024-11-22 22:20:48.810462: Epoch time: 18.54 s +2024-11-22 22:20:49.731455: +2024-11-22 22:20:49.731687: Epoch 6531 +2024-11-22 22:20:49.731802: Current learning rate: 0.00218 +2024-11-22 22:21:08.667607: train_loss -0.8153 +2024-11-22 22:21:08.667923: val_loss -0.7399 +2024-11-22 22:21:08.668003: Pseudo dice [0.8338] +2024-11-22 22:21:08.668084: Epoch time: 18.94 s +2024-11-22 22:21:09.580702: +2024-11-22 22:21:09.580907: Epoch 6532 +2024-11-22 22:21:09.581024: Current learning rate: 0.00217 +2024-11-22 22:21:28.539937: train_loss -0.8137 +2024-11-22 22:21:28.540178: val_loss -0.7723 +2024-11-22 22:21:28.540261: Pseudo dice [0.8509] +2024-11-22 22:21:28.540337: Epoch time: 18.96 s +2024-11-22 22:21:29.446651: +2024-11-22 22:21:29.446870: Epoch 6533 +2024-11-22 22:21:29.446980: Current learning rate: 0.00217 +2024-11-22 22:21:48.854677: train_loss -0.8163 +2024-11-22 22:21:48.854913: val_loss -0.7493 +2024-11-22 22:21:48.854995: Pseudo dice [0.8452] +2024-11-22 22:21:48.855072: Epoch time: 19.41 s +2024-11-22 22:21:49.747097: +2024-11-22 22:21:49.747308: Epoch 6534 +2024-11-22 22:21:49.747421: Current learning rate: 0.00217 +2024-11-22 22:22:08.466386: train_loss -0.8171 +2024-11-22 22:22:08.466643: val_loss -0.7473 +2024-11-22 22:22:08.466718: Pseudo dice [0.8439] +2024-11-22 22:22:08.466806: Epoch time: 18.72 s +2024-11-22 22:22:09.373326: +2024-11-22 22:22:09.373540: Epoch 6535 +2024-11-22 22:22:09.373656: Current learning rate: 0.00217 +2024-11-22 22:22:28.115113: train_loss -0.8144 +2024-11-22 22:22:28.115336: val_loss -0.7432 +2024-11-22 22:22:28.115471: Pseudo dice [0.8257] +2024-11-22 22:22:28.115546: Epoch time: 18.74 s +2024-11-22 22:22:29.084464: +2024-11-22 22:22:29.084684: Epoch 6536 +2024-11-22 22:22:29.084797: Current learning rate: 0.00217 +2024-11-22 22:22:48.369627: train_loss -0.8165 +2024-11-22 22:22:48.369854: val_loss -0.7442 +2024-11-22 22:22:48.369942: Pseudo dice [0.8504] +2024-11-22 22:22:48.370026: Epoch time: 19.29 s +2024-11-22 22:22:49.292347: +2024-11-22 22:22:49.292581: Epoch 6537 +2024-11-22 22:22:49.292695: Current learning rate: 0.00217 +2024-11-22 22:23:07.959116: train_loss -0.8156 +2024-11-22 22:23:07.959334: val_loss -0.7501 +2024-11-22 22:23:07.959411: Pseudo dice [0.8463] +2024-11-22 22:23:07.959488: Epoch time: 18.67 s +2024-11-22 22:23:08.894910: +2024-11-22 22:23:08.895149: Epoch 6538 +2024-11-22 22:23:08.895261: Current learning rate: 0.00217 +2024-11-22 22:23:27.700133: train_loss -0.8169 +2024-11-22 22:23:27.700399: val_loss -0.7454 +2024-11-22 22:23:27.700486: Pseudo dice [0.855] +2024-11-22 22:23:27.700579: Epoch time: 18.81 s +2024-11-22 22:23:28.661531: +2024-11-22 22:23:28.661723: Epoch 6539 +2024-11-22 22:23:28.661833: Current learning rate: 0.00216 +2024-11-22 22:23:47.494367: train_loss -0.8143 +2024-11-22 22:23:47.494589: val_loss -0.7668 +2024-11-22 22:23:47.494667: Pseudo dice [0.8571] +2024-11-22 22:23:47.494748: Epoch time: 18.83 s +2024-11-22 22:23:48.417575: +2024-11-22 22:23:48.417798: Epoch 6540 +2024-11-22 22:23:48.417913: Current learning rate: 0.00216 +2024-11-22 22:24:07.523564: train_loss -0.8013 +2024-11-22 22:24:07.523790: val_loss -0.7327 +2024-11-22 22:24:07.523874: Pseudo dice [0.8316] +2024-11-22 22:24:07.523950: Epoch time: 19.11 s +2024-11-22 22:24:08.450953: +2024-11-22 22:24:08.451149: Epoch 6541 +2024-11-22 22:24:08.451260: Current learning rate: 0.00216 +2024-11-22 22:24:26.908138: train_loss -0.807 +2024-11-22 22:24:26.914409: val_loss -0.7489 +2024-11-22 22:24:26.914502: Pseudo dice [0.8412] +2024-11-22 22:24:26.914596: Epoch time: 18.46 s +2024-11-22 22:24:27.830582: +2024-11-22 22:24:27.830801: Epoch 6542 +2024-11-22 22:24:27.830924: Current learning rate: 0.00216 +2024-11-22 22:24:47.838013: train_loss -0.8147 +2024-11-22 22:24:47.838338: val_loss -0.7599 +2024-11-22 22:24:47.838414: Pseudo dice [0.8536] +2024-11-22 22:24:47.838494: Epoch time: 20.01 s +2024-11-22 22:24:48.854028: +2024-11-22 22:24:48.854319: Epoch 6543 +2024-11-22 22:24:48.854432: Current learning rate: 0.00216 +2024-11-22 22:25:06.527550: train_loss -0.8127 +2024-11-22 22:25:06.527835: val_loss -0.751 +2024-11-22 22:25:06.527917: Pseudo dice [0.8577] +2024-11-22 22:25:06.528001: Epoch time: 17.67 s +2024-11-22 22:25:07.432036: +2024-11-22 22:25:07.432274: Epoch 6544 +2024-11-22 22:25:07.432384: Current learning rate: 0.00216 +2024-11-22 22:25:26.096534: train_loss -0.8149 +2024-11-22 22:25:26.096762: val_loss -0.7552 +2024-11-22 22:25:26.096835: Pseudo dice [0.8321] +2024-11-22 22:25:26.096913: Epoch time: 18.67 s +2024-11-22 22:25:26.991545: +2024-11-22 22:25:26.991780: Epoch 6545 +2024-11-22 22:25:26.991892: Current learning rate: 0.00216 +2024-11-22 22:25:45.864906: train_loss -0.8136 +2024-11-22 22:25:45.865175: val_loss -0.7215 +2024-11-22 22:25:45.867451: Pseudo dice [0.8424] +2024-11-22 22:25:45.867558: Epoch time: 18.87 s +2024-11-22 22:25:46.968723: +2024-11-22 22:25:46.968947: Epoch 6546 +2024-11-22 22:25:46.969073: Current learning rate: 0.00216 +2024-11-22 22:26:05.806090: train_loss -0.8075 +2024-11-22 22:26:05.806313: val_loss -0.762 +2024-11-22 22:26:05.806463: Pseudo dice [0.851] +2024-11-22 22:26:05.806545: Epoch time: 18.84 s +2024-11-22 22:26:06.722178: +2024-11-22 22:26:06.722395: Epoch 6547 +2024-11-22 22:26:06.722511: Current learning rate: 0.00215 +2024-11-22 22:26:25.065784: train_loss -0.8161 +2024-11-22 22:26:25.066030: val_loss -0.734 +2024-11-22 22:26:25.066110: Pseudo dice [0.8584] +2024-11-22 22:26:25.066186: Epoch time: 18.34 s +2024-11-22 22:26:26.039360: +2024-11-22 22:26:26.039583: Epoch 6548 +2024-11-22 22:26:26.039701: Current learning rate: 0.00215 +2024-11-22 22:26:44.409538: train_loss -0.8202 +2024-11-22 22:26:44.409762: val_loss -0.7351 +2024-11-22 22:26:44.409847: Pseudo dice [0.8588] +2024-11-22 22:26:44.409928: Epoch time: 18.37 s +2024-11-22 22:26:45.316857: +2024-11-22 22:26:45.317060: Epoch 6549 +2024-11-22 22:26:45.317172: Current learning rate: 0.00215 +2024-11-22 22:27:03.471260: train_loss -0.8188 +2024-11-22 22:27:03.471514: val_loss -0.7337 +2024-11-22 22:27:03.471591: Pseudo dice [0.8611] +2024-11-22 22:27:03.471673: Epoch time: 18.16 s +2024-11-22 22:27:04.851632: +2024-11-22 22:27:04.851843: Epoch 6550 +2024-11-22 22:27:04.851948: Current learning rate: 0.00215 +2024-11-22 22:27:23.651171: train_loss -0.8209 +2024-11-22 22:27:23.651389: val_loss -0.7653 +2024-11-22 22:27:23.651468: Pseudo dice [0.8507] +2024-11-22 22:27:23.651546: Epoch time: 18.8 s +2024-11-22 22:27:24.561651: +2024-11-22 22:27:24.561867: Epoch 6551 +2024-11-22 22:27:24.561979: Current learning rate: 0.00215 +2024-11-22 22:27:42.958765: train_loss -0.8237 +2024-11-22 22:27:42.959001: val_loss -0.7506 +2024-11-22 22:27:42.959084: Pseudo dice [0.8363] +2024-11-22 22:27:42.959164: Epoch time: 18.4 s +2024-11-22 22:27:43.984299: +2024-11-22 22:27:43.984494: Epoch 6552 +2024-11-22 22:27:43.984604: Current learning rate: 0.00215 +2024-11-22 22:28:02.644297: train_loss -0.8145 +2024-11-22 22:28:02.644497: val_loss -0.7397 +2024-11-22 22:28:02.644574: Pseudo dice [0.8469] +2024-11-22 22:28:02.644653: Epoch time: 18.66 s +2024-11-22 22:28:03.892121: +2024-11-22 22:28:03.892329: Epoch 6553 +2024-11-22 22:28:03.892434: Current learning rate: 0.00215 +2024-11-22 22:28:23.609051: train_loss -0.8086 +2024-11-22 22:28:23.609327: val_loss -0.7501 +2024-11-22 22:28:23.609406: Pseudo dice [0.8387] +2024-11-22 22:28:23.614676: Epoch time: 19.72 s +2024-11-22 22:28:24.543780: +2024-11-22 22:28:24.544007: Epoch 6554 +2024-11-22 22:28:24.544119: Current learning rate: 0.00214 +2024-11-22 22:28:43.036469: train_loss -0.8067 +2024-11-22 22:28:43.036774: val_loss -0.7256 +2024-11-22 22:28:43.036853: Pseudo dice [0.808] +2024-11-22 22:28:43.036934: Epoch time: 18.49 s +2024-11-22 22:28:43.954303: +2024-11-22 22:28:43.954512: Epoch 6555 +2024-11-22 22:28:43.954624: Current learning rate: 0.00214 +2024-11-22 22:29:03.021064: train_loss -0.8124 +2024-11-22 22:29:03.021282: val_loss -0.7731 +2024-11-22 22:29:03.021355: Pseudo dice [0.8532] +2024-11-22 22:29:03.021439: Epoch time: 19.07 s +2024-11-22 22:29:03.930888: +2024-11-22 22:29:03.931100: Epoch 6556 +2024-11-22 22:29:03.931211: Current learning rate: 0.00214 +2024-11-22 22:29:23.277511: train_loss -0.8087 +2024-11-22 22:29:23.279905: val_loss -0.7577 +2024-11-22 22:29:23.279993: Pseudo dice [0.8587] +2024-11-22 22:29:23.280081: Epoch time: 19.35 s +2024-11-22 22:29:24.202690: +2024-11-22 22:29:24.202906: Epoch 6557 +2024-11-22 22:29:24.203022: Current learning rate: 0.00214 +2024-11-22 22:29:41.968203: train_loss -0.8119 +2024-11-22 22:29:41.968468: val_loss -0.7653 +2024-11-22 22:29:41.968550: Pseudo dice [0.8518] +2024-11-22 22:29:41.968631: Epoch time: 17.77 s +2024-11-22 22:29:42.890589: +2024-11-22 22:29:42.890848: Epoch 6558 +2024-11-22 22:29:42.890966: Current learning rate: 0.00214 +2024-11-22 22:30:01.902705: train_loss -0.7982 +2024-11-22 22:30:01.902929: val_loss -0.7552 +2024-11-22 22:30:01.903039: Pseudo dice [0.8428] +2024-11-22 22:30:01.903127: Epoch time: 19.01 s +2024-11-22 22:30:02.824539: +2024-11-22 22:30:02.824759: Epoch 6559 +2024-11-22 22:30:02.824881: Current learning rate: 0.00214 +2024-11-22 22:30:21.473890: train_loss -0.8063 +2024-11-22 22:30:21.474115: val_loss -0.7177 +2024-11-22 22:30:21.474195: Pseudo dice [0.8379] +2024-11-22 22:30:21.474272: Epoch time: 18.65 s +2024-11-22 22:30:22.391407: +2024-11-22 22:30:22.391649: Epoch 6560 +2024-11-22 22:30:22.391768: Current learning rate: 0.00214 +2024-11-22 22:30:41.371050: train_loss -0.8038 +2024-11-22 22:30:41.371277: val_loss -0.7344 +2024-11-22 22:30:41.371356: Pseudo dice [0.8477] +2024-11-22 22:30:41.371433: Epoch time: 18.98 s +2024-11-22 22:30:42.288190: +2024-11-22 22:30:42.288417: Epoch 6561 +2024-11-22 22:30:42.288542: Current learning rate: 0.00214 +2024-11-22 22:31:00.714296: train_loss -0.811 +2024-11-22 22:31:00.714514: val_loss -0.7611 +2024-11-22 22:31:00.714590: Pseudo dice [0.8561] +2024-11-22 22:31:00.714666: Epoch time: 18.43 s +2024-11-22 22:31:01.742571: +2024-11-22 22:31:01.742829: Epoch 6562 +2024-11-22 22:31:01.742944: Current learning rate: 0.00213 +2024-11-22 22:31:20.683152: train_loss -0.8207 +2024-11-22 22:31:20.683368: val_loss -0.7799 +2024-11-22 22:31:20.683444: Pseudo dice [0.8717] +2024-11-22 22:31:20.683518: Epoch time: 18.94 s +2024-11-22 22:31:21.641900: +2024-11-22 22:31:21.642123: Epoch 6563 +2024-11-22 22:31:21.642256: Current learning rate: 0.00213 +2024-11-22 22:31:40.745291: train_loss -0.8087 +2024-11-22 22:31:40.745575: val_loss -0.7624 +2024-11-22 22:31:40.745655: Pseudo dice [0.8633] +2024-11-22 22:31:40.745740: Epoch time: 19.1 s +2024-11-22 22:31:41.658820: +2024-11-22 22:31:41.659090: Epoch 6564 +2024-11-22 22:31:41.659204: Current learning rate: 0.00213 +2024-11-22 22:32:01.327712: train_loss -0.8195 +2024-11-22 22:32:01.327973: val_loss -0.7713 +2024-11-22 22:32:01.328060: Pseudo dice [0.8384] +2024-11-22 22:32:01.328149: Epoch time: 19.67 s +2024-11-22 22:32:02.610235: +2024-11-22 22:32:02.610449: Epoch 6565 +2024-11-22 22:32:02.610559: Current learning rate: 0.00213 +2024-11-22 22:32:21.139870: train_loss -0.8149 +2024-11-22 22:32:21.140102: val_loss -0.7318 +2024-11-22 22:32:21.140182: Pseudo dice [0.8799] +2024-11-22 22:32:21.140263: Epoch time: 18.53 s +2024-11-22 22:32:22.213478: +2024-11-22 22:32:22.213710: Epoch 6566 +2024-11-22 22:32:22.213824: Current learning rate: 0.00213 +2024-11-22 22:32:40.853063: train_loss -0.8172 +2024-11-22 22:32:40.853277: val_loss -0.7416 +2024-11-22 22:32:40.853352: Pseudo dice [0.8288] +2024-11-22 22:32:40.853428: Epoch time: 18.64 s +2024-11-22 22:32:41.769623: +2024-11-22 22:32:41.769844: Epoch 6567 +2024-11-22 22:32:41.769955: Current learning rate: 0.00213 +2024-11-22 22:32:59.086116: train_loss -0.8145 +2024-11-22 22:32:59.086335: val_loss -0.7442 +2024-11-22 22:32:59.086410: Pseudo dice [0.8511] +2024-11-22 22:32:59.086491: Epoch time: 17.32 s +2024-11-22 22:33:00.006552: +2024-11-22 22:33:00.006815: Epoch 6568 +2024-11-22 22:33:00.006928: Current learning rate: 0.00213 +2024-11-22 22:33:19.095410: train_loss -0.8083 +2024-11-22 22:33:19.100828: val_loss -0.7446 +2024-11-22 22:33:19.101032: Pseudo dice [0.8714] +2024-11-22 22:33:19.101132: Epoch time: 19.09 s +2024-11-22 22:33:20.063933: +2024-11-22 22:33:20.064250: Epoch 6569 +2024-11-22 22:33:20.064367: Current learning rate: 0.00212 +2024-11-22 22:33:38.840088: train_loss -0.8145 +2024-11-22 22:33:38.840312: val_loss -0.7776 +2024-11-22 22:33:38.840387: Pseudo dice [0.8709] +2024-11-22 22:33:38.840462: Epoch time: 18.78 s +2024-11-22 22:33:39.861045: +2024-11-22 22:33:39.861282: Epoch 6570 +2024-11-22 22:33:39.861416: Current learning rate: 0.00212 +2024-11-22 22:33:59.422103: train_loss -0.8091 +2024-11-22 22:33:59.422334: val_loss -0.7585 +2024-11-22 22:33:59.422410: Pseudo dice [0.8453] +2024-11-22 22:33:59.422486: Epoch time: 19.56 s +2024-11-22 22:34:00.337793: +2024-11-22 22:34:00.337989: Epoch 6571 +2024-11-22 22:34:00.338106: Current learning rate: 0.00212 +2024-11-22 22:34:18.264958: train_loss -0.818 +2024-11-22 22:34:18.265187: val_loss -0.7711 +2024-11-22 22:34:18.265262: Pseudo dice [0.8627] +2024-11-22 22:34:18.265517: Epoch time: 17.93 s +2024-11-22 22:34:19.188107: +2024-11-22 22:34:19.188333: Epoch 6572 +2024-11-22 22:34:19.188444: Current learning rate: 0.00212 +2024-11-22 22:34:37.546851: train_loss -0.8119 +2024-11-22 22:34:37.547078: val_loss -0.7274 +2024-11-22 22:34:37.547156: Pseudo dice [0.8171] +2024-11-22 22:34:37.547238: Epoch time: 18.36 s +2024-11-22 22:34:38.479903: +2024-11-22 22:34:38.480166: Epoch 6573 +2024-11-22 22:34:38.480286: Current learning rate: 0.00212 +2024-11-22 22:34:58.188144: train_loss -0.8003 +2024-11-22 22:34:58.188364: val_loss -0.7466 +2024-11-22 22:34:58.188441: Pseudo dice [0.8329] +2024-11-22 22:34:58.193699: Epoch time: 19.71 s +2024-11-22 22:34:59.316318: +2024-11-22 22:34:59.316511: Epoch 6574 +2024-11-22 22:34:59.316617: Current learning rate: 0.00212 +2024-11-22 22:35:17.518830: train_loss -0.8169 +2024-11-22 22:35:17.519061: val_loss -0.7473 +2024-11-22 22:35:17.519136: Pseudo dice [0.8383] +2024-11-22 22:35:17.519212: Epoch time: 18.2 s +2024-11-22 22:35:18.530713: +2024-11-22 22:35:18.530942: Epoch 6575 +2024-11-22 22:35:18.531054: Current learning rate: 0.00212 +2024-11-22 22:35:37.128052: train_loss -0.8216 +2024-11-22 22:35:37.133486: val_loss -0.7683 +2024-11-22 22:35:37.133606: Pseudo dice [0.8492] +2024-11-22 22:35:37.133694: Epoch time: 18.6 s +2024-11-22 22:35:38.591942: +2024-11-22 22:35:38.592160: Epoch 6576 +2024-11-22 22:35:38.592274: Current learning rate: 0.00212 +2024-11-22 22:35:57.741584: train_loss -0.8148 +2024-11-22 22:35:57.741902: val_loss -0.7534 +2024-11-22 22:35:57.741983: Pseudo dice [0.8555] +2024-11-22 22:35:57.742076: Epoch time: 19.15 s +2024-11-22 22:35:58.781229: +2024-11-22 22:35:58.781461: Epoch 6577 +2024-11-22 22:35:58.781573: Current learning rate: 0.00211 +2024-11-22 22:36:17.705270: train_loss -0.8125 +2024-11-22 22:36:17.705547: val_loss -0.7641 +2024-11-22 22:36:17.705649: Pseudo dice [0.8711] +2024-11-22 22:36:17.705725: Epoch time: 18.92 s +2024-11-22 22:36:18.623268: +2024-11-22 22:36:18.623484: Epoch 6578 +2024-11-22 22:36:18.623594: Current learning rate: 0.00211 +2024-11-22 22:36:36.250186: train_loss -0.8197 +2024-11-22 22:36:36.250398: val_loss -0.7756 +2024-11-22 22:36:36.250481: Pseudo dice [0.856] +2024-11-22 22:36:36.250561: Epoch time: 17.63 s +2024-11-22 22:36:37.166509: +2024-11-22 22:36:37.166761: Epoch 6579 +2024-11-22 22:36:37.166878: Current learning rate: 0.00211 +2024-11-22 22:36:55.152882: train_loss -0.8274 +2024-11-22 22:36:55.153115: val_loss -0.7134 +2024-11-22 22:36:55.153190: Pseudo dice [0.8217] +2024-11-22 22:36:55.153267: Epoch time: 17.99 s +2024-11-22 22:36:56.070590: +2024-11-22 22:36:56.070799: Epoch 6580 +2024-11-22 22:36:56.070911: Current learning rate: 0.00211 +2024-11-22 22:37:14.107678: train_loss -0.8153 +2024-11-22 22:37:14.114348: val_loss -0.7385 +2024-11-22 22:37:14.114507: Pseudo dice [0.8482] +2024-11-22 22:37:14.114590: Epoch time: 18.04 s +2024-11-22 22:37:15.145626: +2024-11-22 22:37:15.145823: Epoch 6581 +2024-11-22 22:37:15.145937: Current learning rate: 0.00211 +2024-11-22 22:37:33.629934: train_loss -0.8124 +2024-11-22 22:37:33.630140: val_loss -0.7507 +2024-11-22 22:37:33.630240: Pseudo dice [0.8602] +2024-11-22 22:37:33.630315: Epoch time: 18.49 s +2024-11-22 22:37:34.521581: +2024-11-22 22:37:34.521790: Epoch 6582 +2024-11-22 22:37:34.521902: Current learning rate: 0.00211 +2024-11-22 22:37:53.577001: train_loss -0.818 +2024-11-22 22:37:53.577250: val_loss -0.7571 +2024-11-22 22:37:53.577336: Pseudo dice [0.8483] +2024-11-22 22:37:53.577418: Epoch time: 19.06 s +2024-11-22 22:37:54.485899: +2024-11-22 22:37:54.486106: Epoch 6583 +2024-11-22 22:37:54.486215: Current learning rate: 0.00211 +2024-11-22 22:38:13.605421: train_loss -0.8156 +2024-11-22 22:38:13.605645: val_loss -0.7674 +2024-11-22 22:38:13.605723: Pseudo dice [0.8601] +2024-11-22 22:38:13.610956: Epoch time: 19.12 s +2024-11-22 22:38:14.769027: +2024-11-22 22:38:14.769247: Epoch 6584 +2024-11-22 22:38:14.769360: Current learning rate: 0.0021 +2024-11-22 22:38:33.450972: train_loss -0.8193 +2024-11-22 22:38:33.451188: val_loss -0.7258 +2024-11-22 22:38:33.451264: Pseudo dice [0.8249] +2024-11-22 22:38:33.451340: Epoch time: 18.68 s +2024-11-22 22:38:34.365451: +2024-11-22 22:38:34.365667: Epoch 6585 +2024-11-22 22:38:34.365782: Current learning rate: 0.0021 +2024-11-22 22:38:53.287743: train_loss -0.8157 +2024-11-22 22:38:53.287978: val_loss -0.771 +2024-11-22 22:38:53.288063: Pseudo dice [0.8682] +2024-11-22 22:38:53.288141: Epoch time: 18.92 s +2024-11-22 22:38:54.211421: +2024-11-22 22:38:54.211612: Epoch 6586 +2024-11-22 22:38:54.211720: Current learning rate: 0.0021 +2024-11-22 22:39:12.415369: train_loss -0.8187 +2024-11-22 22:39:12.415611: val_loss -0.7633 +2024-11-22 22:39:12.415685: Pseudo dice [0.8561] +2024-11-22 22:39:12.415769: Epoch time: 18.2 s +2024-11-22 22:39:13.332118: +2024-11-22 22:39:13.332325: Epoch 6587 +2024-11-22 22:39:13.332455: Current learning rate: 0.0021 +2024-11-22 22:39:32.068499: train_loss -0.8154 +2024-11-22 22:39:32.068719: val_loss -0.7189 +2024-11-22 22:39:32.068794: Pseudo dice [0.8363] +2024-11-22 22:39:32.074085: Epoch time: 18.74 s +2024-11-22 22:39:33.494763: +2024-11-22 22:39:33.495002: Epoch 6588 +2024-11-22 22:39:33.495113: Current learning rate: 0.0021 +2024-11-22 22:39:51.995911: train_loss -0.8188 +2024-11-22 22:39:51.996151: val_loss -0.7456 +2024-11-22 22:39:51.996226: Pseudo dice [0.8538] +2024-11-22 22:39:51.996303: Epoch time: 18.5 s +2024-11-22 22:39:52.937146: +2024-11-22 22:39:52.937357: Epoch 6589 +2024-11-22 22:39:52.937497: Current learning rate: 0.0021 +2024-11-22 22:40:11.811445: train_loss -0.8171 +2024-11-22 22:40:11.811657: val_loss -0.7714 +2024-11-22 22:40:11.811733: Pseudo dice [0.8542] +2024-11-22 22:40:11.811812: Epoch time: 18.88 s +2024-11-22 22:40:12.737728: +2024-11-22 22:40:12.737939: Epoch 6590 +2024-11-22 22:40:12.738057: Current learning rate: 0.0021 +2024-11-22 22:40:31.412819: train_loss -0.8144 +2024-11-22 22:40:31.413069: val_loss -0.7785 +2024-11-22 22:40:31.413146: Pseudo dice [0.8613] +2024-11-22 22:40:31.413225: Epoch time: 18.68 s +2024-11-22 22:40:32.441808: +2024-11-22 22:40:32.442040: Epoch 6591 +2024-11-22 22:40:32.442154: Current learning rate: 0.0021 +2024-11-22 22:40:51.262328: train_loss -0.8099 +2024-11-22 22:40:51.262541: val_loss -0.7394 +2024-11-22 22:40:51.262628: Pseudo dice [0.8624] +2024-11-22 22:40:51.267855: Epoch time: 18.82 s +2024-11-22 22:40:52.198115: +2024-11-22 22:40:52.198317: Epoch 6592 +2024-11-22 22:40:52.198427: Current learning rate: 0.00209 +2024-11-22 22:41:11.548537: train_loss -0.821 +2024-11-22 22:41:11.548757: val_loss -0.7689 +2024-11-22 22:41:11.548838: Pseudo dice [0.8524] +2024-11-22 22:41:11.548916: Epoch time: 19.35 s +2024-11-22 22:41:12.465843: +2024-11-22 22:41:12.466072: Epoch 6593 +2024-11-22 22:41:12.466182: Current learning rate: 0.00209 +2024-11-22 22:41:31.722317: train_loss -0.8187 +2024-11-22 22:41:31.723904: val_loss -0.7562 +2024-11-22 22:41:31.724005: Pseudo dice [0.8587] +2024-11-22 22:41:31.724086: Epoch time: 19.26 s +2024-11-22 22:41:32.663335: +2024-11-22 22:41:32.663592: Epoch 6594 +2024-11-22 22:41:32.663704: Current learning rate: 0.00209 +2024-11-22 22:41:51.117882: train_loss -0.8215 +2024-11-22 22:41:51.118128: val_loss -0.7592 +2024-11-22 22:41:51.123436: Pseudo dice [0.8521] +2024-11-22 22:41:51.123556: Epoch time: 18.46 s +2024-11-22 22:41:52.079222: +2024-11-22 22:41:52.079419: Epoch 6595 +2024-11-22 22:41:52.079526: Current learning rate: 0.00209 +2024-11-22 22:42:12.217104: train_loss -0.8141 +2024-11-22 22:42:12.217326: val_loss -0.7522 +2024-11-22 22:42:12.217403: Pseudo dice [0.8496] +2024-11-22 22:42:12.217482: Epoch time: 20.14 s +2024-11-22 22:42:13.178374: +2024-11-22 22:42:13.178589: Epoch 6596 +2024-11-22 22:42:13.178702: Current learning rate: 0.00209 +2024-11-22 22:42:31.680142: train_loss -0.8166 +2024-11-22 22:42:31.680370: val_loss -0.7454 +2024-11-22 22:42:31.680442: Pseudo dice [0.8284] +2024-11-22 22:42:31.680519: Epoch time: 18.5 s +2024-11-22 22:42:32.626596: +2024-11-22 22:42:32.626810: Epoch 6597 +2024-11-22 22:42:32.626921: Current learning rate: 0.00209 +2024-11-22 22:42:52.402440: train_loss -0.8115 +2024-11-22 22:42:52.402703: val_loss -0.7397 +2024-11-22 22:42:52.402778: Pseudo dice [0.8334] +2024-11-22 22:42:52.403438: Epoch time: 19.78 s +2024-11-22 22:42:53.321391: +2024-11-22 22:42:53.321588: Epoch 6598 +2024-11-22 22:42:53.321699: Current learning rate: 0.00209 +2024-11-22 22:43:12.190738: train_loss -0.8179 +2024-11-22 22:43:12.193176: val_loss -0.7382 +2024-11-22 22:43:12.193269: Pseudo dice [0.859] +2024-11-22 22:43:12.193355: Epoch time: 18.87 s +2024-11-22 22:43:13.560947: +2024-11-22 22:43:13.561225: Epoch 6599 +2024-11-22 22:43:13.561343: Current learning rate: 0.00208 +2024-11-22 22:43:31.945189: train_loss -0.8139 +2024-11-22 22:43:31.945443: val_loss -0.7515 +2024-11-22 22:43:31.945519: Pseudo dice [0.8279] +2024-11-22 22:43:31.945596: Epoch time: 18.39 s +2024-11-22 22:43:33.175449: +2024-11-22 22:43:33.175683: Epoch 6600 +2024-11-22 22:43:33.175797: Current learning rate: 0.00208 +2024-11-22 22:43:50.925109: train_loss -0.8244 +2024-11-22 22:43:50.925339: val_loss -0.7682 +2024-11-22 22:43:50.925411: Pseudo dice [0.8496] +2024-11-22 22:43:50.925487: Epoch time: 17.75 s +2024-11-22 22:43:51.837541: +2024-11-22 22:43:51.837750: Epoch 6601 +2024-11-22 22:43:51.837863: Current learning rate: 0.00208 +2024-11-22 22:44:09.327670: train_loss -0.8293 +2024-11-22 22:44:09.327931: val_loss -0.7477 +2024-11-22 22:44:09.328016: Pseudo dice [0.8576] +2024-11-22 22:44:09.328102: Epoch time: 17.49 s +2024-11-22 22:44:10.402697: +2024-11-22 22:44:10.402917: Epoch 6602 +2024-11-22 22:44:10.403037: Current learning rate: 0.00208 +2024-11-22 22:44:28.999519: train_loss -0.8181 +2024-11-22 22:44:28.999821: val_loss -0.744 +2024-11-22 22:44:28.999902: Pseudo dice [0.8322] +2024-11-22 22:44:28.999983: Epoch time: 18.6 s +2024-11-22 22:44:29.922953: +2024-11-22 22:44:29.923289: Epoch 6603 +2024-11-22 22:44:29.923403: Current learning rate: 0.00208 +2024-11-22 22:44:48.722495: train_loss -0.8134 +2024-11-22 22:44:48.722713: val_loss -0.756 +2024-11-22 22:44:48.722790: Pseudo dice [0.8557] +2024-11-22 22:44:48.722865: Epoch time: 18.8 s +2024-11-22 22:44:49.633713: +2024-11-22 22:44:49.633926: Epoch 6604 +2024-11-22 22:44:49.634047: Current learning rate: 0.00208 +2024-11-22 22:45:07.361681: train_loss -0.8179 +2024-11-22 22:45:07.361898: val_loss -0.756 +2024-11-22 22:45:07.361978: Pseudo dice [0.8516] +2024-11-22 22:45:07.362064: Epoch time: 17.73 s +2024-11-22 22:45:08.279225: +2024-11-22 22:45:08.279444: Epoch 6605 +2024-11-22 22:45:08.279558: Current learning rate: 0.00208 +2024-11-22 22:45:26.563322: train_loss -0.8213 +2024-11-22 22:45:26.563579: val_loss -0.7771 +2024-11-22 22:45:26.563654: Pseudo dice [0.8417] +2024-11-22 22:45:26.563740: Epoch time: 18.28 s +2024-11-22 22:45:27.479736: +2024-11-22 22:45:27.479958: Epoch 6606 +2024-11-22 22:45:27.480078: Current learning rate: 0.00208 +2024-11-22 22:45:46.192919: train_loss -0.8171 +2024-11-22 22:45:46.193153: val_loss -0.7499 +2024-11-22 22:45:46.193228: Pseudo dice [0.8359] +2024-11-22 22:45:46.193306: Epoch time: 18.71 s +2024-11-22 22:45:47.305584: +2024-11-22 22:45:47.305795: Epoch 6607 +2024-11-22 22:45:47.305909: Current learning rate: 0.00207 +2024-11-22 22:46:06.565125: train_loss -0.8111 +2024-11-22 22:46:06.565352: val_loss -0.7792 +2024-11-22 22:46:06.565427: Pseudo dice [0.8534] +2024-11-22 22:46:06.565504: Epoch time: 19.26 s +2024-11-22 22:46:07.479260: +2024-11-22 22:46:07.479599: Epoch 6608 +2024-11-22 22:46:07.479712: Current learning rate: 0.00207 +2024-11-22 22:46:25.416550: train_loss -0.8215 +2024-11-22 22:46:25.418952: val_loss -0.7365 +2024-11-22 22:46:25.419102: Pseudo dice [0.8449] +2024-11-22 22:46:25.419187: Epoch time: 17.94 s +2024-11-22 22:46:26.384628: +2024-11-22 22:46:26.384836: Epoch 6609 +2024-11-22 22:46:26.384945: Current learning rate: 0.00207 +2024-11-22 22:46:45.066563: train_loss -0.8169 +2024-11-22 22:46:45.066869: val_loss -0.7552 +2024-11-22 22:46:45.066946: Pseudo dice [0.8321] +2024-11-22 22:46:45.067034: Epoch time: 18.68 s +2024-11-22 22:46:46.000078: +2024-11-22 22:46:46.000277: Epoch 6610 +2024-11-22 22:46:46.000393: Current learning rate: 0.00207 +2024-11-22 22:47:05.187752: train_loss -0.8159 +2024-11-22 22:47:05.188029: val_loss -0.7493 +2024-11-22 22:47:05.193321: Pseudo dice [0.8524] +2024-11-22 22:47:05.193448: Epoch time: 19.19 s +2024-11-22 22:47:06.258422: +2024-11-22 22:47:06.258730: Epoch 6611 +2024-11-22 22:47:06.258850: Current learning rate: 0.00207 +2024-11-22 22:47:25.547516: train_loss -0.8117 +2024-11-22 22:47:25.547741: val_loss -0.7379 +2024-11-22 22:47:25.547818: Pseudo dice [0.8478] +2024-11-22 22:47:25.547897: Epoch time: 19.29 s +2024-11-22 22:47:26.570005: +2024-11-22 22:47:26.570304: Epoch 6612 +2024-11-22 22:47:26.570416: Current learning rate: 0.00207 +2024-11-22 22:47:45.415874: train_loss -0.8114 +2024-11-22 22:47:45.416098: val_loss -0.7528 +2024-11-22 22:47:45.416172: Pseudo dice [0.8456] +2024-11-22 22:47:45.416251: Epoch time: 18.85 s +2024-11-22 22:47:46.333403: +2024-11-22 22:47:46.333678: Epoch 6613 +2024-11-22 22:47:46.333839: Current learning rate: 0.00207 +2024-11-22 22:48:05.673296: train_loss -0.8168 +2024-11-22 22:48:05.673529: val_loss -0.7575 +2024-11-22 22:48:05.673603: Pseudo dice [0.8351] +2024-11-22 22:48:05.673682: Epoch time: 19.34 s +2024-11-22 22:48:06.588844: +2024-11-22 22:48:06.589066: Epoch 6614 +2024-11-22 22:48:06.589179: Current learning rate: 0.00206 +2024-11-22 22:48:25.284015: train_loss -0.8126 +2024-11-22 22:48:25.284240: val_loss -0.7331 +2024-11-22 22:48:25.284314: Pseudo dice [0.8286] +2024-11-22 22:48:25.284391: Epoch time: 18.7 s +2024-11-22 22:48:26.359493: +2024-11-22 22:48:26.359756: Epoch 6615 +2024-11-22 22:48:26.359871: Current learning rate: 0.00206 +2024-11-22 22:48:45.944474: train_loss -0.8161 +2024-11-22 22:48:45.944763: val_loss -0.7533 +2024-11-22 22:48:45.944850: Pseudo dice [0.8499] +2024-11-22 22:48:45.944928: Epoch time: 19.59 s +2024-11-22 22:48:46.962236: +2024-11-22 22:48:46.962463: Epoch 6616 +2024-11-22 22:48:46.962578: Current learning rate: 0.00206 +2024-11-22 22:49:05.026610: train_loss -0.8149 +2024-11-22 22:49:05.026836: val_loss -0.7617 +2024-11-22 22:49:05.026910: Pseudo dice [0.868] +2024-11-22 22:49:05.027007: Epoch time: 18.07 s +2024-11-22 22:49:05.944878: +2024-11-22 22:49:05.945099: Epoch 6617 +2024-11-22 22:49:05.945214: Current learning rate: 0.00206 +2024-11-22 22:49:24.713457: train_loss -0.8192 +2024-11-22 22:49:24.713733: val_loss -0.7246 +2024-11-22 22:49:24.713821: Pseudo dice [0.8554] +2024-11-22 22:49:24.713902: Epoch time: 18.77 s +2024-11-22 22:49:25.631295: +2024-11-22 22:49:25.631529: Epoch 6618 +2024-11-22 22:49:25.631642: Current learning rate: 0.00206 +2024-11-22 22:49:43.698924: train_loss -0.8182 +2024-11-22 22:49:43.699151: val_loss -0.7541 +2024-11-22 22:49:43.699227: Pseudo dice [0.854] +2024-11-22 22:49:43.699304: Epoch time: 18.07 s +2024-11-22 22:49:44.642813: +2024-11-22 22:49:44.643021: Epoch 6619 +2024-11-22 22:49:44.643132: Current learning rate: 0.00206 +2024-11-22 22:50:03.163716: train_loss -0.8177 +2024-11-22 22:50:03.163955: val_loss -0.7427 +2024-11-22 22:50:03.166225: Pseudo dice [0.8552] +2024-11-22 22:50:03.166320: Epoch time: 18.52 s +2024-11-22 22:50:04.219299: +2024-11-22 22:50:04.219509: Epoch 6620 +2024-11-22 22:50:04.219622: Current learning rate: 0.00206 +2024-11-22 22:50:22.350751: train_loss -0.8129 +2024-11-22 22:50:22.350969: val_loss -0.7539 +2024-11-22 22:50:22.351050: Pseudo dice [0.8701] +2024-11-22 22:50:22.351130: Epoch time: 18.13 s +2024-11-22 22:50:23.265451: +2024-11-22 22:50:23.265651: Epoch 6621 +2024-11-22 22:50:23.265762: Current learning rate: 0.00206 +2024-11-22 22:50:43.101751: train_loss -0.8177 +2024-11-22 22:50:43.102009: val_loss -0.7646 +2024-11-22 22:50:43.102086: Pseudo dice [0.8469] +2024-11-22 22:50:43.102162: Epoch time: 19.84 s +2024-11-22 22:50:44.011430: +2024-11-22 22:50:44.011672: Epoch 6622 +2024-11-22 22:50:44.011788: Current learning rate: 0.00205 +2024-11-22 22:51:03.422256: train_loss -0.8222 +2024-11-22 22:51:03.422499: val_loss -0.7639 +2024-11-22 22:51:03.422574: Pseudo dice [0.8575] +2024-11-22 22:51:03.422649: Epoch time: 19.41 s +2024-11-22 22:51:04.345033: +2024-11-22 22:51:04.345264: Epoch 6623 +2024-11-22 22:51:04.345384: Current learning rate: 0.00205 +2024-11-22 22:51:22.145203: train_loss -0.8155 +2024-11-22 22:51:22.145447: val_loss -0.7692 +2024-11-22 22:51:22.145602: Pseudo dice [0.8654] +2024-11-22 22:51:22.145685: Epoch time: 17.8 s +2024-11-22 22:51:23.067265: +2024-11-22 22:51:23.067490: Epoch 6624 +2024-11-22 22:51:23.067606: Current learning rate: 0.00205 +2024-11-22 22:51:42.622772: train_loss -0.8251 +2024-11-22 22:51:42.623090: val_loss -0.7322 +2024-11-22 22:51:42.623169: Pseudo dice [0.8383] +2024-11-22 22:51:42.623250: Epoch time: 19.56 s +2024-11-22 22:51:43.541975: +2024-11-22 22:51:43.542196: Epoch 6625 +2024-11-22 22:51:43.542313: Current learning rate: 0.00205 +2024-11-22 22:52:03.845723: train_loss -0.8165 +2024-11-22 22:52:03.845978: val_loss -0.7496 +2024-11-22 22:52:03.846111: Pseudo dice [0.8518] +2024-11-22 22:52:03.846205: Epoch time: 20.3 s +2024-11-22 22:52:04.767146: +2024-11-22 22:52:04.767372: Epoch 6626 +2024-11-22 22:52:04.767478: Current learning rate: 0.00205 +2024-11-22 22:52:23.591948: train_loss -0.8139 +2024-11-22 22:52:23.592195: val_loss -0.7576 +2024-11-22 22:52:23.592271: Pseudo dice [0.8249] +2024-11-22 22:52:23.592348: Epoch time: 18.83 s +2024-11-22 22:52:24.689354: +2024-11-22 22:52:24.689551: Epoch 6627 +2024-11-22 22:52:24.689689: Current learning rate: 0.00205 +2024-11-22 22:52:43.928665: train_loss -0.8189 +2024-11-22 22:52:43.931100: val_loss -0.7502 +2024-11-22 22:52:43.931215: Pseudo dice [0.8358] +2024-11-22 22:52:43.931297: Epoch time: 19.24 s +2024-11-22 22:52:44.955612: +2024-11-22 22:52:44.955800: Epoch 6628 +2024-11-22 22:52:44.955923: Current learning rate: 0.00205 +2024-11-22 22:53:03.952642: train_loss -0.8125 +2024-11-22 22:53:03.952931: val_loss -0.7388 +2024-11-22 22:53:03.953036: Pseudo dice [0.8431] +2024-11-22 22:53:03.953120: Epoch time: 19.0 s +2024-11-22 22:53:04.870039: +2024-11-22 22:53:04.870230: Epoch 6629 +2024-11-22 22:53:04.870338: Current learning rate: 0.00204 +2024-11-22 22:53:24.303196: train_loss -0.8163 +2024-11-22 22:53:24.303493: val_loss -0.7261 +2024-11-22 22:53:24.303573: Pseudo dice [0.8291] +2024-11-22 22:53:24.303652: Epoch time: 19.43 s +2024-11-22 22:53:25.216014: +2024-11-22 22:53:25.216295: Epoch 6630 +2024-11-22 22:53:25.216410: Current learning rate: 0.00204 +2024-11-22 22:53:43.504031: train_loss -0.8185 +2024-11-22 22:53:43.504267: val_loss -0.7722 +2024-11-22 22:53:43.509550: Pseudo dice [0.8207] +2024-11-22 22:53:43.509685: Epoch time: 18.29 s +2024-11-22 22:53:44.457926: +2024-11-22 22:53:44.458154: Epoch 6631 +2024-11-22 22:53:44.458269: Current learning rate: 0.00204 +2024-11-22 22:54:03.214806: train_loss -0.8117 +2024-11-22 22:54:03.215025: val_loss -0.7345 +2024-11-22 22:54:03.217282: Pseudo dice [0.8601] +2024-11-22 22:54:03.217382: Epoch time: 18.76 s +2024-11-22 22:54:04.296182: +2024-11-22 22:54:04.296374: Epoch 6632 +2024-11-22 22:54:04.296483: Current learning rate: 0.00204 +2024-11-22 22:54:23.398841: train_loss -0.8142 +2024-11-22 22:54:23.399168: val_loss -0.7682 +2024-11-22 22:54:23.399256: Pseudo dice [0.8267] +2024-11-22 22:54:23.399337: Epoch time: 19.1 s +2024-11-22 22:54:24.306336: +2024-11-22 22:54:24.306695: Epoch 6633 +2024-11-22 22:54:24.306813: Current learning rate: 0.00204 +2024-11-22 22:54:44.180457: train_loss -0.8111 +2024-11-22 22:54:44.182885: val_loss -0.7252 +2024-11-22 22:54:44.182976: Pseudo dice [0.8362] +2024-11-22 22:54:44.183064: Epoch time: 19.87 s +2024-11-22 22:54:45.226717: +2024-11-22 22:54:45.226944: Epoch 6634 +2024-11-22 22:54:45.227059: Current learning rate: 0.00204 +2024-11-22 22:55:03.610583: train_loss -0.8208 +2024-11-22 22:55:03.610839: val_loss -0.7412 +2024-11-22 22:55:03.610915: Pseudo dice [0.8492] +2024-11-22 22:55:03.611030: Epoch time: 18.38 s +2024-11-22 22:55:04.525588: +2024-11-22 22:55:04.525821: Epoch 6635 +2024-11-22 22:55:04.525932: Current learning rate: 0.00204 +2024-11-22 22:55:22.541867: train_loss -0.8124 +2024-11-22 22:55:22.542158: val_loss -0.7295 +2024-11-22 22:55:22.542263: Pseudo dice [0.8523] +2024-11-22 22:55:22.542351: Epoch time: 18.02 s +2024-11-22 22:55:23.454231: +2024-11-22 22:55:23.454430: Epoch 6636 +2024-11-22 22:55:23.454546: Current learning rate: 0.00203 +2024-11-22 22:55:41.753241: train_loss -0.8175 +2024-11-22 22:55:41.753536: val_loss -0.7308 +2024-11-22 22:55:41.753618: Pseudo dice [0.8544] +2024-11-22 22:55:41.753730: Epoch time: 18.3 s +2024-11-22 22:55:42.671546: +2024-11-22 22:55:42.671761: Epoch 6637 +2024-11-22 22:55:42.671881: Current learning rate: 0.00203 +2024-11-22 22:56:00.765131: train_loss -0.8206 +2024-11-22 22:56:00.765378: val_loss -0.7515 +2024-11-22 22:56:00.765454: Pseudo dice [0.8565] +2024-11-22 22:56:00.765532: Epoch time: 18.09 s +2024-11-22 22:56:01.680328: +2024-11-22 22:56:01.680531: Epoch 6638 +2024-11-22 22:56:01.680643: Current learning rate: 0.00203 +2024-11-22 22:56:20.376024: train_loss -0.817 +2024-11-22 22:56:20.376259: val_loss -0.7522 +2024-11-22 22:56:20.376337: Pseudo dice [0.8418] +2024-11-22 22:56:20.376416: Epoch time: 18.7 s +2024-11-22 22:56:21.313342: +2024-11-22 22:56:21.313544: Epoch 6639 +2024-11-22 22:56:21.313654: Current learning rate: 0.00203 +2024-11-22 22:56:40.332929: train_loss -0.8221 +2024-11-22 22:56:40.333192: val_loss -0.7468 +2024-11-22 22:56:40.333306: Pseudo dice [0.838] +2024-11-22 22:56:40.333393: Epoch time: 19.02 s +2024-11-22 22:56:41.250802: +2024-11-22 22:56:41.251024: Epoch 6640 +2024-11-22 22:56:41.251138: Current learning rate: 0.00203 +2024-11-22 22:56:59.958020: train_loss -0.8231 +2024-11-22 22:56:59.958241: val_loss -0.766 +2024-11-22 22:56:59.958316: Pseudo dice [0.8545] +2024-11-22 22:56:59.958391: Epoch time: 18.71 s +2024-11-22 22:57:00.906810: +2024-11-22 22:57:00.907034: Epoch 6641 +2024-11-22 22:57:00.907149: Current learning rate: 0.00203 +2024-11-22 22:57:20.509514: train_loss -0.817 +2024-11-22 22:57:20.509736: val_loss -0.7377 +2024-11-22 22:57:20.509813: Pseudo dice [0.8574] +2024-11-22 22:57:20.509891: Epoch time: 19.6 s +2024-11-22 22:57:21.450878: +2024-11-22 22:57:21.451074: Epoch 6642 +2024-11-22 22:57:21.451195: Current learning rate: 0.00203 +2024-11-22 22:57:41.101729: train_loss -0.8154 +2024-11-22 22:57:41.101944: val_loss -0.7142 +2024-11-22 22:57:41.102024: Pseudo dice [0.8324] +2024-11-22 22:57:41.102099: Epoch time: 19.65 s +2024-11-22 22:57:42.027909: +2024-11-22 22:57:42.028113: Epoch 6643 +2024-11-22 22:57:42.028230: Current learning rate: 0.00203 +2024-11-22 22:58:00.936706: train_loss -0.8147 +2024-11-22 22:58:00.936985: val_loss -0.746 +2024-11-22 22:58:00.937071: Pseudo dice [0.8433] +2024-11-22 22:58:00.937149: Epoch time: 18.91 s +2024-11-22 22:58:01.852245: +2024-11-22 22:58:01.852501: Epoch 6644 +2024-11-22 22:58:01.852622: Current learning rate: 0.00202 +2024-11-22 22:58:20.240236: train_loss -0.8208 +2024-11-22 22:58:20.240502: val_loss -0.7511 +2024-11-22 22:58:20.240577: Pseudo dice [0.8446] +2024-11-22 22:58:20.240657: Epoch time: 18.39 s +2024-11-22 22:58:21.339930: +2024-11-22 22:58:21.340158: Epoch 6645 +2024-11-22 22:58:21.340270: Current learning rate: 0.00202 +2024-11-22 22:58:41.370177: train_loss -0.8139 +2024-11-22 22:58:41.370433: val_loss -0.7587 +2024-11-22 22:58:41.370508: Pseudo dice [0.8535] +2024-11-22 22:58:41.370585: Epoch time: 20.03 s +2024-11-22 22:58:42.287818: +2024-11-22 22:58:42.288028: Epoch 6646 +2024-11-22 22:58:42.288140: Current learning rate: 0.00202 +2024-11-22 22:59:00.581404: train_loss -0.8191 +2024-11-22 22:59:00.581665: val_loss -0.7207 +2024-11-22 22:59:00.581745: Pseudo dice [0.8413] +2024-11-22 22:59:00.581836: Epoch time: 18.29 s +2024-11-22 22:59:01.593223: +2024-11-22 22:59:01.593413: Epoch 6647 +2024-11-22 22:59:01.593525: Current learning rate: 0.00202 +2024-11-22 22:59:19.345471: train_loss -0.8147 +2024-11-22 22:59:19.345709: val_loss -0.7513 +2024-11-22 22:59:19.345783: Pseudo dice [0.847] +2024-11-22 22:59:19.345861: Epoch time: 17.75 s +2024-11-22 22:59:20.253780: +2024-11-22 22:59:20.254006: Epoch 6648 +2024-11-22 22:59:20.254124: Current learning rate: 0.00202 +2024-11-22 22:59:38.045450: train_loss -0.8241 +2024-11-22 22:59:38.045677: val_loss -0.7671 +2024-11-22 22:59:38.045754: Pseudo dice [0.871] +2024-11-22 22:59:38.045832: Epoch time: 17.79 s +2024-11-22 22:59:38.970128: +2024-11-22 22:59:38.970345: Epoch 6649 +2024-11-22 22:59:38.970458: Current learning rate: 0.00202 +2024-11-22 22:59:57.912573: train_loss -0.8235 +2024-11-22 22:59:57.912817: val_loss -0.7634 +2024-11-22 22:59:57.913049: Pseudo dice [0.854] +2024-11-22 22:59:57.913131: Epoch time: 18.94 s +2024-11-22 22:59:59.158919: +2024-11-22 22:59:59.159130: Epoch 6650 +2024-11-22 22:59:59.159244: Current learning rate: 0.00202 +2024-11-22 23:00:17.679456: train_loss -0.8229 +2024-11-22 23:00:17.679706: val_loss -0.7893 +2024-11-22 23:00:17.679783: Pseudo dice [0.8522] +2024-11-22 23:00:17.679868: Epoch time: 18.52 s +2024-11-22 23:00:18.597823: +2024-11-22 23:00:18.598032: Epoch 6651 +2024-11-22 23:00:18.598145: Current learning rate: 0.00201 +2024-11-22 23:00:37.540678: train_loss -0.8093 +2024-11-22 23:00:37.540906: val_loss -0.7468 +2024-11-22 23:00:37.540984: Pseudo dice [0.8497] +2024-11-22 23:00:37.541069: Epoch time: 18.94 s +2024-11-22 23:00:38.454591: +2024-11-22 23:00:38.454788: Epoch 6652 +2024-11-22 23:00:38.454900: Current learning rate: 0.00201 +2024-11-22 23:00:57.101393: train_loss -0.8169 +2024-11-22 23:00:57.101619: val_loss -0.772 +2024-11-22 23:00:57.101694: Pseudo dice [0.8537] +2024-11-22 23:00:57.101773: Epoch time: 18.65 s +2024-11-22 23:00:58.021894: +2024-11-22 23:00:58.022120: Epoch 6653 +2024-11-22 23:00:58.022231: Current learning rate: 0.00201 +2024-11-22 23:01:17.305798: train_loss -0.8163 +2024-11-22 23:01:17.306028: val_loss -0.7614 +2024-11-22 23:01:17.306106: Pseudo dice [0.8492] +2024-11-22 23:01:17.306187: Epoch time: 19.28 s +2024-11-22 23:01:18.590486: +2024-11-22 23:01:18.590686: Epoch 6654 +2024-11-22 23:01:18.590800: Current learning rate: 0.00201 +2024-11-22 23:01:37.758100: train_loss -0.8104 +2024-11-22 23:01:37.758419: val_loss -0.7473 +2024-11-22 23:01:37.758498: Pseudo dice [0.8517] +2024-11-22 23:01:37.758583: Epoch time: 19.16 s +2024-11-22 23:01:38.850499: +2024-11-22 23:01:38.850753: Epoch 6655 +2024-11-22 23:01:38.850865: Current learning rate: 0.00201 +2024-11-22 23:01:57.696401: train_loss -0.8192 +2024-11-22 23:01:57.696627: val_loss -0.7699 +2024-11-22 23:01:57.696703: Pseudo dice [0.8429] +2024-11-22 23:01:57.696782: Epoch time: 18.85 s +2024-11-22 23:01:58.718895: +2024-11-22 23:01:58.719137: Epoch 6656 +2024-11-22 23:01:58.719265: Current learning rate: 0.00201 +2024-11-22 23:02:17.713921: train_loss -0.8217 +2024-11-22 23:02:17.714152: val_loss -0.7261 +2024-11-22 23:02:17.714229: Pseudo dice [0.8403] +2024-11-22 23:02:17.714308: Epoch time: 19.0 s +2024-11-22 23:02:18.650096: +2024-11-22 23:02:18.650330: Epoch 6657 +2024-11-22 23:02:18.650444: Current learning rate: 0.00201 +2024-11-22 23:02:37.542694: train_loss -0.8224 +2024-11-22 23:02:37.542921: val_loss -0.7848 +2024-11-22 23:02:37.543002: Pseudo dice [0.8504] +2024-11-22 23:02:37.543085: Epoch time: 18.89 s +2024-11-22 23:02:38.459347: +2024-11-22 23:02:38.459585: Epoch 6658 +2024-11-22 23:02:38.459717: Current learning rate: 0.00201 +2024-11-22 23:02:57.323894: train_loss -0.8129 +2024-11-22 23:02:57.324127: val_loss -0.7497 +2024-11-22 23:02:57.324201: Pseudo dice [0.8369] +2024-11-22 23:02:57.324278: Epoch time: 18.87 s +2024-11-22 23:02:58.247317: +2024-11-22 23:02:58.247526: Epoch 6659 +2024-11-22 23:02:58.247637: Current learning rate: 0.002 +2024-11-22 23:03:17.937117: train_loss -0.8107 +2024-11-22 23:03:17.937348: val_loss -0.7512 +2024-11-22 23:03:17.937424: Pseudo dice [0.8492] +2024-11-22 23:03:17.937533: Epoch time: 19.69 s +2024-11-22 23:03:18.872175: +2024-11-22 23:03:18.872375: Epoch 6660 +2024-11-22 23:03:18.872482: Current learning rate: 0.002 +2024-11-22 23:03:37.307372: train_loss -0.8115 +2024-11-22 23:03:37.307590: val_loss -0.7541 +2024-11-22 23:03:37.307667: Pseudo dice [0.8571] +2024-11-22 23:03:37.307742: Epoch time: 18.44 s +2024-11-22 23:03:38.223119: +2024-11-22 23:03:38.223356: Epoch 6661 +2024-11-22 23:03:38.223470: Current learning rate: 0.002 +2024-11-22 23:03:57.145221: train_loss -0.8173 +2024-11-22 23:03:57.145486: val_loss -0.7714 +2024-11-22 23:03:57.145560: Pseudo dice [0.8463] +2024-11-22 23:03:57.145646: Epoch time: 18.92 s +2024-11-22 23:03:58.064203: +2024-11-22 23:03:58.064405: Epoch 6662 +2024-11-22 23:03:58.064517: Current learning rate: 0.002 +2024-11-22 23:04:16.194379: train_loss -0.8232 +2024-11-22 23:04:16.194579: val_loss -0.7482 +2024-11-22 23:04:16.194652: Pseudo dice [0.8259] +2024-11-22 23:04:16.194728: Epoch time: 18.13 s +2024-11-22 23:04:17.114486: +2024-11-22 23:04:17.114684: Epoch 6663 +2024-11-22 23:04:17.114795: Current learning rate: 0.002 +2024-11-22 23:04:36.921496: train_loss -0.8167 +2024-11-22 23:04:36.921727: val_loss -0.7412 +2024-11-22 23:04:36.921802: Pseudo dice [0.843] +2024-11-22 23:04:36.921879: Epoch time: 19.81 s +2024-11-22 23:04:37.855077: +2024-11-22 23:04:37.855273: Epoch 6664 +2024-11-22 23:04:37.855387: Current learning rate: 0.002 +2024-11-22 23:04:55.311987: train_loss -0.8145 +2024-11-22 23:04:55.312220: val_loss -0.7625 +2024-11-22 23:04:55.312295: Pseudo dice [0.8411] +2024-11-22 23:04:55.312379: Epoch time: 17.46 s +2024-11-22 23:04:56.233212: +2024-11-22 23:04:56.233406: Epoch 6665 +2024-11-22 23:04:56.233519: Current learning rate: 0.002 +2024-11-22 23:05:15.897845: train_loss -0.8165 +2024-11-22 23:05:15.898101: val_loss -0.744 +2024-11-22 23:05:15.898175: Pseudo dice [0.854] +2024-11-22 23:05:15.898255: Epoch time: 19.67 s +2024-11-22 23:05:17.191975: +2024-11-22 23:05:17.192194: Epoch 6666 +2024-11-22 23:05:17.192303: Current learning rate: 0.00199 +2024-11-22 23:05:35.639441: train_loss -0.8177 +2024-11-22 23:05:35.639683: val_loss -0.7549 +2024-11-22 23:05:35.639761: Pseudo dice [0.8626] +2024-11-22 23:05:35.639841: Epoch time: 18.45 s +2024-11-22 23:05:36.566537: +2024-11-22 23:05:36.566753: Epoch 6667 +2024-11-22 23:05:36.566867: Current learning rate: 0.00199 +2024-11-22 23:05:55.397291: train_loss -0.8188 +2024-11-22 23:05:55.397587: val_loss -0.7277 +2024-11-22 23:05:55.397669: Pseudo dice [0.8478] +2024-11-22 23:05:55.397753: Epoch time: 18.83 s +2024-11-22 23:05:56.324612: +2024-11-22 23:05:56.324837: Epoch 6668 +2024-11-22 23:05:56.324947: Current learning rate: 0.00199 +2024-11-22 23:06:14.122813: train_loss -0.8148 +2024-11-22 23:06:14.123087: val_loss -0.76 +2024-11-22 23:06:14.123164: Pseudo dice [0.8602] +2024-11-22 23:06:14.123245: Epoch time: 17.8 s +2024-11-22 23:06:15.049828: +2024-11-22 23:06:15.050032: Epoch 6669 +2024-11-22 23:06:15.050148: Current learning rate: 0.00199 +2024-11-22 23:06:33.068510: train_loss -0.8157 +2024-11-22 23:06:33.068745: val_loss -0.7392 +2024-11-22 23:06:33.068822: Pseudo dice [0.8702] +2024-11-22 23:06:33.068901: Epoch time: 18.02 s +2024-11-22 23:06:33.996716: +2024-11-22 23:06:33.996996: Epoch 6670 +2024-11-22 23:06:33.997108: Current learning rate: 0.00199 +2024-11-22 23:06:53.559146: train_loss -0.8135 +2024-11-22 23:06:53.559387: val_loss -0.7422 +2024-11-22 23:06:53.559463: Pseudo dice [0.8405] +2024-11-22 23:06:53.559540: Epoch time: 19.56 s +2024-11-22 23:06:54.494786: +2024-11-22 23:06:54.495000: Epoch 6671 +2024-11-22 23:06:54.495112: Current learning rate: 0.00199 +2024-11-22 23:07:13.959757: train_loss -0.809 +2024-11-22 23:07:13.959986: val_loss -0.7609 +2024-11-22 23:07:13.960144: Pseudo dice [0.8673] +2024-11-22 23:07:13.960250: Epoch time: 19.47 s +2024-11-22 23:07:14.885295: +2024-11-22 23:07:14.885500: Epoch 6672 +2024-11-22 23:07:14.885610: Current learning rate: 0.00199 +2024-11-22 23:07:33.206209: train_loss -0.8267 +2024-11-22 23:07:33.206470: val_loss -0.7551 +2024-11-22 23:07:33.206548: Pseudo dice [0.8521] +2024-11-22 23:07:33.206862: Epoch time: 18.32 s +2024-11-22 23:07:34.170004: +2024-11-22 23:07:34.170195: Epoch 6673 +2024-11-22 23:07:34.170302: Current learning rate: 0.00199 +2024-11-22 23:07:53.137729: train_loss -0.8142 +2024-11-22 23:07:53.137952: val_loss -0.7383 +2024-11-22 23:07:53.138032: Pseudo dice [0.8471] +2024-11-22 23:07:53.138108: Epoch time: 18.97 s +2024-11-22 23:07:54.063029: +2024-11-22 23:07:54.063270: Epoch 6674 +2024-11-22 23:07:54.063380: Current learning rate: 0.00198 +2024-11-22 23:08:11.913312: train_loss -0.8158 +2024-11-22 23:08:11.913531: val_loss -0.7709 +2024-11-22 23:08:11.913602: Pseudo dice [0.87] +2024-11-22 23:08:11.913684: Epoch time: 17.85 s +2024-11-22 23:08:12.885850: +2024-11-22 23:08:12.886052: Epoch 6675 +2024-11-22 23:08:12.886163: Current learning rate: 0.00198 +2024-11-22 23:08:30.919085: train_loss -0.8092 +2024-11-22 23:08:30.919304: val_loss -0.7824 +2024-11-22 23:08:30.920096: Pseudo dice [0.8552] +2024-11-22 23:08:30.920219: Epoch time: 18.03 s +2024-11-22 23:08:31.846528: +2024-11-22 23:08:31.846730: Epoch 6676 +2024-11-22 23:08:31.846839: Current learning rate: 0.00198 +2024-11-22 23:08:52.107973: train_loss -0.8162 +2024-11-22 23:08:52.108751: val_loss -0.7625 +2024-11-22 23:08:52.108829: Pseudo dice [0.8738] +2024-11-22 23:08:52.108912: Epoch time: 20.26 s +2024-11-22 23:08:53.474408: +2024-11-22 23:08:53.474705: Epoch 6677 +2024-11-22 23:08:53.474814: Current learning rate: 0.00198 +2024-11-22 23:09:11.804972: train_loss -0.8196 +2024-11-22 23:09:11.805207: val_loss -0.7816 +2024-11-22 23:09:11.805284: Pseudo dice [0.8704] +2024-11-22 23:09:11.805362: Epoch time: 18.33 s +2024-11-22 23:09:11.805422: Yayy! New best EMA pseudo Dice: 0.857 +2024-11-22 23:09:13.053612: +2024-11-22 23:09:13.053843: Epoch 6678 +2024-11-22 23:09:13.053955: Current learning rate: 0.00198 +2024-11-22 23:09:32.123716: train_loss -0.8132 +2024-11-22 23:09:32.123934: val_loss -0.7439 +2024-11-22 23:09:32.124015: Pseudo dice [0.8473] +2024-11-22 23:09:32.124091: Epoch time: 19.07 s +2024-11-22 23:09:33.115821: +2024-11-22 23:09:33.116056: Epoch 6679 +2024-11-22 23:09:33.116170: Current learning rate: 0.00198 +2024-11-22 23:09:50.913569: train_loss -0.8222 +2024-11-22 23:09:50.916034: val_loss -0.7278 +2024-11-22 23:09:50.916139: Pseudo dice [0.8604] +2024-11-22 23:09:50.916234: Epoch time: 17.8 s +2024-11-22 23:09:51.848185: +2024-11-22 23:09:51.848432: Epoch 6680 +2024-11-22 23:09:51.848560: Current learning rate: 0.00198 +2024-11-22 23:10:10.970955: train_loss -0.816 +2024-11-22 23:10:10.971188: val_loss -0.771 +2024-11-22 23:10:10.971262: Pseudo dice [0.8406] +2024-11-22 23:10:10.971339: Epoch time: 19.12 s +2024-11-22 23:10:11.947954: +2024-11-22 23:10:11.948160: Epoch 6681 +2024-11-22 23:10:11.948282: Current learning rate: 0.00197 +2024-11-22 23:10:30.628532: train_loss -0.8196 +2024-11-22 23:10:30.628764: val_loss -0.76 +2024-11-22 23:10:30.628845: Pseudo dice [0.845] +2024-11-22 23:10:30.628928: Epoch time: 18.68 s +2024-11-22 23:10:31.579097: +2024-11-22 23:10:31.579305: Epoch 6682 +2024-11-22 23:10:31.579420: Current learning rate: 0.00197 +2024-11-22 23:10:49.676810: train_loss -0.8105 +2024-11-22 23:10:49.677034: val_loss -0.7495 +2024-11-22 23:10:49.677114: Pseudo dice [0.8539] +2024-11-22 23:10:49.677192: Epoch time: 18.1 s +2024-11-22 23:10:50.643622: +2024-11-22 23:10:50.643824: Epoch 6683 +2024-11-22 23:10:50.643938: Current learning rate: 0.00197 +2024-11-22 23:11:09.921196: train_loss -0.8065 +2024-11-22 23:11:09.921453: val_loss -0.7628 +2024-11-22 23:11:09.921531: Pseudo dice [0.8536] +2024-11-22 23:11:09.921618: Epoch time: 19.28 s +2024-11-22 23:11:10.874568: +2024-11-22 23:11:10.874789: Epoch 6684 +2024-11-22 23:11:10.874901: Current learning rate: 0.00197 +2024-11-22 23:11:29.291644: train_loss -0.8169 +2024-11-22 23:11:29.291874: val_loss -0.7546 +2024-11-22 23:11:29.291952: Pseudo dice [0.8584] +2024-11-22 23:11:29.292038: Epoch time: 18.42 s +2024-11-22 23:11:30.218285: +2024-11-22 23:11:30.218542: Epoch 6685 +2024-11-22 23:11:30.218651: Current learning rate: 0.00197 +2024-11-22 23:11:49.326658: train_loss -0.8159 +2024-11-22 23:11:49.332088: val_loss -0.7644 +2024-11-22 23:11:49.332233: Pseudo dice [0.856] +2024-11-22 23:11:49.332321: Epoch time: 19.11 s +2024-11-22 23:11:50.312378: +2024-11-22 23:11:50.312582: Epoch 6686 +2024-11-22 23:11:50.312692: Current learning rate: 0.00197 +2024-11-22 23:12:08.784970: train_loss -0.8195 +2024-11-22 23:12:08.785694: val_loss -0.7756 +2024-11-22 23:12:08.785784: Pseudo dice [0.8508] +2024-11-22 23:12:08.785864: Epoch time: 18.47 s +2024-11-22 23:12:09.731651: +2024-11-22 23:12:09.731872: Epoch 6687 +2024-11-22 23:12:09.732004: Current learning rate: 0.00197 +2024-11-22 23:12:29.767138: train_loss -0.806 +2024-11-22 23:12:29.767469: val_loss -0.7625 +2024-11-22 23:12:29.767552: Pseudo dice [0.8564] +2024-11-22 23:12:29.767633: Epoch time: 20.04 s +2024-11-22 23:12:31.091319: +2024-11-22 23:12:31.091549: Epoch 6688 +2024-11-22 23:12:31.091663: Current learning rate: 0.00196 +2024-11-22 23:12:50.440729: train_loss -0.8181 +2024-11-22 23:12:50.440964: val_loss -0.7584 +2024-11-22 23:12:50.441048: Pseudo dice [0.8587] +2024-11-22 23:12:50.441126: Epoch time: 19.35 s +2024-11-22 23:12:51.357495: +2024-11-22 23:12:51.357714: Epoch 6689 +2024-11-22 23:12:51.357827: Current learning rate: 0.00196 +2024-11-22 23:13:09.967656: train_loss -0.8171 +2024-11-22 23:13:09.967918: val_loss -0.7428 +2024-11-22 23:13:09.968002: Pseudo dice [0.8377] +2024-11-22 23:13:09.968088: Epoch time: 18.61 s +2024-11-22 23:13:10.908576: +2024-11-22 23:13:10.908782: Epoch 6690 +2024-11-22 23:13:10.908892: Current learning rate: 0.00196 +2024-11-22 23:13:30.719207: train_loss -0.8156 +2024-11-22 23:13:30.719434: val_loss -0.7514 +2024-11-22 23:13:30.719508: Pseudo dice [0.8457] +2024-11-22 23:13:30.719590: Epoch time: 19.81 s +2024-11-22 23:13:31.654384: +2024-11-22 23:13:31.654631: Epoch 6691 +2024-11-22 23:13:31.654750: Current learning rate: 0.00196 +2024-11-22 23:13:49.989074: train_loss -0.8152 +2024-11-22 23:13:49.994511: val_loss -0.7775 +2024-11-22 23:13:49.994642: Pseudo dice [0.8571] +2024-11-22 23:13:49.994728: Epoch time: 18.34 s +2024-11-22 23:13:51.090874: +2024-11-22 23:13:51.091101: Epoch 6692 +2024-11-22 23:13:51.091215: Current learning rate: 0.00196 +2024-11-22 23:14:09.919513: train_loss -0.8188 +2024-11-22 23:14:09.919807: val_loss -0.785 +2024-11-22 23:14:09.919888: Pseudo dice [0.8463] +2024-11-22 23:14:09.919964: Epoch time: 18.83 s +2024-11-22 23:14:10.848738: +2024-11-22 23:14:10.848934: Epoch 6693 +2024-11-22 23:14:10.849046: Current learning rate: 0.00196 +2024-11-22 23:14:28.504482: train_loss -0.8177 +2024-11-22 23:14:28.504721: val_loss -0.7485 +2024-11-22 23:14:28.504864: Pseudo dice [0.8481] +2024-11-22 23:14:28.504949: Epoch time: 17.66 s +2024-11-22 23:14:29.433901: +2024-11-22 23:14:29.434093: Epoch 6694 +2024-11-22 23:14:29.434201: Current learning rate: 0.00196 +2024-11-22 23:14:48.621630: train_loss -0.8149 +2024-11-22 23:14:48.621888: val_loss -0.7507 +2024-11-22 23:14:48.621963: Pseudo dice [0.8481] +2024-11-22 23:14:48.622052: Epoch time: 19.19 s +2024-11-22 23:14:49.551866: +2024-11-22 23:14:49.552142: Epoch 6695 +2024-11-22 23:14:49.552282: Current learning rate: 0.00196 +2024-11-22 23:15:08.285966: train_loss -0.8204 +2024-11-22 23:15:08.286200: val_loss -0.7503 +2024-11-22 23:15:08.286287: Pseudo dice [0.8373] +2024-11-22 23:15:08.288517: Epoch time: 18.73 s +2024-11-22 23:15:09.232701: +2024-11-22 23:15:09.232913: Epoch 6696 +2024-11-22 23:15:09.233033: Current learning rate: 0.00195 +2024-11-22 23:15:28.490323: train_loss -0.817 +2024-11-22 23:15:28.490546: val_loss -0.7472 +2024-11-22 23:15:28.490625: Pseudo dice [0.8661] +2024-11-22 23:15:28.490725: Epoch time: 19.26 s +2024-11-22 23:15:29.418133: +2024-11-22 23:15:29.418324: Epoch 6697 +2024-11-22 23:15:29.418467: Current learning rate: 0.00195 +2024-11-22 23:15:48.263762: train_loss -0.826 +2024-11-22 23:15:48.263972: val_loss -0.7729 +2024-11-22 23:15:48.264053: Pseudo dice [0.8611] +2024-11-22 23:15:48.264141: Epoch time: 18.85 s +2024-11-22 23:15:49.280558: +2024-11-22 23:15:49.280740: Epoch 6698 +2024-11-22 23:15:49.280840: Current learning rate: 0.00195 +2024-11-22 23:16:07.222579: train_loss -0.813 +2024-11-22 23:16:07.222824: val_loss -0.7668 +2024-11-22 23:16:07.222899: Pseudo dice [0.8512] +2024-11-22 23:16:07.222982: Epoch time: 17.94 s +2024-11-22 23:16:08.584224: +2024-11-22 23:16:08.584531: Epoch 6699 +2024-11-22 23:16:08.584642: Current learning rate: 0.00195 +2024-11-22 23:16:26.833669: train_loss -0.8243 +2024-11-22 23:16:26.833899: val_loss -0.7757 +2024-11-22 23:16:26.833972: Pseudo dice [0.8748] +2024-11-22 23:16:26.834056: Epoch time: 18.25 s +2024-11-22 23:16:28.095725: +2024-11-22 23:16:28.095948: Epoch 6700 +2024-11-22 23:16:28.096067: Current learning rate: 0.00195 +2024-11-22 23:16:46.973512: train_loss -0.8149 +2024-11-22 23:16:46.973721: val_loss -0.773 +2024-11-22 23:16:46.973798: Pseudo dice [0.8494] +2024-11-22 23:16:46.973872: Epoch time: 18.88 s +2024-11-22 23:16:47.884944: +2024-11-22 23:16:47.885180: Epoch 6701 +2024-11-22 23:16:47.885292: Current learning rate: 0.00195 +2024-11-22 23:17:07.406983: train_loss -0.8177 +2024-11-22 23:17:07.407319: val_loss -0.7375 +2024-11-22 23:17:07.407402: Pseudo dice [0.8624] +2024-11-22 23:17:07.407486: Epoch time: 19.52 s +2024-11-22 23:17:08.379461: +2024-11-22 23:17:08.379681: Epoch 6702 +2024-11-22 23:17:08.379796: Current learning rate: 0.00195 +2024-11-22 23:17:27.111480: train_loss -0.8148 +2024-11-22 23:17:27.111694: val_loss -0.7765 +2024-11-22 23:17:27.111767: Pseudo dice [0.8469] +2024-11-22 23:17:27.111841: Epoch time: 18.73 s +2024-11-22 23:17:28.014757: +2024-11-22 23:17:28.014959: Epoch 6703 +2024-11-22 23:17:28.015092: Current learning rate: 0.00194 +2024-11-22 23:17:46.612875: train_loss -0.8036 +2024-11-22 23:17:46.613088: val_loss -0.6981 +2024-11-22 23:17:46.613162: Pseudo dice [0.8333] +2024-11-22 23:17:46.613238: Epoch time: 18.6 s +2024-11-22 23:17:47.746771: +2024-11-22 23:17:47.746996: Epoch 6704 +2024-11-22 23:17:47.747116: Current learning rate: 0.00194 +2024-11-22 23:18:06.130791: train_loss -0.8033 +2024-11-22 23:18:06.131005: val_loss -0.7609 +2024-11-22 23:18:06.131080: Pseudo dice [0.8631] +2024-11-22 23:18:06.131171: Epoch time: 18.38 s +2024-11-22 23:18:07.036526: +2024-11-22 23:18:07.036741: Epoch 6705 +2024-11-22 23:18:07.036850: Current learning rate: 0.00194 +2024-11-22 23:18:25.968372: train_loss -0.8098 +2024-11-22 23:18:25.968615: val_loss -0.7558 +2024-11-22 23:18:25.968695: Pseudo dice [0.8507] +2024-11-22 23:18:25.968876: Epoch time: 18.93 s +2024-11-22 23:18:26.877486: +2024-11-22 23:18:26.877682: Epoch 6706 +2024-11-22 23:18:26.877794: Current learning rate: 0.00194 +2024-11-22 23:18:46.287510: train_loss -0.8199 +2024-11-22 23:18:46.287731: val_loss -0.7727 +2024-11-22 23:18:46.287810: Pseudo dice [0.8342] +2024-11-22 23:18:46.287886: Epoch time: 19.41 s +2024-11-22 23:18:47.210523: +2024-11-22 23:18:47.210766: Epoch 6707 +2024-11-22 23:18:47.210881: Current learning rate: 0.00194 +2024-11-22 23:19:06.074531: train_loss -0.806 +2024-11-22 23:19:06.074754: val_loss -0.7695 +2024-11-22 23:19:06.074826: Pseudo dice [0.8511] +2024-11-22 23:19:06.074902: Epoch time: 18.86 s +2024-11-22 23:19:07.131670: +2024-11-22 23:19:07.131888: Epoch 6708 +2024-11-22 23:19:07.132011: Current learning rate: 0.00194 +2024-11-22 23:19:25.906499: train_loss -0.8088 +2024-11-22 23:19:25.906713: val_loss -0.7451 +2024-11-22 23:19:25.906785: Pseudo dice [0.8319] +2024-11-22 23:19:25.906858: Epoch time: 18.78 s +2024-11-22 23:19:26.831155: +2024-11-22 23:19:26.831380: Epoch 6709 +2024-11-22 23:19:26.831504: Current learning rate: 0.00194 +2024-11-22 23:19:45.529195: train_loss -0.8071 +2024-11-22 23:19:45.529443: val_loss -0.7659 +2024-11-22 23:19:45.529520: Pseudo dice [0.8509] +2024-11-22 23:19:45.529598: Epoch time: 18.7 s +2024-11-22 23:19:46.836818: +2024-11-22 23:19:46.837040: Epoch 6710 +2024-11-22 23:19:46.837148: Current learning rate: 0.00194 +2024-11-22 23:20:05.783777: train_loss -0.8003 +2024-11-22 23:20:05.784086: val_loss -0.7483 +2024-11-22 23:20:05.784172: Pseudo dice [0.8466] +2024-11-22 23:20:05.784248: Epoch time: 18.95 s +2024-11-22 23:20:06.706856: +2024-11-22 23:20:06.707184: Epoch 6711 +2024-11-22 23:20:06.707295: Current learning rate: 0.00193 +2024-11-22 23:20:25.868823: train_loss -0.8095 +2024-11-22 23:20:25.869053: val_loss -0.7686 +2024-11-22 23:20:25.869133: Pseudo dice [0.8569] +2024-11-22 23:20:25.869218: Epoch time: 19.16 s +2024-11-22 23:20:26.799231: +2024-11-22 23:20:26.799492: Epoch 6712 +2024-11-22 23:20:26.799607: Current learning rate: 0.00193 +2024-11-22 23:20:46.311140: train_loss -0.8091 +2024-11-22 23:20:46.316595: val_loss -0.7542 +2024-11-22 23:20:46.316727: Pseudo dice [0.8325] +2024-11-22 23:20:46.316819: Epoch time: 19.51 s +2024-11-22 23:20:47.479669: +2024-11-22 23:20:47.479899: Epoch 6713 +2024-11-22 23:20:47.480016: Current learning rate: 0.00193 +2024-11-22 23:21:06.402484: train_loss -0.8115 +2024-11-22 23:21:06.402701: val_loss -0.7635 +2024-11-22 23:21:06.402771: Pseudo dice [0.8654] +2024-11-22 23:21:06.402847: Epoch time: 18.92 s +2024-11-22 23:21:07.408598: +2024-11-22 23:21:07.408837: Epoch 6714 +2024-11-22 23:21:07.408953: Current learning rate: 0.00193 +2024-11-22 23:21:27.273859: train_loss -0.8097 +2024-11-22 23:21:27.274084: val_loss -0.7515 +2024-11-22 23:21:27.274161: Pseudo dice [0.8651] +2024-11-22 23:21:27.274239: Epoch time: 19.87 s +2024-11-22 23:21:28.387781: +2024-11-22 23:21:28.388025: Epoch 6715 +2024-11-22 23:21:28.388139: Current learning rate: 0.00193 +2024-11-22 23:21:46.463149: train_loss -0.8073 +2024-11-22 23:21:46.463364: val_loss -0.758 +2024-11-22 23:21:46.463439: Pseudo dice [0.8562] +2024-11-22 23:21:46.463577: Epoch time: 18.08 s +2024-11-22 23:21:47.389473: +2024-11-22 23:21:47.389771: Epoch 6716 +2024-11-22 23:21:47.389886: Current learning rate: 0.00193 +2024-11-22 23:22:07.155082: train_loss -0.8201 +2024-11-22 23:22:07.155338: val_loss -0.7567 +2024-11-22 23:22:07.155414: Pseudo dice [0.8521] +2024-11-22 23:22:07.155507: Epoch time: 19.77 s +2024-11-22 23:22:08.087450: +2024-11-22 23:22:08.087689: Epoch 6717 +2024-11-22 23:22:08.087812: Current learning rate: 0.00193 +2024-11-22 23:22:27.061306: train_loss -0.8154 +2024-11-22 23:22:27.061522: val_loss -0.764 +2024-11-22 23:22:27.061600: Pseudo dice [0.8578] +2024-11-22 23:22:27.061676: Epoch time: 18.97 s +2024-11-22 23:22:27.984163: +2024-11-22 23:22:27.984366: Epoch 6718 +2024-11-22 23:22:27.984474: Current learning rate: 0.00192 +2024-11-22 23:22:46.698373: train_loss -0.8086 +2024-11-22 23:22:46.698589: val_loss -0.7754 +2024-11-22 23:22:46.698665: Pseudo dice [0.8503] +2024-11-22 23:22:46.698745: Epoch time: 18.71 s +2024-11-22 23:22:47.636186: +2024-11-22 23:22:47.636390: Epoch 6719 +2024-11-22 23:22:47.636501: Current learning rate: 0.00192 +2024-11-22 23:23:07.158516: train_loss -0.8094 +2024-11-22 23:23:07.158816: val_loss -0.7556 +2024-11-22 23:23:07.158894: Pseudo dice [0.8449] +2024-11-22 23:23:07.158974: Epoch time: 19.52 s +2024-11-22 23:23:08.091426: +2024-11-22 23:23:08.091633: Epoch 6720 +2024-11-22 23:23:08.091742: Current learning rate: 0.00192 +2024-11-22 23:23:25.954592: train_loss -0.8115 +2024-11-22 23:23:25.954842: val_loss -0.7393 +2024-11-22 23:23:25.954918: Pseudo dice [0.8495] +2024-11-22 23:23:25.955004: Epoch time: 17.86 s +2024-11-22 23:23:27.250716: +2024-11-22 23:23:27.251011: Epoch 6721 +2024-11-22 23:23:27.251130: Current learning rate: 0.00192 +2024-11-22 23:23:46.497009: train_loss -0.8157 +2024-11-22 23:23:46.497243: val_loss -0.7648 +2024-11-22 23:23:46.497321: Pseudo dice [0.8562] +2024-11-22 23:23:46.497397: Epoch time: 19.25 s +2024-11-22 23:23:47.430512: +2024-11-22 23:23:47.430726: Epoch 6722 +2024-11-22 23:23:47.430840: Current learning rate: 0.00192 +2024-11-22 23:24:07.317164: train_loss -0.8159 +2024-11-22 23:24:07.319589: val_loss -0.765 +2024-11-22 23:24:07.319684: Pseudo dice [0.8644] +2024-11-22 23:24:07.319764: Epoch time: 19.89 s +2024-11-22 23:24:08.338367: +2024-11-22 23:24:08.338627: Epoch 6723 +2024-11-22 23:24:08.338737: Current learning rate: 0.00192 +2024-11-22 23:24:26.978445: train_loss -0.8189 +2024-11-22 23:24:26.978708: val_loss -0.758 +2024-11-22 23:24:26.978806: Pseudo dice [0.8445] +2024-11-22 23:24:26.978893: Epoch time: 18.64 s +2024-11-22 23:24:27.909988: +2024-11-22 23:24:27.910225: Epoch 6724 +2024-11-22 23:24:27.910336: Current learning rate: 0.00192 +2024-11-22 23:24:47.223303: train_loss -0.8092 +2024-11-22 23:24:47.223574: val_loss -0.7441 +2024-11-22 23:24:47.223653: Pseudo dice [0.8478] +2024-11-22 23:24:47.223733: Epoch time: 19.31 s +2024-11-22 23:24:48.150320: +2024-11-22 23:24:48.150522: Epoch 6725 +2024-11-22 23:24:48.150635: Current learning rate: 0.00192 +2024-11-22 23:25:06.036486: train_loss -0.8208 +2024-11-22 23:25:06.036716: val_loss -0.7614 +2024-11-22 23:25:06.036796: Pseudo dice [0.8399] +2024-11-22 23:25:06.036873: Epoch time: 17.89 s +2024-11-22 23:25:06.968114: +2024-11-22 23:25:06.968354: Epoch 6726 +2024-11-22 23:25:06.968481: Current learning rate: 0.00191 +2024-11-22 23:25:25.266505: train_loss -0.8157 +2024-11-22 23:25:25.266727: val_loss -0.7402 +2024-11-22 23:25:25.266809: Pseudo dice [0.8524] +2024-11-22 23:25:25.266890: Epoch time: 18.3 s +2024-11-22 23:25:26.191522: +2024-11-22 23:25:26.191733: Epoch 6727 +2024-11-22 23:25:26.191847: Current learning rate: 0.00191 +2024-11-22 23:25:44.065795: train_loss -0.8239 +2024-11-22 23:25:44.066064: val_loss -0.7387 +2024-11-22 23:25:44.066142: Pseudo dice [0.8614] +2024-11-22 23:25:44.066225: Epoch time: 17.88 s +2024-11-22 23:25:44.994920: +2024-11-22 23:25:44.995163: Epoch 6728 +2024-11-22 23:25:44.995275: Current learning rate: 0.00191 +2024-11-22 23:26:04.777484: train_loss -0.8179 +2024-11-22 23:26:04.777713: val_loss -0.7509 +2024-11-22 23:26:04.777787: Pseudo dice [0.8587] +2024-11-22 23:26:04.777865: Epoch time: 19.78 s +2024-11-22 23:26:05.831675: +2024-11-22 23:26:05.831891: Epoch 6729 +2024-11-22 23:26:05.832014: Current learning rate: 0.00191 +2024-11-22 23:26:24.495518: train_loss -0.8204 +2024-11-22 23:26:24.495753: val_loss -0.7093 +2024-11-22 23:26:24.495826: Pseudo dice [0.8516] +2024-11-22 23:26:24.495905: Epoch time: 18.66 s +2024-11-22 23:26:25.427673: +2024-11-22 23:26:25.427876: Epoch 6730 +2024-11-22 23:26:25.427989: Current learning rate: 0.00191 +2024-11-22 23:26:44.068861: train_loss -0.8189 +2024-11-22 23:26:44.069084: val_loss -0.7256 +2024-11-22 23:26:44.069161: Pseudo dice [0.8266] +2024-11-22 23:26:44.069243: Epoch time: 18.64 s +2024-11-22 23:26:44.990961: +2024-11-22 23:26:44.991162: Epoch 6731 +2024-11-22 23:26:44.991275: Current learning rate: 0.00191 +2024-11-22 23:27:03.579181: train_loss -0.8132 +2024-11-22 23:27:03.579442: val_loss -0.7567 +2024-11-22 23:27:03.579518: Pseudo dice [0.8128] +2024-11-22 23:27:03.579598: Epoch time: 18.59 s +2024-11-22 23:27:04.932426: +2024-11-22 23:27:04.932665: Epoch 6732 +2024-11-22 23:27:04.932776: Current learning rate: 0.00191 +2024-11-22 23:27:23.542890: train_loss -0.8187 +2024-11-22 23:27:23.543140: val_loss -0.7517 +2024-11-22 23:27:23.543218: Pseudo dice [0.8469] +2024-11-22 23:27:23.543296: Epoch time: 18.61 s +2024-11-22 23:27:24.470485: +2024-11-22 23:27:24.470691: Epoch 6733 +2024-11-22 23:27:24.470801: Current learning rate: 0.0019 +2024-11-22 23:27:43.492833: train_loss -0.8251 +2024-11-22 23:27:43.493111: val_loss -0.7654 +2024-11-22 23:27:43.493187: Pseudo dice [0.835] +2024-11-22 23:27:43.493263: Epoch time: 19.02 s +2024-11-22 23:27:44.419920: +2024-11-22 23:27:44.420165: Epoch 6734 +2024-11-22 23:27:44.420291: Current learning rate: 0.0019 +2024-11-22 23:28:02.268191: train_loss -0.8179 +2024-11-22 23:28:02.268450: val_loss -0.7459 +2024-11-22 23:28:02.268528: Pseudo dice [0.8448] +2024-11-22 23:28:02.268613: Epoch time: 17.85 s +2024-11-22 23:28:03.299818: +2024-11-22 23:28:03.300034: Epoch 6735 +2024-11-22 23:28:03.300153: Current learning rate: 0.0019 +2024-11-22 23:28:22.199876: train_loss -0.8164 +2024-11-22 23:28:22.200125: val_loss -0.7249 +2024-11-22 23:28:22.200206: Pseudo dice [0.8654] +2024-11-22 23:28:22.200284: Epoch time: 18.9 s +2024-11-22 23:28:23.121550: +2024-11-22 23:28:23.121754: Epoch 6736 +2024-11-22 23:28:23.121867: Current learning rate: 0.0019 +2024-11-22 23:28:40.011683: train_loss -0.8164 +2024-11-22 23:28:40.011969: val_loss -0.7292 +2024-11-22 23:28:40.012049: Pseudo dice [0.8276] +2024-11-22 23:28:40.012126: Epoch time: 16.89 s +2024-11-22 23:28:40.938893: +2024-11-22 23:28:40.939109: Epoch 6737 +2024-11-22 23:28:40.939225: Current learning rate: 0.0019 +2024-11-22 23:28:59.620609: train_loss -0.8178 +2024-11-22 23:28:59.620842: val_loss -0.7604 +2024-11-22 23:28:59.620919: Pseudo dice [0.8644] +2024-11-22 23:28:59.621002: Epoch time: 18.68 s +2024-11-22 23:29:00.538427: +2024-11-22 23:29:00.538792: Epoch 6738 +2024-11-22 23:29:00.538904: Current learning rate: 0.0019 +2024-11-22 23:29:20.599824: train_loss -0.8144 +2024-11-22 23:29:20.605277: val_loss -0.764 +2024-11-22 23:29:20.605358: Pseudo dice [0.8309] +2024-11-22 23:29:20.605441: Epoch time: 20.06 s +2024-11-22 23:29:21.651413: +2024-11-22 23:29:21.651628: Epoch 6739 +2024-11-22 23:29:21.651743: Current learning rate: 0.0019 +2024-11-22 23:29:40.266799: train_loss -0.8145 +2024-11-22 23:29:40.267027: val_loss -0.7526 +2024-11-22 23:29:40.267101: Pseudo dice [0.8483] +2024-11-22 23:29:40.267177: Epoch time: 18.62 s +2024-11-22 23:29:41.189772: +2024-11-22 23:29:41.190041: Epoch 6740 +2024-11-22 23:29:41.190154: Current learning rate: 0.00189 +2024-11-22 23:29:59.539877: train_loss -0.8183 +2024-11-22 23:29:59.540121: val_loss -0.7744 +2024-11-22 23:29:59.540202: Pseudo dice [0.8583] +2024-11-22 23:29:59.540280: Epoch time: 18.35 s +2024-11-22 23:30:00.466209: +2024-11-22 23:30:00.466405: Epoch 6741 +2024-11-22 23:30:00.466517: Current learning rate: 0.00189 +2024-11-22 23:30:19.715494: train_loss -0.8112 +2024-11-22 23:30:19.715724: val_loss -0.7636 +2024-11-22 23:30:19.715798: Pseudo dice [0.8401] +2024-11-22 23:30:19.715879: Epoch time: 19.25 s +2024-11-22 23:30:20.649632: +2024-11-22 23:30:20.649857: Epoch 6742 +2024-11-22 23:30:20.649971: Current learning rate: 0.00189 +2024-11-22 23:30:39.614603: train_loss -0.8155 +2024-11-22 23:30:39.614848: val_loss -0.7418 +2024-11-22 23:30:39.614924: Pseudo dice [0.8542] +2024-11-22 23:30:39.628099: Epoch time: 18.97 s +2024-11-22 23:30:40.968040: +2024-11-22 23:30:40.968267: Epoch 6743 +2024-11-22 23:30:40.968377: Current learning rate: 0.00189 +2024-11-22 23:30:59.294764: train_loss -0.8199 +2024-11-22 23:30:59.294986: val_loss -0.7398 +2024-11-22 23:30:59.295066: Pseudo dice [0.8151] +2024-11-22 23:30:59.295141: Epoch time: 18.33 s +2024-11-22 23:31:00.274877: +2024-11-22 23:31:00.275111: Epoch 6744 +2024-11-22 23:31:00.275228: Current learning rate: 0.00189 +2024-11-22 23:31:19.557013: train_loss -0.8171 +2024-11-22 23:31:19.557304: val_loss -0.7374 +2024-11-22 23:31:19.557385: Pseudo dice [0.8427] +2024-11-22 23:31:19.557466: Epoch time: 19.28 s +2024-11-22 23:31:20.654354: +2024-11-22 23:31:20.654568: Epoch 6745 +2024-11-22 23:31:20.654679: Current learning rate: 0.00189 +2024-11-22 23:31:38.801861: train_loss -0.8184 +2024-11-22 23:31:38.802119: val_loss -0.7361 +2024-11-22 23:31:38.802195: Pseudo dice [0.8286] +2024-11-22 23:31:38.802293: Epoch time: 18.15 s +2024-11-22 23:31:39.729349: +2024-11-22 23:31:39.729603: Epoch 6746 +2024-11-22 23:31:39.729721: Current learning rate: 0.00189 +2024-11-22 23:31:58.872629: train_loss -0.8131 +2024-11-22 23:31:58.872855: val_loss -0.7437 +2024-11-22 23:31:58.872928: Pseudo dice [0.8542] +2024-11-22 23:31:58.878177: Epoch time: 19.14 s +2024-11-22 23:31:59.933436: +2024-11-22 23:31:59.933672: Epoch 6747 +2024-11-22 23:31:59.933799: Current learning rate: 0.00189 +2024-11-22 23:32:18.741190: train_loss -0.8128 +2024-11-22 23:32:18.741416: val_loss -0.7795 +2024-11-22 23:32:18.741492: Pseudo dice [0.866] +2024-11-22 23:32:18.741568: Epoch time: 18.81 s +2024-11-22 23:32:19.673226: +2024-11-22 23:32:19.673447: Epoch 6748 +2024-11-22 23:32:19.673561: Current learning rate: 0.00188 +2024-11-22 23:32:38.382487: train_loss -0.818 +2024-11-22 23:32:38.382709: val_loss -0.7419 +2024-11-22 23:32:38.382787: Pseudo dice [0.8451] +2024-11-22 23:32:38.382869: Epoch time: 18.71 s +2024-11-22 23:32:39.309262: +2024-11-22 23:32:39.309566: Epoch 6749 +2024-11-22 23:32:39.309678: Current learning rate: 0.00188 +2024-11-22 23:32:57.470929: train_loss -0.8121 +2024-11-22 23:32:57.471188: val_loss -0.7335 +2024-11-22 23:32:57.471265: Pseudo dice [0.8396] +2024-11-22 23:32:57.471346: Epoch time: 18.16 s +2024-11-22 23:32:58.788397: +2024-11-22 23:32:58.788621: Epoch 6750 +2024-11-22 23:32:58.788732: Current learning rate: 0.00188 +2024-11-22 23:33:17.267548: train_loss -0.816 +2024-11-22 23:33:17.267767: val_loss -0.7608 +2024-11-22 23:33:17.267845: Pseudo dice [0.8465] +2024-11-22 23:33:17.267926: Epoch time: 18.48 s +2024-11-22 23:33:18.196851: +2024-11-22 23:33:18.197132: Epoch 6751 +2024-11-22 23:33:18.197252: Current learning rate: 0.00188 +2024-11-22 23:33:38.074915: train_loss -0.8109 +2024-11-22 23:33:38.075147: val_loss -0.7346 +2024-11-22 23:33:38.075225: Pseudo dice [0.831] +2024-11-22 23:33:38.077572: Epoch time: 19.88 s +2024-11-22 23:33:39.009337: +2024-11-22 23:33:39.009547: Epoch 6752 +2024-11-22 23:33:39.009659: Current learning rate: 0.00188 +2024-11-22 23:33:58.277169: train_loss -0.8135 +2024-11-22 23:33:58.282564: val_loss -0.7311 +2024-11-22 23:33:58.282683: Pseudo dice [0.844] +2024-11-22 23:33:58.282772: Epoch time: 19.27 s +2024-11-22 23:33:59.406680: +2024-11-22 23:33:59.406880: Epoch 6753 +2024-11-22 23:33:59.407109: Current learning rate: 0.00188 +2024-11-22 23:34:18.076166: train_loss -0.8169 +2024-11-22 23:34:18.076422: val_loss -0.7596 +2024-11-22 23:34:18.076510: Pseudo dice [0.8539] +2024-11-22 23:34:18.076593: Epoch time: 18.67 s +2024-11-22 23:34:19.415071: +2024-11-22 23:34:19.415314: Epoch 6754 +2024-11-22 23:34:19.415430: Current learning rate: 0.00188 +2024-11-22 23:34:37.181491: train_loss -0.8136 +2024-11-22 23:34:37.181796: val_loss -0.7486 +2024-11-22 23:34:37.181877: Pseudo dice [0.8756] +2024-11-22 23:34:37.181956: Epoch time: 17.77 s +2024-11-22 23:34:38.108850: +2024-11-22 23:34:38.109074: Epoch 6755 +2024-11-22 23:34:38.109209: Current learning rate: 0.00187 +2024-11-22 23:34:56.861732: train_loss -0.8131 +2024-11-22 23:34:56.861986: val_loss -0.76 +2024-11-22 23:34:56.862072: Pseudo dice [0.8656] +2024-11-22 23:34:56.862151: Epoch time: 18.75 s +2024-11-22 23:34:57.823803: +2024-11-22 23:34:57.824034: Epoch 6756 +2024-11-22 23:34:57.824147: Current learning rate: 0.00187 +2024-11-22 23:35:17.338152: train_loss -0.8164 +2024-11-22 23:35:17.338413: val_loss -0.7775 +2024-11-22 23:35:17.338487: Pseudo dice [0.8553] +2024-11-22 23:35:17.338566: Epoch time: 19.52 s +2024-11-22 23:35:18.267010: +2024-11-22 23:35:18.267220: Epoch 6757 +2024-11-22 23:35:18.267346: Current learning rate: 0.00187 +2024-11-22 23:35:37.329245: train_loss -0.8133 +2024-11-22 23:35:37.329469: val_loss -0.7697 +2024-11-22 23:35:37.329544: Pseudo dice [0.8473] +2024-11-22 23:35:37.329622: Epoch time: 19.06 s +2024-11-22 23:35:38.386859: +2024-11-22 23:35:38.387104: Epoch 6758 +2024-11-22 23:35:38.387219: Current learning rate: 0.00187 +2024-11-22 23:35:56.892013: train_loss -0.8165 +2024-11-22 23:35:56.892251: val_loss -0.7544 +2024-11-22 23:35:56.892327: Pseudo dice [0.8489] +2024-11-22 23:35:56.892404: Epoch time: 18.51 s +2024-11-22 23:35:57.821100: +2024-11-22 23:35:57.821318: Epoch 6759 +2024-11-22 23:35:57.821434: Current learning rate: 0.00187 +2024-11-22 23:36:15.630984: train_loss -0.8207 +2024-11-22 23:36:15.631213: val_loss -0.7778 +2024-11-22 23:36:15.631288: Pseudo dice [0.8591] +2024-11-22 23:36:15.631367: Epoch time: 17.81 s +2024-11-22 23:36:16.774317: +2024-11-22 23:36:16.774518: Epoch 6760 +2024-11-22 23:36:16.774645: Current learning rate: 0.00187 +2024-11-22 23:36:34.837312: train_loss -0.8214 +2024-11-22 23:36:34.837567: val_loss -0.7602 +2024-11-22 23:36:34.837642: Pseudo dice [0.8524] +2024-11-22 23:36:34.837725: Epoch time: 18.06 s +2024-11-22 23:36:35.797888: +2024-11-22 23:36:35.798101: Epoch 6761 +2024-11-22 23:36:35.798215: Current learning rate: 0.00187 +2024-11-22 23:36:55.860348: train_loss -0.8166 +2024-11-22 23:36:55.860569: val_loss -0.7564 +2024-11-22 23:36:55.860643: Pseudo dice [0.8586] +2024-11-22 23:36:55.860718: Epoch time: 20.06 s +2024-11-22 23:36:56.779004: +2024-11-22 23:36:56.779201: Epoch 6762 +2024-11-22 23:36:56.779313: Current learning rate: 0.00186 +2024-11-22 23:37:15.605392: train_loss -0.8237 +2024-11-22 23:37:15.605609: val_loss -0.7538 +2024-11-22 23:37:15.605685: Pseudo dice [0.8501] +2024-11-22 23:37:15.605762: Epoch time: 18.83 s +2024-11-22 23:37:16.545024: +2024-11-22 23:37:16.545234: Epoch 6763 +2024-11-22 23:37:16.545346: Current learning rate: 0.00186 +2024-11-22 23:37:34.544526: train_loss -0.8213 +2024-11-22 23:37:34.544742: val_loss -0.7593 +2024-11-22 23:37:34.544815: Pseudo dice [0.8434] +2024-11-22 23:37:34.544890: Epoch time: 18.0 s +2024-11-22 23:37:35.469087: +2024-11-22 23:37:35.469292: Epoch 6764 +2024-11-22 23:37:35.469401: Current learning rate: 0.00186 +2024-11-22 23:37:54.791907: train_loss -0.8119 +2024-11-22 23:37:54.792163: val_loss -0.745 +2024-11-22 23:37:54.792241: Pseudo dice [0.8691] +2024-11-22 23:37:54.792328: Epoch time: 19.32 s +2024-11-22 23:37:56.097239: +2024-11-22 23:37:56.097465: Epoch 6765 +2024-11-22 23:37:56.097574: Current learning rate: 0.00186 +2024-11-22 23:38:15.765052: train_loss -0.8166 +2024-11-22 23:38:15.765285: val_loss -0.7471 +2024-11-22 23:38:15.765363: Pseudo dice [0.8378] +2024-11-22 23:38:15.765440: Epoch time: 19.67 s +2024-11-22 23:38:16.690406: +2024-11-22 23:38:16.690617: Epoch 6766 +2024-11-22 23:38:16.690725: Current learning rate: 0.00186 +2024-11-22 23:38:35.234222: train_loss -0.8148 +2024-11-22 23:38:35.234469: val_loss -0.7247 +2024-11-22 23:38:35.234551: Pseudo dice [0.8522] +2024-11-22 23:38:35.234631: Epoch time: 18.54 s +2024-11-22 23:38:36.160272: +2024-11-22 23:38:36.160500: Epoch 6767 +2024-11-22 23:38:36.160618: Current learning rate: 0.00186 +2024-11-22 23:38:55.357343: train_loss -0.8188 +2024-11-22 23:38:55.357608: val_loss -0.7755 +2024-11-22 23:38:55.357689: Pseudo dice [0.8625] +2024-11-22 23:38:55.357773: Epoch time: 19.2 s +2024-11-22 23:38:56.279365: +2024-11-22 23:38:56.279580: Epoch 6768 +2024-11-22 23:38:56.279692: Current learning rate: 0.00186 +2024-11-22 23:39:16.209226: train_loss -0.8118 +2024-11-22 23:39:16.209456: val_loss -0.7431 +2024-11-22 23:39:16.209533: Pseudo dice [0.8306] +2024-11-22 23:39:16.209610: Epoch time: 19.93 s +2024-11-22 23:39:17.134800: +2024-11-22 23:39:17.135071: Epoch 6769 +2024-11-22 23:39:17.135190: Current learning rate: 0.00186 +2024-11-22 23:39:35.159138: train_loss -0.8255 +2024-11-22 23:39:35.159360: val_loss -0.758 +2024-11-22 23:39:35.159435: Pseudo dice [0.8385] +2024-11-22 23:39:35.159510: Epoch time: 18.03 s +2024-11-22 23:39:36.088284: +2024-11-22 23:39:36.088523: Epoch 6770 +2024-11-22 23:39:36.088634: Current learning rate: 0.00185 +2024-11-22 23:39:54.722330: train_loss -0.8178 +2024-11-22 23:39:54.722594: val_loss -0.7615 +2024-11-22 23:39:54.722692: Pseudo dice [0.8469] +2024-11-22 23:39:54.722770: Epoch time: 18.63 s +2024-11-22 23:39:55.647768: +2024-11-22 23:39:55.648081: Epoch 6771 +2024-11-22 23:39:55.648196: Current learning rate: 0.00185 +2024-11-22 23:40:14.684670: train_loss -0.8192 +2024-11-22 23:40:14.684983: val_loss -0.7648 +2024-11-22 23:40:14.685068: Pseudo dice [0.8656] +2024-11-22 23:40:14.685158: Epoch time: 19.04 s +2024-11-22 23:40:15.607132: +2024-11-22 23:40:15.607334: Epoch 6772 +2024-11-22 23:40:15.607444: Current learning rate: 0.00185 +2024-11-22 23:40:34.909646: train_loss -0.8193 +2024-11-22 23:40:34.909891: val_loss -0.7635 +2024-11-22 23:40:34.909965: Pseudo dice [0.8601] +2024-11-22 23:40:34.910047: Epoch time: 19.3 s +2024-11-22 23:40:35.998438: +2024-11-22 23:40:35.998642: Epoch 6773 +2024-11-22 23:40:35.998754: Current learning rate: 0.00185 +2024-11-22 23:40:54.774327: train_loss -0.8122 +2024-11-22 23:40:54.774548: val_loss -0.7859 +2024-11-22 23:40:54.774624: Pseudo dice [0.8464] +2024-11-22 23:40:54.774701: Epoch time: 18.78 s +2024-11-22 23:40:55.690365: +2024-11-22 23:40:55.690597: Epoch 6774 +2024-11-22 23:40:55.690708: Current learning rate: 0.00185 +2024-11-22 23:41:14.703048: train_loss -0.8129 +2024-11-22 23:41:14.703268: val_loss -0.7612 +2024-11-22 23:41:14.703341: Pseudo dice [0.8494] +2024-11-22 23:41:14.703417: Epoch time: 19.01 s +2024-11-22 23:41:15.681525: +2024-11-22 23:41:15.681713: Epoch 6775 +2024-11-22 23:41:15.681823: Current learning rate: 0.00185 +2024-11-22 23:41:35.073177: train_loss -0.8167 +2024-11-22 23:41:35.073425: val_loss -0.7344 +2024-11-22 23:41:35.075605: Pseudo dice [0.8709] +2024-11-22 23:41:35.075850: Epoch time: 19.39 s +2024-11-22 23:41:36.445661: +2024-11-22 23:41:36.445874: Epoch 6776 +2024-11-22 23:41:36.445987: Current learning rate: 0.00185 +2024-11-22 23:41:55.520872: train_loss -0.8097 +2024-11-22 23:41:55.521125: val_loss -0.7652 +2024-11-22 23:41:55.521211: Pseudo dice [0.8495] +2024-11-22 23:41:55.521291: Epoch time: 19.08 s +2024-11-22 23:41:56.669052: +2024-11-22 23:41:56.669276: Epoch 6777 +2024-11-22 23:41:56.669391: Current learning rate: 0.00184 +2024-11-22 23:42:16.641795: train_loss -0.8199 +2024-11-22 23:42:16.642057: val_loss -0.7618 +2024-11-22 23:42:16.642132: Pseudo dice [0.851] +2024-11-22 23:42:16.642209: Epoch time: 19.97 s +2024-11-22 23:42:17.689325: +2024-11-22 23:42:17.689544: Epoch 6778 +2024-11-22 23:42:17.689657: Current learning rate: 0.00184 +2024-11-22 23:42:36.981508: train_loss -0.819 +2024-11-22 23:42:36.981775: val_loss -0.7512 +2024-11-22 23:42:36.981854: Pseudo dice [0.853] +2024-11-22 23:42:36.981936: Epoch time: 19.29 s +2024-11-22 23:42:38.130986: +2024-11-22 23:42:38.131394: Epoch 6779 +2024-11-22 23:42:38.131709: Current learning rate: 0.00184 +2024-11-22 23:42:57.301759: train_loss -0.8159 +2024-11-22 23:42:57.302049: val_loss -0.7459 +2024-11-22 23:42:57.302127: Pseudo dice [0.8625] +2024-11-22 23:42:57.302205: Epoch time: 19.17 s +2024-11-22 23:42:58.314321: +2024-11-22 23:42:58.314631: Epoch 6780 +2024-11-22 23:42:58.314742: Current learning rate: 0.00184 +2024-11-22 23:43:17.223566: train_loss -0.8225 +2024-11-22 23:43:17.223796: val_loss -0.7355 +2024-11-22 23:43:17.223877: Pseudo dice [0.8466] +2024-11-22 23:43:17.223955: Epoch time: 18.91 s +2024-11-22 23:43:18.160004: +2024-11-22 23:43:18.160251: Epoch 6781 +2024-11-22 23:43:18.160363: Current learning rate: 0.00184 +2024-11-22 23:43:36.417140: train_loss -0.8193 +2024-11-22 23:43:36.417375: val_loss -0.7463 +2024-11-22 23:43:36.417448: Pseudo dice [0.8534] +2024-11-22 23:43:36.417526: Epoch time: 18.26 s +2024-11-22 23:43:37.438533: +2024-11-22 23:43:37.438725: Epoch 6782 +2024-11-22 23:43:37.438835: Current learning rate: 0.00184 +2024-11-22 23:43:56.426134: train_loss -0.8212 +2024-11-22 23:43:56.426412: val_loss -0.7535 +2024-11-22 23:43:56.426490: Pseudo dice [0.8486] +2024-11-22 23:43:56.426572: Epoch time: 18.99 s +2024-11-22 23:43:57.360359: +2024-11-22 23:43:57.360550: Epoch 6783 +2024-11-22 23:43:57.360659: Current learning rate: 0.00184 +2024-11-22 23:44:15.964080: train_loss -0.8193 +2024-11-22 23:44:15.964329: val_loss -0.7467 +2024-11-22 23:44:15.966242: Pseudo dice [0.8557] +2024-11-22 23:44:15.966385: Epoch time: 18.6 s +2024-11-22 23:44:16.901310: +2024-11-22 23:44:16.901532: Epoch 6784 +2024-11-22 23:44:16.901642: Current learning rate: 0.00184 +2024-11-22 23:44:35.747830: train_loss -0.8182 +2024-11-22 23:44:35.753220: val_loss -0.7223 +2024-11-22 23:44:35.753345: Pseudo dice [0.8539] +2024-11-22 23:44:35.753425: Epoch time: 18.85 s +2024-11-22 23:44:36.883234: +2024-11-22 23:44:36.883431: Epoch 6785 +2024-11-22 23:44:36.883540: Current learning rate: 0.00183 +2024-11-22 23:44:54.866163: train_loss -0.8204 +2024-11-22 23:44:54.866390: val_loss -0.7377 +2024-11-22 23:44:54.866468: Pseudo dice [0.8364] +2024-11-22 23:44:54.866546: Epoch time: 17.98 s +2024-11-22 23:44:55.795491: +2024-11-22 23:44:55.795702: Epoch 6786 +2024-11-22 23:44:55.795818: Current learning rate: 0.00183 +2024-11-22 23:45:14.407871: train_loss -0.8277 +2024-11-22 23:45:14.408133: val_loss -0.7534 +2024-11-22 23:45:14.408210: Pseudo dice [0.8438] +2024-11-22 23:45:14.408292: Epoch time: 18.61 s +2024-11-22 23:45:15.780441: +2024-11-22 23:45:15.780673: Epoch 6787 +2024-11-22 23:45:15.780787: Current learning rate: 0.00183 +2024-11-22 23:45:35.413815: train_loss -0.8247 +2024-11-22 23:45:35.414066: val_loss -0.7632 +2024-11-22 23:45:35.414171: Pseudo dice [0.8551] +2024-11-22 23:45:35.414257: Epoch time: 19.63 s +2024-11-22 23:45:36.324168: +2024-11-22 23:45:36.324404: Epoch 6788 +2024-11-22 23:45:36.324518: Current learning rate: 0.00183 +2024-11-22 23:45:55.091395: train_loss -0.812 +2024-11-22 23:45:55.091661: val_loss -0.7638 +2024-11-22 23:45:55.091782: Pseudo dice [0.8382] +2024-11-22 23:45:55.091858: Epoch time: 18.77 s +2024-11-22 23:45:56.008241: +2024-11-22 23:45:56.008451: Epoch 6789 +2024-11-22 23:45:56.008564: Current learning rate: 0.00183 +2024-11-22 23:46:14.713432: train_loss -0.8158 +2024-11-22 23:46:14.718903: val_loss -0.7876 +2024-11-22 23:46:14.719033: Pseudo dice [0.8639] +2024-11-22 23:46:14.719129: Epoch time: 18.71 s +2024-11-22 23:46:15.820310: +2024-11-22 23:46:15.820503: Epoch 6790 +2024-11-22 23:46:15.820609: Current learning rate: 0.00183 +2024-11-22 23:46:34.284228: train_loss -0.8206 +2024-11-22 23:46:34.284466: val_loss -0.7592 +2024-11-22 23:46:34.284540: Pseudo dice [0.8457] +2024-11-22 23:46:34.284617: Epoch time: 18.46 s +2024-11-22 23:46:35.220304: +2024-11-22 23:46:35.220498: Epoch 6791 +2024-11-22 23:46:35.220606: Current learning rate: 0.00183 +2024-11-22 23:46:53.992222: train_loss -0.8208 +2024-11-22 23:46:53.992455: val_loss -0.7492 +2024-11-22 23:46:53.992529: Pseudo dice [0.8385] +2024-11-22 23:46:53.992637: Epoch time: 18.77 s +2024-11-22 23:46:54.927941: +2024-11-22 23:46:54.928170: Epoch 6792 +2024-11-22 23:46:54.928278: Current learning rate: 0.00182 +2024-11-22 23:47:13.925026: train_loss -0.8183 +2024-11-22 23:47:13.925303: val_loss -0.7462 +2024-11-22 23:47:13.925429: Pseudo dice [0.8261] +2024-11-22 23:47:13.925511: Epoch time: 19.0 s +2024-11-22 23:47:14.863579: +2024-11-22 23:47:14.863783: Epoch 6793 +2024-11-22 23:47:14.863893: Current learning rate: 0.00182 +2024-11-22 23:47:33.623426: train_loss -0.8176 +2024-11-22 23:47:33.623727: val_loss -0.7467 +2024-11-22 23:47:33.623804: Pseudo dice [0.8518] +2024-11-22 23:47:33.623886: Epoch time: 18.76 s +2024-11-22 23:47:34.556319: +2024-11-22 23:47:34.556530: Epoch 6794 +2024-11-22 23:47:34.556644: Current learning rate: 0.00182 +2024-11-22 23:47:53.797388: train_loss -0.8246 +2024-11-22 23:47:53.797618: val_loss -0.7623 +2024-11-22 23:47:53.797697: Pseudo dice [0.8464] +2024-11-22 23:47:53.797773: Epoch time: 19.24 s +2024-11-22 23:47:54.725435: +2024-11-22 23:47:54.725617: Epoch 6795 +2024-11-22 23:47:54.725729: Current learning rate: 0.00182 +2024-11-22 23:48:13.148686: train_loss -0.8207 +2024-11-22 23:48:13.151096: val_loss -0.7483 +2024-11-22 23:48:13.151190: Pseudo dice [0.8679] +2024-11-22 23:48:13.151271: Epoch time: 18.42 s +2024-11-22 23:48:14.302755: +2024-11-22 23:48:14.303023: Epoch 6796 +2024-11-22 23:48:14.303136: Current learning rate: 0.00182 +2024-11-22 23:48:32.164953: train_loss -0.8192 +2024-11-22 23:48:32.165185: val_loss -0.7332 +2024-11-22 23:48:32.165265: Pseudo dice [0.8694] +2024-11-22 23:48:32.165347: Epoch time: 17.86 s +2024-11-22 23:48:33.096860: +2024-11-22 23:48:33.097062: Epoch 6797 +2024-11-22 23:48:33.097177: Current learning rate: 0.00182 +2024-11-22 23:48:51.302874: train_loss -0.8263 +2024-11-22 23:48:51.303158: val_loss -0.7288 +2024-11-22 23:48:51.303234: Pseudo dice [0.8537] +2024-11-22 23:48:51.303313: Epoch time: 18.21 s +2024-11-22 23:48:52.674410: +2024-11-22 23:48:52.674618: Epoch 6798 +2024-11-22 23:48:52.674753: Current learning rate: 0.00182 +2024-11-22 23:49:11.667402: train_loss -0.8216 +2024-11-22 23:49:11.667680: val_loss -0.7329 +2024-11-22 23:49:11.667761: Pseudo dice [0.8259] +2024-11-22 23:49:11.667846: Epoch time: 18.99 s +2024-11-22 23:49:12.587522: +2024-11-22 23:49:12.587730: Epoch 6799 +2024-11-22 23:49:12.587842: Current learning rate: 0.00181 +2024-11-22 23:49:31.258859: train_loss -0.8208 +2024-11-22 23:49:31.259101: val_loss -0.7547 +2024-11-22 23:49:31.259176: Pseudo dice [0.8489] +2024-11-22 23:49:31.259257: Epoch time: 18.67 s +2024-11-22 23:49:32.525151: +2024-11-22 23:49:32.525390: Epoch 6800 +2024-11-22 23:49:32.525497: Current learning rate: 0.00181 +2024-11-22 23:49:50.400003: train_loss -0.8213 +2024-11-22 23:49:50.400257: val_loss -0.7465 +2024-11-22 23:49:50.400332: Pseudo dice [0.8535] +2024-11-22 23:49:50.400417: Epoch time: 17.88 s +2024-11-22 23:49:51.395925: +2024-11-22 23:49:51.396134: Epoch 6801 +2024-11-22 23:49:51.396256: Current learning rate: 0.00181 +2024-11-22 23:50:10.502845: train_loss -0.8201 +2024-11-22 23:50:10.503093: val_loss -0.7518 +2024-11-22 23:50:10.503208: Pseudo dice [0.87] +2024-11-22 23:50:10.503295: Epoch time: 19.11 s +2024-11-22 23:50:11.419971: +2024-11-22 23:50:11.420176: Epoch 6802 +2024-11-22 23:50:11.420286: Current learning rate: 0.00181 +2024-11-22 23:50:29.803678: train_loss -0.8175 +2024-11-22 23:50:29.803906: val_loss -0.7786 +2024-11-22 23:50:29.803982: Pseudo dice [0.8625] +2024-11-22 23:50:29.804072: Epoch time: 18.38 s +2024-11-22 23:50:30.726825: +2024-11-22 23:50:30.727332: Epoch 6803 +2024-11-22 23:50:30.727454: Current learning rate: 0.00181 +2024-11-22 23:50:49.759647: train_loss -0.8187 +2024-11-22 23:50:49.759878: val_loss -0.7801 +2024-11-22 23:50:49.759956: Pseudo dice [0.8597] +2024-11-22 23:50:49.760044: Epoch time: 19.03 s +2024-11-22 23:50:50.857896: +2024-11-22 23:50:50.858097: Epoch 6804 +2024-11-22 23:50:50.858208: Current learning rate: 0.00181 +2024-11-22 23:51:08.383945: train_loss -0.8163 +2024-11-22 23:51:08.384205: val_loss -0.7745 +2024-11-22 23:51:08.384279: Pseudo dice [0.8703] +2024-11-22 23:51:08.384384: Epoch time: 17.53 s +2024-11-22 23:51:09.297313: +2024-11-22 23:51:09.297675: Epoch 6805 +2024-11-22 23:51:09.297799: Current learning rate: 0.00181 +2024-11-22 23:51:28.646103: train_loss -0.8167 +2024-11-22 23:51:28.647767: val_loss -0.7433 +2024-11-22 23:51:28.647938: Pseudo dice [0.8371] +2024-11-22 23:51:28.648039: Epoch time: 19.35 s +2024-11-22 23:51:29.569718: +2024-11-22 23:51:29.569918: Epoch 6806 +2024-11-22 23:51:29.570034: Current learning rate: 0.00181 +2024-11-22 23:51:47.139633: train_loss -0.8215 +2024-11-22 23:51:47.139867: val_loss -0.7317 +2024-11-22 23:51:47.139944: Pseudo dice [0.8429] +2024-11-22 23:51:47.140030: Epoch time: 17.57 s +2024-11-22 23:51:48.054303: +2024-11-22 23:51:48.054526: Epoch 6807 +2024-11-22 23:51:48.054639: Current learning rate: 0.0018 +2024-11-22 23:52:07.501383: train_loss -0.8112 +2024-11-22 23:52:07.501602: val_loss -0.7406 +2024-11-22 23:52:07.501680: Pseudo dice [0.8483] +2024-11-22 23:52:07.501766: Epoch time: 19.45 s +2024-11-22 23:52:08.421977: +2024-11-22 23:52:08.422204: Epoch 6808 +2024-11-22 23:52:08.422333: Current learning rate: 0.0018 +2024-11-22 23:52:27.497048: train_loss -0.8124 +2024-11-22 23:52:27.497292: val_loss -0.7593 +2024-11-22 23:52:27.497376: Pseudo dice [0.8637] +2024-11-22 23:52:27.497459: Epoch time: 19.08 s +2024-11-22 23:52:28.835068: +2024-11-22 23:52:28.835296: Epoch 6809 +2024-11-22 23:52:28.835411: Current learning rate: 0.0018 +2024-11-22 23:52:47.284190: train_loss -0.8189 +2024-11-22 23:52:47.284437: val_loss -0.7509 +2024-11-22 23:52:47.284514: Pseudo dice [0.8493] +2024-11-22 23:52:47.284591: Epoch time: 18.45 s +2024-11-22 23:52:48.208274: +2024-11-22 23:52:48.208488: Epoch 6810 +2024-11-22 23:52:48.208601: Current learning rate: 0.0018 +2024-11-22 23:53:06.536945: train_loss -0.8177 +2024-11-22 23:53:06.537182: val_loss -0.7383 +2024-11-22 23:53:06.537258: Pseudo dice [0.8433] +2024-11-22 23:53:06.540090: Epoch time: 18.33 s +2024-11-22 23:53:07.514169: +2024-11-22 23:53:07.514379: Epoch 6811 +2024-11-22 23:53:07.514490: Current learning rate: 0.0018 +2024-11-22 23:53:25.750761: train_loss -0.8231 +2024-11-22 23:53:25.751009: val_loss -0.7674 +2024-11-22 23:53:25.751085: Pseudo dice [0.8463] +2024-11-22 23:53:25.751173: Epoch time: 18.24 s +2024-11-22 23:53:26.672243: +2024-11-22 23:53:26.672441: Epoch 6812 +2024-11-22 23:53:26.672551: Current learning rate: 0.0018 +2024-11-22 23:53:44.444334: train_loss -0.8242 +2024-11-22 23:53:44.444563: val_loss -0.7674 +2024-11-22 23:53:44.444649: Pseudo dice [0.8358] +2024-11-22 23:53:44.444748: Epoch time: 17.77 s +2024-11-22 23:53:45.369387: +2024-11-22 23:53:45.369619: Epoch 6813 +2024-11-22 23:53:45.369740: Current learning rate: 0.0018 +2024-11-22 23:54:04.352118: train_loss -0.8209 +2024-11-22 23:54:04.352789: val_loss -0.7508 +2024-11-22 23:54:04.352872: Pseudo dice [0.8183] +2024-11-22 23:54:04.352950: Epoch time: 18.98 s +2024-11-22 23:54:05.269349: +2024-11-22 23:54:05.269566: Epoch 6814 +2024-11-22 23:54:05.269678: Current learning rate: 0.00179 +2024-11-22 23:54:24.955187: train_loss -0.8169 +2024-11-22 23:54:24.955410: val_loss -0.7163 +2024-11-22 23:54:24.955484: Pseudo dice [0.8234] +2024-11-22 23:54:24.955563: Epoch time: 19.69 s +2024-11-22 23:54:25.872655: +2024-11-22 23:54:25.872887: Epoch 6815 +2024-11-22 23:54:25.873010: Current learning rate: 0.00179 +2024-11-22 23:54:44.412908: train_loss -0.8163 +2024-11-22 23:54:44.413188: val_loss -0.7442 +2024-11-22 23:54:44.413266: Pseudo dice [0.8405] +2024-11-22 23:54:44.413356: Epoch time: 18.54 s +2024-11-22 23:54:45.428754: +2024-11-22 23:54:45.428993: Epoch 6816 +2024-11-22 23:54:45.429105: Current learning rate: 0.00179 +2024-11-22 23:55:04.101801: train_loss -0.831 +2024-11-22 23:55:04.102029: val_loss -0.7422 +2024-11-22 23:55:04.102106: Pseudo dice [0.861] +2024-11-22 23:55:04.102185: Epoch time: 18.67 s +2024-11-22 23:55:05.023540: +2024-11-22 23:55:05.023763: Epoch 6817 +2024-11-22 23:55:05.023894: Current learning rate: 0.00179 +2024-11-22 23:55:24.189520: train_loss -0.8235 +2024-11-22 23:55:24.194940: val_loss -0.7599 +2024-11-22 23:55:24.195071: Pseudo dice [0.8451] +2024-11-22 23:55:24.195152: Epoch time: 19.17 s +2024-11-22 23:55:25.307818: +2024-11-22 23:55:25.308023: Epoch 6818 +2024-11-22 23:55:25.308206: Current learning rate: 0.00179 +2024-11-22 23:55:43.856024: train_loss -0.8271 +2024-11-22 23:55:43.856250: val_loss -0.7719 +2024-11-22 23:55:43.856328: Pseudo dice [0.8663] +2024-11-22 23:55:43.856404: Epoch time: 18.55 s +2024-11-22 23:55:44.873125: +2024-11-22 23:55:44.873325: Epoch 6819 +2024-11-22 23:55:44.873436: Current learning rate: 0.00179 +2024-11-22 23:56:04.164495: train_loss -0.8217 +2024-11-22 23:56:04.164749: val_loss -0.7759 +2024-11-22 23:56:04.164823: Pseudo dice [0.8554] +2024-11-22 23:56:04.164906: Epoch time: 19.29 s +2024-11-22 23:56:05.101239: +2024-11-22 23:56:05.101456: Epoch 6820 +2024-11-22 23:56:05.101572: Current learning rate: 0.00179 +2024-11-22 23:56:22.587452: train_loss -0.8264 +2024-11-22 23:56:22.587730: val_loss -0.7435 +2024-11-22 23:56:22.587810: Pseudo dice [0.8369] +2024-11-22 23:56:22.587884: Epoch time: 17.49 s +2024-11-22 23:56:23.926131: +2024-11-22 23:56:23.926357: Epoch 6821 +2024-11-22 23:56:23.926473: Current learning rate: 0.00178 +2024-11-22 23:56:41.994809: train_loss -0.8215 +2024-11-22 23:56:41.995053: val_loss -0.7532 +2024-11-22 23:56:41.995132: Pseudo dice [0.8537] +2024-11-22 23:56:41.995211: Epoch time: 18.07 s +2024-11-22 23:56:42.919414: +2024-11-22 23:56:42.919619: Epoch 6822 +2024-11-22 23:56:42.919730: Current learning rate: 0.00178 +2024-11-22 23:57:01.924322: train_loss -0.8242 +2024-11-22 23:57:01.924611: val_loss -0.7592 +2024-11-22 23:57:01.924692: Pseudo dice [0.863] +2024-11-22 23:57:01.924782: Epoch time: 19.01 s +2024-11-22 23:57:02.846669: +2024-11-22 23:57:02.846928: Epoch 6823 +2024-11-22 23:57:02.847042: Current learning rate: 0.00178 +2024-11-22 23:57:22.304896: train_loss -0.8156 +2024-11-22 23:57:22.308437: val_loss -0.742 +2024-11-22 23:57:22.308542: Pseudo dice [0.863] +2024-11-22 23:57:22.308627: Epoch time: 19.46 s +2024-11-22 23:57:23.391115: +2024-11-22 23:57:23.391337: Epoch 6824 +2024-11-22 23:57:23.391457: Current learning rate: 0.00178 +2024-11-22 23:57:43.066984: train_loss -0.8204 +2024-11-22 23:57:43.067241: val_loss -0.7322 +2024-11-22 23:57:43.067318: Pseudo dice [0.8616] +2024-11-22 23:57:43.067436: Epoch time: 19.68 s +2024-11-22 23:57:43.993561: +2024-11-22 23:57:43.993872: Epoch 6825 +2024-11-22 23:57:43.993982: Current learning rate: 0.00178 +2024-11-22 23:58:02.578044: train_loss -0.8124 +2024-11-22 23:58:02.578268: val_loss -0.7514 +2024-11-22 23:58:02.578344: Pseudo dice [0.856] +2024-11-22 23:58:02.578422: Epoch time: 18.59 s +2024-11-22 23:58:03.509698: +2024-11-22 23:58:03.509906: Epoch 6826 +2024-11-22 23:58:03.510020: Current learning rate: 0.00178 +2024-11-22 23:58:20.813089: train_loss -0.82 +2024-11-22 23:58:20.813340: val_loss -0.7386 +2024-11-22 23:58:20.813417: Pseudo dice [0.8469] +2024-11-22 23:58:20.813499: Epoch time: 17.3 s +2024-11-22 23:58:21.735732: +2024-11-22 23:58:21.736006: Epoch 6827 +2024-11-22 23:58:21.736115: Current learning rate: 0.00178 +2024-11-22 23:58:40.261315: train_loss -0.8157 +2024-11-22 23:58:40.261534: val_loss -0.7268 +2024-11-22 23:58:40.261608: Pseudo dice [0.8493] +2024-11-22 23:58:40.261684: Epoch time: 18.53 s +2024-11-22 23:58:41.177723: +2024-11-22 23:58:41.177915: Epoch 6828 +2024-11-22 23:58:41.178030: Current learning rate: 0.00178 +2024-11-22 23:58:59.895035: train_loss -0.8155 +2024-11-22 23:58:59.895263: val_loss -0.781 +2024-11-22 23:58:59.895339: Pseudo dice [0.8517] +2024-11-22 23:58:59.895420: Epoch time: 18.72 s +2024-11-22 23:59:00.810830: +2024-11-22 23:59:00.811043: Epoch 6829 +2024-11-22 23:59:00.811157: Current learning rate: 0.00177 +2024-11-22 23:59:19.488984: train_loss -0.8225 +2024-11-22 23:59:19.489213: val_loss -0.7311 +2024-11-22 23:59:19.489288: Pseudo dice [0.8587] +2024-11-22 23:59:19.489364: Epoch time: 18.68 s +2024-11-22 23:59:20.413880: +2024-11-22 23:59:20.414100: Epoch 6830 +2024-11-22 23:59:20.414250: Current learning rate: 0.00177 +2024-11-22 23:59:38.791509: train_loss -0.8188 +2024-11-22 23:59:38.791761: val_loss -0.7402 +2024-11-22 23:59:38.791838: Pseudo dice [0.8317] +2024-11-22 23:59:38.791921: Epoch time: 18.38 s +2024-11-22 23:59:39.709245: +2024-11-22 23:59:39.709481: Epoch 6831 +2024-11-22 23:59:39.709599: Current learning rate: 0.00177 +2024-11-22 23:59:58.554976: train_loss -0.82 +2024-11-22 23:59:58.555233: val_loss -0.735 +2024-11-22 23:59:58.555313: Pseudo dice [0.8344] +2024-11-22 23:59:58.555391: Epoch time: 18.85 s +2024-11-22 23:59:59.902435: +2024-11-22 23:59:59.902676: Epoch 6832 +2024-11-22 23:59:59.902789: Current learning rate: 0.00177 +2024-11-23 00:00:19.136872: train_loss -0.8226 +2024-11-23 00:00:19.137127: val_loss -0.7668 +2024-11-23 00:00:19.137208: Pseudo dice [0.8646] +2024-11-23 00:00:19.137289: Epoch time: 19.24 s +2024-11-23 00:00:20.052130: +2024-11-23 00:00:20.052574: Epoch 6833 +2024-11-23 00:00:20.052710: Current learning rate: 0.00177 +2024-11-23 00:00:39.935958: train_loss -0.8176 +2024-11-23 00:00:39.936227: val_loss -0.7385 +2024-11-23 00:00:39.936308: Pseudo dice [0.839] +2024-11-23 00:00:39.936391: Epoch time: 19.88 s +2024-11-23 00:00:40.854863: +2024-11-23 00:00:40.855288: Epoch 6834 +2024-11-23 00:00:40.855423: Current learning rate: 0.00177 +2024-11-23 00:00:58.778050: train_loss -0.8241 +2024-11-23 00:00:58.778270: val_loss -0.731 +2024-11-23 00:00:58.778344: Pseudo dice [0.8702] +2024-11-23 00:00:58.778421: Epoch time: 17.92 s +2024-11-23 00:00:59.697194: +2024-11-23 00:00:59.697618: Epoch 6835 +2024-11-23 00:00:59.697746: Current learning rate: 0.00177 +2024-11-23 00:01:18.487755: train_loss -0.8251 +2024-11-23 00:01:18.487978: val_loss -0.7598 +2024-11-23 00:01:18.488064: Pseudo dice [0.8622] +2024-11-23 00:01:18.488140: Epoch time: 18.79 s +2024-11-23 00:01:19.404747: +2024-11-23 00:01:19.405222: Epoch 6836 +2024-11-23 00:01:19.405360: Current learning rate: 0.00176 +2024-11-23 00:01:37.924411: train_loss -0.8208 +2024-11-23 00:01:37.924700: val_loss -0.7369 +2024-11-23 00:01:37.924777: Pseudo dice [0.8591] +2024-11-23 00:01:37.924857: Epoch time: 18.52 s +2024-11-23 00:01:38.848600: +2024-11-23 00:01:38.849097: Epoch 6837 +2024-11-23 00:01:38.849237: Current learning rate: 0.00176 +2024-11-23 00:01:56.986628: train_loss -0.8209 +2024-11-23 00:01:56.988988: val_loss -0.7672 +2024-11-23 00:01:56.989140: Pseudo dice [0.8502] +2024-11-23 00:01:56.989233: Epoch time: 18.14 s +2024-11-23 00:01:57.919798: +2024-11-23 00:01:57.920234: Epoch 6838 +2024-11-23 00:01:57.920362: Current learning rate: 0.00176 +2024-11-23 00:02:16.504184: train_loss -0.8178 +2024-11-23 00:02:16.504402: val_loss -0.7776 +2024-11-23 00:02:16.504474: Pseudo dice [0.8711] +2024-11-23 00:02:16.504549: Epoch time: 18.59 s +2024-11-23 00:02:17.541375: +2024-11-23 00:02:17.541901: Epoch 6839 +2024-11-23 00:02:17.542036: Current learning rate: 0.00176 +2024-11-23 00:02:36.483926: train_loss -0.8203 +2024-11-23 00:02:36.484155: val_loss -0.7696 +2024-11-23 00:02:36.484229: Pseudo dice [0.8466] +2024-11-23 00:02:36.484306: Epoch time: 18.94 s +2024-11-23 00:02:37.502806: +2024-11-23 00:02:37.503242: Epoch 6840 +2024-11-23 00:02:37.503380: Current learning rate: 0.00176 +2024-11-23 00:02:56.888323: train_loss -0.8183 +2024-11-23 00:02:56.888577: val_loss -0.753 +2024-11-23 00:02:56.888659: Pseudo dice [0.858] +2024-11-23 00:02:56.888740: Epoch time: 19.39 s +2024-11-23 00:02:57.803550: +2024-11-23 00:02:57.804062: Epoch 6841 +2024-11-23 00:02:57.804198: Current learning rate: 0.00176 +2024-11-23 00:03:16.457385: train_loss -0.8232 +2024-11-23 00:03:16.457638: val_loss -0.7336 +2024-11-23 00:03:16.457714: Pseudo dice [0.8675] +2024-11-23 00:03:16.457799: Epoch time: 18.65 s +2024-11-23 00:03:17.370816: +2024-11-23 00:03:17.371241: Epoch 6842 +2024-11-23 00:03:17.371372: Current learning rate: 0.00176 +2024-11-23 00:03:36.377313: train_loss -0.8265 +2024-11-23 00:03:36.377528: val_loss -0.7759 +2024-11-23 00:03:36.377602: Pseudo dice [0.8665] +2024-11-23 00:03:36.377678: Epoch time: 19.01 s +2024-11-23 00:03:37.286434: +2024-11-23 00:03:37.286653: Epoch 6843 +2024-11-23 00:03:37.286771: Current learning rate: 0.00175 +2024-11-23 00:03:56.224425: train_loss -0.8235 +2024-11-23 00:03:56.224642: val_loss -0.7564 +2024-11-23 00:03:56.224717: Pseudo dice [0.8497] +2024-11-23 00:03:56.224846: Epoch time: 18.94 s +2024-11-23 00:03:57.529099: +2024-11-23 00:03:57.529413: Epoch 6844 +2024-11-23 00:03:57.529525: Current learning rate: 0.00175 +2024-11-23 00:04:15.789589: train_loss -0.8223 +2024-11-23 00:04:15.789846: val_loss -0.792 +2024-11-23 00:04:15.792135: Pseudo dice [0.8468] +2024-11-23 00:04:15.792231: Epoch time: 18.26 s +2024-11-23 00:04:16.797764: +2024-11-23 00:04:16.797973: Epoch 6845 +2024-11-23 00:04:16.798090: Current learning rate: 0.00175 +2024-11-23 00:04:33.647806: train_loss -0.8172 +2024-11-23 00:04:33.648025: val_loss -0.7557 +2024-11-23 00:04:33.648101: Pseudo dice [0.8495] +2024-11-23 00:04:33.648198: Epoch time: 16.85 s +2024-11-23 00:04:34.568181: +2024-11-23 00:04:34.568420: Epoch 6846 +2024-11-23 00:04:34.568537: Current learning rate: 0.00175 +2024-11-23 00:04:52.830107: train_loss -0.8191 +2024-11-23 00:04:52.830326: val_loss -0.75 +2024-11-23 00:04:52.830403: Pseudo dice [0.8416] +2024-11-23 00:04:52.830478: Epoch time: 18.26 s +2024-11-23 00:04:53.892812: +2024-11-23 00:04:53.893035: Epoch 6847 +2024-11-23 00:04:53.893149: Current learning rate: 0.00175 +2024-11-23 00:05:12.918961: train_loss -0.8159 +2024-11-23 00:05:12.919212: val_loss -0.763 +2024-11-23 00:05:12.919330: Pseudo dice [0.8571] +2024-11-23 00:05:12.919444: Epoch time: 19.03 s +2024-11-23 00:05:13.841926: +2024-11-23 00:05:13.842228: Epoch 6848 +2024-11-23 00:05:13.842343: Current learning rate: 0.00175 +2024-11-23 00:05:32.666173: train_loss -0.8157 +2024-11-23 00:05:32.666455: val_loss -0.7579 +2024-11-23 00:05:32.666530: Pseudo dice [0.8554] +2024-11-23 00:05:32.666607: Epoch time: 18.83 s +2024-11-23 00:05:33.585463: +2024-11-23 00:05:33.585694: Epoch 6849 +2024-11-23 00:05:33.585814: Current learning rate: 0.00175 +2024-11-23 00:05:52.673295: train_loss -0.8194 +2024-11-23 00:05:52.673512: val_loss -0.7624 +2024-11-23 00:05:52.673590: Pseudo dice [0.8714] +2024-11-23 00:05:52.673665: Epoch time: 19.09 s +2024-11-23 00:05:53.911698: +2024-11-23 00:05:53.911917: Epoch 6850 +2024-11-23 00:05:53.912039: Current learning rate: 0.00175 +2024-11-23 00:06:11.984760: train_loss -0.8164 +2024-11-23 00:06:11.984985: val_loss -0.7611 +2024-11-23 00:06:11.985069: Pseudo dice [0.8497] +2024-11-23 00:06:11.985147: Epoch time: 18.07 s +2024-11-23 00:06:12.905622: +2024-11-23 00:06:12.905821: Epoch 6851 +2024-11-23 00:06:12.905931: Current learning rate: 0.00174 +2024-11-23 00:06:31.202123: train_loss -0.8204 +2024-11-23 00:06:31.202447: val_loss -0.7456 +2024-11-23 00:06:31.202528: Pseudo dice [0.865] +2024-11-23 00:06:31.202612: Epoch time: 18.3 s +2024-11-23 00:06:32.138922: +2024-11-23 00:06:32.139159: Epoch 6852 +2024-11-23 00:06:32.139276: Current learning rate: 0.00174 +2024-11-23 00:06:51.173346: train_loss -0.8261 +2024-11-23 00:06:51.173591: val_loss -0.7648 +2024-11-23 00:06:51.173672: Pseudo dice [0.8662] +2024-11-23 00:06:51.173748: Epoch time: 19.04 s +2024-11-23 00:06:52.093108: +2024-11-23 00:06:52.093322: Epoch 6853 +2024-11-23 00:06:52.093435: Current learning rate: 0.00174 +2024-11-23 00:07:11.166334: train_loss -0.8238 +2024-11-23 00:07:11.166551: val_loss -0.7467 +2024-11-23 00:07:11.166624: Pseudo dice [0.8268] +2024-11-23 00:07:11.166731: Epoch time: 19.07 s +2024-11-23 00:07:12.080859: +2024-11-23 00:07:12.081071: Epoch 6854 +2024-11-23 00:07:12.081181: Current learning rate: 0.00174 +2024-11-23 00:07:30.304960: train_loss -0.821 +2024-11-23 00:07:30.305198: val_loss -0.7506 +2024-11-23 00:07:30.305276: Pseudo dice [0.8461] +2024-11-23 00:07:30.305357: Epoch time: 18.22 s +2024-11-23 00:07:31.617215: +2024-11-23 00:07:31.617429: Epoch 6855 +2024-11-23 00:07:31.617537: Current learning rate: 0.00174 +2024-11-23 00:07:49.705225: train_loss -0.822 +2024-11-23 00:07:49.705503: val_loss -0.6952 +2024-11-23 00:07:49.705589: Pseudo dice [0.8284] +2024-11-23 00:07:49.705671: Epoch time: 18.09 s +2024-11-23 00:07:50.698036: +2024-11-23 00:07:50.698256: Epoch 6856 +2024-11-23 00:07:50.698371: Current learning rate: 0.00174 +2024-11-23 00:08:08.631034: train_loss -0.821 +2024-11-23 00:08:08.631252: val_loss -0.7548 +2024-11-23 00:08:08.631327: Pseudo dice [0.8322] +2024-11-23 00:08:08.631402: Epoch time: 17.93 s +2024-11-23 00:08:09.555169: +2024-11-23 00:08:09.555374: Epoch 6857 +2024-11-23 00:08:09.555488: Current learning rate: 0.00174 +2024-11-23 00:08:27.860007: train_loss -0.8165 +2024-11-23 00:08:27.860232: val_loss -0.7577 +2024-11-23 00:08:27.860306: Pseudo dice [0.8589] +2024-11-23 00:08:27.860385: Epoch time: 18.31 s +2024-11-23 00:08:28.816025: +2024-11-23 00:08:28.816258: Epoch 6858 +2024-11-23 00:08:28.816367: Current learning rate: 0.00173 +2024-11-23 00:08:46.720775: train_loss -0.8232 +2024-11-23 00:08:46.721038: val_loss -0.7455 +2024-11-23 00:08:46.721122: Pseudo dice [0.8474] +2024-11-23 00:08:46.721210: Epoch time: 17.91 s +2024-11-23 00:08:47.645760: +2024-11-23 00:08:47.645975: Epoch 6859 +2024-11-23 00:08:47.646094: Current learning rate: 0.00173 +2024-11-23 00:09:06.332514: train_loss -0.8173 +2024-11-23 00:09:06.332738: val_loss -0.7595 +2024-11-23 00:09:06.332813: Pseudo dice [0.849] +2024-11-23 00:09:06.332889: Epoch time: 18.69 s +2024-11-23 00:09:07.253417: +2024-11-23 00:09:07.253665: Epoch 6860 +2024-11-23 00:09:07.253778: Current learning rate: 0.00173 +2024-11-23 00:09:24.669740: train_loss -0.8288 +2024-11-23 00:09:24.669959: val_loss -0.7443 +2024-11-23 00:09:24.670041: Pseudo dice [0.8651] +2024-11-23 00:09:24.670118: Epoch time: 17.42 s +2024-11-23 00:09:25.584324: +2024-11-23 00:09:25.584545: Epoch 6861 +2024-11-23 00:09:25.584658: Current learning rate: 0.00173 +2024-11-23 00:09:44.546320: train_loss -0.8293 +2024-11-23 00:09:44.546544: val_loss -0.7638 +2024-11-23 00:09:44.546623: Pseudo dice [0.8541] +2024-11-23 00:09:44.546719: Epoch time: 18.96 s +2024-11-23 00:09:45.499942: +2024-11-23 00:09:45.500170: Epoch 6862 +2024-11-23 00:09:45.500280: Current learning rate: 0.00173 +2024-11-23 00:10:04.943054: train_loss -0.8224 +2024-11-23 00:10:04.943309: val_loss -0.7834 +2024-11-23 00:10:04.943388: Pseudo dice [0.8583] +2024-11-23 00:10:04.943474: Epoch time: 19.44 s +2024-11-23 00:10:05.864384: +2024-11-23 00:10:05.864624: Epoch 6863 +2024-11-23 00:10:05.864739: Current learning rate: 0.00173 +2024-11-23 00:10:24.485892: train_loss -0.8085 +2024-11-23 00:10:24.491298: val_loss -0.7667 +2024-11-23 00:10:24.491384: Pseudo dice [0.8624] +2024-11-23 00:10:24.491463: Epoch time: 18.62 s +2024-11-23 00:10:25.498473: +2024-11-23 00:10:25.498686: Epoch 6864 +2024-11-23 00:10:25.498801: Current learning rate: 0.00173 +2024-11-23 00:10:44.786217: train_loss -0.8127 +2024-11-23 00:10:44.786511: val_loss -0.747 +2024-11-23 00:10:44.786618: Pseudo dice [0.8641] +2024-11-23 00:10:44.786708: Epoch time: 19.29 s +2024-11-23 00:10:45.733952: +2024-11-23 00:10:45.734176: Epoch 6865 +2024-11-23 00:10:45.734311: Current learning rate: 0.00172 +2024-11-23 00:11:04.552644: train_loss -0.823 +2024-11-23 00:11:04.552891: val_loss -0.7323 +2024-11-23 00:11:04.552969: Pseudo dice [0.8509] +2024-11-23 00:11:04.553061: Epoch time: 18.82 s +2024-11-23 00:11:05.525815: +2024-11-23 00:11:05.526042: Epoch 6866 +2024-11-23 00:11:05.526155: Current learning rate: 0.00172 +2024-11-23 00:11:24.642916: train_loss -0.8198 +2024-11-23 00:11:24.643141: val_loss -0.7821 +2024-11-23 00:11:24.643218: Pseudo dice [0.8383] +2024-11-23 00:11:24.643290: Epoch time: 19.12 s +2024-11-23 00:11:25.949159: +2024-11-23 00:11:25.949362: Epoch 6867 +2024-11-23 00:11:25.949469: Current learning rate: 0.00172 +2024-11-23 00:11:43.896258: train_loss -0.8185 +2024-11-23 00:11:43.896493: val_loss -0.768 +2024-11-23 00:11:43.896568: Pseudo dice [0.8833] +2024-11-23 00:11:43.896647: Epoch time: 17.95 s +2024-11-23 00:11:44.824130: +2024-11-23 00:11:44.824361: Epoch 6868 +2024-11-23 00:11:44.824474: Current learning rate: 0.00172 +2024-11-23 00:12:04.559733: train_loss -0.8111 +2024-11-23 00:12:04.565146: val_loss -0.7627 +2024-11-23 00:12:04.565268: Pseudo dice [0.8295] +2024-11-23 00:12:04.565367: Epoch time: 19.74 s +2024-11-23 00:12:05.597680: +2024-11-23 00:12:05.597910: Epoch 6869 +2024-11-23 00:12:05.598028: Current learning rate: 0.00172 +2024-11-23 00:12:24.571193: train_loss -0.8198 +2024-11-23 00:12:24.571429: val_loss -0.7615 +2024-11-23 00:12:24.571504: Pseudo dice [0.8439] +2024-11-23 00:12:24.571584: Epoch time: 18.97 s +2024-11-23 00:12:25.492489: +2024-11-23 00:12:25.492694: Epoch 6870 +2024-11-23 00:12:25.492801: Current learning rate: 0.00172 +2024-11-23 00:12:43.875491: train_loss -0.8209 +2024-11-23 00:12:43.875718: val_loss -0.7608 +2024-11-23 00:12:43.875796: Pseudo dice [0.825] +2024-11-23 00:12:43.875873: Epoch time: 18.38 s +2024-11-23 00:12:44.802209: +2024-11-23 00:12:44.802423: Epoch 6871 +2024-11-23 00:12:44.802535: Current learning rate: 0.00172 +2024-11-23 00:13:03.762916: train_loss -0.8167 +2024-11-23 00:13:03.763145: val_loss -0.7075 +2024-11-23 00:13:03.763219: Pseudo dice [0.8346] +2024-11-23 00:13:03.763299: Epoch time: 18.96 s +2024-11-23 00:13:04.691970: +2024-11-23 00:13:04.692283: Epoch 6872 +2024-11-23 00:13:04.692401: Current learning rate: 0.00172 +2024-11-23 00:13:23.504078: train_loss -0.8165 +2024-11-23 00:13:23.504301: val_loss -0.7599 +2024-11-23 00:13:23.504376: Pseudo dice [0.8598] +2024-11-23 00:13:23.504451: Epoch time: 18.81 s +2024-11-23 00:13:24.421732: +2024-11-23 00:13:24.421940: Epoch 6873 +2024-11-23 00:13:24.422066: Current learning rate: 0.00171 +2024-11-23 00:13:43.997288: train_loss -0.8169 +2024-11-23 00:13:43.997563: val_loss -0.7647 +2024-11-23 00:13:43.997645: Pseudo dice [0.8604] +2024-11-23 00:13:43.997727: Epoch time: 19.58 s +2024-11-23 00:13:44.923642: +2024-11-23 00:13:44.923908: Epoch 6874 +2024-11-23 00:13:44.924031: Current learning rate: 0.00171 +2024-11-23 00:14:04.416224: train_loss -0.8192 +2024-11-23 00:14:04.416496: val_loss -0.7572 +2024-11-23 00:14:04.416577: Pseudo dice [0.8553] +2024-11-23 00:14:04.416654: Epoch time: 19.49 s +2024-11-23 00:14:05.335388: +2024-11-23 00:14:05.335792: Epoch 6875 +2024-11-23 00:14:05.335906: Current learning rate: 0.00171 +2024-11-23 00:14:24.954422: train_loss -0.8201 +2024-11-23 00:14:24.954645: val_loss -0.774 +2024-11-23 00:14:24.954723: Pseudo dice [0.8393] +2024-11-23 00:14:24.954802: Epoch time: 19.62 s +2024-11-23 00:14:25.903450: +2024-11-23 00:14:25.903696: Epoch 6876 +2024-11-23 00:14:25.903809: Current learning rate: 0.00171 +2024-11-23 00:14:44.522389: train_loss -0.822 +2024-11-23 00:14:44.522611: val_loss -0.7807 +2024-11-23 00:14:44.522693: Pseudo dice [0.8554] +2024-11-23 00:14:44.522771: Epoch time: 18.62 s +2024-11-23 00:14:45.468223: +2024-11-23 00:14:45.468439: Epoch 6877 +2024-11-23 00:14:45.468549: Current learning rate: 0.00171 +2024-11-23 00:15:04.716300: train_loss -0.8125 +2024-11-23 00:15:04.716549: val_loss -0.7555 +2024-11-23 00:15:04.716645: Pseudo dice [0.8559] +2024-11-23 00:15:04.716730: Epoch time: 19.25 s +2024-11-23 00:15:06.012412: +2024-11-23 00:15:06.012626: Epoch 6878 +2024-11-23 00:15:06.012738: Current learning rate: 0.00171 +2024-11-23 00:15:24.284573: train_loss -0.8133 +2024-11-23 00:15:24.284863: val_loss -0.7605 +2024-11-23 00:15:24.284945: Pseudo dice [0.8384] +2024-11-23 00:15:24.285034: Epoch time: 18.27 s +2024-11-23 00:15:25.251578: +2024-11-23 00:15:25.251813: Epoch 6879 +2024-11-23 00:15:25.251929: Current learning rate: 0.00171 +2024-11-23 00:15:44.553725: train_loss -0.8197 +2024-11-23 00:15:44.553958: val_loss -0.7645 +2024-11-23 00:15:44.554046: Pseudo dice [0.8522] +2024-11-23 00:15:44.554145: Epoch time: 19.3 s +2024-11-23 00:15:45.512055: +2024-11-23 00:15:45.512282: Epoch 6880 +2024-11-23 00:15:45.512390: Current learning rate: 0.0017 +2024-11-23 00:16:04.284118: train_loss -0.8199 +2024-11-23 00:16:04.289504: val_loss -0.7528 +2024-11-23 00:16:04.289675: Pseudo dice [0.8714] +2024-11-23 00:16:04.289769: Epoch time: 18.77 s +2024-11-23 00:16:05.299640: +2024-11-23 00:16:05.299874: Epoch 6881 +2024-11-23 00:16:05.299985: Current learning rate: 0.0017 +2024-11-23 00:16:23.968425: train_loss -0.8143 +2024-11-23 00:16:23.968639: val_loss -0.763 +2024-11-23 00:16:23.968711: Pseudo dice [0.8528] +2024-11-23 00:16:23.968795: Epoch time: 18.67 s +2024-11-23 00:16:24.901771: +2024-11-23 00:16:24.901984: Epoch 6882 +2024-11-23 00:16:24.902101: Current learning rate: 0.0017 +2024-11-23 00:16:43.482298: train_loss -0.8013 +2024-11-23 00:16:43.482608: val_loss -0.7485 +2024-11-23 00:16:43.482689: Pseudo dice [0.8533] +2024-11-23 00:16:43.483169: Epoch time: 18.58 s +2024-11-23 00:16:44.409658: +2024-11-23 00:16:44.409868: Epoch 6883 +2024-11-23 00:16:44.409981: Current learning rate: 0.0017 +2024-11-23 00:17:04.015147: train_loss -0.8127 +2024-11-23 00:17:04.015378: val_loss -0.7669 +2024-11-23 00:17:04.015456: Pseudo dice [0.8517] +2024-11-23 00:17:04.015534: Epoch time: 19.61 s +2024-11-23 00:17:05.040616: +2024-11-23 00:17:05.040853: Epoch 6884 +2024-11-23 00:17:05.040969: Current learning rate: 0.0017 +2024-11-23 00:17:23.680776: train_loss -0.8126 +2024-11-23 00:17:23.681037: val_loss -0.7346 +2024-11-23 00:17:23.681115: Pseudo dice [0.8524] +2024-11-23 00:17:23.681196: Epoch time: 18.64 s +2024-11-23 00:17:24.622144: +2024-11-23 00:17:24.622352: Epoch 6885 +2024-11-23 00:17:24.623669: Current learning rate: 0.0017 +2024-11-23 00:17:43.884882: train_loss -0.8047 +2024-11-23 00:17:43.885110: val_loss -0.7404 +2024-11-23 00:17:43.885189: Pseudo dice [0.8261] +2024-11-23 00:17:43.885267: Epoch time: 19.26 s +2024-11-23 00:17:44.801409: +2024-11-23 00:17:44.801601: Epoch 6886 +2024-11-23 00:17:44.801709: Current learning rate: 0.0017 +2024-11-23 00:18:03.663051: train_loss -0.8128 +2024-11-23 00:18:03.663265: val_loss -0.7555 +2024-11-23 00:18:03.663341: Pseudo dice [0.8306] +2024-11-23 00:18:03.663430: Epoch time: 18.86 s +2024-11-23 00:18:04.610589: +2024-11-23 00:18:04.610808: Epoch 6887 +2024-11-23 00:18:04.610921: Current learning rate: 0.00169 +2024-11-23 00:18:22.770060: train_loss -0.8233 +2024-11-23 00:18:22.770307: val_loss -0.7466 +2024-11-23 00:18:22.770381: Pseudo dice [0.8679] +2024-11-23 00:18:22.770468: Epoch time: 18.16 s +2024-11-23 00:18:23.832663: +2024-11-23 00:18:23.832878: Epoch 6888 +2024-11-23 00:18:23.832996: Current learning rate: 0.00169 +2024-11-23 00:18:41.698669: train_loss -0.8289 +2024-11-23 00:18:41.698911: val_loss -0.7563 +2024-11-23 00:18:41.699068: Pseudo dice [0.8589] +2024-11-23 00:18:41.699146: Epoch time: 17.87 s +2024-11-23 00:18:42.726329: +2024-11-23 00:18:42.726540: Epoch 6889 +2024-11-23 00:18:42.726651: Current learning rate: 0.00169 +2024-11-23 00:19:01.659837: train_loss -0.821 +2024-11-23 00:19:01.660067: val_loss -0.7686 +2024-11-23 00:19:01.660145: Pseudo dice [0.8538] +2024-11-23 00:19:01.660224: Epoch time: 18.93 s +2024-11-23 00:19:02.999903: +2024-11-23 00:19:03.000144: Epoch 6890 +2024-11-23 00:19:03.000256: Current learning rate: 0.00169 +2024-11-23 00:19:21.132035: train_loss -0.8259 +2024-11-23 00:19:21.132259: val_loss -0.7656 +2024-11-23 00:19:21.132339: Pseudo dice [0.8712] +2024-11-23 00:19:21.132415: Epoch time: 18.13 s +2024-11-23 00:19:22.058697: +2024-11-23 00:19:22.058916: Epoch 6891 +2024-11-23 00:19:22.059036: Current learning rate: 0.00169 +2024-11-23 00:19:40.532797: train_loss -0.8186 +2024-11-23 00:19:40.533138: val_loss -0.7596 +2024-11-23 00:19:40.533219: Pseudo dice [0.8469] +2024-11-23 00:19:40.533302: Epoch time: 18.47 s +2024-11-23 00:19:41.743822: +2024-11-23 00:19:41.744120: Epoch 6892 +2024-11-23 00:19:41.744234: Current learning rate: 0.00169 +2024-11-23 00:20:00.502617: train_loss -0.8163 +2024-11-23 00:20:00.502836: val_loss -0.7575 +2024-11-23 00:20:00.502912: Pseudo dice [0.8485] +2024-11-23 00:20:00.502988: Epoch time: 18.76 s +2024-11-23 00:20:01.449891: +2024-11-23 00:20:01.450102: Epoch 6893 +2024-11-23 00:20:01.450227: Current learning rate: 0.00169 +2024-11-23 00:20:20.245885: train_loss -0.8247 +2024-11-23 00:20:20.246109: val_loss -0.7281 +2024-11-23 00:20:20.246184: Pseudo dice [0.8388] +2024-11-23 00:20:20.246270: Epoch time: 18.8 s +2024-11-23 00:20:21.169083: +2024-11-23 00:20:21.169294: Epoch 6894 +2024-11-23 00:20:21.169407: Current learning rate: 0.00168 +2024-11-23 00:20:39.458755: train_loss -0.8243 +2024-11-23 00:20:39.458979: val_loss -0.7575 +2024-11-23 00:20:39.459065: Pseudo dice [0.8347] +2024-11-23 00:20:39.459142: Epoch time: 18.29 s +2024-11-23 00:20:40.391203: +2024-11-23 00:20:40.391442: Epoch 6895 +2024-11-23 00:20:40.391553: Current learning rate: 0.00168 +2024-11-23 00:20:59.074179: train_loss -0.8269 +2024-11-23 00:20:59.074425: val_loss -0.7611 +2024-11-23 00:20:59.074504: Pseudo dice [0.8468] +2024-11-23 00:20:59.074582: Epoch time: 18.68 s +2024-11-23 00:21:00.001898: +2024-11-23 00:21:00.002095: Epoch 6896 +2024-11-23 00:21:00.002202: Current learning rate: 0.00168 +2024-11-23 00:21:19.002782: train_loss -0.8158 +2024-11-23 00:21:19.003070: val_loss -0.7734 +2024-11-23 00:21:19.003155: Pseudo dice [0.8592] +2024-11-23 00:21:19.003242: Epoch time: 19.0 s +2024-11-23 00:21:19.927958: +2024-11-23 00:21:19.928185: Epoch 6897 +2024-11-23 00:21:19.928293: Current learning rate: 0.00168 +2024-11-23 00:21:38.459158: train_loss -0.8195 +2024-11-23 00:21:38.459380: val_loss -0.7656 +2024-11-23 00:21:38.461659: Pseudo dice [0.8698] +2024-11-23 00:21:38.461768: Epoch time: 18.53 s +2024-11-23 00:21:39.489026: +2024-11-23 00:21:39.489242: Epoch 6898 +2024-11-23 00:21:39.489356: Current learning rate: 0.00168 +2024-11-23 00:21:58.057699: train_loss -0.82 +2024-11-23 00:21:58.057969: val_loss -0.7312 +2024-11-23 00:21:58.058061: Pseudo dice [0.8277] +2024-11-23 00:21:58.058139: Epoch time: 18.57 s +2024-11-23 00:21:58.977566: +2024-11-23 00:21:58.977777: Epoch 6899 +2024-11-23 00:21:58.977885: Current learning rate: 0.00168 +2024-11-23 00:22:18.180266: train_loss -0.8166 +2024-11-23 00:22:18.180532: val_loss -0.7572 +2024-11-23 00:22:18.180618: Pseudo dice [0.8536] +2024-11-23 00:22:18.180698: Epoch time: 19.2 s +2024-11-23 00:22:19.430006: +2024-11-23 00:22:19.430204: Epoch 6900 +2024-11-23 00:22:19.430305: Current learning rate: 0.00168 +2024-11-23 00:22:38.065792: train_loss -0.8187 +2024-11-23 00:22:38.066015: val_loss -0.7485 +2024-11-23 00:22:38.066094: Pseudo dice [0.8631] +2024-11-23 00:22:38.066175: Epoch time: 18.64 s +2024-11-23 00:22:39.340219: +2024-11-23 00:22:39.340465: Epoch 6901 +2024-11-23 00:22:39.340583: Current learning rate: 0.00168 +2024-11-23 00:22:58.141262: train_loss -0.8269 +2024-11-23 00:22:58.141849: val_loss -0.7736 +2024-11-23 00:22:58.141938: Pseudo dice [0.8474] +2024-11-23 00:22:58.142023: Epoch time: 18.8 s +2024-11-23 00:22:59.072483: +2024-11-23 00:22:59.072768: Epoch 6902 +2024-11-23 00:22:59.072882: Current learning rate: 0.00167 +2024-11-23 00:23:18.717796: train_loss -0.8288 +2024-11-23 00:23:18.718068: val_loss -0.7444 +2024-11-23 00:23:18.718146: Pseudo dice [0.8549] +2024-11-23 00:23:18.718241: Epoch time: 19.65 s +2024-11-23 00:23:19.707100: +2024-11-23 00:23:19.707309: Epoch 6903 +2024-11-23 00:23:19.707426: Current learning rate: 0.00167 +2024-11-23 00:23:38.654476: train_loss -0.8117 +2024-11-23 00:23:38.654699: val_loss -0.7573 +2024-11-23 00:23:38.654773: Pseudo dice [0.851] +2024-11-23 00:23:38.654847: Epoch time: 18.95 s +2024-11-23 00:23:39.574183: +2024-11-23 00:23:39.574387: Epoch 6904 +2024-11-23 00:23:39.574496: Current learning rate: 0.00167 +2024-11-23 00:23:57.835693: train_loss -0.8276 +2024-11-23 00:23:57.835929: val_loss -0.7823 +2024-11-23 00:23:57.836017: Pseudo dice [0.8545] +2024-11-23 00:23:57.836106: Epoch time: 18.26 s +2024-11-23 00:23:58.757726: +2024-11-23 00:23:58.757942: Epoch 6905 +2024-11-23 00:23:58.758058: Current learning rate: 0.00167 +2024-11-23 00:24:17.437691: train_loss -0.8278 +2024-11-23 00:24:17.437921: val_loss -0.7801 +2024-11-23 00:24:17.438038: Pseudo dice [0.8707] +2024-11-23 00:24:17.438119: Epoch time: 18.68 s +2024-11-23 00:24:18.449960: +2024-11-23 00:24:18.450203: Epoch 6906 +2024-11-23 00:24:18.450315: Current learning rate: 0.00167 +2024-11-23 00:24:37.884706: train_loss -0.8154 +2024-11-23 00:24:37.884936: val_loss -0.737 +2024-11-23 00:24:37.885019: Pseudo dice [0.8405] +2024-11-23 00:24:37.885101: Epoch time: 19.44 s +2024-11-23 00:24:38.899230: +2024-11-23 00:24:38.899504: Epoch 6907 +2024-11-23 00:24:38.899617: Current learning rate: 0.00167 +2024-11-23 00:24:57.883276: train_loss -0.8143 +2024-11-23 00:24:57.883495: val_loss -0.7754 +2024-11-23 00:24:57.883567: Pseudo dice [0.8439] +2024-11-23 00:24:57.883667: Epoch time: 18.98 s +2024-11-23 00:24:58.798439: +2024-11-23 00:24:58.798641: Epoch 6908 +2024-11-23 00:24:58.798750: Current learning rate: 0.00167 +2024-11-23 00:25:17.302312: train_loss -0.8224 +2024-11-23 00:25:17.302530: val_loss -0.7502 +2024-11-23 00:25:17.302603: Pseudo dice [0.8455] +2024-11-23 00:25:17.302812: Epoch time: 18.5 s +2024-11-23 00:25:18.219688: +2024-11-23 00:25:18.219921: Epoch 6909 +2024-11-23 00:25:18.220039: Current learning rate: 0.00166 +2024-11-23 00:25:36.927140: train_loss -0.819 +2024-11-23 00:25:36.927363: val_loss -0.7762 +2024-11-23 00:25:36.927438: Pseudo dice [0.8588] +2024-11-23 00:25:36.927513: Epoch time: 18.71 s +2024-11-23 00:25:37.844115: +2024-11-23 00:25:37.844322: Epoch 6910 +2024-11-23 00:25:37.844435: Current learning rate: 0.00166 +2024-11-23 00:25:57.852565: train_loss -0.8138 +2024-11-23 00:25:57.857975: val_loss -0.7475 +2024-11-23 00:25:57.858176: Pseudo dice [0.833] +2024-11-23 00:25:57.858274: Epoch time: 20.01 s +2024-11-23 00:25:58.887532: +2024-11-23 00:25:58.887795: Epoch 6911 +2024-11-23 00:25:58.887908: Current learning rate: 0.00166 +2024-11-23 00:26:17.047936: train_loss -0.8156 +2024-11-23 00:26:17.048169: val_loss -0.745 +2024-11-23 00:26:17.048248: Pseudo dice [0.8433] +2024-11-23 00:26:17.048333: Epoch time: 18.16 s +2024-11-23 00:26:18.333693: +2024-11-23 00:26:18.333907: Epoch 6912 +2024-11-23 00:26:18.334030: Current learning rate: 0.00166 +2024-11-23 00:26:36.270656: train_loss -0.8233 +2024-11-23 00:26:36.270897: val_loss -0.7706 +2024-11-23 00:26:36.270976: Pseudo dice [0.8443] +2024-11-23 00:26:36.271058: Epoch time: 17.94 s +2024-11-23 00:26:37.180737: +2024-11-23 00:26:37.180976: Epoch 6913 +2024-11-23 00:26:37.181096: Current learning rate: 0.00166 +2024-11-23 00:26:55.629287: train_loss -0.818 +2024-11-23 00:26:55.629544: val_loss -0.7436 +2024-11-23 00:26:55.629618: Pseudo dice [0.8424] +2024-11-23 00:26:55.629701: Epoch time: 18.45 s +2024-11-23 00:26:56.552662: +2024-11-23 00:26:56.552880: Epoch 6914 +2024-11-23 00:26:56.553004: Current learning rate: 0.00166 +2024-11-23 00:27:14.484116: train_loss -0.8232 +2024-11-23 00:27:14.484314: val_loss -0.7622 +2024-11-23 00:27:14.484393: Pseudo dice [0.8526] +2024-11-23 00:27:14.484466: Epoch time: 17.93 s +2024-11-23 00:27:15.423222: +2024-11-23 00:27:15.423441: Epoch 6915 +2024-11-23 00:27:15.423551: Current learning rate: 0.00166 +2024-11-23 00:27:34.318230: train_loss -0.8143 +2024-11-23 00:27:34.318444: val_loss -0.723 +2024-11-23 00:27:34.318518: Pseudo dice [0.8427] +2024-11-23 00:27:34.318592: Epoch time: 18.9 s +2024-11-23 00:27:35.223801: +2024-11-23 00:27:35.224019: Epoch 6916 +2024-11-23 00:27:35.224131: Current learning rate: 0.00165 +2024-11-23 00:27:53.194304: train_loss -0.8239 +2024-11-23 00:27:53.194511: val_loss -0.7413 +2024-11-23 00:27:53.194591: Pseudo dice [0.8671] +2024-11-23 00:27:53.194668: Epoch time: 17.97 s +2024-11-23 00:27:54.153337: +2024-11-23 00:27:54.153539: Epoch 6917 +2024-11-23 00:27:54.153652: Current learning rate: 0.00165 +2024-11-23 00:28:12.787170: train_loss -0.8201 +2024-11-23 00:28:12.787463: val_loss -0.7625 +2024-11-23 00:28:12.787564: Pseudo dice [0.8623] +2024-11-23 00:28:12.787646: Epoch time: 18.63 s +2024-11-23 00:28:13.690702: +2024-11-23 00:28:13.690905: Epoch 6918 +2024-11-23 00:28:13.691020: Current learning rate: 0.00165 +2024-11-23 00:28:32.478514: train_loss -0.8233 +2024-11-23 00:28:32.478717: val_loss -0.7713 +2024-11-23 00:28:32.478788: Pseudo dice [0.8617] +2024-11-23 00:28:32.478861: Epoch time: 18.79 s +2024-11-23 00:28:33.454997: +2024-11-23 00:28:33.455207: Epoch 6919 +2024-11-23 00:28:33.455318: Current learning rate: 0.00165 +2024-11-23 00:28:51.913410: train_loss -0.8213 +2024-11-23 00:28:51.913624: val_loss -0.7611 +2024-11-23 00:28:51.913705: Pseudo dice [0.8597] +2024-11-23 00:28:51.913785: Epoch time: 18.46 s +2024-11-23 00:28:52.992142: +2024-11-23 00:28:52.992362: Epoch 6920 +2024-11-23 00:28:52.992473: Current learning rate: 0.00165 +2024-11-23 00:29:12.593010: train_loss -0.8234 +2024-11-23 00:29:12.593237: val_loss -0.7703 +2024-11-23 00:29:12.593312: Pseudo dice [0.8655] +2024-11-23 00:29:12.593390: Epoch time: 19.6 s +2024-11-23 00:29:13.513910: +2024-11-23 00:29:13.514233: Epoch 6921 +2024-11-23 00:29:13.514344: Current learning rate: 0.00165 +2024-11-23 00:29:31.683792: train_loss -0.8227 +2024-11-23 00:29:31.684050: val_loss -0.7696 +2024-11-23 00:29:31.684129: Pseudo dice [0.8512] +2024-11-23 00:29:31.684209: Epoch time: 18.17 s +2024-11-23 00:29:32.598843: +2024-11-23 00:29:32.599110: Epoch 6922 +2024-11-23 00:29:32.599222: Current learning rate: 0.00165 +2024-11-23 00:29:51.679586: train_loss -0.8213 +2024-11-23 00:29:51.679866: val_loss -0.7679 +2024-11-23 00:29:51.679951: Pseudo dice [0.8429] +2024-11-23 00:29:51.680048: Epoch time: 19.08 s +2024-11-23 00:29:52.602339: +2024-11-23 00:29:52.602536: Epoch 6923 +2024-11-23 00:29:52.602646: Current learning rate: 0.00165 +2024-11-23 00:30:10.645203: train_loss -0.8259 +2024-11-23 00:30:10.645424: val_loss -0.7438 +2024-11-23 00:30:10.645498: Pseudo dice [0.8259] +2024-11-23 00:30:10.645576: Epoch time: 18.04 s +2024-11-23 00:30:11.959222: +2024-11-23 00:30:11.959455: Epoch 6924 +2024-11-23 00:30:11.959575: Current learning rate: 0.00164 +2024-11-23 00:30:30.752424: train_loss -0.8178 +2024-11-23 00:30:30.752686: val_loss -0.7668 +2024-11-23 00:30:30.752761: Pseudo dice [0.8623] +2024-11-23 00:30:30.758039: Epoch time: 18.79 s +2024-11-23 00:30:31.892611: +2024-11-23 00:30:31.892824: Epoch 6925 +2024-11-23 00:30:31.892937: Current learning rate: 0.00164 +2024-11-23 00:30:50.517470: train_loss -0.8199 +2024-11-23 00:30:50.517697: val_loss -0.7756 +2024-11-23 00:30:50.517772: Pseudo dice [0.8692] +2024-11-23 00:30:50.517848: Epoch time: 18.63 s +2024-11-23 00:30:51.453413: +2024-11-23 00:30:51.453638: Epoch 6926 +2024-11-23 00:30:51.453751: Current learning rate: 0.00164 +2024-11-23 00:31:10.044141: train_loss -0.8129 +2024-11-23 00:31:10.044392: val_loss -0.7579 +2024-11-23 00:31:10.044474: Pseudo dice [0.8598] +2024-11-23 00:31:10.044554: Epoch time: 18.59 s +2024-11-23 00:31:11.042396: +2024-11-23 00:31:11.042613: Epoch 6927 +2024-11-23 00:31:11.042720: Current learning rate: 0.00164 +2024-11-23 00:31:28.867897: train_loss -0.8172 +2024-11-23 00:31:28.872068: val_loss -0.7666 +2024-11-23 00:31:28.872249: Pseudo dice [0.8424] +2024-11-23 00:31:28.872350: Epoch time: 17.83 s +2024-11-23 00:31:29.848737: +2024-11-23 00:31:29.848950: Epoch 6928 +2024-11-23 00:31:29.849067: Current learning rate: 0.00164 +2024-11-23 00:31:48.749269: train_loss -0.8193 +2024-11-23 00:31:48.749497: val_loss -0.7489 +2024-11-23 00:31:48.749571: Pseudo dice [0.8587] +2024-11-23 00:31:48.749651: Epoch time: 18.9 s +2024-11-23 00:31:49.705825: +2024-11-23 00:31:49.706058: Epoch 6929 +2024-11-23 00:31:49.706166: Current learning rate: 0.00164 +2024-11-23 00:32:08.421505: train_loss -0.8207 +2024-11-23 00:32:08.421727: val_loss -0.7611 +2024-11-23 00:32:08.421799: Pseudo dice [0.8519] +2024-11-23 00:32:08.421876: Epoch time: 18.72 s +2024-11-23 00:32:09.339022: +2024-11-23 00:32:09.339249: Epoch 6930 +2024-11-23 00:32:09.339364: Current learning rate: 0.00164 +2024-11-23 00:32:28.542982: train_loss -0.8126 +2024-11-23 00:32:28.543236: val_loss -0.7765 +2024-11-23 00:32:28.543312: Pseudo dice [0.8592] +2024-11-23 00:32:28.543389: Epoch time: 19.2 s +2024-11-23 00:32:29.468734: +2024-11-23 00:32:29.468932: Epoch 6931 +2024-11-23 00:32:29.469051: Current learning rate: 0.00163 +2024-11-23 00:32:47.899279: train_loss -0.8199 +2024-11-23 00:32:47.899514: val_loss -0.763 +2024-11-23 00:32:47.899592: Pseudo dice [0.8574] +2024-11-23 00:32:47.899676: Epoch time: 18.43 s +2024-11-23 00:32:48.816777: +2024-11-23 00:32:48.816989: Epoch 6932 +2024-11-23 00:32:48.817104: Current learning rate: 0.00163 +2024-11-23 00:33:07.887899: train_loss -0.8274 +2024-11-23 00:33:07.888128: val_loss -0.7571 +2024-11-23 00:33:07.888204: Pseudo dice [0.8677] +2024-11-23 00:33:07.888281: Epoch time: 19.07 s +2024-11-23 00:33:08.824207: +2024-11-23 00:33:08.824412: Epoch 6933 +2024-11-23 00:33:08.824525: Current learning rate: 0.00163 +2024-11-23 00:33:28.508434: train_loss -0.8136 +2024-11-23 00:33:28.510843: val_loss -0.7652 +2024-11-23 00:33:28.510933: Pseudo dice [0.8424] +2024-11-23 00:33:28.511019: Epoch time: 19.69 s +2024-11-23 00:33:29.765062: +2024-11-23 00:33:29.765270: Epoch 6934 +2024-11-23 00:33:29.765382: Current learning rate: 0.00163 +2024-11-23 00:33:48.899758: train_loss -0.822 +2024-11-23 00:33:48.899980: val_loss -0.7663 +2024-11-23 00:33:48.900218: Pseudo dice [0.8562] +2024-11-23 00:33:48.900304: Epoch time: 19.14 s +2024-11-23 00:33:50.169612: +2024-11-23 00:33:50.169820: Epoch 6935 +2024-11-23 00:33:50.169933: Current learning rate: 0.00163 +2024-11-23 00:34:08.743250: train_loss -0.8166 +2024-11-23 00:34:08.743525: val_loss -0.7604 +2024-11-23 00:34:08.743602: Pseudo dice [0.8453] +2024-11-23 00:34:08.743683: Epoch time: 18.57 s +2024-11-23 00:34:09.656721: +2024-11-23 00:34:09.656929: Epoch 6936 +2024-11-23 00:34:09.657043: Current learning rate: 0.00163 +2024-11-23 00:34:28.969905: train_loss -0.8213 +2024-11-23 00:34:28.970133: val_loss -0.7555 +2024-11-23 00:34:28.970207: Pseudo dice [0.8565] +2024-11-23 00:34:28.970325: Epoch time: 19.31 s +2024-11-23 00:34:29.899895: +2024-11-23 00:34:29.900106: Epoch 6937 +2024-11-23 00:34:29.900216: Current learning rate: 0.00163 +2024-11-23 00:34:48.891622: train_loss -0.8264 +2024-11-23 00:34:48.891839: val_loss -0.7625 +2024-11-23 00:34:48.891912: Pseudo dice [0.8592] +2024-11-23 00:34:48.891989: Epoch time: 18.99 s +2024-11-23 00:34:49.809412: +2024-11-23 00:34:49.809633: Epoch 6938 +2024-11-23 00:34:49.809749: Current learning rate: 0.00162 +2024-11-23 00:35:06.978755: train_loss -0.8246 +2024-11-23 00:35:06.979080: val_loss -0.7545 +2024-11-23 00:35:06.979159: Pseudo dice [0.8605] +2024-11-23 00:35:06.979245: Epoch time: 17.17 s +2024-11-23 00:35:07.903115: +2024-11-23 00:35:07.903322: Epoch 6939 +2024-11-23 00:35:07.903436: Current learning rate: 0.00162 +2024-11-23 00:35:26.333204: train_loss -0.8249 +2024-11-23 00:35:26.333430: val_loss -0.7505 +2024-11-23 00:35:26.333504: Pseudo dice [0.8427] +2024-11-23 00:35:26.333577: Epoch time: 18.43 s +2024-11-23 00:35:27.253583: +2024-11-23 00:35:27.253791: Epoch 6940 +2024-11-23 00:35:27.253905: Current learning rate: 0.00162 +2024-11-23 00:35:45.254369: train_loss -0.8229 +2024-11-23 00:35:45.254607: val_loss -0.727 +2024-11-23 00:35:45.254689: Pseudo dice [0.8469] +2024-11-23 00:35:45.254767: Epoch time: 18.0 s +2024-11-23 00:35:46.158632: +2024-11-23 00:35:46.158835: Epoch 6941 +2024-11-23 00:35:46.158946: Current learning rate: 0.00162 +2024-11-23 00:36:04.483914: train_loss -0.8235 +2024-11-23 00:36:04.484133: val_loss -0.744 +2024-11-23 00:36:04.484209: Pseudo dice [0.8463] +2024-11-23 00:36:04.484285: Epoch time: 18.33 s +2024-11-23 00:36:05.386918: +2024-11-23 00:36:05.387141: Epoch 6942 +2024-11-23 00:36:05.387248: Current learning rate: 0.00162 +2024-11-23 00:36:24.501080: train_loss -0.8159 +2024-11-23 00:36:24.501311: val_loss -0.7485 +2024-11-23 00:36:24.501384: Pseudo dice [0.851] +2024-11-23 00:36:24.501461: Epoch time: 19.12 s +2024-11-23 00:36:25.408490: +2024-11-23 00:36:25.408735: Epoch 6943 +2024-11-23 00:36:25.408857: Current learning rate: 0.00162 +2024-11-23 00:36:43.389379: train_loss -0.8205 +2024-11-23 00:36:43.389594: val_loss -0.7622 +2024-11-23 00:36:43.389675: Pseudo dice [0.8431] +2024-11-23 00:36:43.389751: Epoch time: 17.98 s +2024-11-23 00:36:44.308050: +2024-11-23 00:36:44.308264: Epoch 6944 +2024-11-23 00:36:44.308374: Current learning rate: 0.00162 +2024-11-23 00:37:02.532434: train_loss -0.8268 +2024-11-23 00:37:02.532664: val_loss -0.7914 +2024-11-23 00:37:02.534930: Pseudo dice [0.8577] +2024-11-23 00:37:02.535029: Epoch time: 18.23 s +2024-11-23 00:37:03.579024: +2024-11-23 00:37:03.579240: Epoch 6945 +2024-11-23 00:37:03.579359: Current learning rate: 0.00161 +2024-11-23 00:37:22.979260: train_loss -0.8224 +2024-11-23 00:37:22.979500: val_loss -0.737 +2024-11-23 00:37:22.979573: Pseudo dice [0.8778] +2024-11-23 00:37:22.979655: Epoch time: 19.4 s +2024-11-23 00:37:23.898793: +2024-11-23 00:37:23.899000: Epoch 6946 +2024-11-23 00:37:23.899114: Current learning rate: 0.00161 +2024-11-23 00:37:42.020998: train_loss -0.8166 +2024-11-23 00:37:42.021220: val_loss -0.727 +2024-11-23 00:37:42.021296: Pseudo dice [0.8318] +2024-11-23 00:37:42.021371: Epoch time: 18.12 s +2024-11-23 00:37:43.359694: +2024-11-23 00:37:43.359898: Epoch 6947 +2024-11-23 00:37:43.360013: Current learning rate: 0.00161 +2024-11-23 00:38:01.679923: train_loss -0.8253 +2024-11-23 00:38:01.680148: val_loss -0.7577 +2024-11-23 00:38:01.680221: Pseudo dice [0.8509] +2024-11-23 00:38:01.680297: Epoch time: 18.32 s +2024-11-23 00:38:02.599385: +2024-11-23 00:38:02.599611: Epoch 6948 +2024-11-23 00:38:02.599723: Current learning rate: 0.00161 +2024-11-23 00:38:21.445429: train_loss -0.8273 +2024-11-23 00:38:21.447875: val_loss -0.7797 +2024-11-23 00:38:21.448019: Pseudo dice [0.879] +2024-11-23 00:38:21.448108: Epoch time: 18.85 s +2024-11-23 00:38:22.403737: +2024-11-23 00:38:22.403953: Epoch 6949 +2024-11-23 00:38:22.404071: Current learning rate: 0.00161 +2024-11-23 00:38:41.436357: train_loss -0.8278 +2024-11-23 00:38:41.436584: val_loss -0.7633 +2024-11-23 00:38:41.436661: Pseudo dice [0.8478] +2024-11-23 00:38:41.436738: Epoch time: 19.03 s +2024-11-23 00:38:42.693901: +2024-11-23 00:38:42.694133: Epoch 6950 +2024-11-23 00:38:42.694244: Current learning rate: 0.00161 +2024-11-23 00:39:01.323731: train_loss -0.8208 +2024-11-23 00:39:01.323957: val_loss -0.7672 +2024-11-23 00:39:01.324061: Pseudo dice [0.8635] +2024-11-23 00:39:01.324223: Epoch time: 18.63 s +2024-11-23 00:39:02.248934: +2024-11-23 00:39:02.249153: Epoch 6951 +2024-11-23 00:39:02.249264: Current learning rate: 0.00161 +2024-11-23 00:39:20.546101: train_loss -0.8222 +2024-11-23 00:39:20.546327: val_loss -0.7503 +2024-11-23 00:39:20.546402: Pseudo dice [0.8402] +2024-11-23 00:39:20.546487: Epoch time: 18.3 s +2024-11-23 00:39:21.464023: +2024-11-23 00:39:21.464244: Epoch 6952 +2024-11-23 00:39:21.464357: Current learning rate: 0.00161 +2024-11-23 00:39:40.161696: train_loss -0.8232 +2024-11-23 00:39:40.161914: val_loss -0.7299 +2024-11-23 00:39:40.161986: Pseudo dice [0.8314] +2024-11-23 00:39:40.162071: Epoch time: 18.7 s +2024-11-23 00:39:41.080941: +2024-11-23 00:39:41.081203: Epoch 6953 +2024-11-23 00:39:41.081317: Current learning rate: 0.0016 +2024-11-23 00:40:00.311124: train_loss -0.8251 +2024-11-23 00:40:00.311373: val_loss -0.7463 +2024-11-23 00:40:00.311448: Pseudo dice [0.8413] +2024-11-23 00:40:00.311580: Epoch time: 19.23 s +2024-11-23 00:40:01.233126: +2024-11-23 00:40:01.233327: Epoch 6954 +2024-11-23 00:40:01.233436: Current learning rate: 0.0016 +2024-11-23 00:40:20.765168: train_loss -0.8266 +2024-11-23 00:40:20.765393: val_loss -0.7423 +2024-11-23 00:40:20.765474: Pseudo dice [0.831] +2024-11-23 00:40:20.765553: Epoch time: 19.53 s +2024-11-23 00:40:21.685964: +2024-11-23 00:40:21.686195: Epoch 6955 +2024-11-23 00:40:21.686309: Current learning rate: 0.0016 +2024-11-23 00:40:40.231841: train_loss -0.8268 +2024-11-23 00:40:40.232076: val_loss -0.7668 +2024-11-23 00:40:40.232152: Pseudo dice [0.8564] +2024-11-23 00:40:40.232229: Epoch time: 18.55 s +2024-11-23 00:40:41.156204: +2024-11-23 00:40:41.156431: Epoch 6956 +2024-11-23 00:40:41.156544: Current learning rate: 0.0016 +2024-11-23 00:40:59.348294: train_loss -0.8208 +2024-11-23 00:40:59.348604: val_loss -0.7758 +2024-11-23 00:40:59.348684: Pseudo dice [0.8587] +2024-11-23 00:40:59.348768: Epoch time: 18.19 s +2024-11-23 00:41:00.268816: +2024-11-23 00:41:00.269026: Epoch 6957 +2024-11-23 00:41:00.269141: Current learning rate: 0.0016 +2024-11-23 00:41:19.699884: train_loss -0.8177 +2024-11-23 00:41:19.700106: val_loss -0.7659 +2024-11-23 00:41:19.700185: Pseudo dice [0.8557] +2024-11-23 00:41:19.700263: Epoch time: 19.43 s +2024-11-23 00:41:21.016965: +2024-11-23 00:41:21.017184: Epoch 6958 +2024-11-23 00:41:21.017297: Current learning rate: 0.0016 +2024-11-23 00:41:39.883454: train_loss -0.8177 +2024-11-23 00:41:39.883806: val_loss -0.7724 +2024-11-23 00:41:39.883894: Pseudo dice [0.8717] +2024-11-23 00:41:39.883976: Epoch time: 18.87 s +2024-11-23 00:41:40.807553: +2024-11-23 00:41:40.807755: Epoch 6959 +2024-11-23 00:41:40.807869: Current learning rate: 0.0016 +2024-11-23 00:42:00.693301: train_loss -0.822 +2024-11-23 00:42:00.693562: val_loss -0.7763 +2024-11-23 00:42:00.693644: Pseudo dice [0.8616] +2024-11-23 00:42:00.693725: Epoch time: 19.89 s +2024-11-23 00:42:01.610766: +2024-11-23 00:42:01.611043: Epoch 6960 +2024-11-23 00:42:01.611161: Current learning rate: 0.00159 +2024-11-23 00:42:19.641136: train_loss -0.8261 +2024-11-23 00:42:19.641404: val_loss -0.7317 +2024-11-23 00:42:19.641638: Pseudo dice [0.8512] +2024-11-23 00:42:19.641726: Epoch time: 18.03 s +2024-11-23 00:42:20.555271: +2024-11-23 00:42:20.555488: Epoch 6961 +2024-11-23 00:42:20.555601: Current learning rate: 0.00159 +2024-11-23 00:42:38.451324: train_loss -0.8225 +2024-11-23 00:42:38.451548: val_loss -0.7446 +2024-11-23 00:42:38.451624: Pseudo dice [0.8386] +2024-11-23 00:42:38.451699: Epoch time: 17.9 s +2024-11-23 00:42:39.371646: +2024-11-23 00:42:39.371865: Epoch 6962 +2024-11-23 00:42:39.371977: Current learning rate: 0.00159 +2024-11-23 00:42:57.577884: train_loss -0.8223 +2024-11-23 00:42:57.578125: val_loss -0.7621 +2024-11-23 00:42:57.578198: Pseudo dice [0.8625] +2024-11-23 00:42:57.578275: Epoch time: 18.21 s +2024-11-23 00:42:58.495935: +2024-11-23 00:42:58.496137: Epoch 6963 +2024-11-23 00:42:58.496249: Current learning rate: 0.00159 +2024-11-23 00:43:17.940820: train_loss -0.8284 +2024-11-23 00:43:17.941092: val_loss -0.7673 +2024-11-23 00:43:17.941168: Pseudo dice [0.8591] +2024-11-23 00:43:17.941253: Epoch time: 19.45 s +2024-11-23 00:43:19.049283: +2024-11-23 00:43:19.049588: Epoch 6964 +2024-11-23 00:43:19.049705: Current learning rate: 0.00159 +2024-11-23 00:43:36.937495: train_loss -0.821 +2024-11-23 00:43:36.937718: val_loss -0.7417 +2024-11-23 00:43:36.937791: Pseudo dice [0.8503] +2024-11-23 00:43:36.937866: Epoch time: 17.89 s +2024-11-23 00:43:37.881593: +2024-11-23 00:43:37.881799: Epoch 6965 +2024-11-23 00:43:37.881910: Current learning rate: 0.00159 +2024-11-23 00:43:56.402574: train_loss -0.8214 +2024-11-23 00:43:56.402799: val_loss -0.7527 +2024-11-23 00:43:56.402876: Pseudo dice [0.8448] +2024-11-23 00:43:56.402956: Epoch time: 18.52 s +2024-11-23 00:43:57.317826: +2024-11-23 00:43:57.318060: Epoch 6966 +2024-11-23 00:43:57.318176: Current learning rate: 0.00159 +2024-11-23 00:44:16.845598: train_loss -0.8209 +2024-11-23 00:44:16.845840: val_loss -0.7484 +2024-11-23 00:44:16.845918: Pseudo dice [0.8576] +2024-11-23 00:44:16.846001: Epoch time: 19.53 s +2024-11-23 00:44:17.771111: +2024-11-23 00:44:17.771328: Epoch 6967 +2024-11-23 00:44:17.771439: Current learning rate: 0.00158 +2024-11-23 00:44:35.750824: train_loss -0.8117 +2024-11-23 00:44:35.751092: val_loss -0.7749 +2024-11-23 00:44:35.751171: Pseudo dice [0.8784] +2024-11-23 00:44:35.751258: Epoch time: 17.98 s +2024-11-23 00:44:36.666217: +2024-11-23 00:44:36.666429: Epoch 6968 +2024-11-23 00:44:36.666554: Current learning rate: 0.00158 +2024-11-23 00:44:56.377442: train_loss -0.8242 +2024-11-23 00:44:56.377672: val_loss -0.7443 +2024-11-23 00:44:56.377757: Pseudo dice [0.8306] +2024-11-23 00:44:56.377838: Epoch time: 19.71 s +2024-11-23 00:44:57.298080: +2024-11-23 00:44:57.298268: Epoch 6969 +2024-11-23 00:44:57.298378: Current learning rate: 0.00158 +2024-11-23 00:45:16.884358: train_loss -0.8187 +2024-11-23 00:45:16.884573: val_loss -0.7534 +2024-11-23 00:45:16.884648: Pseudo dice [0.8372] +2024-11-23 00:45:16.884725: Epoch time: 19.59 s +2024-11-23 00:45:18.226974: +2024-11-23 00:45:18.227193: Epoch 6970 +2024-11-23 00:45:18.227315: Current learning rate: 0.00158 +2024-11-23 00:45:36.708485: train_loss -0.8146 +2024-11-23 00:45:36.708739: val_loss -0.7706 +2024-11-23 00:45:36.708814: Pseudo dice [0.8375] +2024-11-23 00:45:36.708902: Epoch time: 18.48 s +2024-11-23 00:45:37.625862: +2024-11-23 00:45:37.626088: Epoch 6971 +2024-11-23 00:45:37.626209: Current learning rate: 0.00158 +2024-11-23 00:45:55.936896: train_loss -0.8224 +2024-11-23 00:45:55.937160: val_loss -0.7639 +2024-11-23 00:45:55.937240: Pseudo dice [0.8518] +2024-11-23 00:45:55.937317: Epoch time: 18.31 s +2024-11-23 00:45:57.001037: +2024-11-23 00:45:57.001262: Epoch 6972 +2024-11-23 00:45:57.001372: Current learning rate: 0.00158 +2024-11-23 00:46:15.714438: train_loss -0.8215 +2024-11-23 00:46:15.714669: val_loss -0.7645 +2024-11-23 00:46:15.714745: Pseudo dice [0.854] +2024-11-23 00:46:15.714853: Epoch time: 18.71 s +2024-11-23 00:46:16.740549: +2024-11-23 00:46:16.740772: Epoch 6973 +2024-11-23 00:46:16.740893: Current learning rate: 0.00158 +2024-11-23 00:46:34.945431: train_loss -0.8274 +2024-11-23 00:46:34.945636: val_loss -0.7776 +2024-11-23 00:46:34.945711: Pseudo dice [0.8456] +2024-11-23 00:46:34.945790: Epoch time: 18.21 s +2024-11-23 00:46:35.866281: +2024-11-23 00:46:35.866511: Epoch 6974 +2024-11-23 00:46:35.866656: Current learning rate: 0.00157 +2024-11-23 00:46:54.301337: train_loss -0.8256 +2024-11-23 00:46:54.301588: val_loss -0.731 +2024-11-23 00:46:54.301663: Pseudo dice [0.8369] +2024-11-23 00:46:54.301744: Epoch time: 18.44 s +2024-11-23 00:46:55.224051: +2024-11-23 00:46:55.224260: Epoch 6975 +2024-11-23 00:46:55.224372: Current learning rate: 0.00157 +2024-11-23 00:47:13.800328: train_loss -0.8235 +2024-11-23 00:47:13.800553: val_loss -0.7077 +2024-11-23 00:47:13.800632: Pseudo dice [0.8718] +2024-11-23 00:47:13.800712: Epoch time: 18.58 s +2024-11-23 00:47:14.715966: +2024-11-23 00:47:14.716200: Epoch 6976 +2024-11-23 00:47:14.716315: Current learning rate: 0.00157 +2024-11-23 00:47:33.116500: train_loss -0.8178 +2024-11-23 00:47:33.116752: val_loss -0.7573 +2024-11-23 00:47:33.116828: Pseudo dice [0.8383] +2024-11-23 00:47:33.116903: Epoch time: 18.4 s +2024-11-23 00:47:34.038792: +2024-11-23 00:47:34.039025: Epoch 6977 +2024-11-23 00:47:34.039141: Current learning rate: 0.00157 +2024-11-23 00:47:52.112438: train_loss -0.8118 +2024-11-23 00:47:52.112680: val_loss -0.7619 +2024-11-23 00:47:52.112754: Pseudo dice [0.8511] +2024-11-23 00:47:52.112831: Epoch time: 18.07 s +2024-11-23 00:47:53.039325: +2024-11-23 00:47:53.039541: Epoch 6978 +2024-11-23 00:47:53.039660: Current learning rate: 0.00157 +2024-11-23 00:48:10.461564: train_loss -0.8152 +2024-11-23 00:48:10.467013: val_loss -0.721 +2024-11-23 00:48:10.467127: Pseudo dice [0.848] +2024-11-23 00:48:10.467211: Epoch time: 17.42 s +2024-11-23 00:48:11.404692: +2024-11-23 00:48:11.404909: Epoch 6979 +2024-11-23 00:48:11.405024: Current learning rate: 0.00157 +2024-11-23 00:48:30.356153: train_loss -0.8058 +2024-11-23 00:48:30.356372: val_loss -0.7612 +2024-11-23 00:48:30.356452: Pseudo dice [0.8491] +2024-11-23 00:48:30.356528: Epoch time: 18.95 s +2024-11-23 00:48:31.346939: +2024-11-23 00:48:31.347150: Epoch 6980 +2024-11-23 00:48:31.347257: Current learning rate: 0.00157 +2024-11-23 00:48:49.081059: train_loss -0.8209 +2024-11-23 00:48:49.081272: val_loss -0.757 +2024-11-23 00:48:49.081345: Pseudo dice [0.8523] +2024-11-23 00:48:49.081421: Epoch time: 17.73 s +2024-11-23 00:48:50.369440: +2024-11-23 00:48:50.369648: Epoch 6981 +2024-11-23 00:48:50.369761: Current learning rate: 0.00157 +2024-11-23 00:49:09.609448: train_loss -0.8129 +2024-11-23 00:49:09.609712: val_loss -0.7398 +2024-11-23 00:49:09.609792: Pseudo dice [0.8558] +2024-11-23 00:49:09.609876: Epoch time: 19.24 s +2024-11-23 00:49:10.531142: +2024-11-23 00:49:10.531371: Epoch 6982 +2024-11-23 00:49:10.531483: Current learning rate: 0.00156 +2024-11-23 00:49:30.368622: train_loss -0.8169 +2024-11-23 00:49:30.368846: val_loss -0.7407 +2024-11-23 00:49:30.368927: Pseudo dice [0.8513] +2024-11-23 00:49:30.369170: Epoch time: 19.84 s +2024-11-23 00:49:31.292939: +2024-11-23 00:49:31.293174: Epoch 6983 +2024-11-23 00:49:31.293288: Current learning rate: 0.00156 +2024-11-23 00:49:49.890562: train_loss -0.8266 +2024-11-23 00:49:49.890788: val_loss -0.7547 +2024-11-23 00:49:49.890861: Pseudo dice [0.8452] +2024-11-23 00:49:49.890940: Epoch time: 18.6 s +2024-11-23 00:49:50.816018: +2024-11-23 00:49:50.816262: Epoch 6984 +2024-11-23 00:49:50.816380: Current learning rate: 0.00156 +2024-11-23 00:50:09.194560: train_loss -0.8267 +2024-11-23 00:50:09.194785: val_loss -0.7511 +2024-11-23 00:50:09.194858: Pseudo dice [0.8354] +2024-11-23 00:50:09.194936: Epoch time: 18.38 s +2024-11-23 00:50:10.115731: +2024-11-23 00:50:10.115957: Epoch 6985 +2024-11-23 00:50:10.116079: Current learning rate: 0.00156 +2024-11-23 00:50:27.405395: train_loss -0.8267 +2024-11-23 00:50:27.405642: val_loss -0.7615 +2024-11-23 00:50:27.405718: Pseudo dice [0.8247] +2024-11-23 00:50:27.405803: Epoch time: 17.29 s +2024-11-23 00:50:28.322701: +2024-11-23 00:50:28.323037: Epoch 6986 +2024-11-23 00:50:28.323149: Current learning rate: 0.00156 +2024-11-23 00:50:46.974786: train_loss -0.8294 +2024-11-23 00:50:46.975725: val_loss -0.7731 +2024-11-23 00:50:46.975876: Pseudo dice [0.8587] +2024-11-23 00:50:46.978142: Epoch time: 18.65 s +2024-11-23 00:50:47.900672: +2024-11-23 00:50:47.900898: Epoch 6987 +2024-11-23 00:50:47.901014: Current learning rate: 0.00156 +2024-11-23 00:51:06.690414: train_loss -0.8207 +2024-11-23 00:51:06.690630: val_loss -0.7593 +2024-11-23 00:51:06.690705: Pseudo dice [0.877] +2024-11-23 00:51:06.690780: Epoch time: 18.79 s +2024-11-23 00:51:07.612146: +2024-11-23 00:51:07.612360: Epoch 6988 +2024-11-23 00:51:07.612471: Current learning rate: 0.00156 +2024-11-23 00:51:26.398275: train_loss -0.8262 +2024-11-23 00:51:26.398491: val_loss -0.75 +2024-11-23 00:51:26.398569: Pseudo dice [0.84] +2024-11-23 00:51:26.398648: Epoch time: 18.79 s +2024-11-23 00:51:27.333780: +2024-11-23 00:51:27.334023: Epoch 6989 +2024-11-23 00:51:27.334140: Current learning rate: 0.00155 +2024-11-23 00:51:44.967736: train_loss -0.8249 +2024-11-23 00:51:44.967989: val_loss -0.7839 +2024-11-23 00:51:44.968108: Pseudo dice [0.8511] +2024-11-23 00:51:44.968189: Epoch time: 17.63 s +2024-11-23 00:51:45.981858: +2024-11-23 00:51:45.982159: Epoch 6990 +2024-11-23 00:51:45.982275: Current learning rate: 0.00155 +2024-11-23 00:52:04.053081: train_loss -0.8307 +2024-11-23 00:52:04.055497: val_loss -0.7528 +2024-11-23 00:52:04.055594: Pseudo dice [0.8473] +2024-11-23 00:52:04.055677: Epoch time: 18.07 s +2024-11-23 00:52:05.072785: +2024-11-23 00:52:05.072989: Epoch 6991 +2024-11-23 00:52:05.073105: Current learning rate: 0.00155 +2024-11-23 00:52:23.264245: train_loss -0.826 +2024-11-23 00:52:23.264474: val_loss -0.7603 +2024-11-23 00:52:23.264546: Pseudo dice [0.8646] +2024-11-23 00:52:23.264622: Epoch time: 18.19 s +2024-11-23 00:52:24.298295: +2024-11-23 00:52:24.298567: Epoch 6992 +2024-11-23 00:52:24.298681: Current learning rate: 0.00155 +2024-11-23 00:52:42.649967: train_loss -0.8193 +2024-11-23 00:52:42.650227: val_loss -0.7563 +2024-11-23 00:52:42.650301: Pseudo dice [0.8383] +2024-11-23 00:52:42.650390: Epoch time: 18.35 s +2024-11-23 00:52:44.039216: +2024-11-23 00:52:44.039440: Epoch 6993 +2024-11-23 00:52:44.039553: Current learning rate: 0.00155 +2024-11-23 00:53:03.870343: train_loss -0.8251 +2024-11-23 00:53:03.870584: val_loss -0.7446 +2024-11-23 00:53:03.870661: Pseudo dice [0.8524] +2024-11-23 00:53:03.870737: Epoch time: 19.83 s +2024-11-23 00:53:04.788077: +2024-11-23 00:53:04.788288: Epoch 6994 +2024-11-23 00:53:04.788399: Current learning rate: 0.00155 +2024-11-23 00:53:23.361804: train_loss -0.8217 +2024-11-23 00:53:23.362026: val_loss -0.7645 +2024-11-23 00:53:23.362100: Pseudo dice [0.8628] +2024-11-23 00:53:23.362175: Epoch time: 18.57 s +2024-11-23 00:53:24.284401: +2024-11-23 00:53:24.284634: Epoch 6995 +2024-11-23 00:53:24.284747: Current learning rate: 0.00155 +2024-11-23 00:53:42.143740: train_loss -0.8281 +2024-11-23 00:53:42.143986: val_loss -0.7552 +2024-11-23 00:53:42.144067: Pseudo dice [0.8558] +2024-11-23 00:53:42.144149: Epoch time: 17.86 s +2024-11-23 00:53:43.071083: +2024-11-23 00:53:43.071306: Epoch 6996 +2024-11-23 00:53:43.071422: Current learning rate: 0.00154 +2024-11-23 00:54:01.948302: train_loss -0.8249 +2024-11-23 00:54:01.953688: val_loss -0.7494 +2024-11-23 00:54:01.953850: Pseudo dice [0.8502] +2024-11-23 00:54:01.953932: Epoch time: 18.88 s +2024-11-23 00:54:02.890726: +2024-11-23 00:54:02.890936: Epoch 6997 +2024-11-23 00:54:02.891054: Current learning rate: 0.00154 +2024-11-23 00:54:20.970438: train_loss -0.8328 +2024-11-23 00:54:20.970659: val_loss -0.7333 +2024-11-23 00:54:20.970738: Pseudo dice [0.8342] +2024-11-23 00:54:20.970817: Epoch time: 18.08 s +2024-11-23 00:54:21.925041: +2024-11-23 00:54:21.925282: Epoch 6998 +2024-11-23 00:54:21.925397: Current learning rate: 0.00154 +2024-11-23 00:54:39.611009: train_loss -0.824 +2024-11-23 00:54:39.611230: val_loss -0.7536 +2024-11-23 00:54:39.611304: Pseudo dice [0.8559] +2024-11-23 00:54:39.611381: Epoch time: 17.69 s +2024-11-23 00:54:40.634457: +2024-11-23 00:54:40.634695: Epoch 6999 +2024-11-23 00:54:40.634806: Current learning rate: 0.00154 +2024-11-23 00:54:59.250816: train_loss -0.8243 +2024-11-23 00:54:59.251101: val_loss -0.7561 +2024-11-23 00:54:59.251181: Pseudo dice [0.8362] +2024-11-23 00:54:59.251264: Epoch time: 18.62 s +2024-11-23 00:55:00.513769: +2024-11-23 00:55:00.514011: Epoch 7000 +2024-11-23 00:55:00.514125: Current learning rate: 0.00154 +2024-11-23 00:55:19.710973: train_loss -0.8288 +2024-11-23 00:55:19.711205: val_loss -0.7679 +2024-11-23 00:55:19.711278: Pseudo dice [0.8283] +2024-11-23 00:55:19.711359: Epoch time: 19.2 s +2024-11-23 00:55:20.709446: +2024-11-23 00:55:20.709686: Epoch 7001 +2024-11-23 00:55:20.709801: Current learning rate: 0.00154 +2024-11-23 00:55:38.235347: train_loss -0.8345 +2024-11-23 00:55:38.235565: val_loss -0.7292 +2024-11-23 00:55:38.235640: Pseudo dice [0.8437] +2024-11-23 00:55:38.235717: Epoch time: 17.53 s +2024-11-23 00:55:39.215085: +2024-11-23 00:55:39.215313: Epoch 7002 +2024-11-23 00:55:39.215422: Current learning rate: 0.00154 +2024-11-23 00:55:57.127647: train_loss -0.8224 +2024-11-23 00:55:57.127872: val_loss -0.7502 +2024-11-23 00:55:57.127947: Pseudo dice [0.8609] +2024-11-23 00:55:57.128032: Epoch time: 17.91 s +2024-11-23 00:55:58.064681: +2024-11-23 00:55:58.064916: Epoch 7003 +2024-11-23 00:55:58.065036: Current learning rate: 0.00153 +2024-11-23 00:56:15.975207: train_loss -0.8156 +2024-11-23 00:56:15.975464: val_loss -0.752 +2024-11-23 00:56:15.975538: Pseudo dice [0.8544] +2024-11-23 00:56:15.975621: Epoch time: 17.91 s +2024-11-23 00:56:16.928988: +2024-11-23 00:56:16.929217: Epoch 7004 +2024-11-23 00:56:16.929329: Current learning rate: 0.00153 +2024-11-23 00:56:35.656397: train_loss -0.8202 +2024-11-23 00:56:35.656707: val_loss -0.7612 +2024-11-23 00:56:35.656786: Pseudo dice [0.8249] +2024-11-23 00:56:35.656864: Epoch time: 18.73 s +2024-11-23 00:56:36.673237: +2024-11-23 00:56:36.673465: Epoch 7005 +2024-11-23 00:56:36.673578: Current learning rate: 0.00153 +2024-11-23 00:56:54.661523: train_loss -0.8149 +2024-11-23 00:56:54.661751: val_loss -0.741 +2024-11-23 00:56:54.661823: Pseudo dice [0.8188] +2024-11-23 00:56:54.661901: Epoch time: 17.99 s +2024-11-23 00:56:55.746745: +2024-11-23 00:56:55.746970: Epoch 7006 +2024-11-23 00:56:55.747085: Current learning rate: 0.00153 +2024-11-23 00:57:13.866502: train_loss -0.8244 +2024-11-23 00:57:13.866762: val_loss -0.7168 +2024-11-23 00:57:13.866841: Pseudo dice [0.8467] +2024-11-23 00:57:13.866927: Epoch time: 18.12 s +2024-11-23 00:57:14.790851: +2024-11-23 00:57:14.791057: Epoch 7007 +2024-11-23 00:57:14.791168: Current learning rate: 0.00153 +2024-11-23 00:57:32.072680: train_loss -0.8241 +2024-11-23 00:57:32.078066: val_loss -0.7633 +2024-11-23 00:57:32.078184: Pseudo dice [0.8461] +2024-11-23 00:57:32.078262: Epoch time: 17.28 s +2024-11-23 00:57:33.126964: +2024-11-23 00:57:33.127177: Epoch 7008 +2024-11-23 00:57:33.127290: Current learning rate: 0.00153 +2024-11-23 00:57:52.230550: train_loss -0.8223 +2024-11-23 00:57:52.230790: val_loss -0.7585 +2024-11-23 00:57:52.230867: Pseudo dice [0.8719] +2024-11-23 00:57:52.230946: Epoch time: 19.1 s +2024-11-23 00:57:53.251234: +2024-11-23 00:57:53.251445: Epoch 7009 +2024-11-23 00:57:53.251556: Current learning rate: 0.00153 +2024-11-23 00:58:12.349035: train_loss -0.8217 +2024-11-23 00:58:12.349264: val_loss -0.7478 +2024-11-23 00:58:12.349339: Pseudo dice [0.841] +2024-11-23 00:58:12.349418: Epoch time: 19.1 s +2024-11-23 00:58:13.302176: +2024-11-23 00:58:13.302409: Epoch 7010 +2024-11-23 00:58:13.302522: Current learning rate: 0.00153 +2024-11-23 00:58:31.846666: train_loss -0.8215 +2024-11-23 00:58:31.846961: val_loss -0.7541 +2024-11-23 00:58:31.847054: Pseudo dice [0.8607] +2024-11-23 00:58:31.847145: Epoch time: 18.55 s +2024-11-23 00:58:32.768046: +2024-11-23 00:58:32.768262: Epoch 7011 +2024-11-23 00:58:32.768371: Current learning rate: 0.00152 +2024-11-23 00:58:51.074697: train_loss -0.8184 +2024-11-23 00:58:51.074928: val_loss -0.7529 +2024-11-23 00:58:51.075008: Pseudo dice [0.845] +2024-11-23 00:58:51.075092: Epoch time: 18.31 s +2024-11-23 00:58:52.007283: +2024-11-23 00:58:52.007517: Epoch 7012 +2024-11-23 00:58:52.007634: Current learning rate: 0.00152 +2024-11-23 00:59:10.090979: train_loss -0.8197 +2024-11-23 00:59:10.091352: val_loss -0.7513 +2024-11-23 00:59:10.091440: Pseudo dice [0.8346] +2024-11-23 00:59:10.091516: Epoch time: 18.08 s +2024-11-23 00:59:11.017403: +2024-11-23 00:59:11.017636: Epoch 7013 +2024-11-23 00:59:11.017760: Current learning rate: 0.00152 +2024-11-23 00:59:28.468095: train_loss -0.8228 +2024-11-23 00:59:28.468318: val_loss -0.7472 +2024-11-23 00:59:28.468395: Pseudo dice [0.8647] +2024-11-23 00:59:28.468472: Epoch time: 17.45 s +2024-11-23 00:59:29.388999: +2024-11-23 00:59:29.389201: Epoch 7014 +2024-11-23 00:59:29.389312: Current learning rate: 0.00152 +2024-11-23 00:59:47.939246: train_loss -0.8281 +2024-11-23 00:59:47.939548: val_loss -0.7448 +2024-11-23 00:59:47.939624: Pseudo dice [0.8462] +2024-11-23 00:59:47.939706: Epoch time: 18.55 s +2024-11-23 00:59:48.859269: +2024-11-23 00:59:48.859476: Epoch 7015 +2024-11-23 00:59:48.859587: Current learning rate: 0.00152 +2024-11-23 01:00:08.221379: train_loss -0.8207 +2024-11-23 01:00:08.223790: val_loss -0.7276 +2024-11-23 01:00:08.223884: Pseudo dice [0.8646] +2024-11-23 01:00:08.223965: Epoch time: 19.36 s +2024-11-23 01:00:09.623908: +2024-11-23 01:00:09.624162: Epoch 7016 +2024-11-23 01:00:09.624279: Current learning rate: 0.00152 +2024-11-23 01:00:29.429645: train_loss -0.822 +2024-11-23 01:00:29.429866: val_loss -0.7799 +2024-11-23 01:00:29.429940: Pseudo dice [0.8655] +2024-11-23 01:00:29.430026: Epoch time: 19.81 s +2024-11-23 01:00:30.352548: +2024-11-23 01:00:30.352761: Epoch 7017 +2024-11-23 01:00:30.352871: Current learning rate: 0.00152 +2024-11-23 01:00:48.307631: train_loss -0.829 +2024-11-23 01:00:48.307903: val_loss -0.7665 +2024-11-23 01:00:48.307977: Pseudo dice [0.8452] +2024-11-23 01:00:48.308063: Epoch time: 17.96 s +2024-11-23 01:00:49.261748: +2024-11-23 01:00:49.261969: Epoch 7018 +2024-11-23 01:00:49.262084: Current learning rate: 0.00151 +2024-11-23 01:01:06.894420: train_loss -0.8229 +2024-11-23 01:01:06.894666: val_loss -0.7464 +2024-11-23 01:01:06.894745: Pseudo dice [0.838] +2024-11-23 01:01:06.894825: Epoch time: 17.63 s +2024-11-23 01:01:07.814429: +2024-11-23 01:01:07.814660: Epoch 7019 +2024-11-23 01:01:07.814772: Current learning rate: 0.00151 +2024-11-23 01:01:26.099386: train_loss -0.8235 +2024-11-23 01:01:26.099611: val_loss -0.7713 +2024-11-23 01:01:26.099686: Pseudo dice [0.8601] +2024-11-23 01:01:26.099763: Epoch time: 18.29 s +2024-11-23 01:01:27.017237: +2024-11-23 01:01:27.017441: Epoch 7020 +2024-11-23 01:01:27.017555: Current learning rate: 0.00151 +2024-11-23 01:01:45.458201: train_loss -0.8317 +2024-11-23 01:01:45.458422: val_loss -0.765 +2024-11-23 01:01:45.458497: Pseudo dice [0.8589] +2024-11-23 01:01:45.458577: Epoch time: 18.44 s +2024-11-23 01:01:46.379589: +2024-11-23 01:01:46.379806: Epoch 7021 +2024-11-23 01:01:46.379922: Current learning rate: 0.00151 +2024-11-23 01:02:05.834648: train_loss -0.8261 +2024-11-23 01:02:05.834882: val_loss -0.76 +2024-11-23 01:02:05.834959: Pseudo dice [0.8621] +2024-11-23 01:02:05.835050: Epoch time: 19.46 s +2024-11-23 01:02:06.773597: +2024-11-23 01:02:06.773828: Epoch 7022 +2024-11-23 01:02:06.773945: Current learning rate: 0.00151 +2024-11-23 01:02:25.766858: train_loss -0.8135 +2024-11-23 01:02:25.767119: val_loss -0.7578 +2024-11-23 01:02:25.767196: Pseudo dice [0.8643] +2024-11-23 01:02:25.767277: Epoch time: 18.99 s +2024-11-23 01:02:26.777179: +2024-11-23 01:02:26.777417: Epoch 7023 +2024-11-23 01:02:26.777534: Current learning rate: 0.00151 +2024-11-23 01:02:45.527130: train_loss -0.8109 +2024-11-23 01:02:45.527354: val_loss -0.754 +2024-11-23 01:02:45.527432: Pseudo dice [0.8369] +2024-11-23 01:02:45.527508: Epoch time: 18.75 s +2024-11-23 01:02:46.569722: +2024-11-23 01:02:46.569936: Epoch 7024 +2024-11-23 01:02:46.570055: Current learning rate: 0.00151 +2024-11-23 01:03:05.814051: train_loss -0.8067 +2024-11-23 01:03:05.814270: val_loss -0.7378 +2024-11-23 01:03:05.814347: Pseudo dice [0.8426] +2024-11-23 01:03:05.814429: Epoch time: 19.25 s +2024-11-23 01:03:06.733863: +2024-11-23 01:03:06.734099: Epoch 7025 +2024-11-23 01:03:06.734209: Current learning rate: 0.0015 +2024-11-23 01:03:24.948972: train_loss -0.8159 +2024-11-23 01:03:24.949194: val_loss -0.7424 +2024-11-23 01:03:24.949272: Pseudo dice [0.8698] +2024-11-23 01:03:24.949354: Epoch time: 18.22 s +2024-11-23 01:03:25.874790: +2024-11-23 01:03:25.875007: Epoch 7026 +2024-11-23 01:03:25.875115: Current learning rate: 0.0015 +2024-11-23 01:03:43.724044: train_loss -0.8191 +2024-11-23 01:03:43.724288: val_loss -0.7337 +2024-11-23 01:03:43.724362: Pseudo dice [0.8325] +2024-11-23 01:03:43.724488: Epoch time: 17.85 s +2024-11-23 01:03:44.995860: +2024-11-23 01:03:44.996071: Epoch 7027 +2024-11-23 01:03:44.996185: Current learning rate: 0.0015 +2024-11-23 01:04:04.029293: train_loss -0.8249 +2024-11-23 01:04:04.029539: val_loss -0.7437 +2024-11-23 01:04:04.029619: Pseudo dice [0.8637] +2024-11-23 01:04:04.029697: Epoch time: 19.03 s +2024-11-23 01:04:04.945209: +2024-11-23 01:04:04.945445: Epoch 7028 +2024-11-23 01:04:04.945558: Current learning rate: 0.0015 +2024-11-23 01:04:23.531836: train_loss -0.8243 +2024-11-23 01:04:23.532069: val_loss -0.7938 +2024-11-23 01:04:23.532143: Pseudo dice [0.8721] +2024-11-23 01:04:23.532221: Epoch time: 18.59 s +2024-11-23 01:04:24.455783: +2024-11-23 01:04:24.456027: Epoch 7029 +2024-11-23 01:04:24.456143: Current learning rate: 0.0015 +2024-11-23 01:04:42.266750: train_loss -0.823 +2024-11-23 01:04:42.267007: val_loss -0.7386 +2024-11-23 01:04:42.267081: Pseudo dice [0.8405] +2024-11-23 01:04:42.267162: Epoch time: 17.81 s +2024-11-23 01:04:43.217965: +2024-11-23 01:04:43.218190: Epoch 7030 +2024-11-23 01:04:43.218303: Current learning rate: 0.0015 +2024-11-23 01:05:01.510510: train_loss -0.8278 +2024-11-23 01:05:01.510728: val_loss -0.7555 +2024-11-23 01:05:01.510804: Pseudo dice [0.8504] +2024-11-23 01:05:01.510881: Epoch time: 18.29 s +2024-11-23 01:05:02.433982: +2024-11-23 01:05:02.434218: Epoch 7031 +2024-11-23 01:05:02.434332: Current learning rate: 0.0015 +2024-11-23 01:05:20.588191: train_loss -0.8227 +2024-11-23 01:05:20.588413: val_loss -0.7779 +2024-11-23 01:05:20.590673: Pseudo dice [0.827] +2024-11-23 01:05:20.590772: Epoch time: 18.15 s +2024-11-23 01:05:21.537662: +2024-11-23 01:05:21.537871: Epoch 7032 +2024-11-23 01:05:21.537997: Current learning rate: 0.00149 +2024-11-23 01:05:40.735162: train_loss -0.8127 +2024-11-23 01:05:40.735387: val_loss -0.7313 +2024-11-23 01:05:40.735460: Pseudo dice [0.8439] +2024-11-23 01:05:40.735538: Epoch time: 19.2 s +2024-11-23 01:05:41.695060: +2024-11-23 01:05:41.695317: Epoch 7033 +2024-11-23 01:05:41.695431: Current learning rate: 0.00149 +2024-11-23 01:06:00.085398: train_loss -0.8114 +2024-11-23 01:06:00.085631: val_loss -0.7576 +2024-11-23 01:06:00.085701: Pseudo dice [0.8649] +2024-11-23 01:06:00.085777: Epoch time: 18.39 s +2024-11-23 01:06:01.042372: +2024-11-23 01:06:01.042592: Epoch 7034 +2024-11-23 01:06:01.042709: Current learning rate: 0.00149 +2024-11-23 01:06:19.430104: train_loss -0.8194 +2024-11-23 01:06:19.430330: val_loss -0.726 +2024-11-23 01:06:19.430415: Pseudo dice [0.8445] +2024-11-23 01:06:19.430494: Epoch time: 18.39 s +2024-11-23 01:06:20.453320: +2024-11-23 01:06:20.453531: Epoch 7035 +2024-11-23 01:06:20.453644: Current learning rate: 0.00149 +2024-11-23 01:06:39.252041: train_loss -0.8232 +2024-11-23 01:06:39.252264: val_loss -0.7603 +2024-11-23 01:06:39.252338: Pseudo dice [0.8287] +2024-11-23 01:06:39.252412: Epoch time: 18.8 s +2024-11-23 01:06:40.387057: +2024-11-23 01:06:40.387273: Epoch 7036 +2024-11-23 01:06:40.387383: Current learning rate: 0.00149 +2024-11-23 01:06:58.870031: train_loss -0.8234 +2024-11-23 01:06:58.870255: val_loss -0.7734 +2024-11-23 01:06:58.870331: Pseudo dice [0.8524] +2024-11-23 01:06:58.870406: Epoch time: 18.48 s +2024-11-23 01:06:59.792289: +2024-11-23 01:06:59.792507: Epoch 7037 +2024-11-23 01:06:59.792621: Current learning rate: 0.00149 +2024-11-23 01:07:18.504483: train_loss -0.8228 +2024-11-23 01:07:18.504733: val_loss -0.7497 +2024-11-23 01:07:18.504820: Pseudo dice [0.8586] +2024-11-23 01:07:18.504903: Epoch time: 18.71 s +2024-11-23 01:07:19.427213: +2024-11-23 01:07:19.427422: Epoch 7038 +2024-11-23 01:07:19.427538: Current learning rate: 0.00149 +2024-11-23 01:07:37.867676: train_loss -0.8248 +2024-11-23 01:07:37.867890: val_loss -0.7721 +2024-11-23 01:07:37.867962: Pseudo dice [0.8624] +2024-11-23 01:07:37.868044: Epoch time: 18.44 s +2024-11-23 01:07:39.199900: +2024-11-23 01:07:39.200129: Epoch 7039 +2024-11-23 01:07:39.200240: Current learning rate: 0.00148 +2024-11-23 01:07:57.844898: train_loss -0.8273 +2024-11-23 01:07:57.845131: val_loss -0.7584 +2024-11-23 01:07:57.845206: Pseudo dice [0.8573] +2024-11-23 01:07:57.845284: Epoch time: 18.65 s +2024-11-23 01:07:58.819415: +2024-11-23 01:07:58.819624: Epoch 7040 +2024-11-23 01:07:58.819735: Current learning rate: 0.00148 +2024-11-23 01:08:16.848492: train_loss -0.8246 +2024-11-23 01:08:16.848745: val_loss -0.7541 +2024-11-23 01:08:16.848821: Pseudo dice [0.851] +2024-11-23 01:08:16.848947: Epoch time: 18.03 s +2024-11-23 01:08:17.884007: +2024-11-23 01:08:17.884216: Epoch 7041 +2024-11-23 01:08:17.884326: Current learning rate: 0.00148 +2024-11-23 01:08:36.490732: train_loss -0.8246 +2024-11-23 01:08:36.490999: val_loss -0.7449 +2024-11-23 01:08:36.491077: Pseudo dice [0.8356] +2024-11-23 01:08:36.491160: Epoch time: 18.61 s +2024-11-23 01:08:37.410390: +2024-11-23 01:08:37.410604: Epoch 7042 +2024-11-23 01:08:37.410718: Current learning rate: 0.00148 +2024-11-23 01:08:57.295300: train_loss -0.8222 +2024-11-23 01:08:57.295521: val_loss -0.7329 +2024-11-23 01:08:57.295599: Pseudo dice [0.8416] +2024-11-23 01:08:57.295675: Epoch time: 19.89 s +2024-11-23 01:08:58.351907: +2024-11-23 01:08:58.352156: Epoch 7043 +2024-11-23 01:08:58.352271: Current learning rate: 0.00148 +2024-11-23 01:09:17.429420: train_loss -0.8266 +2024-11-23 01:09:17.429693: val_loss -0.7529 +2024-11-23 01:09:17.429770: Pseudo dice [0.8406] +2024-11-23 01:09:17.429847: Epoch time: 19.08 s +2024-11-23 01:09:18.346485: +2024-11-23 01:09:18.346703: Epoch 7044 +2024-11-23 01:09:18.346818: Current learning rate: 0.00148 +2024-11-23 01:09:37.304683: train_loss -0.8264 +2024-11-23 01:09:37.304933: val_loss -0.7384 +2024-11-23 01:09:37.305036: Pseudo dice [0.8534] +2024-11-23 01:09:37.305114: Epoch time: 18.96 s +2024-11-23 01:09:38.285990: +2024-11-23 01:09:38.286221: Epoch 7045 +2024-11-23 01:09:38.286338: Current learning rate: 0.00148 +2024-11-23 01:09:57.232873: train_loss -0.8163 +2024-11-23 01:09:57.233127: val_loss -0.7558 +2024-11-23 01:09:57.233278: Pseudo dice [0.8585] +2024-11-23 01:09:57.233366: Epoch time: 18.95 s +2024-11-23 01:09:58.156378: +2024-11-23 01:09:58.156603: Epoch 7046 +2024-11-23 01:09:58.156721: Current learning rate: 0.00148 +2024-11-23 01:10:17.558544: train_loss -0.8168 +2024-11-23 01:10:17.558780: val_loss -0.7449 +2024-11-23 01:10:17.558858: Pseudo dice [0.8445] +2024-11-23 01:10:17.558934: Epoch time: 19.4 s +2024-11-23 01:10:18.480238: +2024-11-23 01:10:18.480446: Epoch 7047 +2024-11-23 01:10:18.480556: Current learning rate: 0.00147 +2024-11-23 01:10:37.225895: train_loss -0.8173 +2024-11-23 01:10:37.226112: val_loss -0.7542 +2024-11-23 01:10:37.226188: Pseudo dice [0.8301] +2024-11-23 01:10:37.226268: Epoch time: 18.75 s +2024-11-23 01:10:38.248873: +2024-11-23 01:10:38.249089: Epoch 7048 +2024-11-23 01:10:38.249196: Current learning rate: 0.00147 +2024-11-23 01:10:56.366059: train_loss -0.821 +2024-11-23 01:10:56.366279: val_loss -0.7494 +2024-11-23 01:10:56.366354: Pseudo dice [0.8467] +2024-11-23 01:10:56.366431: Epoch time: 18.12 s +2024-11-23 01:10:57.277625: +2024-11-23 01:10:57.277908: Epoch 7049 +2024-11-23 01:10:57.278024: Current learning rate: 0.00147 +2024-11-23 01:11:16.615914: train_loss -0.8254 +2024-11-23 01:11:16.616228: val_loss -0.7511 +2024-11-23 01:11:16.616305: Pseudo dice [0.8249] +2024-11-23 01:11:16.616388: Epoch time: 19.34 s +2024-11-23 01:11:18.231016: +2024-11-23 01:11:18.231228: Epoch 7050 +2024-11-23 01:11:18.231343: Current learning rate: 0.00147 +2024-11-23 01:11:37.151989: train_loss -0.8239 +2024-11-23 01:11:37.152236: val_loss -0.7436 +2024-11-23 01:11:37.152319: Pseudo dice [0.8578] +2024-11-23 01:11:37.152400: Epoch time: 18.92 s +2024-11-23 01:11:38.186321: +2024-11-23 01:11:38.186535: Epoch 7051 +2024-11-23 01:11:38.186648: Current learning rate: 0.00147 +2024-11-23 01:11:57.603241: train_loss -0.825 +2024-11-23 01:11:57.603473: val_loss -0.7721 +2024-11-23 01:11:57.603554: Pseudo dice [0.8553] +2024-11-23 01:11:57.603639: Epoch time: 19.42 s +2024-11-23 01:11:58.580899: +2024-11-23 01:11:58.581139: Epoch 7052 +2024-11-23 01:11:58.581251: Current learning rate: 0.00147 +2024-11-23 01:12:16.747306: train_loss -0.8299 +2024-11-23 01:12:16.747630: val_loss -0.7837 +2024-11-23 01:12:16.747714: Pseudo dice [0.8621] +2024-11-23 01:12:16.747796: Epoch time: 18.17 s +2024-11-23 01:12:17.673560: +2024-11-23 01:12:17.673780: Epoch 7053 +2024-11-23 01:12:17.673892: Current learning rate: 0.00147 +2024-11-23 01:12:36.616441: train_loss -0.8261 +2024-11-23 01:12:36.616746: val_loss -0.7421 +2024-11-23 01:12:36.616826: Pseudo dice [0.8393] +2024-11-23 01:12:36.616905: Epoch time: 18.94 s +2024-11-23 01:12:37.542934: +2024-11-23 01:12:37.543215: Epoch 7054 +2024-11-23 01:12:37.543330: Current learning rate: 0.00146 +2024-11-23 01:12:57.004149: train_loss -0.8129 +2024-11-23 01:12:57.004376: val_loss -0.7637 +2024-11-23 01:12:57.004454: Pseudo dice [0.8593] +2024-11-23 01:12:57.004537: Epoch time: 19.46 s +2024-11-23 01:12:58.256257: +2024-11-23 01:12:58.256480: Epoch 7055 +2024-11-23 01:12:58.256590: Current learning rate: 0.00146 +2024-11-23 01:13:17.481664: train_loss -0.8105 +2024-11-23 01:13:17.481923: val_loss -0.7697 +2024-11-23 01:13:17.483832: Pseudo dice [0.8608] +2024-11-23 01:13:17.483969: Epoch time: 19.23 s +2024-11-23 01:13:18.406770: +2024-11-23 01:13:18.407002: Epoch 7056 +2024-11-23 01:13:18.407119: Current learning rate: 0.00146 +2024-11-23 01:13:37.181923: train_loss -0.8205 +2024-11-23 01:13:37.182191: val_loss -0.7137 +2024-11-23 01:13:37.182284: Pseudo dice [0.8437] +2024-11-23 01:13:37.182369: Epoch time: 18.78 s +2024-11-23 01:13:38.107280: +2024-11-23 01:13:38.107493: Epoch 7057 +2024-11-23 01:13:38.107605: Current learning rate: 0.00146 +2024-11-23 01:13:57.602262: train_loss -0.8187 +2024-11-23 01:13:57.602502: val_loss -0.7745 +2024-11-23 01:13:57.602640: Pseudo dice [0.8639] +2024-11-23 01:13:57.602719: Epoch time: 19.5 s +2024-11-23 01:13:58.524346: +2024-11-23 01:13:58.524604: Epoch 7058 +2024-11-23 01:13:58.524716: Current learning rate: 0.00146 +2024-11-23 01:14:17.497046: train_loss -0.8144 +2024-11-23 01:14:17.497271: val_loss -0.7529 +2024-11-23 01:14:17.497347: Pseudo dice [0.8529] +2024-11-23 01:14:17.497424: Epoch time: 18.97 s +2024-11-23 01:14:18.411754: +2024-11-23 01:14:18.411969: Epoch 7059 +2024-11-23 01:14:18.412086: Current learning rate: 0.00146 +2024-11-23 01:14:37.251296: train_loss -0.8211 +2024-11-23 01:14:37.251514: val_loss -0.7763 +2024-11-23 01:14:37.251591: Pseudo dice [0.8399] +2024-11-23 01:14:37.251667: Epoch time: 18.84 s +2024-11-23 01:14:38.170021: +2024-11-23 01:14:38.170237: Epoch 7060 +2024-11-23 01:14:38.170352: Current learning rate: 0.00146 +2024-11-23 01:14:57.171088: train_loss -0.8273 +2024-11-23 01:14:57.171379: val_loss -0.76 +2024-11-23 01:14:57.171460: Pseudo dice [0.8374] +2024-11-23 01:14:57.171538: Epoch time: 19.0 s +2024-11-23 01:14:58.092261: +2024-11-23 01:14:58.092525: Epoch 7061 +2024-11-23 01:14:58.092638: Current learning rate: 0.00145 +2024-11-23 01:15:17.172367: train_loss -0.8202 +2024-11-23 01:15:17.172632: val_loss -0.7511 +2024-11-23 01:15:17.172713: Pseudo dice [0.8547] +2024-11-23 01:15:17.172792: Epoch time: 19.08 s +2024-11-23 01:15:18.097282: +2024-11-23 01:15:18.097493: Epoch 7062 +2024-11-23 01:15:18.097606: Current learning rate: 0.00145 +2024-11-23 01:15:38.402266: train_loss -0.8256 +2024-11-23 01:15:38.407674: val_loss -0.7504 +2024-11-23 01:15:38.407792: Pseudo dice [0.8396] +2024-11-23 01:15:38.407875: Epoch time: 20.31 s +2024-11-23 01:15:39.518197: +2024-11-23 01:15:39.518396: Epoch 7063 +2024-11-23 01:15:39.518505: Current learning rate: 0.00145 +2024-11-23 01:15:57.973256: train_loss -0.8183 +2024-11-23 01:15:57.973513: val_loss -0.7445 +2024-11-23 01:15:57.973618: Pseudo dice [0.8547] +2024-11-23 01:15:57.973709: Epoch time: 18.46 s +2024-11-23 01:15:58.892448: +2024-11-23 01:15:58.892680: Epoch 7064 +2024-11-23 01:15:58.892797: Current learning rate: 0.00145 +2024-11-23 01:16:18.191827: train_loss -0.8158 +2024-11-23 01:16:18.192057: val_loss -0.7736 +2024-11-23 01:16:18.192133: Pseudo dice [0.855] +2024-11-23 01:16:18.192207: Epoch time: 19.3 s +2024-11-23 01:16:19.110609: +2024-11-23 01:16:19.110920: Epoch 7065 +2024-11-23 01:16:19.111041: Current learning rate: 0.00145 +2024-11-23 01:16:37.802266: train_loss -0.8204 +2024-11-23 01:16:37.802534: val_loss -0.761 +2024-11-23 01:16:37.802613: Pseudo dice [0.8346] +2024-11-23 01:16:37.802695: Epoch time: 18.69 s +2024-11-23 01:16:38.730946: +2024-11-23 01:16:38.731220: Epoch 7066 +2024-11-23 01:16:38.731328: Current learning rate: 0.00145 +2024-11-23 01:16:56.756413: train_loss -0.8272 +2024-11-23 01:16:56.756671: val_loss -0.7488 +2024-11-23 01:16:56.756745: Pseudo dice [0.8405] +2024-11-23 01:16:56.756825: Epoch time: 18.03 s +2024-11-23 01:16:57.680613: +2024-11-23 01:16:57.680819: Epoch 7067 +2024-11-23 01:16:57.680927: Current learning rate: 0.00145 +2024-11-23 01:17:16.043494: train_loss -0.8187 +2024-11-23 01:17:16.043717: val_loss -0.7783 +2024-11-23 01:17:16.043793: Pseudo dice [0.8469] +2024-11-23 01:17:16.043873: Epoch time: 18.36 s +2024-11-23 01:17:16.966762: +2024-11-23 01:17:16.966987: Epoch 7068 +2024-11-23 01:17:16.967112: Current learning rate: 0.00144 +2024-11-23 01:17:34.847920: train_loss -0.8225 +2024-11-23 01:17:34.848174: val_loss -0.7417 +2024-11-23 01:17:34.848250: Pseudo dice [0.8652] +2024-11-23 01:17:34.851426: Epoch time: 17.88 s +2024-11-23 01:17:35.773075: +2024-11-23 01:17:35.773280: Epoch 7069 +2024-11-23 01:17:35.773393: Current learning rate: 0.00144 +2024-11-23 01:17:54.898148: train_loss -0.8221 +2024-11-23 01:17:54.898373: val_loss -0.764 +2024-11-23 01:17:54.898447: Pseudo dice [0.8449] +2024-11-23 01:17:54.898526: Epoch time: 19.13 s +2024-11-23 01:17:55.826955: +2024-11-23 01:17:55.827156: Epoch 7070 +2024-11-23 01:17:55.827269: Current learning rate: 0.00144 +2024-11-23 01:18:14.454259: train_loss -0.8178 +2024-11-23 01:18:14.454489: val_loss -0.739 +2024-11-23 01:18:14.454564: Pseudo dice [0.8111] +2024-11-23 01:18:14.454646: Epoch time: 18.63 s +2024-11-23 01:18:15.374146: +2024-11-23 01:18:15.374354: Epoch 7071 +2024-11-23 01:18:15.374470: Current learning rate: 0.00144 +2024-11-23 01:18:33.965740: train_loss -0.8206 +2024-11-23 01:18:33.966003: val_loss -0.7621 +2024-11-23 01:18:33.966084: Pseudo dice [0.8289] +2024-11-23 01:18:33.966165: Epoch time: 18.59 s +2024-11-23 01:18:34.890451: +2024-11-23 01:18:34.890704: Epoch 7072 +2024-11-23 01:18:34.890813: Current learning rate: 0.00144 +2024-11-23 01:18:53.378239: train_loss -0.8232 +2024-11-23 01:18:53.378458: val_loss -0.7654 +2024-11-23 01:18:53.378536: Pseudo dice [0.8297] +2024-11-23 01:18:53.378613: Epoch time: 18.49 s +2024-11-23 01:18:54.751814: +2024-11-23 01:18:54.752018: Epoch 7073 +2024-11-23 01:18:54.752127: Current learning rate: 0.00144 +2024-11-23 01:19:13.959601: train_loss -0.821 +2024-11-23 01:19:13.959830: val_loss -0.7567 +2024-11-23 01:19:13.959903: Pseudo dice [0.8513] +2024-11-23 01:19:13.959978: Epoch time: 19.21 s +2024-11-23 01:19:14.885725: +2024-11-23 01:19:14.885932: Epoch 7074 +2024-11-23 01:19:14.886051: Current learning rate: 0.00144 +2024-11-23 01:19:33.392215: train_loss -0.8213 +2024-11-23 01:19:33.392433: val_loss -0.7722 +2024-11-23 01:19:33.394716: Pseudo dice [0.8537] +2024-11-23 01:19:33.394833: Epoch time: 18.51 s +2024-11-23 01:19:34.352051: +2024-11-23 01:19:34.352281: Epoch 7075 +2024-11-23 01:19:34.352393: Current learning rate: 0.00143 +2024-11-23 01:19:52.809937: train_loss -0.8287 +2024-11-23 01:19:52.810197: val_loss -0.7703 +2024-11-23 01:19:52.810271: Pseudo dice [0.8551] +2024-11-23 01:19:52.810349: Epoch time: 18.46 s +2024-11-23 01:19:53.773402: +2024-11-23 01:19:53.773627: Epoch 7076 +2024-11-23 01:19:53.773736: Current learning rate: 0.00143 +2024-11-23 01:20:13.137979: train_loss -0.811 +2024-11-23 01:20:13.138236: val_loss -0.778 +2024-11-23 01:20:13.138324: Pseudo dice [0.8496] +2024-11-23 01:20:13.138439: Epoch time: 19.37 s +2024-11-23 01:20:14.059071: +2024-11-23 01:20:14.059274: Epoch 7077 +2024-11-23 01:20:14.059392: Current learning rate: 0.00143 +2024-11-23 01:20:33.372250: train_loss -0.8064 +2024-11-23 01:20:33.372472: val_loss -0.7438 +2024-11-23 01:20:33.372552: Pseudo dice [0.8306] +2024-11-23 01:20:33.372631: Epoch time: 19.31 s +2024-11-23 01:20:34.296577: +2024-11-23 01:20:34.296812: Epoch 7078 +2024-11-23 01:20:34.296932: Current learning rate: 0.00143 +2024-11-23 01:20:52.577203: train_loss -0.8121 +2024-11-23 01:20:52.577422: val_loss -0.7792 +2024-11-23 01:20:52.577495: Pseudo dice [0.8508] +2024-11-23 01:20:52.577569: Epoch time: 18.28 s +2024-11-23 01:20:53.503114: +2024-11-23 01:20:53.503321: Epoch 7079 +2024-11-23 01:20:53.503431: Current learning rate: 0.00143 +2024-11-23 01:21:12.762515: train_loss -0.8155 +2024-11-23 01:21:12.762766: val_loss -0.756 +2024-11-23 01:21:12.762842: Pseudo dice [0.8692] +2024-11-23 01:21:12.762926: Epoch time: 19.26 s +2024-11-23 01:21:13.693447: +2024-11-23 01:21:13.693681: Epoch 7080 +2024-11-23 01:21:13.693785: Current learning rate: 0.00143 +2024-11-23 01:21:33.258303: train_loss -0.8199 +2024-11-23 01:21:33.258514: val_loss -0.7539 +2024-11-23 01:21:33.258587: Pseudo dice [0.8567] +2024-11-23 01:21:33.258661: Epoch time: 19.57 s +2024-11-23 01:21:34.179766: +2024-11-23 01:21:34.179981: Epoch 7081 +2024-11-23 01:21:34.180092: Current learning rate: 0.00143 +2024-11-23 01:21:51.990098: train_loss -0.8255 +2024-11-23 01:21:51.990340: val_loss -0.7449 +2024-11-23 01:21:51.990417: Pseudo dice [0.8457] +2024-11-23 01:21:51.990494: Epoch time: 17.81 s +2024-11-23 01:21:52.917918: +2024-11-23 01:21:52.918140: Epoch 7082 +2024-11-23 01:21:52.918249: Current learning rate: 0.00142 +2024-11-23 01:22:12.022481: train_loss -0.821 +2024-11-23 01:22:12.022705: val_loss -0.7777 +2024-11-23 01:22:12.022781: Pseudo dice [0.8528] +2024-11-23 01:22:12.022865: Epoch time: 19.11 s +2024-11-23 01:22:12.963766: +2024-11-23 01:22:12.963958: Epoch 7083 +2024-11-23 01:22:12.964071: Current learning rate: 0.00142 +2024-11-23 01:22:31.491372: train_loss -0.8364 +2024-11-23 01:22:31.491626: val_loss -0.784 +2024-11-23 01:22:31.491702: Pseudo dice [0.8628] +2024-11-23 01:22:31.491789: Epoch time: 18.53 s +2024-11-23 01:22:32.412711: +2024-11-23 01:22:32.412909: Epoch 7084 +2024-11-23 01:22:32.413023: Current learning rate: 0.00142 +2024-11-23 01:22:51.194451: train_loss -0.8209 +2024-11-23 01:22:51.194723: val_loss -0.7794 +2024-11-23 01:22:51.194822: Pseudo dice [0.8512] +2024-11-23 01:22:51.194904: Epoch time: 18.78 s +2024-11-23 01:22:52.110822: +2024-11-23 01:22:52.111059: Epoch 7085 +2024-11-23 01:22:52.111176: Current learning rate: 0.00142 +2024-11-23 01:23:12.088715: train_loss -0.8156 +2024-11-23 01:23:12.088931: val_loss -0.7191 +2024-11-23 01:23:12.089010: Pseudo dice [0.837] +2024-11-23 01:23:12.089084: Epoch time: 19.98 s +2024-11-23 01:23:13.168668: +2024-11-23 01:23:13.168891: Epoch 7086 +2024-11-23 01:23:13.169004: Current learning rate: 0.00142 +2024-11-23 01:23:32.623518: train_loss -0.821 +2024-11-23 01:23:32.623778: val_loss -0.7379 +2024-11-23 01:23:32.623859: Pseudo dice [0.833] +2024-11-23 01:23:32.623947: Epoch time: 19.46 s +2024-11-23 01:23:33.560144: +2024-11-23 01:23:33.560378: Epoch 7087 +2024-11-23 01:23:33.560495: Current learning rate: 0.00142 +2024-11-23 01:23:51.935628: train_loss -0.8153 +2024-11-23 01:23:51.935836: val_loss -0.7503 +2024-11-23 01:23:51.935938: Pseudo dice [0.8496] +2024-11-23 01:23:51.936018: Epoch time: 18.38 s +2024-11-23 01:23:52.845895: +2024-11-23 01:23:52.846128: Epoch 7088 +2024-11-23 01:23:52.846245: Current learning rate: 0.00142 +2024-11-23 01:24:11.158638: train_loss -0.8268 +2024-11-23 01:24:11.158849: val_loss -0.7413 +2024-11-23 01:24:11.158924: Pseudo dice [0.8687] +2024-11-23 01:24:11.159025: Epoch time: 18.31 s +2024-11-23 01:24:12.075097: +2024-11-23 01:24:12.075332: Epoch 7089 +2024-11-23 01:24:12.075445: Current learning rate: 0.00142 +2024-11-23 01:24:31.288685: train_loss -0.8226 +2024-11-23 01:24:31.288922: val_loss -0.7226 +2024-11-23 01:24:31.289011: Pseudo dice [0.7994] +2024-11-23 01:24:31.289092: Epoch time: 19.21 s +2024-11-23 01:24:32.236838: +2024-11-23 01:24:32.237047: Epoch 7090 +2024-11-23 01:24:32.237279: Current learning rate: 0.00141 +2024-11-23 01:24:51.711364: train_loss -0.8193 +2024-11-23 01:24:51.711683: val_loss -0.7825 +2024-11-23 01:24:51.711759: Pseudo dice [0.8419] +2024-11-23 01:24:51.711842: Epoch time: 19.48 s +2024-11-23 01:24:52.626573: +2024-11-23 01:24:52.626825: Epoch 7091 +2024-11-23 01:24:52.626939: Current learning rate: 0.00141 +2024-11-23 01:25:11.628380: train_loss -0.8171 +2024-11-23 01:25:11.628624: val_loss -0.7555 +2024-11-23 01:25:11.628700: Pseudo dice [0.8437] +2024-11-23 01:25:11.628778: Epoch time: 19.0 s +2024-11-23 01:25:12.541386: +2024-11-23 01:25:12.541608: Epoch 7092 +2024-11-23 01:25:12.541723: Current learning rate: 0.00141 +2024-11-23 01:25:31.954733: train_loss -0.8202 +2024-11-23 01:25:31.957173: val_loss -0.7173 +2024-11-23 01:25:31.957273: Pseudo dice [0.848] +2024-11-23 01:25:31.957352: Epoch time: 19.41 s +2024-11-23 01:25:33.070351: +2024-11-23 01:25:33.070568: Epoch 7093 +2024-11-23 01:25:33.070680: Current learning rate: 0.00141 +2024-11-23 01:25:50.785742: train_loss -0.8137 +2024-11-23 01:25:50.785969: val_loss -0.7665 +2024-11-23 01:25:50.786055: Pseudo dice [0.8389] +2024-11-23 01:25:50.786133: Epoch time: 17.72 s +2024-11-23 01:25:51.701858: +2024-11-23 01:25:51.702075: Epoch 7094 +2024-11-23 01:25:51.702185: Current learning rate: 0.00141 +2024-11-23 01:26:11.022121: train_loss -0.8221 +2024-11-23 01:26:11.022352: val_loss -0.7442 +2024-11-23 01:26:11.022434: Pseudo dice [0.8611] +2024-11-23 01:26:11.022511: Epoch time: 19.32 s +2024-11-23 01:26:11.993987: +2024-11-23 01:26:11.994224: Epoch 7095 +2024-11-23 01:26:11.994393: Current learning rate: 0.00141 +2024-11-23 01:26:31.355730: train_loss -0.8221 +2024-11-23 01:26:31.355955: val_loss -0.7442 +2024-11-23 01:26:31.356041: Pseudo dice [0.8317] +2024-11-23 01:26:31.356122: Epoch time: 19.36 s +2024-11-23 01:26:32.651063: +2024-11-23 01:26:32.651271: Epoch 7096 +2024-11-23 01:26:32.651385: Current learning rate: 0.00141 +2024-11-23 01:26:51.645147: train_loss -0.8228 +2024-11-23 01:26:51.645367: val_loss -0.7557 +2024-11-23 01:26:51.645442: Pseudo dice [0.8316] +2024-11-23 01:26:51.645517: Epoch time: 18.99 s +2024-11-23 01:26:52.568398: +2024-11-23 01:26:52.568612: Epoch 7097 +2024-11-23 01:26:52.568724: Current learning rate: 0.0014 +2024-11-23 01:27:12.131025: train_loss -0.8259 +2024-11-23 01:27:12.131249: val_loss -0.7684 +2024-11-23 01:27:12.131324: Pseudo dice [0.8532] +2024-11-23 01:27:12.131403: Epoch time: 19.56 s +2024-11-23 01:27:13.054375: +2024-11-23 01:27:13.054610: Epoch 7098 +2024-11-23 01:27:13.054721: Current learning rate: 0.0014 +2024-11-23 01:27:31.008765: train_loss -0.8225 +2024-11-23 01:27:31.009009: val_loss -0.7545 +2024-11-23 01:27:31.009104: Pseudo dice [0.8429] +2024-11-23 01:27:31.009185: Epoch time: 17.96 s +2024-11-23 01:27:31.932346: +2024-11-23 01:27:31.932595: Epoch 7099 +2024-11-23 01:27:31.932709: Current learning rate: 0.0014 +2024-11-23 01:27:49.431701: train_loss -0.8273 +2024-11-23 01:27:49.431923: val_loss -0.7361 +2024-11-23 01:27:49.432073: Pseudo dice [0.8365] +2024-11-23 01:27:49.432156: Epoch time: 17.5 s +2024-11-23 01:27:50.709469: +2024-11-23 01:27:50.709703: Epoch 7100 +2024-11-23 01:27:50.709822: Current learning rate: 0.0014 +2024-11-23 01:28:10.074720: train_loss -0.8214 +2024-11-23 01:28:10.074944: val_loss -0.765 +2024-11-23 01:28:10.075036: Pseudo dice [0.8578] +2024-11-23 01:28:10.075116: Epoch time: 19.37 s +2024-11-23 01:28:10.999299: +2024-11-23 01:28:10.999513: Epoch 7101 +2024-11-23 01:28:10.999626: Current learning rate: 0.0014 +2024-11-23 01:28:30.151049: train_loss -0.8232 +2024-11-23 01:28:30.151282: val_loss -0.7657 +2024-11-23 01:28:30.151359: Pseudo dice [0.8702] +2024-11-23 01:28:30.151442: Epoch time: 19.15 s +2024-11-23 01:28:31.118825: +2024-11-23 01:28:31.119201: Epoch 7102 +2024-11-23 01:28:31.119314: Current learning rate: 0.0014 +2024-11-23 01:28:48.160756: train_loss -0.8291 +2024-11-23 01:28:48.161043: val_loss -0.7639 +2024-11-23 01:28:48.161123: Pseudo dice [0.8638] +2024-11-23 01:28:48.161207: Epoch time: 17.04 s +2024-11-23 01:28:49.099110: +2024-11-23 01:28:49.099324: Epoch 7103 +2024-11-23 01:28:49.099432: Current learning rate: 0.0014 +2024-11-23 01:29:08.052640: train_loss -0.8198 +2024-11-23 01:29:08.052860: val_loss -0.7802 +2024-11-23 01:29:08.052958: Pseudo dice [0.8582] +2024-11-23 01:29:08.053039: Epoch time: 18.95 s +2024-11-23 01:29:08.982527: +2024-11-23 01:29:08.982819: Epoch 7104 +2024-11-23 01:29:08.982929: Current learning rate: 0.00139 +2024-11-23 01:29:27.543586: train_loss -0.8283 +2024-11-23 01:29:27.543817: val_loss -0.7543 +2024-11-23 01:29:27.543892: Pseudo dice [0.8373] +2024-11-23 01:29:27.549083: Epoch time: 18.56 s +2024-11-23 01:29:28.629647: +2024-11-23 01:29:28.629851: Epoch 7105 +2024-11-23 01:29:28.629963: Current learning rate: 0.00139 +2024-11-23 01:29:46.159415: train_loss -0.8225 +2024-11-23 01:29:46.159647: val_loss -0.7176 +2024-11-23 01:29:46.159738: Pseudo dice [0.8332] +2024-11-23 01:29:46.159881: Epoch time: 17.53 s +2024-11-23 01:29:47.084558: +2024-11-23 01:29:47.084752: Epoch 7106 +2024-11-23 01:29:47.084862: Current learning rate: 0.00139 +2024-11-23 01:30:05.638751: train_loss -0.8183 +2024-11-23 01:30:05.639019: val_loss -0.7605 +2024-11-23 01:30:05.639102: Pseudo dice [0.871] +2024-11-23 01:30:05.639189: Epoch time: 18.55 s +2024-11-23 01:30:06.965270: +2024-11-23 01:30:06.965468: Epoch 7107 +2024-11-23 01:30:06.965578: Current learning rate: 0.00139 +2024-11-23 01:30:26.006586: train_loss -0.8244 +2024-11-23 01:30:26.006837: val_loss -0.7778 +2024-11-23 01:30:26.006918: Pseudo dice [0.8658] +2024-11-23 01:30:26.007002: Epoch time: 19.04 s +2024-11-23 01:30:26.926733: +2024-11-23 01:30:26.926976: Epoch 7108 +2024-11-23 01:30:26.927099: Current learning rate: 0.00139 +2024-11-23 01:30:46.017942: train_loss -0.8229 +2024-11-23 01:30:46.018179: val_loss -0.7329 +2024-11-23 01:30:46.018257: Pseudo dice [0.8447] +2024-11-23 01:30:46.018336: Epoch time: 19.09 s +2024-11-23 01:30:46.954257: +2024-11-23 01:30:46.954484: Epoch 7109 +2024-11-23 01:30:46.954595: Current learning rate: 0.00139 +2024-11-23 01:31:05.081704: train_loss -0.8302 +2024-11-23 01:31:05.081950: val_loss -0.7584 +2024-11-23 01:31:05.082101: Pseudo dice [0.8374] +2024-11-23 01:31:05.082185: Epoch time: 18.13 s +2024-11-23 01:31:06.013481: +2024-11-23 01:31:06.013683: Epoch 7110 +2024-11-23 01:31:06.013795: Current learning rate: 0.00139 +2024-11-23 01:31:24.515876: train_loss -0.8138 +2024-11-23 01:31:24.516112: val_loss -0.7454 +2024-11-23 01:31:24.516187: Pseudo dice [0.8462] +2024-11-23 01:31:24.518488: Epoch time: 18.5 s +2024-11-23 01:31:25.512972: +2024-11-23 01:31:25.513195: Epoch 7111 +2024-11-23 01:31:25.513306: Current learning rate: 0.00138 +2024-11-23 01:31:44.596051: train_loss -0.8117 +2024-11-23 01:31:44.596268: val_loss -0.7579 +2024-11-23 01:31:44.596340: Pseudo dice [0.8424] +2024-11-23 01:31:44.596415: Epoch time: 19.08 s +2024-11-23 01:31:45.569792: +2024-11-23 01:31:45.570014: Epoch 7112 +2024-11-23 01:31:45.570139: Current learning rate: 0.00138 +2024-11-23 01:32:04.731544: train_loss -0.8196 +2024-11-23 01:32:04.731763: val_loss -0.7676 +2024-11-23 01:32:04.731841: Pseudo dice [0.8601] +2024-11-23 01:32:04.731915: Epoch time: 19.16 s +2024-11-23 01:32:05.647932: +2024-11-23 01:32:05.648204: Epoch 7113 +2024-11-23 01:32:05.648315: Current learning rate: 0.00138 +2024-11-23 01:32:24.811856: train_loss -0.8172 +2024-11-23 01:32:24.812113: val_loss -0.7593 +2024-11-23 01:32:24.812187: Pseudo dice [0.8498] +2024-11-23 01:32:24.812269: Epoch time: 19.16 s +2024-11-23 01:32:25.732847: +2024-11-23 01:32:25.733062: Epoch 7114 +2024-11-23 01:32:25.733175: Current learning rate: 0.00138 +2024-11-23 01:32:43.850730: train_loss -0.82 +2024-11-23 01:32:43.856144: val_loss -0.768 +2024-11-23 01:32:43.856281: Pseudo dice [0.8446] +2024-11-23 01:32:43.856361: Epoch time: 18.12 s +2024-11-23 01:32:44.799855: +2024-11-23 01:32:44.800089: Epoch 7115 +2024-11-23 01:32:44.800202: Current learning rate: 0.00138 +2024-11-23 01:33:02.228352: train_loss -0.8225 +2024-11-23 01:33:02.228595: val_loss -0.7529 +2024-11-23 01:33:02.228672: Pseudo dice [0.8691] +2024-11-23 01:33:02.228749: Epoch time: 17.43 s +2024-11-23 01:33:03.147275: +2024-11-23 01:33:03.147487: Epoch 7116 +2024-11-23 01:33:03.147722: Current learning rate: 0.00138 +2024-11-23 01:33:22.636909: train_loss -0.8171 +2024-11-23 01:33:22.637140: val_loss -0.755 +2024-11-23 01:33:22.637217: Pseudo dice [0.8602] +2024-11-23 01:33:22.637292: Epoch time: 19.49 s +2024-11-23 01:33:23.552128: +2024-11-23 01:33:23.552328: Epoch 7117 +2024-11-23 01:33:23.552438: Current learning rate: 0.00138 +2024-11-23 01:33:41.498856: train_loss -0.8248 +2024-11-23 01:33:41.499132: val_loss -0.7512 +2024-11-23 01:33:41.499217: Pseudo dice [0.8408] +2024-11-23 01:33:41.499301: Epoch time: 17.95 s +2024-11-23 01:33:42.434003: +2024-11-23 01:33:42.434231: Epoch 7118 +2024-11-23 01:33:42.434343: Current learning rate: 0.00137 +2024-11-23 01:34:01.528426: train_loss -0.8144 +2024-11-23 01:34:01.528648: val_loss -0.7547 +2024-11-23 01:34:01.528724: Pseudo dice [0.857] +2024-11-23 01:34:01.528802: Epoch time: 19.1 s +2024-11-23 01:34:02.869155: +2024-11-23 01:34:02.869352: Epoch 7119 +2024-11-23 01:34:02.869461: Current learning rate: 0.00137 +2024-11-23 01:34:22.159374: train_loss -0.8229 +2024-11-23 01:34:22.159606: val_loss -0.7687 +2024-11-23 01:34:22.159683: Pseudo dice [0.8473] +2024-11-23 01:34:22.162005: Epoch time: 19.29 s +2024-11-23 01:34:23.115758: +2024-11-23 01:34:23.116056: Epoch 7120 +2024-11-23 01:34:23.116169: Current learning rate: 0.00137 +2024-11-23 01:34:41.408673: train_loss -0.8243 +2024-11-23 01:34:41.408898: val_loss -0.7873 +2024-11-23 01:34:41.408972: Pseudo dice [0.8693] +2024-11-23 01:34:41.409054: Epoch time: 18.29 s +2024-11-23 01:34:42.325212: +2024-11-23 01:34:42.325414: Epoch 7121 +2024-11-23 01:34:42.325522: Current learning rate: 0.00137 +2024-11-23 01:35:00.937830: train_loss -0.8136 +2024-11-23 01:35:00.938137: val_loss -0.737 +2024-11-23 01:35:00.938215: Pseudo dice [0.853] +2024-11-23 01:35:00.938294: Epoch time: 18.61 s +2024-11-23 01:35:01.866965: +2024-11-23 01:35:01.867178: Epoch 7122 +2024-11-23 01:35:01.867288: Current learning rate: 0.00137 +2024-11-23 01:35:19.832602: train_loss -0.8192 +2024-11-23 01:35:19.832821: val_loss -0.7642 +2024-11-23 01:35:19.832895: Pseudo dice [0.8657] +2024-11-23 01:35:19.832971: Epoch time: 17.97 s +2024-11-23 01:35:20.759180: +2024-11-23 01:35:20.759386: Epoch 7123 +2024-11-23 01:35:20.759499: Current learning rate: 0.00137 +2024-11-23 01:35:39.020527: train_loss -0.8238 +2024-11-23 01:35:39.020761: val_loss -0.775 +2024-11-23 01:35:39.020843: Pseudo dice [0.8469] +2024-11-23 01:35:39.020924: Epoch time: 18.26 s +2024-11-23 01:35:39.942649: +2024-11-23 01:35:39.942877: Epoch 7124 +2024-11-23 01:35:39.942995: Current learning rate: 0.00137 +2024-11-23 01:36:00.444688: train_loss -0.8175 +2024-11-23 01:36:00.444908: val_loss -0.752 +2024-11-23 01:36:00.444983: Pseudo dice [0.8358] +2024-11-23 01:36:00.445066: Epoch time: 20.5 s +2024-11-23 01:36:01.363235: +2024-11-23 01:36:01.363542: Epoch 7125 +2024-11-23 01:36:01.363652: Current learning rate: 0.00136 +2024-11-23 01:36:19.688639: train_loss -0.8133 +2024-11-23 01:36:19.688887: val_loss -0.7457 +2024-11-23 01:36:19.688962: Pseudo dice [0.852] +2024-11-23 01:36:19.689048: Epoch time: 18.33 s +2024-11-23 01:36:20.607575: +2024-11-23 01:36:20.607792: Epoch 7126 +2024-11-23 01:36:20.607906: Current learning rate: 0.00136 +2024-11-23 01:36:38.731253: train_loss -0.8266 +2024-11-23 01:36:38.731479: val_loss -0.7492 +2024-11-23 01:36:38.731561: Pseudo dice [0.8367] +2024-11-23 01:36:38.731640: Epoch time: 18.12 s +2024-11-23 01:36:39.749798: +2024-11-23 01:36:39.750002: Epoch 7127 +2024-11-23 01:36:39.750112: Current learning rate: 0.00136 +2024-11-23 01:36:57.672003: train_loss -0.8216 +2024-11-23 01:36:57.672233: val_loss -0.7413 +2024-11-23 01:36:57.672310: Pseudo dice [0.85] +2024-11-23 01:36:57.672388: Epoch time: 17.92 s +2024-11-23 01:36:58.599859: +2024-11-23 01:36:58.600064: Epoch 7128 +2024-11-23 01:36:58.600171: Current learning rate: 0.00136 +2024-11-23 01:37:17.283542: train_loss -0.8239 +2024-11-23 01:37:17.283772: val_loss -0.7517 +2024-11-23 01:37:17.283847: Pseudo dice [0.8528] +2024-11-23 01:37:17.283932: Epoch time: 18.68 s +2024-11-23 01:37:18.209848: +2024-11-23 01:37:18.210182: Epoch 7129 +2024-11-23 01:37:18.210294: Current learning rate: 0.00136 +2024-11-23 01:37:36.189546: train_loss -0.8253 +2024-11-23 01:37:36.189798: val_loss -0.7656 +2024-11-23 01:37:36.189875: Pseudo dice [0.8736] +2024-11-23 01:37:36.189954: Epoch time: 17.98 s +2024-11-23 01:37:37.493305: +2024-11-23 01:37:37.493536: Epoch 7130 +2024-11-23 01:37:37.493651: Current learning rate: 0.00136 +2024-11-23 01:37:56.204138: train_loss -0.8255 +2024-11-23 01:37:56.204403: val_loss -0.7571 +2024-11-23 01:37:56.204549: Pseudo dice [0.8447] +2024-11-23 01:37:56.204631: Epoch time: 18.71 s +2024-11-23 01:37:57.134294: +2024-11-23 01:37:57.134523: Epoch 7131 +2024-11-23 01:37:57.134639: Current learning rate: 0.00136 +2024-11-23 01:38:16.041800: train_loss -0.8249 +2024-11-23 01:38:16.042035: val_loss -0.7668 +2024-11-23 01:38:16.042110: Pseudo dice [0.8789] +2024-11-23 01:38:16.042191: Epoch time: 18.91 s +2024-11-23 01:38:17.015763: +2024-11-23 01:38:17.015997: Epoch 7132 +2024-11-23 01:38:17.016111: Current learning rate: 0.00135 +2024-11-23 01:38:36.119124: train_loss -0.828 +2024-11-23 01:38:36.119383: val_loss -0.7721 +2024-11-23 01:38:36.119461: Pseudo dice [0.8517] +2024-11-23 01:38:36.119545: Epoch time: 19.1 s +2024-11-23 01:38:37.047487: +2024-11-23 01:38:37.047688: Epoch 7133 +2024-11-23 01:38:37.047803: Current learning rate: 0.00135 +2024-11-23 01:38:54.844607: train_loss -0.8291 +2024-11-23 01:38:54.844823: val_loss -0.7539 +2024-11-23 01:38:54.844898: Pseudo dice [0.8513] +2024-11-23 01:38:54.844975: Epoch time: 17.8 s +2024-11-23 01:38:55.767060: +2024-11-23 01:38:55.767282: Epoch 7134 +2024-11-23 01:38:55.767397: Current learning rate: 0.00135 +2024-11-23 01:39:14.680313: train_loss -0.8222 +2024-11-23 01:39:14.680584: val_loss -0.7431 +2024-11-23 01:39:14.680661: Pseudo dice [0.8567] +2024-11-23 01:39:14.680739: Epoch time: 18.91 s +2024-11-23 01:39:15.606109: +2024-11-23 01:39:15.606316: Epoch 7135 +2024-11-23 01:39:15.606437: Current learning rate: 0.00135 +2024-11-23 01:39:33.168250: train_loss -0.8279 +2024-11-23 01:39:33.168480: val_loss -0.7392 +2024-11-23 01:39:33.168556: Pseudo dice [0.834] +2024-11-23 01:39:33.168638: Epoch time: 17.56 s +2024-11-23 01:39:34.260974: +2024-11-23 01:39:34.261179: Epoch 7136 +2024-11-23 01:39:34.261292: Current learning rate: 0.00135 +2024-11-23 01:39:52.991643: train_loss -0.8243 +2024-11-23 01:39:52.991878: val_loss -0.7507 +2024-11-23 01:39:52.991964: Pseudo dice [0.8379] +2024-11-23 01:39:52.992086: Epoch time: 18.73 s +2024-11-23 01:39:53.983477: +2024-11-23 01:39:53.983684: Epoch 7137 +2024-11-23 01:39:53.983798: Current learning rate: 0.00135 +2024-11-23 01:40:13.682152: train_loss -0.823 +2024-11-23 01:40:13.682455: val_loss -0.7573 +2024-11-23 01:40:13.682534: Pseudo dice [0.8519] +2024-11-23 01:40:13.682615: Epoch time: 19.7 s +2024-11-23 01:40:14.715489: +2024-11-23 01:40:14.715725: Epoch 7138 +2024-11-23 01:40:14.715844: Current learning rate: 0.00135 +2024-11-23 01:40:34.337601: train_loss -0.8264 +2024-11-23 01:40:34.337835: val_loss -0.7803 +2024-11-23 01:40:34.337911: Pseudo dice [0.8582] +2024-11-23 01:40:34.337989: Epoch time: 19.62 s +2024-11-23 01:40:35.512889: +2024-11-23 01:40:35.513201: Epoch 7139 +2024-11-23 01:40:35.513317: Current learning rate: 0.00134 +2024-11-23 01:40:54.109175: train_loss -0.8307 +2024-11-23 01:40:54.109393: val_loss -0.7576 +2024-11-23 01:40:54.109467: Pseudo dice [0.8453] +2024-11-23 01:40:54.109544: Epoch time: 18.6 s +2024-11-23 01:40:55.025568: +2024-11-23 01:40:55.025778: Epoch 7140 +2024-11-23 01:40:55.025896: Current learning rate: 0.00134 +2024-11-23 01:41:14.079473: train_loss -0.8269 +2024-11-23 01:41:14.079735: val_loss -0.7795 +2024-11-23 01:41:14.079809: Pseudo dice [0.8735] +2024-11-23 01:41:14.079892: Epoch time: 19.05 s +2024-11-23 01:41:15.024864: +2024-11-23 01:41:15.025067: Epoch 7141 +2024-11-23 01:41:15.025180: Current learning rate: 0.00134 +2024-11-23 01:41:32.227216: train_loss -0.827 +2024-11-23 01:41:32.227432: val_loss -0.7138 +2024-11-23 01:41:32.227509: Pseudo dice [0.8335] +2024-11-23 01:41:32.227585: Epoch time: 17.2 s +2024-11-23 01:41:33.572203: +2024-11-23 01:41:33.572753: Epoch 7142 +2024-11-23 01:41:33.572906: Current learning rate: 0.00134 +2024-11-23 01:41:52.297116: train_loss -0.8293 +2024-11-23 01:41:52.297373: val_loss -0.748 +2024-11-23 01:41:52.297448: Pseudo dice [0.8675] +2024-11-23 01:41:52.297535: Epoch time: 18.73 s +2024-11-23 01:41:53.222862: +2024-11-23 01:41:53.223282: Epoch 7143 +2024-11-23 01:41:53.223414: Current learning rate: 0.00134 +2024-11-23 01:42:11.904147: train_loss -0.8288 +2024-11-23 01:42:11.904384: val_loss -0.7653 +2024-11-23 01:42:11.904460: Pseudo dice [0.866] +2024-11-23 01:42:11.906797: Epoch time: 18.68 s +2024-11-23 01:42:12.945082: +2024-11-23 01:42:12.945525: Epoch 7144 +2024-11-23 01:42:12.945665: Current learning rate: 0.00134 +2024-11-23 01:42:30.830368: train_loss -0.8274 +2024-11-23 01:42:30.830615: val_loss -0.7527 +2024-11-23 01:42:30.830703: Pseudo dice [0.8483] +2024-11-23 01:42:30.830786: Epoch time: 17.89 s +2024-11-23 01:42:31.750715: +2024-11-23 01:42:31.751163: Epoch 7145 +2024-11-23 01:42:31.751304: Current learning rate: 0.00134 +2024-11-23 01:42:50.419467: train_loss -0.8253 +2024-11-23 01:42:50.419685: val_loss -0.7495 +2024-11-23 01:42:50.419760: Pseudo dice [0.8513] +2024-11-23 01:42:50.419840: Epoch time: 18.67 s +2024-11-23 01:42:51.345462: +2024-11-23 01:42:51.345897: Epoch 7146 +2024-11-23 01:42:51.346041: Current learning rate: 0.00134 +2024-11-23 01:43:10.951721: train_loss -0.8267 +2024-11-23 01:43:10.951942: val_loss -0.7709 +2024-11-23 01:43:10.952024: Pseudo dice [0.849] +2024-11-23 01:43:10.952099: Epoch time: 19.61 s +2024-11-23 01:43:11.959872: +2024-11-23 01:43:11.960304: Epoch 7147 +2024-11-23 01:43:11.960439: Current learning rate: 0.00133 +2024-11-23 01:43:30.893790: train_loss -0.8314 +2024-11-23 01:43:30.894021: val_loss -0.7255 +2024-11-23 01:43:30.894100: Pseudo dice [0.8493] +2024-11-23 01:43:30.894259: Epoch time: 18.93 s +2024-11-23 01:43:31.816454: +2024-11-23 01:43:31.816882: Epoch 7148 +2024-11-23 01:43:31.817029: Current learning rate: 0.00133 +2024-11-23 01:43:51.133531: train_loss -0.8144 +2024-11-23 01:43:51.133785: val_loss -0.7658 +2024-11-23 01:43:51.133860: Pseudo dice [0.8661] +2024-11-23 01:43:51.133943: Epoch time: 19.32 s +2024-11-23 01:43:52.054214: +2024-11-23 01:43:52.054641: Epoch 7149 +2024-11-23 01:43:52.054781: Current learning rate: 0.00133 +2024-11-23 01:44:11.345522: train_loss -0.8242 +2024-11-23 01:44:11.345742: val_loss -0.7722 +2024-11-23 01:44:11.345823: Pseudo dice [0.8412] +2024-11-23 01:44:11.345899: Epoch time: 19.29 s +2024-11-23 01:44:12.593945: +2024-11-23 01:44:12.594361: Epoch 7150 +2024-11-23 01:44:12.594499: Current learning rate: 0.00133 +2024-11-23 01:44:31.368951: train_loss -0.8189 +2024-11-23 01:44:31.369194: val_loss -0.7588 +2024-11-23 01:44:31.369282: Pseudo dice [0.8437] +2024-11-23 01:44:31.369417: Epoch time: 18.78 s +2024-11-23 01:44:32.290955: +2024-11-23 01:44:32.291449: Epoch 7151 +2024-11-23 01:44:32.291586: Current learning rate: 0.00133 +2024-11-23 01:44:50.381064: train_loss -0.8268 +2024-11-23 01:44:50.381287: val_loss -0.7547 +2024-11-23 01:44:50.381361: Pseudo dice [0.8375] +2024-11-23 01:44:50.381441: Epoch time: 18.09 s +2024-11-23 01:44:51.307946: +2024-11-23 01:44:51.308497: Epoch 7152 +2024-11-23 01:44:51.308669: Current learning rate: 0.00133 +2024-11-23 01:45:09.718775: train_loss -0.8277 +2024-11-23 01:45:09.719013: val_loss -0.7517 +2024-11-23 01:45:09.719090: Pseudo dice [0.8585] +2024-11-23 01:45:09.719170: Epoch time: 18.41 s +2024-11-23 01:45:11.035673: +2024-11-23 01:45:11.035879: Epoch 7153 +2024-11-23 01:45:11.036021: Current learning rate: 0.00133 +2024-11-23 01:45:29.132495: train_loss -0.8282 +2024-11-23 01:45:29.132744: val_loss -0.7506 +2024-11-23 01:45:29.132818: Pseudo dice [0.8351] +2024-11-23 01:45:29.132896: Epoch time: 18.1 s +2024-11-23 01:45:30.062404: +2024-11-23 01:45:30.062617: Epoch 7154 +2024-11-23 01:45:30.062732: Current learning rate: 0.00132 +2024-11-23 01:45:49.259727: train_loss -0.8132 +2024-11-23 01:45:49.259986: val_loss -0.7476 +2024-11-23 01:45:49.260073: Pseudo dice [0.8473] +2024-11-23 01:45:49.260154: Epoch time: 19.2 s +2024-11-23 01:45:50.187483: +2024-11-23 01:45:50.187705: Epoch 7155 +2024-11-23 01:45:50.187816: Current learning rate: 0.00132 +2024-11-23 01:46:08.660123: train_loss -0.8239 +2024-11-23 01:46:08.660373: val_loss -0.7613 +2024-11-23 01:46:08.660450: Pseudo dice [0.8633] +2024-11-23 01:46:08.660531: Epoch time: 18.47 s +2024-11-23 01:46:09.584239: +2024-11-23 01:46:09.584469: Epoch 7156 +2024-11-23 01:46:09.584587: Current learning rate: 0.00132 +2024-11-23 01:46:27.609149: train_loss -0.8243 +2024-11-23 01:46:27.609357: val_loss -0.749 +2024-11-23 01:46:27.609431: Pseudo dice [0.8334] +2024-11-23 01:46:27.609507: Epoch time: 18.03 s +2024-11-23 01:46:28.630896: +2024-11-23 01:46:28.631118: Epoch 7157 +2024-11-23 01:46:28.631232: Current learning rate: 0.00132 +2024-11-23 01:46:46.159051: train_loss -0.8319 +2024-11-23 01:46:46.161436: val_loss -0.7602 +2024-11-23 01:46:46.161526: Pseudo dice [0.8633] +2024-11-23 01:46:46.161605: Epoch time: 17.53 s +2024-11-23 01:46:47.253116: +2024-11-23 01:46:47.253338: Epoch 7158 +2024-11-23 01:46:47.253455: Current learning rate: 0.00132 +2024-11-23 01:47:05.975998: train_loss -0.818 +2024-11-23 01:47:05.976240: val_loss -0.7721 +2024-11-23 01:47:05.976322: Pseudo dice [0.8343] +2024-11-23 01:47:05.976403: Epoch time: 18.72 s +2024-11-23 01:47:06.908595: +2024-11-23 01:47:06.908814: Epoch 7159 +2024-11-23 01:47:06.908931: Current learning rate: 0.00132 +2024-11-23 01:47:24.975312: train_loss -0.8209 +2024-11-23 01:47:24.975581: val_loss -0.7627 +2024-11-23 01:47:24.975656: Pseudo dice [0.8509] +2024-11-23 01:47:24.975736: Epoch time: 18.07 s +2024-11-23 01:47:26.004105: +2024-11-23 01:47:26.004294: Epoch 7160 +2024-11-23 01:47:26.004407: Current learning rate: 0.00132 +2024-11-23 01:47:45.027100: train_loss -0.8211 +2024-11-23 01:47:45.027372: val_loss -0.7763 +2024-11-23 01:47:45.027449: Pseudo dice [0.8552] +2024-11-23 01:47:45.027550: Epoch time: 19.02 s +2024-11-23 01:47:45.948505: +2024-11-23 01:47:45.948736: Epoch 7161 +2024-11-23 01:47:45.948850: Current learning rate: 0.00131 +2024-11-23 01:48:04.771490: train_loss -0.8158 +2024-11-23 01:48:04.771715: val_loss -0.7719 +2024-11-23 01:48:04.771790: Pseudo dice [0.8766] +2024-11-23 01:48:04.771868: Epoch time: 18.82 s +2024-11-23 01:48:05.688982: +2024-11-23 01:48:05.689191: Epoch 7162 +2024-11-23 01:48:05.689300: Current learning rate: 0.00131 +2024-11-23 01:48:25.099897: train_loss -0.8182 +2024-11-23 01:48:25.100125: val_loss -0.7495 +2024-11-23 01:48:25.100198: Pseudo dice [0.8478] +2024-11-23 01:48:25.100276: Epoch time: 19.41 s +2024-11-23 01:48:26.021357: +2024-11-23 01:48:26.021562: Epoch 7163 +2024-11-23 01:48:26.021672: Current learning rate: 0.00131 +2024-11-23 01:48:44.991107: train_loss -0.8238 +2024-11-23 01:48:44.991356: val_loss -0.7182 +2024-11-23 01:48:44.993644: Pseudo dice [0.8514] +2024-11-23 01:48:44.993743: Epoch time: 18.97 s +2024-11-23 01:48:46.041432: +2024-11-23 01:48:46.041860: Epoch 7164 +2024-11-23 01:48:46.042008: Current learning rate: 0.00131 +2024-11-23 01:49:05.090326: train_loss -0.8242 +2024-11-23 01:49:05.092741: val_loss -0.7333 +2024-11-23 01:49:05.092834: Pseudo dice [0.865] +2024-11-23 01:49:05.092914: Epoch time: 19.05 s +2024-11-23 01:49:06.476101: +2024-11-23 01:49:06.476309: Epoch 7165 +2024-11-23 01:49:06.476423: Current learning rate: 0.00131 +2024-11-23 01:49:24.641578: train_loss -0.8342 +2024-11-23 01:49:24.641808: val_loss -0.7433 +2024-11-23 01:49:24.644090: Pseudo dice [0.8474] +2024-11-23 01:49:24.644196: Epoch time: 18.17 s +2024-11-23 01:49:25.699571: +2024-11-23 01:49:25.699810: Epoch 7166 +2024-11-23 01:49:25.699927: Current learning rate: 0.00131 +2024-11-23 01:49:43.995079: train_loss -0.8264 +2024-11-23 01:49:43.995334: val_loss -0.7873 +2024-11-23 01:49:43.995439: Pseudo dice [0.8681] +2024-11-23 01:49:43.995577: Epoch time: 18.3 s +2024-11-23 01:49:44.925184: +2024-11-23 01:49:44.925488: Epoch 7167 +2024-11-23 01:49:44.925599: Current learning rate: 0.00131 +2024-11-23 01:50:03.719575: train_loss -0.8241 +2024-11-23 01:50:03.719793: val_loss -0.7789 +2024-11-23 01:50:03.719868: Pseudo dice [0.8405] +2024-11-23 01:50:03.719948: Epoch time: 18.8 s +2024-11-23 01:50:04.636080: +2024-11-23 01:50:04.636338: Epoch 7168 +2024-11-23 01:50:04.636453: Current learning rate: 0.0013 +2024-11-23 01:50:23.426672: train_loss -0.826 +2024-11-23 01:50:23.426894: val_loss -0.7608 +2024-11-23 01:50:23.426979: Pseudo dice [0.8416] +2024-11-23 01:50:23.427082: Epoch time: 18.79 s +2024-11-23 01:50:24.349163: +2024-11-23 01:50:24.349374: Epoch 7169 +2024-11-23 01:50:24.349483: Current learning rate: 0.0013 +2024-11-23 01:50:42.512761: train_loss -0.821 +2024-11-23 01:50:42.512997: val_loss -0.7493 +2024-11-23 01:50:42.513078: Pseudo dice [0.8508] +2024-11-23 01:50:42.513162: Epoch time: 18.16 s +2024-11-23 01:50:43.441804: +2024-11-23 01:50:43.442071: Epoch 7170 +2024-11-23 01:50:43.442189: Current learning rate: 0.0013 +2024-11-23 01:51:01.971505: train_loss -0.8122 +2024-11-23 01:51:01.971769: val_loss -0.743 +2024-11-23 01:51:01.971849: Pseudo dice [0.859] +2024-11-23 01:51:01.971932: Epoch time: 18.53 s +2024-11-23 01:51:02.891510: +2024-11-23 01:51:02.891725: Epoch 7171 +2024-11-23 01:51:02.891837: Current learning rate: 0.0013 +2024-11-23 01:51:22.215073: train_loss -0.815 +2024-11-23 01:51:22.215865: val_loss -0.7508 +2024-11-23 01:51:22.215955: Pseudo dice [0.8353] +2024-11-23 01:51:22.216039: Epoch time: 19.32 s +2024-11-23 01:51:23.162104: +2024-11-23 01:51:23.162311: Epoch 7172 +2024-11-23 01:51:23.162425: Current learning rate: 0.0013 +2024-11-23 01:51:42.479416: train_loss -0.8145 +2024-11-23 01:51:42.479633: val_loss -0.7614 +2024-11-23 01:51:42.479718: Pseudo dice [0.8495] +2024-11-23 01:51:42.479795: Epoch time: 19.32 s +2024-11-23 01:51:43.417358: +2024-11-23 01:51:43.417710: Epoch 7173 +2024-11-23 01:51:43.417829: Current learning rate: 0.0013 +2024-11-23 01:52:02.143348: train_loss -0.8225 +2024-11-23 01:52:02.143571: val_loss -0.7126 +2024-11-23 01:52:02.143646: Pseudo dice [0.8542] +2024-11-23 01:52:02.143723: Epoch time: 18.73 s +2024-11-23 01:52:03.068946: +2024-11-23 01:52:03.069179: Epoch 7174 +2024-11-23 01:52:03.069299: Current learning rate: 0.0013 +2024-11-23 01:52:22.093709: train_loss -0.8215 +2024-11-23 01:52:22.093965: val_loss -0.767 +2024-11-23 01:52:22.094044: Pseudo dice [0.8583] +2024-11-23 01:52:22.094131: Epoch time: 19.03 s +2024-11-23 01:52:23.014619: +2024-11-23 01:52:23.014840: Epoch 7175 +2024-11-23 01:52:23.014955: Current learning rate: 0.00129 +2024-11-23 01:52:40.944624: train_loss -0.8237 +2024-11-23 01:52:40.944851: val_loss -0.7463 +2024-11-23 01:52:40.944931: Pseudo dice [0.8605] +2024-11-23 01:52:40.945015: Epoch time: 17.93 s +2024-11-23 01:52:42.202076: +2024-11-23 01:52:42.202308: Epoch 7176 +2024-11-23 01:52:42.202422: Current learning rate: 0.00129 +2024-11-23 01:53:01.445226: train_loss -0.8243 +2024-11-23 01:53:01.445477: val_loss -0.7496 +2024-11-23 01:53:01.445555: Pseudo dice [0.855] +2024-11-23 01:53:01.445640: Epoch time: 19.24 s +2024-11-23 01:53:02.362582: +2024-11-23 01:53:02.362807: Epoch 7177 +2024-11-23 01:53:02.362915: Current learning rate: 0.00129 +2024-11-23 01:53:20.427001: train_loss -0.8178 +2024-11-23 01:53:20.427234: val_loss -0.7633 +2024-11-23 01:53:20.427309: Pseudo dice [0.8509] +2024-11-23 01:53:20.427388: Epoch time: 18.07 s +2024-11-23 01:53:21.423988: +2024-11-23 01:53:21.424212: Epoch 7178 +2024-11-23 01:53:21.424321: Current learning rate: 0.00129 +2024-11-23 01:53:41.022198: train_loss -0.8202 +2024-11-23 01:53:41.022473: val_loss -0.7458 +2024-11-23 01:53:41.022579: Pseudo dice [0.8539] +2024-11-23 01:53:41.022655: Epoch time: 19.6 s +2024-11-23 01:53:42.053965: +2024-11-23 01:53:42.054188: Epoch 7179 +2024-11-23 01:53:42.054300: Current learning rate: 0.00129 +2024-11-23 01:54:01.128051: train_loss -0.8144 +2024-11-23 01:54:01.128293: val_loss -0.7496 +2024-11-23 01:54:01.128367: Pseudo dice [0.8544] +2024-11-23 01:54:01.128448: Epoch time: 19.07 s +2024-11-23 01:54:02.304790: +2024-11-23 01:54:02.305013: Epoch 7180 +2024-11-23 01:54:02.305125: Current learning rate: 0.00129 +2024-11-23 01:54:20.593664: train_loss -0.8282 +2024-11-23 01:54:20.593892: val_loss -0.7457 +2024-11-23 01:54:20.593967: Pseudo dice [0.8248] +2024-11-23 01:54:20.594126: Epoch time: 18.29 s +2024-11-23 01:54:21.516096: +2024-11-23 01:54:21.516320: Epoch 7181 +2024-11-23 01:54:21.516431: Current learning rate: 0.00129 +2024-11-23 01:54:39.916034: train_loss -0.8265 +2024-11-23 01:54:39.916315: val_loss -0.7508 +2024-11-23 01:54:39.916393: Pseudo dice [0.8638] +2024-11-23 01:54:39.916480: Epoch time: 18.4 s +2024-11-23 01:54:40.840534: +2024-11-23 01:54:40.840758: Epoch 7182 +2024-11-23 01:54:40.840870: Current learning rate: 0.00128 +2024-11-23 01:54:59.768004: train_loss -0.8246 +2024-11-23 01:54:59.768302: val_loss -0.7809 +2024-11-23 01:54:59.768384: Pseudo dice [0.8468] +2024-11-23 01:54:59.768460: Epoch time: 18.93 s +2024-11-23 01:55:00.863437: +2024-11-23 01:55:00.863657: Epoch 7183 +2024-11-23 01:55:00.863771: Current learning rate: 0.00128 +2024-11-23 01:55:20.417964: train_loss -0.8194 +2024-11-23 01:55:20.418189: val_loss -0.7855 +2024-11-23 01:55:20.418278: Pseudo dice [0.8726] +2024-11-23 01:55:20.418370: Epoch time: 19.56 s +2024-11-23 01:55:21.344591: +2024-11-23 01:55:21.344808: Epoch 7184 +2024-11-23 01:55:21.344921: Current learning rate: 0.00128 +2024-11-23 01:55:40.055186: train_loss -0.8203 +2024-11-23 01:55:40.055407: val_loss -0.7478 +2024-11-23 01:55:40.055480: Pseudo dice [0.8446] +2024-11-23 01:55:40.055557: Epoch time: 18.71 s +2024-11-23 01:55:40.982555: +2024-11-23 01:55:40.982794: Epoch 7185 +2024-11-23 01:55:40.982918: Current learning rate: 0.00128 +2024-11-23 01:56:00.472697: train_loss -0.8212 +2024-11-23 01:56:00.472951: val_loss -0.7456 +2024-11-23 01:56:00.473038: Pseudo dice [0.8637] +2024-11-23 01:56:00.473119: Epoch time: 19.49 s +2024-11-23 01:56:01.398256: +2024-11-23 01:56:01.398473: Epoch 7186 +2024-11-23 01:56:01.398583: Current learning rate: 0.00128 +2024-11-23 01:56:20.036032: train_loss -0.8258 +2024-11-23 01:56:20.036294: val_loss -0.7699 +2024-11-23 01:56:20.036370: Pseudo dice [0.8616] +2024-11-23 01:56:20.036447: Epoch time: 18.64 s +2024-11-23 01:56:20.956044: +2024-11-23 01:56:20.956323: Epoch 7187 +2024-11-23 01:56:20.956433: Current learning rate: 0.00128 +2024-11-23 01:56:41.029049: train_loss -0.8231 +2024-11-23 01:56:41.029268: val_loss -0.7635 +2024-11-23 01:56:41.029341: Pseudo dice [0.8683] +2024-11-23 01:56:41.029420: Epoch time: 20.07 s +2024-11-23 01:56:42.361928: +2024-11-23 01:56:42.362208: Epoch 7188 +2024-11-23 01:56:42.362326: Current learning rate: 0.00128 +2024-11-23 01:57:00.923007: train_loss -0.8237 +2024-11-23 01:57:00.923253: val_loss -0.7659 +2024-11-23 01:57:00.923329: Pseudo dice [0.8623] +2024-11-23 01:57:00.923407: Epoch time: 18.56 s +2024-11-23 01:57:01.901988: +2024-11-23 01:57:01.902235: Epoch 7189 +2024-11-23 01:57:01.902344: Current learning rate: 0.00127 +2024-11-23 01:57:20.976350: train_loss -0.8278 +2024-11-23 01:57:20.976584: val_loss -0.7511 +2024-11-23 01:57:20.976658: Pseudo dice [0.869] +2024-11-23 01:57:20.976733: Epoch time: 19.08 s +2024-11-23 01:57:20.976792: Yayy! New best EMA pseudo Dice: 0.8576 +2024-11-23 01:57:22.298128: +2024-11-23 01:57:22.298339: Epoch 7190 +2024-11-23 01:57:22.298451: Current learning rate: 0.00127 +2024-11-23 01:57:41.574975: train_loss -0.8325 +2024-11-23 01:57:41.577397: val_loss -0.7605 +2024-11-23 01:57:41.577501: Pseudo dice [0.8586] +2024-11-23 01:57:41.577582: Epoch time: 19.28 s +2024-11-23 01:57:41.577645: Yayy! New best EMA pseudo Dice: 0.8577 +2024-11-23 01:57:42.850374: +2024-11-23 01:57:42.850598: Epoch 7191 +2024-11-23 01:57:42.850712: Current learning rate: 0.00127 +2024-11-23 01:58:01.678916: train_loss -0.8264 +2024-11-23 01:58:01.679148: val_loss -0.7551 +2024-11-23 01:58:01.679226: Pseudo dice [0.8374] +2024-11-23 01:58:01.679310: Epoch time: 18.83 s +2024-11-23 01:58:02.606368: +2024-11-23 01:58:02.606589: Epoch 7192 +2024-11-23 01:58:02.606706: Current learning rate: 0.00127 +2024-11-23 01:58:22.651289: train_loss -0.8212 +2024-11-23 01:58:22.651524: val_loss -0.7418 +2024-11-23 01:58:22.651597: Pseudo dice [0.8507] +2024-11-23 01:58:22.654515: Epoch time: 20.05 s +2024-11-23 01:58:23.581574: +2024-11-23 01:58:23.581790: Epoch 7193 +2024-11-23 01:58:23.581901: Current learning rate: 0.00127 +2024-11-23 01:58:42.448785: train_loss -0.8163 +2024-11-23 01:58:42.449174: val_loss -0.777 +2024-11-23 01:58:42.449262: Pseudo dice [0.8673] +2024-11-23 01:58:42.449337: Epoch time: 18.87 s +2024-11-23 01:58:43.439465: +2024-11-23 01:58:43.439717: Epoch 7194 +2024-11-23 01:58:43.439833: Current learning rate: 0.00127 +2024-11-23 01:59:02.573028: train_loss -0.8196 +2024-11-23 01:59:02.573256: val_loss -0.7364 +2024-11-23 01:59:02.573333: Pseudo dice [0.8263] +2024-11-23 01:59:02.573412: Epoch time: 19.13 s +2024-11-23 01:59:03.499522: +2024-11-23 01:59:03.499786: Epoch 7195 +2024-11-23 01:59:03.499902: Current learning rate: 0.00127 +2024-11-23 01:59:21.557614: train_loss -0.8251 +2024-11-23 01:59:21.557841: val_loss -0.7604 +2024-11-23 01:59:21.557935: Pseudo dice [0.8615] +2024-11-23 01:59:21.558021: Epoch time: 18.06 s +2024-11-23 01:59:22.592026: +2024-11-23 01:59:22.592244: Epoch 7196 +2024-11-23 01:59:22.592358: Current learning rate: 0.00126 +2024-11-23 01:59:42.732592: train_loss -0.8182 +2024-11-23 01:59:42.732906: val_loss -0.7804 +2024-11-23 01:59:42.732988: Pseudo dice [0.853] +2024-11-23 01:59:42.733077: Epoch time: 20.14 s +2024-11-23 01:59:43.659344: +2024-11-23 01:59:43.659601: Epoch 7197 +2024-11-23 01:59:43.659715: Current learning rate: 0.00126 +2024-11-23 02:00:02.817289: train_loss -0.8314 +2024-11-23 02:00:02.817508: val_loss -0.72 +2024-11-23 02:00:02.817586: Pseudo dice [0.8747] +2024-11-23 02:00:02.817664: Epoch time: 19.16 s +2024-11-23 02:00:03.765770: +2024-11-23 02:00:03.765993: Epoch 7198 +2024-11-23 02:00:03.766108: Current learning rate: 0.00126 +2024-11-23 02:00:23.270751: train_loss -0.8323 +2024-11-23 02:00:23.270982: val_loss -0.7838 +2024-11-23 02:00:23.271064: Pseudo dice [0.8844] +2024-11-23 02:00:23.271140: Epoch time: 19.51 s +2024-11-23 02:00:23.271201: Yayy! New best EMA pseudo Dice: 0.8589 +2024-11-23 02:00:24.965460: +2024-11-23 02:00:24.965716: Epoch 7199 +2024-11-23 02:00:24.965846: Current learning rate: 0.00126 +2024-11-23 02:00:43.742840: train_loss -0.8295 +2024-11-23 02:00:43.743099: val_loss -0.7491 +2024-11-23 02:00:43.743176: Pseudo dice [0.8514] +2024-11-23 02:00:43.743257: Epoch time: 18.78 s +2024-11-23 02:00:45.080569: +2024-11-23 02:00:45.080831: Epoch 7200 +2024-11-23 02:00:45.080946: Current learning rate: 0.00126 +2024-11-23 02:01:05.259274: train_loss -0.8229 +2024-11-23 02:01:05.259497: val_loss -0.7751 +2024-11-23 02:01:05.259634: Pseudo dice [0.8732] +2024-11-23 02:01:05.259713: Epoch time: 20.18 s +2024-11-23 02:01:05.259775: Yayy! New best EMA pseudo Dice: 0.8597 +2024-11-23 02:01:06.519863: +2024-11-23 02:01:06.520104: Epoch 7201 +2024-11-23 02:01:06.520216: Current learning rate: 0.00126 +2024-11-23 02:01:26.082775: train_loss -0.8233 +2024-11-23 02:01:26.083026: val_loss -0.7775 +2024-11-23 02:01:26.083103: Pseudo dice [0.8573] +2024-11-23 02:01:26.083180: Epoch time: 19.56 s +2024-11-23 02:01:27.005706: +2024-11-23 02:01:27.005902: Epoch 7202 +2024-11-23 02:01:27.006018: Current learning rate: 0.00126 +2024-11-23 02:01:45.375207: train_loss -0.8275 +2024-11-23 02:01:45.375486: val_loss -0.7506 +2024-11-23 02:01:45.375575: Pseudo dice [0.8583] +2024-11-23 02:01:45.375659: Epoch time: 18.37 s +2024-11-23 02:01:46.298417: +2024-11-23 02:01:46.298626: Epoch 7203 +2024-11-23 02:01:46.298736: Current learning rate: 0.00125 +2024-11-23 02:02:05.123237: train_loss -0.8284 +2024-11-23 02:02:05.123459: val_loss -0.759 +2024-11-23 02:02:05.123541: Pseudo dice [0.8276] +2024-11-23 02:02:05.123621: Epoch time: 18.83 s +2024-11-23 02:02:06.046458: +2024-11-23 02:02:06.046665: Epoch 7204 +2024-11-23 02:02:06.046778: Current learning rate: 0.00125 +2024-11-23 02:02:25.117519: train_loss -0.8248 +2024-11-23 02:02:25.117786: val_loss -0.7439 +2024-11-23 02:02:25.117863: Pseudo dice [0.8607] +2024-11-23 02:02:25.117939: Epoch time: 19.07 s +2024-11-23 02:02:26.053703: +2024-11-23 02:02:26.053907: Epoch 7205 +2024-11-23 02:02:26.054022: Current learning rate: 0.00125 +2024-11-23 02:02:44.887492: train_loss -0.8296 +2024-11-23 02:02:44.887727: val_loss -0.7833 +2024-11-23 02:02:44.887803: Pseudo dice [0.8642] +2024-11-23 02:02:44.887900: Epoch time: 18.83 s +2024-11-23 02:02:45.823326: +2024-11-23 02:02:45.823558: Epoch 7206 +2024-11-23 02:02:45.823669: Current learning rate: 0.00125 +2024-11-23 02:03:03.868583: train_loss -0.8304 +2024-11-23 02:03:03.874054: val_loss -0.7497 +2024-11-23 02:03:03.874174: Pseudo dice [0.8501] +2024-11-23 02:03:03.874264: Epoch time: 18.05 s +2024-11-23 02:03:04.883607: +2024-11-23 02:03:04.883812: Epoch 7207 +2024-11-23 02:03:04.883922: Current learning rate: 0.00125 +2024-11-23 02:03:23.615466: train_loss -0.8237 +2024-11-23 02:03:23.615680: val_loss -0.7711 +2024-11-23 02:03:23.615753: Pseudo dice [0.8509] +2024-11-23 02:03:23.615827: Epoch time: 18.73 s +2024-11-23 02:03:24.649515: +2024-11-23 02:03:24.649799: Epoch 7208 +2024-11-23 02:03:24.649914: Current learning rate: 0.00125 +2024-11-23 02:03:43.532197: train_loss -0.8218 +2024-11-23 02:03:43.532420: val_loss -0.7643 +2024-11-23 02:03:43.532495: Pseudo dice [0.8481] +2024-11-23 02:03:43.532573: Epoch time: 18.88 s +2024-11-23 02:03:44.453845: +2024-11-23 02:03:44.454276: Epoch 7209 +2024-11-23 02:03:44.454409: Current learning rate: 0.00125 +2024-11-23 02:04:03.718885: train_loss -0.8183 +2024-11-23 02:04:03.719121: val_loss -0.7433 +2024-11-23 02:04:03.719208: Pseudo dice [0.8495] +2024-11-23 02:04:03.719288: Epoch time: 19.27 s +2024-11-23 02:04:05.140801: +2024-11-23 02:04:05.141033: Epoch 7210 +2024-11-23 02:04:05.141147: Current learning rate: 0.00124 +2024-11-23 02:04:23.978036: train_loss -0.8237 +2024-11-23 02:04:23.978292: val_loss -0.7671 +2024-11-23 02:04:23.978373: Pseudo dice [0.8322] +2024-11-23 02:04:23.978453: Epoch time: 18.84 s +2024-11-23 02:04:24.953726: +2024-11-23 02:04:24.954069: Epoch 7211 +2024-11-23 02:04:24.954180: Current learning rate: 0.00124 +2024-11-23 02:04:42.971592: train_loss -0.8229 +2024-11-23 02:04:42.971808: val_loss -0.777 +2024-11-23 02:04:42.971884: Pseudo dice [0.8459] +2024-11-23 02:04:42.971961: Epoch time: 18.02 s +2024-11-23 02:04:43.890809: +2024-11-23 02:04:43.891027: Epoch 7212 +2024-11-23 02:04:43.891141: Current learning rate: 0.00124 +2024-11-23 02:05:02.848361: train_loss -0.8268 +2024-11-23 02:05:02.848578: val_loss -0.7698 +2024-11-23 02:05:02.848653: Pseudo dice [0.8681] +2024-11-23 02:05:02.848729: Epoch time: 18.96 s +2024-11-23 02:05:03.771758: +2024-11-23 02:05:03.771963: Epoch 7213 +2024-11-23 02:05:03.772080: Current learning rate: 0.00124 +2024-11-23 02:05:23.355558: train_loss -0.8237 +2024-11-23 02:05:23.355814: val_loss -0.7563 +2024-11-23 02:05:23.355891: Pseudo dice [0.8504] +2024-11-23 02:05:23.355974: Epoch time: 19.58 s +2024-11-23 02:05:24.285218: +2024-11-23 02:05:24.285491: Epoch 7214 +2024-11-23 02:05:24.285607: Current learning rate: 0.00124 +2024-11-23 02:05:43.454964: train_loss -0.8303 +2024-11-23 02:05:43.455194: val_loss -0.7378 +2024-11-23 02:05:43.455270: Pseudo dice [0.8583] +2024-11-23 02:05:43.455345: Epoch time: 19.17 s +2024-11-23 02:05:44.375625: +2024-11-23 02:05:44.375833: Epoch 7215 +2024-11-23 02:05:44.375946: Current learning rate: 0.00124 +2024-11-23 02:06:02.452903: train_loss -0.8266 +2024-11-23 02:06:02.453130: val_loss -0.7679 +2024-11-23 02:06:02.453212: Pseudo dice [0.8634] +2024-11-23 02:06:02.453294: Epoch time: 18.08 s +2024-11-23 02:06:03.378391: +2024-11-23 02:06:03.378601: Epoch 7216 +2024-11-23 02:06:03.378712: Current learning rate: 0.00124 +2024-11-23 02:06:21.135230: train_loss -0.8286 +2024-11-23 02:06:21.135457: val_loss -0.7436 +2024-11-23 02:06:21.135535: Pseudo dice [0.8464] +2024-11-23 02:06:21.135631: Epoch time: 17.76 s +2024-11-23 02:06:22.055119: +2024-11-23 02:06:22.055338: Epoch 7217 +2024-11-23 02:06:22.055449: Current learning rate: 0.00123 +2024-11-23 02:06:41.471882: train_loss -0.8302 +2024-11-23 02:06:41.472134: val_loss -0.767 +2024-11-23 02:06:41.472208: Pseudo dice [0.8607] +2024-11-23 02:06:41.472290: Epoch time: 19.42 s +2024-11-23 02:06:42.521059: +2024-11-23 02:06:42.521292: Epoch 7218 +2024-11-23 02:06:42.521406: Current learning rate: 0.00123 +2024-11-23 02:07:00.877067: train_loss -0.8279 +2024-11-23 02:07:00.877310: val_loss -0.779 +2024-11-23 02:07:00.877389: Pseudo dice [0.8439] +2024-11-23 02:07:00.877468: Epoch time: 18.36 s +2024-11-23 02:07:01.806370: +2024-11-23 02:07:01.807451: Epoch 7219 +2024-11-23 02:07:01.807617: Current learning rate: 0.00123 +2024-11-23 02:07:19.554228: train_loss -0.8252 +2024-11-23 02:07:19.554456: val_loss -0.7743 +2024-11-23 02:07:19.554537: Pseudo dice [0.8505] +2024-11-23 02:07:19.554619: Epoch time: 17.75 s +2024-11-23 02:07:20.476435: +2024-11-23 02:07:20.476677: Epoch 7220 +2024-11-23 02:07:20.476791: Current learning rate: 0.00123 +2024-11-23 02:07:38.044302: train_loss -0.8234 +2024-11-23 02:07:38.044549: val_loss -0.7746 +2024-11-23 02:07:38.044628: Pseudo dice [0.8572] +2024-11-23 02:07:38.044713: Epoch time: 17.57 s +2024-11-23 02:07:38.957781: +2024-11-23 02:07:38.957989: Epoch 7221 +2024-11-23 02:07:38.958122: Current learning rate: 0.00123 +2024-11-23 02:07:58.819528: train_loss -0.832 +2024-11-23 02:07:58.819772: val_loss -0.7681 +2024-11-23 02:07:58.819849: Pseudo dice [0.8552] +2024-11-23 02:07:58.824664: Epoch time: 19.86 s +2024-11-23 02:07:59.775242: +2024-11-23 02:07:59.775451: Epoch 7222 +2024-11-23 02:07:59.775565: Current learning rate: 0.00123 +2024-11-23 02:08:18.608906: train_loss -0.8226 +2024-11-23 02:08:18.609209: val_loss -0.7629 +2024-11-23 02:08:18.609291: Pseudo dice [0.8601] +2024-11-23 02:08:18.609390: Epoch time: 18.83 s +2024-11-23 02:08:19.528727: +2024-11-23 02:08:19.528960: Epoch 7223 +2024-11-23 02:08:19.529074: Current learning rate: 0.00123 +2024-11-23 02:08:37.599531: train_loss -0.8266 +2024-11-23 02:08:37.599778: val_loss -0.7589 +2024-11-23 02:08:37.599856: Pseudo dice [0.838] +2024-11-23 02:08:37.599939: Epoch time: 18.07 s +2024-11-23 02:08:38.557003: +2024-11-23 02:08:38.557302: Epoch 7224 +2024-11-23 02:08:38.557417: Current learning rate: 0.00122 +2024-11-23 02:08:56.106545: train_loss -0.8286 +2024-11-23 02:08:56.112003: val_loss -0.7479 +2024-11-23 02:08:56.112091: Pseudo dice [0.8469] +2024-11-23 02:08:56.112180: Epoch time: 17.55 s +2024-11-23 02:08:57.357022: +2024-11-23 02:08:57.357235: Epoch 7225 +2024-11-23 02:08:57.357345: Current learning rate: 0.00122 +2024-11-23 02:09:16.026700: train_loss -0.8265 +2024-11-23 02:09:16.026934: val_loss -0.7762 +2024-11-23 02:09:16.027014: Pseudo dice [0.8522] +2024-11-23 02:09:16.027094: Epoch time: 18.67 s +2024-11-23 02:09:16.956698: +2024-11-23 02:09:16.956927: Epoch 7226 +2024-11-23 02:09:16.957040: Current learning rate: 0.00122 +2024-11-23 02:09:35.722421: train_loss -0.8263 +2024-11-23 02:09:35.722646: val_loss -0.785 +2024-11-23 02:09:35.722724: Pseudo dice [0.8413] +2024-11-23 02:09:35.722802: Epoch time: 18.77 s +2024-11-23 02:09:36.650105: +2024-11-23 02:09:36.650300: Epoch 7227 +2024-11-23 02:09:36.650408: Current learning rate: 0.00122 +2024-11-23 02:09:55.914682: train_loss -0.8276 +2024-11-23 02:09:55.914899: val_loss -0.7528 +2024-11-23 02:09:55.914976: Pseudo dice [0.8569] +2024-11-23 02:09:55.915067: Epoch time: 19.27 s +2024-11-23 02:09:56.835554: +2024-11-23 02:09:56.835775: Epoch 7228 +2024-11-23 02:09:56.835888: Current learning rate: 0.00122 +2024-11-23 02:10:15.547016: train_loss -0.8311 +2024-11-23 02:10:15.547279: val_loss -0.7552 +2024-11-23 02:10:15.547354: Pseudo dice [0.8432] +2024-11-23 02:10:15.547435: Epoch time: 18.71 s +2024-11-23 02:10:16.508778: +2024-11-23 02:10:16.508997: Epoch 7229 +2024-11-23 02:10:16.509106: Current learning rate: 0.00122 +2024-11-23 02:10:35.313130: train_loss -0.8217 +2024-11-23 02:10:35.313360: val_loss -0.7527 +2024-11-23 02:10:35.313442: Pseudo dice [0.8596] +2024-11-23 02:10:35.313520: Epoch time: 18.81 s +2024-11-23 02:10:36.340066: +2024-11-23 02:10:36.340492: Epoch 7230 +2024-11-23 02:10:36.340622: Current learning rate: 0.00122 +2024-11-23 02:10:55.249389: train_loss -0.825 +2024-11-23 02:10:55.251789: val_loss -0.7573 +2024-11-23 02:10:55.251881: Pseudo dice [0.8533] +2024-11-23 02:10:55.251966: Epoch time: 18.91 s +2024-11-23 02:10:56.181129: +2024-11-23 02:10:56.181536: Epoch 7231 +2024-11-23 02:10:56.181665: Current learning rate: 0.00121 +2024-11-23 02:11:16.270871: train_loss -0.8202 +2024-11-23 02:11:16.271105: val_loss -0.7612 +2024-11-23 02:11:16.271183: Pseudo dice [0.84] +2024-11-23 02:11:16.271260: Epoch time: 20.09 s +2024-11-23 02:11:17.203191: +2024-11-23 02:11:17.203418: Epoch 7232 +2024-11-23 02:11:17.203531: Current learning rate: 0.00121 +2024-11-23 02:11:35.978100: train_loss -0.827 +2024-11-23 02:11:35.978347: val_loss -0.7661 +2024-11-23 02:11:35.978433: Pseudo dice [0.8685] +2024-11-23 02:11:35.978514: Epoch time: 18.78 s +2024-11-23 02:11:37.272077: +2024-11-23 02:11:37.272287: Epoch 7233 +2024-11-23 02:11:37.272395: Current learning rate: 0.00121 +2024-11-23 02:11:55.084786: train_loss -0.8232 +2024-11-23 02:11:55.085025: val_loss -0.7623 +2024-11-23 02:11:55.085103: Pseudo dice [0.8478] +2024-11-23 02:11:55.085178: Epoch time: 17.81 s +2024-11-23 02:11:56.003759: +2024-11-23 02:11:56.004013: Epoch 7234 +2024-11-23 02:11:56.004127: Current learning rate: 0.00121 +2024-11-23 02:12:14.876357: train_loss -0.8264 +2024-11-23 02:12:14.876604: val_loss -0.7379 +2024-11-23 02:12:14.876713: Pseudo dice [0.868] +2024-11-23 02:12:14.876795: Epoch time: 18.87 s +2024-11-23 02:12:15.808416: +2024-11-23 02:12:15.808660: Epoch 7235 +2024-11-23 02:12:15.808773: Current learning rate: 0.00121 +2024-11-23 02:12:34.626138: train_loss -0.8267 +2024-11-23 02:12:34.626400: val_loss -0.7427 +2024-11-23 02:12:34.626475: Pseudo dice [0.8475] +2024-11-23 02:12:34.626580: Epoch time: 18.82 s +2024-11-23 02:12:35.547937: +2024-11-23 02:12:35.548180: Epoch 7236 +2024-11-23 02:12:35.548291: Current learning rate: 0.00121 +2024-11-23 02:12:54.500461: train_loss -0.827 +2024-11-23 02:12:54.500701: val_loss -0.7267 +2024-11-23 02:12:54.500776: Pseudo dice [0.8515] +2024-11-23 02:12:54.500853: Epoch time: 18.95 s +2024-11-23 02:12:55.686744: +2024-11-23 02:12:55.686983: Epoch 7237 +2024-11-23 02:12:55.687101: Current learning rate: 0.00121 +2024-11-23 02:13:14.575418: train_loss -0.824 +2024-11-23 02:13:14.575722: val_loss -0.7571 +2024-11-23 02:13:14.575801: Pseudo dice [0.8597] +2024-11-23 02:13:14.575879: Epoch time: 18.89 s +2024-11-23 02:13:15.498270: +2024-11-23 02:13:15.498482: Epoch 7238 +2024-11-23 02:13:15.498591: Current learning rate: 0.0012 +2024-11-23 02:13:34.438379: train_loss -0.8292 +2024-11-23 02:13:34.438602: val_loss -0.763 +2024-11-23 02:13:34.438676: Pseudo dice [0.8429] +2024-11-23 02:13:34.438754: Epoch time: 18.94 s +2024-11-23 02:13:35.360435: +2024-11-23 02:13:35.360665: Epoch 7239 +2024-11-23 02:13:35.360781: Current learning rate: 0.0012 +2024-11-23 02:13:54.490820: train_loss -0.8239 +2024-11-23 02:13:54.491082: val_loss -0.7502 +2024-11-23 02:13:54.496321: Pseudo dice [0.8492] +2024-11-23 02:13:54.496518: Epoch time: 19.13 s +2024-11-23 02:13:55.458297: +2024-11-23 02:13:55.458516: Epoch 7240 +2024-11-23 02:13:55.458629: Current learning rate: 0.0012 +2024-11-23 02:14:14.915468: train_loss -0.8218 +2024-11-23 02:14:14.915695: val_loss -0.753 +2024-11-23 02:14:14.915771: Pseudo dice [0.8653] +2024-11-23 02:14:14.915847: Epoch time: 19.46 s +2024-11-23 02:14:15.932047: +2024-11-23 02:14:15.932489: Epoch 7241 +2024-11-23 02:14:15.932628: Current learning rate: 0.0012 +2024-11-23 02:14:34.787511: train_loss -0.8249 +2024-11-23 02:14:34.787759: val_loss -0.7663 +2024-11-23 02:14:34.787835: Pseudo dice [0.849] +2024-11-23 02:14:34.787947: Epoch time: 18.86 s +2024-11-23 02:14:35.704392: +2024-11-23 02:14:35.704833: Epoch 7242 +2024-11-23 02:14:35.704969: Current learning rate: 0.0012 +2024-11-23 02:14:54.714703: train_loss -0.8263 +2024-11-23 02:14:54.714930: val_loss -0.7612 +2024-11-23 02:14:54.717125: Pseudo dice [0.8433] +2024-11-23 02:14:54.717335: Epoch time: 19.01 s +2024-11-23 02:14:55.677179: +2024-11-23 02:14:55.677459: Epoch 7243 +2024-11-23 02:14:55.677579: Current learning rate: 0.0012 +2024-11-23 02:15:14.991178: train_loss -0.8245 +2024-11-23 02:15:14.991421: val_loss -0.7722 +2024-11-23 02:15:14.991498: Pseudo dice [0.8675] +2024-11-23 02:15:14.991578: Epoch time: 19.31 s +2024-11-23 02:15:16.253840: +2024-11-23 02:15:16.254055: Epoch 7244 +2024-11-23 02:15:16.254171: Current learning rate: 0.0012 +2024-11-23 02:15:34.018207: train_loss -0.8298 +2024-11-23 02:15:34.018479: val_loss -0.7242 +2024-11-23 02:15:34.018558: Pseudo dice [0.8495] +2024-11-23 02:15:34.018633: Epoch time: 17.77 s +2024-11-23 02:15:34.940925: +2024-11-23 02:15:34.941181: Epoch 7245 +2024-11-23 02:15:34.941295: Current learning rate: 0.0012 +2024-11-23 02:15:53.805776: train_loss -0.8305 +2024-11-23 02:15:53.805984: val_loss -0.731 +2024-11-23 02:15:53.806859: Pseudo dice [0.8252] +2024-11-23 02:15:53.807088: Epoch time: 18.87 s +2024-11-23 02:15:54.759846: +2024-11-23 02:15:54.760072: Epoch 7246 +2024-11-23 02:15:54.760184: Current learning rate: 0.00119 +2024-11-23 02:16:13.475467: train_loss -0.8262 +2024-11-23 02:16:13.475709: val_loss -0.744 +2024-11-23 02:16:13.475782: Pseudo dice [0.8598] +2024-11-23 02:16:13.475865: Epoch time: 18.72 s +2024-11-23 02:16:14.398741: +2024-11-23 02:16:14.398948: Epoch 7247 +2024-11-23 02:16:14.399068: Current learning rate: 0.00119 +2024-11-23 02:16:34.670291: train_loss -0.8283 +2024-11-23 02:16:34.670515: val_loss -0.7644 +2024-11-23 02:16:34.670592: Pseudo dice [0.8507] +2024-11-23 02:16:34.670666: Epoch time: 20.27 s +2024-11-23 02:16:35.639217: +2024-11-23 02:16:35.639518: Epoch 7248 +2024-11-23 02:16:35.639640: Current learning rate: 0.00119 +2024-11-23 02:16:54.802943: train_loss -0.8242 +2024-11-23 02:16:54.803164: val_loss -0.7447 +2024-11-23 02:16:54.803241: Pseudo dice [0.8345] +2024-11-23 02:16:54.803321: Epoch time: 19.16 s +2024-11-23 02:16:55.750322: +2024-11-23 02:16:55.750580: Epoch 7249 +2024-11-23 02:16:55.750692: Current learning rate: 0.00119 +2024-11-23 02:17:13.179286: train_loss -0.8203 +2024-11-23 02:17:13.191813: val_loss -0.7394 +2024-11-23 02:17:13.191984: Pseudo dice [0.8507] +2024-11-23 02:17:13.192074: Epoch time: 17.43 s +2024-11-23 02:17:14.456078: +2024-11-23 02:17:14.456298: Epoch 7250 +2024-11-23 02:17:14.456419: Current learning rate: 0.00119 +2024-11-23 02:17:33.587510: train_loss -0.8225 +2024-11-23 02:17:33.587757: val_loss -0.7412 +2024-11-23 02:17:33.587832: Pseudo dice [0.8361] +2024-11-23 02:17:33.587913: Epoch time: 19.13 s +2024-11-23 02:17:34.599729: +2024-11-23 02:17:34.599979: Epoch 7251 +2024-11-23 02:17:34.600101: Current learning rate: 0.00119 +2024-11-23 02:17:53.244042: train_loss -0.8241 +2024-11-23 02:17:53.244254: val_loss -0.7415 +2024-11-23 02:17:53.244332: Pseudo dice [0.847] +2024-11-23 02:17:53.244411: Epoch time: 18.65 s +2024-11-23 02:17:54.157997: +2024-11-23 02:17:54.158275: Epoch 7252 +2024-11-23 02:17:54.158388: Current learning rate: 0.00119 +2024-11-23 02:18:11.708963: train_loss -0.824 +2024-11-23 02:18:11.709196: val_loss -0.7696 +2024-11-23 02:18:11.709271: Pseudo dice [0.8496] +2024-11-23 02:18:11.711576: Epoch time: 17.55 s +2024-11-23 02:18:12.874874: +2024-11-23 02:18:12.875115: Epoch 7253 +2024-11-23 02:18:12.875235: Current learning rate: 0.00118 +2024-11-23 02:18:31.099210: train_loss -0.8347 +2024-11-23 02:18:31.099432: val_loss -0.7668 +2024-11-23 02:18:31.099509: Pseudo dice [0.8576] +2024-11-23 02:18:31.099585: Epoch time: 18.23 s +2024-11-23 02:18:32.031058: +2024-11-23 02:18:32.031273: Epoch 7254 +2024-11-23 02:18:32.031389: Current learning rate: 0.00118 +2024-11-23 02:18:50.666421: train_loss -0.8282 +2024-11-23 02:18:50.666702: val_loss -0.7409 +2024-11-23 02:18:50.666824: Pseudo dice [0.8347] +2024-11-23 02:18:50.666909: Epoch time: 18.64 s +2024-11-23 02:18:51.599556: +2024-11-23 02:18:51.599766: Epoch 7255 +2024-11-23 02:18:51.599879: Current learning rate: 0.00118 +2024-11-23 02:19:09.543147: train_loss -0.8321 +2024-11-23 02:19:09.543362: val_loss -0.7717 +2024-11-23 02:19:09.543492: Pseudo dice [0.8644] +2024-11-23 02:19:09.543607: Epoch time: 17.94 s +2024-11-23 02:19:10.862712: +2024-11-23 02:19:10.862925: Epoch 7256 +2024-11-23 02:19:10.863047: Current learning rate: 0.00118 +2024-11-23 02:19:29.057718: train_loss -0.8218 +2024-11-23 02:19:29.057972: val_loss -0.7685 +2024-11-23 02:19:29.058062: Pseudo dice [0.8462] +2024-11-23 02:19:29.058149: Epoch time: 18.2 s +2024-11-23 02:19:29.980793: +2024-11-23 02:19:29.981028: Epoch 7257 +2024-11-23 02:19:29.981139: Current learning rate: 0.00118 +2024-11-23 02:19:49.324890: train_loss -0.8294 +2024-11-23 02:19:49.325165: val_loss -0.7749 +2024-11-23 02:19:49.325243: Pseudo dice [0.8512] +2024-11-23 02:19:49.325327: Epoch time: 19.34 s +2024-11-23 02:19:50.250077: +2024-11-23 02:19:50.250297: Epoch 7258 +2024-11-23 02:19:50.250412: Current learning rate: 0.00118 +2024-11-23 02:20:09.429337: train_loss -0.8277 +2024-11-23 02:20:09.429569: val_loss -0.7583 +2024-11-23 02:20:09.429644: Pseudo dice [0.8236] +2024-11-23 02:20:09.429719: Epoch time: 19.18 s +2024-11-23 02:20:10.347321: +2024-11-23 02:20:10.347534: Epoch 7259 +2024-11-23 02:20:10.347648: Current learning rate: 0.00118 +2024-11-23 02:20:29.009347: train_loss -0.8321 +2024-11-23 02:20:29.009582: val_loss -0.736 +2024-11-23 02:20:29.009655: Pseudo dice [0.8415] +2024-11-23 02:20:29.009731: Epoch time: 18.66 s +2024-11-23 02:20:29.942413: +2024-11-23 02:20:29.942625: Epoch 7260 +2024-11-23 02:20:29.942760: Current learning rate: 0.00117 +2024-11-23 02:20:47.698726: train_loss -0.8274 +2024-11-23 02:20:47.698967: val_loss -0.7694 +2024-11-23 02:20:47.699053: Pseudo dice [0.8421] +2024-11-23 02:20:47.699140: Epoch time: 17.76 s +2024-11-23 02:20:48.619105: +2024-11-23 02:20:48.619322: Epoch 7261 +2024-11-23 02:20:48.619431: Current learning rate: 0.00117 +2024-11-23 02:21:06.960722: train_loss -0.8281 +2024-11-23 02:21:06.960952: val_loss -0.7554 +2024-11-23 02:21:06.961037: Pseudo dice [0.8451] +2024-11-23 02:21:06.961116: Epoch time: 18.34 s +2024-11-23 02:21:07.880636: +2024-11-23 02:21:07.880860: Epoch 7262 +2024-11-23 02:21:07.880971: Current learning rate: 0.00117 +2024-11-23 02:21:26.276375: train_loss -0.8332 +2024-11-23 02:21:26.276612: val_loss -0.7636 +2024-11-23 02:21:26.276691: Pseudo dice [0.8579] +2024-11-23 02:21:26.276771: Epoch time: 18.4 s +2024-11-23 02:21:27.257040: +2024-11-23 02:21:27.257274: Epoch 7263 +2024-11-23 02:21:27.257391: Current learning rate: 0.00117 +2024-11-23 02:21:45.115988: train_loss -0.8307 +2024-11-23 02:21:45.121366: val_loss -0.7771 +2024-11-23 02:21:45.121534: Pseudo dice [0.8474] +2024-11-23 02:21:45.121618: Epoch time: 17.86 s +2024-11-23 02:21:46.112418: +2024-11-23 02:21:46.112653: Epoch 7264 +2024-11-23 02:21:46.112766: Current learning rate: 0.00117 +2024-11-23 02:22:05.513421: train_loss -0.8291 +2024-11-23 02:22:05.513641: val_loss -0.7808 +2024-11-23 02:22:05.513718: Pseudo dice [0.8408] +2024-11-23 02:22:05.513807: Epoch time: 19.4 s +2024-11-23 02:22:06.442175: +2024-11-23 02:22:06.442404: Epoch 7265 +2024-11-23 02:22:06.442518: Current learning rate: 0.00117 +2024-11-23 02:22:24.962322: train_loss -0.8269 +2024-11-23 02:22:24.962572: val_loss -0.7803 +2024-11-23 02:22:24.962651: Pseudo dice [0.8652] +2024-11-23 02:22:24.962736: Epoch time: 18.52 s +2024-11-23 02:22:25.879821: +2024-11-23 02:22:25.880029: Epoch 7266 +2024-11-23 02:22:25.880141: Current learning rate: 0.00117 +2024-11-23 02:22:45.324187: train_loss -0.8296 +2024-11-23 02:22:45.324491: val_loss -0.7485 +2024-11-23 02:22:45.324568: Pseudo dice [0.8575] +2024-11-23 02:22:45.324646: Epoch time: 19.45 s +2024-11-23 02:22:46.626254: +2024-11-23 02:22:46.626455: Epoch 7267 +2024-11-23 02:22:46.626569: Current learning rate: 0.00116 +2024-11-23 02:23:05.582279: train_loss -0.8309 +2024-11-23 02:23:05.582520: val_loss -0.7664 +2024-11-23 02:23:05.582605: Pseudo dice [0.8708] +2024-11-23 02:23:05.582683: Epoch time: 18.96 s +2024-11-23 02:23:06.499923: +2024-11-23 02:23:06.500160: Epoch 7268 +2024-11-23 02:23:06.500273: Current learning rate: 0.00116 +2024-11-23 02:23:24.919229: train_loss -0.8325 +2024-11-23 02:23:24.919456: val_loss -0.7719 +2024-11-23 02:23:24.919592: Pseudo dice [0.8613] +2024-11-23 02:23:24.919681: Epoch time: 18.42 s +2024-11-23 02:23:25.841846: +2024-11-23 02:23:25.842071: Epoch 7269 +2024-11-23 02:23:25.842181: Current learning rate: 0.00116 +2024-11-23 02:23:44.744816: train_loss -0.828 +2024-11-23 02:23:44.745067: val_loss -0.7669 +2024-11-23 02:23:44.745147: Pseudo dice [0.8601] +2024-11-23 02:23:44.745228: Epoch time: 18.9 s +2024-11-23 02:23:45.667719: +2024-11-23 02:23:45.667951: Epoch 7270 +2024-11-23 02:23:45.668067: Current learning rate: 0.00116 +2024-11-23 02:24:04.986569: train_loss -0.8256 +2024-11-23 02:24:04.986790: val_loss -0.7509 +2024-11-23 02:24:04.986866: Pseudo dice [0.8317] +2024-11-23 02:24:04.986941: Epoch time: 19.32 s +2024-11-23 02:24:05.912654: +2024-11-23 02:24:05.912865: Epoch 7271 +2024-11-23 02:24:05.912982: Current learning rate: 0.00116 +2024-11-23 02:24:23.615730: train_loss -0.827 +2024-11-23 02:24:23.615952: val_loss -0.741 +2024-11-23 02:24:23.616035: Pseudo dice [0.8461] +2024-11-23 02:24:23.616111: Epoch time: 17.7 s +2024-11-23 02:24:24.534139: +2024-11-23 02:24:24.534350: Epoch 7272 +2024-11-23 02:24:24.534460: Current learning rate: 0.00116 +2024-11-23 02:24:43.276988: train_loss -0.8302 +2024-11-23 02:24:43.284940: val_loss -0.7542 +2024-11-23 02:24:43.285064: Pseudo dice [0.8503] +2024-11-23 02:24:43.285146: Epoch time: 18.74 s +2024-11-23 02:24:44.236432: +2024-11-23 02:24:44.236656: Epoch 7273 +2024-11-23 02:24:44.236771: Current learning rate: 0.00116 +2024-11-23 02:25:03.301672: train_loss -0.8217 +2024-11-23 02:25:03.301916: val_loss -0.7453 +2024-11-23 02:25:03.301998: Pseudo dice [0.8399] +2024-11-23 02:25:03.302082: Epoch time: 19.07 s +2024-11-23 02:25:04.237623: +2024-11-23 02:25:04.237840: Epoch 7274 +2024-11-23 02:25:04.237954: Current learning rate: 0.00115 +2024-11-23 02:25:22.818860: train_loss -0.8208 +2024-11-23 02:25:22.819085: val_loss -0.7655 +2024-11-23 02:25:22.819165: Pseudo dice [0.8546] +2024-11-23 02:25:22.819244: Epoch time: 18.58 s +2024-11-23 02:25:23.740865: +2024-11-23 02:25:23.741123: Epoch 7275 +2024-11-23 02:25:23.741237: Current learning rate: 0.00115 +2024-11-23 02:25:42.608784: train_loss -0.8195 +2024-11-23 02:25:42.609006: val_loss -0.7563 +2024-11-23 02:25:42.609083: Pseudo dice [0.8702] +2024-11-23 02:25:42.609160: Epoch time: 18.87 s +2024-11-23 02:25:43.519196: +2024-11-23 02:25:43.519419: Epoch 7276 +2024-11-23 02:25:43.519530: Current learning rate: 0.00115 +2024-11-23 02:26:02.008544: train_loss -0.8259 +2024-11-23 02:26:02.008749: val_loss -0.7594 +2024-11-23 02:26:02.008845: Pseudo dice [0.8521] +2024-11-23 02:26:02.008925: Epoch time: 18.49 s +2024-11-23 02:26:02.921121: +2024-11-23 02:26:02.921298: Epoch 7277 +2024-11-23 02:26:02.921401: Current learning rate: 0.00115 +2024-11-23 02:26:21.427921: train_loss -0.8227 +2024-11-23 02:26:21.430346: val_loss -0.7358 +2024-11-23 02:26:21.430491: Pseudo dice [0.8609] +2024-11-23 02:26:21.430573: Epoch time: 18.51 s +2024-11-23 02:26:22.467354: +2024-11-23 02:26:22.467571: Epoch 7278 +2024-11-23 02:26:22.467685: Current learning rate: 0.00115 +2024-11-23 02:26:41.977030: train_loss -0.8221 +2024-11-23 02:26:41.977312: val_loss -0.7695 +2024-11-23 02:26:41.977396: Pseudo dice [0.849] +2024-11-23 02:26:41.977473: Epoch time: 19.51 s +2024-11-23 02:26:43.255722: +2024-11-23 02:26:43.255941: Epoch 7279 +2024-11-23 02:26:43.256055: Current learning rate: 0.00115 +2024-11-23 02:27:02.431477: train_loss -0.8285 +2024-11-23 02:27:02.431693: val_loss -0.7482 +2024-11-23 02:27:02.431768: Pseudo dice [0.8442] +2024-11-23 02:27:02.431846: Epoch time: 19.18 s +2024-11-23 02:27:03.352157: +2024-11-23 02:27:03.352374: Epoch 7280 +2024-11-23 02:27:03.352482: Current learning rate: 0.00115 +2024-11-23 02:27:21.663579: train_loss -0.8272 +2024-11-23 02:27:21.663833: val_loss -0.7624 +2024-11-23 02:27:21.663909: Pseudo dice [0.8865] +2024-11-23 02:27:21.663989: Epoch time: 18.31 s +2024-11-23 02:27:22.630320: +2024-11-23 02:27:22.630559: Epoch 7281 +2024-11-23 02:27:22.630670: Current learning rate: 0.00114 +2024-11-23 02:27:41.631248: train_loss -0.8271 +2024-11-23 02:27:41.631453: val_loss -0.7595 +2024-11-23 02:27:41.631527: Pseudo dice [0.8646] +2024-11-23 02:27:41.631602: Epoch time: 19.0 s +2024-11-23 02:27:42.545682: +2024-11-23 02:27:42.545903: Epoch 7282 +2024-11-23 02:27:42.546022: Current learning rate: 0.00114 +2024-11-23 02:28:01.666393: train_loss -0.8305 +2024-11-23 02:28:01.666608: val_loss -0.7761 +2024-11-23 02:28:01.666687: Pseudo dice [0.8723] +2024-11-23 02:28:01.666767: Epoch time: 19.12 s +2024-11-23 02:28:02.585395: +2024-11-23 02:28:02.585636: Epoch 7283 +2024-11-23 02:28:02.585754: Current learning rate: 0.00114 +2024-11-23 02:28:21.030287: train_loss -0.8349 +2024-11-23 02:28:21.030514: val_loss -0.76 +2024-11-23 02:28:21.030587: Pseudo dice [0.8516] +2024-11-23 02:28:21.030662: Epoch time: 18.45 s +2024-11-23 02:28:21.951918: +2024-11-23 02:28:21.952133: Epoch 7284 +2024-11-23 02:28:21.952244: Current learning rate: 0.00114 +2024-11-23 02:28:41.235672: train_loss -0.8281 +2024-11-23 02:28:41.235964: val_loss -0.7263 +2024-11-23 02:28:41.236069: Pseudo dice [0.8493] +2024-11-23 02:28:41.236162: Epoch time: 19.28 s +2024-11-23 02:28:42.228310: +2024-11-23 02:28:42.228555: Epoch 7285 +2024-11-23 02:28:42.228671: Current learning rate: 0.00114 +2024-11-23 02:29:00.574795: train_loss -0.8248 +2024-11-23 02:29:00.575016: val_loss -0.7516 +2024-11-23 02:29:00.575090: Pseudo dice [0.8533] +2024-11-23 02:29:00.575164: Epoch time: 18.35 s +2024-11-23 02:29:01.554511: +2024-11-23 02:29:01.554734: Epoch 7286 +2024-11-23 02:29:01.554847: Current learning rate: 0.00114 +2024-11-23 02:29:20.299541: train_loss -0.8315 +2024-11-23 02:29:20.299751: val_loss -0.736 +2024-11-23 02:29:20.299826: Pseudo dice [0.8363] +2024-11-23 02:29:20.299905: Epoch time: 18.75 s +2024-11-23 02:29:21.217741: +2024-11-23 02:29:21.217937: Epoch 7287 +2024-11-23 02:29:21.218053: Current learning rate: 0.00114 +2024-11-23 02:29:40.102581: train_loss -0.8303 +2024-11-23 02:29:40.102801: val_loss -0.7507 +2024-11-23 02:29:40.102879: Pseudo dice [0.8289] +2024-11-23 02:29:40.102962: Epoch time: 18.89 s +2024-11-23 02:29:41.018998: +2024-11-23 02:29:41.019202: Epoch 7288 +2024-11-23 02:29:41.019312: Current learning rate: 0.00113 +2024-11-23 02:29:58.723099: train_loss -0.8331 +2024-11-23 02:29:58.723349: val_loss -0.7703 +2024-11-23 02:29:58.723423: Pseudo dice [0.8559] +2024-11-23 02:29:58.723504: Epoch time: 17.7 s +2024-11-23 02:29:59.648642: +2024-11-23 02:29:59.648842: Epoch 7289 +2024-11-23 02:29:59.648954: Current learning rate: 0.00113 +2024-11-23 02:30:18.408723: train_loss -0.8233 +2024-11-23 02:30:18.408937: val_loss -0.7685 +2024-11-23 02:30:18.409016: Pseudo dice [0.8517] +2024-11-23 02:30:18.409092: Epoch time: 18.76 s +2024-11-23 02:30:19.892420: +2024-11-23 02:30:19.892631: Epoch 7290 +2024-11-23 02:30:19.892741: Current learning rate: 0.00113 +2024-11-23 02:30:39.321458: train_loss -0.8215 +2024-11-23 02:30:39.323903: val_loss -0.758 +2024-11-23 02:30:39.324001: Pseudo dice [0.8443] +2024-11-23 02:30:39.326366: Epoch time: 19.43 s +2024-11-23 02:30:40.318915: +2024-11-23 02:30:40.319203: Epoch 7291 +2024-11-23 02:30:40.319315: Current learning rate: 0.00113 +2024-11-23 02:30:59.919334: train_loss -0.8232 +2024-11-23 02:30:59.919572: val_loss -0.7404 +2024-11-23 02:30:59.919650: Pseudo dice [0.8488] +2024-11-23 02:30:59.919728: Epoch time: 19.6 s +2024-11-23 02:31:00.847573: +2024-11-23 02:31:00.847821: Epoch 7292 +2024-11-23 02:31:00.847950: Current learning rate: 0.00113 +2024-11-23 02:31:20.101422: train_loss -0.8296 +2024-11-23 02:31:20.101668: val_loss -0.7339 +2024-11-23 02:31:20.101744: Pseudo dice [0.8486] +2024-11-23 02:31:20.101831: Epoch time: 19.25 s +2024-11-23 02:31:21.029251: +2024-11-23 02:31:21.029456: Epoch 7293 +2024-11-23 02:31:21.029573: Current learning rate: 0.00113 +2024-11-23 02:31:39.264639: train_loss -0.8292 +2024-11-23 02:31:39.264870: val_loss -0.77 +2024-11-23 02:31:39.264947: Pseudo dice [0.867] +2024-11-23 02:31:39.265032: Epoch time: 18.24 s +2024-11-23 02:31:40.191478: +2024-11-23 02:31:40.191699: Epoch 7294 +2024-11-23 02:31:40.191812: Current learning rate: 0.00112 +2024-11-23 02:31:59.740047: train_loss -0.828 +2024-11-23 02:31:59.740270: val_loss -0.7878 +2024-11-23 02:31:59.740348: Pseudo dice [0.8642] +2024-11-23 02:31:59.740454: Epoch time: 19.55 s +2024-11-23 02:32:00.665250: +2024-11-23 02:32:00.665521: Epoch 7295 +2024-11-23 02:32:00.665634: Current learning rate: 0.00112 +2024-11-23 02:32:20.072157: train_loss -0.826 +2024-11-23 02:32:20.072387: val_loss -0.7823 +2024-11-23 02:32:20.072464: Pseudo dice [0.8528] +2024-11-23 02:32:20.072546: Epoch time: 19.41 s +2024-11-23 02:32:21.000322: +2024-11-23 02:32:21.000555: Epoch 7296 +2024-11-23 02:32:21.000671: Current learning rate: 0.00112 +2024-11-23 02:32:39.451566: train_loss -0.8184 +2024-11-23 02:32:39.451787: val_loss -0.7564 +2024-11-23 02:32:39.451865: Pseudo dice [0.8595] +2024-11-23 02:32:39.452099: Epoch time: 18.45 s +2024-11-23 02:32:40.373517: +2024-11-23 02:32:40.373768: Epoch 7297 +2024-11-23 02:32:40.373896: Current learning rate: 0.00112 +2024-11-23 02:32:58.998259: train_loss -0.8274 +2024-11-23 02:32:58.998479: val_loss -0.7783 +2024-11-23 02:32:58.998553: Pseudo dice [0.8688] +2024-11-23 02:32:59.003798: Epoch time: 18.63 s +2024-11-23 02:32:59.983395: +2024-11-23 02:32:59.983634: Epoch 7298 +2024-11-23 02:32:59.983751: Current learning rate: 0.00112 +2024-11-23 02:33:17.968114: train_loss -0.8305 +2024-11-23 02:33:17.968332: val_loss -0.77 +2024-11-23 02:33:17.968406: Pseudo dice [0.8656] +2024-11-23 02:33:17.970674: Epoch time: 17.99 s +2024-11-23 02:33:19.106750: +2024-11-23 02:33:19.106989: Epoch 7299 +2024-11-23 02:33:19.107113: Current learning rate: 0.00112 +2024-11-23 02:33:38.814792: train_loss -0.83 +2024-11-23 02:33:38.815059: val_loss -0.7905 +2024-11-23 02:33:38.815137: Pseudo dice [0.8723] +2024-11-23 02:33:38.815220: Epoch time: 19.71 s +2024-11-23 02:33:40.075171: +2024-11-23 02:33:40.075371: Epoch 7300 +2024-11-23 02:33:40.075478: Current learning rate: 0.00112 +2024-11-23 02:33:58.326441: train_loss -0.8294 +2024-11-23 02:33:58.326654: val_loss -0.772 +2024-11-23 02:33:58.326728: Pseudo dice [0.8402] +2024-11-23 02:33:58.326804: Epoch time: 18.25 s +2024-11-23 02:33:59.251517: +2024-11-23 02:33:59.251718: Epoch 7301 +2024-11-23 02:33:59.251846: Current learning rate: 0.00111 +2024-11-23 02:34:19.454128: train_loss -0.8241 +2024-11-23 02:34:19.454359: val_loss -0.7491 +2024-11-23 02:34:19.454439: Pseudo dice [0.8345] +2024-11-23 02:34:19.454517: Epoch time: 20.2 s +2024-11-23 02:34:20.799836: +2024-11-23 02:34:20.800272: Epoch 7302 +2024-11-23 02:34:20.800406: Current learning rate: 0.00111 +2024-11-23 02:34:40.047503: train_loss -0.8239 +2024-11-23 02:34:40.047774: val_loss -0.7838 +2024-11-23 02:34:40.047853: Pseudo dice [0.8608] +2024-11-23 02:34:40.047944: Epoch time: 19.25 s +2024-11-23 02:34:40.976721: +2024-11-23 02:34:40.977183: Epoch 7303 +2024-11-23 02:34:40.977318: Current learning rate: 0.00111 +2024-11-23 02:34:58.580901: train_loss -0.8238 +2024-11-23 02:34:58.581131: val_loss -0.737 +2024-11-23 02:34:58.581206: Pseudo dice [0.8195] +2024-11-23 02:34:58.581286: Epoch time: 17.6 s +2024-11-23 02:34:59.507143: +2024-11-23 02:34:59.507576: Epoch 7304 +2024-11-23 02:34:59.507707: Current learning rate: 0.00111 +2024-11-23 02:35:18.708495: train_loss -0.8313 +2024-11-23 02:35:18.708725: val_loss -0.7564 +2024-11-23 02:35:18.708802: Pseudo dice [0.841] +2024-11-23 02:35:18.708883: Epoch time: 19.2 s +2024-11-23 02:35:19.628983: +2024-11-23 02:35:19.629413: Epoch 7305 +2024-11-23 02:35:19.629543: Current learning rate: 0.00111 +2024-11-23 02:35:37.303246: train_loss -0.8346 +2024-11-23 02:35:37.303516: val_loss -0.7501 +2024-11-23 02:35:37.303593: Pseudo dice [0.8596] +2024-11-23 02:35:37.303682: Epoch time: 17.68 s +2024-11-23 02:35:38.230156: +2024-11-23 02:35:38.230569: Epoch 7306 +2024-11-23 02:35:38.230702: Current learning rate: 0.00111 +2024-11-23 02:35:56.364732: train_loss -0.8329 +2024-11-23 02:35:56.364961: val_loss -0.7369 +2024-11-23 02:35:56.365045: Pseudo dice [0.847] +2024-11-23 02:35:56.365122: Epoch time: 18.14 s +2024-11-23 02:35:57.293639: +2024-11-23 02:35:57.294096: Epoch 7307 +2024-11-23 02:35:57.294237: Current learning rate: 0.00111 +2024-11-23 02:36:14.820590: train_loss -0.8329 +2024-11-23 02:36:14.820817: val_loss -0.7664 +2024-11-23 02:36:14.820901: Pseudo dice [0.8333] +2024-11-23 02:36:14.821001: Epoch time: 17.53 s +2024-11-23 02:36:15.750321: +2024-11-23 02:36:15.750735: Epoch 7308 +2024-11-23 02:36:15.750872: Current learning rate: 0.0011 +2024-11-23 02:36:34.337035: train_loss -0.8295 +2024-11-23 02:36:34.337264: val_loss -0.7346 +2024-11-23 02:36:34.337339: Pseudo dice [0.8489] +2024-11-23 02:36:34.337415: Epoch time: 18.59 s +2024-11-23 02:36:35.262240: +2024-11-23 02:36:35.262701: Epoch 7309 +2024-11-23 02:36:35.262839: Current learning rate: 0.0011 +2024-11-23 02:36:53.523809: train_loss -0.8245 +2024-11-23 02:36:53.526286: val_loss -0.7447 +2024-11-23 02:36:53.526381: Pseudo dice [0.8461] +2024-11-23 02:36:53.526470: Epoch time: 18.26 s +2024-11-23 02:36:54.652250: +2024-11-23 02:36:54.652703: Epoch 7310 +2024-11-23 02:36:54.652844: Current learning rate: 0.0011 +2024-11-23 02:37:13.455648: train_loss -0.8303 +2024-11-23 02:37:13.455868: val_loss -0.7694 +2024-11-23 02:37:13.455944: Pseudo dice [0.8683] +2024-11-23 02:37:13.456026: Epoch time: 18.8 s +2024-11-23 02:37:14.382846: +2024-11-23 02:37:14.383322: Epoch 7311 +2024-11-23 02:37:14.383456: Current learning rate: 0.0011 +2024-11-23 02:37:33.791513: train_loss -0.8348 +2024-11-23 02:37:33.791724: val_loss -0.7363 +2024-11-23 02:37:33.791800: Pseudo dice [0.8457] +2024-11-23 02:37:33.791876: Epoch time: 19.41 s +2024-11-23 02:37:34.708242: +2024-11-23 02:37:34.708673: Epoch 7312 +2024-11-23 02:37:34.708818: Current learning rate: 0.0011 +2024-11-23 02:37:52.616887: train_loss -0.8288 +2024-11-23 02:37:52.617114: val_loss -0.7381 +2024-11-23 02:37:52.617189: Pseudo dice [0.8395] +2024-11-23 02:37:52.617267: Epoch time: 17.91 s +2024-11-23 02:37:53.963687: +2024-11-23 02:37:53.963886: Epoch 7313 +2024-11-23 02:37:53.964005: Current learning rate: 0.0011 +2024-11-23 02:38:13.662760: train_loss -0.8233 +2024-11-23 02:38:13.663116: val_loss -0.7214 +2024-11-23 02:38:13.663201: Pseudo dice [0.8553] +2024-11-23 02:38:13.663285: Epoch time: 19.7 s +2024-11-23 02:38:14.686194: +2024-11-23 02:38:14.686421: Epoch 7314 +2024-11-23 02:38:14.686533: Current learning rate: 0.0011 +2024-11-23 02:38:33.918302: train_loss -0.8278 +2024-11-23 02:38:33.918570: val_loss -0.7665 +2024-11-23 02:38:33.918650: Pseudo dice [0.8676] +2024-11-23 02:38:33.918731: Epoch time: 19.23 s +2024-11-23 02:38:34.842988: +2024-11-23 02:38:34.843205: Epoch 7315 +2024-11-23 02:38:34.843320: Current learning rate: 0.00109 +2024-11-23 02:38:53.687409: train_loss -0.8228 +2024-11-23 02:38:53.687624: val_loss -0.7546 +2024-11-23 02:38:53.687700: Pseudo dice [0.8309] +2024-11-23 02:38:53.687776: Epoch time: 18.85 s +2024-11-23 02:38:54.613984: +2024-11-23 02:38:54.614315: Epoch 7316 +2024-11-23 02:38:54.614431: Current learning rate: 0.00109 +2024-11-23 02:39:13.000834: train_loss -0.8313 +2024-11-23 02:39:13.001086: val_loss -0.7465 +2024-11-23 02:39:13.001161: Pseudo dice [0.8475] +2024-11-23 02:39:13.001244: Epoch time: 18.39 s +2024-11-23 02:39:13.929004: +2024-11-23 02:39:13.929260: Epoch 7317 +2024-11-23 02:39:13.929374: Current learning rate: 0.00109 +2024-11-23 02:39:32.098101: train_loss -0.8355 +2024-11-23 02:39:32.098335: val_loss -0.7483 +2024-11-23 02:39:32.098408: Pseudo dice [0.843] +2024-11-23 02:39:32.098486: Epoch time: 18.17 s +2024-11-23 02:39:33.224131: +2024-11-23 02:39:33.224335: Epoch 7318 +2024-11-23 02:39:33.224446: Current learning rate: 0.00109 +2024-11-23 02:39:51.968277: train_loss -0.829 +2024-11-23 02:39:51.968490: val_loss -0.754 +2024-11-23 02:39:51.968565: Pseudo dice [0.8613] +2024-11-23 02:39:51.968643: Epoch time: 18.74 s +2024-11-23 02:39:52.889443: +2024-11-23 02:39:52.889675: Epoch 7319 +2024-11-23 02:39:52.889790: Current learning rate: 0.00109 +2024-11-23 02:40:11.714615: train_loss -0.8265 +2024-11-23 02:40:11.714848: val_loss -0.7628 +2024-11-23 02:40:11.720160: Pseudo dice [0.8526] +2024-11-23 02:40:11.720284: Epoch time: 18.83 s +2024-11-23 02:40:12.685320: +2024-11-23 02:40:12.685558: Epoch 7320 +2024-11-23 02:40:12.685674: Current learning rate: 0.00109 +2024-11-23 02:40:30.876545: train_loss -0.8276 +2024-11-23 02:40:30.876787: val_loss -0.7945 +2024-11-23 02:40:30.876859: Pseudo dice [0.8668] +2024-11-23 02:40:30.876939: Epoch time: 18.19 s +2024-11-23 02:40:32.020364: +2024-11-23 02:40:32.020581: Epoch 7321 +2024-11-23 02:40:32.020692: Current learning rate: 0.00109 +2024-11-23 02:40:50.348839: train_loss -0.8254 +2024-11-23 02:40:50.349087: val_loss -0.761 +2024-11-23 02:40:50.349169: Pseudo dice [0.8528] +2024-11-23 02:40:50.349247: Epoch time: 18.33 s +2024-11-23 02:40:51.410545: +2024-11-23 02:40:51.410758: Epoch 7322 +2024-11-23 02:40:51.410876: Current learning rate: 0.00108 +2024-11-23 02:41:09.399324: train_loss -0.8304 +2024-11-23 02:41:09.399553: val_loss -0.7587 +2024-11-23 02:41:09.399630: Pseudo dice [0.8449] +2024-11-23 02:41:09.399886: Epoch time: 17.99 s +2024-11-23 02:41:10.327522: +2024-11-23 02:41:10.327741: Epoch 7323 +2024-11-23 02:41:10.327853: Current learning rate: 0.00108 +2024-11-23 02:41:28.943542: train_loss -0.8286 +2024-11-23 02:41:28.943795: val_loss -0.7708 +2024-11-23 02:41:28.943871: Pseudo dice [0.862] +2024-11-23 02:41:28.943955: Epoch time: 18.62 s +2024-11-23 02:41:29.872250: +2024-11-23 02:41:29.872463: Epoch 7324 +2024-11-23 02:41:29.872577: Current learning rate: 0.00108 +2024-11-23 02:41:48.923517: train_loss -0.8286 +2024-11-23 02:41:48.923739: val_loss -0.763 +2024-11-23 02:41:48.923814: Pseudo dice [0.8626] +2024-11-23 02:41:48.923892: Epoch time: 19.05 s +2024-11-23 02:41:50.318231: +2024-11-23 02:41:50.318761: Epoch 7325 +2024-11-23 02:41:50.318898: Current learning rate: 0.00108 +2024-11-23 02:42:08.971882: train_loss -0.8298 +2024-11-23 02:42:08.972112: val_loss -0.7511 +2024-11-23 02:42:08.972188: Pseudo dice [0.8292] +2024-11-23 02:42:08.972265: Epoch time: 18.65 s +2024-11-23 02:42:09.981211: +2024-11-23 02:42:09.981635: Epoch 7326 +2024-11-23 02:42:09.981769: Current learning rate: 0.00108 +2024-11-23 02:42:28.343676: train_loss -0.8273 +2024-11-23 02:42:28.343917: val_loss -0.7283 +2024-11-23 02:42:28.344003: Pseudo dice [0.8642] +2024-11-23 02:42:28.344088: Epoch time: 18.36 s +2024-11-23 02:42:29.408158: +2024-11-23 02:42:29.408645: Epoch 7327 +2024-11-23 02:42:29.408788: Current learning rate: 0.00108 +2024-11-23 02:42:48.302915: train_loss -0.8287 +2024-11-23 02:42:48.303192: val_loss -0.7754 +2024-11-23 02:42:48.303273: Pseudo dice [0.8561] +2024-11-23 02:42:48.303365: Epoch time: 18.89 s +2024-11-23 02:42:49.293875: +2024-11-23 02:42:49.294318: Epoch 7328 +2024-11-23 02:42:49.294457: Current learning rate: 0.00108 +2024-11-23 02:43:08.086166: train_loss -0.8322 +2024-11-23 02:43:08.086390: val_loss -0.7539 +2024-11-23 02:43:08.086463: Pseudo dice [0.8512] +2024-11-23 02:43:08.086540: Epoch time: 18.79 s +2024-11-23 02:43:09.009337: +2024-11-23 02:43:09.009792: Epoch 7329 +2024-11-23 02:43:09.009926: Current learning rate: 0.00107 +2024-11-23 02:43:27.749530: train_loss -0.8275 +2024-11-23 02:43:27.751291: val_loss -0.753 +2024-11-23 02:43:27.751414: Pseudo dice [0.8545] +2024-11-23 02:43:27.751499: Epoch time: 18.74 s +2024-11-23 02:43:28.675555: +2024-11-23 02:43:28.675988: Epoch 7330 +2024-11-23 02:43:28.676130: Current learning rate: 0.00107 +2024-11-23 02:43:47.079823: train_loss -0.8283 +2024-11-23 02:43:47.080054: val_loss -0.7614 +2024-11-23 02:43:47.080129: Pseudo dice [0.8516] +2024-11-23 02:43:47.080209: Epoch time: 18.41 s +2024-11-23 02:43:48.141264: +2024-11-23 02:43:48.141710: Epoch 7331 +2024-11-23 02:43:48.141850: Current learning rate: 0.00107 +2024-11-23 02:44:06.460954: train_loss -0.825 +2024-11-23 02:44:06.461185: val_loss -0.7639 +2024-11-23 02:44:06.461261: Pseudo dice [0.8635] +2024-11-23 02:44:06.461340: Epoch time: 18.32 s +2024-11-23 02:44:07.383667: +2024-11-23 02:44:07.384115: Epoch 7332 +2024-11-23 02:44:07.384276: Current learning rate: 0.00107 +2024-11-23 02:44:25.123610: train_loss -0.8305 +2024-11-23 02:44:25.123836: val_loss -0.7491 +2024-11-23 02:44:25.123914: Pseudo dice [0.8558] +2024-11-23 02:44:25.123989: Epoch time: 17.74 s +2024-11-23 02:44:26.048988: +2024-11-23 02:44:26.049484: Epoch 7333 +2024-11-23 02:44:26.049623: Current learning rate: 0.00107 +2024-11-23 02:44:44.925891: train_loss -0.8255 +2024-11-23 02:44:44.926125: val_loss -0.7431 +2024-11-23 02:44:44.926199: Pseudo dice [0.8362] +2024-11-23 02:44:44.926278: Epoch time: 18.88 s +2024-11-23 02:44:45.852833: +2024-11-23 02:44:45.853261: Epoch 7334 +2024-11-23 02:44:45.853391: Current learning rate: 0.00107 +2024-11-23 02:45:04.083485: train_loss -0.8309 +2024-11-23 02:45:04.083715: val_loss -0.7749 +2024-11-23 02:45:04.083792: Pseudo dice [0.846] +2024-11-23 02:45:04.083869: Epoch time: 18.23 s +2024-11-23 02:45:05.144301: +2024-11-23 02:45:05.144786: Epoch 7335 +2024-11-23 02:45:05.144923: Current learning rate: 0.00107 +2024-11-23 02:45:23.204784: train_loss -0.8282 +2024-11-23 02:45:23.205044: val_loss -0.7554 +2024-11-23 02:45:23.205120: Pseudo dice [0.8504] +2024-11-23 02:45:23.205200: Epoch time: 18.06 s +2024-11-23 02:45:24.518735: +2024-11-23 02:45:24.518985: Epoch 7336 +2024-11-23 02:45:24.519102: Current learning rate: 0.00106 +2024-11-23 02:45:43.213358: train_loss -0.8329 +2024-11-23 02:45:43.213602: val_loss -0.7619 +2024-11-23 02:45:43.213679: Pseudo dice [0.8551] +2024-11-23 02:45:43.213763: Epoch time: 18.7 s +2024-11-23 02:45:44.137184: +2024-11-23 02:45:44.137423: Epoch 7337 +2024-11-23 02:45:44.137535: Current learning rate: 0.00106 +2024-11-23 02:46:03.248723: train_loss -0.8367 +2024-11-23 02:46:03.248944: val_loss -0.7491 +2024-11-23 02:46:03.249030: Pseudo dice [0.8411] +2024-11-23 02:46:03.249108: Epoch time: 19.11 s +2024-11-23 02:46:04.175112: +2024-11-23 02:46:04.175325: Epoch 7338 +2024-11-23 02:46:04.175436: Current learning rate: 0.00106 +2024-11-23 02:46:23.306085: train_loss -0.832 +2024-11-23 02:46:23.306339: val_loss -0.7679 +2024-11-23 02:46:23.306416: Pseudo dice [0.8605] +2024-11-23 02:46:23.306497: Epoch time: 19.13 s +2024-11-23 02:46:24.238644: +2024-11-23 02:46:24.238886: Epoch 7339 +2024-11-23 02:46:24.239008: Current learning rate: 0.00106 +2024-11-23 02:46:43.740622: train_loss -0.8198 +2024-11-23 02:46:43.740845: val_loss -0.7461 +2024-11-23 02:46:43.740921: Pseudo dice [0.8551] +2024-11-23 02:46:43.741001: Epoch time: 19.5 s +2024-11-23 02:46:44.714257: +2024-11-23 02:46:44.714475: Epoch 7340 +2024-11-23 02:46:44.714586: Current learning rate: 0.00106 +2024-11-23 02:47:03.663807: train_loss -0.8299 +2024-11-23 02:47:03.664031: val_loss -0.7632 +2024-11-23 02:47:03.664109: Pseudo dice [0.8421] +2024-11-23 02:47:03.664186: Epoch time: 18.95 s +2024-11-23 02:47:04.639372: +2024-11-23 02:47:04.639580: Epoch 7341 +2024-11-23 02:47:04.639695: Current learning rate: 0.00106 +2024-11-23 02:47:23.186396: train_loss -0.8248 +2024-11-23 02:47:23.186616: val_loss -0.7601 +2024-11-23 02:47:23.186691: Pseudo dice [0.8291] +2024-11-23 02:47:23.186769: Epoch time: 18.55 s +2024-11-23 02:47:24.173739: +2024-11-23 02:47:24.174128: Epoch 7342 +2024-11-23 02:47:24.174244: Current learning rate: 0.00106 +2024-11-23 02:47:42.863524: train_loss -0.8322 +2024-11-23 02:47:42.863813: val_loss -0.7367 +2024-11-23 02:47:42.863901: Pseudo dice [0.815] +2024-11-23 02:47:42.863983: Epoch time: 18.69 s +2024-11-23 02:47:43.787234: +2024-11-23 02:47:43.787446: Epoch 7343 +2024-11-23 02:47:43.787557: Current learning rate: 0.00105 +2024-11-23 02:48:03.059768: train_loss -0.8298 +2024-11-23 02:48:03.060002: val_loss -0.7519 +2024-11-23 02:48:03.060079: Pseudo dice [0.8495] +2024-11-23 02:48:03.060154: Epoch time: 19.27 s +2024-11-23 02:48:03.989243: +2024-11-23 02:48:03.989562: Epoch 7344 +2024-11-23 02:48:03.989676: Current learning rate: 0.00105 +2024-11-23 02:48:23.491819: train_loss -0.8243 +2024-11-23 02:48:23.492046: val_loss -0.7716 +2024-11-23 02:48:23.492127: Pseudo dice [0.8573] +2024-11-23 02:48:23.492206: Epoch time: 19.5 s +2024-11-23 02:48:24.413451: +2024-11-23 02:48:24.413676: Epoch 7345 +2024-11-23 02:48:24.413788: Current learning rate: 0.00105 +2024-11-23 02:48:43.084448: train_loss -0.8289 +2024-11-23 02:48:43.084714: val_loss -0.7486 +2024-11-23 02:48:43.084790: Pseudo dice [0.8528] +2024-11-23 02:48:43.084873: Epoch time: 18.67 s +2024-11-23 02:48:44.059330: +2024-11-23 02:48:44.059566: Epoch 7346 +2024-11-23 02:48:44.059676: Current learning rate: 0.00105 +2024-11-23 02:49:02.274683: train_loss -0.8259 +2024-11-23 02:49:02.274905: val_loss -0.7553 +2024-11-23 02:49:02.274983: Pseudo dice [0.8446] +2024-11-23 02:49:02.275070: Epoch time: 18.22 s +2024-11-23 02:49:03.192659: +2024-11-23 02:49:03.193127: Epoch 7347 +2024-11-23 02:49:03.193264: Current learning rate: 0.00105 +2024-11-23 02:49:22.306688: train_loss -0.8276 +2024-11-23 02:49:22.306909: val_loss -0.7447 +2024-11-23 02:49:22.306983: Pseudo dice [0.8243] +2024-11-23 02:49:22.307067: Epoch time: 19.11 s +2024-11-23 02:49:23.634030: +2024-11-23 02:49:23.634450: Epoch 7348 +2024-11-23 02:49:23.634586: Current learning rate: 0.00105 +2024-11-23 02:49:41.859444: train_loss -0.8299 +2024-11-23 02:49:41.859700: val_loss -0.7515 +2024-11-23 02:49:41.859783: Pseudo dice [0.8569] +2024-11-23 02:49:41.860055: Epoch time: 18.23 s +2024-11-23 02:49:42.784090: +2024-11-23 02:49:42.784581: Epoch 7349 +2024-11-23 02:49:42.784717: Current learning rate: 0.00105 +2024-11-23 02:50:02.186594: train_loss -0.8329 +2024-11-23 02:50:02.186828: val_loss -0.7655 +2024-11-23 02:50:02.186904: Pseudo dice [0.8507] +2024-11-23 02:50:02.186980: Epoch time: 19.4 s +2024-11-23 02:50:03.472727: +2024-11-23 02:50:03.473181: Epoch 7350 +2024-11-23 02:50:03.473318: Current learning rate: 0.00104 +2024-11-23 02:50:21.500971: train_loss -0.8335 +2024-11-23 02:50:21.501189: val_loss -0.7472 +2024-11-23 02:50:21.501268: Pseudo dice [0.8333] +2024-11-23 02:50:21.501388: Epoch time: 18.03 s +2024-11-23 02:50:22.432519: +2024-11-23 02:50:22.432946: Epoch 7351 +2024-11-23 02:50:22.433085: Current learning rate: 0.00104 +2024-11-23 02:50:41.274272: train_loss -0.8289 +2024-11-23 02:50:41.274520: val_loss -0.7454 +2024-11-23 02:50:41.274595: Pseudo dice [0.8479] +2024-11-23 02:50:41.274673: Epoch time: 18.84 s +2024-11-23 02:50:42.200666: +2024-11-23 02:50:42.201105: Epoch 7352 +2024-11-23 02:50:42.201236: Current learning rate: 0.00104 +2024-11-23 02:51:01.595011: train_loss -0.8327 +2024-11-23 02:51:01.595266: val_loss -0.7239 +2024-11-23 02:51:01.595341: Pseudo dice [0.8508] +2024-11-23 02:51:01.597653: Epoch time: 19.4 s +2024-11-23 02:51:02.638074: +2024-11-23 02:51:02.638529: Epoch 7353 +2024-11-23 02:51:02.638669: Current learning rate: 0.00104 +2024-11-23 02:51:21.102862: train_loss -0.8227 +2024-11-23 02:51:21.108284: val_loss -0.7745 +2024-11-23 02:51:21.108369: Pseudo dice [0.8264] +2024-11-23 02:51:21.108460: Epoch time: 18.47 s +2024-11-23 02:51:22.057087: +2024-11-23 02:51:22.057617: Epoch 7354 +2024-11-23 02:51:22.057752: Current learning rate: 0.00104 +2024-11-23 02:51:39.872487: train_loss -0.8247 +2024-11-23 02:51:39.872771: val_loss -0.7956 +2024-11-23 02:51:39.872859: Pseudo dice [0.8627] +2024-11-23 02:51:39.872962: Epoch time: 17.82 s +2024-11-23 02:51:40.797684: +2024-11-23 02:51:40.798129: Epoch 7355 +2024-11-23 02:51:40.798265: Current learning rate: 0.00104 +2024-11-23 02:51:59.911243: train_loss -0.8323 +2024-11-23 02:51:59.911458: val_loss -0.7156 +2024-11-23 02:51:59.911578: Pseudo dice [0.8077] +2024-11-23 02:51:59.911659: Epoch time: 19.11 s +2024-11-23 02:52:00.838169: +2024-11-23 02:52:00.838600: Epoch 7356 +2024-11-23 02:52:00.838729: Current learning rate: 0.00104 +2024-11-23 02:52:19.613526: train_loss -0.8198 +2024-11-23 02:52:19.615979: val_loss -0.7722 +2024-11-23 02:52:19.616089: Pseudo dice [0.8538] +2024-11-23 02:52:19.616174: Epoch time: 18.78 s +2024-11-23 02:52:20.550457: +2024-11-23 02:52:20.551012: Epoch 7357 +2024-11-23 02:52:20.551144: Current learning rate: 0.00103 +2024-11-23 02:52:37.815465: train_loss -0.8325 +2024-11-23 02:52:37.815675: val_loss -0.7447 +2024-11-23 02:52:37.815746: Pseudo dice [0.861] +2024-11-23 02:52:37.815823: Epoch time: 17.27 s +2024-11-23 02:52:38.881050: +2024-11-23 02:52:38.881500: Epoch 7358 +2024-11-23 02:52:38.881638: Current learning rate: 0.00103 +2024-11-23 02:52:57.566381: train_loss -0.8223 +2024-11-23 02:52:57.566607: val_loss -0.7811 +2024-11-23 02:52:57.566762: Pseudo dice [0.8751] +2024-11-23 02:52:57.566846: Epoch time: 18.69 s +2024-11-23 02:52:58.919690: +2024-11-23 02:52:58.919916: Epoch 7359 +2024-11-23 02:52:58.920036: Current learning rate: 0.00103 +2024-11-23 02:53:17.957687: train_loss -0.8261 +2024-11-23 02:53:17.957952: val_loss -0.7535 +2024-11-23 02:53:17.958038: Pseudo dice [0.8323] +2024-11-23 02:53:17.958122: Epoch time: 19.04 s +2024-11-23 02:53:18.886377: +2024-11-23 02:53:18.886591: Epoch 7360 +2024-11-23 02:53:18.886712: Current learning rate: 0.00103 +2024-11-23 02:53:38.388649: train_loss -0.8315 +2024-11-23 02:53:38.388878: val_loss -0.7518 +2024-11-23 02:53:38.388951: Pseudo dice [0.8646] +2024-11-23 02:53:38.389030: Epoch time: 19.5 s +2024-11-23 02:53:39.314330: +2024-11-23 02:53:39.314546: Epoch 7361 +2024-11-23 02:53:39.314657: Current learning rate: 0.00103 +2024-11-23 02:53:57.729905: train_loss -0.8366 +2024-11-23 02:53:57.735302: val_loss -0.7477 +2024-11-23 02:53:57.735419: Pseudo dice [0.8695] +2024-11-23 02:53:57.735504: Epoch time: 18.42 s +2024-11-23 02:53:58.701383: +2024-11-23 02:53:58.701597: Epoch 7362 +2024-11-23 02:53:58.701714: Current learning rate: 0.00103 +2024-11-23 02:54:16.455078: train_loss -0.8368 +2024-11-23 02:54:16.455331: val_loss -0.743 +2024-11-23 02:54:16.455407: Pseudo dice [0.842] +2024-11-23 02:54:16.455493: Epoch time: 17.75 s +2024-11-23 02:54:17.379956: +2024-11-23 02:54:17.380169: Epoch 7363 +2024-11-23 02:54:17.380285: Current learning rate: 0.00103 +2024-11-23 02:54:36.646967: train_loss -0.8277 +2024-11-23 02:54:36.647196: val_loss -0.7513 +2024-11-23 02:54:36.647273: Pseudo dice [0.845] +2024-11-23 02:54:36.647350: Epoch time: 19.27 s +2024-11-23 02:54:37.567842: +2024-11-23 02:54:37.568073: Epoch 7364 +2024-11-23 02:54:37.568189: Current learning rate: 0.00102 +2024-11-23 02:54:57.847176: train_loss -0.8276 +2024-11-23 02:54:57.847403: val_loss -0.7365 +2024-11-23 02:54:57.847479: Pseudo dice [0.8394] +2024-11-23 02:54:57.847557: Epoch time: 20.28 s +2024-11-23 02:54:58.779362: +2024-11-23 02:54:58.779593: Epoch 7365 +2024-11-23 02:54:58.779719: Current learning rate: 0.00102 +2024-11-23 02:55:17.203070: train_loss -0.831 +2024-11-23 02:55:17.203308: val_loss -0.7525 +2024-11-23 02:55:17.205600: Pseudo dice [0.8377] +2024-11-23 02:55:17.205704: Epoch time: 18.42 s +2024-11-23 02:55:18.355812: +2024-11-23 02:55:18.356114: Epoch 7366 +2024-11-23 02:55:18.356231: Current learning rate: 0.00102 +2024-11-23 02:55:36.022686: train_loss -0.823 +2024-11-23 02:55:36.028134: val_loss -0.7521 +2024-11-23 02:55:36.028254: Pseudo dice [0.8623] +2024-11-23 02:55:36.028343: Epoch time: 17.67 s +2024-11-23 02:55:37.201328: +2024-11-23 02:55:37.201536: Epoch 7367 +2024-11-23 02:55:37.201648: Current learning rate: 0.00102 +2024-11-23 02:55:56.233420: train_loss -0.8251 +2024-11-23 02:55:56.233633: val_loss -0.7497 +2024-11-23 02:55:56.233710: Pseudo dice [0.8337] +2024-11-23 02:55:56.233787: Epoch time: 19.03 s +2024-11-23 02:55:57.161725: +2024-11-23 02:55:57.161919: Epoch 7368 +2024-11-23 02:55:57.162036: Current learning rate: 0.00102 +2024-11-23 02:56:15.990346: train_loss -0.8287 +2024-11-23 02:56:15.990566: val_loss -0.7382 +2024-11-23 02:56:15.990641: Pseudo dice [0.8334] +2024-11-23 02:56:15.990719: Epoch time: 18.83 s +2024-11-23 02:56:16.916727: +2024-11-23 02:56:16.916923: Epoch 7369 +2024-11-23 02:56:16.917036: Current learning rate: 0.00102 +2024-11-23 02:56:35.118867: train_loss -0.8293 +2024-11-23 02:56:35.119200: val_loss -0.747 +2024-11-23 02:56:35.119307: Pseudo dice [0.843] +2024-11-23 02:56:35.119392: Epoch time: 18.2 s +2024-11-23 02:56:36.515017: +2024-11-23 02:56:36.515239: Epoch 7370 +2024-11-23 02:56:36.515352: Current learning rate: 0.00102 +2024-11-23 02:56:55.092372: train_loss -0.8274 +2024-11-23 02:56:55.092627: val_loss -0.7387 +2024-11-23 02:56:55.092712: Pseudo dice [0.8448] +2024-11-23 02:56:55.092807: Epoch time: 18.58 s +2024-11-23 02:56:56.009049: +2024-11-23 02:56:56.009256: Epoch 7371 +2024-11-23 02:56:56.009365: Current learning rate: 0.00101 +2024-11-23 02:57:16.231122: train_loss -0.8214 +2024-11-23 02:57:16.231332: val_loss -0.7569 +2024-11-23 02:57:16.231403: Pseudo dice [0.8659] +2024-11-23 02:57:16.231481: Epoch time: 20.22 s +2024-11-23 02:57:17.195417: +2024-11-23 02:57:17.195638: Epoch 7372 +2024-11-23 02:57:17.195751: Current learning rate: 0.00101 +2024-11-23 02:57:34.983123: train_loss -0.8241 +2024-11-23 02:57:34.983452: val_loss -0.7574 +2024-11-23 02:57:34.983535: Pseudo dice [0.8417] +2024-11-23 02:57:34.983625: Epoch time: 17.79 s +2024-11-23 02:57:36.123138: +2024-11-23 02:57:36.123431: Epoch 7373 +2024-11-23 02:57:36.123543: Current learning rate: 0.00101 +2024-11-23 02:57:54.875304: train_loss -0.8302 +2024-11-23 02:57:54.875533: val_loss -0.7762 +2024-11-23 02:57:54.875612: Pseudo dice [0.8739] +2024-11-23 02:57:54.875689: Epoch time: 18.75 s +2024-11-23 02:57:55.947555: +2024-11-23 02:57:55.947773: Epoch 7374 +2024-11-23 02:57:55.947892: Current learning rate: 0.00101 +2024-11-23 02:58:14.886103: train_loss -0.833 +2024-11-23 02:58:14.886334: val_loss -0.7543 +2024-11-23 02:58:14.886575: Pseudo dice [0.852] +2024-11-23 02:58:14.886665: Epoch time: 18.94 s +2024-11-23 02:58:15.812614: +2024-11-23 02:58:15.812825: Epoch 7375 +2024-11-23 02:58:15.812934: Current learning rate: 0.00101 +2024-11-23 02:58:34.034772: train_loss -0.8341 +2024-11-23 02:58:34.035006: val_loss -0.7534 +2024-11-23 02:58:34.035084: Pseudo dice [0.831] +2024-11-23 02:58:34.035163: Epoch time: 18.22 s +2024-11-23 02:58:34.965925: +2024-11-23 02:58:34.966170: Epoch 7376 +2024-11-23 02:58:34.966284: Current learning rate: 0.00101 +2024-11-23 02:58:54.392475: train_loss -0.8235 +2024-11-23 02:58:54.392725: val_loss -0.7632 +2024-11-23 02:58:54.392803: Pseudo dice [0.8553] +2024-11-23 02:58:54.392888: Epoch time: 19.43 s +2024-11-23 02:58:55.316333: +2024-11-23 02:58:55.316583: Epoch 7377 +2024-11-23 02:58:55.316698: Current learning rate: 0.00101 +2024-11-23 02:59:13.628262: train_loss -0.8322 +2024-11-23 02:59:13.628489: val_loss -0.7243 +2024-11-23 02:59:13.628567: Pseudo dice [0.8342] +2024-11-23 02:59:13.637965: Epoch time: 18.31 s +2024-11-23 02:59:14.741295: +2024-11-23 02:59:14.741525: Epoch 7378 +2024-11-23 02:59:14.741640: Current learning rate: 0.001 +2024-11-23 02:59:34.038152: train_loss -0.8374 +2024-11-23 02:59:34.038381: val_loss -0.7511 +2024-11-23 02:59:34.038455: Pseudo dice [0.8291] +2024-11-23 02:59:34.038533: Epoch time: 19.3 s +2024-11-23 02:59:34.965608: +2024-11-23 02:59:34.965833: Epoch 7379 +2024-11-23 02:59:34.965944: Current learning rate: 0.001 +2024-11-23 02:59:53.572427: train_loss -0.8274 +2024-11-23 02:59:53.572743: val_loss -0.7411 +2024-11-23 02:59:53.572822: Pseudo dice [0.8446] +2024-11-23 02:59:53.572906: Epoch time: 18.61 s +2024-11-23 02:59:54.499443: +2024-11-23 02:59:54.499642: Epoch 7380 +2024-11-23 02:59:54.499759: Current learning rate: 0.001 +2024-11-23 03:00:13.061410: train_loss -0.8299 +2024-11-23 03:00:13.061654: val_loss -0.7309 +2024-11-23 03:00:13.061731: Pseudo dice [0.8491] +2024-11-23 03:00:13.061809: Epoch time: 18.56 s +2024-11-23 03:00:13.982507: +2024-11-23 03:00:13.982700: Epoch 7381 +2024-11-23 03:00:13.982813: Current learning rate: 0.001 +2024-11-23 03:00:32.364981: train_loss -0.8295 +2024-11-23 03:00:32.365205: val_loss -0.7752 +2024-11-23 03:00:32.365283: Pseudo dice [0.861] +2024-11-23 03:00:32.365361: Epoch time: 18.38 s +2024-11-23 03:00:33.654798: +2024-11-23 03:00:33.655075: Epoch 7382 +2024-11-23 03:00:33.655191: Current learning rate: 0.001 +2024-11-23 03:00:53.445013: train_loss -0.825 +2024-11-23 03:00:53.447448: val_loss -0.7616 +2024-11-23 03:00:53.447545: Pseudo dice [0.874] +2024-11-23 03:00:53.447622: Epoch time: 19.79 s +2024-11-23 03:00:54.390569: +2024-11-23 03:00:54.390776: Epoch 7383 +2024-11-23 03:00:54.390886: Current learning rate: 0.001 +2024-11-23 03:01:12.445084: train_loss -0.826 +2024-11-23 03:01:12.445343: val_loss -0.7743 +2024-11-23 03:01:12.445420: Pseudo dice [0.8647] +2024-11-23 03:01:12.445509: Epoch time: 18.06 s +2024-11-23 03:01:13.366320: +2024-11-23 03:01:13.366545: Epoch 7384 +2024-11-23 03:01:13.366655: Current learning rate: 0.001 +2024-11-23 03:01:31.822623: train_loss -0.8335 +2024-11-23 03:01:31.822846: val_loss -0.7738 +2024-11-23 03:01:31.822924: Pseudo dice [0.853] +2024-11-23 03:01:31.823008: Epoch time: 18.46 s +2024-11-23 03:01:32.813260: +2024-11-23 03:01:32.813517: Epoch 7385 +2024-11-23 03:01:32.813631: Current learning rate: 0.00099 +2024-11-23 03:01:52.083532: train_loss -0.8243 +2024-11-23 03:01:52.083750: val_loss -0.7765 +2024-11-23 03:01:52.083828: Pseudo dice [0.8633] +2024-11-23 03:01:52.083910: Epoch time: 19.27 s +2024-11-23 03:01:53.013074: +2024-11-23 03:01:53.013341: Epoch 7386 +2024-11-23 03:01:53.013459: Current learning rate: 0.00099 +2024-11-23 03:02:12.428328: train_loss -0.8319 +2024-11-23 03:02:12.428547: val_loss -0.7418 +2024-11-23 03:02:12.428622: Pseudo dice [0.8439] +2024-11-23 03:02:12.428698: Epoch time: 19.42 s +2024-11-23 03:02:13.351405: +2024-11-23 03:02:13.351607: Epoch 7387 +2024-11-23 03:02:13.351719: Current learning rate: 0.00099 +2024-11-23 03:02:32.266537: train_loss -0.831 +2024-11-23 03:02:32.266787: val_loss -0.7386 +2024-11-23 03:02:32.266862: Pseudo dice [0.8588] +2024-11-23 03:02:32.267138: Epoch time: 18.92 s +2024-11-23 03:02:33.218605: +2024-11-23 03:02:33.218845: Epoch 7388 +2024-11-23 03:02:33.218967: Current learning rate: 0.00099 +2024-11-23 03:02:52.475507: train_loss -0.8298 +2024-11-23 03:02:52.475733: val_loss -0.7721 +2024-11-23 03:02:52.475809: Pseudo dice [0.8702] +2024-11-23 03:02:52.475884: Epoch time: 19.26 s +2024-11-23 03:02:53.401078: +2024-11-23 03:02:53.401293: Epoch 7389 +2024-11-23 03:02:53.401404: Current learning rate: 0.00099 +2024-11-23 03:03:10.861486: train_loss -0.8273 +2024-11-23 03:03:10.861709: val_loss -0.753 +2024-11-23 03:03:10.861784: Pseudo dice [0.859] +2024-11-23 03:03:10.861859: Epoch time: 17.46 s +2024-11-23 03:03:11.802890: +2024-11-23 03:03:11.803088: Epoch 7390 +2024-11-23 03:03:11.803198: Current learning rate: 0.00099 +2024-11-23 03:03:30.964884: train_loss -0.8336 +2024-11-23 03:03:30.965111: val_loss -0.7606 +2024-11-23 03:03:30.965184: Pseudo dice [0.8478] +2024-11-23 03:03:30.965322: Epoch time: 19.16 s +2024-11-23 03:03:31.887384: +2024-11-23 03:03:31.887634: Epoch 7391 +2024-11-23 03:03:31.887743: Current learning rate: 0.00098 +2024-11-23 03:03:51.475582: train_loss -0.8247 +2024-11-23 03:03:51.475843: val_loss -0.7635 +2024-11-23 03:03:51.475919: Pseudo dice [0.8702] +2024-11-23 03:03:51.476008: Epoch time: 19.59 s +2024-11-23 03:03:52.403674: +2024-11-23 03:03:52.403896: Epoch 7392 +2024-11-23 03:03:52.404019: Current learning rate: 0.00098 +2024-11-23 03:04:11.716903: train_loss -0.8291 +2024-11-23 03:04:11.718623: val_loss -0.7817 +2024-11-23 03:04:11.718740: Pseudo dice [0.8597] +2024-11-23 03:04:11.718819: Epoch time: 19.31 s +2024-11-23 03:04:13.129590: +2024-11-23 03:04:13.129843: Epoch 7393 +2024-11-23 03:04:13.129959: Current learning rate: 0.00098 +2024-11-23 03:04:30.522087: train_loss -0.8279 +2024-11-23 03:04:30.522396: val_loss -0.7584 +2024-11-23 03:04:30.522476: Pseudo dice [0.8615] +2024-11-23 03:04:30.522559: Epoch time: 17.39 s +2024-11-23 03:04:31.611426: +2024-11-23 03:04:31.611716: Epoch 7394 +2024-11-23 03:04:31.611830: Current learning rate: 0.00098 +2024-11-23 03:04:50.661403: train_loss -0.8298 +2024-11-23 03:04:50.661666: val_loss -0.7523 +2024-11-23 03:04:50.661762: Pseudo dice [0.8402] +2024-11-23 03:04:50.661846: Epoch time: 19.05 s +2024-11-23 03:04:51.594043: +2024-11-23 03:04:51.594285: Epoch 7395 +2024-11-23 03:04:51.594396: Current learning rate: 0.00098 +2024-11-23 03:05:09.787395: train_loss -0.8327 +2024-11-23 03:05:09.787621: val_loss -0.7694 +2024-11-23 03:05:09.787693: Pseudo dice [0.8494] +2024-11-23 03:05:09.787770: Epoch time: 18.19 s +2024-11-23 03:05:10.718786: +2024-11-23 03:05:10.719008: Epoch 7396 +2024-11-23 03:05:10.719122: Current learning rate: 0.00098 +2024-11-23 03:05:29.037571: train_loss -0.8232 +2024-11-23 03:05:29.037871: val_loss -0.7595 +2024-11-23 03:05:29.037950: Pseudo dice [0.8645] +2024-11-23 03:05:29.038032: Epoch time: 18.32 s +2024-11-23 03:05:29.962332: +2024-11-23 03:05:29.962546: Epoch 7397 +2024-11-23 03:05:29.962658: Current learning rate: 0.00098 +2024-11-23 03:05:49.668665: train_loss -0.828 +2024-11-23 03:05:49.668879: val_loss -0.7597 +2024-11-23 03:05:49.669034: Pseudo dice [0.8614] +2024-11-23 03:05:49.669117: Epoch time: 19.71 s +2024-11-23 03:05:50.625247: +2024-11-23 03:05:50.625485: Epoch 7398 +2024-11-23 03:05:50.625597: Current learning rate: 0.00097 +2024-11-23 03:06:09.197066: train_loss -0.8302 +2024-11-23 03:06:09.197330: val_loss -0.7686 +2024-11-23 03:06:09.197408: Pseudo dice [0.8538] +2024-11-23 03:06:09.197494: Epoch time: 18.57 s +2024-11-23 03:06:10.126567: +2024-11-23 03:06:10.126781: Epoch 7399 +2024-11-23 03:06:10.126893: Current learning rate: 0.00097 +2024-11-23 03:06:27.792592: train_loss -0.8293 +2024-11-23 03:06:27.792809: val_loss -0.7635 +2024-11-23 03:06:27.792885: Pseudo dice [0.8439] +2024-11-23 03:06:27.792964: Epoch time: 17.67 s +2024-11-23 03:06:29.121348: +2024-11-23 03:06:29.121562: Epoch 7400 +2024-11-23 03:06:29.121677: Current learning rate: 0.00097 +2024-11-23 03:06:47.807269: train_loss -0.8298 +2024-11-23 03:06:47.807484: val_loss -0.7496 +2024-11-23 03:06:47.807642: Pseudo dice [0.8424] +2024-11-23 03:06:47.807722: Epoch time: 18.69 s +2024-11-23 03:06:48.735969: +2024-11-23 03:06:48.736200: Epoch 7401 +2024-11-23 03:06:48.736315: Current learning rate: 0.00097 +2024-11-23 03:07:06.699021: train_loss -0.8287 +2024-11-23 03:07:06.699248: val_loss -0.7676 +2024-11-23 03:07:06.699324: Pseudo dice [0.8717] +2024-11-23 03:07:06.699403: Epoch time: 17.96 s +2024-11-23 03:07:07.625917: +2024-11-23 03:07:07.626153: Epoch 7402 +2024-11-23 03:07:07.626281: Current learning rate: 0.00097 +2024-11-23 03:07:26.564121: train_loss -0.8397 +2024-11-23 03:07:26.564379: val_loss -0.7767 +2024-11-23 03:07:26.569681: Pseudo dice [0.8537] +2024-11-23 03:07:26.569828: Epoch time: 18.94 s +2024-11-23 03:07:27.518771: +2024-11-23 03:07:27.518990: Epoch 7403 +2024-11-23 03:07:27.519105: Current learning rate: 0.00097 +2024-11-23 03:07:46.566745: train_loss -0.8301 +2024-11-23 03:07:46.566962: val_loss -0.7522 +2024-11-23 03:07:46.567046: Pseudo dice [0.8593] +2024-11-23 03:07:46.567123: Epoch time: 19.05 s +2024-11-23 03:07:47.651776: +2024-11-23 03:07:47.651976: Epoch 7404 +2024-11-23 03:07:47.652093: Current learning rate: 0.00097 +2024-11-23 03:08:07.320072: train_loss -0.8271 +2024-11-23 03:08:07.323096: val_loss -0.7646 +2024-11-23 03:08:07.323187: Pseudo dice [0.859] +2024-11-23 03:08:07.323267: Epoch time: 19.67 s +2024-11-23 03:08:08.744041: +2024-11-23 03:08:08.744274: Epoch 7405 +2024-11-23 03:08:08.744389: Current learning rate: 0.00096 +2024-11-23 03:08:27.228223: train_loss -0.8288 +2024-11-23 03:08:27.228492: val_loss -0.7713 +2024-11-23 03:08:27.228571: Pseudo dice [0.849] +2024-11-23 03:08:27.228659: Epoch time: 18.48 s +2024-11-23 03:08:28.159218: +2024-11-23 03:08:28.159442: Epoch 7406 +2024-11-23 03:08:28.159554: Current learning rate: 0.00096 +2024-11-23 03:08:46.875302: train_loss -0.8319 +2024-11-23 03:08:46.875533: val_loss -0.751 +2024-11-23 03:08:46.875618: Pseudo dice [0.8468] +2024-11-23 03:08:46.875694: Epoch time: 18.72 s +2024-11-23 03:08:47.797849: +2024-11-23 03:08:47.798094: Epoch 7407 +2024-11-23 03:08:47.798212: Current learning rate: 0.00096 +2024-11-23 03:09:05.728846: train_loss -0.8316 +2024-11-23 03:09:05.729085: val_loss -0.7785 +2024-11-23 03:09:05.729162: Pseudo dice [0.8445] +2024-11-23 03:09:05.734460: Epoch time: 17.93 s +2024-11-23 03:09:06.689659: +2024-11-23 03:09:06.689923: Epoch 7408 +2024-11-23 03:09:06.690043: Current learning rate: 0.00096 +2024-11-23 03:09:25.613080: train_loss -0.8313 +2024-11-23 03:09:25.613337: val_loss -0.7387 +2024-11-23 03:09:25.613412: Pseudo dice [0.8628] +2024-11-23 03:09:25.613495: Epoch time: 18.92 s +2024-11-23 03:09:26.605777: +2024-11-23 03:09:26.605985: Epoch 7409 +2024-11-23 03:09:26.606099: Current learning rate: 0.00096 +2024-11-23 03:09:45.090597: train_loss -0.8195 +2024-11-23 03:09:45.096024: val_loss -0.7543 +2024-11-23 03:09:45.096151: Pseudo dice [0.8749] +2024-11-23 03:09:45.096252: Epoch time: 18.49 s +2024-11-23 03:09:46.027799: +2024-11-23 03:09:46.028021: Epoch 7410 +2024-11-23 03:09:46.028133: Current learning rate: 0.00096 +2024-11-23 03:10:04.147401: train_loss -0.8326 +2024-11-23 03:10:04.147622: val_loss -0.7803 +2024-11-23 03:10:04.147720: Pseudo dice [0.8679] +2024-11-23 03:10:04.147797: Epoch time: 18.12 s +2024-11-23 03:10:05.067572: +2024-11-23 03:10:05.067780: Epoch 7411 +2024-11-23 03:10:05.067896: Current learning rate: 0.00096 +2024-11-23 03:10:23.572738: train_loss -0.8319 +2024-11-23 03:10:23.572965: val_loss -0.7634 +2024-11-23 03:10:23.573107: Pseudo dice [0.8602] +2024-11-23 03:10:23.573185: Epoch time: 18.51 s +2024-11-23 03:10:24.497735: +2024-11-23 03:10:24.497998: Epoch 7412 +2024-11-23 03:10:24.498116: Current learning rate: 0.00095 +2024-11-23 03:10:44.490065: train_loss -0.824 +2024-11-23 03:10:44.490313: val_loss -0.764 +2024-11-23 03:10:44.490388: Pseudo dice [0.8419] +2024-11-23 03:10:44.490467: Epoch time: 19.99 s +2024-11-23 03:10:45.418631: +2024-11-23 03:10:45.418847: Epoch 7413 +2024-11-23 03:10:45.418973: Current learning rate: 0.00095 +2024-11-23 03:11:04.219946: train_loss -0.8267 +2024-11-23 03:11:04.220169: val_loss -0.7628 +2024-11-23 03:11:04.220251: Pseudo dice [0.8571] +2024-11-23 03:11:04.220327: Epoch time: 18.8 s +2024-11-23 03:11:05.139908: +2024-11-23 03:11:05.140211: Epoch 7414 +2024-11-23 03:11:05.140322: Current learning rate: 0.00095 +2024-11-23 03:11:24.959955: train_loss -0.8301 +2024-11-23 03:11:24.960182: val_loss -0.7763 +2024-11-23 03:11:24.960261: Pseudo dice [0.8731] +2024-11-23 03:11:24.960338: Epoch time: 19.82 s +2024-11-23 03:11:25.875737: +2024-11-23 03:11:25.876003: Epoch 7415 +2024-11-23 03:11:25.876112: Current learning rate: 0.00095 +2024-11-23 03:11:45.935551: train_loss -0.824 +2024-11-23 03:11:45.935781: val_loss -0.7467 +2024-11-23 03:11:45.935859: Pseudo dice [0.8647] +2024-11-23 03:11:45.935940: Epoch time: 20.06 s +2024-11-23 03:11:47.266549: +2024-11-23 03:11:47.266752: Epoch 7416 +2024-11-23 03:11:47.266867: Current learning rate: 0.00095 +2024-11-23 03:12:06.120331: train_loss -0.8254 +2024-11-23 03:12:06.120600: val_loss -0.734 +2024-11-23 03:12:06.120681: Pseudo dice [0.8413] +2024-11-23 03:12:06.120765: Epoch time: 18.85 s +2024-11-23 03:12:07.043153: +2024-11-23 03:12:07.043381: Epoch 7417 +2024-11-23 03:12:07.043497: Current learning rate: 0.00095 +2024-11-23 03:12:25.595338: train_loss -0.8312 +2024-11-23 03:12:25.595579: val_loss -0.7492 +2024-11-23 03:12:25.595655: Pseudo dice [0.8399] +2024-11-23 03:12:25.595736: Epoch time: 18.55 s +2024-11-23 03:12:26.520935: +2024-11-23 03:12:26.521171: Epoch 7418 +2024-11-23 03:12:26.521287: Current learning rate: 0.00095 +2024-11-23 03:12:44.608064: train_loss -0.8317 +2024-11-23 03:12:44.608307: val_loss -0.7418 +2024-11-23 03:12:44.608383: Pseudo dice [0.8476] +2024-11-23 03:12:44.608458: Epoch time: 18.09 s +2024-11-23 03:12:45.533697: +2024-11-23 03:12:45.533915: Epoch 7419 +2024-11-23 03:12:45.534030: Current learning rate: 0.00094 +2024-11-23 03:13:04.646658: train_loss -0.8243 +2024-11-23 03:13:04.646881: val_loss -0.7708 +2024-11-23 03:13:04.646997: Pseudo dice [0.8715] +2024-11-23 03:13:04.647083: Epoch time: 19.11 s +2024-11-23 03:13:05.574875: +2024-11-23 03:13:05.575162: Epoch 7420 +2024-11-23 03:13:05.575298: Current learning rate: 0.00094 +2024-11-23 03:13:25.454013: train_loss -0.8327 +2024-11-23 03:13:25.454226: val_loss -0.7706 +2024-11-23 03:13:25.454299: Pseudo dice [0.8243] +2024-11-23 03:13:25.454373: Epoch time: 19.88 s +2024-11-23 03:13:26.412322: +2024-11-23 03:13:26.412544: Epoch 7421 +2024-11-23 03:13:26.412660: Current learning rate: 0.00094 +2024-11-23 03:13:45.834544: train_loss -0.8277 +2024-11-23 03:13:45.834758: val_loss -0.7714 +2024-11-23 03:13:45.834834: Pseudo dice [0.8454] +2024-11-23 03:13:45.834914: Epoch time: 19.42 s +2024-11-23 03:13:46.777680: +2024-11-23 03:13:46.777920: Epoch 7422 +2024-11-23 03:13:46.778046: Current learning rate: 0.00094 +2024-11-23 03:14:05.046004: train_loss -0.8328 +2024-11-23 03:14:05.046227: val_loss -0.7626 +2024-11-23 03:14:05.046301: Pseudo dice [0.8618] +2024-11-23 03:14:05.046391: Epoch time: 18.27 s +2024-11-23 03:14:06.105106: +2024-11-23 03:14:06.105336: Epoch 7423 +2024-11-23 03:14:06.105456: Current learning rate: 0.00094 +2024-11-23 03:14:25.603188: train_loss -0.8274 +2024-11-23 03:14:25.603436: val_loss -0.7534 +2024-11-23 03:14:25.603530: Pseudo dice [0.8337] +2024-11-23 03:14:25.603618: Epoch time: 19.5 s +2024-11-23 03:14:26.524313: +2024-11-23 03:14:26.524647: Epoch 7424 +2024-11-23 03:14:26.524760: Current learning rate: 0.00094 +2024-11-23 03:14:45.062544: train_loss -0.8329 +2024-11-23 03:14:45.062752: val_loss -0.759 +2024-11-23 03:14:45.062824: Pseudo dice [0.8742] +2024-11-23 03:14:45.062898: Epoch time: 18.54 s +2024-11-23 03:14:45.987024: +2024-11-23 03:14:45.987236: Epoch 7425 +2024-11-23 03:14:45.987346: Current learning rate: 0.00094 +2024-11-23 03:15:04.061821: train_loss -0.8293 +2024-11-23 03:15:04.062057: val_loss -0.7352 +2024-11-23 03:15:04.062135: Pseudo dice [0.8496] +2024-11-23 03:15:04.062212: Epoch time: 18.08 s +2024-11-23 03:15:04.995924: +2024-11-23 03:15:04.996132: Epoch 7426 +2024-11-23 03:15:04.996249: Current learning rate: 0.00093 +2024-11-23 03:15:25.234304: train_loss -0.8322 +2024-11-23 03:15:25.234506: val_loss -0.7491 +2024-11-23 03:15:25.234715: Pseudo dice [0.8496] +2024-11-23 03:15:25.234833: Epoch time: 20.24 s +2024-11-23 03:15:26.139715: +2024-11-23 03:15:26.139935: Epoch 7427 +2024-11-23 03:15:26.140053: Current learning rate: 0.00093 +2024-11-23 03:15:45.245896: train_loss -0.837 +2024-11-23 03:15:45.246174: val_loss -0.7743 +2024-11-23 03:15:45.246252: Pseudo dice [0.8698] +2024-11-23 03:15:45.246335: Epoch time: 19.11 s +2024-11-23 03:15:46.767263: +2024-11-23 03:15:46.767492: Epoch 7428 +2024-11-23 03:15:46.767607: Current learning rate: 0.00093 +2024-11-23 03:16:06.730722: train_loss -0.8282 +2024-11-23 03:16:06.730971: val_loss -0.7527 +2024-11-23 03:16:06.731057: Pseudo dice [0.8398] +2024-11-23 03:16:06.731138: Epoch time: 19.96 s +2024-11-23 03:16:07.655234: +2024-11-23 03:16:07.655463: Epoch 7429 +2024-11-23 03:16:07.655577: Current learning rate: 0.00093 +2024-11-23 03:16:26.659949: train_loss -0.8306 +2024-11-23 03:16:26.660192: val_loss -0.7517 +2024-11-23 03:16:26.660266: Pseudo dice [0.859] +2024-11-23 03:16:26.660346: Epoch time: 19.01 s +2024-11-23 03:16:27.582525: +2024-11-23 03:16:27.582728: Epoch 7430 +2024-11-23 03:16:27.582838: Current learning rate: 0.00093 +2024-11-23 03:16:45.218337: train_loss -0.8302 +2024-11-23 03:16:45.223771: val_loss -0.7906 +2024-11-23 03:16:45.223936: Pseudo dice [0.845] +2024-11-23 03:16:45.224032: Epoch time: 17.64 s +2024-11-23 03:16:46.244038: +2024-11-23 03:16:46.244259: Epoch 7431 +2024-11-23 03:16:46.244370: Current learning rate: 0.00093 +2024-11-23 03:17:05.158245: train_loss -0.8352 +2024-11-23 03:17:05.158480: val_loss -0.7804 +2024-11-23 03:17:05.158560: Pseudo dice [0.867] +2024-11-23 03:17:05.158637: Epoch time: 18.92 s +2024-11-23 03:17:06.080866: +2024-11-23 03:17:06.081093: Epoch 7432 +2024-11-23 03:17:06.081209: Current learning rate: 0.00092 +2024-11-23 03:17:24.409012: train_loss -0.8331 +2024-11-23 03:17:24.409236: val_loss -0.7639 +2024-11-23 03:17:24.409333: Pseudo dice [0.8594] +2024-11-23 03:17:24.409410: Epoch time: 18.33 s +2024-11-23 03:17:25.329664: +2024-11-23 03:17:25.329874: Epoch 7433 +2024-11-23 03:17:25.329987: Current learning rate: 0.00092 +2024-11-23 03:17:43.941836: train_loss -0.8357 +2024-11-23 03:17:43.942126: val_loss -0.7376 +2024-11-23 03:17:43.942212: Pseudo dice [0.8669] +2024-11-23 03:17:43.942291: Epoch time: 18.61 s +2024-11-23 03:17:44.856071: +2024-11-23 03:17:44.856310: Epoch 7434 +2024-11-23 03:17:44.856421: Current learning rate: 0.00092 +2024-11-23 03:18:02.660163: train_loss -0.8331 +2024-11-23 03:18:02.660421: val_loss -0.7688 +2024-11-23 03:18:02.660497: Pseudo dice [0.85] +2024-11-23 03:18:02.660578: Epoch time: 17.8 s +2024-11-23 03:18:03.592731: +2024-11-23 03:18:03.592975: Epoch 7435 +2024-11-23 03:18:03.593094: Current learning rate: 0.00092 +2024-11-23 03:18:22.428102: train_loss -0.833 +2024-11-23 03:18:22.428329: val_loss -0.7277 +2024-11-23 03:18:22.428405: Pseudo dice [0.8536] +2024-11-23 03:18:22.428481: Epoch time: 18.84 s +2024-11-23 03:18:23.433528: +2024-11-23 03:18:23.433718: Epoch 7436 +2024-11-23 03:18:23.433847: Current learning rate: 0.00092 +2024-11-23 03:18:41.635824: train_loss -0.8309 +2024-11-23 03:18:41.636057: val_loss -0.727 +2024-11-23 03:18:41.636138: Pseudo dice [0.8479] +2024-11-23 03:18:41.636220: Epoch time: 18.2 s +2024-11-23 03:18:42.561041: +2024-11-23 03:18:42.561247: Epoch 7437 +2024-11-23 03:18:42.561360: Current learning rate: 0.00092 +2024-11-23 03:19:01.852556: train_loss -0.8309 +2024-11-23 03:19:01.852776: val_loss -0.7479 +2024-11-23 03:19:01.852850: Pseudo dice [0.8278] +2024-11-23 03:19:01.852931: Epoch time: 19.29 s +2024-11-23 03:19:02.784209: +2024-11-23 03:19:02.784422: Epoch 7438 +2024-11-23 03:19:02.784530: Current learning rate: 0.00092 +2024-11-23 03:19:21.491625: train_loss -0.8358 +2024-11-23 03:19:21.491919: val_loss -0.7398 +2024-11-23 03:19:21.492002: Pseudo dice [0.8709] +2024-11-23 03:19:21.492082: Epoch time: 18.71 s +2024-11-23 03:19:22.826648: +2024-11-23 03:19:22.826858: Epoch 7439 +2024-11-23 03:19:22.826970: Current learning rate: 0.00091 +2024-11-23 03:19:41.212789: train_loss -0.8297 +2024-11-23 03:19:41.213042: val_loss -0.7544 +2024-11-23 03:19:41.213181: Pseudo dice [0.8472] +2024-11-23 03:19:41.213263: Epoch time: 18.39 s +2024-11-23 03:19:42.143852: +2024-11-23 03:19:42.144194: Epoch 7440 +2024-11-23 03:19:42.144306: Current learning rate: 0.00091 +2024-11-23 03:20:00.784742: train_loss -0.8384 +2024-11-23 03:20:00.784969: val_loss -0.7508 +2024-11-23 03:20:00.785052: Pseudo dice [0.8586] +2024-11-23 03:20:00.785133: Epoch time: 18.64 s +2024-11-23 03:20:01.713633: +2024-11-23 03:20:01.713848: Epoch 7441 +2024-11-23 03:20:01.713957: Current learning rate: 0.00091 +2024-11-23 03:20:20.262301: train_loss -0.8327 +2024-11-23 03:20:20.262562: val_loss -0.7633 +2024-11-23 03:20:20.262637: Pseudo dice [0.8735] +2024-11-23 03:20:20.262724: Epoch time: 18.55 s +2024-11-23 03:20:21.190469: +2024-11-23 03:20:21.190686: Epoch 7442 +2024-11-23 03:20:21.190802: Current learning rate: 0.00091 +2024-11-23 03:20:40.928308: train_loss -0.8323 +2024-11-23 03:20:40.928533: val_loss -0.7326 +2024-11-23 03:20:40.928608: Pseudo dice [0.8611] +2024-11-23 03:20:40.928687: Epoch time: 19.74 s +2024-11-23 03:20:41.857223: +2024-11-23 03:20:41.857445: Epoch 7443 +2024-11-23 03:20:41.857558: Current learning rate: 0.00091 +2024-11-23 03:20:59.921000: train_loss -0.8294 +2024-11-23 03:20:59.921281: val_loss -0.7654 +2024-11-23 03:20:59.921355: Pseudo dice [0.8536] +2024-11-23 03:20:59.921432: Epoch time: 18.06 s +2024-11-23 03:21:00.879756: +2024-11-23 03:21:00.879975: Epoch 7444 +2024-11-23 03:21:00.880089: Current learning rate: 0.00091 +2024-11-23 03:21:18.736694: train_loss -0.8316 +2024-11-23 03:21:18.736981: val_loss -0.7759 +2024-11-23 03:21:18.737064: Pseudo dice [0.8403] +2024-11-23 03:21:18.737141: Epoch time: 17.86 s +2024-11-23 03:21:19.772438: +2024-11-23 03:21:19.772676: Epoch 7445 +2024-11-23 03:21:19.772791: Current learning rate: 0.00091 +2024-11-23 03:21:39.040305: train_loss -0.8285 +2024-11-23 03:21:39.040551: val_loss -0.7824 +2024-11-23 03:21:39.040627: Pseudo dice [0.8627] +2024-11-23 03:21:39.040709: Epoch time: 19.27 s +2024-11-23 03:21:39.967319: +2024-11-23 03:21:39.967528: Epoch 7446 +2024-11-23 03:21:39.967642: Current learning rate: 0.0009 +2024-11-23 03:21:59.338069: train_loss -0.8361 +2024-11-23 03:21:59.338305: val_loss -0.7751 +2024-11-23 03:21:59.338382: Pseudo dice [0.8664] +2024-11-23 03:21:59.338459: Epoch time: 19.37 s +2024-11-23 03:22:00.317372: +2024-11-23 03:22:00.317609: Epoch 7447 +2024-11-23 03:22:00.317726: Current learning rate: 0.0009 +2024-11-23 03:22:19.862546: train_loss -0.8321 +2024-11-23 03:22:19.862772: val_loss -0.7614 +2024-11-23 03:22:19.862846: Pseudo dice [0.8704] +2024-11-23 03:22:19.862922: Epoch time: 19.55 s +2024-11-23 03:22:20.815277: +2024-11-23 03:22:20.815501: Epoch 7448 +2024-11-23 03:22:20.815618: Current learning rate: 0.0009 +2024-11-23 03:22:39.822191: train_loss -0.8271 +2024-11-23 03:22:39.824641: val_loss -0.758 +2024-11-23 03:22:39.824777: Pseudo dice [0.8496] +2024-11-23 03:22:39.824865: Epoch time: 19.01 s +2024-11-23 03:22:40.775698: +2024-11-23 03:22:40.775926: Epoch 7449 +2024-11-23 03:22:40.776045: Current learning rate: 0.0009 +2024-11-23 03:23:00.477715: train_loss -0.8186 +2024-11-23 03:23:00.477933: val_loss -0.7517 +2024-11-23 03:23:00.478016: Pseudo dice [0.84] +2024-11-23 03:23:00.478093: Epoch time: 19.7 s +2024-11-23 03:23:01.740363: +2024-11-23 03:23:01.740560: Epoch 7450 +2024-11-23 03:23:01.740675: Current learning rate: 0.0009 +2024-11-23 03:23:20.246985: train_loss -0.8361 +2024-11-23 03:23:20.247238: val_loss -0.7653 +2024-11-23 03:23:20.247317: Pseudo dice [0.8549] +2024-11-23 03:23:20.247396: Epoch time: 18.51 s +2024-11-23 03:23:21.525838: +2024-11-23 03:23:21.526096: Epoch 7451 +2024-11-23 03:23:21.526208: Current learning rate: 0.0009 +2024-11-23 03:23:40.946398: train_loss -0.8327 +2024-11-23 03:23:40.946657: val_loss -0.755 +2024-11-23 03:23:40.946733: Pseudo dice [0.8535] +2024-11-23 03:23:40.946815: Epoch time: 19.42 s +2024-11-23 03:23:42.012912: +2024-11-23 03:23:42.013120: Epoch 7452 +2024-11-23 03:23:42.013229: Current learning rate: 0.0009 +2024-11-23 03:24:00.628160: train_loss -0.8337 +2024-11-23 03:24:00.628537: val_loss -0.7616 +2024-11-23 03:24:00.628623: Pseudo dice [0.8549] +2024-11-23 03:24:00.628698: Epoch time: 18.62 s +2024-11-23 03:24:01.558249: +2024-11-23 03:24:01.558465: Epoch 7453 +2024-11-23 03:24:01.558578: Current learning rate: 0.00089 +2024-11-23 03:24:19.975235: train_loss -0.8363 +2024-11-23 03:24:19.975464: val_loss -0.7763 +2024-11-23 03:24:19.975537: Pseudo dice [0.8439] +2024-11-23 03:24:19.975617: Epoch time: 18.42 s +2024-11-23 03:24:20.908904: +2024-11-23 03:24:20.909157: Epoch 7454 +2024-11-23 03:24:20.909273: Current learning rate: 0.00089 +2024-11-23 03:24:40.233634: train_loss -0.8239 +2024-11-23 03:24:40.233849: val_loss -0.7601 +2024-11-23 03:24:40.233929: Pseudo dice [0.8636] +2024-11-23 03:24:40.234027: Epoch time: 19.33 s +2024-11-23 03:24:41.345858: +2024-11-23 03:24:41.346135: Epoch 7455 +2024-11-23 03:24:41.346250: Current learning rate: 0.00089 +2024-11-23 03:24:59.419668: train_loss -0.8315 +2024-11-23 03:24:59.419971: val_loss -0.7589 +2024-11-23 03:24:59.420058: Pseudo dice [0.8311] +2024-11-23 03:24:59.420137: Epoch time: 18.07 s +2024-11-23 03:25:00.413493: +2024-11-23 03:25:00.413772: Epoch 7456 +2024-11-23 03:25:00.413884: Current learning rate: 0.00089 +2024-11-23 03:25:19.923902: train_loss -0.8299 +2024-11-23 03:25:19.924125: val_loss -0.7488 +2024-11-23 03:25:19.924200: Pseudo dice [0.844] +2024-11-23 03:25:19.924278: Epoch time: 19.51 s +2024-11-23 03:25:20.974002: +2024-11-23 03:25:20.974236: Epoch 7457 +2024-11-23 03:25:20.974356: Current learning rate: 0.00089 +2024-11-23 03:25:39.282708: train_loss -0.8333 +2024-11-23 03:25:39.282933: val_loss -0.7716 +2024-11-23 03:25:39.283014: Pseudo dice [0.8315] +2024-11-23 03:25:39.283092: Epoch time: 18.31 s +2024-11-23 03:25:40.217793: +2024-11-23 03:25:40.218056: Epoch 7458 +2024-11-23 03:25:40.218169: Current learning rate: 0.00089 +2024-11-23 03:25:58.663277: train_loss -0.8346 +2024-11-23 03:25:58.663508: val_loss -0.7716 +2024-11-23 03:25:58.663587: Pseudo dice [0.8566] +2024-11-23 03:25:58.663671: Epoch time: 18.45 s +2024-11-23 03:25:59.596858: +2024-11-23 03:25:59.597097: Epoch 7459 +2024-11-23 03:25:59.597215: Current learning rate: 0.00089 +2024-11-23 03:26:19.424566: train_loss -0.8335 +2024-11-23 03:26:19.424813: val_loss -0.7661 +2024-11-23 03:26:19.424890: Pseudo dice [0.84] +2024-11-23 03:26:19.424970: Epoch time: 19.83 s +2024-11-23 03:26:20.351501: +2024-11-23 03:26:20.351715: Epoch 7460 +2024-11-23 03:26:20.351826: Current learning rate: 0.00088 +2024-11-23 03:26:38.783333: train_loss -0.8312 +2024-11-23 03:26:38.783577: val_loss -0.7819 +2024-11-23 03:26:38.783659: Pseudo dice [0.852] +2024-11-23 03:26:38.783739: Epoch time: 18.43 s +2024-11-23 03:26:39.712051: +2024-11-23 03:26:39.712280: Epoch 7461 +2024-11-23 03:26:39.712394: Current learning rate: 0.00088 +2024-11-23 03:26:58.819936: train_loss -0.8391 +2024-11-23 03:26:58.820180: val_loss -0.7593 +2024-11-23 03:26:58.820264: Pseudo dice [0.8614] +2024-11-23 03:26:58.820343: Epoch time: 19.11 s +2024-11-23 03:27:00.172786: +2024-11-23 03:27:00.173005: Epoch 7462 +2024-11-23 03:27:00.173117: Current learning rate: 0.00088 +2024-11-23 03:27:18.717314: train_loss -0.8279 +2024-11-23 03:27:18.719824: val_loss -0.7635 +2024-11-23 03:27:18.719931: Pseudo dice [0.8565] +2024-11-23 03:27:18.720024: Epoch time: 18.55 s +2024-11-23 03:27:19.674665: +2024-11-23 03:27:19.674931: Epoch 7463 +2024-11-23 03:27:19.675054: Current learning rate: 0.00088 +2024-11-23 03:27:38.889915: train_loss -0.8288 +2024-11-23 03:27:38.890161: val_loss -0.7585 +2024-11-23 03:27:38.890240: Pseudo dice [0.8723] +2024-11-23 03:27:38.890316: Epoch time: 19.22 s +2024-11-23 03:27:39.822027: +2024-11-23 03:27:39.822264: Epoch 7464 +2024-11-23 03:27:39.822377: Current learning rate: 0.00088 +2024-11-23 03:27:58.345125: train_loss -0.8333 +2024-11-23 03:27:58.345354: val_loss -0.7479 +2024-11-23 03:27:58.345429: Pseudo dice [0.8316] +2024-11-23 03:27:58.345506: Epoch time: 18.52 s +2024-11-23 03:27:59.332539: +2024-11-23 03:27:59.332754: Epoch 7465 +2024-11-23 03:27:59.332868: Current learning rate: 0.00088 +2024-11-23 03:28:17.078020: train_loss -0.8365 +2024-11-23 03:28:17.078259: val_loss -0.7659 +2024-11-23 03:28:17.078332: Pseudo dice [0.8537] +2024-11-23 03:28:17.078412: Epoch time: 17.75 s +2024-11-23 03:28:18.033585: +2024-11-23 03:28:18.033808: Epoch 7466 +2024-11-23 03:28:18.033922: Current learning rate: 0.00087 +2024-11-23 03:28:36.254940: train_loss -0.8349 +2024-11-23 03:28:36.255197: val_loss -0.7481 +2024-11-23 03:28:36.255282: Pseudo dice [0.8541] +2024-11-23 03:28:36.255363: Epoch time: 18.22 s +2024-11-23 03:28:37.183681: +2024-11-23 03:28:37.183917: Epoch 7467 +2024-11-23 03:28:37.184034: Current learning rate: 0.00087 +2024-11-23 03:28:55.514050: train_loss -0.8358 +2024-11-23 03:28:55.514274: val_loss -0.7584 +2024-11-23 03:28:55.514348: Pseudo dice [0.8459] +2024-11-23 03:28:55.514427: Epoch time: 18.33 s +2024-11-23 03:28:56.448512: +2024-11-23 03:28:56.448741: Epoch 7468 +2024-11-23 03:28:56.448852: Current learning rate: 0.00087 +2024-11-23 03:29:15.183657: train_loss -0.8349 +2024-11-23 03:29:15.183903: val_loss -0.7673 +2024-11-23 03:29:15.183981: Pseudo dice [0.863] +2024-11-23 03:29:15.184128: Epoch time: 18.74 s +2024-11-23 03:29:16.130241: +2024-11-23 03:29:16.130461: Epoch 7469 +2024-11-23 03:29:16.130573: Current learning rate: 0.00087 +2024-11-23 03:29:35.404728: train_loss -0.8315 +2024-11-23 03:29:35.404989: val_loss -0.7602 +2024-11-23 03:29:35.405074: Pseudo dice [0.8587] +2024-11-23 03:29:35.405155: Epoch time: 19.28 s +2024-11-23 03:29:36.336357: +2024-11-23 03:29:36.336574: Epoch 7470 +2024-11-23 03:29:36.336687: Current learning rate: 0.00087 +2024-11-23 03:29:55.876328: train_loss -0.8365 +2024-11-23 03:29:55.876562: val_loss -0.76 +2024-11-23 03:29:55.876639: Pseudo dice [0.8548] +2024-11-23 03:29:55.876719: Epoch time: 19.54 s +2024-11-23 03:29:56.807827: +2024-11-23 03:29:56.808030: Epoch 7471 +2024-11-23 03:29:56.808141: Current learning rate: 0.00087 +2024-11-23 03:30:14.705591: train_loss -0.8335 +2024-11-23 03:30:14.705848: val_loss -0.7663 +2024-11-23 03:30:14.705925: Pseudo dice [0.8608] +2024-11-23 03:30:14.706007: Epoch time: 17.9 s +2024-11-23 03:30:15.736915: +2024-11-23 03:30:15.737138: Epoch 7472 +2024-11-23 03:30:15.737254: Current learning rate: 0.00087 +2024-11-23 03:30:34.201869: train_loss -0.8328 +2024-11-23 03:30:34.202096: val_loss -0.7465 +2024-11-23 03:30:34.202171: Pseudo dice [0.8513] +2024-11-23 03:30:34.202248: Epoch time: 18.47 s +2024-11-23 03:30:35.130841: +2024-11-23 03:30:35.131185: Epoch 7473 +2024-11-23 03:30:35.131297: Current learning rate: 0.00086 +2024-11-23 03:30:52.760601: train_loss -0.8319 +2024-11-23 03:30:52.760847: val_loss -0.7619 +2024-11-23 03:30:52.760923: Pseudo dice [0.8713] +2024-11-23 03:30:52.761010: Epoch time: 17.63 s +2024-11-23 03:30:54.091616: +2024-11-23 03:30:54.091811: Epoch 7474 +2024-11-23 03:30:54.091920: Current learning rate: 0.00086 +2024-11-23 03:31:12.467079: train_loss -0.8336 +2024-11-23 03:31:12.467308: val_loss -0.7493 +2024-11-23 03:31:12.467391: Pseudo dice [0.8646] +2024-11-23 03:31:12.467484: Epoch time: 18.38 s +2024-11-23 03:31:13.395010: +2024-11-23 03:31:13.395215: Epoch 7475 +2024-11-23 03:31:13.395325: Current learning rate: 0.00086 +2024-11-23 03:31:31.800586: train_loss -0.8247 +2024-11-23 03:31:31.800815: val_loss -0.7456 +2024-11-23 03:31:31.800887: Pseudo dice [0.8542] +2024-11-23 03:31:31.800961: Epoch time: 18.41 s +2024-11-23 03:31:32.753052: +2024-11-23 03:31:32.753336: Epoch 7476 +2024-11-23 03:31:32.753448: Current learning rate: 0.00086 +2024-11-23 03:31:50.882293: train_loss -0.8295 +2024-11-23 03:31:50.882646: val_loss -0.749 +2024-11-23 03:31:50.882732: Pseudo dice [0.8477] +2024-11-23 03:31:50.882816: Epoch time: 18.13 s +2024-11-23 03:31:51.807500: +2024-11-23 03:31:51.807727: Epoch 7477 +2024-11-23 03:31:51.807841: Current learning rate: 0.00086 +2024-11-23 03:32:10.547964: train_loss -0.836 +2024-11-23 03:32:10.548261: val_loss -0.7328 +2024-11-23 03:32:10.548342: Pseudo dice [0.8631] +2024-11-23 03:32:10.548423: Epoch time: 18.74 s +2024-11-23 03:32:11.480400: +2024-11-23 03:32:11.480664: Epoch 7478 +2024-11-23 03:32:11.480778: Current learning rate: 0.00086 +2024-11-23 03:32:30.272301: train_loss -0.8269 +2024-11-23 03:32:30.272682: val_loss -0.7501 +2024-11-23 03:32:30.272764: Pseudo dice [0.8686] +2024-11-23 03:32:30.272840: Epoch time: 18.79 s +2024-11-23 03:32:31.207844: +2024-11-23 03:32:31.208071: Epoch 7479 +2024-11-23 03:32:31.208183: Current learning rate: 0.00086 +2024-11-23 03:32:48.737746: train_loss -0.8349 +2024-11-23 03:32:48.737975: val_loss -0.7661 +2024-11-23 03:32:48.738062: Pseudo dice [0.8508] +2024-11-23 03:32:48.738139: Epoch time: 17.53 s +2024-11-23 03:32:49.665649: +2024-11-23 03:32:49.665850: Epoch 7480 +2024-11-23 03:32:49.665961: Current learning rate: 0.00085 +2024-11-23 03:33:07.825361: train_loss -0.8364 +2024-11-23 03:33:07.825616: val_loss -0.751 +2024-11-23 03:33:07.825694: Pseudo dice [0.8497] +2024-11-23 03:33:07.825778: Epoch time: 18.16 s +2024-11-23 03:33:08.861117: +2024-11-23 03:33:08.861452: Epoch 7481 +2024-11-23 03:33:08.861567: Current learning rate: 0.00085 +2024-11-23 03:33:28.299591: train_loss -0.8291 +2024-11-23 03:33:28.299815: val_loss -0.7282 +2024-11-23 03:33:28.299891: Pseudo dice [0.8601] +2024-11-23 03:33:28.299968: Epoch time: 19.44 s +2024-11-23 03:33:29.226599: +2024-11-23 03:33:29.226810: Epoch 7482 +2024-11-23 03:33:29.226929: Current learning rate: 0.00085 +2024-11-23 03:33:47.585003: train_loss -0.8218 +2024-11-23 03:33:47.585221: val_loss -0.7465 +2024-11-23 03:33:47.585297: Pseudo dice [0.8568] +2024-11-23 03:33:47.585375: Epoch time: 18.36 s +2024-11-23 03:33:48.510967: +2024-11-23 03:33:48.511236: Epoch 7483 +2024-11-23 03:33:48.511373: Current learning rate: 0.00085 +2024-11-23 03:34:07.344173: train_loss -0.833 +2024-11-23 03:34:07.344394: val_loss -0.7693 +2024-11-23 03:34:07.344467: Pseudo dice [0.8678] +2024-11-23 03:34:07.344543: Epoch time: 18.83 s +2024-11-23 03:34:08.273244: +2024-11-23 03:34:08.273476: Epoch 7484 +2024-11-23 03:34:08.273601: Current learning rate: 0.00085 +2024-11-23 03:34:27.411876: train_loss -0.8337 +2024-11-23 03:34:27.412128: val_loss -0.7541 +2024-11-23 03:34:27.412204: Pseudo dice [0.8523] +2024-11-23 03:34:27.412288: Epoch time: 19.14 s +2024-11-23 03:34:28.701745: +2024-11-23 03:34:28.701970: Epoch 7485 +2024-11-23 03:34:28.702096: Current learning rate: 0.00085 +2024-11-23 03:34:46.817364: train_loss -0.8348 +2024-11-23 03:34:46.817641: val_loss -0.7617 +2024-11-23 03:34:46.817723: Pseudo dice [0.8469] +2024-11-23 03:34:46.817829: Epoch time: 18.12 s +2024-11-23 03:34:47.742500: +2024-11-23 03:34:47.742817: Epoch 7486 +2024-11-23 03:34:47.742929: Current learning rate: 0.00085 +2024-11-23 03:35:05.880437: train_loss -0.8322 +2024-11-23 03:35:05.880659: val_loss -0.7716 +2024-11-23 03:35:05.880735: Pseudo dice [0.8342] +2024-11-23 03:35:05.880813: Epoch time: 18.14 s +2024-11-23 03:35:06.811275: +2024-11-23 03:35:06.811514: Epoch 7487 +2024-11-23 03:35:06.811623: Current learning rate: 0.00084 +2024-11-23 03:35:25.955539: train_loss -0.828 +2024-11-23 03:35:25.955798: val_loss -0.7599 +2024-11-23 03:35:25.955871: Pseudo dice [0.8607] +2024-11-23 03:35:25.955949: Epoch time: 19.15 s +2024-11-23 03:35:27.020370: +2024-11-23 03:35:27.020588: Epoch 7488 +2024-11-23 03:35:27.020700: Current learning rate: 0.00084 +2024-11-23 03:35:46.100812: train_loss -0.8333 +2024-11-23 03:35:46.101031: val_loss -0.7415 +2024-11-23 03:35:46.101106: Pseudo dice [0.8053] +2024-11-23 03:35:46.101183: Epoch time: 19.08 s +2024-11-23 03:35:47.045390: +2024-11-23 03:35:47.045612: Epoch 7489 +2024-11-23 03:35:47.045726: Current learning rate: 0.00084 +2024-11-23 03:36:06.081870: train_loss -0.8337 +2024-11-23 03:36:06.082092: val_loss -0.755 +2024-11-23 03:36:06.082168: Pseudo dice [0.8649] +2024-11-23 03:36:06.082248: Epoch time: 19.04 s +2024-11-23 03:36:07.007616: +2024-11-23 03:36:07.007880: Epoch 7490 +2024-11-23 03:36:07.008001: Current learning rate: 0.00084 +2024-11-23 03:36:25.699251: train_loss -0.8348 +2024-11-23 03:36:25.699461: val_loss -0.7442 +2024-11-23 03:36:25.699534: Pseudo dice [0.8673] +2024-11-23 03:36:25.699608: Epoch time: 18.69 s +2024-11-23 03:36:26.621899: +2024-11-23 03:36:26.622122: Epoch 7491 +2024-11-23 03:36:26.622231: Current learning rate: 0.00084 +2024-11-23 03:36:46.295970: train_loss -0.836 +2024-11-23 03:36:46.296287: val_loss -0.7863 +2024-11-23 03:36:46.296361: Pseudo dice [0.857] +2024-11-23 03:36:46.296445: Epoch time: 19.67 s +2024-11-23 03:36:47.226111: +2024-11-23 03:36:47.226335: Epoch 7492 +2024-11-23 03:36:47.226447: Current learning rate: 0.00084 +2024-11-23 03:37:06.456245: train_loss -0.831 +2024-11-23 03:37:06.456461: val_loss -0.7747 +2024-11-23 03:37:06.456536: Pseudo dice [0.8454] +2024-11-23 03:37:06.456615: Epoch time: 19.23 s +2024-11-23 03:37:07.383276: +2024-11-23 03:37:07.383535: Epoch 7493 +2024-11-23 03:37:07.383652: Current learning rate: 0.00084 +2024-11-23 03:37:26.628759: train_loss -0.8268 +2024-11-23 03:37:26.629072: val_loss -0.7523 +2024-11-23 03:37:26.629152: Pseudo dice [0.8384] +2024-11-23 03:37:26.629229: Epoch time: 19.25 s +2024-11-23 03:37:27.556938: +2024-11-23 03:37:27.557171: Epoch 7494 +2024-11-23 03:37:27.558962: Current learning rate: 0.00083 +2024-11-23 03:37:46.424095: train_loss -0.8331 +2024-11-23 03:37:46.424321: val_loss -0.7677 +2024-11-23 03:37:46.424395: Pseudo dice [0.8393] +2024-11-23 03:37:46.424470: Epoch time: 18.87 s +2024-11-23 03:37:47.350599: +2024-11-23 03:37:47.350798: Epoch 7495 +2024-11-23 03:37:47.350907: Current learning rate: 0.00083 +2024-11-23 03:38:05.532257: train_loss -0.8329 +2024-11-23 03:38:05.532502: val_loss -0.7462 +2024-11-23 03:38:05.532577: Pseudo dice [0.8337] +2024-11-23 03:38:05.532663: Epoch time: 18.18 s +2024-11-23 03:38:06.459618: +2024-11-23 03:38:06.459832: Epoch 7496 +2024-11-23 03:38:06.459944: Current learning rate: 0.00083 +2024-11-23 03:38:25.385079: train_loss -0.8274 +2024-11-23 03:38:25.385310: val_loss -0.7528 +2024-11-23 03:38:25.385386: Pseudo dice [0.8452] +2024-11-23 03:38:25.385461: Epoch time: 18.93 s +2024-11-23 03:38:26.766140: +2024-11-23 03:38:26.766388: Epoch 7497 +2024-11-23 03:38:26.766503: Current learning rate: 0.00083 +2024-11-23 03:38:45.398175: train_loss -0.8278 +2024-11-23 03:38:45.398407: val_loss -0.7633 +2024-11-23 03:38:45.398487: Pseudo dice [0.8455] +2024-11-23 03:38:45.398561: Epoch time: 18.63 s +2024-11-23 03:38:46.328195: +2024-11-23 03:38:46.328417: Epoch 7498 +2024-11-23 03:38:46.328526: Current learning rate: 0.00083 +2024-11-23 03:39:05.551089: train_loss -0.8409 +2024-11-23 03:39:05.551347: val_loss -0.7707 +2024-11-23 03:39:05.551421: Pseudo dice [0.8594] +2024-11-23 03:39:05.551504: Epoch time: 19.22 s +2024-11-23 03:39:06.482140: +2024-11-23 03:39:06.482375: Epoch 7499 +2024-11-23 03:39:06.482488: Current learning rate: 0.00083 +2024-11-23 03:39:24.406980: train_loss -0.8306 +2024-11-23 03:39:24.420260: val_loss -0.7556 +2024-11-23 03:39:24.427149: Pseudo dice [0.8431] +2024-11-23 03:39:24.427255: Epoch time: 17.93 s +2024-11-23 03:39:26.038300: +2024-11-23 03:39:26.038544: Epoch 7500 +2024-11-23 03:39:26.038654: Current learning rate: 0.00082 +2024-11-23 03:39:44.259543: train_loss -0.8319 +2024-11-23 03:39:44.259765: val_loss -0.7401 +2024-11-23 03:39:44.259845: Pseudo dice [0.8605] +2024-11-23 03:39:44.259932: Epoch time: 18.22 s +2024-11-23 03:39:45.182034: +2024-11-23 03:39:45.182276: Epoch 7501 +2024-11-23 03:39:45.182390: Current learning rate: 0.00082 +2024-11-23 03:40:04.666072: train_loss -0.8287 +2024-11-23 03:40:04.666299: val_loss -0.7715 +2024-11-23 03:40:04.666382: Pseudo dice [0.8429] +2024-11-23 03:40:04.666457: Epoch time: 19.48 s +2024-11-23 03:40:05.588452: +2024-11-23 03:40:05.588691: Epoch 7502 +2024-11-23 03:40:05.588803: Current learning rate: 0.00082 +2024-11-23 03:40:24.916037: train_loss -0.8255 +2024-11-23 03:40:24.916283: val_loss -0.764 +2024-11-23 03:40:24.916360: Pseudo dice [0.8447] +2024-11-23 03:40:24.916443: Epoch time: 19.33 s +2024-11-23 03:40:25.848519: +2024-11-23 03:40:25.848730: Epoch 7503 +2024-11-23 03:40:25.848844: Current learning rate: 0.00082 +2024-11-23 03:40:43.858891: train_loss -0.8306 +2024-11-23 03:40:43.859116: val_loss -0.7608 +2024-11-23 03:40:43.859193: Pseudo dice [0.8512] +2024-11-23 03:40:43.859273: Epoch time: 18.01 s +2024-11-23 03:40:44.788591: +2024-11-23 03:40:44.788807: Epoch 7504 +2024-11-23 03:40:44.788926: Current learning rate: 0.00082 +2024-11-23 03:41:03.714256: train_loss -0.8225 +2024-11-23 03:41:03.714475: val_loss -0.7628 +2024-11-23 03:41:03.714552: Pseudo dice [0.833] +2024-11-23 03:41:03.714641: Epoch time: 18.93 s +2024-11-23 03:41:04.641241: +2024-11-23 03:41:04.641458: Epoch 7505 +2024-11-23 03:41:04.641572: Current learning rate: 0.00082 +2024-11-23 03:41:24.231116: train_loss -0.8315 +2024-11-23 03:41:24.231327: val_loss -0.7675 +2024-11-23 03:41:24.231400: Pseudo dice [0.8643] +2024-11-23 03:41:24.231476: Epoch time: 19.59 s +2024-11-23 03:41:25.158745: +2024-11-23 03:41:25.158947: Epoch 7506 +2024-11-23 03:41:25.159069: Current learning rate: 0.00082 +2024-11-23 03:41:43.999350: train_loss -0.8379 +2024-11-23 03:41:43.999614: val_loss -0.7683 +2024-11-23 03:41:43.999691: Pseudo dice [0.8488] +2024-11-23 03:41:43.999776: Epoch time: 18.84 s +2024-11-23 03:41:44.987280: +2024-11-23 03:41:44.987543: Epoch 7507 +2024-11-23 03:41:44.987654: Current learning rate: 0.00081 +2024-11-23 03:42:02.497489: train_loss -0.839 +2024-11-23 03:42:02.497729: val_loss -0.7718 +2024-11-23 03:42:02.500055: Pseudo dice [0.8625] +2024-11-23 03:42:02.500153: Epoch time: 17.51 s +2024-11-23 03:42:03.435037: +2024-11-23 03:42:03.435340: Epoch 7508 +2024-11-23 03:42:03.435457: Current learning rate: 0.00081 +2024-11-23 03:42:23.074984: train_loss -0.8301 +2024-11-23 03:42:23.075240: val_loss -0.7534 +2024-11-23 03:42:23.075324: Pseudo dice [0.8546] +2024-11-23 03:42:23.075401: Epoch time: 19.64 s +2024-11-23 03:42:24.101315: +2024-11-23 03:42:24.101628: Epoch 7509 +2024-11-23 03:42:24.101741: Current learning rate: 0.00081 +2024-11-23 03:42:42.891922: train_loss -0.8243 +2024-11-23 03:42:42.892224: val_loss -0.7541 +2024-11-23 03:42:42.892306: Pseudo dice [0.8548] +2024-11-23 03:42:42.892389: Epoch time: 18.79 s +2024-11-23 03:42:43.822089: +2024-11-23 03:42:43.822304: Epoch 7510 +2024-11-23 03:42:43.822414: Current learning rate: 0.00081 +2024-11-23 03:43:01.536508: train_loss -0.8332 +2024-11-23 03:43:01.536725: val_loss -0.7295 +2024-11-23 03:43:01.536797: Pseudo dice [0.841] +2024-11-23 03:43:01.536872: Epoch time: 17.72 s +2024-11-23 03:43:02.467648: +2024-11-23 03:43:02.467852: Epoch 7511 +2024-11-23 03:43:02.467963: Current learning rate: 0.00081 +2024-11-23 03:43:19.989256: train_loss -0.8342 +2024-11-23 03:43:19.989497: val_loss -0.7621 +2024-11-23 03:43:19.989574: Pseudo dice [0.8354] +2024-11-23 03:43:19.989657: Epoch time: 17.52 s +2024-11-23 03:43:20.939671: +2024-11-23 03:43:20.939933: Epoch 7512 +2024-11-23 03:43:20.940054: Current learning rate: 0.00081 +2024-11-23 03:43:40.341040: train_loss -0.8303 +2024-11-23 03:43:40.341262: val_loss -0.7277 +2024-11-23 03:43:40.341341: Pseudo dice [0.837] +2024-11-23 03:43:40.341419: Epoch time: 19.4 s +2024-11-23 03:43:41.280447: +2024-11-23 03:43:41.280664: Epoch 7513 +2024-11-23 03:43:41.280784: Current learning rate: 0.00081 +2024-11-23 03:43:59.898501: train_loss -0.8307 +2024-11-23 03:43:59.898759: val_loss -0.7235 +2024-11-23 03:43:59.898891: Pseudo dice [0.8441] +2024-11-23 03:43:59.898976: Epoch time: 18.62 s +2024-11-23 03:44:00.824287: +2024-11-23 03:44:00.824517: Epoch 7514 +2024-11-23 03:44:00.824633: Current learning rate: 0.0008 +2024-11-23 03:44:19.361548: train_loss -0.8294 +2024-11-23 03:44:19.361776: val_loss -0.7529 +2024-11-23 03:44:19.361858: Pseudo dice [0.8654] +2024-11-23 03:44:19.361934: Epoch time: 18.54 s +2024-11-23 03:44:20.285949: +2024-11-23 03:44:20.286189: Epoch 7515 +2024-11-23 03:44:20.286295: Current learning rate: 0.0008 +2024-11-23 03:44:38.526026: train_loss -0.833 +2024-11-23 03:44:38.526249: val_loss -0.791 +2024-11-23 03:44:38.526324: Pseudo dice [0.8718] +2024-11-23 03:44:38.526399: Epoch time: 18.24 s +2024-11-23 03:44:39.451754: +2024-11-23 03:44:39.451957: Epoch 7516 +2024-11-23 03:44:39.452074: Current learning rate: 0.0008 +2024-11-23 03:44:58.751722: train_loss -0.8294 +2024-11-23 03:44:58.751945: val_loss -0.7615 +2024-11-23 03:44:58.752033: Pseudo dice [0.8573] +2024-11-23 03:44:58.752116: Epoch time: 19.3 s +2024-11-23 03:44:59.675112: +2024-11-23 03:44:59.675331: Epoch 7517 +2024-11-23 03:44:59.675440: Current learning rate: 0.0008 +2024-11-23 03:45:19.139636: train_loss -0.829 +2024-11-23 03:45:19.139889: val_loss -0.783 +2024-11-23 03:45:19.139964: Pseudo dice [0.8621] +2024-11-23 03:45:19.140055: Epoch time: 19.47 s +2024-11-23 03:45:20.283689: +2024-11-23 03:45:20.283929: Epoch 7518 +2024-11-23 03:45:20.284045: Current learning rate: 0.0008 +2024-11-23 03:45:37.218046: train_loss -0.8391 +2024-11-23 03:45:37.218261: val_loss -0.7459 +2024-11-23 03:45:37.218339: Pseudo dice [0.8574] +2024-11-23 03:45:37.218416: Epoch time: 16.94 s +2024-11-23 03:45:38.143729: +2024-11-23 03:45:38.143957: Epoch 7519 +2024-11-23 03:45:38.144074: Current learning rate: 0.0008 +2024-11-23 03:45:57.420065: train_loss -0.8318 +2024-11-23 03:45:57.420286: val_loss -0.7445 +2024-11-23 03:45:57.420362: Pseudo dice [0.8576] +2024-11-23 03:45:57.420443: Epoch time: 19.28 s +2024-11-23 03:45:58.703749: +2024-11-23 03:45:58.703961: Epoch 7520 +2024-11-23 03:45:58.704079: Current learning rate: 0.00079 +2024-11-23 03:46:17.342456: train_loss -0.8355 +2024-11-23 03:46:17.342697: val_loss -0.7734 +2024-11-23 03:46:17.344950: Pseudo dice [0.8591] +2024-11-23 03:46:17.345054: Epoch time: 18.64 s +2024-11-23 03:46:18.440411: +2024-11-23 03:46:18.440673: Epoch 7521 +2024-11-23 03:46:18.440823: Current learning rate: 0.00079 +2024-11-23 03:46:37.386055: train_loss -0.8362 +2024-11-23 03:46:37.386284: val_loss -0.7318 +2024-11-23 03:46:37.386359: Pseudo dice [0.8468] +2024-11-23 03:46:37.386440: Epoch time: 18.95 s +2024-11-23 03:46:38.316745: +2024-11-23 03:46:38.317016: Epoch 7522 +2024-11-23 03:46:38.317165: Current learning rate: 0.00079 +2024-11-23 03:46:56.232471: train_loss -0.8309 +2024-11-23 03:46:56.232686: val_loss -0.7734 +2024-11-23 03:46:56.232760: Pseudo dice [0.8629] +2024-11-23 03:46:56.232835: Epoch time: 17.92 s +2024-11-23 03:46:57.158918: +2024-11-23 03:46:57.159131: Epoch 7523 +2024-11-23 03:46:57.159242: Current learning rate: 0.00079 +2024-11-23 03:47:16.812711: train_loss -0.8301 +2024-11-23 03:47:16.812937: val_loss -0.7374 +2024-11-23 03:47:16.813034: Pseudo dice [0.83] +2024-11-23 03:47:16.813112: Epoch time: 19.65 s +2024-11-23 03:47:17.740570: +2024-11-23 03:47:17.740815: Epoch 7524 +2024-11-23 03:47:17.740936: Current learning rate: 0.00079 +2024-11-23 03:47:36.721477: train_loss -0.8264 +2024-11-23 03:47:36.721789: val_loss -0.7586 +2024-11-23 03:47:36.721865: Pseudo dice [0.8642] +2024-11-23 03:47:36.721949: Epoch time: 18.98 s +2024-11-23 03:47:37.661293: +2024-11-23 03:47:37.661557: Epoch 7525 +2024-11-23 03:47:37.661670: Current learning rate: 0.00079 +2024-11-23 03:47:56.880629: train_loss -0.828 +2024-11-23 03:47:56.880855: val_loss -0.7999 +2024-11-23 03:47:56.883239: Pseudo dice [0.862] +2024-11-23 03:47:56.883339: Epoch time: 19.22 s +2024-11-23 03:47:57.896188: +2024-11-23 03:47:57.896387: Epoch 7526 +2024-11-23 03:47:57.896493: Current learning rate: 0.00079 +2024-11-23 03:48:15.963126: train_loss -0.8357 +2024-11-23 03:48:15.963345: val_loss -0.7427 +2024-11-23 03:48:15.963431: Pseudo dice [0.8367] +2024-11-23 03:48:15.963585: Epoch time: 18.07 s +2024-11-23 03:48:16.890847: +2024-11-23 03:48:16.891064: Epoch 7527 +2024-11-23 03:48:16.891174: Current learning rate: 0.00078 +2024-11-23 03:48:35.479759: train_loss -0.8263 +2024-11-23 03:48:35.479980: val_loss -0.7751 +2024-11-23 03:48:35.480065: Pseudo dice [0.846] +2024-11-23 03:48:35.480147: Epoch time: 18.59 s +2024-11-23 03:48:36.402857: +2024-11-23 03:48:36.403067: Epoch 7528 +2024-11-23 03:48:36.403173: Current learning rate: 0.00078 +2024-11-23 03:48:54.946604: train_loss -0.8274 +2024-11-23 03:48:54.946931: val_loss -0.7529 +2024-11-23 03:48:54.947017: Pseudo dice [0.8697] +2024-11-23 03:48:54.947102: Epoch time: 18.54 s +2024-11-23 03:48:55.880017: +2024-11-23 03:48:55.880236: Epoch 7529 +2024-11-23 03:48:55.880357: Current learning rate: 0.00078 +2024-11-23 03:49:14.341446: train_loss -0.8308 +2024-11-23 03:49:14.341689: val_loss -0.7514 +2024-11-23 03:49:14.341766: Pseudo dice [0.8284] +2024-11-23 03:49:14.341842: Epoch time: 18.46 s +2024-11-23 03:49:15.263370: +2024-11-23 03:49:15.263587: Epoch 7530 +2024-11-23 03:49:15.263700: Current learning rate: 0.00078 +2024-11-23 03:49:33.808470: train_loss -0.8338 +2024-11-23 03:49:33.808702: val_loss -0.79 +2024-11-23 03:49:33.808776: Pseudo dice [0.8569] +2024-11-23 03:49:33.808851: Epoch time: 18.55 s +2024-11-23 03:49:35.112509: +2024-11-23 03:49:35.112741: Epoch 7531 +2024-11-23 03:49:35.112860: Current learning rate: 0.00078 +2024-11-23 03:49:52.275781: train_loss -0.8352 +2024-11-23 03:49:52.276050: val_loss -0.7378 +2024-11-23 03:49:52.276129: Pseudo dice [0.8577] +2024-11-23 03:49:52.276213: Epoch time: 17.16 s +2024-11-23 03:49:53.194039: +2024-11-23 03:49:53.194280: Epoch 7532 +2024-11-23 03:49:53.194390: Current learning rate: 0.00078 +2024-11-23 03:50:11.133806: train_loss -0.8347 +2024-11-23 03:50:11.134098: val_loss -0.7679 +2024-11-23 03:50:11.134180: Pseudo dice [0.8361] +2024-11-23 03:50:11.134257: Epoch time: 17.94 s +2024-11-23 03:50:12.060052: +2024-11-23 03:50:12.060288: Epoch 7533 +2024-11-23 03:50:12.060399: Current learning rate: 0.00078 +2024-11-23 03:50:30.921591: train_loss -0.8367 +2024-11-23 03:50:30.921813: val_loss -0.7592 +2024-11-23 03:50:30.921893: Pseudo dice [0.8235] +2024-11-23 03:50:30.921968: Epoch time: 18.86 s +2024-11-23 03:50:31.948564: +2024-11-23 03:50:31.948870: Epoch 7534 +2024-11-23 03:50:31.948988: Current learning rate: 0.00077 +2024-11-23 03:50:49.931132: train_loss -0.8266 +2024-11-23 03:50:49.931387: val_loss -0.7322 +2024-11-23 03:50:49.931464: Pseudo dice [0.8657] +2024-11-23 03:50:49.931551: Epoch time: 17.98 s +2024-11-23 03:50:50.859627: +2024-11-23 03:50:50.859828: Epoch 7535 +2024-11-23 03:50:50.859938: Current learning rate: 0.00077 +2024-11-23 03:51:09.854535: train_loss -0.828 +2024-11-23 03:51:09.854745: val_loss -0.7437 +2024-11-23 03:51:09.854816: Pseudo dice [0.8331] +2024-11-23 03:51:09.854889: Epoch time: 19.0 s +2024-11-23 03:51:10.905893: +2024-11-23 03:51:10.906116: Epoch 7536 +2024-11-23 03:51:10.906229: Current learning rate: 0.00077 +2024-11-23 03:51:29.118195: train_loss -0.8304 +2024-11-23 03:51:29.118419: val_loss -0.727 +2024-11-23 03:51:29.118496: Pseudo dice [0.8671] +2024-11-23 03:51:29.118572: Epoch time: 18.21 s +2024-11-23 03:51:30.082102: +2024-11-23 03:51:30.082309: Epoch 7537 +2024-11-23 03:51:30.082424: Current learning rate: 0.00077 +2024-11-23 03:51:49.699020: train_loss -0.8297 +2024-11-23 03:51:49.699305: val_loss -0.7774 +2024-11-23 03:51:49.699384: Pseudo dice [0.8535] +2024-11-23 03:51:49.699462: Epoch time: 19.62 s +2024-11-23 03:51:50.624651: +2024-11-23 03:51:50.624870: Epoch 7538 +2024-11-23 03:51:50.624987: Current learning rate: 0.00077 +2024-11-23 03:52:10.905803: train_loss -0.8326 +2024-11-23 03:52:10.906065: val_loss -0.7533 +2024-11-23 03:52:10.906142: Pseudo dice [0.8471] +2024-11-23 03:52:10.906228: Epoch time: 20.28 s +2024-11-23 03:52:11.833031: +2024-11-23 03:52:11.833245: Epoch 7539 +2024-11-23 03:52:11.833367: Current learning rate: 0.00077 +2024-11-23 03:52:29.251732: train_loss -0.8357 +2024-11-23 03:52:29.251954: val_loss -0.7712 +2024-11-23 03:52:29.252132: Pseudo dice [0.8564] +2024-11-23 03:52:29.252213: Epoch time: 17.42 s +2024-11-23 03:52:30.337899: +2024-11-23 03:52:30.338127: Epoch 7540 +2024-11-23 03:52:30.338243: Current learning rate: 0.00077 +2024-11-23 03:52:49.139750: train_loss -0.8335 +2024-11-23 03:52:49.139977: val_loss -0.7787 +2024-11-23 03:52:49.140144: Pseudo dice [0.8653] +2024-11-23 03:52:49.140247: Epoch time: 18.8 s +2024-11-23 03:52:50.066507: +2024-11-23 03:52:50.066784: Epoch 7541 +2024-11-23 03:52:50.066896: Current learning rate: 0.00076 +2024-11-23 03:53:09.054687: train_loss -0.8344 +2024-11-23 03:53:09.054916: val_loss -0.7256 +2024-11-23 03:53:09.055001: Pseudo dice [0.8329] +2024-11-23 03:53:09.055078: Epoch time: 18.99 s +2024-11-23 03:53:09.985265: +2024-11-23 03:53:09.985495: Epoch 7542 +2024-11-23 03:53:09.985613: Current learning rate: 0.00076 +2024-11-23 03:53:29.274045: train_loss -0.8369 +2024-11-23 03:53:29.274289: val_loss -0.7709 +2024-11-23 03:53:29.274368: Pseudo dice [0.8576] +2024-11-23 03:53:29.274448: Epoch time: 19.29 s +2024-11-23 03:53:30.614725: +2024-11-23 03:53:30.614959: Epoch 7543 +2024-11-23 03:53:30.615080: Current learning rate: 0.00076 +2024-11-23 03:53:48.866692: train_loss -0.8331 +2024-11-23 03:53:48.866910: val_loss -0.7568 +2024-11-23 03:53:48.866988: Pseudo dice [0.8636] +2024-11-23 03:53:48.867075: Epoch time: 18.25 s +2024-11-23 03:53:49.792881: +2024-11-23 03:53:49.793106: Epoch 7544 +2024-11-23 03:53:49.793216: Current learning rate: 0.00076 +2024-11-23 03:54:08.717208: train_loss -0.8284 +2024-11-23 03:54:08.717446: val_loss -0.773 +2024-11-23 03:54:08.717518: Pseudo dice [0.866] +2024-11-23 03:54:08.717659: Epoch time: 18.93 s +2024-11-23 03:54:09.640704: +2024-11-23 03:54:09.640911: Epoch 7545 +2024-11-23 03:54:09.641029: Current learning rate: 0.00076 +2024-11-23 03:54:29.380476: train_loss -0.8343 +2024-11-23 03:54:29.380751: val_loss -0.7595 +2024-11-23 03:54:29.382965: Pseudo dice [0.8596] +2024-11-23 03:54:29.383090: Epoch time: 19.74 s +2024-11-23 03:54:30.325912: +2024-11-23 03:54:30.326129: Epoch 7546 +2024-11-23 03:54:30.326242: Current learning rate: 0.00076 +2024-11-23 03:54:48.332390: train_loss -0.8351 +2024-11-23 03:54:48.332602: val_loss -0.7386 +2024-11-23 03:54:48.332673: Pseudo dice [0.8556] +2024-11-23 03:54:48.332747: Epoch time: 18.01 s +2024-11-23 03:54:49.260545: +2024-11-23 03:54:49.260764: Epoch 7547 +2024-11-23 03:54:49.260882: Current learning rate: 0.00075 +2024-11-23 03:55:08.103124: train_loss -0.8251 +2024-11-23 03:55:08.103360: val_loss -0.7575 +2024-11-23 03:55:08.103439: Pseudo dice [0.8558] +2024-11-23 03:55:08.103515: Epoch time: 18.84 s +2024-11-23 03:55:09.028249: +2024-11-23 03:55:09.028453: Epoch 7548 +2024-11-23 03:55:09.028563: Current learning rate: 0.00075 +2024-11-23 03:55:28.332504: train_loss -0.8338 +2024-11-23 03:55:28.332728: val_loss -0.749 +2024-11-23 03:55:28.332813: Pseudo dice [0.8595] +2024-11-23 03:55:28.332889: Epoch time: 19.31 s +2024-11-23 03:55:29.262158: +2024-11-23 03:55:29.262358: Epoch 7549 +2024-11-23 03:55:29.262469: Current learning rate: 0.00075 +2024-11-23 03:55:48.479859: train_loss -0.8322 +2024-11-23 03:55:48.480122: val_loss -0.7734 +2024-11-23 03:55:48.480199: Pseudo dice [0.8595] +2024-11-23 03:55:48.480284: Epoch time: 19.22 s +2024-11-23 03:55:49.751837: +2024-11-23 03:55:49.752043: Epoch 7550 +2024-11-23 03:55:49.752153: Current learning rate: 0.00075 +2024-11-23 03:56:08.024413: train_loss -0.8382 +2024-11-23 03:56:08.024628: val_loss -0.7424 +2024-11-23 03:56:08.024702: Pseudo dice [0.8299] +2024-11-23 03:56:08.024776: Epoch time: 18.27 s +2024-11-23 03:56:08.949787: +2024-11-23 03:56:08.950012: Epoch 7551 +2024-11-23 03:56:08.950121: Current learning rate: 0.00075 +2024-11-23 03:56:27.875470: train_loss -0.836 +2024-11-23 03:56:27.875690: val_loss -0.7434 +2024-11-23 03:56:27.875766: Pseudo dice [0.8428] +2024-11-23 03:56:27.875843: Epoch time: 18.93 s +2024-11-23 03:56:28.811115: +2024-11-23 03:56:28.811436: Epoch 7552 +2024-11-23 03:56:28.811548: Current learning rate: 0.00075 +2024-11-23 03:56:48.143766: train_loss -0.8325 +2024-11-23 03:56:48.143987: val_loss -0.7691 +2024-11-23 03:56:48.144077: Pseudo dice [0.8481] +2024-11-23 03:56:48.144177: Epoch time: 19.33 s +2024-11-23 03:56:49.064571: +2024-11-23 03:56:49.064828: Epoch 7553 +2024-11-23 03:56:49.064942: Current learning rate: 0.00075 +2024-11-23 03:57:07.926567: train_loss -0.8326 +2024-11-23 03:57:07.926816: val_loss -0.7306 +2024-11-23 03:57:07.926889: Pseudo dice [0.8552] +2024-11-23 03:57:07.926968: Epoch time: 18.86 s +2024-11-23 03:57:09.210766: +2024-11-23 03:57:09.210995: Epoch 7554 +2024-11-23 03:57:09.211113: Current learning rate: 0.00074 +2024-11-23 03:57:27.520484: train_loss -0.8405 +2024-11-23 03:57:27.520736: val_loss -0.755 +2024-11-23 03:57:27.520839: Pseudo dice [0.8284] +2024-11-23 03:57:27.520923: Epoch time: 18.31 s +2024-11-23 03:57:28.442111: +2024-11-23 03:57:28.442348: Epoch 7555 +2024-11-23 03:57:28.442465: Current learning rate: 0.00074 +2024-11-23 03:57:47.255968: train_loss -0.8326 +2024-11-23 03:57:47.256194: val_loss -0.7502 +2024-11-23 03:57:47.256269: Pseudo dice [0.863] +2024-11-23 03:57:47.256347: Epoch time: 18.81 s +2024-11-23 03:57:48.205787: +2024-11-23 03:57:48.205997: Epoch 7556 +2024-11-23 03:57:48.206180: Current learning rate: 0.00074 +2024-11-23 03:58:06.609640: train_loss -0.8371 +2024-11-23 03:58:06.609886: val_loss -0.7588 +2024-11-23 03:58:06.609961: Pseudo dice [0.8505] +2024-11-23 03:58:06.610048: Epoch time: 18.4 s +2024-11-23 03:58:07.568384: +2024-11-23 03:58:07.568586: Epoch 7557 +2024-11-23 03:58:07.568699: Current learning rate: 0.00074 +2024-11-23 03:58:24.693472: train_loss -0.8348 +2024-11-23 03:58:24.693687: val_loss -0.7139 +2024-11-23 03:58:24.693761: Pseudo dice [0.8489] +2024-11-23 03:58:24.693835: Epoch time: 17.13 s +2024-11-23 03:58:25.623425: +2024-11-23 03:58:25.623704: Epoch 7558 +2024-11-23 03:58:25.623820: Current learning rate: 0.00074 +2024-11-23 03:58:44.203198: train_loss -0.8258 +2024-11-23 03:58:44.203425: val_loss -0.7628 +2024-11-23 03:58:44.203503: Pseudo dice [0.8666] +2024-11-23 03:58:44.203580: Epoch time: 18.58 s +2024-11-23 03:58:45.127440: +2024-11-23 03:58:45.127678: Epoch 7559 +2024-11-23 03:58:45.127788: Current learning rate: 0.00074 +2024-11-23 03:59:02.818965: train_loss -0.8401 +2024-11-23 03:59:02.819232: val_loss -0.718 +2024-11-23 03:59:02.819311: Pseudo dice [0.833] +2024-11-23 03:59:02.819384: Epoch time: 17.69 s +2024-11-23 03:59:03.748162: +2024-11-23 03:59:03.748456: Epoch 7560 +2024-11-23 03:59:03.748580: Current learning rate: 0.00074 +2024-11-23 03:59:22.631670: train_loss -0.8264 +2024-11-23 03:59:22.631918: val_loss -0.7558 +2024-11-23 03:59:22.632020: Pseudo dice [0.8541] +2024-11-23 03:59:22.632106: Epoch time: 18.88 s +2024-11-23 03:59:23.666254: +2024-11-23 03:59:23.666574: Epoch 7561 +2024-11-23 03:59:23.666691: Current learning rate: 0.00073 +2024-11-23 03:59:42.738756: train_loss -0.8277 +2024-11-23 03:59:42.738965: val_loss -0.7776 +2024-11-23 03:59:42.739045: Pseudo dice [0.8828] +2024-11-23 03:59:42.739119: Epoch time: 19.07 s +2024-11-23 03:59:43.660458: +2024-11-23 03:59:43.660684: Epoch 7562 +2024-11-23 03:59:43.660799: Current learning rate: 0.00073 +2024-11-23 04:00:02.166893: train_loss -0.8393 +2024-11-23 04:00:02.167126: val_loss -0.7455 +2024-11-23 04:00:02.167197: Pseudo dice [0.8568] +2024-11-23 04:00:02.167272: Epoch time: 18.51 s +2024-11-23 04:00:03.091305: +2024-11-23 04:00:03.091537: Epoch 7563 +2024-11-23 04:00:03.091653: Current learning rate: 0.00073 +2024-11-23 04:00:21.990939: train_loss -0.8302 +2024-11-23 04:00:21.991176: val_loss -0.7409 +2024-11-23 04:00:21.991253: Pseudo dice [0.833] +2024-11-23 04:00:21.991336: Epoch time: 18.9 s +2024-11-23 04:00:22.917190: +2024-11-23 04:00:22.917443: Epoch 7564 +2024-11-23 04:00:22.917581: Current learning rate: 0.00073 +2024-11-23 04:00:42.871526: train_loss -0.8334 +2024-11-23 04:00:42.871747: val_loss -0.7538 +2024-11-23 04:00:42.871821: Pseudo dice [0.864] +2024-11-23 04:00:42.871897: Epoch time: 19.96 s +2024-11-23 04:00:43.836550: +2024-11-23 04:00:43.836757: Epoch 7565 +2024-11-23 04:00:43.836872: Current learning rate: 0.00073 +2024-11-23 04:01:02.001667: train_loss -0.8365 +2024-11-23 04:01:02.001891: val_loss -0.7499 +2024-11-23 04:01:02.001966: Pseudo dice [0.8167] +2024-11-23 04:01:02.002049: Epoch time: 18.17 s +2024-11-23 04:01:03.369254: +2024-11-23 04:01:03.369467: Epoch 7566 +2024-11-23 04:01:03.369603: Current learning rate: 0.00073 +2024-11-23 04:01:21.640049: train_loss -0.8342 +2024-11-23 04:01:21.640291: val_loss -0.7608 +2024-11-23 04:01:21.640376: Pseudo dice [0.8608] +2024-11-23 04:01:21.640453: Epoch time: 18.27 s +2024-11-23 04:01:22.570090: +2024-11-23 04:01:22.570455: Epoch 7567 +2024-11-23 04:01:22.570606: Current learning rate: 0.00072 +2024-11-23 04:01:41.220904: train_loss -0.8318 +2024-11-23 04:01:41.221134: val_loss -0.7543 +2024-11-23 04:01:41.221207: Pseudo dice [0.8556] +2024-11-23 04:01:41.221285: Epoch time: 18.65 s +2024-11-23 04:01:42.146528: +2024-11-23 04:01:42.146778: Epoch 7568 +2024-11-23 04:01:42.146893: Current learning rate: 0.00072 +2024-11-23 04:02:01.100478: train_loss -0.8375 +2024-11-23 04:02:01.102872: val_loss -0.7571 +2024-11-23 04:02:01.102998: Pseudo dice [0.8641] +2024-11-23 04:02:01.103081: Epoch time: 18.95 s +2024-11-23 04:02:02.139235: +2024-11-23 04:02:02.139449: Epoch 7569 +2024-11-23 04:02:02.139560: Current learning rate: 0.00072 +2024-11-23 04:02:21.412162: train_loss -0.8351 +2024-11-23 04:02:21.412379: val_loss -0.7733 +2024-11-23 04:02:21.412453: Pseudo dice [0.8561] +2024-11-23 04:02:21.412527: Epoch time: 19.27 s +2024-11-23 04:02:22.339272: +2024-11-23 04:02:22.339556: Epoch 7570 +2024-11-23 04:02:22.339669: Current learning rate: 0.00072 +2024-11-23 04:02:40.221654: train_loss -0.8357 +2024-11-23 04:02:40.221909: val_loss -0.7557 +2024-11-23 04:02:40.221986: Pseudo dice [0.8387] +2024-11-23 04:02:40.222098: Epoch time: 17.88 s +2024-11-23 04:02:41.155641: +2024-11-23 04:02:41.155856: Epoch 7571 +2024-11-23 04:02:41.155971: Current learning rate: 0.00072 +2024-11-23 04:02:59.208927: train_loss -0.8256 +2024-11-23 04:02:59.209157: val_loss -0.7865 +2024-11-23 04:02:59.209251: Pseudo dice [0.8681] +2024-11-23 04:02:59.209328: Epoch time: 18.05 s +2024-11-23 04:03:00.136378: +2024-11-23 04:03:00.136598: Epoch 7572 +2024-11-23 04:03:00.136713: Current learning rate: 0.00072 +2024-11-23 04:03:19.239161: train_loss -0.8338 +2024-11-23 04:03:19.239379: val_loss -0.74 +2024-11-23 04:03:19.239456: Pseudo dice [0.8482] +2024-11-23 04:03:19.239534: Epoch time: 19.1 s +2024-11-23 04:03:20.181840: +2024-11-23 04:03:20.182119: Epoch 7573 +2024-11-23 04:03:20.182235: Current learning rate: 0.00072 +2024-11-23 04:03:39.982544: train_loss -0.8374 +2024-11-23 04:03:39.982792: val_loss -0.7527 +2024-11-23 04:03:39.982870: Pseudo dice [0.8655] +2024-11-23 04:03:39.982947: Epoch time: 19.8 s +2024-11-23 04:03:40.912288: +2024-11-23 04:03:40.912499: Epoch 7574 +2024-11-23 04:03:40.912614: Current learning rate: 0.00071 +2024-11-23 04:03:58.852035: train_loss -0.8323 +2024-11-23 04:03:58.852342: val_loss -0.7682 +2024-11-23 04:03:58.852426: Pseudo dice [0.8733] +2024-11-23 04:03:58.852512: Epoch time: 17.94 s +2024-11-23 04:03:59.782146: +2024-11-23 04:03:59.782357: Epoch 7575 +2024-11-23 04:03:59.782474: Current learning rate: 0.00071 +2024-11-23 04:04:18.867835: train_loss -0.8334 +2024-11-23 04:04:18.868131: val_loss -0.7333 +2024-11-23 04:04:18.868207: Pseudo dice [0.879] +2024-11-23 04:04:18.868283: Epoch time: 19.09 s +2024-11-23 04:04:19.802636: +2024-11-23 04:04:19.802837: Epoch 7576 +2024-11-23 04:04:19.802969: Current learning rate: 0.00071 +2024-11-23 04:04:39.577266: train_loss -0.8377 +2024-11-23 04:04:39.577489: val_loss -0.7668 +2024-11-23 04:04:39.577562: Pseudo dice [0.8617] +2024-11-23 04:04:39.577637: Epoch time: 19.78 s +2024-11-23 04:04:40.868275: +2024-11-23 04:04:40.868492: Epoch 7577 +2024-11-23 04:04:40.868610: Current learning rate: 0.00071 +2024-11-23 04:04:59.988045: train_loss -0.8215 +2024-11-23 04:04:59.988328: val_loss -0.774 +2024-11-23 04:04:59.988404: Pseudo dice [0.8554] +2024-11-23 04:04:59.988488: Epoch time: 19.12 s +2024-11-23 04:05:01.029337: +2024-11-23 04:05:01.029817: Epoch 7578 +2024-11-23 04:05:01.029960: Current learning rate: 0.00071 +2024-11-23 04:05:20.151011: train_loss -0.8372 +2024-11-23 04:05:20.151239: val_loss -0.765 +2024-11-23 04:05:20.151316: Pseudo dice [0.8592] +2024-11-23 04:05:20.151395: Epoch time: 19.12 s +2024-11-23 04:05:21.087973: +2024-11-23 04:05:21.088476: Epoch 7579 +2024-11-23 04:05:21.088611: Current learning rate: 0.00071 +2024-11-23 04:05:39.312224: train_loss -0.8406 +2024-11-23 04:05:39.312443: val_loss -0.7697 +2024-11-23 04:05:39.312518: Pseudo dice [0.8761] +2024-11-23 04:05:39.312592: Epoch time: 18.23 s +2024-11-23 04:05:39.312652: Yayy! New best EMA pseudo Dice: 0.8601 +2024-11-23 04:05:40.613988: +2024-11-23 04:05:40.614428: Epoch 7580 +2024-11-23 04:05:40.614560: Current learning rate: 0.0007 +2024-11-23 04:05:59.378870: train_loss -0.8346 +2024-11-23 04:05:59.379105: val_loss -0.7673 +2024-11-23 04:05:59.379178: Pseudo dice [0.8726] +2024-11-23 04:05:59.379261: Epoch time: 18.77 s +2024-11-23 04:05:59.379323: Yayy! New best EMA pseudo Dice: 0.8613 +2024-11-23 04:06:00.762822: +2024-11-23 04:06:00.763267: Epoch 7581 +2024-11-23 04:06:00.763405: Current learning rate: 0.0007 +2024-11-23 04:06:18.784827: train_loss -0.8382 +2024-11-23 04:06:18.785050: val_loss -0.7213 +2024-11-23 04:06:18.785129: Pseudo dice [0.8693] +2024-11-23 04:06:18.785302: Epoch time: 18.02 s +2024-11-23 04:06:18.785376: Yayy! New best EMA pseudo Dice: 0.8621 +2024-11-23 04:06:20.059415: +2024-11-23 04:06:20.059849: Epoch 7582 +2024-11-23 04:06:20.059985: Current learning rate: 0.0007 +2024-11-23 04:06:39.800656: train_loss -0.8293 +2024-11-23 04:06:39.800866: val_loss -0.7676 +2024-11-23 04:06:39.800940: Pseudo dice [0.8496] +2024-11-23 04:06:39.801025: Epoch time: 19.74 s +2024-11-23 04:06:40.731197: +2024-11-23 04:06:40.731648: Epoch 7583 +2024-11-23 04:06:40.731786: Current learning rate: 0.0007 +2024-11-23 04:07:00.084566: train_loss -0.8346 +2024-11-23 04:07:00.089923: val_loss -0.7691 +2024-11-23 04:07:00.090060: Pseudo dice [0.8467] +2024-11-23 04:07:00.090142: Epoch time: 19.35 s +2024-11-23 04:07:01.129910: +2024-11-23 04:07:01.130427: Epoch 7584 +2024-11-23 04:07:01.130563: Current learning rate: 0.0007 +2024-11-23 04:07:19.179677: train_loss -0.8364 +2024-11-23 04:07:19.179935: val_loss -0.7604 +2024-11-23 04:07:19.180021: Pseudo dice [0.8545] +2024-11-23 04:07:19.180109: Epoch time: 18.05 s +2024-11-23 04:07:20.110592: +2024-11-23 04:07:20.111146: Epoch 7585 +2024-11-23 04:07:20.111288: Current learning rate: 0.0007 +2024-11-23 04:07:39.947091: train_loss -0.8373 +2024-11-23 04:07:39.947305: val_loss -0.7273 +2024-11-23 04:07:39.947380: Pseudo dice [0.8128] +2024-11-23 04:07:39.947453: Epoch time: 19.84 s +2024-11-23 04:07:40.866688: +2024-11-23 04:07:40.867192: Epoch 7586 +2024-11-23 04:07:40.867327: Current learning rate: 0.0007 +2024-11-23 04:07:59.874345: train_loss -0.8303 +2024-11-23 04:07:59.874586: val_loss -0.7676 +2024-11-23 04:07:59.874662: Pseudo dice [0.8563] +2024-11-23 04:07:59.874740: Epoch time: 19.01 s +2024-11-23 04:08:00.822069: +2024-11-23 04:08:00.822520: Epoch 7587 +2024-11-23 04:08:00.822661: Current learning rate: 0.00069 +2024-11-23 04:08:19.006887: train_loss -0.8357 +2024-11-23 04:08:19.007205: val_loss -0.7521 +2024-11-23 04:08:19.007283: Pseudo dice [0.8553] +2024-11-23 04:08:19.007366: Epoch time: 18.19 s +2024-11-23 04:08:19.949190: +2024-11-23 04:08:19.949415: Epoch 7588 +2024-11-23 04:08:19.949528: Current learning rate: 0.00069 +2024-11-23 04:08:38.596080: train_loss -0.8291 +2024-11-23 04:08:38.596328: val_loss -0.7546 +2024-11-23 04:08:38.596407: Pseudo dice [0.8495] +2024-11-23 04:08:38.596483: Epoch time: 18.65 s +2024-11-23 04:08:39.518869: +2024-11-23 04:08:39.519100: Epoch 7589 +2024-11-23 04:08:39.519218: Current learning rate: 0.00069 +2024-11-23 04:08:57.612096: train_loss -0.8313 +2024-11-23 04:08:57.617826: val_loss -0.7606 +2024-11-23 04:08:57.617982: Pseudo dice [0.8456] +2024-11-23 04:08:57.618068: Epoch time: 18.09 s +2024-11-23 04:08:58.726376: +2024-11-23 04:08:58.726627: Epoch 7590 +2024-11-23 04:08:58.726740: Current learning rate: 0.00069 +2024-11-23 04:09:15.652845: train_loss -0.833 +2024-11-23 04:09:15.653077: val_loss -0.7734 +2024-11-23 04:09:15.653156: Pseudo dice [0.8649] +2024-11-23 04:09:15.653239: Epoch time: 16.93 s +2024-11-23 04:09:16.580672: +2024-11-23 04:09:16.580901: Epoch 7591 +2024-11-23 04:09:16.581017: Current learning rate: 0.00069 +2024-11-23 04:09:35.038563: train_loss -0.8336 +2024-11-23 04:09:35.038850: val_loss -0.7616 +2024-11-23 04:09:35.038930: Pseudo dice [0.8298] +2024-11-23 04:09:35.039061: Epoch time: 18.46 s +2024-11-23 04:09:35.971941: +2024-11-23 04:09:35.972172: Epoch 7592 +2024-11-23 04:09:35.972288: Current learning rate: 0.00069 +2024-11-23 04:09:55.999237: train_loss -0.8354 +2024-11-23 04:09:55.999460: val_loss -0.7518 +2024-11-23 04:09:55.999535: Pseudo dice [0.8633] +2024-11-23 04:09:55.999612: Epoch time: 20.03 s +2024-11-23 04:09:57.007190: +2024-11-23 04:09:57.007393: Epoch 7593 +2024-11-23 04:09:57.007607: Current learning rate: 0.00069 +2024-11-23 04:10:15.484377: train_loss -0.8356 +2024-11-23 04:10:15.484605: val_loss -0.7579 +2024-11-23 04:10:15.484683: Pseudo dice [0.8639] +2024-11-23 04:10:15.484764: Epoch time: 18.48 s +2024-11-23 04:10:16.415859: +2024-11-23 04:10:16.416099: Epoch 7594 +2024-11-23 04:10:16.416214: Current learning rate: 0.00068 +2024-11-23 04:10:36.015340: train_loss -0.8332 +2024-11-23 04:10:36.015598: val_loss -0.7714 +2024-11-23 04:10:36.015678: Pseudo dice [0.8526] +2024-11-23 04:10:36.015759: Epoch time: 19.6 s +2024-11-23 04:10:36.949050: +2024-11-23 04:10:36.950945: Epoch 7595 +2024-11-23 04:10:36.951073: Current learning rate: 0.00068 +2024-11-23 04:10:54.825196: train_loss -0.8355 +2024-11-23 04:10:54.825418: val_loss -0.7791 +2024-11-23 04:10:54.825492: Pseudo dice [0.8564] +2024-11-23 04:10:54.830554: Epoch time: 17.88 s +2024-11-23 04:10:55.770329: +2024-11-23 04:10:55.770546: Epoch 7596 +2024-11-23 04:10:55.770667: Current learning rate: 0.00068 +2024-11-23 04:11:14.375350: train_loss -0.828 +2024-11-23 04:11:14.375574: val_loss -0.7434 +2024-11-23 04:11:14.375648: Pseudo dice [0.8446] +2024-11-23 04:11:14.375727: Epoch time: 18.61 s +2024-11-23 04:11:15.373838: +2024-11-23 04:11:15.374076: Epoch 7597 +2024-11-23 04:11:15.374190: Current learning rate: 0.00068 +2024-11-23 04:11:34.487118: train_loss -0.8332 +2024-11-23 04:11:34.487345: val_loss -0.7542 +2024-11-23 04:11:34.487419: Pseudo dice [0.8571] +2024-11-23 04:11:34.487502: Epoch time: 19.11 s +2024-11-23 04:11:35.434779: +2024-11-23 04:11:35.434981: Epoch 7598 +2024-11-23 04:11:35.435099: Current learning rate: 0.00068 +2024-11-23 04:11:54.388967: train_loss -0.8288 +2024-11-23 04:11:54.389219: val_loss -0.7678 +2024-11-23 04:11:54.389298: Pseudo dice [0.8678] +2024-11-23 04:11:54.389376: Epoch time: 18.95 s +2024-11-23 04:11:55.315118: +2024-11-23 04:11:55.315317: Epoch 7599 +2024-11-23 04:11:55.315431: Current learning rate: 0.00068 +2024-11-23 04:12:14.298048: train_loss -0.8272 +2024-11-23 04:12:14.298273: val_loss -0.7354 +2024-11-23 04:12:14.298347: Pseudo dice [0.8692] +2024-11-23 04:12:14.298424: Epoch time: 18.98 s +2024-11-23 04:12:16.029866: +2024-11-23 04:12:16.030083: Epoch 7600 +2024-11-23 04:12:16.030191: Current learning rate: 0.00067 +2024-11-23 04:12:34.707455: train_loss -0.832 +2024-11-23 04:12:34.707723: val_loss -0.7826 +2024-11-23 04:12:34.707797: Pseudo dice [0.8648] +2024-11-23 04:12:34.707877: Epoch time: 18.68 s +2024-11-23 04:12:35.632119: +2024-11-23 04:12:35.632348: Epoch 7601 +2024-11-23 04:12:35.632462: Current learning rate: 0.00067 +2024-11-23 04:12:54.086978: train_loss -0.8259 +2024-11-23 04:12:54.087246: val_loss -0.7783 +2024-11-23 04:12:54.087395: Pseudo dice [0.857] +2024-11-23 04:12:54.087483: Epoch time: 18.46 s +2024-11-23 04:12:55.091545: +2024-11-23 04:12:55.091780: Epoch 7602 +2024-11-23 04:12:55.091894: Current learning rate: 0.00067 +2024-11-23 04:13:14.594788: train_loss -0.838 +2024-11-23 04:13:14.595025: val_loss -0.7779 +2024-11-23 04:13:14.595104: Pseudo dice [0.859] +2024-11-23 04:13:14.595183: Epoch time: 19.5 s +2024-11-23 04:13:15.570239: +2024-11-23 04:13:15.570493: Epoch 7603 +2024-11-23 04:13:15.570619: Current learning rate: 0.00067 +2024-11-23 04:13:34.316951: train_loss -0.844 +2024-11-23 04:13:34.317189: val_loss -0.7773 +2024-11-23 04:13:34.317281: Pseudo dice [0.8515] +2024-11-23 04:13:34.317361: Epoch time: 18.75 s +2024-11-23 04:13:35.244630: +2024-11-23 04:13:35.244846: Epoch 7604 +2024-11-23 04:13:35.244957: Current learning rate: 0.00067 +2024-11-23 04:13:53.992143: train_loss -0.8342 +2024-11-23 04:13:53.992421: val_loss -0.7667 +2024-11-23 04:13:53.992497: Pseudo dice [0.8746] +2024-11-23 04:13:53.992575: Epoch time: 18.75 s +2024-11-23 04:13:54.923302: +2024-11-23 04:13:54.923568: Epoch 7605 +2024-11-23 04:13:54.923693: Current learning rate: 0.00067 +2024-11-23 04:14:13.649265: train_loss -0.8252 +2024-11-23 04:14:13.649520: val_loss -0.7614 +2024-11-23 04:14:13.649598: Pseudo dice [0.8672] +2024-11-23 04:14:13.649679: Epoch time: 18.73 s +2024-11-23 04:14:14.575963: +2024-11-23 04:14:14.576212: Epoch 7606 +2024-11-23 04:14:14.576329: Current learning rate: 0.00067 +2024-11-23 04:14:31.965296: train_loss -0.8344 +2024-11-23 04:14:31.965514: val_loss -0.7608 +2024-11-23 04:14:31.965631: Pseudo dice [0.8667] +2024-11-23 04:14:31.965711: Epoch time: 17.39 s +2024-11-23 04:14:32.890841: +2024-11-23 04:14:32.891073: Epoch 7607 +2024-11-23 04:14:32.891183: Current learning rate: 0.00066 +2024-11-23 04:14:51.610878: train_loss -0.8381 +2024-11-23 04:14:51.611310: val_loss -0.7726 +2024-11-23 04:14:51.611402: Pseudo dice [0.8492] +2024-11-23 04:14:51.611479: Epoch time: 18.72 s +2024-11-23 04:14:52.534553: +2024-11-23 04:14:52.534781: Epoch 7608 +2024-11-23 04:14:52.534894: Current learning rate: 0.00066 +2024-11-23 04:15:10.989131: train_loss -0.8313 +2024-11-23 04:15:10.989354: val_loss -0.7397 +2024-11-23 04:15:10.989430: Pseudo dice [0.8503] +2024-11-23 04:15:10.989510: Epoch time: 18.46 s +2024-11-23 04:15:11.923088: +2024-11-23 04:15:11.923305: Epoch 7609 +2024-11-23 04:15:11.923419: Current learning rate: 0.00066 +2024-11-23 04:15:31.549226: train_loss -0.8338 +2024-11-23 04:15:31.549469: val_loss -0.7753 +2024-11-23 04:15:31.549542: Pseudo dice [0.8455] +2024-11-23 04:15:31.549623: Epoch time: 19.63 s +2024-11-23 04:15:32.472262: +2024-11-23 04:15:32.472458: Epoch 7610 +2024-11-23 04:15:32.472569: Current learning rate: 0.00066 +2024-11-23 04:15:52.041707: train_loss -0.8301 +2024-11-23 04:15:52.044382: val_loss -0.7529 +2024-11-23 04:15:52.044480: Pseudo dice [0.8344] +2024-11-23 04:15:52.044556: Epoch time: 19.57 s +2024-11-23 04:15:53.417445: +2024-11-23 04:15:53.417644: Epoch 7611 +2024-11-23 04:15:53.417755: Current learning rate: 0.00066 +2024-11-23 04:16:11.657578: train_loss -0.8388 +2024-11-23 04:16:11.659995: val_loss -0.7592 +2024-11-23 04:16:11.660089: Pseudo dice [0.8606] +2024-11-23 04:16:11.660168: Epoch time: 18.24 s +2024-11-23 04:16:12.637821: +2024-11-23 04:16:12.638053: Epoch 7612 +2024-11-23 04:16:12.638166: Current learning rate: 0.00066 +2024-11-23 04:16:32.084998: train_loss -0.8387 +2024-11-23 04:16:32.085259: val_loss -0.7598 +2024-11-23 04:16:32.085335: Pseudo dice [0.8589] +2024-11-23 04:16:32.085416: Epoch time: 19.45 s +2024-11-23 04:16:33.007778: +2024-11-23 04:16:33.007986: Epoch 7613 +2024-11-23 04:16:33.008104: Current learning rate: 0.00065 +2024-11-23 04:16:52.011512: train_loss -0.8307 +2024-11-23 04:16:52.011728: val_loss -0.7547 +2024-11-23 04:16:52.011803: Pseudo dice [0.8489] +2024-11-23 04:16:52.011875: Epoch time: 19.0 s +2024-11-23 04:16:52.936225: +2024-11-23 04:16:52.936449: Epoch 7614 +2024-11-23 04:16:52.936567: Current learning rate: 0.00065 +2024-11-23 04:17:11.403234: train_loss -0.832 +2024-11-23 04:17:11.403445: val_loss -0.7626 +2024-11-23 04:17:11.403522: Pseudo dice [0.8626] +2024-11-23 04:17:11.403597: Epoch time: 18.47 s +2024-11-23 04:17:12.368653: +2024-11-23 04:17:12.368864: Epoch 7615 +2024-11-23 04:17:12.368973: Current learning rate: 0.00065 +2024-11-23 04:17:31.346514: train_loss -0.8306 +2024-11-23 04:17:31.346732: val_loss -0.7442 +2024-11-23 04:17:31.346805: Pseudo dice [0.8474] +2024-11-23 04:17:31.349146: Epoch time: 18.98 s +2024-11-23 04:17:32.298331: +2024-11-23 04:17:32.298565: Epoch 7616 +2024-11-23 04:17:32.298688: Current learning rate: 0.00065 +2024-11-23 04:17:51.500262: train_loss -0.8378 +2024-11-23 04:17:51.500529: val_loss -0.7506 +2024-11-23 04:17:51.500605: Pseudo dice [0.851] +2024-11-23 04:17:51.500688: Epoch time: 19.2 s +2024-11-23 04:17:52.426938: +2024-11-23 04:17:52.427162: Epoch 7617 +2024-11-23 04:17:52.427275: Current learning rate: 0.00065 +2024-11-23 04:18:11.254091: train_loss -0.8385 +2024-11-23 04:18:11.254312: val_loss -0.7305 +2024-11-23 04:18:11.254385: Pseudo dice [0.8451] +2024-11-23 04:18:11.254462: Epoch time: 18.83 s +2024-11-23 04:18:12.200237: +2024-11-23 04:18:12.200465: Epoch 7618 +2024-11-23 04:18:12.200578: Current learning rate: 0.00065 +2024-11-23 04:18:29.609656: train_loss -0.8387 +2024-11-23 04:18:29.609870: val_loss -0.7563 +2024-11-23 04:18:29.609946: Pseudo dice [0.8619] +2024-11-23 04:18:29.610104: Epoch time: 17.41 s +2024-11-23 04:18:30.540649: +2024-11-23 04:18:30.540881: Epoch 7619 +2024-11-23 04:18:30.541006: Current learning rate: 0.00065 +2024-11-23 04:18:49.151533: train_loss -0.8291 +2024-11-23 04:18:49.151767: val_loss -0.745 +2024-11-23 04:18:49.151840: Pseudo dice [0.849] +2024-11-23 04:18:49.151917: Epoch time: 18.61 s +2024-11-23 04:18:50.080175: +2024-11-23 04:18:50.080389: Epoch 7620 +2024-11-23 04:18:50.080499: Current learning rate: 0.00064 +2024-11-23 04:19:08.570044: train_loss -0.8388 +2024-11-23 04:19:08.570289: val_loss -0.7568 +2024-11-23 04:19:08.570366: Pseudo dice [0.8478] +2024-11-23 04:19:08.570465: Epoch time: 18.49 s +2024-11-23 04:19:09.502916: +2024-11-23 04:19:09.503141: Epoch 7621 +2024-11-23 04:19:09.503253: Current learning rate: 0.00064 +2024-11-23 04:19:27.431643: train_loss -0.8352 +2024-11-23 04:19:27.431949: val_loss -0.7508 +2024-11-23 04:19:27.432034: Pseudo dice [0.8506] +2024-11-23 04:19:27.432111: Epoch time: 17.93 s +2024-11-23 04:19:28.737817: +2024-11-23 04:19:28.738026: Epoch 7622 +2024-11-23 04:19:28.738164: Current learning rate: 0.00064 +2024-11-23 04:19:47.703701: train_loss -0.8363 +2024-11-23 04:19:47.704715: val_loss -0.7462 +2024-11-23 04:19:47.704875: Pseudo dice [0.8597] +2024-11-23 04:19:47.704958: Epoch time: 18.97 s +2024-11-23 04:19:48.655729: +2024-11-23 04:19:48.656023: Epoch 7623 +2024-11-23 04:19:48.656137: Current learning rate: 0.00064 +2024-11-23 04:20:08.449759: train_loss -0.8327 +2024-11-23 04:20:08.450068: val_loss -0.7664 +2024-11-23 04:20:08.450151: Pseudo dice [0.8656] +2024-11-23 04:20:08.450237: Epoch time: 19.79 s +2024-11-23 04:20:09.499987: +2024-11-23 04:20:09.500221: Epoch 7624 +2024-11-23 04:20:09.500333: Current learning rate: 0.00064 +2024-11-23 04:20:27.822735: train_loss -0.8399 +2024-11-23 04:20:27.822982: val_loss -0.7442 +2024-11-23 04:20:27.823061: Pseudo dice [0.8574] +2024-11-23 04:20:27.823300: Epoch time: 18.32 s +2024-11-23 04:20:28.756212: +2024-11-23 04:20:28.756456: Epoch 7625 +2024-11-23 04:20:28.756575: Current learning rate: 0.00064 +2024-11-23 04:20:47.142755: train_loss -0.8356 +2024-11-23 04:20:47.142998: val_loss -0.7691 +2024-11-23 04:20:47.143094: Pseudo dice [0.8596] +2024-11-23 04:20:47.143173: Epoch time: 18.39 s +2024-11-23 04:20:48.255012: +2024-11-23 04:20:48.255283: Epoch 7626 +2024-11-23 04:20:48.255399: Current learning rate: 0.00064 +2024-11-23 04:21:06.228787: train_loss -0.832 +2024-11-23 04:21:06.229025: val_loss -0.7636 +2024-11-23 04:21:06.229104: Pseudo dice [0.8644] +2024-11-23 04:21:06.229182: Epoch time: 17.97 s +2024-11-23 04:21:07.164227: +2024-11-23 04:21:07.164503: Epoch 7627 +2024-11-23 04:21:07.164616: Current learning rate: 0.00063 +2024-11-23 04:21:25.021338: train_loss -0.8363 +2024-11-23 04:21:25.021585: val_loss -0.7511 +2024-11-23 04:21:25.021660: Pseudo dice [0.8617] +2024-11-23 04:21:25.021746: Epoch time: 17.86 s +2024-11-23 04:21:25.955259: +2024-11-23 04:21:25.955487: Epoch 7628 +2024-11-23 04:21:25.955603: Current learning rate: 0.00063 +2024-11-23 04:21:45.609889: train_loss -0.8355 +2024-11-23 04:21:45.610122: val_loss -0.7647 +2024-11-23 04:21:45.610224: Pseudo dice [0.8514] +2024-11-23 04:21:45.610303: Epoch time: 19.66 s +2024-11-23 04:21:46.537876: +2024-11-23 04:21:46.538100: Epoch 7629 +2024-11-23 04:21:46.538214: Current learning rate: 0.00063 +2024-11-23 04:22:04.870028: train_loss -0.8329 +2024-11-23 04:22:04.870242: val_loss -0.7834 +2024-11-23 04:22:04.870316: Pseudo dice [0.8562] +2024-11-23 04:22:04.870397: Epoch time: 18.33 s +2024-11-23 04:22:05.801549: +2024-11-23 04:22:05.801816: Epoch 7630 +2024-11-23 04:22:05.801933: Current learning rate: 0.00063 +2024-11-23 04:22:24.047144: train_loss -0.8308 +2024-11-23 04:22:24.047353: val_loss -0.7581 +2024-11-23 04:22:24.047426: Pseudo dice [0.8699] +2024-11-23 04:22:24.047502: Epoch time: 18.25 s +2024-11-23 04:22:24.982165: +2024-11-23 04:22:24.982483: Epoch 7631 +2024-11-23 04:22:24.982604: Current learning rate: 0.00063 +2024-11-23 04:22:42.481961: train_loss -0.8387 +2024-11-23 04:22:42.482243: val_loss -0.7664 +2024-11-23 04:22:42.482317: Pseudo dice [0.8483] +2024-11-23 04:22:42.482398: Epoch time: 17.5 s +2024-11-23 04:22:43.430399: +2024-11-23 04:22:43.430622: Epoch 7632 +2024-11-23 04:22:43.430740: Current learning rate: 0.00063 +2024-11-23 04:23:01.977003: train_loss -0.8387 +2024-11-23 04:23:01.977235: val_loss -0.7479 +2024-11-23 04:23:01.977313: Pseudo dice [0.8439] +2024-11-23 04:23:01.977389: Epoch time: 18.55 s +2024-11-23 04:23:02.916346: +2024-11-23 04:23:02.916765: Epoch 7633 +2024-11-23 04:23:02.916899: Current learning rate: 0.00062 +2024-11-23 04:23:21.136219: train_loss -0.8342 +2024-11-23 04:23:21.136443: val_loss -0.7519 +2024-11-23 04:23:21.136519: Pseudo dice [0.8465] +2024-11-23 04:23:21.136597: Epoch time: 18.22 s +2024-11-23 04:23:22.466360: +2024-11-23 04:23:22.466605: Epoch 7634 +2024-11-23 04:23:22.466718: Current learning rate: 0.00062 +2024-11-23 04:23:40.745353: train_loss -0.8322 +2024-11-23 04:23:40.745607: val_loss -0.754 +2024-11-23 04:23:40.745683: Pseudo dice [0.8422] +2024-11-23 04:23:40.745767: Epoch time: 18.28 s +2024-11-23 04:23:41.680614: +2024-11-23 04:23:41.680828: Epoch 7635 +2024-11-23 04:23:41.680938: Current learning rate: 0.00062 +2024-11-23 04:24:00.306022: train_loss -0.8346 +2024-11-23 04:24:00.306242: val_loss -0.751 +2024-11-23 04:24:00.306326: Pseudo dice [0.8416] +2024-11-23 04:24:00.308559: Epoch time: 18.63 s +2024-11-23 04:24:01.240505: +2024-11-23 04:24:01.240716: Epoch 7636 +2024-11-23 04:24:01.240827: Current learning rate: 0.00062 +2024-11-23 04:24:20.205113: train_loss -0.8394 +2024-11-23 04:24:20.205321: val_loss -0.7312 +2024-11-23 04:24:20.205394: Pseudo dice [0.8519] +2024-11-23 04:24:20.205468: Epoch time: 18.97 s +2024-11-23 04:24:21.171726: +2024-11-23 04:24:21.171948: Epoch 7637 +2024-11-23 04:24:21.172073: Current learning rate: 0.00062 +2024-11-23 04:24:38.623508: train_loss -0.842 +2024-11-23 04:24:38.623732: val_loss -0.7399 +2024-11-23 04:24:38.623809: Pseudo dice [0.8584] +2024-11-23 04:24:38.623892: Epoch time: 17.45 s +2024-11-23 04:24:39.557283: +2024-11-23 04:24:39.557502: Epoch 7638 +2024-11-23 04:24:39.557626: Current learning rate: 0.00062 +2024-11-23 04:24:57.264259: train_loss -0.8372 +2024-11-23 04:24:57.264521: val_loss -0.7622 +2024-11-23 04:24:57.264598: Pseudo dice [0.8487] +2024-11-23 04:24:57.264678: Epoch time: 17.71 s +2024-11-23 04:24:58.299156: +2024-11-23 04:24:58.299374: Epoch 7639 +2024-11-23 04:24:58.299487: Current learning rate: 0.00062 +2024-11-23 04:25:17.484681: train_loss -0.8354 +2024-11-23 04:25:17.484903: val_loss -0.7676 +2024-11-23 04:25:17.484976: Pseudo dice [0.8507] +2024-11-23 04:25:17.485057: Epoch time: 19.19 s +2024-11-23 04:25:18.412731: +2024-11-23 04:25:18.412950: Epoch 7640 +2024-11-23 04:25:18.413075: Current learning rate: 0.00061 +2024-11-23 04:25:38.046549: train_loss -0.8277 +2024-11-23 04:25:38.046824: val_loss -0.7563 +2024-11-23 04:25:38.046906: Pseudo dice [0.8632] +2024-11-23 04:25:38.046982: Epoch time: 19.63 s +2024-11-23 04:25:39.013747: +2024-11-23 04:25:39.013969: Epoch 7641 +2024-11-23 04:25:39.014089: Current learning rate: 0.00061 +2024-11-23 04:25:57.804896: train_loss -0.8364 +2024-11-23 04:25:57.805142: val_loss -0.7282 +2024-11-23 04:25:57.805237: Pseudo dice [0.8572] +2024-11-23 04:25:57.805329: Epoch time: 18.79 s +2024-11-23 04:25:58.763955: +2024-11-23 04:25:58.764304: Epoch 7642 +2024-11-23 04:25:58.764426: Current learning rate: 0.00061 +2024-11-23 04:26:18.078441: train_loss -0.8384 +2024-11-23 04:26:18.078742: val_loss -0.722 +2024-11-23 04:26:18.078819: Pseudo dice [0.8432] +2024-11-23 04:26:18.078900: Epoch time: 19.32 s +2024-11-23 04:26:19.012193: +2024-11-23 04:26:19.012445: Epoch 7643 +2024-11-23 04:26:19.012554: Current learning rate: 0.00061 +2024-11-23 04:26:38.044293: train_loss -0.8284 +2024-11-23 04:26:38.044513: val_loss -0.7643 +2024-11-23 04:26:38.044589: Pseudo dice [0.8554] +2024-11-23 04:26:38.044665: Epoch time: 19.03 s +2024-11-23 04:26:38.977776: +2024-11-23 04:26:38.978003: Epoch 7644 +2024-11-23 04:26:38.978117: Current learning rate: 0.00061 +2024-11-23 04:26:57.812730: train_loss -0.8331 +2024-11-23 04:26:57.812944: val_loss -0.7479 +2024-11-23 04:26:57.813046: Pseudo dice [0.8428] +2024-11-23 04:26:57.813122: Epoch time: 18.84 s +2024-11-23 04:26:59.147662: +2024-11-23 04:26:59.147909: Epoch 7645 +2024-11-23 04:26:59.148031: Current learning rate: 0.00061 +2024-11-23 04:27:17.866599: train_loss -0.8392 +2024-11-23 04:27:17.869042: val_loss -0.7318 +2024-11-23 04:27:17.869175: Pseudo dice [0.8697] +2024-11-23 04:27:17.869266: Epoch time: 18.72 s +2024-11-23 04:27:18.962440: +2024-11-23 04:27:18.962675: Epoch 7646 +2024-11-23 04:27:18.962794: Current learning rate: 0.0006 +2024-11-23 04:27:37.350053: train_loss -0.8396 +2024-11-23 04:27:37.350312: val_loss -0.7727 +2024-11-23 04:27:37.350390: Pseudo dice [0.8442] +2024-11-23 04:27:37.350469: Epoch time: 18.39 s +2024-11-23 04:27:38.287861: +2024-11-23 04:27:38.288072: Epoch 7647 +2024-11-23 04:27:38.288182: Current learning rate: 0.0006 +2024-11-23 04:27:57.395744: train_loss -0.8374 +2024-11-23 04:27:57.395968: val_loss -0.7702 +2024-11-23 04:27:57.396051: Pseudo dice [0.8483] +2024-11-23 04:27:57.396128: Epoch time: 19.11 s +2024-11-23 04:27:58.486778: +2024-11-23 04:27:58.486986: Epoch 7648 +2024-11-23 04:27:58.487102: Current learning rate: 0.0006 +2024-11-23 04:28:16.632541: train_loss -0.8379 +2024-11-23 04:28:16.637954: val_loss -0.7572 +2024-11-23 04:28:16.638077: Pseudo dice [0.8554] +2024-11-23 04:28:16.638163: Epoch time: 18.15 s +2024-11-23 04:28:17.634920: +2024-11-23 04:28:17.635163: Epoch 7649 +2024-11-23 04:28:17.635271: Current learning rate: 0.0006 +2024-11-23 04:28:35.606184: train_loss -0.8422 +2024-11-23 04:28:35.606415: val_loss -0.7605 +2024-11-23 04:28:35.606489: Pseudo dice [0.8696] +2024-11-23 04:28:35.606565: Epoch time: 17.97 s +2024-11-23 04:28:36.891385: +2024-11-23 04:28:36.891601: Epoch 7650 +2024-11-23 04:28:36.891716: Current learning rate: 0.0006 +2024-11-23 04:28:54.880771: train_loss -0.8359 +2024-11-23 04:28:54.880987: val_loss -0.7644 +2024-11-23 04:28:54.881068: Pseudo dice [0.854] +2024-11-23 04:28:54.881146: Epoch time: 17.99 s +2024-11-23 04:28:55.821498: +2024-11-23 04:28:55.821741: Epoch 7651 +2024-11-23 04:28:55.821859: Current learning rate: 0.0006 +2024-11-23 04:29:14.410064: train_loss -0.8374 +2024-11-23 04:29:14.410360: val_loss -0.7513 +2024-11-23 04:29:14.410444: Pseudo dice [0.8537] +2024-11-23 04:29:14.410520: Epoch time: 18.59 s +2024-11-23 04:29:15.347709: +2024-11-23 04:29:15.347933: Epoch 7652 +2024-11-23 04:29:15.348053: Current learning rate: 0.0006 +2024-11-23 04:29:34.112560: train_loss -0.8393 +2024-11-23 04:29:34.112815: val_loss -0.7803 +2024-11-23 04:29:34.112893: Pseudo dice [0.8607] +2024-11-23 04:29:34.112979: Epoch time: 18.77 s +2024-11-23 04:29:35.052879: +2024-11-23 04:29:35.053105: Epoch 7653 +2024-11-23 04:29:35.053220: Current learning rate: 0.00059 +2024-11-23 04:29:53.991199: train_loss -0.8321 +2024-11-23 04:29:53.991412: val_loss -0.7612 +2024-11-23 04:29:53.991487: Pseudo dice [0.828] +2024-11-23 04:29:53.991565: Epoch time: 18.94 s +2024-11-23 04:29:54.929732: +2024-11-23 04:29:54.929954: Epoch 7654 +2024-11-23 04:29:54.930068: Current learning rate: 0.00059 +2024-11-23 04:30:14.595282: train_loss -0.8336 +2024-11-23 04:30:14.595503: val_loss -0.7443 +2024-11-23 04:30:14.595577: Pseudo dice [0.852] +2024-11-23 04:30:14.595652: Epoch time: 19.67 s +2024-11-23 04:30:15.638199: +2024-11-23 04:30:15.638400: Epoch 7655 +2024-11-23 04:30:15.638508: Current learning rate: 0.00059 +2024-11-23 04:30:33.486905: train_loss -0.8362 +2024-11-23 04:30:33.487142: val_loss -0.7655 +2024-11-23 04:30:33.487225: Pseudo dice [0.8553] +2024-11-23 04:30:33.487302: Epoch time: 17.85 s +2024-11-23 04:30:34.904626: +2024-11-23 04:30:34.904829: Epoch 7656 +2024-11-23 04:30:34.904939: Current learning rate: 0.00059 +2024-11-23 04:30:52.976266: train_loss -0.8379 +2024-11-23 04:30:52.976539: val_loss -0.7515 +2024-11-23 04:30:52.976616: Pseudo dice [0.865] +2024-11-23 04:30:52.976700: Epoch time: 18.07 s +2024-11-23 04:30:53.909100: +2024-11-23 04:30:53.909416: Epoch 7657 +2024-11-23 04:30:53.909532: Current learning rate: 0.00059 +2024-11-23 04:31:12.444560: train_loss -0.835 +2024-11-23 04:31:12.444781: val_loss -0.7742 +2024-11-23 04:31:12.444860: Pseudo dice [0.8353] +2024-11-23 04:31:12.444937: Epoch time: 18.54 s +2024-11-23 04:31:13.384752: +2024-11-23 04:31:13.385020: Epoch 7658 +2024-11-23 04:31:13.385134: Current learning rate: 0.00059 +2024-11-23 04:31:31.802763: train_loss -0.8299 +2024-11-23 04:31:31.803047: val_loss -0.7451 +2024-11-23 04:31:31.803130: Pseudo dice [0.8354] +2024-11-23 04:31:31.803215: Epoch time: 18.42 s +2024-11-23 04:31:32.744322: +2024-11-23 04:31:32.744546: Epoch 7659 +2024-11-23 04:31:32.744655: Current learning rate: 0.00058 +2024-11-23 04:31:50.928355: train_loss -0.8376 +2024-11-23 04:31:50.929819: val_loss -0.7581 +2024-11-23 04:31:50.929927: Pseudo dice [0.8592] +2024-11-23 04:31:50.930031: Epoch time: 18.18 s +2024-11-23 04:31:51.871772: +2024-11-23 04:31:51.871989: Epoch 7660 +2024-11-23 04:31:51.872111: Current learning rate: 0.00058 +2024-11-23 04:32:10.213893: train_loss -0.8354 +2024-11-23 04:32:10.214138: val_loss -0.7522 +2024-11-23 04:32:10.214214: Pseudo dice [0.8623] +2024-11-23 04:32:10.214293: Epoch time: 18.34 s +2024-11-23 04:32:11.195560: +2024-11-23 04:32:11.195776: Epoch 7661 +2024-11-23 04:32:11.195892: Current learning rate: 0.00058 +2024-11-23 04:32:28.523406: train_loss -0.8427 +2024-11-23 04:32:28.523642: val_loss -0.7386 +2024-11-23 04:32:28.523722: Pseudo dice [0.8378] +2024-11-23 04:32:28.523803: Epoch time: 17.33 s +2024-11-23 04:32:29.460392: +2024-11-23 04:32:29.460607: Epoch 7662 +2024-11-23 04:32:29.460721: Current learning rate: 0.00058 +2024-11-23 04:32:47.523422: train_loss -0.8365 +2024-11-23 04:32:47.523642: val_loss -0.753 +2024-11-23 04:32:47.523717: Pseudo dice [0.8539] +2024-11-23 04:32:47.523792: Epoch time: 18.06 s +2024-11-23 04:32:48.455837: +2024-11-23 04:32:48.456064: Epoch 7663 +2024-11-23 04:32:48.456182: Current learning rate: 0.00058 +2024-11-23 04:33:07.303264: train_loss -0.8294 +2024-11-23 04:33:07.303512: val_loss -0.7787 +2024-11-23 04:33:07.303589: Pseudo dice [0.8581] +2024-11-23 04:33:07.303673: Epoch time: 18.85 s +2024-11-23 04:33:08.247224: +2024-11-23 04:33:08.247438: Epoch 7664 +2024-11-23 04:33:08.247552: Current learning rate: 0.00058 +2024-11-23 04:33:27.234968: train_loss -0.838 +2024-11-23 04:33:27.235203: val_loss -0.7629 +2024-11-23 04:33:27.235280: Pseudo dice [0.8487] +2024-11-23 04:33:27.235355: Epoch time: 18.99 s +2024-11-23 04:33:28.171596: +2024-11-23 04:33:28.171811: Epoch 7665 +2024-11-23 04:33:28.171928: Current learning rate: 0.00058 +2024-11-23 04:33:46.911263: train_loss -0.8394 +2024-11-23 04:33:46.911480: val_loss -0.7352 +2024-11-23 04:33:46.911559: Pseudo dice [0.8533] +2024-11-23 04:33:46.911633: Epoch time: 18.74 s +2024-11-23 04:33:47.968629: +2024-11-23 04:33:47.968834: Epoch 7666 +2024-11-23 04:33:47.968948: Current learning rate: 0.00057 +2024-11-23 04:34:06.316132: train_loss -0.8374 +2024-11-23 04:34:06.316359: val_loss -0.7812 +2024-11-23 04:34:06.316439: Pseudo dice [0.8454] +2024-11-23 04:34:06.316518: Epoch time: 18.35 s +2024-11-23 04:34:07.354985: +2024-11-23 04:34:07.355215: Epoch 7667 +2024-11-23 04:34:07.355333: Current learning rate: 0.00057 +2024-11-23 04:34:26.800167: train_loss -0.839 +2024-11-23 04:34:26.800381: val_loss -0.7605 +2024-11-23 04:34:26.802669: Pseudo dice [0.8739] +2024-11-23 04:34:26.802770: Epoch time: 19.45 s +2024-11-23 04:34:28.267476: +2024-11-23 04:34:28.267692: Epoch 7668 +2024-11-23 04:34:28.267800: Current learning rate: 0.00057 +2024-11-23 04:34:46.796966: train_loss -0.831 +2024-11-23 04:34:46.797205: val_loss -0.7715 +2024-11-23 04:34:46.797281: Pseudo dice [0.8691] +2024-11-23 04:34:46.797356: Epoch time: 18.53 s +2024-11-23 04:34:47.735383: +2024-11-23 04:34:47.735666: Epoch 7669 +2024-11-23 04:34:47.735779: Current learning rate: 0.00057 +2024-11-23 04:35:06.139915: train_loss -0.8381 +2024-11-23 04:35:06.140139: val_loss -0.7635 +2024-11-23 04:35:06.140216: Pseudo dice [0.8449] +2024-11-23 04:35:06.140290: Epoch time: 18.41 s +2024-11-23 04:35:07.073867: +2024-11-23 04:35:07.074112: Epoch 7670 +2024-11-23 04:35:07.074225: Current learning rate: 0.00057 +2024-11-23 04:35:25.551411: train_loss -0.8356 +2024-11-23 04:35:25.551677: val_loss -0.7767 +2024-11-23 04:35:25.551752: Pseudo dice [0.8534] +2024-11-23 04:35:25.551837: Epoch time: 18.48 s +2024-11-23 04:35:26.488196: +2024-11-23 04:35:26.488433: Epoch 7671 +2024-11-23 04:35:26.488552: Current learning rate: 0.00057 +2024-11-23 04:35:45.508202: train_loss -0.8377 +2024-11-23 04:35:45.508425: val_loss -0.7586 +2024-11-23 04:35:45.508502: Pseudo dice [0.8611] +2024-11-23 04:35:45.508581: Epoch time: 19.02 s +2024-11-23 04:35:46.442520: +2024-11-23 04:35:46.442726: Epoch 7672 +2024-11-23 04:35:46.442838: Current learning rate: 0.00056 +2024-11-23 04:36:04.813406: train_loss -0.8411 +2024-11-23 04:36:04.813622: val_loss -0.7582 +2024-11-23 04:36:04.813698: Pseudo dice [0.8555] +2024-11-23 04:36:04.813777: Epoch time: 18.37 s +2024-11-23 04:36:05.776798: +2024-11-23 04:36:05.777026: Epoch 7673 +2024-11-23 04:36:05.777146: Current learning rate: 0.00056 +2024-11-23 04:36:25.308085: train_loss -0.8377 +2024-11-23 04:36:25.308315: val_loss -0.7736 +2024-11-23 04:36:25.308387: Pseudo dice [0.8569] +2024-11-23 04:36:25.308463: Epoch time: 19.53 s +2024-11-23 04:36:26.243035: +2024-11-23 04:36:26.243262: Epoch 7674 +2024-11-23 04:36:26.243387: Current learning rate: 0.00056 +2024-11-23 04:36:45.450155: train_loss -0.8334 +2024-11-23 04:36:45.450407: val_loss -0.7762 +2024-11-23 04:36:45.450487: Pseudo dice [0.8537] +2024-11-23 04:36:45.450571: Epoch time: 19.21 s +2024-11-23 04:36:46.396424: +2024-11-23 04:36:46.396636: Epoch 7675 +2024-11-23 04:36:46.396746: Current learning rate: 0.00056 +2024-11-23 04:37:04.922781: train_loss -0.8411 +2024-11-23 04:37:04.923000: val_loss -0.7702 +2024-11-23 04:37:04.923081: Pseudo dice [0.8256] +2024-11-23 04:37:04.923159: Epoch time: 18.53 s +2024-11-23 04:37:05.856938: +2024-11-23 04:37:05.857152: Epoch 7676 +2024-11-23 04:37:05.857264: Current learning rate: 0.00056 +2024-11-23 04:37:24.137676: train_loss -0.8395 +2024-11-23 04:37:24.137891: val_loss -0.7695 +2024-11-23 04:37:24.137965: Pseudo dice [0.8638] +2024-11-23 04:37:24.138052: Epoch time: 18.28 s +2024-11-23 04:37:25.072313: +2024-11-23 04:37:25.072522: Epoch 7677 +2024-11-23 04:37:25.072631: Current learning rate: 0.00056 +2024-11-23 04:37:44.047334: train_loss -0.837 +2024-11-23 04:37:44.047550: val_loss -0.7775 +2024-11-23 04:37:44.047625: Pseudo dice [0.8683] +2024-11-23 04:37:44.047704: Epoch time: 18.98 s +2024-11-23 04:37:44.989002: +2024-11-23 04:37:44.989306: Epoch 7678 +2024-11-23 04:37:44.989433: Current learning rate: 0.00055 +2024-11-23 04:38:04.196309: train_loss -0.8373 +2024-11-23 04:38:04.196605: val_loss -0.7469 +2024-11-23 04:38:04.196682: Pseudo dice [0.8763] +2024-11-23 04:38:04.196764: Epoch time: 19.21 s +2024-11-23 04:38:05.539953: +2024-11-23 04:38:05.540209: Epoch 7679 +2024-11-23 04:38:05.540328: Current learning rate: 0.00055 +2024-11-23 04:38:24.329322: train_loss -0.8372 +2024-11-23 04:38:24.329580: val_loss -0.7589 +2024-11-23 04:38:24.329661: Pseudo dice [0.8493] +2024-11-23 04:38:24.329743: Epoch time: 18.79 s +2024-11-23 04:38:25.264457: +2024-11-23 04:38:25.264656: Epoch 7680 +2024-11-23 04:38:25.264766: Current learning rate: 0.00055 +2024-11-23 04:38:44.471442: train_loss -0.833 +2024-11-23 04:38:44.471659: val_loss -0.75 +2024-11-23 04:38:44.471734: Pseudo dice [0.8565] +2024-11-23 04:38:44.471809: Epoch time: 19.21 s +2024-11-23 04:38:45.408552: +2024-11-23 04:38:45.408766: Epoch 7681 +2024-11-23 04:38:45.408876: Current learning rate: 0.00055 +2024-11-23 04:39:03.436055: train_loss -0.8372 +2024-11-23 04:39:03.436318: val_loss -0.7652 +2024-11-23 04:39:03.436399: Pseudo dice [0.8625] +2024-11-23 04:39:03.436487: Epoch time: 18.03 s +2024-11-23 04:39:04.384477: +2024-11-23 04:39:04.384688: Epoch 7682 +2024-11-23 04:39:04.384798: Current learning rate: 0.00055 +2024-11-23 04:39:21.409766: train_loss -0.8413 +2024-11-23 04:39:21.409978: val_loss -0.7704 +2024-11-23 04:39:21.410066: Pseudo dice [0.8611] +2024-11-23 04:39:21.410140: Epoch time: 17.03 s +2024-11-23 04:39:22.393393: +2024-11-23 04:39:22.393634: Epoch 7683 +2024-11-23 04:39:22.393749: Current learning rate: 0.00055 +2024-11-23 04:39:40.930177: train_loss -0.8354 +2024-11-23 04:39:40.930406: val_loss -0.7705 +2024-11-23 04:39:40.930480: Pseudo dice [0.8722] +2024-11-23 04:39:40.930557: Epoch time: 18.54 s +2024-11-23 04:39:41.912286: +2024-11-23 04:39:41.912579: Epoch 7684 +2024-11-23 04:39:41.912696: Current learning rate: 0.00055 +2024-11-23 04:40:00.521004: train_loss -0.8316 +2024-11-23 04:40:00.521267: val_loss -0.7443 +2024-11-23 04:40:00.521345: Pseudo dice [0.8334] +2024-11-23 04:40:00.521422: Epoch time: 18.61 s +2024-11-23 04:40:01.463060: +2024-11-23 04:40:01.463287: Epoch 7685 +2024-11-23 04:40:01.463556: Current learning rate: 0.00054 +2024-11-23 04:40:20.830326: train_loss -0.8354 +2024-11-23 04:40:20.830552: val_loss -0.7346 +2024-11-23 04:40:20.830626: Pseudo dice [0.8345] +2024-11-23 04:40:20.830708: Epoch time: 19.37 s +2024-11-23 04:40:21.763031: +2024-11-23 04:40:21.763277: Epoch 7686 +2024-11-23 04:40:21.763398: Current learning rate: 0.00054 +2024-11-23 04:40:39.366010: train_loss -0.8369 +2024-11-23 04:40:39.366264: val_loss -0.7764 +2024-11-23 04:40:39.366343: Pseudo dice [0.852] +2024-11-23 04:40:39.366425: Epoch time: 17.6 s +2024-11-23 04:40:40.459696: +2024-11-23 04:40:40.459931: Epoch 7687 +2024-11-23 04:40:40.460054: Current learning rate: 0.00054 +2024-11-23 04:40:59.637444: train_loss -0.8333 +2024-11-23 04:40:59.637642: val_loss -0.7817 +2024-11-23 04:40:59.637713: Pseudo dice [0.8601] +2024-11-23 04:40:59.637787: Epoch time: 19.18 s +2024-11-23 04:41:00.910523: +2024-11-23 04:41:00.910940: Epoch 7688 +2024-11-23 04:41:00.911060: Current learning rate: 0.00054 +2024-11-23 04:41:18.959761: train_loss -0.8354 +2024-11-23 04:41:18.961381: val_loss -0.7918 +2024-11-23 04:41:18.961514: Pseudo dice [0.8594] +2024-11-23 04:41:18.961596: Epoch time: 18.05 s +2024-11-23 04:41:19.897283: +2024-11-23 04:41:19.897487: Epoch 7689 +2024-11-23 04:41:19.897600: Current learning rate: 0.00054 +2024-11-23 04:41:38.699469: train_loss -0.8308 +2024-11-23 04:41:38.699733: val_loss -0.7685 +2024-11-23 04:41:38.699810: Pseudo dice [0.8508] +2024-11-23 04:41:38.699896: Epoch time: 18.8 s +2024-11-23 04:41:39.749156: +2024-11-23 04:41:39.749369: Epoch 7690 +2024-11-23 04:41:39.749484: Current learning rate: 0.00054 +2024-11-23 04:41:57.685516: train_loss -0.8396 +2024-11-23 04:41:57.685728: val_loss -0.7564 +2024-11-23 04:41:57.685804: Pseudo dice [0.8496] +2024-11-23 04:41:57.685880: Epoch time: 17.94 s +2024-11-23 04:41:59.025921: +2024-11-23 04:41:59.026134: Epoch 7691 +2024-11-23 04:41:59.026249: Current learning rate: 0.00053 +2024-11-23 04:42:17.051836: train_loss -0.8393 +2024-11-23 04:42:17.052073: val_loss -0.7669 +2024-11-23 04:42:17.052146: Pseudo dice [0.8682] +2024-11-23 04:42:17.052223: Epoch time: 18.03 s +2024-11-23 04:42:17.994071: +2024-11-23 04:42:17.994292: Epoch 7692 +2024-11-23 04:42:17.994404: Current learning rate: 0.00053 +2024-11-23 04:42:37.740517: train_loss -0.8377 +2024-11-23 04:42:37.740816: val_loss -0.7654 +2024-11-23 04:42:37.740890: Pseudo dice [0.8647] +2024-11-23 04:42:37.741025: Epoch time: 19.75 s +2024-11-23 04:42:38.681053: +2024-11-23 04:42:38.681269: Epoch 7693 +2024-11-23 04:42:38.681379: Current learning rate: 0.00053 +2024-11-23 04:42:57.179359: train_loss -0.8354 +2024-11-23 04:42:57.179577: val_loss -0.7708 +2024-11-23 04:42:57.179651: Pseudo dice [0.874] +2024-11-23 04:42:57.179727: Epoch time: 18.5 s +2024-11-23 04:42:58.248607: +2024-11-23 04:42:58.248824: Epoch 7694 +2024-11-23 04:42:58.248939: Current learning rate: 0.00053 +2024-11-23 04:43:18.335866: train_loss -0.8332 +2024-11-23 04:43:18.336094: val_loss -0.7121 +2024-11-23 04:43:18.336191: Pseudo dice [0.8419] +2024-11-23 04:43:18.336271: Epoch time: 20.09 s +2024-11-23 04:43:19.282696: +2024-11-23 04:43:19.282924: Epoch 7695 +2024-11-23 04:43:19.283049: Current learning rate: 0.00053 +2024-11-23 04:43:37.632516: train_loss -0.8381 +2024-11-23 04:43:37.632737: val_loss -0.7561 +2024-11-23 04:43:37.632822: Pseudo dice [0.8637] +2024-11-23 04:43:37.632900: Epoch time: 18.35 s +2024-11-23 04:43:38.569704: +2024-11-23 04:43:38.570038: Epoch 7696 +2024-11-23 04:43:38.570164: Current learning rate: 0.00053 +2024-11-23 04:43:57.379022: train_loss -0.8382 +2024-11-23 04:43:57.379275: val_loss -0.7449 +2024-11-23 04:43:57.381231: Pseudo dice [0.8607] +2024-11-23 04:43:57.381333: Epoch time: 18.81 s +2024-11-23 04:43:58.331452: +2024-11-23 04:43:58.331739: Epoch 7697 +2024-11-23 04:43:58.331851: Current learning rate: 0.00053 +2024-11-23 04:44:16.842587: train_loss -0.8402 +2024-11-23 04:44:16.842807: val_loss -0.7482 +2024-11-23 04:44:16.842928: Pseudo dice [0.8177] +2024-11-23 04:44:16.843012: Epoch time: 18.51 s +2024-11-23 04:44:17.784855: +2024-11-23 04:44:17.785069: Epoch 7698 +2024-11-23 04:44:17.785183: Current learning rate: 0.00052 +2024-11-23 04:44:35.894569: train_loss -0.84 +2024-11-23 04:44:35.894811: val_loss -0.7794 +2024-11-23 04:44:35.894887: Pseudo dice [0.8555] +2024-11-23 04:44:35.894965: Epoch time: 18.11 s +2024-11-23 04:44:36.911569: +2024-11-23 04:44:36.911807: Epoch 7699 +2024-11-23 04:44:36.911926: Current learning rate: 0.00052 +2024-11-23 04:44:56.587149: train_loss -0.8265 +2024-11-23 04:44:56.587397: val_loss -0.7695 +2024-11-23 04:44:56.587479: Pseudo dice [0.8489] +2024-11-23 04:44:56.587559: Epoch time: 19.68 s +2024-11-23 04:44:57.887314: +2024-11-23 04:44:57.887540: Epoch 7700 +2024-11-23 04:44:57.887654: Current learning rate: 0.00052 +2024-11-23 04:45:16.609278: train_loss -0.8307 +2024-11-23 04:45:16.609541: val_loss -0.7555 +2024-11-23 04:45:16.609617: Pseudo dice [0.8593] +2024-11-23 04:45:16.609731: Epoch time: 18.72 s +2024-11-23 04:45:17.547369: +2024-11-23 04:45:17.547580: Epoch 7701 +2024-11-23 04:45:17.547696: Current learning rate: 0.00052 +2024-11-23 04:45:35.902959: train_loss -0.8357 +2024-11-23 04:45:35.903196: val_loss -0.7438 +2024-11-23 04:45:35.903275: Pseudo dice [0.8507] +2024-11-23 04:45:35.903354: Epoch time: 18.36 s +2024-11-23 04:45:37.217321: +2024-11-23 04:45:37.217561: Epoch 7702 +2024-11-23 04:45:37.217679: Current learning rate: 0.00052 +2024-11-23 04:45:56.069695: train_loss -0.8358 +2024-11-23 04:45:56.069918: val_loss -0.7582 +2024-11-23 04:45:56.070002: Pseudo dice [0.864] +2024-11-23 04:45:56.070079: Epoch time: 18.85 s +2024-11-23 04:45:57.013084: +2024-11-23 04:45:57.013311: Epoch 7703 +2024-11-23 04:45:57.013426: Current learning rate: 0.00052 +2024-11-23 04:46:16.075853: train_loss -0.8326 +2024-11-23 04:46:16.076111: val_loss -0.7615 +2024-11-23 04:46:16.076186: Pseudo dice [0.8614] +2024-11-23 04:46:16.076270: Epoch time: 19.06 s +2024-11-23 04:46:17.014282: +2024-11-23 04:46:17.014529: Epoch 7704 +2024-11-23 04:46:17.014643: Current learning rate: 0.00051 +2024-11-23 04:46:34.422801: train_loss -0.8387 +2024-11-23 04:46:34.425494: val_loss -0.7636 +2024-11-23 04:46:34.425621: Pseudo dice [0.855] +2024-11-23 04:46:34.425702: Epoch time: 17.41 s +2024-11-23 04:46:35.363825: +2024-11-23 04:46:35.364046: Epoch 7705 +2024-11-23 04:46:35.364158: Current learning rate: 0.00051 +2024-11-23 04:46:54.177580: train_loss -0.8341 +2024-11-23 04:46:54.177800: val_loss -0.7475 +2024-11-23 04:46:54.177873: Pseudo dice [0.8653] +2024-11-23 04:46:54.177947: Epoch time: 18.81 s +2024-11-23 04:46:55.185061: +2024-11-23 04:46:55.185267: Epoch 7706 +2024-11-23 04:46:55.185376: Current learning rate: 0.00051 +2024-11-23 04:47:13.990940: train_loss -0.8381 +2024-11-23 04:47:13.991173: val_loss -0.7397 +2024-11-23 04:47:13.991249: Pseudo dice [0.8457] +2024-11-23 04:47:13.991328: Epoch time: 18.81 s +2024-11-23 04:47:14.929374: +2024-11-23 04:47:14.929609: Epoch 7707 +2024-11-23 04:47:14.929722: Current learning rate: 0.00051 +2024-11-23 04:47:33.229207: train_loss -0.8392 +2024-11-23 04:47:33.234632: val_loss -0.7357 +2024-11-23 04:47:33.234794: Pseudo dice [0.8421] +2024-11-23 04:47:33.234901: Epoch time: 18.3 s +2024-11-23 04:47:34.177799: +2024-11-23 04:47:34.178039: Epoch 7708 +2024-11-23 04:47:34.178154: Current learning rate: 0.00051 +2024-11-23 04:47:53.066407: train_loss -0.8393 +2024-11-23 04:47:53.066625: val_loss -0.7835 +2024-11-23 04:47:53.066700: Pseudo dice [0.8433] +2024-11-23 04:47:53.066774: Epoch time: 18.89 s +2024-11-23 04:47:53.998732: +2024-11-23 04:47:53.998954: Epoch 7709 +2024-11-23 04:47:53.999070: Current learning rate: 0.00051 +2024-11-23 04:48:12.524129: train_loss -0.8306 +2024-11-23 04:48:12.524348: val_loss -0.7889 +2024-11-23 04:48:12.524425: Pseudo dice [0.8466] +2024-11-23 04:48:12.524500: Epoch time: 18.53 s +2024-11-23 04:48:13.454924: +2024-11-23 04:48:13.455148: Epoch 7710 +2024-11-23 04:48:13.455265: Current learning rate: 0.00051 +2024-11-23 04:48:31.508309: train_loss -0.8408 +2024-11-23 04:48:31.508533: val_loss -0.7578 +2024-11-23 04:48:31.508608: Pseudo dice [0.8457] +2024-11-23 04:48:31.508684: Epoch time: 18.05 s +2024-11-23 04:48:32.549551: +2024-11-23 04:48:32.549937: Epoch 7711 +2024-11-23 04:48:32.550069: Current learning rate: 0.0005 +2024-11-23 04:48:51.033613: train_loss -0.8325 +2024-11-23 04:48:51.033855: val_loss -0.7523 +2024-11-23 04:48:51.033934: Pseudo dice [0.8591] +2024-11-23 04:48:51.034018: Epoch time: 18.48 s +2024-11-23 04:48:51.968776: +2024-11-23 04:48:51.968985: Epoch 7712 +2024-11-23 04:48:51.969107: Current learning rate: 0.0005 +2024-11-23 04:49:10.184904: train_loss -0.8415 +2024-11-23 04:49:10.185191: val_loss -0.7696 +2024-11-23 04:49:10.185271: Pseudo dice [0.8669] +2024-11-23 04:49:10.185345: Epoch time: 18.22 s +2024-11-23 04:49:11.558502: +2024-11-23 04:49:11.558780: Epoch 7713 +2024-11-23 04:49:11.558891: Current learning rate: 0.0005 +2024-11-23 04:49:29.114222: train_loss -0.8357 +2024-11-23 04:49:29.114472: val_loss -0.7674 +2024-11-23 04:49:29.114548: Pseudo dice [0.8547] +2024-11-23 04:49:29.114627: Epoch time: 17.56 s +2024-11-23 04:49:30.050154: +2024-11-23 04:49:30.050381: Epoch 7714 +2024-11-23 04:49:30.050502: Current learning rate: 0.0005 +2024-11-23 04:49:48.709490: train_loss -0.8404 +2024-11-23 04:49:48.714943: val_loss -0.7674 +2024-11-23 04:49:48.715079: Pseudo dice [0.8401] +2024-11-23 04:49:48.715177: Epoch time: 18.66 s +2024-11-23 04:49:49.877679: +2024-11-23 04:49:49.877891: Epoch 7715 +2024-11-23 04:49:49.878008: Current learning rate: 0.0005 +2024-11-23 04:50:07.727879: train_loss -0.833 +2024-11-23 04:50:07.728109: val_loss -0.7715 +2024-11-23 04:50:07.728188: Pseudo dice [0.8437] +2024-11-23 04:50:07.728297: Epoch time: 17.85 s +2024-11-23 04:50:08.662068: +2024-11-23 04:50:08.662297: Epoch 7716 +2024-11-23 04:50:08.662412: Current learning rate: 0.0005 +2024-11-23 04:50:27.612982: train_loss -0.8349 +2024-11-23 04:50:27.613233: val_loss -0.7562 +2024-11-23 04:50:27.613315: Pseudo dice [0.8515] +2024-11-23 04:50:27.613392: Epoch time: 18.95 s +2024-11-23 04:50:28.552439: +2024-11-23 04:50:28.552656: Epoch 7717 +2024-11-23 04:50:28.552768: Current learning rate: 0.00049 +2024-11-23 04:50:47.094398: train_loss -0.8291 +2024-11-23 04:50:47.094630: val_loss -0.7555 +2024-11-23 04:50:47.094705: Pseudo dice [0.8468] +2024-11-23 04:50:47.094788: Epoch time: 18.54 s +2024-11-23 04:50:48.031768: +2024-11-23 04:50:48.032033: Epoch 7718 +2024-11-23 04:50:48.032148: Current learning rate: 0.00049 +2024-11-23 04:51:06.651163: train_loss -0.8435 +2024-11-23 04:51:06.651408: val_loss -0.7451 +2024-11-23 04:51:06.651481: Pseudo dice [0.8433] +2024-11-23 04:51:06.651559: Epoch time: 18.62 s +2024-11-23 04:51:07.590442: +2024-11-23 04:51:07.590729: Epoch 7719 +2024-11-23 04:51:07.590840: Current learning rate: 0.00049 +2024-11-23 04:51:26.721419: train_loss -0.8326 +2024-11-23 04:51:26.721636: val_loss -0.7564 +2024-11-23 04:51:26.721714: Pseudo dice [0.8347] +2024-11-23 04:51:26.721790: Epoch time: 19.13 s +2024-11-23 04:51:27.656045: +2024-11-23 04:51:27.656255: Epoch 7720 +2024-11-23 04:51:27.656364: Current learning rate: 0.00049 +2024-11-23 04:51:46.751724: train_loss -0.8387 +2024-11-23 04:51:46.751980: val_loss -0.7417 +2024-11-23 04:51:46.752068: Pseudo dice [0.8525] +2024-11-23 04:51:46.752145: Epoch time: 19.1 s +2024-11-23 04:51:47.702504: +2024-11-23 04:51:47.702718: Epoch 7721 +2024-11-23 04:51:47.702828: Current learning rate: 0.00049 +2024-11-23 04:52:06.939037: train_loss -0.8438 +2024-11-23 04:52:06.939260: val_loss -0.7554 +2024-11-23 04:52:06.939337: Pseudo dice [0.8695] +2024-11-23 04:52:06.939414: Epoch time: 19.24 s +2024-11-23 04:52:07.878816: +2024-11-23 04:52:07.879032: Epoch 7722 +2024-11-23 04:52:07.879141: Current learning rate: 0.00049 +2024-11-23 04:52:26.731441: train_loss -0.8406 +2024-11-23 04:52:26.731729: val_loss -0.7192 +2024-11-23 04:52:26.731843: Pseudo dice [0.8543] +2024-11-23 04:52:26.731935: Epoch time: 18.85 s +2024-11-23 04:52:27.669212: +2024-11-23 04:52:27.669446: Epoch 7723 +2024-11-23 04:52:27.669556: Current learning rate: 0.00048 +2024-11-23 04:52:46.836684: train_loss -0.8466 +2024-11-23 04:52:46.839108: val_loss -0.7488 +2024-11-23 04:52:46.839258: Pseudo dice [0.8441] +2024-11-23 04:52:46.839350: Epoch time: 19.17 s +2024-11-23 04:52:47.822717: +2024-11-23 04:52:47.822923: Epoch 7724 +2024-11-23 04:52:47.823041: Current learning rate: 0.00048 +2024-11-23 04:53:05.890298: train_loss -0.838 +2024-11-23 04:53:05.890523: val_loss -0.7712 +2024-11-23 04:53:05.890601: Pseudo dice [0.852] +2024-11-23 04:53:05.890680: Epoch time: 18.07 s +2024-11-23 04:53:07.210857: +2024-11-23 04:53:07.211111: Epoch 7725 +2024-11-23 04:53:07.211228: Current learning rate: 0.00048 +2024-11-23 04:53:26.230111: train_loss -0.8384 +2024-11-23 04:53:26.230366: val_loss -0.7394 +2024-11-23 04:53:26.230440: Pseudo dice [0.8601] +2024-11-23 04:53:26.235681: Epoch time: 19.02 s +2024-11-23 04:53:27.350595: +2024-11-23 04:53:27.350806: Epoch 7726 +2024-11-23 04:53:27.350917: Current learning rate: 0.00048 +2024-11-23 04:53:46.250556: train_loss -0.8348 +2024-11-23 04:53:46.250777: val_loss -0.7628 +2024-11-23 04:53:46.256000: Pseudo dice [0.8433] +2024-11-23 04:53:46.256194: Epoch time: 18.9 s +2024-11-23 04:53:47.368477: +2024-11-23 04:53:47.368733: Epoch 7727 +2024-11-23 04:53:47.368843: Current learning rate: 0.00048 +2024-11-23 04:54:05.091878: train_loss -0.8402 +2024-11-23 04:54:05.092108: val_loss -0.7512 +2024-11-23 04:54:05.092183: Pseudo dice [0.858] +2024-11-23 04:54:05.092259: Epoch time: 17.72 s +2024-11-23 04:54:06.024029: +2024-11-23 04:54:06.024239: Epoch 7728 +2024-11-23 04:54:06.024354: Current learning rate: 0.00048 +2024-11-23 04:54:25.187075: train_loss -0.8381 +2024-11-23 04:54:25.187419: val_loss -0.7564 +2024-11-23 04:54:25.187497: Pseudo dice [0.856] +2024-11-23 04:54:25.187580: Epoch time: 19.16 s +2024-11-23 04:54:26.302493: +2024-11-23 04:54:26.302760: Epoch 7729 +2024-11-23 04:54:26.302875: Current learning rate: 0.00048 +2024-11-23 04:54:45.174663: train_loss -0.8336 +2024-11-23 04:54:45.174900: val_loss -0.7614 +2024-11-23 04:54:45.174976: Pseudo dice [0.8491] +2024-11-23 04:54:45.175062: Epoch time: 18.87 s +2024-11-23 04:54:46.152325: +2024-11-23 04:54:46.152542: Epoch 7730 +2024-11-23 04:54:46.152655: Current learning rate: 0.00047 +2024-11-23 04:55:04.347575: train_loss -0.8397 +2024-11-23 04:55:04.347798: val_loss -0.7658 +2024-11-23 04:55:04.347882: Pseudo dice [0.866] +2024-11-23 04:55:04.347957: Epoch time: 18.2 s +2024-11-23 04:55:05.284285: +2024-11-23 04:55:05.284497: Epoch 7731 +2024-11-23 04:55:05.284608: Current learning rate: 0.00047 +2024-11-23 04:55:23.187661: train_loss -0.8448 +2024-11-23 04:55:23.187886: val_loss -0.7642 +2024-11-23 04:55:23.190157: Pseudo dice [0.8821] +2024-11-23 04:55:23.190248: Epoch time: 17.9 s +2024-11-23 04:55:24.253164: +2024-11-23 04:55:24.253453: Epoch 7732 +2024-11-23 04:55:24.253564: Current learning rate: 0.00047 +2024-11-23 04:55:43.593168: train_loss -0.8402 +2024-11-23 04:55:43.593394: val_loss -0.7606 +2024-11-23 04:55:43.593476: Pseudo dice [0.857] +2024-11-23 04:55:43.593560: Epoch time: 19.34 s +2024-11-23 04:55:44.610670: +2024-11-23 04:55:44.610886: Epoch 7733 +2024-11-23 04:55:44.611008: Current learning rate: 0.00047 +2024-11-23 04:56:03.449805: train_loss -0.8343 +2024-11-23 04:56:03.450217: val_loss -0.7754 +2024-11-23 04:56:03.450299: Pseudo dice [0.8716] +2024-11-23 04:56:03.450380: Epoch time: 18.84 s +2024-11-23 04:56:04.384091: +2024-11-23 04:56:04.384301: Epoch 7734 +2024-11-23 04:56:04.384408: Current learning rate: 0.00047 +2024-11-23 04:56:22.996139: train_loss -0.8414 +2024-11-23 04:56:22.996364: val_loss -0.7592 +2024-11-23 04:56:22.996439: Pseudo dice [0.8614] +2024-11-23 04:56:22.996516: Epoch time: 18.61 s +2024-11-23 04:56:24.056791: +2024-11-23 04:56:24.057024: Epoch 7735 +2024-11-23 04:56:24.057135: Current learning rate: 0.00047 +2024-11-23 04:56:42.237594: train_loss -0.841 +2024-11-23 04:56:42.237820: val_loss -0.7612 +2024-11-23 04:56:42.237902: Pseudo dice [0.8317] +2024-11-23 04:56:42.237980: Epoch time: 18.18 s +2024-11-23 04:56:43.589002: +2024-11-23 04:56:43.589204: Epoch 7736 +2024-11-23 04:56:43.589317: Current learning rate: 0.00046 +2024-11-23 04:57:01.676011: train_loss -0.835 +2024-11-23 04:57:01.676255: val_loss -0.7563 +2024-11-23 04:57:01.676332: Pseudo dice [0.8741] +2024-11-23 04:57:01.676413: Epoch time: 18.09 s +2024-11-23 04:57:02.630732: +2024-11-23 04:57:02.630932: Epoch 7737 +2024-11-23 04:57:02.631049: Current learning rate: 0.00046 +2024-11-23 04:57:20.907405: train_loss -0.8378 +2024-11-23 04:57:20.907623: val_loss -0.7097 +2024-11-23 04:57:20.907717: Pseudo dice [0.8324] +2024-11-23 04:57:20.907795: Epoch time: 18.28 s +2024-11-23 04:57:21.840052: +2024-11-23 04:57:21.840276: Epoch 7738 +2024-11-23 04:57:21.840391: Current learning rate: 0.00046 +2024-11-23 04:57:40.243962: train_loss -0.8334 +2024-11-23 04:57:40.244225: val_loss -0.7687 +2024-11-23 04:57:40.244303: Pseudo dice [0.8785] +2024-11-23 04:57:40.244380: Epoch time: 18.4 s +2024-11-23 04:57:41.188344: +2024-11-23 04:57:41.188610: Epoch 7739 +2024-11-23 04:57:41.188728: Current learning rate: 0.00046 +2024-11-23 04:57:59.851820: train_loss -0.839 +2024-11-23 04:57:59.852083: val_loss -0.7281 +2024-11-23 04:57:59.852160: Pseudo dice [0.8548] +2024-11-23 04:57:59.852242: Epoch time: 18.66 s +2024-11-23 04:58:00.797571: +2024-11-23 04:58:00.797788: Epoch 7740 +2024-11-23 04:58:00.797913: Current learning rate: 0.00046 +2024-11-23 04:58:20.024459: train_loss -0.8389 +2024-11-23 04:58:20.024776: val_loss -0.7701 +2024-11-23 04:58:20.024860: Pseudo dice [0.8755] +2024-11-23 04:58:20.024945: Epoch time: 19.23 s +2024-11-23 04:58:20.961459: +2024-11-23 04:58:20.961671: Epoch 7741 +2024-11-23 04:58:20.961784: Current learning rate: 0.00046 +2024-11-23 04:58:39.722624: train_loss -0.8453 +2024-11-23 04:58:39.722845: val_loss -0.7561 +2024-11-23 04:58:39.722919: Pseudo dice [0.8502] +2024-11-23 04:58:39.725168: Epoch time: 18.76 s +2024-11-23 04:58:40.782085: +2024-11-23 04:58:40.782293: Epoch 7742 +2024-11-23 04:58:40.782405: Current learning rate: 0.00045 +2024-11-23 04:58:58.338035: train_loss -0.8359 +2024-11-23 04:58:58.338253: val_loss -0.7772 +2024-11-23 04:58:58.338329: Pseudo dice [0.8629] +2024-11-23 04:58:58.340583: Epoch time: 17.56 s +2024-11-23 04:58:59.360836: +2024-11-23 04:58:59.361171: Epoch 7743 +2024-11-23 04:58:59.361287: Current learning rate: 0.00045 +2024-11-23 04:59:17.120879: train_loss -0.8405 +2024-11-23 04:59:17.121103: val_loss -0.7545 +2024-11-23 04:59:17.121178: Pseudo dice [0.8367] +2024-11-23 04:59:17.121261: Epoch time: 17.76 s +2024-11-23 04:59:18.169050: +2024-11-23 04:59:18.169323: Epoch 7744 +2024-11-23 04:59:18.169435: Current learning rate: 0.00045 +2024-11-23 04:59:37.390173: train_loss -0.8298 +2024-11-23 04:59:37.390455: val_loss -0.755 +2024-11-23 04:59:37.390564: Pseudo dice [0.8218] +2024-11-23 04:59:37.390649: Epoch time: 19.22 s +2024-11-23 04:59:38.326938: +2024-11-23 04:59:38.327142: Epoch 7745 +2024-11-23 04:59:38.327254: Current learning rate: 0.00045 +2024-11-23 04:59:57.615507: train_loss -0.8369 +2024-11-23 04:59:57.615730: val_loss -0.7697 +2024-11-23 04:59:57.615805: Pseudo dice [0.8732] +2024-11-23 04:59:57.615878: Epoch time: 19.29 s +2024-11-23 04:59:58.660383: +2024-11-23 04:59:58.660580: Epoch 7746 +2024-11-23 04:59:58.660693: Current learning rate: 0.00045 +2024-11-23 05:00:17.821530: train_loss -0.828 +2024-11-23 05:00:17.826953: val_loss -0.7717 +2024-11-23 05:00:17.827074: Pseudo dice [0.8567] +2024-11-23 05:00:17.827155: Epoch time: 19.16 s +2024-11-23 05:00:19.204870: +2024-11-23 05:00:19.205187: Epoch 7747 +2024-11-23 05:00:19.205299: Current learning rate: 0.00045 +2024-11-23 05:00:38.177127: train_loss -0.8375 +2024-11-23 05:00:38.177382: val_loss -0.7611 +2024-11-23 05:00:38.177459: Pseudo dice [0.8451] +2024-11-23 05:00:38.177578: Epoch time: 18.97 s +2024-11-23 05:00:39.115353: +2024-11-23 05:00:39.115957: Epoch 7748 +2024-11-23 05:00:39.116107: Current learning rate: 0.00045 +2024-11-23 05:00:58.490174: train_loss -0.8374 +2024-11-23 05:00:58.490404: val_loss -0.7508 +2024-11-23 05:00:58.490481: Pseudo dice [0.8487] +2024-11-23 05:00:58.490556: Epoch time: 19.38 s +2024-11-23 05:00:59.429203: +2024-11-23 05:00:59.429622: Epoch 7749 +2024-11-23 05:00:59.429750: Current learning rate: 0.00044 +2024-11-23 05:01:17.501892: train_loss -0.8429 +2024-11-23 05:01:17.502131: val_loss -0.7903 +2024-11-23 05:01:17.502208: Pseudo dice [0.8685] +2024-11-23 05:01:17.502291: Epoch time: 18.07 s +2024-11-23 05:01:18.788731: +2024-11-23 05:01:18.789169: Epoch 7750 +2024-11-23 05:01:18.789299: Current learning rate: 0.00044 +2024-11-23 05:01:37.829164: train_loss -0.8404 +2024-11-23 05:01:37.829393: val_loss -0.751 +2024-11-23 05:01:37.829470: Pseudo dice [0.8381] +2024-11-23 05:01:37.831715: Epoch time: 19.04 s +2024-11-23 05:01:38.803730: +2024-11-23 05:01:38.804166: Epoch 7751 +2024-11-23 05:01:38.804304: Current learning rate: 0.00044 +2024-11-23 05:01:57.915812: train_loss -0.8352 +2024-11-23 05:01:57.917934: val_loss -0.7704 +2024-11-23 05:01:57.918051: Pseudo dice [0.8396] +2024-11-23 05:01:57.918210: Epoch time: 19.11 s +2024-11-23 05:01:58.986106: +2024-11-23 05:01:58.986548: Epoch 7752 +2024-11-23 05:01:58.986684: Current learning rate: 0.00044 +2024-11-23 05:02:18.358096: train_loss -0.8336 +2024-11-23 05:02:18.358316: val_loss -0.7639 +2024-11-23 05:02:18.358391: Pseudo dice [0.8506] +2024-11-23 05:02:18.358478: Epoch time: 19.37 s +2024-11-23 05:02:19.304933: +2024-11-23 05:02:19.305362: Epoch 7753 +2024-11-23 05:02:19.305495: Current learning rate: 0.00044 +2024-11-23 05:02:39.427268: train_loss -0.8435 +2024-11-23 05:02:39.427492: val_loss -0.7631 +2024-11-23 05:02:39.427565: Pseudo dice [0.8522] +2024-11-23 05:02:39.427642: Epoch time: 20.12 s +2024-11-23 05:02:40.469146: +2024-11-23 05:02:40.469604: Epoch 7754 +2024-11-23 05:02:40.469740: Current learning rate: 0.00044 +2024-11-23 05:02:59.031296: train_loss -0.8363 +2024-11-23 05:02:59.031525: val_loss -0.7443 +2024-11-23 05:02:59.031674: Pseudo dice [0.8473] +2024-11-23 05:02:59.031753: Epoch time: 18.56 s +2024-11-23 05:02:59.995491: +2024-11-23 05:02:59.995916: Epoch 7755 +2024-11-23 05:02:59.996058: Current learning rate: 0.00043 +2024-11-23 05:03:18.480067: train_loss -0.8346 +2024-11-23 05:03:18.480314: val_loss -0.7675 +2024-11-23 05:03:18.480392: Pseudo dice [0.8631] +2024-11-23 05:03:18.480473: Epoch time: 18.49 s +2024-11-23 05:03:19.414705: +2024-11-23 05:03:19.415139: Epoch 7756 +2024-11-23 05:03:19.415276: Current learning rate: 0.00043 +2024-11-23 05:03:37.708017: train_loss -0.8431 +2024-11-23 05:03:37.708243: val_loss -0.7561 +2024-11-23 05:03:37.708320: Pseudo dice [0.8582] +2024-11-23 05:03:37.708402: Epoch time: 18.29 s +2024-11-23 05:03:38.650179: +2024-11-23 05:03:38.650616: Epoch 7757 +2024-11-23 05:03:38.650754: Current learning rate: 0.00043 +2024-11-23 05:03:56.417384: train_loss -0.8435 +2024-11-23 05:03:56.417606: val_loss -0.7499 +2024-11-23 05:03:56.417682: Pseudo dice [0.86] +2024-11-23 05:03:56.417758: Epoch time: 17.77 s +2024-11-23 05:03:57.746233: +2024-11-23 05:03:57.746432: Epoch 7758 +2024-11-23 05:03:57.746543: Current learning rate: 0.00043 +2024-11-23 05:04:16.401206: train_loss -0.8329 +2024-11-23 05:04:16.403626: val_loss -0.7527 +2024-11-23 05:04:16.403742: Pseudo dice [0.8604] +2024-11-23 05:04:16.403835: Epoch time: 18.66 s +2024-11-23 05:04:17.437037: +2024-11-23 05:04:17.437263: Epoch 7759 +2024-11-23 05:04:17.437373: Current learning rate: 0.00043 +2024-11-23 05:04:35.873196: train_loss -0.8382 +2024-11-23 05:04:35.873409: val_loss -0.7666 +2024-11-23 05:04:35.873484: Pseudo dice [0.8732] +2024-11-23 05:04:35.873559: Epoch time: 18.44 s +2024-11-23 05:04:36.842500: +2024-11-23 05:04:36.842755: Epoch 7760 +2024-11-23 05:04:36.842874: Current learning rate: 0.00043 +2024-11-23 05:04:55.685071: train_loss -0.8336 +2024-11-23 05:04:55.685286: val_loss -0.7692 +2024-11-23 05:04:55.685366: Pseudo dice [0.8503] +2024-11-23 05:04:55.685439: Epoch time: 18.84 s +2024-11-23 05:04:56.683160: +2024-11-23 05:04:56.683368: Epoch 7761 +2024-11-23 05:04:56.683478: Current learning rate: 0.00042 +2024-11-23 05:05:14.804073: train_loss -0.8419 +2024-11-23 05:05:14.804369: val_loss -0.7595 +2024-11-23 05:05:14.804443: Pseudo dice [0.854] +2024-11-23 05:05:14.804525: Epoch time: 18.12 s +2024-11-23 05:05:15.741375: +2024-11-23 05:05:15.741616: Epoch 7762 +2024-11-23 05:05:15.741735: Current learning rate: 0.00042 +2024-11-23 05:05:33.720852: train_loss -0.8381 +2024-11-23 05:05:33.721079: val_loss -0.7629 +2024-11-23 05:05:33.721154: Pseudo dice [0.8575] +2024-11-23 05:05:33.721229: Epoch time: 17.98 s +2024-11-23 05:05:34.660767: +2024-11-23 05:05:34.661068: Epoch 7763 +2024-11-23 05:05:34.661178: Current learning rate: 0.00042 +2024-11-23 05:05:53.402150: train_loss -0.8394 +2024-11-23 05:05:53.402379: val_loss -0.7634 +2024-11-23 05:05:53.402454: Pseudo dice [0.8553] +2024-11-23 05:05:53.402533: Epoch time: 18.74 s +2024-11-23 05:05:54.396801: +2024-11-23 05:05:54.397072: Epoch 7764 +2024-11-23 05:05:54.397191: Current learning rate: 0.00042 +2024-11-23 05:06:12.128629: train_loss -0.8352 +2024-11-23 05:06:12.128865: val_loss -0.7772 +2024-11-23 05:06:12.128940: Pseudo dice [0.8722] +2024-11-23 05:06:12.129025: Epoch time: 17.73 s +2024-11-23 05:06:13.069140: +2024-11-23 05:06:13.069366: Epoch 7765 +2024-11-23 05:06:13.069479: Current learning rate: 0.00042 +2024-11-23 05:06:32.867819: train_loss -0.839 +2024-11-23 05:06:32.868080: val_loss -0.7474 +2024-11-23 05:06:32.868157: Pseudo dice [0.8436] +2024-11-23 05:06:32.868242: Epoch time: 19.8 s +2024-11-23 05:06:33.813722: +2024-11-23 05:06:33.813940: Epoch 7766 +2024-11-23 05:06:33.814067: Current learning rate: 0.00042 +2024-11-23 05:06:53.254554: train_loss -0.838 +2024-11-23 05:06:53.254769: val_loss -0.7675 +2024-11-23 05:06:53.254845: Pseudo dice [0.8401] +2024-11-23 05:06:53.254921: Epoch time: 19.44 s +2024-11-23 05:06:54.182559: +2024-11-23 05:06:54.182764: Epoch 7767 +2024-11-23 05:06:54.182876: Current learning rate: 0.00041 +2024-11-23 05:07:13.354082: train_loss -0.8372 +2024-11-23 05:07:13.354312: val_loss -0.7664 +2024-11-23 05:07:13.359533: Pseudo dice [0.8482] +2024-11-23 05:07:13.359696: Epoch time: 19.17 s +2024-11-23 05:07:14.614064: +2024-11-23 05:07:14.614303: Epoch 7768 +2024-11-23 05:07:14.614417: Current learning rate: 0.00041 +2024-11-23 05:07:33.221128: train_loss -0.837 +2024-11-23 05:07:33.221364: val_loss -0.7567 +2024-11-23 05:07:33.221441: Pseudo dice [0.8725] +2024-11-23 05:07:33.221525: Epoch time: 18.61 s +2024-11-23 05:07:34.532026: +2024-11-23 05:07:34.532262: Epoch 7769 +2024-11-23 05:07:34.532376: Current learning rate: 0.00041 +2024-11-23 05:07:53.338815: train_loss -0.843 +2024-11-23 05:07:53.339077: val_loss -0.7378 +2024-11-23 05:07:53.339175: Pseudo dice [0.8474] +2024-11-23 05:07:53.339262: Epoch time: 18.81 s +2024-11-23 05:07:54.271638: +2024-11-23 05:07:54.271860: Epoch 7770 +2024-11-23 05:07:54.271973: Current learning rate: 0.00041 +2024-11-23 05:08:12.851938: train_loss -0.8421 +2024-11-23 05:08:12.852181: val_loss -0.7484 +2024-11-23 05:08:12.852254: Pseudo dice [0.853] +2024-11-23 05:08:12.852333: Epoch time: 18.58 s +2024-11-23 05:08:13.800344: +2024-11-23 05:08:13.800560: Epoch 7771 +2024-11-23 05:08:13.800672: Current learning rate: 0.00041 +2024-11-23 05:08:33.457852: train_loss -0.8379 +2024-11-23 05:08:33.458078: val_loss -0.7311 +2024-11-23 05:08:33.458152: Pseudo dice [0.8343] +2024-11-23 05:08:33.458226: Epoch time: 19.66 s +2024-11-23 05:08:34.418643: +2024-11-23 05:08:34.418948: Epoch 7772 +2024-11-23 05:08:34.419118: Current learning rate: 0.00041 +2024-11-23 05:08:53.144829: train_loss -0.8362 +2024-11-23 05:08:53.145061: val_loss -0.7833 +2024-11-23 05:08:53.145138: Pseudo dice [0.862] +2024-11-23 05:08:53.145217: Epoch time: 18.73 s +2024-11-23 05:08:54.090043: +2024-11-23 05:08:54.090285: Epoch 7773 +2024-11-23 05:08:54.090393: Current learning rate: 0.00041 +2024-11-23 05:09:13.764626: train_loss -0.8375 +2024-11-23 05:09:13.764873: val_loss -0.7867 +2024-11-23 05:09:13.764949: Pseudo dice [0.8739] +2024-11-23 05:09:13.765031: Epoch time: 19.68 s +2024-11-23 05:09:14.703097: +2024-11-23 05:09:14.703406: Epoch 7774 +2024-11-23 05:09:14.703527: Current learning rate: 0.0004 +2024-11-23 05:09:33.253829: train_loss -0.8344 +2024-11-23 05:09:33.254065: val_loss -0.7579 +2024-11-23 05:09:33.254143: Pseudo dice [0.8565] +2024-11-23 05:09:33.254222: Epoch time: 18.55 s +2024-11-23 05:09:34.188481: +2024-11-23 05:09:34.188698: Epoch 7775 +2024-11-23 05:09:34.188811: Current learning rate: 0.0004 +2024-11-23 05:09:53.506140: train_loss -0.8389 +2024-11-23 05:09:53.506370: val_loss -0.7675 +2024-11-23 05:09:53.506445: Pseudo dice [0.8644] +2024-11-23 05:09:53.506527: Epoch time: 19.32 s +2024-11-23 05:09:54.467106: +2024-11-23 05:09:54.467338: Epoch 7776 +2024-11-23 05:09:54.467452: Current learning rate: 0.0004 +2024-11-23 05:10:12.632928: train_loss -0.8413 +2024-11-23 05:10:12.635029: val_loss -0.7608 +2024-11-23 05:10:12.635159: Pseudo dice [0.8511] +2024-11-23 05:10:12.640382: Epoch time: 18.17 s +2024-11-23 05:10:13.595189: +2024-11-23 05:10:13.595399: Epoch 7777 +2024-11-23 05:10:13.595511: Current learning rate: 0.0004 +2024-11-23 05:10:31.584761: train_loss -0.8403 +2024-11-23 05:10:31.584980: val_loss -0.7665 +2024-11-23 05:10:31.585067: Pseudo dice [0.8425] +2024-11-23 05:10:31.585149: Epoch time: 17.99 s +2024-11-23 05:10:32.531931: +2024-11-23 05:10:32.532213: Epoch 7778 +2024-11-23 05:10:32.532334: Current learning rate: 0.0004 +2024-11-23 05:10:50.699712: train_loss -0.8431 +2024-11-23 05:10:50.705108: val_loss -0.7823 +2024-11-23 05:10:50.705226: Pseudo dice [0.858] +2024-11-23 05:10:50.705308: Epoch time: 18.17 s +2024-11-23 05:10:51.800823: +2024-11-23 05:10:51.801068: Epoch 7779 +2024-11-23 05:10:51.801181: Current learning rate: 0.0004 +2024-11-23 05:11:10.694923: train_loss -0.8378 +2024-11-23 05:11:10.695185: val_loss -0.7834 +2024-11-23 05:11:10.695283: Pseudo dice [0.8667] +2024-11-23 05:11:10.695409: Epoch time: 18.89 s +2024-11-23 05:11:12.011003: +2024-11-23 05:11:12.011207: Epoch 7780 +2024-11-23 05:11:12.011316: Current learning rate: 0.00039 +2024-11-23 05:11:29.524375: train_loss -0.839 +2024-11-23 05:11:29.524642: val_loss -0.7512 +2024-11-23 05:11:29.524722: Pseudo dice [0.8319] +2024-11-23 05:11:29.524801: Epoch time: 17.51 s +2024-11-23 05:11:30.466934: +2024-11-23 05:11:30.467189: Epoch 7781 +2024-11-23 05:11:30.467305: Current learning rate: 0.00039 +2024-11-23 05:11:48.907492: train_loss -0.8384 +2024-11-23 05:11:48.907721: val_loss -0.7603 +2024-11-23 05:11:48.907799: Pseudo dice [0.8528] +2024-11-23 05:11:48.907877: Epoch time: 18.44 s +2024-11-23 05:11:49.844950: +2024-11-23 05:11:49.845342: Epoch 7782 +2024-11-23 05:11:49.845458: Current learning rate: 0.00039 +2024-11-23 05:12:08.576948: train_loss -0.8396 +2024-11-23 05:12:08.577289: val_loss -0.7699 +2024-11-23 05:12:08.577371: Pseudo dice [0.8389] +2024-11-23 05:12:08.577471: Epoch time: 18.73 s +2024-11-23 05:12:09.519661: +2024-11-23 05:12:09.519879: Epoch 7783 +2024-11-23 05:12:09.519995: Current learning rate: 0.00039 +2024-11-23 05:12:27.315466: train_loss -0.8416 +2024-11-23 05:12:27.315687: val_loss -0.7412 +2024-11-23 05:12:27.315763: Pseudo dice [0.8579] +2024-11-23 05:12:27.315840: Epoch time: 17.8 s +2024-11-23 05:12:28.261261: +2024-11-23 05:12:28.261476: Epoch 7784 +2024-11-23 05:12:28.261587: Current learning rate: 0.00039 +2024-11-23 05:12:47.395043: train_loss -0.8429 +2024-11-23 05:12:47.395272: val_loss -0.7588 +2024-11-23 05:12:47.395346: Pseudo dice [0.8256] +2024-11-23 05:12:47.395423: Epoch time: 19.13 s +2024-11-23 05:12:48.334494: +2024-11-23 05:12:48.334725: Epoch 7785 +2024-11-23 05:12:48.334833: Current learning rate: 0.00039 +2024-11-23 05:13:07.170612: train_loss -0.8391 +2024-11-23 05:13:07.170826: val_loss -0.7267 +2024-11-23 05:13:07.170900: Pseudo dice [0.8565] +2024-11-23 05:13:07.170975: Epoch time: 18.84 s +2024-11-23 05:13:08.110339: +2024-11-23 05:13:08.110563: Epoch 7786 +2024-11-23 05:13:08.110685: Current learning rate: 0.00038 +2024-11-23 05:13:27.698825: train_loss -0.8359 +2024-11-23 05:13:27.699080: val_loss -0.7652 +2024-11-23 05:13:27.699157: Pseudo dice [0.8463] +2024-11-23 05:13:27.699242: Epoch time: 19.59 s +2024-11-23 05:13:28.698204: +2024-11-23 05:13:28.698446: Epoch 7787 +2024-11-23 05:13:28.698563: Current learning rate: 0.00038 +2024-11-23 05:13:47.025251: train_loss -0.8356 +2024-11-23 05:13:47.025471: val_loss -0.7424 +2024-11-23 05:13:47.027790: Pseudo dice [0.8499] +2024-11-23 05:13:47.027880: Epoch time: 18.33 s +2024-11-23 05:13:48.138127: +2024-11-23 05:13:48.138426: Epoch 7788 +2024-11-23 05:13:48.138540: Current learning rate: 0.00038 +2024-11-23 05:14:06.083936: train_loss -0.8374 +2024-11-23 05:14:06.084167: val_loss -0.7641 +2024-11-23 05:14:06.084241: Pseudo dice [0.8402] +2024-11-23 05:14:06.084454: Epoch time: 17.95 s +2024-11-23 05:14:07.029849: +2024-11-23 05:14:07.030063: Epoch 7789 +2024-11-23 05:14:07.030176: Current learning rate: 0.00038 +2024-11-23 05:14:26.871816: train_loss -0.8424 +2024-11-23 05:14:26.872047: val_loss -0.7741 +2024-11-23 05:14:26.872122: Pseudo dice [0.8702] +2024-11-23 05:14:26.872200: Epoch time: 19.84 s +2024-11-23 05:14:27.809435: +2024-11-23 05:14:27.809653: Epoch 7790 +2024-11-23 05:14:27.809762: Current learning rate: 0.00038 +2024-11-23 05:14:46.375921: train_loss -0.8403 +2024-11-23 05:14:46.376221: val_loss -0.729 +2024-11-23 05:14:46.376302: Pseudo dice [0.8485] +2024-11-23 05:14:46.376392: Epoch time: 18.57 s +2024-11-23 05:14:47.693775: +2024-11-23 05:14:47.693994: Epoch 7791 +2024-11-23 05:14:47.694105: Current learning rate: 0.00038 +2024-11-23 05:15:06.864053: train_loss -0.8428 +2024-11-23 05:15:06.864310: val_loss -0.7584 +2024-11-23 05:15:06.864390: Pseudo dice [0.8568] +2024-11-23 05:15:06.864468: Epoch time: 19.17 s +2024-11-23 05:15:07.821012: +2024-11-23 05:15:07.821238: Epoch 7792 +2024-11-23 05:15:07.821350: Current learning rate: 0.00037 +2024-11-23 05:15:26.094554: train_loss -0.8423 +2024-11-23 05:15:26.094836: val_loss -0.7837 +2024-11-23 05:15:26.094915: Pseudo dice [0.8503] +2024-11-23 05:15:26.095000: Epoch time: 18.27 s +2024-11-23 05:15:27.031385: +2024-11-23 05:15:27.031610: Epoch 7793 +2024-11-23 05:15:27.031719: Current learning rate: 0.00037 +2024-11-23 05:15:46.672021: train_loss -0.839 +2024-11-23 05:15:46.677479: val_loss -0.7274 +2024-11-23 05:15:46.677667: Pseudo dice [0.8367] +2024-11-23 05:15:46.677763: Epoch time: 19.64 s +2024-11-23 05:15:47.785762: +2024-11-23 05:15:47.786078: Epoch 7794 +2024-11-23 05:15:47.786193: Current learning rate: 0.00037 +2024-11-23 05:16:05.969778: train_loss -0.8471 +2024-11-23 05:16:05.970024: val_loss -0.7742 +2024-11-23 05:16:05.970100: Pseudo dice [0.8654] +2024-11-23 05:16:05.970178: Epoch time: 18.18 s +2024-11-23 05:16:06.940248: +2024-11-23 05:16:06.940488: Epoch 7795 +2024-11-23 05:16:06.940605: Current learning rate: 0.00037 +2024-11-23 05:16:26.552923: train_loss -0.8362 +2024-11-23 05:16:26.553144: val_loss -0.7582 +2024-11-23 05:16:26.553226: Pseudo dice [0.8315] +2024-11-23 05:16:26.553303: Epoch time: 19.61 s +2024-11-23 05:16:27.498557: +2024-11-23 05:16:27.498786: Epoch 7796 +2024-11-23 05:16:27.498911: Current learning rate: 0.00037 +2024-11-23 05:16:45.913273: train_loss -0.8426 +2024-11-23 05:16:45.913497: val_loss -0.7561 +2024-11-23 05:16:45.913573: Pseudo dice [0.8513] +2024-11-23 05:16:45.913651: Epoch time: 18.42 s +2024-11-23 05:16:46.846269: +2024-11-23 05:16:46.846541: Epoch 7797 +2024-11-23 05:16:46.846657: Current learning rate: 0.00037 +2024-11-23 05:17:06.169258: train_loss -0.8443 +2024-11-23 05:17:06.169575: val_loss -0.7619 +2024-11-23 05:17:06.169651: Pseudo dice [0.8641] +2024-11-23 05:17:06.169734: Epoch time: 19.32 s +2024-11-23 05:17:07.107046: +2024-11-23 05:17:07.107272: Epoch 7798 +2024-11-23 05:17:07.107388: Current learning rate: 0.00036 +2024-11-23 05:17:25.114732: train_loss -0.8375 +2024-11-23 05:17:25.114949: val_loss -0.7655 +2024-11-23 05:17:25.115031: Pseudo dice [0.8495] +2024-11-23 05:17:25.115108: Epoch time: 18.01 s +2024-11-23 05:17:26.173782: +2024-11-23 05:17:26.174000: Epoch 7799 +2024-11-23 05:17:26.174118: Current learning rate: 0.00036 +2024-11-23 05:17:44.870640: train_loss -0.838 +2024-11-23 05:17:44.873075: val_loss -0.7693 +2024-11-23 05:17:44.873193: Pseudo dice [0.8439] +2024-11-23 05:17:44.873273: Epoch time: 18.7 s +2024-11-23 05:17:46.167733: +2024-11-23 05:17:46.167936: Epoch 7800 +2024-11-23 05:17:46.168052: Current learning rate: 0.00036 +2024-11-23 05:18:04.649276: train_loss -0.8404 +2024-11-23 05:18:04.649489: val_loss -0.726 +2024-11-23 05:18:04.649566: Pseudo dice [0.8385] +2024-11-23 05:18:04.649643: Epoch time: 18.48 s +2024-11-23 05:18:05.580376: +2024-11-23 05:18:05.580631: Epoch 7801 +2024-11-23 05:18:05.580750: Current learning rate: 0.00036 +2024-11-23 05:18:24.388615: train_loss -0.8416 +2024-11-23 05:18:24.394047: val_loss -0.7513 +2024-11-23 05:18:24.394129: Pseudo dice [0.8428] +2024-11-23 05:18:24.394221: Epoch time: 18.81 s +2024-11-23 05:18:25.524768: +2024-11-23 05:18:25.524965: Epoch 7802 +2024-11-23 05:18:25.525081: Current learning rate: 0.00036 +2024-11-23 05:18:44.864789: train_loss -0.8466 +2024-11-23 05:18:44.865041: val_loss -0.7789 +2024-11-23 05:18:44.865118: Pseudo dice [0.8748] +2024-11-23 05:18:44.865197: Epoch time: 19.34 s +2024-11-23 05:18:45.795449: +2024-11-23 05:18:45.795820: Epoch 7803 +2024-11-23 05:18:45.795931: Current learning rate: 0.00036 +2024-11-23 05:19:06.342591: train_loss -0.8379 +2024-11-23 05:19:06.343092: val_loss -0.761 +2024-11-23 05:19:06.343190: Pseudo dice [0.8559] +2024-11-23 05:19:06.343279: Epoch time: 20.55 s +2024-11-23 05:19:07.278875: +2024-11-23 05:19:07.279352: Epoch 7804 +2024-11-23 05:19:07.279489: Current learning rate: 0.00036 +2024-11-23 05:19:26.997900: train_loss -0.8453 +2024-11-23 05:19:26.998162: val_loss -0.7628 +2024-11-23 05:19:26.998258: Pseudo dice [0.8604] +2024-11-23 05:19:26.998343: Epoch time: 19.72 s +2024-11-23 05:19:27.935315: +2024-11-23 05:19:27.935791: Epoch 7805 +2024-11-23 05:19:27.935927: Current learning rate: 0.00035 +2024-11-23 05:19:45.911087: train_loss -0.8392 +2024-11-23 05:19:45.911319: val_loss -0.7572 +2024-11-23 05:19:45.911392: Pseudo dice [0.8637] +2024-11-23 05:19:45.911470: Epoch time: 17.98 s +2024-11-23 05:19:47.056563: +2024-11-23 05:19:47.057056: Epoch 7806 +2024-11-23 05:19:47.057191: Current learning rate: 0.00035 +2024-11-23 05:20:04.915710: train_loss -0.8438 +2024-11-23 05:20:04.915920: val_loss -0.7814 +2024-11-23 05:20:04.916043: Pseudo dice [0.8682] +2024-11-23 05:20:04.916121: Epoch time: 17.86 s +2024-11-23 05:20:05.853971: +2024-11-23 05:20:05.854427: Epoch 7807 +2024-11-23 05:20:05.854558: Current learning rate: 0.00035 +2024-11-23 05:20:24.838433: train_loss -0.8456 +2024-11-23 05:20:24.838660: val_loss -0.764 +2024-11-23 05:20:24.838736: Pseudo dice [0.8447] +2024-11-23 05:20:24.838812: Epoch time: 18.99 s +2024-11-23 05:20:25.773019: +2024-11-23 05:20:25.773474: Epoch 7808 +2024-11-23 05:20:25.773609: Current learning rate: 0.00035 +2024-11-23 05:20:44.227523: train_loss -0.8398 +2024-11-23 05:20:44.227792: val_loss -0.7768 +2024-11-23 05:20:44.227916: Pseudo dice [0.8514] +2024-11-23 05:20:44.228004: Epoch time: 18.46 s +2024-11-23 05:20:45.171515: +2024-11-23 05:20:45.171928: Epoch 7809 +2024-11-23 05:20:45.172067: Current learning rate: 0.00035 +2024-11-23 05:21:04.106838: train_loss -0.8391 +2024-11-23 05:21:04.107063: val_loss -0.7603 +2024-11-23 05:21:04.107140: Pseudo dice [0.8736] +2024-11-23 05:21:04.107215: Epoch time: 18.94 s +2024-11-23 05:21:05.040749: +2024-11-23 05:21:05.041248: Epoch 7810 +2024-11-23 05:21:05.041384: Current learning rate: 0.00035 +2024-11-23 05:21:23.663329: train_loss -0.8433 +2024-11-23 05:21:23.663561: val_loss -0.7758 +2024-11-23 05:21:23.663705: Pseudo dice [0.8651] +2024-11-23 05:21:23.663785: Epoch time: 18.62 s +2024-11-23 05:21:24.657443: +2024-11-23 05:21:24.657877: Epoch 7811 +2024-11-23 05:21:24.658019: Current learning rate: 0.00034 +2024-11-23 05:21:44.788527: train_loss -0.8414 +2024-11-23 05:21:44.788751: val_loss -0.7899 +2024-11-23 05:21:44.788828: Pseudo dice [0.8485] +2024-11-23 05:21:44.788908: Epoch time: 20.13 s +2024-11-23 05:21:45.729506: +2024-11-23 05:21:45.729945: Epoch 7812 +2024-11-23 05:21:45.730092: Current learning rate: 0.00034 +2024-11-23 05:22:04.489983: train_loss -0.8402 +2024-11-23 05:22:04.490297: val_loss -0.7616 +2024-11-23 05:22:04.490376: Pseudo dice [0.8374] +2024-11-23 05:22:04.490467: Epoch time: 18.76 s +2024-11-23 05:22:05.965363: +2024-11-23 05:22:05.965579: Epoch 7813 +2024-11-23 05:22:05.965688: Current learning rate: 0.00034 +2024-11-23 05:22:25.041022: train_loss -0.8415 +2024-11-23 05:22:25.041299: val_loss -0.7416 +2024-11-23 05:22:25.041374: Pseudo dice [0.857] +2024-11-23 05:22:25.041450: Epoch time: 19.08 s +2024-11-23 05:22:25.976292: +2024-11-23 05:22:25.976750: Epoch 7814 +2024-11-23 05:22:25.976894: Current learning rate: 0.00034 +2024-11-23 05:22:44.404853: train_loss -0.8396 +2024-11-23 05:22:44.405092: val_loss -0.7686 +2024-11-23 05:22:44.405169: Pseudo dice [0.8309] +2024-11-23 05:22:44.405321: Epoch time: 18.43 s +2024-11-23 05:22:45.365538: +2024-11-23 05:22:45.365980: Epoch 7815 +2024-11-23 05:22:45.366116: Current learning rate: 0.00034 +2024-11-23 05:23:03.976351: train_loss -0.8406 +2024-11-23 05:23:03.976601: val_loss -0.7538 +2024-11-23 05:23:03.976676: Pseudo dice [0.8496] +2024-11-23 05:23:03.976760: Epoch time: 18.61 s +2024-11-23 05:23:04.918619: +2024-11-23 05:23:04.919072: Epoch 7816 +2024-11-23 05:23:04.919209: Current learning rate: 0.00034 +2024-11-23 05:23:22.951027: train_loss -0.8389 +2024-11-23 05:23:22.951246: val_loss -0.7734 +2024-11-23 05:23:22.951319: Pseudo dice [0.8612] +2024-11-23 05:23:22.951394: Epoch time: 18.03 s +2024-11-23 05:23:23.890607: +2024-11-23 05:23:23.891044: Epoch 7817 +2024-11-23 05:23:23.891186: Current learning rate: 0.00033 +2024-11-23 05:23:42.110835: train_loss -0.8378 +2024-11-23 05:23:42.111073: val_loss -0.7593 +2024-11-23 05:23:42.111150: Pseudo dice [0.8557] +2024-11-23 05:23:42.111230: Epoch time: 18.22 s +2024-11-23 05:23:43.155910: +2024-11-23 05:23:43.156354: Epoch 7818 +2024-11-23 05:23:43.156487: Current learning rate: 0.00033 +2024-11-23 05:24:01.633523: train_loss -0.8433 +2024-11-23 05:24:01.633748: val_loss -0.7702 +2024-11-23 05:24:01.633823: Pseudo dice [0.8405] +2024-11-23 05:24:01.633899: Epoch time: 18.48 s +2024-11-23 05:24:02.571820: +2024-11-23 05:24:02.572267: Epoch 7819 +2024-11-23 05:24:02.572397: Current learning rate: 0.00033 +2024-11-23 05:24:21.158165: train_loss -0.8385 +2024-11-23 05:24:21.158424: val_loss -0.7515 +2024-11-23 05:24:21.158499: Pseudo dice [0.853] +2024-11-23 05:24:21.158584: Epoch time: 18.59 s +2024-11-23 05:24:22.102263: +2024-11-23 05:24:22.102705: Epoch 7820 +2024-11-23 05:24:22.102844: Current learning rate: 0.00033 +2024-11-23 05:24:40.126371: train_loss -0.8454 +2024-11-23 05:24:40.126590: val_loss -0.777 +2024-11-23 05:24:40.126691: Pseudo dice [0.8658] +2024-11-23 05:24:40.126770: Epoch time: 18.02 s +2024-11-23 05:24:41.063841: +2024-11-23 05:24:41.064302: Epoch 7821 +2024-11-23 05:24:41.064436: Current learning rate: 0.00033 +2024-11-23 05:25:00.249554: train_loss -0.8362 +2024-11-23 05:25:00.249787: val_loss -0.7559 +2024-11-23 05:25:00.249866: Pseudo dice [0.8619] +2024-11-23 05:25:00.249943: Epoch time: 19.19 s +2024-11-23 05:25:01.189271: +2024-11-23 05:25:01.189698: Epoch 7822 +2024-11-23 05:25:01.189832: Current learning rate: 0.00033 +2024-11-23 05:25:20.824157: train_loss -0.8418 +2024-11-23 05:25:20.824369: val_loss -0.777 +2024-11-23 05:25:20.824445: Pseudo dice [0.8533] +2024-11-23 05:25:20.824526: Epoch time: 19.64 s +2024-11-23 05:25:21.761610: +2024-11-23 05:25:21.761843: Epoch 7823 +2024-11-23 05:25:21.761999: Current learning rate: 0.00032 +2024-11-23 05:25:41.183136: train_loss -0.8324 +2024-11-23 05:25:41.183363: val_loss -0.7759 +2024-11-23 05:25:41.183442: Pseudo dice [0.8586] +2024-11-23 05:25:41.183525: Epoch time: 19.42 s +2024-11-23 05:25:42.123087: +2024-11-23 05:25:42.123285: Epoch 7824 +2024-11-23 05:25:42.123397: Current learning rate: 0.00032 +2024-11-23 05:26:00.528523: train_loss -0.8436 +2024-11-23 05:26:00.528781: val_loss -0.7732 +2024-11-23 05:26:00.528859: Pseudo dice [0.8559] +2024-11-23 05:26:00.528941: Epoch time: 18.41 s +2024-11-23 05:26:01.469947: +2024-11-23 05:26:01.470423: Epoch 7825 +2024-11-23 05:26:01.470559: Current learning rate: 0.00032 +2024-11-23 05:26:19.923735: train_loss -0.8403 +2024-11-23 05:26:19.923961: val_loss -0.7639 +2024-11-23 05:26:19.924045: Pseudo dice [0.8271] +2024-11-23 05:26:19.924131: Epoch time: 18.45 s +2024-11-23 05:26:20.867920: +2024-11-23 05:26:20.868420: Epoch 7826 +2024-11-23 05:26:20.868559: Current learning rate: 0.00032 +2024-11-23 05:26:39.362287: train_loss -0.8381 +2024-11-23 05:26:39.362529: val_loss -0.7556 +2024-11-23 05:26:39.362603: Pseudo dice [0.8594] +2024-11-23 05:26:39.362681: Epoch time: 18.5 s +2024-11-23 05:26:40.400537: +2024-11-23 05:26:40.400976: Epoch 7827 +2024-11-23 05:26:40.401115: Current learning rate: 0.00032 +2024-11-23 05:26:58.747834: train_loss -0.8435 +2024-11-23 05:26:58.748069: val_loss -0.7541 +2024-11-23 05:26:58.748144: Pseudo dice [0.8553] +2024-11-23 05:26:58.748220: Epoch time: 18.35 s +2024-11-23 05:26:59.683064: +2024-11-23 05:26:59.683489: Epoch 7828 +2024-11-23 05:26:59.683621: Current learning rate: 0.00032 +2024-11-23 05:27:18.744340: train_loss -0.8363 +2024-11-23 05:27:18.744613: val_loss -0.7609 +2024-11-23 05:27:18.744689: Pseudo dice [0.8511] +2024-11-23 05:27:18.744767: Epoch time: 19.06 s +2024-11-23 05:27:19.704283: +2024-11-23 05:27:19.704742: Epoch 7829 +2024-11-23 05:27:19.704876: Current learning rate: 0.00031 +2024-11-23 05:27:39.815664: train_loss -0.8469 +2024-11-23 05:27:39.815894: val_loss -0.7598 +2024-11-23 05:27:39.815972: Pseudo dice [0.8525] +2024-11-23 05:27:39.816061: Epoch time: 20.11 s +2024-11-23 05:27:40.755959: +2024-11-23 05:27:40.756387: Epoch 7830 +2024-11-23 05:27:40.756520: Current learning rate: 0.00031 +2024-11-23 05:28:00.196400: train_loss -0.8366 +2024-11-23 05:28:00.198841: val_loss -0.7955 +2024-11-23 05:28:00.198931: Pseudo dice [0.8828] +2024-11-23 05:28:00.199018: Epoch time: 19.44 s +2024-11-23 05:28:01.157440: +2024-11-23 05:28:01.157914: Epoch 7831 +2024-11-23 05:28:01.158055: Current learning rate: 0.00031 +2024-11-23 05:28:20.342247: train_loss -0.8414 +2024-11-23 05:28:20.342476: val_loss -0.7227 +2024-11-23 05:28:20.342580: Pseudo dice [0.8418] +2024-11-23 05:28:20.342696: Epoch time: 19.19 s +2024-11-23 05:28:21.302814: +2024-11-23 05:28:21.303251: Epoch 7832 +2024-11-23 05:28:21.303382: Current learning rate: 0.00031 +2024-11-23 05:28:39.954890: train_loss -0.8428 +2024-11-23 05:28:39.955120: val_loss -0.7662 +2024-11-23 05:28:39.955195: Pseudo dice [0.8615] +2024-11-23 05:28:39.955271: Epoch time: 18.65 s +2024-11-23 05:28:40.898306: +2024-11-23 05:28:40.898769: Epoch 7833 +2024-11-23 05:28:40.898908: Current learning rate: 0.00031 +2024-11-23 05:29:00.802107: train_loss -0.8329 +2024-11-23 05:29:00.802330: val_loss -0.7636 +2024-11-23 05:29:00.802403: Pseudo dice [0.8382] +2024-11-23 05:29:00.802481: Epoch time: 19.9 s +2024-11-23 05:29:01.734418: +2024-11-23 05:29:01.734869: Epoch 7834 +2024-11-23 05:29:01.735008: Current learning rate: 0.00031 +2024-11-23 05:29:20.704763: train_loss -0.8439 +2024-11-23 05:29:20.705047: val_loss -0.7679 +2024-11-23 05:29:20.705123: Pseudo dice [0.8383] +2024-11-23 05:29:20.705216: Epoch time: 18.97 s +2024-11-23 05:29:22.174933: +2024-11-23 05:29:22.175164: Epoch 7835 +2024-11-23 05:29:22.175278: Current learning rate: 0.0003 +2024-11-23 05:29:40.363240: train_loss -0.8395 +2024-11-23 05:29:40.363477: val_loss -0.7777 +2024-11-23 05:29:40.363553: Pseudo dice [0.8592] +2024-11-23 05:29:40.363633: Epoch time: 18.19 s +2024-11-23 05:29:41.325228: +2024-11-23 05:29:41.325467: Epoch 7836 +2024-11-23 05:29:41.325576: Current learning rate: 0.0003 +2024-11-23 05:29:59.465768: train_loss -0.8401 +2024-11-23 05:29:59.466008: val_loss -0.7615 +2024-11-23 05:29:59.466086: Pseudo dice [0.8534] +2024-11-23 05:29:59.466163: Epoch time: 18.14 s +2024-11-23 05:30:00.410072: +2024-11-23 05:30:00.410281: Epoch 7837 +2024-11-23 05:30:00.410395: Current learning rate: 0.0003 +2024-11-23 05:30:20.284346: train_loss -0.8333 +2024-11-23 05:30:20.284586: val_loss -0.745 +2024-11-23 05:30:20.284659: Pseudo dice [0.8583] +2024-11-23 05:30:20.284739: Epoch time: 19.88 s +2024-11-23 05:30:21.207771: +2024-11-23 05:30:21.208011: Epoch 7838 +2024-11-23 05:30:21.208133: Current learning rate: 0.0003 +2024-11-23 05:30:39.858656: train_loss -0.8365 +2024-11-23 05:30:39.861058: val_loss -0.765 +2024-11-23 05:30:39.861187: Pseudo dice [0.8447] +2024-11-23 05:30:39.861267: Epoch time: 18.65 s +2024-11-23 05:30:40.817338: +2024-11-23 05:30:40.817560: Epoch 7839 +2024-11-23 05:30:40.817668: Current learning rate: 0.0003 +2024-11-23 05:30:59.549916: train_loss -0.8392 +2024-11-23 05:30:59.552641: val_loss -0.7533 +2024-11-23 05:30:59.552739: Pseudo dice [0.8579] +2024-11-23 05:30:59.552820: Epoch time: 18.73 s +2024-11-23 05:31:00.726103: +2024-11-23 05:31:00.726320: Epoch 7840 +2024-11-23 05:31:00.726431: Current learning rate: 0.0003 +2024-11-23 05:31:19.161857: train_loss -0.841 +2024-11-23 05:31:19.162079: val_loss -0.7495 +2024-11-23 05:31:19.162302: Pseudo dice [0.8437] +2024-11-23 05:31:19.162384: Epoch time: 18.44 s +2024-11-23 05:31:20.095842: +2024-11-23 05:31:20.096069: Epoch 7841 +2024-11-23 05:31:20.096185: Current learning rate: 0.00029 +2024-11-23 05:31:37.843777: train_loss -0.8347 +2024-11-23 05:31:37.844037: val_loss -0.7418 +2024-11-23 05:31:37.844131: Pseudo dice [0.8341] +2024-11-23 05:31:37.844213: Epoch time: 17.75 s +2024-11-23 05:31:38.780649: +2024-11-23 05:31:38.780855: Epoch 7842 +2024-11-23 05:31:38.780970: Current learning rate: 0.00029 +2024-11-23 05:31:57.520218: train_loss -0.8403 +2024-11-23 05:31:57.522422: val_loss -0.7562 +2024-11-23 05:31:57.522626: Pseudo dice [0.8489] +2024-11-23 05:31:57.522744: Epoch time: 18.74 s +2024-11-23 05:31:58.544304: +2024-11-23 05:31:58.544501: Epoch 7843 +2024-11-23 05:31:58.544616: Current learning rate: 0.00029 +2024-11-23 05:32:17.763937: train_loss -0.8435 +2024-11-23 05:32:17.764189: val_loss -0.7683 +2024-11-23 05:32:17.764264: Pseudo dice [0.8734] +2024-11-23 05:32:17.764345: Epoch time: 19.22 s +2024-11-23 05:32:18.820458: +2024-11-23 05:32:18.820688: Epoch 7844 +2024-11-23 05:32:18.820810: Current learning rate: 0.00029 +2024-11-23 05:32:37.038615: train_loss -0.8453 +2024-11-23 05:32:37.038848: val_loss -0.7612 +2024-11-23 05:32:37.038924: Pseudo dice [0.8531] +2024-11-23 05:32:37.039014: Epoch time: 18.22 s +2024-11-23 05:32:38.031211: +2024-11-23 05:32:38.031464: Epoch 7845 +2024-11-23 05:32:38.031593: Current learning rate: 0.00029 +2024-11-23 05:32:55.183786: train_loss -0.8428 +2024-11-23 05:32:55.184038: val_loss -0.7608 +2024-11-23 05:32:55.184116: Pseudo dice [0.839] +2024-11-23 05:32:55.184207: Epoch time: 17.15 s +2024-11-23 05:32:56.139203: +2024-11-23 05:32:56.139444: Epoch 7846 +2024-11-23 05:32:56.139558: Current learning rate: 0.00029 +2024-11-23 05:33:14.725431: train_loss -0.8327 +2024-11-23 05:33:14.725689: val_loss -0.7671 +2024-11-23 05:33:14.725764: Pseudo dice [0.8539] +2024-11-23 05:33:14.725840: Epoch time: 18.59 s +2024-11-23 05:33:15.662920: +2024-11-23 05:33:15.663120: Epoch 7847 +2024-11-23 05:33:15.663229: Current learning rate: 0.00028 +2024-11-23 05:33:34.649652: train_loss -0.8407 +2024-11-23 05:33:34.649890: val_loss -0.7587 +2024-11-23 05:33:34.649966: Pseudo dice [0.8525] +2024-11-23 05:33:34.650054: Epoch time: 18.99 s +2024-11-23 05:33:35.586649: +2024-11-23 05:33:35.586873: Epoch 7848 +2024-11-23 05:33:35.586976: Current learning rate: 0.00028 +2024-11-23 05:33:54.073079: train_loss -0.8447 +2024-11-23 05:33:54.073353: val_loss -0.7723 +2024-11-23 05:33:54.073431: Pseudo dice [0.8601] +2024-11-23 05:33:54.073514: Epoch time: 18.49 s +2024-11-23 05:33:55.130864: +2024-11-23 05:33:55.131093: Epoch 7849 +2024-11-23 05:33:55.131207: Current learning rate: 0.00028 +2024-11-23 05:34:14.504645: train_loss -0.8439 +2024-11-23 05:34:14.504949: val_loss -0.7409 +2024-11-23 05:34:14.505047: Pseudo dice [0.8234] +2024-11-23 05:34:14.505131: Epoch time: 19.37 s +2024-11-23 05:34:15.929774: +2024-11-23 05:34:15.930005: Epoch 7850 +2024-11-23 05:34:15.930119: Current learning rate: 0.00028 +2024-11-23 05:34:34.742246: train_loss -0.8385 +2024-11-23 05:34:34.742488: val_loss -0.783 +2024-11-23 05:34:34.742563: Pseudo dice [0.8621] +2024-11-23 05:34:34.742643: Epoch time: 18.81 s +2024-11-23 05:34:35.687091: +2024-11-23 05:34:35.687315: Epoch 7851 +2024-11-23 05:34:35.687418: Current learning rate: 0.00028 +2024-11-23 05:34:53.777003: train_loss -0.8415 +2024-11-23 05:34:53.777241: val_loss -0.7685 +2024-11-23 05:34:53.777315: Pseudo dice [0.8587] +2024-11-23 05:34:53.778451: Epoch time: 18.09 s +2024-11-23 05:34:54.865132: +2024-11-23 05:34:54.865334: Epoch 7852 +2024-11-23 05:34:54.865439: Current learning rate: 0.00028 +2024-11-23 05:35:13.747118: train_loss -0.8498 +2024-11-23 05:35:13.747359: val_loss -0.7664 +2024-11-23 05:35:13.747434: Pseudo dice [0.8545] +2024-11-23 05:35:13.747535: Epoch time: 18.88 s +2024-11-23 05:35:14.686493: +2024-11-23 05:35:14.686704: Epoch 7853 +2024-11-23 05:35:14.686817: Current learning rate: 0.00027 +2024-11-23 05:35:34.723602: train_loss -0.8356 +2024-11-23 05:35:34.723822: val_loss -0.7864 +2024-11-23 05:35:34.723899: Pseudo dice [0.8565] +2024-11-23 05:35:34.723977: Epoch time: 20.04 s +2024-11-23 05:35:35.668310: +2024-11-23 05:35:35.668509: Epoch 7854 +2024-11-23 05:35:35.668621: Current learning rate: 0.00027 +2024-11-23 05:35:54.754356: train_loss -0.8311 +2024-11-23 05:35:54.754580: val_loss -0.7347 +2024-11-23 05:35:54.754657: Pseudo dice [0.8714] +2024-11-23 05:35:54.754800: Epoch time: 19.09 s +2024-11-23 05:35:55.677248: +2024-11-23 05:35:55.677457: Epoch 7855 +2024-11-23 05:35:55.677564: Current learning rate: 0.00027 +2024-11-23 05:36:14.171136: train_loss -0.8398 +2024-11-23 05:36:14.171393: val_loss -0.7688 +2024-11-23 05:36:14.171470: Pseudo dice [0.8592] +2024-11-23 05:36:14.171553: Epoch time: 18.49 s +2024-11-23 05:36:15.114783: +2024-11-23 05:36:15.115253: Epoch 7856 +2024-11-23 05:36:15.115389: Current learning rate: 0.00027 +2024-11-23 05:36:34.376196: train_loss -0.8343 +2024-11-23 05:36:34.376419: val_loss -0.7316 +2024-11-23 05:36:34.376491: Pseudo dice [0.8584] +2024-11-23 05:36:34.376567: Epoch time: 19.26 s +2024-11-23 05:36:35.690439: +2024-11-23 05:36:35.690648: Epoch 7857 +2024-11-23 05:36:35.690757: Current learning rate: 0.00027 +2024-11-23 05:36:53.516712: train_loss -0.8446 +2024-11-23 05:36:53.516950: val_loss -0.774 +2024-11-23 05:36:53.517035: Pseudo dice [0.8464] +2024-11-23 05:36:53.517113: Epoch time: 17.83 s +2024-11-23 05:36:54.455465: +2024-11-23 05:36:54.455669: Epoch 7858 +2024-11-23 05:36:54.455782: Current learning rate: 0.00027 +2024-11-23 05:37:13.385264: train_loss -0.8396 +2024-11-23 05:37:13.385572: val_loss -0.7569 +2024-11-23 05:37:13.385653: Pseudo dice [0.8797] +2024-11-23 05:37:13.385730: Epoch time: 18.93 s +2024-11-23 05:37:14.326910: +2024-11-23 05:37:14.327326: Epoch 7859 +2024-11-23 05:37:14.327437: Current learning rate: 0.00026 +2024-11-23 05:37:32.437592: train_loss -0.8405 +2024-11-23 05:37:32.437935: val_loss -0.7525 +2024-11-23 05:37:32.438029: Pseudo dice [0.8596] +2024-11-23 05:37:32.438121: Epoch time: 18.11 s +2024-11-23 05:37:33.380686: +2024-11-23 05:37:33.380911: Epoch 7860 +2024-11-23 05:37:33.381034: Current learning rate: 0.00026 +2024-11-23 05:37:50.963369: train_loss -0.8524 +2024-11-23 05:37:50.963597: val_loss -0.7452 +2024-11-23 05:37:50.963675: Pseudo dice [0.8773] +2024-11-23 05:37:50.963750: Epoch time: 17.58 s +2024-11-23 05:37:51.901333: +2024-11-23 05:37:51.901537: Epoch 7861 +2024-11-23 05:37:51.901642: Current learning rate: 0.00026 +2024-11-23 05:38:09.095876: train_loss -0.8399 +2024-11-23 05:38:09.096118: val_loss -0.7615 +2024-11-23 05:38:09.096192: Pseudo dice [0.8501] +2024-11-23 05:38:09.096267: Epoch time: 17.2 s +2024-11-23 05:38:10.031254: +2024-11-23 05:38:10.031458: Epoch 7862 +2024-11-23 05:38:10.031570: Current learning rate: 0.00026 +2024-11-23 05:38:28.446118: train_loss -0.847 +2024-11-23 05:38:28.446354: val_loss -0.7743 +2024-11-23 05:38:28.446429: Pseudo dice [0.8775] +2024-11-23 05:38:28.446507: Epoch time: 18.42 s +2024-11-23 05:38:29.536258: +2024-11-23 05:38:29.536470: Epoch 7863 +2024-11-23 05:38:29.536579: Current learning rate: 0.00026 +2024-11-23 05:38:47.603440: train_loss -0.8462 +2024-11-23 05:38:47.603690: val_loss -0.7316 +2024-11-23 05:38:47.603766: Pseudo dice [0.8635] +2024-11-23 05:38:47.603851: Epoch time: 18.07 s +2024-11-23 05:38:48.544242: +2024-11-23 05:38:48.544586: Epoch 7864 +2024-11-23 05:38:48.544697: Current learning rate: 0.00026 +2024-11-23 05:39:08.842592: train_loss -0.8454 +2024-11-23 05:39:08.842810: val_loss -0.7534 +2024-11-23 05:39:08.842888: Pseudo dice [0.8489] +2024-11-23 05:39:08.842966: Epoch time: 20.3 s +2024-11-23 05:39:09.774767: +2024-11-23 05:39:09.774989: Epoch 7865 +2024-11-23 05:39:09.775112: Current learning rate: 0.00025 +2024-11-23 05:39:28.617880: train_loss -0.8398 +2024-11-23 05:39:28.618102: val_loss -0.7373 +2024-11-23 05:39:28.618179: Pseudo dice [0.8516] +2024-11-23 05:39:28.618257: Epoch time: 18.84 s +2024-11-23 05:39:29.548117: +2024-11-23 05:39:29.548335: Epoch 7866 +2024-11-23 05:39:29.548450: Current learning rate: 0.00025 +2024-11-23 05:39:48.146323: train_loss -0.8392 +2024-11-23 05:39:48.146608: val_loss -0.7458 +2024-11-23 05:39:48.146818: Pseudo dice [0.8325] +2024-11-23 05:39:48.146908: Epoch time: 18.6 s +2024-11-23 05:39:49.089552: +2024-11-23 05:39:49.089767: Epoch 7867 +2024-11-23 05:39:49.089887: Current learning rate: 0.00025 +2024-11-23 05:40:07.867888: train_loss -0.843 +2024-11-23 05:40:07.873282: val_loss -0.7722 +2024-11-23 05:40:07.873426: Pseudo dice [0.8482] +2024-11-23 05:40:07.873513: Epoch time: 18.78 s +2024-11-23 05:40:08.917614: +2024-11-23 05:40:08.917817: Epoch 7868 +2024-11-23 05:40:08.917933: Current learning rate: 0.00025 +2024-11-23 05:40:27.453316: train_loss -0.8447 +2024-11-23 05:40:27.453530: val_loss -0.7577 +2024-11-23 05:40:27.453609: Pseudo dice [0.8635] +2024-11-23 05:40:27.453687: Epoch time: 18.54 s +2024-11-23 05:40:28.684361: +2024-11-23 05:40:28.684592: Epoch 7869 +2024-11-23 05:40:28.684707: Current learning rate: 0.00025 +2024-11-23 05:40:46.556905: train_loss -0.8369 +2024-11-23 05:40:46.557170: val_loss -0.7615 +2024-11-23 05:40:46.557250: Pseudo dice [0.8574] +2024-11-23 05:40:46.557334: Epoch time: 17.87 s +2024-11-23 05:40:47.498372: +2024-11-23 05:40:47.498600: Epoch 7870 +2024-11-23 05:40:47.498710: Current learning rate: 0.00025 +2024-11-23 05:41:06.955622: train_loss -0.8431 +2024-11-23 05:41:06.955881: val_loss -0.7725 +2024-11-23 05:41:06.955983: Pseudo dice [0.8688] +2024-11-23 05:41:06.956075: Epoch time: 19.46 s +2024-11-23 05:41:07.875367: +2024-11-23 05:41:07.875582: Epoch 7871 +2024-11-23 05:41:07.875692: Current learning rate: 0.00024 +2024-11-23 05:41:26.011962: train_loss -0.841 +2024-11-23 05:41:26.012198: val_loss -0.7636 +2024-11-23 05:41:26.012275: Pseudo dice [0.828] +2024-11-23 05:41:26.012352: Epoch time: 18.14 s +2024-11-23 05:41:26.944699: +2024-11-23 05:41:26.944932: Epoch 7872 +2024-11-23 05:41:26.945042: Current learning rate: 0.00024 +2024-11-23 05:41:45.899187: train_loss -0.8421 +2024-11-23 05:41:45.899453: val_loss -0.7543 +2024-11-23 05:41:45.899560: Pseudo dice [0.8647] +2024-11-23 05:41:45.899637: Epoch time: 18.96 s +2024-11-23 05:41:46.843601: +2024-11-23 05:41:46.843827: Epoch 7873 +2024-11-23 05:41:46.843942: Current learning rate: 0.00024 +2024-11-23 05:42:05.490036: train_loss -0.8428 +2024-11-23 05:42:05.490285: val_loss -0.7707 +2024-11-23 05:42:05.490361: Pseudo dice [0.8478] +2024-11-23 05:42:05.492349: Epoch time: 18.65 s +2024-11-23 05:42:06.443452: +2024-11-23 05:42:06.443690: Epoch 7874 +2024-11-23 05:42:06.443799: Current learning rate: 0.00024 +2024-11-23 05:42:25.627417: train_loss -0.8449 +2024-11-23 05:42:25.629832: val_loss -0.7711 +2024-11-23 05:42:25.629914: Pseudo dice [0.8661] +2024-11-23 05:42:25.630003: Epoch time: 19.18 s +2024-11-23 05:42:26.653834: +2024-11-23 05:42:26.654034: Epoch 7875 +2024-11-23 05:42:26.654170: Current learning rate: 0.00024 +2024-11-23 05:42:45.961295: train_loss -0.833 +2024-11-23 05:42:45.961521: val_loss -0.7758 +2024-11-23 05:42:45.961602: Pseudo dice [0.8447] +2024-11-23 05:42:45.961680: Epoch time: 19.31 s +2024-11-23 05:42:46.893379: +2024-11-23 05:42:46.893589: Epoch 7876 +2024-11-23 05:42:46.893700: Current learning rate: 0.00024 +2024-11-23 05:43:05.519363: train_loss -0.8412 +2024-11-23 05:43:05.519583: val_loss -0.7565 +2024-11-23 05:43:05.519657: Pseudo dice [0.8621] +2024-11-23 05:43:05.519733: Epoch time: 18.63 s +2024-11-23 05:43:06.459014: +2024-11-23 05:43:06.459212: Epoch 7877 +2024-11-23 05:43:06.459323: Current learning rate: 0.00023 +2024-11-23 05:43:23.981879: train_loss -0.8362 +2024-11-23 05:43:23.982150: val_loss -0.73 +2024-11-23 05:43:23.982226: Pseudo dice [0.8465] +2024-11-23 05:43:23.982299: Epoch time: 17.52 s +2024-11-23 05:43:24.929425: +2024-11-23 05:43:24.929644: Epoch 7878 +2024-11-23 05:43:24.929761: Current learning rate: 0.00023 +2024-11-23 05:43:45.265745: train_loss -0.8401 +2024-11-23 05:43:45.265987: val_loss -0.7819 +2024-11-23 05:43:45.266071: Pseudo dice [0.8548] +2024-11-23 05:43:45.266156: Epoch time: 20.34 s +2024-11-23 05:43:46.200497: +2024-11-23 05:43:46.200708: Epoch 7879 +2024-11-23 05:43:46.200819: Current learning rate: 0.00023 +2024-11-23 05:44:05.747381: train_loss -0.842 +2024-11-23 05:44:05.747616: val_loss -0.7303 +2024-11-23 05:44:05.747689: Pseudo dice [0.8558] +2024-11-23 05:44:05.747764: Epoch time: 19.55 s +2024-11-23 05:44:07.057516: +2024-11-23 05:44:07.057789: Epoch 7880 +2024-11-23 05:44:07.057907: Current learning rate: 0.00023 +2024-11-23 05:44:25.845727: train_loss -0.8479 +2024-11-23 05:44:25.845963: val_loss -0.7606 +2024-11-23 05:44:25.846043: Pseudo dice [0.8544] +2024-11-23 05:44:25.846119: Epoch time: 18.79 s +2024-11-23 05:44:26.784943: +2024-11-23 05:44:26.785208: Epoch 7881 +2024-11-23 05:44:26.785321: Current learning rate: 0.00023 +2024-11-23 05:44:45.197691: train_loss -0.842 +2024-11-23 05:44:45.198011: val_loss -0.7551 +2024-11-23 05:44:45.198092: Pseudo dice [0.8523] +2024-11-23 05:44:45.198174: Epoch time: 18.41 s +2024-11-23 05:44:46.163562: +2024-11-23 05:44:46.163814: Epoch 7882 +2024-11-23 05:44:46.163923: Current learning rate: 0.00022 +2024-11-23 05:45:04.610240: train_loss -0.8402 +2024-11-23 05:45:04.610470: val_loss -0.7259 +2024-11-23 05:45:04.610543: Pseudo dice [0.819] +2024-11-23 05:45:04.610621: Epoch time: 18.45 s +2024-11-23 05:45:05.550565: +2024-11-23 05:45:05.550786: Epoch 7883 +2024-11-23 05:45:05.550887: Current learning rate: 0.00022 +2024-11-23 05:45:24.397695: train_loss -0.8441 +2024-11-23 05:45:24.397973: val_loss -0.7697 +2024-11-23 05:45:24.398059: Pseudo dice [0.8474] +2024-11-23 05:45:24.398134: Epoch time: 18.85 s +2024-11-23 05:45:25.326830: +2024-11-23 05:45:25.327060: Epoch 7884 +2024-11-23 05:45:25.327178: Current learning rate: 0.00022 +2024-11-23 05:45:43.162056: train_loss -0.845 +2024-11-23 05:45:43.162283: val_loss -0.7545 +2024-11-23 05:45:43.162359: Pseudo dice [0.8587] +2024-11-23 05:45:43.162434: Epoch time: 17.84 s +2024-11-23 05:45:44.083122: +2024-11-23 05:45:44.083333: Epoch 7885 +2024-11-23 05:45:44.083442: Current learning rate: 0.00022 +2024-11-23 05:46:03.138130: train_loss -0.8484 +2024-11-23 05:46:03.138353: val_loss -0.7455 +2024-11-23 05:46:03.138428: Pseudo dice [0.8557] +2024-11-23 05:46:03.138511: Epoch time: 19.06 s +2024-11-23 05:46:04.054368: +2024-11-23 05:46:04.054595: Epoch 7886 +2024-11-23 05:46:04.054718: Current learning rate: 0.00022 +2024-11-23 05:46:21.345320: train_loss -0.8475 +2024-11-23 05:46:21.345639: val_loss -0.7473 +2024-11-23 05:46:21.345719: Pseudo dice [0.8659] +2024-11-23 05:46:21.345800: Epoch time: 17.29 s +2024-11-23 05:46:22.286993: +2024-11-23 05:46:22.287199: Epoch 7887 +2024-11-23 05:46:22.287309: Current learning rate: 0.00022 +2024-11-23 05:46:39.930815: train_loss -0.8439 +2024-11-23 05:46:39.936258: val_loss -0.7623 +2024-11-23 05:46:39.936417: Pseudo dice [0.8492] +2024-11-23 05:46:39.936543: Epoch time: 17.64 s +2024-11-23 05:46:41.063888: +2024-11-23 05:46:41.064100: Epoch 7888 +2024-11-23 05:46:41.064227: Current learning rate: 0.00021 +2024-11-23 05:46:59.834342: train_loss -0.8458 +2024-11-23 05:46:59.836210: val_loss -0.7347 +2024-11-23 05:46:59.836305: Pseudo dice [0.8402] +2024-11-23 05:46:59.836390: Epoch time: 18.77 s +2024-11-23 05:47:00.768007: +2024-11-23 05:47:00.768212: Epoch 7889 +2024-11-23 05:47:00.768325: Current learning rate: 0.00021 +2024-11-23 05:47:18.822215: train_loss -0.8387 +2024-11-23 05:47:18.822456: val_loss -0.7601 +2024-11-23 05:47:18.822539: Pseudo dice [0.8604] +2024-11-23 05:47:18.822621: Epoch time: 18.05 s +2024-11-23 05:47:19.755124: +2024-11-23 05:47:19.755377: Epoch 7890 +2024-11-23 05:47:19.755491: Current learning rate: 0.00021 +2024-11-23 05:47:38.940125: train_loss -0.8398 +2024-11-23 05:47:38.940340: val_loss -0.731 +2024-11-23 05:47:38.940411: Pseudo dice [0.8447] +2024-11-23 05:47:38.940487: Epoch time: 19.19 s +2024-11-23 05:47:40.363838: +2024-11-23 05:47:40.364074: Epoch 7891 +2024-11-23 05:47:40.364190: Current learning rate: 0.00021 +2024-11-23 05:47:59.611310: train_loss -0.841 +2024-11-23 05:47:59.611552: val_loss -0.7724 +2024-11-23 05:47:59.611628: Pseudo dice [0.8599] +2024-11-23 05:47:59.611712: Epoch time: 19.25 s +2024-11-23 05:48:00.572382: +2024-11-23 05:48:00.572607: Epoch 7892 +2024-11-23 05:48:00.572718: Current learning rate: 0.00021 +2024-11-23 05:48:19.074213: train_loss -0.8398 +2024-11-23 05:48:19.074605: val_loss -0.7525 +2024-11-23 05:48:19.074691: Pseudo dice [0.8563] +2024-11-23 05:48:19.074771: Epoch time: 18.5 s +2024-11-23 05:48:20.095372: +2024-11-23 05:48:20.095597: Epoch 7893 +2024-11-23 05:48:20.095711: Current learning rate: 0.00021 +2024-11-23 05:48:40.375921: train_loss -0.8355 +2024-11-23 05:48:40.380757: val_loss -0.7441 +2024-11-23 05:48:40.380872: Pseudo dice [0.8445] +2024-11-23 05:48:40.380960: Epoch time: 20.28 s +2024-11-23 05:48:41.321407: +2024-11-23 05:48:41.321617: Epoch 7894 +2024-11-23 05:48:41.321726: Current learning rate: 0.0002 +2024-11-23 05:49:00.496218: train_loss -0.8463 +2024-11-23 05:49:00.496440: val_loss -0.7643 +2024-11-23 05:49:00.496516: Pseudo dice [0.8599] +2024-11-23 05:49:00.496592: Epoch time: 19.18 s +2024-11-23 05:49:01.415377: +2024-11-23 05:49:01.415643: Epoch 7895 +2024-11-23 05:49:01.415754: Current learning rate: 0.0002 +2024-11-23 05:49:19.853974: train_loss -0.8497 +2024-11-23 05:49:19.854205: val_loss -0.7536 +2024-11-23 05:49:19.854281: Pseudo dice [0.8506] +2024-11-23 05:49:19.854357: Epoch time: 18.44 s +2024-11-23 05:49:20.994395: +2024-11-23 05:49:20.994599: Epoch 7896 +2024-11-23 05:49:20.994712: Current learning rate: 0.0002 +2024-11-23 05:49:39.306940: train_loss -0.8355 +2024-11-23 05:49:39.307165: val_loss -0.7676 +2024-11-23 05:49:39.307243: Pseudo dice [0.8555] +2024-11-23 05:49:39.307326: Epoch time: 18.31 s +2024-11-23 05:49:40.232356: +2024-11-23 05:49:40.232543: Epoch 7897 +2024-11-23 05:49:40.232652: Current learning rate: 0.0002 +2024-11-23 05:49:58.356462: train_loss -0.8453 +2024-11-23 05:49:58.356764: val_loss -0.7447 +2024-11-23 05:49:58.356843: Pseudo dice [0.8731] +2024-11-23 05:49:58.356921: Epoch time: 18.12 s +2024-11-23 05:49:59.278318: +2024-11-23 05:49:59.278511: Epoch 7898 +2024-11-23 05:49:59.278622: Current learning rate: 0.0002 +2024-11-23 05:50:17.493102: train_loss -0.8471 +2024-11-23 05:50:17.493313: val_loss -0.7502 +2024-11-23 05:50:17.493387: Pseudo dice [0.8508] +2024-11-23 05:50:17.493462: Epoch time: 18.22 s +2024-11-23 05:50:18.526664: +2024-11-23 05:50:18.526861: Epoch 7899 +2024-11-23 05:50:18.526971: Current learning rate: 0.0002 +2024-11-23 05:50:37.317266: train_loss -0.8417 +2024-11-23 05:50:37.317481: val_loss -0.7657 +2024-11-23 05:50:37.317554: Pseudo dice [0.8824] +2024-11-23 05:50:37.317629: Epoch time: 18.79 s +2024-11-23 05:50:38.632707: +2024-11-23 05:50:38.632940: Epoch 7900 +2024-11-23 05:50:38.633059: Current learning rate: 0.00019 +2024-11-23 05:50:57.932879: train_loss -0.8395 +2024-11-23 05:50:57.933136: val_loss -0.7635 +2024-11-23 05:50:57.933211: Pseudo dice [0.8626] +2024-11-23 05:50:57.933295: Epoch time: 19.3 s +2024-11-23 05:50:58.875999: +2024-11-23 05:50:58.876224: Epoch 7901 +2024-11-23 05:50:58.876338: Current learning rate: 0.00019 +2024-11-23 05:51:17.331098: train_loss -0.8387 +2024-11-23 05:51:17.333487: val_loss -0.7774 +2024-11-23 05:51:17.333578: Pseudo dice [0.8614] +2024-11-23 05:51:17.333655: Epoch time: 18.46 s +2024-11-23 05:51:18.748527: +2024-11-23 05:51:18.748749: Epoch 7902 +2024-11-23 05:51:18.748864: Current learning rate: 0.00019 +2024-11-23 05:51:36.666467: train_loss -0.8374 +2024-11-23 05:51:36.666676: val_loss -0.7379 +2024-11-23 05:51:36.666749: Pseudo dice [0.8518] +2024-11-23 05:51:36.666825: Epoch time: 17.92 s +2024-11-23 05:51:37.578643: +2024-11-23 05:51:37.578874: Epoch 7903 +2024-11-23 05:51:37.578989: Current learning rate: 0.00019 +2024-11-23 05:51:55.567000: train_loss -0.8428 +2024-11-23 05:51:55.567221: val_loss -0.7647 +2024-11-23 05:51:55.567294: Pseudo dice [0.8645] +2024-11-23 05:51:55.567372: Epoch time: 17.99 s +2024-11-23 05:51:56.533678: +2024-11-23 05:51:56.533913: Epoch 7904 +2024-11-23 05:51:56.534029: Current learning rate: 0.00019 +2024-11-23 05:52:15.696282: train_loss -0.8392 +2024-11-23 05:52:15.696515: val_loss -0.7693 +2024-11-23 05:52:15.696591: Pseudo dice [0.8598] +2024-11-23 05:52:15.696670: Epoch time: 19.16 s +2024-11-23 05:52:16.625535: +2024-11-23 05:52:16.625764: Epoch 7905 +2024-11-23 05:52:16.625875: Current learning rate: 0.00018 +2024-11-23 05:52:35.288570: train_loss -0.8416 +2024-11-23 05:52:35.288771: val_loss -0.7728 +2024-11-23 05:52:35.288848: Pseudo dice [0.8628] +2024-11-23 05:52:35.288924: Epoch time: 18.66 s +2024-11-23 05:52:36.217130: +2024-11-23 05:52:36.217347: Epoch 7906 +2024-11-23 05:52:36.217459: Current learning rate: 0.00018 +2024-11-23 05:52:55.315876: train_loss -0.836 +2024-11-23 05:52:55.316110: val_loss -0.7413 +2024-11-23 05:52:55.316182: Pseudo dice [0.8235] +2024-11-23 05:52:55.316259: Epoch time: 19.1 s +2024-11-23 05:52:56.257767: +2024-11-23 05:52:56.258029: Epoch 7907 +2024-11-23 05:52:56.258140: Current learning rate: 0.00018 +2024-11-23 05:53:15.446581: train_loss -0.8322 +2024-11-23 05:53:15.446806: val_loss -0.7672 +2024-11-23 05:53:15.446879: Pseudo dice [0.8569] +2024-11-23 05:53:15.446965: Epoch time: 19.19 s +2024-11-23 05:53:16.400743: +2024-11-23 05:53:16.400959: Epoch 7908 +2024-11-23 05:53:16.401079: Current learning rate: 0.00018 +2024-11-23 05:53:34.737777: train_loss -0.846 +2024-11-23 05:53:34.738065: val_loss -0.7625 +2024-11-23 05:53:34.738144: Pseudo dice [0.858] +2024-11-23 05:53:34.738225: Epoch time: 18.34 s +2024-11-23 05:53:35.675831: +2024-11-23 05:53:35.676032: Epoch 7909 +2024-11-23 05:53:35.676142: Current learning rate: 0.00018 +2024-11-23 05:53:53.364947: train_loss -0.8388 +2024-11-23 05:53:53.365165: val_loss -0.7425 +2024-11-23 05:53:53.365244: Pseudo dice [0.8562] +2024-11-23 05:53:53.365324: Epoch time: 17.69 s +2024-11-23 05:53:54.301971: +2024-11-23 05:53:54.302208: Epoch 7910 +2024-11-23 05:53:54.302319: Current learning rate: 0.00018 +2024-11-23 05:54:12.171838: train_loss -0.8435 +2024-11-23 05:54:12.172068: val_loss -0.7455 +2024-11-23 05:54:12.177308: Pseudo dice [0.8761] +2024-11-23 05:54:12.177460: Epoch time: 17.87 s +2024-11-23 05:54:13.137307: +2024-11-23 05:54:13.137652: Epoch 7911 +2024-11-23 05:54:13.137764: Current learning rate: 0.00017 +2024-11-23 05:54:33.019846: train_loss -0.8455 +2024-11-23 05:54:33.020089: val_loss -0.7866 +2024-11-23 05:54:33.020164: Pseudo dice [0.8559] +2024-11-23 05:54:33.020245: Epoch time: 19.88 s +2024-11-23 05:54:33.988497: +2024-11-23 05:54:33.988779: Epoch 7912 +2024-11-23 05:54:33.988897: Current learning rate: 0.00017 +2024-11-23 05:54:51.821159: train_loss -0.8487 +2024-11-23 05:54:51.821400: val_loss -0.7349 +2024-11-23 05:54:51.821474: Pseudo dice [0.8597] +2024-11-23 05:54:51.821549: Epoch time: 17.83 s +2024-11-23 05:54:53.123701: +2024-11-23 05:54:53.123932: Epoch 7913 +2024-11-23 05:54:53.124051: Current learning rate: 0.00017 +2024-11-23 05:55:12.243678: train_loss -0.8428 +2024-11-23 05:55:12.243915: val_loss -0.7592 +2024-11-23 05:55:12.243999: Pseudo dice [0.8574] +2024-11-23 05:55:12.244078: Epoch time: 19.12 s +2024-11-23 05:55:13.201678: +2024-11-23 05:55:13.201891: Epoch 7914 +2024-11-23 05:55:13.202007: Current learning rate: 0.00017 +2024-11-23 05:55:31.598701: train_loss -0.8408 +2024-11-23 05:55:31.598928: val_loss -0.7735 +2024-11-23 05:55:31.599008: Pseudo dice [0.8476] +2024-11-23 05:55:31.599086: Epoch time: 18.4 s +2024-11-23 05:55:32.537097: +2024-11-23 05:55:32.537309: Epoch 7915 +2024-11-23 05:55:32.537420: Current learning rate: 0.00017 +2024-11-23 05:55:50.433585: train_loss -0.8457 +2024-11-23 05:55:50.433826: val_loss -0.7664 +2024-11-23 05:55:50.433899: Pseudo dice [0.8468] +2024-11-23 05:55:50.433982: Epoch time: 17.9 s +2024-11-23 05:55:51.376503: +2024-11-23 05:55:51.376747: Epoch 7916 +2024-11-23 05:55:51.376863: Current learning rate: 0.00017 +2024-11-23 05:56:09.109810: train_loss -0.8371 +2024-11-23 05:56:09.110034: val_loss -0.7598 +2024-11-23 05:56:09.110112: Pseudo dice [0.8596] +2024-11-23 05:56:09.110215: Epoch time: 17.73 s +2024-11-23 05:56:10.047504: +2024-11-23 05:56:10.047718: Epoch 7917 +2024-11-23 05:56:10.047832: Current learning rate: 0.00016 +2024-11-23 05:56:28.792742: train_loss -0.8352 +2024-11-23 05:56:28.792958: val_loss -0.7832 +2024-11-23 05:56:28.793043: Pseudo dice [0.8778] +2024-11-23 05:56:28.793126: Epoch time: 18.75 s +2024-11-23 05:56:29.734834: +2024-11-23 05:56:29.735064: Epoch 7918 +2024-11-23 05:56:29.735175: Current learning rate: 0.00016 +2024-11-23 05:56:49.140787: train_loss -0.8368 +2024-11-23 05:56:49.141237: val_loss -0.7727 +2024-11-23 05:56:49.141332: Pseudo dice [0.8389] +2024-11-23 05:56:49.141413: Epoch time: 19.41 s +2024-11-23 05:56:50.082821: +2024-11-23 05:56:50.083027: Epoch 7919 +2024-11-23 05:56:50.083136: Current learning rate: 0.00016 +2024-11-23 05:57:08.754511: train_loss -0.8449 +2024-11-23 05:57:08.754748: val_loss -0.7473 +2024-11-23 05:57:08.754825: Pseudo dice [0.8594] +2024-11-23 05:57:08.754914: Epoch time: 18.67 s +2024-11-23 05:57:09.695726: +2024-11-23 05:57:09.695951: Epoch 7920 +2024-11-23 05:57:09.696073: Current learning rate: 0.00016 +2024-11-23 05:57:28.251012: train_loss -0.846 +2024-11-23 05:57:28.251334: val_loss -0.755 +2024-11-23 05:57:28.251418: Pseudo dice [0.8665] +2024-11-23 05:57:28.251495: Epoch time: 18.56 s +2024-11-23 05:57:29.185139: +2024-11-23 05:57:29.185402: Epoch 7921 +2024-11-23 05:57:29.185521: Current learning rate: 0.00016 +2024-11-23 05:57:47.794354: train_loss -0.8489 +2024-11-23 05:57:47.794578: val_loss -0.7939 +2024-11-23 05:57:47.794657: Pseudo dice [0.8533] +2024-11-23 05:57:47.794732: Epoch time: 18.61 s +2024-11-23 05:57:48.791528: +2024-11-23 05:57:48.791725: Epoch 7922 +2024-11-23 05:57:48.791837: Current learning rate: 0.00015 +2024-11-23 05:58:07.291041: train_loss -0.8392 +2024-11-23 05:58:07.291258: val_loss -0.7478 +2024-11-23 05:58:07.291334: Pseudo dice [0.8544] +2024-11-23 05:58:07.291418: Epoch time: 18.5 s +2024-11-23 05:58:08.440547: +2024-11-23 05:58:08.440756: Epoch 7923 +2024-11-23 05:58:08.440869: Current learning rate: 0.00015 +2024-11-23 05:58:28.332574: train_loss -0.84 +2024-11-23 05:58:28.332805: val_loss -0.7705 +2024-11-23 05:58:28.332876: Pseudo dice [0.8767] +2024-11-23 05:58:28.332953: Epoch time: 19.89 s +2024-11-23 05:58:29.303139: +2024-11-23 05:58:29.303355: Epoch 7924 +2024-11-23 05:58:29.303466: Current learning rate: 0.00015 +2024-11-23 05:58:48.291484: train_loss -0.8451 +2024-11-23 05:58:48.291697: val_loss -0.7528 +2024-11-23 05:58:48.291771: Pseudo dice [0.857] +2024-11-23 05:58:48.291847: Epoch time: 18.99 s +2024-11-23 05:58:49.615836: +2024-11-23 05:58:49.616039: Epoch 7925 +2024-11-23 05:58:49.616148: Current learning rate: 0.00015 +2024-11-23 05:59:08.814844: train_loss -0.8424 +2024-11-23 05:59:08.815138: val_loss -0.7374 +2024-11-23 05:59:08.815218: Pseudo dice [0.8491] +2024-11-23 05:59:08.815296: Epoch time: 19.19 s +2024-11-23 05:59:09.868268: +2024-11-23 05:59:09.868521: Epoch 7926 +2024-11-23 05:59:09.868633: Current learning rate: 0.00015 +2024-11-23 05:59:27.718223: train_loss -0.8444 +2024-11-23 05:59:27.718471: val_loss -0.7454 +2024-11-23 05:59:27.718545: Pseudo dice [0.8547] +2024-11-23 05:59:27.718627: Epoch time: 17.85 s +2024-11-23 05:59:28.831502: +2024-11-23 05:59:28.831724: Epoch 7927 +2024-11-23 05:59:28.831836: Current learning rate: 0.00015 +2024-11-23 05:59:47.827905: train_loss -0.8461 +2024-11-23 05:59:47.828132: val_loss -0.7599 +2024-11-23 05:59:47.828217: Pseudo dice [0.8526] +2024-11-23 05:59:47.828295: Epoch time: 19.0 s +2024-11-23 05:59:48.960141: +2024-11-23 05:59:48.960406: Epoch 7928 +2024-11-23 05:59:48.960521: Current learning rate: 0.00014 +2024-11-23 06:00:07.281507: train_loss -0.8382 +2024-11-23 06:00:07.281711: val_loss -0.7449 +2024-11-23 06:00:07.281785: Pseudo dice [0.8444] +2024-11-23 06:00:07.281866: Epoch time: 18.32 s +2024-11-23 06:00:08.314608: +2024-11-23 06:00:08.314830: Epoch 7929 +2024-11-23 06:00:08.314943: Current learning rate: 0.00014 +2024-11-23 06:00:26.019712: train_loss -0.84 +2024-11-23 06:00:26.019921: val_loss -0.7554 +2024-11-23 06:00:26.020002: Pseudo dice [0.8758] +2024-11-23 06:00:26.020079: Epoch time: 17.71 s +2024-11-23 06:00:26.958689: +2024-11-23 06:00:26.958911: Epoch 7930 +2024-11-23 06:00:26.959036: Current learning rate: 0.00014 +2024-11-23 06:00:44.956253: train_loss -0.8413 +2024-11-23 06:00:44.956492: val_loss -0.7533 +2024-11-23 06:00:44.956565: Pseudo dice [0.8443] +2024-11-23 06:00:44.956647: Epoch time: 18.0 s +2024-11-23 06:00:45.923852: +2024-11-23 06:00:45.924083: Epoch 7931 +2024-11-23 06:00:45.924196: Current learning rate: 0.00014 +2024-11-23 06:01:05.245162: train_loss -0.8435 +2024-11-23 06:01:05.245368: val_loss -0.7601 +2024-11-23 06:01:05.245443: Pseudo dice [0.8644] +2024-11-23 06:01:05.245519: Epoch time: 19.32 s +2024-11-23 06:01:06.181862: +2024-11-23 06:01:06.182087: Epoch 7932 +2024-11-23 06:01:06.182199: Current learning rate: 0.00014 +2024-11-23 06:01:24.761417: train_loss -0.8456 +2024-11-23 06:01:24.761626: val_loss -0.7534 +2024-11-23 06:01:24.761699: Pseudo dice [0.8694] +2024-11-23 06:01:24.761771: Epoch time: 18.58 s +2024-11-23 06:01:25.728314: +2024-11-23 06:01:25.728542: Epoch 7933 +2024-11-23 06:01:25.728651: Current learning rate: 0.00014 +2024-11-23 06:01:44.886112: train_loss -0.845 +2024-11-23 06:01:44.886322: val_loss -0.7634 +2024-11-23 06:01:44.886403: Pseudo dice [0.8604] +2024-11-23 06:01:44.886479: Epoch time: 19.16 s +2024-11-23 06:01:45.823973: +2024-11-23 06:01:45.824207: Epoch 7934 +2024-11-23 06:01:45.824330: Current learning rate: 0.00013 +2024-11-23 06:02:03.603925: train_loss -0.8488 +2024-11-23 06:02:03.604177: val_loss -0.7836 +2024-11-23 06:02:03.604254: Pseudo dice [0.8375] +2024-11-23 06:02:03.604334: Epoch time: 17.78 s +2024-11-23 06:02:04.543895: +2024-11-23 06:02:04.544100: Epoch 7935 +2024-11-23 06:02:04.544209: Current learning rate: 0.00013 +2024-11-23 06:02:22.132268: train_loss -0.8505 +2024-11-23 06:02:22.132485: val_loss -0.7718 +2024-11-23 06:02:22.132564: Pseudo dice [0.8537] +2024-11-23 06:02:22.132646: Epoch time: 17.59 s +2024-11-23 06:02:23.465510: +2024-11-23 06:02:23.465743: Epoch 7936 +2024-11-23 06:02:23.465854: Current learning rate: 0.00013 +2024-11-23 06:02:42.050288: train_loss -0.8432 +2024-11-23 06:02:42.050522: val_loss -0.7822 +2024-11-23 06:02:42.050596: Pseudo dice [0.8604] +2024-11-23 06:02:42.050672: Epoch time: 18.59 s +2024-11-23 06:02:42.985683: +2024-11-23 06:02:42.986008: Epoch 7937 +2024-11-23 06:02:42.986121: Current learning rate: 0.00013 +2024-11-23 06:03:01.523448: train_loss -0.8418 +2024-11-23 06:03:01.523692: val_loss -0.762 +2024-11-23 06:03:01.523765: Pseudo dice [0.8532] +2024-11-23 06:03:01.523849: Epoch time: 18.54 s +2024-11-23 06:03:02.493443: +2024-11-23 06:03:02.493683: Epoch 7938 +2024-11-23 06:03:02.493795: Current learning rate: 0.00013 +2024-11-23 06:03:20.018177: train_loss -0.8487 +2024-11-23 06:03:20.018405: val_loss -0.7418 +2024-11-23 06:03:20.018482: Pseudo dice [0.8341] +2024-11-23 06:03:20.018562: Epoch time: 17.52 s +2024-11-23 06:03:20.974914: +2024-11-23 06:03:20.975156: Epoch 7939 +2024-11-23 06:03:20.975273: Current learning rate: 0.00012 +2024-11-23 06:03:39.817974: train_loss -0.8439 +2024-11-23 06:03:39.818197: val_loss -0.7763 +2024-11-23 06:03:39.818274: Pseudo dice [0.8381] +2024-11-23 06:03:39.818348: Epoch time: 18.84 s +2024-11-23 06:03:40.822956: +2024-11-23 06:03:40.823178: Epoch 7940 +2024-11-23 06:03:40.823290: Current learning rate: 0.00012 +2024-11-23 06:03:58.830363: train_loss -0.8384 +2024-11-23 06:03:58.830580: val_loss -0.7715 +2024-11-23 06:03:58.830656: Pseudo dice [0.8597] +2024-11-23 06:03:58.830741: Epoch time: 18.01 s +2024-11-23 06:03:59.903212: +2024-11-23 06:03:59.903448: Epoch 7941 +2024-11-23 06:03:59.903566: Current learning rate: 0.00012 +2024-11-23 06:04:18.927573: train_loss -0.8451 +2024-11-23 06:04:18.927818: val_loss -0.7811 +2024-11-23 06:04:18.927892: Pseudo dice [0.8489] +2024-11-23 06:04:18.927976: Epoch time: 19.03 s +2024-11-23 06:04:19.869080: +2024-11-23 06:04:19.869274: Epoch 7942 +2024-11-23 06:04:19.869382: Current learning rate: 0.00012 +2024-11-23 06:04:37.483511: train_loss -0.8377 +2024-11-23 06:04:37.483727: val_loss -0.7579 +2024-11-23 06:04:37.483801: Pseudo dice [0.8572] +2024-11-23 06:04:37.483877: Epoch time: 17.62 s +2024-11-23 06:04:38.419597: +2024-11-23 06:04:38.419942: Epoch 7943 +2024-11-23 06:04:38.420063: Current learning rate: 0.00012 +2024-11-23 06:04:57.717114: train_loss -0.8471 +2024-11-23 06:04:57.717366: val_loss -0.7873 +2024-11-23 06:04:57.717448: Pseudo dice [0.8659] +2024-11-23 06:04:57.717524: Epoch time: 19.3 s +2024-11-23 06:04:58.663232: +2024-11-23 06:04:58.663455: Epoch 7944 +2024-11-23 06:04:58.663565: Current learning rate: 0.00011 +2024-11-23 06:05:18.082205: train_loss -0.8363 +2024-11-23 06:05:18.082420: val_loss -0.7513 +2024-11-23 06:05:18.082571: Pseudo dice [0.8532] +2024-11-23 06:05:18.082651: Epoch time: 19.42 s +2024-11-23 06:05:19.076595: +2024-11-23 06:05:19.076797: Epoch 7945 +2024-11-23 06:05:19.076909: Current learning rate: 0.00011 +2024-11-23 06:05:38.155541: train_loss -0.8427 +2024-11-23 06:05:38.160961: val_loss -0.7397 +2024-11-23 06:05:38.161128: Pseudo dice [0.8265] +2024-11-23 06:05:38.161229: Epoch time: 19.08 s +2024-11-23 06:05:39.174894: +2024-11-23 06:05:39.175110: Epoch 7946 +2024-11-23 06:05:39.175221: Current learning rate: 0.00011 +2024-11-23 06:05:57.493195: train_loss -0.8456 +2024-11-23 06:05:57.493414: val_loss -0.7331 +2024-11-23 06:05:57.493490: Pseudo dice [0.8401] +2024-11-23 06:05:57.493567: Epoch time: 18.32 s +2024-11-23 06:05:58.428087: +2024-11-23 06:05:58.428314: Epoch 7947 +2024-11-23 06:05:58.428430: Current learning rate: 0.00011 +2024-11-23 06:06:17.123384: train_loss -0.8378 +2024-11-23 06:06:17.123595: val_loss -0.739 +2024-11-23 06:06:17.123667: Pseudo dice [0.8509] +2024-11-23 06:06:17.123741: Epoch time: 18.7 s +2024-11-23 06:06:18.453391: +2024-11-23 06:06:18.453627: Epoch 7948 +2024-11-23 06:06:18.453738: Current learning rate: 0.00011 +2024-11-23 06:06:37.488816: train_loss -0.839 +2024-11-23 06:06:37.489129: val_loss -0.7712 +2024-11-23 06:06:37.489217: Pseudo dice [0.8553] +2024-11-23 06:06:37.489305: Epoch time: 19.04 s +2024-11-23 06:06:38.437423: +2024-11-23 06:06:38.437639: Epoch 7949 +2024-11-23 06:06:38.437751: Current learning rate: 0.00011 +2024-11-23 06:06:56.807487: train_loss -0.8388 +2024-11-23 06:06:56.807703: val_loss -0.7483 +2024-11-23 06:06:56.807782: Pseudo dice [0.8501] +2024-11-23 06:06:56.807858: Epoch time: 18.37 s +2024-11-23 06:06:58.137308: +2024-11-23 06:06:58.137537: Epoch 7950 +2024-11-23 06:06:58.137654: Current learning rate: 0.0001 +2024-11-23 06:07:16.519647: train_loss -0.8452 +2024-11-23 06:07:16.519868: val_loss -0.7691 +2024-11-23 06:07:16.520015: Pseudo dice [0.8702] +2024-11-23 06:07:16.520096: Epoch time: 18.38 s +2024-11-23 06:07:17.492227: +2024-11-23 06:07:17.492469: Epoch 7951 +2024-11-23 06:07:17.492592: Current learning rate: 0.0001 +2024-11-23 06:07:35.767928: train_loss -0.8433 +2024-11-23 06:07:35.768148: val_loss -0.7559 +2024-11-23 06:07:35.768223: Pseudo dice [0.8285] +2024-11-23 06:07:35.768298: Epoch time: 18.28 s +2024-11-23 06:07:36.719272: +2024-11-23 06:07:36.719502: Epoch 7952 +2024-11-23 06:07:36.719649: Current learning rate: 0.0001 +2024-11-23 06:07:54.446970: train_loss -0.8357 +2024-11-23 06:07:54.447283: val_loss -0.7598 +2024-11-23 06:07:54.447361: Pseudo dice [0.8624] +2024-11-23 06:07:54.447443: Epoch time: 17.73 s +2024-11-23 06:07:55.386456: +2024-11-23 06:07:55.386692: Epoch 7953 +2024-11-23 06:07:55.386804: Current learning rate: 0.0001 +2024-11-23 06:08:13.774809: train_loss -0.847 +2024-11-23 06:08:13.775034: val_loss -0.7709 +2024-11-23 06:08:13.775124: Pseudo dice [0.8716] +2024-11-23 06:08:13.775202: Epoch time: 18.39 s +2024-11-23 06:08:14.713652: +2024-11-23 06:08:14.713859: Epoch 7954 +2024-11-23 06:08:14.713976: Current learning rate: 0.0001 +2024-11-23 06:08:32.831030: train_loss -0.8416 +2024-11-23 06:08:32.831237: val_loss -0.7574 +2024-11-23 06:08:32.831314: Pseudo dice [0.8585] +2024-11-23 06:08:32.831390: Epoch time: 18.12 s +2024-11-23 06:08:33.776034: +2024-11-23 06:08:33.776245: Epoch 7955 +2024-11-23 06:08:33.776359: Current learning rate: 9e-05 +2024-11-23 06:08:52.682217: train_loss -0.8427 +2024-11-23 06:08:52.682441: val_loss -0.7577 +2024-11-23 06:08:52.682520: Pseudo dice [0.8523] +2024-11-23 06:08:52.682601: Epoch time: 18.91 s +2024-11-23 06:08:53.621222: +2024-11-23 06:08:53.621437: Epoch 7956 +2024-11-23 06:08:53.621550: Current learning rate: 9e-05 +2024-11-23 06:09:12.421140: train_loss -0.8401 +2024-11-23 06:09:12.421383: val_loss -0.7352 +2024-11-23 06:09:12.421457: Pseudo dice [0.8521] +2024-11-23 06:09:12.421537: Epoch time: 18.8 s +2024-11-23 06:09:13.398475: +2024-11-23 06:09:13.398682: Epoch 7957 +2024-11-23 06:09:13.398796: Current learning rate: 9e-05 +2024-11-23 06:09:31.992348: train_loss -0.8434 +2024-11-23 06:09:31.992562: val_loss -0.769 +2024-11-23 06:09:31.992636: Pseudo dice [0.8555] +2024-11-23 06:09:31.992711: Epoch time: 18.59 s +2024-11-23 06:09:33.035893: +2024-11-23 06:09:33.036114: Epoch 7958 +2024-11-23 06:09:33.036225: Current learning rate: 9e-05 +2024-11-23 06:09:52.100047: train_loss -0.8507 +2024-11-23 06:09:52.100270: val_loss -0.769 +2024-11-23 06:09:52.100344: Pseudo dice [0.8517] +2024-11-23 06:09:52.100424: Epoch time: 19.06 s +2024-11-23 06:09:53.454520: +2024-11-23 06:09:53.454741: Epoch 7959 +2024-11-23 06:09:53.454857: Current learning rate: 9e-05 +2024-11-23 06:10:12.025306: train_loss -0.8503 +2024-11-23 06:10:12.025557: val_loss -0.7474 +2024-11-23 06:10:12.025633: Pseudo dice [0.8588] +2024-11-23 06:10:12.025726: Epoch time: 18.57 s +2024-11-23 06:10:13.159690: +2024-11-23 06:10:13.159948: Epoch 7960 +2024-11-23 06:10:13.160067: Current learning rate: 8e-05 +2024-11-23 06:10:31.913976: train_loss -0.8409 +2024-11-23 06:10:31.914199: val_loss -0.749 +2024-11-23 06:10:31.914275: Pseudo dice [0.846] +2024-11-23 06:10:31.914350: Epoch time: 18.76 s +2024-11-23 06:10:32.854863: +2024-11-23 06:10:32.855110: Epoch 7961 +2024-11-23 06:10:32.855226: Current learning rate: 8e-05 +2024-11-23 06:10:51.869704: train_loss -0.8405 +2024-11-23 06:10:51.869917: val_loss -0.7406 +2024-11-23 06:10:51.869996: Pseudo dice [0.8506] +2024-11-23 06:10:51.870075: Epoch time: 19.02 s +2024-11-23 06:10:52.810346: +2024-11-23 06:10:52.810595: Epoch 7962 +2024-11-23 06:10:52.810714: Current learning rate: 8e-05 +2024-11-23 06:11:11.427888: train_loss -0.8427 +2024-11-23 06:11:11.428142: val_loss -0.757 +2024-11-23 06:11:11.428218: Pseudo dice [0.8661] +2024-11-23 06:11:11.428303: Epoch time: 18.62 s +2024-11-23 06:11:12.368538: +2024-11-23 06:11:12.368763: Epoch 7963 +2024-11-23 06:11:12.368879: Current learning rate: 8e-05 +2024-11-23 06:11:30.433522: train_loss -0.8429 +2024-11-23 06:11:30.433740: val_loss -0.7359 +2024-11-23 06:11:30.433877: Pseudo dice [0.8412] +2024-11-23 06:11:30.433958: Epoch time: 18.07 s +2024-11-23 06:11:31.375316: +2024-11-23 06:11:31.375533: Epoch 7964 +2024-11-23 06:11:31.375648: Current learning rate: 8e-05 +2024-11-23 06:11:49.941262: train_loss -0.8434 +2024-11-23 06:11:49.941475: val_loss -0.7458 +2024-11-23 06:11:49.941554: Pseudo dice [0.8623] +2024-11-23 06:11:49.941635: Epoch time: 18.57 s +2024-11-23 06:11:50.886811: +2024-11-23 06:11:50.887028: Epoch 7965 +2024-11-23 06:11:50.887143: Current learning rate: 8e-05 +2024-11-23 06:12:09.255978: train_loss -0.8455 +2024-11-23 06:12:09.256201: val_loss -0.7468 +2024-11-23 06:12:09.256284: Pseudo dice [0.8685] +2024-11-23 06:12:09.256365: Epoch time: 18.37 s +2024-11-23 06:12:10.197637: +2024-11-23 06:12:10.197858: Epoch 7966 +2024-11-23 06:12:10.197976: Current learning rate: 7e-05 +2024-11-23 06:12:29.291497: train_loss -0.8431 +2024-11-23 06:12:29.291720: val_loss -0.7408 +2024-11-23 06:12:29.291799: Pseudo dice [0.8456] +2024-11-23 06:12:29.291879: Epoch time: 19.09 s +2024-11-23 06:12:30.374053: +2024-11-23 06:12:30.374290: Epoch 7967 +2024-11-23 06:12:30.374406: Current learning rate: 7e-05 +2024-11-23 06:12:48.308562: train_loss -0.8453 +2024-11-23 06:12:48.308847: val_loss -0.7665 +2024-11-23 06:12:48.308932: Pseudo dice [0.873] +2024-11-23 06:12:48.309019: Epoch time: 17.94 s +2024-11-23 06:12:49.245337: +2024-11-23 06:12:49.245538: Epoch 7968 +2024-11-23 06:12:49.245650: Current learning rate: 7e-05 +2024-11-23 06:13:08.002614: train_loss -0.8388 +2024-11-23 06:13:08.002829: val_loss -0.78 +2024-11-23 06:13:08.002909: Pseudo dice [0.8228] +2024-11-23 06:13:08.002988: Epoch time: 18.76 s +2024-11-23 06:13:08.937867: +2024-11-23 06:13:08.938090: Epoch 7969 +2024-11-23 06:13:08.938202: Current learning rate: 7e-05 +2024-11-23 06:13:27.073874: train_loss -0.8469 +2024-11-23 06:13:27.074092: val_loss -0.7552 +2024-11-23 06:13:27.074169: Pseudo dice [0.8644] +2024-11-23 06:13:27.074316: Epoch time: 18.14 s +2024-11-23 06:13:28.386443: +2024-11-23 06:13:28.386650: Epoch 7970 +2024-11-23 06:13:28.386763: Current learning rate: 7e-05 +2024-11-23 06:13:47.150098: train_loss -0.8491 +2024-11-23 06:13:47.150395: val_loss -0.7755 +2024-11-23 06:13:47.150470: Pseudo dice [0.8489] +2024-11-23 06:13:47.150553: Epoch time: 18.76 s +2024-11-23 06:13:48.098550: +2024-11-23 06:13:48.098769: Epoch 7971 +2024-11-23 06:13:48.098882: Current learning rate: 6e-05 +2024-11-23 06:14:06.979650: train_loss -0.8405 +2024-11-23 06:14:06.979862: val_loss -0.744 +2024-11-23 06:14:06.979938: Pseudo dice [0.8662] +2024-11-23 06:14:06.980020: Epoch time: 18.88 s +2024-11-23 06:14:07.957788: +2024-11-23 06:14:07.958040: Epoch 7972 +2024-11-23 06:14:07.958156: Current learning rate: 6e-05 +2024-11-23 06:14:27.416103: train_loss -0.8502 +2024-11-23 06:14:27.416334: val_loss -0.7705 +2024-11-23 06:14:27.416408: Pseudo dice [0.8558] +2024-11-23 06:14:27.416484: Epoch time: 19.46 s +2024-11-23 06:14:28.405014: +2024-11-23 06:14:28.405233: Epoch 7973 +2024-11-23 06:14:28.405346: Current learning rate: 6e-05 +2024-11-23 06:14:46.828667: train_loss -0.8467 +2024-11-23 06:14:46.828932: val_loss -0.7603 +2024-11-23 06:14:46.829057: Pseudo dice [0.8679] +2024-11-23 06:14:46.829146: Epoch time: 18.42 s +2024-11-23 06:14:47.810381: +2024-11-23 06:14:47.810601: Epoch 7974 +2024-11-23 06:14:47.810712: Current learning rate: 6e-05 +2024-11-23 06:15:06.494401: train_loss -0.843 +2024-11-23 06:15:06.494615: val_loss -0.7959 +2024-11-23 06:15:06.494692: Pseudo dice [0.8739] +2024-11-23 06:15:06.494767: Epoch time: 18.68 s +2024-11-23 06:15:07.433433: +2024-11-23 06:15:07.433731: Epoch 7975 +2024-11-23 06:15:07.433846: Current learning rate: 6e-05 +2024-11-23 06:15:26.807445: train_loss -0.847 +2024-11-23 06:15:26.807662: val_loss -0.7359 +2024-11-23 06:15:26.807741: Pseudo dice [0.8598] +2024-11-23 06:15:26.807817: Epoch time: 19.37 s +2024-11-23 06:15:27.743496: +2024-11-23 06:15:27.743748: Epoch 7976 +2024-11-23 06:15:27.743864: Current learning rate: 5e-05 +2024-11-23 06:15:45.852670: train_loss -0.8434 +2024-11-23 06:15:45.852947: val_loss -0.7793 +2024-11-23 06:15:45.853031: Pseudo dice [0.8627] +2024-11-23 06:15:45.853108: Epoch time: 18.11 s +2024-11-23 06:15:46.786140: +2024-11-23 06:15:46.786369: Epoch 7977 +2024-11-23 06:15:46.786482: Current learning rate: 5e-05 +2024-11-23 06:16:05.029761: train_loss -0.8433 +2024-11-23 06:16:05.030018: val_loss -0.7637 +2024-11-23 06:16:05.030092: Pseudo dice [0.8443] +2024-11-23 06:16:05.030178: Epoch time: 18.24 s +2024-11-23 06:16:05.970765: +2024-11-23 06:16:05.970976: Epoch 7978 +2024-11-23 06:16:05.971097: Current learning rate: 5e-05 +2024-11-23 06:16:25.525499: train_loss -0.8459 +2024-11-23 06:16:25.525713: val_loss -0.757 +2024-11-23 06:16:25.525785: Pseudo dice [0.8559] +2024-11-23 06:16:25.525861: Epoch time: 19.56 s +2024-11-23 06:16:26.465680: +2024-11-23 06:16:26.465906: Epoch 7979 +2024-11-23 06:16:26.466027: Current learning rate: 5e-05 +2024-11-23 06:16:45.188242: train_loss -0.8377 +2024-11-23 06:16:45.188458: val_loss -0.7457 +2024-11-23 06:16:45.188532: Pseudo dice [0.8531] +2024-11-23 06:16:45.188607: Epoch time: 18.72 s +2024-11-23 06:16:46.134193: +2024-11-23 06:16:46.134399: Epoch 7980 +2024-11-23 06:16:46.134512: Current learning rate: 5e-05 +2024-11-23 06:17:05.023058: train_loss -0.846 +2024-11-23 06:17:05.023277: val_loss -0.7622 +2024-11-23 06:17:05.023354: Pseudo dice [0.8408] +2024-11-23 06:17:05.023430: Epoch time: 18.89 s +2024-11-23 06:17:06.396913: +2024-11-23 06:17:06.397119: Epoch 7981 +2024-11-23 06:17:06.397233: Current learning rate: 4e-05 +2024-11-23 06:17:25.209635: train_loss -0.847 +2024-11-23 06:17:25.209897: val_loss -0.7405 +2024-11-23 06:17:25.209973: Pseudo dice [0.8688] +2024-11-23 06:17:25.210061: Epoch time: 18.81 s +2024-11-23 06:17:26.264466: +2024-11-23 06:17:26.264714: Epoch 7982 +2024-11-23 06:17:26.264834: Current learning rate: 4e-05 +2024-11-23 06:17:44.816225: train_loss -0.8432 +2024-11-23 06:17:44.816517: val_loss -0.7882 +2024-11-23 06:17:44.816593: Pseudo dice [0.854] +2024-11-23 06:17:44.816670: Epoch time: 18.55 s +2024-11-23 06:17:45.754441: +2024-11-23 06:17:45.754660: Epoch 7983 +2024-11-23 06:17:45.754772: Current learning rate: 4e-05 +2024-11-23 06:18:04.057138: train_loss -0.8491 +2024-11-23 06:18:04.057374: val_loss -0.7737 +2024-11-23 06:18:04.057446: Pseudo dice [0.8469] +2024-11-23 06:18:04.057523: Epoch time: 18.3 s +2024-11-23 06:18:04.996551: +2024-11-23 06:18:04.996776: Epoch 7984 +2024-11-23 06:18:04.996894: Current learning rate: 4e-05 +2024-11-23 06:18:23.541872: train_loss -0.8488 +2024-11-23 06:18:23.542129: val_loss -0.7665 +2024-11-23 06:18:23.542207: Pseudo dice [0.8692] +2024-11-23 06:18:23.542294: Epoch time: 18.55 s +2024-11-23 06:18:24.487256: +2024-11-23 06:18:24.487455: Epoch 7985 +2024-11-23 06:18:24.487571: Current learning rate: 4e-05 +2024-11-23 06:18:41.703439: train_loss -0.8489 +2024-11-23 06:18:41.703656: val_loss -0.7744 +2024-11-23 06:18:41.703735: Pseudo dice [0.8489] +2024-11-23 06:18:41.703813: Epoch time: 17.22 s +2024-11-23 06:18:42.647169: +2024-11-23 06:18:42.647393: Epoch 7986 +2024-11-23 06:18:42.647507: Current learning rate: 3e-05 +2024-11-23 06:19:01.589141: train_loss -0.8457 +2024-11-23 06:19:01.589352: val_loss -0.7677 +2024-11-23 06:19:01.589448: Pseudo dice [0.8677] +2024-11-23 06:19:01.589526: Epoch time: 18.94 s +2024-11-23 06:19:02.526618: +2024-11-23 06:19:02.526840: Epoch 7987 +2024-11-23 06:19:02.526952: Current learning rate: 3e-05 +2024-11-23 06:19:22.127941: train_loss -0.8441 +2024-11-23 06:19:22.128169: val_loss -0.7451 +2024-11-23 06:19:22.128244: Pseudo dice [0.8612] +2024-11-23 06:19:22.128322: Epoch time: 19.6 s +2024-11-23 06:19:23.071782: +2024-11-23 06:19:23.072063: Epoch 7988 +2024-11-23 06:19:23.072178: Current learning rate: 3e-05 +2024-11-23 06:19:41.478796: train_loss -0.8439 +2024-11-23 06:19:41.479045: val_loss -0.778 +2024-11-23 06:19:41.479122: Pseudo dice [0.8637] +2024-11-23 06:19:41.479212: Epoch time: 18.41 s +2024-11-23 06:19:42.423665: +2024-11-23 06:19:42.423894: Epoch 7989 +2024-11-23 06:19:42.424019: Current learning rate: 3e-05 +2024-11-23 06:20:01.370330: train_loss -0.8435 +2024-11-23 06:20:01.370564: val_loss -0.7782 +2024-11-23 06:20:01.370646: Pseudo dice [0.8759] +2024-11-23 06:20:01.375882: Epoch time: 18.95 s +2024-11-23 06:20:02.492499: +2024-11-23 06:20:02.492709: Epoch 7990 +2024-11-23 06:20:02.492834: Current learning rate: 2e-05 +2024-11-23 06:20:21.716449: train_loss -0.8447 +2024-11-23 06:20:21.716654: val_loss -0.7467 +2024-11-23 06:20:21.716729: Pseudo dice [0.8812] +2024-11-23 06:20:21.716802: Epoch time: 19.22 s +2024-11-23 06:20:22.647767: +2024-11-23 06:20:22.647964: Epoch 7991 +2024-11-23 06:20:22.648086: Current learning rate: 2e-05 +2024-11-23 06:20:40.586636: train_loss -0.8466 +2024-11-23 06:20:40.586845: val_loss -0.7419 +2024-11-23 06:20:40.586925: Pseudo dice [0.8437] +2024-11-23 06:20:40.587012: Epoch time: 17.94 s +2024-11-23 06:20:41.908323: +2024-11-23 06:20:41.908576: Epoch 7992 +2024-11-23 06:20:41.908730: Current learning rate: 2e-05 +2024-11-23 06:21:01.032260: train_loss -0.8432 +2024-11-23 06:21:01.032726: val_loss -0.768 +2024-11-23 06:21:01.032822: Pseudo dice [0.8805] +2024-11-23 06:21:01.032914: Epoch time: 19.12 s +2024-11-23 06:21:01.032977: Yayy! New best EMA pseudo Dice: 0.8622 +2024-11-23 06:21:02.347913: +2024-11-23 06:21:02.348187: Epoch 7993 +2024-11-23 06:21:02.348300: Current learning rate: 2e-05 +2024-11-23 06:21:20.087329: train_loss -0.844 +2024-11-23 06:21:20.089811: val_loss -0.7476 +2024-11-23 06:21:20.089902: Pseudo dice [0.8283] +2024-11-23 06:21:20.089977: Epoch time: 17.74 s +2024-11-23 06:21:21.010842: +2024-11-23 06:21:21.011176: Epoch 7994 +2024-11-23 06:21:21.011288: Current learning rate: 2e-05 +2024-11-23 06:21:39.204117: train_loss -0.8412 +2024-11-23 06:21:39.213579: val_loss -0.7291 +2024-11-23 06:21:39.213693: Pseudo dice [0.8415] +2024-11-23 06:21:39.213779: Epoch time: 18.19 s +2024-11-23 06:21:40.180401: +2024-11-23 06:21:40.180596: Epoch 7995 +2024-11-23 06:21:40.180709: Current learning rate: 1e-05 +2024-11-23 06:21:58.928097: train_loss -0.8506 +2024-11-23 06:21:58.928341: val_loss -0.7567 +2024-11-23 06:21:58.933645: Pseudo dice [0.8592] +2024-11-23 06:21:58.933781: Epoch time: 18.75 s +2024-11-23 06:21:59.939759: +2024-11-23 06:21:59.940012: Epoch 7996 +2024-11-23 06:21:59.940128: Current learning rate: 1e-05 +2024-11-23 06:22:18.578190: train_loss -0.8428 +2024-11-23 06:22:18.578390: val_loss -0.7569 +2024-11-23 06:22:18.578469: Pseudo dice [0.8502] +2024-11-23 06:22:18.578548: Epoch time: 18.64 s +2024-11-23 06:22:19.580676: +2024-11-23 06:22:19.580902: Epoch 7997 +2024-11-23 06:22:19.581020: Current learning rate: 1e-05 +2024-11-23 06:22:37.353002: train_loss -0.8466 +2024-11-23 06:22:37.353214: val_loss -0.759 +2024-11-23 06:22:37.353287: Pseudo dice [0.8593] +2024-11-23 06:22:37.353362: Epoch time: 17.77 s +2024-11-23 06:22:38.273561: +2024-11-23 06:22:38.273753: Epoch 7998 +2024-11-23 06:22:38.273857: Current learning rate: 1e-05 +2024-11-23 06:22:56.004099: train_loss -0.8454 +2024-11-23 06:22:56.004317: val_loss -0.7732 +2024-11-23 06:22:56.004438: Pseudo dice [0.8611] +2024-11-23 06:22:56.004524: Epoch time: 17.73 s +2024-11-23 06:22:57.074399: +2024-11-23 06:22:57.074640: Epoch 7999 +2024-11-23 06:22:57.074754: Current learning rate: 0.0 +2024-11-23 06:23:15.048172: train_loss -0.8402 +2024-11-23 06:23:15.048372: val_loss -0.7643 +2024-11-23 06:23:15.048445: Pseudo dice [0.8581] +2024-11-23 06:23:15.048519: Epoch time: 17.97 s +2024-11-23 06:23:16.368990: Training done. +2024-11-23 06:23:16.382894: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-23 06:23:16.383716: The split file contains 5 splits. +2024-11-23 06:23:16.383781: Desired fold for training: 2 +2024-11-23 06:23:16.383837: This split has 534 training and 134 validation cases. +2024-11-23 06:23:16.384694: predicting FLAIR_013 +2024-11-23 06:23:16.397136: FLAIR_013, shape torch.Size([1, 131, 152, 190]), rank 0 +2024-11-23 06:23:23.358711: predicting FLAIR_017 +2024-11-23 06:23:23.398270: FLAIR_017, shape torch.Size([1, 132, 146, 183]), rank 0 +2024-11-23 06:23:23.978814: predicting FLAIR_018 +2024-11-23 06:23:23.990054: FLAIR_018, shape torch.Size([1, 121, 147, 188]), rank 0 +2024-11-23 06:23:24.568362: predicting FLAIR_020 +2024-11-23 06:23:24.580631: FLAIR_020, shape torch.Size([1, 126, 143, 184]), rank 0 +2024-11-23 06:23:25.158539: predicting FLAIR_031 +2024-11-23 06:23:25.172047: FLAIR_031, shape torch.Size([1, 131, 146, 190]), rank 0 +2024-11-23 06:23:25.751181: predicting FLAIR_032 +2024-11-23 06:23:25.784672: FLAIR_032, shape torch.Size([1, 131, 150, 193]), rank 0 +2024-11-23 06:23:26.377921: predicting FLAIR_039 +2024-11-23 06:23:26.420172: FLAIR_039, shape torch.Size([1, 129, 148, 197]), rank 0 +2024-11-23 06:23:26.999455: predicting FLAIR_042 +2024-11-23 06:23:27.011909: FLAIR_042, shape torch.Size([1, 126, 139, 191]), rank 0 +2024-11-23 06:23:27.590238: predicting FLAIR_050 +2024-11-23 06:23:27.605738: FLAIR_050, shape torch.Size([1, 129, 152, 193]), rank 0 +2024-11-23 06:23:28.185734: predicting FLAIR_051 +2024-11-23 06:23:28.201724: FLAIR_051, shape torch.Size([1, 135, 149, 196]), rank 0 +2024-11-23 06:23:30.818384: predicting FLAIR_052 +2024-11-23 06:23:30.833368: FLAIR_052, shape torch.Size([1, 135, 147, 196]), rank 0 +2024-11-23 06:23:31.420803: predicting FLAIR_061 +2024-11-23 06:23:31.458983: FLAIR_061, shape torch.Size([1, 137, 146, 197]), rank 0 +2024-11-23 06:23:32.061520: predicting FLAIR_065 +2024-11-23 06:23:32.096872: FLAIR_065, shape torch.Size([1, 146, 152, 209]), rank 0 +2024-11-23 06:23:32.681567: predicting FLAIR_074 +2024-11-23 06:23:32.697785: FLAIR_074, shape torch.Size([1, 132, 148, 188]), rank 0 +2024-11-23 06:23:33.289044: predicting FLAIR_089 +2024-11-23 06:23:33.301154: FLAIR_089, shape torch.Size([1, 130, 137, 187]), rank 0 +2024-11-23 06:23:33.893433: predicting FLAIR_094 +2024-11-23 06:23:33.907685: FLAIR_094, shape torch.Size([1, 132, 154, 168]), rank 0 +2024-11-23 06:23:34.498038: predicting FLAIR_096 +2024-11-23 06:23:34.512127: FLAIR_096, shape torch.Size([1, 126, 148, 192]), rank 0 +2024-11-23 06:23:35.114050: predicting FLAIR_104 +2024-11-23 06:23:35.127326: FLAIR_104, shape torch.Size([1, 120, 139, 191]), rank 0 +2024-11-23 06:23:35.734648: predicting FLAIR_111 +2024-11-23 06:23:35.781546: FLAIR_111, shape torch.Size([1, 139, 160, 198]), rank 0 +2024-11-23 06:23:36.410906: predicting FLAIR_114 +2024-11-23 06:23:36.430707: FLAIR_114, shape torch.Size([1, 141, 166, 188]), rank 0 +2024-11-23 06:23:37.039212: predicting FLAIR_129 +2024-11-23 06:23:37.077793: FLAIR_129, shape torch.Size([1, 139, 156, 196]), rank 0 +2024-11-23 06:23:37.696197: predicting FLAIR_133 +2024-11-23 06:23:37.709880: FLAIR_133, shape torch.Size([1, 142, 150, 185]), rank 0 +2024-11-23 06:23:38.328070: predicting FLAIR_138 +2024-11-23 06:23:38.354557: FLAIR_138, shape torch.Size([1, 130, 148, 182]), rank 0 +2024-11-23 06:23:38.985072: predicting FLAIR_153 +2024-11-23 06:23:39.055419: FLAIR_153, shape torch.Size([1, 126, 148, 197]), rank 0 +2024-11-23 06:23:39.693068: predicting FLAIR_158 +2024-11-23 06:23:39.726355: FLAIR_158, shape torch.Size([1, 133, 150, 199]), rank 0 +2024-11-23 06:23:40.376082: predicting FLAIR_161 +2024-11-23 06:23:40.389484: FLAIR_161, shape torch.Size([1, 135, 152, 199]), rank 0 +2024-11-23 06:23:40.992020: predicting FLAIR_162 +2024-11-23 06:23:41.006642: FLAIR_162, shape torch.Size([1, 134, 152, 198]), rank 0 +2024-11-23 06:23:41.613882: predicting FLAIR_170 +2024-11-23 06:23:41.626453: FLAIR_170, shape torch.Size([1, 139, 196, 147]), rank 0 +2024-11-23 06:23:42.094044: predicting FLAIR_183 +2024-11-23 06:23:42.123364: FLAIR_183, shape torch.Size([1, 135, 199, 154]), rank 0 +2024-11-23 06:23:43.055653: predicting FLAIR_195 +2024-11-23 06:23:43.069060: FLAIR_195, shape torch.Size([1, 134, 186, 153]), rank 0 +2024-11-23 06:23:43.423680: predicting FLAIR_202 +2024-11-23 06:23:43.469494: FLAIR_202, shape torch.Size([1, 126, 184, 152]), rank 0 +2024-11-23 06:23:44.212452: predicting FLAIR_205 +2024-11-23 06:23:44.226219: FLAIR_205, shape torch.Size([1, 124, 196, 156]), rank 0 +2024-11-23 06:23:45.172558: predicting FLAIR_206 +2024-11-23 06:23:45.187339: FLAIR_206, shape torch.Size([1, 141, 197, 150]), rank 0 +2024-11-23 06:23:45.652519: predicting FLAIR_208 +2024-11-23 06:23:45.705904: FLAIR_208, shape torch.Size([1, 128, 176, 140]), rank 0 +2024-11-23 06:23:46.024562: predicting FLAIR_212 +2024-11-23 06:23:46.049792: FLAIR_212, shape torch.Size([1, 126, 193, 150]), rank 0 +2024-11-23 06:23:46.555696: predicting FLAIR_216 +2024-11-23 06:23:46.588277: FLAIR_216, shape torch.Size([1, 140, 199, 152]), rank 0 +2024-11-23 06:23:47.102565: predicting FLAIR_218 +2024-11-23 06:23:47.137403: FLAIR_218, shape torch.Size([1, 130, 180, 147]), rank 0 +2024-11-23 06:23:47.475336: predicting FLAIR_220 +2024-11-23 06:23:47.500583: FLAIR_220, shape torch.Size([1, 141, 198, 148]), rank 0 +2024-11-23 06:23:47.957072: predicting FLAIR_230 +2024-11-23 06:23:47.981839: FLAIR_230, shape torch.Size([1, 130, 184, 151]), rank 0 +2024-11-23 06:23:48.297270: predicting FLAIR_231 +2024-11-23 06:23:48.309202: FLAIR_231, shape torch.Size([1, 135, 182, 147]), rank 0 +2024-11-23 06:23:48.641962: predicting FLAIR_235 +2024-11-23 06:23:48.670563: FLAIR_235, shape torch.Size([1, 137, 197, 162]), rank 0 +2024-11-23 06:23:49.570944: predicting FLAIR_247 +2024-11-23 06:23:49.582736: FLAIR_247, shape torch.Size([1, 137, 179, 143]), rank 0 +2024-11-23 06:23:49.883925: predicting FLAIR_248 +2024-11-23 06:23:49.897326: FLAIR_248, shape torch.Size([1, 130, 151, 198]), rank 0 +2024-11-23 06:23:50.478384: predicting FLAIR_251 +2024-11-23 06:23:50.491143: FLAIR_251, shape torch.Size([1, 130, 201, 160]), rank 0 +2024-11-23 06:23:50.939974: predicting FLAIR_253 +2024-11-23 06:23:50.950640: FLAIR_253, shape torch.Size([1, 125, 142, 182]), rank 0 +2024-11-23 06:23:51.547419: predicting FLAIR_261 +2024-11-23 06:23:51.609954: FLAIR_261, shape torch.Size([1, 139, 198, 160]), rank 0 +2024-11-23 06:23:52.077520: predicting FLAIR_273 +2024-11-23 06:23:52.102531: FLAIR_273, shape torch.Size([1, 133, 186, 156]), rank 0 +2024-11-23 06:23:52.417862: predicting FLAIR_275 +2024-11-23 06:23:52.482872: FLAIR_275, shape torch.Size([1, 143, 197, 158]), rank 0 +2024-11-23 06:23:52.953646: predicting FLAIR_277 +2024-11-23 06:23:52.966693: FLAIR_277, shape torch.Size([1, 130, 161, 202]), rank 0 +2024-11-23 06:23:53.567083: predicting FLAIR_279 +2024-11-23 06:23:53.581058: FLAIR_279, shape torch.Size([1, 126, 200, 146]), rank 0 +2024-11-23 06:23:54.040063: predicting FLAIR_283 +2024-11-23 06:23:54.075284: FLAIR_283, shape torch.Size([1, 132, 200, 152]), rank 0 +2024-11-23 06:23:54.571066: predicting FLAIR_293 +2024-11-23 06:23:54.586032: FLAIR_293, shape torch.Size([1, 143, 210, 156]), rank 0 +2024-11-23 06:23:55.040716: predicting FLAIR_296 +2024-11-23 06:23:55.076948: FLAIR_296, shape torch.Size([1, 135, 172, 150]), rank 0 +2024-11-23 06:23:55.391806: predicting FLAIR_307 +2024-11-23 06:23:55.405569: FLAIR_307, shape torch.Size([1, 139, 148, 199]), rank 0 +2024-11-23 06:23:55.987170: predicting FLAIR_320 +2024-11-23 06:23:56.000681: FLAIR_320, shape torch.Size([1, 137, 184, 152]), rank 0 +2024-11-23 06:23:56.304027: predicting FLAIR_324 +2024-11-23 06:23:56.340770: FLAIR_324, shape torch.Size([1, 129, 181, 138]), rank 0 +2024-11-23 06:23:56.657218: predicting FLAIR_328 +2024-11-23 06:23:56.670249: FLAIR_328, shape torch.Size([1, 139, 164, 198]), rank 0 +2024-11-23 06:23:57.259315: predicting FLAIR_331 +2024-11-23 06:23:57.270937: FLAIR_331, shape torch.Size([1, 125, 197, 147]), rank 0 +2024-11-23 06:23:57.741067: predicting FLAIR_336 +2024-11-23 06:23:57.756109: FLAIR_336, shape torch.Size([1, 147, 176, 161]), rank 0 +2024-11-23 06:23:58.359390: predicting FLAIR_339 +2024-11-23 06:23:58.382205: FLAIR_339, shape torch.Size([1, 135, 153, 190]), rank 0 +2024-11-23 06:23:58.972822: predicting FLAIR_340 +2024-11-23 06:23:58.987151: FLAIR_340, shape torch.Size([1, 136, 206, 160]), rank 0 +2024-11-23 06:23:59.440007: predicting FLAIR_347 +2024-11-23 06:23:59.462749: FLAIR_347, shape torch.Size([1, 144, 156, 192]), rank 0 +2024-11-23 06:24:00.066887: predicting FLAIR_348 +2024-11-23 06:24:00.102181: FLAIR_348, shape torch.Size([1, 131, 143, 186]), rank 0 +2024-11-23 06:24:00.694778: predicting FLAIR_349 +2024-11-23 06:24:00.707166: FLAIR_349, shape torch.Size([1, 135, 143, 184]), rank 0 +2024-11-23 06:24:01.315080: predicting FLAIR_352 +2024-11-23 06:24:01.325900: FLAIR_352, shape torch.Size([1, 126, 145, 181]), rank 0 +2024-11-23 06:24:01.917770: predicting FLAIR_359 +2024-11-23 06:24:01.961325: FLAIR_359, shape torch.Size([1, 138, 155, 188]), rank 0 +2024-11-23 06:24:02.550491: predicting FLAIR_362 +2024-11-23 06:24:02.571512: FLAIR_362, shape torch.Size([1, 126, 135, 185]), rank 0 +2024-11-23 06:24:03.162876: predicting FLAIR_364 +2024-11-23 06:24:03.175479: FLAIR_364, shape torch.Size([1, 128, 155, 180]), rank 0 +2024-11-23 06:24:03.762330: predicting FLAIR_365 +2024-11-23 06:24:03.773691: FLAIR_365, shape torch.Size([1, 120, 141, 175]), rank 0 +2024-11-23 06:24:04.364094: predicting FLAIR_368 +2024-11-23 06:24:04.377111: FLAIR_368, shape torch.Size([1, 131, 151, 181]), rank 0 +2024-11-23 06:24:04.970168: predicting FLAIR_369 +2024-11-23 06:24:04.982421: FLAIR_369, shape torch.Size([1, 125, 151, 176]), rank 0 +2024-11-23 06:24:05.594717: predicting FLAIR_371 +2024-11-23 06:24:05.606400: FLAIR_371, shape torch.Size([1, 138, 146, 187]), rank 0 +2024-11-23 06:24:06.198874: predicting FLAIR_373 +2024-11-23 06:24:06.222543: FLAIR_373, shape torch.Size([1, 130, 140, 185]), rank 0 +2024-11-23 06:24:06.815501: predicting FLAIR_376 +2024-11-23 06:24:06.828868: FLAIR_376, shape torch.Size([1, 126, 141, 180]), rank 0 +2024-11-23 06:24:07.412654: predicting FLAIR_378 +2024-11-23 06:24:07.462103: FLAIR_378, shape torch.Size([1, 138, 160, 199]), rank 0 +2024-11-23 06:24:08.078377: predicting FLAIR_382 +2024-11-23 06:24:08.091902: FLAIR_382, shape torch.Size([1, 131, 154, 193]), rank 0 +2024-11-23 06:24:08.689145: predicting FLAIR_389 +2024-11-23 06:24:08.703719: FLAIR_389, shape torch.Size([1, 142, 153, 196]), rank 0 +2024-11-23 06:24:09.293593: predicting FLAIR_392 +2024-11-23 06:24:09.319679: FLAIR_392, shape torch.Size([1, 136, 140, 185]), rank 0 +2024-11-23 06:24:09.912240: predicting FLAIR_395 +2024-11-23 06:24:09.923376: FLAIR_395, shape torch.Size([1, 131, 142, 181]), rank 0 +2024-11-23 06:24:10.542099: predicting FLAIR_415 +2024-11-23 06:24:10.565437: FLAIR_415, shape torch.Size([1, 141, 198, 149]), rank 0 +2024-11-23 06:24:11.078097: predicting FLAIR_417 +2024-11-23 06:24:11.090193: FLAIR_417, shape torch.Size([1, 126, 193, 150]), rank 0 +2024-11-23 06:24:11.574091: predicting FLAIR_422 +2024-11-23 06:24:11.587195: FLAIR_422, shape torch.Size([1, 123, 188, 150]), rank 0 +2024-11-23 06:24:11.915910: predicting FLAIR_432 +2024-11-23 06:24:11.940140: FLAIR_432, shape torch.Size([1, 133, 183, 150]), rank 0 +2024-11-23 06:24:12.253939: predicting FLAIR_439 +2024-11-23 06:24:12.276500: FLAIR_439, shape torch.Size([1, 129, 181, 149]), rank 0 +2024-11-23 06:24:12.611459: predicting FLAIR_443 +2024-11-23 06:24:12.638814: FLAIR_443, shape torch.Size([1, 133, 187, 153]), rank 0 +2024-11-23 06:24:12.953405: predicting FLAIR_447 +2024-11-23 06:24:13.026281: FLAIR_447, shape torch.Size([1, 133, 200, 151]), rank 0 +2024-11-23 06:24:13.491015: predicting FLAIR_448 +2024-11-23 06:24:13.534115: FLAIR_448, shape torch.Size([1, 144, 156, 179]), rank 0 +2024-11-23 06:24:14.141997: predicting FLAIR_453 +2024-11-23 06:24:14.156251: FLAIR_453, shape torch.Size([1, 135, 194, 153]), rank 0 +2024-11-23 06:24:14.607723: predicting FLAIR_455 +2024-11-23 06:24:14.631000: FLAIR_455, shape torch.Size([1, 130, 197, 151]), rank 0 +2024-11-23 06:24:15.086102: predicting FLAIR_458 +2024-11-23 06:24:15.098014: FLAIR_458, shape torch.Size([1, 134, 156, 189]), rank 0 +2024-11-23 06:24:15.698970: predicting FLAIR_466 +2024-11-23 06:24:15.766797: FLAIR_466, shape torch.Size([1, 133, 197, 157]), rank 0 +2024-11-23 06:24:16.244084: predicting FLAIR_467 +2024-11-23 06:24:16.258895: FLAIR_467, shape torch.Size([1, 146, 174, 160]), rank 0 +2024-11-23 06:24:16.572296: predicting FLAIR_470 +2024-11-23 06:24:16.584471: FLAIR_470, shape torch.Size([1, 132, 145, 182]), rank 0 +2024-11-23 06:24:17.163268: predicting FLAIR_471 +2024-11-23 06:24:17.175141: FLAIR_471, shape torch.Size([1, 127, 155, 188]), rank 0 +2024-11-23 06:24:17.754554: predicting FLAIR_472 +2024-11-23 06:24:17.767896: FLAIR_472, shape torch.Size([1, 133, 149, 185]), rank 0 +2024-11-23 06:24:18.347407: predicting FLAIR_475 +2024-11-23 06:24:18.361555: FLAIR_475, shape torch.Size([1, 140, 152, 198]), rank 0 +2024-11-23 06:24:18.951499: predicting FLAIR_477 +2024-11-23 06:24:18.993529: FLAIR_477, shape torch.Size([1, 133, 153, 193]), rank 0 +2024-11-23 06:24:19.623240: predicting FLAIR_480 +2024-11-23 06:24:19.641361: FLAIR_480, shape torch.Size([1, 135, 141, 179]), rank 0 +2024-11-23 06:24:20.267171: predicting FLAIR_482 +2024-11-23 06:24:20.295345: FLAIR_482, shape torch.Size([1, 127, 151, 193]), rank 0 +2024-11-23 06:24:20.946118: predicting FLAIR_489 +2024-11-23 06:24:20.966934: FLAIR_489, shape torch.Size([1, 129, 141, 189]), rank 0 +2024-11-23 06:24:21.614665: predicting FLAIR_491 +2024-11-23 06:24:21.643224: FLAIR_491, shape torch.Size([1, 138, 148, 193]), rank 0 +2024-11-23 06:24:22.293113: predicting FLAIR_497 +2024-11-23 06:24:22.314454: FLAIR_497, shape torch.Size([1, 133, 152, 196]), rank 0 +2024-11-23 06:24:22.934471: predicting FLAIR_505 +2024-11-23 06:24:22.946892: FLAIR_505, shape torch.Size([1, 126, 141, 182]), rank 0 +2024-11-23 06:24:23.544371: predicting FLAIR_509 +2024-11-23 06:24:23.568218: FLAIR_509, shape torch.Size([1, 138, 152, 202]), rank 0 +2024-11-23 06:24:24.563321: predicting FLAIR_518 +2024-11-23 06:24:24.574307: FLAIR_518, shape torch.Size([1, 129, 135, 178]), rank 0 +2024-11-23 06:24:27.677919: predicting FLAIR_522 +2024-11-23 06:24:27.689652: FLAIR_522, shape torch.Size([1, 131, 142, 190]), rank 0 +2024-11-23 06:24:28.307791: predicting FLAIR_523 +2024-11-23 06:24:28.328364: FLAIR_523, shape torch.Size([1, 126, 149, 183]), rank 0 +2024-11-23 06:24:28.953090: predicting FLAIR_541 +2024-11-23 06:24:29.006259: FLAIR_541, shape torch.Size([1, 138, 164, 200]), rank 0 +2024-11-23 06:24:29.622143: predicting FLAIR_555 +2024-11-23 06:24:29.648034: FLAIR_555, shape torch.Size([1, 135, 152, 197]), rank 0 +2024-11-23 06:24:30.269126: predicting FLAIR_559 +2024-11-23 06:24:30.303394: FLAIR_559, shape torch.Size([1, 136, 154, 192]), rank 0 +2024-11-23 06:24:30.925103: predicting FLAIR_567 +2024-11-23 06:24:30.942310: FLAIR_567, shape torch.Size([1, 132, 146, 197]), rank 0 +2024-11-23 06:24:31.570714: predicting FLAIR_573 +2024-11-23 06:24:31.589465: FLAIR_573, shape torch.Size([1, 131, 155, 201]), rank 0 +2024-11-23 06:24:32.230161: predicting FLAIR_574 +2024-11-23 06:24:32.249341: FLAIR_574, shape torch.Size([1, 123, 151, 193]), rank 0 +2024-11-23 06:24:34.372659: predicting FLAIR_576 +2024-11-23 06:24:34.385761: FLAIR_576, shape torch.Size([1, 138, 140, 180]), rank 0 +2024-11-23 06:24:34.984442: predicting FLAIR_588 +2024-11-23 06:24:35.019643: FLAIR_588, shape torch.Size([1, 130, 146, 187]), rank 0 +2024-11-23 06:24:35.653977: predicting FLAIR_590 +2024-11-23 06:24:35.673277: FLAIR_590, shape torch.Size([1, 129, 147, 187]), rank 0 +2024-11-23 06:24:36.308698: predicting FLAIR_592 +2024-11-23 06:24:36.328732: FLAIR_592, shape torch.Size([1, 144, 160, 200]), rank 0 +2024-11-23 06:24:36.960781: predicting FLAIR_596 +2024-11-23 06:24:36.985187: FLAIR_596, shape torch.Size([1, 133, 145, 181]), rank 0 +2024-11-23 06:24:38.315243: predicting FLAIR_608 +2024-11-23 06:24:38.329407: FLAIR_608, shape torch.Size([1, 132, 148, 196]), rank 0 +2024-11-23 06:24:38.944118: predicting FLAIR_614 +2024-11-23 06:24:38.966392: FLAIR_614, shape torch.Size([1, 135, 142, 190]), rank 0 +2024-11-23 06:24:39.798538: predicting FLAIR_616 +2024-11-23 06:24:39.812836: FLAIR_616, shape torch.Size([1, 139, 159, 176]), rank 0 +2024-11-23 06:24:40.732270: predicting FLAIR_625 +2024-11-23 06:24:40.746203: FLAIR_625, shape torch.Size([1, 135, 139, 193]), rank 0 +2024-11-23 06:24:42.659845: predicting FLAIR_628 +2024-11-23 06:24:42.672832: FLAIR_628, shape torch.Size([1, 136, 154, 196]), rank 0 +2024-11-23 06:24:43.274084: predicting FLAIR_635 +2024-11-23 06:24:43.308839: FLAIR_635, shape torch.Size([1, 141, 151, 185]), rank 0 +2024-11-23 06:24:43.909135: predicting FLAIR_636 +2024-11-23 06:24:43.966428: FLAIR_636, shape torch.Size([1, 135, 159, 207]), rank 0 +2024-11-23 06:24:44.587909: predicting FLAIR_641 +2024-11-23 06:24:44.601980: FLAIR_641, shape torch.Size([1, 138, 151, 196]), rank 0 +2024-11-23 06:24:45.424642: predicting FLAIR_654 +2024-11-23 06:24:45.437812: FLAIR_654, shape torch.Size([1, 138, 155, 192]), rank 0 +2024-11-23 06:24:47.262954: predicting FLAIR_656 +2024-11-23 06:24:47.275764: FLAIR_656, shape torch.Size([1, 127, 150, 192]), rank 0 +2024-11-23 06:24:47.921739: predicting FLAIR_657 +2024-11-23 06:24:47.941409: FLAIR_657, shape torch.Size([1, 149, 154, 180]), rank 0 +2024-11-23 06:24:48.673429: predicting FLAIR_658 +2024-11-23 06:24:48.687137: FLAIR_658, shape torch.Size([1, 135, 161, 212]), rank 0 +2024-11-23 06:24:49.321297: predicting FLAIR_661 +2024-11-23 06:24:49.344460: FLAIR_661, shape torch.Size([1, 137, 158, 190]), rank 0 +2024-11-23 06:24:50.781013: predicting FLAIR_662 +2024-11-23 06:24:50.793925: FLAIR_662, shape torch.Size([1, 130, 153, 202]), rank 0 +2024-11-23 06:24:53.018417: predicting FLAIR_667 +2024-11-23 06:24:53.030022: FLAIR_667, shape torch.Size([1, 127, 144, 187]), rank 0 +2024-11-23 06:24:53.932079: predicting FLAIR_668 +2024-11-23 06:24:53.944987: FLAIR_668, shape torch.Size([1, 136, 154, 192]), rank 0 +2024-11-23 06:25:21.353444: Validation complete +2024-11-23 06:25:21.354332: Mean Validation Dice: 0.7701944745885502 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/checkpoint_best.pth b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/checkpoint_best.pth new file mode 100644 index 0000000000000000000000000000000000000000..fbe93add42fed06721e9e61b7ea748b11466e251 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/checkpoint_best.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:370175d8d25c50fb8745fa08e7fa3815ab37d0fea358b07543ae1300a4298c73 +size 249213090 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/checkpoint_final.pth b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/checkpoint_final.pth new file mode 100644 index 0000000000000000000000000000000000000000..a07ac6eb1cbde8dd0806cef40d2ae8b3e5330564 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/checkpoint_final.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8e989caccdcf45368cc8f1ef8a00598f9f072c1fbe23e57458fc572fea434c3f +size 249222462 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/debug.json b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/debug.json new file mode 100644 index 0000000000000000000000000000000000000000..cc40313b332751ea30bf57767f4b0bcceb010e3a --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/debug.json @@ -0,0 +1,53 @@ +{ + "_best_ema": "None", + "batch_size": "2", + "configuration_manager": "{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}", + "configuration_name": "3d_fullres", + "cudnn_version": 8902, + "current_epoch": "0", + "dataloader_train": "", + "dataloader_train.generator": "", + "dataloader_train.num_processes": "12", + "dataloader_train.transform": "None", + "dataloader_val": "", + "dataloader_val.generator": "", + "dataloader_val.num_processes": "6", + "dataloader_val.transform": "None", + "dataset_json": "{'channel_names': {'0': 'FLAIR'}, 'labels': {'background': 0, 'Lesion': 1}, 'numTraining': 668, 'file_ending': '.nii.gz', 'overwrite_image_reader_writer': 'SimpleITKIO'}", + "device": "cuda:0", + "disable_checkpointing": "False", + "enable_deep_supervision": "True", + "fold": "3", + "folder_with_segs_from_previous_stage": "None", + "gpu_name": "NVIDIA H100 80GB HBM3", + "grad_scaler": "", + "hostname": "lg02e16", + "inference_allowed_mirroring_axes": "(0, 1, 2)", + "initial_lr": "0.01", + "is_cascaded": "False", + "is_ddp": "False", + "label_manager": "", + "local_rank": "0", + "log_file": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/training_log_2024_11_21_10_40_15.txt", + "logger": "", + "loss": "DeepSupervisionWrapper(\n (loss): DC_and_CE_loss(\n (ce): RobustCrossEntropyLoss()\n (dc): OptimizedModule(\n (_orig_mod): MemoryEfficientSoftDiceLoss()\n )\n )\n)", + "lr_scheduler": "", + "my_init_kwargs": "{'plans': {'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 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[True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}, 'configuration': '3d_fullres', 'fold': 3, 'dataset_json': {'channel_names': {'0': 'FLAIR'}, 'labels': {'background': 0, 'Lesion': 1}, 'numTraining': 668, 'file_ending': '.nii.gz', 'overwrite_image_reader_writer': 'SimpleITKIO'}, 'unpack_dataset': True, 'device': device(type='cuda')}", + "network": "OptimizedModule", + "num_epochs": "8000", + "num_input_channels": "1", + "num_iterations_per_epoch": "250", + "num_val_iterations_per_epoch": "50", + "optimizer": "SGD (\nParameter Group 0\n dampening: 0\n differentiable: False\n foreach: None\n initial_lr: 0.01\n lr: 0.01\n maximize: False\n momentum: 0.99\n nesterov: True\n weight_decay: 3e-05\n)", + "output_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3", + "output_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres", + "oversample_foreground_percent": "0.33", + "plans_manager": "{'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 106, 'patch_size': [160, 192], 'median_image_size_in_voxels': [154.0, 185.0], 'spacing': [0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}", + "preprocessed_dataset_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/nnUNetPlans_3d_fullres", + "preprocessed_dataset_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML", + "save_every": "50", + "torch_version": "2.1.2+cu121", + "unpack_dataset": "True", + "was_initialized": "True", + "weight_decay": "3e-05" +} \ No newline at end of file diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/progress.png b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/progress.png new file mode 100644 index 0000000000000000000000000000000000000000..2647185f1c3cd33fb648c08ce43b51116418ecd7 Binary files /dev/null and b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/progress.png differ diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/training_log_2024_11_21_10_40_15.txt b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/training_log_2024_11_21_10_40_15.txt new file mode 100644 index 0000000000000000000000000000000000000000..af3b4d82f73e2fada97f85f4b3f6bb4a2fe4f009 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_3/training_log_2024_11_21_10_40_15.txt @@ -0,0 +1,56445 @@ + +####################################################################### +Please cite the following paper when using nnU-Net: +Isensee, F., Jaeger, P. F., Kohl, S. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 18(2), 203-211. +####################################################################### + +2024-11-21 10:40:15.752875: do_dummy_2d_data_aug: False +2024-11-21 10:40:15.757275: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-21 10:40:15.758039: The split file contains 5 splits. +2024-11-21 10:40:15.758103: Desired fold for training: 3 +2024-11-21 10:40:15.758152: This split has 535 training and 133 validation cases. +2024-11-21 10:40:18.635868: Using torch.compile... + +This is the configuration used by this training: +Configuration name: 3d_fullres + {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False} + +These are the global plan.json settings: + {'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}} + +2024-11-21 10:40:19.645452: unpacking dataset... +2024-11-21 10:40:28.334299: unpacking done... +2024-11-21 10:40:28.346844: Unable to plot network architecture: nnUNet_compile is enabled! +2024-11-21 10:40:28.471222: +2024-11-21 10:40:28.471349: Epoch 0 +2024-11-21 10:40:28.471501: Current learning rate: 0.01 +2024-11-21 10:41:59.572231: train_loss -0.2129 +2024-11-21 10:41:59.574562: val_loss -0.4331 +2024-11-21 10:41:59.574657: Pseudo dice [0.5297] +2024-11-21 10:41:59.574745: Epoch time: 91.1 s +2024-11-21 10:41:59.574815: Yayy! New best EMA pseudo Dice: 0.5297 +2024-11-21 10:42:01.897748: +2024-11-21 10:42:01.902486: Epoch 1 +2024-11-21 10:42:01.902608: Current learning rate: 0.01 +2024-11-21 10:42:23.353949: train_loss -0.5145 +2024-11-21 10:42:23.384981: val_loss -0.5698 +2024-11-21 10:42:23.385113: Pseudo dice [0.7133] +2024-11-21 10:42:23.385427: Epoch time: 21.46 s +2024-11-21 10:42:23.385541: Yayy! New best EMA pseudo Dice: 0.548 +2024-11-21 10:42:24.903923: +2024-11-21 10:42:24.905165: Epoch 2 +2024-11-21 10:42:24.905310: Current learning rate: 0.01 +2024-11-21 10:42:53.456629: train_loss -0.5656 +2024-11-21 10:42:53.473180: val_loss -0.597 +2024-11-21 10:42:53.473326: Pseudo dice [0.7476] +2024-11-21 10:42:53.473425: Epoch time: 28.55 s +2024-11-21 10:42:53.473499: Yayy! New best EMA pseudo Dice: 0.568 +2024-11-21 10:42:54.506489: +2024-11-21 10:42:54.506690: Epoch 3 +2024-11-21 10:42:54.506807: Current learning rate: 0.01 +2024-11-21 10:43:13.312159: train_loss -0.5934 +2024-11-21 10:43:13.315013: val_loss -0.6238 +2024-11-21 10:43:13.315123: Pseudo dice [0.766] +2024-11-21 10:43:13.315205: Epoch time: 18.81 s +2024-11-21 10:43:13.315269: Yayy! New best EMA pseudo Dice: 0.5878 +2024-11-21 10:43:14.592092: +2024-11-21 10:43:14.592303: Epoch 4 +2024-11-21 10:43:14.592419: Current learning rate: 0.01 +2024-11-21 10:43:34.093828: train_loss -0.6165 +2024-11-21 10:43:34.099520: val_loss -0.6593 +2024-11-21 10:43:34.099658: Pseudo dice [0.7846] +2024-11-21 10:43:34.099742: Epoch time: 19.5 s +2024-11-21 10:43:34.099806: Yayy! New best EMA pseudo Dice: 0.6075 +2024-11-21 10:43:35.307264: +2024-11-21 10:43:35.307472: Epoch 5 +2024-11-21 10:43:35.307589: Current learning rate: 0.00999 +2024-11-21 10:43:54.522468: train_loss -0.6256 +2024-11-21 10:43:54.532297: val_loss -0.6412 +2024-11-21 10:43:54.532429: Pseudo dice [0.7334] +2024-11-21 10:43:54.532519: Epoch time: 19.22 s +2024-11-21 10:43:54.532587: Yayy! New best EMA pseudo Dice: 0.6201 +2024-11-21 10:43:55.539989: +2024-11-21 10:43:55.540179: Epoch 6 +2024-11-21 10:43:55.540290: Current learning rate: 0.00999 +2024-11-21 10:44:14.058213: train_loss -0.6187 +2024-11-21 10:44:14.068037: val_loss -0.6376 +2024-11-21 10:44:14.068157: Pseudo dice [0.8043] +2024-11-21 10:44:14.068237: Epoch time: 18.52 s +2024-11-21 10:44:14.068307: Yayy! New best EMA pseudo Dice: 0.6385 +2024-11-21 10:44:15.185574: +2024-11-21 10:44:15.185795: Epoch 7 +2024-11-21 10:44:15.185914: Current learning rate: 0.00999 +2024-11-21 10:44:34.765592: train_loss -0.6369 +2024-11-21 10:44:34.779763: val_loss -0.6609 +2024-11-21 10:44:34.779878: Pseudo dice [0.7828] +2024-11-21 10:44:34.779958: Epoch time: 19.58 s +2024-11-21 10:44:34.780023: Yayy! New best EMA pseudo Dice: 0.6529 +2024-11-21 10:44:36.004133: +2024-11-21 10:44:36.004341: Epoch 8 +2024-11-21 10:44:36.004450: Current learning rate: 0.00999 +2024-11-21 10:44:55.292869: train_loss -0.645 +2024-11-21 10:44:55.298420: val_loss -0.6694 +2024-11-21 10:44:55.298549: Pseudo dice [0.7881] +2024-11-21 10:44:55.298632: Epoch time: 19.29 s +2024-11-21 10:44:55.298700: Yayy! New best EMA pseudo Dice: 0.6665 +2024-11-21 10:44:56.421663: +2024-11-21 10:44:56.421866: Epoch 9 +2024-11-21 10:44:56.421983: Current learning rate: 0.00999 +2024-11-21 10:45:14.261822: train_loss -0.6693 +2024-11-21 10:45:14.271991: val_loss -0.6907 +2024-11-21 10:45:14.272167: Pseudo dice [0.8069] +2024-11-21 10:45:14.272259: Epoch time: 17.84 s +2024-11-21 10:45:14.272326: Yayy! New best EMA pseudo Dice: 0.6805 +2024-11-21 10:45:15.256811: +2024-11-21 10:45:15.257015: Epoch 10 +2024-11-21 10:45:15.257126: Current learning rate: 0.00999 +2024-11-21 10:45:33.567606: train_loss -0.6671 +2024-11-21 10:45:33.575210: val_loss -0.6661 +2024-11-21 10:45:33.575346: Pseudo dice [0.7907] +2024-11-21 10:45:33.575432: Epoch time: 18.31 s +2024-11-21 10:45:33.575501: Yayy! New best EMA pseudo Dice: 0.6915 +2024-11-21 10:45:34.563758: +2024-11-21 10:45:34.563941: Epoch 11 +2024-11-21 10:45:34.564055: Current learning rate: 0.00999 +2024-11-21 10:45:54.087044: train_loss -0.6556 +2024-11-21 10:45:54.089993: val_loss -0.7018 +2024-11-21 10:45:54.090127: Pseudo dice [0.8028] +2024-11-21 10:45:54.090215: Epoch time: 19.52 s +2024-11-21 10:45:54.090292: Yayy! New best EMA pseudo Dice: 0.7026 +2024-11-21 10:45:55.390538: +2024-11-21 10:45:55.390744: Epoch 12 +2024-11-21 10:45:55.390870: Current learning rate: 0.00999 +2024-11-21 10:46:14.282497: train_loss -0.6667 +2024-11-21 10:46:14.285277: val_loss -0.6964 +2024-11-21 10:46:14.285388: Pseudo dice [0.8037] +2024-11-21 10:46:14.285472: Epoch time: 18.89 s +2024-11-21 10:46:14.285539: Yayy! New best EMA pseudo Dice: 0.7127 +2024-11-21 10:46:15.267291: +2024-11-21 10:46:15.267489: Epoch 13 +2024-11-21 10:46:15.267597: Current learning rate: 0.00999 +2024-11-21 10:46:35.092903: train_loss -0.6702 +2024-11-21 10:46:35.106186: val_loss -0.6851 +2024-11-21 10:46:35.106313: Pseudo dice [0.7709] +2024-11-21 10:46:35.106399: Epoch time: 19.83 s +2024-11-21 10:46:35.106461: Yayy! New best EMA pseudo Dice: 0.7186 +2024-11-21 10:46:36.151915: +2024-11-21 10:46:36.152134: Epoch 14 +2024-11-21 10:46:36.152249: Current learning rate: 0.00998 +2024-11-21 10:46:55.707472: train_loss -0.6598 +2024-11-21 10:46:55.712498: val_loss -0.7021 +2024-11-21 10:46:55.712636: Pseudo dice [0.7944] +2024-11-21 10:46:55.712723: Epoch time: 19.56 s +2024-11-21 10:46:55.712793: Yayy! New best EMA pseudo Dice: 0.7261 +2024-11-21 10:46:56.717699: +2024-11-21 10:46:56.717906: Epoch 15 +2024-11-21 10:46:56.718024: Current learning rate: 0.00998 +2024-11-21 10:47:16.674982: train_loss -0.6694 +2024-11-21 10:47:16.682762: val_loss -0.7061 +2024-11-21 10:47:16.682894: Pseudo dice [0.8093] +2024-11-21 10:47:16.682977: Epoch time: 19.96 s +2024-11-21 10:47:16.683044: Yayy! New best EMA pseudo Dice: 0.7345 +2024-11-21 10:47:17.775074: +2024-11-21 10:47:17.775291: Epoch 16 +2024-11-21 10:47:17.775415: Current learning rate: 0.00998 +2024-11-21 10:47:36.540934: train_loss -0.6769 +2024-11-21 10:47:36.545855: val_loss -0.6746 +2024-11-21 10:47:36.545969: Pseudo dice [0.8069] +2024-11-21 10:47:36.546071: Epoch time: 18.77 s +2024-11-21 10:47:36.546138: Yayy! New best EMA pseudo Dice: 0.7417 +2024-11-21 10:47:37.550825: +2024-11-21 10:47:37.551013: Epoch 17 +2024-11-21 10:47:37.551139: Current learning rate: 0.00998 +2024-11-21 10:47:56.749900: train_loss -0.6992 +2024-11-21 10:47:56.761631: val_loss -0.7193 +2024-11-21 10:47:56.761761: Pseudo dice [0.8103] +2024-11-21 10:47:56.761843: Epoch time: 19.2 s +2024-11-21 10:47:56.761908: Yayy! New best EMA pseudo Dice: 0.7486 +2024-11-21 10:47:57.738588: +2024-11-21 10:47:57.738795: Epoch 18 +2024-11-21 10:47:57.738910: Current learning rate: 0.00998 +2024-11-21 10:48:17.512807: train_loss -0.6763 +2024-11-21 10:48:17.518210: val_loss -0.6925 +2024-11-21 10:48:17.518335: Pseudo dice [0.8066] +2024-11-21 10:48:17.518414: Epoch time: 19.78 s +2024-11-21 10:48:17.518480: Yayy! New best EMA pseudo Dice: 0.7544 +2024-11-21 10:48:18.501112: +2024-11-21 10:48:18.501305: Epoch 19 +2024-11-21 10:48:18.501419: Current learning rate: 0.00998 +2024-11-21 10:48:36.644988: train_loss -0.6923 +2024-11-21 10:48:36.649919: val_loss -0.7269 +2024-11-21 10:48:36.650084: Pseudo dice [0.8101] +2024-11-21 10:48:36.650166: Epoch time: 18.14 s +2024-11-21 10:48:36.650241: Yayy! New best EMA pseudo Dice: 0.7599 +2024-11-21 10:48:37.637711: +2024-11-21 10:48:37.637939: Epoch 20 +2024-11-21 10:48:37.638052: Current learning rate: 0.00998 +2024-11-21 10:48:56.296377: train_loss -0.6936 +2024-11-21 10:48:56.302076: val_loss -0.6963 +2024-11-21 10:48:56.302213: Pseudo dice [0.8012] +2024-11-21 10:48:56.302300: Epoch time: 18.66 s +2024-11-21 10:48:56.302367: Yayy! New best EMA pseudo Dice: 0.7641 +2024-11-21 10:48:57.276932: +2024-11-21 10:48:57.277117: Epoch 21 +2024-11-21 10:48:57.277233: Current learning rate: 0.00998 +2024-11-21 10:49:16.127382: train_loss -0.7012 +2024-11-21 10:49:16.129385: val_loss -0.6532 +2024-11-21 10:49:16.129492: Pseudo dice [0.7846] +2024-11-21 10:49:16.129573: Epoch time: 18.85 s +2024-11-21 10:49:16.129636: Yayy! New best EMA pseudo Dice: 0.7661 +2024-11-21 10:49:17.245578: +2024-11-21 10:49:17.245788: Epoch 22 +2024-11-21 10:49:17.245900: Current learning rate: 0.00998 +2024-11-21 10:49:35.109076: train_loss -0.7022 +2024-11-21 10:49:35.114980: val_loss -0.6922 +2024-11-21 10:49:35.115097: Pseudo dice [0.7954] +2024-11-21 10:49:35.115188: Epoch time: 17.86 s +2024-11-21 10:49:35.115456: Yayy! New best EMA pseudo Dice: 0.7691 +2024-11-21 10:49:36.099655: +2024-11-21 10:49:36.099866: Epoch 23 +2024-11-21 10:49:36.099976: Current learning rate: 0.00997 +2024-11-21 10:49:55.099986: train_loss -0.6941 +2024-11-21 10:49:55.105693: val_loss -0.724 +2024-11-21 10:49:55.105809: Pseudo dice [0.8076] +2024-11-21 10:49:55.105905: Epoch time: 19.0 s +2024-11-21 10:49:55.105977: Yayy! New best EMA pseudo Dice: 0.7729 +2024-11-21 10:49:56.167430: +2024-11-21 10:49:56.167643: Epoch 24 +2024-11-21 10:49:56.167765: Current learning rate: 0.00997 +2024-11-21 10:50:13.907925: train_loss -0.7031 +2024-11-21 10:50:13.910985: val_loss -0.7204 +2024-11-21 10:50:13.911124: Pseudo dice [0.8202] +2024-11-21 10:50:13.911211: Epoch time: 17.74 s +2024-11-21 10:50:13.911278: Yayy! New best EMA pseudo Dice: 0.7776 +2024-11-21 10:50:14.873987: +2024-11-21 10:50:14.874202: Epoch 25 +2024-11-21 10:50:14.874317: Current learning rate: 0.00997 +2024-11-21 10:50:33.800668: train_loss -0.7171 +2024-11-21 10:50:33.807108: val_loss -0.7096 +2024-11-21 10:50:33.807285: Pseudo dice [0.8222] +2024-11-21 10:50:33.807372: Epoch time: 18.93 s +2024-11-21 10:50:33.807442: Yayy! New best EMA pseudo Dice: 0.7821 +2024-11-21 10:50:34.796202: +2024-11-21 10:50:34.796399: Epoch 26 +2024-11-21 10:50:34.796515: Current learning rate: 0.00997 +2024-11-21 10:50:53.050976: train_loss -0.7068 +2024-11-21 10:50:53.058022: val_loss -0.7315 +2024-11-21 10:50:53.058141: Pseudo dice [0.8164] +2024-11-21 10:50:53.058225: Epoch time: 18.26 s +2024-11-21 10:50:53.058288: Yayy! New best EMA pseudo Dice: 0.7855 +2024-11-21 10:50:54.148506: +2024-11-21 10:50:54.148789: Epoch 27 +2024-11-21 10:50:54.148944: Current learning rate: 0.00997 +2024-11-21 10:51:11.947689: train_loss -0.7095 +2024-11-21 10:51:11.954186: val_loss -0.7408 +2024-11-21 10:51:11.954328: Pseudo dice [0.8125] +2024-11-21 10:51:11.954413: Epoch time: 17.8 s +2024-11-21 10:51:11.954477: Yayy! New best EMA pseudo Dice: 0.7882 +2024-11-21 10:51:12.946363: +2024-11-21 10:51:12.946613: Epoch 28 +2024-11-21 10:51:12.946729: Current learning rate: 0.00997 +2024-11-21 10:51:31.595666: train_loss -0.6989 +2024-11-21 10:51:31.604525: val_loss -0.6863 +2024-11-21 10:51:31.604662: Pseudo dice [0.8079] +2024-11-21 10:51:31.604741: Epoch time: 18.65 s +2024-11-21 10:51:31.604804: Yayy! New best EMA pseudo Dice: 0.7902 +2024-11-21 10:51:32.626703: +2024-11-21 10:51:32.626906: Epoch 29 +2024-11-21 10:51:32.627021: Current learning rate: 0.00997 +2024-11-21 10:51:51.280306: train_loss -0.6861 +2024-11-21 10:51:51.290248: val_loss -0.7109 +2024-11-21 10:51:51.290378: Pseudo dice [0.821] +2024-11-21 10:51:51.290460: Epoch time: 18.65 s +2024-11-21 10:51:51.290524: Yayy! New best EMA pseudo Dice: 0.7933 +2024-11-21 10:51:52.289141: +2024-11-21 10:51:52.289345: Epoch 30 +2024-11-21 10:51:52.289458: Current learning rate: 0.00997 +2024-11-21 10:52:11.648878: train_loss -0.7139 +2024-11-21 10:52:11.657085: val_loss -0.7478 +2024-11-21 10:52:11.657217: Pseudo dice [0.8296] +2024-11-21 10:52:11.657302: Epoch time: 19.36 s +2024-11-21 10:52:11.657370: Yayy! New best EMA pseudo Dice: 0.7969 +2024-11-21 10:52:12.690750: +2024-11-21 10:52:12.690962: Epoch 31 +2024-11-21 10:52:12.691089: Current learning rate: 0.00997 +2024-11-21 10:52:32.593692: train_loss -0.703 +2024-11-21 10:52:32.596498: val_loss -0.7372 +2024-11-21 10:52:32.596643: Pseudo dice [0.8231] +2024-11-21 10:52:32.596746: Epoch time: 19.9 s +2024-11-21 10:52:32.596812: Yayy! New best EMA pseudo Dice: 0.7995 +2024-11-21 10:52:33.567468: +2024-11-21 10:52:33.567694: Epoch 32 +2024-11-21 10:52:33.567806: Current learning rate: 0.00996 +2024-11-21 10:52:52.986506: train_loss -0.6936 +2024-11-21 10:52:52.993610: val_loss -0.7317 +2024-11-21 10:52:52.993736: Pseudo dice [0.8222] +2024-11-21 10:52:52.993823: Epoch time: 19.42 s +2024-11-21 10:52:52.993890: Yayy! New best EMA pseudo Dice: 0.8018 +2024-11-21 10:52:53.980797: +2024-11-21 10:52:53.981238: Epoch 33 +2024-11-21 10:52:53.981354: Current learning rate: 0.00996 +2024-11-21 10:53:13.186721: train_loss -0.7037 +2024-11-21 10:53:13.193693: val_loss -0.6978 +2024-11-21 10:53:13.193825: Pseudo dice [0.8085] +2024-11-21 10:53:13.193915: Epoch time: 19.21 s +2024-11-21 10:53:13.193986: Yayy! New best EMA pseudo Dice: 0.8025 +2024-11-21 10:53:14.223991: +2024-11-21 10:53:14.224184: Epoch 34 +2024-11-21 10:53:14.224299: Current learning rate: 0.00996 +2024-11-21 10:53:32.664526: train_loss -0.6886 +2024-11-21 10:53:32.670782: val_loss -0.7018 +2024-11-21 10:53:32.670910: Pseudo dice [0.8136] +2024-11-21 10:53:32.671005: Epoch time: 18.44 s +2024-11-21 10:53:32.671147: Yayy! New best EMA pseudo Dice: 0.8036 +2024-11-21 10:53:33.695954: +2024-11-21 10:53:33.696157: Epoch 35 +2024-11-21 10:53:33.696269: Current learning rate: 0.00996 +2024-11-21 10:53:52.329577: train_loss -0.711 +2024-11-21 10:53:52.331519: val_loss -0.7123 +2024-11-21 10:53:52.331609: Pseudo dice [0.8196] +2024-11-21 10:53:52.331691: Epoch time: 18.63 s +2024-11-21 10:53:52.331758: Yayy! New best EMA pseudo Dice: 0.8052 +2024-11-21 10:53:53.679487: +2024-11-21 10:53:53.679679: Epoch 36 +2024-11-21 10:53:53.679793: Current learning rate: 0.00996 +2024-11-21 10:54:13.242235: train_loss -0.7077 +2024-11-21 10:54:13.251456: val_loss -0.7319 +2024-11-21 10:54:13.251572: Pseudo dice [0.8218] +2024-11-21 10:54:13.251654: Epoch time: 19.56 s +2024-11-21 10:54:13.251720: Yayy! New best EMA pseudo Dice: 0.8068 +2024-11-21 10:54:14.242684: +2024-11-21 10:54:14.242874: Epoch 37 +2024-11-21 10:54:14.242988: Current learning rate: 0.00996 +2024-11-21 10:54:33.116080: train_loss -0.7091 +2024-11-21 10:54:33.123601: val_loss -0.7137 +2024-11-21 10:54:33.123717: Pseudo dice [0.8102] +2024-11-21 10:54:33.123809: Epoch time: 18.87 s +2024-11-21 10:54:33.123946: Yayy! New best EMA pseudo Dice: 0.8072 +2024-11-21 10:54:34.113009: +2024-11-21 10:54:34.113208: Epoch 38 +2024-11-21 10:54:34.113326: Current learning rate: 0.00996 +2024-11-21 10:54:53.117693: train_loss -0.7125 +2024-11-21 10:54:53.131764: val_loss -0.7325 +2024-11-21 10:54:53.131893: Pseudo dice [0.8056] +2024-11-21 10:54:53.131979: Epoch time: 19.01 s +2024-11-21 10:54:53.918046: +2024-11-21 10:54:53.918291: Epoch 39 +2024-11-21 10:54:53.918406: Current learning rate: 0.00996 +2024-11-21 10:55:12.394591: train_loss -0.713 +2024-11-21 10:55:12.402769: val_loss -0.7289 +2024-11-21 10:55:12.402900: Pseudo dice [0.8187] +2024-11-21 10:55:12.402983: Epoch time: 18.48 s +2024-11-21 10:55:12.403052: Yayy! New best EMA pseudo Dice: 0.8082 +2024-11-21 10:55:13.437978: +2024-11-21 10:55:13.438169: Epoch 40 +2024-11-21 10:55:13.438288: Current learning rate: 0.00995 +2024-11-21 10:55:32.751834: train_loss -0.7095 +2024-11-21 10:55:32.764069: val_loss -0.7477 +2024-11-21 10:55:32.764205: Pseudo dice [0.823] +2024-11-21 10:55:32.764295: Epoch time: 19.31 s +2024-11-21 10:55:32.764445: Yayy! New best EMA pseudo Dice: 0.8097 +2024-11-21 10:55:33.954501: +2024-11-21 10:55:33.954696: Epoch 41 +2024-11-21 10:55:33.954816: Current learning rate: 0.00995 +2024-11-21 10:55:52.658309: train_loss -0.7123 +2024-11-21 10:55:52.663949: val_loss -0.7368 +2024-11-21 10:55:52.664123: Pseudo dice [0.8141] +2024-11-21 10:55:52.672512: Epoch time: 18.7 s +2024-11-21 10:55:52.672652: Yayy! New best EMA pseudo Dice: 0.8101 +2024-11-21 10:55:53.683618: +2024-11-21 10:55:53.683811: Epoch 42 +2024-11-21 10:55:53.683926: Current learning rate: 0.00995 +2024-11-21 10:56:13.069878: train_loss -0.7078 +2024-11-21 10:56:13.078295: val_loss -0.7471 +2024-11-21 10:56:13.078425: Pseudo dice [0.8275] +2024-11-21 10:56:13.078506: Epoch time: 19.39 s +2024-11-21 10:56:13.078571: Yayy! New best EMA pseudo Dice: 0.8119 +2024-11-21 10:56:14.063113: +2024-11-21 10:56:14.063317: Epoch 43 +2024-11-21 10:56:14.063437: Current learning rate: 0.00995 +2024-11-21 10:56:33.517894: train_loss -0.6977 +2024-11-21 10:56:33.524430: val_loss -0.7209 +2024-11-21 10:56:33.524568: Pseudo dice [0.8357] +2024-11-21 10:56:33.524657: Epoch time: 19.46 s +2024-11-21 10:56:33.524728: Yayy! New best EMA pseudo Dice: 0.8142 +2024-11-21 10:56:34.527075: +2024-11-21 10:56:34.527525: Epoch 44 +2024-11-21 10:56:34.527639: Current learning rate: 0.00995 +2024-11-21 10:56:53.921974: train_loss -0.7145 +2024-11-21 10:56:53.928334: val_loss -0.7185 +2024-11-21 10:56:53.928489: Pseudo dice [0.8221] +2024-11-21 10:56:53.928582: Epoch time: 19.4 s +2024-11-21 10:56:53.928650: Yayy! New best EMA pseudo Dice: 0.815 +2024-11-21 10:56:55.000281: +2024-11-21 10:56:55.000489: Epoch 45 +2024-11-21 10:56:55.000599: Current learning rate: 0.00995 +2024-11-21 10:57:13.839378: train_loss -0.7068 +2024-11-21 10:57:13.843095: val_loss -0.7532 +2024-11-21 10:57:13.843238: Pseudo dice [0.8297] +2024-11-21 10:57:13.843323: Epoch time: 18.84 s +2024-11-21 10:57:13.843391: Yayy! New best EMA pseudo Dice: 0.8165 +2024-11-21 10:57:14.865877: +2024-11-21 10:57:14.866091: Epoch 46 +2024-11-21 10:57:14.866215: Current learning rate: 0.00995 +2024-11-21 10:57:33.176886: train_loss -0.726 +2024-11-21 10:57:33.184065: val_loss -0.7012 +2024-11-21 10:57:33.184192: Pseudo dice [0.8176] +2024-11-21 10:57:33.184271: Epoch time: 18.31 s +2024-11-21 10:57:33.184336: Yayy! New best EMA pseudo Dice: 0.8166 +2024-11-21 10:57:34.646047: +2024-11-21 10:57:34.646256: Epoch 47 +2024-11-21 10:57:34.646378: Current learning rate: 0.00995 +2024-11-21 10:57:52.637157: train_loss -0.7117 +2024-11-21 10:57:52.643552: val_loss -0.7287 +2024-11-21 10:57:52.643675: Pseudo dice [0.8181] +2024-11-21 10:57:52.643766: Epoch time: 17.99 s +2024-11-21 10:57:52.643837: Yayy! New best EMA pseudo Dice: 0.8168 +2024-11-21 10:57:53.606373: +2024-11-21 10:57:53.606584: Epoch 48 +2024-11-21 10:57:53.606707: Current learning rate: 0.00995 +2024-11-21 10:58:12.408169: train_loss -0.7137 +2024-11-21 10:58:12.416983: val_loss -0.738 +2024-11-21 10:58:12.417128: Pseudo dice [0.8219] +2024-11-21 10:58:12.417215: Epoch time: 18.8 s +2024-11-21 10:58:12.417280: Yayy! New best EMA pseudo Dice: 0.8173 +2024-11-21 10:58:13.429400: +2024-11-21 10:58:13.429850: Epoch 49 +2024-11-21 10:58:13.429962: Current learning rate: 0.00994 +2024-11-21 10:58:31.531700: train_loss -0.7159 +2024-11-21 10:58:31.539322: val_loss -0.7375 +2024-11-21 10:58:31.539529: Pseudo dice [0.8236] +2024-11-21 10:58:31.539615: Epoch time: 18.1 s +2024-11-21 10:58:31.887004: Yayy! New best EMA pseudo Dice: 0.8179 +2024-11-21 10:58:32.924872: +2024-11-21 10:58:32.925086: Epoch 50 +2024-11-21 10:58:32.925206: Current learning rate: 0.00994 +2024-11-21 10:58:52.034575: train_loss -0.7247 +2024-11-21 10:58:52.039480: val_loss -0.7407 +2024-11-21 10:58:52.039676: Pseudo dice [0.8333] +2024-11-21 10:58:52.039765: Epoch time: 19.11 s +2024-11-21 10:58:52.039832: Yayy! New best EMA pseudo Dice: 0.8194 +2024-11-21 10:58:53.026075: +2024-11-21 10:58:53.026285: Epoch 51 +2024-11-21 10:58:53.026403: Current learning rate: 0.00994 +2024-11-21 10:59:13.036916: train_loss -0.726 +2024-11-21 10:59:13.042748: val_loss -0.7329 +2024-11-21 10:59:13.042882: Pseudo dice [0.8303] +2024-11-21 10:59:13.042976: Epoch time: 20.01 s +2024-11-21 10:59:13.043045: Yayy! New best EMA pseudo Dice: 0.8205 +2024-11-21 10:59:14.040387: +2024-11-21 10:59:14.040606: Epoch 52 +2024-11-21 10:59:14.040726: Current learning rate: 0.00994 +2024-11-21 10:59:32.520711: train_loss -0.7173 +2024-11-21 10:59:32.528493: val_loss -0.7361 +2024-11-21 10:59:32.528659: Pseudo dice [0.8413] +2024-11-21 10:59:32.528744: Epoch time: 18.48 s +2024-11-21 10:59:32.528813: Yayy! New best EMA pseudo Dice: 0.8226 +2024-11-21 10:59:33.625638: +2024-11-21 10:59:33.625842: Epoch 53 +2024-11-21 10:59:33.625959: Current learning rate: 0.00994 +2024-11-21 10:59:51.922466: train_loss -0.7278 +2024-11-21 10:59:51.930337: val_loss -0.7468 +2024-11-21 10:59:51.930506: Pseudo dice [0.8328] +2024-11-21 10:59:51.930586: Epoch time: 18.3 s +2024-11-21 10:59:51.930649: Yayy! New best EMA pseudo Dice: 0.8236 +2024-11-21 10:59:52.971440: +2024-11-21 10:59:52.971643: Epoch 54 +2024-11-21 10:59:52.971765: Current learning rate: 0.00994 +2024-11-21 11:00:12.420830: train_loss -0.7211 +2024-11-21 11:00:12.430764: val_loss -0.7345 +2024-11-21 11:00:12.431153: Pseudo dice [0.8247] +2024-11-21 11:00:12.431266: Epoch time: 19.45 s +2024-11-21 11:00:12.431389: Yayy! New best EMA pseudo Dice: 0.8237 +2024-11-21 11:00:13.451274: +2024-11-21 11:00:13.452050: Epoch 55 +2024-11-21 11:00:13.452175: Current learning rate: 0.00994 +2024-11-21 11:00:32.523710: train_loss -0.7183 +2024-11-21 11:00:32.532838: val_loss -0.706 +2024-11-21 11:00:32.532965: Pseudo dice [0.803] +2024-11-21 11:00:32.533068: Epoch time: 19.07 s +2024-11-21 11:00:33.486583: +2024-11-21 11:00:33.486784: Epoch 56 +2024-11-21 11:00:33.486905: Current learning rate: 0.00994 +2024-11-21 11:00:52.014581: train_loss -0.7229 +2024-11-21 11:00:52.023364: val_loss -0.7211 +2024-11-21 11:00:52.023508: Pseudo dice [0.8282] +2024-11-21 11:00:52.023678: Epoch time: 18.53 s +2024-11-21 11:00:53.000844: +2024-11-21 11:00:53.001073: Epoch 57 +2024-11-21 11:00:53.001213: Current learning rate: 0.00994 +2024-11-21 11:01:11.275934: train_loss -0.7369 +2024-11-21 11:01:11.283241: val_loss -0.7227 +2024-11-21 11:01:11.283403: Pseudo dice [0.8207] +2024-11-21 11:01:11.283489: Epoch time: 18.28 s +2024-11-21 11:01:12.203302: +2024-11-21 11:01:12.203530: Epoch 58 +2024-11-21 11:01:12.203660: Current learning rate: 0.00993 +2024-11-21 11:01:31.033649: train_loss -0.7271 +2024-11-21 11:01:31.042268: val_loss -0.7519 +2024-11-21 11:01:31.042463: Pseudo dice [0.8117] +2024-11-21 11:01:31.042561: Epoch time: 18.83 s +2024-11-21 11:01:32.357126: +2024-11-21 11:01:32.357347: Epoch 59 +2024-11-21 11:01:32.357488: Current learning rate: 0.00993 +2024-11-21 11:01:51.093868: train_loss -0.7183 +2024-11-21 11:01:51.102516: val_loss -0.7103 +2024-11-21 11:01:51.102644: Pseudo dice [0.8028] +2024-11-21 11:01:51.102727: Epoch time: 18.74 s +2024-11-21 11:01:51.909825: +2024-11-21 11:01:51.910057: Epoch 60 +2024-11-21 11:01:51.910185: Current learning rate: 0.00993 +2024-11-21 11:02:10.920885: train_loss -0.7231 +2024-11-21 11:02:10.927650: val_loss -0.739 +2024-11-21 11:02:10.927807: Pseudo dice [0.8322] +2024-11-21 11:02:10.927940: Epoch time: 19.01 s +2024-11-21 11:02:11.748365: +2024-11-21 11:02:11.748594: Epoch 61 +2024-11-21 11:02:11.748713: Current learning rate: 0.00993 +2024-11-21 11:02:31.302642: train_loss -0.7258 +2024-11-21 11:02:31.304857: val_loss -0.7417 +2024-11-21 11:02:31.304990: Pseudo dice [0.8306] +2024-11-21 11:02:31.305111: Epoch time: 19.56 s +2024-11-21 11:02:32.087728: +2024-11-21 11:02:32.087954: Epoch 62 +2024-11-21 11:02:32.088097: Current learning rate: 0.00993 +2024-11-21 11:02:52.824611: train_loss -0.7203 +2024-11-21 11:02:52.830463: val_loss -0.7454 +2024-11-21 11:02:52.830602: Pseudo dice [0.8327] +2024-11-21 11:02:52.830688: Epoch time: 20.74 s +2024-11-21 11:02:53.614668: +2024-11-21 11:02:53.614859: Epoch 63 +2024-11-21 11:02:53.614986: Current learning rate: 0.00993 +2024-11-21 11:03:14.245449: train_loss -0.7314 +2024-11-21 11:03:14.252971: val_loss -0.7312 +2024-11-21 11:03:14.253132: Pseudo dice [0.822] +2024-11-21 11:03:14.253234: Epoch time: 20.63 s +2024-11-21 11:03:15.143709: +2024-11-21 11:03:15.143904: Epoch 64 +2024-11-21 11:03:15.144075: Current learning rate: 0.00993 +2024-11-21 11:03:33.601575: train_loss -0.7275 +2024-11-21 11:03:33.606267: val_loss -0.7185 +2024-11-21 11:03:33.606436: Pseudo dice [0.821] +2024-11-21 11:03:33.606522: Epoch time: 18.46 s +2024-11-21 11:03:34.441994: +2024-11-21 11:03:34.442213: Epoch 65 +2024-11-21 11:03:34.442334: Current learning rate: 0.00993 +2024-11-21 11:03:53.529913: train_loss -0.7086 +2024-11-21 11:03:53.539423: val_loss -0.7128 +2024-11-21 11:03:53.539573: Pseudo dice [0.8114] +2024-11-21 11:03:53.539663: Epoch time: 19.09 s +2024-11-21 11:03:54.327434: +2024-11-21 11:03:54.327669: Epoch 66 +2024-11-21 11:03:54.327785: Current learning rate: 0.00993 +2024-11-21 11:04:13.654490: train_loss -0.7011 +2024-11-21 11:04:13.662286: val_loss -0.7109 +2024-11-21 11:04:13.662430: Pseudo dice [0.7898] +2024-11-21 11:04:13.662522: Epoch time: 19.33 s +2024-11-21 11:04:14.453385: +2024-11-21 11:04:14.453629: Epoch 67 +2024-11-21 11:04:14.453778: Current learning rate: 0.00992 +2024-11-21 11:04:31.620110: train_loss -0.708 +2024-11-21 11:04:31.626777: val_loss -0.7268 +2024-11-21 11:04:31.626915: Pseudo dice [0.8209] +2024-11-21 11:04:31.627008: Epoch time: 17.17 s +2024-11-21 11:04:32.415499: +2024-11-21 11:04:32.415708: Epoch 68 +2024-11-21 11:04:32.415837: Current learning rate: 0.00992 +2024-11-21 11:04:51.947018: train_loss -0.7152 +2024-11-21 11:04:51.961331: val_loss -0.6892 +2024-11-21 11:04:51.961465: Pseudo dice [0.8069] +2024-11-21 11:04:51.961567: Epoch time: 19.53 s +2024-11-21 11:04:52.760390: +2024-11-21 11:04:52.760604: Epoch 69 +2024-11-21 11:04:52.760742: Current learning rate: 0.00992 +2024-11-21 11:05:11.596070: train_loss -0.7214 +2024-11-21 11:05:11.611096: val_loss -0.7388 +2024-11-21 11:05:11.611269: Pseudo dice [0.8266] +2024-11-21 11:05:11.611383: Epoch time: 18.84 s +2024-11-21 11:05:12.967710: +2024-11-21 11:05:12.967888: Epoch 70 +2024-11-21 11:05:12.968006: Current learning rate: 0.00992 +2024-11-21 11:05:31.734321: train_loss -0.7223 +2024-11-21 11:05:31.741444: val_loss -0.7403 +2024-11-21 11:05:31.741601: Pseudo dice [0.8313] +2024-11-21 11:05:31.741711: Epoch time: 18.77 s +2024-11-21 11:05:32.672649: +2024-11-21 11:05:32.672871: Epoch 71 +2024-11-21 11:05:32.673000: Current learning rate: 0.00992 +2024-11-21 11:05:51.605186: train_loss -0.7259 +2024-11-21 11:05:51.611882: val_loss -0.7184 +2024-11-21 11:05:51.612002: Pseudo dice [0.833] +2024-11-21 11:05:51.612104: Epoch time: 18.93 s +2024-11-21 11:05:52.531008: +2024-11-21 11:05:52.531226: Epoch 72 +2024-11-21 11:05:52.531359: Current learning rate: 0.00992 +2024-11-21 11:06:13.522424: train_loss -0.7247 +2024-11-21 11:06:13.529595: val_loss -0.7614 +2024-11-21 11:06:13.529740: Pseudo dice [0.8273] +2024-11-21 11:06:13.529841: Epoch time: 20.99 s +2024-11-21 11:06:14.541541: +2024-11-21 11:06:14.541770: Epoch 73 +2024-11-21 11:06:14.541890: Current learning rate: 0.00992 +2024-11-21 11:06:32.580188: train_loss -0.7176 +2024-11-21 11:06:32.588686: val_loss -0.7158 +2024-11-21 11:06:32.588900: Pseudo dice [0.7937] +2024-11-21 11:06:32.588998: Epoch time: 18.04 s +2024-11-21 11:06:33.471105: +2024-11-21 11:06:33.471317: Epoch 74 +2024-11-21 11:06:33.471462: Current learning rate: 0.00992 +2024-11-21 11:06:52.590772: train_loss -0.7228 +2024-11-21 11:06:52.593598: val_loss -0.7324 +2024-11-21 11:06:52.593714: Pseudo dice [0.8107] +2024-11-21 11:06:52.593824: Epoch time: 19.12 s +2024-11-21 11:06:53.609576: +2024-11-21 11:06:53.609802: Epoch 75 +2024-11-21 11:06:53.609918: Current learning rate: 0.00992 +2024-11-21 11:07:13.138182: train_loss -0.729 +2024-11-21 11:07:13.149763: val_loss -0.729 +2024-11-21 11:07:13.149940: Pseudo dice [0.8149] +2024-11-21 11:07:13.150037: Epoch time: 19.53 s +2024-11-21 11:07:14.091464: +2024-11-21 11:07:14.091669: Epoch 76 +2024-11-21 11:07:14.091809: Current learning rate: 0.00991 +2024-11-21 11:07:33.048916: train_loss -0.7303 +2024-11-21 11:07:33.057802: val_loss -0.7328 +2024-11-21 11:07:33.057946: Pseudo dice [0.8244] +2024-11-21 11:07:33.058051: Epoch time: 18.96 s +2024-11-21 11:07:33.863625: +2024-11-21 11:07:33.863875: Epoch 77 +2024-11-21 11:07:33.864014: Current learning rate: 0.00991 +2024-11-21 11:07:54.249791: train_loss -0.7247 +2024-11-21 11:07:54.252393: val_loss -0.7524 +2024-11-21 11:07:54.252498: Pseudo dice [0.8364] +2024-11-21 11:07:54.252596: Epoch time: 20.39 s +2024-11-21 11:07:55.041419: +2024-11-21 11:07:55.041634: Epoch 78 +2024-11-21 11:07:55.041757: Current learning rate: 0.00991 +2024-11-21 11:08:15.107571: train_loss -0.7276 +2024-11-21 11:08:15.115368: val_loss -0.7392 +2024-11-21 11:08:15.115501: Pseudo dice [0.8327] +2024-11-21 11:08:15.115589: Epoch time: 20.07 s +2024-11-21 11:08:16.031051: +2024-11-21 11:08:16.031352: Epoch 79 +2024-11-21 11:08:16.031482: Current learning rate: 0.00991 +2024-11-21 11:08:33.379777: train_loss -0.7223 +2024-11-21 11:08:33.388161: val_loss -0.732 +2024-11-21 11:08:33.388328: Pseudo dice [0.8173] +2024-11-21 11:08:33.388446: Epoch time: 17.35 s +2024-11-21 11:08:34.218091: +2024-11-21 11:08:34.220125: Epoch 80 +2024-11-21 11:08:34.220266: Current learning rate: 0.00991 +2024-11-21 11:08:52.997706: train_loss -0.7267 +2024-11-21 11:08:53.001380: val_loss -0.7468 +2024-11-21 11:08:53.001537: Pseudo dice [0.8348] +2024-11-21 11:08:53.001648: Epoch time: 18.78 s +2024-11-21 11:08:53.932306: +2024-11-21 11:08:53.932516: Epoch 81 +2024-11-21 11:08:53.932637: Current learning rate: 0.00991 +2024-11-21 11:09:13.216513: train_loss -0.7213 +2024-11-21 11:09:13.219370: val_loss -0.7604 +2024-11-21 11:09:13.219486: Pseudo dice [0.8361] +2024-11-21 11:09:13.219592: Epoch time: 19.29 s +2024-11-21 11:09:14.397853: +2024-11-21 11:09:14.398071: Epoch 82 +2024-11-21 11:09:14.398193: Current learning rate: 0.00991 +2024-11-21 11:09:33.367951: train_loss -0.7261 +2024-11-21 11:09:33.388001: val_loss -0.7388 +2024-11-21 11:09:33.388160: Pseudo dice [0.8131] +2024-11-21 11:09:33.388251: Epoch time: 18.97 s +2024-11-21 11:09:34.369255: +2024-11-21 11:09:34.369486: Epoch 83 +2024-11-21 11:09:34.369606: Current learning rate: 0.00991 +2024-11-21 11:09:54.282832: train_loss -0.7271 +2024-11-21 11:09:54.288693: val_loss -0.7262 +2024-11-21 11:09:54.288888: Pseudo dice [0.8302] +2024-11-21 11:09:54.289012: Epoch time: 19.91 s +2024-11-21 11:09:55.109873: +2024-11-21 11:09:55.110107: Epoch 84 +2024-11-21 11:09:55.110229: Current learning rate: 0.00991 +2024-11-21 11:10:13.482877: train_loss -0.7063 +2024-11-21 11:10:13.488840: val_loss -0.7401 +2024-11-21 11:10:13.488980: Pseudo dice [0.8347] +2024-11-21 11:10:13.489109: Epoch time: 18.37 s +2024-11-21 11:10:13.489189: Yayy! New best EMA pseudo Dice: 0.8245 +2024-11-21 11:10:14.648582: +2024-11-21 11:10:14.648813: Epoch 85 +2024-11-21 11:10:14.648942: Current learning rate: 0.0099 +2024-11-21 11:10:33.057901: train_loss -0.7246 +2024-11-21 11:10:33.061210: val_loss -0.7425 +2024-11-21 11:10:33.061362: Pseudo dice [0.8239] +2024-11-21 11:10:33.061454: Epoch time: 18.41 s +2024-11-21 11:10:33.922768: +2024-11-21 11:10:33.922987: Epoch 86 +2024-11-21 11:10:33.923107: Current learning rate: 0.0099 +2024-11-21 11:10:53.721603: train_loss -0.7184 +2024-11-21 11:10:53.724395: val_loss -0.7492 +2024-11-21 11:10:53.724516: Pseudo dice [0.8318] +2024-11-21 11:10:53.724604: Epoch time: 19.8 s +2024-11-21 11:10:53.724672: Yayy! New best EMA pseudo Dice: 0.8252 +2024-11-21 11:10:54.791682: +2024-11-21 11:10:54.791891: Epoch 87 +2024-11-21 11:10:54.792031: Current learning rate: 0.0099 +2024-11-21 11:11:13.401225: train_loss -0.7209 +2024-11-21 11:11:13.417996: val_loss -0.7329 +2024-11-21 11:11:13.418193: Pseudo dice [0.8338] +2024-11-21 11:11:13.418307: Epoch time: 18.61 s +2024-11-21 11:11:13.418395: Yayy! New best EMA pseudo Dice: 0.8261 +2024-11-21 11:11:14.488587: +2024-11-21 11:11:14.488799: Epoch 88 +2024-11-21 11:11:14.488931: Current learning rate: 0.0099 +2024-11-21 11:11:34.041348: train_loss -0.7253 +2024-11-21 11:11:34.050014: val_loss -0.7289 +2024-11-21 11:11:34.050259: Pseudo dice [0.8201] +2024-11-21 11:11:34.050355: Epoch time: 19.55 s +2024-11-21 11:11:34.949713: +2024-11-21 11:11:34.949922: Epoch 89 +2024-11-21 11:11:34.950071: Current learning rate: 0.0099 +2024-11-21 11:11:55.475081: train_loss -0.7217 +2024-11-21 11:11:55.482746: val_loss -0.753 +2024-11-21 11:11:55.482878: Pseudo dice [0.8359] +2024-11-21 11:11:55.482971: Epoch time: 20.53 s +2024-11-21 11:11:55.483066: Yayy! New best EMA pseudo Dice: 0.8265 +2024-11-21 11:11:56.738401: +2024-11-21 11:11:56.738614: Epoch 90 +2024-11-21 11:11:56.738741: Current learning rate: 0.0099 +2024-11-21 11:12:15.751811: train_loss -0.6977 +2024-11-21 11:12:15.761529: val_loss -0.716 +2024-11-21 11:12:15.761746: Pseudo dice [0.8197] +2024-11-21 11:12:15.761857: Epoch time: 19.01 s +2024-11-21 11:12:16.799374: +2024-11-21 11:12:16.799585: Epoch 91 +2024-11-21 11:12:16.799717: Current learning rate: 0.0099 +2024-11-21 11:12:35.749223: train_loss -0.732 +2024-11-21 11:12:35.756055: val_loss -0.7126 +2024-11-21 11:12:35.756449: Pseudo dice [0.8324] +2024-11-21 11:12:35.756592: Epoch time: 18.95 s +2024-11-21 11:12:36.706767: +2024-11-21 11:12:36.706978: Epoch 92 +2024-11-21 11:12:36.707110: Current learning rate: 0.0099 +2024-11-21 11:12:55.964614: train_loss -0.7215 +2024-11-21 11:12:55.972630: val_loss -0.7434 +2024-11-21 11:12:55.972756: Pseudo dice [0.8287] +2024-11-21 11:12:55.972853: Epoch time: 19.26 s +2024-11-21 11:12:55.972918: Yayy! New best EMA pseudo Dice: 0.8267 +2024-11-21 11:12:56.963107: +2024-11-21 11:12:56.963318: Epoch 93 +2024-11-21 11:12:56.963456: Current learning rate: 0.0099 +2024-11-21 11:13:17.133457: train_loss -0.7067 +2024-11-21 11:13:17.141213: val_loss -0.747 +2024-11-21 11:13:17.141354: Pseudo dice [0.8307] +2024-11-21 11:13:17.141458: Epoch time: 20.17 s +2024-11-21 11:13:17.141536: Yayy! New best EMA pseudo Dice: 0.8271 +2024-11-21 11:13:18.549194: +2024-11-21 11:13:18.549440: Epoch 94 +2024-11-21 11:13:18.549571: Current learning rate: 0.00989 +2024-11-21 11:13:37.752730: train_loss -0.7283 +2024-11-21 11:13:37.761145: val_loss -0.7515 +2024-11-21 11:13:37.761288: Pseudo dice [0.8404] +2024-11-21 11:13:37.761384: Epoch time: 19.2 s +2024-11-21 11:13:37.761468: Yayy! New best EMA pseudo Dice: 0.8284 +2024-11-21 11:13:39.044332: +2024-11-21 11:13:39.044552: Epoch 95 +2024-11-21 11:13:39.044681: Current learning rate: 0.00989 +2024-11-21 11:13:58.006444: train_loss -0.7327 +2024-11-21 11:13:58.012601: val_loss -0.7458 +2024-11-21 11:13:58.012779: Pseudo dice [0.8248] +2024-11-21 11:13:58.012877: Epoch time: 18.96 s +2024-11-21 11:13:58.878865: +2024-11-21 11:13:58.879090: Epoch 96 +2024-11-21 11:13:58.879217: Current learning rate: 0.00989 +2024-11-21 11:14:18.322970: train_loss -0.7362 +2024-11-21 11:14:18.327310: val_loss -0.7297 +2024-11-21 11:14:18.327445: Pseudo dice [0.8094] +2024-11-21 11:14:18.327532: Epoch time: 19.44 s +2024-11-21 11:14:19.320226: +2024-11-21 11:14:19.320435: Epoch 97 +2024-11-21 11:14:19.320580: Current learning rate: 0.00989 +2024-11-21 11:14:38.069714: train_loss -0.7249 +2024-11-21 11:14:38.072634: val_loss -0.7587 +2024-11-21 11:14:38.072742: Pseudo dice [0.8371] +2024-11-21 11:14:38.072833: Epoch time: 18.75 s +2024-11-21 11:14:38.848559: +2024-11-21 11:14:38.848764: Epoch 98 +2024-11-21 11:14:38.848885: Current learning rate: 0.00989 +2024-11-21 11:14:58.126272: train_loss -0.7318 +2024-11-21 11:14:58.129611: val_loss -0.7667 +2024-11-21 11:14:58.129749: Pseudo dice [0.8455] +2024-11-21 11:14:58.129830: Epoch time: 19.28 s +2024-11-21 11:14:58.129896: Yayy! New best EMA pseudo Dice: 0.8291 +2024-11-21 11:14:59.122405: +2024-11-21 11:14:59.122609: Epoch 99 +2024-11-21 11:14:59.122736: Current learning rate: 0.00989 +2024-11-21 11:15:19.061667: train_loss -0.7323 +2024-11-21 11:15:19.063935: val_loss -0.7479 +2024-11-21 11:15:19.064071: Pseudo dice [0.8322] +2024-11-21 11:15:19.064159: Epoch time: 19.94 s +2024-11-21 11:15:19.392848: Yayy! New best EMA pseudo Dice: 0.8294 +2024-11-21 11:15:20.372420: +2024-11-21 11:15:20.372619: Epoch 100 +2024-11-21 11:15:20.372740: Current learning rate: 0.00989 +2024-11-21 11:15:41.062696: train_loss -0.7223 +2024-11-21 11:15:41.069804: val_loss -0.7232 +2024-11-21 11:15:41.069938: Pseudo dice [0.8203] +2024-11-21 11:15:41.070051: Epoch time: 20.69 s +2024-11-21 11:15:42.056608: +2024-11-21 11:15:42.056829: Epoch 101 +2024-11-21 11:15:42.056951: Current learning rate: 0.00989 +2024-11-21 11:16:01.634315: train_loss -0.7313 +2024-11-21 11:16:01.639383: val_loss -0.7256 +2024-11-21 11:16:01.639513: Pseudo dice [0.8242] +2024-11-21 11:16:01.639618: Epoch time: 19.58 s +2024-11-21 11:16:02.531464: +2024-11-21 11:16:02.531679: Epoch 102 +2024-11-21 11:16:02.531808: Current learning rate: 0.00989 +2024-11-21 11:16:21.900292: train_loss -0.7205 +2024-11-21 11:16:21.905562: val_loss -0.7298 +2024-11-21 11:16:21.905698: Pseudo dice [0.8351] +2024-11-21 11:16:21.905799: Epoch time: 19.37 s +2024-11-21 11:16:22.914750: +2024-11-21 11:16:22.914974: Epoch 103 +2024-11-21 11:16:22.915101: Current learning rate: 0.00988 +2024-11-21 11:16:41.417689: train_loss -0.7429 +2024-11-21 11:16:41.419823: val_loss -0.7501 +2024-11-21 11:16:41.420219: Pseudo dice [0.8239] +2024-11-21 11:16:41.420356: Epoch time: 18.5 s +2024-11-21 11:16:42.355010: +2024-11-21 11:16:42.355211: Epoch 104 +2024-11-21 11:16:42.355347: Current learning rate: 0.00988 +2024-11-21 11:17:01.511224: train_loss -0.7411 +2024-11-21 11:17:01.521846: val_loss -0.7319 +2024-11-21 11:17:01.522000: Pseudo dice [0.8372] +2024-11-21 11:17:01.522131: Epoch time: 19.16 s +2024-11-21 11:17:02.397416: +2024-11-21 11:17:02.397627: Epoch 105 +2024-11-21 11:17:02.397758: Current learning rate: 0.00988 +2024-11-21 11:17:21.444008: train_loss -0.734 +2024-11-21 11:17:21.446424: val_loss -0.753 +2024-11-21 11:17:21.446525: Pseudo dice [0.8343] +2024-11-21 11:17:21.446612: Epoch time: 19.05 s +2024-11-21 11:17:21.446674: Yayy! New best EMA pseudo Dice: 0.8297 +2024-11-21 11:17:22.428523: +2024-11-21 11:17:22.428743: Epoch 106 +2024-11-21 11:17:22.428885: Current learning rate: 0.00988 +2024-11-21 11:17:41.587837: train_loss -0.7325 +2024-11-21 11:17:41.593420: val_loss -0.748 +2024-11-21 11:17:41.593551: Pseudo dice [0.8274] +2024-11-21 11:17:41.593655: Epoch time: 19.16 s +2024-11-21 11:17:42.368801: +2024-11-21 11:17:42.369025: Epoch 107 +2024-11-21 11:17:42.369166: Current learning rate: 0.00988 +2024-11-21 11:18:00.390788: train_loss -0.7362 +2024-11-21 11:18:00.397042: val_loss -0.7387 +2024-11-21 11:18:00.397160: Pseudo dice [0.8445] +2024-11-21 11:18:00.397261: Epoch time: 18.02 s +2024-11-21 11:18:00.397333: Yayy! New best EMA pseudo Dice: 0.831 +2024-11-21 11:18:01.454487: +2024-11-21 11:18:01.454682: Epoch 108 +2024-11-21 11:18:01.454798: Current learning rate: 0.00988 +2024-11-21 11:18:19.474266: train_loss -0.7418 +2024-11-21 11:18:19.483395: val_loss -0.7721 +2024-11-21 11:18:19.483558: Pseudo dice [0.8443] +2024-11-21 11:18:19.483676: Epoch time: 18.02 s +2024-11-21 11:18:19.483773: Yayy! New best EMA pseudo Dice: 0.8323 +2024-11-21 11:18:20.582875: +2024-11-21 11:18:20.583117: Epoch 109 +2024-11-21 11:18:20.583231: Current learning rate: 0.00988 +2024-11-21 11:18:39.372461: train_loss -0.7418 +2024-11-21 11:18:39.379665: val_loss -0.7183 +2024-11-21 11:18:39.379828: Pseudo dice [0.849] +2024-11-21 11:18:39.379933: Epoch time: 18.79 s +2024-11-21 11:18:39.380004: Yayy! New best EMA pseudo Dice: 0.834 +2024-11-21 11:18:40.538801: +2024-11-21 11:18:40.539007: Epoch 110 +2024-11-21 11:18:40.539131: Current learning rate: 0.00988 +2024-11-21 11:18:59.857229: train_loss -0.7217 +2024-11-21 11:18:59.864040: val_loss -0.7333 +2024-11-21 11:18:59.864163: Pseudo dice [0.8251] +2024-11-21 11:18:59.864256: Epoch time: 19.32 s +2024-11-21 11:19:00.654867: +2024-11-21 11:19:00.655097: Epoch 111 +2024-11-21 11:19:00.655213: Current learning rate: 0.00988 +2024-11-21 11:19:19.418428: train_loss -0.7316 +2024-11-21 11:19:19.420407: val_loss -0.7481 +2024-11-21 11:19:19.420501: Pseudo dice [0.8372] +2024-11-21 11:19:19.420578: Epoch time: 18.76 s +2024-11-21 11:19:20.200246: +2024-11-21 11:19:20.200484: Epoch 112 +2024-11-21 11:19:20.200628: Current learning rate: 0.00987 +2024-11-21 11:19:39.080243: train_loss -0.7123 +2024-11-21 11:19:39.082349: val_loss -0.737 +2024-11-21 11:19:39.082461: Pseudo dice [0.8239] +2024-11-21 11:19:39.082570: Epoch time: 18.88 s +2024-11-21 11:19:39.861723: +2024-11-21 11:19:39.861919: Epoch 113 +2024-11-21 11:19:39.862041: Current learning rate: 0.00987 +2024-11-21 11:19:59.568669: train_loss -0.7131 +2024-11-21 11:19:59.578180: val_loss -0.736 +2024-11-21 11:19:59.578328: Pseudo dice [0.8226] +2024-11-21 11:19:59.578433: Epoch time: 19.71 s +2024-11-21 11:20:00.362017: +2024-11-21 11:20:00.362253: Epoch 114 +2024-11-21 11:20:00.362392: Current learning rate: 0.00987 +2024-11-21 11:20:18.327595: train_loss -0.7411 +2024-11-21 11:20:18.332718: val_loss -0.7478 +2024-11-21 11:20:18.332844: Pseudo dice [0.8271] +2024-11-21 11:20:18.332939: Epoch time: 17.97 s +2024-11-21 11:20:19.233494: +2024-11-21 11:20:19.233701: Epoch 115 +2024-11-21 11:20:19.233834: Current learning rate: 0.00987 +2024-11-21 11:20:38.654888: train_loss -0.7322 +2024-11-21 11:20:38.660119: val_loss -0.7347 +2024-11-21 11:20:38.671535: Pseudo dice [0.8301] +2024-11-21 11:20:38.671992: Epoch time: 19.42 s +2024-11-21 11:20:39.496771: +2024-11-21 11:20:39.496982: Epoch 116 +2024-11-21 11:20:39.497118: Current learning rate: 0.00987 +2024-11-21 11:20:59.174595: train_loss -0.7397 +2024-11-21 11:20:59.176436: val_loss -0.7228 +2024-11-21 11:20:59.176558: Pseudo dice [0.8102] +2024-11-21 11:20:59.176653: Epoch time: 19.68 s +2024-11-21 11:21:00.354232: +2024-11-21 11:21:00.354475: Epoch 117 +2024-11-21 11:21:00.354600: Current learning rate: 0.00987 +2024-11-21 11:21:19.881792: train_loss -0.7347 +2024-11-21 11:21:19.889008: val_loss -0.7393 +2024-11-21 11:21:19.891092: Pseudo dice [0.8402] +2024-11-21 11:21:19.891239: Epoch time: 19.53 s +2024-11-21 11:21:20.830437: +2024-11-21 11:21:20.830656: Epoch 118 +2024-11-21 11:21:20.830788: Current learning rate: 0.00987 +2024-11-21 11:21:40.193467: train_loss -0.723 +2024-11-21 11:21:40.204846: val_loss -0.7288 +2024-11-21 11:21:40.204982: Pseudo dice [0.8204] +2024-11-21 11:21:40.205090: Epoch time: 19.36 s +2024-11-21 11:21:41.114622: +2024-11-21 11:21:41.114839: Epoch 119 +2024-11-21 11:21:41.114960: Current learning rate: 0.00987 +2024-11-21 11:22:01.263242: train_loss -0.7356 +2024-11-21 11:22:01.265930: val_loss -0.7493 +2024-11-21 11:22:01.266069: Pseudo dice [0.8235] +2024-11-21 11:22:01.266179: Epoch time: 20.15 s +2024-11-21 11:22:02.112738: +2024-11-21 11:22:02.112947: Epoch 120 +2024-11-21 11:22:02.113076: Current learning rate: 0.00986 +2024-11-21 11:22:20.897722: train_loss -0.7339 +2024-11-21 11:22:20.900858: val_loss -0.7415 +2024-11-21 11:22:20.900969: Pseudo dice [0.8295] +2024-11-21 11:22:20.901053: Epoch time: 18.79 s +2024-11-21 11:22:21.705785: +2024-11-21 11:22:21.705988: Epoch 121 +2024-11-21 11:22:21.706115: Current learning rate: 0.00986 +2024-11-21 11:22:40.888383: train_loss -0.7257 +2024-11-21 11:22:40.899790: val_loss -0.7169 +2024-11-21 11:22:40.899925: Pseudo dice [0.8362] +2024-11-21 11:22:40.900022: Epoch time: 19.18 s +2024-11-21 11:22:41.931101: +2024-11-21 11:22:41.931331: Epoch 122 +2024-11-21 11:22:41.931462: Current learning rate: 0.00986 +2024-11-21 11:23:01.889428: train_loss -0.7319 +2024-11-21 11:23:01.891824: val_loss -0.7382 +2024-11-21 11:23:01.891929: Pseudo dice [0.8466] +2024-11-21 11:23:01.892033: Epoch time: 19.96 s +2024-11-21 11:23:02.676957: +2024-11-21 11:23:02.677174: Epoch 123 +2024-11-21 11:23:02.677315: Current learning rate: 0.00986 +2024-11-21 11:23:21.016037: train_loss -0.7286 +2024-11-21 11:23:21.021863: val_loss -0.7341 +2024-11-21 11:23:21.022008: Pseudo dice [0.8361] +2024-11-21 11:23:21.022110: Epoch time: 18.34 s +2024-11-21 11:23:21.909747: +2024-11-21 11:23:21.910023: Epoch 124 +2024-11-21 11:23:21.910245: Current learning rate: 0.00986 +2024-11-21 11:23:40.578290: train_loss -0.7282 +2024-11-21 11:23:40.583554: val_loss -0.7321 +2024-11-21 11:23:40.583707: Pseudo dice [0.8335] +2024-11-21 11:23:40.583820: Epoch time: 18.67 s +2024-11-21 11:23:41.425966: +2024-11-21 11:23:41.426165: Epoch 125 +2024-11-21 11:23:41.426281: Current learning rate: 0.00986 +2024-11-21 11:24:00.580924: train_loss -0.7272 +2024-11-21 11:24:00.587807: val_loss -0.7626 +2024-11-21 11:24:00.587986: Pseudo dice [0.8247] +2024-11-21 11:24:00.588083: Epoch time: 19.16 s +2024-11-21 11:24:01.492567: +2024-11-21 11:24:01.492785: Epoch 126 +2024-11-21 11:24:01.492925: Current learning rate: 0.00986 +2024-11-21 11:24:20.661873: train_loss -0.7372 +2024-11-21 11:24:20.664340: val_loss -0.7517 +2024-11-21 11:24:20.664461: Pseudo dice [0.8485] +2024-11-21 11:24:20.664552: Epoch time: 19.17 s +2024-11-21 11:24:21.691805: +2024-11-21 11:24:21.693883: Epoch 127 +2024-11-21 11:24:21.694074: Current learning rate: 0.00986 +2024-11-21 11:24:40.565989: train_loss -0.7189 +2024-11-21 11:24:40.568390: val_loss -0.736 +2024-11-21 11:24:40.568486: Pseudo dice [0.8185] +2024-11-21 11:24:40.568577: Epoch time: 18.87 s +2024-11-21 11:24:41.699501: +2024-11-21 11:24:41.699667: Epoch 128 +2024-11-21 11:24:41.699781: Current learning rate: 0.00986 +2024-11-21 11:25:01.924391: train_loss -0.7236 +2024-11-21 11:25:01.933063: val_loss -0.7657 +2024-11-21 11:25:01.933188: Pseudo dice [0.8364] +2024-11-21 11:25:01.933348: Epoch time: 20.23 s +2024-11-21 11:25:02.880480: +2024-11-21 11:25:02.880721: Epoch 129 +2024-11-21 11:25:02.880837: Current learning rate: 0.00985 +2024-11-21 11:25:21.125198: train_loss -0.7172 +2024-11-21 11:25:21.133939: val_loss -0.653 +2024-11-21 11:25:21.134096: Pseudo dice [0.7293] +2024-11-21 11:25:21.134192: Epoch time: 18.25 s +2024-11-21 11:25:21.990541: +2024-11-21 11:25:21.990807: Epoch 130 +2024-11-21 11:25:21.990933: Current learning rate: 0.00985 +2024-11-21 11:25:41.780613: train_loss -0.7118 +2024-11-21 11:25:41.792137: val_loss -0.7518 +2024-11-21 11:25:41.792260: Pseudo dice [0.8311] +2024-11-21 11:25:41.792353: Epoch time: 19.79 s +2024-11-21 11:25:42.786820: +2024-11-21 11:25:42.787076: Epoch 131 +2024-11-21 11:25:42.787212: Current learning rate: 0.00985 +2024-11-21 11:26:02.501930: train_loss -0.7069 +2024-11-21 11:26:02.508698: val_loss -0.7255 +2024-11-21 11:26:02.508839: Pseudo dice [0.8166] +2024-11-21 11:26:02.508929: Epoch time: 19.72 s +2024-11-21 11:26:03.386899: +2024-11-21 11:26:03.387125: Epoch 132 +2024-11-21 11:26:03.387267: Current learning rate: 0.00985 +2024-11-21 11:26:22.011791: train_loss -0.7347 +2024-11-21 11:26:22.015319: val_loss -0.7238 +2024-11-21 11:26:22.015458: Pseudo dice [0.8174] +2024-11-21 11:26:22.015546: Epoch time: 18.63 s +2024-11-21 11:26:22.811658: +2024-11-21 11:26:22.811860: Epoch 133 +2024-11-21 11:26:22.811988: Current learning rate: 0.00985 +2024-11-21 11:26:42.600590: train_loss -0.7369 +2024-11-21 11:26:42.611696: val_loss -0.7588 +2024-11-21 11:26:42.611858: Pseudo dice [0.8421] +2024-11-21 11:26:42.611950: Epoch time: 19.79 s +2024-11-21 11:26:43.571472: +2024-11-21 11:26:43.571671: Epoch 134 +2024-11-21 11:26:43.571787: Current learning rate: 0.00985 +2024-11-21 11:27:03.056899: train_loss -0.7281 +2024-11-21 11:27:03.066933: val_loss -0.7367 +2024-11-21 11:27:03.067088: Pseudo dice [0.8227] +2024-11-21 11:27:03.067204: Epoch time: 19.49 s +2024-11-21 11:27:03.971902: +2024-11-21 11:27:03.972178: Epoch 135 +2024-11-21 11:27:03.972318: Current learning rate: 0.00985 +2024-11-21 11:27:21.840042: train_loss -0.7413 +2024-11-21 11:27:21.843135: val_loss -0.748 +2024-11-21 11:27:21.843253: Pseudo dice [0.8286] +2024-11-21 11:27:21.843353: Epoch time: 17.87 s +2024-11-21 11:27:22.638875: +2024-11-21 11:27:22.639093: Epoch 136 +2024-11-21 11:27:22.639230: Current learning rate: 0.00985 +2024-11-21 11:27:41.223313: train_loss -0.7366 +2024-11-21 11:27:41.228848: val_loss -0.7353 +2024-11-21 11:27:41.228998: Pseudo dice [0.8359] +2024-11-21 11:27:41.229087: Epoch time: 18.59 s +2024-11-21 11:27:42.076512: +2024-11-21 11:27:42.076730: Epoch 137 +2024-11-21 11:27:42.076847: Current learning rate: 0.00985 +2024-11-21 11:28:00.846513: train_loss -0.7448 +2024-11-21 11:28:00.848719: val_loss -0.7621 +2024-11-21 11:28:00.848842: Pseudo dice [0.8247] +2024-11-21 11:28:00.848930: Epoch time: 18.77 s +2024-11-21 11:28:01.788254: +2024-11-21 11:28:01.788442: Epoch 138 +2024-11-21 11:28:01.788560: Current learning rate: 0.00984 +2024-11-21 11:28:19.553775: train_loss -0.7354 +2024-11-21 11:28:19.561002: val_loss -0.7207 +2024-11-21 11:28:19.561146: Pseudo dice [0.8237] +2024-11-21 11:28:19.561253: Epoch time: 17.77 s +2024-11-21 11:28:20.417912: +2024-11-21 11:28:20.418123: Epoch 139 +2024-11-21 11:28:20.418248: Current learning rate: 0.00984 +2024-11-21 11:28:39.276544: train_loss -0.7334 +2024-11-21 11:28:39.279180: val_loss -0.7354 +2024-11-21 11:28:39.279301: Pseudo dice [0.8229] +2024-11-21 11:28:39.279400: Epoch time: 18.86 s +2024-11-21 11:28:40.483811: +2024-11-21 11:28:40.484041: Epoch 140 +2024-11-21 11:28:40.484161: Current learning rate: 0.00984 +2024-11-21 11:28:59.144202: train_loss -0.7349 +2024-11-21 11:28:59.149696: val_loss -0.7306 +2024-11-21 11:28:59.149828: Pseudo dice [0.8105] +2024-11-21 11:28:59.149942: Epoch time: 18.66 s +2024-11-21 11:29:00.179429: +2024-11-21 11:29:00.179929: Epoch 141 +2024-11-21 11:29:00.180052: Current learning rate: 0.00984 +2024-11-21 11:29:19.591428: train_loss -0.7389 +2024-11-21 11:29:19.598216: val_loss -0.7392 +2024-11-21 11:29:19.598352: Pseudo dice [0.8386] +2024-11-21 11:29:19.598790: Epoch time: 19.41 s +2024-11-21 11:29:20.628214: +2024-11-21 11:29:20.628450: Epoch 142 +2024-11-21 11:29:20.628567: Current learning rate: 0.00984 +2024-11-21 11:29:39.426098: train_loss -0.7422 +2024-11-21 11:29:39.428549: val_loss -0.7223 +2024-11-21 11:29:39.428673: Pseudo dice [0.8426] +2024-11-21 11:29:39.428777: Epoch time: 18.8 s +2024-11-21 11:29:40.227843: +2024-11-21 11:29:40.228037: Epoch 143 +2024-11-21 11:29:40.228168: Current learning rate: 0.00984 +2024-11-21 11:29:59.508525: train_loss -0.7459 +2024-11-21 11:29:59.513997: val_loss -0.7229 +2024-11-21 11:29:59.514136: Pseudo dice [0.8329] +2024-11-21 11:29:59.514236: Epoch time: 19.28 s +2024-11-21 11:30:00.472406: +2024-11-21 11:30:00.472614: Epoch 144 +2024-11-21 11:30:00.472738: Current learning rate: 0.00984 +2024-11-21 11:30:19.163288: train_loss -0.7356 +2024-11-21 11:30:19.171365: val_loss -0.754 +2024-11-21 11:30:19.171513: Pseudo dice [0.8243] +2024-11-21 11:30:19.171608: Epoch time: 18.69 s +2024-11-21 11:30:19.987933: +2024-11-21 11:30:19.988159: Epoch 145 +2024-11-21 11:30:19.988277: Current learning rate: 0.00984 +2024-11-21 11:30:39.001842: train_loss -0.7303 +2024-11-21 11:30:39.005909: val_loss -0.7418 +2024-11-21 11:30:39.006031: Pseudo dice [0.8397] +2024-11-21 11:30:39.006165: Epoch time: 19.01 s +2024-11-21 11:30:39.810238: +2024-11-21 11:30:39.810451: Epoch 146 +2024-11-21 11:30:39.810596: Current learning rate: 0.00984 +2024-11-21 11:30:59.094440: train_loss -0.7391 +2024-11-21 11:30:59.098763: val_loss -0.7305 +2024-11-21 11:30:59.098863: Pseudo dice [0.8182] +2024-11-21 11:30:59.099005: Epoch time: 19.29 s +2024-11-21 11:30:59.888684: +2024-11-21 11:30:59.888910: Epoch 147 +2024-11-21 11:30:59.889036: Current learning rate: 0.00983 +2024-11-21 11:31:18.854726: train_loss -0.7443 +2024-11-21 11:31:18.861338: val_loss -0.7608 +2024-11-21 11:31:18.861569: Pseudo dice [0.8373] +2024-11-21 11:31:18.861686: Epoch time: 18.97 s +2024-11-21 11:31:19.708511: +2024-11-21 11:31:19.708712: Epoch 148 +2024-11-21 11:31:19.708834: Current learning rate: 0.00983 +2024-11-21 11:31:38.183351: train_loss -0.7443 +2024-11-21 11:31:38.194560: val_loss -0.7537 +2024-11-21 11:31:38.194709: Pseudo dice [0.8489] +2024-11-21 11:31:38.194814: Epoch time: 18.48 s +2024-11-21 11:31:39.066542: +2024-11-21 11:31:39.066737: Epoch 149 +2024-11-21 11:31:39.066855: Current learning rate: 0.00983 +2024-11-21 11:31:58.687114: train_loss -0.7381 +2024-11-21 11:31:58.689306: val_loss -0.7476 +2024-11-21 11:31:58.689470: Pseudo dice [0.8314] +2024-11-21 11:31:58.689578: Epoch time: 19.62 s +2024-11-21 11:31:59.726086: +2024-11-21 11:31:59.726434: Epoch 150 +2024-11-21 11:31:59.726570: Current learning rate: 0.00983 +2024-11-21 11:32:18.276139: train_loss -0.7327 +2024-11-21 11:32:18.283088: val_loss -0.7402 +2024-11-21 11:32:18.283231: Pseudo dice [0.8275] +2024-11-21 11:32:18.283333: Epoch time: 18.55 s +2024-11-21 11:32:19.532614: +2024-11-21 11:32:19.532887: Epoch 151 +2024-11-21 11:32:19.533005: Current learning rate: 0.00983 +2024-11-21 11:32:39.115862: train_loss -0.7395 +2024-11-21 11:32:39.132750: val_loss -0.7704 +2024-11-21 11:32:39.132878: Pseudo dice [0.8301] +2024-11-21 11:32:39.132969: Epoch time: 19.58 s +2024-11-21 11:32:40.071054: +2024-11-21 11:32:40.071292: Epoch 152 +2024-11-21 11:32:40.071431: Current learning rate: 0.00983 +2024-11-21 11:32:59.499219: train_loss -0.7407 +2024-11-21 11:32:59.502188: val_loss -0.7531 +2024-11-21 11:32:59.502324: Pseudo dice [0.8476] +2024-11-21 11:32:59.502414: Epoch time: 19.43 s +2024-11-21 11:33:00.303639: +2024-11-21 11:33:00.303868: Epoch 153 +2024-11-21 11:33:00.303988: Current learning rate: 0.00983 +2024-11-21 11:33:19.479409: train_loss -0.7372 +2024-11-21 11:33:19.486312: val_loss -0.7383 +2024-11-21 11:33:19.486447: Pseudo dice [0.8446] +2024-11-21 11:33:19.486843: Epoch time: 19.18 s +2024-11-21 11:33:20.364875: +2024-11-21 11:33:20.365126: Epoch 154 +2024-11-21 11:33:20.365241: Current learning rate: 0.00983 +2024-11-21 11:33:39.887258: train_loss -0.7445 +2024-11-21 11:33:39.894428: val_loss -0.748 +2024-11-21 11:33:39.894583: Pseudo dice [0.8579] +2024-11-21 11:33:39.894687: Epoch time: 19.52 s +2024-11-21 11:33:39.894787: Yayy! New best EMA pseudo Dice: 0.8356 +2024-11-21 11:33:41.037517: +2024-11-21 11:33:41.037764: Epoch 155 +2024-11-21 11:33:41.037889: Current learning rate: 0.00983 +2024-11-21 11:33:59.348980: train_loss -0.7408 +2024-11-21 11:33:59.352514: val_loss -0.7535 +2024-11-21 11:33:59.352620: Pseudo dice [0.8357] +2024-11-21 11:33:59.352721: Epoch time: 18.31 s +2024-11-21 11:33:59.352794: Yayy! New best EMA pseudo Dice: 0.8356 +2024-11-21 11:34:00.387287: +2024-11-21 11:34:00.387502: Epoch 156 +2024-11-21 11:34:00.387629: Current learning rate: 0.00982 +2024-11-21 11:34:20.721355: train_loss -0.7494 +2024-11-21 11:34:20.724569: val_loss -0.7632 +2024-11-21 11:34:20.724668: Pseudo dice [0.8395] +2024-11-21 11:34:20.724757: Epoch time: 20.33 s +2024-11-21 11:34:20.724833: Yayy! New best EMA pseudo Dice: 0.836 +2024-11-21 11:34:21.748444: +2024-11-21 11:34:21.748651: Epoch 157 +2024-11-21 11:34:21.748769: Current learning rate: 0.00982 +2024-11-21 11:34:40.053960: train_loss -0.7513 +2024-11-21 11:34:40.060023: val_loss -0.7454 +2024-11-21 11:34:40.060165: Pseudo dice [0.8266] +2024-11-21 11:34:40.060263: Epoch time: 18.31 s +2024-11-21 11:34:40.901297: +2024-11-21 11:34:40.901494: Epoch 158 +2024-11-21 11:34:40.901606: Current learning rate: 0.00982 +2024-11-21 11:35:00.811354: train_loss -0.7471 +2024-11-21 11:35:00.817910: val_loss -0.7615 +2024-11-21 11:35:00.818082: Pseudo dice [0.8459] +2024-11-21 11:35:00.818181: Epoch time: 19.91 s +2024-11-21 11:35:00.818262: Yayy! New best EMA pseudo Dice: 0.8362 +2024-11-21 11:35:01.851190: +2024-11-21 11:35:01.851400: Epoch 159 +2024-11-21 11:35:01.851537: Current learning rate: 0.00982 +2024-11-21 11:35:19.626840: train_loss -0.7377 +2024-11-21 11:35:19.634359: val_loss -0.7523 +2024-11-21 11:35:19.634481: Pseudo dice [0.8334] +2024-11-21 11:35:19.634575: Epoch time: 17.78 s +2024-11-21 11:35:20.636264: +2024-11-21 11:35:20.636467: Epoch 160 +2024-11-21 11:35:20.636585: Current learning rate: 0.00982 +2024-11-21 11:35:39.510533: train_loss -0.7321 +2024-11-21 11:35:39.523943: val_loss -0.737 +2024-11-21 11:35:39.524096: Pseudo dice [0.8237] +2024-11-21 11:35:39.524220: Epoch time: 18.88 s +2024-11-21 11:35:40.444251: +2024-11-21 11:35:40.444462: Epoch 161 +2024-11-21 11:35:40.444601: Current learning rate: 0.00982 +2024-11-21 11:35:59.341908: train_loss -0.7359 +2024-11-21 11:35:59.361159: val_loss -0.7503 +2024-11-21 11:35:59.361291: Pseudo dice [0.8358] +2024-11-21 11:35:59.361373: Epoch time: 18.9 s +2024-11-21 11:36:00.625299: +2024-11-21 11:36:00.625531: Epoch 162 +2024-11-21 11:36:00.625661: Current learning rate: 0.00982 +2024-11-21 11:36:19.168148: train_loss -0.7347 +2024-11-21 11:36:19.182035: val_loss -0.7577 +2024-11-21 11:36:19.182178: Pseudo dice [0.8122] +2024-11-21 11:36:19.182274: Epoch time: 18.54 s +2024-11-21 11:36:20.135168: +2024-11-21 11:36:20.135394: Epoch 163 +2024-11-21 11:36:20.135512: Current learning rate: 0.00982 +2024-11-21 11:36:39.423397: train_loss -0.7269 +2024-11-21 11:36:39.431737: val_loss -0.7412 +2024-11-21 11:36:39.431881: Pseudo dice [0.8329] +2024-11-21 11:36:39.431972: Epoch time: 19.29 s +2024-11-21 11:36:40.235288: +2024-11-21 11:36:40.235521: Epoch 164 +2024-11-21 11:36:40.235644: Current learning rate: 0.00982 +2024-11-21 11:36:58.933233: train_loss -0.7347 +2024-11-21 11:36:58.935801: val_loss -0.7283 +2024-11-21 11:36:58.935939: Pseudo dice [0.8312] +2024-11-21 11:36:58.936035: Epoch time: 18.7 s +2024-11-21 11:36:59.725012: +2024-11-21 11:36:59.725244: Epoch 165 +2024-11-21 11:36:59.725366: Current learning rate: 0.00981 +2024-11-21 11:37:18.923267: train_loss -0.7347 +2024-11-21 11:37:18.924846: val_loss -0.7594 +2024-11-21 11:37:18.946385: Pseudo dice [0.83] +2024-11-21 11:37:18.946492: Epoch time: 19.2 s +2024-11-21 11:37:19.736644: +2024-11-21 11:37:19.736855: Epoch 166 +2024-11-21 11:37:19.736979: Current learning rate: 0.00981 +2024-11-21 11:37:39.016720: train_loss -0.7258 +2024-11-21 11:37:39.029897: val_loss -0.7482 +2024-11-21 11:37:39.030104: Pseudo dice [0.8263] +2024-11-21 11:37:39.030207: Epoch time: 19.28 s +2024-11-21 11:37:39.933711: +2024-11-21 11:37:39.933932: Epoch 167 +2024-11-21 11:37:39.934072: Current learning rate: 0.00981 +2024-11-21 11:37:59.873850: train_loss -0.7341 +2024-11-21 11:37:59.880876: val_loss -0.7353 +2024-11-21 11:37:59.881028: Pseudo dice [0.8171] +2024-11-21 11:37:59.881130: Epoch time: 19.94 s +2024-11-21 11:38:00.682465: +2024-11-21 11:38:00.682658: Epoch 168 +2024-11-21 11:38:00.682782: Current learning rate: 0.00981 +2024-11-21 11:38:19.510191: train_loss -0.733 +2024-11-21 11:38:19.519413: val_loss -0.7542 +2024-11-21 11:38:19.519553: Pseudo dice [0.8436] +2024-11-21 11:38:19.519649: Epoch time: 18.83 s +2024-11-21 11:38:20.557423: +2024-11-21 11:38:20.557625: Epoch 169 +2024-11-21 11:38:20.557755: Current learning rate: 0.00981 +2024-11-21 11:38:40.190308: train_loss -0.7366 +2024-11-21 11:38:40.212612: val_loss -0.732 +2024-11-21 11:38:40.212769: Pseudo dice [0.8296] +2024-11-21 11:38:40.212856: Epoch time: 19.63 s +2024-11-21 11:38:41.102425: +2024-11-21 11:38:41.102673: Epoch 170 +2024-11-21 11:38:41.102821: Current learning rate: 0.00981 +2024-11-21 11:38:59.975968: train_loss -0.7411 +2024-11-21 11:38:59.984444: val_loss -0.7529 +2024-11-21 11:38:59.984586: Pseudo dice [0.8358] +2024-11-21 11:38:59.984670: Epoch time: 18.87 s +2024-11-21 11:39:00.881252: +2024-11-21 11:39:00.881488: Epoch 171 +2024-11-21 11:39:00.881630: Current learning rate: 0.00981 +2024-11-21 11:39:20.483537: train_loss -0.7333 +2024-11-21 11:39:20.491782: val_loss -0.7541 +2024-11-21 11:39:20.491966: Pseudo dice [0.8334] +2024-11-21 11:39:20.492087: Epoch time: 19.6 s +2024-11-21 11:39:21.314903: +2024-11-21 11:39:21.315215: Epoch 172 +2024-11-21 11:39:21.315364: Current learning rate: 0.00981 +2024-11-21 11:39:41.035307: train_loss -0.7296 +2024-11-21 11:39:41.043898: val_loss -0.6935 +2024-11-21 11:39:41.044034: Pseudo dice [0.8156] +2024-11-21 11:39:41.044135: Epoch time: 19.72 s +2024-11-21 11:39:42.527893: +2024-11-21 11:39:42.528121: Epoch 173 +2024-11-21 11:39:42.528240: Current learning rate: 0.00981 +2024-11-21 11:40:02.644937: train_loss -0.7134 +2024-11-21 11:40:02.650854: val_loss -0.741 +2024-11-21 11:40:02.651003: Pseudo dice [0.8297] +2024-11-21 11:40:02.651107: Epoch time: 20.12 s +2024-11-21 11:40:03.458906: +2024-11-21 11:40:03.459168: Epoch 174 +2024-11-21 11:40:03.459288: Current learning rate: 0.0098 +2024-11-21 11:40:22.654762: train_loss -0.7335 +2024-11-21 11:40:22.660671: val_loss -0.7481 +2024-11-21 11:40:22.660794: Pseudo dice [0.8437] +2024-11-21 11:40:22.660886: Epoch time: 19.2 s +2024-11-21 11:40:23.471061: +2024-11-21 11:40:23.471291: Epoch 175 +2024-11-21 11:40:23.471415: Current learning rate: 0.0098 +2024-11-21 11:40:42.200756: train_loss -0.7354 +2024-11-21 11:40:42.211016: val_loss -0.7531 +2024-11-21 11:40:42.211187: Pseudo dice [0.8314] +2024-11-21 11:40:42.211306: Epoch time: 18.73 s +2024-11-21 11:40:43.062327: +2024-11-21 11:40:43.062540: Epoch 176 +2024-11-21 11:40:43.062660: Current learning rate: 0.0098 +2024-11-21 11:41:01.834731: train_loss -0.7473 +2024-11-21 11:41:01.842033: val_loss -0.7476 +2024-11-21 11:41:01.842181: Pseudo dice [0.8343] +2024-11-21 11:41:01.842295: Epoch time: 18.77 s +2024-11-21 11:41:02.649097: +2024-11-21 11:41:02.649307: Epoch 177 +2024-11-21 11:41:02.649430: Current learning rate: 0.0098 +2024-11-21 11:41:21.829466: train_loss -0.731 +2024-11-21 11:41:21.836628: val_loss -0.7438 +2024-11-21 11:41:21.836766: Pseudo dice [0.8215] +2024-11-21 11:41:21.836854: Epoch time: 19.18 s +2024-11-21 11:41:22.800198: +2024-11-21 11:41:22.800404: Epoch 178 +2024-11-21 11:41:22.800536: Current learning rate: 0.0098 +2024-11-21 11:41:41.807154: train_loss -0.7419 +2024-11-21 11:41:41.810131: val_loss -0.7092 +2024-11-21 11:41:41.810264: Pseudo dice [0.8122] +2024-11-21 11:41:41.810376: Epoch time: 19.01 s +2024-11-21 11:41:42.700972: +2024-11-21 11:41:42.701195: Epoch 179 +2024-11-21 11:41:42.701334: Current learning rate: 0.0098 +2024-11-21 11:42:01.221445: train_loss -0.7361 +2024-11-21 11:42:01.227384: val_loss -0.7332 +2024-11-21 11:42:01.227525: Pseudo dice [0.8317] +2024-11-21 11:42:01.227627: Epoch time: 18.52 s +2024-11-21 11:42:02.027222: +2024-11-21 11:42:02.027436: Epoch 180 +2024-11-21 11:42:02.027574: Current learning rate: 0.0098 +2024-11-21 11:42:19.822165: train_loss -0.7391 +2024-11-21 11:42:19.825739: val_loss -0.7111 +2024-11-21 11:42:19.825881: Pseudo dice [0.8011] +2024-11-21 11:42:19.825969: Epoch time: 17.8 s +2024-11-21 11:42:20.629749: +2024-11-21 11:42:20.629952: Epoch 181 +2024-11-21 11:42:20.630086: Current learning rate: 0.0098 +2024-11-21 11:42:39.681859: train_loss -0.7195 +2024-11-21 11:42:39.686678: val_loss -0.7294 +2024-11-21 11:42:39.686798: Pseudo dice [0.8308] +2024-11-21 11:42:39.686910: Epoch time: 19.05 s +2024-11-21 11:42:40.630458: +2024-11-21 11:42:40.630666: Epoch 182 +2024-11-21 11:42:40.630798: Current learning rate: 0.0098 +2024-11-21 11:42:59.494600: train_loss -0.7232 +2024-11-21 11:42:59.502673: val_loss -0.7501 +2024-11-21 11:42:59.502821: Pseudo dice [0.8301] +2024-11-21 11:42:59.502930: Epoch time: 18.86 s +2024-11-21 11:43:00.484414: +2024-11-21 11:43:00.484694: Epoch 183 +2024-11-21 11:43:00.484814: Current learning rate: 0.00979 +2024-11-21 11:43:19.088207: train_loss -0.7359 +2024-11-21 11:43:19.093984: val_loss -0.7647 +2024-11-21 11:43:19.094121: Pseudo dice [0.8336] +2024-11-21 11:43:19.094253: Epoch time: 18.6 s +2024-11-21 11:43:20.296726: +2024-11-21 11:43:20.296966: Epoch 184 +2024-11-21 11:43:20.297087: Current learning rate: 0.00979 +2024-11-21 11:43:39.953053: train_loss -0.7308 +2024-11-21 11:43:39.961821: val_loss -0.7447 +2024-11-21 11:43:39.961953: Pseudo dice [0.8351] +2024-11-21 11:43:39.962040: Epoch time: 19.66 s +2024-11-21 11:43:40.765980: +2024-11-21 11:43:40.766199: Epoch 185 +2024-11-21 11:43:40.769532: Current learning rate: 0.00979 +2024-11-21 11:43:58.552220: train_loss -0.7296 +2024-11-21 11:43:58.559092: val_loss -0.749 +2024-11-21 11:43:58.559233: Pseudo dice [0.8366] +2024-11-21 11:43:58.559334: Epoch time: 17.79 s +2024-11-21 11:43:59.359645: +2024-11-21 11:43:59.359887: Epoch 186 +2024-11-21 11:43:59.360009: Current learning rate: 0.00979 +2024-11-21 11:44:18.798786: train_loss -0.7312 +2024-11-21 11:44:18.800830: val_loss -0.7406 +2024-11-21 11:44:18.800941: Pseudo dice [0.8226] +2024-11-21 11:44:18.801040: Epoch time: 19.44 s +2024-11-21 11:44:19.594105: +2024-11-21 11:44:19.594308: Epoch 187 +2024-11-21 11:44:19.594442: Current learning rate: 0.00979 +2024-11-21 11:44:37.881179: train_loss -0.741 +2024-11-21 11:44:37.887318: val_loss -0.7473 +2024-11-21 11:44:37.887452: Pseudo dice [0.8372] +2024-11-21 11:44:37.887537: Epoch time: 18.29 s +2024-11-21 11:44:38.773992: +2024-11-21 11:44:38.774190: Epoch 188 +2024-11-21 11:44:38.774303: Current learning rate: 0.00979 +2024-11-21 11:44:58.264595: train_loss -0.7339 +2024-11-21 11:44:58.273314: val_loss -0.749 +2024-11-21 11:44:58.273461: Pseudo dice [0.8189] +2024-11-21 11:44:58.273554: Epoch time: 19.49 s +2024-11-21 11:44:59.068656: +2024-11-21 11:44:59.068880: Epoch 189 +2024-11-21 11:44:59.069015: Current learning rate: 0.00979 +2024-11-21 11:45:17.839152: train_loss -0.7392 +2024-11-21 11:45:17.841428: val_loss -0.7629 +2024-11-21 11:45:17.841539: Pseudo dice [0.8305] +2024-11-21 11:45:17.841641: Epoch time: 18.77 s +2024-11-21 11:45:18.639665: +2024-11-21 11:45:18.639878: Epoch 190 +2024-11-21 11:45:18.639996: Current learning rate: 0.00979 +2024-11-21 11:45:37.222288: train_loss -0.7298 +2024-11-21 11:45:37.229731: val_loss -0.7336 +2024-11-21 11:45:37.229880: Pseudo dice [0.8352] +2024-11-21 11:45:37.229970: Epoch time: 18.58 s +2024-11-21 11:45:38.020850: +2024-11-21 11:45:38.021057: Epoch 191 +2024-11-21 11:45:38.021428: Current learning rate: 0.00978 +2024-11-21 11:45:56.327130: train_loss -0.7321 +2024-11-21 11:45:56.329892: val_loss -0.7432 +2024-11-21 11:45:56.330020: Pseudo dice [0.8461] +2024-11-21 11:45:56.330107: Epoch time: 18.31 s +2024-11-21 11:45:57.173054: +2024-11-21 11:45:57.173331: Epoch 192 +2024-11-21 11:45:57.173467: Current learning rate: 0.00978 +2024-11-21 11:46:15.943004: train_loss -0.7358 +2024-11-21 11:46:15.964530: val_loss -0.7396 +2024-11-21 11:46:15.964670: Pseudo dice [0.8324] +2024-11-21 11:46:15.964778: Epoch time: 18.77 s +2024-11-21 11:46:16.770755: +2024-11-21 11:46:16.771378: Epoch 193 +2024-11-21 11:46:16.771495: Current learning rate: 0.00978 +2024-11-21 11:46:35.206543: train_loss -0.7346 +2024-11-21 11:46:35.209321: val_loss -0.7285 +2024-11-21 11:46:35.209446: Pseudo dice [0.8332] +2024-11-21 11:46:35.209549: Epoch time: 18.44 s +2024-11-21 11:46:36.009210: +2024-11-21 11:46:36.009431: Epoch 194 +2024-11-21 11:46:36.009546: Current learning rate: 0.00978 +2024-11-21 11:46:54.552123: train_loss -0.746 +2024-11-21 11:46:54.554913: val_loss -0.7505 +2024-11-21 11:46:54.555035: Pseudo dice [0.8345] +2024-11-21 11:46:54.555122: Epoch time: 18.54 s +2024-11-21 11:46:55.347705: +2024-11-21 11:46:55.347903: Epoch 195 +2024-11-21 11:46:55.348023: Current learning rate: 0.00978 +2024-11-21 11:47:14.665198: train_loss -0.7397 +2024-11-21 11:47:14.677124: val_loss -0.7376 +2024-11-21 11:47:14.677274: Pseudo dice [0.8321] +2024-11-21 11:47:14.677374: Epoch time: 19.32 s +2024-11-21 11:47:15.491864: +2024-11-21 11:47:15.492144: Epoch 196 +2024-11-21 11:47:15.492278: Current learning rate: 0.00978 +2024-11-21 11:47:33.619520: train_loss -0.7428 +2024-11-21 11:47:33.643445: val_loss -0.744 +2024-11-21 11:47:33.643596: Pseudo dice [0.8335] +2024-11-21 11:47:33.643698: Epoch time: 18.13 s +2024-11-21 11:47:34.507872: +2024-11-21 11:47:34.508098: Epoch 197 +2024-11-21 11:47:34.508211: Current learning rate: 0.00978 +2024-11-21 11:47:53.566499: train_loss -0.7453 +2024-11-21 11:47:53.573818: val_loss -0.745 +2024-11-21 11:47:53.573957: Pseudo dice [0.8308] +2024-11-21 11:47:53.574072: Epoch time: 19.06 s +2024-11-21 11:47:54.506316: +2024-11-21 11:47:54.506590: Epoch 198 +2024-11-21 11:47:54.506723: Current learning rate: 0.00978 +2024-11-21 11:48:13.826345: train_loss -0.7372 +2024-11-21 11:48:13.832952: val_loss -0.7465 +2024-11-21 11:48:13.833100: Pseudo dice [0.8301] +2024-11-21 11:48:13.833193: Epoch time: 19.32 s +2024-11-21 11:48:14.662012: +2024-11-21 11:48:14.662241: Epoch 199 +2024-11-21 11:48:14.662364: Current learning rate: 0.00978 +2024-11-21 11:48:33.802186: train_loss -0.755 +2024-11-21 11:48:33.814831: val_loss -0.7317 +2024-11-21 11:48:33.814971: Pseudo dice [0.8372] +2024-11-21 11:48:33.815090: Epoch time: 19.14 s +2024-11-21 11:48:34.853033: +2024-11-21 11:48:34.853255: Epoch 200 +2024-11-21 11:48:34.853382: Current learning rate: 0.00977 +2024-11-21 11:48:52.986000: train_loss -0.7435 +2024-11-21 11:48:52.992651: val_loss -0.7579 +2024-11-21 11:48:52.992870: Pseudo dice [0.854] +2024-11-21 11:48:52.992962: Epoch time: 18.13 s +2024-11-21 11:48:53.891036: +2024-11-21 11:48:53.891269: Epoch 201 +2024-11-21 11:48:53.891395: Current learning rate: 0.00977 +2024-11-21 11:49:12.925261: train_loss -0.7502 +2024-11-21 11:49:12.937721: val_loss -0.7495 +2024-11-21 11:49:12.937849: Pseudo dice [0.8474] +2024-11-21 11:49:12.937935: Epoch time: 19.04 s +2024-11-21 11:49:13.930946: +2024-11-21 11:49:13.931159: Epoch 202 +2024-11-21 11:49:13.931282: Current learning rate: 0.00977 +2024-11-21 11:49:33.582946: train_loss -0.7389 +2024-11-21 11:49:33.595832: val_loss -0.7355 +2024-11-21 11:49:33.595963: Pseudo dice [0.8301] +2024-11-21 11:49:33.596072: Epoch time: 19.65 s +2024-11-21 11:49:34.579824: +2024-11-21 11:49:34.580040: Epoch 203 +2024-11-21 11:49:34.580159: Current learning rate: 0.00977 +2024-11-21 11:49:53.222996: train_loss -0.7357 +2024-11-21 11:49:53.231482: val_loss -0.7568 +2024-11-21 11:49:53.231700: Pseudo dice [0.8162] +2024-11-21 11:49:53.231806: Epoch time: 18.64 s +2024-11-21 11:49:54.065270: +2024-11-21 11:49:54.065502: Epoch 204 +2024-11-21 11:49:54.065624: Current learning rate: 0.00977 +2024-11-21 11:50:13.093119: train_loss -0.7383 +2024-11-21 11:50:13.103748: val_loss -0.7387 +2024-11-21 11:50:13.103914: Pseudo dice [0.8355] +2024-11-21 11:50:13.104020: Epoch time: 19.03 s +2024-11-21 11:50:14.021823: +2024-11-21 11:50:14.022050: Epoch 205 +2024-11-21 11:50:14.022178: Current learning rate: 0.00977 +2024-11-21 11:50:33.228239: train_loss -0.7298 +2024-11-21 11:50:33.240793: val_loss -0.7479 +2024-11-21 11:50:33.240942: Pseudo dice [0.8348] +2024-11-21 11:50:33.241056: Epoch time: 19.21 s +2024-11-21 11:50:34.096187: +2024-11-21 11:50:34.096388: Epoch 206 +2024-11-21 11:50:34.096522: Current learning rate: 0.00977 +2024-11-21 11:50:53.403116: train_loss -0.7497 +2024-11-21 11:50:53.405670: val_loss -0.7429 +2024-11-21 11:50:53.405853: Pseudo dice [0.8292] +2024-11-21 11:50:53.405939: Epoch time: 19.31 s +2024-11-21 11:50:54.249373: +2024-11-21 11:50:54.249618: Epoch 207 +2024-11-21 11:50:54.249737: Current learning rate: 0.00977 +2024-11-21 11:51:13.117739: train_loss -0.7452 +2024-11-21 11:51:13.122838: val_loss -0.7256 +2024-11-21 11:51:13.122955: Pseudo dice [0.8427] +2024-11-21 11:51:13.123042: Epoch time: 18.87 s +2024-11-21 11:51:13.895319: +2024-11-21 11:51:13.895548: Epoch 208 +2024-11-21 11:51:13.895690: Current learning rate: 0.00977 +2024-11-21 11:51:33.265934: train_loss -0.7304 +2024-11-21 11:51:33.273533: val_loss -0.7563 +2024-11-21 11:51:33.273674: Pseudo dice [0.847] +2024-11-21 11:51:33.273766: Epoch time: 19.37 s +2024-11-21 11:51:34.046105: +2024-11-21 11:51:34.046322: Epoch 209 +2024-11-21 11:51:34.046456: Current learning rate: 0.00976 +2024-11-21 11:51:54.051664: train_loss -0.723 +2024-11-21 11:51:54.058638: val_loss -0.7626 +2024-11-21 11:51:54.058779: Pseudo dice [0.8424] +2024-11-21 11:51:54.058864: Epoch time: 20.01 s +2024-11-21 11:51:54.960781: +2024-11-21 11:51:54.961021: Epoch 210 +2024-11-21 11:51:54.961164: Current learning rate: 0.00976 +2024-11-21 11:52:14.232456: train_loss -0.7294 +2024-11-21 11:52:14.240706: val_loss -0.7568 +2024-11-21 11:52:14.240831: Pseudo dice [0.851] +2024-11-21 11:52:14.240926: Epoch time: 19.27 s +2024-11-21 11:52:14.241012: Yayy! New best EMA pseudo Dice: 0.8376 +2024-11-21 11:52:15.238586: +2024-11-21 11:52:15.239035: Epoch 211 +2024-11-21 11:52:15.239162: Current learning rate: 0.00976 +2024-11-21 11:52:34.935676: train_loss -0.7388 +2024-11-21 11:52:34.943264: val_loss -0.7628 +2024-11-21 11:52:34.943427: Pseudo dice [0.8479] +2024-11-21 11:52:34.943591: Epoch time: 19.7 s +2024-11-21 11:52:34.943677: Yayy! New best EMA pseudo Dice: 0.8386 +2024-11-21 11:52:35.958653: +2024-11-21 11:52:35.958892: Epoch 212 +2024-11-21 11:52:35.959008: Current learning rate: 0.00976 +2024-11-21 11:52:55.438084: train_loss -0.7146 +2024-11-21 11:52:55.444178: val_loss -0.7467 +2024-11-21 11:52:55.444333: Pseudo dice [0.8334] +2024-11-21 11:52:55.444419: Epoch time: 19.48 s +2024-11-21 11:52:56.221067: +2024-11-21 11:52:56.221282: Epoch 213 +2024-11-21 11:52:56.221418: Current learning rate: 0.00976 +2024-11-21 11:53:15.463547: train_loss -0.7373 +2024-11-21 11:53:15.469748: val_loss -0.6976 +2024-11-21 11:53:15.469895: Pseudo dice [0.7737] +2024-11-21 11:53:15.470037: Epoch time: 19.24 s +2024-11-21 11:53:16.242984: +2024-11-21 11:53:16.243203: Epoch 214 +2024-11-21 11:53:16.243327: Current learning rate: 0.00976 +2024-11-21 11:53:35.026281: train_loss -0.7246 +2024-11-21 11:53:35.034572: val_loss -0.7317 +2024-11-21 11:53:35.034718: Pseudo dice [0.829] +2024-11-21 11:53:35.034881: Epoch time: 18.78 s +2024-11-21 11:53:35.893605: +2024-11-21 11:53:35.893816: Epoch 215 +2024-11-21 11:53:35.893943: Current learning rate: 0.00976 +2024-11-21 11:53:54.230538: train_loss -0.7452 +2024-11-21 11:53:54.238800: val_loss -0.7421 +2024-11-21 11:53:54.238995: Pseudo dice [0.8433] +2024-11-21 11:53:54.239096: Epoch time: 18.34 s +2024-11-21 11:53:55.122166: +2024-11-21 11:53:55.122380: Epoch 216 +2024-11-21 11:53:55.122744: Current learning rate: 0.00976 +2024-11-21 11:54:14.661173: train_loss -0.7391 +2024-11-21 11:54:14.668567: val_loss -0.7475 +2024-11-21 11:54:14.668694: Pseudo dice [0.8263] +2024-11-21 11:54:14.668804: Epoch time: 19.54 s +2024-11-21 11:54:15.463733: +2024-11-21 11:54:15.463938: Epoch 217 +2024-11-21 11:54:15.464054: Current learning rate: 0.00976 +2024-11-21 11:54:34.135937: train_loss -0.7438 +2024-11-21 11:54:34.139055: val_loss -0.7573 +2024-11-21 11:54:34.139199: Pseudo dice [0.8424] +2024-11-21 11:54:34.139297: Epoch time: 18.67 s +2024-11-21 11:54:34.969488: +2024-11-21 11:54:34.969713: Epoch 218 +2024-11-21 11:54:34.969834: Current learning rate: 0.00975 +2024-11-21 11:54:53.758140: train_loss -0.7388 +2024-11-21 11:54:53.763079: val_loss -0.7579 +2024-11-21 11:54:53.763231: Pseudo dice [0.8416] +2024-11-21 11:54:53.763335: Epoch time: 18.79 s +2024-11-21 11:54:54.531553: +2024-11-21 11:54:54.531757: Epoch 219 +2024-11-21 11:54:54.531881: Current learning rate: 0.00975 +2024-11-21 11:55:13.796189: train_loss -0.7348 +2024-11-21 11:55:13.801450: val_loss -0.7249 +2024-11-21 11:55:13.801576: Pseudo dice [0.8251] +2024-11-21 11:55:13.801672: Epoch time: 19.27 s +2024-11-21 11:55:14.635458: +2024-11-21 11:55:14.635706: Epoch 220 +2024-11-21 11:55:14.635825: Current learning rate: 0.00975 +2024-11-21 11:55:33.008838: train_loss -0.7342 +2024-11-21 11:55:33.015737: val_loss -0.7504 +2024-11-21 11:55:33.015849: Pseudo dice [0.8351] +2024-11-21 11:55:33.015938: Epoch time: 18.37 s +2024-11-21 11:55:33.793661: +2024-11-21 11:55:33.793873: Epoch 221 +2024-11-21 11:55:33.793985: Current learning rate: 0.00975 +2024-11-21 11:55:52.231442: train_loss -0.7415 +2024-11-21 11:55:52.237489: val_loss -0.7756 +2024-11-21 11:55:52.237619: Pseudo dice [0.8474] +2024-11-21 11:55:52.237715: Epoch time: 18.44 s +2024-11-21 11:55:53.341163: +2024-11-21 11:55:53.341450: Epoch 222 +2024-11-21 11:55:53.341564: Current learning rate: 0.00975 +2024-11-21 11:56:11.828525: train_loss -0.7496 +2024-11-21 11:56:11.835191: val_loss -0.7337 +2024-11-21 11:56:11.835322: Pseudo dice [0.8276] +2024-11-21 11:56:11.835423: Epoch time: 18.49 s +2024-11-21 11:56:12.612600: +2024-11-21 11:56:12.612796: Epoch 223 +2024-11-21 11:56:12.612921: Current learning rate: 0.00975 +2024-11-21 11:56:32.512685: train_loss -0.7275 +2024-11-21 11:56:32.518519: val_loss -0.73 +2024-11-21 11:56:32.518657: Pseudo dice [0.8299] +2024-11-21 11:56:32.518750: Epoch time: 19.9 s +2024-11-21 11:56:33.304144: +2024-11-21 11:56:33.304356: Epoch 224 +2024-11-21 11:56:33.304498: Current learning rate: 0.00975 +2024-11-21 11:56:52.115700: train_loss -0.7291 +2024-11-21 11:56:52.121169: val_loss -0.7531 +2024-11-21 11:56:52.121316: Pseudo dice [0.8309] +2024-11-21 11:56:52.121473: Epoch time: 18.81 s +2024-11-21 11:56:53.031158: +2024-11-21 11:56:53.031348: Epoch 225 +2024-11-21 11:56:53.031475: Current learning rate: 0.00975 +2024-11-21 11:57:11.639080: train_loss -0.7389 +2024-11-21 11:57:11.645693: val_loss -0.7608 +2024-11-21 11:57:11.645844: Pseudo dice [0.84] +2024-11-21 11:57:11.645937: Epoch time: 18.61 s +2024-11-21 11:57:12.611661: +2024-11-21 11:57:12.611873: Epoch 226 +2024-11-21 11:57:12.612004: Current learning rate: 0.00975 +2024-11-21 11:57:32.120373: train_loss -0.7347 +2024-11-21 11:57:32.126750: val_loss -0.7224 +2024-11-21 11:57:32.126876: Pseudo dice [0.8281] +2024-11-21 11:57:32.126967: Epoch time: 19.51 s +2024-11-21 11:57:33.216961: +2024-11-21 11:57:33.217193: Epoch 227 +2024-11-21 11:57:33.217328: Current learning rate: 0.00974 +2024-11-21 11:57:53.205679: train_loss -0.7377 +2024-11-21 11:57:53.221616: val_loss -0.7427 +2024-11-21 11:57:53.221760: Pseudo dice [0.8232] +2024-11-21 11:57:53.221858: Epoch time: 19.99 s +2024-11-21 11:57:54.009741: +2024-11-21 11:57:54.009942: Epoch 228 +2024-11-21 11:57:54.010072: Current learning rate: 0.00974 +2024-11-21 11:58:12.785475: train_loss -0.7351 +2024-11-21 11:58:12.800329: val_loss -0.7696 +2024-11-21 11:58:12.800495: Pseudo dice [0.8431] +2024-11-21 11:58:12.800601: Epoch time: 18.78 s +2024-11-21 11:58:13.945649: +2024-11-21 11:58:13.945873: Epoch 229 +2024-11-21 11:58:13.945991: Current learning rate: 0.00974 +2024-11-21 11:58:33.464907: train_loss -0.7446 +2024-11-21 11:58:33.470729: val_loss -0.7537 +2024-11-21 11:58:33.470927: Pseudo dice [0.8417] +2024-11-21 11:58:33.471034: Epoch time: 19.52 s +2024-11-21 11:58:34.279377: +2024-11-21 11:58:34.279576: Epoch 230 +2024-11-21 11:58:34.279699: Current learning rate: 0.00974 +2024-11-21 11:58:53.319012: train_loss -0.7439 +2024-11-21 11:58:53.345903: val_loss -0.7514 +2024-11-21 11:58:53.346057: Pseudo dice [0.8496] +2024-11-21 11:58:53.346154: Epoch time: 19.04 s +2024-11-21 11:58:54.161495: +2024-11-21 11:58:54.161711: Epoch 231 +2024-11-21 11:58:54.161841: Current learning rate: 0.00974 +2024-11-21 11:59:13.578762: train_loss -0.7463 +2024-11-21 11:59:13.585491: val_loss -0.7358 +2024-11-21 11:59:13.585634: Pseudo dice [0.8324] +2024-11-21 11:59:13.585733: Epoch time: 19.42 s +2024-11-21 11:59:14.460322: +2024-11-21 11:59:14.460536: Epoch 232 +2024-11-21 11:59:14.460666: Current learning rate: 0.00974 +2024-11-21 11:59:33.388151: train_loss -0.7412 +2024-11-21 11:59:33.395671: val_loss -0.737 +2024-11-21 11:59:33.395798: Pseudo dice [0.8216] +2024-11-21 11:59:33.395905: Epoch time: 18.93 s +2024-11-21 11:59:34.351544: +2024-11-21 11:59:34.351767: Epoch 233 +2024-11-21 11:59:34.351887: Current learning rate: 0.00974 +2024-11-21 11:59:53.073043: train_loss -0.7428 +2024-11-21 11:59:53.077084: val_loss -0.7479 +2024-11-21 11:59:53.077204: Pseudo dice [0.8275] +2024-11-21 11:59:53.077302: Epoch time: 18.72 s +2024-11-21 11:59:53.854611: +2024-11-21 11:59:53.854809: Epoch 234 +2024-11-21 11:59:53.854938: Current learning rate: 0.00974 +2024-11-21 12:00:13.085091: train_loss -0.7471 +2024-11-21 12:00:13.102739: val_loss -0.7684 +2024-11-21 12:00:13.102892: Pseudo dice [0.8496] +2024-11-21 12:00:13.103002: Epoch time: 19.23 s +2024-11-21 12:00:14.040929: +2024-11-21 12:00:14.041188: Epoch 235 +2024-11-21 12:00:14.041310: Current learning rate: 0.00974 +2024-11-21 12:00:33.416439: train_loss -0.7412 +2024-11-21 12:00:33.425712: val_loss -0.7285 +2024-11-21 12:00:33.425841: Pseudo dice [0.8295] +2024-11-21 12:00:33.425941: Epoch time: 19.38 s +2024-11-21 12:00:34.261085: +2024-11-21 12:00:34.261366: Epoch 236 +2024-11-21 12:00:34.261500: Current learning rate: 0.00973 +2024-11-21 12:00:53.749612: train_loss -0.7483 +2024-11-21 12:00:53.755255: val_loss -0.729 +2024-11-21 12:00:53.755412: Pseudo dice [0.8273] +2024-11-21 12:00:53.755515: Epoch time: 19.49 s +2024-11-21 12:00:54.592977: +2024-11-21 12:00:54.593234: Epoch 237 +2024-11-21 12:00:54.593362: Current learning rate: 0.00973 +2024-11-21 12:01:12.345761: train_loss -0.7378 +2024-11-21 12:01:12.353213: val_loss -0.7141 +2024-11-21 12:01:12.353353: Pseudo dice [0.8292] +2024-11-21 12:01:12.353443: Epoch time: 17.75 s +2024-11-21 12:01:13.127508: +2024-11-21 12:01:13.127732: Epoch 238 +2024-11-21 12:01:13.127848: Current learning rate: 0.00973 +2024-11-21 12:01:32.897675: train_loss -0.7378 +2024-11-21 12:01:32.900328: val_loss -0.6877 +2024-11-21 12:01:32.900445: Pseudo dice [0.7922] +2024-11-21 12:01:32.900547: Epoch time: 19.77 s +2024-11-21 12:01:33.671954: +2024-11-21 12:01:33.672152: Epoch 239 +2024-11-21 12:01:33.672265: Current learning rate: 0.00973 +2024-11-21 12:01:52.458481: train_loss -0.7177 +2024-11-21 12:01:52.461766: val_loss -0.7274 +2024-11-21 12:01:52.461901: Pseudo dice [0.8344] +2024-11-21 12:01:52.461988: Epoch time: 18.79 s +2024-11-21 12:01:53.248882: +2024-11-21 12:01:53.249094: Epoch 240 +2024-11-21 12:01:53.249213: Current learning rate: 0.00973 +2024-11-21 12:02:12.673882: train_loss -0.7397 +2024-11-21 12:02:12.681157: val_loss -0.7712 +2024-11-21 12:02:12.681307: Pseudo dice [0.854] +2024-11-21 12:02:12.681420: Epoch time: 19.43 s +2024-11-21 12:02:13.622015: +2024-11-21 12:02:13.622234: Epoch 241 +2024-11-21 12:02:13.622374: Current learning rate: 0.00973 +2024-11-21 12:02:32.257496: train_loss -0.7408 +2024-11-21 12:02:32.268738: val_loss -0.7528 +2024-11-21 12:02:32.269358: Pseudo dice [0.8218] +2024-11-21 12:02:32.269497: Epoch time: 18.64 s +2024-11-21 12:02:33.148397: +2024-11-21 12:02:33.148582: Epoch 242 +2024-11-21 12:02:33.148701: Current learning rate: 0.00973 +2024-11-21 12:02:52.785085: train_loss -0.7393 +2024-11-21 12:02:52.794837: val_loss -0.7499 +2024-11-21 12:02:52.794974: Pseudo dice [0.8327] +2024-11-21 12:02:52.795067: Epoch time: 19.64 s +2024-11-21 12:02:53.594907: +2024-11-21 12:02:53.595142: Epoch 243 +2024-11-21 12:02:53.595266: Current learning rate: 0.00973 +2024-11-21 12:03:12.003191: train_loss -0.7375 +2024-11-21 12:03:12.011745: val_loss -0.7282 +2024-11-21 12:03:12.011897: Pseudo dice [0.8152] +2024-11-21 12:03:12.012017: Epoch time: 18.41 s +2024-11-21 12:03:12.827701: +2024-11-21 12:03:12.827928: Epoch 244 +2024-11-21 12:03:12.828047: Current learning rate: 0.00973 +2024-11-21 12:03:32.338232: train_loss -0.7413 +2024-11-21 12:03:32.347647: val_loss -0.7654 +2024-11-21 12:03:32.347787: Pseudo dice [0.8343] +2024-11-21 12:03:32.347890: Epoch time: 19.51 s +2024-11-21 12:03:33.303720: +2024-11-21 12:03:33.303950: Epoch 245 +2024-11-21 12:03:33.304079: Current learning rate: 0.00972 +2024-11-21 12:03:52.571249: train_loss -0.7452 +2024-11-21 12:03:52.578252: val_loss -0.7203 +2024-11-21 12:03:52.578405: Pseudo dice [0.8373] +2024-11-21 12:03:52.578493: Epoch time: 19.27 s +2024-11-21 12:03:53.526736: +2024-11-21 12:03:53.526934: Epoch 246 +2024-11-21 12:03:53.527066: Current learning rate: 0.00972 +2024-11-21 12:04:13.043409: train_loss -0.7412 +2024-11-21 12:04:13.051534: val_loss -0.7423 +2024-11-21 12:04:13.051682: Pseudo dice [0.8345] +2024-11-21 12:04:13.051790: Epoch time: 19.52 s +2024-11-21 12:04:13.892134: +2024-11-21 12:04:13.892357: Epoch 247 +2024-11-21 12:04:13.892482: Current learning rate: 0.00972 +2024-11-21 12:04:33.778005: train_loss -0.7461 +2024-11-21 12:04:33.783756: val_loss -0.737 +2024-11-21 12:04:33.783898: Pseudo dice [0.8365] +2024-11-21 12:04:33.783997: Epoch time: 19.89 s +2024-11-21 12:04:34.616713: +2024-11-21 12:04:34.616946: Epoch 248 +2024-11-21 12:04:34.617092: Current learning rate: 0.00972 +2024-11-21 12:04:54.959320: train_loss -0.7525 +2024-11-21 12:04:54.963861: val_loss -0.7354 +2024-11-21 12:04:54.964012: Pseudo dice [0.838] +2024-11-21 12:04:54.964117: Epoch time: 20.34 s +2024-11-21 12:04:55.795699: +2024-11-21 12:04:55.795915: Epoch 249 +2024-11-21 12:04:55.796067: Current learning rate: 0.00972 +2024-11-21 12:05:14.252055: train_loss -0.7431 +2024-11-21 12:05:14.264274: val_loss -0.7474 +2024-11-21 12:05:14.264405: Pseudo dice [0.8405] +2024-11-21 12:05:14.264491: Epoch time: 18.46 s +2024-11-21 12:05:15.357748: +2024-11-21 12:05:15.358004: Epoch 250 +2024-11-21 12:05:15.358135: Current learning rate: 0.00972 +2024-11-21 12:05:33.598552: train_loss -0.7411 +2024-11-21 12:05:33.603443: val_loss -0.7217 +2024-11-21 12:05:33.603572: Pseudo dice [0.8539] +2024-11-21 12:05:33.603657: Epoch time: 18.24 s +2024-11-21 12:05:34.404686: +2024-11-21 12:05:34.404903: Epoch 251 +2024-11-21 12:05:34.405023: Current learning rate: 0.00972 +2024-11-21 12:05:53.099682: train_loss -0.7407 +2024-11-21 12:05:53.107497: val_loss -0.7693 +2024-11-21 12:05:53.107650: Pseudo dice [0.8474] +2024-11-21 12:05:53.107747: Epoch time: 18.7 s +2024-11-21 12:05:53.898986: +2024-11-21 12:05:53.899178: Epoch 252 +2024-11-21 12:05:53.899314: Current learning rate: 0.00972 +2024-11-21 12:06:13.691929: train_loss -0.7536 +2024-11-21 12:06:13.723648: val_loss -0.7549 +2024-11-21 12:06:13.723793: Pseudo dice [0.8413] +2024-11-21 12:06:13.723897: Epoch time: 19.79 s +2024-11-21 12:06:14.558854: +2024-11-21 12:06:14.559088: Epoch 253 +2024-11-21 12:06:14.559208: Current learning rate: 0.00971 +2024-11-21 12:06:34.649890: train_loss -0.7455 +2024-11-21 12:06:34.654992: val_loss -0.7325 +2024-11-21 12:06:34.655125: Pseudo dice [0.84] +2024-11-21 12:06:34.655217: Epoch time: 20.09 s +2024-11-21 12:06:35.858088: +2024-11-21 12:06:35.858293: Epoch 254 +2024-11-21 12:06:35.858405: Current learning rate: 0.00971 +2024-11-21 12:06:55.446305: train_loss -0.7436 +2024-11-21 12:06:55.450900: val_loss -0.7396 +2024-11-21 12:06:55.451037: Pseudo dice [0.832] +2024-11-21 12:06:55.451149: Epoch time: 19.59 s +2024-11-21 12:06:56.445259: +2024-11-21 12:06:56.445502: Epoch 255 +2024-11-21 12:06:56.445618: Current learning rate: 0.00971 +2024-11-21 12:07:15.418791: train_loss -0.7347 +2024-11-21 12:07:15.429166: val_loss -0.7367 +2024-11-21 12:07:15.429320: Pseudo dice [0.8391] +2024-11-21 12:07:15.429423: Epoch time: 18.97 s +2024-11-21 12:07:16.290674: +2024-11-21 12:07:16.290895: Epoch 256 +2024-11-21 12:07:16.291030: Current learning rate: 0.00971 +2024-11-21 12:07:36.024517: train_loss -0.7293 +2024-11-21 12:07:36.033066: val_loss -0.7231 +2024-11-21 12:07:36.033210: Pseudo dice [0.8457] +2024-11-21 12:07:36.033330: Epoch time: 19.73 s +2024-11-21 12:07:37.002218: +2024-11-21 12:07:37.002463: Epoch 257 +2024-11-21 12:07:37.002600: Current learning rate: 0.00971 +2024-11-21 12:07:55.554394: train_loss -0.7403 +2024-11-21 12:07:55.563250: val_loss -0.753 +2024-11-21 12:07:55.563415: Pseudo dice [0.8335] +2024-11-21 12:07:55.563550: Epoch time: 18.55 s +2024-11-21 12:07:56.363039: +2024-11-21 12:07:56.363255: Epoch 258 +2024-11-21 12:07:56.363376: Current learning rate: 0.00971 +2024-11-21 12:08:15.218175: train_loss -0.755 +2024-11-21 12:08:15.226614: val_loss -0.765 +2024-11-21 12:08:15.226757: Pseudo dice [0.8504] +2024-11-21 12:08:15.226848: Epoch time: 18.86 s +2024-11-21 12:08:15.226918: Yayy! New best EMA pseudo Dice: 0.8387 +2024-11-21 12:08:16.259740: +2024-11-21 12:08:16.260003: Epoch 259 +2024-11-21 12:08:16.260150: Current learning rate: 0.00971 +2024-11-21 12:08:34.789072: train_loss -0.7453 +2024-11-21 12:08:34.795710: val_loss -0.7351 +2024-11-21 12:08:34.795916: Pseudo dice [0.8374] +2024-11-21 12:08:34.796023: Epoch time: 18.53 s +2024-11-21 12:08:35.632163: +2024-11-21 12:08:35.632379: Epoch 260 +2024-11-21 12:08:35.632494: Current learning rate: 0.00971 +2024-11-21 12:08:55.498638: train_loss -0.7407 +2024-11-21 12:08:55.501871: val_loss -0.7326 +2024-11-21 12:08:55.501976: Pseudo dice [0.8371] +2024-11-21 12:08:55.502071: Epoch time: 19.87 s +2024-11-21 12:08:56.292758: +2024-11-21 12:08:56.292969: Epoch 261 +2024-11-21 12:08:56.293094: Current learning rate: 0.00971 +2024-11-21 12:09:14.672288: train_loss -0.7423 +2024-11-21 12:09:14.690872: val_loss -0.7586 +2024-11-21 12:09:14.691020: Pseudo dice [0.85] +2024-11-21 12:09:14.691124: Epoch time: 18.38 s +2024-11-21 12:09:14.691215: Yayy! New best EMA pseudo Dice: 0.8396 +2024-11-21 12:09:15.734535: +2024-11-21 12:09:15.734768: Epoch 262 +2024-11-21 12:09:15.734891: Current learning rate: 0.0097 +2024-11-21 12:09:34.680210: train_loss -0.7297 +2024-11-21 12:09:34.695147: val_loss -0.7175 +2024-11-21 12:09:34.695300: Pseudo dice [0.8255] +2024-11-21 12:09:34.695423: Epoch time: 18.95 s +2024-11-21 12:09:35.535172: +2024-11-21 12:09:35.535431: Epoch 263 +2024-11-21 12:09:35.535559: Current learning rate: 0.0097 +2024-11-21 12:09:55.186412: train_loss -0.7306 +2024-11-21 12:09:55.202174: val_loss -0.734 +2024-11-21 12:09:55.202330: Pseudo dice [0.8044] +2024-11-21 12:09:55.202418: Epoch time: 19.65 s +2024-11-21 12:09:55.997591: +2024-11-21 12:09:55.997812: Epoch 264 +2024-11-21 12:09:55.997923: Current learning rate: 0.0097 +2024-11-21 12:10:14.101326: train_loss -0.7462 +2024-11-21 12:10:14.113372: val_loss -0.7561 +2024-11-21 12:10:14.113512: Pseudo dice [0.8392] +2024-11-21 12:10:14.113596: Epoch time: 18.1 s +2024-11-21 12:10:14.922754: +2024-11-21 12:10:14.922959: Epoch 265 +2024-11-21 12:10:14.923096: Current learning rate: 0.0097 +2024-11-21 12:10:32.689155: train_loss -0.7486 +2024-11-21 12:10:32.695702: val_loss -0.7593 +2024-11-21 12:10:32.695825: Pseudo dice [0.8431] +2024-11-21 12:10:32.695935: Epoch time: 17.77 s +2024-11-21 12:10:33.943680: +2024-11-21 12:10:33.943910: Epoch 266 +2024-11-21 12:10:33.944062: Current learning rate: 0.0097 +2024-11-21 12:10:53.185819: train_loss -0.7478 +2024-11-21 12:10:53.196013: val_loss -0.7695 +2024-11-21 12:10:53.196164: Pseudo dice [0.8457] +2024-11-21 12:10:53.211520: Epoch time: 19.24 s +2024-11-21 12:10:54.085681: +2024-11-21 12:10:54.085923: Epoch 267 +2024-11-21 12:10:54.086046: Current learning rate: 0.0097 +2024-11-21 12:11:12.978868: train_loss -0.7543 +2024-11-21 12:11:12.990617: val_loss -0.7202 +2024-11-21 12:11:12.990744: Pseudo dice [0.8265] +2024-11-21 12:11:12.990855: Epoch time: 18.89 s +2024-11-21 12:11:13.807617: +2024-11-21 12:11:13.807834: Epoch 268 +2024-11-21 12:11:13.807949: Current learning rate: 0.0097 +2024-11-21 12:11:32.041593: train_loss -0.7357 +2024-11-21 12:11:32.050316: val_loss -0.7405 +2024-11-21 12:11:32.050466: Pseudo dice [0.8315] +2024-11-21 12:11:32.050570: Epoch time: 18.23 s +2024-11-21 12:11:32.849806: +2024-11-21 12:11:32.850048: Epoch 269 +2024-11-21 12:11:32.850181: Current learning rate: 0.0097 +2024-11-21 12:11:51.923096: train_loss -0.7479 +2024-11-21 12:11:51.928048: val_loss -0.74 +2024-11-21 12:11:51.928191: Pseudo dice [0.843] +2024-11-21 12:11:51.928303: Epoch time: 19.07 s +2024-11-21 12:11:52.738531: +2024-11-21 12:11:52.739007: Epoch 270 +2024-11-21 12:11:52.739139: Current learning rate: 0.0097 +2024-11-21 12:12:11.367548: train_loss -0.7453 +2024-11-21 12:12:11.373637: val_loss -0.7416 +2024-11-21 12:12:11.373773: Pseudo dice [0.8518] +2024-11-21 12:12:11.373871: Epoch time: 18.63 s +2024-11-21 12:12:12.298020: +2024-11-21 12:12:12.298210: Epoch 271 +2024-11-21 12:12:12.298324: Current learning rate: 0.00969 +2024-11-21 12:12:31.861487: train_loss -0.7401 +2024-11-21 12:12:31.873141: val_loss -0.7585 +2024-11-21 12:12:31.873266: Pseudo dice [0.8496] +2024-11-21 12:12:31.873365: Epoch time: 19.56 s +2024-11-21 12:12:32.729065: +2024-11-21 12:12:32.729302: Epoch 272 +2024-11-21 12:12:32.729420: Current learning rate: 0.00969 +2024-11-21 12:12:51.285349: train_loss -0.7448 +2024-11-21 12:12:51.290774: val_loss -0.7359 +2024-11-21 12:12:51.290888: Pseudo dice [0.825] +2024-11-21 12:12:51.290986: Epoch time: 18.56 s +2024-11-21 12:12:52.096253: +2024-11-21 12:12:52.096481: Epoch 273 +2024-11-21 12:12:52.096620: Current learning rate: 0.00969 +2024-11-21 12:13:09.565911: train_loss -0.7495 +2024-11-21 12:13:09.575055: val_loss -0.7531 +2024-11-21 12:13:09.575195: Pseudo dice [0.835] +2024-11-21 12:13:09.575316: Epoch time: 17.47 s +2024-11-21 12:13:10.451870: +2024-11-21 12:13:10.452088: Epoch 274 +2024-11-21 12:13:10.452228: Current learning rate: 0.00969 +2024-11-21 12:13:28.998235: train_loss -0.7425 +2024-11-21 12:13:29.001665: val_loss -0.7534 +2024-11-21 12:13:29.001790: Pseudo dice [0.8251] +2024-11-21 12:13:29.001880: Epoch time: 18.55 s +2024-11-21 12:13:29.804710: +2024-11-21 12:13:29.804903: Epoch 275 +2024-11-21 12:13:29.805024: Current learning rate: 0.00969 +2024-11-21 12:13:48.201517: train_loss -0.7448 +2024-11-21 12:13:48.212977: val_loss -0.7688 +2024-11-21 12:13:48.213128: Pseudo dice [0.8472] +2024-11-21 12:13:48.213219: Epoch time: 18.4 s +2024-11-21 12:13:49.100558: +2024-11-21 12:13:49.100775: Epoch 276 +2024-11-21 12:13:49.100895: Current learning rate: 0.00969 +2024-11-21 12:14:08.106506: train_loss -0.7428 +2024-11-21 12:14:08.113419: val_loss -0.7584 +2024-11-21 12:14:08.113565: Pseudo dice [0.8292] +2024-11-21 12:14:08.113662: Epoch time: 19.01 s +2024-11-21 12:14:08.915289: +2024-11-21 12:14:08.915501: Epoch 277 +2024-11-21 12:14:08.915622: Current learning rate: 0.00969 +2024-11-21 12:14:27.706697: train_loss -0.753 +2024-11-21 12:14:27.715766: val_loss -0.7509 +2024-11-21 12:14:27.715912: Pseudo dice [0.8455] +2024-11-21 12:14:27.716008: Epoch time: 18.79 s +2024-11-21 12:14:28.664955: +2024-11-21 12:14:28.665193: Epoch 278 +2024-11-21 12:14:28.665337: Current learning rate: 0.00969 +2024-11-21 12:14:46.897407: train_loss -0.7358 +2024-11-21 12:14:46.902049: val_loss -0.7177 +2024-11-21 12:14:46.902195: Pseudo dice [0.8275] +2024-11-21 12:14:46.902287: Epoch time: 18.23 s +2024-11-21 12:14:47.904338: +2024-11-21 12:14:47.904575: Epoch 279 +2024-11-21 12:14:47.904710: Current learning rate: 0.00969 +2024-11-21 12:15:06.561821: train_loss -0.7444 +2024-11-21 12:15:06.584831: val_loss -0.7474 +2024-11-21 12:15:06.585020: Pseudo dice [0.8458] +2024-11-21 12:15:06.585119: Epoch time: 18.66 s +2024-11-21 12:15:07.543766: +2024-11-21 12:15:07.543980: Epoch 280 +2024-11-21 12:15:07.544106: Current learning rate: 0.00968 +2024-11-21 12:15:26.914184: train_loss -0.7489 +2024-11-21 12:15:26.928661: val_loss -0.7446 +2024-11-21 12:15:26.928809: Pseudo dice [0.8439] +2024-11-21 12:15:26.928909: Epoch time: 19.37 s +2024-11-21 12:15:27.754475: +2024-11-21 12:15:27.754699: Epoch 281 +2024-11-21 12:15:27.754831: Current learning rate: 0.00968 +2024-11-21 12:15:47.891826: train_loss -0.7361 +2024-11-21 12:15:47.898415: val_loss -0.7624 +2024-11-21 12:15:47.898567: Pseudo dice [0.8291] +2024-11-21 12:15:47.898668: Epoch time: 20.14 s +2024-11-21 12:15:48.862661: +2024-11-21 12:15:48.862870: Epoch 282 +2024-11-21 12:15:48.863009: Current learning rate: 0.00968 +2024-11-21 12:16:09.482634: train_loss -0.7455 +2024-11-21 12:16:09.490709: val_loss -0.7284 +2024-11-21 12:16:09.490855: Pseudo dice [0.8272] +2024-11-21 12:16:09.490940: Epoch time: 20.62 s +2024-11-21 12:16:10.288984: +2024-11-21 12:16:10.289199: Epoch 283 +2024-11-21 12:16:10.289331: Current learning rate: 0.00968 +2024-11-21 12:16:28.910100: train_loss -0.7484 +2024-11-21 12:16:28.915981: val_loss -0.7365 +2024-11-21 12:16:28.916138: Pseudo dice [0.8413] +2024-11-21 12:16:28.916234: Epoch time: 18.62 s +2024-11-21 12:16:29.724499: +2024-11-21 12:16:29.724708: Epoch 284 +2024-11-21 12:16:29.724843: Current learning rate: 0.00968 +2024-11-21 12:16:49.174033: train_loss -0.7415 +2024-11-21 12:16:49.181595: val_loss -0.7682 +2024-11-21 12:16:49.181737: Pseudo dice [0.8581] +2024-11-21 12:16:49.181845: Epoch time: 19.45 s +2024-11-21 12:16:49.984259: +2024-11-21 12:16:49.984483: Epoch 285 +2024-11-21 12:16:49.984633: Current learning rate: 0.00968 +2024-11-21 12:17:08.231784: train_loss -0.7507 +2024-11-21 12:17:08.242823: val_loss -0.7406 +2024-11-21 12:17:08.242982: Pseudo dice [0.8281] +2024-11-21 12:17:08.243129: Epoch time: 18.25 s +2024-11-21 12:17:09.094679: +2024-11-21 12:17:09.094869: Epoch 286 +2024-11-21 12:17:09.095079: Current learning rate: 0.00968 +2024-11-21 12:17:27.767531: train_loss -0.7437 +2024-11-21 12:17:27.777981: val_loss -0.7768 +2024-11-21 12:17:27.778139: Pseudo dice [0.8429] +2024-11-21 12:17:27.778229: Epoch time: 18.67 s +2024-11-21 12:17:28.586077: +2024-11-21 12:17:28.586262: Epoch 287 +2024-11-21 12:17:28.586390: Current learning rate: 0.00968 +2024-11-21 12:17:47.871642: train_loss -0.7534 +2024-11-21 12:17:47.880964: val_loss -0.7546 +2024-11-21 12:17:47.881109: Pseudo dice [0.8369] +2024-11-21 12:17:47.881236: Epoch time: 19.29 s +2024-11-21 12:17:48.710116: +2024-11-21 12:17:48.710319: Epoch 288 +2024-11-21 12:17:48.710456: Current learning rate: 0.00968 +2024-11-21 12:18:07.803658: train_loss -0.7461 +2024-11-21 12:18:07.811037: val_loss -0.7505 +2024-11-21 12:18:07.811178: Pseudo dice [0.8401] +2024-11-21 12:18:07.811279: Epoch time: 19.09 s +2024-11-21 12:18:09.011278: +2024-11-21 12:18:09.011504: Epoch 289 +2024-11-21 12:18:09.011638: Current learning rate: 0.00967 +2024-11-21 12:18:28.683128: train_loss -0.7424 +2024-11-21 12:18:28.689958: val_loss -0.7743 +2024-11-21 12:18:28.690079: Pseudo dice [0.8447] +2024-11-21 12:18:28.690173: Epoch time: 19.67 s +2024-11-21 12:18:29.490654: +2024-11-21 12:18:29.490929: Epoch 290 +2024-11-21 12:18:29.491055: Current learning rate: 0.00967 +2024-11-21 12:18:47.482975: train_loss -0.7436 +2024-11-21 12:18:47.493392: val_loss -0.7537 +2024-11-21 12:18:47.493544: Pseudo dice [0.8491] +2024-11-21 12:18:47.493633: Epoch time: 17.99 s +2024-11-21 12:18:47.493783: Yayy! New best EMA pseudo Dice: 0.8399 +2024-11-21 12:18:48.644834: +2024-11-21 12:18:48.645081: Epoch 291 +2024-11-21 12:18:48.645201: Current learning rate: 0.00967 +2024-11-21 12:19:06.894302: train_loss -0.7418 +2024-11-21 12:19:06.903236: val_loss -0.7349 +2024-11-21 12:19:06.903395: Pseudo dice [0.8463] +2024-11-21 12:19:06.903502: Epoch time: 18.25 s +2024-11-21 12:19:06.903590: Yayy! New best EMA pseudo Dice: 0.8406 +2024-11-21 12:19:07.944420: +2024-11-21 12:19:07.944646: Epoch 292 +2024-11-21 12:19:07.944774: Current learning rate: 0.00967 +2024-11-21 12:19:27.544585: train_loss -0.7538 +2024-11-21 12:19:27.552540: val_loss -0.743 +2024-11-21 12:19:27.552677: Pseudo dice [0.8377] +2024-11-21 12:19:27.552775: Epoch time: 19.6 s +2024-11-21 12:19:28.404453: +2024-11-21 12:19:28.405039: Epoch 293 +2024-11-21 12:19:28.405173: Current learning rate: 0.00967 +2024-11-21 12:19:49.063949: train_loss -0.7484 +2024-11-21 12:19:49.070692: val_loss -0.7561 +2024-11-21 12:19:49.070815: Pseudo dice [0.8476] +2024-11-21 12:19:49.070908: Epoch time: 20.66 s +2024-11-21 12:19:49.070977: Yayy! New best EMA pseudo Dice: 0.841 +2024-11-21 12:19:50.371475: +2024-11-21 12:19:50.371692: Epoch 294 +2024-11-21 12:19:50.371820: Current learning rate: 0.00967 +2024-11-21 12:20:10.117298: train_loss -0.7301 +2024-11-21 12:20:10.122783: val_loss -0.723 +2024-11-21 12:20:10.122940: Pseudo dice [0.8244] +2024-11-21 12:20:10.123064: Epoch time: 19.75 s +2024-11-21 12:20:11.102489: +2024-11-21 12:20:11.102696: Epoch 295 +2024-11-21 12:20:11.102841: Current learning rate: 0.00967 +2024-11-21 12:20:30.479970: train_loss -0.7514 +2024-11-21 12:20:30.490914: val_loss -0.7341 +2024-11-21 12:20:30.491042: Pseudo dice [0.8186] +2024-11-21 12:20:30.491161: Epoch time: 19.38 s +2024-11-21 12:20:31.389395: +2024-11-21 12:20:31.389610: Epoch 296 +2024-11-21 12:20:31.389731: Current learning rate: 0.00967 +2024-11-21 12:20:50.826070: train_loss -0.7362 +2024-11-21 12:20:50.833080: val_loss -0.7299 +2024-11-21 12:20:50.833208: Pseudo dice [0.8294] +2024-11-21 12:20:50.833308: Epoch time: 19.44 s +2024-11-21 12:20:51.704791: +2024-11-21 12:20:51.704996: Epoch 297 +2024-11-21 12:20:51.705135: Current learning rate: 0.00967 +2024-11-21 12:21:10.862457: train_loss -0.7531 +2024-11-21 12:21:10.871251: val_loss -0.7616 +2024-11-21 12:21:10.871384: Pseudo dice [0.8482] +2024-11-21 12:21:10.871485: Epoch time: 19.16 s +2024-11-21 12:21:11.677295: +2024-11-21 12:21:11.677539: Epoch 298 +2024-11-21 12:21:11.677675: Current learning rate: 0.00966 +2024-11-21 12:21:30.578778: train_loss -0.747 +2024-11-21 12:21:30.588639: val_loss -0.7587 +2024-11-21 12:21:30.588793: Pseudo dice [0.8439] +2024-11-21 12:21:30.588903: Epoch time: 18.9 s +2024-11-21 12:21:31.392000: +2024-11-21 12:21:31.392247: Epoch 299 +2024-11-21 12:21:31.392417: Current learning rate: 0.00966 +2024-11-21 12:21:50.033518: train_loss -0.7491 +2024-11-21 12:21:50.053419: val_loss -0.7561 +2024-11-21 12:21:50.053607: Pseudo dice [0.8304] +2024-11-21 12:21:50.053715: Epoch time: 18.64 s +2024-11-21 12:21:51.605193: +2024-11-21 12:21:51.605420: Epoch 300 +2024-11-21 12:21:51.605541: Current learning rate: 0.00966 +2024-11-21 12:22:11.277147: train_loss -0.752 +2024-11-21 12:22:11.285034: val_loss -0.7328 +2024-11-21 12:22:11.285215: Pseudo dice [0.825] +2024-11-21 12:22:11.285305: Epoch time: 19.67 s +2024-11-21 12:22:12.156811: +2024-11-21 12:22:12.157064: Epoch 301 +2024-11-21 12:22:12.157196: Current learning rate: 0.00966 +2024-11-21 12:22:32.035635: train_loss -0.7515 +2024-11-21 12:22:32.042804: val_loss -0.762 +2024-11-21 12:22:32.042943: Pseudo dice [0.8376] +2024-11-21 12:22:32.043029: Epoch time: 19.88 s +2024-11-21 12:22:32.863498: +2024-11-21 12:22:32.863718: Epoch 302 +2024-11-21 12:22:32.863833: Current learning rate: 0.00966 +2024-11-21 12:22:52.604293: train_loss -0.7429 +2024-11-21 12:22:52.616176: val_loss -0.7702 +2024-11-21 12:22:52.616339: Pseudo dice [0.8522] +2024-11-21 12:22:52.616434: Epoch time: 19.74 s +2024-11-21 12:22:53.594450: +2024-11-21 12:22:53.594662: Epoch 303 +2024-11-21 12:22:53.594784: Current learning rate: 0.00966 +2024-11-21 12:23:12.459752: train_loss -0.7449 +2024-11-21 12:23:12.462074: val_loss -0.7488 +2024-11-21 12:23:12.462227: Pseudo dice [0.8572] +2024-11-21 12:23:12.462336: Epoch time: 18.87 s +2024-11-21 12:23:13.253333: +2024-11-21 12:23:13.253532: Epoch 304 +2024-11-21 12:23:13.253654: Current learning rate: 0.00966 +2024-11-21 12:23:33.784689: train_loss -0.7538 +2024-11-21 12:23:33.790641: val_loss -0.7623 +2024-11-21 12:23:33.790800: Pseudo dice [0.847] +2024-11-21 12:23:33.790892: Epoch time: 20.53 s +2024-11-21 12:23:34.595320: +2024-11-21 12:23:34.595520: Epoch 305 +2024-11-21 12:23:34.595651: Current learning rate: 0.00966 +2024-11-21 12:23:53.669577: train_loss -0.7503 +2024-11-21 12:23:53.675551: val_loss -0.7502 +2024-11-21 12:23:53.675701: Pseudo dice [0.8387] +2024-11-21 12:23:53.675814: Epoch time: 19.08 s +2024-11-21 12:23:54.498590: +2024-11-21 12:23:54.498801: Epoch 306 +2024-11-21 12:23:54.498929: Current learning rate: 0.00966 +2024-11-21 12:24:13.378451: train_loss -0.7467 +2024-11-21 12:24:13.383820: val_loss -0.7374 +2024-11-21 12:24:13.383959: Pseudo dice [0.8296] +2024-11-21 12:24:13.384051: Epoch time: 18.88 s +2024-11-21 12:24:14.213544: +2024-11-21 12:24:14.213762: Epoch 307 +2024-11-21 12:24:14.213880: Current learning rate: 0.00965 +2024-11-21 12:24:33.966914: train_loss -0.753 +2024-11-21 12:24:33.984045: val_loss -0.7506 +2024-11-21 12:24:33.984263: Pseudo dice [0.8536] +2024-11-21 12:24:33.984364: Epoch time: 19.75 s +2024-11-21 12:24:34.787182: +2024-11-21 12:24:34.787370: Epoch 308 +2024-11-21 12:24:34.787479: Current learning rate: 0.00965 +2024-11-21 12:24:53.181826: train_loss -0.7541 +2024-11-21 12:24:53.187447: val_loss -0.76 +2024-11-21 12:24:53.187563: Pseudo dice [0.8302] +2024-11-21 12:24:53.187649: Epoch time: 18.4 s +2024-11-21 12:24:54.007370: +2024-11-21 12:24:54.007604: Epoch 309 +2024-11-21 12:24:54.007728: Current learning rate: 0.00965 +2024-11-21 12:25:12.724496: train_loss -0.7522 +2024-11-21 12:25:12.732815: val_loss -0.7536 +2024-11-21 12:25:12.732962: Pseudo dice [0.8411] +2024-11-21 12:25:12.733081: Epoch time: 18.72 s +2024-11-21 12:25:13.591890: +2024-11-21 12:25:13.592098: Epoch 310 +2024-11-21 12:25:13.592216: Current learning rate: 0.00965 +2024-11-21 12:25:32.179733: train_loss -0.7477 +2024-11-21 12:25:32.184381: val_loss -0.7573 +2024-11-21 12:25:32.184538: Pseudo dice [0.8197] +2024-11-21 12:25:32.184627: Epoch time: 18.59 s +2024-11-21 12:25:33.401567: +2024-11-21 12:25:33.401737: Epoch 311 +2024-11-21 12:25:33.401850: Current learning rate: 0.00965 +2024-11-21 12:25:54.319817: train_loss -0.7326 +2024-11-21 12:25:54.325916: val_loss -0.7477 +2024-11-21 12:25:54.326088: Pseudo dice [0.8287] +2024-11-21 12:25:54.326196: Epoch time: 20.92 s +2024-11-21 12:25:55.336281: +2024-11-21 12:25:55.336519: Epoch 312 +2024-11-21 12:25:55.336633: Current learning rate: 0.00965 +2024-11-21 12:26:15.671796: train_loss -0.7331 +2024-11-21 12:26:15.674141: val_loss -0.7396 +2024-11-21 12:26:15.674291: Pseudo dice [0.8421] +2024-11-21 12:26:15.674388: Epoch time: 20.34 s +2024-11-21 12:26:16.470922: +2024-11-21 12:26:16.471143: Epoch 313 +2024-11-21 12:26:16.471287: Current learning rate: 0.00965 +2024-11-21 12:26:35.937543: train_loss -0.7456 +2024-11-21 12:26:35.939885: val_loss -0.7284 +2024-11-21 12:26:35.940020: Pseudo dice [0.8375] +2024-11-21 12:26:35.940150: Epoch time: 19.47 s +2024-11-21 12:26:36.788725: +2024-11-21 12:26:36.788926: Epoch 314 +2024-11-21 12:26:36.789042: Current learning rate: 0.00965 +2024-11-21 12:26:56.263038: train_loss -0.7398 +2024-11-21 12:26:56.266718: val_loss -0.7405 +2024-11-21 12:26:56.266867: Pseudo dice [0.8308] +2024-11-21 12:26:56.266957: Epoch time: 19.48 s +2024-11-21 12:26:57.060418: +2024-11-21 12:26:57.060654: Epoch 315 +2024-11-21 12:26:57.060789: Current learning rate: 0.00964 +2024-11-21 12:27:15.988013: train_loss -0.7524 +2024-11-21 12:27:15.994076: val_loss -0.7523 +2024-11-21 12:27:15.994211: Pseudo dice [0.8428] +2024-11-21 12:27:15.994296: Epoch time: 18.93 s +2024-11-21 12:27:16.792397: +2024-11-21 12:27:16.792616: Epoch 316 +2024-11-21 12:27:16.792748: Current learning rate: 0.00964 +2024-11-21 12:27:34.980005: train_loss -0.7469 +2024-11-21 12:27:34.982187: val_loss -0.756 +2024-11-21 12:27:34.982324: Pseudo dice [0.8305] +2024-11-21 12:27:34.982429: Epoch time: 18.19 s +2024-11-21 12:27:35.777934: +2024-11-21 12:27:35.799818: Epoch 317 +2024-11-21 12:27:35.799975: Current learning rate: 0.00964 +2024-11-21 12:27:55.157057: train_loss -0.7424 +2024-11-21 12:27:55.159276: val_loss -0.737 +2024-11-21 12:27:55.159459: Pseudo dice [0.8369] +2024-11-21 12:27:55.159564: Epoch time: 19.38 s +2024-11-21 12:27:56.047564: +2024-11-21 12:27:56.047769: Epoch 318 +2024-11-21 12:27:56.047892: Current learning rate: 0.00964 +2024-11-21 12:28:15.933389: train_loss -0.7443 +2024-11-21 12:28:15.944563: val_loss -0.7618 +2024-11-21 12:28:15.944713: Pseudo dice [0.8352] +2024-11-21 12:28:15.944800: Epoch time: 19.89 s +2024-11-21 12:28:16.754047: +2024-11-21 12:28:16.754264: Epoch 319 +2024-11-21 12:28:16.754400: Current learning rate: 0.00964 +2024-11-21 12:28:35.599665: train_loss -0.7467 +2024-11-21 12:28:35.611381: val_loss -0.7325 +2024-11-21 12:28:35.611545: Pseudo dice [0.8393] +2024-11-21 12:28:35.611653: Epoch time: 18.85 s +2024-11-21 12:28:36.601181: +2024-11-21 12:28:36.601394: Epoch 320 +2024-11-21 12:28:36.601526: Current learning rate: 0.00964 +2024-11-21 12:28:56.332219: train_loss -0.7501 +2024-11-21 12:28:56.343716: val_loss -0.7533 +2024-11-21 12:28:56.343848: Pseudo dice [0.8293] +2024-11-21 12:28:56.343972: Epoch time: 19.73 s +2024-11-21 12:28:57.271490: +2024-11-21 12:28:57.271679: Epoch 321 +2024-11-21 12:28:57.271820: Current learning rate: 0.00964 +2024-11-21 12:29:16.504378: train_loss -0.7522 +2024-11-21 12:29:16.514130: val_loss -0.7447 +2024-11-21 12:29:16.514290: Pseudo dice [0.8342] +2024-11-21 12:29:16.514396: Epoch time: 19.23 s +2024-11-21 12:29:17.665827: +2024-11-21 12:29:17.666032: Epoch 322 +2024-11-21 12:29:17.666163: Current learning rate: 0.00964 +2024-11-21 12:29:36.639863: train_loss -0.7189 +2024-11-21 12:29:36.643753: val_loss -0.76 +2024-11-21 12:29:36.643877: Pseudo dice [0.8382] +2024-11-21 12:29:36.643965: Epoch time: 18.97 s +2024-11-21 12:29:37.840092: +2024-11-21 12:29:37.840348: Epoch 323 +2024-11-21 12:29:37.840479: Current learning rate: 0.00964 +2024-11-21 12:29:57.291969: train_loss -0.7449 +2024-11-21 12:29:57.296944: val_loss -0.7536 +2024-11-21 12:29:57.297080: Pseudo dice [0.8365] +2024-11-21 12:29:57.297197: Epoch time: 19.45 s +2024-11-21 12:29:58.169266: +2024-11-21 12:29:58.169475: Epoch 324 +2024-11-21 12:29:58.169599: Current learning rate: 0.00963 +2024-11-21 12:30:16.410619: train_loss -0.7351 +2024-11-21 12:30:16.414154: val_loss -0.7265 +2024-11-21 12:30:16.414357: Pseudo dice [0.8276] +2024-11-21 12:30:16.414443: Epoch time: 18.24 s +2024-11-21 12:30:17.253057: +2024-11-21 12:30:17.253283: Epoch 325 +2024-11-21 12:30:17.253405: Current learning rate: 0.00963 +2024-11-21 12:30:35.819399: train_loss -0.7438 +2024-11-21 12:30:35.826622: val_loss -0.7614 +2024-11-21 12:30:35.826758: Pseudo dice [0.8432] +2024-11-21 12:30:35.826962: Epoch time: 18.57 s +2024-11-21 12:30:36.655854: +2024-11-21 12:30:36.656070: Epoch 326 +2024-11-21 12:30:36.656199: Current learning rate: 0.00963 +2024-11-21 12:30:55.786639: train_loss -0.7473 +2024-11-21 12:30:55.793795: val_loss -0.7591 +2024-11-21 12:30:55.793943: Pseudo dice [0.8455] +2024-11-21 12:30:55.794034: Epoch time: 19.13 s +2024-11-21 12:30:56.766670: +2024-11-21 12:30:56.766881: Epoch 327 +2024-11-21 12:30:56.767013: Current learning rate: 0.00963 +2024-11-21 12:31:16.162919: train_loss -0.7478 +2024-11-21 12:31:16.164752: val_loss -0.7543 +2024-11-21 12:31:16.164854: Pseudo dice [0.8376] +2024-11-21 12:31:16.164958: Epoch time: 19.4 s +2024-11-21 12:31:16.967863: +2024-11-21 12:31:16.968118: Epoch 328 +2024-11-21 12:31:16.968262: Current learning rate: 0.00963 +2024-11-21 12:31:36.854951: train_loss -0.7413 +2024-11-21 12:31:36.861763: val_loss -0.7496 +2024-11-21 12:31:36.861901: Pseudo dice [0.8294] +2024-11-21 12:31:36.861990: Epoch time: 19.89 s +2024-11-21 12:31:37.700625: +2024-11-21 12:31:37.700834: Epoch 329 +2024-11-21 12:31:37.700972: Current learning rate: 0.00963 +2024-11-21 12:31:58.044679: train_loss -0.7483 +2024-11-21 12:31:58.058247: val_loss -0.7543 +2024-11-21 12:31:58.058426: Pseudo dice [0.8443] +2024-11-21 12:31:58.059206: Epoch time: 20.34 s +2024-11-21 12:31:59.059210: +2024-11-21 12:31:59.059416: Epoch 330 +2024-11-21 12:31:59.059547: Current learning rate: 0.00963 +2024-11-21 12:32:18.729069: train_loss -0.7376 +2024-11-21 12:32:18.736565: val_loss -0.7439 +2024-11-21 12:32:18.736691: Pseudo dice [0.8478] +2024-11-21 12:32:18.736792: Epoch time: 19.67 s +2024-11-21 12:32:19.646190: +2024-11-21 12:32:19.646425: Epoch 331 +2024-11-21 12:32:19.646562: Current learning rate: 0.00963 +2024-11-21 12:32:38.553339: train_loss -0.7352 +2024-11-21 12:32:38.565027: val_loss -0.7418 +2024-11-21 12:32:38.565197: Pseudo dice [0.8174] +2024-11-21 12:32:38.565305: Epoch time: 18.91 s +2024-11-21 12:32:39.484708: +2024-11-21 12:32:39.484925: Epoch 332 +2024-11-21 12:32:39.485048: Current learning rate: 0.00963 +2024-11-21 12:32:59.512903: train_loss -0.7272 +2024-11-21 12:32:59.518134: val_loss -0.7534 +2024-11-21 12:32:59.518259: Pseudo dice [0.8347] +2024-11-21 12:32:59.518363: Epoch time: 20.03 s +2024-11-21 12:33:00.331231: +2024-11-21 12:33:00.331439: Epoch 333 +2024-11-21 12:33:00.331560: Current learning rate: 0.00962 +2024-11-21 12:33:18.718997: train_loss -0.7402 +2024-11-21 12:33:18.730705: val_loss -0.7542 +2024-11-21 12:33:18.730849: Pseudo dice [0.8448] +2024-11-21 12:33:18.730960: Epoch time: 18.39 s +2024-11-21 12:33:19.982761: +2024-11-21 12:33:19.982979: Epoch 334 +2024-11-21 12:33:19.983134: Current learning rate: 0.00962 +2024-11-21 12:33:38.832285: train_loss -0.7511 +2024-11-21 12:33:38.850958: val_loss -0.7713 +2024-11-21 12:33:38.851122: Pseudo dice [0.8331] +2024-11-21 12:33:38.851251: Epoch time: 18.85 s +2024-11-21 12:33:39.943357: +2024-11-21 12:33:39.943787: Epoch 335 +2024-11-21 12:33:39.943941: Current learning rate: 0.00962 +2024-11-21 12:33:59.426199: train_loss -0.7462 +2024-11-21 12:33:59.434212: val_loss -0.7595 +2024-11-21 12:33:59.434348: Pseudo dice [0.8446] +2024-11-21 12:33:59.434446: Epoch time: 19.48 s +2024-11-21 12:34:00.537975: +2024-11-21 12:34:00.538458: Epoch 336 +2024-11-21 12:34:00.538597: Current learning rate: 0.00962 +2024-11-21 12:34:18.783318: train_loss -0.7463 +2024-11-21 12:34:18.790939: val_loss -0.7251 +2024-11-21 12:34:18.791093: Pseudo dice [0.8636] +2024-11-21 12:34:18.791190: Epoch time: 18.25 s +2024-11-21 12:34:19.671295: +2024-11-21 12:34:19.671716: Epoch 337 +2024-11-21 12:34:19.671855: Current learning rate: 0.00962 +2024-11-21 12:34:37.640733: train_loss -0.7426 +2024-11-21 12:34:37.647097: val_loss -0.7446 +2024-11-21 12:34:37.647227: Pseudo dice [0.8393] +2024-11-21 12:34:37.647324: Epoch time: 17.97 s +2024-11-21 12:34:38.564610: +2024-11-21 12:34:38.565028: Epoch 338 +2024-11-21 12:34:38.565175: Current learning rate: 0.00962 +2024-11-21 12:34:58.587565: train_loss -0.7465 +2024-11-21 12:34:58.595701: val_loss -0.7552 +2024-11-21 12:34:58.595849: Pseudo dice [0.8283] +2024-11-21 12:34:58.595963: Epoch time: 20.02 s +2024-11-21 12:34:59.528031: +2024-11-21 12:34:59.528563: Epoch 339 +2024-11-21 12:34:59.528708: Current learning rate: 0.00962 +2024-11-21 12:35:17.596892: train_loss -0.7444 +2024-11-21 12:35:17.610309: val_loss -0.7669 +2024-11-21 12:35:17.610432: Pseudo dice [0.8498] +2024-11-21 12:35:17.610529: Epoch time: 18.07 s +2024-11-21 12:35:18.748544: +2024-11-21 12:35:18.748951: Epoch 340 +2024-11-21 12:35:18.749120: Current learning rate: 0.00962 +2024-11-21 12:35:38.737015: train_loss -0.7551 +2024-11-21 12:35:38.741476: val_loss -0.7452 +2024-11-21 12:35:38.741615: Pseudo dice [0.8341] +2024-11-21 12:35:38.741699: Epoch time: 19.99 s +2024-11-21 12:35:39.804427: +2024-11-21 12:35:39.804906: Epoch 341 +2024-11-21 12:35:39.805076: Current learning rate: 0.00962 +2024-11-21 12:35:58.518305: train_loss -0.7592 +2024-11-21 12:35:58.525630: val_loss -0.7485 +2024-11-21 12:35:58.525770: Pseudo dice [0.8389] +2024-11-21 12:35:58.525866: Epoch time: 18.71 s +2024-11-21 12:35:59.345402: +2024-11-21 12:35:59.345838: Epoch 342 +2024-11-21 12:35:59.345984: Current learning rate: 0.00961 +2024-11-21 12:36:17.478307: train_loss -0.7497 +2024-11-21 12:36:17.497235: val_loss -0.7393 +2024-11-21 12:36:17.497396: Pseudo dice [0.8217] +2024-11-21 12:36:17.497497: Epoch time: 18.13 s +2024-11-21 12:36:18.470856: +2024-11-21 12:36:18.471301: Epoch 343 +2024-11-21 12:36:18.471442: Current learning rate: 0.00961 +2024-11-21 12:36:38.279822: train_loss -0.7402 +2024-11-21 12:36:38.283949: val_loss -0.7483 +2024-11-21 12:36:38.284107: Pseudo dice [0.8326] +2024-11-21 12:36:38.284201: Epoch time: 19.81 s +2024-11-21 12:36:39.219220: +2024-11-21 12:36:39.219437: Epoch 344 +2024-11-21 12:36:39.219551: Current learning rate: 0.00961 +2024-11-21 12:36:58.065502: train_loss -0.7498 +2024-11-21 12:36:58.069885: val_loss -0.7393 +2024-11-21 12:36:58.070031: Pseudo dice [0.8288] +2024-11-21 12:36:58.070288: Epoch time: 18.85 s +2024-11-21 12:36:58.887944: +2024-11-21 12:36:58.888186: Epoch 345 +2024-11-21 12:36:58.888348: Current learning rate: 0.00961 +2024-11-21 12:37:17.437198: train_loss -0.7407 +2024-11-21 12:37:17.443165: val_loss -0.7356 +2024-11-21 12:37:17.443298: Pseudo dice [0.8423] +2024-11-21 12:37:17.443398: Epoch time: 18.55 s +2024-11-21 12:37:18.335841: +2024-11-21 12:37:18.336076: Epoch 346 +2024-11-21 12:37:18.336215: Current learning rate: 0.00961 +2024-11-21 12:37:37.293105: train_loss -0.7472 +2024-11-21 12:37:37.300252: val_loss -0.763 +2024-11-21 12:37:37.300388: Pseudo dice [0.8284] +2024-11-21 12:37:37.300482: Epoch time: 18.96 s +2024-11-21 12:37:38.151598: +2024-11-21 12:37:38.151836: Epoch 347 +2024-11-21 12:37:38.151968: Current learning rate: 0.00961 +2024-11-21 12:37:57.186256: train_loss -0.7553 +2024-11-21 12:37:57.209989: val_loss -0.7513 +2024-11-21 12:37:57.210163: Pseudo dice [0.8438] +2024-11-21 12:37:57.210257: Epoch time: 19.04 s +2024-11-21 12:37:58.197078: +2024-11-21 12:37:58.197334: Epoch 348 +2024-11-21 12:37:58.197462: Current learning rate: 0.00961 +2024-11-21 12:38:17.079199: train_loss -0.7519 +2024-11-21 12:38:17.097495: val_loss -0.7683 +2024-11-21 12:38:17.097647: Pseudo dice [0.843] +2024-11-21 12:38:17.097737: Epoch time: 18.88 s +2024-11-21 12:38:18.047152: +2024-11-21 12:38:18.047370: Epoch 349 +2024-11-21 12:38:18.047505: Current learning rate: 0.00961 +2024-11-21 12:38:37.004247: train_loss -0.74 +2024-11-21 12:38:37.012415: val_loss -0.7454 +2024-11-21 12:38:37.012589: Pseudo dice [0.8395] +2024-11-21 12:38:37.012703: Epoch time: 18.96 s +2024-11-21 12:38:38.092142: +2024-11-21 12:38:38.092364: Epoch 350 +2024-11-21 12:38:38.092499: Current learning rate: 0.00961 +2024-11-21 12:38:57.202177: train_loss -0.7397 +2024-11-21 12:38:57.209352: val_loss -0.7723 +2024-11-21 12:38:57.209485: Pseudo dice [0.8394] +2024-11-21 12:38:57.209581: Epoch time: 19.11 s +2024-11-21 12:38:58.028720: +2024-11-21 12:38:58.028962: Epoch 351 +2024-11-21 12:38:58.029099: Current learning rate: 0.0096 +2024-11-21 12:39:17.062323: train_loss -0.7402 +2024-11-21 12:39:17.069864: val_loss -0.7428 +2024-11-21 12:39:17.069994: Pseudo dice [0.8242] +2024-11-21 12:39:17.070106: Epoch time: 19.03 s +2024-11-21 12:39:18.001467: +2024-11-21 12:39:18.001672: Epoch 352 +2024-11-21 12:39:18.001814: Current learning rate: 0.0096 +2024-11-21 12:39:36.945771: train_loss -0.7329 +2024-11-21 12:39:36.956620: val_loss -0.7361 +2024-11-21 12:39:36.956760: Pseudo dice [0.8215] +2024-11-21 12:39:36.956856: Epoch time: 18.95 s +2024-11-21 12:39:37.845907: +2024-11-21 12:39:37.846117: Epoch 353 +2024-11-21 12:39:37.846234: Current learning rate: 0.0096 +2024-11-21 12:39:56.898259: train_loss -0.7446 +2024-11-21 12:39:56.907398: val_loss -0.736 +2024-11-21 12:39:56.907544: Pseudo dice [0.8445] +2024-11-21 12:39:56.907635: Epoch time: 19.05 s +2024-11-21 12:39:57.858104: +2024-11-21 12:39:57.858322: Epoch 354 +2024-11-21 12:39:57.858444: Current learning rate: 0.0096 +2024-11-21 12:40:16.939242: train_loss -0.7419 +2024-11-21 12:40:16.948479: val_loss -0.7578 +2024-11-21 12:40:16.948630: Pseudo dice [0.83] +2024-11-21 12:40:16.948727: Epoch time: 19.08 s +2024-11-21 12:40:17.835539: +2024-11-21 12:40:17.835748: Epoch 355 +2024-11-21 12:40:17.835887: Current learning rate: 0.0096 +2024-11-21 12:40:36.549229: train_loss -0.7561 +2024-11-21 12:40:36.557652: val_loss -0.7522 +2024-11-21 12:40:36.557781: Pseudo dice [0.8287] +2024-11-21 12:40:36.557965: Epoch time: 18.71 s +2024-11-21 12:40:37.874481: +2024-11-21 12:40:37.874667: Epoch 356 +2024-11-21 12:40:37.874785: Current learning rate: 0.0096 +2024-11-21 12:40:55.751859: train_loss -0.7542 +2024-11-21 12:40:55.766093: val_loss -0.741 +2024-11-21 12:40:55.766227: Pseudo dice [0.8403] +2024-11-21 12:40:55.766319: Epoch time: 17.88 s +2024-11-21 12:40:56.728176: +2024-11-21 12:40:56.728403: Epoch 357 +2024-11-21 12:40:56.728526: Current learning rate: 0.0096 +2024-11-21 12:41:16.057396: train_loss -0.7506 +2024-11-21 12:41:16.062948: val_loss -0.7728 +2024-11-21 12:41:16.063103: Pseudo dice [0.846] +2024-11-21 12:41:16.063205: Epoch time: 19.33 s +2024-11-21 12:41:17.024794: +2024-11-21 12:41:17.025021: Epoch 358 +2024-11-21 12:41:17.025141: Current learning rate: 0.0096 +2024-11-21 12:41:36.038011: train_loss -0.7368 +2024-11-21 12:41:36.046376: val_loss -0.7584 +2024-11-21 12:41:36.046511: Pseudo dice [0.8329] +2024-11-21 12:41:36.046615: Epoch time: 19.01 s +2024-11-21 12:41:36.862139: +2024-11-21 12:41:36.862367: Epoch 359 +2024-11-21 12:41:36.862482: Current learning rate: 0.0096 +2024-11-21 12:41:55.301520: train_loss -0.7397 +2024-11-21 12:41:55.310929: val_loss -0.7585 +2024-11-21 12:41:55.311139: Pseudo dice [0.8375] +2024-11-21 12:41:55.311243: Epoch time: 18.44 s +2024-11-21 12:41:56.118779: +2024-11-21 12:41:56.118994: Epoch 360 +2024-11-21 12:41:56.119113: Current learning rate: 0.00959 +2024-11-21 12:42:14.951329: train_loss -0.7418 +2024-11-21 12:42:14.974744: val_loss -0.7369 +2024-11-21 12:42:14.974911: Pseudo dice [0.806] +2024-11-21 12:42:14.975021: Epoch time: 18.83 s +2024-11-21 12:42:15.842676: +2024-11-21 12:42:15.842887: Epoch 361 +2024-11-21 12:42:15.843012: Current learning rate: 0.00959 +2024-11-21 12:42:35.933435: train_loss -0.7505 +2024-11-21 12:42:35.939404: val_loss -0.7317 +2024-11-21 12:42:35.939552: Pseudo dice [0.8379] +2024-11-21 12:42:35.939643: Epoch time: 20.09 s +2024-11-21 12:42:36.826249: +2024-11-21 12:42:36.826459: Epoch 362 +2024-11-21 12:42:36.826592: Current learning rate: 0.00959 +2024-11-21 12:42:55.168224: train_loss -0.7497 +2024-11-21 12:42:55.173708: val_loss -0.7753 +2024-11-21 12:42:55.173859: Pseudo dice [0.844] +2024-11-21 12:42:55.173953: Epoch time: 18.34 s +2024-11-21 12:42:56.140626: +2024-11-21 12:42:56.140843: Epoch 363 +2024-11-21 12:42:56.140956: Current learning rate: 0.00959 +2024-11-21 12:43:15.230707: train_loss -0.7517 +2024-11-21 12:43:15.291579: val_loss -0.7519 +2024-11-21 12:43:15.291750: Pseudo dice [0.8334] +2024-11-21 12:43:15.291852: Epoch time: 19.09 s +2024-11-21 12:43:16.142997: +2024-11-21 12:43:16.143208: Epoch 364 +2024-11-21 12:43:16.143327: Current learning rate: 0.00959 +2024-11-21 12:43:34.284284: train_loss -0.7519 +2024-11-21 12:43:34.287770: val_loss -0.7473 +2024-11-21 12:43:34.287868: Pseudo dice [0.833] +2024-11-21 12:43:34.287966: Epoch time: 18.14 s +2024-11-21 12:43:35.091125: +2024-11-21 12:43:35.091327: Epoch 365 +2024-11-21 12:43:35.091469: Current learning rate: 0.00959 +2024-11-21 12:43:54.473690: train_loss -0.753 +2024-11-21 12:43:54.484267: val_loss -0.7618 +2024-11-21 12:43:54.484419: Pseudo dice [0.8476] +2024-11-21 12:43:54.484521: Epoch time: 19.38 s +2024-11-21 12:43:55.406005: +2024-11-21 12:43:55.406244: Epoch 366 +2024-11-21 12:43:55.406364: Current learning rate: 0.00959 +2024-11-21 12:44:14.150968: train_loss -0.7409 +2024-11-21 12:44:14.159181: val_loss -0.7465 +2024-11-21 12:44:14.159314: Pseudo dice [0.8317] +2024-11-21 12:44:14.159410: Epoch time: 18.75 s +2024-11-21 12:44:14.970087: +2024-11-21 12:44:14.970292: Epoch 367 +2024-11-21 12:44:14.970417: Current learning rate: 0.00959 +2024-11-21 12:44:33.954814: train_loss -0.7521 +2024-11-21 12:44:33.959780: val_loss -0.7064 +2024-11-21 12:44:33.959890: Pseudo dice [0.8348] +2024-11-21 12:44:33.959996: Epoch time: 18.99 s +2024-11-21 12:44:35.121374: +2024-11-21 12:44:35.152908: Epoch 368 +2024-11-21 12:44:35.153043: Current learning rate: 0.00959 +2024-11-21 12:44:53.323421: train_loss -0.7574 +2024-11-21 12:44:53.333796: val_loss -0.7473 +2024-11-21 12:44:53.333948: Pseudo dice [0.8435] +2024-11-21 12:44:53.334038: Epoch time: 18.2 s +2024-11-21 12:44:54.154125: +2024-11-21 12:44:54.154344: Epoch 369 +2024-11-21 12:44:54.154482: Current learning rate: 0.00958 +2024-11-21 12:45:12.846315: train_loss -0.7462 +2024-11-21 12:45:12.852168: val_loss -0.7554 +2024-11-21 12:45:12.852303: Pseudo dice [0.8457] +2024-11-21 12:45:12.852411: Epoch time: 18.69 s +2024-11-21 12:45:13.834708: +2024-11-21 12:45:13.834931: Epoch 370 +2024-11-21 12:45:13.835068: Current learning rate: 0.00958 +2024-11-21 12:45:32.140978: train_loss -0.7454 +2024-11-21 12:45:32.145448: val_loss -0.7538 +2024-11-21 12:45:32.145589: Pseudo dice [0.8277] +2024-11-21 12:45:32.145836: Epoch time: 18.31 s +2024-11-21 12:45:32.992513: +2024-11-21 12:45:32.992740: Epoch 371 +2024-11-21 12:45:32.992875: Current learning rate: 0.00958 +2024-11-21 12:45:52.461985: train_loss -0.7271 +2024-11-21 12:45:52.468117: val_loss -0.6797 +2024-11-21 12:45:52.468255: Pseudo dice [0.8216] +2024-11-21 12:45:52.468359: Epoch time: 19.47 s +2024-11-21 12:45:53.337527: +2024-11-21 12:45:53.337736: Epoch 372 +2024-11-21 12:45:53.337866: Current learning rate: 0.00958 +2024-11-21 12:46:12.741830: train_loss -0.7365 +2024-11-21 12:46:12.747243: val_loss -0.745 +2024-11-21 12:46:12.747378: Pseudo dice [0.8279] +2024-11-21 12:46:12.747478: Epoch time: 19.41 s +2024-11-21 12:46:13.595543: +2024-11-21 12:46:13.595758: Epoch 373 +2024-11-21 12:46:13.595889: Current learning rate: 0.00958 +2024-11-21 12:46:32.035306: train_loss -0.7483 +2024-11-21 12:46:32.040961: val_loss -0.7686 +2024-11-21 12:46:32.041089: Pseudo dice [0.8403] +2024-11-21 12:46:32.041193: Epoch time: 18.44 s +2024-11-21 12:46:32.841353: +2024-11-21 12:46:32.841544: Epoch 374 +2024-11-21 12:46:32.841676: Current learning rate: 0.00958 +2024-11-21 12:46:52.455019: train_loss -0.7515 +2024-11-21 12:46:52.460454: val_loss -0.7551 +2024-11-21 12:46:52.460581: Pseudo dice [0.8319] +2024-11-21 12:46:52.460675: Epoch time: 19.61 s +2024-11-21 12:46:53.475384: +2024-11-21 12:46:53.475605: Epoch 375 +2024-11-21 12:46:53.475724: Current learning rate: 0.00958 +2024-11-21 12:47:13.395697: train_loss -0.741 +2024-11-21 12:47:13.402867: val_loss -0.77 +2024-11-21 12:47:13.403007: Pseudo dice [0.8365] +2024-11-21 12:47:13.403107: Epoch time: 19.92 s +2024-11-21 12:47:14.343020: +2024-11-21 12:47:14.343237: Epoch 376 +2024-11-21 12:47:14.343362: Current learning rate: 0.00958 +2024-11-21 12:47:32.692585: train_loss -0.736 +2024-11-21 12:47:32.712155: val_loss -0.7136 +2024-11-21 12:47:32.712338: Pseudo dice [0.8111] +2024-11-21 12:47:32.712432: Epoch time: 18.35 s +2024-11-21 12:47:33.516626: +2024-11-21 12:47:33.516871: Epoch 377 +2024-11-21 12:47:33.517015: Current learning rate: 0.00957 +2024-11-21 12:47:51.631966: train_loss -0.7147 +2024-11-21 12:47:51.638011: val_loss -0.751 +2024-11-21 12:47:51.638161: Pseudo dice [0.836] +2024-11-21 12:47:51.638271: Epoch time: 18.11 s +2024-11-21 12:47:52.692538: +2024-11-21 12:47:52.692749: Epoch 378 +2024-11-21 12:47:52.692864: Current learning rate: 0.00957 +2024-11-21 12:48:12.812252: train_loss -0.6947 +2024-11-21 12:48:12.832306: val_loss -0.7418 +2024-11-21 12:48:12.832441: Pseudo dice [0.8262] +2024-11-21 12:48:12.832529: Epoch time: 20.12 s +2024-11-21 12:48:13.866317: +2024-11-21 12:48:13.866572: Epoch 379 +2024-11-21 12:48:13.866696: Current learning rate: 0.00957 +2024-11-21 12:48:33.914580: train_loss -0.7342 +2024-11-21 12:48:33.922276: val_loss -0.7569 +2024-11-21 12:48:33.922426: Pseudo dice [0.8289] +2024-11-21 12:48:33.922508: Epoch time: 20.05 s +2024-11-21 12:48:34.751093: +2024-11-21 12:48:34.751341: Epoch 380 +2024-11-21 12:48:34.751467: Current learning rate: 0.00957 +2024-11-21 12:48:53.427652: train_loss -0.7445 +2024-11-21 12:48:53.442823: val_loss -0.7583 +2024-11-21 12:48:53.442992: Pseudo dice [0.8327] +2024-11-21 12:48:53.458972: Epoch time: 18.68 s +2024-11-21 12:48:54.445333: +2024-11-21 12:48:54.445627: Epoch 381 +2024-11-21 12:48:54.445778: Current learning rate: 0.00957 +2024-11-21 12:49:14.004923: train_loss -0.743 +2024-11-21 12:49:14.008200: val_loss -0.7437 +2024-11-21 12:49:14.008338: Pseudo dice [0.8323] +2024-11-21 12:49:14.008423: Epoch time: 19.56 s +2024-11-21 12:49:14.816570: +2024-11-21 12:49:14.816777: Epoch 382 +2024-11-21 12:49:14.816890: Current learning rate: 0.00957 +2024-11-21 12:49:34.067374: train_loss -0.7485 +2024-11-21 12:49:34.070112: val_loss -0.7554 +2024-11-21 12:49:34.070210: Pseudo dice [0.8298] +2024-11-21 12:49:34.070294: Epoch time: 19.25 s +2024-11-21 12:49:34.877357: +2024-11-21 12:49:34.877559: Epoch 383 +2024-11-21 12:49:34.877680: Current learning rate: 0.00957 +2024-11-21 12:49:53.997274: train_loss -0.7382 +2024-11-21 12:49:54.000934: val_loss -0.7607 +2024-11-21 12:49:54.001033: Pseudo dice [0.8478] +2024-11-21 12:49:54.001130: Epoch time: 19.12 s +2024-11-21 12:49:54.812131: +2024-11-21 12:49:54.812343: Epoch 384 +2024-11-21 12:49:54.812458: Current learning rate: 0.00957 +2024-11-21 12:50:13.599100: train_loss -0.7519 +2024-11-21 12:50:13.606960: val_loss -0.7461 +2024-11-21 12:50:13.607095: Pseudo dice [0.8584] +2024-11-21 12:50:13.607197: Epoch time: 18.79 s +2024-11-21 12:50:14.416497: +2024-11-21 12:50:14.416720: Epoch 385 +2024-11-21 12:50:14.416848: Current learning rate: 0.00957 +2024-11-21 12:50:34.607250: train_loss -0.7412 +2024-11-21 12:50:34.611194: val_loss -0.7519 +2024-11-21 12:50:34.611314: Pseudo dice [0.8262] +2024-11-21 12:50:34.611412: Epoch time: 20.19 s +2024-11-21 12:50:35.419740: +2024-11-21 12:50:35.419943: Epoch 386 +2024-11-21 12:50:35.420092: Current learning rate: 0.00956 +2024-11-21 12:50:54.920190: train_loss -0.7412 +2024-11-21 12:50:54.927097: val_loss -0.7264 +2024-11-21 12:50:54.927238: Pseudo dice [0.8173] +2024-11-21 12:50:54.927326: Epoch time: 19.5 s +2024-11-21 12:50:55.747289: +2024-11-21 12:50:55.747495: Epoch 387 +2024-11-21 12:50:55.747619: Current learning rate: 0.00956 +2024-11-21 12:51:14.539129: train_loss -0.7547 +2024-11-21 12:51:14.543883: val_loss -0.7599 +2024-11-21 12:51:14.544014: Pseudo dice [0.8341] +2024-11-21 12:51:14.544116: Epoch time: 18.79 s +2024-11-21 12:51:15.515472: +2024-11-21 12:51:15.515699: Epoch 388 +2024-11-21 12:51:15.515818: Current learning rate: 0.00956 +2024-11-21 12:51:33.353105: train_loss -0.7501 +2024-11-21 12:51:33.371657: val_loss -0.7456 +2024-11-21 12:51:33.371793: Pseudo dice [0.8313] +2024-11-21 12:51:33.371907: Epoch time: 17.84 s +2024-11-21 12:51:34.212538: +2024-11-21 12:51:34.212773: Epoch 389 +2024-11-21 12:51:34.212903: Current learning rate: 0.00956 +2024-11-21 12:51:52.505042: train_loss -0.7563 +2024-11-21 12:51:52.512049: val_loss -0.7486 +2024-11-21 12:51:52.512297: Pseudo dice [0.8329] +2024-11-21 12:51:52.512401: Epoch time: 18.29 s +2024-11-21 12:51:53.588693: +2024-11-21 12:51:53.588904: Epoch 390 +2024-11-21 12:51:53.589025: Current learning rate: 0.00956 +2024-11-21 12:52:12.300770: train_loss -0.7434 +2024-11-21 12:52:12.310479: val_loss -0.7574 +2024-11-21 12:52:12.310608: Pseudo dice [0.8476] +2024-11-21 12:52:12.310704: Epoch time: 18.71 s +2024-11-21 12:52:13.355967: +2024-11-21 12:52:13.356202: Epoch 391 +2024-11-21 12:52:13.356347: Current learning rate: 0.00956 +2024-11-21 12:52:31.971745: train_loss -0.7467 +2024-11-21 12:52:31.985968: val_loss -0.7875 +2024-11-21 12:52:31.986134: Pseudo dice [0.8497] +2024-11-21 12:52:31.986310: Epoch time: 18.62 s +2024-11-21 12:52:32.869621: +2024-11-21 12:52:32.869855: Epoch 392 +2024-11-21 12:52:32.869997: Current learning rate: 0.00956 +2024-11-21 12:52:51.937983: train_loss -0.7563 +2024-11-21 12:52:51.941778: val_loss -0.7288 +2024-11-21 12:52:51.941878: Pseudo dice [0.816] +2024-11-21 12:52:51.941965: Epoch time: 19.07 s +2024-11-21 12:52:52.748357: +2024-11-21 12:52:52.748586: Epoch 393 +2024-11-21 12:52:52.748705: Current learning rate: 0.00956 +2024-11-21 12:53:11.795046: train_loss -0.7594 +2024-11-21 12:53:11.802791: val_loss -0.7425 +2024-11-21 12:53:11.802903: Pseudo dice [0.8362] +2024-11-21 12:53:11.802997: Epoch time: 19.05 s +2024-11-21 12:53:12.672575: +2024-11-21 12:53:12.672780: Epoch 394 +2024-11-21 12:53:12.672901: Current learning rate: 0.00956 +2024-11-21 12:53:30.879893: train_loss -0.7564 +2024-11-21 12:53:30.885949: val_loss -0.7395 +2024-11-21 12:53:30.886070: Pseudo dice [0.8407] +2024-11-21 12:53:30.886246: Epoch time: 18.21 s +2024-11-21 12:53:31.694782: +2024-11-21 12:53:31.695003: Epoch 395 +2024-11-21 12:53:31.695130: Current learning rate: 0.00955 +2024-11-21 12:53:51.468214: train_loss -0.742 +2024-11-21 12:53:51.476331: val_loss -0.7483 +2024-11-21 12:53:51.476476: Pseudo dice [0.8309] +2024-11-21 12:53:51.476590: Epoch time: 19.77 s +2024-11-21 12:53:52.317034: +2024-11-21 12:53:52.317306: Epoch 396 +2024-11-21 12:53:52.317430: Current learning rate: 0.00955 +2024-11-21 12:54:11.717481: train_loss -0.752 +2024-11-21 12:54:11.726863: val_loss -0.7392 +2024-11-21 12:54:11.726988: Pseudo dice [0.854] +2024-11-21 12:54:11.727087: Epoch time: 19.4 s +2024-11-21 12:54:12.574711: +2024-11-21 12:54:12.574907: Epoch 397 +2024-11-21 12:54:12.575020: Current learning rate: 0.00955 +2024-11-21 12:54:31.230226: train_loss -0.75 +2024-11-21 12:54:31.236722: val_loss -0.7701 +2024-11-21 12:54:31.236883: Pseudo dice [0.8508] +2024-11-21 12:54:31.236970: Epoch time: 18.66 s +2024-11-21 12:54:32.086365: +2024-11-21 12:54:32.086603: Epoch 398 +2024-11-21 12:54:32.086725: Current learning rate: 0.00955 +2024-11-21 12:54:51.777601: train_loss -0.741 +2024-11-21 12:54:51.783106: val_loss -0.7511 +2024-11-21 12:54:51.783241: Pseudo dice [0.8342] +2024-11-21 12:54:51.783340: Epoch time: 19.69 s +2024-11-21 12:54:52.596894: +2024-11-21 12:54:52.597143: Epoch 399 +2024-11-21 12:54:52.597280: Current learning rate: 0.00955 +2024-11-21 12:55:12.030870: train_loss -0.7589 +2024-11-21 12:55:12.035218: val_loss -0.7397 +2024-11-21 12:55:12.035376: Pseudo dice [0.8309] +2024-11-21 12:55:12.035473: Epoch time: 19.43 s +2024-11-21 12:55:13.299943: +2024-11-21 12:55:13.300183: Epoch 400 +2024-11-21 12:55:13.300298: Current learning rate: 0.00955 +2024-11-21 12:55:32.388046: train_loss -0.7394 +2024-11-21 12:55:32.395447: val_loss -0.7215 +2024-11-21 12:55:32.395579: Pseudo dice [0.8223] +2024-11-21 12:55:32.395667: Epoch time: 19.09 s +2024-11-21 12:55:33.350263: +2024-11-21 12:55:33.350468: Epoch 401 +2024-11-21 12:55:33.350584: Current learning rate: 0.00955 +2024-11-21 12:55:52.662273: train_loss -0.748 +2024-11-21 12:55:52.677343: val_loss -0.744 +2024-11-21 12:55:52.677483: Pseudo dice [0.8314] +2024-11-21 12:55:52.677613: Epoch time: 19.31 s +2024-11-21 12:55:53.604687: +2024-11-21 12:55:53.604901: Epoch 402 +2024-11-21 12:55:53.605030: Current learning rate: 0.00955 +2024-11-21 12:56:12.461016: train_loss -0.7268 +2024-11-21 12:56:12.466918: val_loss -0.7545 +2024-11-21 12:56:12.467062: Pseudo dice [0.8338] +2024-11-21 12:56:12.467167: Epoch time: 18.86 s +2024-11-21 12:56:13.335019: +2024-11-21 12:56:13.335228: Epoch 403 +2024-11-21 12:56:13.335351: Current learning rate: 0.00955 +2024-11-21 12:56:33.484441: train_loss -0.7485 +2024-11-21 12:56:33.492102: val_loss -0.7346 +2024-11-21 12:56:33.492253: Pseudo dice [0.825] +2024-11-21 12:56:33.492341: Epoch time: 20.15 s +2024-11-21 12:56:34.385976: +2024-11-21 12:56:34.386205: Epoch 404 +2024-11-21 12:56:34.386334: Current learning rate: 0.00954 +2024-11-21 12:56:53.547856: train_loss -0.7393 +2024-11-21 12:56:53.560122: val_loss -0.7368 +2024-11-21 12:56:53.560282: Pseudo dice [0.8321] +2024-11-21 12:56:53.560369: Epoch time: 19.16 s +2024-11-21 12:56:54.459777: +2024-11-21 12:56:54.460007: Epoch 405 +2024-11-21 12:56:54.460155: Current learning rate: 0.00954 +2024-11-21 12:57:14.434091: train_loss -0.7435 +2024-11-21 12:57:14.439966: val_loss -0.7655 +2024-11-21 12:57:14.440097: Pseudo dice [0.8465] +2024-11-21 12:57:14.440192: Epoch time: 19.98 s +2024-11-21 12:57:15.275137: +2024-11-21 12:57:15.275343: Epoch 406 +2024-11-21 12:57:15.275483: Current learning rate: 0.00954 +2024-11-21 12:57:33.911323: train_loss -0.754 +2024-11-21 12:57:33.917527: val_loss -0.7458 +2024-11-21 12:57:33.917711: Pseudo dice [0.8399] +2024-11-21 12:57:33.917806: Epoch time: 18.64 s +2024-11-21 12:57:34.805219: +2024-11-21 12:57:34.805428: Epoch 407 +2024-11-21 12:57:34.805568: Current learning rate: 0.00954 +2024-11-21 12:57:52.840728: train_loss -0.7629 +2024-11-21 12:57:52.844706: val_loss -0.7509 +2024-11-21 12:57:52.844810: Pseudo dice [0.838] +2024-11-21 12:57:52.844909: Epoch time: 18.04 s +2024-11-21 12:57:53.651125: +2024-11-21 12:57:53.651349: Epoch 408 +2024-11-21 12:57:53.651476: Current learning rate: 0.00954 +2024-11-21 12:58:12.250223: train_loss -0.765 +2024-11-21 12:58:12.257020: val_loss -0.7638 +2024-11-21 12:58:12.257167: Pseudo dice [0.8329] +2024-11-21 12:58:12.257327: Epoch time: 18.6 s +2024-11-21 12:58:13.081363: +2024-11-21 12:58:13.081579: Epoch 409 +2024-11-21 12:58:13.081705: Current learning rate: 0.00954 +2024-11-21 12:58:32.851630: train_loss -0.7536 +2024-11-21 12:58:32.854236: val_loss -0.7575 +2024-11-21 12:58:32.854330: Pseudo dice [0.8541] +2024-11-21 12:58:32.854415: Epoch time: 19.77 s +2024-11-21 12:58:33.662170: +2024-11-21 12:58:33.662436: Epoch 410 +2024-11-21 12:58:33.662564: Current learning rate: 0.00954 +2024-11-21 12:58:53.157717: train_loss -0.7588 +2024-11-21 12:58:53.170350: val_loss -0.7472 +2024-11-21 12:58:53.170521: Pseudo dice [0.8441] +2024-11-21 12:58:53.170678: Epoch time: 19.5 s +2024-11-21 12:58:53.959540: +2024-11-21 12:58:53.959767: Epoch 411 +2024-11-21 12:58:53.959902: Current learning rate: 0.00954 +2024-11-21 12:59:13.233112: train_loss -0.7588 +2024-11-21 12:59:13.237056: val_loss -0.7665 +2024-11-21 12:59:13.237210: Pseudo dice [0.8585] +2024-11-21 12:59:13.237292: Epoch time: 19.27 s +2024-11-21 12:59:14.041762: +2024-11-21 12:59:14.042003: Epoch 412 +2024-11-21 12:59:14.042141: Current learning rate: 0.00954 +2024-11-21 12:59:33.691825: train_loss -0.7519 +2024-11-21 12:59:33.699244: val_loss -0.7329 +2024-11-21 12:59:33.699425: Pseudo dice [0.83] +2024-11-21 12:59:33.699526: Epoch time: 19.65 s +2024-11-21 12:59:34.696326: +2024-11-21 12:59:34.696602: Epoch 413 +2024-11-21 12:59:34.696744: Current learning rate: 0.00953 +2024-11-21 12:59:53.770365: train_loss -0.7506 +2024-11-21 12:59:53.774231: val_loss -0.7579 +2024-11-21 12:59:53.774414: Pseudo dice [0.8418] +2024-11-21 12:59:53.774508: Epoch time: 19.07 s +2024-11-21 12:59:54.609331: +2024-11-21 12:59:54.609565: Epoch 414 +2024-11-21 12:59:54.609682: Current learning rate: 0.00953 +2024-11-21 13:00:14.082098: train_loss -0.744 +2024-11-21 13:00:14.085186: val_loss -0.7355 +2024-11-21 13:00:14.085294: Pseudo dice [0.8289] +2024-11-21 13:00:14.085387: Epoch time: 19.47 s +2024-11-21 13:00:14.867027: +2024-11-21 13:00:14.867283: Epoch 415 +2024-11-21 13:00:14.867415: Current learning rate: 0.00953 +2024-11-21 13:00:34.032717: train_loss -0.7294 +2024-11-21 13:00:34.037982: val_loss -0.7582 +2024-11-21 13:00:34.038161: Pseudo dice [0.8372] +2024-11-21 13:00:34.038246: Epoch time: 19.17 s +2024-11-21 13:00:34.840408: +2024-11-21 13:00:34.840638: Epoch 416 +2024-11-21 13:00:34.840769: Current learning rate: 0.00953 +2024-11-21 13:00:54.495419: train_loss -0.7437 +2024-11-21 13:00:54.498378: val_loss -0.7463 +2024-11-21 13:00:54.498474: Pseudo dice [0.8347] +2024-11-21 13:00:54.498565: Epoch time: 19.66 s +2024-11-21 13:00:55.282487: +2024-11-21 13:00:55.282722: Epoch 417 +2024-11-21 13:00:55.282845: Current learning rate: 0.00953 +2024-11-21 13:01:15.390108: train_loss -0.7459 +2024-11-21 13:01:15.396431: val_loss -0.7241 +2024-11-21 13:01:15.396576: Pseudo dice [0.8421] +2024-11-21 13:01:15.396694: Epoch time: 20.1 s +2024-11-21 13:01:16.344887: +2024-11-21 13:01:16.345115: Epoch 418 +2024-11-21 13:01:16.345234: Current learning rate: 0.00953 +2024-11-21 13:01:36.628629: train_loss -0.7479 +2024-11-21 13:01:36.638489: val_loss -0.7489 +2024-11-21 13:01:36.638644: Pseudo dice [0.8474] +2024-11-21 13:01:36.638758: Epoch time: 20.28 s +2024-11-21 13:01:37.449215: +2024-11-21 13:01:37.449693: Epoch 419 +2024-11-21 13:01:37.449826: Current learning rate: 0.00953 +2024-11-21 13:01:56.733016: train_loss -0.74 +2024-11-21 13:01:56.737322: val_loss -0.7601 +2024-11-21 13:01:56.737438: Pseudo dice [0.8503] +2024-11-21 13:01:56.737525: Epoch time: 19.28 s +2024-11-21 13:01:57.518368: +2024-11-21 13:01:57.518575: Epoch 420 +2024-11-21 13:01:57.518693: Current learning rate: 0.00953 +2024-11-21 13:02:17.188777: train_loss -0.7442 +2024-11-21 13:02:17.196339: val_loss -0.7429 +2024-11-21 13:02:17.196481: Pseudo dice [0.8437] +2024-11-21 13:02:17.196584: Epoch time: 19.67 s +2024-11-21 13:02:17.975063: +2024-11-21 13:02:17.975266: Epoch 421 +2024-11-21 13:02:17.975387: Current learning rate: 0.00953 +2024-11-21 13:02:36.713463: train_loss -0.7417 +2024-11-21 13:02:36.722612: val_loss -0.7603 +2024-11-21 13:02:36.722742: Pseudo dice [0.8388] +2024-11-21 13:02:36.722854: Epoch time: 18.74 s +2024-11-21 13:02:37.649898: +2024-11-21 13:02:37.650139: Epoch 422 +2024-11-21 13:02:37.650282: Current learning rate: 0.00952 +2024-11-21 13:02:57.099055: train_loss -0.7348 +2024-11-21 13:02:57.101599: val_loss -0.7411 +2024-11-21 13:02:57.101701: Pseudo dice [0.8304] +2024-11-21 13:02:57.101817: Epoch time: 19.45 s +2024-11-21 13:02:57.880708: +2024-11-21 13:02:57.880920: Epoch 423 +2024-11-21 13:02:57.881057: Current learning rate: 0.00952 +2024-11-21 13:03:17.120259: train_loss -0.7422 +2024-11-21 13:03:17.130359: val_loss -0.7782 +2024-11-21 13:03:17.130493: Pseudo dice [0.8251] +2024-11-21 13:03:17.130584: Epoch time: 19.24 s +2024-11-21 13:03:17.916507: +2024-11-21 13:03:17.916704: Epoch 424 +2024-11-21 13:03:17.916816: Current learning rate: 0.00952 +2024-11-21 13:03:37.794160: train_loss -0.7334 +2024-11-21 13:03:37.799344: val_loss -0.7593 +2024-11-21 13:03:37.799460: Pseudo dice [0.8402] +2024-11-21 13:03:37.799585: Epoch time: 19.88 s +2024-11-21 13:03:38.695780: +2024-11-21 13:03:38.695998: Epoch 425 +2024-11-21 13:03:38.696126: Current learning rate: 0.00952 +2024-11-21 13:03:57.316746: train_loss -0.7403 +2024-11-21 13:03:57.319448: val_loss -0.7493 +2024-11-21 13:03:57.319611: Pseudo dice [0.8393] +2024-11-21 13:03:57.319697: Epoch time: 18.62 s +2024-11-21 13:03:58.126031: +2024-11-21 13:03:58.126264: Epoch 426 +2024-11-21 13:03:58.126406: Current learning rate: 0.00952 +2024-11-21 13:04:17.492456: train_loss -0.7283 +2024-11-21 13:04:17.508008: val_loss -0.7442 +2024-11-21 13:04:17.508194: Pseudo dice [0.8314] +2024-11-21 13:04:17.508300: Epoch time: 19.37 s +2024-11-21 13:04:18.364126: +2024-11-21 13:04:18.364329: Epoch 427 +2024-11-21 13:04:18.364449: Current learning rate: 0.00952 +2024-11-21 13:04:37.480038: train_loss -0.7462 +2024-11-21 13:04:37.487291: val_loss -0.7455 +2024-11-21 13:04:37.487448: Pseudo dice [0.8471] +2024-11-21 13:04:37.487551: Epoch time: 19.11 s +2024-11-21 13:04:38.370544: +2024-11-21 13:04:38.370757: Epoch 428 +2024-11-21 13:04:38.370875: Current learning rate: 0.00952 +2024-11-21 13:04:57.664813: train_loss -0.7474 +2024-11-21 13:04:57.672343: val_loss -0.7634 +2024-11-21 13:04:57.672490: Pseudo dice [0.8434] +2024-11-21 13:04:57.672588: Epoch time: 19.3 s +2024-11-21 13:04:58.656872: +2024-11-21 13:04:58.657083: Epoch 429 +2024-11-21 13:04:58.657222: Current learning rate: 0.00952 +2024-11-21 13:05:18.342094: train_loss -0.7383 +2024-11-21 13:05:18.348625: val_loss -0.7433 +2024-11-21 13:05:18.348803: Pseudo dice [0.8369] +2024-11-21 13:05:18.348921: Epoch time: 19.69 s +2024-11-21 13:05:19.179895: +2024-11-21 13:05:19.180099: Epoch 430 +2024-11-21 13:05:19.180228: Current learning rate: 0.00951 +2024-11-21 13:05:39.025501: train_loss -0.7323 +2024-11-21 13:05:39.031216: val_loss -0.7495 +2024-11-21 13:05:39.031353: Pseudo dice [0.8293] +2024-11-21 13:05:39.031466: Epoch time: 19.85 s +2024-11-21 13:05:39.816103: +2024-11-21 13:05:39.816308: Epoch 431 +2024-11-21 13:05:39.816439: Current learning rate: 0.00951 +2024-11-21 13:06:00.645725: train_loss -0.7566 +2024-11-21 13:06:00.647465: val_loss -0.7288 +2024-11-21 13:06:00.647558: Pseudo dice [0.8413] +2024-11-21 13:06:00.647853: Epoch time: 20.83 s +2024-11-21 13:06:01.422024: +2024-11-21 13:06:01.422235: Epoch 432 +2024-11-21 13:06:01.422361: Current learning rate: 0.00951 +2024-11-21 13:06:20.197800: train_loss -0.7545 +2024-11-21 13:06:20.205165: val_loss -0.7563 +2024-11-21 13:06:20.205292: Pseudo dice [0.8459] +2024-11-21 13:06:20.205389: Epoch time: 18.78 s +2024-11-21 13:06:21.061926: +2024-11-21 13:06:21.062138: Epoch 433 +2024-11-21 13:06:21.062250: Current learning rate: 0.00951 +2024-11-21 13:06:39.259163: train_loss -0.7488 +2024-11-21 13:06:39.266317: val_loss -0.7492 +2024-11-21 13:06:39.266475: Pseudo dice [0.8415] +2024-11-21 13:06:39.266569: Epoch time: 18.2 s +2024-11-21 13:06:40.090107: +2024-11-21 13:06:40.090343: Epoch 434 +2024-11-21 13:06:40.090458: Current learning rate: 0.00951 +2024-11-21 13:06:58.833554: train_loss -0.7431 +2024-11-21 13:06:58.842972: val_loss -0.7287 +2024-11-21 13:06:58.843119: Pseudo dice [0.829] +2024-11-21 13:06:58.843210: Epoch time: 18.74 s +2024-11-21 13:06:59.671306: +2024-11-21 13:06:59.671633: Epoch 435 +2024-11-21 13:06:59.671760: Current learning rate: 0.00951 +2024-11-21 13:07:19.158545: train_loss -0.7568 +2024-11-21 13:07:19.168180: val_loss -0.7385 +2024-11-21 13:07:19.168307: Pseudo dice [0.848] +2024-11-21 13:07:19.168427: Epoch time: 19.49 s +2024-11-21 13:07:19.984372: +2024-11-21 13:07:19.984584: Epoch 436 +2024-11-21 13:07:19.984729: Current learning rate: 0.00951 +2024-11-21 13:07:38.962396: train_loss -0.7433 +2024-11-21 13:07:38.971371: val_loss -0.7669 +2024-11-21 13:07:38.971509: Pseudo dice [0.8414] +2024-11-21 13:07:38.971608: Epoch time: 18.98 s +2024-11-21 13:07:39.771292: +2024-11-21 13:07:39.771518: Epoch 437 +2024-11-21 13:07:39.771638: Current learning rate: 0.00951 +2024-11-21 13:07:58.300009: train_loss -0.7478 +2024-11-21 13:07:58.303352: val_loss -0.7581 +2024-11-21 13:07:58.303507: Pseudo dice [0.8486] +2024-11-21 13:07:58.303618: Epoch time: 18.53 s +2024-11-21 13:07:59.288644: +2024-11-21 13:07:59.288860: Epoch 438 +2024-11-21 13:07:59.288982: Current learning rate: 0.00951 +2024-11-21 13:08:18.145030: train_loss -0.7603 +2024-11-21 13:08:18.152114: val_loss -0.7456 +2024-11-21 13:08:18.152262: Pseudo dice [0.8522] +2024-11-21 13:08:18.152364: Epoch time: 18.86 s +2024-11-21 13:08:18.152443: Yayy! New best EMA pseudo Dice: 0.8415 +2024-11-21 13:08:19.230411: +2024-11-21 13:08:19.230632: Epoch 439 +2024-11-21 13:08:19.230764: Current learning rate: 0.0095 +2024-11-21 13:08:39.062142: train_loss -0.7541 +2024-11-21 13:08:39.067773: val_loss -0.7702 +2024-11-21 13:08:39.067903: Pseudo dice [0.8334] +2024-11-21 13:08:39.067999: Epoch time: 19.83 s +2024-11-21 13:08:39.870844: +2024-11-21 13:08:39.871068: Epoch 440 +2024-11-21 13:08:39.871189: Current learning rate: 0.0095 +2024-11-21 13:08:58.852815: train_loss -0.7543 +2024-11-21 13:08:58.858391: val_loss -0.7585 +2024-11-21 13:08:58.858519: Pseudo dice [0.8379] +2024-11-21 13:08:58.858695: Epoch time: 18.98 s +2024-11-21 13:08:59.658170: +2024-11-21 13:08:59.658376: Epoch 441 +2024-11-21 13:08:59.658501: Current learning rate: 0.0095 +2024-11-21 13:09:18.783627: train_loss -0.7417 +2024-11-21 13:09:18.792179: val_loss -0.7483 +2024-11-21 13:09:18.792323: Pseudo dice [0.8362] +2024-11-21 13:09:18.792415: Epoch time: 19.13 s +2024-11-21 13:09:19.580877: +2024-11-21 13:09:19.581086: Epoch 442 +2024-11-21 13:09:19.581212: Current learning rate: 0.0095 +2024-11-21 13:09:38.848582: train_loss -0.7472 +2024-11-21 13:09:38.852028: val_loss -0.7552 +2024-11-21 13:09:38.852168: Pseudo dice [0.8356] +2024-11-21 13:09:38.852260: Epoch time: 19.27 s +2024-11-21 13:09:39.638773: +2024-11-21 13:09:39.638983: Epoch 443 +2024-11-21 13:09:39.639101: Current learning rate: 0.0095 +2024-11-21 13:09:59.157238: train_loss -0.7488 +2024-11-21 13:09:59.164430: val_loss -0.7628 +2024-11-21 13:09:59.164552: Pseudo dice [0.8405] +2024-11-21 13:09:59.164637: Epoch time: 19.52 s +2024-11-21 13:09:59.949455: +2024-11-21 13:09:59.949674: Epoch 444 +2024-11-21 13:09:59.949793: Current learning rate: 0.0095 +2024-11-21 13:10:18.492154: train_loss -0.7516 +2024-11-21 13:10:18.504791: val_loss -0.7633 +2024-11-21 13:10:18.504930: Pseudo dice [0.8379] +2024-11-21 13:10:18.505024: Epoch time: 18.54 s +2024-11-21 13:10:19.438084: +2024-11-21 13:10:19.438338: Epoch 445 +2024-11-21 13:10:19.438457: Current learning rate: 0.0095 +2024-11-21 13:10:38.480638: train_loss -0.7473 +2024-11-21 13:10:38.490116: val_loss -0.7405 +2024-11-21 13:10:38.490232: Pseudo dice [0.8319] +2024-11-21 13:10:38.490343: Epoch time: 19.04 s +2024-11-21 13:10:39.333939: +2024-11-21 13:10:39.334155: Epoch 446 +2024-11-21 13:10:39.334273: Current learning rate: 0.0095 +2024-11-21 13:10:59.992561: train_loss -0.758 +2024-11-21 13:10:59.994957: val_loss -0.7427 +2024-11-21 13:10:59.995088: Pseudo dice [0.8318] +2024-11-21 13:10:59.995185: Epoch time: 20.66 s +2024-11-21 13:11:00.782226: +2024-11-21 13:11:00.782448: Epoch 447 +2024-11-21 13:11:00.782568: Current learning rate: 0.0095 +2024-11-21 13:11:20.293793: train_loss -0.7573 +2024-11-21 13:11:20.296683: val_loss -0.7572 +2024-11-21 13:11:20.296817: Pseudo dice [0.8393] +2024-11-21 13:11:20.296918: Epoch time: 19.51 s +2024-11-21 13:11:21.482895: +2024-11-21 13:11:21.483118: Epoch 448 +2024-11-21 13:11:21.483236: Current learning rate: 0.00949 +2024-11-21 13:11:40.417809: train_loss -0.7458 +2024-11-21 13:11:40.427101: val_loss -0.7372 +2024-11-21 13:11:40.427216: Pseudo dice [0.8462] +2024-11-21 13:11:40.427410: Epoch time: 18.94 s +2024-11-21 13:11:41.214002: +2024-11-21 13:11:41.214228: Epoch 449 +2024-11-21 13:11:41.214358: Current learning rate: 0.00949 +2024-11-21 13:12:01.175342: train_loss -0.7542 +2024-11-21 13:12:01.184335: val_loss -0.7526 +2024-11-21 13:12:01.184480: Pseudo dice [0.8322] +2024-11-21 13:12:01.184584: Epoch time: 19.96 s +2024-11-21 13:12:02.290007: +2024-11-21 13:12:02.290240: Epoch 450 +2024-11-21 13:12:02.290375: Current learning rate: 0.00949 +2024-11-21 13:12:20.912703: train_loss -0.7504 +2024-11-21 13:12:20.922303: val_loss -0.7537 +2024-11-21 13:12:20.922442: Pseudo dice [0.8444] +2024-11-21 13:12:20.922538: Epoch time: 18.62 s +2024-11-21 13:12:21.779943: +2024-11-21 13:12:21.780176: Epoch 451 +2024-11-21 13:12:21.780300: Current learning rate: 0.00949 +2024-11-21 13:12:40.118442: train_loss -0.736 +2024-11-21 13:12:40.122246: val_loss -0.7412 +2024-11-21 13:12:40.122363: Pseudo dice [0.837] +2024-11-21 13:12:40.122463: Epoch time: 18.34 s +2024-11-21 13:12:40.906222: +2024-11-21 13:12:40.906438: Epoch 452 +2024-11-21 13:12:40.906556: Current learning rate: 0.00949 +2024-11-21 13:12:59.990654: train_loss -0.7276 +2024-11-21 13:12:59.999027: val_loss -0.7413 +2024-11-21 13:12:59.999180: Pseudo dice [0.8227] +2024-11-21 13:12:59.999280: Epoch time: 19.09 s +2024-11-21 13:13:00.831399: +2024-11-21 13:13:00.831611: Epoch 453 +2024-11-21 13:13:00.831733: Current learning rate: 0.00949 +2024-11-21 13:13:20.382674: train_loss -0.7404 +2024-11-21 13:13:20.391422: val_loss -0.7484 +2024-11-21 13:13:20.391546: Pseudo dice [0.8332] +2024-11-21 13:13:20.391648: Epoch time: 19.55 s +2024-11-21 13:13:21.182698: +2024-11-21 13:13:21.182927: Epoch 454 +2024-11-21 13:13:21.183077: Current learning rate: 0.00949 +2024-11-21 13:13:39.779194: train_loss -0.7471 +2024-11-21 13:13:39.795803: val_loss -0.7489 +2024-11-21 13:13:39.795969: Pseudo dice [0.8385] +2024-11-21 13:13:39.796057: Epoch time: 18.6 s +2024-11-21 13:13:40.609336: +2024-11-21 13:13:40.609550: Epoch 455 +2024-11-21 13:13:40.609676: Current learning rate: 0.00949 +2024-11-21 13:14:00.034475: train_loss -0.7563 +2024-11-21 13:14:00.041197: val_loss -0.7526 +2024-11-21 13:14:00.041318: Pseudo dice [0.8183] +2024-11-21 13:14:00.041405: Epoch time: 19.43 s +2024-11-21 13:14:00.857165: +2024-11-21 13:14:00.857373: Epoch 456 +2024-11-21 13:14:00.857492: Current learning rate: 0.00949 +2024-11-21 13:14:20.340749: train_loss -0.7436 +2024-11-21 13:14:20.343731: val_loss -0.732 +2024-11-21 13:14:20.343846: Pseudo dice [0.8269] +2024-11-21 13:14:20.343954: Epoch time: 19.48 s +2024-11-21 13:14:21.130704: +2024-11-21 13:14:21.131159: Epoch 457 +2024-11-21 13:14:21.131279: Current learning rate: 0.00948 +2024-11-21 13:14:39.852840: train_loss -0.7511 +2024-11-21 13:14:39.857519: val_loss -0.7504 +2024-11-21 13:14:39.857642: Pseudo dice [0.8391] +2024-11-21 13:14:39.857730: Epoch time: 18.72 s +2024-11-21 13:14:40.805967: +2024-11-21 13:14:40.806223: Epoch 458 +2024-11-21 13:14:40.806349: Current learning rate: 0.00948 +2024-11-21 13:14:58.545974: train_loss -0.7453 +2024-11-21 13:14:58.548751: val_loss -0.7455 +2024-11-21 13:14:58.548850: Pseudo dice [0.8349] +2024-11-21 13:14:58.548933: Epoch time: 17.74 s +2024-11-21 13:14:59.330306: +2024-11-21 13:14:59.330530: Epoch 459 +2024-11-21 13:14:59.330664: Current learning rate: 0.00948 +2024-11-21 13:15:19.980155: train_loss -0.7459 +2024-11-21 13:15:19.986069: val_loss -0.7656 +2024-11-21 13:15:19.986212: Pseudo dice [0.8416] +2024-11-21 13:15:19.986303: Epoch time: 20.65 s +2024-11-21 13:15:21.193151: +2024-11-21 13:15:21.193371: Epoch 460 +2024-11-21 13:15:21.193496: Current learning rate: 0.00948 +2024-11-21 13:15:40.359617: train_loss -0.7482 +2024-11-21 13:15:40.362402: val_loss -0.7539 +2024-11-21 13:15:40.362514: Pseudo dice [0.832] +2024-11-21 13:15:40.362614: Epoch time: 19.17 s +2024-11-21 13:15:41.149469: +2024-11-21 13:15:41.149704: Epoch 461 +2024-11-21 13:15:41.149827: Current learning rate: 0.00948 +2024-11-21 13:16:01.205656: train_loss -0.7486 +2024-11-21 13:16:01.219456: val_loss -0.7607 +2024-11-21 13:16:01.219600: Pseudo dice [0.83] +2024-11-21 13:16:01.219702: Epoch time: 20.06 s +2024-11-21 13:16:01.999253: +2024-11-21 13:16:01.999485: Epoch 462 +2024-11-21 13:16:01.999603: Current learning rate: 0.00948 +2024-11-21 13:16:20.462771: train_loss -0.7572 +2024-11-21 13:16:20.478457: val_loss -0.7637 +2024-11-21 13:16:20.478595: Pseudo dice [0.8482] +2024-11-21 13:16:20.478684: Epoch time: 18.46 s +2024-11-21 13:16:21.444319: +2024-11-21 13:16:21.444534: Epoch 463 +2024-11-21 13:16:21.444648: Current learning rate: 0.00948 +2024-11-21 13:16:40.315733: train_loss -0.755 +2024-11-21 13:16:40.324172: val_loss -0.7666 +2024-11-21 13:16:40.324300: Pseudo dice [0.8385] +2024-11-21 13:16:40.324404: Epoch time: 18.87 s +2024-11-21 13:16:41.258111: +2024-11-21 13:16:41.258321: Epoch 464 +2024-11-21 13:16:41.258445: Current learning rate: 0.00948 +2024-11-21 13:17:00.125632: train_loss -0.7622 +2024-11-21 13:17:00.131349: val_loss -0.7542 +2024-11-21 13:17:00.131483: Pseudo dice [0.8431] +2024-11-21 13:17:00.131571: Epoch time: 18.87 s +2024-11-21 13:17:00.937121: +2024-11-21 13:17:00.937347: Epoch 465 +2024-11-21 13:17:00.937457: Current learning rate: 0.00948 +2024-11-21 13:17:19.684940: train_loss -0.7636 +2024-11-21 13:17:19.691321: val_loss -0.7551 +2024-11-21 13:17:19.691468: Pseudo dice [0.8515] +2024-11-21 13:17:19.691556: Epoch time: 18.75 s +2024-11-21 13:17:20.699340: +2024-11-21 13:17:20.699542: Epoch 466 +2024-11-21 13:17:20.699657: Current learning rate: 0.00947 +2024-11-21 13:17:40.277929: train_loss -0.7545 +2024-11-21 13:17:40.280651: val_loss -0.7477 +2024-11-21 13:17:40.280768: Pseudo dice [0.8415] +2024-11-21 13:17:40.280877: Epoch time: 19.58 s +2024-11-21 13:17:41.068694: +2024-11-21 13:17:41.068916: Epoch 467 +2024-11-21 13:17:41.069039: Current learning rate: 0.00947 +2024-11-21 13:18:00.501438: train_loss -0.748 +2024-11-21 13:18:00.510056: val_loss -0.7518 +2024-11-21 13:18:00.510224: Pseudo dice [0.8389] +2024-11-21 13:18:00.510331: Epoch time: 19.43 s +2024-11-21 13:18:01.425334: +2024-11-21 13:18:01.425580: Epoch 468 +2024-11-21 13:18:01.425720: Current learning rate: 0.00947 +2024-11-21 13:18:20.314613: train_loss -0.7464 +2024-11-21 13:18:20.335535: val_loss -0.7575 +2024-11-21 13:18:20.335684: Pseudo dice [0.8447] +2024-11-21 13:18:20.335788: Epoch time: 18.89 s +2024-11-21 13:18:21.244841: +2024-11-21 13:18:21.245051: Epoch 469 +2024-11-21 13:18:21.245186: Current learning rate: 0.00947 +2024-11-21 13:18:40.668995: train_loss -0.7509 +2024-11-21 13:18:40.675406: val_loss -0.7392 +2024-11-21 13:18:40.675525: Pseudo dice [0.8253] +2024-11-21 13:18:40.690110: Epoch time: 19.42 s +2024-11-21 13:18:41.579040: +2024-11-21 13:18:41.579294: Epoch 470 +2024-11-21 13:18:41.579418: Current learning rate: 0.00947 +2024-11-21 13:19:00.986788: train_loss -0.7563 +2024-11-21 13:19:00.993425: val_loss -0.7494 +2024-11-21 13:19:00.993628: Pseudo dice [0.8364] +2024-11-21 13:19:00.993720: Epoch time: 19.41 s +2024-11-21 13:19:01.786716: +2024-11-21 13:19:01.786915: Epoch 471 +2024-11-21 13:19:01.787034: Current learning rate: 0.00947 +2024-11-21 13:19:20.675010: train_loss -0.746 +2024-11-21 13:19:20.681207: val_loss -0.701 +2024-11-21 13:19:20.681334: Pseudo dice [0.8092] +2024-11-21 13:19:20.681427: Epoch time: 18.89 s +2024-11-21 13:19:21.918118: +2024-11-21 13:19:21.918339: Epoch 472 +2024-11-21 13:19:21.918461: Current learning rate: 0.00947 +2024-11-21 13:19:41.389522: train_loss -0.7253 +2024-11-21 13:19:41.404426: val_loss -0.7593 +2024-11-21 13:19:41.404579: Pseudo dice [0.8418] +2024-11-21 13:19:41.404665: Epoch time: 19.47 s +2024-11-21 13:19:42.322410: +2024-11-21 13:19:42.322642: Epoch 473 +2024-11-21 13:19:42.322775: Current learning rate: 0.00947 +2024-11-21 13:20:01.048533: train_loss -0.7468 +2024-11-21 13:20:01.052166: val_loss -0.7519 +2024-11-21 13:20:01.052285: Pseudo dice [0.8462] +2024-11-21 13:20:01.052393: Epoch time: 18.73 s +2024-11-21 13:20:01.853258: +2024-11-21 13:20:01.853483: Epoch 474 +2024-11-21 13:20:01.853621: Current learning rate: 0.00947 +2024-11-21 13:20:21.452272: train_loss -0.7467 +2024-11-21 13:20:21.462731: val_loss -0.7575 +2024-11-21 13:20:21.462892: Pseudo dice [0.829] +2024-11-21 13:20:21.463001: Epoch time: 19.6 s +2024-11-21 13:20:22.497746: +2024-11-21 13:20:22.497972: Epoch 475 +2024-11-21 13:20:22.498108: Current learning rate: 0.00946 +2024-11-21 13:20:41.997388: train_loss -0.7356 +2024-11-21 13:20:42.000490: val_loss -0.7491 +2024-11-21 13:20:42.000593: Pseudo dice [0.8437] +2024-11-21 13:20:42.000696: Epoch time: 19.5 s +2024-11-21 13:20:42.792819: +2024-11-21 13:20:42.793038: Epoch 476 +2024-11-21 13:20:42.793171: Current learning rate: 0.00946 +2024-11-21 13:21:01.616500: train_loss -0.757 +2024-11-21 13:21:01.630963: val_loss -0.7441 +2024-11-21 13:21:01.631095: Pseudo dice [0.8244] +2024-11-21 13:21:01.631194: Epoch time: 18.82 s +2024-11-21 13:21:02.477552: +2024-11-21 13:21:02.477769: Epoch 477 +2024-11-21 13:21:02.477891: Current learning rate: 0.00946 +2024-11-21 13:21:22.270416: train_loss -0.7539 +2024-11-21 13:21:22.274702: val_loss -0.7649 +2024-11-21 13:21:22.274842: Pseudo dice [0.839] +2024-11-21 13:21:22.274940: Epoch time: 19.79 s +2024-11-21 13:21:23.337004: +2024-11-21 13:21:23.337245: Epoch 478 +2024-11-21 13:21:23.337367: Current learning rate: 0.00946 +2024-11-21 13:21:43.358154: train_loss -0.7555 +2024-11-21 13:21:43.360389: val_loss -0.7627 +2024-11-21 13:21:43.360532: Pseudo dice [0.8289] +2024-11-21 13:21:43.360622: Epoch time: 20.02 s +2024-11-21 13:21:44.177612: +2024-11-21 13:21:44.177834: Epoch 479 +2024-11-21 13:21:44.177968: Current learning rate: 0.00946 +2024-11-21 13:22:03.709556: train_loss -0.7544 +2024-11-21 13:22:03.718268: val_loss -0.732 +2024-11-21 13:22:03.718411: Pseudo dice [0.836] +2024-11-21 13:22:03.718520: Epoch time: 19.53 s +2024-11-21 13:22:04.508686: +2024-11-21 13:22:04.508896: Epoch 480 +2024-11-21 13:22:04.509028: Current learning rate: 0.00946 +2024-11-21 13:22:23.821110: train_loss -0.757 +2024-11-21 13:22:23.826833: val_loss -0.763 +2024-11-21 13:22:23.826958: Pseudo dice [0.8405] +2024-11-21 13:22:23.827050: Epoch time: 19.31 s +2024-11-21 13:22:24.738744: +2024-11-21 13:22:24.738952: Epoch 481 +2024-11-21 13:22:24.739077: Current learning rate: 0.00946 +2024-11-21 13:22:44.270301: train_loss -0.7469 +2024-11-21 13:22:44.275596: val_loss -0.7529 +2024-11-21 13:22:44.275723: Pseudo dice [0.8426] +2024-11-21 13:22:44.275814: Epoch time: 19.53 s +2024-11-21 13:22:45.112086: +2024-11-21 13:22:45.112281: Epoch 482 +2024-11-21 13:22:45.112411: Current learning rate: 0.00946 +2024-11-21 13:23:04.136754: train_loss -0.7423 +2024-11-21 13:23:04.172522: val_loss -0.7812 +2024-11-21 13:23:04.172683: Pseudo dice [0.8506] +2024-11-21 13:23:04.172792: Epoch time: 19.03 s +2024-11-21 13:23:05.215490: +2024-11-21 13:23:05.215701: Epoch 483 +2024-11-21 13:23:05.215840: Current learning rate: 0.00945 +2024-11-21 13:23:25.559533: train_loss -0.7347 +2024-11-21 13:23:25.561395: val_loss -0.7388 +2024-11-21 13:23:25.561520: Pseudo dice [0.8407] +2024-11-21 13:23:25.561601: Epoch time: 20.34 s +2024-11-21 13:23:26.887100: +2024-11-21 13:23:26.887334: Epoch 484 +2024-11-21 13:23:26.887475: Current learning rate: 0.00945 +2024-11-21 13:23:47.425318: train_loss -0.7488 +2024-11-21 13:23:47.430985: val_loss -0.7474 +2024-11-21 13:23:47.431140: Pseudo dice [0.8406] +2024-11-21 13:23:47.431234: Epoch time: 20.54 s +2024-11-21 13:23:48.350933: +2024-11-21 13:23:48.351252: Epoch 485 +2024-11-21 13:23:48.351383: Current learning rate: 0.00945 +2024-11-21 13:24:09.013892: train_loss -0.7545 +2024-11-21 13:24:09.022892: val_loss -0.7379 +2024-11-21 13:24:09.023045: Pseudo dice [0.846] +2024-11-21 13:24:09.023149: Epoch time: 20.66 s +2024-11-21 13:24:09.950808: +2024-11-21 13:24:09.951072: Epoch 486 +2024-11-21 13:24:09.951254: Current learning rate: 0.00945 +2024-11-21 13:24:29.385415: train_loss -0.7405 +2024-11-21 13:24:29.394479: val_loss -0.7561 +2024-11-21 13:24:29.394608: Pseudo dice [0.846] +2024-11-21 13:24:29.394701: Epoch time: 19.44 s +2024-11-21 13:24:30.189931: +2024-11-21 13:24:30.190172: Epoch 487 +2024-11-21 13:24:30.190320: Current learning rate: 0.00945 +2024-11-21 13:24:49.326216: train_loss -0.7472 +2024-11-21 13:24:49.333378: val_loss -0.7546 +2024-11-21 13:24:49.333519: Pseudo dice [0.8354] +2024-11-21 13:24:49.333626: Epoch time: 19.14 s +2024-11-21 13:24:50.152809: +2024-11-21 13:24:50.153026: Epoch 488 +2024-11-21 13:24:50.153151: Current learning rate: 0.00945 +2024-11-21 13:25:10.447368: train_loss -0.7435 +2024-11-21 13:25:10.450569: val_loss -0.7358 +2024-11-21 13:25:10.450707: Pseudo dice [0.8287] +2024-11-21 13:25:10.450794: Epoch time: 20.3 s +2024-11-21 13:25:11.437832: +2024-11-21 13:25:11.438077: Epoch 489 +2024-11-21 13:25:11.438191: Current learning rate: 0.00945 +2024-11-21 13:25:30.692785: train_loss -0.7421 +2024-11-21 13:25:30.700243: val_loss -0.7072 +2024-11-21 13:25:30.700380: Pseudo dice [0.8328] +2024-11-21 13:25:30.700472: Epoch time: 19.26 s +2024-11-21 13:25:31.577135: +2024-11-21 13:25:31.577336: Epoch 490 +2024-11-21 13:25:31.577472: Current learning rate: 0.00945 +2024-11-21 13:25:50.579492: train_loss -0.7505 +2024-11-21 13:25:50.581634: val_loss -0.7566 +2024-11-21 13:25:50.581732: Pseudo dice [0.8382] +2024-11-21 13:25:50.581820: Epoch time: 19.0 s +2024-11-21 13:25:51.375829: +2024-11-21 13:25:51.376035: Epoch 491 +2024-11-21 13:25:51.376154: Current learning rate: 0.00945 +2024-11-21 13:26:09.350924: train_loss -0.7445 +2024-11-21 13:26:09.357972: val_loss -0.7465 +2024-11-21 13:26:09.358121: Pseudo dice [0.8383] +2024-11-21 13:26:09.358222: Epoch time: 17.98 s +2024-11-21 13:26:10.151410: +2024-11-21 13:26:10.151627: Epoch 492 +2024-11-21 13:26:10.151742: Current learning rate: 0.00944 +2024-11-21 13:26:28.537986: train_loss -0.7499 +2024-11-21 13:26:28.540107: val_loss -0.7732 +2024-11-21 13:26:28.540240: Pseudo dice [0.8545] +2024-11-21 13:26:28.540331: Epoch time: 18.39 s +2024-11-21 13:26:29.340123: +2024-11-21 13:26:29.340354: Epoch 493 +2024-11-21 13:26:29.340472: Current learning rate: 0.00944 +2024-11-21 13:26:47.758487: train_loss -0.7476 +2024-11-21 13:26:47.765502: val_loss -0.7424 +2024-11-21 13:26:47.765641: Pseudo dice [0.8459] +2024-11-21 13:26:47.765743: Epoch time: 18.42 s +2024-11-21 13:26:48.709409: +2024-11-21 13:26:48.709652: Epoch 494 +2024-11-21 13:26:48.709784: Current learning rate: 0.00944 +2024-11-21 13:27:08.246840: train_loss -0.7523 +2024-11-21 13:27:08.256018: val_loss -0.7547 +2024-11-21 13:27:08.256204: Pseudo dice [0.8438] +2024-11-21 13:27:08.256303: Epoch time: 19.54 s +2024-11-21 13:27:09.166451: +2024-11-21 13:27:09.166652: Epoch 495 +2024-11-21 13:27:09.166792: Current learning rate: 0.00944 +2024-11-21 13:27:28.056450: train_loss -0.7582 +2024-11-21 13:27:28.063950: val_loss -0.7594 +2024-11-21 13:27:28.064090: Pseudo dice [0.8458] +2024-11-21 13:27:28.064181: Epoch time: 18.89 s +2024-11-21 13:27:29.440617: +2024-11-21 13:27:29.440846: Epoch 496 +2024-11-21 13:27:29.440963: Current learning rate: 0.00944 +2024-11-21 13:27:49.826650: train_loss -0.7536 +2024-11-21 13:27:49.830019: val_loss -0.7497 +2024-11-21 13:27:49.830142: Pseudo dice [0.8369] +2024-11-21 13:27:49.830243: Epoch time: 20.39 s +2024-11-21 13:27:50.632907: +2024-11-21 13:27:50.633156: Epoch 497 +2024-11-21 13:27:50.633273: Current learning rate: 0.00944 +2024-11-21 13:28:10.177292: train_loss -0.7479 +2024-11-21 13:28:10.179876: val_loss -0.7605 +2024-11-21 13:28:10.180001: Pseudo dice [0.8409] +2024-11-21 13:28:10.180104: Epoch time: 19.55 s +2024-11-21 13:28:11.075912: +2024-11-21 13:28:11.076138: Epoch 498 +2024-11-21 13:28:11.076266: Current learning rate: 0.00944 +2024-11-21 13:28:31.018384: train_loss -0.7555 +2024-11-21 13:28:31.023617: val_loss -0.7588 +2024-11-21 13:28:31.023773: Pseudo dice [0.8423] +2024-11-21 13:28:31.023878: Epoch time: 19.94 s +2024-11-21 13:28:31.887803: +2024-11-21 13:28:31.888008: Epoch 499 +2024-11-21 13:28:31.888129: Current learning rate: 0.00944 +2024-11-21 13:28:51.080552: train_loss -0.7483 +2024-11-21 13:28:51.088420: val_loss -0.7653 +2024-11-21 13:28:51.088564: Pseudo dice [0.836] +2024-11-21 13:28:51.088653: Epoch time: 19.19 s +2024-11-21 13:28:52.157242: +2024-11-21 13:28:52.157484: Epoch 500 +2024-11-21 13:28:52.157617: Current learning rate: 0.00944 +2024-11-21 13:29:10.944541: train_loss -0.7474 +2024-11-21 13:29:10.950271: val_loss -0.7544 +2024-11-21 13:29:10.950408: Pseudo dice [0.8384] +2024-11-21 13:29:10.950650: Epoch time: 18.79 s +2024-11-21 13:29:11.751706: +2024-11-21 13:29:11.751927: Epoch 501 +2024-11-21 13:29:11.752048: Current learning rate: 0.00943 +2024-11-21 13:29:30.126130: train_loss -0.7536 +2024-11-21 13:29:30.131827: val_loss -0.7452 +2024-11-21 13:29:30.131952: Pseudo dice [0.8301] +2024-11-21 13:29:30.132049: Epoch time: 18.38 s +2024-11-21 13:29:30.967820: +2024-11-21 13:29:30.968036: Epoch 502 +2024-11-21 13:29:30.968158: Current learning rate: 0.00943 +2024-11-21 13:29:49.383637: train_loss -0.7453 +2024-11-21 13:29:49.391172: val_loss -0.7449 +2024-11-21 13:29:49.391310: Pseudo dice [0.8287] +2024-11-21 13:29:49.391398: Epoch time: 18.42 s +2024-11-21 13:29:50.339875: +2024-11-21 13:29:50.340092: Epoch 503 +2024-11-21 13:29:50.340210: Current learning rate: 0.00943 +2024-11-21 13:30:08.851395: train_loss -0.752 +2024-11-21 13:30:08.859042: val_loss -0.7426 +2024-11-21 13:30:08.859188: Pseudo dice [0.8348] +2024-11-21 13:30:08.859277: Epoch time: 18.51 s +2024-11-21 13:30:09.876961: +2024-11-21 13:30:09.877218: Epoch 504 +2024-11-21 13:30:09.877333: Current learning rate: 0.00943 +2024-11-21 13:30:30.496934: train_loss -0.7531 +2024-11-21 13:30:30.499362: val_loss -0.7406 +2024-11-21 13:30:30.499522: Pseudo dice [0.8361] +2024-11-21 13:30:30.499642: Epoch time: 20.62 s +2024-11-21 13:30:31.315648: +2024-11-21 13:30:31.315834: Epoch 505 +2024-11-21 13:30:31.315960: Current learning rate: 0.00943 +2024-11-21 13:30:49.862897: train_loss -0.7597 +2024-11-21 13:30:49.870360: val_loss -0.7317 +2024-11-21 13:30:49.870498: Pseudo dice [0.8332] +2024-11-21 13:30:49.870583: Epoch time: 18.55 s +2024-11-21 13:30:50.712318: +2024-11-21 13:30:50.712512: Epoch 506 +2024-11-21 13:30:50.712626: Current learning rate: 0.00943 +2024-11-21 13:31:08.825985: train_loss -0.7533 +2024-11-21 13:31:08.833145: val_loss -0.7238 +2024-11-21 13:31:08.833285: Pseudo dice [0.8341] +2024-11-21 13:31:08.833386: Epoch time: 18.11 s +2024-11-21 13:31:09.657887: +2024-11-21 13:31:09.658111: Epoch 507 +2024-11-21 13:31:09.658240: Current learning rate: 0.00943 +2024-11-21 13:31:29.083764: train_loss -0.745 +2024-11-21 13:31:29.088111: val_loss -0.7577 +2024-11-21 13:31:29.088229: Pseudo dice [0.8371] +2024-11-21 13:31:29.088340: Epoch time: 19.43 s +2024-11-21 13:31:29.908979: +2024-11-21 13:31:29.909217: Epoch 508 +2024-11-21 13:31:29.909330: Current learning rate: 0.00943 +2024-11-21 13:31:49.038070: train_loss -0.753 +2024-11-21 13:31:49.043137: val_loss -0.7641 +2024-11-21 13:31:49.043285: Pseudo dice [0.8325] +2024-11-21 13:31:49.043400: Epoch time: 19.13 s +2024-11-21 13:31:49.995619: +2024-11-21 13:31:49.995849: Epoch 509 +2024-11-21 13:31:49.995968: Current learning rate: 0.00943 +2024-11-21 13:32:08.407246: train_loss -0.7358 +2024-11-21 13:32:08.417336: val_loss -0.7745 +2024-11-21 13:32:08.417475: Pseudo dice [0.8415] +2024-11-21 13:32:08.417571: Epoch time: 18.41 s +2024-11-21 13:32:09.363516: +2024-11-21 13:32:09.363729: Epoch 510 +2024-11-21 13:32:09.363867: Current learning rate: 0.00942 +2024-11-21 13:32:29.674865: train_loss -0.7379 +2024-11-21 13:32:29.677289: val_loss -0.7301 +2024-11-21 13:32:29.677400: Pseudo dice [0.8349] +2024-11-21 13:32:29.677479: Epoch time: 20.31 s +2024-11-21 13:32:30.472255: +2024-11-21 13:32:30.472465: Epoch 511 +2024-11-21 13:32:30.472588: Current learning rate: 0.00942 +2024-11-21 13:32:49.448159: train_loss -0.7641 +2024-11-21 13:32:49.464466: val_loss -0.76 +2024-11-21 13:32:49.464632: Pseudo dice [0.8589] +2024-11-21 13:32:49.464730: Epoch time: 18.98 s +2024-11-21 13:32:50.353330: +2024-11-21 13:32:50.353541: Epoch 512 +2024-11-21 13:32:50.353665: Current learning rate: 0.00942 +2024-11-21 13:33:10.204751: train_loss -0.7391 +2024-11-21 13:33:10.212918: val_loss -0.7513 +2024-11-21 13:33:10.213083: Pseudo dice [0.8524] +2024-11-21 13:33:10.213236: Epoch time: 19.85 s +2024-11-21 13:33:11.017253: +2024-11-21 13:33:11.017491: Epoch 513 +2024-11-21 13:33:11.017628: Current learning rate: 0.00942 +2024-11-21 13:33:30.141083: train_loss -0.753 +2024-11-21 13:33:30.170276: val_loss -0.7348 +2024-11-21 13:33:30.170461: Pseudo dice [0.8279] +2024-11-21 13:33:30.170565: Epoch time: 19.12 s +2024-11-21 13:33:31.043206: +2024-11-21 13:33:31.043425: Epoch 514 +2024-11-21 13:33:31.043545: Current learning rate: 0.00942 +2024-11-21 13:33:50.194769: train_loss -0.7445 +2024-11-21 13:33:50.197823: val_loss -0.7365 +2024-11-21 13:33:50.197928: Pseudo dice [0.8278] +2024-11-21 13:33:50.198006: Epoch time: 19.15 s +2024-11-21 13:33:51.012897: +2024-11-21 13:33:51.013097: Epoch 515 +2024-11-21 13:33:51.013234: Current learning rate: 0.00942 +2024-11-21 13:34:09.511141: train_loss -0.749 +2024-11-21 13:34:09.518044: val_loss -0.7537 +2024-11-21 13:34:09.518190: Pseudo dice [0.8303] +2024-11-21 13:34:09.518309: Epoch time: 18.5 s +2024-11-21 13:34:10.315111: +2024-11-21 13:34:10.315307: Epoch 516 +2024-11-21 13:34:10.315428: Current learning rate: 0.00942 +2024-11-21 13:34:28.441186: train_loss -0.7543 +2024-11-21 13:34:28.447774: val_loss -0.763 +2024-11-21 13:34:28.447892: Pseudo dice [0.8524] +2024-11-21 13:34:28.448085: Epoch time: 18.13 s +2024-11-21 13:34:29.253313: +2024-11-21 13:34:29.253535: Epoch 517 +2024-11-21 13:34:29.253665: Current learning rate: 0.00942 +2024-11-21 13:34:48.582431: train_loss -0.7528 +2024-11-21 13:34:48.585277: val_loss -0.7722 +2024-11-21 13:34:48.585390: Pseudo dice [0.8416] +2024-11-21 13:34:48.585493: Epoch time: 19.33 s +2024-11-21 13:34:49.381744: +2024-11-21 13:34:49.381945: Epoch 518 +2024-11-21 13:34:49.382079: Current learning rate: 0.00942 +2024-11-21 13:35:08.725827: train_loss -0.7589 +2024-11-21 13:35:08.728611: val_loss -0.743 +2024-11-21 13:35:08.728753: Pseudo dice [0.8486] +2024-11-21 13:35:08.728843: Epoch time: 19.34 s +2024-11-21 13:35:09.918866: +2024-11-21 13:35:09.919095: Epoch 519 +2024-11-21 13:35:09.919207: Current learning rate: 0.00941 +2024-11-21 13:35:29.280433: train_loss -0.7528 +2024-11-21 13:35:29.286377: val_loss -0.7364 +2024-11-21 13:35:29.286524: Pseudo dice [0.8418] +2024-11-21 13:35:29.286636: Epoch time: 19.36 s +2024-11-21 13:35:30.100026: +2024-11-21 13:35:30.100224: Epoch 520 +2024-11-21 13:35:30.100350: Current learning rate: 0.00941 +2024-11-21 13:35:49.314680: train_loss -0.7505 +2024-11-21 13:35:49.317749: val_loss -0.7582 +2024-11-21 13:35:49.317855: Pseudo dice [0.8358] +2024-11-21 13:35:49.318174: Epoch time: 19.22 s +2024-11-21 13:35:50.114556: +2024-11-21 13:35:50.114761: Epoch 521 +2024-11-21 13:35:50.114896: Current learning rate: 0.00941 +2024-11-21 13:36:09.959540: train_loss -0.7631 +2024-11-21 13:36:09.967045: val_loss -0.7538 +2024-11-21 13:36:09.967160: Pseudo dice [0.8424] +2024-11-21 13:36:09.967312: Epoch time: 19.85 s +2024-11-21 13:36:10.770112: +2024-11-21 13:36:10.770338: Epoch 522 +2024-11-21 13:36:10.770466: Current learning rate: 0.00941 +2024-11-21 13:36:29.336131: train_loss -0.7532 +2024-11-21 13:36:29.341589: val_loss -0.7404 +2024-11-21 13:36:29.341717: Pseudo dice [0.8378] +2024-11-21 13:36:29.341795: Epoch time: 18.57 s +2024-11-21 13:36:30.215619: +2024-11-21 13:36:30.215820: Epoch 523 +2024-11-21 13:36:30.215937: Current learning rate: 0.00941 +2024-11-21 13:36:48.530107: train_loss -0.7578 +2024-11-21 13:36:48.536126: val_loss -0.736 +2024-11-21 13:36:48.536268: Pseudo dice [0.832] +2024-11-21 13:36:48.536359: Epoch time: 18.32 s +2024-11-21 13:36:49.463071: +2024-11-21 13:36:49.463263: Epoch 524 +2024-11-21 13:36:49.463384: Current learning rate: 0.00941 +2024-11-21 13:37:08.975934: train_loss -0.7465 +2024-11-21 13:37:08.994818: val_loss -0.736 +2024-11-21 13:37:08.994959: Pseudo dice [0.8297] +2024-11-21 13:37:08.995055: Epoch time: 19.51 s +2024-11-21 13:37:09.914703: +2024-11-21 13:37:09.914929: Epoch 525 +2024-11-21 13:37:09.915050: Current learning rate: 0.00941 +2024-11-21 13:37:28.250953: train_loss -0.7511 +2024-11-21 13:37:28.256133: val_loss -0.7514 +2024-11-21 13:37:28.256248: Pseudo dice [0.8204] +2024-11-21 13:37:28.256360: Epoch time: 18.34 s +2024-11-21 13:37:29.257196: +2024-11-21 13:37:29.257428: Epoch 526 +2024-11-21 13:37:29.257555: Current learning rate: 0.00941 +2024-11-21 13:37:48.759376: train_loss -0.739 +2024-11-21 13:37:48.773404: val_loss -0.7488 +2024-11-21 13:37:48.773533: Pseudo dice [0.8433] +2024-11-21 13:37:48.773624: Epoch time: 19.5 s +2024-11-21 13:37:49.642119: +2024-11-21 13:37:49.642331: Epoch 527 +2024-11-21 13:37:49.642462: Current learning rate: 0.00941 +2024-11-21 13:38:09.278538: train_loss -0.7503 +2024-11-21 13:38:09.295354: val_loss -0.7599 +2024-11-21 13:38:09.295516: Pseudo dice [0.8417] +2024-11-21 13:38:09.295616: Epoch time: 19.64 s +2024-11-21 13:38:10.116068: +2024-11-21 13:38:10.116278: Epoch 528 +2024-11-21 13:38:10.116403: Current learning rate: 0.0094 +2024-11-21 13:38:28.596762: train_loss -0.7463 +2024-11-21 13:38:28.600984: val_loss -0.7561 +2024-11-21 13:38:28.601142: Pseudo dice [0.8378] +2024-11-21 13:38:28.601224: Epoch time: 18.48 s +2024-11-21 13:38:29.409197: +2024-11-21 13:38:29.409414: Epoch 529 +2024-11-21 13:38:29.409551: Current learning rate: 0.0094 +2024-11-21 13:38:48.332806: train_loss -0.7441 +2024-11-21 13:38:48.339288: val_loss -0.7738 +2024-11-21 13:38:48.339429: Pseudo dice [0.8424] +2024-11-21 13:38:48.339548: Epoch time: 18.92 s +2024-11-21 13:38:49.148176: +2024-11-21 13:38:49.148364: Epoch 530 +2024-11-21 13:38:49.148497: Current learning rate: 0.0094 +2024-11-21 13:39:08.772991: train_loss -0.7601 +2024-11-21 13:39:08.775732: val_loss -0.7384 +2024-11-21 13:39:08.775858: Pseudo dice [0.8468] +2024-11-21 13:39:08.775959: Epoch time: 19.63 s +2024-11-21 13:39:09.576339: +2024-11-21 13:39:09.576583: Epoch 531 +2024-11-21 13:39:09.576728: Current learning rate: 0.0094 +2024-11-21 13:39:28.118700: train_loss -0.7554 +2024-11-21 13:39:28.125700: val_loss -0.7682 +2024-11-21 13:39:28.125856: Pseudo dice [0.8468] +2024-11-21 13:39:28.125960: Epoch time: 18.54 s +2024-11-21 13:39:28.964113: +2024-11-21 13:39:28.964337: Epoch 532 +2024-11-21 13:39:28.964455: Current learning rate: 0.0094 +2024-11-21 13:39:48.082917: train_loss -0.7577 +2024-11-21 13:39:48.101051: val_loss -0.7311 +2024-11-21 13:39:48.101196: Pseudo dice [0.84] +2024-11-21 13:39:48.101320: Epoch time: 19.12 s +2024-11-21 13:39:48.908051: +2024-11-21 13:39:48.908274: Epoch 533 +2024-11-21 13:39:48.908399: Current learning rate: 0.0094 +2024-11-21 13:40:07.584183: train_loss -0.7475 +2024-11-21 13:40:07.593051: val_loss -0.7428 +2024-11-21 13:40:07.593222: Pseudo dice [0.8201] +2024-11-21 13:40:07.593338: Epoch time: 18.68 s +2024-11-21 13:40:08.422698: +2024-11-21 13:40:08.422938: Epoch 534 +2024-11-21 13:40:08.423083: Current learning rate: 0.0094 +2024-11-21 13:40:27.514390: train_loss -0.7465 +2024-11-21 13:40:27.522815: val_loss -0.7544 +2024-11-21 13:40:27.522956: Pseudo dice [0.8373] +2024-11-21 13:40:27.523045: Epoch time: 19.09 s +2024-11-21 13:40:28.479532: +2024-11-21 13:40:28.479735: Epoch 535 +2024-11-21 13:40:28.479857: Current learning rate: 0.0094 +2024-11-21 13:40:47.787642: train_loss -0.7514 +2024-11-21 13:40:47.793973: val_loss -0.7412 +2024-11-21 13:40:47.794106: Pseudo dice [0.8312] +2024-11-21 13:40:47.794197: Epoch time: 19.31 s +2024-11-21 13:40:48.679166: +2024-11-21 13:40:48.679388: Epoch 536 +2024-11-21 13:40:48.679520: Current learning rate: 0.00939 +2024-11-21 13:41:08.391592: train_loss -0.749 +2024-11-21 13:41:08.397127: val_loss -0.7296 +2024-11-21 13:41:08.397273: Pseudo dice [0.8318] +2024-11-21 13:41:08.398228: Epoch time: 19.71 s +2024-11-21 13:41:09.218499: +2024-11-21 13:41:09.218708: Epoch 537 +2024-11-21 13:41:09.218826: Current learning rate: 0.00939 +2024-11-21 13:41:28.284097: train_loss -0.7384 +2024-11-21 13:41:28.287186: val_loss -0.7747 +2024-11-21 13:41:28.287318: Pseudo dice [0.8403] +2024-11-21 13:41:28.287414: Epoch time: 19.07 s +2024-11-21 13:41:29.098249: +2024-11-21 13:41:29.098470: Epoch 538 +2024-11-21 13:41:29.098613: Current learning rate: 0.00939 +2024-11-21 13:41:48.264815: train_loss -0.7536 +2024-11-21 13:41:48.272161: val_loss -0.7425 +2024-11-21 13:41:48.272286: Pseudo dice [0.8374] +2024-11-21 13:41:48.272389: Epoch time: 19.17 s +2024-11-21 13:41:49.121764: +2024-11-21 13:41:49.121969: Epoch 539 +2024-11-21 13:41:49.122106: Current learning rate: 0.00939 +2024-11-21 13:42:08.266926: train_loss -0.7559 +2024-11-21 13:42:08.277174: val_loss -0.7674 +2024-11-21 13:42:08.277334: Pseudo dice [0.843] +2024-11-21 13:42:08.277455: Epoch time: 19.15 s +2024-11-21 13:42:09.141125: +2024-11-21 13:42:09.141323: Epoch 540 +2024-11-21 13:42:09.141432: Current learning rate: 0.00939 +2024-11-21 13:42:27.848469: train_loss -0.7546 +2024-11-21 13:42:27.855012: val_loss -0.7377 +2024-11-21 13:42:27.855154: Pseudo dice [0.8224] +2024-11-21 13:42:27.855249: Epoch time: 18.71 s +2024-11-21 13:42:28.641717: +2024-11-21 13:42:28.641947: Epoch 541 +2024-11-21 13:42:28.642076: Current learning rate: 0.00939 +2024-11-21 13:42:47.514532: train_loss -0.7292 +2024-11-21 13:42:47.517479: val_loss -0.7608 +2024-11-21 13:42:47.517617: Pseudo dice [0.8463] +2024-11-21 13:42:47.517724: Epoch time: 18.87 s +2024-11-21 13:42:48.630097: +2024-11-21 13:42:48.630326: Epoch 542 +2024-11-21 13:42:48.630467: Current learning rate: 0.00939 +2024-11-21 13:43:07.479215: train_loss -0.7446 +2024-11-21 13:43:07.490159: val_loss -0.7472 +2024-11-21 13:43:07.490310: Pseudo dice [0.8343] +2024-11-21 13:43:07.490395: Epoch time: 18.85 s +2024-11-21 13:43:08.541746: +2024-11-21 13:43:08.541970: Epoch 543 +2024-11-21 13:43:08.542094: Current learning rate: 0.00939 +2024-11-21 13:43:27.019385: train_loss -0.7415 +2024-11-21 13:43:27.031539: val_loss -0.7508 +2024-11-21 13:43:27.031662: Pseudo dice [0.8394] +2024-11-21 13:43:27.031752: Epoch time: 18.48 s +2024-11-21 13:43:27.968991: +2024-11-21 13:43:27.969207: Epoch 544 +2024-11-21 13:43:27.969342: Current learning rate: 0.00939 +2024-11-21 13:43:46.053802: train_loss -0.7499 +2024-11-21 13:43:46.061133: val_loss -0.7551 +2024-11-21 13:43:46.061287: Pseudo dice [0.8415] +2024-11-21 13:43:46.061392: Epoch time: 18.09 s +2024-11-21 13:43:46.869766: +2024-11-21 13:43:46.869974: Epoch 545 +2024-11-21 13:43:46.870091: Current learning rate: 0.00938 +2024-11-21 13:44:07.269400: train_loss -0.7407 +2024-11-21 13:44:07.273502: val_loss -0.7645 +2024-11-21 13:44:07.273616: Pseudo dice [0.8323] +2024-11-21 13:44:07.273705: Epoch time: 20.4 s +2024-11-21 13:44:08.069668: +2024-11-21 13:44:08.069906: Epoch 546 +2024-11-21 13:44:08.070755: Current learning rate: 0.00938 +2024-11-21 13:44:26.628855: train_loss -0.7455 +2024-11-21 13:44:26.634745: val_loss -0.7319 +2024-11-21 13:44:26.634889: Pseudo dice [0.836] +2024-11-21 13:44:26.634998: Epoch time: 18.56 s +2024-11-21 13:44:27.452647: +2024-11-21 13:44:27.452853: Epoch 547 +2024-11-21 13:44:27.452969: Current learning rate: 0.00938 +2024-11-21 13:44:46.700457: train_loss -0.746 +2024-11-21 13:44:46.705366: val_loss -0.7329 +2024-11-21 13:44:46.705489: Pseudo dice [0.8294] +2024-11-21 13:44:46.705596: Epoch time: 19.25 s +2024-11-21 13:44:47.515607: +2024-11-21 13:44:47.515824: Epoch 548 +2024-11-21 13:44:47.515937: Current learning rate: 0.00938 +2024-11-21 13:45:07.554208: train_loss -0.7411 +2024-11-21 13:45:07.561739: val_loss -0.7038 +2024-11-21 13:45:07.561893: Pseudo dice [0.8174] +2024-11-21 13:45:07.561989: Epoch time: 20.04 s +2024-11-21 13:45:08.459187: +2024-11-21 13:45:08.459408: Epoch 549 +2024-11-21 13:45:08.459546: Current learning rate: 0.00938 +2024-11-21 13:45:27.477814: train_loss -0.7353 +2024-11-21 13:45:27.485032: val_loss -0.7378 +2024-11-21 13:45:27.485173: Pseudo dice [0.8542] +2024-11-21 13:45:27.485268: Epoch time: 19.02 s +2024-11-21 13:45:28.794019: +2024-11-21 13:45:28.794247: Epoch 550 +2024-11-21 13:45:28.794387: Current learning rate: 0.00938 +2024-11-21 13:45:47.945185: train_loss -0.7482 +2024-11-21 13:45:47.952736: val_loss -0.7526 +2024-11-21 13:45:47.952868: Pseudo dice [0.8362] +2024-11-21 13:45:47.952961: Epoch time: 19.15 s +2024-11-21 13:45:48.838054: +2024-11-21 13:45:48.838264: Epoch 551 +2024-11-21 13:45:48.838394: Current learning rate: 0.00938 +2024-11-21 13:46:08.234417: train_loss -0.7594 +2024-11-21 13:46:08.237442: val_loss -0.7625 +2024-11-21 13:46:08.237560: Pseudo dice [0.843] +2024-11-21 13:46:08.237656: Epoch time: 19.4 s +2024-11-21 13:46:09.234848: +2024-11-21 13:46:09.235057: Epoch 552 +2024-11-21 13:46:09.235181: Current learning rate: 0.00938 +2024-11-21 13:46:28.142045: train_loss -0.7486 +2024-11-21 13:46:28.148808: val_loss -0.7694 +2024-11-21 13:46:28.148969: Pseudo dice [0.8466] +2024-11-21 13:46:28.149153: Epoch time: 18.91 s +2024-11-21 13:46:28.980440: +2024-11-21 13:46:28.980649: Epoch 553 +2024-11-21 13:46:28.980779: Current learning rate: 0.00938 +2024-11-21 13:46:47.697039: train_loss -0.7417 +2024-11-21 13:46:47.702503: val_loss -0.7333 +2024-11-21 13:46:47.702632: Pseudo dice [0.8268] +2024-11-21 13:46:47.702733: Epoch time: 18.72 s +2024-11-21 13:46:48.631875: +2024-11-21 13:46:48.632105: Epoch 554 +2024-11-21 13:46:48.632235: Current learning rate: 0.00937 +2024-11-21 13:47:07.462462: train_loss -0.7448 +2024-11-21 13:47:07.470700: val_loss -0.7368 +2024-11-21 13:47:07.470827: Pseudo dice [0.8221] +2024-11-21 13:47:07.470928: Epoch time: 18.83 s +2024-11-21 13:47:08.295345: +2024-11-21 13:47:08.295568: Epoch 555 +2024-11-21 13:47:08.295699: Current learning rate: 0.00937 +2024-11-21 13:47:27.727290: train_loss -0.7591 +2024-11-21 13:47:27.734572: val_loss -0.7588 +2024-11-21 13:47:27.734725: Pseudo dice [0.8371] +2024-11-21 13:47:27.734812: Epoch time: 19.43 s +2024-11-21 13:47:28.617509: +2024-11-21 13:47:28.617738: Epoch 556 +2024-11-21 13:47:28.617880: Current learning rate: 0.00937 +2024-11-21 13:47:49.552271: train_loss -0.7613 +2024-11-21 13:47:49.555249: val_loss -0.7597 +2024-11-21 13:47:49.555385: Pseudo dice [0.8417] +2024-11-21 13:47:49.555488: Epoch time: 20.94 s +2024-11-21 13:47:50.390049: +2024-11-21 13:47:50.390281: Epoch 557 +2024-11-21 13:47:50.390398: Current learning rate: 0.00937 +2024-11-21 13:48:09.215082: train_loss -0.7635 +2024-11-21 13:48:09.218955: val_loss -0.7855 +2024-11-21 13:48:09.219116: Pseudo dice [0.8539] +2024-11-21 13:48:09.219213: Epoch time: 18.83 s +2024-11-21 13:48:10.018557: +2024-11-21 13:48:10.018772: Epoch 558 +2024-11-21 13:48:10.018903: Current learning rate: 0.00937 +2024-11-21 13:48:29.469246: train_loss -0.7524 +2024-11-21 13:48:29.477001: val_loss -0.7399 +2024-11-21 13:48:29.477146: Pseudo dice [0.8277] +2024-11-21 13:48:29.477243: Epoch time: 19.45 s +2024-11-21 13:48:30.332454: +2024-11-21 13:48:30.332688: Epoch 559 +2024-11-21 13:48:30.332818: Current learning rate: 0.00937 +2024-11-21 13:48:49.398301: train_loss -0.757 +2024-11-21 13:48:49.400479: val_loss -0.747 +2024-11-21 13:48:49.400623: Pseudo dice [0.8359] +2024-11-21 13:48:49.400713: Epoch time: 19.07 s +2024-11-21 13:48:50.197324: +2024-11-21 13:48:50.197545: Epoch 560 +2024-11-21 13:48:50.197668: Current learning rate: 0.00937 +2024-11-21 13:49:09.538286: train_loss -0.745 +2024-11-21 13:49:09.545242: val_loss -0.762 +2024-11-21 13:49:09.545390: Pseudo dice [0.83] +2024-11-21 13:49:09.545480: Epoch time: 19.34 s +2024-11-21 13:49:10.385722: +2024-11-21 13:49:10.385923: Epoch 561 +2024-11-21 13:49:10.386070: Current learning rate: 0.00937 +2024-11-21 13:49:30.786669: train_loss -0.7417 +2024-11-21 13:49:30.792283: val_loss -0.7383 +2024-11-21 13:49:30.792418: Pseudo dice [0.8453] +2024-11-21 13:49:30.792514: Epoch time: 20.4 s +2024-11-21 13:49:31.624361: +2024-11-21 13:49:31.624564: Epoch 562 +2024-11-21 13:49:31.624709: Current learning rate: 0.00937 +2024-11-21 13:49:51.172272: train_loss -0.7419 +2024-11-21 13:49:51.180172: val_loss -0.7136 +2024-11-21 13:49:51.180323: Pseudo dice [0.8355] +2024-11-21 13:49:51.180435: Epoch time: 19.55 s +2024-11-21 13:49:52.071463: +2024-11-21 13:49:52.071693: Epoch 563 +2024-11-21 13:49:52.071816: Current learning rate: 0.00936 +2024-11-21 13:50:11.085679: train_loss -0.7521 +2024-11-21 13:50:11.093037: val_loss -0.7656 +2024-11-21 13:50:11.093174: Pseudo dice [0.8446] +2024-11-21 13:50:11.093279: Epoch time: 19.02 s +2024-11-21 13:50:11.900177: +2024-11-21 13:50:11.900372: Epoch 564 +2024-11-21 13:50:11.900511: Current learning rate: 0.00936 +2024-11-21 13:50:31.217046: train_loss -0.7517 +2024-11-21 13:50:31.230600: val_loss -0.7706 +2024-11-21 13:50:31.230730: Pseudo dice [0.8472] +2024-11-21 13:50:31.230825: Epoch time: 19.32 s +2024-11-21 13:50:32.715494: +2024-11-21 13:50:32.715727: Epoch 565 +2024-11-21 13:50:32.715852: Current learning rate: 0.00936 +2024-11-21 13:50:51.851133: train_loss -0.752 +2024-11-21 13:50:51.857890: val_loss -0.7544 +2024-11-21 13:50:51.858065: Pseudo dice [0.8358] +2024-11-21 13:50:51.858171: Epoch time: 19.14 s +2024-11-21 13:50:52.656233: +2024-11-21 13:50:52.656468: Epoch 566 +2024-11-21 13:50:52.656604: Current learning rate: 0.00936 +2024-11-21 13:51:11.456102: train_loss -0.7561 +2024-11-21 13:51:11.460490: val_loss -0.7397 +2024-11-21 13:51:11.460648: Pseudo dice [0.8479] +2024-11-21 13:51:11.460742: Epoch time: 18.8 s +2024-11-21 13:51:12.298006: +2024-11-21 13:51:12.298272: Epoch 567 +2024-11-21 13:51:12.298403: Current learning rate: 0.00936 +2024-11-21 13:51:31.511522: train_loss -0.7448 +2024-11-21 13:51:31.516476: val_loss -0.7502 +2024-11-21 13:51:31.516596: Pseudo dice [0.8399] +2024-11-21 13:51:31.516692: Epoch time: 19.21 s +2024-11-21 13:51:32.309824: +2024-11-21 13:51:32.310040: Epoch 568 +2024-11-21 13:51:32.310182: Current learning rate: 0.00936 +2024-11-21 13:51:51.879429: train_loss -0.742 +2024-11-21 13:51:51.886927: val_loss -0.7449 +2024-11-21 13:51:51.887073: Pseudo dice [0.8461] +2024-11-21 13:51:51.887178: Epoch time: 19.57 s +2024-11-21 13:51:52.702022: +2024-11-21 13:51:52.702265: Epoch 569 +2024-11-21 13:51:52.702424: Current learning rate: 0.00936 +2024-11-21 13:52:11.218464: train_loss -0.7594 +2024-11-21 13:52:11.225278: val_loss -0.7481 +2024-11-21 13:52:11.225415: Pseudo dice [0.8371] +2024-11-21 13:52:11.225515: Epoch time: 18.52 s +2024-11-21 13:52:12.227107: +2024-11-21 13:52:12.227326: Epoch 570 +2024-11-21 13:52:12.227474: Current learning rate: 0.00936 +2024-11-21 13:52:31.334458: train_loss -0.7619 +2024-11-21 13:52:31.347169: val_loss -0.7708 +2024-11-21 13:52:31.347322: Pseudo dice [0.8471] +2024-11-21 13:52:31.347415: Epoch time: 19.11 s +2024-11-21 13:52:32.454249: +2024-11-21 13:52:32.454456: Epoch 571 +2024-11-21 13:52:32.454575: Current learning rate: 0.00936 +2024-11-21 13:52:51.400755: train_loss -0.7662 +2024-11-21 13:52:51.406419: val_loss -0.7435 +2024-11-21 13:52:51.406572: Pseudo dice [0.8426] +2024-11-21 13:52:51.407115: Epoch time: 18.95 s +2024-11-21 13:52:52.283679: +2024-11-21 13:52:52.283899: Epoch 572 +2024-11-21 13:52:52.284034: Current learning rate: 0.00935 +2024-11-21 13:53:11.304808: train_loss -0.7652 +2024-11-21 13:53:11.312467: val_loss -0.7416 +2024-11-21 13:53:11.312618: Pseudo dice [0.8425] +2024-11-21 13:53:11.312710: Epoch time: 19.02 s +2024-11-21 13:53:12.161835: +2024-11-21 13:53:12.162049: Epoch 573 +2024-11-21 13:53:12.162195: Current learning rate: 0.00935 +2024-11-21 13:53:30.502401: train_loss -0.7552 +2024-11-21 13:53:30.510254: val_loss -0.7299 +2024-11-21 13:53:30.510414: Pseudo dice [0.8294] +2024-11-21 13:53:30.510531: Epoch time: 18.34 s +2024-11-21 13:53:31.465398: +2024-11-21 13:53:31.465609: Epoch 574 +2024-11-21 13:53:31.465719: Current learning rate: 0.00935 +2024-11-21 13:53:50.843790: train_loss -0.7589 +2024-11-21 13:53:50.846578: val_loss -0.7435 +2024-11-21 13:53:50.846691: Pseudo dice [0.8174] +2024-11-21 13:53:50.846789: Epoch time: 19.38 s +2024-11-21 13:53:51.651347: +2024-11-21 13:53:51.651544: Epoch 575 +2024-11-21 13:53:51.651663: Current learning rate: 0.00935 +2024-11-21 13:54:10.475589: train_loss -0.7692 +2024-11-21 13:54:10.478289: val_loss -0.7871 +2024-11-21 13:54:10.478399: Pseudo dice [0.8491] +2024-11-21 13:54:10.478479: Epoch time: 18.83 s +2024-11-21 13:54:11.276024: +2024-11-21 13:54:11.276331: Epoch 576 +2024-11-21 13:54:11.276456: Current learning rate: 0.00935 +2024-11-21 13:54:30.845005: train_loss -0.7555 +2024-11-21 13:54:30.867942: val_loss -0.7599 +2024-11-21 13:54:30.868110: Pseudo dice [0.8488] +2024-11-21 13:54:30.868247: Epoch time: 19.57 s +2024-11-21 13:54:31.813963: +2024-11-21 13:54:31.814181: Epoch 577 +2024-11-21 13:54:31.814307: Current learning rate: 0.00935 +2024-11-21 13:54:50.731130: train_loss -0.7549 +2024-11-21 13:54:50.738505: val_loss -0.7558 +2024-11-21 13:54:50.738639: Pseudo dice [0.8385] +2024-11-21 13:54:50.738726: Epoch time: 18.92 s +2024-11-21 13:54:51.592308: +2024-11-21 13:54:51.592536: Epoch 578 +2024-11-21 13:54:51.592657: Current learning rate: 0.00935 +2024-11-21 13:55:11.464723: train_loss -0.7441 +2024-11-21 13:55:11.467440: val_loss -0.7623 +2024-11-21 13:55:11.467613: Pseudo dice [0.8477] +2024-11-21 13:55:11.467717: Epoch time: 19.87 s +2024-11-21 13:55:12.268835: +2024-11-21 13:55:12.269071: Epoch 579 +2024-11-21 13:55:12.269199: Current learning rate: 0.00935 +2024-11-21 13:55:31.655641: train_loss -0.7635 +2024-11-21 13:55:31.658943: val_loss -0.7555 +2024-11-21 13:55:31.659054: Pseudo dice [0.8342] +2024-11-21 13:55:31.659171: Epoch time: 19.39 s +2024-11-21 13:55:32.474182: +2024-11-21 13:55:32.474417: Epoch 580 +2024-11-21 13:55:32.474530: Current learning rate: 0.00935 +2024-11-21 13:55:51.028156: train_loss -0.7466 +2024-11-21 13:55:51.034890: val_loss -0.7345 +2024-11-21 13:55:51.035125: Pseudo dice [0.8436] +2024-11-21 13:55:51.035232: Epoch time: 18.56 s +2024-11-21 13:55:51.950787: +2024-11-21 13:55:51.951008: Epoch 581 +2024-11-21 13:55:51.951148: Current learning rate: 0.00934 +2024-11-21 13:56:10.576679: train_loss -0.735 +2024-11-21 13:56:10.584473: val_loss -0.7313 +2024-11-21 13:56:10.584623: Pseudo dice [0.8336] +2024-11-21 13:56:10.584716: Epoch time: 18.63 s +2024-11-21 13:56:11.650643: +2024-11-21 13:56:11.650852: Epoch 582 +2024-11-21 13:56:11.650987: Current learning rate: 0.00934 +2024-11-21 13:56:30.705174: train_loss -0.7433 +2024-11-21 13:56:30.714123: val_loss -0.7458 +2024-11-21 13:56:30.714281: Pseudo dice [0.829] +2024-11-21 13:56:30.714374: Epoch time: 19.06 s +2024-11-21 13:56:31.625731: +2024-11-21 13:56:31.626040: Epoch 583 +2024-11-21 13:56:31.626177: Current learning rate: 0.00934 +2024-11-21 13:56:51.441966: train_loss -0.7498 +2024-11-21 13:56:51.444947: val_loss -0.7616 +2024-11-21 13:56:51.445067: Pseudo dice [0.8412] +2024-11-21 13:56:51.445156: Epoch time: 19.82 s +2024-11-21 13:56:52.252129: +2024-11-21 13:56:52.252836: Epoch 584 +2024-11-21 13:56:52.252950: Current learning rate: 0.00934 +2024-11-21 13:57:09.956157: train_loss -0.7612 +2024-11-21 13:57:09.981486: val_loss -0.7636 +2024-11-21 13:57:09.981660: Pseudo dice [0.849] +2024-11-21 13:57:09.981776: Epoch time: 17.7 s +2024-11-21 13:57:10.892710: +2024-11-21 13:57:10.892912: Epoch 585 +2024-11-21 13:57:10.893047: Current learning rate: 0.00934 +2024-11-21 13:57:29.906401: train_loss -0.7518 +2024-11-21 13:57:29.912096: val_loss -0.7179 +2024-11-21 13:57:29.912322: Pseudo dice [0.8357] +2024-11-21 13:57:29.912413: Epoch time: 19.01 s +2024-11-21 13:57:30.809934: +2024-11-21 13:57:30.810142: Epoch 586 +2024-11-21 13:57:30.810269: Current learning rate: 0.00934 +2024-11-21 13:57:50.073236: train_loss -0.7354 +2024-11-21 13:57:50.078601: val_loss -0.7543 +2024-11-21 13:57:50.078755: Pseudo dice [0.8296] +2024-11-21 13:57:50.078866: Epoch time: 19.26 s +2024-11-21 13:57:50.887987: +2024-11-21 13:57:50.888194: Epoch 587 +2024-11-21 13:57:50.888328: Current learning rate: 0.00934 +2024-11-21 13:58:09.669131: train_loss -0.7455 +2024-11-21 13:58:09.677091: val_loss -0.7471 +2024-11-21 13:58:09.677250: Pseudo dice [0.8445] +2024-11-21 13:58:09.677372: Epoch time: 18.78 s +2024-11-21 13:58:10.973756: +2024-11-21 13:58:10.974005: Epoch 588 +2024-11-21 13:58:10.974126: Current learning rate: 0.00934 +2024-11-21 13:58:29.770421: train_loss -0.7645 +2024-11-21 13:58:29.776111: val_loss -0.7549 +2024-11-21 13:58:29.776267: Pseudo dice [0.8477] +2024-11-21 13:58:29.776361: Epoch time: 18.8 s +2024-11-21 13:58:30.618494: +2024-11-21 13:58:30.618706: Epoch 589 +2024-11-21 13:58:30.618852: Current learning rate: 0.00933 +2024-11-21 13:58:49.805597: train_loss -0.7523 +2024-11-21 13:58:49.811304: val_loss -0.7625 +2024-11-21 13:58:49.811447: Pseudo dice [0.8186] +2024-11-21 13:58:49.811535: Epoch time: 19.19 s +2024-11-21 13:58:50.743172: +2024-11-21 13:58:50.743450: Epoch 590 +2024-11-21 13:58:50.743573: Current learning rate: 0.00933 +2024-11-21 13:59:10.413971: train_loss -0.7536 +2024-11-21 13:59:10.416914: val_loss -0.7196 +2024-11-21 13:59:10.417032: Pseudo dice [0.8318] +2024-11-21 13:59:10.417148: Epoch time: 19.67 s +2024-11-21 13:59:11.221931: +2024-11-21 13:59:11.222169: Epoch 591 +2024-11-21 13:59:11.222295: Current learning rate: 0.00933 +2024-11-21 13:59:31.220482: train_loss -0.7644 +2024-11-21 13:59:31.235560: val_loss -0.7698 +2024-11-21 13:59:31.235709: Pseudo dice [0.8559] +2024-11-21 13:59:31.235808: Epoch time: 20.0 s +2024-11-21 13:59:32.118394: +2024-11-21 13:59:32.118615: Epoch 592 +2024-11-21 13:59:32.118739: Current learning rate: 0.00933 +2024-11-21 13:59:52.519736: train_loss -0.7521 +2024-11-21 13:59:52.525511: val_loss -0.7625 +2024-11-21 13:59:52.525632: Pseudo dice [0.8393] +2024-11-21 13:59:52.525713: Epoch time: 20.4 s +2024-11-21 13:59:53.448519: +2024-11-21 13:59:53.448761: Epoch 593 +2024-11-21 13:59:53.448873: Current learning rate: 0.00933 +2024-11-21 14:00:12.341158: train_loss -0.7581 +2024-11-21 14:00:12.343756: val_loss -0.7571 +2024-11-21 14:00:12.343881: Pseudo dice [0.8352] +2024-11-21 14:00:12.343974: Epoch time: 18.89 s +2024-11-21 14:00:13.180287: +2024-11-21 14:00:13.180509: Epoch 594 +2024-11-21 14:00:13.180635: Current learning rate: 0.00933 +2024-11-21 14:00:31.589680: train_loss -0.7468 +2024-11-21 14:00:31.596418: val_loss -0.7462 +2024-11-21 14:00:31.596566: Pseudo dice [0.8331] +2024-11-21 14:00:31.596687: Epoch time: 18.41 s +2024-11-21 14:00:32.480445: +2024-11-21 14:00:32.480679: Epoch 595 +2024-11-21 14:00:32.480830: Current learning rate: 0.00933 +2024-11-21 14:00:52.896751: train_loss -0.7622 +2024-11-21 14:00:52.898349: val_loss -0.7638 +2024-11-21 14:00:52.898486: Pseudo dice [0.8388] +2024-11-21 14:00:52.898597: Epoch time: 20.42 s +2024-11-21 14:00:53.701525: +2024-11-21 14:00:53.701739: Epoch 596 +2024-11-21 14:00:53.701861: Current learning rate: 0.00933 +2024-11-21 14:01:13.363370: train_loss -0.747 +2024-11-21 14:01:13.365279: val_loss -0.765 +2024-11-21 14:01:13.365397: Pseudo dice [0.8444] +2024-11-21 14:01:13.365511: Epoch time: 19.66 s +2024-11-21 14:01:14.398609: +2024-11-21 14:01:14.398828: Epoch 597 +2024-11-21 14:01:14.399628: Current learning rate: 0.00933 +2024-11-21 14:01:33.229002: train_loss -0.755 +2024-11-21 14:01:33.234585: val_loss -0.7394 +2024-11-21 14:01:33.234723: Pseudo dice [0.8448] +2024-11-21 14:01:33.234823: Epoch time: 18.83 s +2024-11-21 14:01:34.079146: +2024-11-21 14:01:34.079336: Epoch 598 +2024-11-21 14:01:34.079459: Current learning rate: 0.00932 +2024-11-21 14:01:53.043770: train_loss -0.7545 +2024-11-21 14:01:53.048611: val_loss -0.7349 +2024-11-21 14:01:53.048747: Pseudo dice [0.8323] +2024-11-21 14:01:53.048840: Epoch time: 18.97 s +2024-11-21 14:01:53.925888: +2024-11-21 14:01:53.926130: Epoch 599 +2024-11-21 14:01:53.926264: Current learning rate: 0.00932 +2024-11-21 14:02:12.705781: train_loss -0.7556 +2024-11-21 14:02:12.708937: val_loss -0.7665 +2024-11-21 14:02:12.709087: Pseudo dice [0.8427] +2024-11-21 14:02:12.709175: Epoch time: 18.78 s +2024-11-21 14:02:13.778324: +2024-11-21 14:02:13.778548: Epoch 600 +2024-11-21 14:02:13.778690: Current learning rate: 0.00932 +2024-11-21 14:02:33.430854: train_loss -0.7481 +2024-11-21 14:02:33.432900: val_loss -0.734 +2024-11-21 14:02:33.432991: Pseudo dice [0.8416] +2024-11-21 14:02:33.433100: Epoch time: 19.65 s +2024-11-21 14:02:34.236486: +2024-11-21 14:02:34.236698: Epoch 601 +2024-11-21 14:02:34.236819: Current learning rate: 0.00932 +2024-11-21 14:02:53.200595: train_loss -0.7462 +2024-11-21 14:02:53.202398: val_loss -0.7448 +2024-11-21 14:02:53.202546: Pseudo dice [0.8407] +2024-11-21 14:02:53.202634: Epoch time: 18.96 s +2024-11-21 14:02:54.030527: +2024-11-21 14:02:54.030736: Epoch 602 +2024-11-21 14:02:54.030868: Current learning rate: 0.00932 +2024-11-21 14:03:13.844792: train_loss -0.7541 +2024-11-21 14:03:13.846970: val_loss -0.774 +2024-11-21 14:03:13.847085: Pseudo dice [0.8512] +2024-11-21 14:03:13.847183: Epoch time: 19.82 s +2024-11-21 14:03:14.653833: +2024-11-21 14:03:14.654045: Epoch 603 +2024-11-21 14:03:14.654186: Current learning rate: 0.00932 +2024-11-21 14:03:32.531660: train_loss -0.7579 +2024-11-21 14:03:32.538143: val_loss -0.7562 +2024-11-21 14:03:32.538310: Pseudo dice [0.8354] +2024-11-21 14:03:32.538423: Epoch time: 17.88 s +2024-11-21 14:03:33.351504: +2024-11-21 14:03:33.351700: Epoch 604 +2024-11-21 14:03:33.351849: Current learning rate: 0.00932 +2024-11-21 14:03:52.609653: train_loss -0.7612 +2024-11-21 14:03:52.615542: val_loss -0.7642 +2024-11-21 14:03:52.615671: Pseudo dice [0.8301] +2024-11-21 14:03:52.615778: Epoch time: 19.26 s +2024-11-21 14:03:53.435017: +2024-11-21 14:03:53.435236: Epoch 605 +2024-11-21 14:03:53.435357: Current learning rate: 0.00932 +2024-11-21 14:04:12.940795: train_loss -0.7515 +2024-11-21 14:04:12.944358: val_loss -0.7605 +2024-11-21 14:04:12.944472: Pseudo dice [0.8364] +2024-11-21 14:04:12.944573: Epoch time: 19.51 s +2024-11-21 14:04:13.753323: +2024-11-21 14:04:13.753529: Epoch 606 +2024-11-21 14:04:13.753643: Current learning rate: 0.00932 +2024-11-21 14:04:33.330127: train_loss -0.7487 +2024-11-21 14:04:33.337339: val_loss -0.7617 +2024-11-21 14:04:33.337492: Pseudo dice [0.8349] +2024-11-21 14:04:33.337599: Epoch time: 19.58 s +2024-11-21 14:04:34.258460: +2024-11-21 14:04:34.258668: Epoch 607 +2024-11-21 14:04:34.258836: Current learning rate: 0.00931 +2024-11-21 14:04:52.835666: train_loss -0.7463 +2024-11-21 14:04:52.842837: val_loss -0.7648 +2024-11-21 14:04:52.842958: Pseudo dice [0.843] +2024-11-21 14:04:52.843066: Epoch time: 18.58 s +2024-11-21 14:04:53.728463: +2024-11-21 14:04:53.728666: Epoch 608 +2024-11-21 14:04:53.728807: Current learning rate: 0.00931 +2024-11-21 14:05:13.140507: train_loss -0.7518 +2024-11-21 14:05:13.146194: val_loss -0.7479 +2024-11-21 14:05:13.146339: Pseudo dice [0.8397] +2024-11-21 14:05:13.146442: Epoch time: 19.41 s +2024-11-21 14:05:14.095953: +2024-11-21 14:05:14.096177: Epoch 609 +2024-11-21 14:05:14.096299: Current learning rate: 0.00931 +2024-11-21 14:05:33.242938: train_loss -0.7421 +2024-11-21 14:05:33.245041: val_loss -0.7338 +2024-11-21 14:05:33.245167: Pseudo dice [0.8203] +2024-11-21 14:05:33.245290: Epoch time: 19.15 s +2024-11-21 14:05:34.583196: +2024-11-21 14:05:34.583409: Epoch 610 +2024-11-21 14:05:34.583540: Current learning rate: 0.00931 +2024-11-21 14:05:53.794574: train_loss -0.7485 +2024-11-21 14:05:53.801152: val_loss -0.7438 +2024-11-21 14:05:53.801313: Pseudo dice [0.8354] +2024-11-21 14:05:53.801434: Epoch time: 19.21 s +2024-11-21 14:05:54.605263: +2024-11-21 14:05:54.605494: Epoch 611 +2024-11-21 14:05:54.605637: Current learning rate: 0.00931 +2024-11-21 14:06:13.039356: train_loss -0.7672 +2024-11-21 14:06:13.053157: val_loss -0.7542 +2024-11-21 14:06:13.053292: Pseudo dice [0.8293] +2024-11-21 14:06:13.053381: Epoch time: 18.43 s +2024-11-21 14:06:14.012844: +2024-11-21 14:06:14.013066: Epoch 612 +2024-11-21 14:06:14.013188: Current learning rate: 0.00931 +2024-11-21 14:06:33.846872: train_loss -0.7249 +2024-11-21 14:06:33.852716: val_loss -0.7423 +2024-11-21 14:06:33.852844: Pseudo dice [0.8211] +2024-11-21 14:06:33.852939: Epoch time: 19.83 s +2024-11-21 14:06:34.915157: +2024-11-21 14:06:34.915388: Epoch 613 +2024-11-21 14:06:34.915526: Current learning rate: 0.00931 +2024-11-21 14:06:53.536694: train_loss -0.7327 +2024-11-21 14:06:53.544068: val_loss -0.7364 +2024-11-21 14:06:53.544206: Pseudo dice [0.8184] +2024-11-21 14:06:53.544306: Epoch time: 18.62 s +2024-11-21 14:06:54.491664: +2024-11-21 14:06:54.491868: Epoch 614 +2024-11-21 14:06:54.491993: Current learning rate: 0.00931 +2024-11-21 14:07:13.168257: train_loss -0.7561 +2024-11-21 14:07:13.174361: val_loss -0.7176 +2024-11-21 14:07:13.174501: Pseudo dice [0.8451] +2024-11-21 14:07:13.174581: Epoch time: 18.68 s +2024-11-21 14:07:13.987185: +2024-11-21 14:07:13.987390: Epoch 615 +2024-11-21 14:07:13.987508: Current learning rate: 0.00931 +2024-11-21 14:07:32.223435: train_loss -0.7455 +2024-11-21 14:07:32.228668: val_loss -0.7449 +2024-11-21 14:07:32.228804: Pseudo dice [0.8356] +2024-11-21 14:07:32.228899: Epoch time: 18.24 s +2024-11-21 14:07:33.132364: +2024-11-21 14:07:33.132625: Epoch 616 +2024-11-21 14:07:33.132759: Current learning rate: 0.0093 +2024-11-21 14:07:51.195573: train_loss -0.7412 +2024-11-21 14:07:51.197794: val_loss -0.7429 +2024-11-21 14:07:51.198026: Pseudo dice [0.8344] +2024-11-21 14:07:51.198166: Epoch time: 18.06 s +2024-11-21 14:07:52.004850: +2024-11-21 14:07:52.005070: Epoch 617 +2024-11-21 14:07:52.005195: Current learning rate: 0.0093 +2024-11-21 14:08:10.742874: train_loss -0.7236 +2024-11-21 14:08:10.748307: val_loss -0.7172 +2024-11-21 14:08:10.748430: Pseudo dice [0.8351] +2024-11-21 14:08:10.748530: Epoch time: 18.74 s +2024-11-21 14:08:11.674416: +2024-11-21 14:08:11.674652: Epoch 618 +2024-11-21 14:08:11.674778: Current learning rate: 0.0093 +2024-11-21 14:08:30.940163: train_loss -0.7358 +2024-11-21 14:08:30.952638: val_loss -0.7498 +2024-11-21 14:08:30.952774: Pseudo dice [0.8317] +2024-11-21 14:08:30.952859: Epoch time: 19.27 s +2024-11-21 14:08:32.005811: +2024-11-21 14:08:32.006009: Epoch 619 +2024-11-21 14:08:32.006142: Current learning rate: 0.0093 +2024-11-21 14:08:51.587309: train_loss -0.7395 +2024-11-21 14:08:51.593462: val_loss -0.7514 +2024-11-21 14:08:51.593588: Pseudo dice [0.8402] +2024-11-21 14:08:51.593672: Epoch time: 19.58 s +2024-11-21 14:08:52.563766: +2024-11-21 14:08:52.563974: Epoch 620 +2024-11-21 14:08:52.564122: Current learning rate: 0.0093 +2024-11-21 14:09:12.228317: train_loss -0.7554 +2024-11-21 14:09:12.235452: val_loss -0.7576 +2024-11-21 14:09:12.235597: Pseudo dice [0.8443] +2024-11-21 14:09:12.235702: Epoch time: 19.67 s +2024-11-21 14:09:13.142002: +2024-11-21 14:09:13.142210: Epoch 621 +2024-11-21 14:09:13.142337: Current learning rate: 0.0093 +2024-11-21 14:09:32.606899: train_loss -0.7452 +2024-11-21 14:09:32.612761: val_loss -0.7139 +2024-11-21 14:09:32.612884: Pseudo dice [0.8164] +2024-11-21 14:09:32.612983: Epoch time: 19.47 s +2024-11-21 14:09:33.757430: +2024-11-21 14:09:33.757660: Epoch 622 +2024-11-21 14:09:33.757795: Current learning rate: 0.0093 +2024-11-21 14:09:53.930392: train_loss -0.7528 +2024-11-21 14:09:53.932361: val_loss -0.7673 +2024-11-21 14:09:53.944861: Pseudo dice [0.8511] +2024-11-21 14:09:53.944971: Epoch time: 20.17 s +2024-11-21 14:09:54.748255: +2024-11-21 14:09:54.748500: Epoch 623 +2024-11-21 14:09:54.748624: Current learning rate: 0.0093 +2024-11-21 14:10:14.177896: train_loss -0.7594 +2024-11-21 14:10:14.183546: val_loss -0.746 +2024-11-21 14:10:14.183677: Pseudo dice [0.8494] +2024-11-21 14:10:14.183837: Epoch time: 19.43 s +2024-11-21 14:10:15.008218: +2024-11-21 14:10:15.008434: Epoch 624 +2024-11-21 14:10:15.008554: Current learning rate: 0.0093 +2024-11-21 14:10:33.151483: train_loss -0.7353 +2024-11-21 14:10:33.159727: val_loss -0.7627 +2024-11-21 14:10:33.159860: Pseudo dice [0.8392] +2024-11-21 14:10:33.159977: Epoch time: 18.14 s +2024-11-21 14:10:34.060096: +2024-11-21 14:10:34.060328: Epoch 625 +2024-11-21 14:10:34.060438: Current learning rate: 0.00929 +2024-11-21 14:10:54.135607: train_loss -0.7516 +2024-11-21 14:10:54.143420: val_loss -0.7437 +2024-11-21 14:10:54.143562: Pseudo dice [0.8458] +2024-11-21 14:10:54.143686: Epoch time: 20.08 s +2024-11-21 14:10:54.986011: +2024-11-21 14:10:54.986205: Epoch 626 +2024-11-21 14:10:54.986346: Current learning rate: 0.00929 +2024-11-21 14:11:13.894529: train_loss -0.7498 +2024-11-21 14:11:13.911009: val_loss -0.7674 +2024-11-21 14:11:13.911160: Pseudo dice [0.8498] +2024-11-21 14:11:13.911267: Epoch time: 18.91 s +2024-11-21 14:11:14.996910: +2024-11-21 14:11:14.997153: Epoch 627 +2024-11-21 14:11:14.997297: Current learning rate: 0.00929 +2024-11-21 14:11:33.654416: train_loss -0.7562 +2024-11-21 14:11:33.662731: val_loss -0.7564 +2024-11-21 14:11:33.662861: Pseudo dice [0.8386] +2024-11-21 14:11:33.662967: Epoch time: 18.66 s +2024-11-21 14:11:34.491092: +2024-11-21 14:11:34.491292: Epoch 628 +2024-11-21 14:11:34.491405: Current learning rate: 0.00929 +2024-11-21 14:11:54.558187: train_loss -0.759 +2024-11-21 14:11:54.564335: val_loss -0.776 +2024-11-21 14:11:54.564489: Pseudo dice [0.8424] +2024-11-21 14:11:54.564628: Epoch time: 20.07 s +2024-11-21 14:11:55.415826: +2024-11-21 14:11:55.416075: Epoch 629 +2024-11-21 14:11:55.416206: Current learning rate: 0.00929 +2024-11-21 14:12:15.472786: train_loss -0.7553 +2024-11-21 14:12:15.477030: val_loss -0.762 +2024-11-21 14:12:15.477163: Pseudo dice [0.8403] +2024-11-21 14:12:15.477241: Epoch time: 20.06 s +2024-11-21 14:12:16.286863: +2024-11-21 14:12:16.287082: Epoch 630 +2024-11-21 14:12:16.287221: Current learning rate: 0.00929 +2024-11-21 14:12:35.920528: train_loss -0.7473 +2024-11-21 14:12:35.938152: val_loss -0.7653 +2024-11-21 14:12:35.938304: Pseudo dice [0.8323] +2024-11-21 14:12:35.938393: Epoch time: 19.63 s +2024-11-21 14:12:36.911570: +2024-11-21 14:12:36.911778: Epoch 631 +2024-11-21 14:12:36.911904: Current learning rate: 0.00929 +2024-11-21 14:12:55.337652: train_loss -0.7623 +2024-11-21 14:12:55.340775: val_loss -0.7682 +2024-11-21 14:12:55.340897: Pseudo dice [0.8489] +2024-11-21 14:12:55.341016: Epoch time: 18.43 s +2024-11-21 14:12:56.294415: +2024-11-21 14:12:56.294601: Epoch 632 +2024-11-21 14:12:56.294724: Current learning rate: 0.00929 +2024-11-21 14:13:15.385612: train_loss -0.7693 +2024-11-21 14:13:15.392066: val_loss -0.7481 +2024-11-21 14:13:15.392214: Pseudo dice [0.8354] +2024-11-21 14:13:15.392318: Epoch time: 19.09 s +2024-11-21 14:13:16.213375: +2024-11-21 14:13:16.213626: Epoch 633 +2024-11-21 14:13:16.213744: Current learning rate: 0.00928 +2024-11-21 14:13:35.910377: train_loss -0.7613 +2024-11-21 14:13:35.919596: val_loss -0.7287 +2024-11-21 14:13:35.919735: Pseudo dice [0.8403] +2024-11-21 14:13:35.919824: Epoch time: 19.7 s +2024-11-21 14:13:36.956666: +2024-11-21 14:13:36.956897: Epoch 634 +2024-11-21 14:13:36.957029: Current learning rate: 0.00928 +2024-11-21 14:13:55.665105: train_loss -0.7546 +2024-11-21 14:13:55.667537: val_loss -0.7224 +2024-11-21 14:13:55.667659: Pseudo dice [0.8405] +2024-11-21 14:13:55.667755: Epoch time: 18.71 s +2024-11-21 14:13:56.475951: +2024-11-21 14:13:56.476170: Epoch 635 +2024-11-21 14:13:56.476286: Current learning rate: 0.00928 +2024-11-21 14:14:15.762367: train_loss -0.7567 +2024-11-21 14:14:15.769762: val_loss -0.772 +2024-11-21 14:14:15.769915: Pseudo dice [0.8376] +2024-11-21 14:14:15.769998: Epoch time: 19.29 s +2024-11-21 14:14:16.625092: +2024-11-21 14:14:16.625306: Epoch 636 +2024-11-21 14:14:16.625434: Current learning rate: 0.00928 +2024-11-21 14:14:37.211495: train_loss -0.7623 +2024-11-21 14:14:37.221473: val_loss -0.7286 +2024-11-21 14:14:37.221618: Pseudo dice [0.8375] +2024-11-21 14:14:37.221721: Epoch time: 20.59 s +2024-11-21 14:14:38.079674: +2024-11-21 14:14:38.079908: Epoch 637 +2024-11-21 14:14:38.080051: Current learning rate: 0.00928 +2024-11-21 14:14:58.336629: train_loss -0.7523 +2024-11-21 14:14:58.353072: val_loss -0.7374 +2024-11-21 14:14:58.353219: Pseudo dice [0.845] +2024-11-21 14:14:58.353337: Epoch time: 20.26 s +2024-11-21 14:14:59.236563: +2024-11-21 14:14:59.236769: Epoch 638 +2024-11-21 14:14:59.236885: Current learning rate: 0.00928 +2024-11-21 14:15:19.400937: train_loss -0.7611 +2024-11-21 14:15:19.406657: val_loss -0.7621 +2024-11-21 14:15:19.406803: Pseudo dice [0.8438] +2024-11-21 14:15:19.406908: Epoch time: 20.17 s +2024-11-21 14:15:20.258040: +2024-11-21 14:15:20.258250: Epoch 639 +2024-11-21 14:15:20.258369: Current learning rate: 0.00928 +2024-11-21 14:15:39.748177: train_loss -0.7563 +2024-11-21 14:15:39.759439: val_loss -0.7522 +2024-11-21 14:15:39.759580: Pseudo dice [0.86] +2024-11-21 14:15:39.759678: Epoch time: 19.49 s +2024-11-21 14:15:39.759752: Yayy! New best EMA pseudo Dice: 0.8421 +2024-11-21 14:15:40.838455: +2024-11-21 14:15:40.838678: Epoch 640 +2024-11-21 14:15:40.838813: Current learning rate: 0.00928 +2024-11-21 14:15:59.639320: train_loss -0.7559 +2024-11-21 14:15:59.643949: val_loss -0.7494 +2024-11-21 14:15:59.644113: Pseudo dice [0.8476] +2024-11-21 14:15:59.644213: Epoch time: 18.8 s +2024-11-21 14:15:59.644296: Yayy! New best EMA pseudo Dice: 0.8427 +2024-11-21 14:16:00.674258: +2024-11-21 14:16:00.674475: Epoch 641 +2024-11-21 14:16:00.674598: Current learning rate: 0.00928 +2024-11-21 14:16:20.406010: train_loss -0.7614 +2024-11-21 14:16:20.408111: val_loss -0.7495 +2024-11-21 14:16:20.408232: Pseudo dice [0.837] +2024-11-21 14:16:20.408387: Epoch time: 19.73 s +2024-11-21 14:16:21.218696: +2024-11-21 14:16:21.218897: Epoch 642 +2024-11-21 14:16:21.219012: Current learning rate: 0.00927 +2024-11-21 14:16:40.412345: train_loss -0.7517 +2024-11-21 14:16:40.419508: val_loss -0.7592 +2024-11-21 14:16:40.419642: Pseudo dice [0.8501] +2024-11-21 14:16:40.419742: Epoch time: 19.19 s +2024-11-21 14:16:40.419845: Yayy! New best EMA pseudo Dice: 0.8429 +2024-11-21 14:16:41.556257: +2024-11-21 14:16:41.556478: Epoch 643 +2024-11-21 14:16:41.556602: Current learning rate: 0.00927 +2024-11-21 14:17:00.359073: train_loss -0.7569 +2024-11-21 14:17:00.364675: val_loss -0.7828 +2024-11-21 14:17:00.364804: Pseudo dice [0.8427] +2024-11-21 14:17:00.364893: Epoch time: 18.8 s +2024-11-21 14:17:01.608403: +2024-11-21 14:17:01.608629: Epoch 644 +2024-11-21 14:17:01.608769: Current learning rate: 0.00927 +2024-11-21 14:17:19.562845: train_loss -0.7578 +2024-11-21 14:17:19.567363: val_loss -0.7394 +2024-11-21 14:17:19.567484: Pseudo dice [0.8329] +2024-11-21 14:17:19.567702: Epoch time: 17.96 s +2024-11-21 14:17:20.378042: +2024-11-21 14:17:20.378291: Epoch 645 +2024-11-21 14:17:20.378416: Current learning rate: 0.00927 +2024-11-21 14:17:40.102580: train_loss -0.7429 +2024-11-21 14:17:40.113310: val_loss -0.7568 +2024-11-21 14:17:40.113447: Pseudo dice [0.8382] +2024-11-21 14:17:40.113538: Epoch time: 19.73 s +2024-11-21 14:17:40.935800: +2024-11-21 14:17:40.935994: Epoch 646 +2024-11-21 14:17:40.936107: Current learning rate: 0.00927 +2024-11-21 14:18:00.132932: train_loss -0.7459 +2024-11-21 14:18:00.138237: val_loss -0.7374 +2024-11-21 14:18:00.138366: Pseudo dice [0.8249] +2024-11-21 14:18:00.138466: Epoch time: 19.2 s +2024-11-21 14:18:01.054494: +2024-11-21 14:18:01.054716: Epoch 647 +2024-11-21 14:18:01.054855: Current learning rate: 0.00927 +2024-11-21 14:18:19.609756: train_loss -0.7566 +2024-11-21 14:18:19.615255: val_loss -0.7503 +2024-11-21 14:18:19.615406: Pseudo dice [0.855] +2024-11-21 14:18:19.615495: Epoch time: 18.56 s +2024-11-21 14:18:20.448549: +2024-11-21 14:18:20.448774: Epoch 648 +2024-11-21 14:18:20.448905: Current learning rate: 0.00927 +2024-11-21 14:18:38.191644: train_loss -0.7425 +2024-11-21 14:18:38.197197: val_loss -0.754 +2024-11-21 14:18:38.197328: Pseudo dice [0.8453] +2024-11-21 14:18:38.197437: Epoch time: 17.74 s +2024-11-21 14:18:39.063223: +2024-11-21 14:18:39.063431: Epoch 649 +2024-11-21 14:18:39.063549: Current learning rate: 0.00927 +2024-11-21 14:18:57.720241: train_loss -0.7515 +2024-11-21 14:18:57.728618: val_loss -0.7348 +2024-11-21 14:18:57.728782: Pseudo dice [0.8492] +2024-11-21 14:18:57.728882: Epoch time: 18.66 s +2024-11-21 14:18:58.864823: +2024-11-21 14:18:58.865022: Epoch 650 +2024-11-21 14:18:58.865140: Current learning rate: 0.00927 +2024-11-21 14:19:17.657368: train_loss -0.7451 +2024-11-21 14:19:17.664951: val_loss -0.7595 +2024-11-21 14:19:17.665087: Pseudo dice [0.829] +2024-11-21 14:19:17.665174: Epoch time: 18.79 s +2024-11-21 14:19:18.637985: +2024-11-21 14:19:18.638210: Epoch 651 +2024-11-21 14:19:18.638345: Current learning rate: 0.00926 +2024-11-21 14:19:37.586528: train_loss -0.747 +2024-11-21 14:19:37.588496: val_loss -0.766 +2024-11-21 14:19:37.588598: Pseudo dice [0.8404] +2024-11-21 14:19:37.588696: Epoch time: 18.95 s +2024-11-21 14:19:38.395839: +2024-11-21 14:19:38.396031: Epoch 652 +2024-11-21 14:19:38.396193: Current learning rate: 0.00926 +2024-11-21 14:19:55.963004: train_loss -0.7588 +2024-11-21 14:19:55.971310: val_loss -0.7669 +2024-11-21 14:19:55.971469: Pseudo dice [0.8509] +2024-11-21 14:19:55.971569: Epoch time: 17.56 s +2024-11-21 14:19:56.859546: +2024-11-21 14:19:56.859745: Epoch 653 +2024-11-21 14:19:56.859859: Current learning rate: 0.00926 +2024-11-21 14:20:16.706138: train_loss -0.7571 +2024-11-21 14:20:16.717892: val_loss -0.7387 +2024-11-21 14:20:16.718046: Pseudo dice [0.835] +2024-11-21 14:20:16.718148: Epoch time: 19.85 s +2024-11-21 14:20:17.595924: +2024-11-21 14:20:17.596136: Epoch 654 +2024-11-21 14:20:17.596254: Current learning rate: 0.00926 +2024-11-21 14:20:35.792157: train_loss -0.7533 +2024-11-21 14:20:35.794605: val_loss -0.7398 +2024-11-21 14:20:35.794767: Pseudo dice [0.8388] +2024-11-21 14:20:35.794852: Epoch time: 18.2 s +2024-11-21 14:20:36.713857: +2024-11-21 14:20:36.714055: Epoch 655 +2024-11-21 14:20:36.714182: Current learning rate: 0.00926 +2024-11-21 14:20:55.684080: train_loss -0.7565 +2024-11-21 14:20:55.707213: val_loss -0.745 +2024-11-21 14:20:55.707362: Pseudo dice [0.8452] +2024-11-21 14:20:55.707468: Epoch time: 18.97 s +2024-11-21 14:20:56.552756: +2024-11-21 14:20:56.553025: Epoch 656 +2024-11-21 14:20:56.553169: Current learning rate: 0.00926 +2024-11-21 14:21:13.946923: train_loss -0.748 +2024-11-21 14:21:13.959271: val_loss -0.7374 +2024-11-21 14:21:13.959434: Pseudo dice [0.8432] +2024-11-21 14:21:13.959529: Epoch time: 17.39 s +2024-11-21 14:21:14.775511: +2024-11-21 14:21:14.775725: Epoch 657 +2024-11-21 14:21:14.775835: Current learning rate: 0.00926 +2024-11-21 14:21:33.245888: train_loss -0.7481 +2024-11-21 14:21:33.247434: val_loss -0.7553 +2024-11-21 14:21:33.247534: Pseudo dice [0.8522] +2024-11-21 14:21:33.247624: Epoch time: 18.47 s +2024-11-21 14:21:34.037593: +2024-11-21 14:21:34.037808: Epoch 658 +2024-11-21 14:21:34.037942: Current learning rate: 0.00926 +2024-11-21 14:21:52.496254: train_loss -0.7489 +2024-11-21 14:21:52.503356: val_loss -0.733 +2024-11-21 14:21:52.504137: Pseudo dice [0.8242] +2024-11-21 14:21:52.504299: Epoch time: 18.46 s +2024-11-21 14:21:53.489468: +2024-11-21 14:21:53.489685: Epoch 659 +2024-11-21 14:21:53.489805: Current learning rate: 0.00926 +2024-11-21 14:22:12.366359: train_loss -0.7558 +2024-11-21 14:22:12.374676: val_loss -0.7349 +2024-11-21 14:22:12.374821: Pseudo dice [0.8384] +2024-11-21 14:22:12.374923: Epoch time: 18.88 s +2024-11-21 14:22:13.239707: +2024-11-21 14:22:13.239939: Epoch 660 +2024-11-21 14:22:13.240083: Current learning rate: 0.00925 +2024-11-21 14:22:32.365006: train_loss -0.7516 +2024-11-21 14:22:32.372332: val_loss -0.7635 +2024-11-21 14:22:32.372478: Pseudo dice [0.8466] +2024-11-21 14:22:32.372591: Epoch time: 19.13 s +2024-11-21 14:22:33.383893: +2024-11-21 14:22:33.384119: Epoch 661 +2024-11-21 14:22:33.384238: Current learning rate: 0.00925 +2024-11-21 14:22:51.283383: train_loss -0.7513 +2024-11-21 14:22:51.286447: val_loss -0.7731 +2024-11-21 14:22:51.286544: Pseudo dice [0.8424] +2024-11-21 14:22:51.286668: Epoch time: 17.9 s +2024-11-21 14:22:52.099142: +2024-11-21 14:22:52.099349: Epoch 662 +2024-11-21 14:22:52.099472: Current learning rate: 0.00925 +2024-11-21 14:23:11.159019: train_loss -0.7642 +2024-11-21 14:23:11.165189: val_loss -0.7667 +2024-11-21 14:23:11.165346: Pseudo dice [0.8487] +2024-11-21 14:23:11.165435: Epoch time: 19.06 s +2024-11-21 14:23:12.026385: +2024-11-21 14:23:12.026602: Epoch 663 +2024-11-21 14:23:12.026737: Current learning rate: 0.00925 +2024-11-21 14:23:31.367568: train_loss -0.7552 +2024-11-21 14:23:31.376303: val_loss -0.7639 +2024-11-21 14:23:31.376436: Pseudo dice [0.8604] +2024-11-21 14:23:31.376534: Epoch time: 19.34 s +2024-11-21 14:23:31.376606: Yayy! New best EMA pseudo Dice: 0.8439 +2024-11-21 14:23:32.536948: +2024-11-21 14:23:32.537155: Epoch 664 +2024-11-21 14:23:32.537292: Current learning rate: 0.00925 +2024-11-21 14:23:53.079972: train_loss -0.769 +2024-11-21 14:23:53.098021: val_loss -0.7585 +2024-11-21 14:23:53.098220: Pseudo dice [0.8355] +2024-11-21 14:23:53.098321: Epoch time: 20.54 s +2024-11-21 14:23:54.036208: +2024-11-21 14:23:54.036457: Epoch 665 +2024-11-21 14:23:54.036573: Current learning rate: 0.00925 +2024-11-21 14:24:14.148610: train_loss -0.7514 +2024-11-21 14:24:14.156112: val_loss -0.7638 +2024-11-21 14:24:14.156234: Pseudo dice [0.8411] +2024-11-21 14:24:14.156320: Epoch time: 20.11 s +2024-11-21 14:24:14.967865: +2024-11-21 14:24:14.968100: Epoch 666 +2024-11-21 14:24:14.968246: Current learning rate: 0.00925 +2024-11-21 14:24:34.189987: train_loss -0.7523 +2024-11-21 14:24:34.195141: val_loss -0.7506 +2024-11-21 14:24:34.195288: Pseudo dice [0.8204] +2024-11-21 14:24:34.195415: Epoch time: 19.22 s +2024-11-21 14:24:35.032435: +2024-11-21 14:24:35.032686: Epoch 667 +2024-11-21 14:24:35.032821: Current learning rate: 0.00925 +2024-11-21 14:24:53.395669: train_loss -0.7575 +2024-11-21 14:24:53.397499: val_loss -0.7554 +2024-11-21 14:24:53.397596: Pseudo dice [0.8269] +2024-11-21 14:24:53.397696: Epoch time: 18.36 s +2024-11-21 14:24:54.203047: +2024-11-21 14:24:54.203283: Epoch 668 +2024-11-21 14:24:54.203398: Current learning rate: 0.00925 +2024-11-21 14:25:12.883121: train_loss -0.7528 +2024-11-21 14:25:12.888945: val_loss -0.7388 +2024-11-21 14:25:12.889085: Pseudo dice [0.8414] +2024-11-21 14:25:12.889176: Epoch time: 18.68 s +2024-11-21 14:25:13.796029: +2024-11-21 14:25:13.796242: Epoch 669 +2024-11-21 14:25:13.796376: Current learning rate: 0.00924 +2024-11-21 14:25:33.325949: train_loss -0.7556 +2024-11-21 14:25:33.331851: val_loss -0.7758 +2024-11-21 14:25:33.331979: Pseudo dice [0.8506] +2024-11-21 14:25:33.332073: Epoch time: 19.53 s +2024-11-21 14:25:34.146529: +2024-11-21 14:25:34.146799: Epoch 670 +2024-11-21 14:25:34.146949: Current learning rate: 0.00924 +2024-11-21 14:25:54.300509: train_loss -0.7497 +2024-11-21 14:25:54.308101: val_loss -0.7536 +2024-11-21 14:25:54.308218: Pseudo dice [0.8285] +2024-11-21 14:25:54.308320: Epoch time: 20.15 s +2024-11-21 14:25:55.291618: +2024-11-21 14:25:55.291831: Epoch 671 +2024-11-21 14:25:55.291967: Current learning rate: 0.00924 +2024-11-21 14:26:14.612893: train_loss -0.743 +2024-11-21 14:26:14.625829: val_loss -0.7601 +2024-11-21 14:26:14.626010: Pseudo dice [0.8464] +2024-11-21 14:26:14.626127: Epoch time: 19.32 s +2024-11-21 14:26:15.469296: +2024-11-21 14:26:15.469494: Epoch 672 +2024-11-21 14:26:15.469617: Current learning rate: 0.00924 +2024-11-21 14:26:33.314139: train_loss -0.7448 +2024-11-21 14:26:33.321634: val_loss -0.7419 +2024-11-21 14:26:33.321798: Pseudo dice [0.8388] +2024-11-21 14:26:33.343308: Epoch time: 17.85 s +2024-11-21 14:26:34.172796: +2024-11-21 14:26:34.172989: Epoch 673 +2024-11-21 14:26:34.173117: Current learning rate: 0.00924 +2024-11-21 14:26:53.225812: train_loss -0.7499 +2024-11-21 14:26:53.237047: val_loss -0.7583 +2024-11-21 14:26:53.237214: Pseudo dice [0.8335] +2024-11-21 14:26:53.237325: Epoch time: 19.05 s +2024-11-21 14:26:54.058153: +2024-11-21 14:26:54.058353: Epoch 674 +2024-11-21 14:26:54.058470: Current learning rate: 0.00924 +2024-11-21 14:27:12.752271: train_loss -0.7588 +2024-11-21 14:27:12.754317: val_loss -0.7347 +2024-11-21 14:27:12.754459: Pseudo dice [0.8425] +2024-11-21 14:27:12.754566: Epoch time: 18.69 s +2024-11-21 14:27:13.569136: +2024-11-21 14:27:13.569366: Epoch 675 +2024-11-21 14:27:13.569489: Current learning rate: 0.00924 +2024-11-21 14:27:32.949086: train_loss -0.7514 +2024-11-21 14:27:32.954634: val_loss -0.7539 +2024-11-21 14:27:32.954765: Pseudo dice [0.8369] +2024-11-21 14:27:32.954866: Epoch time: 19.38 s +2024-11-21 14:27:33.784351: +2024-11-21 14:27:33.784548: Epoch 676 +2024-11-21 14:27:33.784663: Current learning rate: 0.00924 +2024-11-21 14:27:52.549442: train_loss -0.7526 +2024-11-21 14:27:52.558066: val_loss -0.7815 +2024-11-21 14:27:52.558231: Pseudo dice [0.845] +2024-11-21 14:27:52.558388: Epoch time: 18.77 s +2024-11-21 14:27:53.779498: +2024-11-21 14:27:53.779707: Epoch 677 +2024-11-21 14:27:53.779849: Current learning rate: 0.00924 +2024-11-21 14:28:13.273532: train_loss -0.7559 +2024-11-21 14:28:13.278702: val_loss -0.7568 +2024-11-21 14:28:13.278854: Pseudo dice [0.8228] +2024-11-21 14:28:13.278961: Epoch time: 19.49 s +2024-11-21 14:28:14.192446: +2024-11-21 14:28:14.192735: Epoch 678 +2024-11-21 14:28:14.192877: Current learning rate: 0.00923 +2024-11-21 14:28:32.699593: train_loss -0.7734 +2024-11-21 14:28:32.707109: val_loss -0.7645 +2024-11-21 14:28:32.707220: Pseudo dice [0.8433] +2024-11-21 14:28:32.707312: Epoch time: 18.51 s +2024-11-21 14:28:33.526488: +2024-11-21 14:28:33.526724: Epoch 679 +2024-11-21 14:28:33.526848: Current learning rate: 0.00923 +2024-11-21 14:28:53.830337: train_loss -0.7647 +2024-11-21 14:28:53.837181: val_loss -0.7567 +2024-11-21 14:28:53.837324: Pseudo dice [0.8477] +2024-11-21 14:28:53.837431: Epoch time: 20.3 s +2024-11-21 14:28:54.772989: +2024-11-21 14:28:54.773204: Epoch 680 +2024-11-21 14:28:54.773318: Current learning rate: 0.00923 +2024-11-21 14:29:13.203377: train_loss -0.7559 +2024-11-21 14:29:13.208899: val_loss -0.7687 +2024-11-21 14:29:13.209031: Pseudo dice [0.8386] +2024-11-21 14:29:13.209147: Epoch time: 18.43 s +2024-11-21 14:29:14.099633: +2024-11-21 14:29:14.099847: Epoch 681 +2024-11-21 14:29:14.099970: Current learning rate: 0.00923 +2024-11-21 14:29:33.579902: train_loss -0.7654 +2024-11-21 14:29:33.585769: val_loss -0.775 +2024-11-21 14:29:33.585913: Pseudo dice [0.8489] +2024-11-21 14:29:33.586021: Epoch time: 19.48 s +2024-11-21 14:29:34.410051: +2024-11-21 14:29:34.410273: Epoch 682 +2024-11-21 14:29:34.410387: Current learning rate: 0.00923 +2024-11-21 14:29:52.735983: train_loss -0.7574 +2024-11-21 14:29:52.738949: val_loss -0.7278 +2024-11-21 14:29:52.739121: Pseudo dice [0.8328] +2024-11-21 14:29:52.739223: Epoch time: 18.33 s +2024-11-21 14:29:53.708039: +2024-11-21 14:29:53.708264: Epoch 683 +2024-11-21 14:29:53.708393: Current learning rate: 0.00923 +2024-11-21 14:30:11.938177: train_loss -0.7562 +2024-11-21 14:30:11.947510: val_loss -0.7585 +2024-11-21 14:30:11.947629: Pseudo dice [0.841] +2024-11-21 14:30:11.947731: Epoch time: 18.23 s +2024-11-21 14:30:12.997496: +2024-11-21 14:30:12.997690: Epoch 684 +2024-11-21 14:30:12.997843: Current learning rate: 0.00923 +2024-11-21 14:30:31.626645: train_loss -0.7621 +2024-11-21 14:30:31.634353: val_loss -0.755 +2024-11-21 14:30:31.634498: Pseudo dice [0.8393] +2024-11-21 14:30:31.634587: Epoch time: 18.63 s +2024-11-21 14:30:32.524465: +2024-11-21 14:30:32.524763: Epoch 685 +2024-11-21 14:30:32.524899: Current learning rate: 0.00923 +2024-11-21 14:30:51.548641: train_loss -0.7327 +2024-11-21 14:30:51.562536: val_loss -0.7191 +2024-11-21 14:30:51.562643: Pseudo dice [0.8272] +2024-11-21 14:30:51.562737: Epoch time: 19.03 s +2024-11-21 14:30:52.375279: +2024-11-21 14:30:52.375483: Epoch 686 +2024-11-21 14:30:52.375606: Current learning rate: 0.00922 +2024-11-21 14:31:12.205269: train_loss -0.742 +2024-11-21 14:31:12.219140: val_loss -0.7565 +2024-11-21 14:31:12.219274: Pseudo dice [0.8409] +2024-11-21 14:31:12.219373: Epoch time: 19.83 s +2024-11-21 14:31:13.138392: +2024-11-21 14:31:13.138609: Epoch 687 +2024-11-21 14:31:13.138724: Current learning rate: 0.00922 +2024-11-21 14:31:31.837693: train_loss -0.7538 +2024-11-21 14:31:31.847465: val_loss -0.7509 +2024-11-21 14:31:31.847605: Pseudo dice [0.8272] +2024-11-21 14:31:31.847710: Epoch time: 18.7 s +2024-11-21 14:31:32.786207: +2024-11-21 14:31:32.786401: Epoch 688 +2024-11-21 14:31:32.786516: Current learning rate: 0.00922 +2024-11-21 14:31:52.604731: train_loss -0.7686 +2024-11-21 14:31:52.612481: val_loss -0.7456 +2024-11-21 14:31:52.612636: Pseudo dice [0.8551] +2024-11-21 14:31:52.612728: Epoch time: 19.82 s +2024-11-21 14:31:53.603225: +2024-11-21 14:31:53.603459: Epoch 689 +2024-11-21 14:31:53.603589: Current learning rate: 0.00922 +2024-11-21 14:32:12.241275: train_loss -0.7598 +2024-11-21 14:32:12.250163: val_loss -0.7682 +2024-11-21 14:32:12.250286: Pseudo dice [0.8533] +2024-11-21 14:32:12.250380: Epoch time: 18.64 s +2024-11-21 14:32:13.200497: +2024-11-21 14:32:13.200721: Epoch 690 +2024-11-21 14:32:13.200851: Current learning rate: 0.00922 +2024-11-21 14:32:32.771357: train_loss -0.7525 +2024-11-21 14:32:32.777308: val_loss -0.7515 +2024-11-21 14:32:32.777452: Pseudo dice [0.8566] +2024-11-21 14:32:32.777538: Epoch time: 19.57 s +2024-11-21 14:32:33.663546: +2024-11-21 14:32:33.663756: Epoch 691 +2024-11-21 14:32:33.663888: Current learning rate: 0.00922 +2024-11-21 14:32:52.244992: train_loss -0.7512 +2024-11-21 14:32:52.252621: val_loss -0.7611 +2024-11-21 14:32:52.252763: Pseudo dice [0.8301] +2024-11-21 14:32:52.252875: Epoch time: 18.58 s +2024-11-21 14:32:53.103606: +2024-11-21 14:32:53.103813: Epoch 692 +2024-11-21 14:32:53.103931: Current learning rate: 0.00922 +2024-11-21 14:33:12.013588: train_loss -0.7546 +2024-11-21 14:33:12.016989: val_loss -0.7477 +2024-11-21 14:33:12.017091: Pseudo dice [0.8432] +2024-11-21 14:33:12.017197: Epoch time: 18.91 s +2024-11-21 14:33:12.829946: +2024-11-21 14:33:12.830235: Epoch 693 +2024-11-21 14:33:12.830369: Current learning rate: 0.00922 +2024-11-21 14:33:30.934831: train_loss -0.7476 +2024-11-21 14:33:30.942342: val_loss -0.749 +2024-11-21 14:33:30.942493: Pseudo dice [0.8472] +2024-11-21 14:33:30.942600: Epoch time: 18.11 s +2024-11-21 14:33:31.972238: +2024-11-21 14:33:31.972438: Epoch 694 +2024-11-21 14:33:31.972553: Current learning rate: 0.00922 +2024-11-21 14:33:51.206568: train_loss -0.7566 +2024-11-21 14:33:51.213412: val_loss -0.7389 +2024-11-21 14:33:51.213601: Pseudo dice [0.8412] +2024-11-21 14:33:51.213688: Epoch time: 19.24 s +2024-11-21 14:33:52.092652: +2024-11-21 14:33:52.092873: Epoch 695 +2024-11-21 14:33:52.092995: Current learning rate: 0.00921 +2024-11-21 14:34:12.102221: train_loss -0.7515 +2024-11-21 14:34:12.107066: val_loss -0.7331 +2024-11-21 14:34:12.107218: Pseudo dice [0.832] +2024-11-21 14:34:12.107340: Epoch time: 20.01 s +2024-11-21 14:34:12.934796: +2024-11-21 14:34:12.935012: Epoch 696 +2024-11-21 14:34:12.935154: Current learning rate: 0.00921 +2024-11-21 14:34:31.312558: train_loss -0.7429 +2024-11-21 14:34:31.322866: val_loss -0.726 +2024-11-21 14:34:31.323005: Pseudo dice [0.8319] +2024-11-21 14:34:31.323147: Epoch time: 18.38 s +2024-11-21 14:34:32.298849: +2024-11-21 14:34:32.299072: Epoch 697 +2024-11-21 14:34:32.299194: Current learning rate: 0.00921 +2024-11-21 14:34:50.570636: train_loss -0.75 +2024-11-21 14:34:50.584855: val_loss -0.7493 +2024-11-21 14:34:50.585012: Pseudo dice [0.8415] +2024-11-21 14:34:50.585133: Epoch time: 18.27 s +2024-11-21 14:34:51.394844: +2024-11-21 14:34:51.395072: Epoch 698 +2024-11-21 14:34:51.395203: Current learning rate: 0.00921 +2024-11-21 14:35:08.655372: train_loss -0.7446 +2024-11-21 14:35:08.664224: val_loss -0.7417 +2024-11-21 14:35:08.664362: Pseudo dice [0.8446] +2024-11-21 14:35:08.664459: Epoch time: 17.26 s +2024-11-21 14:35:09.558969: +2024-11-21 14:35:09.559170: Epoch 699 +2024-11-21 14:35:09.559294: Current learning rate: 0.00921 +2024-11-21 14:35:28.678218: train_loss -0.7367 +2024-11-21 14:35:28.691236: val_loss -0.7505 +2024-11-21 14:35:28.691401: Pseudo dice [0.8401] +2024-11-21 14:35:28.691519: Epoch time: 19.12 s +2024-11-21 14:35:29.844866: +2024-11-21 14:35:29.845089: Epoch 700 +2024-11-21 14:35:29.845216: Current learning rate: 0.00921 +2024-11-21 14:35:49.386294: train_loss -0.7595 +2024-11-21 14:35:49.392721: val_loss -0.7558 +2024-11-21 14:35:49.392874: Pseudo dice [0.8437] +2024-11-21 14:35:49.392990: Epoch time: 19.54 s +2024-11-21 14:35:50.216509: +2024-11-21 14:35:50.216737: Epoch 701 +2024-11-21 14:35:50.216861: Current learning rate: 0.00921 +2024-11-21 14:36:07.902920: train_loss -0.7587 +2024-11-21 14:36:07.908229: val_loss -0.7577 +2024-11-21 14:36:07.908369: Pseudo dice [0.8427] +2024-11-21 14:36:07.908483: Epoch time: 17.69 s +2024-11-21 14:36:08.931524: +2024-11-21 14:36:08.931793: Epoch 702 +2024-11-21 14:36:08.931974: Current learning rate: 0.00921 +2024-11-21 14:36:27.761390: train_loss -0.7557 +2024-11-21 14:36:27.764422: val_loss -0.7596 +2024-11-21 14:36:27.764530: Pseudo dice [0.8369] +2024-11-21 14:36:27.764652: Epoch time: 18.83 s +2024-11-21 14:36:28.585312: +2024-11-21 14:36:28.585504: Epoch 703 +2024-11-21 14:36:28.585619: Current learning rate: 0.00921 +2024-11-21 14:36:48.131030: train_loss -0.7666 +2024-11-21 14:36:48.137686: val_loss -0.756 +2024-11-21 14:36:48.137834: Pseudo dice [0.8483] +2024-11-21 14:36:48.137955: Epoch time: 19.55 s +2024-11-21 14:36:49.022542: +2024-11-21 14:36:49.022777: Epoch 704 +2024-11-21 14:36:49.022927: Current learning rate: 0.0092 +2024-11-21 14:37:08.806424: train_loss -0.7559 +2024-11-21 14:37:08.813000: val_loss -0.7634 +2024-11-21 14:37:08.813127: Pseudo dice [0.8234] +2024-11-21 14:37:08.813211: Epoch time: 19.78 s +2024-11-21 14:37:09.682350: +2024-11-21 14:37:09.682567: Epoch 705 +2024-11-21 14:37:09.682699: Current learning rate: 0.0092 +2024-11-21 14:37:27.307231: train_loss -0.7649 +2024-11-21 14:37:27.313074: val_loss -0.7631 +2024-11-21 14:37:27.313228: Pseudo dice [0.8273] +2024-11-21 14:37:27.313334: Epoch time: 17.63 s +2024-11-21 14:37:28.135355: +2024-11-21 14:37:28.135541: Epoch 706 +2024-11-21 14:37:28.135670: Current learning rate: 0.0092 +2024-11-21 14:37:47.599222: train_loss -0.7465 +2024-11-21 14:37:47.608557: val_loss -0.7753 +2024-11-21 14:37:47.608680: Pseudo dice [0.8369] +2024-11-21 14:37:47.608785: Epoch time: 19.46 s +2024-11-21 14:37:48.547912: +2024-11-21 14:37:48.548121: Epoch 707 +2024-11-21 14:37:48.548241: Current learning rate: 0.0092 +2024-11-21 14:38:06.986555: train_loss -0.7451 +2024-11-21 14:38:06.993728: val_loss -0.7518 +2024-11-21 14:38:06.993866: Pseudo dice [0.8286] +2024-11-21 14:38:06.993949: Epoch time: 18.44 s +2024-11-21 14:38:07.875345: +2024-11-21 14:38:07.875586: Epoch 708 +2024-11-21 14:38:07.875716: Current learning rate: 0.0092 +2024-11-21 14:38:27.540004: train_loss -0.747 +2024-11-21 14:38:27.547834: val_loss -0.7567 +2024-11-21 14:38:27.548000: Pseudo dice [0.8382] +2024-11-21 14:38:27.548109: Epoch time: 19.67 s +2024-11-21 14:38:28.454074: +2024-11-21 14:38:28.454278: Epoch 709 +2024-11-21 14:38:28.454401: Current learning rate: 0.0092 +2024-11-21 14:38:48.225543: train_loss -0.7463 +2024-11-21 14:38:48.231796: val_loss -0.7375 +2024-11-21 14:38:48.231929: Pseudo dice [0.8298] +2024-11-21 14:38:48.232036: Epoch time: 19.77 s +2024-11-21 14:38:49.248137: +2024-11-21 14:38:49.248420: Epoch 710 +2024-11-21 14:38:49.248561: Current learning rate: 0.0092 +2024-11-21 14:39:07.970130: train_loss -0.7492 +2024-11-21 14:39:07.977275: val_loss -0.7517 +2024-11-21 14:39:07.977428: Pseudo dice [0.8415] +2024-11-21 14:39:07.977528: Epoch time: 18.72 s +2024-11-21 14:39:08.936963: +2024-11-21 14:39:08.937209: Epoch 711 +2024-11-21 14:39:08.937338: Current learning rate: 0.0092 +2024-11-21 14:39:28.835459: train_loss -0.7634 +2024-11-21 14:39:28.837922: val_loss -0.7532 +2024-11-21 14:39:28.838035: Pseudo dice [0.8338] +2024-11-21 14:39:28.838141: Epoch time: 19.9 s +2024-11-21 14:39:29.647253: +2024-11-21 14:39:29.647476: Epoch 712 +2024-11-21 14:39:29.647595: Current learning rate: 0.0092 +2024-11-21 14:39:49.602684: train_loss -0.7548 +2024-11-21 14:39:49.605383: val_loss -0.7439 +2024-11-21 14:39:49.605537: Pseudo dice [0.8567] +2024-11-21 14:39:49.605632: Epoch time: 19.96 s +2024-11-21 14:39:50.474088: +2024-11-21 14:39:50.474339: Epoch 713 +2024-11-21 14:39:50.474465: Current learning rate: 0.00919 +2024-11-21 14:40:09.700518: train_loss -0.7398 +2024-11-21 14:40:09.708704: val_loss -0.7537 +2024-11-21 14:40:09.708815: Pseudo dice [0.8361] +2024-11-21 14:40:09.708910: Epoch time: 19.23 s +2024-11-21 14:40:10.525024: +2024-11-21 14:40:10.525242: Epoch 714 +2024-11-21 14:40:10.525391: Current learning rate: 0.00919 +2024-11-21 14:40:29.432272: train_loss -0.7569 +2024-11-21 14:40:29.436355: val_loss -0.7574 +2024-11-21 14:40:29.436495: Pseudo dice [0.8523] +2024-11-21 14:40:29.436591: Epoch time: 18.91 s +2024-11-21 14:40:30.401505: +2024-11-21 14:40:30.401740: Epoch 715 +2024-11-21 14:40:30.401905: Current learning rate: 0.00919 +2024-11-21 14:40:49.229397: train_loss -0.767 +2024-11-21 14:40:49.235387: val_loss -0.7596 +2024-11-21 14:40:49.235521: Pseudo dice [0.848] +2024-11-21 14:40:49.235616: Epoch time: 18.83 s +2024-11-21 14:40:50.074451: +2024-11-21 14:40:50.074672: Epoch 716 +2024-11-21 14:40:50.074807: Current learning rate: 0.00919 +2024-11-21 14:41:08.697343: train_loss -0.7555 +2024-11-21 14:41:08.703657: val_loss -0.7668 +2024-11-21 14:41:08.703792: Pseudo dice [0.8397] +2024-11-21 14:41:08.703900: Epoch time: 18.62 s +2024-11-21 14:41:09.530768: +2024-11-21 14:41:09.530967: Epoch 717 +2024-11-21 14:41:09.531089: Current learning rate: 0.00919 +2024-11-21 14:41:28.576936: train_loss -0.7588 +2024-11-21 14:41:28.581299: val_loss -0.759 +2024-11-21 14:41:28.581448: Pseudo dice [0.8261] +2024-11-21 14:41:28.581556: Epoch time: 19.05 s +2024-11-21 14:41:29.447128: +2024-11-21 14:41:29.447348: Epoch 718 +2024-11-21 14:41:29.447471: Current learning rate: 0.00919 +2024-11-21 14:41:47.096234: train_loss -0.7591 +2024-11-21 14:41:47.110284: val_loss -0.7725 +2024-11-21 14:41:47.113021: Pseudo dice [0.8497] +2024-11-21 14:41:47.113181: Epoch time: 17.65 s +2024-11-21 14:41:47.941922: +2024-11-21 14:41:47.942153: Epoch 719 +2024-11-21 14:41:47.942292: Current learning rate: 0.00919 +2024-11-21 14:42:06.411094: train_loss -0.7629 +2024-11-21 14:42:06.429006: val_loss -0.7679 +2024-11-21 14:42:06.429196: Pseudo dice [0.8524] +2024-11-21 14:42:06.429296: Epoch time: 18.47 s +2024-11-21 14:42:07.239073: +2024-11-21 14:42:07.239278: Epoch 720 +2024-11-21 14:42:07.239408: Current learning rate: 0.00919 +2024-11-21 14:42:26.712560: train_loss -0.7628 +2024-11-21 14:42:26.716375: val_loss -0.7711 +2024-11-21 14:42:26.716544: Pseudo dice [0.8442] +2024-11-21 14:42:26.716642: Epoch time: 19.47 s +2024-11-21 14:42:27.894271: +2024-11-21 14:42:27.896521: Epoch 721 +2024-11-21 14:42:27.896660: Current learning rate: 0.00919 +2024-11-21 14:42:46.437831: train_loss -0.7466 +2024-11-21 14:42:46.442701: val_loss -0.7544 +2024-11-21 14:42:46.442841: Pseudo dice [0.8375] +2024-11-21 14:42:46.442951: Epoch time: 18.54 s +2024-11-21 14:42:47.269400: +2024-11-21 14:42:47.269651: Epoch 722 +2024-11-21 14:42:47.269770: Current learning rate: 0.00918 +2024-11-21 14:43:05.327142: train_loss -0.7527 +2024-11-21 14:43:05.335258: val_loss -0.7303 +2024-11-21 14:43:05.335413: Pseudo dice [0.8326] +2024-11-21 14:43:05.335528: Epoch time: 18.06 s +2024-11-21 14:43:06.485656: +2024-11-21 14:43:06.485911: Epoch 723 +2024-11-21 14:43:06.486044: Current learning rate: 0.00918 +2024-11-21 14:43:25.895539: train_loss -0.7482 +2024-11-21 14:43:25.903454: val_loss -0.7265 +2024-11-21 14:43:25.903582: Pseudo dice [0.8294] +2024-11-21 14:43:25.903907: Epoch time: 19.41 s +2024-11-21 14:43:26.860869: +2024-11-21 14:43:26.861085: Epoch 724 +2024-11-21 14:43:26.861202: Current learning rate: 0.00918 +2024-11-21 14:43:46.339576: train_loss -0.7614 +2024-11-21 14:43:46.346841: val_loss -0.7508 +2024-11-21 14:43:46.346960: Pseudo dice [0.8543] +2024-11-21 14:43:46.347053: Epoch time: 19.48 s +2024-11-21 14:43:47.267489: +2024-11-21 14:43:47.267725: Epoch 725 +2024-11-21 14:43:47.267856: Current learning rate: 0.00918 +2024-11-21 14:44:05.415402: train_loss -0.7664 +2024-11-21 14:44:05.421612: val_loss -0.7686 +2024-11-21 14:44:05.421741: Pseudo dice [0.8476] +2024-11-21 14:44:05.421821: Epoch time: 18.15 s +2024-11-21 14:44:06.257260: +2024-11-21 14:44:06.257540: Epoch 726 +2024-11-21 14:44:06.257706: Current learning rate: 0.00918 +2024-11-21 14:44:25.363861: train_loss -0.7574 +2024-11-21 14:44:25.370776: val_loss -0.7457 +2024-11-21 14:44:25.370920: Pseudo dice [0.8429] +2024-11-21 14:44:25.371025: Epoch time: 19.11 s +2024-11-21 14:44:26.224093: +2024-11-21 14:44:26.224325: Epoch 727 +2024-11-21 14:44:26.224442: Current learning rate: 0.00918 +2024-11-21 14:44:45.081407: train_loss -0.7595 +2024-11-21 14:44:45.090203: val_loss -0.7716 +2024-11-21 14:44:45.090344: Pseudo dice [0.8496] +2024-11-21 14:44:45.090429: Epoch time: 18.86 s +2024-11-21 14:44:45.927384: +2024-11-21 14:44:45.927583: Epoch 728 +2024-11-21 14:44:45.927714: Current learning rate: 0.00918 +2024-11-21 14:45:05.589934: train_loss -0.7575 +2024-11-21 14:45:05.604854: val_loss -0.7639 +2024-11-21 14:45:05.604991: Pseudo dice [0.8525] +2024-11-21 14:45:05.605089: Epoch time: 19.66 s +2024-11-21 14:45:06.537287: +2024-11-21 14:45:06.537483: Epoch 729 +2024-11-21 14:45:06.537618: Current learning rate: 0.00918 +2024-11-21 14:45:24.431335: train_loss -0.7673 +2024-11-21 14:45:24.448448: val_loss -0.7664 +2024-11-21 14:45:24.448604: Pseudo dice [0.8441] +2024-11-21 14:45:24.448694: Epoch time: 17.89 s +2024-11-21 14:45:25.351423: +2024-11-21 14:45:25.351630: Epoch 730 +2024-11-21 14:45:25.351756: Current learning rate: 0.00917 +2024-11-21 14:45:43.546569: train_loss -0.7593 +2024-11-21 14:45:43.548941: val_loss -0.7331 +2024-11-21 14:45:43.549038: Pseudo dice [0.8498] +2024-11-21 14:45:43.549134: Epoch time: 18.2 s +2024-11-21 14:45:43.549202: Yayy! New best EMA pseudo Dice: 0.8441 +2024-11-21 14:45:44.564718: +2024-11-21 14:45:44.564926: Epoch 731 +2024-11-21 14:45:44.565046: Current learning rate: 0.00917 +2024-11-21 14:46:04.423602: train_loss -0.7655 +2024-11-21 14:46:04.430098: val_loss -0.7451 +2024-11-21 14:46:04.430225: Pseudo dice [0.8441] +2024-11-21 14:46:04.430311: Epoch time: 19.86 s +2024-11-21 14:46:05.393481: +2024-11-21 14:46:05.393707: Epoch 732 +2024-11-21 14:46:05.393844: Current learning rate: 0.00917 +2024-11-21 14:46:24.059663: train_loss -0.7712 +2024-11-21 14:46:24.062588: val_loss -0.7527 +2024-11-21 14:46:24.062724: Pseudo dice [0.8557] +2024-11-21 14:46:24.062829: Epoch time: 18.67 s +2024-11-21 14:46:24.062896: Yayy! New best EMA pseudo Dice: 0.8453 +2024-11-21 14:46:25.074684: +2024-11-21 14:46:25.074934: Epoch 733 +2024-11-21 14:46:25.075054: Current learning rate: 0.00917 +2024-11-21 14:46:44.652305: train_loss -0.7578 +2024-11-21 14:46:44.659323: val_loss -0.7607 +2024-11-21 14:46:44.659465: Pseudo dice [0.837] +2024-11-21 14:46:44.659586: Epoch time: 19.58 s +2024-11-21 14:46:45.526329: +2024-11-21 14:46:45.526592: Epoch 734 +2024-11-21 14:46:45.526732: Current learning rate: 0.00917 +2024-11-21 14:47:04.899303: train_loss -0.7237 +2024-11-21 14:47:04.907262: val_loss -0.7193 +2024-11-21 14:47:04.907418: Pseudo dice [0.8188] +2024-11-21 14:47:04.907520: Epoch time: 19.37 s +2024-11-21 14:47:05.732000: +2024-11-21 14:47:05.732301: Epoch 735 +2024-11-21 14:47:05.732419: Current learning rate: 0.00917 +2024-11-21 14:47:25.003670: train_loss -0.7055 +2024-11-21 14:47:25.012118: val_loss -0.7438 +2024-11-21 14:47:25.012307: Pseudo dice [0.8415] +2024-11-21 14:47:25.012405: Epoch time: 19.27 s +2024-11-21 14:47:26.007479: +2024-11-21 14:47:26.008175: Epoch 736 +2024-11-21 14:47:26.008325: Current learning rate: 0.00917 +2024-11-21 14:47:45.611321: train_loss -0.7404 +2024-11-21 14:47:45.613893: val_loss -0.7429 +2024-11-21 14:47:45.614049: Pseudo dice [0.8407] +2024-11-21 14:47:45.614149: Epoch time: 19.6 s +2024-11-21 14:47:46.596385: +2024-11-21 14:47:46.596595: Epoch 737 +2024-11-21 14:47:46.596730: Current learning rate: 0.00917 +2024-11-21 14:48:06.036241: train_loss -0.7478 +2024-11-21 14:48:06.040618: val_loss -0.7776 +2024-11-21 14:48:06.040735: Pseudo dice [0.8375] +2024-11-21 14:48:06.040820: Epoch time: 19.44 s +2024-11-21 14:48:06.852486: +2024-11-21 14:48:06.852694: Epoch 738 +2024-11-21 14:48:06.852822: Current learning rate: 0.00917 +2024-11-21 14:48:26.174902: train_loss -0.7464 +2024-11-21 14:48:26.180103: val_loss -0.727 +2024-11-21 14:48:26.180309: Pseudo dice [0.8316] +2024-11-21 14:48:26.180417: Epoch time: 19.32 s +2024-11-21 14:48:27.037450: +2024-11-21 14:48:27.037719: Epoch 739 +2024-11-21 14:48:27.037842: Current learning rate: 0.00916 +2024-11-21 14:48:44.273875: train_loss -0.7577 +2024-11-21 14:48:44.280700: val_loss -0.7499 +2024-11-21 14:48:44.280846: Pseudo dice [0.8245] +2024-11-21 14:48:44.280935: Epoch time: 17.24 s +2024-11-21 14:48:45.303846: +2024-11-21 14:48:45.304066: Epoch 740 +2024-11-21 14:48:45.304197: Current learning rate: 0.00916 +2024-11-21 14:49:03.999647: train_loss -0.7371 +2024-11-21 14:49:04.013979: val_loss -0.7425 +2024-11-21 14:49:04.014128: Pseudo dice [0.8361] +2024-11-21 14:49:04.014223: Epoch time: 18.7 s +2024-11-21 14:49:04.837152: +2024-11-21 14:49:04.837394: Epoch 741 +2024-11-21 14:49:04.837550: Current learning rate: 0.00916 +2024-11-21 14:49:24.892032: train_loss -0.7365 +2024-11-21 14:49:24.899699: val_loss -0.7544 +2024-11-21 14:49:24.899839: Pseudo dice [0.8397] +2024-11-21 14:49:24.899948: Epoch time: 20.06 s +2024-11-21 14:49:25.723346: +2024-11-21 14:49:25.723535: Epoch 742 +2024-11-21 14:49:25.723648: Current learning rate: 0.00916 +2024-11-21 14:49:44.603976: train_loss -0.7507 +2024-11-21 14:49:44.609730: val_loss -0.7626 +2024-11-21 14:49:44.609878: Pseudo dice [0.851] +2024-11-21 14:49:44.609993: Epoch time: 18.88 s +2024-11-21 14:49:45.788477: +2024-11-21 14:49:45.788662: Epoch 743 +2024-11-21 14:49:45.788778: Current learning rate: 0.00916 +2024-11-21 14:50:04.959462: train_loss -0.7471 +2024-11-21 14:50:04.967804: val_loss -0.7864 +2024-11-21 14:50:04.967969: Pseudo dice [0.8544] +2024-11-21 14:50:04.968070: Epoch time: 19.17 s +2024-11-21 14:50:05.791703: +2024-11-21 14:50:05.791919: Epoch 744 +2024-11-21 14:50:05.792050: Current learning rate: 0.00916 +2024-11-21 14:50:25.400997: train_loss -0.7609 +2024-11-21 14:50:25.407467: val_loss -0.7613 +2024-11-21 14:50:25.407588: Pseudo dice [0.8372] +2024-11-21 14:50:25.407685: Epoch time: 19.61 s +2024-11-21 14:50:26.253337: +2024-11-21 14:50:26.253547: Epoch 745 +2024-11-21 14:50:26.253677: Current learning rate: 0.00916 +2024-11-21 14:50:45.578767: train_loss -0.7558 +2024-11-21 14:50:45.581625: val_loss -0.74 +2024-11-21 14:50:45.581742: Pseudo dice [0.8405] +2024-11-21 14:50:45.581824: Epoch time: 19.33 s +2024-11-21 14:50:46.387198: +2024-11-21 14:50:46.387420: Epoch 746 +2024-11-21 14:50:46.387555: Current learning rate: 0.00916 +2024-11-21 14:51:06.354275: train_loss -0.7418 +2024-11-21 14:51:06.358239: val_loss -0.7373 +2024-11-21 14:51:06.358402: Pseudo dice [0.8199] +2024-11-21 14:51:06.358524: Epoch time: 19.97 s +2024-11-21 14:51:07.342413: +2024-11-21 14:51:07.342632: Epoch 747 +2024-11-21 14:51:07.342754: Current learning rate: 0.00916 +2024-11-21 14:51:26.317091: train_loss -0.7488 +2024-11-21 14:51:26.325275: val_loss -0.758 +2024-11-21 14:51:26.325416: Pseudo dice [0.8469] +2024-11-21 14:51:26.325521: Epoch time: 18.98 s +2024-11-21 14:51:27.185619: +2024-11-21 14:51:27.185835: Epoch 748 +2024-11-21 14:51:27.185973: Current learning rate: 0.00915 +2024-11-21 14:51:46.011412: train_loss -0.756 +2024-11-21 14:51:46.014383: val_loss -0.7608 +2024-11-21 14:51:46.014543: Pseudo dice [0.8504] +2024-11-21 14:51:46.014901: Epoch time: 18.83 s +2024-11-21 14:51:46.825298: +2024-11-21 14:51:46.825541: Epoch 749 +2024-11-21 14:51:46.825664: Current learning rate: 0.00915 +2024-11-21 14:52:06.305287: train_loss -0.7673 +2024-11-21 14:52:06.313171: val_loss -0.741 +2024-11-21 14:52:06.313316: Pseudo dice [0.8408] +2024-11-21 14:52:06.313411: Epoch time: 19.48 s +2024-11-21 14:52:07.458372: +2024-11-21 14:52:07.458592: Epoch 750 +2024-11-21 14:52:07.458713: Current learning rate: 0.00915 +2024-11-21 14:52:27.754423: train_loss -0.7483 +2024-11-21 14:52:27.765678: val_loss -0.7642 +2024-11-21 14:52:27.765837: Pseudo dice [0.8471] +2024-11-21 14:52:27.765941: Epoch time: 20.3 s +2024-11-21 14:52:28.583388: +2024-11-21 14:52:28.583601: Epoch 751 +2024-11-21 14:52:28.583737: Current learning rate: 0.00915 +2024-11-21 14:52:47.050598: train_loss -0.735 +2024-11-21 14:52:47.056666: val_loss -0.7411 +2024-11-21 14:52:47.056815: Pseudo dice [0.8313] +2024-11-21 14:52:47.056920: Epoch time: 18.47 s +2024-11-21 14:52:47.872055: +2024-11-21 14:52:47.872249: Epoch 752 +2024-11-21 14:52:47.872373: Current learning rate: 0.00915 +2024-11-21 14:53:07.940231: train_loss -0.7437 +2024-11-21 14:53:07.947654: val_loss -0.7578 +2024-11-21 14:53:07.947801: Pseudo dice [0.8453] +2024-11-21 14:53:07.947899: Epoch time: 20.07 s +2024-11-21 14:53:08.760403: +2024-11-21 14:53:08.760608: Epoch 753 +2024-11-21 14:53:08.760739: Current learning rate: 0.00915 +2024-11-21 14:53:27.774386: train_loss -0.75 +2024-11-21 14:53:27.782786: val_loss -0.7814 +2024-11-21 14:53:27.782922: Pseudo dice [0.8546] +2024-11-21 14:53:27.783030: Epoch time: 19.01 s +2024-11-21 14:53:28.653888: +2024-11-21 14:53:28.654097: Epoch 754 +2024-11-21 14:53:28.654228: Current learning rate: 0.00915 +2024-11-21 14:53:47.756643: train_loss -0.7491 +2024-11-21 14:53:47.763941: val_loss -0.7477 +2024-11-21 14:53:47.764108: Pseudo dice [0.8299] +2024-11-21 14:53:47.764200: Epoch time: 19.1 s +2024-11-21 14:53:49.020482: +2024-11-21 14:53:49.020689: Epoch 755 +2024-11-21 14:53:49.020827: Current learning rate: 0.00915 +2024-11-21 14:54:08.522388: train_loss -0.7521 +2024-11-21 14:54:08.531723: val_loss -0.7566 +2024-11-21 14:54:08.531841: Pseudo dice [0.8327] +2024-11-21 14:54:08.531960: Epoch time: 19.5 s +2024-11-21 14:54:09.533361: +2024-11-21 14:54:09.533584: Epoch 756 +2024-11-21 14:54:09.533710: Current learning rate: 0.00915 +2024-11-21 14:54:28.994159: train_loss -0.7644 +2024-11-21 14:54:28.997910: val_loss -0.7782 +2024-11-21 14:54:28.998043: Pseudo dice [0.8507] +2024-11-21 14:54:28.998148: Epoch time: 19.46 s +2024-11-21 14:54:29.827504: +2024-11-21 14:54:29.827714: Epoch 757 +2024-11-21 14:54:29.827838: Current learning rate: 0.00914 +2024-11-21 14:54:50.375324: train_loss -0.7554 +2024-11-21 14:54:50.382956: val_loss -0.7483 +2024-11-21 14:54:50.383103: Pseudo dice [0.8537] +2024-11-21 14:54:50.383193: Epoch time: 20.55 s +2024-11-21 14:54:51.327367: +2024-11-21 14:54:51.327582: Epoch 758 +2024-11-21 14:54:51.327702: Current learning rate: 0.00914 +2024-11-21 14:55:11.136592: train_loss -0.7553 +2024-11-21 14:55:11.143795: val_loss -0.7791 +2024-11-21 14:55:11.143950: Pseudo dice [0.8479] +2024-11-21 14:55:11.144075: Epoch time: 19.81 s +2024-11-21 14:55:11.992568: +2024-11-21 14:55:11.992820: Epoch 759 +2024-11-21 14:55:11.992939: Current learning rate: 0.00914 +2024-11-21 14:55:31.110395: train_loss -0.7493 +2024-11-21 14:55:31.117509: val_loss -0.762 +2024-11-21 14:55:31.117625: Pseudo dice [0.8273] +2024-11-21 14:55:31.117723: Epoch time: 19.12 s +2024-11-21 14:55:32.112205: +2024-11-21 14:55:32.112442: Epoch 760 +2024-11-21 14:55:32.112572: Current learning rate: 0.00914 +2024-11-21 14:55:51.193811: train_loss -0.7493 +2024-11-21 14:55:51.202620: val_loss -0.7792 +2024-11-21 14:55:51.202745: Pseudo dice [0.853] +2024-11-21 14:55:51.202856: Epoch time: 19.08 s +2024-11-21 14:55:52.036216: +2024-11-21 14:55:52.036425: Epoch 761 +2024-11-21 14:55:52.036561: Current learning rate: 0.00914 +2024-11-21 14:56:11.619468: train_loss -0.7563 +2024-11-21 14:56:11.625602: val_loss -0.7707 +2024-11-21 14:56:11.625737: Pseudo dice [0.8579] +2024-11-21 14:56:11.625837: Epoch time: 19.58 s +2024-11-21 14:56:12.467927: +2024-11-21 14:56:12.468338: Epoch 762 +2024-11-21 14:56:12.468462: Current learning rate: 0.00914 +2024-11-21 14:56:32.277906: train_loss -0.7441 +2024-11-21 14:56:32.285580: val_loss -0.7499 +2024-11-21 14:56:32.285700: Pseudo dice [0.8365] +2024-11-21 14:56:32.285811: Epoch time: 19.81 s +2024-11-21 14:56:33.275887: +2024-11-21 14:56:33.276084: Epoch 763 +2024-11-21 14:56:33.276242: Current learning rate: 0.00914 +2024-11-21 14:56:51.759450: train_loss -0.7588 +2024-11-21 14:56:51.765883: val_loss -0.7362 +2024-11-21 14:56:51.766029: Pseudo dice [0.8428] +2024-11-21 14:56:51.766139: Epoch time: 18.48 s +2024-11-21 14:56:52.589328: +2024-11-21 14:56:52.589550: Epoch 764 +2024-11-21 14:56:52.589663: Current learning rate: 0.00914 +2024-11-21 14:57:12.523364: train_loss -0.7506 +2024-11-21 14:57:12.540879: val_loss -0.7489 +2024-11-21 14:57:12.541017: Pseudo dice [0.8414] +2024-11-21 14:57:12.541189: Epoch time: 19.93 s +2024-11-21 14:57:13.375086: +2024-11-21 14:57:13.375386: Epoch 765 +2024-11-21 14:57:13.375507: Current learning rate: 0.00914 +2024-11-21 14:57:32.599428: train_loss -0.7556 +2024-11-21 14:57:32.603606: val_loss -0.7786 +2024-11-21 14:57:32.603729: Pseudo dice [0.8532] +2024-11-21 14:57:32.603830: Epoch time: 19.23 s +2024-11-21 14:57:33.843036: +2024-11-21 14:57:33.843261: Epoch 766 +2024-11-21 14:57:33.843376: Current learning rate: 0.00913 +2024-11-21 14:57:53.116735: train_loss -0.7614 +2024-11-21 14:57:53.123597: val_loss -0.7569 +2024-11-21 14:57:53.123746: Pseudo dice [0.8425] +2024-11-21 14:57:53.123844: Epoch time: 19.27 s +2024-11-21 14:57:54.019171: +2024-11-21 14:57:54.019409: Epoch 767 +2024-11-21 14:57:54.019529: Current learning rate: 0.00913 +2024-11-21 14:58:13.303610: train_loss -0.7498 +2024-11-21 14:58:13.311354: val_loss -0.7531 +2024-11-21 14:58:13.311485: Pseudo dice [0.8488] +2024-11-21 14:58:13.311577: Epoch time: 19.29 s +2024-11-21 14:58:14.254284: +2024-11-21 14:58:14.254492: Epoch 768 +2024-11-21 14:58:14.254612: Current learning rate: 0.00913 +2024-11-21 14:58:34.290419: train_loss -0.7526 +2024-11-21 14:58:34.297228: val_loss -0.743 +2024-11-21 14:58:34.297378: Pseudo dice [0.8251] +2024-11-21 14:58:34.297475: Epoch time: 20.04 s +2024-11-21 14:58:35.121803: +2024-11-21 14:58:35.122028: Epoch 769 +2024-11-21 14:58:35.122146: Current learning rate: 0.00913 +2024-11-21 14:58:53.656011: train_loss -0.754 +2024-11-21 14:58:53.662054: val_loss -0.7209 +2024-11-21 14:58:53.662191: Pseudo dice [0.8336] +2024-11-21 14:58:53.662302: Epoch time: 18.54 s +2024-11-21 14:58:54.567133: +2024-11-21 14:58:54.567361: Epoch 770 +2024-11-21 14:58:54.567481: Current learning rate: 0.00913 +2024-11-21 14:59:14.451980: train_loss -0.7439 +2024-11-21 14:59:14.460334: val_loss -0.7569 +2024-11-21 14:59:14.460505: Pseudo dice [0.8566] +2024-11-21 14:59:14.460603: Epoch time: 19.89 s +2024-11-21 14:59:15.561141: +2024-11-21 14:59:15.561371: Epoch 771 +2024-11-21 14:59:15.561512: Current learning rate: 0.00913 +2024-11-21 14:59:34.485721: train_loss -0.7507 +2024-11-21 14:59:34.493352: val_loss -0.7649 +2024-11-21 14:59:34.493463: Pseudo dice [0.8464] +2024-11-21 14:59:34.493562: Epoch time: 18.93 s +2024-11-21 14:59:35.480530: +2024-11-21 14:59:35.480771: Epoch 772 +2024-11-21 14:59:35.480891: Current learning rate: 0.00913 +2024-11-21 14:59:53.712456: train_loss -0.7442 +2024-11-21 14:59:53.715256: val_loss -0.7384 +2024-11-21 14:59:53.715371: Pseudo dice [0.8276] +2024-11-21 14:59:53.715482: Epoch time: 18.23 s +2024-11-21 14:59:54.534795: +2024-11-21 14:59:54.535008: Epoch 773 +2024-11-21 14:59:54.535135: Current learning rate: 0.00913 +2024-11-21 15:00:13.244543: train_loss -0.7465 +2024-11-21 15:00:13.247367: val_loss -0.7488 +2024-11-21 15:00:13.247492: Pseudo dice [0.8358] +2024-11-21 15:00:13.247597: Epoch time: 18.71 s +2024-11-21 15:00:14.065511: +2024-11-21 15:00:14.065707: Epoch 774 +2024-11-21 15:00:14.065840: Current learning rate: 0.00912 +2024-11-21 15:00:33.323901: train_loss -0.7518 +2024-11-21 15:00:33.339092: val_loss -0.7408 +2024-11-21 15:00:33.339247: Pseudo dice [0.8394] +2024-11-21 15:00:33.339335: Epoch time: 19.26 s +2024-11-21 15:00:34.239780: +2024-11-21 15:00:34.239977: Epoch 775 +2024-11-21 15:00:34.240099: Current learning rate: 0.00912 +2024-11-21 15:00:54.770080: train_loss -0.7448 +2024-11-21 15:00:54.772196: val_loss -0.7463 +2024-11-21 15:00:54.772308: Pseudo dice [0.8449] +2024-11-21 15:00:54.772395: Epoch time: 20.53 s +2024-11-21 15:00:55.584555: +2024-11-21 15:00:55.585007: Epoch 776 +2024-11-21 15:00:55.585152: Current learning rate: 0.00912 +2024-11-21 15:01:14.573607: train_loss -0.7621 +2024-11-21 15:01:14.576754: val_loss -0.7421 +2024-11-21 15:01:14.576920: Pseudo dice [0.8455] +2024-11-21 15:01:14.577021: Epoch time: 18.99 s +2024-11-21 15:01:15.409069: +2024-11-21 15:01:15.409277: Epoch 777 +2024-11-21 15:01:15.409403: Current learning rate: 0.00912 +2024-11-21 15:01:34.870463: train_loss -0.7637 +2024-11-21 15:01:34.882183: val_loss -0.7345 +2024-11-21 15:01:34.882343: Pseudo dice [0.8517] +2024-11-21 15:01:34.882437: Epoch time: 19.46 s +2024-11-21 15:01:35.767302: +2024-11-21 15:01:35.767508: Epoch 778 +2024-11-21 15:01:35.767627: Current learning rate: 0.00912 +2024-11-21 15:01:54.891934: train_loss -0.7486 +2024-11-21 15:01:54.901680: val_loss -0.7348 +2024-11-21 15:01:54.901826: Pseudo dice [0.8445] +2024-11-21 15:01:54.901921: Epoch time: 19.13 s +2024-11-21 15:01:55.758804: +2024-11-21 15:01:55.759018: Epoch 779 +2024-11-21 15:01:55.759141: Current learning rate: 0.00912 +2024-11-21 15:02:15.367695: train_loss -0.7525 +2024-11-21 15:02:15.374240: val_loss -0.7672 +2024-11-21 15:02:15.374361: Pseudo dice [0.8365] +2024-11-21 15:02:15.374448: Epoch time: 19.61 s +2024-11-21 15:02:16.190489: +2024-11-21 15:02:16.190704: Epoch 780 +2024-11-21 15:02:16.190835: Current learning rate: 0.00912 +2024-11-21 15:02:35.775184: train_loss -0.7518 +2024-11-21 15:02:35.781478: val_loss -0.7527 +2024-11-21 15:02:35.781613: Pseudo dice [0.8406] +2024-11-21 15:02:35.781706: Epoch time: 19.59 s +2024-11-21 15:02:36.607197: +2024-11-21 15:02:36.607415: Epoch 781 +2024-11-21 15:02:36.607542: Current learning rate: 0.00912 +2024-11-21 15:02:55.904972: train_loss -0.7426 +2024-11-21 15:02:55.915716: val_loss -0.7392 +2024-11-21 15:02:55.915861: Pseudo dice [0.849] +2024-11-21 15:02:55.916043: Epoch time: 19.3 s +2024-11-21 15:02:56.921709: +2024-11-21 15:02:56.921922: Epoch 782 +2024-11-21 15:02:56.922046: Current learning rate: 0.00912 +2024-11-21 15:03:18.091461: train_loss -0.7493 +2024-11-21 15:03:18.098529: val_loss -0.7439 +2024-11-21 15:03:18.098679: Pseudo dice [0.8421] +2024-11-21 15:03:18.098772: Epoch time: 21.17 s +2024-11-21 15:03:19.084522: +2024-11-21 15:03:19.084718: Epoch 783 +2024-11-21 15:03:19.084842: Current learning rate: 0.00911 +2024-11-21 15:03:38.904823: train_loss -0.7418 +2024-11-21 15:03:38.908011: val_loss -0.7534 +2024-11-21 15:03:38.908122: Pseudo dice [0.8418] +2024-11-21 15:03:38.908212: Epoch time: 19.82 s +2024-11-21 15:03:39.727865: +2024-11-21 15:03:39.728066: Epoch 784 +2024-11-21 15:03:39.728186: Current learning rate: 0.00911 +2024-11-21 15:03:59.855487: train_loss -0.7566 +2024-11-21 15:03:59.865048: val_loss -0.7839 +2024-11-21 15:03:59.865276: Pseudo dice [0.8485] +2024-11-21 15:03:59.865382: Epoch time: 20.13 s +2024-11-21 15:04:00.748160: +2024-11-21 15:04:00.748447: Epoch 785 +2024-11-21 15:04:00.748574: Current learning rate: 0.00911 +2024-11-21 15:04:19.720233: train_loss -0.7539 +2024-11-21 15:04:19.732357: val_loss -0.7486 +2024-11-21 15:04:19.732517: Pseudo dice [0.8346] +2024-11-21 15:04:19.732683: Epoch time: 18.97 s +2024-11-21 15:04:20.562050: +2024-11-21 15:04:20.562275: Epoch 786 +2024-11-21 15:04:20.562413: Current learning rate: 0.00911 +2024-11-21 15:04:39.123667: train_loss -0.752 +2024-11-21 15:04:39.136826: val_loss -0.748 +2024-11-21 15:04:39.136977: Pseudo dice [0.8316] +2024-11-21 15:04:39.137074: Epoch time: 18.56 s +2024-11-21 15:04:39.990591: +2024-11-21 15:04:39.990802: Epoch 787 +2024-11-21 15:04:39.990941: Current learning rate: 0.00911 +2024-11-21 15:04:59.893309: train_loss -0.7465 +2024-11-21 15:04:59.900901: val_loss -0.7613 +2024-11-21 15:04:59.901046: Pseudo dice [0.8293] +2024-11-21 15:04:59.901171: Epoch time: 19.9 s +2024-11-21 15:05:01.239950: +2024-11-21 15:05:01.240250: Epoch 788 +2024-11-21 15:05:01.240399: Current learning rate: 0.00911 +2024-11-21 15:05:21.160602: train_loss -0.7612 +2024-11-21 15:05:21.165220: val_loss -0.7472 +2024-11-21 15:05:21.165352: Pseudo dice [0.8466] +2024-11-21 15:05:21.165448: Epoch time: 19.92 s +2024-11-21 15:05:21.986807: +2024-11-21 15:05:21.987265: Epoch 789 +2024-11-21 15:05:21.987432: Current learning rate: 0.00911 +2024-11-21 15:05:40.212100: train_loss -0.7557 +2024-11-21 15:05:40.215982: val_loss -0.7396 +2024-11-21 15:05:40.216096: Pseudo dice [0.839] +2024-11-21 15:05:40.216193: Epoch time: 18.23 s +2024-11-21 15:05:41.037151: +2024-11-21 15:05:41.037620: Epoch 790 +2024-11-21 15:05:41.037776: Current learning rate: 0.00911 +2024-11-21 15:06:00.607865: train_loss -0.7474 +2024-11-21 15:06:00.618852: val_loss -0.7456 +2024-11-21 15:06:00.618990: Pseudo dice [0.8305] +2024-11-21 15:06:00.619098: Epoch time: 19.57 s +2024-11-21 15:06:01.543738: +2024-11-21 15:06:01.544158: Epoch 791 +2024-11-21 15:06:01.544297: Current learning rate: 0.00911 +2024-11-21 15:06:20.885042: train_loss -0.7438 +2024-11-21 15:06:20.893289: val_loss -0.7495 +2024-11-21 15:06:20.893408: Pseudo dice [0.8314] +2024-11-21 15:06:20.893502: Epoch time: 19.34 s +2024-11-21 15:06:21.786109: +2024-11-21 15:06:21.786566: Epoch 792 +2024-11-21 15:06:21.786737: Current learning rate: 0.0091 +2024-11-21 15:06:40.803084: train_loss -0.7495 +2024-11-21 15:06:40.815553: val_loss -0.7536 +2024-11-21 15:06:40.815787: Pseudo dice [0.8481] +2024-11-21 15:06:40.815931: Epoch time: 19.02 s +2024-11-21 15:06:41.638391: +2024-11-21 15:06:41.638817: Epoch 793 +2024-11-21 15:06:41.638953: Current learning rate: 0.0091 +2024-11-21 15:07:00.792003: train_loss -0.7336 +2024-11-21 15:07:00.800266: val_loss -0.7655 +2024-11-21 15:07:00.800375: Pseudo dice [0.841] +2024-11-21 15:07:00.800461: Epoch time: 19.15 s +2024-11-21 15:07:01.616630: +2024-11-21 15:07:01.617032: Epoch 794 +2024-11-21 15:07:01.617168: Current learning rate: 0.0091 +2024-11-21 15:07:21.399174: train_loss -0.7554 +2024-11-21 15:07:21.406813: val_loss -0.7683 +2024-11-21 15:07:21.406960: Pseudo dice [0.8491] +2024-11-21 15:07:21.407049: Epoch time: 19.78 s +2024-11-21 15:07:22.234109: +2024-11-21 15:07:22.234538: Epoch 795 +2024-11-21 15:07:22.234693: Current learning rate: 0.0091 +2024-11-21 15:07:41.719673: train_loss -0.7546 +2024-11-21 15:07:41.722020: val_loss -0.7456 +2024-11-21 15:07:41.722165: Pseudo dice [0.8426] +2024-11-21 15:07:41.722265: Epoch time: 19.49 s +2024-11-21 15:07:42.576981: +2024-11-21 15:07:42.577389: Epoch 796 +2024-11-21 15:07:42.577529: Current learning rate: 0.0091 +2024-11-21 15:08:01.792286: train_loss -0.7358 +2024-11-21 15:08:01.797663: val_loss -0.7717 +2024-11-21 15:08:01.797788: Pseudo dice [0.8404] +2024-11-21 15:08:01.797893: Epoch time: 19.22 s +2024-11-21 15:08:02.780780: +2024-11-21 15:08:02.780983: Epoch 797 +2024-11-21 15:08:02.781131: Current learning rate: 0.0091 +2024-11-21 15:08:22.314628: train_loss -0.7536 +2024-11-21 15:08:22.320618: val_loss -0.7598 +2024-11-21 15:08:22.320763: Pseudo dice [0.8499] +2024-11-21 15:08:22.320871: Epoch time: 19.53 s +2024-11-21 15:08:23.126526: +2024-11-21 15:08:23.126736: Epoch 798 +2024-11-21 15:08:23.126858: Current learning rate: 0.0091 +2024-11-21 15:08:42.542409: train_loss -0.7537 +2024-11-21 15:08:42.544471: val_loss -0.7517 +2024-11-21 15:08:42.544629: Pseudo dice [0.831] +2024-11-21 15:08:42.544723: Epoch time: 19.42 s +2024-11-21 15:08:43.360685: +2024-11-21 15:08:43.360884: Epoch 799 +2024-11-21 15:08:43.361025: Current learning rate: 0.0091 +2024-11-21 15:09:02.411150: train_loss -0.7525 +2024-11-21 15:09:02.415751: val_loss -0.7486 +2024-11-21 15:09:02.415867: Pseudo dice [0.8496] +2024-11-21 15:09:02.416173: Epoch time: 19.05 s +2024-11-21 15:09:03.962431: +2024-11-21 15:09:03.962638: Epoch 800 +2024-11-21 15:09:03.962770: Current learning rate: 0.0091 +2024-11-21 15:09:23.420483: train_loss -0.7479 +2024-11-21 15:09:23.439325: val_loss -0.7556 +2024-11-21 15:09:23.439488: Pseudo dice [0.8481] +2024-11-21 15:09:23.439592: Epoch time: 19.46 s +2024-11-21 15:09:24.479345: +2024-11-21 15:09:24.479563: Epoch 801 +2024-11-21 15:09:24.479684: Current learning rate: 0.00909 +2024-11-21 15:09:44.135185: train_loss -0.757 +2024-11-21 15:09:44.139958: val_loss -0.7476 +2024-11-21 15:09:44.140109: Pseudo dice [0.8422] +2024-11-21 15:09:44.140217: Epoch time: 19.66 s +2024-11-21 15:09:44.972141: +2024-11-21 15:09:44.972376: Epoch 802 +2024-11-21 15:09:44.972495: Current learning rate: 0.00909 +2024-11-21 15:10:04.879988: train_loss -0.7551 +2024-11-21 15:10:04.884574: val_loss -0.7452 +2024-11-21 15:10:04.884721: Pseudo dice [0.8369] +2024-11-21 15:10:04.884829: Epoch time: 19.91 s +2024-11-21 15:10:05.721034: +2024-11-21 15:10:05.721319: Epoch 803 +2024-11-21 15:10:05.721442: Current learning rate: 0.00909 +2024-11-21 15:10:24.415463: train_loss -0.757 +2024-11-21 15:10:24.417581: val_loss -0.7615 +2024-11-21 15:10:24.417765: Pseudo dice [0.8472] +2024-11-21 15:10:24.417869: Epoch time: 18.7 s +2024-11-21 15:10:25.234775: +2024-11-21 15:10:25.234982: Epoch 804 +2024-11-21 15:10:25.235112: Current learning rate: 0.00909 +2024-11-21 15:10:44.027704: train_loss -0.7659 +2024-11-21 15:10:44.031646: val_loss -0.7496 +2024-11-21 15:10:44.031793: Pseudo dice [0.8538] +2024-11-21 15:10:44.031904: Epoch time: 18.79 s +2024-11-21 15:10:44.856296: +2024-11-21 15:10:44.856514: Epoch 805 +2024-11-21 15:10:44.856684: Current learning rate: 0.00909 +2024-11-21 15:11:04.128375: train_loss -0.7645 +2024-11-21 15:11:04.134386: val_loss -0.7463 +2024-11-21 15:11:04.134537: Pseudo dice [0.8471] +2024-11-21 15:11:04.134644: Epoch time: 19.27 s +2024-11-21 15:11:04.963156: +2024-11-21 15:11:04.963412: Epoch 806 +2024-11-21 15:11:04.963540: Current learning rate: 0.00909 +2024-11-21 15:11:23.727585: train_loss -0.7524 +2024-11-21 15:11:23.734697: val_loss -0.7589 +2024-11-21 15:11:23.734813: Pseudo dice [0.8466] +2024-11-21 15:11:23.734903: Epoch time: 18.77 s +2024-11-21 15:11:24.654117: +2024-11-21 15:11:24.654339: Epoch 807 +2024-11-21 15:11:24.654461: Current learning rate: 0.00909 +2024-11-21 15:11:44.327351: train_loss -0.7572 +2024-11-21 15:11:44.332549: val_loss -0.7572 +2024-11-21 15:11:44.332688: Pseudo dice [0.833] +2024-11-21 15:11:44.332799: Epoch time: 19.67 s +2024-11-21 15:11:45.155353: +2024-11-21 15:11:45.155575: Epoch 808 +2024-11-21 15:11:45.155713: Current learning rate: 0.00909 +2024-11-21 15:12:04.850659: train_loss -0.759 +2024-11-21 15:12:04.856676: val_loss -0.7553 +2024-11-21 15:12:04.856821: Pseudo dice [0.8419] +2024-11-21 15:12:04.856917: Epoch time: 19.7 s +2024-11-21 15:12:05.714457: +2024-11-21 15:12:05.714675: Epoch 809 +2024-11-21 15:12:05.714802: Current learning rate: 0.00909 +2024-11-21 15:12:23.875548: train_loss -0.7419 +2024-11-21 15:12:23.885585: val_loss -0.7536 +2024-11-21 15:12:23.885708: Pseudo dice [0.8309] +2024-11-21 15:12:23.885806: Epoch time: 18.16 s +2024-11-21 15:12:25.179976: +2024-11-21 15:12:25.180193: Epoch 810 +2024-11-21 15:12:25.180325: Current learning rate: 0.00908 +2024-11-21 15:12:44.884597: train_loss -0.7486 +2024-11-21 15:12:44.898430: val_loss -0.7812 +2024-11-21 15:12:44.898583: Pseudo dice [0.8502] +2024-11-21 15:12:44.898677: Epoch time: 19.71 s +2024-11-21 15:12:45.787202: +2024-11-21 15:12:45.787418: Epoch 811 +2024-11-21 15:12:45.787553: Current learning rate: 0.00908 +2024-11-21 15:13:04.882006: train_loss -0.767 +2024-11-21 15:13:04.887383: val_loss -0.7707 +2024-11-21 15:13:04.887517: Pseudo dice [0.8473] +2024-11-21 15:13:04.887604: Epoch time: 19.1 s +2024-11-21 15:13:05.751485: +2024-11-21 15:13:05.751717: Epoch 812 +2024-11-21 15:13:05.751845: Current learning rate: 0.00908 +2024-11-21 15:13:24.601448: train_loss -0.7642 +2024-11-21 15:13:24.608420: val_loss -0.7391 +2024-11-21 15:13:24.608567: Pseudo dice [0.8309] +2024-11-21 15:13:24.608674: Epoch time: 18.85 s +2024-11-21 15:13:25.431557: +2024-11-21 15:13:25.431756: Epoch 813 +2024-11-21 15:13:25.431882: Current learning rate: 0.00908 +2024-11-21 15:13:43.583886: train_loss -0.7609 +2024-11-21 15:13:43.585508: val_loss -0.752 +2024-11-21 15:13:43.585642: Pseudo dice [0.8506] +2024-11-21 15:13:43.585730: Epoch time: 18.15 s +2024-11-21 15:13:44.433518: +2024-11-21 15:13:44.433950: Epoch 814 +2024-11-21 15:13:44.434084: Current learning rate: 0.00908 +2024-11-21 15:14:04.006888: train_loss -0.7532 +2024-11-21 15:14:04.008865: val_loss -0.7552 +2024-11-21 15:14:04.009005: Pseudo dice [0.8551] +2024-11-21 15:14:04.009102: Epoch time: 19.57 s +2024-11-21 15:14:04.960943: +2024-11-21 15:14:04.961166: Epoch 815 +2024-11-21 15:14:04.961294: Current learning rate: 0.00908 +2024-11-21 15:14:23.857687: train_loss -0.7501 +2024-11-21 15:14:23.862917: val_loss -0.7691 +2024-11-21 15:14:23.863034: Pseudo dice [0.8544] +2024-11-21 15:14:23.863130: Epoch time: 18.9 s +2024-11-21 15:14:24.761560: +2024-11-21 15:14:24.761759: Epoch 816 +2024-11-21 15:14:24.761875: Current learning rate: 0.00908 +2024-11-21 15:14:44.626317: train_loss -0.7599 +2024-11-21 15:14:44.632650: val_loss -0.7438 +2024-11-21 15:14:44.632777: Pseudo dice [0.8428] +2024-11-21 15:14:44.632860: Epoch time: 19.87 s +2024-11-21 15:14:45.536112: +2024-11-21 15:14:45.536317: Epoch 817 +2024-11-21 15:14:45.536452: Current learning rate: 0.00908 +2024-11-21 15:15:04.677969: train_loss -0.7584 +2024-11-21 15:15:04.685444: val_loss -0.7731 +2024-11-21 15:15:04.685584: Pseudo dice [0.8465] +2024-11-21 15:15:04.685683: Epoch time: 19.14 s +2024-11-21 15:15:05.533905: +2024-11-21 15:15:05.534123: Epoch 818 +2024-11-21 15:15:05.534246: Current learning rate: 0.00907 +2024-11-21 15:15:24.373140: train_loss -0.7487 +2024-11-21 15:15:24.379150: val_loss -0.7469 +2024-11-21 15:15:24.379282: Pseudo dice [0.8276] +2024-11-21 15:15:24.379373: Epoch time: 18.84 s +2024-11-21 15:15:25.230908: +2024-11-21 15:15:25.231175: Epoch 819 +2024-11-21 15:15:25.231297: Current learning rate: 0.00907 +2024-11-21 15:15:44.770564: train_loss -0.7477 +2024-11-21 15:15:44.776290: val_loss -0.7235 +2024-11-21 15:15:44.776430: Pseudo dice [0.8359] +2024-11-21 15:15:44.776513: Epoch time: 19.54 s +2024-11-21 15:15:45.594108: +2024-11-21 15:15:45.594335: Epoch 820 +2024-11-21 15:15:45.594450: Current learning rate: 0.00907 +2024-11-21 15:16:05.248581: train_loss -0.753 +2024-11-21 15:16:05.250852: val_loss -0.7521 +2024-11-21 15:16:05.250999: Pseudo dice [0.8356] +2024-11-21 15:16:05.251115: Epoch time: 19.66 s +2024-11-21 15:16:06.107298: +2024-11-21 15:16:06.107535: Epoch 821 +2024-11-21 15:16:06.107662: Current learning rate: 0.00907 +2024-11-21 15:16:26.699233: train_loss -0.7512 +2024-11-21 15:16:26.703941: val_loss -0.7493 +2024-11-21 15:16:26.704105: Pseudo dice [0.8411] +2024-11-21 15:16:26.704218: Epoch time: 20.59 s +2024-11-21 15:16:27.922021: +2024-11-21 15:16:27.922278: Epoch 822 +2024-11-21 15:16:27.922394: Current learning rate: 0.00907 +2024-11-21 15:16:46.987375: train_loss -0.7562 +2024-11-21 15:16:46.993176: val_loss -0.7446 +2024-11-21 15:16:46.993303: Pseudo dice [0.8159] +2024-11-21 15:16:46.993413: Epoch time: 19.07 s +2024-11-21 15:16:47.931846: +2024-11-21 15:16:47.932080: Epoch 823 +2024-11-21 15:16:47.932216: Current learning rate: 0.00907 +2024-11-21 15:17:07.250020: train_loss -0.75 +2024-11-21 15:17:07.264237: val_loss -0.7684 +2024-11-21 15:17:07.264403: Pseudo dice [0.8467] +2024-11-21 15:17:07.264510: Epoch time: 19.32 s +2024-11-21 15:17:08.130251: +2024-11-21 15:17:08.130473: Epoch 824 +2024-11-21 15:17:08.130595: Current learning rate: 0.00907 +2024-11-21 15:17:27.482759: train_loss -0.7598 +2024-11-21 15:17:27.490045: val_loss -0.7952 +2024-11-21 15:17:27.490182: Pseudo dice [0.8627] +2024-11-21 15:17:27.490267: Epoch time: 19.35 s +2024-11-21 15:17:28.291925: +2024-11-21 15:17:28.292164: Epoch 825 +2024-11-21 15:17:28.292278: Current learning rate: 0.00907 +2024-11-21 15:17:47.783852: train_loss -0.762 +2024-11-21 15:17:47.786633: val_loss -0.7392 +2024-11-21 15:17:47.786800: Pseudo dice [0.8353] +2024-11-21 15:17:47.786909: Epoch time: 19.49 s +2024-11-21 15:17:48.805670: +2024-11-21 15:17:48.805902: Epoch 826 +2024-11-21 15:17:48.806026: Current learning rate: 0.00907 +2024-11-21 15:18:07.227917: train_loss -0.7524 +2024-11-21 15:18:07.230411: val_loss -0.7605 +2024-11-21 15:18:07.230516: Pseudo dice [0.8295] +2024-11-21 15:18:07.230602: Epoch time: 18.42 s +2024-11-21 15:18:08.019444: +2024-11-21 15:18:08.019672: Epoch 827 +2024-11-21 15:18:08.019805: Current learning rate: 0.00906 +2024-11-21 15:18:26.897543: train_loss -0.7565 +2024-11-21 15:18:26.899882: val_loss -0.7796 +2024-11-21 15:18:26.900002: Pseudo dice [0.8386] +2024-11-21 15:18:26.900114: Epoch time: 18.88 s +2024-11-21 15:18:27.745597: +2024-11-21 15:18:27.745814: Epoch 828 +2024-11-21 15:18:27.745953: Current learning rate: 0.00906 +2024-11-21 15:18:46.720933: train_loss -0.7633 +2024-11-21 15:18:46.727867: val_loss -0.7559 +2024-11-21 15:18:46.728033: Pseudo dice [0.8437] +2024-11-21 15:18:46.728148: Epoch time: 18.98 s +2024-11-21 15:18:47.525390: +2024-11-21 15:18:47.525612: Epoch 829 +2024-11-21 15:18:47.525751: Current learning rate: 0.00906 +2024-11-21 15:19:06.549507: train_loss -0.7546 +2024-11-21 15:19:06.551948: val_loss -0.762 +2024-11-21 15:19:06.552083: Pseudo dice [0.8413] +2024-11-21 15:19:06.552164: Epoch time: 19.02 s +2024-11-21 15:19:07.353399: +2024-11-21 15:19:07.353624: Epoch 830 +2024-11-21 15:19:07.353749: Current learning rate: 0.00906 +2024-11-21 15:19:26.717855: train_loss -0.7545 +2024-11-21 15:19:26.724550: val_loss -0.7591 +2024-11-21 15:19:26.724686: Pseudo dice [0.8346] +2024-11-21 15:19:26.724792: Epoch time: 19.37 s +2024-11-21 15:19:27.528458: +2024-11-21 15:19:27.528663: Epoch 831 +2024-11-21 15:19:27.528797: Current learning rate: 0.00906 +2024-11-21 15:19:46.592330: train_loss -0.7595 +2024-11-21 15:19:46.594229: val_loss -0.7606 +2024-11-21 15:19:46.594355: Pseudo dice [0.8312] +2024-11-21 15:19:46.594460: Epoch time: 19.06 s +2024-11-21 15:19:47.550907: +2024-11-21 15:19:47.551121: Epoch 832 +2024-11-21 15:19:47.551244: Current learning rate: 0.00906 +2024-11-21 15:20:06.437142: train_loss -0.7561 +2024-11-21 15:20:06.451318: val_loss -0.6914 +2024-11-21 15:20:06.451481: Pseudo dice [0.832] +2024-11-21 15:20:06.451578: Epoch time: 18.89 s +2024-11-21 15:20:07.420871: +2024-11-21 15:20:07.421109: Epoch 833 +2024-11-21 15:20:07.421247: Current learning rate: 0.00906 +2024-11-21 15:20:27.164174: train_loss -0.7336 +2024-11-21 15:20:27.166936: val_loss -0.7657 +2024-11-21 15:20:27.167080: Pseudo dice [0.8363] +2024-11-21 15:20:27.167182: Epoch time: 19.74 s +2024-11-21 15:20:28.696882: +2024-11-21 15:20:28.697139: Epoch 834 +2024-11-21 15:20:28.697269: Current learning rate: 0.00906 +2024-11-21 15:20:47.386743: train_loss -0.741 +2024-11-21 15:20:47.391630: val_loss -0.7391 +2024-11-21 15:20:47.391775: Pseudo dice [0.8174] +2024-11-21 15:20:47.391888: Epoch time: 18.69 s +2024-11-21 15:20:48.213960: +2024-11-21 15:20:48.214170: Epoch 835 +2024-11-21 15:20:48.214294: Current learning rate: 0.00906 +2024-11-21 15:21:06.694486: train_loss -0.7461 +2024-11-21 15:21:06.696242: val_loss -0.7647 +2024-11-21 15:21:06.696379: Pseudo dice [0.8313] +2024-11-21 15:21:06.696499: Epoch time: 18.48 s +2024-11-21 15:21:07.484009: +2024-11-21 15:21:07.484252: Epoch 836 +2024-11-21 15:21:07.484391: Current learning rate: 0.00905 +2024-11-21 15:21:25.997402: train_loss -0.741 +2024-11-21 15:21:26.006154: val_loss -0.7764 +2024-11-21 15:21:26.006301: Pseudo dice [0.8575] +2024-11-21 15:21:26.006399: Epoch time: 18.51 s +2024-11-21 15:21:26.796099: +2024-11-21 15:21:26.796306: Epoch 837 +2024-11-21 15:21:26.796431: Current learning rate: 0.00905 +2024-11-21 15:21:46.081295: train_loss -0.7555 +2024-11-21 15:21:46.089466: val_loss -0.7464 +2024-11-21 15:21:46.089628: Pseudo dice [0.8333] +2024-11-21 15:21:46.089756: Epoch time: 19.29 s +2024-11-21 15:21:46.963887: +2024-11-21 15:21:46.964109: Epoch 838 +2024-11-21 15:21:46.964230: Current learning rate: 0.00905 +2024-11-21 15:22:05.981755: train_loss -0.7518 +2024-11-21 15:22:05.989186: val_loss -0.7381 +2024-11-21 15:22:05.989344: Pseudo dice [0.8273] +2024-11-21 15:22:05.989451: Epoch time: 19.02 s +2024-11-21 15:22:06.803425: +2024-11-21 15:22:06.803647: Epoch 839 +2024-11-21 15:22:06.803768: Current learning rate: 0.00905 +2024-11-21 15:22:25.719602: train_loss -0.7587 +2024-11-21 15:22:25.724828: val_loss -0.7582 +2024-11-21 15:22:25.724966: Pseudo dice [0.8302] +2024-11-21 15:22:25.725073: Epoch time: 18.92 s +2024-11-21 15:22:26.533828: +2024-11-21 15:22:26.534316: Epoch 840 +2024-11-21 15:22:26.534465: Current learning rate: 0.00905 +2024-11-21 15:22:46.535240: train_loss -0.7579 +2024-11-21 15:22:46.558690: val_loss -0.7618 +2024-11-21 15:22:46.558859: Pseudo dice [0.8553] +2024-11-21 15:22:46.558946: Epoch time: 20.0 s +2024-11-21 15:22:47.431432: +2024-11-21 15:22:47.431672: Epoch 841 +2024-11-21 15:22:47.431809: Current learning rate: 0.00905 +2024-11-21 15:23:06.996746: train_loss -0.7621 +2024-11-21 15:23:07.002609: val_loss -0.7725 +2024-11-21 15:23:07.002721: Pseudo dice [0.8434] +2024-11-21 15:23:07.002810: Epoch time: 19.57 s +2024-11-21 15:23:07.795892: +2024-11-21 15:23:07.796104: Epoch 842 +2024-11-21 15:23:07.796227: Current learning rate: 0.00905 +2024-11-21 15:23:25.705961: train_loss -0.7583 +2024-11-21 15:23:25.713130: val_loss -0.772 +2024-11-21 15:23:25.713252: Pseudo dice [0.8376] +2024-11-21 15:23:25.713353: Epoch time: 17.91 s +2024-11-21 15:23:26.501994: +2024-11-21 15:23:26.502203: Epoch 843 +2024-11-21 15:23:26.502344: Current learning rate: 0.00905 +2024-11-21 15:23:46.324294: train_loss -0.7461 +2024-11-21 15:23:46.328909: val_loss -0.7401 +2024-11-21 15:23:46.329066: Pseudo dice [0.8514] +2024-11-21 15:23:46.329152: Epoch time: 19.82 s +2024-11-21 15:23:47.278122: +2024-11-21 15:23:47.278354: Epoch 844 +2024-11-21 15:23:47.278493: Current learning rate: 0.00905 +2024-11-21 15:24:07.612785: train_loss -0.7535 +2024-11-21 15:24:07.617695: val_loss -0.7413 +2024-11-21 15:24:07.617831: Pseudo dice [0.8446] +2024-11-21 15:24:07.617948: Epoch time: 20.34 s +2024-11-21 15:24:08.412003: +2024-11-21 15:24:08.412205: Epoch 845 +2024-11-21 15:24:08.412338: Current learning rate: 0.00904 +2024-11-21 15:24:26.799334: train_loss -0.7504 +2024-11-21 15:24:26.805287: val_loss -0.7298 +2024-11-21 15:24:26.805428: Pseudo dice [0.8362] +2024-11-21 15:24:26.805523: Epoch time: 18.39 s +2024-11-21 15:24:27.990182: +2024-11-21 15:24:27.990405: Epoch 846 +2024-11-21 15:24:27.990530: Current learning rate: 0.00904 +2024-11-21 15:24:46.833600: train_loss -0.7407 +2024-11-21 15:24:46.844991: val_loss -0.7641 +2024-11-21 15:24:46.845155: Pseudo dice [0.8326] +2024-11-21 15:24:46.845286: Epoch time: 18.84 s +2024-11-21 15:24:47.669660: +2024-11-21 15:24:47.669893: Epoch 847 +2024-11-21 15:24:47.670012: Current learning rate: 0.00904 +2024-11-21 15:25:07.589332: train_loss -0.7536 +2024-11-21 15:25:07.595156: val_loss -0.7495 +2024-11-21 15:25:07.595291: Pseudo dice [0.8287] +2024-11-21 15:25:07.595400: Epoch time: 19.92 s +2024-11-21 15:25:08.409642: +2024-11-21 15:25:08.409911: Epoch 848 +2024-11-21 15:25:08.410047: Current learning rate: 0.00904 +2024-11-21 15:25:27.591545: train_loss -0.7444 +2024-11-21 15:25:27.597354: val_loss -0.7542 +2024-11-21 15:25:27.597509: Pseudo dice [0.8457] +2024-11-21 15:25:27.597609: Epoch time: 19.18 s +2024-11-21 15:25:28.397882: +2024-11-21 15:25:28.398090: Epoch 849 +2024-11-21 15:25:28.398220: Current learning rate: 0.00904 +2024-11-21 15:25:46.043205: train_loss -0.7536 +2024-11-21 15:25:46.056127: val_loss -0.7448 +2024-11-21 15:25:46.056273: Pseudo dice [0.8483] +2024-11-21 15:25:46.056377: Epoch time: 17.65 s +2024-11-21 15:25:47.118561: +2024-11-21 15:25:47.118762: Epoch 850 +2024-11-21 15:25:47.118893: Current learning rate: 0.00904 +2024-11-21 15:26:06.110130: train_loss -0.76 +2024-11-21 15:26:06.136904: val_loss -0.7499 +2024-11-21 15:26:06.137051: Pseudo dice [0.8436] +2024-11-21 15:26:06.137341: Epoch time: 18.99 s +2024-11-21 15:26:07.354044: +2024-11-21 15:26:07.354269: Epoch 851 +2024-11-21 15:26:07.354403: Current learning rate: 0.00904 +2024-11-21 15:26:27.240926: train_loss -0.7471 +2024-11-21 15:26:27.243096: val_loss -0.7646 +2024-11-21 15:26:27.243204: Pseudo dice [0.8601] +2024-11-21 15:26:27.243299: Epoch time: 19.89 s +2024-11-21 15:26:28.038300: +2024-11-21 15:26:28.038501: Epoch 852 +2024-11-21 15:26:28.038625: Current learning rate: 0.00904 +2024-11-21 15:26:47.423726: train_loss -0.7631 +2024-11-21 15:26:47.427769: val_loss -0.7603 +2024-11-21 15:26:47.427913: Pseudo dice [0.8554] +2024-11-21 15:26:47.428127: Epoch time: 19.39 s +2024-11-21 15:26:48.230040: +2024-11-21 15:26:48.230265: Epoch 853 +2024-11-21 15:26:48.230379: Current learning rate: 0.00904 +2024-11-21 15:27:07.612147: train_loss -0.7665 +2024-11-21 15:27:07.615079: val_loss -0.7456 +2024-11-21 15:27:07.615226: Pseudo dice [0.8349] +2024-11-21 15:27:07.615322: Epoch time: 19.38 s +2024-11-21 15:27:08.459409: +2024-11-21 15:27:08.459611: Epoch 854 +2024-11-21 15:27:08.459729: Current learning rate: 0.00903 +2024-11-21 15:27:27.661161: train_loss -0.7563 +2024-11-21 15:27:27.662944: val_loss -0.7485 +2024-11-21 15:27:27.663049: Pseudo dice [0.8519] +2024-11-21 15:27:27.663150: Epoch time: 19.2 s +2024-11-21 15:27:28.451947: +2024-11-21 15:27:28.452179: Epoch 855 +2024-11-21 15:27:28.452306: Current learning rate: 0.00903 +2024-11-21 15:27:48.036133: train_loss -0.7687 +2024-11-21 15:27:48.043224: val_loss -0.7407 +2024-11-21 15:27:48.043357: Pseudo dice [0.8328] +2024-11-21 15:27:48.043468: Epoch time: 19.58 s +2024-11-21 15:27:49.079900: +2024-11-21 15:27:49.080205: Epoch 856 +2024-11-21 15:27:49.080330: Current learning rate: 0.00903 +2024-11-21 15:28:07.423914: train_loss -0.7671 +2024-11-21 15:28:07.426502: val_loss -0.7498 +2024-11-21 15:28:07.426627: Pseudo dice [0.8545] +2024-11-21 15:28:07.426732: Epoch time: 18.34 s +2024-11-21 15:28:08.295817: +2024-11-21 15:28:08.296035: Epoch 857 +2024-11-21 15:28:08.296164: Current learning rate: 0.00903 +2024-11-21 15:28:26.543960: train_loss -0.7656 +2024-11-21 15:28:26.550035: val_loss -0.7427 +2024-11-21 15:28:26.550176: Pseudo dice [0.8496] +2024-11-21 15:28:26.550267: Epoch time: 18.25 s +2024-11-21 15:28:27.824694: +2024-11-21 15:28:27.824926: Epoch 858 +2024-11-21 15:28:27.825042: Current learning rate: 0.00903 +2024-11-21 15:28:47.429089: train_loss -0.7659 +2024-11-21 15:28:47.431949: val_loss -0.7771 +2024-11-21 15:28:47.432088: Pseudo dice [0.8415] +2024-11-21 15:28:47.432193: Epoch time: 19.61 s +2024-11-21 15:28:48.345052: +2024-11-21 15:28:48.345283: Epoch 859 +2024-11-21 15:28:48.345407: Current learning rate: 0.00903 +2024-11-21 15:29:07.045379: train_loss -0.7616 +2024-11-21 15:29:07.052467: val_loss -0.75 +2024-11-21 15:29:07.052599: Pseudo dice [0.8434] +2024-11-21 15:29:07.052699: Epoch time: 18.7 s +2024-11-21 15:29:08.073107: +2024-11-21 15:29:08.073328: Epoch 860 +2024-11-21 15:29:08.073473: Current learning rate: 0.00903 +2024-11-21 15:29:27.933876: train_loss -0.7577 +2024-11-21 15:29:27.939702: val_loss -0.7324 +2024-11-21 15:29:27.939827: Pseudo dice [0.8408] +2024-11-21 15:29:27.939918: Epoch time: 19.86 s +2024-11-21 15:29:28.845904: +2024-11-21 15:29:28.846110: Epoch 861 +2024-11-21 15:29:28.846229: Current learning rate: 0.00903 +2024-11-21 15:29:48.087348: train_loss -0.7547 +2024-11-21 15:29:48.090609: val_loss -0.761 +2024-11-21 15:29:48.090759: Pseudo dice [0.8614] +2024-11-21 15:29:48.090863: Epoch time: 19.24 s +2024-11-21 15:29:48.090940: Yayy! New best EMA pseudo Dice: 0.8454 +2024-11-21 15:29:49.130347: +2024-11-21 15:29:49.130569: Epoch 862 +2024-11-21 15:29:49.130699: Current learning rate: 0.00902 +2024-11-21 15:30:08.409023: train_loss -0.7568 +2024-11-21 15:30:08.410857: val_loss -0.7466 +2024-11-21 15:30:08.410965: Pseudo dice [0.8302] +2024-11-21 15:30:08.411053: Epoch time: 19.28 s +2024-11-21 15:30:09.208951: +2024-11-21 15:30:09.209165: Epoch 863 +2024-11-21 15:30:09.209302: Current learning rate: 0.00902 +2024-11-21 15:30:28.787637: train_loss -0.7498 +2024-11-21 15:30:28.794754: val_loss -0.7164 +2024-11-21 15:30:28.794874: Pseudo dice [0.8211] +2024-11-21 15:30:28.794968: Epoch time: 19.58 s +2024-11-21 15:30:29.812173: +2024-11-21 15:30:29.812379: Epoch 864 +2024-11-21 15:30:29.812505: Current learning rate: 0.00902 +2024-11-21 15:30:48.621101: train_loss -0.7559 +2024-11-21 15:30:48.627647: val_loss -0.748 +2024-11-21 15:30:48.627781: Pseudo dice [0.8441] +2024-11-21 15:30:48.627869: Epoch time: 18.81 s +2024-11-21 15:30:49.426052: +2024-11-21 15:30:49.426319: Epoch 865 +2024-11-21 15:30:49.426445: Current learning rate: 0.00902 +2024-11-21 15:31:08.910870: train_loss -0.7715 +2024-11-21 15:31:08.932690: val_loss -0.7599 +2024-11-21 15:31:08.932852: Pseudo dice [0.8469] +2024-11-21 15:31:08.933194: Epoch time: 19.49 s +2024-11-21 15:31:09.788178: +2024-11-21 15:31:09.788405: Epoch 866 +2024-11-21 15:31:09.788521: Current learning rate: 0.00902 +2024-11-21 15:31:29.391962: train_loss -0.7281 +2024-11-21 15:31:29.398072: val_loss -0.7433 +2024-11-21 15:31:29.398229: Pseudo dice [0.843] +2024-11-21 15:31:29.398341: Epoch time: 19.6 s +2024-11-21 15:31:30.344927: +2024-11-21 15:31:30.345151: Epoch 867 +2024-11-21 15:31:30.345285: Current learning rate: 0.00902 +2024-11-21 15:31:49.538473: train_loss -0.7303 +2024-11-21 15:31:49.545981: val_loss -0.7561 +2024-11-21 15:31:49.546136: Pseudo dice [0.828] +2024-11-21 15:31:49.546223: Epoch time: 19.19 s +2024-11-21 15:31:50.364300: +2024-11-21 15:31:50.364521: Epoch 868 +2024-11-21 15:31:50.364655: Current learning rate: 0.00902 +2024-11-21 15:32:09.962832: train_loss -0.7417 +2024-11-21 15:32:09.968186: val_loss -0.7652 +2024-11-21 15:32:09.968321: Pseudo dice [0.8311] +2024-11-21 15:32:09.968429: Epoch time: 19.6 s +2024-11-21 15:32:10.825815: +2024-11-21 15:32:10.826028: Epoch 869 +2024-11-21 15:32:10.826160: Current learning rate: 0.00902 +2024-11-21 15:32:29.902448: train_loss -0.7428 +2024-11-21 15:32:29.907465: val_loss -0.7399 +2024-11-21 15:32:29.907615: Pseudo dice [0.8446] +2024-11-21 15:32:29.907708: Epoch time: 19.08 s +2024-11-21 15:32:31.116007: +2024-11-21 15:32:31.116225: Epoch 870 +2024-11-21 15:32:31.116363: Current learning rate: 0.00902 +2024-11-21 15:32:50.641745: train_loss -0.756 +2024-11-21 15:32:50.647173: val_loss -0.7622 +2024-11-21 15:32:50.647306: Pseudo dice [0.8335] +2024-11-21 15:32:50.647396: Epoch time: 19.53 s +2024-11-21 15:32:51.540880: +2024-11-21 15:32:51.541111: Epoch 871 +2024-11-21 15:32:51.541262: Current learning rate: 0.00901 +2024-11-21 15:33:10.327710: train_loss -0.7494 +2024-11-21 15:33:10.332920: val_loss -0.7727 +2024-11-21 15:33:10.333051: Pseudo dice [0.8526] +2024-11-21 15:33:10.333148: Epoch time: 18.79 s +2024-11-21 15:33:11.135829: +2024-11-21 15:33:11.136055: Epoch 872 +2024-11-21 15:33:11.136186: Current learning rate: 0.00901 +2024-11-21 15:33:28.816371: train_loss -0.7441 +2024-11-21 15:33:28.823758: val_loss -0.7618 +2024-11-21 15:33:28.823890: Pseudo dice [0.8427] +2024-11-21 15:33:28.823991: Epoch time: 17.68 s +2024-11-21 15:33:29.801292: +2024-11-21 15:33:29.801531: Epoch 873 +2024-11-21 15:33:29.801665: Current learning rate: 0.00901 +2024-11-21 15:33:49.349198: train_loss -0.7601 +2024-11-21 15:33:49.351186: val_loss -0.759 +2024-11-21 15:33:49.351297: Pseudo dice [0.8433] +2024-11-21 15:33:49.351409: Epoch time: 19.55 s +2024-11-21 15:33:50.151839: +2024-11-21 15:33:50.152052: Epoch 874 +2024-11-21 15:33:50.152192: Current learning rate: 0.00901 +2024-11-21 15:34:10.027109: train_loss -0.7438 +2024-11-21 15:34:10.034510: val_loss -0.7573 +2024-11-21 15:34:10.034646: Pseudo dice [0.832] +2024-11-21 15:34:10.034750: Epoch time: 19.88 s +2024-11-21 15:34:10.834743: +2024-11-21 15:34:10.834949: Epoch 875 +2024-11-21 15:34:10.835098: Current learning rate: 0.00901 +2024-11-21 15:34:29.632564: train_loss -0.7462 +2024-11-21 15:34:29.644211: val_loss -0.7548 +2024-11-21 15:34:29.644342: Pseudo dice [0.8325] +2024-11-21 15:34:29.644490: Epoch time: 18.8 s +2024-11-21 15:34:30.486592: +2024-11-21 15:34:30.486813: Epoch 876 +2024-11-21 15:34:30.486944: Current learning rate: 0.00901 +2024-11-21 15:34:50.118373: train_loss -0.7441 +2024-11-21 15:34:50.121441: val_loss -0.7505 +2024-11-21 15:34:50.121572: Pseudo dice [0.8312] +2024-11-21 15:34:50.121653: Epoch time: 19.63 s +2024-11-21 15:34:50.920259: +2024-11-21 15:34:50.920504: Epoch 877 +2024-11-21 15:34:50.920630: Current learning rate: 0.00901 +2024-11-21 15:35:09.140467: train_loss -0.7521 +2024-11-21 15:35:09.146458: val_loss -0.7464 +2024-11-21 15:35:09.146600: Pseudo dice [0.8299] +2024-11-21 15:35:09.146710: Epoch time: 18.22 s +2024-11-21 15:35:10.290498: +2024-11-21 15:35:10.290723: Epoch 878 +2024-11-21 15:35:10.290848: Current learning rate: 0.00901 +2024-11-21 15:35:29.896201: train_loss -0.7573 +2024-11-21 15:35:29.903293: val_loss -0.7663 +2024-11-21 15:35:29.903418: Pseudo dice [0.8445] +2024-11-21 15:35:29.903525: Epoch time: 19.61 s +2024-11-21 15:35:30.872930: +2024-11-21 15:35:30.873130: Epoch 879 +2024-11-21 15:35:30.873243: Current learning rate: 0.00901 +2024-11-21 15:35:50.169149: train_loss -0.7499 +2024-11-21 15:35:50.174791: val_loss -0.7778 +2024-11-21 15:35:50.174923: Pseudo dice [0.8408] +2024-11-21 15:35:50.175023: Epoch time: 19.3 s +2024-11-21 15:35:50.997906: +2024-11-21 15:35:50.998127: Epoch 880 +2024-11-21 15:35:50.998258: Current learning rate: 0.009 +2024-11-21 15:36:09.781760: train_loss -0.7463 +2024-11-21 15:36:09.786572: val_loss -0.7639 +2024-11-21 15:36:09.786763: Pseudo dice [0.8346] +2024-11-21 15:36:09.786857: Epoch time: 18.78 s +2024-11-21 15:36:10.716469: +2024-11-21 15:36:10.716675: Epoch 881 +2024-11-21 15:36:10.716805: Current learning rate: 0.009 +2024-11-21 15:36:29.857854: train_loss -0.7575 +2024-11-21 15:36:29.865187: val_loss -0.7574 +2024-11-21 15:36:29.865310: Pseudo dice [0.8531] +2024-11-21 15:36:29.865431: Epoch time: 19.14 s +2024-11-21 15:36:31.136476: +2024-11-21 15:36:31.136714: Epoch 882 +2024-11-21 15:36:31.136837: Current learning rate: 0.009 +2024-11-21 15:36:49.206721: train_loss -0.7571 +2024-11-21 15:36:49.213040: val_loss -0.7419 +2024-11-21 15:36:49.213265: Pseudo dice [0.8615] +2024-11-21 15:36:49.213365: Epoch time: 18.07 s +2024-11-21 15:36:50.131696: +2024-11-21 15:36:50.131928: Epoch 883 +2024-11-21 15:36:50.132066: Current learning rate: 0.009 +2024-11-21 15:37:09.991465: train_loss -0.7633 +2024-11-21 15:37:09.993145: val_loss -0.7562 +2024-11-21 15:37:09.993263: Pseudo dice [0.8404] +2024-11-21 15:37:09.993346: Epoch time: 19.86 s +2024-11-21 15:37:10.786801: +2024-11-21 15:37:10.787018: Epoch 884 +2024-11-21 15:37:10.787137: Current learning rate: 0.009 +2024-11-21 15:37:29.110947: train_loss -0.7548 +2024-11-21 15:37:29.115687: val_loss -0.7644 +2024-11-21 15:37:29.115885: Pseudo dice [0.8315] +2024-11-21 15:37:29.115992: Epoch time: 18.32 s +2024-11-21 15:37:29.921299: +2024-11-21 15:37:29.921508: Epoch 885 +2024-11-21 15:37:29.921629: Current learning rate: 0.009 +2024-11-21 15:37:48.739300: train_loss -0.7566 +2024-11-21 15:37:48.746859: val_loss -0.766 +2024-11-21 15:37:48.747010: Pseudo dice [0.8537] +2024-11-21 15:37:48.747109: Epoch time: 18.82 s +2024-11-21 15:37:49.677950: +2024-11-21 15:37:49.678177: Epoch 886 +2024-11-21 15:37:49.678298: Current learning rate: 0.009 +2024-11-21 15:38:08.928534: train_loss -0.7672 +2024-11-21 15:38:08.935210: val_loss -0.7508 +2024-11-21 15:38:08.935340: Pseudo dice [0.8426] +2024-11-21 15:38:08.935518: Epoch time: 19.25 s +2024-11-21 15:38:09.837857: +2024-11-21 15:38:09.838094: Epoch 887 +2024-11-21 15:38:09.838212: Current learning rate: 0.009 +2024-11-21 15:38:28.487884: train_loss -0.7506 +2024-11-21 15:38:28.490412: val_loss -0.7473 +2024-11-21 15:38:28.490540: Pseudo dice [0.8556] +2024-11-21 15:38:28.490644: Epoch time: 18.65 s +2024-11-21 15:38:29.310187: +2024-11-21 15:38:29.310421: Epoch 888 +2024-11-21 15:38:29.310543: Current learning rate: 0.009 +2024-11-21 15:38:48.786798: train_loss -0.7563 +2024-11-21 15:38:48.799753: val_loss -0.7654 +2024-11-21 15:38:48.799901: Pseudo dice [0.8498] +2024-11-21 15:38:48.818930: Epoch time: 19.48 s +2024-11-21 15:38:49.626208: +2024-11-21 15:38:49.626504: Epoch 889 +2024-11-21 15:38:49.626659: Current learning rate: 0.00899 +2024-11-21 15:39:09.336895: train_loss -0.7652 +2024-11-21 15:39:09.343382: val_loss -0.7644 +2024-11-21 15:39:09.343516: Pseudo dice [0.8422] +2024-11-21 15:39:09.343623: Epoch time: 19.71 s +2024-11-21 15:39:10.151671: +2024-11-21 15:39:10.151881: Epoch 890 +2024-11-21 15:39:10.152012: Current learning rate: 0.00899 +2024-11-21 15:39:29.138507: train_loss -0.7627 +2024-11-21 15:39:29.143456: val_loss -0.7792 +2024-11-21 15:39:29.143584: Pseudo dice [0.8551] +2024-11-21 15:39:29.143691: Epoch time: 18.99 s +2024-11-21 15:39:29.947380: +2024-11-21 15:39:29.947580: Epoch 891 +2024-11-21 15:39:29.947697: Current learning rate: 0.00899 +2024-11-21 15:39:48.524712: train_loss -0.7688 +2024-11-21 15:39:48.535429: val_loss -0.7772 +2024-11-21 15:39:48.535618: Pseudo dice [0.8539] +2024-11-21 15:39:48.535708: Epoch time: 18.58 s +2024-11-21 15:39:48.535966: Yayy! New best EMA pseudo Dice: 0.8459 +2024-11-21 15:39:49.896071: +2024-11-21 15:39:49.896286: Epoch 892 +2024-11-21 15:39:49.896409: Current learning rate: 0.00899 +2024-11-21 15:40:08.484249: train_loss -0.7694 +2024-11-21 15:40:08.493573: val_loss -0.772 +2024-11-21 15:40:08.493730: Pseudo dice [0.8412] +2024-11-21 15:40:08.493834: Epoch time: 18.59 s +2024-11-21 15:40:09.329024: +2024-11-21 15:40:09.329236: Epoch 893 +2024-11-21 15:40:09.329368: Current learning rate: 0.00899 +2024-11-21 15:40:27.384001: train_loss -0.7601 +2024-11-21 15:40:27.402029: val_loss -0.7604 +2024-11-21 15:40:27.402289: Pseudo dice [0.8356] +2024-11-21 15:40:27.402431: Epoch time: 18.06 s +2024-11-21 15:40:28.651667: +2024-11-21 15:40:28.651922: Epoch 894 +2024-11-21 15:40:28.652035: Current learning rate: 0.00899 +2024-11-21 15:40:47.580248: train_loss -0.7688 +2024-11-21 15:40:47.595694: val_loss -0.7554 +2024-11-21 15:40:47.595847: Pseudo dice [0.843] +2024-11-21 15:40:47.595948: Epoch time: 18.93 s +2024-11-21 15:40:48.414531: +2024-11-21 15:40:48.414758: Epoch 895 +2024-11-21 15:40:48.414891: Current learning rate: 0.00899 +2024-11-21 15:41:07.755771: train_loss -0.7561 +2024-11-21 15:41:07.763007: val_loss -0.7643 +2024-11-21 15:41:07.763168: Pseudo dice [0.8543] +2024-11-21 15:41:07.763272: Epoch time: 19.34 s +2024-11-21 15:41:08.565188: +2024-11-21 15:41:08.565452: Epoch 896 +2024-11-21 15:41:08.565575: Current learning rate: 0.00899 +2024-11-21 15:41:27.033840: train_loss -0.7566 +2024-11-21 15:41:27.039687: val_loss -0.7488 +2024-11-21 15:41:27.039828: Pseudo dice [0.8355] +2024-11-21 15:41:27.039922: Epoch time: 18.47 s +2024-11-21 15:41:27.861259: +2024-11-21 15:41:27.861459: Epoch 897 +2024-11-21 15:41:27.861587: Current learning rate: 0.00898 +2024-11-21 15:41:45.228697: train_loss -0.7557 +2024-11-21 15:41:45.234789: val_loss -0.7257 +2024-11-21 15:41:45.234915: Pseudo dice [0.8334] +2024-11-21 15:41:45.235015: Epoch time: 17.37 s +2024-11-21 15:41:46.101285: +2024-11-21 15:41:46.101527: Epoch 898 +2024-11-21 15:41:46.101655: Current learning rate: 0.00898 +2024-11-21 15:42:04.584566: train_loss -0.744 +2024-11-21 15:42:04.601888: val_loss -0.744 +2024-11-21 15:42:04.602033: Pseudo dice [0.8317] +2024-11-21 15:42:04.602145: Epoch time: 18.48 s +2024-11-21 15:42:05.422611: +2024-11-21 15:42:05.422824: Epoch 899 +2024-11-21 15:42:05.422958: Current learning rate: 0.00898 +2024-11-21 15:42:24.503125: train_loss -0.76 +2024-11-21 15:42:24.511976: val_loss -0.7474 +2024-11-21 15:42:24.512140: Pseudo dice [0.8507] +2024-11-21 15:42:24.512244: Epoch time: 19.08 s +2024-11-21 15:42:25.546669: +2024-11-21 15:42:25.546878: Epoch 900 +2024-11-21 15:42:25.546999: Current learning rate: 0.00898 +2024-11-21 15:42:44.547547: train_loss -0.7663 +2024-11-21 15:42:44.549272: val_loss -0.7366 +2024-11-21 15:42:44.549423: Pseudo dice [0.8456] +2024-11-21 15:42:44.549515: Epoch time: 19.0 s +2024-11-21 15:42:45.468339: +2024-11-21 15:42:45.468578: Epoch 901 +2024-11-21 15:42:45.468695: Current learning rate: 0.00898 +2024-11-21 15:43:05.257617: train_loss -0.7502 +2024-11-21 15:43:05.263695: val_loss -0.7539 +2024-11-21 15:43:05.263816: Pseudo dice [0.8207] +2024-11-21 15:43:05.263897: Epoch time: 19.79 s +2024-11-21 15:43:06.163442: +2024-11-21 15:43:06.163674: Epoch 902 +2024-11-21 15:43:06.163802: Current learning rate: 0.00898 +2024-11-21 15:43:24.944098: train_loss -0.7383 +2024-11-21 15:43:24.946885: val_loss -0.7537 +2024-11-21 15:43:24.946995: Pseudo dice [0.8387] +2024-11-21 15:43:24.947118: Epoch time: 18.78 s +2024-11-21 15:43:25.751233: +2024-11-21 15:43:25.751441: Epoch 903 +2024-11-21 15:43:25.751572: Current learning rate: 0.00898 +2024-11-21 15:43:44.199105: train_loss -0.7403 +2024-11-21 15:43:44.205095: val_loss -0.7435 +2024-11-21 15:43:44.205244: Pseudo dice [0.8385] +2024-11-21 15:43:44.205344: Epoch time: 18.45 s +2024-11-21 15:43:45.082127: +2024-11-21 15:43:45.082397: Epoch 904 +2024-11-21 15:43:45.082527: Current learning rate: 0.00898 +2024-11-21 15:44:03.536080: train_loss -0.7414 +2024-11-21 15:44:03.543196: val_loss -0.7261 +2024-11-21 15:44:03.543342: Pseudo dice [0.8338] +2024-11-21 15:44:03.543482: Epoch time: 18.45 s +2024-11-21 15:44:04.353280: +2024-11-21 15:44:04.353494: Epoch 905 +2024-11-21 15:44:04.353608: Current learning rate: 0.00898 +2024-11-21 15:44:23.750460: train_loss -0.7376 +2024-11-21 15:44:23.754359: val_loss -0.7516 +2024-11-21 15:44:23.754512: Pseudo dice [0.8404] +2024-11-21 15:44:23.754604: Epoch time: 19.4 s +2024-11-21 15:44:24.991537: +2024-11-21 15:44:24.991756: Epoch 906 +2024-11-21 15:44:24.991887: Current learning rate: 0.00897 +2024-11-21 15:44:43.175931: train_loss -0.7475 +2024-11-21 15:44:43.181900: val_loss -0.7564 +2024-11-21 15:44:43.182018: Pseudo dice [0.8551] +2024-11-21 15:44:43.182118: Epoch time: 18.19 s +2024-11-21 15:44:44.073357: +2024-11-21 15:44:44.073598: Epoch 907 +2024-11-21 15:44:44.073725: Current learning rate: 0.00897 +2024-11-21 15:45:03.221727: train_loss -0.7538 +2024-11-21 15:45:03.228181: val_loss -0.7461 +2024-11-21 15:45:03.228322: Pseudo dice [0.843] +2024-11-21 15:45:03.228406: Epoch time: 19.15 s +2024-11-21 15:45:04.044823: +2024-11-21 15:45:04.045071: Epoch 908 +2024-11-21 15:45:04.045196: Current learning rate: 0.00897 +2024-11-21 15:45:22.825191: train_loss -0.7535 +2024-11-21 15:45:22.830788: val_loss -0.7649 +2024-11-21 15:45:22.830920: Pseudo dice [0.8657] +2024-11-21 15:45:22.831010: Epoch time: 18.78 s +2024-11-21 15:45:23.777852: +2024-11-21 15:45:23.778067: Epoch 909 +2024-11-21 15:45:23.778193: Current learning rate: 0.00897 +2024-11-21 15:45:43.544280: train_loss -0.7673 +2024-11-21 15:45:43.550275: val_loss -0.7298 +2024-11-21 15:45:43.550417: Pseudo dice [0.8439] +2024-11-21 15:45:43.550508: Epoch time: 19.77 s +2024-11-21 15:45:44.474157: +2024-11-21 15:45:44.474406: Epoch 910 +2024-11-21 15:45:44.474561: Current learning rate: 0.00897 +2024-11-21 15:46:03.651184: train_loss -0.7617 +2024-11-21 15:46:03.658716: val_loss -0.7639 +2024-11-21 15:46:03.658859: Pseudo dice [0.834] +2024-11-21 15:46:03.658961: Epoch time: 19.18 s +2024-11-21 15:46:04.620918: +2024-11-21 15:46:04.621143: Epoch 911 +2024-11-21 15:46:04.621261: Current learning rate: 0.00897 +2024-11-21 15:46:23.084939: train_loss -0.7605 +2024-11-21 15:46:23.087264: val_loss -0.7616 +2024-11-21 15:46:23.087409: Pseudo dice [0.8574] +2024-11-21 15:46:23.087512: Epoch time: 18.46 s +2024-11-21 15:46:23.871346: +2024-11-21 15:46:23.871545: Epoch 912 +2024-11-21 15:46:23.871658: Current learning rate: 0.00897 +2024-11-21 15:46:42.665801: train_loss -0.7629 +2024-11-21 15:46:42.678555: val_loss -0.7607 +2024-11-21 15:46:42.678696: Pseudo dice [0.8464] +2024-11-21 15:46:42.678793: Epoch time: 18.8 s +2024-11-21 15:46:43.557406: +2024-11-21 15:46:43.557619: Epoch 913 +2024-11-21 15:46:43.557737: Current learning rate: 0.00897 +2024-11-21 15:47:02.399712: train_loss -0.7582 +2024-11-21 15:47:02.404784: val_loss -0.7621 +2024-11-21 15:47:02.404976: Pseudo dice [0.8493] +2024-11-21 15:47:02.405150: Epoch time: 18.84 s +2024-11-21 15:47:03.211953: +2024-11-21 15:47:03.212426: Epoch 914 +2024-11-21 15:47:03.212550: Current learning rate: 0.00897 +2024-11-21 15:47:23.160396: train_loss -0.7559 +2024-11-21 15:47:23.166119: val_loss -0.767 +2024-11-21 15:47:23.166273: Pseudo dice [0.8509] +2024-11-21 15:47:23.166393: Epoch time: 19.95 s +2024-11-21 15:47:24.078017: +2024-11-21 15:47:24.078226: Epoch 915 +2024-11-21 15:47:24.078348: Current learning rate: 0.00896 +2024-11-21 15:47:43.033090: train_loss -0.7613 +2024-11-21 15:47:43.035741: val_loss -0.764 +2024-11-21 15:47:43.035913: Pseudo dice [0.8648] +2024-11-21 15:47:43.036004: Epoch time: 18.96 s +2024-11-21 15:47:43.036077: Yayy! New best EMA pseudo Dice: 0.8476 +2024-11-21 15:47:44.048037: +2024-11-21 15:47:44.048250: Epoch 916 +2024-11-21 15:47:44.048390: Current learning rate: 0.00896 +2024-11-21 15:48:03.017561: train_loss -0.759 +2024-11-21 15:48:03.023727: val_loss -0.7557 +2024-11-21 15:48:03.023877: Pseudo dice [0.8415] +2024-11-21 15:48:03.023971: Epoch time: 18.97 s +2024-11-21 15:48:03.833632: +2024-11-21 15:48:03.833854: Epoch 917 +2024-11-21 15:48:03.833986: Current learning rate: 0.00896 +2024-11-21 15:48:22.795597: train_loss -0.7575 +2024-11-21 15:48:22.802142: val_loss -0.7685 +2024-11-21 15:48:22.802302: Pseudo dice [0.8464] +2024-11-21 15:48:22.802405: Epoch time: 18.96 s +2024-11-21 15:48:24.024565: +2024-11-21 15:48:24.024796: Epoch 918 +2024-11-21 15:48:24.024914: Current learning rate: 0.00896 +2024-11-21 15:48:43.088022: train_loss -0.7394 +2024-11-21 15:48:43.091830: val_loss -0.7392 +2024-11-21 15:48:43.091959: Pseudo dice [0.8233] +2024-11-21 15:48:43.092073: Epoch time: 19.06 s +2024-11-21 15:48:43.880410: +2024-11-21 15:48:43.880640: Epoch 919 +2024-11-21 15:48:43.880760: Current learning rate: 0.00896 +2024-11-21 15:49:03.163797: train_loss -0.7526 +2024-11-21 15:49:03.176469: val_loss -0.7545 +2024-11-21 15:49:03.176635: Pseudo dice [0.8353] +2024-11-21 15:49:03.176728: Epoch time: 19.28 s +2024-11-21 15:49:04.003371: +2024-11-21 15:49:04.003607: Epoch 920 +2024-11-21 15:49:04.003735: Current learning rate: 0.00896 +2024-11-21 15:49:23.085196: train_loss -0.7445 +2024-11-21 15:49:23.087803: val_loss -0.7696 +2024-11-21 15:49:23.087910: Pseudo dice [0.842] +2024-11-21 15:49:23.088014: Epoch time: 19.08 s +2024-11-21 15:49:23.887024: +2024-11-21 15:49:23.887241: Epoch 921 +2024-11-21 15:49:23.887377: Current learning rate: 0.00896 +2024-11-21 15:49:42.627508: train_loss -0.7511 +2024-11-21 15:49:42.629468: val_loss -0.764 +2024-11-21 15:49:42.629643: Pseudo dice [0.8514] +2024-11-21 15:49:42.629728: Epoch time: 18.74 s +2024-11-21 15:49:43.445631: +2024-11-21 15:49:43.445837: Epoch 922 +2024-11-21 15:49:43.445956: Current learning rate: 0.00896 +2024-11-21 15:50:03.177022: train_loss -0.7482 +2024-11-21 15:50:03.182682: val_loss -0.7654 +2024-11-21 15:50:03.182818: Pseudo dice [0.8357] +2024-11-21 15:50:03.182912: Epoch time: 19.73 s +2024-11-21 15:50:03.993662: +2024-11-21 15:50:03.993868: Epoch 923 +2024-11-21 15:50:03.993989: Current learning rate: 0.00896 +2024-11-21 15:50:22.540987: train_loss -0.7594 +2024-11-21 15:50:22.550270: val_loss -0.7525 +2024-11-21 15:50:22.550416: Pseudo dice [0.8434] +2024-11-21 15:50:22.550506: Epoch time: 18.55 s +2024-11-21 15:50:23.350940: +2024-11-21 15:50:23.351185: Epoch 924 +2024-11-21 15:50:23.351319: Current learning rate: 0.00895 +2024-11-21 15:50:42.866923: train_loss -0.7568 +2024-11-21 15:50:42.874453: val_loss -0.7491 +2024-11-21 15:50:42.874605: Pseudo dice [0.8364] +2024-11-21 15:50:42.874705: Epoch time: 19.52 s +2024-11-21 15:50:43.683166: +2024-11-21 15:50:43.683404: Epoch 925 +2024-11-21 15:50:43.683547: Current learning rate: 0.00895 +2024-11-21 15:51:03.805201: train_loss -0.7552 +2024-11-21 15:51:03.809804: val_loss -0.7537 +2024-11-21 15:51:03.809934: Pseudo dice [0.8297] +2024-11-21 15:51:03.810040: Epoch time: 20.12 s +2024-11-21 15:51:04.607873: +2024-11-21 15:51:04.608126: Epoch 926 +2024-11-21 15:51:04.608253: Current learning rate: 0.00895 +2024-11-21 15:51:24.035683: train_loss -0.7439 +2024-11-21 15:51:24.061137: val_loss -0.7417 +2024-11-21 15:51:24.061336: Pseudo dice [0.8257] +2024-11-21 15:51:24.061446: Epoch time: 19.43 s +2024-11-21 15:51:25.016563: +2024-11-21 15:51:25.016775: Epoch 927 +2024-11-21 15:51:25.016912: Current learning rate: 0.00895 +2024-11-21 15:51:44.107992: train_loss -0.7588 +2024-11-21 15:51:44.113227: val_loss -0.7473 +2024-11-21 15:51:44.113352: Pseudo dice [0.8447] +2024-11-21 15:51:44.113462: Epoch time: 19.09 s +2024-11-21 15:51:45.217422: +2024-11-21 15:51:45.217704: Epoch 928 +2024-11-21 15:51:45.217830: Current learning rate: 0.00895 +2024-11-21 15:52:05.658068: train_loss -0.7631 +2024-11-21 15:52:05.660703: val_loss -0.7629 +2024-11-21 15:52:05.660836: Pseudo dice [0.849] +2024-11-21 15:52:05.660949: Epoch time: 20.44 s +2024-11-21 15:52:06.550462: +2024-11-21 15:52:06.550724: Epoch 929 +2024-11-21 15:52:06.550851: Current learning rate: 0.00895 +2024-11-21 15:52:26.160803: train_loss -0.7647 +2024-11-21 15:52:26.165625: val_loss -0.7774 +2024-11-21 15:52:26.165773: Pseudo dice [0.8406] +2024-11-21 15:52:26.165871: Epoch time: 19.61 s +2024-11-21 15:52:27.339316: +2024-11-21 15:52:27.339551: Epoch 930 +2024-11-21 15:52:27.339679: Current learning rate: 0.00895 +2024-11-21 15:52:46.924170: train_loss -0.7597 +2024-11-21 15:52:46.929262: val_loss -0.7605 +2024-11-21 15:52:46.929379: Pseudo dice [0.8365] +2024-11-21 15:52:46.929478: Epoch time: 19.59 s +2024-11-21 15:52:47.734156: +2024-11-21 15:52:47.734396: Epoch 931 +2024-11-21 15:52:47.734522: Current learning rate: 0.00895 +2024-11-21 15:53:06.580577: train_loss -0.7557 +2024-11-21 15:53:06.586489: val_loss -0.765 +2024-11-21 15:53:06.586626: Pseudo dice [0.8179] +2024-11-21 15:53:06.586731: Epoch time: 18.85 s +2024-11-21 15:53:07.394409: +2024-11-21 15:53:07.394647: Epoch 932 +2024-11-21 15:53:07.394769: Current learning rate: 0.00895 +2024-11-21 15:53:27.905666: train_loss -0.7615 +2024-11-21 15:53:27.911749: val_loss -0.7629 +2024-11-21 15:53:27.911896: Pseudo dice [0.8445] +2024-11-21 15:53:27.911986: Epoch time: 20.51 s +2024-11-21 15:53:28.734961: +2024-11-21 15:53:28.735161: Epoch 933 +2024-11-21 15:53:28.735291: Current learning rate: 0.00894 +2024-11-21 15:53:46.863820: train_loss -0.7603 +2024-11-21 15:53:46.867861: val_loss -0.7462 +2024-11-21 15:53:46.868018: Pseudo dice [0.8352] +2024-11-21 15:53:46.868123: Epoch time: 18.13 s +2024-11-21 15:53:47.676034: +2024-11-21 15:53:47.676257: Epoch 934 +2024-11-21 15:53:47.676416: Current learning rate: 0.00894 +2024-11-21 15:54:06.796547: train_loss -0.7575 +2024-11-21 15:54:06.812022: val_loss -0.7388 +2024-11-21 15:54:06.824378: Pseudo dice [0.8394] +2024-11-21 15:54:06.824497: Epoch time: 19.12 s +2024-11-21 15:54:07.737574: +2024-11-21 15:54:07.737797: Epoch 935 +2024-11-21 15:54:07.737919: Current learning rate: 0.00894 +2024-11-21 15:54:26.670127: train_loss -0.762 +2024-11-21 15:54:26.676241: val_loss -0.7817 +2024-11-21 15:54:26.676362: Pseudo dice [0.8603] +2024-11-21 15:54:26.676463: Epoch time: 18.93 s +2024-11-21 15:54:27.620382: +2024-11-21 15:54:27.620608: Epoch 936 +2024-11-21 15:54:27.620733: Current learning rate: 0.00894 +2024-11-21 15:54:46.848923: train_loss -0.7533 +2024-11-21 15:54:46.851817: val_loss -0.7607 +2024-11-21 15:54:46.851953: Pseudo dice [0.8401] +2024-11-21 15:54:46.852049: Epoch time: 19.23 s +2024-11-21 15:54:47.736491: +2024-11-21 15:54:47.736744: Epoch 937 +2024-11-21 15:54:47.736879: Current learning rate: 0.00894 +2024-11-21 15:55:06.717002: train_loss -0.7474 +2024-11-21 15:55:06.720174: val_loss -0.7576 +2024-11-21 15:55:06.720294: Pseudo dice [0.8487] +2024-11-21 15:55:06.720380: Epoch time: 18.98 s +2024-11-21 15:55:07.513148: +2024-11-21 15:55:07.513361: Epoch 938 +2024-11-21 15:55:07.513479: Current learning rate: 0.00894 +2024-11-21 15:55:26.088927: train_loss -0.7334 +2024-11-21 15:55:26.094759: val_loss -0.7275 +2024-11-21 15:55:26.094884: Pseudo dice [0.8225] +2024-11-21 15:55:26.094978: Epoch time: 18.58 s +2024-11-21 15:55:26.906667: +2024-11-21 15:55:26.906873: Epoch 939 +2024-11-21 15:55:26.907010: Current learning rate: 0.00894 +2024-11-21 15:55:45.273057: train_loss -0.7591 +2024-11-21 15:55:45.275206: val_loss -0.7381 +2024-11-21 15:55:45.275346: Pseudo dice [0.8343] +2024-11-21 15:55:45.275445: Epoch time: 18.37 s +2024-11-21 15:55:46.124618: +2024-11-21 15:55:46.124822: Epoch 940 +2024-11-21 15:55:46.124954: Current learning rate: 0.00894 +2024-11-21 15:56:05.091669: train_loss -0.7604 +2024-11-21 15:56:05.094225: val_loss -0.7479 +2024-11-21 15:56:05.094343: Pseudo dice [0.8389] +2024-11-21 15:56:05.094427: Epoch time: 18.97 s +2024-11-21 15:56:05.972948: +2024-11-21 15:56:05.973186: Epoch 941 +2024-11-21 15:56:05.973299: Current learning rate: 0.00893 +2024-11-21 15:56:25.922974: train_loss -0.7445 +2024-11-21 15:56:25.928635: val_loss -0.7637 +2024-11-21 15:56:25.928781: Pseudo dice [0.8448] +2024-11-21 15:56:25.928898: Epoch time: 19.95 s +2024-11-21 15:56:27.141802: +2024-11-21 15:56:27.142024: Epoch 942 +2024-11-21 15:56:27.142149: Current learning rate: 0.00893 +2024-11-21 15:56:46.246792: train_loss -0.7562 +2024-11-21 15:56:46.258496: val_loss -0.7588 +2024-11-21 15:56:46.258642: Pseudo dice [0.8582] +2024-11-21 15:56:46.258749: Epoch time: 19.11 s +2024-11-21 15:56:47.134706: +2024-11-21 15:56:47.134928: Epoch 943 +2024-11-21 15:56:47.135055: Current learning rate: 0.00893 +2024-11-21 15:57:06.546249: train_loss -0.7592 +2024-11-21 15:57:06.553112: val_loss -0.7575 +2024-11-21 15:57:06.553260: Pseudo dice [0.8482] +2024-11-21 15:57:06.553351: Epoch time: 19.41 s +2024-11-21 15:57:07.378479: +2024-11-21 15:57:07.378678: Epoch 944 +2024-11-21 15:57:07.378817: Current learning rate: 0.00893 +2024-11-21 15:57:26.356579: train_loss -0.7573 +2024-11-21 15:57:26.361784: val_loss -0.7551 +2024-11-21 15:57:26.361923: Pseudo dice [0.8423] +2024-11-21 15:57:26.362010: Epoch time: 18.98 s +2024-11-21 15:57:27.152119: +2024-11-21 15:57:27.152333: Epoch 945 +2024-11-21 15:57:27.152475: Current learning rate: 0.00893 +2024-11-21 15:57:45.940763: train_loss -0.7669 +2024-11-21 15:57:45.948496: val_loss -0.771 +2024-11-21 15:57:45.948619: Pseudo dice [0.8577] +2024-11-21 15:57:45.948711: Epoch time: 18.79 s +2024-11-21 15:57:46.802928: +2024-11-21 15:57:46.803153: Epoch 946 +2024-11-21 15:57:46.803288: Current learning rate: 0.00893 +2024-11-21 15:58:05.300896: train_loss -0.7493 +2024-11-21 15:58:05.321983: val_loss -0.7641 +2024-11-21 15:58:05.322139: Pseudo dice [0.8419] +2024-11-21 15:58:05.322251: Epoch time: 18.5 s +2024-11-21 15:58:06.339856: +2024-11-21 15:58:06.340120: Epoch 947 +2024-11-21 15:58:06.340239: Current learning rate: 0.00893 +2024-11-21 15:58:24.952717: train_loss -0.7546 +2024-11-21 15:58:24.959171: val_loss -0.7469 +2024-11-21 15:58:24.959329: Pseudo dice [0.8415] +2024-11-21 15:58:24.959426: Epoch time: 18.61 s +2024-11-21 15:58:25.880016: +2024-11-21 15:58:25.880236: Epoch 948 +2024-11-21 15:58:25.880370: Current learning rate: 0.00893 +2024-11-21 15:58:46.180455: train_loss -0.7596 +2024-11-21 15:58:46.193562: val_loss -0.779 +2024-11-21 15:58:46.193699: Pseudo dice [0.8438] +2024-11-21 15:58:46.193792: Epoch time: 20.3 s +2024-11-21 15:58:47.057200: +2024-11-21 15:58:47.057396: Epoch 949 +2024-11-21 15:58:47.057520: Current learning rate: 0.00893 +2024-11-21 15:59:06.148118: train_loss -0.7597 +2024-11-21 15:59:06.156803: val_loss -0.7575 +2024-11-21 15:59:06.156965: Pseudo dice [0.8456] +2024-11-21 15:59:06.157122: Epoch time: 19.09 s +2024-11-21 15:59:07.200505: +2024-11-21 15:59:07.200911: Epoch 950 +2024-11-21 15:59:07.201046: Current learning rate: 0.00892 +2024-11-21 15:59:27.438079: train_loss -0.7706 +2024-11-21 15:59:27.451044: val_loss -0.7552 +2024-11-21 15:59:27.451236: Pseudo dice [0.8352] +2024-11-21 15:59:27.451349: Epoch time: 20.24 s +2024-11-21 15:59:28.420743: +2024-11-21 15:59:28.420963: Epoch 951 +2024-11-21 15:59:28.421098: Current learning rate: 0.00892 +2024-11-21 15:59:48.401333: train_loss -0.7629 +2024-11-21 15:59:48.405550: val_loss -0.7762 +2024-11-21 15:59:48.405679: Pseudo dice [0.8406] +2024-11-21 15:59:48.405767: Epoch time: 19.98 s +2024-11-21 15:59:49.218580: +2024-11-21 15:59:49.237459: Epoch 952 +2024-11-21 15:59:49.237623: Current learning rate: 0.00892 +2024-11-21 16:00:08.837277: train_loss -0.7578 +2024-11-21 16:00:08.840547: val_loss -0.7731 +2024-11-21 16:00:08.840657: Pseudo dice [0.8555] +2024-11-21 16:00:08.840746: Epoch time: 19.62 s +2024-11-21 16:00:09.633667: +2024-11-21 16:00:09.633943: Epoch 953 +2024-11-21 16:00:09.634071: Current learning rate: 0.00892 +2024-11-21 16:00:27.596534: train_loss -0.7526 +2024-11-21 16:00:27.604614: val_loss -0.7453 +2024-11-21 16:00:27.604734: Pseudo dice [0.8319] +2024-11-21 16:00:27.604824: Epoch time: 17.96 s +2024-11-21 16:00:28.999170: +2024-11-21 16:00:28.999370: Epoch 954 +2024-11-21 16:00:28.999489: Current learning rate: 0.00892 +2024-11-21 16:00:46.910596: train_loss -0.7614 +2024-11-21 16:00:46.922874: val_loss -0.7663 +2024-11-21 16:00:46.922993: Pseudo dice [0.8426] +2024-11-21 16:00:46.923088: Epoch time: 17.91 s +2024-11-21 16:00:47.722503: +2024-11-21 16:00:47.722749: Epoch 955 +2024-11-21 16:00:47.722884: Current learning rate: 0.00892 +2024-11-21 16:01:06.231798: train_loss -0.7634 +2024-11-21 16:01:06.239271: val_loss -0.7652 +2024-11-21 16:01:06.239404: Pseudo dice [0.8593] +2024-11-21 16:01:06.239499: Epoch time: 18.51 s +2024-11-21 16:01:07.147638: +2024-11-21 16:01:07.147957: Epoch 956 +2024-11-21 16:01:07.148108: Current learning rate: 0.00892 +2024-11-21 16:01:25.429657: train_loss -0.7547 +2024-11-21 16:01:25.435329: val_loss -0.7613 +2024-11-21 16:01:25.435477: Pseudo dice [0.8341] +2024-11-21 16:01:25.435589: Epoch time: 18.28 s +2024-11-21 16:01:26.300284: +2024-11-21 16:01:26.300493: Epoch 957 +2024-11-21 16:01:26.300630: Current learning rate: 0.00892 +2024-11-21 16:01:45.422191: train_loss -0.7417 +2024-11-21 16:01:45.426116: val_loss -0.7512 +2024-11-21 16:01:45.426237: Pseudo dice [0.8295] +2024-11-21 16:01:45.426340: Epoch time: 19.12 s +2024-11-21 16:01:46.231971: +2024-11-21 16:01:46.232185: Epoch 958 +2024-11-21 16:01:46.232319: Current learning rate: 0.00892 +2024-11-21 16:02:05.439375: train_loss -0.7703 +2024-11-21 16:02:05.457907: val_loss -0.7563 +2024-11-21 16:02:05.458051: Pseudo dice [0.8328] +2024-11-21 16:02:05.458159: Epoch time: 19.21 s +2024-11-21 16:02:06.357924: +2024-11-21 16:02:06.358131: Epoch 959 +2024-11-21 16:02:06.358265: Current learning rate: 0.00891 +2024-11-21 16:02:25.995603: train_loss -0.7616 +2024-11-21 16:02:26.002901: val_loss -0.7518 +2024-11-21 16:02:26.003036: Pseudo dice [0.8414] +2024-11-21 16:02:26.003139: Epoch time: 19.64 s +2024-11-21 16:02:26.920941: +2024-11-21 16:02:26.921154: Epoch 960 +2024-11-21 16:02:26.921274: Current learning rate: 0.00891 +2024-11-21 16:02:45.825157: train_loss -0.7502 +2024-11-21 16:02:45.839725: val_loss -0.7642 +2024-11-21 16:02:45.839869: Pseudo dice [0.8491] +2024-11-21 16:02:45.839965: Epoch time: 18.91 s +2024-11-21 16:02:46.706097: +2024-11-21 16:02:46.706337: Epoch 961 +2024-11-21 16:02:46.706457: Current learning rate: 0.00891 +2024-11-21 16:03:05.525209: train_loss -0.7511 +2024-11-21 16:03:05.532650: val_loss -0.7376 +2024-11-21 16:03:05.532772: Pseudo dice [0.8315] +2024-11-21 16:03:05.532881: Epoch time: 18.82 s +2024-11-21 16:03:06.441540: +2024-11-21 16:03:06.441963: Epoch 962 +2024-11-21 16:03:06.442107: Current learning rate: 0.00891 +2024-11-21 16:03:25.452400: train_loss -0.7487 +2024-11-21 16:03:25.459472: val_loss -0.773 +2024-11-21 16:03:25.459612: Pseudo dice [0.8454] +2024-11-21 16:03:25.459783: Epoch time: 19.01 s +2024-11-21 16:03:26.413265: +2024-11-21 16:03:26.413479: Epoch 963 +2024-11-21 16:03:26.413606: Current learning rate: 0.00891 +2024-11-21 16:03:45.623464: train_loss -0.7523 +2024-11-21 16:03:45.637030: val_loss -0.7693 +2024-11-21 16:03:45.637189: Pseudo dice [0.8598] +2024-11-21 16:03:45.637300: Epoch time: 19.21 s +2024-11-21 16:03:46.628824: +2024-11-21 16:03:46.629081: Epoch 964 +2024-11-21 16:03:46.629224: Current learning rate: 0.00891 +2024-11-21 16:04:05.895003: train_loss -0.7622 +2024-11-21 16:04:05.905879: val_loss -0.7603 +2024-11-21 16:04:05.906032: Pseudo dice [0.8471] +2024-11-21 16:04:05.906410: Epoch time: 19.27 s +2024-11-21 16:04:06.828573: +2024-11-21 16:04:06.828791: Epoch 965 +2024-11-21 16:04:06.828910: Current learning rate: 0.00891 +2024-11-21 16:04:26.805920: train_loss -0.7585 +2024-11-21 16:04:26.816970: val_loss -0.7322 +2024-11-21 16:04:26.817127: Pseudo dice [0.7986] +2024-11-21 16:04:26.817247: Epoch time: 19.98 s +2024-11-21 16:04:28.051112: +2024-11-21 16:04:28.051325: Epoch 966 +2024-11-21 16:04:28.051450: Current learning rate: 0.00891 +2024-11-21 16:04:47.097522: train_loss -0.734 +2024-11-21 16:04:47.106145: val_loss -0.749 +2024-11-21 16:04:47.106286: Pseudo dice [0.8357] +2024-11-21 16:04:47.106375: Epoch time: 19.05 s +2024-11-21 16:04:47.923962: +2024-11-21 16:04:47.924184: Epoch 967 +2024-11-21 16:04:47.924312: Current learning rate: 0.00891 +2024-11-21 16:05:06.981639: train_loss -0.7459 +2024-11-21 16:05:06.984199: val_loss -0.7544 +2024-11-21 16:05:06.984313: Pseudo dice [0.8332] +2024-11-21 16:05:06.984447: Epoch time: 19.06 s +2024-11-21 16:05:07.785682: +2024-11-21 16:05:07.785920: Epoch 968 +2024-11-21 16:05:07.786043: Current learning rate: 0.0089 +2024-11-21 16:05:27.424167: train_loss -0.7441 +2024-11-21 16:05:27.431192: val_loss -0.7743 +2024-11-21 16:05:27.431389: Pseudo dice [0.8356] +2024-11-21 16:05:27.431499: Epoch time: 19.64 s +2024-11-21 16:05:28.383321: +2024-11-21 16:05:28.383529: Epoch 969 +2024-11-21 16:05:28.383645: Current learning rate: 0.0089 +2024-11-21 16:05:46.352322: train_loss -0.7591 +2024-11-21 16:05:46.361162: val_loss -0.7651 +2024-11-21 16:05:46.361327: Pseudo dice [0.8316] +2024-11-21 16:05:46.361465: Epoch time: 17.97 s +2024-11-21 16:05:47.390525: +2024-11-21 16:05:47.390742: Epoch 970 +2024-11-21 16:05:47.390859: Current learning rate: 0.0089 +2024-11-21 16:06:06.778461: train_loss -0.7454 +2024-11-21 16:06:06.783950: val_loss -0.7432 +2024-11-21 16:06:06.784096: Pseudo dice [0.8335] +2024-11-21 16:06:06.784199: Epoch time: 19.39 s +2024-11-21 16:06:07.636426: +2024-11-21 16:06:07.636693: Epoch 971 +2024-11-21 16:06:07.636811: Current learning rate: 0.0089 +2024-11-21 16:06:27.244986: train_loss -0.7526 +2024-11-21 16:06:27.251767: val_loss -0.7723 +2024-11-21 16:06:27.251913: Pseudo dice [0.8397] +2024-11-21 16:06:27.252007: Epoch time: 19.61 s +2024-11-21 16:06:28.227066: +2024-11-21 16:06:28.227268: Epoch 972 +2024-11-21 16:06:28.227401: Current learning rate: 0.0089 +2024-11-21 16:06:45.939590: train_loss -0.7595 +2024-11-21 16:06:45.944493: val_loss -0.763 +2024-11-21 16:06:45.944626: Pseudo dice [0.8342] +2024-11-21 16:06:45.944724: Epoch time: 17.71 s +2024-11-21 16:06:46.799955: +2024-11-21 16:06:46.800177: Epoch 973 +2024-11-21 16:06:46.800314: Current learning rate: 0.0089 +2024-11-21 16:07:07.460035: train_loss -0.7657 +2024-11-21 16:07:07.470317: val_loss -0.7771 +2024-11-21 16:07:07.470457: Pseudo dice [0.8496] +2024-11-21 16:07:07.470545: Epoch time: 20.66 s +2024-11-21 16:07:08.286371: +2024-11-21 16:07:08.286578: Epoch 974 +2024-11-21 16:07:08.286701: Current learning rate: 0.0089 +2024-11-21 16:07:27.959772: train_loss -0.7637 +2024-11-21 16:07:27.965969: val_loss -0.7582 +2024-11-21 16:07:27.966118: Pseudo dice [0.8488] +2024-11-21 16:07:27.966203: Epoch time: 19.67 s +2024-11-21 16:07:28.955125: +2024-11-21 16:07:28.955320: Epoch 975 +2024-11-21 16:07:28.955437: Current learning rate: 0.0089 +2024-11-21 16:07:47.921323: train_loss -0.7582 +2024-11-21 16:07:47.925602: val_loss -0.7645 +2024-11-21 16:07:47.925743: Pseudo dice [0.846] +2024-11-21 16:07:47.925840: Epoch time: 18.97 s +2024-11-21 16:07:48.957265: +2024-11-21 16:07:48.957451: Epoch 976 +2024-11-21 16:07:48.957585: Current learning rate: 0.00889 +2024-11-21 16:08:07.914598: train_loss -0.7529 +2024-11-21 16:08:07.922592: val_loss -0.7461 +2024-11-21 16:08:07.922759: Pseudo dice [0.8443] +2024-11-21 16:08:07.922861: Epoch time: 18.96 s +2024-11-21 16:08:08.834877: +2024-11-21 16:08:08.835074: Epoch 977 +2024-11-21 16:08:08.835202: Current learning rate: 0.00889 +2024-11-21 16:08:27.729646: train_loss -0.7475 +2024-11-21 16:08:27.777209: val_loss -0.7477 +2024-11-21 16:08:27.777378: Pseudo dice [0.8373] +2024-11-21 16:08:27.777470: Epoch time: 18.9 s +2024-11-21 16:08:29.027055: +2024-11-21 16:08:29.027293: Epoch 978 +2024-11-21 16:08:29.027418: Current learning rate: 0.00889 +2024-11-21 16:08:48.198513: train_loss -0.7468 +2024-11-21 16:08:48.203258: val_loss -0.7687 +2024-11-21 16:08:48.203408: Pseudo dice [0.8392] +2024-11-21 16:08:48.203525: Epoch time: 19.17 s +2024-11-21 16:08:49.122438: +2024-11-21 16:08:49.122712: Epoch 979 +2024-11-21 16:08:49.122828: Current learning rate: 0.00889 +2024-11-21 16:09:07.068769: train_loss -0.7448 +2024-11-21 16:09:07.074332: val_loss -0.7201 +2024-11-21 16:09:07.074459: Pseudo dice [0.828] +2024-11-21 16:09:07.074567: Epoch time: 17.95 s +2024-11-21 16:09:07.968764: +2024-11-21 16:09:07.969027: Epoch 980 +2024-11-21 16:09:07.969158: Current learning rate: 0.00889 +2024-11-21 16:09:27.740782: train_loss -0.7514 +2024-11-21 16:09:27.747711: val_loss -0.7362 +2024-11-21 16:09:27.747852: Pseudo dice [0.8306] +2024-11-21 16:09:27.747939: Epoch time: 19.77 s +2024-11-21 16:09:28.739321: +2024-11-21 16:09:28.739561: Epoch 981 +2024-11-21 16:09:28.739687: Current learning rate: 0.00889 +2024-11-21 16:09:48.295298: train_loss -0.7641 +2024-11-21 16:09:48.318383: val_loss -0.761 +2024-11-21 16:09:48.318528: Pseudo dice [0.8413] +2024-11-21 16:09:48.318630: Epoch time: 19.56 s +2024-11-21 16:09:49.183218: +2024-11-21 16:09:49.183451: Epoch 982 +2024-11-21 16:09:49.183566: Current learning rate: 0.00889 +2024-11-21 16:10:09.160943: train_loss -0.7495 +2024-11-21 16:10:09.166194: val_loss -0.7543 +2024-11-21 16:10:09.166390: Pseudo dice [0.8569] +2024-11-21 16:10:09.166492: Epoch time: 19.98 s +2024-11-21 16:10:10.002124: +2024-11-21 16:10:10.002341: Epoch 983 +2024-11-21 16:10:10.002461: Current learning rate: 0.00889 +2024-11-21 16:10:28.853496: train_loss -0.7643 +2024-11-21 16:10:28.858676: val_loss -0.7484 +2024-11-21 16:10:28.858804: Pseudo dice [0.8539] +2024-11-21 16:10:28.858892: Epoch time: 18.85 s +2024-11-21 16:10:29.662278: +2024-11-21 16:10:29.662507: Epoch 984 +2024-11-21 16:10:29.662642: Current learning rate: 0.00889 +2024-11-21 16:10:49.172755: train_loss -0.7725 +2024-11-21 16:10:49.179813: val_loss -0.7795 +2024-11-21 16:10:49.179960: Pseudo dice [0.853] +2024-11-21 16:10:49.180053: Epoch time: 19.51 s +2024-11-21 16:10:50.002188: +2024-11-21 16:10:50.002407: Epoch 985 +2024-11-21 16:10:50.002537: Current learning rate: 0.00888 +2024-11-21 16:11:09.641737: train_loss -0.7691 +2024-11-21 16:11:09.649742: val_loss -0.7574 +2024-11-21 16:11:09.649862: Pseudo dice [0.8377] +2024-11-21 16:11:09.649959: Epoch time: 19.64 s +2024-11-21 16:11:10.669326: +2024-11-21 16:11:10.669550: Epoch 986 +2024-11-21 16:11:10.669690: Current learning rate: 0.00888 +2024-11-21 16:11:29.713717: train_loss -0.7561 +2024-11-21 16:11:29.718515: val_loss -0.771 +2024-11-21 16:11:29.718665: Pseudo dice [0.8444] +2024-11-21 16:11:29.718788: Epoch time: 19.04 s +2024-11-21 16:11:30.672140: +2024-11-21 16:11:30.672339: Epoch 987 +2024-11-21 16:11:30.672470: Current learning rate: 0.00888 +2024-11-21 16:11:49.004647: train_loss -0.7636 +2024-11-21 16:11:49.011526: val_loss -0.7442 +2024-11-21 16:11:49.011686: Pseudo dice [0.8437] +2024-11-21 16:11:49.011773: Epoch time: 18.33 s +2024-11-21 16:11:49.812707: +2024-11-21 16:11:49.812917: Epoch 988 +2024-11-21 16:11:49.813035: Current learning rate: 0.00888 +2024-11-21 16:12:08.730332: train_loss -0.7652 +2024-11-21 16:12:08.735682: val_loss -0.7662 +2024-11-21 16:12:08.735815: Pseudo dice [0.8456] +2024-11-21 16:12:08.735915: Epoch time: 18.92 s +2024-11-21 16:12:09.578113: +2024-11-21 16:12:09.578329: Epoch 989 +2024-11-21 16:12:09.578471: Current learning rate: 0.00888 +2024-11-21 16:12:28.243026: train_loss -0.7564 +2024-11-21 16:12:28.246003: val_loss -0.7328 +2024-11-21 16:12:28.246117: Pseudo dice [0.8262] +2024-11-21 16:12:28.246248: Epoch time: 18.67 s +2024-11-21 16:12:29.436887: +2024-11-21 16:12:29.437150: Epoch 990 +2024-11-21 16:12:29.437272: Current learning rate: 0.00888 +2024-11-21 16:12:49.224994: train_loss -0.755 +2024-11-21 16:12:49.227309: val_loss -0.7551 +2024-11-21 16:12:49.227409: Pseudo dice [0.8341] +2024-11-21 16:12:49.227495: Epoch time: 19.79 s +2024-11-21 16:12:50.032085: +2024-11-21 16:12:50.032310: Epoch 991 +2024-11-21 16:12:50.032445: Current learning rate: 0.00888 +2024-11-21 16:13:10.978475: train_loss -0.7588 +2024-11-21 16:13:10.981121: val_loss -0.7457 +2024-11-21 16:13:10.981227: Pseudo dice [0.8437] +2024-11-21 16:13:10.981323: Epoch time: 20.95 s +2024-11-21 16:13:11.785025: +2024-11-21 16:13:11.785289: Epoch 992 +2024-11-21 16:13:11.785411: Current learning rate: 0.00888 +2024-11-21 16:13:30.087384: train_loss -0.765 +2024-11-21 16:13:30.094601: val_loss -0.7518 +2024-11-21 16:13:30.094756: Pseudo dice [0.8307] +2024-11-21 16:13:30.094849: Epoch time: 18.3 s +2024-11-21 16:13:30.912503: +2024-11-21 16:13:30.912732: Epoch 993 +2024-11-21 16:13:30.912878: Current learning rate: 0.00888 +2024-11-21 16:13:49.439261: train_loss -0.7639 +2024-11-21 16:13:49.448352: val_loss -0.7616 +2024-11-21 16:13:49.448519: Pseudo dice [0.8468] +2024-11-21 16:13:49.448633: Epoch time: 18.53 s +2024-11-21 16:13:50.275018: +2024-11-21 16:13:50.275248: Epoch 994 +2024-11-21 16:13:50.275365: Current learning rate: 0.00887 +2024-11-21 16:14:08.881962: train_loss -0.7575 +2024-11-21 16:14:08.889596: val_loss -0.7691 +2024-11-21 16:14:08.889731: Pseudo dice [0.8534] +2024-11-21 16:14:08.889833: Epoch time: 18.61 s +2024-11-21 16:14:09.706919: +2024-11-21 16:14:09.707155: Epoch 995 +2024-11-21 16:14:09.707285: Current learning rate: 0.00887 +2024-11-21 16:14:28.591107: train_loss -0.7482 +2024-11-21 16:14:28.597182: val_loss -0.7594 +2024-11-21 16:14:28.597321: Pseudo dice [0.8326] +2024-11-21 16:14:28.597445: Epoch time: 18.89 s +2024-11-21 16:14:29.410660: +2024-11-21 16:14:29.410867: Epoch 996 +2024-11-21 16:14:29.411005: Current learning rate: 0.00887 +2024-11-21 16:14:49.200319: train_loss -0.7627 +2024-11-21 16:14:49.203323: val_loss -0.778 +2024-11-21 16:14:49.203461: Pseudo dice [0.8511] +2024-11-21 16:14:49.203542: Epoch time: 19.79 s +2024-11-21 16:14:50.183633: +2024-11-21 16:14:50.183851: Epoch 997 +2024-11-21 16:14:50.183992: Current learning rate: 0.00887 +2024-11-21 16:15:10.207899: train_loss -0.7533 +2024-11-21 16:15:10.215798: val_loss -0.7606 +2024-11-21 16:15:10.215939: Pseudo dice [0.8574] +2024-11-21 16:15:10.216066: Epoch time: 20.03 s +2024-11-21 16:15:11.034770: +2024-11-21 16:15:11.034976: Epoch 998 +2024-11-21 16:15:11.035105: Current learning rate: 0.00887 +2024-11-21 16:15:31.091220: train_loss -0.74 +2024-11-21 16:15:31.094006: val_loss -0.7485 +2024-11-21 16:15:31.094119: Pseudo dice [0.8512] +2024-11-21 16:15:31.094218: Epoch time: 20.06 s +2024-11-21 16:15:31.896364: +2024-11-21 16:15:31.896566: Epoch 999 +2024-11-21 16:15:31.896696: Current learning rate: 0.00887 +2024-11-21 16:15:50.650223: train_loss -0.7577 +2024-11-21 16:15:50.655865: val_loss -0.7298 +2024-11-21 16:15:50.655972: Pseudo dice [0.8287] +2024-11-21 16:15:50.656077: Epoch time: 18.75 s +2024-11-21 16:15:51.735009: +2024-11-21 16:15:51.735228: Epoch 1000 +2024-11-21 16:15:51.735372: Current learning rate: 0.00887 +2024-11-21 16:16:11.068712: train_loss -0.7582 +2024-11-21 16:16:11.071130: val_loss -0.7521 +2024-11-21 16:16:11.071254: Pseudo dice [0.8456] +2024-11-21 16:16:11.071372: Epoch time: 19.33 s +2024-11-21 16:16:11.879072: +2024-11-21 16:16:11.879525: Epoch 1001 +2024-11-21 16:16:11.879664: Current learning rate: 0.00887 +2024-11-21 16:16:31.594240: train_loss -0.7543 +2024-11-21 16:16:31.602163: val_loss -0.7659 +2024-11-21 16:16:31.602311: Pseudo dice [0.8493] +2024-11-21 16:16:31.602399: Epoch time: 19.72 s +2024-11-21 16:16:32.395634: +2024-11-21 16:16:32.395882: Epoch 1002 +2024-11-21 16:16:32.396009: Current learning rate: 0.00887 +2024-11-21 16:16:51.564855: train_loss -0.7555 +2024-11-21 16:16:51.572659: val_loss -0.775 +2024-11-21 16:16:51.572808: Pseudo dice [0.85] +2024-11-21 16:16:51.572906: Epoch time: 19.17 s +2024-11-21 16:16:52.638154: +2024-11-21 16:16:52.638366: Epoch 1003 +2024-11-21 16:16:52.638482: Current learning rate: 0.00886 +2024-11-21 16:17:11.774011: train_loss -0.7463 +2024-11-21 16:17:11.776602: val_loss -0.735 +2024-11-21 16:17:11.776726: Pseudo dice [0.8382] +2024-11-21 16:17:11.776819: Epoch time: 19.14 s +2024-11-21 16:17:12.600117: +2024-11-21 16:17:12.600345: Epoch 1004 +2024-11-21 16:17:12.600475: Current learning rate: 0.00886 +2024-11-21 16:17:32.488490: train_loss -0.7455 +2024-11-21 16:17:32.490431: val_loss -0.7561 +2024-11-21 16:17:32.490539: Pseudo dice [0.827] +2024-11-21 16:17:32.490699: Epoch time: 19.88 s +2024-11-21 16:17:33.344363: +2024-11-21 16:17:33.344611: Epoch 1005 +2024-11-21 16:17:33.344741: Current learning rate: 0.00886 +2024-11-21 16:17:52.340404: train_loss -0.7487 +2024-11-21 16:17:52.342516: val_loss -0.7569 +2024-11-21 16:17:52.342631: Pseudo dice [0.8445] +2024-11-21 16:17:52.342724: Epoch time: 19.0 s +2024-11-21 16:17:53.147075: +2024-11-21 16:17:53.147289: Epoch 1006 +2024-11-21 16:17:53.147402: Current learning rate: 0.00886 +2024-11-21 16:18:13.531527: train_loss -0.7533 +2024-11-21 16:18:13.537969: val_loss -0.7645 +2024-11-21 16:18:13.538122: Pseudo dice [0.8511] +2024-11-21 16:18:13.538301: Epoch time: 20.39 s +2024-11-21 16:18:14.412307: +2024-11-21 16:18:14.412550: Epoch 1007 +2024-11-21 16:18:14.412673: Current learning rate: 0.00886 +2024-11-21 16:18:32.799516: train_loss -0.7673 +2024-11-21 16:18:32.807444: val_loss -0.768 +2024-11-21 16:18:32.807571: Pseudo dice [0.8371] +2024-11-21 16:18:32.807660: Epoch time: 18.39 s +2024-11-21 16:18:33.790031: +2024-11-21 16:18:33.790292: Epoch 1008 +2024-11-21 16:18:33.790434: Current learning rate: 0.00886 +2024-11-21 16:18:51.836941: train_loss -0.7667 +2024-11-21 16:18:51.844649: val_loss -0.7735 +2024-11-21 16:18:51.844779: Pseudo dice [0.8634] +2024-11-21 16:18:51.844883: Epoch time: 18.05 s +2024-11-21 16:18:52.759089: +2024-11-21 16:18:52.759292: Epoch 1009 +2024-11-21 16:18:52.759420: Current learning rate: 0.00886 +2024-11-21 16:19:11.979775: train_loss -0.768 +2024-11-21 16:19:11.985389: val_loss -0.7686 +2024-11-21 16:19:11.985507: Pseudo dice [0.8538] +2024-11-21 16:19:11.985592: Epoch time: 19.22 s +2024-11-21 16:19:12.833256: +2024-11-21 16:19:12.833471: Epoch 1010 +2024-11-21 16:19:12.833610: Current learning rate: 0.00886 +2024-11-21 16:19:32.146745: train_loss -0.7692 +2024-11-21 16:19:32.156003: val_loss -0.7574 +2024-11-21 16:19:32.156140: Pseudo dice [0.8618] +2024-11-21 16:19:32.156242: Epoch time: 19.31 s +2024-11-21 16:19:33.074970: +2024-11-21 16:19:33.075178: Epoch 1011 +2024-11-21 16:19:33.075302: Current learning rate: 0.00886 +2024-11-21 16:19:53.318494: train_loss -0.7562 +2024-11-21 16:19:53.324738: val_loss -0.7167 +2024-11-21 16:19:53.325071: Pseudo dice [0.8179] +2024-11-21 16:19:53.325217: Epoch time: 20.24 s +2024-11-21 16:19:54.133559: +2024-11-21 16:19:54.133748: Epoch 1012 +2024-11-21 16:19:54.133861: Current learning rate: 0.00885 +2024-11-21 16:20:13.727409: train_loss -0.7455 +2024-11-21 16:20:13.746119: val_loss -0.7457 +2024-11-21 16:20:13.746299: Pseudo dice [0.8434] +2024-11-21 16:20:13.746412: Epoch time: 19.59 s +2024-11-21 16:20:15.037517: +2024-11-21 16:20:15.037750: Epoch 1013 +2024-11-21 16:20:15.037881: Current learning rate: 0.00885 +2024-11-21 16:20:34.337107: train_loss -0.7448 +2024-11-21 16:20:34.349905: val_loss -0.7598 +2024-11-21 16:20:34.350094: Pseudo dice [0.8245] +2024-11-21 16:20:34.350199: Epoch time: 19.3 s +2024-11-21 16:20:35.332280: +2024-11-21 16:20:35.332508: Epoch 1014 +2024-11-21 16:20:35.332649: Current learning rate: 0.00885 +2024-11-21 16:20:54.424633: train_loss -0.7515 +2024-11-21 16:20:54.430949: val_loss -0.7441 +2024-11-21 16:20:54.431097: Pseudo dice [0.8343] +2024-11-21 16:20:54.431195: Epoch time: 19.09 s +2024-11-21 16:20:55.251841: +2024-11-21 16:20:55.252057: Epoch 1015 +2024-11-21 16:20:55.252186: Current learning rate: 0.00885 +2024-11-21 16:21:14.744669: train_loss -0.7621 +2024-11-21 16:21:14.747417: val_loss -0.769 +2024-11-21 16:21:14.747805: Pseudo dice [0.8436] +2024-11-21 16:21:14.747906: Epoch time: 19.49 s +2024-11-21 16:21:15.665758: +2024-11-21 16:21:15.665992: Epoch 1016 +2024-11-21 16:21:15.666133: Current learning rate: 0.00885 +2024-11-21 16:21:34.720995: train_loss -0.75 +2024-11-21 16:21:34.732524: val_loss -0.7693 +2024-11-21 16:21:34.732707: Pseudo dice [0.839] +2024-11-21 16:21:34.732897: Epoch time: 19.06 s +2024-11-21 16:21:35.548111: +2024-11-21 16:21:35.548347: Epoch 1017 +2024-11-21 16:21:35.548465: Current learning rate: 0.00885 +2024-11-21 16:21:55.357080: train_loss -0.7538 +2024-11-21 16:21:55.366505: val_loss -0.7522 +2024-11-21 16:21:55.366641: Pseudo dice [0.8542] +2024-11-21 16:21:55.366758: Epoch time: 19.81 s +2024-11-21 16:21:56.289506: +2024-11-21 16:21:56.289743: Epoch 1018 +2024-11-21 16:21:56.289864: Current learning rate: 0.00885 +2024-11-21 16:22:16.162373: train_loss -0.7679 +2024-11-21 16:22:16.166329: val_loss -0.7832 +2024-11-21 16:22:16.166438: Pseudo dice [0.8598] +2024-11-21 16:22:16.166541: Epoch time: 19.87 s +2024-11-21 16:22:16.968954: +2024-11-21 16:22:16.969204: Epoch 1019 +2024-11-21 16:22:16.969336: Current learning rate: 0.00885 +2024-11-21 16:22:35.679003: train_loss -0.7518 +2024-11-21 16:22:35.681877: val_loss -0.7655 +2024-11-21 16:22:35.681976: Pseudo dice [0.8319] +2024-11-21 16:22:35.682069: Epoch time: 18.71 s +2024-11-21 16:22:36.488703: +2024-11-21 16:22:36.488893: Epoch 1020 +2024-11-21 16:22:36.489061: Current learning rate: 0.00884 +2024-11-21 16:22:54.957706: train_loss -0.7451 +2024-11-21 16:22:54.960408: val_loss -0.7758 +2024-11-21 16:22:54.960511: Pseudo dice [0.8442] +2024-11-21 16:22:54.960603: Epoch time: 18.47 s +2024-11-21 16:22:55.769737: +2024-11-21 16:22:55.769943: Epoch 1021 +2024-11-21 16:22:55.770091: Current learning rate: 0.00884 +2024-11-21 16:23:15.140660: train_loss -0.7444 +2024-11-21 16:23:15.142803: val_loss -0.78 +2024-11-21 16:23:15.142919: Pseudo dice [0.8357] +2024-11-21 16:23:15.143026: Epoch time: 19.37 s +2024-11-21 16:23:16.060854: +2024-11-21 16:23:16.061321: Epoch 1022 +2024-11-21 16:23:16.061457: Current learning rate: 0.00884 +2024-11-21 16:23:34.231934: train_loss -0.7675 +2024-11-21 16:23:34.236662: val_loss -0.7662 +2024-11-21 16:23:34.236805: Pseudo dice [0.8445] +2024-11-21 16:23:34.236894: Epoch time: 18.17 s +2024-11-21 16:23:35.126417: +2024-11-21 16:23:35.126622: Epoch 1023 +2024-11-21 16:23:35.126748: Current learning rate: 0.00884 +2024-11-21 16:23:53.902330: train_loss -0.7623 +2024-11-21 16:23:53.909050: val_loss -0.7491 +2024-11-21 16:23:53.909219: Pseudo dice [0.8292] +2024-11-21 16:23:53.909318: Epoch time: 18.78 s +2024-11-21 16:23:54.713808: +2024-11-21 16:23:54.714253: Epoch 1024 +2024-11-21 16:23:54.714409: Current learning rate: 0.00884 +2024-11-21 16:24:13.703527: train_loss -0.7471 +2024-11-21 16:24:13.711460: val_loss -0.7579 +2024-11-21 16:24:13.711658: Pseudo dice [0.8458] +2024-11-21 16:24:13.711762: Epoch time: 18.99 s +2024-11-21 16:24:14.554595: +2024-11-21 16:24:14.554811: Epoch 1025 +2024-11-21 16:24:14.554946: Current learning rate: 0.00884 +2024-11-21 16:24:33.591543: train_loss -0.7597 +2024-11-21 16:24:33.594400: val_loss -0.7558 +2024-11-21 16:24:33.594523: Pseudo dice [0.8487] +2024-11-21 16:24:33.594626: Epoch time: 19.04 s +2024-11-21 16:24:34.396824: +2024-11-21 16:24:34.397051: Epoch 1026 +2024-11-21 16:24:34.397171: Current learning rate: 0.00884 +2024-11-21 16:24:53.908784: train_loss -0.7455 +2024-11-21 16:24:53.913915: val_loss -0.747 +2024-11-21 16:24:53.914044: Pseudo dice [0.8366] +2024-11-21 16:24:53.914169: Epoch time: 19.51 s +2024-11-21 16:24:54.725312: +2024-11-21 16:24:54.725532: Epoch 1027 +2024-11-21 16:24:54.725648: Current learning rate: 0.00884 +2024-11-21 16:25:14.978593: train_loss -0.7502 +2024-11-21 16:25:14.986491: val_loss -0.774 +2024-11-21 16:25:14.986599: Pseudo dice [0.844] +2024-11-21 16:25:14.986694: Epoch time: 20.25 s +2024-11-21 16:25:15.976917: +2024-11-21 16:25:15.977135: Epoch 1028 +2024-11-21 16:25:15.977257: Current learning rate: 0.00884 +2024-11-21 16:25:35.252315: train_loss -0.7643 +2024-11-21 16:25:35.259507: val_loss -0.7519 +2024-11-21 16:25:35.259646: Pseudo dice [0.8274] +2024-11-21 16:25:35.259742: Epoch time: 19.28 s +2024-11-21 16:25:36.324748: +2024-11-21 16:25:36.324963: Epoch 1029 +2024-11-21 16:25:36.325103: Current learning rate: 0.00883 +2024-11-21 16:25:55.480545: train_loss -0.7581 +2024-11-21 16:25:55.487227: val_loss -0.7501 +2024-11-21 16:25:55.487373: Pseudo dice [0.8441] +2024-11-21 16:25:55.487537: Epoch time: 19.16 s +2024-11-21 16:25:56.499412: +2024-11-21 16:25:56.499651: Epoch 1030 +2024-11-21 16:25:56.499795: Current learning rate: 0.00883 +2024-11-21 16:26:14.989042: train_loss -0.7534 +2024-11-21 16:26:14.998288: val_loss -0.7699 +2024-11-21 16:26:14.998430: Pseudo dice [0.8414] +2024-11-21 16:26:14.998536: Epoch time: 18.49 s +2024-11-21 16:26:15.935464: +2024-11-21 16:26:15.935663: Epoch 1031 +2024-11-21 16:26:15.935780: Current learning rate: 0.00883 +2024-11-21 16:26:34.659081: train_loss -0.7466 +2024-11-21 16:26:34.665874: val_loss -0.7447 +2024-11-21 16:26:34.666049: Pseudo dice [0.8465] +2024-11-21 16:26:34.666184: Epoch time: 18.72 s +2024-11-21 16:26:35.657333: +2024-11-21 16:26:35.657557: Epoch 1032 +2024-11-21 16:26:35.657686: Current learning rate: 0.00883 +2024-11-21 16:26:55.465783: train_loss -0.7593 +2024-11-21 16:26:55.480354: val_loss -0.7461 +2024-11-21 16:26:55.480490: Pseudo dice [0.8467] +2024-11-21 16:26:55.480585: Epoch time: 19.81 s +2024-11-21 16:26:56.290144: +2024-11-21 16:26:56.290350: Epoch 1033 +2024-11-21 16:26:56.290477: Current learning rate: 0.00883 +2024-11-21 16:27:16.108968: train_loss -0.7537 +2024-11-21 16:27:16.117417: val_loss -0.769 +2024-11-21 16:27:16.117560: Pseudo dice [0.8431] +2024-11-21 16:27:16.117651: Epoch time: 19.82 s +2024-11-21 16:27:16.931415: +2024-11-21 16:27:16.931597: Epoch 1034 +2024-11-21 16:27:16.931715: Current learning rate: 0.00883 +2024-11-21 16:27:35.804221: train_loss -0.7565 +2024-11-21 16:27:35.811338: val_loss -0.7492 +2024-11-21 16:27:35.811523: Pseudo dice [0.8447] +2024-11-21 16:27:35.811619: Epoch time: 18.87 s +2024-11-21 16:27:36.696398: +2024-11-21 16:27:36.696801: Epoch 1035 +2024-11-21 16:27:36.696939: Current learning rate: 0.00883 +2024-11-21 16:27:56.495940: train_loss -0.7663 +2024-11-21 16:27:56.502655: val_loss -0.7673 +2024-11-21 16:27:56.502799: Pseudo dice [0.8433] +2024-11-21 16:27:56.502894: Epoch time: 19.8 s +2024-11-21 16:27:57.825492: +2024-11-21 16:27:57.825732: Epoch 1036 +2024-11-21 16:27:57.825865: Current learning rate: 0.00883 +2024-11-21 16:28:17.279492: train_loss -0.7567 +2024-11-21 16:28:17.287209: val_loss -0.753 +2024-11-21 16:28:17.287378: Pseudo dice [0.8439] +2024-11-21 16:28:17.287476: Epoch time: 19.46 s +2024-11-21 16:28:18.259784: +2024-11-21 16:28:18.260001: Epoch 1037 +2024-11-21 16:28:18.260120: Current learning rate: 0.00883 +2024-11-21 16:28:38.401664: train_loss -0.7514 +2024-11-21 16:28:38.407981: val_loss -0.7487 +2024-11-21 16:28:38.408115: Pseudo dice [0.8513] +2024-11-21 16:28:38.408196: Epoch time: 20.14 s +2024-11-21 16:28:39.334316: +2024-11-21 16:28:39.334546: Epoch 1038 +2024-11-21 16:28:39.334662: Current learning rate: 0.00882 +2024-11-21 16:28:57.419609: train_loss -0.76 +2024-11-21 16:28:57.426175: val_loss -0.752 +2024-11-21 16:28:57.426316: Pseudo dice [0.8428] +2024-11-21 16:28:57.426416: Epoch time: 18.09 s +2024-11-21 16:28:58.354534: +2024-11-21 16:28:58.354748: Epoch 1039 +2024-11-21 16:28:58.354884: Current learning rate: 0.00882 +2024-11-21 16:29:17.559409: train_loss -0.7584 +2024-11-21 16:29:17.564515: val_loss -0.7558 +2024-11-21 16:29:17.564672: Pseudo dice [0.8377] +2024-11-21 16:29:17.564765: Epoch time: 19.21 s +2024-11-21 16:29:18.371701: +2024-11-21 16:29:18.371918: Epoch 1040 +2024-11-21 16:29:18.372041: Current learning rate: 0.00882 +2024-11-21 16:29:38.129549: train_loss -0.7669 +2024-11-21 16:29:38.138463: val_loss -0.77 +2024-11-21 16:29:38.138592: Pseudo dice [0.8439] +2024-11-21 16:29:38.138685: Epoch time: 19.76 s +2024-11-21 16:29:39.079023: +2024-11-21 16:29:39.079535: Epoch 1041 +2024-11-21 16:29:39.079659: Current learning rate: 0.00882 +2024-11-21 16:29:58.570882: train_loss -0.7626 +2024-11-21 16:29:58.577379: val_loss -0.7539 +2024-11-21 16:29:58.577538: Pseudo dice [0.84] +2024-11-21 16:29:58.577628: Epoch time: 19.49 s +2024-11-21 16:29:59.398376: +2024-11-21 16:29:59.398587: Epoch 1042 +2024-11-21 16:29:59.398704: Current learning rate: 0.00882 +2024-11-21 16:30:19.668100: train_loss -0.7638 +2024-11-21 16:30:19.675402: val_loss -0.7563 +2024-11-21 16:30:19.675545: Pseudo dice [0.8297] +2024-11-21 16:30:19.675671: Epoch time: 20.27 s +2024-11-21 16:30:20.510473: +2024-11-21 16:30:20.510674: Epoch 1043 +2024-11-21 16:30:20.510795: Current learning rate: 0.00882 +2024-11-21 16:30:39.778017: train_loss -0.7531 +2024-11-21 16:30:39.785746: val_loss -0.7855 +2024-11-21 16:30:39.785890: Pseudo dice [0.8536] +2024-11-21 16:30:39.785974: Epoch time: 19.27 s +2024-11-21 16:30:40.613952: +2024-11-21 16:30:40.614160: Epoch 1044 +2024-11-21 16:30:40.614277: Current learning rate: 0.00882 +2024-11-21 16:30:59.677645: train_loss -0.7648 +2024-11-21 16:30:59.685416: val_loss -0.7633 +2024-11-21 16:30:59.685531: Pseudo dice [0.8468] +2024-11-21 16:30:59.685619: Epoch time: 19.06 s +2024-11-21 16:31:00.624562: +2024-11-21 16:31:00.624830: Epoch 1045 +2024-11-21 16:31:00.624963: Current learning rate: 0.00882 +2024-11-21 16:31:21.156696: train_loss -0.7581 +2024-11-21 16:31:21.163956: val_loss -0.7455 +2024-11-21 16:31:21.164106: Pseudo dice [0.838] +2024-11-21 16:31:21.164197: Epoch time: 20.53 s +2024-11-21 16:31:21.998943: +2024-11-21 16:31:21.999367: Epoch 1046 +2024-11-21 16:31:21.999513: Current learning rate: 0.00882 +2024-11-21 16:31:40.508191: train_loss -0.7542 +2024-11-21 16:31:40.522445: val_loss -0.7556 +2024-11-21 16:31:40.522621: Pseudo dice [0.8481] +2024-11-21 16:31:40.522749: Epoch time: 18.51 s +2024-11-21 16:31:41.379867: +2024-11-21 16:31:41.380086: Epoch 1047 +2024-11-21 16:31:41.380224: Current learning rate: 0.00881 +2024-11-21 16:32:01.996554: train_loss -0.7499 +2024-11-21 16:32:02.004856: val_loss -0.7539 +2024-11-21 16:32:02.004982: Pseudo dice [0.8304] +2024-11-21 16:32:02.005082: Epoch time: 20.62 s +2024-11-21 16:32:02.956806: +2024-11-21 16:32:02.957037: Epoch 1048 +2024-11-21 16:32:02.957169: Current learning rate: 0.00881 +2024-11-21 16:32:21.753636: train_loss -0.7692 +2024-11-21 16:32:21.761141: val_loss -0.7575 +2024-11-21 16:32:21.761321: Pseudo dice [0.8321] +2024-11-21 16:32:21.761440: Epoch time: 18.8 s +2024-11-21 16:32:22.746597: +2024-11-21 16:32:22.746803: Epoch 1049 +2024-11-21 16:32:22.746917: Current learning rate: 0.00881 +2024-11-21 16:32:42.648570: train_loss -0.7559 +2024-11-21 16:32:42.650230: val_loss -0.7381 +2024-11-21 16:32:42.650355: Pseudo dice [0.8371] +2024-11-21 16:32:42.650464: Epoch time: 19.9 s +2024-11-21 16:32:43.683417: +2024-11-21 16:32:43.683627: Epoch 1050 +2024-11-21 16:32:43.683748: Current learning rate: 0.00881 +2024-11-21 16:33:02.714273: train_loss -0.7519 +2024-11-21 16:33:02.718560: val_loss -0.7664 +2024-11-21 16:33:02.718699: Pseudo dice [0.8471] +2024-11-21 16:33:02.718799: Epoch time: 19.03 s +2024-11-21 16:33:03.730197: +2024-11-21 16:33:03.730402: Epoch 1051 +2024-11-21 16:33:03.730517: Current learning rate: 0.00881 +2024-11-21 16:33:22.456802: train_loss -0.756 +2024-11-21 16:33:22.470104: val_loss -0.7471 +2024-11-21 16:33:22.470254: Pseudo dice [0.8453] +2024-11-21 16:33:22.470366: Epoch time: 18.73 s +2024-11-21 16:33:23.281521: +2024-11-21 16:33:23.281726: Epoch 1052 +2024-11-21 16:33:23.281840: Current learning rate: 0.00881 +2024-11-21 16:33:42.218928: train_loss -0.7567 +2024-11-21 16:33:42.225049: val_loss -0.7268 +2024-11-21 16:33:42.225213: Pseudo dice [0.8335] +2024-11-21 16:33:42.225315: Epoch time: 18.94 s +2024-11-21 16:33:43.030387: +2024-11-21 16:33:43.030596: Epoch 1053 +2024-11-21 16:33:43.030721: Current learning rate: 0.00881 +2024-11-21 16:34:02.240903: train_loss -0.7619 +2024-11-21 16:34:02.243352: val_loss -0.742 +2024-11-21 16:34:02.243454: Pseudo dice [0.848] +2024-11-21 16:34:02.243863: Epoch time: 19.21 s +2024-11-21 16:34:03.049500: +2024-11-21 16:34:03.049715: Epoch 1054 +2024-11-21 16:34:03.049846: Current learning rate: 0.00881 +2024-11-21 16:34:21.123563: train_loss -0.738 +2024-11-21 16:34:21.126649: val_loss -0.7735 +2024-11-21 16:34:21.126789: Pseudo dice [0.8422] +2024-11-21 16:34:21.126882: Epoch time: 18.07 s +2024-11-21 16:34:21.986085: +2024-11-21 16:34:21.986297: Epoch 1055 +2024-11-21 16:34:21.986427: Current learning rate: 0.0088 +2024-11-21 16:34:41.411080: train_loss -0.7622 +2024-11-21 16:34:41.418215: val_loss -0.7371 +2024-11-21 16:34:41.418368: Pseudo dice [0.8501] +2024-11-21 16:34:41.418473: Epoch time: 19.43 s +2024-11-21 16:34:42.250708: +2024-11-21 16:34:42.250917: Epoch 1056 +2024-11-21 16:34:42.251046: Current learning rate: 0.0088 +2024-11-21 16:35:01.189737: train_loss -0.7563 +2024-11-21 16:35:01.191681: val_loss -0.7058 +2024-11-21 16:35:01.191801: Pseudo dice [0.8418] +2024-11-21 16:35:01.191900: Epoch time: 18.94 s +2024-11-21 16:35:02.055818: +2024-11-21 16:35:02.056017: Epoch 1057 +2024-11-21 16:35:02.056150: Current learning rate: 0.0088 +2024-11-21 16:35:20.762435: train_loss -0.7618 +2024-11-21 16:35:20.766159: val_loss -0.7569 +2024-11-21 16:35:20.766274: Pseudo dice [0.8459] +2024-11-21 16:35:20.766360: Epoch time: 18.71 s +2024-11-21 16:35:21.706986: +2024-11-21 16:35:21.707177: Epoch 1058 +2024-11-21 16:35:21.707294: Current learning rate: 0.0088 +2024-11-21 16:35:41.622209: train_loss -0.7608 +2024-11-21 16:35:41.633026: val_loss -0.7629 +2024-11-21 16:35:41.633219: Pseudo dice [0.829] +2024-11-21 16:35:41.633310: Epoch time: 19.92 s +2024-11-21 16:35:42.939500: +2024-11-21 16:35:42.939727: Epoch 1059 +2024-11-21 16:35:42.939867: Current learning rate: 0.0088 +2024-11-21 16:36:02.122628: train_loss -0.7634 +2024-11-21 16:36:02.130399: val_loss -0.7603 +2024-11-21 16:36:02.130532: Pseudo dice [0.8435] +2024-11-21 16:36:02.130646: Epoch time: 19.18 s +2024-11-21 16:36:03.073081: +2024-11-21 16:36:03.073299: Epoch 1060 +2024-11-21 16:36:03.073419: Current learning rate: 0.0088 +2024-11-21 16:36:21.374367: train_loss -0.7645 +2024-11-21 16:36:21.376094: val_loss -0.755 +2024-11-21 16:36:21.376204: Pseudo dice [0.8508] +2024-11-21 16:36:21.376318: Epoch time: 18.3 s +2024-11-21 16:36:22.187087: +2024-11-21 16:36:22.187290: Epoch 1061 +2024-11-21 16:36:22.187426: Current learning rate: 0.0088 +2024-11-21 16:36:40.453210: train_loss -0.764 +2024-11-21 16:36:40.460459: val_loss -0.7503 +2024-11-21 16:36:40.460612: Pseudo dice [0.8483] +2024-11-21 16:36:40.460699: Epoch time: 18.27 s +2024-11-21 16:36:41.264725: +2024-11-21 16:36:41.264939: Epoch 1062 +2024-11-21 16:36:41.265055: Current learning rate: 0.0088 +2024-11-21 16:37:00.914973: train_loss -0.7598 +2024-11-21 16:37:00.916772: val_loss -0.7681 +2024-11-21 16:37:00.916895: Pseudo dice [0.8564] +2024-11-21 16:37:00.917000: Epoch time: 19.65 s +2024-11-21 16:37:01.713486: +2024-11-21 16:37:01.713706: Epoch 1063 +2024-11-21 16:37:01.713822: Current learning rate: 0.0088 +2024-11-21 16:37:20.882623: train_loss -0.7663 +2024-11-21 16:37:20.887359: val_loss -0.7557 +2024-11-21 16:37:20.887545: Pseudo dice [0.8485] +2024-11-21 16:37:20.887637: Epoch time: 19.17 s +2024-11-21 16:37:21.699946: +2024-11-21 16:37:21.700176: Epoch 1064 +2024-11-21 16:37:21.700303: Current learning rate: 0.00879 +2024-11-21 16:37:40.551155: train_loss -0.7607 +2024-11-21 16:37:40.557949: val_loss -0.7676 +2024-11-21 16:37:40.558169: Pseudo dice [0.8365] +2024-11-21 16:37:40.558283: Epoch time: 18.85 s +2024-11-21 16:37:41.591758: +2024-11-21 16:37:41.591980: Epoch 1065 +2024-11-21 16:37:41.592117: Current learning rate: 0.00879 +2024-11-21 16:38:00.414336: train_loss -0.758 +2024-11-21 16:38:00.442314: val_loss -0.7672 +2024-11-21 16:38:00.442457: Pseudo dice [0.847] +2024-11-21 16:38:00.442549: Epoch time: 18.82 s +2024-11-21 16:38:01.321252: +2024-11-21 16:38:01.321465: Epoch 1066 +2024-11-21 16:38:01.321582: Current learning rate: 0.00879 +2024-11-21 16:38:20.841223: train_loss -0.7451 +2024-11-21 16:38:20.845096: val_loss -0.7583 +2024-11-21 16:38:20.845239: Pseudo dice [0.846] +2024-11-21 16:38:20.845452: Epoch time: 19.52 s +2024-11-21 16:38:21.661987: +2024-11-21 16:38:21.662184: Epoch 1067 +2024-11-21 16:38:21.662300: Current learning rate: 0.00879 +2024-11-21 16:38:40.478984: train_loss -0.7643 +2024-11-21 16:38:40.482097: val_loss -0.7702 +2024-11-21 16:38:40.482254: Pseudo dice [0.835] +2024-11-21 16:38:40.482333: Epoch time: 18.82 s +2024-11-21 16:38:41.284481: +2024-11-21 16:38:41.284670: Epoch 1068 +2024-11-21 16:38:41.284794: Current learning rate: 0.00879 +2024-11-21 16:38:59.999625: train_loss -0.7613 +2024-11-21 16:39:00.006045: val_loss -0.7776 +2024-11-21 16:39:00.006246: Pseudo dice [0.8458] +2024-11-21 16:39:00.006429: Epoch time: 18.72 s +2024-11-21 16:39:00.907658: +2024-11-21 16:39:00.907856: Epoch 1069 +2024-11-21 16:39:00.907989: Current learning rate: 0.00879 +2024-11-21 16:39:18.583936: train_loss -0.7623 +2024-11-21 16:39:18.593047: val_loss -0.7588 +2024-11-21 16:39:18.593184: Pseudo dice [0.8367] +2024-11-21 16:39:18.593295: Epoch time: 17.68 s +2024-11-21 16:39:19.539361: +2024-11-21 16:39:19.539599: Epoch 1070 +2024-11-21 16:39:19.539715: Current learning rate: 0.00879 +2024-11-21 16:39:38.693307: train_loss -0.7473 +2024-11-21 16:39:38.699482: val_loss -0.7393 +2024-11-21 16:39:38.699715: Pseudo dice [0.8334] +2024-11-21 16:39:38.699806: Epoch time: 19.15 s +2024-11-21 16:39:39.585329: +2024-11-21 16:39:39.585585: Epoch 1071 +2024-11-21 16:39:39.585722: Current learning rate: 0.00879 +2024-11-21 16:39:59.520994: train_loss -0.7253 +2024-11-21 16:39:59.525728: val_loss -0.7562 +2024-11-21 16:39:59.525856: Pseudo dice [0.8277] +2024-11-21 16:39:59.525962: Epoch time: 19.94 s +2024-11-21 16:40:00.332434: +2024-11-21 16:40:00.332692: Epoch 1072 +2024-11-21 16:40:00.332831: Current learning rate: 0.00879 +2024-11-21 16:40:17.521086: train_loss -0.7593 +2024-11-21 16:40:17.528813: val_loss -0.7697 +2024-11-21 16:40:17.528940: Pseudo dice [0.8469] +2024-11-21 16:40:17.529028: Epoch time: 17.19 s +2024-11-21 16:40:18.356445: +2024-11-21 16:40:18.356704: Epoch 1073 +2024-11-21 16:40:18.357108: Current learning rate: 0.00878 +2024-11-21 16:40:37.922793: train_loss -0.7681 +2024-11-21 16:40:37.929638: val_loss -0.7561 +2024-11-21 16:40:37.929776: Pseudo dice [0.8496] +2024-11-21 16:40:37.929866: Epoch time: 19.57 s +2024-11-21 16:40:38.798478: +2024-11-21 16:40:38.798738: Epoch 1074 +2024-11-21 16:40:38.798888: Current learning rate: 0.00878 +2024-11-21 16:40:57.296621: train_loss -0.7602 +2024-11-21 16:40:57.318035: val_loss -0.7675 +2024-11-21 16:40:57.318198: Pseudo dice [0.8393] +2024-11-21 16:40:57.318306: Epoch time: 18.5 s +2024-11-21 16:40:58.192725: +2024-11-21 16:40:58.192935: Epoch 1075 +2024-11-21 16:40:58.193076: Current learning rate: 0.00878 +2024-11-21 16:41:17.953020: train_loss -0.7658 +2024-11-21 16:41:17.959776: val_loss -0.7513 +2024-11-21 16:41:17.959914: Pseudo dice [0.8421] +2024-11-21 16:41:17.960010: Epoch time: 19.76 s +2024-11-21 16:41:18.795142: +2024-11-21 16:41:18.795364: Epoch 1076 +2024-11-21 16:41:18.795482: Current learning rate: 0.00878 +2024-11-21 16:41:37.019819: train_loss -0.7596 +2024-11-21 16:41:37.023425: val_loss -0.7717 +2024-11-21 16:41:37.023554: Pseudo dice [0.8406] +2024-11-21 16:41:37.023657: Epoch time: 18.23 s +2024-11-21 16:41:37.831128: +2024-11-21 16:41:37.831324: Epoch 1077 +2024-11-21 16:41:37.831501: Current learning rate: 0.00878 +2024-11-21 16:41:57.530788: train_loss -0.7605 +2024-11-21 16:41:57.545332: val_loss -0.7672 +2024-11-21 16:41:57.545496: Pseudo dice [0.8527] +2024-11-21 16:41:57.545607: Epoch time: 19.7 s +2024-11-21 16:41:58.381966: +2024-11-21 16:41:58.382188: Epoch 1078 +2024-11-21 16:41:58.382307: Current learning rate: 0.00878 +2024-11-21 16:42:18.245991: train_loss -0.7621 +2024-11-21 16:42:18.249828: val_loss -0.7533 +2024-11-21 16:42:18.249931: Pseudo dice [0.8488] +2024-11-21 16:42:18.250031: Epoch time: 19.86 s +2024-11-21 16:42:19.064751: +2024-11-21 16:42:19.064964: Epoch 1079 +2024-11-21 16:42:19.083915: Current learning rate: 0.00878 +2024-11-21 16:42:38.071499: train_loss -0.7615 +2024-11-21 16:42:38.088571: val_loss -0.7509 +2024-11-21 16:42:38.088725: Pseudo dice [0.84] +2024-11-21 16:42:38.088823: Epoch time: 19.01 s +2024-11-21 16:42:38.992330: +2024-11-21 16:42:38.992525: Epoch 1080 +2024-11-21 16:42:38.992647: Current learning rate: 0.00878 +2024-11-21 16:42:59.286299: train_loss -0.7476 +2024-11-21 16:42:59.297311: val_loss -0.7521 +2024-11-21 16:42:59.297452: Pseudo dice [0.8323] +2024-11-21 16:42:59.297538: Epoch time: 20.29 s +2024-11-21 16:43:00.166413: +2024-11-21 16:43:00.166629: Epoch 1081 +2024-11-21 16:43:00.166786: Current learning rate: 0.00878 +2024-11-21 16:43:18.449444: train_loss -0.7623 +2024-11-21 16:43:18.453028: val_loss -0.7579 +2024-11-21 16:43:18.453168: Pseudo dice [0.831] +2024-11-21 16:43:18.453272: Epoch time: 18.28 s +2024-11-21 16:43:19.700879: +2024-11-21 16:43:19.701194: Epoch 1082 +2024-11-21 16:43:19.701320: Current learning rate: 0.00877 +2024-11-21 16:43:38.208521: train_loss -0.7677 +2024-11-21 16:43:38.218144: val_loss -0.767 +2024-11-21 16:43:38.218359: Pseudo dice [0.8522] +2024-11-21 16:43:38.218603: Epoch time: 18.51 s +2024-11-21 16:43:39.188507: +2024-11-21 16:43:39.188725: Epoch 1083 +2024-11-21 16:43:39.188843: Current learning rate: 0.00877 +2024-11-21 16:43:57.743140: train_loss -0.7636 +2024-11-21 16:43:57.752116: val_loss -0.7134 +2024-11-21 16:43:57.752249: Pseudo dice [0.8462] +2024-11-21 16:43:57.752338: Epoch time: 18.56 s +2024-11-21 16:43:58.810410: +2024-11-21 16:43:58.810624: Epoch 1084 +2024-11-21 16:43:58.810745: Current learning rate: 0.00877 +2024-11-21 16:44:18.840325: train_loss -0.7674 +2024-11-21 16:44:18.846296: val_loss -0.784 +2024-11-21 16:44:18.846439: Pseudo dice [0.8625] +2024-11-21 16:44:18.846544: Epoch time: 20.03 s +2024-11-21 16:44:19.807356: +2024-11-21 16:44:19.807593: Epoch 1085 +2024-11-21 16:44:19.807717: Current learning rate: 0.00877 +2024-11-21 16:44:39.167781: train_loss -0.7447 +2024-11-21 16:44:39.175122: val_loss -0.7425 +2024-11-21 16:44:39.175268: Pseudo dice [0.849] +2024-11-21 16:44:39.175381: Epoch time: 19.36 s +2024-11-21 16:44:40.088166: +2024-11-21 16:44:40.088403: Epoch 1086 +2024-11-21 16:44:40.088557: Current learning rate: 0.00877 +2024-11-21 16:44:58.079866: train_loss -0.7601 +2024-11-21 16:44:58.104676: val_loss -0.7512 +2024-11-21 16:44:58.104845: Pseudo dice [0.8358] +2024-11-21 16:44:58.104945: Epoch time: 17.99 s +2024-11-21 16:44:59.129474: +2024-11-21 16:44:59.129692: Epoch 1087 +2024-11-21 16:44:59.129810: Current learning rate: 0.00877 +2024-11-21 16:45:17.384406: train_loss -0.7669 +2024-11-21 16:45:17.387245: val_loss -0.7533 +2024-11-21 16:45:17.387375: Pseudo dice [0.8541] +2024-11-21 16:45:17.387459: Epoch time: 18.26 s +2024-11-21 16:45:18.195191: +2024-11-21 16:45:18.195421: Epoch 1088 +2024-11-21 16:45:18.195544: Current learning rate: 0.00877 +2024-11-21 16:45:35.952864: train_loss -0.764 +2024-11-21 16:45:35.955591: val_loss -0.765 +2024-11-21 16:45:35.955685: Pseudo dice [0.8303] +2024-11-21 16:45:35.955791: Epoch time: 17.76 s +2024-11-21 16:45:36.755131: +2024-11-21 16:45:36.755373: Epoch 1089 +2024-11-21 16:45:36.755503: Current learning rate: 0.00877 +2024-11-21 16:45:55.766350: train_loss -0.7248 +2024-11-21 16:45:55.774167: val_loss -0.7244 +2024-11-21 16:45:55.774274: Pseudo dice [0.8232] +2024-11-21 16:45:55.774361: Epoch time: 19.01 s +2024-11-21 16:45:56.586936: +2024-11-21 16:45:56.587156: Epoch 1090 +2024-11-21 16:45:56.587277: Current learning rate: 0.00876 +2024-11-21 16:46:15.715608: train_loss -0.7355 +2024-11-21 16:46:15.740428: val_loss -0.744 +2024-11-21 16:46:15.740564: Pseudo dice [0.8452] +2024-11-21 16:46:15.740664: Epoch time: 19.13 s +2024-11-21 16:46:16.547397: +2024-11-21 16:46:16.547626: Epoch 1091 +2024-11-21 16:46:16.547742: Current learning rate: 0.00876 +2024-11-21 16:46:33.953616: train_loss -0.7467 +2024-11-21 16:46:33.975896: val_loss -0.7512 +2024-11-21 16:46:33.976040: Pseudo dice [0.8504] +2024-11-21 16:46:33.976139: Epoch time: 17.41 s +2024-11-21 16:46:34.870875: +2024-11-21 16:46:34.871095: Epoch 1092 +2024-11-21 16:46:34.871226: Current learning rate: 0.00876 +2024-11-21 16:46:54.268587: train_loss -0.7649 +2024-11-21 16:46:54.276084: val_loss -0.7516 +2024-11-21 16:46:54.276242: Pseudo dice [0.829] +2024-11-21 16:46:54.276334: Epoch time: 19.4 s +2024-11-21 16:46:55.089249: +2024-11-21 16:46:55.089469: Epoch 1093 +2024-11-21 16:46:55.089598: Current learning rate: 0.00876 +2024-11-21 16:47:14.500020: train_loss -0.7439 +2024-11-21 16:47:14.507355: val_loss -0.7326 +2024-11-21 16:47:14.507512: Pseudo dice [0.8237] +2024-11-21 16:47:14.507607: Epoch time: 19.41 s +2024-11-21 16:47:15.317535: +2024-11-21 16:47:15.317763: Epoch 1094 +2024-11-21 16:47:15.317907: Current learning rate: 0.00876 +2024-11-21 16:47:35.133906: train_loss -0.7483 +2024-11-21 16:47:35.139511: val_loss -0.7551 +2024-11-21 16:47:35.139666: Pseudo dice [0.8403] +2024-11-21 16:47:35.139763: Epoch time: 19.82 s +2024-11-21 16:47:36.066773: +2024-11-21 16:47:36.066981: Epoch 1095 +2024-11-21 16:47:36.067100: Current learning rate: 0.00876 +2024-11-21 16:47:55.397639: train_loss -0.7677 +2024-11-21 16:47:55.403691: val_loss -0.7676 +2024-11-21 16:47:55.403830: Pseudo dice [0.8515] +2024-11-21 16:47:55.403919: Epoch time: 19.33 s +2024-11-21 16:47:56.255065: +2024-11-21 16:47:56.255312: Epoch 1096 +2024-11-21 16:47:56.255426: Current learning rate: 0.00876 +2024-11-21 16:48:16.744853: train_loss -0.7612 +2024-11-21 16:48:16.752385: val_loss -0.7504 +2024-11-21 16:48:16.752539: Pseudo dice [0.8542] +2024-11-21 16:48:16.752643: Epoch time: 20.49 s +2024-11-21 16:48:17.621516: +2024-11-21 16:48:17.621732: Epoch 1097 +2024-11-21 16:48:17.621845: Current learning rate: 0.00876 +2024-11-21 16:48:36.852086: train_loss -0.7546 +2024-11-21 16:48:36.856666: val_loss -0.7873 +2024-11-21 16:48:36.856912: Pseudo dice [0.8538] +2024-11-21 16:48:36.857010: Epoch time: 19.23 s +2024-11-21 16:48:37.718254: +2024-11-21 16:48:37.718460: Epoch 1098 +2024-11-21 16:48:37.718587: Current learning rate: 0.00876 +2024-11-21 16:48:56.265812: train_loss -0.7465 +2024-11-21 16:48:56.272734: val_loss -0.7555 +2024-11-21 16:48:56.272865: Pseudo dice [0.827] +2024-11-21 16:48:56.272961: Epoch time: 18.55 s +2024-11-21 16:48:57.335635: +2024-11-21 16:48:57.335851: Epoch 1099 +2024-11-21 16:48:57.336186: Current learning rate: 0.00875 +2024-11-21 16:49:16.377073: train_loss -0.75 +2024-11-21 16:49:16.382706: val_loss -0.7411 +2024-11-21 16:49:16.382837: Pseudo dice [0.8371] +2024-11-21 16:49:16.382921: Epoch time: 19.04 s +2024-11-21 16:49:17.457078: +2024-11-21 16:49:17.457275: Epoch 1100 +2024-11-21 16:49:17.457409: Current learning rate: 0.00875 +2024-11-21 16:49:37.736158: train_loss -0.7491 +2024-11-21 16:49:37.740091: val_loss -0.7678 +2024-11-21 16:49:37.740228: Pseudo dice [0.8331] +2024-11-21 16:49:37.740343: Epoch time: 20.28 s +2024-11-21 16:49:38.546391: +2024-11-21 16:49:38.546637: Epoch 1101 +2024-11-21 16:49:38.546759: Current learning rate: 0.00875 +2024-11-21 16:49:58.012974: train_loss -0.7663 +2024-11-21 16:49:58.022553: val_loss -0.7504 +2024-11-21 16:49:58.022697: Pseudo dice [0.8375] +2024-11-21 16:49:58.022788: Epoch time: 19.47 s +2024-11-21 16:49:58.826271: +2024-11-21 16:49:58.826483: Epoch 1102 +2024-11-21 16:49:58.826627: Current learning rate: 0.00875 +2024-11-21 16:50:17.882588: train_loss -0.7564 +2024-11-21 16:50:17.885650: val_loss -0.7578 +2024-11-21 16:50:17.885765: Pseudo dice [0.8333] +2024-11-21 16:50:17.885850: Epoch time: 19.06 s +2024-11-21 16:50:18.689901: +2024-11-21 16:50:18.690103: Epoch 1103 +2024-11-21 16:50:18.690219: Current learning rate: 0.00875 +2024-11-21 16:50:37.776116: train_loss -0.7561 +2024-11-21 16:50:37.783462: val_loss -0.7562 +2024-11-21 16:50:37.783637: Pseudo dice [0.8445] +2024-11-21 16:50:37.783774: Epoch time: 19.09 s +2024-11-21 16:50:38.646679: +2024-11-21 16:50:38.646891: Epoch 1104 +2024-11-21 16:50:38.647006: Current learning rate: 0.00875 +2024-11-21 16:50:58.311778: train_loss -0.7598 +2024-11-21 16:50:58.316420: val_loss -0.748 +2024-11-21 16:50:58.316798: Pseudo dice [0.8472] +2024-11-21 16:50:58.316913: Epoch time: 19.67 s +2024-11-21 16:50:59.563985: +2024-11-21 16:50:59.564245: Epoch 1105 +2024-11-21 16:50:59.564368: Current learning rate: 0.00875 +2024-11-21 16:51:18.527877: train_loss -0.7329 +2024-11-21 16:51:18.536040: val_loss -0.7244 +2024-11-21 16:51:18.536212: Pseudo dice [0.8056] +2024-11-21 16:51:18.536364: Epoch time: 18.96 s +2024-11-21 16:51:19.358512: +2024-11-21 16:51:19.358731: Epoch 1106 +2024-11-21 16:51:19.358861: Current learning rate: 0.00875 +2024-11-21 16:51:37.043149: train_loss -0.7369 +2024-11-21 16:51:37.050450: val_loss -0.7812 +2024-11-21 16:51:37.050605: Pseudo dice [0.8355] +2024-11-21 16:51:37.050708: Epoch time: 17.69 s +2024-11-21 16:51:37.976226: +2024-11-21 16:51:37.976423: Epoch 1107 +2024-11-21 16:51:37.976542: Current learning rate: 0.00875 +2024-11-21 16:51:56.663661: train_loss -0.7551 +2024-11-21 16:51:56.674370: val_loss -0.7541 +2024-11-21 16:51:56.674513: Pseudo dice [0.8382] +2024-11-21 16:51:56.674603: Epoch time: 18.69 s +2024-11-21 16:51:57.614526: +2024-11-21 16:51:57.614749: Epoch 1108 +2024-11-21 16:51:57.614870: Current learning rate: 0.00874 +2024-11-21 16:52:16.188151: train_loss -0.7548 +2024-11-21 16:52:16.197872: val_loss -0.7683 +2024-11-21 16:52:16.198025: Pseudo dice [0.8429] +2024-11-21 16:52:16.198141: Epoch time: 18.57 s +2024-11-21 16:52:17.190470: +2024-11-21 16:52:17.190676: Epoch 1109 +2024-11-21 16:52:17.190793: Current learning rate: 0.00874 +2024-11-21 16:52:36.143954: train_loss -0.7619 +2024-11-21 16:52:36.153013: val_loss -0.7592 +2024-11-21 16:52:36.153168: Pseudo dice [0.8449] +2024-11-21 16:52:36.153262: Epoch time: 18.95 s +2024-11-21 16:52:36.965985: +2024-11-21 16:52:36.966286: Epoch 1110 +2024-11-21 16:52:36.966413: Current learning rate: 0.00874 +2024-11-21 16:52:57.038276: train_loss -0.7691 +2024-11-21 16:52:57.046473: val_loss -0.7785 +2024-11-21 16:52:57.046603: Pseudo dice [0.8539] +2024-11-21 16:52:57.046699: Epoch time: 20.07 s +2024-11-21 16:52:57.927847: +2024-11-21 16:52:57.928115: Epoch 1111 +2024-11-21 16:52:57.928256: Current learning rate: 0.00874 +2024-11-21 16:53:17.464438: train_loss -0.7537 +2024-11-21 16:53:17.471866: val_loss -0.7084 +2024-11-21 16:53:17.471994: Pseudo dice [0.8315] +2024-11-21 16:53:17.472088: Epoch time: 19.54 s +2024-11-21 16:53:18.352864: +2024-11-21 16:53:18.353089: Epoch 1112 +2024-11-21 16:53:18.353207: Current learning rate: 0.00874 +2024-11-21 16:53:36.989419: train_loss -0.7563 +2024-11-21 16:53:36.999291: val_loss -0.7631 +2024-11-21 16:53:36.999434: Pseudo dice [0.8479] +2024-11-21 16:53:36.999532: Epoch time: 18.64 s +2024-11-21 16:53:37.848302: +2024-11-21 16:53:37.848541: Epoch 1113 +2024-11-21 16:53:37.848657: Current learning rate: 0.00874 +2024-11-21 16:53:56.923828: train_loss -0.7634 +2024-11-21 16:53:56.927505: val_loss -0.7382 +2024-11-21 16:53:56.927647: Pseudo dice [0.8483] +2024-11-21 16:53:56.927730: Epoch time: 19.08 s +2024-11-21 16:53:57.808500: +2024-11-21 16:53:57.808738: Epoch 1114 +2024-11-21 16:53:57.808882: Current learning rate: 0.00874 +2024-11-21 16:54:17.189928: train_loss -0.7444 +2024-11-21 16:54:17.205903: val_loss -0.7461 +2024-11-21 16:54:17.206104: Pseudo dice [0.8357] +2024-11-21 16:54:17.206201: Epoch time: 19.38 s +2024-11-21 16:54:18.094251: +2024-11-21 16:54:18.094450: Epoch 1115 +2024-11-21 16:54:18.094580: Current learning rate: 0.00874 +2024-11-21 16:54:37.523951: train_loss -0.7441 +2024-11-21 16:54:37.535198: val_loss -0.7374 +2024-11-21 16:54:37.535335: Pseudo dice [0.8251] +2024-11-21 16:54:37.535437: Epoch time: 19.43 s +2024-11-21 16:54:38.399700: +2024-11-21 16:54:38.399898: Epoch 1116 +2024-11-21 16:54:38.400015: Current learning rate: 0.00874 +2024-11-21 16:54:57.310836: train_loss -0.7508 +2024-11-21 16:54:57.313447: val_loss -0.7574 +2024-11-21 16:54:57.313579: Pseudo dice [0.8441] +2024-11-21 16:54:57.313668: Epoch time: 18.91 s +2024-11-21 16:54:58.271482: +2024-11-21 16:54:58.271746: Epoch 1117 +2024-11-21 16:54:58.271880: Current learning rate: 0.00873 +2024-11-21 16:55:17.587586: train_loss -0.7651 +2024-11-21 16:55:17.595723: val_loss -0.7537 +2024-11-21 16:55:17.595880: Pseudo dice [0.8571] +2024-11-21 16:55:17.596018: Epoch time: 19.32 s +2024-11-21 16:55:18.567075: +2024-11-21 16:55:18.567296: Epoch 1118 +2024-11-21 16:55:18.567411: Current learning rate: 0.00873 +2024-11-21 16:55:38.193617: train_loss -0.7623 +2024-11-21 16:55:38.202588: val_loss -0.7642 +2024-11-21 16:55:38.202786: Pseudo dice [0.864] +2024-11-21 16:55:38.202879: Epoch time: 19.63 s +2024-11-21 16:55:39.275459: +2024-11-21 16:55:39.275708: Epoch 1119 +2024-11-21 16:55:39.275847: Current learning rate: 0.00873 +2024-11-21 16:55:58.153024: train_loss -0.7529 +2024-11-21 16:55:58.159178: val_loss -0.7583 +2024-11-21 16:55:58.159302: Pseudo dice [0.8368] +2024-11-21 16:55:58.159399: Epoch time: 18.88 s +2024-11-21 16:55:59.027975: +2024-11-21 16:55:59.028183: Epoch 1120 +2024-11-21 16:55:59.028321: Current learning rate: 0.00873 +2024-11-21 16:56:18.222948: train_loss -0.7609 +2024-11-21 16:56:18.227838: val_loss -0.7678 +2024-11-21 16:56:18.227991: Pseudo dice [0.8343] +2024-11-21 16:56:18.228101: Epoch time: 19.2 s +2024-11-21 16:56:19.048478: +2024-11-21 16:56:19.048707: Epoch 1121 +2024-11-21 16:56:19.048827: Current learning rate: 0.00873 +2024-11-21 16:56:37.187681: train_loss -0.7528 +2024-11-21 16:56:37.196391: val_loss -0.7525 +2024-11-21 16:56:37.196600: Pseudo dice [0.8339] +2024-11-21 16:56:37.196691: Epoch time: 18.14 s +2024-11-21 16:56:38.050578: +2024-11-21 16:56:38.050806: Epoch 1122 +2024-11-21 16:56:38.050934: Current learning rate: 0.00873 +2024-11-21 16:56:57.519088: train_loss -0.7478 +2024-11-21 16:56:57.522043: val_loss -0.7574 +2024-11-21 16:56:57.522155: Pseudo dice [0.846] +2024-11-21 16:56:57.522264: Epoch time: 19.47 s +2024-11-21 16:56:58.328778: +2024-11-21 16:56:58.329000: Epoch 1123 +2024-11-21 16:56:58.329136: Current learning rate: 0.00873 +2024-11-21 16:57:18.184499: train_loss -0.7549 +2024-11-21 16:57:18.187997: val_loss -0.7609 +2024-11-21 16:57:18.188120: Pseudo dice [0.8445] +2024-11-21 16:57:18.188207: Epoch time: 19.86 s +2024-11-21 16:57:19.114452: +2024-11-21 16:57:19.114661: Epoch 1124 +2024-11-21 16:57:19.114801: Current learning rate: 0.00873 +2024-11-21 16:57:37.218946: train_loss -0.7625 +2024-11-21 16:57:37.222382: val_loss -0.7463 +2024-11-21 16:57:37.222515: Pseudo dice [0.8293] +2024-11-21 16:57:37.222625: Epoch time: 18.11 s +2024-11-21 16:57:38.034045: +2024-11-21 16:57:38.034256: Epoch 1125 +2024-11-21 16:57:38.034616: Current learning rate: 0.00872 +2024-11-21 16:57:57.462953: train_loss -0.752 +2024-11-21 16:57:57.471022: val_loss -0.784 +2024-11-21 16:57:57.471162: Pseudo dice [0.8538] +2024-11-21 16:57:57.471253: Epoch time: 19.43 s +2024-11-21 16:57:58.424491: +2024-11-21 16:57:58.424694: Epoch 1126 +2024-11-21 16:57:58.424811: Current learning rate: 0.00872 +2024-11-21 16:58:18.541471: train_loss -0.752 +2024-11-21 16:58:18.548610: val_loss -0.7646 +2024-11-21 16:58:18.548756: Pseudo dice [0.8386] +2024-11-21 16:58:18.548853: Epoch time: 20.12 s +2024-11-21 16:58:19.474602: +2024-11-21 16:58:19.474821: Epoch 1127 +2024-11-21 16:58:19.474951: Current learning rate: 0.00872 +2024-11-21 16:58:37.668743: train_loss -0.7626 +2024-11-21 16:58:37.674091: val_loss -0.7659 +2024-11-21 16:58:37.674224: Pseudo dice [0.8369] +2024-11-21 16:58:37.674310: Epoch time: 18.19 s +2024-11-21 16:58:38.941018: +2024-11-21 16:58:38.941271: Epoch 1128 +2024-11-21 16:58:38.941394: Current learning rate: 0.00872 +2024-11-21 16:58:58.911954: train_loss -0.7652 +2024-11-21 16:58:58.919521: val_loss -0.7594 +2024-11-21 16:58:58.919672: Pseudo dice [0.8446] +2024-11-21 16:58:58.919794: Epoch time: 19.97 s +2024-11-21 16:58:59.834523: +2024-11-21 16:58:59.834755: Epoch 1129 +2024-11-21 16:58:59.834892: Current learning rate: 0.00872 +2024-11-21 16:59:18.711996: train_loss -0.7688 +2024-11-21 16:59:18.722409: val_loss -0.7686 +2024-11-21 16:59:18.722530: Pseudo dice [0.8585] +2024-11-21 16:59:18.722618: Epoch time: 18.88 s +2024-11-21 16:59:19.600264: +2024-11-21 16:59:19.600482: Epoch 1130 +2024-11-21 16:59:19.600624: Current learning rate: 0.00872 +2024-11-21 16:59:38.621351: train_loss -0.7593 +2024-11-21 16:59:38.629662: val_loss -0.7654 +2024-11-21 16:59:38.629821: Pseudo dice [0.8476] +2024-11-21 16:59:38.629908: Epoch time: 19.02 s +2024-11-21 16:59:39.526793: +2024-11-21 16:59:39.527003: Epoch 1131 +2024-11-21 16:59:39.527128: Current learning rate: 0.00872 +2024-11-21 16:59:59.609372: train_loss -0.7621 +2024-11-21 16:59:59.616930: val_loss -0.7563 +2024-11-21 16:59:59.617091: Pseudo dice [0.8457] +2024-11-21 16:59:59.617189: Epoch time: 20.08 s +2024-11-21 17:00:00.434228: +2024-11-21 17:00:00.434443: Epoch 1132 +2024-11-21 17:00:00.434572: Current learning rate: 0.00872 +2024-11-21 17:00:19.060257: train_loss -0.7674 +2024-11-21 17:00:19.065496: val_loss -0.7524 +2024-11-21 17:00:19.065633: Pseudo dice [0.8444] +2024-11-21 17:00:19.065723: Epoch time: 18.63 s +2024-11-21 17:00:19.875634: +2024-11-21 17:00:19.875867: Epoch 1133 +2024-11-21 17:00:19.876012: Current learning rate: 0.00872 +2024-11-21 17:00:39.592458: train_loss -0.7726 +2024-11-21 17:00:39.610096: val_loss -0.7387 +2024-11-21 17:00:39.610296: Pseudo dice [0.8389] +2024-11-21 17:00:39.610401: Epoch time: 19.72 s +2024-11-21 17:00:40.623409: +2024-11-21 17:00:40.623643: Epoch 1134 +2024-11-21 17:00:40.623786: Current learning rate: 0.00871 +2024-11-21 17:00:59.737543: train_loss -0.7555 +2024-11-21 17:00:59.744119: val_loss -0.764 +2024-11-21 17:00:59.744261: Pseudo dice [0.8397] +2024-11-21 17:00:59.744353: Epoch time: 19.11 s +2024-11-21 17:01:00.682080: +2024-11-21 17:01:00.682293: Epoch 1135 +2024-11-21 17:01:00.682428: Current learning rate: 0.00871 +2024-11-21 17:01:19.040220: train_loss -0.7574 +2024-11-21 17:01:19.049424: val_loss -0.7471 +2024-11-21 17:01:19.049570: Pseudo dice [0.8452] +2024-11-21 17:01:19.049661: Epoch time: 18.36 s +2024-11-21 17:01:19.956927: +2024-11-21 17:01:19.957220: Epoch 1136 +2024-11-21 17:01:19.957350: Current learning rate: 0.00871 +2024-11-21 17:01:39.521528: train_loss -0.7677 +2024-11-21 17:01:39.525698: val_loss -0.748 +2024-11-21 17:01:39.525801: Pseudo dice [0.8465] +2024-11-21 17:01:39.525909: Epoch time: 19.57 s +2024-11-21 17:01:40.335259: +2024-11-21 17:01:40.335525: Epoch 1137 +2024-11-21 17:01:40.335663: Current learning rate: 0.00871 +2024-11-21 17:01:59.247890: train_loss -0.7753 +2024-11-21 17:01:59.252005: val_loss -0.739 +2024-11-21 17:01:59.252133: Pseudo dice [0.8419] +2024-11-21 17:01:59.252249: Epoch time: 18.91 s +2024-11-21 17:02:00.061089: +2024-11-21 17:02:00.061275: Epoch 1138 +2024-11-21 17:02:00.061394: Current learning rate: 0.00871 +2024-11-21 17:02:18.896851: train_loss -0.768 +2024-11-21 17:02:18.901525: val_loss -0.754 +2024-11-21 17:02:18.901685: Pseudo dice [0.8456] +2024-11-21 17:02:18.901782: Epoch time: 18.84 s +2024-11-21 17:02:19.706769: +2024-11-21 17:02:19.706981: Epoch 1139 +2024-11-21 17:02:19.707111: Current learning rate: 0.00871 +2024-11-21 17:02:39.143833: train_loss -0.7617 +2024-11-21 17:02:39.148775: val_loss -0.7679 +2024-11-21 17:02:39.148869: Pseudo dice [0.856] +2024-11-21 17:02:39.148962: Epoch time: 19.44 s +2024-11-21 17:02:39.956756: +2024-11-21 17:02:39.956996: Epoch 1140 +2024-11-21 17:02:39.957114: Current learning rate: 0.00871 +2024-11-21 17:02:59.581519: train_loss -0.7656 +2024-11-21 17:02:59.586591: val_loss -0.7632 +2024-11-21 17:02:59.586690: Pseudo dice [0.8481] +2024-11-21 17:02:59.586800: Epoch time: 19.63 s +2024-11-21 17:03:00.385381: +2024-11-21 17:03:00.385603: Epoch 1141 +2024-11-21 17:03:00.385740: Current learning rate: 0.00871 +2024-11-21 17:03:19.215756: train_loss -0.7687 +2024-11-21 17:03:19.219125: val_loss -0.7596 +2024-11-21 17:03:19.219225: Pseudo dice [0.8574] +2024-11-21 17:03:19.219317: Epoch time: 18.83 s +2024-11-21 17:03:20.022296: +2024-11-21 17:03:20.022517: Epoch 1142 +2024-11-21 17:03:20.022635: Current learning rate: 0.00871 +2024-11-21 17:03:40.083557: train_loss -0.7619 +2024-11-21 17:03:40.096691: val_loss -0.7351 +2024-11-21 17:03:40.096866: Pseudo dice [0.8365] +2024-11-21 17:03:40.097259: Epoch time: 20.06 s +2024-11-21 17:03:41.100573: +2024-11-21 17:03:41.100794: Epoch 1143 +2024-11-21 17:03:41.100912: Current learning rate: 0.0087 +2024-11-21 17:04:00.672406: train_loss -0.7586 +2024-11-21 17:04:00.689528: val_loss -0.7477 +2024-11-21 17:04:00.689682: Pseudo dice [0.8327] +2024-11-21 17:04:00.689771: Epoch time: 19.57 s +2024-11-21 17:04:01.532211: +2024-11-21 17:04:01.532425: Epoch 1144 +2024-11-21 17:04:01.532548: Current learning rate: 0.0087 +2024-11-21 17:04:20.668289: train_loss -0.7408 +2024-11-21 17:04:20.688056: val_loss -0.7755 +2024-11-21 17:04:20.688198: Pseudo dice [0.8444] +2024-11-21 17:04:20.688421: Epoch time: 19.14 s +2024-11-21 17:04:21.588024: +2024-11-21 17:04:21.588293: Epoch 1145 +2024-11-21 17:04:21.588424: Current learning rate: 0.0087 +2024-11-21 17:04:39.466496: train_loss -0.7593 +2024-11-21 17:04:39.473168: val_loss -0.7771 +2024-11-21 17:04:39.473302: Pseudo dice [0.8466] +2024-11-21 17:04:39.473413: Epoch time: 17.88 s +2024-11-21 17:04:40.288235: +2024-11-21 17:04:40.288442: Epoch 1146 +2024-11-21 17:04:40.288568: Current learning rate: 0.0087 +2024-11-21 17:05:00.162975: train_loss -0.7441 +2024-11-21 17:05:00.170698: val_loss -0.7468 +2024-11-21 17:05:00.170850: Pseudo dice [0.8384] +2024-11-21 17:05:00.170941: Epoch time: 19.88 s +2024-11-21 17:05:01.012055: +2024-11-21 17:05:01.012338: Epoch 1147 +2024-11-21 17:05:01.012464: Current learning rate: 0.0087 +2024-11-21 17:05:19.607242: train_loss -0.7674 +2024-11-21 17:05:19.613572: val_loss -0.7579 +2024-11-21 17:05:19.613724: Pseudo dice [0.8447] +2024-11-21 17:05:19.613818: Epoch time: 18.6 s +2024-11-21 17:05:20.438118: +2024-11-21 17:05:20.438339: Epoch 1148 +2024-11-21 17:05:20.438479: Current learning rate: 0.0087 +2024-11-21 17:05:40.129097: train_loss -0.7631 +2024-11-21 17:05:40.134789: val_loss -0.7688 +2024-11-21 17:05:40.134921: Pseudo dice [0.8604] +2024-11-21 17:05:40.135013: Epoch time: 19.69 s +2024-11-21 17:05:40.955470: +2024-11-21 17:05:40.955683: Epoch 1149 +2024-11-21 17:05:40.955802: Current learning rate: 0.0087 +2024-11-21 17:06:00.395001: train_loss -0.7674 +2024-11-21 17:06:00.411715: val_loss -0.7693 +2024-11-21 17:06:00.411866: Pseudo dice [0.8475] +2024-11-21 17:06:00.411969: Epoch time: 19.44 s +2024-11-21 17:06:01.685591: +2024-11-21 17:06:01.685837: Epoch 1150 +2024-11-21 17:06:01.685969: Current learning rate: 0.0087 +2024-11-21 17:06:21.220552: train_loss -0.7658 +2024-11-21 17:06:21.225971: val_loss -0.7635 +2024-11-21 17:06:21.226085: Pseudo dice [0.845] +2024-11-21 17:06:21.226226: Epoch time: 19.54 s +2024-11-21 17:06:22.039046: +2024-11-21 17:06:22.039362: Epoch 1151 +2024-11-21 17:06:22.039497: Current learning rate: 0.0087 +2024-11-21 17:06:40.521250: train_loss -0.7509 +2024-11-21 17:06:40.535453: val_loss -0.7667 +2024-11-21 17:06:40.535601: Pseudo dice [0.8517] +2024-11-21 17:06:40.535697: Epoch time: 18.48 s +2024-11-21 17:06:41.688373: +2024-11-21 17:06:41.688610: Epoch 1152 +2024-11-21 17:06:41.688747: Current learning rate: 0.00869 +2024-11-21 17:07:01.753542: train_loss -0.7504 +2024-11-21 17:07:01.758941: val_loss -0.7714 +2024-11-21 17:07:01.759088: Pseudo dice [0.8336] +2024-11-21 17:07:01.759176: Epoch time: 20.07 s +2024-11-21 17:07:02.640698: +2024-11-21 17:07:02.640913: Epoch 1153 +2024-11-21 17:07:02.641026: Current learning rate: 0.00869 +2024-11-21 17:07:23.051248: train_loss -0.7557 +2024-11-21 17:07:23.059096: val_loss -0.7583 +2024-11-21 17:07:23.059233: Pseudo dice [0.8384] +2024-11-21 17:07:23.059343: Epoch time: 20.41 s +2024-11-21 17:07:23.918211: +2024-11-21 17:07:23.918412: Epoch 1154 +2024-11-21 17:07:23.918558: Current learning rate: 0.00869 +2024-11-21 17:07:43.640945: train_loss -0.7548 +2024-11-21 17:07:43.652481: val_loss -0.7772 +2024-11-21 17:07:43.652624: Pseudo dice [0.8676] +2024-11-21 17:07:43.652712: Epoch time: 19.72 s +2024-11-21 17:07:44.475650: +2024-11-21 17:07:44.475868: Epoch 1155 +2024-11-21 17:07:44.475980: Current learning rate: 0.00869 +2024-11-21 17:08:02.916594: train_loss -0.7603 +2024-11-21 17:08:02.930581: val_loss -0.7673 +2024-11-21 17:08:02.930739: Pseudo dice [0.8545] +2024-11-21 17:08:02.930842: Epoch time: 18.44 s +2024-11-21 17:08:03.917142: +2024-11-21 17:08:03.917380: Epoch 1156 +2024-11-21 17:08:03.917497: Current learning rate: 0.00869 +2024-11-21 17:08:22.629876: train_loss -0.7628 +2024-11-21 17:08:22.639651: val_loss -0.7399 +2024-11-21 17:08:22.639804: Pseudo dice [0.8434] +2024-11-21 17:08:22.639898: Epoch time: 18.71 s +2024-11-21 17:08:23.607785: +2024-11-21 17:08:23.607987: Epoch 1157 +2024-11-21 17:08:23.608129: Current learning rate: 0.00869 +2024-11-21 17:08:42.833085: train_loss -0.7531 +2024-11-21 17:08:42.835296: val_loss -0.7534 +2024-11-21 17:08:42.835410: Pseudo dice [0.843] +2024-11-21 17:08:42.835495: Epoch time: 19.23 s +2024-11-21 17:08:43.653631: +2024-11-21 17:08:43.653873: Epoch 1158 +2024-11-21 17:08:43.653992: Current learning rate: 0.00869 +2024-11-21 17:09:03.523881: train_loss -0.7529 +2024-11-21 17:09:03.529366: val_loss -0.7633 +2024-11-21 17:09:03.529495: Pseudo dice [0.8318] +2024-11-21 17:09:03.529606: Epoch time: 19.87 s +2024-11-21 17:09:04.519493: +2024-11-21 17:09:04.519688: Epoch 1159 +2024-11-21 17:09:04.519859: Current learning rate: 0.00869 +2024-11-21 17:09:22.819974: train_loss -0.7535 +2024-11-21 17:09:22.827546: val_loss -0.754 +2024-11-21 17:09:22.827712: Pseudo dice [0.8357] +2024-11-21 17:09:22.827823: Epoch time: 18.3 s +2024-11-21 17:09:23.750938: +2024-11-21 17:09:23.751177: Epoch 1160 +2024-11-21 17:09:23.751294: Current learning rate: 0.00868 +2024-11-21 17:09:43.175600: train_loss -0.7661 +2024-11-21 17:09:43.180208: val_loss -0.7604 +2024-11-21 17:09:43.180358: Pseudo dice [0.865] +2024-11-21 17:09:43.180449: Epoch time: 19.43 s +2024-11-21 17:09:44.020720: +2024-11-21 17:09:44.020933: Epoch 1161 +2024-11-21 17:09:44.021056: Current learning rate: 0.00868 +2024-11-21 17:10:04.107577: train_loss -0.7562 +2024-11-21 17:10:04.109349: val_loss -0.7553 +2024-11-21 17:10:04.109469: Pseudo dice [0.8391] +2024-11-21 17:10:04.109573: Epoch time: 20.09 s +2024-11-21 17:10:05.333204: +2024-11-21 17:10:05.333441: Epoch 1162 +2024-11-21 17:10:05.333580: Current learning rate: 0.00868 +2024-11-21 17:10:24.924695: train_loss -0.7382 +2024-11-21 17:10:24.937064: val_loss -0.726 +2024-11-21 17:10:24.937209: Pseudo dice [0.8211] +2024-11-21 17:10:24.937300: Epoch time: 19.59 s +2024-11-21 17:10:25.744210: +2024-11-21 17:10:25.744453: Epoch 1163 +2024-11-21 17:10:25.744589: Current learning rate: 0.00868 +2024-11-21 17:10:45.362160: train_loss -0.7446 +2024-11-21 17:10:45.367557: val_loss -0.7607 +2024-11-21 17:10:45.367676: Pseudo dice [0.8462] +2024-11-21 17:10:45.367757: Epoch time: 19.62 s +2024-11-21 17:10:46.186100: +2024-11-21 17:10:46.186352: Epoch 1164 +2024-11-21 17:10:46.186476: Current learning rate: 0.00868 +2024-11-21 17:11:05.504664: train_loss -0.7758 +2024-11-21 17:11:05.516919: val_loss -0.7519 +2024-11-21 17:11:05.517113: Pseudo dice [0.8397] +2024-11-21 17:11:05.517241: Epoch time: 19.32 s +2024-11-21 17:11:06.530757: +2024-11-21 17:11:06.531320: Epoch 1165 +2024-11-21 17:11:06.531465: Current learning rate: 0.00868 +2024-11-21 17:11:25.743731: train_loss -0.7593 +2024-11-21 17:11:25.745764: val_loss -0.7697 +2024-11-21 17:11:25.745869: Pseudo dice [0.8468] +2024-11-21 17:11:25.745970: Epoch time: 19.21 s +2024-11-21 17:11:26.561614: +2024-11-21 17:11:26.561834: Epoch 1166 +2024-11-21 17:11:26.561963: Current learning rate: 0.00868 +2024-11-21 17:11:44.982427: train_loss -0.7634 +2024-11-21 17:11:44.984344: val_loss -0.741 +2024-11-21 17:11:44.984451: Pseudo dice [0.8249] +2024-11-21 17:11:44.984540: Epoch time: 18.42 s +2024-11-21 17:11:45.794789: +2024-11-21 17:11:45.794993: Epoch 1167 +2024-11-21 17:11:45.795109: Current learning rate: 0.00868 +2024-11-21 17:12:05.965113: train_loss -0.7662 +2024-11-21 17:12:05.968175: val_loss -0.7679 +2024-11-21 17:12:05.968277: Pseudo dice [0.8474] +2024-11-21 17:12:05.968379: Epoch time: 20.17 s +2024-11-21 17:12:06.820920: +2024-11-21 17:12:06.821150: Epoch 1168 +2024-11-21 17:12:06.821509: Current learning rate: 0.00868 +2024-11-21 17:12:26.342460: train_loss -0.7625 +2024-11-21 17:12:26.347799: val_loss -0.7734 +2024-11-21 17:12:26.347954: Pseudo dice [0.8336] +2024-11-21 17:12:26.348054: Epoch time: 19.52 s +2024-11-21 17:12:27.169580: +2024-11-21 17:12:27.169781: Epoch 1169 +2024-11-21 17:12:27.169918: Current learning rate: 0.00867 +2024-11-21 17:12:47.739635: train_loss -0.7601 +2024-11-21 17:12:47.742569: val_loss -0.7631 +2024-11-21 17:12:47.742672: Pseudo dice [0.8482] +2024-11-21 17:12:47.742778: Epoch time: 20.57 s +2024-11-21 17:12:48.554206: +2024-11-21 17:12:48.554410: Epoch 1170 +2024-11-21 17:12:48.554534: Current learning rate: 0.00867 +2024-11-21 17:13:07.666682: train_loss -0.7658 +2024-11-21 17:13:07.670453: val_loss -0.7577 +2024-11-21 17:13:07.670554: Pseudo dice [0.8373] +2024-11-21 17:13:07.670665: Epoch time: 19.11 s +2024-11-21 17:13:08.487506: +2024-11-21 17:13:08.487709: Epoch 1171 +2024-11-21 17:13:08.487835: Current learning rate: 0.00867 +2024-11-21 17:13:28.517102: train_loss -0.7596 +2024-11-21 17:13:28.521977: val_loss -0.7635 +2024-11-21 17:13:28.522116: Pseudo dice [0.8509] +2024-11-21 17:13:28.522212: Epoch time: 20.03 s +2024-11-21 17:13:29.353038: +2024-11-21 17:13:29.353248: Epoch 1172 +2024-11-21 17:13:29.353371: Current learning rate: 0.00867 +2024-11-21 17:13:47.653764: train_loss -0.7709 +2024-11-21 17:13:47.663819: val_loss -0.7619 +2024-11-21 17:13:47.663960: Pseudo dice [0.858] +2024-11-21 17:13:47.664053: Epoch time: 18.3 s +2024-11-21 17:13:48.719954: +2024-11-21 17:13:48.720162: Epoch 1173 +2024-11-21 17:13:48.720291: Current learning rate: 0.00867 +2024-11-21 17:14:07.875113: train_loss -0.7576 +2024-11-21 17:14:07.883178: val_loss -0.7611 +2024-11-21 17:14:07.883329: Pseudo dice [0.8463] +2024-11-21 17:14:07.883436: Epoch time: 19.16 s +2024-11-21 17:14:08.778405: +2024-11-21 17:14:08.778622: Epoch 1174 +2024-11-21 17:14:08.778753: Current learning rate: 0.00867 +2024-11-21 17:14:27.853132: train_loss -0.7572 +2024-11-21 17:14:27.859186: val_loss -0.7598 +2024-11-21 17:14:27.859333: Pseudo dice [0.8473] +2024-11-21 17:14:27.859418: Epoch time: 19.08 s +2024-11-21 17:14:28.688031: +2024-11-21 17:14:28.688255: Epoch 1175 +2024-11-21 17:14:28.688382: Current learning rate: 0.00867 +2024-11-21 17:14:48.703232: train_loss -0.7628 +2024-11-21 17:14:48.726777: val_loss -0.7587 +2024-11-21 17:14:48.726950: Pseudo dice [0.8379] +2024-11-21 17:14:48.727057: Epoch time: 20.02 s +2024-11-21 17:14:49.563368: +2024-11-21 17:14:49.563653: Epoch 1176 +2024-11-21 17:14:49.563766: Current learning rate: 0.00867 +2024-11-21 17:15:08.400292: train_loss -0.774 +2024-11-21 17:15:08.409970: val_loss -0.7859 +2024-11-21 17:15:08.410111: Pseudo dice [0.8472] +2024-11-21 17:15:08.410204: Epoch time: 18.84 s +2024-11-21 17:15:09.233510: +2024-11-21 17:15:09.233723: Epoch 1177 +2024-11-21 17:15:09.233855: Current learning rate: 0.00867 +2024-11-21 17:15:28.308427: train_loss -0.7648 +2024-11-21 17:15:28.316459: val_loss -0.7681 +2024-11-21 17:15:28.316587: Pseudo dice [0.8329] +2024-11-21 17:15:28.316675: Epoch time: 19.08 s +2024-11-21 17:15:29.150117: +2024-11-21 17:15:29.150326: Epoch 1178 +2024-11-21 17:15:29.150445: Current learning rate: 0.00866 +2024-11-21 17:15:48.671403: train_loss -0.7723 +2024-11-21 17:15:48.678539: val_loss -0.7572 +2024-11-21 17:15:48.678672: Pseudo dice [0.8244] +2024-11-21 17:15:48.678772: Epoch time: 19.52 s +2024-11-21 17:15:49.619666: +2024-11-21 17:15:49.619874: Epoch 1179 +2024-11-21 17:15:49.620015: Current learning rate: 0.00866 +2024-11-21 17:16:08.344234: train_loss -0.757 +2024-11-21 17:16:08.353925: val_loss -0.7591 +2024-11-21 17:16:08.354081: Pseudo dice [0.8403] +2024-11-21 17:16:08.354181: Epoch time: 18.73 s +2024-11-21 17:16:09.216822: +2024-11-21 17:16:09.217042: Epoch 1180 +2024-11-21 17:16:09.217177: Current learning rate: 0.00866 +2024-11-21 17:16:27.601084: train_loss -0.7687 +2024-11-21 17:16:27.605742: val_loss -0.7343 +2024-11-21 17:16:27.605882: Pseudo dice [0.8343] +2024-11-21 17:16:27.625307: Epoch time: 18.39 s +2024-11-21 17:16:28.444931: +2024-11-21 17:16:28.445143: Epoch 1181 +2024-11-21 17:16:28.445281: Current learning rate: 0.00866 +2024-11-21 17:16:47.250775: train_loss -0.7393 +2024-11-21 17:16:47.258636: val_loss -0.7291 +2024-11-21 17:16:47.258765: Pseudo dice [0.8307] +2024-11-21 17:16:47.258865: Epoch time: 18.81 s +2024-11-21 17:16:48.181137: +2024-11-21 17:16:48.181368: Epoch 1182 +2024-11-21 17:16:48.181490: Current learning rate: 0.00866 +2024-11-21 17:17:06.650301: train_loss -0.7431 +2024-11-21 17:17:06.656592: val_loss -0.7599 +2024-11-21 17:17:06.656728: Pseudo dice [0.843] +2024-11-21 17:17:06.656826: Epoch time: 18.47 s +2024-11-21 17:17:07.635506: +2024-11-21 17:17:07.635697: Epoch 1183 +2024-11-21 17:17:07.635813: Current learning rate: 0.00866 +2024-11-21 17:17:27.009368: train_loss -0.75 +2024-11-21 17:17:27.017941: val_loss -0.7333 +2024-11-21 17:17:27.018178: Pseudo dice [0.839] +2024-11-21 17:17:27.018275: Epoch time: 19.37 s +2024-11-21 17:17:27.982207: +2024-11-21 17:17:27.982417: Epoch 1184 +2024-11-21 17:17:27.982535: Current learning rate: 0.00866 +2024-11-21 17:17:47.599486: train_loss -0.7478 +2024-11-21 17:17:47.603407: val_loss -0.7515 +2024-11-21 17:17:47.603526: Pseudo dice [0.8308] +2024-11-21 17:17:47.603642: Epoch time: 19.62 s +2024-11-21 17:17:48.795964: +2024-11-21 17:17:48.796184: Epoch 1185 +2024-11-21 17:17:48.796308: Current learning rate: 0.00866 +2024-11-21 17:18:07.846693: train_loss -0.7566 +2024-11-21 17:18:07.854265: val_loss -0.7656 +2024-11-21 17:18:07.854395: Pseudo dice [0.8521] +2024-11-21 17:18:07.854474: Epoch time: 19.05 s +2024-11-21 17:18:08.817709: +2024-11-21 17:18:08.817943: Epoch 1186 +2024-11-21 17:18:08.818071: Current learning rate: 0.00866 +2024-11-21 17:18:28.740524: train_loss -0.7592 +2024-11-21 17:18:28.747175: val_loss -0.7427 +2024-11-21 17:18:28.747316: Pseudo dice [0.8415] +2024-11-21 17:18:28.747420: Epoch time: 19.92 s +2024-11-21 17:18:29.572935: +2024-11-21 17:18:29.573203: Epoch 1187 +2024-11-21 17:18:29.573376: Current learning rate: 0.00865 +2024-11-21 17:18:48.811376: train_loss -0.76 +2024-11-21 17:18:48.833277: val_loss -0.7323 +2024-11-21 17:18:48.833427: Pseudo dice [0.8288] +2024-11-21 17:18:48.833537: Epoch time: 19.24 s +2024-11-21 17:18:49.726957: +2024-11-21 17:18:49.727149: Epoch 1188 +2024-11-21 17:18:49.727271: Current learning rate: 0.00865 +2024-11-21 17:19:08.656347: train_loss -0.7559 +2024-11-21 17:19:08.659381: val_loss -0.7613 +2024-11-21 17:19:08.659502: Pseudo dice [0.8433] +2024-11-21 17:19:08.659586: Epoch time: 18.93 s +2024-11-21 17:19:09.476828: +2024-11-21 17:19:09.477048: Epoch 1189 +2024-11-21 17:19:09.477170: Current learning rate: 0.00865 +2024-11-21 17:19:28.616641: train_loss -0.7618 +2024-11-21 17:19:28.627184: val_loss -0.7362 +2024-11-21 17:19:28.627375: Pseudo dice [0.8375] +2024-11-21 17:19:28.627471: Epoch time: 19.14 s +2024-11-21 17:19:29.618376: +2024-11-21 17:19:29.618609: Epoch 1190 +2024-11-21 17:19:29.618745: Current learning rate: 0.00865 +2024-11-21 17:19:49.426833: train_loss -0.7533 +2024-11-21 17:19:49.434278: val_loss -0.7635 +2024-11-21 17:19:49.434424: Pseudo dice [0.8434] +2024-11-21 17:19:49.434527: Epoch time: 19.81 s +2024-11-21 17:19:50.405260: +2024-11-21 17:19:50.405497: Epoch 1191 +2024-11-21 17:19:50.405609: Current learning rate: 0.00865 +2024-11-21 17:20:09.193383: train_loss -0.7554 +2024-11-21 17:20:09.209350: val_loss -0.7583 +2024-11-21 17:20:09.209525: Pseudo dice [0.8441] +2024-11-21 17:20:09.209620: Epoch time: 18.79 s +2024-11-21 17:20:10.103591: +2024-11-21 17:20:10.103800: Epoch 1192 +2024-11-21 17:20:10.103922: Current learning rate: 0.00865 +2024-11-21 17:20:30.598576: train_loss -0.7523 +2024-11-21 17:20:30.601291: val_loss -0.7576 +2024-11-21 17:20:30.601400: Pseudo dice [0.8535] +2024-11-21 17:20:30.601488: Epoch time: 20.5 s +2024-11-21 17:20:31.559329: +2024-11-21 17:20:31.559605: Epoch 1193 +2024-11-21 17:20:31.559725: Current learning rate: 0.00865 +2024-11-21 17:20:49.659933: train_loss -0.7523 +2024-11-21 17:20:49.678328: val_loss -0.7747 +2024-11-21 17:20:49.678504: Pseudo dice [0.8528] +2024-11-21 17:20:49.678594: Epoch time: 18.1 s +2024-11-21 17:20:50.556629: +2024-11-21 17:20:50.556847: Epoch 1194 +2024-11-21 17:20:50.556988: Current learning rate: 0.00865 +2024-11-21 17:21:09.134692: train_loss -0.7373 +2024-11-21 17:21:09.141827: val_loss -0.7604 +2024-11-21 17:21:09.141973: Pseudo dice [0.8426] +2024-11-21 17:21:09.142066: Epoch time: 18.58 s +2024-11-21 17:21:10.115719: +2024-11-21 17:21:10.115975: Epoch 1195 +2024-11-21 17:21:10.116112: Current learning rate: 0.00864 +2024-11-21 17:21:28.982871: train_loss -0.7461 +2024-11-21 17:21:28.986162: val_loss -0.7654 +2024-11-21 17:21:28.986308: Pseudo dice [0.8515] +2024-11-21 17:21:28.986402: Epoch time: 18.87 s +2024-11-21 17:21:30.193303: +2024-11-21 17:21:30.193522: Epoch 1196 +2024-11-21 17:21:30.193652: Current learning rate: 0.00864 +2024-11-21 17:21:49.920663: train_loss -0.7598 +2024-11-21 17:21:49.924607: val_loss -0.7707 +2024-11-21 17:21:49.924746: Pseudo dice [0.8354] +2024-11-21 17:21:49.924826: Epoch time: 19.73 s +2024-11-21 17:21:50.745957: +2024-11-21 17:21:50.746190: Epoch 1197 +2024-11-21 17:21:50.746328: Current learning rate: 0.00864 +2024-11-21 17:22:09.457069: train_loss -0.766 +2024-11-21 17:22:09.465937: val_loss -0.7469 +2024-11-21 17:22:09.466099: Pseudo dice [0.8508] +2024-11-21 17:22:09.466207: Epoch time: 18.71 s +2024-11-21 17:22:10.284125: +2024-11-21 17:22:10.284614: Epoch 1198 +2024-11-21 17:22:10.284732: Current learning rate: 0.00864 +2024-11-21 17:22:29.550716: train_loss -0.7577 +2024-11-21 17:22:29.562204: val_loss -0.7435 +2024-11-21 17:22:29.562363: Pseudo dice [0.8257] +2024-11-21 17:22:29.562449: Epoch time: 19.27 s +2024-11-21 17:22:30.621172: +2024-11-21 17:22:30.621405: Epoch 1199 +2024-11-21 17:22:30.621531: Current learning rate: 0.00864 +2024-11-21 17:22:50.547443: train_loss -0.7603 +2024-11-21 17:22:50.549949: val_loss -0.7588 +2024-11-21 17:22:50.550081: Pseudo dice [0.8407] +2024-11-21 17:22:50.550169: Epoch time: 19.93 s +2024-11-21 17:22:51.671454: +2024-11-21 17:22:51.671666: Epoch 1200 +2024-11-21 17:22:51.671792: Current learning rate: 0.00864 +2024-11-21 17:23:09.509321: train_loss -0.7564 +2024-11-21 17:23:09.514632: val_loss -0.7521 +2024-11-21 17:23:09.514756: Pseudo dice [0.8431] +2024-11-21 17:23:09.514849: Epoch time: 17.84 s +2024-11-21 17:23:10.381097: +2024-11-21 17:23:10.381309: Epoch 1201 +2024-11-21 17:23:10.381433: Current learning rate: 0.00864 +2024-11-21 17:23:29.608141: train_loss -0.7461 +2024-11-21 17:23:29.616179: val_loss -0.7665 +2024-11-21 17:23:29.616318: Pseudo dice [0.8421] +2024-11-21 17:23:29.616439: Epoch time: 19.23 s +2024-11-21 17:23:30.615912: +2024-11-21 17:23:30.616156: Epoch 1202 +2024-11-21 17:23:30.616278: Current learning rate: 0.00864 +2024-11-21 17:23:49.029630: train_loss -0.7478 +2024-11-21 17:23:49.033818: val_loss -0.7438 +2024-11-21 17:23:49.033936: Pseudo dice [0.8304] +2024-11-21 17:23:49.034068: Epoch time: 18.41 s +2024-11-21 17:23:49.850265: +2024-11-21 17:23:49.850470: Epoch 1203 +2024-11-21 17:23:49.850590: Current learning rate: 0.00864 +2024-11-21 17:24:07.951284: train_loss -0.7515 +2024-11-21 17:24:07.970221: val_loss -0.761 +2024-11-21 17:24:07.970376: Pseudo dice [0.8459] +2024-11-21 17:24:07.970467: Epoch time: 18.1 s +2024-11-21 17:24:08.965958: +2024-11-21 17:24:08.966199: Epoch 1204 +2024-11-21 17:24:08.966323: Current learning rate: 0.00863 +2024-11-21 17:24:28.517824: train_loss -0.7643 +2024-11-21 17:24:28.520905: val_loss -0.7611 +2024-11-21 17:24:28.521035: Pseudo dice [0.8622] +2024-11-21 17:24:28.521133: Epoch time: 19.55 s +2024-11-21 17:24:29.336339: +2024-11-21 17:24:29.336593: Epoch 1205 +2024-11-21 17:24:29.336716: Current learning rate: 0.00863 +2024-11-21 17:24:48.188624: train_loss -0.7641 +2024-11-21 17:24:48.197430: val_loss -0.7671 +2024-11-21 17:24:48.197575: Pseudo dice [0.8464] +2024-11-21 17:24:48.197693: Epoch time: 18.85 s +2024-11-21 17:24:49.199710: +2024-11-21 17:24:49.199928: Epoch 1206 +2024-11-21 17:24:49.200305: Current learning rate: 0.00863 +2024-11-21 17:25:08.289007: train_loss -0.7639 +2024-11-21 17:25:08.291727: val_loss -0.7614 +2024-11-21 17:25:08.291845: Pseudo dice [0.8528] +2024-11-21 17:25:08.291946: Epoch time: 19.09 s +2024-11-21 17:25:09.108316: +2024-11-21 17:25:09.108764: Epoch 1207 +2024-11-21 17:25:09.108908: Current learning rate: 0.00863 +2024-11-21 17:25:28.487096: train_loss -0.7574 +2024-11-21 17:25:28.491425: val_loss -0.746 +2024-11-21 17:25:28.491559: Pseudo dice [0.8296] +2024-11-21 17:25:28.491665: Epoch time: 19.38 s +2024-11-21 17:25:29.725036: +2024-11-21 17:25:29.725287: Epoch 1208 +2024-11-21 17:25:29.725407: Current learning rate: 0.00863 +2024-11-21 17:25:49.268258: train_loss -0.7664 +2024-11-21 17:25:49.271807: val_loss -0.7564 +2024-11-21 17:25:49.271912: Pseudo dice [0.8493] +2024-11-21 17:25:49.272019: Epoch time: 19.54 s +2024-11-21 17:25:50.092205: +2024-11-21 17:25:50.092452: Epoch 1209 +2024-11-21 17:25:50.092585: Current learning rate: 0.00863 +2024-11-21 17:26:09.515837: train_loss -0.7641 +2024-11-21 17:26:09.520072: val_loss -0.7582 +2024-11-21 17:26:09.520223: Pseudo dice [0.8421] +2024-11-21 17:26:09.520323: Epoch time: 19.42 s +2024-11-21 17:26:10.348259: +2024-11-21 17:26:10.348469: Epoch 1210 +2024-11-21 17:26:10.348592: Current learning rate: 0.00863 +2024-11-21 17:26:28.841818: train_loss -0.776 +2024-11-21 17:26:28.849234: val_loss -0.7894 +2024-11-21 17:26:28.849356: Pseudo dice [0.8558] +2024-11-21 17:26:28.849439: Epoch time: 18.49 s +2024-11-21 17:26:29.676605: +2024-11-21 17:26:29.676847: Epoch 1211 +2024-11-21 17:26:29.676968: Current learning rate: 0.00863 +2024-11-21 17:26:48.467185: train_loss -0.7589 +2024-11-21 17:26:48.469968: val_loss -0.775 +2024-11-21 17:26:48.470103: Pseudo dice [0.8474] +2024-11-21 17:26:48.470190: Epoch time: 18.79 s +2024-11-21 17:26:49.291768: +2024-11-21 17:26:49.291976: Epoch 1212 +2024-11-21 17:26:49.292107: Current learning rate: 0.00863 +2024-11-21 17:27:09.823471: train_loss -0.7694 +2024-11-21 17:27:09.830535: val_loss -0.7506 +2024-11-21 17:27:09.830683: Pseudo dice [0.8333] +2024-11-21 17:27:09.830778: Epoch time: 20.53 s +2024-11-21 17:27:10.813628: +2024-11-21 17:27:10.813863: Epoch 1213 +2024-11-21 17:27:10.814000: Current learning rate: 0.00862 +2024-11-21 17:27:30.034673: train_loss -0.7538 +2024-11-21 17:27:30.038395: val_loss -0.7567 +2024-11-21 17:27:30.038530: Pseudo dice [0.8243] +2024-11-21 17:27:30.038632: Epoch time: 19.22 s +2024-11-21 17:27:31.018143: +2024-11-21 17:27:31.018356: Epoch 1214 +2024-11-21 17:27:31.018479: Current learning rate: 0.00862 +2024-11-21 17:27:50.434147: train_loss -0.7629 +2024-11-21 17:27:50.440131: val_loss -0.7466 +2024-11-21 17:27:50.440252: Pseudo dice [0.835] +2024-11-21 17:27:50.440348: Epoch time: 19.42 s +2024-11-21 17:27:51.408648: +2024-11-21 17:27:51.408884: Epoch 1215 +2024-11-21 17:27:51.409010: Current learning rate: 0.00862 +2024-11-21 17:28:09.646291: train_loss -0.7621 +2024-11-21 17:28:09.653834: val_loss -0.7515 +2024-11-21 17:28:09.653992: Pseudo dice [0.8459] +2024-11-21 17:28:09.654089: Epoch time: 18.24 s +2024-11-21 17:28:10.484743: +2024-11-21 17:28:10.484973: Epoch 1216 +2024-11-21 17:28:10.485091: Current learning rate: 0.00862 +2024-11-21 17:28:30.015813: train_loss -0.765 +2024-11-21 17:28:30.023806: val_loss -0.781 +2024-11-21 17:28:30.023966: Pseudo dice [0.8555] +2024-11-21 17:28:30.024078: Epoch time: 19.53 s +2024-11-21 17:28:30.848902: +2024-11-21 17:28:30.849119: Epoch 1217 +2024-11-21 17:28:30.849252: Current learning rate: 0.00862 +2024-11-21 17:28:49.792780: train_loss -0.7635 +2024-11-21 17:28:49.799630: val_loss -0.7622 +2024-11-21 17:28:49.799761: Pseudo dice [0.8453] +2024-11-21 17:28:49.799847: Epoch time: 18.94 s +2024-11-21 17:28:50.639217: +2024-11-21 17:28:50.639441: Epoch 1218 +2024-11-21 17:28:50.639561: Current learning rate: 0.00862 +2024-11-21 17:29:10.224368: train_loss -0.7499 +2024-11-21 17:29:10.236499: val_loss -0.7512 +2024-11-21 17:29:10.236630: Pseudo dice [0.8417] +2024-11-21 17:29:10.236719: Epoch time: 19.59 s +2024-11-21 17:29:11.477034: +2024-11-21 17:29:11.477240: Epoch 1219 +2024-11-21 17:29:11.477365: Current learning rate: 0.00862 +2024-11-21 17:29:31.169308: train_loss -0.7479 +2024-11-21 17:29:31.172894: val_loss -0.7391 +2024-11-21 17:29:31.173046: Pseudo dice [0.8422] +2024-11-21 17:29:31.173144: Epoch time: 19.69 s +2024-11-21 17:29:31.991190: +2024-11-21 17:29:31.991465: Epoch 1220 +2024-11-21 17:29:31.991582: Current learning rate: 0.00862 +2024-11-21 17:29:51.805539: train_loss -0.7589 +2024-11-21 17:29:51.855806: val_loss -0.7542 +2024-11-21 17:29:51.855955: Pseudo dice [0.8478] +2024-11-21 17:29:51.856057: Epoch time: 19.82 s +2024-11-21 17:29:52.680995: +2024-11-21 17:29:52.681248: Epoch 1221 +2024-11-21 17:29:52.681375: Current learning rate: 0.00862 +2024-11-21 17:30:10.722576: train_loss -0.7636 +2024-11-21 17:30:10.725590: val_loss -0.7549 +2024-11-21 17:30:10.725730: Pseudo dice [0.8615] +2024-11-21 17:30:10.725841: Epoch time: 18.04 s +2024-11-21 17:30:11.754919: +2024-11-21 17:30:11.755137: Epoch 1222 +2024-11-21 17:30:11.755256: Current learning rate: 0.00861 +2024-11-21 17:30:29.875245: train_loss -0.7547 +2024-11-21 17:30:29.881617: val_loss -0.7425 +2024-11-21 17:30:29.881799: Pseudo dice [0.8355] +2024-11-21 17:30:29.881899: Epoch time: 18.12 s +2024-11-21 17:30:30.710396: +2024-11-21 17:30:30.710603: Epoch 1223 +2024-11-21 17:30:30.710722: Current learning rate: 0.00861 +2024-11-21 17:30:49.554421: train_loss -0.7688 +2024-11-21 17:30:49.561751: val_loss -0.7628 +2024-11-21 17:30:49.561911: Pseudo dice [0.8466] +2024-11-21 17:30:49.562019: Epoch time: 18.84 s +2024-11-21 17:30:50.380619: +2024-11-21 17:30:50.380839: Epoch 1224 +2024-11-21 17:30:50.380962: Current learning rate: 0.00861 +2024-11-21 17:31:09.863659: train_loss -0.7463 +2024-11-21 17:31:09.866907: val_loss -0.7325 +2024-11-21 17:31:09.867029: Pseudo dice [0.8343] +2024-11-21 17:31:09.867141: Epoch time: 19.48 s +2024-11-21 17:31:10.746516: +2024-11-21 17:31:10.746758: Epoch 1225 +2024-11-21 17:31:10.746877: Current learning rate: 0.00861 +2024-11-21 17:31:30.283195: train_loss -0.7487 +2024-11-21 17:31:30.289743: val_loss -0.7568 +2024-11-21 17:31:30.289870: Pseudo dice [0.8407] +2024-11-21 17:31:30.289967: Epoch time: 19.54 s +2024-11-21 17:31:31.144705: +2024-11-21 17:31:31.144928: Epoch 1226 +2024-11-21 17:31:31.145046: Current learning rate: 0.00861 +2024-11-21 17:31:49.738375: train_loss -0.7524 +2024-11-21 17:31:49.753461: val_loss -0.7653 +2024-11-21 17:31:49.753623: Pseudo dice [0.829] +2024-11-21 17:31:49.753713: Epoch time: 18.59 s +2024-11-21 17:31:50.616072: +2024-11-21 17:31:50.616274: Epoch 1227 +2024-11-21 17:31:50.616404: Current learning rate: 0.00861 +2024-11-21 17:32:09.927103: train_loss -0.7579 +2024-11-21 17:32:09.930245: val_loss -0.7778 +2024-11-21 17:32:09.930342: Pseudo dice [0.8415] +2024-11-21 17:32:09.930429: Epoch time: 19.31 s +2024-11-21 17:32:10.746584: +2024-11-21 17:32:10.746783: Epoch 1228 +2024-11-21 17:32:10.746909: Current learning rate: 0.00861 +2024-11-21 17:32:29.388759: train_loss -0.7575 +2024-11-21 17:32:29.401212: val_loss -0.7628 +2024-11-21 17:32:29.401353: Pseudo dice [0.8467] +2024-11-21 17:32:29.401738: Epoch time: 18.64 s +2024-11-21 17:32:30.360359: +2024-11-21 17:32:30.360641: Epoch 1229 +2024-11-21 17:32:30.360766: Current learning rate: 0.00861 +2024-11-21 17:32:50.782111: train_loss -0.772 +2024-11-21 17:32:50.788550: val_loss -0.7736 +2024-11-21 17:32:50.788686: Pseudo dice [0.8491] +2024-11-21 17:32:50.788765: Epoch time: 20.42 s +2024-11-21 17:32:51.670680: +2024-11-21 17:32:51.670884: Epoch 1230 +2024-11-21 17:32:51.671048: Current learning rate: 0.0086 +2024-11-21 17:33:11.607618: train_loss -0.757 +2024-11-21 17:33:11.610936: val_loss -0.7375 +2024-11-21 17:33:11.611047: Pseudo dice [0.837] +2024-11-21 17:33:11.611177: Epoch time: 19.94 s +2024-11-21 17:33:12.824675: +2024-11-21 17:33:12.824888: Epoch 1231 +2024-11-21 17:33:12.825022: Current learning rate: 0.0086 +2024-11-21 17:33:31.181391: train_loss -0.7727 +2024-11-21 17:33:31.204163: val_loss -0.7572 +2024-11-21 17:33:31.204547: Pseudo dice [0.8645] +2024-11-21 17:33:31.204668: Epoch time: 18.36 s +2024-11-21 17:33:32.051129: +2024-11-21 17:33:32.051348: Epoch 1232 +2024-11-21 17:33:32.051461: Current learning rate: 0.0086 +2024-11-21 17:33:50.910325: train_loss -0.7708 +2024-11-21 17:33:50.917355: val_loss -0.7849 +2024-11-21 17:33:50.917486: Pseudo dice [0.854] +2024-11-21 17:33:50.917567: Epoch time: 18.86 s +2024-11-21 17:33:51.956523: +2024-11-21 17:33:51.956748: Epoch 1233 +2024-11-21 17:33:51.956880: Current learning rate: 0.0086 +2024-11-21 17:34:11.542270: train_loss -0.7587 +2024-11-21 17:34:11.562199: val_loss -0.7554 +2024-11-21 17:34:11.562335: Pseudo dice [0.8374] +2024-11-21 17:34:11.562471: Epoch time: 19.59 s +2024-11-21 17:34:12.378444: +2024-11-21 17:34:12.378711: Epoch 1234 +2024-11-21 17:34:12.378829: Current learning rate: 0.0086 +2024-11-21 17:34:31.071938: train_loss -0.7664 +2024-11-21 17:34:31.090605: val_loss -0.7568 +2024-11-21 17:34:31.090766: Pseudo dice [0.8468] +2024-11-21 17:34:31.090874: Epoch time: 18.69 s +2024-11-21 17:34:31.984094: +2024-11-21 17:34:31.984294: Epoch 1235 +2024-11-21 17:34:31.984408: Current learning rate: 0.0086 +2024-11-21 17:34:51.826637: train_loss -0.7689 +2024-11-21 17:34:51.829699: val_loss -0.7635 +2024-11-21 17:34:51.829840: Pseudo dice [0.8615] +2024-11-21 17:34:51.829932: Epoch time: 19.84 s +2024-11-21 17:34:52.645642: +2024-11-21 17:34:52.645859: Epoch 1236 +2024-11-21 17:34:52.645984: Current learning rate: 0.0086 +2024-11-21 17:35:11.884087: train_loss -0.7687 +2024-11-21 17:35:11.890590: val_loss -0.7647 +2024-11-21 17:35:11.890736: Pseudo dice [0.8483] +2024-11-21 17:35:11.890823: Epoch time: 19.24 s +2024-11-21 17:35:12.937897: +2024-11-21 17:35:12.938094: Epoch 1237 +2024-11-21 17:35:12.938212: Current learning rate: 0.0086 +2024-11-21 17:35:32.612541: train_loss -0.7593 +2024-11-21 17:35:32.616075: val_loss -0.757 +2024-11-21 17:35:32.616190: Pseudo dice [0.8488] +2024-11-21 17:35:32.616303: Epoch time: 19.68 s +2024-11-21 17:35:33.435384: +2024-11-21 17:35:33.435593: Epoch 1238 +2024-11-21 17:35:33.435705: Current learning rate: 0.0086 +2024-11-21 17:35:52.219354: train_loss -0.7571 +2024-11-21 17:35:52.225653: val_loss -0.7519 +2024-11-21 17:35:52.225807: Pseudo dice [0.8487] +2024-11-21 17:35:52.225898: Epoch time: 18.78 s +2024-11-21 17:35:53.209564: +2024-11-21 17:35:53.209791: Epoch 1239 +2024-11-21 17:35:53.209908: Current learning rate: 0.00859 +2024-11-21 17:36:12.423018: train_loss -0.7452 +2024-11-21 17:36:12.429252: val_loss -0.7567 +2024-11-21 17:36:12.429459: Pseudo dice [0.8533] +2024-11-21 17:36:12.429555: Epoch time: 19.21 s +2024-11-21 17:36:12.429661: Yayy! New best EMA pseudo Dice: 0.8477 +2024-11-21 17:36:13.481900: +2024-11-21 17:36:13.482140: Epoch 1240 +2024-11-21 17:36:13.482275: Current learning rate: 0.00859 +2024-11-21 17:36:33.088473: train_loss -0.7501 +2024-11-21 17:36:33.092893: val_loss -0.7837 +2024-11-21 17:36:33.093001: Pseudo dice [0.8446] +2024-11-21 17:36:33.093095: Epoch time: 19.61 s +2024-11-21 17:36:33.903088: +2024-11-21 17:36:33.903315: Epoch 1241 +2024-11-21 17:36:33.903438: Current learning rate: 0.00859 +2024-11-21 17:36:53.680914: train_loss -0.7656 +2024-11-21 17:36:53.693898: val_loss -0.7603 +2024-11-21 17:36:53.694056: Pseudo dice [0.8393] +2024-11-21 17:36:53.694166: Epoch time: 19.78 s +2024-11-21 17:36:54.983087: +2024-11-21 17:36:54.983306: Epoch 1242 +2024-11-21 17:36:54.983438: Current learning rate: 0.00859 +2024-11-21 17:37:14.056729: train_loss -0.7629 +2024-11-21 17:37:14.065653: val_loss -0.7542 +2024-11-21 17:37:14.065784: Pseudo dice [0.8536] +2024-11-21 17:37:14.065868: Epoch time: 19.07 s +2024-11-21 17:37:14.891321: +2024-11-21 17:37:14.891541: Epoch 1243 +2024-11-21 17:37:14.891668: Current learning rate: 0.00859 +2024-11-21 17:37:33.671523: train_loss -0.7557 +2024-11-21 17:37:33.678945: val_loss -0.7388 +2024-11-21 17:37:33.679113: Pseudo dice [0.8525] +2024-11-21 17:37:33.679217: Epoch time: 18.78 s +2024-11-21 17:37:33.679311: Yayy! New best EMA pseudo Dice: 0.8478 +2024-11-21 17:37:34.786056: +2024-11-21 17:37:34.786289: Epoch 1244 +2024-11-21 17:37:34.786421: Current learning rate: 0.00859 +2024-11-21 17:37:53.210214: train_loss -0.7676 +2024-11-21 17:37:53.216955: val_loss -0.7704 +2024-11-21 17:37:53.217159: Pseudo dice [0.8557] +2024-11-21 17:37:53.217259: Epoch time: 18.42 s +2024-11-21 17:37:53.217347: Yayy! New best EMA pseudo Dice: 0.8486 +2024-11-21 17:37:54.310571: +2024-11-21 17:37:54.310796: Epoch 1245 +2024-11-21 17:37:54.310919: Current learning rate: 0.00859 +2024-11-21 17:38:13.612999: train_loss -0.7707 +2024-11-21 17:38:13.618213: val_loss -0.7744 +2024-11-21 17:38:13.618330: Pseudo dice [0.8491] +2024-11-21 17:38:13.618419: Epoch time: 19.3 s +2024-11-21 17:38:13.618513: Yayy! New best EMA pseudo Dice: 0.8487 +2024-11-21 17:38:14.709112: +2024-11-21 17:38:14.709369: Epoch 1246 +2024-11-21 17:38:14.709501: Current learning rate: 0.00859 +2024-11-21 17:38:34.140019: train_loss -0.7635 +2024-11-21 17:38:34.143533: val_loss -0.7307 +2024-11-21 17:38:34.143670: Pseudo dice [0.8357] +2024-11-21 17:38:34.143754: Epoch time: 19.43 s +2024-11-21 17:38:34.969785: +2024-11-21 17:38:34.970011: Epoch 1247 +2024-11-21 17:38:34.970142: Current learning rate: 0.00859 +2024-11-21 17:38:53.899880: train_loss -0.7584 +2024-11-21 17:38:53.904706: val_loss -0.7609 +2024-11-21 17:38:53.904820: Pseudo dice [0.847] +2024-11-21 17:38:53.904916: Epoch time: 18.93 s +2024-11-21 17:38:54.723172: +2024-11-21 17:38:54.723389: Epoch 1248 +2024-11-21 17:38:54.723523: Current learning rate: 0.00858 +2024-11-21 17:39:13.754325: train_loss -0.7727 +2024-11-21 17:39:13.761401: val_loss -0.7569 +2024-11-21 17:39:13.761540: Pseudo dice [0.8385] +2024-11-21 17:39:13.761626: Epoch time: 19.03 s +2024-11-21 17:39:14.588400: +2024-11-21 17:39:14.588642: Epoch 1249 +2024-11-21 17:39:14.588790: Current learning rate: 0.00858 +2024-11-21 17:39:33.519934: train_loss -0.7691 +2024-11-21 17:39:33.523289: val_loss -0.7424 +2024-11-21 17:39:33.523418: Pseudo dice [0.8393] +2024-11-21 17:39:33.523518: Epoch time: 18.93 s +2024-11-21 17:39:34.606783: +2024-11-21 17:39:34.606998: Epoch 1250 +2024-11-21 17:39:34.607133: Current learning rate: 0.00858 +2024-11-21 17:39:54.453620: train_loss -0.7516 +2024-11-21 17:39:54.458223: val_loss -0.7736 +2024-11-21 17:39:54.458348: Pseudo dice [0.8538] +2024-11-21 17:39:54.458473: Epoch time: 19.85 s +2024-11-21 17:39:55.273791: +2024-11-21 17:39:55.273997: Epoch 1251 +2024-11-21 17:39:55.274115: Current learning rate: 0.00858 +2024-11-21 17:40:14.990624: train_loss -0.7543 +2024-11-21 17:40:14.993878: val_loss -0.7717 +2024-11-21 17:40:14.994028: Pseudo dice [0.8516] +2024-11-21 17:40:14.994138: Epoch time: 19.72 s +2024-11-21 17:40:15.811764: +2024-11-21 17:40:15.811970: Epoch 1252 +2024-11-21 17:40:15.812094: Current learning rate: 0.00858 +2024-11-21 17:40:35.123528: train_loss -0.7522 +2024-11-21 17:40:35.126756: val_loss -0.7309 +2024-11-21 17:40:35.126865: Pseudo dice [0.8171] +2024-11-21 17:40:35.126974: Epoch time: 19.31 s +2024-11-21 17:40:35.936001: +2024-11-21 17:40:35.936226: Epoch 1253 +2024-11-21 17:40:35.936346: Current learning rate: 0.00858 +2024-11-21 17:40:53.855735: train_loss -0.7687 +2024-11-21 17:40:53.862508: val_loss -0.7581 +2024-11-21 17:40:53.862663: Pseudo dice [0.8412] +2024-11-21 17:40:53.862755: Epoch time: 17.92 s +2024-11-21 17:40:54.847435: +2024-11-21 17:40:54.847672: Epoch 1254 +2024-11-21 17:40:54.847791: Current learning rate: 0.00858 +2024-11-21 17:41:13.432089: train_loss -0.7633 +2024-11-21 17:41:13.439956: val_loss -0.758 +2024-11-21 17:41:13.440120: Pseudo dice [0.8384] +2024-11-21 17:41:13.440207: Epoch time: 18.59 s +2024-11-21 17:41:14.377707: +2024-11-21 17:41:14.377950: Epoch 1255 +2024-11-21 17:41:14.378084: Current learning rate: 0.00858 +2024-11-21 17:41:34.311452: train_loss -0.7605 +2024-11-21 17:41:34.347671: val_loss -0.7615 +2024-11-21 17:41:34.347862: Pseudo dice [0.8559] +2024-11-21 17:41:34.347972: Epoch time: 19.93 s +2024-11-21 17:41:35.254111: +2024-11-21 17:41:35.254311: Epoch 1256 +2024-11-21 17:41:35.254668: Current learning rate: 0.00858 +2024-11-21 17:41:53.814541: train_loss -0.7423 +2024-11-21 17:41:53.817442: val_loss -0.731 +2024-11-21 17:41:53.817548: Pseudo dice [0.8331] +2024-11-21 17:41:53.817636: Epoch time: 18.56 s +2024-11-21 17:41:54.638372: +2024-11-21 17:41:54.638602: Epoch 1257 +2024-11-21 17:41:54.638728: Current learning rate: 0.00857 +2024-11-21 17:42:13.974111: train_loss -0.7316 +2024-11-21 17:42:13.981170: val_loss -0.7253 +2024-11-21 17:42:13.981315: Pseudo dice [0.8156] +2024-11-21 17:42:13.981402: Epoch time: 19.34 s +2024-11-21 17:42:14.796985: +2024-11-21 17:42:14.797225: Epoch 1258 +2024-11-21 17:42:14.797355: Current learning rate: 0.00857 +2024-11-21 17:42:34.619287: train_loss -0.7364 +2024-11-21 17:42:34.624973: val_loss -0.7479 +2024-11-21 17:42:34.625174: Pseudo dice [0.839] +2024-11-21 17:42:34.625275: Epoch time: 19.82 s +2024-11-21 17:42:35.447341: +2024-11-21 17:42:35.447558: Epoch 1259 +2024-11-21 17:42:35.447675: Current learning rate: 0.00857 +2024-11-21 17:42:54.675519: train_loss -0.7501 +2024-11-21 17:42:54.683114: val_loss -0.7551 +2024-11-21 17:42:54.683272: Pseudo dice [0.8398] +2024-11-21 17:42:54.683506: Epoch time: 19.23 s +2024-11-21 17:42:55.507439: +2024-11-21 17:42:55.507668: Epoch 1260 +2024-11-21 17:42:55.507781: Current learning rate: 0.00857 +2024-11-21 17:43:15.073722: train_loss -0.7461 +2024-11-21 17:43:15.079358: val_loss -0.7472 +2024-11-21 17:43:15.079494: Pseudo dice [0.8432] +2024-11-21 17:43:15.079604: Epoch time: 19.57 s +2024-11-21 17:43:15.932094: +2024-11-21 17:43:15.932300: Epoch 1261 +2024-11-21 17:43:15.932422: Current learning rate: 0.00857 +2024-11-21 17:43:35.342390: train_loss -0.7619 +2024-11-21 17:43:35.349833: val_loss -0.7368 +2024-11-21 17:43:35.349957: Pseudo dice [0.8377] +2024-11-21 17:43:35.350139: Epoch time: 19.41 s +2024-11-21 17:43:36.401226: +2024-11-21 17:43:36.401439: Epoch 1262 +2024-11-21 17:43:36.401556: Current learning rate: 0.00857 +2024-11-21 17:43:54.757937: train_loss -0.7501 +2024-11-21 17:43:54.780375: val_loss -0.7576 +2024-11-21 17:43:54.780526: Pseudo dice [0.8361] +2024-11-21 17:43:54.780666: Epoch time: 18.36 s +2024-11-21 17:43:55.791176: +2024-11-21 17:43:55.791381: Epoch 1263 +2024-11-21 17:43:55.791498: Current learning rate: 0.00857 +2024-11-21 17:44:14.956749: train_loss -0.7619 +2024-11-21 17:44:14.965117: val_loss -0.7771 +2024-11-21 17:44:14.965245: Pseudo dice [0.8336] +2024-11-21 17:44:14.965364: Epoch time: 19.17 s +2024-11-21 17:44:15.806290: +2024-11-21 17:44:15.806563: Epoch 1264 +2024-11-21 17:44:15.806690: Current learning rate: 0.00857 +2024-11-21 17:44:35.296978: train_loss -0.7465 +2024-11-21 17:44:35.300900: val_loss -0.7676 +2024-11-21 17:44:35.301033: Pseudo dice [0.8438] +2024-11-21 17:44:35.301156: Epoch time: 19.49 s +2024-11-21 17:44:36.483630: +2024-11-21 17:44:36.483844: Epoch 1265 +2024-11-21 17:44:36.483961: Current learning rate: 0.00856 +2024-11-21 17:44:55.808856: train_loss -0.7656 +2024-11-21 17:44:55.828929: val_loss -0.7473 +2024-11-21 17:44:55.829114: Pseudo dice [0.8452] +2024-11-21 17:44:55.829227: Epoch time: 19.33 s +2024-11-21 17:44:56.733163: +2024-11-21 17:44:56.733374: Epoch 1266 +2024-11-21 17:44:56.733488: Current learning rate: 0.00856 +2024-11-21 17:45:16.902234: train_loss -0.7507 +2024-11-21 17:45:16.908261: val_loss -0.7346 +2024-11-21 17:45:16.908423: Pseudo dice [0.8367] +2024-11-21 17:45:16.908517: Epoch time: 20.17 s +2024-11-21 17:45:17.736270: +2024-11-21 17:45:17.736509: Epoch 1267 +2024-11-21 17:45:17.736643: Current learning rate: 0.00856 +2024-11-21 17:45:36.761048: train_loss -0.7407 +2024-11-21 17:45:36.767429: val_loss -0.7578 +2024-11-21 17:45:36.767553: Pseudo dice [0.8433] +2024-11-21 17:45:36.767664: Epoch time: 19.03 s +2024-11-21 17:45:37.664806: +2024-11-21 17:45:37.665022: Epoch 1268 +2024-11-21 17:45:37.665145: Current learning rate: 0.00856 +2024-11-21 17:45:56.671894: train_loss -0.7543 +2024-11-21 17:45:56.683778: val_loss -0.7612 +2024-11-21 17:45:56.683918: Pseudo dice [0.8332] +2024-11-21 17:45:56.684261: Epoch time: 19.01 s +2024-11-21 17:45:57.503922: +2024-11-21 17:45:57.504135: Epoch 1269 +2024-11-21 17:45:57.504248: Current learning rate: 0.00856 +2024-11-21 17:46:16.560086: train_loss -0.7529 +2024-11-21 17:46:16.569827: val_loss -0.7464 +2024-11-21 17:46:16.569994: Pseudo dice [0.8415] +2024-11-21 17:46:16.570088: Epoch time: 19.06 s +2024-11-21 17:46:17.415414: +2024-11-21 17:46:17.415621: Epoch 1270 +2024-11-21 17:46:17.415734: Current learning rate: 0.00856 +2024-11-21 17:46:35.966056: train_loss -0.7554 +2024-11-21 17:46:35.970841: val_loss -0.7512 +2024-11-21 17:46:35.970978: Pseudo dice [0.8423] +2024-11-21 17:46:35.971092: Epoch time: 18.55 s +2024-11-21 17:46:36.846017: +2024-11-21 17:46:36.846231: Epoch 1271 +2024-11-21 17:46:36.846352: Current learning rate: 0.00856 +2024-11-21 17:46:57.019130: train_loss -0.7649 +2024-11-21 17:46:57.027069: val_loss -0.7613 +2024-11-21 17:46:57.027227: Pseudo dice [0.8569] +2024-11-21 17:46:57.027335: Epoch time: 20.17 s +2024-11-21 17:46:57.849509: +2024-11-21 17:46:57.849727: Epoch 1272 +2024-11-21 17:46:57.849861: Current learning rate: 0.00856 +2024-11-21 17:47:17.596741: train_loss -0.7614 +2024-11-21 17:47:17.603076: val_loss -0.7494 +2024-11-21 17:47:17.603228: Pseudo dice [0.8306] +2024-11-21 17:47:17.603325: Epoch time: 19.75 s +2024-11-21 17:47:18.460903: +2024-11-21 17:47:18.461116: Epoch 1273 +2024-11-21 17:47:18.461236: Current learning rate: 0.00856 +2024-11-21 17:47:37.111349: train_loss -0.7647 +2024-11-21 17:47:37.124098: val_loss -0.7554 +2024-11-21 17:47:37.124237: Pseudo dice [0.8474] +2024-11-21 17:47:37.124324: Epoch time: 18.65 s +2024-11-21 17:47:38.016132: +2024-11-21 17:47:38.016341: Epoch 1274 +2024-11-21 17:47:38.016473: Current learning rate: 0.00855 +2024-11-21 17:47:56.316047: train_loss -0.7665 +2024-11-21 17:47:56.320401: val_loss -0.7503 +2024-11-21 17:47:56.320548: Pseudo dice [0.8394] +2024-11-21 17:47:56.320647: Epoch time: 18.3 s +2024-11-21 17:47:57.631187: +2024-11-21 17:47:57.631404: Epoch 1275 +2024-11-21 17:47:57.631531: Current learning rate: 0.00855 +2024-11-21 17:48:17.250566: train_loss -0.7612 +2024-11-21 17:48:17.259116: val_loss -0.7619 +2024-11-21 17:48:17.259255: Pseudo dice [0.8381] +2024-11-21 17:48:17.259361: Epoch time: 19.62 s +2024-11-21 17:48:18.145093: +2024-11-21 17:48:18.145334: Epoch 1276 +2024-11-21 17:48:18.145449: Current learning rate: 0.00855 +2024-11-21 17:48:36.894801: train_loss -0.7787 +2024-11-21 17:48:36.900010: val_loss -0.7746 +2024-11-21 17:48:36.900168: Pseudo dice [0.8392] +2024-11-21 17:48:36.900265: Epoch time: 18.75 s +2024-11-21 17:48:37.733919: +2024-11-21 17:48:37.734143: Epoch 1277 +2024-11-21 17:48:37.734277: Current learning rate: 0.00855 +2024-11-21 17:48:57.274044: train_loss -0.7639 +2024-11-21 17:48:57.278268: val_loss -0.7563 +2024-11-21 17:48:57.278411: Pseudo dice [0.8325] +2024-11-21 17:48:57.278508: Epoch time: 19.54 s +2024-11-21 17:48:58.276947: +2024-11-21 17:48:58.277219: Epoch 1278 +2024-11-21 17:48:58.277345: Current learning rate: 0.00855 +2024-11-21 17:49:17.387620: train_loss -0.769 +2024-11-21 17:49:17.401313: val_loss -0.7815 +2024-11-21 17:49:17.401489: Pseudo dice [0.8532] +2024-11-21 17:49:17.401578: Epoch time: 19.11 s +2024-11-21 17:49:18.282778: +2024-11-21 17:49:18.282984: Epoch 1279 +2024-11-21 17:49:18.283120: Current learning rate: 0.00855 +2024-11-21 17:49:37.137873: train_loss -0.7604 +2024-11-21 17:49:37.145888: val_loss -0.7741 +2024-11-21 17:49:37.146031: Pseudo dice [0.8569] +2024-11-21 17:49:37.146371: Epoch time: 18.86 s +2024-11-21 17:49:37.963133: +2024-11-21 17:49:37.963333: Epoch 1280 +2024-11-21 17:49:37.963454: Current learning rate: 0.00855 +2024-11-21 17:49:57.632872: train_loss -0.7656 +2024-11-21 17:49:57.640599: val_loss -0.6987 +2024-11-21 17:49:57.640741: Pseudo dice [0.8273] +2024-11-21 17:49:57.640826: Epoch time: 19.67 s +2024-11-21 17:49:58.482570: +2024-11-21 17:49:58.482801: Epoch 1281 +2024-11-21 17:49:58.482920: Current learning rate: 0.00855 +2024-11-21 17:50:17.413490: train_loss -0.7658 +2024-11-21 17:50:17.434377: val_loss -0.7363 +2024-11-21 17:50:17.434556: Pseudo dice [0.847] +2024-11-21 17:50:17.434668: Epoch time: 18.93 s +2024-11-21 17:50:18.321129: +2024-11-21 17:50:18.321390: Epoch 1282 +2024-11-21 17:50:18.321516: Current learning rate: 0.00855 +2024-11-21 17:50:36.813694: train_loss -0.7676 +2024-11-21 17:50:36.817367: val_loss -0.7607 +2024-11-21 17:50:36.817472: Pseudo dice [0.8275] +2024-11-21 17:50:36.817655: Epoch time: 18.49 s +2024-11-21 17:50:37.637405: +2024-11-21 17:50:37.637665: Epoch 1283 +2024-11-21 17:50:37.637788: Current learning rate: 0.00854 +2024-11-21 17:50:58.485512: train_loss -0.7471 +2024-11-21 17:50:58.500375: val_loss -0.7536 +2024-11-21 17:50:58.500518: Pseudo dice [0.835] +2024-11-21 17:50:58.500649: Epoch time: 20.85 s +2024-11-21 17:50:59.553142: +2024-11-21 17:50:59.553378: Epoch 1284 +2024-11-21 17:50:59.553525: Current learning rate: 0.00854 +2024-11-21 17:51:17.801533: train_loss -0.76 +2024-11-21 17:51:17.810979: val_loss -0.7516 +2024-11-21 17:51:17.811117: Pseudo dice [0.8552] +2024-11-21 17:51:17.811226: Epoch time: 18.25 s +2024-11-21 17:51:18.666421: +2024-11-21 17:51:18.666703: Epoch 1285 +2024-11-21 17:51:18.666829: Current learning rate: 0.00854 +2024-11-21 17:51:38.022145: train_loss -0.7414 +2024-11-21 17:51:38.029963: val_loss -0.7355 +2024-11-21 17:51:38.030126: Pseudo dice [0.826] +2024-11-21 17:51:38.030217: Epoch time: 19.36 s +2024-11-21 17:51:38.856276: +2024-11-21 17:51:38.856480: Epoch 1286 +2024-11-21 17:51:38.856614: Current learning rate: 0.00854 +2024-11-21 17:51:57.834282: train_loss -0.7409 +2024-11-21 17:51:57.836694: val_loss -0.7589 +2024-11-21 17:51:57.836790: Pseudo dice [0.8419] +2024-11-21 17:51:57.836896: Epoch time: 18.98 s +2024-11-21 17:51:58.648104: +2024-11-21 17:51:58.648338: Epoch 1287 +2024-11-21 17:51:58.648460: Current learning rate: 0.00854 +2024-11-21 17:52:17.577019: train_loss -0.7491 +2024-11-21 17:52:17.584922: val_loss -0.7546 +2024-11-21 17:52:17.585053: Pseudo dice [0.8412] +2024-11-21 17:52:17.585168: Epoch time: 18.93 s +2024-11-21 17:52:18.643929: +2024-11-21 17:52:18.644174: Epoch 1288 +2024-11-21 17:52:18.644289: Current learning rate: 0.00854 +2024-11-21 17:52:37.648859: train_loss -0.7548 +2024-11-21 17:52:37.657639: val_loss -0.7468 +2024-11-21 17:52:37.657794: Pseudo dice [0.8435] +2024-11-21 17:52:37.657898: Epoch time: 19.01 s +2024-11-21 17:52:38.508381: +2024-11-21 17:52:38.508624: Epoch 1289 +2024-11-21 17:52:38.508738: Current learning rate: 0.00854 +2024-11-21 17:52:57.355626: train_loss -0.7612 +2024-11-21 17:52:57.362658: val_loss -0.7657 +2024-11-21 17:52:57.362793: Pseudo dice [0.8403] +2024-11-21 17:52:57.362896: Epoch time: 18.85 s +2024-11-21 17:52:58.202708: +2024-11-21 17:52:58.202933: Epoch 1290 +2024-11-21 17:52:58.203068: Current learning rate: 0.00854 +2024-11-21 17:53:17.564641: train_loss -0.7665 +2024-11-21 17:53:17.580944: val_loss -0.7204 +2024-11-21 17:53:17.581095: Pseudo dice [0.8474] +2024-11-21 17:53:17.581195: Epoch time: 19.36 s +2024-11-21 17:53:18.557616: +2024-11-21 17:53:18.557840: Epoch 1291 +2024-11-21 17:53:18.557979: Current learning rate: 0.00854 +2024-11-21 17:53:37.584203: train_loss -0.7604 +2024-11-21 17:53:37.590340: val_loss -0.7612 +2024-11-21 17:53:37.590471: Pseudo dice [0.8401] +2024-11-21 17:53:37.590566: Epoch time: 19.03 s +2024-11-21 17:53:38.451194: +2024-11-21 17:53:38.451402: Epoch 1292 +2024-11-21 17:53:38.451529: Current learning rate: 0.00853 +2024-11-21 17:53:57.448753: train_loss -0.7598 +2024-11-21 17:53:57.452424: val_loss -0.7645 +2024-11-21 17:53:57.452525: Pseudo dice [0.8537] +2024-11-21 17:53:57.452607: Epoch time: 19.0 s +2024-11-21 17:53:58.264946: +2024-11-21 17:53:58.265182: Epoch 1293 +2024-11-21 17:53:58.265311: Current learning rate: 0.00853 +2024-11-21 17:54:17.380373: train_loss -0.7671 +2024-11-21 17:54:17.386654: val_loss -0.7583 +2024-11-21 17:54:17.386801: Pseudo dice [0.8482] +2024-11-21 17:54:17.386886: Epoch time: 19.12 s +2024-11-21 17:54:18.263765: +2024-11-21 17:54:18.263993: Epoch 1294 +2024-11-21 17:54:18.264124: Current learning rate: 0.00853 +2024-11-21 17:54:37.576790: train_loss -0.7601 +2024-11-21 17:54:37.579629: val_loss -0.7516 +2024-11-21 17:54:37.579781: Pseudo dice [0.8463] +2024-11-21 17:54:37.579885: Epoch time: 19.31 s +2024-11-21 17:54:38.398362: +2024-11-21 17:54:38.398571: Epoch 1295 +2024-11-21 17:54:38.398711: Current learning rate: 0.00853 +2024-11-21 17:54:58.307735: train_loss -0.7642 +2024-11-21 17:54:58.318977: val_loss -0.7548 +2024-11-21 17:54:58.319114: Pseudo dice [0.8505] +2024-11-21 17:54:58.319213: Epoch time: 19.91 s +2024-11-21 17:54:59.451025: +2024-11-21 17:54:59.451268: Epoch 1296 +2024-11-21 17:54:59.451387: Current learning rate: 0.00853 +2024-11-21 17:55:18.102174: train_loss -0.7637 +2024-11-21 17:55:18.107700: val_loss -0.7753 +2024-11-21 17:55:18.107838: Pseudo dice [0.8478] +2024-11-21 17:55:18.107929: Epoch time: 18.65 s +2024-11-21 17:55:18.945410: +2024-11-21 17:55:18.945615: Epoch 1297 +2024-11-21 17:55:18.945729: Current learning rate: 0.00853 +2024-11-21 17:55:38.186003: train_loss -0.7582 +2024-11-21 17:55:38.194817: val_loss -0.7531 +2024-11-21 17:55:38.194940: Pseudo dice [0.8508] +2024-11-21 17:55:38.195027: Epoch time: 19.24 s +2024-11-21 17:55:39.549569: +2024-11-21 17:55:39.549803: Epoch 1298 +2024-11-21 17:55:39.549954: Current learning rate: 0.00853 +2024-11-21 17:55:58.665822: train_loss -0.7625 +2024-11-21 17:55:58.676326: val_loss -0.7529 +2024-11-21 17:55:58.676460: Pseudo dice [0.8529] +2024-11-21 17:55:58.676558: Epoch time: 19.12 s +2024-11-21 17:55:59.590856: +2024-11-21 17:55:59.591104: Epoch 1299 +2024-11-21 17:55:59.591227: Current learning rate: 0.00853 +2024-11-21 17:56:18.109522: train_loss -0.7651 +2024-11-21 17:56:18.117691: val_loss -0.7759 +2024-11-21 17:56:18.117843: Pseudo dice [0.8362] +2024-11-21 17:56:18.118015: Epoch time: 18.52 s +2024-11-21 17:56:19.275661: +2024-11-21 17:56:19.275894: Epoch 1300 +2024-11-21 17:56:19.276022: Current learning rate: 0.00852 +2024-11-21 17:56:39.106254: train_loss -0.7584 +2024-11-21 17:56:39.108816: val_loss -0.7697 +2024-11-21 17:56:39.108914: Pseudo dice [0.8567] +2024-11-21 17:56:39.108997: Epoch time: 19.83 s +2024-11-21 17:56:39.923434: +2024-11-21 17:56:39.923639: Epoch 1301 +2024-11-21 17:56:39.923757: Current learning rate: 0.00852 +2024-11-21 17:56:58.322800: train_loss -0.7614 +2024-11-21 17:56:58.325952: val_loss -0.7475 +2024-11-21 17:56:58.326090: Pseudo dice [0.8428] +2024-11-21 17:56:58.326210: Epoch time: 18.4 s +2024-11-21 17:56:59.148117: +2024-11-21 17:56:59.148324: Epoch 1302 +2024-11-21 17:56:59.148462: Current learning rate: 0.00852 +2024-11-21 17:57:18.761974: train_loss -0.7618 +2024-11-21 17:57:18.766535: val_loss -0.7696 +2024-11-21 17:57:18.766675: Pseudo dice [0.8559] +2024-11-21 17:57:18.766772: Epoch time: 19.61 s +2024-11-21 17:57:19.612268: +2024-11-21 17:57:19.612498: Epoch 1303 +2024-11-21 17:57:19.612619: Current learning rate: 0.00852 +2024-11-21 17:57:38.544000: train_loss -0.7661 +2024-11-21 17:57:38.562972: val_loss -0.7389 +2024-11-21 17:57:38.563215: Pseudo dice [0.845] +2024-11-21 17:57:38.563350: Epoch time: 18.93 s +2024-11-21 17:57:39.491850: +2024-11-21 17:57:39.492103: Epoch 1304 +2024-11-21 17:57:39.492237: Current learning rate: 0.00852 +2024-11-21 17:57:59.088006: train_loss -0.7595 +2024-11-21 17:57:59.094405: val_loss -0.7524 +2024-11-21 17:57:59.094552: Pseudo dice [0.8455] +2024-11-21 17:57:59.094639: Epoch time: 19.6 s +2024-11-21 17:58:00.161818: +2024-11-21 17:58:00.162071: Epoch 1305 +2024-11-21 17:58:00.162210: Current learning rate: 0.00852 +2024-11-21 17:58:18.667773: train_loss -0.7588 +2024-11-21 17:58:18.676868: val_loss -0.7605 +2024-11-21 17:58:18.677018: Pseudo dice [0.8375] +2024-11-21 17:58:18.677950: Epoch time: 18.51 s +2024-11-21 17:58:19.505229: +2024-11-21 17:58:19.505466: Epoch 1306 +2024-11-21 17:58:19.505582: Current learning rate: 0.00852 +2024-11-21 17:58:37.938771: train_loss -0.772 +2024-11-21 17:58:37.950355: val_loss -0.7956 +2024-11-21 17:58:37.950514: Pseudo dice [0.8547] +2024-11-21 17:58:37.950630: Epoch time: 18.42 s +2024-11-21 17:58:38.951928: +2024-11-21 17:58:38.952129: Epoch 1307 +2024-11-21 17:58:38.952242: Current learning rate: 0.00852 +2024-11-21 17:58:57.909822: train_loss -0.7668 +2024-11-21 17:58:57.925985: val_loss -0.7651 +2024-11-21 17:58:57.926131: Pseudo dice [0.8603] +2024-11-21 17:58:57.926221: Epoch time: 18.96 s +2024-11-21 17:58:58.755542: +2024-11-21 17:58:58.755758: Epoch 1308 +2024-11-21 17:58:58.755893: Current learning rate: 0.00852 +2024-11-21 17:59:17.973172: train_loss -0.7637 +2024-11-21 17:59:17.975796: val_loss -0.7783 +2024-11-21 17:59:17.975938: Pseudo dice [0.8388] +2024-11-21 17:59:17.976025: Epoch time: 19.22 s +2024-11-21 17:59:19.218899: +2024-11-21 17:59:19.219135: Epoch 1309 +2024-11-21 17:59:19.219254: Current learning rate: 0.00851 +2024-11-21 17:59:36.874047: train_loss -0.7633 +2024-11-21 17:59:36.878796: val_loss -0.7627 +2024-11-21 17:59:36.878950: Pseudo dice [0.8509] +2024-11-21 17:59:36.879073: Epoch time: 17.66 s +2024-11-21 17:59:38.007021: +2024-11-21 17:59:38.007290: Epoch 1310 +2024-11-21 17:59:38.007414: Current learning rate: 0.00851 +2024-11-21 17:59:57.842158: train_loss -0.7541 +2024-11-21 17:59:57.848270: val_loss -0.7645 +2024-11-21 17:59:57.848397: Pseudo dice [0.8445] +2024-11-21 17:59:57.848496: Epoch time: 19.84 s +2024-11-21 17:59:58.886871: +2024-11-21 17:59:58.887114: Epoch 1311 +2024-11-21 17:59:58.887224: Current learning rate: 0.00851 +2024-11-21 18:00:18.369867: train_loss -0.7667 +2024-11-21 18:00:18.373186: val_loss -0.7764 +2024-11-21 18:00:18.373339: Pseudo dice [0.8475] +2024-11-21 18:00:18.373428: Epoch time: 19.48 s +2024-11-21 18:00:19.193805: +2024-11-21 18:00:19.194020: Epoch 1312 +2024-11-21 18:00:19.194142: Current learning rate: 0.00851 +2024-11-21 18:00:39.028178: train_loss -0.7615 +2024-11-21 18:00:39.032421: val_loss -0.7697 +2024-11-21 18:00:39.032586: Pseudo dice [0.8616] +2024-11-21 18:00:39.032696: Epoch time: 19.82 s +2024-11-21 18:00:40.085511: +2024-11-21 18:00:40.085724: Epoch 1313 +2024-11-21 18:00:40.085858: Current learning rate: 0.00851 +2024-11-21 18:01:00.179852: train_loss -0.7646 +2024-11-21 18:01:00.185473: val_loss -0.7625 +2024-11-21 18:01:00.185612: Pseudo dice [0.8558] +2024-11-21 18:01:00.185713: Epoch time: 20.1 s +2024-11-21 18:01:00.185785: Yayy! New best EMA pseudo Dice: 0.8493 +2024-11-21 18:01:01.249367: +2024-11-21 18:01:01.249589: Epoch 1314 +2024-11-21 18:01:01.249712: Current learning rate: 0.00851 +2024-11-21 18:01:20.665168: train_loss -0.7577 +2024-11-21 18:01:20.674238: val_loss -0.7618 +2024-11-21 18:01:20.674385: Pseudo dice [0.8201] +2024-11-21 18:01:20.674474: Epoch time: 19.42 s +2024-11-21 18:01:21.499655: +2024-11-21 18:01:21.499848: Epoch 1315 +2024-11-21 18:01:21.499972: Current learning rate: 0.00851 +2024-11-21 18:01:40.157421: train_loss -0.76 +2024-11-21 18:01:40.162386: val_loss -0.7411 +2024-11-21 18:01:40.162512: Pseudo dice [0.8465] +2024-11-21 18:01:40.162613: Epoch time: 18.66 s +2024-11-21 18:01:41.019344: +2024-11-21 18:01:41.019581: Epoch 1316 +2024-11-21 18:01:41.019715: Current learning rate: 0.00851 +2024-11-21 18:02:01.660409: train_loss -0.755 +2024-11-21 18:02:01.666737: val_loss -0.7821 +2024-11-21 18:02:01.666848: Pseudo dice [0.8544] +2024-11-21 18:02:01.666934: Epoch time: 20.64 s +2024-11-21 18:02:02.497991: +2024-11-21 18:02:02.498201: Epoch 1317 +2024-11-21 18:02:02.498335: Current learning rate: 0.00851 +2024-11-21 18:02:21.210628: train_loss -0.7592 +2024-11-21 18:02:21.218184: val_loss -0.753 +2024-11-21 18:02:21.218320: Pseudo dice [0.8474] +2024-11-21 18:02:21.218425: Epoch time: 18.71 s +2024-11-21 18:02:22.096774: +2024-11-21 18:02:22.096990: Epoch 1318 +2024-11-21 18:02:22.097127: Current learning rate: 0.0085 +2024-11-21 18:02:41.240366: train_loss -0.7528 +2024-11-21 18:02:41.243781: val_loss -0.7598 +2024-11-21 18:02:41.243940: Pseudo dice [0.8501] +2024-11-21 18:02:41.244044: Epoch time: 19.14 s +2024-11-21 18:02:42.072318: +2024-11-21 18:02:42.072503: Epoch 1319 +2024-11-21 18:02:42.072613: Current learning rate: 0.0085 +2024-11-21 18:03:00.700782: train_loss -0.7619 +2024-11-21 18:03:00.709042: val_loss -0.741 +2024-11-21 18:03:00.709187: Pseudo dice [0.8381] +2024-11-21 18:03:00.709276: Epoch time: 18.63 s +2024-11-21 18:03:02.073997: +2024-11-21 18:03:02.074235: Epoch 1320 +2024-11-21 18:03:02.074358: Current learning rate: 0.0085 +2024-11-21 18:03:20.645222: train_loss -0.7668 +2024-11-21 18:03:20.658346: val_loss -0.7804 +2024-11-21 18:03:20.659456: Pseudo dice [0.8609] +2024-11-21 18:03:20.659580: Epoch time: 18.57 s +2024-11-21 18:03:21.507940: +2024-11-21 18:03:21.508192: Epoch 1321 +2024-11-21 18:03:21.508313: Current learning rate: 0.0085 +2024-11-21 18:03:40.507051: train_loss -0.7712 +2024-11-21 18:03:40.513078: val_loss -0.7696 +2024-11-21 18:03:40.513226: Pseudo dice [0.8451] +2024-11-21 18:03:40.513331: Epoch time: 19.0 s +2024-11-21 18:03:41.345431: +2024-11-21 18:03:41.345669: Epoch 1322 +2024-11-21 18:03:41.345803: Current learning rate: 0.0085 +2024-11-21 18:04:01.114755: train_loss -0.7755 +2024-11-21 18:04:01.127254: val_loss -0.7815 +2024-11-21 18:04:01.127395: Pseudo dice [0.8505] +2024-11-21 18:04:01.127501: Epoch time: 19.77 s +2024-11-21 18:04:01.946281: +2024-11-21 18:04:01.946503: Epoch 1323 +2024-11-21 18:04:01.946629: Current learning rate: 0.0085 +2024-11-21 18:04:20.766900: train_loss -0.7688 +2024-11-21 18:04:20.773678: val_loss -0.7663 +2024-11-21 18:04:20.773826: Pseudo dice [0.8451] +2024-11-21 18:04:20.773936: Epoch time: 18.82 s +2024-11-21 18:04:21.641657: +2024-11-21 18:04:21.641937: Epoch 1324 +2024-11-21 18:04:21.642091: Current learning rate: 0.0085 +2024-11-21 18:04:40.202199: train_loss -0.7671 +2024-11-21 18:04:40.209342: val_loss -0.7654 +2024-11-21 18:04:40.209515: Pseudo dice [0.8336] +2024-11-21 18:04:40.209609: Epoch time: 18.56 s +2024-11-21 18:04:41.063535: +2024-11-21 18:04:41.063756: Epoch 1325 +2024-11-21 18:04:41.063891: Current learning rate: 0.0085 +2024-11-21 18:05:00.376334: train_loss -0.7698 +2024-11-21 18:05:00.379366: val_loss -0.7543 +2024-11-21 18:05:00.379488: Pseudo dice [0.8406] +2024-11-21 18:05:00.379585: Epoch time: 19.31 s +2024-11-21 18:05:01.392108: +2024-11-21 18:05:01.392312: Epoch 1326 +2024-11-21 18:05:01.392440: Current learning rate: 0.0085 +2024-11-21 18:05:20.307712: train_loss -0.7635 +2024-11-21 18:05:20.312603: val_loss -0.773 +2024-11-21 18:05:20.312717: Pseudo dice [0.8604] +2024-11-21 18:05:20.312811: Epoch time: 18.92 s +2024-11-21 18:05:21.135028: +2024-11-21 18:05:21.135280: Epoch 1327 +2024-11-21 18:05:21.135408: Current learning rate: 0.00849 +2024-11-21 18:05:41.518763: train_loss -0.7647 +2024-11-21 18:05:41.524266: val_loss -0.7566 +2024-11-21 18:05:41.524476: Pseudo dice [0.8297] +2024-11-21 18:05:41.524596: Epoch time: 20.38 s +2024-11-21 18:05:42.407065: +2024-11-21 18:05:42.407281: Epoch 1328 +2024-11-21 18:05:42.407423: Current learning rate: 0.00849 +2024-11-21 18:06:01.111704: train_loss -0.7592 +2024-11-21 18:06:01.117901: val_loss -0.7771 +2024-11-21 18:06:01.118057: Pseudo dice [0.8619] +2024-11-21 18:06:01.118164: Epoch time: 18.71 s +2024-11-21 18:06:02.070729: +2024-11-21 18:06:02.070956: Epoch 1329 +2024-11-21 18:06:02.071090: Current learning rate: 0.00849 +2024-11-21 18:06:20.905636: train_loss -0.7676 +2024-11-21 18:06:20.911858: val_loss -0.7833 +2024-11-21 18:06:20.912001: Pseudo dice [0.8401] +2024-11-21 18:06:20.912104: Epoch time: 18.84 s +2024-11-21 18:06:21.806505: +2024-11-21 18:06:21.806742: Epoch 1330 +2024-11-21 18:06:21.806874: Current learning rate: 0.00849 +2024-11-21 18:06:40.324023: train_loss -0.7603 +2024-11-21 18:06:40.331207: val_loss -0.7708 +2024-11-21 18:06:40.331346: Pseudo dice [0.8406] +2024-11-21 18:06:40.331551: Epoch time: 18.52 s +2024-11-21 18:06:41.152951: +2024-11-21 18:06:41.153162: Epoch 1331 +2024-11-21 18:06:41.153278: Current learning rate: 0.00849 +2024-11-21 18:06:59.702647: train_loss -0.7628 +2024-11-21 18:06:59.710747: val_loss -0.7593 +2024-11-21 18:06:59.710899: Pseudo dice [0.8574] +2024-11-21 18:06:59.711009: Epoch time: 18.55 s +2024-11-21 18:07:00.532772: +2024-11-21 18:07:00.533015: Epoch 1332 +2024-11-21 18:07:00.533363: Current learning rate: 0.00849 +2024-11-21 18:07:19.440185: train_loss -0.7605 +2024-11-21 18:07:19.456069: val_loss -0.7479 +2024-11-21 18:07:19.456406: Pseudo dice [0.8419] +2024-11-21 18:07:19.456525: Epoch time: 18.91 s +2024-11-21 18:07:20.598007: +2024-11-21 18:07:20.598268: Epoch 1333 +2024-11-21 18:07:20.598385: Current learning rate: 0.00849 +2024-11-21 18:07:39.931642: train_loss -0.7479 +2024-11-21 18:07:39.935071: val_loss -0.745 +2024-11-21 18:07:39.935244: Pseudo dice [0.8292] +2024-11-21 18:07:39.935351: Epoch time: 19.33 s +2024-11-21 18:07:40.938130: +2024-11-21 18:07:40.938327: Epoch 1334 +2024-11-21 18:07:40.938441: Current learning rate: 0.00849 +2024-11-21 18:07:59.194417: train_loss -0.7588 +2024-11-21 18:07:59.197782: val_loss -0.7513 +2024-11-21 18:07:59.197934: Pseudo dice [0.8371] +2024-11-21 18:07:59.198035: Epoch time: 18.26 s +2024-11-21 18:08:00.140982: +2024-11-21 18:08:00.141206: Epoch 1335 +2024-11-21 18:08:00.141317: Current learning rate: 0.00848 +2024-11-21 18:08:18.965426: train_loss -0.7703 +2024-11-21 18:08:18.986220: val_loss -0.7822 +2024-11-21 18:08:18.986378: Pseudo dice [0.8539] +2024-11-21 18:08:18.986490: Epoch time: 18.83 s +2024-11-21 18:08:19.822129: +2024-11-21 18:08:19.822349: Epoch 1336 +2024-11-21 18:08:19.822493: Current learning rate: 0.00848 +2024-11-21 18:08:38.448239: train_loss -0.7413 +2024-11-21 18:08:38.454502: val_loss -0.7114 +2024-11-21 18:08:38.454618: Pseudo dice [0.83] +2024-11-21 18:08:38.454723: Epoch time: 18.63 s +2024-11-21 18:08:39.283001: +2024-11-21 18:08:39.283237: Epoch 1337 +2024-11-21 18:08:39.283374: Current learning rate: 0.00848 +2024-11-21 18:08:58.298239: train_loss -0.7592 +2024-11-21 18:08:58.343417: val_loss -0.7763 +2024-11-21 18:08:58.343597: Pseudo dice [0.8492] +2024-11-21 18:08:58.343698: Epoch time: 19.02 s +2024-11-21 18:08:59.191787: +2024-11-21 18:08:59.192006: Epoch 1338 +2024-11-21 18:08:59.192146: Current learning rate: 0.00848 +2024-11-21 18:09:18.455157: train_loss -0.7472 +2024-11-21 18:09:18.477099: val_loss -0.7595 +2024-11-21 18:09:18.477275: Pseudo dice [0.8382] +2024-11-21 18:09:18.477394: Epoch time: 19.26 s +2024-11-21 18:09:19.377224: +2024-11-21 18:09:19.377429: Epoch 1339 +2024-11-21 18:09:19.377544: Current learning rate: 0.00848 +2024-11-21 18:09:39.927647: train_loss -0.7495 +2024-11-21 18:09:39.935195: val_loss -0.7588 +2024-11-21 18:09:39.935345: Pseudo dice [0.834] +2024-11-21 18:09:39.935452: Epoch time: 20.55 s +2024-11-21 18:09:40.756204: +2024-11-21 18:09:40.756410: Epoch 1340 +2024-11-21 18:09:40.756537: Current learning rate: 0.00848 +2024-11-21 18:09:59.978161: train_loss -0.7686 +2024-11-21 18:09:59.988384: val_loss -0.7722 +2024-11-21 18:09:59.988526: Pseudo dice [0.8373] +2024-11-21 18:09:59.988638: Epoch time: 19.22 s +2024-11-21 18:10:01.078072: +2024-11-21 18:10:01.078262: Epoch 1341 +2024-11-21 18:10:01.078393: Current learning rate: 0.00848 +2024-11-21 18:10:20.492487: train_loss -0.7483 +2024-11-21 18:10:20.497755: val_loss -0.757 +2024-11-21 18:10:20.497891: Pseudo dice [0.8359] +2024-11-21 18:10:20.498001: Epoch time: 19.42 s +2024-11-21 18:10:21.811567: +2024-11-21 18:10:21.811758: Epoch 1342 +2024-11-21 18:10:21.811878: Current learning rate: 0.00848 +2024-11-21 18:10:41.265887: train_loss -0.7571 +2024-11-21 18:10:41.268038: val_loss -0.7242 +2024-11-21 18:10:41.268161: Pseudo dice [0.8275] +2024-11-21 18:10:41.268284: Epoch time: 19.46 s +2024-11-21 18:10:42.181369: +2024-11-21 18:10:42.181854: Epoch 1343 +2024-11-21 18:10:42.182006: Current learning rate: 0.00848 +2024-11-21 18:11:01.187763: train_loss -0.7371 +2024-11-21 18:11:01.193835: val_loss -0.7532 +2024-11-21 18:11:01.194002: Pseudo dice [0.8341] +2024-11-21 18:11:01.194099: Epoch time: 19.01 s +2024-11-21 18:11:02.033428: +2024-11-21 18:11:02.033861: Epoch 1344 +2024-11-21 18:11:02.034015: Current learning rate: 0.00847 +2024-11-21 18:11:22.783753: train_loss -0.7506 +2024-11-21 18:11:22.789966: val_loss -0.7759 +2024-11-21 18:11:22.790113: Pseudo dice [0.8435] +2024-11-21 18:11:22.790491: Epoch time: 20.75 s +2024-11-21 18:11:23.629015: +2024-11-21 18:11:23.629449: Epoch 1345 +2024-11-21 18:11:23.629598: Current learning rate: 0.00847 +2024-11-21 18:11:43.495899: train_loss -0.7474 +2024-11-21 18:11:43.499986: val_loss -0.7581 +2024-11-21 18:11:43.500107: Pseudo dice [0.8303] +2024-11-21 18:11:43.500204: Epoch time: 19.87 s +2024-11-21 18:11:44.331685: +2024-11-21 18:11:44.332140: Epoch 1346 +2024-11-21 18:11:44.332289: Current learning rate: 0.00847 +2024-11-21 18:12:03.204325: train_loss -0.7454 +2024-11-21 18:12:03.208465: val_loss -0.7612 +2024-11-21 18:12:03.208558: Pseudo dice [0.8462] +2024-11-21 18:12:03.208655: Epoch time: 18.87 s +2024-11-21 18:12:04.036835: +2024-11-21 18:12:04.037285: Epoch 1347 +2024-11-21 18:12:04.037445: Current learning rate: 0.00847 +2024-11-21 18:12:22.982542: train_loss -0.7481 +2024-11-21 18:12:22.986903: val_loss -0.7508 +2024-11-21 18:12:22.987039: Pseudo dice [0.8424] +2024-11-21 18:12:22.987140: Epoch time: 18.95 s +2024-11-21 18:12:23.810638: +2024-11-21 18:12:23.811052: Epoch 1348 +2024-11-21 18:12:23.811198: Current learning rate: 0.00847 +2024-11-21 18:12:42.956410: train_loss -0.7496 +2024-11-21 18:12:42.968854: val_loss -0.7316 +2024-11-21 18:12:42.969034: Pseudo dice [0.8387] +2024-11-21 18:12:42.969129: Epoch time: 19.15 s +2024-11-21 18:12:43.867260: +2024-11-21 18:12:43.867669: Epoch 1349 +2024-11-21 18:12:43.867817: Current learning rate: 0.00847 +2024-11-21 18:13:03.255033: train_loss -0.7581 +2024-11-21 18:13:03.266428: val_loss -0.7409 +2024-11-21 18:13:03.266576: Pseudo dice [0.8283] +2024-11-21 18:13:03.266687: Epoch time: 19.39 s +2024-11-21 18:13:04.542739: +2024-11-21 18:13:04.543156: Epoch 1350 +2024-11-21 18:13:04.543302: Current learning rate: 0.00847 +2024-11-21 18:13:24.439117: train_loss -0.7695 +2024-11-21 18:13:24.445115: val_loss -0.7394 +2024-11-21 18:13:24.445260: Pseudo dice [0.8416] +2024-11-21 18:13:24.445348: Epoch time: 19.9 s +2024-11-21 18:13:25.465344: +2024-11-21 18:13:25.465742: Epoch 1351 +2024-11-21 18:13:25.465884: Current learning rate: 0.00847 +2024-11-21 18:13:44.661998: train_loss -0.762 +2024-11-21 18:13:44.664634: val_loss -0.7555 +2024-11-21 18:13:44.664724: Pseudo dice [0.8383] +2024-11-21 18:13:44.664803: Epoch time: 19.2 s +2024-11-21 18:13:45.487552: +2024-11-21 18:13:45.487978: Epoch 1352 +2024-11-21 18:13:45.488138: Current learning rate: 0.00847 +2024-11-21 18:14:04.426956: train_loss -0.7569 +2024-11-21 18:14:04.433240: val_loss -0.7437 +2024-11-21 18:14:04.433463: Pseudo dice [0.8435] +2024-11-21 18:14:04.433587: Epoch time: 18.94 s +2024-11-21 18:14:05.647344: +2024-11-21 18:14:05.647570: Epoch 1353 +2024-11-21 18:14:05.647688: Current learning rate: 0.00846 +2024-11-21 18:14:24.330151: train_loss -0.7535 +2024-11-21 18:14:24.333306: val_loss -0.7772 +2024-11-21 18:14:24.333431: Pseudo dice [0.8412] +2024-11-21 18:14:24.333534: Epoch time: 18.68 s +2024-11-21 18:14:25.156721: +2024-11-21 18:14:25.156944: Epoch 1354 +2024-11-21 18:14:25.157063: Current learning rate: 0.00846 +2024-11-21 18:14:44.152573: train_loss -0.7642 +2024-11-21 18:14:44.160582: val_loss -0.7813 +2024-11-21 18:14:44.160718: Pseudo dice [0.8528] +2024-11-21 18:14:44.160821: Epoch time: 19.0 s +2024-11-21 18:14:45.019691: +2024-11-21 18:14:45.019903: Epoch 1355 +2024-11-21 18:14:45.020035: Current learning rate: 0.00846 +2024-11-21 18:15:04.723450: train_loss -0.7507 +2024-11-21 18:15:04.741337: val_loss -0.7657 +2024-11-21 18:15:04.741510: Pseudo dice [0.8605] +2024-11-21 18:15:04.741621: Epoch time: 19.7 s +2024-11-21 18:15:05.667897: +2024-11-21 18:15:05.668147: Epoch 1356 +2024-11-21 18:15:05.668288: Current learning rate: 0.00846 +2024-11-21 18:15:24.764360: train_loss -0.7642 +2024-11-21 18:15:24.778499: val_loss -0.7632 +2024-11-21 18:15:24.778638: Pseudo dice [0.8439] +2024-11-21 18:15:24.778750: Epoch time: 19.1 s +2024-11-21 18:15:25.619154: +2024-11-21 18:15:25.619369: Epoch 1357 +2024-11-21 18:15:25.619487: Current learning rate: 0.00846 +2024-11-21 18:15:45.077476: train_loss -0.7668 +2024-11-21 18:15:45.081645: val_loss -0.7705 +2024-11-21 18:15:45.081801: Pseudo dice [0.8473] +2024-11-21 18:15:45.081900: Epoch time: 19.46 s +2024-11-21 18:15:45.915533: +2024-11-21 18:15:45.915745: Epoch 1358 +2024-11-21 18:15:45.915882: Current learning rate: 0.00846 +2024-11-21 18:16:05.994070: train_loss -0.7619 +2024-11-21 18:16:05.997883: val_loss -0.7814 +2024-11-21 18:16:05.998035: Pseudo dice [0.8448] +2024-11-21 18:16:05.998126: Epoch time: 20.08 s +2024-11-21 18:16:06.844585: +2024-11-21 18:16:06.844797: Epoch 1359 +2024-11-21 18:16:06.844927: Current learning rate: 0.00846 +2024-11-21 18:16:26.600398: train_loss -0.7545 +2024-11-21 18:16:26.607740: val_loss -0.7275 +2024-11-21 18:16:26.607861: Pseudo dice [0.836] +2024-11-21 18:16:26.607954: Epoch time: 19.76 s +2024-11-21 18:16:27.519948: +2024-11-21 18:16:27.520159: Epoch 1360 +2024-11-21 18:16:27.520285: Current learning rate: 0.00846 +2024-11-21 18:16:49.082173: train_loss -0.749 +2024-11-21 18:16:49.091551: val_loss -0.7418 +2024-11-21 18:16:49.091694: Pseudo dice [0.824] +2024-11-21 18:16:49.091795: Epoch time: 21.56 s +2024-11-21 18:16:49.949618: +2024-11-21 18:16:49.949830: Epoch 1361 +2024-11-21 18:16:49.949949: Current learning rate: 0.00845 +2024-11-21 18:17:08.303843: train_loss -0.7615 +2024-11-21 18:17:08.311736: val_loss -0.7253 +2024-11-21 18:17:08.311864: Pseudo dice [0.8317] +2024-11-21 18:17:08.311948: Epoch time: 18.36 s +2024-11-21 18:17:09.375160: +2024-11-21 18:17:09.375386: Epoch 1362 +2024-11-21 18:17:09.375512: Current learning rate: 0.00845 +2024-11-21 18:17:28.378051: train_loss -0.7664 +2024-11-21 18:17:28.382823: val_loss -0.7325 +2024-11-21 18:17:28.382949: Pseudo dice [0.8378] +2024-11-21 18:17:28.383048: Epoch time: 19.0 s +2024-11-21 18:17:29.276226: +2024-11-21 18:17:29.276433: Epoch 1363 +2024-11-21 18:17:29.276548: Current learning rate: 0.00845 +2024-11-21 18:17:49.010029: train_loss -0.7681 +2024-11-21 18:17:49.017633: val_loss -0.7635 +2024-11-21 18:17:49.017754: Pseudo dice [0.8442] +2024-11-21 18:17:49.017872: Epoch time: 19.73 s +2024-11-21 18:17:49.867340: +2024-11-21 18:17:49.867561: Epoch 1364 +2024-11-21 18:17:49.867681: Current learning rate: 0.00845 +2024-11-21 18:18:08.978315: train_loss -0.7529 +2024-11-21 18:18:08.987550: val_loss -0.7736 +2024-11-21 18:18:08.987672: Pseudo dice [0.8445] +2024-11-21 18:18:08.987770: Epoch time: 19.11 s +2024-11-21 18:18:09.876917: +2024-11-21 18:18:09.877163: Epoch 1365 +2024-11-21 18:18:09.877283: Current learning rate: 0.00845 +2024-11-21 18:18:30.202451: train_loss -0.763 +2024-11-21 18:18:30.206722: val_loss -0.7514 +2024-11-21 18:18:30.206876: Pseudo dice [0.8437] +2024-11-21 18:18:30.206967: Epoch time: 20.33 s +2024-11-21 18:18:31.088899: +2024-11-21 18:18:31.089128: Epoch 1366 +2024-11-21 18:18:31.089261: Current learning rate: 0.00845 +2024-11-21 18:18:50.225440: train_loss -0.7608 +2024-11-21 18:18:50.234072: val_loss -0.7455 +2024-11-21 18:18:50.234283: Pseudo dice [0.845] +2024-11-21 18:18:50.234397: Epoch time: 19.14 s +2024-11-21 18:18:51.342963: +2024-11-21 18:18:51.343176: Epoch 1367 +2024-11-21 18:18:51.343309: Current learning rate: 0.00845 +2024-11-21 18:19:10.329911: train_loss -0.7614 +2024-11-21 18:19:10.336826: val_loss -0.7342 +2024-11-21 18:19:10.336964: Pseudo dice [0.8525] +2024-11-21 18:19:10.337077: Epoch time: 18.99 s +2024-11-21 18:19:11.193941: +2024-11-21 18:19:11.194192: Epoch 1368 +2024-11-21 18:19:11.194315: Current learning rate: 0.00845 +2024-11-21 18:19:29.712301: train_loss -0.7732 +2024-11-21 18:19:29.722272: val_loss -0.7683 +2024-11-21 18:19:29.722423: Pseudo dice [0.8453] +2024-11-21 18:19:29.722521: Epoch time: 18.52 s +2024-11-21 18:19:30.704604: +2024-11-21 18:19:30.704830: Epoch 1369 +2024-11-21 18:19:30.704951: Current learning rate: 0.00845 +2024-11-21 18:19:50.272242: train_loss -0.7725 +2024-11-21 18:19:50.280697: val_loss -0.7493 +2024-11-21 18:19:50.280830: Pseudo dice [0.8441] +2024-11-21 18:19:50.280920: Epoch time: 19.57 s +2024-11-21 18:19:51.120564: +2024-11-21 18:19:51.120796: Epoch 1370 +2024-11-21 18:19:51.120924: Current learning rate: 0.00844 +2024-11-21 18:20:10.813305: train_loss -0.7701 +2024-11-21 18:20:10.820028: val_loss -0.7722 +2024-11-21 18:20:10.820184: Pseudo dice [0.8451] +2024-11-21 18:20:10.820303: Epoch time: 19.69 s +2024-11-21 18:20:11.651915: +2024-11-21 18:20:11.652109: Epoch 1371 +2024-11-21 18:20:11.652232: Current learning rate: 0.00844 +2024-11-21 18:20:31.127973: train_loss -0.7602 +2024-11-21 18:20:31.142958: val_loss -0.7653 +2024-11-21 18:20:31.143117: Pseudo dice [0.8483] +2024-11-21 18:20:31.143214: Epoch time: 19.48 s +2024-11-21 18:20:32.035124: +2024-11-21 18:20:32.035325: Epoch 1372 +2024-11-21 18:20:32.035459: Current learning rate: 0.00844 +2024-11-21 18:20:51.887132: train_loss -0.7546 +2024-11-21 18:20:51.896987: val_loss -0.7642 +2024-11-21 18:20:51.897139: Pseudo dice [0.8512] +2024-11-21 18:20:51.897222: Epoch time: 19.85 s +2024-11-21 18:20:52.725711: +2024-11-21 18:20:52.725915: Epoch 1373 +2024-11-21 18:20:52.726031: Current learning rate: 0.00844 +2024-11-21 18:21:11.713999: train_loss -0.7575 +2024-11-21 18:21:11.734136: val_loss -0.7596 +2024-11-21 18:21:11.734285: Pseudo dice [0.84] +2024-11-21 18:21:11.734393: Epoch time: 18.99 s +2024-11-21 18:21:12.639839: +2024-11-21 18:21:12.640041: Epoch 1374 +2024-11-21 18:21:12.640175: Current learning rate: 0.00844 +2024-11-21 18:21:31.333241: train_loss -0.7637 +2024-11-21 18:21:31.339456: val_loss -0.7597 +2024-11-21 18:21:31.339598: Pseudo dice [0.8525] +2024-11-21 18:21:31.339701: Epoch time: 18.69 s +2024-11-21 18:21:32.573020: +2024-11-21 18:21:32.573277: Epoch 1375 +2024-11-21 18:21:32.573409: Current learning rate: 0.00844 +2024-11-21 18:21:50.958868: train_loss -0.7586 +2024-11-21 18:21:50.965863: val_loss -0.7819 +2024-11-21 18:21:50.966020: Pseudo dice [0.8423] +2024-11-21 18:21:50.966115: Epoch time: 18.39 s +2024-11-21 18:21:51.799252: +2024-11-21 18:21:51.799453: Epoch 1376 +2024-11-21 18:21:51.799572: Current learning rate: 0.00844 +2024-11-21 18:22:10.831653: train_loss -0.7645 +2024-11-21 18:22:10.840572: val_loss -0.7592 +2024-11-21 18:22:10.840718: Pseudo dice [0.8301] +2024-11-21 18:22:10.840814: Epoch time: 19.03 s +2024-11-21 18:22:11.730394: +2024-11-21 18:22:11.730626: Epoch 1377 +2024-11-21 18:22:11.730753: Current learning rate: 0.00844 +2024-11-21 18:22:29.813847: train_loss -0.7656 +2024-11-21 18:22:29.828040: val_loss -0.7502 +2024-11-21 18:22:29.828197: Pseudo dice [0.8504] +2024-11-21 18:22:29.828297: Epoch time: 18.08 s +2024-11-21 18:22:30.772033: +2024-11-21 18:22:30.772263: Epoch 1378 +2024-11-21 18:22:30.772378: Current learning rate: 0.00844 +2024-11-21 18:22:50.401070: train_loss -0.7646 +2024-11-21 18:22:50.408887: val_loss -0.7759 +2024-11-21 18:22:50.409022: Pseudo dice [0.8471] +2024-11-21 18:22:50.409131: Epoch time: 19.63 s +2024-11-21 18:22:51.512244: +2024-11-21 18:22:51.512514: Epoch 1379 +2024-11-21 18:22:51.512661: Current learning rate: 0.00843 +2024-11-21 18:23:10.447609: train_loss -0.7728 +2024-11-21 18:23:10.451285: val_loss -0.7785 +2024-11-21 18:23:10.451388: Pseudo dice [0.8491] +2024-11-21 18:23:10.451473: Epoch time: 18.94 s +2024-11-21 18:23:11.286759: +2024-11-21 18:23:11.286983: Epoch 1380 +2024-11-21 18:23:11.287111: Current learning rate: 0.00843 +2024-11-21 18:23:30.534268: train_loss -0.769 +2024-11-21 18:23:30.546230: val_loss -0.7721 +2024-11-21 18:23:30.546383: Pseudo dice [0.8493] +2024-11-21 18:23:30.546504: Epoch time: 19.25 s +2024-11-21 18:23:31.481887: +2024-11-21 18:23:31.482104: Epoch 1381 +2024-11-21 18:23:31.482229: Current learning rate: 0.00843 +2024-11-21 18:23:50.180762: train_loss -0.7553 +2024-11-21 18:23:50.184055: val_loss -0.7732 +2024-11-21 18:23:50.184184: Pseudo dice [0.8547] +2024-11-21 18:23:50.184282: Epoch time: 18.7 s +2024-11-21 18:23:51.009766: +2024-11-21 18:23:51.009972: Epoch 1382 +2024-11-21 18:23:51.010107: Current learning rate: 0.00843 +2024-11-21 18:24:10.524408: train_loss -0.7721 +2024-11-21 18:24:10.532181: val_loss -0.7787 +2024-11-21 18:24:10.532345: Pseudo dice [0.852] +2024-11-21 18:24:10.532438: Epoch time: 19.52 s +2024-11-21 18:24:11.393656: +2024-11-21 18:24:11.393873: Epoch 1383 +2024-11-21 18:24:11.394012: Current learning rate: 0.00843 +2024-11-21 18:24:31.463588: train_loss -0.7734 +2024-11-21 18:24:31.466753: val_loss -0.7756 +2024-11-21 18:24:31.466852: Pseudo dice [0.8391] +2024-11-21 18:24:31.466937: Epoch time: 20.07 s +2024-11-21 18:24:32.293607: +2024-11-21 18:24:32.293831: Epoch 1384 +2024-11-21 18:24:32.293976: Current learning rate: 0.00843 +2024-11-21 18:24:50.369623: train_loss -0.7679 +2024-11-21 18:24:50.376378: val_loss -0.7477 +2024-11-21 18:24:50.376506: Pseudo dice [0.8193] +2024-11-21 18:24:50.376597: Epoch time: 18.08 s +2024-11-21 18:24:51.206293: +2024-11-21 18:24:51.206718: Epoch 1385 +2024-11-21 18:24:51.206883: Current learning rate: 0.00843 +2024-11-21 18:25:09.961542: train_loss -0.7588 +2024-11-21 18:25:09.976666: val_loss -0.7413 +2024-11-21 18:25:09.976858: Pseudo dice [0.8368] +2024-11-21 18:25:09.976969: Epoch time: 18.76 s +2024-11-21 18:25:10.922038: +2024-11-21 18:25:10.922247: Epoch 1386 +2024-11-21 18:25:10.922385: Current learning rate: 0.00843 +2024-11-21 18:25:29.123907: train_loss -0.7403 +2024-11-21 18:25:29.136560: val_loss -0.7106 +2024-11-21 18:25:29.136691: Pseudo dice [0.8036] +2024-11-21 18:25:29.136791: Epoch time: 18.2 s +2024-11-21 18:25:29.962882: +2024-11-21 18:25:29.963143: Epoch 1387 +2024-11-21 18:25:29.963269: Current learning rate: 0.00843 +2024-11-21 18:25:49.094379: train_loss -0.7259 +2024-11-21 18:25:49.101220: val_loss -0.7553 +2024-11-21 18:25:49.101399: Pseudo dice [0.8377] +2024-11-21 18:25:49.101484: Epoch time: 19.13 s +2024-11-21 18:25:50.009671: +2024-11-21 18:25:50.009918: Epoch 1388 +2024-11-21 18:25:50.010055: Current learning rate: 0.00842 +2024-11-21 18:26:09.323118: train_loss -0.7367 +2024-11-21 18:26:09.337739: val_loss -0.7582 +2024-11-21 18:26:09.337968: Pseudo dice [0.8442] +2024-11-21 18:26:09.338089: Epoch time: 19.31 s +2024-11-21 18:26:10.283983: +2024-11-21 18:26:10.284325: Epoch 1389 +2024-11-21 18:26:10.284449: Current learning rate: 0.00842 +2024-11-21 18:26:29.177024: train_loss -0.7438 +2024-11-21 18:26:29.187447: val_loss -0.7687 +2024-11-21 18:26:29.187624: Pseudo dice [0.8428] +2024-11-21 18:26:29.187731: Epoch time: 18.89 s +2024-11-21 18:26:30.215600: +2024-11-21 18:26:30.215846: Epoch 1390 +2024-11-21 18:26:30.215975: Current learning rate: 0.00842 +2024-11-21 18:26:50.000072: train_loss -0.7551 +2024-11-21 18:26:50.006680: val_loss -0.7597 +2024-11-21 18:26:50.006816: Pseudo dice [0.8424] +2024-11-21 18:26:50.006901: Epoch time: 19.79 s +2024-11-21 18:26:50.941486: +2024-11-21 18:26:50.941694: Epoch 1391 +2024-11-21 18:26:50.941827: Current learning rate: 0.00842 +2024-11-21 18:27:09.581714: train_loss -0.7306 +2024-11-21 18:27:09.584919: val_loss -0.7464 +2024-11-21 18:27:09.585070: Pseudo dice [0.8361] +2024-11-21 18:27:09.585175: Epoch time: 18.64 s +2024-11-21 18:27:10.506263: +2024-11-21 18:27:10.506493: Epoch 1392 +2024-11-21 18:27:10.506615: Current learning rate: 0.00842 +2024-11-21 18:27:31.345130: train_loss -0.7469 +2024-11-21 18:27:31.352742: val_loss -0.7803 +2024-11-21 18:27:31.352892: Pseudo dice [0.8369] +2024-11-21 18:27:31.352986: Epoch time: 20.84 s +2024-11-21 18:27:32.186651: +2024-11-21 18:27:32.186891: Epoch 1393 +2024-11-21 18:27:32.187007: Current learning rate: 0.00842 +2024-11-21 18:27:51.661191: train_loss -0.741 +2024-11-21 18:27:51.664277: val_loss -0.7509 +2024-11-21 18:27:51.664385: Pseudo dice [0.8357] +2024-11-21 18:27:51.664471: Epoch time: 19.48 s +2024-11-21 18:27:52.490391: +2024-11-21 18:27:52.490601: Epoch 1394 +2024-11-21 18:27:52.490723: Current learning rate: 0.00842 +2024-11-21 18:28:12.917780: train_loss -0.7407 +2024-11-21 18:28:12.921951: val_loss -0.765 +2024-11-21 18:28:12.922046: Pseudo dice [0.8407] +2024-11-21 18:28:12.922133: Epoch time: 20.43 s +2024-11-21 18:28:13.751722: +2024-11-21 18:28:13.751915: Epoch 1395 +2024-11-21 18:28:13.752042: Current learning rate: 0.00842 +2024-11-21 18:28:31.480743: train_loss -0.7615 +2024-11-21 18:28:31.491938: val_loss -0.7736 +2024-11-21 18:28:31.506887: Pseudo dice [0.8472] +2024-11-21 18:28:31.507088: Epoch time: 17.73 s +2024-11-21 18:28:32.527202: +2024-11-21 18:28:32.527426: Epoch 1396 +2024-11-21 18:28:32.527575: Current learning rate: 0.00841 +2024-11-21 18:28:51.723295: train_loss -0.7579 +2024-11-21 18:28:51.731434: val_loss -0.7738 +2024-11-21 18:28:51.731600: Pseudo dice [0.8421] +2024-11-21 18:28:51.731703: Epoch time: 19.2 s +2024-11-21 18:28:52.940792: +2024-11-21 18:28:52.941025: Epoch 1397 +2024-11-21 18:28:52.941151: Current learning rate: 0.00841 +2024-11-21 18:29:11.832982: train_loss -0.7576 +2024-11-21 18:29:11.850814: val_loss -0.7609 +2024-11-21 18:29:11.850991: Pseudo dice [0.8414] +2024-11-21 18:29:11.851133: Epoch time: 18.89 s +2024-11-21 18:29:12.681076: +2024-11-21 18:29:12.681289: Epoch 1398 +2024-11-21 18:29:12.681409: Current learning rate: 0.00841 +2024-11-21 18:29:31.577788: train_loss -0.7571 +2024-11-21 18:29:31.586231: val_loss -0.7467 +2024-11-21 18:29:31.586363: Pseudo dice [0.8638] +2024-11-21 18:29:31.586519: Epoch time: 18.9 s +2024-11-21 18:29:32.515274: +2024-11-21 18:29:32.515496: Epoch 1399 +2024-11-21 18:29:32.515615: Current learning rate: 0.00841 +2024-11-21 18:29:51.291425: train_loss -0.756 +2024-11-21 18:29:51.300107: val_loss -0.7465 +2024-11-21 18:29:51.300249: Pseudo dice [0.8487] +2024-11-21 18:29:51.300356: Epoch time: 18.78 s +2024-11-21 18:29:52.383907: +2024-11-21 18:29:52.384101: Epoch 1400 +2024-11-21 18:29:52.384223: Current learning rate: 0.00841 +2024-11-21 18:30:11.274386: train_loss -0.7509 +2024-11-21 18:30:11.292460: val_loss -0.7366 +2024-11-21 18:30:11.292624: Pseudo dice [0.8395] +2024-11-21 18:30:11.292707: Epoch time: 18.89 s +2024-11-21 18:30:12.182958: +2024-11-21 18:30:12.183173: Epoch 1401 +2024-11-21 18:30:12.183316: Current learning rate: 0.00841 +2024-11-21 18:30:30.098243: train_loss -0.7718 +2024-11-21 18:30:30.113336: val_loss -0.7584 +2024-11-21 18:30:30.113489: Pseudo dice [0.8454] +2024-11-21 18:30:30.113589: Epoch time: 17.92 s +2024-11-21 18:30:31.016380: +2024-11-21 18:30:31.016586: Epoch 1402 +2024-11-21 18:30:31.016712: Current learning rate: 0.00841 +2024-11-21 18:30:49.984558: train_loss -0.7531 +2024-11-21 18:30:49.994037: val_loss -0.7436 +2024-11-21 18:30:49.994177: Pseudo dice [0.8336] +2024-11-21 18:30:49.994288: Epoch time: 18.97 s +2024-11-21 18:30:51.042087: +2024-11-21 18:30:51.042288: Epoch 1403 +2024-11-21 18:30:51.042414: Current learning rate: 0.00841 +2024-11-21 18:31:09.634933: train_loss -0.7598 +2024-11-21 18:31:09.638813: val_loss -0.7706 +2024-11-21 18:31:09.638911: Pseudo dice [0.8557] +2024-11-21 18:31:09.639004: Epoch time: 18.59 s +2024-11-21 18:31:10.463539: +2024-11-21 18:31:10.463733: Epoch 1404 +2024-11-21 18:31:10.463847: Current learning rate: 0.00841 +2024-11-21 18:31:29.992584: train_loss -0.7679 +2024-11-21 18:31:30.018787: val_loss -0.779 +2024-11-21 18:31:30.018950: Pseudo dice [0.8457] +2024-11-21 18:31:30.019038: Epoch time: 19.53 s +2024-11-21 18:31:31.008816: +2024-11-21 18:31:31.009080: Epoch 1405 +2024-11-21 18:31:31.009209: Current learning rate: 0.0084 +2024-11-21 18:31:49.469858: train_loss -0.7678 +2024-11-21 18:31:49.478085: val_loss -0.7799 +2024-11-21 18:31:49.478212: Pseudo dice [0.8423] +2024-11-21 18:31:49.478296: Epoch time: 18.46 s +2024-11-21 18:31:50.484535: +2024-11-21 18:31:50.484736: Epoch 1406 +2024-11-21 18:31:50.484866: Current learning rate: 0.0084 +2024-11-21 18:32:09.209568: train_loss -0.7686 +2024-11-21 18:32:09.234494: val_loss -0.7598 +2024-11-21 18:32:09.234759: Pseudo dice [0.8593] +2024-11-21 18:32:09.234882: Epoch time: 18.73 s +2024-11-21 18:32:10.057778: +2024-11-21 18:32:10.057983: Epoch 1407 +2024-11-21 18:32:10.058127: Current learning rate: 0.0084 +2024-11-21 18:32:28.347962: train_loss -0.7671 +2024-11-21 18:32:28.351371: val_loss -0.7426 +2024-11-21 18:32:28.351504: Pseudo dice [0.838] +2024-11-21 18:32:28.351615: Epoch time: 18.29 s +2024-11-21 18:32:29.569752: +2024-11-21 18:32:29.569949: Epoch 1408 +2024-11-21 18:32:29.570073: Current learning rate: 0.0084 +2024-11-21 18:32:48.221337: train_loss -0.7483 +2024-11-21 18:32:48.251200: val_loss -0.7617 +2024-11-21 18:32:48.251366: Pseudo dice [0.8335] +2024-11-21 18:32:48.251461: Epoch time: 18.65 s +2024-11-21 18:32:49.084054: +2024-11-21 18:32:49.084309: Epoch 1409 +2024-11-21 18:32:49.084515: Current learning rate: 0.0084 +2024-11-21 18:33:08.376052: train_loss -0.7591 +2024-11-21 18:33:08.383706: val_loss -0.7796 +2024-11-21 18:33:08.383838: Pseudo dice [0.8465] +2024-11-21 18:33:08.383934: Epoch time: 19.29 s +2024-11-21 18:33:09.428840: +2024-11-21 18:33:09.429079: Epoch 1410 +2024-11-21 18:33:09.429214: Current learning rate: 0.0084 +2024-11-21 18:33:29.031840: train_loss -0.7703 +2024-11-21 18:33:29.037372: val_loss -0.7593 +2024-11-21 18:33:29.037514: Pseudo dice [0.8441] +2024-11-21 18:33:29.037613: Epoch time: 19.6 s +2024-11-21 18:33:30.021851: +2024-11-21 18:33:30.022083: Epoch 1411 +2024-11-21 18:33:30.022200: Current learning rate: 0.0084 +2024-11-21 18:33:49.408804: train_loss -0.7701 +2024-11-21 18:33:49.417263: val_loss -0.7677 +2024-11-21 18:33:49.417400: Pseudo dice [0.8412] +2024-11-21 18:33:49.417484: Epoch time: 19.39 s +2024-11-21 18:33:50.269860: +2024-11-21 18:33:50.270096: Epoch 1412 +2024-11-21 18:33:50.270228: Current learning rate: 0.0084 +2024-11-21 18:34:09.465906: train_loss -0.7679 +2024-11-21 18:34:09.473262: val_loss -0.7446 +2024-11-21 18:34:09.473407: Pseudo dice [0.8305] +2024-11-21 18:34:09.473511: Epoch time: 19.2 s +2024-11-21 18:34:10.421843: +2024-11-21 18:34:10.422073: Epoch 1413 +2024-11-21 18:34:10.422212: Current learning rate: 0.0084 +2024-11-21 18:34:28.950718: train_loss -0.7659 +2024-11-21 18:34:28.959717: val_loss -0.7523 +2024-11-21 18:34:28.959866: Pseudo dice [0.853] +2024-11-21 18:34:28.959964: Epoch time: 18.53 s +2024-11-21 18:34:29.947170: +2024-11-21 18:34:29.947381: Epoch 1414 +2024-11-21 18:34:29.947496: Current learning rate: 0.00839 +2024-11-21 18:34:48.761142: train_loss -0.7618 +2024-11-21 18:34:48.784844: val_loss -0.7662 +2024-11-21 18:34:48.784989: Pseudo dice [0.8489] +2024-11-21 18:34:48.785092: Epoch time: 18.81 s +2024-11-21 18:34:49.820843: +2024-11-21 18:34:49.821122: Epoch 1415 +2024-11-21 18:34:49.821239: Current learning rate: 0.00839 +2024-11-21 18:35:09.582001: train_loss -0.7635 +2024-11-21 18:35:09.591361: val_loss -0.7896 +2024-11-21 18:35:09.591513: Pseudo dice [0.8567] +2024-11-21 18:35:09.591618: Epoch time: 19.76 s +2024-11-21 18:35:10.419132: +2024-11-21 18:35:10.419330: Epoch 1416 +2024-11-21 18:35:10.419448: Current learning rate: 0.00839 +2024-11-21 18:35:30.007545: train_loss -0.7627 +2024-11-21 18:35:30.015032: val_loss -0.7468 +2024-11-21 18:35:30.015158: Pseudo dice [0.8306] +2024-11-21 18:35:30.015251: Epoch time: 19.59 s +2024-11-21 18:35:31.025121: +2024-11-21 18:35:31.025329: Epoch 1417 +2024-11-21 18:35:31.025454: Current learning rate: 0.00839 +2024-11-21 18:35:49.919326: train_loss -0.7701 +2024-11-21 18:35:49.943646: val_loss -0.7732 +2024-11-21 18:35:49.943801: Pseudo dice [0.8565] +2024-11-21 18:35:49.943916: Epoch time: 18.9 s +2024-11-21 18:35:50.815928: +2024-11-21 18:35:50.816174: Epoch 1418 +2024-11-21 18:35:50.816305: Current learning rate: 0.00839 +2024-11-21 18:36:10.949696: train_loss -0.7714 +2024-11-21 18:36:10.957168: val_loss -0.745 +2024-11-21 18:36:10.957307: Pseudo dice [0.8468] +2024-11-21 18:36:10.957396: Epoch time: 20.13 s +2024-11-21 18:36:11.793233: +2024-11-21 18:36:11.793432: Epoch 1419 +2024-11-21 18:36:11.793567: Current learning rate: 0.00839 +2024-11-21 18:36:30.353263: train_loss -0.7616 +2024-11-21 18:36:30.356865: val_loss -0.7446 +2024-11-21 18:36:30.357002: Pseudo dice [0.8421] +2024-11-21 18:36:30.357277: Epoch time: 18.56 s +2024-11-21 18:36:31.180474: +2024-11-21 18:36:31.180674: Epoch 1420 +2024-11-21 18:36:31.180789: Current learning rate: 0.00839 +2024-11-21 18:36:50.973431: train_loss -0.7666 +2024-11-21 18:36:50.993299: val_loss -0.7618 +2024-11-21 18:36:50.993463: Pseudo dice [0.8485] +2024-11-21 18:36:50.993580: Epoch time: 19.79 s +2024-11-21 18:36:51.952516: +2024-11-21 18:36:51.953006: Epoch 1421 +2024-11-21 18:36:51.953148: Current learning rate: 0.00839 +2024-11-21 18:37:11.843267: train_loss -0.7614 +2024-11-21 18:37:11.849295: val_loss -0.7656 +2024-11-21 18:37:11.849438: Pseudo dice [0.8491] +2024-11-21 18:37:11.849523: Epoch time: 19.89 s +2024-11-21 18:37:12.717596: +2024-11-21 18:37:12.717811: Epoch 1422 +2024-11-21 18:37:12.717954: Current learning rate: 0.00839 +2024-11-21 18:37:32.021376: train_loss -0.7599 +2024-11-21 18:37:32.043367: val_loss -0.756 +2024-11-21 18:37:32.043545: Pseudo dice [0.8321] +2024-11-21 18:37:32.043654: Epoch time: 19.3 s +2024-11-21 18:37:32.873491: +2024-11-21 18:37:32.873714: Epoch 1423 +2024-11-21 18:37:32.873839: Current learning rate: 0.00838 +2024-11-21 18:37:53.280607: train_loss -0.7641 +2024-11-21 18:37:53.287085: val_loss -0.7592 +2024-11-21 18:37:53.287240: Pseudo dice [0.8452] +2024-11-21 18:37:53.287327: Epoch time: 20.41 s +2024-11-21 18:37:54.126674: +2024-11-21 18:37:54.126944: Epoch 1424 +2024-11-21 18:37:54.127067: Current learning rate: 0.00838 +2024-11-21 18:38:12.576708: train_loss -0.7522 +2024-11-21 18:38:12.582138: val_loss -0.7776 +2024-11-21 18:38:12.582315: Pseudo dice [0.8445] +2024-11-21 18:38:12.582424: Epoch time: 18.45 s +2024-11-21 18:38:13.431055: +2024-11-21 18:38:13.431261: Epoch 1425 +2024-11-21 18:38:13.431378: Current learning rate: 0.00838 +2024-11-21 18:38:33.326128: train_loss -0.7532 +2024-11-21 18:38:33.351796: val_loss -0.7522 +2024-11-21 18:38:33.351973: Pseudo dice [0.829] +2024-11-21 18:38:33.352084: Epoch time: 19.9 s +2024-11-21 18:38:34.185433: +2024-11-21 18:38:34.185659: Epoch 1426 +2024-11-21 18:38:34.185783: Current learning rate: 0.00838 +2024-11-21 18:38:53.342996: train_loss -0.7672 +2024-11-21 18:38:53.360089: val_loss -0.7535 +2024-11-21 18:38:53.360259: Pseudo dice [0.8462] +2024-11-21 18:38:53.360364: Epoch time: 19.16 s +2024-11-21 18:38:54.219498: +2024-11-21 18:38:54.219716: Epoch 1427 +2024-11-21 18:38:54.219833: Current learning rate: 0.00838 +2024-11-21 18:39:12.883485: train_loss -0.7666 +2024-11-21 18:39:12.893468: val_loss -0.7553 +2024-11-21 18:39:12.893582: Pseudo dice [0.8427] +2024-11-21 18:39:12.893687: Epoch time: 18.66 s +2024-11-21 18:39:13.723121: +2024-11-21 18:39:13.723345: Epoch 1428 +2024-11-21 18:39:13.723484: Current learning rate: 0.00838 +2024-11-21 18:39:33.816127: train_loss -0.7698 +2024-11-21 18:39:33.819613: val_loss -0.7567 +2024-11-21 18:39:33.819726: Pseudo dice [0.8502] +2024-11-21 18:39:33.819817: Epoch time: 20.09 s +2024-11-21 18:39:34.750993: +2024-11-21 18:39:34.751220: Epoch 1429 +2024-11-21 18:39:34.751336: Current learning rate: 0.00838 +2024-11-21 18:39:53.465868: train_loss -0.7558 +2024-11-21 18:39:53.471856: val_loss -0.7355 +2024-11-21 18:39:53.471995: Pseudo dice [0.8544] +2024-11-21 18:39:53.472106: Epoch time: 18.72 s +2024-11-21 18:39:54.717133: +2024-11-21 18:39:54.717320: Epoch 1430 +2024-11-21 18:39:54.717427: Current learning rate: 0.00838 +2024-11-21 18:40:12.870382: train_loss -0.7654 +2024-11-21 18:40:12.881393: val_loss -0.7527 +2024-11-21 18:40:12.881529: Pseudo dice [0.8431] +2024-11-21 18:40:12.881623: Epoch time: 18.15 s +2024-11-21 18:40:13.870363: +2024-11-21 18:40:13.870592: Epoch 1431 +2024-11-21 18:40:13.870707: Current learning rate: 0.00837 +2024-11-21 18:40:33.526197: train_loss -0.7623 +2024-11-21 18:40:33.543581: val_loss -0.7632 +2024-11-21 18:40:33.543710: Pseudo dice [0.8463] +2024-11-21 18:40:33.543815: Epoch time: 19.66 s +2024-11-21 18:40:34.366123: +2024-11-21 18:40:34.366324: Epoch 1432 +2024-11-21 18:40:34.366446: Current learning rate: 0.00837 +2024-11-21 18:40:53.730529: train_loss -0.7554 +2024-11-21 18:40:53.733669: val_loss -0.7611 +2024-11-21 18:40:53.733802: Pseudo dice [0.8397] +2024-11-21 18:40:53.733889: Epoch time: 19.37 s +2024-11-21 18:40:54.560386: +2024-11-21 18:40:54.560600: Epoch 1433 +2024-11-21 18:40:54.560721: Current learning rate: 0.00837 +2024-11-21 18:41:12.845130: train_loss -0.7686 +2024-11-21 18:41:12.853623: val_loss -0.7767 +2024-11-21 18:41:12.853763: Pseudo dice [0.8467] +2024-11-21 18:41:12.854117: Epoch time: 18.29 s +2024-11-21 18:41:13.716422: +2024-11-21 18:41:13.716639: Epoch 1434 +2024-11-21 18:41:13.716768: Current learning rate: 0.00837 +2024-11-21 18:41:32.380881: train_loss -0.7714 +2024-11-21 18:41:32.395860: val_loss -0.7579 +2024-11-21 18:41:32.395997: Pseudo dice [0.8506] +2024-11-21 18:41:32.396103: Epoch time: 18.67 s +2024-11-21 18:41:33.293149: +2024-11-21 18:41:33.293389: Epoch 1435 +2024-11-21 18:41:33.293941: Current learning rate: 0.00837 +2024-11-21 18:41:51.994557: train_loss -0.755 +2024-11-21 18:41:52.010161: val_loss -0.7664 +2024-11-21 18:41:52.010278: Pseudo dice [0.8527] +2024-11-21 18:41:52.010386: Epoch time: 18.7 s +2024-11-21 18:41:52.832135: +2024-11-21 18:41:52.832354: Epoch 1436 +2024-11-21 18:41:52.832490: Current learning rate: 0.00837 +2024-11-21 18:42:12.068891: train_loss -0.7553 +2024-11-21 18:42:12.077320: val_loss -0.7477 +2024-11-21 18:42:12.077455: Pseudo dice [0.8494] +2024-11-21 18:42:12.077544: Epoch time: 19.24 s +2024-11-21 18:42:12.913512: +2024-11-21 18:42:12.913734: Epoch 1437 +2024-11-21 18:42:12.913865: Current learning rate: 0.00837 +2024-11-21 18:42:31.517466: train_loss -0.7499 +2024-11-21 18:42:31.523329: val_loss -0.7474 +2024-11-21 18:42:31.523456: Pseudo dice [0.8232] +2024-11-21 18:42:31.523609: Epoch time: 18.6 s +2024-11-21 18:42:32.359589: +2024-11-21 18:42:32.359819: Epoch 1438 +2024-11-21 18:42:32.359938: Current learning rate: 0.00837 +2024-11-21 18:42:52.371318: train_loss -0.7564 +2024-11-21 18:42:52.377656: val_loss -0.7559 +2024-11-21 18:42:52.377822: Pseudo dice [0.8545] +2024-11-21 18:42:52.377922: Epoch time: 20.01 s +2024-11-21 18:42:53.240468: +2024-11-21 18:42:53.240671: Epoch 1439 +2024-11-21 18:42:53.240800: Current learning rate: 0.00837 +2024-11-21 18:43:12.684972: train_loss -0.7522 +2024-11-21 18:43:12.702014: val_loss -0.7528 +2024-11-21 18:43:12.702182: Pseudo dice [0.8289] +2024-11-21 18:43:12.702274: Epoch time: 19.45 s +2024-11-21 18:43:13.580189: +2024-11-21 18:43:13.580412: Epoch 1440 +2024-11-21 18:43:13.580554: Current learning rate: 0.00836 +2024-11-21 18:43:32.388024: train_loss -0.7536 +2024-11-21 18:43:32.392382: val_loss -0.7622 +2024-11-21 18:43:32.392515: Pseudo dice [0.8507] +2024-11-21 18:43:32.392599: Epoch time: 18.81 s +2024-11-21 18:43:33.730866: +2024-11-21 18:43:33.731086: Epoch 1441 +2024-11-21 18:43:33.731203: Current learning rate: 0.00836 +2024-11-21 18:43:52.574486: train_loss -0.7609 +2024-11-21 18:43:52.577176: val_loss -0.7466 +2024-11-21 18:43:52.577275: Pseudo dice [0.8195] +2024-11-21 18:43:52.577369: Epoch time: 18.84 s +2024-11-21 18:43:53.395623: +2024-11-21 18:43:53.395878: Epoch 1442 +2024-11-21 18:43:53.395999: Current learning rate: 0.00836 +2024-11-21 18:44:12.788943: train_loss -0.7624 +2024-11-21 18:44:12.818903: val_loss -0.7487 +2024-11-21 18:44:12.819088: Pseudo dice [0.852] +2024-11-21 18:44:12.819193: Epoch time: 19.39 s +2024-11-21 18:44:13.669936: +2024-11-21 18:44:13.670166: Epoch 1443 +2024-11-21 18:44:13.670285: Current learning rate: 0.00836 +2024-11-21 18:44:31.603979: train_loss -0.7694 +2024-11-21 18:44:31.617237: val_loss -0.7426 +2024-11-21 18:44:31.617364: Pseudo dice [0.8211] +2024-11-21 18:44:31.617457: Epoch time: 17.93 s +2024-11-21 18:44:32.438643: +2024-11-21 18:44:32.438925: Epoch 1444 +2024-11-21 18:44:32.439054: Current learning rate: 0.00836 +2024-11-21 18:44:51.044915: train_loss -0.7734 +2024-11-21 18:44:51.047202: val_loss -0.7585 +2024-11-21 18:44:51.047318: Pseudo dice [0.8548] +2024-11-21 18:44:51.047419: Epoch time: 18.61 s +2024-11-21 18:44:51.872818: +2024-11-21 18:44:51.873062: Epoch 1445 +2024-11-21 18:44:51.873180: Current learning rate: 0.00836 +2024-11-21 18:45:11.994667: train_loss -0.7677 +2024-11-21 18:45:12.000417: val_loss -0.7669 +2024-11-21 18:45:12.000552: Pseudo dice [0.8536] +2024-11-21 18:45:12.000659: Epoch time: 20.12 s +2024-11-21 18:45:12.823274: +2024-11-21 18:45:12.823540: Epoch 1446 +2024-11-21 18:45:12.823685: Current learning rate: 0.00836 +2024-11-21 18:45:32.512707: train_loss -0.769 +2024-11-21 18:45:32.519083: val_loss -0.7641 +2024-11-21 18:45:32.519221: Pseudo dice [0.8487] +2024-11-21 18:45:32.519368: Epoch time: 19.69 s +2024-11-21 18:45:33.351267: +2024-11-21 18:45:33.351482: Epoch 1447 +2024-11-21 18:45:33.351623: Current learning rate: 0.00836 +2024-11-21 18:45:54.144210: train_loss -0.7671 +2024-11-21 18:45:54.150452: val_loss -0.7578 +2024-11-21 18:45:54.150575: Pseudo dice [0.8491] +2024-11-21 18:45:54.150662: Epoch time: 20.79 s +2024-11-21 18:45:55.000511: +2024-11-21 18:45:55.000723: Epoch 1448 +2024-11-21 18:45:55.000843: Current learning rate: 0.00836 +2024-11-21 18:46:14.191744: train_loss -0.7682 +2024-11-21 18:46:14.196787: val_loss -0.7461 +2024-11-21 18:46:14.196933: Pseudo dice [0.8488] +2024-11-21 18:46:14.197083: Epoch time: 19.19 s +2024-11-21 18:46:15.016682: +2024-11-21 18:46:15.016896: Epoch 1449 +2024-11-21 18:46:15.017016: Current learning rate: 0.00835 +2024-11-21 18:46:34.157465: train_loss -0.7598 +2024-11-21 18:46:34.184736: val_loss -0.7712 +2024-11-21 18:46:34.184888: Pseudo dice [0.8517] +2024-11-21 18:46:34.184990: Epoch time: 19.14 s +2024-11-21 18:46:35.243203: +2024-11-21 18:46:35.243404: Epoch 1450 +2024-11-21 18:46:35.243527: Current learning rate: 0.00835 +2024-11-21 18:46:54.356791: train_loss -0.7698 +2024-11-21 18:46:54.359814: val_loss -0.7687 +2024-11-21 18:46:54.359962: Pseudo dice [0.8361] +2024-11-21 18:46:54.360079: Epoch time: 19.11 s +2024-11-21 18:46:55.403459: +2024-11-21 18:46:55.403678: Epoch 1451 +2024-11-21 18:46:55.403796: Current learning rate: 0.00835 +2024-11-21 18:47:14.042342: train_loss -0.7659 +2024-11-21 18:47:14.049291: val_loss -0.75 +2024-11-21 18:47:14.049431: Pseudo dice [0.8402] +2024-11-21 18:47:14.049524: Epoch time: 18.64 s +2024-11-21 18:47:14.907334: +2024-11-21 18:47:14.907546: Epoch 1452 +2024-11-21 18:47:14.907667: Current learning rate: 0.00835 +2024-11-21 18:47:33.550564: train_loss -0.7692 +2024-11-21 18:47:33.557588: val_loss -0.7637 +2024-11-21 18:47:33.557736: Pseudo dice [0.8437] +2024-11-21 18:47:33.557840: Epoch time: 18.64 s +2024-11-21 18:47:34.429067: +2024-11-21 18:47:34.429289: Epoch 1453 +2024-11-21 18:47:34.429434: Current learning rate: 0.00835 +2024-11-21 18:47:53.579188: train_loss -0.7585 +2024-11-21 18:47:53.581481: val_loss -0.7563 +2024-11-21 18:47:53.581735: Pseudo dice [0.8508] +2024-11-21 18:47:53.581867: Epoch time: 19.15 s +2024-11-21 18:47:54.404402: +2024-11-21 18:47:54.404627: Epoch 1454 +2024-11-21 18:47:54.404742: Current learning rate: 0.00835 +2024-11-21 18:48:12.414369: train_loss -0.7612 +2024-11-21 18:48:12.417970: val_loss -0.7509 +2024-11-21 18:48:12.418106: Pseudo dice [0.8434] +2024-11-21 18:48:12.418198: Epoch time: 18.01 s +2024-11-21 18:48:13.312823: +2024-11-21 18:48:13.313045: Epoch 1455 +2024-11-21 18:48:13.313179: Current learning rate: 0.00835 +2024-11-21 18:48:31.896976: train_loss -0.7782 +2024-11-21 18:48:31.909597: val_loss -0.7754 +2024-11-21 18:48:31.909757: Pseudo dice [0.8412] +2024-11-21 18:48:31.909848: Epoch time: 18.58 s +2024-11-21 18:48:32.738338: +2024-11-21 18:48:32.738551: Epoch 1456 +2024-11-21 18:48:32.738672: Current learning rate: 0.00835 +2024-11-21 18:48:52.149347: train_loss -0.7637 +2024-11-21 18:48:52.157165: val_loss -0.7625 +2024-11-21 18:48:52.157334: Pseudo dice [0.843] +2024-11-21 18:48:52.157450: Epoch time: 19.41 s +2024-11-21 18:48:52.991481: +2024-11-21 18:48:52.991708: Epoch 1457 +2024-11-21 18:48:52.991830: Current learning rate: 0.00834 +2024-11-21 18:49:12.896049: train_loss -0.771 +2024-11-21 18:49:12.903382: val_loss -0.7545 +2024-11-21 18:49:12.903523: Pseudo dice [0.8305] +2024-11-21 18:49:12.903615: Epoch time: 19.91 s +2024-11-21 18:49:13.755709: +2024-11-21 18:49:13.755916: Epoch 1458 +2024-11-21 18:49:13.756052: Current learning rate: 0.00834 +2024-11-21 18:49:33.273981: train_loss -0.7671 +2024-11-21 18:49:33.281194: val_loss -0.7726 +2024-11-21 18:49:33.281348: Pseudo dice [0.856] +2024-11-21 18:49:33.281442: Epoch time: 19.52 s +2024-11-21 18:49:34.206197: +2024-11-21 18:49:34.206403: Epoch 1459 +2024-11-21 18:49:34.206791: Current learning rate: 0.00834 +2024-11-21 18:49:52.572491: train_loss -0.7454 +2024-11-21 18:49:52.574095: val_loss -0.769 +2024-11-21 18:49:52.574228: Pseudo dice [0.832] +2024-11-21 18:49:52.574317: Epoch time: 18.37 s +2024-11-21 18:49:53.521441: +2024-11-21 18:49:53.521663: Epoch 1460 +2024-11-21 18:49:53.521792: Current learning rate: 0.00834 +2024-11-21 18:50:12.329701: train_loss -0.757 +2024-11-21 18:50:12.331682: val_loss -0.7587 +2024-11-21 18:50:12.331825: Pseudo dice [0.8507] +2024-11-21 18:50:12.331924: Epoch time: 18.81 s +2024-11-21 18:50:13.290754: +2024-11-21 18:50:13.291602: Epoch 1461 +2024-11-21 18:50:13.291773: Current learning rate: 0.00834 +2024-11-21 18:50:31.649686: train_loss -0.7636 +2024-11-21 18:50:31.666187: val_loss -0.7433 +2024-11-21 18:50:31.666338: Pseudo dice [0.8398] +2024-11-21 18:50:31.666439: Epoch time: 18.36 s +2024-11-21 18:50:32.550359: +2024-11-21 18:50:32.550574: Epoch 1462 +2024-11-21 18:50:32.550709: Current learning rate: 0.00834 +2024-11-21 18:50:51.981870: train_loss -0.7608 +2024-11-21 18:50:51.984159: val_loss -0.7735 +2024-11-21 18:50:51.984256: Pseudo dice [0.8347] +2024-11-21 18:50:51.984334: Epoch time: 19.43 s +2024-11-21 18:50:53.178405: +2024-11-21 18:50:53.178614: Epoch 1463 +2024-11-21 18:50:53.178746: Current learning rate: 0.00834 +2024-11-21 18:51:11.156851: train_loss -0.7605 +2024-11-21 18:51:11.162976: val_loss -0.7413 +2024-11-21 18:51:11.163118: Pseudo dice [0.8401] +2024-11-21 18:51:11.163216: Epoch time: 17.98 s +2024-11-21 18:51:11.987837: +2024-11-21 18:51:11.988097: Epoch 1464 +2024-11-21 18:51:11.988257: Current learning rate: 0.00834 +2024-11-21 18:51:30.883523: train_loss -0.7628 +2024-11-21 18:51:30.889080: val_loss -0.769 +2024-11-21 18:51:30.889210: Pseudo dice [0.8432] +2024-11-21 18:51:30.889319: Epoch time: 18.9 s +2024-11-21 18:51:31.890487: +2024-11-21 18:51:31.890705: Epoch 1465 +2024-11-21 18:51:31.890829: Current learning rate: 0.00834 +2024-11-21 18:51:51.717000: train_loss -0.7555 +2024-11-21 18:51:51.721561: val_loss -0.7809 +2024-11-21 18:51:51.721695: Pseudo dice [0.8679] +2024-11-21 18:51:51.721781: Epoch time: 19.83 s +2024-11-21 18:51:52.616648: +2024-11-21 18:51:52.616866: Epoch 1466 +2024-11-21 18:51:52.616990: Current learning rate: 0.00833 +2024-11-21 18:52:11.845711: train_loss -0.7655 +2024-11-21 18:52:11.853284: val_loss -0.7678 +2024-11-21 18:52:11.853398: Pseudo dice [0.8321] +2024-11-21 18:52:11.853491: Epoch time: 19.23 s +2024-11-21 18:52:12.773113: +2024-11-21 18:52:12.773367: Epoch 1467 +2024-11-21 18:52:12.773501: Current learning rate: 0.00833 +2024-11-21 18:52:32.032982: train_loss -0.7563 +2024-11-21 18:52:32.039557: val_loss -0.7575 +2024-11-21 18:52:32.039701: Pseudo dice [0.8321] +2024-11-21 18:52:32.039788: Epoch time: 19.26 s +2024-11-21 18:52:32.968549: +2024-11-21 18:52:32.968777: Epoch 1468 +2024-11-21 18:52:32.968901: Current learning rate: 0.00833 +2024-11-21 18:52:51.686960: train_loss -0.763 +2024-11-21 18:52:51.693110: val_loss -0.7394 +2024-11-21 18:52:51.693266: Pseudo dice [0.8431] +2024-11-21 18:52:51.693365: Epoch time: 18.72 s +2024-11-21 18:52:52.729937: +2024-11-21 18:52:52.730157: Epoch 1469 +2024-11-21 18:52:52.730284: Current learning rate: 0.00833 +2024-11-21 18:53:11.994195: train_loss -0.7634 +2024-11-21 18:53:12.000350: val_loss -0.7638 +2024-11-21 18:53:12.000502: Pseudo dice [0.8357] +2024-11-21 18:53:12.000601: Epoch time: 19.27 s +2024-11-21 18:53:12.918994: +2024-11-21 18:53:12.919213: Epoch 1470 +2024-11-21 18:53:12.919334: Current learning rate: 0.00833 +2024-11-21 18:53:31.264450: train_loss -0.7702 +2024-11-21 18:53:31.277687: val_loss -0.7701 +2024-11-21 18:53:31.277858: Pseudo dice [0.8561] +2024-11-21 18:53:31.277958: Epoch time: 18.35 s +2024-11-21 18:53:32.120555: +2024-11-21 18:53:32.120771: Epoch 1471 +2024-11-21 18:53:32.120901: Current learning rate: 0.00833 +2024-11-21 18:53:50.816158: train_loss -0.7652 +2024-11-21 18:53:50.819398: val_loss -0.7693 +2024-11-21 18:53:50.819548: Pseudo dice [0.8446] +2024-11-21 18:53:50.819916: Epoch time: 18.7 s +2024-11-21 18:53:51.657025: +2024-11-21 18:53:51.657231: Epoch 1472 +2024-11-21 18:53:51.657367: Current learning rate: 0.00833 +2024-11-21 18:54:10.878178: train_loss -0.7692 +2024-11-21 18:54:10.881179: val_loss -0.7607 +2024-11-21 18:54:10.881277: Pseudo dice [0.8321] +2024-11-21 18:54:10.881371: Epoch time: 19.22 s +2024-11-21 18:54:11.706659: +2024-11-21 18:54:11.706844: Epoch 1473 +2024-11-21 18:54:11.706951: Current learning rate: 0.00833 +2024-11-21 18:54:30.694360: train_loss -0.7598 +2024-11-21 18:54:30.719402: val_loss -0.7811 +2024-11-21 18:54:30.719566: Pseudo dice [0.857] +2024-11-21 18:54:30.719664: Epoch time: 18.99 s +2024-11-21 18:54:31.590651: +2024-11-21 18:54:31.590892: Epoch 1474 +2024-11-21 18:54:31.591015: Current learning rate: 0.00833 +2024-11-21 18:54:49.572194: train_loss -0.7706 +2024-11-21 18:54:49.576947: val_loss -0.7689 +2024-11-21 18:54:49.577080: Pseudo dice [0.8521] +2024-11-21 18:54:49.577264: Epoch time: 17.98 s +2024-11-21 18:54:51.107621: +2024-11-21 18:54:51.107825: Epoch 1475 +2024-11-21 18:54:51.107961: Current learning rate: 0.00832 +2024-11-21 18:55:09.700609: train_loss -0.7659 +2024-11-21 18:55:09.707836: val_loss -0.759 +2024-11-21 18:55:09.707970: Pseudo dice [0.8551] +2024-11-21 18:55:09.708080: Epoch time: 18.59 s +2024-11-21 18:55:10.539239: +2024-11-21 18:55:10.539447: Epoch 1476 +2024-11-21 18:55:10.539566: Current learning rate: 0.00832 +2024-11-21 18:55:30.112824: train_loss -0.7381 +2024-11-21 18:55:30.115647: val_loss -0.766 +2024-11-21 18:55:30.115775: Pseudo dice [0.8367] +2024-11-21 18:55:30.115855: Epoch time: 19.57 s +2024-11-21 18:55:30.982969: +2024-11-21 18:55:30.983203: Epoch 1477 +2024-11-21 18:55:30.983319: Current learning rate: 0.00832 +2024-11-21 18:55:49.829112: train_loss -0.7582 +2024-11-21 18:55:49.833481: val_loss -0.7642 +2024-11-21 18:55:49.833635: Pseudo dice [0.8339] +2024-11-21 18:55:49.833733: Epoch time: 18.85 s +2024-11-21 18:55:50.683465: +2024-11-21 18:55:50.683686: Epoch 1478 +2024-11-21 18:55:50.683811: Current learning rate: 0.00832 +2024-11-21 18:56:10.398386: train_loss -0.759 +2024-11-21 18:56:10.419620: val_loss -0.761 +2024-11-21 18:56:10.419787: Pseudo dice [0.8572] +2024-11-21 18:56:10.419882: Epoch time: 19.72 s +2024-11-21 18:56:11.331684: +2024-11-21 18:56:11.331887: Epoch 1479 +2024-11-21 18:56:11.332017: Current learning rate: 0.00832 +2024-11-21 18:56:29.721744: train_loss -0.7659 +2024-11-21 18:56:29.727150: val_loss -0.7565 +2024-11-21 18:56:29.727276: Pseudo dice [0.8485] +2024-11-21 18:56:29.727371: Epoch time: 18.39 s +2024-11-21 18:56:30.555341: +2024-11-21 18:56:30.555578: Epoch 1480 +2024-11-21 18:56:30.555702: Current learning rate: 0.00832 +2024-11-21 18:56:48.759387: train_loss -0.7635 +2024-11-21 18:56:48.765324: val_loss -0.751 +2024-11-21 18:56:48.765464: Pseudo dice [0.8206] +2024-11-21 18:56:48.765580: Epoch time: 18.2 s +2024-11-21 18:56:49.735329: +2024-11-21 18:56:49.735532: Epoch 1481 +2024-11-21 18:56:49.735651: Current learning rate: 0.00832 +2024-11-21 18:57:08.593103: train_loss -0.7542 +2024-11-21 18:57:08.598102: val_loss -0.7275 +2024-11-21 18:57:08.598262: Pseudo dice [0.837] +2024-11-21 18:57:08.598352: Epoch time: 18.86 s +2024-11-21 18:57:09.427023: +2024-11-21 18:57:09.427231: Epoch 1482 +2024-11-21 18:57:09.427376: Current learning rate: 0.00832 +2024-11-21 18:57:29.624084: train_loss -0.757 +2024-11-21 18:57:29.627439: val_loss -0.7524 +2024-11-21 18:57:29.627550: Pseudo dice [0.8543] +2024-11-21 18:57:29.627690: Epoch time: 20.2 s +2024-11-21 18:57:30.467843: +2024-11-21 18:57:30.468045: Epoch 1483 +2024-11-21 18:57:30.468169: Current learning rate: 0.00831 +2024-11-21 18:57:51.226446: train_loss -0.76 +2024-11-21 18:57:51.233303: val_loss -0.7482 +2024-11-21 18:57:51.233444: Pseudo dice [0.8321] +2024-11-21 18:57:51.233546: Epoch time: 20.76 s +2024-11-21 18:57:52.069398: +2024-11-21 18:57:52.069658: Epoch 1484 +2024-11-21 18:57:52.069784: Current learning rate: 0.00831 +2024-11-21 18:58:10.305678: train_loss -0.77 +2024-11-21 18:58:10.320112: val_loss -0.7822 +2024-11-21 18:58:10.320273: Pseudo dice [0.8539] +2024-11-21 18:58:10.320374: Epoch time: 18.24 s +2024-11-21 18:58:11.160434: +2024-11-21 18:58:11.160630: Epoch 1485 +2024-11-21 18:58:11.160748: Current learning rate: 0.00831 +2024-11-21 18:58:30.445608: train_loss -0.771 +2024-11-21 18:58:30.461924: val_loss -0.7543 +2024-11-21 18:58:30.462113: Pseudo dice [0.858] +2024-11-21 18:58:30.462209: Epoch time: 19.29 s +2024-11-21 18:58:31.720791: +2024-11-21 18:58:31.721005: Epoch 1486 +2024-11-21 18:58:31.721131: Current learning rate: 0.00831 +2024-11-21 18:58:51.609400: train_loss -0.76 +2024-11-21 18:58:51.616158: val_loss -0.776 +2024-11-21 18:58:51.616302: Pseudo dice [0.8572] +2024-11-21 18:58:51.616388: Epoch time: 19.89 s +2024-11-21 18:58:52.692581: +2024-11-21 18:58:52.692794: Epoch 1487 +2024-11-21 18:58:52.692924: Current learning rate: 0.00831 +2024-11-21 18:59:10.342391: train_loss -0.7619 +2024-11-21 18:59:10.350143: val_loss -0.7662 +2024-11-21 18:59:10.350286: Pseudo dice [0.8442] +2024-11-21 18:59:10.350378: Epoch time: 17.65 s +2024-11-21 18:59:11.277431: +2024-11-21 18:59:11.277703: Epoch 1488 +2024-11-21 18:59:11.277835: Current learning rate: 0.00831 +2024-11-21 18:59:30.181879: train_loss -0.7651 +2024-11-21 18:59:30.186465: val_loss -0.7718 +2024-11-21 18:59:30.186598: Pseudo dice [0.8432] +2024-11-21 18:59:30.186697: Epoch time: 18.91 s +2024-11-21 18:59:31.047993: +2024-11-21 18:59:31.048232: Epoch 1489 +2024-11-21 18:59:31.048346: Current learning rate: 0.00831 +2024-11-21 18:59:50.102140: train_loss -0.7623 +2024-11-21 18:59:50.117596: val_loss -0.7417 +2024-11-21 18:59:50.117748: Pseudo dice [0.8517] +2024-11-21 18:59:50.117840: Epoch time: 19.05 s +2024-11-21 18:59:51.017885: +2024-11-21 18:59:51.018103: Epoch 1490 +2024-11-21 18:59:51.018238: Current learning rate: 0.00831 +2024-11-21 19:00:10.025972: train_loss -0.7647 +2024-11-21 19:00:10.032527: val_loss -0.7667 +2024-11-21 19:00:10.032695: Pseudo dice [0.8369] +2024-11-21 19:00:10.032787: Epoch time: 19.01 s +2024-11-21 19:00:10.986977: +2024-11-21 19:00:10.987205: Epoch 1491 +2024-11-21 19:00:10.987334: Current learning rate: 0.00831 +2024-11-21 19:00:29.472597: train_loss -0.7659 +2024-11-21 19:00:29.476126: val_loss -0.742 +2024-11-21 19:00:29.476228: Pseudo dice [0.837] +2024-11-21 19:00:29.476320: Epoch time: 18.49 s +2024-11-21 19:00:30.301881: +2024-11-21 19:00:30.302109: Epoch 1492 +2024-11-21 19:00:30.302231: Current learning rate: 0.0083 +2024-11-21 19:00:51.458902: train_loss -0.7655 +2024-11-21 19:00:51.467484: val_loss -0.7409 +2024-11-21 19:00:51.467616: Pseudo dice [0.8359] +2024-11-21 19:00:51.467775: Epoch time: 21.16 s +2024-11-21 19:00:52.296799: +2024-11-21 19:00:52.296996: Epoch 1493 +2024-11-21 19:00:52.297127: Current learning rate: 0.0083 +2024-11-21 19:01:12.552845: train_loss -0.7533 +2024-11-21 19:01:12.570673: val_loss -0.7593 +2024-11-21 19:01:12.570837: Pseudo dice [0.8511] +2024-11-21 19:01:12.570946: Epoch time: 20.26 s +2024-11-21 19:01:13.395619: +2024-11-21 19:01:13.395817: Epoch 1494 +2024-11-21 19:01:13.395941: Current learning rate: 0.0083 +2024-11-21 19:01:31.687032: train_loss -0.7623 +2024-11-21 19:01:31.698546: val_loss -0.7795 +2024-11-21 19:01:31.698695: Pseudo dice [0.8469] +2024-11-21 19:01:31.698800: Epoch time: 18.29 s +2024-11-21 19:01:32.616455: +2024-11-21 19:01:32.616653: Epoch 1495 +2024-11-21 19:01:32.616771: Current learning rate: 0.0083 +2024-11-21 19:01:50.776627: train_loss -0.7736 +2024-11-21 19:01:50.783866: val_loss -0.7664 +2024-11-21 19:01:50.784025: Pseudo dice [0.8636] +2024-11-21 19:01:50.784148: Epoch time: 18.16 s +2024-11-21 19:01:51.854623: +2024-11-21 19:01:51.854840: Epoch 1496 +2024-11-21 19:01:51.854954: Current learning rate: 0.0083 +2024-11-21 19:02:11.818357: train_loss -0.7643 +2024-11-21 19:02:11.837501: val_loss -0.7625 +2024-11-21 19:02:11.837656: Pseudo dice [0.864] +2024-11-21 19:02:11.837754: Epoch time: 19.96 s +2024-11-21 19:02:12.793791: +2024-11-21 19:02:12.793990: Epoch 1497 +2024-11-21 19:02:12.794134: Current learning rate: 0.0083 +2024-11-21 19:02:30.890262: train_loss -0.7769 +2024-11-21 19:02:30.893116: val_loss -0.7613 +2024-11-21 19:02:30.893237: Pseudo dice [0.8475] +2024-11-21 19:02:30.893322: Epoch time: 18.1 s +2024-11-21 19:02:32.130891: +2024-11-21 19:02:32.131094: Epoch 1498 +2024-11-21 19:02:32.131205: Current learning rate: 0.0083 +2024-11-21 19:02:51.802330: train_loss -0.7592 +2024-11-21 19:02:51.804882: val_loss -0.7461 +2024-11-21 19:02:51.804978: Pseudo dice [0.8501] +2024-11-21 19:02:51.805084: Epoch time: 19.67 s +2024-11-21 19:02:52.633233: +2024-11-21 19:02:52.633447: Epoch 1499 +2024-11-21 19:02:52.633584: Current learning rate: 0.0083 +2024-11-21 19:03:11.739793: train_loss -0.7689 +2024-11-21 19:03:11.743556: val_loss -0.7859 +2024-11-21 19:03:11.743653: Pseudo dice [0.8573] +2024-11-21 19:03:11.743742: Epoch time: 19.11 s +2024-11-21 19:03:11.939449: Yayy! New best EMA pseudo Dice: 0.8493 +2024-11-21 19:03:12.947579: +2024-11-21 19:03:12.947792: Epoch 1500 +2024-11-21 19:03:12.947918: Current learning rate: 0.0083 +2024-11-21 19:03:32.564536: train_loss -0.7652 +2024-11-21 19:03:32.573019: val_loss -0.7393 +2024-11-21 19:03:32.573171: Pseudo dice [0.8316] +2024-11-21 19:03:32.573296: Epoch time: 19.62 s +2024-11-21 19:03:33.517385: +2024-11-21 19:03:33.517613: Epoch 1501 +2024-11-21 19:03:33.517728: Current learning rate: 0.00829 +2024-11-21 19:03:53.757090: train_loss -0.7518 +2024-11-21 19:03:53.764661: val_loss -0.7805 +2024-11-21 19:03:53.764787: Pseudo dice [0.8448] +2024-11-21 19:03:53.764874: Epoch time: 20.24 s +2024-11-21 19:03:54.590478: +2024-11-21 19:03:54.590707: Epoch 1502 +2024-11-21 19:03:54.590826: Current learning rate: 0.00829 +2024-11-21 19:04:13.539578: train_loss -0.7625 +2024-11-21 19:04:13.544225: val_loss -0.73 +2024-11-21 19:04:13.544412: Pseudo dice [0.8545] +2024-11-21 19:04:13.544520: Epoch time: 18.95 s +2024-11-21 19:04:14.382914: +2024-11-21 19:04:14.383164: Epoch 1503 +2024-11-21 19:04:14.383305: Current learning rate: 0.00829 +2024-11-21 19:04:35.053653: train_loss -0.7632 +2024-11-21 19:04:35.057043: val_loss -0.7679 +2024-11-21 19:04:35.057160: Pseudo dice [0.8372] +2024-11-21 19:04:35.057251: Epoch time: 20.67 s +2024-11-21 19:04:35.881992: +2024-11-21 19:04:35.882207: Epoch 1504 +2024-11-21 19:04:35.882338: Current learning rate: 0.00829 +2024-11-21 19:04:55.067782: train_loss -0.7687 +2024-11-21 19:04:55.094720: val_loss -0.782 +2024-11-21 19:04:55.094851: Pseudo dice [0.8451] +2024-11-21 19:04:55.094945: Epoch time: 19.19 s +2024-11-21 19:04:56.055945: +2024-11-21 19:04:56.056142: Epoch 1505 +2024-11-21 19:04:56.056274: Current learning rate: 0.00829 +2024-11-21 19:05:14.494946: train_loss -0.7658 +2024-11-21 19:05:14.501805: val_loss -0.7772 +2024-11-21 19:05:14.501951: Pseudo dice [0.8524] +2024-11-21 19:05:14.502057: Epoch time: 18.44 s +2024-11-21 19:05:15.396305: +2024-11-21 19:05:15.396507: Epoch 1506 +2024-11-21 19:05:15.396631: Current learning rate: 0.00829 +2024-11-21 19:05:34.611864: train_loss -0.768 +2024-11-21 19:05:34.620057: val_loss -0.7614 +2024-11-21 19:05:34.620191: Pseudo dice [0.8426] +2024-11-21 19:05:34.626790: Epoch time: 19.22 s +2024-11-21 19:05:35.521986: +2024-11-21 19:05:35.522197: Epoch 1507 +2024-11-21 19:05:35.522319: Current learning rate: 0.00829 +2024-11-21 19:05:54.232526: train_loss -0.7671 +2024-11-21 19:05:54.235613: val_loss -0.7491 +2024-11-21 19:05:54.235800: Pseudo dice [0.8408] +2024-11-21 19:05:54.235889: Epoch time: 18.71 s +2024-11-21 19:05:55.209390: +2024-11-21 19:05:55.209611: Epoch 1508 +2024-11-21 19:05:55.209751: Current learning rate: 0.00829 +2024-11-21 19:06:14.925750: train_loss -0.7575 +2024-11-21 19:06:14.929576: val_loss -0.7798 +2024-11-21 19:06:14.929673: Pseudo dice [0.8443] +2024-11-21 19:06:14.929764: Epoch time: 19.72 s +2024-11-21 19:06:16.121007: +2024-11-21 19:06:16.121472: Epoch 1509 +2024-11-21 19:06:16.121611: Current learning rate: 0.00829 +2024-11-21 19:06:35.427858: train_loss -0.7579 +2024-11-21 19:06:35.435481: val_loss -0.7552 +2024-11-21 19:06:35.435626: Pseudo dice [0.8485] +2024-11-21 19:06:35.435933: Epoch time: 19.31 s +2024-11-21 19:06:36.304962: +2024-11-21 19:06:36.305220: Epoch 1510 +2024-11-21 19:06:36.305362: Current learning rate: 0.00828 +2024-11-21 19:06:55.297970: train_loss -0.7562 +2024-11-21 19:06:55.306009: val_loss -0.7031 +2024-11-21 19:06:55.306181: Pseudo dice [0.8003] +2024-11-21 19:06:55.306282: Epoch time: 18.99 s +2024-11-21 19:06:56.303048: +2024-11-21 19:06:56.303282: Epoch 1511 +2024-11-21 19:06:56.303398: Current learning rate: 0.00828 +2024-11-21 19:07:15.031397: train_loss -0.7475 +2024-11-21 19:07:15.039315: val_loss -0.7359 +2024-11-21 19:07:15.039458: Pseudo dice [0.8093] +2024-11-21 19:07:15.039556: Epoch time: 18.73 s +2024-11-21 19:07:15.923404: +2024-11-21 19:07:15.923624: Epoch 1512 +2024-11-21 19:07:15.923745: Current learning rate: 0.00828 +2024-11-21 19:07:34.054397: train_loss -0.7593 +2024-11-21 19:07:34.061287: val_loss -0.7442 +2024-11-21 19:07:34.061474: Pseudo dice [0.8409] +2024-11-21 19:07:34.061811: Epoch time: 18.13 s +2024-11-21 19:07:35.062183: +2024-11-21 19:07:35.062392: Epoch 1513 +2024-11-21 19:07:35.062519: Current learning rate: 0.00828 +2024-11-21 19:07:54.778422: train_loss -0.7718 +2024-11-21 19:07:54.784774: val_loss -0.7581 +2024-11-21 19:07:54.784925: Pseudo dice [0.8352] +2024-11-21 19:07:54.785029: Epoch time: 19.72 s +2024-11-21 19:07:55.635865: +2024-11-21 19:07:55.636161: Epoch 1514 +2024-11-21 19:07:55.636288: Current learning rate: 0.00828 +2024-11-21 19:08:15.284860: train_loss -0.7583 +2024-11-21 19:08:15.290071: val_loss -0.7515 +2024-11-21 19:08:15.290228: Pseudo dice [0.8349] +2024-11-21 19:08:15.290323: Epoch time: 19.65 s +2024-11-21 19:08:16.307479: +2024-11-21 19:08:16.307698: Epoch 1515 +2024-11-21 19:08:16.307828: Current learning rate: 0.00828 +2024-11-21 19:08:35.560394: train_loss -0.7633 +2024-11-21 19:08:35.563505: val_loss -0.7831 +2024-11-21 19:08:35.563617: Pseudo dice [0.8465] +2024-11-21 19:08:35.563717: Epoch time: 19.25 s +2024-11-21 19:08:36.466392: +2024-11-21 19:08:36.466605: Epoch 1516 +2024-11-21 19:08:36.466716: Current learning rate: 0.00828 +2024-11-21 19:08:55.140359: train_loss -0.7647 +2024-11-21 19:08:55.143659: val_loss -0.7788 +2024-11-21 19:08:55.143799: Pseudo dice [0.8413] +2024-11-21 19:08:55.143883: Epoch time: 18.67 s +2024-11-21 19:08:56.055095: +2024-11-21 19:08:56.055383: Epoch 1517 +2024-11-21 19:08:56.055538: Current learning rate: 0.00828 +2024-11-21 19:09:15.759165: train_loss -0.7615 +2024-11-21 19:09:15.763312: val_loss -0.7421 +2024-11-21 19:09:15.763459: Pseudo dice [0.8201] +2024-11-21 19:09:15.763573: Epoch time: 19.71 s +2024-11-21 19:09:16.619587: +2024-11-21 19:09:16.619809: Epoch 1518 +2024-11-21 19:09:16.619935: Current learning rate: 0.00827 +2024-11-21 19:09:36.238412: train_loss -0.7616 +2024-11-21 19:09:36.240988: val_loss -0.7629 +2024-11-21 19:09:36.241110: Pseudo dice [0.8558] +2024-11-21 19:09:36.241221: Epoch time: 19.62 s +2024-11-21 19:09:37.070804: +2024-11-21 19:09:37.071052: Epoch 1519 +2024-11-21 19:09:37.071199: Current learning rate: 0.00827 +2024-11-21 19:09:55.596236: train_loss -0.7595 +2024-11-21 19:09:55.617784: val_loss -0.7613 +2024-11-21 19:09:55.617932: Pseudo dice [0.834] +2024-11-21 19:09:55.618050: Epoch time: 18.53 s +2024-11-21 19:09:56.965523: +2024-11-21 19:09:56.965745: Epoch 1520 +2024-11-21 19:09:56.965858: Current learning rate: 0.00827 +2024-11-21 19:10:16.926932: train_loss -0.758 +2024-11-21 19:10:16.933906: val_loss -0.7734 +2024-11-21 19:10:16.934071: Pseudo dice [0.8518] +2024-11-21 19:10:16.934184: Epoch time: 19.96 s +2024-11-21 19:10:17.822861: +2024-11-21 19:10:17.823099: Epoch 1521 +2024-11-21 19:10:17.823219: Current learning rate: 0.00827 +2024-11-21 19:10:36.805769: train_loss -0.7617 +2024-11-21 19:10:36.812805: val_loss -0.7691 +2024-11-21 19:10:36.812951: Pseudo dice [0.8498] +2024-11-21 19:10:36.813044: Epoch time: 18.98 s +2024-11-21 19:10:37.673955: +2024-11-21 19:10:37.674230: Epoch 1522 +2024-11-21 19:10:37.674343: Current learning rate: 0.00827 +2024-11-21 19:10:56.581053: train_loss -0.7682 +2024-11-21 19:10:56.585984: val_loss -0.7779 +2024-11-21 19:10:56.586141: Pseudo dice [0.8516] +2024-11-21 19:10:56.586230: Epoch time: 18.91 s +2024-11-21 19:10:57.434702: +2024-11-21 19:10:57.434966: Epoch 1523 +2024-11-21 19:10:57.435102: Current learning rate: 0.00827 +2024-11-21 19:11:16.331126: train_loss -0.7659 +2024-11-21 19:11:16.334152: val_loss -0.7753 +2024-11-21 19:11:16.334296: Pseudo dice [0.8592] +2024-11-21 19:11:16.334388: Epoch time: 18.9 s +2024-11-21 19:11:17.243084: +2024-11-21 19:11:17.243327: Epoch 1524 +2024-11-21 19:11:17.243468: Current learning rate: 0.00827 +2024-11-21 19:11:36.701840: train_loss -0.7757 +2024-11-21 19:11:36.723128: val_loss -0.7436 +2024-11-21 19:11:36.723305: Pseudo dice [0.8473] +2024-11-21 19:11:36.723419: Epoch time: 19.46 s +2024-11-21 19:11:37.806235: +2024-11-21 19:11:37.806456: Epoch 1525 +2024-11-21 19:11:37.806585: Current learning rate: 0.00827 +2024-11-21 19:11:57.172692: train_loss -0.7638 +2024-11-21 19:11:57.179907: val_loss -0.773 +2024-11-21 19:11:57.180093: Pseudo dice [0.8551] +2024-11-21 19:11:57.180185: Epoch time: 19.37 s +2024-11-21 19:11:58.177610: +2024-11-21 19:11:58.177829: Epoch 1526 +2024-11-21 19:11:58.177967: Current learning rate: 0.00827 +2024-11-21 19:12:17.443510: train_loss -0.7641 +2024-11-21 19:12:17.460423: val_loss -0.7675 +2024-11-21 19:12:17.460553: Pseudo dice [0.8461] +2024-11-21 19:12:17.460658: Epoch time: 19.27 s +2024-11-21 19:12:18.574318: +2024-11-21 19:12:18.574557: Epoch 1527 +2024-11-21 19:12:18.574682: Current learning rate: 0.00826 +2024-11-21 19:12:37.254021: train_loss -0.7696 +2024-11-21 19:12:37.256907: val_loss -0.7586 +2024-11-21 19:12:37.257010: Pseudo dice [0.8524] +2024-11-21 19:12:37.257106: Epoch time: 18.68 s +2024-11-21 19:12:38.089658: +2024-11-21 19:12:38.089878: Epoch 1528 +2024-11-21 19:12:38.089998: Current learning rate: 0.00826 +2024-11-21 19:12:56.824214: train_loss -0.7637 +2024-11-21 19:12:56.829955: val_loss -0.7747 +2024-11-21 19:12:56.830108: Pseudo dice [0.8527] +2024-11-21 19:12:56.830213: Epoch time: 18.74 s +2024-11-21 19:12:57.850978: +2024-11-21 19:12:57.851175: Epoch 1529 +2024-11-21 19:12:57.851290: Current learning rate: 0.00826 +2024-11-21 19:13:15.753018: train_loss -0.7678 +2024-11-21 19:13:15.770041: val_loss -0.7687 +2024-11-21 19:13:15.770183: Pseudo dice [0.8482] +2024-11-21 19:13:15.770270: Epoch time: 17.9 s +2024-11-21 19:13:16.646355: +2024-11-21 19:13:16.646548: Epoch 1530 +2024-11-21 19:13:16.646671: Current learning rate: 0.00826 +2024-11-21 19:13:34.594435: train_loss -0.7678 +2024-11-21 19:13:34.599665: val_loss -0.7624 +2024-11-21 19:13:34.599816: Pseudo dice [0.8519] +2024-11-21 19:13:34.599921: Epoch time: 17.95 s +2024-11-21 19:13:35.870203: +2024-11-21 19:13:35.870427: Epoch 1531 +2024-11-21 19:13:35.870559: Current learning rate: 0.00826 +2024-11-21 19:13:54.351185: train_loss -0.7669 +2024-11-21 19:13:54.357269: val_loss -0.7577 +2024-11-21 19:13:54.357407: Pseudo dice [0.8355] +2024-11-21 19:13:54.357658: Epoch time: 18.48 s +2024-11-21 19:13:55.243212: +2024-11-21 19:13:55.243427: Epoch 1532 +2024-11-21 19:13:55.243566: Current learning rate: 0.00826 +2024-11-21 19:14:14.614030: train_loss -0.772 +2024-11-21 19:14:14.620749: val_loss -0.7492 +2024-11-21 19:14:14.620897: Pseudo dice [0.8513] +2024-11-21 19:14:14.620992: Epoch time: 19.37 s +2024-11-21 19:14:15.511669: +2024-11-21 19:14:15.511892: Epoch 1533 +2024-11-21 19:14:15.512011: Current learning rate: 0.00826 +2024-11-21 19:14:35.894422: train_loss -0.768 +2024-11-21 19:14:35.902563: val_loss -0.7405 +2024-11-21 19:14:35.902716: Pseudo dice [0.8568] +2024-11-21 19:14:35.902800: Epoch time: 20.38 s +2024-11-21 19:14:36.925012: +2024-11-21 19:14:36.925223: Epoch 1534 +2024-11-21 19:14:36.925341: Current learning rate: 0.00826 +2024-11-21 19:14:55.860118: train_loss -0.7527 +2024-11-21 19:14:55.867323: val_loss -0.7561 +2024-11-21 19:14:55.867466: Pseudo dice [0.8487] +2024-11-21 19:14:55.867572: Epoch time: 18.94 s +2024-11-21 19:14:56.750031: +2024-11-21 19:14:56.750259: Epoch 1535 +2024-11-21 19:14:56.750652: Current learning rate: 0.00826 +2024-11-21 19:15:15.261032: train_loss -0.7572 +2024-11-21 19:15:15.264189: val_loss -0.7635 +2024-11-21 19:15:15.264329: Pseudo dice [0.8311] +2024-11-21 19:15:15.264424: Epoch time: 18.51 s +2024-11-21 19:15:16.113161: +2024-11-21 19:15:16.113392: Epoch 1536 +2024-11-21 19:15:16.113513: Current learning rate: 0.00825 +2024-11-21 19:15:35.554511: train_loss -0.7576 +2024-11-21 19:15:35.576913: val_loss -0.7778 +2024-11-21 19:15:35.577068: Pseudo dice [0.8461] +2024-11-21 19:15:35.577157: Epoch time: 19.44 s +2024-11-21 19:15:36.544887: +2024-11-21 19:15:36.545111: Epoch 1537 +2024-11-21 19:15:36.545231: Current learning rate: 0.00825 +2024-11-21 19:15:55.862868: train_loss -0.7611 +2024-11-21 19:15:55.868918: val_loss -0.7744 +2024-11-21 19:15:55.869048: Pseudo dice [0.8438] +2024-11-21 19:15:55.869177: Epoch time: 19.32 s +2024-11-21 19:15:56.738772: +2024-11-21 19:15:56.738982: Epoch 1538 +2024-11-21 19:15:56.739121: Current learning rate: 0.00825 +2024-11-21 19:16:16.502313: train_loss -0.7601 +2024-11-21 19:16:16.515372: val_loss -0.7484 +2024-11-21 19:16:16.515785: Pseudo dice [0.8459] +2024-11-21 19:16:16.515881: Epoch time: 19.76 s +2024-11-21 19:16:17.557505: +2024-11-21 19:16:17.557731: Epoch 1539 +2024-11-21 19:16:17.557859: Current learning rate: 0.00825 +2024-11-21 19:16:36.141092: train_loss -0.7626 +2024-11-21 19:16:36.149311: val_loss -0.7501 +2024-11-21 19:16:36.149467: Pseudo dice [0.8295] +2024-11-21 19:16:36.149563: Epoch time: 18.58 s +2024-11-21 19:16:37.010386: +2024-11-21 19:16:37.010583: Epoch 1540 +2024-11-21 19:16:37.010703: Current learning rate: 0.00825 +2024-11-21 19:16:56.092806: train_loss -0.7514 +2024-11-21 19:16:56.098748: val_loss -0.7572 +2024-11-21 19:16:56.098884: Pseudo dice [0.8519] +2024-11-21 19:16:56.098993: Epoch time: 19.08 s +2024-11-21 19:16:57.014179: +2024-11-21 19:16:57.014422: Epoch 1541 +2024-11-21 19:16:57.014550: Current learning rate: 0.00825 +2024-11-21 19:17:16.331122: train_loss -0.7668 +2024-11-21 19:17:16.336797: val_loss -0.7626 +2024-11-21 19:17:16.336941: Pseudo dice [0.8445] +2024-11-21 19:17:16.337099: Epoch time: 19.32 s +2024-11-21 19:17:17.627009: +2024-11-21 19:17:17.627480: Epoch 1542 +2024-11-21 19:17:17.627601: Current learning rate: 0.00825 +2024-11-21 19:17:36.033221: train_loss -0.7717 +2024-11-21 19:17:36.039699: val_loss -0.7505 +2024-11-21 19:17:36.039843: Pseudo dice [0.8438] +2024-11-21 19:17:36.039941: Epoch time: 18.41 s +2024-11-21 19:17:36.903585: +2024-11-21 19:17:36.903802: Epoch 1543 +2024-11-21 19:17:36.903920: Current learning rate: 0.00825 +2024-11-21 19:17:55.742746: train_loss -0.7675 +2024-11-21 19:17:55.756433: val_loss -0.7688 +2024-11-21 19:17:55.756585: Pseudo dice [0.8402] +2024-11-21 19:17:55.756691: Epoch time: 18.84 s +2024-11-21 19:17:56.780144: +2024-11-21 19:17:56.780363: Epoch 1544 +2024-11-21 19:17:56.780477: Current learning rate: 0.00824 +2024-11-21 19:18:16.092499: train_loss -0.7657 +2024-11-21 19:18:16.100023: val_loss -0.7333 +2024-11-21 19:18:16.100175: Pseudo dice [0.8421] +2024-11-21 19:18:16.100261: Epoch time: 19.31 s +2024-11-21 19:18:16.934439: +2024-11-21 19:18:16.934688: Epoch 1545 +2024-11-21 19:18:16.934820: Current learning rate: 0.00824 +2024-11-21 19:18:35.901927: train_loss -0.7594 +2024-11-21 19:18:35.909629: val_loss -0.7774 +2024-11-21 19:18:35.909765: Pseudo dice [0.8471] +2024-11-21 19:18:35.909856: Epoch time: 18.97 s +2024-11-21 19:18:36.748166: +2024-11-21 19:18:36.748379: Epoch 1546 +2024-11-21 19:18:36.748502: Current learning rate: 0.00824 +2024-11-21 19:18:55.984436: train_loss -0.7623 +2024-11-21 19:18:55.998947: val_loss -0.7392 +2024-11-21 19:18:55.999092: Pseudo dice [0.8214] +2024-11-21 19:18:55.999183: Epoch time: 19.24 s +2024-11-21 19:18:56.851431: +2024-11-21 19:18:56.851644: Epoch 1547 +2024-11-21 19:18:56.851791: Current learning rate: 0.00824 +2024-11-21 19:19:17.242388: train_loss -0.7596 +2024-11-21 19:19:17.249331: val_loss -0.7567 +2024-11-21 19:19:17.249468: Pseudo dice [0.8503] +2024-11-21 19:19:17.249780: Epoch time: 20.39 s +2024-11-21 19:19:18.094027: +2024-11-21 19:19:18.094248: Epoch 1548 +2024-11-21 19:19:18.094365: Current learning rate: 0.00824 +2024-11-21 19:19:36.604269: train_loss -0.7705 +2024-11-21 19:19:36.609699: val_loss -0.7729 +2024-11-21 19:19:36.609828: Pseudo dice [0.8505] +2024-11-21 19:19:36.609915: Epoch time: 18.51 s +2024-11-21 19:19:37.466098: +2024-11-21 19:19:37.466311: Epoch 1549 +2024-11-21 19:19:37.466444: Current learning rate: 0.00824 +2024-11-21 19:19:57.294002: train_loss -0.7586 +2024-11-21 19:19:57.301113: val_loss -0.7691 +2024-11-21 19:19:57.301274: Pseudo dice [0.8481] +2024-11-21 19:19:57.301395: Epoch time: 19.83 s +2024-11-21 19:19:58.401026: +2024-11-21 19:19:58.401274: Epoch 1550 +2024-11-21 19:19:58.401397: Current learning rate: 0.00824 +2024-11-21 19:20:16.930009: train_loss -0.7682 +2024-11-21 19:20:16.932323: val_loss -0.7361 +2024-11-21 19:20:16.932425: Pseudo dice [0.8409] +2024-11-21 19:20:16.932517: Epoch time: 18.53 s +2024-11-21 19:20:17.761815: +2024-11-21 19:20:17.762019: Epoch 1551 +2024-11-21 19:20:17.762154: Current learning rate: 0.00824 +2024-11-21 19:20:37.474273: train_loss -0.7699 +2024-11-21 19:20:37.480341: val_loss -0.7579 +2024-11-21 19:20:37.480498: Pseudo dice [0.851] +2024-11-21 19:20:37.480590: Epoch time: 19.71 s +2024-11-21 19:20:38.318398: +2024-11-21 19:20:38.318604: Epoch 1552 +2024-11-21 19:20:38.318728: Current learning rate: 0.00824 +2024-11-21 19:20:57.172257: train_loss -0.7602 +2024-11-21 19:20:57.178464: val_loss -0.7484 +2024-11-21 19:20:57.178618: Pseudo dice [0.8251] +2024-11-21 19:20:57.178729: Epoch time: 18.85 s +2024-11-21 19:20:58.423382: +2024-11-21 19:20:58.423641: Epoch 1553 +2024-11-21 19:20:58.423773: Current learning rate: 0.00823 +2024-11-21 19:21:17.558440: train_loss -0.7651 +2024-11-21 19:21:17.567903: val_loss -0.7661 +2024-11-21 19:21:17.568048: Pseudo dice [0.8533] +2024-11-21 19:21:17.568170: Epoch time: 19.14 s +2024-11-21 19:21:18.417398: +2024-11-21 19:21:18.417634: Epoch 1554 +2024-11-21 19:21:18.417757: Current learning rate: 0.00823 +2024-11-21 19:21:37.422465: train_loss -0.7622 +2024-11-21 19:21:37.425398: val_loss -0.7565 +2024-11-21 19:21:37.425493: Pseudo dice [0.8407] +2024-11-21 19:21:37.425592: Epoch time: 19.01 s +2024-11-21 19:21:38.259274: +2024-11-21 19:21:38.259487: Epoch 1555 +2024-11-21 19:21:38.259603: Current learning rate: 0.00823 +2024-11-21 19:21:56.850638: train_loss -0.7636 +2024-11-21 19:21:56.853232: val_loss -0.7484 +2024-11-21 19:21:56.853334: Pseudo dice [0.8232] +2024-11-21 19:21:56.853422: Epoch time: 18.59 s +2024-11-21 19:21:57.692900: +2024-11-21 19:21:57.693129: Epoch 1556 +2024-11-21 19:21:57.693251: Current learning rate: 0.00823 +2024-11-21 19:22:17.392313: train_loss -0.7589 +2024-11-21 19:22:17.395012: val_loss -0.7533 +2024-11-21 19:22:17.395145: Pseudo dice [0.8404] +2024-11-21 19:22:17.395247: Epoch time: 19.7 s +2024-11-21 19:22:18.260993: +2024-11-21 19:22:18.261238: Epoch 1557 +2024-11-21 19:22:18.261356: Current learning rate: 0.00823 +2024-11-21 19:22:36.446982: train_loss -0.7685 +2024-11-21 19:22:36.450329: val_loss -0.7631 +2024-11-21 19:22:36.450475: Pseudo dice [0.8499] +2024-11-21 19:22:36.450570: Epoch time: 18.19 s +2024-11-21 19:22:37.285211: +2024-11-21 19:22:37.285423: Epoch 1558 +2024-11-21 19:22:37.285559: Current learning rate: 0.00823 +2024-11-21 19:22:56.447986: train_loss -0.7644 +2024-11-21 19:22:56.454199: val_loss -0.7658 +2024-11-21 19:22:56.454316: Pseudo dice [0.8487] +2024-11-21 19:22:56.454421: Epoch time: 19.16 s +2024-11-21 19:22:57.672219: +2024-11-21 19:22:57.672467: Epoch 1559 +2024-11-21 19:22:57.672602: Current learning rate: 0.00823 +2024-11-21 19:23:17.933888: train_loss -0.7831 +2024-11-21 19:23:17.941601: val_loss -0.7559 +2024-11-21 19:23:17.941754: Pseudo dice [0.8569] +2024-11-21 19:23:17.941842: Epoch time: 20.26 s +2024-11-21 19:23:18.772147: +2024-11-21 19:23:18.772376: Epoch 1560 +2024-11-21 19:23:18.772506: Current learning rate: 0.00823 +2024-11-21 19:23:38.457101: train_loss -0.7752 +2024-11-21 19:23:38.466892: val_loss -0.7535 +2024-11-21 19:23:38.467041: Pseudo dice [0.8345] +2024-11-21 19:23:38.467146: Epoch time: 19.69 s +2024-11-21 19:23:39.342042: +2024-11-21 19:23:39.342282: Epoch 1561 +2024-11-21 19:23:39.342402: Current learning rate: 0.00823 +2024-11-21 19:23:59.368713: train_loss -0.7737 +2024-11-21 19:23:59.373182: val_loss -0.7671 +2024-11-21 19:23:59.373323: Pseudo dice [0.8362] +2024-11-21 19:23:59.373426: Epoch time: 20.02 s +2024-11-21 19:24:00.409373: +2024-11-21 19:24:00.409576: Epoch 1562 +2024-11-21 19:24:00.409693: Current learning rate: 0.00822 +2024-11-21 19:24:20.159174: train_loss -0.7563 +2024-11-21 19:24:20.167807: val_loss -0.7674 +2024-11-21 19:24:20.167933: Pseudo dice [0.8487] +2024-11-21 19:24:20.168032: Epoch time: 19.75 s +2024-11-21 19:24:21.200204: +2024-11-21 19:24:21.200426: Epoch 1563 +2024-11-21 19:24:21.200540: Current learning rate: 0.00822 +2024-11-21 19:24:40.838531: train_loss -0.7632 +2024-11-21 19:24:40.850483: val_loss -0.7534 +2024-11-21 19:24:40.850636: Pseudo dice [0.8428] +2024-11-21 19:24:40.850723: Epoch time: 19.64 s +2024-11-21 19:24:42.079743: +2024-11-21 19:24:42.079969: Epoch 1564 +2024-11-21 19:24:42.080104: Current learning rate: 0.00822 +2024-11-21 19:25:01.032106: train_loss -0.7687 +2024-11-21 19:25:01.035546: val_loss -0.7715 +2024-11-21 19:25:01.035979: Pseudo dice [0.8404] +2024-11-21 19:25:01.036089: Epoch time: 18.95 s +2024-11-21 19:25:01.871301: +2024-11-21 19:25:01.871525: Epoch 1565 +2024-11-21 19:25:01.871646: Current learning rate: 0.00822 +2024-11-21 19:25:20.915633: train_loss -0.7619 +2024-11-21 19:25:20.937830: val_loss -0.7906 +2024-11-21 19:25:20.937953: Pseudo dice [0.8653] +2024-11-21 19:25:20.938056: Epoch time: 19.05 s +2024-11-21 19:25:22.114986: +2024-11-21 19:25:22.115257: Epoch 1566 +2024-11-21 19:25:22.115396: Current learning rate: 0.00822 +2024-11-21 19:25:41.502069: train_loss -0.7595 +2024-11-21 19:25:41.508192: val_loss -0.7533 +2024-11-21 19:25:41.508360: Pseudo dice [0.835] +2024-11-21 19:25:41.508528: Epoch time: 19.39 s +2024-11-21 19:25:42.488054: +2024-11-21 19:25:42.488277: Epoch 1567 +2024-11-21 19:25:42.488395: Current learning rate: 0.00822 +2024-11-21 19:26:01.788745: train_loss -0.7642 +2024-11-21 19:26:01.800626: val_loss -0.7749 +2024-11-21 19:26:01.800767: Pseudo dice [0.8487] +2024-11-21 19:26:01.800864: Epoch time: 19.3 s +2024-11-21 19:26:02.643859: +2024-11-21 19:26:02.644084: Epoch 1568 +2024-11-21 19:26:02.644223: Current learning rate: 0.00822 +2024-11-21 19:26:20.430232: train_loss -0.7686 +2024-11-21 19:26:20.437418: val_loss -0.7491 +2024-11-21 19:26:20.437546: Pseudo dice [0.8494] +2024-11-21 19:26:20.437626: Epoch time: 17.79 s +2024-11-21 19:26:21.586672: +2024-11-21 19:26:21.586884: Epoch 1569 +2024-11-21 19:26:21.587014: Current learning rate: 0.00822 +2024-11-21 19:26:40.760151: train_loss -0.7506 +2024-11-21 19:26:40.762990: val_loss -0.773 +2024-11-21 19:26:40.763105: Pseudo dice [0.845] +2024-11-21 19:26:40.763182: Epoch time: 19.17 s +2024-11-21 19:26:41.601963: +2024-11-21 19:26:41.602193: Epoch 1570 +2024-11-21 19:26:41.602310: Current learning rate: 0.00822 +2024-11-21 19:27:01.897264: train_loss -0.7483 +2024-11-21 19:27:01.912222: val_loss -0.7538 +2024-11-21 19:27:01.912390: Pseudo dice [0.8322] +2024-11-21 19:27:01.912495: Epoch time: 20.3 s +2024-11-21 19:27:02.891229: +2024-11-21 19:27:02.891477: Epoch 1571 +2024-11-21 19:27:02.891616: Current learning rate: 0.00821 +2024-11-21 19:27:22.097924: train_loss -0.7706 +2024-11-21 19:27:22.109984: val_loss -0.7672 +2024-11-21 19:27:22.110143: Pseudo dice [0.8385] +2024-11-21 19:27:22.110234: Epoch time: 19.21 s +2024-11-21 19:27:23.077189: +2024-11-21 19:27:23.077392: Epoch 1572 +2024-11-21 19:27:23.077517: Current learning rate: 0.00821 +2024-11-21 19:27:41.556045: train_loss -0.7681 +2024-11-21 19:27:41.564470: val_loss -0.76 +2024-11-21 19:27:41.564690: Pseudo dice [0.8502] +2024-11-21 19:27:41.564794: Epoch time: 18.48 s +2024-11-21 19:27:42.631119: +2024-11-21 19:27:42.631348: Epoch 1573 +2024-11-21 19:27:42.631483: Current learning rate: 0.00821 +2024-11-21 19:28:02.535051: train_loss -0.7743 +2024-11-21 19:28:02.541543: val_loss -0.7572 +2024-11-21 19:28:02.541692: Pseudo dice [0.8447] +2024-11-21 19:28:02.541790: Epoch time: 19.9 s +2024-11-21 19:28:03.418712: +2024-11-21 19:28:03.418949: Epoch 1574 +2024-11-21 19:28:03.419072: Current learning rate: 0.00821 +2024-11-21 19:28:22.523141: train_loss -0.7662 +2024-11-21 19:28:22.525647: val_loss -0.7605 +2024-11-21 19:28:22.525742: Pseudo dice [0.8426] +2024-11-21 19:28:22.525819: Epoch time: 19.11 s +2024-11-21 19:28:23.740544: +2024-11-21 19:28:23.740799: Epoch 1575 +2024-11-21 19:28:23.740911: Current learning rate: 0.00821 +2024-11-21 19:28:43.620440: train_loss -0.7636 +2024-11-21 19:28:43.623643: val_loss -0.7456 +2024-11-21 19:28:43.623759: Pseudo dice [0.8437] +2024-11-21 19:28:43.623849: Epoch time: 19.88 s +2024-11-21 19:28:44.453079: +2024-11-21 19:28:44.453319: Epoch 1576 +2024-11-21 19:28:44.453441: Current learning rate: 0.00821 +2024-11-21 19:29:02.552104: train_loss -0.7537 +2024-11-21 19:29:02.558191: val_loss -0.7648 +2024-11-21 19:29:02.558324: Pseudo dice [0.8423] +2024-11-21 19:29:02.558413: Epoch time: 18.1 s +2024-11-21 19:29:03.489412: +2024-11-21 19:29:03.489633: Epoch 1577 +2024-11-21 19:29:03.489755: Current learning rate: 0.00821 +2024-11-21 19:29:22.500778: train_loss -0.7713 +2024-11-21 19:29:22.514769: val_loss -0.7623 +2024-11-21 19:29:22.514915: Pseudo dice [0.857] +2024-11-21 19:29:22.514996: Epoch time: 19.01 s +2024-11-21 19:29:23.365372: +2024-11-21 19:29:23.365588: Epoch 1578 +2024-11-21 19:29:23.365710: Current learning rate: 0.00821 +2024-11-21 19:29:41.774404: train_loss -0.7646 +2024-11-21 19:29:41.780659: val_loss -0.7403 +2024-11-21 19:29:41.780811: Pseudo dice [0.827] +2024-11-21 19:29:41.780912: Epoch time: 18.41 s +2024-11-21 19:29:42.633875: +2024-11-21 19:29:42.634126: Epoch 1579 +2024-11-21 19:29:42.634241: Current learning rate: 0.0082 +2024-11-21 19:30:02.148314: train_loss -0.7624 +2024-11-21 19:30:02.157272: val_loss -0.7467 +2024-11-21 19:30:02.157410: Pseudo dice [0.8455] +2024-11-21 19:30:02.157569: Epoch time: 19.52 s +2024-11-21 19:30:03.005802: +2024-11-21 19:30:03.006037: Epoch 1580 +2024-11-21 19:30:03.006177: Current learning rate: 0.0082 +2024-11-21 19:30:22.581603: train_loss -0.7589 +2024-11-21 19:30:22.588071: val_loss -0.7721 +2024-11-21 19:30:22.588198: Pseudo dice [0.8376] +2024-11-21 19:30:22.588297: Epoch time: 19.58 s +2024-11-21 19:30:23.581960: +2024-11-21 19:30:23.582166: Epoch 1581 +2024-11-21 19:30:23.582291: Current learning rate: 0.0082 +2024-11-21 19:30:43.816687: train_loss -0.758 +2024-11-21 19:30:43.824699: val_loss -0.7456 +2024-11-21 19:30:43.824861: Pseudo dice [0.8441] +2024-11-21 19:30:43.824953: Epoch time: 20.24 s +2024-11-21 19:30:44.655367: +2024-11-21 19:30:44.655569: Epoch 1582 +2024-11-21 19:30:44.655686: Current learning rate: 0.0082 +2024-11-21 19:31:03.778715: train_loss -0.7613 +2024-11-21 19:31:03.788638: val_loss -0.7571 +2024-11-21 19:31:03.788770: Pseudo dice [0.8512] +2024-11-21 19:31:03.788861: Epoch time: 19.12 s +2024-11-21 19:31:05.012161: +2024-11-21 19:31:05.012402: Epoch 1583 +2024-11-21 19:31:05.012529: Current learning rate: 0.0082 +2024-11-21 19:31:23.634995: train_loss -0.7665 +2024-11-21 19:31:23.637235: val_loss -0.7647 +2024-11-21 19:31:23.637346: Pseudo dice [0.8369] +2024-11-21 19:31:23.637464: Epoch time: 18.62 s +2024-11-21 19:31:24.468593: +2024-11-21 19:31:24.468795: Epoch 1584 +2024-11-21 19:31:24.468919: Current learning rate: 0.0082 +2024-11-21 19:31:43.625656: train_loss -0.7604 +2024-11-21 19:31:43.630769: val_loss -0.7596 +2024-11-21 19:31:43.630964: Pseudo dice [0.8437] +2024-11-21 19:31:43.631076: Epoch time: 19.16 s +2024-11-21 19:31:44.575566: +2024-11-21 19:31:44.575761: Epoch 1585 +2024-11-21 19:31:44.575876: Current learning rate: 0.0082 +2024-11-21 19:32:03.315530: train_loss -0.7385 +2024-11-21 19:32:03.318501: val_loss -0.7393 +2024-11-21 19:32:03.318632: Pseudo dice [0.8377] +2024-11-21 19:32:03.318721: Epoch time: 18.74 s +2024-11-21 19:32:04.557838: +2024-11-21 19:32:04.558054: Epoch 1586 +2024-11-21 19:32:04.558186: Current learning rate: 0.0082 +2024-11-21 19:32:23.668859: train_loss -0.7401 +2024-11-21 19:32:23.672397: val_loss -0.748 +2024-11-21 19:32:23.672500: Pseudo dice [0.8386] +2024-11-21 19:32:23.672610: Epoch time: 19.11 s +2024-11-21 19:32:24.508178: +2024-11-21 19:32:24.508412: Epoch 1587 +2024-11-21 19:32:24.508529: Current learning rate: 0.0082 +2024-11-21 19:32:44.588130: train_loss -0.7462 +2024-11-21 19:32:44.591257: val_loss -0.7519 +2024-11-21 19:32:44.591407: Pseudo dice [0.844] +2024-11-21 19:32:44.591509: Epoch time: 20.08 s +2024-11-21 19:32:45.463178: +2024-11-21 19:32:45.463398: Epoch 1588 +2024-11-21 19:32:45.463515: Current learning rate: 0.00819 +2024-11-21 19:33:05.923368: train_loss -0.7606 +2024-11-21 19:33:05.928684: val_loss -0.7671 +2024-11-21 19:33:05.928842: Pseudo dice [0.861] +2024-11-21 19:33:05.928944: Epoch time: 20.46 s +2024-11-21 19:33:07.046758: +2024-11-21 19:33:07.046984: Epoch 1589 +2024-11-21 19:33:07.047105: Current learning rate: 0.00819 +2024-11-21 19:33:26.456680: train_loss -0.7628 +2024-11-21 19:33:26.466403: val_loss -0.7409 +2024-11-21 19:33:26.466564: Pseudo dice [0.8393] +2024-11-21 19:33:26.466660: Epoch time: 19.41 s +2024-11-21 19:33:27.315420: +2024-11-21 19:33:27.315666: Epoch 1590 +2024-11-21 19:33:27.315782: Current learning rate: 0.00819 +2024-11-21 19:33:47.447163: train_loss -0.7613 +2024-11-21 19:33:47.455911: val_loss -0.7728 +2024-11-21 19:33:47.456068: Pseudo dice [0.8483] +2024-11-21 19:33:47.456172: Epoch time: 20.13 s +2024-11-21 19:33:48.355124: +2024-11-21 19:33:48.355339: Epoch 1591 +2024-11-21 19:33:48.355476: Current learning rate: 0.00819 +2024-11-21 19:34:06.888958: train_loss -0.7604 +2024-11-21 19:34:06.897782: val_loss -0.7135 +2024-11-21 19:34:06.897986: Pseudo dice [0.8355] +2024-11-21 19:34:06.898079: Epoch time: 18.53 s +2024-11-21 19:34:07.886267: +2024-11-21 19:34:07.886966: Epoch 1592 +2024-11-21 19:34:07.887105: Current learning rate: 0.00819 +2024-11-21 19:34:27.032162: train_loss -0.7728 +2024-11-21 19:34:27.035953: val_loss -0.7627 +2024-11-21 19:34:27.036083: Pseudo dice [0.8437] +2024-11-21 19:34:27.036184: Epoch time: 19.15 s +2024-11-21 19:34:27.874000: +2024-11-21 19:34:27.874242: Epoch 1593 +2024-11-21 19:34:27.874358: Current learning rate: 0.00819 +2024-11-21 19:34:47.986972: train_loss -0.7554 +2024-11-21 19:34:47.991449: val_loss -0.7419 +2024-11-21 19:34:47.991571: Pseudo dice [0.8429] +2024-11-21 19:34:47.991664: Epoch time: 20.11 s +2024-11-21 19:34:48.821940: +2024-11-21 19:34:48.822155: Epoch 1594 +2024-11-21 19:34:48.822283: Current learning rate: 0.00819 +2024-11-21 19:35:07.722412: train_loss -0.7454 +2024-11-21 19:35:07.729453: val_loss -0.7676 +2024-11-21 19:35:07.732679: Pseudo dice [0.8398] +2024-11-21 19:35:07.732794: Epoch time: 18.9 s +2024-11-21 19:35:08.602579: +2024-11-21 19:35:08.602802: Epoch 1595 +2024-11-21 19:35:08.602936: Current learning rate: 0.00819 +2024-11-21 19:35:27.517508: train_loss -0.7556 +2024-11-21 19:35:27.526856: val_loss -0.756 +2024-11-21 19:35:27.527026: Pseudo dice [0.835] +2024-11-21 19:35:27.527137: Epoch time: 18.92 s +2024-11-21 19:35:28.359509: +2024-11-21 19:35:28.359724: Epoch 1596 +2024-11-21 19:35:28.359845: Current learning rate: 0.00819 +2024-11-21 19:35:47.014197: train_loss -0.7679 +2024-11-21 19:35:47.020870: val_loss -0.7432 +2024-11-21 19:35:47.021010: Pseudo dice [0.8321] +2024-11-21 19:35:47.021109: Epoch time: 18.66 s +2024-11-21 19:35:48.286478: +2024-11-21 19:35:48.286680: Epoch 1597 +2024-11-21 19:35:48.286820: Current learning rate: 0.00818 +2024-11-21 19:36:07.043384: train_loss -0.7658 +2024-11-21 19:36:07.046024: val_loss -0.7738 +2024-11-21 19:36:07.046160: Pseudo dice [0.848] +2024-11-21 19:36:07.046252: Epoch time: 18.76 s +2024-11-21 19:36:08.153816: +2024-11-21 19:36:08.154053: Epoch 1598 +2024-11-21 19:36:08.154198: Current learning rate: 0.00818 +2024-11-21 19:36:27.093081: train_loss -0.7556 +2024-11-21 19:36:27.101264: val_loss -0.7635 +2024-11-21 19:36:27.134839: Pseudo dice [0.8453] +2024-11-21 19:36:27.135005: Epoch time: 18.94 s +2024-11-21 19:36:28.023637: +2024-11-21 19:36:28.023875: Epoch 1599 +2024-11-21 19:36:28.024009: Current learning rate: 0.00818 +2024-11-21 19:36:47.754908: train_loss -0.7606 +2024-11-21 19:36:47.762142: val_loss -0.757 +2024-11-21 19:36:47.762265: Pseudo dice [0.8517] +2024-11-21 19:36:47.762373: Epoch time: 19.73 s +2024-11-21 19:36:49.114879: +2024-11-21 19:36:49.115096: Epoch 1600 +2024-11-21 19:36:49.115209: Current learning rate: 0.00818 +2024-11-21 19:37:09.707812: train_loss -0.7577 +2024-11-21 19:37:09.712423: val_loss -0.7629 +2024-11-21 19:37:09.712585: Pseudo dice [0.8577] +2024-11-21 19:37:09.712695: Epoch time: 20.59 s +2024-11-21 19:37:10.750764: +2024-11-21 19:37:10.750977: Epoch 1601 +2024-11-21 19:37:10.751099: Current learning rate: 0.00818 +2024-11-21 19:37:30.050062: train_loss -0.7746 +2024-11-21 19:37:30.058081: val_loss -0.7596 +2024-11-21 19:37:30.058228: Pseudo dice [0.8388] +2024-11-21 19:37:30.058322: Epoch time: 19.3 s +2024-11-21 19:37:30.924783: +2024-11-21 19:37:30.925034: Epoch 1602 +2024-11-21 19:37:30.925155: Current learning rate: 0.00818 +2024-11-21 19:37:48.735828: train_loss -0.7624 +2024-11-21 19:37:48.743941: val_loss -0.7545 +2024-11-21 19:37:48.744092: Pseudo dice [0.8506] +2024-11-21 19:37:48.744181: Epoch time: 17.81 s +2024-11-21 19:37:49.744134: +2024-11-21 19:37:49.744324: Epoch 1603 +2024-11-21 19:37:49.744435: Current learning rate: 0.00818 +2024-11-21 19:38:08.674917: train_loss -0.7561 +2024-11-21 19:38:08.681780: val_loss -0.7461 +2024-11-21 19:38:08.681926: Pseudo dice [0.837] +2024-11-21 19:38:08.682029: Epoch time: 18.93 s +2024-11-21 19:38:09.516126: +2024-11-21 19:38:09.516371: Epoch 1604 +2024-11-21 19:38:09.516497: Current learning rate: 0.00818 +2024-11-21 19:38:29.062901: train_loss -0.7527 +2024-11-21 19:38:29.068998: val_loss -0.7568 +2024-11-21 19:38:29.069144: Pseudo dice [0.8493] +2024-11-21 19:38:29.069251: Epoch time: 19.55 s +2024-11-21 19:38:29.932440: +2024-11-21 19:38:29.932662: Epoch 1605 +2024-11-21 19:38:29.932774: Current learning rate: 0.00817 +2024-11-21 19:38:49.535303: train_loss -0.7583 +2024-11-21 19:38:49.541912: val_loss -0.7553 +2024-11-21 19:38:49.542037: Pseudo dice [0.8355] +2024-11-21 19:38:49.542198: Epoch time: 19.6 s +2024-11-21 19:38:50.408395: +2024-11-21 19:38:50.408605: Epoch 1606 +2024-11-21 19:38:50.408744: Current learning rate: 0.00817 +2024-11-21 19:39:09.110149: train_loss -0.7576 +2024-11-21 19:39:09.122566: val_loss -0.7652 +2024-11-21 19:39:09.122715: Pseudo dice [0.8293] +2024-11-21 19:39:09.122810: Epoch time: 18.7 s +2024-11-21 19:39:09.969231: +2024-11-21 19:39:09.969458: Epoch 1607 +2024-11-21 19:39:09.969574: Current learning rate: 0.00817 +2024-11-21 19:39:28.452999: train_loss -0.7528 +2024-11-21 19:39:28.461690: val_loss -0.7862 +2024-11-21 19:39:28.461818: Pseudo dice [0.8474] +2024-11-21 19:39:28.461911: Epoch time: 18.48 s +2024-11-21 19:39:29.905696: +2024-11-21 19:39:29.905968: Epoch 1608 +2024-11-21 19:39:29.906084: Current learning rate: 0.00817 +2024-11-21 19:39:49.376393: train_loss -0.7728 +2024-11-21 19:39:49.385941: val_loss -0.7607 +2024-11-21 19:39:49.386102: Pseudo dice [0.8281] +2024-11-21 19:39:49.386215: Epoch time: 19.47 s +2024-11-21 19:39:50.344212: +2024-11-21 19:39:50.344425: Epoch 1609 +2024-11-21 19:39:50.344548: Current learning rate: 0.00817 +2024-11-21 19:40:09.194672: train_loss -0.7717 +2024-11-21 19:40:09.203897: val_loss -0.7551 +2024-11-21 19:40:09.204016: Pseudo dice [0.8509] +2024-11-21 19:40:09.204115: Epoch time: 18.85 s +2024-11-21 19:40:10.049454: +2024-11-21 19:40:10.049692: Epoch 1610 +2024-11-21 19:40:10.049831: Current learning rate: 0.00817 +2024-11-21 19:40:30.799395: train_loss -0.7726 +2024-11-21 19:40:30.801867: val_loss -0.7484 +2024-11-21 19:40:30.802010: Pseudo dice [0.8416] +2024-11-21 19:40:30.802149: Epoch time: 20.75 s +2024-11-21 19:40:31.641902: +2024-11-21 19:40:31.642119: Epoch 1611 +2024-11-21 19:40:31.642244: Current learning rate: 0.00817 +2024-11-21 19:40:51.255269: train_loss -0.7679 +2024-11-21 19:40:51.268237: val_loss -0.7465 +2024-11-21 19:40:51.268410: Pseudo dice [0.8389] +2024-11-21 19:40:51.268574: Epoch time: 19.61 s +2024-11-21 19:40:52.319478: +2024-11-21 19:40:52.319685: Epoch 1612 +2024-11-21 19:40:52.319823: Current learning rate: 0.00817 +2024-11-21 19:41:11.380181: train_loss -0.7646 +2024-11-21 19:41:11.386291: val_loss -0.7731 +2024-11-21 19:41:11.386435: Pseudo dice [0.8516] +2024-11-21 19:41:11.386543: Epoch time: 19.06 s +2024-11-21 19:41:12.221066: +2024-11-21 19:41:12.221304: Epoch 1613 +2024-11-21 19:41:12.221440: Current learning rate: 0.00817 +2024-11-21 19:41:30.870857: train_loss -0.7535 +2024-11-21 19:41:30.895468: val_loss -0.7442 +2024-11-21 19:41:30.895643: Pseudo dice [0.835] +2024-11-21 19:41:30.895745: Epoch time: 18.65 s +2024-11-21 19:41:31.736911: +2024-11-21 19:41:31.737111: Epoch 1614 +2024-11-21 19:41:31.737239: Current learning rate: 0.00816 +2024-11-21 19:41:50.352781: train_loss -0.7636 +2024-11-21 19:41:50.355940: val_loss -0.7484 +2024-11-21 19:41:50.356081: Pseudo dice [0.8527] +2024-11-21 19:41:50.356181: Epoch time: 18.62 s +2024-11-21 19:41:51.292279: +2024-11-21 19:41:51.292520: Epoch 1615 +2024-11-21 19:41:51.292714: Current learning rate: 0.00816 +2024-11-21 19:42:09.429759: train_loss -0.7585 +2024-11-21 19:42:09.439817: val_loss -0.777 +2024-11-21 19:42:09.439975: Pseudo dice [0.8577] +2024-11-21 19:42:09.440088: Epoch time: 18.14 s +2024-11-21 19:42:10.271840: +2024-11-21 19:42:10.272034: Epoch 1616 +2024-11-21 19:42:10.272155: Current learning rate: 0.00816 +2024-11-21 19:42:29.192806: train_loss -0.777 +2024-11-21 19:42:29.198865: val_loss -0.7569 +2024-11-21 19:42:29.199013: Pseudo dice [0.839] +2024-11-21 19:42:29.199150: Epoch time: 18.92 s +2024-11-21 19:42:30.035801: +2024-11-21 19:42:30.035994: Epoch 1617 +2024-11-21 19:42:30.036112: Current learning rate: 0.00816 +2024-11-21 19:42:48.456556: train_loss -0.7673 +2024-11-21 19:42:48.461786: val_loss -0.7688 +2024-11-21 19:42:48.461928: Pseudo dice [0.8379] +2024-11-21 19:42:48.462023: Epoch time: 18.42 s +2024-11-21 19:42:49.302958: +2024-11-21 19:42:49.303270: Epoch 1618 +2024-11-21 19:42:49.303392: Current learning rate: 0.00816 +2024-11-21 19:43:08.544834: train_loss -0.7607 +2024-11-21 19:43:08.550033: val_loss -0.7614 +2024-11-21 19:43:08.550183: Pseudo dice [0.8435] +2024-11-21 19:43:08.550280: Epoch time: 19.24 s +2024-11-21 19:43:10.003690: +2024-11-21 19:43:10.003918: Epoch 1619 +2024-11-21 19:43:10.004046: Current learning rate: 0.00816 +2024-11-21 19:43:28.534638: train_loss -0.7632 +2024-11-21 19:43:28.537372: val_loss -0.7552 +2024-11-21 19:43:28.537473: Pseudo dice [0.8406] +2024-11-21 19:43:28.537569: Epoch time: 18.53 s +2024-11-21 19:43:29.367126: +2024-11-21 19:43:29.367356: Epoch 1620 +2024-11-21 19:43:29.367496: Current learning rate: 0.00816 +2024-11-21 19:43:49.255326: train_loss -0.7519 +2024-11-21 19:43:49.261473: val_loss -0.7542 +2024-11-21 19:43:49.261599: Pseudo dice [0.8533] +2024-11-21 19:43:49.261707: Epoch time: 19.89 s +2024-11-21 19:43:50.148336: +2024-11-21 19:43:50.148570: Epoch 1621 +2024-11-21 19:43:50.148701: Current learning rate: 0.00816 +2024-11-21 19:44:09.261792: train_loss -0.7594 +2024-11-21 19:44:09.267442: val_loss -0.7639 +2024-11-21 19:44:09.267576: Pseudo dice [0.8552] +2024-11-21 19:44:09.267672: Epoch time: 19.11 s +2024-11-21 19:44:10.118518: +2024-11-21 19:44:10.118762: Epoch 1622 +2024-11-21 19:44:10.118898: Current learning rate: 0.00816 +2024-11-21 19:44:29.824992: train_loss -0.7602 +2024-11-21 19:44:29.828350: val_loss -0.7504 +2024-11-21 19:44:29.828471: Pseudo dice [0.8343] +2024-11-21 19:44:29.828587: Epoch time: 19.71 s +2024-11-21 19:44:30.663417: +2024-11-21 19:44:30.663626: Epoch 1623 +2024-11-21 19:44:30.663751: Current learning rate: 0.00815 +2024-11-21 19:44:50.204708: train_loss -0.7584 +2024-11-21 19:44:50.207252: val_loss -0.7365 +2024-11-21 19:44:50.207350: Pseudo dice [0.8394] +2024-11-21 19:44:50.207461: Epoch time: 19.54 s +2024-11-21 19:44:51.037790: +2024-11-21 19:44:51.038237: Epoch 1624 +2024-11-21 19:44:51.038364: Current learning rate: 0.00815 +2024-11-21 19:45:10.118400: train_loss -0.7551 +2024-11-21 19:45:10.125293: val_loss -0.7533 +2024-11-21 19:45:10.125449: Pseudo dice [0.8411] +2024-11-21 19:45:10.125542: Epoch time: 19.08 s +2024-11-21 19:45:10.960653: +2024-11-21 19:45:10.960874: Epoch 1625 +2024-11-21 19:45:10.961005: Current learning rate: 0.00815 +2024-11-21 19:45:29.511339: train_loss -0.7539 +2024-11-21 19:45:29.536130: val_loss -0.7398 +2024-11-21 19:45:29.536264: Pseudo dice [0.838] +2024-11-21 19:45:29.536356: Epoch time: 18.55 s +2024-11-21 19:45:30.470128: +2024-11-21 19:45:30.470347: Epoch 1626 +2024-11-21 19:45:30.470482: Current learning rate: 0.00815 +2024-11-21 19:45:50.081572: train_loss -0.7589 +2024-11-21 19:45:50.085665: val_loss -0.773 +2024-11-21 19:45:50.085823: Pseudo dice [0.8532] +2024-11-21 19:45:50.085956: Epoch time: 19.61 s +2024-11-21 19:45:51.011222: +2024-11-21 19:45:51.011445: Epoch 1627 +2024-11-21 19:45:51.011556: Current learning rate: 0.00815 +2024-11-21 19:46:11.120130: train_loss -0.7703 +2024-11-21 19:46:11.128001: val_loss -0.7627 +2024-11-21 19:46:11.128135: Pseudo dice [0.8485] +2024-11-21 19:46:11.128244: Epoch time: 20.11 s +2024-11-21 19:46:11.979147: +2024-11-21 19:46:11.979354: Epoch 1628 +2024-11-21 19:46:11.979479: Current learning rate: 0.00815 +2024-11-21 19:46:30.442345: train_loss -0.765 +2024-11-21 19:46:30.460103: val_loss -0.7759 +2024-11-21 19:46:30.460249: Pseudo dice [0.8548] +2024-11-21 19:46:30.460346: Epoch time: 18.46 s +2024-11-21 19:46:31.308320: +2024-11-21 19:46:31.308524: Epoch 1629 +2024-11-21 19:46:31.308641: Current learning rate: 0.00815 +2024-11-21 19:46:50.412036: train_loss -0.767 +2024-11-21 19:46:50.418554: val_loss -0.7658 +2024-11-21 19:46:50.418722: Pseudo dice [0.8333] +2024-11-21 19:46:50.418829: Epoch time: 19.1 s +2024-11-21 19:46:51.659159: +2024-11-21 19:46:51.659382: Epoch 1630 +2024-11-21 19:46:51.659516: Current learning rate: 0.00815 +2024-11-21 19:47:11.083160: train_loss -0.754 +2024-11-21 19:47:11.089911: val_loss -0.7373 +2024-11-21 19:47:11.090035: Pseudo dice [0.8411] +2024-11-21 19:47:11.090136: Epoch time: 19.42 s +2024-11-21 19:47:12.026559: +2024-11-21 19:47:12.026774: Epoch 1631 +2024-11-21 19:47:12.026903: Current learning rate: 0.00814 +2024-11-21 19:47:31.477464: train_loss -0.7666 +2024-11-21 19:47:31.483879: val_loss -0.7605 +2024-11-21 19:47:31.484009: Pseudo dice [0.8398] +2024-11-21 19:47:31.484102: Epoch time: 19.45 s +2024-11-21 19:47:32.440786: +2024-11-21 19:47:32.441004: Epoch 1632 +2024-11-21 19:47:32.441136: Current learning rate: 0.00814 +2024-11-21 19:47:51.815880: train_loss -0.7674 +2024-11-21 19:47:51.818648: val_loss -0.7655 +2024-11-21 19:47:51.818738: Pseudo dice [0.8413] +2024-11-21 19:47:51.818835: Epoch time: 19.38 s +2024-11-21 19:47:52.655369: +2024-11-21 19:47:52.655582: Epoch 1633 +2024-11-21 19:47:52.655710: Current learning rate: 0.00814 +2024-11-21 19:48:11.412436: train_loss -0.7491 +2024-11-21 19:48:11.424049: val_loss -0.7271 +2024-11-21 19:48:11.424196: Pseudo dice [0.8344] +2024-11-21 19:48:11.424303: Epoch time: 18.76 s +2024-11-21 19:48:12.326352: +2024-11-21 19:48:12.326583: Epoch 1634 +2024-11-21 19:48:12.326699: Current learning rate: 0.00814 +2024-11-21 19:48:30.201539: train_loss -0.7527 +2024-11-21 19:48:30.204861: val_loss -0.7599 +2024-11-21 19:48:30.204988: Pseudo dice [0.8455] +2024-11-21 19:48:30.205086: Epoch time: 17.88 s +2024-11-21 19:48:31.144700: +2024-11-21 19:48:31.144956: Epoch 1635 +2024-11-21 19:48:31.145092: Current learning rate: 0.00814 +2024-11-21 19:48:50.512601: train_loss -0.7758 +2024-11-21 19:48:50.520742: val_loss -0.7842 +2024-11-21 19:48:50.520907: Pseudo dice [0.8547] +2024-11-21 19:48:50.520993: Epoch time: 19.37 s +2024-11-21 19:48:51.481937: +2024-11-21 19:48:51.482175: Epoch 1636 +2024-11-21 19:48:51.482306: Current learning rate: 0.00814 +2024-11-21 19:49:09.674043: train_loss -0.7718 +2024-11-21 19:49:09.681951: val_loss -0.7634 +2024-11-21 19:49:09.682121: Pseudo dice [0.8428] +2024-11-21 19:49:09.682464: Epoch time: 18.19 s +2024-11-21 19:49:10.543624: +2024-11-21 19:49:10.543865: Epoch 1637 +2024-11-21 19:49:10.543999: Current learning rate: 0.00814 +2024-11-21 19:49:29.892290: train_loss -0.7708 +2024-11-21 19:49:29.899410: val_loss -0.7653 +2024-11-21 19:49:29.899539: Pseudo dice [0.8459] +2024-11-21 19:49:29.899640: Epoch time: 19.35 s +2024-11-21 19:49:30.854501: +2024-11-21 19:49:30.854695: Epoch 1638 +2024-11-21 19:49:30.854820: Current learning rate: 0.00814 +2024-11-21 19:49:49.441010: train_loss -0.7673 +2024-11-21 19:49:49.443968: val_loss -0.7487 +2024-11-21 19:49:49.444103: Pseudo dice [0.8315] +2024-11-21 19:49:49.444218: Epoch time: 18.59 s +2024-11-21 19:49:50.380875: +2024-11-21 19:49:50.381099: Epoch 1639 +2024-11-21 19:49:50.381217: Current learning rate: 0.00814 +2024-11-21 19:50:08.836609: train_loss -0.7603 +2024-11-21 19:50:08.846176: val_loss -0.7389 +2024-11-21 19:50:08.846333: Pseudo dice [0.8342] +2024-11-21 19:50:08.846439: Epoch time: 18.46 s +2024-11-21 19:50:09.848577: +2024-11-21 19:50:09.848807: Epoch 1640 +2024-11-21 19:50:09.848928: Current learning rate: 0.00813 +2024-11-21 19:50:28.309880: train_loss -0.7705 +2024-11-21 19:50:28.320859: val_loss -0.7648 +2024-11-21 19:50:28.321004: Pseudo dice [0.8458] +2024-11-21 19:50:28.321092: Epoch time: 18.46 s +2024-11-21 19:50:29.598848: +2024-11-21 19:50:29.599092: Epoch 1641 +2024-11-21 19:50:29.599206: Current learning rate: 0.00813 +2024-11-21 19:50:48.460409: train_loss -0.7631 +2024-11-21 19:50:48.474587: val_loss -0.7391 +2024-11-21 19:50:48.474714: Pseudo dice [0.8496] +2024-11-21 19:50:48.474812: Epoch time: 18.86 s +2024-11-21 19:50:49.542875: +2024-11-21 19:50:49.543125: Epoch 1642 +2024-11-21 19:50:49.543239: Current learning rate: 0.00813 +2024-11-21 19:51:07.252575: train_loss -0.754 +2024-11-21 19:51:07.266826: val_loss -0.7344 +2024-11-21 19:51:07.266989: Pseudo dice [0.8342] +2024-11-21 19:51:07.267150: Epoch time: 17.71 s +2024-11-21 19:51:08.129926: +2024-11-21 19:51:08.130171: Epoch 1643 +2024-11-21 19:51:08.130297: Current learning rate: 0.00813 +2024-11-21 19:51:28.117111: train_loss -0.7648 +2024-11-21 19:51:28.124083: val_loss -0.7623 +2024-11-21 19:51:28.124237: Pseudo dice [0.8569] +2024-11-21 19:51:28.124339: Epoch time: 19.99 s +2024-11-21 19:51:28.944388: +2024-11-21 19:51:28.944621: Epoch 1644 +2024-11-21 19:51:28.944758: Current learning rate: 0.00813 +2024-11-21 19:51:48.229602: train_loss -0.7657 +2024-11-21 19:51:48.237508: val_loss -0.7666 +2024-11-21 19:51:48.237658: Pseudo dice [0.8412] +2024-11-21 19:51:48.237743: Epoch time: 19.29 s +2024-11-21 19:51:49.151551: +2024-11-21 19:51:49.151805: Epoch 1645 +2024-11-21 19:51:49.151953: Current learning rate: 0.00813 +2024-11-21 19:52:08.551172: train_loss -0.7738 +2024-11-21 19:52:08.557239: val_loss -0.7684 +2024-11-21 19:52:08.557374: Pseudo dice [0.8537] +2024-11-21 19:52:08.557473: Epoch time: 19.4 s +2024-11-21 19:52:09.378030: +2024-11-21 19:52:09.378252: Epoch 1646 +2024-11-21 19:52:09.378371: Current learning rate: 0.00813 +2024-11-21 19:52:28.587112: train_loss -0.767 +2024-11-21 19:52:28.590129: val_loss -0.7702 +2024-11-21 19:52:28.590256: Pseudo dice [0.85] +2024-11-21 19:52:28.590364: Epoch time: 19.21 s +2024-11-21 19:52:29.411929: +2024-11-21 19:52:29.412172: Epoch 1647 +2024-11-21 19:52:29.412290: Current learning rate: 0.00813 +2024-11-21 19:52:48.635171: train_loss -0.7589 +2024-11-21 19:52:48.665957: val_loss -0.763 +2024-11-21 19:52:48.666136: Pseudo dice [0.8507] +2024-11-21 19:52:48.666268: Epoch time: 19.22 s +2024-11-21 19:52:49.680985: +2024-11-21 19:52:49.681189: Epoch 1648 +2024-11-21 19:52:49.681306: Current learning rate: 0.00813 +2024-11-21 19:53:08.185031: train_loss -0.765 +2024-11-21 19:53:08.193098: val_loss -0.7357 +2024-11-21 19:53:08.193227: Pseudo dice [0.8345] +2024-11-21 19:53:08.193340: Epoch time: 18.5 s +2024-11-21 19:53:09.061844: +2024-11-21 19:53:09.062046: Epoch 1649 +2024-11-21 19:53:09.062166: Current learning rate: 0.00812 +2024-11-21 19:53:28.073763: train_loss -0.7621 +2024-11-21 19:53:28.101229: val_loss -0.7452 +2024-11-21 19:53:28.101370: Pseudo dice [0.8474] +2024-11-21 19:53:28.101459: Epoch time: 19.01 s +2024-11-21 19:53:29.245981: +2024-11-21 19:53:29.246227: Epoch 1650 +2024-11-21 19:53:29.246374: Current learning rate: 0.00812 +2024-11-21 19:53:48.357517: train_loss -0.7735 +2024-11-21 19:53:48.371640: val_loss -0.7544 +2024-11-21 19:53:48.371805: Pseudo dice [0.8451] +2024-11-21 19:53:48.371927: Epoch time: 19.11 s +2024-11-21 19:53:49.300778: +2024-11-21 19:53:49.300993: Epoch 1651 +2024-11-21 19:53:49.301113: Current learning rate: 0.00812 +2024-11-21 19:54:08.446721: train_loss -0.7747 +2024-11-21 19:54:08.456781: val_loss -0.7772 +2024-11-21 19:54:08.456956: Pseudo dice [0.8495] +2024-11-21 19:54:08.457070: Epoch time: 19.15 s +2024-11-21 19:54:09.304556: +2024-11-21 19:54:09.304755: Epoch 1652 +2024-11-21 19:54:09.304894: Current learning rate: 0.00812 +2024-11-21 19:54:27.923250: train_loss -0.7698 +2024-11-21 19:54:27.929780: val_loss -0.7653 +2024-11-21 19:54:27.929927: Pseudo dice [0.8389] +2024-11-21 19:54:27.930028: Epoch time: 18.62 s +2024-11-21 19:54:28.906362: +2024-11-21 19:54:28.906629: Epoch 1653 +2024-11-21 19:54:28.906752: Current learning rate: 0.00812 +2024-11-21 19:54:47.648864: train_loss -0.7743 +2024-11-21 19:54:47.666299: val_loss -0.7546 +2024-11-21 19:54:47.666422: Pseudo dice [0.8611] +2024-11-21 19:54:47.666517: Epoch time: 18.74 s +2024-11-21 19:54:48.492489: +2024-11-21 19:54:48.492731: Epoch 1654 +2024-11-21 19:54:48.492855: Current learning rate: 0.00812 +2024-11-21 19:55:07.674278: train_loss -0.7769 +2024-11-21 19:55:07.679219: val_loss -0.764 +2024-11-21 19:55:07.679339: Pseudo dice [0.8394] +2024-11-21 19:55:07.679439: Epoch time: 19.18 s +2024-11-21 19:55:08.748208: +2024-11-21 19:55:08.748420: Epoch 1655 +2024-11-21 19:55:08.748543: Current learning rate: 0.00812 +2024-11-21 19:55:28.930078: train_loss -0.7584 +2024-11-21 19:55:28.936999: val_loss -0.764 +2024-11-21 19:55:28.937151: Pseudo dice [0.8547] +2024-11-21 19:55:28.937252: Epoch time: 20.18 s +2024-11-21 19:55:29.806134: +2024-11-21 19:55:29.806382: Epoch 1656 +2024-11-21 19:55:29.806503: Current learning rate: 0.00812 +2024-11-21 19:55:48.894926: train_loss -0.7625 +2024-11-21 19:55:48.905071: val_loss -0.7829 +2024-11-21 19:55:48.905222: Pseudo dice [0.8489] +2024-11-21 19:55:48.905344: Epoch time: 19.09 s +2024-11-21 19:55:49.870742: +2024-11-21 19:55:49.870942: Epoch 1657 +2024-11-21 19:55:49.871088: Current learning rate: 0.00811 +2024-11-21 19:56:09.170598: train_loss -0.7574 +2024-11-21 19:56:09.190239: val_loss -0.7511 +2024-11-21 19:56:09.190397: Pseudo dice [0.8309] +2024-11-21 19:56:09.190486: Epoch time: 19.3 s +2024-11-21 19:56:10.165389: +2024-11-21 19:56:10.165596: Epoch 1658 +2024-11-21 19:56:10.165715: Current learning rate: 0.00811 +2024-11-21 19:56:28.632001: train_loss -0.7601 +2024-11-21 19:56:28.634367: val_loss -0.7692 +2024-11-21 19:56:28.634479: Pseudo dice [0.8588] +2024-11-21 19:56:28.634574: Epoch time: 18.47 s +2024-11-21 19:56:29.457979: +2024-11-21 19:56:29.458207: Epoch 1659 +2024-11-21 19:56:29.458335: Current learning rate: 0.00811 +2024-11-21 19:56:47.987102: train_loss -0.7729 +2024-11-21 19:56:47.995085: val_loss -0.7555 +2024-11-21 19:56:47.995213: Pseudo dice [0.8537] +2024-11-21 19:56:47.995305: Epoch time: 18.53 s +2024-11-21 19:56:48.924582: +2024-11-21 19:56:48.924772: Epoch 1660 +2024-11-21 19:56:48.924884: Current learning rate: 0.00811 +2024-11-21 19:57:07.593858: train_loss -0.7692 +2024-11-21 19:57:07.596916: val_loss -0.741 +2024-11-21 19:57:07.597047: Pseudo dice [0.8308] +2024-11-21 19:57:07.597177: Epoch time: 18.67 s +2024-11-21 19:57:08.438963: +2024-11-21 19:57:08.439216: Epoch 1661 +2024-11-21 19:57:08.439341: Current learning rate: 0.00811 +2024-11-21 19:57:28.360403: train_loss -0.7615 +2024-11-21 19:57:28.363304: val_loss -0.7629 +2024-11-21 19:57:28.363425: Pseudo dice [0.8394] +2024-11-21 19:57:28.363518: Epoch time: 19.92 s +2024-11-21 19:57:29.208236: +2024-11-21 19:57:29.208471: Epoch 1662 +2024-11-21 19:57:29.208808: Current learning rate: 0.00811 +2024-11-21 19:57:49.404876: train_loss -0.7538 +2024-11-21 19:57:49.410776: val_loss -0.7427 +2024-11-21 19:57:49.410941: Pseudo dice [0.8334] +2024-11-21 19:57:49.411066: Epoch time: 20.2 s +2024-11-21 19:57:50.231354: +2024-11-21 19:57:50.231546: Epoch 1663 +2024-11-21 19:57:50.231670: Current learning rate: 0.00811 +2024-11-21 19:58:09.605768: train_loss -0.7567 +2024-11-21 19:58:09.635280: val_loss -0.7387 +2024-11-21 19:58:09.635428: Pseudo dice [0.8467] +2024-11-21 19:58:09.635515: Epoch time: 19.38 s +2024-11-21 19:58:10.572958: +2024-11-21 19:58:10.573206: Epoch 1664 +2024-11-21 19:58:10.573339: Current learning rate: 0.00811 +2024-11-21 19:58:30.007362: train_loss -0.7509 +2024-11-21 19:58:30.012756: val_loss -0.7593 +2024-11-21 19:58:30.012881: Pseudo dice [0.8376] +2024-11-21 19:58:30.013024: Epoch time: 19.44 s +2024-11-21 19:58:30.843113: +2024-11-21 19:58:30.850016: Epoch 1665 +2024-11-21 19:58:30.850162: Current learning rate: 0.00811 +2024-11-21 19:58:50.208960: train_loss -0.7672 +2024-11-21 19:58:50.216071: val_loss -0.7762 +2024-11-21 19:58:50.216195: Pseudo dice [0.8441] +2024-11-21 19:58:50.216295: Epoch time: 19.37 s +2024-11-21 19:58:51.290301: +2024-11-21 19:58:51.290526: Epoch 1666 +2024-11-21 19:58:51.290640: Current learning rate: 0.0081 +2024-11-21 19:59:09.820596: train_loss -0.7652 +2024-11-21 19:59:09.834705: val_loss -0.7617 +2024-11-21 19:59:09.834849: Pseudo dice [0.8528] +2024-11-21 19:59:09.834939: Epoch time: 18.53 s +2024-11-21 19:59:10.861515: +2024-11-21 19:59:10.861749: Epoch 1667 +2024-11-21 19:59:10.861877: Current learning rate: 0.0081 +2024-11-21 19:59:30.329257: train_loss -0.7649 +2024-11-21 19:59:30.336891: val_loss -0.7535 +2024-11-21 19:59:30.337041: Pseudo dice [0.8417] +2024-11-21 19:59:30.337138: Epoch time: 19.47 s +2024-11-21 19:59:31.272163: +2024-11-21 19:59:31.272410: Epoch 1668 +2024-11-21 19:59:31.272553: Current learning rate: 0.0081 +2024-11-21 19:59:50.764050: train_loss -0.7505 +2024-11-21 19:59:50.774039: val_loss -0.746 +2024-11-21 19:59:50.774268: Pseudo dice [0.8351] +2024-11-21 19:59:50.774361: Epoch time: 19.49 s +2024-11-21 19:59:51.712530: +2024-11-21 19:59:51.712786: Epoch 1669 +2024-11-21 19:59:51.712908: Current learning rate: 0.0081 +2024-11-21 20:00:12.230880: train_loss -0.7308 +2024-11-21 20:00:12.236879: val_loss -0.7121 +2024-11-21 20:00:12.237010: Pseudo dice [0.753] +2024-11-21 20:00:12.237101: Epoch time: 20.52 s +2024-11-21 20:00:13.065931: +2024-11-21 20:00:13.066145: Epoch 1670 +2024-11-21 20:00:13.066277: Current learning rate: 0.0081 +2024-11-21 20:00:32.706784: train_loss -0.7375 +2024-11-21 20:00:32.714510: val_loss -0.7381 +2024-11-21 20:00:32.714702: Pseudo dice [0.8228] +2024-11-21 20:00:32.714811: Epoch time: 19.64 s +2024-11-21 20:00:33.544305: +2024-11-21 20:00:33.544524: Epoch 1671 +2024-11-21 20:00:33.544662: Current learning rate: 0.0081 +2024-11-21 20:00:52.410308: train_loss -0.7437 +2024-11-21 20:00:52.434730: val_loss -0.7195 +2024-11-21 20:00:52.434875: Pseudo dice [0.816] +2024-11-21 20:00:52.434979: Epoch time: 18.87 s +2024-11-21 20:00:53.336742: +2024-11-21 20:00:53.336974: Epoch 1672 +2024-11-21 20:00:53.337094: Current learning rate: 0.0081 +2024-11-21 20:01:12.707228: train_loss -0.7539 +2024-11-21 20:01:12.714460: val_loss -0.7305 +2024-11-21 20:01:12.714605: Pseudo dice [0.8341] +2024-11-21 20:01:12.714700: Epoch time: 19.37 s +2024-11-21 20:01:13.749199: +2024-11-21 20:01:13.749415: Epoch 1673 +2024-11-21 20:01:13.749536: Current learning rate: 0.0081 +2024-11-21 20:01:32.846850: train_loss -0.7419 +2024-11-21 20:01:32.852893: val_loss -0.7526 +2024-11-21 20:01:32.853066: Pseudo dice [0.8351] +2024-11-21 20:01:32.853159: Epoch time: 19.1 s +2024-11-21 20:01:34.050984: +2024-11-21 20:01:34.051193: Epoch 1674 +2024-11-21 20:01:34.051310: Current learning rate: 0.0081 +2024-11-21 20:01:52.946193: train_loss -0.7429 +2024-11-21 20:01:52.958278: val_loss -0.7457 +2024-11-21 20:01:52.958430: Pseudo dice [0.8343] +2024-11-21 20:01:52.958537: Epoch time: 18.9 s +2024-11-21 20:01:53.896322: +2024-11-21 20:01:53.896570: Epoch 1675 +2024-11-21 20:01:53.896693: Current learning rate: 0.00809 +2024-11-21 20:02:13.361902: train_loss -0.7456 +2024-11-21 20:02:13.364641: val_loss -0.7491 +2024-11-21 20:02:13.364786: Pseudo dice [0.8488] +2024-11-21 20:02:13.364907: Epoch time: 19.47 s +2024-11-21 20:02:14.193268: +2024-11-21 20:02:14.193942: Epoch 1676 +2024-11-21 20:02:14.194068: Current learning rate: 0.00809 +2024-11-21 20:02:33.215257: train_loss -0.76 +2024-11-21 20:02:33.236104: val_loss -0.7603 +2024-11-21 20:02:33.236245: Pseudo dice [0.8386] +2024-11-21 20:02:33.236333: Epoch time: 19.02 s +2024-11-21 20:02:34.305387: +2024-11-21 20:02:34.305604: Epoch 1677 +2024-11-21 20:02:34.305735: Current learning rate: 0.00809 +2024-11-21 20:02:55.005384: train_loss -0.7567 +2024-11-21 20:02:55.011349: val_loss -0.7519 +2024-11-21 20:02:55.011499: Pseudo dice [0.8343] +2024-11-21 20:02:55.011581: Epoch time: 20.7 s +2024-11-21 20:02:55.918390: +2024-11-21 20:02:55.918631: Epoch 1678 +2024-11-21 20:02:55.918759: Current learning rate: 0.00809 +2024-11-21 20:03:15.343881: train_loss -0.7561 +2024-11-21 20:03:15.350882: val_loss -0.7489 +2024-11-21 20:03:15.351006: Pseudo dice [0.8396] +2024-11-21 20:03:15.351116: Epoch time: 19.43 s +2024-11-21 20:03:16.278818: +2024-11-21 20:03:16.279077: Epoch 1679 +2024-11-21 20:03:16.279192: Current learning rate: 0.00809 +2024-11-21 20:03:35.975588: train_loss -0.7632 +2024-11-21 20:03:35.982403: val_loss -0.7587 +2024-11-21 20:03:35.982550: Pseudo dice [0.8412] +2024-11-21 20:03:35.982645: Epoch time: 19.7 s +2024-11-21 20:03:36.888774: +2024-11-21 20:03:36.889003: Epoch 1680 +2024-11-21 20:03:36.889130: Current learning rate: 0.00809 +2024-11-21 20:03:55.723433: train_loss -0.7653 +2024-11-21 20:03:55.729503: val_loss -0.7651 +2024-11-21 20:03:55.729626: Pseudo dice [0.8455] +2024-11-21 20:03:55.729722: Epoch time: 18.84 s +2024-11-21 20:03:56.620903: +2024-11-21 20:03:56.621116: Epoch 1681 +2024-11-21 20:03:56.621253: Current learning rate: 0.00809 +2024-11-21 20:04:15.526608: train_loss -0.7744 +2024-11-21 20:04:15.529609: val_loss -0.7349 +2024-11-21 20:04:15.529773: Pseudo dice [0.8443] +2024-11-21 20:04:15.529873: Epoch time: 18.91 s +2024-11-21 20:04:16.361577: +2024-11-21 20:04:16.361781: Epoch 1682 +2024-11-21 20:04:16.361919: Current learning rate: 0.00809 +2024-11-21 20:04:35.847418: train_loss -0.7663 +2024-11-21 20:04:35.855264: val_loss -0.749 +2024-11-21 20:04:35.855413: Pseudo dice [0.8504] +2024-11-21 20:04:35.855525: Epoch time: 19.49 s +2024-11-21 20:04:36.687167: +2024-11-21 20:04:36.687373: Epoch 1683 +2024-11-21 20:04:36.687513: Current learning rate: 0.00808 +2024-11-21 20:04:56.292552: train_loss -0.7737 +2024-11-21 20:04:56.295383: val_loss -0.746 +2024-11-21 20:04:56.295510: Pseudo dice [0.8438] +2024-11-21 20:04:56.295613: Epoch time: 19.61 s +2024-11-21 20:04:57.123700: +2024-11-21 20:04:57.123904: Epoch 1684 +2024-11-21 20:04:57.124031: Current learning rate: 0.00808 +2024-11-21 20:05:15.860816: train_loss -0.7608 +2024-11-21 20:05:15.865998: val_loss -0.7692 +2024-11-21 20:05:15.866136: Pseudo dice [0.8388] +2024-11-21 20:05:15.866221: Epoch time: 18.74 s +2024-11-21 20:05:16.803766: +2024-11-21 20:05:16.804019: Epoch 1685 +2024-11-21 20:05:16.804168: Current learning rate: 0.00808 +2024-11-21 20:05:36.757051: train_loss -0.7582 +2024-11-21 20:05:36.763010: val_loss -0.7635 +2024-11-21 20:05:36.763135: Pseudo dice [0.8479] +2024-11-21 20:05:36.763242: Epoch time: 19.95 s +2024-11-21 20:05:37.590307: +2024-11-21 20:05:37.590531: Epoch 1686 +2024-11-21 20:05:37.590673: Current learning rate: 0.00808 +2024-11-21 20:05:57.046109: train_loss -0.7586 +2024-11-21 20:05:57.062593: val_loss -0.7665 +2024-11-21 20:05:57.062723: Pseudo dice [0.8459] +2024-11-21 20:05:57.062809: Epoch time: 19.46 s +2024-11-21 20:05:58.174300: +2024-11-21 20:05:58.174517: Epoch 1687 +2024-11-21 20:05:58.174651: Current learning rate: 0.00808 +2024-11-21 20:06:19.006840: train_loss -0.7592 +2024-11-21 20:06:19.011801: val_loss -0.7486 +2024-11-21 20:06:19.030751: Pseudo dice [0.8404] +2024-11-21 20:06:19.030898: Epoch time: 20.83 s +2024-11-21 20:06:19.859159: +2024-11-21 20:06:19.859397: Epoch 1688 +2024-11-21 20:06:19.859531: Current learning rate: 0.00808 +2024-11-21 20:06:39.567747: train_loss -0.776 +2024-11-21 20:06:39.575764: val_loss -0.7776 +2024-11-21 20:06:39.575911: Pseudo dice [0.8611] +2024-11-21 20:06:39.576023: Epoch time: 19.71 s +2024-11-21 20:06:40.495594: +2024-11-21 20:06:40.495830: Epoch 1689 +2024-11-21 20:06:40.495955: Current learning rate: 0.00808 +2024-11-21 20:06:58.535916: train_loss -0.7667 +2024-11-21 20:06:58.543323: val_loss -0.746 +2024-11-21 20:06:58.543449: Pseudo dice [0.839] +2024-11-21 20:06:58.543547: Epoch time: 18.04 s +2024-11-21 20:06:59.375600: +2024-11-21 20:06:59.375787: Epoch 1690 +2024-11-21 20:06:59.375918: Current learning rate: 0.00808 +2024-11-21 20:07:18.963803: train_loss -0.7742 +2024-11-21 20:07:18.970390: val_loss -0.7686 +2024-11-21 20:07:18.970519: Pseudo dice [0.848] +2024-11-21 20:07:18.970621: Epoch time: 19.59 s +2024-11-21 20:07:19.911129: +2024-11-21 20:07:19.911357: Epoch 1691 +2024-11-21 20:07:19.911502: Current learning rate: 0.00808 +2024-11-21 20:07:38.395606: train_loss -0.7632 +2024-11-21 20:07:38.406455: val_loss -0.7502 +2024-11-21 20:07:38.406612: Pseudo dice [0.834] +2024-11-21 20:07:38.406702: Epoch time: 18.49 s +2024-11-21 20:07:39.244509: +2024-11-21 20:07:39.244733: Epoch 1692 +2024-11-21 20:07:39.244856: Current learning rate: 0.00807 +2024-11-21 20:07:57.380644: train_loss -0.778 +2024-11-21 20:07:57.406174: val_loss -0.7561 +2024-11-21 20:07:57.406341: Pseudo dice [0.8396] +2024-11-21 20:07:57.406429: Epoch time: 18.14 s +2024-11-21 20:07:58.274693: +2024-11-21 20:07:58.274910: Epoch 1693 +2024-11-21 20:07:58.275026: Current learning rate: 0.00807 +2024-11-21 20:08:17.226236: train_loss -0.7836 +2024-11-21 20:08:17.231122: val_loss -0.7542 +2024-11-21 20:08:17.231260: Pseudo dice [0.8342] +2024-11-21 20:08:17.231353: Epoch time: 18.95 s +2024-11-21 20:08:18.165124: +2024-11-21 20:08:18.165336: Epoch 1694 +2024-11-21 20:08:18.165459: Current learning rate: 0.00807 +2024-11-21 20:08:36.280770: train_loss -0.7604 +2024-11-21 20:08:36.287512: val_loss -0.7596 +2024-11-21 20:08:36.287823: Pseudo dice [0.8375] +2024-11-21 20:08:36.287922: Epoch time: 18.12 s +2024-11-21 20:08:37.128430: +2024-11-21 20:08:37.128648: Epoch 1695 +2024-11-21 20:08:37.128772: Current learning rate: 0.00807 +2024-11-21 20:08:56.373513: train_loss -0.7558 +2024-11-21 20:08:56.379339: val_loss -0.7626 +2024-11-21 20:08:56.379470: Pseudo dice [0.8498] +2024-11-21 20:08:56.379554: Epoch time: 19.25 s +2024-11-21 20:08:57.588653: +2024-11-21 20:08:57.588868: Epoch 1696 +2024-11-21 20:08:57.589043: Current learning rate: 0.00807 +2024-11-21 20:09:17.456768: train_loss -0.7581 +2024-11-21 20:09:17.463624: val_loss -0.7669 +2024-11-21 20:09:17.463762: Pseudo dice [0.8359] +2024-11-21 20:09:17.463869: Epoch time: 19.87 s +2024-11-21 20:09:18.314930: +2024-11-21 20:09:18.315182: Epoch 1697 +2024-11-21 20:09:18.315303: Current learning rate: 0.00807 +2024-11-21 20:09:37.710889: train_loss -0.7576 +2024-11-21 20:09:37.719143: val_loss -0.7806 +2024-11-21 20:09:37.719279: Pseudo dice [0.8456] +2024-11-21 20:09:37.719385: Epoch time: 19.4 s +2024-11-21 20:09:38.579738: +2024-11-21 20:09:38.579978: Epoch 1698 +2024-11-21 20:09:38.580112: Current learning rate: 0.00807 +2024-11-21 20:09:57.582777: train_loss -0.7457 +2024-11-21 20:09:57.588482: val_loss -0.7566 +2024-11-21 20:09:57.588614: Pseudo dice [0.8326] +2024-11-21 20:09:57.588727: Epoch time: 19.0 s +2024-11-21 20:09:58.423105: +2024-11-21 20:09:58.423358: Epoch 1699 +2024-11-21 20:09:58.423480: Current learning rate: 0.00807 +2024-11-21 20:10:18.549582: train_loss -0.7558 +2024-11-21 20:10:18.558642: val_loss -0.7528 +2024-11-21 20:10:18.558762: Pseudo dice [0.8378] +2024-11-21 20:10:18.558851: Epoch time: 20.13 s +2024-11-21 20:10:19.695950: +2024-11-21 20:10:19.696204: Epoch 1700 +2024-11-21 20:10:19.696330: Current learning rate: 0.00807 +2024-11-21 20:10:39.595309: train_loss -0.7597 +2024-11-21 20:10:39.600200: val_loss -0.7699 +2024-11-21 20:10:39.600335: Pseudo dice [0.8425] +2024-11-21 20:10:39.600430: Epoch time: 19.9 s +2024-11-21 20:10:40.470011: +2024-11-21 20:10:40.470220: Epoch 1701 +2024-11-21 20:10:40.470354: Current learning rate: 0.00806 +2024-11-21 20:10:58.813247: train_loss -0.7675 +2024-11-21 20:10:58.819571: val_loss -0.7633 +2024-11-21 20:10:58.819713: Pseudo dice [0.8478] +2024-11-21 20:10:58.819799: Epoch time: 18.34 s +2024-11-21 20:10:59.880651: +2024-11-21 20:10:59.880858: Epoch 1702 +2024-11-21 20:10:59.880979: Current learning rate: 0.00806 +2024-11-21 20:11:18.241883: train_loss -0.7601 +2024-11-21 20:11:18.250770: val_loss -0.7458 +2024-11-21 20:11:18.250913: Pseudo dice [0.8379] +2024-11-21 20:11:18.251026: Epoch time: 18.36 s +2024-11-21 20:11:19.316420: +2024-11-21 20:11:19.316631: Epoch 1703 +2024-11-21 20:11:19.316764: Current learning rate: 0.00806 +2024-11-21 20:11:38.432369: train_loss -0.7499 +2024-11-21 20:11:38.439881: val_loss -0.7717 +2024-11-21 20:11:38.440013: Pseudo dice [0.849] +2024-11-21 20:11:38.440106: Epoch time: 19.12 s +2024-11-21 20:11:39.270174: +2024-11-21 20:11:39.270395: Epoch 1704 +2024-11-21 20:11:39.270527: Current learning rate: 0.00806 +2024-11-21 20:11:57.638543: train_loss -0.7549 +2024-11-21 20:11:57.641357: val_loss -0.7661 +2024-11-21 20:11:57.641498: Pseudo dice [0.847] +2024-11-21 20:11:57.641610: Epoch time: 18.37 s +2024-11-21 20:11:58.634485: +2024-11-21 20:11:58.634689: Epoch 1705 +2024-11-21 20:11:58.634825: Current learning rate: 0.00806 +2024-11-21 20:12:17.272397: train_loss -0.7686 +2024-11-21 20:12:17.279100: val_loss -0.7698 +2024-11-21 20:12:17.279222: Pseudo dice [0.845] +2024-11-21 20:12:17.279318: Epoch time: 18.64 s +2024-11-21 20:12:18.167639: +2024-11-21 20:12:18.167836: Epoch 1706 +2024-11-21 20:12:18.167972: Current learning rate: 0.00806 +2024-11-21 20:12:37.352560: train_loss -0.7674 +2024-11-21 20:12:37.359259: val_loss -0.7546 +2024-11-21 20:12:37.359395: Pseudo dice [0.8348] +2024-11-21 20:12:37.359483: Epoch time: 19.19 s +2024-11-21 20:12:38.317893: +2024-11-21 20:12:38.318099: Epoch 1707 +2024-11-21 20:12:38.318228: Current learning rate: 0.00806 +2024-11-21 20:12:57.260593: train_loss -0.7683 +2024-11-21 20:12:57.266641: val_loss -0.7551 +2024-11-21 20:12:57.266767: Pseudo dice [0.8479] +2024-11-21 20:12:57.266856: Epoch time: 18.94 s +2024-11-21 20:12:58.112233: +2024-11-21 20:12:58.112484: Epoch 1708 +2024-11-21 20:12:58.112637: Current learning rate: 0.00806 +2024-11-21 20:13:17.485880: train_loss -0.7645 +2024-11-21 20:13:17.489157: val_loss -0.7977 +2024-11-21 20:13:17.489284: Pseudo dice [0.8533] +2024-11-21 20:13:17.489385: Epoch time: 19.37 s +2024-11-21 20:13:18.364360: +2024-11-21 20:13:18.364604: Epoch 1709 +2024-11-21 20:13:18.364730: Current learning rate: 0.00806 +2024-11-21 20:13:38.489374: train_loss -0.7633 +2024-11-21 20:13:38.496105: val_loss -0.7769 +2024-11-21 20:13:38.496251: Pseudo dice [0.8344] +2024-11-21 20:13:38.496347: Epoch time: 20.13 s +2024-11-21 20:13:39.334690: +2024-11-21 20:13:39.334917: Epoch 1710 +2024-11-21 20:13:39.335028: Current learning rate: 0.00805 +2024-11-21 20:13:58.234612: train_loss -0.7735 +2024-11-21 20:13:58.245278: val_loss -0.758 +2024-11-21 20:13:58.245422: Pseudo dice [0.8447] +2024-11-21 20:13:58.245514: Epoch time: 18.9 s +2024-11-21 20:13:59.210166: +2024-11-21 20:13:59.210382: Epoch 1711 +2024-11-21 20:13:59.210497: Current learning rate: 0.00805 +2024-11-21 20:14:19.426909: train_loss -0.7537 +2024-11-21 20:14:19.435442: val_loss -0.7444 +2024-11-21 20:14:19.435583: Pseudo dice [0.8319] +2024-11-21 20:14:19.435715: Epoch time: 20.22 s +2024-11-21 20:14:20.297136: +2024-11-21 20:14:20.297382: Epoch 1712 +2024-11-21 20:14:20.297506: Current learning rate: 0.00805 +2024-11-21 20:14:39.379887: train_loss -0.7671 +2024-11-21 20:14:39.391287: val_loss -0.7703 +2024-11-21 20:14:39.391433: Pseudo dice [0.8432] +2024-11-21 20:14:39.391533: Epoch time: 19.08 s +2024-11-21 20:14:40.293278: +2024-11-21 20:14:40.293498: Epoch 1713 +2024-11-21 20:14:40.293639: Current learning rate: 0.00805 +2024-11-21 20:15:00.246355: train_loss -0.7707 +2024-11-21 20:15:00.262158: val_loss -0.7426 +2024-11-21 20:15:00.262335: Pseudo dice [0.8479] +2024-11-21 20:15:00.262448: Epoch time: 19.95 s +2024-11-21 20:15:01.097402: +2024-11-21 20:15:01.097604: Epoch 1714 +2024-11-21 20:15:01.097743: Current learning rate: 0.00805 +2024-11-21 20:15:21.577976: train_loss -0.7662 +2024-11-21 20:15:21.581294: val_loss -0.7829 +2024-11-21 20:15:21.581444: Pseudo dice [0.858] +2024-11-21 20:15:21.581546: Epoch time: 20.48 s +2024-11-21 20:15:22.414622: +2024-11-21 20:15:22.414835: Epoch 1715 +2024-11-21 20:15:22.414958: Current learning rate: 0.00805 +2024-11-21 20:15:41.211335: train_loss -0.7731 +2024-11-21 20:15:41.218333: val_loss -0.7521 +2024-11-21 20:15:41.218470: Pseudo dice [0.8506] +2024-11-21 20:15:41.218567: Epoch time: 18.8 s +2024-11-21 20:15:42.051803: +2024-11-21 20:15:42.052032: Epoch 1716 +2024-11-21 20:15:42.052168: Current learning rate: 0.00805 +2024-11-21 20:16:01.218914: train_loss -0.7652 +2024-11-21 20:16:01.225224: val_loss -0.7426 +2024-11-21 20:16:01.225374: Pseudo dice [0.8458] +2024-11-21 20:16:01.225537: Epoch time: 19.17 s +2024-11-21 20:16:02.203208: +2024-11-21 20:16:02.203405: Epoch 1717 +2024-11-21 20:16:02.203541: Current learning rate: 0.00805 +2024-11-21 20:16:20.714102: train_loss -0.7647 +2024-11-21 20:16:20.725093: val_loss -0.7619 +2024-11-21 20:16:20.725223: Pseudo dice [0.8602] +2024-11-21 20:16:20.725328: Epoch time: 18.51 s +2024-11-21 20:16:22.009715: +2024-11-21 20:16:22.009918: Epoch 1718 +2024-11-21 20:16:22.010032: Current learning rate: 0.00804 +2024-11-21 20:16:42.012846: train_loss -0.7587 +2024-11-21 20:16:42.016358: val_loss -0.7523 +2024-11-21 20:16:42.016461: Pseudo dice [0.8345] +2024-11-21 20:16:42.016557: Epoch time: 20.0 s +2024-11-21 20:16:42.845874: +2024-11-21 20:16:42.846081: Epoch 1719 +2024-11-21 20:16:42.846212: Current learning rate: 0.00804 +2024-11-21 20:17:01.461015: train_loss -0.7626 +2024-11-21 20:17:01.466032: val_loss -0.7571 +2024-11-21 20:17:01.466183: Pseudo dice [0.8442] +2024-11-21 20:17:01.466349: Epoch time: 18.62 s +2024-11-21 20:17:02.381407: +2024-11-21 20:17:02.381626: Epoch 1720 +2024-11-21 20:17:02.381756: Current learning rate: 0.00804 +2024-11-21 20:17:20.582239: train_loss -0.7601 +2024-11-21 20:17:20.590978: val_loss -0.76 +2024-11-21 20:17:20.591148: Pseudo dice [0.8364] +2024-11-21 20:17:20.591242: Epoch time: 18.2 s +2024-11-21 20:17:21.586816: +2024-11-21 20:17:21.587033: Epoch 1721 +2024-11-21 20:17:21.587153: Current learning rate: 0.00804 +2024-11-21 20:17:38.900660: train_loss -0.761 +2024-11-21 20:17:38.903724: val_loss -0.7682 +2024-11-21 20:17:38.903830: Pseudo dice [0.8425] +2024-11-21 20:17:38.903931: Epoch time: 17.31 s +2024-11-21 20:17:39.734353: +2024-11-21 20:17:39.734572: Epoch 1722 +2024-11-21 20:17:39.734688: Current learning rate: 0.00804 +2024-11-21 20:17:58.363016: train_loss -0.7668 +2024-11-21 20:17:58.369389: val_loss -0.7574 +2024-11-21 20:17:58.369525: Pseudo dice [0.8455] +2024-11-21 20:17:58.369624: Epoch time: 18.63 s +2024-11-21 20:17:59.222017: +2024-11-21 20:17:59.222260: Epoch 1723 +2024-11-21 20:17:59.222385: Current learning rate: 0.00804 +2024-11-21 20:18:18.530070: train_loss -0.7661 +2024-11-21 20:18:18.534069: val_loss -0.7736 +2024-11-21 20:18:18.534186: Pseudo dice [0.8515] +2024-11-21 20:18:18.534294: Epoch time: 19.31 s +2024-11-21 20:18:19.367503: +2024-11-21 20:18:19.367710: Epoch 1724 +2024-11-21 20:18:19.367839: Current learning rate: 0.00804 +2024-11-21 20:18:39.199093: train_loss -0.7532 +2024-11-21 20:18:39.215686: val_loss -0.768 +2024-11-21 20:18:39.215812: Pseudo dice [0.8463] +2024-11-21 20:18:39.215912: Epoch time: 19.83 s +2024-11-21 20:18:40.142614: +2024-11-21 20:18:40.142840: Epoch 1725 +2024-11-21 20:18:40.142961: Current learning rate: 0.00804 +2024-11-21 20:18:58.856217: train_loss -0.7603 +2024-11-21 20:18:58.859271: val_loss -0.7852 +2024-11-21 20:18:58.859680: Pseudo dice [0.8445] +2024-11-21 20:18:58.859789: Epoch time: 18.71 s +2024-11-21 20:18:59.689660: +2024-11-21 20:18:59.689848: Epoch 1726 +2024-11-21 20:18:59.689975: Current learning rate: 0.00804 +2024-11-21 20:19:19.006322: train_loss -0.766 +2024-11-21 20:19:19.009475: val_loss -0.77 +2024-11-21 20:19:19.009586: Pseudo dice [0.8496] +2024-11-21 20:19:19.009673: Epoch time: 19.32 s +2024-11-21 20:19:19.834766: +2024-11-21 20:19:19.834967: Epoch 1727 +2024-11-21 20:19:19.835090: Current learning rate: 0.00803 +2024-11-21 20:19:40.431593: train_loss -0.7678 +2024-11-21 20:19:40.434473: val_loss -0.7485 +2024-11-21 20:19:40.434599: Pseudo dice [0.8404] +2024-11-21 20:19:40.434681: Epoch time: 20.6 s +2024-11-21 20:19:41.397765: +2024-11-21 20:19:41.397966: Epoch 1728 +2024-11-21 20:19:41.398112: Current learning rate: 0.00803 +2024-11-21 20:20:01.078203: train_loss -0.7587 +2024-11-21 20:20:01.080465: val_loss -0.7716 +2024-11-21 20:20:01.080581: Pseudo dice [0.8299] +2024-11-21 20:20:01.080675: Epoch time: 19.68 s +2024-11-21 20:20:01.892495: +2024-11-21 20:20:01.892691: Epoch 1729 +2024-11-21 20:20:01.892815: Current learning rate: 0.00803 +2024-11-21 20:20:21.440713: train_loss -0.762 +2024-11-21 20:20:21.446776: val_loss -0.7809 +2024-11-21 20:20:21.446905: Pseudo dice [0.861] +2024-11-21 20:20:21.447021: Epoch time: 19.55 s +2024-11-21 20:20:22.344933: +2024-11-21 20:20:22.345146: Epoch 1730 +2024-11-21 20:20:22.345271: Current learning rate: 0.00803 +2024-11-21 20:20:40.504695: train_loss -0.7801 +2024-11-21 20:20:40.506683: val_loss -0.7648 +2024-11-21 20:20:40.506826: Pseudo dice [0.848] +2024-11-21 20:20:40.506931: Epoch time: 18.16 s +2024-11-21 20:20:41.435846: +2024-11-21 20:20:41.436065: Epoch 1731 +2024-11-21 20:20:41.436197: Current learning rate: 0.00803 +2024-11-21 20:21:00.527171: train_loss -0.7696 +2024-11-21 20:21:00.534893: val_loss -0.738 +2024-11-21 20:21:00.535025: Pseudo dice [0.8459] +2024-11-21 20:21:00.535116: Epoch time: 19.09 s +2024-11-21 20:21:01.594732: +2024-11-21 20:21:01.594931: Epoch 1732 +2024-11-21 20:21:01.595045: Current learning rate: 0.00803 +2024-11-21 20:21:21.085719: train_loss -0.7755 +2024-11-21 20:21:21.098367: val_loss -0.7518 +2024-11-21 20:21:21.098502: Pseudo dice [0.8474] +2024-11-21 20:21:21.098602: Epoch time: 19.49 s +2024-11-21 20:21:21.932693: +2024-11-21 20:21:21.932970: Epoch 1733 +2024-11-21 20:21:21.933164: Current learning rate: 0.00803 +2024-11-21 20:21:41.745342: train_loss -0.7696 +2024-11-21 20:21:41.747267: val_loss -0.7779 +2024-11-21 20:21:41.747416: Pseudo dice [0.8273] +2024-11-21 20:21:41.747511: Epoch time: 19.81 s +2024-11-21 20:21:42.660453: +2024-11-21 20:21:42.660660: Epoch 1734 +2024-11-21 20:21:42.660782: Current learning rate: 0.00803 +2024-11-21 20:22:02.624074: train_loss -0.7717 +2024-11-21 20:22:02.642971: val_loss -0.7487 +2024-11-21 20:22:02.643131: Pseudo dice [0.8417] +2024-11-21 20:22:02.643222: Epoch time: 19.96 s +2024-11-21 20:22:03.622206: +2024-11-21 20:22:03.622445: Epoch 1735 +2024-11-21 20:22:03.622572: Current learning rate: 0.00803 +2024-11-21 20:22:23.979740: train_loss -0.7636 +2024-11-21 20:22:23.986107: val_loss -0.7452 +2024-11-21 20:22:23.986225: Pseudo dice [0.8484] +2024-11-21 20:22:23.986324: Epoch time: 20.36 s +2024-11-21 20:22:25.032594: +2024-11-21 20:22:25.032790: Epoch 1736 +2024-11-21 20:22:25.032913: Current learning rate: 0.00802 +2024-11-21 20:22:43.063067: train_loss -0.7519 +2024-11-21 20:22:43.070960: val_loss -0.7656 +2024-11-21 20:22:43.071112: Pseudo dice [0.8402] +2024-11-21 20:22:43.071233: Epoch time: 18.03 s +2024-11-21 20:22:43.945225: +2024-11-21 20:22:43.945440: Epoch 1737 +2024-11-21 20:22:43.945580: Current learning rate: 0.00802 +2024-11-21 20:23:03.170317: train_loss -0.7574 +2024-11-21 20:23:03.177453: val_loss -0.7455 +2024-11-21 20:23:03.177586: Pseudo dice [0.8337] +2024-11-21 20:23:03.177681: Epoch time: 19.23 s +2024-11-21 20:23:04.012100: +2024-11-21 20:23:04.012314: Epoch 1738 +2024-11-21 20:23:04.012427: Current learning rate: 0.00802 +2024-11-21 20:23:22.896769: train_loss -0.7608 +2024-11-21 20:23:22.905985: val_loss -0.7741 +2024-11-21 20:23:22.906132: Pseudo dice [0.8519] +2024-11-21 20:23:22.906220: Epoch time: 18.89 s +2024-11-21 20:23:23.775895: +2024-11-21 20:23:23.776106: Epoch 1739 +2024-11-21 20:23:23.776249: Current learning rate: 0.00802 +2024-11-21 20:23:41.128138: train_loss -0.7589 +2024-11-21 20:23:41.134106: val_loss -0.7634 +2024-11-21 20:23:41.134250: Pseudo dice [0.8389] +2024-11-21 20:23:41.134339: Epoch time: 17.35 s +2024-11-21 20:23:42.360370: +2024-11-21 20:23:42.360593: Epoch 1740 +2024-11-21 20:23:42.360711: Current learning rate: 0.00802 +2024-11-21 20:24:00.924033: train_loss -0.772 +2024-11-21 20:24:00.930192: val_loss -0.7511 +2024-11-21 20:24:00.930331: Pseudo dice [0.8515] +2024-11-21 20:24:00.930443: Epoch time: 18.56 s +2024-11-21 20:24:01.928450: +2024-11-21 20:24:01.928665: Epoch 1741 +2024-11-21 20:24:01.928773: Current learning rate: 0.00802 +2024-11-21 20:24:22.307921: train_loss -0.7725 +2024-11-21 20:24:22.314951: val_loss -0.7648 +2024-11-21 20:24:22.315109: Pseudo dice [0.8524] +2024-11-21 20:24:22.315205: Epoch time: 20.38 s +2024-11-21 20:24:23.145508: +2024-11-21 20:24:23.145748: Epoch 1742 +2024-11-21 20:24:23.145867: Current learning rate: 0.00802 +2024-11-21 20:24:41.565419: train_loss -0.7594 +2024-11-21 20:24:41.568487: val_loss -0.7506 +2024-11-21 20:24:41.568596: Pseudo dice [0.8365] +2024-11-21 20:24:41.568701: Epoch time: 18.42 s +2024-11-21 20:24:42.443272: +2024-11-21 20:24:42.443503: Epoch 1743 +2024-11-21 20:24:42.443644: Current learning rate: 0.00802 +2024-11-21 20:25:01.909431: train_loss -0.7557 +2024-11-21 20:25:01.917562: val_loss -0.7418 +2024-11-21 20:25:01.917703: Pseudo dice [0.8434] +2024-11-21 20:25:01.917800: Epoch time: 19.47 s +2024-11-21 20:25:02.845088: +2024-11-21 20:25:02.845309: Epoch 1744 +2024-11-21 20:25:02.845426: Current learning rate: 0.00801 +2024-11-21 20:25:21.649252: train_loss -0.756 +2024-11-21 20:25:21.653603: val_loss -0.7553 +2024-11-21 20:25:21.653741: Pseudo dice [0.8562] +2024-11-21 20:25:21.653834: Epoch time: 18.81 s +2024-11-21 20:25:22.514106: +2024-11-21 20:25:22.514322: Epoch 1745 +2024-11-21 20:25:22.514443: Current learning rate: 0.00801 +2024-11-21 20:25:42.072630: train_loss -0.7502 +2024-11-21 20:25:42.079247: val_loss -0.7645 +2024-11-21 20:25:42.079395: Pseudo dice [0.8446] +2024-11-21 20:25:42.079493: Epoch time: 19.56 s +2024-11-21 20:25:42.935454: +2024-11-21 20:25:42.935666: Epoch 1746 +2024-11-21 20:25:42.936385: Current learning rate: 0.00801 +2024-11-21 20:26:01.945908: train_loss -0.7659 +2024-11-21 20:26:01.948630: val_loss -0.763 +2024-11-21 20:26:01.948746: Pseudo dice [0.8397] +2024-11-21 20:26:01.948848: Epoch time: 19.01 s +2024-11-21 20:26:02.959459: +2024-11-21 20:26:02.959703: Epoch 1747 +2024-11-21 20:26:02.959853: Current learning rate: 0.00801 +2024-11-21 20:26:22.526445: train_loss -0.7716 +2024-11-21 20:26:22.535769: val_loss -0.7356 +2024-11-21 20:26:22.535922: Pseudo dice [0.8042] +2024-11-21 20:26:22.536048: Epoch time: 19.57 s +2024-11-21 20:26:23.570295: +2024-11-21 20:26:23.570514: Epoch 1748 +2024-11-21 20:26:23.570651: Current learning rate: 0.00801 +2024-11-21 20:26:42.171867: train_loss -0.7539 +2024-11-21 20:26:42.189519: val_loss -0.7752 +2024-11-21 20:26:42.189646: Pseudo dice [0.8565] +2024-11-21 20:26:42.189747: Epoch time: 18.6 s +2024-11-21 20:26:43.130014: +2024-11-21 20:26:43.130208: Epoch 1749 +2024-11-21 20:26:43.130321: Current learning rate: 0.00801 +2024-11-21 20:27:03.524379: train_loss -0.7514 +2024-11-21 20:27:03.526758: val_loss -0.7697 +2024-11-21 20:27:03.526876: Pseudo dice [0.85] +2024-11-21 20:27:03.526959: Epoch time: 20.4 s +2024-11-21 20:27:04.551511: +2024-11-21 20:27:04.551709: Epoch 1750 +2024-11-21 20:27:04.551838: Current learning rate: 0.00801 +2024-11-21 20:27:24.406017: train_loss -0.7401 +2024-11-21 20:27:24.409763: val_loss -0.7309 +2024-11-21 20:27:24.409879: Pseudo dice [0.8236] +2024-11-21 20:27:24.409983: Epoch time: 19.86 s +2024-11-21 20:27:25.344658: +2024-11-21 20:27:25.345048: Epoch 1751 +2024-11-21 20:27:25.345187: Current learning rate: 0.00801 +2024-11-21 20:27:43.954637: train_loss -0.7376 +2024-11-21 20:27:43.960722: val_loss -0.7648 +2024-11-21 20:27:43.960854: Pseudo dice [0.8482] +2024-11-21 20:27:43.960967: Epoch time: 18.61 s +2024-11-21 20:27:44.865548: +2024-11-21 20:27:44.865780: Epoch 1752 +2024-11-21 20:27:44.865913: Current learning rate: 0.00801 +2024-11-21 20:28:03.981044: train_loss -0.7512 +2024-11-21 20:28:03.982932: val_loss -0.7672 +2024-11-21 20:28:03.983035: Pseudo dice [0.8349] +2024-11-21 20:28:03.983119: Epoch time: 19.12 s +2024-11-21 20:28:04.813476: +2024-11-21 20:28:04.813767: Epoch 1753 +2024-11-21 20:28:04.813909: Current learning rate: 0.008 +2024-11-21 20:28:23.325108: train_loss -0.7595 +2024-11-21 20:28:23.328696: val_loss -0.7542 +2024-11-21 20:28:23.328835: Pseudo dice [0.846] +2024-11-21 20:28:23.328945: Epoch time: 18.51 s +2024-11-21 20:28:24.469976: +2024-11-21 20:28:24.470214: Epoch 1754 +2024-11-21 20:28:24.470345: Current learning rate: 0.008 +2024-11-21 20:28:42.861191: train_loss -0.7641 +2024-11-21 20:28:42.881821: val_loss -0.7872 +2024-11-21 20:28:42.881982: Pseudo dice [0.8422] +2024-11-21 20:28:42.882086: Epoch time: 18.39 s +2024-11-21 20:28:43.877964: +2024-11-21 20:28:43.878240: Epoch 1755 +2024-11-21 20:28:43.878370: Current learning rate: 0.008 +2024-11-21 20:29:02.814471: train_loss -0.7624 +2024-11-21 20:29:02.840772: val_loss -0.7422 +2024-11-21 20:29:02.840933: Pseudo dice [0.8526] +2024-11-21 20:29:02.841029: Epoch time: 18.94 s +2024-11-21 20:29:03.714545: +2024-11-21 20:29:03.714761: Epoch 1756 +2024-11-21 20:29:03.714894: Current learning rate: 0.008 +2024-11-21 20:29:24.125547: train_loss -0.7606 +2024-11-21 20:29:24.129251: val_loss -0.7338 +2024-11-21 20:29:24.129399: Pseudo dice [0.8371] +2024-11-21 20:29:24.129486: Epoch time: 20.41 s +2024-11-21 20:29:24.999950: +2024-11-21 20:29:25.000153: Epoch 1757 +2024-11-21 20:29:25.000267: Current learning rate: 0.008 +2024-11-21 20:29:43.958150: train_loss -0.7548 +2024-11-21 20:29:43.960518: val_loss -0.7617 +2024-11-21 20:29:43.960646: Pseudo dice [0.8418] +2024-11-21 20:29:43.960732: Epoch time: 18.96 s +2024-11-21 20:29:44.787617: +2024-11-21 20:29:44.787821: Epoch 1758 +2024-11-21 20:29:44.787957: Current learning rate: 0.008 +2024-11-21 20:30:04.089780: train_loss -0.7777 +2024-11-21 20:30:04.094798: val_loss -0.7612 +2024-11-21 20:30:04.094935: Pseudo dice [0.8305] +2024-11-21 20:30:04.095041: Epoch time: 19.3 s +2024-11-21 20:30:05.011197: +2024-11-21 20:30:05.011398: Epoch 1759 +2024-11-21 20:30:05.011533: Current learning rate: 0.008 +2024-11-21 20:30:24.991843: train_loss -0.7679 +2024-11-21 20:30:24.996581: val_loss -0.7556 +2024-11-21 20:30:24.996727: Pseudo dice [0.8349] +2024-11-21 20:30:24.996827: Epoch time: 19.98 s +2024-11-21 20:30:25.837005: +2024-11-21 20:30:25.837223: Epoch 1760 +2024-11-21 20:30:25.837343: Current learning rate: 0.008 +2024-11-21 20:30:45.206040: train_loss -0.7705 +2024-11-21 20:30:45.212624: val_loss -0.7493 +2024-11-21 20:30:45.212760: Pseudo dice [0.8444] +2024-11-21 20:30:45.212860: Epoch time: 19.37 s +2024-11-21 20:30:46.207955: +2024-11-21 20:30:46.208183: Epoch 1761 +2024-11-21 20:30:46.208306: Current learning rate: 0.008 +2024-11-21 20:31:06.524690: train_loss -0.7725 +2024-11-21 20:31:06.539739: val_loss -0.7525 +2024-11-21 20:31:06.540137: Pseudo dice [0.8509] +2024-11-21 20:31:06.540249: Epoch time: 20.32 s +2024-11-21 20:31:07.885439: +2024-11-21 20:31:07.885656: Epoch 1762 +2024-11-21 20:31:07.885786: Current learning rate: 0.00799 +2024-11-21 20:31:28.042449: train_loss -0.7806 +2024-11-21 20:31:28.056013: val_loss -0.7639 +2024-11-21 20:31:28.056193: Pseudo dice [0.8394] +2024-11-21 20:31:28.056283: Epoch time: 20.16 s +2024-11-21 20:31:28.896442: +2024-11-21 20:31:28.896682: Epoch 1763 +2024-11-21 20:31:28.896814: Current learning rate: 0.00799 +2024-11-21 20:31:47.163928: train_loss -0.772 +2024-11-21 20:31:47.168253: val_loss -0.7623 +2024-11-21 20:31:47.168424: Pseudo dice [0.8486] +2024-11-21 20:31:47.168796: Epoch time: 18.27 s +2024-11-21 20:31:47.995784: +2024-11-21 20:31:47.996007: Epoch 1764 +2024-11-21 20:31:47.996150: Current learning rate: 0.00799 +2024-11-21 20:32:08.823828: train_loss -0.7598 +2024-11-21 20:32:08.826314: val_loss -0.7481 +2024-11-21 20:32:08.826431: Pseudo dice [0.8452] +2024-11-21 20:32:08.826512: Epoch time: 20.83 s +2024-11-21 20:32:09.655740: +2024-11-21 20:32:09.656030: Epoch 1765 +2024-11-21 20:32:09.656201: Current learning rate: 0.00799 +2024-11-21 20:32:28.840993: train_loss -0.771 +2024-11-21 20:32:28.843903: val_loss -0.7693 +2024-11-21 20:32:28.844006: Pseudo dice [0.8498] +2024-11-21 20:32:28.844112: Epoch time: 19.19 s +2024-11-21 20:32:29.681936: +2024-11-21 20:32:29.682157: Epoch 1766 +2024-11-21 20:32:29.682281: Current learning rate: 0.00799 +2024-11-21 20:32:49.234385: train_loss -0.7644 +2024-11-21 20:32:49.240671: val_loss -0.7442 +2024-11-21 20:32:49.240823: Pseudo dice [0.8422] +2024-11-21 20:32:49.240958: Epoch time: 19.55 s +2024-11-21 20:32:50.256278: +2024-11-21 20:32:50.256502: Epoch 1767 +2024-11-21 20:32:50.256634: Current learning rate: 0.00799 +2024-11-21 20:33:09.440475: train_loss -0.7619 +2024-11-21 20:33:09.449063: val_loss -0.7417 +2024-11-21 20:33:09.449220: Pseudo dice [0.835] +2024-11-21 20:33:09.449385: Epoch time: 19.19 s +2024-11-21 20:33:10.523135: +2024-11-21 20:33:10.523348: Epoch 1768 +2024-11-21 20:33:10.523487: Current learning rate: 0.00799 +2024-11-21 20:33:30.275710: train_loss -0.7681 +2024-11-21 20:33:30.277925: val_loss -0.7656 +2024-11-21 20:33:30.278044: Pseudo dice [0.8404] +2024-11-21 20:33:30.278137: Epoch time: 19.75 s +2024-11-21 20:33:31.107767: +2024-11-21 20:33:31.107965: Epoch 1769 +2024-11-21 20:33:31.108102: Current learning rate: 0.00799 +2024-11-21 20:33:50.779719: train_loss -0.759 +2024-11-21 20:33:50.787113: val_loss -0.7523 +2024-11-21 20:33:50.787246: Pseudo dice [0.8292] +2024-11-21 20:33:50.787349: Epoch time: 19.67 s +2024-11-21 20:33:51.621871: +2024-11-21 20:33:51.622088: Epoch 1770 +2024-11-21 20:33:51.622219: Current learning rate: 0.00798 +2024-11-21 20:34:10.765887: train_loss -0.7714 +2024-11-21 20:34:10.771271: val_loss -0.7843 +2024-11-21 20:34:10.771400: Pseudo dice [0.8644] +2024-11-21 20:34:10.771487: Epoch time: 19.14 s +2024-11-21 20:34:11.673258: +2024-11-21 20:34:11.673461: Epoch 1771 +2024-11-21 20:34:11.673584: Current learning rate: 0.00798 +2024-11-21 20:34:31.440106: train_loss -0.7676 +2024-11-21 20:34:31.446162: val_loss -0.7753 +2024-11-21 20:34:31.446299: Pseudo dice [0.8446] +2024-11-21 20:34:31.446392: Epoch time: 19.77 s +2024-11-21 20:34:32.286776: +2024-11-21 20:34:32.287023: Epoch 1772 +2024-11-21 20:34:32.287307: Current learning rate: 0.00798 +2024-11-21 20:34:51.618754: train_loss -0.7636 +2024-11-21 20:34:51.625232: val_loss -0.747 +2024-11-21 20:34:51.625376: Pseudo dice [0.8545] +2024-11-21 20:34:51.625476: Epoch time: 19.33 s +2024-11-21 20:34:52.572819: +2024-11-21 20:34:52.573043: Epoch 1773 +2024-11-21 20:34:52.573174: Current learning rate: 0.00798 +2024-11-21 20:35:12.138182: train_loss -0.7593 +2024-11-21 20:35:12.144778: val_loss -0.7679 +2024-11-21 20:35:12.144906: Pseudo dice [0.8528] +2024-11-21 20:35:12.145021: Epoch time: 19.57 s +2024-11-21 20:35:12.965663: +2024-11-21 20:35:12.965874: Epoch 1774 +2024-11-21 20:35:12.965997: Current learning rate: 0.00798 +2024-11-21 20:35:31.434239: train_loss -0.755 +2024-11-21 20:35:31.440192: val_loss -0.7493 +2024-11-21 20:35:31.440337: Pseudo dice [0.8477] +2024-11-21 20:35:31.440444: Epoch time: 18.47 s +2024-11-21 20:35:32.361561: +2024-11-21 20:35:32.361786: Epoch 1775 +2024-11-21 20:35:32.361902: Current learning rate: 0.00798 +2024-11-21 20:35:50.741193: train_loss -0.7685 +2024-11-21 20:35:50.759333: val_loss -0.772 +2024-11-21 20:35:50.759484: Pseudo dice [0.8447] +2024-11-21 20:35:50.759597: Epoch time: 18.38 s +2024-11-21 20:35:51.699510: +2024-11-21 20:35:51.699732: Epoch 1776 +2024-11-21 20:35:51.699863: Current learning rate: 0.00798 +2024-11-21 20:36:09.434326: train_loss -0.7573 +2024-11-21 20:36:09.441344: val_loss -0.7448 +2024-11-21 20:36:09.441517: Pseudo dice [0.8212] +2024-11-21 20:36:09.441609: Epoch time: 17.74 s +2024-11-21 20:36:10.309624: +2024-11-21 20:36:10.309836: Epoch 1777 +2024-11-21 20:36:10.309967: Current learning rate: 0.00798 +2024-11-21 20:36:29.039353: train_loss -0.7593 +2024-11-21 20:36:29.042428: val_loss -0.7604 +2024-11-21 20:36:29.042558: Pseudo dice [0.8454] +2024-11-21 20:36:29.042665: Epoch time: 18.73 s +2024-11-21 20:36:29.867822: +2024-11-21 20:36:29.868036: Epoch 1778 +2024-11-21 20:36:29.868174: Current learning rate: 0.00798 +2024-11-21 20:36:48.433698: train_loss -0.7652 +2024-11-21 20:36:48.461136: val_loss -0.7675 +2024-11-21 20:36:48.461279: Pseudo dice [0.8462] +2024-11-21 20:36:48.461389: Epoch time: 18.57 s +2024-11-21 20:36:49.291421: +2024-11-21 20:36:49.291631: Epoch 1779 +2024-11-21 20:36:49.291762: Current learning rate: 0.00797 +2024-11-21 20:37:08.677535: train_loss -0.7575 +2024-11-21 20:37:08.686480: val_loss -0.7322 +2024-11-21 20:37:08.686638: Pseudo dice [0.8336] +2024-11-21 20:37:08.686759: Epoch time: 19.39 s +2024-11-21 20:37:09.585328: +2024-11-21 20:37:09.585568: Epoch 1780 +2024-11-21 20:37:09.585687: Current learning rate: 0.00797 +2024-11-21 20:37:29.690078: train_loss -0.7577 +2024-11-21 20:37:29.692801: val_loss -0.7566 +2024-11-21 20:37:29.692919: Pseudo dice [0.8522] +2024-11-21 20:37:29.693029: Epoch time: 20.11 s +2024-11-21 20:37:30.518381: +2024-11-21 20:37:30.518584: Epoch 1781 +2024-11-21 20:37:30.518716: Current learning rate: 0.00797 +2024-11-21 20:37:49.732974: train_loss -0.7674 +2024-11-21 20:37:49.738164: val_loss -0.7757 +2024-11-21 20:37:49.738299: Pseudo dice [0.8445] +2024-11-21 20:37:49.738381: Epoch time: 19.22 s +2024-11-21 20:37:50.588700: +2024-11-21 20:37:50.588927: Epoch 1782 +2024-11-21 20:37:50.589062: Current learning rate: 0.00797 +2024-11-21 20:38:09.691555: train_loss -0.7619 +2024-11-21 20:38:09.699038: val_loss -0.7713 +2024-11-21 20:38:09.699189: Pseudo dice [0.8479] +2024-11-21 20:38:09.699294: Epoch time: 19.1 s +2024-11-21 20:38:10.643638: +2024-11-21 20:38:10.643824: Epoch 1783 +2024-11-21 20:38:10.643942: Current learning rate: 0.00797 +2024-11-21 20:38:29.245656: train_loss -0.7598 +2024-11-21 20:38:29.251192: val_loss -0.7747 +2024-11-21 20:38:29.251311: Pseudo dice [0.8499] +2024-11-21 20:38:29.251407: Epoch time: 18.6 s +2024-11-21 20:38:30.564262: +2024-11-21 20:38:30.564473: Epoch 1784 +2024-11-21 20:38:30.564603: Current learning rate: 0.00797 +2024-11-21 20:38:48.887760: train_loss -0.7692 +2024-11-21 20:38:48.895755: val_loss -0.7785 +2024-11-21 20:38:48.895902: Pseudo dice [0.8527] +2024-11-21 20:38:48.896002: Epoch time: 18.32 s +2024-11-21 20:38:49.935668: +2024-11-21 20:38:49.935894: Epoch 1785 +2024-11-21 20:38:49.936013: Current learning rate: 0.00797 +2024-11-21 20:39:09.031690: train_loss -0.7697 +2024-11-21 20:39:09.037879: val_loss -0.7435 +2024-11-21 20:39:09.038011: Pseudo dice [0.8273] +2024-11-21 20:39:09.038100: Epoch time: 19.1 s +2024-11-21 20:39:09.881761: +2024-11-21 20:39:09.881989: Epoch 1786 +2024-11-21 20:39:09.882130: Current learning rate: 0.00797 +2024-11-21 20:39:29.595164: train_loss -0.7664 +2024-11-21 20:39:29.602942: val_loss -0.7676 +2024-11-21 20:39:29.603105: Pseudo dice [0.8624] +2024-11-21 20:39:29.603205: Epoch time: 19.71 s +2024-11-21 20:39:30.456229: +2024-11-21 20:39:30.456449: Epoch 1787 +2024-11-21 20:39:30.456578: Current learning rate: 0.00797 +2024-11-21 20:39:49.027620: train_loss -0.7707 +2024-11-21 20:39:49.034491: val_loss -0.7731 +2024-11-21 20:39:49.034610: Pseudo dice [0.8436] +2024-11-21 20:39:49.034698: Epoch time: 18.57 s +2024-11-21 20:39:49.979120: +2024-11-21 20:39:49.979352: Epoch 1788 +2024-11-21 20:39:49.979482: Current learning rate: 0.00796 +2024-11-21 20:40:09.279690: train_loss -0.7666 +2024-11-21 20:40:09.286803: val_loss -0.777 +2024-11-21 20:40:09.286933: Pseudo dice [0.8546] +2024-11-21 20:40:09.287037: Epoch time: 19.3 s +2024-11-21 20:40:10.194986: +2024-11-21 20:40:10.195202: Epoch 1789 +2024-11-21 20:40:10.195315: Current learning rate: 0.00796 +2024-11-21 20:40:29.170907: train_loss -0.7765 +2024-11-21 20:40:29.178213: val_loss -0.763 +2024-11-21 20:40:29.178372: Pseudo dice [0.8505] +2024-11-21 20:40:29.178479: Epoch time: 18.98 s +2024-11-21 20:40:30.010809: +2024-11-21 20:40:30.011038: Epoch 1790 +2024-11-21 20:40:30.011172: Current learning rate: 0.00796 +2024-11-21 20:40:50.276093: train_loss -0.767 +2024-11-21 20:40:50.279718: val_loss -0.7496 +2024-11-21 20:40:50.279853: Pseudo dice [0.84] +2024-11-21 20:40:50.279945: Epoch time: 20.27 s +2024-11-21 20:40:51.115148: +2024-11-21 20:40:51.115363: Epoch 1791 +2024-11-21 20:40:51.115488: Current learning rate: 0.00796 +2024-11-21 20:41:10.162431: train_loss -0.7669 +2024-11-21 20:41:10.175397: val_loss -0.7462 +2024-11-21 20:41:10.175557: Pseudo dice [0.8462] +2024-11-21 20:41:10.175665: Epoch time: 19.05 s +2024-11-21 20:41:11.034877: +2024-11-21 20:41:11.035093: Epoch 1792 +2024-11-21 20:41:11.035237: Current learning rate: 0.00796 +2024-11-21 20:41:30.490905: train_loss -0.772 +2024-11-21 20:41:30.497608: val_loss -0.7802 +2024-11-21 20:41:30.497748: Pseudo dice [0.8566] +2024-11-21 20:41:30.497847: Epoch time: 19.46 s +2024-11-21 20:41:31.416384: +2024-11-21 20:41:31.416589: Epoch 1793 +2024-11-21 20:41:31.416711: Current learning rate: 0.00796 +2024-11-21 20:41:50.281073: train_loss -0.7603 +2024-11-21 20:41:50.284076: val_loss -0.7424 +2024-11-21 20:41:50.284236: Pseudo dice [0.8421] +2024-11-21 20:41:50.284341: Epoch time: 18.87 s +2024-11-21 20:41:51.125586: +2024-11-21 20:41:51.125793: Epoch 1794 +2024-11-21 20:41:51.125907: Current learning rate: 0.00796 +2024-11-21 20:42:08.895486: train_loss -0.7698 +2024-11-21 20:42:08.900935: val_loss -0.7469 +2024-11-21 20:42:08.901077: Pseudo dice [0.837] +2024-11-21 20:42:08.901170: Epoch time: 17.77 s +2024-11-21 20:42:09.791238: +2024-11-21 20:42:09.791451: Epoch 1795 +2024-11-21 20:42:09.791576: Current learning rate: 0.00796 +2024-11-21 20:42:29.418803: train_loss -0.7696 +2024-11-21 20:42:29.443251: val_loss -0.7854 +2024-11-21 20:42:29.443412: Pseudo dice [0.8404] +2024-11-21 20:42:29.443524: Epoch time: 19.63 s +2024-11-21 20:42:30.427550: +2024-11-21 20:42:30.427775: Epoch 1796 +2024-11-21 20:42:30.427902: Current learning rate: 0.00795 +2024-11-21 20:42:49.420050: train_loss -0.7639 +2024-11-21 20:42:49.434624: val_loss -0.7343 +2024-11-21 20:42:49.434793: Pseudo dice [0.8273] +2024-11-21 20:42:49.434910: Epoch time: 18.99 s +2024-11-21 20:42:50.367224: +2024-11-21 20:42:50.367446: Epoch 1797 +2024-11-21 20:42:50.367573: Current learning rate: 0.00795 +2024-11-21 20:43:09.785906: train_loss -0.7489 +2024-11-21 20:43:09.792286: val_loss -0.7743 +2024-11-21 20:43:09.792434: Pseudo dice [0.833] +2024-11-21 20:43:09.792541: Epoch time: 19.42 s +2024-11-21 20:43:10.790720: +2024-11-21 20:43:10.790953: Epoch 1798 +2024-11-21 20:43:10.791614: Current learning rate: 0.00795 +2024-11-21 20:43:30.707545: train_loss -0.7607 +2024-11-21 20:43:30.712562: val_loss -0.7689 +2024-11-21 20:43:30.712677: Pseudo dice [0.8399] +2024-11-21 20:43:30.712775: Epoch time: 19.92 s +2024-11-21 20:43:31.549419: +2024-11-21 20:43:31.549640: Epoch 1799 +2024-11-21 20:43:31.549767: Current learning rate: 0.00795 +2024-11-21 20:43:50.880039: train_loss -0.7527 +2024-11-21 20:43:50.888980: val_loss -0.7578 +2024-11-21 20:43:50.889110: Pseudo dice [0.8417] +2024-11-21 20:43:50.889198: Epoch time: 19.33 s +2024-11-21 20:43:52.068594: +2024-11-21 20:43:52.068804: Epoch 1800 +2024-11-21 20:43:52.068923: Current learning rate: 0.00795 +2024-11-21 20:44:10.705788: train_loss -0.7598 +2024-11-21 20:44:10.722189: val_loss -0.7358 +2024-11-21 20:44:10.722371: Pseudo dice [0.8293] +2024-11-21 20:44:10.722465: Epoch time: 18.64 s +2024-11-21 20:44:11.617841: +2024-11-21 20:44:11.618056: Epoch 1801 +2024-11-21 20:44:11.618196: Current learning rate: 0.00795 +2024-11-21 20:44:30.031959: train_loss -0.7633 +2024-11-21 20:44:30.039172: val_loss -0.7635 +2024-11-21 20:44:30.039393: Pseudo dice [0.8365] +2024-11-21 20:44:30.039513: Epoch time: 18.41 s +2024-11-21 20:44:30.880640: +2024-11-21 20:44:30.880854: Epoch 1802 +2024-11-21 20:44:30.880974: Current learning rate: 0.00795 +2024-11-21 20:44:50.334344: train_loss -0.769 +2024-11-21 20:44:50.337356: val_loss -0.7788 +2024-11-21 20:44:50.337491: Pseudo dice [0.8505] +2024-11-21 20:44:50.337580: Epoch time: 19.45 s +2024-11-21 20:44:51.162089: +2024-11-21 20:44:51.162276: Epoch 1803 +2024-11-21 20:44:51.162395: Current learning rate: 0.00795 +2024-11-21 20:45:10.986646: train_loss -0.7672 +2024-11-21 20:45:10.991693: val_loss -0.7656 +2024-11-21 20:45:10.991844: Pseudo dice [0.8426] +2024-11-21 20:45:10.991948: Epoch time: 19.83 s +2024-11-21 20:45:11.990309: +2024-11-21 20:45:11.990537: Epoch 1804 +2024-11-21 20:45:11.990674: Current learning rate: 0.00795 +2024-11-21 20:45:30.841558: train_loss -0.7605 +2024-11-21 20:45:30.845612: val_loss -0.7418 +2024-11-21 20:45:30.845709: Pseudo dice [0.834] +2024-11-21 20:45:30.845813: Epoch time: 18.85 s +2024-11-21 20:45:31.675526: +2024-11-21 20:45:31.675737: Epoch 1805 +2024-11-21 20:45:31.675865: Current learning rate: 0.00794 +2024-11-21 20:45:50.476261: train_loss -0.7613 +2024-11-21 20:45:50.483465: val_loss -0.7566 +2024-11-21 20:45:50.483593: Pseudo dice [0.8444] +2024-11-21 20:45:50.483677: Epoch time: 18.8 s +2024-11-21 20:45:51.312741: +2024-11-21 20:45:51.312930: Epoch 1806 +2024-11-21 20:45:51.313055: Current learning rate: 0.00794 +2024-11-21 20:46:10.145022: train_loss -0.7625 +2024-11-21 20:46:10.147608: val_loss -0.7481 +2024-11-21 20:46:10.147761: Pseudo dice [0.8402] +2024-11-21 20:46:10.147891: Epoch time: 18.83 s +2024-11-21 20:46:11.015489: +2024-11-21 20:46:11.015785: Epoch 1807 +2024-11-21 20:46:11.015913: Current learning rate: 0.00794 +2024-11-21 20:46:29.815802: train_loss -0.7577 +2024-11-21 20:46:29.821106: val_loss -0.758 +2024-11-21 20:46:29.821235: Pseudo dice [0.8595] +2024-11-21 20:46:29.821346: Epoch time: 18.8 s +2024-11-21 20:46:30.889761: +2024-11-21 20:46:30.890044: Epoch 1808 +2024-11-21 20:46:30.890187: Current learning rate: 0.00794 +2024-11-21 20:46:49.998641: train_loss -0.7691 +2024-11-21 20:46:50.003332: val_loss -0.771 +2024-11-21 20:46:50.003454: Pseudo dice [0.8476] +2024-11-21 20:46:50.003564: Epoch time: 19.11 s +2024-11-21 20:46:50.998766: +2024-11-21 20:46:50.999008: Epoch 1809 +2024-11-21 20:46:50.999129: Current learning rate: 0.00794 +2024-11-21 20:47:11.156508: train_loss -0.7633 +2024-11-21 20:47:11.163644: val_loss -0.7402 +2024-11-21 20:47:11.163759: Pseudo dice [0.84] +2024-11-21 20:47:11.163844: Epoch time: 20.16 s +2024-11-21 20:47:12.032253: +2024-11-21 20:47:12.032493: Epoch 1810 +2024-11-21 20:47:12.032623: Current learning rate: 0.00794 +2024-11-21 20:47:31.175039: train_loss -0.7603 +2024-11-21 20:47:31.177852: val_loss -0.7712 +2024-11-21 20:47:31.177962: Pseudo dice [0.8591] +2024-11-21 20:47:31.178043: Epoch time: 19.14 s +2024-11-21 20:47:32.004970: +2024-11-21 20:47:32.005200: Epoch 1811 +2024-11-21 20:47:32.005337: Current learning rate: 0.00794 +2024-11-21 20:47:53.225113: train_loss -0.7532 +2024-11-21 20:47:53.230682: val_loss -0.7793 +2024-11-21 20:47:53.230801: Pseudo dice [0.8506] +2024-11-21 20:47:53.230910: Epoch time: 21.22 s +2024-11-21 20:47:54.057909: +2024-11-21 20:47:54.058135: Epoch 1812 +2024-11-21 20:47:54.058249: Current learning rate: 0.00794 +2024-11-21 20:48:13.769852: train_loss -0.7698 +2024-11-21 20:48:13.774084: val_loss -0.7743 +2024-11-21 20:48:13.774200: Pseudo dice [0.8474] +2024-11-21 20:48:13.774297: Epoch time: 19.71 s +2024-11-21 20:48:14.598049: +2024-11-21 20:48:14.598245: Epoch 1813 +2024-11-21 20:48:14.598377: Current learning rate: 0.00794 +2024-11-21 20:48:34.575933: train_loss -0.7576 +2024-11-21 20:48:34.581103: val_loss -0.7684 +2024-11-21 20:48:34.581235: Pseudo dice [0.837] +2024-11-21 20:48:34.581343: Epoch time: 19.98 s +2024-11-21 20:48:35.491895: +2024-11-21 20:48:35.492099: Epoch 1814 +2024-11-21 20:48:35.492227: Current learning rate: 0.00793 +2024-11-21 20:48:54.671365: train_loss -0.7679 +2024-11-21 20:48:54.678389: val_loss -0.7812 +2024-11-21 20:48:54.679080: Pseudo dice [0.8576] +2024-11-21 20:48:54.679183: Epoch time: 19.18 s +2024-11-21 20:48:55.550677: +2024-11-21 20:48:55.550894: Epoch 1815 +2024-11-21 20:48:55.551025: Current learning rate: 0.00793 +2024-11-21 20:49:14.123920: train_loss -0.7596 +2024-11-21 20:49:14.131482: val_loss -0.7544 +2024-11-21 20:49:14.131607: Pseudo dice [0.8399] +2024-11-21 20:49:14.131707: Epoch time: 18.57 s +2024-11-21 20:49:15.183108: +2024-11-21 20:49:15.183316: Epoch 1816 +2024-11-21 20:49:15.183435: Current learning rate: 0.00793 +2024-11-21 20:49:34.425613: train_loss -0.7674 +2024-11-21 20:49:34.435189: val_loss -0.7472 +2024-11-21 20:49:34.435338: Pseudo dice [0.8379] +2024-11-21 20:49:34.435428: Epoch time: 19.24 s +2024-11-21 20:49:35.515745: +2024-11-21 20:49:35.515953: Epoch 1817 +2024-11-21 20:49:35.516084: Current learning rate: 0.00793 +2024-11-21 20:49:54.309039: train_loss -0.7682 +2024-11-21 20:49:54.319702: val_loss -0.7614 +2024-11-21 20:49:54.319852: Pseudo dice [0.8508] +2024-11-21 20:49:54.319950: Epoch time: 18.79 s +2024-11-21 20:49:55.558139: +2024-11-21 20:49:55.558364: Epoch 1818 +2024-11-21 20:49:55.558484: Current learning rate: 0.00793 +2024-11-21 20:50:15.463937: train_loss -0.7595 +2024-11-21 20:50:15.473400: val_loss -0.7596 +2024-11-21 20:50:15.473548: Pseudo dice [0.8478] +2024-11-21 20:50:15.473674: Epoch time: 19.91 s +2024-11-21 20:50:16.351383: +2024-11-21 20:50:16.351581: Epoch 1819 +2024-11-21 20:50:16.351713: Current learning rate: 0.00793 +2024-11-21 20:50:35.494134: train_loss -0.7665 +2024-11-21 20:50:35.496389: val_loss -0.7601 +2024-11-21 20:50:35.496493: Pseudo dice [0.8442] +2024-11-21 20:50:35.496580: Epoch time: 19.14 s +2024-11-21 20:50:36.324008: +2024-11-21 20:50:36.324243: Epoch 1820 +2024-11-21 20:50:36.324359: Current learning rate: 0.00793 +2024-11-21 20:50:55.069327: train_loss -0.76 +2024-11-21 20:50:55.075533: val_loss -0.7473 +2024-11-21 20:50:55.075682: Pseudo dice [0.8455] +2024-11-21 20:50:55.075797: Epoch time: 18.75 s +2024-11-21 20:50:56.060932: +2024-11-21 20:50:56.061181: Epoch 1821 +2024-11-21 20:50:56.061311: Current learning rate: 0.00793 +2024-11-21 20:51:14.195756: train_loss -0.7462 +2024-11-21 20:51:14.203624: val_loss -0.7579 +2024-11-21 20:51:14.203813: Pseudo dice [0.8374] +2024-11-21 20:51:14.203905: Epoch time: 18.14 s +2024-11-21 20:51:15.035922: +2024-11-21 20:51:15.036153: Epoch 1822 +2024-11-21 20:51:15.036276: Current learning rate: 0.00792 +2024-11-21 20:51:32.980187: train_loss -0.7744 +2024-11-21 20:51:32.984162: val_loss -0.7541 +2024-11-21 20:51:32.984277: Pseudo dice [0.8553] +2024-11-21 20:51:32.984387: Epoch time: 17.95 s +2024-11-21 20:51:33.815730: +2024-11-21 20:51:33.815969: Epoch 1823 +2024-11-21 20:51:33.816114: Current learning rate: 0.00792 +2024-11-21 20:51:53.777134: train_loss -0.7678 +2024-11-21 20:51:53.781914: val_loss -0.7634 +2024-11-21 20:51:53.782048: Pseudo dice [0.8409] +2024-11-21 20:51:53.782185: Epoch time: 19.96 s +2024-11-21 20:51:54.607321: +2024-11-21 20:51:54.607737: Epoch 1824 +2024-11-21 20:51:54.607888: Current learning rate: 0.00792 +2024-11-21 20:52:13.508036: train_loss -0.7639 +2024-11-21 20:52:13.516705: val_loss -0.7563 +2024-11-21 20:52:13.516913: Pseudo dice [0.8464] +2024-11-21 20:52:13.517012: Epoch time: 18.9 s +2024-11-21 20:52:14.704758: +2024-11-21 20:52:14.704970: Epoch 1825 +2024-11-21 20:52:14.705097: Current learning rate: 0.00792 +2024-11-21 20:52:34.514494: train_loss -0.7614 +2024-11-21 20:52:34.518690: val_loss -0.7601 +2024-11-21 20:52:34.518831: Pseudo dice [0.8528] +2024-11-21 20:52:34.518925: Epoch time: 19.81 s +2024-11-21 20:52:35.420028: +2024-11-21 20:52:35.420291: Epoch 1826 +2024-11-21 20:52:35.420410: Current learning rate: 0.00792 +2024-11-21 20:52:54.301936: train_loss -0.7734 +2024-11-21 20:52:54.311796: val_loss -0.7557 +2024-11-21 20:52:54.311949: Pseudo dice [0.8502] +2024-11-21 20:52:54.312063: Epoch time: 18.88 s +2024-11-21 20:52:55.145949: +2024-11-21 20:52:55.146138: Epoch 1827 +2024-11-21 20:52:55.146255: Current learning rate: 0.00792 +2024-11-21 20:53:13.799440: train_loss -0.7677 +2024-11-21 20:53:13.804270: val_loss -0.7611 +2024-11-21 20:53:13.804415: Pseudo dice [0.8452] +2024-11-21 20:53:13.804515: Epoch time: 18.65 s +2024-11-21 20:53:14.660361: +2024-11-21 20:53:14.660559: Epoch 1828 +2024-11-21 20:53:14.660675: Current learning rate: 0.00792 +2024-11-21 20:53:33.741468: train_loss -0.7738 +2024-11-21 20:53:33.749404: val_loss -0.7643 +2024-11-21 20:53:33.749529: Pseudo dice [0.8557] +2024-11-21 20:53:33.749619: Epoch time: 19.08 s +2024-11-21 20:53:35.233908: +2024-11-21 20:53:35.234125: Epoch 1829 +2024-11-21 20:53:35.234258: Current learning rate: 0.00792 +2024-11-21 20:53:54.480010: train_loss -0.7658 +2024-11-21 20:53:54.482589: val_loss -0.7637 +2024-11-21 20:53:54.482704: Pseudo dice [0.8523] +2024-11-21 20:53:54.482810: Epoch time: 19.25 s +2024-11-21 20:53:55.324780: +2024-11-21 20:53:55.325019: Epoch 1830 +2024-11-21 20:53:55.325144: Current learning rate: 0.00792 +2024-11-21 20:54:14.543329: train_loss -0.7708 +2024-11-21 20:54:14.551832: val_loss -0.7682 +2024-11-21 20:54:14.552017: Pseudo dice [0.8569] +2024-11-21 20:54:14.552114: Epoch time: 19.22 s +2024-11-21 20:54:15.544125: +2024-11-21 20:54:15.544336: Epoch 1831 +2024-11-21 20:54:15.544453: Current learning rate: 0.00791 +2024-11-21 20:54:34.765321: train_loss -0.7557 +2024-11-21 20:54:34.773087: val_loss -0.7503 +2024-11-21 20:54:34.773223: Pseudo dice [0.8441] +2024-11-21 20:54:34.773322: Epoch time: 19.22 s +2024-11-21 20:54:35.630127: +2024-11-21 20:54:35.630332: Epoch 1832 +2024-11-21 20:54:35.630453: Current learning rate: 0.00791 +2024-11-21 20:54:55.821728: train_loss -0.7691 +2024-11-21 20:54:55.828377: val_loss -0.7703 +2024-11-21 20:54:55.828514: Pseudo dice [0.8535] +2024-11-21 20:54:55.828606: Epoch time: 20.19 s +2024-11-21 20:54:56.708161: +2024-11-21 20:54:56.708364: Epoch 1833 +2024-11-21 20:54:56.708487: Current learning rate: 0.00791 +2024-11-21 20:55:15.487343: train_loss -0.7589 +2024-11-21 20:55:15.500931: val_loss -0.7591 +2024-11-21 20:55:15.501094: Pseudo dice [0.847] +2024-11-21 20:55:15.501207: Epoch time: 18.78 s +2024-11-21 20:55:16.481490: +2024-11-21 20:55:16.481732: Epoch 1834 +2024-11-21 20:55:16.481863: Current learning rate: 0.00791 +2024-11-21 20:55:35.412584: train_loss -0.764 +2024-11-21 20:55:35.416846: val_loss -0.727 +2024-11-21 20:55:35.417005: Pseudo dice [0.8452] +2024-11-21 20:55:35.417119: Epoch time: 18.93 s +2024-11-21 20:55:36.243989: +2024-11-21 20:55:36.244192: Epoch 1835 +2024-11-21 20:55:36.244312: Current learning rate: 0.00791 +2024-11-21 20:55:54.838515: train_loss -0.771 +2024-11-21 20:55:54.840901: val_loss -0.7665 +2024-11-21 20:55:54.841008: Pseudo dice [0.8457] +2024-11-21 20:55:54.841102: Epoch time: 18.6 s +2024-11-21 20:55:55.661824: +2024-11-21 20:55:55.662028: Epoch 1836 +2024-11-21 20:55:55.662160: Current learning rate: 0.00791 +2024-11-21 20:56:15.044177: train_loss -0.7769 +2024-11-21 20:56:15.048344: val_loss -0.7697 +2024-11-21 20:56:15.048504: Pseudo dice [0.8604] +2024-11-21 20:56:15.048616: Epoch time: 19.38 s +2024-11-21 20:56:15.880411: +2024-11-21 20:56:15.880626: Epoch 1837 +2024-11-21 20:56:15.880754: Current learning rate: 0.00791 +2024-11-21 20:56:35.783020: train_loss -0.7666 +2024-11-21 20:56:35.796194: val_loss -0.7655 +2024-11-21 20:56:35.796376: Pseudo dice [0.852] +2024-11-21 20:56:35.796470: Epoch time: 19.9 s +2024-11-21 20:56:35.796550: Yayy! New best EMA pseudo Dice: 0.8495 +2024-11-21 20:56:36.854156: +2024-11-21 20:56:36.854351: Epoch 1838 +2024-11-21 20:56:36.854474: Current learning rate: 0.00791 +2024-11-21 20:56:56.539462: train_loss -0.7719 +2024-11-21 20:56:56.546298: val_loss -0.7567 +2024-11-21 20:56:56.546442: Pseudo dice [0.8373] +2024-11-21 20:56:56.546562: Epoch time: 19.69 s +2024-11-21 20:56:57.370760: +2024-11-21 20:56:57.370978: Epoch 1839 +2024-11-21 20:56:57.371119: Current learning rate: 0.00791 +2024-11-21 20:57:16.577824: train_loss -0.7579 +2024-11-21 20:57:16.588431: val_loss -0.7719 +2024-11-21 20:57:16.588590: Pseudo dice [0.8439] +2024-11-21 20:57:16.588899: Epoch time: 19.21 s +2024-11-21 20:57:17.541566: +2024-11-21 20:57:17.541781: Epoch 1840 +2024-11-21 20:57:17.541914: Current learning rate: 0.0079 +2024-11-21 20:57:37.016527: train_loss -0.7555 +2024-11-21 20:57:37.025119: val_loss -0.722 +2024-11-21 20:57:37.025262: Pseudo dice [0.8294] +2024-11-21 20:57:37.025355: Epoch time: 19.48 s +2024-11-21 20:57:38.268570: +2024-11-21 20:57:38.268804: Epoch 1841 +2024-11-21 20:57:38.268926: Current learning rate: 0.0079 +2024-11-21 20:57:58.054550: train_loss -0.7521 +2024-11-21 20:57:58.056953: val_loss -0.728 +2024-11-21 20:57:58.057051: Pseudo dice [0.8364] +2024-11-21 20:57:58.057145: Epoch time: 19.79 s +2024-11-21 20:57:58.882082: +2024-11-21 20:57:58.882318: Epoch 1842 +2024-11-21 20:57:58.882442: Current learning rate: 0.0079 +2024-11-21 20:58:17.728502: train_loss -0.7621 +2024-11-21 20:58:17.733204: val_loss -0.7673 +2024-11-21 20:58:17.733340: Pseudo dice [0.8459] +2024-11-21 20:58:17.733448: Epoch time: 18.85 s +2024-11-21 20:58:18.706353: +2024-11-21 20:58:18.706577: Epoch 1843 +2024-11-21 20:58:18.706698: Current learning rate: 0.0079 +2024-11-21 20:58:36.120124: train_loss -0.7633 +2024-11-21 20:58:36.129557: val_loss -0.7738 +2024-11-21 20:58:36.129704: Pseudo dice [0.8544] +2024-11-21 20:58:36.129810: Epoch time: 17.41 s +2024-11-21 20:58:37.223657: +2024-11-21 20:58:37.223864: Epoch 1844 +2024-11-21 20:58:37.223978: Current learning rate: 0.0079 +2024-11-21 20:58:55.945369: train_loss -0.7672 +2024-11-21 20:58:55.953369: val_loss -0.7776 +2024-11-21 20:58:55.953498: Pseudo dice [0.8503] +2024-11-21 20:58:55.953597: Epoch time: 18.72 s +2024-11-21 20:58:56.840155: +2024-11-21 20:58:56.840353: Epoch 1845 +2024-11-21 20:58:56.840482: Current learning rate: 0.0079 +2024-11-21 20:59:15.592690: train_loss -0.7618 +2024-11-21 20:59:15.595301: val_loss -0.7892 +2024-11-21 20:59:15.595436: Pseudo dice [0.8461] +2024-11-21 20:59:15.595524: Epoch time: 18.75 s +2024-11-21 20:59:16.525490: +2024-11-21 20:59:16.525757: Epoch 1846 +2024-11-21 20:59:16.525886: Current learning rate: 0.0079 +2024-11-21 20:59:36.142638: train_loss -0.7676 +2024-11-21 20:59:36.146844: val_loss -0.7837 +2024-11-21 20:59:36.147002: Pseudo dice [0.8429] +2024-11-21 20:59:36.147271: Epoch time: 19.62 s +2024-11-21 20:59:36.976833: +2024-11-21 20:59:36.977036: Epoch 1847 +2024-11-21 20:59:36.977175: Current learning rate: 0.0079 +2024-11-21 20:59:55.416331: train_loss -0.7554 +2024-11-21 20:59:55.419259: val_loss -0.7314 +2024-11-21 20:59:55.419376: Pseudo dice [0.8173] +2024-11-21 20:59:55.419474: Epoch time: 18.44 s +2024-11-21 20:59:56.241722: +2024-11-21 20:59:56.241920: Epoch 1848 +2024-11-21 20:59:56.242058: Current learning rate: 0.00789 +2024-11-21 21:00:14.969744: train_loss -0.7526 +2024-11-21 21:00:14.977170: val_loss -0.7685 +2024-11-21 21:00:14.977300: Pseudo dice [0.8502] +2024-11-21 21:00:14.977385: Epoch time: 18.73 s +2024-11-21 21:00:15.835675: +2024-11-21 21:00:15.835881: Epoch 1849 +2024-11-21 21:00:15.836020: Current learning rate: 0.00789 +2024-11-21 21:00:34.135029: train_loss -0.7662 +2024-11-21 21:00:34.141716: val_loss -0.7612 +2024-11-21 21:00:34.141840: Pseudo dice [0.8484] +2024-11-21 21:00:34.142158: Epoch time: 18.3 s +2024-11-21 21:00:35.180489: +2024-11-21 21:00:35.180705: Epoch 1850 +2024-11-21 21:00:35.180834: Current learning rate: 0.00789 +2024-11-21 21:00:53.950471: train_loss -0.7615 +2024-11-21 21:00:53.957169: val_loss -0.7418 +2024-11-21 21:00:53.957306: Pseudo dice [0.8271] +2024-11-21 21:00:53.957417: Epoch time: 18.77 s +2024-11-21 21:00:54.787698: +2024-11-21 21:00:54.787940: Epoch 1851 +2024-11-21 21:00:54.788068: Current learning rate: 0.00789 +2024-11-21 21:01:13.485780: train_loss -0.7734 +2024-11-21 21:01:13.492200: val_loss -0.7309 +2024-11-21 21:01:13.492320: Pseudo dice [0.8378] +2024-11-21 21:01:13.492410: Epoch time: 18.7 s +2024-11-21 21:01:14.776833: +2024-11-21 21:01:14.777036: Epoch 1852 +2024-11-21 21:01:14.777156: Current learning rate: 0.00789 +2024-11-21 21:01:35.091066: train_loss -0.771 +2024-11-21 21:01:35.098492: val_loss -0.7531 +2024-11-21 21:01:35.098639: Pseudo dice [0.8527] +2024-11-21 21:01:35.098737: Epoch time: 20.32 s +2024-11-21 21:01:36.084659: +2024-11-21 21:01:36.084898: Epoch 1853 +2024-11-21 21:01:36.085016: Current learning rate: 0.00789 +2024-11-21 21:01:55.759483: train_loss -0.7389 +2024-11-21 21:01:55.766251: val_loss -0.7422 +2024-11-21 21:01:55.766387: Pseudo dice [0.8419] +2024-11-21 21:01:55.766495: Epoch time: 19.68 s +2024-11-21 21:01:56.607837: +2024-11-21 21:01:56.608054: Epoch 1854 +2024-11-21 21:01:56.608189: Current learning rate: 0.00789 +2024-11-21 21:02:15.556644: train_loss -0.7524 +2024-11-21 21:02:15.565140: val_loss -0.7583 +2024-11-21 21:02:15.565303: Pseudo dice [0.8382] +2024-11-21 21:02:15.565415: Epoch time: 18.95 s +2024-11-21 21:02:16.593355: +2024-11-21 21:02:16.593555: Epoch 1855 +2024-11-21 21:02:16.593671: Current learning rate: 0.00789 +2024-11-21 21:02:36.524388: train_loss -0.751 +2024-11-21 21:02:36.533222: val_loss -0.7699 +2024-11-21 21:02:36.533362: Pseudo dice [0.8519] +2024-11-21 21:02:36.533462: Epoch time: 19.93 s +2024-11-21 21:02:37.387837: +2024-11-21 21:02:37.388076: Epoch 1856 +2024-11-21 21:02:37.388204: Current learning rate: 0.00789 +2024-11-21 21:02:55.842182: train_loss -0.7619 +2024-11-21 21:02:55.850567: val_loss -0.7624 +2024-11-21 21:02:55.850732: Pseudo dice [0.8485] +2024-11-21 21:02:55.850844: Epoch time: 18.46 s +2024-11-21 21:02:56.811090: +2024-11-21 21:02:56.811288: Epoch 1857 +2024-11-21 21:02:56.811407: Current learning rate: 0.00788 +2024-11-21 21:03:15.005141: train_loss -0.7584 +2024-11-21 21:03:15.013017: val_loss -0.7674 +2024-11-21 21:03:15.013168: Pseudo dice [0.8435] +2024-11-21 21:03:15.013267: Epoch time: 18.19 s +2024-11-21 21:03:15.834710: +2024-11-21 21:03:15.834903: Epoch 1858 +2024-11-21 21:03:15.835033: Current learning rate: 0.00788 +2024-11-21 21:03:34.639366: train_loss -0.766 +2024-11-21 21:03:34.647467: val_loss -0.7742 +2024-11-21 21:03:34.647594: Pseudo dice [0.8453] +2024-11-21 21:03:34.647685: Epoch time: 18.81 s +2024-11-21 21:03:35.630889: +2024-11-21 21:03:35.631095: Epoch 1859 +2024-11-21 21:03:35.631223: Current learning rate: 0.00788 +2024-11-21 21:03:54.284405: train_loss -0.7506 +2024-11-21 21:03:54.293041: val_loss -0.7698 +2024-11-21 21:03:54.293244: Pseudo dice [0.8558] +2024-11-21 21:03:54.293340: Epoch time: 18.65 s +2024-11-21 21:03:55.131924: +2024-11-21 21:03:55.132144: Epoch 1860 +2024-11-21 21:03:55.132275: Current learning rate: 0.00788 +2024-11-21 21:04:14.832715: train_loss -0.7668 +2024-11-21 21:04:14.841100: val_loss -0.7647 +2024-11-21 21:04:14.841288: Pseudo dice [0.8488] +2024-11-21 21:04:14.841380: Epoch time: 19.7 s +2024-11-21 21:04:15.692255: +2024-11-21 21:04:15.692656: Epoch 1861 +2024-11-21 21:04:15.692804: Current learning rate: 0.00788 +2024-11-21 21:04:34.354590: train_loss -0.7688 +2024-11-21 21:04:34.362678: val_loss -0.7473 +2024-11-21 21:04:34.362806: Pseudo dice [0.8452] +2024-11-21 21:04:34.362915: Epoch time: 18.66 s +2024-11-21 21:04:35.289905: +2024-11-21 21:04:35.290096: Epoch 1862 +2024-11-21 21:04:35.290217: Current learning rate: 0.00788 +2024-11-21 21:04:54.037337: train_loss -0.7666 +2024-11-21 21:04:54.040114: val_loss -0.7327 +2024-11-21 21:04:54.040252: Pseudo dice [0.8617] +2024-11-21 21:04:54.040337: Epoch time: 18.75 s +2024-11-21 21:04:55.305985: +2024-11-21 21:04:55.306194: Epoch 1863 +2024-11-21 21:04:55.306315: Current learning rate: 0.00788 +2024-11-21 21:05:14.995764: train_loss -0.7664 +2024-11-21 21:05:15.003055: val_loss -0.7583 +2024-11-21 21:05:15.003188: Pseudo dice [0.8425] +2024-11-21 21:05:15.003290: Epoch time: 19.69 s +2024-11-21 21:05:15.838338: +2024-11-21 21:05:15.838564: Epoch 1864 +2024-11-21 21:05:15.838697: Current learning rate: 0.00788 +2024-11-21 21:05:34.711236: train_loss -0.7735 +2024-11-21 21:05:34.720350: val_loss -0.7741 +2024-11-21 21:05:34.720472: Pseudo dice [0.858] +2024-11-21 21:05:34.720568: Epoch time: 18.87 s +2024-11-21 21:05:35.562610: +2024-11-21 21:05:35.562873: Epoch 1865 +2024-11-21 21:05:35.563004: Current learning rate: 0.00788 +2024-11-21 21:05:54.701283: train_loss -0.7786 +2024-11-21 21:05:54.709349: val_loss -0.7753 +2024-11-21 21:05:54.709496: Pseudo dice [0.8383] +2024-11-21 21:05:54.709596: Epoch time: 19.14 s +2024-11-21 21:05:55.553281: +2024-11-21 21:05:55.553517: Epoch 1866 +2024-11-21 21:05:55.553629: Current learning rate: 0.00787 +2024-11-21 21:06:14.846407: train_loss -0.7735 +2024-11-21 21:06:14.852062: val_loss -0.7725 +2024-11-21 21:06:14.852161: Pseudo dice [0.8487] +2024-11-21 21:06:14.852264: Epoch time: 19.29 s +2024-11-21 21:06:15.676929: +2024-11-21 21:06:15.677131: Epoch 1867 +2024-11-21 21:06:15.677251: Current learning rate: 0.00787 +2024-11-21 21:06:35.576666: train_loss -0.7654 +2024-11-21 21:06:35.595785: val_loss -0.7613 +2024-11-21 21:06:35.595937: Pseudo dice [0.8333] +2024-11-21 21:06:35.596026: Epoch time: 19.9 s +2024-11-21 21:06:36.640089: +2024-11-21 21:06:36.640306: Epoch 1868 +2024-11-21 21:06:36.640424: Current learning rate: 0.00787 +2024-11-21 21:06:55.870616: train_loss -0.7653 +2024-11-21 21:06:55.879777: val_loss -0.7637 +2024-11-21 21:06:55.879920: Pseudo dice [0.8496] +2024-11-21 21:06:55.880011: Epoch time: 19.23 s +2024-11-21 21:06:56.753925: +2024-11-21 21:06:56.754223: Epoch 1869 +2024-11-21 21:06:56.754345: Current learning rate: 0.00787 +2024-11-21 21:07:15.666632: train_loss -0.768 +2024-11-21 21:07:15.670124: val_loss -0.7782 +2024-11-21 21:07:15.670241: Pseudo dice [0.8575] +2024-11-21 21:07:15.670424: Epoch time: 18.91 s +2024-11-21 21:07:16.501107: +2024-11-21 21:07:16.501339: Epoch 1870 +2024-11-21 21:07:16.501475: Current learning rate: 0.00787 +2024-11-21 21:07:34.919748: train_loss -0.7622 +2024-11-21 21:07:34.925179: val_loss -0.7543 +2024-11-21 21:07:34.925323: Pseudo dice [0.8564] +2024-11-21 21:07:34.925421: Epoch time: 18.42 s +2024-11-21 21:07:35.855697: +2024-11-21 21:07:35.855909: Epoch 1871 +2024-11-21 21:07:35.856037: Current learning rate: 0.00787 +2024-11-21 21:07:54.889543: train_loss -0.7685 +2024-11-21 21:07:54.895717: val_loss -0.7634 +2024-11-21 21:07:54.895853: Pseudo dice [0.8401] +2024-11-21 21:07:54.895964: Epoch time: 19.03 s +2024-11-21 21:07:55.840167: +2024-11-21 21:07:55.840400: Epoch 1872 +2024-11-21 21:07:55.840534: Current learning rate: 0.00787 +2024-11-21 21:08:14.497039: train_loss -0.7541 +2024-11-21 21:08:14.503687: val_loss -0.7593 +2024-11-21 21:08:14.503834: Pseudo dice [0.8445] +2024-11-21 21:08:14.503939: Epoch time: 18.66 s +2024-11-21 21:08:15.346126: +2024-11-21 21:08:15.346367: Epoch 1873 +2024-11-21 21:08:15.346487: Current learning rate: 0.00787 +2024-11-21 21:08:34.715088: train_loss -0.7641 +2024-11-21 21:08:34.721539: val_loss -0.7565 +2024-11-21 21:08:34.721696: Pseudo dice [0.8306] +2024-11-21 21:08:34.721797: Epoch time: 19.37 s +2024-11-21 21:08:35.636487: +2024-11-21 21:08:35.636711: Epoch 1874 +2024-11-21 21:08:35.636848: Current learning rate: 0.00786 +2024-11-21 21:08:54.280258: train_loss -0.7508 +2024-11-21 21:08:54.286360: val_loss -0.7491 +2024-11-21 21:08:54.286506: Pseudo dice [0.8307] +2024-11-21 21:08:54.286598: Epoch time: 18.64 s +2024-11-21 21:08:55.587198: +2024-11-21 21:08:55.587438: Epoch 1875 +2024-11-21 21:08:55.587581: Current learning rate: 0.00786 +2024-11-21 21:09:15.127667: train_loss -0.7262 +2024-11-21 21:09:15.153280: val_loss -0.7659 +2024-11-21 21:09:15.153778: Pseudo dice [0.8395] +2024-11-21 21:09:15.153890: Epoch time: 19.54 s +2024-11-21 21:09:16.023416: +2024-11-21 21:09:16.023705: Epoch 1876 +2024-11-21 21:09:16.023839: Current learning rate: 0.00786 +2024-11-21 21:09:34.644425: train_loss -0.7428 +2024-11-21 21:09:34.646900: val_loss -0.7355 +2024-11-21 21:09:34.646992: Pseudo dice [0.8404] +2024-11-21 21:09:34.647083: Epoch time: 18.62 s +2024-11-21 21:09:35.472670: +2024-11-21 21:09:35.472926: Epoch 1877 +2024-11-21 21:09:35.473047: Current learning rate: 0.00786 +2024-11-21 21:09:55.317199: train_loss -0.7529 +2024-11-21 21:09:55.324704: val_loss -0.7728 +2024-11-21 21:09:55.324821: Pseudo dice [0.846] +2024-11-21 21:09:55.324971: Epoch time: 19.85 s +2024-11-21 21:09:56.273296: +2024-11-21 21:09:56.273517: Epoch 1878 +2024-11-21 21:09:56.273646: Current learning rate: 0.00786 +2024-11-21 21:10:15.649663: train_loss -0.7531 +2024-11-21 21:10:15.652578: val_loss -0.7759 +2024-11-21 21:10:15.652683: Pseudo dice [0.8473] +2024-11-21 21:10:15.652783: Epoch time: 19.38 s +2024-11-21 21:10:16.484076: +2024-11-21 21:10:16.484299: Epoch 1879 +2024-11-21 21:10:16.484426: Current learning rate: 0.00786 +2024-11-21 21:10:34.874778: train_loss -0.765 +2024-11-21 21:10:34.883873: val_loss -0.7698 +2024-11-21 21:10:34.884030: Pseudo dice [0.8541] +2024-11-21 21:10:34.884150: Epoch time: 18.39 s +2024-11-21 21:10:35.715695: +2024-11-21 21:10:35.715915: Epoch 1880 +2024-11-21 21:10:35.716040: Current learning rate: 0.00786 +2024-11-21 21:10:55.021047: train_loss -0.7604 +2024-11-21 21:10:55.026006: val_loss -0.7559 +2024-11-21 21:10:55.026142: Pseudo dice [0.8448] +2024-11-21 21:10:55.026237: Epoch time: 19.31 s +2024-11-21 21:10:55.851088: +2024-11-21 21:10:55.851289: Epoch 1881 +2024-11-21 21:10:55.851425: Current learning rate: 0.00786 +2024-11-21 21:11:15.170145: train_loss -0.7681 +2024-11-21 21:11:15.177848: val_loss -0.7633 +2024-11-21 21:11:15.177994: Pseudo dice [0.8407] +2024-11-21 21:11:15.178111: Epoch time: 19.32 s +2024-11-21 21:11:16.032232: +2024-11-21 21:11:16.032449: Epoch 1882 +2024-11-21 21:11:16.032566: Current learning rate: 0.00786 +2024-11-21 21:11:34.904465: train_loss -0.7672 +2024-11-21 21:11:34.909270: val_loss -0.77 +2024-11-21 21:11:34.909387: Pseudo dice [0.8496] +2024-11-21 21:11:34.909482: Epoch time: 18.87 s +2024-11-21 21:11:35.791453: +2024-11-21 21:11:35.791656: Epoch 1883 +2024-11-21 21:11:35.791796: Current learning rate: 0.00785 +2024-11-21 21:11:55.447966: train_loss -0.7707 +2024-11-21 21:11:55.454154: val_loss -0.7802 +2024-11-21 21:11:55.454288: Pseudo dice [0.8534] +2024-11-21 21:11:55.454380: Epoch time: 19.66 s +2024-11-21 21:11:56.388488: +2024-11-21 21:11:56.388687: Epoch 1884 +2024-11-21 21:11:56.388820: Current learning rate: 0.00785 +2024-11-21 21:12:15.304565: train_loss -0.738 +2024-11-21 21:12:15.310028: val_loss -0.7505 +2024-11-21 21:12:15.310148: Pseudo dice [0.8174] +2024-11-21 21:12:15.310263: Epoch time: 18.92 s +2024-11-21 21:12:16.293083: +2024-11-21 21:12:16.293495: Epoch 1885 +2024-11-21 21:12:16.293633: Current learning rate: 0.00785 +2024-11-21 21:12:35.876549: train_loss -0.7373 +2024-11-21 21:12:35.882985: val_loss -0.7548 +2024-11-21 21:12:35.883143: Pseudo dice [0.8315] +2024-11-21 21:12:35.883233: Epoch time: 19.58 s +2024-11-21 21:12:37.119838: +2024-11-21 21:12:37.120062: Epoch 1886 +2024-11-21 21:12:37.120174: Current learning rate: 0.00785 +2024-11-21 21:12:56.609955: train_loss -0.7531 +2024-11-21 21:12:56.616798: val_loss -0.7766 +2024-11-21 21:12:56.616947: Pseudo dice [0.8553] +2024-11-21 21:12:56.617043: Epoch time: 19.49 s +2024-11-21 21:12:57.556535: +2024-11-21 21:12:57.556771: Epoch 1887 +2024-11-21 21:12:57.556885: Current learning rate: 0.00785 +2024-11-21 21:13:16.011850: train_loss -0.7566 +2024-11-21 21:13:16.019592: val_loss -0.7787 +2024-11-21 21:13:16.019723: Pseudo dice [0.8551] +2024-11-21 21:13:16.019813: Epoch time: 18.46 s +2024-11-21 21:13:16.942942: +2024-11-21 21:13:16.943184: Epoch 1888 +2024-11-21 21:13:16.943305: Current learning rate: 0.00785 +2024-11-21 21:13:35.914737: train_loss -0.7609 +2024-11-21 21:13:35.917808: val_loss -0.7751 +2024-11-21 21:13:35.917965: Pseudo dice [0.8488] +2024-11-21 21:13:35.918118: Epoch time: 18.97 s +2024-11-21 21:13:36.795192: +2024-11-21 21:13:36.795434: Epoch 1889 +2024-11-21 21:13:36.795574: Current learning rate: 0.00785 +2024-11-21 21:13:55.840736: train_loss -0.7713 +2024-11-21 21:13:55.859415: val_loss -0.7707 +2024-11-21 21:13:55.859566: Pseudo dice [0.841] +2024-11-21 21:13:55.859662: Epoch time: 19.05 s +2024-11-21 21:13:56.791777: +2024-11-21 21:13:56.791991: Epoch 1890 +2024-11-21 21:13:56.792125: Current learning rate: 0.00785 +2024-11-21 21:14:15.899682: train_loss -0.7664 +2024-11-21 21:14:15.902126: val_loss -0.7591 +2024-11-21 21:14:15.920293: Pseudo dice [0.8444] +2024-11-21 21:14:15.920483: Epoch time: 19.11 s +2024-11-21 21:14:16.830390: +2024-11-21 21:14:16.830599: Epoch 1891 +2024-11-21 21:14:16.830722: Current learning rate: 0.00784 +2024-11-21 21:14:36.393425: train_loss -0.7666 +2024-11-21 21:14:36.399645: val_loss -0.7682 +2024-11-21 21:14:36.399787: Pseudo dice [0.8454] +2024-11-21 21:14:36.399879: Epoch time: 19.56 s +2024-11-21 21:14:37.288797: +2024-11-21 21:14:37.289021: Epoch 1892 +2024-11-21 21:14:37.289147: Current learning rate: 0.00784 +2024-11-21 21:14:55.256831: train_loss -0.767 +2024-11-21 21:14:55.261590: val_loss -0.7719 +2024-11-21 21:14:55.261722: Pseudo dice [0.8347] +2024-11-21 21:14:55.261829: Epoch time: 17.97 s +2024-11-21 21:14:56.268346: +2024-11-21 21:14:56.268553: Epoch 1893 +2024-11-21 21:14:56.268669: Current learning rate: 0.00784 +2024-11-21 21:15:16.193240: train_loss -0.7693 +2024-11-21 21:15:16.200376: val_loss -0.7677 +2024-11-21 21:15:16.200528: Pseudo dice [0.843] +2024-11-21 21:15:16.200631: Epoch time: 19.93 s +2024-11-21 21:15:17.212138: +2024-11-21 21:15:17.212373: Epoch 1894 +2024-11-21 21:15:17.212489: Current learning rate: 0.00784 +2024-11-21 21:15:36.057939: train_loss -0.7608 +2024-11-21 21:15:36.065041: val_loss -0.7567 +2024-11-21 21:15:36.065180: Pseudo dice [0.8394] +2024-11-21 21:15:36.065279: Epoch time: 18.85 s +2024-11-21 21:15:36.973152: +2024-11-21 21:15:36.973346: Epoch 1895 +2024-11-21 21:15:36.973456: Current learning rate: 0.00784 +2024-11-21 21:15:56.372835: train_loss -0.7733 +2024-11-21 21:15:56.379984: val_loss -0.7825 +2024-11-21 21:15:56.380127: Pseudo dice [0.8536] +2024-11-21 21:15:56.380218: Epoch time: 19.4 s +2024-11-21 21:15:57.257267: +2024-11-21 21:15:57.257479: Epoch 1896 +2024-11-21 21:15:57.257621: Current learning rate: 0.00784 +2024-11-21 21:16:16.584640: train_loss -0.7726 +2024-11-21 21:16:16.593098: val_loss -0.7793 +2024-11-21 21:16:16.593309: Pseudo dice [0.8546] +2024-11-21 21:16:16.593418: Epoch time: 19.33 s +2024-11-21 21:16:17.453002: +2024-11-21 21:16:17.453200: Epoch 1897 +2024-11-21 21:16:17.453312: Current learning rate: 0.00784 +2024-11-21 21:16:36.173530: train_loss -0.7736 +2024-11-21 21:16:36.179766: val_loss -0.7569 +2024-11-21 21:16:36.179915: Pseudo dice [0.8428] +2024-11-21 21:16:36.180026: Epoch time: 18.72 s +2024-11-21 21:16:37.449296: +2024-11-21 21:16:37.449521: Epoch 1898 +2024-11-21 21:16:37.449644: Current learning rate: 0.00784 +2024-11-21 21:16:56.876705: train_loss -0.7697 +2024-11-21 21:16:56.890795: val_loss -0.7844 +2024-11-21 21:16:56.890960: Pseudo dice [0.859] +2024-11-21 21:16:56.891071: Epoch time: 19.43 s +2024-11-21 21:16:57.730614: +2024-11-21 21:16:57.730841: Epoch 1899 +2024-11-21 21:16:57.730953: Current learning rate: 0.00784 +2024-11-21 21:17:16.821810: train_loss -0.7651 +2024-11-21 21:17:16.828902: val_loss -0.7516 +2024-11-21 21:17:16.837333: Pseudo dice [0.8364] +2024-11-21 21:17:16.837438: Epoch time: 19.09 s +2024-11-21 21:17:18.008329: +2024-11-21 21:17:18.008558: Epoch 1900 +2024-11-21 21:17:18.008680: Current learning rate: 0.00783 +2024-11-21 21:17:37.128468: train_loss -0.777 +2024-11-21 21:17:37.134172: val_loss -0.7562 +2024-11-21 21:17:37.134319: Pseudo dice [0.8612] +2024-11-21 21:17:37.134413: Epoch time: 19.12 s +2024-11-21 21:17:38.010139: +2024-11-21 21:17:38.010458: Epoch 1901 +2024-11-21 21:17:38.010631: Current learning rate: 0.00783 +2024-11-21 21:17:57.043030: train_loss -0.7673 +2024-11-21 21:17:57.052906: val_loss -0.7716 +2024-11-21 21:17:57.053361: Pseudo dice [0.8448] +2024-11-21 21:17:57.053479: Epoch time: 19.03 s +2024-11-21 21:17:57.896525: +2024-11-21 21:17:57.896720: Epoch 1902 +2024-11-21 21:17:57.896848: Current learning rate: 0.00783 +2024-11-21 21:18:18.285772: train_loss -0.7693 +2024-11-21 21:18:18.291755: val_loss -0.7736 +2024-11-21 21:18:18.291873: Pseudo dice [0.8436] +2024-11-21 21:18:18.291980: Epoch time: 20.39 s +2024-11-21 21:18:19.127819: +2024-11-21 21:18:19.128040: Epoch 1903 +2024-11-21 21:18:19.128169: Current learning rate: 0.00783 +2024-11-21 21:18:38.812549: train_loss -0.7654 +2024-11-21 21:18:38.825377: val_loss -0.7475 +2024-11-21 21:18:38.825533: Pseudo dice [0.8535] +2024-11-21 21:18:38.825645: Epoch time: 19.69 s +2024-11-21 21:18:39.791472: +2024-11-21 21:18:39.791681: Epoch 1904 +2024-11-21 21:18:39.791798: Current learning rate: 0.00783 +2024-11-21 21:18:58.395401: train_loss -0.7606 +2024-11-21 21:18:58.403155: val_loss -0.7419 +2024-11-21 21:18:58.403298: Pseudo dice [0.845] +2024-11-21 21:18:58.403399: Epoch time: 18.6 s +2024-11-21 21:18:59.250543: +2024-11-21 21:18:59.250730: Epoch 1905 +2024-11-21 21:18:59.250871: Current learning rate: 0.00783 +2024-11-21 21:19:17.501716: train_loss -0.7699 +2024-11-21 21:19:17.513763: val_loss -0.7795 +2024-11-21 21:19:17.513892: Pseudo dice [0.8468] +2024-11-21 21:19:17.514010: Epoch time: 18.25 s +2024-11-21 21:19:18.544670: +2024-11-21 21:19:18.544883: Epoch 1906 +2024-11-21 21:19:18.545003: Current learning rate: 0.00783 +2024-11-21 21:19:36.487938: train_loss -0.7747 +2024-11-21 21:19:36.498640: val_loss -0.7539 +2024-11-21 21:19:36.498801: Pseudo dice [0.8519] +2024-11-21 21:19:36.498896: Epoch time: 17.94 s +2024-11-21 21:19:37.462538: +2024-11-21 21:19:37.462765: Epoch 1907 +2024-11-21 21:19:37.462888: Current learning rate: 0.00783 +2024-11-21 21:19:55.961866: train_loss -0.7681 +2024-11-21 21:19:55.993200: val_loss -0.7379 +2024-11-21 21:19:55.993382: Pseudo dice [0.8526] +2024-11-21 21:19:55.993478: Epoch time: 18.5 s +2024-11-21 21:19:56.960149: +2024-11-21 21:19:56.960343: Epoch 1908 +2024-11-21 21:19:56.960463: Current learning rate: 0.00783 +2024-11-21 21:20:16.422031: train_loss -0.7658 +2024-11-21 21:20:16.428885: val_loss -0.7576 +2024-11-21 21:20:16.429028: Pseudo dice [0.837] +2024-11-21 21:20:16.429146: Epoch time: 19.46 s +2024-11-21 21:20:17.677135: +2024-11-21 21:20:17.677376: Epoch 1909 +2024-11-21 21:20:17.677512: Current learning rate: 0.00782 +2024-11-21 21:20:36.871722: train_loss -0.7737 +2024-11-21 21:20:36.878810: val_loss -0.766 +2024-11-21 21:20:36.878954: Pseudo dice [0.855] +2024-11-21 21:20:36.879036: Epoch time: 19.2 s +2024-11-21 21:20:37.732634: +2024-11-21 21:20:37.732867: Epoch 1910 +2024-11-21 21:20:37.732991: Current learning rate: 0.00782 +2024-11-21 21:20:55.433423: train_loss -0.7742 +2024-11-21 21:20:55.454521: val_loss -0.7725 +2024-11-21 21:20:55.454669: Pseudo dice [0.8414] +2024-11-21 21:20:55.454768: Epoch time: 17.7 s +2024-11-21 21:20:56.304030: +2024-11-21 21:20:56.304265: Epoch 1911 +2024-11-21 21:20:56.304395: Current learning rate: 0.00782 +2024-11-21 21:21:15.811977: train_loss -0.7655 +2024-11-21 21:21:15.816207: val_loss -0.7535 +2024-11-21 21:21:15.816325: Pseudo dice [0.8485] +2024-11-21 21:21:15.816410: Epoch time: 19.51 s +2024-11-21 21:21:16.817290: +2024-11-21 21:21:16.817516: Epoch 1912 +2024-11-21 21:21:16.817648: Current learning rate: 0.00782 +2024-11-21 21:21:35.490548: train_loss -0.7812 +2024-11-21 21:21:35.504811: val_loss -0.7719 +2024-11-21 21:21:35.504949: Pseudo dice [0.8352] +2024-11-21 21:21:35.505043: Epoch time: 18.67 s +2024-11-21 21:21:36.411484: +2024-11-21 21:21:36.411724: Epoch 1913 +2024-11-21 21:21:36.411867: Current learning rate: 0.00782 +2024-11-21 21:21:57.032835: train_loss -0.7718 +2024-11-21 21:21:57.036147: val_loss -0.7648 +2024-11-21 21:21:57.036259: Pseudo dice [0.8532] +2024-11-21 21:21:57.036352: Epoch time: 20.62 s +2024-11-21 21:21:57.873299: +2024-11-21 21:21:57.873533: Epoch 1914 +2024-11-21 21:21:57.873668: Current learning rate: 0.00782 +2024-11-21 21:22:16.623725: train_loss -0.7695 +2024-11-21 21:22:16.626063: val_loss -0.7809 +2024-11-21 21:22:16.626174: Pseudo dice [0.8393] +2024-11-21 21:22:16.626261: Epoch time: 18.75 s +2024-11-21 21:22:17.509230: +2024-11-21 21:22:17.509472: Epoch 1915 +2024-11-21 21:22:17.509594: Current learning rate: 0.00782 +2024-11-21 21:22:36.725219: train_loss -0.7784 +2024-11-21 21:22:36.731140: val_loss -0.777 +2024-11-21 21:22:36.731268: Pseudo dice [0.8631] +2024-11-21 21:22:36.731367: Epoch time: 19.22 s +2024-11-21 21:22:37.564322: +2024-11-21 21:22:37.564767: Epoch 1916 +2024-11-21 21:22:37.564907: Current learning rate: 0.00782 +2024-11-21 21:22:57.032207: train_loss -0.7754 +2024-11-21 21:22:57.043018: val_loss -0.7631 +2024-11-21 21:22:57.043183: Pseudo dice [0.8434] +2024-11-21 21:22:57.043284: Epoch time: 19.47 s +2024-11-21 21:22:58.005343: +2024-11-21 21:22:58.005548: Epoch 1917 +2024-11-21 21:22:58.005661: Current learning rate: 0.00781 +2024-11-21 21:23:17.398254: train_loss -0.7745 +2024-11-21 21:23:17.405562: val_loss -0.7778 +2024-11-21 21:23:17.405710: Pseudo dice [0.8419] +2024-11-21 21:23:17.405823: Epoch time: 19.39 s +2024-11-21 21:23:18.256066: +2024-11-21 21:23:18.256284: Epoch 1918 +2024-11-21 21:23:18.256421: Current learning rate: 0.00781 +2024-11-21 21:23:37.232454: train_loss -0.7597 +2024-11-21 21:23:37.241676: val_loss -0.7529 +2024-11-21 21:23:37.241813: Pseudo dice [0.846] +2024-11-21 21:23:37.241928: Epoch time: 18.98 s +2024-11-21 21:23:38.130951: +2024-11-21 21:23:38.131170: Epoch 1919 +2024-11-21 21:23:38.131288: Current learning rate: 0.00781 +2024-11-21 21:23:56.492126: train_loss -0.7779 +2024-11-21 21:23:56.495289: val_loss -0.7646 +2024-11-21 21:23:56.495401: Pseudo dice [0.8572] +2024-11-21 21:23:56.495495: Epoch time: 18.36 s +2024-11-21 21:23:57.710978: +2024-11-21 21:23:57.711198: Epoch 1920 +2024-11-21 21:23:57.711332: Current learning rate: 0.00781 +2024-11-21 21:24:15.746411: train_loss -0.7808 +2024-11-21 21:24:15.755498: val_loss -0.7699 +2024-11-21 21:24:15.755641: Pseudo dice [0.8523] +2024-11-21 21:24:15.755734: Epoch time: 18.04 s +2024-11-21 21:24:16.816531: +2024-11-21 21:24:16.816781: Epoch 1921 +2024-11-21 21:24:16.816923: Current learning rate: 0.00781 +2024-11-21 21:24:35.667096: train_loss -0.7794 +2024-11-21 21:24:35.675818: val_loss -0.7613 +2024-11-21 21:24:35.675929: Pseudo dice [0.8316] +2024-11-21 21:24:35.676024: Epoch time: 18.85 s +2024-11-21 21:24:36.507167: +2024-11-21 21:24:36.507394: Epoch 1922 +2024-11-21 21:24:36.507519: Current learning rate: 0.00781 +2024-11-21 21:24:54.609930: train_loss -0.774 +2024-11-21 21:24:54.629459: val_loss -0.75 +2024-11-21 21:24:54.629680: Pseudo dice [0.8328] +2024-11-21 21:24:54.629804: Epoch time: 18.1 s +2024-11-21 21:24:55.588828: +2024-11-21 21:24:55.589048: Epoch 1923 +2024-11-21 21:24:55.589189: Current learning rate: 0.00781 +2024-11-21 21:25:15.166773: train_loss -0.7737 +2024-11-21 21:25:15.171868: val_loss -0.7587 +2024-11-21 21:25:15.171997: Pseudo dice [0.8475] +2024-11-21 21:25:15.172085: Epoch time: 19.58 s +2024-11-21 21:25:16.030024: +2024-11-21 21:25:16.030259: Epoch 1924 +2024-11-21 21:25:16.030408: Current learning rate: 0.00781 +2024-11-21 21:25:35.917783: train_loss -0.7832 +2024-11-21 21:25:35.923642: val_loss -0.7522 +2024-11-21 21:25:35.923765: Pseudo dice [0.8372] +2024-11-21 21:25:35.923866: Epoch time: 19.89 s +2024-11-21 21:25:36.806923: +2024-11-21 21:25:36.807177: Epoch 1925 +2024-11-21 21:25:36.807300: Current learning rate: 0.00781 +2024-11-21 21:25:55.554012: train_loss -0.7642 +2024-11-21 21:25:55.556328: val_loss -0.7645 +2024-11-21 21:25:55.556427: Pseudo dice [0.8398] +2024-11-21 21:25:55.556511: Epoch time: 18.75 s +2024-11-21 21:25:56.391963: +2024-11-21 21:25:56.392200: Epoch 1926 +2024-11-21 21:25:56.392342: Current learning rate: 0.0078 +2024-11-21 21:26:15.093530: train_loss -0.7738 +2024-11-21 21:26:15.104914: val_loss -0.7683 +2024-11-21 21:26:15.105073: Pseudo dice [0.8476] +2024-11-21 21:26:15.105175: Epoch time: 18.7 s +2024-11-21 21:26:16.024504: +2024-11-21 21:26:16.024719: Epoch 1927 +2024-11-21 21:26:16.024833: Current learning rate: 0.0078 +2024-11-21 21:26:35.019732: train_loss -0.7776 +2024-11-21 21:26:35.027826: val_loss -0.7697 +2024-11-21 21:26:35.027978: Pseudo dice [0.847] +2024-11-21 21:26:35.028076: Epoch time: 19.0 s +2024-11-21 21:26:35.991142: +2024-11-21 21:26:35.991347: Epoch 1928 +2024-11-21 21:26:35.991476: Current learning rate: 0.0078 +2024-11-21 21:26:54.755081: train_loss -0.7751 +2024-11-21 21:26:54.761220: val_loss -0.77 +2024-11-21 21:26:54.761341: Pseudo dice [0.8521] +2024-11-21 21:26:54.761651: Epoch time: 18.76 s +2024-11-21 21:26:55.662640: +2024-11-21 21:26:55.662872: Epoch 1929 +2024-11-21 21:26:55.662995: Current learning rate: 0.0078 +2024-11-21 21:27:14.433340: train_loss -0.7789 +2024-11-21 21:27:14.439825: val_loss -0.7779 +2024-11-21 21:27:14.439974: Pseudo dice [0.8558] +2024-11-21 21:27:14.440076: Epoch time: 18.77 s +2024-11-21 21:27:15.462095: +2024-11-21 21:27:15.462326: Epoch 1930 +2024-11-21 21:27:15.462449: Current learning rate: 0.0078 +2024-11-21 21:27:33.623827: train_loss -0.778 +2024-11-21 21:27:33.627886: val_loss -0.7496 +2024-11-21 21:27:33.628039: Pseudo dice [0.8504] +2024-11-21 21:27:33.628148: Epoch time: 18.16 s +2024-11-21 21:27:34.892877: +2024-11-21 21:27:34.893157: Epoch 1931 +2024-11-21 21:27:34.893287: Current learning rate: 0.0078 +2024-11-21 21:27:54.019055: train_loss -0.7718 +2024-11-21 21:27:54.025260: val_loss -0.7556 +2024-11-21 21:27:54.025406: Pseudo dice [0.8392] +2024-11-21 21:27:54.025508: Epoch time: 19.13 s +2024-11-21 21:27:54.879265: +2024-11-21 21:27:54.879478: Epoch 1932 +2024-11-21 21:27:54.879596: Current learning rate: 0.0078 +2024-11-21 21:28:13.881890: train_loss -0.7781 +2024-11-21 21:28:13.890800: val_loss -0.7726 +2024-11-21 21:28:13.890936: Pseudo dice [0.8618] +2024-11-21 21:28:13.891034: Epoch time: 19.0 s +2024-11-21 21:28:14.723936: +2024-11-21 21:28:14.724164: Epoch 1933 +2024-11-21 21:28:14.724298: Current learning rate: 0.0078 +2024-11-21 21:28:34.251065: train_loss -0.7694 +2024-11-21 21:28:34.268141: val_loss -0.7473 +2024-11-21 21:28:34.268296: Pseudo dice [0.8469] +2024-11-21 21:28:34.268389: Epoch time: 19.53 s +2024-11-21 21:28:35.209587: +2024-11-21 21:28:35.209808: Epoch 1934 +2024-11-21 21:28:35.209928: Current learning rate: 0.0078 +2024-11-21 21:28:54.723989: train_loss -0.7591 +2024-11-21 21:28:54.732789: val_loss -0.7619 +2024-11-21 21:28:54.732978: Pseudo dice [0.8405] +2024-11-21 21:28:54.733080: Epoch time: 19.52 s +2024-11-21 21:28:55.592666: +2024-11-21 21:28:55.592873: Epoch 1935 +2024-11-21 21:28:55.592992: Current learning rate: 0.00779 +2024-11-21 21:29:13.206008: train_loss -0.7675 +2024-11-21 21:29:13.210544: val_loss -0.7506 +2024-11-21 21:29:13.210687: Pseudo dice [0.8385] +2024-11-21 21:29:13.210776: Epoch time: 17.61 s +2024-11-21 21:29:14.042828: +2024-11-21 21:29:14.043047: Epoch 1936 +2024-11-21 21:29:14.043187: Current learning rate: 0.00779 +2024-11-21 21:29:32.442441: train_loss -0.7691 +2024-11-21 21:29:32.444023: val_loss -0.7597 +2024-11-21 21:29:32.444136: Pseudo dice [0.851] +2024-11-21 21:29:32.444226: Epoch time: 18.4 s +2024-11-21 21:29:33.275826: +2024-11-21 21:29:33.276031: Epoch 1937 +2024-11-21 21:29:33.276164: Current learning rate: 0.00779 +2024-11-21 21:29:52.248948: train_loss -0.775 +2024-11-21 21:29:52.255320: val_loss -0.7573 +2024-11-21 21:29:52.255507: Pseudo dice [0.8392] +2024-11-21 21:29:52.255616: Epoch time: 18.97 s +2024-11-21 21:29:53.156856: +2024-11-21 21:29:53.157079: Epoch 1938 +2024-11-21 21:29:53.157202: Current learning rate: 0.00779 +2024-11-21 21:30:11.995898: train_loss -0.772 +2024-11-21 21:30:11.997662: val_loss -0.7915 +2024-11-21 21:30:11.997763: Pseudo dice [0.8561] +2024-11-21 21:30:11.997862: Epoch time: 18.84 s +2024-11-21 21:30:12.843263: +2024-11-21 21:30:12.843478: Epoch 1939 +2024-11-21 21:30:12.843610: Current learning rate: 0.00779 +2024-11-21 21:30:31.345369: train_loss -0.7739 +2024-11-21 21:30:31.347301: val_loss -0.7778 +2024-11-21 21:30:31.347453: Pseudo dice [0.8504] +2024-11-21 21:30:31.347556: Epoch time: 18.5 s +2024-11-21 21:30:32.369438: +2024-11-21 21:30:32.369652: Epoch 1940 +2024-11-21 21:30:32.369795: Current learning rate: 0.00779 +2024-11-21 21:30:51.742784: train_loss -0.7589 +2024-11-21 21:30:51.745129: val_loss -0.7852 +2024-11-21 21:30:51.745233: Pseudo dice [0.8625] +2024-11-21 21:30:51.745317: Epoch time: 19.37 s +2024-11-21 21:30:52.574650: +2024-11-21 21:30:52.574908: Epoch 1941 +2024-11-21 21:30:52.575049: Current learning rate: 0.00779 +2024-11-21 21:31:11.904788: train_loss -0.7727 +2024-11-21 21:31:11.915286: val_loss -0.7589 +2024-11-21 21:31:11.915426: Pseudo dice [0.8537] +2024-11-21 21:31:11.915531: Epoch time: 19.33 s +2024-11-21 21:31:13.264766: +2024-11-21 21:31:13.264987: Epoch 1942 +2024-11-21 21:31:13.265111: Current learning rate: 0.00779 +2024-11-21 21:31:31.854429: train_loss -0.78 +2024-11-21 21:31:31.860754: val_loss -0.7697 +2024-11-21 21:31:31.860880: Pseudo dice [0.8483] +2024-11-21 21:31:31.860987: Epoch time: 18.59 s +2024-11-21 21:31:32.876095: +2024-11-21 21:31:32.876314: Epoch 1943 +2024-11-21 21:31:32.876445: Current learning rate: 0.00778 +2024-11-21 21:31:52.025991: train_loss -0.7725 +2024-11-21 21:31:52.033453: val_loss -0.7693 +2024-11-21 21:31:52.033606: Pseudo dice [0.8459] +2024-11-21 21:31:52.033710: Epoch time: 19.15 s +2024-11-21 21:31:52.870578: +2024-11-21 21:31:52.870804: Epoch 1944 +2024-11-21 21:31:52.870927: Current learning rate: 0.00778 +2024-11-21 21:32:10.679019: train_loss -0.7737 +2024-11-21 21:32:10.685332: val_loss -0.7509 +2024-11-21 21:32:10.685469: Pseudo dice [0.8408] +2024-11-21 21:32:10.685578: Epoch time: 17.81 s +2024-11-21 21:32:11.744602: +2024-11-21 21:32:11.744809: Epoch 1945 +2024-11-21 21:32:11.744946: Current learning rate: 0.00778 +2024-11-21 21:32:30.077134: train_loss -0.7677 +2024-11-21 21:32:30.083173: val_loss -0.7523 +2024-11-21 21:32:30.083316: Pseudo dice [0.8413] +2024-11-21 21:32:30.083409: Epoch time: 18.33 s +2024-11-21 21:32:30.936092: +2024-11-21 21:32:30.936308: Epoch 1946 +2024-11-21 21:32:30.936424: Current learning rate: 0.00778 +2024-11-21 21:32:50.120133: train_loss -0.7753 +2024-11-21 21:32:50.125862: val_loss -0.7874 +2024-11-21 21:32:50.125992: Pseudo dice [0.851] +2024-11-21 21:32:50.126082: Epoch time: 19.18 s +2024-11-21 21:32:51.052793: +2024-11-21 21:32:51.053007: Epoch 1947 +2024-11-21 21:32:51.053149: Current learning rate: 0.00778 +2024-11-21 21:33:10.514677: train_loss -0.7712 +2024-11-21 21:33:10.532579: val_loss -0.7705 +2024-11-21 21:33:10.532747: Pseudo dice [0.8499] +2024-11-21 21:33:10.532858: Epoch time: 19.46 s +2024-11-21 21:33:11.469555: +2024-11-21 21:33:11.469751: Epoch 1948 +2024-11-21 21:33:11.469862: Current learning rate: 0.00778 +2024-11-21 21:33:30.380306: train_loss -0.7729 +2024-11-21 21:33:30.383350: val_loss -0.7831 +2024-11-21 21:33:30.383459: Pseudo dice [0.8455] +2024-11-21 21:33:30.383570: Epoch time: 18.91 s +2024-11-21 21:33:31.312419: +2024-11-21 21:33:31.312636: Epoch 1949 +2024-11-21 21:33:31.312752: Current learning rate: 0.00778 +2024-11-21 21:33:50.234963: train_loss -0.7712 +2024-11-21 21:33:50.242452: val_loss -0.7641 +2024-11-21 21:33:50.242579: Pseudo dice [0.8498] +2024-11-21 21:33:50.242675: Epoch time: 18.92 s +2024-11-21 21:33:51.355324: +2024-11-21 21:33:51.355526: Epoch 1950 +2024-11-21 21:33:51.355639: Current learning rate: 0.00778 +2024-11-21 21:34:09.476662: train_loss -0.7597 +2024-11-21 21:34:09.483820: val_loss -0.7277 +2024-11-21 21:34:09.483957: Pseudo dice [0.8487] +2024-11-21 21:34:09.484056: Epoch time: 18.12 s +2024-11-21 21:34:10.594702: +2024-11-21 21:34:10.594923: Epoch 1951 +2024-11-21 21:34:10.595053: Current learning rate: 0.00778 +2024-11-21 21:34:29.200979: train_loss -0.7594 +2024-11-21 21:34:29.203540: val_loss -0.7578 +2024-11-21 21:34:29.203677: Pseudo dice [0.8424] +2024-11-21 21:34:29.203778: Epoch time: 18.61 s +2024-11-21 21:34:30.041459: +2024-11-21 21:34:30.041665: Epoch 1952 +2024-11-21 21:34:30.041791: Current learning rate: 0.00777 +2024-11-21 21:34:49.462364: train_loss -0.7635 +2024-11-21 21:34:49.468591: val_loss -0.7565 +2024-11-21 21:34:49.468707: Pseudo dice [0.8536] +2024-11-21 21:34:49.468823: Epoch time: 19.42 s +2024-11-21 21:34:50.732698: +2024-11-21 21:34:50.732915: Epoch 1953 +2024-11-21 21:34:50.733039: Current learning rate: 0.00777 +2024-11-21 21:35:08.697583: train_loss -0.7573 +2024-11-21 21:35:08.700449: val_loss -0.7512 +2024-11-21 21:35:08.700603: Pseudo dice [0.8437] +2024-11-21 21:35:08.700686: Epoch time: 17.97 s +2024-11-21 21:35:09.529963: +2024-11-21 21:35:09.530193: Epoch 1954 +2024-11-21 21:35:09.530533: Current learning rate: 0.00777 +2024-11-21 21:35:28.724754: train_loss -0.7682 +2024-11-21 21:35:28.731414: val_loss -0.7725 +2024-11-21 21:35:28.731578: Pseudo dice [0.8493] +2024-11-21 21:35:28.731765: Epoch time: 19.2 s +2024-11-21 21:35:29.599779: +2024-11-21 21:35:29.600033: Epoch 1955 +2024-11-21 21:35:29.600247: Current learning rate: 0.00777 +2024-11-21 21:35:48.564950: train_loss -0.76 +2024-11-21 21:35:48.572922: val_loss -0.7582 +2024-11-21 21:35:48.573047: Pseudo dice [0.8444] +2024-11-21 21:35:48.573145: Epoch time: 18.97 s +2024-11-21 21:35:49.404911: +2024-11-21 21:35:49.405132: Epoch 1956 +2024-11-21 21:35:49.405267: Current learning rate: 0.00777 +2024-11-21 21:36:08.255432: train_loss -0.7597 +2024-11-21 21:36:08.261841: val_loss -0.7729 +2024-11-21 21:36:08.261965: Pseudo dice [0.8443] +2024-11-21 21:36:08.262080: Epoch time: 18.85 s +2024-11-21 21:36:09.335408: +2024-11-21 21:36:09.335638: Epoch 1957 +2024-11-21 21:36:09.335754: Current learning rate: 0.00777 +2024-11-21 21:36:29.057750: train_loss -0.763 +2024-11-21 21:36:29.065802: val_loss -0.7365 +2024-11-21 21:36:29.065944: Pseudo dice [0.8161] +2024-11-21 21:36:29.066037: Epoch time: 19.72 s +2024-11-21 21:36:29.906632: +2024-11-21 21:36:29.906853: Epoch 1958 +2024-11-21 21:36:29.906985: Current learning rate: 0.00777 +2024-11-21 21:36:50.581968: train_loss -0.766 +2024-11-21 21:36:50.599218: val_loss -0.7421 +2024-11-21 21:36:50.599345: Pseudo dice [0.841] +2024-11-21 21:36:50.599440: Epoch time: 20.68 s +2024-11-21 21:36:51.567747: +2024-11-21 21:36:51.567973: Epoch 1959 +2024-11-21 21:36:51.568110: Current learning rate: 0.00777 +2024-11-21 21:37:11.257410: train_loss -0.7589 +2024-11-21 21:37:11.260931: val_loss -0.7648 +2024-11-21 21:37:11.261034: Pseudo dice [0.8462] +2024-11-21 21:37:11.261128: Epoch time: 19.69 s +2024-11-21 21:37:12.093926: +2024-11-21 21:37:12.094145: Epoch 1960 +2024-11-21 21:37:12.094260: Current learning rate: 0.00777 +2024-11-21 21:37:31.222754: train_loss -0.773 +2024-11-21 21:37:31.245373: val_loss -0.7676 +2024-11-21 21:37:31.245521: Pseudo dice [0.8383] +2024-11-21 21:37:31.245610: Epoch time: 19.13 s +2024-11-21 21:37:32.158597: +2024-11-21 21:37:32.158795: Epoch 1961 +2024-11-21 21:37:32.158925: Current learning rate: 0.00776 +2024-11-21 21:37:53.239800: train_loss -0.7673 +2024-11-21 21:37:53.247016: val_loss -0.7802 +2024-11-21 21:37:53.247165: Pseudo dice [0.8492] +2024-11-21 21:37:53.247258: Epoch time: 21.08 s +2024-11-21 21:37:54.156290: +2024-11-21 21:37:54.156547: Epoch 1962 +2024-11-21 21:37:54.156666: Current learning rate: 0.00776 +2024-11-21 21:38:12.612663: train_loss -0.7726 +2024-11-21 21:38:12.620361: val_loss -0.7501 +2024-11-21 21:38:12.620512: Pseudo dice [0.8364] +2024-11-21 21:38:12.620629: Epoch time: 18.46 s +2024-11-21 21:38:13.910973: +2024-11-21 21:38:13.911172: Epoch 1963 +2024-11-21 21:38:13.911283: Current learning rate: 0.00776 +2024-11-21 21:38:33.391759: train_loss -0.765 +2024-11-21 21:38:33.397606: val_loss -0.761 +2024-11-21 21:38:33.397743: Pseudo dice [0.8546] +2024-11-21 21:38:33.397934: Epoch time: 19.48 s +2024-11-21 21:38:34.306707: +2024-11-21 21:38:34.306909: Epoch 1964 +2024-11-21 21:38:34.307050: Current learning rate: 0.00776 +2024-11-21 21:38:52.645909: train_loss -0.7646 +2024-11-21 21:38:52.652449: val_loss -0.7508 +2024-11-21 21:38:52.652589: Pseudo dice [0.8362] +2024-11-21 21:38:52.652776: Epoch time: 18.34 s +2024-11-21 21:38:53.536808: +2024-11-21 21:38:53.537039: Epoch 1965 +2024-11-21 21:38:53.537197: Current learning rate: 0.00776 +2024-11-21 21:39:12.748653: train_loss -0.7732 +2024-11-21 21:39:12.757643: val_loss -0.7622 +2024-11-21 21:39:12.757782: Pseudo dice [0.8509] +2024-11-21 21:39:12.757947: Epoch time: 19.21 s +2024-11-21 21:39:13.690198: +2024-11-21 21:39:13.690436: Epoch 1966 +2024-11-21 21:39:13.690549: Current learning rate: 0.00776 +2024-11-21 21:39:33.378204: train_loss -0.7651 +2024-11-21 21:39:33.397176: val_loss -0.7487 +2024-11-21 21:39:33.397360: Pseudo dice [0.8412] +2024-11-21 21:39:33.397460: Epoch time: 19.69 s +2024-11-21 21:39:34.397859: +2024-11-21 21:39:34.398078: Epoch 1967 +2024-11-21 21:39:34.398199: Current learning rate: 0.00776 +2024-11-21 21:39:53.389310: train_loss -0.7614 +2024-11-21 21:39:53.392824: val_loss -0.7443 +2024-11-21 21:39:53.392936: Pseudo dice [0.836] +2024-11-21 21:39:53.393024: Epoch time: 18.99 s +2024-11-21 21:39:54.227458: +2024-11-21 21:39:54.227665: Epoch 1968 +2024-11-21 21:39:54.227785: Current learning rate: 0.00776 +2024-11-21 21:40:12.930505: train_loss -0.7679 +2024-11-21 21:40:12.937201: val_loss -0.7781 +2024-11-21 21:40:12.937405: Pseudo dice [0.856] +2024-11-21 21:40:12.937511: Epoch time: 18.7 s +2024-11-21 21:40:13.808357: +2024-11-21 21:40:13.808592: Epoch 1969 +2024-11-21 21:40:13.808725: Current learning rate: 0.00775 +2024-11-21 21:40:33.283166: train_loss -0.7697 +2024-11-21 21:40:33.286190: val_loss -0.7572 +2024-11-21 21:40:33.286283: Pseudo dice [0.854] +2024-11-21 21:40:33.286379: Epoch time: 19.48 s +2024-11-21 21:40:34.120028: +2024-11-21 21:40:34.120253: Epoch 1970 +2024-11-21 21:40:34.120373: Current learning rate: 0.00775 +2024-11-21 21:40:53.085006: train_loss -0.7756 +2024-11-21 21:40:53.091623: val_loss -0.7505 +2024-11-21 21:40:53.091766: Pseudo dice [0.8502] +2024-11-21 21:40:53.091869: Epoch time: 18.97 s +2024-11-21 21:40:53.920089: +2024-11-21 21:40:53.920294: Epoch 1971 +2024-11-21 21:40:53.920433: Current learning rate: 0.00775 +2024-11-21 21:41:13.894113: train_loss -0.7758 +2024-11-21 21:41:13.897724: val_loss -0.767 +2024-11-21 21:41:13.897842: Pseudo dice [0.8552] +2024-11-21 21:41:13.897942: Epoch time: 19.97 s +2024-11-21 21:41:14.730563: +2024-11-21 21:41:14.730768: Epoch 1972 +2024-11-21 21:41:14.730900: Current learning rate: 0.00775 +2024-11-21 21:41:34.732441: train_loss -0.767 +2024-11-21 21:41:34.740031: val_loss -0.7753 +2024-11-21 21:41:34.740192: Pseudo dice [0.8563] +2024-11-21 21:41:34.740310: Epoch time: 20.0 s +2024-11-21 21:41:35.583992: +2024-11-21 21:41:35.584250: Epoch 1973 +2024-11-21 21:41:35.584376: Current learning rate: 0.00775 +2024-11-21 21:41:54.880791: train_loss -0.7805 +2024-11-21 21:41:54.888543: val_loss -0.7566 +2024-11-21 21:41:54.888664: Pseudo dice [0.8313] +2024-11-21 21:41:54.888750: Epoch time: 19.3 s +2024-11-21 21:41:55.884609: +2024-11-21 21:41:55.884892: Epoch 1974 +2024-11-21 21:41:55.885021: Current learning rate: 0.00775 +2024-11-21 21:42:13.432534: train_loss -0.7778 +2024-11-21 21:42:13.447979: val_loss -0.7272 +2024-11-21 21:42:13.452287: Pseudo dice [0.8517] +2024-11-21 21:42:13.452439: Epoch time: 17.55 s +2024-11-21 21:42:14.738450: +2024-11-21 21:42:14.738640: Epoch 1975 +2024-11-21 21:42:14.738761: Current learning rate: 0.00775 +2024-11-21 21:42:34.746415: train_loss -0.7689 +2024-11-21 21:42:34.762588: val_loss -0.7525 +2024-11-21 21:42:34.762743: Pseudo dice [0.85] +2024-11-21 21:42:34.762839: Epoch time: 20.01 s +2024-11-21 21:42:35.736741: +2024-11-21 21:42:35.736955: Epoch 1976 +2024-11-21 21:42:35.737104: Current learning rate: 0.00775 +2024-11-21 21:42:55.864130: train_loss -0.7555 +2024-11-21 21:42:55.870764: val_loss -0.787 +2024-11-21 21:42:55.870993: Pseudo dice [0.8562] +2024-11-21 21:42:55.871115: Epoch time: 20.13 s +2024-11-21 21:42:56.887087: +2024-11-21 21:42:56.887297: Epoch 1977 +2024-11-21 21:42:56.887419: Current learning rate: 0.00775 +2024-11-21 21:43:16.001309: train_loss -0.7687 +2024-11-21 21:43:16.003910: val_loss -0.7289 +2024-11-21 21:43:16.004065: Pseudo dice [0.8421] +2024-11-21 21:43:16.004181: Epoch time: 19.12 s +2024-11-21 21:43:16.926186: +2024-11-21 21:43:16.926407: Epoch 1978 +2024-11-21 21:43:16.926546: Current learning rate: 0.00774 +2024-11-21 21:43:36.710871: train_loss -0.7794 +2024-11-21 21:43:36.713876: val_loss -0.7482 +2024-11-21 21:43:36.713980: Pseudo dice [0.837] +2024-11-21 21:43:36.714089: Epoch time: 19.79 s +2024-11-21 21:43:37.552783: +2024-11-21 21:43:37.553015: Epoch 1979 +2024-11-21 21:43:37.553136: Current learning rate: 0.00774 +2024-11-21 21:43:57.059944: train_loss -0.77 +2024-11-21 21:43:57.066430: val_loss -0.7681 +2024-11-21 21:43:57.066888: Pseudo dice [0.8562] +2024-11-21 21:43:57.067046: Epoch time: 19.51 s +2024-11-21 21:43:58.063670: +2024-11-21 21:43:58.063884: Epoch 1980 +2024-11-21 21:43:58.064011: Current learning rate: 0.00774 +2024-11-21 21:44:17.534453: train_loss -0.7798 +2024-11-21 21:44:17.540890: val_loss -0.7819 +2024-11-21 21:44:17.541045: Pseudo dice [0.8676] +2024-11-21 21:44:17.541162: Epoch time: 19.47 s +2024-11-21 21:44:18.491277: +2024-11-21 21:44:18.491505: Epoch 1981 +2024-11-21 21:44:18.491636: Current learning rate: 0.00774 +2024-11-21 21:44:37.637894: train_loss -0.7748 +2024-11-21 21:44:37.648545: val_loss -0.764 +2024-11-21 21:44:37.648708: Pseudo dice [0.8434] +2024-11-21 21:44:37.648796: Epoch time: 19.15 s +2024-11-21 21:44:38.503163: +2024-11-21 21:44:38.503370: Epoch 1982 +2024-11-21 21:44:38.503478: Current learning rate: 0.00774 +2024-11-21 21:44:58.145283: train_loss -0.7711 +2024-11-21 21:44:58.150586: val_loss -0.7832 +2024-11-21 21:44:58.150728: Pseudo dice [0.857] +2024-11-21 21:44:58.150838: Epoch time: 19.64 s +2024-11-21 21:44:58.150905: Yayy! New best EMA pseudo Dice: 0.8496 +2024-11-21 21:44:59.208833: +2024-11-21 21:44:59.209032: Epoch 1983 +2024-11-21 21:44:59.209150: Current learning rate: 0.00774 +2024-11-21 21:45:18.503146: train_loss -0.7711 +2024-11-21 21:45:18.504948: val_loss -0.7587 +2024-11-21 21:45:18.505194: Pseudo dice [0.8465] +2024-11-21 21:45:18.505322: Epoch time: 19.3 s +2024-11-21 21:45:19.571871: +2024-11-21 21:45:19.572075: Epoch 1984 +2024-11-21 21:45:19.572212: Current learning rate: 0.00774 +2024-11-21 21:45:38.491914: train_loss -0.7713 +2024-11-21 21:45:38.498847: val_loss -0.7693 +2024-11-21 21:45:38.498997: Pseudo dice [0.8476] +2024-11-21 21:45:38.499108: Epoch time: 18.92 s +2024-11-21 21:45:39.457935: +2024-11-21 21:45:39.458159: Epoch 1985 +2024-11-21 21:45:39.458289: Current learning rate: 0.00774 +2024-11-21 21:45:58.914647: train_loss -0.7716 +2024-11-21 21:45:58.920500: val_loss -0.7564 +2024-11-21 21:45:58.920637: Pseudo dice [0.8663] +2024-11-21 21:45:58.920741: Epoch time: 19.46 s +2024-11-21 21:45:58.920816: Yayy! New best EMA pseudo Dice: 0.8508 +2024-11-21 21:46:00.350602: +2024-11-21 21:46:00.350806: Epoch 1986 +2024-11-21 21:46:00.350938: Current learning rate: 0.00774 +2024-11-21 21:46:18.903779: train_loss -0.7722 +2024-11-21 21:46:18.905786: val_loss -0.7698 +2024-11-21 21:46:18.905913: Pseudo dice [0.8508] +2024-11-21 21:46:18.906014: Epoch time: 18.55 s +2024-11-21 21:46:19.733761: +2024-11-21 21:46:19.733962: Epoch 1987 +2024-11-21 21:46:19.734076: Current learning rate: 0.00773 +2024-11-21 21:46:38.597676: train_loss -0.7684 +2024-11-21 21:46:38.602710: val_loss -0.7548 +2024-11-21 21:46:38.602874: Pseudo dice [0.8503] +2024-11-21 21:46:38.602983: Epoch time: 18.86 s +2024-11-21 21:46:39.479205: +2024-11-21 21:46:39.479441: Epoch 1988 +2024-11-21 21:46:39.479576: Current learning rate: 0.00773 +2024-11-21 21:46:58.499997: train_loss -0.7709 +2024-11-21 21:46:58.507099: val_loss -0.7738 +2024-11-21 21:46:58.507237: Pseudo dice [0.8539] +2024-11-21 21:46:58.507327: Epoch time: 19.02 s +2024-11-21 21:46:58.507392: Yayy! New best EMA pseudo Dice: 0.8511 +2024-11-21 21:46:59.859342: +2024-11-21 21:46:59.859560: Epoch 1989 +2024-11-21 21:46:59.859687: Current learning rate: 0.00773 +2024-11-21 21:47:20.351782: train_loss -0.7728 +2024-11-21 21:47:20.362902: val_loss -0.7645 +2024-11-21 21:47:20.363074: Pseudo dice [0.8518] +2024-11-21 21:47:20.363179: Epoch time: 20.49 s +2024-11-21 21:47:20.363260: Yayy! New best EMA pseudo Dice: 0.8511 +2024-11-21 21:47:21.499211: +2024-11-21 21:47:21.499427: Epoch 1990 +2024-11-21 21:47:21.499562: Current learning rate: 0.00773 +2024-11-21 21:47:41.093359: train_loss -0.7685 +2024-11-21 21:47:41.095141: val_loss -0.74 +2024-11-21 21:47:41.095263: Pseudo dice [0.8517] +2024-11-21 21:47:41.095363: Epoch time: 19.6 s +2024-11-21 21:47:41.095449: Yayy! New best EMA pseudo Dice: 0.8512 +2024-11-21 21:47:42.199776: +2024-11-21 21:47:42.199983: Epoch 1991 +2024-11-21 21:47:42.200109: Current learning rate: 0.00773 +2024-11-21 21:48:00.770473: train_loss -0.7658 +2024-11-21 21:48:00.773565: val_loss -0.7513 +2024-11-21 21:48:00.773705: Pseudo dice [0.8459] +2024-11-21 21:48:00.773796: Epoch time: 18.57 s +2024-11-21 21:48:01.669280: +2024-11-21 21:48:01.669480: Epoch 1992 +2024-11-21 21:48:01.669601: Current learning rate: 0.00773 +2024-11-21 21:48:21.394980: train_loss -0.7609 +2024-11-21 21:48:21.401597: val_loss -0.7635 +2024-11-21 21:48:21.401721: Pseudo dice [0.8538] +2024-11-21 21:48:21.401834: Epoch time: 19.73 s +2024-11-21 21:48:22.354664: +2024-11-21 21:48:22.354894: Epoch 1993 +2024-11-21 21:48:22.355013: Current learning rate: 0.00773 +2024-11-21 21:48:41.716312: train_loss -0.7532 +2024-11-21 21:48:41.723670: val_loss -0.7418 +2024-11-21 21:48:41.723808: Pseudo dice [0.8125] +2024-11-21 21:48:41.723901: Epoch time: 19.36 s +2024-11-21 21:48:42.766806: +2024-11-21 21:48:42.767026: Epoch 1994 +2024-11-21 21:48:42.767161: Current learning rate: 0.00773 +2024-11-21 21:49:02.231148: train_loss -0.768 +2024-11-21 21:49:02.233910: val_loss -0.7799 +2024-11-21 21:49:02.234043: Pseudo dice [0.8521] +2024-11-21 21:49:02.234140: Epoch time: 19.47 s +2024-11-21 21:49:03.178709: +2024-11-21 21:49:03.178932: Epoch 1995 +2024-11-21 21:49:03.179054: Current learning rate: 0.00772 +2024-11-21 21:49:22.107127: train_loss -0.7663 +2024-11-21 21:49:22.112813: val_loss -0.7436 +2024-11-21 21:49:22.112950: Pseudo dice [0.837] +2024-11-21 21:49:22.113047: Epoch time: 18.93 s +2024-11-21 21:49:23.061038: +2024-11-21 21:49:23.061257: Epoch 1996 +2024-11-21 21:49:23.061407: Current learning rate: 0.00772 +2024-11-21 21:49:42.111069: train_loss -0.7609 +2024-11-21 21:49:42.116784: val_loss -0.7651 +2024-11-21 21:49:42.116891: Pseudo dice [0.8337] +2024-11-21 21:49:42.116978: Epoch time: 19.05 s +2024-11-21 21:49:43.455646: +2024-11-21 21:49:43.455880: Epoch 1997 +2024-11-21 21:49:43.456009: Current learning rate: 0.00772 +2024-11-21 21:50:03.801164: train_loss -0.7655 +2024-11-21 21:50:03.808545: val_loss -0.7497 +2024-11-21 21:50:03.808700: Pseudo dice [0.8533] +2024-11-21 21:50:03.808811: Epoch time: 20.35 s +2024-11-21 21:50:04.765552: +2024-11-21 21:50:04.765779: Epoch 1998 +2024-11-21 21:50:04.765901: Current learning rate: 0.00772 +2024-11-21 21:50:24.462315: train_loss -0.761 +2024-11-21 21:50:24.469806: val_loss -0.7581 +2024-11-21 21:50:24.469956: Pseudo dice [0.8353] +2024-11-21 21:50:24.470048: Epoch time: 19.7 s +2024-11-21 21:50:25.311010: +2024-11-21 21:50:25.311230: Epoch 1999 +2024-11-21 21:50:25.311342: Current learning rate: 0.00772 +2024-11-21 21:50:44.303834: train_loss -0.7694 +2024-11-21 21:50:44.310953: val_loss -0.7423 +2024-11-21 21:50:44.311103: Pseudo dice [0.8236] +2024-11-21 21:50:44.311205: Epoch time: 18.99 s +2024-11-21 21:50:45.607068: +2024-11-21 21:50:45.607282: Epoch 2000 +2024-11-21 21:50:45.607411: Current learning rate: 0.00772 +2024-11-21 21:51:04.270782: train_loss -0.769 +2024-11-21 21:51:04.287162: val_loss -0.758 +2024-11-21 21:51:04.287299: Pseudo dice [0.8432] +2024-11-21 21:51:04.287405: Epoch time: 18.66 s +2024-11-21 21:51:05.209743: +2024-11-21 21:51:05.210005: Epoch 2001 +2024-11-21 21:51:05.210125: Current learning rate: 0.00772 +2024-11-21 21:51:25.173905: train_loss -0.7522 +2024-11-21 21:51:25.179202: val_loss -0.7344 +2024-11-21 21:51:25.179339: Pseudo dice [0.8352] +2024-11-21 21:51:25.179449: Epoch time: 19.96 s +2024-11-21 21:51:26.032877: +2024-11-21 21:51:26.033092: Epoch 2002 +2024-11-21 21:51:26.033229: Current learning rate: 0.00772 +2024-11-21 21:51:44.921449: train_loss -0.7608 +2024-11-21 21:51:44.923266: val_loss -0.7617 +2024-11-21 21:51:44.923370: Pseudo dice [0.8346] +2024-11-21 21:51:44.923451: Epoch time: 18.89 s +2024-11-21 21:51:45.757957: +2024-11-21 21:51:45.758165: Epoch 2003 +2024-11-21 21:51:45.758302: Current learning rate: 0.00772 +2024-11-21 21:52:06.030432: train_loss -0.7621 +2024-11-21 21:52:06.034441: val_loss -0.7547 +2024-11-21 21:52:06.036706: Pseudo dice [0.8335] +2024-11-21 21:52:06.036933: Epoch time: 20.27 s +2024-11-21 21:52:06.881444: +2024-11-21 21:52:06.881675: Epoch 2004 +2024-11-21 21:52:06.881802: Current learning rate: 0.00771 +2024-11-21 21:52:27.355770: train_loss -0.7659 +2024-11-21 21:52:27.366041: val_loss -0.7672 +2024-11-21 21:52:27.366183: Pseudo dice [0.8543] +2024-11-21 21:52:27.366266: Epoch time: 20.48 s +2024-11-21 21:52:28.401714: +2024-11-21 21:52:28.401922: Epoch 2005 +2024-11-21 21:52:28.402063: Current learning rate: 0.00771 +2024-11-21 21:52:47.234365: train_loss -0.7562 +2024-11-21 21:52:47.241086: val_loss -0.766 +2024-11-21 21:52:47.241264: Pseudo dice [0.8496] +2024-11-21 21:52:47.241355: Epoch time: 18.83 s +2024-11-21 21:52:48.125211: +2024-11-21 21:52:48.125406: Epoch 2006 +2024-11-21 21:52:48.125525: Current learning rate: 0.00771 +2024-11-21 21:53:08.398089: train_loss -0.761 +2024-11-21 21:53:08.404100: val_loss -0.7591 +2024-11-21 21:53:08.404233: Pseudo dice [0.8277] +2024-11-21 21:53:08.404347: Epoch time: 20.27 s +2024-11-21 21:53:09.502023: +2024-11-21 21:53:09.502245: Epoch 2007 +2024-11-21 21:53:09.502371: Current learning rate: 0.00771 +2024-11-21 21:53:29.816868: train_loss -0.7402 +2024-11-21 21:53:29.823519: val_loss -0.7432 +2024-11-21 21:53:29.823663: Pseudo dice [0.8427] +2024-11-21 21:53:29.823766: Epoch time: 20.32 s +2024-11-21 21:53:31.156697: +2024-11-21 21:53:31.156932: Epoch 2008 +2024-11-21 21:53:31.157056: Current learning rate: 0.00771 +2024-11-21 21:53:50.995630: train_loss -0.7451 +2024-11-21 21:53:51.003327: val_loss -0.7803 +2024-11-21 21:53:51.003549: Pseudo dice [0.8552] +2024-11-21 21:53:51.003659: Epoch time: 19.84 s +2024-11-21 21:53:51.835977: +2024-11-21 21:53:51.836195: Epoch 2009 +2024-11-21 21:53:51.836316: Current learning rate: 0.00771 +2024-11-21 21:54:09.753413: train_loss -0.7566 +2024-11-21 21:54:09.758298: val_loss -0.7409 +2024-11-21 21:54:09.758431: Pseudo dice [0.8387] +2024-11-21 21:54:09.758528: Epoch time: 17.92 s +2024-11-21 21:54:10.600090: +2024-11-21 21:54:10.600306: Epoch 2010 +2024-11-21 21:54:10.600439: Current learning rate: 0.00771 +2024-11-21 21:54:29.350779: train_loss -0.7711 +2024-11-21 21:54:29.356976: val_loss -0.7606 +2024-11-21 21:54:29.357152: Pseudo dice [0.8445] +2024-11-21 21:54:29.357255: Epoch time: 18.75 s +2024-11-21 21:54:30.205571: +2024-11-21 21:54:30.205799: Epoch 2011 +2024-11-21 21:54:30.205917: Current learning rate: 0.00771 +2024-11-21 21:54:49.146816: train_loss -0.7575 +2024-11-21 21:54:49.161439: val_loss -0.7925 +2024-11-21 21:54:49.161596: Pseudo dice [0.8424] +2024-11-21 21:54:49.161685: Epoch time: 18.94 s +2024-11-21 21:54:50.278323: +2024-11-21 21:54:50.278546: Epoch 2012 +2024-11-21 21:54:50.278662: Current learning rate: 0.0077 +2024-11-21 21:55:09.200936: train_loss -0.7667 +2024-11-21 21:55:09.204881: val_loss -0.7613 +2024-11-21 21:55:09.205050: Pseudo dice [0.8561] +2024-11-21 21:55:09.205162: Epoch time: 18.92 s +2024-11-21 21:55:10.042177: +2024-11-21 21:55:10.042383: Epoch 2013 +2024-11-21 21:55:10.042510: Current learning rate: 0.0077 +2024-11-21 21:55:29.758745: train_loss -0.7653 +2024-11-21 21:55:29.766231: val_loss -0.7832 +2024-11-21 21:55:29.766373: Pseudo dice [0.8498] +2024-11-21 21:55:29.766472: Epoch time: 19.72 s +2024-11-21 21:55:30.996367: +2024-11-21 21:55:30.996585: Epoch 2014 +2024-11-21 21:55:30.996710: Current learning rate: 0.0077 +2024-11-21 21:55:51.129541: train_loss -0.7677 +2024-11-21 21:55:51.143423: val_loss -0.7677 +2024-11-21 21:55:51.143724: Pseudo dice [0.8525] +2024-11-21 21:55:51.143839: Epoch time: 20.13 s +2024-11-21 21:55:52.023597: +2024-11-21 21:55:52.023818: Epoch 2015 +2024-11-21 21:55:52.023930: Current learning rate: 0.0077 +2024-11-21 21:56:11.597863: train_loss -0.7606 +2024-11-21 21:56:11.619252: val_loss -0.7582 +2024-11-21 21:56:11.619426: Pseudo dice [0.8308] +2024-11-21 21:56:11.619523: Epoch time: 19.58 s +2024-11-21 21:56:12.515848: +2024-11-21 21:56:12.516090: Epoch 2016 +2024-11-21 21:56:12.516209: Current learning rate: 0.0077 +2024-11-21 21:56:30.726317: train_loss -0.768 +2024-11-21 21:56:30.734997: val_loss -0.7745 +2024-11-21 21:56:30.735326: Pseudo dice [0.8425] +2024-11-21 21:56:30.735436: Epoch time: 18.21 s +2024-11-21 21:56:31.588227: +2024-11-21 21:56:31.588428: Epoch 2017 +2024-11-21 21:56:31.588547: Current learning rate: 0.0077 +2024-11-21 21:56:49.287232: train_loss -0.7721 +2024-11-21 21:56:49.290696: val_loss -0.7408 +2024-11-21 21:56:49.290834: Pseudo dice [0.8433] +2024-11-21 21:56:49.290977: Epoch time: 17.7 s +2024-11-21 21:56:50.246901: +2024-11-21 21:56:50.247102: Epoch 2018 +2024-11-21 21:56:50.247226: Current learning rate: 0.0077 +2024-11-21 21:57:09.524842: train_loss -0.7608 +2024-11-21 21:57:09.536497: val_loss -0.7588 +2024-11-21 21:57:09.536644: Pseudo dice [0.8421] +2024-11-21 21:57:09.536744: Epoch time: 19.28 s +2024-11-21 21:57:10.925167: +2024-11-21 21:57:10.925392: Epoch 2019 +2024-11-21 21:57:10.925505: Current learning rate: 0.0077 +2024-11-21 21:57:29.532716: train_loss -0.7635 +2024-11-21 21:57:29.547746: val_loss -0.7729 +2024-11-21 21:57:29.547911: Pseudo dice [0.8534] +2024-11-21 21:57:29.548028: Epoch time: 18.61 s +2024-11-21 21:57:30.426863: +2024-11-21 21:57:30.427127: Epoch 2020 +2024-11-21 21:57:30.427258: Current learning rate: 0.0077 +2024-11-21 21:57:50.213651: train_loss -0.7564 +2024-11-21 21:57:50.239275: val_loss -0.7754 +2024-11-21 21:57:50.239429: Pseudo dice [0.8444] +2024-11-21 21:57:50.239523: Epoch time: 19.79 s +2024-11-21 21:57:51.153971: +2024-11-21 21:57:51.154221: Epoch 2021 +2024-11-21 21:57:51.154340: Current learning rate: 0.00769 +2024-11-21 21:58:10.026932: train_loss -0.7438 +2024-11-21 21:58:10.036084: val_loss -0.7613 +2024-11-21 21:58:10.036282: Pseudo dice [0.8305] +2024-11-21 21:58:10.036402: Epoch time: 18.87 s +2024-11-21 21:58:10.896621: +2024-11-21 21:58:10.896823: Epoch 2022 +2024-11-21 21:58:10.896941: Current learning rate: 0.00769 +2024-11-21 21:58:28.993759: train_loss -0.7522 +2024-11-21 21:58:29.002800: val_loss -0.7583 +2024-11-21 21:58:29.002922: Pseudo dice [0.8332] +2024-11-21 21:58:29.003030: Epoch time: 18.1 s +2024-11-21 21:58:29.871171: +2024-11-21 21:58:29.871358: Epoch 2023 +2024-11-21 21:58:29.871471: Current learning rate: 0.00769 +2024-11-21 21:58:50.078893: train_loss -0.7511 +2024-11-21 21:58:50.093374: val_loss -0.7458 +2024-11-21 21:58:50.093530: Pseudo dice [0.8474] +2024-11-21 21:58:50.093634: Epoch time: 20.21 s +2024-11-21 21:58:51.132738: +2024-11-21 21:58:51.132961: Epoch 2024 +2024-11-21 21:58:51.133100: Current learning rate: 0.00769 +2024-11-21 21:59:10.066208: train_loss -0.7652 +2024-11-21 21:59:10.080867: val_loss -0.753 +2024-11-21 21:59:10.081004: Pseudo dice [0.8403] +2024-11-21 21:59:10.081104: Epoch time: 18.93 s +2024-11-21 21:59:11.049154: +2024-11-21 21:59:11.049354: Epoch 2025 +2024-11-21 21:59:11.049493: Current learning rate: 0.00769 +2024-11-21 21:59:30.341533: train_loss -0.7707 +2024-11-21 21:59:30.354283: val_loss -0.7456 +2024-11-21 21:59:30.354435: Pseudo dice [0.8488] +2024-11-21 21:59:30.354539: Epoch time: 19.29 s +2024-11-21 21:59:31.194602: +2024-11-21 21:59:31.194835: Epoch 2026 +2024-11-21 21:59:31.194957: Current learning rate: 0.00769 +2024-11-21 21:59:49.242887: train_loss -0.7666 +2024-11-21 21:59:49.249407: val_loss -0.7578 +2024-11-21 21:59:49.249557: Pseudo dice [0.8461] +2024-11-21 21:59:49.249650: Epoch time: 18.05 s +2024-11-21 21:59:50.293927: +2024-11-21 21:59:50.294138: Epoch 2027 +2024-11-21 21:59:50.294274: Current learning rate: 0.00769 +2024-11-21 22:00:09.538157: train_loss -0.7669 +2024-11-21 22:00:09.546523: val_loss -0.75 +2024-11-21 22:00:09.546670: Pseudo dice [0.8351] +2024-11-21 22:00:09.546760: Epoch time: 19.25 s +2024-11-21 22:00:10.518202: +2024-11-21 22:00:10.518419: Epoch 2028 +2024-11-21 22:00:10.518535: Current learning rate: 0.00769 +2024-11-21 22:00:30.555972: train_loss -0.7694 +2024-11-21 22:00:30.563560: val_loss -0.761 +2024-11-21 22:00:30.563700: Pseudo dice [0.8526] +2024-11-21 22:00:30.563791: Epoch time: 20.04 s +2024-11-21 22:00:31.410407: +2024-11-21 22:00:31.410607: Epoch 2029 +2024-11-21 22:00:31.410730: Current learning rate: 0.00769 +2024-11-21 22:00:50.447414: train_loss -0.7764 +2024-11-21 22:00:50.454028: val_loss -0.7569 +2024-11-21 22:00:50.454159: Pseudo dice [0.8553] +2024-11-21 22:00:50.454256: Epoch time: 19.04 s +2024-11-21 22:00:51.758865: +2024-11-21 22:00:51.759089: Epoch 2030 +2024-11-21 22:00:51.759209: Current learning rate: 0.00768 +2024-11-21 22:01:10.220221: train_loss -0.771 +2024-11-21 22:01:10.222421: val_loss -0.7572 +2024-11-21 22:01:10.222524: Pseudo dice [0.8487] +2024-11-21 22:01:10.222618: Epoch time: 18.46 s +2024-11-21 22:01:11.052716: +2024-11-21 22:01:11.052943: Epoch 2031 +2024-11-21 22:01:11.053079: Current learning rate: 0.00768 +2024-11-21 22:01:29.820262: train_loss -0.7736 +2024-11-21 22:01:29.823509: val_loss -0.7766 +2024-11-21 22:01:29.823664: Pseudo dice [0.8482] +2024-11-21 22:01:29.823862: Epoch time: 18.77 s +2024-11-21 22:01:30.695263: +2024-11-21 22:01:30.695476: Epoch 2032 +2024-11-21 22:01:30.695601: Current learning rate: 0.00768 +2024-11-21 22:01:49.552555: train_loss -0.7731 +2024-11-21 22:01:49.556996: val_loss -0.7617 +2024-11-21 22:01:49.557142: Pseudo dice [0.8326] +2024-11-21 22:01:49.557236: Epoch time: 18.86 s +2024-11-21 22:01:50.472655: +2024-11-21 22:01:50.472885: Epoch 2033 +2024-11-21 22:01:50.473029: Current learning rate: 0.00768 +2024-11-21 22:02:09.557275: train_loss -0.776 +2024-11-21 22:02:09.577085: val_loss -0.7424 +2024-11-21 22:02:09.577389: Pseudo dice [0.8454] +2024-11-21 22:02:09.577623: Epoch time: 19.09 s +2024-11-21 22:02:10.453296: +2024-11-21 22:02:10.453560: Epoch 2034 +2024-11-21 22:02:10.453674: Current learning rate: 0.00768 +2024-11-21 22:02:28.793164: train_loss -0.7764 +2024-11-21 22:02:28.800784: val_loss -0.7629 +2024-11-21 22:02:28.800927: Pseudo dice [0.8542] +2024-11-21 22:02:28.801017: Epoch time: 18.34 s +2024-11-21 22:02:29.750330: +2024-11-21 22:02:29.750544: Epoch 2035 +2024-11-21 22:02:29.750684: Current learning rate: 0.00768 +2024-11-21 22:02:47.987673: train_loss -0.7773 +2024-11-21 22:02:47.993107: val_loss -0.7776 +2024-11-21 22:02:47.993247: Pseudo dice [0.8363] +2024-11-21 22:02:47.993352: Epoch time: 18.24 s +2024-11-21 22:02:48.849030: +2024-11-21 22:02:48.849260: Epoch 2036 +2024-11-21 22:02:48.849400: Current learning rate: 0.00768 +2024-11-21 22:03:08.621186: train_loss -0.7724 +2024-11-21 22:03:08.629494: val_loss -0.7626 +2024-11-21 22:03:08.629657: Pseudo dice [0.8497] +2024-11-21 22:03:08.629778: Epoch time: 19.77 s +2024-11-21 22:03:09.550076: +2024-11-21 22:03:09.550281: Epoch 2037 +2024-11-21 22:03:09.550406: Current learning rate: 0.00768 +2024-11-21 22:03:28.915812: train_loss -0.7639 +2024-11-21 22:03:28.925906: val_loss -0.7595 +2024-11-21 22:03:28.926075: Pseudo dice [0.8497] +2024-11-21 22:03:28.926195: Epoch time: 19.37 s +2024-11-21 22:03:29.776408: +2024-11-21 22:03:29.776616: Epoch 2038 +2024-11-21 22:03:29.776751: Current learning rate: 0.00767 +2024-11-21 22:03:49.383368: train_loss -0.7648 +2024-11-21 22:03:49.396986: val_loss -0.7732 +2024-11-21 22:03:49.397189: Pseudo dice [0.8502] +2024-11-21 22:03:49.397297: Epoch time: 19.61 s +2024-11-21 22:03:50.294924: +2024-11-21 22:03:50.295168: Epoch 2039 +2024-11-21 22:03:50.295300: Current learning rate: 0.00767 +2024-11-21 22:04:10.378265: train_loss -0.7686 +2024-11-21 22:04:10.381361: val_loss -0.7731 +2024-11-21 22:04:10.381481: Pseudo dice [0.8444] +2024-11-21 22:04:10.381582: Epoch time: 20.08 s +2024-11-21 22:04:11.212124: +2024-11-21 22:04:11.212355: Epoch 2040 +2024-11-21 22:04:11.212483: Current learning rate: 0.00767 +2024-11-21 22:04:31.701017: train_loss -0.7673 +2024-11-21 22:04:31.705736: val_loss -0.7718 +2024-11-21 22:04:31.705876: Pseudo dice [0.8592] +2024-11-21 22:04:31.705962: Epoch time: 20.49 s +2024-11-21 22:04:32.943936: +2024-11-21 22:04:32.944205: Epoch 2041 +2024-11-21 22:04:32.944335: Current learning rate: 0.00767 +2024-11-21 22:04:52.341818: train_loss -0.7666 +2024-11-21 22:04:52.344793: val_loss -0.7528 +2024-11-21 22:04:52.344905: Pseudo dice [0.8483] +2024-11-21 22:04:52.345001: Epoch time: 19.4 s +2024-11-21 22:04:53.175048: +2024-11-21 22:04:53.175508: Epoch 2042 +2024-11-21 22:04:53.175647: Current learning rate: 0.00767 +2024-11-21 22:05:13.712269: train_loss -0.7717 +2024-11-21 22:05:13.722427: val_loss -0.7633 +2024-11-21 22:05:13.722574: Pseudo dice [0.8491] +2024-11-21 22:05:13.722659: Epoch time: 20.54 s +2024-11-21 22:05:14.726887: +2024-11-21 22:05:14.727093: Epoch 2043 +2024-11-21 22:05:14.727213: Current learning rate: 0.00767 +2024-11-21 22:05:33.818737: train_loss -0.7735 +2024-11-21 22:05:33.832114: val_loss -0.7684 +2024-11-21 22:05:33.832249: Pseudo dice [0.8448] +2024-11-21 22:05:33.832335: Epoch time: 19.09 s +2024-11-21 22:05:34.679594: +2024-11-21 22:05:34.679817: Epoch 2044 +2024-11-21 22:05:34.679948: Current learning rate: 0.00767 +2024-11-21 22:05:53.983481: train_loss -0.7739 +2024-11-21 22:05:53.988872: val_loss -0.7475 +2024-11-21 22:05:53.988992: Pseudo dice [0.8544] +2024-11-21 22:05:53.989079: Epoch time: 19.3 s +2024-11-21 22:05:54.849495: +2024-11-21 22:05:54.849697: Epoch 2045 +2024-11-21 22:05:54.849828: Current learning rate: 0.00767 +2024-11-21 22:06:14.741878: train_loss -0.7679 +2024-11-21 22:06:14.749028: val_loss -0.7783 +2024-11-21 22:06:14.749165: Pseudo dice [0.8435] +2024-11-21 22:06:14.749264: Epoch time: 19.89 s +2024-11-21 22:06:15.740844: +2024-11-21 22:06:15.741042: Epoch 2046 +2024-11-21 22:06:15.741159: Current learning rate: 0.00767 +2024-11-21 22:06:35.573284: train_loss -0.768 +2024-11-21 22:06:35.580974: val_loss -0.7479 +2024-11-21 22:06:35.581094: Pseudo dice [0.8448] +2024-11-21 22:06:35.581176: Epoch time: 19.83 s +2024-11-21 22:06:36.444111: +2024-11-21 22:06:36.444356: Epoch 2047 +2024-11-21 22:06:36.444491: Current learning rate: 0.00766 +2024-11-21 22:06:55.364894: train_loss -0.7731 +2024-11-21 22:06:55.377420: val_loss -0.7594 +2024-11-21 22:06:55.377590: Pseudo dice [0.8381] +2024-11-21 22:06:55.377717: Epoch time: 18.92 s +2024-11-21 22:06:56.300946: +2024-11-21 22:06:56.301161: Epoch 2048 +2024-11-21 22:06:56.301303: Current learning rate: 0.00766 +2024-11-21 22:07:14.885018: train_loss -0.7723 +2024-11-21 22:07:14.889697: val_loss -0.7529 +2024-11-21 22:07:14.889839: Pseudo dice [0.837] +2024-11-21 22:07:14.889937: Epoch time: 18.58 s +2024-11-21 22:07:15.737529: +2024-11-21 22:07:15.737748: Epoch 2049 +2024-11-21 22:07:15.737883: Current learning rate: 0.00766 +2024-11-21 22:07:35.104142: train_loss -0.7733 +2024-11-21 22:07:35.111500: val_loss -0.7693 +2024-11-21 22:07:35.111641: Pseudo dice [0.8583] +2024-11-21 22:07:35.111736: Epoch time: 19.37 s +2024-11-21 22:07:36.379660: +2024-11-21 22:07:36.379894: Epoch 2050 +2024-11-21 22:07:36.380013: Current learning rate: 0.00766 +2024-11-21 22:07:55.190986: train_loss -0.7715 +2024-11-21 22:07:55.198364: val_loss -0.7412 +2024-11-21 22:07:55.198500: Pseudo dice [0.836] +2024-11-21 22:07:55.198591: Epoch time: 18.81 s +2024-11-21 22:07:56.132212: +2024-11-21 22:07:56.132416: Epoch 2051 +2024-11-21 22:07:56.132548: Current learning rate: 0.00766 +2024-11-21 22:08:15.464736: train_loss -0.7611 +2024-11-21 22:08:15.474443: val_loss -0.7436 +2024-11-21 22:08:15.474603: Pseudo dice [0.8534] +2024-11-21 22:08:15.474710: Epoch time: 19.33 s +2024-11-21 22:08:16.296185: +2024-11-21 22:08:16.296438: Epoch 2052 +2024-11-21 22:08:16.296575: Current learning rate: 0.00766 +2024-11-21 22:08:36.123351: train_loss -0.7669 +2024-11-21 22:08:36.148603: val_loss -0.7505 +2024-11-21 22:08:36.148757: Pseudo dice [0.8422] +2024-11-21 22:08:36.148877: Epoch time: 19.83 s +2024-11-21 22:08:36.950311: +2024-11-21 22:08:36.950537: Epoch 2053 +2024-11-21 22:08:36.950657: Current learning rate: 0.00766 +2024-11-21 22:08:55.880863: train_loss -0.7663 +2024-11-21 22:08:55.885789: val_loss -0.7694 +2024-11-21 22:08:55.885952: Pseudo dice [0.8522] +2024-11-21 22:08:55.886051: Epoch time: 18.93 s +2024-11-21 22:08:56.701940: +2024-11-21 22:08:56.702160: Epoch 2054 +2024-11-21 22:08:56.702290: Current learning rate: 0.00766 +2024-11-21 22:09:15.747387: train_loss -0.7501 +2024-11-21 22:09:15.749734: val_loss -0.7497 +2024-11-21 22:09:15.749828: Pseudo dice [0.835] +2024-11-21 22:09:15.750200: Epoch time: 19.05 s +2024-11-21 22:09:16.550549: +2024-11-21 22:09:16.550801: Epoch 2055 +2024-11-21 22:09:16.550939: Current learning rate: 0.00766 +2024-11-21 22:09:35.480611: train_loss -0.7615 +2024-11-21 22:09:35.486436: val_loss -0.7701 +2024-11-21 22:09:35.486578: Pseudo dice [0.8508] +2024-11-21 22:09:35.486676: Epoch time: 18.93 s +2024-11-21 22:09:36.343515: +2024-11-21 22:09:36.343741: Epoch 2056 +2024-11-21 22:09:36.344042: Current learning rate: 0.00765 +2024-11-21 22:09:56.502328: train_loss -0.7667 +2024-11-21 22:09:56.508463: val_loss -0.7622 +2024-11-21 22:09:56.508603: Pseudo dice [0.8499] +2024-11-21 22:09:56.508693: Epoch time: 20.16 s +2024-11-21 22:09:57.384791: +2024-11-21 22:09:57.384994: Epoch 2057 +2024-11-21 22:09:57.385121: Current learning rate: 0.00765 +2024-11-21 22:10:16.993461: train_loss -0.7652 +2024-11-21 22:10:16.999804: val_loss -0.7542 +2024-11-21 22:10:16.999947: Pseudo dice [0.8387] +2024-11-21 22:10:17.000035: Epoch time: 19.61 s +2024-11-21 22:10:17.878810: +2024-11-21 22:10:17.879020: Epoch 2058 +2024-11-21 22:10:17.879162: Current learning rate: 0.00765 +2024-11-21 22:10:36.153566: train_loss -0.7727 +2024-11-21 22:10:36.159581: val_loss -0.7633 +2024-11-21 22:10:36.159718: Pseudo dice [0.8416] +2024-11-21 22:10:36.159834: Epoch time: 18.28 s +2024-11-21 22:10:37.135905: +2024-11-21 22:10:37.136116: Epoch 2059 +2024-11-21 22:10:37.136233: Current learning rate: 0.00765 +2024-11-21 22:10:56.833449: train_loss -0.7633 +2024-11-21 22:10:56.838174: val_loss -0.7652 +2024-11-21 22:10:56.838320: Pseudo dice [0.8596] +2024-11-21 22:10:56.838432: Epoch time: 19.7 s +2024-11-21 22:10:57.721479: +2024-11-21 22:10:57.721741: Epoch 2060 +2024-11-21 22:10:57.721862: Current learning rate: 0.00765 +2024-11-21 22:11:17.045793: train_loss -0.7668 +2024-11-21 22:11:17.047796: val_loss -0.7406 +2024-11-21 22:11:17.047889: Pseudo dice [0.8321] +2024-11-21 22:11:17.047988: Epoch time: 19.33 s +2024-11-21 22:11:17.854589: +2024-11-21 22:11:17.854782: Epoch 2061 +2024-11-21 22:11:17.854905: Current learning rate: 0.00765 +2024-11-21 22:11:36.576231: train_loss -0.7329 +2024-11-21 22:11:36.580419: val_loss -0.7627 +2024-11-21 22:11:36.580538: Pseudo dice [0.8463] +2024-11-21 22:11:36.580640: Epoch time: 18.72 s +2024-11-21 22:11:37.392661: +2024-11-21 22:11:37.392872: Epoch 2062 +2024-11-21 22:11:37.392991: Current learning rate: 0.00765 +2024-11-21 22:11:56.303374: train_loss -0.7518 +2024-11-21 22:11:56.310657: val_loss -0.7519 +2024-11-21 22:11:56.310781: Pseudo dice [0.8269] +2024-11-21 22:11:56.310880: Epoch time: 18.91 s +2024-11-21 22:11:57.115593: +2024-11-21 22:11:57.115813: Epoch 2063 +2024-11-21 22:11:57.115931: Current learning rate: 0.00765 +2024-11-21 22:12:16.225045: train_loss -0.7518 +2024-11-21 22:12:16.227617: val_loss -0.7497 +2024-11-21 22:12:16.227752: Pseudo dice [0.8361] +2024-11-21 22:12:16.227853: Epoch time: 19.11 s +2024-11-21 22:12:17.036787: +2024-11-21 22:12:17.036993: Epoch 2064 +2024-11-21 22:12:17.037131: Current learning rate: 0.00764 +2024-11-21 22:12:36.129559: train_loss -0.7654 +2024-11-21 22:12:36.138833: val_loss -0.759 +2024-11-21 22:12:36.138980: Pseudo dice [0.8489] +2024-11-21 22:12:36.139087: Epoch time: 19.09 s +2024-11-21 22:12:37.170354: +2024-11-21 22:12:37.170563: Epoch 2065 +2024-11-21 22:12:37.170686: Current learning rate: 0.00764 +2024-11-21 22:12:55.155850: train_loss -0.7658 +2024-11-21 22:12:55.162370: val_loss -0.7606 +2024-11-21 22:12:55.162503: Pseudo dice [0.8489] +2024-11-21 22:12:55.162606: Epoch time: 17.99 s +2024-11-21 22:12:55.971776: +2024-11-21 22:12:55.971987: Epoch 2066 +2024-11-21 22:12:55.972112: Current learning rate: 0.00764 +2024-11-21 22:13:15.289495: train_loss -0.7668 +2024-11-21 22:13:15.317796: val_loss -0.7658 +2024-11-21 22:13:15.317990: Pseudo dice [0.8568] +2024-11-21 22:13:15.318101: Epoch time: 19.32 s +2024-11-21 22:13:16.178413: +2024-11-21 22:13:16.178653: Epoch 2067 +2024-11-21 22:13:16.178768: Current learning rate: 0.00764 +2024-11-21 22:13:34.603302: train_loss -0.769 +2024-11-21 22:13:34.610913: val_loss -0.7503 +2024-11-21 22:13:34.611067: Pseudo dice [0.8515] +2024-11-21 22:13:34.611171: Epoch time: 18.43 s +2024-11-21 22:13:35.495291: +2024-11-21 22:13:35.495520: Epoch 2068 +2024-11-21 22:13:35.495644: Current learning rate: 0.00764 +2024-11-21 22:13:54.744703: train_loss -0.7651 +2024-11-21 22:13:54.750919: val_loss -0.7613 +2024-11-21 22:13:54.751036: Pseudo dice [0.8451] +2024-11-21 22:13:54.751137: Epoch time: 19.25 s +2024-11-21 22:13:55.568707: +2024-11-21 22:13:55.568929: Epoch 2069 +2024-11-21 22:13:55.569065: Current learning rate: 0.00764 +2024-11-21 22:14:13.908712: train_loss -0.7789 +2024-11-21 22:14:13.916292: val_loss -0.7561 +2024-11-21 22:14:13.916411: Pseudo dice [0.84] +2024-11-21 22:14:13.916521: Epoch time: 18.34 s +2024-11-21 22:14:14.815100: +2024-11-21 22:14:14.815307: Epoch 2070 +2024-11-21 22:14:14.815427: Current learning rate: 0.00764 +2024-11-21 22:14:33.895252: train_loss -0.7675 +2024-11-21 22:14:33.899245: val_loss -0.7568 +2024-11-21 22:14:33.899389: Pseudo dice [0.8549] +2024-11-21 22:14:33.899490: Epoch time: 19.08 s +2024-11-21 22:14:34.939738: +2024-11-21 22:14:34.939961: Epoch 2071 +2024-11-21 22:14:34.940088: Current learning rate: 0.00764 +2024-11-21 22:14:54.233831: train_loss -0.7625 +2024-11-21 22:14:54.255788: val_loss -0.7612 +2024-11-21 22:14:54.255943: Pseudo dice [0.8632] +2024-11-21 22:14:54.256037: Epoch time: 19.29 s +2024-11-21 22:14:55.162420: +2024-11-21 22:14:55.162665: Epoch 2072 +2024-11-21 22:14:55.162785: Current learning rate: 0.00764 +2024-11-21 22:15:15.046707: train_loss -0.7634 +2024-11-21 22:15:15.061926: val_loss -0.7846 +2024-11-21 22:15:15.062079: Pseudo dice [0.8508] +2024-11-21 22:15:15.062178: Epoch time: 19.89 s +2024-11-21 22:15:15.880391: +2024-11-21 22:15:15.880643: Epoch 2073 +2024-11-21 22:15:15.880762: Current learning rate: 0.00763 +2024-11-21 22:15:34.419707: train_loss -0.7702 +2024-11-21 22:15:34.425146: val_loss -0.755 +2024-11-21 22:15:34.425266: Pseudo dice [0.8217] +2024-11-21 22:15:34.425364: Epoch time: 18.54 s +2024-11-21 22:15:35.563390: +2024-11-21 22:15:35.563612: Epoch 2074 +2024-11-21 22:15:35.563730: Current learning rate: 0.00763 +2024-11-21 22:15:53.956923: train_loss -0.7544 +2024-11-21 22:15:53.958501: val_loss -0.7601 +2024-11-21 22:15:53.958611: Pseudo dice [0.8419] +2024-11-21 22:15:53.958703: Epoch time: 18.39 s +2024-11-21 22:15:54.765149: +2024-11-21 22:15:54.765378: Epoch 2075 +2024-11-21 22:15:54.765497: Current learning rate: 0.00763 +2024-11-21 22:16:14.334038: train_loss -0.7486 +2024-11-21 22:16:14.349378: val_loss -0.7458 +2024-11-21 22:16:14.349559: Pseudo dice [0.8537] +2024-11-21 22:16:14.349664: Epoch time: 19.57 s +2024-11-21 22:16:15.193541: +2024-11-21 22:16:15.193837: Epoch 2076 +2024-11-21 22:16:15.193964: Current learning rate: 0.00763 +2024-11-21 22:16:34.436440: train_loss -0.7659 +2024-11-21 22:16:34.443559: val_loss -0.7615 +2024-11-21 22:16:34.443707: Pseudo dice [0.8495] +2024-11-21 22:16:34.443791: Epoch time: 19.24 s +2024-11-21 22:16:35.249464: +2024-11-21 22:16:35.249727: Epoch 2077 +2024-11-21 22:16:35.249864: Current learning rate: 0.00763 +2024-11-21 22:16:55.029753: train_loss -0.7706 +2024-11-21 22:16:55.054245: val_loss -0.7609 +2024-11-21 22:16:55.054421: Pseudo dice [0.8473] +2024-11-21 22:16:55.054525: Epoch time: 19.78 s +2024-11-21 22:16:55.999478: +2024-11-21 22:16:55.999700: Epoch 2078 +2024-11-21 22:16:55.999817: Current learning rate: 0.00763 +2024-11-21 22:17:14.784028: train_loss -0.7639 +2024-11-21 22:17:14.798512: val_loss -0.7581 +2024-11-21 22:17:14.798662: Pseudo dice [0.8484] +2024-11-21 22:17:14.798749: Epoch time: 18.79 s +2024-11-21 22:17:15.888099: +2024-11-21 22:17:15.888331: Epoch 2079 +2024-11-21 22:17:15.888476: Current learning rate: 0.00763 +2024-11-21 22:17:35.340047: train_loss -0.7512 +2024-11-21 22:17:35.353217: val_loss -0.7574 +2024-11-21 22:17:35.353379: Pseudo dice [0.8471] +2024-11-21 22:17:35.353480: Epoch time: 19.45 s +2024-11-21 22:17:36.207575: +2024-11-21 22:17:36.207784: Epoch 2080 +2024-11-21 22:17:36.208142: Current learning rate: 0.00763 +2024-11-21 22:17:55.922111: train_loss -0.7628 +2024-11-21 22:17:55.924797: val_loss -0.7651 +2024-11-21 22:17:55.924922: Pseudo dice [0.8585] +2024-11-21 22:17:55.925031: Epoch time: 19.72 s +2024-11-21 22:17:56.756535: +2024-11-21 22:17:56.756759: Epoch 2081 +2024-11-21 22:17:56.756888: Current learning rate: 0.00763 +2024-11-21 22:18:15.172713: train_loss -0.7623 +2024-11-21 22:18:15.180581: val_loss -0.7615 +2024-11-21 22:18:15.180712: Pseudo dice [0.8415] +2024-11-21 22:18:15.180823: Epoch time: 18.42 s +2024-11-21 22:18:16.289667: +2024-11-21 22:18:16.290126: Epoch 2082 +2024-11-21 22:18:16.290261: Current learning rate: 0.00762 +2024-11-21 22:18:35.148990: train_loss -0.7635 +2024-11-21 22:18:35.153814: val_loss -0.7485 +2024-11-21 22:18:35.153946: Pseudo dice [0.84] +2024-11-21 22:18:35.154037: Epoch time: 18.86 s +2024-11-21 22:18:36.241912: +2024-11-21 22:18:36.242158: Epoch 2083 +2024-11-21 22:18:36.242284: Current learning rate: 0.00762 +2024-11-21 22:18:55.073702: train_loss -0.7671 +2024-11-21 22:18:55.094445: val_loss -0.7611 +2024-11-21 22:18:55.094609: Pseudo dice [0.8399] +2024-11-21 22:18:55.094712: Epoch time: 18.83 s +2024-11-21 22:18:55.932814: +2024-11-21 22:18:55.933032: Epoch 2084 +2024-11-21 22:18:55.933168: Current learning rate: 0.00762 +2024-11-21 22:19:16.226886: train_loss -0.7673 +2024-11-21 22:19:16.230039: val_loss -0.7606 +2024-11-21 22:19:16.230148: Pseudo dice [0.8532] +2024-11-21 22:19:16.230293: Epoch time: 20.29 s +2024-11-21 22:19:17.044578: +2024-11-21 22:19:17.044804: Epoch 2085 +2024-11-21 22:19:17.044939: Current learning rate: 0.00762 +2024-11-21 22:19:36.887497: train_loss -0.7786 +2024-11-21 22:19:36.889835: val_loss -0.7758 +2024-11-21 22:19:36.889941: Pseudo dice [0.8518] +2024-11-21 22:19:36.890049: Epoch time: 19.84 s +2024-11-21 22:19:37.697434: +2024-11-21 22:19:37.697640: Epoch 2086 +2024-11-21 22:19:37.697762: Current learning rate: 0.00762 +2024-11-21 22:19:57.784669: train_loss -0.7666 +2024-11-21 22:19:57.790980: val_loss -0.7518 +2024-11-21 22:19:57.791172: Pseudo dice [0.849] +2024-11-21 22:19:57.791286: Epoch time: 20.09 s +2024-11-21 22:19:58.618030: +2024-11-21 22:19:58.618255: Epoch 2087 +2024-11-21 22:19:58.618376: Current learning rate: 0.00762 +2024-11-21 22:20:17.347946: train_loss -0.7603 +2024-11-21 22:20:17.350955: val_loss -0.7762 +2024-11-21 22:20:17.351177: Pseudo dice [0.8584] +2024-11-21 22:20:17.351271: Epoch time: 18.73 s +2024-11-21 22:20:18.188088: +2024-11-21 22:20:18.188347: Epoch 2088 +2024-11-21 22:20:18.188475: Current learning rate: 0.00762 +2024-11-21 22:20:36.979454: train_loss -0.7716 +2024-11-21 22:20:36.981428: val_loss -0.7682 +2024-11-21 22:20:36.981540: Pseudo dice [0.8517] +2024-11-21 22:20:36.981637: Epoch time: 18.79 s +2024-11-21 22:20:37.791156: +2024-11-21 22:20:37.791380: Epoch 2089 +2024-11-21 22:20:37.791504: Current learning rate: 0.00762 +2024-11-21 22:20:56.821517: train_loss -0.7801 +2024-11-21 22:20:56.823302: val_loss -0.771 +2024-11-21 22:20:56.823454: Pseudo dice [0.8498] +2024-11-21 22:20:56.823555: Epoch time: 19.03 s +2024-11-21 22:20:57.629886: +2024-11-21 22:20:57.630140: Epoch 2090 +2024-11-21 22:20:57.630263: Current learning rate: 0.00761 +2024-11-21 22:21:17.727393: train_loss -0.7584 +2024-11-21 22:21:17.733427: val_loss -0.772 +2024-11-21 22:21:17.733561: Pseudo dice [0.8466] +2024-11-21 22:21:17.733644: Epoch time: 20.1 s +2024-11-21 22:21:18.771501: +2024-11-21 22:21:18.771724: Epoch 2091 +2024-11-21 22:21:18.771853: Current learning rate: 0.00761 +2024-11-21 22:21:37.583334: train_loss -0.7698 +2024-11-21 22:21:37.603434: val_loss -0.7703 +2024-11-21 22:21:37.603580: Pseudo dice [0.8536] +2024-11-21 22:21:37.603683: Epoch time: 18.81 s +2024-11-21 22:21:38.511736: +2024-11-21 22:21:38.511956: Epoch 2092 +2024-11-21 22:21:38.512085: Current learning rate: 0.00761 +2024-11-21 22:21:57.445907: train_loss -0.7817 +2024-11-21 22:21:57.456749: val_loss -0.7603 +2024-11-21 22:21:57.456903: Pseudo dice [0.8504] +2024-11-21 22:21:57.475133: Epoch time: 18.94 s +2024-11-21 22:21:58.321227: +2024-11-21 22:21:58.321471: Epoch 2093 +2024-11-21 22:21:58.321590: Current learning rate: 0.00761 +2024-11-21 22:22:18.091037: train_loss -0.7791 +2024-11-21 22:22:18.097308: val_loss -0.7683 +2024-11-21 22:22:18.097439: Pseudo dice [0.8455] +2024-11-21 22:22:18.097533: Epoch time: 19.77 s +2024-11-21 22:22:18.907338: +2024-11-21 22:22:18.907557: Epoch 2094 +2024-11-21 22:22:18.907692: Current learning rate: 0.00761 +2024-11-21 22:22:38.729568: train_loss -0.7773 +2024-11-21 22:22:38.736399: val_loss -0.784 +2024-11-21 22:22:38.736554: Pseudo dice [0.843] +2024-11-21 22:22:38.736664: Epoch time: 19.82 s +2024-11-21 22:22:39.576707: +2024-11-21 22:22:39.576901: Epoch 2095 +2024-11-21 22:22:39.577033: Current learning rate: 0.00761 +2024-11-21 22:22:58.499722: train_loss -0.7663 +2024-11-21 22:22:58.504191: val_loss -0.7671 +2024-11-21 22:22:58.504350: Pseudo dice [0.8586] +2024-11-21 22:22:58.504497: Epoch time: 18.92 s +2024-11-21 22:22:59.320681: +2024-11-21 22:22:59.320893: Epoch 2096 +2024-11-21 22:22:59.321013: Current learning rate: 0.00761 +2024-11-21 22:23:18.345464: train_loss -0.7651 +2024-11-21 22:23:18.353511: val_loss -0.7675 +2024-11-21 22:23:18.353661: Pseudo dice [0.8561] +2024-11-21 22:23:18.353759: Epoch time: 19.03 s +2024-11-21 22:23:19.351725: +2024-11-21 22:23:19.351922: Epoch 2097 +2024-11-21 22:23:19.352049: Current learning rate: 0.00761 +2024-11-21 22:23:37.740958: train_loss -0.7728 +2024-11-21 22:23:37.748082: val_loss -0.7696 +2024-11-21 22:23:37.748204: Pseudo dice [0.8597] +2024-11-21 22:23:37.748313: Epoch time: 18.39 s +2024-11-21 22:23:38.659469: +2024-11-21 22:23:38.659681: Epoch 2098 +2024-11-21 22:23:38.659820: Current learning rate: 0.00761 +2024-11-21 22:23:58.475805: train_loss -0.7692 +2024-11-21 22:23:58.484314: val_loss -0.7564 +2024-11-21 22:23:58.484453: Pseudo dice [0.8574] +2024-11-21 22:23:58.484547: Epoch time: 19.82 s +2024-11-21 22:23:58.484610: Yayy! New best EMA pseudo Dice: 0.8516 +2024-11-21 22:23:59.501870: +2024-11-21 22:23:59.502083: Epoch 2099 +2024-11-21 22:23:59.502205: Current learning rate: 0.0076 +2024-11-21 22:24:18.518101: train_loss -0.7666 +2024-11-21 22:24:18.523318: val_loss -0.7893 +2024-11-21 22:24:18.523441: Pseudo dice [0.8497] +2024-11-21 22:24:18.523535: Epoch time: 19.02 s +2024-11-21 22:24:19.950443: +2024-11-21 22:24:19.950685: Epoch 2100 +2024-11-21 22:24:19.950808: Current learning rate: 0.0076 +2024-11-21 22:24:39.713296: train_loss -0.7582 +2024-11-21 22:24:39.716141: val_loss -0.7528 +2024-11-21 22:24:39.716292: Pseudo dice [0.8434] +2024-11-21 22:24:39.716394: Epoch time: 19.76 s +2024-11-21 22:24:40.736459: +2024-11-21 22:24:40.736686: Epoch 2101 +2024-11-21 22:24:40.736808: Current learning rate: 0.0076 +2024-11-21 22:25:00.338650: train_loss -0.7615 +2024-11-21 22:25:00.341930: val_loss -0.7636 +2024-11-21 22:25:00.342046: Pseudo dice [0.8573] +2024-11-21 22:25:00.342160: Epoch time: 19.6 s +2024-11-21 22:25:01.152130: +2024-11-21 22:25:01.152375: Epoch 2102 +2024-11-21 22:25:01.152508: Current learning rate: 0.0076 +2024-11-21 22:25:20.062516: train_loss -0.7652 +2024-11-21 22:25:20.091576: val_loss -0.7364 +2024-11-21 22:25:20.091761: Pseudo dice [0.8278] +2024-11-21 22:25:20.091892: Epoch time: 18.91 s +2024-11-21 22:25:20.999232: +2024-11-21 22:25:20.999456: Epoch 2103 +2024-11-21 22:25:20.999586: Current learning rate: 0.0076 +2024-11-21 22:25:40.612709: train_loss -0.7542 +2024-11-21 22:25:40.620636: val_loss -0.7563 +2024-11-21 22:25:40.620782: Pseudo dice [0.8322] +2024-11-21 22:25:40.620878: Epoch time: 19.61 s +2024-11-21 22:25:41.475432: +2024-11-21 22:25:41.475644: Epoch 2104 +2024-11-21 22:25:41.475761: Current learning rate: 0.0076 +2024-11-21 22:25:58.763660: train_loss -0.7449 +2024-11-21 22:25:58.771071: val_loss -0.7422 +2024-11-21 22:25:58.771216: Pseudo dice [0.8322] +2024-11-21 22:25:58.771311: Epoch time: 17.29 s +2024-11-21 22:25:59.762587: +2024-11-21 22:25:59.762791: Epoch 2105 +2024-11-21 22:25:59.762918: Current learning rate: 0.0076 +2024-11-21 22:26:18.720246: train_loss -0.764 +2024-11-21 22:26:18.726981: val_loss -0.7731 +2024-11-21 22:26:18.727112: Pseudo dice [0.8475] +2024-11-21 22:26:18.727207: Epoch time: 18.96 s +2024-11-21 22:26:19.624847: +2024-11-21 22:26:19.625053: Epoch 2106 +2024-11-21 22:26:19.625176: Current learning rate: 0.0076 +2024-11-21 22:26:39.461504: train_loss -0.7591 +2024-11-21 22:26:39.467694: val_loss -0.7378 +2024-11-21 22:26:39.467833: Pseudo dice [0.8256] +2024-11-21 22:26:39.467927: Epoch time: 19.84 s +2024-11-21 22:26:40.456564: +2024-11-21 22:26:40.456782: Epoch 2107 +2024-11-21 22:26:40.456902: Current learning rate: 0.00759 +2024-11-21 22:27:00.282735: train_loss -0.7514 +2024-11-21 22:27:00.288031: val_loss -0.7498 +2024-11-21 22:27:00.288177: Pseudo dice [0.8414] +2024-11-21 22:27:00.288541: Epoch time: 19.83 s +2024-11-21 22:27:01.121144: +2024-11-21 22:27:01.121367: Epoch 2108 +2024-11-21 22:27:01.121500: Current learning rate: 0.00759 +2024-11-21 22:27:20.719483: train_loss -0.7528 +2024-11-21 22:27:20.721546: val_loss -0.749 +2024-11-21 22:27:20.721684: Pseudo dice [0.8424] +2024-11-21 22:27:20.721779: Epoch time: 19.6 s +2024-11-21 22:27:21.692260: +2024-11-21 22:27:21.692537: Epoch 2109 +2024-11-21 22:27:21.692664: Current learning rate: 0.00759 +2024-11-21 22:27:41.408901: train_loss -0.7509 +2024-11-21 22:27:41.416659: val_loss -0.7461 +2024-11-21 22:27:41.416791: Pseudo dice [0.8428] +2024-11-21 22:27:41.416895: Epoch time: 19.72 s +2024-11-21 22:27:42.305356: +2024-11-21 22:27:42.305580: Epoch 2110 +2024-11-21 22:27:42.305696: Current learning rate: 0.00759 +2024-11-21 22:28:01.139404: train_loss -0.7383 +2024-11-21 22:28:01.143834: val_loss -0.74 +2024-11-21 22:28:01.143966: Pseudo dice [0.8278] +2024-11-21 22:28:01.144066: Epoch time: 18.82 s +2024-11-21 22:28:02.171436: +2024-11-21 22:28:02.171642: Epoch 2111 +2024-11-21 22:28:02.171757: Current learning rate: 0.00759 +2024-11-21 22:28:20.823012: train_loss -0.7603 +2024-11-21 22:28:20.830037: val_loss -0.7767 +2024-11-21 22:28:20.830268: Pseudo dice [0.8531] +2024-11-21 22:28:20.830374: Epoch time: 18.65 s +2024-11-21 22:28:21.843884: +2024-11-21 22:28:21.844085: Epoch 2112 +2024-11-21 22:28:21.844200: Current learning rate: 0.00759 +2024-11-21 22:28:41.158081: train_loss -0.7707 +2024-11-21 22:28:41.161289: val_loss -0.7702 +2024-11-21 22:28:41.161395: Pseudo dice [0.8487] +2024-11-21 22:28:41.161486: Epoch time: 19.32 s +2024-11-21 22:28:41.968218: +2024-11-21 22:28:41.968442: Epoch 2113 +2024-11-21 22:28:41.968565: Current learning rate: 0.00759 +2024-11-21 22:29:00.903773: train_loss -0.7718 +2024-11-21 22:29:00.909902: val_loss -0.7466 +2024-11-21 22:29:00.910092: Pseudo dice [0.8445] +2024-11-21 22:29:00.910222: Epoch time: 18.94 s +2024-11-21 22:29:01.722672: +2024-11-21 22:29:01.722886: Epoch 2114 +2024-11-21 22:29:01.723020: Current learning rate: 0.00759 +2024-11-21 22:29:21.065253: train_loss -0.7677 +2024-11-21 22:29:21.073092: val_loss -0.7653 +2024-11-21 22:29:21.073214: Pseudo dice [0.8586] +2024-11-21 22:29:21.073312: Epoch time: 19.34 s +2024-11-21 22:29:22.099757: +2024-11-21 22:29:22.099995: Epoch 2115 +2024-11-21 22:29:22.100116: Current learning rate: 0.00759 +2024-11-21 22:29:41.035541: train_loss -0.77 +2024-11-21 22:29:41.041875: val_loss -0.7833 +2024-11-21 22:29:41.042017: Pseudo dice [0.8327] +2024-11-21 22:29:41.042147: Epoch time: 18.94 s +2024-11-21 22:29:41.865143: +2024-11-21 22:29:41.865374: Epoch 2116 +2024-11-21 22:29:41.865502: Current learning rate: 0.00758 +2024-11-21 22:30:00.270871: train_loss -0.7444 +2024-11-21 22:30:00.286136: val_loss -0.7561 +2024-11-21 22:30:00.286303: Pseudo dice [0.8398] +2024-11-21 22:30:00.286400: Epoch time: 18.41 s +2024-11-21 22:30:01.111252: +2024-11-21 22:30:01.111458: Epoch 2117 +2024-11-21 22:30:01.111583: Current learning rate: 0.00758 +2024-11-21 22:30:20.493543: train_loss -0.7617 +2024-11-21 22:30:20.497537: val_loss -0.7481 +2024-11-21 22:30:20.497673: Pseudo dice [0.8387] +2024-11-21 22:30:20.497776: Epoch time: 19.38 s +2024-11-21 22:30:21.349344: +2024-11-21 22:30:21.349812: Epoch 2118 +2024-11-21 22:30:21.349939: Current learning rate: 0.00758 +2024-11-21 22:30:39.973423: train_loss -0.7625 +2024-11-21 22:30:39.980157: val_loss -0.7548 +2024-11-21 22:30:39.980309: Pseudo dice [0.8597] +2024-11-21 22:30:39.980411: Epoch time: 18.62 s +2024-11-21 22:30:40.932592: +2024-11-21 22:30:40.932789: Epoch 2119 +2024-11-21 22:30:40.932906: Current learning rate: 0.00758 +2024-11-21 22:30:59.690968: train_loss -0.769 +2024-11-21 22:30:59.698292: val_loss -0.7282 +2024-11-21 22:30:59.698431: Pseudo dice [0.8182] +2024-11-21 22:30:59.698532: Epoch time: 18.76 s +2024-11-21 22:31:00.561756: +2024-11-21 22:31:00.561967: Epoch 2120 +2024-11-21 22:31:00.562100: Current learning rate: 0.00758 +2024-11-21 22:31:19.814091: train_loss -0.7654 +2024-11-21 22:31:19.822342: val_loss -0.7508 +2024-11-21 22:31:19.822481: Pseudo dice [0.8523] +2024-11-21 22:31:19.822580: Epoch time: 19.25 s +2024-11-21 22:31:20.701662: +2024-11-21 22:31:20.701909: Epoch 2121 +2024-11-21 22:31:20.702028: Current learning rate: 0.00758 +2024-11-21 22:31:39.456588: train_loss -0.7711 +2024-11-21 22:31:39.458954: val_loss -0.7658 +2024-11-21 22:31:39.459104: Pseudo dice [0.8469] +2024-11-21 22:31:39.459215: Epoch time: 18.76 s +2024-11-21 22:31:40.404018: +2024-11-21 22:31:40.404254: Epoch 2122 +2024-11-21 22:31:40.404384: Current learning rate: 0.00758 +2024-11-21 22:31:59.871634: train_loss -0.765 +2024-11-21 22:31:59.874266: val_loss -0.7405 +2024-11-21 22:31:59.874379: Pseudo dice [0.849] +2024-11-21 22:31:59.874460: Epoch time: 19.47 s +2024-11-21 22:32:00.813043: +2024-11-21 22:32:00.813286: Epoch 2123 +2024-11-21 22:32:00.813409: Current learning rate: 0.00758 +2024-11-21 22:32:21.365341: train_loss -0.7694 +2024-11-21 22:32:21.370574: val_loss -0.7546 +2024-11-21 22:32:21.370716: Pseudo dice [0.8278] +2024-11-21 22:32:21.370830: Epoch time: 20.55 s +2024-11-21 22:32:22.269068: +2024-11-21 22:32:22.269298: Epoch 2124 +2024-11-21 22:32:22.269427: Current learning rate: 0.00758 +2024-11-21 22:32:41.121159: train_loss -0.7771 +2024-11-21 22:32:41.132138: val_loss -0.7468 +2024-11-21 22:32:41.132252: Pseudo dice [0.837] +2024-11-21 22:32:41.132341: Epoch time: 18.85 s +2024-11-21 22:32:42.261709: +2024-11-21 22:32:42.261921: Epoch 2125 +2024-11-21 22:32:42.262038: Current learning rate: 0.00757 +2024-11-21 22:33:00.281421: train_loss -0.7812 +2024-11-21 22:33:00.289983: val_loss -0.7648 +2024-11-21 22:33:00.290175: Pseudo dice [0.8529] +2024-11-21 22:33:00.290265: Epoch time: 18.02 s +2024-11-21 22:33:01.266683: +2024-11-21 22:33:01.266929: Epoch 2126 +2024-11-21 22:33:01.267056: Current learning rate: 0.00757 +2024-11-21 22:33:20.040635: train_loss -0.7731 +2024-11-21 22:33:20.045728: val_loss -0.7551 +2024-11-21 22:33:20.045874: Pseudo dice [0.8334] +2024-11-21 22:33:20.045980: Epoch time: 18.77 s +2024-11-21 22:33:20.966542: +2024-11-21 22:33:20.966769: Epoch 2127 +2024-11-21 22:33:20.966889: Current learning rate: 0.00757 +2024-11-21 22:33:41.326110: train_loss -0.7616 +2024-11-21 22:33:41.335384: val_loss -0.7652 +2024-11-21 22:33:41.336048: Pseudo dice [0.8481] +2024-11-21 22:33:41.336580: Epoch time: 20.36 s +2024-11-21 22:33:42.491817: +2024-11-21 22:33:42.492055: Epoch 2128 +2024-11-21 22:33:42.492194: Current learning rate: 0.00757 +2024-11-21 22:34:01.923829: train_loss -0.7775 +2024-11-21 22:34:01.930856: val_loss -0.759 +2024-11-21 22:34:01.930974: Pseudo dice [0.8457] +2024-11-21 22:34:01.931082: Epoch time: 19.43 s +2024-11-21 22:34:02.766794: +2024-11-21 22:34:02.767006: Epoch 2129 +2024-11-21 22:34:02.767143: Current learning rate: 0.00757 +2024-11-21 22:34:20.876617: train_loss -0.774 +2024-11-21 22:34:20.884328: val_loss -0.7615 +2024-11-21 22:34:20.884462: Pseudo dice [0.8463] +2024-11-21 22:34:20.884563: Epoch time: 18.11 s +2024-11-21 22:34:21.806029: +2024-11-21 22:34:21.806266: Epoch 2130 +2024-11-21 22:34:21.806401: Current learning rate: 0.00757 +2024-11-21 22:34:40.181671: train_loss -0.762 +2024-11-21 22:34:40.189617: val_loss -0.7639 +2024-11-21 22:34:40.189747: Pseudo dice [0.8499] +2024-11-21 22:34:40.196921: Epoch time: 18.38 s +2024-11-21 22:34:41.183843: +2024-11-21 22:34:41.184088: Epoch 2131 +2024-11-21 22:34:41.184207: Current learning rate: 0.00757 +2024-11-21 22:35:00.439144: train_loss -0.7701 +2024-11-21 22:35:00.445673: val_loss -0.7601 +2024-11-21 22:35:00.445810: Pseudo dice [0.8305] +2024-11-21 22:35:00.445902: Epoch time: 19.26 s +2024-11-21 22:35:01.259265: +2024-11-21 22:35:01.259473: Epoch 2132 +2024-11-21 22:35:01.259597: Current learning rate: 0.00757 +2024-11-21 22:35:19.679798: train_loss -0.7771 +2024-11-21 22:35:19.688220: val_loss -0.7669 +2024-11-21 22:35:19.688384: Pseudo dice [0.8512] +2024-11-21 22:35:19.688539: Epoch time: 18.42 s +2024-11-21 22:35:20.725268: +2024-11-21 22:35:20.725506: Epoch 2133 +2024-11-21 22:35:20.725639: Current learning rate: 0.00756 +2024-11-21 22:35:39.780002: train_loss -0.7685 +2024-11-21 22:35:39.786450: val_loss -0.7854 +2024-11-21 22:35:39.786820: Pseudo dice [0.8612] +2024-11-21 22:35:39.786916: Epoch time: 19.06 s +2024-11-21 22:35:40.598687: +2024-11-21 22:35:40.598882: Epoch 2134 +2024-11-21 22:35:40.599011: Current learning rate: 0.00756 +2024-11-21 22:35:58.959611: train_loss -0.7625 +2024-11-21 22:35:58.964899: val_loss -0.7469 +2024-11-21 22:35:58.965022: Pseudo dice [0.8492] +2024-11-21 22:35:58.965136: Epoch time: 18.36 s +2024-11-21 22:35:59.978201: +2024-11-21 22:35:59.978421: Epoch 2135 +2024-11-21 22:35:59.978538: Current learning rate: 0.00756 +2024-11-21 22:36:19.470413: train_loss -0.7672 +2024-11-21 22:36:19.477218: val_loss -0.7867 +2024-11-21 22:36:19.477393: Pseudo dice [0.8485] +2024-11-21 22:36:19.477479: Epoch time: 19.49 s +2024-11-21 22:36:20.346744: +2024-11-21 22:36:20.346991: Epoch 2136 +2024-11-21 22:36:20.347114: Current learning rate: 0.00756 +2024-11-21 22:36:39.929653: train_loss -0.7664 +2024-11-21 22:36:39.941389: val_loss -0.7211 +2024-11-21 22:36:39.941583: Pseudo dice [0.8569] +2024-11-21 22:36:39.941668: Epoch time: 19.58 s +2024-11-21 22:36:40.753595: +2024-11-21 22:36:40.753804: Epoch 2137 +2024-11-21 22:36:40.753944: Current learning rate: 0.00756 +2024-11-21 22:36:59.031617: train_loss -0.7809 +2024-11-21 22:36:59.036422: val_loss -0.7573 +2024-11-21 22:36:59.036588: Pseudo dice [0.8473] +2024-11-21 22:36:59.036716: Epoch time: 18.28 s +2024-11-21 22:36:59.959594: +2024-11-21 22:36:59.959825: Epoch 2138 +2024-11-21 22:36:59.959944: Current learning rate: 0.00756 +2024-11-21 22:37:19.496791: train_loss -0.7714 +2024-11-21 22:37:19.503450: val_loss -0.7597 +2024-11-21 22:37:19.503599: Pseudo dice [0.8495] +2024-11-21 22:37:19.503692: Epoch time: 19.54 s +2024-11-21 22:37:20.518904: +2024-11-21 22:37:20.519130: Epoch 2139 +2024-11-21 22:37:20.519249: Current learning rate: 0.00756 +2024-11-21 22:37:41.302419: train_loss -0.7694 +2024-11-21 22:37:41.309211: val_loss -0.7684 +2024-11-21 22:37:41.309400: Pseudo dice [0.8567] +2024-11-21 22:37:41.309515: Epoch time: 20.78 s +2024-11-21 22:37:42.135482: +2024-11-21 22:37:42.135680: Epoch 2140 +2024-11-21 22:37:42.135792: Current learning rate: 0.00756 +2024-11-21 22:38:01.339819: train_loss -0.7712 +2024-11-21 22:38:01.365756: val_loss -0.755 +2024-11-21 22:38:01.365933: Pseudo dice [0.8459] +2024-11-21 22:38:01.366030: Epoch time: 19.21 s +2024-11-21 22:38:02.181504: +2024-11-21 22:38:02.181721: Epoch 2141 +2024-11-21 22:38:02.181845: Current learning rate: 0.00756 +2024-11-21 22:38:20.099878: train_loss -0.7776 +2024-11-21 22:38:20.106847: val_loss -0.7733 +2024-11-21 22:38:20.106994: Pseudo dice [0.8642] +2024-11-21 22:38:20.107083: Epoch time: 17.92 s +2024-11-21 22:38:20.964794: +2024-11-21 22:38:20.965012: Epoch 2142 +2024-11-21 22:38:20.965149: Current learning rate: 0.00755 +2024-11-21 22:38:40.561128: train_loss -0.7807 +2024-11-21 22:38:40.569278: val_loss -0.7721 +2024-11-21 22:38:40.569392: Pseudo dice [0.8345] +2024-11-21 22:38:40.569486: Epoch time: 19.6 s +2024-11-21 22:38:41.378543: +2024-11-21 22:38:41.378749: Epoch 2143 +2024-11-21 22:38:41.378862: Current learning rate: 0.00755 +2024-11-21 22:39:00.424073: train_loss -0.778 +2024-11-21 22:39:00.431310: val_loss -0.7709 +2024-11-21 22:39:00.431472: Pseudo dice [0.8581] +2024-11-21 22:39:00.431572: Epoch time: 19.05 s +2024-11-21 22:39:01.332862: +2024-11-21 22:39:01.333106: Epoch 2144 +2024-11-21 22:39:01.333240: Current learning rate: 0.00755 +2024-11-21 22:39:21.115696: train_loss -0.7822 +2024-11-21 22:39:21.122516: val_loss -0.7739 +2024-11-21 22:39:21.122659: Pseudo dice [0.8548] +2024-11-21 22:39:21.122767: Epoch time: 19.78 s +2024-11-21 22:39:22.167913: +2024-11-21 22:39:22.168158: Epoch 2145 +2024-11-21 22:39:22.168292: Current learning rate: 0.00755 +2024-11-21 22:39:40.558511: train_loss -0.7764 +2024-11-21 22:39:40.567053: val_loss -0.7687 +2024-11-21 22:39:40.567254: Pseudo dice [0.8621] +2024-11-21 22:39:40.567352: Epoch time: 18.39 s +2024-11-21 22:39:41.409086: +2024-11-21 22:39:41.409309: Epoch 2146 +2024-11-21 22:39:41.409427: Current learning rate: 0.00755 +2024-11-21 22:40:00.684869: train_loss -0.779 +2024-11-21 22:40:00.691508: val_loss -0.7713 +2024-11-21 22:40:00.691652: Pseudo dice [0.8457] +2024-11-21 22:40:00.691752: Epoch time: 19.28 s +2024-11-21 22:40:01.596872: +2024-11-21 22:40:01.597105: Epoch 2147 +2024-11-21 22:40:01.597215: Current learning rate: 0.00755 +2024-11-21 22:40:20.481538: train_loss -0.7737 +2024-11-21 22:40:20.489023: val_loss -0.7572 +2024-11-21 22:40:20.489151: Pseudo dice [0.846] +2024-11-21 22:40:20.489246: Epoch time: 18.89 s +2024-11-21 22:40:21.328217: +2024-11-21 22:40:21.328435: Epoch 2148 +2024-11-21 22:40:21.328562: Current learning rate: 0.00755 +2024-11-21 22:40:41.142310: train_loss -0.7686 +2024-11-21 22:40:41.147338: val_loss -0.7622 +2024-11-21 22:40:41.147499: Pseudo dice [0.8532] +2024-11-21 22:40:41.147602: Epoch time: 19.81 s +2024-11-21 22:40:42.014039: +2024-11-21 22:40:42.014481: Epoch 2149 +2024-11-21 22:40:42.014631: Current learning rate: 0.00755 +2024-11-21 22:41:01.044843: train_loss -0.7733 +2024-11-21 22:41:01.057305: val_loss -0.786 +2024-11-21 22:41:01.057463: Pseudo dice [0.8537] +2024-11-21 22:41:01.057571: Epoch time: 19.03 s +2024-11-21 22:41:02.175157: +2024-11-21 22:41:02.175607: Epoch 2150 +2024-11-21 22:41:02.175764: Current learning rate: 0.00755 +2024-11-21 22:41:21.265515: train_loss -0.7805 +2024-11-21 22:41:21.272114: val_loss -0.7589 +2024-11-21 22:41:21.272243: Pseudo dice [0.8413] +2024-11-21 22:41:21.272336: Epoch time: 19.09 s +2024-11-21 22:41:22.307141: +2024-11-21 22:41:22.307630: Epoch 2151 +2024-11-21 22:41:22.307769: Current learning rate: 0.00754 +2024-11-21 22:41:40.849528: train_loss -0.774 +2024-11-21 22:41:40.858248: val_loss -0.7773 +2024-11-21 22:41:40.858630: Pseudo dice [0.8548] +2024-11-21 22:41:40.858802: Epoch time: 18.54 s +2024-11-21 22:41:41.674287: +2024-11-21 22:41:41.674725: Epoch 2152 +2024-11-21 22:41:41.674869: Current learning rate: 0.00754 +2024-11-21 22:42:00.648721: train_loss -0.7793 +2024-11-21 22:42:00.655609: val_loss -0.7661 +2024-11-21 22:42:00.655734: Pseudo dice [0.8424] +2024-11-21 22:42:00.655837: Epoch time: 18.98 s +2024-11-21 22:42:01.672998: +2024-11-21 22:42:01.673464: Epoch 2153 +2024-11-21 22:42:01.673604: Current learning rate: 0.00754 +2024-11-21 22:42:20.735108: train_loss -0.7673 +2024-11-21 22:42:20.750853: val_loss -0.7756 +2024-11-21 22:42:20.750985: Pseudo dice [0.8429] +2024-11-21 22:42:20.751093: Epoch time: 19.06 s +2024-11-21 22:42:21.598394: +2024-11-21 22:42:21.598831: Epoch 2154 +2024-11-21 22:42:21.598973: Current learning rate: 0.00754 +2024-11-21 22:42:40.565098: train_loss -0.7657 +2024-11-21 22:42:40.573752: val_loss -0.7533 +2024-11-21 22:42:40.573904: Pseudo dice [0.8362] +2024-11-21 22:42:40.574053: Epoch time: 18.97 s +2024-11-21 22:42:41.435479: +2024-11-21 22:42:41.435878: Epoch 2155 +2024-11-21 22:42:41.436014: Current learning rate: 0.00754 +2024-11-21 22:43:01.162028: train_loss -0.7596 +2024-11-21 22:43:01.170337: val_loss -0.7579 +2024-11-21 22:43:01.170480: Pseudo dice [0.8351] +2024-11-21 22:43:01.170592: Epoch time: 19.73 s +2024-11-21 22:43:02.142940: +2024-11-21 22:43:02.143356: Epoch 2156 +2024-11-21 22:43:02.143753: Current learning rate: 0.00754 +2024-11-21 22:43:21.470099: train_loss -0.7599 +2024-11-21 22:43:21.475188: val_loss -0.7556 +2024-11-21 22:43:21.475316: Pseudo dice [0.8366] +2024-11-21 22:43:21.475427: Epoch time: 19.33 s +2024-11-21 22:43:22.409296: +2024-11-21 22:43:22.409762: Epoch 2157 +2024-11-21 22:43:22.409907: Current learning rate: 0.00754 +2024-11-21 22:43:40.928921: train_loss -0.7732 +2024-11-21 22:43:40.940618: val_loss -0.7698 +2024-11-21 22:43:40.940746: Pseudo dice [0.8425] +2024-11-21 22:43:40.940853: Epoch time: 18.52 s +2024-11-21 22:43:41.774105: +2024-11-21 22:43:41.774309: Epoch 2158 +2024-11-21 22:43:41.774448: Current learning rate: 0.00754 +2024-11-21 22:44:01.480740: train_loss -0.752 +2024-11-21 22:44:01.487867: val_loss -0.7421 +2024-11-21 22:44:01.488004: Pseudo dice [0.8443] +2024-11-21 22:44:01.488149: Epoch time: 19.71 s +2024-11-21 22:44:02.299676: +2024-11-21 22:44:02.299876: Epoch 2159 +2024-11-21 22:44:02.300008: Current learning rate: 0.00753 +2024-11-21 22:44:21.035235: train_loss -0.7649 +2024-11-21 22:44:21.041031: val_loss -0.7566 +2024-11-21 22:44:21.041448: Pseudo dice [0.8468] +2024-11-21 22:44:21.041548: Epoch time: 18.74 s +2024-11-21 22:44:22.252253: +2024-11-21 22:44:22.252682: Epoch 2160 +2024-11-21 22:44:22.252823: Current learning rate: 0.00753 +2024-11-21 22:44:41.709574: train_loss -0.7532 +2024-11-21 22:44:41.717486: val_loss -0.7675 +2024-11-21 22:44:41.717620: Pseudo dice [0.8427] +2024-11-21 22:44:41.717723: Epoch time: 19.46 s +2024-11-21 22:44:42.575033: +2024-11-21 22:44:42.575464: Epoch 2161 +2024-11-21 22:44:42.575608: Current learning rate: 0.00753 +2024-11-21 22:45:02.398138: train_loss -0.764 +2024-11-21 22:45:02.404084: val_loss -0.7722 +2024-11-21 22:45:02.404202: Pseudo dice [0.8471] +2024-11-21 22:45:02.404292: Epoch time: 19.82 s +2024-11-21 22:45:03.301293: +2024-11-21 22:45:03.301732: Epoch 2162 +2024-11-21 22:45:03.301885: Current learning rate: 0.00753 +2024-11-21 22:45:22.916397: train_loss -0.7693 +2024-11-21 22:45:22.924174: val_loss -0.7645 +2024-11-21 22:45:22.924322: Pseudo dice [0.8433] +2024-11-21 22:45:22.924426: Epoch time: 19.62 s +2024-11-21 22:45:23.863920: +2024-11-21 22:45:23.864328: Epoch 2163 +2024-11-21 22:45:23.864476: Current learning rate: 0.00753 +2024-11-21 22:45:43.507164: train_loss -0.7671 +2024-11-21 22:45:43.515164: val_loss -0.7503 +2024-11-21 22:45:43.515292: Pseudo dice [0.8365] +2024-11-21 22:45:43.515382: Epoch time: 19.64 s +2024-11-21 22:45:44.423435: +2024-11-21 22:45:44.423869: Epoch 2164 +2024-11-21 22:45:44.424012: Current learning rate: 0.00753 +2024-11-21 22:46:02.990897: train_loss -0.7629 +2024-11-21 22:46:03.008789: val_loss -0.776 +2024-11-21 22:46:03.008939: Pseudo dice [0.8503] +2024-11-21 22:46:03.009039: Epoch time: 18.57 s +2024-11-21 22:46:04.019395: +2024-11-21 22:46:04.019844: Epoch 2165 +2024-11-21 22:46:04.019999: Current learning rate: 0.00753 +2024-11-21 22:46:23.342998: train_loss -0.7676 +2024-11-21 22:46:23.355822: val_loss -0.7512 +2024-11-21 22:46:23.355994: Pseudo dice [0.8422] +2024-11-21 22:46:23.356096: Epoch time: 19.32 s +2024-11-21 22:46:24.401779: +2024-11-21 22:46:24.402244: Epoch 2166 +2024-11-21 22:46:24.402409: Current learning rate: 0.00753 +2024-11-21 22:46:42.873076: train_loss -0.776 +2024-11-21 22:46:42.881489: val_loss -0.7634 +2024-11-21 22:46:42.881639: Pseudo dice [0.8499] +2024-11-21 22:46:42.881809: Epoch time: 18.47 s +2024-11-21 22:46:43.873158: +2024-11-21 22:46:43.880599: Epoch 2167 +2024-11-21 22:46:43.880748: Current learning rate: 0.00753 +2024-11-21 22:47:03.748439: train_loss -0.779 +2024-11-21 22:47:03.756851: val_loss -0.7677 +2024-11-21 22:47:03.757005: Pseudo dice [0.8486] +2024-11-21 22:47:03.757115: Epoch time: 19.88 s +2024-11-21 22:47:04.747370: +2024-11-21 22:47:04.747888: Epoch 2168 +2024-11-21 22:47:04.748039: Current learning rate: 0.00752 +2024-11-21 22:47:24.050400: train_loss -0.7723 +2024-11-21 22:47:24.058075: val_loss -0.7655 +2024-11-21 22:47:24.058226: Pseudo dice [0.8598] +2024-11-21 22:47:24.058637: Epoch time: 19.3 s +2024-11-21 22:47:24.882313: +2024-11-21 22:47:24.882735: Epoch 2169 +2024-11-21 22:47:24.882875: Current learning rate: 0.00752 +2024-11-21 22:47:44.681903: train_loss -0.779 +2024-11-21 22:47:44.687956: val_loss -0.7716 +2024-11-21 22:47:44.688127: Pseudo dice [0.8528] +2024-11-21 22:47:44.688240: Epoch time: 19.8 s +2024-11-21 22:47:45.517608: +2024-11-21 22:47:45.517885: Epoch 2170 +2024-11-21 22:47:45.518030: Current learning rate: 0.00752 +2024-11-21 22:48:05.238225: train_loss -0.7722 +2024-11-21 22:48:05.241087: val_loss -0.7877 +2024-11-21 22:48:05.241310: Pseudo dice [0.844] +2024-11-21 22:48:05.241404: Epoch time: 19.72 s +2024-11-21 22:48:06.195841: +2024-11-21 22:48:06.196070: Epoch 2171 +2024-11-21 22:48:06.196187: Current learning rate: 0.00752 +2024-11-21 22:48:24.441150: train_loss -0.7641 +2024-11-21 22:48:24.443542: val_loss -0.7291 +2024-11-21 22:48:24.443683: Pseudo dice [0.8487] +2024-11-21 22:48:24.443780: Epoch time: 18.25 s +2024-11-21 22:48:25.663954: +2024-11-21 22:48:25.664175: Epoch 2172 +2024-11-21 22:48:25.664300: Current learning rate: 0.00752 +2024-11-21 22:48:45.106594: train_loss -0.7665 +2024-11-21 22:48:45.112029: val_loss -0.786 +2024-11-21 22:48:45.112145: Pseudo dice [0.8504] +2024-11-21 22:48:45.112245: Epoch time: 19.44 s +2024-11-21 22:48:46.069225: +2024-11-21 22:48:46.069436: Epoch 2173 +2024-11-21 22:48:46.069562: Current learning rate: 0.00752 +2024-11-21 22:49:04.911880: train_loss -0.7691 +2024-11-21 22:49:04.918902: val_loss -0.7696 +2024-11-21 22:49:04.919054: Pseudo dice [0.8518] +2024-11-21 22:49:04.919158: Epoch time: 18.84 s +2024-11-21 22:49:05.719836: +2024-11-21 22:49:05.720050: Epoch 2174 +2024-11-21 22:49:05.720185: Current learning rate: 0.00752 +2024-11-21 22:49:25.149671: train_loss -0.784 +2024-11-21 22:49:25.155564: val_loss -0.7661 +2024-11-21 22:49:25.155695: Pseudo dice [0.8558] +2024-11-21 22:49:25.155790: Epoch time: 19.43 s +2024-11-21 22:49:25.977109: +2024-11-21 22:49:25.977340: Epoch 2175 +2024-11-21 22:49:25.977463: Current learning rate: 0.00752 +2024-11-21 22:49:44.988303: train_loss -0.7703 +2024-11-21 22:49:44.993151: val_loss -0.7617 +2024-11-21 22:49:44.993287: Pseudo dice [0.8583] +2024-11-21 22:49:44.993386: Epoch time: 19.01 s +2024-11-21 22:49:46.005308: +2024-11-21 22:49:46.005512: Epoch 2176 +2024-11-21 22:49:46.005637: Current learning rate: 0.00751 +2024-11-21 22:50:05.734054: train_loss -0.7699 +2024-11-21 22:50:05.741640: val_loss -0.7628 +2024-11-21 22:50:05.741775: Pseudo dice [0.8337] +2024-11-21 22:50:05.741878: Epoch time: 19.73 s +2024-11-21 22:50:06.668863: +2024-11-21 22:50:06.669073: Epoch 2177 +2024-11-21 22:50:06.669189: Current learning rate: 0.00751 +2024-11-21 22:50:24.635226: train_loss -0.7762 +2024-11-21 22:50:24.642425: val_loss -0.7547 +2024-11-21 22:50:24.642575: Pseudo dice [0.8396] +2024-11-21 22:50:24.642657: Epoch time: 17.97 s +2024-11-21 22:50:25.461313: +2024-11-21 22:50:25.461529: Epoch 2178 +2024-11-21 22:50:25.461653: Current learning rate: 0.00751 +2024-11-21 22:50:44.489779: train_loss -0.7655 +2024-11-21 22:50:44.492460: val_loss -0.7359 +2024-11-21 22:50:44.492602: Pseudo dice [0.8369] +2024-11-21 22:50:44.492686: Epoch time: 19.03 s +2024-11-21 22:50:45.346696: +2024-11-21 22:50:45.346907: Epoch 2179 +2024-11-21 22:50:45.347018: Current learning rate: 0.00751 +2024-11-21 22:51:04.651518: train_loss -0.7575 +2024-11-21 22:51:04.653604: val_loss -0.7826 +2024-11-21 22:51:04.653730: Pseudo dice [0.8505] +2024-11-21 22:51:04.653832: Epoch time: 19.31 s +2024-11-21 22:51:05.564965: +2024-11-21 22:51:05.565179: Epoch 2180 +2024-11-21 22:51:05.565311: Current learning rate: 0.00751 +2024-11-21 22:51:24.635189: train_loss -0.7717 +2024-11-21 22:51:24.639013: val_loss -0.7703 +2024-11-21 22:51:24.639162: Pseudo dice [0.8477] +2024-11-21 22:51:24.639272: Epoch time: 19.07 s +2024-11-21 22:51:25.533376: +2024-11-21 22:51:25.533595: Epoch 2181 +2024-11-21 22:51:25.533715: Current learning rate: 0.00751 +2024-11-21 22:51:43.714199: train_loss -0.7721 +2024-11-21 22:51:43.722443: val_loss -0.7417 +2024-11-21 22:51:43.722598: Pseudo dice [0.8464] +2024-11-21 22:51:43.722704: Epoch time: 18.18 s +2024-11-21 22:51:44.669125: +2024-11-21 22:51:44.669311: Epoch 2182 +2024-11-21 22:51:44.669427: Current learning rate: 0.00751 +2024-11-21 22:52:04.292311: train_loss -0.7711 +2024-11-21 22:52:04.298769: val_loss -0.7727 +2024-11-21 22:52:04.298917: Pseudo dice [0.8413] +2024-11-21 22:52:04.299016: Epoch time: 19.62 s +2024-11-21 22:52:05.110986: +2024-11-21 22:52:05.111188: Epoch 2183 +2024-11-21 22:52:05.111300: Current learning rate: 0.00751 +2024-11-21 22:52:26.103013: train_loss -0.7593 +2024-11-21 22:52:26.109257: val_loss -0.7778 +2024-11-21 22:52:26.109410: Pseudo dice [0.8517] +2024-11-21 22:52:26.109508: Epoch time: 20.99 s +2024-11-21 22:52:27.332797: +2024-11-21 22:52:27.333032: Epoch 2184 +2024-11-21 22:52:27.333151: Current learning rate: 0.00751 +2024-11-21 22:52:45.978185: train_loss -0.7612 +2024-11-21 22:52:45.985278: val_loss -0.763 +2024-11-21 22:52:45.985421: Pseudo dice [0.8394] +2024-11-21 22:52:45.985508: Epoch time: 18.65 s +2024-11-21 22:52:46.952770: +2024-11-21 22:52:46.952981: Epoch 2185 +2024-11-21 22:52:46.953111: Current learning rate: 0.0075 +2024-11-21 22:53:05.817451: train_loss -0.7662 +2024-11-21 22:53:05.835268: val_loss -0.7764 +2024-11-21 22:53:05.835431: Pseudo dice [0.8535] +2024-11-21 22:53:05.835530: Epoch time: 18.87 s +2024-11-21 22:53:06.684300: +2024-11-21 22:53:06.684549: Epoch 2186 +2024-11-21 22:53:06.684669: Current learning rate: 0.0075 +2024-11-21 22:53:26.773772: train_loss -0.7637 +2024-11-21 22:53:26.776616: val_loss -0.7637 +2024-11-21 22:53:26.776761: Pseudo dice [0.8553] +2024-11-21 22:53:26.776866: Epoch time: 20.09 s +2024-11-21 22:53:27.589139: +2024-11-21 22:53:27.589353: Epoch 2187 +2024-11-21 22:53:27.589494: Current learning rate: 0.0075 +2024-11-21 22:53:46.818475: train_loss -0.7683 +2024-11-21 22:53:46.820943: val_loss -0.764 +2024-11-21 22:53:46.821089: Pseudo dice [0.8537] +2024-11-21 22:53:46.821207: Epoch time: 19.23 s +2024-11-21 22:53:47.635276: +2024-11-21 22:53:47.635487: Epoch 2188 +2024-11-21 22:53:47.635627: Current learning rate: 0.0075 +2024-11-21 22:54:07.032506: train_loss -0.774 +2024-11-21 22:54:07.046004: val_loss -0.7727 +2024-11-21 22:54:07.046160: Pseudo dice [0.8615] +2024-11-21 22:54:07.046246: Epoch time: 19.4 s +2024-11-21 22:54:08.247837: +2024-11-21 22:54:08.248051: Epoch 2189 +2024-11-21 22:54:08.248180: Current learning rate: 0.0075 +2024-11-21 22:54:26.314139: train_loss -0.7633 +2024-11-21 22:54:26.334783: val_loss -0.7772 +2024-11-21 22:54:26.334951: Pseudo dice [0.8564] +2024-11-21 22:54:26.335053: Epoch time: 18.07 s +2024-11-21 22:54:27.396560: +2024-11-21 22:54:27.396752: Epoch 2190 +2024-11-21 22:54:27.396863: Current learning rate: 0.0075 +2024-11-21 22:54:46.350289: train_loss -0.7726 +2024-11-21 22:54:46.352012: val_loss -0.7562 +2024-11-21 22:54:46.352115: Pseudo dice [0.8424] +2024-11-21 22:54:46.352219: Epoch time: 18.95 s +2024-11-21 22:54:47.160532: +2024-11-21 22:54:47.160769: Epoch 2191 +2024-11-21 22:54:47.160887: Current learning rate: 0.0075 +2024-11-21 22:55:05.848006: train_loss -0.7765 +2024-11-21 22:55:05.862450: val_loss -0.7787 +2024-11-21 22:55:05.862603: Pseudo dice [0.8592] +2024-11-21 22:55:05.862697: Epoch time: 18.69 s +2024-11-21 22:55:06.831856: +2024-11-21 22:55:06.832073: Epoch 2192 +2024-11-21 22:55:06.832190: Current learning rate: 0.0075 +2024-11-21 22:55:26.787172: train_loss -0.7807 +2024-11-21 22:55:26.794379: val_loss -0.7698 +2024-11-21 22:55:26.794498: Pseudo dice [0.8539] +2024-11-21 22:55:26.794584: Epoch time: 19.96 s +2024-11-21 22:55:28.031650: +2024-11-21 22:55:28.031892: Epoch 2193 +2024-11-21 22:55:28.032012: Current learning rate: 0.0075 +2024-11-21 22:55:46.083290: train_loss -0.7755 +2024-11-21 22:55:46.088533: val_loss -0.781 +2024-11-21 22:55:46.088654: Pseudo dice [0.8504] +2024-11-21 22:55:46.088760: Epoch time: 18.05 s +2024-11-21 22:55:47.032856: +2024-11-21 22:55:47.033074: Epoch 2194 +2024-11-21 22:55:47.033208: Current learning rate: 0.00749 +2024-11-21 22:56:06.918601: train_loss -0.7769 +2024-11-21 22:56:06.925348: val_loss -0.7686 +2024-11-21 22:56:06.925501: Pseudo dice [0.8508] +2024-11-21 22:56:06.925606: Epoch time: 19.89 s +2024-11-21 22:56:07.801824: +2024-11-21 22:56:07.802050: Epoch 2195 +2024-11-21 22:56:07.802174: Current learning rate: 0.00749 +2024-11-21 22:56:28.548508: train_loss -0.7663 +2024-11-21 22:56:28.553546: val_loss -0.7618 +2024-11-21 22:56:28.553659: Pseudo dice [0.8412] +2024-11-21 22:56:28.553774: Epoch time: 20.75 s +2024-11-21 22:56:29.784400: +2024-11-21 22:56:29.784616: Epoch 2196 +2024-11-21 22:56:29.784737: Current learning rate: 0.00749 +2024-11-21 22:56:48.071912: train_loss -0.7757 +2024-11-21 22:56:48.078669: val_loss -0.7707 +2024-11-21 22:56:48.078833: Pseudo dice [0.8503] +2024-11-21 22:56:48.078923: Epoch time: 18.29 s +2024-11-21 22:56:48.887770: +2024-11-21 22:56:48.888044: Epoch 2197 +2024-11-21 22:56:48.888176: Current learning rate: 0.00749 +2024-11-21 22:57:07.747015: train_loss -0.7716 +2024-11-21 22:57:07.751510: val_loss -0.7488 +2024-11-21 22:57:07.751678: Pseudo dice [0.8465] +2024-11-21 22:57:07.751781: Epoch time: 18.86 s +2024-11-21 22:57:08.578083: +2024-11-21 22:57:08.578339: Epoch 2198 +2024-11-21 22:57:08.578485: Current learning rate: 0.00749 +2024-11-21 22:57:26.951159: train_loss -0.7677 +2024-11-21 22:57:26.953764: val_loss -0.7627 +2024-11-21 22:57:26.953918: Pseudo dice [0.8477] +2024-11-21 22:57:26.954021: Epoch time: 18.37 s +2024-11-21 22:57:27.760473: +2024-11-21 22:57:27.760706: Epoch 2199 +2024-11-21 22:57:27.760848: Current learning rate: 0.00749 +2024-11-21 22:57:47.417586: train_loss -0.7774 +2024-11-21 22:57:47.424536: val_loss -0.7721 +2024-11-21 22:57:47.424681: Pseudo dice [0.851] +2024-11-21 22:57:47.424777: Epoch time: 19.66 s +2024-11-21 22:57:48.459481: +2024-11-21 22:57:48.459700: Epoch 2200 +2024-11-21 22:57:48.459826: Current learning rate: 0.00749 +2024-11-21 22:58:06.840751: train_loss -0.7751 +2024-11-21 22:58:06.845810: val_loss -0.7587 +2024-11-21 22:58:06.845941: Pseudo dice [0.8362] +2024-11-21 22:58:06.846030: Epoch time: 18.38 s +2024-11-21 22:58:07.855303: +2024-11-21 22:58:07.855522: Epoch 2201 +2024-11-21 22:58:07.855647: Current learning rate: 0.00749 +2024-11-21 22:58:25.929109: train_loss -0.7654 +2024-11-21 22:58:25.936351: val_loss -0.7693 +2024-11-21 22:58:25.936488: Pseudo dice [0.8463] +2024-11-21 22:58:25.936571: Epoch time: 18.07 s +2024-11-21 22:58:26.804871: +2024-11-21 22:58:26.805089: Epoch 2202 +2024-11-21 22:58:26.805214: Current learning rate: 0.00748 +2024-11-21 22:58:45.696246: train_loss -0.7644 +2024-11-21 22:58:45.698629: val_loss -0.7762 +2024-11-21 22:58:45.698751: Pseudo dice [0.848] +2024-11-21 22:58:45.698874: Epoch time: 18.89 s +2024-11-21 22:58:46.510224: +2024-11-21 22:58:46.510439: Epoch 2203 +2024-11-21 22:58:46.510575: Current learning rate: 0.00748 +2024-11-21 22:59:05.741021: train_loss -0.7658 +2024-11-21 22:59:05.743087: val_loss -0.7811 +2024-11-21 22:59:05.743209: Pseudo dice [0.8354] +2024-11-21 22:59:05.743306: Epoch time: 19.23 s +2024-11-21 22:59:06.926811: +2024-11-21 22:59:06.927028: Epoch 2204 +2024-11-21 22:59:06.927166: Current learning rate: 0.00748 +2024-11-21 22:59:26.576050: train_loss -0.7778 +2024-11-21 22:59:26.577960: val_loss -0.7894 +2024-11-21 22:59:26.578101: Pseudo dice [0.84] +2024-11-21 22:59:26.578186: Epoch time: 19.65 s +2024-11-21 22:59:27.419683: +2024-11-21 22:59:27.419932: Epoch 2205 +2024-11-21 22:59:27.420045: Current learning rate: 0.00748 +2024-11-21 22:59:46.569324: train_loss -0.7837 +2024-11-21 22:59:46.575879: val_loss -0.7892 +2024-11-21 22:59:46.576011: Pseudo dice [0.8511] +2024-11-21 22:59:46.576107: Epoch time: 19.15 s +2024-11-21 22:59:47.439115: +2024-11-21 22:59:47.439324: Epoch 2206 +2024-11-21 22:59:47.439451: Current learning rate: 0.00748 +2024-11-21 23:00:07.602496: train_loss -0.7755 +2024-11-21 23:00:07.605000: val_loss -0.766 +2024-11-21 23:00:07.605123: Pseudo dice [0.8515] +2024-11-21 23:00:07.605207: Epoch time: 20.16 s +2024-11-21 23:00:08.428650: +2024-11-21 23:00:08.428857: Epoch 2207 +2024-11-21 23:00:08.428976: Current learning rate: 0.00748 +2024-11-21 23:00:27.427590: train_loss -0.773 +2024-11-21 23:00:27.438943: val_loss -0.7692 +2024-11-21 23:00:27.439125: Pseudo dice [0.8511] +2024-11-21 23:00:27.439243: Epoch time: 19.0 s +2024-11-21 23:00:28.707313: +2024-11-21 23:00:28.707541: Epoch 2208 +2024-11-21 23:00:28.707665: Current learning rate: 0.00748 +2024-11-21 23:00:47.295667: train_loss -0.77 +2024-11-21 23:00:47.316326: val_loss -0.7189 +2024-11-21 23:00:47.316452: Pseudo dice [0.848] +2024-11-21 23:00:47.316563: Epoch time: 18.59 s +2024-11-21 23:00:48.198004: +2024-11-21 23:00:48.198282: Epoch 2209 +2024-11-21 23:00:48.198421: Current learning rate: 0.00748 +2024-11-21 23:01:07.614667: train_loss -0.7734 +2024-11-21 23:01:07.618826: val_loss -0.7818 +2024-11-21 23:01:07.618945: Pseudo dice [0.8497] +2024-11-21 23:01:07.619024: Epoch time: 19.42 s +2024-11-21 23:01:08.590608: +2024-11-21 23:01:08.590843: Epoch 2210 +2024-11-21 23:01:08.590985: Current learning rate: 0.00748 +2024-11-21 23:01:27.567860: train_loss -0.7734 +2024-11-21 23:01:27.577711: val_loss -0.7495 +2024-11-21 23:01:27.577887: Pseudo dice [0.8437] +2024-11-21 23:01:27.577992: Epoch time: 18.98 s +2024-11-21 23:01:28.387636: +2024-11-21 23:01:28.387837: Epoch 2211 +2024-11-21 23:01:28.387956: Current learning rate: 0.00747 +2024-11-21 23:01:46.641683: train_loss -0.7627 +2024-11-21 23:01:46.649311: val_loss -0.7554 +2024-11-21 23:01:46.649472: Pseudo dice [0.8366] +2024-11-21 23:01:46.649558: Epoch time: 18.25 s +2024-11-21 23:01:47.577877: +2024-11-21 23:01:47.578109: Epoch 2212 +2024-11-21 23:01:47.578226: Current learning rate: 0.00747 +2024-11-21 23:02:06.893917: train_loss -0.7511 +2024-11-21 23:02:06.900843: val_loss -0.7434 +2024-11-21 23:02:06.900989: Pseudo dice [0.8431] +2024-11-21 23:02:06.901112: Epoch time: 19.32 s +2024-11-21 23:02:07.805226: +2024-11-21 23:02:07.805460: Epoch 2213 +2024-11-21 23:02:07.805578: Current learning rate: 0.00747 +2024-11-21 23:02:25.950779: train_loss -0.7573 +2024-11-21 23:02:25.958280: val_loss -0.7728 +2024-11-21 23:02:25.958415: Pseudo dice [0.8483] +2024-11-21 23:02:25.958502: Epoch time: 18.15 s +2024-11-21 23:02:26.864605: +2024-11-21 23:02:26.864814: Epoch 2214 +2024-11-21 23:02:26.864956: Current learning rate: 0.00747 +2024-11-21 23:02:46.870223: train_loss -0.7403 +2024-11-21 23:02:46.874151: val_loss -0.76 +2024-11-21 23:02:46.874276: Pseudo dice [0.8533] +2024-11-21 23:02:46.874372: Epoch time: 20.01 s +2024-11-21 23:02:47.683293: +2024-11-21 23:02:47.683507: Epoch 2215 +2024-11-21 23:02:47.683637: Current learning rate: 0.00747 +2024-11-21 23:03:07.300650: train_loss -0.7578 +2024-11-21 23:03:07.304779: val_loss -0.7531 +2024-11-21 23:03:07.304914: Pseudo dice [0.8569] +2024-11-21 23:03:07.305004: Epoch time: 19.62 s +2024-11-21 23:03:08.256486: +2024-11-21 23:03:08.256739: Epoch 2216 +2024-11-21 23:03:08.256893: Current learning rate: 0.00747 +2024-11-21 23:03:26.972661: train_loss -0.7578 +2024-11-21 23:03:26.974730: val_loss -0.7788 +2024-11-21 23:03:26.974833: Pseudo dice [0.8531] +2024-11-21 23:03:26.974929: Epoch time: 18.72 s +2024-11-21 23:03:27.784351: +2024-11-21 23:03:27.784562: Epoch 2217 +2024-11-21 23:03:27.784696: Current learning rate: 0.00747 +2024-11-21 23:03:46.331723: train_loss -0.774 +2024-11-21 23:03:46.338923: val_loss -0.7608 +2024-11-21 23:03:46.339085: Pseudo dice [0.8559] +2024-11-21 23:03:46.339185: Epoch time: 18.55 s +2024-11-21 23:03:47.292874: +2024-11-21 23:03:47.293076: Epoch 2218 +2024-11-21 23:03:47.293192: Current learning rate: 0.00747 +2024-11-21 23:04:06.412704: train_loss -0.7631 +2024-11-21 23:04:06.420401: val_loss -0.7791 +2024-11-21 23:04:06.420532: Pseudo dice [0.8471] +2024-11-21 23:04:06.420627: Epoch time: 19.12 s +2024-11-21 23:04:07.246818: +2024-11-21 23:04:07.247073: Epoch 2219 +2024-11-21 23:04:07.247197: Current learning rate: 0.00746 +2024-11-21 23:04:25.936244: train_loss -0.7672 +2024-11-21 23:04:25.941269: val_loss -0.7616 +2024-11-21 23:04:25.942831: Pseudo dice [0.8526] +2024-11-21 23:04:25.942976: Epoch time: 18.69 s +2024-11-21 23:04:27.239763: +2024-11-21 23:04:27.239982: Epoch 2220 +2024-11-21 23:04:27.240104: Current learning rate: 0.00746 +2024-11-21 23:04:47.178534: train_loss -0.7633 +2024-11-21 23:04:47.182408: val_loss -0.7592 +2024-11-21 23:04:47.182554: Pseudo dice [0.8418] +2024-11-21 23:04:47.182646: Epoch time: 19.94 s +2024-11-21 23:04:48.053948: +2024-11-21 23:04:48.054232: Epoch 2221 +2024-11-21 23:04:48.054354: Current learning rate: 0.00746 +2024-11-21 23:05:06.511682: train_loss -0.7564 +2024-11-21 23:05:06.517402: val_loss -0.7503 +2024-11-21 23:05:06.517548: Pseudo dice [0.8499] +2024-11-21 23:05:06.517657: Epoch time: 18.46 s +2024-11-21 23:05:07.338976: +2024-11-21 23:05:07.339237: Epoch 2222 +2024-11-21 23:05:07.339355: Current learning rate: 0.00746 +2024-11-21 23:05:27.342908: train_loss -0.7765 +2024-11-21 23:05:27.350758: val_loss -0.7722 +2024-11-21 23:05:27.350893: Pseudo dice [0.8578] +2024-11-21 23:05:27.350985: Epoch time: 20.0 s +2024-11-21 23:05:28.389868: +2024-11-21 23:05:28.390093: Epoch 2223 +2024-11-21 23:05:28.390235: Current learning rate: 0.00746 +2024-11-21 23:05:46.263042: train_loss -0.7651 +2024-11-21 23:05:46.265296: val_loss -0.7602 +2024-11-21 23:05:46.265392: Pseudo dice [0.8436] +2024-11-21 23:05:46.265482: Epoch time: 17.87 s +2024-11-21 23:05:47.081842: +2024-11-21 23:05:47.082065: Epoch 2224 +2024-11-21 23:05:47.082184: Current learning rate: 0.00746 +2024-11-21 23:06:06.150627: train_loss -0.7636 +2024-11-21 23:06:06.153957: val_loss -0.7812 +2024-11-21 23:06:06.154074: Pseudo dice [0.8548] +2024-11-21 23:06:06.154163: Epoch time: 19.07 s +2024-11-21 23:06:06.964751: +2024-11-21 23:06:06.964980: Epoch 2225 +2024-11-21 23:06:06.965108: Current learning rate: 0.00746 +2024-11-21 23:06:25.511625: train_loss -0.7668 +2024-11-21 23:06:25.514720: val_loss -0.743 +2024-11-21 23:06:25.514833: Pseudo dice [0.8423] +2024-11-21 23:06:25.514933: Epoch time: 18.55 s +2024-11-21 23:06:26.428014: +2024-11-21 23:06:26.428252: Epoch 2226 +2024-11-21 23:06:26.428385: Current learning rate: 0.00746 +2024-11-21 23:06:45.340168: train_loss -0.7775 +2024-11-21 23:06:45.343617: val_loss -0.7747 +2024-11-21 23:06:45.343716: Pseudo dice [0.8486] +2024-11-21 23:06:45.343812: Epoch time: 18.91 s +2024-11-21 23:06:46.155792: +2024-11-21 23:06:46.156007: Epoch 2227 +2024-11-21 23:06:46.156141: Current learning rate: 0.00746 +2024-11-21 23:07:05.720569: train_loss -0.7778 +2024-11-21 23:07:05.730989: val_loss -0.7603 +2024-11-21 23:07:05.731162: Pseudo dice [0.8521] +2024-11-21 23:07:05.731321: Epoch time: 19.57 s +2024-11-21 23:07:06.651361: +2024-11-21 23:07:06.651584: Epoch 2228 +2024-11-21 23:07:06.651707: Current learning rate: 0.00745 +2024-11-21 23:07:26.242211: train_loss -0.7759 +2024-11-21 23:07:26.244874: val_loss -0.7483 +2024-11-21 23:07:26.245018: Pseudo dice [0.8505] +2024-11-21 23:07:26.245135: Epoch time: 19.59 s +2024-11-21 23:07:27.048452: +2024-11-21 23:07:27.048667: Epoch 2229 +2024-11-21 23:07:27.048792: Current learning rate: 0.00745 +2024-11-21 23:07:45.080886: train_loss -0.7742 +2024-11-21 23:07:45.096205: val_loss -0.7708 +2024-11-21 23:07:45.096353: Pseudo dice [0.8528] +2024-11-21 23:07:45.096445: Epoch time: 18.03 s +2024-11-21 23:07:46.083236: +2024-11-21 23:07:46.083453: Epoch 2230 +2024-11-21 23:07:46.083569: Current learning rate: 0.00745 +2024-11-21 23:08:04.805614: train_loss -0.7716 +2024-11-21 23:08:04.808121: val_loss -0.7675 +2024-11-21 23:08:04.808273: Pseudo dice [0.8502] +2024-11-21 23:08:04.808377: Epoch time: 18.72 s +2024-11-21 23:08:05.621822: +2024-11-21 23:08:05.622023: Epoch 2231 +2024-11-21 23:08:05.622142: Current learning rate: 0.00745 +2024-11-21 23:08:23.889896: train_loss -0.7732 +2024-11-21 23:08:23.900577: val_loss -0.7435 +2024-11-21 23:08:23.900735: Pseudo dice [0.8468] +2024-11-21 23:08:23.900850: Epoch time: 18.27 s +2024-11-21 23:08:25.125310: +2024-11-21 23:08:25.125525: Epoch 2232 +2024-11-21 23:08:25.125651: Current learning rate: 0.00745 +2024-11-21 23:08:44.011599: train_loss -0.7686 +2024-11-21 23:08:44.023906: val_loss -0.762 +2024-11-21 23:08:44.024047: Pseudo dice [0.8309] +2024-11-21 23:08:44.024153: Epoch time: 18.89 s +2024-11-21 23:08:45.000211: +2024-11-21 23:08:45.000427: Epoch 2233 +2024-11-21 23:08:45.000549: Current learning rate: 0.00745 +2024-11-21 23:09:03.787174: train_loss -0.7687 +2024-11-21 23:09:03.789157: val_loss -0.7807 +2024-11-21 23:09:03.789286: Pseudo dice [0.8507] +2024-11-21 23:09:03.789387: Epoch time: 18.79 s +2024-11-21 23:09:04.679972: +2024-11-21 23:09:04.680196: Epoch 2234 +2024-11-21 23:09:04.680325: Current learning rate: 0.00745 +2024-11-21 23:09:23.773661: train_loss -0.7614 +2024-11-21 23:09:23.801510: val_loss -0.7647 +2024-11-21 23:09:23.801662: Pseudo dice [0.8444] +2024-11-21 23:09:23.801772: Epoch time: 19.09 s +2024-11-21 23:09:24.614509: +2024-11-21 23:09:24.614738: Epoch 2235 +2024-11-21 23:09:24.614854: Current learning rate: 0.00745 +2024-11-21 23:09:44.379550: train_loss -0.7629 +2024-11-21 23:09:44.390949: val_loss -0.7486 +2024-11-21 23:09:44.391090: Pseudo dice [0.8549] +2024-11-21 23:09:44.391186: Epoch time: 19.77 s +2024-11-21 23:09:45.339222: +2024-11-21 23:09:45.339440: Epoch 2236 +2024-11-21 23:09:45.339562: Current learning rate: 0.00745 +2024-11-21 23:10:04.872198: train_loss -0.7613 +2024-11-21 23:10:04.874609: val_loss -0.7447 +2024-11-21 23:10:04.874728: Pseudo dice [0.8371] +2024-11-21 23:10:04.874832: Epoch time: 19.53 s +2024-11-21 23:10:05.681864: +2024-11-21 23:10:05.682068: Epoch 2237 +2024-11-21 23:10:05.682194: Current learning rate: 0.00744 +2024-11-21 23:10:25.152809: train_loss -0.7626 +2024-11-21 23:10:25.160015: val_loss -0.7597 +2024-11-21 23:10:25.160174: Pseudo dice [0.8376] +2024-11-21 23:10:25.160260: Epoch time: 19.47 s +2024-11-21 23:10:25.998409: +2024-11-21 23:10:25.998608: Epoch 2238 +2024-11-21 23:10:25.998734: Current learning rate: 0.00744 +2024-11-21 23:10:44.504969: train_loss -0.7655 +2024-11-21 23:10:44.511276: val_loss -0.7344 +2024-11-21 23:10:44.511409: Pseudo dice [0.8339] +2024-11-21 23:10:44.511512: Epoch time: 18.51 s +2024-11-21 23:10:45.533558: +2024-11-21 23:10:45.533765: Epoch 2239 +2024-11-21 23:10:45.533885: Current learning rate: 0.00744 +2024-11-21 23:11:04.198135: train_loss -0.7523 +2024-11-21 23:11:04.202765: val_loss -0.7405 +2024-11-21 23:11:04.202910: Pseudo dice [0.8514] +2024-11-21 23:11:04.202999: Epoch time: 18.67 s +2024-11-21 23:11:05.013256: +2024-11-21 23:11:05.013472: Epoch 2240 +2024-11-21 23:11:05.013592: Current learning rate: 0.00744 +2024-11-21 23:11:24.107202: train_loss -0.7573 +2024-11-21 23:11:24.112448: val_loss -0.7256 +2024-11-21 23:11:24.112571: Pseudo dice [0.8184] +2024-11-21 23:11:24.112673: Epoch time: 19.09 s +2024-11-21 23:11:24.969794: +2024-11-21 23:11:24.970369: Epoch 2241 +2024-11-21 23:11:24.970500: Current learning rate: 0.00744 +2024-11-21 23:11:44.652369: train_loss -0.7587 +2024-11-21 23:11:44.657076: val_loss -0.773 +2024-11-21 23:11:44.657283: Pseudo dice [0.8509] +2024-11-21 23:11:44.657424: Epoch time: 19.68 s +2024-11-21 23:11:45.496439: +2024-11-21 23:11:45.496660: Epoch 2242 +2024-11-21 23:11:45.496778: Current learning rate: 0.00744 +2024-11-21 23:12:05.098199: train_loss -0.7567 +2024-11-21 23:12:05.099716: val_loss -0.7667 +2024-11-21 23:12:05.099825: Pseudo dice [0.8479] +2024-11-21 23:12:05.099908: Epoch time: 19.6 s +2024-11-21 23:12:05.908974: +2024-11-21 23:12:05.909199: Epoch 2243 +2024-11-21 23:12:05.909337: Current learning rate: 0.00744 +2024-11-21 23:12:24.380518: train_loss -0.76 +2024-11-21 23:12:24.386966: val_loss -0.782 +2024-11-21 23:12:24.387103: Pseudo dice [0.8476] +2024-11-21 23:12:24.387198: Epoch time: 18.47 s +2024-11-21 23:12:25.525855: +2024-11-21 23:12:25.526128: Epoch 2244 +2024-11-21 23:12:25.526251: Current learning rate: 0.00744 +2024-11-21 23:12:44.012320: train_loss -0.7581 +2024-11-21 23:12:44.016291: val_loss -0.7626 +2024-11-21 23:12:44.016435: Pseudo dice [0.8517] +2024-11-21 23:12:44.016540: Epoch time: 18.49 s +2024-11-21 23:12:45.046330: +2024-11-21 23:12:45.046806: Epoch 2245 +2024-11-21 23:12:45.046920: Current learning rate: 0.00743 +2024-11-21 23:13:03.865962: train_loss -0.7588 +2024-11-21 23:13:03.878939: val_loss -0.7684 +2024-11-21 23:13:03.879107: Pseudo dice [0.8392] +2024-11-21 23:13:03.879211: Epoch time: 18.82 s +2024-11-21 23:13:04.914112: +2024-11-21 23:13:04.914327: Epoch 2246 +2024-11-21 23:13:04.914454: Current learning rate: 0.00743 +2024-11-21 23:13:23.356920: train_loss -0.7518 +2024-11-21 23:13:23.362636: val_loss -0.7402 +2024-11-21 23:13:23.362783: Pseudo dice [0.8393] +2024-11-21 23:13:23.362886: Epoch time: 18.44 s +2024-11-21 23:13:24.350173: +2024-11-21 23:13:24.350391: Epoch 2247 +2024-11-21 23:13:24.350505: Current learning rate: 0.00743 +2024-11-21 23:13:43.248652: train_loss -0.762 +2024-11-21 23:13:43.254561: val_loss -0.7563 +2024-11-21 23:13:43.254685: Pseudo dice [0.8567] +2024-11-21 23:13:43.254790: Epoch time: 18.9 s +2024-11-21 23:13:44.165436: +2024-11-21 23:13:44.165704: Epoch 2248 +2024-11-21 23:13:44.165826: Current learning rate: 0.00743 +2024-11-21 23:14:03.253561: train_loss -0.7709 +2024-11-21 23:14:03.256304: val_loss -0.7663 +2024-11-21 23:14:03.256418: Pseudo dice [0.8548] +2024-11-21 23:14:03.256525: Epoch time: 19.09 s +2024-11-21 23:14:04.069551: +2024-11-21 23:14:04.069783: Epoch 2249 +2024-11-21 23:14:04.069922: Current learning rate: 0.00743 +2024-11-21 23:14:22.471570: train_loss -0.7722 +2024-11-21 23:14:22.477706: val_loss -0.759 +2024-11-21 23:14:22.477844: Pseudo dice [0.8487] +2024-11-21 23:14:22.477929: Epoch time: 18.4 s +2024-11-21 23:14:23.573715: +2024-11-21 23:14:23.573933: Epoch 2250 +2024-11-21 23:14:23.574074: Current learning rate: 0.00743 +2024-11-21 23:14:43.600388: train_loss -0.7734 +2024-11-21 23:14:43.607350: val_loss -0.7552 +2024-11-21 23:14:43.607507: Pseudo dice [0.8503] +2024-11-21 23:14:43.607613: Epoch time: 20.03 s +2024-11-21 23:14:44.418831: +2024-11-21 23:14:44.419050: Epoch 2251 +2024-11-21 23:14:44.419188: Current learning rate: 0.00743 +2024-11-21 23:15:03.618790: train_loss -0.7748 +2024-11-21 23:15:03.631551: val_loss -0.7435 +2024-11-21 23:15:03.631725: Pseudo dice [0.8532] +2024-11-21 23:15:03.631823: Epoch time: 19.2 s +2024-11-21 23:15:04.600438: +2024-11-21 23:15:04.600645: Epoch 2252 +2024-11-21 23:15:04.600766: Current learning rate: 0.00743 +2024-11-21 23:15:23.259958: train_loss -0.7559 +2024-11-21 23:15:23.266105: val_loss -0.7281 +2024-11-21 23:15:23.266247: Pseudo dice [0.8489] +2024-11-21 23:15:23.266363: Epoch time: 18.66 s +2024-11-21 23:15:24.083925: +2024-11-21 23:15:24.084148: Epoch 2253 +2024-11-21 23:15:24.084266: Current learning rate: 0.00743 +2024-11-21 23:15:43.442205: train_loss -0.7602 +2024-11-21 23:15:43.450029: val_loss -0.7629 +2024-11-21 23:15:43.450243: Pseudo dice [0.8366] +2024-11-21 23:15:43.450349: Epoch time: 19.36 s +2024-11-21 23:15:44.485755: +2024-11-21 23:15:44.485999: Epoch 2254 +2024-11-21 23:15:44.486125: Current learning rate: 0.00742 +2024-11-21 23:16:04.177774: train_loss -0.765 +2024-11-21 23:16:04.185747: val_loss -0.7545 +2024-11-21 23:16:04.185901: Pseudo dice [0.8509] +2024-11-21 23:16:04.185998: Epoch time: 19.69 s +2024-11-21 23:16:05.031934: +2024-11-21 23:16:05.032169: Epoch 2255 +2024-11-21 23:16:05.032295: Current learning rate: 0.00742 +2024-11-21 23:16:24.268822: train_loss -0.7706 +2024-11-21 23:16:24.274369: val_loss -0.7432 +2024-11-21 23:16:24.274523: Pseudo dice [0.8486] +2024-11-21 23:16:24.274684: Epoch time: 19.24 s +2024-11-21 23:16:25.457226: +2024-11-21 23:16:25.457431: Epoch 2256 +2024-11-21 23:16:25.457567: Current learning rate: 0.00742 +2024-11-21 23:16:45.060099: train_loss -0.769 +2024-11-21 23:16:45.064790: val_loss -0.7763 +2024-11-21 23:16:45.064930: Pseudo dice [0.8465] +2024-11-21 23:16:45.065016: Epoch time: 19.6 s +2024-11-21 23:16:46.014598: +2024-11-21 23:16:46.014833: Epoch 2257 +2024-11-21 23:16:46.014983: Current learning rate: 0.00742 +2024-11-21 23:17:05.531757: train_loss -0.7813 +2024-11-21 23:17:05.538236: val_loss -0.7786 +2024-11-21 23:17:05.538378: Pseudo dice [0.8651] +2024-11-21 23:17:05.538716: Epoch time: 19.52 s +2024-11-21 23:17:06.510084: +2024-11-21 23:17:06.510297: Epoch 2258 +2024-11-21 23:17:06.510411: Current learning rate: 0.00742 +2024-11-21 23:17:25.941271: train_loss -0.7557 +2024-11-21 23:17:25.950541: val_loss -0.7502 +2024-11-21 23:17:25.950706: Pseudo dice [0.8421] +2024-11-21 23:17:25.950816: Epoch time: 19.43 s +2024-11-21 23:17:26.843777: +2024-11-21 23:17:26.844044: Epoch 2259 +2024-11-21 23:17:26.844194: Current learning rate: 0.00742 +2024-11-21 23:17:46.119492: train_loss -0.7621 +2024-11-21 23:17:46.124946: val_loss -0.7495 +2024-11-21 23:17:46.125163: Pseudo dice [0.8391] +2024-11-21 23:17:46.125290: Epoch time: 19.28 s +2024-11-21 23:17:47.031804: +2024-11-21 23:17:47.032022: Epoch 2260 +2024-11-21 23:17:47.032203: Current learning rate: 0.00742 +2024-11-21 23:18:05.643826: train_loss -0.7727 +2024-11-21 23:18:05.645484: val_loss -0.7613 +2024-11-21 23:18:05.645588: Pseudo dice [0.844] +2024-11-21 23:18:05.645672: Epoch time: 18.61 s +2024-11-21 23:18:06.526174: +2024-11-21 23:18:06.526383: Epoch 2261 +2024-11-21 23:18:06.526511: Current learning rate: 0.00742 +2024-11-21 23:18:25.782166: train_loss -0.7665 +2024-11-21 23:18:25.789806: val_loss -0.7725 +2024-11-21 23:18:25.789961: Pseudo dice [0.8519] +2024-11-21 23:18:25.790070: Epoch time: 19.26 s +2024-11-21 23:18:26.709297: +2024-11-21 23:18:26.709505: Epoch 2262 +2024-11-21 23:18:26.709625: Current learning rate: 0.00741 +2024-11-21 23:18:46.779281: train_loss -0.7695 +2024-11-21 23:18:46.786925: val_loss -0.759 +2024-11-21 23:18:46.787068: Pseudo dice [0.8601] +2024-11-21 23:18:46.787165: Epoch time: 20.07 s +2024-11-21 23:18:47.757915: +2024-11-21 23:18:47.758128: Epoch 2263 +2024-11-21 23:18:47.758250: Current learning rate: 0.00741 +2024-11-21 23:19:06.028535: train_loss -0.7672 +2024-11-21 23:19:06.030313: val_loss -0.7516 +2024-11-21 23:19:06.030421: Pseudo dice [0.8304] +2024-11-21 23:19:06.030525: Epoch time: 18.27 s +2024-11-21 23:19:06.844257: +2024-11-21 23:19:06.844466: Epoch 2264 +2024-11-21 23:19:06.844586: Current learning rate: 0.00741 +2024-11-21 23:19:26.052277: train_loss -0.7522 +2024-11-21 23:19:26.057827: val_loss -0.7733 +2024-11-21 23:19:26.058045: Pseudo dice [0.8437] +2024-11-21 23:19:26.058194: Epoch time: 19.21 s +2024-11-21 23:19:26.915217: +2024-11-21 23:19:26.915420: Epoch 2265 +2024-11-21 23:19:26.915532: Current learning rate: 0.00741 +2024-11-21 23:19:45.169673: train_loss -0.7658 +2024-11-21 23:19:45.174922: val_loss -0.7628 +2024-11-21 23:19:45.175068: Pseudo dice [0.8484] +2024-11-21 23:19:45.175185: Epoch time: 18.26 s +2024-11-21 23:19:45.992397: +2024-11-21 23:19:45.992610: Epoch 2266 +2024-11-21 23:19:45.992727: Current learning rate: 0.00741 +2024-11-21 23:20:05.674236: train_loss -0.7683 +2024-11-21 23:20:05.676624: val_loss -0.7584 +2024-11-21 23:20:05.676759: Pseudo dice [0.8379] +2024-11-21 23:20:05.676857: Epoch time: 19.68 s +2024-11-21 23:20:06.491009: +2024-11-21 23:20:06.491235: Epoch 2267 +2024-11-21 23:20:06.491360: Current learning rate: 0.00741 +2024-11-21 23:20:24.356675: train_loss -0.7673 +2024-11-21 23:20:24.358633: val_loss -0.7415 +2024-11-21 23:20:24.358731: Pseudo dice [0.8544] +2024-11-21 23:20:24.358834: Epoch time: 17.87 s +2024-11-21 23:20:25.544688: +2024-11-21 23:20:25.544932: Epoch 2268 +2024-11-21 23:20:25.545050: Current learning rate: 0.00741 +2024-11-21 23:20:45.874212: train_loss -0.7668 +2024-11-21 23:20:45.877252: val_loss -0.7614 +2024-11-21 23:20:45.877378: Pseudo dice [0.8473] +2024-11-21 23:20:45.877577: Epoch time: 20.33 s +2024-11-21 23:20:46.693450: +2024-11-21 23:20:46.693674: Epoch 2269 +2024-11-21 23:20:46.693804: Current learning rate: 0.00741 +2024-11-21 23:21:05.424921: train_loss -0.7596 +2024-11-21 23:21:05.434236: val_loss -0.7589 +2024-11-21 23:21:05.434382: Pseudo dice [0.8539] +2024-11-21 23:21:05.434485: Epoch time: 18.73 s +2024-11-21 23:21:06.275375: +2024-11-21 23:21:06.275601: Epoch 2270 +2024-11-21 23:21:06.275724: Current learning rate: 0.00741 +2024-11-21 23:21:26.757522: train_loss -0.7767 +2024-11-21 23:21:26.773464: val_loss -0.7739 +2024-11-21 23:21:26.773627: Pseudo dice [0.8526] +2024-11-21 23:21:26.773725: Epoch time: 20.48 s +2024-11-21 23:21:27.722114: +2024-11-21 23:21:27.722346: Epoch 2271 +2024-11-21 23:21:27.722490: Current learning rate: 0.0074 +2024-11-21 23:21:46.907044: train_loss -0.7679 +2024-11-21 23:21:46.914774: val_loss -0.7735 +2024-11-21 23:21:46.914919: Pseudo dice [0.8487] +2024-11-21 23:21:46.915009: Epoch time: 19.19 s +2024-11-21 23:21:47.730287: +2024-11-21 23:21:47.730557: Epoch 2272 +2024-11-21 23:21:47.730684: Current learning rate: 0.0074 +2024-11-21 23:22:06.253984: train_loss -0.7715 +2024-11-21 23:22:06.260417: val_loss -0.754 +2024-11-21 23:22:06.260557: Pseudo dice [0.8445] +2024-11-21 23:22:06.260658: Epoch time: 18.52 s +2024-11-21 23:22:07.083264: +2024-11-21 23:22:07.083508: Epoch 2273 +2024-11-21 23:22:07.083647: Current learning rate: 0.0074 +2024-11-21 23:22:26.387795: train_loss -0.7702 +2024-11-21 23:22:26.389960: val_loss -0.768 +2024-11-21 23:22:26.390101: Pseudo dice [0.855] +2024-11-21 23:22:26.390208: Epoch time: 19.31 s +2024-11-21 23:22:27.197258: +2024-11-21 23:22:27.197463: Epoch 2274 +2024-11-21 23:22:27.197591: Current learning rate: 0.0074 +2024-11-21 23:22:46.429313: train_loss -0.7595 +2024-11-21 23:22:46.433958: val_loss -0.756 +2024-11-21 23:22:46.434105: Pseudo dice [0.8468] +2024-11-21 23:22:46.434204: Epoch time: 19.23 s +2024-11-21 23:22:47.321724: +2024-11-21 23:22:47.321916: Epoch 2275 +2024-11-21 23:22:47.322034: Current learning rate: 0.0074 +2024-11-21 23:23:06.377682: train_loss -0.7574 +2024-11-21 23:23:06.382729: val_loss -0.7706 +2024-11-21 23:23:06.382869: Pseudo dice [0.8421] +2024-11-21 23:23:06.382952: Epoch time: 19.06 s +2024-11-21 23:23:07.206462: +2024-11-21 23:23:07.206672: Epoch 2276 +2024-11-21 23:23:07.206804: Current learning rate: 0.0074 +2024-11-21 23:23:26.260963: train_loss -0.77 +2024-11-21 23:23:26.274368: val_loss -0.7727 +2024-11-21 23:23:26.274522: Pseudo dice [0.8562] +2024-11-21 23:23:26.274611: Epoch time: 19.06 s +2024-11-21 23:23:27.183585: +2024-11-21 23:23:27.183797: Epoch 2277 +2024-11-21 23:23:27.183911: Current learning rate: 0.0074 +2024-11-21 23:23:46.441624: train_loss -0.7664 +2024-11-21 23:23:46.443640: val_loss -0.7667 +2024-11-21 23:23:46.443756: Pseudo dice [0.8474] +2024-11-21 23:23:46.443857: Epoch time: 19.26 s +2024-11-21 23:23:47.418165: +2024-11-21 23:23:47.418400: Epoch 2278 +2024-11-21 23:23:47.418542: Current learning rate: 0.0074 +2024-11-21 23:24:06.792367: train_loss -0.7779 +2024-11-21 23:24:06.796657: val_loss -0.7558 +2024-11-21 23:24:06.796795: Pseudo dice [0.8436] +2024-11-21 23:24:06.796923: Epoch time: 19.38 s +2024-11-21 23:24:07.612860: +2024-11-21 23:24:07.613093: Epoch 2279 +2024-11-21 23:24:07.613208: Current learning rate: 0.0074 +2024-11-21 23:24:27.229799: train_loss -0.7719 +2024-11-21 23:24:27.232812: val_loss -0.7766 +2024-11-21 23:24:27.232934: Pseudo dice [0.844] +2024-11-21 23:24:27.233043: Epoch time: 19.62 s +2024-11-21 23:24:28.560278: +2024-11-21 23:24:28.560500: Epoch 2280 +2024-11-21 23:24:28.560631: Current learning rate: 0.00739 +2024-11-21 23:24:47.707324: train_loss -0.776 +2024-11-21 23:24:47.713629: val_loss -0.7879 +2024-11-21 23:24:47.713769: Pseudo dice [0.8658] +2024-11-21 23:24:47.713884: Epoch time: 19.15 s +2024-11-21 23:24:48.564645: +2024-11-21 23:24:48.564865: Epoch 2281 +2024-11-21 23:24:48.564989: Current learning rate: 0.00739 +2024-11-21 23:25:08.426193: train_loss -0.7641 +2024-11-21 23:25:08.441932: val_loss -0.7499 +2024-11-21 23:25:08.442101: Pseudo dice [0.8464] +2024-11-21 23:25:08.442194: Epoch time: 19.86 s +2024-11-21 23:25:09.277984: +2024-11-21 23:25:09.278232: Epoch 2282 +2024-11-21 23:25:09.278366: Current learning rate: 0.00739 +2024-11-21 23:25:27.252783: train_loss -0.7691 +2024-11-21 23:25:27.255070: val_loss -0.7516 +2024-11-21 23:25:27.255179: Pseudo dice [0.8259] +2024-11-21 23:25:27.255282: Epoch time: 17.98 s +2024-11-21 23:25:28.068531: +2024-11-21 23:25:28.068737: Epoch 2283 +2024-11-21 23:25:28.069520: Current learning rate: 0.00739 +2024-11-21 23:25:46.264879: train_loss -0.7706 +2024-11-21 23:25:46.274839: val_loss -0.7808 +2024-11-21 23:25:46.274993: Pseudo dice [0.8573] +2024-11-21 23:25:46.275096: Epoch time: 18.2 s +2024-11-21 23:25:47.384620: +2024-11-21 23:25:47.384849: Epoch 2284 +2024-11-21 23:25:47.384976: Current learning rate: 0.00739 +2024-11-21 23:26:07.207978: train_loss -0.7817 +2024-11-21 23:26:07.216925: val_loss -0.7677 +2024-11-21 23:26:07.217048: Pseudo dice [0.8522] +2024-11-21 23:26:07.217165: Epoch time: 19.82 s +2024-11-21 23:26:08.244376: +2024-11-21 23:26:08.244608: Epoch 2285 +2024-11-21 23:26:08.244736: Current learning rate: 0.00739 +2024-11-21 23:26:27.732464: train_loss -0.7806 +2024-11-21 23:26:27.736911: val_loss -0.7748 +2024-11-21 23:26:27.737149: Pseudo dice [0.8474] +2024-11-21 23:26:27.737256: Epoch time: 19.49 s +2024-11-21 23:26:28.562102: +2024-11-21 23:26:28.562339: Epoch 2286 +2024-11-21 23:26:28.562479: Current learning rate: 0.00739 +2024-11-21 23:26:47.029175: train_loss -0.7746 +2024-11-21 23:26:47.037072: val_loss -0.7813 +2024-11-21 23:26:47.037233: Pseudo dice [0.8442] +2024-11-21 23:26:47.037347: Epoch time: 18.47 s +2024-11-21 23:26:47.928689: +2024-11-21 23:26:47.930485: Epoch 2287 +2024-11-21 23:26:47.930617: Current learning rate: 0.00739 +2024-11-21 23:27:06.389626: train_loss -0.7715 +2024-11-21 23:27:06.396603: val_loss -0.7565 +2024-11-21 23:27:06.396800: Pseudo dice [0.8364] +2024-11-21 23:27:06.396896: Epoch time: 18.46 s +2024-11-21 23:27:07.357887: +2024-11-21 23:27:07.358125: Epoch 2288 +2024-11-21 23:27:07.358245: Current learning rate: 0.00738 +2024-11-21 23:27:27.222548: train_loss -0.764 +2024-11-21 23:27:27.228725: val_loss -0.753 +2024-11-21 23:27:27.228833: Pseudo dice [0.8341] +2024-11-21 23:27:27.228921: Epoch time: 19.87 s +2024-11-21 23:27:28.038036: +2024-11-21 23:27:28.038257: Epoch 2289 +2024-11-21 23:27:28.038607: Current learning rate: 0.00738 +2024-11-21 23:27:47.080241: train_loss -0.7745 +2024-11-21 23:27:47.086394: val_loss -0.7688 +2024-11-21 23:27:47.086526: Pseudo dice [0.8511] +2024-11-21 23:27:47.086605: Epoch time: 19.04 s +2024-11-21 23:27:48.071508: +2024-11-21 23:27:48.071721: Epoch 2290 +2024-11-21 23:27:48.071838: Current learning rate: 0.00738 +2024-11-21 23:28:06.596295: train_loss -0.7724 +2024-11-21 23:28:06.602509: val_loss -0.7577 +2024-11-21 23:28:06.602663: Pseudo dice [0.8514] +2024-11-21 23:28:06.602763: Epoch time: 18.53 s +2024-11-21 23:28:07.422165: +2024-11-21 23:28:07.422374: Epoch 2291 +2024-11-21 23:28:07.422495: Current learning rate: 0.00738 +2024-11-21 23:28:27.323607: train_loss -0.7758 +2024-11-21 23:28:27.329608: val_loss -0.7729 +2024-11-21 23:28:27.329750: Pseudo dice [0.861] +2024-11-21 23:28:27.329859: Epoch time: 19.9 s +2024-11-21 23:28:28.566609: +2024-11-21 23:28:28.566848: Epoch 2292 +2024-11-21 23:28:28.566975: Current learning rate: 0.00738 +2024-11-21 23:28:47.417828: train_loss -0.7944 +2024-11-21 23:28:47.419612: val_loss -0.7714 +2024-11-21 23:28:47.419856: Pseudo dice [0.8396] +2024-11-21 23:28:47.419957: Epoch time: 18.85 s +2024-11-21 23:28:48.325308: +2024-11-21 23:28:48.325544: Epoch 2293 +2024-11-21 23:28:48.325684: Current learning rate: 0.00738 +2024-11-21 23:29:07.608175: train_loss -0.7782 +2024-11-21 23:29:07.622383: val_loss -0.77 +2024-11-21 23:29:07.622508: Pseudo dice [0.8493] +2024-11-21 23:29:07.622605: Epoch time: 19.28 s +2024-11-21 23:29:08.726649: +2024-11-21 23:29:08.726873: Epoch 2294 +2024-11-21 23:29:08.726995: Current learning rate: 0.00738 +2024-11-21 23:29:27.867716: train_loss -0.7854 +2024-11-21 23:29:27.869369: val_loss -0.7706 +2024-11-21 23:29:27.869470: Pseudo dice [0.855] +2024-11-21 23:29:27.869561: Epoch time: 19.14 s +2024-11-21 23:29:28.680489: +2024-11-21 23:29:28.680700: Epoch 2295 +2024-11-21 23:29:28.680827: Current learning rate: 0.00738 +2024-11-21 23:29:48.391570: train_loss -0.7811 +2024-11-21 23:29:48.398960: val_loss -0.7739 +2024-11-21 23:29:48.399084: Pseudo dice [0.8624] +2024-11-21 23:29:48.399200: Epoch time: 19.71 s +2024-11-21 23:29:49.280024: +2024-11-21 23:29:49.280337: Epoch 2296 +2024-11-21 23:29:49.280466: Current learning rate: 0.00738 +2024-11-21 23:30:08.193188: train_loss -0.7754 +2024-11-21 23:30:08.199332: val_loss -0.7795 +2024-11-21 23:30:08.199471: Pseudo dice [0.8624] +2024-11-21 23:30:08.199558: Epoch time: 18.91 s +2024-11-21 23:30:09.013644: +2024-11-21 23:30:09.013860: Epoch 2297 +2024-11-21 23:30:09.014000: Current learning rate: 0.00737 +2024-11-21 23:30:27.949965: train_loss -0.7752 +2024-11-21 23:30:27.953624: val_loss -0.7576 +2024-11-21 23:30:27.953793: Pseudo dice [0.8439] +2024-11-21 23:30:27.953886: Epoch time: 18.94 s +2024-11-21 23:30:28.781634: +2024-11-21 23:30:28.781868: Epoch 2298 +2024-11-21 23:30:28.781990: Current learning rate: 0.00737 +2024-11-21 23:30:46.916476: train_loss -0.7761 +2024-11-21 23:30:46.918474: val_loss -0.7658 +2024-11-21 23:30:46.918605: Pseudo dice [0.8563] +2024-11-21 23:30:46.918717: Epoch time: 18.14 s +2024-11-21 23:30:47.733980: +2024-11-21 23:30:47.734190: Epoch 2299 +2024-11-21 23:30:47.734328: Current learning rate: 0.00737 +2024-11-21 23:31:07.333284: train_loss -0.7657 +2024-11-21 23:31:07.336773: val_loss -0.7537 +2024-11-21 23:31:07.336909: Pseudo dice [0.8362] +2024-11-21 23:31:07.337006: Epoch time: 19.6 s +2024-11-21 23:31:08.458206: +2024-11-21 23:31:08.458439: Epoch 2300 +2024-11-21 23:31:08.458574: Current learning rate: 0.00737 +2024-11-21 23:31:27.936426: train_loss -0.7615 +2024-11-21 23:31:27.942382: val_loss -0.7333 +2024-11-21 23:31:27.942507: Pseudo dice [0.797] +2024-11-21 23:31:27.942594: Epoch time: 19.48 s +2024-11-21 23:31:28.760338: +2024-11-21 23:31:28.760559: Epoch 2301 +2024-11-21 23:31:28.760678: Current learning rate: 0.00737 +2024-11-21 23:31:48.089389: train_loss -0.7542 +2024-11-21 23:31:48.093357: val_loss -0.7389 +2024-11-21 23:31:48.093483: Pseudo dice [0.8405] +2024-11-21 23:31:48.093581: Epoch time: 19.33 s +2024-11-21 23:31:48.905444: +2024-11-21 23:31:48.905658: Epoch 2302 +2024-11-21 23:31:48.905787: Current learning rate: 0.00737 +2024-11-21 23:32:07.513247: train_loss -0.7621 +2024-11-21 23:32:07.522923: val_loss -0.7489 +2024-11-21 23:32:07.523084: Pseudo dice [0.8283] +2024-11-21 23:32:07.523182: Epoch time: 18.61 s +2024-11-21 23:32:08.407261: +2024-11-21 23:32:08.407478: Epoch 2303 +2024-11-21 23:32:08.407606: Current learning rate: 0.00737 +2024-11-21 23:32:27.461095: train_loss -0.771 +2024-11-21 23:32:27.462863: val_loss -0.7807 +2024-11-21 23:32:27.462970: Pseudo dice [0.8524] +2024-11-21 23:32:27.463073: Epoch time: 19.05 s +2024-11-21 23:32:28.644003: +2024-11-21 23:32:28.644276: Epoch 2304 +2024-11-21 23:32:28.644406: Current learning rate: 0.00737 +2024-11-21 23:32:47.471020: train_loss -0.7701 +2024-11-21 23:32:47.478955: val_loss -0.7712 +2024-11-21 23:32:47.479096: Pseudo dice [0.8484] +2024-11-21 23:32:47.479306: Epoch time: 18.83 s +2024-11-21 23:32:48.378951: +2024-11-21 23:32:48.379376: Epoch 2305 +2024-11-21 23:32:48.379512: Current learning rate: 0.00736 +2024-11-21 23:33:06.633330: train_loss -0.7724 +2024-11-21 23:33:06.639472: val_loss -0.7822 +2024-11-21 23:33:06.639697: Pseudo dice [0.8545] +2024-11-21 23:33:06.639845: Epoch time: 18.26 s +2024-11-21 23:33:07.440211: +2024-11-21 23:33:07.440692: Epoch 2306 +2024-11-21 23:33:07.440907: Current learning rate: 0.00736 +2024-11-21 23:33:25.755133: train_loss -0.7598 +2024-11-21 23:33:25.764384: val_loss -0.7697 +2024-11-21 23:33:25.764520: Pseudo dice [0.8493] +2024-11-21 23:33:25.764620: Epoch time: 18.32 s +2024-11-21 23:33:26.664961: +2024-11-21 23:33:26.665396: Epoch 2307 +2024-11-21 23:33:26.665547: Current learning rate: 0.00736 +2024-11-21 23:33:44.988606: train_loss -0.7688 +2024-11-21 23:33:44.994041: val_loss -0.7483 +2024-11-21 23:33:44.994209: Pseudo dice [0.8472] +2024-11-21 23:33:44.994311: Epoch time: 18.32 s +2024-11-21 23:33:45.849323: +2024-11-21 23:33:45.849777: Epoch 2308 +2024-11-21 23:33:45.849920: Current learning rate: 0.00736 +2024-11-21 23:34:05.270663: train_loss -0.7607 +2024-11-21 23:34:05.277901: val_loss -0.7519 +2024-11-21 23:34:05.304465: Pseudo dice [0.8502] +2024-11-21 23:34:05.304663: Epoch time: 19.42 s +2024-11-21 23:34:06.304927: +2024-11-21 23:34:06.305377: Epoch 2309 +2024-11-21 23:34:06.305521: Current learning rate: 0.00736 +2024-11-21 23:34:25.368694: train_loss -0.7596 +2024-11-21 23:34:25.390333: val_loss -0.7649 +2024-11-21 23:34:25.390486: Pseudo dice [0.8418] +2024-11-21 23:34:25.390593: Epoch time: 19.06 s +2024-11-21 23:34:26.296317: +2024-11-21 23:34:26.296812: Epoch 2310 +2024-11-21 23:34:26.296973: Current learning rate: 0.00736 +2024-11-21 23:34:46.067568: train_loss -0.7462 +2024-11-21 23:34:46.075811: val_loss -0.7475 +2024-11-21 23:34:46.075943: Pseudo dice [0.8369] +2024-11-21 23:34:46.076039: Epoch time: 19.77 s +2024-11-21 23:34:46.953247: +2024-11-21 23:34:46.953669: Epoch 2311 +2024-11-21 23:34:46.953822: Current learning rate: 0.00736 +2024-11-21 23:35:05.794510: train_loss -0.7572 +2024-11-21 23:35:05.800473: val_loss -0.7652 +2024-11-21 23:35:05.800613: Pseudo dice [0.8528] +2024-11-21 23:35:05.800699: Epoch time: 18.84 s +2024-11-21 23:35:06.725836: +2024-11-21 23:35:06.726299: Epoch 2312 +2024-11-21 23:35:06.726436: Current learning rate: 0.00736 +2024-11-21 23:35:25.950869: train_loss -0.7685 +2024-11-21 23:35:25.958412: val_loss -0.7723 +2024-11-21 23:35:25.958559: Pseudo dice [0.8376] +2024-11-21 23:35:25.958656: Epoch time: 19.23 s +2024-11-21 23:35:26.875933: +2024-11-21 23:35:26.876149: Epoch 2313 +2024-11-21 23:35:26.876271: Current learning rate: 0.00736 +2024-11-21 23:35:45.723201: train_loss -0.7537 +2024-11-21 23:35:45.726641: val_loss -0.7592 +2024-11-21 23:35:45.726790: Pseudo dice [0.8527] +2024-11-21 23:35:45.726886: Epoch time: 18.85 s +2024-11-21 23:35:46.539331: +2024-11-21 23:35:46.539530: Epoch 2314 +2024-11-21 23:35:46.539648: Current learning rate: 0.00735 +2024-11-21 23:36:05.127435: train_loss -0.7619 +2024-11-21 23:36:05.134394: val_loss -0.7805 +2024-11-21 23:36:05.134589: Pseudo dice [0.8569] +2024-11-21 23:36:05.134691: Epoch time: 18.59 s +2024-11-21 23:36:06.140357: +2024-11-21 23:36:06.140567: Epoch 2315 +2024-11-21 23:36:06.140898: Current learning rate: 0.00735 +2024-11-21 23:36:24.178013: train_loss -0.766 +2024-11-21 23:36:24.180556: val_loss -0.7657 +2024-11-21 23:36:24.180680: Pseudo dice [0.8381] +2024-11-21 23:36:24.180783: Epoch time: 18.04 s +2024-11-21 23:36:25.386081: +2024-11-21 23:36:25.386320: Epoch 2316 +2024-11-21 23:36:25.386445: Current learning rate: 0.00735 +2024-11-21 23:36:43.862874: train_loss -0.7655 +2024-11-21 23:36:43.868412: val_loss -0.7556 +2024-11-21 23:36:43.868582: Pseudo dice [0.858] +2024-11-21 23:36:43.868695: Epoch time: 18.48 s +2024-11-21 23:36:44.690054: +2024-11-21 23:36:44.690319: Epoch 2317 +2024-11-21 23:36:44.690440: Current learning rate: 0.00735 +2024-11-21 23:37:05.055522: train_loss -0.7601 +2024-11-21 23:37:05.066173: val_loss -0.7631 +2024-11-21 23:37:05.066315: Pseudo dice [0.8507] +2024-11-21 23:37:05.066406: Epoch time: 20.37 s +2024-11-21 23:37:05.962664: +2024-11-21 23:37:05.962898: Epoch 2318 +2024-11-21 23:37:05.963026: Current learning rate: 0.00735 +2024-11-21 23:37:24.987880: train_loss -0.7586 +2024-11-21 23:37:25.003397: val_loss -0.7591 +2024-11-21 23:37:25.003571: Pseudo dice [0.8486] +2024-11-21 23:37:25.003715: Epoch time: 19.03 s +2024-11-21 23:37:25.974474: +2024-11-21 23:37:25.974705: Epoch 2319 +2024-11-21 23:37:25.974831: Current learning rate: 0.00735 +2024-11-21 23:37:44.655028: train_loss -0.7647 +2024-11-21 23:37:44.658572: val_loss -0.75 +2024-11-21 23:37:44.658713: Pseudo dice [0.8374] +2024-11-21 23:37:44.658814: Epoch time: 18.68 s +2024-11-21 23:37:45.476114: +2024-11-21 23:37:45.476318: Epoch 2320 +2024-11-21 23:37:45.476433: Current learning rate: 0.00735 +2024-11-21 23:38:04.065165: train_loss -0.7471 +2024-11-21 23:38:04.068377: val_loss -0.7583 +2024-11-21 23:38:04.068531: Pseudo dice [0.8334] +2024-11-21 23:38:04.068629: Epoch time: 18.58 s +2024-11-21 23:38:04.923929: +2024-11-21 23:38:04.924152: Epoch 2321 +2024-11-21 23:38:04.924278: Current learning rate: 0.00735 +2024-11-21 23:38:24.799912: train_loss -0.7479 +2024-11-21 23:38:24.807210: val_loss -0.7644 +2024-11-21 23:38:24.807357: Pseudo dice [0.8412] +2024-11-21 23:38:24.807442: Epoch time: 19.88 s +2024-11-21 23:38:25.623485: +2024-11-21 23:38:25.623682: Epoch 2322 +2024-11-21 23:38:25.623824: Current learning rate: 0.00735 +2024-11-21 23:38:44.848551: train_loss -0.7611 +2024-11-21 23:38:44.854311: val_loss -0.7589 +2024-11-21 23:38:44.854454: Pseudo dice [0.8493] +2024-11-21 23:38:44.854543: Epoch time: 19.23 s +2024-11-21 23:38:45.665744: +2024-11-21 23:38:45.665958: Epoch 2323 +2024-11-21 23:38:45.666098: Current learning rate: 0.00734 +2024-11-21 23:39:04.451933: train_loss -0.7515 +2024-11-21 23:39:04.458735: val_loss -0.765 +2024-11-21 23:39:04.458882: Pseudo dice [0.8431] +2024-11-21 23:39:04.458981: Epoch time: 18.79 s +2024-11-21 23:39:05.322103: +2024-11-21 23:39:05.322319: Epoch 2324 +2024-11-21 23:39:05.322471: Current learning rate: 0.00734 +2024-11-21 23:39:24.747535: train_loss -0.762 +2024-11-21 23:39:24.756793: val_loss -0.7654 +2024-11-21 23:39:24.756945: Pseudo dice [0.859] +2024-11-21 23:39:24.757035: Epoch time: 19.43 s +2024-11-21 23:39:25.609981: +2024-11-21 23:39:25.610194: Epoch 2325 +2024-11-21 23:39:25.610332: Current learning rate: 0.00734 +2024-11-21 23:39:45.240503: train_loss -0.7641 +2024-11-21 23:39:45.267117: val_loss -0.7707 +2024-11-21 23:39:45.267290: Pseudo dice [0.8645] +2024-11-21 23:39:45.267387: Epoch time: 19.63 s +2024-11-21 23:39:46.171873: +2024-11-21 23:39:46.172123: Epoch 2326 +2024-11-21 23:39:46.172239: Current learning rate: 0.00734 +2024-11-21 23:40:05.356185: train_loss -0.7688 +2024-11-21 23:40:05.361189: val_loss -0.7593 +2024-11-21 23:40:05.361327: Pseudo dice [0.8532] +2024-11-21 23:40:05.361421: Epoch time: 19.19 s +2024-11-21 23:40:06.310014: +2024-11-21 23:40:06.310235: Epoch 2327 +2024-11-21 23:40:06.310358: Current learning rate: 0.00734 +2024-11-21 23:40:25.589367: train_loss -0.7763 +2024-11-21 23:40:25.594164: val_loss -0.7515 +2024-11-21 23:40:25.594315: Pseudo dice [0.8353] +2024-11-21 23:40:25.594416: Epoch time: 19.28 s +2024-11-21 23:40:26.877223: +2024-11-21 23:40:26.877652: Epoch 2328 +2024-11-21 23:40:26.877797: Current learning rate: 0.00734 +2024-11-21 23:40:46.516665: train_loss -0.7638 +2024-11-21 23:40:46.525587: val_loss -0.7739 +2024-11-21 23:40:46.525728: Pseudo dice [0.8282] +2024-11-21 23:40:46.525827: Epoch time: 19.64 s +2024-11-21 23:40:47.420902: +2024-11-21 23:40:47.421372: Epoch 2329 +2024-11-21 23:40:47.421524: Current learning rate: 0.00734 +2024-11-21 23:41:06.523738: train_loss -0.7644 +2024-11-21 23:41:06.526145: val_loss -0.7871 +2024-11-21 23:41:06.526255: Pseudo dice [0.8444] +2024-11-21 23:41:06.526344: Epoch time: 19.1 s +2024-11-21 23:41:07.333985: +2024-11-21 23:41:07.334404: Epoch 2330 +2024-11-21 23:41:07.334548: Current learning rate: 0.00734 +2024-11-21 23:41:27.374261: train_loss -0.771 +2024-11-21 23:41:27.376603: val_loss -0.7735 +2024-11-21 23:41:27.376753: Pseudo dice [0.8618] +2024-11-21 23:41:27.376857: Epoch time: 20.04 s +2024-11-21 23:41:28.194963: +2024-11-21 23:41:28.195453: Epoch 2331 +2024-11-21 23:41:28.195654: Current learning rate: 0.00733 +2024-11-21 23:41:47.957503: train_loss -0.765 +2024-11-21 23:41:47.962809: val_loss -0.7542 +2024-11-21 23:41:47.962942: Pseudo dice [0.8386] +2024-11-21 23:41:47.963124: Epoch time: 19.76 s +2024-11-21 23:41:48.803472: +2024-11-21 23:41:48.803886: Epoch 2332 +2024-11-21 23:41:48.804031: Current learning rate: 0.00733 +2024-11-21 23:42:07.933682: train_loss -0.764 +2024-11-21 23:42:07.936851: val_loss -0.7541 +2024-11-21 23:42:07.937054: Pseudo dice [0.8258] +2024-11-21 23:42:07.937155: Epoch time: 19.13 s +2024-11-21 23:42:09.042845: +2024-11-21 23:42:09.043314: Epoch 2333 +2024-11-21 23:42:09.043460: Current learning rate: 0.00733 +2024-11-21 23:42:28.238171: train_loss -0.7708 +2024-11-21 23:42:28.260661: val_loss -0.7438 +2024-11-21 23:42:28.260828: Pseudo dice [0.8418] +2024-11-21 23:42:28.260919: Epoch time: 19.2 s +2024-11-21 23:42:29.075851: +2024-11-21 23:42:29.076290: Epoch 2334 +2024-11-21 23:42:29.076432: Current learning rate: 0.00733 +2024-11-21 23:42:47.944535: train_loss -0.7667 +2024-11-21 23:42:47.957766: val_loss -0.7623 +2024-11-21 23:42:47.957931: Pseudo dice [0.8448] +2024-11-21 23:42:47.958045: Epoch time: 18.87 s +2024-11-21 23:42:48.787982: +2024-11-21 23:42:48.788413: Epoch 2335 +2024-11-21 23:42:48.788572: Current learning rate: 0.00733 +2024-11-21 23:43:08.125742: train_loss -0.7618 +2024-11-21 23:43:08.128476: val_loss -0.7688 +2024-11-21 23:43:08.128609: Pseudo dice [0.8401] +2024-11-21 23:43:08.128710: Epoch time: 19.34 s +2024-11-21 23:43:09.121235: +2024-11-21 23:43:09.121638: Epoch 2336 +2024-11-21 23:43:09.121806: Current learning rate: 0.00733 +2024-11-21 23:43:27.790717: train_loss -0.7666 +2024-11-21 23:43:27.798746: val_loss -0.775 +2024-11-21 23:43:27.798864: Pseudo dice [0.8595] +2024-11-21 23:43:27.798952: Epoch time: 18.67 s +2024-11-21 23:43:28.696454: +2024-11-21 23:43:28.696697: Epoch 2337 +2024-11-21 23:43:28.696828: Current learning rate: 0.00733 +2024-11-21 23:43:47.227831: train_loss -0.7813 +2024-11-21 23:43:47.251655: val_loss -0.7552 +2024-11-21 23:43:47.251826: Pseudo dice [0.8498] +2024-11-21 23:43:47.251949: Epoch time: 18.53 s +2024-11-21 23:43:48.175202: +2024-11-21 23:43:48.175403: Epoch 2338 +2024-11-21 23:43:48.175526: Current learning rate: 0.00733 +2024-11-21 23:44:08.000642: train_loss -0.7733 +2024-11-21 23:44:08.006624: val_loss -0.76 +2024-11-21 23:44:08.006755: Pseudo dice [0.8429] +2024-11-21 23:44:08.006845: Epoch time: 19.83 s +2024-11-21 23:44:08.836035: +2024-11-21 23:44:08.836247: Epoch 2339 +2024-11-21 23:44:08.836364: Current learning rate: 0.00733 +2024-11-21 23:44:27.931826: train_loss -0.7697 +2024-11-21 23:44:27.936952: val_loss -0.7671 +2024-11-21 23:44:27.937126: Pseudo dice [0.8436] +2024-11-21 23:44:27.937218: Epoch time: 19.1 s +2024-11-21 23:44:29.170408: +2024-11-21 23:44:29.170643: Epoch 2340 +2024-11-21 23:44:29.170780: Current learning rate: 0.00732 +2024-11-21 23:44:48.687166: train_loss -0.7746 +2024-11-21 23:44:48.695944: val_loss -0.756 +2024-11-21 23:44:48.696082: Pseudo dice [0.8473] +2024-11-21 23:44:48.696189: Epoch time: 19.52 s +2024-11-21 23:44:49.747470: +2024-11-21 23:44:49.747938: Epoch 2341 +2024-11-21 23:44:49.748081: Current learning rate: 0.00732 +2024-11-21 23:45:08.589006: train_loss -0.7699 +2024-11-21 23:45:08.597547: val_loss -0.7697 +2024-11-21 23:45:08.597694: Pseudo dice [0.853] +2024-11-21 23:45:08.597781: Epoch time: 18.84 s +2024-11-21 23:45:09.443035: +2024-11-21 23:45:09.443271: Epoch 2342 +2024-11-21 23:45:09.443394: Current learning rate: 0.00732 +2024-11-21 23:45:28.619073: train_loss -0.7741 +2024-11-21 23:45:28.640840: val_loss -0.7417 +2024-11-21 23:45:28.641001: Pseudo dice [0.8415] +2024-11-21 23:45:28.641100: Epoch time: 19.18 s +2024-11-21 23:45:29.764012: +2024-11-21 23:45:29.764236: Epoch 2343 +2024-11-21 23:45:29.764354: Current learning rate: 0.00732 +2024-11-21 23:45:49.147798: train_loss -0.7782 +2024-11-21 23:45:49.155188: val_loss -0.7722 +2024-11-21 23:45:49.155294: Pseudo dice [0.8553] +2024-11-21 23:45:49.155379: Epoch time: 19.38 s +2024-11-21 23:45:50.105507: +2024-11-21 23:45:50.105717: Epoch 2344 +2024-11-21 23:45:50.105860: Current learning rate: 0.00732 +2024-11-21 23:46:07.484778: train_loss -0.7674 +2024-11-21 23:46:07.490382: val_loss -0.762 +2024-11-21 23:46:07.490530: Pseudo dice [0.8554] +2024-11-21 23:46:07.490639: Epoch time: 17.38 s +2024-11-21 23:46:08.419110: +2024-11-21 23:46:08.419336: Epoch 2345 +2024-11-21 23:46:08.419470: Current learning rate: 0.00732 +2024-11-21 23:46:26.650034: train_loss -0.7786 +2024-11-21 23:46:26.653071: val_loss -0.7839 +2024-11-21 23:46:26.653188: Pseudo dice [0.8596] +2024-11-21 23:46:26.653294: Epoch time: 18.23 s +2024-11-21 23:46:27.464149: +2024-11-21 23:46:27.464353: Epoch 2346 +2024-11-21 23:46:27.464487: Current learning rate: 0.00732 +2024-11-21 23:46:46.054698: train_loss -0.7674 +2024-11-21 23:46:46.065148: val_loss -0.7692 +2024-11-21 23:46:46.065497: Pseudo dice [0.8391] +2024-11-21 23:46:46.065624: Epoch time: 18.59 s +2024-11-21 23:46:47.093758: +2024-11-21 23:46:47.093969: Epoch 2347 +2024-11-21 23:46:47.094112: Current learning rate: 0.00732 +2024-11-21 23:47:06.712440: train_loss -0.7751 +2024-11-21 23:47:06.719931: val_loss -0.7673 +2024-11-21 23:47:06.720140: Pseudo dice [0.8529] +2024-11-21 23:47:06.720301: Epoch time: 19.62 s +2024-11-21 23:47:07.733489: +2024-11-21 23:47:07.733724: Epoch 2348 +2024-11-21 23:47:07.733836: Current learning rate: 0.00731 +2024-11-21 23:47:26.364113: train_loss -0.7708 +2024-11-21 23:47:26.371791: val_loss -0.7742 +2024-11-21 23:47:26.371951: Pseudo dice [0.8389] +2024-11-21 23:47:26.372072: Epoch time: 18.63 s +2024-11-21 23:47:27.238381: +2024-11-21 23:47:27.238575: Epoch 2349 +2024-11-21 23:47:27.238686: Current learning rate: 0.00731 +2024-11-21 23:47:45.463872: train_loss -0.7832 +2024-11-21 23:47:45.473002: val_loss -0.7555 +2024-11-21 23:47:45.473149: Pseudo dice [0.865] +2024-11-21 23:47:45.473249: Epoch time: 18.23 s +2024-11-21 23:47:46.687260: +2024-11-21 23:47:46.687451: Epoch 2350 +2024-11-21 23:47:46.687571: Current learning rate: 0.00731 +2024-11-21 23:48:06.310281: train_loss -0.7717 +2024-11-21 23:48:06.335967: val_loss -0.7818 +2024-11-21 23:48:06.336079: Pseudo dice [0.8615] +2024-11-21 23:48:06.336170: Epoch time: 19.62 s +2024-11-21 23:48:07.141698: +2024-11-21 23:48:07.141911: Epoch 2351 +2024-11-21 23:48:07.142049: Current learning rate: 0.00731 +2024-11-21 23:48:26.686580: train_loss -0.777 +2024-11-21 23:48:26.700287: val_loss -0.7759 +2024-11-21 23:48:26.700437: Pseudo dice [0.8554] +2024-11-21 23:48:26.700535: Epoch time: 19.55 s +2024-11-21 23:48:27.962414: +2024-11-21 23:48:27.962641: Epoch 2352 +2024-11-21 23:48:27.962752: Current learning rate: 0.00731 +2024-11-21 23:48:46.251816: train_loss -0.7742 +2024-11-21 23:48:46.254771: val_loss -0.7667 +2024-11-21 23:48:46.254922: Pseudo dice [0.8524] +2024-11-21 23:48:46.255023: Epoch time: 18.29 s +2024-11-21 23:48:47.072917: +2024-11-21 23:48:47.073139: Epoch 2353 +2024-11-21 23:48:47.073269: Current learning rate: 0.00731 +2024-11-21 23:49:05.810080: train_loss -0.7709 +2024-11-21 23:49:05.819311: val_loss -0.7911 +2024-11-21 23:49:05.819497: Pseudo dice [0.8543] +2024-11-21 23:49:05.819617: Epoch time: 18.74 s +2024-11-21 23:49:06.655287: +2024-11-21 23:49:06.655495: Epoch 2354 +2024-11-21 23:49:06.655611: Current learning rate: 0.00731 +2024-11-21 23:49:25.047670: train_loss -0.7714 +2024-11-21 23:49:25.050272: val_loss -0.7518 +2024-11-21 23:49:25.050375: Pseudo dice [0.8467] +2024-11-21 23:49:25.050495: Epoch time: 18.39 s +2024-11-21 23:49:25.857956: +2024-11-21 23:49:25.858166: Epoch 2355 +2024-11-21 23:49:25.858281: Current learning rate: 0.00731 +2024-11-21 23:49:45.226265: train_loss -0.7748 +2024-11-21 23:49:45.240044: val_loss -0.7441 +2024-11-21 23:49:45.240188: Pseudo dice [0.8576] +2024-11-21 23:49:45.240285: Epoch time: 19.37 s +2024-11-21 23:49:46.230145: +2024-11-21 23:49:46.230355: Epoch 2356 +2024-11-21 23:49:46.230495: Current learning rate: 0.00731 +2024-11-21 23:50:05.614561: train_loss -0.7723 +2024-11-21 23:50:05.631439: val_loss -0.7762 +2024-11-21 23:50:05.631587: Pseudo dice [0.8496] +2024-11-21 23:50:05.631689: Epoch time: 19.39 s +2024-11-21 23:50:06.551796: +2024-11-21 23:50:06.551985: Epoch 2357 +2024-11-21 23:50:06.552123: Current learning rate: 0.0073 +2024-11-21 23:50:24.711797: train_loss -0.7671 +2024-11-21 23:50:24.714440: val_loss -0.7812 +2024-11-21 23:50:24.714535: Pseudo dice [0.8421] +2024-11-21 23:50:24.714623: Epoch time: 18.16 s +2024-11-21 23:50:25.528822: +2024-11-21 23:50:25.529025: Epoch 2358 +2024-11-21 23:50:25.529148: Current learning rate: 0.0073 +2024-11-21 23:50:44.914311: train_loss -0.7706 +2024-11-21 23:50:44.923692: val_loss -0.7691 +2024-11-21 23:50:44.923844: Pseudo dice [0.8426] +2024-11-21 23:50:44.923926: Epoch time: 19.39 s +2024-11-21 23:50:45.778278: +2024-11-21 23:50:45.778539: Epoch 2359 +2024-11-21 23:50:45.778676: Current learning rate: 0.0073 +2024-11-21 23:51:04.911957: train_loss -0.7718 +2024-11-21 23:51:04.914116: val_loss -0.7615 +2024-11-21 23:51:04.914219: Pseudo dice [0.8454] +2024-11-21 23:51:04.914363: Epoch time: 19.13 s +2024-11-21 23:51:05.734776: +2024-11-21 23:51:05.735016: Epoch 2360 +2024-11-21 23:51:05.735132: Current learning rate: 0.0073 +2024-11-21 23:51:24.907307: train_loss -0.7756 +2024-11-21 23:51:24.912027: val_loss -0.7585 +2024-11-21 23:51:24.912156: Pseudo dice [0.843] +2024-11-21 23:51:24.912263: Epoch time: 19.17 s +2024-11-21 23:51:25.933571: +2024-11-21 23:51:25.933768: Epoch 2361 +2024-11-21 23:51:25.933890: Current learning rate: 0.0073 +2024-11-21 23:51:44.448955: train_loss -0.7755 +2024-11-21 23:51:44.454856: val_loss -0.7355 +2024-11-21 23:51:44.455011: Pseudo dice [0.8301] +2024-11-21 23:51:44.455113: Epoch time: 18.52 s +2024-11-21 23:51:45.340262: +2024-11-21 23:51:45.340496: Epoch 2362 +2024-11-21 23:51:45.340620: Current learning rate: 0.0073 +2024-11-21 23:52:04.866369: train_loss -0.7698 +2024-11-21 23:52:04.872342: val_loss -0.7519 +2024-11-21 23:52:04.872550: Pseudo dice [0.8423] +2024-11-21 23:52:04.872665: Epoch time: 19.53 s +2024-11-21 23:52:05.691133: +2024-11-21 23:52:05.691556: Epoch 2363 +2024-11-21 23:52:05.691702: Current learning rate: 0.0073 +2024-11-21 23:52:24.248440: train_loss -0.7712 +2024-11-21 23:52:24.257655: val_loss -0.777 +2024-11-21 23:52:24.257803: Pseudo dice [0.8636] +2024-11-21 23:52:24.257906: Epoch time: 18.56 s +2024-11-21 23:52:25.699077: +2024-11-21 23:52:25.699523: Epoch 2364 +2024-11-21 23:52:25.699663: Current learning rate: 0.0073 +2024-11-21 23:52:45.024722: train_loss -0.7524 +2024-11-21 23:52:45.027172: val_loss -0.7372 +2024-11-21 23:52:45.027308: Pseudo dice [0.8495] +2024-11-21 23:52:45.027388: Epoch time: 19.33 s +2024-11-21 23:52:45.886905: +2024-11-21 23:52:45.887325: Epoch 2365 +2024-11-21 23:52:45.887481: Current learning rate: 0.00729 +2024-11-21 23:53:04.501211: train_loss -0.7694 +2024-11-21 23:53:04.505693: val_loss -0.7583 +2024-11-21 23:53:04.505827: Pseudo dice [0.8643] +2024-11-21 23:53:04.505961: Epoch time: 18.62 s +2024-11-21 23:53:05.436853: +2024-11-21 23:53:05.437338: Epoch 2366 +2024-11-21 23:53:05.437481: Current learning rate: 0.00729 +2024-11-21 23:53:25.204320: train_loss -0.7779 +2024-11-21 23:53:25.210843: val_loss -0.7496 +2024-11-21 23:53:25.210983: Pseudo dice [0.8405] +2024-11-21 23:53:25.211089: Epoch time: 19.77 s +2024-11-21 23:53:26.026272: +2024-11-21 23:53:26.026711: Epoch 2367 +2024-11-21 23:53:26.026848: Current learning rate: 0.00729 +2024-11-21 23:53:45.372730: train_loss -0.7713 +2024-11-21 23:53:45.380994: val_loss -0.7495 +2024-11-21 23:53:45.381208: Pseudo dice [0.8427] +2024-11-21 23:53:45.381321: Epoch time: 19.35 s +2024-11-21 23:53:46.197177: +2024-11-21 23:53:46.197628: Epoch 2368 +2024-11-21 23:53:46.197772: Current learning rate: 0.00729 +2024-11-21 23:54:05.184498: train_loss -0.7732 +2024-11-21 23:54:05.189023: val_loss -0.784 +2024-11-21 23:54:05.189181: Pseudo dice [0.8524] +2024-11-21 23:54:05.189277: Epoch time: 18.99 s +2024-11-21 23:54:06.019009: +2024-11-21 23:54:06.019483: Epoch 2369 +2024-11-21 23:54:06.019649: Current learning rate: 0.00729 +2024-11-21 23:54:25.581509: train_loss -0.7686 +2024-11-21 23:54:25.587184: val_loss -0.7483 +2024-11-21 23:54:25.587323: Pseudo dice [0.8515] +2024-11-21 23:54:25.587415: Epoch time: 19.56 s +2024-11-21 23:54:26.423460: +2024-11-21 23:54:26.423909: Epoch 2370 +2024-11-21 23:54:26.424069: Current learning rate: 0.00729 +2024-11-21 23:54:45.683157: train_loss -0.7833 +2024-11-21 23:54:45.689501: val_loss -0.773 +2024-11-21 23:54:45.689655: Pseudo dice [0.8615] +2024-11-21 23:54:45.689775: Epoch time: 19.26 s +2024-11-21 23:54:46.528412: +2024-11-21 23:54:46.528865: Epoch 2371 +2024-11-21 23:54:46.529018: Current learning rate: 0.00729 +2024-11-21 23:55:05.485317: train_loss -0.7787 +2024-11-21 23:55:05.490793: val_loss -0.7623 +2024-11-21 23:55:05.490924: Pseudo dice [0.8545] +2024-11-21 23:55:05.491011: Epoch time: 18.96 s +2024-11-21 23:55:06.302452: +2024-11-21 23:55:06.302902: Epoch 2372 +2024-11-21 23:55:06.303040: Current learning rate: 0.00729 +2024-11-21 23:55:25.772806: train_loss -0.7714 +2024-11-21 23:55:25.789707: val_loss -0.7588 +2024-11-21 23:55:25.789812: Pseudo dice [0.8533] +2024-11-21 23:55:25.789928: Epoch time: 19.47 s +2024-11-21 23:55:26.594939: +2024-11-21 23:55:26.595160: Epoch 2373 +2024-11-21 23:55:26.595280: Current learning rate: 0.00729 +2024-11-21 23:55:45.823977: train_loss -0.7551 +2024-11-21 23:55:45.832740: val_loss -0.7669 +2024-11-21 23:55:45.832880: Pseudo dice [0.85] +2024-11-21 23:55:45.832977: Epoch time: 19.23 s +2024-11-21 23:55:46.772363: +2024-11-21 23:55:46.772603: Epoch 2374 +2024-11-21 23:55:46.772732: Current learning rate: 0.00728 +2024-11-21 23:56:05.369421: train_loss -0.764 +2024-11-21 23:56:05.377964: val_loss -0.7509 +2024-11-21 23:56:05.378176: Pseudo dice [0.8423] +2024-11-21 23:56:05.378278: Epoch time: 18.6 s +2024-11-21 23:56:06.218078: +2024-11-21 23:56:06.218275: Epoch 2375 +2024-11-21 23:56:06.218395: Current learning rate: 0.00728 +2024-11-21 23:56:24.447818: train_loss -0.7735 +2024-11-21 23:56:24.456555: val_loss -0.773 +2024-11-21 23:56:24.456678: Pseudo dice [0.8339] +2024-11-21 23:56:24.456771: Epoch time: 18.23 s +2024-11-21 23:56:25.781229: +2024-11-21 23:56:25.781751: Epoch 2376 +2024-11-21 23:56:25.781917: Current learning rate: 0.00728 +2024-11-21 23:56:44.729774: train_loss -0.7644 +2024-11-21 23:56:44.732247: val_loss -0.7527 +2024-11-21 23:56:44.732343: Pseudo dice [0.8397] +2024-11-21 23:56:44.732439: Epoch time: 18.95 s +2024-11-21 23:56:45.539389: +2024-11-21 23:56:45.539898: Epoch 2377 +2024-11-21 23:56:45.540067: Current learning rate: 0.00728 +2024-11-21 23:57:04.099652: train_loss -0.7658 +2024-11-21 23:57:04.106099: val_loss -0.7516 +2024-11-21 23:57:04.106223: Pseudo dice [0.8283] +2024-11-21 23:57:04.106314: Epoch time: 18.56 s +2024-11-21 23:57:05.009570: +2024-11-21 23:57:05.009997: Epoch 2378 +2024-11-21 23:57:05.010160: Current learning rate: 0.00728 +2024-11-21 23:57:24.071176: train_loss -0.7762 +2024-11-21 23:57:24.073789: val_loss -0.7686 +2024-11-21 23:57:24.073917: Pseudo dice [0.8534] +2024-11-21 23:57:24.074016: Epoch time: 19.06 s +2024-11-21 23:57:24.894944: +2024-11-21 23:57:24.895356: Epoch 2379 +2024-11-21 23:57:24.895499: Current learning rate: 0.00728 +2024-11-21 23:57:43.555568: train_loss -0.7757 +2024-11-21 23:57:43.564383: val_loss -0.7725 +2024-11-21 23:57:43.564506: Pseudo dice [0.851] +2024-11-21 23:57:43.564590: Epoch time: 18.66 s +2024-11-21 23:57:44.453352: +2024-11-21 23:57:44.453780: Epoch 2380 +2024-11-21 23:57:44.453932: Current learning rate: 0.00728 +2024-11-21 23:58:04.714115: train_loss -0.7783 +2024-11-21 23:58:04.726737: val_loss -0.7657 +2024-11-21 23:58:04.726892: Pseudo dice [0.8444] +2024-11-21 23:58:04.727011: Epoch time: 20.26 s +2024-11-21 23:58:05.561496: +2024-11-21 23:58:05.561937: Epoch 2381 +2024-11-21 23:58:05.562089: Current learning rate: 0.00728 +2024-11-21 23:58:24.672438: train_loss -0.773 +2024-11-21 23:58:24.681480: val_loss -0.7508 +2024-11-21 23:58:24.681634: Pseudo dice [0.8397] +2024-11-21 23:58:24.681737: Epoch time: 19.11 s +2024-11-21 23:58:25.500056: +2024-11-21 23:58:25.500503: Epoch 2382 +2024-11-21 23:58:25.500667: Current learning rate: 0.00728 +2024-11-21 23:58:44.288661: train_loss -0.7728 +2024-11-21 23:58:44.292969: val_loss -0.7577 +2024-11-21 23:58:44.293119: Pseudo dice [0.849] +2024-11-21 23:58:44.293217: Epoch time: 18.79 s +2024-11-21 23:58:45.110016: +2024-11-21 23:58:45.110461: Epoch 2383 +2024-11-21 23:58:45.110603: Current learning rate: 0.00727 +2024-11-21 23:59:04.726651: train_loss -0.7727 +2024-11-21 23:59:04.735665: val_loss -0.7841 +2024-11-21 23:59:04.735792: Pseudo dice [0.846] +2024-11-21 23:59:04.735893: Epoch time: 19.62 s +2024-11-21 23:59:05.614905: +2024-11-21 23:59:05.615117: Epoch 2384 +2024-11-21 23:59:05.615236: Current learning rate: 0.00727 +2024-11-21 23:59:24.396713: train_loss -0.7776 +2024-11-21 23:59:24.404829: val_loss -0.7929 +2024-11-21 23:59:24.404955: Pseudo dice [0.8601] +2024-11-21 23:59:24.405341: Epoch time: 18.78 s +2024-11-21 23:59:25.285494: +2024-11-21 23:59:25.285733: Epoch 2385 +2024-11-21 23:59:25.285881: Current learning rate: 0.00727 +2024-11-21 23:59:44.104121: train_loss -0.7664 +2024-11-21 23:59:44.108783: val_loss -0.7733 +2024-11-21 23:59:44.108983: Pseudo dice [0.8572] +2024-11-21 23:59:44.109090: Epoch time: 18.82 s +2024-11-21 23:59:45.045572: +2024-11-21 23:59:45.045779: Epoch 2386 +2024-11-21 23:59:45.045907: Current learning rate: 0.00727 +2024-11-22 00:00:04.200657: train_loss -0.7728 +2024-11-22 00:00:04.210186: val_loss -0.7522 +2024-11-22 00:00:04.210322: Pseudo dice [0.8548] +2024-11-22 00:00:04.210427: Epoch time: 19.16 s +2024-11-22 00:00:05.234141: +2024-11-22 00:00:05.234375: Epoch 2387 +2024-11-22 00:00:05.234515: Current learning rate: 0.00727 +2024-11-22 00:00:23.782629: train_loss -0.7708 +2024-11-22 00:00:23.794846: val_loss -0.7848 +2024-11-22 00:00:23.794981: Pseudo dice [0.8406] +2024-11-22 00:00:23.795099: Epoch time: 18.55 s +2024-11-22 00:00:25.156240: +2024-11-22 00:00:25.156461: Epoch 2388 +2024-11-22 00:00:25.156598: Current learning rate: 0.00727 +2024-11-22 00:00:44.972286: train_loss -0.7772 +2024-11-22 00:00:44.979107: val_loss -0.7716 +2024-11-22 00:00:44.979267: Pseudo dice [0.857] +2024-11-22 00:00:44.979374: Epoch time: 19.82 s +2024-11-22 00:00:45.944967: +2024-11-22 00:00:45.945178: Epoch 2389 +2024-11-22 00:00:45.945294: Current learning rate: 0.00727 +2024-11-22 00:01:05.797944: train_loss -0.7658 +2024-11-22 00:01:05.806482: val_loss -0.7514 +2024-11-22 00:01:05.806641: Pseudo dice [0.8546] +2024-11-22 00:01:05.806813: Epoch time: 19.85 s +2024-11-22 00:01:06.629167: +2024-11-22 00:01:06.629396: Epoch 2390 +2024-11-22 00:01:06.629516: Current learning rate: 0.00727 +2024-11-22 00:01:26.534024: train_loss -0.7684 +2024-11-22 00:01:26.540353: val_loss -0.7707 +2024-11-22 00:01:26.540499: Pseudo dice [0.8397] +2024-11-22 00:01:26.540595: Epoch time: 19.91 s +2024-11-22 00:01:27.364881: +2024-11-22 00:01:27.365099: Epoch 2391 +2024-11-22 00:01:27.365213: Current learning rate: 0.00726 +2024-11-22 00:01:45.891115: train_loss -0.7596 +2024-11-22 00:01:45.896979: val_loss -0.7577 +2024-11-22 00:01:45.897098: Pseudo dice [0.8508] +2024-11-22 00:01:45.897203: Epoch time: 18.53 s +2024-11-22 00:01:46.753628: +2024-11-22 00:01:46.753844: Epoch 2392 +2024-11-22 00:01:46.753961: Current learning rate: 0.00726 +2024-11-22 00:02:06.033919: train_loss -0.7621 +2024-11-22 00:02:06.039795: val_loss -0.7204 +2024-11-22 00:02:06.039948: Pseudo dice [0.8371] +2024-11-22 00:02:06.040054: Epoch time: 19.28 s +2024-11-22 00:02:06.871085: +2024-11-22 00:02:06.871333: Epoch 2393 +2024-11-22 00:02:06.871460: Current learning rate: 0.00726 +2024-11-22 00:02:25.934437: train_loss -0.7406 +2024-11-22 00:02:25.941663: val_loss -0.7902 +2024-11-22 00:02:25.941817: Pseudo dice [0.8325] +2024-11-22 00:02:25.941935: Epoch time: 19.06 s +2024-11-22 00:02:27.002363: +2024-11-22 00:02:27.002591: Epoch 2394 +2024-11-22 00:02:27.002737: Current learning rate: 0.00726 +2024-11-22 00:02:45.830254: train_loss -0.7534 +2024-11-22 00:02:45.849081: val_loss -0.7682 +2024-11-22 00:02:45.849229: Pseudo dice [0.8387] +2024-11-22 00:02:45.849318: Epoch time: 18.83 s +2024-11-22 00:02:46.748082: +2024-11-22 00:02:46.748287: Epoch 2395 +2024-11-22 00:02:46.748421: Current learning rate: 0.00726 +2024-11-22 00:03:06.682907: train_loss -0.7612 +2024-11-22 00:03:06.685422: val_loss -0.7624 +2024-11-22 00:03:06.685557: Pseudo dice [0.8453] +2024-11-22 00:03:06.685659: Epoch time: 19.94 s +2024-11-22 00:03:07.510747: +2024-11-22 00:03:07.510941: Epoch 2396 +2024-11-22 00:03:07.511066: Current learning rate: 0.00726 +2024-11-22 00:03:26.863412: train_loss -0.7628 +2024-11-22 00:03:26.870801: val_loss -0.7617 +2024-11-22 00:03:26.870959: Pseudo dice [0.8403] +2024-11-22 00:03:26.871079: Epoch time: 19.35 s +2024-11-22 00:03:27.739460: +2024-11-22 00:03:27.739724: Epoch 2397 +2024-11-22 00:03:27.739845: Current learning rate: 0.00726 +2024-11-22 00:03:46.373810: train_loss -0.7657 +2024-11-22 00:03:46.392322: val_loss -0.7301 +2024-11-22 00:03:46.392507: Pseudo dice [0.8403] +2024-11-22 00:03:46.392606: Epoch time: 18.64 s +2024-11-22 00:03:47.252821: +2024-11-22 00:03:47.253034: Epoch 2398 +2024-11-22 00:03:47.253165: Current learning rate: 0.00726 +2024-11-22 00:04:06.586861: train_loss -0.7809 +2024-11-22 00:04:06.594768: val_loss -0.7497 +2024-11-22 00:04:06.594917: Pseudo dice [0.8261] +2024-11-22 00:04:06.595015: Epoch time: 19.33 s +2024-11-22 00:04:07.426601: +2024-11-22 00:04:07.426857: Epoch 2399 +2024-11-22 00:04:07.426981: Current learning rate: 0.00726 +2024-11-22 00:04:26.756543: train_loss -0.7749 +2024-11-22 00:04:26.759830: val_loss -0.7577 +2024-11-22 00:04:26.759926: Pseudo dice [0.8576] +2024-11-22 00:04:26.760021: Epoch time: 19.33 s +2024-11-22 00:04:28.200671: +2024-11-22 00:04:28.200910: Epoch 2400 +2024-11-22 00:04:28.201028: Current learning rate: 0.00725 +2024-11-22 00:04:46.805252: train_loss -0.7744 +2024-11-22 00:04:46.811953: val_loss -0.7854 +2024-11-22 00:04:46.812124: Pseudo dice [0.8478] +2024-11-22 00:04:46.812220: Epoch time: 18.61 s +2024-11-22 00:04:47.840496: +2024-11-22 00:04:47.840704: Epoch 2401 +2024-11-22 00:04:47.840828: Current learning rate: 0.00725 +2024-11-22 00:05:06.882598: train_loss -0.7698 +2024-11-22 00:05:06.889175: val_loss -0.7389 +2024-11-22 00:05:06.889310: Pseudo dice [0.8419] +2024-11-22 00:05:06.889410: Epoch time: 19.04 s +2024-11-22 00:05:07.819628: +2024-11-22 00:05:07.819863: Epoch 2402 +2024-11-22 00:05:07.819996: Current learning rate: 0.00725 +2024-11-22 00:05:27.566448: train_loss -0.7515 +2024-11-22 00:05:27.570199: val_loss -0.7667 +2024-11-22 00:05:27.570323: Pseudo dice [0.8443] +2024-11-22 00:05:27.570425: Epoch time: 19.75 s +2024-11-22 00:05:28.502292: +2024-11-22 00:05:28.502489: Epoch 2403 +2024-11-22 00:05:28.502606: Current learning rate: 0.00725 +2024-11-22 00:05:47.131561: train_loss -0.7764 +2024-11-22 00:05:47.140367: val_loss -0.7626 +2024-11-22 00:05:47.140507: Pseudo dice [0.8438] +2024-11-22 00:05:47.140599: Epoch time: 18.63 s +2024-11-22 00:05:47.978468: +2024-11-22 00:05:47.978729: Epoch 2404 +2024-11-22 00:05:47.978863: Current learning rate: 0.00725 +2024-11-22 00:06:07.434700: train_loss -0.7757 +2024-11-22 00:06:07.440330: val_loss -0.7736 +2024-11-22 00:06:07.440486: Pseudo dice [0.8393] +2024-11-22 00:06:07.440581: Epoch time: 19.46 s +2024-11-22 00:06:08.387681: +2024-11-22 00:06:08.387908: Epoch 2405 +2024-11-22 00:06:08.388030: Current learning rate: 0.00725 +2024-11-22 00:06:27.936310: train_loss -0.7808 +2024-11-22 00:06:27.938677: val_loss -0.7782 +2024-11-22 00:06:27.938808: Pseudo dice [0.8529] +2024-11-22 00:06:27.938901: Epoch time: 19.55 s +2024-11-22 00:06:28.760924: +2024-11-22 00:06:28.761132: Epoch 2406 +2024-11-22 00:06:28.761266: Current learning rate: 0.00725 +2024-11-22 00:06:47.968171: train_loss -0.7803 +2024-11-22 00:06:47.977850: val_loss -0.7565 +2024-11-22 00:06:47.978005: Pseudo dice [0.8432] +2024-11-22 00:06:47.978163: Epoch time: 19.21 s +2024-11-22 00:06:48.803796: +2024-11-22 00:06:48.803994: Epoch 2407 +2024-11-22 00:06:48.804122: Current learning rate: 0.00725 +2024-11-22 00:07:06.797152: train_loss -0.7749 +2024-11-22 00:07:06.804105: val_loss -0.7665 +2024-11-22 00:07:06.804241: Pseudo dice [0.8503] +2024-11-22 00:07:06.804334: Epoch time: 17.99 s +2024-11-22 00:07:07.636966: +2024-11-22 00:07:07.637208: Epoch 2408 +2024-11-22 00:07:07.637334: Current learning rate: 0.00724 +2024-11-22 00:07:26.252082: train_loss -0.7726 +2024-11-22 00:07:26.255826: val_loss -0.7626 +2024-11-22 00:07:26.255959: Pseudo dice [0.8488] +2024-11-22 00:07:26.256045: Epoch time: 18.62 s +2024-11-22 00:07:27.077319: +2024-11-22 00:07:27.077516: Epoch 2409 +2024-11-22 00:07:27.077631: Current learning rate: 0.00724 +2024-11-22 00:07:46.007944: train_loss -0.7688 +2024-11-22 00:07:46.013100: val_loss -0.7502 +2024-11-22 00:07:46.013252: Pseudo dice [0.8486] +2024-11-22 00:07:46.013356: Epoch time: 18.93 s +2024-11-22 00:07:46.837454: +2024-11-22 00:07:46.837652: Epoch 2410 +2024-11-22 00:07:46.855173: Current learning rate: 0.00724 +2024-11-22 00:08:05.258646: train_loss -0.7756 +2024-11-22 00:08:05.265736: val_loss -0.7465 +2024-11-22 00:08:05.265863: Pseudo dice [0.8365] +2024-11-22 00:08:05.265954: Epoch time: 18.42 s +2024-11-22 00:08:06.593149: +2024-11-22 00:08:06.593389: Epoch 2411 +2024-11-22 00:08:06.593524: Current learning rate: 0.00724 +2024-11-22 00:08:25.013716: train_loss -0.7625 +2024-11-22 00:08:25.022759: val_loss -0.7762 +2024-11-22 00:08:25.022917: Pseudo dice [0.8542] +2024-11-22 00:08:25.023028: Epoch time: 18.42 s +2024-11-22 00:08:26.008244: +2024-11-22 00:08:26.008449: Epoch 2412 +2024-11-22 00:08:26.008580: Current learning rate: 0.00724 +2024-11-22 00:08:44.404904: train_loss -0.7684 +2024-11-22 00:08:44.407202: val_loss -0.7629 +2024-11-22 00:08:44.407307: Pseudo dice [0.8404] +2024-11-22 00:08:44.407407: Epoch time: 18.4 s +2024-11-22 00:08:45.226242: +2024-11-22 00:08:45.226446: Epoch 2413 +2024-11-22 00:08:45.226572: Current learning rate: 0.00724 +2024-11-22 00:09:04.427311: train_loss -0.7658 +2024-11-22 00:09:04.429223: val_loss -0.7667 +2024-11-22 00:09:04.429327: Pseudo dice [0.838] +2024-11-22 00:09:04.429426: Epoch time: 19.2 s +2024-11-22 00:09:05.248863: +2024-11-22 00:09:05.249102: Epoch 2414 +2024-11-22 00:09:05.249254: Current learning rate: 0.00724 +2024-11-22 00:09:24.692117: train_loss -0.7573 +2024-11-22 00:09:24.695957: val_loss -0.7552 +2024-11-22 00:09:24.696082: Pseudo dice [0.8462] +2024-11-22 00:09:24.696170: Epoch time: 19.44 s +2024-11-22 00:09:25.514395: +2024-11-22 00:09:25.514595: Epoch 2415 +2024-11-22 00:09:25.514713: Current learning rate: 0.00724 +2024-11-22 00:09:45.565265: train_loss -0.7659 +2024-11-22 00:09:45.569071: val_loss -0.7586 +2024-11-22 00:09:45.569231: Pseudo dice [0.8324] +2024-11-22 00:09:45.569325: Epoch time: 20.05 s +2024-11-22 00:09:46.393098: +2024-11-22 00:09:46.393315: Epoch 2416 +2024-11-22 00:09:46.393440: Current learning rate: 0.00724 +2024-11-22 00:10:05.925484: train_loss -0.7619 +2024-11-22 00:10:05.943521: val_loss -0.766 +2024-11-22 00:10:05.943675: Pseudo dice [0.841] +2024-11-22 00:10:05.943770: Epoch time: 19.53 s +2024-11-22 00:10:06.834316: +2024-11-22 00:10:06.834516: Epoch 2417 +2024-11-22 00:10:06.834636: Current learning rate: 0.00723 +2024-11-22 00:10:25.637906: train_loss -0.768 +2024-11-22 00:10:25.644037: val_loss -0.757 +2024-11-22 00:10:25.644173: Pseudo dice [0.8439] +2024-11-22 00:10:25.644281: Epoch time: 18.8 s +2024-11-22 00:10:26.478593: +2024-11-22 00:10:26.478828: Epoch 2418 +2024-11-22 00:10:26.478948: Current learning rate: 0.00723 +2024-11-22 00:10:45.111684: train_loss -0.7842 +2024-11-22 00:10:45.114468: val_loss -0.7624 +2024-11-22 00:10:45.114619: Pseudo dice [0.8487] +2024-11-22 00:10:45.115444: Epoch time: 18.63 s +2024-11-22 00:10:45.967948: +2024-11-22 00:10:45.968148: Epoch 2419 +2024-11-22 00:10:45.968282: Current learning rate: 0.00723 +2024-11-22 00:11:04.686116: train_loss -0.7783 +2024-11-22 00:11:04.692588: val_loss -0.7723 +2024-11-22 00:11:04.692731: Pseudo dice [0.8464] +2024-11-22 00:11:04.692820: Epoch time: 18.72 s +2024-11-22 00:11:05.777270: +2024-11-22 00:11:05.777503: Epoch 2420 +2024-11-22 00:11:05.777627: Current learning rate: 0.00723 +2024-11-22 00:11:25.081324: train_loss -0.7796 +2024-11-22 00:11:25.096219: val_loss -0.7883 +2024-11-22 00:11:25.096385: Pseudo dice [0.8518] +2024-11-22 00:11:25.096510: Epoch time: 19.3 s +2024-11-22 00:11:26.090414: +2024-11-22 00:11:26.090639: Epoch 2421 +2024-11-22 00:11:26.090783: Current learning rate: 0.00723 +2024-11-22 00:11:46.057726: train_loss -0.7856 +2024-11-22 00:11:46.071681: val_loss -0.7805 +2024-11-22 00:11:46.071911: Pseudo dice [0.8581] +2024-11-22 00:11:46.072090: Epoch time: 19.97 s +2024-11-22 00:11:46.894262: +2024-11-22 00:11:46.894481: Epoch 2422 +2024-11-22 00:11:46.894635: Current learning rate: 0.00723 +2024-11-22 00:12:06.437161: train_loss -0.7777 +2024-11-22 00:12:06.440029: val_loss -0.7629 +2024-11-22 00:12:06.440136: Pseudo dice [0.8426] +2024-11-22 00:12:06.440233: Epoch time: 19.54 s +2024-11-22 00:12:07.643455: +2024-11-22 00:12:07.643663: Epoch 2423 +2024-11-22 00:12:07.643773: Current learning rate: 0.00723 +2024-11-22 00:12:27.295224: train_loss -0.7712 +2024-11-22 00:12:27.325254: val_loss -0.7516 +2024-11-22 00:12:27.325445: Pseudo dice [0.8316] +2024-11-22 00:12:27.325559: Epoch time: 19.65 s +2024-11-22 00:12:28.147316: +2024-11-22 00:12:28.147552: Epoch 2424 +2024-11-22 00:12:28.147680: Current learning rate: 0.00723 +2024-11-22 00:12:47.513854: train_loss -0.7545 +2024-11-22 00:12:47.519649: val_loss -0.7603 +2024-11-22 00:12:47.519789: Pseudo dice [0.8332] +2024-11-22 00:12:47.519896: Epoch time: 19.37 s +2024-11-22 00:12:48.347088: +2024-11-22 00:12:48.347313: Epoch 2425 +2024-11-22 00:12:48.347438: Current learning rate: 0.00723 +2024-11-22 00:13:07.667555: train_loss -0.7658 +2024-11-22 00:13:07.676355: val_loss -0.7695 +2024-11-22 00:13:07.676510: Pseudo dice [0.8416] +2024-11-22 00:13:07.676609: Epoch time: 19.32 s +2024-11-22 00:13:08.517143: +2024-11-22 00:13:08.517395: Epoch 2426 +2024-11-22 00:13:08.517517: Current learning rate: 0.00722 +2024-11-22 00:13:27.881261: train_loss -0.7759 +2024-11-22 00:13:27.890091: val_loss -0.7774 +2024-11-22 00:13:27.890214: Pseudo dice [0.8524] +2024-11-22 00:13:27.890325: Epoch time: 19.36 s +2024-11-22 00:13:28.907981: +2024-11-22 00:13:28.908225: Epoch 2427 +2024-11-22 00:13:28.908344: Current learning rate: 0.00722 +2024-11-22 00:13:47.506498: train_loss -0.769 +2024-11-22 00:13:47.510967: val_loss -0.7548 +2024-11-22 00:13:47.511100: Pseudo dice [0.8572] +2024-11-22 00:13:47.511196: Epoch time: 18.6 s +2024-11-22 00:13:48.328695: +2024-11-22 00:13:48.328910: Epoch 2428 +2024-11-22 00:13:48.329026: Current learning rate: 0.00722 +2024-11-22 00:14:06.557006: train_loss -0.765 +2024-11-22 00:14:06.565256: val_loss -0.7779 +2024-11-22 00:14:06.565521: Pseudo dice [0.8553] +2024-11-22 00:14:06.565661: Epoch time: 18.23 s +2024-11-22 00:14:07.396595: +2024-11-22 00:14:07.396811: Epoch 2429 +2024-11-22 00:14:07.396944: Current learning rate: 0.00722 +2024-11-22 00:14:27.018953: train_loss -0.7726 +2024-11-22 00:14:27.021361: val_loss -0.7437 +2024-11-22 00:14:27.021488: Pseudo dice [0.8441] +2024-11-22 00:14:27.021600: Epoch time: 19.62 s +2024-11-22 00:14:27.838455: +2024-11-22 00:14:27.838660: Epoch 2430 +2024-11-22 00:14:27.838792: Current learning rate: 0.00722 +2024-11-22 00:14:47.174144: train_loss -0.7782 +2024-11-22 00:14:47.182815: val_loss -0.7622 +2024-11-22 00:14:47.182969: Pseudo dice [0.8568] +2024-11-22 00:14:47.183084: Epoch time: 19.34 s +2024-11-22 00:14:48.045239: +2024-11-22 00:14:48.045456: Epoch 2431 +2024-11-22 00:14:48.045586: Current learning rate: 0.00722 +2024-11-22 00:15:07.484958: train_loss -0.7782 +2024-11-22 00:15:07.492081: val_loss -0.7701 +2024-11-22 00:15:07.492239: Pseudo dice [0.8575] +2024-11-22 00:15:07.492347: Epoch time: 19.44 s +2024-11-22 00:15:08.426966: +2024-11-22 00:15:08.427220: Epoch 2432 +2024-11-22 00:15:08.427340: Current learning rate: 0.00722 +2024-11-22 00:15:28.194643: train_loss -0.7648 +2024-11-22 00:15:28.198592: val_loss -0.7489 +2024-11-22 00:15:28.198748: Pseudo dice [0.8397] +2024-11-22 00:15:28.198844: Epoch time: 19.77 s +2024-11-22 00:15:29.029528: +2024-11-22 00:15:29.029749: Epoch 2433 +2024-11-22 00:15:29.029865: Current learning rate: 0.00722 +2024-11-22 00:15:47.218108: train_loss -0.7807 +2024-11-22 00:15:47.231460: val_loss -0.7607 +2024-11-22 00:15:47.231610: Pseudo dice [0.8558] +2024-11-22 00:15:47.231796: Epoch time: 18.19 s +2024-11-22 00:15:48.211993: +2024-11-22 00:15:48.212252: Epoch 2434 +2024-11-22 00:15:48.212386: Current learning rate: 0.00721 +2024-11-22 00:16:07.763187: train_loss -0.7712 +2024-11-22 00:16:07.766282: val_loss -0.7711 +2024-11-22 00:16:07.766431: Pseudo dice [0.848] +2024-11-22 00:16:07.766516: Epoch time: 19.55 s +2024-11-22 00:16:09.016816: +2024-11-22 00:16:09.017034: Epoch 2435 +2024-11-22 00:16:09.017156: Current learning rate: 0.00721 +2024-11-22 00:16:27.104178: train_loss -0.7681 +2024-11-22 00:16:27.114573: val_loss -0.7573 +2024-11-22 00:16:27.114760: Pseudo dice [0.8517] +2024-11-22 00:16:27.114861: Epoch time: 18.09 s +2024-11-22 00:16:28.121315: +2024-11-22 00:16:28.121552: Epoch 2436 +2024-11-22 00:16:28.121678: Current learning rate: 0.00721 +2024-11-22 00:16:47.318879: train_loss -0.7804 +2024-11-22 00:16:47.357289: val_loss -0.7587 +2024-11-22 00:16:47.357433: Pseudo dice [0.8319] +2024-11-22 00:16:47.357515: Epoch time: 19.2 s +2024-11-22 00:16:48.277055: +2024-11-22 00:16:48.277301: Epoch 2437 +2024-11-22 00:16:48.277428: Current learning rate: 0.00721 +2024-11-22 00:17:07.191017: train_loss -0.7618 +2024-11-22 00:17:07.203360: val_loss -0.7543 +2024-11-22 00:17:07.203548: Pseudo dice [0.8427] +2024-11-22 00:17:07.203639: Epoch time: 18.91 s +2024-11-22 00:17:08.069816: +2024-11-22 00:17:08.070029: Epoch 2438 +2024-11-22 00:17:08.070163: Current learning rate: 0.00721 +2024-11-22 00:17:26.631007: train_loss -0.7794 +2024-11-22 00:17:26.636716: val_loss -0.7838 +2024-11-22 00:17:26.636913: Pseudo dice [0.8479] +2024-11-22 00:17:26.637013: Epoch time: 18.56 s +2024-11-22 00:17:27.489553: +2024-11-22 00:17:27.489769: Epoch 2439 +2024-11-22 00:17:27.489895: Current learning rate: 0.00721 +2024-11-22 00:17:47.606028: train_loss -0.7773 +2024-11-22 00:17:47.610832: val_loss -0.7742 +2024-11-22 00:17:47.610963: Pseudo dice [0.8461] +2024-11-22 00:17:47.611057: Epoch time: 20.12 s +2024-11-22 00:17:48.510448: +2024-11-22 00:17:48.510696: Epoch 2440 +2024-11-22 00:17:48.510850: Current learning rate: 0.00721 +2024-11-22 00:18:07.821798: train_loss -0.777 +2024-11-22 00:18:07.830891: val_loss -0.7768 +2024-11-22 00:18:07.831031: Pseudo dice [0.8363] +2024-11-22 00:18:07.831128: Epoch time: 19.31 s +2024-11-22 00:18:08.667282: +2024-11-22 00:18:08.667537: Epoch 2441 +2024-11-22 00:18:08.667656: Current learning rate: 0.00721 +2024-11-22 00:18:29.027307: train_loss -0.7671 +2024-11-22 00:18:29.044266: val_loss -0.7823 +2024-11-22 00:18:29.044487: Pseudo dice [0.851] +2024-11-22 00:18:29.044587: Epoch time: 20.36 s +2024-11-22 00:18:29.874975: +2024-11-22 00:18:29.875193: Epoch 2442 +2024-11-22 00:18:29.875314: Current learning rate: 0.00721 +2024-11-22 00:18:47.515803: train_loss -0.7672 +2024-11-22 00:18:47.541812: val_loss -0.7665 +2024-11-22 00:18:47.541991: Pseudo dice [0.8481] +2024-11-22 00:18:47.542111: Epoch time: 17.64 s +2024-11-22 00:18:48.547287: +2024-11-22 00:18:48.547556: Epoch 2443 +2024-11-22 00:18:48.547678: Current learning rate: 0.0072 +2024-11-22 00:19:07.880131: train_loss -0.7773 +2024-11-22 00:19:07.886865: val_loss -0.7615 +2024-11-22 00:19:07.887006: Pseudo dice [0.8464] +2024-11-22 00:19:07.887093: Epoch time: 19.33 s +2024-11-22 00:19:08.842164: +2024-11-22 00:19:08.842361: Epoch 2444 +2024-11-22 00:19:08.842488: Current learning rate: 0.0072 +2024-11-22 00:19:27.833574: train_loss -0.7681 +2024-11-22 00:19:27.836418: val_loss -0.7528 +2024-11-22 00:19:27.836564: Pseudo dice [0.8404] +2024-11-22 00:19:27.836908: Epoch time: 18.99 s +2024-11-22 00:19:28.712572: +2024-11-22 00:19:28.712772: Epoch 2445 +2024-11-22 00:19:28.712899: Current learning rate: 0.0072 +2024-11-22 00:19:48.483170: train_loss -0.7722 +2024-11-22 00:19:48.485441: val_loss -0.7686 +2024-11-22 00:19:48.485549: Pseudo dice [0.8516] +2024-11-22 00:19:48.485643: Epoch time: 19.77 s +2024-11-22 00:19:49.301064: +2024-11-22 00:19:49.301294: Epoch 2446 +2024-11-22 00:19:49.301426: Current learning rate: 0.0072 +2024-11-22 00:20:07.481733: train_loss -0.77 +2024-11-22 00:20:07.484426: val_loss -0.7553 +2024-11-22 00:20:07.484549: Pseudo dice [0.8423] +2024-11-22 00:20:07.484665: Epoch time: 18.18 s +2024-11-22 00:20:08.724253: +2024-11-22 00:20:08.724465: Epoch 2447 +2024-11-22 00:20:08.724611: Current learning rate: 0.0072 +2024-11-22 00:20:27.773969: train_loss -0.7782 +2024-11-22 00:20:27.780673: val_loss -0.7496 +2024-11-22 00:20:27.780818: Pseudo dice [0.8253] +2024-11-22 00:20:27.780909: Epoch time: 19.05 s +2024-11-22 00:20:28.623340: +2024-11-22 00:20:28.623545: Epoch 2448 +2024-11-22 00:20:28.623666: Current learning rate: 0.0072 +2024-11-22 00:20:47.519639: train_loss -0.7766 +2024-11-22 00:20:47.521786: val_loss -0.7912 +2024-11-22 00:20:47.521890: Pseudo dice [0.8567] +2024-11-22 00:20:47.521998: Epoch time: 18.9 s +2024-11-22 00:20:48.403202: +2024-11-22 00:20:48.403441: Epoch 2449 +2024-11-22 00:20:48.403574: Current learning rate: 0.0072 +2024-11-22 00:21:07.714962: train_loss -0.7715 +2024-11-22 00:21:07.721403: val_loss -0.7486 +2024-11-22 00:21:07.721541: Pseudo dice [0.8539] +2024-11-22 00:21:07.721644: Epoch time: 19.31 s +2024-11-22 00:21:08.793716: +2024-11-22 00:21:08.793983: Epoch 2450 +2024-11-22 00:21:08.794112: Current learning rate: 0.0072 +2024-11-22 00:21:28.121784: train_loss -0.7812 +2024-11-22 00:21:28.124419: val_loss -0.737 +2024-11-22 00:21:28.124587: Pseudo dice [0.8552] +2024-11-22 00:21:28.124728: Epoch time: 19.33 s +2024-11-22 00:21:29.044683: +2024-11-22 00:21:29.044902: Epoch 2451 +2024-11-22 00:21:29.045020: Current learning rate: 0.00719 +2024-11-22 00:21:48.459581: train_loss -0.7755 +2024-11-22 00:21:48.465294: val_loss -0.7416 +2024-11-22 00:21:48.465421: Pseudo dice [0.8365] +2024-11-22 00:21:48.465511: Epoch time: 19.42 s +2024-11-22 00:21:49.320187: +2024-11-22 00:21:49.320410: Epoch 2452 +2024-11-22 00:21:49.320531: Current learning rate: 0.00719 +2024-11-22 00:22:08.579268: train_loss -0.7731 +2024-11-22 00:22:08.583519: val_loss -0.7803 +2024-11-22 00:22:08.583637: Pseudo dice [0.8398] +2024-11-22 00:22:08.583718: Epoch time: 19.26 s +2024-11-22 00:22:09.610781: +2024-11-22 00:22:09.611004: Epoch 2453 +2024-11-22 00:22:09.611146: Current learning rate: 0.00719 +2024-11-22 00:22:29.351034: train_loss -0.7686 +2024-11-22 00:22:29.359019: val_loss -0.7606 +2024-11-22 00:22:29.359174: Pseudo dice [0.849] +2024-11-22 00:22:29.359281: Epoch time: 19.74 s +2024-11-22 00:22:30.268147: +2024-11-22 00:22:30.268371: Epoch 2454 +2024-11-22 00:22:30.268499: Current learning rate: 0.00719 +2024-11-22 00:22:49.963728: train_loss -0.7659 +2024-11-22 00:22:49.979378: val_loss -0.7549 +2024-11-22 00:22:49.979549: Pseudo dice [0.8346] +2024-11-22 00:22:49.979664: Epoch time: 19.7 s +2024-11-22 00:22:50.893050: +2024-11-22 00:22:50.893255: Epoch 2455 +2024-11-22 00:22:50.893381: Current learning rate: 0.00719 +2024-11-22 00:23:09.640295: train_loss -0.7685 +2024-11-22 00:23:09.657424: val_loss -0.7617 +2024-11-22 00:23:09.657568: Pseudo dice [0.8527] +2024-11-22 00:23:09.657666: Epoch time: 18.75 s +2024-11-22 00:23:10.612762: +2024-11-22 00:23:10.613000: Epoch 2456 +2024-11-22 00:23:10.613123: Current learning rate: 0.00719 +2024-11-22 00:23:29.409431: train_loss -0.7802 +2024-11-22 00:23:29.415464: val_loss -0.7405 +2024-11-22 00:23:29.415586: Pseudo dice [0.8497] +2024-11-22 00:23:29.415686: Epoch time: 18.8 s +2024-11-22 00:23:30.433828: +2024-11-22 00:23:30.434057: Epoch 2457 +2024-11-22 00:23:30.434176: Current learning rate: 0.00719 +2024-11-22 00:23:48.538216: train_loss -0.7782 +2024-11-22 00:23:48.546684: val_loss -0.7861 +2024-11-22 00:23:48.546827: Pseudo dice [0.8543] +2024-11-22 00:23:48.546927: Epoch time: 18.11 s +2024-11-22 00:23:49.481141: +2024-11-22 00:23:49.481343: Epoch 2458 +2024-11-22 00:23:49.481480: Current learning rate: 0.00719 +2024-11-22 00:24:08.317903: train_loss -0.7728 +2024-11-22 00:24:08.320381: val_loss -0.7849 +2024-11-22 00:24:08.320533: Pseudo dice [0.8557] +2024-11-22 00:24:08.320645: Epoch time: 18.84 s +2024-11-22 00:24:09.146302: +2024-11-22 00:24:09.146514: Epoch 2459 +2024-11-22 00:24:09.146649: Current learning rate: 0.00719 +2024-11-22 00:24:28.811330: train_loss -0.7757 +2024-11-22 00:24:28.819609: val_loss -0.7474 +2024-11-22 00:24:28.819769: Pseudo dice [0.8409] +2024-11-22 00:24:28.819944: Epoch time: 19.67 s +2024-11-22 00:24:29.649735: +2024-11-22 00:24:29.649948: Epoch 2460 +2024-11-22 00:24:29.650078: Current learning rate: 0.00718 +2024-11-22 00:24:48.647225: train_loss -0.7706 +2024-11-22 00:24:48.668715: val_loss -0.7717 +2024-11-22 00:24:48.668856: Pseudo dice [0.8563] +2024-11-22 00:24:48.668944: Epoch time: 19.0 s +2024-11-22 00:24:49.592805: +2024-11-22 00:24:49.593073: Epoch 2461 +2024-11-22 00:24:49.593211: Current learning rate: 0.00718 +2024-11-22 00:25:08.772847: train_loss -0.7584 +2024-11-22 00:25:08.779534: val_loss -0.7747 +2024-11-22 00:25:08.779658: Pseudo dice [0.8546] +2024-11-22 00:25:08.779745: Epoch time: 19.18 s +2024-11-22 00:25:09.616938: +2024-11-22 00:25:09.617149: Epoch 2462 +2024-11-22 00:25:09.617269: Current learning rate: 0.00718 +2024-11-22 00:25:28.283828: train_loss -0.7663 +2024-11-22 00:25:28.290415: val_loss -0.7704 +2024-11-22 00:25:28.290562: Pseudo dice [0.8482] +2024-11-22 00:25:28.290660: Epoch time: 18.66 s +2024-11-22 00:25:29.434037: +2024-11-22 00:25:29.434284: Epoch 2463 +2024-11-22 00:25:29.434402: Current learning rate: 0.00718 +2024-11-22 00:25:49.068407: train_loss -0.759 +2024-11-22 00:25:49.072944: val_loss -0.7801 +2024-11-22 00:25:49.073053: Pseudo dice [0.8466] +2024-11-22 00:25:49.073171: Epoch time: 19.64 s +2024-11-22 00:25:49.903975: +2024-11-22 00:25:49.904224: Epoch 2464 +2024-11-22 00:25:49.904368: Current learning rate: 0.00718 +2024-11-22 00:26:09.094427: train_loss -0.7618 +2024-11-22 00:26:09.099442: val_loss -0.769 +2024-11-22 00:26:09.099570: Pseudo dice [0.8549] +2024-11-22 00:26:09.099675: Epoch time: 19.19 s +2024-11-22 00:26:09.944214: +2024-11-22 00:26:09.944448: Epoch 2465 +2024-11-22 00:26:09.944566: Current learning rate: 0.00718 +2024-11-22 00:26:28.524362: train_loss -0.7598 +2024-11-22 00:26:28.530681: val_loss -0.7505 +2024-11-22 00:26:28.530869: Pseudo dice [0.8503] +2024-11-22 00:26:28.530989: Epoch time: 18.58 s +2024-11-22 00:26:29.365776: +2024-11-22 00:26:29.365986: Epoch 2466 +2024-11-22 00:26:29.366119: Current learning rate: 0.00718 +2024-11-22 00:26:48.780287: train_loss -0.7714 +2024-11-22 00:26:48.785975: val_loss -0.7726 +2024-11-22 00:26:48.786126: Pseudo dice [0.852] +2024-11-22 00:26:48.786221: Epoch time: 19.42 s +2024-11-22 00:26:49.605452: +2024-11-22 00:26:49.605658: Epoch 2467 +2024-11-22 00:26:49.605782: Current learning rate: 0.00718 +2024-11-22 00:27:08.296660: train_loss -0.7706 +2024-11-22 00:27:08.302753: val_loss -0.7443 +2024-11-22 00:27:08.302936: Pseudo dice [0.8489] +2024-11-22 00:27:08.303052: Epoch time: 18.69 s +2024-11-22 00:27:09.193270: +2024-11-22 00:27:09.193509: Epoch 2468 +2024-11-22 00:27:09.193628: Current learning rate: 0.00717 +2024-11-22 00:27:28.808944: train_loss -0.7682 +2024-11-22 00:27:28.816722: val_loss -0.7802 +2024-11-22 00:27:28.816871: Pseudo dice [0.8435] +2024-11-22 00:27:28.816974: Epoch time: 19.62 s +2024-11-22 00:27:29.657967: +2024-11-22 00:27:29.658175: Epoch 2469 +2024-11-22 00:27:29.658295: Current learning rate: 0.00717 +2024-11-22 00:27:47.846104: train_loss -0.7756 +2024-11-22 00:27:47.853913: val_loss -0.7612 +2024-11-22 00:27:47.854042: Pseudo dice [0.8468] +2024-11-22 00:27:47.854149: Epoch time: 18.19 s +2024-11-22 00:27:49.272762: +2024-11-22 00:27:49.272973: Epoch 2470 +2024-11-22 00:27:49.273103: Current learning rate: 0.00717 +2024-11-22 00:28:07.739099: train_loss -0.7652 +2024-11-22 00:28:07.745309: val_loss -0.7704 +2024-11-22 00:28:07.745775: Pseudo dice [0.8517] +2024-11-22 00:28:07.745930: Epoch time: 18.47 s +2024-11-22 00:28:08.598979: +2024-11-22 00:28:08.599220: Epoch 2471 +2024-11-22 00:28:08.599356: Current learning rate: 0.00717 +2024-11-22 00:28:27.581537: train_loss -0.77 +2024-11-22 00:28:27.586940: val_loss -0.732 +2024-11-22 00:28:27.587081: Pseudo dice [0.8396] +2024-11-22 00:28:27.587229: Epoch time: 18.98 s +2024-11-22 00:28:28.547686: +2024-11-22 00:28:28.547898: Epoch 2472 +2024-11-22 00:28:28.548016: Current learning rate: 0.00717 +2024-11-22 00:28:47.171978: train_loss -0.7751 +2024-11-22 00:28:47.178576: val_loss -0.7485 +2024-11-22 00:28:47.178721: Pseudo dice [0.8514] +2024-11-22 00:28:47.178816: Epoch time: 18.63 s +2024-11-22 00:28:48.238723: +2024-11-22 00:28:48.238934: Epoch 2473 +2024-11-22 00:28:48.239056: Current learning rate: 0.00717 +2024-11-22 00:29:07.222423: train_loss -0.7755 +2024-11-22 00:29:07.228611: val_loss -0.7808 +2024-11-22 00:29:07.228951: Pseudo dice [0.8436] +2024-11-22 00:29:07.229047: Epoch time: 18.98 s +2024-11-22 00:29:08.165873: +2024-11-22 00:29:08.166104: Epoch 2474 +2024-11-22 00:29:08.166218: Current learning rate: 0.00717 +2024-11-22 00:29:27.603178: train_loss -0.7649 +2024-11-22 00:29:27.610572: val_loss -0.7524 +2024-11-22 00:29:27.610687: Pseudo dice [0.8417] +2024-11-22 00:29:27.610774: Epoch time: 19.44 s +2024-11-22 00:29:28.557074: +2024-11-22 00:29:28.557315: Epoch 2475 +2024-11-22 00:29:28.557451: Current learning rate: 0.00717 +2024-11-22 00:29:47.077739: train_loss -0.7867 +2024-11-22 00:29:47.084563: val_loss -0.7793 +2024-11-22 00:29:47.084787: Pseudo dice [0.8472] +2024-11-22 00:29:47.084888: Epoch time: 18.52 s +2024-11-22 00:29:47.924322: +2024-11-22 00:29:47.924534: Epoch 2476 +2024-11-22 00:29:47.924646: Current learning rate: 0.00717 +2024-11-22 00:30:08.086280: train_loss -0.7717 +2024-11-22 00:30:08.093973: val_loss -0.7668 +2024-11-22 00:30:08.094115: Pseudo dice [0.8472] +2024-11-22 00:30:08.094221: Epoch time: 20.16 s +2024-11-22 00:30:08.915196: +2024-11-22 00:30:08.915395: Epoch 2477 +2024-11-22 00:30:08.915533: Current learning rate: 0.00716 +2024-11-22 00:30:28.912112: train_loss -0.7798 +2024-11-22 00:30:28.917316: val_loss -0.7936 +2024-11-22 00:30:28.917463: Pseudo dice [0.8553] +2024-11-22 00:30:28.917558: Epoch time: 20.0 s +2024-11-22 00:30:29.855923: +2024-11-22 00:30:29.856158: Epoch 2478 +2024-11-22 00:30:29.856295: Current learning rate: 0.00716 +2024-11-22 00:30:49.644408: train_loss -0.7813 +2024-11-22 00:30:49.652201: val_loss -0.7737 +2024-11-22 00:30:49.652344: Pseudo dice [0.8618] +2024-11-22 00:30:49.652433: Epoch time: 19.79 s +2024-11-22 00:30:50.718879: +2024-11-22 00:30:50.719127: Epoch 2479 +2024-11-22 00:30:50.719258: Current learning rate: 0.00716 +2024-11-22 00:31:09.657978: train_loss -0.7819 +2024-11-22 00:31:09.661872: val_loss -0.758 +2024-11-22 00:31:09.662015: Pseudo dice [0.8438] +2024-11-22 00:31:09.662106: Epoch time: 18.94 s +2024-11-22 00:31:10.490071: +2024-11-22 00:31:10.490286: Epoch 2480 +2024-11-22 00:31:10.490396: Current learning rate: 0.00716 +2024-11-22 00:31:29.456476: train_loss -0.7785 +2024-11-22 00:31:29.459900: val_loss -0.7656 +2024-11-22 00:31:29.460043: Pseudo dice [0.8504] +2024-11-22 00:31:29.460144: Epoch time: 18.97 s +2024-11-22 00:31:30.411528: +2024-11-22 00:31:30.411726: Epoch 2481 +2024-11-22 00:31:30.411840: Current learning rate: 0.00716 +2024-11-22 00:31:50.286186: train_loss -0.7772 +2024-11-22 00:31:50.301982: val_loss -0.7878 +2024-11-22 00:31:50.302124: Pseudo dice [0.8597] +2024-11-22 00:31:50.302220: Epoch time: 19.88 s +2024-11-22 00:31:51.515733: +2024-11-22 00:31:51.515952: Epoch 2482 +2024-11-22 00:31:51.516099: Current learning rate: 0.00716 +2024-11-22 00:32:11.544391: train_loss -0.778 +2024-11-22 00:32:11.547300: val_loss -0.7641 +2024-11-22 00:32:11.547429: Pseudo dice [0.85] +2024-11-22 00:32:11.547532: Epoch time: 20.03 s +2024-11-22 00:32:12.366129: +2024-11-22 00:32:12.366333: Epoch 2483 +2024-11-22 00:32:12.366452: Current learning rate: 0.00716 +2024-11-22 00:32:30.544276: train_loss -0.7835 +2024-11-22 00:32:30.549484: val_loss -0.7718 +2024-11-22 00:32:30.549628: Pseudo dice [0.8555] +2024-11-22 00:32:30.549717: Epoch time: 18.18 s +2024-11-22 00:32:31.365621: +2024-11-22 00:32:31.365840: Epoch 2484 +2024-11-22 00:32:31.365956: Current learning rate: 0.00716 +2024-11-22 00:32:50.116597: train_loss -0.778 +2024-11-22 00:32:50.123950: val_loss -0.7624 +2024-11-22 00:32:50.124088: Pseudo dice [0.8457] +2024-11-22 00:32:50.124179: Epoch time: 18.75 s +2024-11-22 00:32:51.035513: +2024-11-22 00:32:51.035751: Epoch 2485 +2024-11-22 00:32:51.035873: Current learning rate: 0.00716 +2024-11-22 00:33:11.076302: train_loss -0.765 +2024-11-22 00:33:11.089757: val_loss -0.742 +2024-11-22 00:33:11.089894: Pseudo dice [0.8476] +2024-11-22 00:33:11.089991: Epoch time: 20.04 s +2024-11-22 00:33:11.928055: +2024-11-22 00:33:11.928269: Epoch 2486 +2024-11-22 00:33:11.928415: Current learning rate: 0.00715 +2024-11-22 00:33:31.072819: train_loss -0.7748 +2024-11-22 00:33:31.075103: val_loss -0.7659 +2024-11-22 00:33:31.075209: Pseudo dice [0.8583] +2024-11-22 00:33:31.075296: Epoch time: 19.15 s +2024-11-22 00:33:31.898781: +2024-11-22 00:33:31.898987: Epoch 2487 +2024-11-22 00:33:31.899109: Current learning rate: 0.00715 +2024-11-22 00:33:51.104260: train_loss -0.7672 +2024-11-22 00:33:51.106823: val_loss -0.7457 +2024-11-22 00:33:51.106961: Pseudo dice [0.8517] +2024-11-22 00:33:51.107052: Epoch time: 19.21 s +2024-11-22 00:33:51.927138: +2024-11-22 00:33:51.927347: Epoch 2488 +2024-11-22 00:33:51.927491: Current learning rate: 0.00715 +2024-11-22 00:34:10.120983: train_loss -0.7709 +2024-11-22 00:34:10.127452: val_loss -0.7712 +2024-11-22 00:34:10.127559: Pseudo dice [0.8448] +2024-11-22 00:34:10.127654: Epoch time: 18.19 s +2024-11-22 00:34:11.072669: +2024-11-22 00:34:11.072902: Epoch 2489 +2024-11-22 00:34:11.073029: Current learning rate: 0.00715 +2024-11-22 00:34:30.535862: train_loss -0.7673 +2024-11-22 00:34:30.541081: val_loss -0.7618 +2024-11-22 00:34:30.541221: Pseudo dice [0.8416] +2024-11-22 00:34:30.541367: Epoch time: 19.46 s +2024-11-22 00:34:31.364310: +2024-11-22 00:34:31.364519: Epoch 2490 +2024-11-22 00:34:31.364640: Current learning rate: 0.00715 +2024-11-22 00:34:51.237814: train_loss -0.7623 +2024-11-22 00:34:51.245365: val_loss -0.7774 +2024-11-22 00:34:51.245704: Pseudo dice [0.8449] +2024-11-22 00:34:51.246016: Epoch time: 19.87 s +2024-11-22 00:34:52.079450: +2024-11-22 00:34:52.079693: Epoch 2491 +2024-11-22 00:34:52.079818: Current learning rate: 0.00715 +2024-11-22 00:35:10.665021: train_loss -0.7777 +2024-11-22 00:35:10.671410: val_loss -0.7537 +2024-11-22 00:35:10.671543: Pseudo dice [0.8458] +2024-11-22 00:35:10.671648: Epoch time: 18.59 s +2024-11-22 00:35:11.584090: +2024-11-22 00:35:11.584299: Epoch 2492 +2024-11-22 00:35:11.584421: Current learning rate: 0.00715 +2024-11-22 00:35:29.705129: train_loss -0.7715 +2024-11-22 00:35:29.718926: val_loss -0.738 +2024-11-22 00:35:29.719068: Pseudo dice [0.8495] +2024-11-22 00:35:29.719160: Epoch time: 18.12 s +2024-11-22 00:35:30.760317: +2024-11-22 00:35:30.760548: Epoch 2493 +2024-11-22 00:35:30.760674: Current learning rate: 0.00715 +2024-11-22 00:35:50.032610: train_loss -0.7736 +2024-11-22 00:35:50.046057: val_loss -0.7684 +2024-11-22 00:35:50.046207: Pseudo dice [0.8438] +2024-11-22 00:35:50.046312: Epoch time: 19.27 s +2024-11-22 00:35:51.499414: +2024-11-22 00:35:51.499645: Epoch 2494 +2024-11-22 00:35:51.499780: Current learning rate: 0.00714 +2024-11-22 00:36:09.866501: train_loss -0.7396 +2024-11-22 00:36:09.869145: val_loss -0.7469 +2024-11-22 00:36:09.869340: Pseudo dice [0.8318] +2024-11-22 00:36:09.869448: Epoch time: 18.37 s +2024-11-22 00:36:10.759927: +2024-11-22 00:36:10.760384: Epoch 2495 +2024-11-22 00:36:10.760628: Current learning rate: 0.00714 +2024-11-22 00:36:29.517023: train_loss -0.7552 +2024-11-22 00:36:29.521555: val_loss -0.7564 +2024-11-22 00:36:29.521682: Pseudo dice [0.8579] +2024-11-22 00:36:29.521882: Epoch time: 18.76 s +2024-11-22 00:36:30.508559: +2024-11-22 00:36:30.508779: Epoch 2496 +2024-11-22 00:36:30.508894: Current learning rate: 0.00714 +2024-11-22 00:36:50.121151: train_loss -0.7669 +2024-11-22 00:36:50.128682: val_loss -0.7811 +2024-11-22 00:36:50.129163: Pseudo dice [0.8408] +2024-11-22 00:36:50.129274: Epoch time: 19.61 s +2024-11-22 00:36:50.975712: +2024-11-22 00:36:50.975947: Epoch 2497 +2024-11-22 00:36:50.976080: Current learning rate: 0.00714 +2024-11-22 00:37:09.191150: train_loss -0.7465 +2024-11-22 00:37:09.196314: val_loss -0.7311 +2024-11-22 00:37:09.196465: Pseudo dice [0.8348] +2024-11-22 00:37:09.196559: Epoch time: 18.22 s +2024-11-22 00:37:10.083237: +2024-11-22 00:37:10.083423: Epoch 2498 +2024-11-22 00:37:10.083541: Current learning rate: 0.00714 +2024-11-22 00:37:29.160827: train_loss -0.7412 +2024-11-22 00:37:29.167405: val_loss -0.7648 +2024-11-22 00:37:29.167592: Pseudo dice [0.8421] +2024-11-22 00:37:29.167694: Epoch time: 19.08 s +2024-11-22 00:37:30.108958: +2024-11-22 00:37:30.113617: Epoch 2499 +2024-11-22 00:37:30.113751: Current learning rate: 0.00714 +2024-11-22 00:37:50.292125: train_loss -0.7575 +2024-11-22 00:37:50.299226: val_loss -0.7729 +2024-11-22 00:37:50.299356: Pseudo dice [0.8401] +2024-11-22 00:37:50.299471: Epoch time: 20.18 s +2024-11-22 00:37:51.415555: +2024-11-22 00:37:51.415770: Epoch 2500 +2024-11-22 00:37:51.415891: Current learning rate: 0.00714 +2024-11-22 00:38:10.146486: train_loss -0.7663 +2024-11-22 00:38:10.149119: val_loss -0.7552 +2024-11-22 00:38:10.149243: Pseudo dice [0.8473] +2024-11-22 00:38:10.149337: Epoch time: 18.73 s +2024-11-22 00:38:11.141972: +2024-11-22 00:38:11.142182: Epoch 2501 +2024-11-22 00:38:11.142296: Current learning rate: 0.00714 +2024-11-22 00:38:29.476633: train_loss -0.7619 +2024-11-22 00:38:29.479206: val_loss -0.7792 +2024-11-22 00:38:29.479311: Pseudo dice [0.8465] +2024-11-22 00:38:29.479418: Epoch time: 18.34 s +2024-11-22 00:38:30.295541: +2024-11-22 00:38:30.295764: Epoch 2502 +2024-11-22 00:38:30.295916: Current learning rate: 0.00714 +2024-11-22 00:38:50.200255: train_loss -0.7772 +2024-11-22 00:38:50.207042: val_loss -0.7464 +2024-11-22 00:38:50.207474: Pseudo dice [0.8433] +2024-11-22 00:38:50.207602: Epoch time: 19.91 s +2024-11-22 00:38:51.046473: +2024-11-22 00:38:51.046701: Epoch 2503 +2024-11-22 00:38:51.046822: Current learning rate: 0.00713 +2024-11-22 00:39:08.705863: train_loss -0.7619 +2024-11-22 00:39:08.712229: val_loss -0.7499 +2024-11-22 00:39:08.712354: Pseudo dice [0.8476] +2024-11-22 00:39:08.712451: Epoch time: 17.66 s +2024-11-22 00:39:09.565413: +2024-11-22 00:39:09.565618: Epoch 2504 +2024-11-22 00:39:09.565737: Current learning rate: 0.00713 +2024-11-22 00:39:27.831254: train_loss -0.7726 +2024-11-22 00:39:27.839034: val_loss -0.759 +2024-11-22 00:39:27.839182: Pseudo dice [0.8408] +2024-11-22 00:39:27.839295: Epoch time: 18.27 s +2024-11-22 00:39:28.761844: +2024-11-22 00:39:28.762121: Epoch 2505 +2024-11-22 00:39:28.762250: Current learning rate: 0.00713 +2024-11-22 00:39:47.564344: train_loss -0.7658 +2024-11-22 00:39:47.578183: val_loss -0.7744 +2024-11-22 00:39:47.578571: Pseudo dice [0.8411] +2024-11-22 00:39:47.578668: Epoch time: 18.8 s +2024-11-22 00:39:48.504989: +2024-11-22 00:39:48.505193: Epoch 2506 +2024-11-22 00:39:48.505305: Current learning rate: 0.00713 +2024-11-22 00:40:08.331393: train_loss -0.7707 +2024-11-22 00:40:08.337105: val_loss -0.7685 +2024-11-22 00:40:08.337237: Pseudo dice [0.8443] +2024-11-22 00:40:08.337336: Epoch time: 19.83 s +2024-11-22 00:40:09.176720: +2024-11-22 00:40:09.176947: Epoch 2507 +2024-11-22 00:40:09.177101: Current learning rate: 0.00713 +2024-11-22 00:40:27.734320: train_loss -0.7813 +2024-11-22 00:40:27.749577: val_loss -0.7622 +2024-11-22 00:40:27.749742: Pseudo dice [0.8412] +2024-11-22 00:40:27.749900: Epoch time: 18.55 s +2024-11-22 00:40:28.658783: +2024-11-22 00:40:28.659007: Epoch 2508 +2024-11-22 00:40:28.659130: Current learning rate: 0.00713 +2024-11-22 00:40:48.032796: train_loss -0.779 +2024-11-22 00:40:48.036525: val_loss -0.7683 +2024-11-22 00:40:48.036673: Pseudo dice [0.8504] +2024-11-22 00:40:48.036763: Epoch time: 19.37 s +2024-11-22 00:40:48.987082: +2024-11-22 00:40:48.987298: Epoch 2509 +2024-11-22 00:40:48.987412: Current learning rate: 0.00713 +2024-11-22 00:41:07.887427: train_loss -0.7744 +2024-11-22 00:41:07.899835: val_loss -0.7898 +2024-11-22 00:41:07.899961: Pseudo dice [0.868] +2024-11-22 00:41:07.900065: Epoch time: 18.9 s +2024-11-22 00:41:08.895567: +2024-11-22 00:41:08.895772: Epoch 2510 +2024-11-22 00:41:08.895897: Current learning rate: 0.00713 +2024-11-22 00:41:29.025658: train_loss -0.7699 +2024-11-22 00:41:29.027871: val_loss -0.7719 +2024-11-22 00:41:29.027968: Pseudo dice [0.8483] +2024-11-22 00:41:29.028072: Epoch time: 20.13 s +2024-11-22 00:41:29.851320: +2024-11-22 00:41:29.851520: Epoch 2511 +2024-11-22 00:41:29.851664: Current learning rate: 0.00712 +2024-11-22 00:41:48.968868: train_loss -0.7661 +2024-11-22 00:41:48.983906: val_loss -0.7677 +2024-11-22 00:41:48.984077: Pseudo dice [0.8383] +2024-11-22 00:41:48.999354: Epoch time: 19.12 s +2024-11-22 00:41:49.822321: +2024-11-22 00:41:49.822519: Epoch 2512 +2024-11-22 00:41:49.822637: Current learning rate: 0.00712 +2024-11-22 00:42:08.702780: train_loss -0.7704 +2024-11-22 00:42:08.709965: val_loss -0.7394 +2024-11-22 00:42:08.710139: Pseudo dice [0.8437] +2024-11-22 00:42:08.710253: Epoch time: 18.88 s +2024-11-22 00:42:09.566233: +2024-11-22 00:42:09.566469: Epoch 2513 +2024-11-22 00:42:09.566634: Current learning rate: 0.00712 +2024-11-22 00:42:27.685452: train_loss -0.7621 +2024-11-22 00:42:27.691618: val_loss -0.7601 +2024-11-22 00:42:27.691747: Pseudo dice [0.8418] +2024-11-22 00:42:27.691853: Epoch time: 18.12 s +2024-11-22 00:42:28.658216: +2024-11-22 00:42:28.658447: Epoch 2514 +2024-11-22 00:42:28.658574: Current learning rate: 0.00712 +2024-11-22 00:42:48.108615: train_loss -0.7647 +2024-11-22 00:42:48.117346: val_loss -0.7733 +2024-11-22 00:42:48.117543: Pseudo dice [0.8561] +2024-11-22 00:42:48.120492: Epoch time: 19.45 s +2024-11-22 00:42:49.192036: +2024-11-22 00:42:49.192246: Epoch 2515 +2024-11-22 00:42:49.192370: Current learning rate: 0.00712 +2024-11-22 00:43:08.125672: train_loss -0.7461 +2024-11-22 00:43:08.131781: val_loss -0.747 +2024-11-22 00:43:08.131918: Pseudo dice [0.8442] +2024-11-22 00:43:08.132010: Epoch time: 18.93 s +2024-11-22 00:43:08.958973: +2024-11-22 00:43:08.959204: Epoch 2516 +2024-11-22 00:43:08.959320: Current learning rate: 0.00712 +2024-11-22 00:43:27.269245: train_loss -0.7546 +2024-11-22 00:43:27.277018: val_loss -0.7698 +2024-11-22 00:43:27.277148: Pseudo dice [0.8431] +2024-11-22 00:43:27.277240: Epoch time: 18.31 s +2024-11-22 00:43:28.660214: +2024-11-22 00:43:28.660421: Epoch 2517 +2024-11-22 00:43:28.660535: Current learning rate: 0.00712 +2024-11-22 00:43:48.895323: train_loss -0.7661 +2024-11-22 00:43:48.902751: val_loss -0.7701 +2024-11-22 00:43:48.902895: Pseudo dice [0.8468] +2024-11-22 00:43:48.903015: Epoch time: 20.24 s +2024-11-22 00:43:49.732016: +2024-11-22 00:43:49.732359: Epoch 2518 +2024-11-22 00:43:49.732493: Current learning rate: 0.00712 +2024-11-22 00:44:10.403124: train_loss -0.7556 +2024-11-22 00:44:10.408751: val_loss -0.7692 +2024-11-22 00:44:10.408909: Pseudo dice [0.8497] +2024-11-22 00:44:10.408997: Epoch time: 20.67 s +2024-11-22 00:44:11.292912: +2024-11-22 00:44:11.293126: Epoch 2519 +2024-11-22 00:44:11.293261: Current learning rate: 0.00712 +2024-11-22 00:44:30.697235: train_loss -0.7748 +2024-11-22 00:44:30.705737: val_loss -0.7641 +2024-11-22 00:44:30.705860: Pseudo dice [0.8504] +2024-11-22 00:44:30.705956: Epoch time: 19.41 s +2024-11-22 00:44:31.532071: +2024-11-22 00:44:31.532305: Epoch 2520 +2024-11-22 00:44:31.532435: Current learning rate: 0.00711 +2024-11-22 00:44:50.275417: train_loss -0.7748 +2024-11-22 00:44:50.278671: val_loss -0.7711 +2024-11-22 00:44:50.278787: Pseudo dice [0.8361] +2024-11-22 00:44:50.278939: Epoch time: 18.74 s +2024-11-22 00:44:51.103564: +2024-11-22 00:44:51.103785: Epoch 2521 +2024-11-22 00:44:51.103916: Current learning rate: 0.00711 +2024-11-22 00:45:10.725566: train_loss -0.7674 +2024-11-22 00:45:10.731755: val_loss -0.7648 +2024-11-22 00:45:10.731876: Pseudo dice [0.8469] +2024-11-22 00:45:10.731984: Epoch time: 19.62 s +2024-11-22 00:45:11.671585: +2024-11-22 00:45:11.671810: Epoch 2522 +2024-11-22 00:45:11.671934: Current learning rate: 0.00711 +2024-11-22 00:45:29.670644: train_loss -0.772 +2024-11-22 00:45:29.680177: val_loss -0.7738 +2024-11-22 00:45:29.680343: Pseudo dice [0.8551] +2024-11-22 00:45:29.680460: Epoch time: 18.0 s +2024-11-22 00:45:30.575505: +2024-11-22 00:45:30.575694: Epoch 2523 +2024-11-22 00:45:30.575907: Current learning rate: 0.00711 +2024-11-22 00:45:49.020318: train_loss -0.7729 +2024-11-22 00:45:49.035836: val_loss -0.7544 +2024-11-22 00:45:49.035973: Pseudo dice [0.8424] +2024-11-22 00:45:49.043046: Epoch time: 18.45 s +2024-11-22 00:45:49.888998: +2024-11-22 00:45:49.889217: Epoch 2524 +2024-11-22 00:45:49.889334: Current learning rate: 0.00711 +2024-11-22 00:46:09.237338: train_loss -0.7793 +2024-11-22 00:46:09.240129: val_loss -0.7739 +2024-11-22 00:46:09.240267: Pseudo dice [0.8463] +2024-11-22 00:46:09.240382: Epoch time: 19.35 s +2024-11-22 00:46:10.066401: +2024-11-22 00:46:10.066621: Epoch 2525 +2024-11-22 00:46:10.066753: Current learning rate: 0.00711 +2024-11-22 00:46:28.968346: train_loss -0.7684 +2024-11-22 00:46:28.976094: val_loss -0.7555 +2024-11-22 00:46:28.976248: Pseudo dice [0.8474] +2024-11-22 00:46:28.976420: Epoch time: 18.9 s +2024-11-22 00:46:29.895462: +2024-11-22 00:46:29.895679: Epoch 2526 +2024-11-22 00:46:29.895822: Current learning rate: 0.00711 +2024-11-22 00:46:48.537178: train_loss -0.7639 +2024-11-22 00:46:48.540815: val_loss -0.7765 +2024-11-22 00:46:48.540941: Pseudo dice [0.8503] +2024-11-22 00:46:48.541030: Epoch time: 18.64 s +2024-11-22 00:46:49.367547: +2024-11-22 00:46:49.367759: Epoch 2527 +2024-11-22 00:46:49.367886: Current learning rate: 0.00711 +2024-11-22 00:47:08.233186: train_loss -0.768 +2024-11-22 00:47:08.239608: val_loss -0.7315 +2024-11-22 00:47:08.239733: Pseudo dice [0.8442] +2024-11-22 00:47:08.239817: Epoch time: 18.87 s +2024-11-22 00:47:09.196577: +2024-11-22 00:47:09.196819: Epoch 2528 +2024-11-22 00:47:09.196945: Current learning rate: 0.0071 +2024-11-22 00:47:27.426244: train_loss -0.7666 +2024-11-22 00:47:27.435039: val_loss -0.7322 +2024-11-22 00:47:27.435191: Pseudo dice [0.8387] +2024-11-22 00:47:27.435295: Epoch time: 18.23 s +2024-11-22 00:47:28.266839: +2024-11-22 00:47:28.267091: Epoch 2529 +2024-11-22 00:47:28.267224: Current learning rate: 0.0071 +2024-11-22 00:47:47.345790: train_loss -0.7708 +2024-11-22 00:47:47.350268: val_loss -0.7496 +2024-11-22 00:47:47.350491: Pseudo dice [0.8408] +2024-11-22 00:47:47.350584: Epoch time: 19.08 s +2024-11-22 00:47:48.203102: +2024-11-22 00:47:48.203340: Epoch 2530 +2024-11-22 00:47:48.203459: Current learning rate: 0.0071 +2024-11-22 00:48:07.794657: train_loss -0.781 +2024-11-22 00:48:07.802516: val_loss -0.7513 +2024-11-22 00:48:07.802658: Pseudo dice [0.85] +2024-11-22 00:48:07.802742: Epoch time: 19.59 s +2024-11-22 00:48:08.767329: +2024-11-22 00:48:08.767596: Epoch 2531 +2024-11-22 00:48:08.767720: Current learning rate: 0.0071 +2024-11-22 00:48:28.378079: train_loss -0.7661 +2024-11-22 00:48:28.385455: val_loss -0.7619 +2024-11-22 00:48:28.385619: Pseudo dice [0.8539] +2024-11-22 00:48:28.385711: Epoch time: 19.61 s +2024-11-22 00:48:29.212206: +2024-11-22 00:48:29.215964: Epoch 2532 +2024-11-22 00:48:29.216089: Current learning rate: 0.0071 +2024-11-22 00:48:48.661817: train_loss -0.7782 +2024-11-22 00:48:48.669361: val_loss -0.7649 +2024-11-22 00:48:48.669516: Pseudo dice [0.8529] +2024-11-22 00:48:48.669616: Epoch time: 19.45 s +2024-11-22 00:48:49.521578: +2024-11-22 00:48:49.521963: Epoch 2533 +2024-11-22 00:48:49.522080: Current learning rate: 0.0071 +2024-11-22 00:49:07.891047: train_loss -0.7821 +2024-11-22 00:49:07.905508: val_loss -0.7655 +2024-11-22 00:49:07.905646: Pseudo dice [0.8494] +2024-11-22 00:49:07.905732: Epoch time: 18.37 s +2024-11-22 00:49:08.812986: +2024-11-22 00:49:08.813265: Epoch 2534 +2024-11-22 00:49:08.813401: Current learning rate: 0.0071 +2024-11-22 00:49:27.026175: train_loss -0.7899 +2024-11-22 00:49:27.028995: val_loss -0.7807 +2024-11-22 00:49:27.029324: Pseudo dice [0.8589] +2024-11-22 00:49:27.029411: Epoch time: 18.21 s +2024-11-22 00:49:27.847569: +2024-11-22 00:49:27.847856: Epoch 2535 +2024-11-22 00:49:27.847966: Current learning rate: 0.0071 +2024-11-22 00:49:46.979676: train_loss -0.7887 +2024-11-22 00:49:46.987417: val_loss -0.7668 +2024-11-22 00:49:46.987558: Pseudo dice [0.8428] +2024-11-22 00:49:46.987653: Epoch time: 19.13 s +2024-11-22 00:49:47.975102: +2024-11-22 00:49:47.975340: Epoch 2536 +2024-11-22 00:49:47.975475: Current learning rate: 0.0071 +2024-11-22 00:50:06.657452: train_loss -0.781 +2024-11-22 00:50:06.660774: val_loss -0.771 +2024-11-22 00:50:06.660913: Pseudo dice [0.8534] +2024-11-22 00:50:06.661047: Epoch time: 18.68 s +2024-11-22 00:50:07.494583: +2024-11-22 00:50:07.495050: Epoch 2537 +2024-11-22 00:50:07.495423: Current learning rate: 0.00709 +2024-11-22 00:50:26.487538: train_loss -0.774 +2024-11-22 00:50:26.493818: val_loss -0.7579 +2024-11-22 00:50:26.494207: Pseudo dice [0.8414] +2024-11-22 00:50:26.494308: Epoch time: 18.99 s +2024-11-22 00:50:27.324163: +2024-11-22 00:50:27.324373: Epoch 2538 +2024-11-22 00:50:27.324487: Current learning rate: 0.00709 +2024-11-22 00:50:46.499879: train_loss -0.7639 +2024-11-22 00:50:46.502486: val_loss -0.7456 +2024-11-22 00:50:46.502588: Pseudo dice [0.8363] +2024-11-22 00:50:46.502694: Epoch time: 19.18 s +2024-11-22 00:50:47.322944: +2024-11-22 00:50:47.323210: Epoch 2539 +2024-11-22 00:50:47.323337: Current learning rate: 0.00709 +2024-11-22 00:51:06.368151: train_loss -0.775 +2024-11-22 00:51:06.374221: val_loss -0.7616 +2024-11-22 00:51:06.374371: Pseudo dice [0.8442] +2024-11-22 00:51:06.374469: Epoch time: 19.05 s +2024-11-22 00:51:07.660738: +2024-11-22 00:51:07.660976: Epoch 2540 +2024-11-22 00:51:07.661119: Current learning rate: 0.00709 +2024-11-22 00:51:27.458167: train_loss -0.7415 +2024-11-22 00:51:27.474510: val_loss -0.7637 +2024-11-22 00:51:27.474707: Pseudo dice [0.8342] +2024-11-22 00:51:27.474809: Epoch time: 19.8 s +2024-11-22 00:51:28.329265: +2024-11-22 00:51:28.329502: Epoch 2541 +2024-11-22 00:51:28.329632: Current learning rate: 0.00709 +2024-11-22 00:51:47.081226: train_loss -0.7473 +2024-11-22 00:51:47.107075: val_loss -0.7538 +2024-11-22 00:51:47.107396: Pseudo dice [0.8461] +2024-11-22 00:51:47.107507: Epoch time: 18.75 s +2024-11-22 00:51:47.929896: +2024-11-22 00:51:47.930137: Epoch 2542 +2024-11-22 00:51:47.930268: Current learning rate: 0.00709 +2024-11-22 00:52:05.505011: train_loss -0.775 +2024-11-22 00:52:05.512305: val_loss -0.7701 +2024-11-22 00:52:05.512463: Pseudo dice [0.8569] +2024-11-22 00:52:05.518728: Epoch time: 17.58 s +2024-11-22 00:52:06.368858: +2024-11-22 00:52:06.369112: Epoch 2543 +2024-11-22 00:52:06.369246: Current learning rate: 0.00709 +2024-11-22 00:52:26.550705: train_loss -0.7649 +2024-11-22 00:52:26.552718: val_loss -0.7556 +2024-11-22 00:52:26.552832: Pseudo dice [0.842] +2024-11-22 00:52:26.552960: Epoch time: 20.18 s +2024-11-22 00:52:27.382866: +2024-11-22 00:52:27.383084: Epoch 2544 +2024-11-22 00:52:27.383195: Current learning rate: 0.00709 +2024-11-22 00:52:46.146165: train_loss -0.7767 +2024-11-22 00:52:46.152666: val_loss -0.7598 +2024-11-22 00:52:46.152852: Pseudo dice [0.8436] +2024-11-22 00:52:46.152963: Epoch time: 18.76 s +2024-11-22 00:52:47.209883: +2024-11-22 00:52:47.210304: Epoch 2545 +2024-11-22 00:52:47.210423: Current learning rate: 0.00708 +2024-11-22 00:53:06.644229: train_loss -0.775 +2024-11-22 00:53:06.656530: val_loss -0.758 +2024-11-22 00:53:06.656657: Pseudo dice [0.8457] +2024-11-22 00:53:06.656747: Epoch time: 19.44 s +2024-11-22 00:53:07.572309: +2024-11-22 00:53:07.572514: Epoch 2546 +2024-11-22 00:53:07.572629: Current learning rate: 0.00708 +2024-11-22 00:53:25.100931: train_loss -0.7799 +2024-11-22 00:53:25.115986: val_loss -0.7583 +2024-11-22 00:53:25.116145: Pseudo dice [0.8487] +2024-11-22 00:53:25.116278: Epoch time: 17.53 s +2024-11-22 00:53:25.963926: +2024-11-22 00:53:25.964148: Epoch 2547 +2024-11-22 00:53:25.964262: Current learning rate: 0.00708 +2024-11-22 00:53:45.129661: train_loss -0.7682 +2024-11-22 00:53:45.137101: val_loss -0.7732 +2024-11-22 00:53:45.137228: Pseudo dice [0.8501] +2024-11-22 00:53:45.137344: Epoch time: 19.17 s +2024-11-22 00:53:46.023686: +2024-11-22 00:53:46.023877: Epoch 2548 +2024-11-22 00:53:46.023995: Current learning rate: 0.00708 +2024-11-22 00:54:05.524979: train_loss -0.7748 +2024-11-22 00:54:05.539969: val_loss -0.7876 +2024-11-22 00:54:05.540127: Pseudo dice [0.864] +2024-11-22 00:54:05.540218: Epoch time: 19.5 s +2024-11-22 00:54:06.540329: +2024-11-22 00:54:06.540579: Epoch 2549 +2024-11-22 00:54:06.540702: Current learning rate: 0.00708 +2024-11-22 00:54:25.511160: train_loss -0.7857 +2024-11-22 00:54:25.519043: val_loss -0.7512 +2024-11-22 00:54:25.519199: Pseudo dice [0.8493] +2024-11-22 00:54:25.519295: Epoch time: 18.97 s +2024-11-22 00:54:26.625268: +2024-11-22 00:54:26.625477: Epoch 2550 +2024-11-22 00:54:26.625600: Current learning rate: 0.00708 +2024-11-22 00:54:46.108214: train_loss -0.7755 +2024-11-22 00:54:46.115542: val_loss -0.7377 +2024-11-22 00:54:46.115691: Pseudo dice [0.8503] +2024-11-22 00:54:46.115784: Epoch time: 19.48 s +2024-11-22 00:54:47.236670: +2024-11-22 00:54:47.236876: Epoch 2551 +2024-11-22 00:54:47.236996: Current learning rate: 0.00708 +2024-11-22 00:55:06.829035: train_loss -0.7488 +2024-11-22 00:55:06.833653: val_loss -0.7525 +2024-11-22 00:55:06.833820: Pseudo dice [0.8392] +2024-11-22 00:55:06.833928: Epoch time: 19.59 s +2024-11-22 00:55:07.655617: +2024-11-22 00:55:07.655849: Epoch 2552 +2024-11-22 00:55:07.655976: Current learning rate: 0.00708 +2024-11-22 00:55:27.113782: train_loss -0.7554 +2024-11-22 00:55:27.124473: val_loss -0.7738 +2024-11-22 00:55:27.124620: Pseudo dice [0.8581] +2024-11-22 00:55:27.124709: Epoch time: 19.46 s +2024-11-22 00:55:27.953493: +2024-11-22 00:55:27.953725: Epoch 2553 +2024-11-22 00:55:27.953845: Current learning rate: 0.00708 +2024-11-22 00:55:46.151941: train_loss -0.7675 +2024-11-22 00:55:46.159390: val_loss -0.7713 +2024-11-22 00:55:46.161505: Pseudo dice [0.8376] +2024-11-22 00:55:46.161638: Epoch time: 18.2 s +2024-11-22 00:55:46.990711: +2024-11-22 00:55:46.990937: Epoch 2554 +2024-11-22 00:55:46.991056: Current learning rate: 0.00707 +2024-11-22 00:56:05.201819: train_loss -0.7647 +2024-11-22 00:56:05.206412: val_loss -0.7566 +2024-11-22 00:56:05.206548: Pseudo dice [0.855] +2024-11-22 00:56:05.206638: Epoch time: 18.21 s +2024-11-22 00:56:06.070279: +2024-11-22 00:56:06.070503: Epoch 2555 +2024-11-22 00:56:06.070639: Current learning rate: 0.00707 +2024-11-22 00:56:24.638827: train_loss -0.7732 +2024-11-22 00:56:24.677902: val_loss -0.7475 +2024-11-22 00:56:24.678118: Pseudo dice [0.8397] +2024-11-22 00:56:24.678226: Epoch time: 18.57 s +2024-11-22 00:56:25.521297: +2024-11-22 00:56:25.521535: Epoch 2556 +2024-11-22 00:56:25.521665: Current learning rate: 0.00707 +2024-11-22 00:56:45.039009: train_loss -0.7666 +2024-11-22 00:56:45.063773: val_loss -0.7512 +2024-11-22 00:56:45.064338: Pseudo dice [0.8385] +2024-11-22 00:56:45.064460: Epoch time: 19.52 s +2024-11-22 00:56:45.933068: +2024-11-22 00:56:45.933301: Epoch 2557 +2024-11-22 00:56:45.933428: Current learning rate: 0.00707 +2024-11-22 00:57:06.141002: train_loss -0.78 +2024-11-22 00:57:06.146837: val_loss -0.7793 +2024-11-22 00:57:06.146989: Pseudo dice [0.8519] +2024-11-22 00:57:06.147082: Epoch time: 20.21 s +2024-11-22 00:57:07.066601: +2024-11-22 00:57:07.066809: Epoch 2558 +2024-11-22 00:57:07.066929: Current learning rate: 0.00707 +2024-11-22 00:57:25.992532: train_loss -0.7761 +2024-11-22 00:57:26.043868: val_loss -0.761 +2024-11-22 00:57:26.044037: Pseudo dice [0.8502] +2024-11-22 00:57:26.044155: Epoch time: 18.93 s +2024-11-22 00:57:26.866323: +2024-11-22 00:57:26.866528: Epoch 2559 +2024-11-22 00:57:26.866641: Current learning rate: 0.00707 +2024-11-22 00:57:44.780572: train_loss -0.7487 +2024-11-22 00:57:44.821838: val_loss -0.7638 +2024-11-22 00:57:44.822037: Pseudo dice [0.8197] +2024-11-22 00:57:44.822164: Epoch time: 17.92 s +2024-11-22 00:57:45.682003: +2024-11-22 00:57:45.682231: Epoch 2560 +2024-11-22 00:57:45.682358: Current learning rate: 0.00707 +2024-11-22 00:58:05.005520: train_loss -0.7562 +2024-11-22 00:58:05.032680: val_loss -0.7694 +2024-11-22 00:58:05.032865: Pseudo dice [0.8461] +2024-11-22 00:58:05.032990: Epoch time: 19.32 s +2024-11-22 00:58:05.894659: +2024-11-22 00:58:05.894869: Epoch 2561 +2024-11-22 00:58:05.894993: Current learning rate: 0.00707 +2024-11-22 00:58:24.240645: train_loss -0.747 +2024-11-22 00:58:24.252160: val_loss -0.728 +2024-11-22 00:58:24.252305: Pseudo dice [0.8227] +2024-11-22 00:58:24.252404: Epoch time: 18.35 s +2024-11-22 00:58:25.244843: +2024-11-22 00:58:25.245064: Epoch 2562 +2024-11-22 00:58:25.245180: Current learning rate: 0.00707 +2024-11-22 00:58:44.801052: train_loss -0.7362 +2024-11-22 00:58:44.808351: val_loss -0.7259 +2024-11-22 00:58:44.808719: Pseudo dice [0.8251] +2024-11-22 00:58:44.808827: Epoch time: 19.56 s +2024-11-22 00:58:46.083873: +2024-11-22 00:58:46.084110: Epoch 2563 +2024-11-22 00:58:46.084235: Current learning rate: 0.00706 +2024-11-22 00:59:04.297338: train_loss -0.74 +2024-11-22 00:59:04.311458: val_loss -0.7291 +2024-11-22 00:59:04.311605: Pseudo dice [0.8282] +2024-11-22 00:59:04.311721: Epoch time: 18.21 s +2024-11-22 00:59:05.152512: +2024-11-22 00:59:05.152774: Epoch 2564 +2024-11-22 00:59:05.152907: Current learning rate: 0.00706 +2024-11-22 00:59:24.005427: train_loss -0.7679 +2024-11-22 00:59:24.018576: val_loss -0.7593 +2024-11-22 00:59:24.018770: Pseudo dice [0.8611] +2024-11-22 00:59:24.018869: Epoch time: 18.85 s +2024-11-22 00:59:24.929133: +2024-11-22 00:59:24.929351: Epoch 2565 +2024-11-22 00:59:24.929469: Current learning rate: 0.00706 +2024-11-22 00:59:44.180837: train_loss -0.7594 +2024-11-22 00:59:44.186260: val_loss -0.7573 +2024-11-22 00:59:44.186371: Pseudo dice [0.8526] +2024-11-22 00:59:44.186468: Epoch time: 19.25 s +2024-11-22 00:59:45.054352: +2024-11-22 00:59:45.054565: Epoch 2566 +2024-11-22 00:59:45.054703: Current learning rate: 0.00706 +2024-11-22 01:00:04.099591: train_loss -0.7639 +2024-11-22 01:00:04.105403: val_loss -0.776 +2024-11-22 01:00:04.105560: Pseudo dice [0.8456] +2024-11-22 01:00:04.105674: Epoch time: 19.05 s +2024-11-22 01:00:04.999885: +2024-11-22 01:00:05.000122: Epoch 2567 +2024-11-22 01:00:05.000258: Current learning rate: 0.00706 +2024-11-22 01:00:24.769825: train_loss -0.7752 +2024-11-22 01:00:24.780586: val_loss -0.7639 +2024-11-22 01:00:24.780711: Pseudo dice [0.8542] +2024-11-22 01:00:24.780807: Epoch time: 19.77 s +2024-11-22 01:00:25.603887: +2024-11-22 01:00:25.604103: Epoch 2568 +2024-11-22 01:00:25.604244: Current learning rate: 0.00706 +2024-11-22 01:00:44.146217: train_loss -0.7727 +2024-11-22 01:00:44.150867: val_loss -0.7466 +2024-11-22 01:00:44.150974: Pseudo dice [0.8526] +2024-11-22 01:00:44.151067: Epoch time: 18.54 s +2024-11-22 01:00:45.194322: +2024-11-22 01:00:45.194533: Epoch 2569 +2024-11-22 01:00:45.194648: Current learning rate: 0.00706 +2024-11-22 01:01:04.977542: train_loss -0.7569 +2024-11-22 01:01:04.979746: val_loss -0.7514 +2024-11-22 01:01:04.979854: Pseudo dice [0.8474] +2024-11-22 01:01:04.979949: Epoch time: 19.78 s +2024-11-22 01:01:05.800860: +2024-11-22 01:01:05.801064: Epoch 2570 +2024-11-22 01:01:05.801186: Current learning rate: 0.00706 +2024-11-22 01:01:25.211937: train_loss -0.773 +2024-11-22 01:01:25.218626: val_loss -0.7636 +2024-11-22 01:01:25.218773: Pseudo dice [0.8481] +2024-11-22 01:01:25.218986: Epoch time: 19.41 s +2024-11-22 01:01:26.045394: +2024-11-22 01:01:26.045597: Epoch 2571 +2024-11-22 01:01:26.045722: Current learning rate: 0.00705 +2024-11-22 01:01:45.605118: train_loss -0.7687 +2024-11-22 01:01:45.613081: val_loss -0.7667 +2024-11-22 01:01:45.613233: Pseudo dice [0.8469] +2024-11-22 01:01:45.613336: Epoch time: 19.56 s +2024-11-22 01:01:46.541215: +2024-11-22 01:01:46.541436: Epoch 2572 +2024-11-22 01:01:46.541574: Current learning rate: 0.00705 +2024-11-22 01:02:06.257077: train_loss -0.7683 +2024-11-22 01:02:06.263294: val_loss -0.774 +2024-11-22 01:02:06.263477: Pseudo dice [0.848] +2024-11-22 01:02:06.263697: Epoch time: 19.72 s +2024-11-22 01:02:07.100413: +2024-11-22 01:02:07.100635: Epoch 2573 +2024-11-22 01:02:07.100764: Current learning rate: 0.00705 +2024-11-22 01:02:24.689776: train_loss -0.7835 +2024-11-22 01:02:24.696896: val_loss -0.7791 +2024-11-22 01:02:24.697036: Pseudo dice [0.8486] +2024-11-22 01:02:24.697145: Epoch time: 17.59 s +2024-11-22 01:02:25.565709: +2024-11-22 01:02:25.566008: Epoch 2574 +2024-11-22 01:02:25.566154: Current learning rate: 0.00705 +2024-11-22 01:02:44.631489: train_loss -0.7709 +2024-11-22 01:02:44.635416: val_loss -0.7654 +2024-11-22 01:02:44.635573: Pseudo dice [0.851] +2024-11-22 01:02:44.635680: Epoch time: 19.07 s +2024-11-22 01:02:45.955709: +2024-11-22 01:02:45.955941: Epoch 2575 +2024-11-22 01:02:45.956074: Current learning rate: 0.00705 +2024-11-22 01:03:04.961936: train_loss -0.7676 +2024-11-22 01:03:04.971644: val_loss -0.7784 +2024-11-22 01:03:04.971803: Pseudo dice [0.8467] +2024-11-22 01:03:04.971904: Epoch time: 19.01 s +2024-11-22 01:03:05.809995: +2024-11-22 01:03:05.810243: Epoch 2576 +2024-11-22 01:03:05.810366: Current learning rate: 0.00705 +2024-11-22 01:03:24.675995: train_loss -0.7641 +2024-11-22 01:03:24.677594: val_loss -0.7713 +2024-11-22 01:03:24.677683: Pseudo dice [0.8395] +2024-11-22 01:03:24.677770: Epoch time: 18.87 s +2024-11-22 01:03:25.499105: +2024-11-22 01:03:25.499311: Epoch 2577 +2024-11-22 01:03:25.499429: Current learning rate: 0.00705 +2024-11-22 01:03:45.101055: train_loss -0.7637 +2024-11-22 01:03:45.107855: val_loss -0.7571 +2024-11-22 01:03:45.108063: Pseudo dice [0.841] +2024-11-22 01:03:45.108160: Epoch time: 19.6 s +2024-11-22 01:03:46.063853: +2024-11-22 01:03:46.064055: Epoch 2578 +2024-11-22 01:03:46.064228: Current learning rate: 0.00705 +2024-11-22 01:04:05.095906: train_loss -0.7655 +2024-11-22 01:04:05.097531: val_loss -0.7654 +2024-11-22 01:04:05.097675: Pseudo dice [0.8355] +2024-11-22 01:04:05.097781: Epoch time: 19.03 s +2024-11-22 01:04:06.031283: +2024-11-22 01:04:06.031487: Epoch 2579 +2024-11-22 01:04:06.031611: Current learning rate: 0.00705 +2024-11-22 01:04:24.840452: train_loss -0.7692 +2024-11-22 01:04:24.844788: val_loss -0.769 +2024-11-22 01:04:24.844951: Pseudo dice [0.8547] +2024-11-22 01:04:24.845068: Epoch time: 18.81 s +2024-11-22 01:04:25.683846: +2024-11-22 01:04:25.684062: Epoch 2580 +2024-11-22 01:04:25.684182: Current learning rate: 0.00704 +2024-11-22 01:04:43.699844: train_loss -0.7685 +2024-11-22 01:04:43.719118: val_loss -0.7688 +2024-11-22 01:04:43.719275: Pseudo dice [0.8498] +2024-11-22 01:04:43.719378: Epoch time: 18.02 s +2024-11-22 01:04:44.596516: +2024-11-22 01:04:44.596716: Epoch 2581 +2024-11-22 01:04:44.596862: Current learning rate: 0.00704 +2024-11-22 01:05:04.125421: train_loss -0.7711 +2024-11-22 01:05:04.127611: val_loss -0.7787 +2024-11-22 01:05:04.127761: Pseudo dice [0.8405] +2024-11-22 01:05:04.127860: Epoch time: 19.53 s +2024-11-22 01:05:04.960234: +2024-11-22 01:05:04.960427: Epoch 2582 +2024-11-22 01:05:04.960565: Current learning rate: 0.00704 +2024-11-22 01:05:25.478188: train_loss -0.7516 +2024-11-22 01:05:25.523830: val_loss -0.7491 +2024-11-22 01:05:25.524014: Pseudo dice [0.8477] +2024-11-22 01:05:25.524120: Epoch time: 20.52 s +2024-11-22 01:05:26.346356: +2024-11-22 01:05:26.346575: Epoch 2583 +2024-11-22 01:05:26.346689: Current learning rate: 0.00704 +2024-11-22 01:05:45.795679: train_loss -0.7577 +2024-11-22 01:05:45.803549: val_loss -0.761 +2024-11-22 01:05:45.803688: Pseudo dice [0.8357] +2024-11-22 01:05:45.803790: Epoch time: 19.45 s +2024-11-22 01:05:46.650164: +2024-11-22 01:05:46.650395: Epoch 2584 +2024-11-22 01:05:46.650513: Current learning rate: 0.00704 +2024-11-22 01:06:05.238668: train_loss -0.7707 +2024-11-22 01:06:05.262528: val_loss -0.7547 +2024-11-22 01:06:05.262723: Pseudo dice [0.8404] +2024-11-22 01:06:05.262838: Epoch time: 18.59 s +2024-11-22 01:06:06.299461: +2024-11-22 01:06:06.299679: Epoch 2585 +2024-11-22 01:06:06.299799: Current learning rate: 0.00704 +2024-11-22 01:06:25.922831: train_loss -0.7749 +2024-11-22 01:06:25.939924: val_loss -0.7664 +2024-11-22 01:06:25.940063: Pseudo dice [0.8484] +2024-11-22 01:06:25.940171: Epoch time: 19.62 s +2024-11-22 01:06:26.761918: +2024-11-22 01:06:26.762129: Epoch 2586 +2024-11-22 01:06:26.762253: Current learning rate: 0.00704 +2024-11-22 01:06:45.790758: train_loss -0.7844 +2024-11-22 01:06:45.809314: val_loss -0.766 +2024-11-22 01:06:45.809489: Pseudo dice [0.8389] +2024-11-22 01:06:45.809589: Epoch time: 19.03 s +2024-11-22 01:06:47.116662: +2024-11-22 01:06:47.116878: Epoch 2587 +2024-11-22 01:06:47.117008: Current learning rate: 0.00704 +2024-11-22 01:07:07.030517: train_loss -0.7629 +2024-11-22 01:07:07.037367: val_loss -0.7479 +2024-11-22 01:07:07.037527: Pseudo dice [0.8364] +2024-11-22 01:07:07.037651: Epoch time: 19.91 s +2024-11-22 01:07:07.868260: +2024-11-22 01:07:07.868483: Epoch 2588 +2024-11-22 01:07:07.868600: Current learning rate: 0.00703 +2024-11-22 01:07:27.228793: train_loss -0.7867 +2024-11-22 01:07:27.255883: val_loss -0.7691 +2024-11-22 01:07:27.256071: Pseudo dice [0.8508] +2024-11-22 01:07:27.256285: Epoch time: 19.36 s +2024-11-22 01:07:28.261956: +2024-11-22 01:07:28.262243: Epoch 2589 +2024-11-22 01:07:28.262372: Current learning rate: 0.00703 +2024-11-22 01:07:47.458521: train_loss -0.78 +2024-11-22 01:07:47.483393: val_loss -0.7815 +2024-11-22 01:07:47.483524: Pseudo dice [0.8469] +2024-11-22 01:07:47.483620: Epoch time: 19.2 s +2024-11-22 01:07:48.305657: +2024-11-22 01:07:48.305931: Epoch 2590 +2024-11-22 01:07:48.306051: Current learning rate: 0.00703 +2024-11-22 01:08:07.855205: train_loss -0.7793 +2024-11-22 01:08:07.877623: val_loss -0.7567 +2024-11-22 01:08:07.877781: Pseudo dice [0.8401] +2024-11-22 01:08:07.877888: Epoch time: 19.55 s +2024-11-22 01:08:08.851298: +2024-11-22 01:08:08.851898: Epoch 2591 +2024-11-22 01:08:08.852017: Current learning rate: 0.00703 +2024-11-22 01:08:28.509635: train_loss -0.7749 +2024-11-22 01:08:28.525090: val_loss -0.7741 +2024-11-22 01:08:28.525231: Pseudo dice [0.844] +2024-11-22 01:08:28.525341: Epoch time: 19.66 s +2024-11-22 01:08:29.516228: +2024-11-22 01:08:29.516427: Epoch 2592 +2024-11-22 01:08:29.516555: Current learning rate: 0.00703 +2024-11-22 01:08:48.927457: train_loss -0.7769 +2024-11-22 01:08:48.940952: val_loss -0.7892 +2024-11-22 01:08:48.941129: Pseudo dice [0.8629] +2024-11-22 01:08:48.941225: Epoch time: 19.41 s +2024-11-22 01:08:49.820456: +2024-11-22 01:08:49.820689: Epoch 2593 +2024-11-22 01:08:49.820816: Current learning rate: 0.00703 +2024-11-22 01:09:08.384457: train_loss -0.7776 +2024-11-22 01:09:08.394044: val_loss -0.7618 +2024-11-22 01:09:08.394184: Pseudo dice [0.8396] +2024-11-22 01:09:08.394270: Epoch time: 18.56 s +2024-11-22 01:09:09.293952: +2024-11-22 01:09:09.294188: Epoch 2594 +2024-11-22 01:09:09.294315: Current learning rate: 0.00703 +2024-11-22 01:09:28.769890: train_loss -0.7855 +2024-11-22 01:09:28.773406: val_loss -0.7876 +2024-11-22 01:09:28.773578: Pseudo dice [0.8494] +2024-11-22 01:09:28.773689: Epoch time: 19.48 s +2024-11-22 01:09:29.601386: +2024-11-22 01:09:29.601587: Epoch 2595 +2024-11-22 01:09:29.601703: Current learning rate: 0.00703 +2024-11-22 01:09:48.515238: train_loss -0.7716 +2024-11-22 01:09:48.534680: val_loss -0.7672 +2024-11-22 01:09:48.534832: Pseudo dice [0.8514] +2024-11-22 01:09:48.534932: Epoch time: 18.91 s +2024-11-22 01:09:49.386407: +2024-11-22 01:09:49.386614: Epoch 2596 +2024-11-22 01:09:49.386734: Current learning rate: 0.00703 +2024-11-22 01:10:09.490109: train_loss -0.7745 +2024-11-22 01:10:09.509872: val_loss -0.7515 +2024-11-22 01:10:09.510045: Pseudo dice [0.8532] +2024-11-22 01:10:09.510184: Epoch time: 20.1 s +2024-11-22 01:10:10.338579: +2024-11-22 01:10:10.338786: Epoch 2597 +2024-11-22 01:10:10.338911: Current learning rate: 0.00702 +2024-11-22 01:10:29.397763: train_loss -0.7736 +2024-11-22 01:10:29.403424: val_loss -0.7707 +2024-11-22 01:10:29.403584: Pseudo dice [0.8552] +2024-11-22 01:10:29.403670: Epoch time: 19.06 s +2024-11-22 01:10:30.342187: +2024-11-22 01:10:30.342436: Epoch 2598 +2024-11-22 01:10:30.342549: Current learning rate: 0.00702 +2024-11-22 01:10:48.031361: train_loss -0.7794 +2024-11-22 01:10:48.056999: val_loss -0.7639 +2024-11-22 01:10:48.057178: Pseudo dice [0.8437] +2024-11-22 01:10:48.057281: Epoch time: 17.69 s +2024-11-22 01:10:48.919097: +2024-11-22 01:10:48.919318: Epoch 2599 +2024-11-22 01:10:48.919442: Current learning rate: 0.00702 +2024-11-22 01:11:07.653217: train_loss -0.7773 +2024-11-22 01:11:07.676435: val_loss -0.7705 +2024-11-22 01:11:07.676601: Pseudo dice [0.8585] +2024-11-22 01:11:07.676695: Epoch time: 18.73 s +2024-11-22 01:11:08.774340: +2024-11-22 01:11:08.774576: Epoch 2600 +2024-11-22 01:11:08.774714: Current learning rate: 0.00702 +2024-11-22 01:11:28.583584: train_loss -0.7789 +2024-11-22 01:11:28.589241: val_loss -0.7741 +2024-11-22 01:11:28.589839: Pseudo dice [0.8437] +2024-11-22 01:11:28.589962: Epoch time: 19.81 s +2024-11-22 01:11:29.503180: +2024-11-22 01:11:29.503399: Epoch 2601 +2024-11-22 01:11:29.503527: Current learning rate: 0.00702 +2024-11-22 01:11:48.919703: train_loss -0.7717 +2024-11-22 01:11:48.922629: val_loss -0.7611 +2024-11-22 01:11:48.922779: Pseudo dice [0.8353] +2024-11-22 01:11:48.922881: Epoch time: 19.42 s +2024-11-22 01:11:49.762271: +2024-11-22 01:11:49.762489: Epoch 2602 +2024-11-22 01:11:49.762609: Current learning rate: 0.00702 +2024-11-22 01:12:08.281590: train_loss -0.7677 +2024-11-22 01:12:08.284198: val_loss -0.7757 +2024-11-22 01:12:08.284339: Pseudo dice [0.8403] +2024-11-22 01:12:08.284455: Epoch time: 18.52 s +2024-11-22 01:12:09.126296: +2024-11-22 01:12:09.126498: Epoch 2603 +2024-11-22 01:12:09.126618: Current learning rate: 0.00702 +2024-11-22 01:12:28.090727: train_loss -0.7614 +2024-11-22 01:12:28.102124: val_loss -0.7339 +2024-11-22 01:12:28.102358: Pseudo dice [0.8266] +2024-11-22 01:12:28.102466: Epoch time: 18.97 s +2024-11-22 01:12:29.022148: +2024-11-22 01:12:29.022362: Epoch 2604 +2024-11-22 01:12:29.022483: Current learning rate: 0.00702 +2024-11-22 01:12:48.492089: train_loss -0.7664 +2024-11-22 01:12:48.496847: val_loss -0.7492 +2024-11-22 01:12:48.497001: Pseudo dice [0.8345] +2024-11-22 01:12:48.497099: Epoch time: 19.47 s +2024-11-22 01:12:49.333534: +2024-11-22 01:12:49.333739: Epoch 2605 +2024-11-22 01:12:49.333863: Current learning rate: 0.00701 +2024-11-22 01:13:07.994320: train_loss -0.7684 +2024-11-22 01:13:08.009022: val_loss -0.7434 +2024-11-22 01:13:08.009192: Pseudo dice [0.841] +2024-11-22 01:13:08.009287: Epoch time: 18.66 s +2024-11-22 01:13:08.834017: +2024-11-22 01:13:08.834266: Epoch 2606 +2024-11-22 01:13:08.834393: Current learning rate: 0.00701 +2024-11-22 01:13:27.497081: train_loss -0.7588 +2024-11-22 01:13:27.500860: val_loss -0.7506 +2024-11-22 01:13:27.501008: Pseudo dice [0.8352] +2024-11-22 01:13:27.501122: Epoch time: 18.66 s +2024-11-22 01:13:28.326727: +2024-11-22 01:13:28.326938: Epoch 2607 +2024-11-22 01:13:28.327057: Current learning rate: 0.00701 +2024-11-22 01:13:47.651000: train_loss -0.7664 +2024-11-22 01:13:47.656748: val_loss -0.7736 +2024-11-22 01:13:47.656901: Pseudo dice [0.8512] +2024-11-22 01:13:47.657066: Epoch time: 19.33 s +2024-11-22 01:13:48.632102: +2024-11-22 01:13:48.632309: Epoch 2608 +2024-11-22 01:13:48.632437: Current learning rate: 0.00701 +2024-11-22 01:14:07.306734: train_loss -0.759 +2024-11-22 01:14:07.317149: val_loss -0.7738 +2024-11-22 01:14:07.317300: Pseudo dice [0.8381] +2024-11-22 01:14:07.317401: Epoch time: 18.68 s +2024-11-22 01:14:08.261791: +2024-11-22 01:14:08.262028: Epoch 2609 +2024-11-22 01:14:08.262179: Current learning rate: 0.00701 +2024-11-22 01:14:27.987315: train_loss -0.7737 +2024-11-22 01:14:27.994286: val_loss -0.744 +2024-11-22 01:14:27.994459: Pseudo dice [0.8538] +2024-11-22 01:14:27.994563: Epoch time: 19.73 s +2024-11-22 01:14:29.205596: +2024-11-22 01:14:29.205827: Epoch 2610 +2024-11-22 01:14:29.205949: Current learning rate: 0.00701 +2024-11-22 01:14:48.850925: train_loss -0.7717 +2024-11-22 01:14:48.856447: val_loss -0.775 +2024-11-22 01:14:48.856594: Pseudo dice [0.8417] +2024-11-22 01:14:48.856707: Epoch time: 19.65 s +2024-11-22 01:14:49.828449: +2024-11-22 01:14:49.828700: Epoch 2611 +2024-11-22 01:14:49.828833: Current learning rate: 0.00701 +2024-11-22 01:15:08.785453: train_loss -0.7722 +2024-11-22 01:15:08.787337: val_loss -0.7546 +2024-11-22 01:15:08.787490: Pseudo dice [0.8401] +2024-11-22 01:15:08.787593: Epoch time: 18.96 s +2024-11-22 01:15:09.638186: +2024-11-22 01:15:09.638452: Epoch 2612 +2024-11-22 01:15:09.638580: Current learning rate: 0.00701 +2024-11-22 01:15:28.559299: train_loss -0.7784 +2024-11-22 01:15:28.594041: val_loss -0.7509 +2024-11-22 01:15:28.594231: Pseudo dice [0.844] +2024-11-22 01:15:28.594349: Epoch time: 18.92 s +2024-11-22 01:15:29.598985: +2024-11-22 01:15:29.599276: Epoch 2613 +2024-11-22 01:15:29.599397: Current learning rate: 0.00701 +2024-11-22 01:15:49.234483: train_loss -0.776 +2024-11-22 01:15:49.243391: val_loss -0.7612 +2024-11-22 01:15:49.243625: Pseudo dice [0.8504] +2024-11-22 01:15:49.243732: Epoch time: 19.64 s +2024-11-22 01:15:50.101685: +2024-11-22 01:15:50.101910: Epoch 2614 +2024-11-22 01:15:50.102036: Current learning rate: 0.007 +2024-11-22 01:16:09.182494: train_loss -0.7724 +2024-11-22 01:16:09.190048: val_loss -0.7415 +2024-11-22 01:16:09.190197: Pseudo dice [0.8292] +2024-11-22 01:16:09.190291: Epoch time: 19.08 s +2024-11-22 01:16:10.134156: +2024-11-22 01:16:10.134366: Epoch 2615 +2024-11-22 01:16:10.134488: Current learning rate: 0.007 +2024-11-22 01:16:29.566986: train_loss -0.7671 +2024-11-22 01:16:29.571115: val_loss -0.7673 +2024-11-22 01:16:29.571251: Pseudo dice [0.8647] +2024-11-22 01:16:29.571341: Epoch time: 19.43 s +2024-11-22 01:16:30.450040: +2024-11-22 01:16:30.450268: Epoch 2616 +2024-11-22 01:16:30.450391: Current learning rate: 0.007 +2024-11-22 01:16:49.501205: train_loss -0.7746 +2024-11-22 01:16:49.527937: val_loss -0.7822 +2024-11-22 01:16:49.528116: Pseudo dice [0.8522] +2024-11-22 01:16:49.528224: Epoch time: 19.05 s +2024-11-22 01:16:50.356280: +2024-11-22 01:16:50.356506: Epoch 2617 +2024-11-22 01:16:50.356633: Current learning rate: 0.007 +2024-11-22 01:17:10.371926: train_loss -0.7816 +2024-11-22 01:17:10.377233: val_loss -0.751 +2024-11-22 01:17:10.377361: Pseudo dice [0.8626] +2024-11-22 01:17:10.377458: Epoch time: 20.02 s +2024-11-22 01:17:11.265401: +2024-11-22 01:17:11.265617: Epoch 2618 +2024-11-22 01:17:11.265737: Current learning rate: 0.007 +2024-11-22 01:17:29.559306: train_loss -0.771 +2024-11-22 01:17:29.566730: val_loss -0.7627 +2024-11-22 01:17:29.566874: Pseudo dice [0.8538] +2024-11-22 01:17:29.566979: Epoch time: 18.29 s +2024-11-22 01:17:30.554666: +2024-11-22 01:17:30.554895: Epoch 2619 +2024-11-22 01:17:30.555025: Current learning rate: 0.007 +2024-11-22 01:17:50.492705: train_loss -0.7798 +2024-11-22 01:17:50.496171: val_loss -0.7686 +2024-11-22 01:17:50.496320: Pseudo dice [0.8613] +2024-11-22 01:17:50.496414: Epoch time: 19.94 s +2024-11-22 01:17:51.332565: +2024-11-22 01:17:51.332788: Epoch 2620 +2024-11-22 01:17:51.332927: Current learning rate: 0.007 +2024-11-22 01:18:11.119282: train_loss -0.7646 +2024-11-22 01:18:11.122845: val_loss -0.7557 +2024-11-22 01:18:11.122991: Pseudo dice [0.8445] +2024-11-22 01:18:11.123115: Epoch time: 19.79 s +2024-11-22 01:18:11.992201: +2024-11-22 01:18:11.992659: Epoch 2621 +2024-11-22 01:18:11.992820: Current learning rate: 0.007 +2024-11-22 01:18:30.967269: train_loss -0.771 +2024-11-22 01:18:30.971935: val_loss -0.7846 +2024-11-22 01:18:30.972090: Pseudo dice [0.8482] +2024-11-22 01:18:30.972183: Epoch time: 18.98 s +2024-11-22 01:18:31.884344: +2024-11-22 01:18:31.884581: Epoch 2622 +2024-11-22 01:18:31.884719: Current learning rate: 0.00699 +2024-11-22 01:18:49.990145: train_loss -0.7713 +2024-11-22 01:18:50.014594: val_loss -0.7837 +2024-11-22 01:18:50.014756: Pseudo dice [0.8581] +2024-11-22 01:18:50.014858: Epoch time: 18.11 s +2024-11-22 01:18:51.022995: +2024-11-22 01:18:51.023225: Epoch 2623 +2024-11-22 01:18:51.023363: Current learning rate: 0.00699 +2024-11-22 01:19:10.200355: train_loss -0.7761 +2024-11-22 01:19:10.203844: val_loss -0.7717 +2024-11-22 01:19:10.204053: Pseudo dice [0.8448] +2024-11-22 01:19:10.204164: Epoch time: 19.18 s +2024-11-22 01:19:11.055509: +2024-11-22 01:19:11.055748: Epoch 2624 +2024-11-22 01:19:11.055876: Current learning rate: 0.00699 +2024-11-22 01:19:28.806802: train_loss -0.777 +2024-11-22 01:19:28.808255: val_loss -0.7567 +2024-11-22 01:19:28.808349: Pseudo dice [0.8375] +2024-11-22 01:19:28.808444: Epoch time: 17.75 s +2024-11-22 01:19:29.633999: +2024-11-22 01:19:29.634221: Epoch 2625 +2024-11-22 01:19:29.634366: Current learning rate: 0.00699 +2024-11-22 01:19:50.928094: train_loss -0.7762 +2024-11-22 01:19:50.936502: val_loss -0.7803 +2024-11-22 01:19:50.936624: Pseudo dice [0.8468] +2024-11-22 01:19:50.936710: Epoch time: 21.29 s +2024-11-22 01:19:51.926194: +2024-11-22 01:19:51.926392: Epoch 2626 +2024-11-22 01:19:51.926767: Current learning rate: 0.00699 +2024-11-22 01:20:10.663366: train_loss -0.7621 +2024-11-22 01:20:10.669401: val_loss -0.7643 +2024-11-22 01:20:10.669522: Pseudo dice [0.8337] +2024-11-22 01:20:10.669603: Epoch time: 18.74 s +2024-11-22 01:20:11.597800: +2024-11-22 01:20:11.598031: Epoch 2627 +2024-11-22 01:20:11.598156: Current learning rate: 0.00699 +2024-11-22 01:20:30.692159: train_loss -0.7582 +2024-11-22 01:20:30.696730: val_loss -0.7377 +2024-11-22 01:20:30.696921: Pseudo dice [0.8348] +2024-11-22 01:20:30.697022: Epoch time: 19.1 s +2024-11-22 01:20:31.522512: +2024-11-22 01:20:31.522700: Epoch 2628 +2024-11-22 01:20:31.522823: Current learning rate: 0.00699 +2024-11-22 01:20:51.132503: train_loss -0.7708 +2024-11-22 01:20:51.134807: val_loss -0.7584 +2024-11-22 01:20:51.134908: Pseudo dice [0.8415] +2024-11-22 01:20:51.135002: Epoch time: 19.61 s +2024-11-22 01:20:51.958404: +2024-11-22 01:20:51.958603: Epoch 2629 +2024-11-22 01:20:51.958733: Current learning rate: 0.00699 +2024-11-22 01:21:10.546952: train_loss -0.7702 +2024-11-22 01:21:10.548775: val_loss -0.7519 +2024-11-22 01:21:10.548875: Pseudo dice [0.8467] +2024-11-22 01:21:10.548958: Epoch time: 18.59 s +2024-11-22 01:21:11.369633: +2024-11-22 01:21:11.369810: Epoch 2630 +2024-11-22 01:21:11.369924: Current learning rate: 0.00699 +2024-11-22 01:21:29.184131: train_loss -0.7765 +2024-11-22 01:21:29.212446: val_loss -0.7506 +2024-11-22 01:21:29.212623: Pseudo dice [0.8346] +2024-11-22 01:21:29.212724: Epoch time: 17.82 s +2024-11-22 01:21:30.079630: +2024-11-22 01:21:30.079832: Epoch 2631 +2024-11-22 01:21:30.079962: Current learning rate: 0.00698 +2024-11-22 01:21:49.760608: train_loss -0.7617 +2024-11-22 01:21:49.762904: val_loss -0.7658 +2024-11-22 01:21:49.763011: Pseudo dice [0.8485] +2024-11-22 01:21:49.763113: Epoch time: 19.68 s +2024-11-22 01:21:50.583367: +2024-11-22 01:21:50.583575: Epoch 2632 +2024-11-22 01:21:50.583711: Current learning rate: 0.00698 +2024-11-22 01:22:09.279880: train_loss -0.7704 +2024-11-22 01:22:09.286776: val_loss -0.7517 +2024-11-22 01:22:09.286925: Pseudo dice [0.8501] +2024-11-22 01:22:09.287008: Epoch time: 18.7 s +2024-11-22 01:22:10.529344: +2024-11-22 01:22:10.529560: Epoch 2633 +2024-11-22 01:22:10.529682: Current learning rate: 0.00698 +2024-11-22 01:22:30.203815: train_loss -0.7682 +2024-11-22 01:22:30.216549: val_loss -0.7613 +2024-11-22 01:22:30.216694: Pseudo dice [0.8398] +2024-11-22 01:22:30.216784: Epoch time: 19.68 s +2024-11-22 01:22:31.071369: +2024-11-22 01:22:31.071592: Epoch 2634 +2024-11-22 01:22:31.071729: Current learning rate: 0.00698 +2024-11-22 01:22:49.930407: train_loss -0.7641 +2024-11-22 01:22:49.938221: val_loss -0.7748 +2024-11-22 01:22:49.938353: Pseudo dice [0.8547] +2024-11-22 01:22:49.938462: Epoch time: 18.86 s +2024-11-22 01:22:50.794282: +2024-11-22 01:22:50.794529: Epoch 2635 +2024-11-22 01:22:50.794653: Current learning rate: 0.00698 +2024-11-22 01:23:09.974043: train_loss -0.7747 +2024-11-22 01:23:09.980485: val_loss -0.7476 +2024-11-22 01:23:09.980635: Pseudo dice [0.8388] +2024-11-22 01:23:09.980744: Epoch time: 19.18 s +2024-11-22 01:23:10.830154: +2024-11-22 01:23:10.830355: Epoch 2636 +2024-11-22 01:23:10.830489: Current learning rate: 0.00698 +2024-11-22 01:23:29.862606: train_loss -0.7677 +2024-11-22 01:23:29.868656: val_loss -0.7509 +2024-11-22 01:23:29.868793: Pseudo dice [0.843] +2024-11-22 01:23:29.868886: Epoch time: 19.03 s +2024-11-22 01:23:30.815177: +2024-11-22 01:23:30.815374: Epoch 2637 +2024-11-22 01:23:30.815495: Current learning rate: 0.00698 +2024-11-22 01:23:48.354886: train_loss -0.7734 +2024-11-22 01:23:48.361040: val_loss -0.777 +2024-11-22 01:23:48.361170: Pseudo dice [0.8564] +2024-11-22 01:23:48.361260: Epoch time: 17.54 s +2024-11-22 01:23:49.324569: +2024-11-22 01:23:49.324775: Epoch 2638 +2024-11-22 01:23:49.324893: Current learning rate: 0.00698 +2024-11-22 01:24:08.724688: train_loss -0.7817 +2024-11-22 01:24:08.730481: val_loss -0.7586 +2024-11-22 01:24:08.730671: Pseudo dice [0.842] +2024-11-22 01:24:08.730998: Epoch time: 19.4 s +2024-11-22 01:24:09.571256: +2024-11-22 01:24:09.571477: Epoch 2639 +2024-11-22 01:24:09.571590: Current learning rate: 0.00697 +2024-11-22 01:24:28.807452: train_loss -0.7617 +2024-11-22 01:24:28.812510: val_loss -0.7519 +2024-11-22 01:24:28.812621: Pseudo dice [0.8443] +2024-11-22 01:24:28.812713: Epoch time: 19.24 s +2024-11-22 01:24:29.689867: +2024-11-22 01:24:29.690082: Epoch 2640 +2024-11-22 01:24:29.690214: Current learning rate: 0.00697 +2024-11-22 01:24:48.330729: train_loss -0.7808 +2024-11-22 01:24:48.344205: val_loss -0.7661 +2024-11-22 01:24:48.344354: Pseudo dice [0.836] +2024-11-22 01:24:48.344460: Epoch time: 18.64 s +2024-11-22 01:24:49.246540: +2024-11-22 01:24:49.246774: Epoch 2641 +2024-11-22 01:24:49.246890: Current learning rate: 0.00697 +2024-11-22 01:25:09.200413: train_loss -0.7818 +2024-11-22 01:25:09.205679: val_loss -0.7668 +2024-11-22 01:25:09.205836: Pseudo dice [0.8552] +2024-11-22 01:25:09.205940: Epoch time: 19.95 s +2024-11-22 01:25:10.057092: +2024-11-22 01:25:10.057303: Epoch 2642 +2024-11-22 01:25:10.057437: Current learning rate: 0.00697 +2024-11-22 01:25:29.615141: train_loss -0.7816 +2024-11-22 01:25:29.619493: val_loss -0.7624 +2024-11-22 01:25:29.619668: Pseudo dice [0.8413] +2024-11-22 01:25:29.619780: Epoch time: 19.56 s +2024-11-22 01:25:30.446200: +2024-11-22 01:25:30.446399: Epoch 2643 +2024-11-22 01:25:30.446519: Current learning rate: 0.00697 +2024-11-22 01:25:50.597457: train_loss -0.7841 +2024-11-22 01:25:50.610157: val_loss -0.7672 +2024-11-22 01:25:50.610311: Pseudo dice [0.8518] +2024-11-22 01:25:50.610413: Epoch time: 20.15 s +2024-11-22 01:25:51.663830: +2024-11-22 01:25:51.664025: Epoch 2644 +2024-11-22 01:25:51.664169: Current learning rate: 0.00697 +2024-11-22 01:26:11.042537: train_loss -0.7773 +2024-11-22 01:26:11.048524: val_loss -0.7834 +2024-11-22 01:26:11.056369: Pseudo dice [0.852] +2024-11-22 01:26:11.056554: Epoch time: 19.38 s +2024-11-22 01:26:12.364784: +2024-11-22 01:26:12.365033: Epoch 2645 +2024-11-22 01:26:12.365159: Current learning rate: 0.00697 +2024-11-22 01:26:31.865623: train_loss -0.7778 +2024-11-22 01:26:31.871937: val_loss -0.7388 +2024-11-22 01:26:31.872104: Pseudo dice [0.851] +2024-11-22 01:26:31.872240: Epoch time: 19.5 s +2024-11-22 01:26:32.791481: +2024-11-22 01:26:32.791706: Epoch 2646 +2024-11-22 01:26:32.791842: Current learning rate: 0.00697 +2024-11-22 01:26:51.171067: train_loss -0.7727 +2024-11-22 01:26:51.174268: val_loss -0.7697 +2024-11-22 01:26:51.174399: Pseudo dice [0.8507] +2024-11-22 01:26:51.174497: Epoch time: 18.38 s +2024-11-22 01:26:52.204999: +2024-11-22 01:26:52.205206: Epoch 2647 +2024-11-22 01:26:52.205322: Current learning rate: 0.00697 +2024-11-22 01:27:10.873208: train_loss -0.7815 +2024-11-22 01:27:10.882838: val_loss -0.7614 +2024-11-22 01:27:10.883002: Pseudo dice [0.8478] +2024-11-22 01:27:10.883111: Epoch time: 18.67 s +2024-11-22 01:27:11.718428: +2024-11-22 01:27:11.718691: Epoch 2648 +2024-11-22 01:27:11.718814: Current learning rate: 0.00696 +2024-11-22 01:27:30.394789: train_loss -0.7649 +2024-11-22 01:27:30.401605: val_loss -0.7692 +2024-11-22 01:27:30.401742: Pseudo dice [0.8543] +2024-11-22 01:27:30.401826: Epoch time: 18.68 s +2024-11-22 01:27:31.314146: +2024-11-22 01:27:31.314340: Epoch 2649 +2024-11-22 01:27:31.314502: Current learning rate: 0.00696 +2024-11-22 01:27:50.448037: train_loss -0.7804 +2024-11-22 01:27:50.449744: val_loss -0.7737 +2024-11-22 01:27:50.449847: Pseudo dice [0.8617] +2024-11-22 01:27:50.449948: Epoch time: 19.13 s +2024-11-22 01:27:51.504357: +2024-11-22 01:27:51.504569: Epoch 2650 +2024-11-22 01:27:51.504695: Current learning rate: 0.00696 +2024-11-22 01:28:10.004700: train_loss -0.7716 +2024-11-22 01:28:10.012379: val_loss -0.7067 +2024-11-22 01:28:10.012519: Pseudo dice [0.8362] +2024-11-22 01:28:10.012602: Epoch time: 18.5 s +2024-11-22 01:28:10.840507: +2024-11-22 01:28:10.840713: Epoch 2651 +2024-11-22 01:28:10.840838: Current learning rate: 0.00696 +2024-11-22 01:28:29.756090: train_loss -0.7584 +2024-11-22 01:28:29.760855: val_loss -0.7417 +2024-11-22 01:28:29.761015: Pseudo dice [0.8553] +2024-11-22 01:28:29.761114: Epoch time: 18.92 s +2024-11-22 01:28:30.612094: +2024-11-22 01:28:30.612304: Epoch 2652 +2024-11-22 01:28:30.612436: Current learning rate: 0.00696 +2024-11-22 01:28:48.995080: train_loss -0.7668 +2024-11-22 01:28:48.997782: val_loss -0.7476 +2024-11-22 01:28:48.997918: Pseudo dice [0.8332] +2024-11-22 01:28:48.998003: Epoch time: 18.38 s +2024-11-22 01:28:49.921410: +2024-11-22 01:28:49.921625: Epoch 2653 +2024-11-22 01:28:49.921747: Current learning rate: 0.00696 +2024-11-22 01:29:08.925004: train_loss -0.7584 +2024-11-22 01:29:08.927472: val_loss -0.7613 +2024-11-22 01:29:08.927567: Pseudo dice [0.8415] +2024-11-22 01:29:08.927653: Epoch time: 19.0 s +2024-11-22 01:29:09.753802: +2024-11-22 01:29:09.753993: Epoch 2654 +2024-11-22 01:29:09.754123: Current learning rate: 0.00696 +2024-11-22 01:29:28.786848: train_loss -0.7681 +2024-11-22 01:29:28.792187: val_loss -0.7704 +2024-11-22 01:29:28.792340: Pseudo dice [0.8439] +2024-11-22 01:29:28.792547: Epoch time: 19.03 s +2024-11-22 01:29:29.654420: +2024-11-22 01:29:29.654652: Epoch 2655 +2024-11-22 01:29:29.654783: Current learning rate: 0.00696 +2024-11-22 01:29:48.435442: train_loss -0.7693 +2024-11-22 01:29:48.442610: val_loss -0.7651 +2024-11-22 01:29:48.442773: Pseudo dice [0.8405] +2024-11-22 01:29:48.442873: Epoch time: 18.78 s +2024-11-22 01:29:49.314428: +2024-11-22 01:29:49.314636: Epoch 2656 +2024-11-22 01:29:49.314748: Current learning rate: 0.00696 +2024-11-22 01:30:08.682593: train_loss -0.7709 +2024-11-22 01:30:08.687256: val_loss -0.7444 +2024-11-22 01:30:08.687398: Pseudo dice [0.8537] +2024-11-22 01:30:08.687488: Epoch time: 19.37 s +2024-11-22 01:30:09.529967: +2024-11-22 01:30:09.530420: Epoch 2657 +2024-11-22 01:30:09.530577: Current learning rate: 0.00695 +2024-11-22 01:30:28.052412: train_loss -0.7602 +2024-11-22 01:30:28.054904: val_loss -0.7703 +2024-11-22 01:30:28.055012: Pseudo dice [0.846] +2024-11-22 01:30:28.055107: Epoch time: 18.52 s +2024-11-22 01:30:28.877432: +2024-11-22 01:30:28.877893: Epoch 2658 +2024-11-22 01:30:28.878057: Current learning rate: 0.00695 +2024-11-22 01:30:47.240158: train_loss -0.7517 +2024-11-22 01:30:47.246996: val_loss -0.7816 +2024-11-22 01:30:47.247153: Pseudo dice [0.8435] +2024-11-22 01:30:47.247253: Epoch time: 18.36 s +2024-11-22 01:30:48.091033: +2024-11-22 01:30:48.091473: Epoch 2659 +2024-11-22 01:30:48.091614: Current learning rate: 0.00695 +2024-11-22 01:31:07.421614: train_loss -0.7623 +2024-11-22 01:31:07.424362: val_loss -0.7682 +2024-11-22 01:31:07.424508: Pseudo dice [0.8496] +2024-11-22 01:31:07.424597: Epoch time: 19.33 s +2024-11-22 01:31:08.543752: +2024-11-22 01:31:08.544230: Epoch 2660 +2024-11-22 01:31:08.544414: Current learning rate: 0.00695 +2024-11-22 01:31:27.778409: train_loss -0.7649 +2024-11-22 01:31:27.790226: val_loss -0.7828 +2024-11-22 01:31:27.790336: Pseudo dice [0.8484] +2024-11-22 01:31:27.790423: Epoch time: 19.24 s +2024-11-22 01:31:28.623527: +2024-11-22 01:31:28.623935: Epoch 2661 +2024-11-22 01:31:28.624081: Current learning rate: 0.00695 +2024-11-22 01:31:47.727238: train_loss -0.7775 +2024-11-22 01:31:47.728842: val_loss -0.7682 +2024-11-22 01:31:47.728956: Pseudo dice [0.8554] +2024-11-22 01:31:47.729054: Epoch time: 19.1 s +2024-11-22 01:31:48.550105: +2024-11-22 01:31:48.550495: Epoch 2662 +2024-11-22 01:31:48.550633: Current learning rate: 0.00695 +2024-11-22 01:32:07.245254: train_loss -0.7714 +2024-11-22 01:32:07.249471: val_loss -0.7611 +2024-11-22 01:32:07.249629: Pseudo dice [0.8372] +2024-11-22 01:32:07.249739: Epoch time: 18.7 s +2024-11-22 01:32:08.126050: +2024-11-22 01:32:08.126267: Epoch 2663 +2024-11-22 01:32:08.126379: Current learning rate: 0.00695 +2024-11-22 01:32:27.208589: train_loss -0.7582 +2024-11-22 01:32:27.213352: val_loss -0.7602 +2024-11-22 01:32:27.213503: Pseudo dice [0.8483] +2024-11-22 01:32:27.213598: Epoch time: 19.08 s +2024-11-22 01:32:28.036251: +2024-11-22 01:32:28.036452: Epoch 2664 +2024-11-22 01:32:28.036902: Current learning rate: 0.00695 +2024-11-22 01:32:47.375235: train_loss -0.7728 +2024-11-22 01:32:47.382349: val_loss -0.7499 +2024-11-22 01:32:47.382477: Pseudo dice [0.847] +2024-11-22 01:32:47.382587: Epoch time: 19.34 s +2024-11-22 01:32:48.207257: +2024-11-22 01:32:48.207452: Epoch 2665 +2024-11-22 01:32:48.207567: Current learning rate: 0.00694 +2024-11-22 01:33:06.361660: train_loss -0.779 +2024-11-22 01:33:06.367297: val_loss -0.7798 +2024-11-22 01:33:06.367429: Pseudo dice [0.8551] +2024-11-22 01:33:06.367511: Epoch time: 18.16 s +2024-11-22 01:33:07.241993: +2024-11-22 01:33:07.242207: Epoch 2666 +2024-11-22 01:33:07.242330: Current learning rate: 0.00694 +2024-11-22 01:33:25.974911: train_loss -0.7835 +2024-11-22 01:33:25.983096: val_loss -0.7733 +2024-11-22 01:33:25.983276: Pseudo dice [0.8583] +2024-11-22 01:33:25.983384: Epoch time: 18.73 s +2024-11-22 01:33:26.822306: +2024-11-22 01:33:26.822755: Epoch 2667 +2024-11-22 01:33:26.822897: Current learning rate: 0.00694 +2024-11-22 01:33:46.003718: train_loss -0.7807 +2024-11-22 01:33:46.013175: val_loss -0.7625 +2024-11-22 01:33:46.013342: Pseudo dice [0.851] +2024-11-22 01:33:46.013428: Epoch time: 19.18 s +2024-11-22 01:33:47.235011: +2024-11-22 01:33:47.235227: Epoch 2668 +2024-11-22 01:33:47.235360: Current learning rate: 0.00694 +2024-11-22 01:34:06.820641: train_loss -0.7672 +2024-11-22 01:34:06.827917: val_loss -0.763 +2024-11-22 01:34:06.828056: Pseudo dice [0.8461] +2024-11-22 01:34:06.828172: Epoch time: 19.59 s +2024-11-22 01:34:07.842881: +2024-11-22 01:34:07.843094: Epoch 2669 +2024-11-22 01:34:07.843223: Current learning rate: 0.00694 +2024-11-22 01:34:27.145320: train_loss -0.772 +2024-11-22 01:34:27.161239: val_loss -0.7848 +2024-11-22 01:34:27.161403: Pseudo dice [0.8612] +2024-11-22 01:34:27.161493: Epoch time: 19.3 s +2024-11-22 01:34:28.005244: +2024-11-22 01:34:28.005484: Epoch 2670 +2024-11-22 01:34:28.005610: Current learning rate: 0.00694 +2024-11-22 01:34:48.110790: train_loss -0.7711 +2024-11-22 01:34:48.113725: val_loss -0.757 +2024-11-22 01:34:48.113874: Pseudo dice [0.8498] +2024-11-22 01:34:48.113963: Epoch time: 20.11 s +2024-11-22 01:34:49.003639: +2024-11-22 01:34:49.003895: Epoch 2671 +2024-11-22 01:34:49.004023: Current learning rate: 0.00694 +2024-11-22 01:35:08.786896: train_loss -0.7774 +2024-11-22 01:35:08.789049: val_loss -0.7868 +2024-11-22 01:35:08.789168: Pseudo dice [0.8675] +2024-11-22 01:35:08.789282: Epoch time: 19.78 s +2024-11-22 01:35:08.789373: Yayy! New best EMA pseudo Dice: 0.8516 +2024-11-22 01:35:09.837122: +2024-11-22 01:35:09.837370: Epoch 2672 +2024-11-22 01:35:09.837512: Current learning rate: 0.00694 +2024-11-22 01:35:27.808631: train_loss -0.7857 +2024-11-22 01:35:27.816028: val_loss -0.7693 +2024-11-22 01:35:27.816172: Pseudo dice [0.8404] +2024-11-22 01:35:27.816256: Epoch time: 17.97 s +2024-11-22 01:35:28.671990: +2024-11-22 01:35:28.672196: Epoch 2673 +2024-11-22 01:35:28.672316: Current learning rate: 0.00694 +2024-11-22 01:35:47.488502: train_loss -0.7795 +2024-11-22 01:35:47.497609: val_loss -0.7471 +2024-11-22 01:35:47.497920: Pseudo dice [0.8398] +2024-11-22 01:35:47.498238: Epoch time: 18.82 s +2024-11-22 01:35:48.406897: +2024-11-22 01:35:48.407121: Epoch 2674 +2024-11-22 01:35:48.407243: Current learning rate: 0.00693 +2024-11-22 01:36:08.469990: train_loss -0.7698 +2024-11-22 01:36:08.472987: val_loss -0.7844 +2024-11-22 01:36:08.473106: Pseudo dice [0.8503] +2024-11-22 01:36:08.473201: Epoch time: 20.06 s +2024-11-22 01:36:09.292635: +2024-11-22 01:36:09.292845: Epoch 2675 +2024-11-22 01:36:09.292962: Current learning rate: 0.00693 +2024-11-22 01:36:28.373445: train_loss -0.7802 +2024-11-22 01:36:28.381535: val_loss -0.7807 +2024-11-22 01:36:28.381682: Pseudo dice [0.8514] +2024-11-22 01:36:28.381795: Epoch time: 19.08 s +2024-11-22 01:36:29.208446: +2024-11-22 01:36:29.208660: Epoch 2676 +2024-11-22 01:36:29.208780: Current learning rate: 0.00693 +2024-11-22 01:36:48.234050: train_loss -0.7774 +2024-11-22 01:36:48.237190: val_loss -0.7596 +2024-11-22 01:36:48.237327: Pseudo dice [0.8594] +2024-11-22 01:36:48.237722: Epoch time: 19.03 s +2024-11-22 01:36:49.062318: +2024-11-22 01:36:49.062499: Epoch 2677 +2024-11-22 01:36:49.062625: Current learning rate: 0.00693 +2024-11-22 01:37:08.111483: train_loss -0.765 +2024-11-22 01:37:08.128406: val_loss -0.7601 +2024-11-22 01:37:08.128569: Pseudo dice [0.847] +2024-11-22 01:37:08.128672: Epoch time: 19.05 s +2024-11-22 01:37:09.131066: +2024-11-22 01:37:09.131495: Epoch 2678 +2024-11-22 01:37:09.131640: Current learning rate: 0.00693 +2024-11-22 01:37:28.209665: train_loss -0.7711 +2024-11-22 01:37:28.223688: val_loss -0.7397 +2024-11-22 01:37:28.223867: Pseudo dice [0.8489] +2024-11-22 01:37:28.223978: Epoch time: 19.08 s +2024-11-22 01:37:29.212988: +2024-11-22 01:37:29.213202: Epoch 2679 +2024-11-22 01:37:29.213324: Current learning rate: 0.00693 +2024-11-22 01:37:48.321410: train_loss -0.7703 +2024-11-22 01:37:48.326840: val_loss -0.759 +2024-11-22 01:37:48.326980: Pseudo dice [0.8397] +2024-11-22 01:37:48.327083: Epoch time: 19.11 s +2024-11-22 01:37:49.279741: +2024-11-22 01:37:49.280202: Epoch 2680 +2024-11-22 01:37:49.280324: Current learning rate: 0.00693 +2024-11-22 01:38:07.688631: train_loss -0.7773 +2024-11-22 01:38:07.697502: val_loss -0.7597 +2024-11-22 01:38:07.697619: Pseudo dice [0.858] +2024-11-22 01:38:07.697789: Epoch time: 18.41 s +2024-11-22 01:38:08.666904: +2024-11-22 01:38:08.667130: Epoch 2681 +2024-11-22 01:38:08.667257: Current learning rate: 0.00693 +2024-11-22 01:38:27.492708: train_loss -0.7771 +2024-11-22 01:38:27.496946: val_loss -0.7669 +2024-11-22 01:38:27.497086: Pseudo dice [0.8544] +2024-11-22 01:38:27.497195: Epoch time: 18.83 s +2024-11-22 01:38:28.404851: +2024-11-22 01:38:28.405076: Epoch 2682 +2024-11-22 01:38:28.405195: Current learning rate: 0.00692 +2024-11-22 01:38:46.770364: train_loss -0.7722 +2024-11-22 01:38:46.780321: val_loss -0.7427 +2024-11-22 01:38:46.780466: Pseudo dice [0.8657] +2024-11-22 01:38:46.780562: Epoch time: 18.37 s +2024-11-22 01:38:46.780646: Yayy! New best EMA pseudo Dice: 0.852 +2024-11-22 01:38:47.877489: +2024-11-22 01:38:47.877702: Epoch 2683 +2024-11-22 01:38:47.877828: Current learning rate: 0.00692 +2024-11-22 01:39:06.399633: train_loss -0.7758 +2024-11-22 01:39:06.406750: val_loss -0.7932 +2024-11-22 01:39:06.406871: Pseudo dice [0.8597] +2024-11-22 01:39:06.406959: Epoch time: 18.52 s +2024-11-22 01:39:06.407035: Yayy! New best EMA pseudo Dice: 0.8527 +2024-11-22 01:39:07.515911: +2024-11-22 01:39:07.516152: Epoch 2684 +2024-11-22 01:39:07.516277: Current learning rate: 0.00692 +2024-11-22 01:39:27.585157: train_loss -0.7859 +2024-11-22 01:39:27.591047: val_loss -0.7729 +2024-11-22 01:39:27.591223: Pseudo dice [0.8406] +2024-11-22 01:39:27.591329: Epoch time: 20.07 s +2024-11-22 01:39:28.414815: +2024-11-22 01:39:28.415031: Epoch 2685 +2024-11-22 01:39:28.415178: Current learning rate: 0.00692 +2024-11-22 01:39:48.049781: train_loss -0.7714 +2024-11-22 01:39:48.055032: val_loss -0.7909 +2024-11-22 01:39:48.055184: Pseudo dice [0.8472] +2024-11-22 01:39:48.055279: Epoch time: 19.64 s +2024-11-22 01:39:48.954512: +2024-11-22 01:39:48.954766: Epoch 2686 +2024-11-22 01:39:48.954885: Current learning rate: 0.00692 +2024-11-22 01:40:08.918239: train_loss -0.7669 +2024-11-22 01:40:08.925008: val_loss -0.7526 +2024-11-22 01:40:08.925144: Pseudo dice [0.8518] +2024-11-22 01:40:08.925249: Epoch time: 19.96 s +2024-11-22 01:40:09.771570: +2024-11-22 01:40:09.771772: Epoch 2687 +2024-11-22 01:40:09.771891: Current learning rate: 0.00692 +2024-11-22 01:40:28.543864: train_loss -0.777 +2024-11-22 01:40:28.551842: val_loss -0.79 +2024-11-22 01:40:28.551991: Pseudo dice [0.8567] +2024-11-22 01:40:28.552094: Epoch time: 18.77 s +2024-11-22 01:40:29.555002: +2024-11-22 01:40:29.555264: Epoch 2688 +2024-11-22 01:40:29.555392: Current learning rate: 0.00692 +2024-11-22 01:40:49.097196: train_loss -0.7708 +2024-11-22 01:40:49.099814: val_loss -0.7553 +2024-11-22 01:40:49.100009: Pseudo dice [0.8355] +2024-11-22 01:40:49.100123: Epoch time: 19.54 s +2024-11-22 01:40:49.928573: +2024-11-22 01:40:49.928789: Epoch 2689 +2024-11-22 01:40:49.928916: Current learning rate: 0.00692 +2024-11-22 01:41:08.553644: train_loss -0.7542 +2024-11-22 01:41:08.559035: val_loss -0.7668 +2024-11-22 01:41:08.559185: Pseudo dice [0.8588] +2024-11-22 01:41:08.559283: Epoch time: 18.63 s +2024-11-22 01:41:09.563473: +2024-11-22 01:41:09.563693: Epoch 2690 +2024-11-22 01:41:09.563816: Current learning rate: 0.00692 +2024-11-22 01:41:29.062909: train_loss -0.7766 +2024-11-22 01:41:29.069618: val_loss -0.768 +2024-11-22 01:41:29.069758: Pseudo dice [0.8588] +2024-11-22 01:41:29.069846: Epoch time: 19.5 s +2024-11-22 01:41:30.134442: +2024-11-22 01:41:30.134696: Epoch 2691 +2024-11-22 01:41:30.134835: Current learning rate: 0.00691 +2024-11-22 01:41:49.122239: train_loss -0.7738 +2024-11-22 01:41:49.127827: val_loss -0.7637 +2024-11-22 01:41:49.127960: Pseudo dice [0.8497] +2024-11-22 01:41:49.128048: Epoch time: 18.99 s +2024-11-22 01:41:49.955981: +2024-11-22 01:41:49.956204: Epoch 2692 +2024-11-22 01:41:49.956323: Current learning rate: 0.00691 +2024-11-22 01:42:09.033010: train_loss -0.7657 +2024-11-22 01:42:09.035800: val_loss -0.7548 +2024-11-22 01:42:09.035929: Pseudo dice [0.8419] +2024-11-22 01:42:09.036024: Epoch time: 19.08 s +2024-11-22 01:42:09.918336: +2024-11-22 01:42:09.918554: Epoch 2693 +2024-11-22 01:42:09.918684: Current learning rate: 0.00691 +2024-11-22 01:42:28.615750: train_loss -0.774 +2024-11-22 01:42:28.627063: val_loss -0.7703 +2024-11-22 01:42:28.627210: Pseudo dice [0.8433] +2024-11-22 01:42:28.627318: Epoch time: 18.7 s +2024-11-22 01:42:29.490983: +2024-11-22 01:42:29.491194: Epoch 2694 +2024-11-22 01:42:29.491331: Current learning rate: 0.00691 +2024-11-22 01:42:47.707622: train_loss -0.771 +2024-11-22 01:42:47.712007: val_loss -0.7508 +2024-11-22 01:42:47.712131: Pseudo dice [0.8559] +2024-11-22 01:42:47.712245: Epoch time: 18.22 s +2024-11-22 01:42:48.539332: +2024-11-22 01:42:48.539546: Epoch 2695 +2024-11-22 01:42:48.539659: Current learning rate: 0.00691 +2024-11-22 01:43:07.036664: train_loss -0.7801 +2024-11-22 01:43:07.042250: val_loss -0.7742 +2024-11-22 01:43:07.042385: Pseudo dice [0.8504] +2024-11-22 01:43:07.042488: Epoch time: 18.5 s +2024-11-22 01:43:07.971918: +2024-11-22 01:43:07.972183: Epoch 2696 +2024-11-22 01:43:07.972306: Current learning rate: 0.00691 +2024-11-22 01:43:27.026972: train_loss -0.7782 +2024-11-22 01:43:27.053362: val_loss -0.7443 +2024-11-22 01:43:27.053491: Pseudo dice [0.8556] +2024-11-22 01:43:27.053574: Epoch time: 19.06 s +2024-11-22 01:43:28.036179: +2024-11-22 01:43:28.036374: Epoch 2697 +2024-11-22 01:43:28.036502: Current learning rate: 0.00691 +2024-11-22 01:43:46.504621: train_loss -0.7764 +2024-11-22 01:43:46.509419: val_loss -0.763 +2024-11-22 01:43:46.509574: Pseudo dice [0.8378] +2024-11-22 01:43:46.509673: Epoch time: 18.47 s +2024-11-22 01:43:47.336206: +2024-11-22 01:43:47.336421: Epoch 2698 +2024-11-22 01:43:47.336558: Current learning rate: 0.00691 +2024-11-22 01:44:06.029109: train_loss -0.7608 +2024-11-22 01:44:06.035097: val_loss -0.7652 +2024-11-22 01:44:06.035238: Pseudo dice [0.8424] +2024-11-22 01:44:06.035343: Epoch time: 18.69 s +2024-11-22 01:44:06.891048: +2024-11-22 01:44:06.891280: Epoch 2699 +2024-11-22 01:44:06.891405: Current learning rate: 0.0069 +2024-11-22 01:44:25.942799: train_loss -0.7796 +2024-11-22 01:44:25.945204: val_loss -0.7653 +2024-11-22 01:44:25.945317: Pseudo dice [0.85] +2024-11-22 01:44:25.945418: Epoch time: 19.05 s +2024-11-22 01:44:26.993570: +2024-11-22 01:44:26.993775: Epoch 2700 +2024-11-22 01:44:26.993910: Current learning rate: 0.0069 +2024-11-22 01:44:45.525386: train_loss -0.7716 +2024-11-22 01:44:45.527599: val_loss -0.7623 +2024-11-22 01:44:45.527753: Pseudo dice [0.8446] +2024-11-22 01:44:45.527867: Epoch time: 18.53 s +2024-11-22 01:44:46.354909: +2024-11-22 01:44:46.355117: Epoch 2701 +2024-11-22 01:44:46.355243: Current learning rate: 0.0069 +2024-11-22 01:45:05.951330: train_loss -0.7823 +2024-11-22 01:45:05.955222: val_loss -0.7778 +2024-11-22 01:45:05.955370: Pseudo dice [0.8439] +2024-11-22 01:45:05.962182: Epoch time: 19.6 s +2024-11-22 01:45:07.208568: +2024-11-22 01:45:07.208802: Epoch 2702 +2024-11-22 01:45:07.208917: Current learning rate: 0.0069 +2024-11-22 01:45:25.526041: train_loss -0.7813 +2024-11-22 01:45:25.532081: val_loss -0.7819 +2024-11-22 01:45:25.532236: Pseudo dice [0.8617] +2024-11-22 01:45:25.532331: Epoch time: 18.32 s +2024-11-22 01:45:26.365269: +2024-11-22 01:45:26.365496: Epoch 2703 +2024-11-22 01:45:26.365631: Current learning rate: 0.0069 +2024-11-22 01:45:44.506360: train_loss -0.7688 +2024-11-22 01:45:44.514072: val_loss -0.7537 +2024-11-22 01:45:44.514211: Pseudo dice [0.8365] +2024-11-22 01:45:44.514303: Epoch time: 18.14 s +2024-11-22 01:45:45.439092: +2024-11-22 01:45:45.439324: Epoch 2704 +2024-11-22 01:45:45.439453: Current learning rate: 0.0069 +2024-11-22 01:46:04.403651: train_loss -0.768 +2024-11-22 01:46:04.409541: val_loss -0.7475 +2024-11-22 01:46:04.409698: Pseudo dice [0.847] +2024-11-22 01:46:04.409806: Epoch time: 18.97 s +2024-11-22 01:46:05.404133: +2024-11-22 01:46:05.404356: Epoch 2705 +2024-11-22 01:46:05.404483: Current learning rate: 0.0069 +2024-11-22 01:46:25.195194: train_loss -0.7738 +2024-11-22 01:46:25.208244: val_loss -0.744 +2024-11-22 01:46:25.208388: Pseudo dice [0.8403] +2024-11-22 01:46:25.208486: Epoch time: 19.79 s +2024-11-22 01:46:26.149485: +2024-11-22 01:46:26.149706: Epoch 2706 +2024-11-22 01:46:26.149838: Current learning rate: 0.0069 +2024-11-22 01:46:45.243714: train_loss -0.7725 +2024-11-22 01:46:45.256357: val_loss -0.7639 +2024-11-22 01:46:45.256527: Pseudo dice [0.8458] +2024-11-22 01:46:45.256626: Epoch time: 19.1 s +2024-11-22 01:46:46.126987: +2024-11-22 01:46:46.127191: Epoch 2707 +2024-11-22 01:46:46.127316: Current learning rate: 0.0069 +2024-11-22 01:47:05.203998: train_loss -0.7765 +2024-11-22 01:47:05.208997: val_loss -0.7578 +2024-11-22 01:47:05.209144: Pseudo dice [0.8542] +2024-11-22 01:47:05.209237: Epoch time: 19.08 s +2024-11-22 01:47:06.068866: +2024-11-22 01:47:06.069078: Epoch 2708 +2024-11-22 01:47:06.069211: Current learning rate: 0.00689 +2024-11-22 01:47:25.915480: train_loss -0.7771 +2024-11-22 01:47:25.918355: val_loss -0.7692 +2024-11-22 01:47:25.918476: Pseudo dice [0.8521] +2024-11-22 01:47:25.918586: Epoch time: 19.85 s +2024-11-22 01:47:26.749762: +2024-11-22 01:47:26.749982: Epoch 2709 +2024-11-22 01:47:26.750113: Current learning rate: 0.00689 +2024-11-22 01:47:46.216087: train_loss -0.7762 +2024-11-22 01:47:46.223998: val_loss -0.7689 +2024-11-22 01:47:46.224142: Pseudo dice [0.8617] +2024-11-22 01:47:46.224224: Epoch time: 19.47 s +2024-11-22 01:47:47.208093: +2024-11-22 01:47:47.208315: Epoch 2710 +2024-11-22 01:47:47.208453: Current learning rate: 0.00689 +2024-11-22 01:48:05.937959: train_loss -0.7694 +2024-11-22 01:48:05.945469: val_loss -0.7799 +2024-11-22 01:48:05.945624: Pseudo dice [0.8521] +2024-11-22 01:48:05.945717: Epoch time: 18.73 s +2024-11-22 01:48:06.926318: +2024-11-22 01:48:06.926536: Epoch 2711 +2024-11-22 01:48:06.926664: Current learning rate: 0.00689 +2024-11-22 01:48:26.067569: train_loss -0.7773 +2024-11-22 01:48:26.072945: val_loss -0.7551 +2024-11-22 01:48:26.073076: Pseudo dice [0.8478] +2024-11-22 01:48:26.073207: Epoch time: 19.14 s +2024-11-22 01:48:26.976547: +2024-11-22 01:48:26.976954: Epoch 2712 +2024-11-22 01:48:26.977099: Current learning rate: 0.00689 +2024-11-22 01:48:45.064023: train_loss -0.7795 +2024-11-22 01:48:45.071771: val_loss -0.774 +2024-11-22 01:48:45.071909: Pseudo dice [0.8659] +2024-11-22 01:48:45.072000: Epoch time: 18.09 s +2024-11-22 01:48:46.082768: +2024-11-22 01:48:46.082967: Epoch 2713 +2024-11-22 01:48:46.083092: Current learning rate: 0.00689 +2024-11-22 01:49:05.595870: train_loss -0.7671 +2024-11-22 01:49:05.622652: val_loss -0.7728 +2024-11-22 01:49:05.622785: Pseudo dice [0.8469] +2024-11-22 01:49:05.622901: Epoch time: 19.51 s +2024-11-22 01:49:06.888941: +2024-11-22 01:49:06.889159: Epoch 2714 +2024-11-22 01:49:06.889279: Current learning rate: 0.00689 +2024-11-22 01:49:25.803252: train_loss -0.7791 +2024-11-22 01:49:25.834851: val_loss -0.7745 +2024-11-22 01:49:25.835048: Pseudo dice [0.8581] +2024-11-22 01:49:25.835172: Epoch time: 18.92 s +2024-11-22 01:49:26.865186: +2024-11-22 01:49:26.865451: Epoch 2715 +2024-11-22 01:49:26.865606: Current learning rate: 0.00689 +2024-11-22 01:49:45.744556: train_loss -0.7757 +2024-11-22 01:49:45.752154: val_loss -0.7574 +2024-11-22 01:49:45.752307: Pseudo dice [0.8471] +2024-11-22 01:49:45.752419: Epoch time: 18.88 s +2024-11-22 01:49:46.777587: +2024-11-22 01:49:46.777813: Epoch 2716 +2024-11-22 01:49:46.777928: Current learning rate: 0.00688 +2024-11-22 01:50:07.108539: train_loss -0.7722 +2024-11-22 01:50:07.116536: val_loss -0.7485 +2024-11-22 01:50:07.116688: Pseudo dice [0.8373] +2024-11-22 01:50:07.116777: Epoch time: 20.33 s +2024-11-22 01:50:07.958825: +2024-11-22 01:50:07.959050: Epoch 2717 +2024-11-22 01:50:07.959191: Current learning rate: 0.00688 +2024-11-22 01:50:25.992750: train_loss -0.7741 +2024-11-22 01:50:26.003906: val_loss -0.7684 +2024-11-22 01:50:26.004095: Pseudo dice [0.8492] +2024-11-22 01:50:26.004186: Epoch time: 18.03 s +2024-11-22 01:50:26.976865: +2024-11-22 01:50:26.977093: Epoch 2718 +2024-11-22 01:50:26.977247: Current learning rate: 0.00688 +2024-11-22 01:50:46.797537: train_loss -0.7775 +2024-11-22 01:50:46.801148: val_loss -0.7765 +2024-11-22 01:50:46.801274: Pseudo dice [0.8582] +2024-11-22 01:50:46.801396: Epoch time: 19.81 s +2024-11-22 01:50:47.649868: +2024-11-22 01:50:47.650086: Epoch 2719 +2024-11-22 01:50:47.650203: Current learning rate: 0.00688 +2024-11-22 01:51:06.655801: train_loss -0.7711 +2024-11-22 01:51:06.666283: val_loss -0.7697 +2024-11-22 01:51:06.666487: Pseudo dice [0.8384] +2024-11-22 01:51:06.666602: Epoch time: 19.01 s +2024-11-22 01:51:07.494227: +2024-11-22 01:51:07.494451: Epoch 2720 +2024-11-22 01:51:07.494582: Current learning rate: 0.00688 +2024-11-22 01:51:26.186285: train_loss -0.7809 +2024-11-22 01:51:26.190053: val_loss -0.7758 +2024-11-22 01:51:26.190195: Pseudo dice [0.8607] +2024-11-22 01:51:26.190284: Epoch time: 18.69 s +2024-11-22 01:51:27.111537: +2024-11-22 01:51:27.111734: Epoch 2721 +2024-11-22 01:51:27.111857: Current learning rate: 0.00688 +2024-11-22 01:51:45.366901: train_loss -0.77 +2024-11-22 01:51:45.372585: val_loss -0.7429 +2024-11-22 01:51:45.372730: Pseudo dice [0.8351] +2024-11-22 01:51:45.372830: Epoch time: 18.26 s +2024-11-22 01:51:46.448828: +2024-11-22 01:51:46.449041: Epoch 2722 +2024-11-22 01:51:46.449166: Current learning rate: 0.00688 +2024-11-22 01:52:05.415318: train_loss -0.7721 +2024-11-22 01:52:05.423586: val_loss -0.776 +2024-11-22 01:52:05.423727: Pseudo dice [0.8511] +2024-11-22 01:52:05.423821: Epoch time: 18.97 s +2024-11-22 01:52:06.267715: +2024-11-22 01:52:06.267912: Epoch 2723 +2024-11-22 01:52:06.268034: Current learning rate: 0.00688 +2024-11-22 01:52:25.926333: train_loss -0.7684 +2024-11-22 01:52:25.934619: val_loss -0.762 +2024-11-22 01:52:25.934757: Pseudo dice [0.84] +2024-11-22 01:52:25.934857: Epoch time: 19.66 s +2024-11-22 01:52:26.944368: +2024-11-22 01:52:26.944570: Epoch 2724 +2024-11-22 01:52:26.944691: Current learning rate: 0.00688 +2024-11-22 01:52:47.366301: train_loss -0.7798 +2024-11-22 01:52:47.372985: val_loss -0.7681 +2024-11-22 01:52:47.373135: Pseudo dice [0.8466] +2024-11-22 01:52:47.373229: Epoch time: 20.42 s +2024-11-22 01:52:48.229952: +2024-11-22 01:52:48.230158: Epoch 2725 +2024-11-22 01:52:48.230283: Current learning rate: 0.00687 +2024-11-22 01:53:07.574804: train_loss -0.7788 +2024-11-22 01:53:07.596661: val_loss -0.7758 +2024-11-22 01:53:07.596833: Pseudo dice [0.8435] +2024-11-22 01:53:07.596953: Epoch time: 19.35 s +2024-11-22 01:53:08.495097: +2024-11-22 01:53:08.495296: Epoch 2726 +2024-11-22 01:53:08.495412: Current learning rate: 0.00687 +2024-11-22 01:53:28.052903: train_loss -0.7712 +2024-11-22 01:53:28.055340: val_loss -0.7788 +2024-11-22 01:53:28.055441: Pseudo dice [0.8509] +2024-11-22 01:53:28.055537: Epoch time: 19.56 s +2024-11-22 01:53:28.873473: +2024-11-22 01:53:28.873721: Epoch 2727 +2024-11-22 01:53:28.874076: Current learning rate: 0.00687 +2024-11-22 01:53:47.434271: train_loss -0.7829 +2024-11-22 01:53:47.445139: val_loss -0.7792 +2024-11-22 01:53:47.445287: Pseudo dice [0.8499] +2024-11-22 01:53:47.445383: Epoch time: 18.56 s +2024-11-22 01:53:48.362523: +2024-11-22 01:53:48.362725: Epoch 2728 +2024-11-22 01:53:48.362847: Current learning rate: 0.00687 +2024-11-22 01:54:07.096146: train_loss -0.7763 +2024-11-22 01:54:07.102152: val_loss -0.7416 +2024-11-22 01:54:07.102301: Pseudo dice [0.85] +2024-11-22 01:54:07.102407: Epoch time: 18.73 s +2024-11-22 01:54:07.944097: +2024-11-22 01:54:07.944317: Epoch 2729 +2024-11-22 01:54:07.944451: Current learning rate: 0.00687 +2024-11-22 01:54:28.028939: train_loss -0.776 +2024-11-22 01:54:28.035906: val_loss -0.7718 +2024-11-22 01:54:28.036079: Pseudo dice [0.8309] +2024-11-22 01:54:28.036184: Epoch time: 20.09 s +2024-11-22 01:54:28.869247: +2024-11-22 01:54:28.869462: Epoch 2730 +2024-11-22 01:54:28.869595: Current learning rate: 0.00687 +2024-11-22 01:54:48.120145: train_loss -0.7638 +2024-11-22 01:54:48.122998: val_loss -0.7995 +2024-11-22 01:54:48.123112: Pseudo dice [0.8524] +2024-11-22 01:54:48.123204: Epoch time: 19.25 s +2024-11-22 01:54:48.944569: +2024-11-22 01:54:48.944774: Epoch 2731 +2024-11-22 01:54:48.944886: Current learning rate: 0.00687 +2024-11-22 01:55:06.788365: train_loss -0.7783 +2024-11-22 01:55:06.796627: val_loss -0.7579 +2024-11-22 01:55:06.796766: Pseudo dice [0.8418] +2024-11-22 01:55:06.796858: Epoch time: 17.84 s +2024-11-22 01:55:07.652325: +2024-11-22 01:55:07.652534: Epoch 2732 +2024-11-22 01:55:07.652667: Current learning rate: 0.00687 +2024-11-22 01:55:26.349555: train_loss -0.773 +2024-11-22 01:55:26.373604: val_loss -0.774 +2024-11-22 01:55:26.373715: Pseudo dice [0.8502] +2024-11-22 01:55:26.373805: Epoch time: 18.7 s +2024-11-22 01:55:27.194366: +2024-11-22 01:55:27.194567: Epoch 2733 +2024-11-22 01:55:27.194689: Current learning rate: 0.00686 +2024-11-22 01:55:45.227934: train_loss -0.775 +2024-11-22 01:55:45.235301: val_loss -0.7482 +2024-11-22 01:55:45.235419: Pseudo dice [0.849] +2024-11-22 01:55:45.235532: Epoch time: 18.03 s +2024-11-22 01:55:46.374533: +2024-11-22 01:55:46.374727: Epoch 2734 +2024-11-22 01:55:46.374844: Current learning rate: 0.00686 +2024-11-22 01:56:04.982373: train_loss -0.7743 +2024-11-22 01:56:04.987171: val_loss -0.7425 +2024-11-22 01:56:04.987315: Pseudo dice [0.8583] +2024-11-22 01:56:04.987405: Epoch time: 18.61 s +2024-11-22 01:56:05.842438: +2024-11-22 01:56:05.842634: Epoch 2735 +2024-11-22 01:56:05.842757: Current learning rate: 0.00686 +2024-11-22 01:56:24.713436: train_loss -0.7686 +2024-11-22 01:56:24.720864: val_loss -0.7625 +2024-11-22 01:56:24.720986: Pseudo dice [0.85] +2024-11-22 01:56:24.721086: Epoch time: 18.87 s +2024-11-22 01:56:25.549553: +2024-11-22 01:56:25.549810: Epoch 2736 +2024-11-22 01:56:25.549930: Current learning rate: 0.00686 +2024-11-22 01:56:44.656891: train_loss -0.7716 +2024-11-22 01:56:44.669188: val_loss -0.7626 +2024-11-22 01:56:44.669339: Pseudo dice [0.8421] +2024-11-22 01:56:44.669436: Epoch time: 19.11 s +2024-11-22 01:56:45.911421: +2024-11-22 01:56:45.911667: Epoch 2737 +2024-11-22 01:56:45.911788: Current learning rate: 0.00686 +2024-11-22 01:57:05.105631: train_loss -0.7668 +2024-11-22 01:57:05.115811: val_loss -0.7576 +2024-11-22 01:57:05.115963: Pseudo dice [0.8599] +2024-11-22 01:57:05.116056: Epoch time: 19.2 s +2024-11-22 01:57:06.090602: +2024-11-22 01:57:06.090812: Epoch 2738 +2024-11-22 01:57:06.090952: Current learning rate: 0.00686 +2024-11-22 01:57:25.697560: train_loss -0.7829 +2024-11-22 01:57:25.705924: val_loss -0.778 +2024-11-22 01:57:25.706063: Pseudo dice [0.8534] +2024-11-22 01:57:25.706153: Epoch time: 19.61 s +2024-11-22 01:57:26.877129: +2024-11-22 01:57:26.877327: Epoch 2739 +2024-11-22 01:57:26.877451: Current learning rate: 0.00686 +2024-11-22 01:57:46.248706: train_loss -0.7699 +2024-11-22 01:57:46.260760: val_loss -0.771 +2024-11-22 01:57:46.260886: Pseudo dice [0.8545] +2024-11-22 01:57:46.261589: Epoch time: 19.37 s +2024-11-22 01:57:47.146441: +2024-11-22 01:57:47.146670: Epoch 2740 +2024-11-22 01:57:47.146805: Current learning rate: 0.00686 +2024-11-22 01:58:06.766521: train_loss -0.7751 +2024-11-22 01:58:06.773722: val_loss -0.771 +2024-11-22 01:58:06.773847: Pseudo dice [0.8411] +2024-11-22 01:58:06.773936: Epoch time: 19.62 s +2024-11-22 01:58:07.622251: +2024-11-22 01:58:07.622472: Epoch 2741 +2024-11-22 01:58:07.622598: Current learning rate: 0.00686 +2024-11-22 01:58:26.116445: train_loss -0.7805 +2024-11-22 01:58:26.124115: val_loss -0.764 +2024-11-22 01:58:26.124236: Pseudo dice [0.8421] +2024-11-22 01:58:26.124342: Epoch time: 18.5 s +2024-11-22 01:58:26.946922: +2024-11-22 01:58:26.947160: Epoch 2742 +2024-11-22 01:58:26.947290: Current learning rate: 0.00685 +2024-11-22 01:58:47.707434: train_loss -0.7791 +2024-11-22 01:58:47.710255: val_loss -0.7493 +2024-11-22 01:58:47.710366: Pseudo dice [0.8418] +2024-11-22 01:58:47.710468: Epoch time: 20.76 s +2024-11-22 01:58:48.532435: +2024-11-22 01:58:48.532635: Epoch 2743 +2024-11-22 01:58:48.532771: Current learning rate: 0.00685 +2024-11-22 01:59:06.907465: train_loss -0.7727 +2024-11-22 01:59:06.915885: val_loss -0.7926 +2024-11-22 01:59:06.916019: Pseudo dice [0.8728] +2024-11-22 01:59:06.916117: Epoch time: 18.38 s +2024-11-22 01:59:07.737899: +2024-11-22 01:59:07.738116: Epoch 2744 +2024-11-22 01:59:07.738244: Current learning rate: 0.00685 +2024-11-22 01:59:27.664164: train_loss -0.775 +2024-11-22 01:59:27.668601: val_loss -0.7574 +2024-11-22 01:59:27.668723: Pseudo dice [0.8496] +2024-11-22 01:59:27.668819: Epoch time: 19.93 s +2024-11-22 01:59:28.497346: +2024-11-22 01:59:28.497558: Epoch 2745 +2024-11-22 01:59:28.497698: Current learning rate: 0.00685 +2024-11-22 01:59:46.689669: train_loss -0.7722 +2024-11-22 01:59:46.698994: val_loss -0.7299 +2024-11-22 01:59:46.699116: Pseudo dice [0.8351] +2024-11-22 01:59:46.699208: Epoch time: 18.19 s +2024-11-22 01:59:47.663656: +2024-11-22 01:59:47.663912: Epoch 2746 +2024-11-22 01:59:47.664037: Current learning rate: 0.00685 +2024-11-22 02:00:05.411360: train_loss -0.7729 +2024-11-22 02:00:05.416711: val_loss -0.7553 +2024-11-22 02:00:05.416846: Pseudo dice [0.8628] +2024-11-22 02:00:05.416941: Epoch time: 17.75 s +2024-11-22 02:00:06.271879: +2024-11-22 02:00:06.272091: Epoch 2747 +2024-11-22 02:00:06.272231: Current learning rate: 0.00685 +2024-11-22 02:00:25.704024: train_loss -0.7706 +2024-11-22 02:00:25.710015: val_loss -0.7675 +2024-11-22 02:00:25.710157: Pseudo dice [0.854] +2024-11-22 02:00:25.710285: Epoch time: 19.43 s +2024-11-22 02:00:26.557774: +2024-11-22 02:00:26.558030: Epoch 2748 +2024-11-22 02:00:26.558174: Current learning rate: 0.00685 +2024-11-22 02:00:46.702877: train_loss -0.7773 +2024-11-22 02:00:46.711422: val_loss -0.7702 +2024-11-22 02:00:46.711557: Pseudo dice [0.8549] +2024-11-22 02:00:46.711646: Epoch time: 20.15 s +2024-11-22 02:00:47.693413: +2024-11-22 02:00:47.693635: Epoch 2749 +2024-11-22 02:00:47.693777: Current learning rate: 0.00685 +2024-11-22 02:01:05.574979: train_loss -0.7781 +2024-11-22 02:01:05.582207: val_loss -0.7797 +2024-11-22 02:01:05.582357: Pseudo dice [0.8473] +2024-11-22 02:01:05.582461: Epoch time: 17.88 s +2024-11-22 02:01:06.714619: +2024-11-22 02:01:06.714842: Epoch 2750 +2024-11-22 02:01:06.714959: Current learning rate: 0.00684 +2024-11-22 02:01:25.359772: train_loss -0.7694 +2024-11-22 02:01:25.370063: val_loss -0.7633 +2024-11-22 02:01:25.370204: Pseudo dice [0.8443] +2024-11-22 02:01:25.370305: Epoch time: 18.65 s +2024-11-22 02:01:26.252723: +2024-11-22 02:01:26.252939: Epoch 2751 +2024-11-22 02:01:26.253053: Current learning rate: 0.00684 +2024-11-22 02:01:45.603786: train_loss -0.781 +2024-11-22 02:01:45.612491: val_loss -0.7534 +2024-11-22 02:01:45.612634: Pseudo dice [0.8451] +2024-11-22 02:01:45.612751: Epoch time: 19.35 s +2024-11-22 02:01:46.666621: +2024-11-22 02:01:46.666852: Epoch 2752 +2024-11-22 02:01:46.666970: Current learning rate: 0.00684 +2024-11-22 02:02:04.812243: train_loss -0.7732 +2024-11-22 02:02:04.851889: val_loss -0.769 +2024-11-22 02:02:04.852086: Pseudo dice [0.8375] +2024-11-22 02:02:04.852188: Epoch time: 18.15 s +2024-11-22 02:02:05.776477: +2024-11-22 02:02:05.776723: Epoch 2753 +2024-11-22 02:02:05.776853: Current learning rate: 0.00684 +2024-11-22 02:02:24.877487: train_loss -0.7712 +2024-11-22 02:02:24.880278: val_loss -0.7399 +2024-11-22 02:02:24.880399: Pseudo dice [0.837] +2024-11-22 02:02:24.880485: Epoch time: 19.1 s +2024-11-22 02:02:25.703275: +2024-11-22 02:02:25.703475: Epoch 2754 +2024-11-22 02:02:25.703588: Current learning rate: 0.00684 +2024-11-22 02:02:43.968779: train_loss -0.7648 +2024-11-22 02:02:43.974539: val_loss -0.7372 +2024-11-22 02:02:43.974684: Pseudo dice [0.8527] +2024-11-22 02:02:43.974795: Epoch time: 18.27 s +2024-11-22 02:02:44.796462: +2024-11-22 02:02:44.796670: Epoch 2755 +2024-11-22 02:02:44.796799: Current learning rate: 0.00684 +2024-11-22 02:03:03.608609: train_loss -0.7716 +2024-11-22 02:03:03.621081: val_loss -0.7489 +2024-11-22 02:03:03.621239: Pseudo dice [0.8603] +2024-11-22 02:03:03.621349: Epoch time: 18.81 s +2024-11-22 02:03:04.584722: +2024-11-22 02:03:04.584932: Epoch 2756 +2024-11-22 02:03:04.585053: Current learning rate: 0.00684 +2024-11-22 02:03:24.285204: train_loss -0.7719 +2024-11-22 02:03:24.291106: val_loss -0.7663 +2024-11-22 02:03:24.291248: Pseudo dice [0.8409] +2024-11-22 02:03:24.291333: Epoch time: 19.7 s +2024-11-22 02:03:25.126560: +2024-11-22 02:03:25.126789: Epoch 2757 +2024-11-22 02:03:25.126923: Current learning rate: 0.00684 +2024-11-22 02:03:43.530442: train_loss -0.7773 +2024-11-22 02:03:43.543444: val_loss -0.7646 +2024-11-22 02:03:43.543617: Pseudo dice [0.8454] +2024-11-22 02:03:43.543707: Epoch time: 18.4 s +2024-11-22 02:03:44.508943: +2024-11-22 02:03:44.509170: Epoch 2758 +2024-11-22 02:03:44.509285: Current learning rate: 0.00684 +2024-11-22 02:04:04.404558: train_loss -0.7722 +2024-11-22 02:04:04.410411: val_loss -0.767 +2024-11-22 02:04:04.410524: Pseudo dice [0.844] +2024-11-22 02:04:04.410625: Epoch time: 19.9 s +2024-11-22 02:04:05.275306: +2024-11-22 02:04:05.275501: Epoch 2759 +2024-11-22 02:04:05.275622: Current learning rate: 0.00683 +2024-11-22 02:04:25.560031: train_loss -0.7762 +2024-11-22 02:04:25.563312: val_loss -0.7549 +2024-11-22 02:04:25.563446: Pseudo dice [0.8436] +2024-11-22 02:04:25.563547: Epoch time: 20.29 s +2024-11-22 02:04:26.798443: +2024-11-22 02:04:26.798648: Epoch 2760 +2024-11-22 02:04:26.798761: Current learning rate: 0.00683 +2024-11-22 02:04:46.531626: train_loss -0.7665 +2024-11-22 02:04:46.533666: val_loss -0.7598 +2024-11-22 02:04:46.533776: Pseudo dice [0.8423] +2024-11-22 02:04:46.533881: Epoch time: 19.73 s +2024-11-22 02:04:47.350920: +2024-11-22 02:04:47.351172: Epoch 2761 +2024-11-22 02:04:47.351310: Current learning rate: 0.00683 +2024-11-22 02:05:06.178288: train_loss -0.7709 +2024-11-22 02:05:06.188426: val_loss -0.7734 +2024-11-22 02:05:06.188551: Pseudo dice [0.8518] +2024-11-22 02:05:06.188659: Epoch time: 18.83 s +2024-11-22 02:05:07.022339: +2024-11-22 02:05:07.022563: Epoch 2762 +2024-11-22 02:05:07.022686: Current learning rate: 0.00683 +2024-11-22 02:05:26.066982: train_loss -0.7815 +2024-11-22 02:05:26.075468: val_loss -0.7739 +2024-11-22 02:05:26.075667: Pseudo dice [0.8458] +2024-11-22 02:05:26.075765: Epoch time: 19.05 s +2024-11-22 02:05:26.924920: +2024-11-22 02:05:26.925136: Epoch 2763 +2024-11-22 02:05:26.925249: Current learning rate: 0.00683 +2024-11-22 02:05:45.571647: train_loss -0.7766 +2024-11-22 02:05:45.579512: val_loss -0.7774 +2024-11-22 02:05:45.579627: Pseudo dice [0.8463] +2024-11-22 02:05:45.579720: Epoch time: 18.65 s +2024-11-22 02:05:46.549909: +2024-11-22 02:05:46.550145: Epoch 2764 +2024-11-22 02:05:46.550262: Current learning rate: 0.00683 +2024-11-22 02:06:04.828351: train_loss -0.765 +2024-11-22 02:06:04.831186: val_loss -0.759 +2024-11-22 02:06:04.831303: Pseudo dice [0.8463] +2024-11-22 02:06:04.831409: Epoch time: 18.28 s +2024-11-22 02:06:05.653654: +2024-11-22 02:06:05.653890: Epoch 2765 +2024-11-22 02:06:05.654018: Current learning rate: 0.00683 +2024-11-22 02:06:26.100197: train_loss -0.7638 +2024-11-22 02:06:26.108116: val_loss -0.7533 +2024-11-22 02:06:26.108234: Pseudo dice [0.8445] +2024-11-22 02:06:26.108335: Epoch time: 20.45 s +2024-11-22 02:06:27.037979: +2024-11-22 02:06:27.038209: Epoch 2766 +2024-11-22 02:06:27.038341: Current learning rate: 0.00683 +2024-11-22 02:06:46.618192: train_loss -0.7688 +2024-11-22 02:06:46.620797: val_loss -0.7479 +2024-11-22 02:06:46.621012: Pseudo dice [0.8402] +2024-11-22 02:06:46.621124: Epoch time: 19.58 s +2024-11-22 02:06:47.442921: +2024-11-22 02:06:47.443130: Epoch 2767 +2024-11-22 02:06:47.443245: Current learning rate: 0.00682 +2024-11-22 02:07:06.137452: train_loss -0.7705 +2024-11-22 02:07:06.141361: val_loss -0.7418 +2024-11-22 02:07:06.141493: Pseudo dice [0.8197] +2024-11-22 02:07:06.141585: Epoch time: 18.7 s +2024-11-22 02:07:07.009079: +2024-11-22 02:07:07.009278: Epoch 2768 +2024-11-22 02:07:07.009398: Current learning rate: 0.00682 +2024-11-22 02:07:25.894454: train_loss -0.772 +2024-11-22 02:07:25.901148: val_loss -0.7698 +2024-11-22 02:07:25.901266: Pseudo dice [0.8524] +2024-11-22 02:07:25.901370: Epoch time: 18.89 s +2024-11-22 02:07:26.757400: +2024-11-22 02:07:26.757642: Epoch 2769 +2024-11-22 02:07:26.757769: Current learning rate: 0.00682 +2024-11-22 02:07:45.102372: train_loss -0.7783 +2024-11-22 02:07:45.108595: val_loss -0.7596 +2024-11-22 02:07:45.108782: Pseudo dice [0.8415] +2024-11-22 02:07:45.108914: Epoch time: 18.35 s +2024-11-22 02:07:45.938679: +2024-11-22 02:07:45.938917: Epoch 2770 +2024-11-22 02:07:45.939052: Current learning rate: 0.00682 +2024-11-22 02:08:04.121293: train_loss -0.7832 +2024-11-22 02:08:04.124743: val_loss -0.7745 +2024-11-22 02:08:04.124876: Pseudo dice [0.8542] +2024-11-22 02:08:04.124972: Epoch time: 18.18 s +2024-11-22 02:08:04.947135: +2024-11-22 02:08:04.947540: Epoch 2771 +2024-11-22 02:08:04.947697: Current learning rate: 0.00682 +2024-11-22 02:08:24.186634: train_loss -0.7835 +2024-11-22 02:08:24.194677: val_loss -0.7849 +2024-11-22 02:08:24.194813: Pseudo dice [0.8465] +2024-11-22 02:08:24.194911: Epoch time: 19.24 s +2024-11-22 02:08:25.471812: +2024-11-22 02:08:25.472038: Epoch 2772 +2024-11-22 02:08:25.472159: Current learning rate: 0.00682 +2024-11-22 02:08:44.514785: train_loss -0.7827 +2024-11-22 02:08:44.516601: val_loss -0.7467 +2024-11-22 02:08:44.516706: Pseudo dice [0.8566] +2024-11-22 02:08:44.516809: Epoch time: 19.04 s +2024-11-22 02:08:45.341295: +2024-11-22 02:08:45.341518: Epoch 2773 +2024-11-22 02:08:45.341647: Current learning rate: 0.00682 +2024-11-22 02:09:05.193619: train_loss -0.7784 +2024-11-22 02:09:05.204831: val_loss -0.7735 +2024-11-22 02:09:05.204975: Pseudo dice [0.853] +2024-11-22 02:09:05.205077: Epoch time: 19.85 s +2024-11-22 02:09:06.027706: +2024-11-22 02:09:06.027938: Epoch 2774 +2024-11-22 02:09:06.028056: Current learning rate: 0.00682 +2024-11-22 02:09:24.211747: train_loss -0.7868 +2024-11-22 02:09:24.218036: val_loss -0.7622 +2024-11-22 02:09:24.218184: Pseudo dice [0.8466] +2024-11-22 02:09:24.218382: Epoch time: 18.18 s +2024-11-22 02:09:25.081528: +2024-11-22 02:09:25.081769: Epoch 2775 +2024-11-22 02:09:25.081911: Current learning rate: 0.00682 +2024-11-22 02:09:44.929889: train_loss -0.7826 +2024-11-22 02:09:44.938706: val_loss -0.76 +2024-11-22 02:09:44.938856: Pseudo dice [0.8446] +2024-11-22 02:09:44.938959: Epoch time: 19.85 s +2024-11-22 02:09:45.869266: +2024-11-22 02:09:45.869489: Epoch 2776 +2024-11-22 02:09:45.869611: Current learning rate: 0.00681 +2024-11-22 02:10:05.194802: train_loss -0.7847 +2024-11-22 02:10:05.202398: val_loss -0.7693 +2024-11-22 02:10:05.202545: Pseudo dice [0.8333] +2024-11-22 02:10:05.202650: Epoch time: 19.33 s +2024-11-22 02:10:06.237661: +2024-11-22 02:10:06.237864: Epoch 2777 +2024-11-22 02:10:06.237981: Current learning rate: 0.00681 +2024-11-22 02:10:25.117039: train_loss -0.775 +2024-11-22 02:10:25.137843: val_loss -0.7696 +2024-11-22 02:10:25.137992: Pseudo dice [0.8595] +2024-11-22 02:10:25.138091: Epoch time: 18.88 s +2024-11-22 02:10:26.227022: +2024-11-22 02:10:26.227246: Epoch 2778 +2024-11-22 02:10:26.227367: Current learning rate: 0.00681 +2024-11-22 02:10:47.188790: train_loss -0.7811 +2024-11-22 02:10:47.195847: val_loss -0.7838 +2024-11-22 02:10:47.196046: Pseudo dice [0.8405] +2024-11-22 02:10:47.196144: Epoch time: 20.96 s +2024-11-22 02:10:48.029503: +2024-11-22 02:10:48.029704: Epoch 2779 +2024-11-22 02:10:48.029820: Current learning rate: 0.00681 +2024-11-22 02:11:06.736795: train_loss -0.7788 +2024-11-22 02:11:06.743149: val_loss -0.7502 +2024-11-22 02:11:06.743288: Pseudo dice [0.8533] +2024-11-22 02:11:06.743395: Epoch time: 18.71 s +2024-11-22 02:11:07.681853: +2024-11-22 02:11:07.682111: Epoch 2780 +2024-11-22 02:11:07.682259: Current learning rate: 0.00681 +2024-11-22 02:11:28.073392: train_loss -0.7744 +2024-11-22 02:11:28.081283: val_loss -0.7862 +2024-11-22 02:11:28.081447: Pseudo dice [0.8573] +2024-11-22 02:11:28.081558: Epoch time: 20.39 s +2024-11-22 02:11:28.921164: +2024-11-22 02:11:28.921373: Epoch 2781 +2024-11-22 02:11:28.921487: Current learning rate: 0.00681 +2024-11-22 02:11:47.498591: train_loss -0.7798 +2024-11-22 02:11:47.500791: val_loss -0.7954 +2024-11-22 02:11:47.500914: Pseudo dice [0.8616] +2024-11-22 02:11:47.500997: Epoch time: 18.58 s +2024-11-22 02:11:48.321874: +2024-11-22 02:11:48.322083: Epoch 2782 +2024-11-22 02:11:48.322209: Current learning rate: 0.00681 +2024-11-22 02:12:07.060568: train_loss -0.7741 +2024-11-22 02:12:07.062961: val_loss -0.7596 +2024-11-22 02:12:07.063104: Pseudo dice [0.8578] +2024-11-22 02:12:07.063192: Epoch time: 18.74 s +2024-11-22 02:12:07.977494: +2024-11-22 02:12:07.977700: Epoch 2783 +2024-11-22 02:12:07.977846: Current learning rate: 0.00681 +2024-11-22 02:12:27.882912: train_loss -0.7613 +2024-11-22 02:12:27.889996: val_loss -0.7531 +2024-11-22 02:12:27.890186: Pseudo dice [0.832] +2024-11-22 02:12:27.890295: Epoch time: 19.91 s +2024-11-22 02:12:28.767709: +2024-11-22 02:12:28.767917: Epoch 2784 +2024-11-22 02:12:28.768033: Current learning rate: 0.0068 +2024-11-22 02:12:48.874420: train_loss -0.761 +2024-11-22 02:12:48.882878: val_loss -0.7539 +2024-11-22 02:12:48.883014: Pseudo dice [0.8396] +2024-11-22 02:12:48.883124: Epoch time: 20.11 s +2024-11-22 02:12:49.928812: +2024-11-22 02:12:49.929020: Epoch 2785 +2024-11-22 02:12:49.929145: Current learning rate: 0.0068 +2024-11-22 02:13:08.308743: train_loss -0.7611 +2024-11-22 02:13:08.314514: val_loss -0.7692 +2024-11-22 02:13:08.314632: Pseudo dice [0.8584] +2024-11-22 02:13:08.314736: Epoch time: 18.38 s +2024-11-22 02:13:09.154866: +2024-11-22 02:13:09.155135: Epoch 2786 +2024-11-22 02:13:09.155257: Current learning rate: 0.0068 +2024-11-22 02:13:27.758048: train_loss -0.7751 +2024-11-22 02:13:27.764354: val_loss -0.7794 +2024-11-22 02:13:27.764492: Pseudo dice [0.8469] +2024-11-22 02:13:27.764594: Epoch time: 18.6 s +2024-11-22 02:13:28.751891: +2024-11-22 02:13:28.752128: Epoch 2787 +2024-11-22 02:13:28.752252: Current learning rate: 0.0068 +2024-11-22 02:13:48.322336: train_loss -0.7719 +2024-11-22 02:13:48.340881: val_loss -0.7603 +2024-11-22 02:13:48.341020: Pseudo dice [0.8584] +2024-11-22 02:13:48.341119: Epoch time: 19.57 s +2024-11-22 02:13:49.233455: +2024-11-22 02:13:49.233658: Epoch 2788 +2024-11-22 02:13:49.233778: Current learning rate: 0.0068 +2024-11-22 02:14:08.770997: train_loss -0.7502 +2024-11-22 02:14:08.786845: val_loss -0.7392 +2024-11-22 02:14:08.786975: Pseudo dice [0.848] +2024-11-22 02:14:08.787079: Epoch time: 19.54 s +2024-11-22 02:14:09.606539: +2024-11-22 02:14:09.606770: Epoch 2789 +2024-11-22 02:14:09.606896: Current learning rate: 0.0068 +2024-11-22 02:14:28.014745: train_loss -0.7656 +2024-11-22 02:14:28.021651: val_loss -0.7601 +2024-11-22 02:14:28.021771: Pseudo dice [0.8487] +2024-11-22 02:14:28.021862: Epoch time: 18.41 s +2024-11-22 02:14:28.885341: +2024-11-22 02:14:28.885573: Epoch 2790 +2024-11-22 02:14:28.885701: Current learning rate: 0.0068 +2024-11-22 02:14:48.526698: train_loss -0.7699 +2024-11-22 02:14:48.529888: val_loss -0.7383 +2024-11-22 02:14:48.542368: Pseudo dice [0.8394] +2024-11-22 02:14:48.542554: Epoch time: 19.64 s +2024-11-22 02:14:49.557615: +2024-11-22 02:14:49.557809: Epoch 2791 +2024-11-22 02:14:49.557924: Current learning rate: 0.0068 +2024-11-22 02:15:08.467603: train_loss -0.7635 +2024-11-22 02:15:08.474085: val_loss -0.7707 +2024-11-22 02:15:08.474235: Pseudo dice [0.8404] +2024-11-22 02:15:08.474329: Epoch time: 18.91 s +2024-11-22 02:15:09.339536: +2024-11-22 02:15:09.339768: Epoch 2792 +2024-11-22 02:15:09.339890: Current learning rate: 0.0068 +2024-11-22 02:15:27.828119: train_loss -0.7748 +2024-11-22 02:15:27.832756: val_loss -0.7747 +2024-11-22 02:15:27.832885: Pseudo dice [0.8507] +2024-11-22 02:15:27.832988: Epoch time: 18.49 s +2024-11-22 02:15:28.783381: +2024-11-22 02:15:28.783586: Epoch 2793 +2024-11-22 02:15:28.783726: Current learning rate: 0.00679 +2024-11-22 02:15:47.959084: train_loss -0.7731 +2024-11-22 02:15:47.964280: val_loss -0.7834 +2024-11-22 02:15:47.964419: Pseudo dice [0.8458] +2024-11-22 02:15:47.964519: Epoch time: 19.18 s +2024-11-22 02:15:48.925735: +2024-11-22 02:15:48.925946: Epoch 2794 +2024-11-22 02:15:48.926069: Current learning rate: 0.00679 +2024-11-22 02:16:07.787097: train_loss -0.7582 +2024-11-22 02:16:07.793054: val_loss -0.7691 +2024-11-22 02:16:07.793231: Pseudo dice [0.8474] +2024-11-22 02:16:07.793328: Epoch time: 18.86 s +2024-11-22 02:16:09.032707: +2024-11-22 02:16:09.032917: Epoch 2795 +2024-11-22 02:16:09.033039: Current learning rate: 0.00679 +2024-11-22 02:16:29.359352: train_loss -0.7694 +2024-11-22 02:16:29.361981: val_loss -0.7721 +2024-11-22 02:16:29.362099: Pseudo dice [0.8608] +2024-11-22 02:16:29.362203: Epoch time: 20.33 s +2024-11-22 02:16:30.178276: +2024-11-22 02:16:30.178483: Epoch 2796 +2024-11-22 02:16:30.178603: Current learning rate: 0.00679 +2024-11-22 02:16:49.444436: train_loss -0.7688 +2024-11-22 02:16:49.446759: val_loss -0.7731 +2024-11-22 02:16:49.446881: Pseudo dice [0.852] +2024-11-22 02:16:49.446983: Epoch time: 19.27 s +2024-11-22 02:16:50.295903: +2024-11-22 02:16:50.296139: Epoch 2797 +2024-11-22 02:16:50.296270: Current learning rate: 0.00679 +2024-11-22 02:17:09.715994: train_loss -0.7747 +2024-11-22 02:17:09.718497: val_loss -0.7554 +2024-11-22 02:17:09.718609: Pseudo dice [0.8547] +2024-11-22 02:17:09.718731: Epoch time: 19.42 s +2024-11-22 02:17:10.546610: +2024-11-22 02:17:10.546864: Epoch 2798 +2024-11-22 02:17:10.547015: Current learning rate: 0.00679 +2024-11-22 02:17:30.401195: train_loss -0.777 +2024-11-22 02:17:30.406369: val_loss -0.7623 +2024-11-22 02:17:30.406496: Pseudo dice [0.8499] +2024-11-22 02:17:30.406587: Epoch time: 19.86 s +2024-11-22 02:17:31.279165: +2024-11-22 02:17:31.279358: Epoch 2799 +2024-11-22 02:17:31.279473: Current learning rate: 0.00679 +2024-11-22 02:17:49.393488: train_loss -0.7706 +2024-11-22 02:17:49.409442: val_loss -0.7724 +2024-11-22 02:17:49.409565: Pseudo dice [0.8494] +2024-11-22 02:17:49.409667: Epoch time: 18.12 s +2024-11-22 02:17:50.661482: +2024-11-22 02:17:50.661705: Epoch 2800 +2024-11-22 02:17:50.661822: Current learning rate: 0.00679 +2024-11-22 02:18:10.354653: train_loss -0.7657 +2024-11-22 02:18:10.364646: val_loss -0.747 +2024-11-22 02:18:10.364846: Pseudo dice [0.8442] +2024-11-22 02:18:10.364949: Epoch time: 19.69 s +2024-11-22 02:18:11.244863: +2024-11-22 02:18:11.245122: Epoch 2801 +2024-11-22 02:18:11.245250: Current learning rate: 0.00678 +2024-11-22 02:18:30.732496: train_loss -0.7702 +2024-11-22 02:18:30.741391: val_loss -0.7546 +2024-11-22 02:18:30.741511: Pseudo dice [0.8518] +2024-11-22 02:18:30.741598: Epoch time: 19.49 s +2024-11-22 02:18:31.615394: +2024-11-22 02:18:31.615596: Epoch 2802 +2024-11-22 02:18:31.615715: Current learning rate: 0.00678 +2024-11-22 02:18:50.404171: train_loss -0.7706 +2024-11-22 02:18:50.406633: val_loss -0.7487 +2024-11-22 02:18:50.406746: Pseudo dice [0.822] +2024-11-22 02:18:50.406837: Epoch time: 18.79 s +2024-11-22 02:18:51.226384: +2024-11-22 02:18:51.226599: Epoch 2803 +2024-11-22 02:18:51.226716: Current learning rate: 0.00678 +2024-11-22 02:19:11.632502: train_loss -0.7633 +2024-11-22 02:19:11.634739: val_loss -0.7706 +2024-11-22 02:19:11.634860: Pseudo dice [0.8479] +2024-11-22 02:19:11.634945: Epoch time: 20.41 s +2024-11-22 02:19:12.479864: +2024-11-22 02:19:12.480080: Epoch 2804 +2024-11-22 02:19:12.480199: Current learning rate: 0.00678 +2024-11-22 02:19:31.896211: train_loss -0.772 +2024-11-22 02:19:31.902676: val_loss -0.718 +2024-11-22 02:19:31.902792: Pseudo dice [0.8379] +2024-11-22 02:19:31.902891: Epoch time: 19.42 s +2024-11-22 02:19:32.878506: +2024-11-22 02:19:32.878709: Epoch 2805 +2024-11-22 02:19:32.878832: Current learning rate: 0.00678 +2024-11-22 02:19:51.946753: train_loss -0.7529 +2024-11-22 02:19:51.955564: val_loss -0.7644 +2024-11-22 02:19:51.955707: Pseudo dice [0.841] +2024-11-22 02:19:51.955801: Epoch time: 19.07 s +2024-11-22 02:19:52.792182: +2024-11-22 02:19:52.792376: Epoch 2806 +2024-11-22 02:19:52.792497: Current learning rate: 0.00678 +2024-11-22 02:20:12.592269: train_loss -0.7632 +2024-11-22 02:20:12.600152: val_loss -0.7738 +2024-11-22 02:20:12.600272: Pseudo dice [0.8422] +2024-11-22 02:20:12.600365: Epoch time: 19.8 s +2024-11-22 02:20:13.480071: +2024-11-22 02:20:13.480309: Epoch 2807 +2024-11-22 02:20:13.480520: Current learning rate: 0.00678 +2024-11-22 02:20:33.199149: train_loss -0.7709 +2024-11-22 02:20:33.207750: val_loss -0.7571 +2024-11-22 02:20:33.207881: Pseudo dice [0.8376] +2024-11-22 02:20:33.208034: Epoch time: 19.72 s +2024-11-22 02:20:34.048233: +2024-11-22 02:20:34.048448: Epoch 2808 +2024-11-22 02:20:34.048575: Current learning rate: 0.00678 +2024-11-22 02:20:52.882103: train_loss -0.7657 +2024-11-22 02:20:52.886343: val_loss -0.7864 +2024-11-22 02:20:52.886480: Pseudo dice [0.8438] +2024-11-22 02:20:52.886590: Epoch time: 18.83 s +2024-11-22 02:20:53.733672: +2024-11-22 02:20:53.733894: Epoch 2809 +2024-11-22 02:20:53.734024: Current learning rate: 0.00678 +2024-11-22 02:21:13.308297: train_loss -0.7643 +2024-11-22 02:21:13.319298: val_loss -0.7528 +2024-11-22 02:21:13.319441: Pseudo dice [0.837] +2024-11-22 02:21:13.319537: Epoch time: 19.58 s +2024-11-22 02:21:14.280922: +2024-11-22 02:21:14.281141: Epoch 2810 +2024-11-22 02:21:14.281259: Current learning rate: 0.00677 +2024-11-22 02:21:33.214332: train_loss -0.7739 +2024-11-22 02:21:33.222661: val_loss -0.7446 +2024-11-22 02:21:33.222818: Pseudo dice [0.8435] +2024-11-22 02:21:33.222916: Epoch time: 18.93 s +2024-11-22 02:21:34.106244: +2024-11-22 02:21:34.106472: Epoch 2811 +2024-11-22 02:21:34.106600: Current learning rate: 0.00677 +2024-11-22 02:21:52.555327: train_loss -0.7725 +2024-11-22 02:21:52.557455: val_loss -0.7735 +2024-11-22 02:21:52.557613: Pseudo dice [0.8449] +2024-11-22 02:21:52.557705: Epoch time: 18.45 s +2024-11-22 02:21:53.384487: +2024-11-22 02:21:53.384702: Epoch 2812 +2024-11-22 02:21:53.384835: Current learning rate: 0.00677 +2024-11-22 02:22:12.548740: train_loss -0.7704 +2024-11-22 02:22:12.556561: val_loss -0.7654 +2024-11-22 02:22:12.556760: Pseudo dice [0.8594] +2024-11-22 02:22:12.556865: Epoch time: 19.17 s +2024-11-22 02:22:13.548519: +2024-11-22 02:22:13.548796: Epoch 2813 +2024-11-22 02:22:13.548927: Current learning rate: 0.00677 +2024-11-22 02:22:32.537910: train_loss -0.7698 +2024-11-22 02:22:32.544632: val_loss -0.7683 +2024-11-22 02:22:32.544779: Pseudo dice [0.8566] +2024-11-22 02:22:32.544875: Epoch time: 18.99 s +2024-11-22 02:22:33.494516: +2024-11-22 02:22:33.494733: Epoch 2814 +2024-11-22 02:22:33.494856: Current learning rate: 0.00677 +2024-11-22 02:22:51.279369: train_loss -0.7733 +2024-11-22 02:22:51.292628: val_loss -0.7683 +2024-11-22 02:22:51.292764: Pseudo dice [0.8574] +2024-11-22 02:22:51.292854: Epoch time: 17.78 s +2024-11-22 02:22:52.145637: +2024-11-22 02:22:52.145854: Epoch 2815 +2024-11-22 02:22:52.145981: Current learning rate: 0.00677 +2024-11-22 02:23:10.701106: train_loss -0.7591 +2024-11-22 02:23:10.705976: val_loss -0.7584 +2024-11-22 02:23:10.706138: Pseudo dice [0.847] +2024-11-22 02:23:10.706237: Epoch time: 18.56 s +2024-11-22 02:23:11.626341: +2024-11-22 02:23:11.650506: Epoch 2816 +2024-11-22 02:23:11.650647: Current learning rate: 0.00677 +2024-11-22 02:23:30.971871: train_loss -0.7676 +2024-11-22 02:23:30.978416: val_loss -0.7633 +2024-11-22 02:23:30.978561: Pseudo dice [0.849] +2024-11-22 02:23:30.978657: Epoch time: 19.35 s +2024-11-22 02:23:31.813748: +2024-11-22 02:23:31.813967: Epoch 2817 +2024-11-22 02:23:31.814107: Current learning rate: 0.00677 +2024-11-22 02:23:51.274470: train_loss -0.7672 +2024-11-22 02:23:51.276671: val_loss -0.7529 +2024-11-22 02:23:51.276795: Pseudo dice [0.8437] +2024-11-22 02:23:51.276902: Epoch time: 19.46 s +2024-11-22 02:23:52.495562: +2024-11-22 02:23:52.495780: Epoch 2818 +2024-11-22 02:23:52.495915: Current learning rate: 0.00676 +2024-11-22 02:24:11.787329: train_loss -0.7722 +2024-11-22 02:24:11.796869: val_loss -0.7589 +2024-11-22 02:24:11.797034: Pseudo dice [0.8703] +2024-11-22 02:24:11.797141: Epoch time: 19.29 s +2024-11-22 02:24:12.632298: +2024-11-22 02:24:12.632533: Epoch 2819 +2024-11-22 02:24:12.632663: Current learning rate: 0.00676 +2024-11-22 02:24:31.705992: train_loss -0.7721 +2024-11-22 02:24:31.720136: val_loss -0.7701 +2024-11-22 02:24:31.720281: Pseudo dice [0.8408] +2024-11-22 02:24:31.720376: Epoch time: 19.07 s +2024-11-22 02:24:32.664015: +2024-11-22 02:24:32.664268: Epoch 2820 +2024-11-22 02:24:32.664385: Current learning rate: 0.00676 +2024-11-22 02:24:51.837804: train_loss -0.7818 +2024-11-22 02:24:51.845970: val_loss -0.7799 +2024-11-22 02:24:51.846116: Pseudo dice [0.8531] +2024-11-22 02:24:51.846216: Epoch time: 19.17 s +2024-11-22 02:24:52.866453: +2024-11-22 02:24:52.866673: Epoch 2821 +2024-11-22 02:24:52.866791: Current learning rate: 0.00676 +2024-11-22 02:25:11.794821: train_loss -0.78 +2024-11-22 02:25:11.796962: val_loss -0.7746 +2024-11-22 02:25:11.797051: Pseudo dice [0.8417] +2024-11-22 02:25:11.797149: Epoch time: 18.93 s +2024-11-22 02:25:12.618082: +2024-11-22 02:25:12.618298: Epoch 2822 +2024-11-22 02:25:12.618422: Current learning rate: 0.00676 +2024-11-22 02:25:30.940876: train_loss -0.7732 +2024-11-22 02:25:30.947364: val_loss -0.761 +2024-11-22 02:25:30.947493: Pseudo dice [0.8449] +2024-11-22 02:25:30.947641: Epoch time: 18.32 s +2024-11-22 02:25:31.866472: +2024-11-22 02:25:31.866698: Epoch 2823 +2024-11-22 02:25:31.866815: Current learning rate: 0.00676 +2024-11-22 02:25:52.505977: train_loss -0.7807 +2024-11-22 02:25:52.508401: val_loss -0.7529 +2024-11-22 02:25:52.508526: Pseudo dice [0.8506] +2024-11-22 02:25:52.508612: Epoch time: 20.64 s +2024-11-22 02:25:53.347051: +2024-11-22 02:25:53.347249: Epoch 2824 +2024-11-22 02:25:53.347372: Current learning rate: 0.00676 +2024-11-22 02:26:11.997126: train_loss -0.7715 +2024-11-22 02:26:11.999825: val_loss -0.7721 +2024-11-22 02:26:11.999975: Pseudo dice [0.8588] +2024-11-22 02:26:12.000089: Epoch time: 18.65 s +2024-11-22 02:26:13.070004: +2024-11-22 02:26:13.070231: Epoch 2825 +2024-11-22 02:26:13.070350: Current learning rate: 0.00676 +2024-11-22 02:26:31.491785: train_loss -0.7768 +2024-11-22 02:26:31.498354: val_loss -0.7564 +2024-11-22 02:26:31.498483: Pseudo dice [0.845] +2024-11-22 02:26:31.498628: Epoch time: 18.42 s +2024-11-22 02:26:32.518004: +2024-11-22 02:26:32.518218: Epoch 2826 +2024-11-22 02:26:32.518341: Current learning rate: 0.00676 +2024-11-22 02:26:51.484275: train_loss -0.7737 +2024-11-22 02:26:51.497785: val_loss -0.7534 +2024-11-22 02:26:51.497986: Pseudo dice [0.8491] +2024-11-22 02:26:51.498110: Epoch time: 18.97 s +2024-11-22 02:26:52.372183: +2024-11-22 02:26:52.372395: Epoch 2827 +2024-11-22 02:26:52.372511: Current learning rate: 0.00675 +2024-11-22 02:27:11.092079: train_loss -0.7804 +2024-11-22 02:27:11.109160: val_loss -0.7714 +2024-11-22 02:27:11.114442: Pseudo dice [0.8469] +2024-11-22 02:27:11.114560: Epoch time: 18.72 s +2024-11-22 02:27:12.171027: +2024-11-22 02:27:12.171247: Epoch 2828 +2024-11-22 02:27:12.171359: Current learning rate: 0.00675 +2024-11-22 02:27:31.017233: train_loss -0.7684 +2024-11-22 02:27:31.025027: val_loss -0.7731 +2024-11-22 02:27:31.025186: Pseudo dice [0.8512] +2024-11-22 02:27:31.025505: Epoch time: 18.85 s +2024-11-22 02:27:31.910573: +2024-11-22 02:27:31.910796: Epoch 2829 +2024-11-22 02:27:31.910911: Current learning rate: 0.00675 +2024-11-22 02:27:50.486188: train_loss -0.7772 +2024-11-22 02:27:50.492568: val_loss -0.7879 +2024-11-22 02:27:50.492712: Pseudo dice [0.8637] +2024-11-22 02:27:50.492829: Epoch time: 18.58 s +2024-11-22 02:27:51.779635: +2024-11-22 02:27:51.779888: Epoch 2830 +2024-11-22 02:27:51.780028: Current learning rate: 0.00675 +2024-11-22 02:28:11.112664: train_loss -0.7828 +2024-11-22 02:28:11.116899: val_loss -0.7672 +2024-11-22 02:28:11.117099: Pseudo dice [0.8424] +2024-11-22 02:28:11.117188: Epoch time: 19.33 s +2024-11-22 02:28:11.973402: +2024-11-22 02:28:11.973623: Epoch 2831 +2024-11-22 02:28:11.973741: Current learning rate: 0.00675 +2024-11-22 02:28:31.524684: train_loss -0.7814 +2024-11-22 02:28:31.526938: val_loss -0.7682 +2024-11-22 02:28:31.527038: Pseudo dice [0.8601] +2024-11-22 02:28:31.527123: Epoch time: 19.55 s +2024-11-22 02:28:32.341488: +2024-11-22 02:28:32.341709: Epoch 2832 +2024-11-22 02:28:32.341841: Current learning rate: 0.00675 +2024-11-22 02:28:51.832209: train_loss -0.7778 +2024-11-22 02:28:51.834807: val_loss -0.7636 +2024-11-22 02:28:51.834952: Pseudo dice [0.8508] +2024-11-22 02:28:51.835075: Epoch time: 19.49 s +2024-11-22 02:28:52.662131: +2024-11-22 02:28:52.662386: Epoch 2833 +2024-11-22 02:28:52.662718: Current learning rate: 0.00675 +2024-11-22 02:29:11.992927: train_loss -0.7765 +2024-11-22 02:29:12.000344: val_loss -0.7671 +2024-11-22 02:29:12.000483: Pseudo dice [0.8547] +2024-11-22 02:29:12.000611: Epoch time: 19.33 s +2024-11-22 02:29:12.889888: +2024-11-22 02:29:12.890106: Epoch 2834 +2024-11-22 02:29:12.890231: Current learning rate: 0.00675 +2024-11-22 02:29:31.497418: train_loss -0.7852 +2024-11-22 02:29:31.503787: val_loss -0.7806 +2024-11-22 02:29:31.503906: Pseudo dice [0.8525] +2024-11-22 02:29:31.503994: Epoch time: 18.61 s +2024-11-22 02:29:32.490498: +2024-11-22 02:29:32.490696: Epoch 2835 +2024-11-22 02:29:32.490826: Current learning rate: 0.00675 +2024-11-22 02:29:51.510871: train_loss -0.7821 +2024-11-22 02:29:51.516982: val_loss -0.7872 +2024-11-22 02:29:51.517131: Pseudo dice [0.8533] +2024-11-22 02:29:51.517223: Epoch time: 19.02 s +2024-11-22 02:29:52.709679: +2024-11-22 02:29:52.709903: Epoch 2836 +2024-11-22 02:29:52.710015: Current learning rate: 0.00674 +2024-11-22 02:30:11.339096: train_loss -0.7804 +2024-11-22 02:30:11.352566: val_loss -0.7749 +2024-11-22 02:30:11.352705: Pseudo dice [0.8524] +2024-11-22 02:30:11.352809: Epoch time: 18.63 s +2024-11-22 02:30:12.304381: +2024-11-22 02:30:12.304591: Epoch 2837 +2024-11-22 02:30:12.304741: Current learning rate: 0.00674 +2024-11-22 02:30:32.096482: train_loss -0.7747 +2024-11-22 02:30:32.104609: val_loss -0.7644 +2024-11-22 02:30:32.104767: Pseudo dice [0.8536] +2024-11-22 02:30:32.104881: Epoch time: 19.79 s +2024-11-22 02:30:32.939089: +2024-11-22 02:30:32.939276: Epoch 2838 +2024-11-22 02:30:32.939399: Current learning rate: 0.00674 +2024-11-22 02:30:52.790732: train_loss -0.7777 +2024-11-22 02:30:52.798819: val_loss -0.7601 +2024-11-22 02:30:52.805504: Pseudo dice [0.8473] +2024-11-22 02:30:52.805614: Epoch time: 19.85 s +2024-11-22 02:30:53.720543: +2024-11-22 02:30:53.720744: Epoch 2839 +2024-11-22 02:30:53.720879: Current learning rate: 0.00674 +2024-11-22 02:31:12.768293: train_loss -0.7647 +2024-11-22 02:31:12.782048: val_loss -0.7486 +2024-11-22 02:31:12.782201: Pseudo dice [0.8447] +2024-11-22 02:31:12.782295: Epoch time: 19.05 s +2024-11-22 02:31:13.643829: +2024-11-22 02:31:13.644038: Epoch 2840 +2024-11-22 02:31:13.644161: Current learning rate: 0.00674 +2024-11-22 02:31:32.303246: train_loss -0.7644 +2024-11-22 02:31:32.310297: val_loss -0.751 +2024-11-22 02:31:32.310441: Pseudo dice [0.8388] +2024-11-22 02:31:32.310565: Epoch time: 18.66 s +2024-11-22 02:31:33.158684: +2024-11-22 02:31:33.158911: Epoch 2841 +2024-11-22 02:31:33.159045: Current learning rate: 0.00674 +2024-11-22 02:31:52.500015: train_loss -0.7759 +2024-11-22 02:31:52.517698: val_loss -0.7763 +2024-11-22 02:31:52.517838: Pseudo dice [0.8588] +2024-11-22 02:31:52.517941: Epoch time: 19.34 s +2024-11-22 02:31:53.863179: +2024-11-22 02:31:53.863417: Epoch 2842 +2024-11-22 02:31:53.863539: Current learning rate: 0.00674 +2024-11-22 02:32:13.503081: train_loss -0.77 +2024-11-22 02:32:13.510297: val_loss -0.7601 +2024-11-22 02:32:13.510416: Pseudo dice [0.8561] +2024-11-22 02:32:13.510522: Epoch time: 19.64 s +2024-11-22 02:32:14.444955: +2024-11-22 02:32:14.445196: Epoch 2843 +2024-11-22 02:32:14.445320: Current learning rate: 0.00674 +2024-11-22 02:32:32.911295: train_loss -0.7666 +2024-11-22 02:32:32.936387: val_loss -0.7698 +2024-11-22 02:32:32.936536: Pseudo dice [0.8421] +2024-11-22 02:32:32.936645: Epoch time: 18.47 s +2024-11-22 02:32:33.976578: +2024-11-22 02:32:33.976795: Epoch 2844 +2024-11-22 02:32:33.976915: Current learning rate: 0.00673 +2024-11-22 02:32:53.546104: train_loss -0.7763 +2024-11-22 02:32:53.552481: val_loss -0.7364 +2024-11-22 02:32:53.552612: Pseudo dice [0.8405] +2024-11-22 02:32:53.552712: Epoch time: 19.57 s +2024-11-22 02:32:54.566165: +2024-11-22 02:32:54.566403: Epoch 2845 +2024-11-22 02:32:54.566537: Current learning rate: 0.00673 +2024-11-22 02:33:12.158685: train_loss -0.7717 +2024-11-22 02:33:12.166867: val_loss -0.7478 +2024-11-22 02:33:12.166997: Pseudo dice [0.847] +2024-11-22 02:33:12.167087: Epoch time: 17.59 s +2024-11-22 02:33:13.067174: +2024-11-22 02:33:13.067454: Epoch 2846 +2024-11-22 02:33:13.067571: Current learning rate: 0.00673 +2024-11-22 02:33:32.366601: train_loss -0.7619 +2024-11-22 02:33:32.369065: val_loss -0.755 +2024-11-22 02:33:32.369162: Pseudo dice [0.8523] +2024-11-22 02:33:32.369241: Epoch time: 19.3 s +2024-11-22 02:33:33.198416: +2024-11-22 02:33:33.198616: Epoch 2847 +2024-11-22 02:33:33.198767: Current learning rate: 0.00673 +2024-11-22 02:33:51.381862: train_loss -0.7724 +2024-11-22 02:33:51.390242: val_loss -0.7812 +2024-11-22 02:33:51.390374: Pseudo dice [0.8549] +2024-11-22 02:33:51.390459: Epoch time: 18.18 s +2024-11-22 02:33:52.224764: +2024-11-22 02:33:52.224988: Epoch 2848 +2024-11-22 02:33:52.225131: Current learning rate: 0.00673 +2024-11-22 02:34:11.294316: train_loss -0.7616 +2024-11-22 02:34:11.300000: val_loss -0.7568 +2024-11-22 02:34:11.300156: Pseudo dice [0.8462] +2024-11-22 02:34:11.300254: Epoch time: 19.07 s +2024-11-22 02:34:12.169249: +2024-11-22 02:34:12.169454: Epoch 2849 +2024-11-22 02:34:12.169593: Current learning rate: 0.00673 +2024-11-22 02:34:31.868986: train_loss -0.7737 +2024-11-22 02:34:31.872664: val_loss -0.7197 +2024-11-22 02:34:31.872816: Pseudo dice [0.8321] +2024-11-22 02:34:31.872908: Epoch time: 19.7 s +2024-11-22 02:34:32.936649: +2024-11-22 02:34:32.936883: Epoch 2850 +2024-11-22 02:34:32.937010: Current learning rate: 0.00673 +2024-11-22 02:34:51.696424: train_loss -0.7672 +2024-11-22 02:34:51.699849: val_loss -0.7653 +2024-11-22 02:34:51.699977: Pseudo dice [0.8408] +2024-11-22 02:34:51.700070: Epoch time: 18.76 s +2024-11-22 02:34:52.539521: +2024-11-22 02:34:52.539793: Epoch 2851 +2024-11-22 02:34:52.539948: Current learning rate: 0.00673 +2024-11-22 02:35:11.044715: train_loss -0.7585 +2024-11-22 02:35:11.056479: val_loss -0.7522 +2024-11-22 02:35:11.056614: Pseudo dice [0.8436] +2024-11-22 02:35:11.056728: Epoch time: 18.51 s +2024-11-22 02:35:12.134285: +2024-11-22 02:35:12.134484: Epoch 2852 +2024-11-22 02:35:12.134601: Current learning rate: 0.00673 +2024-11-22 02:35:31.936432: train_loss -0.7681 +2024-11-22 02:35:31.947484: val_loss -0.7602 +2024-11-22 02:35:31.947629: Pseudo dice [0.8459] +2024-11-22 02:35:31.947729: Epoch time: 19.8 s +2024-11-22 02:35:32.816935: +2024-11-22 02:35:32.817156: Epoch 2853 +2024-11-22 02:35:32.817279: Current learning rate: 0.00672 +2024-11-22 02:35:51.433200: train_loss -0.7773 +2024-11-22 02:35:51.439817: val_loss -0.7715 +2024-11-22 02:35:51.440014: Pseudo dice [0.8504] +2024-11-22 02:35:51.440120: Epoch time: 18.62 s +2024-11-22 02:35:52.413921: +2024-11-22 02:35:52.414163: Epoch 2854 +2024-11-22 02:35:52.414506: Current learning rate: 0.00672 +2024-11-22 02:36:11.417581: train_loss -0.7722 +2024-11-22 02:36:11.424107: val_loss -0.7568 +2024-11-22 02:36:11.424262: Pseudo dice [0.8392] +2024-11-22 02:36:11.424365: Epoch time: 19.0 s +2024-11-22 02:36:12.246133: +2024-11-22 02:36:12.246389: Epoch 2855 +2024-11-22 02:36:12.246529: Current learning rate: 0.00672 +2024-11-22 02:36:31.671516: train_loss -0.775 +2024-11-22 02:36:31.680168: val_loss -0.7697 +2024-11-22 02:36:31.680322: Pseudo dice [0.8613] +2024-11-22 02:36:31.680408: Epoch time: 19.43 s +2024-11-22 02:36:32.671171: +2024-11-22 02:36:32.671427: Epoch 2856 +2024-11-22 02:36:32.671556: Current learning rate: 0.00672 +2024-11-22 02:36:51.160886: train_loss -0.7758 +2024-11-22 02:36:51.173721: val_loss -0.7696 +2024-11-22 02:36:51.173890: Pseudo dice [0.8457] +2024-11-22 02:36:51.173987: Epoch time: 18.49 s +2024-11-22 02:36:52.112088: +2024-11-22 02:36:52.112298: Epoch 2857 +2024-11-22 02:36:52.112433: Current learning rate: 0.00672 +2024-11-22 02:37:11.576280: train_loss -0.7718 +2024-11-22 02:37:11.585009: val_loss -0.7787 +2024-11-22 02:37:11.585161: Pseudo dice [0.8482] +2024-11-22 02:37:11.585332: Epoch time: 19.47 s +2024-11-22 02:37:12.418218: +2024-11-22 02:37:12.418488: Epoch 2858 +2024-11-22 02:37:12.418605: Current learning rate: 0.00672 +2024-11-22 02:37:30.164706: train_loss -0.778 +2024-11-22 02:37:30.173595: val_loss -0.7548 +2024-11-22 02:37:30.173721: Pseudo dice [0.843] +2024-11-22 02:37:30.173822: Epoch time: 17.75 s +2024-11-22 02:37:31.046407: +2024-11-22 02:37:31.046856: Epoch 2859 +2024-11-22 02:37:31.046980: Current learning rate: 0.00672 +2024-11-22 02:37:49.812837: train_loss -0.7786 +2024-11-22 02:37:49.821012: val_loss -0.7767 +2024-11-22 02:37:49.821168: Pseudo dice [0.8494] +2024-11-22 02:37:49.821295: Epoch time: 18.77 s +2024-11-22 02:37:50.710163: +2024-11-22 02:37:50.710375: Epoch 2860 +2024-11-22 02:37:50.710503: Current learning rate: 0.00672 +2024-11-22 02:38:09.729286: train_loss -0.7794 +2024-11-22 02:38:09.732814: val_loss -0.7318 +2024-11-22 02:38:09.732927: Pseudo dice [0.833] +2024-11-22 02:38:09.733018: Epoch time: 19.02 s +2024-11-22 02:38:10.565319: +2024-11-22 02:38:10.565506: Epoch 2861 +2024-11-22 02:38:10.565616: Current learning rate: 0.00671 +2024-11-22 02:38:30.016179: train_loss -0.7668 +2024-11-22 02:38:30.023906: val_loss -0.7444 +2024-11-22 02:38:30.024031: Pseudo dice [0.8452] +2024-11-22 02:38:30.024143: Epoch time: 19.45 s +2024-11-22 02:38:30.855962: +2024-11-22 02:38:30.856216: Epoch 2862 +2024-11-22 02:38:30.856337: Current learning rate: 0.00671 +2024-11-22 02:38:50.451890: train_loss -0.7747 +2024-11-22 02:38:50.454404: val_loss -0.7759 +2024-11-22 02:38:50.454524: Pseudo dice [0.8423] +2024-11-22 02:38:50.454607: Epoch time: 19.6 s +2024-11-22 02:38:51.283657: +2024-11-22 02:38:51.283854: Epoch 2863 +2024-11-22 02:38:51.283982: Current learning rate: 0.00671 +2024-11-22 02:39:10.289064: train_loss -0.7694 +2024-11-22 02:39:10.295275: val_loss -0.7456 +2024-11-22 02:39:10.295409: Pseudo dice [0.8486] +2024-11-22 02:39:10.295499: Epoch time: 19.01 s +2024-11-22 02:39:11.330724: +2024-11-22 02:39:11.330986: Epoch 2864 +2024-11-22 02:39:11.331114: Current learning rate: 0.00671 +2024-11-22 02:39:29.919708: train_loss -0.7731 +2024-11-22 02:39:29.928115: val_loss -0.7845 +2024-11-22 02:39:29.928233: Pseudo dice [0.8533] +2024-11-22 02:39:29.928361: Epoch time: 18.59 s +2024-11-22 02:39:31.278001: +2024-11-22 02:39:31.278250: Epoch 2865 +2024-11-22 02:39:31.278366: Current learning rate: 0.00671 +2024-11-22 02:39:50.721807: train_loss -0.7749 +2024-11-22 02:39:50.730267: val_loss -0.766 +2024-11-22 02:39:50.730453: Pseudo dice [0.8449] +2024-11-22 02:39:50.730549: Epoch time: 19.44 s +2024-11-22 02:39:51.736133: +2024-11-22 02:39:51.736375: Epoch 2866 +2024-11-22 02:39:51.736490: Current learning rate: 0.00671 +2024-11-22 02:40:10.496224: train_loss -0.774 +2024-11-22 02:40:10.502905: val_loss -0.7274 +2024-11-22 02:40:10.503033: Pseudo dice [0.8413] +2024-11-22 02:40:10.503183: Epoch time: 18.76 s +2024-11-22 02:40:11.459893: +2024-11-22 02:40:11.460148: Epoch 2867 +2024-11-22 02:40:11.460293: Current learning rate: 0.00671 +2024-11-22 02:40:30.871602: train_loss -0.7844 +2024-11-22 02:40:30.877312: val_loss -0.7534 +2024-11-22 02:40:30.877435: Pseudo dice [0.8482] +2024-11-22 02:40:30.877544: Epoch time: 19.41 s +2024-11-22 02:40:31.811516: +2024-11-22 02:40:31.811725: Epoch 2868 +2024-11-22 02:40:31.811865: Current learning rate: 0.00671 +2024-11-22 02:40:49.926334: train_loss -0.7755 +2024-11-22 02:40:49.928974: val_loss -0.77 +2024-11-22 02:40:49.929102: Pseudo dice [0.8652] +2024-11-22 02:40:49.929202: Epoch time: 18.12 s +2024-11-22 02:40:50.759588: +2024-11-22 02:40:50.759798: Epoch 2869 +2024-11-22 02:40:50.759917: Current learning rate: 0.00671 +2024-11-22 02:41:10.525123: train_loss -0.7829 +2024-11-22 02:41:10.533962: val_loss -0.7533 +2024-11-22 02:41:10.534128: Pseudo dice [0.86] +2024-11-22 02:41:10.534240: Epoch time: 19.77 s +2024-11-22 02:41:11.369206: +2024-11-22 02:41:11.369415: Epoch 2870 +2024-11-22 02:41:11.369553: Current learning rate: 0.0067 +2024-11-22 02:41:30.206599: train_loss -0.782 +2024-11-22 02:41:30.209072: val_loss -0.7547 +2024-11-22 02:41:30.209186: Pseudo dice [0.8601] +2024-11-22 02:41:30.209507: Epoch time: 18.84 s +2024-11-22 02:41:31.043358: +2024-11-22 02:41:31.043565: Epoch 2871 +2024-11-22 02:41:31.043686: Current learning rate: 0.0067 +2024-11-22 02:41:50.433517: train_loss -0.7858 +2024-11-22 02:41:50.435974: val_loss -0.7808 +2024-11-22 02:41:50.436108: Pseudo dice [0.8667] +2024-11-22 02:41:50.436202: Epoch time: 19.39 s +2024-11-22 02:41:51.266462: +2024-11-22 02:41:51.266692: Epoch 2872 +2024-11-22 02:41:51.266815: Current learning rate: 0.0067 +2024-11-22 02:42:09.878282: train_loss -0.7763 +2024-11-22 02:42:09.884477: val_loss -0.7562 +2024-11-22 02:42:09.884613: Pseudo dice [0.8459] +2024-11-22 02:42:09.884702: Epoch time: 18.61 s +2024-11-22 02:42:10.769770: +2024-11-22 02:42:10.769998: Epoch 2873 +2024-11-22 02:42:10.770134: Current learning rate: 0.0067 +2024-11-22 02:42:30.424018: train_loss -0.7821 +2024-11-22 02:42:30.435185: val_loss -0.7391 +2024-11-22 02:42:30.435341: Pseudo dice [0.8486] +2024-11-22 02:42:30.435446: Epoch time: 19.66 s +2024-11-22 02:42:31.320971: +2024-11-22 02:42:31.321194: Epoch 2874 +2024-11-22 02:42:31.321324: Current learning rate: 0.0067 +2024-11-22 02:42:51.359640: train_loss -0.7847 +2024-11-22 02:42:51.370966: val_loss -0.7659 +2024-11-22 02:42:51.371128: Pseudo dice [0.8422] +2024-11-22 02:42:51.371219: Epoch time: 20.04 s +2024-11-22 02:42:52.334286: +2024-11-22 02:42:52.334498: Epoch 2875 +2024-11-22 02:42:52.334608: Current learning rate: 0.0067 +2024-11-22 02:43:10.878199: train_loss -0.7771 +2024-11-22 02:43:10.886825: val_loss -0.7804 +2024-11-22 02:43:10.887014: Pseudo dice [0.8568] +2024-11-22 02:43:10.887113: Epoch time: 18.54 s +2024-11-22 02:43:11.922014: +2024-11-22 02:43:11.922219: Epoch 2876 +2024-11-22 02:43:11.922334: Current learning rate: 0.0067 +2024-11-22 02:43:31.484015: train_loss -0.7717 +2024-11-22 02:43:31.485437: val_loss -0.7725 +2024-11-22 02:43:31.485535: Pseudo dice [0.8524] +2024-11-22 02:43:31.485620: Epoch time: 19.56 s +2024-11-22 02:43:32.296493: +2024-11-22 02:43:32.296694: Epoch 2877 +2024-11-22 02:43:32.296831: Current learning rate: 0.0067 +2024-11-22 02:43:50.713578: train_loss -0.7826 +2024-11-22 02:43:50.732577: val_loss -0.773 +2024-11-22 02:43:50.732709: Pseudo dice [0.8557] +2024-11-22 02:43:50.732798: Epoch time: 18.42 s +2024-11-22 02:43:51.673676: +2024-11-22 02:43:51.673904: Epoch 2878 +2024-11-22 02:43:51.674032: Current learning rate: 0.00669 +2024-11-22 02:44:11.446332: train_loss -0.7659 +2024-11-22 02:44:11.453652: val_loss -0.777 +2024-11-22 02:44:11.453757: Pseudo dice [0.8525] +2024-11-22 02:44:11.453846: Epoch time: 19.77 s +2024-11-22 02:44:12.429733: +2024-11-22 02:44:12.429937: Epoch 2879 +2024-11-22 02:44:12.430055: Current learning rate: 0.00669 +2024-11-22 02:44:31.612479: train_loss -0.779 +2024-11-22 02:44:31.617048: val_loss -0.7903 +2024-11-22 02:44:31.617810: Pseudo dice [0.8576] +2024-11-22 02:44:31.617922: Epoch time: 19.18 s +2024-11-22 02:44:32.440161: +2024-11-22 02:44:32.440388: Epoch 2880 +2024-11-22 02:44:32.440527: Current learning rate: 0.00669 +2024-11-22 02:44:51.495738: train_loss -0.7817 +2024-11-22 02:44:51.502816: val_loss -0.7655 +2024-11-22 02:44:51.502964: Pseudo dice [0.8649] +2024-11-22 02:44:51.503078: Epoch time: 19.06 s +2024-11-22 02:44:51.503165: Yayy! New best EMA pseudo Dice: 0.8534 +2024-11-22 02:44:52.708497: +2024-11-22 02:44:52.708731: Epoch 2881 +2024-11-22 02:44:52.708849: Current learning rate: 0.00669 +2024-11-22 02:45:11.828198: train_loss -0.7745 +2024-11-22 02:45:11.829763: val_loss -0.7752 +2024-11-22 02:45:11.829863: Pseudo dice [0.8623] +2024-11-22 02:45:11.829960: Epoch time: 19.12 s +2024-11-22 02:45:11.830035: Yayy! New best EMA pseudo Dice: 0.8543 +2024-11-22 02:45:12.870650: +2024-11-22 02:45:12.870863: Epoch 2882 +2024-11-22 02:45:12.870983: Current learning rate: 0.00669 +2024-11-22 02:45:32.643393: train_loss -0.7881 +2024-11-22 02:45:32.648451: val_loss -0.7579 +2024-11-22 02:45:32.648568: Pseudo dice [0.8451] +2024-11-22 02:45:32.648657: Epoch time: 19.77 s +2024-11-22 02:45:33.526517: +2024-11-22 02:45:33.526714: Epoch 2883 +2024-11-22 02:45:33.526842: Current learning rate: 0.00669 +2024-11-22 02:45:52.584388: train_loss -0.7709 +2024-11-22 02:45:52.591106: val_loss -0.7709 +2024-11-22 02:45:52.591227: Pseudo dice [0.845] +2024-11-22 02:45:52.591322: Epoch time: 19.06 s +2024-11-22 02:45:53.668929: +2024-11-22 02:45:53.669168: Epoch 2884 +2024-11-22 02:45:53.669293: Current learning rate: 0.00669 +2024-11-22 02:46:12.666445: train_loss -0.7744 +2024-11-22 02:46:12.668514: val_loss -0.7613 +2024-11-22 02:46:12.668899: Pseudo dice [0.8504] +2024-11-22 02:46:12.669011: Epoch time: 19.0 s +2024-11-22 02:46:13.499312: +2024-11-22 02:46:13.499515: Epoch 2885 +2024-11-22 02:46:13.499626: Current learning rate: 0.00669 +2024-11-22 02:46:32.284411: train_loss -0.7769 +2024-11-22 02:46:32.300070: val_loss -0.7648 +2024-11-22 02:46:32.300204: Pseudo dice [0.8578] +2024-11-22 02:46:32.300295: Epoch time: 18.79 s +2024-11-22 02:46:33.321247: +2024-11-22 02:46:33.321451: Epoch 2886 +2024-11-22 02:46:33.321583: Current learning rate: 0.00669 +2024-11-22 02:46:52.642683: train_loss -0.7738 +2024-11-22 02:46:52.655158: val_loss -0.7511 +2024-11-22 02:46:52.655295: Pseudo dice [0.8369] +2024-11-22 02:46:52.655381: Epoch time: 19.32 s +2024-11-22 02:46:53.896377: +2024-11-22 02:46:53.896585: Epoch 2887 +2024-11-22 02:46:53.896710: Current learning rate: 0.00668 +2024-11-22 02:47:13.369659: train_loss -0.7943 +2024-11-22 02:47:13.374921: val_loss -0.756 +2024-11-22 02:47:13.375046: Pseudo dice [0.8478] +2024-11-22 02:47:13.375148: Epoch time: 19.47 s +2024-11-22 02:47:14.372443: +2024-11-22 02:47:14.372651: Epoch 2888 +2024-11-22 02:47:14.372771: Current learning rate: 0.00668 +2024-11-22 02:47:33.263118: train_loss -0.7831 +2024-11-22 02:47:33.270553: val_loss -0.7793 +2024-11-22 02:47:33.270685: Pseudo dice [0.8609] +2024-11-22 02:47:33.270783: Epoch time: 18.89 s +2024-11-22 02:47:34.338370: +2024-11-22 02:47:34.338601: Epoch 2889 +2024-11-22 02:47:34.338723: Current learning rate: 0.00668 +2024-11-22 02:47:53.445175: train_loss -0.7806 +2024-11-22 02:47:53.446889: val_loss -0.7685 +2024-11-22 02:47:53.447016: Pseudo dice [0.8544] +2024-11-22 02:47:53.447112: Epoch time: 19.11 s +2024-11-22 02:47:54.298152: +2024-11-22 02:47:54.298362: Epoch 2890 +2024-11-22 02:47:54.298490: Current learning rate: 0.00668 +2024-11-22 02:48:13.614475: train_loss -0.7825 +2024-11-22 02:48:13.623203: val_loss -0.7698 +2024-11-22 02:48:13.623337: Pseudo dice [0.8465] +2024-11-22 02:48:13.623423: Epoch time: 19.32 s +2024-11-22 02:48:14.526875: +2024-11-22 02:48:14.527089: Epoch 2891 +2024-11-22 02:48:14.527211: Current learning rate: 0.00668 +2024-11-22 02:48:33.265428: train_loss -0.7844 +2024-11-22 02:48:33.268417: val_loss -0.7801 +2024-11-22 02:48:33.268532: Pseudo dice [0.8562] +2024-11-22 02:48:33.268620: Epoch time: 18.74 s +2024-11-22 02:48:34.136126: +2024-11-22 02:48:34.136352: Epoch 2892 +2024-11-22 02:48:34.136492: Current learning rate: 0.00668 +2024-11-22 02:48:53.658154: train_loss -0.7822 +2024-11-22 02:48:53.662659: val_loss -0.7764 +2024-11-22 02:48:53.662781: Pseudo dice [0.8547] +2024-11-22 02:48:53.662884: Epoch time: 19.52 s +2024-11-22 02:48:54.522744: +2024-11-22 02:48:54.522950: Epoch 2893 +2024-11-22 02:48:54.523068: Current learning rate: 0.00668 +2024-11-22 02:49:13.497163: train_loss -0.7699 +2024-11-22 02:49:13.502836: val_loss -0.752 +2024-11-22 02:49:13.502965: Pseudo dice [0.8534] +2024-11-22 02:49:13.503044: Epoch time: 18.98 s +2024-11-22 02:49:14.334972: +2024-11-22 02:49:14.335177: Epoch 2894 +2024-11-22 02:49:14.335294: Current learning rate: 0.00668 +2024-11-22 02:49:33.348507: train_loss -0.7693 +2024-11-22 02:49:33.351910: val_loss -0.7623 +2024-11-22 02:49:33.352045: Pseudo dice [0.8643] +2024-11-22 02:49:33.352166: Epoch time: 19.01 s +2024-11-22 02:49:34.228899: +2024-11-22 02:49:34.229121: Epoch 2895 +2024-11-22 02:49:34.229252: Current learning rate: 0.00667 +2024-11-22 02:49:52.779478: train_loss -0.7698 +2024-11-22 02:49:52.790648: val_loss -0.7479 +2024-11-22 02:49:52.790810: Pseudo dice [0.8607] +2024-11-22 02:49:52.790920: Epoch time: 18.55 s +2024-11-22 02:49:52.791009: Yayy! New best EMA pseudo Dice: 0.8543 +2024-11-22 02:49:54.006811: +2024-11-22 02:49:54.007046: Epoch 2896 +2024-11-22 02:49:54.007165: Current learning rate: 0.00667 +2024-11-22 02:50:12.400737: train_loss -0.7803 +2024-11-22 02:50:12.419039: val_loss -0.7653 +2024-11-22 02:50:12.419200: Pseudo dice [0.8513] +2024-11-22 02:50:12.419287: Epoch time: 18.39 s +2024-11-22 02:50:13.255465: +2024-11-22 02:50:13.255661: Epoch 2897 +2024-11-22 02:50:13.255778: Current learning rate: 0.00667 +2024-11-22 02:50:31.906307: train_loss -0.7693 +2024-11-22 02:50:31.914703: val_loss -0.7456 +2024-11-22 02:50:31.914852: Pseudo dice [0.8539] +2024-11-22 02:50:31.914954: Epoch time: 18.65 s +2024-11-22 02:50:32.844227: +2024-11-22 02:50:32.844432: Epoch 2898 +2024-11-22 02:50:32.844564: Current learning rate: 0.00667 +2024-11-22 02:50:51.372347: train_loss -0.7704 +2024-11-22 02:50:51.374698: val_loss -0.7605 +2024-11-22 02:50:51.374795: Pseudo dice [0.856] +2024-11-22 02:50:51.374893: Epoch time: 18.53 s +2024-11-22 02:50:52.602705: +2024-11-22 02:50:52.602924: Epoch 2899 +2024-11-22 02:50:52.603053: Current learning rate: 0.00667 +2024-11-22 02:51:12.357160: train_loss -0.7773 +2024-11-22 02:51:12.365546: val_loss -0.7505 +2024-11-22 02:51:12.365703: Pseudo dice [0.8441] +2024-11-22 02:51:12.365794: Epoch time: 19.76 s +2024-11-22 02:51:13.466965: +2024-11-22 02:51:13.467196: Epoch 2900 +2024-11-22 02:51:13.467326: Current learning rate: 0.00667 +2024-11-22 02:51:33.122184: train_loss -0.7672 +2024-11-22 02:51:33.130865: val_loss -0.7632 +2024-11-22 02:51:33.131008: Pseudo dice [0.8458] +2024-11-22 02:51:33.131247: Epoch time: 19.66 s +2024-11-22 02:51:34.181442: +2024-11-22 02:51:34.181701: Epoch 2901 +2024-11-22 02:51:34.181827: Current learning rate: 0.00667 +2024-11-22 02:51:51.578578: train_loss -0.7778 +2024-11-22 02:51:51.581005: val_loss -0.7343 +2024-11-22 02:51:51.581122: Pseudo dice [0.8575] +2024-11-22 02:51:51.581213: Epoch time: 17.4 s +2024-11-22 02:51:52.416606: +2024-11-22 02:51:52.416840: Epoch 2902 +2024-11-22 02:51:52.416965: Current learning rate: 0.00667 +2024-11-22 02:52:10.616756: train_loss -0.7818 +2024-11-22 02:52:10.622872: val_loss -0.7571 +2024-11-22 02:52:10.623018: Pseudo dice [0.8614] +2024-11-22 02:52:10.623123: Epoch time: 18.2 s +2024-11-22 02:52:11.716719: +2024-11-22 02:52:11.716938: Epoch 2903 +2024-11-22 02:52:11.717077: Current learning rate: 0.00667 +2024-11-22 02:52:30.730631: train_loss -0.7659 +2024-11-22 02:52:30.733238: val_loss -0.7653 +2024-11-22 02:52:30.733367: Pseudo dice [0.8421] +2024-11-22 02:52:30.733460: Epoch time: 19.01 s +2024-11-22 02:52:31.582685: +2024-11-22 02:52:31.582906: Epoch 2904 +2024-11-22 02:52:31.583030: Current learning rate: 0.00666 +2024-11-22 02:52:50.363108: train_loss -0.7548 +2024-11-22 02:52:50.367506: val_loss -0.7777 +2024-11-22 02:52:50.367646: Pseudo dice [0.8508] +2024-11-22 02:52:50.367754: Epoch time: 18.78 s +2024-11-22 02:52:51.311928: +2024-11-22 02:52:51.312132: Epoch 2905 +2024-11-22 02:52:51.312254: Current learning rate: 0.00666 +2024-11-22 02:53:10.098933: train_loss -0.7579 +2024-11-22 02:53:10.104906: val_loss -0.7789 +2024-11-22 02:53:10.105080: Pseudo dice [0.8589] +2024-11-22 02:53:10.105182: Epoch time: 18.79 s +2024-11-22 02:53:10.947905: +2024-11-22 02:53:10.948144: Epoch 2906 +2024-11-22 02:53:10.948271: Current learning rate: 0.00666 +2024-11-22 02:53:30.174790: train_loss -0.7682 +2024-11-22 02:53:30.180347: val_loss -0.7466 +2024-11-22 02:53:30.180472: Pseudo dice [0.85] +2024-11-22 02:53:30.180581: Epoch time: 19.23 s +2024-11-22 02:53:31.168588: +2024-11-22 02:53:31.168818: Epoch 2907 +2024-11-22 02:53:31.168941: Current learning rate: 0.00666 +2024-11-22 02:53:50.616958: train_loss -0.7674 +2024-11-22 02:53:50.623449: val_loss -0.7515 +2024-11-22 02:53:50.623584: Pseudo dice [0.8111] +2024-11-22 02:53:50.623670: Epoch time: 19.45 s +2024-11-22 02:53:51.489734: +2024-11-22 02:53:51.489933: Epoch 2908 +2024-11-22 02:53:51.490056: Current learning rate: 0.00666 +2024-11-22 02:54:09.857464: train_loss -0.729 +2024-11-22 02:54:09.862899: val_loss -0.7639 +2024-11-22 02:54:09.863054: Pseudo dice [0.8501] +2024-11-22 02:54:09.863144: Epoch time: 18.37 s +2024-11-22 02:54:10.713418: +2024-11-22 02:54:10.713640: Epoch 2909 +2024-11-22 02:54:10.713760: Current learning rate: 0.00666 +2024-11-22 02:54:29.821613: train_loss -0.7644 +2024-11-22 02:54:29.833496: val_loss -0.7601 +2024-11-22 02:54:29.833646: Pseudo dice [0.839] +2024-11-22 02:54:29.833774: Epoch time: 19.11 s +2024-11-22 02:54:31.250473: +2024-11-22 02:54:31.250688: Epoch 2910 +2024-11-22 02:54:31.250808: Current learning rate: 0.00666 +2024-11-22 02:54:50.834047: train_loss -0.7568 +2024-11-22 02:54:50.839744: val_loss -0.7731 +2024-11-22 02:54:50.839882: Pseudo dice [0.8415] +2024-11-22 02:54:50.846300: Epoch time: 19.58 s +2024-11-22 02:54:51.806404: +2024-11-22 02:54:51.806635: Epoch 2911 +2024-11-22 02:54:51.806750: Current learning rate: 0.00666 +2024-11-22 02:55:10.984594: train_loss -0.7626 +2024-11-22 02:55:10.992691: val_loss -0.7959 +2024-11-22 02:55:10.992832: Pseudo dice [0.8563] +2024-11-22 02:55:10.992928: Epoch time: 19.18 s +2024-11-22 02:55:11.829077: +2024-11-22 02:55:11.829302: Epoch 2912 +2024-11-22 02:55:11.829432: Current learning rate: 0.00665 +2024-11-22 02:55:30.548856: train_loss -0.768 +2024-11-22 02:55:30.550847: val_loss -0.7543 +2024-11-22 02:55:30.550943: Pseudo dice [0.8359] +2024-11-22 02:55:30.551047: Epoch time: 18.72 s +2024-11-22 02:55:31.385875: +2024-11-22 02:55:31.386089: Epoch 2913 +2024-11-22 02:55:31.386209: Current learning rate: 0.00665 +2024-11-22 02:55:50.722592: train_loss -0.776 +2024-11-22 02:55:50.726481: val_loss -0.7769 +2024-11-22 02:55:50.726618: Pseudo dice [0.8595] +2024-11-22 02:55:50.726719: Epoch time: 19.34 s +2024-11-22 02:55:51.633811: +2024-11-22 02:55:51.634022: Epoch 2914 +2024-11-22 02:55:51.634174: Current learning rate: 0.00665 +2024-11-22 02:56:10.148548: train_loss -0.775 +2024-11-22 02:56:10.159630: val_loss -0.7643 +2024-11-22 02:56:10.159791: Pseudo dice [0.8462] +2024-11-22 02:56:10.159894: Epoch time: 18.52 s +2024-11-22 02:56:11.116273: +2024-11-22 02:56:11.116481: Epoch 2915 +2024-11-22 02:56:11.116603: Current learning rate: 0.00665 +2024-11-22 02:56:30.792527: train_loss -0.7465 +2024-11-22 02:56:30.799119: val_loss -0.7385 +2024-11-22 02:56:30.799244: Pseudo dice [0.851] +2024-11-22 02:56:30.799341: Epoch time: 19.68 s +2024-11-22 02:56:31.670381: +2024-11-22 02:56:31.670590: Epoch 2916 +2024-11-22 02:56:31.670707: Current learning rate: 0.00665 +2024-11-22 02:56:49.964602: train_loss -0.7624 +2024-11-22 02:56:49.974408: val_loss -0.7594 +2024-11-22 02:56:49.974542: Pseudo dice [0.8556] +2024-11-22 02:56:49.974638: Epoch time: 18.3 s +2024-11-22 02:56:50.955380: +2024-11-22 02:56:50.972243: Epoch 2917 +2024-11-22 02:56:50.972385: Current learning rate: 0.00665 +2024-11-22 02:57:09.898614: train_loss -0.7679 +2024-11-22 02:57:09.917558: val_loss -0.7822 +2024-11-22 02:57:09.917708: Pseudo dice [0.834] +2024-11-22 02:57:09.917823: Epoch time: 18.94 s +2024-11-22 02:57:10.847829: +2024-11-22 02:57:10.848048: Epoch 2918 +2024-11-22 02:57:10.848174: Current learning rate: 0.00665 +2024-11-22 02:57:30.625616: train_loss -0.7711 +2024-11-22 02:57:30.632579: val_loss -0.7909 +2024-11-22 02:57:30.632773: Pseudo dice [0.8594] +2024-11-22 02:57:30.632865: Epoch time: 19.78 s +2024-11-22 02:57:31.479064: +2024-11-22 02:57:31.479258: Epoch 2919 +2024-11-22 02:57:31.479369: Current learning rate: 0.00665 +2024-11-22 02:57:50.489102: train_loss -0.7803 +2024-11-22 02:57:50.491955: val_loss -0.762 +2024-11-22 02:57:50.492053: Pseudo dice [0.8424] +2024-11-22 02:57:50.492151: Epoch time: 19.01 s +2024-11-22 02:57:51.328409: +2024-11-22 02:57:51.328633: Epoch 2920 +2024-11-22 02:57:51.328751: Current learning rate: 0.00665 +2024-11-22 02:58:10.122382: train_loss -0.7818 +2024-11-22 02:58:10.124614: val_loss -0.7549 +2024-11-22 02:58:10.124722: Pseudo dice [0.8482] +2024-11-22 02:58:10.124818: Epoch time: 18.79 s +2024-11-22 02:58:10.961423: +2024-11-22 02:58:10.961632: Epoch 2921 +2024-11-22 02:58:10.961781: Current learning rate: 0.00664 +2024-11-22 02:58:29.813695: train_loss -0.7677 +2024-11-22 02:58:29.817951: val_loss -0.763 +2024-11-22 02:58:29.818112: Pseudo dice [0.8435] +2024-11-22 02:58:29.818206: Epoch time: 18.84 s +2024-11-22 02:58:31.274264: +2024-11-22 02:58:31.274496: Epoch 2922 +2024-11-22 02:58:31.274619: Current learning rate: 0.00664 +2024-11-22 02:58:49.969273: train_loss -0.7714 +2024-11-22 02:58:49.972081: val_loss -0.76 +2024-11-22 02:58:49.972212: Pseudo dice [0.8313] +2024-11-22 02:58:49.972299: Epoch time: 18.7 s +2024-11-22 02:58:50.928845: +2024-11-22 02:58:50.929049: Epoch 2923 +2024-11-22 02:58:50.929180: Current learning rate: 0.00664 +2024-11-22 02:59:09.354215: train_loss -0.7773 +2024-11-22 02:59:09.361147: val_loss -0.7618 +2024-11-22 02:59:09.361324: Pseudo dice [0.8596] +2024-11-22 02:59:09.361428: Epoch time: 18.43 s +2024-11-22 02:59:10.203308: +2024-11-22 02:59:10.203513: Epoch 2924 +2024-11-22 02:59:10.203631: Current learning rate: 0.00664 +2024-11-22 02:59:28.807132: train_loss -0.7716 +2024-11-22 02:59:28.809521: val_loss -0.7474 +2024-11-22 02:59:28.809654: Pseudo dice [0.8523] +2024-11-22 02:59:28.809745: Epoch time: 18.6 s +2024-11-22 02:59:29.721003: +2024-11-22 02:59:29.721303: Epoch 2925 +2024-11-22 02:59:29.721436: Current learning rate: 0.00664 +2024-11-22 02:59:48.339335: train_loss -0.7741 +2024-11-22 02:59:48.347175: val_loss -0.7569 +2024-11-22 02:59:48.347315: Pseudo dice [0.8487] +2024-11-22 02:59:48.347404: Epoch time: 18.62 s +2024-11-22 02:59:49.332310: +2024-11-22 02:59:49.332520: Epoch 2926 +2024-11-22 02:59:49.332651: Current learning rate: 0.00664 +2024-11-22 03:00:08.325754: train_loss -0.7748 +2024-11-22 03:00:08.330954: val_loss -0.747 +2024-11-22 03:00:08.331107: Pseudo dice [0.8377] +2024-11-22 03:00:08.331220: Epoch time: 18.99 s +2024-11-22 03:00:09.257268: +2024-11-22 03:00:09.257528: Epoch 2927 +2024-11-22 03:00:09.257659: Current learning rate: 0.00664 +2024-11-22 03:00:29.433019: train_loss -0.7815 +2024-11-22 03:00:29.439577: val_loss -0.7475 +2024-11-22 03:00:29.439715: Pseudo dice [0.8498] +2024-11-22 03:00:29.439835: Epoch time: 20.18 s +2024-11-22 03:00:30.509701: +2024-11-22 03:00:30.509902: Epoch 2928 +2024-11-22 03:00:30.510022: Current learning rate: 0.00664 +2024-11-22 03:00:49.923812: train_loss -0.7802 +2024-11-22 03:00:49.934993: val_loss -0.7306 +2024-11-22 03:00:49.935121: Pseudo dice [0.8495] +2024-11-22 03:00:49.935226: Epoch time: 19.41 s +2024-11-22 03:00:50.780627: +2024-11-22 03:00:50.780830: Epoch 2929 +2024-11-22 03:00:50.780940: Current learning rate: 0.00663 +2024-11-22 03:01:10.965230: train_loss -0.7684 +2024-11-22 03:01:10.973346: val_loss -0.7501 +2024-11-22 03:01:10.973476: Pseudo dice [0.8537] +2024-11-22 03:01:10.973795: Epoch time: 20.19 s +2024-11-22 03:01:12.009063: +2024-11-22 03:01:12.009312: Epoch 2930 +2024-11-22 03:01:12.009431: Current learning rate: 0.00663 +2024-11-22 03:01:30.104341: train_loss -0.7729 +2024-11-22 03:01:30.108550: val_loss -0.7865 +2024-11-22 03:01:30.108667: Pseudo dice [0.8654] +2024-11-22 03:01:30.108770: Epoch time: 18.1 s +2024-11-22 03:01:31.162962: +2024-11-22 03:01:31.163161: Epoch 2931 +2024-11-22 03:01:31.163285: Current learning rate: 0.00663 +2024-11-22 03:01:50.740246: train_loss -0.7851 +2024-11-22 03:01:50.743105: val_loss -0.7623 +2024-11-22 03:01:50.743236: Pseudo dice [0.857] +2024-11-22 03:01:50.743326: Epoch time: 19.58 s +2024-11-22 03:01:51.807702: +2024-11-22 03:01:51.807914: Epoch 2932 +2024-11-22 03:01:51.808033: Current learning rate: 0.00663 +2024-11-22 03:02:10.422407: train_loss -0.7834 +2024-11-22 03:02:10.426225: val_loss -0.7701 +2024-11-22 03:02:10.426430: Pseudo dice [0.8435] +2024-11-22 03:02:10.426513: Epoch time: 18.62 s +2024-11-22 03:02:11.717133: +2024-11-22 03:02:11.717346: Epoch 2933 +2024-11-22 03:02:11.717459: Current learning rate: 0.00663 +2024-11-22 03:02:29.090098: train_loss -0.7844 +2024-11-22 03:02:29.094411: val_loss -0.7876 +2024-11-22 03:02:29.094545: Pseudo dice [0.846] +2024-11-22 03:02:29.094639: Epoch time: 17.37 s +2024-11-22 03:02:30.020973: +2024-11-22 03:02:30.021183: Epoch 2934 +2024-11-22 03:02:30.021301: Current learning rate: 0.00663 +2024-11-22 03:02:48.916706: train_loss -0.774 +2024-11-22 03:02:48.921162: val_loss -0.7932 +2024-11-22 03:02:48.921301: Pseudo dice [0.846] +2024-11-22 03:02:48.921406: Epoch time: 18.9 s +2024-11-22 03:02:49.761221: +2024-11-22 03:02:49.761468: Epoch 2935 +2024-11-22 03:02:49.761606: Current learning rate: 0.00663 +2024-11-22 03:03:09.566152: train_loss -0.777 +2024-11-22 03:03:09.568511: val_loss -0.7741 +2024-11-22 03:03:09.568631: Pseudo dice [0.8394] +2024-11-22 03:03:09.568730: Epoch time: 19.81 s +2024-11-22 03:03:10.405549: +2024-11-22 03:03:10.405764: Epoch 2936 +2024-11-22 03:03:10.406127: Current learning rate: 0.00663 +2024-11-22 03:03:28.794242: train_loss -0.775 +2024-11-22 03:03:28.802437: val_loss -0.7725 +2024-11-22 03:03:28.802582: Pseudo dice [0.8473] +2024-11-22 03:03:28.802687: Epoch time: 18.39 s +2024-11-22 03:03:29.839350: +2024-11-22 03:03:29.839569: Epoch 2937 +2024-11-22 03:03:29.839702: Current learning rate: 0.00663 +2024-11-22 03:03:49.207364: train_loss -0.7685 +2024-11-22 03:03:49.209815: val_loss -0.7472 +2024-11-22 03:03:49.209923: Pseudo dice [0.8356] +2024-11-22 03:03:49.210022: Epoch time: 19.37 s +2024-11-22 03:03:50.047925: +2024-11-22 03:03:50.048134: Epoch 2938 +2024-11-22 03:03:50.048259: Current learning rate: 0.00662 +2024-11-22 03:04:09.285285: train_loss -0.7531 +2024-11-22 03:04:09.300122: val_loss -0.7599 +2024-11-22 03:04:09.300274: Pseudo dice [0.8547] +2024-11-22 03:04:09.300375: Epoch time: 19.24 s +2024-11-22 03:04:10.244026: +2024-11-22 03:04:10.244226: Epoch 2939 +2024-11-22 03:04:10.244353: Current learning rate: 0.00662 +2024-11-22 03:04:28.728301: train_loss -0.7692 +2024-11-22 03:04:28.737203: val_loss -0.7526 +2024-11-22 03:04:28.737392: Pseudo dice [0.8474] +2024-11-22 03:04:28.737529: Epoch time: 18.49 s +2024-11-22 03:04:29.722750: +2024-11-22 03:04:29.723004: Epoch 2940 +2024-11-22 03:04:29.723145: Current learning rate: 0.00662 +2024-11-22 03:04:48.072100: train_loss -0.7759 +2024-11-22 03:04:48.074535: val_loss -0.7521 +2024-11-22 03:04:48.074651: Pseudo dice [0.8439] +2024-11-22 03:04:48.074757: Epoch time: 18.35 s +2024-11-22 03:04:48.912621: +2024-11-22 03:04:48.912843: Epoch 2941 +2024-11-22 03:04:48.912966: Current learning rate: 0.00662 +2024-11-22 03:05:08.249171: train_loss -0.7724 +2024-11-22 03:05:08.255053: val_loss -0.7599 +2024-11-22 03:05:08.255213: Pseudo dice [0.8506] +2024-11-22 03:05:08.255319: Epoch time: 19.34 s +2024-11-22 03:05:09.107022: +2024-11-22 03:05:09.107229: Epoch 2942 +2024-11-22 03:05:09.107346: Current learning rate: 0.00662 +2024-11-22 03:05:28.427055: train_loss -0.7743 +2024-11-22 03:05:28.429958: val_loss -0.7801 +2024-11-22 03:05:28.430105: Pseudo dice [0.8587] +2024-11-22 03:05:28.430205: Epoch time: 19.32 s +2024-11-22 03:05:29.503187: +2024-11-22 03:05:29.503388: Epoch 2943 +2024-11-22 03:05:29.503514: Current learning rate: 0.00662 +2024-11-22 03:05:49.159217: train_loss -0.7731 +2024-11-22 03:05:49.161316: val_loss -0.7706 +2024-11-22 03:05:49.161415: Pseudo dice [0.8691] +2024-11-22 03:05:49.161504: Epoch time: 19.66 s +2024-11-22 03:05:49.990563: +2024-11-22 03:05:49.990774: Epoch 2944 +2024-11-22 03:05:49.990900: Current learning rate: 0.00662 +2024-11-22 03:06:07.893527: train_loss -0.7607 +2024-11-22 03:06:07.895767: val_loss -0.7283 +2024-11-22 03:06:07.895894: Pseudo dice [0.8229] +2024-11-22 03:06:07.895991: Epoch time: 17.9 s +2024-11-22 03:06:09.176861: +2024-11-22 03:06:09.177109: Epoch 2945 +2024-11-22 03:06:09.177240: Current learning rate: 0.00662 +2024-11-22 03:06:28.953332: train_loss -0.7643 +2024-11-22 03:06:28.955722: val_loss -0.7684 +2024-11-22 03:06:28.955820: Pseudo dice [0.861] +2024-11-22 03:06:28.955921: Epoch time: 19.78 s +2024-11-22 03:06:29.793041: +2024-11-22 03:06:29.793266: Epoch 2946 +2024-11-22 03:06:29.793400: Current learning rate: 0.00661 +2024-11-22 03:06:48.948669: train_loss -0.7754 +2024-11-22 03:06:48.962132: val_loss -0.7702 +2024-11-22 03:06:48.962266: Pseudo dice [0.8405] +2024-11-22 03:06:48.962366: Epoch time: 19.16 s +2024-11-22 03:06:50.154657: +2024-11-22 03:06:50.154907: Epoch 2947 +2024-11-22 03:06:50.155028: Current learning rate: 0.00661 +2024-11-22 03:07:09.988674: train_loss -0.7879 +2024-11-22 03:07:09.995469: val_loss -0.7773 +2024-11-22 03:07:10.021347: Pseudo dice [0.8531] +2024-11-22 03:07:10.021676: Epoch time: 19.83 s +2024-11-22 03:07:11.069991: +2024-11-22 03:07:11.070206: Epoch 2948 +2024-11-22 03:07:11.070344: Current learning rate: 0.00661 +2024-11-22 03:07:30.622301: train_loss -0.7831 +2024-11-22 03:07:30.627715: val_loss -0.7703 +2024-11-22 03:07:30.627941: Pseudo dice [0.8398] +2024-11-22 03:07:30.628065: Epoch time: 19.55 s +2024-11-22 03:07:31.818169: +2024-11-22 03:07:31.818428: Epoch 2949 +2024-11-22 03:07:31.818580: Current learning rate: 0.00661 +2024-11-22 03:07:51.486728: train_loss -0.7781 +2024-11-22 03:07:51.502804: val_loss -0.7532 +2024-11-22 03:07:51.502948: Pseudo dice [0.8388] +2024-11-22 03:07:51.503048: Epoch time: 19.67 s +2024-11-22 03:07:52.609328: +2024-11-22 03:07:52.609525: Epoch 2950 +2024-11-22 03:07:52.609654: Current learning rate: 0.00661 +2024-11-22 03:08:11.085583: train_loss -0.7854 +2024-11-22 03:08:11.091931: val_loss -0.7718 +2024-11-22 03:08:11.092073: Pseudo dice [0.8565] +2024-11-22 03:08:11.092170: Epoch time: 18.48 s +2024-11-22 03:08:11.949647: +2024-11-22 03:08:11.949845: Epoch 2951 +2024-11-22 03:08:11.949970: Current learning rate: 0.00661 +2024-11-22 03:08:30.552274: train_loss -0.7677 +2024-11-22 03:08:30.559206: val_loss -0.7614 +2024-11-22 03:08:30.569525: Pseudo dice [0.846] +2024-11-22 03:08:30.569647: Epoch time: 18.6 s +2024-11-22 03:08:31.457162: +2024-11-22 03:08:31.457384: Epoch 2952 +2024-11-22 03:08:31.457507: Current learning rate: 0.00661 +2024-11-22 03:08:50.308065: train_loss -0.7639 +2024-11-22 03:08:50.314310: val_loss -0.7772 +2024-11-22 03:08:50.314536: Pseudo dice [0.8408] +2024-11-22 03:08:50.314682: Epoch time: 18.85 s +2024-11-22 03:08:51.154557: +2024-11-22 03:08:51.154771: Epoch 2953 +2024-11-22 03:08:51.154905: Current learning rate: 0.00661 +2024-11-22 03:09:10.573350: train_loss -0.7655 +2024-11-22 03:09:10.582985: val_loss -0.7503 +2024-11-22 03:09:10.583158: Pseudo dice [0.8402] +2024-11-22 03:09:10.583265: Epoch time: 19.42 s +2024-11-22 03:09:11.424842: +2024-11-22 03:09:11.425038: Epoch 2954 +2024-11-22 03:09:11.425159: Current learning rate: 0.0066 +2024-11-22 03:09:31.428706: train_loss -0.7704 +2024-11-22 03:09:31.430820: val_loss -0.7768 +2024-11-22 03:09:31.430920: Pseudo dice [0.8553] +2024-11-22 03:09:31.431036: Epoch time: 20.0 s +2024-11-22 03:09:32.271895: +2024-11-22 03:09:32.272129: Epoch 2955 +2024-11-22 03:09:32.272491: Current learning rate: 0.0066 +2024-11-22 03:09:51.945555: train_loss -0.7801 +2024-11-22 03:09:51.952667: val_loss -0.7836 +2024-11-22 03:09:51.952790: Pseudo dice [0.8573] +2024-11-22 03:09:51.952879: Epoch time: 19.67 s +2024-11-22 03:09:53.209280: +2024-11-22 03:09:53.209475: Epoch 2956 +2024-11-22 03:09:53.209607: Current learning rate: 0.0066 +2024-11-22 03:10:11.735178: train_loss -0.7776 +2024-11-22 03:10:11.739969: val_loss -0.7487 +2024-11-22 03:10:11.740100: Pseudo dice [0.8428] +2024-11-22 03:10:11.740205: Epoch time: 18.53 s +2024-11-22 03:10:12.850192: +2024-11-22 03:10:12.850412: Epoch 2957 +2024-11-22 03:10:12.850533: Current learning rate: 0.0066 +2024-11-22 03:10:30.869986: train_loss -0.7833 +2024-11-22 03:10:30.872425: val_loss -0.7732 +2024-11-22 03:10:30.872547: Pseudo dice [0.8379] +2024-11-22 03:10:30.872643: Epoch time: 18.02 s +2024-11-22 03:10:31.864761: +2024-11-22 03:10:31.865015: Epoch 2958 +2024-11-22 03:10:31.865141: Current learning rate: 0.0066 +2024-11-22 03:10:50.473001: train_loss -0.7792 +2024-11-22 03:10:50.479478: val_loss -0.7731 +2024-11-22 03:10:50.479627: Pseudo dice [0.8596] +2024-11-22 03:10:50.479732: Epoch time: 18.61 s +2024-11-22 03:10:51.351093: +2024-11-22 03:10:51.351315: Epoch 2959 +2024-11-22 03:10:51.351431: Current learning rate: 0.0066 +2024-11-22 03:11:10.388073: train_loss -0.7785 +2024-11-22 03:11:10.393213: val_loss -0.788 +2024-11-22 03:11:10.393372: Pseudo dice [0.8524] +2024-11-22 03:11:10.393467: Epoch time: 19.04 s +2024-11-22 03:11:11.276013: +2024-11-22 03:11:11.276253: Epoch 2960 +2024-11-22 03:11:11.276393: Current learning rate: 0.0066 +2024-11-22 03:11:30.981375: train_loss -0.7842 +2024-11-22 03:11:30.988119: val_loss -0.7611 +2024-11-22 03:11:30.988277: Pseudo dice [0.845] +2024-11-22 03:11:30.988386: Epoch time: 19.71 s +2024-11-22 03:11:31.837635: +2024-11-22 03:11:31.837909: Epoch 2961 +2024-11-22 03:11:31.838041: Current learning rate: 0.0066 +2024-11-22 03:11:51.071920: train_loss -0.7819 +2024-11-22 03:11:51.079188: val_loss -0.7531 +2024-11-22 03:11:51.079387: Pseudo dice [0.8575] +2024-11-22 03:11:51.079486: Epoch time: 19.24 s +2024-11-22 03:11:51.921743: +2024-11-22 03:11:51.921948: Epoch 2962 +2024-11-22 03:11:51.922622: Current learning rate: 0.0066 +2024-11-22 03:12:10.272588: train_loss -0.7798 +2024-11-22 03:12:10.282953: val_loss -0.7706 +2024-11-22 03:12:10.283191: Pseudo dice [0.8454] +2024-11-22 03:12:10.283292: Epoch time: 18.35 s +2024-11-22 03:12:11.120371: +2024-11-22 03:12:11.120597: Epoch 2963 +2024-11-22 03:12:11.120739: Current learning rate: 0.00659 +2024-11-22 03:12:29.939552: train_loss -0.7687 +2024-11-22 03:12:29.948809: val_loss -0.7634 +2024-11-22 03:12:29.948939: Pseudo dice [0.8435] +2024-11-22 03:12:29.949027: Epoch time: 18.82 s +2024-11-22 03:12:30.967558: +2024-11-22 03:12:30.967781: Epoch 2964 +2024-11-22 03:12:30.967915: Current learning rate: 0.00659 +2024-11-22 03:12:50.382098: train_loss -0.765 +2024-11-22 03:12:50.387025: val_loss -0.7474 +2024-11-22 03:12:50.387219: Pseudo dice [0.8531] +2024-11-22 03:12:50.387323: Epoch time: 19.42 s +2024-11-22 03:12:51.227605: +2024-11-22 03:12:51.227807: Epoch 2965 +2024-11-22 03:12:51.227926: Current learning rate: 0.00659 +2024-11-22 03:13:10.220765: train_loss -0.7777 +2024-11-22 03:13:10.242038: val_loss -0.77 +2024-11-22 03:13:10.242197: Pseudo dice [0.8593] +2024-11-22 03:13:10.242298: Epoch time: 18.99 s +2024-11-22 03:13:11.217620: +2024-11-22 03:13:11.217838: Epoch 2966 +2024-11-22 03:13:11.217961: Current learning rate: 0.00659 +2024-11-22 03:13:31.274137: train_loss -0.7626 +2024-11-22 03:13:31.281595: val_loss -0.7512 +2024-11-22 03:13:31.281794: Pseudo dice [0.8519] +2024-11-22 03:13:31.281911: Epoch time: 20.06 s +2024-11-22 03:13:32.354541: +2024-11-22 03:13:32.354725: Epoch 2967 +2024-11-22 03:13:32.354844: Current learning rate: 0.00659 +2024-11-22 03:13:51.367598: train_loss -0.781 +2024-11-22 03:13:51.376197: val_loss -0.779 +2024-11-22 03:13:51.376401: Pseudo dice [0.8534] +2024-11-22 03:13:51.376507: Epoch time: 19.01 s +2024-11-22 03:13:52.815291: +2024-11-22 03:13:52.815546: Epoch 2968 +2024-11-22 03:13:52.815673: Current learning rate: 0.00659 +2024-11-22 03:14:12.469735: train_loss -0.78 +2024-11-22 03:14:12.477146: val_loss -0.7762 +2024-11-22 03:14:12.477264: Pseudo dice [0.8545] +2024-11-22 03:14:12.477365: Epoch time: 19.66 s +2024-11-22 03:14:13.407261: +2024-11-22 03:14:13.407479: Epoch 2969 +2024-11-22 03:14:13.407603: Current learning rate: 0.00659 +2024-11-22 03:14:32.384179: train_loss -0.7711 +2024-11-22 03:14:32.390853: val_loss -0.7703 +2024-11-22 03:14:32.391004: Pseudo dice [0.8618] +2024-11-22 03:14:32.391158: Epoch time: 18.98 s +2024-11-22 03:14:33.289045: +2024-11-22 03:14:33.289285: Epoch 2970 +2024-11-22 03:14:33.289430: Current learning rate: 0.00659 +2024-11-22 03:14:51.190747: train_loss -0.7835 +2024-11-22 03:14:51.199038: val_loss -0.7641 +2024-11-22 03:14:51.199172: Pseudo dice [0.8649] +2024-11-22 03:14:51.199273: Epoch time: 17.9 s +2024-11-22 03:14:52.252210: +2024-11-22 03:14:52.256900: Epoch 2971 +2024-11-22 03:14:52.257031: Current learning rate: 0.00658 +2024-11-22 03:15:11.714544: train_loss -0.7868 +2024-11-22 03:15:11.721208: val_loss -0.7694 +2024-11-22 03:15:11.721339: Pseudo dice [0.8444] +2024-11-22 03:15:11.721430: Epoch time: 19.46 s +2024-11-22 03:15:12.577370: +2024-11-22 03:15:12.577591: Epoch 2972 +2024-11-22 03:15:12.577717: Current learning rate: 0.00658 +2024-11-22 03:15:30.412283: train_loss -0.7707 +2024-11-22 03:15:30.414912: val_loss -0.7608 +2024-11-22 03:15:30.415026: Pseudo dice [0.8472] +2024-11-22 03:15:30.415128: Epoch time: 17.84 s +2024-11-22 03:15:31.283836: +2024-11-22 03:15:31.284063: Epoch 2973 +2024-11-22 03:15:31.284176: Current learning rate: 0.00658 +2024-11-22 03:15:49.672875: train_loss -0.7798 +2024-11-22 03:15:49.680482: val_loss -0.7661 +2024-11-22 03:15:49.680634: Pseudo dice [0.8501] +2024-11-22 03:15:49.680792: Epoch time: 18.39 s +2024-11-22 03:15:50.623495: +2024-11-22 03:15:50.623738: Epoch 2974 +2024-11-22 03:15:50.623888: Current learning rate: 0.00658 +2024-11-22 03:16:09.117153: train_loss -0.7745 +2024-11-22 03:16:09.119330: val_loss -0.7621 +2024-11-22 03:16:09.119437: Pseudo dice [0.8625] +2024-11-22 03:16:09.119528: Epoch time: 18.49 s +2024-11-22 03:16:09.954740: +2024-11-22 03:16:09.954969: Epoch 2975 +2024-11-22 03:16:09.955086: Current learning rate: 0.00658 +2024-11-22 03:16:27.983533: train_loss -0.7829 +2024-11-22 03:16:27.985969: val_loss -0.7611 +2024-11-22 03:16:27.986093: Pseudo dice [0.8517] +2024-11-22 03:16:27.986181: Epoch time: 18.03 s +2024-11-22 03:16:28.862227: +2024-11-22 03:16:28.862478: Epoch 2976 +2024-11-22 03:16:28.862620: Current learning rate: 0.00658 +2024-11-22 03:16:48.605869: train_loss -0.7767 +2024-11-22 03:16:48.612399: val_loss -0.7811 +2024-11-22 03:16:48.612509: Pseudo dice [0.8424] +2024-11-22 03:16:48.612604: Epoch time: 19.74 s +2024-11-22 03:16:49.720358: +2024-11-22 03:16:49.720604: Epoch 2977 +2024-11-22 03:16:49.720737: Current learning rate: 0.00658 +2024-11-22 03:17:10.022954: train_loss -0.7706 +2024-11-22 03:17:10.031352: val_loss -0.7652 +2024-11-22 03:17:10.031534: Pseudo dice [0.8466] +2024-11-22 03:17:10.031651: Epoch time: 20.3 s +2024-11-22 03:17:11.043448: +2024-11-22 03:17:11.043685: Epoch 2978 +2024-11-22 03:17:11.043810: Current learning rate: 0.00658 +2024-11-22 03:17:30.345123: train_loss -0.7713 +2024-11-22 03:17:30.357709: val_loss -0.755 +2024-11-22 03:17:30.357845: Pseudo dice [0.8577] +2024-11-22 03:17:30.357944: Epoch time: 19.3 s +2024-11-22 03:17:31.672700: +2024-11-22 03:17:31.672898: Epoch 2979 +2024-11-22 03:17:31.673021: Current learning rate: 0.00658 +2024-11-22 03:17:51.456410: train_loss -0.7787 +2024-11-22 03:17:51.463310: val_loss -0.7508 +2024-11-22 03:17:51.463452: Pseudo dice [0.8521] +2024-11-22 03:17:51.463546: Epoch time: 19.78 s +2024-11-22 03:17:52.405949: +2024-11-22 03:17:52.406188: Epoch 2980 +2024-11-22 03:17:52.406330: Current learning rate: 0.00657 +2024-11-22 03:18:10.693064: train_loss -0.7817 +2024-11-22 03:18:10.700127: val_loss -0.7773 +2024-11-22 03:18:10.700484: Pseudo dice [0.8491] +2024-11-22 03:18:10.700594: Epoch time: 18.29 s +2024-11-22 03:18:11.691456: +2024-11-22 03:18:11.691708: Epoch 2981 +2024-11-22 03:18:11.691826: Current learning rate: 0.00657 +2024-11-22 03:18:31.287012: train_loss -0.7805 +2024-11-22 03:18:31.295752: val_loss -0.7616 +2024-11-22 03:18:31.295908: Pseudo dice [0.8361] +2024-11-22 03:18:31.296006: Epoch time: 19.6 s +2024-11-22 03:18:32.150693: +2024-11-22 03:18:32.150888: Epoch 2982 +2024-11-22 03:18:32.151005: Current learning rate: 0.00657 +2024-11-22 03:18:51.618826: train_loss -0.7678 +2024-11-22 03:18:51.627387: val_loss -0.7696 +2024-11-22 03:18:51.627520: Pseudo dice [0.8396] +2024-11-22 03:18:51.627698: Epoch time: 19.47 s +2024-11-22 03:18:52.589178: +2024-11-22 03:18:52.589389: Epoch 2983 +2024-11-22 03:18:52.589533: Current learning rate: 0.00657 +2024-11-22 03:19:11.753500: train_loss -0.7779 +2024-11-22 03:19:11.762627: val_loss -0.7475 +2024-11-22 03:19:11.762798: Pseudo dice [0.8424] +2024-11-22 03:19:11.762910: Epoch time: 19.17 s +2024-11-22 03:19:12.604443: +2024-11-22 03:19:12.604655: Epoch 2984 +2024-11-22 03:19:12.604770: Current learning rate: 0.00657 +2024-11-22 03:19:30.970785: train_loss -0.7752 +2024-11-22 03:19:30.977280: val_loss -0.7726 +2024-11-22 03:19:30.977461: Pseudo dice [0.8526] +2024-11-22 03:19:30.977548: Epoch time: 18.37 s +2024-11-22 03:19:31.901771: +2024-11-22 03:19:31.902033: Epoch 2985 +2024-11-22 03:19:31.902156: Current learning rate: 0.00657 +2024-11-22 03:19:52.035091: train_loss -0.7918 +2024-11-22 03:19:52.043324: val_loss -0.7832 +2024-11-22 03:19:52.043442: Pseudo dice [0.8532] +2024-11-22 03:19:52.043538: Epoch time: 20.13 s +2024-11-22 03:19:53.009158: +2024-11-22 03:19:53.009362: Epoch 2986 +2024-11-22 03:19:53.009474: Current learning rate: 0.00657 +2024-11-22 03:20:11.876843: train_loss -0.7739 +2024-11-22 03:20:11.883407: val_loss -0.7302 +2024-11-22 03:20:11.883542: Pseudo dice [0.8391] +2024-11-22 03:20:11.883705: Epoch time: 18.87 s +2024-11-22 03:20:12.750816: +2024-11-22 03:20:12.751050: Epoch 2987 +2024-11-22 03:20:12.751177: Current learning rate: 0.00657 +2024-11-22 03:20:32.024972: train_loss -0.7834 +2024-11-22 03:20:32.032202: val_loss -0.7596 +2024-11-22 03:20:32.032349: Pseudo dice [0.8453] +2024-11-22 03:20:32.032447: Epoch time: 19.27 s +2024-11-22 03:20:33.129968: +2024-11-22 03:20:33.130353: Epoch 2988 +2024-11-22 03:20:33.130491: Current learning rate: 0.00656 +2024-11-22 03:20:52.079279: train_loss -0.7678 +2024-11-22 03:20:52.083904: val_loss -0.7523 +2024-11-22 03:20:52.084070: Pseudo dice [0.838] +2024-11-22 03:20:52.084173: Epoch time: 18.95 s +2024-11-22 03:20:52.928480: +2024-11-22 03:20:52.928714: Epoch 2989 +2024-11-22 03:20:52.928834: Current learning rate: 0.00656 +2024-11-22 03:21:11.223585: train_loss -0.7744 +2024-11-22 03:21:11.229688: val_loss -0.7773 +2024-11-22 03:21:11.229817: Pseudo dice [0.855] +2024-11-22 03:21:11.229920: Epoch time: 18.3 s +2024-11-22 03:21:12.249863: +2024-11-22 03:21:12.250055: Epoch 2990 +2024-11-22 03:21:12.250173: Current learning rate: 0.00656 +2024-11-22 03:21:31.348073: train_loss -0.7782 +2024-11-22 03:21:31.356154: val_loss -0.7549 +2024-11-22 03:21:31.356284: Pseudo dice [0.8335] +2024-11-22 03:21:31.356377: Epoch time: 19.1 s +2024-11-22 03:21:32.840674: +2024-11-22 03:21:32.840892: Epoch 2991 +2024-11-22 03:21:32.841004: Current learning rate: 0.00656 +2024-11-22 03:21:51.922937: train_loss -0.779 +2024-11-22 03:21:51.925559: val_loss -0.7731 +2024-11-22 03:21:51.925661: Pseudo dice [0.8487] +2024-11-22 03:21:51.925762: Epoch time: 19.08 s +2024-11-22 03:21:52.758975: +2024-11-22 03:21:52.759230: Epoch 2992 +2024-11-22 03:21:52.759397: Current learning rate: 0.00656 +2024-11-22 03:22:11.782146: train_loss -0.776 +2024-11-22 03:22:11.787832: val_loss -0.7632 +2024-11-22 03:22:11.787971: Pseudo dice [0.8728] +2024-11-22 03:22:11.788080: Epoch time: 19.02 s +2024-11-22 03:22:12.637127: +2024-11-22 03:22:12.637350: Epoch 2993 +2024-11-22 03:22:12.637484: Current learning rate: 0.00656 +2024-11-22 03:22:30.189044: train_loss -0.7696 +2024-11-22 03:22:30.191254: val_loss -0.7585 +2024-11-22 03:22:30.191358: Pseudo dice [0.8564] +2024-11-22 03:22:30.191461: Epoch time: 17.55 s +2024-11-22 03:22:31.026171: +2024-11-22 03:22:31.026381: Epoch 2994 +2024-11-22 03:22:31.026514: Current learning rate: 0.00656 +2024-11-22 03:22:50.892235: train_loss -0.7837 +2024-11-22 03:22:50.894635: val_loss -0.7542 +2024-11-22 03:22:50.894757: Pseudo dice [0.8527] +2024-11-22 03:22:50.894876: Epoch time: 19.87 s +2024-11-22 03:22:51.736052: +2024-11-22 03:22:51.736295: Epoch 2995 +2024-11-22 03:22:51.736465: Current learning rate: 0.00656 +2024-11-22 03:23:10.985851: train_loss -0.7867 +2024-11-22 03:23:10.991121: val_loss -0.7811 +2024-11-22 03:23:10.991282: Pseudo dice [0.8528] +2024-11-22 03:23:10.991397: Epoch time: 19.25 s +2024-11-22 03:23:11.899953: +2024-11-22 03:23:11.900174: Epoch 2996 +2024-11-22 03:23:11.900308: Current learning rate: 0.00656 +2024-11-22 03:23:30.459193: train_loss -0.7684 +2024-11-22 03:23:30.466671: val_loss -0.7872 +2024-11-22 03:23:30.466813: Pseudo dice [0.8503] +2024-11-22 03:23:30.466904: Epoch time: 18.56 s +2024-11-22 03:23:31.369775: +2024-11-22 03:23:31.369983: Epoch 2997 +2024-11-22 03:23:31.370122: Current learning rate: 0.00655 +2024-11-22 03:23:50.590783: train_loss -0.765 +2024-11-22 03:23:50.593407: val_loss -0.7464 +2024-11-22 03:23:50.593551: Pseudo dice [0.8469] +2024-11-22 03:23:50.593634: Epoch time: 19.22 s +2024-11-22 03:23:51.427139: +2024-11-22 03:23:51.427351: Epoch 2998 +2024-11-22 03:23:51.427467: Current learning rate: 0.00655 +2024-11-22 03:24:10.152494: train_loss -0.7612 +2024-11-22 03:24:10.154834: val_loss -0.7645 +2024-11-22 03:24:10.154945: Pseudo dice [0.8496] +2024-11-22 03:24:10.155042: Epoch time: 18.73 s +2024-11-22 03:24:10.991862: +2024-11-22 03:24:10.992078: Epoch 2999 +2024-11-22 03:24:10.992185: Current learning rate: 0.00655 +2024-11-22 03:24:30.255836: train_loss -0.7788 +2024-11-22 03:24:30.262031: val_loss -0.7412 +2024-11-22 03:24:30.262187: Pseudo dice [0.8293] +2024-11-22 03:24:30.262356: Epoch time: 19.26 s +2024-11-22 03:24:31.508414: +2024-11-22 03:24:31.508685: Epoch 3000 +2024-11-22 03:24:31.508803: Current learning rate: 0.00655 +2024-11-22 03:24:51.194977: train_loss -0.7727 +2024-11-22 03:24:51.208516: val_loss -0.7703 +2024-11-22 03:24:51.208646: Pseudo dice [0.8471] +2024-11-22 03:24:51.208784: Epoch time: 19.69 s +2024-11-22 03:24:52.047678: +2024-11-22 03:24:52.047907: Epoch 3001 +2024-11-22 03:24:52.048043: Current learning rate: 0.00655 +2024-11-22 03:25:10.472919: train_loss -0.7809 +2024-11-22 03:25:10.480963: val_loss -0.7557 +2024-11-22 03:25:10.481093: Pseudo dice [0.8321] +2024-11-22 03:25:10.481180: Epoch time: 18.43 s +2024-11-22 03:25:11.596336: +2024-11-22 03:25:11.596581: Epoch 3002 +2024-11-22 03:25:11.596709: Current learning rate: 0.00655 +2024-11-22 03:25:29.748606: train_loss -0.7811 +2024-11-22 03:25:29.766548: val_loss -0.7287 +2024-11-22 03:25:29.766759: Pseudo dice [0.8455] +2024-11-22 03:25:29.766861: Epoch time: 18.15 s +2024-11-22 03:25:30.715076: +2024-11-22 03:25:30.715290: Epoch 3003 +2024-11-22 03:25:30.715423: Current learning rate: 0.00655 +2024-11-22 03:25:49.385403: train_loss -0.7842 +2024-11-22 03:25:49.395625: val_loss -0.7994 +2024-11-22 03:25:49.395761: Pseudo dice [0.8573] +2024-11-22 03:25:49.395857: Epoch time: 18.67 s +2024-11-22 03:25:50.230391: +2024-11-22 03:25:50.230648: Epoch 3004 +2024-11-22 03:25:50.230791: Current learning rate: 0.00655 +2024-11-22 03:26:09.762436: train_loss -0.7865 +2024-11-22 03:26:09.766529: val_loss -0.7703 +2024-11-22 03:26:09.766652: Pseudo dice [0.8381] +2024-11-22 03:26:09.766741: Epoch time: 19.53 s +2024-11-22 03:26:10.747490: +2024-11-22 03:26:10.747698: Epoch 3005 +2024-11-22 03:26:10.747819: Current learning rate: 0.00654 +2024-11-22 03:26:28.738781: train_loss -0.7857 +2024-11-22 03:26:28.747397: val_loss -0.763 +2024-11-22 03:26:28.747551: Pseudo dice [0.8467] +2024-11-22 03:26:28.747662: Epoch time: 17.99 s +2024-11-22 03:26:29.761046: +2024-11-22 03:26:29.761276: Epoch 3006 +2024-11-22 03:26:29.761415: Current learning rate: 0.00654 +2024-11-22 03:26:49.067804: train_loss -0.7844 +2024-11-22 03:26:49.070011: val_loss -0.7805 +2024-11-22 03:26:49.070126: Pseudo dice [0.8553] +2024-11-22 03:26:49.070226: Epoch time: 19.31 s +2024-11-22 03:26:49.920580: +2024-11-22 03:26:49.920806: Epoch 3007 +2024-11-22 03:26:49.920922: Current learning rate: 0.00654 +2024-11-22 03:27:09.130738: train_loss -0.7765 +2024-11-22 03:27:09.133508: val_loss -0.7669 +2024-11-22 03:27:09.133596: Pseudo dice [0.8566] +2024-11-22 03:27:09.133674: Epoch time: 19.21 s +2024-11-22 03:27:09.973687: +2024-11-22 03:27:09.973918: Epoch 3008 +2024-11-22 03:27:09.974035: Current learning rate: 0.00654 +2024-11-22 03:27:29.879437: train_loss -0.7697 +2024-11-22 03:27:29.881519: val_loss -0.7527 +2024-11-22 03:27:29.881608: Pseudo dice [0.8497] +2024-11-22 03:27:29.881681: Epoch time: 19.91 s +2024-11-22 03:27:30.713747: +2024-11-22 03:27:30.713945: Epoch 3009 +2024-11-22 03:27:30.714063: Current learning rate: 0.00654 +2024-11-22 03:27:49.952576: train_loss -0.7747 +2024-11-22 03:27:49.958170: val_loss -0.7324 +2024-11-22 03:27:49.958302: Pseudo dice [0.8347] +2024-11-22 03:27:49.958386: Epoch time: 19.24 s +2024-11-22 03:27:50.797836: +2024-11-22 03:27:50.798041: Epoch 3010 +2024-11-22 03:27:50.798162: Current learning rate: 0.00654 +2024-11-22 03:28:08.688617: train_loss -0.7805 +2024-11-22 03:28:08.695707: val_loss -0.7718 +2024-11-22 03:28:08.695841: Pseudo dice [0.853] +2024-11-22 03:28:08.695935: Epoch time: 17.89 s +2024-11-22 03:28:09.755320: +2024-11-22 03:28:09.755528: Epoch 3011 +2024-11-22 03:28:09.755644: Current learning rate: 0.00654 +2024-11-22 03:28:27.557615: train_loss -0.7747 +2024-11-22 03:28:27.560627: val_loss -0.7603 +2024-11-22 03:28:27.560762: Pseudo dice [0.8456] +2024-11-22 03:28:27.560846: Epoch time: 17.8 s +2024-11-22 03:28:28.445316: +2024-11-22 03:28:28.445502: Epoch 3012 +2024-11-22 03:28:28.445614: Current learning rate: 0.00654 +2024-11-22 03:28:46.975335: train_loss -0.7645 +2024-11-22 03:28:46.980361: val_loss -0.7738 +2024-11-22 03:28:46.980493: Pseudo dice [0.8475] +2024-11-22 03:28:46.980600: Epoch time: 18.53 s +2024-11-22 03:28:47.813055: +2024-11-22 03:28:47.813257: Epoch 3013 +2024-11-22 03:28:47.813369: Current learning rate: 0.00654 +2024-11-22 03:29:07.293978: train_loss -0.7698 +2024-11-22 03:29:07.301707: val_loss -0.7536 +2024-11-22 03:29:07.301842: Pseudo dice [0.838] +2024-11-22 03:29:07.301932: Epoch time: 19.48 s +2024-11-22 03:29:08.563475: +2024-11-22 03:29:08.563714: Epoch 3014 +2024-11-22 03:29:08.563826: Current learning rate: 0.00653 +2024-11-22 03:29:27.632328: train_loss -0.7581 +2024-11-22 03:29:27.635041: val_loss -0.7758 +2024-11-22 03:29:27.635170: Pseudo dice [0.8377] +2024-11-22 03:29:27.635251: Epoch time: 19.07 s +2024-11-22 03:29:28.480791: +2024-11-22 03:29:28.481036: Epoch 3015 +2024-11-22 03:29:28.481157: Current learning rate: 0.00653 +2024-11-22 03:29:47.046812: train_loss -0.7689 +2024-11-22 03:29:47.059163: val_loss -0.7425 +2024-11-22 03:29:47.059276: Pseudo dice [0.8439] +2024-11-22 03:29:47.059356: Epoch time: 18.57 s +2024-11-22 03:29:47.917874: +2024-11-22 03:29:47.918107: Epoch 3016 +2024-11-22 03:29:47.918222: Current learning rate: 0.00653 +2024-11-22 03:30:06.493550: train_loss -0.7638 +2024-11-22 03:30:06.498863: val_loss -0.7555 +2024-11-22 03:30:06.499003: Pseudo dice [0.8476] +2024-11-22 03:30:06.499097: Epoch time: 18.58 s +2024-11-22 03:30:07.513806: +2024-11-22 03:30:07.513997: Epoch 3017 +2024-11-22 03:30:07.514112: Current learning rate: 0.00653 +2024-11-22 03:30:26.460222: train_loss -0.7728 +2024-11-22 03:30:26.467461: val_loss -0.7656 +2024-11-22 03:30:26.467572: Pseudo dice [0.8475] +2024-11-22 03:30:26.467667: Epoch time: 18.95 s +2024-11-22 03:30:27.455421: +2024-11-22 03:30:27.455630: Epoch 3018 +2024-11-22 03:30:27.455749: Current learning rate: 0.00653 +2024-11-22 03:30:46.670412: train_loss -0.7763 +2024-11-22 03:30:46.677709: val_loss -0.7524 +2024-11-22 03:30:46.697989: Pseudo dice [0.8536] +2024-11-22 03:30:46.698182: Epoch time: 19.22 s +2024-11-22 03:30:47.531020: +2024-11-22 03:30:47.531288: Epoch 3019 +2024-11-22 03:30:47.531412: Current learning rate: 0.00653 +2024-11-22 03:31:07.826136: train_loss -0.7721 +2024-11-22 03:31:07.831862: val_loss -0.7647 +2024-11-22 03:31:07.832005: Pseudo dice [0.8351] +2024-11-22 03:31:07.832098: Epoch time: 20.3 s +2024-11-22 03:31:08.672530: +2024-11-22 03:31:08.672737: Epoch 3020 +2024-11-22 03:31:08.672849: Current learning rate: 0.00653 +2024-11-22 03:31:27.967041: train_loss -0.7826 +2024-11-22 03:31:27.978942: val_loss -0.7756 +2024-11-22 03:31:27.979088: Pseudo dice [0.8616] +2024-11-22 03:31:27.979173: Epoch time: 19.3 s +2024-11-22 03:31:28.951173: +2024-11-22 03:31:28.951491: Epoch 3021 +2024-11-22 03:31:28.951621: Current learning rate: 0.00653 +2024-11-22 03:31:48.588433: train_loss -0.7847 +2024-11-22 03:31:48.596083: val_loss -0.7716 +2024-11-22 03:31:48.596213: Pseudo dice [0.8501] +2024-11-22 03:31:48.596302: Epoch time: 19.64 s +2024-11-22 03:31:49.478386: +2024-11-22 03:31:49.478657: Epoch 3022 +2024-11-22 03:31:49.478775: Current learning rate: 0.00652 +2024-11-22 03:32:08.131162: train_loss -0.7851 +2024-11-22 03:32:08.140515: val_loss -0.751 +2024-11-22 03:32:08.140648: Pseudo dice [0.8476] +2024-11-22 03:32:08.140727: Epoch time: 18.65 s +2024-11-22 03:32:09.101223: +2024-11-22 03:32:09.101422: Epoch 3023 +2024-11-22 03:32:09.101535: Current learning rate: 0.00652 +2024-11-22 03:32:28.679134: train_loss -0.7809 +2024-11-22 03:32:28.685375: val_loss -0.7711 +2024-11-22 03:32:28.685510: Pseudo dice [0.8501] +2024-11-22 03:32:28.685591: Epoch time: 19.58 s +2024-11-22 03:32:29.849838: +2024-11-22 03:32:29.850041: Epoch 3024 +2024-11-22 03:32:29.850194: Current learning rate: 0.00652 +2024-11-22 03:32:48.986205: train_loss -0.7775 +2024-11-22 03:32:48.992520: val_loss -0.7545 +2024-11-22 03:32:48.992637: Pseudo dice [0.8456] +2024-11-22 03:32:48.992727: Epoch time: 19.14 s +2024-11-22 03:32:50.225943: +2024-11-22 03:32:50.226146: Epoch 3025 +2024-11-22 03:32:50.226262: Current learning rate: 0.00652 +2024-11-22 03:33:09.585002: train_loss -0.7792 +2024-11-22 03:33:09.587349: val_loss -0.7679 +2024-11-22 03:33:09.587450: Pseudo dice [0.8522] +2024-11-22 03:33:09.587534: Epoch time: 19.36 s +2024-11-22 03:33:10.424041: +2024-11-22 03:33:10.424246: Epoch 3026 +2024-11-22 03:33:10.424354: Current learning rate: 0.00652 +2024-11-22 03:33:28.842118: train_loss -0.7839 +2024-11-22 03:33:28.853237: val_loss -0.7881 +2024-11-22 03:33:28.853374: Pseudo dice [0.8473] +2024-11-22 03:33:28.853473: Epoch time: 18.42 s +2024-11-22 03:33:29.780907: +2024-11-22 03:33:29.781124: Epoch 3027 +2024-11-22 03:33:29.781235: Current learning rate: 0.00652 +2024-11-22 03:33:49.562222: train_loss -0.7824 +2024-11-22 03:33:49.570243: val_loss -0.7634 +2024-11-22 03:33:49.570373: Pseudo dice [0.8357] +2024-11-22 03:33:49.570457: Epoch time: 19.78 s +2024-11-22 03:33:50.541646: +2024-11-22 03:33:50.541930: Epoch 3028 +2024-11-22 03:33:50.542042: Current learning rate: 0.00652 +2024-11-22 03:34:08.927610: train_loss -0.7891 +2024-11-22 03:34:08.936275: val_loss -0.7656 +2024-11-22 03:34:08.936402: Pseudo dice [0.844] +2024-11-22 03:34:08.936498: Epoch time: 18.39 s +2024-11-22 03:34:10.004532: +2024-11-22 03:34:10.004756: Epoch 3029 +2024-11-22 03:34:10.004866: Current learning rate: 0.00652 +2024-11-22 03:34:28.434457: train_loss -0.7653 +2024-11-22 03:34:28.437532: val_loss -0.7693 +2024-11-22 03:34:28.437636: Pseudo dice [0.8619] +2024-11-22 03:34:28.437715: Epoch time: 18.43 s +2024-11-22 03:34:29.276203: +2024-11-22 03:34:29.276395: Epoch 3030 +2024-11-22 03:34:29.276507: Current learning rate: 0.00652 +2024-11-22 03:34:48.451682: train_loss -0.7671 +2024-11-22 03:34:48.458528: val_loss -0.7581 +2024-11-22 03:34:48.458642: Pseudo dice [0.8484] +2024-11-22 03:34:48.458723: Epoch time: 19.18 s +2024-11-22 03:34:49.382296: +2024-11-22 03:34:49.382495: Epoch 3031 +2024-11-22 03:34:49.382608: Current learning rate: 0.00651 +2024-11-22 03:35:08.409424: train_loss -0.7672 +2024-11-22 03:35:08.415498: val_loss -0.7623 +2024-11-22 03:35:08.415619: Pseudo dice [0.8462] +2024-11-22 03:35:08.415703: Epoch time: 19.03 s +2024-11-22 03:35:09.316823: +2024-11-22 03:35:09.317037: Epoch 3032 +2024-11-22 03:35:09.317160: Current learning rate: 0.00651 +2024-11-22 03:35:28.056157: train_loss -0.7713 +2024-11-22 03:35:28.062386: val_loss -0.7849 +2024-11-22 03:35:28.062568: Pseudo dice [0.8561] +2024-11-22 03:35:28.062663: Epoch time: 18.74 s +2024-11-22 03:35:28.902671: +2024-11-22 03:35:28.902879: Epoch 3033 +2024-11-22 03:35:28.902994: Current learning rate: 0.00651 +2024-11-22 03:35:48.563224: train_loss -0.7751 +2024-11-22 03:35:48.576006: val_loss -0.7565 +2024-11-22 03:35:48.576141: Pseudo dice [0.8487] +2024-11-22 03:35:48.576232: Epoch time: 19.66 s +2024-11-22 03:35:49.557257: +2024-11-22 03:35:49.557461: Epoch 3034 +2024-11-22 03:35:49.557578: Current learning rate: 0.00651 +2024-11-22 03:36:09.054078: train_loss -0.7682 +2024-11-22 03:36:09.060596: val_loss -0.7396 +2024-11-22 03:36:09.060729: Pseudo dice [0.842] +2024-11-22 03:36:09.060823: Epoch time: 19.5 s +2024-11-22 03:36:09.926331: +2024-11-22 03:36:09.926538: Epoch 3035 +2024-11-22 03:36:09.926645: Current learning rate: 0.00651 +2024-11-22 03:36:29.139349: train_loss -0.76 +2024-11-22 03:36:29.148185: val_loss -0.7468 +2024-11-22 03:36:29.148369: Pseudo dice [0.8353] +2024-11-22 03:36:29.148463: Epoch time: 19.21 s +2024-11-22 03:36:30.008886: +2024-11-22 03:36:30.009102: Epoch 3036 +2024-11-22 03:36:30.009220: Current learning rate: 0.00651 +2024-11-22 03:36:48.890972: train_loss -0.7666 +2024-11-22 03:36:48.897560: val_loss -0.7605 +2024-11-22 03:36:48.897682: Pseudo dice [0.8462] +2024-11-22 03:36:48.897821: Epoch time: 18.88 s +2024-11-22 03:36:50.190061: +2024-11-22 03:36:50.190279: Epoch 3037 +2024-11-22 03:36:50.190391: Current learning rate: 0.00651 +2024-11-22 03:37:09.195873: train_loss -0.7637 +2024-11-22 03:37:09.198342: val_loss -0.7545 +2024-11-22 03:37:09.198445: Pseudo dice [0.8485] +2024-11-22 03:37:09.198562: Epoch time: 19.01 s +2024-11-22 03:37:10.032889: +2024-11-22 03:37:10.033115: Epoch 3038 +2024-11-22 03:37:10.033232: Current learning rate: 0.00651 +2024-11-22 03:37:28.805752: train_loss -0.7711 +2024-11-22 03:37:28.813694: val_loss -0.7643 +2024-11-22 03:37:28.813828: Pseudo dice [0.8363] +2024-11-22 03:37:28.813912: Epoch time: 18.77 s +2024-11-22 03:37:29.676274: +2024-11-22 03:37:29.676508: Epoch 3039 +2024-11-22 03:37:29.676622: Current learning rate: 0.0065 +2024-11-22 03:37:48.413565: train_loss -0.7706 +2024-11-22 03:37:48.415895: val_loss -0.7579 +2024-11-22 03:37:48.416004: Pseudo dice [0.8573] +2024-11-22 03:37:48.416101: Epoch time: 18.74 s +2024-11-22 03:37:49.253208: +2024-11-22 03:37:49.253432: Epoch 3040 +2024-11-22 03:37:49.253550: Current learning rate: 0.0065 +2024-11-22 03:38:08.203167: train_loss -0.7712 +2024-11-22 03:38:08.209783: val_loss -0.7597 +2024-11-22 03:38:08.209897: Pseudo dice [0.8518] +2024-11-22 03:38:08.209979: Epoch time: 18.95 s +2024-11-22 03:38:09.234465: +2024-11-22 03:38:09.234763: Epoch 3041 +2024-11-22 03:38:09.234882: Current learning rate: 0.0065 +2024-11-22 03:38:27.921476: train_loss -0.7739 +2024-11-22 03:38:27.928756: val_loss -0.7837 +2024-11-22 03:38:27.928868: Pseudo dice [0.862] +2024-11-22 03:38:27.928951: Epoch time: 18.69 s +2024-11-22 03:38:29.069108: +2024-11-22 03:38:29.069302: Epoch 3042 +2024-11-22 03:38:29.069411: Current learning rate: 0.0065 +2024-11-22 03:38:47.497841: train_loss -0.769 +2024-11-22 03:38:47.506563: val_loss -0.7415 +2024-11-22 03:38:47.506697: Pseudo dice [0.8411] +2024-11-22 03:38:47.506792: Epoch time: 18.43 s +2024-11-22 03:38:48.394198: +2024-11-22 03:38:48.394406: Epoch 3043 +2024-11-22 03:38:48.394518: Current learning rate: 0.0065 +2024-11-22 03:39:06.817176: train_loss -0.7748 +2024-11-22 03:39:06.822562: val_loss -0.7435 +2024-11-22 03:39:06.822703: Pseudo dice [0.8656] +2024-11-22 03:39:06.822787: Epoch time: 18.42 s +2024-11-22 03:39:07.705340: +2024-11-22 03:39:07.705734: Epoch 3044 +2024-11-22 03:39:07.705851: Current learning rate: 0.0065 +2024-11-22 03:39:26.236373: train_loss -0.7891 +2024-11-22 03:39:26.244878: val_loss -0.7556 +2024-11-22 03:39:26.245022: Pseudo dice [0.8521] +2024-11-22 03:39:26.245169: Epoch time: 18.53 s +2024-11-22 03:39:27.104783: +2024-11-22 03:39:27.104988: Epoch 3045 +2024-11-22 03:39:27.105108: Current learning rate: 0.0065 +2024-11-22 03:39:45.303021: train_loss -0.7836 +2024-11-22 03:39:45.310868: val_loss -0.7703 +2024-11-22 03:39:45.310997: Pseudo dice [0.8614] +2024-11-22 03:39:45.311086: Epoch time: 18.2 s +2024-11-22 03:39:46.154346: +2024-11-22 03:39:46.154564: Epoch 3046 +2024-11-22 03:39:46.154685: Current learning rate: 0.0065 +2024-11-22 03:40:05.423698: train_loss -0.7745 +2024-11-22 03:40:05.425668: val_loss -0.7645 +2024-11-22 03:40:05.425784: Pseudo dice [0.8421] +2024-11-22 03:40:05.425877: Epoch time: 19.27 s +2024-11-22 03:40:06.261805: +2024-11-22 03:40:06.262001: Epoch 3047 +2024-11-22 03:40:06.262118: Current learning rate: 0.0065 +2024-11-22 03:40:25.379721: train_loss -0.7694 +2024-11-22 03:40:25.382213: val_loss -0.7701 +2024-11-22 03:40:25.382341: Pseudo dice [0.8446] +2024-11-22 03:40:25.382422: Epoch time: 19.12 s +2024-11-22 03:40:26.595885: +2024-11-22 03:40:26.596122: Epoch 3048 +2024-11-22 03:40:26.596236: Current learning rate: 0.00649 +2024-11-22 03:40:44.562538: train_loss -0.7712 +2024-11-22 03:40:44.575066: val_loss -0.7864 +2024-11-22 03:40:44.576961: Pseudo dice [0.8622] +2024-11-22 03:40:44.577083: Epoch time: 17.97 s +2024-11-22 03:40:45.600428: +2024-11-22 03:40:45.600656: Epoch 3049 +2024-11-22 03:40:45.600772: Current learning rate: 0.00649 +2024-11-22 03:41:04.605700: train_loss -0.7659 +2024-11-22 03:41:04.612979: val_loss -0.7607 +2024-11-22 03:41:04.613101: Pseudo dice [0.8353] +2024-11-22 03:41:04.613194: Epoch time: 19.01 s +2024-11-22 03:41:05.692729: +2024-11-22 03:41:05.692946: Epoch 3050 +2024-11-22 03:41:05.693056: Current learning rate: 0.00649 +2024-11-22 03:41:24.718944: train_loss -0.7792 +2024-11-22 03:41:24.721378: val_loss -0.7797 +2024-11-22 03:41:24.721496: Pseudo dice [0.8542] +2024-11-22 03:41:24.721581: Epoch time: 19.03 s +2024-11-22 03:41:25.555788: +2024-11-22 03:41:25.556005: Epoch 3051 +2024-11-22 03:41:25.556118: Current learning rate: 0.00649 +2024-11-22 03:41:44.253504: train_loss -0.7736 +2024-11-22 03:41:44.259133: val_loss -0.7576 +2024-11-22 03:41:44.259277: Pseudo dice [0.8663] +2024-11-22 03:41:44.259367: Epoch time: 18.7 s +2024-11-22 03:41:45.105112: +2024-11-22 03:41:45.105328: Epoch 3052 +2024-11-22 03:41:45.105439: Current learning rate: 0.00649 +2024-11-22 03:42:03.916783: train_loss -0.7769 +2024-11-22 03:42:03.929713: val_loss -0.7814 +2024-11-22 03:42:03.929862: Pseudo dice [0.8521] +2024-11-22 03:42:03.929966: Epoch time: 18.81 s +2024-11-22 03:42:04.795891: +2024-11-22 03:42:04.796098: Epoch 3053 +2024-11-22 03:42:04.796207: Current learning rate: 0.00649 +2024-11-22 03:42:24.322483: train_loss -0.7645 +2024-11-22 03:42:24.324641: val_loss -0.7689 +2024-11-22 03:42:24.324738: Pseudo dice [0.8374] +2024-11-22 03:42:24.324831: Epoch time: 19.53 s +2024-11-22 03:42:25.153678: +2024-11-22 03:42:25.153885: Epoch 3054 +2024-11-22 03:42:25.154004: Current learning rate: 0.00649 +2024-11-22 03:42:43.450345: train_loss -0.7746 +2024-11-22 03:42:43.452493: val_loss -0.7513 +2024-11-22 03:42:43.452595: Pseudo dice [0.8512] +2024-11-22 03:42:43.452675: Epoch time: 18.3 s +2024-11-22 03:42:44.288283: +2024-11-22 03:42:44.288494: Epoch 3055 +2024-11-22 03:42:44.288608: Current learning rate: 0.00649 +2024-11-22 03:43:03.403108: train_loss -0.7659 +2024-11-22 03:43:03.405595: val_loss -0.7713 +2024-11-22 03:43:03.405680: Pseudo dice [0.8525] +2024-11-22 03:43:03.405759: Epoch time: 19.12 s +2024-11-22 03:43:04.241454: +2024-11-22 03:43:04.241660: Epoch 3056 +2024-11-22 03:43:04.241773: Current learning rate: 0.00648 +2024-11-22 03:43:24.150367: train_loss -0.7727 +2024-11-22 03:43:24.152687: val_loss -0.7653 +2024-11-22 03:43:24.152817: Pseudo dice [0.8367] +2024-11-22 03:43:24.169623: Epoch time: 19.91 s +2024-11-22 03:43:25.026393: +2024-11-22 03:43:25.026589: Epoch 3057 +2024-11-22 03:43:25.026706: Current learning rate: 0.00648 +2024-11-22 03:43:44.484150: train_loss -0.753 +2024-11-22 03:43:44.489866: val_loss -0.7525 +2024-11-22 03:43:44.490000: Pseudo dice [0.8483] +2024-11-22 03:43:44.490096: Epoch time: 19.46 s +2024-11-22 03:43:45.328798: +2024-11-22 03:43:45.329001: Epoch 3058 +2024-11-22 03:43:45.329120: Current learning rate: 0.00648 +2024-11-22 03:44:04.136019: train_loss -0.7551 +2024-11-22 03:44:04.138624: val_loss -0.778 +2024-11-22 03:44:04.138710: Pseudo dice [0.8407] +2024-11-22 03:44:04.138788: Epoch time: 18.81 s +2024-11-22 03:44:04.977238: +2024-11-22 03:44:04.977438: Epoch 3059 +2024-11-22 03:44:04.977548: Current learning rate: 0.00648 +2024-11-22 03:44:23.930052: train_loss -0.766 +2024-11-22 03:44:23.940940: val_loss -0.7662 +2024-11-22 03:44:23.941103: Pseudo dice [0.8471] +2024-11-22 03:44:23.941191: Epoch time: 18.95 s +2024-11-22 03:44:25.213218: +2024-11-22 03:44:25.213426: Epoch 3060 +2024-11-22 03:44:25.213541: Current learning rate: 0.00648 +2024-11-22 03:44:44.074367: train_loss -0.7854 +2024-11-22 03:44:44.084192: val_loss -0.7538 +2024-11-22 03:44:44.084323: Pseudo dice [0.8434] +2024-11-22 03:44:44.084403: Epoch time: 18.86 s +2024-11-22 03:44:44.928952: +2024-11-22 03:44:44.929163: Epoch 3061 +2024-11-22 03:44:44.929277: Current learning rate: 0.00648 +2024-11-22 03:45:03.464352: train_loss -0.7764 +2024-11-22 03:45:03.475070: val_loss -0.7579 +2024-11-22 03:45:03.475186: Pseudo dice [0.8576] +2024-11-22 03:45:03.475263: Epoch time: 18.54 s +2024-11-22 03:45:04.380596: +2024-11-22 03:45:04.380814: Epoch 3062 +2024-11-22 03:45:04.380929: Current learning rate: 0.00648 +2024-11-22 03:45:23.484717: train_loss -0.7728 +2024-11-22 03:45:23.491780: val_loss -0.7823 +2024-11-22 03:45:23.491901: Pseudo dice [0.8628] +2024-11-22 03:45:23.491978: Epoch time: 19.1 s +2024-11-22 03:45:24.476524: +2024-11-22 03:45:24.476764: Epoch 3063 +2024-11-22 03:45:24.476879: Current learning rate: 0.00648 +2024-11-22 03:45:43.316694: train_loss -0.7782 +2024-11-22 03:45:43.325135: val_loss -0.7779 +2024-11-22 03:45:43.325307: Pseudo dice [0.8499] +2024-11-22 03:45:43.325416: Epoch time: 18.84 s +2024-11-22 03:45:44.162554: +2024-11-22 03:45:44.162779: Epoch 3064 +2024-11-22 03:45:44.162891: Current learning rate: 0.00648 +2024-11-22 03:46:03.145750: train_loss -0.778 +2024-11-22 03:46:03.151561: val_loss -0.7701 +2024-11-22 03:46:03.151679: Pseudo dice [0.8563] +2024-11-22 03:46:03.151779: Epoch time: 18.98 s +2024-11-22 03:46:03.988499: +2024-11-22 03:46:03.988725: Epoch 3065 +2024-11-22 03:46:03.988842: Current learning rate: 0.00647 +2024-11-22 03:46:22.224455: train_loss -0.7768 +2024-11-22 03:46:22.239468: val_loss -0.754 +2024-11-22 03:46:22.239604: Pseudo dice [0.8277] +2024-11-22 03:46:22.240334: Epoch time: 18.24 s +2024-11-22 03:46:23.088758: +2024-11-22 03:46:23.088961: Epoch 3066 +2024-11-22 03:46:23.089076: Current learning rate: 0.00647 +2024-11-22 03:46:42.263099: train_loss -0.7447 +2024-11-22 03:46:42.265484: val_loss -0.7698 +2024-11-22 03:46:42.265588: Pseudo dice [0.8543] +2024-11-22 03:46:42.265676: Epoch time: 19.18 s +2024-11-22 03:46:43.098191: +2024-11-22 03:46:43.098391: Epoch 3067 +2024-11-22 03:46:43.098504: Current learning rate: 0.00647 +2024-11-22 03:47:01.562148: train_loss -0.7612 +2024-11-22 03:47:01.579339: val_loss -0.7504 +2024-11-22 03:47:01.579465: Pseudo dice [0.8354] +2024-11-22 03:47:01.579565: Epoch time: 18.46 s +2024-11-22 03:47:02.655685: +2024-11-22 03:47:02.655909: Epoch 3068 +2024-11-22 03:47:02.656029: Current learning rate: 0.00647 +2024-11-22 03:47:21.019002: train_loss -0.7655 +2024-11-22 03:47:21.022177: val_loss -0.7602 +2024-11-22 03:47:21.022292: Pseudo dice [0.8305] +2024-11-22 03:47:21.022372: Epoch time: 18.36 s +2024-11-22 03:47:21.896080: +2024-11-22 03:47:21.896296: Epoch 3069 +2024-11-22 03:47:21.896414: Current learning rate: 0.00647 +2024-11-22 03:47:41.809581: train_loss -0.7688 +2024-11-22 03:47:41.817466: val_loss -0.7568 +2024-11-22 03:47:41.817590: Pseudo dice [0.8321] +2024-11-22 03:47:41.817671: Epoch time: 19.91 s +2024-11-22 03:47:42.902960: +2024-11-22 03:47:42.903164: Epoch 3070 +2024-11-22 03:47:42.903272: Current learning rate: 0.00647 +2024-11-22 03:48:00.840405: train_loss -0.7673 +2024-11-22 03:48:00.851979: val_loss -0.7734 +2024-11-22 03:48:00.852121: Pseudo dice [0.8545] +2024-11-22 03:48:00.852215: Epoch time: 17.94 s +2024-11-22 03:48:02.071179: +2024-11-22 03:48:02.071368: Epoch 3071 +2024-11-22 03:48:02.071475: Current learning rate: 0.00647 +2024-11-22 03:48:19.857904: train_loss -0.765 +2024-11-22 03:48:19.860191: val_loss -0.7742 +2024-11-22 03:48:19.860307: Pseudo dice [0.844] +2024-11-22 03:48:19.860391: Epoch time: 17.79 s +2024-11-22 03:48:20.768905: +2024-11-22 03:48:20.769133: Epoch 3072 +2024-11-22 03:48:20.769247: Current learning rate: 0.00647 +2024-11-22 03:48:40.439971: train_loss -0.778 +2024-11-22 03:48:40.447711: val_loss -0.7852 +2024-11-22 03:48:40.447850: Pseudo dice [0.8507] +2024-11-22 03:48:40.447970: Epoch time: 19.67 s +2024-11-22 03:48:41.282680: +2024-11-22 03:48:41.282923: Epoch 3073 +2024-11-22 03:48:41.283043: Current learning rate: 0.00646 +2024-11-22 03:49:00.854503: train_loss -0.7742 +2024-11-22 03:49:00.856978: val_loss -0.7651 +2024-11-22 03:49:00.857077: Pseudo dice [0.8462] +2024-11-22 03:49:00.857159: Epoch time: 19.57 s +2024-11-22 03:49:01.692580: +2024-11-22 03:49:01.692771: Epoch 3074 +2024-11-22 03:49:01.692880: Current learning rate: 0.00646 +2024-11-22 03:49:20.703341: train_loss -0.769 +2024-11-22 03:49:20.705630: val_loss -0.7706 +2024-11-22 03:49:20.705722: Pseudo dice [0.8519] +2024-11-22 03:49:20.705807: Epoch time: 19.01 s +2024-11-22 03:49:21.543170: +2024-11-22 03:49:21.543378: Epoch 3075 +2024-11-22 03:49:21.543488: Current learning rate: 0.00646 +2024-11-22 03:49:40.228604: train_loss -0.7492 +2024-11-22 03:49:40.232239: val_loss -0.766 +2024-11-22 03:49:40.232348: Pseudo dice [0.8511] +2024-11-22 03:49:40.232431: Epoch time: 18.69 s +2024-11-22 03:49:41.076012: +2024-11-22 03:49:41.076246: Epoch 3076 +2024-11-22 03:49:41.076366: Current learning rate: 0.00646 +2024-11-22 03:49:59.963991: train_loss -0.7554 +2024-11-22 03:49:59.984866: val_loss -0.751 +2024-11-22 03:49:59.985001: Pseudo dice [0.8498] +2024-11-22 03:49:59.985093: Epoch time: 18.89 s +2024-11-22 03:50:00.944293: +2024-11-22 03:50:00.944499: Epoch 3077 +2024-11-22 03:50:00.944616: Current learning rate: 0.00646 +2024-11-22 03:50:19.694874: train_loss -0.7663 +2024-11-22 03:50:19.701570: val_loss -0.7863 +2024-11-22 03:50:19.701763: Pseudo dice [0.8621] +2024-11-22 03:50:19.701854: Epoch time: 18.75 s +2024-11-22 03:50:20.538841: +2024-11-22 03:50:20.539045: Epoch 3078 +2024-11-22 03:50:20.539160: Current learning rate: 0.00646 +2024-11-22 03:50:38.839477: train_loss -0.775 +2024-11-22 03:50:38.851235: val_loss -0.7658 +2024-11-22 03:50:38.851375: Pseudo dice [0.8496] +2024-11-22 03:50:38.851471: Epoch time: 18.3 s +2024-11-22 03:50:39.713804: +2024-11-22 03:50:39.714011: Epoch 3079 +2024-11-22 03:50:39.714128: Current learning rate: 0.00646 +2024-11-22 03:50:57.817985: train_loss -0.783 +2024-11-22 03:50:57.822515: val_loss -0.773 +2024-11-22 03:50:57.822659: Pseudo dice [0.8581] +2024-11-22 03:50:57.822740: Epoch time: 18.1 s +2024-11-22 03:50:58.658142: +2024-11-22 03:50:58.658355: Epoch 3080 +2024-11-22 03:50:58.658471: Current learning rate: 0.00646 +2024-11-22 03:51:17.377350: train_loss -0.7867 +2024-11-22 03:51:17.383382: val_loss -0.7552 +2024-11-22 03:51:17.383520: Pseudo dice [0.8451] +2024-11-22 03:51:17.383604: Epoch time: 18.72 s +2024-11-22 03:51:18.253338: +2024-11-22 03:51:18.253540: Epoch 3081 +2024-11-22 03:51:18.253650: Current learning rate: 0.00646 +2024-11-22 03:51:37.640378: train_loss -0.7771 +2024-11-22 03:51:37.647680: val_loss -0.7627 +2024-11-22 03:51:37.647817: Pseudo dice [0.8565] +2024-11-22 03:51:37.647916: Epoch time: 19.39 s +2024-11-22 03:51:38.581104: +2024-11-22 03:51:38.581302: Epoch 3082 +2024-11-22 03:51:38.581656: Current learning rate: 0.00645 +2024-11-22 03:51:57.789640: train_loss -0.7663 +2024-11-22 03:51:57.795621: val_loss -0.7532 +2024-11-22 03:51:57.795754: Pseudo dice [0.8643] +2024-11-22 03:51:57.795842: Epoch time: 19.21 s +2024-11-22 03:51:59.064462: +2024-11-22 03:51:59.064669: Epoch 3083 +2024-11-22 03:51:59.064785: Current learning rate: 0.00645 +2024-11-22 03:52:18.011243: train_loss -0.784 +2024-11-22 03:52:18.021408: val_loss -0.7789 +2024-11-22 03:52:18.021532: Pseudo dice [0.845] +2024-11-22 03:52:18.021610: Epoch time: 18.95 s +2024-11-22 03:52:18.868931: +2024-11-22 03:52:18.869152: Epoch 3084 +2024-11-22 03:52:18.869261: Current learning rate: 0.00645 +2024-11-22 03:52:37.541096: train_loss -0.7723 +2024-11-22 03:52:37.542972: val_loss -0.7574 +2024-11-22 03:52:37.543101: Pseudo dice [0.8566] +2024-11-22 03:52:37.543194: Epoch time: 18.67 s +2024-11-22 03:52:38.386538: +2024-11-22 03:52:38.386764: Epoch 3085 +2024-11-22 03:52:38.386877: Current learning rate: 0.00645 +2024-11-22 03:52:57.055597: train_loss -0.7732 +2024-11-22 03:52:57.068398: val_loss -0.7635 +2024-11-22 03:52:57.068568: Pseudo dice [0.8575] +2024-11-22 03:52:57.068672: Epoch time: 18.67 s +2024-11-22 03:52:57.932650: +2024-11-22 03:52:57.932874: Epoch 3086 +2024-11-22 03:52:57.932989: Current learning rate: 0.00645 +2024-11-22 03:53:15.210057: train_loss -0.7683 +2024-11-22 03:53:15.217350: val_loss -0.7711 +2024-11-22 03:53:15.217489: Pseudo dice [0.8442] +2024-11-22 03:53:15.217576: Epoch time: 17.28 s +2024-11-22 03:53:16.212457: +2024-11-22 03:53:16.212653: Epoch 3087 +2024-11-22 03:53:16.212770: Current learning rate: 0.00645 +2024-11-22 03:53:35.935593: train_loss -0.773 +2024-11-22 03:53:35.953789: val_loss -0.7596 +2024-11-22 03:53:35.953913: Pseudo dice [0.8542] +2024-11-22 03:53:35.953999: Epoch time: 19.72 s +2024-11-22 03:53:36.833544: +2024-11-22 03:53:36.833748: Epoch 3088 +2024-11-22 03:53:36.833866: Current learning rate: 0.00645 +2024-11-22 03:53:55.679605: train_loss -0.7722 +2024-11-22 03:53:55.685883: val_loss -0.7744 +2024-11-22 03:53:55.686016: Pseudo dice [0.8524] +2024-11-22 03:53:55.686114: Epoch time: 18.85 s +2024-11-22 03:53:56.574942: +2024-11-22 03:53:56.575160: Epoch 3089 +2024-11-22 03:53:56.575274: Current learning rate: 0.00645 +2024-11-22 03:54:15.747401: train_loss -0.7737 +2024-11-22 03:54:15.754725: val_loss -0.7537 +2024-11-22 03:54:15.754861: Pseudo dice [0.8403] +2024-11-22 03:54:15.754959: Epoch time: 19.17 s +2024-11-22 03:54:16.610374: +2024-11-22 03:54:16.610560: Epoch 3090 +2024-11-22 03:54:16.610674: Current learning rate: 0.00644 +2024-11-22 03:54:35.819707: train_loss -0.7665 +2024-11-22 03:54:35.825299: val_loss -0.7715 +2024-11-22 03:54:35.825412: Pseudo dice [0.8556] +2024-11-22 03:54:35.825493: Epoch time: 19.21 s +2024-11-22 03:54:36.725842: +2024-11-22 03:54:36.726073: Epoch 3091 +2024-11-22 03:54:36.726186: Current learning rate: 0.00644 +2024-11-22 03:54:54.489793: train_loss -0.775 +2024-11-22 03:54:54.496912: val_loss -0.7492 +2024-11-22 03:54:54.497023: Pseudo dice [0.8501] +2024-11-22 03:54:54.497324: Epoch time: 17.76 s +2024-11-22 03:54:55.515378: +2024-11-22 03:54:55.515574: Epoch 3092 +2024-11-22 03:54:55.515688: Current learning rate: 0.00644 +2024-11-22 03:55:15.590498: train_loss -0.7707 +2024-11-22 03:55:15.594874: val_loss -0.7713 +2024-11-22 03:55:15.595011: Pseudo dice [0.8468] +2024-11-22 03:55:15.595223: Epoch time: 20.08 s +2024-11-22 03:55:16.456542: +2024-11-22 03:55:16.456772: Epoch 3093 +2024-11-22 03:55:16.456883: Current learning rate: 0.00644 +2024-11-22 03:55:35.243787: train_loss -0.7751 +2024-11-22 03:55:35.245271: val_loss -0.7644 +2024-11-22 03:55:35.245365: Pseudo dice [0.8441] +2024-11-22 03:55:35.245442: Epoch time: 18.79 s +2024-11-22 03:55:36.080451: +2024-11-22 03:55:36.080642: Epoch 3094 +2024-11-22 03:55:36.080759: Current learning rate: 0.00644 +2024-11-22 03:55:54.970371: train_loss -0.7739 +2024-11-22 03:55:54.978142: val_loss -0.7575 +2024-11-22 03:55:54.978255: Pseudo dice [0.8311] +2024-11-22 03:55:54.978341: Epoch time: 18.89 s +2024-11-22 03:55:56.094784: +2024-11-22 03:55:56.095022: Epoch 3095 +2024-11-22 03:55:56.095138: Current learning rate: 0.00644 +2024-11-22 03:56:15.488541: train_loss -0.7745 +2024-11-22 03:56:15.495741: val_loss -0.7705 +2024-11-22 03:56:15.495879: Pseudo dice [0.8537] +2024-11-22 03:56:15.495969: Epoch time: 19.39 s +2024-11-22 03:56:16.495692: +2024-11-22 03:56:16.495966: Epoch 3096 +2024-11-22 03:56:16.496087: Current learning rate: 0.00644 +2024-11-22 03:56:35.723385: train_loss -0.7774 +2024-11-22 03:56:35.729017: val_loss -0.7443 +2024-11-22 03:56:35.729126: Pseudo dice [0.8588] +2024-11-22 03:56:35.729216: Epoch time: 19.23 s +2024-11-22 03:56:36.583242: +2024-11-22 03:56:36.583493: Epoch 3097 +2024-11-22 03:56:36.583608: Current learning rate: 0.00644 +2024-11-22 03:56:54.850767: train_loss -0.778 +2024-11-22 03:56:54.857908: val_loss -0.77 +2024-11-22 03:56:54.858081: Pseudo dice [0.8545] +2024-11-22 03:56:54.858163: Epoch time: 18.27 s +2024-11-22 03:56:55.706401: +2024-11-22 03:56:55.706591: Epoch 3098 +2024-11-22 03:56:55.706702: Current learning rate: 0.00644 +2024-11-22 03:57:14.674433: train_loss -0.7796 +2024-11-22 03:57:14.681532: val_loss -0.7658 +2024-11-22 03:57:14.681671: Pseudo dice [0.8614] +2024-11-22 03:57:14.681764: Epoch time: 18.97 s +2024-11-22 03:57:15.612983: +2024-11-22 03:57:15.613203: Epoch 3099 +2024-11-22 03:57:15.613314: Current learning rate: 0.00643 +2024-11-22 03:57:33.249413: train_loss -0.7801 +2024-11-22 03:57:33.254392: val_loss -0.7587 +2024-11-22 03:57:33.254541: Pseudo dice [0.8539] +2024-11-22 03:57:33.254632: Epoch time: 17.64 s +2024-11-22 03:57:34.349574: +2024-11-22 03:57:34.349806: Epoch 3100 +2024-11-22 03:57:34.349921: Current learning rate: 0.00643 +2024-11-22 03:57:53.077076: train_loss -0.7777 +2024-11-22 03:57:53.078430: val_loss -0.7615 +2024-11-22 03:57:53.078520: Pseudo dice [0.842] +2024-11-22 03:57:53.078599: Epoch time: 18.73 s +2024-11-22 03:57:53.911469: +2024-11-22 03:57:53.911707: Epoch 3101 +2024-11-22 03:57:53.911823: Current learning rate: 0.00643 +2024-11-22 03:58:13.315962: train_loss -0.7652 +2024-11-22 03:58:13.322649: val_loss -0.7706 +2024-11-22 03:58:13.322767: Pseudo dice [0.8528] +2024-11-22 03:58:13.322851: Epoch time: 19.41 s +2024-11-22 03:58:14.182591: +2024-11-22 03:58:14.182788: Epoch 3102 +2024-11-22 03:58:14.182900: Current learning rate: 0.00643 +2024-11-22 03:58:33.398408: train_loss -0.7691 +2024-11-22 03:58:33.401359: val_loss -0.7808 +2024-11-22 03:58:33.401463: Pseudo dice [0.8537] +2024-11-22 03:58:33.401543: Epoch time: 19.22 s +2024-11-22 03:58:34.261645: +2024-11-22 03:58:34.261918: Epoch 3103 +2024-11-22 03:58:34.262027: Current learning rate: 0.00643 +2024-11-22 03:58:53.717338: train_loss -0.7724 +2024-11-22 03:58:53.723052: val_loss -0.7517 +2024-11-22 03:58:53.723172: Pseudo dice [0.8566] +2024-11-22 03:58:53.723259: Epoch time: 19.46 s +2024-11-22 03:58:54.559664: +2024-11-22 03:58:54.559873: Epoch 3104 +2024-11-22 03:58:54.559984: Current learning rate: 0.00643 +2024-11-22 03:59:12.373818: train_loss -0.7787 +2024-11-22 03:59:12.387047: val_loss -0.783 +2024-11-22 03:59:12.387220: Pseudo dice [0.8626] +2024-11-22 03:59:12.387308: Epoch time: 17.81 s +2024-11-22 03:59:13.322900: +2024-11-22 03:59:13.323141: Epoch 3105 +2024-11-22 03:59:13.323261: Current learning rate: 0.00643 +2024-11-22 03:59:32.037917: train_loss -0.7628 +2024-11-22 03:59:32.043540: val_loss -0.7633 +2024-11-22 03:59:32.043688: Pseudo dice [0.8353] +2024-11-22 03:59:32.043783: Epoch time: 18.72 s +2024-11-22 03:59:32.892503: +2024-11-22 03:59:32.892800: Epoch 3106 +2024-11-22 03:59:32.892911: Current learning rate: 0.00643 +2024-11-22 03:59:52.686274: train_loss -0.7655 +2024-11-22 03:59:52.692428: val_loss -0.7459 +2024-11-22 03:59:52.692563: Pseudo dice [0.8515] +2024-11-22 03:59:52.692648: Epoch time: 19.79 s +2024-11-22 03:59:53.589887: +2024-11-22 03:59:53.590115: Epoch 3107 +2024-11-22 03:59:53.590235: Current learning rate: 0.00642 +2024-11-22 04:00:13.232529: train_loss -0.7637 +2024-11-22 04:00:13.238012: val_loss -0.7543 +2024-11-22 04:00:13.257090: Pseudo dice [0.8469] +2024-11-22 04:00:13.257273: Epoch time: 19.64 s +2024-11-22 04:00:14.096468: +2024-11-22 04:00:14.096672: Epoch 3108 +2024-11-22 04:00:14.096781: Current learning rate: 0.00642 +2024-11-22 04:00:32.596485: train_loss -0.7777 +2024-11-22 04:00:32.604640: val_loss -0.7764 +2024-11-22 04:00:32.604759: Pseudo dice [0.8597] +2024-11-22 04:00:32.604842: Epoch time: 18.5 s +2024-11-22 04:00:33.604846: +2024-11-22 04:00:33.605088: Epoch 3109 +2024-11-22 04:00:33.605210: Current learning rate: 0.00642 +2024-11-22 04:00:53.507399: train_loss -0.7835 +2024-11-22 04:00:53.514618: val_loss -0.7612 +2024-11-22 04:00:53.514753: Pseudo dice [0.8372] +2024-11-22 04:00:53.514847: Epoch time: 19.9 s +2024-11-22 04:00:54.391448: +2024-11-22 04:00:54.391690: Epoch 3110 +2024-11-22 04:00:54.391805: Current learning rate: 0.00642 +2024-11-22 04:01:13.448721: train_loss -0.778 +2024-11-22 04:01:13.452404: val_loss -0.7448 +2024-11-22 04:01:13.452642: Pseudo dice [0.8452] +2024-11-22 04:01:13.452790: Epoch time: 19.06 s +2024-11-22 04:01:14.369588: +2024-11-22 04:01:14.369781: Epoch 3111 +2024-11-22 04:01:14.369891: Current learning rate: 0.00642 +2024-11-22 04:01:33.366789: train_loss -0.7866 +2024-11-22 04:01:33.378880: val_loss -0.7854 +2024-11-22 04:01:33.379027: Pseudo dice [0.8498] +2024-11-22 04:01:33.379127: Epoch time: 19.0 s +2024-11-22 04:01:34.307514: +2024-11-22 04:01:34.307724: Epoch 3112 +2024-11-22 04:01:34.307835: Current learning rate: 0.00642 +2024-11-22 04:01:52.647344: train_loss -0.7749 +2024-11-22 04:01:52.650127: val_loss -0.7905 +2024-11-22 04:01:52.650239: Pseudo dice [0.8603] +2024-11-22 04:01:52.650322: Epoch time: 18.34 s +2024-11-22 04:01:53.529124: +2024-11-22 04:01:53.529321: Epoch 3113 +2024-11-22 04:01:53.529436: Current learning rate: 0.00642 +2024-11-22 04:02:12.613679: train_loss -0.7836 +2024-11-22 04:02:12.615408: val_loss -0.7533 +2024-11-22 04:02:12.615495: Pseudo dice [0.8422] +2024-11-22 04:02:12.615579: Epoch time: 19.09 s +2024-11-22 04:02:13.452972: +2024-11-22 04:02:13.453187: Epoch 3114 +2024-11-22 04:02:13.453311: Current learning rate: 0.00642 +2024-11-22 04:02:31.687424: train_loss -0.7863 +2024-11-22 04:02:31.692523: val_loss -0.7594 +2024-11-22 04:02:31.692655: Pseudo dice [0.8411] +2024-11-22 04:02:31.692740: Epoch time: 18.24 s +2024-11-22 04:02:32.609021: +2024-11-22 04:02:32.609236: Epoch 3115 +2024-11-22 04:02:32.609347: Current learning rate: 0.00642 +2024-11-22 04:02:51.310278: train_loss -0.778 +2024-11-22 04:02:51.315825: val_loss -0.7556 +2024-11-22 04:02:51.315953: Pseudo dice [0.8535] +2024-11-22 04:02:51.316032: Epoch time: 18.7 s +2024-11-22 04:02:52.163597: +2024-11-22 04:02:52.163795: Epoch 3116 +2024-11-22 04:02:52.163909: Current learning rate: 0.00641 +2024-11-22 04:03:10.385623: train_loss -0.7853 +2024-11-22 04:03:10.386769: val_loss -0.7657 +2024-11-22 04:03:10.386872: Pseudo dice [0.8482] +2024-11-22 04:03:10.386960: Epoch time: 18.22 s +2024-11-22 04:03:11.646365: +2024-11-22 04:03:11.646600: Epoch 3117 +2024-11-22 04:03:11.646732: Current learning rate: 0.00641 +2024-11-22 04:03:29.840433: train_loss -0.7816 +2024-11-22 04:03:29.847295: val_loss -0.7595 +2024-11-22 04:03:29.847437: Pseudo dice [0.8578] +2024-11-22 04:03:29.847854: Epoch time: 18.19 s +2024-11-22 04:03:30.793849: +2024-11-22 04:03:30.794084: Epoch 3118 +2024-11-22 04:03:30.794202: Current learning rate: 0.00641 +2024-11-22 04:03:49.008822: train_loss -0.7904 +2024-11-22 04:03:49.014198: val_loss -0.7723 +2024-11-22 04:03:49.014323: Pseudo dice [0.8595] +2024-11-22 04:03:49.014410: Epoch time: 18.22 s +2024-11-22 04:03:50.204041: +2024-11-22 04:03:50.204679: Epoch 3119 +2024-11-22 04:03:50.204785: Current learning rate: 0.00641 +2024-11-22 04:04:08.382426: train_loss -0.779 +2024-11-22 04:04:08.387420: val_loss -0.7476 +2024-11-22 04:04:08.389970: Pseudo dice [0.8319] +2024-11-22 04:04:08.390131: Epoch time: 18.18 s +2024-11-22 04:04:09.241648: +2024-11-22 04:04:09.241863: Epoch 3120 +2024-11-22 04:04:09.241974: Current learning rate: 0.00641 +2024-11-22 04:04:28.463101: train_loss -0.7749 +2024-11-22 04:04:28.468378: val_loss -0.7285 +2024-11-22 04:04:28.468513: Pseudo dice [0.8393] +2024-11-22 04:04:28.468608: Epoch time: 19.22 s +2024-11-22 04:04:29.481077: +2024-11-22 04:04:29.481289: Epoch 3121 +2024-11-22 04:04:29.481404: Current learning rate: 0.00641 +2024-11-22 04:04:48.748109: train_loss -0.784 +2024-11-22 04:04:48.753037: val_loss -0.775 +2024-11-22 04:04:48.753164: Pseudo dice [0.8615] +2024-11-22 04:04:48.753259: Epoch time: 19.27 s +2024-11-22 04:04:49.596328: +2024-11-22 04:04:49.596537: Epoch 3122 +2024-11-22 04:04:49.596646: Current learning rate: 0.00641 +2024-11-22 04:05:08.539825: train_loss -0.7812 +2024-11-22 04:05:08.546773: val_loss -0.7646 +2024-11-22 04:05:08.546909: Pseudo dice [0.8706] +2024-11-22 04:05:08.546993: Epoch time: 18.94 s +2024-11-22 04:05:09.687257: +2024-11-22 04:05:09.687480: Epoch 3123 +2024-11-22 04:05:09.687594: Current learning rate: 0.00641 +2024-11-22 04:05:28.372653: train_loss -0.7837 +2024-11-22 04:05:28.374599: val_loss -0.7776 +2024-11-22 04:05:28.374689: Pseudo dice [0.8517] +2024-11-22 04:05:28.374769: Epoch time: 18.69 s +2024-11-22 04:05:29.214375: +2024-11-22 04:05:29.214586: Epoch 3124 +2024-11-22 04:05:29.214699: Current learning rate: 0.0064 +2024-11-22 04:05:49.027838: train_loss -0.7798 +2024-11-22 04:05:49.035241: val_loss -0.767 +2024-11-22 04:05:49.035364: Pseudo dice [0.8522] +2024-11-22 04:05:49.035455: Epoch time: 19.81 s +2024-11-22 04:05:49.912140: +2024-11-22 04:05:49.912333: Epoch 3125 +2024-11-22 04:05:49.912451: Current learning rate: 0.0064 +2024-11-22 04:06:09.163872: train_loss -0.7914 +2024-11-22 04:06:09.168996: val_loss -0.7707 +2024-11-22 04:06:09.169116: Pseudo dice [0.8512] +2024-11-22 04:06:09.169200: Epoch time: 19.25 s +2024-11-22 04:06:10.012725: +2024-11-22 04:06:10.012937: Epoch 3126 +2024-11-22 04:06:10.013047: Current learning rate: 0.0064 +2024-11-22 04:06:29.389877: train_loss -0.773 +2024-11-22 04:06:29.394416: val_loss -0.7666 +2024-11-22 04:06:29.394536: Pseudo dice [0.8567] +2024-11-22 04:06:29.394621: Epoch time: 19.38 s +2024-11-22 04:06:30.228302: +2024-11-22 04:06:30.228547: Epoch 3127 +2024-11-22 04:06:30.228661: Current learning rate: 0.0064 +2024-11-22 04:06:49.104205: train_loss -0.7581 +2024-11-22 04:06:49.105973: val_loss -0.7457 +2024-11-22 04:06:49.106070: Pseudo dice [0.8379] +2024-11-22 04:06:49.106162: Epoch time: 18.88 s +2024-11-22 04:06:49.939564: +2024-11-22 04:06:49.939814: Epoch 3128 +2024-11-22 04:06:49.939948: Current learning rate: 0.0064 +2024-11-22 04:07:08.964336: train_loss -0.7728 +2024-11-22 04:07:08.968986: val_loss -0.7705 +2024-11-22 04:07:08.969181: Pseudo dice [0.8402] +2024-11-22 04:07:08.969269: Epoch time: 19.03 s +2024-11-22 04:07:09.805894: +2024-11-22 04:07:09.806088: Epoch 3129 +2024-11-22 04:07:09.806200: Current learning rate: 0.0064 +2024-11-22 04:07:27.819988: train_loss -0.7725 +2024-11-22 04:07:27.826589: val_loss -0.7364 +2024-11-22 04:07:27.826698: Pseudo dice [0.8598] +2024-11-22 04:07:27.826779: Epoch time: 18.01 s +2024-11-22 04:07:28.805834: +2024-11-22 04:07:28.806046: Epoch 3130 +2024-11-22 04:07:28.806165: Current learning rate: 0.0064 +2024-11-22 04:07:48.612420: train_loss -0.7839 +2024-11-22 04:07:48.617932: val_loss -0.7853 +2024-11-22 04:07:48.618050: Pseudo dice [0.866] +2024-11-22 04:07:48.618140: Epoch time: 19.81 s +2024-11-22 04:07:49.755794: +2024-11-22 04:07:49.756027: Epoch 3131 +2024-11-22 04:07:49.756147: Current learning rate: 0.0064 +2024-11-22 04:08:08.015426: train_loss -0.784 +2024-11-22 04:08:08.017543: val_loss -0.758 +2024-11-22 04:08:08.017636: Pseudo dice [0.8561] +2024-11-22 04:08:08.017726: Epoch time: 18.26 s +2024-11-22 04:08:08.855202: +2024-11-22 04:08:08.855405: Epoch 3132 +2024-11-22 04:08:08.855519: Current learning rate: 0.00639 +2024-11-22 04:08:27.760294: train_loss -0.7779 +2024-11-22 04:08:27.763386: val_loss -0.7471 +2024-11-22 04:08:27.763531: Pseudo dice [0.8331] +2024-11-22 04:08:27.763618: Epoch time: 18.91 s +2024-11-22 04:08:28.608379: +2024-11-22 04:08:28.608828: Epoch 3133 +2024-11-22 04:08:28.608945: Current learning rate: 0.00639 +2024-11-22 04:08:48.150888: train_loss -0.7503 +2024-11-22 04:08:48.153156: val_loss -0.7407 +2024-11-22 04:08:48.153247: Pseudo dice [0.8328] +2024-11-22 04:08:48.153326: Epoch time: 19.54 s +2024-11-22 04:08:48.991419: +2024-11-22 04:08:48.991642: Epoch 3134 +2024-11-22 04:08:48.991751: Current learning rate: 0.00639 +2024-11-22 04:09:07.671991: train_loss -0.7588 +2024-11-22 04:09:07.675046: val_loss -0.7537 +2024-11-22 04:09:07.675178: Pseudo dice [0.8363] +2024-11-22 04:09:07.675263: Epoch time: 18.68 s +2024-11-22 04:09:08.550674: +2024-11-22 04:09:08.550941: Epoch 3135 +2024-11-22 04:09:08.551062: Current learning rate: 0.00639 +2024-11-22 04:09:27.746268: train_loss -0.7544 +2024-11-22 04:09:27.761303: val_loss -0.7615 +2024-11-22 04:09:27.761448: Pseudo dice [0.8486] +2024-11-22 04:09:27.761547: Epoch time: 19.2 s +2024-11-22 04:09:28.728486: +2024-11-22 04:09:28.728742: Epoch 3136 +2024-11-22 04:09:28.728859: Current learning rate: 0.00639 +2024-11-22 04:09:47.908798: train_loss -0.7557 +2024-11-22 04:09:47.910563: val_loss -0.7535 +2024-11-22 04:09:47.910677: Pseudo dice [0.8414] +2024-11-22 04:09:47.910759: Epoch time: 19.18 s +2024-11-22 04:09:48.771397: +2024-11-22 04:09:48.771601: Epoch 3137 +2024-11-22 04:09:48.771715: Current learning rate: 0.00639 +2024-11-22 04:10:07.196969: train_loss -0.776 +2024-11-22 04:10:07.202044: val_loss -0.77 +2024-11-22 04:10:07.202192: Pseudo dice [0.8498] +2024-11-22 04:10:07.202278: Epoch time: 18.43 s +2024-11-22 04:10:08.053548: +2024-11-22 04:10:08.053800: Epoch 3138 +2024-11-22 04:10:08.053910: Current learning rate: 0.00639 +2024-11-22 04:10:27.026713: train_loss -0.7773 +2024-11-22 04:10:27.031872: val_loss -0.7815 +2024-11-22 04:10:27.032019: Pseudo dice [0.8514] +2024-11-22 04:10:27.032126: Epoch time: 18.97 s +2024-11-22 04:10:27.872936: +2024-11-22 04:10:27.873148: Epoch 3139 +2024-11-22 04:10:27.873261: Current learning rate: 0.00639 +2024-11-22 04:10:47.672013: train_loss -0.7733 +2024-11-22 04:10:47.676380: val_loss -0.7804 +2024-11-22 04:10:47.676522: Pseudo dice [0.8636] +2024-11-22 04:10:47.676611: Epoch time: 19.8 s +2024-11-22 04:10:48.950275: +2024-11-22 04:10:48.950511: Epoch 3140 +2024-11-22 04:10:48.950626: Current learning rate: 0.00639 +2024-11-22 04:11:08.518573: train_loss -0.7819 +2024-11-22 04:11:08.522419: val_loss -0.7787 +2024-11-22 04:11:08.522554: Pseudo dice [0.8534] +2024-11-22 04:11:08.522637: Epoch time: 19.57 s +2024-11-22 04:11:09.368901: +2024-11-22 04:11:09.369143: Epoch 3141 +2024-11-22 04:11:09.369260: Current learning rate: 0.00638 +2024-11-22 04:11:28.370524: train_loss -0.7863 +2024-11-22 04:11:28.377784: val_loss -0.7524 +2024-11-22 04:11:28.377918: Pseudo dice [0.8531] +2024-11-22 04:11:28.378009: Epoch time: 19.0 s +2024-11-22 04:11:29.376235: +2024-11-22 04:11:29.376468: Epoch 3142 +2024-11-22 04:11:29.376581: Current learning rate: 0.00638 +2024-11-22 04:11:49.645128: train_loss -0.774 +2024-11-22 04:11:49.651221: val_loss -0.7478 +2024-11-22 04:11:49.651355: Pseudo dice [0.8442] +2024-11-22 04:11:49.651437: Epoch time: 20.27 s +2024-11-22 04:11:50.666940: +2024-11-22 04:11:50.667153: Epoch 3143 +2024-11-22 04:11:50.667264: Current learning rate: 0.00638 +2024-11-22 04:12:08.145973: train_loss -0.7784 +2024-11-22 04:12:08.149570: val_loss -0.7784 +2024-11-22 04:12:08.149935: Pseudo dice [0.8439] +2024-11-22 04:12:08.150027: Epoch time: 17.48 s +2024-11-22 04:12:09.366441: +2024-11-22 04:12:09.366685: Epoch 3144 +2024-11-22 04:12:09.366799: Current learning rate: 0.00638 +2024-11-22 04:12:29.790150: train_loss -0.779 +2024-11-22 04:12:29.796316: val_loss -0.7423 +2024-11-22 04:12:29.796454: Pseudo dice [0.8304] +2024-11-22 04:12:29.796539: Epoch time: 20.42 s +2024-11-22 04:12:30.706717: +2024-11-22 04:12:30.706962: Epoch 3145 +2024-11-22 04:12:30.707085: Current learning rate: 0.00638 +2024-11-22 04:12:49.500817: train_loss -0.777 +2024-11-22 04:12:49.506510: val_loss -0.79 +2024-11-22 04:12:49.506630: Pseudo dice [0.8513] +2024-11-22 04:12:49.506939: Epoch time: 18.79 s +2024-11-22 04:12:50.474641: +2024-11-22 04:12:50.474886: Epoch 3146 +2024-11-22 04:12:50.475002: Current learning rate: 0.00638 +2024-11-22 04:13:09.478809: train_loss -0.7852 +2024-11-22 04:13:09.482300: val_loss -0.7619 +2024-11-22 04:13:09.482490: Pseudo dice [0.8588] +2024-11-22 04:13:09.482577: Epoch time: 19.01 s +2024-11-22 04:13:10.428604: +2024-11-22 04:13:10.428818: Epoch 3147 +2024-11-22 04:13:10.428929: Current learning rate: 0.00638 +2024-11-22 04:13:28.853714: train_loss -0.7693 +2024-11-22 04:13:28.855953: val_loss -0.7538 +2024-11-22 04:13:28.856073: Pseudo dice [0.8339] +2024-11-22 04:13:28.856216: Epoch time: 18.43 s +2024-11-22 04:13:29.704958: +2024-11-22 04:13:29.705194: Epoch 3148 +2024-11-22 04:13:29.705310: Current learning rate: 0.00638 +2024-11-22 04:13:47.569717: train_loss -0.7795 +2024-11-22 04:13:47.576170: val_loss -0.7616 +2024-11-22 04:13:47.576287: Pseudo dice [0.8473] +2024-11-22 04:13:47.576369: Epoch time: 17.87 s +2024-11-22 04:13:48.433128: +2024-11-22 04:13:48.433340: Epoch 3149 +2024-11-22 04:13:48.433455: Current learning rate: 0.00637 +2024-11-22 04:14:06.910750: train_loss -0.7772 +2024-11-22 04:14:06.912430: val_loss -0.7607 +2024-11-22 04:14:06.912554: Pseudo dice [0.8497] +2024-11-22 04:14:06.912715: Epoch time: 18.48 s +2024-11-22 04:14:08.018306: +2024-11-22 04:14:08.018489: Epoch 3150 +2024-11-22 04:14:08.018605: Current learning rate: 0.00637 +2024-11-22 04:14:26.627948: train_loss -0.7777 +2024-11-22 04:14:26.633778: val_loss -0.7351 +2024-11-22 04:14:26.633906: Pseudo dice [0.8402] +2024-11-22 04:14:26.633989: Epoch time: 18.61 s +2024-11-22 04:14:28.131087: +2024-11-22 04:14:28.131305: Epoch 3151 +2024-11-22 04:14:28.131414: Current learning rate: 0.00637 +2024-11-22 04:14:48.192235: train_loss -0.7814 +2024-11-22 04:14:48.199692: val_loss -0.765 +2024-11-22 04:14:48.199839: Pseudo dice [0.8577] +2024-11-22 04:14:48.199984: Epoch time: 20.06 s +2024-11-22 04:14:49.102395: +2024-11-22 04:14:49.102606: Epoch 3152 +2024-11-22 04:14:49.102717: Current learning rate: 0.00637 +2024-11-22 04:15:07.732827: train_loss -0.7821 +2024-11-22 04:15:07.740114: val_loss -0.7794 +2024-11-22 04:15:07.740236: Pseudo dice [0.847] +2024-11-22 04:15:07.740333: Epoch time: 18.63 s +2024-11-22 04:15:08.574084: +2024-11-22 04:15:08.574311: Epoch 3153 +2024-11-22 04:15:08.574433: Current learning rate: 0.00637 +2024-11-22 04:15:28.098730: train_loss -0.7807 +2024-11-22 04:15:28.100323: val_loss -0.7684 +2024-11-22 04:15:28.100410: Pseudo dice [0.8525] +2024-11-22 04:15:28.100488: Epoch time: 19.53 s +2024-11-22 04:15:28.937574: +2024-11-22 04:15:28.937779: Epoch 3154 +2024-11-22 04:15:28.937889: Current learning rate: 0.00637 +2024-11-22 04:15:47.898338: train_loss -0.7808 +2024-11-22 04:15:47.911937: val_loss -0.7525 +2024-11-22 04:15:47.912070: Pseudo dice [0.8487] +2024-11-22 04:15:47.912157: Epoch time: 18.96 s +2024-11-22 04:15:48.786782: +2024-11-22 04:15:48.787006: Epoch 3155 +2024-11-22 04:15:48.787122: Current learning rate: 0.00637 +2024-11-22 04:16:07.698043: train_loss -0.7728 +2024-11-22 04:16:07.703410: val_loss -0.7661 +2024-11-22 04:16:07.703549: Pseudo dice [0.8483] +2024-11-22 04:16:07.703635: Epoch time: 18.91 s +2024-11-22 04:16:08.608982: +2024-11-22 04:16:08.609210: Epoch 3156 +2024-11-22 04:16:08.609323: Current learning rate: 0.00637 +2024-11-22 04:16:27.833653: train_loss -0.7735 +2024-11-22 04:16:27.836325: val_loss -0.764 +2024-11-22 04:16:27.836445: Pseudo dice [0.8359] +2024-11-22 04:16:27.836542: Epoch time: 19.23 s +2024-11-22 04:16:28.686211: +2024-11-22 04:16:28.686442: Epoch 3157 +2024-11-22 04:16:28.686563: Current learning rate: 0.00637 +2024-11-22 04:16:47.569097: train_loss -0.7744 +2024-11-22 04:16:47.574214: val_loss -0.766 +2024-11-22 04:16:47.574343: Pseudo dice [0.862] +2024-11-22 04:16:47.574425: Epoch time: 18.88 s +2024-11-22 04:16:48.436569: +2024-11-22 04:16:48.436793: Epoch 3158 +2024-11-22 04:16:48.436914: Current learning rate: 0.00636 +2024-11-22 04:17:07.636477: train_loss -0.7735 +2024-11-22 04:17:07.643847: val_loss -0.7302 +2024-11-22 04:17:07.643958: Pseudo dice [0.8268] +2024-11-22 04:17:07.644039: Epoch time: 19.2 s +2024-11-22 04:17:08.619787: +2024-11-22 04:17:08.620002: Epoch 3159 +2024-11-22 04:17:08.620119: Current learning rate: 0.00636 +2024-11-22 04:17:27.582961: train_loss -0.7743 +2024-11-22 04:17:27.589182: val_loss -0.7751 +2024-11-22 04:17:27.589299: Pseudo dice [0.8612] +2024-11-22 04:17:27.589393: Epoch time: 18.96 s +2024-11-22 04:17:28.473785: +2024-11-22 04:17:28.473994: Epoch 3160 +2024-11-22 04:17:28.474112: Current learning rate: 0.00636 +2024-11-22 04:17:46.844008: train_loss -0.781 +2024-11-22 04:17:46.846183: val_loss -0.7495 +2024-11-22 04:17:46.846345: Pseudo dice [0.844] +2024-11-22 04:17:46.846438: Epoch time: 18.37 s +2024-11-22 04:17:47.679284: +2024-11-22 04:17:47.679511: Epoch 3161 +2024-11-22 04:17:47.679619: Current learning rate: 0.00636 +2024-11-22 04:18:06.402015: train_loss -0.7778 +2024-11-22 04:18:06.409464: val_loss -0.7746 +2024-11-22 04:18:06.409571: Pseudo dice [0.8491] +2024-11-22 04:18:06.409654: Epoch time: 18.72 s +2024-11-22 04:18:07.250373: +2024-11-22 04:18:07.250569: Epoch 3162 +2024-11-22 04:18:07.250678: Current learning rate: 0.00636 +2024-11-22 04:18:25.907569: train_loss -0.7679 +2024-11-22 04:18:25.909194: val_loss -0.766 +2024-11-22 04:18:25.909319: Pseudo dice [0.8414] +2024-11-22 04:18:25.909397: Epoch time: 18.66 s +2024-11-22 04:18:26.851357: +2024-11-22 04:18:26.851612: Epoch 3163 +2024-11-22 04:18:26.851741: Current learning rate: 0.00636 +2024-11-22 04:18:45.422946: train_loss -0.7694 +2024-11-22 04:18:45.430572: val_loss -0.7711 +2024-11-22 04:18:45.430713: Pseudo dice [0.8547] +2024-11-22 04:18:45.430795: Epoch time: 18.57 s +2024-11-22 04:18:46.282190: +2024-11-22 04:18:46.282399: Epoch 3164 +2024-11-22 04:18:46.282512: Current learning rate: 0.00636 +2024-11-22 04:19:05.337742: train_loss -0.7839 +2024-11-22 04:19:05.339352: val_loss -0.77 +2024-11-22 04:19:05.339446: Pseudo dice [0.8492] +2024-11-22 04:19:05.339525: Epoch time: 19.06 s +2024-11-22 04:19:06.174400: +2024-11-22 04:19:06.174639: Epoch 3165 +2024-11-22 04:19:06.174752: Current learning rate: 0.00636 +2024-11-22 04:19:25.736807: train_loss -0.786 +2024-11-22 04:19:25.740044: val_loss -0.7901 +2024-11-22 04:19:25.740159: Pseudo dice [0.8518] +2024-11-22 04:19:25.740247: Epoch time: 19.56 s +2024-11-22 04:19:26.624892: +2024-11-22 04:19:26.625119: Epoch 3166 +2024-11-22 04:19:26.625234: Current learning rate: 0.00635 +2024-11-22 04:19:46.004800: train_loss -0.7808 +2024-11-22 04:19:46.007092: val_loss -0.7735 +2024-11-22 04:19:46.007225: Pseudo dice [0.8395] +2024-11-22 04:19:46.007312: Epoch time: 19.38 s +2024-11-22 04:19:46.862324: +2024-11-22 04:19:46.862587: Epoch 3167 +2024-11-22 04:19:46.862700: Current learning rate: 0.00635 +2024-11-22 04:20:06.961885: train_loss -0.771 +2024-11-22 04:20:06.969395: val_loss -0.7727 +2024-11-22 04:20:06.969529: Pseudo dice [0.8571] +2024-11-22 04:20:06.969612: Epoch time: 20.1 s +2024-11-22 04:20:07.906834: +2024-11-22 04:20:07.907022: Epoch 3168 +2024-11-22 04:20:07.907135: Current learning rate: 0.00635 +2024-11-22 04:20:27.959222: train_loss -0.7636 +2024-11-22 04:20:27.964543: val_loss -0.7728 +2024-11-22 04:20:27.964668: Pseudo dice [0.8469] +2024-11-22 04:20:27.964762: Epoch time: 20.05 s +2024-11-22 04:20:28.814617: +2024-11-22 04:20:28.814836: Epoch 3169 +2024-11-22 04:20:28.814948: Current learning rate: 0.00635 +2024-11-22 04:20:47.948499: train_loss -0.7737 +2024-11-22 04:20:47.951418: val_loss -0.7682 +2024-11-22 04:20:47.951717: Pseudo dice [0.8525] +2024-11-22 04:20:47.951837: Epoch time: 19.13 s +2024-11-22 04:20:48.793927: +2024-11-22 04:20:48.794140: Epoch 3170 +2024-11-22 04:20:48.794255: Current learning rate: 0.00635 +2024-11-22 04:21:08.221925: train_loss -0.7829 +2024-11-22 04:21:08.230307: val_loss -0.7785 +2024-11-22 04:21:08.230440: Pseudo dice [0.8475] +2024-11-22 04:21:08.230532: Epoch time: 19.43 s +2024-11-22 04:21:09.071550: +2024-11-22 04:21:09.071743: Epoch 3171 +2024-11-22 04:21:09.072091: Current learning rate: 0.00635 +2024-11-22 04:21:27.334076: train_loss -0.7767 +2024-11-22 04:21:27.341651: val_loss -0.7575 +2024-11-22 04:21:27.341793: Pseudo dice [0.858] +2024-11-22 04:21:27.341877: Epoch time: 18.26 s +2024-11-22 04:21:28.389401: +2024-11-22 04:21:28.389623: Epoch 3172 +2024-11-22 04:21:28.389736: Current learning rate: 0.00635 +2024-11-22 04:21:46.183355: train_loss -0.7767 +2024-11-22 04:21:46.188826: val_loss -0.7677 +2024-11-22 04:21:46.188960: Pseudo dice [0.8484] +2024-11-22 04:21:46.189042: Epoch time: 17.79 s +2024-11-22 04:21:47.253892: +2024-11-22 04:21:47.254129: Epoch 3173 +2024-11-22 04:21:47.254243: Current learning rate: 0.00635 +2024-11-22 04:22:06.850308: train_loss -0.778 +2024-11-22 04:22:06.856876: val_loss -0.7606 +2024-11-22 04:22:06.857004: Pseudo dice [0.8383] +2024-11-22 04:22:06.857098: Epoch time: 19.6 s +2024-11-22 04:22:08.148545: +2024-11-22 04:22:08.148799: Epoch 3174 +2024-11-22 04:22:08.148913: Current learning rate: 0.00635 +2024-11-22 04:22:26.951876: train_loss -0.7845 +2024-11-22 04:22:26.957588: val_loss -0.7841 +2024-11-22 04:22:26.957699: Pseudo dice [0.8582] +2024-11-22 04:22:26.957779: Epoch time: 18.8 s +2024-11-22 04:22:28.070004: +2024-11-22 04:22:28.070217: Epoch 3175 +2024-11-22 04:22:28.070327: Current learning rate: 0.00634 +2024-11-22 04:22:47.271327: train_loss -0.7882 +2024-11-22 04:22:47.277278: val_loss -0.7691 +2024-11-22 04:22:47.277430: Pseudo dice [0.8623] +2024-11-22 04:22:47.277519: Epoch time: 19.2 s +2024-11-22 04:22:48.220931: +2024-11-22 04:22:48.221176: Epoch 3176 +2024-11-22 04:22:48.221298: Current learning rate: 0.00634 +2024-11-22 04:23:07.589591: train_loss -0.7822 +2024-11-22 04:23:07.595497: val_loss -0.7288 +2024-11-22 04:23:07.595622: Pseudo dice [0.8415] +2024-11-22 04:23:07.595704: Epoch time: 19.37 s +2024-11-22 04:23:08.481340: +2024-11-22 04:23:08.481586: Epoch 3177 +2024-11-22 04:23:08.481735: Current learning rate: 0.00634 +2024-11-22 04:23:27.152901: train_loss -0.7722 +2024-11-22 04:23:27.158164: val_loss -0.7825 +2024-11-22 04:23:27.158299: Pseudo dice [0.8575] +2024-11-22 04:23:27.158392: Epoch time: 18.67 s +2024-11-22 04:23:28.098527: +2024-11-22 04:23:28.098731: Epoch 3178 +2024-11-22 04:23:28.098841: Current learning rate: 0.00634 +2024-11-22 04:23:46.814854: train_loss -0.771 +2024-11-22 04:23:46.816638: val_loss -0.7589 +2024-11-22 04:23:46.816761: Pseudo dice [0.8355] +2024-11-22 04:23:46.816844: Epoch time: 18.72 s +2024-11-22 04:23:47.702314: +2024-11-22 04:23:47.702555: Epoch 3179 +2024-11-22 04:23:47.702675: Current learning rate: 0.00634 +2024-11-22 04:24:06.007496: train_loss -0.7625 +2024-11-22 04:24:06.012927: val_loss -0.7794 +2024-11-22 04:24:06.013052: Pseudo dice [0.8491] +2024-11-22 04:24:06.013137: Epoch time: 18.31 s +2024-11-22 04:24:06.931794: +2024-11-22 04:24:06.932007: Epoch 3180 +2024-11-22 04:24:06.932122: Current learning rate: 0.00634 +2024-11-22 04:24:25.502041: train_loss -0.7794 +2024-11-22 04:24:25.503497: val_loss -0.7537 +2024-11-22 04:24:25.503610: Pseudo dice [0.8554] +2024-11-22 04:24:25.503695: Epoch time: 18.57 s +2024-11-22 04:24:26.347670: +2024-11-22 04:24:26.347916: Epoch 3181 +2024-11-22 04:24:26.348031: Current learning rate: 0.00634 +2024-11-22 04:24:45.507645: train_loss -0.7801 +2024-11-22 04:24:45.509081: val_loss -0.7589 +2024-11-22 04:24:45.509190: Pseudo dice [0.8547] +2024-11-22 04:24:45.509283: Epoch time: 19.16 s +2024-11-22 04:24:46.472431: +2024-11-22 04:24:46.472638: Epoch 3182 +2024-11-22 04:24:46.472754: Current learning rate: 0.00634 +2024-11-22 04:25:06.271856: train_loss -0.7752 +2024-11-22 04:25:06.273851: val_loss -0.7671 +2024-11-22 04:25:06.273941: Pseudo dice [0.8551] +2024-11-22 04:25:06.274024: Epoch time: 19.8 s +2024-11-22 04:25:07.102160: +2024-11-22 04:25:07.102354: Epoch 3183 +2024-11-22 04:25:07.102468: Current learning rate: 0.00633 +2024-11-22 04:25:26.570436: train_loss -0.7849 +2024-11-22 04:25:26.576619: val_loss -0.7726 +2024-11-22 04:25:26.576825: Pseudo dice [0.852] +2024-11-22 04:25:26.580804: Epoch time: 19.47 s +2024-11-22 04:25:27.441284: +2024-11-22 04:25:27.441497: Epoch 3184 +2024-11-22 04:25:27.441611: Current learning rate: 0.00633 +2024-11-22 04:25:47.522805: train_loss -0.7803 +2024-11-22 04:25:47.529568: val_loss -0.7569 +2024-11-22 04:25:47.529699: Pseudo dice [0.8416] +2024-11-22 04:25:47.529795: Epoch time: 20.08 s +2024-11-22 04:25:48.770753: +2024-11-22 04:25:48.770974: Epoch 3185 +2024-11-22 04:25:48.771093: Current learning rate: 0.00633 +2024-11-22 04:26:10.351565: train_loss -0.7771 +2024-11-22 04:26:10.353925: val_loss -0.7728 +2024-11-22 04:26:10.354014: Pseudo dice [0.8292] +2024-11-22 04:26:10.354101: Epoch time: 21.58 s +2024-11-22 04:26:11.186392: +2024-11-22 04:26:11.186610: Epoch 3186 +2024-11-22 04:26:11.186722: Current learning rate: 0.00633 +2024-11-22 04:26:29.675004: train_loss -0.7875 +2024-11-22 04:26:29.677362: val_loss -0.7675 +2024-11-22 04:26:29.677451: Pseudo dice [0.8436] +2024-11-22 04:26:29.677529: Epoch time: 18.49 s +2024-11-22 04:26:30.507631: +2024-11-22 04:26:30.507878: Epoch 3187 +2024-11-22 04:26:30.507993: Current learning rate: 0.00633 +2024-11-22 04:26:49.417373: train_loss -0.7856 +2024-11-22 04:26:49.420821: val_loss -0.7751 +2024-11-22 04:26:49.420956: Pseudo dice [0.861] +2024-11-22 04:26:49.421042: Epoch time: 18.91 s +2024-11-22 04:26:50.273421: +2024-11-22 04:26:50.273677: Epoch 3188 +2024-11-22 04:26:50.273834: Current learning rate: 0.00633 +2024-11-22 04:27:09.519159: train_loss -0.7685 +2024-11-22 04:27:09.524698: val_loss -0.771 +2024-11-22 04:27:09.524819: Pseudo dice [0.8585] +2024-11-22 04:27:09.524913: Epoch time: 19.25 s +2024-11-22 04:27:10.409592: +2024-11-22 04:27:10.409805: Epoch 3189 +2024-11-22 04:27:10.409919: Current learning rate: 0.00633 +2024-11-22 04:27:30.671601: train_loss -0.7722 +2024-11-22 04:27:30.677978: val_loss -0.7723 +2024-11-22 04:27:30.678115: Pseudo dice [0.839] +2024-11-22 04:27:30.678195: Epoch time: 20.26 s +2024-11-22 04:27:31.534757: +2024-11-22 04:27:31.534986: Epoch 3190 +2024-11-22 04:27:31.535107: Current learning rate: 0.00633 +2024-11-22 04:27:50.165087: train_loss -0.768 +2024-11-22 04:27:50.170347: val_loss -0.772 +2024-11-22 04:27:50.170474: Pseudo dice [0.8564] +2024-11-22 04:27:50.170555: Epoch time: 18.63 s +2024-11-22 04:27:51.128363: +2024-11-22 04:27:51.128572: Epoch 3191 +2024-11-22 04:27:51.128687: Current learning rate: 0.00633 +2024-11-22 04:28:10.348324: train_loss -0.7821 +2024-11-22 04:28:10.352361: val_loss -0.7574 +2024-11-22 04:28:10.352492: Pseudo dice [0.841] +2024-11-22 04:28:10.352580: Epoch time: 19.22 s +2024-11-22 04:28:11.222672: +2024-11-22 04:28:11.222857: Epoch 3192 +2024-11-22 04:28:11.222963: Current learning rate: 0.00632 +2024-11-22 04:28:29.500166: train_loss -0.7778 +2024-11-22 04:28:29.502082: val_loss -0.7743 +2024-11-22 04:28:29.502171: Pseudo dice [0.8525] +2024-11-22 04:28:29.502252: Epoch time: 18.28 s +2024-11-22 04:28:30.334650: +2024-11-22 04:28:30.334859: Epoch 3193 +2024-11-22 04:28:30.334979: Current learning rate: 0.00632 +2024-11-22 04:28:48.951669: train_loss -0.7817 +2024-11-22 04:28:48.956502: val_loss -0.7688 +2024-11-22 04:28:48.956627: Pseudo dice [0.8455] +2024-11-22 04:28:48.956714: Epoch time: 18.62 s +2024-11-22 04:28:49.884221: +2024-11-22 04:28:49.884418: Epoch 3194 +2024-11-22 04:28:49.884533: Current learning rate: 0.00632 +2024-11-22 04:29:08.702643: train_loss -0.7785 +2024-11-22 04:29:08.708268: val_loss -0.7897 +2024-11-22 04:29:08.708385: Pseudo dice [0.8568] +2024-11-22 04:29:08.708468: Epoch time: 18.82 s +2024-11-22 04:29:09.592288: +2024-11-22 04:29:09.592508: Epoch 3195 +2024-11-22 04:29:09.592620: Current learning rate: 0.00632 +2024-11-22 04:29:28.451646: train_loss -0.7765 +2024-11-22 04:29:28.458980: val_loss -0.7786 +2024-11-22 04:29:28.467084: Pseudo dice [0.8418] +2024-11-22 04:29:28.467243: Epoch time: 18.86 s +2024-11-22 04:29:29.420644: +2024-11-22 04:29:29.420839: Epoch 3196 +2024-11-22 04:29:29.420954: Current learning rate: 0.00632 +2024-11-22 04:29:49.252955: train_loss -0.7721 +2024-11-22 04:29:49.259114: val_loss -0.7637 +2024-11-22 04:29:49.259256: Pseudo dice [0.8276] +2024-11-22 04:29:49.259339: Epoch time: 19.83 s +2024-11-22 04:29:50.533281: +2024-11-22 04:29:50.533500: Epoch 3197 +2024-11-22 04:29:50.533612: Current learning rate: 0.00632 +2024-11-22 04:30:09.538143: train_loss -0.7844 +2024-11-22 04:30:09.544123: val_loss -0.7634 +2024-11-22 04:30:09.544253: Pseudo dice [0.8484] +2024-11-22 04:30:09.544348: Epoch time: 19.01 s +2024-11-22 04:30:10.569519: +2024-11-22 04:30:10.569738: Epoch 3198 +2024-11-22 04:30:10.569849: Current learning rate: 0.00632 +2024-11-22 04:30:29.158449: train_loss -0.7778 +2024-11-22 04:30:29.165556: val_loss -0.7674 +2024-11-22 04:30:29.165677: Pseudo dice [0.8542] +2024-11-22 04:30:29.165774: Epoch time: 18.59 s +2024-11-22 04:30:30.095628: +2024-11-22 04:30:30.095824: Epoch 3199 +2024-11-22 04:30:30.095932: Current learning rate: 0.00632 +2024-11-22 04:30:50.105334: train_loss -0.7806 +2024-11-22 04:30:50.107003: val_loss -0.7659 +2024-11-22 04:30:50.107091: Pseudo dice [0.8443] +2024-11-22 04:30:50.107166: Epoch time: 20.01 s +2024-11-22 04:30:51.182575: +2024-11-22 04:30:51.183101: Epoch 3200 +2024-11-22 04:30:51.183218: Current learning rate: 0.00631 +2024-11-22 04:31:10.712316: train_loss -0.7749 +2024-11-22 04:31:10.724587: val_loss -0.7589 +2024-11-22 04:31:10.724715: Pseudo dice [0.8317] +2024-11-22 04:31:10.724802: Epoch time: 19.53 s +2024-11-22 04:31:11.932256: +2024-11-22 04:31:11.932472: Epoch 3201 +2024-11-22 04:31:11.932590: Current learning rate: 0.00631 +2024-11-22 04:31:31.261622: train_loss -0.7826 +2024-11-22 04:31:31.266639: val_loss -0.76 +2024-11-22 04:31:31.266747: Pseudo dice [0.8458] +2024-11-22 04:31:31.266840: Epoch time: 19.33 s +2024-11-22 04:31:32.232326: +2024-11-22 04:31:32.232539: Epoch 3202 +2024-11-22 04:31:32.232651: Current learning rate: 0.00631 +2024-11-22 04:31:52.570670: train_loss -0.7805 +2024-11-22 04:31:52.572462: val_loss -0.7919 +2024-11-22 04:31:52.572592: Pseudo dice [0.8645] +2024-11-22 04:31:52.572736: Epoch time: 20.34 s +2024-11-22 04:31:53.486819: +2024-11-22 04:31:53.487047: Epoch 3203 +2024-11-22 04:31:53.487162: Current learning rate: 0.00631 +2024-11-22 04:32:12.085841: train_loss -0.7766 +2024-11-22 04:32:12.092408: val_loss -0.7685 +2024-11-22 04:32:12.092573: Pseudo dice [0.8438] +2024-11-22 04:32:12.092654: Epoch time: 18.6 s +2024-11-22 04:32:12.959783: +2024-11-22 04:32:12.959989: Epoch 3204 +2024-11-22 04:32:12.960107: Current learning rate: 0.00631 +2024-11-22 04:32:31.818002: train_loss -0.7786 +2024-11-22 04:32:31.819603: val_loss -0.7749 +2024-11-22 04:32:31.819718: Pseudo dice [0.8547] +2024-11-22 04:32:31.819802: Epoch time: 18.86 s +2024-11-22 04:32:32.654985: +2024-11-22 04:32:32.655195: Epoch 3205 +2024-11-22 04:32:32.655310: Current learning rate: 0.00631 +2024-11-22 04:32:53.200549: train_loss -0.7784 +2024-11-22 04:32:53.202400: val_loss -0.7605 +2024-11-22 04:32:53.202526: Pseudo dice [0.8492] +2024-11-22 04:32:53.202613: Epoch time: 20.55 s +2024-11-22 04:32:54.174732: +2024-11-22 04:32:54.174924: Epoch 3206 +2024-11-22 04:32:54.175032: Current learning rate: 0.00631 +2024-11-22 04:33:13.731571: train_loss -0.7841 +2024-11-22 04:33:13.733654: val_loss -0.7604 +2024-11-22 04:33:13.733783: Pseudo dice [0.8565] +2024-11-22 04:33:13.733864: Epoch time: 19.56 s +2024-11-22 04:33:14.670839: +2024-11-22 04:33:14.671051: Epoch 3207 +2024-11-22 04:33:14.671175: Current learning rate: 0.00631 +2024-11-22 04:33:33.737778: train_loss -0.772 +2024-11-22 04:33:33.744989: val_loss -0.7707 +2024-11-22 04:33:33.745109: Pseudo dice [0.8419] +2024-11-22 04:33:33.745194: Epoch time: 19.07 s +2024-11-22 04:33:35.056177: +2024-11-22 04:33:35.056379: Epoch 3208 +2024-11-22 04:33:35.056489: Current learning rate: 0.0063 +2024-11-22 04:33:54.945845: train_loss -0.7781 +2024-11-22 04:33:54.948272: val_loss -0.7799 +2024-11-22 04:33:54.948405: Pseudo dice [0.841] +2024-11-22 04:33:54.948494: Epoch time: 19.89 s +2024-11-22 04:33:55.807227: +2024-11-22 04:33:55.807448: Epoch 3209 +2024-11-22 04:33:55.807560: Current learning rate: 0.0063 +2024-11-22 04:34:14.192790: train_loss -0.7825 +2024-11-22 04:34:14.200198: val_loss -0.7595 +2024-11-22 04:34:14.200318: Pseudo dice [0.8506] +2024-11-22 04:34:14.200397: Epoch time: 18.39 s +2024-11-22 04:34:15.103828: +2024-11-22 04:34:15.104065: Epoch 3210 +2024-11-22 04:34:15.104186: Current learning rate: 0.0063 +2024-11-22 04:34:34.152501: train_loss -0.7737 +2024-11-22 04:34:34.154642: val_loss -0.7702 +2024-11-22 04:34:34.154739: Pseudo dice [0.8561] +2024-11-22 04:34:34.154826: Epoch time: 19.05 s +2024-11-22 04:34:34.992993: +2024-11-22 04:34:34.993255: Epoch 3211 +2024-11-22 04:34:34.993363: Current learning rate: 0.0063 +2024-11-22 04:34:54.346536: train_loss -0.7825 +2024-11-22 04:34:54.351876: val_loss -0.7698 +2024-11-22 04:34:54.352014: Pseudo dice [0.8484] +2024-11-22 04:34:54.352116: Epoch time: 19.35 s +2024-11-22 04:34:55.277062: +2024-11-22 04:34:55.277272: Epoch 3212 +2024-11-22 04:34:55.277390: Current learning rate: 0.0063 +2024-11-22 04:35:14.379084: train_loss -0.7813 +2024-11-22 04:35:14.387382: val_loss -0.7911 +2024-11-22 04:35:14.387518: Pseudo dice [0.867] +2024-11-22 04:35:14.387655: Epoch time: 19.1 s +2024-11-22 04:35:15.248256: +2024-11-22 04:35:15.248480: Epoch 3213 +2024-11-22 04:35:15.248599: Current learning rate: 0.0063 +2024-11-22 04:35:33.687399: train_loss -0.7843 +2024-11-22 04:35:33.702664: val_loss -0.795 +2024-11-22 04:35:33.702803: Pseudo dice [0.8562] +2024-11-22 04:35:33.702884: Epoch time: 18.44 s +2024-11-22 04:35:34.544553: +2024-11-22 04:35:34.545147: Epoch 3214 +2024-11-22 04:35:34.545261: Current learning rate: 0.0063 +2024-11-22 04:35:52.697908: train_loss -0.7855 +2024-11-22 04:35:52.709758: val_loss -0.7826 +2024-11-22 04:35:52.709899: Pseudo dice [0.8579] +2024-11-22 04:35:52.709987: Epoch time: 18.15 s +2024-11-22 04:35:53.554161: +2024-11-22 04:35:53.554371: Epoch 3215 +2024-11-22 04:35:53.554485: Current learning rate: 0.0063 +2024-11-22 04:36:12.198826: train_loss -0.792 +2024-11-22 04:36:12.203807: val_loss -0.788 +2024-11-22 04:36:12.203943: Pseudo dice [0.8664] +2024-11-22 04:36:12.204048: Epoch time: 18.65 s +2024-11-22 04:36:13.050690: +2024-11-22 04:36:13.050890: Epoch 3216 +2024-11-22 04:36:13.051005: Current learning rate: 0.0063 +2024-11-22 04:36:32.479741: train_loss -0.7776 +2024-11-22 04:36:32.485297: val_loss -0.773 +2024-11-22 04:36:32.485431: Pseudo dice [0.8414] +2024-11-22 04:36:32.485522: Epoch time: 19.43 s +2024-11-22 04:36:33.332737: +2024-11-22 04:36:33.332932: Epoch 3217 +2024-11-22 04:36:33.333039: Current learning rate: 0.00629 +2024-11-22 04:36:53.024755: train_loss -0.7803 +2024-11-22 04:36:53.026708: val_loss -0.7545 +2024-11-22 04:36:53.026796: Pseudo dice [0.8419] +2024-11-22 04:36:53.026876: Epoch time: 19.69 s +2024-11-22 04:36:53.858075: +2024-11-22 04:36:53.858297: Epoch 3218 +2024-11-22 04:36:53.858411: Current learning rate: 0.00629 +2024-11-22 04:37:13.531286: train_loss -0.7713 +2024-11-22 04:37:13.538074: val_loss -0.7758 +2024-11-22 04:37:13.538192: Pseudo dice [0.8553] +2024-11-22 04:37:13.538273: Epoch time: 19.67 s +2024-11-22 04:37:14.371612: +2024-11-22 04:37:14.371812: Epoch 3219 +2024-11-22 04:37:14.371927: Current learning rate: 0.00629 +2024-11-22 04:37:33.298029: train_loss -0.7774 +2024-11-22 04:37:33.315369: val_loss -0.7668 +2024-11-22 04:37:33.315490: Pseudo dice [0.8589] +2024-11-22 04:37:33.315584: Epoch time: 18.93 s +2024-11-22 04:37:34.564752: +2024-11-22 04:37:34.564952: Epoch 3220 +2024-11-22 04:37:34.565072: Current learning rate: 0.00629 +2024-11-22 04:37:53.881596: train_loss -0.7681 +2024-11-22 04:37:53.887646: val_loss -0.742 +2024-11-22 04:37:53.887777: Pseudo dice [0.8468] +2024-11-22 04:37:53.887855: Epoch time: 19.32 s +2024-11-22 04:37:54.731534: +2024-11-22 04:37:54.731760: Epoch 3221 +2024-11-22 04:37:54.731873: Current learning rate: 0.00629 +2024-11-22 04:38:14.127793: train_loss -0.7926 +2024-11-22 04:38:14.136015: val_loss -0.7454 +2024-11-22 04:38:14.136253: Pseudo dice [0.8599] +2024-11-22 04:38:14.136362: Epoch time: 19.4 s +2024-11-22 04:38:14.992220: +2024-11-22 04:38:14.992447: Epoch 3222 +2024-11-22 04:38:14.992564: Current learning rate: 0.00629 +2024-11-22 04:38:33.860664: train_loss -0.7762 +2024-11-22 04:38:33.864890: val_loss -0.7759 +2024-11-22 04:38:33.865057: Pseudo dice [0.845] +2024-11-22 04:38:33.865155: Epoch time: 18.87 s +2024-11-22 04:38:34.716396: +2024-11-22 04:38:34.716601: Epoch 3223 +2024-11-22 04:38:34.716712: Current learning rate: 0.00629 +2024-11-22 04:38:54.193141: train_loss -0.7826 +2024-11-22 04:38:54.199339: val_loss -0.7687 +2024-11-22 04:38:54.199473: Pseudo dice [0.8294] +2024-11-22 04:38:54.199553: Epoch time: 19.48 s +2024-11-22 04:38:55.041888: +2024-11-22 04:38:55.042099: Epoch 3224 +2024-11-22 04:38:55.042215: Current learning rate: 0.00629 +2024-11-22 04:39:14.957711: train_loss -0.7726 +2024-11-22 04:39:14.963439: val_loss -0.7673 +2024-11-22 04:39:14.963550: Pseudo dice [0.8433] +2024-11-22 04:39:14.963637: Epoch time: 19.92 s +2024-11-22 04:39:15.855761: +2024-11-22 04:39:15.855982: Epoch 3225 +2024-11-22 04:39:15.856103: Current learning rate: 0.00628 +2024-11-22 04:39:34.574914: train_loss -0.783 +2024-11-22 04:39:34.583287: val_loss -0.7683 +2024-11-22 04:39:34.583417: Pseudo dice [0.8503] +2024-11-22 04:39:34.583495: Epoch time: 18.72 s +2024-11-22 04:39:35.522493: +2024-11-22 04:39:35.522692: Epoch 3226 +2024-11-22 04:39:35.522802: Current learning rate: 0.00628 +2024-11-22 04:39:55.505941: train_loss -0.7831 +2024-11-22 04:39:55.513658: val_loss -0.751 +2024-11-22 04:39:55.513812: Pseudo dice [0.8331] +2024-11-22 04:39:55.513898: Epoch time: 19.98 s +2024-11-22 04:39:56.354967: +2024-11-22 04:39:56.355159: Epoch 3227 +2024-11-22 04:39:56.355266: Current learning rate: 0.00628 +2024-11-22 04:40:15.239428: train_loss -0.778 +2024-11-22 04:40:15.245009: val_loss -0.7322 +2024-11-22 04:40:15.245135: Pseudo dice [0.8367] +2024-11-22 04:40:15.245224: Epoch time: 18.89 s +2024-11-22 04:40:16.115718: +2024-11-22 04:40:16.115930: Epoch 3228 +2024-11-22 04:40:16.116044: Current learning rate: 0.00628 +2024-11-22 04:40:35.051741: train_loss -0.7684 +2024-11-22 04:40:35.053789: val_loss -0.7445 +2024-11-22 04:40:35.053900: Pseudo dice [0.8491] +2024-11-22 04:40:35.053983: Epoch time: 18.94 s +2024-11-22 04:40:35.894963: +2024-11-22 04:40:35.895195: Epoch 3229 +2024-11-22 04:40:35.895313: Current learning rate: 0.00628 +2024-11-22 04:40:54.964744: train_loss -0.7658 +2024-11-22 04:40:54.979077: val_loss -0.7602 +2024-11-22 04:40:54.979217: Pseudo dice [0.8441] +2024-11-22 04:40:54.979298: Epoch time: 19.07 s +2024-11-22 04:40:55.823598: +2024-11-22 04:40:55.823865: Epoch 3230 +2024-11-22 04:40:55.823981: Current learning rate: 0.00628 +2024-11-22 04:41:15.669651: train_loss -0.7718 +2024-11-22 04:41:15.676269: val_loss -0.7692 +2024-11-22 04:41:15.676405: Pseudo dice [0.8578] +2024-11-22 04:41:15.676502: Epoch time: 19.85 s +2024-11-22 04:41:16.928631: +2024-11-22 04:41:16.928823: Epoch 3231 +2024-11-22 04:41:16.928935: Current learning rate: 0.00628 +2024-11-22 04:41:36.571561: train_loss -0.7757 +2024-11-22 04:41:36.577873: val_loss -0.7922 +2024-11-22 04:41:36.578005: Pseudo dice [0.8523] +2024-11-22 04:41:36.578092: Epoch time: 19.64 s +2024-11-22 04:41:37.424072: +2024-11-22 04:41:37.424306: Epoch 3232 +2024-11-22 04:41:37.424425: Current learning rate: 0.00628 +2024-11-22 04:41:57.146177: train_loss -0.7816 +2024-11-22 04:41:57.154354: val_loss -0.7738 +2024-11-22 04:41:57.154475: Pseudo dice [0.8488] +2024-11-22 04:41:57.154559: Epoch time: 19.72 s +2024-11-22 04:41:58.026367: +2024-11-22 04:41:58.026588: Epoch 3233 +2024-11-22 04:41:58.026700: Current learning rate: 0.00628 +2024-11-22 04:42:16.907448: train_loss -0.7755 +2024-11-22 04:42:16.914387: val_loss -0.7784 +2024-11-22 04:42:16.914496: Pseudo dice [0.8497] +2024-11-22 04:42:16.914591: Epoch time: 18.88 s +2024-11-22 04:42:17.748950: +2024-11-22 04:42:17.749173: Epoch 3234 +2024-11-22 04:42:17.749285: Current learning rate: 0.00627 +2024-11-22 04:42:35.820665: train_loss -0.7776 +2024-11-22 04:42:35.826017: val_loss -0.7375 +2024-11-22 04:42:35.826414: Pseudo dice [0.841] +2024-11-22 04:42:35.826548: Epoch time: 18.07 s +2024-11-22 04:42:36.678493: +2024-11-22 04:42:36.678706: Epoch 3235 +2024-11-22 04:42:36.678814: Current learning rate: 0.00627 +2024-11-22 04:42:55.727328: train_loss -0.7656 +2024-11-22 04:42:55.735622: val_loss -0.7484 +2024-11-22 04:42:55.735742: Pseudo dice [0.846] +2024-11-22 04:42:55.735818: Epoch time: 19.05 s +2024-11-22 04:42:56.903140: +2024-11-22 04:42:56.903358: Epoch 3236 +2024-11-22 04:42:56.903470: Current learning rate: 0.00627 +2024-11-22 04:43:16.085929: train_loss -0.7757 +2024-11-22 04:43:16.088309: val_loss -0.7767 +2024-11-22 04:43:16.088411: Pseudo dice [0.8501] +2024-11-22 04:43:16.088493: Epoch time: 19.18 s +2024-11-22 04:43:16.925460: +2024-11-22 04:43:16.925680: Epoch 3237 +2024-11-22 04:43:16.925792: Current learning rate: 0.00627 +2024-11-22 04:43:35.799819: train_loss -0.7817 +2024-11-22 04:43:35.802017: val_loss -0.7684 +2024-11-22 04:43:35.802149: Pseudo dice [0.8629] +2024-11-22 04:43:35.802269: Epoch time: 18.88 s +2024-11-22 04:43:36.647970: +2024-11-22 04:43:36.648177: Epoch 3238 +2024-11-22 04:43:36.648293: Current learning rate: 0.00627 +2024-11-22 04:43:56.009749: train_loss -0.7822 +2024-11-22 04:43:56.017942: val_loss -0.7619 +2024-11-22 04:43:56.018078: Pseudo dice [0.8654] +2024-11-22 04:43:56.018157: Epoch time: 19.36 s +2024-11-22 04:43:56.972711: +2024-11-22 04:43:56.972925: Epoch 3239 +2024-11-22 04:43:56.973034: Current learning rate: 0.00627 +2024-11-22 04:44:15.419356: train_loss -0.7896 +2024-11-22 04:44:15.422823: val_loss -0.7802 +2024-11-22 04:44:15.422925: Pseudo dice [0.8551] +2024-11-22 04:44:15.423004: Epoch time: 18.45 s +2024-11-22 04:44:16.263631: +2024-11-22 04:44:16.263843: Epoch 3240 +2024-11-22 04:44:16.263957: Current learning rate: 0.00627 +2024-11-22 04:44:35.890003: train_loss -0.7752 +2024-11-22 04:44:35.892487: val_loss -0.7685 +2024-11-22 04:44:35.892606: Pseudo dice [0.842] +2024-11-22 04:44:35.892696: Epoch time: 19.63 s +2024-11-22 04:44:36.870348: +2024-11-22 04:44:36.870576: Epoch 3241 +2024-11-22 04:44:36.870692: Current learning rate: 0.00627 +2024-11-22 04:44:55.200598: train_loss -0.7838 +2024-11-22 04:44:55.206697: val_loss -0.7466 +2024-11-22 04:44:55.206830: Pseudo dice [0.8446] +2024-11-22 04:44:55.206915: Epoch time: 18.33 s +2024-11-22 04:44:56.084236: +2024-11-22 04:44:56.084648: Epoch 3242 +2024-11-22 04:44:56.084775: Current learning rate: 0.00626 +2024-11-22 04:45:14.199300: train_loss -0.7742 +2024-11-22 04:45:14.201423: val_loss -0.7491 +2024-11-22 04:45:14.201535: Pseudo dice [0.8496] +2024-11-22 04:45:14.201619: Epoch time: 18.12 s +2024-11-22 04:45:15.457115: +2024-11-22 04:45:15.457394: Epoch 3243 +2024-11-22 04:45:15.457505: Current learning rate: 0.00626 +2024-11-22 04:45:35.184584: train_loss -0.7751 +2024-11-22 04:45:35.187423: val_loss -0.7599 +2024-11-22 04:45:35.187523: Pseudo dice [0.8469] +2024-11-22 04:45:35.187611: Epoch time: 19.73 s +2024-11-22 04:45:36.029637: +2024-11-22 04:45:36.029869: Epoch 3244 +2024-11-22 04:45:36.029982: Current learning rate: 0.00626 +2024-11-22 04:45:54.719972: train_loss -0.7702 +2024-11-22 04:45:54.726993: val_loss -0.7848 +2024-11-22 04:45:54.727116: Pseudo dice [0.85] +2024-11-22 04:45:54.727198: Epoch time: 18.69 s +2024-11-22 04:45:55.562826: +2024-11-22 04:45:55.563047: Epoch 3245 +2024-11-22 04:45:55.563164: Current learning rate: 0.00626 +2024-11-22 04:46:15.118324: train_loss -0.7789 +2024-11-22 04:46:15.120867: val_loss -0.7796 +2024-11-22 04:46:15.120959: Pseudo dice [0.8416] +2024-11-22 04:46:15.121033: Epoch time: 19.56 s +2024-11-22 04:46:15.966481: +2024-11-22 04:46:15.966708: Epoch 3246 +2024-11-22 04:46:15.966822: Current learning rate: 0.00626 +2024-11-22 04:46:35.094268: train_loss -0.7825 +2024-11-22 04:46:35.097785: val_loss -0.7554 +2024-11-22 04:46:35.097894: Pseudo dice [0.8506] +2024-11-22 04:46:35.097997: Epoch time: 19.13 s +2024-11-22 04:46:35.971803: +2024-11-22 04:46:35.972157: Epoch 3247 +2024-11-22 04:46:35.972271: Current learning rate: 0.00626 +2024-11-22 04:46:55.313914: train_loss -0.77 +2024-11-22 04:46:55.325153: val_loss -0.7824 +2024-11-22 04:46:55.325393: Pseudo dice [0.8407] +2024-11-22 04:46:55.325536: Epoch time: 19.34 s +2024-11-22 04:46:56.204946: +2024-11-22 04:46:56.205158: Epoch 3248 +2024-11-22 04:46:56.205276: Current learning rate: 0.00626 +2024-11-22 04:47:15.150554: train_loss -0.7624 +2024-11-22 04:47:15.158397: val_loss -0.7553 +2024-11-22 04:47:15.158512: Pseudo dice [0.8417] +2024-11-22 04:47:15.158603: Epoch time: 18.95 s +2024-11-22 04:47:16.112906: +2024-11-22 04:47:16.113105: Epoch 3249 +2024-11-22 04:47:16.113223: Current learning rate: 0.00626 +2024-11-22 04:47:34.267092: train_loss -0.7805 +2024-11-22 04:47:34.280257: val_loss -0.7575 +2024-11-22 04:47:34.280469: Pseudo dice [0.8654] +2024-11-22 04:47:34.280549: Epoch time: 18.16 s +2024-11-22 04:47:35.641629: +2024-11-22 04:47:35.641872: Epoch 3250 +2024-11-22 04:47:35.641988: Current learning rate: 0.00626 +2024-11-22 04:47:55.222921: train_loss -0.7809 +2024-11-22 04:47:55.224716: val_loss -0.757 +2024-11-22 04:47:55.224809: Pseudo dice [0.857] +2024-11-22 04:47:55.224896: Epoch time: 19.58 s +2024-11-22 04:47:56.061394: +2024-11-22 04:47:56.061600: Epoch 3251 +2024-11-22 04:47:56.061716: Current learning rate: 0.00625 +2024-11-22 04:48:14.036248: train_loss -0.77 +2024-11-22 04:48:14.047794: val_loss -0.7775 +2024-11-22 04:48:14.047928: Pseudo dice [0.8368] +2024-11-22 04:48:14.048034: Epoch time: 17.98 s +2024-11-22 04:48:14.895399: +2024-11-22 04:48:14.895625: Epoch 3252 +2024-11-22 04:48:14.895737: Current learning rate: 0.00625 +2024-11-22 04:48:34.109307: train_loss -0.7692 +2024-11-22 04:48:34.115662: val_loss -0.7442 +2024-11-22 04:48:34.115792: Pseudo dice [0.8369] +2024-11-22 04:48:34.115874: Epoch time: 19.21 s +2024-11-22 04:48:34.963776: +2024-11-22 04:48:34.964003: Epoch 3253 +2024-11-22 04:48:34.964118: Current learning rate: 0.00625 +2024-11-22 04:48:53.574167: train_loss -0.7598 +2024-11-22 04:48:53.578269: val_loss -0.7677 +2024-11-22 04:48:53.578378: Pseudo dice [0.8349] +2024-11-22 04:48:53.578460: Epoch time: 18.61 s +2024-11-22 04:48:54.822317: +2024-11-22 04:48:54.822514: Epoch 3254 +2024-11-22 04:48:54.822621: Current learning rate: 0.00625 +2024-11-22 04:49:13.721976: train_loss -0.7743 +2024-11-22 04:49:13.732157: val_loss -0.7779 +2024-11-22 04:49:13.732298: Pseudo dice [0.8392] +2024-11-22 04:49:13.732398: Epoch time: 18.9 s +2024-11-22 04:49:14.590011: +2024-11-22 04:49:14.590306: Epoch 3255 +2024-11-22 04:49:14.590422: Current learning rate: 0.00625 +2024-11-22 04:49:32.449812: train_loss -0.784 +2024-11-22 04:49:32.453373: val_loss -0.763 +2024-11-22 04:49:32.453508: Pseudo dice [0.8539] +2024-11-22 04:49:32.453586: Epoch time: 17.86 s +2024-11-22 04:49:33.293301: +2024-11-22 04:49:33.293537: Epoch 3256 +2024-11-22 04:49:33.293651: Current learning rate: 0.00625 +2024-11-22 04:49:51.884988: train_loss -0.7708 +2024-11-22 04:49:51.890274: val_loss -0.7627 +2024-11-22 04:49:51.890439: Pseudo dice [0.8487] +2024-11-22 04:49:51.890519: Epoch time: 18.59 s +2024-11-22 04:49:52.744944: +2024-11-22 04:49:52.745152: Epoch 3257 +2024-11-22 04:49:52.745267: Current learning rate: 0.00625 +2024-11-22 04:50:12.639516: train_loss -0.7748 +2024-11-22 04:50:12.654257: val_loss -0.7823 +2024-11-22 04:50:12.654372: Pseudo dice [0.8574] +2024-11-22 04:50:12.654455: Epoch time: 19.9 s +2024-11-22 04:50:13.505940: +2024-11-22 04:50:13.506152: Epoch 3258 +2024-11-22 04:50:13.506264: Current learning rate: 0.00625 +2024-11-22 04:50:32.470715: train_loss -0.7885 +2024-11-22 04:50:32.478851: val_loss -0.7473 +2024-11-22 04:50:32.478994: Pseudo dice [0.8495] +2024-11-22 04:50:32.479099: Epoch time: 18.97 s +2024-11-22 04:50:33.329512: +2024-11-22 04:50:33.329716: Epoch 3259 +2024-11-22 04:50:33.329828: Current learning rate: 0.00624 +2024-11-22 04:50:53.048502: train_loss -0.7818 +2024-11-22 04:50:53.052326: val_loss -0.7675 +2024-11-22 04:50:53.052445: Pseudo dice [0.8601] +2024-11-22 04:50:53.052531: Epoch time: 19.72 s +2024-11-22 04:50:54.072397: +2024-11-22 04:50:54.072827: Epoch 3260 +2024-11-22 04:50:54.072943: Current learning rate: 0.00624 +2024-11-22 04:51:13.893277: train_loss -0.7782 +2024-11-22 04:51:13.901690: val_loss -0.7654 +2024-11-22 04:51:13.901807: Pseudo dice [0.8484] +2024-11-22 04:51:13.901892: Epoch time: 19.82 s +2024-11-22 04:51:14.764899: +2024-11-22 04:51:14.765112: Epoch 3261 +2024-11-22 04:51:14.765228: Current learning rate: 0.00624 +2024-11-22 04:51:34.238754: train_loss -0.7776 +2024-11-22 04:51:34.240817: val_loss -0.7632 +2024-11-22 04:51:34.240899: Pseudo dice [0.8536] +2024-11-22 04:51:34.240984: Epoch time: 19.47 s +2024-11-22 04:51:35.075127: +2024-11-22 04:51:35.075331: Epoch 3262 +2024-11-22 04:51:35.075445: Current learning rate: 0.00624 +2024-11-22 04:51:54.366018: train_loss -0.7822 +2024-11-22 04:51:54.370130: val_loss -0.7845 +2024-11-22 04:51:54.370247: Pseudo dice [0.8617] +2024-11-22 04:51:54.370345: Epoch time: 19.29 s +2024-11-22 04:51:55.211250: +2024-11-22 04:51:55.211493: Epoch 3263 +2024-11-22 04:51:55.211616: Current learning rate: 0.00624 +2024-11-22 04:52:13.859541: train_loss -0.7705 +2024-11-22 04:52:13.863611: val_loss -0.7696 +2024-11-22 04:52:13.863746: Pseudo dice [0.8518] +2024-11-22 04:52:13.863827: Epoch time: 18.65 s +2024-11-22 04:52:14.714381: +2024-11-22 04:52:14.714608: Epoch 3264 +2024-11-22 04:52:14.714729: Current learning rate: 0.00624 +2024-11-22 04:52:33.665663: train_loss -0.7814 +2024-11-22 04:52:33.673301: val_loss -0.7783 +2024-11-22 04:52:33.673431: Pseudo dice [0.8565] +2024-11-22 04:52:33.673518: Epoch time: 18.95 s +2024-11-22 04:52:34.730747: +2024-11-22 04:52:34.730955: Epoch 3265 +2024-11-22 04:52:34.731070: Current learning rate: 0.00624 +2024-11-22 04:52:54.575193: train_loss -0.7807 +2024-11-22 04:52:54.585123: val_loss -0.7495 +2024-11-22 04:52:54.585250: Pseudo dice [0.8611] +2024-11-22 04:52:54.585337: Epoch time: 19.85 s +2024-11-22 04:52:55.915981: +2024-11-22 04:52:55.916237: Epoch 3266 +2024-11-22 04:52:55.916350: Current learning rate: 0.00624 +2024-11-22 04:53:15.215943: train_loss -0.7852 +2024-11-22 04:53:15.217842: val_loss -0.7751 +2024-11-22 04:53:15.217935: Pseudo dice [0.8471] +2024-11-22 04:53:15.218018: Epoch time: 19.3 s +2024-11-22 04:53:16.049748: +2024-11-22 04:53:16.050015: Epoch 3267 +2024-11-22 04:53:16.050128: Current learning rate: 0.00624 +2024-11-22 04:53:35.072066: train_loss -0.7789 +2024-11-22 04:53:35.074272: val_loss -0.7544 +2024-11-22 04:53:35.074385: Pseudo dice [0.8553] +2024-11-22 04:53:35.074470: Epoch time: 19.02 s +2024-11-22 04:53:36.109418: +2024-11-22 04:53:36.109616: Epoch 3268 +2024-11-22 04:53:36.109724: Current learning rate: 0.00623 +2024-11-22 04:53:55.027299: train_loss -0.7883 +2024-11-22 04:53:55.033535: val_loss -0.7478 +2024-11-22 04:53:55.033670: Pseudo dice [0.8428] +2024-11-22 04:53:55.033758: Epoch time: 18.92 s +2024-11-22 04:53:55.952162: +2024-11-22 04:53:55.952373: Epoch 3269 +2024-11-22 04:53:55.952490: Current learning rate: 0.00623 +2024-11-22 04:54:15.080142: train_loss -0.7567 +2024-11-22 04:54:15.082553: val_loss -0.7708 +2024-11-22 04:54:15.082702: Pseudo dice [0.8507] +2024-11-22 04:54:15.082796: Epoch time: 19.13 s +2024-11-22 04:54:15.931359: +2024-11-22 04:54:15.931571: Epoch 3270 +2024-11-22 04:54:15.931688: Current learning rate: 0.00623 +2024-11-22 04:54:34.814570: train_loss -0.7664 +2024-11-22 04:54:34.817672: val_loss -0.7255 +2024-11-22 04:54:34.817761: Pseudo dice [0.844] +2024-11-22 04:54:34.817839: Epoch time: 18.88 s +2024-11-22 04:54:35.663422: +2024-11-22 04:54:35.663621: Epoch 3271 +2024-11-22 04:54:35.663735: Current learning rate: 0.00623 +2024-11-22 04:54:55.056159: train_loss -0.7698 +2024-11-22 04:54:55.064386: val_loss -0.7646 +2024-11-22 04:54:55.064518: Pseudo dice [0.8376] +2024-11-22 04:54:55.064659: Epoch time: 19.39 s +2024-11-22 04:54:56.025175: +2024-11-22 04:54:56.025392: Epoch 3272 +2024-11-22 04:54:56.025503: Current learning rate: 0.00623 +2024-11-22 04:55:14.672177: train_loss -0.7705 +2024-11-22 04:55:14.686165: val_loss -0.7873 +2024-11-22 04:55:14.686280: Pseudo dice [0.8553] +2024-11-22 04:55:14.686626: Epoch time: 18.65 s +2024-11-22 04:55:15.763817: +2024-11-22 04:55:15.764039: Epoch 3273 +2024-11-22 04:55:15.764154: Current learning rate: 0.00623 +2024-11-22 04:55:33.900528: train_loss -0.772 +2024-11-22 04:55:33.907217: val_loss -0.7844 +2024-11-22 04:55:33.907340: Pseudo dice [0.8538] +2024-11-22 04:55:33.907432: Epoch time: 18.14 s +2024-11-22 04:55:34.887609: +2024-11-22 04:55:34.887834: Epoch 3274 +2024-11-22 04:55:34.887945: Current learning rate: 0.00623 +2024-11-22 04:55:54.356204: train_loss -0.7716 +2024-11-22 04:55:54.358172: val_loss -0.768 +2024-11-22 04:55:54.358265: Pseudo dice [0.8586] +2024-11-22 04:55:54.358377: Epoch time: 19.47 s +2024-11-22 04:55:55.200684: +2024-11-22 04:55:55.200890: Epoch 3275 +2024-11-22 04:55:55.201005: Current learning rate: 0.00623 +2024-11-22 04:56:15.010906: train_loss -0.7663 +2024-11-22 04:56:15.015721: val_loss -0.7616 +2024-11-22 04:56:15.015848: Pseudo dice [0.8465] +2024-11-22 04:56:15.016049: Epoch time: 19.81 s +2024-11-22 04:56:15.884376: +2024-11-22 04:56:15.884591: Epoch 3276 +2024-11-22 04:56:15.884702: Current learning rate: 0.00622 +2024-11-22 04:56:34.344897: train_loss -0.7767 +2024-11-22 04:56:34.355441: val_loss -0.7783 +2024-11-22 04:56:34.355582: Pseudo dice [0.8466] +2024-11-22 04:56:34.355680: Epoch time: 18.46 s +2024-11-22 04:56:35.259392: +2024-11-22 04:56:35.259615: Epoch 3277 +2024-11-22 04:56:35.259725: Current learning rate: 0.00622 +2024-11-22 04:56:54.802226: train_loss -0.7873 +2024-11-22 04:56:54.805066: val_loss -0.7609 +2024-11-22 04:56:54.805183: Pseudo dice [0.8408] +2024-11-22 04:56:54.805270: Epoch time: 19.54 s +2024-11-22 04:56:55.642023: +2024-11-22 04:56:55.642252: Epoch 3278 +2024-11-22 04:56:55.642367: Current learning rate: 0.00622 +2024-11-22 04:57:15.393405: train_loss -0.7751 +2024-11-22 04:57:15.395787: val_loss -0.7762 +2024-11-22 04:57:15.395887: Pseudo dice [0.8645] +2024-11-22 04:57:15.395965: Epoch time: 19.75 s +2024-11-22 04:57:16.229358: +2024-11-22 04:57:16.229589: Epoch 3279 +2024-11-22 04:57:16.229707: Current learning rate: 0.00622 +2024-11-22 04:57:34.974247: train_loss -0.7794 +2024-11-22 04:57:34.979304: val_loss -0.7938 +2024-11-22 04:57:34.979449: Pseudo dice [0.8547] +2024-11-22 04:57:34.979540: Epoch time: 18.75 s +2024-11-22 04:57:35.819531: +2024-11-22 04:57:35.819744: Epoch 3280 +2024-11-22 04:57:35.819855: Current learning rate: 0.00622 +2024-11-22 04:57:54.278196: train_loss -0.7781 +2024-11-22 04:57:54.290177: val_loss -0.7627 +2024-11-22 04:57:54.290324: Pseudo dice [0.8528] +2024-11-22 04:57:54.290415: Epoch time: 18.46 s +2024-11-22 04:57:55.161119: +2024-11-22 04:57:55.161332: Epoch 3281 +2024-11-22 04:57:55.161445: Current learning rate: 0.00622 +2024-11-22 04:58:13.943266: train_loss -0.7861 +2024-11-22 04:58:13.944981: val_loss -0.762 +2024-11-22 04:58:13.945078: Pseudo dice [0.8541] +2024-11-22 04:58:13.945159: Epoch time: 18.78 s +2024-11-22 04:58:14.785305: +2024-11-22 04:58:14.785517: Epoch 3282 +2024-11-22 04:58:14.785629: Current learning rate: 0.00622 +2024-11-22 04:58:33.804156: train_loss -0.7767 +2024-11-22 04:58:33.807076: val_loss -0.7848 +2024-11-22 04:58:33.807190: Pseudo dice [0.8376] +2024-11-22 04:58:33.807273: Epoch time: 19.02 s +2024-11-22 04:58:34.783321: +2024-11-22 04:58:34.783569: Epoch 3283 +2024-11-22 04:58:34.783679: Current learning rate: 0.00622 +2024-11-22 04:58:53.025246: train_loss -0.782 +2024-11-22 04:58:53.030764: val_loss -0.7776 +2024-11-22 04:58:53.030890: Pseudo dice [0.8521] +2024-11-22 04:58:53.030973: Epoch time: 18.24 s +2024-11-22 04:58:53.978674: +2024-11-22 04:58:53.978889: Epoch 3284 +2024-11-22 04:58:53.979003: Current learning rate: 0.00621 +2024-11-22 04:59:14.011950: train_loss -0.771 +2024-11-22 04:59:14.014824: val_loss -0.7586 +2024-11-22 04:59:14.014935: Pseudo dice [0.8522] +2024-11-22 04:59:14.015021: Epoch time: 20.03 s +2024-11-22 04:59:14.870801: +2024-11-22 04:59:14.871006: Epoch 3285 +2024-11-22 04:59:14.871127: Current learning rate: 0.00621 +2024-11-22 04:59:34.167964: train_loss -0.7719 +2024-11-22 04:59:34.170056: val_loss -0.7554 +2024-11-22 04:59:34.170168: Pseudo dice [0.854] +2024-11-22 04:59:34.170248: Epoch time: 19.3 s +2024-11-22 04:59:35.015522: +2024-11-22 04:59:35.015726: Epoch 3286 +2024-11-22 04:59:35.015836: Current learning rate: 0.00621 +2024-11-22 04:59:54.075137: train_loss -0.7602 +2024-11-22 04:59:54.076763: val_loss -0.7687 +2024-11-22 04:59:54.076857: Pseudo dice [0.8516] +2024-11-22 04:59:54.076959: Epoch time: 19.06 s +2024-11-22 04:59:54.910441: +2024-11-22 04:59:54.910625: Epoch 3287 +2024-11-22 04:59:54.910731: Current learning rate: 0.00621 +2024-11-22 05:00:13.389159: train_loss -0.7736 +2024-11-22 05:00:13.395644: val_loss -0.7584 +2024-11-22 05:00:13.395783: Pseudo dice [0.8426] +2024-11-22 05:00:13.395878: Epoch time: 18.48 s +2024-11-22 05:00:14.283787: +2024-11-22 05:00:14.284020: Epoch 3288 +2024-11-22 05:00:14.284138: Current learning rate: 0.00621 +2024-11-22 05:00:33.445545: train_loss -0.7719 +2024-11-22 05:00:33.449786: val_loss -0.7652 +2024-11-22 05:00:33.449915: Pseudo dice [0.855] +2024-11-22 05:00:33.449994: Epoch time: 19.16 s +2024-11-22 05:00:34.740847: +2024-11-22 05:00:34.741075: Epoch 3289 +2024-11-22 05:00:34.741184: Current learning rate: 0.00621 +2024-11-22 05:00:53.610313: train_loss -0.7736 +2024-11-22 05:00:53.611844: val_loss -0.7573 +2024-11-22 05:00:53.611961: Pseudo dice [0.8432] +2024-11-22 05:00:53.612053: Epoch time: 18.87 s +2024-11-22 05:00:54.447221: +2024-11-22 05:00:54.447438: Epoch 3290 +2024-11-22 05:00:54.447554: Current learning rate: 0.00621 +2024-11-22 05:01:12.510087: train_loss -0.7761 +2024-11-22 05:01:12.515251: val_loss -0.7578 +2024-11-22 05:01:12.515381: Pseudo dice [0.8369] +2024-11-22 05:01:12.515467: Epoch time: 18.06 s +2024-11-22 05:01:13.567487: +2024-11-22 05:01:13.567780: Epoch 3291 +2024-11-22 05:01:13.567896: Current learning rate: 0.00621 +2024-11-22 05:01:32.787516: train_loss -0.7741 +2024-11-22 05:01:32.795178: val_loss -0.7588 +2024-11-22 05:01:32.795287: Pseudo dice [0.8469] +2024-11-22 05:01:32.795372: Epoch time: 19.22 s +2024-11-22 05:01:33.745232: +2024-11-22 05:01:33.745437: Epoch 3292 +2024-11-22 05:01:33.745551: Current learning rate: 0.00621 +2024-11-22 05:01:52.640153: train_loss -0.773 +2024-11-22 05:01:52.645833: val_loss -0.7556 +2024-11-22 05:01:52.645964: Pseudo dice [0.8607] +2024-11-22 05:01:52.646045: Epoch time: 18.9 s +2024-11-22 05:01:53.506471: +2024-11-22 05:01:53.506703: Epoch 3293 +2024-11-22 05:01:53.506824: Current learning rate: 0.0062 +2024-11-22 05:02:13.346197: train_loss -0.7708 +2024-11-22 05:02:13.347830: val_loss -0.7469 +2024-11-22 05:02:13.347959: Pseudo dice [0.8542] +2024-11-22 05:02:13.348042: Epoch time: 19.84 s +2024-11-22 05:02:14.190567: +2024-11-22 05:02:14.190832: Epoch 3294 +2024-11-22 05:02:14.190946: Current learning rate: 0.0062 +2024-11-22 05:02:32.957176: train_loss -0.761 +2024-11-22 05:02:32.960024: val_loss -0.7559 +2024-11-22 05:02:32.960179: Pseudo dice [0.8458] +2024-11-22 05:02:32.960271: Epoch time: 18.76 s +2024-11-22 05:02:33.912077: +2024-11-22 05:02:33.912294: Epoch 3295 +2024-11-22 05:02:33.912412: Current learning rate: 0.0062 +2024-11-22 05:02:52.629147: train_loss -0.761 +2024-11-22 05:02:52.635331: val_loss -0.7642 +2024-11-22 05:02:52.635464: Pseudo dice [0.8532] +2024-11-22 05:02:52.635557: Epoch time: 18.72 s +2024-11-22 05:02:53.552479: +2024-11-22 05:02:53.552673: Epoch 3296 +2024-11-22 05:02:53.552785: Current learning rate: 0.0062 +2024-11-22 05:03:12.533808: train_loss -0.7771 +2024-11-22 05:03:12.537501: val_loss -0.7833 +2024-11-22 05:03:12.537633: Pseudo dice [0.8497] +2024-11-22 05:03:12.537716: Epoch time: 18.98 s +2024-11-22 05:03:13.453282: +2024-11-22 05:03:13.453472: Epoch 3297 +2024-11-22 05:03:13.453588: Current learning rate: 0.0062 +2024-11-22 05:03:32.377244: train_loss -0.7832 +2024-11-22 05:03:32.380787: val_loss -0.7723 +2024-11-22 05:03:32.380895: Pseudo dice [0.8507] +2024-11-22 05:03:32.380973: Epoch time: 18.92 s +2024-11-22 05:03:33.252109: +2024-11-22 05:03:33.252312: Epoch 3298 +2024-11-22 05:03:33.252652: Current learning rate: 0.0062 +2024-11-22 05:03:51.833949: train_loss -0.7788 +2024-11-22 05:03:51.835534: val_loss -0.7843 +2024-11-22 05:03:51.835671: Pseudo dice [0.8599] +2024-11-22 05:03:51.835767: Epoch time: 18.58 s +2024-11-22 05:03:52.874020: +2024-11-22 05:03:52.874303: Epoch 3299 +2024-11-22 05:03:52.874416: Current learning rate: 0.0062 +2024-11-22 05:04:11.009637: train_loss -0.7774 +2024-11-22 05:04:11.011425: val_loss -0.7547 +2024-11-22 05:04:11.011541: Pseudo dice [0.8493] +2024-11-22 05:04:11.011623: Epoch time: 18.14 s +2024-11-22 05:04:12.577999: +2024-11-22 05:04:12.578231: Epoch 3300 +2024-11-22 05:04:12.578343: Current learning rate: 0.0062 +2024-11-22 05:04:31.727866: train_loss -0.7679 +2024-11-22 05:04:31.729644: val_loss -0.7389 +2024-11-22 05:04:31.729738: Pseudo dice [0.844] +2024-11-22 05:04:31.729817: Epoch time: 19.15 s +2024-11-22 05:04:32.561268: +2024-11-22 05:04:32.561540: Epoch 3301 +2024-11-22 05:04:32.561657: Current learning rate: 0.00619 +2024-11-22 05:04:51.532263: train_loss -0.7751 +2024-11-22 05:04:51.533716: val_loss -0.7503 +2024-11-22 05:04:51.533808: Pseudo dice [0.8597] +2024-11-22 05:04:51.533894: Epoch time: 18.97 s +2024-11-22 05:04:52.373924: +2024-11-22 05:04:52.374150: Epoch 3302 +2024-11-22 05:04:52.374264: Current learning rate: 0.00619 +2024-11-22 05:05:10.364559: train_loss -0.7685 +2024-11-22 05:05:10.371763: val_loss -0.754 +2024-11-22 05:05:10.371884: Pseudo dice [0.8359] +2024-11-22 05:05:10.371972: Epoch time: 17.99 s +2024-11-22 05:05:11.450213: +2024-11-22 05:05:11.450451: Epoch 3303 +2024-11-22 05:05:11.450563: Current learning rate: 0.00619 +2024-11-22 05:05:30.582033: train_loss -0.7745 +2024-11-22 05:05:30.583633: val_loss -0.7488 +2024-11-22 05:05:30.583735: Pseudo dice [0.8566] +2024-11-22 05:05:30.583819: Epoch time: 19.13 s +2024-11-22 05:05:31.422698: +2024-11-22 05:05:31.422917: Epoch 3304 +2024-11-22 05:05:31.423031: Current learning rate: 0.00619 +2024-11-22 05:05:50.821502: train_loss -0.7793 +2024-11-22 05:05:50.823333: val_loss -0.7761 +2024-11-22 05:05:50.823421: Pseudo dice [0.8357] +2024-11-22 05:05:50.823523: Epoch time: 19.4 s +2024-11-22 05:05:51.684537: +2024-11-22 05:05:51.684735: Epoch 3305 +2024-11-22 05:05:51.684852: Current learning rate: 0.00619 +2024-11-22 05:06:10.477960: train_loss -0.7809 +2024-11-22 05:06:10.479831: val_loss -0.7675 +2024-11-22 05:06:10.479948: Pseudo dice [0.84] +2024-11-22 05:06:10.480031: Epoch time: 18.79 s +2024-11-22 05:06:11.511641: +2024-11-22 05:06:11.511847: Epoch 3306 +2024-11-22 05:06:11.511961: Current learning rate: 0.00619 +2024-11-22 05:06:30.728625: train_loss -0.768 +2024-11-22 05:06:30.732450: val_loss -0.777 +2024-11-22 05:06:30.732579: Pseudo dice [0.8523] +2024-11-22 05:06:30.732664: Epoch time: 19.22 s +2024-11-22 05:06:31.595479: +2024-11-22 05:06:31.595682: Epoch 3307 +2024-11-22 05:06:31.595796: Current learning rate: 0.00619 +2024-11-22 05:06:50.712160: train_loss -0.7755 +2024-11-22 05:06:50.717924: val_loss -0.78 +2024-11-22 05:06:50.718072: Pseudo dice [0.8509] +2024-11-22 05:06:50.718160: Epoch time: 19.12 s +2024-11-22 05:06:51.573080: +2024-11-22 05:06:51.573291: Epoch 3308 +2024-11-22 05:06:51.573407: Current learning rate: 0.00619 +2024-11-22 05:07:09.682930: train_loss -0.7759 +2024-11-22 05:07:09.691033: val_loss -0.7707 +2024-11-22 05:07:09.691151: Pseudo dice [0.8554] +2024-11-22 05:07:09.691231: Epoch time: 18.11 s +2024-11-22 05:07:10.688894: +2024-11-22 05:07:10.689104: Epoch 3309 +2024-11-22 05:07:10.689216: Current learning rate: 0.00619 +2024-11-22 05:07:29.579205: train_loss -0.7788 +2024-11-22 05:07:29.586573: val_loss -0.7711 +2024-11-22 05:07:29.586692: Pseudo dice [0.8449] +2024-11-22 05:07:29.586786: Epoch time: 18.89 s +2024-11-22 05:07:30.455005: +2024-11-22 05:07:30.455205: Epoch 3310 +2024-11-22 05:07:30.455316: Current learning rate: 0.00618 +2024-11-22 05:07:49.127090: train_loss -0.7666 +2024-11-22 05:07:49.129291: val_loss -0.77 +2024-11-22 05:07:49.129374: Pseudo dice [0.8488] +2024-11-22 05:07:49.129449: Epoch time: 18.67 s +2024-11-22 05:07:49.979556: +2024-11-22 05:07:49.979755: Epoch 3311 +2024-11-22 05:07:49.979869: Current learning rate: 0.00618 +2024-11-22 05:08:08.607235: train_loss -0.7666 +2024-11-22 05:08:08.613631: val_loss -0.7591 +2024-11-22 05:08:08.613759: Pseudo dice [0.8532] +2024-11-22 05:08:08.613840: Epoch time: 18.63 s +2024-11-22 05:08:09.864841: +2024-11-22 05:08:09.865075: Epoch 3312 +2024-11-22 05:08:09.865191: Current learning rate: 0.00618 +2024-11-22 05:08:27.923852: train_loss -0.7782 +2024-11-22 05:08:27.934169: val_loss -0.7507 +2024-11-22 05:08:27.934299: Pseudo dice [0.8506] +2024-11-22 05:08:27.934386: Epoch time: 18.06 s +2024-11-22 05:08:28.778502: +2024-11-22 05:08:28.778731: Epoch 3313 +2024-11-22 05:08:28.778845: Current learning rate: 0.00618 +2024-11-22 05:08:46.994865: train_loss -0.7723 +2024-11-22 05:08:47.000823: val_loss -0.7354 +2024-11-22 05:08:47.000941: Pseudo dice [0.846] +2024-11-22 05:08:47.001027: Epoch time: 18.22 s +2024-11-22 05:08:47.870461: +2024-11-22 05:08:47.870685: Epoch 3314 +2024-11-22 05:08:47.870796: Current learning rate: 0.00618 +2024-11-22 05:09:07.397659: train_loss -0.7756 +2024-11-22 05:09:07.403884: val_loss -0.7794 +2024-11-22 05:09:07.404078: Pseudo dice [0.8559] +2024-11-22 05:09:07.404173: Epoch time: 19.53 s +2024-11-22 05:09:08.248345: +2024-11-22 05:09:08.248583: Epoch 3315 +2024-11-22 05:09:08.248699: Current learning rate: 0.00618 +2024-11-22 05:09:27.373274: train_loss -0.7852 +2024-11-22 05:09:27.384652: val_loss -0.7544 +2024-11-22 05:09:27.384766: Pseudo dice [0.8644] +2024-11-22 05:09:27.384850: Epoch time: 19.13 s +2024-11-22 05:09:28.319484: +2024-11-22 05:09:28.319686: Epoch 3316 +2024-11-22 05:09:28.319800: Current learning rate: 0.00618 +2024-11-22 05:09:47.281392: train_loss -0.772 +2024-11-22 05:09:47.286807: val_loss -0.7739 +2024-11-22 05:09:47.286944: Pseudo dice [0.8471] +2024-11-22 05:09:47.287040: Epoch time: 18.96 s +2024-11-22 05:09:48.195907: +2024-11-22 05:09:48.196146: Epoch 3317 +2024-11-22 05:09:48.196260: Current learning rate: 0.00618 +2024-11-22 05:10:05.994862: train_loss -0.7827 +2024-11-22 05:10:06.003256: val_loss -0.7579 +2024-11-22 05:10:06.003366: Pseudo dice [0.8484] +2024-11-22 05:10:06.003448: Epoch time: 17.8 s +2024-11-22 05:10:07.018493: +2024-11-22 05:10:07.018785: Epoch 3318 +2024-11-22 05:10:07.018896: Current learning rate: 0.00617 +2024-11-22 05:10:26.603277: train_loss -0.7762 +2024-11-22 05:10:26.612454: val_loss -0.7666 +2024-11-22 05:10:26.612612: Pseudo dice [0.8492] +2024-11-22 05:10:26.612717: Epoch time: 19.59 s +2024-11-22 05:10:27.496421: +2024-11-22 05:10:27.496640: Epoch 3319 +2024-11-22 05:10:27.496752: Current learning rate: 0.00617 +2024-11-22 05:10:45.737793: train_loss -0.7797 +2024-11-22 05:10:45.745241: val_loss -0.7756 +2024-11-22 05:10:45.745363: Pseudo dice [0.8446] +2024-11-22 05:10:45.745450: Epoch time: 18.24 s +2024-11-22 05:10:46.752665: +2024-11-22 05:10:46.752868: Epoch 3320 +2024-11-22 05:10:46.752980: Current learning rate: 0.00617 +2024-11-22 05:11:05.476261: train_loss -0.7722 +2024-11-22 05:11:05.488145: val_loss -0.7408 +2024-11-22 05:11:05.488281: Pseudo dice [0.8486] +2024-11-22 05:11:05.488372: Epoch time: 18.72 s +2024-11-22 05:11:06.358094: +2024-11-22 05:11:06.358294: Epoch 3321 +2024-11-22 05:11:06.358405: Current learning rate: 0.00617 +2024-11-22 05:11:24.919438: train_loss -0.7717 +2024-11-22 05:11:24.921828: val_loss -0.7416 +2024-11-22 05:11:24.921940: Pseudo dice [0.8494] +2024-11-22 05:11:24.922016: Epoch time: 18.56 s +2024-11-22 05:11:25.793332: +2024-11-22 05:11:25.793542: Epoch 3322 +2024-11-22 05:11:25.793653: Current learning rate: 0.00617 +2024-11-22 05:11:45.302400: train_loss -0.7717 +2024-11-22 05:11:45.304421: val_loss -0.7786 +2024-11-22 05:11:45.304559: Pseudo dice [0.8654] +2024-11-22 05:11:45.304643: Epoch time: 19.51 s +2024-11-22 05:11:46.525463: +2024-11-22 05:11:46.525668: Epoch 3323 +2024-11-22 05:11:46.525782: Current learning rate: 0.00617 +2024-11-22 05:12:05.261318: train_loss -0.7725 +2024-11-22 05:12:05.265204: val_loss -0.7782 +2024-11-22 05:12:05.291073: Pseudo dice [0.8454] +2024-11-22 05:12:05.291233: Epoch time: 18.74 s +2024-11-22 05:12:06.128652: +2024-11-22 05:12:06.128882: Epoch 3324 +2024-11-22 05:12:06.128995: Current learning rate: 0.00617 +2024-11-22 05:12:25.323155: train_loss -0.7797 +2024-11-22 05:12:25.325462: val_loss -0.7653 +2024-11-22 05:12:25.325553: Pseudo dice [0.8493] +2024-11-22 05:12:25.325636: Epoch time: 19.2 s +2024-11-22 05:12:26.158585: +2024-11-22 05:12:26.158785: Epoch 3325 +2024-11-22 05:12:26.158906: Current learning rate: 0.00617 +2024-11-22 05:12:45.169539: train_loss -0.79 +2024-11-22 05:12:45.172019: val_loss -0.7844 +2024-11-22 05:12:45.172110: Pseudo dice [0.8571] +2024-11-22 05:12:45.172230: Epoch time: 19.01 s +2024-11-22 05:12:46.008409: +2024-11-22 05:12:46.008626: Epoch 3326 +2024-11-22 05:12:46.008739: Current learning rate: 0.00617 +2024-11-22 05:13:05.121016: train_loss -0.7877 +2024-11-22 05:13:05.137269: val_loss -0.7781 +2024-11-22 05:13:05.137419: Pseudo dice [0.8497] +2024-11-22 05:13:05.137506: Epoch time: 19.11 s +2024-11-22 05:13:05.987248: +2024-11-22 05:13:05.987459: Epoch 3327 +2024-11-22 05:13:05.987577: Current learning rate: 0.00616 +2024-11-22 05:13:24.406177: train_loss -0.7851 +2024-11-22 05:13:24.408481: val_loss -0.7883 +2024-11-22 05:13:24.408580: Pseudo dice [0.8655] +2024-11-22 05:13:24.408670: Epoch time: 18.42 s +2024-11-22 05:13:25.261495: +2024-11-22 05:13:25.261717: Epoch 3328 +2024-11-22 05:13:25.261830: Current learning rate: 0.00616 +2024-11-22 05:13:43.572451: train_loss -0.7793 +2024-11-22 05:13:43.577434: val_loss -0.7389 +2024-11-22 05:13:43.577566: Pseudo dice [0.8479] +2024-11-22 05:13:43.577663: Epoch time: 18.31 s +2024-11-22 05:13:44.613404: +2024-11-22 05:13:44.613620: Epoch 3329 +2024-11-22 05:13:44.613742: Current learning rate: 0.00616 +2024-11-22 05:14:03.899260: train_loss -0.7621 +2024-11-22 05:14:03.904465: val_loss -0.7596 +2024-11-22 05:14:03.904595: Pseudo dice [0.8571] +2024-11-22 05:14:03.904680: Epoch time: 19.29 s +2024-11-22 05:14:04.773475: +2024-11-22 05:14:04.773708: Epoch 3330 +2024-11-22 05:14:04.773822: Current learning rate: 0.00616 +2024-11-22 05:14:23.904849: train_loss -0.7749 +2024-11-22 05:14:23.912438: val_loss -0.7448 +2024-11-22 05:14:23.912572: Pseudo dice [0.8511] +2024-11-22 05:14:23.912660: Epoch time: 19.13 s +2024-11-22 05:14:24.756839: +2024-11-22 05:14:24.757064: Epoch 3331 +2024-11-22 05:14:24.757182: Current learning rate: 0.00616 +2024-11-22 05:14:44.360057: train_loss -0.7748 +2024-11-22 05:14:44.366301: val_loss -0.7816 +2024-11-22 05:14:44.366436: Pseudo dice [0.8706] +2024-11-22 05:14:44.366534: Epoch time: 19.6 s +2024-11-22 05:14:45.224555: +2024-11-22 05:14:45.224754: Epoch 3332 +2024-11-22 05:14:45.224869: Current learning rate: 0.00616 +2024-11-22 05:15:05.164025: train_loss -0.7753 +2024-11-22 05:15:05.171396: val_loss -0.7659 +2024-11-22 05:15:05.171511: Pseudo dice [0.855] +2024-11-22 05:15:05.171590: Epoch time: 19.94 s +2024-11-22 05:15:06.187556: +2024-11-22 05:15:06.187789: Epoch 3333 +2024-11-22 05:15:06.187897: Current learning rate: 0.00616 +2024-11-22 05:15:25.486637: train_loss -0.7831 +2024-11-22 05:15:25.488904: val_loss -0.7904 +2024-11-22 05:15:25.488998: Pseudo dice [0.8481] +2024-11-22 05:15:25.489093: Epoch time: 19.3 s +2024-11-22 05:15:26.328348: +2024-11-22 05:15:26.328566: Epoch 3334 +2024-11-22 05:15:26.328699: Current learning rate: 0.00616 +2024-11-22 05:15:45.410291: train_loss -0.7724 +2024-11-22 05:15:45.416420: val_loss -0.7755 +2024-11-22 05:15:45.416538: Pseudo dice [0.8458] +2024-11-22 05:15:45.416622: Epoch time: 19.08 s +2024-11-22 05:15:46.854753: +2024-11-22 05:15:46.855033: Epoch 3335 +2024-11-22 05:15:46.855179: Current learning rate: 0.00615 +2024-11-22 05:16:06.208340: train_loss -0.7771 +2024-11-22 05:16:06.227359: val_loss -0.7917 +2024-11-22 05:16:06.227523: Pseudo dice [0.87] +2024-11-22 05:16:06.227613: Epoch time: 19.35 s +2024-11-22 05:16:06.227683: Yayy! New best EMA pseudo Dice: 0.8546 +2024-11-22 05:16:07.378994: +2024-11-22 05:16:07.379528: Epoch 3336 +2024-11-22 05:16:07.379645: Current learning rate: 0.00615 +2024-11-22 05:16:27.537326: train_loss -0.7726 +2024-11-22 05:16:27.546481: val_loss -0.7604 +2024-11-22 05:16:27.546613: Pseudo dice [0.8575] +2024-11-22 05:16:27.546691: Epoch time: 20.16 s +2024-11-22 05:16:27.546754: Yayy! New best EMA pseudo Dice: 0.8549 +2024-11-22 05:16:28.700211: +2024-11-22 05:16:28.700409: Epoch 3337 +2024-11-22 05:16:28.700520: Current learning rate: 0.00615 +2024-11-22 05:16:48.058861: train_loss -0.7773 +2024-11-22 05:16:48.066304: val_loss -0.7627 +2024-11-22 05:16:48.066442: Pseudo dice [0.8581] +2024-11-22 05:16:48.066530: Epoch time: 19.36 s +2024-11-22 05:16:48.066597: Yayy! New best EMA pseudo Dice: 0.8552 +2024-11-22 05:16:49.221756: +2024-11-22 05:16:49.221961: Epoch 3338 +2024-11-22 05:16:49.222075: Current learning rate: 0.00615 +2024-11-22 05:17:09.617895: train_loss -0.7831 +2024-11-22 05:17:09.624969: val_loss -0.7746 +2024-11-22 05:17:09.625121: Pseudo dice [0.8595] +2024-11-22 05:17:09.625219: Epoch time: 20.4 s +2024-11-22 05:17:09.625291: Yayy! New best EMA pseudo Dice: 0.8556 +2024-11-22 05:17:10.757195: +2024-11-22 05:17:10.757414: Epoch 3339 +2024-11-22 05:17:10.757526: Current learning rate: 0.00615 +2024-11-22 05:17:29.518275: train_loss -0.7689 +2024-11-22 05:17:29.520552: val_loss -0.7708 +2024-11-22 05:17:29.520697: Pseudo dice [0.8677] +2024-11-22 05:17:29.520783: Epoch time: 18.76 s +2024-11-22 05:17:29.520857: Yayy! New best EMA pseudo Dice: 0.8568 +2024-11-22 05:17:30.609513: +2024-11-22 05:17:30.609730: Epoch 3340 +2024-11-22 05:17:30.609838: Current learning rate: 0.00615 +2024-11-22 05:17:48.911712: train_loss -0.773 +2024-11-22 05:17:48.918332: val_loss -0.7678 +2024-11-22 05:17:48.918463: Pseudo dice [0.8428] +2024-11-22 05:17:48.918548: Epoch time: 18.3 s +2024-11-22 05:17:49.770554: +2024-11-22 05:17:49.770807: Epoch 3341 +2024-11-22 05:17:49.770918: Current learning rate: 0.00615 +2024-11-22 05:18:09.556414: train_loss -0.7781 +2024-11-22 05:18:09.563779: val_loss -0.7644 +2024-11-22 05:18:09.563921: Pseudo dice [0.8341] +2024-11-22 05:18:09.564007: Epoch time: 19.79 s +2024-11-22 05:18:10.424063: +2024-11-22 05:18:10.424258: Epoch 3342 +2024-11-22 05:18:10.424362: Current learning rate: 0.00615 +2024-11-22 05:18:29.823810: train_loss -0.79 +2024-11-22 05:18:29.826400: val_loss -0.7559 +2024-11-22 05:18:29.826501: Pseudo dice [0.8628] +2024-11-22 05:18:29.826589: Epoch time: 19.4 s +2024-11-22 05:18:30.681625: +2024-11-22 05:18:30.681809: Epoch 3343 +2024-11-22 05:18:30.681920: Current learning rate: 0.00614 +2024-11-22 05:18:48.890820: train_loss -0.7766 +2024-11-22 05:18:48.901483: val_loss -0.7901 +2024-11-22 05:18:48.901623: Pseudo dice [0.8552] +2024-11-22 05:18:48.901709: Epoch time: 18.21 s +2024-11-22 05:18:49.832018: +2024-11-22 05:18:49.832212: Epoch 3344 +2024-11-22 05:18:49.832327: Current learning rate: 0.00614 +2024-11-22 05:19:08.840159: train_loss -0.7857 +2024-11-22 05:19:08.847806: val_loss -0.7541 +2024-11-22 05:19:08.847928: Pseudo dice [0.8466] +2024-11-22 05:19:08.848014: Epoch time: 19.01 s +2024-11-22 05:19:10.117322: +2024-11-22 05:19:10.117514: Epoch 3345 +2024-11-22 05:19:10.117633: Current learning rate: 0.00614 +2024-11-22 05:19:30.207819: train_loss -0.7802 +2024-11-22 05:19:30.211333: val_loss -0.7513 +2024-11-22 05:19:30.211572: Pseudo dice [0.8665] +2024-11-22 05:19:30.211696: Epoch time: 20.09 s +2024-11-22 05:19:31.078200: +2024-11-22 05:19:31.078415: Epoch 3346 +2024-11-22 05:19:31.078532: Current learning rate: 0.00614 +2024-11-22 05:19:50.674363: train_loss -0.7829 +2024-11-22 05:19:50.681403: val_loss -0.77 +2024-11-22 05:19:50.681548: Pseudo dice [0.8526] +2024-11-22 05:19:50.681633: Epoch time: 19.6 s +2024-11-22 05:19:51.531875: +2024-11-22 05:19:51.532102: Epoch 3347 +2024-11-22 05:19:51.532209: Current learning rate: 0.00614 +2024-11-22 05:20:10.749862: train_loss -0.7836 +2024-11-22 05:20:10.757566: val_loss -0.7681 +2024-11-22 05:20:10.757703: Pseudo dice [0.8576] +2024-11-22 05:20:10.757796: Epoch time: 19.22 s +2024-11-22 05:20:11.627828: +2024-11-22 05:20:11.628044: Epoch 3348 +2024-11-22 05:20:11.628159: Current learning rate: 0.00614 +2024-11-22 05:20:30.647844: train_loss -0.7866 +2024-11-22 05:20:30.652580: val_loss -0.7422 +2024-11-22 05:20:30.652692: Pseudo dice [0.8277] +2024-11-22 05:20:30.652778: Epoch time: 19.02 s +2024-11-22 05:20:31.513687: +2024-11-22 05:20:31.513898: Epoch 3349 +2024-11-22 05:20:31.514008: Current learning rate: 0.00614 +2024-11-22 05:20:51.469660: train_loss -0.7783 +2024-11-22 05:20:51.472689: val_loss -0.7481 +2024-11-22 05:20:51.472810: Pseudo dice [0.8452] +2024-11-22 05:20:51.472901: Epoch time: 19.96 s +2024-11-22 05:20:52.577102: +2024-11-22 05:20:52.577315: Epoch 3350 +2024-11-22 05:20:52.577592: Current learning rate: 0.00614 +2024-11-22 05:21:10.083584: train_loss -0.7779 +2024-11-22 05:21:10.090524: val_loss -0.79 +2024-11-22 05:21:10.090704: Pseudo dice [0.8536] +2024-11-22 05:21:10.090799: Epoch time: 17.51 s +2024-11-22 05:21:10.949041: +2024-11-22 05:21:10.949262: Epoch 3351 +2024-11-22 05:21:10.949377: Current learning rate: 0.00614 +2024-11-22 05:21:30.196868: train_loss -0.7689 +2024-11-22 05:21:30.201864: val_loss -0.7549 +2024-11-22 05:21:30.202000: Pseudo dice [0.8437] +2024-11-22 05:21:30.202091: Epoch time: 19.25 s +2024-11-22 05:21:31.070661: +2024-11-22 05:21:31.070897: Epoch 3352 +2024-11-22 05:21:31.071008: Current learning rate: 0.00613 +2024-11-22 05:21:49.319128: train_loss -0.7747 +2024-11-22 05:21:49.326256: val_loss -0.7735 +2024-11-22 05:21:49.326395: Pseudo dice [0.8566] +2024-11-22 05:21:49.326483: Epoch time: 18.25 s +2024-11-22 05:21:50.227224: +2024-11-22 05:21:50.227432: Epoch 3353 +2024-11-22 05:21:50.227549: Current learning rate: 0.00613 +2024-11-22 05:22:08.503505: train_loss -0.7753 +2024-11-22 05:22:08.507681: val_loss -0.7713 +2024-11-22 05:22:08.507812: Pseudo dice [0.8644] +2024-11-22 05:22:08.507905: Epoch time: 18.28 s +2024-11-22 05:22:09.357330: +2024-11-22 05:22:09.357541: Epoch 3354 +2024-11-22 05:22:09.357650: Current learning rate: 0.00613 +2024-11-22 05:22:28.511730: train_loss -0.7866 +2024-11-22 05:22:28.519007: val_loss -0.7699 +2024-11-22 05:22:28.519140: Pseudo dice [0.8543] +2024-11-22 05:22:28.519224: Epoch time: 19.16 s +2024-11-22 05:22:29.367203: +2024-11-22 05:22:29.367402: Epoch 3355 +2024-11-22 05:22:29.367514: Current learning rate: 0.00613 +2024-11-22 05:22:47.838661: train_loss -0.7877 +2024-11-22 05:22:47.841326: val_loss -0.7523 +2024-11-22 05:22:47.841412: Pseudo dice [0.8625] +2024-11-22 05:22:47.841493: Epoch time: 18.47 s +2024-11-22 05:22:48.688948: +2024-11-22 05:22:48.689149: Epoch 3356 +2024-11-22 05:22:48.689264: Current learning rate: 0.00613 +2024-11-22 05:23:08.997066: train_loss -0.7777 +2024-11-22 05:23:09.007092: val_loss -0.7522 +2024-11-22 05:23:09.007253: Pseudo dice [0.8358] +2024-11-22 05:23:09.007356: Epoch time: 20.31 s +2024-11-22 05:23:09.862661: +2024-11-22 05:23:09.862876: Epoch 3357 +2024-11-22 05:23:09.862990: Current learning rate: 0.00613 +2024-11-22 05:23:28.876498: train_loss -0.7739 +2024-11-22 05:23:28.878690: val_loss -0.775 +2024-11-22 05:23:28.878781: Pseudo dice [0.8678] +2024-11-22 05:23:28.878859: Epoch time: 19.01 s +2024-11-22 05:23:29.725564: +2024-11-22 05:23:29.725796: Epoch 3358 +2024-11-22 05:23:29.725904: Current learning rate: 0.00613 +2024-11-22 05:23:48.342304: train_loss -0.7697 +2024-11-22 05:23:48.348389: val_loss -0.7587 +2024-11-22 05:23:48.348502: Pseudo dice [0.8363] +2024-11-22 05:23:48.348602: Epoch time: 18.62 s +2024-11-22 05:23:49.359017: +2024-11-22 05:23:49.359235: Epoch 3359 +2024-11-22 05:23:49.359352: Current learning rate: 0.00613 +2024-11-22 05:24:08.864954: train_loss -0.7708 +2024-11-22 05:24:08.873516: val_loss -0.7393 +2024-11-22 05:24:08.873646: Pseudo dice [0.8431] +2024-11-22 05:24:08.873793: Epoch time: 19.51 s +2024-11-22 05:24:09.836337: +2024-11-22 05:24:09.836572: Epoch 3360 +2024-11-22 05:24:09.836685: Current learning rate: 0.00612 +2024-11-22 05:24:28.744417: train_loss -0.7678 +2024-11-22 05:24:28.748831: val_loss -0.757 +2024-11-22 05:24:28.749245: Pseudo dice [0.8325] +2024-11-22 05:24:28.749435: Epoch time: 18.91 s +2024-11-22 05:24:29.619817: +2024-11-22 05:24:29.620097: Epoch 3361 +2024-11-22 05:24:29.620211: Current learning rate: 0.00612 +2024-11-22 05:24:49.150719: train_loss -0.7529 +2024-11-22 05:24:49.166155: val_loss -0.7424 +2024-11-22 05:24:49.166274: Pseudo dice [0.8337] +2024-11-22 05:24:49.166356: Epoch time: 19.53 s +2024-11-22 05:24:50.041748: +2024-11-22 05:24:50.041987: Epoch 3362 +2024-11-22 05:24:50.042112: Current learning rate: 0.00612 +2024-11-22 05:25:08.730462: train_loss -0.7521 +2024-11-22 05:25:08.739235: val_loss -0.7546 +2024-11-22 05:25:08.739347: Pseudo dice [0.8382] +2024-11-22 05:25:08.739427: Epoch time: 18.69 s +2024-11-22 05:25:09.730831: +2024-11-22 05:25:09.731078: Epoch 3363 +2024-11-22 05:25:09.731189: Current learning rate: 0.00612 +2024-11-22 05:25:29.034157: train_loss -0.7618 +2024-11-22 05:25:29.043013: val_loss -0.769 +2024-11-22 05:25:29.043151: Pseudo dice [0.8467] +2024-11-22 05:25:29.043244: Epoch time: 19.3 s +2024-11-22 05:25:30.200207: +2024-11-22 05:25:30.200461: Epoch 3364 +2024-11-22 05:25:30.200585: Current learning rate: 0.00612 +2024-11-22 05:25:49.155504: train_loss -0.7656 +2024-11-22 05:25:49.162550: val_loss -0.7883 +2024-11-22 05:25:49.162663: Pseudo dice [0.8543] +2024-11-22 05:25:49.162756: Epoch time: 18.96 s +2024-11-22 05:25:50.068466: +2024-11-22 05:25:50.068672: Epoch 3365 +2024-11-22 05:25:50.068788: Current learning rate: 0.00612 +2024-11-22 05:26:09.246921: train_loss -0.7635 +2024-11-22 05:26:09.249167: val_loss -0.7427 +2024-11-22 05:26:09.249279: Pseudo dice [0.8349] +2024-11-22 05:26:09.249359: Epoch time: 19.18 s +2024-11-22 05:26:10.098999: +2024-11-22 05:26:10.099192: Epoch 3366 +2024-11-22 05:26:10.099309: Current learning rate: 0.00612 +2024-11-22 05:26:29.148212: train_loss -0.7635 +2024-11-22 05:26:29.156516: val_loss -0.7556 +2024-11-22 05:26:29.156659: Pseudo dice [0.8261] +2024-11-22 05:26:29.156747: Epoch time: 19.05 s +2024-11-22 05:26:30.489382: +2024-11-22 05:26:30.489568: Epoch 3367 +2024-11-22 05:26:30.489681: Current learning rate: 0.00612 +2024-11-22 05:26:50.006942: train_loss -0.7809 +2024-11-22 05:26:50.016349: val_loss -0.7682 +2024-11-22 05:26:50.016486: Pseudo dice [0.8518] +2024-11-22 05:26:50.016576: Epoch time: 19.52 s +2024-11-22 05:26:51.092816: +2024-11-22 05:26:51.093029: Epoch 3368 +2024-11-22 05:26:51.093143: Current learning rate: 0.00612 +2024-11-22 05:27:10.031807: train_loss -0.7745 +2024-11-22 05:27:10.038719: val_loss -0.7695 +2024-11-22 05:27:10.038916: Pseudo dice [0.8541] +2024-11-22 05:27:10.039013: Epoch time: 18.94 s +2024-11-22 05:27:10.886322: +2024-11-22 05:27:10.886544: Epoch 3369 +2024-11-22 05:27:10.886658: Current learning rate: 0.00611 +2024-11-22 05:27:29.315476: train_loss -0.7704 +2024-11-22 05:27:29.319769: val_loss -0.7881 +2024-11-22 05:27:29.319898: Pseudo dice [0.847] +2024-11-22 05:27:29.319980: Epoch time: 18.43 s +2024-11-22 05:27:30.160425: +2024-11-22 05:27:30.160635: Epoch 3370 +2024-11-22 05:27:30.160743: Current learning rate: 0.00611 +2024-11-22 05:27:48.219957: train_loss -0.7801 +2024-11-22 05:27:48.222275: val_loss -0.7623 +2024-11-22 05:27:48.222382: Pseudo dice [0.8645] +2024-11-22 05:27:48.222470: Epoch time: 18.06 s +2024-11-22 05:27:49.075743: +2024-11-22 05:27:49.075975: Epoch 3371 +2024-11-22 05:27:49.076097: Current learning rate: 0.00611 +2024-11-22 05:28:08.161005: train_loss -0.7832 +2024-11-22 05:28:08.186756: val_loss -0.7643 +2024-11-22 05:28:08.186925: Pseudo dice [0.8639] +2024-11-22 05:28:08.187034: Epoch time: 19.09 s +2024-11-22 05:28:09.043540: +2024-11-22 05:28:09.043739: Epoch 3372 +2024-11-22 05:28:09.043856: Current learning rate: 0.00611 +2024-11-22 05:28:28.075229: train_loss -0.7693 +2024-11-22 05:28:28.081309: val_loss -0.7304 +2024-11-22 05:28:28.081440: Pseudo dice [0.8371] +2024-11-22 05:28:28.081541: Epoch time: 19.03 s +2024-11-22 05:28:28.950680: +2024-11-22 05:28:28.950893: Epoch 3373 +2024-11-22 05:28:28.951005: Current learning rate: 0.00611 +2024-11-22 05:28:48.409304: train_loss -0.771 +2024-11-22 05:28:48.415861: val_loss -0.7424 +2024-11-22 05:28:48.415983: Pseudo dice [0.8437] +2024-11-22 05:28:48.416079: Epoch time: 19.46 s +2024-11-22 05:28:49.311244: +2024-11-22 05:28:49.311472: Epoch 3374 +2024-11-22 05:28:49.311585: Current learning rate: 0.00611 +2024-11-22 05:29:08.088357: train_loss -0.7783 +2024-11-22 05:29:08.097071: val_loss -0.7788 +2024-11-22 05:29:08.097203: Pseudo dice [0.8555] +2024-11-22 05:29:08.097288: Epoch time: 18.78 s +2024-11-22 05:29:08.969606: +2024-11-22 05:29:08.969838: Epoch 3375 +2024-11-22 05:29:08.969957: Current learning rate: 0.00611 +2024-11-22 05:29:27.088233: train_loss -0.7788 +2024-11-22 05:29:27.095891: val_loss -0.763 +2024-11-22 05:29:27.096021: Pseudo dice [0.8394] +2024-11-22 05:29:27.096122: Epoch time: 18.12 s +2024-11-22 05:29:27.953015: +2024-11-22 05:29:27.953841: Epoch 3376 +2024-11-22 05:29:27.953999: Current learning rate: 0.00611 +2024-11-22 05:29:46.607208: train_loss -0.7793 +2024-11-22 05:29:46.616986: val_loss -0.7535 +2024-11-22 05:29:46.617231: Pseudo dice [0.8456] +2024-11-22 05:29:46.617322: Epoch time: 18.66 s +2024-11-22 05:29:47.677067: +2024-11-22 05:29:47.677272: Epoch 3377 +2024-11-22 05:29:47.677385: Current learning rate: 0.0061 +2024-11-22 05:30:07.277823: train_loss -0.778 +2024-11-22 05:30:07.280268: val_loss -0.7621 +2024-11-22 05:30:07.280357: Pseudo dice [0.8565] +2024-11-22 05:30:07.280434: Epoch time: 19.6 s +2024-11-22 05:30:08.128707: +2024-11-22 05:30:08.128911: Epoch 3378 +2024-11-22 05:30:08.129026: Current learning rate: 0.0061 +2024-11-22 05:30:28.186037: train_loss -0.7686 +2024-11-22 05:30:28.190258: val_loss -0.7434 +2024-11-22 05:30:28.190402: Pseudo dice [0.8422] +2024-11-22 05:30:28.190491: Epoch time: 20.06 s +2024-11-22 05:30:29.152065: +2024-11-22 05:30:29.152279: Epoch 3379 +2024-11-22 05:30:29.152394: Current learning rate: 0.0061 +2024-11-22 05:30:47.617402: train_loss -0.7861 +2024-11-22 05:30:47.621831: val_loss -0.7667 +2024-11-22 05:30:47.621961: Pseudo dice [0.8489] +2024-11-22 05:30:47.622045: Epoch time: 18.47 s +2024-11-22 05:30:48.549596: +2024-11-22 05:30:48.549799: Epoch 3380 +2024-11-22 05:30:48.549911: Current learning rate: 0.0061 +2024-11-22 05:31:07.240945: train_loss -0.7803 +2024-11-22 05:31:07.248966: val_loss -0.7614 +2024-11-22 05:31:07.249081: Pseudo dice [0.8623] +2024-11-22 05:31:07.249161: Epoch time: 18.69 s +2024-11-22 05:31:08.261609: +2024-11-22 05:31:08.261836: Epoch 3381 +2024-11-22 05:31:08.261953: Current learning rate: 0.0061 +2024-11-22 05:31:27.529649: train_loss -0.7848 +2024-11-22 05:31:27.535428: val_loss -0.7509 +2024-11-22 05:31:27.535561: Pseudo dice [0.8389] +2024-11-22 05:31:27.535652: Epoch time: 19.27 s +2024-11-22 05:31:28.423408: +2024-11-22 05:31:28.423625: Epoch 3382 +2024-11-22 05:31:28.423730: Current learning rate: 0.0061 +2024-11-22 05:31:47.374895: train_loss -0.7645 +2024-11-22 05:31:47.380416: val_loss -0.7621 +2024-11-22 05:31:47.380545: Pseudo dice [0.8392] +2024-11-22 05:31:47.380641: Epoch time: 18.95 s +2024-11-22 05:31:48.576807: +2024-11-22 05:31:48.577029: Epoch 3383 +2024-11-22 05:31:48.577151: Current learning rate: 0.0061 +2024-11-22 05:32:08.735700: train_loss -0.7662 +2024-11-22 05:32:08.741416: val_loss -0.771 +2024-11-22 05:32:08.741563: Pseudo dice [0.8629] +2024-11-22 05:32:08.741676: Epoch time: 20.16 s +2024-11-22 05:32:09.626739: +2024-11-22 05:32:09.626941: Epoch 3384 +2024-11-22 05:32:09.627054: Current learning rate: 0.0061 +2024-11-22 05:32:29.520357: train_loss -0.768 +2024-11-22 05:32:29.533569: val_loss -0.7622 +2024-11-22 05:32:29.533741: Pseudo dice [0.8426] +2024-11-22 05:32:29.533834: Epoch time: 19.89 s +2024-11-22 05:32:30.383795: +2024-11-22 05:32:30.384021: Epoch 3385 +2024-11-22 05:32:30.384145: Current learning rate: 0.00609 +2024-11-22 05:32:50.314756: train_loss -0.7616 +2024-11-22 05:32:50.316452: val_loss -0.7615 +2024-11-22 05:32:50.316543: Pseudo dice [0.844] +2024-11-22 05:32:50.316627: Epoch time: 19.93 s +2024-11-22 05:32:51.162037: +2024-11-22 05:32:51.162479: Epoch 3386 +2024-11-22 05:32:51.162591: Current learning rate: 0.00609 +2024-11-22 05:33:10.454915: train_loss -0.7714 +2024-11-22 05:33:10.462219: val_loss -0.7383 +2024-11-22 05:33:10.462352: Pseudo dice [0.8406] +2024-11-22 05:33:10.462442: Epoch time: 19.29 s +2024-11-22 05:33:11.332075: +2024-11-22 05:33:11.332285: Epoch 3387 +2024-11-22 05:33:11.332397: Current learning rate: 0.00609 +2024-11-22 05:33:29.868084: train_loss -0.7749 +2024-11-22 05:33:29.870581: val_loss -0.7665 +2024-11-22 05:33:29.870706: Pseudo dice [0.8397] +2024-11-22 05:33:29.870792: Epoch time: 18.54 s +2024-11-22 05:33:30.797885: +2024-11-22 05:33:30.798114: Epoch 3388 +2024-11-22 05:33:30.798226: Current learning rate: 0.00609 +2024-11-22 05:33:49.536838: train_loss -0.7757 +2024-11-22 05:33:49.544712: val_loss -0.768 +2024-11-22 05:33:49.544846: Pseudo dice [0.8337] +2024-11-22 05:33:49.544925: Epoch time: 18.74 s +2024-11-22 05:33:50.477413: +2024-11-22 05:33:50.477613: Epoch 3389 +2024-11-22 05:33:50.477727: Current learning rate: 0.00609 +2024-11-22 05:34:09.861161: train_loss -0.7753 +2024-11-22 05:34:09.867229: val_loss -0.7746 +2024-11-22 05:34:09.867371: Pseudo dice [0.8524] +2024-11-22 05:34:09.867455: Epoch time: 19.38 s +2024-11-22 05:34:10.732458: +2024-11-22 05:34:10.732678: Epoch 3390 +2024-11-22 05:34:10.732791: Current learning rate: 0.00609 +2024-11-22 05:34:30.518996: train_loss -0.7733 +2024-11-22 05:34:30.536431: val_loss -0.7751 +2024-11-22 05:34:30.536590: Pseudo dice [0.8433] +2024-11-22 05:34:30.536678: Epoch time: 19.79 s +2024-11-22 05:34:31.472648: +2024-11-22 05:34:31.472874: Epoch 3391 +2024-11-22 05:34:31.472984: Current learning rate: 0.00609 +2024-11-22 05:34:50.837609: train_loss -0.7717 +2024-11-22 05:34:50.843786: val_loss -0.758 +2024-11-22 05:34:50.843917: Pseudo dice [0.8485] +2024-11-22 05:34:50.843996: Epoch time: 19.37 s +2024-11-22 05:34:51.806627: +2024-11-22 05:34:51.806859: Epoch 3392 +2024-11-22 05:34:51.806973: Current learning rate: 0.00609 +2024-11-22 05:35:10.949147: train_loss -0.7846 +2024-11-22 05:35:10.951583: val_loss -0.7946 +2024-11-22 05:35:10.951694: Pseudo dice [0.8547] +2024-11-22 05:35:10.951790: Epoch time: 19.14 s +2024-11-22 05:35:11.809362: +2024-11-22 05:35:11.809594: Epoch 3393 +2024-11-22 05:35:11.809711: Current learning rate: 0.00609 +2024-11-22 05:35:30.652331: train_loss -0.7763 +2024-11-22 05:35:30.657891: val_loss -0.7797 +2024-11-22 05:35:30.658009: Pseudo dice [0.8564] +2024-11-22 05:35:30.658090: Epoch time: 18.84 s +2024-11-22 05:35:31.536924: +2024-11-22 05:35:31.537159: Epoch 3394 +2024-11-22 05:35:31.537274: Current learning rate: 0.00608 +2024-11-22 05:35:50.332808: train_loss -0.7861 +2024-11-22 05:35:50.334664: val_loss -0.779 +2024-11-22 05:35:50.334800: Pseudo dice [0.8494] +2024-11-22 05:35:50.334881: Epoch time: 18.8 s +2024-11-22 05:35:51.225937: +2024-11-22 05:35:51.226169: Epoch 3395 +2024-11-22 05:35:51.226278: Current learning rate: 0.00608 +2024-11-22 05:36:09.677262: train_loss -0.7726 +2024-11-22 05:36:09.684426: val_loss -0.7584 +2024-11-22 05:36:09.684558: Pseudo dice [0.8397] +2024-11-22 05:36:09.684643: Epoch time: 18.45 s +2024-11-22 05:36:10.631159: +2024-11-22 05:36:10.631365: Epoch 3396 +2024-11-22 05:36:10.631482: Current learning rate: 0.00608 +2024-11-22 05:36:28.617007: train_loss -0.7794 +2024-11-22 05:36:28.622211: val_loss -0.764 +2024-11-22 05:36:28.622349: Pseudo dice [0.8395] +2024-11-22 05:36:28.622432: Epoch time: 17.99 s +2024-11-22 05:36:29.593594: +2024-11-22 05:36:29.593801: Epoch 3397 +2024-11-22 05:36:29.593915: Current learning rate: 0.00608 +2024-11-22 05:36:48.891389: train_loss -0.779 +2024-11-22 05:36:48.897815: val_loss -0.7367 +2024-11-22 05:36:48.897942: Pseudo dice [0.8431] +2024-11-22 05:36:48.898032: Epoch time: 19.3 s +2024-11-22 05:36:49.767680: +2024-11-22 05:36:49.767906: Epoch 3398 +2024-11-22 05:36:49.768020: Current learning rate: 0.00608 +2024-11-22 05:37:10.215107: train_loss -0.7879 +2024-11-22 05:37:10.220968: val_loss -0.7261 +2024-11-22 05:37:10.221111: Pseudo dice [0.8399] +2024-11-22 05:37:10.221440: Epoch time: 20.45 s +2024-11-22 05:37:11.083171: +2024-11-22 05:37:11.083375: Epoch 3399 +2024-11-22 05:37:11.083494: Current learning rate: 0.00608 +2024-11-22 05:37:29.898624: train_loss -0.7788 +2024-11-22 05:37:29.902650: val_loss -0.7691 +2024-11-22 05:37:29.902783: Pseudo dice [0.848] +2024-11-22 05:37:29.902871: Epoch time: 18.82 s +2024-11-22 05:37:31.386756: +2024-11-22 05:37:31.386996: Epoch 3400 +2024-11-22 05:37:31.387111: Current learning rate: 0.00608 +2024-11-22 05:37:50.737305: train_loss -0.7795 +2024-11-22 05:37:50.739988: val_loss -0.7793 +2024-11-22 05:37:50.740095: Pseudo dice [0.8609] +2024-11-22 05:37:50.740186: Epoch time: 19.35 s +2024-11-22 05:37:51.588401: +2024-11-22 05:37:51.588623: Epoch 3401 +2024-11-22 05:37:51.588737: Current learning rate: 0.00608 +2024-11-22 05:38:10.865127: train_loss -0.7834 +2024-11-22 05:38:10.872003: val_loss -0.7667 +2024-11-22 05:38:10.872120: Pseudo dice [0.8587] +2024-11-22 05:38:10.872211: Epoch time: 19.28 s +2024-11-22 05:38:11.746170: +2024-11-22 05:38:11.746401: Epoch 3402 +2024-11-22 05:38:11.746518: Current learning rate: 0.00607 +2024-11-22 05:38:30.739315: train_loss -0.773 +2024-11-22 05:38:30.743893: val_loss -0.7674 +2024-11-22 05:38:30.744014: Pseudo dice [0.8591] +2024-11-22 05:38:30.744100: Epoch time: 18.99 s +2024-11-22 05:38:31.599702: +2024-11-22 05:38:31.599924: Epoch 3403 +2024-11-22 05:38:31.600042: Current learning rate: 0.00607 +2024-11-22 05:38:50.665911: train_loss -0.7803 +2024-11-22 05:38:50.668497: val_loss -0.7801 +2024-11-22 05:38:50.668622: Pseudo dice [0.8499] +2024-11-22 05:38:50.668712: Epoch time: 19.07 s +2024-11-22 05:38:51.522503: +2024-11-22 05:38:51.522705: Epoch 3404 +2024-11-22 05:38:51.522817: Current learning rate: 0.00607 +2024-11-22 05:39:09.435442: train_loss -0.7949 +2024-11-22 05:39:09.442406: val_loss -0.7822 +2024-11-22 05:39:09.442534: Pseudo dice [0.8537] +2024-11-22 05:39:09.442616: Epoch time: 17.91 s +2024-11-22 05:39:10.317725: +2024-11-22 05:39:10.317921: Epoch 3405 +2024-11-22 05:39:10.318034: Current learning rate: 0.00607 +2024-11-22 05:39:30.046149: train_loss -0.7827 +2024-11-22 05:39:30.049609: val_loss -0.7646 +2024-11-22 05:39:30.049750: Pseudo dice [0.8519] +2024-11-22 05:39:30.049842: Epoch time: 19.73 s +2024-11-22 05:39:31.137474: +2024-11-22 05:39:31.137683: Epoch 3406 +2024-11-22 05:39:31.137794: Current learning rate: 0.00607 +2024-11-22 05:39:50.948440: train_loss -0.7726 +2024-11-22 05:39:50.956591: val_loss -0.7706 +2024-11-22 05:39:50.956703: Pseudo dice [0.8491] +2024-11-22 05:39:50.956786: Epoch time: 19.81 s +2024-11-22 05:39:51.809141: +2024-11-22 05:39:51.809340: Epoch 3407 +2024-11-22 05:39:51.809456: Current learning rate: 0.00607 +2024-11-22 05:40:11.378428: train_loss -0.7776 +2024-11-22 05:40:11.380996: val_loss -0.7725 +2024-11-22 05:40:11.381107: Pseudo dice [0.8498] +2024-11-22 05:40:11.381189: Epoch time: 19.57 s +2024-11-22 05:40:12.367760: +2024-11-22 05:40:12.367986: Epoch 3408 +2024-11-22 05:40:12.368104: Current learning rate: 0.00607 +2024-11-22 05:40:32.351840: train_loss -0.7768 +2024-11-22 05:40:32.366224: val_loss -0.7353 +2024-11-22 05:40:32.366362: Pseudo dice [0.8325] +2024-11-22 05:40:32.366455: Epoch time: 19.98 s +2024-11-22 05:40:33.271330: +2024-11-22 05:40:33.271544: Epoch 3409 +2024-11-22 05:40:33.271654: Current learning rate: 0.00607 +2024-11-22 05:40:52.307463: train_loss -0.7702 +2024-11-22 05:40:52.315065: val_loss -0.7504 +2024-11-22 05:40:52.315211: Pseudo dice [0.8461] +2024-11-22 05:40:52.315294: Epoch time: 19.04 s +2024-11-22 05:40:53.174809: +2024-11-22 05:40:53.175049: Epoch 3410 +2024-11-22 05:40:53.175169: Current learning rate: 0.00607 +2024-11-22 05:41:11.033093: train_loss -0.7624 +2024-11-22 05:41:11.035632: val_loss -0.694 +2024-11-22 05:41:11.035719: Pseudo dice [0.8047] +2024-11-22 05:41:11.035793: Epoch time: 17.86 s +2024-11-22 05:41:12.273181: +2024-11-22 05:41:12.273403: Epoch 3411 +2024-11-22 05:41:12.273512: Current learning rate: 0.00606 +2024-11-22 05:41:31.101929: train_loss -0.7522 +2024-11-22 05:41:31.124632: val_loss -0.7496 +2024-11-22 05:41:31.124806: Pseudo dice [0.8448] +2024-11-22 05:41:31.124907: Epoch time: 18.83 s +2024-11-22 05:41:32.014101: +2024-11-22 05:41:32.014533: Epoch 3412 +2024-11-22 05:41:32.014645: Current learning rate: 0.00606 +2024-11-22 05:41:49.742543: train_loss -0.7828 +2024-11-22 05:41:49.744378: val_loss -0.7661 +2024-11-22 05:41:49.744475: Pseudo dice [0.8283] +2024-11-22 05:41:49.744558: Epoch time: 17.73 s +2024-11-22 05:41:50.586143: +2024-11-22 05:41:50.586390: Epoch 3413 +2024-11-22 05:41:50.586500: Current learning rate: 0.00606 +2024-11-22 05:42:11.037105: train_loss -0.7755 +2024-11-22 05:42:11.042136: val_loss -0.7603 +2024-11-22 05:42:11.042281: Pseudo dice [0.8519] +2024-11-22 05:42:11.042427: Epoch time: 20.45 s +2024-11-22 05:42:11.994650: +2024-11-22 05:42:11.994895: Epoch 3414 +2024-11-22 05:42:11.995016: Current learning rate: 0.00606 +2024-11-22 05:42:30.732825: train_loss -0.7719 +2024-11-22 05:42:30.739760: val_loss -0.78 +2024-11-22 05:42:30.739874: Pseudo dice [0.8514] +2024-11-22 05:42:30.739958: Epoch time: 18.74 s +2024-11-22 05:42:31.593248: +2024-11-22 05:42:31.593463: Epoch 3415 +2024-11-22 05:42:31.593577: Current learning rate: 0.00606 +2024-11-22 05:42:50.921549: train_loss -0.7773 +2024-11-22 05:42:50.929885: val_loss -0.7768 +2024-11-22 05:42:50.930011: Pseudo dice [0.8557] +2024-11-22 05:42:50.930107: Epoch time: 19.33 s +2024-11-22 05:42:51.915460: +2024-11-22 05:42:51.915670: Epoch 3416 +2024-11-22 05:42:51.915783: Current learning rate: 0.00606 +2024-11-22 05:43:10.379220: train_loss -0.7683 +2024-11-22 05:43:10.381327: val_loss -0.7621 +2024-11-22 05:43:10.381415: Pseudo dice [0.8596] +2024-11-22 05:43:10.381490: Epoch time: 18.46 s +2024-11-22 05:43:11.234494: +2024-11-22 05:43:11.234692: Epoch 3417 +2024-11-22 05:43:11.234809: Current learning rate: 0.00606 +2024-11-22 05:43:29.895071: train_loss -0.7733 +2024-11-22 05:43:29.896951: val_loss -0.7825 +2024-11-22 05:43:29.897080: Pseudo dice [0.8482] +2024-11-22 05:43:29.897161: Epoch time: 18.66 s +2024-11-22 05:43:30.835080: +2024-11-22 05:43:30.835280: Epoch 3418 +2024-11-22 05:43:30.835391: Current learning rate: 0.00606 +2024-11-22 05:43:48.166945: train_loss -0.7757 +2024-11-22 05:43:48.175102: val_loss -0.7788 +2024-11-22 05:43:48.175249: Pseudo dice [0.8584] +2024-11-22 05:43:48.175351: Epoch time: 17.33 s +2024-11-22 05:43:49.029762: +2024-11-22 05:43:49.030015: Epoch 3419 +2024-11-22 05:43:49.030133: Current learning rate: 0.00605 +2024-11-22 05:44:07.056305: train_loss -0.7831 +2024-11-22 05:44:07.064616: val_loss -0.7831 +2024-11-22 05:44:07.064754: Pseudo dice [0.8503] +2024-11-22 05:44:07.064845: Epoch time: 18.03 s +2024-11-22 05:44:07.911340: +2024-11-22 05:44:07.911572: Epoch 3420 +2024-11-22 05:44:07.911686: Current learning rate: 0.00605 +2024-11-22 05:44:26.214288: train_loss -0.7873 +2024-11-22 05:44:26.219796: val_loss -0.7724 +2024-11-22 05:44:26.219918: Pseudo dice [0.8544] +2024-11-22 05:44:26.219996: Epoch time: 18.3 s +2024-11-22 05:44:27.188809: +2024-11-22 05:44:27.188994: Epoch 3421 +2024-11-22 05:44:27.189108: Current learning rate: 0.00605 +2024-11-22 05:44:45.506843: train_loss -0.787 +2024-11-22 05:44:45.514680: val_loss -0.7697 +2024-11-22 05:44:45.514817: Pseudo dice [0.8497] +2024-11-22 05:44:45.514904: Epoch time: 18.32 s +2024-11-22 05:44:46.373197: +2024-11-22 05:44:46.373395: Epoch 3422 +2024-11-22 05:44:46.373511: Current learning rate: 0.00605 +2024-11-22 05:45:05.612300: train_loss -0.783 +2024-11-22 05:45:05.614574: val_loss -0.7871 +2024-11-22 05:45:05.614671: Pseudo dice [0.8525] +2024-11-22 05:45:05.614750: Epoch time: 19.24 s +2024-11-22 05:45:06.493595: +2024-11-22 05:45:06.493926: Epoch 3423 +2024-11-22 05:45:06.494041: Current learning rate: 0.00605 +2024-11-22 05:45:25.353802: train_loss -0.7806 +2024-11-22 05:45:25.355718: val_loss -0.7524 +2024-11-22 05:45:25.355811: Pseudo dice [0.8443] +2024-11-22 05:45:25.355891: Epoch time: 18.86 s +2024-11-22 05:45:26.202805: +2024-11-22 05:45:26.203040: Epoch 3424 +2024-11-22 05:45:26.226187: Current learning rate: 0.00605 +2024-11-22 05:45:45.423353: train_loss -0.7754 +2024-11-22 05:45:45.424903: val_loss -0.7648 +2024-11-22 05:45:45.424992: Pseudo dice [0.8558] +2024-11-22 05:45:45.425071: Epoch time: 19.22 s +2024-11-22 05:45:46.269762: +2024-11-22 05:45:46.270003: Epoch 3425 +2024-11-22 05:45:46.270121: Current learning rate: 0.00605 +2024-11-22 05:46:04.123761: train_loss -0.7829 +2024-11-22 05:46:04.141199: val_loss -0.7807 +2024-11-22 05:46:04.141365: Pseudo dice [0.8595] +2024-11-22 05:46:04.141469: Epoch time: 17.85 s +2024-11-22 05:46:05.003693: +2024-11-22 05:46:05.003896: Epoch 3426 +2024-11-22 05:46:05.004010: Current learning rate: 0.00605 +2024-11-22 05:46:23.723528: train_loss -0.7676 +2024-11-22 05:46:23.728456: val_loss -0.7589 +2024-11-22 05:46:23.728572: Pseudo dice [0.8437] +2024-11-22 05:46:23.728650: Epoch time: 18.72 s +2024-11-22 05:46:24.680349: +2024-11-22 05:46:24.680578: Epoch 3427 +2024-11-22 05:46:24.680688: Current learning rate: 0.00605 +2024-11-22 05:46:45.054716: train_loss -0.7806 +2024-11-22 05:46:45.060117: val_loss -0.7732 +2024-11-22 05:46:45.060246: Pseudo dice [0.8467] +2024-11-22 05:46:45.060330: Epoch time: 20.38 s +2024-11-22 05:46:46.230176: +2024-11-22 05:46:46.230414: Epoch 3428 +2024-11-22 05:46:46.230536: Current learning rate: 0.00604 +2024-11-22 05:47:04.846128: train_loss -0.7736 +2024-11-22 05:47:04.848500: val_loss -0.7654 +2024-11-22 05:47:04.848613: Pseudo dice [0.8484] +2024-11-22 05:47:04.848695: Epoch time: 18.62 s +2024-11-22 05:47:05.810141: +2024-11-22 05:47:05.810341: Epoch 3429 +2024-11-22 05:47:05.810454: Current learning rate: 0.00604 +2024-11-22 05:47:25.553179: train_loss -0.7766 +2024-11-22 05:47:25.561061: val_loss -0.7843 +2024-11-22 05:47:25.561203: Pseudo dice [0.8621] +2024-11-22 05:47:25.561304: Epoch time: 19.74 s +2024-11-22 05:47:26.455148: +2024-11-22 05:47:26.455340: Epoch 3430 +2024-11-22 05:47:26.455453: Current learning rate: 0.00604 +2024-11-22 05:47:44.961475: train_loss -0.7746 +2024-11-22 05:47:44.974454: val_loss -0.7485 +2024-11-22 05:47:44.974612: Pseudo dice [0.8476] +2024-11-22 05:47:44.974696: Epoch time: 18.51 s +2024-11-22 05:47:45.930565: +2024-11-22 05:47:45.930774: Epoch 3431 +2024-11-22 05:47:45.930900: Current learning rate: 0.00604 +2024-11-22 05:48:06.275399: train_loss -0.7787 +2024-11-22 05:48:06.277272: val_loss -0.775 +2024-11-22 05:48:06.277365: Pseudo dice [0.855] +2024-11-22 05:48:06.277447: Epoch time: 20.35 s +2024-11-22 05:48:07.126587: +2024-11-22 05:48:07.126794: Epoch 3432 +2024-11-22 05:48:07.126913: Current learning rate: 0.00604 +2024-11-22 05:48:26.288092: train_loss -0.7738 +2024-11-22 05:48:26.292731: val_loss -0.7771 +2024-11-22 05:48:26.292854: Pseudo dice [0.8698] +2024-11-22 05:48:26.292934: Epoch time: 19.16 s +2024-11-22 05:48:27.599554: +2024-11-22 05:48:27.599768: Epoch 3433 +2024-11-22 05:48:27.599878: Current learning rate: 0.00604 +2024-11-22 05:48:46.922205: train_loss -0.7797 +2024-11-22 05:48:46.930986: val_loss -0.7588 +2024-11-22 05:48:46.931119: Pseudo dice [0.8372] +2024-11-22 05:48:46.931216: Epoch time: 19.32 s +2024-11-22 05:48:47.796890: +2024-11-22 05:48:47.797101: Epoch 3434 +2024-11-22 05:48:47.797211: Current learning rate: 0.00604 +2024-11-22 05:49:06.580026: train_loss -0.7831 +2024-11-22 05:49:06.584195: val_loss -0.7819 +2024-11-22 05:49:06.584305: Pseudo dice [0.8502] +2024-11-22 05:49:06.584390: Epoch time: 18.78 s +2024-11-22 05:49:07.591804: +2024-11-22 05:49:07.592023: Epoch 3435 +2024-11-22 05:49:07.592136: Current learning rate: 0.00604 +2024-11-22 05:49:26.555896: train_loss -0.7862 +2024-11-22 05:49:26.561457: val_loss -0.7924 +2024-11-22 05:49:26.561573: Pseudo dice [0.865] +2024-11-22 05:49:26.561658: Epoch time: 18.96 s +2024-11-22 05:49:27.533929: +2024-11-22 05:49:27.534165: Epoch 3436 +2024-11-22 05:49:27.534279: Current learning rate: 0.00603 +2024-11-22 05:49:46.076833: train_loss -0.7764 +2024-11-22 05:49:46.082529: val_loss -0.7685 +2024-11-22 05:49:46.082638: Pseudo dice [0.8462] +2024-11-22 05:49:46.082730: Epoch time: 18.54 s +2024-11-22 05:49:47.131042: +2024-11-22 05:49:47.131323: Epoch 3437 +2024-11-22 05:49:47.131441: Current learning rate: 0.00603 +2024-11-22 05:50:06.176541: train_loss -0.7863 +2024-11-22 05:50:06.181851: val_loss -0.7663 +2024-11-22 05:50:06.181984: Pseudo dice [0.8492] +2024-11-22 05:50:06.182077: Epoch time: 19.05 s +2024-11-22 05:50:07.062602: +2024-11-22 05:50:07.062834: Epoch 3438 +2024-11-22 05:50:07.062945: Current learning rate: 0.00603 +2024-11-22 05:50:26.336849: train_loss -0.7777 +2024-11-22 05:50:26.338716: val_loss -0.7496 +2024-11-22 05:50:26.338798: Pseudo dice [0.8516] +2024-11-22 05:50:26.338874: Epoch time: 19.28 s +2024-11-22 05:50:27.184777: +2024-11-22 05:50:27.184974: Epoch 3439 +2024-11-22 05:50:27.185101: Current learning rate: 0.00603 +2024-11-22 05:50:45.982484: train_loss -0.7774 +2024-11-22 05:50:46.002159: val_loss -0.7639 +2024-11-22 05:50:46.002288: Pseudo dice [0.8405] +2024-11-22 05:50:46.002376: Epoch time: 18.8 s +2024-11-22 05:50:46.983030: +2024-11-22 05:50:46.983240: Epoch 3440 +2024-11-22 05:50:46.983351: Current learning rate: 0.00603 +2024-11-22 05:51:06.128170: train_loss -0.7839 +2024-11-22 05:51:06.133641: val_loss -0.7595 +2024-11-22 05:51:06.133753: Pseudo dice [0.8443] +2024-11-22 05:51:06.133898: Epoch time: 19.15 s +2024-11-22 05:51:06.987009: +2024-11-22 05:51:06.987234: Epoch 3441 +2024-11-22 05:51:06.987347: Current learning rate: 0.00603 +2024-11-22 05:51:28.077737: train_loss -0.7774 +2024-11-22 05:51:28.086648: val_loss -0.7664 +2024-11-22 05:51:28.086786: Pseudo dice [0.8518] +2024-11-22 05:51:28.086868: Epoch time: 21.09 s +2024-11-22 05:51:29.022851: +2024-11-22 05:51:29.023051: Epoch 3442 +2024-11-22 05:51:29.023167: Current learning rate: 0.00603 +2024-11-22 05:51:46.651048: train_loss -0.7756 +2024-11-22 05:51:46.657402: val_loss -0.7645 +2024-11-22 05:51:46.657529: Pseudo dice [0.8463] +2024-11-22 05:51:46.657616: Epoch time: 17.63 s +2024-11-22 05:51:47.555560: +2024-11-22 05:51:47.555778: Epoch 3443 +2024-11-22 05:51:47.555900: Current learning rate: 0.00603 +2024-11-22 05:52:07.043571: train_loss -0.7713 +2024-11-22 05:52:07.058303: val_loss -0.7798 +2024-11-22 05:52:07.058444: Pseudo dice [0.8535] +2024-11-22 05:52:07.058538: Epoch time: 19.49 s +2024-11-22 05:52:07.936754: +2024-11-22 05:52:07.936982: Epoch 3444 +2024-11-22 05:52:07.937100: Current learning rate: 0.00602 +2024-11-22 05:52:28.127157: train_loss -0.776 +2024-11-22 05:52:28.129691: val_loss -0.7839 +2024-11-22 05:52:28.129811: Pseudo dice [0.8515] +2024-11-22 05:52:28.129894: Epoch time: 20.19 s +2024-11-22 05:52:28.976529: +2024-11-22 05:52:28.976775: Epoch 3445 +2024-11-22 05:52:28.976897: Current learning rate: 0.00602 +2024-11-22 05:52:48.134308: train_loss -0.7891 +2024-11-22 05:52:48.140783: val_loss -0.7616 +2024-11-22 05:52:48.140955: Pseudo dice [0.8515] +2024-11-22 05:52:48.141037: Epoch time: 19.16 s +2024-11-22 05:52:49.001483: +2024-11-22 05:52:49.001698: Epoch 3446 +2024-11-22 05:52:49.001805: Current learning rate: 0.00602 +2024-11-22 05:53:08.242926: train_loss -0.7798 +2024-11-22 05:53:08.245539: val_loss -0.7377 +2024-11-22 05:53:08.245634: Pseudo dice [0.8589] +2024-11-22 05:53:08.245719: Epoch time: 19.24 s +2024-11-22 05:53:09.096929: +2024-11-22 05:53:09.097122: Epoch 3447 +2024-11-22 05:53:09.097232: Current learning rate: 0.00602 +2024-11-22 05:53:28.016650: train_loss -0.7855 +2024-11-22 05:53:28.031512: val_loss -0.7807 +2024-11-22 05:53:28.031675: Pseudo dice [0.847] +2024-11-22 05:53:28.031799: Epoch time: 18.92 s +2024-11-22 05:53:28.964507: +2024-11-22 05:53:28.964720: Epoch 3448 +2024-11-22 05:53:28.964833: Current learning rate: 0.00602 +2024-11-22 05:53:47.088237: train_loss -0.7789 +2024-11-22 05:53:47.090687: val_loss -0.7898 +2024-11-22 05:53:47.090780: Pseudo dice [0.855] +2024-11-22 05:53:47.090861: Epoch time: 18.12 s +2024-11-22 05:53:47.941359: +2024-11-22 05:53:47.941579: Epoch 3449 +2024-11-22 05:53:47.941690: Current learning rate: 0.00602 +2024-11-22 05:54:06.754095: train_loss -0.7783 +2024-11-22 05:54:06.763104: val_loss -0.7808 +2024-11-22 05:54:06.763262: Pseudo dice [0.8567] +2024-11-22 05:54:06.763345: Epoch time: 18.81 s +2024-11-22 05:54:08.018738: +2024-11-22 05:54:08.018946: Epoch 3450 +2024-11-22 05:54:08.019055: Current learning rate: 0.00602 +2024-11-22 05:54:26.542960: train_loss -0.7953 +2024-11-22 05:54:26.545841: val_loss -0.7777 +2024-11-22 05:54:26.545964: Pseudo dice [0.8602] +2024-11-22 05:54:26.546050: Epoch time: 18.53 s +2024-11-22 05:54:27.655413: +2024-11-22 05:54:27.655609: Epoch 3451 +2024-11-22 05:54:27.655721: Current learning rate: 0.00602 +2024-11-22 05:54:47.165719: train_loss -0.7744 +2024-11-22 05:54:47.175701: val_loss -0.7258 +2024-11-22 05:54:47.175830: Pseudo dice [0.8555] +2024-11-22 05:54:47.175919: Epoch time: 19.51 s +2024-11-22 05:54:48.162866: +2024-11-22 05:54:48.163081: Epoch 3452 +2024-11-22 05:54:48.163193: Current learning rate: 0.00602 +2024-11-22 05:55:07.561559: train_loss -0.7831 +2024-11-22 05:55:07.579830: val_loss -0.7729 +2024-11-22 05:55:07.579958: Pseudo dice [0.8593] +2024-11-22 05:55:07.580039: Epoch time: 19.4 s +2024-11-22 05:55:08.429053: +2024-11-22 05:55:08.429276: Epoch 3453 +2024-11-22 05:55:08.429392: Current learning rate: 0.00601 +2024-11-22 05:55:28.451329: train_loss -0.7843 +2024-11-22 05:55:28.453691: val_loss -0.7823 +2024-11-22 05:55:28.453783: Pseudo dice [0.8528] +2024-11-22 05:55:28.454054: Epoch time: 20.02 s +2024-11-22 05:55:29.300405: +2024-11-22 05:55:29.300600: Epoch 3454 +2024-11-22 05:55:29.300717: Current learning rate: 0.00601 +2024-11-22 05:55:48.125834: train_loss -0.7913 +2024-11-22 05:55:48.131862: val_loss -0.7536 +2024-11-22 05:55:48.131999: Pseudo dice [0.8457] +2024-11-22 05:55:48.132108: Epoch time: 18.83 s +2024-11-22 05:55:49.374778: +2024-11-22 05:55:49.374973: Epoch 3455 +2024-11-22 05:55:49.375086: Current learning rate: 0.00601 +2024-11-22 05:56:06.894640: train_loss -0.7906 +2024-11-22 05:56:06.900775: val_loss -0.7498 +2024-11-22 05:56:06.900903: Pseudo dice [0.8451] +2024-11-22 05:56:06.900992: Epoch time: 17.52 s +2024-11-22 05:56:07.757586: +2024-11-22 05:56:07.757844: Epoch 3456 +2024-11-22 05:56:07.757955: Current learning rate: 0.00601 +2024-11-22 05:56:27.855291: train_loss -0.7855 +2024-11-22 05:56:27.860544: val_loss -0.7687 +2024-11-22 05:56:27.860673: Pseudo dice [0.8627] +2024-11-22 05:56:27.860752: Epoch time: 20.1 s +2024-11-22 05:56:28.716713: +2024-11-22 05:56:28.716946: Epoch 3457 +2024-11-22 05:56:28.717066: Current learning rate: 0.00601 +2024-11-22 05:56:48.525581: train_loss -0.7917 +2024-11-22 05:56:48.527671: val_loss -0.7652 +2024-11-22 05:56:48.527766: Pseudo dice [0.846] +2024-11-22 05:56:48.527846: Epoch time: 19.81 s +2024-11-22 05:56:49.372768: +2024-11-22 05:56:49.373001: Epoch 3458 +2024-11-22 05:56:49.373128: Current learning rate: 0.00601 +2024-11-22 05:57:08.925956: train_loss -0.7832 +2024-11-22 05:57:08.932867: val_loss -0.7722 +2024-11-22 05:57:08.932985: Pseudo dice [0.8519] +2024-11-22 05:57:08.933087: Epoch time: 19.55 s +2024-11-22 05:57:09.828971: +2024-11-22 05:57:09.829174: Epoch 3459 +2024-11-22 05:57:09.829288: Current learning rate: 0.00601 +2024-11-22 05:57:29.364590: train_loss -0.7874 +2024-11-22 05:57:29.368174: val_loss -0.7775 +2024-11-22 05:57:29.368355: Pseudo dice [0.8541] +2024-11-22 05:57:29.368437: Epoch time: 19.54 s +2024-11-22 05:57:30.226378: +2024-11-22 05:57:30.226572: Epoch 3460 +2024-11-22 05:57:30.226683: Current learning rate: 0.00601 +2024-11-22 05:57:49.372549: train_loss -0.7887 +2024-11-22 05:57:49.379423: val_loss -0.7514 +2024-11-22 05:57:49.379535: Pseudo dice [0.8457] +2024-11-22 05:57:49.379621: Epoch time: 19.15 s +2024-11-22 05:57:50.350839: +2024-11-22 05:57:50.351047: Epoch 3461 +2024-11-22 05:57:50.351171: Current learning rate: 0.006 +2024-11-22 05:58:08.576369: train_loss -0.7837 +2024-11-22 05:58:08.581447: val_loss -0.7558 +2024-11-22 05:58:08.581558: Pseudo dice [0.8562] +2024-11-22 05:58:08.581643: Epoch time: 18.23 s +2024-11-22 05:58:09.685816: +2024-11-22 05:58:09.686028: Epoch 3462 +2024-11-22 05:58:09.686145: Current learning rate: 0.006 +2024-11-22 05:58:27.601395: train_loss -0.7817 +2024-11-22 05:58:27.605051: val_loss -0.7567 +2024-11-22 05:58:27.605196: Pseudo dice [0.8541] +2024-11-22 05:58:27.605288: Epoch time: 17.92 s +2024-11-22 05:58:28.571943: +2024-11-22 05:58:28.572181: Epoch 3463 +2024-11-22 05:58:28.572296: Current learning rate: 0.006 +2024-11-22 05:58:47.422412: train_loss -0.7867 +2024-11-22 05:58:47.424659: val_loss -0.7498 +2024-11-22 05:58:47.424750: Pseudo dice [0.8441] +2024-11-22 05:58:47.424831: Epoch time: 18.85 s +2024-11-22 05:58:48.614344: +2024-11-22 05:58:48.614607: Epoch 3464 +2024-11-22 05:58:48.614725: Current learning rate: 0.006 +2024-11-22 05:59:07.543467: train_loss -0.7846 +2024-11-22 05:59:07.550475: val_loss -0.77 +2024-11-22 05:59:07.550594: Pseudo dice [0.8394] +2024-11-22 05:59:07.550674: Epoch time: 18.93 s +2024-11-22 05:59:08.437091: +2024-11-22 05:59:08.437293: Epoch 3465 +2024-11-22 05:59:08.437411: Current learning rate: 0.006 +2024-11-22 05:59:26.880224: train_loss -0.786 +2024-11-22 05:59:26.889376: val_loss -0.787 +2024-11-22 05:59:26.889498: Pseudo dice [0.8543] +2024-11-22 05:59:26.889586: Epoch time: 18.44 s +2024-11-22 05:59:27.758893: +2024-11-22 05:59:27.759117: Epoch 3466 +2024-11-22 05:59:27.759235: Current learning rate: 0.006 +2024-11-22 05:59:47.197754: train_loss -0.794 +2024-11-22 05:59:47.206391: val_loss -0.7613 +2024-11-22 05:59:47.206537: Pseudo dice [0.8572] +2024-11-22 05:59:47.206617: Epoch time: 19.44 s +2024-11-22 05:59:48.086278: +2024-11-22 05:59:48.086499: Epoch 3467 +2024-11-22 05:59:48.086614: Current learning rate: 0.006 +2024-11-22 06:00:07.962427: train_loss -0.791 +2024-11-22 06:00:07.969566: val_loss -0.7842 +2024-11-22 06:00:07.969692: Pseudo dice [0.8556] +2024-11-22 06:00:07.969824: Epoch time: 19.88 s +2024-11-22 06:00:08.819745: +2024-11-22 06:00:08.819964: Epoch 3468 +2024-11-22 06:00:08.820080: Current learning rate: 0.006 +2024-11-22 06:00:26.186121: train_loss -0.7842 +2024-11-22 06:00:26.195651: val_loss -0.7652 +2024-11-22 06:00:26.195772: Pseudo dice [0.8557] +2024-11-22 06:00:26.195868: Epoch time: 17.37 s +2024-11-22 06:00:27.100919: +2024-11-22 06:00:27.101140: Epoch 3469 +2024-11-22 06:00:27.101256: Current learning rate: 0.006 +2024-11-22 06:00:45.801537: train_loss -0.7801 +2024-11-22 06:00:45.806770: val_loss -0.7591 +2024-11-22 06:00:45.806888: Pseudo dice [0.8398] +2024-11-22 06:00:45.806973: Epoch time: 18.7 s +2024-11-22 06:00:46.704223: +2024-11-22 06:00:46.704440: Epoch 3470 +2024-11-22 06:00:46.704555: Current learning rate: 0.00599 +2024-11-22 06:01:06.386483: train_loss -0.7731 +2024-11-22 06:01:06.394446: val_loss -0.7808 +2024-11-22 06:01:06.394579: Pseudo dice [0.8466] +2024-11-22 06:01:06.394670: Epoch time: 19.68 s +2024-11-22 06:01:07.247999: +2024-11-22 06:01:07.248213: Epoch 3471 +2024-11-22 06:01:07.248334: Current learning rate: 0.00599 +2024-11-22 06:01:25.409843: train_loss -0.7725 +2024-11-22 06:01:25.416294: val_loss -0.7771 +2024-11-22 06:01:25.416428: Pseudo dice [0.857] +2024-11-22 06:01:25.416513: Epoch time: 18.16 s +2024-11-22 06:01:26.280573: +2024-11-22 06:01:26.280781: Epoch 3472 +2024-11-22 06:01:26.280892: Current learning rate: 0.00599 +2024-11-22 06:01:44.519990: train_loss -0.7847 +2024-11-22 06:01:44.525873: val_loss -0.766 +2024-11-22 06:01:44.526007: Pseudo dice [0.841] +2024-11-22 06:01:44.526099: Epoch time: 18.24 s +2024-11-22 06:01:45.379154: +2024-11-22 06:01:45.379401: Epoch 3473 +2024-11-22 06:01:45.379535: Current learning rate: 0.00599 +2024-11-22 06:02:04.107659: train_loss -0.7792 +2024-11-22 06:02:04.111387: val_loss -0.7533 +2024-11-22 06:02:04.111522: Pseudo dice [0.851] +2024-11-22 06:02:04.111612: Epoch time: 18.73 s +2024-11-22 06:02:04.963784: +2024-11-22 06:02:04.963992: Epoch 3474 +2024-11-22 06:02:04.964107: Current learning rate: 0.00599 +2024-11-22 06:02:24.346891: train_loss -0.7768 +2024-11-22 06:02:24.353814: val_loss -0.7871 +2024-11-22 06:02:24.353925: Pseudo dice [0.8517] +2024-11-22 06:02:24.354006: Epoch time: 19.38 s +2024-11-22 06:02:25.469475: +2024-11-22 06:02:25.469998: Epoch 3475 +2024-11-22 06:02:25.470116: Current learning rate: 0.00599 +2024-11-22 06:02:44.468669: train_loss -0.7793 +2024-11-22 06:02:44.475281: val_loss -0.7795 +2024-11-22 06:02:44.475415: Pseudo dice [0.8604] +2024-11-22 06:02:44.475498: Epoch time: 19.0 s +2024-11-22 06:02:45.327315: +2024-11-22 06:02:45.327538: Epoch 3476 +2024-11-22 06:02:45.327657: Current learning rate: 0.00599 +2024-11-22 06:03:04.064967: train_loss -0.7822 +2024-11-22 06:03:04.073322: val_loss -0.7674 +2024-11-22 06:03:04.073462: Pseudo dice [0.847] +2024-11-22 06:03:04.073555: Epoch time: 18.74 s +2024-11-22 06:03:05.493950: +2024-11-22 06:03:05.494155: Epoch 3477 +2024-11-22 06:03:05.494266: Current learning rate: 0.00599 +2024-11-22 06:03:24.642041: train_loss -0.7854 +2024-11-22 06:03:24.651026: val_loss -0.755 +2024-11-22 06:03:24.651183: Pseudo dice [0.8466] +2024-11-22 06:03:24.651429: Epoch time: 19.15 s +2024-11-22 06:03:25.497653: +2024-11-22 06:03:25.497885: Epoch 3478 +2024-11-22 06:03:25.498000: Current learning rate: 0.00598 +2024-11-22 06:03:44.535114: train_loss -0.7789 +2024-11-22 06:03:44.539500: val_loss -0.7809 +2024-11-22 06:03:44.539635: Pseudo dice [0.8482] +2024-11-22 06:03:44.539723: Epoch time: 19.04 s +2024-11-22 06:03:45.412795: +2024-11-22 06:03:45.413068: Epoch 3479 +2024-11-22 06:03:45.413184: Current learning rate: 0.00598 +2024-11-22 06:04:05.352796: train_loss -0.774 +2024-11-22 06:04:05.360926: val_loss -0.76 +2024-11-22 06:04:05.361067: Pseudo dice [0.8482] +2024-11-22 06:04:05.361757: Epoch time: 19.94 s +2024-11-22 06:04:06.393668: +2024-11-22 06:04:06.393880: Epoch 3480 +2024-11-22 06:04:06.393991: Current learning rate: 0.00598 +2024-11-22 06:04:25.673005: train_loss -0.7831 +2024-11-22 06:04:25.679411: val_loss -0.7608 +2024-11-22 06:04:25.679543: Pseudo dice [0.8484] +2024-11-22 06:04:25.679625: Epoch time: 19.28 s +2024-11-22 06:04:26.562345: +2024-11-22 06:04:26.562558: Epoch 3481 +2024-11-22 06:04:26.562675: Current learning rate: 0.00598 +2024-11-22 06:04:45.823894: train_loss -0.7714 +2024-11-22 06:04:45.829477: val_loss -0.7684 +2024-11-22 06:04:45.829620: Pseudo dice [0.8401] +2024-11-22 06:04:45.829708: Epoch time: 19.26 s +2024-11-22 06:04:46.690009: +2024-11-22 06:04:46.690228: Epoch 3482 +2024-11-22 06:04:46.690342: Current learning rate: 0.00598 +2024-11-22 06:05:05.308508: train_loss -0.7863 +2024-11-22 06:05:05.315096: val_loss -0.7649 +2024-11-22 06:05:05.315214: Pseudo dice [0.864] +2024-11-22 06:05:05.315293: Epoch time: 18.62 s +2024-11-22 06:05:06.207053: +2024-11-22 06:05:06.207281: Epoch 3483 +2024-11-22 06:05:06.207393: Current learning rate: 0.00598 +2024-11-22 06:05:24.509602: train_loss -0.7743 +2024-11-22 06:05:24.532371: val_loss -0.7816 +2024-11-22 06:05:24.532541: Pseudo dice [0.8601] +2024-11-22 06:05:24.532640: Epoch time: 18.3 s +2024-11-22 06:05:25.581427: +2024-11-22 06:05:25.581644: Epoch 3484 +2024-11-22 06:05:25.581756: Current learning rate: 0.00598 +2024-11-22 06:05:45.105713: train_loss -0.7777 +2024-11-22 06:05:45.114037: val_loss -0.7656 +2024-11-22 06:05:45.114151: Pseudo dice [0.8435] +2024-11-22 06:05:45.114233: Epoch time: 19.53 s +2024-11-22 06:05:45.967664: +2024-11-22 06:05:45.967865: Epoch 3485 +2024-11-22 06:05:45.967975: Current learning rate: 0.00598 +2024-11-22 06:06:05.300500: train_loss -0.7823 +2024-11-22 06:06:05.308153: val_loss -0.7782 +2024-11-22 06:06:05.308266: Pseudo dice [0.8534] +2024-11-22 06:06:05.308352: Epoch time: 19.33 s +2024-11-22 06:06:06.355210: +2024-11-22 06:06:06.355410: Epoch 3486 +2024-11-22 06:06:06.355522: Current learning rate: 0.00597 +2024-11-22 06:06:24.745896: train_loss -0.7817 +2024-11-22 06:06:24.747923: val_loss -0.7659 +2024-11-22 06:06:24.748017: Pseudo dice [0.8265] +2024-11-22 06:06:24.748104: Epoch time: 18.39 s +2024-11-22 06:06:25.599801: +2024-11-22 06:06:25.600001: Epoch 3487 +2024-11-22 06:06:25.600112: Current learning rate: 0.00597 +2024-11-22 06:06:46.285318: train_loss -0.7547 +2024-11-22 06:06:46.303998: val_loss -0.7578 +2024-11-22 06:06:46.304149: Pseudo dice [0.8374] +2024-11-22 06:06:46.304519: Epoch time: 20.69 s +2024-11-22 06:06:47.215928: +2024-11-22 06:06:47.216158: Epoch 3488 +2024-11-22 06:06:47.216272: Current learning rate: 0.00597 +2024-11-22 06:07:06.222926: train_loss -0.763 +2024-11-22 06:07:06.229370: val_loss -0.7683 +2024-11-22 06:07:06.229481: Pseudo dice [0.84] +2024-11-22 06:07:06.229569: Epoch time: 19.01 s +2024-11-22 06:07:07.208143: +2024-11-22 06:07:07.208363: Epoch 3489 +2024-11-22 06:07:07.208472: Current learning rate: 0.00597 +2024-11-22 06:07:25.825793: train_loss -0.7699 +2024-11-22 06:07:25.828261: val_loss -0.7691 +2024-11-22 06:07:25.828359: Pseudo dice [0.8407] +2024-11-22 06:07:25.828450: Epoch time: 18.62 s +2024-11-22 06:07:26.674889: +2024-11-22 06:07:26.675130: Epoch 3490 +2024-11-22 06:07:26.675242: Current learning rate: 0.00597 +2024-11-22 06:07:46.035114: train_loss -0.7658 +2024-11-22 06:07:46.037178: val_loss -0.7576 +2024-11-22 06:07:46.037296: Pseudo dice [0.8299] +2024-11-22 06:07:46.037399: Epoch time: 19.36 s +2024-11-22 06:07:46.889243: +2024-11-22 06:07:46.889469: Epoch 3491 +2024-11-22 06:07:46.889584: Current learning rate: 0.00597 +2024-11-22 06:08:05.836124: train_loss -0.7634 +2024-11-22 06:08:05.838117: val_loss -0.7788 +2024-11-22 06:08:05.838238: Pseudo dice [0.8544] +2024-11-22 06:08:05.838322: Epoch time: 18.95 s +2024-11-22 06:08:06.951118: +2024-11-22 06:08:06.951323: Epoch 3492 +2024-11-22 06:08:06.951436: Current learning rate: 0.00597 +2024-11-22 06:08:26.144565: train_loss -0.7701 +2024-11-22 06:08:26.151843: val_loss -0.7559 +2024-11-22 06:08:26.151953: Pseudo dice [0.8452] +2024-11-22 06:08:26.152035: Epoch time: 19.19 s +2024-11-22 06:08:27.035924: +2024-11-22 06:08:27.036146: Epoch 3493 +2024-11-22 06:08:27.036263: Current learning rate: 0.00597 +2024-11-22 06:08:45.720197: train_loss -0.784 +2024-11-22 06:08:45.722221: val_loss -0.7919 +2024-11-22 06:08:45.722314: Pseudo dice [0.8577] +2024-11-22 06:08:45.722395: Epoch time: 18.69 s +2024-11-22 06:08:46.574843: +2024-11-22 06:08:46.575085: Epoch 3494 +2024-11-22 06:08:46.575196: Current learning rate: 0.00597 +2024-11-22 06:09:06.229216: train_loss -0.783 +2024-11-22 06:09:06.237200: val_loss -0.7844 +2024-11-22 06:09:06.237350: Pseudo dice [0.8609] +2024-11-22 06:09:06.237449: Epoch time: 19.66 s +2024-11-22 06:09:07.228611: +2024-11-22 06:09:07.228860: Epoch 3495 +2024-11-22 06:09:07.229010: Current learning rate: 0.00596 +2024-11-22 06:09:26.145951: train_loss -0.7847 +2024-11-22 06:09:26.151340: val_loss -0.7553 +2024-11-22 06:09:26.151454: Pseudo dice [0.8472] +2024-11-22 06:09:26.151542: Epoch time: 18.92 s +2024-11-22 06:09:26.998610: +2024-11-22 06:09:26.998812: Epoch 3496 +2024-11-22 06:09:26.998927: Current learning rate: 0.00596 +2024-11-22 06:09:46.922400: train_loss -0.7903 +2024-11-22 06:09:46.927985: val_loss -0.7655 +2024-11-22 06:09:46.928115: Pseudo dice [0.8551] +2024-11-22 06:09:46.928197: Epoch time: 19.92 s +2024-11-22 06:09:47.778239: +2024-11-22 06:09:47.778438: Epoch 3497 +2024-11-22 06:09:47.778546: Current learning rate: 0.00596 +2024-11-22 06:10:06.954564: train_loss -0.7859 +2024-11-22 06:10:06.960268: val_loss -0.7559 +2024-11-22 06:10:06.960453: Pseudo dice [0.8448] +2024-11-22 06:10:06.960536: Epoch time: 19.18 s +2024-11-22 06:10:07.808522: +2024-11-22 06:10:07.808733: Epoch 3498 +2024-11-22 06:10:07.808849: Current learning rate: 0.00596 +2024-11-22 06:10:26.314298: train_loss -0.785 +2024-11-22 06:10:26.320014: val_loss -0.7612 +2024-11-22 06:10:26.320134: Pseudo dice [0.8597] +2024-11-22 06:10:26.320228: Epoch time: 18.51 s +2024-11-22 06:10:27.575677: +2024-11-22 06:10:27.575875: Epoch 3499 +2024-11-22 06:10:27.575985: Current learning rate: 0.00596 +2024-11-22 06:10:46.611600: train_loss -0.7715 +2024-11-22 06:10:46.620037: val_loss -0.7718 +2024-11-22 06:10:46.620166: Pseudo dice [0.8487] +2024-11-22 06:10:46.620249: Epoch time: 19.04 s +2024-11-22 06:10:47.782927: +2024-11-22 06:10:47.783146: Epoch 3500 +2024-11-22 06:10:47.783257: Current learning rate: 0.00596 +2024-11-22 06:11:06.611266: train_loss -0.7806 +2024-11-22 06:11:06.615727: val_loss -0.7759 +2024-11-22 06:11:06.615853: Pseudo dice [0.8508] +2024-11-22 06:11:06.615936: Epoch time: 18.83 s +2024-11-22 06:11:07.485714: +2024-11-22 06:11:07.485943: Epoch 3501 +2024-11-22 06:11:07.486063: Current learning rate: 0.00596 +2024-11-22 06:11:26.745983: train_loss -0.7856 +2024-11-22 06:11:26.756361: val_loss -0.7684 +2024-11-22 06:11:26.756495: Pseudo dice [0.8497] +2024-11-22 06:11:26.756587: Epoch time: 19.26 s +2024-11-22 06:11:27.610784: +2024-11-22 06:11:27.610997: Epoch 3502 +2024-11-22 06:11:27.611114: Current learning rate: 0.00596 +2024-11-22 06:11:46.527391: train_loss -0.7905 +2024-11-22 06:11:46.529676: val_loss -0.756 +2024-11-22 06:11:46.529770: Pseudo dice [0.8507] +2024-11-22 06:11:46.529847: Epoch time: 18.92 s +2024-11-22 06:11:47.380934: +2024-11-22 06:11:47.381187: Epoch 3503 +2024-11-22 06:11:47.381308: Current learning rate: 0.00595 +2024-11-22 06:12:06.302227: train_loss -0.7915 +2024-11-22 06:12:06.311067: val_loss -0.7536 +2024-11-22 06:12:06.311176: Pseudo dice [0.8319] +2024-11-22 06:12:06.311254: Epoch time: 18.92 s +2024-11-22 06:12:07.228232: +2024-11-22 06:12:07.228440: Epoch 3504 +2024-11-22 06:12:07.228550: Current learning rate: 0.00595 +2024-11-22 06:12:26.328203: train_loss -0.7826 +2024-11-22 06:12:26.337741: val_loss -0.767 +2024-11-22 06:12:26.337878: Pseudo dice [0.847] +2024-11-22 06:12:26.337965: Epoch time: 19.1 s +2024-11-22 06:12:27.267354: +2024-11-22 06:12:27.267610: Epoch 3505 +2024-11-22 06:12:27.267725: Current learning rate: 0.00595 +2024-11-22 06:12:46.606054: train_loss -0.7853 +2024-11-22 06:12:46.614364: val_loss -0.7563 +2024-11-22 06:12:46.614488: Pseudo dice [0.8646] +2024-11-22 06:12:46.614870: Epoch time: 19.34 s +2024-11-22 06:12:47.471839: +2024-11-22 06:12:47.472044: Epoch 3506 +2024-11-22 06:12:47.472167: Current learning rate: 0.00595 +2024-11-22 06:13:05.433356: train_loss -0.792 +2024-11-22 06:13:05.438786: val_loss -0.7764 +2024-11-22 06:13:05.438904: Pseudo dice [0.857] +2024-11-22 06:13:05.438994: Epoch time: 17.96 s +2024-11-22 06:13:06.306426: +2024-11-22 06:13:06.306655: Epoch 3507 +2024-11-22 06:13:06.306774: Current learning rate: 0.00595 +2024-11-22 06:13:25.623227: train_loss -0.7791 +2024-11-22 06:13:25.627691: val_loss -0.7702 +2024-11-22 06:13:25.627803: Pseudo dice [0.8481] +2024-11-22 06:13:25.627893: Epoch time: 19.32 s +2024-11-22 06:13:26.502194: +2024-11-22 06:13:26.502374: Epoch 3508 +2024-11-22 06:13:26.502482: Current learning rate: 0.00595 +2024-11-22 06:13:45.893595: train_loss -0.7743 +2024-11-22 06:13:45.917756: val_loss -0.7667 +2024-11-22 06:13:45.917907: Pseudo dice [0.8413] +2024-11-22 06:13:45.917999: Epoch time: 19.39 s +2024-11-22 06:13:46.810323: +2024-11-22 06:13:46.810571: Epoch 3509 +2024-11-22 06:13:46.810683: Current learning rate: 0.00595 +2024-11-22 06:14:06.119048: train_loss -0.7656 +2024-11-22 06:14:06.125014: val_loss -0.7478 +2024-11-22 06:14:06.125153: Pseudo dice [0.8501] +2024-11-22 06:14:06.125238: Epoch time: 19.31 s +2024-11-22 06:14:07.389952: +2024-11-22 06:14:07.390148: Epoch 3510 +2024-11-22 06:14:07.390260: Current learning rate: 0.00595 +2024-11-22 06:14:26.084900: train_loss -0.7828 +2024-11-22 06:14:26.091646: val_loss -0.7667 +2024-11-22 06:14:26.091781: Pseudo dice [0.8464] +2024-11-22 06:14:26.091867: Epoch time: 18.7 s +2024-11-22 06:14:26.942248: +2024-11-22 06:14:26.942501: Epoch 3511 +2024-11-22 06:14:26.942614: Current learning rate: 0.00595 +2024-11-22 06:14:45.861287: train_loss -0.7848 +2024-11-22 06:14:45.865856: val_loss -0.7768 +2024-11-22 06:14:45.866032: Pseudo dice [0.8496] +2024-11-22 06:14:45.866127: Epoch time: 18.92 s +2024-11-22 06:14:46.774961: +2024-11-22 06:14:46.775224: Epoch 3512 +2024-11-22 06:14:46.775334: Current learning rate: 0.00594 +2024-11-22 06:15:06.716378: train_loss -0.7825 +2024-11-22 06:15:06.724230: val_loss -0.7471 +2024-11-22 06:15:06.724372: Pseudo dice [0.8376] +2024-11-22 06:15:06.724461: Epoch time: 19.94 s +2024-11-22 06:15:07.782774: +2024-11-22 06:15:07.783010: Epoch 3513 +2024-11-22 06:15:07.793950: Current learning rate: 0.00594 +2024-11-22 06:15:27.475939: train_loss -0.7875 +2024-11-22 06:15:27.479204: val_loss -0.7814 +2024-11-22 06:15:27.479334: Pseudo dice [0.8539] +2024-11-22 06:15:27.479414: Epoch time: 19.69 s +2024-11-22 06:15:28.371195: +2024-11-22 06:15:28.371395: Epoch 3514 +2024-11-22 06:15:28.371505: Current learning rate: 0.00594 +2024-11-22 06:15:46.858249: train_loss -0.7881 +2024-11-22 06:15:46.864747: val_loss -0.7664 +2024-11-22 06:15:46.864854: Pseudo dice [0.828] +2024-11-22 06:15:46.865026: Epoch time: 18.49 s +2024-11-22 06:15:47.800282: +2024-11-22 06:15:47.800513: Epoch 3515 +2024-11-22 06:15:47.800626: Current learning rate: 0.00594 +2024-11-22 06:16:08.376963: train_loss -0.7743 +2024-11-22 06:16:08.387005: val_loss -0.7899 +2024-11-22 06:16:08.387142: Pseudo dice [0.8511] +2024-11-22 06:16:08.387239: Epoch time: 20.58 s +2024-11-22 06:16:09.289635: +2024-11-22 06:16:09.289852: Epoch 3516 +2024-11-22 06:16:09.289970: Current learning rate: 0.00594 +2024-11-22 06:16:27.889719: train_loss -0.775 +2024-11-22 06:16:27.896438: val_loss -0.777 +2024-11-22 06:16:27.896580: Pseudo dice [0.8452] +2024-11-22 06:16:27.896667: Epoch time: 18.6 s +2024-11-22 06:16:28.782605: +2024-11-22 06:16:28.782816: Epoch 3517 +2024-11-22 06:16:28.782927: Current learning rate: 0.00594 +2024-11-22 06:16:48.579802: train_loss -0.7757 +2024-11-22 06:16:48.584984: val_loss -0.7583 +2024-11-22 06:16:48.585113: Pseudo dice [0.8455] +2024-11-22 06:16:48.585196: Epoch time: 19.8 s +2024-11-22 06:16:49.449965: +2024-11-22 06:16:49.450160: Epoch 3518 +2024-11-22 06:16:49.450276: Current learning rate: 0.00594 +2024-11-22 06:17:09.136298: train_loss -0.7816 +2024-11-22 06:17:09.152669: val_loss -0.7811 +2024-11-22 06:17:09.152807: Pseudo dice [0.8568] +2024-11-22 06:17:09.152894: Epoch time: 19.69 s +2024-11-22 06:17:10.041306: +2024-11-22 06:17:10.041489: Epoch 3519 +2024-11-22 06:17:10.041605: Current learning rate: 0.00594 +2024-11-22 06:17:30.448341: train_loss -0.7629 +2024-11-22 06:17:30.453083: val_loss -0.7699 +2024-11-22 06:17:30.453211: Pseudo dice [0.8371] +2024-11-22 06:17:30.453312: Epoch time: 20.41 s +2024-11-22 06:17:31.331413: +2024-11-22 06:17:31.331638: Epoch 3520 +2024-11-22 06:17:31.331746: Current learning rate: 0.00593 +2024-11-22 06:17:49.305561: train_loss -0.7724 +2024-11-22 06:17:49.313431: val_loss -0.7452 +2024-11-22 06:17:49.313576: Pseudo dice [0.8407] +2024-11-22 06:17:49.313666: Epoch time: 17.97 s +2024-11-22 06:17:50.189887: +2024-11-22 06:17:50.190155: Epoch 3521 +2024-11-22 06:17:50.190276: Current learning rate: 0.00593 +2024-11-22 06:18:10.608843: train_loss -0.784 +2024-11-22 06:18:10.613610: val_loss -0.7666 +2024-11-22 06:18:10.613732: Pseudo dice [0.8615] +2024-11-22 06:18:10.613818: Epoch time: 20.42 s +2024-11-22 06:18:11.488925: +2024-11-22 06:18:11.489149: Epoch 3522 +2024-11-22 06:18:11.489259: Current learning rate: 0.00593 +2024-11-22 06:18:30.532103: train_loss -0.7854 +2024-11-22 06:18:30.537920: val_loss -0.7644 +2024-11-22 06:18:30.538106: Pseudo dice [0.8532] +2024-11-22 06:18:30.538199: Epoch time: 19.04 s +2024-11-22 06:18:31.426517: +2024-11-22 06:18:31.426747: Epoch 3523 +2024-11-22 06:18:31.426861: Current learning rate: 0.00593 +2024-11-22 06:18:50.024420: train_loss -0.7873 +2024-11-22 06:18:50.031414: val_loss -0.7975 +2024-11-22 06:18:50.031533: Pseudo dice [0.849] +2024-11-22 06:18:50.031616: Epoch time: 18.6 s +2024-11-22 06:18:50.918970: +2024-11-22 06:18:50.919179: Epoch 3524 +2024-11-22 06:18:50.919287: Current learning rate: 0.00593 +2024-11-22 06:19:10.665407: train_loss -0.7856 +2024-11-22 06:19:10.670489: val_loss -0.7909 +2024-11-22 06:19:10.670687: Pseudo dice [0.8413] +2024-11-22 06:19:10.670769: Epoch time: 19.75 s +2024-11-22 06:19:11.702507: +2024-11-22 06:19:11.702710: Epoch 3525 +2024-11-22 06:19:11.702828: Current learning rate: 0.00593 +2024-11-22 06:19:30.711749: train_loss -0.7848 +2024-11-22 06:19:30.719128: val_loss -0.7835 +2024-11-22 06:19:30.719316: Pseudo dice [0.8507] +2024-11-22 06:19:30.740163: Epoch time: 19.01 s +2024-11-22 06:19:31.604055: +2024-11-22 06:19:31.604300: Epoch 3526 +2024-11-22 06:19:31.604415: Current learning rate: 0.00593 +2024-11-22 06:19:51.158287: train_loss -0.7735 +2024-11-22 06:19:51.171559: val_loss -0.7774 +2024-11-22 06:19:51.171710: Pseudo dice [0.8504] +2024-11-22 06:19:51.171801: Epoch time: 19.56 s +2024-11-22 06:19:52.059206: +2024-11-22 06:19:52.059411: Epoch 3527 +2024-11-22 06:19:52.059523: Current learning rate: 0.00593 +2024-11-22 06:20:11.421820: train_loss -0.7857 +2024-11-22 06:20:11.442184: val_loss -0.774 +2024-11-22 06:20:11.442417: Pseudo dice [0.8509] +2024-11-22 06:20:11.442515: Epoch time: 19.36 s +2024-11-22 06:20:12.344879: +2024-11-22 06:20:12.345089: Epoch 3528 +2024-11-22 06:20:12.345206: Current learning rate: 0.00592 +2024-11-22 06:20:32.008092: train_loss -0.776 +2024-11-22 06:20:32.016253: val_loss -0.7755 +2024-11-22 06:20:32.016382: Pseudo dice [0.8441] +2024-11-22 06:20:32.016466: Epoch time: 19.66 s +2024-11-22 06:20:32.931620: +2024-11-22 06:20:32.931798: Epoch 3529 +2024-11-22 06:20:32.931906: Current learning rate: 0.00592 +2024-11-22 06:20:52.291877: train_loss -0.7878 +2024-11-22 06:20:52.297892: val_loss -0.7739 +2024-11-22 06:20:52.298035: Pseudo dice [0.8419] +2024-11-22 06:20:52.298133: Epoch time: 19.36 s +2024-11-22 06:20:53.228704: +2024-11-22 06:20:53.228887: Epoch 3530 +2024-11-22 06:20:53.228990: Current learning rate: 0.00592 +2024-11-22 06:21:12.563110: train_loss -0.7876 +2024-11-22 06:21:12.566696: val_loss -0.7685 +2024-11-22 06:21:12.566831: Pseudo dice [0.849] +2024-11-22 06:21:12.566914: Epoch time: 19.34 s +2024-11-22 06:21:13.601560: +2024-11-22 06:21:13.601758: Epoch 3531 +2024-11-22 06:21:13.601870: Current learning rate: 0.00592 +2024-11-22 06:21:32.847125: train_loss -0.7783 +2024-11-22 06:21:32.855346: val_loss -0.8021 +2024-11-22 06:21:32.855476: Pseudo dice [0.8594] +2024-11-22 06:21:32.857111: Epoch time: 19.25 s +2024-11-22 06:21:34.114315: +2024-11-22 06:21:34.114523: Epoch 3532 +2024-11-22 06:21:34.114635: Current learning rate: 0.00592 +2024-11-22 06:21:53.657268: train_loss -0.8007 +2024-11-22 06:21:53.665128: val_loss -0.7753 +2024-11-22 06:21:53.665251: Pseudo dice [0.8469] +2024-11-22 06:21:53.665340: Epoch time: 19.54 s +2024-11-22 06:21:54.594765: +2024-11-22 06:21:54.595016: Epoch 3533 +2024-11-22 06:21:54.595128: Current learning rate: 0.00592 +2024-11-22 06:22:13.657658: train_loss -0.7713 +2024-11-22 06:22:13.664104: val_loss -0.7668 +2024-11-22 06:22:13.664236: Pseudo dice [0.854] +2024-11-22 06:22:13.664330: Epoch time: 19.06 s +2024-11-22 06:22:14.520043: +2024-11-22 06:22:14.520271: Epoch 3534 +2024-11-22 06:22:14.520382: Current learning rate: 0.00592 +2024-11-22 06:22:33.869709: train_loss -0.7831 +2024-11-22 06:22:33.876128: val_loss -0.7678 +2024-11-22 06:22:33.876265: Pseudo dice [0.8669] +2024-11-22 06:22:33.876345: Epoch time: 19.35 s +2024-11-22 06:22:34.734653: +2024-11-22 06:22:34.734858: Epoch 3535 +2024-11-22 06:22:34.734969: Current learning rate: 0.00592 +2024-11-22 06:22:54.283215: train_loss -0.7692 +2024-11-22 06:22:54.293342: val_loss -0.7471 +2024-11-22 06:22:54.293462: Pseudo dice [0.8409] +2024-11-22 06:22:54.293547: Epoch time: 19.55 s +2024-11-22 06:22:55.154784: +2024-11-22 06:22:55.155003: Epoch 3536 +2024-11-22 06:22:55.155114: Current learning rate: 0.00592 +2024-11-22 06:23:14.708233: train_loss -0.7801 +2024-11-22 06:23:14.713192: val_loss -0.7579 +2024-11-22 06:23:14.713334: Pseudo dice [0.8522] +2024-11-22 06:23:14.713425: Epoch time: 19.55 s +2024-11-22 06:23:15.883407: +2024-11-22 06:23:15.883645: Epoch 3537 +2024-11-22 06:23:15.883776: Current learning rate: 0.00591 +2024-11-22 06:23:35.780193: train_loss -0.7863 +2024-11-22 06:23:35.787564: val_loss -0.7712 +2024-11-22 06:23:35.787696: Pseudo dice [0.8516] +2024-11-22 06:23:35.787777: Epoch time: 19.9 s +2024-11-22 06:23:36.808197: +2024-11-22 06:23:36.808391: Epoch 3538 +2024-11-22 06:23:36.808503: Current learning rate: 0.00591 +2024-11-22 06:23:55.709269: train_loss -0.7717 +2024-11-22 06:23:55.710973: val_loss -0.7788 +2024-11-22 06:23:55.711082: Pseudo dice [0.8452] +2024-11-22 06:23:55.711159: Epoch time: 18.9 s +2024-11-22 06:23:56.685596: +2024-11-22 06:23:56.685838: Epoch 3539 +2024-11-22 06:23:56.685955: Current learning rate: 0.00591 +2024-11-22 06:24:15.598445: train_loss -0.7737 +2024-11-22 06:24:15.605051: val_loss -0.7723 +2024-11-22 06:24:15.605200: Pseudo dice [0.8437] +2024-11-22 06:24:15.605281: Epoch time: 18.91 s +2024-11-22 06:24:16.468909: +2024-11-22 06:24:16.469105: Epoch 3540 +2024-11-22 06:24:16.469212: Current learning rate: 0.00591 +2024-11-22 06:24:35.858918: train_loss -0.7664 +2024-11-22 06:24:35.865930: val_loss -0.7822 +2024-11-22 06:24:35.866078: Pseudo dice [0.8474] +2024-11-22 06:24:35.866174: Epoch time: 19.39 s +2024-11-22 06:24:36.746170: +2024-11-22 06:24:36.746389: Epoch 3541 +2024-11-22 06:24:36.746500: Current learning rate: 0.00591 +2024-11-22 06:24:55.708594: train_loss -0.767 +2024-11-22 06:24:55.719796: val_loss -0.778 +2024-11-22 06:24:55.719938: Pseudo dice [0.8467] +2024-11-22 06:24:55.720022: Epoch time: 18.96 s +2024-11-22 06:24:56.698772: +2024-11-22 06:24:56.698994: Epoch 3542 +2024-11-22 06:24:56.699114: Current learning rate: 0.00591 +2024-11-22 06:25:15.495225: train_loss -0.7775 +2024-11-22 06:25:15.501679: val_loss -0.75 +2024-11-22 06:25:15.501822: Pseudo dice [0.8483] +2024-11-22 06:25:15.501909: Epoch time: 18.8 s +2024-11-22 06:25:16.362159: +2024-11-22 06:25:16.362423: Epoch 3543 +2024-11-22 06:25:16.362544: Current learning rate: 0.00591 +2024-11-22 06:25:34.544267: train_loss -0.7951 +2024-11-22 06:25:34.546266: val_loss -0.775 +2024-11-22 06:25:34.546391: Pseudo dice [0.86] +2024-11-22 06:25:34.546483: Epoch time: 18.18 s +2024-11-22 06:25:35.863261: +2024-11-22 06:25:35.863468: Epoch 3544 +2024-11-22 06:25:35.863580: Current learning rate: 0.00591 +2024-11-22 06:25:54.824907: train_loss -0.7902 +2024-11-22 06:25:54.831811: val_loss -0.7501 +2024-11-22 06:25:54.831944: Pseudo dice [0.8446] +2024-11-22 06:25:54.832036: Epoch time: 18.96 s +2024-11-22 06:25:55.680864: +2024-11-22 06:25:55.681076: Epoch 3545 +2024-11-22 06:25:55.681190: Current learning rate: 0.0059 +2024-11-22 06:26:15.293927: train_loss -0.77 +2024-11-22 06:26:15.297373: val_loss -0.7699 +2024-11-22 06:26:15.297517: Pseudo dice [0.8547] +2024-11-22 06:26:15.297605: Epoch time: 19.61 s +2024-11-22 06:26:16.142541: +2024-11-22 06:26:16.142757: Epoch 3546 +2024-11-22 06:26:16.142869: Current learning rate: 0.0059 +2024-11-22 06:26:35.164585: train_loss -0.7752 +2024-11-22 06:26:35.167220: val_loss -0.7755 +2024-11-22 06:26:35.167342: Pseudo dice [0.8529] +2024-11-22 06:26:35.167418: Epoch time: 19.02 s +2024-11-22 06:26:36.113572: +2024-11-22 06:26:36.113774: Epoch 3547 +2024-11-22 06:26:36.113886: Current learning rate: 0.0059 +2024-11-22 06:26:54.594232: train_loss -0.7827 +2024-11-22 06:26:54.601860: val_loss -0.7785 +2024-11-22 06:26:54.601968: Pseudo dice [0.8565] +2024-11-22 06:26:54.602117: Epoch time: 18.48 s +2024-11-22 06:26:55.554542: +2024-11-22 06:26:55.554757: Epoch 3548 +2024-11-22 06:26:55.554869: Current learning rate: 0.0059 +2024-11-22 06:27:13.503197: train_loss -0.7789 +2024-11-22 06:27:13.509237: val_loss -0.7511 +2024-11-22 06:27:13.509377: Pseudo dice [0.8468] +2024-11-22 06:27:13.509467: Epoch time: 17.95 s +2024-11-22 06:27:14.405015: +2024-11-22 06:27:14.405233: Epoch 3549 +2024-11-22 06:27:14.405352: Current learning rate: 0.0059 +2024-11-22 06:27:33.276619: train_loss -0.7843 +2024-11-22 06:27:33.281751: val_loss -0.7559 +2024-11-22 06:27:33.281877: Pseudo dice [0.8546] +2024-11-22 06:27:33.281965: Epoch time: 18.87 s +2024-11-22 06:27:34.490988: +2024-11-22 06:27:34.491231: Epoch 3550 +2024-11-22 06:27:34.491348: Current learning rate: 0.0059 +2024-11-22 06:27:53.470041: train_loss -0.7922 +2024-11-22 06:27:53.477553: val_loss -0.7731 +2024-11-22 06:27:53.477691: Pseudo dice [0.8534] +2024-11-22 06:27:53.477775: Epoch time: 18.98 s +2024-11-22 06:27:54.562735: +2024-11-22 06:27:54.562958: Epoch 3551 +2024-11-22 06:27:54.563077: Current learning rate: 0.0059 +2024-11-22 06:28:12.658473: train_loss -0.7873 +2024-11-22 06:28:12.665672: val_loss -0.784 +2024-11-22 06:28:12.665807: Pseudo dice [0.8525] +2024-11-22 06:28:12.665898: Epoch time: 18.1 s +2024-11-22 06:28:13.535858: +2024-11-22 06:28:13.536056: Epoch 3552 +2024-11-22 06:28:13.536175: Current learning rate: 0.0059 +2024-11-22 06:28:32.337356: train_loss -0.7823 +2024-11-22 06:28:32.344379: val_loss -0.7625 +2024-11-22 06:28:32.344580: Pseudo dice [0.85] +2024-11-22 06:28:32.344660: Epoch time: 18.8 s +2024-11-22 06:28:33.236311: +2024-11-22 06:28:33.236535: Epoch 3553 +2024-11-22 06:28:33.236644: Current learning rate: 0.00589 +2024-11-22 06:28:53.011099: train_loss -0.7805 +2024-11-22 06:28:53.023076: val_loss -0.7672 +2024-11-22 06:28:53.023235: Pseudo dice [0.8387] +2024-11-22 06:28:53.023323: Epoch time: 19.78 s +2024-11-22 06:28:53.871366: +2024-11-22 06:28:53.871556: Epoch 3554 +2024-11-22 06:28:53.871662: Current learning rate: 0.00589 +2024-11-22 06:29:12.588863: train_loss -0.7868 +2024-11-22 06:29:12.594130: val_loss -0.7553 +2024-11-22 06:29:12.594262: Pseudo dice [0.8482] +2024-11-22 06:29:12.594358: Epoch time: 18.72 s +2024-11-22 06:29:13.868356: +2024-11-22 06:29:13.868597: Epoch 3555 +2024-11-22 06:29:13.868711: Current learning rate: 0.00589 +2024-11-22 06:29:32.541293: train_loss -0.7856 +2024-11-22 06:29:32.546659: val_loss -0.7827 +2024-11-22 06:29:32.546808: Pseudo dice [0.8608] +2024-11-22 06:29:32.546890: Epoch time: 18.67 s +2024-11-22 06:29:33.391985: +2024-11-22 06:29:33.392234: Epoch 3556 +2024-11-22 06:29:33.392344: Current learning rate: 0.00589 +2024-11-22 06:29:53.089399: train_loss -0.7741 +2024-11-22 06:29:53.096368: val_loss -0.7506 +2024-11-22 06:29:53.096503: Pseudo dice [0.8444] +2024-11-22 06:29:53.096589: Epoch time: 19.7 s +2024-11-22 06:29:54.100368: +2024-11-22 06:29:54.100613: Epoch 3557 +2024-11-22 06:29:54.100729: Current learning rate: 0.00589 +2024-11-22 06:30:14.003084: train_loss -0.7651 +2024-11-22 06:30:14.008566: val_loss -0.7474 +2024-11-22 06:30:14.008678: Pseudo dice [0.8431] +2024-11-22 06:30:14.009127: Epoch time: 19.9 s +2024-11-22 06:30:14.979935: +2024-11-22 06:30:14.980157: Epoch 3558 +2024-11-22 06:30:14.980272: Current learning rate: 0.00589 +2024-11-22 06:30:34.190817: train_loss -0.7658 +2024-11-22 06:30:34.196301: val_loss -0.7587 +2024-11-22 06:30:34.196434: Pseudo dice [0.8442] +2024-11-22 06:30:34.196515: Epoch time: 19.21 s +2024-11-22 06:30:35.314032: +2024-11-22 06:30:35.314292: Epoch 3559 +2024-11-22 06:30:35.314402: Current learning rate: 0.00589 +2024-11-22 06:30:55.212326: train_loss -0.7538 +2024-11-22 06:30:55.227438: val_loss -0.7428 +2024-11-22 06:30:55.227566: Pseudo dice [0.8556] +2024-11-22 06:30:55.227650: Epoch time: 19.9 s +2024-11-22 06:30:56.142073: +2024-11-22 06:30:56.142272: Epoch 3560 +2024-11-22 06:30:56.142383: Current learning rate: 0.00589 +2024-11-22 06:31:16.437794: train_loss -0.7541 +2024-11-22 06:31:16.445583: val_loss -0.7357 +2024-11-22 06:31:16.445711: Pseudo dice [0.7768] +2024-11-22 06:31:16.445801: Epoch time: 20.3 s +2024-11-22 06:31:17.296692: +2024-11-22 06:31:17.296926: Epoch 3561 +2024-11-22 06:31:17.297041: Current learning rate: 0.00589 +2024-11-22 06:31:37.435960: train_loss -0.7436 +2024-11-22 06:31:37.441885: val_loss -0.7478 +2024-11-22 06:31:37.442005: Pseudo dice [0.841] +2024-11-22 06:31:37.442098: Epoch time: 20.14 s +2024-11-22 06:31:38.304729: +2024-11-22 06:31:38.304937: Epoch 3562 +2024-11-22 06:31:38.305048: Current learning rate: 0.00588 +2024-11-22 06:31:56.762820: train_loss -0.7694 +2024-11-22 06:31:56.768833: val_loss -0.7826 +2024-11-22 06:31:56.768965: Pseudo dice [0.8568] +2024-11-22 06:31:56.769052: Epoch time: 18.46 s +2024-11-22 06:31:57.690978: +2024-11-22 06:31:57.691194: Epoch 3563 +2024-11-22 06:31:57.691312: Current learning rate: 0.00588 +2024-11-22 06:32:16.468145: train_loss -0.7785 +2024-11-22 06:32:16.474205: val_loss -0.7392 +2024-11-22 06:32:16.474332: Pseudo dice [0.8413] +2024-11-22 06:32:16.474410: Epoch time: 18.78 s +2024-11-22 06:32:17.370424: +2024-11-22 06:32:17.370625: Epoch 3564 +2024-11-22 06:32:17.370742: Current learning rate: 0.00588 +2024-11-22 06:32:37.672694: train_loss -0.7807 +2024-11-22 06:32:37.682001: val_loss -0.77 +2024-11-22 06:32:37.682128: Pseudo dice [0.8592] +2024-11-22 06:32:37.682213: Epoch time: 20.3 s +2024-11-22 06:32:38.545703: +2024-11-22 06:32:38.545902: Epoch 3565 +2024-11-22 06:32:38.546015: Current learning rate: 0.00588 +2024-11-22 06:32:58.104010: train_loss -0.7776 +2024-11-22 06:32:58.111449: val_loss -0.7683 +2024-11-22 06:32:58.111593: Pseudo dice [0.855] +2024-11-22 06:32:58.111682: Epoch time: 19.56 s +2024-11-22 06:32:58.959509: +2024-11-22 06:32:58.959708: Epoch 3566 +2024-11-22 06:32:58.959817: Current learning rate: 0.00588 +2024-11-22 06:33:19.234285: train_loss -0.7828 +2024-11-22 06:33:19.239452: val_loss -0.7744 +2024-11-22 06:33:19.239574: Pseudo dice [0.8461] +2024-11-22 06:33:19.239660: Epoch time: 20.28 s +2024-11-22 06:33:20.550057: +2024-11-22 06:33:20.550273: Epoch 3567 +2024-11-22 06:33:20.550391: Current learning rate: 0.00588 +2024-11-22 06:33:39.450845: train_loss -0.7836 +2024-11-22 06:33:39.457611: val_loss -0.7621 +2024-11-22 06:33:39.457745: Pseudo dice [0.8411] +2024-11-22 06:33:39.457834: Epoch time: 18.9 s +2024-11-22 06:33:40.301447: +2024-11-22 06:33:40.301654: Epoch 3568 +2024-11-22 06:33:40.301768: Current learning rate: 0.00588 +2024-11-22 06:33:59.833742: train_loss -0.7868 +2024-11-22 06:33:59.839456: val_loss -0.7554 +2024-11-22 06:33:59.839592: Pseudo dice [0.8621] +2024-11-22 06:33:59.839680: Epoch time: 19.53 s +2024-11-22 06:34:00.690413: +2024-11-22 06:34:00.690612: Epoch 3569 +2024-11-22 06:34:00.690727: Current learning rate: 0.00588 +2024-11-22 06:34:19.294571: train_loss -0.7841 +2024-11-22 06:34:19.296470: val_loss -0.7593 +2024-11-22 06:34:19.296584: Pseudo dice [0.8459] +2024-11-22 06:34:19.296664: Epoch time: 18.6 s +2024-11-22 06:34:20.157425: +2024-11-22 06:34:20.157632: Epoch 3570 +2024-11-22 06:34:20.157749: Current learning rate: 0.00587 +2024-11-22 06:34:38.785465: train_loss -0.7846 +2024-11-22 06:34:38.789523: val_loss -0.7413 +2024-11-22 06:34:38.789624: Pseudo dice [0.8491] +2024-11-22 06:34:38.789711: Epoch time: 18.63 s +2024-11-22 06:34:39.635224: +2024-11-22 06:34:39.635428: Epoch 3571 +2024-11-22 06:34:39.635542: Current learning rate: 0.00587 +2024-11-22 06:34:59.115663: train_loss -0.7791 +2024-11-22 06:34:59.122095: val_loss -0.7639 +2024-11-22 06:34:59.122216: Pseudo dice [0.8493] +2024-11-22 06:34:59.122293: Epoch time: 19.48 s +2024-11-22 06:34:59.969798: +2024-11-22 06:34:59.970017: Epoch 3572 +2024-11-22 06:34:59.970149: Current learning rate: 0.00587 +2024-11-22 06:35:19.682576: train_loss -0.7725 +2024-11-22 06:35:19.685156: val_loss -0.7679 +2024-11-22 06:35:19.685276: Pseudo dice [0.8455] +2024-11-22 06:35:19.685363: Epoch time: 19.71 s +2024-11-22 06:35:20.535583: +2024-11-22 06:35:20.535843: Epoch 3573 +2024-11-22 06:35:20.535992: Current learning rate: 0.00587 +2024-11-22 06:35:40.065263: train_loss -0.7771 +2024-11-22 06:35:40.071586: val_loss -0.7515 +2024-11-22 06:35:40.071719: Pseudo dice [0.8492] +2024-11-22 06:35:40.071806: Epoch time: 19.53 s +2024-11-22 06:35:40.967953: +2024-11-22 06:35:40.968180: Epoch 3574 +2024-11-22 06:35:40.968296: Current learning rate: 0.00587 +2024-11-22 06:35:59.414946: train_loss -0.7711 +2024-11-22 06:35:59.417540: val_loss -0.7745 +2024-11-22 06:35:59.417637: Pseudo dice [0.8524] +2024-11-22 06:35:59.417717: Epoch time: 18.45 s +2024-11-22 06:36:00.259504: +2024-11-22 06:36:00.259707: Epoch 3575 +2024-11-22 06:36:00.259824: Current learning rate: 0.00587 +2024-11-22 06:36:20.797273: train_loss -0.7767 +2024-11-22 06:36:20.804634: val_loss -0.7602 +2024-11-22 06:36:20.804782: Pseudo dice [0.8496] +2024-11-22 06:36:20.804870: Epoch time: 20.54 s +2024-11-22 06:36:21.647880: +2024-11-22 06:36:21.648132: Epoch 3576 +2024-11-22 06:36:21.648245: Current learning rate: 0.00587 +2024-11-22 06:36:41.278610: train_loss -0.778 +2024-11-22 06:36:41.281305: val_loss -0.7598 +2024-11-22 06:36:41.281665: Pseudo dice [0.8539] +2024-11-22 06:36:41.281760: Epoch time: 19.63 s +2024-11-22 06:36:42.163168: +2024-11-22 06:36:42.163396: Epoch 3577 +2024-11-22 06:36:42.163513: Current learning rate: 0.00587 +2024-11-22 06:37:00.688179: train_loss -0.7682 +2024-11-22 06:37:00.693949: val_loss -0.7466 +2024-11-22 06:37:00.694054: Pseudo dice [0.8431] +2024-11-22 06:37:00.694138: Epoch time: 18.53 s +2024-11-22 06:37:01.558464: +2024-11-22 06:37:01.558663: Epoch 3578 +2024-11-22 06:37:01.558775: Current learning rate: 0.00587 +2024-11-22 06:37:20.340124: train_loss -0.7731 +2024-11-22 06:37:20.354663: val_loss -0.7521 +2024-11-22 06:37:20.354796: Pseudo dice [0.8569] +2024-11-22 06:37:20.354998: Epoch time: 18.78 s +2024-11-22 06:37:21.221035: +2024-11-22 06:37:21.221269: Epoch 3579 +2024-11-22 06:37:21.221380: Current learning rate: 0.00586 +2024-11-22 06:37:39.686087: train_loss -0.7688 +2024-11-22 06:37:39.693211: val_loss -0.7777 +2024-11-22 06:37:39.693336: Pseudo dice [0.8535] +2024-11-22 06:37:39.693423: Epoch time: 18.47 s +2024-11-22 06:37:40.570885: +2024-11-22 06:37:40.571119: Epoch 3580 +2024-11-22 06:37:40.571232: Current learning rate: 0.00586 +2024-11-22 06:37:59.068628: train_loss -0.7717 +2024-11-22 06:37:59.072265: val_loss -0.7619 +2024-11-22 06:37:59.072409: Pseudo dice [0.8506] +2024-11-22 06:37:59.072491: Epoch time: 18.5 s +2024-11-22 06:38:00.010310: +2024-11-22 06:38:00.010531: Epoch 3581 +2024-11-22 06:38:00.010642: Current learning rate: 0.00586 +2024-11-22 06:38:19.634702: train_loss -0.7736 +2024-11-22 06:38:19.640299: val_loss -0.7455 +2024-11-22 06:38:19.640428: Pseudo dice [0.8455] +2024-11-22 06:38:19.640517: Epoch time: 19.63 s +2024-11-22 06:38:20.487401: +2024-11-22 06:38:20.487592: Epoch 3582 +2024-11-22 06:38:20.487703: Current learning rate: 0.00586 +2024-11-22 06:38:39.789766: train_loss -0.7623 +2024-11-22 06:38:39.796183: val_loss -0.7849 +2024-11-22 06:38:39.796321: Pseudo dice [0.8501] +2024-11-22 06:38:39.796420: Epoch time: 19.3 s +2024-11-22 06:38:40.646516: +2024-11-22 06:38:40.646728: Epoch 3583 +2024-11-22 06:38:40.646840: Current learning rate: 0.00586 +2024-11-22 06:39:00.382635: train_loss -0.783 +2024-11-22 06:39:00.412361: val_loss -0.7655 +2024-11-22 06:39:00.412897: Pseudo dice [0.8526] +2024-11-22 06:39:00.413009: Epoch time: 19.74 s +2024-11-22 06:39:01.580248: +2024-11-22 06:39:01.580495: Epoch 3584 +2024-11-22 06:39:01.580609: Current learning rate: 0.00586 +2024-11-22 06:39:20.476489: train_loss -0.7919 +2024-11-22 06:39:20.480571: val_loss -0.78 +2024-11-22 06:39:20.480686: Pseudo dice [0.8657] +2024-11-22 06:39:20.480771: Epoch time: 18.9 s +2024-11-22 06:39:21.322450: +2024-11-22 06:39:21.322646: Epoch 3585 +2024-11-22 06:39:21.322762: Current learning rate: 0.00586 +2024-11-22 06:39:41.085447: train_loss -0.7884 +2024-11-22 06:39:41.101715: val_loss -0.7695 +2024-11-22 06:39:41.101856: Pseudo dice [0.8665] +2024-11-22 06:39:41.101939: Epoch time: 19.76 s +2024-11-22 06:39:42.047360: +2024-11-22 06:39:42.047608: Epoch 3586 +2024-11-22 06:39:42.047723: Current learning rate: 0.00586 +2024-11-22 06:40:00.771187: train_loss -0.7816 +2024-11-22 06:40:00.773594: val_loss -0.7521 +2024-11-22 06:40:00.773713: Pseudo dice [0.8524] +2024-11-22 06:40:00.773800: Epoch time: 18.72 s +2024-11-22 06:40:01.618731: +2024-11-22 06:40:01.618935: Epoch 3587 +2024-11-22 06:40:01.619064: Current learning rate: 0.00585 +2024-11-22 06:40:20.732346: train_loss -0.7743 +2024-11-22 06:40:20.734561: val_loss -0.7368 +2024-11-22 06:40:20.734653: Pseudo dice [0.8314] +2024-11-22 06:40:20.734746: Epoch time: 19.11 s +2024-11-22 06:40:21.580933: +2024-11-22 06:40:21.581141: Epoch 3588 +2024-11-22 06:40:21.581252: Current learning rate: 0.00585 +2024-11-22 06:40:40.426003: train_loss -0.7669 +2024-11-22 06:40:40.435678: val_loss -0.7493 +2024-11-22 06:40:40.435801: Pseudo dice [0.8373] +2024-11-22 06:40:40.435887: Epoch time: 18.85 s +2024-11-22 06:40:41.285539: +2024-11-22 06:40:41.285723: Epoch 3589 +2024-11-22 06:40:41.285838: Current learning rate: 0.00585 +2024-11-22 06:40:59.645327: train_loss -0.7753 +2024-11-22 06:40:59.647635: val_loss -0.7657 +2024-11-22 06:40:59.647753: Pseudo dice [0.8449] +2024-11-22 06:40:59.647842: Epoch time: 18.36 s +2024-11-22 06:41:00.909736: +2024-11-22 06:41:00.909986: Epoch 3590 +2024-11-22 06:41:00.910108: Current learning rate: 0.00585 +2024-11-22 06:41:20.007623: train_loss -0.7836 +2024-11-22 06:41:20.016512: val_loss -0.7653 +2024-11-22 06:41:20.016646: Pseudo dice [0.8377] +2024-11-22 06:41:20.016732: Epoch time: 19.1 s +2024-11-22 06:41:21.119825: +2024-11-22 06:41:21.120053: Epoch 3591 +2024-11-22 06:41:21.120167: Current learning rate: 0.00585 +2024-11-22 06:41:39.199938: train_loss -0.78 +2024-11-22 06:41:39.202314: val_loss -0.7251 +2024-11-22 06:41:39.202424: Pseudo dice [0.84] +2024-11-22 06:41:39.202507: Epoch time: 18.08 s +2024-11-22 06:41:40.289742: +2024-11-22 06:41:40.289970: Epoch 3592 +2024-11-22 06:41:40.290091: Current learning rate: 0.00585 +2024-11-22 06:41:59.306144: train_loss -0.7769 +2024-11-22 06:41:59.311133: val_loss -0.7589 +2024-11-22 06:41:59.311266: Pseudo dice [0.853] +2024-11-22 06:41:59.311353: Epoch time: 19.02 s +2024-11-22 06:42:00.204499: +2024-11-22 06:42:00.204710: Epoch 3593 +2024-11-22 06:42:00.204826: Current learning rate: 0.00585 +2024-11-22 06:42:19.140847: train_loss -0.7631 +2024-11-22 06:42:19.146681: val_loss -0.7534 +2024-11-22 06:42:19.146814: Pseudo dice [0.8278] +2024-11-22 06:42:19.146902: Epoch time: 18.94 s +2024-11-22 06:42:20.006055: +2024-11-22 06:42:20.006273: Epoch 3594 +2024-11-22 06:42:20.006396: Current learning rate: 0.00585 +2024-11-22 06:42:39.230564: train_loss -0.77 +2024-11-22 06:42:39.236108: val_loss -0.7486 +2024-11-22 06:42:39.236224: Pseudo dice [0.8423] +2024-11-22 06:42:39.236306: Epoch time: 19.23 s +2024-11-22 06:42:40.093380: +2024-11-22 06:42:40.093592: Epoch 3595 +2024-11-22 06:42:40.093706: Current learning rate: 0.00584 +2024-11-22 06:42:58.722191: train_loss -0.7714 +2024-11-22 06:42:58.730170: val_loss -0.7563 +2024-11-22 06:42:58.730313: Pseudo dice [0.8411] +2024-11-22 06:42:58.730402: Epoch time: 18.63 s +2024-11-22 06:42:59.594989: +2024-11-22 06:42:59.595203: Epoch 3596 +2024-11-22 06:42:59.595315: Current learning rate: 0.00584 +2024-11-22 06:43:18.475071: train_loss -0.7741 +2024-11-22 06:43:18.481354: val_loss -0.7602 +2024-11-22 06:43:18.481482: Pseudo dice [0.838] +2024-11-22 06:43:18.481612: Epoch time: 18.88 s +2024-11-22 06:43:19.340918: +2024-11-22 06:43:19.341136: Epoch 3597 +2024-11-22 06:43:19.341255: Current learning rate: 0.00584 +2024-11-22 06:43:38.585053: train_loss -0.7782 +2024-11-22 06:43:38.590623: val_loss -0.7364 +2024-11-22 06:43:38.590810: Pseudo dice [0.8431] +2024-11-22 06:43:38.590913: Epoch time: 19.24 s +2024-11-22 06:43:39.455307: +2024-11-22 06:43:39.455567: Epoch 3598 +2024-11-22 06:43:39.455684: Current learning rate: 0.00584 +2024-11-22 06:43:57.634457: train_loss -0.7927 +2024-11-22 06:43:57.641904: val_loss -0.7605 +2024-11-22 06:43:57.642025: Pseudo dice [0.8497] +2024-11-22 06:43:57.642116: Epoch time: 18.18 s +2024-11-22 06:43:58.565304: +2024-11-22 06:43:58.565524: Epoch 3599 +2024-11-22 06:43:58.565640: Current learning rate: 0.00584 +2024-11-22 06:44:17.650387: train_loss -0.7755 +2024-11-22 06:44:17.654575: val_loss -0.7713 +2024-11-22 06:44:17.654688: Pseudo dice [0.8519] +2024-11-22 06:44:17.654769: Epoch time: 19.09 s +2024-11-22 06:44:18.783748: +2024-11-22 06:44:18.783976: Epoch 3600 +2024-11-22 06:44:18.784094: Current learning rate: 0.00584 +2024-11-22 06:44:37.537457: train_loss -0.7848 +2024-11-22 06:44:37.545809: val_loss -0.7832 +2024-11-22 06:44:37.546020: Pseudo dice [0.8414] +2024-11-22 06:44:37.546123: Epoch time: 18.75 s +2024-11-22 06:44:38.831567: +2024-11-22 06:44:38.831797: Epoch 3601 +2024-11-22 06:44:38.831913: Current learning rate: 0.00584 +2024-11-22 06:44:57.800934: train_loss -0.7866 +2024-11-22 06:44:57.805188: val_loss -0.7438 +2024-11-22 06:44:57.805321: Pseudo dice [0.8441] +2024-11-22 06:44:57.805399: Epoch time: 18.97 s +2024-11-22 06:44:58.758641: +2024-11-22 06:44:58.772741: Epoch 3602 +2024-11-22 06:44:58.772864: Current learning rate: 0.00584 +2024-11-22 06:45:19.100684: train_loss -0.7746 +2024-11-22 06:45:19.103453: val_loss -0.7725 +2024-11-22 06:45:19.103546: Pseudo dice [0.8561] +2024-11-22 06:45:19.103627: Epoch time: 20.34 s +2024-11-22 06:45:19.948552: +2024-11-22 06:45:19.948766: Epoch 3603 +2024-11-22 06:45:19.948877: Current learning rate: 0.00584 +2024-11-22 06:45:37.959781: train_loss -0.7748 +2024-11-22 06:45:37.962782: val_loss -0.7592 +2024-11-22 06:45:37.962897: Pseudo dice [0.8427] +2024-11-22 06:45:37.962991: Epoch time: 18.01 s +2024-11-22 06:45:38.813974: +2024-11-22 06:45:38.814192: Epoch 3604 +2024-11-22 06:45:38.814302: Current learning rate: 0.00583 +2024-11-22 06:45:58.920204: train_loss -0.7715 +2024-11-22 06:45:58.926471: val_loss -0.7624 +2024-11-22 06:45:58.926605: Pseudo dice [0.8579] +2024-11-22 06:45:58.926741: Epoch time: 20.11 s +2024-11-22 06:45:59.784677: +2024-11-22 06:45:59.784899: Epoch 3605 +2024-11-22 06:45:59.785016: Current learning rate: 0.00583 +2024-11-22 06:46:18.763837: train_loss -0.7821 +2024-11-22 06:46:18.776481: val_loss -0.736 +2024-11-22 06:46:18.776599: Pseudo dice [0.8361] +2024-11-22 06:46:18.776685: Epoch time: 18.98 s +2024-11-22 06:46:19.658530: +2024-11-22 06:46:19.658747: Epoch 3606 +2024-11-22 06:46:19.658857: Current learning rate: 0.00583 +2024-11-22 06:46:38.696392: train_loss -0.7742 +2024-11-22 06:46:38.701226: val_loss -0.7463 +2024-11-22 06:46:38.701333: Pseudo dice [0.8445] +2024-11-22 06:46:38.701410: Epoch time: 19.04 s +2024-11-22 06:46:39.909567: +2024-11-22 06:46:39.909792: Epoch 3607 +2024-11-22 06:46:39.909907: Current learning rate: 0.00583 +2024-11-22 06:46:59.018542: train_loss -0.7851 +2024-11-22 06:46:59.025886: val_loss -0.7565 +2024-11-22 06:46:59.026001: Pseudo dice [0.8453] +2024-11-22 06:46:59.026104: Epoch time: 19.11 s +2024-11-22 06:46:59.874514: +2024-11-22 06:46:59.874750: Epoch 3608 +2024-11-22 06:46:59.874865: Current learning rate: 0.00583 +2024-11-22 06:47:19.548560: train_loss -0.7751 +2024-11-22 06:47:19.555670: val_loss -0.7781 +2024-11-22 06:47:19.555882: Pseudo dice [0.8496] +2024-11-22 06:47:19.555965: Epoch time: 19.67 s +2024-11-22 06:47:20.416171: +2024-11-22 06:47:20.416389: Epoch 3609 +2024-11-22 06:47:20.416504: Current learning rate: 0.00583 +2024-11-22 06:47:38.756875: train_loss -0.7794 +2024-11-22 06:47:38.763461: val_loss -0.7691 +2024-11-22 06:47:38.763810: Pseudo dice [0.8477] +2024-11-22 06:47:38.763917: Epoch time: 18.34 s +2024-11-22 06:47:39.616559: +2024-11-22 06:47:39.616779: Epoch 3610 +2024-11-22 06:47:39.616891: Current learning rate: 0.00583 +2024-11-22 06:47:59.043248: train_loss -0.786 +2024-11-22 06:47:59.052436: val_loss -0.7853 +2024-11-22 06:47:59.052559: Pseudo dice [0.8539] +2024-11-22 06:47:59.052659: Epoch time: 19.43 s +2024-11-22 06:48:00.044049: +2024-11-22 06:48:00.044266: Epoch 3611 +2024-11-22 06:48:00.044381: Current learning rate: 0.00583 +2024-11-22 06:48:18.014871: train_loss -0.7827 +2024-11-22 06:48:18.017938: val_loss -0.7631 +2024-11-22 06:48:18.018036: Pseudo dice [0.8469] +2024-11-22 06:48:18.018124: Epoch time: 17.97 s +2024-11-22 06:48:18.856836: +2024-11-22 06:48:18.857084: Epoch 3612 +2024-11-22 06:48:18.857199: Current learning rate: 0.00582 +2024-11-22 06:48:36.669673: train_loss -0.7878 +2024-11-22 06:48:36.678309: val_loss -0.7716 +2024-11-22 06:48:36.678429: Pseudo dice [0.8402] +2024-11-22 06:48:36.678521: Epoch time: 17.81 s +2024-11-22 06:48:37.697411: +2024-11-22 06:48:37.697653: Epoch 3613 +2024-11-22 06:48:37.697772: Current learning rate: 0.00582 +2024-11-22 06:48:56.370833: train_loss -0.7948 +2024-11-22 06:48:56.373823: val_loss -0.7715 +2024-11-22 06:48:56.373919: Pseudo dice [0.8527] +2024-11-22 06:48:56.374002: Epoch time: 18.67 s +2024-11-22 06:48:57.218255: +2024-11-22 06:48:57.218467: Epoch 3614 +2024-11-22 06:48:57.218582: Current learning rate: 0.00582 +2024-11-22 06:49:15.214815: train_loss -0.7805 +2024-11-22 06:49:15.219866: val_loss -0.7688 +2024-11-22 06:49:15.220025: Pseudo dice [0.8482] +2024-11-22 06:49:15.239038: Epoch time: 18.0 s +2024-11-22 06:49:16.183767: +2024-11-22 06:49:16.184000: Epoch 3615 +2024-11-22 06:49:16.184117: Current learning rate: 0.00582 +2024-11-22 06:49:35.964026: train_loss -0.7758 +2024-11-22 06:49:35.966712: val_loss -0.7682 +2024-11-22 06:49:35.966815: Pseudo dice [0.8561] +2024-11-22 06:49:35.966907: Epoch time: 19.78 s +2024-11-22 06:49:36.813750: +2024-11-22 06:49:36.813973: Epoch 3616 +2024-11-22 06:49:36.814090: Current learning rate: 0.00582 +2024-11-22 06:49:55.843311: train_loss -0.7832 +2024-11-22 06:49:55.857776: val_loss -0.7752 +2024-11-22 06:49:55.857887: Pseudo dice [0.8505] +2024-11-22 06:49:55.858034: Epoch time: 19.03 s +2024-11-22 06:49:56.715946: +2024-11-22 06:49:56.716179: Epoch 3617 +2024-11-22 06:49:56.716294: Current learning rate: 0.00582 +2024-11-22 06:50:16.058170: train_loss -0.7828 +2024-11-22 06:50:16.064273: val_loss -0.7521 +2024-11-22 06:50:16.064404: Pseudo dice [0.8535] +2024-11-22 06:50:16.064596: Epoch time: 19.34 s +2024-11-22 06:50:16.948867: +2024-11-22 06:50:16.949085: Epoch 3618 +2024-11-22 06:50:16.949199: Current learning rate: 0.00582 +2024-11-22 06:50:36.059279: train_loss -0.7827 +2024-11-22 06:50:36.071657: val_loss -0.7643 +2024-11-22 06:50:36.071805: Pseudo dice [0.8681] +2024-11-22 06:50:36.071903: Epoch time: 19.11 s +2024-11-22 06:50:36.941952: +2024-11-22 06:50:36.942183: Epoch 3619 +2024-11-22 06:50:36.942298: Current learning rate: 0.00582 +2024-11-22 06:50:55.165087: train_loss -0.7768 +2024-11-22 06:50:55.167372: val_loss -0.7478 +2024-11-22 06:50:55.167465: Pseudo dice [0.8448] +2024-11-22 06:50:55.167551: Epoch time: 18.22 s +2024-11-22 06:50:56.014358: +2024-11-22 06:50:56.014563: Epoch 3620 +2024-11-22 06:50:56.014670: Current learning rate: 0.00581 +2024-11-22 06:51:13.614514: train_loss -0.7895 +2024-11-22 06:51:13.621168: val_loss -0.7514 +2024-11-22 06:51:13.621294: Pseudo dice [0.8464] +2024-11-22 06:51:13.621379: Epoch time: 17.6 s +2024-11-22 06:51:14.550995: +2024-11-22 06:51:14.551198: Epoch 3621 +2024-11-22 06:51:14.551307: Current learning rate: 0.00581 +2024-11-22 06:51:34.039130: train_loss -0.7865 +2024-11-22 06:51:34.041403: val_loss -0.7768 +2024-11-22 06:51:34.041526: Pseudo dice [0.8562] +2024-11-22 06:51:34.041600: Epoch time: 19.49 s +2024-11-22 06:51:35.075303: +2024-11-22 06:51:35.075513: Epoch 3622 +2024-11-22 06:51:35.075624: Current learning rate: 0.00581 +2024-11-22 06:51:54.750542: train_loss -0.7917 +2024-11-22 06:51:54.753567: val_loss -0.7748 +2024-11-22 06:51:54.753702: Pseudo dice [0.8428] +2024-11-22 06:51:54.753793: Epoch time: 19.68 s +2024-11-22 06:51:55.635808: +2024-11-22 06:51:55.635998: Epoch 3623 +2024-11-22 06:51:55.636115: Current learning rate: 0.00581 +2024-11-22 06:52:14.927115: train_loss -0.793 +2024-11-22 06:52:14.942024: val_loss -0.7565 +2024-11-22 06:52:14.942179: Pseudo dice [0.8567] +2024-11-22 06:52:14.942265: Epoch time: 19.29 s +2024-11-22 06:52:16.387701: +2024-11-22 06:52:16.387933: Epoch 3624 +2024-11-22 06:52:16.388051: Current learning rate: 0.00581 +2024-11-22 06:52:35.625660: train_loss -0.7828 +2024-11-22 06:52:35.632391: val_loss -0.7643 +2024-11-22 06:52:35.632533: Pseudo dice [0.8414] +2024-11-22 06:52:35.632631: Epoch time: 19.24 s +2024-11-22 06:52:36.628549: +2024-11-22 06:52:36.628795: Epoch 3625 +2024-11-22 06:52:36.628917: Current learning rate: 0.00581 +2024-11-22 06:52:55.551747: train_loss -0.7869 +2024-11-22 06:52:55.555412: val_loss -0.7715 +2024-11-22 06:52:55.555621: Pseudo dice [0.8465] +2024-11-22 06:52:55.555716: Epoch time: 18.92 s +2024-11-22 06:52:56.490283: +2024-11-22 06:52:56.490493: Epoch 3626 +2024-11-22 06:52:56.490607: Current learning rate: 0.00581 +2024-11-22 06:53:15.555344: train_loss -0.7822 +2024-11-22 06:53:15.558715: val_loss -0.777 +2024-11-22 06:53:15.558828: Pseudo dice [0.8584] +2024-11-22 06:53:15.558912: Epoch time: 19.07 s +2024-11-22 06:53:16.409138: +2024-11-22 06:53:16.409388: Epoch 3627 +2024-11-22 06:53:16.409511: Current learning rate: 0.00581 +2024-11-22 06:53:35.623881: train_loss -0.7775 +2024-11-22 06:53:35.659276: val_loss -0.7723 +2024-11-22 06:53:35.659454: Pseudo dice [0.8464] +2024-11-22 06:53:35.659542: Epoch time: 19.22 s +2024-11-22 06:53:36.616066: +2024-11-22 06:53:36.616286: Epoch 3628 +2024-11-22 06:53:36.616396: Current learning rate: 0.00581 +2024-11-22 06:53:55.536006: train_loss -0.7844 +2024-11-22 06:53:55.545378: val_loss -0.7819 +2024-11-22 06:53:55.545508: Pseudo dice [0.8487] +2024-11-22 06:53:55.545595: Epoch time: 18.92 s +2024-11-22 06:53:56.559737: +2024-11-22 06:53:56.559971: Epoch 3629 +2024-11-22 06:53:56.560096: Current learning rate: 0.0058 +2024-11-22 06:54:16.609353: train_loss -0.783 +2024-11-22 06:54:16.615423: val_loss -0.7844 +2024-11-22 06:54:16.615545: Pseudo dice [0.86] +2024-11-22 06:54:16.615629: Epoch time: 20.05 s +2024-11-22 06:54:17.476094: +2024-11-22 06:54:17.476301: Epoch 3630 +2024-11-22 06:54:17.476415: Current learning rate: 0.0058 +2024-11-22 06:54:36.533584: train_loss -0.7744 +2024-11-22 06:54:36.559248: val_loss -0.7758 +2024-11-22 06:54:36.559399: Pseudo dice [0.85] +2024-11-22 06:54:36.559494: Epoch time: 19.06 s +2024-11-22 06:54:37.605571: +2024-11-22 06:54:37.605769: Epoch 3631 +2024-11-22 06:54:37.605883: Current learning rate: 0.0058 +2024-11-22 06:54:56.741976: train_loss -0.7768 +2024-11-22 06:54:56.748889: val_loss -0.7963 +2024-11-22 06:54:56.749021: Pseudo dice [0.8619] +2024-11-22 06:54:56.749127: Epoch time: 19.14 s +2024-11-22 06:54:57.761467: +2024-11-22 06:54:57.761687: Epoch 3632 +2024-11-22 06:54:57.761797: Current learning rate: 0.0058 +2024-11-22 06:55:16.098774: train_loss -0.7794 +2024-11-22 06:55:16.107851: val_loss -0.7646 +2024-11-22 06:55:16.107965: Pseudo dice [0.8574] +2024-11-22 06:55:16.108050: Epoch time: 18.34 s +2024-11-22 06:55:17.022910: +2024-11-22 06:55:17.023103: Epoch 3633 +2024-11-22 06:55:17.023217: Current learning rate: 0.0058 +2024-11-22 06:55:35.821277: train_loss -0.7879 +2024-11-22 06:55:35.823766: val_loss -0.7856 +2024-11-22 06:55:35.823914: Pseudo dice [0.8564] +2024-11-22 06:55:35.824012: Epoch time: 18.8 s +2024-11-22 06:55:36.670352: +2024-11-22 06:55:36.670598: Epoch 3634 +2024-11-22 06:55:36.670714: Current learning rate: 0.0058 +2024-11-22 06:55:56.628279: train_loss -0.7773 +2024-11-22 06:55:56.635541: val_loss -0.7432 +2024-11-22 06:55:56.635670: Pseudo dice [0.8446] +2024-11-22 06:55:56.635758: Epoch time: 19.96 s +2024-11-22 06:55:57.888270: +2024-11-22 06:55:57.888467: Epoch 3635 +2024-11-22 06:55:57.888574: Current learning rate: 0.0058 +2024-11-22 06:56:16.463000: train_loss -0.7843 +2024-11-22 06:56:16.477860: val_loss -0.7732 +2024-11-22 06:56:16.478014: Pseudo dice [0.8464] +2024-11-22 06:56:16.478198: Epoch time: 18.58 s +2024-11-22 06:56:17.413866: +2024-11-22 06:56:17.414338: Epoch 3636 +2024-11-22 06:56:17.414474: Current learning rate: 0.0058 +2024-11-22 06:56:35.834161: train_loss -0.7812 +2024-11-22 06:56:35.839156: val_loss -0.7509 +2024-11-22 06:56:35.839293: Pseudo dice [0.8305] +2024-11-22 06:56:35.839375: Epoch time: 18.42 s +2024-11-22 06:56:36.711920: +2024-11-22 06:56:36.712375: Epoch 3637 +2024-11-22 06:56:36.712515: Current learning rate: 0.00579 +2024-11-22 06:56:56.198335: train_loss -0.7661 +2024-11-22 06:56:56.204919: val_loss -0.7712 +2024-11-22 06:56:56.205068: Pseudo dice [0.8487] +2024-11-22 06:56:56.205154: Epoch time: 19.49 s +2024-11-22 06:56:57.063834: +2024-11-22 06:56:57.064273: Epoch 3638 +2024-11-22 06:56:57.064412: Current learning rate: 0.00579 +2024-11-22 06:57:15.594977: train_loss -0.7826 +2024-11-22 06:57:15.598768: val_loss -0.7861 +2024-11-22 06:57:15.598930: Pseudo dice [0.8643] +2024-11-22 06:57:15.599010: Epoch time: 18.53 s +2024-11-22 06:57:16.500732: +2024-11-22 06:57:16.501182: Epoch 3639 +2024-11-22 06:57:16.501315: Current learning rate: 0.00579 +2024-11-22 06:57:35.940487: train_loss -0.7807 +2024-11-22 06:57:35.949082: val_loss -0.7718 +2024-11-22 06:57:35.949220: Pseudo dice [0.8586] +2024-11-22 06:57:35.949320: Epoch time: 19.44 s +2024-11-22 06:57:36.877126: +2024-11-22 06:57:36.877515: Epoch 3640 +2024-11-22 06:57:36.877850: Current learning rate: 0.00579 +2024-11-22 06:57:55.396461: train_loss -0.7781 +2024-11-22 06:57:55.408866: val_loss -0.7075 +2024-11-22 06:57:55.409002: Pseudo dice [0.82] +2024-11-22 06:57:55.409112: Epoch time: 18.52 s +2024-11-22 06:57:56.500322: +2024-11-22 06:57:56.500747: Epoch 3641 +2024-11-22 06:57:56.500885: Current learning rate: 0.00579 +2024-11-22 06:58:15.975628: train_loss -0.7594 +2024-11-22 06:58:15.983775: val_loss -0.7681 +2024-11-22 06:58:15.983918: Pseudo dice [0.8424] +2024-11-22 06:58:15.984005: Epoch time: 19.48 s +2024-11-22 06:58:16.894865: +2024-11-22 06:58:16.895329: Epoch 3642 +2024-11-22 06:58:16.895470: Current learning rate: 0.00579 +2024-11-22 06:58:36.394391: train_loss -0.7782 +2024-11-22 06:58:36.400705: val_loss -0.7793 +2024-11-22 06:58:36.400822: Pseudo dice [0.8483] +2024-11-22 06:58:36.400911: Epoch time: 19.5 s +2024-11-22 06:58:37.360577: +2024-11-22 06:58:37.361029: Epoch 3643 +2024-11-22 06:58:37.361171: Current learning rate: 0.00579 +2024-11-22 06:58:55.092131: train_loss -0.7728 +2024-11-22 06:58:55.098615: val_loss -0.7496 +2024-11-22 06:58:55.104909: Pseudo dice [0.8358] +2024-11-22 06:58:55.105022: Epoch time: 17.73 s +2024-11-22 06:58:56.098963: +2024-11-22 06:58:56.099397: Epoch 3644 +2024-11-22 06:58:56.099541: Current learning rate: 0.00579 +2024-11-22 06:59:14.886084: train_loss -0.7689 +2024-11-22 06:59:14.890771: val_loss -0.7843 +2024-11-22 06:59:14.890910: Pseudo dice [0.8513] +2024-11-22 06:59:14.891085: Epoch time: 18.79 s +2024-11-22 06:59:15.760230: +2024-11-22 06:59:15.760628: Epoch 3645 +2024-11-22 06:59:15.760758: Current learning rate: 0.00579 +2024-11-22 06:59:35.306005: train_loss -0.7534 +2024-11-22 06:59:35.314596: val_loss -0.7514 +2024-11-22 06:59:35.314751: Pseudo dice [0.8311] +2024-11-22 06:59:35.314899: Epoch time: 19.55 s +2024-11-22 06:59:36.301789: +2024-11-22 06:59:36.301988: Epoch 3646 +2024-11-22 06:59:36.302107: Current learning rate: 0.00578 +2024-11-22 06:59:55.987821: train_loss -0.7557 +2024-11-22 06:59:55.989849: val_loss -0.7474 +2024-11-22 06:59:55.989942: Pseudo dice [0.8285] +2024-11-22 06:59:55.990016: Epoch time: 19.69 s +2024-11-22 06:59:57.236651: +2024-11-22 06:59:57.237086: Epoch 3647 +2024-11-22 06:59:57.237223: Current learning rate: 0.00578 +2024-11-22 07:00:16.449051: train_loss -0.7646 +2024-11-22 07:00:16.455353: val_loss -0.7639 +2024-11-22 07:00:16.455485: Pseudo dice [0.8468] +2024-11-22 07:00:16.455579: Epoch time: 19.21 s +2024-11-22 07:00:17.334854: +2024-11-22 07:00:17.335304: Epoch 3648 +2024-11-22 07:00:17.335441: Current learning rate: 0.00578 +2024-11-22 07:00:36.423969: train_loss -0.7675 +2024-11-22 07:00:36.428529: val_loss -0.7654 +2024-11-22 07:00:36.428635: Pseudo dice [0.8348] +2024-11-22 07:00:36.428712: Epoch time: 19.09 s +2024-11-22 07:00:37.477254: +2024-11-22 07:00:37.477685: Epoch 3649 +2024-11-22 07:00:37.477817: Current learning rate: 0.00578 +2024-11-22 07:00:56.154310: train_loss -0.7702 +2024-11-22 07:00:56.156596: val_loss -0.7394 +2024-11-22 07:00:56.156693: Pseudo dice [0.8485] +2024-11-22 07:00:56.156818: Epoch time: 18.68 s +2024-11-22 07:00:57.267372: +2024-11-22 07:00:57.267798: Epoch 3650 +2024-11-22 07:00:57.267923: Current learning rate: 0.00578 +2024-11-22 07:01:17.012342: train_loss -0.7592 +2024-11-22 07:01:17.015064: val_loss -0.7587 +2024-11-22 07:01:17.015192: Pseudo dice [0.8509] +2024-11-22 07:01:17.015276: Epoch time: 19.75 s +2024-11-22 07:01:17.989206: +2024-11-22 07:01:17.989633: Epoch 3651 +2024-11-22 07:01:17.989765: Current learning rate: 0.00578 +2024-11-22 07:01:36.242974: train_loss -0.7558 +2024-11-22 07:01:36.253035: val_loss -0.7859 +2024-11-22 07:01:36.253178: Pseudo dice [0.8548] +2024-11-22 07:01:36.253282: Epoch time: 18.25 s +2024-11-22 07:01:37.274787: +2024-11-22 07:01:37.275208: Epoch 3652 +2024-11-22 07:01:37.275344: Current learning rate: 0.00578 +2024-11-22 07:01:56.423645: train_loss -0.7615 +2024-11-22 07:01:56.430877: val_loss -0.7367 +2024-11-22 07:01:56.430991: Pseudo dice [0.8319] +2024-11-22 07:01:56.431081: Epoch time: 19.15 s +2024-11-22 07:01:57.325322: +2024-11-22 07:01:57.325733: Epoch 3653 +2024-11-22 07:01:57.325869: Current learning rate: 0.00578 +2024-11-22 07:02:15.683539: train_loss -0.7625 +2024-11-22 07:02:15.685118: val_loss -0.766 +2024-11-22 07:02:15.685238: Pseudo dice [0.8582] +2024-11-22 07:02:15.685319: Epoch time: 18.36 s +2024-11-22 07:02:16.536725: +2024-11-22 07:02:16.537163: Epoch 3654 +2024-11-22 07:02:16.537302: Current learning rate: 0.00577 +2024-11-22 07:02:36.473752: train_loss -0.7774 +2024-11-22 07:02:36.476481: val_loss -0.7731 +2024-11-22 07:02:36.476653: Pseudo dice [0.8503] +2024-11-22 07:02:36.476758: Epoch time: 19.94 s +2024-11-22 07:02:37.326638: +2024-11-22 07:02:37.327043: Epoch 3655 +2024-11-22 07:02:37.327177: Current learning rate: 0.00577 +2024-11-22 07:02:56.286832: train_loss -0.7725 +2024-11-22 07:02:56.292360: val_loss -0.7676 +2024-11-22 07:02:56.292492: Pseudo dice [0.8525] +2024-11-22 07:02:56.292585: Epoch time: 18.96 s +2024-11-22 07:02:57.171221: +2024-11-22 07:02:57.171646: Epoch 3656 +2024-11-22 07:02:57.171783: Current learning rate: 0.00577 +2024-11-22 07:03:16.069035: train_loss -0.7689 +2024-11-22 07:03:16.070895: val_loss -0.7765 +2024-11-22 07:03:16.071019: Pseudo dice [0.8488] +2024-11-22 07:03:16.071103: Epoch time: 18.9 s +2024-11-22 07:03:16.910583: +2024-11-22 07:03:16.910991: Epoch 3657 +2024-11-22 07:03:16.911127: Current learning rate: 0.00577 +2024-11-22 07:03:36.159340: train_loss -0.7601 +2024-11-22 07:03:36.171176: val_loss -0.7628 +2024-11-22 07:03:36.171364: Pseudo dice [0.8456] +2024-11-22 07:03:36.171455: Epoch time: 19.25 s +2024-11-22 07:03:37.012568: +2024-11-22 07:03:37.012779: Epoch 3658 +2024-11-22 07:03:37.012896: Current learning rate: 0.00577 +2024-11-22 07:03:55.607248: train_loss -0.7732 +2024-11-22 07:03:55.614357: val_loss -0.7591 +2024-11-22 07:03:55.614474: Pseudo dice [0.8402] +2024-11-22 07:03:55.614556: Epoch time: 18.6 s +2024-11-22 07:03:56.838392: +2024-11-22 07:03:56.838863: Epoch 3659 +2024-11-22 07:03:56.838996: Current learning rate: 0.00577 +2024-11-22 07:04:16.410154: train_loss -0.7703 +2024-11-22 07:04:16.416796: val_loss -0.7723 +2024-11-22 07:04:16.416932: Pseudo dice [0.8385] +2024-11-22 07:04:16.417028: Epoch time: 19.57 s +2024-11-22 07:04:17.338433: +2024-11-22 07:04:17.338842: Epoch 3660 +2024-11-22 07:04:17.338975: Current learning rate: 0.00577 +2024-11-22 07:04:35.587671: train_loss -0.7834 +2024-11-22 07:04:35.592090: val_loss -0.7714 +2024-11-22 07:04:35.592201: Pseudo dice [0.8499] +2024-11-22 07:04:35.592289: Epoch time: 18.25 s +2024-11-22 07:04:36.437529: +2024-11-22 07:04:36.437939: Epoch 3661 +2024-11-22 07:04:36.438073: Current learning rate: 0.00577 +2024-11-22 07:04:55.775599: train_loss -0.778 +2024-11-22 07:04:55.790332: val_loss -0.7815 +2024-11-22 07:04:55.790491: Pseudo dice [0.8514] +2024-11-22 07:04:55.790579: Epoch time: 19.34 s +2024-11-22 07:04:56.771719: +2024-11-22 07:04:56.772144: Epoch 3662 +2024-11-22 07:04:56.772284: Current learning rate: 0.00576 +2024-11-22 07:05:14.958477: train_loss -0.7742 +2024-11-22 07:05:14.960939: val_loss -0.7562 +2024-11-22 07:05:14.961041: Pseudo dice [0.8409] +2024-11-22 07:05:14.961136: Epoch time: 18.19 s +2024-11-22 07:05:16.013379: +2024-11-22 07:05:16.013804: Epoch 3663 +2024-11-22 07:05:16.013935: Current learning rate: 0.00576 +2024-11-22 07:05:34.797567: train_loss -0.784 +2024-11-22 07:05:34.799158: val_loss -0.7754 +2024-11-22 07:05:34.799249: Pseudo dice [0.8517] +2024-11-22 07:05:34.799332: Epoch time: 18.78 s +2024-11-22 07:05:35.641412: +2024-11-22 07:05:35.641825: Epoch 3664 +2024-11-22 07:05:35.641960: Current learning rate: 0.00576 +2024-11-22 07:05:55.082296: train_loss -0.785 +2024-11-22 07:05:55.087651: val_loss -0.7646 +2024-11-22 07:05:55.087764: Pseudo dice [0.8487] +2024-11-22 07:05:55.087845: Epoch time: 19.44 s +2024-11-22 07:05:56.026597: +2024-11-22 07:05:56.027024: Epoch 3665 +2024-11-22 07:05:56.027163: Current learning rate: 0.00576 +2024-11-22 07:06:15.431756: train_loss -0.7806 +2024-11-22 07:06:15.435626: val_loss -0.7585 +2024-11-22 07:06:15.436971: Pseudo dice [0.8639] +2024-11-22 07:06:15.437098: Epoch time: 19.41 s +2024-11-22 07:06:16.313734: +2024-11-22 07:06:16.314153: Epoch 3666 +2024-11-22 07:06:16.314288: Current learning rate: 0.00576 +2024-11-22 07:06:34.689053: train_loss -0.7807 +2024-11-22 07:06:34.692786: val_loss -0.7659 +2024-11-22 07:06:34.692910: Pseudo dice [0.8314] +2024-11-22 07:06:34.693002: Epoch time: 18.38 s +2024-11-22 07:06:35.673100: +2024-11-22 07:06:35.673508: Epoch 3667 +2024-11-22 07:06:35.673641: Current learning rate: 0.00576 +2024-11-22 07:06:54.248878: train_loss -0.7719 +2024-11-22 07:06:54.252852: val_loss -0.7685 +2024-11-22 07:06:54.252960: Pseudo dice [0.8359] +2024-11-22 07:06:54.253037: Epoch time: 18.58 s +2024-11-22 07:06:55.185444: +2024-11-22 07:06:55.185871: Epoch 3668 +2024-11-22 07:06:55.186015: Current learning rate: 0.00576 +2024-11-22 07:07:13.571388: train_loss -0.7713 +2024-11-22 07:07:13.578417: val_loss -0.7854 +2024-11-22 07:07:13.578580: Pseudo dice [0.8483] +2024-11-22 07:07:13.578671: Epoch time: 18.39 s +2024-11-22 07:07:14.572052: +2024-11-22 07:07:14.572499: Epoch 3669 +2024-11-22 07:07:14.572628: Current learning rate: 0.00576 +2024-11-22 07:07:33.724567: train_loss -0.7759 +2024-11-22 07:07:33.753818: val_loss -0.7392 +2024-11-22 07:07:33.753971: Pseudo dice [0.8429] +2024-11-22 07:07:33.754069: Epoch time: 19.15 s +2024-11-22 07:07:35.072427: +2024-11-22 07:07:35.072855: Epoch 3670 +2024-11-22 07:07:35.072998: Current learning rate: 0.00576 +2024-11-22 07:07:54.184558: train_loss -0.7867 +2024-11-22 07:07:54.186567: val_loss -0.7821 +2024-11-22 07:07:54.186668: Pseudo dice [0.8395] +2024-11-22 07:07:54.186755: Epoch time: 19.11 s +2024-11-22 07:07:55.032039: +2024-11-22 07:07:55.032482: Epoch 3671 +2024-11-22 07:07:55.032623: Current learning rate: 0.00575 +2024-11-22 07:08:13.657727: train_loss -0.782 +2024-11-22 07:08:13.664839: val_loss -0.7701 +2024-11-22 07:08:13.664968: Pseudo dice [0.854] +2024-11-22 07:08:13.665052: Epoch time: 18.63 s +2024-11-22 07:08:14.674012: +2024-11-22 07:08:14.674465: Epoch 3672 +2024-11-22 07:08:14.674595: Current learning rate: 0.00575 +2024-11-22 07:08:34.747977: train_loss -0.7717 +2024-11-22 07:08:34.752802: val_loss -0.7544 +2024-11-22 07:08:34.752942: Pseudo dice [0.8545] +2024-11-22 07:08:34.753026: Epoch time: 20.07 s +2024-11-22 07:08:35.613624: +2024-11-22 07:08:35.614035: Epoch 3673 +2024-11-22 07:08:35.614176: Current learning rate: 0.00575 +2024-11-22 07:08:55.509238: train_loss -0.7873 +2024-11-22 07:08:55.513588: val_loss -0.7405 +2024-11-22 07:08:55.513718: Pseudo dice [0.8488] +2024-11-22 07:08:55.513798: Epoch time: 19.9 s +2024-11-22 07:08:56.365648: +2024-11-22 07:08:56.366121: Epoch 3674 +2024-11-22 07:08:56.366302: Current learning rate: 0.00575 +2024-11-22 07:09:15.400537: train_loss -0.7853 +2024-11-22 07:09:15.415808: val_loss -0.7712 +2024-11-22 07:09:15.415936: Pseudo dice [0.8654] +2024-11-22 07:09:15.416038: Epoch time: 19.04 s +2024-11-22 07:09:16.267575: +2024-11-22 07:09:16.268009: Epoch 3675 +2024-11-22 07:09:16.268149: Current learning rate: 0.00575 +2024-11-22 07:09:35.867029: train_loss -0.7758 +2024-11-22 07:09:35.868635: val_loss -0.7717 +2024-11-22 07:09:35.868833: Pseudo dice [0.8607] +2024-11-22 07:09:35.868918: Epoch time: 19.6 s +2024-11-22 07:09:36.742303: +2024-11-22 07:09:36.742702: Epoch 3676 +2024-11-22 07:09:36.742841: Current learning rate: 0.00575 +2024-11-22 07:09:55.234563: train_loss -0.7886 +2024-11-22 07:09:55.236444: val_loss -0.7709 +2024-11-22 07:09:55.236537: Pseudo dice [0.8607] +2024-11-22 07:09:55.236614: Epoch time: 18.49 s +2024-11-22 07:09:56.084841: +2024-11-22 07:09:56.085256: Epoch 3677 +2024-11-22 07:09:56.085390: Current learning rate: 0.00575 +2024-11-22 07:10:14.746017: train_loss -0.7803 +2024-11-22 07:10:14.748322: val_loss -0.7795 +2024-11-22 07:10:14.748436: Pseudo dice [0.8544] +2024-11-22 07:10:14.748523: Epoch time: 18.66 s +2024-11-22 07:10:15.600169: +2024-11-22 07:10:15.600601: Epoch 3678 +2024-11-22 07:10:15.600734: Current learning rate: 0.00575 +2024-11-22 07:10:32.830698: train_loss -0.7914 +2024-11-22 07:10:32.837655: val_loss -0.7679 +2024-11-22 07:10:32.837781: Pseudo dice [0.853] +2024-11-22 07:10:32.837871: Epoch time: 17.23 s +2024-11-22 07:10:33.890452: +2024-11-22 07:10:33.890900: Epoch 3679 +2024-11-22 07:10:33.891037: Current learning rate: 0.00574 +2024-11-22 07:10:53.389876: train_loss -0.7839 +2024-11-22 07:10:53.397607: val_loss -0.7796 +2024-11-22 07:10:53.397724: Pseudo dice [0.8516] +2024-11-22 07:10:53.397804: Epoch time: 19.5 s +2024-11-22 07:10:54.336313: +2024-11-22 07:10:54.336734: Epoch 3680 +2024-11-22 07:10:54.336878: Current learning rate: 0.00574 +2024-11-22 07:11:13.692714: train_loss -0.7777 +2024-11-22 07:11:13.697994: val_loss -0.7618 +2024-11-22 07:11:13.698134: Pseudo dice [0.8506] +2024-11-22 07:11:13.698219: Epoch time: 19.36 s +2024-11-22 07:11:14.953744: +2024-11-22 07:11:14.954255: Epoch 3681 +2024-11-22 07:11:14.954372: Current learning rate: 0.00574 +2024-11-22 07:11:34.454712: train_loss -0.778 +2024-11-22 07:11:34.463117: val_loss -0.7748 +2024-11-22 07:11:34.464639: Pseudo dice [0.8364] +2024-11-22 07:11:34.464803: Epoch time: 19.5 s +2024-11-22 07:11:35.326086: +2024-11-22 07:11:35.326527: Epoch 3682 +2024-11-22 07:11:35.326659: Current learning rate: 0.00574 +2024-11-22 07:11:54.849364: train_loss -0.7763 +2024-11-22 07:11:54.855897: val_loss -0.7447 +2024-11-22 07:11:54.856023: Pseudo dice [0.8384] +2024-11-22 07:11:54.856120: Epoch time: 19.52 s +2024-11-22 07:11:55.707689: +2024-11-22 07:11:55.708178: Epoch 3683 +2024-11-22 07:11:55.708314: Current learning rate: 0.00574 +2024-11-22 07:12:14.533440: train_loss -0.781 +2024-11-22 07:12:14.535053: val_loss -0.7305 +2024-11-22 07:12:14.535177: Pseudo dice [0.8307] +2024-11-22 07:12:14.535264: Epoch time: 18.83 s +2024-11-22 07:12:15.379203: +2024-11-22 07:12:15.379654: Epoch 3684 +2024-11-22 07:12:15.379786: Current learning rate: 0.00574 +2024-11-22 07:12:35.079748: train_loss -0.773 +2024-11-22 07:12:35.087242: val_loss -0.7579 +2024-11-22 07:12:35.087352: Pseudo dice [0.8465] +2024-11-22 07:12:35.087431: Epoch time: 19.7 s +2024-11-22 07:12:36.240947: +2024-11-22 07:12:36.241402: Epoch 3685 +2024-11-22 07:12:36.241546: Current learning rate: 0.00574 +2024-11-22 07:12:55.139593: train_loss -0.7871 +2024-11-22 07:12:55.141785: val_loss -0.7378 +2024-11-22 07:12:55.141917: Pseudo dice [0.8489] +2024-11-22 07:12:55.142018: Epoch time: 18.9 s +2024-11-22 07:12:55.992255: +2024-11-22 07:12:55.992683: Epoch 3686 +2024-11-22 07:12:55.992815: Current learning rate: 0.00574 +2024-11-22 07:13:14.358458: train_loss -0.7713 +2024-11-22 07:13:14.366201: val_loss -0.7413 +2024-11-22 07:13:14.366318: Pseudo dice [0.8391] +2024-11-22 07:13:14.366401: Epoch time: 18.37 s +2024-11-22 07:13:15.299170: +2024-11-22 07:13:15.299614: Epoch 3687 +2024-11-22 07:13:15.299754: Current learning rate: 0.00573 +2024-11-22 07:13:34.448540: train_loss -0.7744 +2024-11-22 07:13:34.453804: val_loss -0.7614 +2024-11-22 07:13:34.453937: Pseudo dice [0.8611] +2024-11-22 07:13:34.454022: Epoch time: 19.15 s +2024-11-22 07:13:35.316901: +2024-11-22 07:13:35.317319: Epoch 3688 +2024-11-22 07:13:35.317461: Current learning rate: 0.00573 +2024-11-22 07:13:53.581437: train_loss -0.7755 +2024-11-22 07:13:53.588493: val_loss -0.7954 +2024-11-22 07:13:53.588609: Pseudo dice [0.8556] +2024-11-22 07:13:53.588696: Epoch time: 18.27 s +2024-11-22 07:13:54.609763: +2024-11-22 07:13:54.610179: Epoch 3689 +2024-11-22 07:13:54.610308: Current learning rate: 0.00573 +2024-11-22 07:14:13.375961: train_loss -0.7714 +2024-11-22 07:14:13.378651: val_loss -0.7609 +2024-11-22 07:14:13.378754: Pseudo dice [0.8445] +2024-11-22 07:14:13.378842: Epoch time: 18.77 s +2024-11-22 07:14:14.222635: +2024-11-22 07:14:14.223026: Epoch 3690 +2024-11-22 07:14:14.223163: Current learning rate: 0.00573 +2024-11-22 07:14:32.409858: train_loss -0.775 +2024-11-22 07:14:32.416667: val_loss -0.7879 +2024-11-22 07:14:32.416813: Pseudo dice [0.8668] +2024-11-22 07:14:32.416900: Epoch time: 18.19 s +2024-11-22 07:14:33.263466: +2024-11-22 07:14:33.263889: Epoch 3691 +2024-11-22 07:14:33.264022: Current learning rate: 0.00573 +2024-11-22 07:14:52.637456: train_loss -0.7847 +2024-11-22 07:14:52.644177: val_loss -0.7773 +2024-11-22 07:14:52.644317: Pseudo dice [0.8625] +2024-11-22 07:14:52.644403: Epoch time: 19.37 s +2024-11-22 07:14:53.511174: +2024-11-22 07:14:53.511373: Epoch 3692 +2024-11-22 07:14:53.511482: Current learning rate: 0.00573 +2024-11-22 07:15:12.604737: train_loss -0.7787 +2024-11-22 07:15:12.609834: val_loss -0.7705 +2024-11-22 07:15:12.609990: Pseudo dice [0.868] +2024-11-22 07:15:12.610081: Epoch time: 19.09 s +2024-11-22 07:15:13.858515: +2024-11-22 07:15:13.858728: Epoch 3693 +2024-11-22 07:15:13.858847: Current learning rate: 0.00573 +2024-11-22 07:15:31.921650: train_loss -0.7894 +2024-11-22 07:15:31.926086: val_loss -0.7765 +2024-11-22 07:15:31.926244: Pseudo dice [0.8437] +2024-11-22 07:15:31.926329: Epoch time: 18.06 s +2024-11-22 07:15:32.785898: +2024-11-22 07:15:32.786136: Epoch 3694 +2024-11-22 07:15:32.786262: Current learning rate: 0.00573 +2024-11-22 07:15:52.528857: train_loss -0.7752 +2024-11-22 07:15:52.532206: val_loss -0.767 +2024-11-22 07:15:52.532340: Pseudo dice [0.8536] +2024-11-22 07:15:52.532437: Epoch time: 19.74 s +2024-11-22 07:15:53.378027: +2024-11-22 07:15:53.378252: Epoch 3695 +2024-11-22 07:15:53.378383: Current learning rate: 0.00573 +2024-11-22 07:16:12.528820: train_loss -0.7803 +2024-11-22 07:16:12.534765: val_loss -0.7662 +2024-11-22 07:16:12.534899: Pseudo dice [0.8418] +2024-11-22 07:16:12.534982: Epoch time: 19.15 s +2024-11-22 07:16:13.402405: +2024-11-22 07:16:13.402627: Epoch 3696 +2024-11-22 07:16:13.402743: Current learning rate: 0.00572 +2024-11-22 07:16:32.141622: train_loss -0.7741 +2024-11-22 07:16:32.148035: val_loss -0.7836 +2024-11-22 07:16:32.148257: Pseudo dice [0.8685] +2024-11-22 07:16:32.148352: Epoch time: 18.74 s +2024-11-22 07:16:33.023772: +2024-11-22 07:16:33.023991: Epoch 3697 +2024-11-22 07:16:33.024107: Current learning rate: 0.00572 +2024-11-22 07:16:52.469745: train_loss -0.7937 +2024-11-22 07:16:52.471292: val_loss -0.7559 +2024-11-22 07:16:52.471442: Pseudo dice [0.8464] +2024-11-22 07:16:52.471524: Epoch time: 19.45 s +2024-11-22 07:16:53.457184: +2024-11-22 07:16:53.457392: Epoch 3698 +2024-11-22 07:16:53.457503: Current learning rate: 0.00572 +2024-11-22 07:17:11.762233: train_loss -0.7846 +2024-11-22 07:17:11.765150: val_loss -0.7404 +2024-11-22 07:17:11.765255: Pseudo dice [0.8563] +2024-11-22 07:17:11.765330: Epoch time: 18.31 s +2024-11-22 07:17:12.643005: +2024-11-22 07:17:12.643226: Epoch 3699 +2024-11-22 07:17:12.643337: Current learning rate: 0.00572 +2024-11-22 07:17:32.076808: train_loss -0.7828 +2024-11-22 07:17:32.078281: val_loss -0.7703 +2024-11-22 07:17:32.078379: Pseudo dice [0.8517] +2024-11-22 07:17:32.078459: Epoch time: 19.43 s +2024-11-22 07:17:33.170343: +2024-11-22 07:17:33.170545: Epoch 3700 +2024-11-22 07:17:33.170656: Current learning rate: 0.00572 +2024-11-22 07:17:52.846419: train_loss -0.7765 +2024-11-22 07:17:52.852557: val_loss -0.7881 +2024-11-22 07:17:52.852688: Pseudo dice [0.8564] +2024-11-22 07:17:52.852774: Epoch time: 19.68 s +2024-11-22 07:17:53.859866: +2024-11-22 07:17:53.860084: Epoch 3701 +2024-11-22 07:17:53.860193: Current learning rate: 0.00572 +2024-11-22 07:18:12.461911: train_loss -0.7847 +2024-11-22 07:18:12.472952: val_loss -0.771 +2024-11-22 07:18:12.473091: Pseudo dice [0.8363] +2024-11-22 07:18:12.473185: Epoch time: 18.6 s +2024-11-22 07:18:13.316050: +2024-11-22 07:18:13.316301: Epoch 3702 +2024-11-22 07:18:13.316415: Current learning rate: 0.00572 +2024-11-22 07:18:32.439525: train_loss -0.78 +2024-11-22 07:18:32.451045: val_loss -0.7761 +2024-11-22 07:18:32.451185: Pseudo dice [0.8609] +2024-11-22 07:18:32.451412: Epoch time: 19.12 s +2024-11-22 07:18:33.330170: +2024-11-22 07:18:33.330385: Epoch 3703 +2024-11-22 07:18:33.330493: Current learning rate: 0.00572 +2024-11-22 07:18:52.299747: train_loss -0.7857 +2024-11-22 07:18:52.304730: val_loss -0.7784 +2024-11-22 07:18:52.305109: Pseudo dice [0.8482] +2024-11-22 07:18:52.305221: Epoch time: 18.97 s +2024-11-22 07:18:53.692119: +2024-11-22 07:18:53.692354: Epoch 3704 +2024-11-22 07:18:53.692472: Current learning rate: 0.00571 +2024-11-22 07:19:12.309221: train_loss -0.78 +2024-11-22 07:19:12.314710: val_loss -0.7776 +2024-11-22 07:19:12.314829: Pseudo dice [0.8489] +2024-11-22 07:19:12.314919: Epoch time: 18.62 s +2024-11-22 07:19:13.211926: +2024-11-22 07:19:13.212165: Epoch 3705 +2024-11-22 07:19:13.212284: Current learning rate: 0.00571 +2024-11-22 07:19:32.462144: train_loss -0.7669 +2024-11-22 07:19:32.471861: val_loss -0.7669 +2024-11-22 07:19:32.472000: Pseudo dice [0.8571] +2024-11-22 07:19:32.472089: Epoch time: 19.25 s +2024-11-22 07:19:33.330912: +2024-11-22 07:19:33.331168: Epoch 3706 +2024-11-22 07:19:33.331282: Current learning rate: 0.00571 +2024-11-22 07:19:52.192374: train_loss -0.7798 +2024-11-22 07:19:52.195772: val_loss -0.7795 +2024-11-22 07:19:52.195902: Pseudo dice [0.838] +2024-11-22 07:19:52.196020: Epoch time: 18.86 s +2024-11-22 07:19:53.251484: +2024-11-22 07:19:53.251710: Epoch 3707 +2024-11-22 07:19:53.251819: Current learning rate: 0.00571 +2024-11-22 07:20:12.734511: train_loss -0.7816 +2024-11-22 07:20:12.738715: val_loss -0.7898 +2024-11-22 07:20:12.738899: Pseudo dice [0.8537] +2024-11-22 07:20:12.739014: Epoch time: 19.48 s +2024-11-22 07:20:13.606564: +2024-11-22 07:20:13.606809: Epoch 3708 +2024-11-22 07:20:13.606921: Current learning rate: 0.00571 +2024-11-22 07:20:32.741125: train_loss -0.7869 +2024-11-22 07:20:32.742487: val_loss -0.7645 +2024-11-22 07:20:32.742575: Pseudo dice [0.8488] +2024-11-22 07:20:32.742657: Epoch time: 19.14 s +2024-11-22 07:20:33.587378: +2024-11-22 07:20:33.587572: Epoch 3709 +2024-11-22 07:20:33.587686: Current learning rate: 0.00571 +2024-11-22 07:20:52.054927: train_loss -0.7903 +2024-11-22 07:20:52.062629: val_loss -0.7361 +2024-11-22 07:20:52.062759: Pseudo dice [0.8299] +2024-11-22 07:20:52.062848: Epoch time: 18.47 s +2024-11-22 07:20:53.003844: +2024-11-22 07:20:53.004080: Epoch 3710 +2024-11-22 07:20:53.004197: Current learning rate: 0.00571 +2024-11-22 07:21:11.506613: train_loss -0.7571 +2024-11-22 07:21:11.508503: val_loss -0.777 +2024-11-22 07:21:11.508695: Pseudo dice [0.8449] +2024-11-22 07:21:11.508783: Epoch time: 18.5 s +2024-11-22 07:21:12.443150: +2024-11-22 07:21:12.443361: Epoch 3711 +2024-11-22 07:21:12.443479: Current learning rate: 0.00571 +2024-11-22 07:21:32.140419: train_loss -0.7664 +2024-11-22 07:21:32.142128: val_loss -0.7417 +2024-11-22 07:21:32.142227: Pseudo dice [0.8499] +2024-11-22 07:21:32.142310: Epoch time: 19.7 s +2024-11-22 07:21:33.026438: +2024-11-22 07:21:33.026666: Epoch 3712 +2024-11-22 07:21:33.026780: Current learning rate: 0.0057 +2024-11-22 07:21:52.214604: train_loss -0.7751 +2024-11-22 07:21:52.216509: val_loss -0.744 +2024-11-22 07:21:52.216598: Pseudo dice [0.8446] +2024-11-22 07:21:52.216678: Epoch time: 19.19 s +2024-11-22 07:21:53.057705: +2024-11-22 07:21:53.057933: Epoch 3713 +2024-11-22 07:21:53.058047: Current learning rate: 0.0057 +2024-11-22 07:22:11.588715: train_loss -0.7784 +2024-11-22 07:22:11.594082: val_loss -0.7675 +2024-11-22 07:22:11.594212: Pseudo dice [0.8554] +2024-11-22 07:22:11.594294: Epoch time: 18.53 s +2024-11-22 07:22:12.626362: +2024-11-22 07:22:12.626567: Epoch 3714 +2024-11-22 07:22:12.626676: Current learning rate: 0.0057 +2024-11-22 07:22:31.279938: train_loss -0.7816 +2024-11-22 07:22:31.290796: val_loss -0.7595 +2024-11-22 07:22:31.290927: Pseudo dice [0.8459] +2024-11-22 07:22:31.291007: Epoch time: 18.65 s +2024-11-22 07:22:32.312979: +2024-11-22 07:22:32.313200: Epoch 3715 +2024-11-22 07:22:32.313317: Current learning rate: 0.0057 +2024-11-22 07:22:51.532363: train_loss -0.7778 +2024-11-22 07:22:51.533972: val_loss -0.7824 +2024-11-22 07:22:51.534098: Pseudo dice [0.8681] +2024-11-22 07:22:51.534187: Epoch time: 19.22 s +2024-11-22 07:22:52.765643: +2024-11-22 07:22:52.765849: Epoch 3716 +2024-11-22 07:22:52.765965: Current learning rate: 0.0057 +2024-11-22 07:23:12.705933: train_loss -0.7831 +2024-11-22 07:23:12.709835: val_loss -0.7679 +2024-11-22 07:23:12.709965: Pseudo dice [0.8491] +2024-11-22 07:23:12.710045: Epoch time: 19.94 s +2024-11-22 07:23:13.609718: +2024-11-22 07:23:13.609946: Epoch 3717 +2024-11-22 07:23:13.610064: Current learning rate: 0.0057 +2024-11-22 07:23:32.007307: train_loss -0.7712 +2024-11-22 07:23:32.009692: val_loss -0.7541 +2024-11-22 07:23:32.009789: Pseudo dice [0.8423] +2024-11-22 07:23:32.009869: Epoch time: 18.4 s +2024-11-22 07:23:32.891001: +2024-11-22 07:23:32.891308: Epoch 3718 +2024-11-22 07:23:32.891435: Current learning rate: 0.0057 +2024-11-22 07:23:52.074130: train_loss -0.781 +2024-11-22 07:23:52.076597: val_loss -0.787 +2024-11-22 07:23:52.076711: Pseudo dice [0.8659] +2024-11-22 07:23:52.076827: Epoch time: 19.18 s +2024-11-22 07:23:53.058546: +2024-11-22 07:23:53.058758: Epoch 3719 +2024-11-22 07:23:53.058878: Current learning rate: 0.0057 +2024-11-22 07:24:11.781705: train_loss -0.7822 +2024-11-22 07:24:11.788726: val_loss -0.7907 +2024-11-22 07:24:11.788854: Pseudo dice [0.8613] +2024-11-22 07:24:11.788937: Epoch time: 18.72 s +2024-11-22 07:24:12.653467: +2024-11-22 07:24:12.653716: Epoch 3720 +2024-11-22 07:24:12.653831: Current learning rate: 0.0057 +2024-11-22 07:24:32.407555: train_loss -0.7807 +2024-11-22 07:24:32.413405: val_loss -0.7627 +2024-11-22 07:24:32.413538: Pseudo dice [0.8525] +2024-11-22 07:24:32.413616: Epoch time: 19.75 s +2024-11-22 07:24:33.266454: +2024-11-22 07:24:33.266659: Epoch 3721 +2024-11-22 07:24:33.266777: Current learning rate: 0.00569 +2024-11-22 07:24:52.436703: train_loss -0.7826 +2024-11-22 07:24:52.444206: val_loss -0.7739 +2024-11-22 07:24:52.444333: Pseudo dice [0.8664] +2024-11-22 07:24:52.444414: Epoch time: 19.17 s +2024-11-22 07:24:53.341366: +2024-11-22 07:24:53.341571: Epoch 3722 +2024-11-22 07:24:53.341681: Current learning rate: 0.00569 +2024-11-22 07:25:12.299895: train_loss -0.7922 +2024-11-22 07:25:12.306912: val_loss -0.7563 +2024-11-22 07:25:12.307034: Pseudo dice [0.8533] +2024-11-22 07:25:12.307129: Epoch time: 18.96 s +2024-11-22 07:25:13.335040: +2024-11-22 07:25:13.335344: Epoch 3723 +2024-11-22 07:25:13.335499: Current learning rate: 0.00569 +2024-11-22 07:25:32.335056: train_loss -0.7953 +2024-11-22 07:25:32.338685: val_loss -0.7762 +2024-11-22 07:25:32.338794: Pseudo dice [0.8482] +2024-11-22 07:25:32.338882: Epoch time: 19.0 s +2024-11-22 07:25:33.216332: +2024-11-22 07:25:33.216515: Epoch 3724 +2024-11-22 07:25:33.216630: Current learning rate: 0.00569 +2024-11-22 07:25:51.734447: train_loss -0.7971 +2024-11-22 07:25:51.743650: val_loss -0.7882 +2024-11-22 07:25:51.743789: Pseudo dice [0.8589] +2024-11-22 07:25:51.743875: Epoch time: 18.52 s +2024-11-22 07:25:52.592671: +2024-11-22 07:25:52.592853: Epoch 3725 +2024-11-22 07:25:52.592979: Current learning rate: 0.00569 +2024-11-22 07:26:10.320182: train_loss -0.7841 +2024-11-22 07:26:10.325005: val_loss -0.7741 +2024-11-22 07:26:10.325121: Pseudo dice [0.8582] +2024-11-22 07:26:10.325207: Epoch time: 17.73 s +2024-11-22 07:26:11.177449: +2024-11-22 07:26:11.177659: Epoch 3726 +2024-11-22 07:26:11.177771: Current learning rate: 0.00569 +2024-11-22 07:26:30.205598: train_loss -0.7774 +2024-11-22 07:26:30.208021: val_loss -0.7709 +2024-11-22 07:26:30.208125: Pseudo dice [0.8487] +2024-11-22 07:26:30.208214: Epoch time: 19.03 s +2024-11-22 07:26:31.465238: +2024-11-22 07:26:31.465447: Epoch 3727 +2024-11-22 07:26:31.465567: Current learning rate: 0.00569 +2024-11-22 07:26:51.014084: train_loss -0.7587 +2024-11-22 07:26:51.020465: val_loss -0.7618 +2024-11-22 07:26:51.020596: Pseudo dice [0.8512] +2024-11-22 07:26:51.020678: Epoch time: 19.55 s +2024-11-22 07:26:51.894130: +2024-11-22 07:26:51.894333: Epoch 3728 +2024-11-22 07:26:51.894441: Current learning rate: 0.00569 +2024-11-22 07:27:11.193889: train_loss -0.7751 +2024-11-22 07:27:11.201044: val_loss -0.7731 +2024-11-22 07:27:11.201162: Pseudo dice [0.8454] +2024-11-22 07:27:11.201243: Epoch time: 19.3 s +2024-11-22 07:27:12.145166: +2024-11-22 07:27:12.145385: Epoch 3729 +2024-11-22 07:27:12.168537: Current learning rate: 0.00568 +2024-11-22 07:27:30.095298: train_loss -0.7777 +2024-11-22 07:27:30.105827: val_loss -0.7625 +2024-11-22 07:27:30.105961: Pseudo dice [0.8492] +2024-11-22 07:27:30.106053: Epoch time: 17.95 s +2024-11-22 07:27:31.095261: +2024-11-22 07:27:31.095483: Epoch 3730 +2024-11-22 07:27:31.095594: Current learning rate: 0.00568 +2024-11-22 07:27:49.393025: train_loss -0.7726 +2024-11-22 07:27:49.397439: val_loss -0.7486 +2024-11-22 07:27:49.397577: Pseudo dice [0.8559] +2024-11-22 07:27:49.397662: Epoch time: 18.3 s +2024-11-22 07:27:50.247148: +2024-11-22 07:27:50.247373: Epoch 3731 +2024-11-22 07:27:50.247483: Current learning rate: 0.00568 +2024-11-22 07:28:09.420091: train_loss -0.7532 +2024-11-22 07:28:09.429722: val_loss -0.7283 +2024-11-22 07:28:09.429870: Pseudo dice [0.8177] +2024-11-22 07:28:09.429962: Epoch time: 19.17 s +2024-11-22 07:28:10.278172: +2024-11-22 07:28:10.278383: Epoch 3732 +2024-11-22 07:28:10.278494: Current learning rate: 0.00568 +2024-11-22 07:28:30.155974: train_loss -0.7565 +2024-11-22 07:28:30.170822: val_loss -0.7544 +2024-11-22 07:28:30.170958: Pseudo dice [0.8191] +2024-11-22 07:28:30.171038: Epoch time: 19.88 s +2024-11-22 07:28:31.122373: +2024-11-22 07:28:31.122590: Epoch 3733 +2024-11-22 07:28:31.122708: Current learning rate: 0.00568 +2024-11-22 07:28:50.238926: train_loss -0.7437 +2024-11-22 07:28:50.240786: val_loss -0.757 +2024-11-22 07:28:50.240874: Pseudo dice [0.845] +2024-11-22 07:28:50.240959: Epoch time: 19.12 s +2024-11-22 07:28:51.090662: +2024-11-22 07:28:51.090869: Epoch 3734 +2024-11-22 07:28:51.090981: Current learning rate: 0.00568 +2024-11-22 07:29:09.931273: train_loss -0.7564 +2024-11-22 07:29:09.933185: val_loss -0.7559 +2024-11-22 07:29:09.933278: Pseudo dice [0.8419] +2024-11-22 07:29:09.933358: Epoch time: 18.84 s +2024-11-22 07:29:10.780858: +2024-11-22 07:29:10.781094: Epoch 3735 +2024-11-22 07:29:10.781207: Current learning rate: 0.00568 +2024-11-22 07:29:29.758786: train_loss -0.7707 +2024-11-22 07:29:29.762110: val_loss -0.7779 +2024-11-22 07:29:29.762224: Pseudo dice [0.85] +2024-11-22 07:29:29.762311: Epoch time: 18.98 s +2024-11-22 07:29:30.637774: +2024-11-22 07:29:30.638213: Epoch 3736 +2024-11-22 07:29:30.638328: Current learning rate: 0.00568 +2024-11-22 07:29:51.532744: train_loss -0.7725 +2024-11-22 07:29:51.540116: val_loss -0.7619 +2024-11-22 07:29:51.540236: Pseudo dice [0.849] +2024-11-22 07:29:51.540325: Epoch time: 20.9 s +2024-11-22 07:29:52.385008: +2024-11-22 07:29:52.385194: Epoch 3737 +2024-11-22 07:29:52.385310: Current learning rate: 0.00567 +2024-11-22 07:30:11.806589: train_loss -0.773 +2024-11-22 07:30:11.814015: val_loss -0.7576 +2024-11-22 07:30:11.814123: Pseudo dice [0.8478] +2024-11-22 07:30:11.814204: Epoch time: 19.42 s +2024-11-22 07:30:12.666512: +2024-11-22 07:30:12.666708: Epoch 3738 +2024-11-22 07:30:12.666822: Current learning rate: 0.00567 +2024-11-22 07:30:31.585808: train_loss -0.7837 +2024-11-22 07:30:31.588474: val_loss -0.778 +2024-11-22 07:30:31.588568: Pseudo dice [0.8457] +2024-11-22 07:30:31.588649: Epoch time: 18.92 s +2024-11-22 07:30:32.830931: +2024-11-22 07:30:32.831134: Epoch 3739 +2024-11-22 07:30:32.831320: Current learning rate: 0.00567 +2024-11-22 07:30:53.074330: train_loss -0.7747 +2024-11-22 07:30:53.077305: val_loss -0.758 +2024-11-22 07:30:53.077444: Pseudo dice [0.8528] +2024-11-22 07:30:53.077529: Epoch time: 20.24 s +2024-11-22 07:30:54.036943: +2024-11-22 07:30:54.037190: Epoch 3740 +2024-11-22 07:30:54.037342: Current learning rate: 0.00567 +2024-11-22 07:31:12.934365: train_loss -0.7812 +2024-11-22 07:31:12.942470: val_loss -0.7848 +2024-11-22 07:31:12.942595: Pseudo dice [0.8637] +2024-11-22 07:31:12.942680: Epoch time: 18.9 s +2024-11-22 07:31:13.822998: +2024-11-22 07:31:13.823233: Epoch 3741 +2024-11-22 07:31:13.823344: Current learning rate: 0.00567 +2024-11-22 07:31:32.235249: train_loss -0.7825 +2024-11-22 07:31:32.237751: val_loss -0.7783 +2024-11-22 07:31:32.237868: Pseudo dice [0.8569] +2024-11-22 07:31:32.238171: Epoch time: 18.41 s +2024-11-22 07:31:33.143413: +2024-11-22 07:31:33.143653: Epoch 3742 +2024-11-22 07:31:33.143764: Current learning rate: 0.00567 +2024-11-22 07:31:51.435543: train_loss -0.7826 +2024-11-22 07:31:51.442980: val_loss -0.7556 +2024-11-22 07:31:51.443115: Pseudo dice [0.8552] +2024-11-22 07:31:51.443202: Epoch time: 18.29 s +2024-11-22 07:31:52.328175: +2024-11-22 07:31:52.328401: Epoch 3743 +2024-11-22 07:31:52.328518: Current learning rate: 0.00567 +2024-11-22 07:32:11.815942: train_loss -0.7768 +2024-11-22 07:32:11.826199: val_loss -0.755 +2024-11-22 07:32:11.826341: Pseudo dice [0.8344] +2024-11-22 07:32:11.826425: Epoch time: 19.49 s +2024-11-22 07:32:12.707125: +2024-11-22 07:32:12.707342: Epoch 3744 +2024-11-22 07:32:12.707452: Current learning rate: 0.00567 +2024-11-22 07:32:31.853372: train_loss -0.7756 +2024-11-22 07:32:31.855023: val_loss -0.741 +2024-11-22 07:32:31.855143: Pseudo dice [0.8529] +2024-11-22 07:32:31.855225: Epoch time: 19.15 s +2024-11-22 07:32:32.703828: +2024-11-22 07:32:32.704024: Epoch 3745 +2024-11-22 07:32:32.704139: Current learning rate: 0.00567 +2024-11-22 07:32:52.204479: train_loss -0.7777 +2024-11-22 07:32:52.210950: val_loss -0.777 +2024-11-22 07:32:52.211096: Pseudo dice [0.85] +2024-11-22 07:32:52.211184: Epoch time: 19.5 s +2024-11-22 07:32:53.093627: +2024-11-22 07:32:53.093843: Epoch 3746 +2024-11-22 07:32:53.093956: Current learning rate: 0.00566 +2024-11-22 07:33:12.770266: train_loss -0.7816 +2024-11-22 07:33:12.772772: val_loss -0.7631 +2024-11-22 07:33:12.772869: Pseudo dice [0.8431] +2024-11-22 07:33:12.772961: Epoch time: 19.68 s +2024-11-22 07:33:13.627239: +2024-11-22 07:33:13.627455: Epoch 3747 +2024-11-22 07:33:13.627565: Current learning rate: 0.00566 +2024-11-22 07:33:33.224756: train_loss -0.7832 +2024-11-22 07:33:33.231950: val_loss -0.738 +2024-11-22 07:33:33.232117: Pseudo dice [0.8371] +2024-11-22 07:33:33.232200: Epoch time: 19.6 s +2024-11-22 07:33:34.278986: +2024-11-22 07:33:34.279186: Epoch 3748 +2024-11-22 07:33:34.279295: Current learning rate: 0.00566 +2024-11-22 07:33:54.037517: train_loss -0.7718 +2024-11-22 07:33:54.043603: val_loss -0.746 +2024-11-22 07:33:54.043731: Pseudo dice [0.8608] +2024-11-22 07:33:54.043818: Epoch time: 19.76 s +2024-11-22 07:33:55.011338: +2024-11-22 07:33:55.011560: Epoch 3749 +2024-11-22 07:33:55.011686: Current learning rate: 0.00566 +2024-11-22 07:34:13.436303: train_loss -0.785 +2024-11-22 07:34:13.442351: val_loss -0.7747 +2024-11-22 07:34:13.442473: Pseudo dice [0.8619] +2024-11-22 07:34:13.442559: Epoch time: 18.43 s +2024-11-22 07:34:15.077115: +2024-11-22 07:34:15.077339: Epoch 3750 +2024-11-22 07:34:15.077454: Current learning rate: 0.00566 +2024-11-22 07:34:34.166987: train_loss -0.7823 +2024-11-22 07:34:34.173702: val_loss -0.7686 +2024-11-22 07:34:34.173819: Pseudo dice [0.8454] +2024-11-22 07:34:34.173944: Epoch time: 19.09 s +2024-11-22 07:34:35.024085: +2024-11-22 07:34:35.024333: Epoch 3751 +2024-11-22 07:34:35.024453: Current learning rate: 0.00566 +2024-11-22 07:34:53.822859: train_loss -0.7826 +2024-11-22 07:34:53.825540: val_loss -0.7459 +2024-11-22 07:34:53.825630: Pseudo dice [0.8524] +2024-11-22 07:34:53.825707: Epoch time: 18.8 s +2024-11-22 07:34:54.674876: +2024-11-22 07:34:54.675107: Epoch 3752 +2024-11-22 07:34:54.675218: Current learning rate: 0.00566 +2024-11-22 07:35:14.029204: train_loss -0.778 +2024-11-22 07:35:14.036289: val_loss -0.7912 +2024-11-22 07:35:14.036408: Pseudo dice [0.8518] +2024-11-22 07:35:14.036493: Epoch time: 19.36 s +2024-11-22 07:35:14.896665: +2024-11-22 07:35:14.896948: Epoch 3753 +2024-11-22 07:35:14.897071: Current learning rate: 0.00566 +2024-11-22 07:35:33.871199: train_loss -0.7744 +2024-11-22 07:35:33.878459: val_loss -0.7614 +2024-11-22 07:35:33.878571: Pseudo dice [0.8589] +2024-11-22 07:35:33.878662: Epoch time: 18.98 s +2024-11-22 07:35:34.826363: +2024-11-22 07:35:34.826576: Epoch 3754 +2024-11-22 07:35:34.826686: Current learning rate: 0.00565 +2024-11-22 07:35:54.019032: train_loss -0.7775 +2024-11-22 07:35:54.026141: val_loss -0.7702 +2024-11-22 07:35:54.026282: Pseudo dice [0.8567] +2024-11-22 07:35:54.026380: Epoch time: 19.19 s +2024-11-22 07:35:55.015915: +2024-11-22 07:35:55.016129: Epoch 3755 +2024-11-22 07:35:55.016243: Current learning rate: 0.00565 +2024-11-22 07:36:13.220354: train_loss -0.771 +2024-11-22 07:36:13.229306: val_loss -0.743 +2024-11-22 07:36:13.229462: Pseudo dice [0.8472] +2024-11-22 07:36:13.229553: Epoch time: 18.21 s +2024-11-22 07:36:14.293774: +2024-11-22 07:36:14.294045: Epoch 3756 +2024-11-22 07:36:14.294169: Current learning rate: 0.00565 +2024-11-22 07:36:34.141396: train_loss -0.7615 +2024-11-22 07:36:34.144016: val_loss -0.7444 +2024-11-22 07:36:34.144122: Pseudo dice [0.8263] +2024-11-22 07:36:34.144198: Epoch time: 19.85 s +2024-11-22 07:36:35.219962: +2024-11-22 07:36:35.220189: Epoch 3757 +2024-11-22 07:36:35.220304: Current learning rate: 0.00565 +2024-11-22 07:36:53.973651: train_loss -0.7544 +2024-11-22 07:36:53.976448: val_loss -0.7541 +2024-11-22 07:36:53.976548: Pseudo dice [0.8375] +2024-11-22 07:36:53.976636: Epoch time: 18.75 s +2024-11-22 07:36:54.830318: +2024-11-22 07:36:54.830516: Epoch 3758 +2024-11-22 07:36:54.830631: Current learning rate: 0.00565 +2024-11-22 07:37:14.456464: train_loss -0.7728 +2024-11-22 07:37:14.464655: val_loss -0.7564 +2024-11-22 07:37:14.464774: Pseudo dice [0.8455] +2024-11-22 07:37:14.464872: Epoch time: 19.63 s +2024-11-22 07:37:15.469584: +2024-11-22 07:37:15.469791: Epoch 3759 +2024-11-22 07:37:15.469903: Current learning rate: 0.00565 +2024-11-22 07:37:34.286401: train_loss -0.7763 +2024-11-22 07:37:34.293786: val_loss -0.7687 +2024-11-22 07:37:34.293906: Pseudo dice [0.8641] +2024-11-22 07:37:34.293991: Epoch time: 18.82 s +2024-11-22 07:37:35.239093: +2024-11-22 07:37:35.239304: Epoch 3760 +2024-11-22 07:37:35.239420: Current learning rate: 0.00565 +2024-11-22 07:37:55.045658: train_loss -0.7802 +2024-11-22 07:37:55.049987: val_loss -0.7553 +2024-11-22 07:37:55.050120: Pseudo dice [0.8524] +2024-11-22 07:37:55.050200: Epoch time: 19.81 s +2024-11-22 07:37:56.219049: +2024-11-22 07:37:56.219261: Epoch 3761 +2024-11-22 07:37:56.219368: Current learning rate: 0.00565 +2024-11-22 07:38:13.584136: train_loss -0.7874 +2024-11-22 07:38:13.586645: val_loss -0.7672 +2024-11-22 07:38:13.586763: Pseudo dice [0.8498] +2024-11-22 07:38:13.586862: Epoch time: 17.37 s +2024-11-22 07:38:14.434905: +2024-11-22 07:38:14.435122: Epoch 3762 +2024-11-22 07:38:14.435235: Current learning rate: 0.00564 +2024-11-22 07:38:33.879216: train_loss -0.7794 +2024-11-22 07:38:33.883947: val_loss -0.7662 +2024-11-22 07:38:33.884114: Pseudo dice [0.8441] +2024-11-22 07:38:33.884229: Epoch time: 19.45 s +2024-11-22 07:38:34.751529: +2024-11-22 07:38:34.751765: Epoch 3763 +2024-11-22 07:38:34.751880: Current learning rate: 0.00564 +2024-11-22 07:38:53.879759: train_loss -0.7847 +2024-11-22 07:38:53.882750: val_loss -0.7723 +2024-11-22 07:38:53.882861: Pseudo dice [0.8522] +2024-11-22 07:38:53.882939: Epoch time: 19.13 s +2024-11-22 07:38:54.781117: +2024-11-22 07:38:54.781328: Epoch 3764 +2024-11-22 07:38:54.781441: Current learning rate: 0.00564 +2024-11-22 07:39:13.771377: train_loss -0.7847 +2024-11-22 07:39:13.778454: val_loss -0.767 +2024-11-22 07:39:13.778581: Pseudo dice [0.8609] +2024-11-22 07:39:13.778670: Epoch time: 18.99 s +2024-11-22 07:39:14.642517: +2024-11-22 07:39:14.642748: Epoch 3765 +2024-11-22 07:39:14.643048: Current learning rate: 0.00564 +2024-11-22 07:39:33.897952: train_loss -0.7727 +2024-11-22 07:39:33.900652: val_loss -0.7477 +2024-11-22 07:39:33.900786: Pseudo dice [0.8483] +2024-11-22 07:39:33.900890: Epoch time: 19.26 s +2024-11-22 07:39:34.760645: +2024-11-22 07:39:34.760854: Epoch 3766 +2024-11-22 07:39:34.760968: Current learning rate: 0.00564 +2024-11-22 07:39:54.766723: train_loss -0.7748 +2024-11-22 07:39:54.779850: val_loss -0.7562 +2024-11-22 07:39:54.779974: Pseudo dice [0.8399] +2024-11-22 07:39:54.780055: Epoch time: 20.01 s +2024-11-22 07:39:55.625098: +2024-11-22 07:39:55.625320: Epoch 3767 +2024-11-22 07:39:55.625439: Current learning rate: 0.00564 +2024-11-22 07:40:16.045335: train_loss -0.766 +2024-11-22 07:40:16.052182: val_loss -0.7669 +2024-11-22 07:40:16.052289: Pseudo dice [0.8502] +2024-11-22 07:40:16.052370: Epoch time: 20.42 s +2024-11-22 07:40:17.123024: +2024-11-22 07:40:17.123244: Epoch 3768 +2024-11-22 07:40:17.123350: Current learning rate: 0.00564 +2024-11-22 07:40:36.272739: train_loss -0.774 +2024-11-22 07:40:36.279228: val_loss -0.7714 +2024-11-22 07:40:36.279344: Pseudo dice [0.8578] +2024-11-22 07:40:36.279424: Epoch time: 19.15 s +2024-11-22 07:40:37.142499: +2024-11-22 07:40:37.142699: Epoch 3769 +2024-11-22 07:40:37.142810: Current learning rate: 0.00564 +2024-11-22 07:40:55.260278: train_loss -0.7861 +2024-11-22 07:40:55.287735: val_loss -0.7586 +2024-11-22 07:40:55.287885: Pseudo dice [0.8636] +2024-11-22 07:40:55.287977: Epoch time: 18.12 s +2024-11-22 07:40:56.277672: +2024-11-22 07:40:56.277883: Epoch 3770 +2024-11-22 07:40:56.277999: Current learning rate: 0.00564 +2024-11-22 07:41:15.566088: train_loss -0.7829 +2024-11-22 07:41:15.570404: val_loss -0.7754 +2024-11-22 07:41:15.570522: Pseudo dice [0.8466] +2024-11-22 07:41:15.570599: Epoch time: 19.29 s +2024-11-22 07:41:16.488173: +2024-11-22 07:41:16.488390: Epoch 3771 +2024-11-22 07:41:16.488497: Current learning rate: 0.00563 +2024-11-22 07:41:35.496206: train_loss -0.7828 +2024-11-22 07:41:35.497640: val_loss -0.7461 +2024-11-22 07:41:35.497727: Pseudo dice [0.8529] +2024-11-22 07:41:35.497807: Epoch time: 19.01 s +2024-11-22 07:41:36.327769: +2024-11-22 07:41:36.327973: Epoch 3772 +2024-11-22 07:41:36.328089: Current learning rate: 0.00563 +2024-11-22 07:41:55.292327: train_loss -0.7872 +2024-11-22 07:41:55.299789: val_loss -0.7582 +2024-11-22 07:41:55.299924: Pseudo dice [0.8594] +2024-11-22 07:41:55.300005: Epoch time: 18.97 s +2024-11-22 07:41:56.603374: +2024-11-22 07:41:56.603598: Epoch 3773 +2024-11-22 07:41:56.603718: Current learning rate: 0.00563 +2024-11-22 07:42:16.111221: train_loss -0.7779 +2024-11-22 07:42:16.112959: val_loss -0.7732 +2024-11-22 07:42:16.113068: Pseudo dice [0.8585] +2024-11-22 07:42:16.113158: Epoch time: 19.51 s +2024-11-22 07:42:17.007219: +2024-11-22 07:42:17.007458: Epoch 3774 +2024-11-22 07:42:17.007570: Current learning rate: 0.00563 +2024-11-22 07:42:36.135520: train_loss -0.7827 +2024-11-22 07:42:36.137054: val_loss -0.8082 +2024-11-22 07:42:36.137162: Pseudo dice [0.8632] +2024-11-22 07:42:36.137238: Epoch time: 19.13 s +2024-11-22 07:42:37.092725: +2024-11-22 07:42:37.092949: Epoch 3775 +2024-11-22 07:42:37.093069: Current learning rate: 0.00563 +2024-11-22 07:42:55.720550: train_loss -0.7807 +2024-11-22 07:42:55.726621: val_loss -0.7515 +2024-11-22 07:42:55.726741: Pseudo dice [0.8535] +2024-11-22 07:42:55.726825: Epoch time: 18.63 s +2024-11-22 07:42:56.836429: +2024-11-22 07:42:56.836627: Epoch 3776 +2024-11-22 07:42:56.836739: Current learning rate: 0.00563 +2024-11-22 07:43:15.203303: train_loss -0.7777 +2024-11-22 07:43:15.207134: val_loss -0.7788 +2024-11-22 07:43:15.207273: Pseudo dice [0.8477] +2024-11-22 07:43:15.207366: Epoch time: 18.37 s +2024-11-22 07:43:16.128298: +2024-11-22 07:43:16.128508: Epoch 3777 +2024-11-22 07:43:16.128622: Current learning rate: 0.00563 +2024-11-22 07:43:35.573616: train_loss -0.7764 +2024-11-22 07:43:35.578985: val_loss -0.7613 +2024-11-22 07:43:35.579126: Pseudo dice [0.8587] +2024-11-22 07:43:35.579215: Epoch time: 19.45 s +2024-11-22 07:43:36.535404: +2024-11-22 07:43:36.535683: Epoch 3778 +2024-11-22 07:43:36.535796: Current learning rate: 0.00563 +2024-11-22 07:43:55.034458: train_loss -0.7776 +2024-11-22 07:43:55.036247: val_loss -0.7808 +2024-11-22 07:43:55.036374: Pseudo dice [0.8418] +2024-11-22 07:43:55.036453: Epoch time: 18.5 s +2024-11-22 07:43:55.885915: +2024-11-22 07:43:55.886124: Epoch 3779 +2024-11-22 07:43:55.886232: Current learning rate: 0.00562 +2024-11-22 07:44:14.990622: train_loss -0.7902 +2024-11-22 07:44:14.996462: val_loss -0.7818 +2024-11-22 07:44:14.996593: Pseudo dice [0.8472] +2024-11-22 07:44:14.996690: Epoch time: 19.11 s +2024-11-22 07:44:15.976929: +2024-11-22 07:44:15.977147: Epoch 3780 +2024-11-22 07:44:15.977263: Current learning rate: 0.00562 +2024-11-22 07:44:34.401175: train_loss -0.779 +2024-11-22 07:44:34.402847: val_loss -0.7544 +2024-11-22 07:44:34.402987: Pseudo dice [0.8452] +2024-11-22 07:44:34.403082: Epoch time: 18.43 s +2024-11-22 07:44:35.268631: +2024-11-22 07:44:35.268841: Epoch 3781 +2024-11-22 07:44:35.268954: Current learning rate: 0.00562 +2024-11-22 07:44:53.280376: train_loss -0.7765 +2024-11-22 07:44:53.281887: val_loss -0.7581 +2024-11-22 07:44:53.281989: Pseudo dice [0.8641] +2024-11-22 07:44:53.282073: Epoch time: 18.01 s +2024-11-22 07:44:54.133729: +2024-11-22 07:44:54.133926: Epoch 3782 +2024-11-22 07:44:54.134039: Current learning rate: 0.00562 +2024-11-22 07:45:12.255185: train_loss -0.7737 +2024-11-22 07:45:12.256969: val_loss -0.7596 +2024-11-22 07:45:12.257101: Pseudo dice [0.8613] +2024-11-22 07:45:12.257181: Epoch time: 18.12 s +2024-11-22 07:45:13.112540: +2024-11-22 07:45:13.112740: Epoch 3783 +2024-11-22 07:45:13.112851: Current learning rate: 0.00562 +2024-11-22 07:45:32.642890: train_loss -0.7807 +2024-11-22 07:45:32.650763: val_loss -0.7634 +2024-11-22 07:45:32.650883: Pseudo dice [0.8486] +2024-11-22 07:45:32.650972: Epoch time: 19.53 s +2024-11-22 07:45:33.527525: +2024-11-22 07:45:33.528001: Epoch 3784 +2024-11-22 07:45:33.528141: Current learning rate: 0.00562 +2024-11-22 07:45:52.670449: train_loss -0.7812 +2024-11-22 07:45:52.676776: val_loss -0.7545 +2024-11-22 07:45:52.676953: Pseudo dice [0.8585] +2024-11-22 07:45:52.677047: Epoch time: 19.14 s +2024-11-22 07:45:53.524277: +2024-11-22 07:45:53.524516: Epoch 3785 +2024-11-22 07:45:53.524627: Current learning rate: 0.00562 +2024-11-22 07:46:11.374902: train_loss -0.7759 +2024-11-22 07:46:11.376285: val_loss -0.7873 +2024-11-22 07:46:11.376389: Pseudo dice [0.8591] +2024-11-22 07:46:11.376470: Epoch time: 17.85 s +2024-11-22 07:46:12.207477: +2024-11-22 07:46:12.207697: Epoch 3786 +2024-11-22 07:46:12.207810: Current learning rate: 0.00562 +2024-11-22 07:46:30.971363: train_loss -0.7884 +2024-11-22 07:46:30.973623: val_loss -0.7711 +2024-11-22 07:46:30.973711: Pseudo dice [0.8523] +2024-11-22 07:46:30.973789: Epoch time: 18.76 s +2024-11-22 07:46:31.817753: +2024-11-22 07:46:31.817970: Epoch 3787 +2024-11-22 07:46:31.818078: Current learning rate: 0.00562 +2024-11-22 07:46:51.099721: train_loss -0.7827 +2024-11-22 07:46:51.105207: val_loss -0.7736 +2024-11-22 07:46:51.105331: Pseudo dice [0.8582] +2024-11-22 07:46:51.105419: Epoch time: 19.28 s +2024-11-22 07:46:51.997937: +2024-11-22 07:46:51.998187: Epoch 3788 +2024-11-22 07:46:51.998340: Current learning rate: 0.00561 +2024-11-22 07:47:10.043079: train_loss -0.7744 +2024-11-22 07:47:10.046539: val_loss -0.7578 +2024-11-22 07:47:10.046655: Pseudo dice [0.86] +2024-11-22 07:47:10.046741: Epoch time: 18.05 s +2024-11-22 07:47:11.074295: +2024-11-22 07:47:11.074542: Epoch 3789 +2024-11-22 07:47:11.074660: Current learning rate: 0.00561 +2024-11-22 07:47:30.153750: train_loss -0.7796 +2024-11-22 07:47:30.167169: val_loss -0.7836 +2024-11-22 07:47:30.167290: Pseudo dice [0.8444] +2024-11-22 07:47:30.167372: Epoch time: 19.08 s +2024-11-22 07:47:31.063945: +2024-11-22 07:47:31.064142: Epoch 3790 +2024-11-22 07:47:31.064261: Current learning rate: 0.00561 +2024-11-22 07:47:50.758493: train_loss -0.7837 +2024-11-22 07:47:50.766624: val_loss -0.7822 +2024-11-22 07:47:50.766744: Pseudo dice [0.8488] +2024-11-22 07:47:50.766823: Epoch time: 19.7 s +2024-11-22 07:47:51.864412: +2024-11-22 07:47:51.864840: Epoch 3791 +2024-11-22 07:47:51.864966: Current learning rate: 0.00561 +2024-11-22 07:48:10.181164: train_loss -0.7827 +2024-11-22 07:48:10.188089: val_loss -0.7829 +2024-11-22 07:48:10.188218: Pseudo dice [0.863] +2024-11-22 07:48:10.188316: Epoch time: 18.32 s +2024-11-22 07:48:11.043591: +2024-11-22 07:48:11.043811: Epoch 3792 +2024-11-22 07:48:11.043920: Current learning rate: 0.00561 +2024-11-22 07:48:31.005005: train_loss -0.7819 +2024-11-22 07:48:31.006570: val_loss -0.7672 +2024-11-22 07:48:31.006943: Pseudo dice [0.8604] +2024-11-22 07:48:31.007050: Epoch time: 19.96 s +2024-11-22 07:48:31.998027: +2024-11-22 07:48:31.998231: Epoch 3793 +2024-11-22 07:48:31.998347: Current learning rate: 0.00561 +2024-11-22 07:48:50.304278: train_loss -0.7826 +2024-11-22 07:48:50.314199: val_loss -0.7578 +2024-11-22 07:48:50.314349: Pseudo dice [0.8465] +2024-11-22 07:48:50.314437: Epoch time: 18.31 s +2024-11-22 07:48:51.168920: +2024-11-22 07:48:51.169126: Epoch 3794 +2024-11-22 07:48:51.169240: Current learning rate: 0.00561 +2024-11-22 07:49:10.704489: train_loss -0.789 +2024-11-22 07:49:10.706477: val_loss -0.7792 +2024-11-22 07:49:10.706599: Pseudo dice [0.8668] +2024-11-22 07:49:10.706684: Epoch time: 19.54 s +2024-11-22 07:49:11.712796: +2024-11-22 07:49:11.712974: Epoch 3795 +2024-11-22 07:49:11.713088: Current learning rate: 0.00561 +2024-11-22 07:49:31.019714: train_loss -0.785 +2024-11-22 07:49:31.026853: val_loss -0.7598 +2024-11-22 07:49:31.026978: Pseudo dice [0.864] +2024-11-22 07:49:31.027073: Epoch time: 19.31 s +2024-11-22 07:49:32.274710: +2024-11-22 07:49:32.274915: Epoch 3796 +2024-11-22 07:49:32.275026: Current learning rate: 0.0056 +2024-11-22 07:49:50.989109: train_loss -0.7825 +2024-11-22 07:49:50.993784: val_loss -0.762 +2024-11-22 07:49:50.993953: Pseudo dice [0.8536] +2024-11-22 07:49:50.994044: Epoch time: 18.72 s +2024-11-22 07:49:51.876791: +2024-11-22 07:49:51.877009: Epoch 3797 +2024-11-22 07:49:51.877130: Current learning rate: 0.0056 +2024-11-22 07:50:10.554149: train_loss -0.7878 +2024-11-22 07:50:10.556868: val_loss -0.76 +2024-11-22 07:50:10.556996: Pseudo dice [0.8499] +2024-11-22 07:50:10.557089: Epoch time: 18.68 s +2024-11-22 07:50:11.474153: +2024-11-22 07:50:11.474399: Epoch 3798 +2024-11-22 07:50:11.474515: Current learning rate: 0.0056 +2024-11-22 07:50:30.375594: train_loss -0.7894 +2024-11-22 07:50:30.383407: val_loss -0.7645 +2024-11-22 07:50:30.383560: Pseudo dice [0.862] +2024-11-22 07:50:30.383646: Epoch time: 18.9 s +2024-11-22 07:50:31.230180: +2024-11-22 07:50:31.230404: Epoch 3799 +2024-11-22 07:50:31.230513: Current learning rate: 0.0056 +2024-11-22 07:50:50.807620: train_loss -0.7869 +2024-11-22 07:50:50.819385: val_loss -0.7436 +2024-11-22 07:50:50.819523: Pseudo dice [0.8554] +2024-11-22 07:50:50.819613: Epoch time: 19.58 s +2024-11-22 07:50:52.032717: +2024-11-22 07:50:52.032933: Epoch 3800 +2024-11-22 07:50:52.033042: Current learning rate: 0.0056 +2024-11-22 07:51:12.126484: train_loss -0.7758 +2024-11-22 07:51:12.133665: val_loss -0.7613 +2024-11-22 07:51:12.133786: Pseudo dice [0.8479] +2024-11-22 07:51:12.133872: Epoch time: 20.09 s +2024-11-22 07:51:13.169797: +2024-11-22 07:51:13.170010: Epoch 3801 +2024-11-22 07:51:13.170133: Current learning rate: 0.0056 +2024-11-22 07:51:32.199194: train_loss -0.7825 +2024-11-22 07:51:32.207093: val_loss -0.7695 +2024-11-22 07:51:32.207224: Pseudo dice [0.8533] +2024-11-22 07:51:32.207313: Epoch time: 19.03 s +2024-11-22 07:51:33.102181: +2024-11-22 07:51:33.102395: Epoch 3802 +2024-11-22 07:51:33.102514: Current learning rate: 0.0056 +2024-11-22 07:51:51.998866: train_loss -0.7835 +2024-11-22 07:51:52.004439: val_loss -0.7652 +2024-11-22 07:51:52.004561: Pseudo dice [0.8543] +2024-11-22 07:51:52.004657: Epoch time: 18.9 s +2024-11-22 07:51:52.866148: +2024-11-22 07:51:52.866389: Epoch 3803 +2024-11-22 07:51:52.866498: Current learning rate: 0.0056 +2024-11-22 07:52:11.637451: train_loss -0.7856 +2024-11-22 07:52:11.644739: val_loss -0.7637 +2024-11-22 07:52:11.644861: Pseudo dice [0.8597] +2024-11-22 07:52:11.644952: Epoch time: 18.77 s +2024-11-22 07:52:12.506614: +2024-11-22 07:52:12.506829: Epoch 3804 +2024-11-22 07:52:12.506944: Current learning rate: 0.00559 +2024-11-22 07:52:31.692756: train_loss -0.794 +2024-11-22 07:52:31.702447: val_loss -0.7542 +2024-11-22 07:52:31.702581: Pseudo dice [0.8438] +2024-11-22 07:52:31.702673: Epoch time: 19.19 s +2024-11-22 07:52:32.588312: +2024-11-22 07:52:32.588517: Epoch 3805 +2024-11-22 07:52:32.588631: Current learning rate: 0.00559 +2024-11-22 07:52:51.518108: train_loss -0.786 +2024-11-22 07:52:51.527452: val_loss -0.7691 +2024-11-22 07:52:51.527591: Pseudo dice [0.8447] +2024-11-22 07:52:51.527679: Epoch time: 18.93 s +2024-11-22 07:52:52.530346: +2024-11-22 07:52:52.530555: Epoch 3806 +2024-11-22 07:52:52.530670: Current learning rate: 0.00559 +2024-11-22 07:53:11.718431: train_loss -0.7677 +2024-11-22 07:53:11.719871: val_loss -0.7823 +2024-11-22 07:53:11.720083: Pseudo dice [0.858] +2024-11-22 07:53:11.720180: Epoch time: 19.19 s +2024-11-22 07:53:12.763523: +2024-11-22 07:53:12.763769: Epoch 3807 +2024-11-22 07:53:12.763901: Current learning rate: 0.00559 +2024-11-22 07:53:32.525538: train_loss -0.7582 +2024-11-22 07:53:32.532099: val_loss -0.7474 +2024-11-22 07:53:32.532245: Pseudo dice [0.8452] +2024-11-22 07:53:32.532328: Epoch time: 19.76 s +2024-11-22 07:53:33.388115: +2024-11-22 07:53:33.388327: Epoch 3808 +2024-11-22 07:53:33.388443: Current learning rate: 0.00559 +2024-11-22 07:53:51.925746: train_loss -0.7584 +2024-11-22 07:53:51.940349: val_loss -0.7522 +2024-11-22 07:53:51.940469: Pseudo dice [0.8482] +2024-11-22 07:53:51.940548: Epoch time: 18.54 s +2024-11-22 07:53:52.834856: +2024-11-22 07:53:52.835083: Epoch 3809 +2024-11-22 07:53:52.835199: Current learning rate: 0.00559 +2024-11-22 07:54:11.791225: train_loss -0.7552 +2024-11-22 07:54:11.794591: val_loss -0.7656 +2024-11-22 07:54:11.794703: Pseudo dice [0.8417] +2024-11-22 07:54:11.794789: Epoch time: 18.96 s +2024-11-22 07:54:12.644963: +2024-11-22 07:54:12.645188: Epoch 3810 +2024-11-22 07:54:12.645298: Current learning rate: 0.00559 +2024-11-22 07:54:30.994891: train_loss -0.7645 +2024-11-22 07:54:30.996349: val_loss -0.7603 +2024-11-22 07:54:30.996526: Pseudo dice [0.8457] +2024-11-22 07:54:30.996614: Epoch time: 18.35 s +2024-11-22 07:54:31.850331: +2024-11-22 07:54:31.850548: Epoch 3811 +2024-11-22 07:54:31.850668: Current learning rate: 0.00559 +2024-11-22 07:54:50.442034: train_loss -0.7682 +2024-11-22 07:54:50.443537: val_loss -0.7761 +2024-11-22 07:54:50.443713: Pseudo dice [0.8665] +2024-11-22 07:54:50.443848: Epoch time: 18.59 s +2024-11-22 07:54:51.296686: +2024-11-22 07:54:51.296893: Epoch 3812 +2024-11-22 07:54:51.297012: Current learning rate: 0.00559 +2024-11-22 07:55:09.521374: train_loss -0.7808 +2024-11-22 07:55:09.523947: val_loss -0.7774 +2024-11-22 07:55:09.524045: Pseudo dice [0.8475] +2024-11-22 07:55:09.524130: Epoch time: 18.23 s +2024-11-22 07:55:10.380784: +2024-11-22 07:55:10.380997: Epoch 3813 +2024-11-22 07:55:10.381110: Current learning rate: 0.00558 +2024-11-22 07:55:28.624178: train_loss -0.7793 +2024-11-22 07:55:28.627160: val_loss -0.7333 +2024-11-22 07:55:28.627255: Pseudo dice [0.8474] +2024-11-22 07:55:28.627343: Epoch time: 18.24 s +2024-11-22 07:55:29.486639: +2024-11-22 07:55:29.486856: Epoch 3814 +2024-11-22 07:55:29.486962: Current learning rate: 0.00558 +2024-11-22 07:55:48.197911: train_loss -0.7795 +2024-11-22 07:55:48.206271: val_loss -0.7641 +2024-11-22 07:55:48.206388: Pseudo dice [0.8513] +2024-11-22 07:55:48.206505: Epoch time: 18.71 s +2024-11-22 07:55:49.237931: +2024-11-22 07:55:49.238168: Epoch 3815 +2024-11-22 07:55:49.238288: Current learning rate: 0.00558 +2024-11-22 07:56:08.743200: train_loss -0.7778 +2024-11-22 07:56:08.749359: val_loss -0.7786 +2024-11-22 07:56:08.749489: Pseudo dice [0.845] +2024-11-22 07:56:08.749578: Epoch time: 19.51 s +2024-11-22 07:56:09.623544: +2024-11-22 07:56:09.623758: Epoch 3816 +2024-11-22 07:56:09.623872: Current learning rate: 0.00558 +2024-11-22 07:56:27.930715: train_loss -0.7844 +2024-11-22 07:56:27.937462: val_loss -0.759 +2024-11-22 07:56:27.937594: Pseudo dice [0.8462] +2024-11-22 07:56:27.937678: Epoch time: 18.31 s +2024-11-22 07:56:28.817478: +2024-11-22 07:56:28.817689: Epoch 3817 +2024-11-22 07:56:28.817802: Current learning rate: 0.00558 +2024-11-22 07:56:47.450424: train_loss -0.7839 +2024-11-22 07:56:47.453407: val_loss -0.7696 +2024-11-22 07:56:47.453537: Pseudo dice [0.8416] +2024-11-22 07:56:47.453632: Epoch time: 18.63 s +2024-11-22 07:56:48.330186: +2024-11-22 07:56:48.337615: Epoch 3818 +2024-11-22 07:56:48.337741: Current learning rate: 0.00558 +2024-11-22 07:57:06.491475: train_loss -0.7839 +2024-11-22 07:57:06.498651: val_loss -0.7869 +2024-11-22 07:57:06.498834: Pseudo dice [0.8528] +2024-11-22 07:57:06.498927: Epoch time: 18.16 s +2024-11-22 07:57:07.348746: +2024-11-22 07:57:07.348963: Epoch 3819 +2024-11-22 07:57:07.349085: Current learning rate: 0.00558 +2024-11-22 07:57:26.422431: train_loss -0.7815 +2024-11-22 07:57:26.431201: val_loss -0.7542 +2024-11-22 07:57:26.431385: Pseudo dice [0.8496] +2024-11-22 07:57:26.431473: Epoch time: 19.07 s +2024-11-22 07:57:27.415955: +2024-11-22 07:57:27.416180: Epoch 3820 +2024-11-22 07:57:27.416291: Current learning rate: 0.00558 +2024-11-22 07:57:45.977661: train_loss -0.777 +2024-11-22 07:57:45.984284: val_loss -0.7711 +2024-11-22 07:57:45.984415: Pseudo dice [0.8483] +2024-11-22 07:57:45.984503: Epoch time: 18.56 s +2024-11-22 07:57:46.867605: +2024-11-22 07:57:46.867926: Epoch 3821 +2024-11-22 07:57:46.868087: Current learning rate: 0.00557 +2024-11-22 07:58:05.212724: train_loss -0.7803 +2024-11-22 07:58:05.220855: val_loss -0.7658 +2024-11-22 07:58:05.220964: Pseudo dice [0.8528] +2024-11-22 07:58:05.221047: Epoch time: 18.35 s +2024-11-22 07:58:06.230821: +2024-11-22 07:58:06.231045: Epoch 3822 +2024-11-22 07:58:06.231171: Current learning rate: 0.00557 +2024-11-22 07:58:24.667569: train_loss -0.7823 +2024-11-22 07:58:24.679856: val_loss -0.7694 +2024-11-22 07:58:24.679971: Pseudo dice [0.8461] +2024-11-22 07:58:24.680055: Epoch time: 18.44 s +2024-11-22 07:58:25.618628: +2024-11-22 07:58:25.618825: Epoch 3823 +2024-11-22 07:58:25.618939: Current learning rate: 0.00557 +2024-11-22 07:58:44.978864: train_loss -0.7888 +2024-11-22 07:58:44.984232: val_loss -0.7562 +2024-11-22 07:58:44.984357: Pseudo dice [0.8524] +2024-11-22 07:58:44.984437: Epoch time: 19.36 s +2024-11-22 07:58:45.853524: +2024-11-22 07:58:45.853760: Epoch 3824 +2024-11-22 07:58:45.853868: Current learning rate: 0.00557 +2024-11-22 07:59:04.070891: train_loss -0.7887 +2024-11-22 07:59:04.078850: val_loss -0.778 +2024-11-22 07:59:04.078979: Pseudo dice [0.8558] +2024-11-22 07:59:04.079070: Epoch time: 18.22 s +2024-11-22 07:59:04.949447: +2024-11-22 07:59:04.949651: Epoch 3825 +2024-11-22 07:59:04.949765: Current learning rate: 0.00557 +2024-11-22 07:59:24.086618: train_loss -0.7961 +2024-11-22 07:59:24.093129: val_loss -0.7663 +2024-11-22 07:59:24.093267: Pseudo dice [0.8551] +2024-11-22 07:59:24.093428: Epoch time: 19.14 s +2024-11-22 07:59:24.991767: +2024-11-22 07:59:24.991996: Epoch 3826 +2024-11-22 07:59:24.992120: Current learning rate: 0.00557 +2024-11-22 07:59:44.076820: train_loss -0.7796 +2024-11-22 07:59:44.081161: val_loss -0.76 +2024-11-22 07:59:44.081284: Pseudo dice [0.8433] +2024-11-22 07:59:44.081370: Epoch time: 19.09 s +2024-11-22 07:59:44.962987: +2024-11-22 07:59:44.963187: Epoch 3827 +2024-11-22 07:59:44.963296: Current learning rate: 0.00557 +2024-11-22 08:00:03.400611: train_loss -0.7857 +2024-11-22 08:00:03.409359: val_loss -0.7484 +2024-11-22 08:00:03.409472: Pseudo dice [0.8557] +2024-11-22 08:00:03.409557: Epoch time: 18.44 s +2024-11-22 08:00:04.313956: +2024-11-22 08:00:04.314183: Epoch 3828 +2024-11-22 08:00:04.314302: Current learning rate: 0.00557 +2024-11-22 08:00:24.026953: train_loss -0.7724 +2024-11-22 08:00:24.029625: val_loss -0.7742 +2024-11-22 08:00:24.029756: Pseudo dice [0.8553] +2024-11-22 08:00:24.029852: Epoch time: 19.71 s +2024-11-22 08:00:25.250939: +2024-11-22 08:00:25.251155: Epoch 3829 +2024-11-22 08:00:25.251272: Current learning rate: 0.00556 +2024-11-22 08:00:43.756487: train_loss -0.7872 +2024-11-22 08:00:43.759659: val_loss -0.7762 +2024-11-22 08:00:43.759786: Pseudo dice [0.853] +2024-11-22 08:00:43.759865: Epoch time: 18.51 s +2024-11-22 08:00:44.613124: +2024-11-22 08:00:44.613351: Epoch 3830 +2024-11-22 08:00:44.613464: Current learning rate: 0.00556 +2024-11-22 08:01:03.354553: train_loss -0.7728 +2024-11-22 08:01:03.362553: val_loss -0.8082 +2024-11-22 08:01:03.362688: Pseudo dice [0.8706] +2024-11-22 08:01:03.385053: Epoch time: 18.74 s +2024-11-22 08:01:04.431477: +2024-11-22 08:01:04.431699: Epoch 3831 +2024-11-22 08:01:04.431811: Current learning rate: 0.00556 +2024-11-22 08:01:23.818601: train_loss -0.7846 +2024-11-22 08:01:23.822774: val_loss -0.7478 +2024-11-22 08:01:23.822904: Pseudo dice [0.8476] +2024-11-22 08:01:23.822989: Epoch time: 19.39 s +2024-11-22 08:01:24.710704: +2024-11-22 08:01:24.710937: Epoch 3832 +2024-11-22 08:01:24.711048: Current learning rate: 0.00556 +2024-11-22 08:01:44.070206: train_loss -0.778 +2024-11-22 08:01:44.072449: val_loss -0.7637 +2024-11-22 08:01:44.072547: Pseudo dice [0.8479] +2024-11-22 08:01:44.072642: Epoch time: 19.36 s +2024-11-22 08:01:44.928031: +2024-11-22 08:01:44.928257: Epoch 3833 +2024-11-22 08:01:44.928372: Current learning rate: 0.00556 +2024-11-22 08:02:04.320274: train_loss -0.7784 +2024-11-22 08:02:04.326790: val_loss -0.7522 +2024-11-22 08:02:04.326989: Pseudo dice [0.8482] +2024-11-22 08:02:04.327089: Epoch time: 19.39 s +2024-11-22 08:02:05.200868: +2024-11-22 08:02:05.201087: Epoch 3834 +2024-11-22 08:02:05.201202: Current learning rate: 0.00556 +2024-11-22 08:02:23.894158: train_loss -0.7769 +2024-11-22 08:02:23.901941: val_loss -0.7601 +2024-11-22 08:02:23.902052: Pseudo dice [0.838] +2024-11-22 08:02:23.902136: Epoch time: 18.69 s +2024-11-22 08:02:24.857448: +2024-11-22 08:02:24.857666: Epoch 3835 +2024-11-22 08:02:24.857785: Current learning rate: 0.00556 +2024-11-22 08:02:44.484281: train_loss -0.7644 +2024-11-22 08:02:44.486998: val_loss -0.7596 +2024-11-22 08:02:44.487130: Pseudo dice [0.8625] +2024-11-22 08:02:44.487212: Epoch time: 19.63 s +2024-11-22 08:02:45.344673: +2024-11-22 08:02:45.344881: Epoch 3836 +2024-11-22 08:02:45.344993: Current learning rate: 0.00556 +2024-11-22 08:03:05.289203: train_loss -0.7817 +2024-11-22 08:03:05.291497: val_loss -0.7709 +2024-11-22 08:03:05.291592: Pseudo dice [0.8537] +2024-11-22 08:03:05.291680: Epoch time: 19.95 s +2024-11-22 08:03:06.141206: +2024-11-22 08:03:06.141412: Epoch 3837 +2024-11-22 08:03:06.141528: Current learning rate: 0.00556 +2024-11-22 08:03:25.001448: train_loss -0.7874 +2024-11-22 08:03:25.006502: val_loss -0.7625 +2024-11-22 08:03:25.006616: Pseudo dice [0.8517] +2024-11-22 08:03:25.006708: Epoch time: 18.86 s +2024-11-22 08:03:25.867345: +2024-11-22 08:03:25.867576: Epoch 3838 +2024-11-22 08:03:25.867690: Current learning rate: 0.00555 +2024-11-22 08:03:45.631972: train_loss -0.7838 +2024-11-22 08:03:45.638510: val_loss -0.7809 +2024-11-22 08:03:45.638647: Pseudo dice [0.8572] +2024-11-22 08:03:45.638733: Epoch time: 19.77 s +2024-11-22 08:03:46.560069: +2024-11-22 08:03:46.560270: Epoch 3839 +2024-11-22 08:03:46.560381: Current learning rate: 0.00555 +2024-11-22 08:04:05.365894: train_loss -0.786 +2024-11-22 08:04:05.375441: val_loss -0.7757 +2024-11-22 08:04:05.375578: Pseudo dice [0.8534] +2024-11-22 08:04:05.375725: Epoch time: 18.81 s +2024-11-22 08:04:06.230526: +2024-11-22 08:04:06.230723: Epoch 3840 +2024-11-22 08:04:06.230832: Current learning rate: 0.00555 +2024-11-22 08:04:25.556066: train_loss -0.788 +2024-11-22 08:04:25.559579: val_loss -0.7757 +2024-11-22 08:04:25.559686: Pseudo dice [0.8668] +2024-11-22 08:04:25.559764: Epoch time: 19.33 s +2024-11-22 08:04:27.042143: +2024-11-22 08:04:27.042584: Epoch 3841 +2024-11-22 08:04:27.042712: Current learning rate: 0.00555 +2024-11-22 08:04:46.188837: train_loss -0.7917 +2024-11-22 08:04:46.193193: val_loss -0.7793 +2024-11-22 08:04:46.193325: Pseudo dice [0.844] +2024-11-22 08:04:46.193406: Epoch time: 19.15 s +2024-11-22 08:04:47.052084: +2024-11-22 08:04:47.052529: Epoch 3842 +2024-11-22 08:04:47.052662: Current learning rate: 0.00555 +2024-11-22 08:05:06.148104: train_loss -0.7911 +2024-11-22 08:05:06.154302: val_loss -0.7962 +2024-11-22 08:05:06.154428: Pseudo dice [0.8573] +2024-11-22 08:05:06.154516: Epoch time: 19.1 s +2024-11-22 08:05:07.006612: +2024-11-22 08:05:07.007045: Epoch 3843 +2024-11-22 08:05:07.007185: Current learning rate: 0.00555 +2024-11-22 08:05:26.069806: train_loss -0.7794 +2024-11-22 08:05:26.075869: val_loss -0.7553 +2024-11-22 08:05:26.076024: Pseudo dice [0.8615] +2024-11-22 08:05:26.076121: Epoch time: 19.06 s +2024-11-22 08:05:27.181540: +2024-11-22 08:05:27.182019: Epoch 3844 +2024-11-22 08:05:27.182159: Current learning rate: 0.00555 +2024-11-22 08:05:47.129829: train_loss -0.7707 +2024-11-22 08:05:47.132087: val_loss -0.7653 +2024-11-22 08:05:47.132215: Pseudo dice [0.8317] +2024-11-22 08:05:47.132298: Epoch time: 19.95 s +2024-11-22 08:05:48.088851: +2024-11-22 08:05:48.089283: Epoch 3845 +2024-11-22 08:05:48.089425: Current learning rate: 0.00555 +2024-11-22 08:06:08.104247: train_loss -0.775 +2024-11-22 08:06:08.111332: val_loss -0.7772 +2024-11-22 08:06:08.111452: Pseudo dice [0.8503] +2024-11-22 08:06:08.111547: Epoch time: 20.02 s +2024-11-22 08:06:08.965648: +2024-11-22 08:06:08.966079: Epoch 3846 +2024-11-22 08:06:08.966213: Current learning rate: 0.00554 +2024-11-22 08:06:29.875792: train_loss -0.7772 +2024-11-22 08:06:29.880769: val_loss -0.7659 +2024-11-22 08:06:29.880918: Pseudo dice [0.8496] +2024-11-22 08:06:29.881023: Epoch time: 20.91 s +2024-11-22 08:06:30.741228: +2024-11-22 08:06:30.741633: Epoch 3847 +2024-11-22 08:06:30.741771: Current learning rate: 0.00554 +2024-11-22 08:06:50.555956: train_loss -0.7889 +2024-11-22 08:06:50.558558: val_loss -0.7745 +2024-11-22 08:06:50.558662: Pseudo dice [0.8454] +2024-11-22 08:06:50.558748: Epoch time: 19.82 s +2024-11-22 08:06:51.592001: +2024-11-22 08:06:51.592414: Epoch 3848 +2024-11-22 08:06:51.592546: Current learning rate: 0.00554 +2024-11-22 08:07:10.813036: train_loss -0.7824 +2024-11-22 08:07:10.820794: val_loss -0.7692 +2024-11-22 08:07:10.820927: Pseudo dice [0.8496] +2024-11-22 08:07:10.821008: Epoch time: 19.22 s +2024-11-22 08:07:11.677392: +2024-11-22 08:07:11.677818: Epoch 3849 +2024-11-22 08:07:11.677951: Current learning rate: 0.00554 +2024-11-22 08:07:30.873876: train_loss -0.7452 +2024-11-22 08:07:30.883649: val_loss -0.7574 +2024-11-22 08:07:30.883779: Pseudo dice [0.8334] +2024-11-22 08:07:30.883861: Epoch time: 19.2 s +2024-11-22 08:07:32.018919: +2024-11-22 08:07:32.019324: Epoch 3850 +2024-11-22 08:07:32.019452: Current learning rate: 0.00554 +2024-11-22 08:07:50.959843: train_loss -0.7742 +2024-11-22 08:07:50.963617: val_loss -0.7475 +2024-11-22 08:07:50.963742: Pseudo dice [0.8369] +2024-11-22 08:07:50.963828: Epoch time: 18.94 s +2024-11-22 08:07:51.866784: +2024-11-22 08:07:51.867212: Epoch 3851 +2024-11-22 08:07:51.867343: Current learning rate: 0.00554 +2024-11-22 08:08:10.729287: train_loss -0.7699 +2024-11-22 08:08:10.731686: val_loss -0.7569 +2024-11-22 08:08:10.731788: Pseudo dice [0.8439] +2024-11-22 08:08:10.731870: Epoch time: 18.86 s +2024-11-22 08:08:12.002915: +2024-11-22 08:08:12.003156: Epoch 3852 +2024-11-22 08:08:12.003273: Current learning rate: 0.00554 +2024-11-22 08:08:31.025689: train_loss -0.7736 +2024-11-22 08:08:31.036025: val_loss -0.7634 +2024-11-22 08:08:31.036190: Pseudo dice [0.8392] +2024-11-22 08:08:31.036274: Epoch time: 19.02 s +2024-11-22 08:08:31.926035: +2024-11-22 08:08:31.926253: Epoch 3853 +2024-11-22 08:08:31.926363: Current learning rate: 0.00554 +2024-11-22 08:08:51.884550: train_loss -0.7771 +2024-11-22 08:08:51.889348: val_loss -0.7718 +2024-11-22 08:08:51.889473: Pseudo dice [0.8397] +2024-11-22 08:08:51.889566: Epoch time: 19.96 s +2024-11-22 08:08:52.872711: +2024-11-22 08:08:52.872917: Epoch 3854 +2024-11-22 08:08:52.873025: Current learning rate: 0.00553 +2024-11-22 08:09:11.792794: train_loss -0.7745 +2024-11-22 08:09:11.798404: val_loss -0.7684 +2024-11-22 08:09:11.798530: Pseudo dice [0.8329] +2024-11-22 08:09:11.798610: Epoch time: 18.92 s +2024-11-22 08:09:12.704457: +2024-11-22 08:09:12.704708: Epoch 3855 +2024-11-22 08:09:12.704817: Current learning rate: 0.00553 +2024-11-22 08:09:31.731349: train_loss -0.7749 +2024-11-22 08:09:31.732922: val_loss -0.7404 +2024-11-22 08:09:31.733011: Pseudo dice [0.8412] +2024-11-22 08:09:31.733098: Epoch time: 19.03 s +2024-11-22 08:09:32.580942: +2024-11-22 08:09:32.581172: Epoch 3856 +2024-11-22 08:09:32.581510: Current learning rate: 0.00553 +2024-11-22 08:09:51.216770: train_loss -0.7752 +2024-11-22 08:09:51.221000: val_loss -0.7729 +2024-11-22 08:09:51.221118: Pseudo dice [0.8655] +2024-11-22 08:09:51.221197: Epoch time: 18.64 s +2024-11-22 08:09:52.100152: +2024-11-22 08:09:52.100369: Epoch 3857 +2024-11-22 08:09:52.100481: Current learning rate: 0.00553 +2024-11-22 08:10:10.459712: train_loss -0.7884 +2024-11-22 08:10:10.462321: val_loss -0.7704 +2024-11-22 08:10:10.462435: Pseudo dice [0.8455] +2024-11-22 08:10:10.462524: Epoch time: 18.36 s +2024-11-22 08:10:11.502492: +2024-11-22 08:10:11.502708: Epoch 3858 +2024-11-22 08:10:11.502816: Current learning rate: 0.00553 +2024-11-22 08:10:29.902444: train_loss -0.791 +2024-11-22 08:10:29.906833: val_loss -0.7925 +2024-11-22 08:10:29.907044: Pseudo dice [0.8594] +2024-11-22 08:10:29.907174: Epoch time: 18.4 s +2024-11-22 08:10:30.773489: +2024-11-22 08:10:30.773697: Epoch 3859 +2024-11-22 08:10:30.773809: Current learning rate: 0.00553 +2024-11-22 08:10:49.709254: train_loss -0.7715 +2024-11-22 08:10:49.711815: val_loss -0.7567 +2024-11-22 08:10:49.711907: Pseudo dice [0.8449] +2024-11-22 08:10:49.711990: Epoch time: 18.94 s +2024-11-22 08:10:50.569407: +2024-11-22 08:10:50.569630: Epoch 3860 +2024-11-22 08:10:50.569744: Current learning rate: 0.00553 +2024-11-22 08:11:11.240279: train_loss -0.7419 +2024-11-22 08:11:11.254026: val_loss -0.7506 +2024-11-22 08:11:11.254179: Pseudo dice [0.8433] +2024-11-22 08:11:11.254267: Epoch time: 20.67 s +2024-11-22 08:11:12.260206: +2024-11-22 08:11:12.260421: Epoch 3861 +2024-11-22 08:11:12.260528: Current learning rate: 0.00553 +2024-11-22 08:11:30.522680: train_loss -0.7638 +2024-11-22 08:11:30.536645: val_loss -0.7693 +2024-11-22 08:11:30.536793: Pseudo dice [0.8593] +2024-11-22 08:11:30.536885: Epoch time: 18.26 s +2024-11-22 08:11:31.582448: +2024-11-22 08:11:31.582668: Epoch 3862 +2024-11-22 08:11:31.582793: Current learning rate: 0.00552 +2024-11-22 08:11:50.234132: train_loss -0.7789 +2024-11-22 08:11:50.236822: val_loss -0.7819 +2024-11-22 08:11:50.236946: Pseudo dice [0.8572] +2024-11-22 08:11:50.237029: Epoch time: 18.65 s +2024-11-22 08:11:51.256339: +2024-11-22 08:11:51.256608: Epoch 3863 +2024-11-22 08:11:51.256727: Current learning rate: 0.00552 +2024-11-22 08:12:10.565493: train_loss -0.7817 +2024-11-22 08:12:10.570983: val_loss -0.7716 +2024-11-22 08:12:10.571136: Pseudo dice [0.8533] +2024-11-22 08:12:10.571221: Epoch time: 19.31 s +2024-11-22 08:12:11.446964: +2024-11-22 08:12:11.447194: Epoch 3864 +2024-11-22 08:12:11.447301: Current learning rate: 0.00552 +2024-11-22 08:12:30.535095: train_loss -0.7852 +2024-11-22 08:12:30.540744: val_loss -0.7641 +2024-11-22 08:12:30.540878: Pseudo dice [0.8587] +2024-11-22 08:12:30.541024: Epoch time: 19.09 s +2024-11-22 08:12:31.395564: +2024-11-22 08:12:31.395787: Epoch 3865 +2024-11-22 08:12:31.395903: Current learning rate: 0.00552 +2024-11-22 08:12:49.480686: train_loss -0.779 +2024-11-22 08:12:49.483249: val_loss -0.77 +2024-11-22 08:12:49.483350: Pseudo dice [0.8621] +2024-11-22 08:12:49.483439: Epoch time: 18.09 s +2024-11-22 08:12:50.337603: +2024-11-22 08:12:50.337812: Epoch 3866 +2024-11-22 08:12:50.337922: Current learning rate: 0.00552 +2024-11-22 08:13:08.680008: train_loss -0.7779 +2024-11-22 08:13:08.686801: val_loss -0.7517 +2024-11-22 08:13:08.686905: Pseudo dice [0.8363] +2024-11-22 08:13:08.686980: Epoch time: 18.34 s +2024-11-22 08:13:09.755407: +2024-11-22 08:13:09.755619: Epoch 3867 +2024-11-22 08:13:09.755731: Current learning rate: 0.00552 +2024-11-22 08:13:29.963697: train_loss -0.763 +2024-11-22 08:13:29.970915: val_loss -0.7622 +2024-11-22 08:13:29.971051: Pseudo dice [0.8442] +2024-11-22 08:13:29.971159: Epoch time: 20.21 s +2024-11-22 08:13:30.834616: +2024-11-22 08:13:30.834831: Epoch 3868 +2024-11-22 08:13:30.834939: Current learning rate: 0.00552 +2024-11-22 08:13:48.397581: train_loss -0.7909 +2024-11-22 08:13:48.400148: val_loss -0.7707 +2024-11-22 08:13:48.400241: Pseudo dice [0.8486] +2024-11-22 08:13:48.400571: Epoch time: 17.56 s +2024-11-22 08:13:49.255409: +2024-11-22 08:13:49.255625: Epoch 3869 +2024-11-22 08:13:49.255736: Current learning rate: 0.00552 +2024-11-22 08:14:08.777015: train_loss -0.7793 +2024-11-22 08:14:08.784221: val_loss -0.7696 +2024-11-22 08:14:08.784345: Pseudo dice [0.8449] +2024-11-22 08:14:08.784427: Epoch time: 19.52 s +2024-11-22 08:14:09.651569: +2024-11-22 08:14:09.651780: Epoch 3870 +2024-11-22 08:14:09.651891: Current learning rate: 0.00552 +2024-11-22 08:14:29.965330: train_loss -0.7667 +2024-11-22 08:14:29.974414: val_loss -0.7719 +2024-11-22 08:14:29.974553: Pseudo dice [0.8534] +2024-11-22 08:14:29.974636: Epoch time: 20.31 s +2024-11-22 08:14:30.858545: +2024-11-22 08:14:30.858749: Epoch 3871 +2024-11-22 08:14:30.858867: Current learning rate: 0.00551 +2024-11-22 08:14:49.685648: train_loss -0.7661 +2024-11-22 08:14:49.690814: val_loss -0.7227 +2024-11-22 08:14:49.690948: Pseudo dice [0.8259] +2024-11-22 08:14:49.691030: Epoch time: 18.83 s +2024-11-22 08:14:50.668678: +2024-11-22 08:14:50.668927: Epoch 3872 +2024-11-22 08:14:50.669087: Current learning rate: 0.00551 +2024-11-22 08:15:08.915586: train_loss -0.7643 +2024-11-22 08:15:08.918571: val_loss -0.7785 +2024-11-22 08:15:08.918689: Pseudo dice [0.843] +2024-11-22 08:15:08.918775: Epoch time: 18.25 s +2024-11-22 08:15:09.821324: +2024-11-22 08:15:09.821535: Epoch 3873 +2024-11-22 08:15:09.821650: Current learning rate: 0.00551 +2024-11-22 08:15:28.373788: train_loss -0.7717 +2024-11-22 08:15:28.377637: val_loss -0.7716 +2024-11-22 08:15:28.377751: Pseudo dice [0.8496] +2024-11-22 08:15:28.377839: Epoch time: 18.55 s +2024-11-22 08:15:29.594972: +2024-11-22 08:15:29.595181: Epoch 3874 +2024-11-22 08:15:29.595298: Current learning rate: 0.00551 +2024-11-22 08:15:49.440820: train_loss -0.782 +2024-11-22 08:15:49.443080: val_loss -0.7565 +2024-11-22 08:15:49.443181: Pseudo dice [0.8574] +2024-11-22 08:15:49.443274: Epoch time: 19.85 s +2024-11-22 08:15:50.299770: +2024-11-22 08:15:50.300030: Epoch 3875 +2024-11-22 08:15:50.300146: Current learning rate: 0.00551 +2024-11-22 08:16:09.730857: train_loss -0.7849 +2024-11-22 08:16:09.735845: val_loss -0.7825 +2024-11-22 08:16:09.735967: Pseudo dice [0.8535] +2024-11-22 08:16:09.736050: Epoch time: 19.43 s +2024-11-22 08:16:10.614435: +2024-11-22 08:16:10.614670: Epoch 3876 +2024-11-22 08:16:10.614783: Current learning rate: 0.00551 +2024-11-22 08:16:30.425733: train_loss -0.7857 +2024-11-22 08:16:30.430436: val_loss -0.7638 +2024-11-22 08:16:30.430605: Pseudo dice [0.839] +2024-11-22 08:16:30.432599: Epoch time: 19.81 s +2024-11-22 08:16:31.283372: +2024-11-22 08:16:31.283587: Epoch 3877 +2024-11-22 08:16:31.283700: Current learning rate: 0.00551 +2024-11-22 08:16:49.726533: train_loss -0.7844 +2024-11-22 08:16:49.736164: val_loss -0.7581 +2024-11-22 08:16:49.736295: Pseudo dice [0.8496] +2024-11-22 08:16:49.736372: Epoch time: 18.44 s +2024-11-22 08:16:50.578763: +2024-11-22 08:16:50.578992: Epoch 3878 +2024-11-22 08:16:50.579113: Current learning rate: 0.00551 +2024-11-22 08:17:10.587163: train_loss -0.7868 +2024-11-22 08:17:10.593275: val_loss -0.7658 +2024-11-22 08:17:10.593401: Pseudo dice [0.8527] +2024-11-22 08:17:10.593489: Epoch time: 20.01 s +2024-11-22 08:17:11.556165: +2024-11-22 08:17:11.556369: Epoch 3879 +2024-11-22 08:17:11.556482: Current learning rate: 0.0055 +2024-11-22 08:17:30.419361: train_loss -0.7867 +2024-11-22 08:17:30.421245: val_loss -0.7899 +2024-11-22 08:17:30.421368: Pseudo dice [0.8682] +2024-11-22 08:17:30.421456: Epoch time: 18.86 s +2024-11-22 08:17:31.272679: +2024-11-22 08:17:31.272894: Epoch 3880 +2024-11-22 08:17:31.273005: Current learning rate: 0.0055 +2024-11-22 08:17:50.413361: train_loss -0.7835 +2024-11-22 08:17:50.418128: val_loss -0.7705 +2024-11-22 08:17:50.418259: Pseudo dice [0.8515] +2024-11-22 08:17:50.418345: Epoch time: 19.14 s +2024-11-22 08:17:51.277500: +2024-11-22 08:17:51.277704: Epoch 3881 +2024-11-22 08:17:51.277817: Current learning rate: 0.0055 +2024-11-22 08:18:10.110395: train_loss -0.7818 +2024-11-22 08:18:10.116208: val_loss -0.7561 +2024-11-22 08:18:10.116348: Pseudo dice [0.8448] +2024-11-22 08:18:10.116439: Epoch time: 18.83 s +2024-11-22 08:18:10.984753: +2024-11-22 08:18:10.984953: Epoch 3882 +2024-11-22 08:18:10.985070: Current learning rate: 0.0055 +2024-11-22 08:18:30.691488: train_loss -0.7766 +2024-11-22 08:18:30.694158: val_loss -0.7554 +2024-11-22 08:18:30.694269: Pseudo dice [0.8358] +2024-11-22 08:18:30.694363: Epoch time: 19.71 s +2024-11-22 08:18:31.557919: +2024-11-22 08:18:31.558123: Epoch 3883 +2024-11-22 08:18:31.558234: Current learning rate: 0.0055 +2024-11-22 08:18:50.398851: train_loss -0.7775 +2024-11-22 08:18:50.402024: val_loss -0.7611 +2024-11-22 08:18:50.402174: Pseudo dice [0.8567] +2024-11-22 08:18:50.402259: Epoch time: 18.84 s +2024-11-22 08:18:51.368546: +2024-11-22 08:18:51.368746: Epoch 3884 +2024-11-22 08:18:51.368859: Current learning rate: 0.0055 +2024-11-22 08:19:10.355763: train_loss -0.7823 +2024-11-22 08:19:10.358338: val_loss -0.7597 +2024-11-22 08:19:10.358431: Pseudo dice [0.8502] +2024-11-22 08:19:10.358509: Epoch time: 18.99 s +2024-11-22 08:19:11.209239: +2024-11-22 08:19:11.209442: Epoch 3885 +2024-11-22 08:19:11.209555: Current learning rate: 0.0055 +2024-11-22 08:19:30.951168: train_loss -0.7836 +2024-11-22 08:19:30.958347: val_loss -0.7928 +2024-11-22 08:19:30.958468: Pseudo dice [0.8625] +2024-11-22 08:19:30.958546: Epoch time: 19.74 s +2024-11-22 08:19:32.323113: +2024-11-22 08:19:32.323322: Epoch 3886 +2024-11-22 08:19:32.323433: Current learning rate: 0.0055 +2024-11-22 08:19:50.573690: train_loss -0.7772 +2024-11-22 08:19:50.575196: val_loss -0.7757 +2024-11-22 08:19:50.575323: Pseudo dice [0.8482] +2024-11-22 08:19:50.575416: Epoch time: 18.25 s +2024-11-22 08:19:51.448352: +2024-11-22 08:19:51.448556: Epoch 3887 +2024-11-22 08:19:51.448680: Current learning rate: 0.00549 +2024-11-22 08:20:10.683070: train_loss -0.7787 +2024-11-22 08:20:10.686199: val_loss -0.7681 +2024-11-22 08:20:10.686323: Pseudo dice [0.8544] +2024-11-22 08:20:10.686400: Epoch time: 19.24 s +2024-11-22 08:20:11.605681: +2024-11-22 08:20:11.605918: Epoch 3888 +2024-11-22 08:20:11.606032: Current learning rate: 0.00549 +2024-11-22 08:20:31.126201: train_loss -0.7772 +2024-11-22 08:20:31.129541: val_loss -0.7368 +2024-11-22 08:20:31.129645: Pseudo dice [0.8616] +2024-11-22 08:20:31.129719: Epoch time: 19.52 s +2024-11-22 08:20:31.995369: +2024-11-22 08:20:31.995590: Epoch 3889 +2024-11-22 08:20:31.995703: Current learning rate: 0.00549 +2024-11-22 08:20:51.441611: train_loss -0.7609 +2024-11-22 08:20:51.448761: val_loss -0.7584 +2024-11-22 08:20:51.448876: Pseudo dice [0.8596] +2024-11-22 08:20:51.448964: Epoch time: 19.45 s +2024-11-22 08:20:52.310520: +2024-11-22 08:20:52.310736: Epoch 3890 +2024-11-22 08:20:52.310855: Current learning rate: 0.00549 +2024-11-22 08:21:10.072635: train_loss -0.7806 +2024-11-22 08:21:10.077256: val_loss -0.7764 +2024-11-22 08:21:10.082196: Pseudo dice [0.8615] +2024-11-22 08:21:10.082308: Epoch time: 17.76 s +2024-11-22 08:21:11.092150: +2024-11-22 08:21:11.092360: Epoch 3891 +2024-11-22 08:21:11.092477: Current learning rate: 0.00549 +2024-11-22 08:21:30.486403: train_loss -0.7882 +2024-11-22 08:21:30.493637: val_loss -0.7456 +2024-11-22 08:21:30.493758: Pseudo dice [0.8374] +2024-11-22 08:21:30.493840: Epoch time: 19.4 s +2024-11-22 08:21:31.352285: +2024-11-22 08:21:31.352485: Epoch 3892 +2024-11-22 08:21:31.352596: Current learning rate: 0.00549 +2024-11-22 08:21:52.420021: train_loss -0.7764 +2024-11-22 08:21:52.427254: val_loss -0.8031 +2024-11-22 08:21:52.427398: Pseudo dice [0.8636] +2024-11-22 08:21:52.427482: Epoch time: 21.07 s +2024-11-22 08:21:53.290517: +2024-11-22 08:21:53.290733: Epoch 3893 +2024-11-22 08:21:53.290849: Current learning rate: 0.00549 +2024-11-22 08:22:12.499580: train_loss -0.777 +2024-11-22 08:22:12.513775: val_loss -0.7547 +2024-11-22 08:22:12.513903: Pseudo dice [0.8472] +2024-11-22 08:22:12.513993: Epoch time: 19.21 s +2024-11-22 08:22:13.464820: +2024-11-22 08:22:13.465008: Epoch 3894 +2024-11-22 08:22:13.465127: Current learning rate: 0.00549 +2024-11-22 08:22:31.474054: train_loss -0.7881 +2024-11-22 08:22:31.479841: val_loss -0.7889 +2024-11-22 08:22:31.479967: Pseudo dice [0.8622] +2024-11-22 08:22:31.480290: Epoch time: 18.01 s +2024-11-22 08:22:32.358564: +2024-11-22 08:22:32.358772: Epoch 3895 +2024-11-22 08:22:32.358889: Current learning rate: 0.00549 +2024-11-22 08:22:51.441989: train_loss -0.7782 +2024-11-22 08:22:51.449178: val_loss -0.741 +2024-11-22 08:22:51.449310: Pseudo dice [0.8419] +2024-11-22 08:22:51.449393: Epoch time: 19.08 s +2024-11-22 08:22:52.303675: +2024-11-22 08:22:52.303883: Epoch 3896 +2024-11-22 08:22:52.303997: Current learning rate: 0.00548 +2024-11-22 08:23:11.128852: train_loss -0.7822 +2024-11-22 08:23:11.131794: val_loss -0.7689 +2024-11-22 08:23:11.131937: Pseudo dice [0.8467] +2024-11-22 08:23:11.132030: Epoch time: 18.83 s +2024-11-22 08:23:12.375960: +2024-11-22 08:23:12.376172: Epoch 3897 +2024-11-22 08:23:12.376283: Current learning rate: 0.00548 +2024-11-22 08:23:31.526323: train_loss -0.782 +2024-11-22 08:23:31.533390: val_loss -0.7823 +2024-11-22 08:23:31.533533: Pseudo dice [0.8523] +2024-11-22 08:23:31.533623: Epoch time: 19.15 s +2024-11-22 08:23:32.394996: +2024-11-22 08:23:32.395243: Epoch 3898 +2024-11-22 08:23:32.395359: Current learning rate: 0.00548 +2024-11-22 08:23:52.318669: train_loss -0.7898 +2024-11-22 08:23:52.324170: val_loss -0.7831 +2024-11-22 08:23:52.324320: Pseudo dice [0.8511] +2024-11-22 08:23:52.324431: Epoch time: 19.92 s +2024-11-22 08:23:53.190729: +2024-11-22 08:23:53.190962: Epoch 3899 +2024-11-22 08:23:53.191078: Current learning rate: 0.00548 +2024-11-22 08:24:12.986239: train_loss -0.7852 +2024-11-22 08:24:12.991714: val_loss -0.7639 +2024-11-22 08:24:12.991818: Pseudo dice [0.8466] +2024-11-22 08:24:12.991904: Epoch time: 19.8 s +2024-11-22 08:24:14.131629: +2024-11-22 08:24:14.131837: Epoch 3900 +2024-11-22 08:24:14.131953: Current learning rate: 0.00548 +2024-11-22 08:24:33.489401: train_loss -0.7888 +2024-11-22 08:24:33.496434: val_loss -0.7559 +2024-11-22 08:24:33.496569: Pseudo dice [0.8575] +2024-11-22 08:24:33.496654: Epoch time: 19.36 s +2024-11-22 08:24:34.384910: +2024-11-22 08:24:34.385136: Epoch 3901 +2024-11-22 08:24:34.385247: Current learning rate: 0.00548 +2024-11-22 08:24:53.054479: train_loss -0.7832 +2024-11-22 08:24:53.056024: val_loss -0.767 +2024-11-22 08:24:53.056139: Pseudo dice [0.8544] +2024-11-22 08:24:53.056222: Epoch time: 18.67 s +2024-11-22 08:24:54.146250: +2024-11-22 08:24:54.146456: Epoch 3902 +2024-11-22 08:24:54.146569: Current learning rate: 0.00548 +2024-11-22 08:25:12.236795: train_loss -0.7914 +2024-11-22 08:25:12.243249: val_loss -0.7558 +2024-11-22 08:25:12.243370: Pseudo dice [0.8571] +2024-11-22 08:25:12.243452: Epoch time: 18.09 s +2024-11-22 08:25:13.279148: +2024-11-22 08:25:13.279345: Epoch 3903 +2024-11-22 08:25:13.279455: Current learning rate: 0.00548 +2024-11-22 08:25:32.124460: train_loss -0.7799 +2024-11-22 08:25:32.138355: val_loss -0.7645 +2024-11-22 08:25:32.138495: Pseudo dice [0.8322] +2024-11-22 08:25:32.138579: Epoch time: 18.85 s +2024-11-22 08:25:33.050068: +2024-11-22 08:25:33.050262: Epoch 3904 +2024-11-22 08:25:33.050375: Current learning rate: 0.00547 +2024-11-22 08:25:51.256291: train_loss -0.7907 +2024-11-22 08:25:51.258830: val_loss -0.7575 +2024-11-22 08:25:51.258948: Pseudo dice [0.8514] +2024-11-22 08:25:51.259034: Epoch time: 18.21 s +2024-11-22 08:25:52.260530: +2024-11-22 08:25:52.260748: Epoch 3905 +2024-11-22 08:25:52.260868: Current learning rate: 0.00547 +2024-11-22 08:26:11.194023: train_loss -0.7881 +2024-11-22 08:26:11.201666: val_loss -0.7834 +2024-11-22 08:26:11.201802: Pseudo dice [0.8498] +2024-11-22 08:26:11.201891: Epoch time: 18.93 s +2024-11-22 08:26:12.058369: +2024-11-22 08:26:12.058576: Epoch 3906 +2024-11-22 08:26:12.058686: Current learning rate: 0.00547 +2024-11-22 08:26:31.727863: train_loss -0.7926 +2024-11-22 08:26:31.729985: val_loss -0.7701 +2024-11-22 08:26:31.730080: Pseudo dice [0.8442] +2024-11-22 08:26:31.730156: Epoch time: 19.67 s +2024-11-22 08:26:32.582169: +2024-11-22 08:26:32.582369: Epoch 3907 +2024-11-22 08:26:32.582483: Current learning rate: 0.00547 +2024-11-22 08:26:51.893781: train_loss -0.7815 +2024-11-22 08:26:51.895755: val_loss -0.7825 +2024-11-22 08:26:51.895883: Pseudo dice [0.8581] +2024-11-22 08:26:51.895971: Epoch time: 19.31 s +2024-11-22 08:26:53.156962: +2024-11-22 08:26:53.157161: Epoch 3908 +2024-11-22 08:26:53.157274: Current learning rate: 0.00547 +2024-11-22 08:27:11.884201: train_loss -0.7888 +2024-11-22 08:27:11.896179: val_loss -0.7581 +2024-11-22 08:27:11.896317: Pseudo dice [0.8551] +2024-11-22 08:27:11.896406: Epoch time: 18.73 s +2024-11-22 08:27:12.758541: +2024-11-22 08:27:12.758757: Epoch 3909 +2024-11-22 08:27:12.758873: Current learning rate: 0.00547 +2024-11-22 08:27:32.145812: train_loss -0.7854 +2024-11-22 08:27:32.149339: val_loss -0.7681 +2024-11-22 08:27:32.149451: Pseudo dice [0.8491] +2024-11-22 08:27:32.149535: Epoch time: 19.39 s +2024-11-22 08:27:33.158795: +2024-11-22 08:27:33.158993: Epoch 3910 +2024-11-22 08:27:33.159107: Current learning rate: 0.00547 +2024-11-22 08:27:52.912843: train_loss -0.7916 +2024-11-22 08:27:52.915744: val_loss -0.7888 +2024-11-22 08:27:52.915925: Pseudo dice [0.8517] +2024-11-22 08:27:52.916024: Epoch time: 19.75 s +2024-11-22 08:27:53.928964: +2024-11-22 08:27:53.929174: Epoch 3911 +2024-11-22 08:27:53.929285: Current learning rate: 0.00547 +2024-11-22 08:28:12.509793: train_loss -0.7846 +2024-11-22 08:28:12.517657: val_loss -0.7748 +2024-11-22 08:28:12.517772: Pseudo dice [0.8602] +2024-11-22 08:28:12.517850: Epoch time: 18.58 s +2024-11-22 08:28:13.502536: +2024-11-22 08:28:13.502738: Epoch 3912 +2024-11-22 08:28:13.502854: Current learning rate: 0.00546 +2024-11-22 08:28:32.256170: train_loss -0.7881 +2024-11-22 08:28:32.263222: val_loss -0.7836 +2024-11-22 08:28:32.263365: Pseudo dice [0.8564] +2024-11-22 08:28:32.263460: Epoch time: 18.75 s +2024-11-22 08:28:33.205609: +2024-11-22 08:28:33.205832: Epoch 3913 +2024-11-22 08:28:33.205941: Current learning rate: 0.00546 +2024-11-22 08:28:52.603935: train_loss -0.7828 +2024-11-22 08:28:52.605482: val_loss -0.7574 +2024-11-22 08:28:52.605574: Pseudo dice [0.8461] +2024-11-22 08:28:52.605654: Epoch time: 19.4 s +2024-11-22 08:28:53.461999: +2024-11-22 08:28:53.462208: Epoch 3914 +2024-11-22 08:28:53.462327: Current learning rate: 0.00546 +2024-11-22 08:29:11.704266: train_loss -0.7791 +2024-11-22 08:29:11.710266: val_loss -0.7709 +2024-11-22 08:29:11.710399: Pseudo dice [0.8459] +2024-11-22 08:29:11.710479: Epoch time: 18.24 s +2024-11-22 08:29:12.758435: +2024-11-22 08:29:12.758625: Epoch 3915 +2024-11-22 08:29:12.758736: Current learning rate: 0.00546 +2024-11-22 08:29:31.495896: train_loss -0.775 +2024-11-22 08:29:31.502191: val_loss -0.7749 +2024-11-22 08:29:31.502315: Pseudo dice [0.8292] +2024-11-22 08:29:31.502402: Epoch time: 18.74 s +2024-11-22 08:29:32.375821: +2024-11-22 08:29:32.376047: Epoch 3916 +2024-11-22 08:29:32.376163: Current learning rate: 0.00546 +2024-11-22 08:29:52.165056: train_loss -0.7682 +2024-11-22 08:29:52.168598: val_loss -0.7671 +2024-11-22 08:29:52.168817: Pseudo dice [0.8387] +2024-11-22 08:29:52.168941: Epoch time: 19.79 s +2024-11-22 08:29:53.052928: +2024-11-22 08:29:53.053145: Epoch 3917 +2024-11-22 08:29:53.053260: Current learning rate: 0.00546 +2024-11-22 08:30:12.196782: train_loss -0.7765 +2024-11-22 08:30:12.201495: val_loss -0.7625 +2024-11-22 08:30:12.201618: Pseudo dice [0.8467] +2024-11-22 08:30:12.201697: Epoch time: 19.14 s +2024-11-22 08:30:13.059721: +2024-11-22 08:30:13.059967: Epoch 3918 +2024-11-22 08:30:13.060084: Current learning rate: 0.00546 +2024-11-22 08:30:32.252083: train_loss -0.7822 +2024-11-22 08:30:32.254725: val_loss -0.7624 +2024-11-22 08:30:32.254831: Pseudo dice [0.8529] +2024-11-22 08:30:32.254912: Epoch time: 19.19 s +2024-11-22 08:30:33.512459: +2024-11-22 08:30:33.512662: Epoch 3919 +2024-11-22 08:30:33.512779: Current learning rate: 0.00546 +2024-11-22 08:30:52.088577: train_loss -0.7802 +2024-11-22 08:30:52.091709: val_loss -0.7637 +2024-11-22 08:30:52.109195: Pseudo dice [0.8603] +2024-11-22 08:30:52.109430: Epoch time: 18.58 s +2024-11-22 08:30:52.968078: +2024-11-22 08:30:52.968493: Epoch 3920 +2024-11-22 08:30:52.968633: Current learning rate: 0.00546 +2024-11-22 08:31:12.455320: train_loss -0.7845 +2024-11-22 08:31:12.457127: val_loss -0.7917 +2024-11-22 08:31:12.457219: Pseudo dice [0.8672] +2024-11-22 08:31:12.457559: Epoch time: 19.49 s +2024-11-22 08:31:13.310068: +2024-11-22 08:31:13.310514: Epoch 3921 +2024-11-22 08:31:13.310645: Current learning rate: 0.00545 +2024-11-22 08:31:32.540177: train_loss -0.7761 +2024-11-22 08:31:32.545553: val_loss -0.7965 +2024-11-22 08:31:32.545690: Pseudo dice [0.8623] +2024-11-22 08:31:32.545769: Epoch time: 19.23 s +2024-11-22 08:31:33.416769: +2024-11-22 08:31:33.417243: Epoch 3922 +2024-11-22 08:31:33.417379: Current learning rate: 0.00545 +2024-11-22 08:31:52.090104: train_loss -0.7854 +2024-11-22 08:31:52.096143: val_loss -0.7619 +2024-11-22 08:31:52.096295: Pseudo dice [0.8676] +2024-11-22 08:31:52.096392: Epoch time: 18.67 s +2024-11-22 08:31:52.952341: +2024-11-22 08:31:52.952751: Epoch 3923 +2024-11-22 08:31:52.952880: Current learning rate: 0.00545 +2024-11-22 08:32:11.555907: train_loss -0.7805 +2024-11-22 08:32:11.561012: val_loss -0.7788 +2024-11-22 08:32:11.561125: Pseudo dice [0.8527] +2024-11-22 08:32:11.561211: Epoch time: 18.6 s +2024-11-22 08:32:12.461709: +2024-11-22 08:32:12.462124: Epoch 3924 +2024-11-22 08:32:12.462251: Current learning rate: 0.00545 +2024-11-22 08:32:32.202842: train_loss -0.7812 +2024-11-22 08:32:32.211573: val_loss -0.7797 +2024-11-22 08:32:32.211693: Pseudo dice [0.8619] +2024-11-22 08:32:32.211780: Epoch time: 19.74 s +2024-11-22 08:32:33.165306: +2024-11-22 08:32:33.165705: Epoch 3925 +2024-11-22 08:32:33.165843: Current learning rate: 0.00545 +2024-11-22 08:32:53.539990: train_loss -0.7719 +2024-11-22 08:32:53.542710: val_loss -0.7668 +2024-11-22 08:32:53.542809: Pseudo dice [0.8331] +2024-11-22 08:32:53.549969: Epoch time: 20.38 s +2024-11-22 08:32:54.407947: +2024-11-22 08:32:54.408364: Epoch 3926 +2024-11-22 08:32:54.408496: Current learning rate: 0.00545 +2024-11-22 08:33:13.091342: train_loss -0.7801 +2024-11-22 08:33:13.093656: val_loss -0.766 +2024-11-22 08:33:13.093782: Pseudo dice [0.8594] +2024-11-22 08:33:13.093874: Epoch time: 18.68 s +2024-11-22 08:33:14.045038: +2024-11-22 08:33:14.045456: Epoch 3927 +2024-11-22 08:33:14.045588: Current learning rate: 0.00545 +2024-11-22 08:33:33.412668: train_loss -0.7743 +2024-11-22 08:33:33.415028: val_loss -0.7308 +2024-11-22 08:33:33.415134: Pseudo dice [0.8558] +2024-11-22 08:33:33.415215: Epoch time: 19.37 s +2024-11-22 08:33:34.268101: +2024-11-22 08:33:34.268531: Epoch 3928 +2024-11-22 08:33:34.268661: Current learning rate: 0.00545 +2024-11-22 08:33:52.753350: train_loss -0.7879 +2024-11-22 08:33:52.762235: val_loss -0.7539 +2024-11-22 08:33:52.762369: Pseudo dice [0.8424] +2024-11-22 08:33:52.762458: Epoch time: 18.49 s +2024-11-22 08:33:53.612960: +2024-11-22 08:33:53.613373: Epoch 3929 +2024-11-22 08:33:53.613507: Current learning rate: 0.00544 +2024-11-22 08:34:13.483386: train_loss -0.7759 +2024-11-22 08:34:13.497066: val_loss -0.7619 +2024-11-22 08:34:13.497196: Pseudo dice [0.8466] +2024-11-22 08:34:13.497280: Epoch time: 19.87 s +2024-11-22 08:34:14.407777: +2024-11-22 08:34:14.407991: Epoch 3930 +2024-11-22 08:34:14.408108: Current learning rate: 0.00544 +2024-11-22 08:34:32.070395: train_loss -0.7832 +2024-11-22 08:34:32.077167: val_loss -0.7713 +2024-11-22 08:34:32.077306: Pseudo dice [0.8544] +2024-11-22 08:34:32.077397: Epoch time: 17.66 s +2024-11-22 08:34:33.414327: +2024-11-22 08:34:33.414613: Epoch 3931 +2024-11-22 08:34:33.414732: Current learning rate: 0.00544 +2024-11-22 08:34:51.895117: train_loss -0.7837 +2024-11-22 08:34:51.900213: val_loss -0.741 +2024-11-22 08:34:51.900346: Pseudo dice [0.8378] +2024-11-22 08:34:51.900425: Epoch time: 18.48 s +2024-11-22 08:34:52.781129: +2024-11-22 08:34:52.781343: Epoch 3932 +2024-11-22 08:34:52.781472: Current learning rate: 0.00544 +2024-11-22 08:35:11.596859: train_loss -0.7837 +2024-11-22 08:35:11.599180: val_loss -0.7777 +2024-11-22 08:35:11.599272: Pseudo dice [0.8586] +2024-11-22 08:35:11.599354: Epoch time: 18.82 s +2024-11-22 08:35:12.455801: +2024-11-22 08:35:12.456020: Epoch 3933 +2024-11-22 08:35:12.456137: Current learning rate: 0.00544 +2024-11-22 08:35:31.167200: train_loss -0.7772 +2024-11-22 08:35:31.172190: val_loss -0.7702 +2024-11-22 08:35:31.172324: Pseudo dice [0.8375] +2024-11-22 08:35:31.172409: Epoch time: 18.71 s +2024-11-22 08:35:32.068751: +2024-11-22 08:35:32.069035: Epoch 3934 +2024-11-22 08:35:32.069195: Current learning rate: 0.00544 +2024-11-22 08:35:51.069389: train_loss -0.7776 +2024-11-22 08:35:51.076477: val_loss -0.7437 +2024-11-22 08:35:51.076613: Pseudo dice [0.8589] +2024-11-22 08:35:51.076705: Epoch time: 19.0 s +2024-11-22 08:35:52.004163: +2024-11-22 08:35:52.004389: Epoch 3935 +2024-11-22 08:35:52.004505: Current learning rate: 0.00544 +2024-11-22 08:36:10.435544: train_loss -0.7752 +2024-11-22 08:36:10.437817: val_loss -0.7829 +2024-11-22 08:36:10.438007: Pseudo dice [0.862] +2024-11-22 08:36:10.438096: Epoch time: 18.43 s +2024-11-22 08:36:11.300936: +2024-11-22 08:36:11.301230: Epoch 3936 +2024-11-22 08:36:11.301349: Current learning rate: 0.00544 +2024-11-22 08:36:30.938997: train_loss -0.7825 +2024-11-22 08:36:30.941384: val_loss -0.7501 +2024-11-22 08:36:30.941475: Pseudo dice [0.8549] +2024-11-22 08:36:30.941555: Epoch time: 19.64 s +2024-11-22 08:36:31.796989: +2024-11-22 08:36:31.797195: Epoch 3937 +2024-11-22 08:36:31.797307: Current learning rate: 0.00543 +2024-11-22 08:36:51.036004: train_loss -0.7738 +2024-11-22 08:36:51.038549: val_loss -0.7615 +2024-11-22 08:36:51.038690: Pseudo dice [0.8415] +2024-11-22 08:36:51.038780: Epoch time: 19.24 s +2024-11-22 08:36:51.901453: +2024-11-22 08:36:51.901658: Epoch 3938 +2024-11-22 08:36:51.901772: Current learning rate: 0.00543 +2024-11-22 08:37:11.881651: train_loss -0.7795 +2024-11-22 08:37:11.885460: val_loss -0.7394 +2024-11-22 08:37:11.885570: Pseudo dice [0.8164] +2024-11-22 08:37:11.885654: Epoch time: 19.98 s +2024-11-22 08:37:12.743912: +2024-11-22 08:37:12.744148: Epoch 3939 +2024-11-22 08:37:12.744258: Current learning rate: 0.00543 +2024-11-22 08:37:30.578183: train_loss -0.7773 +2024-11-22 08:37:30.584147: val_loss -0.7482 +2024-11-22 08:37:30.584276: Pseudo dice [0.8538] +2024-11-22 08:37:30.584365: Epoch time: 17.84 s +2024-11-22 08:37:31.441819: +2024-11-22 08:37:31.442011: Epoch 3940 +2024-11-22 08:37:31.442128: Current learning rate: 0.00543 +2024-11-22 08:37:50.308963: train_loss -0.7922 +2024-11-22 08:37:50.313725: val_loss -0.7443 +2024-11-22 08:37:50.313837: Pseudo dice [0.8443] +2024-11-22 08:37:50.313920: Epoch time: 18.87 s +2024-11-22 08:37:51.386428: +2024-11-22 08:37:51.386635: Epoch 3941 +2024-11-22 08:37:51.386748: Current learning rate: 0.00543 +2024-11-22 08:38:09.986387: train_loss -0.7867 +2024-11-22 08:38:09.988531: val_loss -0.7577 +2024-11-22 08:38:09.988667: Pseudo dice [0.8551] +2024-11-22 08:38:09.988750: Epoch time: 18.6 s +2024-11-22 08:38:11.256473: +2024-11-22 08:38:11.256674: Epoch 3942 +2024-11-22 08:38:11.256811: Current learning rate: 0.00543 +2024-11-22 08:38:31.113384: train_loss -0.7854 +2024-11-22 08:38:31.118902: val_loss -0.7565 +2024-11-22 08:38:31.119031: Pseudo dice [0.8437] +2024-11-22 08:38:31.119121: Epoch time: 19.86 s +2024-11-22 08:38:31.972775: +2024-11-22 08:38:31.973051: Epoch 3943 +2024-11-22 08:38:31.973165: Current learning rate: 0.00543 +2024-11-22 08:38:52.092972: train_loss -0.7817 +2024-11-22 08:38:52.101129: val_loss -0.7821 +2024-11-22 08:38:52.101265: Pseudo dice [0.8548] +2024-11-22 08:38:52.101347: Epoch time: 20.12 s +2024-11-22 08:38:53.142087: +2024-11-22 08:38:53.142393: Epoch 3944 +2024-11-22 08:38:53.142503: Current learning rate: 0.00543 +2024-11-22 08:39:13.057087: train_loss -0.78 +2024-11-22 08:39:13.063405: val_loss -0.764 +2024-11-22 08:39:13.063598: Pseudo dice [0.8551] +2024-11-22 08:39:13.063687: Epoch time: 19.91 s +2024-11-22 08:39:13.922623: +2024-11-22 08:39:13.923099: Epoch 3945 +2024-11-22 08:39:13.923218: Current learning rate: 0.00543 +2024-11-22 08:39:33.187189: train_loss -0.7844 +2024-11-22 08:39:33.189731: val_loss -0.7822 +2024-11-22 08:39:33.189853: Pseudo dice [0.8559] +2024-11-22 08:39:33.189944: Epoch time: 19.27 s +2024-11-22 08:39:34.252283: +2024-11-22 08:39:34.252536: Epoch 3946 +2024-11-22 08:39:34.252646: Current learning rate: 0.00542 +2024-11-22 08:39:53.166637: train_loss -0.7787 +2024-11-22 08:39:53.170959: val_loss -0.7468 +2024-11-22 08:39:53.171360: Pseudo dice [0.852] +2024-11-22 08:39:53.171456: Epoch time: 18.92 s +2024-11-22 08:39:54.040232: +2024-11-22 08:39:54.040449: Epoch 3947 +2024-11-22 08:39:54.040562: Current learning rate: 0.00542 +2024-11-22 08:40:14.676251: train_loss -0.776 +2024-11-22 08:40:14.683204: val_loss -0.7792 +2024-11-22 08:40:14.683334: Pseudo dice [0.8597] +2024-11-22 08:40:14.683416: Epoch time: 20.64 s +2024-11-22 08:40:15.540483: +2024-11-22 08:40:15.540716: Epoch 3948 +2024-11-22 08:40:15.540831: Current learning rate: 0.00542 +2024-11-22 08:40:35.859546: train_loss -0.7779 +2024-11-22 08:40:35.867263: val_loss -0.7659 +2024-11-22 08:40:35.867401: Pseudo dice [0.8583] +2024-11-22 08:40:35.867492: Epoch time: 20.32 s +2024-11-22 08:40:36.721714: +2024-11-22 08:40:36.721916: Epoch 3949 +2024-11-22 08:40:36.722026: Current learning rate: 0.00542 +2024-11-22 08:40:55.072789: train_loss -0.7791 +2024-11-22 08:40:55.075416: val_loss -0.7716 +2024-11-22 08:40:55.075522: Pseudo dice [0.854] +2024-11-22 08:40:55.075608: Epoch time: 18.35 s +2024-11-22 08:40:56.202328: +2024-11-22 08:40:56.202600: Epoch 3950 +2024-11-22 08:40:56.202757: Current learning rate: 0.00542 +2024-11-22 08:41:16.307068: train_loss -0.7826 +2024-11-22 08:41:16.309606: val_loss -0.7695 +2024-11-22 08:41:16.309691: Pseudo dice [0.8479] +2024-11-22 08:41:16.309769: Epoch time: 20.11 s +2024-11-22 08:41:17.156233: +2024-11-22 08:41:17.156678: Epoch 3951 +2024-11-22 08:41:17.156791: Current learning rate: 0.00542 +2024-11-22 08:41:36.183716: train_loss -0.7841 +2024-11-22 08:41:36.187481: val_loss -0.7626 +2024-11-22 08:41:36.187582: Pseudo dice [0.8524] +2024-11-22 08:41:36.187670: Epoch time: 19.03 s +2024-11-22 08:41:37.043347: +2024-11-22 08:41:37.043548: Epoch 3952 +2024-11-22 08:41:37.043659: Current learning rate: 0.00542 +2024-11-22 08:41:56.088284: train_loss -0.7827 +2024-11-22 08:41:56.112613: val_loss -0.7854 +2024-11-22 08:41:56.112784: Pseudo dice [0.8563] +2024-11-22 08:41:56.112872: Epoch time: 19.05 s +2024-11-22 08:41:57.359668: +2024-11-22 08:41:57.359905: Epoch 3953 +2024-11-22 08:41:57.360018: Current learning rate: 0.00542 +2024-11-22 08:42:15.482573: train_loss -0.7774 +2024-11-22 08:42:15.489450: val_loss -0.7661 +2024-11-22 08:42:15.489595: Pseudo dice [0.8483] +2024-11-22 08:42:15.489684: Epoch time: 18.12 s +2024-11-22 08:42:16.366956: +2024-11-22 08:42:16.367220: Epoch 3954 +2024-11-22 08:42:16.367332: Current learning rate: 0.00541 +2024-11-22 08:42:36.247461: train_loss -0.7799 +2024-11-22 08:42:36.255081: val_loss -0.7618 +2024-11-22 08:42:36.255218: Pseudo dice [0.8543] +2024-11-22 08:42:36.255300: Epoch time: 19.88 s +2024-11-22 08:42:37.116866: +2024-11-22 08:42:37.117095: Epoch 3955 +2024-11-22 08:42:37.117214: Current learning rate: 0.00541 +2024-11-22 08:42:56.545101: train_loss -0.79 +2024-11-22 08:42:56.549378: val_loss -0.7633 +2024-11-22 08:42:56.549511: Pseudo dice [0.8521] +2024-11-22 08:42:56.549587: Epoch time: 19.43 s +2024-11-22 08:42:57.409594: +2024-11-22 08:42:57.409788: Epoch 3956 +2024-11-22 08:42:57.409900: Current learning rate: 0.00541 +2024-11-22 08:43:16.327265: train_loss -0.7889 +2024-11-22 08:43:16.329523: val_loss -0.7607 +2024-11-22 08:43:16.329630: Pseudo dice [0.8532] +2024-11-22 08:43:16.329713: Epoch time: 18.92 s +2024-11-22 08:43:17.430361: +2024-11-22 08:43:17.430586: Epoch 3957 +2024-11-22 08:43:17.430701: Current learning rate: 0.00541 +2024-11-22 08:43:37.090999: train_loss -0.7867 +2024-11-22 08:43:37.091236: val_loss -0.7633 +2024-11-22 08:43:37.091317: Pseudo dice [0.8548] +2024-11-22 08:43:37.091896: Epoch time: 19.66 s +2024-11-22 08:43:37.950610: +2024-11-22 08:43:37.950825: Epoch 3958 +2024-11-22 08:43:37.950932: Current learning rate: 0.00541 +2024-11-22 08:43:56.029576: train_loss -0.7794 +2024-11-22 08:43:56.029811: val_loss -0.7594 +2024-11-22 08:43:56.029887: Pseudo dice [0.8414] +2024-11-22 08:43:56.029962: Epoch time: 18.08 s +2024-11-22 08:43:56.879971: +2024-11-22 08:43:56.880192: Epoch 3959 +2024-11-22 08:43:56.880303: Current learning rate: 0.00541 +2024-11-22 08:44:14.777320: train_loss -0.7884 +2024-11-22 08:44:14.777520: val_loss -0.7775 +2024-11-22 08:44:14.777596: Pseudo dice [0.848] +2024-11-22 08:44:14.777670: Epoch time: 17.9 s +2024-11-22 08:44:15.633981: +2024-11-22 08:44:15.634252: Epoch 3960 +2024-11-22 08:44:15.634362: Current learning rate: 0.00541 +2024-11-22 08:44:36.230929: train_loss -0.7813 +2024-11-22 08:44:36.231136: val_loss -0.7718 +2024-11-22 08:44:36.231219: Pseudo dice [0.8419] +2024-11-22 08:44:36.231301: Epoch time: 20.6 s +2024-11-22 08:44:37.074346: +2024-11-22 08:44:37.074559: Epoch 3961 +2024-11-22 08:44:37.074664: Current learning rate: 0.00541 +2024-11-22 08:44:54.889650: train_loss -0.7846 +2024-11-22 08:44:54.889867: val_loss -0.7744 +2024-11-22 08:44:54.889943: Pseudo dice [0.843] +2024-11-22 08:44:54.890023: Epoch time: 17.82 s +2024-11-22 08:44:55.845200: +2024-11-22 08:44:55.845392: Epoch 3962 +2024-11-22 08:44:55.845502: Current learning rate: 0.0054 +2024-11-22 08:45:14.443174: train_loss -0.7854 +2024-11-22 08:45:14.443374: val_loss -0.759 +2024-11-22 08:45:14.443447: Pseudo dice [0.8509] +2024-11-22 08:45:14.443524: Epoch time: 18.6 s +2024-11-22 08:45:15.321504: +2024-11-22 08:45:15.321718: Epoch 3963 +2024-11-22 08:45:15.321832: Current learning rate: 0.0054 +2024-11-22 08:45:33.575947: train_loss -0.7922 +2024-11-22 08:45:33.576167: val_loss -0.7817 +2024-11-22 08:45:33.576243: Pseudo dice [0.8623] +2024-11-22 08:45:33.576319: Epoch time: 18.26 s +2024-11-22 08:45:34.426494: +2024-11-22 08:45:34.426709: Epoch 3964 +2024-11-22 08:45:34.426816: Current learning rate: 0.0054 +2024-11-22 08:45:53.038194: train_loss -0.7824 +2024-11-22 08:45:53.038446: val_loss -0.7744 +2024-11-22 08:45:53.038523: Pseudo dice [0.8485] +2024-11-22 08:45:53.038664: Epoch time: 18.61 s +2024-11-22 08:45:54.275938: +2024-11-22 08:45:54.276108: Epoch 3965 +2024-11-22 08:45:54.276200: Current learning rate: 0.0054 +2024-11-22 08:46:12.060585: train_loss -0.7896 +2024-11-22 08:46:12.060807: val_loss -0.7742 +2024-11-22 08:46:12.060882: Pseudo dice [0.8401] +2024-11-22 08:46:12.060959: Epoch time: 17.79 s +2024-11-22 08:46:12.916787: +2024-11-22 08:46:12.917041: Epoch 3966 +2024-11-22 08:46:12.917151: Current learning rate: 0.0054 +2024-11-22 08:46:32.923238: train_loss -0.7937 +2024-11-22 08:46:32.923451: val_loss -0.7701 +2024-11-22 08:46:32.923527: Pseudo dice [0.8493] +2024-11-22 08:46:32.923601: Epoch time: 20.01 s +2024-11-22 08:46:33.932266: +2024-11-22 08:46:33.932511: Epoch 3967 +2024-11-22 08:46:33.932622: Current learning rate: 0.0054 +2024-11-22 08:46:52.300267: train_loss -0.7947 +2024-11-22 08:46:52.300470: val_loss -0.7847 +2024-11-22 08:46:52.300543: Pseudo dice [0.8507] +2024-11-22 08:46:52.300620: Epoch time: 18.37 s +2024-11-22 08:46:53.263763: +2024-11-22 08:46:53.263947: Epoch 3968 +2024-11-22 08:46:53.264092: Current learning rate: 0.0054 +2024-11-22 08:47:10.907561: train_loss -0.7938 +2024-11-22 08:47:10.907804: val_loss -0.7784 +2024-11-22 08:47:10.907897: Pseudo dice [0.8559] +2024-11-22 08:47:10.907976: Epoch time: 17.64 s +2024-11-22 08:47:11.838822: +2024-11-22 08:47:11.839045: Epoch 3969 +2024-11-22 08:47:11.839164: Current learning rate: 0.0054 +2024-11-22 08:47:30.817455: train_loss -0.7839 +2024-11-22 08:47:30.817672: val_loss -0.7447 +2024-11-22 08:47:30.817748: Pseudo dice [0.8436] +2024-11-22 08:47:30.817822: Epoch time: 18.98 s +2024-11-22 08:47:31.677532: +2024-11-22 08:47:31.677755: Epoch 3970 +2024-11-22 08:47:31.677864: Current learning rate: 0.0054 +2024-11-22 08:47:50.448009: train_loss -0.7822 +2024-11-22 08:47:50.449277: val_loss -0.7497 +2024-11-22 08:47:50.449399: Pseudo dice [0.8618] +2024-11-22 08:47:50.449488: Epoch time: 18.77 s +2024-11-22 08:47:51.331862: +2024-11-22 08:47:51.332103: Epoch 3971 +2024-11-22 08:47:51.332216: Current learning rate: 0.00539 +2024-11-22 08:48:10.738569: train_loss -0.7899 +2024-11-22 08:48:10.738784: val_loss -0.7721 +2024-11-22 08:48:10.738857: Pseudo dice [0.8458] +2024-11-22 08:48:10.738932: Epoch time: 19.41 s +2024-11-22 08:48:11.657230: +2024-11-22 08:48:11.657427: Epoch 3972 +2024-11-22 08:48:11.657536: Current learning rate: 0.00539 +2024-11-22 08:48:30.501549: train_loss -0.785 +2024-11-22 08:48:30.501796: val_loss -0.7819 +2024-11-22 08:48:30.502173: Pseudo dice [0.8485] +2024-11-22 08:48:30.502262: Epoch time: 18.85 s +2024-11-22 08:48:31.361731: +2024-11-22 08:48:31.361942: Epoch 3973 +2024-11-22 08:48:31.362053: Current learning rate: 0.00539 +2024-11-22 08:48:49.163505: train_loss -0.781 +2024-11-22 08:48:49.165911: val_loss -0.7779 +2024-11-22 08:48:49.166034: Pseudo dice [0.8481] +2024-11-22 08:48:49.166123: Epoch time: 17.8 s +2024-11-22 08:48:50.037415: +2024-11-22 08:48:50.037651: Epoch 3974 +2024-11-22 08:48:50.037764: Current learning rate: 0.00539 +2024-11-22 08:49:08.477581: train_loss -0.782 +2024-11-22 08:49:08.477805: val_loss -0.7682 +2024-11-22 08:49:08.477882: Pseudo dice [0.8534] +2024-11-22 08:49:08.477959: Epoch time: 18.44 s +2024-11-22 08:49:09.515648: +2024-11-22 08:49:09.515837: Epoch 3975 +2024-11-22 08:49:09.515944: Current learning rate: 0.00539 +2024-11-22 08:49:26.976398: train_loss -0.7814 +2024-11-22 08:49:26.976598: val_loss -0.7617 +2024-11-22 08:49:26.976675: Pseudo dice [0.8467] +2024-11-22 08:49:26.976752: Epoch time: 17.46 s +2024-11-22 08:49:28.215773: +2024-11-22 08:49:28.215963: Epoch 3976 +2024-11-22 08:49:28.216080: Current learning rate: 0.00539 +2024-11-22 08:49:45.801401: train_loss -0.7849 +2024-11-22 08:49:45.801653: val_loss -0.7697 +2024-11-22 08:49:45.801733: Pseudo dice [0.8497] +2024-11-22 08:49:45.801815: Epoch time: 17.59 s +2024-11-22 08:49:46.655556: +2024-11-22 08:49:46.655794: Epoch 3977 +2024-11-22 08:49:46.655905: Current learning rate: 0.00539 +2024-11-22 08:50:05.341807: train_loss -0.7856 +2024-11-22 08:50:05.342013: val_loss -0.7718 +2024-11-22 08:50:05.342101: Pseudo dice [0.8529] +2024-11-22 08:50:05.342178: Epoch time: 18.69 s +2024-11-22 08:50:06.211576: +2024-11-22 08:50:06.211798: Epoch 3978 +2024-11-22 08:50:06.211907: Current learning rate: 0.00539 +2024-11-22 08:50:24.655759: train_loss -0.7799 +2024-11-22 08:50:24.655976: val_loss -0.773 +2024-11-22 08:50:24.656050: Pseudo dice [0.8524] +2024-11-22 08:50:24.656130: Epoch time: 18.44 s +2024-11-22 08:50:25.510990: +2024-11-22 08:50:25.511215: Epoch 3979 +2024-11-22 08:50:25.511328: Current learning rate: 0.00538 +2024-11-22 08:50:45.140711: train_loss -0.7747 +2024-11-22 08:50:45.140965: val_loss -0.7485 +2024-11-22 08:50:45.141046: Pseudo dice [0.8319] +2024-11-22 08:50:45.141127: Epoch time: 19.63 s +2024-11-22 08:50:45.996681: +2024-11-22 08:50:45.996911: Epoch 3980 +2024-11-22 08:50:45.997023: Current learning rate: 0.00538 +2024-11-22 08:51:05.276328: train_loss -0.7803 +2024-11-22 08:51:05.276572: val_loss -0.7714 +2024-11-22 08:51:05.276654: Pseudo dice [0.8446] +2024-11-22 08:51:05.276737: Epoch time: 19.28 s +2024-11-22 08:51:06.134128: +2024-11-22 08:51:06.134343: Epoch 3981 +2024-11-22 08:51:06.134453: Current learning rate: 0.00538 +2024-11-22 08:51:23.837182: train_loss -0.7895 +2024-11-22 08:51:23.837384: val_loss -0.7644 +2024-11-22 08:51:23.837465: Pseudo dice [0.8518] +2024-11-22 08:51:23.837542: Epoch time: 17.7 s +2024-11-22 08:51:24.702426: +2024-11-22 08:51:24.702662: Epoch 3982 +2024-11-22 08:51:24.702777: Current learning rate: 0.00538 +2024-11-22 08:51:42.927176: train_loss -0.7816 +2024-11-22 08:51:42.927400: val_loss -0.7662 +2024-11-22 08:51:42.927476: Pseudo dice [0.857] +2024-11-22 08:51:42.927551: Epoch time: 18.23 s +2024-11-22 08:51:43.835399: +2024-11-22 08:51:43.835587: Epoch 3983 +2024-11-22 08:51:43.835911: Current learning rate: 0.00538 +2024-11-22 08:52:02.160454: train_loss -0.7839 +2024-11-22 08:52:02.160688: val_loss -0.7804 +2024-11-22 08:52:02.160767: Pseudo dice [0.8662] +2024-11-22 08:52:02.160845: Epoch time: 18.33 s +2024-11-22 08:52:03.127770: +2024-11-22 08:52:03.127982: Epoch 3984 +2024-11-22 08:52:03.128099: Current learning rate: 0.00538 +2024-11-22 08:52:19.885506: train_loss -0.7903 +2024-11-22 08:52:19.885797: val_loss -0.7728 +2024-11-22 08:52:19.885876: Pseudo dice [0.8749] +2024-11-22 08:52:19.885960: Epoch time: 16.76 s +2024-11-22 08:52:20.773479: +2024-11-22 08:52:20.773668: Epoch 3985 +2024-11-22 08:52:20.773774: Current learning rate: 0.00538 +2024-11-22 08:52:39.000868: train_loss -0.7864 +2024-11-22 08:52:39.001090: val_loss -0.7464 +2024-11-22 08:52:39.001166: Pseudo dice [0.841] +2024-11-22 08:52:39.001243: Epoch time: 18.23 s +2024-11-22 08:52:40.040909: +2024-11-22 08:52:40.041115: Epoch 3986 +2024-11-22 08:52:40.041230: Current learning rate: 0.00538 +2024-11-22 08:52:59.049255: train_loss -0.7651 +2024-11-22 08:52:59.049475: val_loss -0.7514 +2024-11-22 08:52:59.049547: Pseudo dice [0.8462] +2024-11-22 08:52:59.049620: Epoch time: 19.01 s +2024-11-22 08:52:59.896111: +2024-11-22 08:52:59.896302: Epoch 3987 +2024-11-22 08:52:59.896409: Current learning rate: 0.00537 +2024-11-22 08:53:18.962999: train_loss -0.7742 +2024-11-22 08:53:18.968351: val_loss -0.7771 +2024-11-22 08:53:18.968519: Pseudo dice [0.8511] +2024-11-22 08:53:18.968613: Epoch time: 19.07 s +2024-11-22 08:53:20.570785: +2024-11-22 08:53:20.571029: Epoch 3988 +2024-11-22 08:53:20.571147: Current learning rate: 0.00537 +2024-11-22 08:53:38.852270: train_loss -0.7705 +2024-11-22 08:53:38.852507: val_loss -0.7736 +2024-11-22 08:53:38.852583: Pseudo dice [0.8615] +2024-11-22 08:53:38.852660: Epoch time: 18.28 s +2024-11-22 08:53:39.834796: +2024-11-22 08:53:39.835006: Epoch 3989 +2024-11-22 08:53:39.835122: Current learning rate: 0.00537 +2024-11-22 08:53:57.246310: train_loss -0.7862 +2024-11-22 08:53:57.246583: val_loss -0.7589 +2024-11-22 08:53:57.246663: Pseudo dice [0.8331] +2024-11-22 08:53:57.246740: Epoch time: 17.41 s +2024-11-22 08:53:58.078564: +2024-11-22 08:53:58.078780: Epoch 3990 +2024-11-22 08:53:58.078889: Current learning rate: 0.00537 +2024-11-22 08:54:17.527977: train_loss -0.785 +2024-11-22 08:54:17.528199: val_loss -0.7475 +2024-11-22 08:54:17.528275: Pseudo dice [0.8465] +2024-11-22 08:54:17.528350: Epoch time: 19.45 s +2024-11-22 08:54:18.390402: +2024-11-22 08:54:18.390615: Epoch 3991 +2024-11-22 08:54:18.390726: Current learning rate: 0.00537 +2024-11-22 08:54:37.437556: train_loss -0.7815 +2024-11-22 08:54:37.437796: val_loss -0.7642 +2024-11-22 08:54:37.437873: Pseudo dice [0.8477] +2024-11-22 08:54:37.437957: Epoch time: 19.05 s +2024-11-22 08:54:38.316503: +2024-11-22 08:54:38.316715: Epoch 3992 +2024-11-22 08:54:38.316827: Current learning rate: 0.00537 +2024-11-22 08:54:56.680928: train_loss -0.7826 +2024-11-22 08:54:56.681182: val_loss -0.7656 +2024-11-22 08:54:56.681258: Pseudo dice [0.8654] +2024-11-22 08:54:56.681333: Epoch time: 18.37 s +2024-11-22 08:54:57.535401: +2024-11-22 08:54:57.535611: Epoch 3993 +2024-11-22 08:54:57.535726: Current learning rate: 0.00537 +2024-11-22 08:55:15.687222: train_loss -0.7904 +2024-11-22 08:55:15.687433: val_loss -0.7667 +2024-11-22 08:55:15.687507: Pseudo dice [0.8577] +2024-11-22 08:55:15.687579: Epoch time: 18.15 s +2024-11-22 08:55:16.634495: +2024-11-22 08:55:16.634691: Epoch 3994 +2024-11-22 08:55:16.634801: Current learning rate: 0.00537 +2024-11-22 08:55:35.679040: train_loss -0.7893 +2024-11-22 08:55:35.679253: val_loss -0.7742 +2024-11-22 08:55:35.679327: Pseudo dice [0.8652] +2024-11-22 08:55:35.679435: Epoch time: 19.05 s +2024-11-22 08:55:36.528269: +2024-11-22 08:55:36.528458: Epoch 3995 +2024-11-22 08:55:36.528565: Current learning rate: 0.00536 +2024-11-22 08:55:54.798764: train_loss -0.7753 +2024-11-22 08:55:54.799006: val_loss -0.7812 +2024-11-22 08:55:54.799142: Pseudo dice [0.8464] +2024-11-22 08:55:54.803393: Epoch time: 18.27 s +2024-11-22 08:55:55.665112: +2024-11-22 08:55:55.665312: Epoch 3996 +2024-11-22 08:55:55.665426: Current learning rate: 0.00536 +2024-11-22 08:56:13.919451: train_loss -0.7736 +2024-11-22 08:56:13.919667: val_loss -0.7494 +2024-11-22 08:56:13.919740: Pseudo dice [0.8466] +2024-11-22 08:56:13.919816: Epoch time: 18.26 s +2024-11-22 08:56:14.778742: +2024-11-22 08:56:14.778923: Epoch 3997 +2024-11-22 08:56:14.779119: Current learning rate: 0.00536 +2024-11-22 08:56:33.004888: train_loss -0.7658 +2024-11-22 08:56:33.005102: val_loss -0.7747 +2024-11-22 08:56:33.005173: Pseudo dice [0.8493] +2024-11-22 08:56:33.005249: Epoch time: 18.23 s +2024-11-22 08:56:34.019678: +2024-11-22 08:56:34.019890: Epoch 3998 +2024-11-22 08:56:34.020002: Current learning rate: 0.00536 +2024-11-22 08:56:52.228412: train_loss -0.7734 +2024-11-22 08:56:52.229023: val_loss -0.7588 +2024-11-22 08:56:52.229118: Pseudo dice [0.8453] +2024-11-22 08:56:52.229225: Epoch time: 18.21 s +2024-11-22 08:56:53.474887: +2024-11-22 08:56:53.475101: Epoch 3999 +2024-11-22 08:56:53.475217: Current learning rate: 0.00536 +2024-11-22 08:57:12.522004: train_loss -0.7818 +2024-11-22 08:57:12.522260: val_loss -0.7678 +2024-11-22 08:57:12.522338: Pseudo dice [0.8529] +2024-11-22 08:57:12.522416: Epoch time: 19.05 s +2024-11-22 08:57:13.623454: +2024-11-22 08:57:13.623679: Epoch 4000 +2024-11-22 08:57:13.623788: Current learning rate: 0.00536 +2024-11-22 08:57:32.222846: train_loss -0.7742 +2024-11-22 08:57:32.223056: val_loss -0.7682 +2024-11-22 08:57:32.223139: Pseudo dice [0.8419] +2024-11-22 08:57:32.223216: Epoch time: 18.6 s +2024-11-22 08:57:33.077595: +2024-11-22 08:57:33.077849: Epoch 4001 +2024-11-22 08:57:33.077964: Current learning rate: 0.00536 +2024-11-22 08:57:53.224149: train_loss -0.7833 +2024-11-22 08:57:53.224360: val_loss -0.7343 +2024-11-22 08:57:53.224439: Pseudo dice [0.8364] +2024-11-22 08:57:53.224514: Epoch time: 20.15 s +2024-11-22 08:57:54.103904: +2024-11-22 08:57:54.104120: Epoch 4002 +2024-11-22 08:57:54.104237: Current learning rate: 0.00536 +2024-11-22 08:58:13.678687: train_loss -0.7673 +2024-11-22 08:58:13.678907: val_loss -0.7682 +2024-11-22 08:58:13.678985: Pseudo dice [0.8484] +2024-11-22 08:58:13.679073: Epoch time: 19.58 s +2024-11-22 08:58:14.535084: +2024-11-22 08:58:14.535305: Epoch 4003 +2024-11-22 08:58:14.535414: Current learning rate: 0.00536 +2024-11-22 08:58:33.772957: train_loss -0.7891 +2024-11-22 08:58:33.773198: val_loss -0.7725 +2024-11-22 08:58:33.773274: Pseudo dice [0.8513] +2024-11-22 08:58:33.773351: Epoch time: 19.24 s +2024-11-22 08:58:34.630536: +2024-11-22 08:58:34.630742: Epoch 4004 +2024-11-22 08:58:34.630851: Current learning rate: 0.00535 +2024-11-22 08:58:52.336936: train_loss -0.7797 +2024-11-22 08:58:52.337154: val_loss -0.7652 +2024-11-22 08:58:52.337227: Pseudo dice [0.8409] +2024-11-22 08:58:52.337298: Epoch time: 17.71 s +2024-11-22 08:58:53.186052: +2024-11-22 08:58:53.186259: Epoch 4005 +2024-11-22 08:58:53.186368: Current learning rate: 0.00535 +2024-11-22 08:59:10.391122: train_loss -0.7834 +2024-11-22 08:59:10.391328: val_loss -0.7727 +2024-11-22 08:59:10.391403: Pseudo dice [0.8516] +2024-11-22 08:59:10.391497: Epoch time: 17.21 s +2024-11-22 08:59:11.242490: +2024-11-22 08:59:11.242674: Epoch 4006 +2024-11-22 08:59:11.242783: Current learning rate: 0.00535 +2024-11-22 08:59:29.178733: train_loss -0.7893 +2024-11-22 08:59:29.178975: val_loss -0.7855 +2024-11-22 08:59:29.179053: Pseudo dice [0.8477] +2024-11-22 08:59:29.179139: Epoch time: 17.94 s +2024-11-22 08:59:30.036689: +2024-11-22 08:59:30.036892: Epoch 4007 +2024-11-22 08:59:30.037006: Current learning rate: 0.00535 +2024-11-22 08:59:48.995174: train_loss -0.772 +2024-11-22 08:59:48.995386: val_loss -0.7513 +2024-11-22 08:59:49.000599: Pseudo dice [0.8406] +2024-11-22 08:59:49.000767: Epoch time: 18.96 s +2024-11-22 08:59:49.991647: +2024-11-22 08:59:49.991876: Epoch 4008 +2024-11-22 08:59:49.991985: Current learning rate: 0.00535 +2024-11-22 09:00:08.787263: train_loss -0.7749 +2024-11-22 09:00:08.788106: val_loss -0.7508 +2024-11-22 09:00:08.788186: Pseudo dice [0.8633] +2024-11-22 09:00:08.788261: Epoch time: 18.8 s +2024-11-22 09:00:09.637764: +2024-11-22 09:00:09.637941: Epoch 4009 +2024-11-22 09:00:09.638050: Current learning rate: 0.00535 +2024-11-22 09:00:28.075396: train_loss -0.7852 +2024-11-22 09:00:28.075641: val_loss -0.7467 +2024-11-22 09:00:28.075749: Pseudo dice [0.8406] +2024-11-22 09:00:28.075854: Epoch time: 18.44 s +2024-11-22 09:00:29.418109: +2024-11-22 09:00:29.418312: Epoch 4010 +2024-11-22 09:00:29.418424: Current learning rate: 0.00535 +2024-11-22 09:00:48.214875: train_loss -0.7765 +2024-11-22 09:00:48.215137: val_loss -0.7497 +2024-11-22 09:00:48.215216: Pseudo dice [0.8528] +2024-11-22 09:00:48.215299: Epoch time: 18.8 s +2024-11-22 09:00:49.064064: +2024-11-22 09:00:49.064341: Epoch 4011 +2024-11-22 09:00:49.064452: Current learning rate: 0.00535 +2024-11-22 09:01:08.108909: train_loss -0.7821 +2024-11-22 09:01:08.109163: val_loss -0.7653 +2024-11-22 09:01:08.109246: Pseudo dice [0.8479] +2024-11-22 09:01:08.109324: Epoch time: 19.05 s +2024-11-22 09:01:08.975950: +2024-11-22 09:01:08.976167: Epoch 4012 +2024-11-22 09:01:08.976276: Current learning rate: 0.00534 +2024-11-22 09:01:27.013431: train_loss -0.7744 +2024-11-22 09:01:27.013634: val_loss -0.767 +2024-11-22 09:01:27.013711: Pseudo dice [0.8538] +2024-11-22 09:01:27.013785: Epoch time: 18.04 s +2024-11-22 09:01:27.903974: +2024-11-22 09:01:27.904201: Epoch 4013 +2024-11-22 09:01:27.904310: Current learning rate: 0.00534 +2024-11-22 09:01:46.434017: train_loss -0.7815 +2024-11-22 09:01:46.434378: val_loss -0.755 +2024-11-22 09:01:46.434468: Pseudo dice [0.8532] +2024-11-22 09:01:46.434554: Epoch time: 18.53 s +2024-11-22 09:01:47.311589: +2024-11-22 09:01:47.311809: Epoch 4014 +2024-11-22 09:01:47.311922: Current learning rate: 0.00534 +2024-11-22 09:02:05.089895: train_loss -0.7933 +2024-11-22 09:02:05.090136: val_loss -0.7751 +2024-11-22 09:02:05.090211: Pseudo dice [0.8414] +2024-11-22 09:02:05.090290: Epoch time: 17.78 s +2024-11-22 09:02:05.948137: +2024-11-22 09:02:05.948336: Epoch 4015 +2024-11-22 09:02:05.948443: Current learning rate: 0.00534 +2024-11-22 09:02:25.911431: train_loss -0.7904 +2024-11-22 09:02:25.911640: val_loss -0.7643 +2024-11-22 09:02:25.911714: Pseudo dice [0.8493] +2024-11-22 09:02:25.911788: Epoch time: 19.96 s +2024-11-22 09:02:26.764109: +2024-11-22 09:02:26.764329: Epoch 4016 +2024-11-22 09:02:26.764442: Current learning rate: 0.00534 +2024-11-22 09:02:45.215493: train_loss -0.7846 +2024-11-22 09:02:45.215770: val_loss -0.7553 +2024-11-22 09:02:45.215846: Pseudo dice [0.8568] +2024-11-22 09:02:45.215919: Epoch time: 18.45 s +2024-11-22 09:02:46.124026: +2024-11-22 09:02:46.124248: Epoch 4017 +2024-11-22 09:02:46.124364: Current learning rate: 0.00534 +2024-11-22 09:03:04.611452: train_loss -0.7832 +2024-11-22 09:03:04.611664: val_loss -0.7612 +2024-11-22 09:03:04.611740: Pseudo dice [0.8411] +2024-11-22 09:03:04.611814: Epoch time: 18.49 s +2024-11-22 09:03:05.476733: +2024-11-22 09:03:05.476975: Epoch 4018 +2024-11-22 09:03:05.477092: Current learning rate: 0.00534 +2024-11-22 09:03:25.681171: train_loss -0.7838 +2024-11-22 09:03:25.681477: val_loss -0.769 +2024-11-22 09:03:25.681553: Pseudo dice [0.8416] +2024-11-22 09:03:25.681632: Epoch time: 20.21 s +2024-11-22 09:03:26.531918: +2024-11-22 09:03:26.532114: Epoch 4019 +2024-11-22 09:03:26.532229: Current learning rate: 0.00534 +2024-11-22 09:03:45.650533: train_loss -0.7904 +2024-11-22 09:03:45.656975: val_loss -0.7852 +2024-11-22 09:03:45.657078: Pseudo dice [0.844] +2024-11-22 09:03:45.657159: Epoch time: 19.12 s +2024-11-22 09:03:46.527736: +2024-11-22 09:03:46.527916: Epoch 4020 +2024-11-22 09:03:46.528029: Current learning rate: 0.00533 +2024-11-22 09:04:04.309063: train_loss -0.7839 +2024-11-22 09:04:04.309265: val_loss -0.7855 +2024-11-22 09:04:04.309340: Pseudo dice [0.8679] +2024-11-22 09:04:04.309431: Epoch time: 17.78 s +2024-11-22 09:04:05.171847: +2024-11-22 09:04:05.172054: Epoch 4021 +2024-11-22 09:04:05.191837: Current learning rate: 0.00533 +2024-11-22 09:04:23.559008: train_loss -0.7895 +2024-11-22 09:04:23.559248: val_loss -0.7431 +2024-11-22 09:04:23.559325: Pseudo dice [0.8569] +2024-11-22 09:04:23.559416: Epoch time: 18.39 s +2024-11-22 09:04:24.946459: +2024-11-22 09:04:24.946676: Epoch 4022 +2024-11-22 09:04:24.946786: Current learning rate: 0.00533 +2024-11-22 09:04:42.758233: train_loss -0.7876 +2024-11-22 09:04:42.758453: val_loss -0.7712 +2024-11-22 09:04:42.758528: Pseudo dice [0.8607] +2024-11-22 09:04:42.758601: Epoch time: 17.81 s +2024-11-22 09:04:43.629972: +2024-11-22 09:04:43.630228: Epoch 4023 +2024-11-22 09:04:43.630342: Current learning rate: 0.00533 +2024-11-22 09:05:02.088454: train_loss -0.7872 +2024-11-22 09:05:02.088675: val_loss -0.7702 +2024-11-22 09:05:02.088753: Pseudo dice [0.8462] +2024-11-22 09:05:02.088840: Epoch time: 18.46 s +2024-11-22 09:05:02.943928: +2024-11-22 09:05:02.944154: Epoch 4024 +2024-11-22 09:05:02.944262: Current learning rate: 0.00533 +2024-11-22 09:05:21.494401: train_loss -0.7662 +2024-11-22 09:05:21.494703: val_loss -0.7523 +2024-11-22 09:05:21.494789: Pseudo dice [0.8469] +2024-11-22 09:05:21.494876: Epoch time: 18.55 s +2024-11-22 09:05:22.347025: +2024-11-22 09:05:22.347239: Epoch 4025 +2024-11-22 09:05:22.347352: Current learning rate: 0.00533 +2024-11-22 09:05:41.468676: train_loss -0.7447 +2024-11-22 09:05:41.468890: val_loss -0.742 +2024-11-22 09:05:41.468964: Pseudo dice [0.8421] +2024-11-22 09:05:41.469044: Epoch time: 19.12 s +2024-11-22 09:05:42.326202: +2024-11-22 09:05:42.326433: Epoch 4026 +2024-11-22 09:05:42.326547: Current learning rate: 0.00533 +2024-11-22 09:05:59.641162: train_loss -0.761 +2024-11-22 09:05:59.641398: val_loss -0.775 +2024-11-22 09:05:59.641481: Pseudo dice [0.8457] +2024-11-22 09:05:59.641562: Epoch time: 17.32 s +2024-11-22 09:06:00.493443: +2024-11-22 09:06:00.493649: Epoch 4027 +2024-11-22 09:06:00.493760: Current learning rate: 0.00533 +2024-11-22 09:06:17.686210: train_loss -0.7528 +2024-11-22 09:06:17.686419: val_loss -0.7626 +2024-11-22 09:06:17.686549: Pseudo dice [0.8531] +2024-11-22 09:06:17.686627: Epoch time: 17.19 s +2024-11-22 09:06:18.545800: +2024-11-22 09:06:18.546020: Epoch 4028 +2024-11-22 09:06:18.546138: Current learning rate: 0.00533 +2024-11-22 09:06:36.756518: train_loss -0.7646 +2024-11-22 09:06:36.756734: val_loss -0.7596 +2024-11-22 09:06:36.756812: Pseudo dice [0.8549] +2024-11-22 09:06:36.756889: Epoch time: 18.21 s +2024-11-22 09:06:37.623150: +2024-11-22 09:06:37.623353: Epoch 4029 +2024-11-22 09:06:37.623464: Current learning rate: 0.00532 +2024-11-22 09:06:56.222965: train_loss -0.7726 +2024-11-22 09:06:56.223233: val_loss -0.7626 +2024-11-22 09:06:56.223311: Pseudo dice [0.8402] +2024-11-22 09:06:56.223392: Epoch time: 18.6 s +2024-11-22 09:06:57.083188: +2024-11-22 09:06:57.083397: Epoch 4030 +2024-11-22 09:06:57.083509: Current learning rate: 0.00532 +2024-11-22 09:07:15.208141: train_loss -0.7728 +2024-11-22 09:07:15.208342: val_loss -0.7717 +2024-11-22 09:07:15.208415: Pseudo dice [0.857] +2024-11-22 09:07:15.208488: Epoch time: 18.13 s +2024-11-22 09:07:16.066572: +2024-11-22 09:07:16.066787: Epoch 4031 +2024-11-22 09:07:16.066908: Current learning rate: 0.00532 +2024-11-22 09:07:34.224365: train_loss -0.7689 +2024-11-22 09:07:34.224567: val_loss -0.7764 +2024-11-22 09:07:34.224639: Pseudo dice [0.8441] +2024-11-22 09:07:34.224714: Epoch time: 18.16 s +2024-11-22 09:07:35.079755: +2024-11-22 09:07:35.079968: Epoch 4032 +2024-11-22 09:07:35.080086: Current learning rate: 0.00532 +2024-11-22 09:07:54.519768: train_loss -0.778 +2024-11-22 09:07:54.519978: val_loss -0.7722 +2024-11-22 09:07:54.520049: Pseudo dice [0.8541] +2024-11-22 09:07:54.520129: Epoch time: 19.44 s +2024-11-22 09:07:55.770871: +2024-11-22 09:07:55.771096: Epoch 4033 +2024-11-22 09:07:55.771203: Current learning rate: 0.00532 +2024-11-22 09:08:13.202456: train_loss -0.7741 +2024-11-22 09:08:13.202721: val_loss -0.7679 +2024-11-22 09:08:13.202804: Pseudo dice [0.839] +2024-11-22 09:08:13.202884: Epoch time: 17.43 s +2024-11-22 09:08:14.095748: +2024-11-22 09:08:14.096056: Epoch 4034 +2024-11-22 09:08:14.096172: Current learning rate: 0.00532 +2024-11-22 09:08:32.613859: train_loss -0.7866 +2024-11-22 09:08:32.614135: val_loss -0.7714 +2024-11-22 09:08:32.614214: Pseudo dice [0.85] +2024-11-22 09:08:32.614289: Epoch time: 18.52 s +2024-11-22 09:08:33.465593: +2024-11-22 09:08:33.465797: Epoch 4035 +2024-11-22 09:08:33.465907: Current learning rate: 0.00532 +2024-11-22 09:08:51.397923: train_loss -0.7803 +2024-11-22 09:08:51.403322: val_loss -0.7559 +2024-11-22 09:08:51.403446: Pseudo dice [0.8522] +2024-11-22 09:08:51.403526: Epoch time: 17.93 s +2024-11-22 09:08:52.259646: +2024-11-22 09:08:52.259856: Epoch 4036 +2024-11-22 09:08:52.259972: Current learning rate: 0.00532 +2024-11-22 09:09:10.627784: train_loss -0.7843 +2024-11-22 09:09:10.627991: val_loss -0.7511 +2024-11-22 09:09:10.628071: Pseudo dice [0.8378] +2024-11-22 09:09:10.628155: Epoch time: 18.37 s +2024-11-22 09:09:11.474738: +2024-11-22 09:09:11.474955: Epoch 4037 +2024-11-22 09:09:11.475078: Current learning rate: 0.00531 +2024-11-22 09:09:29.340898: train_loss -0.7787 +2024-11-22 09:09:29.341133: val_loss -0.7665 +2024-11-22 09:09:29.341209: Pseudo dice [0.8445] +2024-11-22 09:09:29.341285: Epoch time: 17.87 s +2024-11-22 09:09:30.194661: +2024-11-22 09:09:30.194863: Epoch 4038 +2024-11-22 09:09:30.194970: Current learning rate: 0.00531 +2024-11-22 09:09:48.261318: train_loss -0.784 +2024-11-22 09:09:48.261521: val_loss -0.7696 +2024-11-22 09:09:48.261598: Pseudo dice [0.8421] +2024-11-22 09:09:48.261673: Epoch time: 18.07 s +2024-11-22 09:09:49.121777: +2024-11-22 09:09:49.121989: Epoch 4039 +2024-11-22 09:09:49.122103: Current learning rate: 0.00531 +2024-11-22 09:10:07.673965: train_loss -0.7891 +2024-11-22 09:10:07.674175: val_loss -0.7477 +2024-11-22 09:10:07.674252: Pseudo dice [0.8427] +2024-11-22 09:10:07.674326: Epoch time: 18.55 s +2024-11-22 09:10:08.530141: +2024-11-22 09:10:08.530352: Epoch 4040 +2024-11-22 09:10:08.530463: Current learning rate: 0.00531 +2024-11-22 09:10:26.633063: train_loss -0.7735 +2024-11-22 09:10:26.633342: val_loss -0.7488 +2024-11-22 09:10:26.633423: Pseudo dice [0.8406] +2024-11-22 09:10:26.633513: Epoch time: 18.1 s +2024-11-22 09:10:27.536905: +2024-11-22 09:10:27.537104: Epoch 4041 +2024-11-22 09:10:27.537207: Current learning rate: 0.00531 +2024-11-22 09:10:45.831338: train_loss -0.7842 +2024-11-22 09:10:45.831609: val_loss -0.7487 +2024-11-22 09:10:45.831688: Pseudo dice [0.8628] +2024-11-22 09:10:45.831767: Epoch time: 18.3 s +2024-11-22 09:10:46.695913: +2024-11-22 09:10:46.696106: Epoch 4042 +2024-11-22 09:10:46.696217: Current learning rate: 0.00531 +2024-11-22 09:11:04.598454: train_loss -0.7902 +2024-11-22 09:11:04.603858: val_loss -0.7813 +2024-11-22 09:11:04.604039: Pseudo dice [0.8502] +2024-11-22 09:11:04.604132: Epoch time: 17.9 s +2024-11-22 09:11:05.588534: +2024-11-22 09:11:05.588740: Epoch 4043 +2024-11-22 09:11:05.588847: Current learning rate: 0.00531 +2024-11-22 09:11:25.094831: train_loss -0.7786 +2024-11-22 09:11:25.095041: val_loss -0.753 +2024-11-22 09:11:25.095120: Pseudo dice [0.8417] +2024-11-22 09:11:25.095195: Epoch time: 19.51 s +2024-11-22 09:11:25.946784: +2024-11-22 09:11:25.947021: Epoch 4044 +2024-11-22 09:11:25.947136: Current learning rate: 0.00531 +2024-11-22 09:11:44.671340: train_loss -0.7805 +2024-11-22 09:11:44.671577: val_loss -0.7742 +2024-11-22 09:11:44.671649: Pseudo dice [0.8455] +2024-11-22 09:11:44.671732: Epoch time: 18.73 s +2024-11-22 09:11:45.955983: +2024-11-22 09:11:45.956186: Epoch 4045 +2024-11-22 09:11:45.956288: Current learning rate: 0.0053 +2024-11-22 09:12:03.839515: train_loss -0.7828 +2024-11-22 09:12:03.839733: val_loss -0.7803 +2024-11-22 09:12:03.839814: Pseudo dice [0.8585] +2024-11-22 09:12:03.839889: Epoch time: 17.88 s +2024-11-22 09:12:04.690673: +2024-11-22 09:12:04.690923: Epoch 4046 +2024-11-22 09:12:04.691031: Current learning rate: 0.0053 +2024-11-22 09:12:23.174468: train_loss -0.7833 +2024-11-22 09:12:23.174690: val_loss -0.7923 +2024-11-22 09:12:23.174766: Pseudo dice [0.8553] +2024-11-22 09:12:23.175189: Epoch time: 18.48 s +2024-11-22 09:12:24.033822: +2024-11-22 09:12:24.034064: Epoch 4047 +2024-11-22 09:12:24.034177: Current learning rate: 0.0053 +2024-11-22 09:12:41.839757: train_loss -0.7891 +2024-11-22 09:12:41.839970: val_loss -0.7533 +2024-11-22 09:12:41.840121: Pseudo dice [0.8586] +2024-11-22 09:12:41.840198: Epoch time: 17.81 s +2024-11-22 09:12:42.689967: +2024-11-22 09:12:42.690174: Epoch 4048 +2024-11-22 09:12:42.690286: Current learning rate: 0.0053 +2024-11-22 09:13:01.036009: train_loss -0.7775 +2024-11-22 09:13:01.036251: val_loss -0.7876 +2024-11-22 09:13:01.036325: Pseudo dice [0.8614] +2024-11-22 09:13:01.036404: Epoch time: 18.35 s +2024-11-22 09:13:01.894475: +2024-11-22 09:13:01.894702: Epoch 4049 +2024-11-22 09:13:01.894810: Current learning rate: 0.0053 +2024-11-22 09:13:20.609624: train_loss -0.7866 +2024-11-22 09:13:20.609831: val_loss -0.7699 +2024-11-22 09:13:20.609905: Pseudo dice [0.8507] +2024-11-22 09:13:20.609983: Epoch time: 18.72 s +2024-11-22 09:13:21.747220: +2024-11-22 09:13:21.747422: Epoch 4050 +2024-11-22 09:13:21.747536: Current learning rate: 0.0053 +2024-11-22 09:13:40.654948: train_loss -0.7789 +2024-11-22 09:13:40.655165: val_loss -0.7332 +2024-11-22 09:13:40.655243: Pseudo dice [0.8504] +2024-11-22 09:13:40.655370: Epoch time: 18.91 s +2024-11-22 09:13:41.513400: +2024-11-22 09:13:41.513612: Epoch 4051 +2024-11-22 09:13:41.513726: Current learning rate: 0.0053 +2024-11-22 09:14:00.029703: train_loss -0.7909 +2024-11-22 09:14:00.029922: val_loss -0.7844 +2024-11-22 09:14:00.029998: Pseudo dice [0.8486] +2024-11-22 09:14:00.030081: Epoch time: 18.52 s +2024-11-22 09:14:00.894733: +2024-11-22 09:14:00.894951: Epoch 4052 +2024-11-22 09:14:00.895070: Current learning rate: 0.0053 +2024-11-22 09:14:18.409118: train_loss -0.7846 +2024-11-22 09:14:18.409370: val_loss -0.7497 +2024-11-22 09:14:18.409449: Pseudo dice [0.8278] +2024-11-22 09:14:18.409530: Epoch time: 17.52 s +2024-11-22 09:14:19.267648: +2024-11-22 09:14:19.267852: Epoch 4053 +2024-11-22 09:14:19.267962: Current learning rate: 0.00529 +2024-11-22 09:14:37.794578: train_loss -0.7847 +2024-11-22 09:14:37.794793: val_loss -0.7846 +2024-11-22 09:14:37.794868: Pseudo dice [0.8571] +2024-11-22 09:14:37.794940: Epoch time: 18.53 s +2024-11-22 09:14:38.653341: +2024-11-22 09:14:38.653550: Epoch 4054 +2024-11-22 09:14:38.653662: Current learning rate: 0.00529 +2024-11-22 09:14:57.401399: train_loss -0.7846 +2024-11-22 09:14:57.401614: val_loss -0.7883 +2024-11-22 09:14:57.401692: Pseudo dice [0.8462] +2024-11-22 09:14:57.401768: Epoch time: 18.75 s +2024-11-22 09:14:58.274219: +2024-11-22 09:14:58.274414: Epoch 4055 +2024-11-22 09:14:58.274525: Current learning rate: 0.00529 +2024-11-22 09:15:17.426312: train_loss -0.7861 +2024-11-22 09:15:17.426529: val_loss -0.7619 +2024-11-22 09:15:17.426606: Pseudo dice [0.8655] +2024-11-22 09:15:17.426683: Epoch time: 19.15 s +2024-11-22 09:15:18.843678: +2024-11-22 09:15:18.843900: Epoch 4056 +2024-11-22 09:15:18.844005: Current learning rate: 0.00529 +2024-11-22 09:15:37.514466: train_loss -0.7721 +2024-11-22 09:15:37.515034: val_loss -0.7683 +2024-11-22 09:15:37.515145: Pseudo dice [0.8417] +2024-11-22 09:15:37.515234: Epoch time: 18.67 s +2024-11-22 09:15:38.367008: +2024-11-22 09:15:38.367212: Epoch 4057 +2024-11-22 09:15:38.367318: Current learning rate: 0.00529 +2024-11-22 09:15:56.572293: train_loss -0.7734 +2024-11-22 09:15:56.572500: val_loss -0.7529 +2024-11-22 09:15:56.572575: Pseudo dice [0.8432] +2024-11-22 09:15:56.572647: Epoch time: 18.21 s +2024-11-22 09:15:57.435910: +2024-11-22 09:15:57.436140: Epoch 4058 +2024-11-22 09:15:57.436257: Current learning rate: 0.00529 +2024-11-22 09:16:16.274215: train_loss -0.7808 +2024-11-22 09:16:16.274431: val_loss -0.7607 +2024-11-22 09:16:16.274504: Pseudo dice [0.8529] +2024-11-22 09:16:16.274579: Epoch time: 18.84 s +2024-11-22 09:16:17.167846: +2024-11-22 09:16:17.168054: Epoch 4059 +2024-11-22 09:16:17.168169: Current learning rate: 0.00529 +2024-11-22 09:16:35.852959: train_loss -0.7839 +2024-11-22 09:16:35.853181: val_loss -0.7549 +2024-11-22 09:16:35.853259: Pseudo dice [0.85] +2024-11-22 09:16:35.853334: Epoch time: 18.69 s +2024-11-22 09:16:36.710957: +2024-11-22 09:16:36.711185: Epoch 4060 +2024-11-22 09:16:36.711291: Current learning rate: 0.00529 +2024-11-22 09:16:56.453934: train_loss -0.783 +2024-11-22 09:16:56.454174: val_loss -0.7971 +2024-11-22 09:16:56.454251: Pseudo dice [0.8525] +2024-11-22 09:16:56.454336: Epoch time: 19.74 s +2024-11-22 09:16:57.340613: +2024-11-22 09:16:57.340820: Epoch 4061 +2024-11-22 09:16:57.340928: Current learning rate: 0.00529 +2024-11-22 09:17:16.580525: train_loss -0.7846 +2024-11-22 09:17:16.580728: val_loss -0.7528 +2024-11-22 09:17:16.580807: Pseudo dice [0.8351] +2024-11-22 09:17:16.580881: Epoch time: 19.24 s +2024-11-22 09:17:17.439146: +2024-11-22 09:17:17.439358: Epoch 4062 +2024-11-22 09:17:17.439466: Current learning rate: 0.00528 +2024-11-22 09:17:37.006753: train_loss -0.7755 +2024-11-22 09:17:37.006964: val_loss -0.7504 +2024-11-22 09:17:37.007037: Pseudo dice [0.8332] +2024-11-22 09:17:37.007118: Epoch time: 19.57 s +2024-11-22 09:17:37.873088: +2024-11-22 09:17:37.873291: Epoch 4063 +2024-11-22 09:17:37.873403: Current learning rate: 0.00528 +2024-11-22 09:17:55.837042: train_loss -0.7857 +2024-11-22 09:17:55.837259: val_loss -0.7841 +2024-11-22 09:17:55.837337: Pseudo dice [0.8491] +2024-11-22 09:17:55.837420: Epoch time: 17.96 s +2024-11-22 09:17:56.694363: +2024-11-22 09:17:56.694585: Epoch 4064 +2024-11-22 09:17:56.694698: Current learning rate: 0.00528 +2024-11-22 09:18:15.286992: train_loss -0.7758 +2024-11-22 09:18:15.287247: val_loss -0.7268 +2024-11-22 09:18:15.287327: Pseudo dice [0.8268] +2024-11-22 09:18:15.287407: Epoch time: 18.59 s +2024-11-22 09:18:16.143252: +2024-11-22 09:18:16.143487: Epoch 4065 +2024-11-22 09:18:16.143602: Current learning rate: 0.00528 +2024-11-22 09:18:34.588701: train_loss -0.7851 +2024-11-22 09:18:34.588913: val_loss -0.7865 +2024-11-22 09:18:34.588990: Pseudo dice [0.8531] +2024-11-22 09:18:34.589073: Epoch time: 18.45 s +2024-11-22 09:18:35.465662: +2024-11-22 09:18:35.465837: Epoch 4066 +2024-11-22 09:18:35.465944: Current learning rate: 0.00528 +2024-11-22 09:18:53.934856: train_loss -0.7816 +2024-11-22 09:18:53.935070: val_loss -0.7616 +2024-11-22 09:18:53.935144: Pseudo dice [0.8405] +2024-11-22 09:18:53.935218: Epoch time: 18.47 s +2024-11-22 09:18:55.162548: +2024-11-22 09:18:55.162741: Epoch 4067 +2024-11-22 09:18:55.162854: Current learning rate: 0.00528 +2024-11-22 09:19:12.958851: train_loss -0.7705 +2024-11-22 09:19:12.959125: val_loss -0.7696 +2024-11-22 09:19:12.959203: Pseudo dice [0.8485] +2024-11-22 09:19:12.959285: Epoch time: 17.8 s +2024-11-22 09:19:13.813668: +2024-11-22 09:19:13.813895: Epoch 4068 +2024-11-22 09:19:13.814002: Current learning rate: 0.00528 +2024-11-22 09:19:31.268390: train_loss -0.7812 +2024-11-22 09:19:31.268599: val_loss -0.7963 +2024-11-22 09:19:31.268674: Pseudo dice [0.8592] +2024-11-22 09:19:31.270905: Epoch time: 17.46 s +2024-11-22 09:19:32.289859: +2024-11-22 09:19:32.290087: Epoch 4069 +2024-11-22 09:19:32.290199: Current learning rate: 0.00528 +2024-11-22 09:19:51.521111: train_loss -0.7855 +2024-11-22 09:19:51.521316: val_loss -0.757 +2024-11-22 09:19:51.521390: Pseudo dice [0.8508] +2024-11-22 09:19:51.521463: Epoch time: 19.23 s +2024-11-22 09:19:52.393453: +2024-11-22 09:19:52.393669: Epoch 4070 +2024-11-22 09:19:52.393781: Current learning rate: 0.00527 +2024-11-22 09:20:10.243592: train_loss -0.7761 +2024-11-22 09:20:10.243811: val_loss -0.7749 +2024-11-22 09:20:10.243925: Pseudo dice [0.8578] +2024-11-22 09:20:10.244004: Epoch time: 17.85 s +2024-11-22 09:20:11.094397: +2024-11-22 09:20:11.094614: Epoch 4071 +2024-11-22 09:20:11.094724: Current learning rate: 0.00527 +2024-11-22 09:20:30.560731: train_loss -0.7843 +2024-11-22 09:20:30.560958: val_loss -0.7581 +2024-11-22 09:20:30.561034: Pseudo dice [0.8413] +2024-11-22 09:20:30.561117: Epoch time: 19.47 s +2024-11-22 09:20:31.424565: +2024-11-22 09:20:31.424806: Epoch 4072 +2024-11-22 09:20:31.424917: Current learning rate: 0.00527 +2024-11-22 09:20:49.680551: train_loss -0.7747 +2024-11-22 09:20:49.680762: val_loss -0.7501 +2024-11-22 09:20:49.680837: Pseudo dice [0.8397] +2024-11-22 09:20:49.680911: Epoch time: 18.26 s +2024-11-22 09:20:50.641320: +2024-11-22 09:20:50.641548: Epoch 4073 +2024-11-22 09:20:50.641660: Current learning rate: 0.00527 +2024-11-22 09:21:09.305768: train_loss -0.7856 +2024-11-22 09:21:09.306052: val_loss -0.7844 +2024-11-22 09:21:09.306139: Pseudo dice [0.8528] +2024-11-22 09:21:09.306218: Epoch time: 18.67 s +2024-11-22 09:21:10.162222: +2024-11-22 09:21:10.162433: Epoch 4074 +2024-11-22 09:21:10.162547: Current learning rate: 0.00527 +2024-11-22 09:21:29.428206: train_loss -0.7925 +2024-11-22 09:21:29.428410: val_loss -0.7637 +2024-11-22 09:21:29.428483: Pseudo dice [0.832] +2024-11-22 09:21:29.428558: Epoch time: 19.27 s +2024-11-22 09:21:30.279601: +2024-11-22 09:21:30.279850: Epoch 4075 +2024-11-22 09:21:30.279978: Current learning rate: 0.00527 +2024-11-22 09:21:49.171940: train_loss -0.795 +2024-11-22 09:21:49.172181: val_loss -0.7544 +2024-11-22 09:21:49.172264: Pseudo dice [0.8507] +2024-11-22 09:21:49.172344: Epoch time: 18.89 s +2024-11-22 09:21:50.244920: +2024-11-22 09:21:50.245122: Epoch 4076 +2024-11-22 09:21:50.245231: Current learning rate: 0.00527 +2024-11-22 09:22:08.720433: train_loss -0.7868 +2024-11-22 09:22:08.720654: val_loss -0.7791 +2024-11-22 09:22:08.720731: Pseudo dice [0.8528] +2024-11-22 09:22:08.720805: Epoch time: 18.48 s +2024-11-22 09:22:09.573809: +2024-11-22 09:22:09.574026: Epoch 4077 +2024-11-22 09:22:09.574146: Current learning rate: 0.00527 +2024-11-22 09:22:28.102550: train_loss -0.7871 +2024-11-22 09:22:28.102787: val_loss -0.7439 +2024-11-22 09:22:28.102869: Pseudo dice [0.8543] +2024-11-22 09:22:28.102982: Epoch time: 18.53 s +2024-11-22 09:22:28.958344: +2024-11-22 09:22:28.958537: Epoch 4078 +2024-11-22 09:22:28.958648: Current learning rate: 0.00526 +2024-11-22 09:22:48.059936: train_loss -0.7885 +2024-11-22 09:22:48.060148: val_loss -0.769 +2024-11-22 09:22:48.060222: Pseudo dice [0.8488] +2024-11-22 09:22:48.060298: Epoch time: 19.1 s +2024-11-22 09:22:49.310379: +2024-11-22 09:22:49.310592: Epoch 4079 +2024-11-22 09:22:49.310701: Current learning rate: 0.00526 +2024-11-22 09:23:08.074822: train_loss -0.7845 +2024-11-22 09:23:08.075100: val_loss -0.7687 +2024-11-22 09:23:08.075181: Pseudo dice [0.8479] +2024-11-22 09:23:08.075263: Epoch time: 18.77 s +2024-11-22 09:23:08.953949: +2024-11-22 09:23:08.954169: Epoch 4080 +2024-11-22 09:23:08.954283: Current learning rate: 0.00526 +2024-11-22 09:23:27.582872: train_loss -0.7825 +2024-11-22 09:23:27.583109: val_loss -0.7621 +2024-11-22 09:23:27.583194: Pseudo dice [0.8577] +2024-11-22 09:23:27.583271: Epoch time: 18.63 s +2024-11-22 09:23:28.523753: +2024-11-22 09:23:28.523973: Epoch 4081 +2024-11-22 09:23:28.524090: Current learning rate: 0.00526 +2024-11-22 09:23:46.969228: train_loss -0.7877 +2024-11-22 09:23:46.969443: val_loss -0.7878 +2024-11-22 09:23:46.969519: Pseudo dice [0.8579] +2024-11-22 09:23:46.969596: Epoch time: 18.45 s +2024-11-22 09:23:47.826544: +2024-11-22 09:23:47.826755: Epoch 4082 +2024-11-22 09:23:47.826872: Current learning rate: 0.00526 +2024-11-22 09:24:06.720037: train_loss -0.7864 +2024-11-22 09:24:06.720262: val_loss -0.7603 +2024-11-22 09:24:06.720338: Pseudo dice [0.8619] +2024-11-22 09:24:06.720412: Epoch time: 18.89 s +2024-11-22 09:24:07.587847: +2024-11-22 09:24:07.588068: Epoch 4083 +2024-11-22 09:24:07.588181: Current learning rate: 0.00526 +2024-11-22 09:24:25.878112: train_loss -0.7865 +2024-11-22 09:24:25.878351: val_loss -0.7783 +2024-11-22 09:24:25.878429: Pseudo dice [0.8525] +2024-11-22 09:24:25.878514: Epoch time: 18.29 s +2024-11-22 09:24:26.793048: +2024-11-22 09:24:26.793275: Epoch 4084 +2024-11-22 09:24:26.793393: Current learning rate: 0.00526 +2024-11-22 09:24:47.263431: train_loss -0.7792 +2024-11-22 09:24:47.263641: val_loss -0.7812 +2024-11-22 09:24:47.263716: Pseudo dice [0.8571] +2024-11-22 09:24:47.263790: Epoch time: 20.47 s +2024-11-22 09:24:48.119996: +2024-11-22 09:24:48.120208: Epoch 4085 +2024-11-22 09:24:48.120319: Current learning rate: 0.00526 +2024-11-22 09:25:07.835983: train_loss -0.7902 +2024-11-22 09:25:07.836201: val_loss -0.7698 +2024-11-22 09:25:07.836275: Pseudo dice [0.8641] +2024-11-22 09:25:07.836351: Epoch time: 19.72 s +2024-11-22 09:25:08.697001: +2024-11-22 09:25:08.697217: Epoch 4086 +2024-11-22 09:25:08.697331: Current learning rate: 0.00526 +2024-11-22 09:25:27.626106: train_loss -0.782 +2024-11-22 09:25:27.626303: val_loss -0.7726 +2024-11-22 09:25:27.626374: Pseudo dice [0.8567] +2024-11-22 09:25:27.626447: Epoch time: 18.93 s +2024-11-22 09:25:28.487535: +2024-11-22 09:25:28.487761: Epoch 4087 +2024-11-22 09:25:28.487884: Current learning rate: 0.00525 +2024-11-22 09:25:46.141119: train_loss -0.7984 +2024-11-22 09:25:46.141360: val_loss -0.7867 +2024-11-22 09:25:46.141441: Pseudo dice [0.8662] +2024-11-22 09:25:46.141521: Epoch time: 17.65 s +2024-11-22 09:25:46.993443: +2024-11-22 09:25:46.993636: Epoch 4088 +2024-11-22 09:25:46.993747: Current learning rate: 0.00525 +2024-11-22 09:26:04.701522: train_loss -0.7789 +2024-11-22 09:26:04.701740: val_loss -0.7649 +2024-11-22 09:26:04.701814: Pseudo dice [0.8608] +2024-11-22 09:26:04.701890: Epoch time: 17.71 s +2024-11-22 09:26:05.659761: +2024-11-22 09:26:05.659975: Epoch 4089 +2024-11-22 09:26:05.660091: Current learning rate: 0.00525 +2024-11-22 09:26:23.849418: train_loss -0.7807 +2024-11-22 09:26:23.849630: val_loss -0.7861 +2024-11-22 09:26:23.849708: Pseudo dice [0.8575] +2024-11-22 09:26:23.849783: Epoch time: 18.19 s +2024-11-22 09:26:25.076257: +2024-11-22 09:26:25.076468: Epoch 4090 +2024-11-22 09:26:25.076580: Current learning rate: 0.00525 +2024-11-22 09:26:43.821542: train_loss -0.7851 +2024-11-22 09:26:43.821850: val_loss -0.765 +2024-11-22 09:26:43.821929: Pseudo dice [0.8537] +2024-11-22 09:26:43.822012: Epoch time: 18.75 s +2024-11-22 09:26:44.679360: +2024-11-22 09:26:44.679595: Epoch 4091 +2024-11-22 09:26:44.679706: Current learning rate: 0.00525 +2024-11-22 09:27:02.881418: train_loss -0.7758 +2024-11-22 09:27:02.881636: val_loss -0.7929 +2024-11-22 09:27:02.881718: Pseudo dice [0.8607] +2024-11-22 09:27:02.881798: Epoch time: 18.2 s +2024-11-22 09:27:03.811451: +2024-11-22 09:27:03.811692: Epoch 4092 +2024-11-22 09:27:03.811803: Current learning rate: 0.00525 +2024-11-22 09:27:21.822367: train_loss -0.7799 +2024-11-22 09:27:21.822575: val_loss -0.7909 +2024-11-22 09:27:21.822651: Pseudo dice [0.8479] +2024-11-22 09:27:21.825010: Epoch time: 18.01 s +2024-11-22 09:27:22.661075: +2024-11-22 09:27:22.661288: Epoch 4093 +2024-11-22 09:27:22.661395: Current learning rate: 0.00525 +2024-11-22 09:27:40.854243: train_loss -0.7831 +2024-11-22 09:27:40.854462: val_loss -0.7841 +2024-11-22 09:27:40.854542: Pseudo dice [0.8562] +2024-11-22 09:27:40.854620: Epoch time: 18.19 s +2024-11-22 09:27:41.788715: +2024-11-22 09:27:41.788996: Epoch 4094 +2024-11-22 09:27:41.789117: Current learning rate: 0.00525 +2024-11-22 09:28:01.163750: train_loss -0.7892 +2024-11-22 09:28:01.163999: val_loss -0.7768 +2024-11-22 09:28:01.164080: Pseudo dice [0.8663] +2024-11-22 09:28:01.164170: Epoch time: 19.38 s +2024-11-22 09:28:02.161004: +2024-11-22 09:28:02.161241: Epoch 4095 +2024-11-22 09:28:02.161358: Current learning rate: 0.00524 +2024-11-22 09:28:20.164378: train_loss -0.7878 +2024-11-22 09:28:20.164583: val_loss -0.7652 +2024-11-22 09:28:20.164661: Pseudo dice [0.8633] +2024-11-22 09:28:20.164738: Epoch time: 18.0 s +2024-11-22 09:28:20.164800: Yayy! New best EMA pseudo Dice: 0.857 +2024-11-22 09:28:21.252446: +2024-11-22 09:28:21.252666: Epoch 4096 +2024-11-22 09:28:21.252773: Current learning rate: 0.00524 +2024-11-22 09:28:39.615834: train_loss -0.7972 +2024-11-22 09:28:39.625129: val_loss -0.7831 +2024-11-22 09:28:39.625288: Pseudo dice [0.8513] +2024-11-22 09:28:39.625372: Epoch time: 18.36 s +2024-11-22 09:28:40.645498: +2024-11-22 09:28:40.645713: Epoch 4097 +2024-11-22 09:28:40.645828: Current learning rate: 0.00524 +2024-11-22 09:28:58.090142: train_loss -0.7943 +2024-11-22 09:28:58.090363: val_loss -0.7739 +2024-11-22 09:28:58.095587: Pseudo dice [0.847] +2024-11-22 09:28:58.095733: Epoch time: 17.45 s +2024-11-22 09:28:59.082406: +2024-11-22 09:28:59.082621: Epoch 4098 +2024-11-22 09:28:59.082729: Current learning rate: 0.00524 +2024-11-22 09:29:17.209079: train_loss -0.7831 +2024-11-22 09:29:17.209358: val_loss -0.7874 +2024-11-22 09:29:17.209440: Pseudo dice [0.8568] +2024-11-22 09:29:17.209522: Epoch time: 18.13 s +2024-11-22 09:29:18.271408: +2024-11-22 09:29:18.271627: Epoch 4099 +2024-11-22 09:29:18.271737: Current learning rate: 0.00524 +2024-11-22 09:29:37.018569: train_loss -0.7788 +2024-11-22 09:29:37.018777: val_loss -0.7474 +2024-11-22 09:29:37.018852: Pseudo dice [0.8223] +2024-11-22 09:29:37.018925: Epoch time: 18.75 s +2024-11-22 09:29:38.098789: +2024-11-22 09:29:38.098982: Epoch 4100 +2024-11-22 09:29:38.099099: Current learning rate: 0.00524 +2024-11-22 09:29:55.863490: train_loss -0.767 +2024-11-22 09:29:55.863702: val_loss -0.7679 +2024-11-22 09:29:55.863777: Pseudo dice [0.8507] +2024-11-22 09:29:55.863852: Epoch time: 17.77 s +2024-11-22 09:29:56.687929: +2024-11-22 09:29:56.688134: Epoch 4101 +2024-11-22 09:29:56.688242: Current learning rate: 0.00524 +2024-11-22 09:30:14.777894: train_loss -0.7812 +2024-11-22 09:30:14.778111: val_loss -0.7694 +2024-11-22 09:30:14.778192: Pseudo dice [0.863] +2024-11-22 09:30:14.778271: Epoch time: 18.09 s +2024-11-22 09:30:16.002331: +2024-11-22 09:30:16.002551: Epoch 4102 +2024-11-22 09:30:16.002660: Current learning rate: 0.00524 +2024-11-22 09:30:34.058302: train_loss -0.7993 +2024-11-22 09:30:34.058547: val_loss -0.7601 +2024-11-22 09:30:34.058626: Pseudo dice [0.8526] +2024-11-22 09:30:34.058706: Epoch time: 18.06 s +2024-11-22 09:30:34.885508: +2024-11-22 09:30:34.885727: Epoch 4103 +2024-11-22 09:30:34.885835: Current learning rate: 0.00523 +2024-11-22 09:30:52.914090: train_loss -0.7843 +2024-11-22 09:30:52.914346: val_loss -0.773 +2024-11-22 09:30:52.914422: Pseudo dice [0.8523] +2024-11-22 09:30:52.914498: Epoch time: 18.03 s +2024-11-22 09:30:53.752553: +2024-11-22 09:30:53.752759: Epoch 4104 +2024-11-22 09:30:53.752872: Current learning rate: 0.00523 +2024-11-22 09:31:12.645380: train_loss -0.7696 +2024-11-22 09:31:12.645593: val_loss -0.7874 +2024-11-22 09:31:12.645669: Pseudo dice [0.8567] +2024-11-22 09:31:12.645744: Epoch time: 18.89 s +2024-11-22 09:31:13.573649: +2024-11-22 09:31:13.573851: Epoch 4105 +2024-11-22 09:31:13.573963: Current learning rate: 0.00523 +2024-11-22 09:31:33.168205: train_loss -0.7807 +2024-11-22 09:31:33.168457: val_loss -0.7549 +2024-11-22 09:31:33.168535: Pseudo dice [0.8342] +2024-11-22 09:31:33.168613: Epoch time: 19.6 s +2024-11-22 09:31:34.024044: +2024-11-22 09:31:34.024272: Epoch 4106 +2024-11-22 09:31:34.024387: Current learning rate: 0.00523 +2024-11-22 09:31:51.431598: train_loss -0.7902 +2024-11-22 09:31:51.431837: val_loss -0.7698 +2024-11-22 09:31:51.431921: Pseudo dice [0.8538] +2024-11-22 09:31:51.432001: Epoch time: 17.41 s +2024-11-22 09:31:52.268200: +2024-11-22 09:31:52.268407: Epoch 4107 +2024-11-22 09:31:52.268524: Current learning rate: 0.00523 +2024-11-22 09:32:10.850531: train_loss -0.7839 +2024-11-22 09:32:10.850802: val_loss -0.7635 +2024-11-22 09:32:10.850884: Pseudo dice [0.8485] +2024-11-22 09:32:10.850965: Epoch time: 18.58 s +2024-11-22 09:32:11.698274: +2024-11-22 09:32:11.698489: Epoch 4108 +2024-11-22 09:32:11.698602: Current learning rate: 0.00523 +2024-11-22 09:32:30.056793: train_loss -0.795 +2024-11-22 09:32:30.059180: val_loss -0.7617 +2024-11-22 09:32:30.059278: Pseudo dice [0.8456] +2024-11-22 09:32:30.059356: Epoch time: 18.36 s +2024-11-22 09:32:30.981302: +2024-11-22 09:32:30.981538: Epoch 4109 +2024-11-22 09:32:30.981651: Current learning rate: 0.00523 +2024-11-22 09:32:49.701892: train_loss -0.7823 +2024-11-22 09:32:49.702147: val_loss -0.773 +2024-11-22 09:32:49.702235: Pseudo dice [0.8587] +2024-11-22 09:32:49.702316: Epoch time: 18.72 s +2024-11-22 09:32:50.536725: +2024-11-22 09:32:50.536934: Epoch 4110 +2024-11-22 09:32:50.537045: Current learning rate: 0.00523 +2024-11-22 09:33:09.821349: train_loss -0.7789 +2024-11-22 09:33:09.821595: val_loss -0.7732 +2024-11-22 09:33:09.821672: Pseudo dice [0.8486] +2024-11-22 09:33:09.821762: Epoch time: 19.29 s +2024-11-22 09:33:10.655756: +2024-11-22 09:33:10.655982: Epoch 4111 +2024-11-22 09:33:10.656109: Current learning rate: 0.00522 +2024-11-22 09:33:29.351565: train_loss -0.778 +2024-11-22 09:33:29.351774: val_loss -0.7456 +2024-11-22 09:33:29.351848: Pseudo dice [0.8314] +2024-11-22 09:33:29.351924: Epoch time: 18.7 s +2024-11-22 09:33:30.185540: +2024-11-22 09:33:30.185761: Epoch 4112 +2024-11-22 09:33:30.185871: Current learning rate: 0.00522 +2024-11-22 09:33:48.466213: train_loss -0.7807 +2024-11-22 09:33:48.466415: val_loss -0.7584 +2024-11-22 09:33:48.466488: Pseudo dice [0.8496] +2024-11-22 09:33:48.466564: Epoch time: 18.28 s +2024-11-22 09:33:49.398814: +2024-11-22 09:33:49.399245: Epoch 4113 +2024-11-22 09:33:49.399378: Current learning rate: 0.00522 +2024-11-22 09:34:08.777369: train_loss -0.7791 +2024-11-22 09:34:08.777573: val_loss -0.7446 +2024-11-22 09:34:08.777645: Pseudo dice [0.8533] +2024-11-22 09:34:08.777721: Epoch time: 19.38 s +2024-11-22 09:34:10.009166: +2024-11-22 09:34:10.009406: Epoch 4114 +2024-11-22 09:34:10.009526: Current learning rate: 0.00522 +2024-11-22 09:34:28.898191: train_loss -0.7701 +2024-11-22 09:34:28.898440: val_loss -0.7573 +2024-11-22 09:34:28.898518: Pseudo dice [0.8432] +2024-11-22 09:34:28.900787: Epoch time: 18.89 s +2024-11-22 09:34:30.006908: +2024-11-22 09:34:30.007141: Epoch 4115 +2024-11-22 09:34:30.007251: Current learning rate: 0.00522 +2024-11-22 09:34:48.041099: train_loss -0.7779 +2024-11-22 09:34:48.041314: val_loss -0.7533 +2024-11-22 09:34:48.043562: Pseudo dice [0.8749] +2024-11-22 09:34:48.043658: Epoch time: 18.03 s +2024-11-22 09:34:48.928618: +2024-11-22 09:34:48.928874: Epoch 4116 +2024-11-22 09:34:48.928983: Current learning rate: 0.00522 +2024-11-22 09:35:07.656271: train_loss -0.7846 +2024-11-22 09:35:07.656489: val_loss -0.7478 +2024-11-22 09:35:07.656567: Pseudo dice [0.8496] +2024-11-22 09:35:07.656641: Epoch time: 18.73 s +2024-11-22 09:35:08.490669: +2024-11-22 09:35:08.490904: Epoch 4117 +2024-11-22 09:35:08.491017: Current learning rate: 0.00522 +2024-11-22 09:35:28.038431: train_loss -0.7757 +2024-11-22 09:35:28.038679: val_loss -0.7749 +2024-11-22 09:35:28.038772: Pseudo dice [0.8564] +2024-11-22 09:35:28.038909: Epoch time: 19.55 s +2024-11-22 09:35:28.897250: +2024-11-22 09:35:28.897462: Epoch 4118 +2024-11-22 09:35:28.897570: Current learning rate: 0.00522 +2024-11-22 09:35:47.312145: train_loss -0.776 +2024-11-22 09:35:47.312373: val_loss -0.7592 +2024-11-22 09:35:47.312446: Pseudo dice [0.8467] +2024-11-22 09:35:47.312523: Epoch time: 18.42 s +2024-11-22 09:35:48.174742: +2024-11-22 09:35:48.174949: Epoch 4119 +2024-11-22 09:35:48.175067: Current learning rate: 0.00522 +2024-11-22 09:36:06.046383: train_loss -0.783 +2024-11-22 09:36:06.046618: val_loss -0.7549 +2024-11-22 09:36:06.046697: Pseudo dice [0.8439] +2024-11-22 09:36:06.046770: Epoch time: 17.87 s +2024-11-22 09:36:06.878867: +2024-11-22 09:36:06.879075: Epoch 4120 +2024-11-22 09:36:06.879185: Current learning rate: 0.00521 +2024-11-22 09:36:25.202510: train_loss -0.7886 +2024-11-22 09:36:25.202726: val_loss -0.7761 +2024-11-22 09:36:25.202802: Pseudo dice [0.853] +2024-11-22 09:36:25.202878: Epoch time: 18.32 s +2024-11-22 09:36:26.028718: +2024-11-22 09:36:26.028905: Epoch 4121 +2024-11-22 09:36:26.029011: Current learning rate: 0.00521 +2024-11-22 09:36:45.448531: train_loss -0.7769 +2024-11-22 09:36:45.448744: val_loss -0.7467 +2024-11-22 09:36:45.448822: Pseudo dice [0.84] +2024-11-22 09:36:45.448905: Epoch time: 19.42 s +2024-11-22 09:36:46.277498: +2024-11-22 09:36:46.277720: Epoch 4122 +2024-11-22 09:36:46.277833: Current learning rate: 0.00521 +2024-11-22 09:37:05.894602: train_loss -0.7706 +2024-11-22 09:37:05.894832: val_loss -0.7536 +2024-11-22 09:37:05.894934: Pseudo dice [0.8437] +2024-11-22 09:37:05.895019: Epoch time: 19.62 s +2024-11-22 09:37:06.722823: +2024-11-22 09:37:06.723026: Epoch 4123 +2024-11-22 09:37:06.723154: Current learning rate: 0.00521 +2024-11-22 09:37:25.588432: train_loss -0.7843 +2024-11-22 09:37:25.588649: val_loss -0.7539 +2024-11-22 09:37:25.588726: Pseudo dice [0.8329] +2024-11-22 09:37:25.588806: Epoch time: 18.87 s +2024-11-22 09:37:26.532293: +2024-11-22 09:37:26.532525: Epoch 4124 +2024-11-22 09:37:26.532636: Current learning rate: 0.00521 +2024-11-22 09:37:45.094364: train_loss -0.7879 +2024-11-22 09:37:45.094574: val_loss -0.7762 +2024-11-22 09:37:45.094649: Pseudo dice [0.8643] +2024-11-22 09:37:45.094724: Epoch time: 18.56 s +2024-11-22 09:37:45.922469: +2024-11-22 09:37:45.922667: Epoch 4125 +2024-11-22 09:37:45.922778: Current learning rate: 0.00521 +2024-11-22 09:38:03.365908: train_loss -0.7787 +2024-11-22 09:38:03.366180: val_loss -0.7834 +2024-11-22 09:38:03.366257: Pseudo dice [0.8453] +2024-11-22 09:38:03.366334: Epoch time: 17.44 s +2024-11-22 09:38:04.620738: +2024-11-22 09:38:04.620951: Epoch 4126 +2024-11-22 09:38:04.621069: Current learning rate: 0.00521 +2024-11-22 09:38:22.344800: train_loss -0.7841 +2024-11-22 09:38:22.345053: val_loss -0.7717 +2024-11-22 09:38:22.345145: Pseudo dice [0.8507] +2024-11-22 09:38:22.345235: Epoch time: 17.72 s +2024-11-22 09:38:23.283619: +2024-11-22 09:38:23.283835: Epoch 4127 +2024-11-22 09:38:23.283945: Current learning rate: 0.00521 +2024-11-22 09:38:42.009639: train_loss -0.7788 +2024-11-22 09:38:42.009848: val_loss -0.7931 +2024-11-22 09:38:42.009922: Pseudo dice [0.8555] +2024-11-22 09:38:42.009996: Epoch time: 18.73 s +2024-11-22 09:38:42.843962: +2024-11-22 09:38:42.844199: Epoch 4128 +2024-11-22 09:38:42.844309: Current learning rate: 0.0052 +2024-11-22 09:39:01.447896: train_loss -0.79 +2024-11-22 09:39:01.448114: val_loss -0.7832 +2024-11-22 09:39:01.448189: Pseudo dice [0.869] +2024-11-22 09:39:01.448262: Epoch time: 18.6 s +2024-11-22 09:39:02.344131: +2024-11-22 09:39:02.344353: Epoch 4129 +2024-11-22 09:39:02.344463: Current learning rate: 0.0052 +2024-11-22 09:39:20.163519: train_loss -0.7856 +2024-11-22 09:39:20.163743: val_loss -0.7684 +2024-11-22 09:39:20.163819: Pseudo dice [0.851] +2024-11-22 09:39:20.163904: Epoch time: 17.82 s +2024-11-22 09:39:21.003294: +2024-11-22 09:39:21.003539: Epoch 4130 +2024-11-22 09:39:21.003688: Current learning rate: 0.0052 +2024-11-22 09:39:40.244421: train_loss -0.7741 +2024-11-22 09:39:40.244675: val_loss -0.7614 +2024-11-22 09:39:40.244753: Pseudo dice [0.8388] +2024-11-22 09:39:40.244830: Epoch time: 19.24 s +2024-11-22 09:39:41.075261: +2024-11-22 09:39:41.075479: Epoch 4131 +2024-11-22 09:39:41.075592: Current learning rate: 0.0052 +2024-11-22 09:39:59.687145: train_loss -0.7577 +2024-11-22 09:39:59.687353: val_loss -0.7521 +2024-11-22 09:39:59.687433: Pseudo dice [0.8434] +2024-11-22 09:39:59.687509: Epoch time: 18.61 s +2024-11-22 09:40:00.521046: +2024-11-22 09:40:00.521275: Epoch 4132 +2024-11-22 09:40:00.521387: Current learning rate: 0.0052 +2024-11-22 09:40:18.477590: train_loss -0.7691 +2024-11-22 09:40:18.477802: val_loss -0.7728 +2024-11-22 09:40:18.477877: Pseudo dice [0.8601] +2024-11-22 09:40:18.477950: Epoch time: 17.96 s +2024-11-22 09:40:19.428320: +2024-11-22 09:40:19.428512: Epoch 4133 +2024-11-22 09:40:19.428624: Current learning rate: 0.0052 +2024-11-22 09:40:37.846193: train_loss -0.7748 +2024-11-22 09:40:37.846403: val_loss -0.7557 +2024-11-22 09:40:37.846477: Pseudo dice [0.8559] +2024-11-22 09:40:37.846554: Epoch time: 18.42 s +2024-11-22 09:40:38.676513: +2024-11-22 09:40:38.676730: Epoch 4134 +2024-11-22 09:40:38.676846: Current learning rate: 0.0052 +2024-11-22 09:40:57.136322: train_loss -0.7776 +2024-11-22 09:40:57.136549: val_loss -0.779 +2024-11-22 09:40:57.136626: Pseudo dice [0.8486] +2024-11-22 09:40:57.136709: Epoch time: 18.46 s +2024-11-22 09:40:58.228849: +2024-11-22 09:40:58.229071: Epoch 4135 +2024-11-22 09:40:58.229185: Current learning rate: 0.0052 +2024-11-22 09:41:16.291518: train_loss -0.7793 +2024-11-22 09:41:16.291734: val_loss -0.7512 +2024-11-22 09:41:16.291806: Pseudo dice [0.8436] +2024-11-22 09:41:16.291882: Epoch time: 18.06 s +2024-11-22 09:41:17.176389: +2024-11-22 09:41:17.176595: Epoch 4136 +2024-11-22 09:41:17.176703: Current learning rate: 0.00519 +2024-11-22 09:41:35.896613: train_loss -0.7814 +2024-11-22 09:41:35.896868: val_loss -0.778 +2024-11-22 09:41:35.896944: Pseudo dice [0.8338] +2024-11-22 09:41:35.897022: Epoch time: 18.72 s +2024-11-22 09:41:36.797021: +2024-11-22 09:41:36.797249: Epoch 4137 +2024-11-22 09:41:36.797359: Current learning rate: 0.00519 +2024-11-22 09:41:55.091255: train_loss -0.7897 +2024-11-22 09:41:55.091508: val_loss -0.7853 +2024-11-22 09:41:55.091590: Pseudo dice [0.8453] +2024-11-22 09:41:55.091677: Epoch time: 18.29 s +2024-11-22 09:41:56.326267: +2024-11-22 09:41:56.326463: Epoch 4138 +2024-11-22 09:41:56.326574: Current learning rate: 0.00519 +2024-11-22 09:42:14.568794: train_loss -0.7846 +2024-11-22 09:42:14.569001: val_loss -0.7635 +2024-11-22 09:42:14.569085: Pseudo dice [0.8418] +2024-11-22 09:42:14.569158: Epoch time: 18.24 s +2024-11-22 09:42:15.401529: +2024-11-22 09:42:15.401759: Epoch 4139 +2024-11-22 09:42:15.401870: Current learning rate: 0.00519 +2024-11-22 09:42:34.103848: train_loss -0.7872 +2024-11-22 09:42:34.104067: val_loss -0.7676 +2024-11-22 09:42:34.104142: Pseudo dice [0.8451] +2024-11-22 09:42:34.104219: Epoch time: 18.7 s +2024-11-22 09:42:35.044434: +2024-11-22 09:42:35.044674: Epoch 4140 +2024-11-22 09:42:35.044791: Current learning rate: 0.00519 +2024-11-22 09:42:53.823838: train_loss -0.7859 +2024-11-22 09:42:53.824051: val_loss -0.7481 +2024-11-22 09:42:53.824183: Pseudo dice [0.8545] +2024-11-22 09:42:53.824262: Epoch time: 18.78 s +2024-11-22 09:42:54.657378: +2024-11-22 09:42:54.657601: Epoch 4141 +2024-11-22 09:42:54.657707: Current learning rate: 0.00519 +2024-11-22 09:43:11.935529: train_loss -0.7802 +2024-11-22 09:43:11.935784: val_loss -0.7518 +2024-11-22 09:43:11.935865: Pseudo dice [0.8452] +2024-11-22 09:43:11.935947: Epoch time: 17.28 s +2024-11-22 09:43:12.904636: +2024-11-22 09:43:12.904855: Epoch 4142 +2024-11-22 09:43:12.904971: Current learning rate: 0.00519 +2024-11-22 09:43:30.879250: train_loss -0.7677 +2024-11-22 09:43:30.879522: val_loss -0.7907 +2024-11-22 09:43:30.879604: Pseudo dice [0.8585] +2024-11-22 09:43:30.879683: Epoch time: 17.98 s +2024-11-22 09:43:31.814487: +2024-11-22 09:43:31.814709: Epoch 4143 +2024-11-22 09:43:31.814824: Current learning rate: 0.00519 +2024-11-22 09:43:50.612821: train_loss -0.7836 +2024-11-22 09:43:50.613029: val_loss -0.7533 +2024-11-22 09:43:50.613109: Pseudo dice [0.8451] +2024-11-22 09:43:50.613181: Epoch time: 18.8 s +2024-11-22 09:43:51.526494: +2024-11-22 09:43:51.526679: Epoch 4144 +2024-11-22 09:43:51.526796: Current learning rate: 0.00518 +2024-11-22 09:44:10.105458: train_loss -0.7855 +2024-11-22 09:44:10.105668: val_loss -0.7821 +2024-11-22 09:44:10.105748: Pseudo dice [0.844] +2024-11-22 09:44:10.105827: Epoch time: 18.58 s +2024-11-22 09:44:10.942734: +2024-11-22 09:44:10.942976: Epoch 4145 +2024-11-22 09:44:10.943093: Current learning rate: 0.00518 +2024-11-22 09:44:29.328325: train_loss -0.7729 +2024-11-22 09:44:29.328567: val_loss -0.7606 +2024-11-22 09:44:29.328642: Pseudo dice [0.8415] +2024-11-22 09:44:29.328720: Epoch time: 18.39 s +2024-11-22 09:44:30.160033: +2024-11-22 09:44:30.160242: Epoch 4146 +2024-11-22 09:44:30.160351: Current learning rate: 0.00518 +2024-11-22 09:44:48.689993: train_loss -0.7717 +2024-11-22 09:44:48.690214: val_loss -0.7319 +2024-11-22 09:44:48.690295: Pseudo dice [0.8534] +2024-11-22 09:44:48.690371: Epoch time: 18.53 s +2024-11-22 09:44:49.518903: +2024-11-22 09:44:49.519109: Epoch 4147 +2024-11-22 09:44:49.519219: Current learning rate: 0.00518 +2024-11-22 09:45:07.284353: train_loss -0.7758 +2024-11-22 09:45:07.284572: val_loss -0.8006 +2024-11-22 09:45:07.284649: Pseudo dice [0.8685] +2024-11-22 09:45:07.284727: Epoch time: 17.77 s +2024-11-22 09:45:08.118377: +2024-11-22 09:45:08.118603: Epoch 4148 +2024-11-22 09:45:08.118715: Current learning rate: 0.00518 +2024-11-22 09:45:26.994302: train_loss -0.7903 +2024-11-22 09:45:26.994518: val_loss -0.7471 +2024-11-22 09:45:26.994595: Pseudo dice [0.8612] +2024-11-22 09:45:26.994668: Epoch time: 18.88 s +2024-11-22 09:45:27.826231: +2024-11-22 09:45:27.826465: Epoch 4149 +2024-11-22 09:45:27.826583: Current learning rate: 0.00518 +2024-11-22 09:45:45.843930: train_loss -0.7927 +2024-11-22 09:45:45.844211: val_loss -0.7651 +2024-11-22 09:45:45.844289: Pseudo dice [0.848] +2024-11-22 09:45:45.844372: Epoch time: 18.02 s +2024-11-22 09:45:47.298886: +2024-11-22 09:45:47.299103: Epoch 4150 +2024-11-22 09:45:47.299217: Current learning rate: 0.00518 +2024-11-22 09:46:05.928216: train_loss -0.7828 +2024-11-22 09:46:05.928427: val_loss -0.7626 +2024-11-22 09:46:05.928501: Pseudo dice [0.8481] +2024-11-22 09:46:05.928575: Epoch time: 18.63 s +2024-11-22 09:46:06.757035: +2024-11-22 09:46:06.757285: Epoch 4151 +2024-11-22 09:46:06.757404: Current learning rate: 0.00518 +2024-11-22 09:46:24.845973: train_loss -0.7862 +2024-11-22 09:46:24.846182: val_loss -0.7807 +2024-11-22 09:46:24.846256: Pseudo dice [0.8587] +2024-11-22 09:46:24.846333: Epoch time: 18.09 s +2024-11-22 09:46:25.682205: +2024-11-22 09:46:25.682500: Epoch 4152 +2024-11-22 09:46:25.682611: Current learning rate: 0.00518 +2024-11-22 09:46:44.330232: train_loss -0.7826 +2024-11-22 09:46:44.330463: val_loss -0.7704 +2024-11-22 09:46:44.330536: Pseudo dice [0.854] +2024-11-22 09:46:44.330618: Epoch time: 18.65 s +2024-11-22 09:46:45.301815: +2024-11-22 09:46:45.301999: Epoch 4153 +2024-11-22 09:46:45.302116: Current learning rate: 0.00517 +2024-11-22 09:47:04.547349: train_loss -0.7815 +2024-11-22 09:47:04.547568: val_loss -0.7801 +2024-11-22 09:47:04.547644: Pseudo dice [0.8616] +2024-11-22 09:47:04.553151: Epoch time: 19.25 s +2024-11-22 09:47:05.455926: +2024-11-22 09:47:05.456140: Epoch 4154 +2024-11-22 09:47:05.456252: Current learning rate: 0.00517 +2024-11-22 09:47:24.173045: train_loss -0.7788 +2024-11-22 09:47:24.173262: val_loss -0.7637 +2024-11-22 09:47:24.173336: Pseudo dice [0.8477] +2024-11-22 09:47:24.173409: Epoch time: 18.72 s +2024-11-22 09:47:25.017947: +2024-11-22 09:47:25.018178: Epoch 4155 +2024-11-22 09:47:25.018289: Current learning rate: 0.00517 +2024-11-22 09:47:44.384675: train_loss -0.7833 +2024-11-22 09:47:44.384920: val_loss -0.761 +2024-11-22 09:47:44.384995: Pseudo dice [0.8612] +2024-11-22 09:47:44.385081: Epoch time: 19.37 s +2024-11-22 09:47:45.248401: +2024-11-22 09:47:45.248600: Epoch 4156 +2024-11-22 09:47:45.248707: Current learning rate: 0.00517 +2024-11-22 09:48:03.544167: train_loss -0.7769 +2024-11-22 09:48:03.544374: val_loss -0.7711 +2024-11-22 09:48:03.544447: Pseudo dice [0.8513] +2024-11-22 09:48:03.544522: Epoch time: 18.3 s +2024-11-22 09:48:04.381594: +2024-11-22 09:48:04.381807: Epoch 4157 +2024-11-22 09:48:04.381932: Current learning rate: 0.00517 +2024-11-22 09:48:24.504022: train_loss -0.7771 +2024-11-22 09:48:24.506436: val_loss -0.7502 +2024-11-22 09:48:24.506527: Pseudo dice [0.8538] +2024-11-22 09:48:24.506610: Epoch time: 20.12 s +2024-11-22 09:48:25.380534: +2024-11-22 09:48:25.380752: Epoch 4158 +2024-11-22 09:48:25.380870: Current learning rate: 0.00517 +2024-11-22 09:48:44.752845: train_loss -0.7805 +2024-11-22 09:48:44.753055: val_loss -0.7586 +2024-11-22 09:48:44.753140: Pseudo dice [0.8511] +2024-11-22 09:48:44.753216: Epoch time: 19.37 s +2024-11-22 09:48:45.587527: +2024-11-22 09:48:45.587776: Epoch 4159 +2024-11-22 09:48:45.587891: Current learning rate: 0.00517 +2024-11-22 09:49:03.635170: train_loss -0.7826 +2024-11-22 09:49:03.635382: val_loss -0.7703 +2024-11-22 09:49:03.635457: Pseudo dice [0.8566] +2024-11-22 09:49:03.635531: Epoch time: 18.05 s +2024-11-22 09:49:04.571561: +2024-11-22 09:49:04.571752: Epoch 4160 +2024-11-22 09:49:04.571863: Current learning rate: 0.00517 +2024-11-22 09:49:24.142413: train_loss -0.7849 +2024-11-22 09:49:24.142625: val_loss -0.7827 +2024-11-22 09:49:24.142703: Pseudo dice [0.843] +2024-11-22 09:49:24.142787: Epoch time: 19.57 s +2024-11-22 09:49:24.983695: +2024-11-22 09:49:24.983914: Epoch 4161 +2024-11-22 09:49:24.984032: Current learning rate: 0.00516 +2024-11-22 09:49:43.494752: train_loss -0.7842 +2024-11-22 09:49:43.495021: val_loss -0.7569 +2024-11-22 09:49:43.495104: Pseudo dice [0.8588] +2024-11-22 09:49:43.495185: Epoch time: 18.51 s +2024-11-22 09:49:44.742176: +2024-11-22 09:49:44.742406: Epoch 4162 +2024-11-22 09:49:44.742515: Current learning rate: 0.00516 +2024-11-22 09:50:02.730447: train_loss -0.7847 +2024-11-22 09:50:02.730669: val_loss -0.7989 +2024-11-22 09:50:02.730751: Pseudo dice [0.8575] +2024-11-22 09:50:02.730831: Epoch time: 17.99 s +2024-11-22 09:50:03.565338: +2024-11-22 09:50:03.565568: Epoch 4163 +2024-11-22 09:50:03.565684: Current learning rate: 0.00516 +2024-11-22 09:50:23.072995: train_loss -0.7835 +2024-11-22 09:50:23.073219: val_loss -0.7739 +2024-11-22 09:50:23.073299: Pseudo dice [0.8689] +2024-11-22 09:50:23.073378: Epoch time: 19.51 s +2024-11-22 09:50:23.956199: +2024-11-22 09:50:23.956421: Epoch 4164 +2024-11-22 09:50:23.956536: Current learning rate: 0.00516 +2024-11-22 09:50:42.956766: train_loss -0.7843 +2024-11-22 09:50:42.956977: val_loss -0.7962 +2024-11-22 09:50:42.957052: Pseudo dice [0.866] +2024-11-22 09:50:42.957134: Epoch time: 19.0 s +2024-11-22 09:50:43.811947: +2024-11-22 09:50:43.812180: Epoch 4165 +2024-11-22 09:50:43.812295: Current learning rate: 0.00516 +2024-11-22 09:51:02.296484: train_loss -0.7894 +2024-11-22 09:51:02.296695: val_loss -0.7772 +2024-11-22 09:51:02.296771: Pseudo dice [0.8525] +2024-11-22 09:51:02.296847: Epoch time: 18.49 s +2024-11-22 09:51:03.132964: +2024-11-22 09:51:03.133180: Epoch 4166 +2024-11-22 09:51:03.133288: Current learning rate: 0.00516 +2024-11-22 09:51:20.465825: train_loss -0.7644 +2024-11-22 09:51:20.466034: val_loss -0.7488 +2024-11-22 09:51:20.466114: Pseudo dice [0.8434] +2024-11-22 09:51:20.466190: Epoch time: 17.33 s +2024-11-22 09:51:21.296767: +2024-11-22 09:51:21.296974: Epoch 4167 +2024-11-22 09:51:21.297089: Current learning rate: 0.00516 +2024-11-22 09:51:39.622730: train_loss -0.7796 +2024-11-22 09:51:39.622945: val_loss -0.7704 +2024-11-22 09:51:39.623087: Pseudo dice [0.8525] +2024-11-22 09:51:39.623164: Epoch time: 18.33 s +2024-11-22 09:51:40.465182: +2024-11-22 09:51:40.465382: Epoch 4168 +2024-11-22 09:51:40.465489: Current learning rate: 0.00516 +2024-11-22 09:51:58.671272: train_loss -0.7847 +2024-11-22 09:51:58.671498: val_loss -0.7712 +2024-11-22 09:51:58.671575: Pseudo dice [0.8666] +2024-11-22 09:51:58.671654: Epoch time: 18.21 s +2024-11-22 09:51:59.574900: +2024-11-22 09:51:59.575134: Epoch 4169 +2024-11-22 09:51:59.575246: Current learning rate: 0.00515 +2024-11-22 09:52:18.162811: train_loss -0.7843 +2024-11-22 09:52:18.163049: val_loss -0.7678 +2024-11-22 09:52:18.163132: Pseudo dice [0.8563] +2024-11-22 09:52:18.163208: Epoch time: 18.59 s +2024-11-22 09:52:18.992587: +2024-11-22 09:52:18.992792: Epoch 4170 +2024-11-22 09:52:18.992904: Current learning rate: 0.00515 +2024-11-22 09:52:37.006029: train_loss -0.7973 +2024-11-22 09:52:37.016275: val_loss -0.7714 +2024-11-22 09:52:37.016384: Pseudo dice [0.8452] +2024-11-22 09:52:37.016461: Epoch time: 18.01 s +2024-11-22 09:52:37.847162: +2024-11-22 09:52:37.847361: Epoch 4171 +2024-11-22 09:52:37.847472: Current learning rate: 0.00515 +2024-11-22 09:52:56.352346: train_loss -0.7878 +2024-11-22 09:52:56.352558: val_loss -0.7568 +2024-11-22 09:52:56.352635: Pseudo dice [0.8614] +2024-11-22 09:52:56.352708: Epoch time: 18.51 s +2024-11-22 09:52:57.183126: +2024-11-22 09:52:57.183336: Epoch 4172 +2024-11-22 09:52:57.183449: Current learning rate: 0.00515 +2024-11-22 09:53:16.314805: train_loss -0.7826 +2024-11-22 09:53:16.315051: val_loss -0.7866 +2024-11-22 09:53:16.315149: Pseudo dice [0.8558] +2024-11-22 09:53:16.315233: Epoch time: 19.13 s +2024-11-22 09:53:17.150912: +2024-11-22 09:53:17.151128: Epoch 4173 +2024-11-22 09:53:17.151240: Current learning rate: 0.00515 +2024-11-22 09:53:35.408872: train_loss -0.7853 +2024-11-22 09:53:35.414319: val_loss -0.7767 +2024-11-22 09:53:35.414447: Pseudo dice [0.8492] +2024-11-22 09:53:35.414529: Epoch time: 18.26 s +2024-11-22 09:53:36.645815: +2024-11-22 09:53:36.646032: Epoch 4174 +2024-11-22 09:53:36.646147: Current learning rate: 0.00515 +2024-11-22 09:53:55.248822: train_loss -0.784 +2024-11-22 09:53:55.249046: val_loss -0.7825 +2024-11-22 09:53:55.249131: Pseudo dice [0.8681] +2024-11-22 09:53:55.249207: Epoch time: 18.6 s +2024-11-22 09:53:56.078953: +2024-11-22 09:53:56.079184: Epoch 4175 +2024-11-22 09:53:56.079297: Current learning rate: 0.00515 +2024-11-22 09:54:13.577009: train_loss -0.79 +2024-11-22 09:54:13.577245: val_loss -0.7632 +2024-11-22 09:54:13.577325: Pseudo dice [0.863] +2024-11-22 09:54:13.577408: Epoch time: 17.5 s +2024-11-22 09:54:14.438447: +2024-11-22 09:54:14.438691: Epoch 4176 +2024-11-22 09:54:14.438811: Current learning rate: 0.00515 +2024-11-22 09:54:33.118857: train_loss -0.7878 +2024-11-22 09:54:33.119147: val_loss -0.7848 +2024-11-22 09:54:33.119231: Pseudo dice [0.8613] +2024-11-22 09:54:33.119312: Epoch time: 18.68 s +2024-11-22 09:54:33.119376: Yayy! New best EMA pseudo Dice: 0.8571 +2024-11-22 09:54:34.216583: +2024-11-22 09:54:34.216768: Epoch 4177 +2024-11-22 09:54:34.216877: Current learning rate: 0.00514 +2024-11-22 09:54:51.535071: train_loss -0.7747 +2024-11-22 09:54:51.535312: val_loss -0.7694 +2024-11-22 09:54:51.535386: Pseudo dice [0.8599] +2024-11-22 09:54:51.535459: Epoch time: 17.32 s +2024-11-22 09:54:51.535520: Yayy! New best EMA pseudo Dice: 0.8574 +2024-11-22 09:54:52.627569: +2024-11-22 09:54:52.627775: Epoch 4178 +2024-11-22 09:54:52.627887: Current learning rate: 0.00514 +2024-11-22 09:55:10.736519: train_loss -0.7835 +2024-11-22 09:55:10.736770: val_loss -0.7837 +2024-11-22 09:55:10.736849: Pseudo dice [0.8549] +2024-11-22 09:55:10.736962: Epoch time: 18.11 s +2024-11-22 09:55:11.573573: +2024-11-22 09:55:11.573797: Epoch 4179 +2024-11-22 09:55:11.573905: Current learning rate: 0.00514 +2024-11-22 09:55:30.006992: train_loss -0.7837 +2024-11-22 09:55:30.007276: val_loss -0.7752 +2024-11-22 09:55:30.007357: Pseudo dice [0.8589] +2024-11-22 09:55:30.007435: Epoch time: 18.43 s +2024-11-22 09:55:30.849584: +2024-11-22 09:55:30.849793: Epoch 4180 +2024-11-22 09:55:30.849902: Current learning rate: 0.00514 +2024-11-22 09:55:48.743000: train_loss -0.7829 +2024-11-22 09:55:48.743243: val_loss -0.767 +2024-11-22 09:55:48.743323: Pseudo dice [0.8398] +2024-11-22 09:55:48.743403: Epoch time: 17.89 s +2024-11-22 09:55:49.579151: +2024-11-22 09:55:49.579387: Epoch 4181 +2024-11-22 09:55:49.579503: Current learning rate: 0.00514 +2024-11-22 09:56:07.270784: train_loss -0.7864 +2024-11-22 09:56:07.270992: val_loss -0.7595 +2024-11-22 09:56:07.271074: Pseudo dice [0.8341] +2024-11-22 09:56:07.271148: Epoch time: 17.69 s +2024-11-22 09:56:08.099453: +2024-11-22 09:56:08.099680: Epoch 4182 +2024-11-22 09:56:08.099793: Current learning rate: 0.00514 +2024-11-22 09:56:26.018625: train_loss -0.7927 +2024-11-22 09:56:26.018901: val_loss -0.7635 +2024-11-22 09:56:26.018982: Pseudo dice [0.8537] +2024-11-22 09:56:26.019062: Epoch time: 17.92 s +2024-11-22 09:56:26.864036: +2024-11-22 09:56:26.864269: Epoch 4183 +2024-11-22 09:56:26.864389: Current learning rate: 0.00514 +2024-11-22 09:56:45.601439: train_loss -0.7839 +2024-11-22 09:56:45.601657: val_loss -0.76 +2024-11-22 09:56:45.601740: Pseudo dice [0.8516] +2024-11-22 09:56:45.601819: Epoch time: 18.74 s +2024-11-22 09:56:46.435373: +2024-11-22 09:56:46.435579: Epoch 4184 +2024-11-22 09:56:46.435690: Current learning rate: 0.00514 +2024-11-22 09:57:04.732075: train_loss -0.7762 +2024-11-22 09:57:04.732355: val_loss -0.7664 +2024-11-22 09:57:04.732435: Pseudo dice [0.8547] +2024-11-22 09:57:04.732522: Epoch time: 18.3 s +2024-11-22 09:57:05.568467: +2024-11-22 09:57:05.568681: Epoch 4185 +2024-11-22 09:57:05.568793: Current learning rate: 0.00514 +2024-11-22 09:57:24.339101: train_loss -0.7846 +2024-11-22 09:57:24.339342: val_loss -0.7855 +2024-11-22 09:57:24.339461: Pseudo dice [0.859] +2024-11-22 09:57:24.339535: Epoch time: 18.77 s +2024-11-22 09:57:25.168330: +2024-11-22 09:57:25.168546: Epoch 4186 +2024-11-22 09:57:25.168661: Current learning rate: 0.00513 +2024-11-22 09:57:42.817267: train_loss -0.7914 +2024-11-22 09:57:42.817477: val_loss -0.7837 +2024-11-22 09:57:42.817553: Pseudo dice [0.8471] +2024-11-22 09:57:42.817629: Epoch time: 17.65 s +2024-11-22 09:57:43.657389: +2024-11-22 09:57:43.657611: Epoch 4187 +2024-11-22 09:57:43.657724: Current learning rate: 0.00513 +2024-11-22 09:58:01.893957: train_loss -0.7865 +2024-11-22 09:58:01.894255: val_loss -0.7669 +2024-11-22 09:58:01.894332: Pseudo dice [0.8569] +2024-11-22 09:58:01.894417: Epoch time: 18.24 s +2024-11-22 09:58:02.732196: +2024-11-22 09:58:02.732410: Epoch 4188 +2024-11-22 09:58:02.732523: Current learning rate: 0.00513 +2024-11-22 09:58:21.195403: train_loss -0.7947 +2024-11-22 09:58:21.195616: val_loss -0.7751 +2024-11-22 09:58:21.195705: Pseudo dice [0.8579] +2024-11-22 09:58:21.195780: Epoch time: 18.46 s +2024-11-22 09:58:22.030307: +2024-11-22 09:58:22.030504: Epoch 4189 +2024-11-22 09:58:22.030619: Current learning rate: 0.00513 +2024-11-22 09:58:40.967283: train_loss -0.7872 +2024-11-22 09:58:40.967501: val_loss -0.765 +2024-11-22 09:58:40.967577: Pseudo dice [0.848] +2024-11-22 09:58:40.967654: Epoch time: 18.94 s +2024-11-22 09:58:41.824164: +2024-11-22 09:58:41.824439: Epoch 4190 +2024-11-22 09:58:41.824551: Current learning rate: 0.00513 +2024-11-22 09:59:01.010924: train_loss -0.7847 +2024-11-22 09:59:01.013326: val_loss -0.7602 +2024-11-22 09:59:01.013431: Pseudo dice [0.847] +2024-11-22 09:59:01.013510: Epoch time: 19.19 s +2024-11-22 09:59:01.873956: +2024-11-22 09:59:01.874140: Epoch 4191 +2024-11-22 09:59:01.874248: Current learning rate: 0.00513 +2024-11-22 09:59:20.668464: train_loss -0.7928 +2024-11-22 09:59:20.670846: val_loss -0.7965 +2024-11-22 09:59:20.670947: Pseudo dice [0.8625] +2024-11-22 09:59:20.671031: Epoch time: 18.8 s +2024-11-22 09:59:21.696516: +2024-11-22 09:59:21.696726: Epoch 4192 +2024-11-22 09:59:21.696840: Current learning rate: 0.00513 +2024-11-22 09:59:40.362630: train_loss -0.7826 +2024-11-22 09:59:40.362870: val_loss -0.796 +2024-11-22 09:59:40.362946: Pseudo dice [0.8626] +2024-11-22 09:59:40.363028: Epoch time: 18.67 s +2024-11-22 09:59:41.200608: +2024-11-22 09:59:41.200795: Epoch 4193 +2024-11-22 09:59:41.200906: Current learning rate: 0.00513 +2024-11-22 09:59:59.872435: train_loss -0.7812 +2024-11-22 09:59:59.872642: val_loss -0.7968 +2024-11-22 09:59:59.872716: Pseudo dice [0.862] +2024-11-22 09:59:59.872818: Epoch time: 18.67 s +2024-11-22 10:00:00.706719: +2024-11-22 10:00:00.706935: Epoch 4194 +2024-11-22 10:00:00.707042: Current learning rate: 0.00512 +2024-11-22 10:00:18.753088: train_loss -0.7859 +2024-11-22 10:00:18.753303: val_loss -0.7788 +2024-11-22 10:00:18.753380: Pseudo dice [0.857] +2024-11-22 10:00:18.753455: Epoch time: 18.05 s +2024-11-22 10:00:19.586839: +2024-11-22 10:00:19.587037: Epoch 4195 +2024-11-22 10:00:19.587148: Current learning rate: 0.00512 +2024-11-22 10:00:38.205791: train_loss -0.7803 +2024-11-22 10:00:38.206010: val_loss -0.7627 +2024-11-22 10:00:38.206095: Pseudo dice [0.8532] +2024-11-22 10:00:38.206177: Epoch time: 18.62 s +2024-11-22 10:00:39.043655: +2024-11-22 10:00:39.043906: Epoch 4196 +2024-11-22 10:00:39.044054: Current learning rate: 0.00512 +2024-11-22 10:00:56.952924: train_loss -0.777 +2024-11-22 10:00:56.953132: val_loss -0.7576 +2024-11-22 10:00:56.953207: Pseudo dice [0.8723] +2024-11-22 10:00:56.953284: Epoch time: 17.91 s +2024-11-22 10:00:57.791296: +2024-11-22 10:00:57.791504: Epoch 4197 +2024-11-22 10:00:57.791620: Current learning rate: 0.00512 +2024-11-22 10:01:16.549312: train_loss -0.7798 +2024-11-22 10:01:16.549615: val_loss -0.7796 +2024-11-22 10:01:16.549723: Pseudo dice [0.8625] +2024-11-22 10:01:16.549798: Epoch time: 18.76 s +2024-11-22 10:01:16.549858: Yayy! New best EMA pseudo Dice: 0.8576 +2024-11-22 10:01:17.648874: +2024-11-22 10:01:17.649091: Epoch 4198 +2024-11-22 10:01:17.649201: Current learning rate: 0.00512 +2024-11-22 10:01:35.960324: train_loss -0.7736 +2024-11-22 10:01:35.960528: val_loss -0.7514 +2024-11-22 10:01:35.960600: Pseudo dice [0.858] +2024-11-22 10:01:35.960673: Epoch time: 18.31 s +2024-11-22 10:01:35.960733: Yayy! New best EMA pseudo Dice: 0.8576 +2024-11-22 10:01:37.072535: +2024-11-22 10:01:37.072772: Epoch 4199 +2024-11-22 10:01:37.072882: Current learning rate: 0.00512 +2024-11-22 10:01:54.762768: train_loss -0.7886 +2024-11-22 10:01:54.763002: val_loss -0.7746 +2024-11-22 10:01:54.763083: Pseudo dice [0.8432] +2024-11-22 10:01:54.763159: Epoch time: 17.69 s +2024-11-22 10:01:55.869159: +2024-11-22 10:01:55.869400: Epoch 4200 +2024-11-22 10:01:55.869523: Current learning rate: 0.00512 +2024-11-22 10:02:14.450867: train_loss -0.773 +2024-11-22 10:02:14.451147: val_loss -0.7689 +2024-11-22 10:02:14.451224: Pseudo dice [0.8615] +2024-11-22 10:02:14.451302: Epoch time: 18.58 s +2024-11-22 10:02:15.437318: +2024-11-22 10:02:15.437541: Epoch 4201 +2024-11-22 10:02:15.437653: Current learning rate: 0.00512 +2024-11-22 10:02:34.648734: train_loss -0.7807 +2024-11-22 10:02:34.648963: val_loss -0.7655 +2024-11-22 10:02:34.649042: Pseudo dice [0.8501] +2024-11-22 10:02:34.649131: Epoch time: 19.21 s +2024-11-22 10:02:35.528102: +2024-11-22 10:02:35.528342: Epoch 4202 +2024-11-22 10:02:35.528452: Current learning rate: 0.00511 +2024-11-22 10:02:54.055826: train_loss -0.7891 +2024-11-22 10:02:54.056101: val_loss -0.7987 +2024-11-22 10:02:54.056179: Pseudo dice [0.8621] +2024-11-22 10:02:54.056255: Epoch time: 18.53 s +2024-11-22 10:02:54.893729: +2024-11-22 10:02:54.893943: Epoch 4203 +2024-11-22 10:02:54.894056: Current learning rate: 0.00511 +2024-11-22 10:03:12.974989: train_loss -0.7867 +2024-11-22 10:03:12.975241: val_loss -0.7715 +2024-11-22 10:03:12.975322: Pseudo dice [0.8481] +2024-11-22 10:03:12.975406: Epoch time: 18.08 s +2024-11-22 10:03:13.884664: +2024-11-22 10:03:13.884884: Epoch 4204 +2024-11-22 10:03:13.884995: Current learning rate: 0.00511 +2024-11-22 10:03:32.295610: train_loss -0.7824 +2024-11-22 10:03:32.295811: val_loss -0.7609 +2024-11-22 10:03:32.295886: Pseudo dice [0.8435] +2024-11-22 10:03:32.295958: Epoch time: 18.41 s +2024-11-22 10:03:33.165785: +2024-11-22 10:03:33.165979: Epoch 4205 +2024-11-22 10:03:33.166094: Current learning rate: 0.00511 +2024-11-22 10:03:51.326480: train_loss -0.7928 +2024-11-22 10:03:51.326697: val_loss -0.7947 +2024-11-22 10:03:51.326769: Pseudo dice [0.8515] +2024-11-22 10:03:51.326848: Epoch time: 18.16 s +2024-11-22 10:03:52.159426: +2024-11-22 10:03:52.159642: Epoch 4206 +2024-11-22 10:03:52.159751: Current learning rate: 0.00511 +2024-11-22 10:04:10.560051: train_loss -0.7829 +2024-11-22 10:04:10.560323: val_loss -0.7875 +2024-11-22 10:04:10.560399: Pseudo dice [0.8564] +2024-11-22 10:04:10.560475: Epoch time: 18.4 s +2024-11-22 10:04:11.410933: +2024-11-22 10:04:11.411155: Epoch 4207 +2024-11-22 10:04:11.411263: Current learning rate: 0.00511 +2024-11-22 10:04:29.730900: train_loss -0.7871 +2024-11-22 10:04:29.731155: val_loss -0.7643 +2024-11-22 10:04:29.745136: Pseudo dice [0.8554] +2024-11-22 10:04:29.745346: Epoch time: 18.32 s +2024-11-22 10:04:30.590769: +2024-11-22 10:04:30.590985: Epoch 4208 +2024-11-22 10:04:30.591098: Current learning rate: 0.00511 +2024-11-22 10:04:50.029318: train_loss -0.7872 +2024-11-22 10:04:50.029560: val_loss -0.7483 +2024-11-22 10:04:50.029638: Pseudo dice [0.8366] +2024-11-22 10:04:50.029713: Epoch time: 19.44 s +2024-11-22 10:04:51.170621: +2024-11-22 10:04:51.170845: Epoch 4209 +2024-11-22 10:04:51.170953: Current learning rate: 0.00511 +2024-11-22 10:05:09.454293: train_loss -0.7763 +2024-11-22 10:05:09.454509: val_loss -0.7755 +2024-11-22 10:05:09.454584: Pseudo dice [0.8461] +2024-11-22 10:05:09.454658: Epoch time: 18.28 s +2024-11-22 10:05:10.403542: +2024-11-22 10:05:10.403734: Epoch 4210 +2024-11-22 10:05:10.403839: Current learning rate: 0.0051 +2024-11-22 10:05:30.166176: train_loss -0.7775 +2024-11-22 10:05:30.166402: val_loss -0.7561 +2024-11-22 10:05:30.166480: Pseudo dice [0.8344] +2024-11-22 10:05:30.166558: Epoch time: 19.76 s +2024-11-22 10:05:30.981435: +2024-11-22 10:05:30.981651: Epoch 4211 +2024-11-22 10:05:30.981761: Current learning rate: 0.0051 +2024-11-22 10:05:50.280256: train_loss -0.7776 +2024-11-22 10:05:50.280488: val_loss -0.7811 +2024-11-22 10:05:50.280564: Pseudo dice [0.8384] +2024-11-22 10:05:50.280644: Epoch time: 19.3 s +2024-11-22 10:05:51.114864: +2024-11-22 10:05:51.115103: Epoch 4212 +2024-11-22 10:05:51.115216: Current learning rate: 0.0051 +2024-11-22 10:06:10.226011: train_loss -0.7803 +2024-11-22 10:06:10.226246: val_loss -0.7706 +2024-11-22 10:06:10.226396: Pseudo dice [0.85] +2024-11-22 10:06:10.226476: Epoch time: 19.11 s +2024-11-22 10:06:11.072332: +2024-11-22 10:06:11.072528: Epoch 4213 +2024-11-22 10:06:11.072638: Current learning rate: 0.0051 +2024-11-22 10:06:29.469601: train_loss -0.7768 +2024-11-22 10:06:29.469815: val_loss -0.7847 +2024-11-22 10:06:29.469893: Pseudo dice [0.8531] +2024-11-22 10:06:29.469968: Epoch time: 18.4 s +2024-11-22 10:06:30.505035: +2024-11-22 10:06:30.505263: Epoch 4214 +2024-11-22 10:06:30.505373: Current learning rate: 0.0051 +2024-11-22 10:06:48.183275: train_loss -0.7754 +2024-11-22 10:06:48.183484: val_loss -0.7633 +2024-11-22 10:06:48.183562: Pseudo dice [0.8444] +2024-11-22 10:06:48.183638: Epoch time: 17.68 s +2024-11-22 10:06:49.035331: +2024-11-22 10:06:49.035548: Epoch 4215 +2024-11-22 10:06:49.035659: Current learning rate: 0.0051 +2024-11-22 10:07:07.323534: train_loss -0.7706 +2024-11-22 10:07:07.323776: val_loss -0.7842 +2024-11-22 10:07:07.323852: Pseudo dice [0.8548] +2024-11-22 10:07:07.323935: Epoch time: 18.29 s +2024-11-22 10:07:08.352343: +2024-11-22 10:07:08.352548: Epoch 4216 +2024-11-22 10:07:08.352660: Current learning rate: 0.0051 +2024-11-22 10:07:26.510973: train_loss -0.7696 +2024-11-22 10:07:26.511231: val_loss -0.7784 +2024-11-22 10:07:26.511311: Pseudo dice [0.8612] +2024-11-22 10:07:26.511393: Epoch time: 18.16 s +2024-11-22 10:07:27.460069: +2024-11-22 10:07:27.460288: Epoch 4217 +2024-11-22 10:07:27.460399: Current learning rate: 0.0051 +2024-11-22 10:07:45.554200: train_loss -0.7677 +2024-11-22 10:07:45.554407: val_loss -0.7747 +2024-11-22 10:07:45.554482: Pseudo dice [0.8389] +2024-11-22 10:07:45.554556: Epoch time: 18.09 s +2024-11-22 10:07:46.495062: +2024-11-22 10:07:46.495273: Epoch 4218 +2024-11-22 10:07:46.495387: Current learning rate: 0.0051 +2024-11-22 10:08:04.705593: train_loss -0.7835 +2024-11-22 10:08:04.710967: val_loss -0.765 +2024-11-22 10:08:04.711075: Pseudo dice [0.8575] +2024-11-22 10:08:04.711152: Epoch time: 18.21 s +2024-11-22 10:08:05.560825: +2024-11-22 10:08:05.561038: Epoch 4219 +2024-11-22 10:08:05.561153: Current learning rate: 0.00509 +2024-11-22 10:08:24.078496: train_loss -0.7764 +2024-11-22 10:08:24.078726: val_loss -0.7495 +2024-11-22 10:08:24.078804: Pseudo dice [0.8399] +2024-11-22 10:08:24.078886: Epoch time: 18.52 s +2024-11-22 10:08:24.903775: +2024-11-22 10:08:24.903969: Epoch 4220 +2024-11-22 10:08:24.904083: Current learning rate: 0.00509 +2024-11-22 10:08:42.923983: train_loss -0.7846 +2024-11-22 10:08:42.924187: val_loss -0.7755 +2024-11-22 10:08:42.924262: Pseudo dice [0.8539] +2024-11-22 10:08:42.924335: Epoch time: 18.02 s +2024-11-22 10:08:43.993766: +2024-11-22 10:08:43.993979: Epoch 4221 +2024-11-22 10:08:43.994090: Current learning rate: 0.00509 +2024-11-22 10:09:02.211235: train_loss -0.7853 +2024-11-22 10:09:02.211447: val_loss -0.7562 +2024-11-22 10:09:02.211524: Pseudo dice [0.8518] +2024-11-22 10:09:02.211608: Epoch time: 18.22 s +2024-11-22 10:09:03.043325: +2024-11-22 10:09:03.043539: Epoch 4222 +2024-11-22 10:09:03.043644: Current learning rate: 0.00509 +2024-11-22 10:09:22.441050: train_loss -0.7909 +2024-11-22 10:09:22.441258: val_loss -0.7609 +2024-11-22 10:09:22.441334: Pseudo dice [0.8502] +2024-11-22 10:09:22.441411: Epoch time: 19.4 s +2024-11-22 10:09:23.270591: +2024-11-22 10:09:23.270817: Epoch 4223 +2024-11-22 10:09:23.270928: Current learning rate: 0.00509 +2024-11-22 10:09:42.503652: train_loss -0.7826 +2024-11-22 10:09:42.503887: val_loss -0.7545 +2024-11-22 10:09:42.503961: Pseudo dice [0.8514] +2024-11-22 10:09:42.504040: Epoch time: 19.23 s +2024-11-22 10:09:43.339520: +2024-11-22 10:09:43.339732: Epoch 4224 +2024-11-22 10:09:43.339854: Current learning rate: 0.00509 +2024-11-22 10:10:03.344685: train_loss -0.7821 +2024-11-22 10:10:03.344893: val_loss -0.7751 +2024-11-22 10:10:03.344971: Pseudo dice [0.856] +2024-11-22 10:10:03.345046: Epoch time: 20.01 s +2024-11-22 10:10:04.179550: +2024-11-22 10:10:04.179752: Epoch 4225 +2024-11-22 10:10:04.179865: Current learning rate: 0.00509 +2024-11-22 10:10:22.192683: train_loss -0.7807 +2024-11-22 10:10:22.192905: val_loss -0.7726 +2024-11-22 10:10:22.192983: Pseudo dice [0.8577] +2024-11-22 10:10:22.193057: Epoch time: 18.01 s +2024-11-22 10:10:23.028819: +2024-11-22 10:10:23.029028: Epoch 4226 +2024-11-22 10:10:23.029149: Current learning rate: 0.00509 +2024-11-22 10:10:42.142657: train_loss -0.7731 +2024-11-22 10:10:42.142866: val_loss -0.7648 +2024-11-22 10:10:42.142942: Pseudo dice [0.8355] +2024-11-22 10:10:42.143014: Epoch time: 19.11 s +2024-11-22 10:10:42.976812: +2024-11-22 10:10:42.977076: Epoch 4227 +2024-11-22 10:10:42.977190: Current learning rate: 0.00508 +2024-11-22 10:11:01.559803: train_loss -0.7834 +2024-11-22 10:11:01.560043: val_loss -0.7661 +2024-11-22 10:11:01.560127: Pseudo dice [0.8441] +2024-11-22 10:11:01.560215: Epoch time: 18.58 s +2024-11-22 10:11:02.389818: +2024-11-22 10:11:02.390023: Epoch 4228 +2024-11-22 10:11:02.390141: Current learning rate: 0.00508 +2024-11-22 10:11:20.902082: train_loss -0.7712 +2024-11-22 10:11:20.902293: val_loss -0.738 +2024-11-22 10:11:20.902368: Pseudo dice [0.8459] +2024-11-22 10:11:20.902445: Epoch time: 18.51 s +2024-11-22 10:11:21.731329: +2024-11-22 10:11:21.731535: Epoch 4229 +2024-11-22 10:11:21.731648: Current learning rate: 0.00508 +2024-11-22 10:11:40.177002: train_loss -0.7662 +2024-11-22 10:11:40.177216: val_loss -0.7783 +2024-11-22 10:11:40.177288: Pseudo dice [0.8337] +2024-11-22 10:11:40.177361: Epoch time: 18.45 s +2024-11-22 10:11:41.009407: +2024-11-22 10:11:41.009616: Epoch 4230 +2024-11-22 10:11:41.009732: Current learning rate: 0.00508 +2024-11-22 10:11:59.642519: train_loss -0.781 +2024-11-22 10:11:59.642798: val_loss -0.7686 +2024-11-22 10:11:59.642879: Pseudo dice [0.8389] +2024-11-22 10:11:59.643150: Epoch time: 18.63 s +2024-11-22 10:12:00.471526: +2024-11-22 10:12:00.471725: Epoch 4231 +2024-11-22 10:12:00.471837: Current learning rate: 0.00508 +2024-11-22 10:12:19.569576: train_loss -0.7848 +2024-11-22 10:12:19.569817: val_loss -0.7804 +2024-11-22 10:12:19.569895: Pseudo dice [0.8466] +2024-11-22 10:12:19.569977: Epoch time: 19.1 s +2024-11-22 10:12:20.401938: +2024-11-22 10:12:20.402158: Epoch 4232 +2024-11-22 10:12:20.402268: Current learning rate: 0.00508 +2024-11-22 10:12:38.006129: train_loss -0.7861 +2024-11-22 10:12:38.006353: val_loss -0.7586 +2024-11-22 10:12:38.006430: Pseudo dice [0.8463] +2024-11-22 10:12:38.006509: Epoch time: 17.6 s +2024-11-22 10:12:39.239949: +2024-11-22 10:12:39.240183: Epoch 4233 +2024-11-22 10:12:39.240299: Current learning rate: 0.00508 +2024-11-22 10:12:58.367629: train_loss -0.7909 +2024-11-22 10:12:58.367856: val_loss -0.7659 +2024-11-22 10:12:58.367936: Pseudo dice [0.8427] +2024-11-22 10:12:58.368012: Epoch time: 19.13 s +2024-11-22 10:12:59.200697: +2024-11-22 10:12:59.200926: Epoch 4234 +2024-11-22 10:12:59.201036: Current learning rate: 0.00508 +2024-11-22 10:13:18.775027: train_loss -0.7908 +2024-11-22 10:13:18.776539: val_loss -0.7826 +2024-11-22 10:13:18.776642: Pseudo dice [0.8522] +2024-11-22 10:13:18.776735: Epoch time: 19.58 s +2024-11-22 10:13:19.626587: +2024-11-22 10:13:19.626808: Epoch 4235 +2024-11-22 10:13:19.626924: Current learning rate: 0.00507 +2024-11-22 10:13:37.899025: train_loss -0.7884 +2024-11-22 10:13:37.899254: val_loss -0.7746 +2024-11-22 10:13:37.899333: Pseudo dice [0.8577] +2024-11-22 10:13:37.899408: Epoch time: 18.27 s +2024-11-22 10:13:38.733253: +2024-11-22 10:13:38.734659: Epoch 4236 +2024-11-22 10:13:38.734777: Current learning rate: 0.00507 +2024-11-22 10:13:57.261124: train_loss -0.7886 +2024-11-22 10:13:57.261329: val_loss -0.7661 +2024-11-22 10:13:57.261401: Pseudo dice [0.8542] +2024-11-22 10:13:57.261479: Epoch time: 18.53 s +2024-11-22 10:13:58.096356: +2024-11-22 10:13:58.096580: Epoch 4237 +2024-11-22 10:13:58.096687: Current learning rate: 0.00507 +2024-11-22 10:14:16.340792: train_loss -0.7786 +2024-11-22 10:14:16.340999: val_loss -0.7731 +2024-11-22 10:14:16.341082: Pseudo dice [0.8446] +2024-11-22 10:14:16.341160: Epoch time: 18.25 s +2024-11-22 10:14:17.177895: +2024-11-22 10:14:17.178123: Epoch 4238 +2024-11-22 10:14:17.178234: Current learning rate: 0.00507 +2024-11-22 10:14:35.200085: train_loss -0.7957 +2024-11-22 10:14:35.202508: val_loss -0.7726 +2024-11-22 10:14:35.202603: Pseudo dice [0.8567] +2024-11-22 10:14:35.202686: Epoch time: 18.02 s +2024-11-22 10:14:36.061330: +2024-11-22 10:14:36.061509: Epoch 4239 +2024-11-22 10:14:36.061666: Current learning rate: 0.00507 +2024-11-22 10:14:55.427011: train_loss -0.7696 +2024-11-22 10:14:55.427304: val_loss -0.7424 +2024-11-22 10:14:55.427392: Pseudo dice [0.8443] +2024-11-22 10:14:55.427472: Epoch time: 19.37 s +2024-11-22 10:14:56.261848: +2024-11-22 10:14:56.262045: Epoch 4240 +2024-11-22 10:14:56.262161: Current learning rate: 0.00507 +2024-11-22 10:15:14.466216: train_loss -0.7706 +2024-11-22 10:15:14.466429: val_loss -0.769 +2024-11-22 10:15:14.466503: Pseudo dice [0.8487] +2024-11-22 10:15:14.466577: Epoch time: 18.21 s +2024-11-22 10:15:15.300203: +2024-11-22 10:15:15.300428: Epoch 4241 +2024-11-22 10:15:15.300539: Current learning rate: 0.00507 +2024-11-22 10:15:33.618991: train_loss -0.7855 +2024-11-22 10:15:33.619206: val_loss -0.7834 +2024-11-22 10:15:33.619279: Pseudo dice [0.8563] +2024-11-22 10:15:33.619352: Epoch time: 18.32 s +2024-11-22 10:15:34.459180: +2024-11-22 10:15:34.459382: Epoch 4242 +2024-11-22 10:15:34.459496: Current learning rate: 0.00507 +2024-11-22 10:15:53.736142: train_loss -0.7796 +2024-11-22 10:15:53.736358: val_loss -0.783 +2024-11-22 10:15:53.736439: Pseudo dice [0.8555] +2024-11-22 10:15:53.736516: Epoch time: 19.28 s +2024-11-22 10:15:54.593653: +2024-11-22 10:15:54.593843: Epoch 4243 +2024-11-22 10:15:54.593957: Current learning rate: 0.00506 +2024-11-22 10:16:13.192954: train_loss -0.7844 +2024-11-22 10:16:13.193196: val_loss -0.7577 +2024-11-22 10:16:13.193277: Pseudo dice [0.8529] +2024-11-22 10:16:13.193359: Epoch time: 18.6 s +2024-11-22 10:16:14.029849: +2024-11-22 10:16:14.030057: Epoch 4244 +2024-11-22 10:16:14.030177: Current learning rate: 0.00506 +2024-11-22 10:16:33.193812: train_loss -0.7894 +2024-11-22 10:16:33.194079: val_loss -0.7495 +2024-11-22 10:16:33.194155: Pseudo dice [0.8576] +2024-11-22 10:16:33.194228: Epoch time: 19.16 s +2024-11-22 10:16:34.425985: +2024-11-22 10:16:34.426213: Epoch 4245 +2024-11-22 10:16:34.426324: Current learning rate: 0.00506 +2024-11-22 10:16:52.172258: train_loss -0.7867 +2024-11-22 10:16:52.177651: val_loss -0.7718 +2024-11-22 10:16:52.177846: Pseudo dice [0.8496] +2024-11-22 10:16:52.177929: Epoch time: 17.75 s +2024-11-22 10:16:53.062607: +2024-11-22 10:16:53.062828: Epoch 4246 +2024-11-22 10:16:53.062942: Current learning rate: 0.00506 +2024-11-22 10:17:11.842309: train_loss -0.7806 +2024-11-22 10:17:11.842551: val_loss -0.7731 +2024-11-22 10:17:11.842631: Pseudo dice [0.8602] +2024-11-22 10:17:11.842971: Epoch time: 18.78 s +2024-11-22 10:17:12.676846: +2024-11-22 10:17:12.677070: Epoch 4247 +2024-11-22 10:17:12.677181: Current learning rate: 0.00506 +2024-11-22 10:17:31.170870: train_loss -0.7894 +2024-11-22 10:17:31.171087: val_loss -0.7875 +2024-11-22 10:17:31.171184: Pseudo dice [0.8549] +2024-11-22 10:17:31.171262: Epoch time: 18.49 s +2024-11-22 10:17:32.045569: +2024-11-22 10:17:32.045804: Epoch 4248 +2024-11-22 10:17:32.045916: Current learning rate: 0.00506 +2024-11-22 10:17:51.417142: train_loss -0.7873 +2024-11-22 10:17:51.419540: val_loss -0.7562 +2024-11-22 10:17:51.419668: Pseudo dice [0.8537] +2024-11-22 10:17:51.419747: Epoch time: 19.37 s +2024-11-22 10:17:52.355364: +2024-11-22 10:17:52.355562: Epoch 4249 +2024-11-22 10:17:52.355670: Current learning rate: 0.00506 +2024-11-22 10:18:09.722822: train_loss -0.7914 +2024-11-22 10:18:09.723090: val_loss -0.7431 +2024-11-22 10:18:09.723167: Pseudo dice [0.8411] +2024-11-22 10:18:09.723241: Epoch time: 17.37 s +2024-11-22 10:18:10.832444: +2024-11-22 10:18:10.832646: Epoch 4250 +2024-11-22 10:18:10.832758: Current learning rate: 0.00506 +2024-11-22 10:18:30.385397: train_loss -0.7905 +2024-11-22 10:18:30.385618: val_loss -0.7753 +2024-11-22 10:18:30.385695: Pseudo dice [0.8464] +2024-11-22 10:18:30.385774: Epoch time: 19.55 s +2024-11-22 10:18:31.281443: +2024-11-22 10:18:31.281659: Epoch 4251 +2024-11-22 10:18:31.281773: Current learning rate: 0.00506 +2024-11-22 10:18:50.537057: train_loss -0.7853 +2024-11-22 10:18:50.537319: val_loss -0.7485 +2024-11-22 10:18:50.537397: Pseudo dice [0.8551] +2024-11-22 10:18:50.539910: Epoch time: 19.26 s +2024-11-22 10:18:51.604094: +2024-11-22 10:18:51.604301: Epoch 4252 +2024-11-22 10:18:51.604412: Current learning rate: 0.00505 +2024-11-22 10:19:09.271325: train_loss -0.7894 +2024-11-22 10:19:09.271542: val_loss -0.7556 +2024-11-22 10:19:09.271634: Pseudo dice [0.8497] +2024-11-22 10:19:09.271710: Epoch time: 17.67 s +2024-11-22 10:19:10.103723: +2024-11-22 10:19:10.103930: Epoch 4253 +2024-11-22 10:19:10.104046: Current learning rate: 0.00505 +2024-11-22 10:19:28.664048: train_loss -0.7828 +2024-11-22 10:19:28.664260: val_loss -0.7498 +2024-11-22 10:19:28.664334: Pseudo dice [0.8396] +2024-11-22 10:19:28.664407: Epoch time: 18.56 s +2024-11-22 10:19:29.490551: +2024-11-22 10:19:29.490769: Epoch 4254 +2024-11-22 10:19:29.490885: Current learning rate: 0.00505 +2024-11-22 10:19:48.838496: train_loss -0.775 +2024-11-22 10:19:48.838715: val_loss -0.782 +2024-11-22 10:19:48.838794: Pseudo dice [0.8493] +2024-11-22 10:19:48.838874: Epoch time: 19.35 s +2024-11-22 10:19:49.672834: +2024-11-22 10:19:49.673048: Epoch 4255 +2024-11-22 10:19:49.673166: Current learning rate: 0.00505 +2024-11-22 10:20:07.321812: train_loss -0.7812 +2024-11-22 10:20:07.322048: val_loss -0.7455 +2024-11-22 10:20:07.322144: Pseudo dice [0.8508] +2024-11-22 10:20:07.322278: Epoch time: 17.65 s +2024-11-22 10:20:08.285628: +2024-11-22 10:20:08.286050: Epoch 4256 +2024-11-22 10:20:08.286190: Current learning rate: 0.00505 +2024-11-22 10:20:26.521872: train_loss -0.7887 +2024-11-22 10:20:26.522098: val_loss -0.77 +2024-11-22 10:20:26.522175: Pseudo dice [0.8499] +2024-11-22 10:20:26.522453: Epoch time: 18.24 s +2024-11-22 10:20:27.762815: +2024-11-22 10:20:27.763046: Epoch 4257 +2024-11-22 10:20:27.763177: Current learning rate: 0.00505 +2024-11-22 10:20:46.136589: train_loss -0.7843 +2024-11-22 10:20:46.136808: val_loss -0.7705 +2024-11-22 10:20:46.136883: Pseudo dice [0.8735] +2024-11-22 10:20:46.136956: Epoch time: 18.37 s +2024-11-22 10:20:46.991224: +2024-11-22 10:20:46.991453: Epoch 4258 +2024-11-22 10:20:46.991561: Current learning rate: 0.00505 +2024-11-22 10:21:06.208133: train_loss -0.7781 +2024-11-22 10:21:06.208387: val_loss -0.7879 +2024-11-22 10:21:06.208464: Pseudo dice [0.8717] +2024-11-22 10:21:06.208545: Epoch time: 19.22 s +2024-11-22 10:21:07.041071: +2024-11-22 10:21:07.041302: Epoch 4259 +2024-11-22 10:21:07.041410: Current learning rate: 0.00505 +2024-11-22 10:21:25.569536: train_loss -0.7883 +2024-11-22 10:21:25.569774: val_loss -0.7675 +2024-11-22 10:21:25.569852: Pseudo dice [0.8467] +2024-11-22 10:21:25.569927: Epoch time: 18.53 s +2024-11-22 10:21:26.400539: +2024-11-22 10:21:26.400733: Epoch 4260 +2024-11-22 10:21:26.400842: Current learning rate: 0.00504 +2024-11-22 10:21:43.407577: train_loss -0.7898 +2024-11-22 10:21:43.407789: val_loss -0.784 +2024-11-22 10:21:43.413071: Pseudo dice [0.8579] +2024-11-22 10:21:43.413201: Epoch time: 17.01 s +2024-11-22 10:21:44.419507: +2024-11-22 10:21:44.419714: Epoch 4261 +2024-11-22 10:21:44.419824: Current learning rate: 0.00504 +2024-11-22 10:22:03.832542: train_loss -0.7797 +2024-11-22 10:22:03.832761: val_loss -0.7689 +2024-11-22 10:22:03.832839: Pseudo dice [0.8461] +2024-11-22 10:22:03.832916: Epoch time: 19.41 s +2024-11-22 10:22:04.737072: +2024-11-22 10:22:04.737256: Epoch 4262 +2024-11-22 10:22:04.737368: Current learning rate: 0.00504 +2024-11-22 10:22:22.561996: train_loss -0.7786 +2024-11-22 10:22:22.562233: val_loss -0.7622 +2024-11-22 10:22:22.562311: Pseudo dice [0.8573] +2024-11-22 10:22:22.562392: Epoch time: 17.83 s +2024-11-22 10:22:23.400125: +2024-11-22 10:22:23.400354: Epoch 4263 +2024-11-22 10:22:23.400474: Current learning rate: 0.00504 +2024-11-22 10:22:41.142132: train_loss -0.7728 +2024-11-22 10:22:41.142349: val_loss -0.7829 +2024-11-22 10:22:41.142427: Pseudo dice [0.8513] +2024-11-22 10:22:41.142502: Epoch time: 17.74 s +2024-11-22 10:22:41.979480: +2024-11-22 10:22:41.979667: Epoch 4264 +2024-11-22 10:22:41.979782: Current learning rate: 0.00504 +2024-11-22 10:23:01.310671: train_loss -0.7792 +2024-11-22 10:23:01.313075: val_loss -0.7766 +2024-11-22 10:23:01.313169: Pseudo dice [0.8451] +2024-11-22 10:23:01.313244: Epoch time: 19.33 s +2024-11-22 10:23:02.323325: +2024-11-22 10:23:02.323550: Epoch 4265 +2024-11-22 10:23:02.323663: Current learning rate: 0.00504 +2024-11-22 10:23:20.852756: train_loss -0.779 +2024-11-22 10:23:20.853013: val_loss -0.7593 +2024-11-22 10:23:20.853096: Pseudo dice [0.8457] +2024-11-22 10:23:20.853175: Epoch time: 18.53 s +2024-11-22 10:23:21.685981: +2024-11-22 10:23:21.686190: Epoch 4266 +2024-11-22 10:23:21.686302: Current learning rate: 0.00504 +2024-11-22 10:23:40.199777: train_loss -0.7848 +2024-11-22 10:23:40.200042: val_loss -0.7703 +2024-11-22 10:23:40.200193: Pseudo dice [0.8485] +2024-11-22 10:23:40.200286: Epoch time: 18.51 s +2024-11-22 10:23:41.033588: +2024-11-22 10:23:41.033827: Epoch 4267 +2024-11-22 10:23:41.033935: Current learning rate: 0.00504 +2024-11-22 10:23:59.957894: train_loss -0.7899 +2024-11-22 10:23:59.958118: val_loss -0.7789 +2024-11-22 10:23:59.958200: Pseudo dice [0.8479] +2024-11-22 10:23:59.958277: Epoch time: 18.93 s +2024-11-22 10:24:00.788471: +2024-11-22 10:24:00.788686: Epoch 4268 +2024-11-22 10:24:00.788797: Current learning rate: 0.00503 +2024-11-22 10:24:19.948217: train_loss -0.7781 +2024-11-22 10:24:19.948432: val_loss -0.7562 +2024-11-22 10:24:19.948509: Pseudo dice [0.8519] +2024-11-22 10:24:19.948584: Epoch time: 19.16 s +2024-11-22 10:24:21.175370: +2024-11-22 10:24:21.175579: Epoch 4269 +2024-11-22 10:24:21.175690: Current learning rate: 0.00503 +2024-11-22 10:24:40.592699: train_loss -0.7792 +2024-11-22 10:24:40.592923: val_loss -0.7716 +2024-11-22 10:24:40.593004: Pseudo dice [0.8497] +2024-11-22 10:24:40.593093: Epoch time: 19.42 s +2024-11-22 10:24:41.428701: +2024-11-22 10:24:41.428924: Epoch 4270 +2024-11-22 10:24:41.429035: Current learning rate: 0.00503 +2024-11-22 10:24:59.400373: train_loss -0.7763 +2024-11-22 10:24:59.400586: val_loss -0.7643 +2024-11-22 10:24:59.400660: Pseudo dice [0.8475] +2024-11-22 10:24:59.400745: Epoch time: 17.97 s +2024-11-22 10:25:00.238770: +2024-11-22 10:25:00.239004: Epoch 4271 +2024-11-22 10:25:00.239121: Current learning rate: 0.00503 +2024-11-22 10:25:18.665164: train_loss -0.7887 +2024-11-22 10:25:18.665432: val_loss -0.7431 +2024-11-22 10:25:18.665544: Pseudo dice [0.8701] +2024-11-22 10:25:18.665619: Epoch time: 18.43 s +2024-11-22 10:25:19.500238: +2024-11-22 10:25:19.500458: Epoch 4272 +2024-11-22 10:25:19.500574: Current learning rate: 0.00503 +2024-11-22 10:25:38.738809: train_loss -0.7875 +2024-11-22 10:25:38.739008: val_loss -0.7794 +2024-11-22 10:25:38.739088: Pseudo dice [0.8535] +2024-11-22 10:25:38.739161: Epoch time: 19.24 s +2024-11-22 10:25:39.574795: +2024-11-22 10:25:39.575019: Epoch 4273 +2024-11-22 10:25:39.575134: Current learning rate: 0.00503 +2024-11-22 10:25:58.402219: train_loss -0.7929 +2024-11-22 10:25:58.402468: val_loss -0.7821 +2024-11-22 10:25:58.402547: Pseudo dice [0.8466] +2024-11-22 10:25:58.402632: Epoch time: 18.83 s +2024-11-22 10:25:59.244178: +2024-11-22 10:25:59.244475: Epoch 4274 +2024-11-22 10:25:59.244596: Current learning rate: 0.00503 +2024-11-22 10:26:16.386111: train_loss -0.7952 +2024-11-22 10:26:16.386327: val_loss -0.7463 +2024-11-22 10:26:16.386405: Pseudo dice [0.8472] +2024-11-22 10:26:16.386488: Epoch time: 17.14 s +2024-11-22 10:26:17.268553: +2024-11-22 10:26:17.268767: Epoch 4275 +2024-11-22 10:26:17.268876: Current learning rate: 0.00503 +2024-11-22 10:26:35.344348: train_loss -0.7863 +2024-11-22 10:26:35.344565: val_loss -0.7765 +2024-11-22 10:26:35.344641: Pseudo dice [0.861] +2024-11-22 10:26:35.344716: Epoch time: 18.08 s +2024-11-22 10:26:36.182008: +2024-11-22 10:26:36.182206: Epoch 4276 +2024-11-22 10:26:36.182320: Current learning rate: 0.00502 +2024-11-22 10:26:55.504632: train_loss -0.791 +2024-11-22 10:26:55.506971: val_loss -0.7721 +2024-11-22 10:26:55.507098: Pseudo dice [0.8457] +2024-11-22 10:26:55.507175: Epoch time: 19.32 s +2024-11-22 10:26:56.384169: +2024-11-22 10:26:56.384382: Epoch 4277 +2024-11-22 10:26:56.384494: Current learning rate: 0.00502 +2024-11-22 10:27:15.341210: train_loss -0.7801 +2024-11-22 10:27:15.341453: val_loss -0.7616 +2024-11-22 10:27:15.341539: Pseudo dice [0.86] +2024-11-22 10:27:15.341621: Epoch time: 18.96 s +2024-11-22 10:27:16.174290: +2024-11-22 10:27:16.174483: Epoch 4278 +2024-11-22 10:27:16.174594: Current learning rate: 0.00502 +2024-11-22 10:27:35.222713: train_loss -0.7833 +2024-11-22 10:27:35.222925: val_loss -0.7662 +2024-11-22 10:27:35.223033: Pseudo dice [0.8488] +2024-11-22 10:27:35.223116: Epoch time: 19.05 s +2024-11-22 10:27:36.078726: +2024-11-22 10:27:36.078990: Epoch 4279 +2024-11-22 10:27:36.079107: Current learning rate: 0.00502 +2024-11-22 10:27:54.731270: train_loss -0.7823 +2024-11-22 10:27:54.731470: val_loss -0.7662 +2024-11-22 10:27:54.731546: Pseudo dice [0.8432] +2024-11-22 10:27:54.731620: Epoch time: 18.65 s +2024-11-22 10:27:55.576852: +2024-11-22 10:27:55.577084: Epoch 4280 +2024-11-22 10:27:55.577198: Current learning rate: 0.00502 +2024-11-22 10:28:14.112703: train_loss -0.7786 +2024-11-22 10:28:14.112920: val_loss -0.7482 +2024-11-22 10:28:14.112996: Pseudo dice [0.8468] +2024-11-22 10:28:14.113080: Epoch time: 18.54 s +2024-11-22 10:28:15.320002: +2024-11-22 10:28:15.320232: Epoch 4281 +2024-11-22 10:28:15.320349: Current learning rate: 0.00502 +2024-11-22 10:28:35.188262: train_loss -0.7896 +2024-11-22 10:28:35.188509: val_loss -0.7585 +2024-11-22 10:28:35.188588: Pseudo dice [0.8491] +2024-11-22 10:28:35.188670: Epoch time: 19.87 s +2024-11-22 10:28:36.027699: +2024-11-22 10:28:36.027949: Epoch 4282 +2024-11-22 10:28:36.028069: Current learning rate: 0.00502 +2024-11-22 10:28:55.067334: train_loss -0.7866 +2024-11-22 10:28:55.067547: val_loss -0.7596 +2024-11-22 10:28:55.067877: Pseudo dice [0.855] +2024-11-22 10:28:55.067960: Epoch time: 19.04 s +2024-11-22 10:28:55.902433: +2024-11-22 10:28:55.902682: Epoch 4283 +2024-11-22 10:28:55.902794: Current learning rate: 0.00502 +2024-11-22 10:29:15.029352: train_loss -0.7793 +2024-11-22 10:29:15.029566: val_loss -0.7745 +2024-11-22 10:29:15.029641: Pseudo dice [0.8535] +2024-11-22 10:29:15.029712: Epoch time: 19.13 s +2024-11-22 10:29:15.859464: +2024-11-22 10:29:15.859654: Epoch 4284 +2024-11-22 10:29:15.859768: Current learning rate: 0.00502 +2024-11-22 10:29:33.535392: train_loss -0.7931 +2024-11-22 10:29:33.535643: val_loss -0.7488 +2024-11-22 10:29:33.535720: Pseudo dice [0.8519] +2024-11-22 10:29:33.535796: Epoch time: 17.68 s +2024-11-22 10:29:34.378362: +2024-11-22 10:29:34.378590: Epoch 4285 +2024-11-22 10:29:34.378706: Current learning rate: 0.00501 +2024-11-22 10:29:52.064312: train_loss -0.797 +2024-11-22 10:29:52.064544: val_loss -0.7847 +2024-11-22 10:29:52.064619: Pseudo dice [0.8552] +2024-11-22 10:29:52.064707: Epoch time: 17.69 s +2024-11-22 10:29:52.898591: +2024-11-22 10:29:52.898820: Epoch 4286 +2024-11-22 10:29:52.898940: Current learning rate: 0.00501 +2024-11-22 10:30:12.574199: train_loss -0.7857 +2024-11-22 10:30:12.574408: val_loss -0.7871 +2024-11-22 10:30:12.574480: Pseudo dice [0.8562] +2024-11-22 10:30:12.574554: Epoch time: 19.68 s +2024-11-22 10:30:13.408494: +2024-11-22 10:30:13.408694: Epoch 4287 +2024-11-22 10:30:13.408805: Current learning rate: 0.00501 +2024-11-22 10:30:32.546541: train_loss -0.773 +2024-11-22 10:30:32.546774: val_loss -0.7575 +2024-11-22 10:30:32.546848: Pseudo dice [0.8568] +2024-11-22 10:30:32.546922: Epoch time: 19.14 s +2024-11-22 10:30:33.483511: +2024-11-22 10:30:33.483729: Epoch 4288 +2024-11-22 10:30:33.483845: Current learning rate: 0.00501 +2024-11-22 10:30:52.088685: train_loss -0.7778 +2024-11-22 10:30:52.088909: val_loss -0.7804 +2024-11-22 10:30:52.088985: Pseudo dice [0.8498] +2024-11-22 10:30:52.089071: Epoch time: 18.61 s +2024-11-22 10:30:52.941975: +2024-11-22 10:30:52.942187: Epoch 4289 +2024-11-22 10:30:52.942299: Current learning rate: 0.00501 +2024-11-22 10:31:11.861470: train_loss -0.7836 +2024-11-22 10:31:11.861695: val_loss -0.7815 +2024-11-22 10:31:11.861769: Pseudo dice [0.8444] +2024-11-22 10:31:11.861851: Epoch time: 18.92 s +2024-11-22 10:31:12.844663: +2024-11-22 10:31:12.844887: Epoch 4290 +2024-11-22 10:31:12.844998: Current learning rate: 0.00501 +2024-11-22 10:31:30.911871: train_loss -0.7835 +2024-11-22 10:31:30.912101: val_loss -0.755 +2024-11-22 10:31:30.912174: Pseudo dice [0.8541] +2024-11-22 10:31:30.912249: Epoch time: 18.07 s +2024-11-22 10:31:31.746028: +2024-11-22 10:31:31.746236: Epoch 4291 +2024-11-22 10:31:31.746350: Current learning rate: 0.00501 +2024-11-22 10:31:50.670818: train_loss -0.7815 +2024-11-22 10:31:50.671027: val_loss -0.7803 +2024-11-22 10:31:50.671117: Pseudo dice [0.8475] +2024-11-22 10:31:50.671194: Epoch time: 18.93 s +2024-11-22 10:31:51.499003: +2024-11-22 10:31:51.499204: Epoch 4292 +2024-11-22 10:31:51.499316: Current learning rate: 0.00501 +2024-11-22 10:32:11.318038: train_loss -0.7849 +2024-11-22 10:32:11.318302: val_loss -0.7793 +2024-11-22 10:32:11.318389: Pseudo dice [0.8582] +2024-11-22 10:32:11.318476: Epoch time: 19.82 s +2024-11-22 10:32:12.527833: +2024-11-22 10:32:12.528046: Epoch 4293 +2024-11-22 10:32:12.528160: Current learning rate: 0.005 +2024-11-22 10:32:31.550261: train_loss -0.7881 +2024-11-22 10:32:31.550474: val_loss -0.7602 +2024-11-22 10:32:31.550550: Pseudo dice [0.8572] +2024-11-22 10:32:31.550634: Epoch time: 19.02 s +2024-11-22 10:32:32.365335: +2024-11-22 10:32:32.365538: Epoch 4294 +2024-11-22 10:32:32.365647: Current learning rate: 0.005 +2024-11-22 10:32:51.347063: train_loss -0.7817 +2024-11-22 10:32:51.347272: val_loss -0.7515 +2024-11-22 10:32:51.347349: Pseudo dice [0.8534] +2024-11-22 10:32:51.347428: Epoch time: 18.98 s +2024-11-22 10:32:52.182377: +2024-11-22 10:32:52.182618: Epoch 4295 +2024-11-22 10:32:52.182726: Current learning rate: 0.005 +2024-11-22 10:33:11.813192: train_loss -0.7759 +2024-11-22 10:33:11.813398: val_loss -0.7882 +2024-11-22 10:33:11.813475: Pseudo dice [0.8588] +2024-11-22 10:33:11.813550: Epoch time: 19.63 s +2024-11-22 10:33:12.630516: +2024-11-22 10:33:12.630728: Epoch 4296 +2024-11-22 10:33:12.630837: Current learning rate: 0.005 +2024-11-22 10:33:30.034434: train_loss -0.7797 +2024-11-22 10:33:30.034661: val_loss -0.7872 +2024-11-22 10:33:30.034739: Pseudo dice [0.8577] +2024-11-22 10:33:30.034822: Epoch time: 17.4 s +2024-11-22 10:33:30.875677: +2024-11-22 10:33:30.875856: Epoch 4297 +2024-11-22 10:33:30.875965: Current learning rate: 0.005 +2024-11-22 10:33:49.743624: train_loss -0.7714 +2024-11-22 10:33:49.743864: val_loss -0.7564 +2024-11-22 10:33:49.743941: Pseudo dice [0.836] +2024-11-22 10:33:49.744021: Epoch time: 18.87 s +2024-11-22 10:33:50.576472: +2024-11-22 10:33:50.576685: Epoch 4298 +2024-11-22 10:33:50.576798: Current learning rate: 0.005 +2024-11-22 10:34:09.464750: train_loss -0.7811 +2024-11-22 10:34:09.464959: val_loss -0.7865 +2024-11-22 10:34:09.465032: Pseudo dice [0.8499] +2024-11-22 10:34:09.465111: Epoch time: 18.89 s +2024-11-22 10:34:10.314140: +2024-11-22 10:34:10.314403: Epoch 4299 +2024-11-22 10:34:10.314525: Current learning rate: 0.005 +2024-11-22 10:34:28.479378: train_loss -0.7813 +2024-11-22 10:34:28.479584: val_loss -0.7626 +2024-11-22 10:34:28.479660: Pseudo dice [0.8536] +2024-11-22 10:34:28.479733: Epoch time: 18.17 s +2024-11-22 10:34:29.570580: +2024-11-22 10:34:29.570800: Epoch 4300 +2024-11-22 10:34:29.570912: Current learning rate: 0.005 +2024-11-22 10:34:47.708206: train_loss -0.7921 +2024-11-22 10:34:47.708419: val_loss -0.7761 +2024-11-22 10:34:47.708494: Pseudo dice [0.851] +2024-11-22 10:34:47.708570: Epoch time: 18.14 s +2024-11-22 10:34:48.542681: +2024-11-22 10:34:48.542883: Epoch 4301 +2024-11-22 10:34:48.542998: Current learning rate: 0.00499 +2024-11-22 10:35:07.007142: train_loss -0.7867 +2024-11-22 10:35:07.007383: val_loss -0.7831 +2024-11-22 10:35:07.009614: Pseudo dice [0.8551] +2024-11-22 10:35:07.009723: Epoch time: 18.47 s +2024-11-22 10:35:08.007441: +2024-11-22 10:35:08.007662: Epoch 4302 +2024-11-22 10:35:08.007772: Current learning rate: 0.00499 +2024-11-22 10:35:27.510423: train_loss -0.7877 +2024-11-22 10:35:27.510630: val_loss -0.7575 +2024-11-22 10:35:27.510715: Pseudo dice [0.8562] +2024-11-22 10:35:27.510796: Epoch time: 19.5 s +2024-11-22 10:35:28.336802: +2024-11-22 10:35:28.337019: Epoch 4303 +2024-11-22 10:35:28.337139: Current learning rate: 0.00499 +2024-11-22 10:35:45.844750: train_loss -0.782 +2024-11-22 10:35:45.844967: val_loss -0.786 +2024-11-22 10:35:45.845083: Pseudo dice [0.8477] +2024-11-22 10:35:45.845162: Epoch time: 17.51 s +2024-11-22 10:35:46.674087: +2024-11-22 10:35:46.674301: Epoch 4304 +2024-11-22 10:35:46.674407: Current learning rate: 0.00499 +2024-11-22 10:36:05.006144: train_loss -0.7741 +2024-11-22 10:36:05.006360: val_loss -0.7462 +2024-11-22 10:36:05.006437: Pseudo dice [0.852] +2024-11-22 10:36:05.006514: Epoch time: 18.33 s +2024-11-22 10:36:06.261929: +2024-11-22 10:36:06.262148: Epoch 4305 +2024-11-22 10:36:06.262263: Current learning rate: 0.00499 +2024-11-22 10:36:24.455951: train_loss -0.7894 +2024-11-22 10:36:24.461389: val_loss -0.7746 +2024-11-22 10:36:24.461511: Pseudo dice [0.8638] +2024-11-22 10:36:24.461595: Epoch time: 18.19 s +2024-11-22 10:36:25.347109: +2024-11-22 10:36:25.347324: Epoch 4306 +2024-11-22 10:36:25.347433: Current learning rate: 0.00499 +2024-11-22 10:36:44.664656: train_loss -0.7849 +2024-11-22 10:36:44.664877: val_loss -0.785 +2024-11-22 10:36:44.664954: Pseudo dice [0.855] +2024-11-22 10:36:44.665029: Epoch time: 19.32 s +2024-11-22 10:36:45.494120: +2024-11-22 10:36:45.494360: Epoch 4307 +2024-11-22 10:36:45.494480: Current learning rate: 0.00499 +2024-11-22 10:37:02.932915: train_loss -0.7953 +2024-11-22 10:37:02.933138: val_loss -0.781 +2024-11-22 10:37:02.933225: Pseudo dice [0.8654] +2024-11-22 10:37:02.933305: Epoch time: 17.44 s +2024-11-22 10:37:03.798473: +2024-11-22 10:37:03.798697: Epoch 4308 +2024-11-22 10:37:03.798805: Current learning rate: 0.00499 +2024-11-22 10:37:22.358419: train_loss -0.7925 +2024-11-22 10:37:22.358639: val_loss -0.7758 +2024-11-22 10:37:22.359035: Pseudo dice [0.8579] +2024-11-22 10:37:22.359128: Epoch time: 18.56 s +2024-11-22 10:37:23.199889: +2024-11-22 10:37:23.200075: Epoch 4309 +2024-11-22 10:37:23.200184: Current learning rate: 0.00498 +2024-11-22 10:37:41.170571: train_loss -0.7863 +2024-11-22 10:37:41.170801: val_loss -0.7934 +2024-11-22 10:37:41.170877: Pseudo dice [0.868] +2024-11-22 10:37:41.170953: Epoch time: 17.97 s +2024-11-22 10:37:42.000784: +2024-11-22 10:37:42.001000: Epoch 4310 +2024-11-22 10:37:42.001121: Current learning rate: 0.00498 +2024-11-22 10:37:59.881899: train_loss -0.7957 +2024-11-22 10:37:59.882127: val_loss -0.7572 +2024-11-22 10:37:59.882208: Pseudo dice [0.8318] +2024-11-22 10:37:59.882285: Epoch time: 17.88 s +2024-11-22 10:38:00.715015: +2024-11-22 10:38:00.715247: Epoch 4311 +2024-11-22 10:38:00.715358: Current learning rate: 0.00498 +2024-11-22 10:38:20.272574: train_loss -0.7865 +2024-11-22 10:38:20.272809: val_loss -0.7769 +2024-11-22 10:38:20.272882: Pseudo dice [0.8503] +2024-11-22 10:38:20.272959: Epoch time: 19.56 s +2024-11-22 10:38:21.126775: +2024-11-22 10:38:21.127029: Epoch 4312 +2024-11-22 10:38:21.127147: Current learning rate: 0.00498 +2024-11-22 10:38:39.735664: train_loss -0.7846 +2024-11-22 10:38:39.735884: val_loss -0.765 +2024-11-22 10:38:39.735965: Pseudo dice [0.8555] +2024-11-22 10:38:39.736042: Epoch time: 18.61 s +2024-11-22 10:38:40.575884: +2024-11-22 10:38:40.576159: Epoch 4313 +2024-11-22 10:38:40.576270: Current learning rate: 0.00498 +2024-11-22 10:38:58.785501: train_loss -0.779 +2024-11-22 10:38:58.785731: val_loss -0.7702 +2024-11-22 10:38:58.785816: Pseudo dice [0.851] +2024-11-22 10:38:58.785897: Epoch time: 18.21 s +2024-11-22 10:38:59.612670: +2024-11-22 10:38:59.612873: Epoch 4314 +2024-11-22 10:38:59.612982: Current learning rate: 0.00498 +2024-11-22 10:39:18.830299: train_loss -0.7899 +2024-11-22 10:39:18.830504: val_loss -0.7767 +2024-11-22 10:39:18.830580: Pseudo dice [0.8531] +2024-11-22 10:39:18.830653: Epoch time: 19.22 s +2024-11-22 10:39:19.657662: +2024-11-22 10:39:19.657893: Epoch 4315 +2024-11-22 10:39:19.658012: Current learning rate: 0.00498 +2024-11-22 10:39:38.514250: train_loss -0.7793 +2024-11-22 10:39:38.514466: val_loss -0.7743 +2024-11-22 10:39:38.514540: Pseudo dice [0.8557] +2024-11-22 10:39:38.514615: Epoch time: 18.86 s +2024-11-22 10:39:39.351910: +2024-11-22 10:39:39.352124: Epoch 4316 +2024-11-22 10:39:39.352241: Current learning rate: 0.00498 +2024-11-22 10:39:58.756248: train_loss -0.7894 +2024-11-22 10:39:58.756487: val_loss -0.7764 +2024-11-22 10:39:58.756562: Pseudo dice [0.8384] +2024-11-22 10:39:58.756641: Epoch time: 19.41 s +2024-11-22 10:40:00.006979: +2024-11-22 10:40:00.007246: Epoch 4317 +2024-11-22 10:40:00.007354: Current learning rate: 0.00498 +2024-11-22 10:40:17.005580: train_loss -0.7776 +2024-11-22 10:40:17.005801: val_loss -0.7625 +2024-11-22 10:40:17.005879: Pseudo dice [0.8386] +2024-11-22 10:40:17.005955: Epoch time: 17.0 s +2024-11-22 10:40:17.836881: +2024-11-22 10:40:17.837159: Epoch 4318 +2024-11-22 10:40:17.837280: Current learning rate: 0.00497 +2024-11-22 10:40:35.945806: train_loss -0.7789 +2024-11-22 10:40:35.946013: val_loss -0.7858 +2024-11-22 10:40:35.946090: Pseudo dice [0.8625] +2024-11-22 10:40:35.946172: Epoch time: 18.11 s +2024-11-22 10:40:36.804878: +2024-11-22 10:40:36.805106: Epoch 4319 +2024-11-22 10:40:36.805217: Current learning rate: 0.00497 +2024-11-22 10:40:55.779193: train_loss -0.7722 +2024-11-22 10:40:55.779469: val_loss -0.7797 +2024-11-22 10:40:55.779549: Pseudo dice [0.8503] +2024-11-22 10:40:55.779624: Epoch time: 18.98 s +2024-11-22 10:40:56.716443: +2024-11-22 10:40:56.716646: Epoch 4320 +2024-11-22 10:40:56.716756: Current learning rate: 0.00497 +2024-11-22 10:41:14.831529: train_loss -0.7883 +2024-11-22 10:41:14.831770: val_loss -0.7638 +2024-11-22 10:41:14.831845: Pseudo dice [0.8578] +2024-11-22 10:41:14.831926: Epoch time: 18.12 s +2024-11-22 10:41:15.670971: +2024-11-22 10:41:15.671191: Epoch 4321 +2024-11-22 10:41:15.671304: Current learning rate: 0.00497 +2024-11-22 10:41:34.476029: train_loss -0.7811 +2024-11-22 10:41:34.476252: val_loss -0.7822 +2024-11-22 10:41:34.476332: Pseudo dice [0.8651] +2024-11-22 10:41:34.476409: Epoch time: 18.81 s +2024-11-22 10:41:35.314485: +2024-11-22 10:41:35.314677: Epoch 4322 +2024-11-22 10:41:35.314791: Current learning rate: 0.00497 +2024-11-22 10:41:54.395831: train_loss -0.7841 +2024-11-22 10:41:54.396049: val_loss -0.7799 +2024-11-22 10:41:54.396134: Pseudo dice [0.8515] +2024-11-22 10:41:54.396211: Epoch time: 19.08 s +2024-11-22 10:41:55.239338: +2024-11-22 10:41:55.239534: Epoch 4323 +2024-11-22 10:41:55.239646: Current learning rate: 0.00497 +2024-11-22 10:42:13.589987: train_loss -0.7888 +2024-11-22 10:42:13.595390: val_loss -0.7872 +2024-11-22 10:42:13.595583: Pseudo dice [0.8509] +2024-11-22 10:42:13.595667: Epoch time: 18.35 s +2024-11-22 10:42:14.518886: +2024-11-22 10:42:14.519104: Epoch 4324 +2024-11-22 10:42:14.519214: Current learning rate: 0.00497 +2024-11-22 10:42:33.128661: train_loss -0.7717 +2024-11-22 10:42:33.128908: val_loss -0.7668 +2024-11-22 10:42:33.128984: Pseudo dice [0.8423] +2024-11-22 10:42:33.129070: Epoch time: 18.61 s +2024-11-22 10:42:33.966895: +2024-11-22 10:42:33.967110: Epoch 4325 +2024-11-22 10:42:33.967226: Current learning rate: 0.00497 +2024-11-22 10:42:53.617813: train_loss -0.7844 +2024-11-22 10:42:53.618017: val_loss -0.7667 +2024-11-22 10:42:53.618098: Pseudo dice [0.8628] +2024-11-22 10:42:53.618174: Epoch time: 19.65 s +2024-11-22 10:42:54.621492: +2024-11-22 10:42:54.621697: Epoch 4326 +2024-11-22 10:42:54.621804: Current learning rate: 0.00496 +2024-11-22 10:43:12.930212: train_loss -0.786 +2024-11-22 10:43:12.930454: val_loss -0.773 +2024-11-22 10:43:12.930531: Pseudo dice [0.8603] +2024-11-22 10:43:12.930608: Epoch time: 18.31 s +2024-11-22 10:43:13.775726: +2024-11-22 10:43:13.775942: Epoch 4327 +2024-11-22 10:43:13.776052: Current learning rate: 0.00496 +2024-11-22 10:43:32.948738: train_loss -0.7877 +2024-11-22 10:43:32.948947: val_loss -0.7775 +2024-11-22 10:43:32.949021: Pseudo dice [0.8573] +2024-11-22 10:43:32.949101: Epoch time: 19.17 s +2024-11-22 10:43:33.776885: +2024-11-22 10:43:33.777088: Epoch 4328 +2024-11-22 10:43:33.777198: Current learning rate: 0.00496 +2024-11-22 10:43:52.566175: train_loss -0.7766 +2024-11-22 10:43:52.566427: val_loss -0.7634 +2024-11-22 10:43:52.566506: Pseudo dice [0.8565] +2024-11-22 10:43:52.566591: Epoch time: 18.79 s +2024-11-22 10:43:53.807052: +2024-11-22 10:43:53.807284: Epoch 4329 +2024-11-22 10:43:53.807400: Current learning rate: 0.00496 +2024-11-22 10:44:12.542586: train_loss -0.766 +2024-11-22 10:44:12.542802: val_loss -0.7799 +2024-11-22 10:44:12.542878: Pseudo dice [0.8417] +2024-11-22 10:44:12.542952: Epoch time: 18.74 s +2024-11-22 10:44:13.381721: +2024-11-22 10:44:13.381943: Epoch 4330 +2024-11-22 10:44:13.382052: Current learning rate: 0.00496 +2024-11-22 10:44:31.385513: train_loss -0.7736 +2024-11-22 10:44:31.385722: val_loss -0.7762 +2024-11-22 10:44:31.385796: Pseudo dice [0.8428] +2024-11-22 10:44:31.385870: Epoch time: 18.0 s +2024-11-22 10:44:32.217905: +2024-11-22 10:44:32.218132: Epoch 4331 +2024-11-22 10:44:32.218246: Current learning rate: 0.00496 +2024-11-22 10:44:50.601619: train_loss -0.7727 +2024-11-22 10:44:50.607044: val_loss -0.7682 +2024-11-22 10:44:50.607199: Pseudo dice [0.8484] +2024-11-22 10:44:50.607290: Epoch time: 18.38 s +2024-11-22 10:44:51.590215: +2024-11-22 10:44:51.590436: Epoch 4332 +2024-11-22 10:44:51.590549: Current learning rate: 0.00496 +2024-11-22 10:45:09.901112: train_loss -0.7757 +2024-11-22 10:45:09.907150: val_loss -0.7621 +2024-11-22 10:45:09.907319: Pseudo dice [0.8418] +2024-11-22 10:45:09.907403: Epoch time: 18.31 s +2024-11-22 10:45:11.043200: +2024-11-22 10:45:11.043410: Epoch 4333 +2024-11-22 10:45:11.043514: Current learning rate: 0.00496 +2024-11-22 10:45:29.710503: train_loss -0.7844 +2024-11-22 10:45:29.710708: val_loss -0.7688 +2024-11-22 10:45:29.710791: Pseudo dice [0.8586] +2024-11-22 10:45:29.710867: Epoch time: 18.67 s +2024-11-22 10:45:30.536389: +2024-11-22 10:45:30.536588: Epoch 4334 +2024-11-22 10:45:30.536690: Current learning rate: 0.00495 +2024-11-22 10:45:49.839037: train_loss -0.787 +2024-11-22 10:45:49.839246: val_loss -0.7817 +2024-11-22 10:45:49.839541: Pseudo dice [0.8469] +2024-11-22 10:45:49.839620: Epoch time: 19.3 s +2024-11-22 10:45:50.666251: +2024-11-22 10:45:50.666450: Epoch 4335 +2024-11-22 10:45:50.666559: Current learning rate: 0.00495 +2024-11-22 10:46:09.293952: train_loss -0.7885 +2024-11-22 10:46:09.294161: val_loss -0.7705 +2024-11-22 10:46:09.294237: Pseudo dice [0.8669] +2024-11-22 10:46:09.294314: Epoch time: 18.63 s +2024-11-22 10:46:10.118650: +2024-11-22 10:46:10.118830: Epoch 4336 +2024-11-22 10:46:10.118939: Current learning rate: 0.00495 +2024-11-22 10:46:29.882412: train_loss -0.7867 +2024-11-22 10:46:29.882649: val_loss -0.764 +2024-11-22 10:46:29.882725: Pseudo dice [0.8564] +2024-11-22 10:46:29.882804: Epoch time: 19.76 s +2024-11-22 10:46:30.712683: +2024-11-22 10:46:30.712890: Epoch 4337 +2024-11-22 10:46:30.713001: Current learning rate: 0.00495 +2024-11-22 10:46:48.787749: train_loss -0.7845 +2024-11-22 10:46:48.787951: val_loss -0.7751 +2024-11-22 10:46:48.788029: Pseudo dice [0.856] +2024-11-22 10:46:48.790290: Epoch time: 18.08 s +2024-11-22 10:46:49.610283: +2024-11-22 10:46:49.610477: Epoch 4338 +2024-11-22 10:46:49.610586: Current learning rate: 0.00495 +2024-11-22 10:47:07.096141: train_loss -0.7884 +2024-11-22 10:47:07.096352: val_loss -0.7593 +2024-11-22 10:47:07.096426: Pseudo dice [0.8435] +2024-11-22 10:47:07.096499: Epoch time: 17.49 s +2024-11-22 10:47:07.949310: +2024-11-22 10:47:07.949507: Epoch 4339 +2024-11-22 10:47:07.949620: Current learning rate: 0.00495 +2024-11-22 10:47:26.504214: train_loss -0.7899 +2024-11-22 10:47:26.504427: val_loss -0.7634 +2024-11-22 10:47:26.504505: Pseudo dice [0.8471] +2024-11-22 10:47:26.504580: Epoch time: 18.56 s +2024-11-22 10:47:27.382436: +2024-11-22 10:47:27.382663: Epoch 4340 +2024-11-22 10:47:27.382774: Current learning rate: 0.00495 +2024-11-22 10:47:45.634788: train_loss -0.7953 +2024-11-22 10:47:45.635007: val_loss -0.7861 +2024-11-22 10:47:45.635092: Pseudo dice [0.8565] +2024-11-22 10:47:45.635172: Epoch time: 18.25 s +2024-11-22 10:47:46.841697: +2024-11-22 10:47:46.842149: Epoch 4341 +2024-11-22 10:47:46.842279: Current learning rate: 0.00495 +2024-11-22 10:48:05.090670: train_loss -0.7957 +2024-11-22 10:48:05.090896: val_loss -0.7785 +2024-11-22 10:48:05.090971: Pseudo dice [0.8534] +2024-11-22 10:48:05.091046: Epoch time: 18.25 s +2024-11-22 10:48:05.924638: +2024-11-22 10:48:05.925069: Epoch 4342 +2024-11-22 10:48:05.925203: Current learning rate: 0.00494 +2024-11-22 10:48:23.865182: train_loss -0.7892 +2024-11-22 10:48:23.865396: val_loss -0.7983 +2024-11-22 10:48:23.865470: Pseudo dice [0.856] +2024-11-22 10:48:23.865545: Epoch time: 17.94 s +2024-11-22 10:48:24.696473: +2024-11-22 10:48:24.696893: Epoch 4343 +2024-11-22 10:48:24.697022: Current learning rate: 0.00494 +2024-11-22 10:48:44.126688: train_loss -0.7759 +2024-11-22 10:48:44.126968: val_loss -0.7534 +2024-11-22 10:48:44.127048: Pseudo dice [0.8375] +2024-11-22 10:48:44.127139: Epoch time: 19.43 s +2024-11-22 10:48:44.963064: +2024-11-22 10:48:44.963457: Epoch 4344 +2024-11-22 10:48:44.963585: Current learning rate: 0.00494 +2024-11-22 10:49:04.551403: train_loss -0.7738 +2024-11-22 10:49:04.551628: val_loss -0.7681 +2024-11-22 10:49:04.551705: Pseudo dice [0.8513] +2024-11-22 10:49:04.551781: Epoch time: 19.59 s +2024-11-22 10:49:05.402235: +2024-11-22 10:49:05.402657: Epoch 4345 +2024-11-22 10:49:05.402785: Current learning rate: 0.00494 +2024-11-22 10:49:23.479649: train_loss -0.7903 +2024-11-22 10:49:23.479858: val_loss -0.7694 +2024-11-22 10:49:23.479947: Pseudo dice [0.8437] +2024-11-22 10:49:23.480028: Epoch time: 18.08 s +2024-11-22 10:49:24.310929: +2024-11-22 10:49:24.311355: Epoch 4346 +2024-11-22 10:49:24.311481: Current learning rate: 0.00494 +2024-11-22 10:49:41.860684: train_loss -0.7922 +2024-11-22 10:49:41.860904: val_loss -0.784 +2024-11-22 10:49:41.860989: Pseudo dice [0.8549] +2024-11-22 10:49:41.861074: Epoch time: 17.55 s +2024-11-22 10:49:42.689786: +2024-11-22 10:49:42.690207: Epoch 4347 +2024-11-22 10:49:42.690339: Current learning rate: 0.00494 +2024-11-22 10:50:01.205777: train_loss -0.7949 +2024-11-22 10:50:01.206028: val_loss -0.7721 +2024-11-22 10:50:01.206106: Pseudo dice [0.8525] +2024-11-22 10:50:01.206190: Epoch time: 18.52 s +2024-11-22 10:50:02.039218: +2024-11-22 10:50:02.039669: Epoch 4348 +2024-11-22 10:50:02.039807: Current learning rate: 0.00494 +2024-11-22 10:50:19.658114: train_loss -0.789 +2024-11-22 10:50:19.658325: val_loss -0.7525 +2024-11-22 10:50:19.658404: Pseudo dice [0.8447] +2024-11-22 10:50:19.658478: Epoch time: 17.62 s +2024-11-22 10:50:20.593777: +2024-11-22 10:50:20.594222: Epoch 4349 +2024-11-22 10:50:20.594363: Current learning rate: 0.00494 +2024-11-22 10:50:40.396017: train_loss -0.7943 +2024-11-22 10:50:40.396238: val_loss -0.7955 +2024-11-22 10:50:40.396311: Pseudo dice [0.8565] +2024-11-22 10:50:40.396411: Epoch time: 19.8 s +2024-11-22 10:50:41.494553: +2024-11-22 10:50:41.494974: Epoch 4350 +2024-11-22 10:50:41.495111: Current learning rate: 0.00493 +2024-11-22 10:51:00.051583: train_loss -0.7953 +2024-11-22 10:51:00.051863: val_loss -0.7719 +2024-11-22 10:51:00.051940: Pseudo dice [0.8639] +2024-11-22 10:51:00.052018: Epoch time: 18.56 s +2024-11-22 10:51:00.941964: +2024-11-22 10:51:00.942383: Epoch 4351 +2024-11-22 10:51:00.942512: Current learning rate: 0.00493 +2024-11-22 10:51:19.941213: train_loss -0.7747 +2024-11-22 10:51:19.941495: val_loss -0.7572 +2024-11-22 10:51:19.941577: Pseudo dice [0.8362] +2024-11-22 10:51:19.941658: Epoch time: 19.0 s +2024-11-22 10:51:20.769725: +2024-11-22 10:51:20.769933: Epoch 4352 +2024-11-22 10:51:20.770044: Current learning rate: 0.00493 +2024-11-22 10:51:38.579940: train_loss -0.7963 +2024-11-22 10:51:38.580157: val_loss -0.7753 +2024-11-22 10:51:38.580236: Pseudo dice [0.8417] +2024-11-22 10:51:38.580313: Epoch time: 17.81 s +2024-11-22 10:51:39.800409: +2024-11-22 10:51:39.800666: Epoch 4353 +2024-11-22 10:51:39.800777: Current learning rate: 0.00493 +2024-11-22 10:51:57.958448: train_loss -0.7889 +2024-11-22 10:51:57.958663: val_loss -0.7465 +2024-11-22 10:51:57.958735: Pseudo dice [0.8621] +2024-11-22 10:51:57.958807: Epoch time: 18.16 s +2024-11-22 10:51:58.791355: +2024-11-22 10:51:58.791576: Epoch 4354 +2024-11-22 10:51:58.791687: Current learning rate: 0.00493 +2024-11-22 10:52:17.824337: train_loss -0.7966 +2024-11-22 10:52:17.824551: val_loss -0.7633 +2024-11-22 10:52:17.824624: Pseudo dice [0.8536] +2024-11-22 10:52:17.824697: Epoch time: 19.03 s +2024-11-22 10:52:18.663741: +2024-11-22 10:52:18.663969: Epoch 4355 +2024-11-22 10:52:18.664083: Current learning rate: 0.00493 +2024-11-22 10:52:37.165037: train_loss -0.7882 +2024-11-22 10:52:37.165293: val_loss -0.7198 +2024-11-22 10:52:37.165372: Pseudo dice [0.8434] +2024-11-22 10:52:37.165454: Epoch time: 18.5 s +2024-11-22 10:52:38.026804: +2024-11-22 10:52:38.027028: Epoch 4356 +2024-11-22 10:52:38.027151: Current learning rate: 0.00493 +2024-11-22 10:52:55.988109: train_loss -0.7848 +2024-11-22 10:52:55.988313: val_loss -0.7652 +2024-11-22 10:52:55.988394: Pseudo dice [0.8515] +2024-11-22 10:52:55.988472: Epoch time: 17.96 s +2024-11-22 10:52:56.814574: +2024-11-22 10:52:56.814780: Epoch 4357 +2024-11-22 10:52:56.814889: Current learning rate: 0.00493 +2024-11-22 10:53:16.086704: train_loss -0.7903 +2024-11-22 10:53:16.086991: val_loss -0.7729 +2024-11-22 10:53:16.087077: Pseudo dice [0.8544] +2024-11-22 10:53:16.087151: Epoch time: 19.27 s +2024-11-22 10:53:16.919664: +2024-11-22 10:53:16.919859: Epoch 4358 +2024-11-22 10:53:16.919966: Current learning rate: 0.00493 +2024-11-22 10:53:34.757226: train_loss -0.7946 +2024-11-22 10:53:34.757451: val_loss -0.7576 +2024-11-22 10:53:34.757543: Pseudo dice [0.8441] +2024-11-22 10:53:34.757623: Epoch time: 17.84 s +2024-11-22 10:53:35.589592: +2024-11-22 10:53:35.589822: Epoch 4359 +2024-11-22 10:53:35.589931: Current learning rate: 0.00492 +2024-11-22 10:53:54.276190: train_loss -0.7873 +2024-11-22 10:53:54.276441: val_loss -0.768 +2024-11-22 10:53:54.276521: Pseudo dice [0.8611] +2024-11-22 10:53:54.276609: Epoch time: 18.69 s +2024-11-22 10:53:55.206284: +2024-11-22 10:53:55.206493: Epoch 4360 +2024-11-22 10:53:55.206606: Current learning rate: 0.00492 +2024-11-22 10:54:13.477395: train_loss -0.7823 +2024-11-22 10:54:13.477928: val_loss -0.7521 +2024-11-22 10:54:13.478024: Pseudo dice [0.8468] +2024-11-22 10:54:13.478105: Epoch time: 18.27 s +2024-11-22 10:54:14.310064: +2024-11-22 10:54:14.310287: Epoch 4361 +2024-11-22 10:54:14.310400: Current learning rate: 0.00492 +2024-11-22 10:54:33.346938: train_loss -0.7793 +2024-11-22 10:54:33.347166: val_loss -0.7357 +2024-11-22 10:54:33.347239: Pseudo dice [0.8516] +2024-11-22 10:54:33.347312: Epoch time: 19.04 s +2024-11-22 10:54:34.179554: +2024-11-22 10:54:34.179794: Epoch 4362 +2024-11-22 10:54:34.179904: Current learning rate: 0.00492 +2024-11-22 10:54:53.832141: train_loss -0.779 +2024-11-22 10:54:53.832360: val_loss -0.7732 +2024-11-22 10:54:53.832436: Pseudo dice [0.8605] +2024-11-22 10:54:53.832508: Epoch time: 19.65 s +2024-11-22 10:54:54.807683: +2024-11-22 10:54:54.807887: Epoch 4363 +2024-11-22 10:54:54.807998: Current learning rate: 0.00492 +2024-11-22 10:55:13.581128: train_loss -0.7931 +2024-11-22 10:55:13.581377: val_loss -0.7703 +2024-11-22 10:55:13.581454: Pseudo dice [0.847] +2024-11-22 10:55:13.581535: Epoch time: 18.77 s +2024-11-22 10:55:14.415206: +2024-11-22 10:55:14.415402: Epoch 4364 +2024-11-22 10:55:14.415511: Current learning rate: 0.00492 +2024-11-22 10:55:32.613624: train_loss -0.7864 +2024-11-22 10:55:32.613840: val_loss -0.759 +2024-11-22 10:55:32.613916: Pseudo dice [0.8481] +2024-11-22 10:55:32.613992: Epoch time: 18.2 s +2024-11-22 10:55:33.851290: +2024-11-22 10:55:33.851513: Epoch 4365 +2024-11-22 10:55:33.851629: Current learning rate: 0.00492 +2024-11-22 10:55:51.339235: train_loss -0.7835 +2024-11-22 10:55:51.339460: val_loss -0.7863 +2024-11-22 10:55:51.339535: Pseudo dice [0.8585] +2024-11-22 10:55:51.339610: Epoch time: 17.49 s +2024-11-22 10:55:52.301194: +2024-11-22 10:55:52.301458: Epoch 4366 +2024-11-22 10:55:52.301567: Current learning rate: 0.00492 +2024-11-22 10:56:10.584510: train_loss -0.7883 +2024-11-22 10:56:10.584788: val_loss -0.7592 +2024-11-22 10:56:10.584868: Pseudo dice [0.8435] +2024-11-22 10:56:10.584945: Epoch time: 18.28 s +2024-11-22 10:56:11.421041: +2024-11-22 10:56:11.421244: Epoch 4367 +2024-11-22 10:56:11.421358: Current learning rate: 0.00491 +2024-11-22 10:56:29.423805: train_loss -0.7891 +2024-11-22 10:56:29.424079: val_loss -0.7625 +2024-11-22 10:56:29.424157: Pseudo dice [0.8497] +2024-11-22 10:56:29.424237: Epoch time: 18.0 s +2024-11-22 10:56:30.260108: +2024-11-22 10:56:30.260315: Epoch 4368 +2024-11-22 10:56:30.260427: Current learning rate: 0.00491 +2024-11-22 10:56:50.058973: train_loss -0.7997 +2024-11-22 10:56:50.059189: val_loss -0.7856 +2024-11-22 10:56:50.059264: Pseudo dice [0.8543] +2024-11-22 10:56:50.059339: Epoch time: 19.8 s +2024-11-22 10:56:50.975794: +2024-11-22 10:56:50.975976: Epoch 4369 +2024-11-22 10:56:50.976087: Current learning rate: 0.00491 +2024-11-22 10:57:09.985493: train_loss -0.7892 +2024-11-22 10:57:09.985704: val_loss -0.7512 +2024-11-22 10:57:09.985777: Pseudo dice [0.8439] +2024-11-22 10:57:09.985851: Epoch time: 19.01 s +2024-11-22 10:57:10.823576: +2024-11-22 10:57:10.823797: Epoch 4370 +2024-11-22 10:57:10.823905: Current learning rate: 0.00491 +2024-11-22 10:57:28.695933: train_loss -0.7876 +2024-11-22 10:57:28.696171: val_loss -0.7697 +2024-11-22 10:57:28.696244: Pseudo dice [0.8519] +2024-11-22 10:57:28.696317: Epoch time: 17.87 s +2024-11-22 10:57:29.542770: +2024-11-22 10:57:29.542982: Epoch 4371 +2024-11-22 10:57:29.543102: Current learning rate: 0.00491 +2024-11-22 10:57:48.111793: train_loss -0.7887 +2024-11-22 10:57:48.112037: val_loss -0.7757 +2024-11-22 10:57:48.112120: Pseudo dice [0.8507] +2024-11-22 10:57:48.112204: Epoch time: 18.57 s +2024-11-22 10:57:48.965732: +2024-11-22 10:57:48.965912: Epoch 4372 +2024-11-22 10:57:48.966023: Current learning rate: 0.00491 +2024-11-22 10:58:07.350794: train_loss -0.783 +2024-11-22 10:58:07.351010: val_loss -0.7609 +2024-11-22 10:58:07.351090: Pseudo dice [0.8442] +2024-11-22 10:58:07.351166: Epoch time: 18.39 s +2024-11-22 10:58:08.274390: +2024-11-22 10:58:08.274604: Epoch 4373 +2024-11-22 10:58:08.274716: Current learning rate: 0.00491 +2024-11-22 10:58:25.708612: train_loss -0.7882 +2024-11-22 10:58:25.708830: val_loss -0.7668 +2024-11-22 10:58:25.708905: Pseudo dice [0.8612] +2024-11-22 10:58:25.708981: Epoch time: 17.44 s +2024-11-22 10:58:26.543355: +2024-11-22 10:58:26.543557: Epoch 4374 +2024-11-22 10:58:26.543667: Current learning rate: 0.00491 +2024-11-22 10:58:45.075855: train_loss -0.7962 +2024-11-22 10:58:45.076072: val_loss -0.7832 +2024-11-22 10:58:45.076146: Pseudo dice [0.8566] +2024-11-22 10:58:45.076220: Epoch time: 18.53 s +2024-11-22 10:58:45.905171: +2024-11-22 10:58:45.905379: Epoch 4375 +2024-11-22 10:58:45.905488: Current learning rate: 0.0049 +2024-11-22 10:59:04.413988: train_loss -0.7981 +2024-11-22 10:59:04.414241: val_loss -0.7568 +2024-11-22 10:59:04.414321: Pseudo dice [0.8535] +2024-11-22 10:59:04.414409: Epoch time: 18.51 s +2024-11-22 10:59:05.250599: +2024-11-22 10:59:05.250801: Epoch 4376 +2024-11-22 10:59:05.250912: Current learning rate: 0.0049 +2024-11-22 10:59:24.560936: train_loss -0.7838 +2024-11-22 10:59:24.561150: val_loss -0.7772 +2024-11-22 10:59:24.561226: Pseudo dice [0.8482] +2024-11-22 10:59:24.561299: Epoch time: 19.31 s +2024-11-22 10:59:25.863865: +2024-11-22 10:59:25.864087: Epoch 4377 +2024-11-22 10:59:25.864198: Current learning rate: 0.0049 +2024-11-22 10:59:43.645710: train_loss -0.7819 +2024-11-22 10:59:43.645920: val_loss -0.7717 +2024-11-22 10:59:43.645997: Pseudo dice [0.8434] +2024-11-22 10:59:43.646081: Epoch time: 17.78 s +2024-11-22 10:59:44.481141: +2024-11-22 10:59:44.481349: Epoch 4378 +2024-11-22 10:59:44.481460: Current learning rate: 0.0049 +2024-11-22 11:00:03.022554: train_loss -0.7849 +2024-11-22 11:00:03.022763: val_loss -0.7582 +2024-11-22 11:00:03.022842: Pseudo dice [0.8562] +2024-11-22 11:00:03.022922: Epoch time: 18.54 s +2024-11-22 11:00:03.857373: +2024-11-22 11:00:03.857612: Epoch 4379 +2024-11-22 11:00:03.857721: Current learning rate: 0.0049 +2024-11-22 11:00:22.168198: train_loss -0.7799 +2024-11-22 11:00:22.168414: val_loss -0.7628 +2024-11-22 11:00:22.168490: Pseudo dice [0.8535] +2024-11-22 11:00:22.168567: Epoch time: 18.31 s +2024-11-22 11:00:22.999633: +2024-11-22 11:00:22.999872: Epoch 4380 +2024-11-22 11:00:22.999984: Current learning rate: 0.0049 +2024-11-22 11:00:41.636450: train_loss -0.7783 +2024-11-22 11:00:41.636666: val_loss -0.7705 +2024-11-22 11:00:41.636747: Pseudo dice [0.8347] +2024-11-22 11:00:41.636822: Epoch time: 18.64 s +2024-11-22 11:00:42.528655: +2024-11-22 11:00:42.528889: Epoch 4381 +2024-11-22 11:00:42.529002: Current learning rate: 0.0049 +2024-11-22 11:01:01.389761: train_loss -0.7565 +2024-11-22 11:01:01.389978: val_loss -0.7317 +2024-11-22 11:01:01.390056: Pseudo dice [0.8329] +2024-11-22 11:01:01.390141: Epoch time: 18.86 s +2024-11-22 11:01:02.221818: +2024-11-22 11:01:02.222130: Epoch 4382 +2024-11-22 11:01:02.222244: Current learning rate: 0.0049 +2024-11-22 11:01:18.832983: train_loss -0.7695 +2024-11-22 11:01:18.833206: val_loss -0.74 +2024-11-22 11:01:18.833288: Pseudo dice [0.8435] +2024-11-22 11:01:18.833372: Epoch time: 16.61 s +2024-11-22 11:01:19.669894: +2024-11-22 11:01:19.670090: Epoch 4383 +2024-11-22 11:01:19.670197: Current learning rate: 0.00489 +2024-11-22 11:01:38.089769: train_loss -0.7649 +2024-11-22 11:01:38.090076: val_loss -0.7807 +2024-11-22 11:01:38.090153: Pseudo dice [0.8594] +2024-11-22 11:01:38.090232: Epoch time: 18.42 s +2024-11-22 11:01:39.020611: +2024-11-22 11:01:39.020825: Epoch 4384 +2024-11-22 11:01:39.020936: Current learning rate: 0.00489 +2024-11-22 11:01:57.047664: train_loss -0.7806 +2024-11-22 11:01:57.047886: val_loss -0.7685 +2024-11-22 11:01:57.047960: Pseudo dice [0.8523] +2024-11-22 11:01:57.048033: Epoch time: 18.03 s +2024-11-22 11:01:57.989023: +2024-11-22 11:01:57.989239: Epoch 4385 +2024-11-22 11:01:57.989348: Current learning rate: 0.00489 +2024-11-22 11:02:16.066551: train_loss -0.7655 +2024-11-22 11:02:16.066757: val_loss -0.7801 +2024-11-22 11:02:16.066831: Pseudo dice [0.8523] +2024-11-22 11:02:16.066908: Epoch time: 18.08 s +2024-11-22 11:02:16.928071: +2024-11-22 11:02:16.928270: Epoch 4386 +2024-11-22 11:02:16.928382: Current learning rate: 0.00489 +2024-11-22 11:02:35.893557: train_loss -0.7827 +2024-11-22 11:02:35.894072: val_loss -0.7577 +2024-11-22 11:02:35.894167: Pseudo dice [0.8648] +2024-11-22 11:02:35.894250: Epoch time: 18.97 s +2024-11-22 11:02:36.731895: +2024-11-22 11:02:36.732116: Epoch 4387 +2024-11-22 11:02:36.732229: Current learning rate: 0.00489 +2024-11-22 11:02:54.903911: train_loss -0.7738 +2024-11-22 11:02:54.906292: val_loss -0.7575 +2024-11-22 11:02:54.906393: Pseudo dice [0.85] +2024-11-22 11:02:54.906472: Epoch time: 18.17 s +2024-11-22 11:02:55.744794: +2024-11-22 11:02:55.745019: Epoch 4388 +2024-11-22 11:02:55.745135: Current learning rate: 0.00489 +2024-11-22 11:03:14.083860: train_loss -0.7714 +2024-11-22 11:03:14.084071: val_loss -0.7766 +2024-11-22 11:03:14.084148: Pseudo dice [0.8611] +2024-11-22 11:03:14.084225: Epoch time: 18.34 s +2024-11-22 11:03:15.322014: +2024-11-22 11:03:15.322260: Epoch 4389 +2024-11-22 11:03:15.322374: Current learning rate: 0.00489 +2024-11-22 11:03:32.691115: train_loss -0.7724 +2024-11-22 11:03:32.691395: val_loss -0.7528 +2024-11-22 11:03:32.691474: Pseudo dice [0.8668] +2024-11-22 11:03:32.691563: Epoch time: 17.37 s +2024-11-22 11:03:33.740213: +2024-11-22 11:03:33.740457: Epoch 4390 +2024-11-22 11:03:33.740570: Current learning rate: 0.00489 +2024-11-22 11:03:51.305636: train_loss -0.7676 +2024-11-22 11:03:51.305844: val_loss -0.7398 +2024-11-22 11:03:51.305918: Pseudo dice [0.8092] +2024-11-22 11:03:51.305991: Epoch time: 17.57 s +2024-11-22 11:03:52.134815: +2024-11-22 11:03:52.135025: Epoch 4391 +2024-11-22 11:03:52.135142: Current learning rate: 0.00489 +2024-11-22 11:04:10.571153: train_loss -0.7573 +2024-11-22 11:04:10.571375: val_loss -0.7661 +2024-11-22 11:04:10.571451: Pseudo dice [0.8396] +2024-11-22 11:04:10.571526: Epoch time: 18.44 s +2024-11-22 11:04:11.493385: +2024-11-22 11:04:11.493588: Epoch 4392 +2024-11-22 11:04:11.493702: Current learning rate: 0.00488 +2024-11-22 11:04:30.242435: train_loss -0.7673 +2024-11-22 11:04:30.242650: val_loss -0.7654 +2024-11-22 11:04:30.242727: Pseudo dice [0.8404] +2024-11-22 11:04:30.242802: Epoch time: 18.75 s +2024-11-22 11:04:31.082749: +2024-11-22 11:04:31.083001: Epoch 4393 +2024-11-22 11:04:31.083117: Current learning rate: 0.00488 +2024-11-22 11:04:49.364976: train_loss -0.7628 +2024-11-22 11:04:49.365225: val_loss -0.776 +2024-11-22 11:04:49.365306: Pseudo dice [0.8501] +2024-11-22 11:04:49.365384: Epoch time: 18.28 s +2024-11-22 11:04:50.200894: +2024-11-22 11:04:50.201104: Epoch 4394 +2024-11-22 11:04:50.201216: Current learning rate: 0.00488 +2024-11-22 11:05:08.523155: train_loss -0.7896 +2024-11-22 11:05:08.523360: val_loss -0.7729 +2024-11-22 11:05:08.523432: Pseudo dice [0.8507] +2024-11-22 11:05:08.523503: Epoch time: 18.32 s +2024-11-22 11:05:09.450847: +2024-11-22 11:05:09.451057: Epoch 4395 +2024-11-22 11:05:09.451173: Current learning rate: 0.00488 +2024-11-22 11:05:28.658909: train_loss -0.7834 +2024-11-22 11:05:28.659147: val_loss -0.7597 +2024-11-22 11:05:28.659223: Pseudo dice [0.8391] +2024-11-22 11:05:28.659299: Epoch time: 19.21 s +2024-11-22 11:05:29.492607: +2024-11-22 11:05:29.492809: Epoch 4396 +2024-11-22 11:05:29.492917: Current learning rate: 0.00488 +2024-11-22 11:05:48.960745: train_loss -0.7828 +2024-11-22 11:05:48.961011: val_loss -0.763 +2024-11-22 11:05:48.961097: Pseudo dice [0.8364] +2024-11-22 11:05:48.961174: Epoch time: 19.47 s +2024-11-22 11:05:49.799243: +2024-11-22 11:05:49.799458: Epoch 4397 +2024-11-22 11:05:49.799569: Current learning rate: 0.00488 +2024-11-22 11:06:09.299208: train_loss -0.7761 +2024-11-22 11:06:09.299448: val_loss -0.775 +2024-11-22 11:06:09.299524: Pseudo dice [0.8434] +2024-11-22 11:06:09.301781: Epoch time: 19.5 s +2024-11-22 11:06:10.232393: +2024-11-22 11:06:10.232624: Epoch 4398 +2024-11-22 11:06:10.232743: Current learning rate: 0.00488 +2024-11-22 11:06:29.242967: train_loss -0.7861 +2024-11-22 11:06:29.243175: val_loss -0.7803 +2024-11-22 11:06:29.243248: Pseudo dice [0.8564] +2024-11-22 11:06:29.243323: Epoch time: 19.01 s +2024-11-22 11:06:30.104712: +2024-11-22 11:06:30.104928: Epoch 4399 +2024-11-22 11:06:30.105044: Current learning rate: 0.00488 +2024-11-22 11:06:47.777865: train_loss -0.7876 +2024-11-22 11:06:47.778085: val_loss -0.7872 +2024-11-22 11:06:47.778161: Pseudo dice [0.8458] +2024-11-22 11:06:47.778244: Epoch time: 17.67 s +2024-11-22 11:06:48.867961: +2024-11-22 11:06:48.868161: Epoch 4400 +2024-11-22 11:06:48.868273: Current learning rate: 0.00487 +2024-11-22 11:07:07.376385: train_loss -0.793 +2024-11-22 11:07:07.376596: val_loss -0.7685 +2024-11-22 11:07:07.376683: Pseudo dice [0.8468] +2024-11-22 11:07:07.376760: Epoch time: 18.51 s +2024-11-22 11:07:08.629425: +2024-11-22 11:07:08.629667: Epoch 4401 +2024-11-22 11:07:08.629822: Current learning rate: 0.00487 +2024-11-22 11:07:27.551940: train_loss -0.7903 +2024-11-22 11:07:27.552166: val_loss -0.7574 +2024-11-22 11:07:27.552244: Pseudo dice [0.8443] +2024-11-22 11:07:27.552323: Epoch time: 18.92 s +2024-11-22 11:07:28.482412: +2024-11-22 11:07:28.482614: Epoch 4402 +2024-11-22 11:07:28.482721: Current learning rate: 0.00487 +2024-11-22 11:07:47.373356: train_loss -0.7874 +2024-11-22 11:07:47.373562: val_loss -0.7545 +2024-11-22 11:07:47.373636: Pseudo dice [0.8546] +2024-11-22 11:07:47.373721: Epoch time: 18.89 s +2024-11-22 11:07:48.207245: +2024-11-22 11:07:48.207499: Epoch 4403 +2024-11-22 11:07:48.207613: Current learning rate: 0.00487 +2024-11-22 11:08:05.488710: train_loss -0.7923 +2024-11-22 11:08:05.488931: val_loss -0.7677 +2024-11-22 11:08:05.489006: Pseudo dice [0.8505] +2024-11-22 11:08:05.489088: Epoch time: 17.28 s +2024-11-22 11:08:06.324327: +2024-11-22 11:08:06.324580: Epoch 4404 +2024-11-22 11:08:06.324689: Current learning rate: 0.00487 +2024-11-22 11:08:24.194939: train_loss -0.7838 +2024-11-22 11:08:24.195187: val_loss -0.7598 +2024-11-22 11:08:24.195270: Pseudo dice [0.8512] +2024-11-22 11:08:24.195349: Epoch time: 17.87 s +2024-11-22 11:08:25.039629: +2024-11-22 11:08:25.039881: Epoch 4405 +2024-11-22 11:08:25.039992: Current learning rate: 0.00487 +2024-11-22 11:08:43.386331: train_loss -0.7797 +2024-11-22 11:08:43.386553: val_loss -0.7752 +2024-11-22 11:08:43.386629: Pseudo dice [0.8576] +2024-11-22 11:08:43.386704: Epoch time: 18.35 s +2024-11-22 11:08:44.221712: +2024-11-22 11:08:44.221916: Epoch 4406 +2024-11-22 11:08:44.222031: Current learning rate: 0.00487 +2024-11-22 11:09:02.356544: train_loss -0.7893 +2024-11-22 11:09:02.356752: val_loss -0.7734 +2024-11-22 11:09:02.356826: Pseudo dice [0.8617] +2024-11-22 11:09:02.356900: Epoch time: 18.14 s +2024-11-22 11:09:03.189524: +2024-11-22 11:09:03.189732: Epoch 4407 +2024-11-22 11:09:03.189845: Current learning rate: 0.00487 +2024-11-22 11:09:22.156394: train_loss -0.7826 +2024-11-22 11:09:22.156601: val_loss -0.7646 +2024-11-22 11:09:22.156675: Pseudo dice [0.8637] +2024-11-22 11:09:22.156749: Epoch time: 18.97 s +2024-11-22 11:09:23.186049: +2024-11-22 11:09:23.186257: Epoch 4408 +2024-11-22 11:09:23.186372: Current learning rate: 0.00486 +2024-11-22 11:09:41.901346: train_loss -0.7879 +2024-11-22 11:09:41.901584: val_loss -0.753 +2024-11-22 11:09:41.901661: Pseudo dice [0.8414] +2024-11-22 11:09:41.901746: Epoch time: 18.72 s +2024-11-22 11:09:42.837366: +2024-11-22 11:09:42.837594: Epoch 4409 +2024-11-22 11:09:42.837705: Current learning rate: 0.00486 +2024-11-22 11:10:00.961366: train_loss -0.7894 +2024-11-22 11:10:00.961634: val_loss -0.7683 +2024-11-22 11:10:00.961710: Pseudo dice [0.8516] +2024-11-22 11:10:00.961786: Epoch time: 18.12 s +2024-11-22 11:10:01.800029: +2024-11-22 11:10:01.800247: Epoch 4410 +2024-11-22 11:10:01.800359: Current learning rate: 0.00486 +2024-11-22 11:10:20.097778: train_loss -0.7837 +2024-11-22 11:10:20.097989: val_loss -0.7755 +2024-11-22 11:10:20.098067: Pseudo dice [0.8497] +2024-11-22 11:10:20.098141: Epoch time: 18.3 s +2024-11-22 11:10:20.929399: +2024-11-22 11:10:20.929613: Epoch 4411 +2024-11-22 11:10:20.929723: Current learning rate: 0.00486 +2024-11-22 11:10:39.381184: train_loss -0.7832 +2024-11-22 11:10:39.381400: val_loss -0.7695 +2024-11-22 11:10:39.381480: Pseudo dice [0.8594] +2024-11-22 11:10:39.381559: Epoch time: 18.45 s +2024-11-22 11:10:40.353858: +2024-11-22 11:10:40.354053: Epoch 4412 +2024-11-22 11:10:40.354167: Current learning rate: 0.00486 +2024-11-22 11:10:59.773603: train_loss -0.7752 +2024-11-22 11:10:59.773834: val_loss -0.7553 +2024-11-22 11:10:59.773908: Pseudo dice [0.8599] +2024-11-22 11:10:59.773987: Epoch time: 19.42 s +2024-11-22 11:11:01.024506: +2024-11-22 11:11:01.024748: Epoch 4413 +2024-11-22 11:11:01.024863: Current learning rate: 0.00486 +2024-11-22 11:11:19.296634: train_loss -0.7875 +2024-11-22 11:11:19.296857: val_loss -0.7741 +2024-11-22 11:11:19.296931: Pseudo dice [0.8549] +2024-11-22 11:11:19.297006: Epoch time: 18.27 s +2024-11-22 11:11:20.263020: +2024-11-22 11:11:20.263232: Epoch 4414 +2024-11-22 11:11:20.263344: Current learning rate: 0.00486 +2024-11-22 11:11:37.969653: train_loss -0.7882 +2024-11-22 11:11:37.969876: val_loss -0.7837 +2024-11-22 11:11:37.969953: Pseudo dice [0.8653] +2024-11-22 11:11:37.970028: Epoch time: 17.71 s +2024-11-22 11:11:38.802983: +2024-11-22 11:11:38.803214: Epoch 4415 +2024-11-22 11:11:38.803331: Current learning rate: 0.00486 +2024-11-22 11:11:56.857237: train_loss -0.7941 +2024-11-22 11:11:56.857547: val_loss -0.7814 +2024-11-22 11:11:56.857627: Pseudo dice [0.854] +2024-11-22 11:11:56.857712: Epoch time: 18.06 s +2024-11-22 11:11:57.696485: +2024-11-22 11:11:57.696708: Epoch 4416 +2024-11-22 11:11:57.696820: Current learning rate: 0.00485 +2024-11-22 11:12:15.688972: train_loss -0.7873 +2024-11-22 11:12:15.689188: val_loss -0.7753 +2024-11-22 11:12:15.689265: Pseudo dice [0.8461] +2024-11-22 11:12:15.689339: Epoch time: 17.99 s +2024-11-22 11:12:16.527407: +2024-11-22 11:12:16.527631: Epoch 4417 +2024-11-22 11:12:16.527741: Current learning rate: 0.00485 +2024-11-22 11:12:34.860506: train_loss -0.78 +2024-11-22 11:12:34.860723: val_loss -0.7793 +2024-11-22 11:12:34.860798: Pseudo dice [0.8611] +2024-11-22 11:12:34.860874: Epoch time: 18.33 s +2024-11-22 11:12:35.698102: +2024-11-22 11:12:35.698314: Epoch 4418 +2024-11-22 11:12:35.698431: Current learning rate: 0.00485 +2024-11-22 11:12:54.340823: train_loss -0.7841 +2024-11-22 11:12:54.341035: val_loss -0.7658 +2024-11-22 11:12:54.341113: Pseudo dice [0.8617] +2024-11-22 11:12:54.341186: Epoch time: 18.64 s +2024-11-22 11:12:55.196784: +2024-11-22 11:12:55.197000: Epoch 4419 +2024-11-22 11:12:55.197147: Current learning rate: 0.00485 +2024-11-22 11:13:13.874566: train_loss -0.8006 +2024-11-22 11:13:13.874781: val_loss -0.7785 +2024-11-22 11:13:13.874866: Pseudo dice [0.8544] +2024-11-22 11:13:13.877197: Epoch time: 18.68 s +2024-11-22 11:13:14.800639: +2024-11-22 11:13:14.800879: Epoch 4420 +2024-11-22 11:13:14.800987: Current learning rate: 0.00485 +2024-11-22 11:13:32.334323: train_loss -0.7863 +2024-11-22 11:13:32.334563: val_loss -0.7715 +2024-11-22 11:13:32.334642: Pseudo dice [0.862] +2024-11-22 11:13:32.334723: Epoch time: 17.53 s +2024-11-22 11:13:33.173272: +2024-11-22 11:13:33.173471: Epoch 4421 +2024-11-22 11:13:33.173579: Current learning rate: 0.00485 +2024-11-22 11:13:50.679293: train_loss -0.7895 +2024-11-22 11:13:50.679505: val_loss -0.7442 +2024-11-22 11:13:50.679578: Pseudo dice [0.8481] +2024-11-22 11:13:50.679652: Epoch time: 17.51 s +2024-11-22 11:13:51.515572: +2024-11-22 11:13:51.515811: Epoch 4422 +2024-11-22 11:13:51.515927: Current learning rate: 0.00485 +2024-11-22 11:14:09.894580: train_loss -0.7879 +2024-11-22 11:14:09.894790: val_loss -0.7601 +2024-11-22 11:14:09.894864: Pseudo dice [0.8482] +2024-11-22 11:14:09.894939: Epoch time: 18.38 s +2024-11-22 11:14:10.731505: +2024-11-22 11:14:10.731729: Epoch 4423 +2024-11-22 11:14:10.731841: Current learning rate: 0.00485 +2024-11-22 11:14:29.359071: train_loss -0.7854 +2024-11-22 11:14:29.359288: val_loss -0.7643 +2024-11-22 11:14:29.359364: Pseudo dice [0.8594] +2024-11-22 11:14:29.359446: Epoch time: 18.63 s +2024-11-22 11:14:30.192687: +2024-11-22 11:14:30.192895: Epoch 4424 +2024-11-22 11:14:30.193006: Current learning rate: 0.00484 +2024-11-22 11:14:48.276274: train_loss -0.7845 +2024-11-22 11:14:48.276512: val_loss -0.7496 +2024-11-22 11:14:48.276588: Pseudo dice [0.8439] +2024-11-22 11:14:48.276668: Epoch time: 18.08 s +2024-11-22 11:14:49.528706: +2024-11-22 11:14:49.528935: Epoch 4425 +2024-11-22 11:14:49.529045: Current learning rate: 0.00484 +2024-11-22 11:15:07.717313: train_loss -0.7707 +2024-11-22 11:15:07.717530: val_loss -0.774 +2024-11-22 11:15:07.717605: Pseudo dice [0.859] +2024-11-22 11:15:07.717684: Epoch time: 18.19 s +2024-11-22 11:15:08.553449: +2024-11-22 11:15:08.553705: Epoch 4426 +2024-11-22 11:15:08.553817: Current learning rate: 0.00484 +2024-11-22 11:15:26.589532: train_loss -0.7925 +2024-11-22 11:15:26.589754: val_loss -0.753 +2024-11-22 11:15:26.589830: Pseudo dice [0.8488] +2024-11-22 11:15:26.589905: Epoch time: 18.04 s +2024-11-22 11:15:27.416974: +2024-11-22 11:15:27.417211: Epoch 4427 +2024-11-22 11:15:27.417317: Current learning rate: 0.00484 +2024-11-22 11:15:45.929008: train_loss -0.7903 +2024-11-22 11:15:45.929247: val_loss -0.7708 +2024-11-22 11:15:45.929330: Pseudo dice [0.8646] +2024-11-22 11:15:45.929412: Epoch time: 18.51 s +2024-11-22 11:15:46.834382: +2024-11-22 11:15:46.834575: Epoch 4428 +2024-11-22 11:15:46.834684: Current learning rate: 0.00484 +2024-11-22 11:16:04.210045: train_loss -0.7816 +2024-11-22 11:16:04.210252: val_loss -0.7638 +2024-11-22 11:16:04.210328: Pseudo dice [0.849] +2024-11-22 11:16:04.210404: Epoch time: 17.38 s +2024-11-22 11:16:05.150540: +2024-11-22 11:16:05.150760: Epoch 4429 +2024-11-22 11:16:05.150872: Current learning rate: 0.00484 +2024-11-22 11:16:23.470504: train_loss -0.7666 +2024-11-22 11:16:23.470710: val_loss -0.763 +2024-11-22 11:16:23.470784: Pseudo dice [0.8444] +2024-11-22 11:16:23.470857: Epoch time: 18.32 s +2024-11-22 11:16:24.304241: +2024-11-22 11:16:24.304423: Epoch 4430 +2024-11-22 11:16:24.304555: Current learning rate: 0.00484 +2024-11-22 11:16:43.916612: train_loss -0.7691 +2024-11-22 11:16:43.916831: val_loss -0.7558 +2024-11-22 11:16:43.916907: Pseudo dice [0.8415] +2024-11-22 11:16:43.916981: Epoch time: 19.61 s +2024-11-22 11:16:44.751831: +2024-11-22 11:16:44.752047: Epoch 4431 +2024-11-22 11:16:44.752167: Current learning rate: 0.00484 +2024-11-22 11:17:04.200871: train_loss -0.7823 +2024-11-22 11:17:04.201122: val_loss -0.7757 +2024-11-22 11:17:04.201203: Pseudo dice [0.8691] +2024-11-22 11:17:04.201288: Epoch time: 19.45 s +2024-11-22 11:17:05.040367: +2024-11-22 11:17:05.040581: Epoch 4432 +2024-11-22 11:17:05.040696: Current learning rate: 0.00484 +2024-11-22 11:17:23.375027: train_loss -0.7818 +2024-11-22 11:17:23.375252: val_loss -0.7578 +2024-11-22 11:17:23.375327: Pseudo dice [0.843] +2024-11-22 11:17:23.375402: Epoch time: 18.34 s +2024-11-22 11:17:24.254790: +2024-11-22 11:17:24.255007: Epoch 4433 +2024-11-22 11:17:24.255120: Current learning rate: 0.00483 +2024-11-22 11:17:42.508237: train_loss -0.7875 +2024-11-22 11:17:42.508448: val_loss -0.7805 +2024-11-22 11:17:42.508526: Pseudo dice [0.8602] +2024-11-22 11:17:42.508603: Epoch time: 18.25 s +2024-11-22 11:17:43.342013: +2024-11-22 11:17:43.342234: Epoch 4434 +2024-11-22 11:17:43.342349: Current learning rate: 0.00483 +2024-11-22 11:18:01.567584: train_loss -0.7801 +2024-11-22 11:18:01.567800: val_loss -0.7848 +2024-11-22 11:18:01.567882: Pseudo dice [0.854] +2024-11-22 11:18:01.567958: Epoch time: 18.23 s +2024-11-22 11:18:02.397304: +2024-11-22 11:18:02.397519: Epoch 4435 +2024-11-22 11:18:02.397630: Current learning rate: 0.00483 +2024-11-22 11:18:20.760143: train_loss -0.7934 +2024-11-22 11:18:20.762561: val_loss -0.7671 +2024-11-22 11:18:20.762654: Pseudo dice [0.856] +2024-11-22 11:18:20.762739: Epoch time: 18.36 s +2024-11-22 11:18:21.753261: +2024-11-22 11:18:21.753459: Epoch 4436 +2024-11-22 11:18:21.753573: Current learning rate: 0.00483 +2024-11-22 11:18:39.562215: train_loss -0.7992 +2024-11-22 11:18:39.562423: val_loss -0.786 +2024-11-22 11:18:39.562500: Pseudo dice [0.8627] +2024-11-22 11:18:39.562574: Epoch time: 17.81 s +2024-11-22 11:18:40.871530: +2024-11-22 11:18:40.871742: Epoch 4437 +2024-11-22 11:18:40.871853: Current learning rate: 0.00483 +2024-11-22 11:18:59.368305: train_loss -0.7826 +2024-11-22 11:18:59.368526: val_loss -0.7704 +2024-11-22 11:18:59.368605: Pseudo dice [0.8602] +2024-11-22 11:18:59.368687: Epoch time: 18.5 s +2024-11-22 11:19:00.193183: +2024-11-22 11:19:00.193396: Epoch 4438 +2024-11-22 11:19:00.193507: Current learning rate: 0.00483 +2024-11-22 11:19:18.662902: train_loss -0.7897 +2024-11-22 11:19:18.663160: val_loss -0.7764 +2024-11-22 11:19:18.663238: Pseudo dice [0.8555] +2024-11-22 11:19:18.663318: Epoch time: 18.47 s +2024-11-22 11:19:19.501540: +2024-11-22 11:19:19.501770: Epoch 4439 +2024-11-22 11:19:19.501881: Current learning rate: 0.00483 +2024-11-22 11:19:38.612027: train_loss -0.7969 +2024-11-22 11:19:38.612268: val_loss -0.7635 +2024-11-22 11:19:38.612343: Pseudo dice [0.8472] +2024-11-22 11:19:38.612434: Epoch time: 19.11 s +2024-11-22 11:19:39.444531: +2024-11-22 11:19:39.444753: Epoch 4440 +2024-11-22 11:19:39.444870: Current learning rate: 0.00483 +2024-11-22 11:19:58.875183: train_loss -0.7936 +2024-11-22 11:19:58.875443: val_loss -0.7581 +2024-11-22 11:19:58.875519: Pseudo dice [0.8436] +2024-11-22 11:19:58.875593: Epoch time: 19.43 s +2024-11-22 11:19:59.711030: +2024-11-22 11:19:59.711228: Epoch 4441 +2024-11-22 11:19:59.711341: Current learning rate: 0.00482 +2024-11-22 11:20:17.590386: train_loss -0.7897 +2024-11-22 11:20:17.590604: val_loss -0.7631 +2024-11-22 11:20:17.590687: Pseudo dice [0.8421] +2024-11-22 11:20:17.590761: Epoch time: 17.88 s +2024-11-22 11:20:18.419852: +2024-11-22 11:20:18.420045: Epoch 4442 +2024-11-22 11:20:18.420162: Current learning rate: 0.00482 +2024-11-22 11:20:36.532796: train_loss -0.7908 +2024-11-22 11:20:36.533022: val_loss -0.7699 +2024-11-22 11:20:36.533108: Pseudo dice [0.8385] +2024-11-22 11:20:36.533186: Epoch time: 18.11 s +2024-11-22 11:20:37.365845: +2024-11-22 11:20:37.366038: Epoch 4443 +2024-11-22 11:20:37.366152: Current learning rate: 0.00482 +2024-11-22 11:20:56.980760: train_loss -0.7922 +2024-11-22 11:20:56.980998: val_loss -0.7387 +2024-11-22 11:20:56.981078: Pseudo dice [0.851] +2024-11-22 11:20:56.981161: Epoch time: 19.62 s +2024-11-22 11:20:57.819308: +2024-11-22 11:20:57.819506: Epoch 4444 +2024-11-22 11:20:57.819616: Current learning rate: 0.00482 +2024-11-22 11:21:15.930420: train_loss -0.7932 +2024-11-22 11:21:15.930621: val_loss -0.7557 +2024-11-22 11:21:15.930699: Pseudo dice [0.8594] +2024-11-22 11:21:15.930774: Epoch time: 18.11 s +2024-11-22 11:21:16.756642: +2024-11-22 11:21:16.756846: Epoch 4445 +2024-11-22 11:21:16.756958: Current learning rate: 0.00482 +2024-11-22 11:21:36.702850: train_loss -0.7798 +2024-11-22 11:21:36.703057: val_loss -0.7562 +2024-11-22 11:21:36.703142: Pseudo dice [0.8562] +2024-11-22 11:21:36.703215: Epoch time: 19.95 s +2024-11-22 11:21:37.538234: +2024-11-22 11:21:37.538433: Epoch 4446 +2024-11-22 11:21:37.538552: Current learning rate: 0.00482 +2024-11-22 11:21:56.101533: train_loss -0.7832 +2024-11-22 11:21:56.101756: val_loss -0.765 +2024-11-22 11:21:56.101835: Pseudo dice [0.8607] +2024-11-22 11:21:56.101912: Epoch time: 18.56 s +2024-11-22 11:21:57.036921: +2024-11-22 11:21:57.037150: Epoch 4447 +2024-11-22 11:21:57.037262: Current learning rate: 0.00482 +2024-11-22 11:22:14.968047: train_loss -0.7895 +2024-11-22 11:22:14.968368: val_loss -0.7784 +2024-11-22 11:22:14.968448: Pseudo dice [0.8566] +2024-11-22 11:22:14.968532: Epoch time: 17.93 s +2024-11-22 11:22:15.805688: +2024-11-22 11:22:15.805900: Epoch 4448 +2024-11-22 11:22:15.806009: Current learning rate: 0.00482 +2024-11-22 11:22:34.067558: train_loss -0.7824 +2024-11-22 11:22:34.069933: val_loss -0.7618 +2024-11-22 11:22:34.070048: Pseudo dice [0.8645] +2024-11-22 11:22:34.070133: Epoch time: 18.26 s +2024-11-22 11:22:35.364918: +2024-11-22 11:22:35.365130: Epoch 4449 +2024-11-22 11:22:35.365242: Current learning rate: 0.00481 +2024-11-22 11:22:55.210235: train_loss -0.7836 +2024-11-22 11:22:55.210458: val_loss -0.7865 +2024-11-22 11:22:55.210562: Pseudo dice [0.8648] +2024-11-22 11:22:55.210640: Epoch time: 19.85 s +2024-11-22 11:22:56.318202: +2024-11-22 11:22:56.318469: Epoch 4450 +2024-11-22 11:22:56.318584: Current learning rate: 0.00481 +2024-11-22 11:23:15.311578: train_loss -0.7923 +2024-11-22 11:23:15.311804: val_loss -0.7552 +2024-11-22 11:23:15.311883: Pseudo dice [0.8524] +2024-11-22 11:23:15.311962: Epoch time: 18.99 s +2024-11-22 11:23:16.158615: +2024-11-22 11:23:16.158856: Epoch 4451 +2024-11-22 11:23:16.158970: Current learning rate: 0.00481 +2024-11-22 11:23:34.526850: train_loss -0.7884 +2024-11-22 11:23:34.527077: val_loss -0.7759 +2024-11-22 11:23:34.527151: Pseudo dice [0.8551] +2024-11-22 11:23:34.527228: Epoch time: 18.37 s +2024-11-22 11:23:35.356223: +2024-11-22 11:23:35.356464: Epoch 4452 +2024-11-22 11:23:35.356579: Current learning rate: 0.00481 +2024-11-22 11:23:54.971116: train_loss -0.7888 +2024-11-22 11:23:54.971328: val_loss -0.7696 +2024-11-22 11:23:54.971406: Pseudo dice [0.8554] +2024-11-22 11:23:54.976625: Epoch time: 19.62 s +2024-11-22 11:23:55.828276: +2024-11-22 11:23:55.828470: Epoch 4453 +2024-11-22 11:23:55.828585: Current learning rate: 0.00481 +2024-11-22 11:24:13.921257: train_loss -0.7811 +2024-11-22 11:24:13.921470: val_loss -0.752 +2024-11-22 11:24:13.921550: Pseudo dice [0.8586] +2024-11-22 11:24:13.921625: Epoch time: 18.09 s +2024-11-22 11:24:14.758022: +2024-11-22 11:24:14.758222: Epoch 4454 +2024-11-22 11:24:14.758334: Current learning rate: 0.00481 +2024-11-22 11:24:32.905747: train_loss -0.803 +2024-11-22 11:24:32.905973: val_loss -0.7898 +2024-11-22 11:24:32.906048: Pseudo dice [0.86] +2024-11-22 11:24:32.906133: Epoch time: 18.15 s +2024-11-22 11:24:33.862418: +2024-11-22 11:24:33.862646: Epoch 4455 +2024-11-22 11:24:33.862757: Current learning rate: 0.00481 +2024-11-22 11:24:53.094869: train_loss -0.7734 +2024-11-22 11:24:53.095120: val_loss -0.7787 +2024-11-22 11:24:53.095202: Pseudo dice [0.846] +2024-11-22 11:24:53.095285: Epoch time: 19.23 s +2024-11-22 11:24:53.937474: +2024-11-22 11:24:53.937668: Epoch 4456 +2024-11-22 11:24:53.937778: Current learning rate: 0.00481 +2024-11-22 11:25:13.591423: train_loss -0.7686 +2024-11-22 11:25:13.591628: val_loss -0.756 +2024-11-22 11:25:13.591700: Pseudo dice [0.8477] +2024-11-22 11:25:13.591772: Epoch time: 19.65 s +2024-11-22 11:25:14.423484: +2024-11-22 11:25:14.423672: Epoch 4457 +2024-11-22 11:25:14.423780: Current learning rate: 0.0048 +2024-11-22 11:25:33.407910: train_loss -0.7745 +2024-11-22 11:25:33.408122: val_loss -0.7754 +2024-11-22 11:25:33.408235: Pseudo dice [0.8588] +2024-11-22 11:25:33.408312: Epoch time: 18.99 s +2024-11-22 11:25:34.248235: +2024-11-22 11:25:34.248453: Epoch 4458 +2024-11-22 11:25:34.248562: Current learning rate: 0.0048 +2024-11-22 11:25:53.186074: train_loss -0.778 +2024-11-22 11:25:53.186287: val_loss -0.7418 +2024-11-22 11:25:53.186367: Pseudo dice [0.8422] +2024-11-22 11:25:53.186443: Epoch time: 18.94 s +2024-11-22 11:25:54.018615: +2024-11-22 11:25:54.018842: Epoch 4459 +2024-11-22 11:25:54.018960: Current learning rate: 0.0048 +2024-11-22 11:26:12.269202: train_loss -0.7752 +2024-11-22 11:26:12.269434: val_loss -0.7613 +2024-11-22 11:26:12.269515: Pseudo dice [0.8431] +2024-11-22 11:26:12.269593: Epoch time: 18.25 s +2024-11-22 11:26:13.104783: +2024-11-22 11:26:13.105014: Epoch 4460 +2024-11-22 11:26:13.105133: Current learning rate: 0.0048 +2024-11-22 11:26:32.301366: train_loss -0.7675 +2024-11-22 11:26:32.301583: val_loss -0.7493 +2024-11-22 11:26:32.301658: Pseudo dice [0.8427] +2024-11-22 11:26:32.301733: Epoch time: 19.2 s +2024-11-22 11:26:33.530825: +2024-11-22 11:26:33.531022: Epoch 4461 +2024-11-22 11:26:33.531149: Current learning rate: 0.0048 +2024-11-22 11:26:52.118136: train_loss -0.7853 +2024-11-22 11:26:52.118429: val_loss -0.7616 +2024-11-22 11:26:52.118513: Pseudo dice [0.8385] +2024-11-22 11:26:52.118594: Epoch time: 18.59 s +2024-11-22 11:26:52.947287: +2024-11-22 11:26:52.947491: Epoch 4462 +2024-11-22 11:26:52.947599: Current learning rate: 0.0048 +2024-11-22 11:27:10.327646: train_loss -0.7784 +2024-11-22 11:27:10.327881: val_loss -0.7609 +2024-11-22 11:27:10.327956: Pseudo dice [0.863] +2024-11-22 11:27:10.328038: Epoch time: 17.38 s +2024-11-22 11:27:11.163621: +2024-11-22 11:27:11.163846: Epoch 4463 +2024-11-22 11:27:11.163957: Current learning rate: 0.0048 +2024-11-22 11:27:30.536877: train_loss -0.7722 +2024-11-22 11:27:30.537097: val_loss -0.7604 +2024-11-22 11:27:30.537198: Pseudo dice [0.8489] +2024-11-22 11:27:30.537276: Epoch time: 19.37 s +2024-11-22 11:27:31.365192: +2024-11-22 11:27:31.365404: Epoch 4464 +2024-11-22 11:27:31.365771: Current learning rate: 0.0048 +2024-11-22 11:27:48.927067: train_loss -0.7761 +2024-11-22 11:27:48.927278: val_loss -0.7528 +2024-11-22 11:27:48.927356: Pseudo dice [0.8514] +2024-11-22 11:27:48.927433: Epoch time: 17.56 s +2024-11-22 11:27:49.766064: +2024-11-22 11:27:49.766268: Epoch 4465 +2024-11-22 11:27:49.766379: Current learning rate: 0.00479 +2024-11-22 11:28:08.730932: train_loss -0.7778 +2024-11-22 11:28:08.731228: val_loss -0.7923 +2024-11-22 11:28:08.731307: Pseudo dice [0.852] +2024-11-22 11:28:08.731384: Epoch time: 18.97 s +2024-11-22 11:28:09.568975: +2024-11-22 11:28:09.569180: Epoch 4466 +2024-11-22 11:28:09.569290: Current learning rate: 0.00479 +2024-11-22 11:28:27.657889: train_loss -0.7911 +2024-11-22 11:28:27.658259: val_loss -0.7806 +2024-11-22 11:28:27.658345: Pseudo dice [0.8563] +2024-11-22 11:28:27.658434: Epoch time: 18.08 s +2024-11-22 11:28:28.534383: +2024-11-22 11:28:28.534580: Epoch 4467 +2024-11-22 11:28:28.534691: Current learning rate: 0.00479 +2024-11-22 11:28:47.825898: train_loss -0.7818 +2024-11-22 11:28:47.826120: val_loss -0.7409 +2024-11-22 11:28:47.826196: Pseudo dice [0.8374] +2024-11-22 11:28:47.826272: Epoch time: 19.29 s +2024-11-22 11:28:48.694539: +2024-11-22 11:28:48.694747: Epoch 4468 +2024-11-22 11:28:48.694862: Current learning rate: 0.00479 +2024-11-22 11:29:07.302371: train_loss -0.7742 +2024-11-22 11:29:07.302579: val_loss -0.7756 +2024-11-22 11:29:07.302691: Pseudo dice [0.8585] +2024-11-22 11:29:07.302827: Epoch time: 18.61 s +2024-11-22 11:29:08.137422: +2024-11-22 11:29:08.137694: Epoch 4469 +2024-11-22 11:29:08.137808: Current learning rate: 0.00479 +2024-11-22 11:29:26.392948: train_loss -0.7798 +2024-11-22 11:29:26.393163: val_loss -0.7696 +2024-11-22 11:29:26.393236: Pseudo dice [0.843] +2024-11-22 11:29:26.393311: Epoch time: 18.26 s +2024-11-22 11:29:27.225449: +2024-11-22 11:29:27.225658: Epoch 4470 +2024-11-22 11:29:27.225765: Current learning rate: 0.00479 +2024-11-22 11:29:46.446507: train_loss -0.7815 +2024-11-22 11:29:46.446760: val_loss -0.7898 +2024-11-22 11:29:46.446835: Pseudo dice [0.8414] +2024-11-22 11:29:46.446916: Epoch time: 19.22 s +2024-11-22 11:29:47.320908: +2024-11-22 11:29:47.321141: Epoch 4471 +2024-11-22 11:29:47.321256: Current learning rate: 0.00479 +2024-11-22 11:30:06.154093: train_loss -0.795 +2024-11-22 11:30:06.154301: val_loss -0.7805 +2024-11-22 11:30:06.154375: Pseudo dice [0.8607] +2024-11-22 11:30:06.154450: Epoch time: 18.83 s +2024-11-22 11:30:07.086556: +2024-11-22 11:30:07.086776: Epoch 4472 +2024-11-22 11:30:07.086887: Current learning rate: 0.00479 +2024-11-22 11:30:24.907968: train_loss -0.7949 +2024-11-22 11:30:24.908189: val_loss -0.7815 +2024-11-22 11:30:24.908267: Pseudo dice [0.8599] +2024-11-22 11:30:24.908345: Epoch time: 17.82 s +2024-11-22 11:30:26.127090: +2024-11-22 11:30:26.127323: Epoch 4473 +2024-11-22 11:30:26.127439: Current learning rate: 0.00479 +2024-11-22 11:30:44.965461: train_loss -0.7928 +2024-11-22 11:30:44.965707: val_loss -0.7741 +2024-11-22 11:30:44.965783: Pseudo dice [0.8491] +2024-11-22 11:30:44.965864: Epoch time: 18.84 s +2024-11-22 11:30:45.802851: +2024-11-22 11:30:45.803094: Epoch 4474 +2024-11-22 11:30:45.803215: Current learning rate: 0.00478 +2024-11-22 11:31:04.354899: train_loss -0.7825 +2024-11-22 11:31:04.355120: val_loss -0.7741 +2024-11-22 11:31:04.355200: Pseudo dice [0.8571] +2024-11-22 11:31:04.360421: Epoch time: 18.55 s +2024-11-22 11:31:05.245580: +2024-11-22 11:31:05.245776: Epoch 4475 +2024-11-22 11:31:05.245886: Current learning rate: 0.00478 +2024-11-22 11:31:22.696112: train_loss -0.7865 +2024-11-22 11:31:22.696336: val_loss -0.7741 +2024-11-22 11:31:22.696413: Pseudo dice [0.852] +2024-11-22 11:31:22.696494: Epoch time: 17.45 s +2024-11-22 11:31:23.548244: +2024-11-22 11:31:23.548487: Epoch 4476 +2024-11-22 11:31:23.548602: Current learning rate: 0.00478 +2024-11-22 11:31:42.791776: train_loss -0.7926 +2024-11-22 11:31:42.792004: val_loss -0.7821 +2024-11-22 11:31:42.792087: Pseudo dice [0.8428] +2024-11-22 11:31:42.792171: Epoch time: 19.24 s +2024-11-22 11:31:43.677658: +2024-11-22 11:31:43.677844: Epoch 4477 +2024-11-22 11:31:43.677953: Current learning rate: 0.00478 +2024-11-22 11:32:01.535562: train_loss -0.7962 +2024-11-22 11:32:01.535797: val_loss -0.7719 +2024-11-22 11:32:01.535872: Pseudo dice [0.853] +2024-11-22 11:32:01.535947: Epoch time: 17.86 s +2024-11-22 11:32:02.410092: +2024-11-22 11:32:02.410336: Epoch 4478 +2024-11-22 11:32:02.410459: Current learning rate: 0.00478 +2024-11-22 11:32:21.191318: train_loss -0.7944 +2024-11-22 11:32:21.191527: val_loss -0.7705 +2024-11-22 11:32:21.191598: Pseudo dice [0.8468] +2024-11-22 11:32:21.191671: Epoch time: 18.78 s +2024-11-22 11:32:22.150256: +2024-11-22 11:32:22.150470: Epoch 4479 +2024-11-22 11:32:22.150579: Current learning rate: 0.00478 +2024-11-22 11:32:40.513761: train_loss -0.7934 +2024-11-22 11:32:40.513975: val_loss -0.7661 +2024-11-22 11:32:40.514054: Pseudo dice [0.8478] +2024-11-22 11:32:40.514139: Epoch time: 18.36 s +2024-11-22 11:32:41.345444: +2024-11-22 11:32:41.345654: Epoch 4480 +2024-11-22 11:32:41.345768: Current learning rate: 0.00478 +2024-11-22 11:32:59.619401: train_loss -0.7895 +2024-11-22 11:32:59.619615: val_loss -0.784 +2024-11-22 11:32:59.619693: Pseudo dice [0.8538] +2024-11-22 11:32:59.619769: Epoch time: 18.27 s +2024-11-22 11:33:00.624115: +2024-11-22 11:33:00.624307: Epoch 4481 +2024-11-22 11:33:00.624415: Current learning rate: 0.00478 +2024-11-22 11:33:18.762579: train_loss -0.7855 +2024-11-22 11:33:18.762810: val_loss -0.779 +2024-11-22 11:33:18.762890: Pseudo dice [0.8563] +2024-11-22 11:33:18.763029: Epoch time: 18.14 s +2024-11-22 11:33:19.594213: +2024-11-22 11:33:19.594442: Epoch 4482 +2024-11-22 11:33:19.594555: Current learning rate: 0.00477 +2024-11-22 11:33:38.027202: train_loss -0.7887 +2024-11-22 11:33:38.027411: val_loss -0.7468 +2024-11-22 11:33:38.027488: Pseudo dice [0.8559] +2024-11-22 11:33:38.027562: Epoch time: 18.43 s +2024-11-22 11:33:38.854483: +2024-11-22 11:33:38.854684: Epoch 4483 +2024-11-22 11:33:38.854792: Current learning rate: 0.00477 +2024-11-22 11:33:56.961342: train_loss -0.7976 +2024-11-22 11:33:56.961571: val_loss -0.7569 +2024-11-22 11:33:56.961706: Pseudo dice [0.8502] +2024-11-22 11:33:56.961779: Epoch time: 18.11 s +2024-11-22 11:33:57.792456: +2024-11-22 11:33:57.792664: Epoch 4484 +2024-11-22 11:33:57.792775: Current learning rate: 0.00477 +2024-11-22 11:34:15.471051: train_loss -0.7883 +2024-11-22 11:34:15.471312: val_loss -0.7832 +2024-11-22 11:34:15.471389: Pseudo dice [0.8535] +2024-11-22 11:34:15.471467: Epoch time: 17.68 s +2024-11-22 11:34:16.773727: +2024-11-22 11:34:16.774177: Epoch 4485 +2024-11-22 11:34:16.774309: Current learning rate: 0.00477 +2024-11-22 11:34:35.065209: train_loss -0.7952 +2024-11-22 11:34:35.065435: val_loss -0.7809 +2024-11-22 11:34:35.065540: Pseudo dice [0.8564] +2024-11-22 11:34:35.065619: Epoch time: 18.29 s +2024-11-22 11:34:35.906680: +2024-11-22 11:34:35.907120: Epoch 4486 +2024-11-22 11:34:35.907255: Current learning rate: 0.00477 +2024-11-22 11:34:54.195422: train_loss -0.7709 +2024-11-22 11:34:54.195634: val_loss -0.7579 +2024-11-22 11:34:54.195719: Pseudo dice [0.8348] +2024-11-22 11:34:54.195799: Epoch time: 18.29 s +2024-11-22 11:34:55.028813: +2024-11-22 11:34:55.029235: Epoch 4487 +2024-11-22 11:34:55.029362: Current learning rate: 0.00477 +2024-11-22 11:35:13.548647: train_loss -0.7729 +2024-11-22 11:35:13.548862: val_loss -0.7688 +2024-11-22 11:35:13.548935: Pseudo dice [0.8462] +2024-11-22 11:35:13.549011: Epoch time: 18.52 s +2024-11-22 11:35:14.485759: +2024-11-22 11:35:14.486200: Epoch 4488 +2024-11-22 11:35:14.486333: Current learning rate: 0.00477 +2024-11-22 11:35:33.562514: train_loss -0.7846 +2024-11-22 11:35:33.562745: val_loss -0.762 +2024-11-22 11:35:33.562827: Pseudo dice [0.8594] +2024-11-22 11:35:33.562915: Epoch time: 19.08 s +2024-11-22 11:35:34.399531: +2024-11-22 11:35:34.399995: Epoch 4489 +2024-11-22 11:35:34.400137: Current learning rate: 0.00477 +2024-11-22 11:35:52.971417: train_loss -0.7844 +2024-11-22 11:35:52.971653: val_loss -0.7967 +2024-11-22 11:35:52.971733: Pseudo dice [0.8625] +2024-11-22 11:35:52.971809: Epoch time: 18.57 s +2024-11-22 11:35:53.807477: +2024-11-22 11:35:53.807882: Epoch 4490 +2024-11-22 11:35:53.808243: Current learning rate: 0.00476 +2024-11-22 11:36:13.470700: train_loss -0.7903 +2024-11-22 11:36:13.470912: val_loss -0.7734 +2024-11-22 11:36:13.470987: Pseudo dice [0.8478] +2024-11-22 11:36:13.471074: Epoch time: 19.66 s +2024-11-22 11:36:14.299774: +2024-11-22 11:36:14.300185: Epoch 4491 +2024-11-22 11:36:14.300314: Current learning rate: 0.00476 +2024-11-22 11:36:33.989110: train_loss -0.7862 +2024-11-22 11:36:33.989388: val_loss -0.7732 +2024-11-22 11:36:33.989467: Pseudo dice [0.8533] +2024-11-22 11:36:33.989542: Epoch time: 19.69 s +2024-11-22 11:36:34.832828: +2024-11-22 11:36:34.833292: Epoch 4492 +2024-11-22 11:36:34.833431: Current learning rate: 0.00476 +2024-11-22 11:36:52.860406: train_loss -0.7722 +2024-11-22 11:36:52.860646: val_loss -0.7621 +2024-11-22 11:36:52.860723: Pseudo dice [0.8628] +2024-11-22 11:36:52.860805: Epoch time: 18.03 s +2024-11-22 11:36:53.741361: +2024-11-22 11:36:53.741784: Epoch 4493 +2024-11-22 11:36:53.741929: Current learning rate: 0.00476 +2024-11-22 11:37:11.793587: train_loss -0.7832 +2024-11-22 11:37:11.793798: val_loss -0.7563 +2024-11-22 11:37:11.793874: Pseudo dice [0.841] +2024-11-22 11:37:11.793949: Epoch time: 18.05 s +2024-11-22 11:37:12.725047: +2024-11-22 11:37:12.725464: Epoch 4494 +2024-11-22 11:37:12.725590: Current learning rate: 0.00476 +2024-11-22 11:37:30.966283: train_loss -0.7927 +2024-11-22 11:37:30.966506: val_loss -0.7918 +2024-11-22 11:37:30.966587: Pseudo dice [0.8553] +2024-11-22 11:37:30.978127: Epoch time: 18.24 s +2024-11-22 11:37:31.906070: +2024-11-22 11:37:31.906557: Epoch 4495 +2024-11-22 11:37:31.906691: Current learning rate: 0.00476 +2024-11-22 11:37:51.070622: train_loss -0.7945 +2024-11-22 11:37:51.070836: val_loss -0.7602 +2024-11-22 11:37:51.070910: Pseudo dice [0.8403] +2024-11-22 11:37:51.076213: Epoch time: 19.17 s +2024-11-22 11:37:52.017494: +2024-11-22 11:37:52.017759: Epoch 4496 +2024-11-22 11:37:52.017870: Current learning rate: 0.00476 +2024-11-22 11:38:10.207950: train_loss -0.7853 +2024-11-22 11:38:10.208169: val_loss -0.7745 +2024-11-22 11:38:10.208246: Pseudo dice [0.8568] +2024-11-22 11:38:10.208323: Epoch time: 18.19 s +2024-11-22 11:38:11.487322: +2024-11-22 11:38:11.487582: Epoch 4497 +2024-11-22 11:38:11.487737: Current learning rate: 0.00476 +2024-11-22 11:38:29.780283: train_loss -0.7745 +2024-11-22 11:38:29.780536: val_loss -0.761 +2024-11-22 11:38:29.780617: Pseudo dice [0.8546] +2024-11-22 11:38:29.780696: Epoch time: 18.29 s +2024-11-22 11:38:30.607787: +2024-11-22 11:38:30.607991: Epoch 4498 +2024-11-22 11:38:30.608107: Current learning rate: 0.00475 +2024-11-22 11:38:49.532053: train_loss -0.7693 +2024-11-22 11:38:49.532267: val_loss -0.7543 +2024-11-22 11:38:49.532341: Pseudo dice [0.8392] +2024-11-22 11:38:49.532418: Epoch time: 18.93 s +2024-11-22 11:38:50.366635: +2024-11-22 11:38:50.366860: Epoch 4499 +2024-11-22 11:38:50.366972: Current learning rate: 0.00475 +2024-11-22 11:39:09.497941: train_loss -0.771 +2024-11-22 11:39:09.498155: val_loss -0.7874 +2024-11-22 11:39:09.498229: Pseudo dice [0.8626] +2024-11-22 11:39:09.498303: Epoch time: 19.13 s +2024-11-22 11:39:10.601712: +2024-11-22 11:39:10.601918: Epoch 4500 +2024-11-22 11:39:10.602031: Current learning rate: 0.00475 +2024-11-22 11:39:28.755453: train_loss -0.7791 +2024-11-22 11:39:28.755669: val_loss -0.7719 +2024-11-22 11:39:28.755744: Pseudo dice [0.8485] +2024-11-22 11:39:28.755827: Epoch time: 18.15 s +2024-11-22 11:39:29.620105: +2024-11-22 11:39:29.620328: Epoch 4501 +2024-11-22 11:39:29.620442: Current learning rate: 0.00475 +2024-11-22 11:39:47.756872: train_loss -0.7872 +2024-11-22 11:39:47.757115: val_loss -0.7675 +2024-11-22 11:39:47.757191: Pseudo dice [0.8441] +2024-11-22 11:39:47.757267: Epoch time: 18.14 s +2024-11-22 11:39:48.781343: +2024-11-22 11:39:48.781591: Epoch 4502 +2024-11-22 11:39:48.781708: Current learning rate: 0.00475 +2024-11-22 11:40:07.033731: train_loss -0.7788 +2024-11-22 11:40:07.036144: val_loss -0.7481 +2024-11-22 11:40:07.036238: Pseudo dice [0.8567] +2024-11-22 11:40:07.036315: Epoch time: 18.25 s +2024-11-22 11:40:07.902512: +2024-11-22 11:40:07.902735: Epoch 4503 +2024-11-22 11:40:07.902850: Current learning rate: 0.00475 +2024-11-22 11:40:26.909091: train_loss -0.7867 +2024-11-22 11:40:26.909298: val_loss -0.7482 +2024-11-22 11:40:26.909373: Pseudo dice [0.8417] +2024-11-22 11:40:26.909445: Epoch time: 19.01 s +2024-11-22 11:40:27.734907: +2024-11-22 11:40:27.735094: Epoch 4504 +2024-11-22 11:40:27.735226: Current learning rate: 0.00475 +2024-11-22 11:40:46.594652: train_loss -0.7758 +2024-11-22 11:40:46.594893: val_loss -0.7658 +2024-11-22 11:40:46.594969: Pseudo dice [0.8539] +2024-11-22 11:40:46.595052: Epoch time: 18.86 s +2024-11-22 11:40:47.434369: +2024-11-22 11:40:47.434574: Epoch 4505 +2024-11-22 11:40:47.434684: Current learning rate: 0.00475 +2024-11-22 11:41:04.769684: train_loss -0.7919 +2024-11-22 11:41:04.769891: val_loss -0.7368 +2024-11-22 11:41:04.769970: Pseudo dice [0.8509] +2024-11-22 11:41:04.770043: Epoch time: 17.34 s +2024-11-22 11:41:05.600728: +2024-11-22 11:41:05.600932: Epoch 4506 +2024-11-22 11:41:05.601040: Current learning rate: 0.00474 +2024-11-22 11:41:22.885754: train_loss -0.7923 +2024-11-22 11:41:22.885959: val_loss -0.7625 +2024-11-22 11:41:22.886031: Pseudo dice [0.8621] +2024-11-22 11:41:22.886111: Epoch time: 17.29 s +2024-11-22 11:41:23.726222: +2024-11-22 11:41:23.726441: Epoch 4507 +2024-11-22 11:41:23.726558: Current learning rate: 0.00474 +2024-11-22 11:41:42.464874: train_loss -0.7864 +2024-11-22 11:41:42.465170: val_loss -0.7755 +2024-11-22 11:41:42.465255: Pseudo dice [0.8635] +2024-11-22 11:41:42.465329: Epoch time: 18.74 s +2024-11-22 11:41:43.300259: +2024-11-22 11:41:43.300474: Epoch 4508 +2024-11-22 11:41:43.300587: Current learning rate: 0.00474 +2024-11-22 11:42:02.506989: train_loss -0.7844 +2024-11-22 11:42:02.507251: val_loss -0.7788 +2024-11-22 11:42:02.507330: Pseudo dice [0.8598] +2024-11-22 11:42:02.507416: Epoch time: 19.21 s +2024-11-22 11:42:03.750396: +2024-11-22 11:42:03.750620: Epoch 4509 +2024-11-22 11:42:03.750728: Current learning rate: 0.00474 +2024-11-22 11:42:20.981461: train_loss -0.794 +2024-11-22 11:42:20.986855: val_loss -0.7733 +2024-11-22 11:42:20.987009: Pseudo dice [0.8483] +2024-11-22 11:42:20.987096: Epoch time: 17.23 s +2024-11-22 11:42:22.007682: +2024-11-22 11:42:22.007932: Epoch 4510 +2024-11-22 11:42:22.008047: Current learning rate: 0.00474 +2024-11-22 11:42:39.924466: train_loss -0.7852 +2024-11-22 11:42:39.924676: val_loss -0.7324 +2024-11-22 11:42:39.924749: Pseudo dice [0.857] +2024-11-22 11:42:39.924826: Epoch time: 17.92 s +2024-11-22 11:42:40.752722: +2024-11-22 11:42:40.752956: Epoch 4511 +2024-11-22 11:42:40.753072: Current learning rate: 0.00474 +2024-11-22 11:42:58.974031: train_loss -0.7839 +2024-11-22 11:42:58.974249: val_loss -0.7594 +2024-11-22 11:42:58.974324: Pseudo dice [0.8536] +2024-11-22 11:42:58.974401: Epoch time: 18.22 s +2024-11-22 11:42:59.809272: +2024-11-22 11:42:59.809473: Epoch 4512 +2024-11-22 11:42:59.809583: Current learning rate: 0.00474 +2024-11-22 11:43:19.329012: train_loss -0.7804 +2024-11-22 11:43:19.329255: val_loss -0.7899 +2024-11-22 11:43:19.329334: Pseudo dice [0.8575] +2024-11-22 11:43:19.329417: Epoch time: 19.52 s +2024-11-22 11:43:20.167285: +2024-11-22 11:43:20.167501: Epoch 4513 +2024-11-22 11:43:20.167614: Current learning rate: 0.00474 +2024-11-22 11:43:37.384827: train_loss -0.7925 +2024-11-22 11:43:37.385043: val_loss -0.7422 +2024-11-22 11:43:37.385121: Pseudo dice [0.8396] +2024-11-22 11:43:37.385195: Epoch time: 17.22 s +2024-11-22 11:43:38.222084: +2024-11-22 11:43:38.222292: Epoch 4514 +2024-11-22 11:43:38.222405: Current learning rate: 0.00473 +2024-11-22 11:43:56.816662: train_loss -0.7879 +2024-11-22 11:43:56.816878: val_loss -0.7537 +2024-11-22 11:43:56.816951: Pseudo dice [0.8561] +2024-11-22 11:43:56.817026: Epoch time: 18.6 s +2024-11-22 11:43:57.662898: +2024-11-22 11:43:57.663115: Epoch 4515 +2024-11-22 11:43:57.663232: Current learning rate: 0.00473 +2024-11-22 11:44:15.765934: train_loss -0.7902 +2024-11-22 11:44:15.766152: val_loss -0.7583 +2024-11-22 11:44:15.766227: Pseudo dice [0.8489] +2024-11-22 11:44:15.766300: Epoch time: 18.1 s +2024-11-22 11:44:16.596917: +2024-11-22 11:44:16.597349: Epoch 4516 +2024-11-22 11:44:16.597469: Current learning rate: 0.00473 +2024-11-22 11:44:35.024923: train_loss -0.7866 +2024-11-22 11:44:35.025174: val_loss -0.7712 +2024-11-22 11:44:35.025252: Pseudo dice [0.8475] +2024-11-22 11:44:35.025335: Epoch time: 18.43 s +2024-11-22 11:44:35.861845: +2024-11-22 11:44:35.862041: Epoch 4517 +2024-11-22 11:44:35.862155: Current learning rate: 0.00473 +2024-11-22 11:44:54.859004: train_loss -0.7929 +2024-11-22 11:44:54.861436: val_loss -0.7484 +2024-11-22 11:44:54.861570: Pseudo dice [0.8582] +2024-11-22 11:44:54.861652: Epoch time: 19.0 s +2024-11-22 11:44:55.876110: +2024-11-22 11:44:55.876324: Epoch 4518 +2024-11-22 11:44:55.876437: Current learning rate: 0.00473 +2024-11-22 11:45:13.691155: train_loss -0.7706 +2024-11-22 11:45:13.691402: val_loss -0.7697 +2024-11-22 11:45:13.691479: Pseudo dice [0.8718] +2024-11-22 11:45:13.691556: Epoch time: 17.82 s +2024-11-22 11:45:14.535309: +2024-11-22 11:45:14.535496: Epoch 4519 +2024-11-22 11:45:14.535604: Current learning rate: 0.00473 +2024-11-22 11:45:33.333796: train_loss -0.7687 +2024-11-22 11:45:33.334021: val_loss -0.7717 +2024-11-22 11:45:33.334102: Pseudo dice [0.8511] +2024-11-22 11:45:33.334179: Epoch time: 18.8 s +2024-11-22 11:45:34.166821: +2024-11-22 11:45:34.167046: Epoch 4520 +2024-11-22 11:45:34.167160: Current learning rate: 0.00473 +2024-11-22 11:45:52.264587: train_loss -0.7874 +2024-11-22 11:45:52.264832: val_loss -0.7747 +2024-11-22 11:45:52.264909: Pseudo dice [0.8533] +2024-11-22 11:45:52.264988: Epoch time: 18.1 s +2024-11-22 11:45:53.489974: +2024-11-22 11:45:53.490224: Epoch 4521 +2024-11-22 11:45:53.490336: Current learning rate: 0.00473 +2024-11-22 11:46:11.997115: train_loss -0.7903 +2024-11-22 11:46:11.997324: val_loss -0.7667 +2024-11-22 11:46:11.997406: Pseudo dice [0.8561] +2024-11-22 11:46:11.997483: Epoch time: 18.51 s +2024-11-22 11:46:12.828312: +2024-11-22 11:46:12.828553: Epoch 4522 +2024-11-22 11:46:12.828669: Current learning rate: 0.00473 +2024-11-22 11:46:31.362031: train_loss -0.7877 +2024-11-22 11:46:31.362253: val_loss -0.7634 +2024-11-22 11:46:31.362334: Pseudo dice [0.8342] +2024-11-22 11:46:31.362411: Epoch time: 18.53 s +2024-11-22 11:46:32.203785: +2024-11-22 11:46:32.204000: Epoch 4523 +2024-11-22 11:46:32.204117: Current learning rate: 0.00472 +2024-11-22 11:46:51.904456: train_loss -0.7875 +2024-11-22 11:46:51.906891: val_loss -0.7394 +2024-11-22 11:46:51.906977: Pseudo dice [0.8457] +2024-11-22 11:46:51.907073: Epoch time: 19.7 s +2024-11-22 11:46:52.763453: +2024-11-22 11:46:52.763665: Epoch 4524 +2024-11-22 11:46:52.763774: Current learning rate: 0.00472 +2024-11-22 11:47:10.166946: train_loss -0.7915 +2024-11-22 11:47:10.167167: val_loss -0.7892 +2024-11-22 11:47:10.167246: Pseudo dice [0.8461] +2024-11-22 11:47:10.167325: Epoch time: 17.4 s +2024-11-22 11:47:10.998590: +2024-11-22 11:47:10.998814: Epoch 4525 +2024-11-22 11:47:10.998924: Current learning rate: 0.00472 +2024-11-22 11:47:29.505315: train_loss -0.7807 +2024-11-22 11:47:29.505523: val_loss -0.7401 +2024-11-22 11:47:29.505601: Pseudo dice [0.8454] +2024-11-22 11:47:29.505675: Epoch time: 18.51 s +2024-11-22 11:47:30.344563: +2024-11-22 11:47:30.344778: Epoch 4526 +2024-11-22 11:47:30.344888: Current learning rate: 0.00472 +2024-11-22 11:47:47.181900: train_loss -0.7881 +2024-11-22 11:47:47.182153: val_loss -0.7836 +2024-11-22 11:47:47.182232: Pseudo dice [0.8482] +2024-11-22 11:47:47.182307: Epoch time: 16.84 s +2024-11-22 11:47:48.016055: +2024-11-22 11:47:48.016252: Epoch 4527 +2024-11-22 11:47:48.016360: Current learning rate: 0.00472 +2024-11-22 11:48:06.892199: train_loss -0.7786 +2024-11-22 11:48:06.892470: val_loss -0.7499 +2024-11-22 11:48:06.892547: Pseudo dice [0.8467] +2024-11-22 11:48:06.892630: Epoch time: 18.88 s +2024-11-22 11:48:07.733800: +2024-11-22 11:48:07.734004: Epoch 4528 +2024-11-22 11:48:07.734118: Current learning rate: 0.00472 +2024-11-22 11:48:25.440633: train_loss -0.7841 +2024-11-22 11:48:25.440873: val_loss -0.7547 +2024-11-22 11:48:25.440948: Pseudo dice [0.8466] +2024-11-22 11:48:25.441026: Epoch time: 17.71 s +2024-11-22 11:48:26.324780: +2024-11-22 11:48:26.324989: Epoch 4529 +2024-11-22 11:48:26.325103: Current learning rate: 0.00472 +2024-11-22 11:48:44.697649: train_loss -0.7901 +2024-11-22 11:48:44.697856: val_loss -0.7737 +2024-11-22 11:48:44.697931: Pseudo dice [0.8465] +2024-11-22 11:48:44.698004: Epoch time: 18.37 s +2024-11-22 11:48:45.534714: +2024-11-22 11:48:45.534935: Epoch 4530 +2024-11-22 11:48:45.535048: Current learning rate: 0.00472 +2024-11-22 11:49:04.818965: train_loss -0.7883 +2024-11-22 11:49:04.819264: val_loss -0.7579 +2024-11-22 11:49:04.819345: Pseudo dice [0.8475] +2024-11-22 11:49:04.819419: Epoch time: 19.29 s +2024-11-22 11:49:05.652294: +2024-11-22 11:49:05.652521: Epoch 4531 +2024-11-22 11:49:05.652632: Current learning rate: 0.00471 +2024-11-22 11:49:24.110670: train_loss -0.7893 +2024-11-22 11:49:24.110885: val_loss -0.764 +2024-11-22 11:49:24.110960: Pseudo dice [0.8567] +2024-11-22 11:49:24.111036: Epoch time: 18.46 s +2024-11-22 11:49:25.090935: +2024-11-22 11:49:25.091172: Epoch 4532 +2024-11-22 11:49:25.091282: Current learning rate: 0.00471 +2024-11-22 11:49:43.220908: train_loss -0.7876 +2024-11-22 11:49:43.222786: val_loss -0.7885 +2024-11-22 11:49:43.222895: Pseudo dice [0.8623] +2024-11-22 11:49:43.222978: Epoch time: 18.13 s +2024-11-22 11:49:44.519424: +2024-11-22 11:49:44.519907: Epoch 4533 +2024-11-22 11:49:44.520043: Current learning rate: 0.00471 +2024-11-22 11:50:03.659624: train_loss -0.7813 +2024-11-22 11:50:03.659900: val_loss -0.7811 +2024-11-22 11:50:03.659982: Pseudo dice [0.8574] +2024-11-22 11:50:03.660069: Epoch time: 19.14 s +2024-11-22 11:50:04.537282: +2024-11-22 11:50:04.537752: Epoch 4534 +2024-11-22 11:50:04.537883: Current learning rate: 0.00471 +2024-11-22 11:50:22.980470: train_loss -0.7907 +2024-11-22 11:50:22.980691: val_loss -0.8015 +2024-11-22 11:50:22.980764: Pseudo dice [0.8626] +2024-11-22 11:50:22.980837: Epoch time: 18.44 s +2024-11-22 11:50:23.807946: +2024-11-22 11:50:23.808365: Epoch 4535 +2024-11-22 11:50:23.808492: Current learning rate: 0.00471 +2024-11-22 11:50:43.198978: train_loss -0.7832 +2024-11-22 11:50:43.199224: val_loss -0.7563 +2024-11-22 11:50:43.199307: Pseudo dice [0.8428] +2024-11-22 11:50:43.199394: Epoch time: 19.39 s +2024-11-22 11:50:44.037556: +2024-11-22 11:50:44.038023: Epoch 4536 +2024-11-22 11:50:44.038162: Current learning rate: 0.00471 +2024-11-22 11:51:03.029751: train_loss -0.7982 +2024-11-22 11:51:03.029967: val_loss -0.7808 +2024-11-22 11:51:03.030046: Pseudo dice [0.8634] +2024-11-22 11:51:03.030126: Epoch time: 18.99 s +2024-11-22 11:51:03.885670: +2024-11-22 11:51:03.886072: Epoch 4537 +2024-11-22 11:51:03.886224: Current learning rate: 0.00471 +2024-11-22 11:51:22.002618: train_loss -0.7937 +2024-11-22 11:51:22.002817: val_loss -0.7822 +2024-11-22 11:51:22.002891: Pseudo dice [0.8507] +2024-11-22 11:51:22.002965: Epoch time: 18.12 s +2024-11-22 11:51:22.857566: +2024-11-22 11:51:22.857975: Epoch 4538 +2024-11-22 11:51:22.858110: Current learning rate: 0.00471 +2024-11-22 11:51:41.267525: train_loss -0.7889 +2024-11-22 11:51:41.267743: val_loss -0.7584 +2024-11-22 11:51:41.267818: Pseudo dice [0.8451] +2024-11-22 11:51:41.267892: Epoch time: 18.41 s +2024-11-22 11:51:42.175280: +2024-11-22 11:51:42.175696: Epoch 4539 +2024-11-22 11:51:42.175826: Current learning rate: 0.0047 +2024-11-22 11:52:00.361346: train_loss -0.7873 +2024-11-22 11:52:00.364572: val_loss -0.7755 +2024-11-22 11:52:00.364699: Pseudo dice [0.8552] +2024-11-22 11:52:00.364788: Epoch time: 18.19 s +2024-11-22 11:52:01.344946: +2024-11-22 11:52:01.345405: Epoch 4540 +2024-11-22 11:52:01.345542: Current learning rate: 0.0047 +2024-11-22 11:52:20.565291: train_loss -0.7903 +2024-11-22 11:52:20.565504: val_loss -0.7649 +2024-11-22 11:52:20.565576: Pseudo dice [0.8583] +2024-11-22 11:52:20.565648: Epoch time: 19.22 s +2024-11-22 11:52:21.424017: +2024-11-22 11:52:21.424523: Epoch 4541 +2024-11-22 11:52:21.424660: Current learning rate: 0.0047 +2024-11-22 11:52:40.200372: train_loss -0.786 +2024-11-22 11:52:40.200581: val_loss -0.755 +2024-11-22 11:52:40.200659: Pseudo dice [0.8435] +2024-11-22 11:52:40.200741: Epoch time: 18.78 s +2024-11-22 11:52:41.034236: +2024-11-22 11:52:41.034683: Epoch 4542 +2024-11-22 11:52:41.034817: Current learning rate: 0.0047 +2024-11-22 11:52:59.196056: train_loss -0.7923 +2024-11-22 11:52:59.196277: val_loss -0.7722 +2024-11-22 11:52:59.196352: Pseudo dice [0.8599] +2024-11-22 11:52:59.196425: Epoch time: 18.16 s +2024-11-22 11:53:00.026039: +2024-11-22 11:53:00.026470: Epoch 4543 +2024-11-22 11:53:00.026606: Current learning rate: 0.0047 +2024-11-22 11:53:18.773335: train_loss -0.7959 +2024-11-22 11:53:18.773575: val_loss -0.7711 +2024-11-22 11:53:18.773654: Pseudo dice [0.8615] +2024-11-22 11:53:18.773741: Epoch time: 18.75 s +2024-11-22 11:53:19.609869: +2024-11-22 11:53:19.610365: Epoch 4544 +2024-11-22 11:53:19.610500: Current learning rate: 0.0047 +2024-11-22 11:53:37.153351: train_loss -0.7838 +2024-11-22 11:53:37.153564: val_loss -0.7444 +2024-11-22 11:53:37.153638: Pseudo dice [0.8458] +2024-11-22 11:53:37.153711: Epoch time: 17.54 s +2024-11-22 11:53:38.382441: +2024-11-22 11:53:38.382672: Epoch 4545 +2024-11-22 11:53:38.382787: Current learning rate: 0.0047 +2024-11-22 11:53:56.745800: train_loss -0.7856 +2024-11-22 11:53:56.746016: val_loss -0.7713 +2024-11-22 11:53:56.746102: Pseudo dice [0.8533] +2024-11-22 11:53:56.746179: Epoch time: 18.36 s +2024-11-22 11:53:57.622174: +2024-11-22 11:53:57.622374: Epoch 4546 +2024-11-22 11:53:57.622484: Current learning rate: 0.0047 +2024-11-22 11:54:16.925579: train_loss -0.7867 +2024-11-22 11:54:16.925788: val_loss -0.7793 +2024-11-22 11:54:16.925865: Pseudo dice [0.8472] +2024-11-22 11:54:16.925941: Epoch time: 19.3 s +2024-11-22 11:54:17.762570: +2024-11-22 11:54:17.762766: Epoch 4547 +2024-11-22 11:54:17.762874: Current learning rate: 0.00469 +2024-11-22 11:54:35.926795: train_loss -0.791 +2024-11-22 11:54:35.927026: val_loss -0.7556 +2024-11-22 11:54:35.927108: Pseudo dice [0.8593] +2024-11-22 11:54:35.927191: Epoch time: 18.17 s +2024-11-22 11:54:36.761892: +2024-11-22 11:54:36.762104: Epoch 4548 +2024-11-22 11:54:36.762214: Current learning rate: 0.00469 +2024-11-22 11:54:55.022013: train_loss -0.7905 +2024-11-22 11:54:55.022218: val_loss -0.7659 +2024-11-22 11:54:55.022292: Pseudo dice [0.8527] +2024-11-22 11:54:55.022366: Epoch time: 18.26 s +2024-11-22 11:54:56.056115: +2024-11-22 11:54:56.056314: Epoch 4549 +2024-11-22 11:54:56.056424: Current learning rate: 0.00469 +2024-11-22 11:55:14.072746: train_loss -0.7936 +2024-11-22 11:55:14.072964: val_loss -0.7401 +2024-11-22 11:55:14.073038: Pseudo dice [0.8567] +2024-11-22 11:55:14.073119: Epoch time: 18.02 s +2024-11-22 11:55:15.210433: +2024-11-22 11:55:15.210662: Epoch 4550 +2024-11-22 11:55:15.210767: Current learning rate: 0.00469 +2024-11-22 11:55:34.719297: train_loss -0.7854 +2024-11-22 11:55:34.719501: val_loss -0.7511 +2024-11-22 11:55:34.719575: Pseudo dice [0.8316] +2024-11-22 11:55:34.719650: Epoch time: 19.51 s +2024-11-22 11:55:35.551700: +2024-11-22 11:55:35.551935: Epoch 4551 +2024-11-22 11:55:35.552062: Current learning rate: 0.00469 +2024-11-22 11:55:54.497342: train_loss -0.7846 +2024-11-22 11:55:54.497570: val_loss -0.7639 +2024-11-22 11:55:54.497648: Pseudo dice [0.8442] +2024-11-22 11:55:54.497783: Epoch time: 18.95 s +2024-11-22 11:55:55.335075: +2024-11-22 11:55:55.335273: Epoch 4552 +2024-11-22 11:55:55.335386: Current learning rate: 0.00469 +2024-11-22 11:56:14.547890: train_loss -0.7983 +2024-11-22 11:56:14.548102: val_loss -0.7895 +2024-11-22 11:56:14.548181: Pseudo dice [0.8636] +2024-11-22 11:56:14.548258: Epoch time: 19.21 s +2024-11-22 11:56:15.383512: +2024-11-22 11:56:15.383723: Epoch 4553 +2024-11-22 11:56:15.383834: Current learning rate: 0.00469 +2024-11-22 11:56:33.584335: train_loss -0.7932 +2024-11-22 11:56:33.584544: val_loss -0.7507 +2024-11-22 11:56:33.584617: Pseudo dice [0.8569] +2024-11-22 11:56:33.584691: Epoch time: 18.2 s +2024-11-22 11:56:34.413944: +2024-11-22 11:56:34.414156: Epoch 4554 +2024-11-22 11:56:34.414266: Current learning rate: 0.00469 +2024-11-22 11:56:53.501910: train_loss -0.7805 +2024-11-22 11:56:53.502126: val_loss -0.7724 +2024-11-22 11:56:53.502205: Pseudo dice [0.8607] +2024-11-22 11:56:53.502284: Epoch time: 19.09 s +2024-11-22 11:56:54.339419: +2024-11-22 11:56:54.339696: Epoch 4555 +2024-11-22 11:56:54.339811: Current learning rate: 0.00468 +2024-11-22 11:57:13.365396: train_loss -0.7827 +2024-11-22 11:57:13.365644: val_loss -0.7761 +2024-11-22 11:57:13.365716: Pseudo dice [0.8417] +2024-11-22 11:57:13.365796: Epoch time: 19.03 s +2024-11-22 11:57:14.214347: +2024-11-22 11:57:14.214557: Epoch 4556 +2024-11-22 11:57:14.214666: Current learning rate: 0.00468 +2024-11-22 11:57:33.312277: train_loss -0.775 +2024-11-22 11:57:33.314687: val_loss -0.789 +2024-11-22 11:57:33.314781: Pseudo dice [0.8532] +2024-11-22 11:57:33.314857: Epoch time: 19.1 s +2024-11-22 11:57:34.673826: +2024-11-22 11:57:34.674036: Epoch 4557 +2024-11-22 11:57:34.674149: Current learning rate: 0.00468 +2024-11-22 11:57:52.449809: train_loss -0.7783 +2024-11-22 11:57:52.450030: val_loss -0.752 +2024-11-22 11:57:52.450107: Pseudo dice [0.852] +2024-11-22 11:57:52.450181: Epoch time: 17.78 s +2024-11-22 11:57:53.285054: +2024-11-22 11:57:53.285260: Epoch 4558 +2024-11-22 11:57:53.285372: Current learning rate: 0.00468 +2024-11-22 11:58:10.935521: train_loss -0.7766 +2024-11-22 11:58:10.940894: val_loss -0.775 +2024-11-22 11:58:10.941094: Pseudo dice [0.8515] +2024-11-22 11:58:10.941187: Epoch time: 17.65 s +2024-11-22 11:58:11.898277: +2024-11-22 11:58:11.898556: Epoch 4559 +2024-11-22 11:58:11.898712: Current learning rate: 0.00468 +2024-11-22 11:58:30.636295: train_loss -0.7888 +2024-11-22 11:58:30.636513: val_loss -0.7591 +2024-11-22 11:58:30.636591: Pseudo dice [0.8469] +2024-11-22 11:58:30.636669: Epoch time: 18.74 s +2024-11-22 11:58:31.468638: +2024-11-22 11:58:31.468834: Epoch 4560 +2024-11-22 11:58:31.468948: Current learning rate: 0.00468 +2024-11-22 11:58:50.132049: train_loss -0.783 +2024-11-22 11:58:50.132257: val_loss -0.7759 +2024-11-22 11:58:50.132333: Pseudo dice [0.8581] +2024-11-22 11:58:50.132408: Epoch time: 18.66 s +2024-11-22 11:58:51.000321: +2024-11-22 11:58:51.000525: Epoch 4561 +2024-11-22 11:58:51.000638: Current learning rate: 0.00468 +2024-11-22 11:59:09.955887: train_loss -0.772 +2024-11-22 11:59:09.956106: val_loss -0.7644 +2024-11-22 11:59:09.956182: Pseudo dice [0.8481] +2024-11-22 11:59:09.956257: Epoch time: 18.96 s +2024-11-22 11:59:10.793358: +2024-11-22 11:59:10.793538: Epoch 4562 +2024-11-22 11:59:10.793643: Current learning rate: 0.00468 +2024-11-22 11:59:29.317233: train_loss -0.7723 +2024-11-22 11:59:29.317462: val_loss -0.7762 +2024-11-22 11:59:29.317545: Pseudo dice [0.8557] +2024-11-22 11:59:29.317621: Epoch time: 18.52 s +2024-11-22 11:59:30.157936: +2024-11-22 11:59:30.158174: Epoch 4563 +2024-11-22 11:59:30.158285: Current learning rate: 0.00467 +2024-11-22 11:59:50.077957: train_loss -0.783 +2024-11-22 11:59:50.078195: val_loss -0.7681 +2024-11-22 11:59:50.078272: Pseudo dice [0.8587] +2024-11-22 11:59:50.078358: Epoch time: 19.92 s +2024-11-22 11:59:50.911709: +2024-11-22 11:59:50.911927: Epoch 4564 +2024-11-22 11:59:50.912039: Current learning rate: 0.00467 +2024-11-22 12:00:10.169642: train_loss -0.7789 +2024-11-22 12:00:10.169851: val_loss -0.7705 +2024-11-22 12:00:10.169995: Pseudo dice [0.8623] +2024-11-22 12:00:10.170076: Epoch time: 19.26 s +2024-11-22 12:00:10.999454: +2024-11-22 12:00:10.999675: Epoch 4565 +2024-11-22 12:00:10.999788: Current learning rate: 0.00467 +2024-11-22 12:00:29.003178: train_loss -0.7885 +2024-11-22 12:00:29.003385: val_loss -0.7759 +2024-11-22 12:00:29.003507: Pseudo dice [0.8547] +2024-11-22 12:00:29.003579: Epoch time: 18.0 s +2024-11-22 12:00:29.837328: +2024-11-22 12:00:29.837551: Epoch 4566 +2024-11-22 12:00:29.837664: Current learning rate: 0.00467 +2024-11-22 12:00:49.556440: train_loss -0.7964 +2024-11-22 12:00:49.556666: val_loss -0.7562 +2024-11-22 12:00:49.556745: Pseudo dice [0.8663] +2024-11-22 12:00:49.559002: Epoch time: 19.72 s +2024-11-22 12:00:50.422010: +2024-11-22 12:00:50.422225: Epoch 4567 +2024-11-22 12:00:50.422338: Current learning rate: 0.00467 +2024-11-22 12:01:09.026312: train_loss -0.7829 +2024-11-22 12:01:09.026554: val_loss -0.7644 +2024-11-22 12:01:09.026633: Pseudo dice [0.851] +2024-11-22 12:01:09.026711: Epoch time: 18.61 s +2024-11-22 12:01:09.855513: +2024-11-22 12:01:09.855740: Epoch 4568 +2024-11-22 12:01:09.855859: Current learning rate: 0.00467 +2024-11-22 12:01:28.826995: train_loss -0.7857 +2024-11-22 12:01:28.827269: val_loss -0.78 +2024-11-22 12:01:28.827348: Pseudo dice [0.8585] +2024-11-22 12:01:28.827426: Epoch time: 18.97 s +2024-11-22 12:01:30.084309: +2024-11-22 12:01:30.084554: Epoch 4569 +2024-11-22 12:01:30.084665: Current learning rate: 0.00467 +2024-11-22 12:01:49.447014: train_loss -0.7893 +2024-11-22 12:01:49.447332: val_loss -0.7537 +2024-11-22 12:01:49.447411: Pseudo dice [0.8559] +2024-11-22 12:01:49.447485: Epoch time: 19.36 s +2024-11-22 12:01:50.294334: +2024-11-22 12:01:50.294538: Epoch 4570 +2024-11-22 12:01:50.294650: Current learning rate: 0.00467 +2024-11-22 12:02:09.788352: train_loss -0.792 +2024-11-22 12:02:09.788594: val_loss -0.7588 +2024-11-22 12:02:09.788674: Pseudo dice [0.8393] +2024-11-22 12:02:09.788766: Epoch time: 19.49 s +2024-11-22 12:02:10.636866: +2024-11-22 12:02:10.637113: Epoch 4571 +2024-11-22 12:02:10.637226: Current learning rate: 0.00467 +2024-11-22 12:02:29.574617: train_loss -0.7848 +2024-11-22 12:02:29.574820: val_loss -0.7544 +2024-11-22 12:02:29.574895: Pseudo dice [0.8402] +2024-11-22 12:02:29.574968: Epoch time: 18.94 s +2024-11-22 12:02:30.418978: +2024-11-22 12:02:30.419224: Epoch 4572 +2024-11-22 12:02:30.419335: Current learning rate: 0.00466 +2024-11-22 12:02:49.631361: train_loss -0.7793 +2024-11-22 12:02:49.631571: val_loss -0.7703 +2024-11-22 12:02:49.631644: Pseudo dice [0.8432] +2024-11-22 12:02:49.631718: Epoch time: 19.21 s +2024-11-22 12:02:50.485287: +2024-11-22 12:02:50.485481: Epoch 4573 +2024-11-22 12:02:50.485589: Current learning rate: 0.00466 +2024-11-22 12:03:08.762756: train_loss -0.7795 +2024-11-22 12:03:08.762968: val_loss -0.7549 +2024-11-22 12:03:08.763044: Pseudo dice [0.8391] +2024-11-22 12:03:08.763128: Epoch time: 18.28 s +2024-11-22 12:03:09.608318: +2024-11-22 12:03:09.608496: Epoch 4574 +2024-11-22 12:03:09.608604: Current learning rate: 0.00466 +2024-11-22 12:03:28.284945: train_loss -0.7555 +2024-11-22 12:03:28.285167: val_loss -0.758 +2024-11-22 12:03:28.285244: Pseudo dice [0.8417] +2024-11-22 12:03:28.285324: Epoch time: 18.68 s +2024-11-22 12:03:29.143590: +2024-11-22 12:03:29.143792: Epoch 4575 +2024-11-22 12:03:29.143901: Current learning rate: 0.00466 +2024-11-22 12:03:47.809572: train_loss -0.765 +2024-11-22 12:03:47.809810: val_loss -0.7259 +2024-11-22 12:03:47.809885: Pseudo dice [0.848] +2024-11-22 12:03:47.809965: Epoch time: 18.67 s +2024-11-22 12:03:48.683304: +2024-11-22 12:03:48.683505: Epoch 4576 +2024-11-22 12:03:48.683619: Current learning rate: 0.00466 +2024-11-22 12:04:07.546798: train_loss -0.7756 +2024-11-22 12:04:07.547000: val_loss -0.782 +2024-11-22 12:04:07.553096: Pseudo dice [0.8537] +2024-11-22 12:04:07.553198: Epoch time: 18.86 s +2024-11-22 12:04:08.403556: +2024-11-22 12:04:08.403776: Epoch 4577 +2024-11-22 12:04:08.403885: Current learning rate: 0.00466 +2024-11-22 12:04:26.318297: train_loss -0.7792 +2024-11-22 12:04:26.318508: val_loss -0.7662 +2024-11-22 12:04:26.318586: Pseudo dice [0.8496] +2024-11-22 12:04:26.318665: Epoch time: 17.92 s +2024-11-22 12:04:27.166489: +2024-11-22 12:04:27.166690: Epoch 4578 +2024-11-22 12:04:27.166802: Current learning rate: 0.00466 +2024-11-22 12:04:46.967208: train_loss -0.7848 +2024-11-22 12:04:46.967418: val_loss -0.7842 +2024-11-22 12:04:46.967493: Pseudo dice [0.8449] +2024-11-22 12:04:46.967569: Epoch time: 19.8 s +2024-11-22 12:04:47.814895: +2024-11-22 12:04:47.815176: Epoch 4579 +2024-11-22 12:04:47.815290: Current learning rate: 0.00466 +2024-11-22 12:05:07.116932: train_loss -0.7902 +2024-11-22 12:05:07.117175: val_loss -0.7654 +2024-11-22 12:05:07.117258: Pseudo dice [0.8474] +2024-11-22 12:05:07.119537: Epoch time: 19.3 s +2024-11-22 12:05:08.106376: +2024-11-22 12:05:08.106599: Epoch 4580 +2024-11-22 12:05:08.106712: Current learning rate: 0.00465 +2024-11-22 12:05:26.746064: train_loss -0.7892 +2024-11-22 12:05:26.746270: val_loss -0.7775 +2024-11-22 12:05:26.746347: Pseudo dice [0.859] +2024-11-22 12:05:26.746422: Epoch time: 18.64 s +2024-11-22 12:05:27.976790: +2024-11-22 12:05:27.977070: Epoch 4581 +2024-11-22 12:05:27.977188: Current learning rate: 0.00465 +2024-11-22 12:05:45.781971: train_loss -0.7852 +2024-11-22 12:05:45.782234: val_loss -0.7681 +2024-11-22 12:05:45.782310: Pseudo dice [0.8536] +2024-11-22 12:05:45.782387: Epoch time: 17.81 s +2024-11-22 12:05:46.621812: +2024-11-22 12:05:46.622036: Epoch 4582 +2024-11-22 12:05:46.622153: Current learning rate: 0.00465 +2024-11-22 12:06:04.614005: train_loss -0.7822 +2024-11-22 12:06:04.614222: val_loss -0.7666 +2024-11-22 12:06:04.614297: Pseudo dice [0.846] +2024-11-22 12:06:04.614375: Epoch time: 17.99 s +2024-11-22 12:06:05.570804: +2024-11-22 12:06:05.571039: Epoch 4583 +2024-11-22 12:06:05.571156: Current learning rate: 0.00465 +2024-11-22 12:06:23.848052: train_loss -0.7817 +2024-11-22 12:06:23.848279: val_loss -0.7933 +2024-11-22 12:06:23.848356: Pseudo dice [0.8575] +2024-11-22 12:06:23.848435: Epoch time: 18.28 s +2024-11-22 12:06:24.687031: +2024-11-22 12:06:24.687266: Epoch 4584 +2024-11-22 12:06:24.687385: Current learning rate: 0.00465 +2024-11-22 12:06:42.426245: train_loss -0.767 +2024-11-22 12:06:42.426455: val_loss -0.7417 +2024-11-22 12:06:42.426532: Pseudo dice [0.8327] +2024-11-22 12:06:42.426606: Epoch time: 17.74 s +2024-11-22 12:06:43.258573: +2024-11-22 12:06:43.258796: Epoch 4585 +2024-11-22 12:06:43.258904: Current learning rate: 0.00465 +2024-11-22 12:07:01.432369: train_loss -0.771 +2024-11-22 12:07:01.432581: val_loss -0.7776 +2024-11-22 12:07:01.432654: Pseudo dice [0.8483] +2024-11-22 12:07:01.432728: Epoch time: 18.17 s +2024-11-22 12:07:02.281835: +2024-11-22 12:07:02.282020: Epoch 4586 +2024-11-22 12:07:02.282134: Current learning rate: 0.00465 +2024-11-22 12:07:20.342072: train_loss -0.7726 +2024-11-22 12:07:20.342292: val_loss -0.7616 +2024-11-22 12:07:20.342369: Pseudo dice [0.8439] +2024-11-22 12:07:20.342448: Epoch time: 18.06 s +2024-11-22 12:07:21.192953: +2024-11-22 12:07:21.193188: Epoch 4587 +2024-11-22 12:07:21.193301: Current learning rate: 0.00465 +2024-11-22 12:07:39.617265: train_loss -0.7721 +2024-11-22 12:07:39.617507: val_loss -0.7588 +2024-11-22 12:07:39.617582: Pseudo dice [0.8481] +2024-11-22 12:07:39.625783: Epoch time: 18.43 s +2024-11-22 12:07:40.525921: +2024-11-22 12:07:40.526134: Epoch 4588 +2024-11-22 12:07:40.526249: Current learning rate: 0.00464 +2024-11-22 12:07:58.972643: train_loss -0.7774 +2024-11-22 12:07:58.972851: val_loss -0.7886 +2024-11-22 12:07:58.972943: Pseudo dice [0.8533] +2024-11-22 12:07:58.973019: Epoch time: 18.45 s +2024-11-22 12:07:59.824623: +2024-11-22 12:07:59.824890: Epoch 4589 +2024-11-22 12:07:59.825001: Current learning rate: 0.00464 +2024-11-22 12:08:17.866206: train_loss -0.7883 +2024-11-22 12:08:17.866419: val_loss -0.7633 +2024-11-22 12:08:17.866493: Pseudo dice [0.8512] +2024-11-22 12:08:17.866568: Epoch time: 18.04 s +2024-11-22 12:08:18.712105: +2024-11-22 12:08:18.712315: Epoch 4590 +2024-11-22 12:08:18.712428: Current learning rate: 0.00464 +2024-11-22 12:08:36.627765: train_loss -0.7858 +2024-11-22 12:08:36.628017: val_loss -0.7608 +2024-11-22 12:08:36.628099: Pseudo dice [0.8359] +2024-11-22 12:08:36.628180: Epoch time: 17.92 s +2024-11-22 12:08:37.504627: +2024-11-22 12:08:37.504839: Epoch 4591 +2024-11-22 12:08:37.504946: Current learning rate: 0.00464 +2024-11-22 12:08:57.967180: train_loss -0.7859 +2024-11-22 12:08:57.967401: val_loss -0.7808 +2024-11-22 12:08:57.967484: Pseudo dice [0.8516] +2024-11-22 12:08:57.967562: Epoch time: 20.46 s +2024-11-22 12:08:58.827889: +2024-11-22 12:08:58.828126: Epoch 4592 +2024-11-22 12:08:58.828240: Current learning rate: 0.00464 +2024-11-22 12:09:17.521474: train_loss -0.7882 +2024-11-22 12:09:17.521686: val_loss -0.7962 +2024-11-22 12:09:17.521760: Pseudo dice [0.8587] +2024-11-22 12:09:17.521833: Epoch time: 18.69 s +2024-11-22 12:09:18.743504: +2024-11-22 12:09:18.743710: Epoch 4593 +2024-11-22 12:09:18.743820: Current learning rate: 0.00464 +2024-11-22 12:09:37.097045: train_loss -0.7804 +2024-11-22 12:09:37.097283: val_loss -0.7689 +2024-11-22 12:09:37.097359: Pseudo dice [0.8425] +2024-11-22 12:09:37.097504: Epoch time: 18.35 s +2024-11-22 12:09:37.937657: +2024-11-22 12:09:37.937872: Epoch 4594 +2024-11-22 12:09:37.937984: Current learning rate: 0.00464 +2024-11-22 12:09:57.415624: train_loss -0.7823 +2024-11-22 12:09:57.415859: val_loss -0.7752 +2024-11-22 12:09:57.415939: Pseudo dice [0.8559] +2024-11-22 12:09:57.416020: Epoch time: 19.48 s +2024-11-22 12:09:58.254503: +2024-11-22 12:09:58.254753: Epoch 4595 +2024-11-22 12:09:58.254862: Current learning rate: 0.00464 +2024-11-22 12:10:17.128220: train_loss -0.7681 +2024-11-22 12:10:17.128435: val_loss -0.7744 +2024-11-22 12:10:17.130679: Pseudo dice [0.8453] +2024-11-22 12:10:17.130777: Epoch time: 18.87 s +2024-11-22 12:10:18.139207: +2024-11-22 12:10:18.139418: Epoch 4596 +2024-11-22 12:10:18.139528: Current learning rate: 0.00463 +2024-11-22 12:10:35.389946: train_loss -0.7918 +2024-11-22 12:10:35.390166: val_loss -0.7652 +2024-11-22 12:10:35.390241: Pseudo dice [0.8576] +2024-11-22 12:10:35.390316: Epoch time: 17.25 s +2024-11-22 12:10:36.234252: +2024-11-22 12:10:36.234442: Epoch 4597 +2024-11-22 12:10:36.234552: Current learning rate: 0.00463 +2024-11-22 12:10:55.202409: train_loss -0.7931 +2024-11-22 12:10:55.202626: val_loss -0.7725 +2024-11-22 12:10:55.202706: Pseudo dice [0.8531] +2024-11-22 12:10:55.202780: Epoch time: 18.97 s +2024-11-22 12:10:56.043095: +2024-11-22 12:10:56.043322: Epoch 4598 +2024-11-22 12:10:56.043440: Current learning rate: 0.00463 +2024-11-22 12:11:14.022066: train_loss -0.7864 +2024-11-22 12:11:14.022306: val_loss -0.7842 +2024-11-22 12:11:14.022384: Pseudo dice [0.8536] +2024-11-22 12:11:14.022513: Epoch time: 17.98 s +2024-11-22 12:11:14.864393: +2024-11-22 12:11:14.864569: Epoch 4599 +2024-11-22 12:11:14.864680: Current learning rate: 0.00463 +2024-11-22 12:11:34.530717: train_loss -0.7978 +2024-11-22 12:11:34.530928: val_loss -0.7749 +2024-11-22 12:11:34.531004: Pseudo dice [0.8595] +2024-11-22 12:11:34.531090: Epoch time: 19.67 s +2024-11-22 12:11:35.690570: +2024-11-22 12:11:35.690777: Epoch 4600 +2024-11-22 12:11:35.690886: Current learning rate: 0.00463 +2024-11-22 12:11:53.859963: train_loss -0.7959 +2024-11-22 12:11:53.860193: val_loss -0.7721 +2024-11-22 12:11:53.860269: Pseudo dice [0.8597] +2024-11-22 12:11:53.860407: Epoch time: 18.17 s +2024-11-22 12:11:54.690419: +2024-11-22 12:11:54.690645: Epoch 4601 +2024-11-22 12:11:54.690756: Current learning rate: 0.00463 +2024-11-22 12:12:13.591071: train_loss -0.7944 +2024-11-22 12:12:13.591285: val_loss -0.7896 +2024-11-22 12:12:13.591362: Pseudo dice [0.8611] +2024-11-22 12:12:13.591437: Epoch time: 18.9 s +2024-11-22 12:12:14.432714: +2024-11-22 12:12:14.432901: Epoch 4602 +2024-11-22 12:12:14.433010: Current learning rate: 0.00463 +2024-11-22 12:12:32.334116: train_loss -0.797 +2024-11-22 12:12:32.334356: val_loss -0.7801 +2024-11-22 12:12:32.334433: Pseudo dice [0.8718] +2024-11-22 12:12:32.334516: Epoch time: 17.9 s +2024-11-22 12:12:33.176238: +2024-11-22 12:12:33.176450: Epoch 4603 +2024-11-22 12:12:33.176562: Current learning rate: 0.00463 +2024-11-22 12:12:51.041559: train_loss -0.7946 +2024-11-22 12:12:51.041765: val_loss -0.7433 +2024-11-22 12:12:51.041838: Pseudo dice [0.8532] +2024-11-22 12:12:51.041913: Epoch time: 17.87 s +2024-11-22 12:12:51.876580: +2024-11-22 12:12:51.876784: Epoch 4604 +2024-11-22 12:12:51.876896: Current learning rate: 0.00462 +2024-11-22 12:13:09.986395: train_loss -0.7881 +2024-11-22 12:13:09.986599: val_loss -0.7768 +2024-11-22 12:13:09.986672: Pseudo dice [0.863] +2024-11-22 12:13:09.986747: Epoch time: 18.11 s +2024-11-22 12:13:11.232998: +2024-11-22 12:13:11.233244: Epoch 4605 +2024-11-22 12:13:11.233360: Current learning rate: 0.00462 +2024-11-22 12:13:30.020813: train_loss -0.7642 +2024-11-22 12:13:30.021056: val_loss -0.7379 +2024-11-22 12:13:30.021141: Pseudo dice [0.8488] +2024-11-22 12:13:30.021230: Epoch time: 18.79 s +2024-11-22 12:13:30.857559: +2024-11-22 12:13:30.857757: Epoch 4606 +2024-11-22 12:13:30.857866: Current learning rate: 0.00462 +2024-11-22 12:13:48.858169: train_loss -0.7737 +2024-11-22 12:13:48.858370: val_loss -0.7767 +2024-11-22 12:13:48.858445: Pseudo dice [0.8524] +2024-11-22 12:13:48.858520: Epoch time: 18.0 s +2024-11-22 12:13:49.690810: +2024-11-22 12:13:49.691030: Epoch 4607 +2024-11-22 12:13:49.691147: Current learning rate: 0.00462 +2024-11-22 12:14:09.503622: train_loss -0.7812 +2024-11-22 12:14:09.503834: val_loss -0.7874 +2024-11-22 12:14:09.503911: Pseudo dice [0.8535] +2024-11-22 12:14:09.503983: Epoch time: 19.81 s +2024-11-22 12:14:10.336339: +2024-11-22 12:14:10.336547: Epoch 4608 +2024-11-22 12:14:10.336656: Current learning rate: 0.00462 +2024-11-22 12:14:29.430388: train_loss -0.7883 +2024-11-22 12:14:29.439500: val_loss -0.778 +2024-11-22 12:14:29.439631: Pseudo dice [0.8615] +2024-11-22 12:14:29.439719: Epoch time: 19.09 s +2024-11-22 12:14:30.499447: +2024-11-22 12:14:30.499718: Epoch 4609 +2024-11-22 12:14:30.499828: Current learning rate: 0.00462 +2024-11-22 12:14:48.724829: train_loss -0.7979 +2024-11-22 12:14:48.728887: val_loss -0.7664 +2024-11-22 12:14:48.728978: Pseudo dice [0.8503] +2024-11-22 12:14:48.729071: Epoch time: 18.23 s +2024-11-22 12:14:49.573599: +2024-11-22 12:14:49.573806: Epoch 4610 +2024-11-22 12:14:49.573919: Current learning rate: 0.00462 +2024-11-22 12:15:08.973443: train_loss -0.7855 +2024-11-22 12:15:08.979831: val_loss -0.7851 +2024-11-22 12:15:08.979946: Pseudo dice [0.8484] +2024-11-22 12:15:08.980026: Epoch time: 19.4 s +2024-11-22 12:15:09.975622: +2024-11-22 12:15:09.975836: Epoch 4611 +2024-11-22 12:15:09.975954: Current learning rate: 0.00462 +2024-11-22 12:15:27.927755: train_loss -0.7887 +2024-11-22 12:15:27.928016: val_loss -0.7965 +2024-11-22 12:15:27.928100: Pseudo dice [0.8676] +2024-11-22 12:15:27.928174: Epoch time: 17.95 s +2024-11-22 12:15:28.760587: +2024-11-22 12:15:28.760809: Epoch 4612 +2024-11-22 12:15:28.760924: Current learning rate: 0.00461 +2024-11-22 12:15:47.139728: train_loss -0.789 +2024-11-22 12:15:47.148296: val_loss -0.7986 +2024-11-22 12:15:47.148403: Pseudo dice [0.8545] +2024-11-22 12:15:47.148482: Epoch time: 18.38 s +2024-11-22 12:15:48.202337: +2024-11-22 12:15:48.202550: Epoch 4613 +2024-11-22 12:15:48.202659: Current learning rate: 0.00461 +2024-11-22 12:16:08.730303: train_loss -0.7881 +2024-11-22 12:16:08.746814: val_loss -0.7648 +2024-11-22 12:16:08.746961: Pseudo dice [0.8427] +2024-11-22 12:16:08.747080: Epoch time: 20.53 s +2024-11-22 12:16:09.890567: +2024-11-22 12:16:09.891004: Epoch 4614 +2024-11-22 12:16:09.891127: Current learning rate: 0.00461 +2024-11-22 12:16:29.662091: train_loss -0.7889 +2024-11-22 12:16:29.675311: val_loss -0.7723 +2024-11-22 12:16:29.675434: Pseudo dice [0.8542] +2024-11-22 12:16:29.675518: Epoch time: 19.77 s +2024-11-22 12:16:30.768132: +2024-11-22 12:16:30.768901: Epoch 4615 +2024-11-22 12:16:30.769013: Current learning rate: 0.00461 +2024-11-22 12:16:51.713931: train_loss -0.794 +2024-11-22 12:16:51.728322: val_loss -0.7697 +2024-11-22 12:16:51.728478: Pseudo dice [0.8633] +2024-11-22 12:16:51.728562: Epoch time: 20.95 s +2024-11-22 12:16:52.586906: +2024-11-22 12:16:52.587356: Epoch 4616 +2024-11-22 12:16:52.587494: Current learning rate: 0.00461 +2024-11-22 12:17:11.929278: train_loss -0.7885 +2024-11-22 12:17:11.942109: val_loss -0.7576 +2024-11-22 12:17:11.942273: Pseudo dice [0.8547] +2024-11-22 12:17:11.942374: Epoch time: 19.34 s +2024-11-22 12:17:13.445527: +2024-11-22 12:17:13.447068: Epoch 4617 +2024-11-22 12:17:13.447822: Current learning rate: 0.00461 +2024-11-22 12:17:34.007331: train_loss -0.7865 +2024-11-22 12:17:34.012131: val_loss -0.7737 +2024-11-22 12:17:34.012273: Pseudo dice [0.834] +2024-11-22 12:17:34.012370: Epoch time: 20.56 s +2024-11-22 12:17:35.084962: +2024-11-22 12:17:35.085474: Epoch 4618 +2024-11-22 12:17:35.085608: Current learning rate: 0.00461 +2024-11-22 12:17:56.156938: train_loss -0.7803 +2024-11-22 12:17:56.164595: val_loss -0.7585 +2024-11-22 12:17:56.164732: Pseudo dice [0.846] +2024-11-22 12:17:56.164829: Epoch time: 21.07 s +2024-11-22 12:17:57.004755: +2024-11-22 12:17:57.005232: Epoch 4619 +2024-11-22 12:17:57.005368: Current learning rate: 0.00461 +2024-11-22 12:18:15.505994: train_loss -0.7802 +2024-11-22 12:18:15.511280: val_loss -0.7607 +2024-11-22 12:18:15.511410: Pseudo dice [0.8547] +2024-11-22 12:18:15.511751: Epoch time: 18.5 s +2024-11-22 12:18:16.418153: +2024-11-22 12:18:16.419188: Epoch 4620 +2024-11-22 12:18:16.419320: Current learning rate: 0.00461 +2024-11-22 12:18:36.597443: train_loss -0.7917 +2024-11-22 12:18:36.599859: val_loss -0.7735 +2024-11-22 12:18:36.599966: Pseudo dice [0.857] +2024-11-22 12:18:36.600062: Epoch time: 20.18 s +2024-11-22 12:18:37.452168: +2024-11-22 12:18:37.453056: Epoch 4621 +2024-11-22 12:18:37.453189: Current learning rate: 0.0046 +2024-11-22 12:18:58.612381: train_loss -0.7929 +2024-11-22 12:18:58.619306: val_loss -0.7833 +2024-11-22 12:18:58.619463: Pseudo dice [0.8534] +2024-11-22 12:18:58.619568: Epoch time: 21.16 s +2024-11-22 12:18:59.482382: +2024-11-22 12:18:59.484845: Epoch 4622 +2024-11-22 12:18:59.484988: Current learning rate: 0.0046 +2024-11-22 12:19:18.791784: train_loss -0.7845 +2024-11-22 12:19:18.800496: val_loss -0.7688 +2024-11-22 12:19:18.800623: Pseudo dice [0.8604] +2024-11-22 12:19:18.800718: Epoch time: 19.31 s +2024-11-22 12:19:19.871191: +2024-11-22 12:19:19.872125: Epoch 4623 +2024-11-22 12:19:19.872245: Current learning rate: 0.0046 +2024-11-22 12:19:39.103056: train_loss -0.7897 +2024-11-22 12:19:39.115793: val_loss -0.7754 +2024-11-22 12:19:39.115928: Pseudo dice [0.8407] +2024-11-22 12:19:39.116024: Epoch time: 19.23 s +2024-11-22 12:19:39.967479: +2024-11-22 12:19:39.967924: Epoch 4624 +2024-11-22 12:19:39.968051: Current learning rate: 0.0046 +2024-11-22 12:19:59.756315: train_loss -0.7928 +2024-11-22 12:19:59.766186: val_loss -0.7617 +2024-11-22 12:19:59.766318: Pseudo dice [0.8486] +2024-11-22 12:19:59.766428: Epoch time: 19.79 s +2024-11-22 12:20:00.963633: +2024-11-22 12:20:00.964093: Epoch 4625 +2024-11-22 12:20:00.964214: Current learning rate: 0.0046 +2024-11-22 12:20:19.996063: train_loss -0.7918 +2024-11-22 12:20:20.012646: val_loss -0.7826 +2024-11-22 12:20:20.012799: Pseudo dice [0.8595] +2024-11-22 12:20:20.012897: Epoch time: 19.03 s +2024-11-22 12:20:21.210698: +2024-11-22 12:20:21.214220: Epoch 4626 +2024-11-22 12:20:21.214344: Current learning rate: 0.0046 +2024-11-22 12:20:40.562153: train_loss -0.7892 +2024-11-22 12:20:40.567744: val_loss -0.777 +2024-11-22 12:20:40.567878: Pseudo dice [0.8538] +2024-11-22 12:20:40.567967: Epoch time: 19.35 s +2024-11-22 12:20:41.480174: +2024-11-22 12:20:41.480927: Epoch 4627 +2024-11-22 12:20:41.481055: Current learning rate: 0.0046 +2024-11-22 12:21:00.515853: train_loss -0.7883 +2024-11-22 12:21:00.518702: val_loss -0.7805 +2024-11-22 12:21:00.518801: Pseudo dice [0.8532] +2024-11-22 12:21:00.518893: Epoch time: 19.04 s +2024-11-22 12:21:01.379542: +2024-11-22 12:21:01.380001: Epoch 4628 +2024-11-22 12:21:01.380122: Current learning rate: 0.0046 +2024-11-22 12:21:19.857033: train_loss -0.79 +2024-11-22 12:21:19.864370: val_loss -0.7705 +2024-11-22 12:21:19.864521: Pseudo dice [0.8511] +2024-11-22 12:21:19.864619: Epoch time: 18.48 s +2024-11-22 12:21:21.264531: +2024-11-22 12:21:21.268879: Epoch 4629 +2024-11-22 12:21:21.269005: Current learning rate: 0.00459 +2024-11-22 12:21:41.157791: train_loss -0.7927 +2024-11-22 12:21:41.163477: val_loss -0.7799 +2024-11-22 12:21:41.163625: Pseudo dice [0.8485] +2024-11-22 12:21:41.177420: Epoch time: 19.89 s +2024-11-22 12:21:42.034535: +2024-11-22 12:21:42.035026: Epoch 4630 +2024-11-22 12:21:42.035152: Current learning rate: 0.00459 +2024-11-22 12:22:01.920703: train_loss -0.7868 +2024-11-22 12:22:01.928272: val_loss -0.775 +2024-11-22 12:22:01.928384: Pseudo dice [0.8692] +2024-11-22 12:22:01.928475: Epoch time: 19.89 s +2024-11-22 12:22:02.865118: +2024-11-22 12:22:02.865608: Epoch 4631 +2024-11-22 12:22:02.865728: Current learning rate: 0.00459 +2024-11-22 12:22:23.411147: train_loss -0.7917 +2024-11-22 12:22:23.417598: val_loss -0.7698 +2024-11-22 12:22:23.417749: Pseudo dice [0.8608] +2024-11-22 12:22:23.417835: Epoch time: 20.55 s +2024-11-22 12:22:24.289218: +2024-11-22 12:22:24.292512: Epoch 4632 +2024-11-22 12:22:24.292644: Current learning rate: 0.00459 +2024-11-22 12:22:43.741310: train_loss -0.7856 +2024-11-22 12:22:43.748852: val_loss -0.7949 +2024-11-22 12:22:43.748975: Pseudo dice [0.8497] +2024-11-22 12:22:43.749077: Epoch time: 19.45 s +2024-11-22 12:22:44.695827: +2024-11-22 12:22:44.697313: Epoch 4633 +2024-11-22 12:22:44.697436: Current learning rate: 0.00459 +2024-11-22 12:23:03.306163: train_loss -0.7928 +2024-11-22 12:23:03.309304: val_loss -0.7721 +2024-11-22 12:23:03.309424: Pseudo dice [0.8481] +2024-11-22 12:23:03.309524: Epoch time: 18.61 s +2024-11-22 12:23:04.158073: +2024-11-22 12:23:04.159590: Epoch 4634 +2024-11-22 12:23:04.159717: Current learning rate: 0.00459 +2024-11-22 12:23:23.508401: train_loss -0.791 +2024-11-22 12:23:23.512318: val_loss -0.7818 +2024-11-22 12:23:23.512415: Pseudo dice [0.8489] +2024-11-22 12:23:23.512494: Epoch time: 19.35 s +2024-11-22 12:23:24.353616: +2024-11-22 12:23:24.354046: Epoch 4635 +2024-11-22 12:23:24.354176: Current learning rate: 0.00459 +2024-11-22 12:23:44.024623: train_loss -0.7976 +2024-11-22 12:23:44.030185: val_loss -0.7494 +2024-11-22 12:23:44.030294: Pseudo dice [0.8482] +2024-11-22 12:23:44.030378: Epoch time: 19.67 s +2024-11-22 12:23:44.887154: +2024-11-22 12:23:44.887607: Epoch 4636 +2024-11-22 12:23:44.887726: Current learning rate: 0.00459 +2024-11-22 12:24:04.247167: train_loss -0.7941 +2024-11-22 12:24:04.252608: val_loss -0.7988 +2024-11-22 12:24:04.252725: Pseudo dice [0.8726] +2024-11-22 12:24:04.252808: Epoch time: 19.36 s +2024-11-22 12:24:05.243871: +2024-11-22 12:24:05.244349: Epoch 4637 +2024-11-22 12:24:05.244468: Current learning rate: 0.00458 +2024-11-22 12:24:25.207509: train_loss -0.8033 +2024-11-22 12:24:25.214409: val_loss -0.7637 +2024-11-22 12:24:25.214564: Pseudo dice [0.8483] +2024-11-22 12:24:25.214665: Epoch time: 19.96 s +2024-11-22 12:24:26.082870: +2024-11-22 12:24:26.083336: Epoch 4638 +2024-11-22 12:24:26.083453: Current learning rate: 0.00458 +2024-11-22 12:24:45.693036: train_loss -0.7905 +2024-11-22 12:24:45.701017: val_loss -0.8035 +2024-11-22 12:24:45.701163: Pseudo dice [0.847] +2024-11-22 12:24:45.701250: Epoch time: 19.61 s +2024-11-22 12:24:46.633159: +2024-11-22 12:24:46.633937: Epoch 4639 +2024-11-22 12:24:46.634068: Current learning rate: 0.00458 +2024-11-22 12:25:05.957543: train_loss -0.8057 +2024-11-22 12:25:05.985905: val_loss -0.7776 +2024-11-22 12:25:05.986027: Pseudo dice [0.8516] +2024-11-22 12:25:05.986121: Epoch time: 19.33 s +2024-11-22 12:25:06.820738: +2024-11-22 12:25:06.821186: Epoch 4640 +2024-11-22 12:25:06.821314: Current learning rate: 0.00458 +2024-11-22 12:25:26.312896: train_loss -0.7909 +2024-11-22 12:25:26.319294: val_loss -0.7876 +2024-11-22 12:25:26.319419: Pseudo dice [0.8442] +2024-11-22 12:25:26.319505: Epoch time: 19.49 s +2024-11-22 12:25:27.721885: +2024-11-22 12:25:27.723734: Epoch 4641 +2024-11-22 12:25:27.723861: Current learning rate: 0.00458 +2024-11-22 12:25:47.313735: train_loss -0.7991 +2024-11-22 12:25:47.316599: val_loss -0.7762 +2024-11-22 12:25:47.316736: Pseudo dice [0.8637] +2024-11-22 12:25:47.316830: Epoch time: 19.59 s +2024-11-22 12:25:48.187159: +2024-11-22 12:25:48.189430: Epoch 4642 +2024-11-22 12:25:48.189552: Current learning rate: 0.00458 +2024-11-22 12:26:06.983941: train_loss -0.7981 +2024-11-22 12:26:07.011730: val_loss -0.766 +2024-11-22 12:26:07.011903: Pseudo dice [0.8503] +2024-11-22 12:26:07.011995: Epoch time: 18.8 s +2024-11-22 12:26:07.934628: +2024-11-22 12:26:07.935160: Epoch 4643 +2024-11-22 12:26:07.935280: Current learning rate: 0.00458 +2024-11-22 12:26:27.081010: train_loss -0.7956 +2024-11-22 12:26:27.086569: val_loss -0.7646 +2024-11-22 12:26:27.086700: Pseudo dice [0.8647] +2024-11-22 12:26:27.086782: Epoch time: 19.15 s +2024-11-22 12:26:28.046345: +2024-11-22 12:26:28.046772: Epoch 4644 +2024-11-22 12:26:28.046908: Current learning rate: 0.00458 +2024-11-22 12:26:46.081471: train_loss -0.8052 +2024-11-22 12:26:46.093759: val_loss -0.791 +2024-11-22 12:26:46.093899: Pseudo dice [0.8561] +2024-11-22 12:26:46.093998: Epoch time: 18.04 s +2024-11-22 12:26:46.945499: +2024-11-22 12:26:46.945720: Epoch 4645 +2024-11-22 12:26:46.945835: Current learning rate: 0.00457 +2024-11-22 12:27:06.134014: train_loss -0.802 +2024-11-22 12:27:06.140899: val_loss -0.7771 +2024-11-22 12:27:06.141377: Pseudo dice [0.8625] +2024-11-22 12:27:06.141488: Epoch time: 19.19 s +2024-11-22 12:27:07.024010: +2024-11-22 12:27:07.024467: Epoch 4646 +2024-11-22 12:27:07.024582: Current learning rate: 0.00457 +2024-11-22 12:27:26.973340: train_loss -0.7911 +2024-11-22 12:27:26.979558: val_loss -0.7863 +2024-11-22 12:27:26.979717: Pseudo dice [0.8572] +2024-11-22 12:27:26.979830: Epoch time: 19.95 s +2024-11-22 12:27:27.839838: +2024-11-22 12:27:27.840288: Epoch 4647 +2024-11-22 12:27:27.840416: Current learning rate: 0.00457 +2024-11-22 12:27:46.607016: train_loss -0.7947 +2024-11-22 12:27:46.619015: val_loss -0.7965 +2024-11-22 12:27:46.619151: Pseudo dice [0.8655] +2024-11-22 12:27:46.619241: Epoch time: 18.77 s +2024-11-22 12:27:47.566182: +2024-11-22 12:27:47.566699: Epoch 4648 +2024-11-22 12:27:47.566819: Current learning rate: 0.00457 +2024-11-22 12:28:06.250076: train_loss -0.805 +2024-11-22 12:28:06.256254: val_loss -0.7746 +2024-11-22 12:28:06.256396: Pseudo dice [0.8569] +2024-11-22 12:28:06.256500: Epoch time: 18.68 s +2024-11-22 12:28:07.233641: +2024-11-22 12:28:07.234514: Epoch 4649 +2024-11-22 12:28:07.234631: Current learning rate: 0.00457 +2024-11-22 12:28:27.365104: train_loss -0.7976 +2024-11-22 12:28:27.396046: val_loss -0.7496 +2024-11-22 12:28:27.396202: Pseudo dice [0.8571] +2024-11-22 12:28:27.396321: Epoch time: 20.13 s +2024-11-22 12:28:28.684115: +2024-11-22 12:28:28.684607: Epoch 4650 +2024-11-22 12:28:28.684733: Current learning rate: 0.00457 +2024-11-22 12:28:48.024305: train_loss -0.7975 +2024-11-22 12:28:48.029241: val_loss -0.7637 +2024-11-22 12:28:48.029433: Pseudo dice [0.8563] +2024-11-22 12:28:48.029542: Epoch time: 19.34 s +2024-11-22 12:28:48.889436: +2024-11-22 12:28:48.889904: Epoch 4651 +2024-11-22 12:28:48.890042: Current learning rate: 0.00457 +2024-11-22 12:29:07.573982: train_loss -0.7933 +2024-11-22 12:29:07.584273: val_loss -0.7537 +2024-11-22 12:29:07.584443: Pseudo dice [0.8598] +2024-11-22 12:29:07.584547: Epoch time: 18.69 s +2024-11-22 12:29:08.481161: +2024-11-22 12:29:08.481684: Epoch 4652 +2024-11-22 12:29:08.481826: Current learning rate: 0.00457 +2024-11-22 12:29:27.953919: train_loss -0.7844 +2024-11-22 12:29:27.960534: val_loss -0.7787 +2024-11-22 12:29:27.960718: Pseudo dice [0.8521] +2024-11-22 12:29:27.960812: Epoch time: 19.47 s +2024-11-22 12:29:29.216789: +2024-11-22 12:29:29.217250: Epoch 4653 +2024-11-22 12:29:29.217366: Current learning rate: 0.00456 +2024-11-22 12:29:48.826875: train_loss -0.7934 +2024-11-22 12:29:48.841192: val_loss -0.7576 +2024-11-22 12:29:48.841334: Pseudo dice [0.8438] +2024-11-22 12:29:48.841448: Epoch time: 19.61 s +2024-11-22 12:29:49.933872: +2024-11-22 12:29:49.934363: Epoch 4654 +2024-11-22 12:29:49.934486: Current learning rate: 0.00456 +2024-11-22 12:30:08.366970: train_loss -0.7994 +2024-11-22 12:30:08.375024: val_loss -0.7295 +2024-11-22 12:30:08.375177: Pseudo dice [0.8493] +2024-11-22 12:30:08.375288: Epoch time: 18.43 s +2024-11-22 12:30:09.448488: +2024-11-22 12:30:09.448969: Epoch 4655 +2024-11-22 12:30:09.449104: Current learning rate: 0.00456 +2024-11-22 12:30:29.122389: train_loss -0.7957 +2024-11-22 12:30:29.141900: val_loss -0.7714 +2024-11-22 12:30:29.142069: Pseudo dice [0.857] +2024-11-22 12:30:29.142169: Epoch time: 19.67 s +2024-11-22 12:30:30.171767: +2024-11-22 12:30:30.172250: Epoch 4656 +2024-11-22 12:30:30.172369: Current learning rate: 0.00456 +2024-11-22 12:30:49.250818: train_loss -0.7851 +2024-11-22 12:30:49.255079: val_loss -0.7447 +2024-11-22 12:30:49.255198: Pseudo dice [0.831] +2024-11-22 12:30:49.255290: Epoch time: 19.08 s +2024-11-22 12:30:50.155016: +2024-11-22 12:30:50.158185: Epoch 4657 +2024-11-22 12:30:50.158326: Current learning rate: 0.00456 +2024-11-22 12:31:09.776800: train_loss -0.7887 +2024-11-22 12:31:09.786646: val_loss -0.7649 +2024-11-22 12:31:09.786794: Pseudo dice [0.8403] +2024-11-22 12:31:09.786891: Epoch time: 19.62 s +2024-11-22 12:31:10.666961: +2024-11-22 12:31:10.667173: Epoch 4658 +2024-11-22 12:31:10.667290: Current learning rate: 0.00456 +2024-11-22 12:31:31.455161: train_loss -0.791 +2024-11-22 12:31:31.461331: val_loss -0.7674 +2024-11-22 12:31:31.461452: Pseudo dice [0.8531] +2024-11-22 12:31:31.461534: Epoch time: 20.79 s +2024-11-22 12:31:32.358990: +2024-11-22 12:31:32.359874: Epoch 4659 +2024-11-22 12:31:32.359992: Current learning rate: 0.00456 +2024-11-22 12:31:51.270035: train_loss -0.7898 +2024-11-22 12:31:51.277180: val_loss -0.7507 +2024-11-22 12:31:51.277309: Pseudo dice [0.8392] +2024-11-22 12:31:51.277420: Epoch time: 18.91 s +2024-11-22 12:31:52.344640: +2024-11-22 12:31:52.345185: Epoch 4660 +2024-11-22 12:31:52.345308: Current learning rate: 0.00456 +2024-11-22 12:32:11.417678: train_loss -0.7938 +2024-11-22 12:32:11.422464: val_loss -0.787 +2024-11-22 12:32:11.422602: Pseudo dice [0.8431] +2024-11-22 12:32:11.422691: Epoch time: 19.07 s +2024-11-22 12:32:12.318036: +2024-11-22 12:32:12.318532: Epoch 4661 +2024-11-22 12:32:12.318667: Current learning rate: 0.00455 +2024-11-22 12:32:31.211020: train_loss -0.7979 +2024-11-22 12:32:31.221680: val_loss -0.7836 +2024-11-22 12:32:31.221831: Pseudo dice [0.8578] +2024-11-22 12:32:31.221934: Epoch time: 18.89 s +2024-11-22 12:32:32.137575: +2024-11-22 12:32:32.138434: Epoch 4662 +2024-11-22 12:32:32.138550: Current learning rate: 0.00455 +2024-11-22 12:32:50.791481: train_loss -0.799 +2024-11-22 12:32:50.799593: val_loss -0.7524 +2024-11-22 12:32:50.799744: Pseudo dice [0.8591] +2024-11-22 12:32:50.799837: Epoch time: 18.65 s +2024-11-22 12:32:51.683743: +2024-11-22 12:32:51.684604: Epoch 4663 +2024-11-22 12:32:51.684725: Current learning rate: 0.00455 +2024-11-22 12:33:11.192638: train_loss -0.7903 +2024-11-22 12:33:11.197716: val_loss -0.7731 +2024-11-22 12:33:11.197808: Pseudo dice [0.8581] +2024-11-22 12:33:11.197891: Epoch time: 19.51 s +2024-11-22 12:33:12.044615: +2024-11-22 12:33:12.045384: Epoch 4664 +2024-11-22 12:33:12.045502: Current learning rate: 0.00455 +2024-11-22 12:33:31.041802: train_loss -0.794 +2024-11-22 12:33:31.046398: val_loss -0.7791 +2024-11-22 12:33:31.046519: Pseudo dice [0.8555] +2024-11-22 12:33:31.046602: Epoch time: 19.0 s +2024-11-22 12:33:32.341421: +2024-11-22 12:33:32.341873: Epoch 4665 +2024-11-22 12:33:32.341996: Current learning rate: 0.00455 +2024-11-22 12:33:51.711327: train_loss -0.7767 +2024-11-22 12:33:51.714315: val_loss -0.7587 +2024-11-22 12:33:51.714430: Pseudo dice [0.8537] +2024-11-22 12:33:51.714516: Epoch time: 19.37 s +2024-11-22 12:33:52.667861: +2024-11-22 12:33:52.668310: Epoch 4666 +2024-11-22 12:33:52.668425: Current learning rate: 0.00455 +2024-11-22 12:34:12.200551: train_loss -0.7811 +2024-11-22 12:34:12.212134: val_loss -0.7682 +2024-11-22 12:34:12.212284: Pseudo dice [0.8541] +2024-11-22 12:34:12.212382: Epoch time: 19.53 s +2024-11-22 12:34:13.106383: +2024-11-22 12:34:13.106904: Epoch 4667 +2024-11-22 12:34:13.107022: Current learning rate: 0.00455 +2024-11-22 12:34:31.618612: train_loss -0.7887 +2024-11-22 12:34:31.629304: val_loss -0.7776 +2024-11-22 12:34:31.629462: Pseudo dice [0.8491] +2024-11-22 12:34:31.629550: Epoch time: 18.51 s +2024-11-22 12:34:32.609872: +2024-11-22 12:34:32.610375: Epoch 4668 +2024-11-22 12:34:32.610497: Current learning rate: 0.00455 +2024-11-22 12:34:52.162833: train_loss -0.793 +2024-11-22 12:34:52.170627: val_loss -0.7811 +2024-11-22 12:34:52.170759: Pseudo dice [0.8447] +2024-11-22 12:34:52.170866: Epoch time: 19.55 s +2024-11-22 12:34:53.118557: +2024-11-22 12:34:53.118761: Epoch 4669 +2024-11-22 12:34:53.118878: Current learning rate: 0.00455 +2024-11-22 12:35:12.245290: train_loss -0.7854 +2024-11-22 12:35:12.265109: val_loss -0.7807 +2024-11-22 12:35:12.265293: Pseudo dice [0.8542] +2024-11-22 12:35:12.265398: Epoch time: 19.13 s +2024-11-22 12:35:13.132600: +2024-11-22 12:35:13.133084: Epoch 4670 +2024-11-22 12:35:13.133204: Current learning rate: 0.00454 +2024-11-22 12:35:33.442884: train_loss -0.7874 +2024-11-22 12:35:33.459291: val_loss -0.7763 +2024-11-22 12:35:33.459440: Pseudo dice [0.8516] +2024-11-22 12:35:33.459536: Epoch time: 20.31 s +2024-11-22 12:35:34.490297: +2024-11-22 12:35:34.490754: Epoch 4671 +2024-11-22 12:35:34.490866: Current learning rate: 0.00454 +2024-11-22 12:35:54.116248: train_loss -0.7755 +2024-11-22 12:35:54.122254: val_loss -0.7845 +2024-11-22 12:35:54.122611: Pseudo dice [0.8582] +2024-11-22 12:35:54.122708: Epoch time: 19.63 s +2024-11-22 12:35:55.011344: +2024-11-22 12:35:55.012184: Epoch 4672 +2024-11-22 12:35:55.012305: Current learning rate: 0.00454 +2024-11-22 12:36:13.935872: train_loss -0.782 +2024-11-22 12:36:13.946804: val_loss -0.7534 +2024-11-22 12:36:13.946945: Pseudo dice [0.8619] +2024-11-22 12:36:13.947031: Epoch time: 18.93 s +2024-11-22 12:36:14.899325: +2024-11-22 12:36:14.899755: Epoch 4673 +2024-11-22 12:36:14.899870: Current learning rate: 0.00454 +2024-11-22 12:36:34.279379: train_loss -0.7734 +2024-11-22 12:36:34.290826: val_loss -0.7504 +2024-11-22 12:36:34.290918: Pseudo dice [0.8296] +2024-11-22 12:36:34.291013: Epoch time: 19.38 s +2024-11-22 12:36:35.133917: +2024-11-22 12:36:35.134116: Epoch 4674 +2024-11-22 12:36:35.134228: Current learning rate: 0.00454 +2024-11-22 12:36:55.794000: train_loss -0.7885 +2024-11-22 12:36:55.805220: val_loss -0.7604 +2024-11-22 12:36:55.805338: Pseudo dice [0.8467] +2024-11-22 12:36:55.805440: Epoch time: 20.66 s +2024-11-22 12:36:56.864848: +2024-11-22 12:36:56.865324: Epoch 4675 +2024-11-22 12:36:56.865443: Current learning rate: 0.00454 +2024-11-22 12:37:15.942697: train_loss -0.7857 +2024-11-22 12:37:15.949611: val_loss -0.7559 +2024-11-22 12:37:15.949752: Pseudo dice [0.8453] +2024-11-22 12:37:15.949836: Epoch time: 19.08 s +2024-11-22 12:37:16.865795: +2024-11-22 12:37:16.866317: Epoch 4676 +2024-11-22 12:37:16.866434: Current learning rate: 0.00454 +2024-11-22 12:37:36.665218: train_loss -0.7808 +2024-11-22 12:37:36.673546: val_loss -0.7674 +2024-11-22 12:37:36.673698: Pseudo dice [0.852] +2024-11-22 12:37:36.673797: Epoch time: 19.8 s +2024-11-22 12:37:38.046579: +2024-11-22 12:37:38.047314: Epoch 4677 +2024-11-22 12:37:38.047433: Current learning rate: 0.00454 +2024-11-22 12:37:57.534975: train_loss -0.7896 +2024-11-22 12:37:57.542315: val_loss -0.7985 +2024-11-22 12:37:57.542430: Pseudo dice [0.8642] +2024-11-22 12:37:57.542529: Epoch time: 19.49 s +2024-11-22 12:37:58.415447: +2024-11-22 12:37:58.415668: Epoch 4678 +2024-11-22 12:37:58.415782: Current learning rate: 0.00453 +2024-11-22 12:38:18.538604: train_loss -0.7897 +2024-11-22 12:38:18.545570: val_loss -0.7641 +2024-11-22 12:38:18.545704: Pseudo dice [0.8436] +2024-11-22 12:38:18.545786: Epoch time: 20.12 s +2024-11-22 12:38:19.400208: +2024-11-22 12:38:19.400419: Epoch 4679 +2024-11-22 12:38:19.400545: Current learning rate: 0.00453 +2024-11-22 12:38:39.674930: train_loss -0.7834 +2024-11-22 12:38:39.683598: val_loss -0.7641 +2024-11-22 12:38:39.683738: Pseudo dice [0.8434] +2024-11-22 12:38:39.683836: Epoch time: 20.28 s +2024-11-22 12:38:40.566271: +2024-11-22 12:38:40.566719: Epoch 4680 +2024-11-22 12:38:40.566849: Current learning rate: 0.00453 +2024-11-22 12:39:00.051116: train_loss -0.7896 +2024-11-22 12:39:00.061423: val_loss -0.7808 +2024-11-22 12:39:00.061846: Pseudo dice [0.8489] +2024-11-22 12:39:00.061968: Epoch time: 19.49 s +2024-11-22 12:39:01.272550: +2024-11-22 12:39:01.274760: Epoch 4681 +2024-11-22 12:39:01.274882: Current learning rate: 0.00453 +2024-11-22 12:39:19.924673: train_loss -0.7924 +2024-11-22 12:39:19.950499: val_loss -0.7778 +2024-11-22 12:39:19.950664: Pseudo dice [0.8521] +2024-11-22 12:39:19.950775: Epoch time: 18.65 s +2024-11-22 12:39:20.834856: +2024-11-22 12:39:20.835627: Epoch 4682 +2024-11-22 12:39:20.835752: Current learning rate: 0.00453 +2024-11-22 12:39:40.096909: train_loss -0.788 +2024-11-22 12:39:40.108421: val_loss -0.7564 +2024-11-22 12:39:40.108556: Pseudo dice [0.8455] +2024-11-22 12:39:40.108642: Epoch time: 19.26 s +2024-11-22 12:39:40.977556: +2024-11-22 12:39:40.978016: Epoch 4683 +2024-11-22 12:39:40.978140: Current learning rate: 0.00453 +2024-11-22 12:40:00.816112: train_loss -0.7848 +2024-11-22 12:40:00.822588: val_loss -0.7744 +2024-11-22 12:40:00.822749: Pseudo dice [0.853] +2024-11-22 12:40:00.822835: Epoch time: 19.84 s +2024-11-22 12:40:01.937610: +2024-11-22 12:40:01.938052: Epoch 4684 +2024-11-22 12:40:01.938178: Current learning rate: 0.00453 +2024-11-22 12:40:23.014115: train_loss -0.7748 +2024-11-22 12:40:23.023540: val_loss -0.7632 +2024-11-22 12:40:23.023690: Pseudo dice [0.8471] +2024-11-22 12:40:23.023784: Epoch time: 21.08 s +2024-11-22 12:40:23.912472: +2024-11-22 12:40:23.912991: Epoch 4685 +2024-11-22 12:40:23.913117: Current learning rate: 0.00453 +2024-11-22 12:40:43.336611: train_loss -0.783 +2024-11-22 12:40:43.345855: val_loss -0.7592 +2024-11-22 12:40:43.346007: Pseudo dice [0.8596] +2024-11-22 12:40:43.346128: Epoch time: 19.42 s +2024-11-22 12:40:44.208183: +2024-11-22 12:40:44.209335: Epoch 4686 +2024-11-22 12:40:44.209463: Current learning rate: 0.00452 +2024-11-22 12:41:02.828536: train_loss -0.7679 +2024-11-22 12:41:02.852579: val_loss -0.7672 +2024-11-22 12:41:02.852738: Pseudo dice [0.8433] +2024-11-22 12:41:02.852824: Epoch time: 18.62 s +2024-11-22 12:41:03.855936: +2024-11-22 12:41:03.856505: Epoch 4687 +2024-11-22 12:41:03.856633: Current learning rate: 0.00452 +2024-11-22 12:41:23.859505: train_loss -0.776 +2024-11-22 12:41:23.869115: val_loss -0.7747 +2024-11-22 12:41:23.869237: Pseudo dice [0.8416] +2024-11-22 12:41:23.869325: Epoch time: 20.0 s +2024-11-22 12:41:24.874142: +2024-11-22 12:41:24.874928: Epoch 4688 +2024-11-22 12:41:24.875057: Current learning rate: 0.00452 +2024-11-22 12:41:43.669083: train_loss -0.779 +2024-11-22 12:41:43.677712: val_loss -0.7806 +2024-11-22 12:41:43.677847: Pseudo dice [0.8475] +2024-11-22 12:41:43.677948: Epoch time: 18.8 s +2024-11-22 12:41:44.944088: +2024-11-22 12:41:44.944555: Epoch 4689 +2024-11-22 12:41:44.944687: Current learning rate: 0.00452 +2024-11-22 12:42:04.856264: train_loss -0.7729 +2024-11-22 12:42:04.862417: val_loss -0.7489 +2024-11-22 12:42:04.862631: Pseudo dice [0.83] +2024-11-22 12:42:04.862730: Epoch time: 19.91 s +2024-11-22 12:42:06.007876: +2024-11-22 12:42:06.008732: Epoch 4690 +2024-11-22 12:42:06.008849: Current learning rate: 0.00452 +2024-11-22 12:42:28.097708: train_loss -0.7711 +2024-11-22 12:42:28.105836: val_loss -0.7513 +2024-11-22 12:42:28.105983: Pseudo dice [0.8521] +2024-11-22 12:42:28.106082: Epoch time: 22.09 s +2024-11-22 12:42:29.037533: +2024-11-22 12:42:29.038009: Epoch 4691 +2024-11-22 12:42:29.038131: Current learning rate: 0.00452 +2024-11-22 12:42:48.213876: train_loss -0.7796 +2024-11-22 12:42:48.224646: val_loss -0.7522 +2024-11-22 12:42:48.224802: Pseudo dice [0.8446] +2024-11-22 12:42:48.224903: Epoch time: 19.18 s +2024-11-22 12:42:49.230175: +2024-11-22 12:42:49.230666: Epoch 4692 +2024-11-22 12:42:49.230798: Current learning rate: 0.00452 +2024-11-22 12:43:08.782716: train_loss -0.7845 +2024-11-22 12:43:08.797549: val_loss -0.7757 +2024-11-22 12:43:08.797711: Pseudo dice [0.8422] +2024-11-22 12:43:08.797809: Epoch time: 19.55 s +2024-11-22 12:43:09.757513: +2024-11-22 12:43:09.757972: Epoch 4693 +2024-11-22 12:43:09.758100: Current learning rate: 0.00452 +2024-11-22 12:43:29.607893: train_loss -0.7874 +2024-11-22 12:43:29.621237: val_loss -0.766 +2024-11-22 12:43:29.621385: Pseudo dice [0.8532] +2024-11-22 12:43:29.621479: Epoch time: 19.85 s +2024-11-22 12:43:30.488533: +2024-11-22 12:43:30.488742: Epoch 4694 +2024-11-22 12:43:30.488861: Current learning rate: 0.00451 +2024-11-22 12:43:49.783656: train_loss -0.7907 +2024-11-22 12:43:49.804834: val_loss -0.758 +2024-11-22 12:43:49.804987: Pseudo dice [0.8304] +2024-11-22 12:43:49.805083: Epoch time: 19.3 s +2024-11-22 12:43:51.068031: +2024-11-22 12:43:51.069729: Epoch 4695 +2024-11-22 12:43:51.069862: Current learning rate: 0.00451 +2024-11-22 12:44:10.665913: train_loss -0.7816 +2024-11-22 12:44:10.673391: val_loss -0.7774 +2024-11-22 12:44:10.673507: Pseudo dice [0.8447] +2024-11-22 12:44:10.673614: Epoch time: 19.6 s +2024-11-22 12:44:11.647544: +2024-11-22 12:44:11.648414: Epoch 4696 +2024-11-22 12:44:11.648528: Current learning rate: 0.00451 +2024-11-22 12:44:31.254981: train_loss -0.7785 +2024-11-22 12:44:31.263198: val_loss -0.7558 +2024-11-22 12:44:31.263328: Pseudo dice [0.8628] +2024-11-22 12:44:31.263448: Epoch time: 19.61 s +2024-11-22 12:44:32.203101: +2024-11-22 12:44:32.205773: Epoch 4697 +2024-11-22 12:44:32.205901: Current learning rate: 0.00451 +2024-11-22 12:44:50.909959: train_loss -0.7863 +2024-11-22 12:44:50.916414: val_loss -0.7659 +2024-11-22 12:44:50.916544: Pseudo dice [0.857] +2024-11-22 12:44:50.916629: Epoch time: 18.71 s +2024-11-22 12:44:51.928802: +2024-11-22 12:44:51.930167: Epoch 4698 +2024-11-22 12:44:51.930288: Current learning rate: 0.00451 +2024-11-22 12:45:11.880790: train_loss -0.7782 +2024-11-22 12:45:11.890459: val_loss -0.7868 +2024-11-22 12:45:11.890574: Pseudo dice [0.8504] +2024-11-22 12:45:11.890664: Epoch time: 19.95 s +2024-11-22 12:45:12.985160: +2024-11-22 12:45:12.985656: Epoch 4699 +2024-11-22 12:45:12.985782: Current learning rate: 0.00451 +2024-11-22 12:45:32.802458: train_loss -0.7901 +2024-11-22 12:45:32.811819: val_loss -0.7868 +2024-11-22 12:45:32.811958: Pseudo dice [0.8503] +2024-11-22 12:45:32.812039: Epoch time: 19.82 s +2024-11-22 12:45:33.939302: +2024-11-22 12:45:33.939796: Epoch 4700 +2024-11-22 12:45:33.939918: Current learning rate: 0.00451 +2024-11-22 12:45:53.009898: train_loss -0.7956 +2024-11-22 12:45:53.018390: val_loss -0.7809 +2024-11-22 12:45:53.018525: Pseudo dice [0.8476] +2024-11-22 12:45:53.018620: Epoch time: 19.07 s +2024-11-22 12:45:54.265849: +2024-11-22 12:45:54.266324: Epoch 4701 +2024-11-22 12:45:54.266451: Current learning rate: 0.00451 +2024-11-22 12:46:13.943957: train_loss -0.7827 +2024-11-22 12:46:13.946783: val_loss -0.7622 +2024-11-22 12:46:13.946905: Pseudo dice [0.8408] +2024-11-22 12:46:13.947004: Epoch time: 19.68 s +2024-11-22 12:46:14.904524: +2024-11-22 12:46:14.904942: Epoch 4702 +2024-11-22 12:46:14.905069: Current learning rate: 0.0045 +2024-11-22 12:46:34.505979: train_loss -0.7848 +2024-11-22 12:46:34.509078: val_loss -0.7795 +2024-11-22 12:46:34.509180: Pseudo dice [0.8512] +2024-11-22 12:46:34.509270: Epoch time: 19.6 s +2024-11-22 12:46:35.354181: +2024-11-22 12:46:35.355155: Epoch 4703 +2024-11-22 12:46:35.355272: Current learning rate: 0.0045 +2024-11-22 12:46:55.270967: train_loss -0.7806 +2024-11-22 12:46:55.278766: val_loss -0.7829 +2024-11-22 12:46:55.278909: Pseudo dice [0.8595] +2024-11-22 12:46:55.279001: Epoch time: 19.92 s +2024-11-22 12:46:56.219385: +2024-11-22 12:46:56.219883: Epoch 4704 +2024-11-22 12:46:56.220007: Current learning rate: 0.0045 +2024-11-22 12:47:15.105180: train_loss -0.7892 +2024-11-22 12:47:15.109880: val_loss -0.7775 +2024-11-22 12:47:15.109989: Pseudo dice [0.8609] +2024-11-22 12:47:15.110110: Epoch time: 18.89 s +2024-11-22 12:47:15.970925: +2024-11-22 12:47:15.973015: Epoch 4705 +2024-11-22 12:47:15.973206: Current learning rate: 0.0045 +2024-11-22 12:47:35.051640: train_loss -0.7976 +2024-11-22 12:47:35.054993: val_loss -0.756 +2024-11-22 12:47:35.055118: Pseudo dice [0.8569] +2024-11-22 12:47:35.055207: Epoch time: 19.08 s +2024-11-22 12:47:35.904765: +2024-11-22 12:47:35.905425: Epoch 4706 +2024-11-22 12:47:35.905545: Current learning rate: 0.0045 +2024-11-22 12:47:54.538949: train_loss -0.7934 +2024-11-22 12:47:54.546791: val_loss -0.7723 +2024-11-22 12:47:54.546901: Pseudo dice [0.849] +2024-11-22 12:47:54.546981: Epoch time: 18.63 s +2024-11-22 12:47:55.497389: +2024-11-22 12:47:55.497634: Epoch 4707 +2024-11-22 12:47:55.497770: Current learning rate: 0.0045 +2024-11-22 12:48:13.831533: train_loss -0.795 +2024-11-22 12:48:13.832588: val_loss -0.7775 +2024-11-22 12:48:13.832713: Pseudo dice [0.8603] +2024-11-22 12:48:13.832799: Epoch time: 18.33 s +2024-11-22 12:48:14.736685: +2024-11-22 12:48:14.736922: Epoch 4708 +2024-11-22 12:48:14.737031: Current learning rate: 0.0045 +2024-11-22 12:48:34.208857: train_loss -0.7896 +2024-11-22 12:48:34.209470: val_loss -0.7943 +2024-11-22 12:48:34.209568: Pseudo dice [0.855] +2024-11-22 12:48:34.209665: Epoch time: 19.47 s +2024-11-22 12:48:35.049451: +2024-11-22 12:48:35.049671: Epoch 4709 +2024-11-22 12:48:35.049794: Current learning rate: 0.0045 +2024-11-22 12:48:53.118200: train_loss -0.7927 +2024-11-22 12:48:53.121879: val_loss -0.7831 +2024-11-22 12:48:53.122025: Pseudo dice [0.8552] +2024-11-22 12:48:53.122125: Epoch time: 18.07 s +2024-11-22 12:48:54.008283: +2024-11-22 12:48:54.008496: Epoch 4710 +2024-11-22 12:48:54.008631: Current learning rate: 0.00449 +2024-11-22 12:49:11.865452: train_loss -0.7894 +2024-11-22 12:49:11.866692: val_loss -0.7737 +2024-11-22 12:49:11.866824: Pseudo dice [0.8514] +2024-11-22 12:49:11.866904: Epoch time: 17.86 s +2024-11-22 12:49:12.717970: +2024-11-22 12:49:12.718196: Epoch 4711 +2024-11-22 12:49:12.718324: Current learning rate: 0.00449 +2024-11-22 12:49:30.849459: train_loss -0.7932 +2024-11-22 12:49:30.849909: val_loss -0.7565 +2024-11-22 12:49:30.849990: Pseudo dice [0.8569] +2024-11-22 12:49:30.850115: Epoch time: 18.13 s +2024-11-22 12:49:31.688585: +2024-11-22 12:49:31.688796: Epoch 4712 +2024-11-22 12:49:31.688914: Current learning rate: 0.00449 +2024-11-22 12:49:51.057930: train_loss -0.7937 +2024-11-22 12:49:51.058924: val_loss -0.7599 +2024-11-22 12:49:51.059030: Pseudo dice [0.8513] +2024-11-22 12:49:51.059135: Epoch time: 19.37 s +2024-11-22 12:49:51.945932: +2024-11-22 12:49:51.946145: Epoch 4713 +2024-11-22 12:49:51.946255: Current learning rate: 0.00449 +2024-11-22 12:50:12.123127: train_loss -0.7932 +2024-11-22 12:50:12.123654: val_loss -0.7599 +2024-11-22 12:50:12.123754: Pseudo dice [0.8595] +2024-11-22 12:50:12.123837: Epoch time: 20.18 s +2024-11-22 12:50:12.954736: +2024-11-22 12:50:12.954947: Epoch 4714 +2024-11-22 12:50:12.955075: Current learning rate: 0.00449 +2024-11-22 12:50:31.054765: train_loss -0.7846 +2024-11-22 12:50:31.059766: val_loss -0.7835 +2024-11-22 12:50:31.059904: Pseudo dice [0.855] +2024-11-22 12:50:31.059996: Epoch time: 18.1 s +2024-11-22 12:50:32.024376: +2024-11-22 12:50:32.024597: Epoch 4715 +2024-11-22 12:50:32.024732: Current learning rate: 0.00449 +2024-11-22 12:50:50.538805: train_loss -0.7975 +2024-11-22 12:50:50.547228: val_loss -0.7672 +2024-11-22 12:50:50.547366: Pseudo dice [0.8447] +2024-11-22 12:50:50.547467: Epoch time: 18.52 s +2024-11-22 12:50:51.535569: +2024-11-22 12:50:51.536447: Epoch 4716 +2024-11-22 12:50:51.536569: Current learning rate: 0.00449 +2024-11-22 12:51:10.973325: train_loss -0.8002 +2024-11-22 12:51:10.981257: val_loss -0.7518 +2024-11-22 12:51:10.981400: Pseudo dice [0.8489] +2024-11-22 12:51:10.981502: Epoch time: 19.44 s +2024-11-22 12:51:11.899337: +2024-11-22 12:51:11.900760: Epoch 4717 +2024-11-22 12:51:11.900879: Current learning rate: 0.00449 +2024-11-22 12:51:31.508412: train_loss -0.792 +2024-11-22 12:51:31.518410: val_loss -0.772 +2024-11-22 12:51:31.518535: Pseudo dice [0.8557] +2024-11-22 12:51:31.518625: Epoch time: 19.61 s +2024-11-22 12:51:32.498906: +2024-11-22 12:51:32.500299: Epoch 4718 +2024-11-22 12:51:32.500421: Current learning rate: 0.00448 +2024-11-22 12:51:52.326632: train_loss -0.7946 +2024-11-22 12:51:52.330758: val_loss -0.7714 +2024-11-22 12:51:52.330876: Pseudo dice [0.8628] +2024-11-22 12:51:52.335356: Epoch time: 19.83 s +2024-11-22 12:51:53.274909: +2024-11-22 12:51:53.275697: Epoch 4719 +2024-11-22 12:51:53.275831: Current learning rate: 0.00448 +2024-11-22 12:52:12.516371: train_loss -0.7946 +2024-11-22 12:52:12.526051: val_loss -0.7795 +2024-11-22 12:52:12.526199: Pseudo dice [0.8531] +2024-11-22 12:52:12.526295: Epoch time: 19.24 s +2024-11-22 12:52:13.392075: +2024-11-22 12:52:13.392997: Epoch 4720 +2024-11-22 12:52:13.393122: Current learning rate: 0.00448 +2024-11-22 12:52:32.803994: train_loss -0.7995 +2024-11-22 12:52:32.810801: val_loss -0.7702 +2024-11-22 12:52:32.810938: Pseudo dice [0.87] +2024-11-22 12:52:32.811030: Epoch time: 19.41 s +2024-11-22 12:52:33.679781: +2024-11-22 12:52:33.680574: Epoch 4721 +2024-11-22 12:52:33.680694: Current learning rate: 0.00448 +2024-11-22 12:52:53.353747: train_loss -0.7973 +2024-11-22 12:52:53.361197: val_loss -0.7843 +2024-11-22 12:52:53.361337: Pseudo dice [0.8596] +2024-11-22 12:52:53.361420: Epoch time: 19.67 s +2024-11-22 12:52:54.282718: +2024-11-22 12:52:54.283489: Epoch 4722 +2024-11-22 12:52:54.283610: Current learning rate: 0.00448 +2024-11-22 12:53:14.255301: train_loss -0.7946 +2024-11-22 12:53:14.271227: val_loss -0.7771 +2024-11-22 12:53:14.271426: Pseudo dice [0.8565] +2024-11-22 12:53:14.271528: Epoch time: 19.97 s +2024-11-22 12:53:15.137462: +2024-11-22 12:53:15.137880: Epoch 4723 +2024-11-22 12:53:15.137997: Current learning rate: 0.00448 +2024-11-22 12:53:33.460109: train_loss -0.7965 +2024-11-22 12:53:33.474275: val_loss -0.7772 +2024-11-22 12:53:33.474418: Pseudo dice [0.8562] +2024-11-22 12:53:33.474516: Epoch time: 18.32 s +2024-11-22 12:53:34.393832: +2024-11-22 12:53:34.394295: Epoch 4724 +2024-11-22 12:53:34.394417: Current learning rate: 0.00448 +2024-11-22 12:53:53.253611: train_loss -0.795 +2024-11-22 12:53:53.257973: val_loss -0.8025 +2024-11-22 12:53:53.258096: Pseudo dice [0.8618] +2024-11-22 12:53:53.258192: Epoch time: 18.86 s +2024-11-22 12:53:54.366936: +2024-11-22 12:53:54.367380: Epoch 4725 +2024-11-22 12:53:54.367512: Current learning rate: 0.00448 +2024-11-22 12:54:14.670511: train_loss -0.7884 +2024-11-22 12:54:14.696391: val_loss -0.7602 +2024-11-22 12:54:14.696532: Pseudo dice [0.8479] +2024-11-22 12:54:14.696629: Epoch time: 20.3 s +2024-11-22 12:54:15.623575: +2024-11-22 12:54:15.625487: Epoch 4726 +2024-11-22 12:54:15.625616: Current learning rate: 0.00447 +2024-11-22 12:54:34.583425: train_loss -0.7984 +2024-11-22 12:54:34.594316: val_loss -0.7787 +2024-11-22 12:54:34.594464: Pseudo dice [0.8576] +2024-11-22 12:54:34.594558: Epoch time: 18.96 s +2024-11-22 12:54:35.627949: +2024-11-22 12:54:35.628740: Epoch 4727 +2024-11-22 12:54:35.628871: Current learning rate: 0.00447 +2024-11-22 12:54:55.248627: train_loss -0.8015 +2024-11-22 12:54:55.262344: val_loss -0.7745 +2024-11-22 12:54:55.262506: Pseudo dice [0.8453] +2024-11-22 12:54:55.262618: Epoch time: 19.62 s +2024-11-22 12:54:56.198183: +2024-11-22 12:54:56.198693: Epoch 4728 +2024-11-22 12:54:56.198822: Current learning rate: 0.00447 +2024-11-22 12:55:15.480886: train_loss -0.7951 +2024-11-22 12:55:15.485107: val_loss -0.7966 +2024-11-22 12:55:15.485255: Pseudo dice [0.8649] +2024-11-22 12:55:15.485336: Epoch time: 19.28 s +2024-11-22 12:55:16.407845: +2024-11-22 12:55:16.408649: Epoch 4729 +2024-11-22 12:55:16.408774: Current learning rate: 0.00447 +2024-11-22 12:55:35.175912: train_loss -0.8006 +2024-11-22 12:55:35.181082: val_loss -0.7733 +2024-11-22 12:55:35.181218: Pseudo dice [0.8504] +2024-11-22 12:55:35.181318: Epoch time: 18.77 s +2024-11-22 12:55:36.085850: +2024-11-22 12:55:36.087422: Epoch 4730 +2024-11-22 12:55:36.087547: Current learning rate: 0.00447 +2024-11-22 12:55:55.091718: train_loss -0.7946 +2024-11-22 12:55:55.109613: val_loss -0.7869 +2024-11-22 12:55:55.109737: Pseudo dice [0.8422] +2024-11-22 12:55:55.109820: Epoch time: 19.01 s +2024-11-22 12:55:56.073004: +2024-11-22 12:55:56.073903: Epoch 4731 +2024-11-22 12:55:56.074036: Current learning rate: 0.00447 +2024-11-22 12:56:15.704156: train_loss -0.7934 +2024-11-22 12:56:15.726528: val_loss -0.779 +2024-11-22 12:56:15.726707: Pseudo dice [0.8436] +2024-11-22 12:56:15.726797: Epoch time: 19.63 s +2024-11-22 12:56:16.627956: +2024-11-22 12:56:16.629677: Epoch 4732 +2024-11-22 12:56:16.629799: Current learning rate: 0.00447 +2024-11-22 12:56:36.485156: train_loss -0.7884 +2024-11-22 12:56:36.496822: val_loss -0.7774 +2024-11-22 12:56:36.496956: Pseudo dice [0.8574] +2024-11-22 12:56:36.497057: Epoch time: 19.86 s +2024-11-22 12:56:37.498683: +2024-11-22 12:56:37.501000: Epoch 4733 +2024-11-22 12:56:37.501132: Current learning rate: 0.00447 +2024-11-22 12:56:55.890187: train_loss -0.7908 +2024-11-22 12:56:55.897471: val_loss -0.7757 +2024-11-22 12:56:55.897613: Pseudo dice [0.86] +2024-11-22 12:56:55.897698: Epoch time: 18.39 s +2024-11-22 12:56:56.824568: +2024-11-22 12:56:56.825576: Epoch 4734 +2024-11-22 12:56:56.825720: Current learning rate: 0.00447 +2024-11-22 12:57:16.187670: train_loss -0.7911 +2024-11-22 12:57:16.208673: val_loss -0.7587 +2024-11-22 12:57:16.208810: Pseudo dice [0.8587] +2024-11-22 12:57:16.208894: Epoch time: 19.36 s +2024-11-22 12:57:17.136695: +2024-11-22 12:57:17.137534: Epoch 4735 +2024-11-22 12:57:17.137675: Current learning rate: 0.00446 +2024-11-22 12:57:36.496692: train_loss -0.7933 +2024-11-22 12:57:36.500155: val_loss -0.7683 +2024-11-22 12:57:36.500302: Pseudo dice [0.8511] +2024-11-22 12:57:36.500387: Epoch time: 19.36 s +2024-11-22 12:57:37.462281: +2024-11-22 12:57:37.463129: Epoch 4736 +2024-11-22 12:57:37.463252: Current learning rate: 0.00446 +2024-11-22 12:57:57.002549: train_loss -0.7948 +2024-11-22 12:57:57.013525: val_loss -0.7675 +2024-11-22 12:57:57.013668: Pseudo dice [0.8432] +2024-11-22 12:57:57.013760: Epoch time: 19.54 s +2024-11-22 12:57:57.950517: +2024-11-22 12:57:57.951275: Epoch 4737 +2024-11-22 12:57:57.951400: Current learning rate: 0.00446 +2024-11-22 12:58:17.081826: train_loss -0.7878 +2024-11-22 12:58:17.089848: val_loss -0.7736 +2024-11-22 12:58:17.090003: Pseudo dice [0.8506] +2024-11-22 12:58:17.090096: Epoch time: 19.13 s +2024-11-22 12:58:17.974183: +2024-11-22 12:58:17.976071: Epoch 4738 +2024-11-22 12:58:17.976193: Current learning rate: 0.00446 +2024-11-22 12:58:37.227445: train_loss -0.7954 +2024-11-22 12:58:37.236465: val_loss -0.7741 +2024-11-22 12:58:37.236588: Pseudo dice [0.8472] +2024-11-22 12:58:37.236688: Epoch time: 19.25 s +2024-11-22 12:58:38.093333: +2024-11-22 12:58:38.095666: Epoch 4739 +2024-11-22 12:58:38.095811: Current learning rate: 0.00446 +2024-11-22 12:58:58.434007: train_loss -0.7875 +2024-11-22 12:58:58.443745: val_loss -0.7624 +2024-11-22 12:58:58.443874: Pseudo dice [0.858] +2024-11-22 12:58:58.443973: Epoch time: 20.34 s +2024-11-22 12:58:59.466198: +2024-11-22 12:58:59.467241: Epoch 4740 +2024-11-22 12:58:59.467365: Current learning rate: 0.00446 +2024-11-22 12:59:19.059052: train_loss -0.7937 +2024-11-22 12:59:19.062387: val_loss -0.747 +2024-11-22 12:59:19.062496: Pseudo dice [0.8411] +2024-11-22 12:59:19.062594: Epoch time: 19.59 s +2024-11-22 12:59:19.912421: +2024-11-22 12:59:19.912873: Epoch 4741 +2024-11-22 12:59:19.912996: Current learning rate: 0.00446 +2024-11-22 12:59:39.272820: train_loss -0.7879 +2024-11-22 12:59:39.282920: val_loss -0.766 +2024-11-22 12:59:39.283048: Pseudo dice [0.8682] +2024-11-22 12:59:39.283140: Epoch time: 19.36 s +2024-11-22 12:59:40.196326: +2024-11-22 12:59:40.197946: Epoch 4742 +2024-11-22 12:59:40.198077: Current learning rate: 0.00446 +2024-11-22 13:00:00.420992: train_loss -0.7918 +2024-11-22 13:00:00.429942: val_loss -0.7695 +2024-11-22 13:00:00.430082: Pseudo dice [0.8641] +2024-11-22 13:00:00.430188: Epoch time: 20.23 s +2024-11-22 13:00:01.470658: +2024-11-22 13:00:01.471159: Epoch 4743 +2024-11-22 13:00:01.471289: Current learning rate: 0.00445 +2024-11-22 13:00:19.638445: train_loss -0.7902 +2024-11-22 13:00:19.647118: val_loss -0.7835 +2024-11-22 13:00:19.647254: Pseudo dice [0.8588] +2024-11-22 13:00:19.647339: Epoch time: 18.17 s +2024-11-22 13:00:20.688726: +2024-11-22 13:00:20.690794: Epoch 4744 +2024-11-22 13:00:20.714738: Current learning rate: 0.00445 +2024-11-22 13:00:41.268433: train_loss -0.7946 +2024-11-22 13:00:41.274570: val_loss -0.7717 +2024-11-22 13:00:41.274713: Pseudo dice [0.852] +2024-11-22 13:00:41.274813: Epoch time: 20.58 s +2024-11-22 13:00:42.190554: +2024-11-22 13:00:42.192004: Epoch 4745 +2024-11-22 13:00:42.192130: Current learning rate: 0.00445 +2024-11-22 13:01:02.717351: train_loss -0.7903 +2024-11-22 13:01:02.722351: val_loss -0.7814 +2024-11-22 13:01:02.722479: Pseudo dice [0.846] +2024-11-22 13:01:02.722574: Epoch time: 20.52 s +2024-11-22 13:01:03.618822: +2024-11-22 13:01:03.619641: Epoch 4746 +2024-11-22 13:01:03.619768: Current learning rate: 0.00445 +2024-11-22 13:01:23.237040: train_loss -0.7974 +2024-11-22 13:01:23.247344: val_loss -0.7651 +2024-11-22 13:01:23.247457: Pseudo dice [0.8482] +2024-11-22 13:01:23.247553: Epoch time: 19.62 s +2024-11-22 13:01:24.224282: +2024-11-22 13:01:24.226199: Epoch 4747 +2024-11-22 13:01:24.226340: Current learning rate: 0.00445 +2024-11-22 13:01:43.777685: train_loss -0.7928 +2024-11-22 13:01:43.794852: val_loss -0.7727 +2024-11-22 13:01:43.794987: Pseudo dice [0.8502] +2024-11-22 13:01:43.795097: Epoch time: 19.55 s +2024-11-22 13:01:44.856438: +2024-11-22 13:01:44.857447: Epoch 4748 +2024-11-22 13:01:44.857562: Current learning rate: 0.00445 +2024-11-22 13:02:04.643842: train_loss -0.7973 +2024-11-22 13:02:04.657028: val_loss -0.7501 +2024-11-22 13:02:04.657165: Pseudo dice [0.8432] +2024-11-22 13:02:04.657278: Epoch time: 19.79 s +2024-11-22 13:02:05.554829: +2024-11-22 13:02:05.555288: Epoch 4749 +2024-11-22 13:02:05.555402: Current learning rate: 0.00445 +2024-11-22 13:02:24.793714: train_loss -0.7674 +2024-11-22 13:02:24.807095: val_loss -0.7742 +2024-11-22 13:02:24.807277: Pseudo dice [0.8559] +2024-11-22 13:02:24.807369: Epoch time: 19.24 s +2024-11-22 13:02:25.952583: +2024-11-22 13:02:25.953533: Epoch 4750 +2024-11-22 13:02:25.953665: Current learning rate: 0.00445 +2024-11-22 13:02:44.697449: train_loss -0.7886 +2024-11-22 13:02:44.705709: val_loss -0.7818 +2024-11-22 13:02:44.705852: Pseudo dice [0.85] +2024-11-22 13:02:44.705938: Epoch time: 18.75 s +2024-11-22 13:02:45.563482: +2024-11-22 13:02:45.563944: Epoch 4751 +2024-11-22 13:02:45.564069: Current learning rate: 0.00444 +2024-11-22 13:03:05.065885: train_loss -0.7934 +2024-11-22 13:03:05.073843: val_loss -0.7748 +2024-11-22 13:03:05.073967: Pseudo dice [0.8466] +2024-11-22 13:03:05.074058: Epoch time: 19.5 s +2024-11-22 13:03:06.016177: +2024-11-22 13:03:06.017016: Epoch 4752 +2024-11-22 13:03:06.017157: Current learning rate: 0.00444 +2024-11-22 13:03:26.415382: train_loss -0.7859 +2024-11-22 13:03:26.422518: val_loss -0.7903 +2024-11-22 13:03:26.422667: Pseudo dice [0.8474] +2024-11-22 13:03:26.422766: Epoch time: 20.4 s +2024-11-22 13:03:27.297032: +2024-11-22 13:03:27.298387: Epoch 4753 +2024-11-22 13:03:27.298524: Current learning rate: 0.00444 +2024-11-22 13:03:46.811731: train_loss -0.7886 +2024-11-22 13:03:46.833845: val_loss -0.7662 +2024-11-22 13:03:46.835784: Pseudo dice [0.8283] +2024-11-22 13:03:46.835879: Epoch time: 19.52 s +2024-11-22 13:03:47.742483: +2024-11-22 13:03:47.743501: Epoch 4754 +2024-11-22 13:03:47.743627: Current learning rate: 0.00444 +2024-11-22 13:04:07.717907: train_loss -0.7803 +2024-11-22 13:04:07.722593: val_loss -0.7553 +2024-11-22 13:04:07.722713: Pseudo dice [0.8557] +2024-11-22 13:04:07.722808: Epoch time: 19.98 s +2024-11-22 13:04:08.616158: +2024-11-22 13:04:08.616639: Epoch 4755 +2024-11-22 13:04:08.616762: Current learning rate: 0.00444 +2024-11-22 13:04:27.756568: train_loss -0.7833 +2024-11-22 13:04:27.768971: val_loss -0.7558 +2024-11-22 13:04:27.769105: Pseudo dice [0.849] +2024-11-22 13:04:27.769219: Epoch time: 19.14 s +2024-11-22 13:04:28.793898: +2024-11-22 13:04:28.795111: Epoch 4756 +2024-11-22 13:04:28.795239: Current learning rate: 0.00444 +2024-11-22 13:04:48.079118: train_loss -0.7718 +2024-11-22 13:04:48.089698: val_loss -0.7637 +2024-11-22 13:04:48.089863: Pseudo dice [0.8532] +2024-11-22 13:04:48.089975: Epoch time: 19.29 s +2024-11-22 13:04:48.955929: +2024-11-22 13:04:48.956376: Epoch 4757 +2024-11-22 13:04:48.956497: Current learning rate: 0.00444 +2024-11-22 13:05:08.641598: train_loss -0.7917 +2024-11-22 13:05:08.653530: val_loss -0.7899 +2024-11-22 13:05:08.653664: Pseudo dice [0.8609] +2024-11-22 13:05:08.653771: Epoch time: 19.69 s +2024-11-22 13:05:09.847518: +2024-11-22 13:05:09.849097: Epoch 4758 +2024-11-22 13:05:09.849221: Current learning rate: 0.00444 +2024-11-22 13:05:29.243146: train_loss -0.7823 +2024-11-22 13:05:29.249990: val_loss -0.761 +2024-11-22 13:05:29.250150: Pseudo dice [0.859] +2024-11-22 13:05:29.250244: Epoch time: 19.4 s +2024-11-22 13:05:30.177377: +2024-11-22 13:05:30.177856: Epoch 4759 +2024-11-22 13:05:30.177966: Current learning rate: 0.00443 +2024-11-22 13:05:48.709836: train_loss -0.793 +2024-11-22 13:05:48.717276: val_loss -0.7849 +2024-11-22 13:05:48.717409: Pseudo dice [0.8607] +2024-11-22 13:05:48.717504: Epoch time: 18.53 s +2024-11-22 13:05:49.728033: +2024-11-22 13:05:49.729175: Epoch 4760 +2024-11-22 13:05:49.729303: Current learning rate: 0.00443 +2024-11-22 13:06:08.658145: train_loss -0.7915 +2024-11-22 13:06:08.664630: val_loss -0.7836 +2024-11-22 13:06:08.664761: Pseudo dice [0.8629] +2024-11-22 13:06:08.664855: Epoch time: 18.93 s +2024-11-22 13:06:10.001586: +2024-11-22 13:06:10.003454: Epoch 4761 +2024-11-22 13:06:10.003590: Current learning rate: 0.00443 +2024-11-22 13:06:29.559497: train_loss -0.791 +2024-11-22 13:06:29.571150: val_loss -0.7934 +2024-11-22 13:06:29.571296: Pseudo dice [0.8579] +2024-11-22 13:06:29.571383: Epoch time: 19.56 s +2024-11-22 13:06:30.445033: +2024-11-22 13:06:30.447270: Epoch 4762 +2024-11-22 13:06:30.447398: Current learning rate: 0.00443 +2024-11-22 13:06:50.242348: train_loss -0.7815 +2024-11-22 13:06:50.245084: val_loss -0.7563 +2024-11-22 13:06:50.245184: Pseudo dice [0.8456] +2024-11-22 13:06:50.245272: Epoch time: 19.8 s +2024-11-22 13:06:51.091684: +2024-11-22 13:06:51.092211: Epoch 4763 +2024-11-22 13:06:51.092326: Current learning rate: 0.00443 +2024-11-22 13:07:10.979976: train_loss -0.779 +2024-11-22 13:07:10.983953: val_loss -0.7852 +2024-11-22 13:07:10.984068: Pseudo dice [0.8525] +2024-11-22 13:07:10.984157: Epoch time: 19.89 s +2024-11-22 13:07:11.837176: +2024-11-22 13:07:11.837600: Epoch 4764 +2024-11-22 13:07:11.837712: Current learning rate: 0.00443 +2024-11-22 13:07:30.682758: train_loss -0.7892 +2024-11-22 13:07:30.684901: val_loss -0.7679 +2024-11-22 13:07:30.685012: Pseudo dice [0.8435] +2024-11-22 13:07:30.685112: Epoch time: 18.85 s +2024-11-22 13:07:31.616888: +2024-11-22 13:07:31.617828: Epoch 4765 +2024-11-22 13:07:31.617951: Current learning rate: 0.00443 +2024-11-22 13:07:51.255581: train_loss -0.7936 +2024-11-22 13:07:51.263567: val_loss -0.7441 +2024-11-22 13:07:51.263688: Pseudo dice [0.8348] +2024-11-22 13:07:51.263788: Epoch time: 19.64 s +2024-11-22 13:07:52.341637: +2024-11-22 13:07:52.342105: Epoch 4766 +2024-11-22 13:07:52.342217: Current learning rate: 0.00443 +2024-11-22 13:08:10.178645: train_loss -0.7794 +2024-11-22 13:08:10.190637: val_loss -0.7669 +2024-11-22 13:08:10.190769: Pseudo dice [0.8546] +2024-11-22 13:08:10.190857: Epoch time: 17.84 s +2024-11-22 13:08:11.124220: +2024-11-22 13:08:11.125620: Epoch 4767 +2024-11-22 13:08:11.125787: Current learning rate: 0.00442 +2024-11-22 13:08:30.733022: train_loss -0.7923 +2024-11-22 13:08:30.740312: val_loss -0.7977 +2024-11-22 13:08:30.740460: Pseudo dice [0.8693] +2024-11-22 13:08:30.740557: Epoch time: 19.61 s +2024-11-22 13:08:31.661150: +2024-11-22 13:08:31.661989: Epoch 4768 +2024-11-22 13:08:31.662114: Current learning rate: 0.00442 +2024-11-22 13:08:50.362168: train_loss -0.8051 +2024-11-22 13:08:50.381662: val_loss -0.7624 +2024-11-22 13:08:50.381831: Pseudo dice [0.8579] +2024-11-22 13:08:50.381919: Epoch time: 18.7 s +2024-11-22 13:08:51.319038: +2024-11-22 13:08:51.319529: Epoch 4769 +2024-11-22 13:08:51.319652: Current learning rate: 0.00442 +2024-11-22 13:09:11.251854: train_loss -0.789 +2024-11-22 13:09:11.256505: val_loss -0.7794 +2024-11-22 13:09:11.256841: Pseudo dice [0.8611] +2024-11-22 13:09:11.256935: Epoch time: 19.93 s +2024-11-22 13:09:12.199390: +2024-11-22 13:09:12.201962: Epoch 4770 +2024-11-22 13:09:12.202096: Current learning rate: 0.00442 +2024-11-22 13:09:32.560398: train_loss -0.7997 +2024-11-22 13:09:32.569373: val_loss -0.7767 +2024-11-22 13:09:32.569534: Pseudo dice [0.8543] +2024-11-22 13:09:32.569635: Epoch time: 20.36 s +2024-11-22 13:09:33.437413: +2024-11-22 13:09:33.438811: Epoch 4771 +2024-11-22 13:09:33.438935: Current learning rate: 0.00442 +2024-11-22 13:09:52.183131: train_loss -0.796 +2024-11-22 13:09:52.202755: val_loss -0.7788 +2024-11-22 13:09:52.202921: Pseudo dice [0.8623] +2024-11-22 13:09:52.203049: Epoch time: 18.75 s +2024-11-22 13:09:53.209302: +2024-11-22 13:09:53.210574: Epoch 4772 +2024-11-22 13:09:53.210705: Current learning rate: 0.00442 +2024-11-22 13:10:11.711337: train_loss -0.7881 +2024-11-22 13:10:11.714298: val_loss -0.7607 +2024-11-22 13:10:11.714450: Pseudo dice [0.8546] +2024-11-22 13:10:11.714541: Epoch time: 18.5 s +2024-11-22 13:10:12.997701: +2024-11-22 13:10:12.999114: Epoch 4773 +2024-11-22 13:10:12.999239: Current learning rate: 0.00442 +2024-11-22 13:10:32.193915: train_loss -0.7827 +2024-11-22 13:10:32.201635: val_loss -0.7598 +2024-11-22 13:10:32.201753: Pseudo dice [0.8536] +2024-11-22 13:10:32.201842: Epoch time: 19.2 s +2024-11-22 13:10:33.280257: +2024-11-22 13:10:33.280765: Epoch 4774 +2024-11-22 13:10:33.280891: Current learning rate: 0.00442 +2024-11-22 13:10:52.609704: train_loss -0.7752 +2024-11-22 13:10:52.612628: val_loss -0.7682 +2024-11-22 13:10:52.612725: Pseudo dice [0.8451] +2024-11-22 13:10:52.612807: Epoch time: 19.33 s +2024-11-22 13:10:53.471630: +2024-11-22 13:10:53.472415: Epoch 4775 +2024-11-22 13:10:53.472529: Current learning rate: 0.00441 +2024-11-22 13:11:12.455440: train_loss -0.78 +2024-11-22 13:11:12.459778: val_loss -0.7676 +2024-11-22 13:11:12.459898: Pseudo dice [0.8632] +2024-11-22 13:11:12.460007: Epoch time: 18.98 s +2024-11-22 13:11:13.499321: +2024-11-22 13:11:13.501004: Epoch 4776 +2024-11-22 13:11:13.501134: Current learning rate: 0.00441 +2024-11-22 13:11:34.210427: train_loss -0.7819 +2024-11-22 13:11:34.226710: val_loss -0.7574 +2024-11-22 13:11:34.226862: Pseudo dice [0.8418] +2024-11-22 13:11:34.226947: Epoch time: 20.71 s +2024-11-22 13:11:35.241222: +2024-11-22 13:11:35.242665: Epoch 4777 +2024-11-22 13:11:35.242783: Current learning rate: 0.00441 +2024-11-22 13:11:55.619457: train_loss -0.7848 +2024-11-22 13:11:55.625898: val_loss -0.7739 +2024-11-22 13:11:55.626031: Pseudo dice [0.8558] +2024-11-22 13:11:55.626189: Epoch time: 20.38 s +2024-11-22 13:11:56.536143: +2024-11-22 13:11:56.537468: Epoch 4778 +2024-11-22 13:11:56.537587: Current learning rate: 0.00441 +2024-11-22 13:12:15.563075: train_loss -0.7868 +2024-11-22 13:12:15.566658: val_loss -0.7542 +2024-11-22 13:12:15.566783: Pseudo dice [0.8579] +2024-11-22 13:12:15.566882: Epoch time: 19.03 s +2024-11-22 13:12:16.779987: +2024-11-22 13:12:16.781627: Epoch 4779 +2024-11-22 13:12:16.781749: Current learning rate: 0.00441 +2024-11-22 13:12:35.497220: train_loss -0.789 +2024-11-22 13:12:35.506979: val_loss -0.7934 +2024-11-22 13:12:35.507165: Pseudo dice [0.8552] +2024-11-22 13:12:35.507313: Epoch time: 18.72 s +2024-11-22 13:12:36.516396: +2024-11-22 13:12:36.517777: Epoch 4780 +2024-11-22 13:12:36.517898: Current learning rate: 0.00441 +2024-11-22 13:12:55.663854: train_loss -0.7966 +2024-11-22 13:12:55.672582: val_loss -0.7809 +2024-11-22 13:12:55.672772: Pseudo dice [0.841] +2024-11-22 13:12:55.672871: Epoch time: 19.15 s +2024-11-22 13:12:56.872733: +2024-11-22 13:12:56.873739: Epoch 4781 +2024-11-22 13:12:56.873857: Current learning rate: 0.00441 +2024-11-22 13:13:15.270090: train_loss -0.7971 +2024-11-22 13:13:15.284753: val_loss -0.7774 +2024-11-22 13:13:15.284892: Pseudo dice [0.8554] +2024-11-22 13:13:15.284970: Epoch time: 18.4 s +2024-11-22 13:13:16.135399: +2024-11-22 13:13:16.135619: Epoch 4782 +2024-11-22 13:13:16.135751: Current learning rate: 0.00441 +2024-11-22 13:13:34.831902: train_loss -0.7903 +2024-11-22 13:13:34.833681: val_loss -0.7918 +2024-11-22 13:13:34.833798: Pseudo dice [0.8598] +2024-11-22 13:13:34.833878: Epoch time: 18.7 s +2024-11-22 13:13:35.676353: +2024-11-22 13:13:35.676548: Epoch 4783 +2024-11-22 13:13:35.676679: Current learning rate: 0.0044 +2024-11-22 13:13:53.161711: train_loss -0.7926 +2024-11-22 13:13:53.162755: val_loss -0.7377 +2024-11-22 13:13:53.162858: Pseudo dice [0.8502] +2024-11-22 13:13:53.162945: Epoch time: 17.49 s +2024-11-22 13:13:54.006575: +2024-11-22 13:13:54.006768: Epoch 4784 +2024-11-22 13:13:54.006884: Current learning rate: 0.0044 +2024-11-22 13:14:13.988254: train_loss -0.7821 +2024-11-22 13:14:13.989186: val_loss -0.7684 +2024-11-22 13:14:13.989292: Pseudo dice [0.8472] +2024-11-22 13:14:13.989375: Epoch time: 19.98 s +2024-11-22 13:14:15.369365: +2024-11-22 13:14:15.369596: Epoch 4785 +2024-11-22 13:14:15.369711: Current learning rate: 0.0044 +2024-11-22 13:14:33.463304: train_loss -0.7811 +2024-11-22 13:14:33.467958: val_loss -0.7692 +2024-11-22 13:14:33.468110: Pseudo dice [0.8437] +2024-11-22 13:14:33.468203: Epoch time: 18.09 s +2024-11-22 13:14:34.343037: +2024-11-22 13:14:34.343279: Epoch 4786 +2024-11-22 13:14:34.343399: Current learning rate: 0.0044 +2024-11-22 13:14:52.944240: train_loss -0.7909 +2024-11-22 13:14:52.946146: val_loss -0.7824 +2024-11-22 13:14:52.946267: Pseudo dice [0.8668] +2024-11-22 13:14:52.946364: Epoch time: 18.6 s +2024-11-22 13:14:53.953623: +2024-11-22 13:14:53.953854: Epoch 4787 +2024-11-22 13:14:53.953969: Current learning rate: 0.0044 +2024-11-22 13:15:12.359909: train_loss -0.7845 +2024-11-22 13:15:12.360447: val_loss -0.7742 +2024-11-22 13:15:12.360530: Pseudo dice [0.8561] +2024-11-22 13:15:12.360615: Epoch time: 18.41 s +2024-11-22 13:15:13.202942: +2024-11-22 13:15:13.203149: Epoch 4788 +2024-11-22 13:15:13.203268: Current learning rate: 0.0044 +2024-11-22 13:15:32.593809: train_loss -0.7904 +2024-11-22 13:15:32.598886: val_loss -0.7682 +2024-11-22 13:15:32.599044: Pseudo dice [0.845] +2024-11-22 13:15:32.599143: Epoch time: 19.39 s +2024-11-22 13:15:33.495250: +2024-11-22 13:15:33.495476: Epoch 4789 +2024-11-22 13:15:33.495600: Current learning rate: 0.0044 +2024-11-22 13:15:52.154546: train_loss -0.7846 +2024-11-22 13:15:52.155106: val_loss -0.7792 +2024-11-22 13:15:52.155197: Pseudo dice [0.8491] +2024-11-22 13:15:52.155288: Epoch time: 18.66 s +2024-11-22 13:15:53.001963: +2024-11-22 13:15:53.002162: Epoch 4790 +2024-11-22 13:15:53.002293: Current learning rate: 0.0044 +2024-11-22 13:16:11.594624: train_loss -0.7941 +2024-11-22 13:16:11.606783: val_loss -0.782 +2024-11-22 13:16:11.606988: Pseudo dice [0.8439] +2024-11-22 13:16:11.607087: Epoch time: 18.59 s +2024-11-22 13:16:12.489539: +2024-11-22 13:16:12.490515: Epoch 4791 +2024-11-22 13:16:12.490643: Current learning rate: 0.00439 +2024-11-22 13:16:31.731526: train_loss -0.8009 +2024-11-22 13:16:31.736944: val_loss -0.7856 +2024-11-22 13:16:31.737078: Pseudo dice [0.861] +2024-11-22 13:16:31.737180: Epoch time: 19.24 s +2024-11-22 13:16:32.661482: +2024-11-22 13:16:32.662792: Epoch 4792 +2024-11-22 13:16:32.662916: Current learning rate: 0.00439 +2024-11-22 13:16:51.939166: train_loss -0.7979 +2024-11-22 13:16:51.941468: val_loss -0.7984 +2024-11-22 13:16:51.941560: Pseudo dice [0.8694] +2024-11-22 13:16:51.941649: Epoch time: 19.28 s +2024-11-22 13:16:52.792375: +2024-11-22 13:16:52.793859: Epoch 4793 +2024-11-22 13:16:52.793986: Current learning rate: 0.00439 +2024-11-22 13:17:12.681582: train_loss -0.7915 +2024-11-22 13:17:12.689881: val_loss -0.7816 +2024-11-22 13:17:12.690025: Pseudo dice [0.8513] +2024-11-22 13:17:12.690134: Epoch time: 19.89 s +2024-11-22 13:17:13.587803: +2024-11-22 13:17:13.588605: Epoch 4794 +2024-11-22 13:17:13.588742: Current learning rate: 0.00439 +2024-11-22 13:17:32.670170: train_loss -0.7955 +2024-11-22 13:17:32.673025: val_loss -0.7562 +2024-11-22 13:17:32.673132: Pseudo dice [0.842] +2024-11-22 13:17:32.673222: Epoch time: 19.08 s +2024-11-22 13:17:33.525856: +2024-11-22 13:17:33.526957: Epoch 4795 +2024-11-22 13:17:33.527081: Current learning rate: 0.00439 +2024-11-22 13:17:52.797738: train_loss -0.7727 +2024-11-22 13:17:52.803357: val_loss -0.7609 +2024-11-22 13:17:52.803494: Pseudo dice [0.8487] +2024-11-22 13:17:52.803601: Epoch time: 19.27 s +2024-11-22 13:17:53.664031: +2024-11-22 13:17:53.666233: Epoch 4796 +2024-11-22 13:17:53.666375: Current learning rate: 0.00439 +2024-11-22 13:18:11.169933: train_loss -0.7855 +2024-11-22 13:18:11.187305: val_loss -0.7456 +2024-11-22 13:18:11.187459: Pseudo dice [0.8359] +2024-11-22 13:18:11.187556: Epoch time: 17.51 s +2024-11-22 13:18:12.601489: +2024-11-22 13:18:12.603062: Epoch 4797 +2024-11-22 13:18:12.603182: Current learning rate: 0.00439 +2024-11-22 13:18:33.475218: train_loss -0.7822 +2024-11-22 13:18:33.481602: val_loss -0.7624 +2024-11-22 13:18:33.481745: Pseudo dice [0.8461] +2024-11-22 13:18:33.481849: Epoch time: 20.87 s +2024-11-22 13:18:34.443274: +2024-11-22 13:18:34.444384: Epoch 4798 +2024-11-22 13:18:34.444520: Current learning rate: 0.00439 +2024-11-22 13:18:54.419132: train_loss -0.7936 +2024-11-22 13:18:54.428311: val_loss -0.7539 +2024-11-22 13:18:54.428444: Pseudo dice [0.8682] +2024-11-22 13:18:54.428547: Epoch time: 19.98 s +2024-11-22 13:18:55.290676: +2024-11-22 13:18:55.292750: Epoch 4799 +2024-11-22 13:18:55.292872: Current learning rate: 0.00439 +2024-11-22 13:19:15.303397: train_loss -0.7772 +2024-11-22 13:19:15.306533: val_loss -0.7838 +2024-11-22 13:19:15.306638: Pseudo dice [0.8458] +2024-11-22 13:19:15.306729: Epoch time: 20.01 s +2024-11-22 13:19:16.444095: +2024-11-22 13:19:16.445649: Epoch 4800 +2024-11-22 13:19:16.445771: Current learning rate: 0.00438 +2024-11-22 13:19:36.339391: train_loss -0.7837 +2024-11-22 13:19:36.345441: val_loss -0.7767 +2024-11-22 13:19:36.345565: Pseudo dice [0.8426] +2024-11-22 13:19:36.345654: Epoch time: 19.9 s +2024-11-22 13:19:37.269056: +2024-11-22 13:19:37.270672: Epoch 4801 +2024-11-22 13:19:37.270796: Current learning rate: 0.00438 +2024-11-22 13:19:56.844129: train_loss -0.7867 +2024-11-22 13:19:56.847757: val_loss -0.7681 +2024-11-22 13:19:56.847905: Pseudo dice [0.8618] +2024-11-22 13:19:56.847993: Epoch time: 19.58 s +2024-11-22 13:19:57.791201: +2024-11-22 13:19:57.792592: Epoch 4802 +2024-11-22 13:19:57.792719: Current learning rate: 0.00438 +2024-11-22 13:20:16.993559: train_loss -0.7944 +2024-11-22 13:20:16.995993: val_loss -0.7714 +2024-11-22 13:20:16.996133: Pseudo dice [0.8453] +2024-11-22 13:20:16.996228: Epoch time: 19.2 s +2024-11-22 13:20:17.847929: +2024-11-22 13:20:17.849049: Epoch 4803 +2024-11-22 13:20:17.849180: Current learning rate: 0.00438 +2024-11-22 13:20:37.530290: train_loss -0.794 +2024-11-22 13:20:37.536987: val_loss -0.7754 +2024-11-22 13:20:37.537257: Pseudo dice [0.8585] +2024-11-22 13:20:37.537355: Epoch time: 19.68 s +2024-11-22 13:20:38.584620: +2024-11-22 13:20:38.586171: Epoch 4804 +2024-11-22 13:20:38.586295: Current learning rate: 0.00438 +2024-11-22 13:20:57.291441: train_loss -0.7803 +2024-11-22 13:20:57.310456: val_loss -0.7582 +2024-11-22 13:20:57.310609: Pseudo dice [0.8497] +2024-11-22 13:20:57.310718: Epoch time: 18.71 s +2024-11-22 13:20:58.168931: +2024-11-22 13:20:58.170632: Epoch 4805 +2024-11-22 13:20:58.170764: Current learning rate: 0.00438 +2024-11-22 13:21:17.992554: train_loss -0.7908 +2024-11-22 13:21:17.998777: val_loss -0.7719 +2024-11-22 13:21:17.998914: Pseudo dice [0.8528] +2024-11-22 13:21:17.999013: Epoch time: 19.82 s +2024-11-22 13:21:18.871324: +2024-11-22 13:21:18.872671: Epoch 4806 +2024-11-22 13:21:18.872792: Current learning rate: 0.00438 +2024-11-22 13:21:37.121432: train_loss -0.7956 +2024-11-22 13:21:37.130848: val_loss -0.7602 +2024-11-22 13:21:37.130972: Pseudo dice [0.8502] +2024-11-22 13:21:37.131085: Epoch time: 18.25 s +2024-11-22 13:21:38.200240: +2024-11-22 13:21:38.200752: Epoch 4807 +2024-11-22 13:21:38.200887: Current learning rate: 0.00438 +2024-11-22 13:21:57.212183: train_loss -0.7932 +2024-11-22 13:21:57.214622: val_loss -0.7656 +2024-11-22 13:21:57.214991: Pseudo dice [0.862] +2024-11-22 13:21:57.215166: Epoch time: 19.01 s +2024-11-22 13:21:58.088309: +2024-11-22 13:21:58.089635: Epoch 4808 +2024-11-22 13:21:58.089756: Current learning rate: 0.00437 +2024-11-22 13:22:18.211694: train_loss -0.7911 +2024-11-22 13:22:18.221780: val_loss -0.7503 +2024-11-22 13:22:18.221932: Pseudo dice [0.8542] +2024-11-22 13:22:18.222019: Epoch time: 20.12 s +2024-11-22 13:22:19.113839: +2024-11-22 13:22:19.115231: Epoch 4809 +2024-11-22 13:22:19.115357: Current learning rate: 0.00437 +2024-11-22 13:22:38.664842: train_loss -0.7751 +2024-11-22 13:22:38.673517: val_loss -0.7457 +2024-11-22 13:22:38.673702: Pseudo dice [0.8486] +2024-11-22 13:22:38.673792: Epoch time: 19.55 s +2024-11-22 13:22:39.574612: +2024-11-22 13:22:39.575098: Epoch 4810 +2024-11-22 13:22:39.575214: Current learning rate: 0.00437 +2024-11-22 13:22:59.784748: train_loss -0.7723 +2024-11-22 13:22:59.786862: val_loss -0.7547 +2024-11-22 13:22:59.786981: Pseudo dice [0.8494] +2024-11-22 13:22:59.787091: Epoch time: 20.21 s +2024-11-22 13:23:00.640086: +2024-11-22 13:23:00.640919: Epoch 4811 +2024-11-22 13:23:00.641051: Current learning rate: 0.00437 +2024-11-22 13:23:20.611466: train_loss -0.7746 +2024-11-22 13:23:20.618706: val_loss -0.7628 +2024-11-22 13:23:20.618899: Pseudo dice [0.8451] +2024-11-22 13:23:20.619002: Epoch time: 19.97 s +2024-11-22 13:23:21.483196: +2024-11-22 13:23:21.485329: Epoch 4812 +2024-11-22 13:23:21.485508: Current learning rate: 0.00437 +2024-11-22 13:23:41.170462: train_loss -0.7828 +2024-11-22 13:23:41.173212: val_loss -0.7661 +2024-11-22 13:23:41.173309: Pseudo dice [0.8531] +2024-11-22 13:23:41.173414: Epoch time: 19.69 s +2024-11-22 13:23:42.024132: +2024-11-22 13:23:42.025676: Epoch 4813 +2024-11-22 13:23:42.025819: Current learning rate: 0.00437 +2024-11-22 13:24:01.346424: train_loss -0.7764 +2024-11-22 13:24:01.352305: val_loss -0.7615 +2024-11-22 13:24:01.352435: Pseudo dice [0.8441] +2024-11-22 13:24:01.352530: Epoch time: 19.32 s +2024-11-22 13:24:02.213407: +2024-11-22 13:24:02.214482: Epoch 4814 +2024-11-22 13:24:02.214599: Current learning rate: 0.00437 +2024-11-22 13:24:21.530172: train_loss -0.7756 +2024-11-22 13:24:21.532369: val_loss -0.7864 +2024-11-22 13:24:21.532474: Pseudo dice [0.8636] +2024-11-22 13:24:21.532568: Epoch time: 19.32 s +2024-11-22 13:24:22.384327: +2024-11-22 13:24:22.385086: Epoch 4815 +2024-11-22 13:24:22.385206: Current learning rate: 0.00437 +2024-11-22 13:24:42.061731: train_loss -0.7694 +2024-11-22 13:24:42.071893: val_loss -0.7786 +2024-11-22 13:24:42.072043: Pseudo dice [0.8532] +2024-11-22 13:24:42.072140: Epoch time: 19.68 s +2024-11-22 13:24:43.028300: +2024-11-22 13:24:43.028735: Epoch 4816 +2024-11-22 13:24:43.028855: Current learning rate: 0.00436 +2024-11-22 13:25:02.255160: train_loss -0.7701 +2024-11-22 13:25:02.257931: val_loss -0.765 +2024-11-22 13:25:02.258035: Pseudo dice [0.8359] +2024-11-22 13:25:02.258132: Epoch time: 19.23 s +2024-11-22 13:25:03.103304: +2024-11-22 13:25:03.104054: Epoch 4817 +2024-11-22 13:25:03.104182: Current learning rate: 0.00436 +2024-11-22 13:25:23.480808: train_loss -0.7893 +2024-11-22 13:25:23.484731: val_loss -0.7507 +2024-11-22 13:25:23.484895: Pseudo dice [0.8295] +2024-11-22 13:25:23.484988: Epoch time: 20.38 s +2024-11-22 13:25:24.404722: +2024-11-22 13:25:24.406179: Epoch 4818 +2024-11-22 13:25:24.406308: Current learning rate: 0.00436 +2024-11-22 13:25:44.119676: train_loss -0.7663 +2024-11-22 13:25:44.131312: val_loss -0.7619 +2024-11-22 13:25:44.131469: Pseudo dice [0.8506] +2024-11-22 13:25:44.131575: Epoch time: 19.72 s +2024-11-22 13:25:45.029547: +2024-11-22 13:25:45.031506: Epoch 4819 +2024-11-22 13:25:45.031633: Current learning rate: 0.00436 +2024-11-22 13:26:06.065467: train_loss -0.7779 +2024-11-22 13:26:06.073508: val_loss -0.7645 +2024-11-22 13:26:06.073625: Pseudo dice [0.8577] +2024-11-22 13:26:06.073722: Epoch time: 21.04 s +2024-11-22 13:26:07.370670: +2024-11-22 13:26:07.372287: Epoch 4820 +2024-11-22 13:26:07.372432: Current learning rate: 0.00436 +2024-11-22 13:26:27.178154: train_loss -0.7825 +2024-11-22 13:26:27.188691: val_loss -0.7596 +2024-11-22 13:26:27.188827: Pseudo dice [0.854] +2024-11-22 13:26:27.188919: Epoch time: 19.81 s +2024-11-22 13:26:28.161466: +2024-11-22 13:26:28.162299: Epoch 4821 +2024-11-22 13:26:28.162434: Current learning rate: 0.00436 +2024-11-22 13:26:48.327774: train_loss -0.7946 +2024-11-22 13:26:48.332716: val_loss -0.7955 +2024-11-22 13:26:48.332833: Pseudo dice [0.8675] +2024-11-22 13:26:48.332924: Epoch time: 20.17 s +2024-11-22 13:26:49.523231: +2024-11-22 13:26:49.524869: Epoch 4822 +2024-11-22 13:26:49.524995: Current learning rate: 0.00436 +2024-11-22 13:27:09.809667: train_loss -0.7848 +2024-11-22 13:27:09.815488: val_loss -0.7837 +2024-11-22 13:27:09.815622: Pseudo dice [0.8607] +2024-11-22 13:27:09.815732: Epoch time: 20.29 s +2024-11-22 13:27:10.692834: +2024-11-22 13:27:10.694397: Epoch 4823 +2024-11-22 13:27:10.694523: Current learning rate: 0.00436 +2024-11-22 13:27:30.163784: train_loss -0.7783 +2024-11-22 13:27:30.177178: val_loss -0.7725 +2024-11-22 13:27:30.177317: Pseudo dice [0.8522] +2024-11-22 13:27:30.177399: Epoch time: 19.47 s +2024-11-22 13:27:31.125435: +2024-11-22 13:27:31.125650: Epoch 4824 +2024-11-22 13:27:31.125766: Current learning rate: 0.00435 +2024-11-22 13:27:50.658416: train_loss -0.7885 +2024-11-22 13:27:50.681498: val_loss -0.7744 +2024-11-22 13:27:50.681639: Pseudo dice [0.8507] +2024-11-22 13:27:50.681740: Epoch time: 19.53 s +2024-11-22 13:27:51.642117: +2024-11-22 13:27:51.643172: Epoch 4825 +2024-11-22 13:27:51.643295: Current learning rate: 0.00435 +2024-11-22 13:28:10.577318: train_loss -0.7895 +2024-11-22 13:28:10.580238: val_loss -0.7504 +2024-11-22 13:28:10.580353: Pseudo dice [0.8553] +2024-11-22 13:28:10.580434: Epoch time: 18.94 s +2024-11-22 13:28:11.684347: +2024-11-22 13:28:11.684808: Epoch 4826 +2024-11-22 13:28:11.684935: Current learning rate: 0.00435 +2024-11-22 13:28:32.086143: train_loss -0.7785 +2024-11-22 13:28:32.092983: val_loss -0.7834 +2024-11-22 13:28:32.093132: Pseudo dice [0.8606] +2024-11-22 13:28:32.093217: Epoch time: 20.4 s +2024-11-22 13:28:32.975172: +2024-11-22 13:28:32.976120: Epoch 4827 +2024-11-22 13:28:32.977074: Current learning rate: 0.00435 +2024-11-22 13:28:53.448038: train_loss -0.7612 +2024-11-22 13:28:53.456604: val_loss -0.7683 +2024-11-22 13:28:53.456742: Pseudo dice [0.837] +2024-11-22 13:28:53.456838: Epoch time: 20.47 s +2024-11-22 13:28:54.424312: +2024-11-22 13:28:54.425784: Epoch 4828 +2024-11-22 13:28:54.425908: Current learning rate: 0.00435 +2024-11-22 13:29:13.417043: train_loss -0.7628 +2024-11-22 13:29:13.420453: val_loss -0.753 +2024-11-22 13:29:13.420581: Pseudo dice [0.8399] +2024-11-22 13:29:13.420663: Epoch time: 18.99 s +2024-11-22 13:29:14.264845: +2024-11-22 13:29:14.266020: Epoch 4829 +2024-11-22 13:29:14.266148: Current learning rate: 0.00435 +2024-11-22 13:29:33.575552: train_loss -0.7795 +2024-11-22 13:29:33.588598: val_loss -0.7647 +2024-11-22 13:29:33.588731: Pseudo dice [0.8464] +2024-11-22 13:29:33.588824: Epoch time: 19.31 s +2024-11-22 13:29:34.483151: +2024-11-22 13:29:34.483568: Epoch 4830 +2024-11-22 13:29:34.483693: Current learning rate: 0.00435 +2024-11-22 13:29:54.015727: train_loss -0.7846 +2024-11-22 13:29:54.028206: val_loss -0.7953 +2024-11-22 13:29:54.028348: Pseudo dice [0.8648] +2024-11-22 13:29:54.028439: Epoch time: 19.53 s +2024-11-22 13:29:54.965517: +2024-11-22 13:29:54.966727: Epoch 4831 +2024-11-22 13:29:54.966865: Current learning rate: 0.00435 +2024-11-22 13:30:14.415026: train_loss -0.7847 +2024-11-22 13:30:14.422407: val_loss -0.7669 +2024-11-22 13:30:14.422538: Pseudo dice [0.8458] +2024-11-22 13:30:14.422637: Epoch time: 19.45 s +2024-11-22 13:30:15.779780: +2024-11-22 13:30:15.780813: Epoch 4832 +2024-11-22 13:30:15.780940: Current learning rate: 0.00434 +2024-11-22 13:30:35.906506: train_loss -0.7825 +2024-11-22 13:30:35.915325: val_loss -0.7893 +2024-11-22 13:30:35.915478: Pseudo dice [0.8621] +2024-11-22 13:30:35.915565: Epoch time: 20.13 s +2024-11-22 13:30:36.810490: +2024-11-22 13:30:36.824940: Epoch 4833 +2024-11-22 13:30:36.825106: Current learning rate: 0.00434 +2024-11-22 13:30:56.874403: train_loss -0.7898 +2024-11-22 13:30:56.888395: val_loss -0.7703 +2024-11-22 13:30:56.888522: Pseudo dice [0.8634] +2024-11-22 13:30:56.888612: Epoch time: 20.06 s +2024-11-22 13:30:57.888034: +2024-11-22 13:30:57.889171: Epoch 4834 +2024-11-22 13:30:57.889298: Current learning rate: 0.00434 +2024-11-22 13:31:17.614908: train_loss -0.7854 +2024-11-22 13:31:17.623314: val_loss -0.7695 +2024-11-22 13:31:17.623516: Pseudo dice [0.8549] +2024-11-22 13:31:17.623622: Epoch time: 19.73 s +2024-11-22 13:31:18.656662: +2024-11-22 13:31:18.657500: Epoch 4835 +2024-11-22 13:31:18.657668: Current learning rate: 0.00434 +2024-11-22 13:31:38.270870: train_loss -0.7897 +2024-11-22 13:31:38.283051: val_loss -0.7844 +2024-11-22 13:31:38.283190: Pseudo dice [0.8475] +2024-11-22 13:31:38.283279: Epoch time: 19.62 s +2024-11-22 13:31:39.310177: +2024-11-22 13:31:39.310962: Epoch 4836 +2024-11-22 13:31:39.311097: Current learning rate: 0.00434 +2024-11-22 13:31:58.884263: train_loss -0.794 +2024-11-22 13:31:58.896327: val_loss -0.7829 +2024-11-22 13:31:58.896483: Pseudo dice [0.8588] +2024-11-22 13:31:58.898010: Epoch time: 19.57 s +2024-11-22 13:31:59.836638: +2024-11-22 13:31:59.837156: Epoch 4837 +2024-11-22 13:31:59.837279: Current learning rate: 0.00434 +2024-11-22 13:32:18.898949: train_loss -0.7937 +2024-11-22 13:32:18.905923: val_loss -0.7818 +2024-11-22 13:32:18.913127: Pseudo dice [0.8463] +2024-11-22 13:32:18.913279: Epoch time: 19.06 s +2024-11-22 13:32:19.932003: +2024-11-22 13:32:19.932857: Epoch 4838 +2024-11-22 13:32:19.932976: Current learning rate: 0.00434 +2024-11-22 13:32:38.328942: train_loss -0.7956 +2024-11-22 13:32:38.334811: val_loss -0.7597 +2024-11-22 13:32:38.335007: Pseudo dice [0.8471] +2024-11-22 13:32:38.335125: Epoch time: 18.4 s +2024-11-22 13:32:39.235092: +2024-11-22 13:32:39.235941: Epoch 4839 +2024-11-22 13:32:39.236065: Current learning rate: 0.00434 +2024-11-22 13:32:58.069522: train_loss -0.7844 +2024-11-22 13:32:58.087831: val_loss -0.7506 +2024-11-22 13:32:58.087984: Pseudo dice [0.8304] +2024-11-22 13:32:58.088085: Epoch time: 18.84 s +2024-11-22 13:32:58.995272: +2024-11-22 13:32:58.996219: Epoch 4840 +2024-11-22 13:32:58.996334: Current learning rate: 0.00433 +2024-11-22 13:33:17.849244: train_loss -0.7837 +2024-11-22 13:33:17.864587: val_loss -0.7838 +2024-11-22 13:33:17.864741: Pseudo dice [0.8586] +2024-11-22 13:33:17.864833: Epoch time: 18.85 s +2024-11-22 13:33:18.735590: +2024-11-22 13:33:18.736439: Epoch 4841 +2024-11-22 13:33:18.736584: Current learning rate: 0.00433 +2024-11-22 13:33:37.251116: train_loss -0.7869 +2024-11-22 13:33:37.273385: val_loss -0.7976 +2024-11-22 13:33:37.273537: Pseudo dice [0.8578] +2024-11-22 13:33:37.273641: Epoch time: 18.52 s +2024-11-22 13:33:38.169485: +2024-11-22 13:33:38.169975: Epoch 4842 +2024-11-22 13:33:38.170113: Current learning rate: 0.00433 +2024-11-22 13:33:57.615832: train_loss -0.7852 +2024-11-22 13:33:57.619194: val_loss -0.7734 +2024-11-22 13:33:57.619310: Pseudo dice [0.8502] +2024-11-22 13:33:57.619405: Epoch time: 19.45 s +2024-11-22 13:33:58.510501: +2024-11-22 13:33:58.512457: Epoch 4843 +2024-11-22 13:33:58.512581: Current learning rate: 0.00433 +2024-11-22 13:34:18.348491: train_loss -0.7841 +2024-11-22 13:34:18.354801: val_loss -0.7819 +2024-11-22 13:34:18.354978: Pseudo dice [0.8533] +2024-11-22 13:34:18.355083: Epoch time: 19.84 s +2024-11-22 13:34:19.615538: +2024-11-22 13:34:19.616366: Epoch 4844 +2024-11-22 13:34:19.616492: Current learning rate: 0.00433 +2024-11-22 13:34:38.799684: train_loss -0.7889 +2024-11-22 13:34:38.808213: val_loss -0.7762 +2024-11-22 13:34:38.808349: Pseudo dice [0.85] +2024-11-22 13:34:38.808441: Epoch time: 19.18 s +2024-11-22 13:34:39.741163: +2024-11-22 13:34:39.742888: Epoch 4845 +2024-11-22 13:34:39.743012: Current learning rate: 0.00433 +2024-11-22 13:34:59.128463: train_loss -0.7922 +2024-11-22 13:34:59.134875: val_loss -0.7657 +2024-11-22 13:34:59.135112: Pseudo dice [0.8526] +2024-11-22 13:34:59.166902: Epoch time: 19.39 s +2024-11-22 13:35:00.060569: +2024-11-22 13:35:00.126419: Epoch 4846 +2024-11-22 13:35:00.126967: Current learning rate: 0.00433 +2024-11-22 13:35:19.335493: train_loss -0.7953 +2024-11-22 13:35:19.342874: val_loss -0.7803 +2024-11-22 13:35:19.343023: Pseudo dice [0.8533] +2024-11-22 13:35:19.343123: Epoch time: 19.28 s +2024-11-22 13:35:20.291017: +2024-11-22 13:35:20.291545: Epoch 4847 +2024-11-22 13:35:20.291671: Current learning rate: 0.00433 +2024-11-22 13:35:40.308004: train_loss -0.7911 +2024-11-22 13:35:40.314976: val_loss -0.7642 +2024-11-22 13:35:40.315136: Pseudo dice [0.8397] +2024-11-22 13:35:40.315233: Epoch time: 20.02 s +2024-11-22 13:35:41.235102: +2024-11-22 13:35:41.235962: Epoch 4848 +2024-11-22 13:35:41.236093: Current learning rate: 0.00432 +2024-11-22 13:36:00.888846: train_loss -0.7868 +2024-11-22 13:36:00.897378: val_loss -0.7713 +2024-11-22 13:36:00.897527: Pseudo dice [0.8501] +2024-11-22 13:36:00.897629: Epoch time: 19.65 s +2024-11-22 13:36:01.867457: +2024-11-22 13:36:01.868791: Epoch 4849 +2024-11-22 13:36:01.868916: Current learning rate: 0.00432 +2024-11-22 13:36:21.360902: train_loss -0.7903 +2024-11-22 13:36:21.367645: val_loss -0.7432 +2024-11-22 13:36:21.367802: Pseudo dice [0.8655] +2024-11-22 13:36:21.367945: Epoch time: 19.49 s +2024-11-22 13:36:22.655654: +2024-11-22 13:36:22.658127: Epoch 4850 +2024-11-22 13:36:22.658255: Current learning rate: 0.00432 +2024-11-22 13:36:41.174429: train_loss -0.7902 +2024-11-22 13:36:41.177567: val_loss -0.7697 +2024-11-22 13:36:41.177667: Pseudo dice [0.8539] +2024-11-22 13:36:41.177759: Epoch time: 18.52 s +2024-11-22 13:36:42.034927: +2024-11-22 13:36:42.035813: Epoch 4851 +2024-11-22 13:36:42.035959: Current learning rate: 0.00432 +2024-11-22 13:37:01.127826: train_loss -0.7835 +2024-11-22 13:37:01.136226: val_loss -0.7874 +2024-11-22 13:37:01.136366: Pseudo dice [0.8605] +2024-11-22 13:37:01.136481: Epoch time: 19.09 s +2024-11-22 13:37:02.120763: +2024-11-22 13:37:02.121702: Epoch 4852 +2024-11-22 13:37:02.121829: Current learning rate: 0.00432 +2024-11-22 13:37:21.598021: train_loss -0.7767 +2024-11-22 13:37:21.604695: val_loss -0.7904 +2024-11-22 13:37:21.604892: Pseudo dice [0.8577] +2024-11-22 13:37:21.604985: Epoch time: 19.48 s +2024-11-22 13:37:22.701971: +2024-11-22 13:37:22.704145: Epoch 4853 +2024-11-22 13:37:22.704280: Current learning rate: 0.00432 +2024-11-22 13:37:43.564553: train_loss -0.7834 +2024-11-22 13:37:43.571777: val_loss -0.7867 +2024-11-22 13:37:43.571953: Pseudo dice [0.8554] +2024-11-22 13:37:43.572050: Epoch time: 20.86 s +2024-11-22 13:37:44.610785: +2024-11-22 13:37:44.610971: Epoch 4854 +2024-11-22 13:37:44.611099: Current learning rate: 0.00432 +2024-11-22 13:38:03.454751: train_loss -0.7835 +2024-11-22 13:38:03.455976: val_loss -0.7713 +2024-11-22 13:38:03.456108: Pseudo dice [0.8461] +2024-11-22 13:38:03.456210: Epoch time: 18.84 s +2024-11-22 13:38:04.388347: +2024-11-22 13:38:04.388557: Epoch 4855 +2024-11-22 13:38:04.388681: Current learning rate: 0.00432 +2024-11-22 13:38:23.707428: train_loss -0.79 +2024-11-22 13:38:23.712308: val_loss -0.7785 +2024-11-22 13:38:23.712451: Pseudo dice [0.8517] +2024-11-22 13:38:23.712536: Epoch time: 19.32 s +2024-11-22 13:38:24.597914: +2024-11-22 13:38:24.598135: Epoch 4856 +2024-11-22 13:38:24.598248: Current learning rate: 0.00431 +2024-11-22 13:38:43.478989: train_loss -0.7893 +2024-11-22 13:38:43.485908: val_loss -0.7717 +2024-11-22 13:38:43.486053: Pseudo dice [0.8542] +2024-11-22 13:38:43.486142: Epoch time: 18.88 s +2024-11-22 13:38:44.503335: +2024-11-22 13:38:44.503572: Epoch 4857 +2024-11-22 13:38:44.503693: Current learning rate: 0.00431 +2024-11-22 13:39:04.205909: train_loss -0.7924 +2024-11-22 13:39:04.210699: val_loss -0.744 +2024-11-22 13:39:04.210853: Pseudo dice [0.8497] +2024-11-22 13:39:04.210952: Epoch time: 19.7 s +2024-11-22 13:39:05.066152: +2024-11-22 13:39:05.066410: Epoch 4858 +2024-11-22 13:39:05.066523: Current learning rate: 0.00431 +2024-11-22 13:39:25.059479: train_loss -0.7864 +2024-11-22 13:39:25.063984: val_loss -0.7745 +2024-11-22 13:39:25.064152: Pseudo dice [0.861] +2024-11-22 13:39:25.064241: Epoch time: 19.99 s +2024-11-22 13:39:25.929469: +2024-11-22 13:39:25.929676: Epoch 4859 +2024-11-22 13:39:25.929793: Current learning rate: 0.00431 +2024-11-22 13:39:44.342699: train_loss -0.7842 +2024-11-22 13:39:44.345186: val_loss -0.7979 +2024-11-22 13:39:44.345330: Pseudo dice [0.8598] +2024-11-22 13:39:44.345419: Epoch time: 18.41 s +2024-11-22 13:39:45.201349: +2024-11-22 13:39:45.201542: Epoch 4860 +2024-11-22 13:39:45.201679: Current learning rate: 0.00431 +2024-11-22 13:40:03.974480: train_loss -0.7981 +2024-11-22 13:40:03.974995: val_loss -0.7854 +2024-11-22 13:40:03.975099: Pseudo dice [0.8599] +2024-11-22 13:40:03.975182: Epoch time: 18.77 s +2024-11-22 13:40:04.848021: +2024-11-22 13:40:04.848233: Epoch 4861 +2024-11-22 13:40:04.848343: Current learning rate: 0.00431 +2024-11-22 13:40:22.753961: train_loss -0.7956 +2024-11-22 13:40:22.757660: val_loss -0.7892 +2024-11-22 13:40:22.757774: Pseudo dice [0.8507] +2024-11-22 13:40:22.757854: Epoch time: 17.91 s +2024-11-22 13:40:23.615532: +2024-11-22 13:40:23.615724: Epoch 4862 +2024-11-22 13:40:23.615831: Current learning rate: 0.00431 +2024-11-22 13:40:43.527815: train_loss -0.7896 +2024-11-22 13:40:43.534604: val_loss -0.7694 +2024-11-22 13:40:43.534729: Pseudo dice [0.8461] +2024-11-22 13:40:43.534826: Epoch time: 19.91 s +2024-11-22 13:40:44.719245: +2024-11-22 13:40:44.720437: Epoch 4863 +2024-11-22 13:40:44.720562: Current learning rate: 0.00431 +2024-11-22 13:41:03.483278: train_loss -0.783 +2024-11-22 13:41:03.489781: val_loss -0.7659 +2024-11-22 13:41:03.489915: Pseudo dice [0.8361] +2024-11-22 13:41:03.490011: Epoch time: 18.77 s +2024-11-22 13:41:04.360947: +2024-11-22 13:41:04.361434: Epoch 4864 +2024-11-22 13:41:04.361572: Current learning rate: 0.0043 +2024-11-22 13:41:22.727434: train_loss -0.7953 +2024-11-22 13:41:22.744279: val_loss -0.7772 +2024-11-22 13:41:22.744426: Pseudo dice [0.8592] +2024-11-22 13:41:22.744522: Epoch time: 18.37 s +2024-11-22 13:41:23.673985: +2024-11-22 13:41:23.675201: Epoch 4865 +2024-11-22 13:41:23.675330: Current learning rate: 0.0043 +2024-11-22 13:41:42.878818: train_loss -0.789 +2024-11-22 13:41:42.887037: val_loss -0.7913 +2024-11-22 13:41:42.887152: Pseudo dice [0.8526] +2024-11-22 13:41:42.887262: Epoch time: 19.21 s +2024-11-22 13:41:43.738472: +2024-11-22 13:41:43.738904: Epoch 4866 +2024-11-22 13:41:43.739028: Current learning rate: 0.0043 +2024-11-22 13:42:04.258683: train_loss -0.7955 +2024-11-22 13:42:04.274877: val_loss -0.7691 +2024-11-22 13:42:04.275011: Pseudo dice [0.8478] +2024-11-22 13:42:04.275112: Epoch time: 20.52 s +2024-11-22 13:42:05.590471: +2024-11-22 13:42:05.590947: Epoch 4867 +2024-11-22 13:42:05.591084: Current learning rate: 0.0043 +2024-11-22 13:42:25.553768: train_loss -0.7849 +2024-11-22 13:42:25.563276: val_loss -0.7846 +2024-11-22 13:42:25.563424: Pseudo dice [0.87] +2024-11-22 13:42:25.563532: Epoch time: 19.96 s +2024-11-22 13:42:26.698629: +2024-11-22 13:42:26.700551: Epoch 4868 +2024-11-22 13:42:26.700683: Current learning rate: 0.0043 +2024-11-22 13:42:46.681388: train_loss -0.788 +2024-11-22 13:42:46.685433: val_loss -0.7643 +2024-11-22 13:42:46.685565: Pseudo dice [0.8459] +2024-11-22 13:42:46.685655: Epoch time: 19.98 s +2024-11-22 13:42:47.657967: +2024-11-22 13:42:47.658834: Epoch 4869 +2024-11-22 13:42:47.658962: Current learning rate: 0.0043 +2024-11-22 13:43:07.314820: train_loss -0.7896 +2024-11-22 13:43:07.323368: val_loss -0.7695 +2024-11-22 13:43:07.323529: Pseudo dice [0.8527] +2024-11-22 13:43:07.323637: Epoch time: 19.66 s +2024-11-22 13:43:08.237072: +2024-11-22 13:43:08.238304: Epoch 4870 +2024-11-22 13:43:08.238436: Current learning rate: 0.0043 +2024-11-22 13:43:27.799467: train_loss -0.7823 +2024-11-22 13:43:27.803317: val_loss -0.7661 +2024-11-22 13:43:27.803459: Pseudo dice [0.854] +2024-11-22 13:43:27.803558: Epoch time: 19.56 s +2024-11-22 13:43:28.766735: +2024-11-22 13:43:28.768161: Epoch 4871 +2024-11-22 13:43:28.768480: Current learning rate: 0.0043 +2024-11-22 13:43:47.309813: train_loss -0.7802 +2024-11-22 13:43:47.317313: val_loss -0.7609 +2024-11-22 13:43:47.317500: Pseudo dice [0.8602] +2024-11-22 13:43:47.317595: Epoch time: 18.54 s +2024-11-22 13:43:48.490604: +2024-11-22 13:43:48.493243: Epoch 4872 +2024-11-22 13:43:48.493376: Current learning rate: 0.00429 +2024-11-22 13:44:08.396847: train_loss -0.7864 +2024-11-22 13:44:08.399692: val_loss -0.7972 +2024-11-22 13:44:08.399789: Pseudo dice [0.8617] +2024-11-22 13:44:08.399880: Epoch time: 19.91 s +2024-11-22 13:44:09.251140: +2024-11-22 13:44:09.251671: Epoch 4873 +2024-11-22 13:44:09.251789: Current learning rate: 0.00429 +2024-11-22 13:44:29.852841: train_loss -0.7789 +2024-11-22 13:44:29.859179: val_loss -0.7623 +2024-11-22 13:44:29.859318: Pseudo dice [0.839] +2024-11-22 13:44:29.859411: Epoch time: 20.6 s +2024-11-22 13:44:30.785344: +2024-11-22 13:44:30.788430: Epoch 4874 +2024-11-22 13:44:30.788557: Current learning rate: 0.00429 +2024-11-22 13:44:49.566854: train_loss -0.791 +2024-11-22 13:44:49.573704: val_loss -0.7817 +2024-11-22 13:44:49.573929: Pseudo dice [0.8547] +2024-11-22 13:44:49.574039: Epoch time: 18.78 s +2024-11-22 13:44:50.557683: +2024-11-22 13:44:50.558582: Epoch 4875 +2024-11-22 13:44:50.558705: Current learning rate: 0.00429 +2024-11-22 13:45:10.465088: train_loss -0.7881 +2024-11-22 13:45:10.468851: val_loss -0.7904 +2024-11-22 13:45:10.468972: Pseudo dice [0.8718] +2024-11-22 13:45:10.469071: Epoch time: 19.91 s +2024-11-22 13:45:11.324649: +2024-11-22 13:45:11.325718: Epoch 4876 +2024-11-22 13:45:11.325839: Current learning rate: 0.00429 +2024-11-22 13:45:30.065350: train_loss -0.7992 +2024-11-22 13:45:30.068564: val_loss -0.779 +2024-11-22 13:45:30.068671: Pseudo dice [0.8446] +2024-11-22 13:45:30.068757: Epoch time: 18.74 s +2024-11-22 13:45:31.061966: +2024-11-22 13:45:31.064499: Epoch 4877 +2024-11-22 13:45:31.064631: Current learning rate: 0.00429 +2024-11-22 13:45:50.622355: train_loss -0.7979 +2024-11-22 13:45:50.640062: val_loss -0.7866 +2024-11-22 13:45:50.640211: Pseudo dice [0.866] +2024-11-22 13:45:50.640302: Epoch time: 19.56 s +2024-11-22 13:45:51.585804: +2024-11-22 13:45:51.586552: Epoch 4878 +2024-11-22 13:45:51.586672: Current learning rate: 0.00429 +2024-11-22 13:46:10.929690: train_loss -0.7974 +2024-11-22 13:46:10.932649: val_loss -0.7837 +2024-11-22 13:46:10.932901: Pseudo dice [0.8602] +2024-11-22 13:46:10.933034: Epoch time: 19.34 s +2024-11-22 13:46:12.242969: +2024-11-22 13:46:12.244169: Epoch 4879 +2024-11-22 13:46:12.244302: Current learning rate: 0.00429 +2024-11-22 13:46:31.433465: train_loss -0.7884 +2024-11-22 13:46:31.440524: val_loss -0.7623 +2024-11-22 13:46:31.440665: Pseudo dice [0.8637] +2024-11-22 13:46:31.440760: Epoch time: 19.19 s +2024-11-22 13:46:32.309510: +2024-11-22 13:46:32.310335: Epoch 4880 +2024-11-22 13:46:32.310460: Current learning rate: 0.00429 +2024-11-22 13:46:50.951327: train_loss -0.7881 +2024-11-22 13:46:50.961605: val_loss -0.7865 +2024-11-22 13:46:50.961771: Pseudo dice [0.8674] +2024-11-22 13:46:50.961861: Epoch time: 18.64 s +2024-11-22 13:46:51.822641: +2024-11-22 13:46:51.823545: Epoch 4881 +2024-11-22 13:46:51.823670: Current learning rate: 0.00428 +2024-11-22 13:47:11.600312: train_loss -0.7942 +2024-11-22 13:47:11.610239: val_loss -0.7775 +2024-11-22 13:47:11.610377: Pseudo dice [0.8531] +2024-11-22 13:47:11.610484: Epoch time: 19.78 s +2024-11-22 13:47:12.475458: +2024-11-22 13:47:12.476298: Epoch 4882 +2024-11-22 13:47:12.476419: Current learning rate: 0.00428 +2024-11-22 13:47:31.395971: train_loss -0.7984 +2024-11-22 13:47:31.406009: val_loss -0.7789 +2024-11-22 13:47:31.406130: Pseudo dice [0.8633] +2024-11-22 13:47:31.406241: Epoch time: 18.92 s +2024-11-22 13:47:31.406336: Yayy! New best EMA pseudo Dice: 0.8578 +2024-11-22 13:47:32.607027: +2024-11-22 13:47:32.608504: Epoch 4883 +2024-11-22 13:47:32.608634: Current learning rate: 0.00428 +2024-11-22 13:47:52.764176: train_loss -0.7938 +2024-11-22 13:47:52.771364: val_loss -0.7663 +2024-11-22 13:47:52.771689: Pseudo dice [0.8564] +2024-11-22 13:47:52.771788: Epoch time: 20.16 s +2024-11-22 13:47:53.659724: +2024-11-22 13:47:53.660619: Epoch 4884 +2024-11-22 13:47:53.660746: Current learning rate: 0.00428 +2024-11-22 13:48:12.026520: train_loss -0.8005 +2024-11-22 13:48:12.033859: val_loss -0.7652 +2024-11-22 13:48:12.034031: Pseudo dice [0.8568] +2024-11-22 13:48:12.034127: Epoch time: 18.37 s +2024-11-22 13:48:13.009963: +2024-11-22 13:48:13.011121: Epoch 4885 +2024-11-22 13:48:13.011240: Current learning rate: 0.00428 +2024-11-22 13:48:33.870507: train_loss -0.784 +2024-11-22 13:48:33.875638: val_loss -0.7436 +2024-11-22 13:48:33.875792: Pseudo dice [0.8641] +2024-11-22 13:48:33.875889: Epoch time: 20.86 s +2024-11-22 13:48:33.875973: Yayy! New best EMA pseudo Dice: 0.8582 +2024-11-22 13:48:35.003196: +2024-11-22 13:48:35.004259: Epoch 4886 +2024-11-22 13:48:35.004388: Current learning rate: 0.00428 +2024-11-22 13:48:54.177545: train_loss -0.7843 +2024-11-22 13:48:54.180513: val_loss -0.7806 +2024-11-22 13:48:54.180619: Pseudo dice [0.8664] +2024-11-22 13:48:54.180708: Epoch time: 19.18 s +2024-11-22 13:48:54.180775: Yayy! New best EMA pseudo Dice: 0.859 +2024-11-22 13:48:55.327736: +2024-11-22 13:48:55.328192: Epoch 4887 +2024-11-22 13:48:55.328326: Current learning rate: 0.00428 +2024-11-22 13:49:15.532632: train_loss -0.7867 +2024-11-22 13:49:15.538563: val_loss -0.7615 +2024-11-22 13:49:15.538689: Pseudo dice [0.8548] +2024-11-22 13:49:15.538777: Epoch time: 20.21 s +2024-11-22 13:49:16.393517: +2024-11-22 13:49:16.394276: Epoch 4888 +2024-11-22 13:49:16.394397: Current learning rate: 0.00428 +2024-11-22 13:49:35.216332: train_loss -0.7971 +2024-11-22 13:49:35.219945: val_loss -0.7685 +2024-11-22 13:49:35.220119: Pseudo dice [0.8591] +2024-11-22 13:49:35.220212: Epoch time: 18.82 s +2024-11-22 13:49:36.095698: +2024-11-22 13:49:36.096114: Epoch 4889 +2024-11-22 13:49:36.096237: Current learning rate: 0.00427 +2024-11-22 13:49:55.711814: train_loss -0.7908 +2024-11-22 13:49:55.718167: val_loss -0.7612 +2024-11-22 13:49:55.718307: Pseudo dice [0.8637] +2024-11-22 13:49:55.718395: Epoch time: 19.62 s +2024-11-22 13:49:55.718475: Yayy! New best EMA pseudo Dice: 0.8591 +2024-11-22 13:49:57.313668: +2024-11-22 13:49:57.315230: Epoch 4890 +2024-11-22 13:49:57.315349: Current learning rate: 0.00427 +2024-11-22 13:50:16.961315: train_loss -0.7916 +2024-11-22 13:50:16.964017: val_loss -0.7854 +2024-11-22 13:50:16.964154: Pseudo dice [0.8607] +2024-11-22 13:50:16.964245: Epoch time: 19.65 s +2024-11-22 13:50:16.964325: Yayy! New best EMA pseudo Dice: 0.8593 +2024-11-22 13:50:18.120720: +2024-11-22 13:50:18.121800: Epoch 4891 +2024-11-22 13:50:18.121928: Current learning rate: 0.00427 +2024-11-22 13:50:37.237336: train_loss -0.7777 +2024-11-22 13:50:37.242165: val_loss -0.7779 +2024-11-22 13:50:37.242295: Pseudo dice [0.8464] +2024-11-22 13:50:37.242395: Epoch time: 19.12 s +2024-11-22 13:50:38.242090: +2024-11-22 13:50:38.244287: Epoch 4892 +2024-11-22 13:50:38.244420: Current learning rate: 0.00427 +2024-11-22 13:50:59.077872: train_loss -0.7794 +2024-11-22 13:50:59.085067: val_loss -0.7427 +2024-11-22 13:50:59.085184: Pseudo dice [0.8514] +2024-11-22 13:50:59.085328: Epoch time: 20.84 s +2024-11-22 13:51:00.008442: +2024-11-22 13:51:00.009324: Epoch 4893 +2024-11-22 13:51:00.009447: Current learning rate: 0.00427 +2024-11-22 13:51:20.576523: train_loss -0.7868 +2024-11-22 13:51:20.584323: val_loss -0.7972 +2024-11-22 13:51:20.584468: Pseudo dice [0.8509] +2024-11-22 13:51:20.584563: Epoch time: 20.57 s +2024-11-22 13:51:21.511391: +2024-11-22 13:51:21.511863: Epoch 4894 +2024-11-22 13:51:21.511982: Current learning rate: 0.00427 +2024-11-22 13:51:40.855846: train_loss -0.7828 +2024-11-22 13:51:40.858015: val_loss -0.7634 +2024-11-22 13:51:40.858155: Pseudo dice [0.8342] +2024-11-22 13:51:40.858242: Epoch time: 19.35 s +2024-11-22 13:51:41.920091: +2024-11-22 13:51:41.922129: Epoch 4895 +2024-11-22 13:51:41.922261: Current learning rate: 0.00427 +2024-11-22 13:52:01.123296: train_loss -0.7925 +2024-11-22 13:52:01.128343: val_loss -0.7626 +2024-11-22 13:52:01.128472: Pseudo dice [0.8553] +2024-11-22 13:52:01.128556: Epoch time: 19.2 s +2024-11-22 13:52:01.985705: +2024-11-22 13:52:01.986129: Epoch 4896 +2024-11-22 13:52:01.986246: Current learning rate: 0.00427 +2024-11-22 13:52:20.745565: train_loss -0.7831 +2024-11-22 13:52:20.747457: val_loss -0.7427 +2024-11-22 13:52:20.747571: Pseudo dice [0.8347] +2024-11-22 13:52:20.747722: Epoch time: 18.76 s +2024-11-22 13:52:21.742643: +2024-11-22 13:52:21.743045: Epoch 4897 +2024-11-22 13:52:21.743169: Current learning rate: 0.00426 +2024-11-22 13:52:39.843085: train_loss -0.782 +2024-11-22 13:52:39.849384: val_loss -0.7593 +2024-11-22 13:52:39.849511: Pseudo dice [0.8446] +2024-11-22 13:52:39.849605: Epoch time: 18.1 s +2024-11-22 13:52:40.714231: +2024-11-22 13:52:40.715351: Epoch 4898 +2024-11-22 13:52:40.715476: Current learning rate: 0.00426 +2024-11-22 13:52:59.890229: train_loss -0.7889 +2024-11-22 13:52:59.894086: val_loss -0.7552 +2024-11-22 13:52:59.894246: Pseudo dice [0.842] +2024-11-22 13:52:59.894352: Epoch time: 19.18 s +2024-11-22 13:53:00.899995: +2024-11-22 13:53:00.901375: Epoch 4899 +2024-11-22 13:53:00.901504: Current learning rate: 0.00426 +2024-11-22 13:53:19.844604: train_loss -0.7922 +2024-11-22 13:53:19.851579: val_loss -0.7953 +2024-11-22 13:53:19.851732: Pseudo dice [0.859] +2024-11-22 13:53:19.851825: Epoch time: 18.95 s +2024-11-22 13:53:21.026458: +2024-11-22 13:53:21.028793: Epoch 4900 +2024-11-22 13:53:21.028939: Current learning rate: 0.00426 +2024-11-22 13:53:40.387940: train_loss -0.7675 +2024-11-22 13:53:40.408276: val_loss -0.759 +2024-11-22 13:53:40.408437: Pseudo dice [0.8386] +2024-11-22 13:53:40.408531: Epoch time: 19.36 s +2024-11-22 13:53:41.788607: +2024-11-22 13:53:41.791244: Epoch 4901 +2024-11-22 13:53:41.791370: Current learning rate: 0.00426 +2024-11-22 13:54:01.583033: train_loss -0.7768 +2024-11-22 13:54:01.594848: val_loss -0.7754 +2024-11-22 13:54:01.594978: Pseudo dice [0.856] +2024-11-22 13:54:01.595092: Epoch time: 19.8 s +2024-11-22 13:54:02.468843: +2024-11-22 13:54:02.470690: Epoch 4902 +2024-11-22 13:54:02.470807: Current learning rate: 0.00426 +2024-11-22 13:54:21.838362: train_loss -0.7791 +2024-11-22 13:54:21.846546: val_loss -0.7606 +2024-11-22 13:54:21.846686: Pseudo dice [0.8523] +2024-11-22 13:54:21.846783: Epoch time: 19.37 s +2024-11-22 13:54:22.914702: +2024-11-22 13:54:22.915324: Epoch 4903 +2024-11-22 13:54:22.915453: Current learning rate: 0.00426 +2024-11-22 13:54:42.409503: train_loss -0.7886 +2024-11-22 13:54:42.415694: val_loss -0.7677 +2024-11-22 13:54:42.415831: Pseudo dice [0.8456] +2024-11-22 13:54:42.415923: Epoch time: 19.5 s +2024-11-22 13:54:43.311753: +2024-11-22 13:54:43.313486: Epoch 4904 +2024-11-22 13:54:43.313618: Current learning rate: 0.00426 +2024-11-22 13:55:02.106542: train_loss -0.7826 +2024-11-22 13:55:02.114317: val_loss -0.7668 +2024-11-22 13:55:02.114442: Pseudo dice [0.8347] +2024-11-22 13:55:02.114531: Epoch time: 18.8 s +2024-11-22 13:55:03.226211: +2024-11-22 13:55:03.227861: Epoch 4905 +2024-11-22 13:55:03.227982: Current learning rate: 0.00425 +2024-11-22 13:55:22.629692: train_loss -0.7815 +2024-11-22 13:55:22.636426: val_loss -0.7742 +2024-11-22 13:55:22.636561: Pseudo dice [0.8513] +2024-11-22 13:55:22.636656: Epoch time: 19.4 s +2024-11-22 13:55:23.564082: +2024-11-22 13:55:23.565386: Epoch 4906 +2024-11-22 13:55:23.565507: Current learning rate: 0.00425 +2024-11-22 13:55:43.340546: train_loss -0.7845 +2024-11-22 13:55:43.360840: val_loss -0.7541 +2024-11-22 13:55:43.360972: Pseudo dice [0.8489] +2024-11-22 13:55:43.361054: Epoch time: 19.78 s +2024-11-22 13:55:44.225677: +2024-11-22 13:55:44.227649: Epoch 4907 +2024-11-22 13:55:44.227776: Current learning rate: 0.00425 +2024-11-22 13:56:04.115638: train_loss -0.7779 +2024-11-22 13:56:04.118095: val_loss -0.7789 +2024-11-22 13:56:04.118211: Pseudo dice [0.8569] +2024-11-22 13:56:04.118305: Epoch time: 19.89 s +2024-11-22 13:56:04.975140: +2024-11-22 13:56:04.976354: Epoch 4908 +2024-11-22 13:56:04.976473: Current learning rate: 0.00425 +2024-11-22 13:56:24.521806: train_loss -0.8016 +2024-11-22 13:56:24.533379: val_loss -0.7724 +2024-11-22 13:56:24.533546: Pseudo dice [0.8476] +2024-11-22 13:56:24.533668: Epoch time: 19.55 s +2024-11-22 13:56:25.447391: +2024-11-22 13:56:25.448293: Epoch 4909 +2024-11-22 13:56:25.448418: Current learning rate: 0.00425 +2024-11-22 13:56:44.784538: train_loss -0.7971 +2024-11-22 13:56:44.793085: val_loss -0.7691 +2024-11-22 13:56:44.793293: Pseudo dice [0.8486] +2024-11-22 13:56:44.793414: Epoch time: 19.34 s +2024-11-22 13:56:45.804332: +2024-11-22 13:56:45.805135: Epoch 4910 +2024-11-22 13:56:45.805269: Current learning rate: 0.00425 +2024-11-22 13:57:05.631548: train_loss -0.7878 +2024-11-22 13:57:05.638867: val_loss -0.7784 +2024-11-22 13:57:05.638985: Pseudo dice [0.8556] +2024-11-22 13:57:05.639140: Epoch time: 19.83 s +2024-11-22 13:57:06.682512: +2024-11-22 13:57:06.683938: Epoch 4911 +2024-11-22 13:57:06.684079: Current learning rate: 0.00425 +2024-11-22 13:57:25.187579: train_loss -0.7908 +2024-11-22 13:57:25.194877: val_loss -0.7838 +2024-11-22 13:57:25.195030: Pseudo dice [0.8437] +2024-11-22 13:57:25.195143: Epoch time: 18.51 s +2024-11-22 13:57:26.129086: +2024-11-22 13:57:26.131315: Epoch 4912 +2024-11-22 13:57:26.131440: Current learning rate: 0.00425 +2024-11-22 13:57:45.473675: train_loss -0.7905 +2024-11-22 13:57:45.487561: val_loss -0.7787 +2024-11-22 13:57:45.487699: Pseudo dice [0.854] +2024-11-22 13:57:45.487794: Epoch time: 19.35 s +2024-11-22 13:57:46.954405: +2024-11-22 13:57:46.954821: Epoch 4913 +2024-11-22 13:57:46.954943: Current learning rate: 0.00424 +2024-11-22 13:58:06.449963: train_loss -0.7958 +2024-11-22 13:58:06.456506: val_loss -0.7881 +2024-11-22 13:58:06.456647: Pseudo dice [0.8526] +2024-11-22 13:58:06.456746: Epoch time: 19.5 s +2024-11-22 13:58:07.444813: +2024-11-22 13:58:07.446013: Epoch 4914 +2024-11-22 13:58:07.446144: Current learning rate: 0.00424 +2024-11-22 13:58:26.115420: train_loss -0.7894 +2024-11-22 13:58:26.126998: val_loss -0.7598 +2024-11-22 13:58:26.127170: Pseudo dice [0.8406] +2024-11-22 13:58:26.127272: Epoch time: 18.67 s +2024-11-22 13:58:27.159878: +2024-11-22 13:58:27.160628: Epoch 4915 +2024-11-22 13:58:27.160743: Current learning rate: 0.00424 +2024-11-22 13:58:46.862463: train_loss -0.7779 +2024-11-22 13:58:46.891732: val_loss -0.782 +2024-11-22 13:58:46.891876: Pseudo dice [0.8377] +2024-11-22 13:58:46.891968: Epoch time: 19.7 s +2024-11-22 13:58:48.011733: +2024-11-22 13:58:48.013189: Epoch 4916 +2024-11-22 13:58:48.013323: Current learning rate: 0.00424 +2024-11-22 13:59:07.723111: train_loss -0.792 +2024-11-22 13:59:07.731608: val_loss -0.7809 +2024-11-22 13:59:07.731747: Pseudo dice [0.8615] +2024-11-22 13:59:07.731838: Epoch time: 19.71 s +2024-11-22 13:59:08.677735: +2024-11-22 13:59:08.678680: Epoch 4917 +2024-11-22 13:59:08.678841: Current learning rate: 0.00424 +2024-11-22 13:59:28.793539: train_loss -0.7914 +2024-11-22 13:59:28.799820: val_loss -0.7742 +2024-11-22 13:59:28.799970: Pseudo dice [0.8538] +2024-11-22 13:59:28.800082: Epoch time: 20.12 s +2024-11-22 13:59:29.822788: +2024-11-22 13:59:29.823252: Epoch 4918 +2024-11-22 13:59:29.823380: Current learning rate: 0.00424 +2024-11-22 13:59:50.830256: train_loss -0.7929 +2024-11-22 13:59:50.837980: val_loss -0.798 +2024-11-22 13:59:50.838134: Pseudo dice [0.866] +2024-11-22 13:59:50.838233: Epoch time: 21.01 s +2024-11-22 13:59:51.727186: +2024-11-22 13:59:51.728531: Epoch 4919 +2024-11-22 13:59:51.728652: Current learning rate: 0.00424 +2024-11-22 14:00:10.357016: train_loss -0.7885 +2024-11-22 14:00:10.359749: val_loss -0.787 +2024-11-22 14:00:10.359960: Pseudo dice [0.8494] +2024-11-22 14:00:10.360056: Epoch time: 18.63 s +2024-11-22 14:00:11.292535: +2024-11-22 14:00:11.292761: Epoch 4920 +2024-11-22 14:00:11.292876: Current learning rate: 0.00424 +2024-11-22 14:00:29.474452: train_loss -0.7963 +2024-11-22 14:00:29.479402: val_loss -0.7561 +2024-11-22 14:00:29.479539: Pseudo dice [0.8535] +2024-11-22 14:00:29.479642: Epoch time: 18.18 s +2024-11-22 14:00:30.432603: +2024-11-22 14:00:30.433021: Epoch 4921 +2024-11-22 14:00:30.433143: Current learning rate: 0.00423 +2024-11-22 14:00:49.217186: train_loss -0.8019 +2024-11-22 14:00:49.225181: val_loss -0.7658 +2024-11-22 14:00:49.225312: Pseudo dice [0.8551] +2024-11-22 14:00:49.225401: Epoch time: 18.79 s +2024-11-22 14:00:50.113874: +2024-11-22 14:00:50.115394: Epoch 4922 +2024-11-22 14:00:50.115520: Current learning rate: 0.00423 +2024-11-22 14:01:09.620190: train_loss -0.7984 +2024-11-22 14:01:09.627585: val_loss -0.7709 +2024-11-22 14:01:09.627727: Pseudo dice [0.8573] +2024-11-22 14:01:09.627849: Epoch time: 19.51 s +2024-11-22 14:01:10.492908: +2024-11-22 14:01:10.493977: Epoch 4923 +2024-11-22 14:01:10.494100: Current learning rate: 0.00423 +2024-11-22 14:01:31.206779: train_loss -0.7928 +2024-11-22 14:01:31.215405: val_loss -0.7663 +2024-11-22 14:01:31.215550: Pseudo dice [0.8447] +2024-11-22 14:01:31.215703: Epoch time: 20.71 s +2024-11-22 14:01:32.091386: +2024-11-22 14:01:32.091824: Epoch 4924 +2024-11-22 14:01:32.091954: Current learning rate: 0.00423 +2024-11-22 14:01:51.018004: train_loss -0.7912 +2024-11-22 14:01:51.024781: val_loss -0.7797 +2024-11-22 14:01:51.024936: Pseudo dice [0.8448] +2024-11-22 14:01:51.025035: Epoch time: 18.93 s +2024-11-22 14:01:52.292655: +2024-11-22 14:01:52.294958: Epoch 4925 +2024-11-22 14:01:52.295093: Current learning rate: 0.00423 +2024-11-22 14:02:10.268672: train_loss -0.794 +2024-11-22 14:02:10.277397: val_loss -0.7864 +2024-11-22 14:02:10.277553: Pseudo dice [0.8478] +2024-11-22 14:02:10.277648: Epoch time: 17.98 s +2024-11-22 14:02:11.181499: +2024-11-22 14:02:11.182498: Epoch 4926 +2024-11-22 14:02:11.182621: Current learning rate: 0.00423 +2024-11-22 14:02:29.614373: train_loss -0.7981 +2024-11-22 14:02:29.617492: val_loss -0.781 +2024-11-22 14:02:29.617614: Pseudo dice [0.8517] +2024-11-22 14:02:29.617700: Epoch time: 18.43 s +2024-11-22 14:02:30.470702: +2024-11-22 14:02:30.470942: Epoch 4927 +2024-11-22 14:02:30.471070: Current learning rate: 0.00423 +2024-11-22 14:02:49.289277: train_loss -0.7924 +2024-11-22 14:02:49.291975: val_loss -0.7759 +2024-11-22 14:02:49.292133: Pseudo dice [0.8489] +2024-11-22 14:02:49.292229: Epoch time: 18.82 s +2024-11-22 14:02:50.208967: +2024-11-22 14:02:50.209180: Epoch 4928 +2024-11-22 14:02:50.209291: Current learning rate: 0.00423 +2024-11-22 14:03:08.690946: train_loss -0.7826 +2024-11-22 14:03:08.692980: val_loss -0.7815 +2024-11-22 14:03:08.693087: Pseudo dice [0.8468] +2024-11-22 14:03:08.693174: Epoch time: 18.48 s +2024-11-22 14:03:09.549315: +2024-11-22 14:03:09.549540: Epoch 4929 +2024-11-22 14:03:09.549660: Current learning rate: 0.00422 +2024-11-22 14:03:28.298701: train_loss -0.8025 +2024-11-22 14:03:28.299190: val_loss -0.7818 +2024-11-22 14:03:28.299300: Pseudo dice [0.8652] +2024-11-22 14:03:28.299747: Epoch time: 18.75 s +2024-11-22 14:03:29.148605: +2024-11-22 14:03:29.148844: Epoch 4930 +2024-11-22 14:03:29.148973: Current learning rate: 0.00422 +2024-11-22 14:03:48.366848: train_loss -0.7959 +2024-11-22 14:03:48.368763: val_loss -0.7664 +2024-11-22 14:03:48.368873: Pseudo dice [0.859] +2024-11-22 14:03:48.368954: Epoch time: 19.22 s +2024-11-22 14:03:49.247247: +2024-11-22 14:03:49.247446: Epoch 4931 +2024-11-22 14:03:49.247561: Current learning rate: 0.00422 +2024-11-22 14:04:07.529768: train_loss -0.7851 +2024-11-22 14:04:07.536427: val_loss -0.7842 +2024-11-22 14:04:07.536570: Pseudo dice [0.8523] +2024-11-22 14:04:07.536670: Epoch time: 18.28 s +2024-11-22 14:04:08.425612: +2024-11-22 14:04:08.425837: Epoch 4932 +2024-11-22 14:04:08.425964: Current learning rate: 0.00422 +2024-11-22 14:04:27.604507: train_loss -0.7916 +2024-11-22 14:04:27.607079: val_loss -0.7929 +2024-11-22 14:04:27.607265: Pseudo dice [0.8488] +2024-11-22 14:04:27.607364: Epoch time: 19.18 s +2024-11-22 14:04:28.485175: +2024-11-22 14:04:28.485376: Epoch 4933 +2024-11-22 14:04:28.485505: Current learning rate: 0.00422 +2024-11-22 14:04:48.076709: train_loss -0.7898 +2024-11-22 14:04:48.077312: val_loss -0.7741 +2024-11-22 14:04:48.092934: Pseudo dice [0.8533] +2024-11-22 14:04:48.093118: Epoch time: 19.59 s +2024-11-22 14:04:49.084066: +2024-11-22 14:04:49.084265: Epoch 4934 +2024-11-22 14:04:49.084385: Current learning rate: 0.00422 +2024-11-22 14:05:08.035519: train_loss -0.7987 +2024-11-22 14:05:08.042807: val_loss -0.7578 +2024-11-22 14:05:08.042924: Pseudo dice [0.8676] +2024-11-22 14:05:08.043023: Epoch time: 18.95 s +2024-11-22 14:05:09.051684: +2024-11-22 14:05:09.051881: Epoch 4935 +2024-11-22 14:05:09.051996: Current learning rate: 0.00422 +2024-11-22 14:05:26.661093: train_loss -0.7997 +2024-11-22 14:05:26.667979: val_loss -0.793 +2024-11-22 14:05:26.668098: Pseudo dice [0.8551] +2024-11-22 14:05:26.668181: Epoch time: 17.61 s +2024-11-22 14:05:27.645892: +2024-11-22 14:05:27.646969: Epoch 4936 +2024-11-22 14:05:27.647106: Current learning rate: 0.00422 +2024-11-22 14:05:47.707803: train_loss -0.8014 +2024-11-22 14:05:47.713890: val_loss -0.758 +2024-11-22 14:05:47.714034: Pseudo dice [0.8666] +2024-11-22 14:05:47.714143: Epoch time: 20.06 s +2024-11-22 14:05:48.998704: +2024-11-22 14:05:48.999148: Epoch 4937 +2024-11-22 14:05:48.999275: Current learning rate: 0.00421 +2024-11-22 14:06:07.330051: train_loss -0.7957 +2024-11-22 14:06:07.331452: val_loss -0.7745 +2024-11-22 14:06:07.331554: Pseudo dice [0.8616] +2024-11-22 14:06:07.331639: Epoch time: 18.33 s +2024-11-22 14:06:08.169934: +2024-11-22 14:06:08.170362: Epoch 4938 +2024-11-22 14:06:08.170479: Current learning rate: 0.00421 +2024-11-22 14:06:27.800939: train_loss -0.8026 +2024-11-22 14:06:27.804814: val_loss -0.7733 +2024-11-22 14:06:27.804926: Pseudo dice [0.8566] +2024-11-22 14:06:27.805024: Epoch time: 19.63 s +2024-11-22 14:06:28.653795: +2024-11-22 14:06:28.655286: Epoch 4939 +2024-11-22 14:06:28.655412: Current learning rate: 0.00421 +2024-11-22 14:06:48.304914: train_loss -0.7988 +2024-11-22 14:06:48.306661: val_loss -0.782 +2024-11-22 14:06:48.306783: Pseudo dice [0.8722] +2024-11-22 14:06:48.306879: Epoch time: 19.65 s +2024-11-22 14:06:49.178977: +2024-11-22 14:06:49.180108: Epoch 4940 +2024-11-22 14:06:49.180232: Current learning rate: 0.00421 +2024-11-22 14:07:07.821237: train_loss -0.7967 +2024-11-22 14:07:07.824311: val_loss -0.7652 +2024-11-22 14:07:07.824446: Pseudo dice [0.8542] +2024-11-22 14:07:07.824539: Epoch time: 18.64 s +2024-11-22 14:07:08.797239: +2024-11-22 14:07:08.797623: Epoch 4941 +2024-11-22 14:07:08.797746: Current learning rate: 0.00421 +2024-11-22 14:07:28.636787: train_loss -0.7945 +2024-11-22 14:07:28.647006: val_loss -0.7749 +2024-11-22 14:07:28.647144: Pseudo dice [0.8471] +2024-11-22 14:07:28.647248: Epoch time: 19.84 s +2024-11-22 14:07:29.560571: +2024-11-22 14:07:29.561021: Epoch 4942 +2024-11-22 14:07:29.561160: Current learning rate: 0.00421 +2024-11-22 14:07:48.865261: train_loss -0.798 +2024-11-22 14:07:48.871813: val_loss -0.7633 +2024-11-22 14:07:48.871941: Pseudo dice [0.8453] +2024-11-22 14:07:48.872028: Epoch time: 19.31 s +2024-11-22 14:07:49.750432: +2024-11-22 14:07:49.751234: Epoch 4943 +2024-11-22 14:07:49.751356: Current learning rate: 0.00421 +2024-11-22 14:08:09.489275: train_loss -0.8055 +2024-11-22 14:08:09.490980: val_loss -0.7812 +2024-11-22 14:08:09.491165: Pseudo dice [0.8542] +2024-11-22 14:08:09.491266: Epoch time: 19.74 s +2024-11-22 14:08:10.624030: +2024-11-22 14:08:10.624466: Epoch 4944 +2024-11-22 14:08:10.624585: Current learning rate: 0.00421 +2024-11-22 14:08:30.972377: train_loss -0.7953 +2024-11-22 14:08:30.981537: val_loss -0.794 +2024-11-22 14:08:30.981660: Pseudo dice [0.8509] +2024-11-22 14:08:30.981756: Epoch time: 20.35 s +2024-11-22 14:08:31.887119: +2024-11-22 14:08:31.887573: Epoch 4945 +2024-11-22 14:08:31.887706: Current learning rate: 0.0042 +2024-11-22 14:08:50.695996: train_loss -0.7976 +2024-11-22 14:08:50.702147: val_loss -0.7716 +2024-11-22 14:08:50.702358: Pseudo dice [0.8591] +2024-11-22 14:08:50.702447: Epoch time: 18.81 s +2024-11-22 14:08:51.646323: +2024-11-22 14:08:51.647151: Epoch 4946 +2024-11-22 14:08:51.647270: Current learning rate: 0.0042 +2024-11-22 14:09:11.371338: train_loss -0.7927 +2024-11-22 14:09:11.377531: val_loss -0.765 +2024-11-22 14:09:11.377654: Pseudo dice [0.839] +2024-11-22 14:09:11.377739: Epoch time: 19.73 s +2024-11-22 14:09:12.281063: +2024-11-22 14:09:12.281513: Epoch 4947 +2024-11-22 14:09:12.281631: Current learning rate: 0.0042 +2024-11-22 14:09:32.087230: train_loss -0.7988 +2024-11-22 14:09:32.089524: val_loss -0.7577 +2024-11-22 14:09:32.089649: Pseudo dice [0.8467] +2024-11-22 14:09:32.089741: Epoch time: 19.81 s +2024-11-22 14:09:33.057470: +2024-11-22 14:09:33.058505: Epoch 4948 +2024-11-22 14:09:33.058628: Current learning rate: 0.0042 +2024-11-22 14:09:51.686710: train_loss -0.7909 +2024-11-22 14:09:51.693051: val_loss -0.7926 +2024-11-22 14:09:51.693183: Pseudo dice [0.8626] +2024-11-22 14:09:51.693275: Epoch time: 18.63 s +2024-11-22 14:09:53.236090: +2024-11-22 14:09:53.237159: Epoch 4949 +2024-11-22 14:09:53.237287: Current learning rate: 0.0042 +2024-11-22 14:10:12.298135: train_loss -0.789 +2024-11-22 14:10:12.303540: val_loss -0.7914 +2024-11-22 14:10:12.303662: Pseudo dice [0.8657] +2024-11-22 14:10:12.303758: Epoch time: 19.06 s +2024-11-22 14:10:13.522234: +2024-11-22 14:10:13.523512: Epoch 4950 +2024-11-22 14:10:13.523637: Current learning rate: 0.0042 +2024-11-22 14:10:33.144689: train_loss -0.7953 +2024-11-22 14:10:33.148478: val_loss -0.7669 +2024-11-22 14:10:33.148597: Pseudo dice [0.8555] +2024-11-22 14:10:33.148684: Epoch time: 19.62 s +2024-11-22 14:10:34.173961: +2024-11-22 14:10:34.175909: Epoch 4951 +2024-11-22 14:10:34.176039: Current learning rate: 0.0042 +2024-11-22 14:10:53.133145: train_loss -0.7934 +2024-11-22 14:10:53.147360: val_loss -0.7723 +2024-11-22 14:10:53.147503: Pseudo dice [0.8531] +2024-11-22 14:10:53.147600: Epoch time: 18.96 s +2024-11-22 14:10:54.139565: +2024-11-22 14:10:54.140402: Epoch 4952 +2024-11-22 14:10:54.140527: Current learning rate: 0.0042 +2024-11-22 14:11:14.089225: train_loss -0.801 +2024-11-22 14:11:14.096490: val_loss -0.7733 +2024-11-22 14:11:14.096617: Pseudo dice [0.8569] +2024-11-22 14:11:14.096725: Epoch time: 19.95 s +2024-11-22 14:11:14.999819: +2024-11-22 14:11:15.000953: Epoch 4953 +2024-11-22 14:11:15.001090: Current learning rate: 0.00419 +2024-11-22 14:11:34.864626: train_loss -0.7867 +2024-11-22 14:11:34.869810: val_loss -0.7665 +2024-11-22 14:11:34.869967: Pseudo dice [0.8622] +2024-11-22 14:11:34.870056: Epoch time: 19.87 s +2024-11-22 14:11:35.795759: +2024-11-22 14:11:35.796971: Epoch 4954 +2024-11-22 14:11:35.797104: Current learning rate: 0.00419 +2024-11-22 14:11:54.721451: train_loss -0.7926 +2024-11-22 14:11:54.729973: val_loss -0.7792 +2024-11-22 14:11:54.730140: Pseudo dice [0.8494] +2024-11-22 14:11:54.730237: Epoch time: 18.93 s +2024-11-22 14:11:55.634670: +2024-11-22 14:11:55.635135: Epoch 4955 +2024-11-22 14:11:55.635252: Current learning rate: 0.00419 +2024-11-22 14:12:14.306398: train_loss -0.7984 +2024-11-22 14:12:14.314144: val_loss -0.7763 +2024-11-22 14:12:14.314296: Pseudo dice [0.8501] +2024-11-22 14:12:14.314707: Epoch time: 18.67 s +2024-11-22 14:12:15.305234: +2024-11-22 14:12:15.305738: Epoch 4956 +2024-11-22 14:12:15.305864: Current learning rate: 0.00419 +2024-11-22 14:12:33.173702: train_loss -0.7975 +2024-11-22 14:12:33.176533: val_loss -0.797 +2024-11-22 14:12:33.176641: Pseudo dice [0.8744] +2024-11-22 14:12:33.176732: Epoch time: 17.87 s +2024-11-22 14:12:34.026615: +2024-11-22 14:12:34.027538: Epoch 4957 +2024-11-22 14:12:34.027657: Current learning rate: 0.00419 +2024-11-22 14:12:53.840134: train_loss -0.804 +2024-11-22 14:12:53.844711: val_loss -0.7682 +2024-11-22 14:12:53.844843: Pseudo dice [0.8523] +2024-11-22 14:12:53.844946: Epoch time: 19.81 s +2024-11-22 14:12:54.706097: +2024-11-22 14:12:54.706956: Epoch 4958 +2024-11-22 14:12:54.707089: Current learning rate: 0.00419 +2024-11-22 14:13:14.289089: train_loss -0.7858 +2024-11-22 14:13:14.303246: val_loss -0.7438 +2024-11-22 14:13:14.303377: Pseudo dice [0.8525] +2024-11-22 14:13:14.303461: Epoch time: 19.58 s +2024-11-22 14:13:15.271001: +2024-11-22 14:13:15.271623: Epoch 4959 +2024-11-22 14:13:15.271740: Current learning rate: 0.00419 +2024-11-22 14:13:33.866556: train_loss -0.7748 +2024-11-22 14:13:33.875103: val_loss -0.7404 +2024-11-22 14:13:33.875234: Pseudo dice [0.8184] +2024-11-22 14:13:33.875350: Epoch time: 18.6 s +2024-11-22 14:13:34.846792: +2024-11-22 14:13:34.847857: Epoch 4960 +2024-11-22 14:13:34.847973: Current learning rate: 0.00419 +2024-11-22 14:13:54.814872: train_loss -0.7831 +2024-11-22 14:13:54.820972: val_loss -0.7783 +2024-11-22 14:13:54.821160: Pseudo dice [0.854] +2024-11-22 14:13:54.821249: Epoch time: 19.97 s +2024-11-22 14:13:55.730530: +2024-11-22 14:13:55.731012: Epoch 4961 +2024-11-22 14:13:55.731141: Current learning rate: 0.00418 +2024-11-22 14:14:14.839822: train_loss -0.7686 +2024-11-22 14:14:14.850942: val_loss -0.753 +2024-11-22 14:14:14.851093: Pseudo dice [0.8347] +2024-11-22 14:14:14.851194: Epoch time: 19.11 s +2024-11-22 14:14:15.914948: +2024-11-22 14:14:15.916687: Epoch 4962 +2024-11-22 14:14:15.916804: Current learning rate: 0.00418 +2024-11-22 14:14:34.972809: train_loss -0.7574 +2024-11-22 14:14:34.976195: val_loss -0.7651 +2024-11-22 14:14:34.976341: Pseudo dice [0.8431] +2024-11-22 14:14:34.976465: Epoch time: 19.06 s +2024-11-22 14:14:35.951035: +2024-11-22 14:14:35.952788: Epoch 4963 +2024-11-22 14:14:35.952916: Current learning rate: 0.00418 +2024-11-22 14:14:54.730251: train_loss -0.7782 +2024-11-22 14:14:54.738725: val_loss -0.7604 +2024-11-22 14:14:54.738932: Pseudo dice [0.8484] +2024-11-22 14:14:54.739044: Epoch time: 18.78 s +2024-11-22 14:14:55.615562: +2024-11-22 14:14:55.616807: Epoch 4964 +2024-11-22 14:14:55.616943: Current learning rate: 0.00418 +2024-11-22 14:15:14.379469: train_loss -0.7701 +2024-11-22 14:15:14.386396: val_loss -0.7633 +2024-11-22 14:15:14.386534: Pseudo dice [0.8376] +2024-11-22 14:15:14.386629: Epoch time: 18.76 s +2024-11-22 14:15:15.385292: +2024-11-22 14:15:15.385682: Epoch 4965 +2024-11-22 14:15:15.385804: Current learning rate: 0.00418 +2024-11-22 14:15:34.945981: train_loss -0.7731 +2024-11-22 14:15:34.951367: val_loss -0.7709 +2024-11-22 14:15:34.951498: Pseudo dice [0.8548] +2024-11-22 14:15:34.951580: Epoch time: 19.56 s +2024-11-22 14:15:36.026200: +2024-11-22 14:15:36.027659: Epoch 4966 +2024-11-22 14:15:36.027788: Current learning rate: 0.00418 +2024-11-22 14:15:55.236980: train_loss -0.7842 +2024-11-22 14:15:55.240889: val_loss -0.7678 +2024-11-22 14:15:55.241034: Pseudo dice [0.8678] +2024-11-22 14:15:55.241143: Epoch time: 19.21 s +2024-11-22 14:15:56.198021: +2024-11-22 14:15:56.199209: Epoch 4967 +2024-11-22 14:15:56.199324: Current learning rate: 0.00418 +2024-11-22 14:16:15.540262: train_loss -0.7962 +2024-11-22 14:16:15.545613: val_loss -0.7781 +2024-11-22 14:16:15.545771: Pseudo dice [0.8598] +2024-11-22 14:16:15.545880: Epoch time: 19.34 s +2024-11-22 14:16:16.420163: +2024-11-22 14:16:16.420599: Epoch 4968 +2024-11-22 14:16:16.420728: Current learning rate: 0.00418 +2024-11-22 14:16:36.346809: train_loss -0.7867 +2024-11-22 14:16:36.353653: val_loss -0.785 +2024-11-22 14:16:36.353791: Pseudo dice [0.8577] +2024-11-22 14:16:36.353986: Epoch time: 19.93 s +2024-11-22 14:16:37.349439: +2024-11-22 14:16:37.350250: Epoch 4969 +2024-11-22 14:16:37.350398: Current learning rate: 0.00417 +2024-11-22 14:16:57.017759: train_loss -0.784 +2024-11-22 14:16:57.026976: val_loss -0.7589 +2024-11-22 14:16:57.027104: Pseudo dice [0.86] +2024-11-22 14:16:57.027205: Epoch time: 19.67 s +2024-11-22 14:16:57.970590: +2024-11-22 14:16:57.971054: Epoch 4970 +2024-11-22 14:16:57.971186: Current learning rate: 0.00417 +2024-11-22 14:17:18.001655: train_loss -0.7938 +2024-11-22 14:17:18.007150: val_loss -0.7869 +2024-11-22 14:17:18.007301: Pseudo dice [0.8521] +2024-11-22 14:17:18.007386: Epoch time: 20.03 s +2024-11-22 14:17:18.860611: +2024-11-22 14:17:18.861079: Epoch 4971 +2024-11-22 14:17:18.861198: Current learning rate: 0.00417 +2024-11-22 14:17:37.015630: train_loss -0.7877 +2024-11-22 14:17:37.018669: val_loss -0.7672 +2024-11-22 14:17:37.018783: Pseudo dice [0.8482] +2024-11-22 14:17:37.019069: Epoch time: 18.16 s +2024-11-22 14:17:38.304395: +2024-11-22 14:17:38.305079: Epoch 4972 +2024-11-22 14:17:38.305193: Current learning rate: 0.00417 +2024-11-22 14:17:58.234742: train_loss -0.787 +2024-11-22 14:17:58.236616: val_loss -0.7787 +2024-11-22 14:17:58.236800: Pseudo dice [0.8475] +2024-11-22 14:17:58.236950: Epoch time: 19.93 s +2024-11-22 14:17:59.161229: +2024-11-22 14:17:59.161667: Epoch 4973 +2024-11-22 14:17:59.161795: Current learning rate: 0.00417 +2024-11-22 14:18:18.600910: train_loss -0.794 +2024-11-22 14:18:18.609871: val_loss -0.7625 +2024-11-22 14:18:18.609991: Pseudo dice [0.8442] +2024-11-22 14:18:18.610081: Epoch time: 19.44 s +2024-11-22 14:18:19.530670: +2024-11-22 14:18:19.531467: Epoch 4974 +2024-11-22 14:18:19.531594: Current learning rate: 0.00417 +2024-11-22 14:18:38.375986: train_loss -0.7923 +2024-11-22 14:18:38.380898: val_loss -0.7529 +2024-11-22 14:18:38.381028: Pseudo dice [0.8478] +2024-11-22 14:18:38.381120: Epoch time: 18.84 s +2024-11-22 14:18:39.395728: +2024-11-22 14:18:39.396163: Epoch 4975 +2024-11-22 14:18:39.396287: Current learning rate: 0.00417 +2024-11-22 14:18:58.615516: train_loss -0.7893 +2024-11-22 14:18:58.623095: val_loss -0.7711 +2024-11-22 14:18:58.623256: Pseudo dice [0.8693] +2024-11-22 14:18:58.623353: Epoch time: 19.22 s +2024-11-22 14:18:59.865754: +2024-11-22 14:18:59.867288: Epoch 4976 +2024-11-22 14:18:59.867428: Current learning rate: 0.00417 +2024-11-22 14:19:19.741134: train_loss -0.7868 +2024-11-22 14:19:19.744577: val_loss -0.7875 +2024-11-22 14:19:19.744720: Pseudo dice [0.8629] +2024-11-22 14:19:19.744812: Epoch time: 19.88 s +2024-11-22 14:19:20.599221: +2024-11-22 14:19:20.600072: Epoch 4977 +2024-11-22 14:19:20.600203: Current learning rate: 0.00416 +2024-11-22 14:19:40.269630: train_loss -0.7865 +2024-11-22 14:19:40.278254: val_loss -0.7691 +2024-11-22 14:19:40.278385: Pseudo dice [0.8589] +2024-11-22 14:19:40.278475: Epoch time: 19.67 s +2024-11-22 14:19:41.148500: +2024-11-22 14:19:41.149270: Epoch 4978 +2024-11-22 14:19:41.149392: Current learning rate: 0.00416 +2024-11-22 14:20:01.148897: train_loss -0.787 +2024-11-22 14:20:01.157818: val_loss -0.7626 +2024-11-22 14:20:01.157950: Pseudo dice [0.8373] +2024-11-22 14:20:01.158043: Epoch time: 20.0 s +2024-11-22 14:20:02.110823: +2024-11-22 14:20:02.111407: Epoch 4979 +2024-11-22 14:20:02.111522: Current learning rate: 0.00416 +2024-11-22 14:20:22.233103: train_loss -0.7858 +2024-11-22 14:20:22.242926: val_loss -0.7708 +2024-11-22 14:20:22.243049: Pseudo dice [0.8638] +2024-11-22 14:20:22.243152: Epoch time: 20.12 s +2024-11-22 14:20:23.165265: +2024-11-22 14:20:23.167367: Epoch 4980 +2024-11-22 14:20:23.167523: Current learning rate: 0.00416 +2024-11-22 14:20:42.904959: train_loss -0.7879 +2024-11-22 14:20:42.911036: val_loss -0.7823 +2024-11-22 14:20:42.911155: Pseudo dice [0.8497] +2024-11-22 14:20:42.911249: Epoch time: 19.74 s +2024-11-22 14:20:43.910042: +2024-11-22 14:20:43.910468: Epoch 4981 +2024-11-22 14:20:43.910597: Current learning rate: 0.00416 +2024-11-22 14:21:03.602323: train_loss -0.7908 +2024-11-22 14:21:03.604742: val_loss -0.7599 +2024-11-22 14:21:03.605084: Pseudo dice [0.8556] +2024-11-22 14:21:03.605181: Epoch time: 19.69 s +2024-11-22 14:21:04.508235: +2024-11-22 14:21:04.509085: Epoch 4982 +2024-11-22 14:21:04.509217: Current learning rate: 0.00416 +2024-11-22 14:21:24.061621: train_loss -0.7887 +2024-11-22 14:21:24.071687: val_loss -0.7686 +2024-11-22 14:21:24.071811: Pseudo dice [0.865] +2024-11-22 14:21:24.071907: Epoch time: 19.55 s +2024-11-22 14:21:25.077205: +2024-11-22 14:21:25.078892: Epoch 4983 +2024-11-22 14:21:25.079023: Current learning rate: 0.00416 +2024-11-22 14:21:44.754024: train_loss -0.7943 +2024-11-22 14:21:44.763315: val_loss -0.7642 +2024-11-22 14:21:44.763433: Pseudo dice [0.85] +2024-11-22 14:21:44.763525: Epoch time: 19.68 s +2024-11-22 14:21:46.046019: +2024-11-22 14:21:46.047136: Epoch 4984 +2024-11-22 14:21:46.047256: Current learning rate: 0.00416 +2024-11-22 14:22:05.566222: train_loss -0.7922 +2024-11-22 14:22:05.573042: val_loss -0.7717 +2024-11-22 14:22:05.573183: Pseudo dice [0.8408] +2024-11-22 14:22:05.573269: Epoch time: 19.52 s +2024-11-22 14:22:06.574747: +2024-11-22 14:22:06.576465: Epoch 4985 +2024-11-22 14:22:06.576595: Current learning rate: 0.00416 +2024-11-22 14:22:26.386671: train_loss -0.7913 +2024-11-22 14:22:26.391511: val_loss -0.7774 +2024-11-22 14:22:26.391639: Pseudo dice [0.8354] +2024-11-22 14:22:26.391732: Epoch time: 19.81 s +2024-11-22 14:22:27.483169: +2024-11-22 14:22:27.485186: Epoch 4986 +2024-11-22 14:22:27.485317: Current learning rate: 0.00415 +2024-11-22 14:22:46.577715: train_loss -0.7953 +2024-11-22 14:22:46.583905: val_loss -0.7758 +2024-11-22 14:22:46.584129: Pseudo dice [0.8611] +2024-11-22 14:22:46.584248: Epoch time: 19.1 s +2024-11-22 14:22:47.455579: +2024-11-22 14:22:47.456087: Epoch 4987 +2024-11-22 14:22:47.456210: Current learning rate: 0.00415 +2024-11-22 14:23:07.484842: train_loss -0.7904 +2024-11-22 14:23:07.491386: val_loss -0.7554 +2024-11-22 14:23:07.491510: Pseudo dice [0.8453] +2024-11-22 14:23:07.491616: Epoch time: 20.03 s +2024-11-22 14:23:08.473264: +2024-11-22 14:23:08.475028: Epoch 4988 +2024-11-22 14:23:08.475164: Current learning rate: 0.00415 +2024-11-22 14:23:26.858853: train_loss -0.7942 +2024-11-22 14:23:26.865047: val_loss -0.7429 +2024-11-22 14:23:26.865206: Pseudo dice [0.8505] +2024-11-22 14:23:26.865320: Epoch time: 18.39 s +2024-11-22 14:23:27.914979: +2024-11-22 14:23:27.917958: Epoch 4989 +2024-11-22 14:23:27.918103: Current learning rate: 0.00415 +2024-11-22 14:23:47.545682: train_loss -0.7953 +2024-11-22 14:23:47.561700: val_loss -0.7717 +2024-11-22 14:23:47.561851: Pseudo dice [0.8438] +2024-11-22 14:23:47.561935: Epoch time: 19.63 s +2024-11-22 14:23:48.478562: +2024-11-22 14:23:48.479380: Epoch 4990 +2024-11-22 14:23:48.479508: Current learning rate: 0.00415 +2024-11-22 14:24:07.372889: train_loss -0.7934 +2024-11-22 14:24:07.379384: val_loss -0.7887 +2024-11-22 14:24:07.379530: Pseudo dice [0.8582] +2024-11-22 14:24:07.379627: Epoch time: 18.9 s +2024-11-22 14:24:08.431268: +2024-11-22 14:24:08.432734: Epoch 4991 +2024-11-22 14:24:08.432854: Current learning rate: 0.00415 +2024-11-22 14:24:29.339811: train_loss -0.7947 +2024-11-22 14:24:29.346752: val_loss -0.7626 +2024-11-22 14:24:29.346886: Pseudo dice [0.8572] +2024-11-22 14:24:29.347004: Epoch time: 20.91 s +2024-11-22 14:24:30.229191: +2024-11-22 14:24:30.230731: Epoch 4992 +2024-11-22 14:24:30.230877: Current learning rate: 0.00415 +2024-11-22 14:24:49.902900: train_loss -0.7902 +2024-11-22 14:24:49.910335: val_loss -0.7837 +2024-11-22 14:24:49.910460: Pseudo dice [0.8562] +2024-11-22 14:24:49.910564: Epoch time: 19.67 s +2024-11-22 14:24:50.828702: +2024-11-22 14:24:50.829819: Epoch 4993 +2024-11-22 14:24:50.829940: Current learning rate: 0.00415 +2024-11-22 14:25:10.328958: train_loss -0.7995 +2024-11-22 14:25:10.338029: val_loss -0.7754 +2024-11-22 14:25:10.338167: Pseudo dice [0.8614] +2024-11-22 14:25:10.338253: Epoch time: 19.5 s +2024-11-22 14:25:11.338926: +2024-11-22 14:25:11.339716: Epoch 4994 +2024-11-22 14:25:11.339842: Current learning rate: 0.00414 +2024-11-22 14:25:30.872780: train_loss -0.7906 +2024-11-22 14:25:30.884356: val_loss -0.7729 +2024-11-22 14:25:30.884477: Pseudo dice [0.8423] +2024-11-22 14:25:30.884567: Epoch time: 19.53 s +2024-11-22 14:25:31.848330: +2024-11-22 14:25:31.849138: Epoch 4995 +2024-11-22 14:25:31.849263: Current learning rate: 0.00414 +2024-11-22 14:25:51.864013: train_loss -0.7848 +2024-11-22 14:25:51.881499: val_loss -0.7593 +2024-11-22 14:25:51.881634: Pseudo dice [0.8491] +2024-11-22 14:25:51.881746: Epoch time: 20.02 s +2024-11-22 14:25:53.232230: +2024-11-22 14:25:53.233248: Epoch 4996 +2024-11-22 14:25:53.233370: Current learning rate: 0.00414 +2024-11-22 14:26:13.233759: train_loss -0.7934 +2024-11-22 14:26:13.239092: val_loss -0.7547 +2024-11-22 14:26:13.239292: Pseudo dice [0.8441] +2024-11-22 14:26:13.239381: Epoch time: 20.0 s +2024-11-22 14:26:14.127316: +2024-11-22 14:26:14.127748: Epoch 4997 +2024-11-22 14:26:14.128078: Current learning rate: 0.00414 +2024-11-22 14:26:32.513905: train_loss -0.7945 +2024-11-22 14:26:32.516497: val_loss -0.7824 +2024-11-22 14:26:32.516629: Pseudo dice [0.8544] +2024-11-22 14:26:32.516724: Epoch time: 18.39 s +2024-11-22 14:26:33.459977: +2024-11-22 14:26:33.461648: Epoch 4998 +2024-11-22 14:26:33.461776: Current learning rate: 0.00414 +2024-11-22 14:26:53.276414: train_loss -0.7875 +2024-11-22 14:26:53.289880: val_loss -0.7523 +2024-11-22 14:26:53.290025: Pseudo dice [0.8505] +2024-11-22 14:26:53.290137: Epoch time: 19.82 s +2024-11-22 14:26:54.298127: +2024-11-22 14:26:54.298596: Epoch 4999 +2024-11-22 14:26:54.298716: Current learning rate: 0.00414 +2024-11-22 14:27:13.165216: train_loss -0.7881 +2024-11-22 14:27:13.173280: val_loss -0.7939 +2024-11-22 14:27:13.173409: Pseudo dice [0.8618] +2024-11-22 14:27:13.173500: Epoch time: 18.87 s +2024-11-22 14:27:14.322524: +2024-11-22 14:27:14.324064: Epoch 5000 +2024-11-22 14:27:14.324180: Current learning rate: 0.00414 +2024-11-22 14:27:33.011591: train_loss -0.7997 +2024-11-22 14:27:33.017960: val_loss -0.7646 +2024-11-22 14:27:33.018079: Pseudo dice [0.8438] +2024-11-22 14:27:33.018163: Epoch time: 18.69 s +2024-11-22 14:27:33.995502: +2024-11-22 14:27:33.996324: Epoch 5001 +2024-11-22 14:27:33.996452: Current learning rate: 0.00414 +2024-11-22 14:27:53.060373: train_loss -0.788 +2024-11-22 14:27:53.063109: val_loss -0.7854 +2024-11-22 14:27:53.063254: Pseudo dice [0.8601] +2024-11-22 14:27:53.063352: Epoch time: 19.07 s +2024-11-22 14:27:54.149568: +2024-11-22 14:27:54.149987: Epoch 5002 +2024-11-22 14:27:54.150109: Current learning rate: 0.00413 +2024-11-22 14:28:12.181584: train_loss -0.7932 +2024-11-22 14:28:12.191105: val_loss -0.7746 +2024-11-22 14:28:12.191246: Pseudo dice [0.859] +2024-11-22 14:28:12.191342: Epoch time: 18.03 s +2024-11-22 14:28:13.062126: +2024-11-22 14:28:13.062351: Epoch 5003 +2024-11-22 14:28:13.062460: Current learning rate: 0.00413 +2024-11-22 14:28:31.116749: train_loss -0.7886 +2024-11-22 14:28:31.123936: val_loss -0.767 +2024-11-22 14:28:31.124085: Pseudo dice [0.8524] +2024-11-22 14:28:31.124193: Epoch time: 18.06 s +2024-11-22 14:28:32.140008: +2024-11-22 14:28:32.140212: Epoch 5004 +2024-11-22 14:28:32.140322: Current learning rate: 0.00413 +2024-11-22 14:28:51.535581: train_loss -0.7701 +2024-11-22 14:28:51.536705: val_loss -0.7628 +2024-11-22 14:28:51.536805: Pseudo dice [0.8401] +2024-11-22 14:28:51.536899: Epoch time: 19.4 s +2024-11-22 14:28:52.385002: +2024-11-22 14:28:52.385228: Epoch 5005 +2024-11-22 14:28:52.385349: Current learning rate: 0.00413 +2024-11-22 14:29:12.486024: train_loss -0.7893 +2024-11-22 14:29:12.490841: val_loss -0.77 +2024-11-22 14:29:12.490992: Pseudo dice [0.8442] +2024-11-22 14:29:12.491102: Epoch time: 20.1 s +2024-11-22 14:29:13.349393: +2024-11-22 14:29:13.349578: Epoch 5006 +2024-11-22 14:29:13.349708: Current learning rate: 0.00413 +2024-11-22 14:29:31.109700: train_loss -0.7863 +2024-11-22 14:29:31.110312: val_loss -0.7625 +2024-11-22 14:29:31.110441: Pseudo dice [0.8531] +2024-11-22 14:29:31.110533: Epoch time: 17.76 s +2024-11-22 14:29:31.973098: +2024-11-22 14:29:31.973329: Epoch 5007 +2024-11-22 14:29:31.973453: Current learning rate: 0.00413 +2024-11-22 14:29:52.297518: train_loss -0.772 +2024-11-22 14:29:52.298011: val_loss -0.7497 +2024-11-22 14:29:52.298581: Pseudo dice [0.8511] +2024-11-22 14:29:52.298716: Epoch time: 20.33 s +2024-11-22 14:29:53.150415: +2024-11-22 14:29:53.150620: Epoch 5008 +2024-11-22 14:29:53.150732: Current learning rate: 0.00413 +2024-11-22 14:30:11.713482: train_loss -0.7853 +2024-11-22 14:30:11.716938: val_loss -0.7367 +2024-11-22 14:30:11.717085: Pseudo dice [0.8625] +2024-11-22 14:30:11.717172: Epoch time: 18.56 s +2024-11-22 14:30:12.935537: +2024-11-22 14:30:12.935775: Epoch 5009 +2024-11-22 14:30:12.935894: Current learning rate: 0.00413 +2024-11-22 14:30:31.413511: train_loss -0.7837 +2024-11-22 14:30:31.415641: val_loss -0.7724 +2024-11-22 14:30:31.415769: Pseudo dice [0.847] +2024-11-22 14:30:31.415854: Epoch time: 18.48 s +2024-11-22 14:30:32.292448: +2024-11-22 14:30:32.292691: Epoch 5010 +2024-11-22 14:30:32.292815: Current learning rate: 0.00412 +2024-11-22 14:30:50.090477: train_loss -0.7924 +2024-11-22 14:30:50.095676: val_loss -0.7629 +2024-11-22 14:30:50.095807: Pseudo dice [0.8497] +2024-11-22 14:30:50.095902: Epoch time: 17.8 s +2024-11-22 14:30:51.006164: +2024-11-22 14:30:51.006366: Epoch 5011 +2024-11-22 14:30:51.006478: Current learning rate: 0.00412 +2024-11-22 14:31:10.507214: train_loss -0.801 +2024-11-22 14:31:10.514779: val_loss -0.7745 +2024-11-22 14:31:10.514897: Pseudo dice [0.8494] +2024-11-22 14:31:10.514987: Epoch time: 19.5 s +2024-11-22 14:31:11.370250: +2024-11-22 14:31:11.370701: Epoch 5012 +2024-11-22 14:31:11.370833: Current learning rate: 0.00412 +2024-11-22 14:31:30.573272: train_loss -0.7932 +2024-11-22 14:31:30.577672: val_loss -0.7547 +2024-11-22 14:31:30.577837: Pseudo dice [0.8428] +2024-11-22 14:31:30.577938: Epoch time: 19.2 s +2024-11-22 14:31:31.470192: +2024-11-22 14:31:31.473180: Epoch 5013 +2024-11-22 14:31:31.473306: Current learning rate: 0.00412 +2024-11-22 14:31:49.616013: train_loss -0.794 +2024-11-22 14:31:49.624246: val_loss -0.7695 +2024-11-22 14:31:49.624382: Pseudo dice [0.8504] +2024-11-22 14:31:49.624476: Epoch time: 18.15 s +2024-11-22 14:31:50.529692: +2024-11-22 14:31:50.532433: Epoch 5014 +2024-11-22 14:31:50.532581: Current learning rate: 0.00412 +2024-11-22 14:32:09.443491: train_loss -0.7975 +2024-11-22 14:32:09.446048: val_loss -0.7594 +2024-11-22 14:32:09.446164: Pseudo dice [0.8595] +2024-11-22 14:32:09.446266: Epoch time: 18.91 s +2024-11-22 14:32:10.309724: +2024-11-22 14:32:10.310653: Epoch 5015 +2024-11-22 14:32:10.310773: Current learning rate: 0.00412 +2024-11-22 14:32:30.726387: train_loss -0.798 +2024-11-22 14:32:30.733914: val_loss -0.7733 +2024-11-22 14:32:30.734064: Pseudo dice [0.8592] +2024-11-22 14:32:30.734163: Epoch time: 20.42 s +2024-11-22 14:32:31.600276: +2024-11-22 14:32:31.601071: Epoch 5016 +2024-11-22 14:32:31.601185: Current learning rate: 0.00412 +2024-11-22 14:32:51.774616: train_loss -0.7802 +2024-11-22 14:32:51.782635: val_loss -0.7777 +2024-11-22 14:32:51.782758: Pseudo dice [0.844] +2024-11-22 14:32:51.782845: Epoch time: 20.18 s +2024-11-22 14:32:52.679396: +2024-11-22 14:32:52.680667: Epoch 5017 +2024-11-22 14:32:52.680784: Current learning rate: 0.00412 +2024-11-22 14:33:12.186920: train_loss -0.7916 +2024-11-22 14:33:12.190516: val_loss -0.7771 +2024-11-22 14:33:12.190646: Pseudo dice [0.849] +2024-11-22 14:33:12.190735: Epoch time: 19.51 s +2024-11-22 14:33:13.047560: +2024-11-22 14:33:13.048485: Epoch 5018 +2024-11-22 14:33:13.048606: Current learning rate: 0.00411 +2024-11-22 14:33:32.292668: train_loss -0.7799 +2024-11-22 14:33:32.298236: val_loss -0.7786 +2024-11-22 14:33:32.298384: Pseudo dice [0.852] +2024-11-22 14:33:32.298474: Epoch time: 19.25 s +2024-11-22 14:33:33.612055: +2024-11-22 14:33:33.614249: Epoch 5019 +2024-11-22 14:33:33.614397: Current learning rate: 0.00411 +2024-11-22 14:33:52.627333: train_loss -0.7841 +2024-11-22 14:33:52.635215: val_loss -0.772 +2024-11-22 14:33:52.635338: Pseudo dice [0.8459] +2024-11-22 14:33:52.635431: Epoch time: 19.02 s +2024-11-22 14:33:53.624121: +2024-11-22 14:33:53.625152: Epoch 5020 +2024-11-22 14:33:53.625278: Current learning rate: 0.00411 +2024-11-22 14:34:13.443364: train_loss -0.7962 +2024-11-22 14:34:13.461733: val_loss -0.7728 +2024-11-22 14:34:13.461869: Pseudo dice [0.8478] +2024-11-22 14:34:13.461958: Epoch time: 19.81 s +2024-11-22 14:34:14.326549: +2024-11-22 14:34:14.327667: Epoch 5021 +2024-11-22 14:34:14.327798: Current learning rate: 0.00411 +2024-11-22 14:34:34.588830: train_loss -0.7939 +2024-11-22 14:34:34.592802: val_loss -0.772 +2024-11-22 14:34:34.592937: Pseudo dice [0.8538] +2024-11-22 14:34:34.593032: Epoch time: 20.26 s +2024-11-22 14:34:35.543425: +2024-11-22 14:34:35.544985: Epoch 5022 +2024-11-22 14:34:35.545114: Current learning rate: 0.00411 +2024-11-22 14:34:55.148631: train_loss -0.7971 +2024-11-22 14:34:55.157365: val_loss -0.7792 +2024-11-22 14:34:55.157780: Pseudo dice [0.8416] +2024-11-22 14:34:55.157950: Epoch time: 19.61 s +2024-11-22 14:34:56.016831: +2024-11-22 14:34:56.018992: Epoch 5023 +2024-11-22 14:34:56.019165: Current learning rate: 0.00411 +2024-11-22 14:35:16.019992: train_loss -0.7926 +2024-11-22 14:35:16.030372: val_loss -0.7493 +2024-11-22 14:35:16.030519: Pseudo dice [0.8364] +2024-11-22 14:35:16.030632: Epoch time: 20.0 s +2024-11-22 14:35:16.920499: +2024-11-22 14:35:16.921356: Epoch 5024 +2024-11-22 14:35:16.921477: Current learning rate: 0.00411 +2024-11-22 14:35:37.105580: train_loss -0.7888 +2024-11-22 14:35:37.109226: val_loss -0.7672 +2024-11-22 14:35:37.109372: Pseudo dice [0.8709] +2024-11-22 14:35:37.109459: Epoch time: 20.19 s +2024-11-22 14:35:38.001526: +2024-11-22 14:35:38.003368: Epoch 5025 +2024-11-22 14:35:38.003491: Current learning rate: 0.00411 +2024-11-22 14:35:56.688606: train_loss -0.7908 +2024-11-22 14:35:56.690978: val_loss -0.7557 +2024-11-22 14:35:56.691085: Pseudo dice [0.8503] +2024-11-22 14:35:56.691195: Epoch time: 18.69 s +2024-11-22 14:35:57.541242: +2024-11-22 14:35:57.542137: Epoch 5026 +2024-11-22 14:35:57.542255: Current learning rate: 0.0041 +2024-11-22 14:36:17.326046: train_loss -0.8019 +2024-11-22 14:36:17.333798: val_loss -0.7856 +2024-11-22 14:36:17.333947: Pseudo dice [0.8489] +2024-11-22 14:36:17.334046: Epoch time: 19.79 s +2024-11-22 14:36:18.277563: +2024-11-22 14:36:18.279017: Epoch 5027 +2024-11-22 14:36:18.279143: Current learning rate: 0.0041 +2024-11-22 14:36:37.072234: train_loss -0.759 +2024-11-22 14:36:37.080495: val_loss -0.7415 +2024-11-22 14:36:37.080652: Pseudo dice [0.8205] +2024-11-22 14:36:37.080795: Epoch time: 18.8 s +2024-11-22 14:36:38.027381: +2024-11-22 14:36:38.028314: Epoch 5028 +2024-11-22 14:36:38.028445: Current learning rate: 0.0041 +2024-11-22 14:36:57.308622: train_loss -0.7603 +2024-11-22 14:36:57.317585: val_loss -0.7542 +2024-11-22 14:36:57.317715: Pseudo dice [0.8318] +2024-11-22 14:36:57.317802: Epoch time: 19.28 s +2024-11-22 14:36:58.244864: +2024-11-22 14:36:58.247619: Epoch 5029 +2024-11-22 14:36:58.247764: Current learning rate: 0.0041 +2024-11-22 14:37:16.941416: train_loss -0.7712 +2024-11-22 14:37:16.944153: val_loss -0.7565 +2024-11-22 14:37:16.944270: Pseudo dice [0.8428] +2024-11-22 14:37:16.944352: Epoch time: 18.7 s +2024-11-22 14:37:17.870250: +2024-11-22 14:37:17.871499: Epoch 5030 +2024-11-22 14:37:17.871620: Current learning rate: 0.0041 +2024-11-22 14:37:37.648136: train_loss -0.7788 +2024-11-22 14:37:37.654899: val_loss -0.7744 +2024-11-22 14:37:37.655031: Pseudo dice [0.8562] +2024-11-22 14:37:37.655145: Epoch time: 19.78 s +2024-11-22 14:37:39.194753: +2024-11-22 14:37:39.196349: Epoch 5031 +2024-11-22 14:37:39.196491: Current learning rate: 0.0041 +2024-11-22 14:37:58.087801: train_loss -0.7512 +2024-11-22 14:37:58.096312: val_loss -0.771 +2024-11-22 14:37:58.096453: Pseudo dice [0.8235] +2024-11-22 14:37:58.096540: Epoch time: 18.89 s +2024-11-22 14:37:58.965055: +2024-11-22 14:37:58.966136: Epoch 5032 +2024-11-22 14:37:58.966270: Current learning rate: 0.0041 +2024-11-22 14:38:18.264590: train_loss -0.7535 +2024-11-22 14:38:18.277429: val_loss -0.7584 +2024-11-22 14:38:18.277588: Pseudo dice [0.8428] +2024-11-22 14:38:18.277685: Epoch time: 19.3 s +2024-11-22 14:38:19.212506: +2024-11-22 14:38:19.214811: Epoch 5033 +2024-11-22 14:38:19.214956: Current learning rate: 0.0041 +2024-11-22 14:38:38.677434: train_loss -0.7788 +2024-11-22 14:38:38.685641: val_loss -0.767 +2024-11-22 14:38:38.685869: Pseudo dice [0.8482] +2024-11-22 14:38:38.685966: Epoch time: 19.47 s +2024-11-22 14:38:39.696266: +2024-11-22 14:38:39.698591: Epoch 5034 +2024-11-22 14:38:39.698754: Current learning rate: 0.00409 +2024-11-22 14:38:59.118298: train_loss -0.7788 +2024-11-22 14:38:59.125008: val_loss -0.7835 +2024-11-22 14:38:59.125241: Pseudo dice [0.855] +2024-11-22 14:38:59.125349: Epoch time: 19.42 s +2024-11-22 14:39:00.010770: +2024-11-22 14:39:00.012601: Epoch 5035 +2024-11-22 14:39:00.012751: Current learning rate: 0.00409 +2024-11-22 14:39:18.913249: train_loss -0.7943 +2024-11-22 14:39:18.920000: val_loss -0.7522 +2024-11-22 14:39:18.920143: Pseudo dice [0.8501] +2024-11-22 14:39:18.920252: Epoch time: 18.9 s +2024-11-22 14:39:19.815217: +2024-11-22 14:39:19.815964: Epoch 5036 +2024-11-22 14:39:19.816107: Current learning rate: 0.00409 +2024-11-22 14:39:39.396648: train_loss -0.7827 +2024-11-22 14:39:39.401884: val_loss -0.7697 +2024-11-22 14:39:39.402012: Pseudo dice [0.8461] +2024-11-22 14:39:39.402124: Epoch time: 19.58 s +2024-11-22 14:39:40.259597: +2024-11-22 14:39:40.261332: Epoch 5037 +2024-11-22 14:39:40.261488: Current learning rate: 0.00409 +2024-11-22 14:39:59.024024: train_loss -0.7917 +2024-11-22 14:39:59.030827: val_loss -0.7735 +2024-11-22 14:39:59.030971: Pseudo dice [0.8559] +2024-11-22 14:39:59.031079: Epoch time: 18.77 s +2024-11-22 14:40:00.065563: +2024-11-22 14:40:00.066300: Epoch 5038 +2024-11-22 14:40:00.066455: Current learning rate: 0.00409 +2024-11-22 14:40:19.798514: train_loss -0.7876 +2024-11-22 14:40:19.806200: val_loss -0.7753 +2024-11-22 14:40:19.806341: Pseudo dice [0.8585] +2024-11-22 14:40:19.806440: Epoch time: 19.73 s +2024-11-22 14:40:20.686944: +2024-11-22 14:40:20.687693: Epoch 5039 +2024-11-22 14:40:20.687836: Current learning rate: 0.00409 +2024-11-22 14:40:40.514480: train_loss -0.7902 +2024-11-22 14:40:40.523690: val_loss -0.786 +2024-11-22 14:40:40.523821: Pseudo dice [0.8623] +2024-11-22 14:40:40.523916: Epoch time: 19.83 s +2024-11-22 14:40:41.590878: +2024-11-22 14:40:41.592227: Epoch 5040 +2024-11-22 14:40:41.592382: Current learning rate: 0.00409 +2024-11-22 14:41:01.036120: train_loss -0.7983 +2024-11-22 14:41:01.043855: val_loss -0.7656 +2024-11-22 14:41:01.044003: Pseudo dice [0.8457] +2024-11-22 14:41:01.044109: Epoch time: 19.45 s +2024-11-22 14:41:02.006883: +2024-11-22 14:41:02.007961: Epoch 5041 +2024-11-22 14:41:02.008108: Current learning rate: 0.00409 +2024-11-22 14:41:21.774229: train_loss -0.7937 +2024-11-22 14:41:21.788761: val_loss -0.7801 +2024-11-22 14:41:21.788886: Pseudo dice [0.8541] +2024-11-22 14:41:21.788983: Epoch time: 19.77 s +2024-11-22 14:41:22.878430: +2024-11-22 14:41:22.879595: Epoch 5042 +2024-11-22 14:41:22.879736: Current learning rate: 0.00408 +2024-11-22 14:41:42.854734: train_loss -0.787 +2024-11-22 14:41:42.863684: val_loss -0.7694 +2024-11-22 14:41:42.863804: Pseudo dice [0.8277] +2024-11-22 14:41:42.863890: Epoch time: 19.98 s +2024-11-22 14:41:43.852998: +2024-11-22 14:41:43.854051: Epoch 5043 +2024-11-22 14:41:43.854198: Current learning rate: 0.00408 +2024-11-22 14:42:02.719409: train_loss -0.7807 +2024-11-22 14:42:02.732288: val_loss -0.7537 +2024-11-22 14:42:02.732457: Pseudo dice [0.851] +2024-11-22 14:42:02.732567: Epoch time: 18.87 s +2024-11-22 14:42:03.760310: +2024-11-22 14:42:03.761556: Epoch 5044 +2024-11-22 14:42:03.761697: Current learning rate: 0.00408 +2024-11-22 14:42:23.090924: train_loss -0.7848 +2024-11-22 14:42:23.093940: val_loss -0.76 +2024-11-22 14:42:23.094049: Pseudo dice [0.8548] +2024-11-22 14:42:23.094160: Epoch time: 19.33 s +2024-11-22 14:42:23.948911: +2024-11-22 14:42:23.949774: Epoch 5045 +2024-11-22 14:42:23.949906: Current learning rate: 0.00408 +2024-11-22 14:42:43.436466: train_loss -0.7934 +2024-11-22 14:42:43.442469: val_loss -0.7615 +2024-11-22 14:42:43.442600: Pseudo dice [0.8481] +2024-11-22 14:42:43.442687: Epoch time: 19.49 s +2024-11-22 14:42:44.366760: +2024-11-22 14:42:44.368246: Epoch 5046 +2024-11-22 14:42:44.368364: Current learning rate: 0.00408 +2024-11-22 14:43:02.603014: train_loss -0.7968 +2024-11-22 14:43:02.605259: val_loss -0.7778 +2024-11-22 14:43:02.605373: Pseudo dice [0.8468] +2024-11-22 14:43:02.605467: Epoch time: 18.24 s +2024-11-22 14:43:03.643004: +2024-11-22 14:43:03.644099: Epoch 5047 +2024-11-22 14:43:03.644223: Current learning rate: 0.00408 +2024-11-22 14:43:23.253040: train_loss -0.7952 +2024-11-22 14:43:23.259726: val_loss -0.7544 +2024-11-22 14:43:23.259866: Pseudo dice [0.8635] +2024-11-22 14:43:23.259980: Epoch time: 19.61 s +2024-11-22 14:43:24.201457: +2024-11-22 14:43:24.202682: Epoch 5048 +2024-11-22 14:43:24.202812: Current learning rate: 0.00408 +2024-11-22 14:43:44.060791: train_loss -0.7948 +2024-11-22 14:43:44.062995: val_loss -0.7835 +2024-11-22 14:43:44.063100: Pseudo dice [0.8566] +2024-11-22 14:43:44.063202: Epoch time: 19.86 s +2024-11-22 14:43:44.921489: +2024-11-22 14:43:44.923115: Epoch 5049 +2024-11-22 14:43:44.923245: Current learning rate: 0.00408 +2024-11-22 14:44:04.785338: train_loss -0.789 +2024-11-22 14:44:04.793955: val_loss -0.7795 +2024-11-22 14:44:04.794176: Pseudo dice [0.8488] +2024-11-22 14:44:04.794281: Epoch time: 19.86 s +2024-11-22 14:44:06.149323: +2024-11-22 14:44:06.150976: Epoch 5050 +2024-11-22 14:44:06.151108: Current learning rate: 0.00407 +2024-11-22 14:44:26.086866: train_loss -0.7997 +2024-11-22 14:44:26.091231: val_loss -0.753 +2024-11-22 14:44:26.091371: Pseudo dice [0.8366] +2024-11-22 14:44:26.091480: Epoch time: 19.94 s +2024-11-22 14:44:26.981572: +2024-11-22 14:44:26.982683: Epoch 5051 +2024-11-22 14:44:26.982816: Current learning rate: 0.00407 +2024-11-22 14:44:46.601891: train_loss -0.8003 +2024-11-22 14:44:46.609852: val_loss -0.7737 +2024-11-22 14:44:46.610005: Pseudo dice [0.8568] +2024-11-22 14:44:46.610134: Epoch time: 19.62 s +2024-11-22 14:44:47.690362: +2024-11-22 14:44:47.691618: Epoch 5052 +2024-11-22 14:44:47.691749: Current learning rate: 0.00407 +2024-11-22 14:45:06.993662: train_loss -0.8002 +2024-11-22 14:45:07.006430: val_loss -0.7833 +2024-11-22 14:45:07.006593: Pseudo dice [0.8708] +2024-11-22 14:45:07.006704: Epoch time: 19.3 s +2024-11-22 14:45:08.055238: +2024-11-22 14:45:08.056027: Epoch 5053 +2024-11-22 14:45:08.056161: Current learning rate: 0.00407 +2024-11-22 14:45:29.059704: train_loss -0.787 +2024-11-22 14:45:29.062131: val_loss -0.7565 +2024-11-22 14:45:29.062241: Pseudo dice [0.8459] +2024-11-22 14:45:29.062363: Epoch time: 21.01 s +2024-11-22 14:45:30.404037: +2024-11-22 14:45:30.406493: Epoch 5054 +2024-11-22 14:45:30.406629: Current learning rate: 0.00407 +2024-11-22 14:45:49.922237: train_loss -0.7935 +2024-11-22 14:45:49.931130: val_loss -0.7976 +2024-11-22 14:45:49.931358: Pseudo dice [0.8653] +2024-11-22 14:45:49.931474: Epoch time: 19.52 s +2024-11-22 14:45:51.072956: +2024-11-22 14:45:51.074121: Epoch 5055 +2024-11-22 14:45:51.074252: Current learning rate: 0.00407 +2024-11-22 14:46:11.211629: train_loss -0.7891 +2024-11-22 14:46:11.223811: val_loss -0.784 +2024-11-22 14:46:11.223952: Pseudo dice [0.8554] +2024-11-22 14:46:11.224046: Epoch time: 20.14 s +2024-11-22 14:46:12.265892: +2024-11-22 14:46:12.266111: Epoch 5056 +2024-11-22 14:46:12.266241: Current learning rate: 0.00407 +2024-11-22 14:46:31.344299: train_loss -0.7915 +2024-11-22 14:46:31.346316: val_loss -0.7901 +2024-11-22 14:46:31.346431: Pseudo dice [0.8686] +2024-11-22 14:46:31.346529: Epoch time: 19.08 s +2024-11-22 14:46:32.208062: +2024-11-22 14:46:32.209441: Epoch 5057 +2024-11-22 14:46:32.209574: Current learning rate: 0.00407 +2024-11-22 14:46:52.996087: train_loss -0.7943 +2024-11-22 14:46:53.001015: val_loss -0.7579 +2024-11-22 14:46:53.001160: Pseudo dice [0.8427] +2024-11-22 14:46:53.001270: Epoch time: 20.79 s +2024-11-22 14:46:54.031021: +2024-11-22 14:46:54.031868: Epoch 5058 +2024-11-22 14:46:54.032022: Current learning rate: 0.00406 +2024-11-22 14:47:13.075835: train_loss -0.7922 +2024-11-22 14:47:13.083551: val_loss -0.7594 +2024-11-22 14:47:13.083712: Pseudo dice [0.8403] +2024-11-22 14:47:13.083810: Epoch time: 19.05 s +2024-11-22 14:47:14.202727: +2024-11-22 14:47:14.203138: Epoch 5059 +2024-11-22 14:47:14.203258: Current learning rate: 0.00406 +2024-11-22 14:47:34.037099: train_loss -0.7947 +2024-11-22 14:47:34.040840: val_loss -0.7751 +2024-11-22 14:47:34.041051: Pseudo dice [0.8518] +2024-11-22 14:47:34.041166: Epoch time: 19.84 s +2024-11-22 14:47:34.898454: +2024-11-22 14:47:34.899237: Epoch 5060 +2024-11-22 14:47:34.899377: Current learning rate: 0.00406 +2024-11-22 14:47:53.595997: train_loss -0.7963 +2024-11-22 14:47:53.599402: val_loss -0.7698 +2024-11-22 14:47:53.599525: Pseudo dice [0.8541] +2024-11-22 14:47:53.605227: Epoch time: 18.69 s +2024-11-22 14:47:54.656332: +2024-11-22 14:47:54.657706: Epoch 5061 +2024-11-22 14:47:54.657838: Current learning rate: 0.00406 +2024-11-22 14:48:15.219819: train_loss -0.7986 +2024-11-22 14:48:15.225126: val_loss -0.7548 +2024-11-22 14:48:15.225286: Pseudo dice [0.8487] +2024-11-22 14:48:15.225396: Epoch time: 20.56 s +2024-11-22 14:48:16.281723: +2024-11-22 14:48:16.282502: Epoch 5062 +2024-11-22 14:48:16.282650: Current learning rate: 0.00406 +2024-11-22 14:48:36.226668: train_loss -0.787 +2024-11-22 14:48:36.233920: val_loss -0.7893 +2024-11-22 14:48:36.234071: Pseudo dice [0.8569] +2024-11-22 14:48:36.234179: Epoch time: 19.95 s +2024-11-22 14:48:37.082410: +2024-11-22 14:48:37.084414: Epoch 5063 +2024-11-22 14:48:37.084553: Current learning rate: 0.00406 +2024-11-22 14:48:55.773146: train_loss -0.7906 +2024-11-22 14:48:55.794546: val_loss -0.8008 +2024-11-22 14:48:55.794701: Pseudo dice [0.8627] +2024-11-22 14:48:55.794796: Epoch time: 18.69 s +2024-11-22 14:48:56.679246: +2024-11-22 14:48:56.680932: Epoch 5064 +2024-11-22 14:48:56.681056: Current learning rate: 0.00406 +2024-11-22 14:49:15.460019: train_loss -0.7941 +2024-11-22 14:49:15.483436: val_loss -0.7863 +2024-11-22 14:49:15.483578: Pseudo dice [0.8699] +2024-11-22 14:49:15.483675: Epoch time: 18.78 s +2024-11-22 14:49:16.419096: +2024-11-22 14:49:16.420863: Epoch 5065 +2024-11-22 14:49:16.420986: Current learning rate: 0.00406 +2024-11-22 14:49:34.795108: train_loss -0.8012 +2024-11-22 14:49:34.816173: val_loss -0.7749 +2024-11-22 14:49:34.816311: Pseudo dice [0.8597] +2024-11-22 14:49:34.816419: Epoch time: 18.38 s +2024-11-22 14:49:36.342809: +2024-11-22 14:49:36.344434: Epoch 5066 +2024-11-22 14:49:36.344610: Current learning rate: 0.00405 +2024-11-22 14:49:56.058013: train_loss -0.7945 +2024-11-22 14:49:56.064038: val_loss -0.7721 +2024-11-22 14:49:56.064189: Pseudo dice [0.8582] +2024-11-22 14:49:56.064281: Epoch time: 19.72 s +2024-11-22 14:49:56.964374: +2024-11-22 14:49:56.965485: Epoch 5067 +2024-11-22 14:49:56.965626: Current learning rate: 0.00405 +2024-11-22 14:50:17.001926: train_loss -0.7953 +2024-11-22 14:50:17.007601: val_loss -0.7821 +2024-11-22 14:50:17.007730: Pseudo dice [0.8542] +2024-11-22 14:50:17.014517: Epoch time: 20.04 s +2024-11-22 14:50:18.007329: +2024-11-22 14:50:18.008560: Epoch 5068 +2024-11-22 14:50:18.008689: Current learning rate: 0.00405 +2024-11-22 14:50:37.799069: train_loss -0.8022 +2024-11-22 14:50:37.807535: val_loss -0.7873 +2024-11-22 14:50:37.807712: Pseudo dice [0.8628] +2024-11-22 14:50:37.807811: Epoch time: 19.79 s +2024-11-22 14:50:38.667392: +2024-11-22 14:50:38.667841: Epoch 5069 +2024-11-22 14:50:38.667966: Current learning rate: 0.00405 +2024-11-22 14:50:57.376136: train_loss -0.7912 +2024-11-22 14:50:57.398252: val_loss -0.7899 +2024-11-22 14:50:57.398403: Pseudo dice [0.8568] +2024-11-22 14:50:57.398522: Epoch time: 18.71 s +2024-11-22 14:50:58.485770: +2024-11-22 14:50:58.487303: Epoch 5070 +2024-11-22 14:50:58.487433: Current learning rate: 0.00405 +2024-11-22 14:51:18.509416: train_loss -0.801 +2024-11-22 14:51:18.516272: val_loss -0.7898 +2024-11-22 14:51:18.516402: Pseudo dice [0.8677] +2024-11-22 14:51:18.516495: Epoch time: 20.02 s +2024-11-22 14:51:19.392420: +2024-11-22 14:51:19.392856: Epoch 5071 +2024-11-22 14:51:19.393003: Current learning rate: 0.00405 +2024-11-22 14:51:38.564941: train_loss -0.8029 +2024-11-22 14:51:38.577652: val_loss -0.7568 +2024-11-22 14:51:38.577796: Pseudo dice [0.8479] +2024-11-22 14:51:38.577898: Epoch time: 19.17 s +2024-11-22 14:51:39.490378: +2024-11-22 14:51:39.490842: Epoch 5072 +2024-11-22 14:51:39.490971: Current learning rate: 0.00405 +2024-11-22 14:51:59.123769: train_loss -0.7922 +2024-11-22 14:51:59.132403: val_loss -0.7743 +2024-11-22 14:51:59.132556: Pseudo dice [0.845] +2024-11-22 14:51:59.132654: Epoch time: 19.63 s +2024-11-22 14:52:00.206964: +2024-11-22 14:52:00.207957: Epoch 5073 +2024-11-22 14:52:00.208087: Current learning rate: 0.00405 +2024-11-22 14:52:20.429000: train_loss -0.7968 +2024-11-22 14:52:20.436238: val_loss -0.7327 +2024-11-22 14:52:20.436477: Pseudo dice [0.8452] +2024-11-22 14:52:20.436587: Epoch time: 20.22 s +2024-11-22 14:52:21.436003: +2024-11-22 14:52:21.439722: Epoch 5074 +2024-11-22 14:52:21.439844: Current learning rate: 0.00404 +2024-11-22 14:52:41.148535: train_loss -0.8029 +2024-11-22 14:52:41.155554: val_loss -0.7716 +2024-11-22 14:52:41.155683: Pseudo dice [0.8349] +2024-11-22 14:52:41.155777: Epoch time: 19.71 s +2024-11-22 14:52:42.137690: +2024-11-22 14:52:42.138588: Epoch 5075 +2024-11-22 14:52:42.138713: Current learning rate: 0.00404 +2024-11-22 14:53:02.535105: train_loss -0.8009 +2024-11-22 14:53:02.542713: val_loss -0.7947 +2024-11-22 14:53:02.542841: Pseudo dice [0.8726] +2024-11-22 14:53:02.542940: Epoch time: 20.4 s +2024-11-22 14:53:03.496394: +2024-11-22 14:53:03.497791: Epoch 5076 +2024-11-22 14:53:03.497926: Current learning rate: 0.00404 +2024-11-22 14:53:23.525445: train_loss -0.7998 +2024-11-22 14:53:23.530192: val_loss -0.7576 +2024-11-22 14:53:23.530309: Pseudo dice [0.8479] +2024-11-22 14:53:23.530398: Epoch time: 20.03 s +2024-11-22 14:53:24.524362: +2024-11-22 14:53:24.525621: Epoch 5077 +2024-11-22 14:53:24.525750: Current learning rate: 0.00404 +2024-11-22 14:53:43.710228: train_loss -0.8032 +2024-11-22 14:53:43.712691: val_loss -0.7597 +2024-11-22 14:53:43.712803: Pseudo dice [0.8491] +2024-11-22 14:53:43.712899: Epoch time: 19.19 s +2024-11-22 14:53:44.838808: +2024-11-22 14:53:44.839036: Epoch 5078 +2024-11-22 14:53:44.839165: Current learning rate: 0.00404 +2024-11-22 14:54:02.736300: train_loss -0.797 +2024-11-22 14:54:02.739171: val_loss -0.7775 +2024-11-22 14:54:02.739307: Pseudo dice [0.8519] +2024-11-22 14:54:02.739402: Epoch time: 17.9 s +2024-11-22 14:54:03.844693: +2024-11-22 14:54:03.844928: Epoch 5079 +2024-11-22 14:54:03.845082: Current learning rate: 0.00404 +2024-11-22 14:54:21.268333: train_loss -0.8032 +2024-11-22 14:54:21.273182: val_loss -0.7761 +2024-11-22 14:54:21.273310: Pseudo dice [0.857] +2024-11-22 14:54:21.273408: Epoch time: 17.42 s +2024-11-22 14:54:22.282467: +2024-11-22 14:54:22.282717: Epoch 5080 +2024-11-22 14:54:22.282847: Current learning rate: 0.00404 +2024-11-22 14:54:42.257997: train_loss -0.7996 +2024-11-22 14:54:42.266309: val_loss -0.7771 +2024-11-22 14:54:42.266541: Pseudo dice [0.8454] +2024-11-22 14:54:42.266664: Epoch time: 19.98 s +2024-11-22 14:54:43.193772: +2024-11-22 14:54:43.193995: Epoch 5081 +2024-11-22 14:54:43.194129: Current learning rate: 0.00404 +2024-11-22 14:55:01.953675: train_loss -0.7896 +2024-11-22 14:55:01.956383: val_loss -0.7612 +2024-11-22 14:55:01.962105: Pseudo dice [0.8584] +2024-11-22 14:55:01.962305: Epoch time: 18.76 s +2024-11-22 14:55:02.894810: +2024-11-22 14:55:02.895009: Epoch 5082 +2024-11-22 14:55:02.895173: Current learning rate: 0.00403 +2024-11-22 14:55:22.211269: train_loss -0.7911 +2024-11-22 14:55:22.214529: val_loss -0.7863 +2024-11-22 14:55:22.214683: Pseudo dice [0.852] +2024-11-22 14:55:22.214783: Epoch time: 19.32 s +2024-11-22 14:55:23.164105: +2024-11-22 14:55:23.164306: Epoch 5083 +2024-11-22 14:55:23.164439: Current learning rate: 0.00403 +2024-11-22 14:55:43.542763: train_loss -0.7843 +2024-11-22 14:55:43.549257: val_loss -0.7667 +2024-11-22 14:55:43.549391: Pseudo dice [0.8451] +2024-11-22 14:55:43.549474: Epoch time: 20.38 s +2024-11-22 14:55:44.465327: +2024-11-22 14:55:44.465523: Epoch 5084 +2024-11-22 14:55:44.465646: Current learning rate: 0.00403 +2024-11-22 14:56:02.008164: train_loss -0.7879 +2024-11-22 14:56:02.011806: val_loss -0.7811 +2024-11-22 14:56:02.011940: Pseudo dice [0.8579] +2024-11-22 14:56:02.012040: Epoch time: 17.54 s +2024-11-22 14:56:03.058102: +2024-11-22 14:56:03.058328: Epoch 5085 +2024-11-22 14:56:03.058463: Current learning rate: 0.00403 +2024-11-22 14:56:21.964423: train_loss -0.7916 +2024-11-22 14:56:21.969930: val_loss -0.7628 +2024-11-22 14:56:21.970082: Pseudo dice [0.8536] +2024-11-22 14:56:21.970173: Epoch time: 18.91 s +2024-11-22 14:56:22.847832: +2024-11-22 14:56:22.848247: Epoch 5086 +2024-11-22 14:56:22.848383: Current learning rate: 0.00403 +2024-11-22 14:56:42.787810: train_loss -0.7817 +2024-11-22 14:56:42.798480: val_loss -0.7557 +2024-11-22 14:56:42.798617: Pseudo dice [0.8526] +2024-11-22 14:56:42.798728: Epoch time: 19.94 s +2024-11-22 14:56:43.679474: +2024-11-22 14:56:43.680289: Epoch 5087 +2024-11-22 14:56:43.680419: Current learning rate: 0.00403 +2024-11-22 14:57:01.867504: train_loss -0.7849 +2024-11-22 14:57:01.876276: val_loss -0.7684 +2024-11-22 14:57:01.876434: Pseudo dice [0.8399] +2024-11-22 14:57:01.876549: Epoch time: 18.19 s +2024-11-22 14:57:02.880374: +2024-11-22 14:57:02.881339: Epoch 5088 +2024-11-22 14:57:02.881484: Current learning rate: 0.00403 +2024-11-22 14:57:22.090428: train_loss -0.769 +2024-11-22 14:57:22.096103: val_loss -0.746 +2024-11-22 14:57:22.096226: Pseudo dice [0.8489] +2024-11-22 14:57:22.096324: Epoch time: 19.21 s +2024-11-22 14:57:22.978550: +2024-11-22 14:57:22.978973: Epoch 5089 +2024-11-22 14:57:22.979117: Current learning rate: 0.00403 +2024-11-22 14:57:43.613101: train_loss -0.7841 +2024-11-22 14:57:43.617914: val_loss -0.7846 +2024-11-22 14:57:43.618076: Pseudo dice [0.8556] +2024-11-22 14:57:43.618177: Epoch time: 20.64 s +2024-11-22 14:57:45.055033: +2024-11-22 14:57:45.057765: Epoch 5090 +2024-11-22 14:57:45.057910: Current learning rate: 0.00402 +2024-11-22 14:58:03.552900: train_loss -0.7926 +2024-11-22 14:58:03.564195: val_loss -0.7346 +2024-11-22 14:58:03.564358: Pseudo dice [0.8251] +2024-11-22 14:58:03.564468: Epoch time: 18.5 s +2024-11-22 14:58:04.569934: +2024-11-22 14:58:04.571408: Epoch 5091 +2024-11-22 14:58:04.571571: Current learning rate: 0.00402 +2024-11-22 14:58:24.302737: train_loss -0.7926 +2024-11-22 14:58:24.328382: val_loss -0.7887 +2024-11-22 14:58:24.328560: Pseudo dice [0.8614] +2024-11-22 14:58:24.328675: Epoch time: 19.73 s +2024-11-22 14:58:25.322005: +2024-11-22 14:58:25.323920: Epoch 5092 +2024-11-22 14:58:25.324067: Current learning rate: 0.00402 +2024-11-22 14:58:45.028330: train_loss -0.7841 +2024-11-22 14:58:45.037652: val_loss -0.7704 +2024-11-22 14:58:45.037788: Pseudo dice [0.8501] +2024-11-22 14:58:45.037895: Epoch time: 19.71 s +2024-11-22 14:58:46.244523: +2024-11-22 14:58:46.246055: Epoch 5093 +2024-11-22 14:58:46.246221: Current learning rate: 0.00402 +2024-11-22 14:59:04.968205: train_loss -0.7934 +2024-11-22 14:59:04.971662: val_loss -0.7577 +2024-11-22 14:59:04.971788: Pseudo dice [0.8393] +2024-11-22 14:59:04.971894: Epoch time: 18.72 s +2024-11-22 14:59:06.086341: +2024-11-22 14:59:06.088404: Epoch 5094 +2024-11-22 14:59:06.088577: Current learning rate: 0.00402 +2024-11-22 14:59:24.794604: train_loss -0.7852 +2024-11-22 14:59:24.801686: val_loss -0.7604 +2024-11-22 14:59:24.801850: Pseudo dice [0.8516] +2024-11-22 14:59:24.801951: Epoch time: 18.71 s +2024-11-22 14:59:25.676317: +2024-11-22 14:59:25.679152: Epoch 5095 +2024-11-22 14:59:25.679294: Current learning rate: 0.00402 +2024-11-22 14:59:44.756026: train_loss -0.7991 +2024-11-22 14:59:44.766962: val_loss -0.7661 +2024-11-22 14:59:44.767138: Pseudo dice [0.842] +2024-11-22 14:59:44.767251: Epoch time: 19.08 s +2024-11-22 14:59:45.807951: +2024-11-22 14:59:45.808942: Epoch 5096 +2024-11-22 14:59:45.809098: Current learning rate: 0.00402 +2024-11-22 15:00:05.151323: train_loss -0.7956 +2024-11-22 15:00:05.157933: val_loss -0.784 +2024-11-22 15:00:05.158118: Pseudo dice [0.8582] +2024-11-22 15:00:05.158242: Epoch time: 19.34 s +2024-11-22 15:00:06.014601: +2024-11-22 15:00:06.015564: Epoch 5097 +2024-11-22 15:00:06.015704: Current learning rate: 0.00402 +2024-11-22 15:00:25.204441: train_loss -0.7876 +2024-11-22 15:00:25.212393: val_loss -0.7741 +2024-11-22 15:00:25.212521: Pseudo dice [0.8566] +2024-11-22 15:00:25.212613: Epoch time: 19.19 s +2024-11-22 15:00:26.360806: +2024-11-22 15:00:26.362953: Epoch 5098 +2024-11-22 15:00:26.363111: Current learning rate: 0.00401 +2024-11-22 15:00:46.040764: train_loss -0.7922 +2024-11-22 15:00:46.051180: val_loss -0.7809 +2024-11-22 15:00:46.051342: Pseudo dice [0.8597] +2024-11-22 15:00:46.051668: Epoch time: 19.68 s +2024-11-22 15:00:47.202823: +2024-11-22 15:00:47.203497: Epoch 5099 +2024-11-22 15:00:47.203647: Current learning rate: 0.00401 +2024-11-22 15:01:05.428658: train_loss -0.7944 +2024-11-22 15:01:05.436770: val_loss -0.7884 +2024-11-22 15:01:05.436914: Pseudo dice [0.8626] +2024-11-22 15:01:05.437012: Epoch time: 18.23 s +2024-11-22 15:01:06.675531: +2024-11-22 15:01:06.677625: Epoch 5100 +2024-11-22 15:01:06.677790: Current learning rate: 0.00401 +2024-11-22 15:01:26.389304: train_loss -0.7952 +2024-11-22 15:01:26.397428: val_loss -0.7584 +2024-11-22 15:01:26.397584: Pseudo dice [0.8577] +2024-11-22 15:01:26.397687: Epoch time: 19.71 s +2024-11-22 15:01:27.377215: +2024-11-22 15:01:27.378702: Epoch 5101 +2024-11-22 15:01:27.378836: Current learning rate: 0.00401 +2024-11-22 15:01:46.890766: train_loss -0.7967 +2024-11-22 15:01:46.897130: val_loss -0.7602 +2024-11-22 15:01:46.897260: Pseudo dice [0.8406] +2024-11-22 15:01:46.897418: Epoch time: 19.51 s +2024-11-22 15:01:48.084185: +2024-11-22 15:01:48.085982: Epoch 5102 +2024-11-22 15:01:48.086152: Current learning rate: 0.00401 +2024-11-22 15:02:07.723746: train_loss -0.7912 +2024-11-22 15:02:07.727862: val_loss -0.742 +2024-11-22 15:02:07.728011: Pseudo dice [0.8634] +2024-11-22 15:02:07.728108: Epoch time: 19.64 s +2024-11-22 15:02:08.767343: +2024-11-22 15:02:08.769699: Epoch 5103 +2024-11-22 15:02:08.769836: Current learning rate: 0.00401 +2024-11-22 15:02:28.465008: train_loss -0.7959 +2024-11-22 15:02:28.468448: val_loss -0.7709 +2024-11-22 15:02:28.468557: Pseudo dice [0.8515] +2024-11-22 15:02:28.468644: Epoch time: 19.7 s +2024-11-22 15:02:29.327944: +2024-11-22 15:02:29.329824: Epoch 5104 +2024-11-22 15:02:29.329968: Current learning rate: 0.00401 +2024-11-22 15:02:49.579932: train_loss -0.7901 +2024-11-22 15:02:49.587400: val_loss -0.7729 +2024-11-22 15:02:49.587543: Pseudo dice [0.8606] +2024-11-22 15:02:49.587707: Epoch time: 20.25 s +2024-11-22 15:02:50.449603: +2024-11-22 15:02:50.450764: Epoch 5105 +2024-11-22 15:02:50.450900: Current learning rate: 0.00401 +2024-11-22 15:03:09.805213: train_loss -0.7929 +2024-11-22 15:03:09.810189: val_loss -0.7667 +2024-11-22 15:03:09.810325: Pseudo dice [0.854] +2024-11-22 15:03:09.810420: Epoch time: 19.36 s +2024-11-22 15:03:10.862068: +2024-11-22 15:03:10.863382: Epoch 5106 +2024-11-22 15:03:10.863516: Current learning rate: 0.004 +2024-11-22 15:03:30.982319: train_loss -0.801 +2024-11-22 15:03:30.990777: val_loss -0.7909 +2024-11-22 15:03:30.990913: Pseudo dice [0.8619] +2024-11-22 15:03:30.991081: Epoch time: 20.12 s +2024-11-22 15:03:31.996069: +2024-11-22 15:03:31.997419: Epoch 5107 +2024-11-22 15:03:31.997554: Current learning rate: 0.004 +2024-11-22 15:03:51.947020: train_loss -0.7992 +2024-11-22 15:03:51.957020: val_loss -0.7768 +2024-11-22 15:03:51.957210: Pseudo dice [0.8601] +2024-11-22 15:03:51.957328: Epoch time: 19.95 s +2024-11-22 15:03:52.945656: +2024-11-22 15:03:52.946884: Epoch 5108 +2024-11-22 15:03:52.947016: Current learning rate: 0.004 +2024-11-22 15:04:12.176859: train_loss -0.786 +2024-11-22 15:04:12.181798: val_loss -0.7756 +2024-11-22 15:04:12.181927: Pseudo dice [0.8496] +2024-11-22 15:04:12.182054: Epoch time: 19.23 s +2024-11-22 15:04:13.167786: +2024-11-22 15:04:13.168553: Epoch 5109 +2024-11-22 15:04:13.168678: Current learning rate: 0.004 +2024-11-22 15:04:32.435247: train_loss -0.7888 +2024-11-22 15:04:32.444440: val_loss -0.7784 +2024-11-22 15:04:32.444601: Pseudo dice [0.8634] +2024-11-22 15:04:32.444707: Epoch time: 19.27 s +2024-11-22 15:04:33.426097: +2024-11-22 15:04:33.427229: Epoch 5110 +2024-11-22 15:04:33.427362: Current learning rate: 0.004 +2024-11-22 15:04:53.458231: train_loss -0.7972 +2024-11-22 15:04:53.465913: val_loss -0.7588 +2024-11-22 15:04:53.466054: Pseudo dice [0.863] +2024-11-22 15:04:53.466158: Epoch time: 20.03 s +2024-11-22 15:04:54.404784: +2024-11-22 15:04:54.405206: Epoch 5111 +2024-11-22 15:04:54.405337: Current learning rate: 0.004 +2024-11-22 15:05:15.004740: train_loss -0.7875 +2024-11-22 15:05:15.011461: val_loss -0.7457 +2024-11-22 15:05:15.011636: Pseudo dice [0.8367] +2024-11-22 15:05:15.011740: Epoch time: 20.6 s +2024-11-22 15:05:15.943996: +2024-11-22 15:05:15.945577: Epoch 5112 +2024-11-22 15:05:15.945705: Current learning rate: 0.004 +2024-11-22 15:05:34.883006: train_loss -0.7736 +2024-11-22 15:05:34.906071: val_loss -0.7404 +2024-11-22 15:05:34.906261: Pseudo dice [0.8494] +2024-11-22 15:05:34.906376: Epoch time: 18.94 s +2024-11-22 15:05:36.252380: +2024-11-22 15:05:36.254011: Epoch 5113 +2024-11-22 15:05:36.254169: Current learning rate: 0.004 +2024-11-22 15:05:55.411226: train_loss -0.7888 +2024-11-22 15:05:55.426080: val_loss -0.7768 +2024-11-22 15:05:55.426240: Pseudo dice [0.8587] +2024-11-22 15:05:55.426337: Epoch time: 19.16 s +2024-11-22 15:05:56.452154: +2024-11-22 15:05:56.453187: Epoch 5114 +2024-11-22 15:05:56.453311: Current learning rate: 0.00399 +2024-11-22 15:06:14.908484: train_loss -0.7881 +2024-11-22 15:06:14.922544: val_loss -0.7684 +2024-11-22 15:06:14.922699: Pseudo dice [0.8458] +2024-11-22 15:06:14.922817: Epoch time: 18.46 s +2024-11-22 15:06:15.781812: +2024-11-22 15:06:15.784613: Epoch 5115 +2024-11-22 15:06:15.784750: Current learning rate: 0.00399 +2024-11-22 15:06:35.720676: train_loss -0.7859 +2024-11-22 15:06:35.724566: val_loss -0.7556 +2024-11-22 15:06:35.724684: Pseudo dice [0.8468] +2024-11-22 15:06:35.724802: Epoch time: 19.94 s +2024-11-22 15:06:36.582692: +2024-11-22 15:06:36.583547: Epoch 5116 +2024-11-22 15:06:36.583669: Current learning rate: 0.00399 +2024-11-22 15:06:56.079306: train_loss -0.798 +2024-11-22 15:06:56.087370: val_loss -0.7526 +2024-11-22 15:06:56.087534: Pseudo dice [0.8548] +2024-11-22 15:06:56.087631: Epoch time: 19.5 s +2024-11-22 15:06:57.108427: +2024-11-22 15:06:57.110843: Epoch 5117 +2024-11-22 15:06:57.110979: Current learning rate: 0.00399 +2024-11-22 15:07:16.920867: train_loss -0.7759 +2024-11-22 15:07:16.931007: val_loss -0.7401 +2024-11-22 15:07:16.931163: Pseudo dice [0.8449] +2024-11-22 15:07:16.931253: Epoch time: 19.81 s +2024-11-22 15:07:18.022685: +2024-11-22 15:07:18.024166: Epoch 5118 +2024-11-22 15:07:18.024293: Current learning rate: 0.00399 +2024-11-22 15:07:36.947764: train_loss -0.7884 +2024-11-22 15:07:36.959352: val_loss -0.7549 +2024-11-22 15:07:36.959505: Pseudo dice [0.836] +2024-11-22 15:07:36.959599: Epoch time: 18.93 s +2024-11-22 15:07:37.987282: +2024-11-22 15:07:37.988185: Epoch 5119 +2024-11-22 15:07:37.988324: Current learning rate: 0.00399 +2024-11-22 15:07:58.466524: train_loss -0.774 +2024-11-22 15:07:58.480095: val_loss -0.7722 +2024-11-22 15:07:58.480267: Pseudo dice [0.8467] +2024-11-22 15:07:58.480386: Epoch time: 20.48 s +2024-11-22 15:07:59.494186: +2024-11-22 15:07:59.494614: Epoch 5120 +2024-11-22 15:07:59.494749: Current learning rate: 0.00399 +2024-11-22 15:08:18.399210: train_loss -0.7665 +2024-11-22 15:08:18.405670: val_loss -0.7592 +2024-11-22 15:08:18.405843: Pseudo dice [0.8369] +2024-11-22 15:08:18.405998: Epoch time: 18.91 s +2024-11-22 15:08:19.292727: +2024-11-22 15:08:19.293144: Epoch 5121 +2024-11-22 15:08:19.293268: Current learning rate: 0.00399 +2024-11-22 15:08:40.466971: train_loss -0.7701 +2024-11-22 15:08:40.475799: val_loss -0.7727 +2024-11-22 15:08:40.475967: Pseudo dice [0.8374] +2024-11-22 15:08:40.476088: Epoch time: 21.18 s +2024-11-22 15:08:41.357494: +2024-11-22 15:08:41.358745: Epoch 5122 +2024-11-22 15:08:41.358886: Current learning rate: 0.00398 +2024-11-22 15:08:59.344172: train_loss -0.7878 +2024-11-22 15:08:59.348625: val_loss -0.7907 +2024-11-22 15:08:59.348777: Pseudo dice [0.8566] +2024-11-22 15:08:59.348879: Epoch time: 17.99 s +2024-11-22 15:09:00.307314: +2024-11-22 15:09:00.308969: Epoch 5123 +2024-11-22 15:09:00.309123: Current learning rate: 0.00398 +2024-11-22 15:09:18.709145: train_loss -0.8015 +2024-11-22 15:09:18.714094: val_loss -0.7743 +2024-11-22 15:09:18.714224: Pseudo dice [0.8607] +2024-11-22 15:09:18.714324: Epoch time: 18.4 s +2024-11-22 15:09:19.647272: +2024-11-22 15:09:19.647487: Epoch 5124 +2024-11-22 15:09:19.647603: Current learning rate: 0.00398 +2024-11-22 15:09:39.168431: train_loss -0.7927 +2024-11-22 15:09:39.177246: val_loss -0.8041 +2024-11-22 15:09:39.177392: Pseudo dice [0.8647] +2024-11-22 15:09:39.177518: Epoch time: 19.52 s +2024-11-22 15:09:40.577434: +2024-11-22 15:09:40.578849: Epoch 5125 +2024-11-22 15:09:40.578970: Current learning rate: 0.00398 +2024-11-22 15:10:01.523533: train_loss -0.7896 +2024-11-22 15:10:01.530260: val_loss -0.7812 +2024-11-22 15:10:01.530503: Pseudo dice [0.8456] +2024-11-22 15:10:01.530613: Epoch time: 20.95 s +2024-11-22 15:10:02.491324: +2024-11-22 15:10:02.493218: Epoch 5126 +2024-11-22 15:10:02.493346: Current learning rate: 0.00398 +2024-11-22 15:10:21.382169: train_loss -0.7959 +2024-11-22 15:10:21.398600: val_loss -0.784 +2024-11-22 15:10:21.398762: Pseudo dice [0.8529] +2024-11-22 15:10:21.398863: Epoch time: 18.89 s +2024-11-22 15:10:22.382782: +2024-11-22 15:10:22.384143: Epoch 5127 +2024-11-22 15:10:22.384260: Current learning rate: 0.00398 +2024-11-22 15:10:42.362913: train_loss -0.7735 +2024-11-22 15:10:42.367540: val_loss -0.7924 +2024-11-22 15:10:42.367675: Pseudo dice [0.8628] +2024-11-22 15:10:42.367777: Epoch time: 19.98 s +2024-11-22 15:10:43.435208: +2024-11-22 15:10:43.436547: Epoch 5128 +2024-11-22 15:10:43.436672: Current learning rate: 0.00398 +2024-11-22 15:11:03.878476: train_loss -0.773 +2024-11-22 15:11:03.892947: val_loss -0.7593 +2024-11-22 15:11:03.893083: Pseudo dice [0.8591] +2024-11-22 15:11:03.893197: Epoch time: 20.44 s +2024-11-22 15:11:04.910412: +2024-11-22 15:11:04.911789: Epoch 5129 +2024-11-22 15:11:04.911921: Current learning rate: 0.00398 +2024-11-22 15:11:23.770044: train_loss -0.7995 +2024-11-22 15:11:23.781804: val_loss -0.796 +2024-11-22 15:11:23.781945: Pseudo dice [0.8606] +2024-11-22 15:11:23.782038: Epoch time: 18.86 s +2024-11-22 15:11:24.707266: +2024-11-22 15:11:24.708814: Epoch 5130 +2024-11-22 15:11:24.708947: Current learning rate: 0.00397 +2024-11-22 15:11:44.262866: train_loss -0.7966 +2024-11-22 15:11:44.265827: val_loss -0.7708 +2024-11-22 15:11:44.265970: Pseudo dice [0.8593] +2024-11-22 15:11:44.266079: Epoch time: 19.56 s +2024-11-22 15:11:45.139956: +2024-11-22 15:11:45.142143: Epoch 5131 +2024-11-22 15:11:45.142276: Current learning rate: 0.00397 +2024-11-22 15:12:04.948503: train_loss -0.8017 +2024-11-22 15:12:04.958800: val_loss -0.7474 +2024-11-22 15:12:04.958951: Pseudo dice [0.8587] +2024-11-22 15:12:04.959076: Epoch time: 19.81 s +2024-11-22 15:12:05.824458: +2024-11-22 15:12:05.825569: Epoch 5132 +2024-11-22 15:12:05.825711: Current learning rate: 0.00397 +2024-11-22 15:12:25.149836: train_loss -0.7935 +2024-11-22 15:12:25.174068: val_loss -0.7786 +2024-11-22 15:12:25.174263: Pseudo dice [0.8537] +2024-11-22 15:12:25.174384: Epoch time: 19.33 s +2024-11-22 15:12:26.141996: +2024-11-22 15:12:26.142960: Epoch 5133 +2024-11-22 15:12:26.143091: Current learning rate: 0.00397 +2024-11-22 15:12:44.742072: train_loss -0.7912 +2024-11-22 15:12:44.754725: val_loss -0.7744 +2024-11-22 15:12:44.754880: Pseudo dice [0.8528] +2024-11-22 15:12:44.754977: Epoch time: 18.6 s +2024-11-22 15:12:45.641332: +2024-11-22 15:12:45.642691: Epoch 5134 +2024-11-22 15:12:45.642814: Current learning rate: 0.00397 +2024-11-22 15:13:05.458056: train_loss -0.7944 +2024-11-22 15:13:05.465638: val_loss -0.7631 +2024-11-22 15:13:05.465773: Pseudo dice [0.8393] +2024-11-22 15:13:05.465856: Epoch time: 19.82 s +2024-11-22 15:13:06.412584: +2024-11-22 15:13:06.413399: Epoch 5135 +2024-11-22 15:13:06.413523: Current learning rate: 0.00397 +2024-11-22 15:13:25.674143: train_loss -0.7936 +2024-11-22 15:13:25.689442: val_loss -0.7685 +2024-11-22 15:13:25.689578: Pseudo dice [0.8552] +2024-11-22 15:13:25.689686: Epoch time: 19.26 s +2024-11-22 15:13:26.713973: +2024-11-22 15:13:26.716089: Epoch 5136 +2024-11-22 15:13:26.716309: Current learning rate: 0.00397 +2024-11-22 15:13:44.970708: train_loss -0.7948 +2024-11-22 15:13:44.975268: val_loss -0.7829 +2024-11-22 15:13:44.975397: Pseudo dice [0.8668] +2024-11-22 15:13:44.975505: Epoch time: 18.26 s +2024-11-22 15:13:46.364269: +2024-11-22 15:13:46.365664: Epoch 5137 +2024-11-22 15:13:46.365789: Current learning rate: 0.00397 +2024-11-22 15:14:06.004431: train_loss -0.7942 +2024-11-22 15:14:06.010795: val_loss -0.7989 +2024-11-22 15:14:06.010928: Pseudo dice [0.8565] +2024-11-22 15:14:06.011030: Epoch time: 19.64 s +2024-11-22 15:14:07.057032: +2024-11-22 15:14:07.059455: Epoch 5138 +2024-11-22 15:14:07.059588: Current learning rate: 0.00396 +2024-11-22 15:14:26.152367: train_loss -0.7973 +2024-11-22 15:14:26.158378: val_loss -0.7744 +2024-11-22 15:14:26.158525: Pseudo dice [0.8617] +2024-11-22 15:14:26.158653: Epoch time: 19.1 s +2024-11-22 15:14:27.042488: +2024-11-22 15:14:27.043735: Epoch 5139 +2024-11-22 15:14:27.043883: Current learning rate: 0.00396 +2024-11-22 15:14:46.169978: train_loss -0.7971 +2024-11-22 15:14:46.175030: val_loss -0.7754 +2024-11-22 15:14:46.175163: Pseudo dice [0.848] +2024-11-22 15:14:46.175291: Epoch time: 19.13 s +2024-11-22 15:14:47.091536: +2024-11-22 15:14:47.092858: Epoch 5140 +2024-11-22 15:14:47.092983: Current learning rate: 0.00396 +2024-11-22 15:15:07.000164: train_loss -0.8027 +2024-11-22 15:15:07.008754: val_loss -0.7592 +2024-11-22 15:15:07.009005: Pseudo dice [0.8502] +2024-11-22 15:15:07.009133: Epoch time: 19.91 s +2024-11-22 15:15:08.039991: +2024-11-22 15:15:08.053484: Epoch 5141 +2024-11-22 15:15:08.053621: Current learning rate: 0.00396 +2024-11-22 15:15:27.359508: train_loss -0.7905 +2024-11-22 15:15:27.368934: val_loss -0.7577 +2024-11-22 15:15:27.369086: Pseudo dice [0.8508] +2024-11-22 15:15:27.369170: Epoch time: 19.32 s +2024-11-22 15:15:28.281991: +2024-11-22 15:15:28.282923: Epoch 5142 +2024-11-22 15:15:28.283073: Current learning rate: 0.00396 +2024-11-22 15:15:49.403720: train_loss -0.7896 +2024-11-22 15:15:49.411149: val_loss -0.7728 +2024-11-22 15:15:49.411289: Pseudo dice [0.8641] +2024-11-22 15:15:49.411443: Epoch time: 21.12 s +2024-11-22 15:15:50.438106: +2024-11-22 15:15:50.438551: Epoch 5143 +2024-11-22 15:15:50.438680: Current learning rate: 0.00396 +2024-11-22 15:16:10.514238: train_loss -0.7895 +2024-11-22 15:16:10.517216: val_loss -0.7864 +2024-11-22 15:16:10.517368: Pseudo dice [0.8678] +2024-11-22 15:16:10.517471: Epoch time: 20.08 s +2024-11-22 15:16:11.455382: +2024-11-22 15:16:11.456563: Epoch 5144 +2024-11-22 15:16:11.456686: Current learning rate: 0.00396 +2024-11-22 15:16:31.355663: train_loss -0.7963 +2024-11-22 15:16:31.363517: val_loss -0.7636 +2024-11-22 15:16:31.363636: Pseudo dice [0.8418] +2024-11-22 15:16:31.363734: Epoch time: 19.9 s +2024-11-22 15:16:32.271436: +2024-11-22 15:16:32.272946: Epoch 5145 +2024-11-22 15:16:32.273088: Current learning rate: 0.00396 +2024-11-22 15:16:53.232592: train_loss -0.7994 +2024-11-22 15:16:53.255689: val_loss -0.7728 +2024-11-22 15:16:53.255865: Pseudo dice [0.8534] +2024-11-22 15:16:53.255959: Epoch time: 20.96 s +2024-11-22 15:16:54.174008: +2024-11-22 15:16:54.175526: Epoch 5146 +2024-11-22 15:16:54.175658: Current learning rate: 0.00395 +2024-11-22 15:17:13.894282: train_loss -0.8003 +2024-11-22 15:17:13.897359: val_loss -0.7651 +2024-11-22 15:17:13.897499: Pseudo dice [0.8737] +2024-11-22 15:17:13.897602: Epoch time: 19.72 s +2024-11-22 15:17:14.798197: +2024-11-22 15:17:14.798413: Epoch 5147 +2024-11-22 15:17:14.798540: Current learning rate: 0.00395 +2024-11-22 15:17:33.859873: train_loss -0.7973 +2024-11-22 15:17:33.885384: val_loss -0.7654 +2024-11-22 15:17:33.885533: Pseudo dice [0.87] +2024-11-22 15:17:33.885629: Epoch time: 19.06 s +2024-11-22 15:17:34.753298: +2024-11-22 15:17:34.753795: Epoch 5148 +2024-11-22 15:17:34.753917: Current learning rate: 0.00395 +2024-11-22 15:17:54.444004: train_loss -0.7954 +2024-11-22 15:17:54.450110: val_loss -0.7748 +2024-11-22 15:17:54.450240: Pseudo dice [0.8586] +2024-11-22 15:17:54.450333: Epoch time: 19.69 s +2024-11-22 15:17:55.725055: +2024-11-22 15:17:55.726118: Epoch 5149 +2024-11-22 15:17:55.726247: Current learning rate: 0.00395 +2024-11-22 15:18:15.069772: train_loss -0.7979 +2024-11-22 15:18:15.076746: val_loss -0.7727 +2024-11-22 15:18:15.098861: Pseudo dice [0.8548] +2024-11-22 15:18:15.099041: Epoch time: 19.35 s +2024-11-22 15:18:16.366767: +2024-11-22 15:18:16.368108: Epoch 5150 +2024-11-22 15:18:16.368240: Current learning rate: 0.00395 +2024-11-22 15:18:35.302431: train_loss -0.7961 +2024-11-22 15:18:35.314182: val_loss -0.7715 +2024-11-22 15:18:35.314342: Pseudo dice [0.8441] +2024-11-22 15:18:35.314433: Epoch time: 18.94 s +2024-11-22 15:18:36.253225: +2024-11-22 15:18:36.254740: Epoch 5151 +2024-11-22 15:18:36.254868: Current learning rate: 0.00395 +2024-11-22 15:18:55.802950: train_loss -0.8032 +2024-11-22 15:18:55.810184: val_loss -0.7905 +2024-11-22 15:18:55.810297: Pseudo dice [0.8612] +2024-11-22 15:18:55.810401: Epoch time: 19.55 s +2024-11-22 15:18:56.798296: +2024-11-22 15:18:56.798516: Epoch 5152 +2024-11-22 15:18:56.798644: Current learning rate: 0.00395 +2024-11-22 15:19:14.662705: train_loss -0.7988 +2024-11-22 15:19:14.665736: val_loss -0.7756 +2024-11-22 15:19:14.665862: Pseudo dice [0.8541] +2024-11-22 15:19:14.665964: Epoch time: 17.87 s +2024-11-22 15:19:15.546537: +2024-11-22 15:19:15.546736: Epoch 5153 +2024-11-22 15:19:15.546853: Current learning rate: 0.00395 +2024-11-22 15:19:33.769793: train_loss -0.8033 +2024-11-22 15:19:33.774494: val_loss -0.7576 +2024-11-22 15:19:33.774631: Pseudo dice [0.86] +2024-11-22 15:19:33.774720: Epoch time: 18.22 s +2024-11-22 15:19:34.881987: +2024-11-22 15:19:34.882205: Epoch 5154 +2024-11-22 15:19:34.882339: Current learning rate: 0.00394 +2024-11-22 15:19:53.352517: train_loss -0.7994 +2024-11-22 15:19:53.359521: val_loss -0.7816 +2024-11-22 15:19:53.359671: Pseudo dice [0.8471] +2024-11-22 15:19:53.359781: Epoch time: 18.47 s +2024-11-22 15:19:54.374686: +2024-11-22 15:19:54.374913: Epoch 5155 +2024-11-22 15:19:54.375044: Current learning rate: 0.00394 +2024-11-22 15:20:12.931602: train_loss -0.7992 +2024-11-22 15:20:12.934041: val_loss -0.7654 +2024-11-22 15:20:12.934180: Pseudo dice [0.8564] +2024-11-22 15:20:12.934278: Epoch time: 18.56 s +2024-11-22 15:20:13.860387: +2024-11-22 15:20:13.860617: Epoch 5156 +2024-11-22 15:20:13.860746: Current learning rate: 0.00394 +2024-11-22 15:20:33.918934: train_loss -0.7999 +2024-11-22 15:20:33.919505: val_loss -0.7834 +2024-11-22 15:20:33.919596: Pseudo dice [0.8398] +2024-11-22 15:20:33.919685: Epoch time: 20.06 s +2024-11-22 15:20:34.785940: +2024-11-22 15:20:34.786132: Epoch 5157 +2024-11-22 15:20:34.786251: Current learning rate: 0.00394 +2024-11-22 15:20:54.778843: train_loss -0.7932 +2024-11-22 15:20:54.779298: val_loss -0.7598 +2024-11-22 15:20:54.779392: Pseudo dice [0.8303] +2024-11-22 15:20:54.779473: Epoch time: 19.99 s +2024-11-22 15:20:55.637077: +2024-11-22 15:20:55.637284: Epoch 5158 +2024-11-22 15:20:55.637401: Current learning rate: 0.00394 +2024-11-22 15:21:14.824069: train_loss -0.78 +2024-11-22 15:21:14.828424: val_loss -0.7557 +2024-11-22 15:21:14.828564: Pseudo dice [0.8477] +2024-11-22 15:21:14.828660: Epoch time: 19.19 s +2024-11-22 15:21:15.698078: +2024-11-22 15:21:15.698302: Epoch 5159 +2024-11-22 15:21:15.698432: Current learning rate: 0.00394 +2024-11-22 15:21:33.907717: train_loss -0.7955 +2024-11-22 15:21:33.909006: val_loss -0.7806 +2024-11-22 15:21:33.909135: Pseudo dice [0.8695] +2024-11-22 15:21:33.909234: Epoch time: 18.21 s +2024-11-22 15:21:34.909802: +2024-11-22 15:21:34.910010: Epoch 5160 +2024-11-22 15:21:34.910146: Current learning rate: 0.00394 +2024-11-22 15:21:53.517614: train_loss -0.7951 +2024-11-22 15:21:53.523259: val_loss -0.7831 +2024-11-22 15:21:53.523468: Pseudo dice [0.8567] +2024-11-22 15:21:53.523560: Epoch time: 18.61 s +2024-11-22 15:21:54.620388: +2024-11-22 15:21:54.622036: Epoch 5161 +2024-11-22 15:21:54.622175: Current learning rate: 0.00394 +2024-11-22 15:22:14.196629: train_loss -0.7855 +2024-11-22 15:22:14.204660: val_loss -0.7762 +2024-11-22 15:22:14.204782: Pseudo dice [0.8544] +2024-11-22 15:22:14.204894: Epoch time: 19.58 s +2024-11-22 15:22:15.320036: +2024-11-22 15:22:15.321297: Epoch 5162 +2024-11-22 15:22:15.321451: Current learning rate: 0.00393 +2024-11-22 15:22:35.245196: train_loss -0.7975 +2024-11-22 15:22:35.251858: val_loss -0.7809 +2024-11-22 15:22:35.251997: Pseudo dice [0.8522] +2024-11-22 15:22:35.252117: Epoch time: 19.93 s +2024-11-22 15:22:36.144314: +2024-11-22 15:22:36.145475: Epoch 5163 +2024-11-22 15:22:36.145616: Current learning rate: 0.00393 +2024-11-22 15:22:57.410081: train_loss -0.7917 +2024-11-22 15:22:57.418626: val_loss -0.7706 +2024-11-22 15:22:57.418778: Pseudo dice [0.8609] +2024-11-22 15:22:57.418897: Epoch time: 21.27 s +2024-11-22 15:22:58.441100: +2024-11-22 15:22:58.443885: Epoch 5164 +2024-11-22 15:22:58.444029: Current learning rate: 0.00393 +2024-11-22 15:23:18.777021: train_loss -0.7939 +2024-11-22 15:23:18.782272: val_loss -0.7855 +2024-11-22 15:23:18.782499: Pseudo dice [0.8583] +2024-11-22 15:23:18.782604: Epoch time: 20.34 s +2024-11-22 15:23:19.781695: +2024-11-22 15:23:19.782503: Epoch 5165 +2024-11-22 15:23:19.782646: Current learning rate: 0.00393 +2024-11-22 15:23:39.310711: train_loss -0.7779 +2024-11-22 15:23:39.315874: val_loss -0.7856 +2024-11-22 15:23:39.316019: Pseudo dice [0.8502] +2024-11-22 15:23:39.316117: Epoch time: 19.53 s +2024-11-22 15:23:40.222636: +2024-11-22 15:23:40.223516: Epoch 5166 +2024-11-22 15:23:40.223652: Current learning rate: 0.00393 +2024-11-22 15:23:59.181365: train_loss -0.79 +2024-11-22 15:23:59.198514: val_loss -0.7727 +2024-11-22 15:23:59.198663: Pseudo dice [0.8579] +2024-11-22 15:23:59.198780: Epoch time: 18.96 s +2024-11-22 15:24:00.144100: +2024-11-22 15:24:00.144975: Epoch 5167 +2024-11-22 15:24:00.145103: Current learning rate: 0.00393 +2024-11-22 15:24:19.681412: train_loss -0.7853 +2024-11-22 15:24:19.688305: val_loss -0.756 +2024-11-22 15:24:19.688526: Pseudo dice [0.8391] +2024-11-22 15:24:19.688633: Epoch time: 19.54 s +2024-11-22 15:24:20.729106: +2024-11-22 15:24:20.730472: Epoch 5168 +2024-11-22 15:24:20.730603: Current learning rate: 0.00393 +2024-11-22 15:24:40.196196: train_loss -0.7926 +2024-11-22 15:24:40.199145: val_loss -0.7633 +2024-11-22 15:24:40.199261: Pseudo dice [0.8378] +2024-11-22 15:24:40.199352: Epoch time: 19.47 s +2024-11-22 15:24:41.129765: +2024-11-22 15:24:41.130970: Epoch 5169 +2024-11-22 15:24:41.131101: Current learning rate: 0.00393 +2024-11-22 15:24:59.536760: train_loss -0.7916 +2024-11-22 15:24:59.545123: val_loss -0.7803 +2024-11-22 15:24:59.545261: Pseudo dice [0.8475] +2024-11-22 15:24:59.545363: Epoch time: 18.41 s +2024-11-22 15:25:00.608975: +2024-11-22 15:25:00.610066: Epoch 5170 +2024-11-22 15:25:00.610197: Current learning rate: 0.00392 +2024-11-22 15:25:20.659445: train_loss -0.7866 +2024-11-22 15:25:20.667562: val_loss -0.7674 +2024-11-22 15:25:20.667833: Pseudo dice [0.8528] +2024-11-22 15:25:20.667971: Epoch time: 20.05 s +2024-11-22 15:25:21.693829: +2024-11-22 15:25:21.695817: Epoch 5171 +2024-11-22 15:25:21.695943: Current learning rate: 0.00392 +2024-11-22 15:25:41.651697: train_loss -0.792 +2024-11-22 15:25:41.654768: val_loss -0.7526 +2024-11-22 15:25:41.654891: Pseudo dice [0.8387] +2024-11-22 15:25:41.654974: Epoch time: 19.96 s +2024-11-22 15:25:43.018181: +2024-11-22 15:25:43.020553: Epoch 5172 +2024-11-22 15:25:43.020678: Current learning rate: 0.00392 +2024-11-22 15:26:02.341431: train_loss -0.7887 +2024-11-22 15:26:02.351133: val_loss -0.7611 +2024-11-22 15:26:02.351257: Pseudo dice [0.8465] +2024-11-22 15:26:02.351375: Epoch time: 19.32 s +2024-11-22 15:26:03.338530: +2024-11-22 15:26:03.340456: Epoch 5173 +2024-11-22 15:26:03.340604: Current learning rate: 0.00392 +2024-11-22 15:26:22.528135: train_loss -0.7812 +2024-11-22 15:26:22.530403: val_loss -0.7565 +2024-11-22 15:26:22.530642: Pseudo dice [0.8442] +2024-11-22 15:26:22.530800: Epoch time: 19.19 s +2024-11-22 15:26:23.409986: +2024-11-22 15:26:23.410733: Epoch 5174 +2024-11-22 15:26:23.410858: Current learning rate: 0.00392 +2024-11-22 15:26:42.232195: train_loss -0.7878 +2024-11-22 15:26:42.234723: val_loss -0.7607 +2024-11-22 15:26:42.234844: Pseudo dice [0.8571] +2024-11-22 15:26:42.234959: Epoch time: 18.82 s +2024-11-22 15:26:43.118128: +2024-11-22 15:26:43.119422: Epoch 5175 +2024-11-22 15:26:43.119537: Current learning rate: 0.00392 +2024-11-22 15:27:03.470010: train_loss -0.792 +2024-11-22 15:27:03.477772: val_loss -0.7622 +2024-11-22 15:27:03.477897: Pseudo dice [0.8544] +2024-11-22 15:27:03.478001: Epoch time: 20.35 s +2024-11-22 15:27:04.441963: +2024-11-22 15:27:04.442886: Epoch 5176 +2024-11-22 15:27:04.443005: Current learning rate: 0.00392 +2024-11-22 15:27:24.167802: train_loss -0.7908 +2024-11-22 15:27:24.175056: val_loss -0.7787 +2024-11-22 15:27:24.175214: Pseudo dice [0.8485] +2024-11-22 15:27:24.175347: Epoch time: 19.73 s +2024-11-22 15:27:25.035686: +2024-11-22 15:27:25.037379: Epoch 5177 +2024-11-22 15:27:25.037503: Current learning rate: 0.00392 +2024-11-22 15:27:44.383524: train_loss -0.7817 +2024-11-22 15:27:44.391886: val_loss -0.7793 +2024-11-22 15:27:44.392033: Pseudo dice [0.8434] +2024-11-22 15:27:44.392132: Epoch time: 19.35 s +2024-11-22 15:27:45.349153: +2024-11-22 15:27:45.350734: Epoch 5178 +2024-11-22 15:27:45.350861: Current learning rate: 0.00391 +2024-11-22 15:28:05.921725: train_loss -0.7909 +2024-11-22 15:28:05.928928: val_loss -0.7459 +2024-11-22 15:28:05.929072: Pseudo dice [0.8441] +2024-11-22 15:28:05.929158: Epoch time: 20.57 s +2024-11-22 15:28:06.844634: +2024-11-22 15:28:06.845084: Epoch 5179 +2024-11-22 15:28:06.845208: Current learning rate: 0.00391 +2024-11-22 15:28:27.167055: train_loss -0.795 +2024-11-22 15:28:27.173401: val_loss -0.7844 +2024-11-22 15:28:27.173552: Pseudo dice [0.8579] +2024-11-22 15:28:27.173726: Epoch time: 20.32 s +2024-11-22 15:28:28.098352: +2024-11-22 15:28:28.099271: Epoch 5180 +2024-11-22 15:28:28.099420: Current learning rate: 0.00391 +2024-11-22 15:28:47.727944: train_loss -0.7846 +2024-11-22 15:28:47.730714: val_loss -0.7593 +2024-11-22 15:28:47.730849: Pseudo dice [0.8584] +2024-11-22 15:28:47.730953: Epoch time: 19.63 s +2024-11-22 15:28:48.715964: +2024-11-22 15:28:48.716492: Epoch 5181 +2024-11-22 15:28:48.716618: Current learning rate: 0.00391 +2024-11-22 15:29:08.474305: train_loss -0.7951 +2024-11-22 15:29:08.488763: val_loss -0.7648 +2024-11-22 15:29:08.488930: Pseudo dice [0.8562] +2024-11-22 15:29:08.489043: Epoch time: 19.76 s +2024-11-22 15:29:09.361909: +2024-11-22 15:29:09.363769: Epoch 5182 +2024-11-22 15:29:09.363907: Current learning rate: 0.00391 +2024-11-22 15:29:29.284364: train_loss -0.7876 +2024-11-22 15:29:29.290949: val_loss -0.7619 +2024-11-22 15:29:29.291081: Pseudo dice [0.8565] +2024-11-22 15:29:29.291177: Epoch time: 19.92 s +2024-11-22 15:29:30.358343: +2024-11-22 15:29:30.359641: Epoch 5183 +2024-11-22 15:29:30.359785: Current learning rate: 0.00391 +2024-11-22 15:29:51.336623: train_loss -0.7942 +2024-11-22 15:29:51.348764: val_loss -0.7791 +2024-11-22 15:29:51.348928: Pseudo dice [0.8644] +2024-11-22 15:29:51.349024: Epoch time: 20.98 s +2024-11-22 15:29:52.733654: +2024-11-22 15:29:52.734809: Epoch 5184 +2024-11-22 15:29:52.734950: Current learning rate: 0.00391 +2024-11-22 15:30:12.056649: train_loss -0.8032 +2024-11-22 15:30:12.060432: val_loss -0.7905 +2024-11-22 15:30:12.060571: Pseudo dice [0.8606] +2024-11-22 15:30:12.060662: Epoch time: 19.32 s +2024-11-22 15:30:13.021515: +2024-11-22 15:30:13.022340: Epoch 5185 +2024-11-22 15:30:13.022462: Current learning rate: 0.00391 +2024-11-22 15:30:32.863032: train_loss -0.7956 +2024-11-22 15:30:32.881419: val_loss -0.7683 +2024-11-22 15:30:32.881578: Pseudo dice [0.8605] +2024-11-22 15:30:32.881683: Epoch time: 19.84 s +2024-11-22 15:30:33.968652: +2024-11-22 15:30:33.970955: Epoch 5186 +2024-11-22 15:30:33.971090: Current learning rate: 0.0039 +2024-11-22 15:30:52.735249: train_loss -0.797 +2024-11-22 15:30:52.742150: val_loss -0.7675 +2024-11-22 15:30:52.742274: Pseudo dice [0.8565] +2024-11-22 15:30:52.742366: Epoch time: 18.77 s +2024-11-22 15:30:53.800171: +2024-11-22 15:30:53.802886: Epoch 5187 +2024-11-22 15:30:53.803019: Current learning rate: 0.0039 +2024-11-22 15:31:13.845076: train_loss -0.7867 +2024-11-22 15:31:13.848048: val_loss -0.7683 +2024-11-22 15:31:13.848199: Pseudo dice [0.8539] +2024-11-22 15:31:13.848520: Epoch time: 20.05 s +2024-11-22 15:31:14.923328: +2024-11-22 15:31:14.925046: Epoch 5188 +2024-11-22 15:31:14.925173: Current learning rate: 0.0039 +2024-11-22 15:31:33.490907: train_loss -0.8002 +2024-11-22 15:31:33.498093: val_loss -0.7714 +2024-11-22 15:31:33.498232: Pseudo dice [0.8492] +2024-11-22 15:31:33.498331: Epoch time: 18.57 s +2024-11-22 15:31:34.528381: +2024-11-22 15:31:34.530189: Epoch 5189 +2024-11-22 15:31:34.530570: Current learning rate: 0.0039 +2024-11-22 15:31:54.110099: train_loss -0.7945 +2024-11-22 15:31:54.119103: val_loss -0.7842 +2024-11-22 15:31:54.119262: Pseudo dice [0.8487] +2024-11-22 15:31:54.119405: Epoch time: 19.58 s +2024-11-22 15:31:55.223937: +2024-11-22 15:31:55.226048: Epoch 5190 +2024-11-22 15:31:55.226208: Current learning rate: 0.0039 +2024-11-22 15:32:15.523561: train_loss -0.7942 +2024-11-22 15:32:15.542221: val_loss -0.7806 +2024-11-22 15:32:15.542361: Pseudo dice [0.852] +2024-11-22 15:32:15.542454: Epoch time: 20.3 s +2024-11-22 15:32:16.414715: +2024-11-22 15:32:16.415165: Epoch 5191 +2024-11-22 15:32:16.415285: Current learning rate: 0.0039 +2024-11-22 15:32:35.765363: train_loss -0.795 +2024-11-22 15:32:35.771254: val_loss -0.7748 +2024-11-22 15:32:35.771403: Pseudo dice [0.8537] +2024-11-22 15:32:35.771510: Epoch time: 19.35 s +2024-11-22 15:32:36.652493: +2024-11-22 15:32:36.654982: Epoch 5192 +2024-11-22 15:32:36.655119: Current learning rate: 0.0039 +2024-11-22 15:32:56.557684: train_loss -0.7675 +2024-11-22 15:32:56.574518: val_loss -0.7638 +2024-11-22 15:32:56.574656: Pseudo dice [0.8626] +2024-11-22 15:32:56.574771: Epoch time: 19.91 s +2024-11-22 15:32:57.600946: +2024-11-22 15:32:57.601389: Epoch 5193 +2024-11-22 15:32:57.601532: Current learning rate: 0.0039 +2024-11-22 15:33:16.459294: train_loss -0.7862 +2024-11-22 15:33:16.468535: val_loss -0.7709 +2024-11-22 15:33:16.468678: Pseudo dice [0.8424] +2024-11-22 15:33:16.468779: Epoch time: 18.86 s +2024-11-22 15:33:17.496876: +2024-11-22 15:33:17.498473: Epoch 5194 +2024-11-22 15:33:17.498614: Current learning rate: 0.00389 +2024-11-22 15:33:35.973926: train_loss -0.7856 +2024-11-22 15:33:35.978811: val_loss -0.7903 +2024-11-22 15:33:35.978966: Pseudo dice [0.8549] +2024-11-22 15:33:35.979069: Epoch time: 18.48 s +2024-11-22 15:33:36.845461: +2024-11-22 15:33:36.847166: Epoch 5195 +2024-11-22 15:33:36.847305: Current learning rate: 0.00389 +2024-11-22 15:33:57.680135: train_loss -0.7869 +2024-11-22 15:33:57.689008: val_loss -0.7912 +2024-11-22 15:33:57.689137: Pseudo dice [0.8593] +2024-11-22 15:33:57.689232: Epoch time: 20.84 s +2024-11-22 15:33:59.234474: +2024-11-22 15:33:59.235715: Epoch 5196 +2024-11-22 15:33:59.235844: Current learning rate: 0.00389 +2024-11-22 15:34:19.566984: train_loss -0.7782 +2024-11-22 15:34:19.573693: val_loss -0.7822 +2024-11-22 15:34:19.573834: Pseudo dice [0.8505] +2024-11-22 15:34:19.573937: Epoch time: 20.33 s +2024-11-22 15:34:20.720727: +2024-11-22 15:34:20.722419: Epoch 5197 +2024-11-22 15:34:20.722543: Current learning rate: 0.00389 +2024-11-22 15:34:40.359690: train_loss -0.7785 +2024-11-22 15:34:40.372011: val_loss -0.7082 +2024-11-22 15:34:40.372171: Pseudo dice [0.8185] +2024-11-22 15:34:40.372267: Epoch time: 19.64 s +2024-11-22 15:34:41.483403: +2024-11-22 15:34:41.484303: Epoch 5198 +2024-11-22 15:34:41.484434: Current learning rate: 0.00389 +2024-11-22 15:35:01.725618: train_loss -0.7575 +2024-11-22 15:35:01.732376: val_loss -0.7673 +2024-11-22 15:35:01.732523: Pseudo dice [0.8443] +2024-11-22 15:35:01.732627: Epoch time: 20.24 s +2024-11-22 15:35:02.668141: +2024-11-22 15:35:02.669296: Epoch 5199 +2024-11-22 15:35:02.669430: Current learning rate: 0.00389 +2024-11-22 15:35:21.342186: train_loss -0.7695 +2024-11-22 15:35:21.344634: val_loss -0.7781 +2024-11-22 15:35:21.344747: Pseudo dice [0.8569] +2024-11-22 15:35:21.344853: Epoch time: 18.67 s +2024-11-22 15:35:22.685338: +2024-11-22 15:35:22.687385: Epoch 5200 +2024-11-22 15:35:22.687516: Current learning rate: 0.00389 +2024-11-22 15:35:41.341936: train_loss -0.7791 +2024-11-22 15:35:41.349438: val_loss -0.771 +2024-11-22 15:35:41.349593: Pseudo dice [0.8554] +2024-11-22 15:35:41.349698: Epoch time: 18.66 s +2024-11-22 15:35:42.291904: +2024-11-22 15:35:42.294055: Epoch 5201 +2024-11-22 15:35:42.294214: Current learning rate: 0.00389 +2024-11-22 15:36:01.416476: train_loss -0.7886 +2024-11-22 15:36:01.432062: val_loss -0.7597 +2024-11-22 15:36:01.432218: Pseudo dice [0.8508] +2024-11-22 15:36:01.432324: Epoch time: 19.13 s +2024-11-22 15:36:02.503643: +2024-11-22 15:36:02.505074: Epoch 5202 +2024-11-22 15:36:02.505198: Current learning rate: 0.00388 +2024-11-22 15:36:22.171151: train_loss -0.7901 +2024-11-22 15:36:22.181928: val_loss -0.7899 +2024-11-22 15:36:22.182090: Pseudo dice [0.8556] +2024-11-22 15:36:22.182289: Epoch time: 19.67 s +2024-11-22 15:36:23.102513: +2024-11-22 15:36:23.102934: Epoch 5203 +2024-11-22 15:36:23.103062: Current learning rate: 0.00388 +2024-11-22 15:36:43.126794: train_loss -0.7907 +2024-11-22 15:36:43.134183: val_loss -0.765 +2024-11-22 15:36:43.134327: Pseudo dice [0.8562] +2024-11-22 15:36:43.134448: Epoch time: 20.03 s +2024-11-22 15:36:44.149605: +2024-11-22 15:36:44.150958: Epoch 5204 +2024-11-22 15:36:44.151094: Current learning rate: 0.00388 +2024-11-22 15:37:03.526608: train_loss -0.7874 +2024-11-22 15:37:03.535601: val_loss -0.7841 +2024-11-22 15:37:03.535753: Pseudo dice [0.8651] +2024-11-22 15:37:03.535849: Epoch time: 19.38 s +2024-11-22 15:37:04.482365: +2024-11-22 15:37:04.483730: Epoch 5205 +2024-11-22 15:37:04.483860: Current learning rate: 0.00388 +2024-11-22 15:37:25.790922: train_loss -0.7843 +2024-11-22 15:37:25.794905: val_loss -0.7694 +2024-11-22 15:37:25.795070: Pseudo dice [0.8545] +2024-11-22 15:37:25.795180: Epoch time: 21.31 s +2024-11-22 15:37:26.748808: +2024-11-22 15:37:26.751194: Epoch 5206 +2024-11-22 15:37:26.751324: Current learning rate: 0.00388 +2024-11-22 15:37:45.899387: train_loss -0.7807 +2024-11-22 15:37:45.908484: val_loss -0.752 +2024-11-22 15:37:45.908640: Pseudo dice [0.8359] +2024-11-22 15:37:45.908740: Epoch time: 19.15 s +2024-11-22 15:37:46.795185: +2024-11-22 15:37:46.795937: Epoch 5207 +2024-11-22 15:37:46.796056: Current learning rate: 0.00388 +2024-11-22 15:38:06.420689: train_loss -0.7848 +2024-11-22 15:38:06.427900: val_loss -0.7473 +2024-11-22 15:38:06.428055: Pseudo dice [0.8627] +2024-11-22 15:38:06.428180: Epoch time: 19.63 s +2024-11-22 15:38:07.298858: +2024-11-22 15:38:07.300309: Epoch 5208 +2024-11-22 15:38:07.300429: Current learning rate: 0.00388 +2024-11-22 15:38:26.451605: train_loss -0.7928 +2024-11-22 15:38:26.478459: val_loss -0.7723 +2024-11-22 15:38:26.478628: Pseudo dice [0.8453] +2024-11-22 15:38:26.478720: Epoch time: 19.15 s +2024-11-22 15:38:27.509628: +2024-11-22 15:38:27.511006: Epoch 5209 +2024-11-22 15:38:27.511145: Current learning rate: 0.00388 +2024-11-22 15:38:47.242034: train_loss -0.8001 +2024-11-22 15:38:47.249017: val_loss -0.7638 +2024-11-22 15:38:47.249174: Pseudo dice [0.8496] +2024-11-22 15:38:47.249323: Epoch time: 19.73 s +2024-11-22 15:38:48.137439: +2024-11-22 15:38:48.138610: Epoch 5210 +2024-11-22 15:38:48.138751: Current learning rate: 0.00387 +2024-11-22 15:39:07.797869: train_loss -0.7961 +2024-11-22 15:39:07.810361: val_loss -0.7778 +2024-11-22 15:39:07.810515: Pseudo dice [0.8579] +2024-11-22 15:39:07.810627: Epoch time: 19.66 s +2024-11-22 15:39:08.831602: +2024-11-22 15:39:08.832802: Epoch 5211 +2024-11-22 15:39:08.832935: Current learning rate: 0.00387 +2024-11-22 15:39:28.269310: train_loss -0.7974 +2024-11-22 15:39:28.273460: val_loss -0.769 +2024-11-22 15:39:28.273584: Pseudo dice [0.8438] +2024-11-22 15:39:28.273670: Epoch time: 19.44 s +2024-11-22 15:39:29.320423: +2024-11-22 15:39:29.321188: Epoch 5212 +2024-11-22 15:39:29.321326: Current learning rate: 0.00387 +2024-11-22 15:39:49.505775: train_loss -0.7961 +2024-11-22 15:39:49.512755: val_loss -0.7862 +2024-11-22 15:39:49.512905: Pseudo dice [0.8577] +2024-11-22 15:39:49.513000: Epoch time: 20.19 s +2024-11-22 15:39:50.377596: +2024-11-22 15:39:50.378380: Epoch 5213 +2024-11-22 15:39:50.378705: Current learning rate: 0.00387 +2024-11-22 15:40:09.923265: train_loss -0.8023 +2024-11-22 15:40:09.931084: val_loss -0.7629 +2024-11-22 15:40:09.931237: Pseudo dice [0.8539] +2024-11-22 15:40:09.931326: Epoch time: 19.55 s +2024-11-22 15:40:10.884802: +2024-11-22 15:40:10.885534: Epoch 5214 +2024-11-22 15:40:10.885682: Current learning rate: 0.00387 +2024-11-22 15:40:30.520703: train_loss -0.8007 +2024-11-22 15:40:30.526812: val_loss -0.7729 +2024-11-22 15:40:30.533144: Pseudo dice [0.8528] +2024-11-22 15:40:30.533300: Epoch time: 19.64 s +2024-11-22 15:40:31.537351: +2024-11-22 15:40:31.539428: Epoch 5215 +2024-11-22 15:40:31.539649: Current learning rate: 0.00387 +2024-11-22 15:40:50.766433: train_loss -0.7912 +2024-11-22 15:40:50.771074: val_loss -0.7851 +2024-11-22 15:40:50.771205: Pseudo dice [0.8572] +2024-11-22 15:40:50.771299: Epoch time: 19.23 s +2024-11-22 15:40:51.680503: +2024-11-22 15:40:51.681279: Epoch 5216 +2024-11-22 15:40:51.681418: Current learning rate: 0.00387 +2024-11-22 15:41:11.595464: train_loss -0.7986 +2024-11-22 15:41:11.601281: val_loss -0.7427 +2024-11-22 15:41:11.601429: Pseudo dice [0.8592] +2024-11-22 15:41:11.601533: Epoch time: 19.92 s +2024-11-22 15:41:12.507924: +2024-11-22 15:41:12.508733: Epoch 5217 +2024-11-22 15:41:12.508850: Current learning rate: 0.00387 +2024-11-22 15:41:31.278265: train_loss -0.8006 +2024-11-22 15:41:31.283804: val_loss -0.7641 +2024-11-22 15:41:31.283946: Pseudo dice [0.8544] +2024-11-22 15:41:31.284056: Epoch time: 18.77 s +2024-11-22 15:41:32.260695: +2024-11-22 15:41:32.261822: Epoch 5218 +2024-11-22 15:41:32.261974: Current learning rate: 0.00386 +2024-11-22 15:41:52.683736: train_loss -0.7923 +2024-11-22 15:41:52.690373: val_loss -0.7693 +2024-11-22 15:41:52.690514: Pseudo dice [0.8472] +2024-11-22 15:41:52.690619: Epoch time: 20.42 s +2024-11-22 15:41:53.996987: +2024-11-22 15:41:53.998070: Epoch 5219 +2024-11-22 15:41:53.998205: Current learning rate: 0.00386 +2024-11-22 15:42:13.545781: train_loss -0.7984 +2024-11-22 15:42:13.563246: val_loss -0.7706 +2024-11-22 15:42:13.563410: Pseudo dice [0.8513] +2024-11-22 15:42:13.563518: Epoch time: 19.55 s +2024-11-22 15:42:14.422306: +2024-11-22 15:42:14.424638: Epoch 5220 +2024-11-22 15:42:14.424760: Current learning rate: 0.00386 +2024-11-22 15:42:34.173997: train_loss -0.7882 +2024-11-22 15:42:34.179674: val_loss -0.7514 +2024-11-22 15:42:34.179798: Pseudo dice [0.8602] +2024-11-22 15:42:34.179891: Epoch time: 19.75 s +2024-11-22 15:42:35.051241: +2024-11-22 15:42:35.052508: Epoch 5221 +2024-11-22 15:42:35.052632: Current learning rate: 0.00386 +2024-11-22 15:42:54.681691: train_loss -0.7942 +2024-11-22 15:42:54.688283: val_loss -0.7617 +2024-11-22 15:42:54.688430: Pseudo dice [0.8714] +2024-11-22 15:42:54.688563: Epoch time: 19.63 s +2024-11-22 15:42:55.845123: +2024-11-22 15:42:55.845973: Epoch 5222 +2024-11-22 15:42:55.846095: Current learning rate: 0.00386 +2024-11-22 15:43:16.623756: train_loss -0.7863 +2024-11-22 15:43:16.634884: val_loss -0.7917 +2024-11-22 15:43:16.635021: Pseudo dice [0.8569] +2024-11-22 15:43:16.635138: Epoch time: 20.78 s +2024-11-22 15:43:17.531240: +2024-11-22 15:43:17.532008: Epoch 5223 +2024-11-22 15:43:17.532136: Current learning rate: 0.00386 +2024-11-22 15:43:37.180196: train_loss -0.7919 +2024-11-22 15:43:37.184198: val_loss -0.769 +2024-11-22 15:43:37.184357: Pseudo dice [0.8584] +2024-11-22 15:43:37.184515: Epoch time: 19.65 s +2024-11-22 15:43:38.175644: +2024-11-22 15:43:38.177858: Epoch 5224 +2024-11-22 15:43:38.177984: Current learning rate: 0.00386 +2024-11-22 15:43:58.055531: train_loss -0.7936 +2024-11-22 15:43:58.065137: val_loss -0.7859 +2024-11-22 15:43:58.065264: Pseudo dice [0.8521] +2024-11-22 15:43:58.065370: Epoch time: 19.88 s +2024-11-22 15:43:59.160645: +2024-11-22 15:43:59.161116: Epoch 5225 +2024-11-22 15:43:59.161238: Current learning rate: 0.00386 +2024-11-22 15:44:18.413475: train_loss -0.7904 +2024-11-22 15:44:18.424772: val_loss -0.757 +2024-11-22 15:44:18.424914: Pseudo dice [0.8538] +2024-11-22 15:44:18.425328: Epoch time: 19.25 s +2024-11-22 15:44:19.535997: +2024-11-22 15:44:19.536191: Epoch 5226 +2024-11-22 15:44:19.536316: Current learning rate: 0.00385 +2024-11-22 15:44:38.566050: train_loss -0.8055 +2024-11-22 15:44:38.567008: val_loss -0.7847 +2024-11-22 15:44:38.567165: Pseudo dice [0.8554] +2024-11-22 15:44:38.567280: Epoch time: 19.03 s +2024-11-22 15:44:39.422126: +2024-11-22 15:44:39.422365: Epoch 5227 +2024-11-22 15:44:39.422487: Current learning rate: 0.00385 +2024-11-22 15:44:57.916652: train_loss -0.8047 +2024-11-22 15:44:57.921165: val_loss -0.7524 +2024-11-22 15:44:57.921307: Pseudo dice [0.8365] +2024-11-22 15:44:57.921405: Epoch time: 18.5 s +2024-11-22 15:44:58.886041: +2024-11-22 15:44:58.886280: Epoch 5228 +2024-11-22 15:44:58.886391: Current learning rate: 0.00385 +2024-11-22 15:45:17.308957: train_loss -0.7883 +2024-11-22 15:45:17.311597: val_loss -0.7938 +2024-11-22 15:45:17.311729: Pseudo dice [0.8691] +2024-11-22 15:45:17.311837: Epoch time: 18.42 s +2024-11-22 15:45:18.250512: +2024-11-22 15:45:18.250703: Epoch 5229 +2024-11-22 15:45:18.250831: Current learning rate: 0.00385 +2024-11-22 15:45:37.583411: train_loss -0.788 +2024-11-22 15:45:37.583921: val_loss -0.7793 +2024-11-22 15:45:37.584020: Pseudo dice [0.8672] +2024-11-22 15:45:37.584107: Epoch time: 19.33 s +2024-11-22 15:45:38.442617: +2024-11-22 15:45:38.442813: Epoch 5230 +2024-11-22 15:45:38.442930: Current learning rate: 0.00385 +2024-11-22 15:45:57.112825: train_loss -0.7995 +2024-11-22 15:45:57.117046: val_loss -0.7749 +2024-11-22 15:45:57.117200: Pseudo dice [0.8598] +2024-11-22 15:45:57.117308: Epoch time: 18.67 s +2024-11-22 15:45:58.384953: +2024-11-22 15:45:58.385177: Epoch 5231 +2024-11-22 15:45:58.385319: Current learning rate: 0.00385 +2024-11-22 15:46:17.294826: train_loss -0.7932 +2024-11-22 15:46:17.296389: val_loss -0.7791 +2024-11-22 15:46:17.296522: Pseudo dice [0.858] +2024-11-22 15:46:17.296621: Epoch time: 18.91 s +2024-11-22 15:46:18.159344: +2024-11-22 15:46:18.159582: Epoch 5232 +2024-11-22 15:46:18.159701: Current learning rate: 0.00385 +2024-11-22 15:46:36.876725: train_loss -0.7903 +2024-11-22 15:46:36.883191: val_loss -0.781 +2024-11-22 15:46:36.883330: Pseudo dice [0.855] +2024-11-22 15:46:36.883431: Epoch time: 18.72 s +2024-11-22 15:46:37.808658: +2024-11-22 15:46:37.808903: Epoch 5233 +2024-11-22 15:46:37.809025: Current learning rate: 0.00385 +2024-11-22 15:46:57.368016: train_loss -0.7954 +2024-11-22 15:46:57.375016: val_loss -0.7633 +2024-11-22 15:46:57.375186: Pseudo dice [0.8484] +2024-11-22 15:46:57.375279: Epoch time: 19.56 s +2024-11-22 15:46:58.230431: +2024-11-22 15:46:58.230659: Epoch 5234 +2024-11-22 15:46:58.230783: Current learning rate: 0.00384 +2024-11-22 15:47:17.048195: train_loss -0.7916 +2024-11-22 15:47:17.054077: val_loss -0.7741 +2024-11-22 15:47:17.054211: Pseudo dice [0.8463] +2024-11-22 15:47:17.054314: Epoch time: 18.82 s +2024-11-22 15:47:17.926665: +2024-11-22 15:47:17.927107: Epoch 5235 +2024-11-22 15:47:17.927225: Current learning rate: 0.00384 +2024-11-22 15:47:37.238396: train_loss -0.7912 +2024-11-22 15:47:37.245287: val_loss -0.7738 +2024-11-22 15:47:37.245421: Pseudo dice [0.8509] +2024-11-22 15:47:37.245512: Epoch time: 19.31 s +2024-11-22 15:47:38.226611: +2024-11-22 15:47:38.227398: Epoch 5236 +2024-11-22 15:47:38.227545: Current learning rate: 0.00384 +2024-11-22 15:47:57.444806: train_loss -0.7928 +2024-11-22 15:47:57.467422: val_loss -0.7658 +2024-11-22 15:47:57.467587: Pseudo dice [0.8449] +2024-11-22 15:47:57.467689: Epoch time: 19.22 s +2024-11-22 15:47:58.374901: +2024-11-22 15:47:58.375669: Epoch 5237 +2024-11-22 15:47:58.375807: Current learning rate: 0.00384 +2024-11-22 15:48:18.540822: train_loss -0.7973 +2024-11-22 15:48:18.550429: val_loss -0.7795 +2024-11-22 15:48:18.550554: Pseudo dice [0.8461] +2024-11-22 15:48:18.550665: Epoch time: 20.17 s +2024-11-22 15:48:19.412809: +2024-11-22 15:48:19.414115: Epoch 5238 +2024-11-22 15:48:19.414238: Current learning rate: 0.00384 +2024-11-22 15:48:38.791313: train_loss -0.7983 +2024-11-22 15:48:38.819508: val_loss -0.7666 +2024-11-22 15:48:38.819682: Pseudo dice [0.8454] +2024-11-22 15:48:38.819795: Epoch time: 19.38 s +2024-11-22 15:48:39.687258: +2024-11-22 15:48:39.688966: Epoch 5239 +2024-11-22 15:48:39.689105: Current learning rate: 0.00384 +2024-11-22 15:48:59.240077: train_loss -0.796 +2024-11-22 15:48:59.248742: val_loss -0.7606 +2024-11-22 15:48:59.248905: Pseudo dice [0.8527] +2024-11-22 15:48:59.249002: Epoch time: 19.55 s +2024-11-22 15:49:00.232508: +2024-11-22 15:49:00.233611: Epoch 5240 +2024-11-22 15:49:00.233745: Current learning rate: 0.00384 +2024-11-22 15:49:20.496803: train_loss -0.7959 +2024-11-22 15:49:20.503241: val_loss -0.7711 +2024-11-22 15:49:20.503423: Pseudo dice [0.8502] +2024-11-22 15:49:20.503587: Epoch time: 20.27 s +2024-11-22 15:49:21.389674: +2024-11-22 15:49:21.395854: Epoch 5241 +2024-11-22 15:49:21.396014: Current learning rate: 0.00384 +2024-11-22 15:49:39.948767: train_loss -0.7923 +2024-11-22 15:49:39.955179: val_loss -0.7696 +2024-11-22 15:49:39.955327: Pseudo dice [0.8537] +2024-11-22 15:49:39.955437: Epoch time: 18.56 s +2024-11-22 15:49:41.090310: +2024-11-22 15:49:41.091578: Epoch 5242 +2024-11-22 15:49:41.091732: Current learning rate: 0.00383 +2024-11-22 15:50:01.411812: train_loss -0.7928 +2024-11-22 15:50:01.415467: val_loss -0.7626 +2024-11-22 15:50:01.415610: Pseudo dice [0.8435] +2024-11-22 15:50:01.415721: Epoch time: 20.32 s +2024-11-22 15:50:02.691334: +2024-11-22 15:50:02.693241: Epoch 5243 +2024-11-22 15:50:02.693376: Current learning rate: 0.00383 +2024-11-22 15:50:22.306057: train_loss -0.7998 +2024-11-22 15:50:22.312998: val_loss -0.7822 +2024-11-22 15:50:22.320267: Pseudo dice [0.8727] +2024-11-22 15:50:22.320444: Epoch time: 19.62 s +2024-11-22 15:50:23.373655: +2024-11-22 15:50:23.374889: Epoch 5244 +2024-11-22 15:50:23.375005: Current learning rate: 0.00383 +2024-11-22 15:50:43.313857: train_loss -0.7857 +2024-11-22 15:50:43.316586: val_loss -0.7563 +2024-11-22 15:50:43.316715: Pseudo dice [0.8357] +2024-11-22 15:50:43.316823: Epoch time: 19.94 s +2024-11-22 15:50:44.169883: +2024-11-22 15:50:44.171283: Epoch 5245 +2024-11-22 15:50:44.171409: Current learning rate: 0.00383 +2024-11-22 15:51:03.820561: train_loss -0.7822 +2024-11-22 15:51:03.829116: val_loss -0.7695 +2024-11-22 15:51:03.829305: Pseudo dice [0.8665] +2024-11-22 15:51:03.829413: Epoch time: 19.65 s +2024-11-22 15:51:04.806972: +2024-11-22 15:51:04.808702: Epoch 5246 +2024-11-22 15:51:04.808837: Current learning rate: 0.00383 +2024-11-22 15:51:24.299940: train_loss -0.765 +2024-11-22 15:51:24.302448: val_loss -0.7631 +2024-11-22 15:51:24.302576: Pseudo dice [0.8517] +2024-11-22 15:51:24.302669: Epoch time: 19.49 s +2024-11-22 15:51:25.207336: +2024-11-22 15:51:25.208131: Epoch 5247 +2024-11-22 15:51:25.208249: Current learning rate: 0.00383 +2024-11-22 15:51:44.993685: train_loss -0.7883 +2024-11-22 15:51:45.002472: val_loss -0.7964 +2024-11-22 15:51:45.002601: Pseudo dice [0.8568] +2024-11-22 15:51:45.002710: Epoch time: 19.79 s +2024-11-22 15:51:46.080432: +2024-11-22 15:51:46.081872: Epoch 5248 +2024-11-22 15:51:46.082011: Current learning rate: 0.00383 +2024-11-22 15:52:05.876440: train_loss -0.7869 +2024-11-22 15:52:05.888736: val_loss -0.7852 +2024-11-22 15:52:05.888880: Pseudo dice [0.8643] +2024-11-22 15:52:05.888990: Epoch time: 19.8 s +2024-11-22 15:52:07.026410: +2024-11-22 15:52:07.027316: Epoch 5249 +2024-11-22 15:52:07.027443: Current learning rate: 0.00383 +2024-11-22 15:52:27.340752: train_loss -0.7905 +2024-11-22 15:52:27.346634: val_loss -0.8008 +2024-11-22 15:52:27.346834: Pseudo dice [0.8697] +2024-11-22 15:52:27.346933: Epoch time: 20.32 s +2024-11-22 15:52:28.692867: +2024-11-22 15:52:28.694214: Epoch 5250 +2024-11-22 15:52:28.694353: Current learning rate: 0.00382 +2024-11-22 15:52:48.155238: train_loss -0.7923 +2024-11-22 15:52:48.171066: val_loss -0.7549 +2024-11-22 15:52:48.171241: Pseudo dice [0.8539] +2024-11-22 15:52:48.171361: Epoch time: 19.46 s +2024-11-22 15:52:49.133114: +2024-11-22 15:52:49.134715: Epoch 5251 +2024-11-22 15:52:49.159961: Current learning rate: 0.00382 +2024-11-22 15:53:08.279869: train_loss -0.7934 +2024-11-22 15:53:08.306244: val_loss -0.7859 +2024-11-22 15:53:08.306395: Pseudo dice [0.855] +2024-11-22 15:53:08.306499: Epoch time: 19.15 s +2024-11-22 15:53:09.214272: +2024-11-22 15:53:09.215081: Epoch 5252 +2024-11-22 15:53:09.215197: Current learning rate: 0.00382 +2024-11-22 15:53:28.131299: train_loss -0.7803 +2024-11-22 15:53:28.139138: val_loss -0.7571 +2024-11-22 15:53:28.139292: Pseudo dice [0.8502] +2024-11-22 15:53:28.139446: Epoch time: 18.92 s +2024-11-22 15:53:29.004076: +2024-11-22 15:53:29.004827: Epoch 5253 +2024-11-22 15:53:29.004960: Current learning rate: 0.00382 +2024-11-22 15:53:47.778833: train_loss -0.79 +2024-11-22 15:53:47.799433: val_loss -0.7821 +2024-11-22 15:53:47.799566: Pseudo dice [0.853] +2024-11-22 15:53:47.799658: Epoch time: 18.78 s +2024-11-22 15:53:48.747033: +2024-11-22 15:53:48.748880: Epoch 5254 +2024-11-22 15:53:48.749015: Current learning rate: 0.00382 +2024-11-22 15:54:08.671764: train_loss -0.7899 +2024-11-22 15:54:08.679207: val_loss -0.7773 +2024-11-22 15:54:08.679393: Pseudo dice [0.8499] +2024-11-22 15:54:08.679516: Epoch time: 19.93 s +2024-11-22 15:54:09.538845: +2024-11-22 15:54:09.539298: Epoch 5255 +2024-11-22 15:54:09.539427: Current learning rate: 0.00382 +2024-11-22 15:54:29.897521: train_loss -0.7996 +2024-11-22 15:54:29.904070: val_loss -0.765 +2024-11-22 15:54:29.904272: Pseudo dice [0.8452] +2024-11-22 15:54:29.904381: Epoch time: 20.36 s +2024-11-22 15:54:30.898489: +2024-11-22 15:54:30.900607: Epoch 5256 +2024-11-22 15:54:30.900744: Current learning rate: 0.00382 +2024-11-22 15:54:50.793091: train_loss -0.7901 +2024-11-22 15:54:50.801585: val_loss -0.7547 +2024-11-22 15:54:50.801733: Pseudo dice [0.8407] +2024-11-22 15:54:50.801828: Epoch time: 19.9 s +2024-11-22 15:54:51.744330: +2024-11-22 15:54:51.745461: Epoch 5257 +2024-11-22 15:54:51.745601: Current learning rate: 0.00382 +2024-11-22 15:55:11.480568: train_loss -0.7874 +2024-11-22 15:55:11.484831: val_loss -0.7828 +2024-11-22 15:55:11.484954: Pseudo dice [0.8498] +2024-11-22 15:55:11.485045: Epoch time: 19.74 s +2024-11-22 15:55:12.487368: +2024-11-22 15:55:12.492574: Epoch 5258 +2024-11-22 15:55:12.492718: Current learning rate: 0.00381 +2024-11-22 15:55:32.519327: train_loss -0.795 +2024-11-22 15:55:32.523965: val_loss -0.7836 +2024-11-22 15:55:32.524132: Pseudo dice [0.8551] +2024-11-22 15:55:32.524235: Epoch time: 20.03 s +2024-11-22 15:55:33.406409: +2024-11-22 15:55:33.407754: Epoch 5259 +2024-11-22 15:55:33.407903: Current learning rate: 0.00381 +2024-11-22 15:55:53.036468: train_loss -0.7986 +2024-11-22 15:55:53.042874: val_loss -0.7733 +2024-11-22 15:55:53.043013: Pseudo dice [0.8596] +2024-11-22 15:55:53.043101: Epoch time: 19.63 s +2024-11-22 15:55:54.046022: +2024-11-22 15:55:54.047427: Epoch 5260 +2024-11-22 15:55:54.047552: Current learning rate: 0.00381 +2024-11-22 15:56:14.035997: train_loss -0.7934 +2024-11-22 15:56:14.044520: val_loss -0.7713 +2024-11-22 15:56:14.044668: Pseudo dice [0.8629] +2024-11-22 15:56:14.044803: Epoch time: 19.99 s +2024-11-22 15:56:14.944898: +2024-11-22 15:56:14.948139: Epoch 5261 +2024-11-22 15:56:14.948270: Current learning rate: 0.00381 +2024-11-22 15:56:35.015554: train_loss -0.7897 +2024-11-22 15:56:35.023741: val_loss -0.7693 +2024-11-22 15:56:35.023910: Pseudo dice [0.8553] +2024-11-22 15:56:35.024014: Epoch time: 20.07 s +2024-11-22 15:56:35.908631: +2024-11-22 15:56:35.910120: Epoch 5262 +2024-11-22 15:56:35.910254: Current learning rate: 0.00381 +2024-11-22 15:56:55.247809: train_loss -0.8056 +2024-11-22 15:56:55.253732: val_loss -0.7694 +2024-11-22 15:56:55.253855: Pseudo dice [0.8596] +2024-11-22 15:56:55.253941: Epoch time: 19.34 s +2024-11-22 15:56:56.394536: +2024-11-22 15:56:56.395564: Epoch 5263 +2024-11-22 15:56:56.395691: Current learning rate: 0.00381 +2024-11-22 15:57:16.926683: train_loss -0.7926 +2024-11-22 15:57:16.937032: val_loss -0.7689 +2024-11-22 15:57:16.937160: Pseudo dice [0.8426] +2024-11-22 15:57:16.937249: Epoch time: 20.53 s +2024-11-22 15:57:17.978878: +2024-11-22 15:57:17.979794: Epoch 5264 +2024-11-22 15:57:17.979924: Current learning rate: 0.00381 +2024-11-22 15:57:37.879251: train_loss -0.7858 +2024-11-22 15:57:37.892174: val_loss -0.7651 +2024-11-22 15:57:37.892314: Pseudo dice [0.8464] +2024-11-22 15:57:37.892414: Epoch time: 19.9 s +2024-11-22 15:57:38.792901: +2024-11-22 15:57:38.794306: Epoch 5265 +2024-11-22 15:57:38.794442: Current learning rate: 0.00381 +2024-11-22 15:57:57.999921: train_loss -0.7917 +2024-11-22 15:57:58.013855: val_loss -0.7624 +2024-11-22 15:57:58.013988: Pseudo dice [0.8461] +2024-11-22 15:57:58.014092: Epoch time: 19.21 s +2024-11-22 15:57:59.394907: +2024-11-22 15:57:59.396118: Epoch 5266 +2024-11-22 15:57:59.396255: Current learning rate: 0.0038 +2024-11-22 15:58:18.990352: train_loss -0.7858 +2024-11-22 15:58:18.996924: val_loss -0.765 +2024-11-22 15:58:18.997053: Pseudo dice [0.8621] +2024-11-22 15:58:18.997158: Epoch time: 19.6 s +2024-11-22 15:58:19.986643: +2024-11-22 15:58:19.987482: Epoch 5267 +2024-11-22 15:58:19.987607: Current learning rate: 0.0038 +2024-11-22 15:58:39.880185: train_loss -0.7873 +2024-11-22 15:58:39.888225: val_loss -0.7751 +2024-11-22 15:58:39.888371: Pseudo dice [0.8637] +2024-11-22 15:58:39.888469: Epoch time: 19.89 s +2024-11-22 15:58:41.101421: +2024-11-22 15:58:41.102435: Epoch 5268 +2024-11-22 15:58:41.102557: Current learning rate: 0.0038 +2024-11-22 15:59:00.535697: train_loss -0.784 +2024-11-22 15:59:00.543555: val_loss -0.7806 +2024-11-22 15:59:00.543682: Pseudo dice [0.863] +2024-11-22 15:59:00.543774: Epoch time: 19.44 s +2024-11-22 15:59:01.480437: +2024-11-22 15:59:01.482561: Epoch 5269 +2024-11-22 15:59:01.482707: Current learning rate: 0.0038 +2024-11-22 15:59:22.217644: train_loss -0.7836 +2024-11-22 15:59:22.224184: val_loss -0.7843 +2024-11-22 15:59:22.224312: Pseudo dice [0.8585] +2024-11-22 15:59:22.224410: Epoch time: 20.74 s +2024-11-22 15:59:23.384771: +2024-11-22 15:59:23.386147: Epoch 5270 +2024-11-22 15:59:23.386311: Current learning rate: 0.0038 +2024-11-22 15:59:42.097507: train_loss -0.794 +2024-11-22 15:59:42.104156: val_loss -0.7665 +2024-11-22 15:59:42.104291: Pseudo dice [0.8559] +2024-11-22 15:59:42.104408: Epoch time: 18.71 s +2024-11-22 15:59:42.979319: +2024-11-22 15:59:42.980131: Epoch 5271 +2024-11-22 15:59:42.980256: Current learning rate: 0.0038 +2024-11-22 16:00:02.460979: train_loss -0.791 +2024-11-22 16:00:02.466908: val_loss -0.7894 +2024-11-22 16:00:02.467036: Pseudo dice [0.8478] +2024-11-22 16:00:02.467131: Epoch time: 19.48 s +2024-11-22 16:00:03.391588: +2024-11-22 16:00:03.392946: Epoch 5272 +2024-11-22 16:00:03.393090: Current learning rate: 0.0038 +2024-11-22 16:00:23.493505: train_loss -0.795 +2024-11-22 16:00:23.499563: val_loss -0.7813 +2024-11-22 16:00:23.499693: Pseudo dice [0.8468] +2024-11-22 16:00:23.499800: Epoch time: 20.1 s +2024-11-22 16:00:24.529685: +2024-11-22 16:00:24.530787: Epoch 5273 +2024-11-22 16:00:24.530927: Current learning rate: 0.0038 +2024-11-22 16:00:44.041363: train_loss -0.7979 +2024-11-22 16:00:44.044161: val_loss -0.7849 +2024-11-22 16:00:44.044270: Pseudo dice [0.8644] +2024-11-22 16:00:44.044384: Epoch time: 19.51 s +2024-11-22 16:00:44.897614: +2024-11-22 16:00:44.898911: Epoch 5274 +2024-11-22 16:00:44.899050: Current learning rate: 0.00379 +2024-11-22 16:01:03.816228: train_loss -0.7867 +2024-11-22 16:01:03.818637: val_loss -0.7555 +2024-11-22 16:01:03.818778: Pseudo dice [0.8537] +2024-11-22 16:01:03.818867: Epoch time: 18.92 s +2024-11-22 16:01:04.824434: +2024-11-22 16:01:04.825814: Epoch 5275 +2024-11-22 16:01:04.825949: Current learning rate: 0.00379 +2024-11-22 16:01:24.507318: train_loss -0.7913 +2024-11-22 16:01:24.510948: val_loss -0.7685 +2024-11-22 16:01:24.511085: Pseudo dice [0.8574] +2024-11-22 16:01:24.511196: Epoch time: 19.68 s +2024-11-22 16:01:25.367415: +2024-11-22 16:01:25.368197: Epoch 5276 +2024-11-22 16:01:25.368331: Current learning rate: 0.00379 +2024-11-22 16:01:45.466810: train_loss -0.7978 +2024-11-22 16:01:45.470761: val_loss -0.7938 +2024-11-22 16:01:45.471165: Pseudo dice [0.8514] +2024-11-22 16:01:45.471297: Epoch time: 20.1 s +2024-11-22 16:01:46.415528: +2024-11-22 16:01:46.417709: Epoch 5277 +2024-11-22 16:01:46.417852: Current learning rate: 0.00379 +2024-11-22 16:02:05.512041: train_loss -0.7987 +2024-11-22 16:02:05.520749: val_loss -0.7622 +2024-11-22 16:02:05.520874: Pseudo dice [0.8547] +2024-11-22 16:02:05.520993: Epoch time: 19.1 s +2024-11-22 16:02:06.989543: +2024-11-22 16:02:06.990573: Epoch 5278 +2024-11-22 16:02:06.990698: Current learning rate: 0.00379 +2024-11-22 16:02:25.149600: train_loss -0.796 +2024-11-22 16:02:25.155785: val_loss -0.7538 +2024-11-22 16:02:25.155904: Pseudo dice [0.8634] +2024-11-22 16:02:25.155999: Epoch time: 18.16 s +2024-11-22 16:02:26.069479: +2024-11-22 16:02:26.071084: Epoch 5279 +2024-11-22 16:02:26.071225: Current learning rate: 0.00379 +2024-11-22 16:02:46.807734: train_loss -0.7929 +2024-11-22 16:02:46.813573: val_loss -0.7875 +2024-11-22 16:02:46.813703: Pseudo dice [0.8507] +2024-11-22 16:02:46.813798: Epoch time: 20.74 s +2024-11-22 16:02:47.692493: +2024-11-22 16:02:47.694709: Epoch 5280 +2024-11-22 16:02:47.694870: Current learning rate: 0.00379 +2024-11-22 16:03:08.569319: train_loss -0.7973 +2024-11-22 16:03:08.579210: val_loss -0.7618 +2024-11-22 16:03:08.579366: Pseudo dice [0.8634] +2024-11-22 16:03:08.579467: Epoch time: 20.88 s +2024-11-22 16:03:09.505990: +2024-11-22 16:03:09.507456: Epoch 5281 +2024-11-22 16:03:09.507601: Current learning rate: 0.00379 +2024-11-22 16:03:28.120687: train_loss -0.798 +2024-11-22 16:03:28.143019: val_loss -0.7463 +2024-11-22 16:03:28.143173: Pseudo dice [0.848] +2024-11-22 16:03:28.143288: Epoch time: 18.62 s +2024-11-22 16:03:29.146976: +2024-11-22 16:03:29.147428: Epoch 5282 +2024-11-22 16:03:29.147563: Current learning rate: 0.00378 +2024-11-22 16:03:50.136163: train_loss -0.7869 +2024-11-22 16:03:50.138762: val_loss -0.8052 +2024-11-22 16:03:50.138897: Pseudo dice [0.87] +2024-11-22 16:03:50.138998: Epoch time: 20.99 s +2024-11-22 16:03:50.996208: +2024-11-22 16:03:50.997850: Epoch 5283 +2024-11-22 16:03:50.997990: Current learning rate: 0.00378 +2024-11-22 16:04:10.682605: train_loss -0.7979 +2024-11-22 16:04:10.701919: val_loss -0.776 +2024-11-22 16:04:10.702069: Pseudo dice [0.8638] +2024-11-22 16:04:10.702158: Epoch time: 19.69 s +2024-11-22 16:04:11.702192: +2024-11-22 16:04:11.702979: Epoch 5284 +2024-11-22 16:04:11.703111: Current learning rate: 0.00378 +2024-11-22 16:04:31.934640: train_loss -0.7972 +2024-11-22 16:04:31.952037: val_loss -0.7695 +2024-11-22 16:04:31.952194: Pseudo dice [0.8499] +2024-11-22 16:04:31.952313: Epoch time: 20.23 s +2024-11-22 16:04:32.938252: +2024-11-22 16:04:32.939827: Epoch 5285 +2024-11-22 16:04:32.939951: Current learning rate: 0.00378 +2024-11-22 16:04:52.669318: train_loss -0.789 +2024-11-22 16:04:52.675604: val_loss -0.7705 +2024-11-22 16:04:52.675733: Pseudo dice [0.8624] +2024-11-22 16:04:52.675901: Epoch time: 19.73 s +2024-11-22 16:04:53.790398: +2024-11-22 16:04:53.792024: Epoch 5286 +2024-11-22 16:04:53.792172: Current learning rate: 0.00378 +2024-11-22 16:05:12.816843: train_loss -0.7964 +2024-11-22 16:05:12.824120: val_loss -0.782 +2024-11-22 16:05:12.824337: Pseudo dice [0.8493] +2024-11-22 16:05:12.824456: Epoch time: 19.03 s +2024-11-22 16:05:13.930737: +2024-11-22 16:05:13.932342: Epoch 5287 +2024-11-22 16:05:13.932478: Current learning rate: 0.00378 +2024-11-22 16:05:34.209249: train_loss -0.792 +2024-11-22 16:05:34.219165: val_loss -0.7734 +2024-11-22 16:05:34.219319: Pseudo dice [0.8576] +2024-11-22 16:05:34.219420: Epoch time: 20.28 s +2024-11-22 16:05:35.403635: +2024-11-22 16:05:35.405244: Epoch 5288 +2024-11-22 16:05:35.405372: Current learning rate: 0.00378 +2024-11-22 16:05:54.919209: train_loss -0.7889 +2024-11-22 16:05:54.927876: val_loss -0.7935 +2024-11-22 16:05:54.928100: Pseudo dice [0.8478] +2024-11-22 16:05:54.928214: Epoch time: 19.52 s +2024-11-22 16:05:55.970922: +2024-11-22 16:05:55.973297: Epoch 5289 +2024-11-22 16:05:55.973442: Current learning rate: 0.00378 +2024-11-22 16:06:15.688007: train_loss -0.7937 +2024-11-22 16:06:15.704056: val_loss -0.7798 +2024-11-22 16:06:15.704204: Pseudo dice [0.8565] +2024-11-22 16:06:15.704307: Epoch time: 19.72 s +2024-11-22 16:06:17.213242: +2024-11-22 16:06:17.214342: Epoch 5290 +2024-11-22 16:06:17.214481: Current learning rate: 0.00377 +2024-11-22 16:06:37.994712: train_loss -0.7923 +2024-11-22 16:06:37.999389: val_loss -0.7618 +2024-11-22 16:06:37.999541: Pseudo dice [0.8554] +2024-11-22 16:06:37.999638: Epoch time: 20.78 s +2024-11-22 16:06:39.087929: +2024-11-22 16:06:39.088148: Epoch 5291 +2024-11-22 16:06:39.088279: Current learning rate: 0.00377 +2024-11-22 16:06:58.802838: train_loss -0.8041 +2024-11-22 16:06:58.811169: val_loss -0.7777 +2024-11-22 16:06:58.811296: Pseudo dice [0.8495] +2024-11-22 16:06:58.811396: Epoch time: 19.72 s +2024-11-22 16:06:59.885549: +2024-11-22 16:06:59.887149: Epoch 5292 +2024-11-22 16:06:59.887302: Current learning rate: 0.00377 +2024-11-22 16:07:19.633006: train_loss -0.8003 +2024-11-22 16:07:19.635271: val_loss -0.7722 +2024-11-22 16:07:19.635418: Pseudo dice [0.8646] +2024-11-22 16:07:19.635512: Epoch time: 19.75 s +2024-11-22 16:07:20.722540: +2024-11-22 16:07:20.724392: Epoch 5293 +2024-11-22 16:07:20.724519: Current learning rate: 0.00377 +2024-11-22 16:07:39.849336: train_loss -0.7989 +2024-11-22 16:07:39.855646: val_loss -0.7904 +2024-11-22 16:07:39.855781: Pseudo dice [0.8554] +2024-11-22 16:07:39.855889: Epoch time: 19.13 s +2024-11-22 16:07:40.893077: +2024-11-22 16:07:40.895447: Epoch 5294 +2024-11-22 16:07:40.895601: Current learning rate: 0.00377 +2024-11-22 16:08:01.176523: train_loss -0.7899 +2024-11-22 16:08:01.186225: val_loss -0.7715 +2024-11-22 16:08:01.186347: Pseudo dice [0.8649] +2024-11-22 16:08:01.186451: Epoch time: 20.28 s +2024-11-22 16:08:02.215744: +2024-11-22 16:08:02.216931: Epoch 5295 +2024-11-22 16:08:02.217071: Current learning rate: 0.00377 +2024-11-22 16:08:21.520304: train_loss -0.7995 +2024-11-22 16:08:21.535242: val_loss -0.784 +2024-11-22 16:08:21.535394: Pseudo dice [0.8475] +2024-11-22 16:08:21.535590: Epoch time: 19.31 s +2024-11-22 16:08:22.627359: +2024-11-22 16:08:22.629687: Epoch 5296 +2024-11-22 16:08:22.629829: Current learning rate: 0.00377 +2024-11-22 16:08:41.498186: train_loss -0.7977 +2024-11-22 16:08:41.507700: val_loss -0.7612 +2024-11-22 16:08:41.507837: Pseudo dice [0.8551] +2024-11-22 16:08:41.507926: Epoch time: 18.87 s +2024-11-22 16:08:42.564757: +2024-11-22 16:08:42.565192: Epoch 5297 +2024-11-22 16:08:42.565320: Current learning rate: 0.00377 +2024-11-22 16:09:00.086696: train_loss -0.7892 +2024-11-22 16:09:00.097372: val_loss -0.7828 +2024-11-22 16:09:00.097546: Pseudo dice [0.854] +2024-11-22 16:09:00.097640: Epoch time: 17.52 s +2024-11-22 16:09:01.006703: +2024-11-22 16:09:01.006970: Epoch 5298 +2024-11-22 16:09:01.007105: Current learning rate: 0.00376 +2024-11-22 16:09:19.937167: train_loss -0.7922 +2024-11-22 16:09:19.941140: val_loss -0.7616 +2024-11-22 16:09:19.943553: Pseudo dice [0.8517] +2024-11-22 16:09:19.943679: Epoch time: 18.93 s +2024-11-22 16:09:20.971291: +2024-11-22 16:09:20.971505: Epoch 5299 +2024-11-22 16:09:20.971635: Current learning rate: 0.00376 +2024-11-22 16:09:38.505583: train_loss -0.8014 +2024-11-22 16:09:38.510124: val_loss -0.7944 +2024-11-22 16:09:38.510260: Pseudo dice [0.8637] +2024-11-22 16:09:38.510353: Epoch time: 17.54 s +2024-11-22 16:09:39.682504: +2024-11-22 16:09:39.682733: Epoch 5300 +2024-11-22 16:09:39.682866: Current learning rate: 0.00376 +2024-11-22 16:09:58.790045: train_loss -0.7919 +2024-11-22 16:09:58.790522: val_loss -0.784 +2024-11-22 16:09:58.790630: Pseudo dice [0.8637] +2024-11-22 16:09:58.790720: Epoch time: 19.11 s +2024-11-22 16:09:59.638393: +2024-11-22 16:09:59.638644: Epoch 5301 +2024-11-22 16:09:59.638764: Current learning rate: 0.00376 +2024-11-22 16:10:18.461697: train_loss -0.7971 +2024-11-22 16:10:18.462247: val_loss -0.7985 +2024-11-22 16:10:18.462345: Pseudo dice [0.8687] +2024-11-22 16:10:18.462444: Epoch time: 18.82 s +2024-11-22 16:10:19.455952: +2024-11-22 16:10:19.456433: Epoch 5302 +2024-11-22 16:10:19.456574: Current learning rate: 0.00376 +2024-11-22 16:10:37.073912: train_loss -0.7943 +2024-11-22 16:10:37.074806: val_loss -0.8047 +2024-11-22 16:10:37.074914: Pseudo dice [0.8623] +2024-11-22 16:10:37.074998: Epoch time: 17.62 s +2024-11-22 16:10:38.153750: +2024-11-22 16:10:38.153981: Epoch 5303 +2024-11-22 16:10:38.154112: Current learning rate: 0.00376 +2024-11-22 16:10:57.869052: train_loss -0.7946 +2024-11-22 16:10:57.869537: val_loss -0.7773 +2024-11-22 16:10:57.869633: Pseudo dice [0.8522] +2024-11-22 16:10:57.869726: Epoch time: 19.72 s +2024-11-22 16:10:58.726513: +2024-11-22 16:10:58.726727: Epoch 5304 +2024-11-22 16:10:58.726852: Current learning rate: 0.00376 +2024-11-22 16:11:17.185084: train_loss -0.7942 +2024-11-22 16:11:17.186497: val_loss -0.7809 +2024-11-22 16:11:17.186614: Pseudo dice [0.8423] +2024-11-22 16:11:17.186720: Epoch time: 18.46 s +2024-11-22 16:11:18.046286: +2024-11-22 16:11:18.046507: Epoch 5305 +2024-11-22 16:11:18.046620: Current learning rate: 0.00376 +2024-11-22 16:11:36.890281: train_loss -0.7994 +2024-11-22 16:11:36.902239: val_loss -0.7752 +2024-11-22 16:11:36.907352: Pseudo dice [0.8449] +2024-11-22 16:11:36.907549: Epoch time: 18.85 s +2024-11-22 16:11:37.868694: +2024-11-22 16:11:37.868900: Epoch 5306 +2024-11-22 16:11:37.869016: Current learning rate: 0.00375 +2024-11-22 16:11:56.801809: train_loss -0.7957 +2024-11-22 16:11:56.809264: val_loss -0.7863 +2024-11-22 16:11:56.809412: Pseudo dice [0.8597] +2024-11-22 16:11:56.809505: Epoch time: 18.93 s +2024-11-22 16:11:57.741972: +2024-11-22 16:11:57.742728: Epoch 5307 +2024-11-22 16:11:57.742859: Current learning rate: 0.00375 +2024-11-22 16:12:17.271929: train_loss -0.7896 +2024-11-22 16:12:17.292742: val_loss -0.7914 +2024-11-22 16:12:17.292866: Pseudo dice [0.8722] +2024-11-22 16:12:17.292958: Epoch time: 19.53 s +2024-11-22 16:12:18.274333: +2024-11-22 16:12:18.275186: Epoch 5308 +2024-11-22 16:12:18.275305: Current learning rate: 0.00375 +2024-11-22 16:12:38.045040: train_loss -0.8053 +2024-11-22 16:12:38.053729: val_loss -0.7689 +2024-11-22 16:12:38.053878: Pseudo dice [0.8589] +2024-11-22 16:12:38.054004: Epoch time: 19.77 s +2024-11-22 16:12:38.999254: +2024-11-22 16:12:39.000522: Epoch 5309 +2024-11-22 16:12:39.000646: Current learning rate: 0.00375 +2024-11-22 16:12:58.216203: train_loss -0.7991 +2024-11-22 16:12:58.225100: val_loss -0.771 +2024-11-22 16:12:58.225334: Pseudo dice [0.8393] +2024-11-22 16:12:58.225441: Epoch time: 19.22 s +2024-11-22 16:12:59.312668: +2024-11-22 16:12:59.313441: Epoch 5310 +2024-11-22 16:12:59.313570: Current learning rate: 0.00375 +2024-11-22 16:13:19.336012: train_loss -0.7957 +2024-11-22 16:13:19.352746: val_loss -0.7741 +2024-11-22 16:13:19.352923: Pseudo dice [0.8503] +2024-11-22 16:13:19.353020: Epoch time: 20.02 s +2024-11-22 16:13:20.503236: +2024-11-22 16:13:20.505482: Epoch 5311 +2024-11-22 16:13:20.505613: Current learning rate: 0.00375 +2024-11-22 16:13:39.917836: train_loss -0.7972 +2024-11-22 16:13:39.924714: val_loss -0.761 +2024-11-22 16:13:39.924915: Pseudo dice [0.8576] +2024-11-22 16:13:39.925022: Epoch time: 19.42 s +2024-11-22 16:13:40.872493: +2024-11-22 16:13:40.874622: Epoch 5312 +2024-11-22 16:13:40.874767: Current learning rate: 0.00375 +2024-11-22 16:14:00.321408: train_loss -0.8016 +2024-11-22 16:14:00.335372: val_loss -0.7736 +2024-11-22 16:14:00.335528: Pseudo dice [0.8524] +2024-11-22 16:14:00.335622: Epoch time: 19.45 s +2024-11-22 16:14:01.701090: +2024-11-22 16:14:01.703126: Epoch 5313 +2024-11-22 16:14:01.703256: Current learning rate: 0.00375 +2024-11-22 16:14:20.809932: train_loss -0.7957 +2024-11-22 16:14:20.833568: val_loss -0.7986 +2024-11-22 16:14:20.833833: Pseudo dice [0.8622] +2024-11-22 16:14:20.834037: Epoch time: 19.11 s +2024-11-22 16:14:21.797500: +2024-11-22 16:14:21.799499: Epoch 5314 +2024-11-22 16:14:21.799636: Current learning rate: 0.00374 +2024-11-22 16:14:41.557829: train_loss -0.7926 +2024-11-22 16:14:41.565226: val_loss -0.7853 +2024-11-22 16:14:41.565364: Pseudo dice [0.8583] +2024-11-22 16:14:41.565629: Epoch time: 19.76 s +2024-11-22 16:14:42.444019: +2024-11-22 16:14:42.445488: Epoch 5315 +2024-11-22 16:14:42.445615: Current learning rate: 0.00374 +2024-11-22 16:15:01.864027: train_loss -0.8066 +2024-11-22 16:15:01.868785: val_loss -0.7515 +2024-11-22 16:15:01.868917: Pseudo dice [0.8597] +2024-11-22 16:15:01.869025: Epoch time: 19.42 s +2024-11-22 16:15:02.735385: +2024-11-22 16:15:02.736747: Epoch 5316 +2024-11-22 16:15:02.736872: Current learning rate: 0.00374 +2024-11-22 16:15:22.118404: train_loss -0.7889 +2024-11-22 16:15:22.120871: val_loss -0.774 +2024-11-22 16:15:22.121011: Pseudo dice [0.865] +2024-11-22 16:15:22.121117: Epoch time: 19.38 s +2024-11-22 16:15:23.011115: +2024-11-22 16:15:23.012269: Epoch 5317 +2024-11-22 16:15:23.012394: Current learning rate: 0.00374 +2024-11-22 16:15:43.084449: train_loss -0.7952 +2024-11-22 16:15:43.089392: val_loss -0.7653 +2024-11-22 16:15:43.089522: Pseudo dice [0.8467] +2024-11-22 16:15:43.089628: Epoch time: 20.07 s +2024-11-22 16:15:44.019983: +2024-11-22 16:15:44.021843: Epoch 5318 +2024-11-22 16:15:44.021976: Current learning rate: 0.00374 +2024-11-22 16:16:02.991615: train_loss -0.7985 +2024-11-22 16:16:03.018955: val_loss -0.7613 +2024-11-22 16:16:03.019135: Pseudo dice [0.8355] +2024-11-22 16:16:03.019987: Epoch time: 18.97 s +2024-11-22 16:16:04.032355: +2024-11-22 16:16:04.033261: Epoch 5319 +2024-11-22 16:16:04.033394: Current learning rate: 0.00374 +2024-11-22 16:16:24.101608: train_loss -0.7968 +2024-11-22 16:16:24.109160: val_loss -0.7789 +2024-11-22 16:16:24.109298: Pseudo dice [0.8576] +2024-11-22 16:16:24.109393: Epoch time: 20.07 s +2024-11-22 16:16:25.119274: +2024-11-22 16:16:25.120805: Epoch 5320 +2024-11-22 16:16:25.120936: Current learning rate: 0.00374 +2024-11-22 16:16:45.105458: train_loss -0.7979 +2024-11-22 16:16:45.112216: val_loss -0.7868 +2024-11-22 16:16:45.112408: Pseudo dice [0.8682] +2024-11-22 16:16:45.112514: Epoch time: 19.99 s +2024-11-22 16:16:46.107673: +2024-11-22 16:16:46.108963: Epoch 5321 +2024-11-22 16:16:46.109108: Current learning rate: 0.00374 +2024-11-22 16:17:04.660245: train_loss -0.7969 +2024-11-22 16:17:04.662749: val_loss -0.786 +2024-11-22 16:17:04.662862: Pseudo dice [0.8504] +2024-11-22 16:17:04.662951: Epoch time: 18.55 s +2024-11-22 16:17:05.524389: +2024-11-22 16:17:05.525536: Epoch 5322 +2024-11-22 16:17:05.525672: Current learning rate: 0.00373 +2024-11-22 16:17:25.354796: train_loss -0.8 +2024-11-22 16:17:25.366419: val_loss -0.7585 +2024-11-22 16:17:25.366554: Pseudo dice [0.8546] +2024-11-22 16:17:25.366661: Epoch time: 19.83 s +2024-11-22 16:17:26.347020: +2024-11-22 16:17:26.347834: Epoch 5323 +2024-11-22 16:17:26.347965: Current learning rate: 0.00373 +2024-11-22 16:17:45.889617: train_loss -0.8036 +2024-11-22 16:17:45.891655: val_loss -0.7886 +2024-11-22 16:17:45.891751: Pseudo dice [0.8527] +2024-11-22 16:17:45.891852: Epoch time: 19.54 s +2024-11-22 16:17:46.745760: +2024-11-22 16:17:46.747667: Epoch 5324 +2024-11-22 16:17:46.747808: Current learning rate: 0.00373 +2024-11-22 16:18:05.912411: train_loss -0.7824 +2024-11-22 16:18:05.925895: val_loss -0.7446 +2024-11-22 16:18:05.926019: Pseudo dice [0.835] +2024-11-22 16:18:05.926128: Epoch time: 19.17 s +2024-11-22 16:18:07.443892: +2024-11-22 16:18:07.445642: Epoch 5325 +2024-11-22 16:18:07.445776: Current learning rate: 0.00373 +2024-11-22 16:18:28.099400: train_loss -0.7905 +2024-11-22 16:18:28.101655: val_loss -0.7671 +2024-11-22 16:18:28.101770: Pseudo dice [0.8549] +2024-11-22 16:18:28.101895: Epoch time: 20.66 s +2024-11-22 16:18:28.956338: +2024-11-22 16:18:28.957790: Epoch 5326 +2024-11-22 16:18:28.957918: Current learning rate: 0.00373 +2024-11-22 16:18:48.028847: train_loss -0.7913 +2024-11-22 16:18:48.045664: val_loss -0.7925 +2024-11-22 16:18:48.050212: Pseudo dice [0.8529] +2024-11-22 16:18:48.050336: Epoch time: 19.07 s +2024-11-22 16:18:49.087307: +2024-11-22 16:18:49.088836: Epoch 5327 +2024-11-22 16:18:49.088963: Current learning rate: 0.00373 +2024-11-22 16:19:07.659117: train_loss -0.78 +2024-11-22 16:19:07.665470: val_loss -0.7604 +2024-11-22 16:19:07.665598: Pseudo dice [0.8418] +2024-11-22 16:19:07.665726: Epoch time: 18.57 s +2024-11-22 16:19:08.682766: +2024-11-22 16:19:08.684496: Epoch 5328 +2024-11-22 16:19:08.684648: Current learning rate: 0.00373 +2024-11-22 16:19:27.903087: train_loss -0.7831 +2024-11-22 16:19:27.909318: val_loss -0.7604 +2024-11-22 16:19:27.909462: Pseudo dice [0.8609] +2024-11-22 16:19:27.909626: Epoch time: 19.22 s +2024-11-22 16:19:28.818608: +2024-11-22 16:19:28.820437: Epoch 5329 +2024-11-22 16:19:28.820568: Current learning rate: 0.00373 +2024-11-22 16:19:48.387742: train_loss -0.7868 +2024-11-22 16:19:48.396627: val_loss -0.7775 +2024-11-22 16:19:48.403314: Pseudo dice [0.8524] +2024-11-22 16:19:48.403844: Epoch time: 19.57 s +2024-11-22 16:19:49.415128: +2024-11-22 16:19:49.416682: Epoch 5330 +2024-11-22 16:19:49.416809: Current learning rate: 0.00372 +2024-11-22 16:20:08.859267: train_loss -0.8023 +2024-11-22 16:20:08.865641: val_loss -0.7766 +2024-11-22 16:20:08.865810: Pseudo dice [0.8521] +2024-11-22 16:20:08.865915: Epoch time: 19.44 s +2024-11-22 16:20:09.793428: +2024-11-22 16:20:09.795166: Epoch 5331 +2024-11-22 16:20:09.795291: Current learning rate: 0.00372 +2024-11-22 16:20:29.774324: train_loss -0.7953 +2024-11-22 16:20:29.781129: val_loss -0.7809 +2024-11-22 16:20:29.781273: Pseudo dice [0.8674] +2024-11-22 16:20:29.781370: Epoch time: 19.98 s +2024-11-22 16:20:30.687226: +2024-11-22 16:20:30.687992: Epoch 5332 +2024-11-22 16:20:30.688118: Current learning rate: 0.00372 +2024-11-22 16:20:49.978769: train_loss -0.7936 +2024-11-22 16:20:49.984767: val_loss -0.7563 +2024-11-22 16:20:49.984899: Pseudo dice [0.8609] +2024-11-22 16:20:49.984991: Epoch time: 19.29 s +2024-11-22 16:20:50.850957: +2024-11-22 16:20:50.852699: Epoch 5333 +2024-11-22 16:20:50.852857: Current learning rate: 0.00372 +2024-11-22 16:21:10.767228: train_loss -0.7991 +2024-11-22 16:21:10.784956: val_loss -0.7832 +2024-11-22 16:21:10.785092: Pseudo dice [0.8643] +2024-11-22 16:21:10.785197: Epoch time: 19.92 s +2024-11-22 16:21:11.742238: +2024-11-22 16:21:11.744044: Epoch 5334 +2024-11-22 16:21:11.744187: Current learning rate: 0.00372 +2024-11-22 16:21:31.053095: train_loss -0.7951 +2024-11-22 16:21:31.060252: val_loss -0.7651 +2024-11-22 16:21:31.060398: Pseudo dice [0.8507] +2024-11-22 16:21:31.060492: Epoch time: 19.31 s +2024-11-22 16:21:31.966532: +2024-11-22 16:21:31.968431: Epoch 5335 +2024-11-22 16:21:31.968562: Current learning rate: 0.00372 +2024-11-22 16:21:51.377613: train_loss -0.8052 +2024-11-22 16:21:51.388835: val_loss -0.768 +2024-11-22 16:21:51.388970: Pseudo dice [0.8522] +2024-11-22 16:21:51.389072: Epoch time: 19.41 s +2024-11-22 16:21:52.384763: +2024-11-22 16:21:52.385272: Epoch 5336 +2024-11-22 16:21:52.385399: Current learning rate: 0.00372 +2024-11-22 16:22:11.592105: train_loss -0.7945 +2024-11-22 16:22:11.598118: val_loss -0.7842 +2024-11-22 16:22:11.598246: Pseudo dice [0.8601] +2024-11-22 16:22:11.598369: Epoch time: 19.21 s +2024-11-22 16:22:13.051479: +2024-11-22 16:22:13.052812: Epoch 5337 +2024-11-22 16:22:13.052965: Current learning rate: 0.00372 +2024-11-22 16:22:33.852575: train_loss -0.8004 +2024-11-22 16:22:33.859882: val_loss -0.8024 +2024-11-22 16:22:33.860016: Pseudo dice [0.858] +2024-11-22 16:22:33.860273: Epoch time: 20.8 s +2024-11-22 16:22:34.876877: +2024-11-22 16:22:34.877985: Epoch 5338 +2024-11-22 16:22:34.878120: Current learning rate: 0.00371 +2024-11-22 16:22:53.700495: train_loss -0.7956 +2024-11-22 16:22:53.705631: val_loss -0.769 +2024-11-22 16:22:53.705774: Pseudo dice [0.8529] +2024-11-22 16:22:53.705875: Epoch time: 18.82 s +2024-11-22 16:22:54.633856: +2024-11-22 16:22:54.635218: Epoch 5339 +2024-11-22 16:22:54.635361: Current learning rate: 0.00371 +2024-11-22 16:23:12.996666: train_loss -0.8049 +2024-11-22 16:23:13.015830: val_loss -0.7851 +2024-11-22 16:23:13.015977: Pseudo dice [0.8559] +2024-11-22 16:23:13.016097: Epoch time: 18.36 s +2024-11-22 16:23:13.908972: +2024-11-22 16:23:13.909941: Epoch 5340 +2024-11-22 16:23:13.917887: Current learning rate: 0.00371 +2024-11-22 16:23:32.899245: train_loss -0.7925 +2024-11-22 16:23:32.923337: val_loss -0.7825 +2024-11-22 16:23:32.923471: Pseudo dice [0.858] +2024-11-22 16:23:32.923579: Epoch time: 18.99 s +2024-11-22 16:23:33.886101: +2024-11-22 16:23:33.887425: Epoch 5341 +2024-11-22 16:23:33.887550: Current learning rate: 0.00371 +2024-11-22 16:23:52.850725: train_loss -0.7848 +2024-11-22 16:23:52.859476: val_loss -0.7572 +2024-11-22 16:23:52.859601: Pseudo dice [0.8396] +2024-11-22 16:23:52.859708: Epoch time: 18.97 s +2024-11-22 16:23:53.768905: +2024-11-22 16:23:53.769725: Epoch 5342 +2024-11-22 16:23:53.769854: Current learning rate: 0.00371 +2024-11-22 16:24:13.529005: train_loss -0.7792 +2024-11-22 16:24:13.535653: val_loss -0.7842 +2024-11-22 16:24:13.535798: Pseudo dice [0.8378] +2024-11-22 16:24:13.535938: Epoch time: 19.76 s +2024-11-22 16:24:14.417070: +2024-11-22 16:24:14.418768: Epoch 5343 +2024-11-22 16:24:14.418901: Current learning rate: 0.00371 +2024-11-22 16:24:33.653373: train_loss -0.781 +2024-11-22 16:24:33.655937: val_loss -0.7627 +2024-11-22 16:24:33.656051: Pseudo dice [0.8489] +2024-11-22 16:24:33.656158: Epoch time: 19.24 s +2024-11-22 16:24:34.586615: +2024-11-22 16:24:34.588312: Epoch 5344 +2024-11-22 16:24:34.588482: Current learning rate: 0.00371 +2024-11-22 16:24:53.654289: train_loss -0.7945 +2024-11-22 16:24:53.662227: val_loss -0.7631 +2024-11-22 16:24:53.662366: Pseudo dice [0.8543] +2024-11-22 16:24:53.662736: Epoch time: 19.07 s +2024-11-22 16:24:54.676182: +2024-11-22 16:24:54.677738: Epoch 5345 +2024-11-22 16:24:54.677860: Current learning rate: 0.00371 +2024-11-22 16:25:13.728774: train_loss -0.7821 +2024-11-22 16:25:13.732175: val_loss -0.7861 +2024-11-22 16:25:13.732277: Pseudo dice [0.8619] +2024-11-22 16:25:13.732388: Epoch time: 19.05 s +2024-11-22 16:25:14.597994: +2024-11-22 16:25:14.598781: Epoch 5346 +2024-11-22 16:25:14.598902: Current learning rate: 0.0037 +2024-11-22 16:25:35.270138: train_loss -0.7819 +2024-11-22 16:25:35.276827: val_loss -0.7898 +2024-11-22 16:25:35.276958: Pseudo dice [0.8571] +2024-11-22 16:25:35.277077: Epoch time: 20.67 s +2024-11-22 16:25:36.343585: +2024-11-22 16:25:36.345072: Epoch 5347 +2024-11-22 16:25:36.345194: Current learning rate: 0.0037 +2024-11-22 16:25:55.971620: train_loss -0.7966 +2024-11-22 16:25:55.974896: val_loss -0.7808 +2024-11-22 16:25:55.975033: Pseudo dice [0.8681] +2024-11-22 16:25:55.975133: Epoch time: 19.63 s +2024-11-22 16:25:56.931793: +2024-11-22 16:25:56.933006: Epoch 5348 +2024-11-22 16:25:56.933139: Current learning rate: 0.0037 +2024-11-22 16:26:17.058206: train_loss -0.7956 +2024-11-22 16:26:17.072491: val_loss -0.7781 +2024-11-22 16:26:17.072644: Pseudo dice [0.8482] +2024-11-22 16:26:17.072754: Epoch time: 20.13 s +2024-11-22 16:26:18.550740: +2024-11-22 16:26:18.552383: Epoch 5349 +2024-11-22 16:26:18.552534: Current learning rate: 0.0037 +2024-11-22 16:26:37.338407: train_loss -0.7883 +2024-11-22 16:26:37.347185: val_loss -0.7664 +2024-11-22 16:26:37.347335: Pseudo dice [0.8459] +2024-11-22 16:26:37.347428: Epoch time: 18.79 s +2024-11-22 16:26:38.579422: +2024-11-22 16:26:38.581173: Epoch 5350 +2024-11-22 16:26:38.581297: Current learning rate: 0.0037 +2024-11-22 16:26:57.881822: train_loss -0.8011 +2024-11-22 16:26:57.889502: val_loss -0.7928 +2024-11-22 16:26:57.889621: Pseudo dice [0.8597] +2024-11-22 16:26:57.889722: Epoch time: 19.3 s +2024-11-22 16:26:59.045080: +2024-11-22 16:26:59.046546: Epoch 5351 +2024-11-22 16:26:59.046674: Current learning rate: 0.0037 +2024-11-22 16:27:19.419018: train_loss -0.792 +2024-11-22 16:27:19.433021: val_loss -0.7525 +2024-11-22 16:27:19.433183: Pseudo dice [0.8532] +2024-11-22 16:27:19.433305: Epoch time: 20.37 s +2024-11-22 16:27:20.511849: +2024-11-22 16:27:20.513218: Epoch 5352 +2024-11-22 16:27:20.513355: Current learning rate: 0.0037 +2024-11-22 16:27:39.427225: train_loss -0.7928 +2024-11-22 16:27:39.442761: val_loss -0.7633 +2024-11-22 16:27:39.442980: Pseudo dice [0.848] +2024-11-22 16:27:39.467068: Epoch time: 18.92 s +2024-11-22 16:27:40.437458: +2024-11-22 16:27:40.438226: Epoch 5353 +2024-11-22 16:27:40.438370: Current learning rate: 0.0037 +2024-11-22 16:27:59.499556: train_loss -0.7985 +2024-11-22 16:27:59.511719: val_loss -0.7984 +2024-11-22 16:27:59.511856: Pseudo dice [0.8547] +2024-11-22 16:27:59.511950: Epoch time: 19.06 s +2024-11-22 16:28:00.513983: +2024-11-22 16:28:00.515415: Epoch 5354 +2024-11-22 16:28:00.515562: Current learning rate: 0.00369 +2024-11-22 16:28:20.349188: train_loss -0.7954 +2024-11-22 16:28:20.361086: val_loss -0.7809 +2024-11-22 16:28:20.361241: Pseudo dice [0.8572] +2024-11-22 16:28:20.361345: Epoch time: 19.84 s +2024-11-22 16:28:21.387003: +2024-11-22 16:28:21.388510: Epoch 5355 +2024-11-22 16:28:21.388632: Current learning rate: 0.00369 +2024-11-22 16:28:40.766485: train_loss -0.8057 +2024-11-22 16:28:40.824206: val_loss -0.7709 +2024-11-22 16:28:40.824371: Pseudo dice [0.8551] +2024-11-22 16:28:40.824475: Epoch time: 19.38 s +2024-11-22 16:28:41.832099: +2024-11-22 16:28:41.833826: Epoch 5356 +2024-11-22 16:28:41.833949: Current learning rate: 0.00369 +2024-11-22 16:29:01.988616: train_loss -0.8001 +2024-11-22 16:29:01.995986: val_loss -0.792 +2024-11-22 16:29:01.996224: Pseudo dice [0.8677] +2024-11-22 16:29:01.996328: Epoch time: 20.16 s +2024-11-22 16:29:02.879992: +2024-11-22 16:29:02.881467: Epoch 5357 +2024-11-22 16:29:02.881588: Current learning rate: 0.00369 +2024-11-22 16:29:22.794064: train_loss -0.8038 +2024-11-22 16:29:22.801188: val_loss -0.8006 +2024-11-22 16:29:22.801348: Pseudo dice [0.8551] +2024-11-22 16:29:22.801437: Epoch time: 19.91 s +2024-11-22 16:29:23.668434: +2024-11-22 16:29:23.669411: Epoch 5358 +2024-11-22 16:29:23.669527: Current learning rate: 0.00369 +2024-11-22 16:29:44.016895: train_loss -0.801 +2024-11-22 16:29:44.022720: val_loss -0.7855 +2024-11-22 16:29:44.022850: Pseudo dice [0.8629] +2024-11-22 16:29:44.022937: Epoch time: 20.35 s +2024-11-22 16:29:44.982245: +2024-11-22 16:29:44.983541: Epoch 5359 +2024-11-22 16:29:44.983688: Current learning rate: 0.00369 +2024-11-22 16:30:03.960793: train_loss -0.8044 +2024-11-22 16:30:03.968190: val_loss -0.7632 +2024-11-22 16:30:03.968340: Pseudo dice [0.8484] +2024-11-22 16:30:03.968427: Epoch time: 18.98 s +2024-11-22 16:30:04.860673: +2024-11-22 16:30:04.861498: Epoch 5360 +2024-11-22 16:30:04.861623: Current learning rate: 0.00369 +2024-11-22 16:30:24.091544: train_loss -0.7955 +2024-11-22 16:30:24.104266: val_loss -0.7669 +2024-11-22 16:30:24.104419: Pseudo dice [0.8484] +2024-11-22 16:30:24.104538: Epoch time: 19.23 s +2024-11-22 16:30:25.122321: +2024-11-22 16:30:25.122527: Epoch 5361 +2024-11-22 16:30:25.122642: Current learning rate: 0.00369 +2024-11-22 16:30:45.476003: train_loss -0.7964 +2024-11-22 16:30:45.482669: val_loss -0.7895 +2024-11-22 16:30:45.482820: Pseudo dice [0.865] +2024-11-22 16:30:45.482907: Epoch time: 20.35 s +2024-11-22 16:30:46.355419: +2024-11-22 16:30:46.355897: Epoch 5362 +2024-11-22 16:30:46.356024: Current learning rate: 0.00368 +2024-11-22 16:31:05.283735: train_loss -0.798 +2024-11-22 16:31:05.289397: val_loss -0.7474 +2024-11-22 16:31:05.289522: Pseudo dice [0.8469] +2024-11-22 16:31:05.289626: Epoch time: 18.93 s +2024-11-22 16:31:06.156168: +2024-11-22 16:31:06.157580: Epoch 5363 +2024-11-22 16:31:06.157701: Current learning rate: 0.00368 +2024-11-22 16:31:27.123741: train_loss -0.7997 +2024-11-22 16:31:27.126947: val_loss -0.7728 +2024-11-22 16:31:27.127079: Pseudo dice [0.8584] +2024-11-22 16:31:27.127182: Epoch time: 20.97 s +2024-11-22 16:31:28.153888: +2024-11-22 16:31:28.155179: Epoch 5364 +2024-11-22 16:31:28.155317: Current learning rate: 0.00368 +2024-11-22 16:31:47.796432: train_loss -0.7974 +2024-11-22 16:31:47.807911: val_loss -0.7756 +2024-11-22 16:31:47.808044: Pseudo dice [0.8576] +2024-11-22 16:31:47.808150: Epoch time: 19.64 s +2024-11-22 16:31:48.878145: +2024-11-22 16:31:48.879496: Epoch 5365 +2024-11-22 16:31:48.879637: Current learning rate: 0.00368 +2024-11-22 16:32:09.617013: train_loss -0.7961 +2024-11-22 16:32:09.623634: val_loss -0.788 +2024-11-22 16:32:09.623786: Pseudo dice [0.858] +2024-11-22 16:32:09.623912: Epoch time: 20.74 s +2024-11-22 16:32:10.664534: +2024-11-22 16:32:10.665826: Epoch 5366 +2024-11-22 16:32:10.665968: Current learning rate: 0.00368 +2024-11-22 16:32:30.476662: train_loss -0.7977 +2024-11-22 16:32:30.483560: val_loss -0.795 +2024-11-22 16:32:30.483694: Pseudo dice [0.8663] +2024-11-22 16:32:30.483806: Epoch time: 19.81 s +2024-11-22 16:32:31.475885: +2024-11-22 16:32:31.476353: Epoch 5367 +2024-11-22 16:32:31.476488: Current learning rate: 0.00368 +2024-11-22 16:32:52.084829: train_loss -0.7975 +2024-11-22 16:32:52.107928: val_loss -0.7853 +2024-11-22 16:32:52.108083: Pseudo dice [0.8623] +2024-11-22 16:32:52.108167: Epoch time: 20.61 s +2024-11-22 16:32:53.050177: +2024-11-22 16:32:53.051416: Epoch 5368 +2024-11-22 16:32:53.051554: Current learning rate: 0.00368 +2024-11-22 16:33:13.475545: train_loss -0.7919 +2024-11-22 16:33:13.482427: val_loss -0.7856 +2024-11-22 16:33:13.482553: Pseudo dice [0.8579] +2024-11-22 16:33:13.482670: Epoch time: 20.43 s +2024-11-22 16:33:14.468590: +2024-11-22 16:33:14.469321: Epoch 5369 +2024-11-22 16:33:14.469453: Current learning rate: 0.00368 +2024-11-22 16:33:34.443146: train_loss -0.7966 +2024-11-22 16:33:34.451144: val_loss -0.7691 +2024-11-22 16:33:34.451272: Pseudo dice [0.8526] +2024-11-22 16:33:34.451393: Epoch time: 19.98 s +2024-11-22 16:33:35.534670: +2024-11-22 16:33:35.536439: Epoch 5370 +2024-11-22 16:33:35.536562: Current learning rate: 0.00367 +2024-11-22 16:33:54.974112: train_loss -0.7975 +2024-11-22 16:33:54.995564: val_loss -0.7646 +2024-11-22 16:33:54.995894: Pseudo dice [0.8584] +2024-11-22 16:33:54.995997: Epoch time: 19.44 s +2024-11-22 16:33:56.094736: +2024-11-22 16:33:56.095492: Epoch 5371 +2024-11-22 16:33:56.095615: Current learning rate: 0.00367 +2024-11-22 16:34:14.859980: train_loss -0.7978 +2024-11-22 16:34:14.867143: val_loss -0.781 +2024-11-22 16:34:14.867280: Pseudo dice [0.8553] +2024-11-22 16:34:14.867363: Epoch time: 18.77 s +2024-11-22 16:34:16.219718: +2024-11-22 16:34:16.220030: Epoch 5372 +2024-11-22 16:34:16.220166: Current learning rate: 0.00367 +2024-11-22 16:34:34.842766: train_loss -0.7975 +2024-11-22 16:34:34.850051: val_loss -0.7467 +2024-11-22 16:34:34.850168: Pseudo dice [0.8488] +2024-11-22 16:34:34.850326: Epoch time: 18.62 s +2024-11-22 16:34:35.928372: +2024-11-22 16:34:35.928615: Epoch 5373 +2024-11-22 16:34:35.928741: Current learning rate: 0.00367 +2024-11-22 16:34:54.803727: train_loss -0.7877 +2024-11-22 16:34:54.808955: val_loss -0.7658 +2024-11-22 16:34:54.809112: Pseudo dice [0.8548] +2024-11-22 16:34:54.809226: Epoch time: 18.88 s +2024-11-22 16:34:55.681332: +2024-11-22 16:34:55.681545: Epoch 5374 +2024-11-22 16:34:55.681662: Current learning rate: 0.00367 +2024-11-22 16:35:14.437845: train_loss -0.7954 +2024-11-22 16:35:14.442639: val_loss -0.763 +2024-11-22 16:35:14.442840: Pseudo dice [0.857] +2024-11-22 16:35:14.442947: Epoch time: 18.76 s +2024-11-22 16:35:15.357682: +2024-11-22 16:35:15.357902: Epoch 5375 +2024-11-22 16:35:15.358025: Current learning rate: 0.00367 +2024-11-22 16:35:34.233735: train_loss -0.7844 +2024-11-22 16:35:34.236662: val_loss -0.7659 +2024-11-22 16:35:34.236792: Pseudo dice [0.842] +2024-11-22 16:35:34.236873: Epoch time: 18.88 s +2024-11-22 16:35:35.091858: +2024-11-22 16:35:35.092080: Epoch 5376 +2024-11-22 16:35:35.092201: Current learning rate: 0.00367 +2024-11-22 16:35:54.613118: train_loss -0.7891 +2024-11-22 16:35:54.613626: val_loss -0.7894 +2024-11-22 16:35:54.613735: Pseudo dice [0.8584] +2024-11-22 16:35:54.613827: Epoch time: 19.52 s +2024-11-22 16:35:55.470524: +2024-11-22 16:35:55.470716: Epoch 5377 +2024-11-22 16:35:55.470850: Current learning rate: 0.00367 +2024-11-22 16:36:13.523551: train_loss -0.8032 +2024-11-22 16:36:13.524146: val_loss -0.7524 +2024-11-22 16:36:13.524240: Pseudo dice [0.8524] +2024-11-22 16:36:13.524357: Epoch time: 18.05 s +2024-11-22 16:36:14.382772: +2024-11-22 16:36:14.382959: Epoch 5378 +2024-11-22 16:36:14.383081: Current learning rate: 0.00366 +2024-11-22 16:36:34.286192: train_loss -0.7877 +2024-11-22 16:36:34.293402: val_loss -0.7754 +2024-11-22 16:36:34.293539: Pseudo dice [0.8475] +2024-11-22 16:36:34.293633: Epoch time: 19.9 s +2024-11-22 16:36:35.311713: +2024-11-22 16:36:35.311918: Epoch 5379 +2024-11-22 16:36:35.312040: Current learning rate: 0.00366 +2024-11-22 16:36:54.512564: train_loss -0.792 +2024-11-22 16:36:54.515662: val_loss -0.761 +2024-11-22 16:36:54.515778: Pseudo dice [0.8504] +2024-11-22 16:36:54.515876: Epoch time: 19.2 s +2024-11-22 16:36:55.405941: +2024-11-22 16:36:55.406378: Epoch 5380 +2024-11-22 16:36:55.406507: Current learning rate: 0.00366 +2024-11-22 16:37:15.353413: train_loss -0.7855 +2024-11-22 16:37:15.357477: val_loss -0.7848 +2024-11-22 16:37:15.357611: Pseudo dice [0.8606] +2024-11-22 16:37:15.357702: Epoch time: 19.95 s +2024-11-22 16:37:16.227845: +2024-11-22 16:37:16.228303: Epoch 5381 +2024-11-22 16:37:16.228446: Current learning rate: 0.00366 +2024-11-22 16:37:36.016216: train_loss -0.8048 +2024-11-22 16:37:36.018836: val_loss -0.7831 +2024-11-22 16:37:36.018957: Pseudo dice [0.8573] +2024-11-22 16:37:36.019044: Epoch time: 19.79 s +2024-11-22 16:37:36.882528: +2024-11-22 16:37:36.883010: Epoch 5382 +2024-11-22 16:37:36.883133: Current learning rate: 0.00366 +2024-11-22 16:37:56.594685: train_loss -0.8005 +2024-11-22 16:37:56.600401: val_loss -0.7818 +2024-11-22 16:37:56.600531: Pseudo dice [0.8625] +2024-11-22 16:37:56.600626: Epoch time: 19.71 s +2024-11-22 16:37:57.555906: +2024-11-22 16:37:57.557679: Epoch 5383 +2024-11-22 16:37:57.557801: Current learning rate: 0.00366 +2024-11-22 16:38:17.668293: train_loss -0.7918 +2024-11-22 16:38:17.674085: val_loss -0.7351 +2024-11-22 16:38:17.674230: Pseudo dice [0.8329] +2024-11-22 16:38:17.674321: Epoch time: 20.11 s +2024-11-22 16:38:18.950504: +2024-11-22 16:38:18.952065: Epoch 5384 +2024-11-22 16:38:18.952194: Current learning rate: 0.00366 +2024-11-22 16:38:37.904752: train_loss -0.7986 +2024-11-22 16:38:37.910162: val_loss -0.7662 +2024-11-22 16:38:37.910294: Pseudo dice [0.8527] +2024-11-22 16:38:37.910392: Epoch time: 18.96 s +2024-11-22 16:38:38.797267: +2024-11-22 16:38:38.798021: Epoch 5385 +2024-11-22 16:38:38.798148: Current learning rate: 0.00366 +2024-11-22 16:38:58.242166: train_loss -0.7877 +2024-11-22 16:38:58.249096: val_loss -0.7507 +2024-11-22 16:38:58.249242: Pseudo dice [0.8571] +2024-11-22 16:38:58.249343: Epoch time: 19.45 s +2024-11-22 16:38:59.115410: +2024-11-22 16:38:59.116244: Epoch 5386 +2024-11-22 16:38:59.116378: Current learning rate: 0.00365 +2024-11-22 16:39:19.099173: train_loss -0.7819 +2024-11-22 16:39:19.115599: val_loss -0.7643 +2024-11-22 16:39:19.115752: Pseudo dice [0.8423] +2024-11-22 16:39:19.115849: Epoch time: 19.98 s +2024-11-22 16:39:19.985276: +2024-11-22 16:39:19.985916: Epoch 5387 +2024-11-22 16:39:19.986034: Current learning rate: 0.00365 +2024-11-22 16:39:39.665933: train_loss -0.7948 +2024-11-22 16:39:39.674117: val_loss -0.7648 +2024-11-22 16:39:39.674241: Pseudo dice [0.8565] +2024-11-22 16:39:39.674332: Epoch time: 19.68 s +2024-11-22 16:39:40.580553: +2024-11-22 16:39:40.583502: Epoch 5388 +2024-11-22 16:39:40.583631: Current learning rate: 0.00365 +2024-11-22 16:39:59.625820: train_loss -0.7919 +2024-11-22 16:39:59.635857: val_loss -0.7801 +2024-11-22 16:39:59.636005: Pseudo dice [0.8536] +2024-11-22 16:39:59.636102: Epoch time: 19.05 s +2024-11-22 16:40:00.514270: +2024-11-22 16:40:00.514738: Epoch 5389 +2024-11-22 16:40:00.514865: Current learning rate: 0.00365 +2024-11-22 16:40:20.502115: train_loss -0.7912 +2024-11-22 16:40:20.509387: val_loss -0.7849 +2024-11-22 16:40:20.509530: Pseudo dice [0.8501] +2024-11-22 16:40:20.509633: Epoch time: 19.99 s +2024-11-22 16:40:21.377447: +2024-11-22 16:40:21.378259: Epoch 5390 +2024-11-22 16:40:21.378393: Current learning rate: 0.00365 +2024-11-22 16:40:41.077022: train_loss -0.7945 +2024-11-22 16:40:41.089587: val_loss -0.7866 +2024-11-22 16:40:41.089740: Pseudo dice [0.8723] +2024-11-22 16:40:41.089841: Epoch time: 19.7 s +2024-11-22 16:40:42.088404: +2024-11-22 16:40:42.089874: Epoch 5391 +2024-11-22 16:40:42.090001: Current learning rate: 0.00365 +2024-11-22 16:41:01.647523: train_loss -0.7951 +2024-11-22 16:41:01.655394: val_loss -0.7704 +2024-11-22 16:41:01.655533: Pseudo dice [0.8587] +2024-11-22 16:41:01.655633: Epoch time: 19.56 s +2024-11-22 16:41:02.552147: +2024-11-22 16:41:02.553145: Epoch 5392 +2024-11-22 16:41:02.553359: Current learning rate: 0.00365 +2024-11-22 16:41:22.222884: train_loss -0.7927 +2024-11-22 16:41:22.230746: val_loss -0.7642 +2024-11-22 16:41:22.230892: Pseudo dice [0.8585] +2024-11-22 16:41:22.230999: Epoch time: 19.67 s +2024-11-22 16:41:23.168890: +2024-11-22 16:41:23.170878: Epoch 5393 +2024-11-22 16:41:23.171003: Current learning rate: 0.00365 +2024-11-22 16:41:43.328552: train_loss -0.7925 +2024-11-22 16:41:43.335416: val_loss -0.7632 +2024-11-22 16:41:43.335571: Pseudo dice [0.8467] +2024-11-22 16:41:43.335690: Epoch time: 20.16 s +2024-11-22 16:41:44.261896: +2024-11-22 16:41:44.262908: Epoch 5394 +2024-11-22 16:41:44.263035: Current learning rate: 0.00364 +2024-11-22 16:42:04.502110: train_loss -0.7949 +2024-11-22 16:42:04.506746: val_loss -0.7985 +2024-11-22 16:42:04.506898: Pseudo dice [0.8624] +2024-11-22 16:42:04.507001: Epoch time: 20.24 s +2024-11-22 16:42:05.394816: +2024-11-22 16:42:05.396877: Epoch 5395 +2024-11-22 16:42:05.397010: Current learning rate: 0.00364 +2024-11-22 16:42:25.774872: train_loss -0.8008 +2024-11-22 16:42:25.784297: val_loss -0.7887 +2024-11-22 16:42:25.784495: Pseudo dice [0.852] +2024-11-22 16:42:25.784593: Epoch time: 20.38 s +2024-11-22 16:42:27.091941: +2024-11-22 16:42:27.093280: Epoch 5396 +2024-11-22 16:42:27.093413: Current learning rate: 0.00364 +2024-11-22 16:42:45.656700: train_loss -0.7997 +2024-11-22 16:42:45.663823: val_loss -0.778 +2024-11-22 16:42:45.664046: Pseudo dice [0.8556] +2024-11-22 16:42:45.664233: Epoch time: 18.57 s +2024-11-22 16:42:46.873791: +2024-11-22 16:42:46.875631: Epoch 5397 +2024-11-22 16:42:46.875765: Current learning rate: 0.00364 +2024-11-22 16:43:06.782093: train_loss -0.7904 +2024-11-22 16:43:06.810512: val_loss -0.7842 +2024-11-22 16:43:06.810689: Pseudo dice [0.8579] +2024-11-22 16:43:06.810800: Epoch time: 19.91 s +2024-11-22 16:43:07.674668: +2024-11-22 16:43:07.676005: Epoch 5398 +2024-11-22 16:43:07.676142: Current learning rate: 0.00364 +2024-11-22 16:43:26.922044: train_loss -0.7988 +2024-11-22 16:43:26.931017: val_loss -0.7773 +2024-11-22 16:43:26.931164: Pseudo dice [0.854] +2024-11-22 16:43:26.931261: Epoch time: 19.25 s +2024-11-22 16:43:28.043960: +2024-11-22 16:43:28.045312: Epoch 5399 +2024-11-22 16:43:28.045449: Current learning rate: 0.00364 +2024-11-22 16:43:47.742946: train_loss -0.804 +2024-11-22 16:43:47.763112: val_loss -0.7787 +2024-11-22 16:43:47.763271: Pseudo dice [0.8413] +2024-11-22 16:43:47.763391: Epoch time: 19.7 s +2024-11-22 16:43:49.018788: +2024-11-22 16:43:49.020159: Epoch 5400 +2024-11-22 16:43:49.020289: Current learning rate: 0.00364 +2024-11-22 16:44:08.203426: train_loss -0.7939 +2024-11-22 16:44:08.206037: val_loss -0.7805 +2024-11-22 16:44:08.206155: Pseudo dice [0.8679] +2024-11-22 16:44:08.206251: Epoch time: 19.19 s +2024-11-22 16:44:09.079408: +2024-11-22 16:44:09.080891: Epoch 5401 +2024-11-22 16:44:09.081026: Current learning rate: 0.00364 +2024-11-22 16:44:29.113381: train_loss -0.7956 +2024-11-22 16:44:29.132358: val_loss -0.7844 +2024-11-22 16:44:29.132506: Pseudo dice [0.857] +2024-11-22 16:44:29.132606: Epoch time: 20.03 s +2024-11-22 16:44:30.194386: +2024-11-22 16:44:30.196250: Epoch 5402 +2024-11-22 16:44:30.196398: Current learning rate: 0.00363 +2024-11-22 16:44:49.474333: train_loss -0.8002 +2024-11-22 16:44:49.480106: val_loss -0.772 +2024-11-22 16:44:49.480238: Pseudo dice [0.8677] +2024-11-22 16:44:49.480328: Epoch time: 19.28 s +2024-11-22 16:44:50.539757: +2024-11-22 16:44:50.540549: Epoch 5403 +2024-11-22 16:44:50.540680: Current learning rate: 0.00363 +2024-11-22 16:45:10.227244: train_loss -0.7916 +2024-11-22 16:45:10.232582: val_loss -0.7652 +2024-11-22 16:45:10.232898: Pseudo dice [0.8459] +2024-11-22 16:45:10.233011: Epoch time: 19.69 s +2024-11-22 16:45:11.264080: +2024-11-22 16:45:11.265622: Epoch 5404 +2024-11-22 16:45:11.265762: Current learning rate: 0.00363 +2024-11-22 16:45:31.173010: train_loss -0.7736 +2024-11-22 16:45:31.181544: val_loss -0.7639 +2024-11-22 16:45:31.181674: Pseudo dice [0.8479] +2024-11-22 16:45:31.181766: Epoch time: 19.91 s +2024-11-22 16:45:32.120138: +2024-11-22 16:45:32.122205: Epoch 5405 +2024-11-22 16:45:32.122384: Current learning rate: 0.00363 +2024-11-22 16:45:52.435609: train_loss -0.7904 +2024-11-22 16:45:52.450298: val_loss -0.7758 +2024-11-22 16:45:52.450443: Pseudo dice [0.8609] +2024-11-22 16:45:52.450543: Epoch time: 20.32 s +2024-11-22 16:45:53.319626: +2024-11-22 16:45:53.320737: Epoch 5406 +2024-11-22 16:45:53.320863: Current learning rate: 0.00363 +2024-11-22 16:46:13.088349: train_loss -0.7863 +2024-11-22 16:46:13.094422: val_loss -0.7767 +2024-11-22 16:46:13.094549: Pseudo dice [0.8629] +2024-11-22 16:46:13.094707: Epoch time: 19.76 s +2024-11-22 16:46:13.958749: +2024-11-22 16:46:13.959528: Epoch 5407 +2024-11-22 16:46:13.959648: Current learning rate: 0.00363 +2024-11-22 16:46:33.725165: train_loss -0.7957 +2024-11-22 16:46:33.730831: val_loss -0.7664 +2024-11-22 16:46:33.731023: Pseudo dice [0.8557] +2024-11-22 16:46:33.731158: Epoch time: 19.77 s +2024-11-22 16:46:34.593150: +2024-11-22 16:46:34.594939: Epoch 5408 +2024-11-22 16:46:34.595086: Current learning rate: 0.00363 +2024-11-22 16:46:54.487808: train_loss -0.8011 +2024-11-22 16:46:54.504076: val_loss -0.7597 +2024-11-22 16:46:54.504237: Pseudo dice [0.8411] +2024-11-22 16:46:54.504337: Epoch time: 19.9 s +2024-11-22 16:46:55.397760: +2024-11-22 16:46:55.398671: Epoch 5409 +2024-11-22 16:46:55.398810: Current learning rate: 0.00363 +2024-11-22 16:47:15.304872: train_loss -0.7803 +2024-11-22 16:47:15.311418: val_loss -0.7674 +2024-11-22 16:47:15.311550: Pseudo dice [0.8442] +2024-11-22 16:47:15.311654: Epoch time: 19.91 s +2024-11-22 16:47:16.219006: +2024-11-22 16:47:16.219470: Epoch 5410 +2024-11-22 16:47:16.219614: Current learning rate: 0.00362 +2024-11-22 16:47:36.055952: train_loss -0.7899 +2024-11-22 16:47:36.070053: val_loss -0.7778 +2024-11-22 16:47:36.070236: Pseudo dice [0.8549] +2024-11-22 16:47:36.070345: Epoch time: 19.84 s +2024-11-22 16:47:37.035539: +2024-11-22 16:47:37.036631: Epoch 5411 +2024-11-22 16:47:37.036763: Current learning rate: 0.00362 +2024-11-22 16:47:55.586186: train_loss -0.7945 +2024-11-22 16:47:55.597802: val_loss -0.7695 +2024-11-22 16:47:55.597943: Pseudo dice [0.8551] +2024-11-22 16:47:55.598082: Epoch time: 18.54 s +2024-11-22 16:47:56.782601: +2024-11-22 16:47:56.784269: Epoch 5412 +2024-11-22 16:47:56.784404: Current learning rate: 0.00362 +2024-11-22 16:48:16.339301: train_loss -0.7899 +2024-11-22 16:48:16.348865: val_loss -0.77 +2024-11-22 16:48:16.349114: Pseudo dice [0.8586] +2024-11-22 16:48:16.349212: Epoch time: 19.56 s +2024-11-22 16:48:17.296766: +2024-11-22 16:48:17.298572: Epoch 5413 +2024-11-22 16:48:17.298697: Current learning rate: 0.00362 +2024-11-22 16:48:36.813591: train_loss -0.7878 +2024-11-22 16:48:36.819557: val_loss -0.7885 +2024-11-22 16:48:36.819680: Pseudo dice [0.8574] +2024-11-22 16:48:36.819781: Epoch time: 19.52 s +2024-11-22 16:48:37.746376: +2024-11-22 16:48:37.747737: Epoch 5414 +2024-11-22 16:48:37.747867: Current learning rate: 0.00362 +2024-11-22 16:48:58.229707: train_loss -0.786 +2024-11-22 16:48:58.236340: val_loss -0.7725 +2024-11-22 16:48:58.236485: Pseudo dice [0.8634] +2024-11-22 16:48:58.236603: Epoch time: 20.48 s +2024-11-22 16:48:59.197154: +2024-11-22 16:48:59.198955: Epoch 5415 +2024-11-22 16:48:59.199104: Current learning rate: 0.00362 +2024-11-22 16:49:18.771995: train_loss -0.7924 +2024-11-22 16:49:18.785714: val_loss -0.7641 +2024-11-22 16:49:18.785860: Pseudo dice [0.8559] +2024-11-22 16:49:18.785960: Epoch time: 19.58 s +2024-11-22 16:49:19.743639: +2024-11-22 16:49:19.746210: Epoch 5416 +2024-11-22 16:49:19.746341: Current learning rate: 0.00362 +2024-11-22 16:49:38.935050: train_loss -0.8066 +2024-11-22 16:49:38.937457: val_loss -0.7887 +2024-11-22 16:49:38.937568: Pseudo dice [0.8615] +2024-11-22 16:49:38.937664: Epoch time: 19.19 s +2024-11-22 16:49:39.869000: +2024-11-22 16:49:39.870280: Epoch 5417 +2024-11-22 16:49:39.870423: Current learning rate: 0.00362 +2024-11-22 16:49:59.668778: train_loss -0.8082 +2024-11-22 16:49:59.675860: val_loss -0.7697 +2024-11-22 16:49:59.675980: Pseudo dice [0.8652] +2024-11-22 16:49:59.676105: Epoch time: 19.8 s +2024-11-22 16:50:00.672399: +2024-11-22 16:50:00.673728: Epoch 5418 +2024-11-22 16:50:00.673862: Current learning rate: 0.00361 +2024-11-22 16:50:19.678508: train_loss -0.7951 +2024-11-22 16:50:19.685844: val_loss -0.7754 +2024-11-22 16:50:19.685974: Pseudo dice [0.8583] +2024-11-22 16:50:19.686128: Epoch time: 19.01 s +2024-11-22 16:50:21.047364: +2024-11-22 16:50:21.049505: Epoch 5419 +2024-11-22 16:50:21.049677: Current learning rate: 0.00361 +2024-11-22 16:50:40.423490: train_loss -0.8046 +2024-11-22 16:50:40.439512: val_loss -0.7788 +2024-11-22 16:50:40.439660: Pseudo dice [0.8505] +2024-11-22 16:50:40.439773: Epoch time: 19.38 s +2024-11-22 16:50:41.337438: +2024-11-22 16:50:41.339017: Epoch 5420 +2024-11-22 16:50:41.339162: Current learning rate: 0.00361 +2024-11-22 16:51:00.289369: train_loss -0.8042 +2024-11-22 16:51:00.306849: val_loss -0.7985 +2024-11-22 16:51:00.306988: Pseudo dice [0.8595] +2024-11-22 16:51:00.307111: Epoch time: 18.95 s +2024-11-22 16:51:01.256791: +2024-11-22 16:51:01.257225: Epoch 5421 +2024-11-22 16:51:01.257356: Current learning rate: 0.00361 +2024-11-22 16:51:21.888962: train_loss -0.7897 +2024-11-22 16:51:21.907119: val_loss -0.7688 +2024-11-22 16:51:21.907289: Pseudo dice [0.8575] +2024-11-22 16:51:21.907406: Epoch time: 20.63 s +2024-11-22 16:51:22.813580: +2024-11-22 16:51:22.815506: Epoch 5422 +2024-11-22 16:51:22.815633: Current learning rate: 0.00361 +2024-11-22 16:51:41.428556: train_loss -0.8004 +2024-11-22 16:51:41.442535: val_loss -0.7697 +2024-11-22 16:51:41.442710: Pseudo dice [0.8496] +2024-11-22 16:51:41.442816: Epoch time: 18.62 s +2024-11-22 16:51:42.568785: +2024-11-22 16:51:42.570358: Epoch 5423 +2024-11-22 16:51:42.570489: Current learning rate: 0.00361 +2024-11-22 16:52:01.433801: train_loss -0.7943 +2024-11-22 16:52:01.446750: val_loss -0.7654 +2024-11-22 16:52:01.446894: Pseudo dice [0.852] +2024-11-22 16:52:01.446985: Epoch time: 18.87 s +2024-11-22 16:52:02.373122: +2024-11-22 16:52:02.374620: Epoch 5424 +2024-11-22 16:52:02.374772: Current learning rate: 0.00361 +2024-11-22 16:52:21.615607: train_loss -0.7951 +2024-11-22 16:52:21.621253: val_loss -0.7568 +2024-11-22 16:52:21.621429: Pseudo dice [0.8507] +2024-11-22 16:52:21.621516: Epoch time: 19.24 s +2024-11-22 16:52:22.575088: +2024-11-22 16:52:22.576284: Epoch 5425 +2024-11-22 16:52:22.576406: Current learning rate: 0.00361 +2024-11-22 16:52:42.121454: train_loss -0.7787 +2024-11-22 16:52:42.132967: val_loss -0.7677 +2024-11-22 16:52:42.133109: Pseudo dice [0.8507] +2024-11-22 16:52:42.133216: Epoch time: 19.55 s +2024-11-22 16:52:43.027704: +2024-11-22 16:52:43.029172: Epoch 5426 +2024-11-22 16:52:43.029307: Current learning rate: 0.0036 +2024-11-22 16:53:02.517028: train_loss -0.7843 +2024-11-22 16:53:02.519724: val_loss -0.7696 +2024-11-22 16:53:02.519858: Pseudo dice [0.8504] +2024-11-22 16:53:02.519958: Epoch time: 19.49 s +2024-11-22 16:53:03.390150: +2024-11-22 16:53:03.390924: Epoch 5427 +2024-11-22 16:53:03.391050: Current learning rate: 0.0036 +2024-11-22 16:53:24.143932: train_loss -0.7975 +2024-11-22 16:53:24.154911: val_loss -0.7926 +2024-11-22 16:53:24.155069: Pseudo dice [0.8488] +2024-11-22 16:53:24.155158: Epoch time: 20.75 s +2024-11-22 16:53:25.179579: +2024-11-22 16:53:25.181406: Epoch 5428 +2024-11-22 16:53:25.181540: Current learning rate: 0.0036 +2024-11-22 16:53:44.348755: train_loss -0.7923 +2024-11-22 16:53:44.355017: val_loss -0.764 +2024-11-22 16:53:44.355204: Pseudo dice [0.8426] +2024-11-22 16:53:44.355323: Epoch time: 19.17 s +2024-11-22 16:53:45.295392: +2024-11-22 16:53:45.297335: Epoch 5429 +2024-11-22 16:53:45.297475: Current learning rate: 0.0036 +2024-11-22 16:54:05.419592: train_loss -0.803 +2024-11-22 16:54:05.427527: val_loss -0.786 +2024-11-22 16:54:05.430603: Pseudo dice [0.8672] +2024-11-22 16:54:05.430717: Epoch time: 20.13 s +2024-11-22 16:54:06.403461: +2024-11-22 16:54:06.404792: Epoch 5430 +2024-11-22 16:54:06.404928: Current learning rate: 0.0036 +2024-11-22 16:54:26.032477: train_loss -0.7998 +2024-11-22 16:54:26.042346: val_loss -0.7827 +2024-11-22 16:54:26.042490: Pseudo dice [0.8574] +2024-11-22 16:54:26.042602: Epoch time: 19.63 s +2024-11-22 16:54:27.580301: +2024-11-22 16:54:27.581608: Epoch 5431 +2024-11-22 16:54:27.581729: Current learning rate: 0.0036 +2024-11-22 16:54:47.058816: train_loss -0.795 +2024-11-22 16:54:47.061054: val_loss -0.7561 +2024-11-22 16:54:47.061189: Pseudo dice [0.8459] +2024-11-22 16:54:47.061283: Epoch time: 19.48 s +2024-11-22 16:54:47.938787: +2024-11-22 16:54:47.939573: Epoch 5432 +2024-11-22 16:54:47.939715: Current learning rate: 0.0036 +2024-11-22 16:55:06.969211: train_loss -0.7934 +2024-11-22 16:55:06.979011: val_loss -0.7817 +2024-11-22 16:55:06.979158: Pseudo dice [0.8508] +2024-11-22 16:55:06.979249: Epoch time: 19.03 s +2024-11-22 16:55:07.858232: +2024-11-22 16:55:07.859140: Epoch 5433 +2024-11-22 16:55:07.859271: Current learning rate: 0.0036 +2024-11-22 16:55:27.842225: train_loss -0.7767 +2024-11-22 16:55:27.862609: val_loss -0.7566 +2024-11-22 16:55:27.862758: Pseudo dice [0.8548] +2024-11-22 16:55:27.862853: Epoch time: 19.98 s +2024-11-22 16:55:28.807326: +2024-11-22 16:55:28.808069: Epoch 5434 +2024-11-22 16:55:28.808191: Current learning rate: 0.00359 +2024-11-22 16:55:49.666571: train_loss -0.7864 +2024-11-22 16:55:49.687777: val_loss -0.7694 +2024-11-22 16:55:49.687964: Pseudo dice [0.8645] +2024-11-22 16:55:49.688102: Epoch time: 20.86 s +2024-11-22 16:55:50.619497: +2024-11-22 16:55:50.621164: Epoch 5435 +2024-11-22 16:55:50.621287: Current learning rate: 0.00359 +2024-11-22 16:56:09.486422: train_loss -0.7873 +2024-11-22 16:56:09.498284: val_loss -0.7773 +2024-11-22 16:56:09.498441: Pseudo dice [0.8659] +2024-11-22 16:56:09.498557: Epoch time: 18.87 s +2024-11-22 16:56:10.449642: +2024-11-22 16:56:10.450140: Epoch 5436 +2024-11-22 16:56:10.450257: Current learning rate: 0.00359 +2024-11-22 16:56:30.055639: train_loss -0.7902 +2024-11-22 16:56:30.059433: val_loss -0.7727 +2024-11-22 16:56:30.059597: Pseudo dice [0.8573] +2024-11-22 16:56:30.059712: Epoch time: 19.61 s +2024-11-22 16:56:30.933009: +2024-11-22 16:56:30.934729: Epoch 5437 +2024-11-22 16:56:30.934865: Current learning rate: 0.00359 +2024-11-22 16:56:49.750677: train_loss -0.7957 +2024-11-22 16:56:49.771146: val_loss -0.7919 +2024-11-22 16:56:49.771308: Pseudo dice [0.8482] +2024-11-22 16:56:49.771449: Epoch time: 18.82 s +2024-11-22 16:56:50.798023: +2024-11-22 16:56:50.798954: Epoch 5438 +2024-11-22 16:56:50.799117: Current learning rate: 0.00359 +2024-11-22 16:57:11.560508: train_loss -0.789 +2024-11-22 16:57:11.569397: val_loss -0.7783 +2024-11-22 16:57:11.569553: Pseudo dice [0.8507] +2024-11-22 16:57:11.569665: Epoch time: 20.76 s +2024-11-22 16:57:12.690460: +2024-11-22 16:57:12.691931: Epoch 5439 +2024-11-22 16:57:12.692092: Current learning rate: 0.00359 +2024-11-22 16:57:32.742239: train_loss -0.7903 +2024-11-22 16:57:32.750595: val_loss -0.7653 +2024-11-22 16:57:32.750749: Pseudo dice [0.8603] +2024-11-22 16:57:32.750852: Epoch time: 20.05 s +2024-11-22 16:57:33.776499: +2024-11-22 16:57:33.778116: Epoch 5440 +2024-11-22 16:57:33.778246: Current learning rate: 0.00359 +2024-11-22 16:57:52.002306: train_loss -0.7938 +2024-11-22 16:57:52.022712: val_loss -0.7675 +2024-11-22 16:57:52.022845: Pseudo dice [0.862] +2024-11-22 16:57:52.022936: Epoch time: 18.23 s +2024-11-22 16:57:52.981561: +2024-11-22 16:57:52.982105: Epoch 5441 +2024-11-22 16:57:52.982239: Current learning rate: 0.00358 +2024-11-22 16:58:12.742279: train_loss -0.8025 +2024-11-22 16:58:12.748266: val_loss -0.7576 +2024-11-22 16:58:12.748403: Pseudo dice [0.851] +2024-11-22 16:58:12.762804: Epoch time: 19.76 s +2024-11-22 16:58:13.817697: +2024-11-22 16:58:13.818846: Epoch 5442 +2024-11-22 16:58:13.818969: Current learning rate: 0.00358 +2024-11-22 16:58:33.507545: train_loss -0.7902 +2024-11-22 16:58:33.512870: val_loss -0.7911 +2024-11-22 16:58:33.513014: Pseudo dice [0.8581] +2024-11-22 16:58:33.513134: Epoch time: 19.69 s +2024-11-22 16:58:34.824070: +2024-11-22 16:58:34.826108: Epoch 5443 +2024-11-22 16:58:34.826244: Current learning rate: 0.00358 +2024-11-22 16:58:54.164449: train_loss -0.7947 +2024-11-22 16:58:54.171721: val_loss -0.7792 +2024-11-22 16:58:54.171885: Pseudo dice [0.8669] +2024-11-22 16:58:54.172003: Epoch time: 19.34 s +2024-11-22 16:58:55.058211: +2024-11-22 16:58:55.059021: Epoch 5444 +2024-11-22 16:58:55.059154: Current learning rate: 0.00358 +2024-11-22 16:59:14.356995: train_loss -0.7881 +2024-11-22 16:59:14.359881: val_loss -0.7694 +2024-11-22 16:59:14.360018: Pseudo dice [0.828] +2024-11-22 16:59:14.360132: Epoch time: 19.3 s +2024-11-22 16:59:15.240465: +2024-11-22 16:59:15.240930: Epoch 5445 +2024-11-22 16:59:15.241054: Current learning rate: 0.00358 +2024-11-22 16:59:35.922274: train_loss -0.7722 +2024-11-22 16:59:35.925356: val_loss -0.7838 +2024-11-22 16:59:35.925493: Pseudo dice [0.8607] +2024-11-22 16:59:35.925610: Epoch time: 20.68 s +2024-11-22 16:59:36.789287: +2024-11-22 16:59:36.790750: Epoch 5446 +2024-11-22 16:59:36.790887: Current learning rate: 0.00358 +2024-11-22 16:59:55.491345: train_loss -0.7885 +2024-11-22 16:59:55.493082: val_loss -0.7805 +2024-11-22 16:59:55.493189: Pseudo dice [0.8502] +2024-11-22 16:59:55.493294: Epoch time: 18.7 s +2024-11-22 16:59:56.357788: +2024-11-22 16:59:56.357991: Epoch 5447 +2024-11-22 16:59:56.358110: Current learning rate: 0.00358 +2024-11-22 17:00:15.306661: train_loss -0.7901 +2024-11-22 17:00:15.314198: val_loss -0.7577 +2024-11-22 17:00:15.314345: Pseudo dice [0.8467] +2024-11-22 17:00:15.314443: Epoch time: 18.95 s +2024-11-22 17:00:16.345674: +2024-11-22 17:00:16.345876: Epoch 5448 +2024-11-22 17:00:16.346002: Current learning rate: 0.00358 +2024-11-22 17:00:35.832685: train_loss -0.789 +2024-11-22 17:00:35.835002: val_loss -0.7782 +2024-11-22 17:00:35.835162: Pseudo dice [0.8538] +2024-11-22 17:00:35.835257: Epoch time: 19.49 s +2024-11-22 17:00:36.698157: +2024-11-22 17:00:36.698373: Epoch 5449 +2024-11-22 17:00:36.698486: Current learning rate: 0.00357 +2024-11-22 17:00:55.497285: train_loss -0.7879 +2024-11-22 17:00:55.497763: val_loss -0.7894 +2024-11-22 17:00:55.497846: Pseudo dice [0.8699] +2024-11-22 17:00:55.497927: Epoch time: 18.8 s +2024-11-22 17:00:56.638585: +2024-11-22 17:00:56.638827: Epoch 5450 +2024-11-22 17:00:56.638963: Current learning rate: 0.00357 +2024-11-22 17:01:15.149474: train_loss -0.7989 +2024-11-22 17:01:15.154068: val_loss -0.779 +2024-11-22 17:01:15.154218: Pseudo dice [0.847] +2024-11-22 17:01:15.154361: Epoch time: 18.51 s +2024-11-22 17:01:16.019058: +2024-11-22 17:01:16.019277: Epoch 5451 +2024-11-22 17:01:16.019397: Current learning rate: 0.00357 +2024-11-22 17:01:34.501097: train_loss -0.7841 +2024-11-22 17:01:34.505890: val_loss -0.7712 +2024-11-22 17:01:34.506047: Pseudo dice [0.8509] +2024-11-22 17:01:34.506135: Epoch time: 18.48 s +2024-11-22 17:01:35.384642: +2024-11-22 17:01:35.384859: Epoch 5452 +2024-11-22 17:01:35.385007: Current learning rate: 0.00357 +2024-11-22 17:01:53.617969: train_loss -0.7951 +2024-11-22 17:01:53.619246: val_loss -0.794 +2024-11-22 17:01:53.619395: Pseudo dice [0.8588] +2024-11-22 17:01:53.619509: Epoch time: 18.23 s +2024-11-22 17:01:54.482817: +2024-11-22 17:01:54.483021: Epoch 5453 +2024-11-22 17:01:54.483145: Current learning rate: 0.00357 +2024-11-22 17:02:13.414888: train_loss -0.7891 +2024-11-22 17:02:13.427713: val_loss -0.7684 +2024-11-22 17:02:13.427852: Pseudo dice [0.8453] +2024-11-22 17:02:13.427953: Epoch time: 18.93 s +2024-11-22 17:02:14.547923: +2024-11-22 17:02:14.548122: Epoch 5454 +2024-11-22 17:02:14.548249: Current learning rate: 0.00357 +2024-11-22 17:02:32.608590: train_loss -0.7736 +2024-11-22 17:02:32.639735: val_loss -0.7714 +2024-11-22 17:02:32.639937: Pseudo dice [0.8506] +2024-11-22 17:02:32.640057: Epoch time: 18.06 s +2024-11-22 17:02:33.606756: +2024-11-22 17:02:33.606975: Epoch 5455 +2024-11-22 17:02:33.607099: Current learning rate: 0.00357 +2024-11-22 17:02:53.237797: train_loss -0.7887 +2024-11-22 17:02:53.242489: val_loss -0.7484 +2024-11-22 17:02:53.242604: Pseudo dice [0.8485] +2024-11-22 17:02:53.242702: Epoch time: 19.63 s +2024-11-22 17:02:54.167836: +2024-11-22 17:02:54.168939: Epoch 5456 +2024-11-22 17:02:54.169068: Current learning rate: 0.00357 +2024-11-22 17:03:12.030961: train_loss -0.7886 +2024-11-22 17:03:12.037628: val_loss -0.7793 +2024-11-22 17:03:12.037784: Pseudo dice [0.8547] +2024-11-22 17:03:12.037886: Epoch time: 17.86 s +2024-11-22 17:03:12.903554: +2024-11-22 17:03:12.904354: Epoch 5457 +2024-11-22 17:03:12.904495: Current learning rate: 0.00356 +2024-11-22 17:03:32.854243: train_loss -0.7841 +2024-11-22 17:03:32.858735: val_loss -0.7816 +2024-11-22 17:03:32.858881: Pseudo dice [0.866] +2024-11-22 17:03:32.858974: Epoch time: 19.95 s +2024-11-22 17:03:33.802907: +2024-11-22 17:03:33.804649: Epoch 5458 +2024-11-22 17:03:33.804776: Current learning rate: 0.00356 +2024-11-22 17:03:53.952934: train_loss -0.7848 +2024-11-22 17:03:53.959037: val_loss -0.771 +2024-11-22 17:03:53.959182: Pseudo dice [0.8506] +2024-11-22 17:03:53.959283: Epoch time: 20.15 s +2024-11-22 17:03:54.835568: +2024-11-22 17:03:54.837207: Epoch 5459 +2024-11-22 17:03:54.837337: Current learning rate: 0.00356 +2024-11-22 17:04:15.031313: train_loss -0.7899 +2024-11-22 17:04:15.038434: val_loss -0.7943 +2024-11-22 17:04:15.038561: Pseudo dice [0.8678] +2024-11-22 17:04:15.038669: Epoch time: 20.2 s +2024-11-22 17:04:16.017743: +2024-11-22 17:04:16.019270: Epoch 5460 +2024-11-22 17:04:16.019398: Current learning rate: 0.00356 +2024-11-22 17:04:35.113477: train_loss -0.8017 +2024-11-22 17:04:35.118631: val_loss -0.7861 +2024-11-22 17:04:35.118781: Pseudo dice [0.8738] +2024-11-22 17:04:35.118876: Epoch time: 19.1 s +2024-11-22 17:04:35.980256: +2024-11-22 17:04:35.981314: Epoch 5461 +2024-11-22 17:04:35.981486: Current learning rate: 0.00356 +2024-11-22 17:04:55.979832: train_loss -0.7977 +2024-11-22 17:04:55.985105: val_loss -0.7812 +2024-11-22 17:04:55.985255: Pseudo dice [0.8507] +2024-11-22 17:04:55.985359: Epoch time: 20.0 s +2024-11-22 17:04:56.939394: +2024-11-22 17:04:56.941073: Epoch 5462 +2024-11-22 17:04:56.941195: Current learning rate: 0.00356 +2024-11-22 17:05:16.046493: train_loss -0.7999 +2024-11-22 17:05:16.054309: val_loss -0.769 +2024-11-22 17:05:16.054441: Pseudo dice [0.8551] +2024-11-22 17:05:16.054554: Epoch time: 19.11 s +2024-11-22 17:05:16.976754: +2024-11-22 17:05:16.978354: Epoch 5463 +2024-11-22 17:05:16.978490: Current learning rate: 0.00356 +2024-11-22 17:05:36.570065: train_loss -0.799 +2024-11-22 17:05:36.576381: val_loss -0.7847 +2024-11-22 17:05:36.576514: Pseudo dice [0.8759] +2024-11-22 17:05:36.576633: Epoch time: 19.59 s +2024-11-22 17:05:37.615594: +2024-11-22 17:05:37.617019: Epoch 5464 +2024-11-22 17:05:37.617150: Current learning rate: 0.00356 +2024-11-22 17:05:57.115291: train_loss -0.7948 +2024-11-22 17:05:57.124837: val_loss -0.7834 +2024-11-22 17:05:57.124988: Pseudo dice [0.8706] +2024-11-22 17:05:57.125108: Epoch time: 19.5 s +2024-11-22 17:05:57.125199: Yayy! New best EMA pseudo Dice: 0.8595 +2024-11-22 17:05:58.597674: +2024-11-22 17:05:58.599644: Epoch 5465 +2024-11-22 17:05:58.599779: Current learning rate: 0.00355 +2024-11-22 17:06:18.658345: train_loss -0.7929 +2024-11-22 17:06:18.667604: val_loss -0.7724 +2024-11-22 17:06:18.667759: Pseudo dice [0.8594] +2024-11-22 17:06:18.667855: Epoch time: 20.06 s +2024-11-22 17:06:19.965594: +2024-11-22 17:06:19.966712: Epoch 5466 +2024-11-22 17:06:19.966841: Current learning rate: 0.00355 +2024-11-22 17:06:40.191700: train_loss -0.8062 +2024-11-22 17:06:40.197488: val_loss -0.7886 +2024-11-22 17:06:40.197632: Pseudo dice [0.8625] +2024-11-22 17:06:40.197735: Epoch time: 20.23 s +2024-11-22 17:06:40.198054: Yayy! New best EMA pseudo Dice: 0.8598 +2024-11-22 17:06:41.653610: +2024-11-22 17:06:41.655215: Epoch 5467 +2024-11-22 17:06:41.655343: Current learning rate: 0.00355 +2024-11-22 17:07:02.297950: train_loss -0.8014 +2024-11-22 17:07:02.304802: val_loss -0.7762 +2024-11-22 17:07:02.305012: Pseudo dice [0.8644] +2024-11-22 17:07:02.305128: Epoch time: 20.65 s +2024-11-22 17:07:02.305208: Yayy! New best EMA pseudo Dice: 0.8603 +2024-11-22 17:07:03.488662: +2024-11-22 17:07:03.490026: Epoch 5468 +2024-11-22 17:07:03.490171: Current learning rate: 0.00355 +2024-11-22 17:07:23.730960: train_loss -0.7907 +2024-11-22 17:07:23.738590: val_loss -0.7821 +2024-11-22 17:07:23.738729: Pseudo dice [0.8428] +2024-11-22 17:07:23.738829: Epoch time: 20.24 s +2024-11-22 17:07:24.630075: +2024-11-22 17:07:24.630828: Epoch 5469 +2024-11-22 17:07:24.630946: Current learning rate: 0.00355 +2024-11-22 17:07:44.723632: train_loss -0.7999 +2024-11-22 17:07:44.734689: val_loss -0.7674 +2024-11-22 17:07:44.734857: Pseudo dice [0.8569] +2024-11-22 17:07:44.734966: Epoch time: 20.09 s +2024-11-22 17:07:45.618231: +2024-11-22 17:07:45.619963: Epoch 5470 +2024-11-22 17:07:45.620105: Current learning rate: 0.00355 +2024-11-22 17:08:04.041833: train_loss -0.7972 +2024-11-22 17:08:04.049670: val_loss -0.7911 +2024-11-22 17:08:04.049807: Pseudo dice [0.8719] +2024-11-22 17:08:04.049913: Epoch time: 18.42 s +2024-11-22 17:08:04.943975: +2024-11-22 17:08:04.944475: Epoch 5471 +2024-11-22 17:08:04.944607: Current learning rate: 0.00355 +2024-11-22 17:08:25.250469: train_loss -0.8068 +2024-11-22 17:08:25.262093: val_loss -0.7829 +2024-11-22 17:08:25.262281: Pseudo dice [0.8563] +2024-11-22 17:08:25.262396: Epoch time: 20.31 s +2024-11-22 17:08:26.214097: +2024-11-22 17:08:26.215731: Epoch 5472 +2024-11-22 17:08:26.215874: Current learning rate: 0.00355 +2024-11-22 17:08:46.460499: train_loss -0.8057 +2024-11-22 17:08:46.467662: val_loss -0.7839 +2024-11-22 17:08:46.467804: Pseudo dice [0.8559] +2024-11-22 17:08:46.467920: Epoch time: 20.25 s +2024-11-22 17:08:47.460186: +2024-11-22 17:08:47.462064: Epoch 5473 +2024-11-22 17:08:47.462229: Current learning rate: 0.00354 +2024-11-22 17:09:06.992443: train_loss -0.8006 +2024-11-22 17:09:07.000512: val_loss -0.7927 +2024-11-22 17:09:07.000645: Pseudo dice [0.8671] +2024-11-22 17:09:07.000961: Epoch time: 19.53 s +2024-11-22 17:09:07.921679: +2024-11-22 17:09:07.923056: Epoch 5474 +2024-11-22 17:09:07.923191: Current learning rate: 0.00354 +2024-11-22 17:09:27.108742: train_loss -0.8012 +2024-11-22 17:09:27.113973: val_loss -0.7737 +2024-11-22 17:09:27.114112: Pseudo dice [0.8664] +2024-11-22 17:09:27.114214: Epoch time: 19.19 s +2024-11-22 17:09:27.114290: Yayy! New best EMA pseudo Dice: 0.8605 +2024-11-22 17:09:28.302880: +2024-11-22 17:09:28.305050: Epoch 5475 +2024-11-22 17:09:28.305203: Current learning rate: 0.00354 +2024-11-22 17:09:49.193268: train_loss -0.8039 +2024-11-22 17:09:49.206469: val_loss -0.7753 +2024-11-22 17:09:49.206626: Pseudo dice [0.8615] +2024-11-22 17:09:49.206736: Epoch time: 20.89 s +2024-11-22 17:09:49.206810: Yayy! New best EMA pseudo Dice: 0.8606 +2024-11-22 17:09:50.422729: +2024-11-22 17:09:50.424577: Epoch 5476 +2024-11-22 17:09:50.424714: Current learning rate: 0.00354 +2024-11-22 17:10:09.757849: train_loss -0.7977 +2024-11-22 17:10:09.776615: val_loss -0.784 +2024-11-22 17:10:09.776752: Pseudo dice [0.8511] +2024-11-22 17:10:09.776851: Epoch time: 19.34 s +2024-11-22 17:10:11.119670: +2024-11-22 17:10:11.120120: Epoch 5477 +2024-11-22 17:10:11.120249: Current learning rate: 0.00354 +2024-11-22 17:10:31.224857: train_loss -0.7965 +2024-11-22 17:10:31.226895: val_loss -0.7702 +2024-11-22 17:10:31.227002: Pseudo dice [0.8489] +2024-11-22 17:10:31.227115: Epoch time: 20.11 s +2024-11-22 17:10:32.104678: +2024-11-22 17:10:32.105467: Epoch 5478 +2024-11-22 17:10:32.105600: Current learning rate: 0.00354 +2024-11-22 17:10:51.809580: train_loss -0.7979 +2024-11-22 17:10:51.815757: val_loss -0.7783 +2024-11-22 17:10:51.815929: Pseudo dice [0.8531] +2024-11-22 17:10:51.816237: Epoch time: 19.71 s +2024-11-22 17:10:52.694424: +2024-11-22 17:10:52.696045: Epoch 5479 +2024-11-22 17:10:52.696193: Current learning rate: 0.00354 +2024-11-22 17:11:12.648436: train_loss -0.8033 +2024-11-22 17:11:12.661981: val_loss -0.7868 +2024-11-22 17:11:12.662126: Pseudo dice [0.86] +2024-11-22 17:11:12.662227: Epoch time: 19.95 s +2024-11-22 17:11:13.610103: +2024-11-22 17:11:13.610890: Epoch 5480 +2024-11-22 17:11:13.611017: Current learning rate: 0.00354 +2024-11-22 17:11:33.051638: train_loss -0.7945 +2024-11-22 17:11:33.062213: val_loss -0.7784 +2024-11-22 17:11:33.062339: Pseudo dice [0.8531] +2024-11-22 17:11:33.062422: Epoch time: 19.44 s +2024-11-22 17:11:34.058017: +2024-11-22 17:11:34.059493: Epoch 5481 +2024-11-22 17:11:34.059616: Current learning rate: 0.00353 +2024-11-22 17:11:54.351617: train_loss -0.8007 +2024-11-22 17:11:54.359755: val_loss -0.7548 +2024-11-22 17:11:54.359911: Pseudo dice [0.8522] +2024-11-22 17:11:54.360075: Epoch time: 20.29 s +2024-11-22 17:11:55.241763: +2024-11-22 17:11:55.243835: Epoch 5482 +2024-11-22 17:11:55.243986: Current learning rate: 0.00353 +2024-11-22 17:12:14.779319: train_loss -0.7973 +2024-11-22 17:12:14.781943: val_loss -0.7648 +2024-11-22 17:12:14.782084: Pseudo dice [0.8439] +2024-11-22 17:12:14.782198: Epoch time: 19.54 s +2024-11-22 17:12:15.649983: +2024-11-22 17:12:15.650434: Epoch 5483 +2024-11-22 17:12:15.650578: Current learning rate: 0.00353 +2024-11-22 17:12:34.529259: train_loss -0.8042 +2024-11-22 17:12:34.536770: val_loss -0.7457 +2024-11-22 17:12:34.536901: Pseudo dice [0.8364] +2024-11-22 17:12:34.537020: Epoch time: 18.88 s +2024-11-22 17:12:35.900534: +2024-11-22 17:12:35.902848: Epoch 5484 +2024-11-22 17:12:35.902979: Current learning rate: 0.00353 +2024-11-22 17:12:54.933172: train_loss -0.806 +2024-11-22 17:12:54.942140: val_loss -0.7711 +2024-11-22 17:12:54.942253: Pseudo dice [0.8564] +2024-11-22 17:12:54.942343: Epoch time: 19.03 s +2024-11-22 17:12:55.824337: +2024-11-22 17:12:55.826260: Epoch 5485 +2024-11-22 17:12:55.826383: Current learning rate: 0.00353 +2024-11-22 17:13:15.561296: train_loss -0.7992 +2024-11-22 17:13:15.570487: val_loss -0.7753 +2024-11-22 17:13:15.570715: Pseudo dice [0.8554] +2024-11-22 17:13:15.570826: Epoch time: 19.74 s +2024-11-22 17:13:16.505361: +2024-11-22 17:13:16.507459: Epoch 5486 +2024-11-22 17:13:16.507641: Current learning rate: 0.00353 +2024-11-22 17:13:35.562656: train_loss -0.8005 +2024-11-22 17:13:35.574202: val_loss -0.7875 +2024-11-22 17:13:35.574358: Pseudo dice [0.8521] +2024-11-22 17:13:35.574457: Epoch time: 19.06 s +2024-11-22 17:13:36.606101: +2024-11-22 17:13:36.607172: Epoch 5487 +2024-11-22 17:13:36.607296: Current learning rate: 0.00353 +2024-11-22 17:13:56.391215: train_loss -0.801 +2024-11-22 17:13:56.393375: val_loss -0.7902 +2024-11-22 17:13:56.393498: Pseudo dice [0.8648] +2024-11-22 17:13:56.393609: Epoch time: 19.79 s +2024-11-22 17:13:57.358272: +2024-11-22 17:13:57.359537: Epoch 5488 +2024-11-22 17:13:57.359671: Current learning rate: 0.00353 +2024-11-22 17:14:16.758998: train_loss -0.8015 +2024-11-22 17:14:16.767144: val_loss -0.789 +2024-11-22 17:14:16.767272: Pseudo dice [0.86] +2024-11-22 17:14:16.767383: Epoch time: 19.4 s +2024-11-22 17:14:18.263521: +2024-11-22 17:14:18.264887: Epoch 5489 +2024-11-22 17:14:18.265025: Current learning rate: 0.00352 +2024-11-22 17:14:37.648777: train_loss -0.8001 +2024-11-22 17:14:37.655524: val_loss -0.7477 +2024-11-22 17:14:37.655679: Pseudo dice [0.8402] +2024-11-22 17:14:37.655779: Epoch time: 19.39 s +2024-11-22 17:14:38.589087: +2024-11-22 17:14:38.590369: Epoch 5490 +2024-11-22 17:14:38.590490: Current learning rate: 0.00352 +2024-11-22 17:14:56.975590: train_loss -0.7976 +2024-11-22 17:14:56.984247: val_loss -0.7894 +2024-11-22 17:14:56.984410: Pseudo dice [0.8604] +2024-11-22 17:14:56.984527: Epoch time: 18.39 s +2024-11-22 17:14:57.934536: +2024-11-22 17:14:57.935090: Epoch 5491 +2024-11-22 17:14:57.935211: Current learning rate: 0.00352 +2024-11-22 17:15:18.039047: train_loss -0.7914 +2024-11-22 17:15:18.046530: val_loss -0.763 +2024-11-22 17:15:18.046656: Pseudo dice [0.8444] +2024-11-22 17:15:18.046746: Epoch time: 20.11 s +2024-11-22 17:15:19.221147: +2024-11-22 17:15:19.222533: Epoch 5492 +2024-11-22 17:15:19.222654: Current learning rate: 0.00352 +2024-11-22 17:15:38.839835: train_loss -0.7861 +2024-11-22 17:15:38.850895: val_loss -0.7952 +2024-11-22 17:15:38.851048: Pseudo dice [0.8626] +2024-11-22 17:15:38.851154: Epoch time: 19.62 s +2024-11-22 17:15:39.859922: +2024-11-22 17:15:39.860169: Epoch 5493 +2024-11-22 17:15:39.860286: Current learning rate: 0.00352 +2024-11-22 17:15:59.138966: train_loss -0.799 +2024-11-22 17:15:59.159848: val_loss -0.7609 +2024-11-22 17:15:59.160001: Pseudo dice [0.8629] +2024-11-22 17:15:59.160109: Epoch time: 19.28 s +2024-11-22 17:16:00.287580: +2024-11-22 17:16:00.288572: Epoch 5494 +2024-11-22 17:16:00.288706: Current learning rate: 0.00352 +2024-11-22 17:16:20.174998: train_loss -0.8023 +2024-11-22 17:16:20.183213: val_loss -0.7836 +2024-11-22 17:16:20.183354: Pseudo dice [0.8547] +2024-11-22 17:16:20.183498: Epoch time: 19.89 s +2024-11-22 17:16:21.106644: +2024-11-22 17:16:21.107596: Epoch 5495 +2024-11-22 17:16:21.107727: Current learning rate: 0.00352 +2024-11-22 17:16:40.744270: train_loss -0.8098 +2024-11-22 17:16:40.758806: val_loss -0.7804 +2024-11-22 17:16:40.758925: Pseudo dice [0.8441] +2024-11-22 17:16:40.759053: Epoch time: 19.64 s +2024-11-22 17:16:41.627018: +2024-11-22 17:16:41.629069: Epoch 5496 +2024-11-22 17:16:41.629204: Current learning rate: 0.00352 +2024-11-22 17:17:01.553211: train_loss -0.7995 +2024-11-22 17:17:01.559239: val_loss -0.7766 +2024-11-22 17:17:01.559414: Pseudo dice [0.8687] +2024-11-22 17:17:01.559532: Epoch time: 19.93 s +2024-11-22 17:17:02.428019: +2024-11-22 17:17:02.429563: Epoch 5497 +2024-11-22 17:17:02.429702: Current learning rate: 0.00351 +2024-11-22 17:17:23.097641: train_loss -0.7883 +2024-11-22 17:17:23.101029: val_loss -0.7627 +2024-11-22 17:17:23.101169: Pseudo dice [0.8634] +2024-11-22 17:17:23.101272: Epoch time: 20.67 s +2024-11-22 17:17:24.015337: +2024-11-22 17:17:24.016370: Epoch 5498 +2024-11-22 17:17:24.016495: Current learning rate: 0.00351 +2024-11-22 17:17:43.665473: train_loss -0.7997 +2024-11-22 17:17:43.669981: val_loss -0.7812 +2024-11-22 17:17:43.670115: Pseudo dice [0.85] +2024-11-22 17:17:43.670210: Epoch time: 19.65 s +2024-11-22 17:17:44.596788: +2024-11-22 17:17:44.597261: Epoch 5499 +2024-11-22 17:17:44.597417: Current learning rate: 0.00351 +2024-11-22 17:18:06.560532: train_loss -0.7915 +2024-11-22 17:18:06.569650: val_loss -0.7868 +2024-11-22 17:18:06.569783: Pseudo dice [0.8591] +2024-11-22 17:18:06.569874: Epoch time: 21.96 s +2024-11-22 17:18:07.811786: +2024-11-22 17:18:07.812970: Epoch 5500 +2024-11-22 17:18:07.813112: Current learning rate: 0.00351 +2024-11-22 17:18:26.240798: train_loss -0.7978 +2024-11-22 17:18:26.245321: val_loss -0.7662 +2024-11-22 17:18:26.245444: Pseudo dice [0.8609] +2024-11-22 17:18:26.245552: Epoch time: 18.43 s +2024-11-22 17:18:27.112591: +2024-11-22 17:18:27.142278: Epoch 5501 +2024-11-22 17:18:27.142422: Current learning rate: 0.00351 +2024-11-22 17:18:46.423788: train_loss -0.7948 +2024-11-22 17:18:46.429195: val_loss -0.7684 +2024-11-22 17:18:46.429345: Pseudo dice [0.8557] +2024-11-22 17:18:46.429437: Epoch time: 19.31 s +2024-11-22 17:18:47.299487: +2024-11-22 17:18:47.300545: Epoch 5502 +2024-11-22 17:18:47.300672: Current learning rate: 0.00351 +2024-11-22 17:19:07.531402: train_loss -0.7974 +2024-11-22 17:19:07.532898: val_loss -0.756 +2024-11-22 17:19:07.533002: Pseudo dice [0.859] +2024-11-22 17:19:07.533095: Epoch time: 20.23 s +2024-11-22 17:19:08.380353: +2024-11-22 17:19:08.380793: Epoch 5503 +2024-11-22 17:19:08.380918: Current learning rate: 0.00351 +2024-11-22 17:19:27.267867: train_loss -0.7958 +2024-11-22 17:19:27.274590: val_loss -0.7587 +2024-11-22 17:19:27.274829: Pseudo dice [0.855] +2024-11-22 17:19:27.274934: Epoch time: 18.89 s +2024-11-22 17:19:28.416559: +2024-11-22 17:19:28.416807: Epoch 5504 +2024-11-22 17:19:28.417129: Current learning rate: 0.00351 +2024-11-22 17:19:48.668262: train_loss -0.7926 +2024-11-22 17:19:48.675608: val_loss -0.799 +2024-11-22 17:19:48.675753: Pseudo dice [0.8571] +2024-11-22 17:19:48.675855: Epoch time: 20.25 s +2024-11-22 17:19:49.594267: +2024-11-22 17:19:49.594693: Epoch 5505 +2024-11-22 17:19:49.594832: Current learning rate: 0.0035 +2024-11-22 17:20:09.141715: train_loss -0.7955 +2024-11-22 17:20:09.160684: val_loss -0.7917 +2024-11-22 17:20:09.160898: Pseudo dice [0.8733] +2024-11-22 17:20:09.160995: Epoch time: 19.55 s +2024-11-22 17:20:10.116484: +2024-11-22 17:20:10.117993: Epoch 5506 +2024-11-22 17:20:10.118125: Current learning rate: 0.0035 +2024-11-22 17:20:29.060512: train_loss -0.804 +2024-11-22 17:20:29.067440: val_loss -0.782 +2024-11-22 17:20:29.067579: Pseudo dice [0.8596] +2024-11-22 17:20:29.067686: Epoch time: 18.94 s +2024-11-22 17:20:29.954030: +2024-11-22 17:20:29.955277: Epoch 5507 +2024-11-22 17:20:29.955397: Current learning rate: 0.0035 +2024-11-22 17:20:48.635558: train_loss -0.7991 +2024-11-22 17:20:48.644455: val_loss -0.7807 +2024-11-22 17:20:48.644599: Pseudo dice [0.8576] +2024-11-22 17:20:48.644697: Epoch time: 18.68 s +2024-11-22 17:20:49.696845: +2024-11-22 17:20:49.698882: Epoch 5508 +2024-11-22 17:20:49.699025: Current learning rate: 0.0035 +2024-11-22 17:21:08.989065: train_loss -0.7927 +2024-11-22 17:21:08.998004: val_loss -0.794 +2024-11-22 17:21:08.998152: Pseudo dice [0.8565] +2024-11-22 17:21:08.998276: Epoch time: 19.29 s +2024-11-22 17:21:10.015826: +2024-11-22 17:21:10.030217: Epoch 5509 +2024-11-22 17:21:10.030352: Current learning rate: 0.0035 +2024-11-22 17:21:28.735819: train_loss -0.795 +2024-11-22 17:21:28.740364: val_loss -0.7642 +2024-11-22 17:21:28.747326: Pseudo dice [0.8536] +2024-11-22 17:21:28.747452: Epoch time: 18.72 s +2024-11-22 17:21:29.720222: +2024-11-22 17:21:29.721688: Epoch 5510 +2024-11-22 17:21:29.721810: Current learning rate: 0.0035 +2024-11-22 17:21:49.024976: train_loss -0.8071 +2024-11-22 17:21:49.030371: val_loss -0.76 +2024-11-22 17:21:49.030519: Pseudo dice [0.8575] +2024-11-22 17:21:49.030618: Epoch time: 19.31 s +2024-11-22 17:21:50.031668: +2024-11-22 17:21:50.033206: Epoch 5511 +2024-11-22 17:21:50.033340: Current learning rate: 0.0035 +2024-11-22 17:22:08.848291: train_loss -0.8057 +2024-11-22 17:22:08.856894: val_loss -0.7597 +2024-11-22 17:22:08.857034: Pseudo dice [0.8638] +2024-11-22 17:22:08.857137: Epoch time: 18.82 s +2024-11-22 17:22:10.239541: +2024-11-22 17:22:10.241241: Epoch 5512 +2024-11-22 17:22:10.241367: Current learning rate: 0.0035 +2024-11-22 17:22:28.906779: train_loss -0.8119 +2024-11-22 17:22:28.914598: val_loss -0.7659 +2024-11-22 17:22:28.914834: Pseudo dice [0.8604] +2024-11-22 17:22:28.914965: Epoch time: 18.67 s +2024-11-22 17:22:29.830371: +2024-11-22 17:22:29.831710: Epoch 5513 +2024-11-22 17:22:29.831853: Current learning rate: 0.00349 +2024-11-22 17:22:49.744509: train_loss -0.7972 +2024-11-22 17:22:49.752697: val_loss -0.7794 +2024-11-22 17:22:49.752818: Pseudo dice [0.8701] +2024-11-22 17:22:49.752920: Epoch time: 19.91 s +2024-11-22 17:22:50.692357: +2024-11-22 17:22:50.693218: Epoch 5514 +2024-11-22 17:22:50.693353: Current learning rate: 0.00349 +2024-11-22 17:23:10.774092: train_loss -0.8037 +2024-11-22 17:23:10.776476: val_loss -0.775 +2024-11-22 17:23:10.776601: Pseudo dice [0.8599] +2024-11-22 17:23:10.776701: Epoch time: 20.08 s +2024-11-22 17:23:11.696541: +2024-11-22 17:23:11.697819: Epoch 5515 +2024-11-22 17:23:11.697958: Current learning rate: 0.00349 +2024-11-22 17:23:31.476183: train_loss -0.8042 +2024-11-22 17:23:31.481578: val_loss -0.7916 +2024-11-22 17:23:31.481805: Pseudo dice [0.8585] +2024-11-22 17:23:31.481918: Epoch time: 19.78 s +2024-11-22 17:23:32.433717: +2024-11-22 17:23:32.435159: Epoch 5516 +2024-11-22 17:23:32.435299: Current learning rate: 0.00349 +2024-11-22 17:23:51.456302: train_loss -0.8057 +2024-11-22 17:23:51.461933: val_loss -0.7773 +2024-11-22 17:23:51.462075: Pseudo dice [0.8628] +2024-11-22 17:23:51.462170: Epoch time: 19.02 s +2024-11-22 17:23:52.472286: +2024-11-22 17:23:52.473625: Epoch 5517 +2024-11-22 17:23:52.473745: Current learning rate: 0.00349 +2024-11-22 17:24:12.572130: train_loss -0.8022 +2024-11-22 17:24:12.585302: val_loss -0.7686 +2024-11-22 17:24:12.585438: Pseudo dice [0.8514] +2024-11-22 17:24:12.585526: Epoch time: 20.1 s +2024-11-22 17:24:13.581624: +2024-11-22 17:24:13.582718: Epoch 5518 +2024-11-22 17:24:13.582840: Current learning rate: 0.00349 +2024-11-22 17:24:33.275399: train_loss -0.8085 +2024-11-22 17:24:33.293361: val_loss -0.7837 +2024-11-22 17:24:33.293496: Pseudo dice [0.8557] +2024-11-22 17:24:33.293585: Epoch time: 19.69 s +2024-11-22 17:24:34.156133: +2024-11-22 17:24:34.156358: Epoch 5519 +2024-11-22 17:24:34.156490: Current learning rate: 0.00349 +2024-11-22 17:24:52.492252: train_loss -0.8042 +2024-11-22 17:24:52.492727: val_loss -0.7784 +2024-11-22 17:24:52.492834: Pseudo dice [0.8616] +2024-11-22 17:24:52.492944: Epoch time: 18.34 s +2024-11-22 17:24:53.349248: +2024-11-22 17:24:53.349458: Epoch 5520 +2024-11-22 17:24:53.349574: Current learning rate: 0.00349 +2024-11-22 17:25:13.276549: train_loss -0.8103 +2024-11-22 17:25:13.283502: val_loss -0.7645 +2024-11-22 17:25:13.283644: Pseudo dice [0.8585] +2024-11-22 17:25:13.283749: Epoch time: 19.93 s +2024-11-22 17:25:14.351343: +2024-11-22 17:25:14.351561: Epoch 5521 +2024-11-22 17:25:14.351686: Current learning rate: 0.00348 +2024-11-22 17:25:33.609518: train_loss -0.8052 +2024-11-22 17:25:33.618285: val_loss -0.7988 +2024-11-22 17:25:33.618486: Pseudo dice [0.8631] +2024-11-22 17:25:33.618596: Epoch time: 19.26 s +2024-11-22 17:25:34.690439: +2024-11-22 17:25:34.690679: Epoch 5522 +2024-11-22 17:25:34.690822: Current learning rate: 0.00348 +2024-11-22 17:25:53.690614: train_loss -0.7921 +2024-11-22 17:25:53.691675: val_loss -0.7752 +2024-11-22 17:25:53.691776: Pseudo dice [0.8602] +2024-11-22 17:25:53.691863: Epoch time: 19.0 s +2024-11-22 17:25:54.544661: +2024-11-22 17:25:54.544880: Epoch 5523 +2024-11-22 17:25:54.544999: Current learning rate: 0.00348 +2024-11-22 17:26:12.749436: train_loss -0.8002 +2024-11-22 17:26:12.751276: val_loss -0.7584 +2024-11-22 17:26:12.751388: Pseudo dice [0.8428] +2024-11-22 17:26:12.751482: Epoch time: 18.21 s +2024-11-22 17:26:14.017951: +2024-11-22 17:26:14.018179: Epoch 5524 +2024-11-22 17:26:14.018308: Current learning rate: 0.00348 +2024-11-22 17:26:32.901696: train_loss -0.8067 +2024-11-22 17:26:32.904916: val_loss -0.7568 +2024-11-22 17:26:32.905071: Pseudo dice [0.8565] +2024-11-22 17:26:32.905174: Epoch time: 18.88 s +2024-11-22 17:26:33.830709: +2024-11-22 17:26:33.830910: Epoch 5525 +2024-11-22 17:26:33.831123: Current learning rate: 0.00348 +2024-11-22 17:26:51.585596: train_loss -0.8054 +2024-11-22 17:26:51.604858: val_loss -0.78 +2024-11-22 17:26:51.605023: Pseudo dice [0.8572] +2024-11-22 17:26:51.605128: Epoch time: 17.76 s +2024-11-22 17:26:52.471495: +2024-11-22 17:26:52.471718: Epoch 5526 +2024-11-22 17:26:52.471856: Current learning rate: 0.00348 +2024-11-22 17:27:11.051521: train_loss -0.7996 +2024-11-22 17:27:11.054823: val_loss -0.7908 +2024-11-22 17:27:11.054982: Pseudo dice [0.862] +2024-11-22 17:27:11.055102: Epoch time: 18.58 s +2024-11-22 17:27:12.022953: +2024-11-22 17:27:12.023177: Epoch 5527 +2024-11-22 17:27:12.023295: Current learning rate: 0.00348 +2024-11-22 17:27:31.869817: train_loss -0.806 +2024-11-22 17:27:31.875282: val_loss -0.7967 +2024-11-22 17:27:31.875461: Pseudo dice [0.863] +2024-11-22 17:27:31.875573: Epoch time: 19.85 s +2024-11-22 17:27:32.776245: +2024-11-22 17:27:32.777017: Epoch 5528 +2024-11-22 17:27:32.777143: Current learning rate: 0.00348 +2024-11-22 17:27:52.841850: train_loss -0.8079 +2024-11-22 17:27:52.848922: val_loss -0.764 +2024-11-22 17:27:52.849068: Pseudo dice [0.8607] +2024-11-22 17:27:52.849155: Epoch time: 20.07 s +2024-11-22 17:27:53.873660: +2024-11-22 17:27:53.875357: Epoch 5529 +2024-11-22 17:27:53.875492: Current learning rate: 0.00347 +2024-11-22 17:28:13.442601: train_loss -0.802 +2024-11-22 17:28:13.455813: val_loss -0.7856 +2024-11-22 17:28:13.456169: Pseudo dice [0.851] +2024-11-22 17:28:13.456271: Epoch time: 19.57 s +2024-11-22 17:28:14.462312: +2024-11-22 17:28:14.464329: Epoch 5530 +2024-11-22 17:28:14.464450: Current learning rate: 0.00347 +2024-11-22 17:28:34.506970: train_loss -0.8042 +2024-11-22 17:28:34.513910: val_loss -0.7571 +2024-11-22 17:28:34.514068: Pseudo dice [0.8521] +2024-11-22 17:28:34.514175: Epoch time: 20.05 s +2024-11-22 17:28:35.421042: +2024-11-22 17:28:35.421546: Epoch 5531 +2024-11-22 17:28:35.421668: Current learning rate: 0.00347 +2024-11-22 17:28:54.445516: train_loss -0.8006 +2024-11-22 17:28:54.453850: val_loss -0.7943 +2024-11-22 17:28:54.453994: Pseudo dice [0.8698] +2024-11-22 17:28:54.454093: Epoch time: 19.03 s +2024-11-22 17:28:55.333497: +2024-11-22 17:28:55.333985: Epoch 5532 +2024-11-22 17:28:55.334134: Current learning rate: 0.00347 +2024-11-22 17:29:15.396511: train_loss -0.8039 +2024-11-22 17:29:15.403264: val_loss -0.789 +2024-11-22 17:29:15.403417: Pseudo dice [0.8617] +2024-11-22 17:29:15.403532: Epoch time: 20.06 s +2024-11-22 17:29:16.279414: +2024-11-22 17:29:16.281038: Epoch 5533 +2024-11-22 17:29:16.281172: Current learning rate: 0.00347 +2024-11-22 17:29:36.124219: train_loss -0.7969 +2024-11-22 17:29:36.144755: val_loss -0.7841 +2024-11-22 17:29:36.144906: Pseudo dice [0.8423] +2024-11-22 17:29:36.145051: Epoch time: 19.85 s +2024-11-22 17:29:37.183456: +2024-11-22 17:29:37.185097: Epoch 5534 +2024-11-22 17:29:37.185218: Current learning rate: 0.00347 +2024-11-22 17:29:56.760123: train_loss -0.8013 +2024-11-22 17:29:56.764420: val_loss -0.7631 +2024-11-22 17:29:56.764585: Pseudo dice [0.8596] +2024-11-22 17:29:56.764684: Epoch time: 19.58 s +2024-11-22 17:29:57.648520: +2024-11-22 17:29:57.649774: Epoch 5535 +2024-11-22 17:29:57.649961: Current learning rate: 0.00347 +2024-11-22 17:30:18.057731: train_loss -0.8028 +2024-11-22 17:30:18.065249: val_loss -0.7965 +2024-11-22 17:30:18.065375: Pseudo dice [0.8566] +2024-11-22 17:30:18.065502: Epoch time: 20.41 s +2024-11-22 17:30:19.479957: +2024-11-22 17:30:19.481256: Epoch 5536 +2024-11-22 17:30:19.481413: Current learning rate: 0.00346 +2024-11-22 17:30:38.773141: train_loss -0.8051 +2024-11-22 17:30:38.789106: val_loss -0.7766 +2024-11-22 17:30:38.789297: Pseudo dice [0.8581] +2024-11-22 17:30:38.789440: Epoch time: 19.29 s +2024-11-22 17:30:39.814687: +2024-11-22 17:30:39.815915: Epoch 5537 +2024-11-22 17:30:39.816041: Current learning rate: 0.00346 +2024-11-22 17:31:00.548476: train_loss -0.8044 +2024-11-22 17:31:00.554866: val_loss -0.768 +2024-11-22 17:31:00.555013: Pseudo dice [0.8516] +2024-11-22 17:31:00.555124: Epoch time: 20.72 s +2024-11-22 17:31:01.679446: +2024-11-22 17:31:01.680953: Epoch 5538 +2024-11-22 17:31:01.681089: Current learning rate: 0.00346 +2024-11-22 17:31:20.966490: train_loss -0.7971 +2024-11-22 17:31:20.976465: val_loss -0.7859 +2024-11-22 17:31:20.976622: Pseudo dice [0.8478] +2024-11-22 17:31:20.976729: Epoch time: 19.29 s +2024-11-22 17:31:21.991615: +2024-11-22 17:31:21.992414: Epoch 5539 +2024-11-22 17:31:21.992546: Current learning rate: 0.00346 +2024-11-22 17:31:42.242635: train_loss -0.8043 +2024-11-22 17:31:42.271468: val_loss -0.7808 +2024-11-22 17:31:42.271653: Pseudo dice [0.8695] +2024-11-22 17:31:42.271775: Epoch time: 20.25 s +2024-11-22 17:31:43.157001: +2024-11-22 17:31:43.157850: Epoch 5540 +2024-11-22 17:31:43.157989: Current learning rate: 0.00346 +2024-11-22 17:32:02.482347: train_loss -0.7941 +2024-11-22 17:32:02.491729: val_loss -0.7714 +2024-11-22 17:32:02.491867: Pseudo dice [0.8533] +2024-11-22 17:32:02.491952: Epoch time: 19.33 s +2024-11-22 17:32:03.464722: +2024-11-22 17:32:03.466200: Epoch 5541 +2024-11-22 17:32:03.466328: Current learning rate: 0.00346 +2024-11-22 17:32:24.863574: train_loss -0.7982 +2024-11-22 17:32:24.871657: val_loss -0.8044 +2024-11-22 17:32:24.871791: Pseudo dice [0.8675] +2024-11-22 17:32:24.871914: Epoch time: 21.4 s +2024-11-22 17:32:25.963250: +2024-11-22 17:32:25.964217: Epoch 5542 +2024-11-22 17:32:25.964337: Current learning rate: 0.00346 +2024-11-22 17:32:45.702940: train_loss -0.7968 +2024-11-22 17:32:45.711266: val_loss -0.7652 +2024-11-22 17:32:45.711404: Pseudo dice [0.846] +2024-11-22 17:32:45.711536: Epoch time: 19.74 s +2024-11-22 17:32:46.712201: +2024-11-22 17:32:46.713581: Epoch 5543 +2024-11-22 17:32:46.713715: Current learning rate: 0.00346 +2024-11-22 17:33:06.167651: train_loss -0.7955 +2024-11-22 17:33:06.174650: val_loss -0.7702 +2024-11-22 17:33:06.174787: Pseudo dice [0.8466] +2024-11-22 17:33:06.174879: Epoch time: 19.46 s +2024-11-22 17:33:07.054019: +2024-11-22 17:33:07.054785: Epoch 5544 +2024-11-22 17:33:07.054923: Current learning rate: 0.00345 +2024-11-22 17:33:26.088953: train_loss -0.788 +2024-11-22 17:33:26.091333: val_loss -0.7785 +2024-11-22 17:33:26.091485: Pseudo dice [0.8612] +2024-11-22 17:33:26.091588: Epoch time: 19.04 s +2024-11-22 17:33:26.952049: +2024-11-22 17:33:26.953314: Epoch 5545 +2024-11-22 17:33:26.953443: Current learning rate: 0.00345 +2024-11-22 17:33:47.013117: train_loss -0.8033 +2024-11-22 17:33:47.015646: val_loss -0.7657 +2024-11-22 17:33:47.015753: Pseudo dice [0.8572] +2024-11-22 17:33:47.015835: Epoch time: 20.06 s +2024-11-22 17:33:47.877008: +2024-11-22 17:33:47.878666: Epoch 5546 +2024-11-22 17:33:47.878790: Current learning rate: 0.00345 +2024-11-22 17:34:06.236924: train_loss -0.7822 +2024-11-22 17:34:06.242840: val_loss -0.7645 +2024-11-22 17:34:06.250437: Pseudo dice [0.8488] +2024-11-22 17:34:06.250567: Epoch time: 18.36 s +2024-11-22 17:34:07.284524: +2024-11-22 17:34:07.285362: Epoch 5547 +2024-11-22 17:34:07.285516: Current learning rate: 0.00345 +2024-11-22 17:34:27.732229: train_loss -0.791 +2024-11-22 17:34:27.737977: val_loss -0.7628 +2024-11-22 17:34:27.738130: Pseudo dice [0.8468] +2024-11-22 17:34:27.738239: Epoch time: 20.45 s +2024-11-22 17:34:29.191228: +2024-11-22 17:34:29.193300: Epoch 5548 +2024-11-22 17:34:29.193439: Current learning rate: 0.00345 +2024-11-22 17:34:49.335502: train_loss -0.7944 +2024-11-22 17:34:49.342977: val_loss -0.7736 +2024-11-22 17:34:49.343174: Pseudo dice [0.8493] +2024-11-22 17:34:49.343271: Epoch time: 20.15 s +2024-11-22 17:34:50.283856: +2024-11-22 17:34:50.285861: Epoch 5549 +2024-11-22 17:34:50.286003: Current learning rate: 0.00345 +2024-11-22 17:35:09.633693: train_loss -0.7849 +2024-11-22 17:35:09.641704: val_loss -0.7684 +2024-11-22 17:35:09.641829: Pseudo dice [0.8602] +2024-11-22 17:35:09.641931: Epoch time: 19.35 s +2024-11-22 17:35:10.978121: +2024-11-22 17:35:10.979253: Epoch 5550 +2024-11-22 17:35:10.979391: Current learning rate: 0.00345 +2024-11-22 17:35:30.425740: train_loss -0.7796 +2024-11-22 17:35:30.431438: val_loss -0.7404 +2024-11-22 17:35:30.431572: Pseudo dice [0.852] +2024-11-22 17:35:30.431662: Epoch time: 19.45 s +2024-11-22 17:35:31.330909: +2024-11-22 17:35:31.332537: Epoch 5551 +2024-11-22 17:35:31.332862: Current learning rate: 0.00345 +2024-11-22 17:35:50.908981: train_loss -0.7716 +2024-11-22 17:35:50.914678: val_loss -0.763 +2024-11-22 17:35:50.914841: Pseudo dice [0.8326] +2024-11-22 17:35:50.914998: Epoch time: 19.58 s +2024-11-22 17:35:51.779284: +2024-11-22 17:35:51.780667: Epoch 5552 +2024-11-22 17:35:51.780809: Current learning rate: 0.00344 +2024-11-22 17:36:12.574644: train_loss -0.7907 +2024-11-22 17:36:12.580981: val_loss -0.7893 +2024-11-22 17:36:12.581111: Pseudo dice [0.8459] +2024-11-22 17:36:12.581208: Epoch time: 20.8 s +2024-11-22 17:36:13.523117: +2024-11-22 17:36:13.523583: Epoch 5553 +2024-11-22 17:36:13.523719: Current learning rate: 0.00344 +2024-11-22 17:36:33.275893: train_loss -0.7945 +2024-11-22 17:36:33.293633: val_loss -0.7645 +2024-11-22 17:36:33.293791: Pseudo dice [0.8416] +2024-11-22 17:36:33.293902: Epoch time: 19.75 s +2024-11-22 17:36:34.324990: +2024-11-22 17:36:34.326402: Epoch 5554 +2024-11-22 17:36:34.326535: Current learning rate: 0.00344 +2024-11-22 17:36:54.522156: train_loss -0.7836 +2024-11-22 17:36:54.529010: val_loss -0.7729 +2024-11-22 17:36:54.529157: Pseudo dice [0.8483] +2024-11-22 17:36:54.529265: Epoch time: 20.19 s +2024-11-22 17:36:55.501179: +2024-11-22 17:36:55.533505: Epoch 5555 +2024-11-22 17:36:55.533669: Current learning rate: 0.00344 +2024-11-22 17:37:16.049386: train_loss -0.7822 +2024-11-22 17:37:16.051587: val_loss -0.7729 +2024-11-22 17:37:16.051691: Pseudo dice [0.8568] +2024-11-22 17:37:16.051812: Epoch time: 20.55 s +2024-11-22 17:37:16.916832: +2024-11-22 17:37:16.917274: Epoch 5556 +2024-11-22 17:37:16.917408: Current learning rate: 0.00344 +2024-11-22 17:37:36.723560: train_loss -0.7819 +2024-11-22 17:37:36.728724: val_loss -0.7489 +2024-11-22 17:37:36.728863: Pseudo dice [0.8499] +2024-11-22 17:37:36.728950: Epoch time: 19.81 s +2024-11-22 17:37:37.820883: +2024-11-22 17:37:37.822387: Epoch 5557 +2024-11-22 17:37:37.822512: Current learning rate: 0.00344 +2024-11-22 17:37:56.749206: train_loss -0.7894 +2024-11-22 17:37:56.757287: val_loss -0.7822 +2024-11-22 17:37:56.757417: Pseudo dice [0.8513] +2024-11-22 17:37:56.757532: Epoch time: 18.93 s +2024-11-22 17:37:57.735958: +2024-11-22 17:37:57.737892: Epoch 5558 +2024-11-22 17:37:57.738032: Current learning rate: 0.00344 +2024-11-22 17:38:16.638728: train_loss -0.7958 +2024-11-22 17:38:16.646659: val_loss -0.7819 +2024-11-22 17:38:16.646810: Pseudo dice [0.8389] +2024-11-22 17:38:16.646906: Epoch time: 18.9 s +2024-11-22 17:38:17.544276: +2024-11-22 17:38:17.545667: Epoch 5559 +2024-11-22 17:38:17.545789: Current learning rate: 0.00344 +2024-11-22 17:38:36.120222: train_loss -0.8 +2024-11-22 17:38:36.122772: val_loss -0.7744 +2024-11-22 17:38:36.122923: Pseudo dice [0.8531] +2024-11-22 17:38:36.123053: Epoch time: 18.58 s +2024-11-22 17:38:37.078207: +2024-11-22 17:38:37.079578: Epoch 5560 +2024-11-22 17:38:37.079707: Current learning rate: 0.00343 +2024-11-22 17:38:56.162160: train_loss -0.7946 +2024-11-22 17:38:56.170923: val_loss -0.7777 +2024-11-22 17:38:56.171330: Pseudo dice [0.8523] +2024-11-22 17:38:56.171446: Epoch time: 19.08 s +2024-11-22 17:38:57.181949: +2024-11-22 17:38:57.183667: Epoch 5561 +2024-11-22 17:38:57.183802: Current learning rate: 0.00343 +2024-11-22 17:39:16.242709: train_loss -0.7909 +2024-11-22 17:39:16.247699: val_loss -0.7464 +2024-11-22 17:39:16.247843: Pseudo dice [0.848] +2024-11-22 17:39:16.247956: Epoch time: 19.06 s +2024-11-22 17:39:17.108501: +2024-11-22 17:39:17.109829: Epoch 5562 +2024-11-22 17:39:17.109976: Current learning rate: 0.00343 +2024-11-22 17:39:36.523297: train_loss -0.797 +2024-11-22 17:39:36.534015: val_loss -0.7646 +2024-11-22 17:39:36.534286: Pseudo dice [0.8525] +2024-11-22 17:39:36.534379: Epoch time: 19.42 s +2024-11-22 17:39:37.571772: +2024-11-22 17:39:37.574142: Epoch 5563 +2024-11-22 17:39:37.574271: Current learning rate: 0.00343 +2024-11-22 17:39:56.832859: train_loss -0.7965 +2024-11-22 17:39:56.868240: val_loss -0.7664 +2024-11-22 17:39:56.868431: Pseudo dice [0.8453] +2024-11-22 17:39:56.868556: Epoch time: 19.26 s +2024-11-22 17:39:57.851076: +2024-11-22 17:39:57.852294: Epoch 5564 +2024-11-22 17:39:57.852422: Current learning rate: 0.00343 +2024-11-22 17:40:17.478900: train_loss -0.7963 +2024-11-22 17:40:17.483098: val_loss -0.7649 +2024-11-22 17:40:17.483225: Pseudo dice [0.8456] +2024-11-22 17:40:17.483319: Epoch time: 19.63 s +2024-11-22 17:40:18.396599: +2024-11-22 17:40:18.398094: Epoch 5565 +2024-11-22 17:40:18.398230: Current learning rate: 0.00343 +2024-11-22 17:40:38.559616: train_loss -0.7984 +2024-11-22 17:40:38.576580: val_loss -0.7861 +2024-11-22 17:40:38.576725: Pseudo dice [0.8663] +2024-11-22 17:40:38.576820: Epoch time: 20.16 s +2024-11-22 17:40:39.474760: +2024-11-22 17:40:39.476518: Epoch 5566 +2024-11-22 17:40:39.476649: Current learning rate: 0.00343 +2024-11-22 17:40:58.565086: train_loss -0.8007 +2024-11-22 17:40:58.567239: val_loss -0.7773 +2024-11-22 17:40:58.567338: Pseudo dice [0.8511] +2024-11-22 17:40:58.567474: Epoch time: 19.09 s +2024-11-22 17:40:59.433455: +2024-11-22 17:40:59.434496: Epoch 5567 +2024-11-22 17:40:59.434630: Current learning rate: 0.00343 +2024-11-22 17:41:19.018041: train_loss -0.8042 +2024-11-22 17:41:19.026263: val_loss -0.7546 +2024-11-22 17:41:19.026410: Pseudo dice [0.8605] +2024-11-22 17:41:19.026711: Epoch time: 19.59 s +2024-11-22 17:41:19.954766: +2024-11-22 17:41:19.956434: Epoch 5568 +2024-11-22 17:41:19.956575: Current learning rate: 0.00342 +2024-11-22 17:41:38.625738: train_loss -0.8057 +2024-11-22 17:41:38.639246: val_loss -0.7645 +2024-11-22 17:41:38.639399: Pseudo dice [0.857] +2024-11-22 17:41:38.639502: Epoch time: 18.67 s +2024-11-22 17:41:39.576912: +2024-11-22 17:41:39.577756: Epoch 5569 +2024-11-22 17:41:39.577898: Current learning rate: 0.00342 +2024-11-22 17:41:59.678292: train_loss -0.7985 +2024-11-22 17:41:59.686457: val_loss -0.7558 +2024-11-22 17:41:59.686610: Pseudo dice [0.8411] +2024-11-22 17:41:59.686710: Epoch time: 20.1 s +2024-11-22 17:42:00.589324: +2024-11-22 17:42:00.590118: Epoch 5570 +2024-11-22 17:42:00.590237: Current learning rate: 0.00342 +2024-11-22 17:42:20.074639: train_loss -0.793 +2024-11-22 17:42:20.090119: val_loss -0.772 +2024-11-22 17:42:20.090268: Pseudo dice [0.8407] +2024-11-22 17:42:20.090356: Epoch time: 19.49 s +2024-11-22 17:42:21.478045: +2024-11-22 17:42:21.479685: Epoch 5571 +2024-11-22 17:42:21.479811: Current learning rate: 0.00342 +2024-11-22 17:42:42.249416: train_loss -0.7949 +2024-11-22 17:42:42.271927: val_loss -0.7696 +2024-11-22 17:42:42.272077: Pseudo dice [0.8503] +2024-11-22 17:42:42.272181: Epoch time: 20.77 s +2024-11-22 17:42:43.280488: +2024-11-22 17:42:43.281326: Epoch 5572 +2024-11-22 17:42:43.281445: Current learning rate: 0.00342 +2024-11-22 17:43:03.858166: train_loss -0.7813 +2024-11-22 17:43:03.867244: val_loss -0.7615 +2024-11-22 17:43:03.867400: Pseudo dice [0.8484] +2024-11-22 17:43:03.867505: Epoch time: 20.58 s +2024-11-22 17:43:04.911947: +2024-11-22 17:43:04.913450: Epoch 5573 +2024-11-22 17:43:04.913582: Current learning rate: 0.00342 +2024-11-22 17:43:23.756448: train_loss -0.7992 +2024-11-22 17:43:23.771108: val_loss -0.7775 +2024-11-22 17:43:23.771254: Pseudo dice [0.8501] +2024-11-22 17:43:23.771362: Epoch time: 18.85 s +2024-11-22 17:43:24.665116: +2024-11-22 17:43:24.666552: Epoch 5574 +2024-11-22 17:43:24.666681: Current learning rate: 0.00342 +2024-11-22 17:43:44.113317: train_loss -0.8011 +2024-11-22 17:43:44.120789: val_loss -0.7774 +2024-11-22 17:43:44.120930: Pseudo dice [0.8498] +2024-11-22 17:43:44.121025: Epoch time: 19.45 s +2024-11-22 17:43:45.222396: +2024-11-22 17:43:45.224125: Epoch 5575 +2024-11-22 17:43:45.224252: Current learning rate: 0.00342 +2024-11-22 17:44:06.810980: train_loss -0.7922 +2024-11-22 17:44:06.817374: val_loss -0.7744 +2024-11-22 17:44:06.817525: Pseudo dice [0.8531] +2024-11-22 17:44:06.817630: Epoch time: 21.59 s +2024-11-22 17:44:07.680531: +2024-11-22 17:44:07.681036: Epoch 5576 +2024-11-22 17:44:07.681175: Current learning rate: 0.00341 +2024-11-22 17:44:26.942337: train_loss -0.8066 +2024-11-22 17:44:26.951680: val_loss -0.7357 +2024-11-22 17:44:26.951848: Pseudo dice [0.8504] +2024-11-22 17:44:26.951943: Epoch time: 19.26 s +2024-11-22 17:44:27.844021: +2024-11-22 17:44:27.845985: Epoch 5577 +2024-11-22 17:44:27.846122: Current learning rate: 0.00341 +2024-11-22 17:44:46.390522: train_loss -0.7924 +2024-11-22 17:44:46.403020: val_loss -0.7664 +2024-11-22 17:44:46.403193: Pseudo dice [0.8563] +2024-11-22 17:44:46.403293: Epoch time: 18.55 s +2024-11-22 17:44:47.402671: +2024-11-22 17:44:47.404594: Epoch 5578 +2024-11-22 17:44:47.404734: Current learning rate: 0.00341 +2024-11-22 17:45:07.721913: train_loss -0.793 +2024-11-22 17:45:07.732674: val_loss -0.7507 +2024-11-22 17:45:07.732818: Pseudo dice [0.848] +2024-11-22 17:45:07.732919: Epoch time: 20.32 s +2024-11-22 17:45:08.637892: +2024-11-22 17:45:08.639376: Epoch 5579 +2024-11-22 17:45:08.639514: Current learning rate: 0.00341 +2024-11-22 17:45:29.088521: train_loss -0.7832 +2024-11-22 17:45:29.104441: val_loss -0.7605 +2024-11-22 17:45:29.104569: Pseudo dice [0.8475] +2024-11-22 17:45:29.104670: Epoch time: 20.45 s +2024-11-22 17:45:30.042774: +2024-11-22 17:45:30.043680: Epoch 5580 +2024-11-22 17:45:30.043823: Current learning rate: 0.00341 +2024-11-22 17:45:47.913057: train_loss -0.7806 +2024-11-22 17:45:47.919183: val_loss -0.7614 +2024-11-22 17:45:47.919325: Pseudo dice [0.8474] +2024-11-22 17:45:47.919422: Epoch time: 17.87 s +2024-11-22 17:45:48.893787: +2024-11-22 17:45:48.894215: Epoch 5581 +2024-11-22 17:45:48.894342: Current learning rate: 0.00341 +2024-11-22 17:46:07.844350: train_loss -0.7891 +2024-11-22 17:46:07.851785: val_loss -0.7719 +2024-11-22 17:46:07.851902: Pseudo dice [0.8428] +2024-11-22 17:46:07.851985: Epoch time: 18.95 s +2024-11-22 17:46:08.904353: +2024-11-22 17:46:08.906205: Epoch 5582 +2024-11-22 17:46:08.906330: Current learning rate: 0.00341 +2024-11-22 17:46:29.131099: train_loss -0.7835 +2024-11-22 17:46:29.136137: val_loss -0.7861 +2024-11-22 17:46:29.136271: Pseudo dice [0.8524] +2024-11-22 17:46:29.136379: Epoch time: 20.23 s +2024-11-22 17:46:30.756996: +2024-11-22 17:46:30.759220: Epoch 5583 +2024-11-22 17:46:30.759351: Current learning rate: 0.00341 +2024-11-22 17:46:49.017451: train_loss -0.7856 +2024-11-22 17:46:49.026992: val_loss -0.7758 +2024-11-22 17:46:49.027121: Pseudo dice [0.8626] +2024-11-22 17:46:49.027214: Epoch time: 18.26 s +2024-11-22 17:46:50.038068: +2024-11-22 17:46:50.038641: Epoch 5584 +2024-11-22 17:46:50.038762: Current learning rate: 0.0034 +2024-11-22 17:47:10.272201: train_loss -0.8009 +2024-11-22 17:47:10.280596: val_loss -0.7544 +2024-11-22 17:47:10.280777: Pseudo dice [0.854] +2024-11-22 17:47:10.280912: Epoch time: 20.23 s +2024-11-22 17:47:11.238529: +2024-11-22 17:47:11.240330: Epoch 5585 +2024-11-22 17:47:11.240474: Current learning rate: 0.0034 +2024-11-22 17:47:32.279074: train_loss -0.8012 +2024-11-22 17:47:32.297458: val_loss -0.7721 +2024-11-22 17:47:32.297624: Pseudo dice [0.8543] +2024-11-22 17:47:32.297727: Epoch time: 21.04 s +2024-11-22 17:47:33.282076: +2024-11-22 17:47:33.283569: Epoch 5586 +2024-11-22 17:47:33.283689: Current learning rate: 0.0034 +2024-11-22 17:47:52.528231: train_loss -0.7948 +2024-11-22 17:47:52.545500: val_loss -0.7847 +2024-11-22 17:47:52.545661: Pseudo dice [0.8455] +2024-11-22 17:47:52.545769: Epoch time: 19.25 s +2024-11-22 17:47:53.644747: +2024-11-22 17:47:53.646756: Epoch 5587 +2024-11-22 17:47:53.646880: Current learning rate: 0.0034 +2024-11-22 17:48:12.129056: train_loss -0.7933 +2024-11-22 17:48:12.134704: val_loss -0.7783 +2024-11-22 17:48:12.134816: Pseudo dice [0.873] +2024-11-22 17:48:12.134932: Epoch time: 18.49 s +2024-11-22 17:48:13.272286: +2024-11-22 17:48:13.273039: Epoch 5588 +2024-11-22 17:48:13.273168: Current learning rate: 0.0034 +2024-11-22 17:48:32.997922: train_loss -0.8 +2024-11-22 17:48:33.002655: val_loss -0.7395 +2024-11-22 17:48:33.002764: Pseudo dice [0.8566] +2024-11-22 17:48:33.002855: Epoch time: 19.73 s +2024-11-22 17:48:33.939061: +2024-11-22 17:48:33.939889: Epoch 5589 +2024-11-22 17:48:33.940026: Current learning rate: 0.0034 +2024-11-22 17:48:54.483029: train_loss -0.805 +2024-11-22 17:48:54.485451: val_loss -0.7505 +2024-11-22 17:48:54.485552: Pseudo dice [0.8442] +2024-11-22 17:48:54.485642: Epoch time: 20.54 s +2024-11-22 17:48:55.351877: +2024-11-22 17:48:55.352737: Epoch 5590 +2024-11-22 17:48:55.352863: Current learning rate: 0.0034 +2024-11-22 17:49:15.612641: train_loss -0.793 +2024-11-22 17:49:15.615472: val_loss -0.7919 +2024-11-22 17:49:15.615568: Pseudo dice [0.8543] +2024-11-22 17:49:15.615654: Epoch time: 20.26 s +2024-11-22 17:49:16.482920: +2024-11-22 17:49:16.483156: Epoch 5591 +2024-11-22 17:49:16.483277: Current learning rate: 0.0034 +2024-11-22 17:49:35.423942: train_loss -0.7933 +2024-11-22 17:49:35.426514: val_loss -0.7601 +2024-11-22 17:49:35.426664: Pseudo dice [0.8466] +2024-11-22 17:49:35.426766: Epoch time: 18.94 s +2024-11-22 17:49:36.291416: +2024-11-22 17:49:36.291682: Epoch 5592 +2024-11-22 17:49:36.291835: Current learning rate: 0.00339 +2024-11-22 17:49:54.791438: train_loss -0.7962 +2024-11-22 17:49:54.804251: val_loss -0.756 +2024-11-22 17:49:54.804425: Pseudo dice [0.8473] +2024-11-22 17:49:54.804545: Epoch time: 18.5 s +2024-11-22 17:49:55.704216: +2024-11-22 17:49:55.704414: Epoch 5593 +2024-11-22 17:49:55.704788: Current learning rate: 0.00339 +2024-11-22 17:50:14.782167: train_loss -0.8006 +2024-11-22 17:50:14.798422: val_loss -0.7815 +2024-11-22 17:50:14.798595: Pseudo dice [0.8478] +2024-11-22 17:50:14.798697: Epoch time: 19.08 s +2024-11-22 17:50:15.652052: +2024-11-22 17:50:15.652257: Epoch 5594 +2024-11-22 17:50:15.652376: Current learning rate: 0.00339 +2024-11-22 17:50:35.414140: train_loss -0.7955 +2024-11-22 17:50:35.414748: val_loss -0.7847 +2024-11-22 17:50:35.414851: Pseudo dice [0.8552] +2024-11-22 17:50:35.414970: Epoch time: 19.76 s +2024-11-22 17:50:36.689462: +2024-11-22 17:50:36.689679: Epoch 5595 +2024-11-22 17:50:36.689814: Current learning rate: 0.00339 +2024-11-22 17:50:55.745645: train_loss -0.7924 +2024-11-22 17:50:55.747369: val_loss -0.77 +2024-11-22 17:50:55.747533: Pseudo dice [0.8651] +2024-11-22 17:50:55.747626: Epoch time: 19.06 s +2024-11-22 17:50:56.611350: +2024-11-22 17:50:56.611576: Epoch 5596 +2024-11-22 17:50:56.611711: Current learning rate: 0.00339 +2024-11-22 17:51:14.908986: train_loss -0.7921 +2024-11-22 17:51:14.922353: val_loss -0.7755 +2024-11-22 17:51:14.922472: Pseudo dice [0.85] +2024-11-22 17:51:14.922578: Epoch time: 18.3 s +2024-11-22 17:51:15.781907: +2024-11-22 17:51:15.782128: Epoch 5597 +2024-11-22 17:51:15.782253: Current learning rate: 0.00339 +2024-11-22 17:51:34.463660: train_loss -0.7809 +2024-11-22 17:51:34.474937: val_loss -0.7849 +2024-11-22 17:51:34.475101: Pseudo dice [0.859] +2024-11-22 17:51:34.475206: Epoch time: 18.68 s +2024-11-22 17:51:35.547808: +2024-11-22 17:51:35.548101: Epoch 5598 +2024-11-22 17:51:35.548229: Current learning rate: 0.00339 +2024-11-22 17:51:54.665662: train_loss -0.7958 +2024-11-22 17:51:54.685676: val_loss -0.7718 +2024-11-22 17:51:54.685822: Pseudo dice [0.8433] +2024-11-22 17:51:54.685920: Epoch time: 19.12 s +2024-11-22 17:51:55.549408: +2024-11-22 17:51:55.549599: Epoch 5599 +2024-11-22 17:51:55.549721: Current learning rate: 0.00339 +2024-11-22 17:52:14.272854: train_loss -0.799 +2024-11-22 17:52:14.346594: val_loss -0.7622 +2024-11-22 17:52:14.346806: Pseudo dice [0.8585] +2024-11-22 17:52:14.346917: Epoch time: 18.72 s +2024-11-22 17:52:15.515700: +2024-11-22 17:52:15.515951: Epoch 5600 +2024-11-22 17:52:15.516071: Current learning rate: 0.00338 +2024-11-22 17:52:34.944763: train_loss -0.7983 +2024-11-22 17:52:34.998863: val_loss -0.7826 +2024-11-22 17:52:34.999044: Pseudo dice [0.8709] +2024-11-22 17:52:34.999160: Epoch time: 19.43 s +2024-11-22 17:52:35.866783: +2024-11-22 17:52:35.866990: Epoch 5601 +2024-11-22 17:52:35.867108: Current learning rate: 0.00338 +2024-11-22 17:52:55.201174: train_loss -0.8075 +2024-11-22 17:52:55.226181: val_loss -0.7868 +2024-11-22 17:52:55.226332: Pseudo dice [0.8605] +2024-11-22 17:52:55.226419: Epoch time: 19.34 s +2024-11-22 17:52:56.386001: +2024-11-22 17:52:56.386198: Epoch 5602 +2024-11-22 17:52:56.386319: Current learning rate: 0.00338 +2024-11-22 17:53:15.287362: train_loss -0.799 +2024-11-22 17:53:15.328614: val_loss -0.7936 +2024-11-22 17:53:15.328785: Pseudo dice [0.8546] +2024-11-22 17:53:15.328888: Epoch time: 18.9 s +2024-11-22 17:53:16.314796: +2024-11-22 17:53:16.315441: Epoch 5603 +2024-11-22 17:53:16.315576: Current learning rate: 0.00338 +2024-11-22 17:53:36.009961: train_loss -0.8061 +2024-11-22 17:53:36.039187: val_loss -0.7498 +2024-11-22 17:53:36.039363: Pseudo dice [0.8411] +2024-11-22 17:53:36.039481: Epoch time: 19.7 s +2024-11-22 17:53:37.152874: +2024-11-22 17:53:37.153093: Epoch 5604 +2024-11-22 17:53:37.153210: Current learning rate: 0.00338 +2024-11-22 17:53:55.966493: train_loss -0.7986 +2024-11-22 17:53:55.982557: val_loss -0.7734 +2024-11-22 17:53:55.982692: Pseudo dice [0.8363] +2024-11-22 17:53:55.982777: Epoch time: 18.81 s +2024-11-22 17:53:56.851789: +2024-11-22 17:53:56.852026: Epoch 5605 +2024-11-22 17:53:56.852156: Current learning rate: 0.00338 +2024-11-22 17:54:16.737869: train_loss -0.7957 +2024-11-22 17:54:16.752197: val_loss -0.7831 +2024-11-22 17:54:16.752362: Pseudo dice [0.8585] +2024-11-22 17:54:16.752471: Epoch time: 19.89 s +2024-11-22 17:54:17.629040: +2024-11-22 17:54:17.629439: Epoch 5606 +2024-11-22 17:54:17.629591: Current learning rate: 0.00338 +2024-11-22 17:54:38.200945: train_loss -0.7985 +2024-11-22 17:54:38.237590: val_loss -0.7647 +2024-11-22 17:54:38.237778: Pseudo dice [0.8532] +2024-11-22 17:54:38.237886: Epoch time: 20.57 s +2024-11-22 17:54:39.096724: +2024-11-22 17:54:39.096936: Epoch 5607 +2024-11-22 17:54:39.097074: Current learning rate: 0.00337 +2024-11-22 17:54:58.454652: train_loss -0.7629 +2024-11-22 17:54:58.473233: val_loss -0.7522 +2024-11-22 17:54:58.473392: Pseudo dice [0.8437] +2024-11-22 17:54:58.473484: Epoch time: 19.36 s +2024-11-22 17:54:59.367611: +2024-11-22 17:54:59.367831: Epoch 5608 +2024-11-22 17:54:59.367956: Current learning rate: 0.00337 +2024-11-22 17:55:18.256938: train_loss -0.7868 +2024-11-22 17:55:18.271315: val_loss -0.7575 +2024-11-22 17:55:18.271541: Pseudo dice [0.8501] +2024-11-22 17:55:18.271634: Epoch time: 18.89 s +2024-11-22 17:55:19.322876: +2024-11-22 17:55:19.323093: Epoch 5609 +2024-11-22 17:55:19.323210: Current learning rate: 0.00337 +2024-11-22 17:55:38.312375: train_loss -0.7823 +2024-11-22 17:55:38.324319: val_loss -0.7698 +2024-11-22 17:55:38.324462: Pseudo dice [0.8547] +2024-11-22 17:55:38.324555: Epoch time: 18.99 s +2024-11-22 17:55:39.362293: +2024-11-22 17:55:39.362494: Epoch 5610 +2024-11-22 17:55:39.362631: Current learning rate: 0.00337 +2024-11-22 17:55:59.916051: train_loss -0.7882 +2024-11-22 17:55:59.921750: val_loss -0.7583 +2024-11-22 17:55:59.921942: Pseudo dice [0.8391] +2024-11-22 17:55:59.922045: Epoch time: 20.55 s +2024-11-22 17:56:00.878865: +2024-11-22 17:56:00.879074: Epoch 5611 +2024-11-22 17:56:00.879208: Current learning rate: 0.00337 +2024-11-22 17:56:20.699849: train_loss -0.788 +2024-11-22 17:56:20.732458: val_loss -0.7834 +2024-11-22 17:56:20.732676: Pseudo dice [0.8646] +2024-11-22 17:56:20.732770: Epoch time: 19.82 s +2024-11-22 17:56:21.607703: +2024-11-22 17:56:21.607944: Epoch 5612 +2024-11-22 17:56:21.608066: Current learning rate: 0.00337 +2024-11-22 17:56:40.748052: train_loss -0.7942 +2024-11-22 17:56:40.776523: val_loss -0.7751 +2024-11-22 17:56:40.776700: Pseudo dice [0.8558] +2024-11-22 17:56:40.776801: Epoch time: 19.14 s +2024-11-22 17:56:41.780356: +2024-11-22 17:56:41.780808: Epoch 5613 +2024-11-22 17:56:41.780926: Current learning rate: 0.00337 +2024-11-22 17:57:00.517439: train_loss -0.7823 +2024-11-22 17:57:00.554098: val_loss -0.7649 +2024-11-22 17:57:00.554292: Pseudo dice [0.8563] +2024-11-22 17:57:00.554403: Epoch time: 18.74 s +2024-11-22 17:57:01.762037: +2024-11-22 17:57:01.762241: Epoch 5614 +2024-11-22 17:57:01.762367: Current learning rate: 0.00337 +2024-11-22 17:57:20.521427: train_loss -0.7977 +2024-11-22 17:57:20.539862: val_loss -0.7711 +2024-11-22 17:57:20.540035: Pseudo dice [0.8662] +2024-11-22 17:57:20.540138: Epoch time: 18.76 s +2024-11-22 17:57:21.543746: +2024-11-22 17:57:21.543946: Epoch 5615 +2024-11-22 17:57:21.544082: Current learning rate: 0.00336 +2024-11-22 17:57:39.883976: train_loss -0.7997 +2024-11-22 17:57:39.909206: val_loss -0.7708 +2024-11-22 17:57:39.909378: Pseudo dice [0.8514] +2024-11-22 17:57:39.909492: Epoch time: 18.34 s +2024-11-22 17:57:40.921926: +2024-11-22 17:57:40.922111: Epoch 5616 +2024-11-22 17:57:40.922241: Current learning rate: 0.00336 +2024-11-22 17:57:58.879990: train_loss -0.7954 +2024-11-22 17:57:58.888208: val_loss -0.7745 +2024-11-22 17:57:58.888371: Pseudo dice [0.8524] +2024-11-22 17:57:58.888473: Epoch time: 17.96 s +2024-11-22 17:57:59.760042: +2024-11-22 17:57:59.760272: Epoch 5617 +2024-11-22 17:57:59.760396: Current learning rate: 0.00336 +2024-11-22 17:58:19.628543: train_loss -0.799 +2024-11-22 17:58:19.635323: val_loss -0.7782 +2024-11-22 17:58:19.635464: Pseudo dice [0.8502] +2024-11-22 17:58:19.635558: Epoch time: 19.87 s +2024-11-22 17:58:20.973943: +2024-11-22 17:58:20.974185: Epoch 5618 +2024-11-22 17:58:20.974357: Current learning rate: 0.00336 +2024-11-22 17:58:39.108194: train_loss -0.7955 +2024-11-22 17:58:39.166705: val_loss -0.7399 +2024-11-22 17:58:39.167147: Pseudo dice [0.8421] +2024-11-22 17:58:39.167263: Epoch time: 18.14 s +2024-11-22 17:58:40.214095: +2024-11-22 17:58:40.214315: Epoch 5619 +2024-11-22 17:58:40.214450: Current learning rate: 0.00336 +2024-11-22 17:58:59.333581: train_loss -0.7881 +2024-11-22 17:58:59.339022: val_loss -0.7672 +2024-11-22 17:58:59.339148: Pseudo dice [0.8614] +2024-11-22 17:58:59.339241: Epoch time: 19.12 s +2024-11-22 17:59:00.210759: +2024-11-22 17:59:00.210984: Epoch 5620 +2024-11-22 17:59:00.211126: Current learning rate: 0.00336 +2024-11-22 17:59:18.863671: train_loss -0.792 +2024-11-22 17:59:18.879998: val_loss -0.7522 +2024-11-22 17:59:18.880160: Pseudo dice [0.8438] +2024-11-22 17:59:18.880251: Epoch time: 18.65 s +2024-11-22 17:59:19.904270: +2024-11-22 17:59:19.904488: Epoch 5621 +2024-11-22 17:59:19.904629: Current learning rate: 0.00336 +2024-11-22 17:59:39.863726: train_loss -0.789 +2024-11-22 17:59:39.869083: val_loss -0.7803 +2024-11-22 17:59:39.869196: Pseudo dice [0.8528] +2024-11-22 17:59:39.869289: Epoch time: 19.96 s +2024-11-22 17:59:40.952172: +2024-11-22 17:59:40.952372: Epoch 5622 +2024-11-22 17:59:40.952492: Current learning rate: 0.00336 +2024-11-22 18:00:00.690881: train_loss -0.7936 +2024-11-22 18:00:00.701114: val_loss -0.7803 +2024-11-22 18:00:00.701271: Pseudo dice [0.8436] +2024-11-22 18:00:00.701362: Epoch time: 19.74 s +2024-11-22 18:00:01.651712: +2024-11-22 18:00:01.651918: Epoch 5623 +2024-11-22 18:00:01.652039: Current learning rate: 0.00335 +2024-11-22 18:00:21.369010: train_loss -0.8021 +2024-11-22 18:00:21.374938: val_loss -0.7769 +2024-11-22 18:00:21.375083: Pseudo dice [0.8602] +2024-11-22 18:00:21.375167: Epoch time: 19.72 s +2024-11-22 18:00:22.397005: +2024-11-22 18:00:22.397223: Epoch 5624 +2024-11-22 18:00:22.397337: Current learning rate: 0.00335 +2024-11-22 18:00:41.113771: train_loss -0.7937 +2024-11-22 18:00:41.119853: val_loss -0.7422 +2024-11-22 18:00:41.119993: Pseudo dice [0.8517] +2024-11-22 18:00:41.120085: Epoch time: 18.72 s +2024-11-22 18:00:42.196251: +2024-11-22 18:00:42.196475: Epoch 5625 +2024-11-22 18:00:42.196599: Current learning rate: 0.00335 +2024-11-22 18:01:01.564933: train_loss -0.7968 +2024-11-22 18:01:01.573503: val_loss -0.7619 +2024-11-22 18:01:01.573631: Pseudo dice [0.8496] +2024-11-22 18:01:01.573737: Epoch time: 19.37 s +2024-11-22 18:01:02.639960: +2024-11-22 18:01:02.640170: Epoch 5626 +2024-11-22 18:01:02.640284: Current learning rate: 0.00335 +2024-11-22 18:01:21.696588: train_loss -0.8038 +2024-11-22 18:01:21.710630: val_loss -0.7444 +2024-11-22 18:01:21.710792: Pseudo dice [0.8584] +2024-11-22 18:01:21.710895: Epoch time: 19.06 s +2024-11-22 18:01:22.671523: +2024-11-22 18:01:22.671726: Epoch 5627 +2024-11-22 18:01:22.671847: Current learning rate: 0.00335 +2024-11-22 18:01:41.365048: train_loss -0.7944 +2024-11-22 18:01:41.374163: val_loss -0.7848 +2024-11-22 18:01:41.374295: Pseudo dice [0.8699] +2024-11-22 18:01:41.374388: Epoch time: 18.69 s +2024-11-22 18:01:42.331760: +2024-11-22 18:01:42.331958: Epoch 5628 +2024-11-22 18:01:42.332087: Current learning rate: 0.00335 +2024-11-22 18:02:02.018803: train_loss -0.7963 +2024-11-22 18:02:02.025280: val_loss -0.7812 +2024-11-22 18:02:02.025410: Pseudo dice [0.8551] +2024-11-22 18:02:02.025496: Epoch time: 19.69 s +2024-11-22 18:02:02.994336: +2024-11-22 18:02:02.997790: Epoch 5629 +2024-11-22 18:02:02.997924: Current learning rate: 0.00335 +2024-11-22 18:02:22.935191: train_loss -0.804 +2024-11-22 18:02:22.946568: val_loss -0.7633 +2024-11-22 18:02:22.946716: Pseudo dice [0.8426] +2024-11-22 18:02:22.946816: Epoch time: 19.94 s +2024-11-22 18:02:24.240272: +2024-11-22 18:02:24.240699: Epoch 5630 +2024-11-22 18:02:24.240860: Current learning rate: 0.00335 +2024-11-22 18:02:43.183066: train_loss -0.8042 +2024-11-22 18:02:43.188087: val_loss -0.773 +2024-11-22 18:02:43.188196: Pseudo dice [0.8573] +2024-11-22 18:02:43.188289: Epoch time: 18.94 s +2024-11-22 18:02:44.048692: +2024-11-22 18:02:44.049136: Epoch 5631 +2024-11-22 18:02:44.049282: Current learning rate: 0.00334 +2024-11-22 18:03:02.656304: train_loss -0.8007 +2024-11-22 18:03:02.662842: val_loss -0.7861 +2024-11-22 18:03:02.663001: Pseudo dice [0.8657] +2024-11-22 18:03:02.663108: Epoch time: 18.61 s +2024-11-22 18:03:03.523504: +2024-11-22 18:03:03.524110: Epoch 5632 +2024-11-22 18:03:03.524243: Current learning rate: 0.00334 +2024-11-22 18:03:22.514235: train_loss -0.8075 +2024-11-22 18:03:22.533445: val_loss -0.7732 +2024-11-22 18:03:22.533600: Pseudo dice [0.8546] +2024-11-22 18:03:22.533701: Epoch time: 18.99 s +2024-11-22 18:03:23.388647: +2024-11-22 18:03:23.389053: Epoch 5633 +2024-11-22 18:03:23.389189: Current learning rate: 0.00334 +2024-11-22 18:03:42.555513: train_loss -0.7988 +2024-11-22 18:03:42.562741: val_loss -0.7357 +2024-11-22 18:03:42.562889: Pseudo dice [0.8602] +2024-11-22 18:03:42.562984: Epoch time: 19.17 s +2024-11-22 18:03:43.714258: +2024-11-22 18:03:43.714674: Epoch 5634 +2024-11-22 18:03:43.714831: Current learning rate: 0.00334 +2024-11-22 18:04:02.983064: train_loss -0.7974 +2024-11-22 18:04:02.987156: val_loss -0.7662 +2024-11-22 18:04:02.987284: Pseudo dice [0.8493] +2024-11-22 18:04:02.987386: Epoch time: 19.27 s +2024-11-22 18:04:03.870665: +2024-11-22 18:04:03.871097: Epoch 5635 +2024-11-22 18:04:03.871234: Current learning rate: 0.00334 +2024-11-22 18:04:21.740249: train_loss -0.7976 +2024-11-22 18:04:21.757732: val_loss -0.7726 +2024-11-22 18:04:21.757887: Pseudo dice [0.858] +2024-11-22 18:04:21.757980: Epoch time: 17.87 s +2024-11-22 18:04:22.627918: +2024-11-22 18:04:22.628536: Epoch 5636 +2024-11-22 18:04:22.628678: Current learning rate: 0.00334 +2024-11-22 18:04:42.104210: train_loss -0.7954 +2024-11-22 18:04:42.113094: val_loss -0.7914 +2024-11-22 18:04:42.113215: Pseudo dice [0.8601] +2024-11-22 18:04:42.113318: Epoch time: 19.48 s +2024-11-22 18:04:43.032665: +2024-11-22 18:04:43.033363: Epoch 5637 +2024-11-22 18:04:43.033502: Current learning rate: 0.00334 +2024-11-22 18:05:02.211411: train_loss -0.7912 +2024-11-22 18:05:02.217758: val_loss -0.7968 +2024-11-22 18:05:02.217901: Pseudo dice [0.85] +2024-11-22 18:05:02.217999: Epoch time: 19.18 s +2024-11-22 18:05:03.113691: +2024-11-22 18:05:03.114337: Epoch 5638 +2024-11-22 18:05:03.114491: Current learning rate: 0.00334 +2024-11-22 18:05:22.281047: train_loss -0.7997 +2024-11-22 18:05:22.286963: val_loss -0.7626 +2024-11-22 18:05:22.287167: Pseudo dice [0.8622] +2024-11-22 18:05:22.287257: Epoch time: 19.17 s +2024-11-22 18:05:23.164681: +2024-11-22 18:05:23.165057: Epoch 5639 +2024-11-22 18:05:23.165200: Current learning rate: 0.00333 +2024-11-22 18:05:42.888600: train_loss -0.7995 +2024-11-22 18:05:42.898170: val_loss -0.7913 +2024-11-22 18:05:42.898310: Pseudo dice [0.8608] +2024-11-22 18:05:42.898397: Epoch time: 19.72 s +2024-11-22 18:05:43.945110: +2024-11-22 18:05:43.946222: Epoch 5640 +2024-11-22 18:05:43.946353: Current learning rate: 0.00333 +2024-11-22 18:06:04.134903: train_loss -0.8011 +2024-11-22 18:06:04.143620: val_loss -0.7524 +2024-11-22 18:06:04.143763: Pseudo dice [0.8429] +2024-11-22 18:06:04.143864: Epoch time: 20.19 s +2024-11-22 18:06:05.258752: +2024-11-22 18:06:05.258960: Epoch 5641 +2024-11-22 18:06:05.259093: Current learning rate: 0.00333 +2024-11-22 18:06:24.480183: train_loss -0.8028 +2024-11-22 18:06:24.486833: val_loss -0.7542 +2024-11-22 18:06:24.487084: Pseudo dice [0.8483] +2024-11-22 18:06:24.487192: Epoch time: 19.22 s +2024-11-22 18:06:25.792092: +2024-11-22 18:06:25.793095: Epoch 5642 +2024-11-22 18:06:25.793229: Current learning rate: 0.00333 +2024-11-22 18:06:45.337725: train_loss -0.7964 +2024-11-22 18:06:45.341228: val_loss -0.7711 +2024-11-22 18:06:45.341359: Pseudo dice [0.8461] +2024-11-22 18:06:45.341448: Epoch time: 19.55 s +2024-11-22 18:06:46.241994: +2024-11-22 18:06:46.242478: Epoch 5643 +2024-11-22 18:06:46.242606: Current learning rate: 0.00333 +2024-11-22 18:07:05.971076: train_loss -0.7984 +2024-11-22 18:07:05.976614: val_loss -0.7615 +2024-11-22 18:07:05.976765: Pseudo dice [0.8621] +2024-11-22 18:07:05.976879: Epoch time: 19.73 s +2024-11-22 18:07:06.923552: +2024-11-22 18:07:06.924055: Epoch 5644 +2024-11-22 18:07:06.924198: Current learning rate: 0.00333 +2024-11-22 18:07:26.101585: train_loss -0.8043 +2024-11-22 18:07:26.106343: val_loss -0.7713 +2024-11-22 18:07:26.106479: Pseudo dice [0.856] +2024-11-22 18:07:26.106580: Epoch time: 19.18 s +2024-11-22 18:07:27.239351: +2024-11-22 18:07:27.240828: Epoch 5645 +2024-11-22 18:07:27.240962: Current learning rate: 0.00333 +2024-11-22 18:07:47.657566: train_loss -0.8029 +2024-11-22 18:07:47.663198: val_loss -0.79 +2024-11-22 18:07:47.663348: Pseudo dice [0.8586] +2024-11-22 18:07:47.663448: Epoch time: 20.42 s +2024-11-22 18:07:48.685125: +2024-11-22 18:07:48.686437: Epoch 5646 +2024-11-22 18:07:48.686576: Current learning rate: 0.00333 +2024-11-22 18:08:09.167072: train_loss -0.7974 +2024-11-22 18:08:09.175174: val_loss -0.7855 +2024-11-22 18:08:09.175310: Pseudo dice [0.8596] +2024-11-22 18:08:09.175398: Epoch time: 20.48 s +2024-11-22 18:08:10.232645: +2024-11-22 18:08:10.233617: Epoch 5647 +2024-11-22 18:08:10.233746: Current learning rate: 0.00332 +2024-11-22 18:08:30.769605: train_loss -0.7972 +2024-11-22 18:08:30.774003: val_loss -0.7788 +2024-11-22 18:08:30.774163: Pseudo dice [0.8755] +2024-11-22 18:08:30.774272: Epoch time: 20.54 s +2024-11-22 18:08:31.636708: +2024-11-22 18:08:31.637725: Epoch 5648 +2024-11-22 18:08:31.637861: Current learning rate: 0.00332 +2024-11-22 18:08:50.257457: train_loss -0.8049 +2024-11-22 18:08:50.263977: val_loss -0.7782 +2024-11-22 18:08:50.264150: Pseudo dice [0.8475] +2024-11-22 18:08:50.264261: Epoch time: 18.62 s +2024-11-22 18:08:51.197637: +2024-11-22 18:08:51.198105: Epoch 5649 +2024-11-22 18:08:51.198231: Current learning rate: 0.00332 +2024-11-22 18:09:11.121221: train_loss -0.8 +2024-11-22 18:09:11.129777: val_loss -0.7799 +2024-11-22 18:09:11.129930: Pseudo dice [0.8627] +2024-11-22 18:09:11.130115: Epoch time: 19.92 s +2024-11-22 18:09:12.312108: +2024-11-22 18:09:12.313024: Epoch 5650 +2024-11-22 18:09:12.313151: Current learning rate: 0.00332 +2024-11-22 18:09:31.642071: train_loss -0.792 +2024-11-22 18:09:31.653725: val_loss -0.7862 +2024-11-22 18:09:31.653866: Pseudo dice [0.858] +2024-11-22 18:09:31.653953: Epoch time: 19.33 s +2024-11-22 18:09:32.637941: +2024-11-22 18:09:32.639766: Epoch 5651 +2024-11-22 18:09:32.639897: Current learning rate: 0.00332 +2024-11-22 18:09:52.119272: train_loss -0.801 +2024-11-22 18:09:52.128697: val_loss -0.7759 +2024-11-22 18:09:52.128827: Pseudo dice [0.872] +2024-11-22 18:09:52.128919: Epoch time: 19.48 s +2024-11-22 18:09:53.108303: +2024-11-22 18:09:53.109664: Epoch 5652 +2024-11-22 18:09:53.109796: Current learning rate: 0.00332 +2024-11-22 18:10:12.679509: train_loss -0.8067 +2024-11-22 18:10:12.695417: val_loss -0.7553 +2024-11-22 18:10:12.695573: Pseudo dice [0.8547] +2024-11-22 18:10:12.695676: Epoch time: 19.57 s +2024-11-22 18:10:13.694498: +2024-11-22 18:10:13.695076: Epoch 5653 +2024-11-22 18:10:13.695205: Current learning rate: 0.00332 +2024-11-22 18:10:33.152816: train_loss -0.8006 +2024-11-22 18:10:33.159561: val_loss -0.7812 +2024-11-22 18:10:33.159726: Pseudo dice [0.8615] +2024-11-22 18:10:33.159830: Epoch time: 19.46 s +2024-11-22 18:10:34.021506: +2024-11-22 18:10:34.023115: Epoch 5654 +2024-11-22 18:10:34.023246: Current learning rate: 0.00332 +2024-11-22 18:10:54.051950: train_loss -0.8108 +2024-11-22 18:10:54.057964: val_loss -0.8048 +2024-11-22 18:10:54.058168: Pseudo dice [0.8555] +2024-11-22 18:10:54.058278: Epoch time: 20.03 s +2024-11-22 18:10:54.955533: +2024-11-22 18:10:54.956362: Epoch 5655 +2024-11-22 18:10:54.956497: Current learning rate: 0.00331 +2024-11-22 18:11:15.388119: train_loss -0.7996 +2024-11-22 18:11:15.395123: val_loss -0.7918 +2024-11-22 18:11:15.395274: Pseudo dice [0.8711] +2024-11-22 18:11:15.395366: Epoch time: 20.43 s +2024-11-22 18:11:16.398081: +2024-11-22 18:11:16.399611: Epoch 5656 +2024-11-22 18:11:16.399741: Current learning rate: 0.00331 +2024-11-22 18:11:36.261429: train_loss -0.8017 +2024-11-22 18:11:36.264315: val_loss -0.7803 +2024-11-22 18:11:36.282228: Pseudo dice [0.8596] +2024-11-22 18:11:36.282357: Epoch time: 19.86 s +2024-11-22 18:11:37.149884: +2024-11-22 18:11:37.150974: Epoch 5657 +2024-11-22 18:11:37.151120: Current learning rate: 0.00331 +2024-11-22 18:11:57.291081: train_loss -0.7961 +2024-11-22 18:11:57.310386: val_loss -0.7638 +2024-11-22 18:11:57.310519: Pseudo dice [0.8622] +2024-11-22 18:11:57.310634: Epoch time: 20.14 s +2024-11-22 18:11:58.340429: +2024-11-22 18:11:58.341415: Epoch 5658 +2024-11-22 18:11:58.341537: Current learning rate: 0.00331 +2024-11-22 18:12:18.125103: train_loss -0.7879 +2024-11-22 18:12:18.137282: val_loss -0.7772 +2024-11-22 18:12:18.137419: Pseudo dice [0.8563] +2024-11-22 18:12:18.137681: Epoch time: 19.79 s +2024-11-22 18:12:19.086241: +2024-11-22 18:12:19.087551: Epoch 5659 +2024-11-22 18:12:19.087687: Current learning rate: 0.00331 +2024-11-22 18:12:39.131993: train_loss -0.8007 +2024-11-22 18:12:39.135612: val_loss -0.7705 +2024-11-22 18:12:39.135732: Pseudo dice [0.858] +2024-11-22 18:12:39.135830: Epoch time: 20.05 s +2024-11-22 18:12:40.057650: +2024-11-22 18:12:40.058555: Epoch 5660 +2024-11-22 18:12:40.058687: Current learning rate: 0.00331 +2024-11-22 18:13:00.312571: train_loss -0.7997 +2024-11-22 18:13:00.317210: val_loss -0.8024 +2024-11-22 18:13:00.317345: Pseudo dice [0.8713] +2024-11-22 18:13:00.317435: Epoch time: 20.26 s +2024-11-22 18:13:01.187282: +2024-11-22 18:13:01.188724: Epoch 5661 +2024-11-22 18:13:01.188869: Current learning rate: 0.00331 +2024-11-22 18:13:20.370193: train_loss -0.8057 +2024-11-22 18:13:20.375814: val_loss -0.7732 +2024-11-22 18:13:20.375969: Pseudo dice [0.8568] +2024-11-22 18:13:20.376085: Epoch time: 19.18 s +2024-11-22 18:13:21.348385: +2024-11-22 18:13:21.349564: Epoch 5662 +2024-11-22 18:13:21.349690: Current learning rate: 0.00331 +2024-11-22 18:13:41.334968: train_loss -0.7918 +2024-11-22 18:13:41.342394: val_loss -0.7651 +2024-11-22 18:13:41.342531: Pseudo dice [0.8506] +2024-11-22 18:13:41.342635: Epoch time: 19.99 s +2024-11-22 18:13:42.217870: +2024-11-22 18:13:42.219304: Epoch 5663 +2024-11-22 18:13:42.219449: Current learning rate: 0.0033 +2024-11-22 18:14:01.193432: train_loss -0.8029 +2024-11-22 18:14:01.216043: val_loss -0.785 +2024-11-22 18:14:01.216215: Pseudo dice [0.8544] +2024-11-22 18:14:01.216320: Epoch time: 18.98 s +2024-11-22 18:14:02.221657: +2024-11-22 18:14:02.222778: Epoch 5664 +2024-11-22 18:14:02.222907: Current learning rate: 0.0033 +2024-11-22 18:14:21.641897: train_loss -0.7982 +2024-11-22 18:14:21.648952: val_loss -0.7714 +2024-11-22 18:14:21.649111: Pseudo dice [0.8574] +2024-11-22 18:14:21.649317: Epoch time: 19.42 s +2024-11-22 18:14:22.973011: +2024-11-22 18:14:22.974285: Epoch 5665 +2024-11-22 18:14:22.974412: Current learning rate: 0.0033 +2024-11-22 18:14:43.339433: train_loss -0.7993 +2024-11-22 18:14:43.361269: val_loss -0.7405 +2024-11-22 18:14:43.361418: Pseudo dice [0.8478] +2024-11-22 18:14:43.361523: Epoch time: 20.37 s +2024-11-22 18:14:44.381664: +2024-11-22 18:14:44.383057: Epoch 5666 +2024-11-22 18:14:44.383188: Current learning rate: 0.0033 +2024-11-22 18:15:04.747567: train_loss -0.8003 +2024-11-22 18:15:04.754008: val_loss -0.7701 +2024-11-22 18:15:04.754154: Pseudo dice [0.8548] +2024-11-22 18:15:04.754250: Epoch time: 20.37 s +2024-11-22 18:15:05.820621: +2024-11-22 18:15:05.822444: Epoch 5667 +2024-11-22 18:15:05.822569: Current learning rate: 0.0033 +2024-11-22 18:15:25.417093: train_loss -0.7995 +2024-11-22 18:15:25.425265: val_loss -0.771 +2024-11-22 18:15:25.425388: Pseudo dice [0.8447] +2024-11-22 18:15:25.425473: Epoch time: 19.6 s +2024-11-22 18:15:26.401876: +2024-11-22 18:15:26.403440: Epoch 5668 +2024-11-22 18:15:26.403562: Current learning rate: 0.0033 +2024-11-22 18:15:46.872853: train_loss -0.7968 +2024-11-22 18:15:46.878712: val_loss -0.7954 +2024-11-22 18:15:46.878884: Pseudo dice [0.8589] +2024-11-22 18:15:46.878990: Epoch time: 20.47 s +2024-11-22 18:15:47.794699: +2024-11-22 18:15:47.795688: Epoch 5669 +2024-11-22 18:15:47.795812: Current learning rate: 0.0033 +2024-11-22 18:16:07.031879: train_loss -0.8026 +2024-11-22 18:16:07.041305: val_loss -0.7625 +2024-11-22 18:16:07.041451: Pseudo dice [0.8463] +2024-11-22 18:16:07.041609: Epoch time: 19.24 s +2024-11-22 18:16:08.119108: +2024-11-22 18:16:08.120567: Epoch 5670 +2024-11-22 18:16:08.120693: Current learning rate: 0.00329 +2024-11-22 18:16:26.514112: train_loss -0.7944 +2024-11-22 18:16:26.520967: val_loss -0.7827 +2024-11-22 18:16:26.521114: Pseudo dice [0.8589] +2024-11-22 18:16:26.521266: Epoch time: 18.4 s +2024-11-22 18:16:27.638622: +2024-11-22 18:16:27.639087: Epoch 5671 +2024-11-22 18:16:27.639227: Current learning rate: 0.00329 +2024-11-22 18:16:47.336382: train_loss -0.7931 +2024-11-22 18:16:47.347022: val_loss -0.7681 +2024-11-22 18:16:47.347234: Pseudo dice [0.8453] +2024-11-22 18:16:47.347340: Epoch time: 19.7 s +2024-11-22 18:16:48.261746: +2024-11-22 18:16:48.263441: Epoch 5672 +2024-11-22 18:16:48.263569: Current learning rate: 0.00329 +2024-11-22 18:17:08.057367: train_loss -0.7725 +2024-11-22 18:17:08.065176: val_loss -0.7714 +2024-11-22 18:17:08.065310: Pseudo dice [0.8426] +2024-11-22 18:17:08.065417: Epoch time: 19.8 s +2024-11-22 18:17:09.071249: +2024-11-22 18:17:09.072303: Epoch 5673 +2024-11-22 18:17:09.072437: Current learning rate: 0.00329 +2024-11-22 18:17:28.189710: train_loss -0.7755 +2024-11-22 18:17:28.198009: val_loss -0.7411 +2024-11-22 18:17:28.198157: Pseudo dice [0.8436] +2024-11-22 18:17:28.198248: Epoch time: 19.12 s +2024-11-22 18:17:29.214252: +2024-11-22 18:17:29.215824: Epoch 5674 +2024-11-22 18:17:29.215968: Current learning rate: 0.00329 +2024-11-22 18:17:48.114884: train_loss -0.7846 +2024-11-22 18:17:48.123017: val_loss -0.77 +2024-11-22 18:17:48.123158: Pseudo dice [0.8421] +2024-11-22 18:17:48.123247: Epoch time: 18.9 s +2024-11-22 18:17:49.086738: +2024-11-22 18:17:49.087530: Epoch 5675 +2024-11-22 18:17:49.087646: Current learning rate: 0.00329 +2024-11-22 18:18:10.228687: train_loss -0.7877 +2024-11-22 18:18:10.232461: val_loss -0.7633 +2024-11-22 18:18:10.232679: Pseudo dice [0.8458] +2024-11-22 18:18:10.232785: Epoch time: 21.14 s +2024-11-22 18:18:11.166796: +2024-11-22 18:18:11.167995: Epoch 5676 +2024-11-22 18:18:11.168142: Current learning rate: 0.00329 +2024-11-22 18:18:30.115374: train_loss -0.7934 +2024-11-22 18:18:30.125962: val_loss -0.788 +2024-11-22 18:18:30.126140: Pseudo dice [0.8487] +2024-11-22 18:18:30.126260: Epoch time: 18.95 s +2024-11-22 18:18:31.071069: +2024-11-22 18:18:31.071577: Epoch 5677 +2024-11-22 18:18:31.071706: Current learning rate: 0.00329 +2024-11-22 18:18:50.750667: train_loss -0.7941 +2024-11-22 18:18:50.757272: val_loss -0.7679 +2024-11-22 18:18:50.757415: Pseudo dice [0.86] +2024-11-22 18:18:50.757510: Epoch time: 19.68 s +2024-11-22 18:18:51.734726: +2024-11-22 18:18:51.736230: Epoch 5678 +2024-11-22 18:18:51.736371: Current learning rate: 0.00328 +2024-11-22 18:19:10.840727: train_loss -0.8025 +2024-11-22 18:19:10.848578: val_loss -0.7587 +2024-11-22 18:19:10.848735: Pseudo dice [0.8469] +2024-11-22 18:19:10.848842: Epoch time: 19.11 s +2024-11-22 18:19:11.814346: +2024-11-22 18:19:11.815523: Epoch 5679 +2024-11-22 18:19:11.815651: Current learning rate: 0.00328 +2024-11-22 18:19:31.630830: train_loss -0.8004 +2024-11-22 18:19:31.639605: val_loss -0.7841 +2024-11-22 18:19:31.639860: Pseudo dice [0.8536] +2024-11-22 18:19:31.639957: Epoch time: 19.82 s +2024-11-22 18:19:32.542354: +2024-11-22 18:19:32.543334: Epoch 5680 +2024-11-22 18:19:32.543464: Current learning rate: 0.00328 +2024-11-22 18:19:51.762812: train_loss -0.8031 +2024-11-22 18:19:51.781011: val_loss -0.7653 +2024-11-22 18:19:51.781184: Pseudo dice [0.8604] +2024-11-22 18:19:51.781579: Epoch time: 19.22 s +2024-11-22 18:19:52.693215: +2024-11-22 18:19:52.693735: Epoch 5681 +2024-11-22 18:19:52.693869: Current learning rate: 0.00328 +2024-11-22 18:20:11.838191: train_loss -0.8 +2024-11-22 18:20:11.868916: val_loss -0.7635 +2024-11-22 18:20:11.869072: Pseudo dice [0.8594] +2024-11-22 18:20:11.869159: Epoch time: 19.15 s +2024-11-22 18:20:12.919326: +2024-11-22 18:20:12.921040: Epoch 5682 +2024-11-22 18:20:12.921185: Current learning rate: 0.00328 +2024-11-22 18:20:31.840409: train_loss -0.8006 +2024-11-22 18:20:31.846070: val_loss -0.7983 +2024-11-22 18:20:31.846219: Pseudo dice [0.8677] +2024-11-22 18:20:31.846327: Epoch time: 18.92 s +2024-11-22 18:20:32.851248: +2024-11-22 18:20:32.852770: Epoch 5683 +2024-11-22 18:20:32.852913: Current learning rate: 0.00328 +2024-11-22 18:20:52.455802: train_loss -0.7974 +2024-11-22 18:20:52.457954: val_loss -0.7781 +2024-11-22 18:20:52.458116: Pseudo dice [0.8597] +2024-11-22 18:20:52.458214: Epoch time: 19.61 s +2024-11-22 18:20:53.334773: +2024-11-22 18:20:53.335538: Epoch 5684 +2024-11-22 18:20:53.335674: Current learning rate: 0.00328 +2024-11-22 18:21:12.646472: train_loss -0.8028 +2024-11-22 18:21:12.652378: val_loss -0.7628 +2024-11-22 18:21:12.652521: Pseudo dice [0.8538] +2024-11-22 18:21:12.652644: Epoch time: 19.31 s +2024-11-22 18:21:13.562836: +2024-11-22 18:21:13.565083: Epoch 5685 +2024-11-22 18:21:13.565222: Current learning rate: 0.00328 +2024-11-22 18:21:33.051166: train_loss -0.7959 +2024-11-22 18:21:33.053431: val_loss -0.7747 +2024-11-22 18:21:33.053546: Pseudo dice [0.8554] +2024-11-22 18:21:33.053654: Epoch time: 19.49 s +2024-11-22 18:21:33.919362: +2024-11-22 18:21:33.919842: Epoch 5686 +2024-11-22 18:21:33.919973: Current learning rate: 0.00327 +2024-11-22 18:21:53.436924: train_loss -0.7962 +2024-11-22 18:21:53.445092: val_loss -0.7645 +2024-11-22 18:21:53.445260: Pseudo dice [0.8645] +2024-11-22 18:21:53.445368: Epoch time: 19.52 s +2024-11-22 18:21:54.316128: +2024-11-22 18:21:54.318342: Epoch 5687 +2024-11-22 18:21:54.318478: Current learning rate: 0.00327 +2024-11-22 18:22:14.026828: train_loss -0.8024 +2024-11-22 18:22:14.035188: val_loss -0.796 +2024-11-22 18:22:14.035310: Pseudo dice [0.8645] +2024-11-22 18:22:14.035409: Epoch time: 19.71 s +2024-11-22 18:22:15.447179: +2024-11-22 18:22:15.449500: Epoch 5688 +2024-11-22 18:22:15.449639: Current learning rate: 0.00327 +2024-11-22 18:22:33.887959: train_loss -0.8087 +2024-11-22 18:22:33.896020: val_loss -0.7819 +2024-11-22 18:22:33.896150: Pseudo dice [0.8706] +2024-11-22 18:22:33.896267: Epoch time: 18.44 s +2024-11-22 18:22:34.928397: +2024-11-22 18:22:34.930007: Epoch 5689 +2024-11-22 18:22:34.930138: Current learning rate: 0.00327 +2024-11-22 18:22:54.208371: train_loss -0.7848 +2024-11-22 18:22:54.211517: val_loss -0.7503 +2024-11-22 18:22:54.211671: Pseudo dice [0.8338] +2024-11-22 18:22:54.211797: Epoch time: 19.28 s +2024-11-22 18:22:55.115560: +2024-11-22 18:22:55.117219: Epoch 5690 +2024-11-22 18:22:55.117362: Current learning rate: 0.00327 +2024-11-22 18:23:14.048877: train_loss -0.7915 +2024-11-22 18:23:14.057271: val_loss -0.7591 +2024-11-22 18:23:14.064271: Pseudo dice [0.8661] +2024-11-22 18:23:14.064408: Epoch time: 18.93 s +2024-11-22 18:23:15.056328: +2024-11-22 18:23:15.057434: Epoch 5691 +2024-11-22 18:23:15.057565: Current learning rate: 0.00327 +2024-11-22 18:23:34.928734: train_loss -0.7941 +2024-11-22 18:23:34.936900: val_loss -0.7701 +2024-11-22 18:23:34.937041: Pseudo dice [0.8675] +2024-11-22 18:23:34.937157: Epoch time: 19.87 s +2024-11-22 18:23:36.084449: +2024-11-22 18:23:36.085917: Epoch 5692 +2024-11-22 18:23:36.086046: Current learning rate: 0.00327 +2024-11-22 18:23:56.317638: train_loss -0.7933 +2024-11-22 18:23:56.327349: val_loss -0.789 +2024-11-22 18:23:56.327517: Pseudo dice [0.8646] +2024-11-22 18:23:56.327615: Epoch time: 20.23 s +2024-11-22 18:23:57.387993: +2024-11-22 18:23:57.389668: Epoch 5693 +2024-11-22 18:23:57.389788: Current learning rate: 0.00327 +2024-11-22 18:24:17.289679: train_loss -0.8006 +2024-11-22 18:24:17.292176: val_loss -0.754 +2024-11-22 18:24:17.292284: Pseudo dice [0.8584] +2024-11-22 18:24:17.292373: Epoch time: 19.9 s +2024-11-22 18:24:18.155596: +2024-11-22 18:24:18.156070: Epoch 5694 +2024-11-22 18:24:18.156193: Current learning rate: 0.00326 +2024-11-22 18:24:38.037133: train_loss -0.7992 +2024-11-22 18:24:38.039668: val_loss -0.775 +2024-11-22 18:24:38.039798: Pseudo dice [0.8581] +2024-11-22 18:24:38.040108: Epoch time: 19.88 s +2024-11-22 18:24:38.988685: +2024-11-22 18:24:38.990421: Epoch 5695 +2024-11-22 18:24:38.990551: Current learning rate: 0.00326 +2024-11-22 18:24:57.769505: train_loss -0.7963 +2024-11-22 18:24:57.790641: val_loss -0.7613 +2024-11-22 18:24:57.790788: Pseudo dice [0.8529] +2024-11-22 18:24:57.790888: Epoch time: 18.78 s +2024-11-22 18:24:58.755449: +2024-11-22 18:24:58.756320: Epoch 5696 +2024-11-22 18:24:58.756485: Current learning rate: 0.00326 +2024-11-22 18:25:19.027738: train_loss -0.787 +2024-11-22 18:25:19.038563: val_loss -0.7782 +2024-11-22 18:25:19.038712: Pseudo dice [0.8398] +2024-11-22 18:25:19.038811: Epoch time: 20.27 s +2024-11-22 18:25:20.225925: +2024-11-22 18:25:20.226747: Epoch 5697 +2024-11-22 18:25:20.226872: Current learning rate: 0.00326 +2024-11-22 18:25:39.875370: train_loss -0.7952 +2024-11-22 18:25:39.883914: val_loss -0.7504 +2024-11-22 18:25:39.884036: Pseudo dice [0.8616] +2024-11-22 18:25:39.884168: Epoch time: 19.65 s +2024-11-22 18:25:40.782295: +2024-11-22 18:25:40.783709: Epoch 5698 +2024-11-22 18:25:40.783836: Current learning rate: 0.00326 +2024-11-22 18:26:00.898448: train_loss -0.8007 +2024-11-22 18:26:00.904940: val_loss -0.7883 +2024-11-22 18:26:00.905093: Pseudo dice [0.8679] +2024-11-22 18:26:00.905183: Epoch time: 20.12 s +2024-11-22 18:26:01.815021: +2024-11-22 18:26:01.816934: Epoch 5699 +2024-11-22 18:26:01.817055: Current learning rate: 0.00326 +2024-11-22 18:26:21.494073: train_loss -0.805 +2024-11-22 18:26:21.502480: val_loss -0.7846 +2024-11-22 18:26:21.502602: Pseudo dice [0.8549] +2024-11-22 18:26:21.502692: Epoch time: 19.68 s +2024-11-22 18:26:22.766305: +2024-11-22 18:26:22.778378: Epoch 5700 +2024-11-22 18:26:22.778533: Current learning rate: 0.00326 +2024-11-22 18:26:43.426267: train_loss -0.7904 +2024-11-22 18:26:43.447300: val_loss -0.7666 +2024-11-22 18:26:43.447462: Pseudo dice [0.8558] +2024-11-22 18:26:43.447566: Epoch time: 20.66 s +2024-11-22 18:26:44.376997: +2024-11-22 18:26:44.377503: Epoch 5701 +2024-11-22 18:26:44.377625: Current learning rate: 0.00326 +2024-11-22 18:27:03.395751: train_loss -0.79 +2024-11-22 18:27:03.399882: val_loss -0.774 +2024-11-22 18:27:03.399997: Pseudo dice [0.853] +2024-11-22 18:27:03.400094: Epoch time: 19.02 s +2024-11-22 18:27:04.277726: +2024-11-22 18:27:04.277942: Epoch 5702 +2024-11-22 18:27:04.278077: Current learning rate: 0.00325 +2024-11-22 18:27:24.406828: train_loss -0.7941 +2024-11-22 18:27:24.407573: val_loss -0.786 +2024-11-22 18:27:24.407662: Pseudo dice [0.8652] +2024-11-22 18:27:24.407744: Epoch time: 20.13 s +2024-11-22 18:27:25.273787: +2024-11-22 18:27:25.274001: Epoch 5703 +2024-11-22 18:27:25.274136: Current learning rate: 0.00325 +2024-11-22 18:27:45.774281: train_loss -0.7947 +2024-11-22 18:27:45.775415: val_loss -0.7522 +2024-11-22 18:27:45.775531: Pseudo dice [0.8524] +2024-11-22 18:27:45.775639: Epoch time: 20.5 s +2024-11-22 18:27:46.637658: +2024-11-22 18:27:46.637889: Epoch 5704 +2024-11-22 18:27:46.638016: Current learning rate: 0.00325 +2024-11-22 18:28:05.057808: train_loss -0.7992 +2024-11-22 18:28:05.059819: val_loss -0.795 +2024-11-22 18:28:05.059922: Pseudo dice [0.8646] +2024-11-22 18:28:05.060013: Epoch time: 18.42 s +2024-11-22 18:28:05.925098: +2024-11-22 18:28:05.925297: Epoch 5705 +2024-11-22 18:28:05.925439: Current learning rate: 0.00325 +2024-11-22 18:28:24.737379: train_loss -0.8012 +2024-11-22 18:28:24.738635: val_loss -0.7928 +2024-11-22 18:28:24.738788: Pseudo dice [0.8631] +2024-11-22 18:28:24.738898: Epoch time: 18.81 s +2024-11-22 18:28:25.640525: +2024-11-22 18:28:25.640715: Epoch 5706 +2024-11-22 18:28:25.640833: Current learning rate: 0.00325 +2024-11-22 18:28:44.895188: train_loss -0.7899 +2024-11-22 18:28:44.895695: val_loss -0.7724 +2024-11-22 18:28:44.895797: Pseudo dice [0.8682] +2024-11-22 18:28:44.896205: Epoch time: 19.26 s +2024-11-22 18:28:45.856316: +2024-11-22 18:28:45.856540: Epoch 5707 +2024-11-22 18:28:45.856652: Current learning rate: 0.00325 +2024-11-22 18:29:05.029821: train_loss -0.7904 +2024-11-22 18:29:05.031985: val_loss -0.7835 +2024-11-22 18:29:05.032110: Pseudo dice [0.8657] +2024-11-22 18:29:05.032221: Epoch time: 19.17 s +2024-11-22 18:29:05.903729: +2024-11-22 18:29:05.910743: Epoch 5708 +2024-11-22 18:29:05.912974: Current learning rate: 0.00325 +2024-11-22 18:29:25.141017: train_loss -0.7836 +2024-11-22 18:29:25.145870: val_loss -0.7887 +2024-11-22 18:29:25.145999: Pseudo dice [0.8648] +2024-11-22 18:29:25.146114: Epoch time: 19.24 s +2024-11-22 18:29:26.012107: +2024-11-22 18:29:26.012321: Epoch 5709 +2024-11-22 18:29:26.012460: Current learning rate: 0.00325 +2024-11-22 18:29:45.231252: train_loss -0.7882 +2024-11-22 18:29:45.233757: val_loss -0.7745 +2024-11-22 18:29:45.233862: Pseudo dice [0.8499] +2024-11-22 18:29:45.233950: Epoch time: 19.22 s +2024-11-22 18:29:46.099841: +2024-11-22 18:29:46.100072: Epoch 5710 +2024-11-22 18:29:46.100195: Current learning rate: 0.00324 +2024-11-22 18:30:04.152234: train_loss -0.7974 +2024-11-22 18:30:04.159854: val_loss -0.7681 +2024-11-22 18:30:04.159993: Pseudo dice [0.8596] +2024-11-22 18:30:04.160095: Epoch time: 18.05 s +2024-11-22 18:30:05.495373: +2024-11-22 18:30:05.495804: Epoch 5711 +2024-11-22 18:30:05.495944: Current learning rate: 0.00324 +2024-11-22 18:30:24.679717: train_loss -0.7997 +2024-11-22 18:30:24.699635: val_loss -0.7856 +2024-11-22 18:30:24.699807: Pseudo dice [0.8571] +2024-11-22 18:30:24.699906: Epoch time: 19.19 s +2024-11-22 18:30:25.614419: +2024-11-22 18:30:25.614614: Epoch 5712 +2024-11-22 18:30:25.614727: Current learning rate: 0.00324 +2024-11-22 18:30:44.900955: train_loss -0.8005 +2024-11-22 18:30:44.910283: val_loss -0.774 +2024-11-22 18:30:44.910381: Pseudo dice [0.8509] +2024-11-22 18:30:44.910470: Epoch time: 19.29 s +2024-11-22 18:30:45.772891: +2024-11-22 18:30:45.773377: Epoch 5713 +2024-11-22 18:30:45.773498: Current learning rate: 0.00324 +2024-11-22 18:31:04.531711: train_loss -0.8021 +2024-11-22 18:31:04.534634: val_loss -0.792 +2024-11-22 18:31:04.534750: Pseudo dice [0.8613] +2024-11-22 18:31:04.534844: Epoch time: 18.76 s +2024-11-22 18:31:05.401424: +2024-11-22 18:31:05.401634: Epoch 5714 +2024-11-22 18:31:05.401752: Current learning rate: 0.00324 +2024-11-22 18:31:24.850946: train_loss -0.8037 +2024-11-22 18:31:24.858126: val_loss -0.7745 +2024-11-22 18:31:24.858298: Pseudo dice [0.8638] +2024-11-22 18:31:24.858405: Epoch time: 19.45 s +2024-11-22 18:31:25.987215: +2024-11-22 18:31:25.987738: Epoch 5715 +2024-11-22 18:31:25.987856: Current learning rate: 0.00324 +2024-11-22 18:31:45.968540: train_loss -0.7998 +2024-11-22 18:31:45.972537: val_loss -0.762 +2024-11-22 18:31:45.982117: Pseudo dice [0.8566] +2024-11-22 18:31:45.982251: Epoch time: 19.98 s +2024-11-22 18:31:46.936014: +2024-11-22 18:31:46.936484: Epoch 5716 +2024-11-22 18:31:46.936618: Current learning rate: 0.00324 +2024-11-22 18:32:06.420195: train_loss -0.798 +2024-11-22 18:32:06.425564: val_loss -0.7679 +2024-11-22 18:32:06.425688: Pseudo dice [0.8553] +2024-11-22 18:32:06.425781: Epoch time: 19.49 s +2024-11-22 18:32:07.302981: +2024-11-22 18:32:07.303205: Epoch 5717 +2024-11-22 18:32:07.303337: Current learning rate: 0.00324 +2024-11-22 18:32:27.292498: train_loss -0.8034 +2024-11-22 18:32:27.338767: val_loss -0.7718 +2024-11-22 18:32:27.338914: Pseudo dice [0.8577] +2024-11-22 18:32:27.339000: Epoch time: 19.99 s +2024-11-22 18:32:28.266170: +2024-11-22 18:32:28.266409: Epoch 5718 +2024-11-22 18:32:28.266532: Current learning rate: 0.00323 +2024-11-22 18:32:46.938358: train_loss -0.7993 +2024-11-22 18:32:46.949888: val_loss -0.7816 +2024-11-22 18:32:46.950091: Pseudo dice [0.8505] +2024-11-22 18:32:46.950207: Epoch time: 18.67 s +2024-11-22 18:32:47.824306: +2024-11-22 18:32:47.824748: Epoch 5719 +2024-11-22 18:32:47.824871: Current learning rate: 0.00323 +2024-11-22 18:33:08.156387: train_loss -0.7965 +2024-11-22 18:33:08.193685: val_loss -0.7732 +2024-11-22 18:33:08.193862: Pseudo dice [0.8579] +2024-11-22 18:33:08.193955: Epoch time: 20.33 s +2024-11-22 18:33:09.237978: +2024-11-22 18:33:09.238194: Epoch 5720 +2024-11-22 18:33:09.238597: Current learning rate: 0.00323 +2024-11-22 18:33:29.007791: train_loss -0.7919 +2024-11-22 18:33:29.037502: val_loss -0.7853 +2024-11-22 18:33:29.037690: Pseudo dice [0.8549] +2024-11-22 18:33:29.037793: Epoch time: 19.77 s +2024-11-22 18:33:29.943529: +2024-11-22 18:33:29.943722: Epoch 5721 +2024-11-22 18:33:29.943831: Current learning rate: 0.00323 +2024-11-22 18:33:48.327090: train_loss -0.8002 +2024-11-22 18:33:48.333425: val_loss -0.7827 +2024-11-22 18:33:48.333546: Pseudo dice [0.8517] +2024-11-22 18:33:48.333648: Epoch time: 18.38 s +2024-11-22 18:33:49.624677: +2024-11-22 18:33:49.625501: Epoch 5722 +2024-11-22 18:33:49.625620: Current learning rate: 0.00323 +2024-11-22 18:34:09.058432: train_loss -0.7997 +2024-11-22 18:34:09.063718: val_loss -0.7837 +2024-11-22 18:34:09.063877: Pseudo dice [0.8556] +2024-11-22 18:34:09.064032: Epoch time: 19.43 s +2024-11-22 18:34:09.974298: +2024-11-22 18:34:09.974794: Epoch 5723 +2024-11-22 18:34:09.974919: Current learning rate: 0.00323 +2024-11-22 18:34:29.184280: train_loss -0.7979 +2024-11-22 18:34:29.203347: val_loss -0.7779 +2024-11-22 18:34:29.203505: Pseudo dice [0.8601] +2024-11-22 18:34:29.203590: Epoch time: 19.21 s +2024-11-22 18:34:30.075842: +2024-11-22 18:34:30.076053: Epoch 5724 +2024-11-22 18:34:30.076172: Current learning rate: 0.00323 +2024-11-22 18:34:49.235002: train_loss -0.8031 +2024-11-22 18:34:49.272497: val_loss -0.7777 +2024-11-22 18:34:49.272675: Pseudo dice [0.8499] +2024-11-22 18:34:49.272796: Epoch time: 19.16 s +2024-11-22 18:34:50.254469: +2024-11-22 18:34:50.254663: Epoch 5725 +2024-11-22 18:34:50.254792: Current learning rate: 0.00322 +2024-11-22 18:35:09.366368: train_loss -0.8054 +2024-11-22 18:35:09.383237: val_loss -0.7747 +2024-11-22 18:35:09.383393: Pseudo dice [0.8662] +2024-11-22 18:35:09.383484: Epoch time: 19.11 s +2024-11-22 18:35:10.259799: +2024-11-22 18:35:10.260229: Epoch 5726 +2024-11-22 18:35:10.260372: Current learning rate: 0.00322 +2024-11-22 18:35:29.770840: train_loss -0.8135 +2024-11-22 18:35:29.787571: val_loss -0.7638 +2024-11-22 18:35:29.787749: Pseudo dice [0.8692] +2024-11-22 18:35:29.787860: Epoch time: 19.51 s +2024-11-22 18:35:30.774859: +2024-11-22 18:35:30.775289: Epoch 5727 +2024-11-22 18:35:30.775403: Current learning rate: 0.00322 +2024-11-22 18:35:50.381152: train_loss -0.8044 +2024-11-22 18:35:50.421291: val_loss -0.7868 +2024-11-22 18:35:50.421455: Pseudo dice [0.8517] +2024-11-22 18:35:50.421562: Epoch time: 19.61 s +2024-11-22 18:35:51.447967: +2024-11-22 18:35:51.448176: Epoch 5728 +2024-11-22 18:35:51.448306: Current learning rate: 0.00322 +2024-11-22 18:36:11.899549: train_loss -0.7876 +2024-11-22 18:36:11.908001: val_loss -0.7482 +2024-11-22 18:36:11.908148: Pseudo dice [0.8597] +2024-11-22 18:36:11.908244: Epoch time: 20.45 s +2024-11-22 18:36:12.913716: +2024-11-22 18:36:12.914264: Epoch 5729 +2024-11-22 18:36:12.914392: Current learning rate: 0.00322 +2024-11-22 18:36:32.737723: train_loss -0.8032 +2024-11-22 18:36:32.767323: val_loss -0.7677 +2024-11-22 18:36:32.767498: Pseudo dice [0.8401] +2024-11-22 18:36:32.767602: Epoch time: 19.82 s +2024-11-22 18:36:33.668584: +2024-11-22 18:36:33.668813: Epoch 5730 +2024-11-22 18:36:33.668931: Current learning rate: 0.00322 +2024-11-22 18:36:53.059788: train_loss -0.8017 +2024-11-22 18:36:53.086390: val_loss -0.779 +2024-11-22 18:36:53.086562: Pseudo dice [0.839] +2024-11-22 18:36:53.086663: Epoch time: 19.39 s +2024-11-22 18:36:54.081504: +2024-11-22 18:36:54.081719: Epoch 5731 +2024-11-22 18:36:54.081848: Current learning rate: 0.00322 +2024-11-22 18:37:13.199794: train_loss -0.7965 +2024-11-22 18:37:13.220454: val_loss -0.7797 +2024-11-22 18:37:13.220600: Pseudo dice [0.8463] +2024-11-22 18:37:13.220826: Epoch time: 19.12 s +2024-11-22 18:37:14.211807: +2024-11-22 18:37:14.211998: Epoch 5732 +2024-11-22 18:37:14.212119: Current learning rate: 0.00322 +2024-11-22 18:37:32.269698: train_loss -0.8015 +2024-11-22 18:37:32.275176: val_loss -0.7842 +2024-11-22 18:37:32.275334: Pseudo dice [0.8589] +2024-11-22 18:37:32.275603: Epoch time: 18.06 s +2024-11-22 18:37:33.161933: +2024-11-22 18:37:33.162349: Epoch 5733 +2024-11-22 18:37:33.162474: Current learning rate: 0.00321 +2024-11-22 18:37:52.572286: train_loss -0.7954 +2024-11-22 18:37:52.602384: val_loss -0.7886 +2024-11-22 18:37:52.602551: Pseudo dice [0.8517] +2024-11-22 18:37:52.602661: Epoch time: 19.41 s +2024-11-22 18:37:53.880943: +2024-11-22 18:37:53.881163: Epoch 5734 +2024-11-22 18:37:53.881282: Current learning rate: 0.00321 +2024-11-22 18:38:14.088854: train_loss -0.7915 +2024-11-22 18:38:14.112694: val_loss -0.7776 +2024-11-22 18:38:14.112862: Pseudo dice [0.8613] +2024-11-22 18:38:14.112967: Epoch time: 20.21 s +2024-11-22 18:38:15.197391: +2024-11-22 18:38:15.197627: Epoch 5735 +2024-11-22 18:38:15.197750: Current learning rate: 0.00321 +2024-11-22 18:38:35.642817: train_loss -0.7922 +2024-11-22 18:38:35.661674: val_loss -0.7468 +2024-11-22 18:38:35.661835: Pseudo dice [0.837] +2024-11-22 18:38:35.661943: Epoch time: 20.45 s +2024-11-22 18:38:36.579852: +2024-11-22 18:38:36.580085: Epoch 5736 +2024-11-22 18:38:36.580204: Current learning rate: 0.00321 +2024-11-22 18:38:54.348122: train_loss -0.8007 +2024-11-22 18:38:54.367728: val_loss -0.7729 +2024-11-22 18:38:54.367915: Pseudo dice [0.8463] +2024-11-22 18:38:54.368035: Epoch time: 17.77 s +2024-11-22 18:38:55.270182: +2024-11-22 18:38:55.270396: Epoch 5737 +2024-11-22 18:38:55.270515: Current learning rate: 0.00321 +2024-11-22 18:39:14.135201: train_loss -0.8059 +2024-11-22 18:39:14.153533: val_loss -0.7699 +2024-11-22 18:39:14.153649: Pseudo dice [0.8602] +2024-11-22 18:39:14.153734: Epoch time: 18.87 s +2024-11-22 18:39:15.020624: +2024-11-22 18:39:15.020832: Epoch 5738 +2024-11-22 18:39:15.020951: Current learning rate: 0.00321 +2024-11-22 18:39:34.955346: train_loss -0.7741 +2024-11-22 18:39:34.972504: val_loss -0.777 +2024-11-22 18:39:34.972666: Pseudo dice [0.8552] +2024-11-22 18:39:34.972768: Epoch time: 19.94 s +2024-11-22 18:39:35.911297: +2024-11-22 18:39:35.911497: Epoch 5739 +2024-11-22 18:39:35.911609: Current learning rate: 0.00321 +2024-11-22 18:39:55.783302: train_loss -0.7878 +2024-11-22 18:39:55.799732: val_loss -0.7633 +2024-11-22 18:39:55.799902: Pseudo dice [0.8624] +2024-11-22 18:39:55.800009: Epoch time: 19.87 s +2024-11-22 18:39:56.676158: +2024-11-22 18:39:56.676368: Epoch 5740 +2024-11-22 18:39:56.676498: Current learning rate: 0.00321 +2024-11-22 18:40:15.926823: train_loss -0.7948 +2024-11-22 18:40:15.952227: val_loss -0.7532 +2024-11-22 18:40:15.952391: Pseudo dice [0.8515] +2024-11-22 18:40:15.952492: Epoch time: 19.25 s +2024-11-22 18:40:16.867266: +2024-11-22 18:40:16.867709: Epoch 5741 +2024-11-22 18:40:16.867830: Current learning rate: 0.0032 +2024-11-22 18:40:36.464341: train_loss -0.7749 +2024-11-22 18:40:36.480178: val_loss -0.7645 +2024-11-22 18:40:36.480340: Pseudo dice [0.8487] +2024-11-22 18:40:36.480432: Epoch time: 19.6 s +2024-11-22 18:40:37.380270: +2024-11-22 18:40:37.380481: Epoch 5742 +2024-11-22 18:40:37.380614: Current learning rate: 0.0032 +2024-11-22 18:40:56.862305: train_loss -0.7829 +2024-11-22 18:40:56.890229: val_loss -0.7816 +2024-11-22 18:40:56.890397: Pseudo dice [0.8586] +2024-11-22 18:40:56.890490: Epoch time: 19.48 s +2024-11-22 18:40:57.937011: +2024-11-22 18:40:57.937244: Epoch 5743 +2024-11-22 18:40:57.937361: Current learning rate: 0.0032 +2024-11-22 18:41:17.502783: train_loss -0.7936 +2024-11-22 18:41:17.510748: val_loss -0.7831 +2024-11-22 18:41:17.510900: Pseudo dice [0.8428] +2024-11-22 18:41:17.511066: Epoch time: 19.57 s +2024-11-22 18:41:18.472663: +2024-11-22 18:41:18.472853: Epoch 5744 +2024-11-22 18:41:18.472978: Current learning rate: 0.0032 +2024-11-22 18:41:37.378132: train_loss -0.802 +2024-11-22 18:41:37.403564: val_loss -0.7288 +2024-11-22 18:41:37.403760: Pseudo dice [0.8381] +2024-11-22 18:41:37.403882: Epoch time: 18.91 s +2024-11-22 18:41:38.281372: +2024-11-22 18:41:38.281846: Epoch 5745 +2024-11-22 18:41:38.281969: Current learning rate: 0.0032 +2024-11-22 18:41:58.135880: train_loss -0.7936 +2024-11-22 18:41:58.207823: val_loss -0.7811 +2024-11-22 18:41:58.214222: Pseudo dice [0.8596] +2024-11-22 18:41:58.214425: Epoch time: 19.86 s +2024-11-22 18:41:59.176575: +2024-11-22 18:41:59.177185: Epoch 5746 +2024-11-22 18:41:59.177333: Current learning rate: 0.0032 +2024-11-22 18:42:19.115369: train_loss -0.8021 +2024-11-22 18:42:19.133134: val_loss -0.7785 +2024-11-22 18:42:19.133294: Pseudo dice [0.8518] +2024-11-22 18:42:19.133388: Epoch time: 19.94 s +2024-11-22 18:42:20.167686: +2024-11-22 18:42:20.168140: Epoch 5747 +2024-11-22 18:42:20.168256: Current learning rate: 0.0032 +2024-11-22 18:42:38.370012: train_loss -0.7999 +2024-11-22 18:42:38.385835: val_loss -0.7909 +2024-11-22 18:42:38.385985: Pseudo dice [0.873] +2024-11-22 18:42:38.386111: Epoch time: 18.2 s +2024-11-22 18:42:39.262464: +2024-11-22 18:42:39.262697: Epoch 5748 +2024-11-22 18:42:39.262819: Current learning rate: 0.0032 +2024-11-22 18:42:57.704801: train_loss -0.8031 +2024-11-22 18:42:57.722254: val_loss -0.7624 +2024-11-22 18:42:57.722419: Pseudo dice [0.8455] +2024-11-22 18:42:57.722522: Epoch time: 18.44 s +2024-11-22 18:42:58.926617: +2024-11-22 18:42:58.927074: Epoch 5749 +2024-11-22 18:42:58.927190: Current learning rate: 0.00319 +2024-11-22 18:43:17.401474: train_loss -0.8016 +2024-11-22 18:43:17.408637: val_loss -0.768 +2024-11-22 18:43:17.408767: Pseudo dice [0.8625] +2024-11-22 18:43:17.408871: Epoch time: 18.48 s +2024-11-22 18:43:18.671203: +2024-11-22 18:43:18.671697: Epoch 5750 +2024-11-22 18:43:18.671821: Current learning rate: 0.00319 +2024-11-22 18:43:36.996995: train_loss -0.7994 +2024-11-22 18:43:37.018771: val_loss -0.7653 +2024-11-22 18:43:37.018938: Pseudo dice [0.85] +2024-11-22 18:43:37.019047: Epoch time: 18.33 s +2024-11-22 18:43:37.948721: +2024-11-22 18:43:37.948923: Epoch 5751 +2024-11-22 18:43:37.949040: Current learning rate: 0.00319 +2024-11-22 18:43:58.263167: train_loss -0.7878 +2024-11-22 18:43:58.295929: val_loss -0.8052 +2024-11-22 18:43:58.296105: Pseudo dice [0.8638] +2024-11-22 18:43:58.296196: Epoch time: 20.32 s +2024-11-22 18:43:59.277217: +2024-11-22 18:43:59.277428: Epoch 5752 +2024-11-22 18:43:59.277550: Current learning rate: 0.00319 +2024-11-22 18:44:18.243361: train_loss -0.7994 +2024-11-22 18:44:18.273463: val_loss -0.7912 +2024-11-22 18:44:18.273644: Pseudo dice [0.8613] +2024-11-22 18:44:18.273759: Epoch time: 18.97 s +2024-11-22 18:44:19.208567: +2024-11-22 18:44:19.208772: Epoch 5753 +2024-11-22 18:44:19.208899: Current learning rate: 0.00319 +2024-11-22 18:44:38.779766: train_loss -0.7955 +2024-11-22 18:44:38.782040: val_loss -0.7973 +2024-11-22 18:44:38.782160: Pseudo dice [0.859] +2024-11-22 18:44:38.782346: Epoch time: 19.57 s +2024-11-22 18:44:39.653427: +2024-11-22 18:44:39.653635: Epoch 5754 +2024-11-22 18:44:39.653762: Current learning rate: 0.00319 +2024-11-22 18:44:58.945710: train_loss -0.7934 +2024-11-22 18:44:58.978243: val_loss -0.7803 +2024-11-22 18:44:58.978411: Pseudo dice [0.8641] +2024-11-22 18:44:58.978507: Epoch time: 19.29 s +2024-11-22 18:44:59.877575: +2024-11-22 18:44:59.877780: Epoch 5755 +2024-11-22 18:44:59.877905: Current learning rate: 0.00319 +2024-11-22 18:45:18.224215: train_loss -0.8029 +2024-11-22 18:45:18.231607: val_loss -0.7772 +2024-11-22 18:45:18.231746: Pseudo dice [0.8616] +2024-11-22 18:45:18.231836: Epoch time: 18.35 s +2024-11-22 18:45:19.362211: +2024-11-22 18:45:19.362401: Epoch 5756 +2024-11-22 18:45:19.362512: Current learning rate: 0.00319 +2024-11-22 18:45:38.453667: train_loss -0.797 +2024-11-22 18:45:38.475049: val_loss -0.7831 +2024-11-22 18:45:38.475257: Pseudo dice [0.8485] +2024-11-22 18:45:38.475374: Epoch time: 19.09 s +2024-11-22 18:45:39.428556: +2024-11-22 18:45:39.428781: Epoch 5757 +2024-11-22 18:45:39.428912: Current learning rate: 0.00318 +2024-11-22 18:45:57.832636: train_loss -0.7863 +2024-11-22 18:45:57.852733: val_loss -0.7764 +2024-11-22 18:45:57.852885: Pseudo dice [0.8567] +2024-11-22 18:45:57.852973: Epoch time: 18.4 s +2024-11-22 18:45:58.727981: +2024-11-22 18:45:58.728201: Epoch 5758 +2024-11-22 18:45:58.728320: Current learning rate: 0.00318 +2024-11-22 18:46:17.434621: train_loss -0.7872 +2024-11-22 18:46:17.445709: val_loss -0.769 +2024-11-22 18:46:17.446096: Pseudo dice [0.8622] +2024-11-22 18:46:17.446209: Epoch time: 18.71 s +2024-11-22 18:46:18.409964: +2024-11-22 18:46:18.410394: Epoch 5759 +2024-11-22 18:46:18.410523: Current learning rate: 0.00318 +2024-11-22 18:46:36.909542: train_loss -0.7879 +2024-11-22 18:46:36.943021: val_loss -0.7837 +2024-11-22 18:46:36.943205: Pseudo dice [0.845] +2024-11-22 18:46:36.943315: Epoch time: 18.5 s +2024-11-22 18:46:37.865788: +2024-11-22 18:46:37.866028: Epoch 5760 +2024-11-22 18:46:37.866190: Current learning rate: 0.00318 +2024-11-22 18:46:56.983167: train_loss -0.7868 +2024-11-22 18:46:57.003858: val_loss -0.7746 +2024-11-22 18:46:57.004020: Pseudo dice [0.8537] +2024-11-22 18:46:57.004128: Epoch time: 19.12 s +2024-11-22 18:46:57.928250: +2024-11-22 18:46:57.928479: Epoch 5761 +2024-11-22 18:46:57.928607: Current learning rate: 0.00318 +2024-11-22 18:47:17.410020: train_loss -0.7948 +2024-11-22 18:47:17.418214: val_loss -0.7738 +2024-11-22 18:47:17.418348: Pseudo dice [0.8493] +2024-11-22 18:47:17.418442: Epoch time: 19.48 s +2024-11-22 18:47:18.445750: +2024-11-22 18:47:18.445971: Epoch 5762 +2024-11-22 18:47:18.446103: Current learning rate: 0.00318 +2024-11-22 18:47:38.287967: train_loss -0.7968 +2024-11-22 18:47:38.298145: val_loss -0.7674 +2024-11-22 18:47:38.298266: Pseudo dice [0.846] +2024-11-22 18:47:38.298353: Epoch time: 19.84 s +2024-11-22 18:47:39.184238: +2024-11-22 18:47:39.184689: Epoch 5763 +2024-11-22 18:47:39.184810: Current learning rate: 0.00318 +2024-11-22 18:47:58.451020: train_loss -0.8029 +2024-11-22 18:47:58.527975: val_loss -0.7639 +2024-11-22 18:47:58.528151: Pseudo dice [0.8492] +2024-11-22 18:47:58.528265: Epoch time: 19.27 s +2024-11-22 18:47:59.487872: +2024-11-22 18:47:59.488099: Epoch 5764 +2024-11-22 18:47:59.488220: Current learning rate: 0.00317 +2024-11-22 18:48:20.035341: train_loss -0.7879 +2024-11-22 18:48:20.038332: val_loss -0.7446 +2024-11-22 18:48:20.038420: Pseudo dice [0.8332] +2024-11-22 18:48:20.038499: Epoch time: 20.55 s +2024-11-22 18:48:20.899707: +2024-11-22 18:48:20.899904: Epoch 5765 +2024-11-22 18:48:20.900021: Current learning rate: 0.00317 +2024-11-22 18:48:40.002897: train_loss -0.7905 +2024-11-22 18:48:40.024400: val_loss -0.7735 +2024-11-22 18:48:40.024564: Pseudo dice [0.8476] +2024-11-22 18:48:40.024657: Epoch time: 19.1 s +2024-11-22 18:48:40.898624: +2024-11-22 18:48:40.899214: Epoch 5766 +2024-11-22 18:48:40.899333: Current learning rate: 0.00317 +2024-11-22 18:48:59.601255: train_loss -0.786 +2024-11-22 18:48:59.643703: val_loss -0.7613 +2024-11-22 18:48:59.643856: Pseudo dice [0.8543] +2024-11-22 18:48:59.643958: Epoch time: 18.7 s +2024-11-22 18:49:00.512690: +2024-11-22 18:49:00.512878: Epoch 5767 +2024-11-22 18:49:00.512990: Current learning rate: 0.00317 +2024-11-22 18:49:18.998349: train_loss -0.7972 +2024-11-22 18:49:19.013185: val_loss -0.7781 +2024-11-22 18:49:19.013368: Pseudo dice [0.8523] +2024-11-22 18:49:19.013496: Epoch time: 18.49 s +2024-11-22 18:49:20.285613: +2024-11-22 18:49:20.285857: Epoch 5768 +2024-11-22 18:49:20.285988: Current learning rate: 0.00317 +2024-11-22 18:49:40.716993: train_loss -0.7854 +2024-11-22 18:49:40.719486: val_loss -0.7429 +2024-11-22 18:49:40.719608: Pseudo dice [0.851] +2024-11-22 18:49:40.719692: Epoch time: 20.43 s +2024-11-22 18:49:41.788365: +2024-11-22 18:49:41.788823: Epoch 5769 +2024-11-22 18:49:41.788936: Current learning rate: 0.00317 +2024-11-22 18:50:01.499669: train_loss -0.7757 +2024-11-22 18:50:01.525987: val_loss -0.7609 +2024-11-22 18:50:01.526155: Pseudo dice [0.8563] +2024-11-22 18:50:01.526258: Epoch time: 19.71 s +2024-11-22 18:50:02.487808: +2024-11-22 18:50:02.488022: Epoch 5770 +2024-11-22 18:50:02.488136: Current learning rate: 0.00317 +2024-11-22 18:50:21.523183: train_loss -0.793 +2024-11-22 18:50:21.545267: val_loss -0.7752 +2024-11-22 18:50:21.545439: Pseudo dice [0.8691] +2024-11-22 18:50:21.545535: Epoch time: 19.04 s +2024-11-22 18:50:22.506639: +2024-11-22 18:50:22.507064: Epoch 5771 +2024-11-22 18:50:22.507197: Current learning rate: 0.00317 +2024-11-22 18:50:41.267298: train_loss -0.7937 +2024-11-22 18:50:41.276375: val_loss -0.7569 +2024-11-22 18:50:41.276507: Pseudo dice [0.8582] +2024-11-22 18:50:41.276601: Epoch time: 18.76 s +2024-11-22 18:50:42.254006: +2024-11-22 18:50:42.254885: Epoch 5772 +2024-11-22 18:50:42.255008: Current learning rate: 0.00316 +2024-11-22 18:51:00.510086: train_loss -0.79 +2024-11-22 18:51:00.518451: val_loss -0.7842 +2024-11-22 18:51:00.518592: Pseudo dice [0.8486] +2024-11-22 18:51:00.518675: Epoch time: 18.26 s +2024-11-22 18:51:01.435634: +2024-11-22 18:51:01.435836: Epoch 5773 +2024-11-22 18:51:01.435958: Current learning rate: 0.00316 +2024-11-22 18:51:20.621131: train_loss -0.8005 +2024-11-22 18:51:20.634447: val_loss -0.7658 +2024-11-22 18:51:20.634600: Pseudo dice [0.8595] +2024-11-22 18:51:20.634701: Epoch time: 19.19 s +2024-11-22 18:51:21.673698: +2024-11-22 18:51:21.674282: Epoch 5774 +2024-11-22 18:51:21.674407: Current learning rate: 0.00316 +2024-11-22 18:51:39.960468: train_loss -0.7944 +2024-11-22 18:51:39.966022: val_loss -0.763 +2024-11-22 18:51:39.966186: Pseudo dice [0.8641] +2024-11-22 18:51:39.966286: Epoch time: 18.29 s +2024-11-22 18:51:40.909107: +2024-11-22 18:51:40.909579: Epoch 5775 +2024-11-22 18:51:40.909697: Current learning rate: 0.00316 +2024-11-22 18:52:00.274020: train_loss -0.8023 +2024-11-22 18:52:00.280337: val_loss -0.7796 +2024-11-22 18:52:00.280488: Pseudo dice [0.8575] +2024-11-22 18:52:00.280589: Epoch time: 19.37 s +2024-11-22 18:52:01.157011: +2024-11-22 18:52:01.157224: Epoch 5776 +2024-11-22 18:52:01.157350: Current learning rate: 0.00316 +2024-11-22 18:52:19.890647: train_loss -0.7965 +2024-11-22 18:52:19.911266: val_loss -0.7639 +2024-11-22 18:52:19.911418: Pseudo dice [0.8454] +2024-11-22 18:52:19.911502: Epoch time: 18.73 s +2024-11-22 18:52:20.980468: +2024-11-22 18:52:20.980906: Epoch 5777 +2024-11-22 18:52:20.981027: Current learning rate: 0.00316 +2024-11-22 18:52:40.808783: train_loss -0.8057 +2024-11-22 18:52:40.835032: val_loss -0.7671 +2024-11-22 18:52:40.835213: Pseudo dice [0.8565] +2024-11-22 18:52:40.835323: Epoch time: 19.83 s +2024-11-22 18:52:42.020950: +2024-11-22 18:52:42.021159: Epoch 5778 +2024-11-22 18:52:42.021281: Current learning rate: 0.00316 +2024-11-22 18:53:01.176543: train_loss -0.7942 +2024-11-22 18:53:01.191131: val_loss -0.7955 +2024-11-22 18:53:01.191286: Pseudo dice [0.8692] +2024-11-22 18:53:01.191374: Epoch time: 19.16 s +2024-11-22 18:53:02.077249: +2024-11-22 18:53:02.077460: Epoch 5779 +2024-11-22 18:53:02.077595: Current learning rate: 0.00316 +2024-11-22 18:53:20.568703: train_loss -0.8024 +2024-11-22 18:53:20.578305: val_loss -0.7475 +2024-11-22 18:53:20.578455: Pseudo dice [0.8465] +2024-11-22 18:53:20.578547: Epoch time: 18.49 s +2024-11-22 18:53:21.535865: +2024-11-22 18:53:21.536144: Epoch 5780 +2024-11-22 18:53:21.536271: Current learning rate: 0.00315 +2024-11-22 18:53:41.298294: train_loss -0.7884 +2024-11-22 18:53:41.307806: val_loss -0.7786 +2024-11-22 18:53:41.307950: Pseudo dice [0.8679] +2024-11-22 18:53:41.308404: Epoch time: 19.76 s +2024-11-22 18:53:42.334617: +2024-11-22 18:53:42.335142: Epoch 5781 +2024-11-22 18:53:42.335258: Current learning rate: 0.00315 +2024-11-22 18:54:01.049886: train_loss -0.7985 +2024-11-22 18:54:01.061664: val_loss -0.7821 +2024-11-22 18:54:01.061804: Pseudo dice [0.8586] +2024-11-22 18:54:01.061897: Epoch time: 18.72 s +2024-11-22 18:54:02.048555: +2024-11-22 18:54:02.048981: Epoch 5782 +2024-11-22 18:54:02.049104: Current learning rate: 0.00315 +2024-11-22 18:54:22.811286: train_loss -0.7983 +2024-11-22 18:54:22.815358: val_loss -0.7699 +2024-11-22 18:54:22.815501: Pseudo dice [0.8486] +2024-11-22 18:54:22.815615: Epoch time: 20.76 s +2024-11-22 18:54:23.885040: +2024-11-22 18:54:23.885542: Epoch 5783 +2024-11-22 18:54:23.885677: Current learning rate: 0.00315 +2024-11-22 18:54:42.903908: train_loss -0.7915 +2024-11-22 18:54:42.915235: val_loss -0.7725 +2024-11-22 18:54:42.915571: Pseudo dice [0.8572] +2024-11-22 18:54:42.915678: Epoch time: 19.02 s +2024-11-22 18:54:43.798011: +2024-11-22 18:54:43.798465: Epoch 5784 +2024-11-22 18:54:43.798608: Current learning rate: 0.00315 +2024-11-22 18:55:03.861326: train_loss -0.7972 +2024-11-22 18:55:03.866875: val_loss -0.7648 +2024-11-22 18:55:03.867328: Pseudo dice [0.8569] +2024-11-22 18:55:03.867501: Epoch time: 20.06 s +2024-11-22 18:55:04.746111: +2024-11-22 18:55:04.746599: Epoch 5785 +2024-11-22 18:55:04.746727: Current learning rate: 0.00315 +2024-11-22 18:55:24.799717: train_loss -0.7999 +2024-11-22 18:55:24.808320: val_loss -0.7717 +2024-11-22 18:55:24.808495: Pseudo dice [0.8631] +2024-11-22 18:55:24.808589: Epoch time: 20.05 s +2024-11-22 18:55:25.684628: +2024-11-22 18:55:25.685553: Epoch 5786 +2024-11-22 18:55:25.685679: Current learning rate: 0.00315 +2024-11-22 18:55:43.689085: train_loss -0.8084 +2024-11-22 18:55:43.697442: val_loss -0.7648 +2024-11-22 18:55:43.697583: Pseudo dice [0.8571] +2024-11-22 18:55:43.697681: Epoch time: 18.01 s +2024-11-22 18:55:44.592573: +2024-11-22 18:55:44.593057: Epoch 5787 +2024-11-22 18:55:44.593193: Current learning rate: 0.00315 +2024-11-22 18:56:03.124076: train_loss -0.8006 +2024-11-22 18:56:03.142156: val_loss -0.7814 +2024-11-22 18:56:03.142323: Pseudo dice [0.861] +2024-11-22 18:56:03.142429: Epoch time: 18.53 s +2024-11-22 18:56:04.115118: +2024-11-22 18:56:04.115581: Epoch 5788 +2024-11-22 18:56:04.115728: Current learning rate: 0.00314 +2024-11-22 18:56:23.727026: train_loss -0.8024 +2024-11-22 18:56:23.734662: val_loss -0.7757 +2024-11-22 18:56:23.734809: Pseudo dice [0.8566] +2024-11-22 18:56:23.734905: Epoch time: 19.61 s +2024-11-22 18:56:24.663466: +2024-11-22 18:56:24.663665: Epoch 5789 +2024-11-22 18:56:24.663785: Current learning rate: 0.00314 +2024-11-22 18:56:44.581066: train_loss -0.8027 +2024-11-22 18:56:44.589415: val_loss -0.7872 +2024-11-22 18:56:44.596231: Pseudo dice [0.8597] +2024-11-22 18:56:44.596351: Epoch time: 19.92 s +2024-11-22 18:56:45.589790: +2024-11-22 18:56:45.591482: Epoch 5790 +2024-11-22 18:56:45.591606: Current learning rate: 0.00314 +2024-11-22 18:57:05.120824: train_loss -0.7923 +2024-11-22 18:57:05.154526: val_loss -0.772 +2024-11-22 18:57:05.154704: Pseudo dice [0.8573] +2024-11-22 18:57:05.154815: Epoch time: 19.53 s +2024-11-22 18:57:06.515705: +2024-11-22 18:57:06.516989: Epoch 5791 +2024-11-22 18:57:06.517146: Current learning rate: 0.00314 +2024-11-22 18:57:25.251636: train_loss -0.8049 +2024-11-22 18:57:25.266121: val_loss -0.7594 +2024-11-22 18:57:25.266271: Pseudo dice [0.8607] +2024-11-22 18:57:25.266363: Epoch time: 18.74 s +2024-11-22 18:57:26.221624: +2024-11-22 18:57:26.223003: Epoch 5792 +2024-11-22 18:57:26.223129: Current learning rate: 0.00314 +2024-11-22 18:57:46.729637: train_loss -0.7961 +2024-11-22 18:57:46.735936: val_loss -0.7573 +2024-11-22 18:57:46.736082: Pseudo dice [0.8568] +2024-11-22 18:57:46.736191: Epoch time: 20.51 s +2024-11-22 18:57:47.669166: +2024-11-22 18:57:47.670026: Epoch 5793 +2024-11-22 18:57:47.670169: Current learning rate: 0.00314 +2024-11-22 18:58:06.681818: train_loss -0.8068 +2024-11-22 18:58:06.688141: val_loss -0.785 +2024-11-22 18:58:06.688289: Pseudo dice [0.8579] +2024-11-22 18:58:06.688402: Epoch time: 19.01 s +2024-11-22 18:58:07.600903: +2024-11-22 18:58:07.602533: Epoch 5794 +2024-11-22 18:58:07.602657: Current learning rate: 0.00314 +2024-11-22 18:58:27.914775: train_loss -0.8046 +2024-11-22 18:58:27.923014: val_loss -0.7673 +2024-11-22 18:58:27.923268: Pseudo dice [0.8564] +2024-11-22 18:58:27.923381: Epoch time: 20.31 s +2024-11-22 18:58:29.004666: +2024-11-22 18:58:29.006092: Epoch 5795 +2024-11-22 18:58:29.006220: Current learning rate: 0.00314 +2024-11-22 18:58:48.300973: train_loss -0.7971 +2024-11-22 18:58:48.303592: val_loss -0.7771 +2024-11-22 18:58:48.303717: Pseudo dice [0.8618] +2024-11-22 18:58:48.303797: Epoch time: 19.3 s +2024-11-22 18:58:49.234738: +2024-11-22 18:58:49.235745: Epoch 5796 +2024-11-22 18:58:49.235888: Current learning rate: 0.00313 +2024-11-22 18:59:08.212002: train_loss -0.8039 +2024-11-22 18:59:08.221069: val_loss -0.7946 +2024-11-22 18:59:08.221236: Pseudo dice [0.8403] +2024-11-22 18:59:08.221339: Epoch time: 18.98 s +2024-11-22 18:59:09.306707: +2024-11-22 18:59:09.308496: Epoch 5797 +2024-11-22 18:59:09.308634: Current learning rate: 0.00313 +2024-11-22 18:59:28.435617: train_loss -0.7961 +2024-11-22 18:59:28.437912: val_loss -0.7869 +2024-11-22 18:59:28.438044: Pseudo dice [0.868] +2024-11-22 18:59:28.438153: Epoch time: 19.13 s +2024-11-22 18:59:29.395196: +2024-11-22 18:59:29.396356: Epoch 5798 +2024-11-22 18:59:29.396498: Current learning rate: 0.00313 +2024-11-22 18:59:48.668599: train_loss -0.7979 +2024-11-22 18:59:48.672638: val_loss -0.7688 +2024-11-22 18:59:48.672869: Pseudo dice [0.8671] +2024-11-22 18:59:48.672984: Epoch time: 19.27 s +2024-11-22 18:59:49.666045: +2024-11-22 18:59:49.667475: Epoch 5799 +2024-11-22 18:59:49.667611: Current learning rate: 0.00313 +2024-11-22 19:00:09.535887: train_loss -0.8019 +2024-11-22 19:00:09.542382: val_loss -0.7792 +2024-11-22 19:00:09.542516: Pseudo dice [0.8649] +2024-11-22 19:00:09.542675: Epoch time: 19.87 s +2024-11-22 19:00:10.824484: +2024-11-22 19:00:10.826150: Epoch 5800 +2024-11-22 19:00:10.826283: Current learning rate: 0.00313 +2024-11-22 19:00:30.345632: train_loss -0.7931 +2024-11-22 19:00:30.372687: val_loss -0.7848 +2024-11-22 19:00:30.372875: Pseudo dice [0.8557] +2024-11-22 19:00:30.372993: Epoch time: 19.52 s +2024-11-22 19:00:31.330409: +2024-11-22 19:00:31.331778: Epoch 5801 +2024-11-22 19:00:31.331928: Current learning rate: 0.00313 +2024-11-22 19:00:51.950273: train_loss -0.7949 +2024-11-22 19:00:51.959181: val_loss -0.7828 +2024-11-22 19:00:51.959317: Pseudo dice [0.8626] +2024-11-22 19:00:51.959410: Epoch time: 20.62 s +2024-11-22 19:00:52.879375: +2024-11-22 19:00:52.880585: Epoch 5802 +2024-11-22 19:00:52.880726: Current learning rate: 0.00313 +2024-11-22 19:01:13.224383: train_loss -0.7989 +2024-11-22 19:01:13.229665: val_loss -0.7749 +2024-11-22 19:01:13.229864: Pseudo dice [0.8521] +2024-11-22 19:01:13.229972: Epoch time: 20.35 s +2024-11-22 19:01:14.137313: +2024-11-22 19:01:14.138459: Epoch 5803 +2024-11-22 19:01:14.138581: Current learning rate: 0.00313 +2024-11-22 19:01:33.300127: train_loss -0.8015 +2024-11-22 19:01:33.319426: val_loss -0.7813 +2024-11-22 19:01:33.319614: Pseudo dice [0.8618] +2024-11-22 19:01:33.319707: Epoch time: 19.16 s +2024-11-22 19:01:34.227651: +2024-11-22 19:01:34.229031: Epoch 5804 +2024-11-22 19:01:34.229162: Current learning rate: 0.00312 +2024-11-22 19:01:54.182814: train_loss -0.8008 +2024-11-22 19:01:54.190182: val_loss -0.7683 +2024-11-22 19:01:54.190382: Pseudo dice [0.8554] +2024-11-22 19:01:54.190478: Epoch time: 19.96 s +2024-11-22 19:01:55.233313: +2024-11-22 19:01:55.235164: Epoch 5805 +2024-11-22 19:01:55.235307: Current learning rate: 0.00312 +2024-11-22 19:02:14.711179: train_loss -0.8054 +2024-11-22 19:02:14.717650: val_loss -0.7427 +2024-11-22 19:02:14.717796: Pseudo dice [0.8579] +2024-11-22 19:02:14.717898: Epoch time: 19.48 s +2024-11-22 19:02:15.604622: +2024-11-22 19:02:15.605855: Epoch 5806 +2024-11-22 19:02:15.605991: Current learning rate: 0.00312 +2024-11-22 19:02:35.164298: train_loss -0.8046 +2024-11-22 19:02:35.168417: val_loss -0.774 +2024-11-22 19:02:35.168542: Pseudo dice [0.8512] +2024-11-22 19:02:35.168654: Epoch time: 19.56 s +2024-11-22 19:02:36.166233: +2024-11-22 19:02:36.167472: Epoch 5807 +2024-11-22 19:02:36.167603: Current learning rate: 0.00312 +2024-11-22 19:02:55.239779: train_loss -0.8038 +2024-11-22 19:02:55.295805: val_loss -0.785 +2024-11-22 19:02:55.295975: Pseudo dice [0.8641] +2024-11-22 19:02:55.296076: Epoch time: 19.07 s +2024-11-22 19:02:56.512540: +2024-11-22 19:02:56.512945: Epoch 5808 +2024-11-22 19:02:56.513077: Current learning rate: 0.00312 +2024-11-22 19:03:16.064286: train_loss -0.8021 +2024-11-22 19:03:16.067900: val_loss -0.7809 +2024-11-22 19:03:16.068040: Pseudo dice [0.8559] +2024-11-22 19:03:16.068156: Epoch time: 19.55 s +2024-11-22 19:03:17.225815: +2024-11-22 19:03:17.227383: Epoch 5809 +2024-11-22 19:03:17.227505: Current learning rate: 0.00312 +2024-11-22 19:03:36.581944: train_loss -0.7992 +2024-11-22 19:03:36.584580: val_loss -0.7555 +2024-11-22 19:03:36.584688: Pseudo dice [0.8581] +2024-11-22 19:03:36.584786: Epoch time: 19.36 s +2024-11-22 19:03:37.645391: +2024-11-22 19:03:37.646257: Epoch 5810 +2024-11-22 19:03:37.646399: Current learning rate: 0.00312 +2024-11-22 19:03:57.363936: train_loss -0.8029 +2024-11-22 19:03:57.372739: val_loss -0.7848 +2024-11-22 19:03:57.379686: Pseudo dice [0.8674] +2024-11-22 19:03:57.379864: Epoch time: 19.72 s +2024-11-22 19:03:58.326488: +2024-11-22 19:03:58.328025: Epoch 5811 +2024-11-22 19:03:58.328158: Current learning rate: 0.00311 +2024-11-22 19:04:17.653538: train_loss -0.8146 +2024-11-22 19:04:17.662552: val_loss -0.7668 +2024-11-22 19:04:17.662703: Pseudo dice [0.8608] +2024-11-22 19:04:17.662807: Epoch time: 19.33 s +2024-11-22 19:04:18.669256: +2024-11-22 19:04:18.672050: Epoch 5812 +2024-11-22 19:04:18.672191: Current learning rate: 0.00311 +2024-11-22 19:04:37.716154: train_loss -0.8027 +2024-11-22 19:04:37.719551: val_loss -0.7608 +2024-11-22 19:04:37.719687: Pseudo dice [0.8498] +2024-11-22 19:04:37.719861: Epoch time: 19.05 s +2024-11-22 19:04:38.787177: +2024-11-22 19:04:38.788586: Epoch 5813 +2024-11-22 19:04:38.788729: Current learning rate: 0.00311 +2024-11-22 19:04:57.917174: train_loss -0.7901 +2024-11-22 19:04:57.922925: val_loss -0.7779 +2024-11-22 19:04:57.923070: Pseudo dice [0.8354] +2024-11-22 19:04:57.923159: Epoch time: 19.13 s +2024-11-22 19:04:59.360677: +2024-11-22 19:04:59.362450: Epoch 5814 +2024-11-22 19:04:59.362599: Current learning rate: 0.00311 +2024-11-22 19:05:19.252763: train_loss -0.7981 +2024-11-22 19:05:19.260239: val_loss -0.7713 +2024-11-22 19:05:19.260361: Pseudo dice [0.8533] +2024-11-22 19:05:19.260465: Epoch time: 19.89 s +2024-11-22 19:05:20.548797: +2024-11-22 19:05:20.550536: Epoch 5815 +2024-11-22 19:05:20.550675: Current learning rate: 0.00311 +2024-11-22 19:05:39.197769: train_loss -0.7992 +2024-11-22 19:05:39.211890: val_loss -0.7878 +2024-11-22 19:05:39.212043: Pseudo dice [0.8547] +2024-11-22 19:05:39.212146: Epoch time: 18.65 s +2024-11-22 19:05:40.278741: +2024-11-22 19:05:40.279973: Epoch 5816 +2024-11-22 19:05:40.280128: Current learning rate: 0.00311 +2024-11-22 19:05:59.677716: train_loss -0.8073 +2024-11-22 19:05:59.701250: val_loss -0.7816 +2024-11-22 19:05:59.701428: Pseudo dice [0.8681] +2024-11-22 19:05:59.701538: Epoch time: 19.4 s +2024-11-22 19:06:00.725894: +2024-11-22 19:06:00.727123: Epoch 5817 +2024-11-22 19:06:00.727258: Current learning rate: 0.00311 +2024-11-22 19:06:19.957463: train_loss -0.8016 +2024-11-22 19:06:19.987179: val_loss -0.7689 +2024-11-22 19:06:19.987353: Pseudo dice [0.8565] +2024-11-22 19:06:19.987444: Epoch time: 19.23 s +2024-11-22 19:06:20.967641: +2024-11-22 19:06:20.969847: Epoch 5818 +2024-11-22 19:06:20.969979: Current learning rate: 0.00311 +2024-11-22 19:06:41.943762: train_loss -0.801 +2024-11-22 19:06:41.952065: val_loss -0.7695 +2024-11-22 19:06:41.952218: Pseudo dice [0.8374] +2024-11-22 19:06:41.952343: Epoch time: 20.98 s +2024-11-22 19:06:42.989569: +2024-11-22 19:06:42.990860: Epoch 5819 +2024-11-22 19:06:42.991016: Current learning rate: 0.0031 +2024-11-22 19:07:01.546578: train_loss -0.809 +2024-11-22 19:07:01.554313: val_loss -0.7856 +2024-11-22 19:07:01.554506: Pseudo dice [0.848] +2024-11-22 19:07:01.554619: Epoch time: 18.56 s +2024-11-22 19:07:02.450608: +2024-11-22 19:07:02.451782: Epoch 5820 +2024-11-22 19:07:02.451913: Current learning rate: 0.0031 +2024-11-22 19:07:21.308648: train_loss -0.804 +2024-11-22 19:07:21.316943: val_loss -0.7606 +2024-11-22 19:07:21.317102: Pseudo dice [0.858] +2024-11-22 19:07:21.317225: Epoch time: 18.86 s +2024-11-22 19:07:22.283641: +2024-11-22 19:07:22.284818: Epoch 5821 +2024-11-22 19:07:22.284947: Current learning rate: 0.0031 +2024-11-22 19:07:41.661749: train_loss -0.8019 +2024-11-22 19:07:41.675921: val_loss -0.7815 +2024-11-22 19:07:41.676117: Pseudo dice [0.8467] +2024-11-22 19:07:41.676594: Epoch time: 19.38 s +2024-11-22 19:07:42.702249: +2024-11-22 19:07:42.703788: Epoch 5822 +2024-11-22 19:07:42.703912: Current learning rate: 0.0031 +2024-11-22 19:08:02.741546: train_loss -0.8036 +2024-11-22 19:08:02.749362: val_loss -0.767 +2024-11-22 19:08:02.749513: Pseudo dice [0.863] +2024-11-22 19:08:02.749595: Epoch time: 20.04 s +2024-11-22 19:08:03.822665: +2024-11-22 19:08:03.823220: Epoch 5823 +2024-11-22 19:08:03.823349: Current learning rate: 0.0031 +2024-11-22 19:08:22.815333: train_loss -0.8077 +2024-11-22 19:08:22.824557: val_loss -0.7692 +2024-11-22 19:08:22.824693: Pseudo dice [0.8355] +2024-11-22 19:08:22.824797: Epoch time: 18.99 s +2024-11-22 19:08:23.892725: +2024-11-22 19:08:23.893486: Epoch 5824 +2024-11-22 19:08:23.893618: Current learning rate: 0.0031 +2024-11-22 19:08:44.005155: train_loss -0.7947 +2024-11-22 19:08:44.037505: val_loss -0.782 +2024-11-22 19:08:44.037710: Pseudo dice [0.8479] +2024-11-22 19:08:44.037931: Epoch time: 20.11 s +2024-11-22 19:08:45.115601: +2024-11-22 19:08:45.116410: Epoch 5825 +2024-11-22 19:08:45.116545: Current learning rate: 0.0031 +2024-11-22 19:09:05.669216: train_loss -0.8002 +2024-11-22 19:09:05.675971: val_loss -0.7712 +2024-11-22 19:09:05.676134: Pseudo dice [0.8483] +2024-11-22 19:09:05.676274: Epoch time: 20.55 s +2024-11-22 19:09:06.559248: +2024-11-22 19:09:06.560138: Epoch 5826 +2024-11-22 19:09:06.560292: Current learning rate: 0.0031 +2024-11-22 19:09:26.372586: train_loss -0.804 +2024-11-22 19:09:26.402836: val_loss -0.7753 +2024-11-22 19:09:26.402989: Pseudo dice [0.8621] +2024-11-22 19:09:26.403086: Epoch time: 19.81 s +2024-11-22 19:09:27.419389: +2024-11-22 19:09:27.420563: Epoch 5827 +2024-11-22 19:09:27.420700: Current learning rate: 0.00309 +2024-11-22 19:09:48.043084: train_loss -0.7988 +2024-11-22 19:09:48.045511: val_loss -0.7637 +2024-11-22 19:09:48.045662: Pseudo dice [0.8581] +2024-11-22 19:09:48.045759: Epoch time: 20.62 s +2024-11-22 19:09:49.040931: +2024-11-22 19:09:49.041891: Epoch 5828 +2024-11-22 19:09:49.042007: Current learning rate: 0.00309 +2024-11-22 19:10:08.480607: train_loss -0.8008 +2024-11-22 19:10:08.513272: val_loss -0.7872 +2024-11-22 19:10:08.513466: Pseudo dice [0.8493] +2024-11-22 19:10:08.513565: Epoch time: 19.44 s +2024-11-22 19:10:09.619181: +2024-11-22 19:10:09.619607: Epoch 5829 +2024-11-22 19:10:09.619757: Current learning rate: 0.00309 +2024-11-22 19:10:29.397488: train_loss -0.8011 +2024-11-22 19:10:29.400755: val_loss -0.7973 +2024-11-22 19:10:29.400904: Pseudo dice [0.8676] +2024-11-22 19:10:29.401018: Epoch time: 19.78 s +2024-11-22 19:10:30.449512: +2024-11-22 19:10:30.451057: Epoch 5830 +2024-11-22 19:10:30.451211: Current learning rate: 0.00309 +2024-11-22 19:10:49.713414: train_loss -0.8071 +2024-11-22 19:10:49.734783: val_loss -0.7963 +2024-11-22 19:10:49.734969: Pseudo dice [0.8623] +2024-11-22 19:10:49.735081: Epoch time: 19.26 s +2024-11-22 19:10:50.769832: +2024-11-22 19:10:50.770849: Epoch 5831 +2024-11-22 19:10:50.770974: Current learning rate: 0.00309 +2024-11-22 19:11:10.074343: train_loss -0.8087 +2024-11-22 19:11:10.104297: val_loss -0.7646 +2024-11-22 19:11:10.104436: Pseudo dice [0.8452] +2024-11-22 19:11:10.104537: Epoch time: 19.31 s +2024-11-22 19:11:11.058802: +2024-11-22 19:11:11.059424: Epoch 5832 +2024-11-22 19:11:11.059549: Current learning rate: 0.00309 +2024-11-22 19:11:29.948750: train_loss -0.8011 +2024-11-22 19:11:29.989943: val_loss -0.7643 +2024-11-22 19:11:29.990130: Pseudo dice [0.8462] +2024-11-22 19:11:29.990248: Epoch time: 18.89 s +2024-11-22 19:11:30.952782: +2024-11-22 19:11:30.953246: Epoch 5833 +2024-11-22 19:11:30.953389: Current learning rate: 0.00309 +2024-11-22 19:11:50.150030: train_loss -0.8074 +2024-11-22 19:11:50.157679: val_loss -0.788 +2024-11-22 19:11:50.157817: Pseudo dice [0.8543] +2024-11-22 19:11:50.157915: Epoch time: 19.2 s +2024-11-22 19:11:51.182633: +2024-11-22 19:11:51.182825: Epoch 5834 +2024-11-22 19:11:51.182942: Current learning rate: 0.00309 +2024-11-22 19:12:10.429076: train_loss -0.8115 +2024-11-22 19:12:10.437480: val_loss -0.7577 +2024-11-22 19:12:10.437617: Pseudo dice [0.8602] +2024-11-22 19:12:10.437714: Epoch time: 19.25 s +2024-11-22 19:12:11.337738: +2024-11-22 19:12:11.337917: Epoch 5835 +2024-11-22 19:12:11.338030: Current learning rate: 0.00308 +2024-11-22 19:12:29.848437: train_loss -0.8129 +2024-11-22 19:12:29.849753: val_loss -0.7817 +2024-11-22 19:12:29.849879: Pseudo dice [0.8622] +2024-11-22 19:12:29.849987: Epoch time: 18.51 s +2024-11-22 19:12:30.736850: +2024-11-22 19:12:30.737046: Epoch 5836 +2024-11-22 19:12:30.737171: Current learning rate: 0.00308 +2024-11-22 19:12:50.122848: train_loss -0.8128 +2024-11-22 19:12:50.130259: val_loss -0.7802 +2024-11-22 19:12:50.130412: Pseudo dice [0.8598] +2024-11-22 19:12:50.130507: Epoch time: 19.39 s +2024-11-22 19:12:51.461617: +2024-11-22 19:12:51.461815: Epoch 5837 +2024-11-22 19:12:51.461934: Current learning rate: 0.00308 +2024-11-22 19:13:10.049249: train_loss -0.8086 +2024-11-22 19:13:10.078000: val_loss -0.7834 +2024-11-22 19:13:10.078175: Pseudo dice [0.8546] +2024-11-22 19:13:10.078281: Epoch time: 18.59 s +2024-11-22 19:13:11.097996: +2024-11-22 19:13:11.098209: Epoch 5838 +2024-11-22 19:13:11.098337: Current learning rate: 0.00308 +2024-11-22 19:13:30.274537: train_loss -0.8031 +2024-11-22 19:13:30.288745: val_loss -0.7744 +2024-11-22 19:13:30.288914: Pseudo dice [0.8537] +2024-11-22 19:13:30.289012: Epoch time: 19.18 s +2024-11-22 19:13:31.174923: +2024-11-22 19:13:31.175135: Epoch 5839 +2024-11-22 19:13:31.175262: Current learning rate: 0.00308 +2024-11-22 19:13:48.980427: train_loss -0.8048 +2024-11-22 19:13:48.983463: val_loss -0.766 +2024-11-22 19:13:48.983606: Pseudo dice [0.8569] +2024-11-22 19:13:48.983706: Epoch time: 17.81 s +2024-11-22 19:13:49.993174: +2024-11-22 19:13:49.993396: Epoch 5840 +2024-11-22 19:13:49.993517: Current learning rate: 0.00308 +2024-11-22 19:14:08.990517: train_loss -0.8067 +2024-11-22 19:14:08.993205: val_loss -0.7814 +2024-11-22 19:14:08.993307: Pseudo dice [0.8556] +2024-11-22 19:14:08.993418: Epoch time: 19.0 s +2024-11-22 19:14:09.878430: +2024-11-22 19:14:09.878662: Epoch 5841 +2024-11-22 19:14:09.878791: Current learning rate: 0.00308 +2024-11-22 19:14:28.316021: train_loss -0.8099 +2024-11-22 19:14:28.316767: val_loss -0.7721 +2024-11-22 19:14:28.316864: Pseudo dice [0.8548] +2024-11-22 19:14:28.316973: Epoch time: 18.44 s +2024-11-22 19:14:29.200210: +2024-11-22 19:14:29.200420: Epoch 5842 +2024-11-22 19:14:29.200543: Current learning rate: 0.00308 +2024-11-22 19:14:47.912084: train_loss -0.8038 +2024-11-22 19:14:47.933181: val_loss -0.7847 +2024-11-22 19:14:47.933347: Pseudo dice [0.8609] +2024-11-22 19:14:47.933444: Epoch time: 18.71 s +2024-11-22 19:14:48.897435: +2024-11-22 19:14:48.897638: Epoch 5843 +2024-11-22 19:14:48.897769: Current learning rate: 0.00307 +2024-11-22 19:15:07.144145: train_loss -0.8126 +2024-11-22 19:15:07.147895: val_loss -0.7959 +2024-11-22 19:15:07.148043: Pseudo dice [0.8647] +2024-11-22 19:15:07.148135: Epoch time: 18.25 s +2024-11-22 19:15:08.004575: +2024-11-22 19:15:08.004785: Epoch 5844 +2024-11-22 19:15:08.004904: Current learning rate: 0.00307 +2024-11-22 19:15:26.498958: train_loss -0.8023 +2024-11-22 19:15:26.501809: val_loss -0.7726 +2024-11-22 19:15:26.501918: Pseudo dice [0.8643] +2024-11-22 19:15:26.502062: Epoch time: 18.5 s +2024-11-22 19:15:27.374546: +2024-11-22 19:15:27.374738: Epoch 5845 +2024-11-22 19:15:27.374845: Current learning rate: 0.00307 +2024-11-22 19:15:46.999978: train_loss -0.7973 +2024-11-22 19:15:47.002315: val_loss -0.7757 +2024-11-22 19:15:47.002428: Pseudo dice [0.8528] +2024-11-22 19:15:47.002517: Epoch time: 19.63 s +2024-11-22 19:15:48.022540: +2024-11-22 19:15:48.022757: Epoch 5846 +2024-11-22 19:15:48.022902: Current learning rate: 0.00307 +2024-11-22 19:16:07.303686: train_loss -0.7989 +2024-11-22 19:16:07.311069: val_loss -0.7779 +2024-11-22 19:16:07.311224: Pseudo dice [0.8647] +2024-11-22 19:16:07.311320: Epoch time: 19.28 s +2024-11-22 19:16:08.285378: +2024-11-22 19:16:08.285564: Epoch 5847 +2024-11-22 19:16:08.301893: Current learning rate: 0.00307 +2024-11-22 19:16:27.519580: train_loss -0.8017 +2024-11-22 19:16:27.523441: val_loss -0.7745 +2024-11-22 19:16:27.523576: Pseudo dice [0.8636] +2024-11-22 19:16:27.523767: Epoch time: 19.24 s +2024-11-22 19:16:28.581383: +2024-11-22 19:16:28.581603: Epoch 5848 +2024-11-22 19:16:28.581724: Current learning rate: 0.00307 +2024-11-22 19:16:49.154016: train_loss -0.8125 +2024-11-22 19:16:49.157470: val_loss -0.7839 +2024-11-22 19:16:49.157590: Pseudo dice [0.8631] +2024-11-22 19:16:49.157682: Epoch time: 20.57 s +2024-11-22 19:16:50.097545: +2024-11-22 19:16:50.097770: Epoch 5849 +2024-11-22 19:16:50.097906: Current learning rate: 0.00307 +2024-11-22 19:17:08.752841: train_loss -0.8109 +2024-11-22 19:17:08.761106: val_loss -0.7831 +2024-11-22 19:17:08.761216: Pseudo dice [0.8621] +2024-11-22 19:17:08.761303: Epoch time: 18.66 s +2024-11-22 19:17:10.113760: +2024-11-22 19:17:10.114212: Epoch 5850 +2024-11-22 19:17:10.114328: Current learning rate: 0.00306 +2024-11-22 19:17:29.973209: train_loss -0.7948 +2024-11-22 19:17:29.979586: val_loss -0.772 +2024-11-22 19:17:29.979706: Pseudo dice [0.8649] +2024-11-22 19:17:29.979802: Epoch time: 19.86 s +2024-11-22 19:17:30.865957: +2024-11-22 19:17:30.866455: Epoch 5851 +2024-11-22 19:17:30.866581: Current learning rate: 0.00306 +2024-11-22 19:17:49.550500: train_loss -0.7957 +2024-11-22 19:17:49.552953: val_loss -0.7823 +2024-11-22 19:17:49.553055: Pseudo dice [0.8521] +2024-11-22 19:17:49.553164: Epoch time: 18.69 s +2024-11-22 19:17:50.422141: +2024-11-22 19:17:50.422354: Epoch 5852 +2024-11-22 19:17:50.422488: Current learning rate: 0.00306 +2024-11-22 19:18:09.034767: train_loss -0.7997 +2024-11-22 19:18:09.041046: val_loss -0.771 +2024-11-22 19:18:09.041181: Pseudo dice [0.8485] +2024-11-22 19:18:09.041275: Epoch time: 18.61 s +2024-11-22 19:18:09.923088: +2024-11-22 19:18:09.923297: Epoch 5853 +2024-11-22 19:18:09.923418: Current learning rate: 0.00306 +2024-11-22 19:18:28.138043: train_loss -0.795 +2024-11-22 19:18:28.141956: val_loss -0.7999 +2024-11-22 19:18:28.142100: Pseudo dice [0.861] +2024-11-22 19:18:28.142182: Epoch time: 18.22 s +2024-11-22 19:18:29.001001: +2024-11-22 19:18:29.001207: Epoch 5854 +2024-11-22 19:18:29.001322: Current learning rate: 0.00306 +2024-11-22 19:18:47.882888: train_loss -0.8115 +2024-11-22 19:18:47.897692: val_loss -0.7854 +2024-11-22 19:18:47.897842: Pseudo dice [0.8642] +2024-11-22 19:18:47.897931: Epoch time: 18.88 s +2024-11-22 19:18:48.850855: +2024-11-22 19:18:48.851055: Epoch 5855 +2024-11-22 19:18:48.851185: Current learning rate: 0.00306 +2024-11-22 19:19:07.598076: train_loss -0.8078 +2024-11-22 19:19:07.603251: val_loss -0.78 +2024-11-22 19:19:07.603400: Pseudo dice [0.8536] +2024-11-22 19:19:07.603500: Epoch time: 18.75 s +2024-11-22 19:19:08.510728: +2024-11-22 19:19:08.511604: Epoch 5856 +2024-11-22 19:19:08.511735: Current learning rate: 0.00306 +2024-11-22 19:19:28.006425: train_loss -0.7941 +2024-11-22 19:19:28.014803: val_loss -0.781 +2024-11-22 19:19:28.014949: Pseudo dice [0.8528] +2024-11-22 19:19:28.015055: Epoch time: 19.5 s +2024-11-22 19:19:29.047107: +2024-11-22 19:19:29.047589: Epoch 5857 +2024-11-22 19:19:29.047716: Current learning rate: 0.00306 +2024-11-22 19:19:48.753153: train_loss -0.8027 +2024-11-22 19:19:48.763354: val_loss -0.7766 +2024-11-22 19:19:48.763486: Pseudo dice [0.8553] +2024-11-22 19:19:48.763573: Epoch time: 19.71 s +2024-11-22 19:19:49.917477: +2024-11-22 19:19:49.917943: Epoch 5858 +2024-11-22 19:19:49.918072: Current learning rate: 0.00305 +2024-11-22 19:20:09.262636: train_loss -0.8035 +2024-11-22 19:20:09.271394: val_loss -0.7824 +2024-11-22 19:20:09.271524: Pseudo dice [0.8494] +2024-11-22 19:20:09.271606: Epoch time: 19.35 s +2024-11-22 19:20:10.707457: +2024-11-22 19:20:10.707974: Epoch 5859 +2024-11-22 19:20:10.708116: Current learning rate: 0.00305 +2024-11-22 19:20:29.303926: train_loss -0.8072 +2024-11-22 19:20:29.309860: val_loss -0.7913 +2024-11-22 19:20:29.309989: Pseudo dice [0.8465] +2024-11-22 19:20:29.310108: Epoch time: 18.6 s +2024-11-22 19:20:30.310891: +2024-11-22 19:20:30.311124: Epoch 5860 +2024-11-22 19:20:30.311242: Current learning rate: 0.00305 +2024-11-22 19:20:50.311103: train_loss -0.8013 +2024-11-22 19:20:50.331407: val_loss -0.7942 +2024-11-22 19:20:50.331565: Pseudo dice [0.8664] +2024-11-22 19:20:50.331665: Epoch time: 20.0 s +2024-11-22 19:20:51.305684: +2024-11-22 19:20:51.306079: Epoch 5861 +2024-11-22 19:20:51.306209: Current learning rate: 0.00305 +2024-11-22 19:21:11.343823: train_loss -0.7934 +2024-11-22 19:21:11.352135: val_loss -0.7828 +2024-11-22 19:21:11.352269: Pseudo dice [0.858] +2024-11-22 19:21:11.352383: Epoch time: 20.04 s +2024-11-22 19:21:12.293244: +2024-11-22 19:21:12.294161: Epoch 5862 +2024-11-22 19:21:12.294293: Current learning rate: 0.00305 +2024-11-22 19:21:32.576403: train_loss -0.806 +2024-11-22 19:21:32.588663: val_loss -0.7688 +2024-11-22 19:21:32.588814: Pseudo dice [0.854] +2024-11-22 19:21:32.588925: Epoch time: 20.28 s +2024-11-22 19:21:33.484447: +2024-11-22 19:21:33.484847: Epoch 5863 +2024-11-22 19:21:33.484977: Current learning rate: 0.00305 +2024-11-22 19:21:52.757153: train_loss -0.7984 +2024-11-22 19:21:52.762764: val_loss -0.7733 +2024-11-22 19:21:52.762904: Pseudo dice [0.8459] +2024-11-22 19:21:52.762998: Epoch time: 19.27 s +2024-11-22 19:21:53.643400: +2024-11-22 19:21:53.644691: Epoch 5864 +2024-11-22 19:21:53.644830: Current learning rate: 0.00305 +2024-11-22 19:22:12.923520: train_loss -0.7996 +2024-11-22 19:22:12.928629: val_loss -0.777 +2024-11-22 19:22:12.929338: Pseudo dice [0.8544] +2024-11-22 19:22:12.929481: Epoch time: 19.28 s +2024-11-22 19:22:14.091082: +2024-11-22 19:22:14.092339: Epoch 5865 +2024-11-22 19:22:14.092470: Current learning rate: 0.00305 +2024-11-22 19:22:33.538795: train_loss -0.7999 +2024-11-22 19:22:33.542240: val_loss -0.7786 +2024-11-22 19:22:33.542360: Pseudo dice [0.8602] +2024-11-22 19:22:33.542448: Epoch time: 19.45 s +2024-11-22 19:22:34.414948: +2024-11-22 19:22:34.415839: Epoch 5866 +2024-11-22 19:22:34.415965: Current learning rate: 0.00304 +2024-11-22 19:22:55.427011: train_loss -0.7863 +2024-11-22 19:22:55.431373: val_loss -0.7528 +2024-11-22 19:22:55.431523: Pseudo dice [0.8603] +2024-11-22 19:22:55.431629: Epoch time: 21.01 s +2024-11-22 19:22:56.411277: +2024-11-22 19:22:56.412631: Epoch 5867 +2024-11-22 19:22:56.412766: Current learning rate: 0.00304 +2024-11-22 19:23:16.662109: train_loss -0.7964 +2024-11-22 19:23:16.668673: val_loss -0.7578 +2024-11-22 19:23:16.668827: Pseudo dice [0.847] +2024-11-22 19:23:16.668939: Epoch time: 20.25 s +2024-11-22 19:23:17.654515: +2024-11-22 19:23:17.655257: Epoch 5868 +2024-11-22 19:23:17.655379: Current learning rate: 0.00304 +2024-11-22 19:23:35.898358: train_loss -0.7903 +2024-11-22 19:23:35.903714: val_loss -0.7706 +2024-11-22 19:23:35.903824: Pseudo dice [0.8665] +2024-11-22 19:23:35.903924: Epoch time: 18.24 s +2024-11-22 19:23:36.958975: +2024-11-22 19:23:36.960725: Epoch 5869 +2024-11-22 19:23:36.960861: Current learning rate: 0.00304 +2024-11-22 19:23:56.498869: train_loss -0.7942 +2024-11-22 19:23:56.501548: val_loss -0.7833 +2024-11-22 19:23:56.501681: Pseudo dice [0.8593] +2024-11-22 19:23:56.501775: Epoch time: 19.54 s +2024-11-22 19:23:57.432265: +2024-11-22 19:23:57.433600: Epoch 5870 +2024-11-22 19:23:57.433749: Current learning rate: 0.00304 +2024-11-22 19:24:17.046497: train_loss -0.7973 +2024-11-22 19:24:17.054215: val_loss -0.7791 +2024-11-22 19:24:17.054378: Pseudo dice [0.8583] +2024-11-22 19:24:17.054472: Epoch time: 19.62 s +2024-11-22 19:24:18.306328: +2024-11-22 19:24:18.307985: Epoch 5871 +2024-11-22 19:24:18.308139: Current learning rate: 0.00304 +2024-11-22 19:24:39.142715: train_loss -0.7948 +2024-11-22 19:24:39.149816: val_loss -0.7766 +2024-11-22 19:24:39.149965: Pseudo dice [0.8365] +2024-11-22 19:24:39.150093: Epoch time: 20.84 s +2024-11-22 19:24:40.251453: +2024-11-22 19:24:40.252609: Epoch 5872 +2024-11-22 19:24:40.252740: Current learning rate: 0.00304 +2024-11-22 19:24:59.238606: train_loss -0.7902 +2024-11-22 19:24:59.244781: val_loss -0.7643 +2024-11-22 19:24:59.245112: Pseudo dice [0.8408] +2024-11-22 19:24:59.245214: Epoch time: 18.99 s +2024-11-22 19:25:00.369865: +2024-11-22 19:25:00.371054: Epoch 5873 +2024-11-22 19:25:00.371193: Current learning rate: 0.00304 +2024-11-22 19:25:19.321922: train_loss -0.7992 +2024-11-22 19:25:19.327692: val_loss -0.7729 +2024-11-22 19:25:19.327841: Pseudo dice [0.8638] +2024-11-22 19:25:19.327984: Epoch time: 18.95 s +2024-11-22 19:25:20.232274: +2024-11-22 19:25:20.233191: Epoch 5874 +2024-11-22 19:25:20.233331: Current learning rate: 0.00303 +2024-11-22 19:25:39.608449: train_loss -0.7962 +2024-11-22 19:25:39.615901: val_loss -0.7671 +2024-11-22 19:25:39.616040: Pseudo dice [0.8367] +2024-11-22 19:25:39.616148: Epoch time: 19.38 s +2024-11-22 19:25:40.623862: +2024-11-22 19:25:40.624638: Epoch 5875 +2024-11-22 19:25:40.624765: Current learning rate: 0.00303 +2024-11-22 19:26:00.307568: train_loss -0.7887 +2024-11-22 19:26:00.322455: val_loss -0.7661 +2024-11-22 19:26:00.322617: Pseudo dice [0.8592] +2024-11-22 19:26:00.322727: Epoch time: 19.68 s +2024-11-22 19:26:01.324673: +2024-11-22 19:26:01.325852: Epoch 5876 +2024-11-22 19:26:01.325973: Current learning rate: 0.00303 +2024-11-22 19:26:20.171576: train_loss -0.7922 +2024-11-22 19:26:20.177814: val_loss -0.7619 +2024-11-22 19:26:20.177960: Pseudo dice [0.8561] +2024-11-22 19:26:20.178082: Epoch time: 18.85 s +2024-11-22 19:26:21.188308: +2024-11-22 19:26:21.188775: Epoch 5877 +2024-11-22 19:26:21.188903: Current learning rate: 0.00303 +2024-11-22 19:26:39.865531: train_loss -0.7879 +2024-11-22 19:26:39.868027: val_loss -0.777 +2024-11-22 19:26:39.868160: Pseudo dice [0.8646] +2024-11-22 19:26:39.868261: Epoch time: 18.68 s +2024-11-22 19:26:40.736501: +2024-11-22 19:26:40.737263: Epoch 5878 +2024-11-22 19:26:40.737376: Current learning rate: 0.00303 +2024-11-22 19:27:00.439719: train_loss -0.7918 +2024-11-22 19:27:00.450762: val_loss -0.781 +2024-11-22 19:27:00.450885: Pseudo dice [0.8579] +2024-11-22 19:27:00.450970: Epoch time: 19.7 s +2024-11-22 19:27:01.457986: +2024-11-22 19:27:01.458804: Epoch 5879 +2024-11-22 19:27:01.458979: Current learning rate: 0.00303 +2024-11-22 19:27:20.887009: train_loss -0.7966 +2024-11-22 19:27:20.892450: val_loss -0.7471 +2024-11-22 19:27:20.892579: Pseudo dice [0.8543] +2024-11-22 19:27:20.892674: Epoch time: 19.43 s +2024-11-22 19:27:22.079783: +2024-11-22 19:27:22.083384: Epoch 5880 +2024-11-22 19:27:22.083512: Current learning rate: 0.00303 +2024-11-22 19:27:42.099783: train_loss -0.7989 +2024-11-22 19:27:42.108394: val_loss -0.7777 +2024-11-22 19:27:42.108556: Pseudo dice [0.8524] +2024-11-22 19:27:42.108665: Epoch time: 20.02 s +2024-11-22 19:27:43.159448: +2024-11-22 19:27:43.160781: Epoch 5881 +2024-11-22 19:27:43.160900: Current learning rate: 0.00303 +2024-11-22 19:28:02.325105: train_loss -0.7914 +2024-11-22 19:28:02.330590: val_loss -0.756 +2024-11-22 19:28:02.330749: Pseudo dice [0.849] +2024-11-22 19:28:02.330854: Epoch time: 19.17 s +2024-11-22 19:28:03.772625: +2024-11-22 19:28:03.773992: Epoch 5882 +2024-11-22 19:28:03.774143: Current learning rate: 0.00302 +2024-11-22 19:28:22.278572: train_loss -0.7979 +2024-11-22 19:28:22.287105: val_loss -0.7784 +2024-11-22 19:28:22.287329: Pseudo dice [0.8703] +2024-11-22 19:28:22.287431: Epoch time: 18.51 s +2024-11-22 19:28:23.241935: +2024-11-22 19:28:23.243220: Epoch 5883 +2024-11-22 19:28:23.243349: Current learning rate: 0.00302 +2024-11-22 19:28:42.250630: train_loss -0.8012 +2024-11-22 19:28:42.261445: val_loss -0.767 +2024-11-22 19:28:42.261604: Pseudo dice [0.8507] +2024-11-22 19:28:42.261701: Epoch time: 19.01 s +2024-11-22 19:28:43.302998: +2024-11-22 19:28:43.303497: Epoch 5884 +2024-11-22 19:28:43.303624: Current learning rate: 0.00302 +2024-11-22 19:29:02.677869: train_loss -0.7943 +2024-11-22 19:29:02.684345: val_loss -0.7485 +2024-11-22 19:29:02.684481: Pseudo dice [0.8533] +2024-11-22 19:29:02.684591: Epoch time: 19.38 s +2024-11-22 19:29:03.595767: +2024-11-22 19:29:03.596516: Epoch 5885 +2024-11-22 19:29:03.596640: Current learning rate: 0.00302 +2024-11-22 19:29:22.810519: train_loss -0.7973 +2024-11-22 19:29:22.818092: val_loss -0.7611 +2024-11-22 19:29:22.818221: Pseudo dice [0.8496] +2024-11-22 19:29:22.818318: Epoch time: 19.22 s +2024-11-22 19:29:23.821393: +2024-11-22 19:29:23.822324: Epoch 5886 +2024-11-22 19:29:23.822447: Current learning rate: 0.00302 +2024-11-22 19:29:44.399976: train_loss -0.8048 +2024-11-22 19:29:44.407311: val_loss -0.7929 +2024-11-22 19:29:44.407469: Pseudo dice [0.8461] +2024-11-22 19:29:44.407576: Epoch time: 20.58 s +2024-11-22 19:29:45.297804: +2024-11-22 19:29:45.298616: Epoch 5887 +2024-11-22 19:29:45.298741: Current learning rate: 0.00302 +2024-11-22 19:30:03.352177: train_loss -0.8095 +2024-11-22 19:30:03.356087: val_loss -0.7745 +2024-11-22 19:30:03.356209: Pseudo dice [0.8574] +2024-11-22 19:30:03.356311: Epoch time: 18.06 s +2024-11-22 19:30:04.228920: +2024-11-22 19:30:04.229317: Epoch 5888 +2024-11-22 19:30:04.229434: Current learning rate: 0.00302 +2024-11-22 19:30:23.581519: train_loss -0.8001 +2024-11-22 19:30:23.587341: val_loss -0.7907 +2024-11-22 19:30:23.587469: Pseudo dice [0.8512] +2024-11-22 19:30:23.587574: Epoch time: 19.35 s +2024-11-22 19:30:24.596301: +2024-11-22 19:30:24.597121: Epoch 5889 +2024-11-22 19:30:24.597241: Current learning rate: 0.00301 +2024-11-22 19:30:44.999303: train_loss -0.7816 +2024-11-22 19:30:45.003921: val_loss -0.7636 +2024-11-22 19:30:45.004079: Pseudo dice [0.8479] +2024-11-22 19:30:45.004181: Epoch time: 20.4 s +2024-11-22 19:30:45.965327: +2024-11-22 19:30:45.966143: Epoch 5890 +2024-11-22 19:30:45.966265: Current learning rate: 0.00301 +2024-11-22 19:31:06.084216: train_loss -0.8045 +2024-11-22 19:31:06.112210: val_loss -0.7916 +2024-11-22 19:31:06.112367: Pseudo dice [0.8618] +2024-11-22 19:31:06.112478: Epoch time: 20.12 s +2024-11-22 19:31:07.154044: +2024-11-22 19:31:07.155321: Epoch 5891 +2024-11-22 19:31:07.155441: Current learning rate: 0.00301 +2024-11-22 19:31:26.546515: train_loss -0.8029 +2024-11-22 19:31:26.566552: val_loss -0.7725 +2024-11-22 19:31:26.566721: Pseudo dice [0.8569] +2024-11-22 19:31:26.566834: Epoch time: 19.39 s +2024-11-22 19:31:27.757172: +2024-11-22 19:31:27.758911: Epoch 5892 +2024-11-22 19:31:27.759043: Current learning rate: 0.00301 +2024-11-22 19:31:47.601091: train_loss -0.8001 +2024-11-22 19:31:47.608651: val_loss -0.7594 +2024-11-22 19:31:47.608787: Pseudo dice [0.8634] +2024-11-22 19:31:47.608885: Epoch time: 19.84 s +2024-11-22 19:31:48.571300: +2024-11-22 19:31:48.572162: Epoch 5893 +2024-11-22 19:31:48.572298: Current learning rate: 0.00301 +2024-11-22 19:32:07.663198: train_loss -0.8084 +2024-11-22 19:32:07.675010: val_loss -0.792 +2024-11-22 19:32:07.675167: Pseudo dice [0.8716] +2024-11-22 19:32:07.675254: Epoch time: 19.09 s +2024-11-22 19:32:08.970349: +2024-11-22 19:32:08.971777: Epoch 5894 +2024-11-22 19:32:08.971910: Current learning rate: 0.00301 +2024-11-22 19:32:28.162865: train_loss -0.8098 +2024-11-22 19:32:28.165891: val_loss -0.7875 +2024-11-22 19:32:28.166061: Pseudo dice [0.864] +2024-11-22 19:32:28.166240: Epoch time: 19.19 s +2024-11-22 19:32:29.040906: +2024-11-22 19:32:29.041373: Epoch 5895 +2024-11-22 19:32:29.041511: Current learning rate: 0.00301 +2024-11-22 19:32:49.497820: train_loss -0.802 +2024-11-22 19:32:49.504956: val_loss -0.7607 +2024-11-22 19:32:49.505093: Pseudo dice [0.8745] +2024-11-22 19:32:49.505183: Epoch time: 20.46 s +2024-11-22 19:32:50.394004: +2024-11-22 19:32:50.395660: Epoch 5896 +2024-11-22 19:32:50.395793: Current learning rate: 0.00301 +2024-11-22 19:33:10.077093: train_loss -0.7994 +2024-11-22 19:33:10.088798: val_loss -0.7603 +2024-11-22 19:33:10.088965: Pseudo dice [0.8447] +2024-11-22 19:33:10.089063: Epoch time: 19.68 s +2024-11-22 19:33:11.184197: +2024-11-22 19:33:11.185703: Epoch 5897 +2024-11-22 19:33:11.185836: Current learning rate: 0.003 +2024-11-22 19:33:30.219799: train_loss -0.7949 +2024-11-22 19:33:30.221730: val_loss -0.7786 +2024-11-22 19:33:30.221850: Pseudo dice [0.8497] +2024-11-22 19:33:30.221936: Epoch time: 19.04 s +2024-11-22 19:33:31.115092: +2024-11-22 19:33:31.116167: Epoch 5898 +2024-11-22 19:33:31.116296: Current learning rate: 0.003 +2024-11-22 19:33:51.165175: train_loss -0.7973 +2024-11-22 19:33:51.168305: val_loss -0.7612 +2024-11-22 19:33:51.168421: Pseudo dice [0.8431] +2024-11-22 19:33:51.168514: Epoch time: 20.05 s +2024-11-22 19:33:52.117543: +2024-11-22 19:33:52.119674: Epoch 5899 +2024-11-22 19:33:52.119801: Current learning rate: 0.003 +2024-11-22 19:34:12.426863: train_loss -0.8043 +2024-11-22 19:34:12.433745: val_loss -0.7813 +2024-11-22 19:34:12.433883: Pseudo dice [0.8605] +2024-11-22 19:34:12.433995: Epoch time: 20.31 s +2024-11-22 19:34:13.628108: +2024-11-22 19:34:13.629839: Epoch 5900 +2024-11-22 19:34:13.629981: Current learning rate: 0.003 +2024-11-22 19:34:33.913193: train_loss -0.7995 +2024-11-22 19:34:33.919418: val_loss -0.7716 +2024-11-22 19:34:33.919573: Pseudo dice [0.8589] +2024-11-22 19:34:33.919666: Epoch time: 20.29 s +2024-11-22 19:34:34.922037: +2024-11-22 19:34:34.924215: Epoch 5901 +2024-11-22 19:34:34.924348: Current learning rate: 0.003 +2024-11-22 19:34:53.727322: train_loss -0.7931 +2024-11-22 19:34:53.733432: val_loss -0.7816 +2024-11-22 19:34:53.733561: Pseudo dice [0.8539] +2024-11-22 19:34:53.733664: Epoch time: 18.81 s +2024-11-22 19:34:54.676107: +2024-11-22 19:34:54.678858: Epoch 5902 +2024-11-22 19:34:54.678992: Current learning rate: 0.003 +2024-11-22 19:35:13.968228: train_loss -0.7993 +2024-11-22 19:35:13.994331: val_loss -0.7928 +2024-11-22 19:35:13.994462: Pseudo dice [0.8571] +2024-11-22 19:35:13.994565: Epoch time: 19.29 s +2024-11-22 19:35:15.083339: +2024-11-22 19:35:15.084212: Epoch 5903 +2024-11-22 19:35:15.084343: Current learning rate: 0.003 +2024-11-22 19:35:35.305076: train_loss -0.7922 +2024-11-22 19:35:35.315850: val_loss -0.7943 +2024-11-22 19:35:35.315992: Pseudo dice [0.859] +2024-11-22 19:35:35.316094: Epoch time: 20.22 s +2024-11-22 19:35:36.538073: +2024-11-22 19:35:36.540452: Epoch 5904 +2024-11-22 19:35:36.540593: Current learning rate: 0.003 +2024-11-22 19:35:55.955497: train_loss -0.8038 +2024-11-22 19:35:55.961615: val_loss -0.7589 +2024-11-22 19:35:55.961757: Pseudo dice [0.8538] +2024-11-22 19:35:55.961852: Epoch time: 19.42 s +2024-11-22 19:35:56.838125: +2024-11-22 19:35:56.839628: Epoch 5905 +2024-11-22 19:35:56.839759: Current learning rate: 0.00299 +2024-11-22 19:36:15.925858: train_loss -0.808 +2024-11-22 19:36:15.929628: val_loss -0.7848 +2024-11-22 19:36:15.929764: Pseudo dice [0.8568] +2024-11-22 19:36:15.929887: Epoch time: 19.09 s +2024-11-22 19:36:16.809639: +2024-11-22 19:36:16.811170: Epoch 5906 +2024-11-22 19:36:16.811298: Current learning rate: 0.00299 +2024-11-22 19:36:35.404786: train_loss -0.8031 +2024-11-22 19:36:35.411346: val_loss -0.7791 +2024-11-22 19:36:35.411472: Pseudo dice [0.8538] +2024-11-22 19:36:35.411657: Epoch time: 18.6 s +2024-11-22 19:36:36.409756: +2024-11-22 19:36:36.410226: Epoch 5907 +2024-11-22 19:36:36.410374: Current learning rate: 0.00299 +2024-11-22 19:36:55.633157: train_loss -0.8012 +2024-11-22 19:36:55.639723: val_loss -0.7862 +2024-11-22 19:36:55.639863: Pseudo dice [0.8481] +2024-11-22 19:36:55.639956: Epoch time: 19.22 s +2024-11-22 19:36:56.573936: +2024-11-22 19:36:56.575381: Epoch 5908 +2024-11-22 19:36:56.575516: Current learning rate: 0.00299 +2024-11-22 19:37:16.898645: train_loss -0.7963 +2024-11-22 19:37:16.909827: val_loss -0.7835 +2024-11-22 19:37:16.909963: Pseudo dice [0.8567] +2024-11-22 19:37:16.910085: Epoch time: 20.33 s +2024-11-22 19:37:17.841706: +2024-11-22 19:37:17.843331: Epoch 5909 +2024-11-22 19:37:17.843452: Current learning rate: 0.00299 +2024-11-22 19:37:37.242284: train_loss -0.8002 +2024-11-22 19:37:37.244909: val_loss -0.7651 +2024-11-22 19:37:37.245018: Pseudo dice [0.8516] +2024-11-22 19:37:37.245125: Epoch time: 19.4 s +2024-11-22 19:37:38.116902: +2024-11-22 19:37:38.117640: Epoch 5910 +2024-11-22 19:37:38.117761: Current learning rate: 0.00299 +2024-11-22 19:37:57.655500: train_loss -0.8002 +2024-11-22 19:37:57.675195: val_loss -0.7573 +2024-11-22 19:37:57.675360: Pseudo dice [0.8523] +2024-11-22 19:37:57.675662: Epoch time: 19.54 s +2024-11-22 19:37:58.653996: +2024-11-22 19:37:58.654923: Epoch 5911 +2024-11-22 19:37:58.655041: Current learning rate: 0.00299 +2024-11-22 19:38:18.476521: train_loss -0.7953 +2024-11-22 19:38:18.486679: val_loss -0.7815 +2024-11-22 19:38:18.486801: Pseudo dice [0.8498] +2024-11-22 19:38:18.486903: Epoch time: 19.82 s +2024-11-22 19:38:19.374700: +2024-11-22 19:38:19.376065: Epoch 5912 +2024-11-22 19:38:19.376193: Current learning rate: 0.00299 +2024-11-22 19:38:38.612760: train_loss -0.7989 +2024-11-22 19:38:38.615631: val_loss -0.7852 +2024-11-22 19:38:38.615815: Pseudo dice [0.8524] +2024-11-22 19:38:38.615909: Epoch time: 19.24 s +2024-11-22 19:38:39.661246: +2024-11-22 19:38:39.663644: Epoch 5913 +2024-11-22 19:38:39.663785: Current learning rate: 0.00298 +2024-11-22 19:38:59.389133: train_loss -0.8006 +2024-11-22 19:38:59.394035: val_loss -0.7654 +2024-11-22 19:38:59.394226: Pseudo dice [0.8518] +2024-11-22 19:38:59.394354: Epoch time: 19.73 s +2024-11-22 19:39:00.464421: +2024-11-22 19:39:00.465881: Epoch 5914 +2024-11-22 19:39:00.466256: Current learning rate: 0.00298 +2024-11-22 19:39:19.469384: train_loss -0.8023 +2024-11-22 19:39:19.483120: val_loss -0.7785 +2024-11-22 19:39:19.483265: Pseudo dice [0.8519] +2024-11-22 19:39:19.483366: Epoch time: 19.01 s +2024-11-22 19:39:20.482198: +2024-11-22 19:39:20.482624: Epoch 5915 +2024-11-22 19:39:20.482745: Current learning rate: 0.00298 +2024-11-22 19:39:38.866386: train_loss -0.7918 +2024-11-22 19:39:38.871948: val_loss -0.7732 +2024-11-22 19:39:38.872096: Pseudo dice [0.8614] +2024-11-22 19:39:38.872185: Epoch time: 18.38 s +2024-11-22 19:39:39.753378: +2024-11-22 19:39:39.753824: Epoch 5916 +2024-11-22 19:39:39.753952: Current learning rate: 0.00298 +2024-11-22 19:39:59.091253: train_loss -0.7984 +2024-11-22 19:39:59.098713: val_loss -0.7982 +2024-11-22 19:39:59.098863: Pseudo dice [0.8549] +2024-11-22 19:39:59.098957: Epoch time: 19.34 s +2024-11-22 19:40:00.435535: +2024-11-22 19:40:00.436470: Epoch 5917 +2024-11-22 19:40:00.436606: Current learning rate: 0.00298 +2024-11-22 19:40:19.698766: train_loss -0.7993 +2024-11-22 19:40:19.709152: val_loss -0.7663 +2024-11-22 19:40:19.709285: Pseudo dice [0.8509] +2024-11-22 19:40:19.709396: Epoch time: 19.26 s +2024-11-22 19:40:20.603632: +2024-11-22 19:40:20.605516: Epoch 5918 +2024-11-22 19:40:20.605675: Current learning rate: 0.00298 +2024-11-22 19:40:40.552534: train_loss -0.7973 +2024-11-22 19:40:40.576350: val_loss -0.7728 +2024-11-22 19:40:40.578300: Pseudo dice [0.8592] +2024-11-22 19:40:40.578415: Epoch time: 19.95 s +2024-11-22 19:40:41.600269: +2024-11-22 19:40:41.601461: Epoch 5919 +2024-11-22 19:40:41.601603: Current learning rate: 0.00298 +2024-11-22 19:41:00.983773: train_loss -0.8042 +2024-11-22 19:41:00.990110: val_loss -0.7778 +2024-11-22 19:41:00.990242: Pseudo dice [0.8697] +2024-11-22 19:41:00.990335: Epoch time: 19.38 s +2024-11-22 19:41:01.935153: +2024-11-22 19:41:01.937132: Epoch 5920 +2024-11-22 19:41:01.937283: Current learning rate: 0.00297 +2024-11-22 19:41:22.476697: train_loss -0.808 +2024-11-22 19:41:22.489914: val_loss -0.7742 +2024-11-22 19:41:22.490037: Pseudo dice [0.8629] +2024-11-22 19:41:22.490168: Epoch time: 20.54 s +2024-11-22 19:41:23.359933: +2024-11-22 19:41:23.361535: Epoch 5921 +2024-11-22 19:41:23.361666: Current learning rate: 0.00297 +2024-11-22 19:41:42.893121: train_loss -0.8062 +2024-11-22 19:41:42.899482: val_loss -0.7823 +2024-11-22 19:41:42.899602: Pseudo dice [0.8654] +2024-11-22 19:41:42.899705: Epoch time: 19.53 s +2024-11-22 19:41:43.847851: +2024-11-22 19:41:43.849447: Epoch 5922 +2024-11-22 19:41:43.849581: Current learning rate: 0.00297 +2024-11-22 19:42:03.493099: train_loss -0.8037 +2024-11-22 19:42:03.498611: val_loss -0.7577 +2024-11-22 19:42:03.498791: Pseudo dice [0.8431] +2024-11-22 19:42:03.498895: Epoch time: 19.65 s +2024-11-22 19:42:04.505105: +2024-11-22 19:42:04.507002: Epoch 5923 +2024-11-22 19:42:04.507148: Current learning rate: 0.00297 +2024-11-22 19:42:22.535218: train_loss -0.7984 +2024-11-22 19:42:22.543096: val_loss -0.7674 +2024-11-22 19:42:22.543208: Pseudo dice [0.8429] +2024-11-22 19:42:22.543309: Epoch time: 18.03 s +2024-11-22 19:42:23.664465: +2024-11-22 19:42:23.664690: Epoch 5924 +2024-11-22 19:42:23.664803: Current learning rate: 0.00297 +2024-11-22 19:42:41.280526: train_loss -0.8025 +2024-11-22 19:42:41.288198: val_loss -0.7852 +2024-11-22 19:42:41.288371: Pseudo dice [0.8577] +2024-11-22 19:42:41.288457: Epoch time: 17.62 s +2024-11-22 19:42:42.168751: +2024-11-22 19:42:42.168944: Epoch 5925 +2024-11-22 19:42:42.169065: Current learning rate: 0.00297 +2024-11-22 19:43:01.059117: train_loss -0.7931 +2024-11-22 19:43:01.065827: val_loss -0.7838 +2024-11-22 19:43:01.065964: Pseudo dice [0.8605] +2024-11-22 19:43:01.066050: Epoch time: 18.89 s +2024-11-22 19:43:01.945732: +2024-11-22 19:43:01.945948: Epoch 5926 +2024-11-22 19:43:01.946085: Current learning rate: 0.00297 +2024-11-22 19:43:20.767034: train_loss -0.8051 +2024-11-22 19:43:20.772129: val_loss -0.7717 +2024-11-22 19:43:20.772285: Pseudo dice [0.8647] +2024-11-22 19:43:20.772388: Epoch time: 18.82 s +2024-11-22 19:43:21.655051: +2024-11-22 19:43:21.655258: Epoch 5927 +2024-11-22 19:43:21.655390: Current learning rate: 0.00297 +2024-11-22 19:43:39.805213: train_loss -0.802 +2024-11-22 19:43:39.810154: val_loss -0.7935 +2024-11-22 19:43:39.810315: Pseudo dice [0.8652] +2024-11-22 19:43:39.810404: Epoch time: 18.15 s +2024-11-22 19:43:40.976752: +2024-11-22 19:43:40.976968: Epoch 5928 +2024-11-22 19:43:40.977108: Current learning rate: 0.00296 +2024-11-22 19:44:00.199263: train_loss -0.7988 +2024-11-22 19:44:00.206253: val_loss -0.7858 +2024-11-22 19:44:00.206468: Pseudo dice [0.8482] +2024-11-22 19:44:00.206572: Epoch time: 19.22 s +2024-11-22 19:44:01.176356: +2024-11-22 19:44:01.176581: Epoch 5929 +2024-11-22 19:44:01.176717: Current learning rate: 0.00296 +2024-11-22 19:44:20.311913: train_loss -0.7969 +2024-11-22 19:44:20.314135: val_loss -0.7456 +2024-11-22 19:44:20.314305: Pseudo dice [0.8467] +2024-11-22 19:44:20.314423: Epoch time: 19.14 s +2024-11-22 19:44:21.224558: +2024-11-22 19:44:21.224792: Epoch 5930 +2024-11-22 19:44:21.224908: Current learning rate: 0.00296 +2024-11-22 19:44:40.339544: train_loss -0.79 +2024-11-22 19:44:40.343369: val_loss -0.7843 +2024-11-22 19:44:40.343508: Pseudo dice [0.8505] +2024-11-22 19:44:40.343598: Epoch time: 19.12 s +2024-11-22 19:44:41.308621: +2024-11-22 19:44:41.308854: Epoch 5931 +2024-11-22 19:44:41.308971: Current learning rate: 0.00296 +2024-11-22 19:45:00.293003: train_loss -0.8062 +2024-11-22 19:45:00.299862: val_loss -0.7692 +2024-11-22 19:45:00.300072: Pseudo dice [0.866] +2024-11-22 19:45:00.300326: Epoch time: 18.99 s +2024-11-22 19:45:01.479071: +2024-11-22 19:45:01.479287: Epoch 5932 +2024-11-22 19:45:01.479403: Current learning rate: 0.00296 +2024-11-22 19:45:22.477607: train_loss -0.8033 +2024-11-22 19:45:22.480453: val_loss -0.7646 +2024-11-22 19:45:22.480574: Pseudo dice [0.8444] +2024-11-22 19:45:22.480671: Epoch time: 21.0 s +2024-11-22 19:45:23.369281: +2024-11-22 19:45:23.370103: Epoch 5933 +2024-11-22 19:45:23.370248: Current learning rate: 0.00296 +2024-11-22 19:45:42.668427: train_loss -0.8067 +2024-11-22 19:45:42.677383: val_loss -0.7805 +2024-11-22 19:45:42.677520: Pseudo dice [0.8567] +2024-11-22 19:45:42.677682: Epoch time: 19.3 s +2024-11-22 19:45:43.582359: +2024-11-22 19:45:43.582803: Epoch 5934 +2024-11-22 19:45:43.582927: Current learning rate: 0.00296 +2024-11-22 19:46:04.053993: train_loss -0.8023 +2024-11-22 19:46:04.070837: val_loss -0.7705 +2024-11-22 19:46:04.070972: Pseudo dice [0.856] +2024-11-22 19:46:04.071077: Epoch time: 20.47 s +2024-11-22 19:46:05.105548: +2024-11-22 19:46:05.106087: Epoch 5935 +2024-11-22 19:46:05.106239: Current learning rate: 0.00296 +2024-11-22 19:46:25.078163: train_loss -0.803 +2024-11-22 19:46:25.086120: val_loss -0.7905 +2024-11-22 19:46:25.086254: Pseudo dice [0.8544] +2024-11-22 19:46:25.086345: Epoch time: 19.97 s +2024-11-22 19:46:26.138164: +2024-11-22 19:46:26.139397: Epoch 5936 +2024-11-22 19:46:26.139839: Current learning rate: 0.00295 +2024-11-22 19:46:45.251459: train_loss -0.8021 +2024-11-22 19:46:45.257736: val_loss -0.7896 +2024-11-22 19:46:45.257959: Pseudo dice [0.8636] +2024-11-22 19:46:45.258090: Epoch time: 19.11 s +2024-11-22 19:46:46.161312: +2024-11-22 19:46:46.162641: Epoch 5937 +2024-11-22 19:46:46.162768: Current learning rate: 0.00295 +2024-11-22 19:47:06.854145: train_loss -0.8003 +2024-11-22 19:47:06.859914: val_loss -0.7695 +2024-11-22 19:47:06.860063: Pseudo dice [0.8402] +2024-11-22 19:47:06.860156: Epoch time: 20.69 s +2024-11-22 19:47:07.815485: +2024-11-22 19:47:07.816758: Epoch 5938 +2024-11-22 19:47:07.816902: Current learning rate: 0.00295 +2024-11-22 19:47:26.690711: train_loss -0.8 +2024-11-22 19:47:26.697915: val_loss -0.7644 +2024-11-22 19:47:26.698087: Pseudo dice [0.8429] +2024-11-22 19:47:26.698231: Epoch time: 18.88 s +2024-11-22 19:47:27.588516: +2024-11-22 19:47:27.590130: Epoch 5939 +2024-11-22 19:47:27.590279: Current learning rate: 0.00295 +2024-11-22 19:47:45.806168: train_loss -0.8108 +2024-11-22 19:47:45.810676: val_loss -0.7667 +2024-11-22 19:47:45.810822: Pseudo dice [0.8395] +2024-11-22 19:47:45.810924: Epoch time: 18.22 s +2024-11-22 19:47:47.148392: +2024-11-22 19:47:47.149675: Epoch 5940 +2024-11-22 19:47:47.149867: Current learning rate: 0.00295 +2024-11-22 19:48:07.874722: train_loss -0.803 +2024-11-22 19:48:07.883837: val_loss -0.769 +2024-11-22 19:48:07.883974: Pseudo dice [0.8488] +2024-11-22 19:48:07.884087: Epoch time: 20.73 s +2024-11-22 19:48:08.795356: +2024-11-22 19:48:08.796697: Epoch 5941 +2024-11-22 19:48:08.796842: Current learning rate: 0.00295 +2024-11-22 19:48:27.962942: train_loss -0.8088 +2024-11-22 19:48:27.972085: val_loss -0.7741 +2024-11-22 19:48:27.972230: Pseudo dice [0.8501] +2024-11-22 19:48:27.972313: Epoch time: 19.17 s +2024-11-22 19:48:28.874561: +2024-11-22 19:48:28.876343: Epoch 5942 +2024-11-22 19:48:28.876463: Current learning rate: 0.00295 +2024-11-22 19:48:48.453128: train_loss -0.8108 +2024-11-22 19:48:48.463250: val_loss -0.7872 +2024-11-22 19:48:48.463403: Pseudo dice [0.8616] +2024-11-22 19:48:48.463519: Epoch time: 19.58 s +2024-11-22 19:48:49.351612: +2024-11-22 19:48:49.352719: Epoch 5943 +2024-11-22 19:48:49.352895: Current learning rate: 0.00295 +2024-11-22 19:49:08.355207: train_loss -0.8125 +2024-11-22 19:49:08.360245: val_loss -0.7795 +2024-11-22 19:49:08.360357: Pseudo dice [0.8746] +2024-11-22 19:49:08.360468: Epoch time: 19.0 s +2024-11-22 19:49:09.451582: +2024-11-22 19:49:09.452916: Epoch 5944 +2024-11-22 19:49:09.453052: Current learning rate: 0.00294 +2024-11-22 19:49:29.342690: train_loss -0.807 +2024-11-22 19:49:29.352075: val_loss -0.7835 +2024-11-22 19:49:29.352283: Pseudo dice [0.8645] +2024-11-22 19:49:29.352387: Epoch time: 19.89 s +2024-11-22 19:49:30.295465: +2024-11-22 19:49:30.321389: Epoch 5945 +2024-11-22 19:49:30.321543: Current learning rate: 0.00294 +2024-11-22 19:49:49.152588: train_loss -0.803 +2024-11-22 19:49:49.158794: val_loss -0.7716 +2024-11-22 19:49:49.158932: Pseudo dice [0.8448] +2024-11-22 19:49:49.159029: Epoch time: 18.86 s +2024-11-22 19:49:50.233983: +2024-11-22 19:49:50.234406: Epoch 5946 +2024-11-22 19:49:50.234550: Current learning rate: 0.00294 +2024-11-22 19:50:10.436248: train_loss -0.7936 +2024-11-22 19:50:10.448107: val_loss -0.7792 +2024-11-22 19:50:10.448251: Pseudo dice [0.8483] +2024-11-22 19:50:10.448343: Epoch time: 20.2 s +2024-11-22 19:50:11.519211: +2024-11-22 19:50:11.521104: Epoch 5947 +2024-11-22 19:50:11.521284: Current learning rate: 0.00294 +2024-11-22 19:50:30.728163: train_loss -0.797 +2024-11-22 19:50:30.736811: val_loss -0.7541 +2024-11-22 19:50:30.736995: Pseudo dice [0.8391] +2024-11-22 19:50:30.737092: Epoch time: 19.21 s +2024-11-22 19:50:31.843366: +2024-11-22 19:50:31.844876: Epoch 5948 +2024-11-22 19:50:31.845007: Current learning rate: 0.00294 +2024-11-22 19:50:51.414199: train_loss -0.7997 +2024-11-22 19:50:51.424722: val_loss -0.7759 +2024-11-22 19:50:51.424867: Pseudo dice [0.8576] +2024-11-22 19:50:51.431102: Epoch time: 19.57 s +2024-11-22 19:50:52.433647: +2024-11-22 19:50:52.434769: Epoch 5949 +2024-11-22 19:50:52.434900: Current learning rate: 0.00294 +2024-11-22 19:51:11.597241: train_loss -0.8077 +2024-11-22 19:51:11.610123: val_loss -0.7797 +2024-11-22 19:51:11.610290: Pseudo dice [0.8508] +2024-11-22 19:51:11.610417: Epoch time: 19.16 s +2024-11-22 19:51:12.937322: +2024-11-22 19:51:12.938638: Epoch 5950 +2024-11-22 19:51:12.938771: Current learning rate: 0.00294 +2024-11-22 19:51:32.092426: train_loss -0.8067 +2024-11-22 19:51:32.097095: val_loss -0.7735 +2024-11-22 19:51:32.097210: Pseudo dice [0.8608] +2024-11-22 19:51:32.097313: Epoch time: 19.16 s +2024-11-22 19:51:32.977105: +2024-11-22 19:51:32.978004: Epoch 5951 +2024-11-22 19:51:32.978135: Current learning rate: 0.00293 +2024-11-22 19:51:53.348081: train_loss -0.8076 +2024-11-22 19:51:53.354531: val_loss -0.7733 +2024-11-22 19:51:53.354676: Pseudo dice [0.8561] +2024-11-22 19:51:53.354777: Epoch time: 20.37 s +2024-11-22 19:51:54.273274: +2024-11-22 19:51:54.274177: Epoch 5952 +2024-11-22 19:51:54.274300: Current learning rate: 0.00293 +2024-11-22 19:52:13.627778: train_loss -0.799 +2024-11-22 19:52:13.635118: val_loss -0.7837 +2024-11-22 19:52:13.635314: Pseudo dice [0.8481] +2024-11-22 19:52:13.635419: Epoch time: 19.36 s +2024-11-22 19:52:14.728817: +2024-11-22 19:52:14.730833: Epoch 5953 +2024-11-22 19:52:14.730954: Current learning rate: 0.00293 +2024-11-22 19:52:34.938169: train_loss -0.7952 +2024-11-22 19:52:34.941368: val_loss -0.7895 +2024-11-22 19:52:34.941513: Pseudo dice [0.8621] +2024-11-22 19:52:34.941611: Epoch time: 20.21 s +2024-11-22 19:52:35.909672: +2024-11-22 19:52:35.910124: Epoch 5954 +2024-11-22 19:52:35.910249: Current learning rate: 0.00293 +2024-11-22 19:52:54.974988: train_loss -0.8062 +2024-11-22 19:52:54.984761: val_loss -0.7946 +2024-11-22 19:52:54.984911: Pseudo dice [0.8516] +2024-11-22 19:52:54.985017: Epoch time: 19.07 s +2024-11-22 19:52:55.973121: +2024-11-22 19:52:55.974588: Epoch 5955 +2024-11-22 19:52:55.974721: Current learning rate: 0.00293 +2024-11-22 19:53:15.012214: train_loss -0.808 +2024-11-22 19:53:15.021160: val_loss -0.786 +2024-11-22 19:53:15.021295: Pseudo dice [0.8661] +2024-11-22 19:53:15.021406: Epoch time: 19.04 s +2024-11-22 19:53:15.924663: +2024-11-22 19:53:15.925469: Epoch 5956 +2024-11-22 19:53:15.925593: Current learning rate: 0.00293 +2024-11-22 19:53:35.137168: train_loss -0.8021 +2024-11-22 19:53:35.140372: val_loss -0.7778 +2024-11-22 19:53:35.140558: Pseudo dice [0.8568] +2024-11-22 19:53:35.140683: Epoch time: 19.21 s +2024-11-22 19:53:36.020627: +2024-11-22 19:53:36.022157: Epoch 5957 +2024-11-22 19:53:36.022308: Current learning rate: 0.00293 +2024-11-22 19:53:55.210026: train_loss -0.8006 +2024-11-22 19:53:55.213432: val_loss -0.7761 +2024-11-22 19:53:55.213596: Pseudo dice [0.8722] +2024-11-22 19:53:55.213704: Epoch time: 19.19 s +2024-11-22 19:53:56.094281: +2024-11-22 19:53:56.095119: Epoch 5958 +2024-11-22 19:53:56.095246: Current learning rate: 0.00293 +2024-11-22 19:54:16.590918: train_loss -0.8058 +2024-11-22 19:54:16.594133: val_loss -0.7832 +2024-11-22 19:54:16.594255: Pseudo dice [0.8582] +2024-11-22 19:54:16.594366: Epoch time: 20.5 s +2024-11-22 19:54:17.604783: +2024-11-22 19:54:17.606988: Epoch 5959 +2024-11-22 19:54:17.607140: Current learning rate: 0.00292 +2024-11-22 19:54:38.019698: train_loss -0.7917 +2024-11-22 19:54:38.035088: val_loss -0.7631 +2024-11-22 19:54:38.035250: Pseudo dice [0.8567] +2024-11-22 19:54:38.035369: Epoch time: 20.42 s +2024-11-22 19:54:39.120489: +2024-11-22 19:54:39.120913: Epoch 5960 +2024-11-22 19:54:39.121041: Current learning rate: 0.00292 +2024-11-22 19:54:57.770905: train_loss -0.7992 +2024-11-22 19:54:57.784138: val_loss -0.799 +2024-11-22 19:54:57.784266: Pseudo dice [0.8584] +2024-11-22 19:54:57.784357: Epoch time: 18.65 s +2024-11-22 19:54:58.825377: +2024-11-22 19:54:58.827396: Epoch 5961 +2024-11-22 19:54:58.827552: Current learning rate: 0.00292 +2024-11-22 19:55:18.461670: train_loss -0.81 +2024-11-22 19:55:18.496562: val_loss -0.7786 +2024-11-22 19:55:18.496732: Pseudo dice [0.8591] +2024-11-22 19:55:18.496829: Epoch time: 19.64 s +2024-11-22 19:55:19.383727: +2024-11-22 19:55:19.384214: Epoch 5962 +2024-11-22 19:55:19.384333: Current learning rate: 0.00292 +2024-11-22 19:55:39.501525: train_loss -0.8133 +2024-11-22 19:55:39.525831: val_loss -0.7545 +2024-11-22 19:55:39.525984: Pseudo dice [0.8562] +2024-11-22 19:55:39.526094: Epoch time: 20.12 s +2024-11-22 19:55:40.925156: +2024-11-22 19:55:40.927492: Epoch 5963 +2024-11-22 19:55:40.927628: Current learning rate: 0.00292 +2024-11-22 19:56:00.849827: train_loss -0.7983 +2024-11-22 19:56:00.860292: val_loss -0.7507 +2024-11-22 19:56:00.860448: Pseudo dice [0.8379] +2024-11-22 19:56:00.860560: Epoch time: 19.93 s +2024-11-22 19:56:01.766638: +2024-11-22 19:56:01.768559: Epoch 5964 +2024-11-22 19:56:01.768691: Current learning rate: 0.00292 +2024-11-22 19:56:21.049080: train_loss -0.8112 +2024-11-22 19:56:21.063736: val_loss -0.7871 +2024-11-22 19:56:21.063887: Pseudo dice [0.8651] +2024-11-22 19:56:21.063982: Epoch time: 19.28 s +2024-11-22 19:56:22.026980: +2024-11-22 19:56:22.027914: Epoch 5965 +2024-11-22 19:56:22.028038: Current learning rate: 0.00292 +2024-11-22 19:56:41.554959: train_loss -0.7997 +2024-11-22 19:56:41.562225: val_loss -0.7777 +2024-11-22 19:56:41.562442: Pseudo dice [0.8555] +2024-11-22 19:56:41.562531: Epoch time: 19.53 s +2024-11-22 19:56:42.624340: +2024-11-22 19:56:42.625825: Epoch 5966 +2024-11-22 19:56:42.626262: Current learning rate: 0.00292 +2024-11-22 19:57:02.179373: train_loss -0.8071 +2024-11-22 19:57:02.196119: val_loss -0.7899 +2024-11-22 19:57:02.196291: Pseudo dice [0.8613] +2024-11-22 19:57:02.196405: Epoch time: 19.56 s +2024-11-22 19:57:03.401232: +2024-11-22 19:57:03.402754: Epoch 5967 +2024-11-22 19:57:03.402883: Current learning rate: 0.00291 +2024-11-22 19:57:22.580607: train_loss -0.7998 +2024-11-22 19:57:22.609063: val_loss -0.7855 +2024-11-22 19:57:22.609216: Pseudo dice [0.8562] +2024-11-22 19:57:22.609310: Epoch time: 19.18 s +2024-11-22 19:57:23.565946: +2024-11-22 19:57:23.567194: Epoch 5968 +2024-11-22 19:57:23.567314: Current learning rate: 0.00291 +2024-11-22 19:57:42.944581: train_loss -0.7984 +2024-11-22 19:57:42.951656: val_loss -0.7806 +2024-11-22 19:57:42.951801: Pseudo dice [0.8551] +2024-11-22 19:57:42.951912: Epoch time: 19.38 s +2024-11-22 19:57:43.840356: +2024-11-22 19:57:43.841022: Epoch 5969 +2024-11-22 19:57:43.841147: Current learning rate: 0.00291 +2024-11-22 19:58:03.095491: train_loss -0.8009 +2024-11-22 19:58:03.113340: val_loss -0.7804 +2024-11-22 19:58:03.113468: Pseudo dice [0.8631] +2024-11-22 19:58:03.113556: Epoch time: 19.26 s +2024-11-22 19:58:04.151837: +2024-11-22 19:58:04.152628: Epoch 5970 +2024-11-22 19:58:04.152752: Current learning rate: 0.00291 +2024-11-22 19:58:22.902785: train_loss -0.8012 +2024-11-22 19:58:22.910951: val_loss -0.762 +2024-11-22 19:58:22.911096: Pseudo dice [0.8382] +2024-11-22 19:58:22.911204: Epoch time: 18.75 s +2024-11-22 19:58:24.037394: +2024-11-22 19:58:24.038557: Epoch 5971 +2024-11-22 19:58:24.038690: Current learning rate: 0.00291 +2024-11-22 19:58:43.399105: train_loss -0.8009 +2024-11-22 19:58:43.402378: val_loss -0.789 +2024-11-22 19:58:43.402491: Pseudo dice [0.8576] +2024-11-22 19:58:43.402586: Epoch time: 19.36 s +2024-11-22 19:58:44.280323: +2024-11-22 19:58:44.280539: Epoch 5972 +2024-11-22 19:58:44.280668: Current learning rate: 0.00291 +2024-11-22 19:59:04.179479: train_loss -0.8038 +2024-11-22 19:59:04.184486: val_loss -0.7662 +2024-11-22 19:59:04.184690: Pseudo dice [0.8423] +2024-11-22 19:59:04.184806: Epoch time: 19.9 s +2024-11-22 19:59:05.134881: +2024-11-22 19:59:05.135706: Epoch 5973 +2024-11-22 19:59:05.135833: Current learning rate: 0.00291 +2024-11-22 19:59:24.571107: train_loss -0.7971 +2024-11-22 19:59:24.585923: val_loss -0.758 +2024-11-22 19:59:24.586082: Pseudo dice [0.8654] +2024-11-22 19:59:24.586191: Epoch time: 19.44 s +2024-11-22 19:59:26.022009: +2024-11-22 19:59:26.023033: Epoch 5974 +2024-11-22 19:59:26.023165: Current learning rate: 0.00291 +2024-11-22 19:59:45.872638: train_loss -0.8011 +2024-11-22 19:59:45.883166: val_loss -0.7704 +2024-11-22 19:59:45.883332: Pseudo dice [0.8465] +2024-11-22 19:59:45.883426: Epoch time: 19.85 s +2024-11-22 19:59:46.906516: +2024-11-22 19:59:46.906970: Epoch 5975 +2024-11-22 19:59:46.907114: Current learning rate: 0.0029 +2024-11-22 20:00:06.869639: train_loss -0.8102 +2024-11-22 20:00:06.875735: val_loss -0.774 +2024-11-22 20:00:06.875882: Pseudo dice [0.8526] +2024-11-22 20:00:06.875984: Epoch time: 19.96 s +2024-11-22 20:00:07.790743: +2024-11-22 20:00:07.791993: Epoch 5976 +2024-11-22 20:00:07.792146: Current learning rate: 0.0029 +2024-11-22 20:00:27.621968: train_loss -0.7972 +2024-11-22 20:00:27.629395: val_loss -0.7764 +2024-11-22 20:00:27.629535: Pseudo dice [0.8485] +2024-11-22 20:00:27.629623: Epoch time: 19.83 s +2024-11-22 20:00:28.660500: +2024-11-22 20:00:28.662265: Epoch 5977 +2024-11-22 20:00:28.662411: Current learning rate: 0.0029 +2024-11-22 20:00:48.291131: train_loss -0.8078 +2024-11-22 20:00:48.294419: val_loss -0.7799 +2024-11-22 20:00:48.294556: Pseudo dice [0.8539] +2024-11-22 20:00:48.294663: Epoch time: 19.63 s +2024-11-22 20:00:49.171356: +2024-11-22 20:00:49.173097: Epoch 5978 +2024-11-22 20:00:49.173233: Current learning rate: 0.0029 +2024-11-22 20:01:08.849384: train_loss -0.8059 +2024-11-22 20:01:08.865278: val_loss -0.7959 +2024-11-22 20:01:08.865438: Pseudo dice [0.8576] +2024-11-22 20:01:08.865562: Epoch time: 19.68 s +2024-11-22 20:01:09.979531: +2024-11-22 20:01:09.980367: Epoch 5979 +2024-11-22 20:01:09.980509: Current learning rate: 0.0029 +2024-11-22 20:01:30.288822: train_loss -0.8 +2024-11-22 20:01:30.305845: val_loss -0.7864 +2024-11-22 20:01:30.306005: Pseudo dice [0.8568] +2024-11-22 20:01:30.306108: Epoch time: 20.31 s +2024-11-22 20:01:31.210453: +2024-11-22 20:01:31.211484: Epoch 5980 +2024-11-22 20:01:31.211602: Current learning rate: 0.0029 +2024-11-22 20:01:51.306981: train_loss -0.807 +2024-11-22 20:01:51.310343: val_loss -0.7787 +2024-11-22 20:01:51.310448: Pseudo dice [0.8528] +2024-11-22 20:01:51.310535: Epoch time: 20.1 s +2024-11-22 20:01:52.188018: +2024-11-22 20:01:52.188464: Epoch 5981 +2024-11-22 20:01:52.188583: Current learning rate: 0.0029 +2024-11-22 20:02:12.290694: train_loss -0.8043 +2024-11-22 20:02:12.293924: val_loss -0.7658 +2024-11-22 20:02:12.294069: Pseudo dice [0.8578] +2024-11-22 20:02:12.294162: Epoch time: 20.1 s +2024-11-22 20:02:13.389944: +2024-11-22 20:02:13.391358: Epoch 5982 +2024-11-22 20:02:13.391498: Current learning rate: 0.00289 +2024-11-22 20:02:33.007759: train_loss -0.8085 +2024-11-22 20:02:33.010642: val_loss -0.7699 +2024-11-22 20:02:33.010773: Pseudo dice [0.8541] +2024-11-22 20:02:33.010871: Epoch time: 19.62 s +2024-11-22 20:02:33.971052: +2024-11-22 20:02:33.972713: Epoch 5983 +2024-11-22 20:02:33.972873: Current learning rate: 0.00289 +2024-11-22 20:02:54.409323: train_loss -0.809 +2024-11-22 20:02:54.416747: val_loss -0.788 +2024-11-22 20:02:54.416909: Pseudo dice [0.8572] +2024-11-22 20:02:54.417013: Epoch time: 20.44 s +2024-11-22 20:02:55.402993: +2024-11-22 20:02:55.403811: Epoch 5984 +2024-11-22 20:02:55.403933: Current learning rate: 0.00289 +2024-11-22 20:03:15.069808: train_loss -0.8056 +2024-11-22 20:03:15.072099: val_loss -0.762 +2024-11-22 20:03:15.072197: Pseudo dice [0.8545] +2024-11-22 20:03:15.072300: Epoch time: 19.67 s +2024-11-22 20:03:15.941796: +2024-11-22 20:03:15.942883: Epoch 5985 +2024-11-22 20:03:15.943014: Current learning rate: 0.00289 +2024-11-22 20:03:34.897855: train_loss -0.8066 +2024-11-22 20:03:34.901194: val_loss -0.7792 +2024-11-22 20:03:34.901320: Pseudo dice [0.8514] +2024-11-22 20:03:34.901419: Epoch time: 18.96 s +2024-11-22 20:03:36.377239: +2024-11-22 20:03:36.378817: Epoch 5986 +2024-11-22 20:03:36.378938: Current learning rate: 0.00289 +2024-11-22 20:03:55.832148: train_loss -0.8062 +2024-11-22 20:03:55.837385: val_loss -0.7707 +2024-11-22 20:03:55.837540: Pseudo dice [0.8555] +2024-11-22 20:03:55.837656: Epoch time: 19.46 s +2024-11-22 20:03:56.743643: +2024-11-22 20:03:56.744757: Epoch 5987 +2024-11-22 20:03:56.744892: Current learning rate: 0.00289 +2024-11-22 20:04:16.429100: train_loss -0.8014 +2024-11-22 20:04:16.435332: val_loss -0.7934 +2024-11-22 20:04:16.435467: Pseudo dice [0.8606] +2024-11-22 20:04:16.435565: Epoch time: 19.69 s +2024-11-22 20:04:17.369099: +2024-11-22 20:04:17.370874: Epoch 5988 +2024-11-22 20:04:17.371004: Current learning rate: 0.00289 +2024-11-22 20:04:36.931015: train_loss -0.8066 +2024-11-22 20:04:36.937758: val_loss -0.7681 +2024-11-22 20:04:36.937892: Pseudo dice [0.8544] +2024-11-22 20:04:36.937978: Epoch time: 19.56 s +2024-11-22 20:04:38.050969: +2024-11-22 20:04:38.052043: Epoch 5989 +2024-11-22 20:04:38.052171: Current learning rate: 0.00289 +2024-11-22 20:04:57.239174: train_loss -0.8058 +2024-11-22 20:04:57.247257: val_loss -0.7515 +2024-11-22 20:04:57.247408: Pseudo dice [0.8431] +2024-11-22 20:04:57.247525: Epoch time: 19.19 s +2024-11-22 20:04:58.160648: +2024-11-22 20:04:58.162081: Epoch 5990 +2024-11-22 20:04:58.162216: Current learning rate: 0.00288 +2024-11-22 20:05:17.682013: train_loss -0.8073 +2024-11-22 20:05:17.701722: val_loss -0.761 +2024-11-22 20:05:17.701879: Pseudo dice [0.8595] +2024-11-22 20:05:17.701975: Epoch time: 19.52 s +2024-11-22 20:05:18.635823: +2024-11-22 20:05:18.636955: Epoch 5991 +2024-11-22 20:05:18.637092: Current learning rate: 0.00288 +2024-11-22 20:05:38.233692: train_loss -0.8056 +2024-11-22 20:05:38.241388: val_loss -0.7676 +2024-11-22 20:05:38.241527: Pseudo dice [0.8705] +2024-11-22 20:05:38.241626: Epoch time: 19.6 s +2024-11-22 20:05:39.139630: +2024-11-22 20:05:39.140328: Epoch 5992 +2024-11-22 20:05:39.140456: Current learning rate: 0.00288 +2024-11-22 20:05:58.427145: train_loss -0.7931 +2024-11-22 20:05:58.435894: val_loss -0.7768 +2024-11-22 20:05:58.436031: Pseudo dice [0.8687] +2024-11-22 20:05:58.436189: Epoch time: 19.29 s +2024-11-22 20:05:59.368388: +2024-11-22 20:05:59.369586: Epoch 5993 +2024-11-22 20:05:59.369707: Current learning rate: 0.00288 +2024-11-22 20:06:19.008640: train_loss -0.8089 +2024-11-22 20:06:19.017175: val_loss -0.7998 +2024-11-22 20:06:19.017309: Pseudo dice [0.8726] +2024-11-22 20:06:19.017408: Epoch time: 19.64 s +2024-11-22 20:06:20.109691: +2024-11-22 20:06:20.111375: Epoch 5994 +2024-11-22 20:06:20.111528: Current learning rate: 0.00288 +2024-11-22 20:06:39.612829: train_loss -0.8107 +2024-11-22 20:06:39.617430: val_loss -0.7861 +2024-11-22 20:06:39.617565: Pseudo dice [0.8444] +2024-11-22 20:06:39.617671: Epoch time: 19.5 s +2024-11-22 20:06:40.494786: +2024-11-22 20:06:40.495307: Epoch 5995 +2024-11-22 20:06:40.495460: Current learning rate: 0.00288 +2024-11-22 20:07:00.305806: train_loss -0.8057 +2024-11-22 20:07:00.314072: val_loss -0.7785 +2024-11-22 20:07:00.314289: Pseudo dice [0.8554] +2024-11-22 20:07:00.314389: Epoch time: 19.81 s +2024-11-22 20:07:01.434187: +2024-11-22 20:07:01.435731: Epoch 5996 +2024-11-22 20:07:01.435869: Current learning rate: 0.00288 +2024-11-22 20:07:21.026937: train_loss -0.8119 +2024-11-22 20:07:21.038080: val_loss -0.7579 +2024-11-22 20:07:21.038235: Pseudo dice [0.8575] +2024-11-22 20:07:21.038332: Epoch time: 19.59 s +2024-11-22 20:07:22.126099: +2024-11-22 20:07:22.127249: Epoch 5997 +2024-11-22 20:07:22.127373: Current learning rate: 0.00288 +2024-11-22 20:07:41.984054: train_loss -0.8046 +2024-11-22 20:07:41.992117: val_loss -0.7669 +2024-11-22 20:07:41.992266: Pseudo dice [0.849] +2024-11-22 20:07:41.992371: Epoch time: 19.86 s +2024-11-22 20:07:42.923776: +2024-11-22 20:07:42.924012: Epoch 5998 +2024-11-22 20:07:42.924146: Current learning rate: 0.00287 +2024-11-22 20:08:00.503886: train_loss -0.805 +2024-11-22 20:08:00.508744: val_loss -0.7862 +2024-11-22 20:08:00.508905: Pseudo dice [0.8576] +2024-11-22 20:08:00.509000: Epoch time: 17.58 s +2024-11-22 20:08:01.555490: +2024-11-22 20:08:01.555703: Epoch 5999 +2024-11-22 20:08:01.555835: Current learning rate: 0.00287 +2024-11-22 20:08:20.017336: train_loss -0.8064 +2024-11-22 20:08:20.018368: val_loss -0.7739 +2024-11-22 20:08:20.018751: Pseudo dice [0.8469] +2024-11-22 20:08:20.018851: Epoch time: 18.46 s +2024-11-22 20:08:21.194547: +2024-11-22 20:08:21.194776: Epoch 6000 +2024-11-22 20:08:21.194891: Current learning rate: 0.00287 +2024-11-22 20:08:40.110214: train_loss -0.803 +2024-11-22 20:08:40.115239: val_loss -0.768 +2024-11-22 20:08:40.115407: Pseudo dice [0.8575] +2024-11-22 20:08:40.115513: Epoch time: 18.92 s +2024-11-22 20:08:41.001921: +2024-11-22 20:08:41.002129: Epoch 6001 +2024-11-22 20:08:41.002248: Current learning rate: 0.00287 +2024-11-22 20:08:59.227313: train_loss -0.807 +2024-11-22 20:08:59.229203: val_loss -0.7666 +2024-11-22 20:08:59.229377: Pseudo dice [0.8438] +2024-11-22 20:08:59.229470: Epoch time: 18.23 s +2024-11-22 20:09:00.242031: +2024-11-22 20:09:00.242246: Epoch 6002 +2024-11-22 20:09:00.242361: Current learning rate: 0.00287 +2024-11-22 20:09:20.047380: train_loss -0.8024 +2024-11-22 20:09:20.054615: val_loss -0.7907 +2024-11-22 20:09:20.054752: Pseudo dice [0.8558] +2024-11-22 20:09:20.054855: Epoch time: 19.81 s +2024-11-22 20:09:21.044902: +2024-11-22 20:09:21.045095: Epoch 6003 +2024-11-22 20:09:21.045233: Current learning rate: 0.00287 +2024-11-22 20:09:39.992553: train_loss -0.8097 +2024-11-22 20:09:39.997383: val_loss -0.7673 +2024-11-22 20:09:39.997524: Pseudo dice [0.8591] +2024-11-22 20:09:39.997640: Epoch time: 18.95 s +2024-11-22 20:09:40.894415: +2024-11-22 20:09:40.894623: Epoch 6004 +2024-11-22 20:09:40.894734: Current learning rate: 0.00287 +2024-11-22 20:10:00.144549: train_loss -0.8017 +2024-11-22 20:10:00.145716: val_loss -0.7913 +2024-11-22 20:10:00.145836: Pseudo dice [0.8597] +2024-11-22 20:10:00.145931: Epoch time: 19.25 s +2024-11-22 20:10:01.021513: +2024-11-22 20:10:01.021728: Epoch 6005 +2024-11-22 20:10:01.021871: Current learning rate: 0.00287 +2024-11-22 20:10:20.060538: train_loss -0.8091 +2024-11-22 20:10:20.066106: val_loss -0.7722 +2024-11-22 20:10:20.066239: Pseudo dice [0.8648] +2024-11-22 20:10:20.068540: Epoch time: 19.04 s +2024-11-22 20:10:20.961383: +2024-11-22 20:10:20.961583: Epoch 6006 +2024-11-22 20:10:20.961703: Current learning rate: 0.00286 +2024-11-22 20:10:40.568322: train_loss -0.8101 +2024-11-22 20:10:40.576528: val_loss -0.791 +2024-11-22 20:10:40.576651: Pseudo dice [0.8594] +2024-11-22 20:10:40.576828: Epoch time: 19.61 s +2024-11-22 20:10:41.658078: +2024-11-22 20:10:41.659879: Epoch 6007 +2024-11-22 20:10:41.660012: Current learning rate: 0.00286 +2024-11-22 20:11:01.599604: train_loss -0.8123 +2024-11-22 20:11:01.607734: val_loss -0.7874 +2024-11-22 20:11:01.607857: Pseudo dice [0.859] +2024-11-22 20:11:01.607946: Epoch time: 19.94 s +2024-11-22 20:11:02.608322: +2024-11-22 20:11:02.609404: Epoch 6008 +2024-11-22 20:11:02.609522: Current learning rate: 0.00286 +2024-11-22 20:11:21.911325: train_loss -0.8197 +2024-11-22 20:11:21.916334: val_loss -0.7818 +2024-11-22 20:11:21.917393: Pseudo dice [0.872] +2024-11-22 20:11:21.917514: Epoch time: 19.3 s +2024-11-22 20:11:22.856370: +2024-11-22 20:11:22.857690: Epoch 6009 +2024-11-22 20:11:22.857820: Current learning rate: 0.00286 +2024-11-22 20:11:42.731055: train_loss -0.8143 +2024-11-22 20:11:42.768939: val_loss -0.7824 +2024-11-22 20:11:42.769109: Pseudo dice [0.8699] +2024-11-22 20:11:42.769220: Epoch time: 19.88 s +2024-11-22 20:11:43.671472: +2024-11-22 20:11:43.672460: Epoch 6010 +2024-11-22 20:11:43.672590: Current learning rate: 0.00286 +2024-11-22 20:12:03.379653: train_loss -0.8136 +2024-11-22 20:12:03.385889: val_loss -0.7847 +2024-11-22 20:12:03.386017: Pseudo dice [0.8535] +2024-11-22 20:12:03.386117: Epoch time: 19.71 s +2024-11-22 20:12:04.429507: +2024-11-22 20:12:04.431198: Epoch 6011 +2024-11-22 20:12:04.431328: Current learning rate: 0.00286 +2024-11-22 20:12:24.643280: train_loss -0.8066 +2024-11-22 20:12:24.648993: val_loss -0.7765 +2024-11-22 20:12:24.649123: Pseudo dice [0.8638] +2024-11-22 20:12:24.649228: Epoch time: 20.21 s +2024-11-22 20:12:25.594360: +2024-11-22 20:12:25.595564: Epoch 6012 +2024-11-22 20:12:25.595703: Current learning rate: 0.00286 +2024-11-22 20:12:46.083107: train_loss -0.8054 +2024-11-22 20:12:46.087257: val_loss -0.7868 +2024-11-22 20:12:46.087380: Pseudo dice [0.8614] +2024-11-22 20:12:46.087474: Epoch time: 20.49 s +2024-11-22 20:12:47.032241: +2024-11-22 20:12:47.033568: Epoch 6013 +2024-11-22 20:12:47.033695: Current learning rate: 0.00285 +2024-11-22 20:13:06.444301: train_loss -0.8049 +2024-11-22 20:13:06.453816: val_loss -0.795 +2024-11-22 20:13:06.453964: Pseudo dice [0.8598] +2024-11-22 20:13:06.454069: Epoch time: 19.41 s +2024-11-22 20:13:07.454971: +2024-11-22 20:13:07.456344: Epoch 6014 +2024-11-22 20:13:07.456487: Current learning rate: 0.00285 +2024-11-22 20:13:26.261732: train_loss -0.7976 +2024-11-22 20:13:26.269901: val_loss -0.7756 +2024-11-22 20:13:26.270040: Pseudo dice [0.8606] +2024-11-22 20:13:26.270147: Epoch time: 18.81 s +2024-11-22 20:13:27.487764: +2024-11-22 20:13:27.490141: Epoch 6015 +2024-11-22 20:13:27.490277: Current learning rate: 0.00285 +2024-11-22 20:13:48.462933: train_loss -0.8055 +2024-11-22 20:13:48.470736: val_loss -0.7755 +2024-11-22 20:13:48.475327: Pseudo dice [0.853] +2024-11-22 20:13:48.475434: Epoch time: 20.98 s +2024-11-22 20:13:49.428762: +2024-11-22 20:13:49.429272: Epoch 6016 +2024-11-22 20:13:49.429410: Current learning rate: 0.00285 +2024-11-22 20:14:08.502341: train_loss -0.8082 +2024-11-22 20:14:08.508871: val_loss -0.7699 +2024-11-22 20:14:08.509093: Pseudo dice [0.852] +2024-11-22 20:14:08.509215: Epoch time: 19.07 s +2024-11-22 20:14:09.544990: +2024-11-22 20:14:09.546227: Epoch 6017 +2024-11-22 20:14:09.546376: Current learning rate: 0.00285 +2024-11-22 20:14:30.999556: train_loss -0.8077 +2024-11-22 20:14:31.005389: val_loss -0.7825 +2024-11-22 20:14:31.005532: Pseudo dice [0.8559] +2024-11-22 20:14:31.005627: Epoch time: 21.46 s +2024-11-22 20:14:32.160900: +2024-11-22 20:14:32.162542: Epoch 6018 +2024-11-22 20:14:32.162692: Current learning rate: 0.00285 +2024-11-22 20:14:50.653052: train_loss -0.8111 +2024-11-22 20:14:50.660639: val_loss -0.787 +2024-11-22 20:14:50.660782: Pseudo dice [0.8685] +2024-11-22 20:14:50.660883: Epoch time: 18.49 s +2024-11-22 20:14:51.647629: +2024-11-22 20:14:51.649269: Epoch 6019 +2024-11-22 20:14:51.649406: Current learning rate: 0.00285 +2024-11-22 20:15:11.028452: train_loss -0.8083 +2024-11-22 20:15:11.037659: val_loss -0.779 +2024-11-22 20:15:11.037802: Pseudo dice [0.869] +2024-11-22 20:15:11.037893: Epoch time: 19.38 s +2024-11-22 20:15:12.478516: +2024-11-22 20:15:12.480351: Epoch 6020 +2024-11-22 20:15:12.480493: Current learning rate: 0.00285 +2024-11-22 20:15:32.941126: train_loss -0.81 +2024-11-22 20:15:32.943948: val_loss -0.7688 +2024-11-22 20:15:32.944165: Pseudo dice [0.8584] +2024-11-22 20:15:32.944274: Epoch time: 20.46 s +2024-11-22 20:15:33.829073: +2024-11-22 20:15:33.829519: Epoch 6021 +2024-11-22 20:15:33.829676: Current learning rate: 0.00284 +2024-11-22 20:15:54.389753: train_loss -0.8043 +2024-11-22 20:15:54.391914: val_loss -0.7794 +2024-11-22 20:15:54.392050: Pseudo dice [0.8619] +2024-11-22 20:15:54.392166: Epoch time: 20.56 s +2024-11-22 20:15:55.511996: +2024-11-22 20:15:55.513520: Epoch 6022 +2024-11-22 20:15:55.513724: Current learning rate: 0.00284 +2024-11-22 20:16:14.981475: train_loss -0.8159 +2024-11-22 20:16:14.988144: val_loss -0.7923 +2024-11-22 20:16:14.988283: Pseudo dice [0.8572] +2024-11-22 20:16:14.988370: Epoch time: 19.47 s +2024-11-22 20:16:15.884465: +2024-11-22 20:16:15.886373: Epoch 6023 +2024-11-22 20:16:15.886496: Current learning rate: 0.00284 +2024-11-22 20:16:35.574403: train_loss -0.8047 +2024-11-22 20:16:35.577040: val_loss -0.7964 +2024-11-22 20:16:35.577215: Pseudo dice [0.8666] +2024-11-22 20:16:35.577327: Epoch time: 19.69 s +2024-11-22 20:16:36.579405: +2024-11-22 20:16:36.580379: Epoch 6024 +2024-11-22 20:16:36.580538: Current learning rate: 0.00284 +2024-11-22 20:16:56.259616: train_loss -0.8105 +2024-11-22 20:16:56.261630: val_loss -0.7697 +2024-11-22 20:16:56.261756: Pseudo dice [0.8405] +2024-11-22 20:16:56.261847: Epoch time: 19.68 s +2024-11-22 20:16:57.193281: +2024-11-22 20:16:57.194534: Epoch 6025 +2024-11-22 20:16:57.194676: Current learning rate: 0.00284 +2024-11-22 20:17:15.796483: train_loss -0.8042 +2024-11-22 20:17:15.802835: val_loss -0.7553 +2024-11-22 20:17:15.802984: Pseudo dice [0.8416] +2024-11-22 20:17:15.803080: Epoch time: 18.6 s +2024-11-22 20:17:16.783767: +2024-11-22 20:17:16.784788: Epoch 6026 +2024-11-22 20:17:16.784904: Current learning rate: 0.00284 +2024-11-22 20:17:35.840966: train_loss -0.8063 +2024-11-22 20:17:35.848654: val_loss -0.775 +2024-11-22 20:17:35.848788: Pseudo dice [0.8673] +2024-11-22 20:17:35.848869: Epoch time: 19.06 s +2024-11-22 20:17:36.785260: +2024-11-22 20:17:36.786598: Epoch 6027 +2024-11-22 20:17:36.786730: Current learning rate: 0.00284 +2024-11-22 20:17:56.036508: train_loss -0.8124 +2024-11-22 20:17:56.041644: val_loss -0.774 +2024-11-22 20:17:56.041781: Pseudo dice [0.8633] +2024-11-22 20:17:56.041878: Epoch time: 19.25 s +2024-11-22 20:17:57.069386: +2024-11-22 20:17:57.070366: Epoch 6028 +2024-11-22 20:17:57.070512: Current learning rate: 0.00284 +2024-11-22 20:18:16.344548: train_loss -0.805 +2024-11-22 20:18:16.360369: val_loss -0.7592 +2024-11-22 20:18:16.360518: Pseudo dice [0.85] +2024-11-22 20:18:16.360609: Epoch time: 19.28 s +2024-11-22 20:18:17.327702: +2024-11-22 20:18:17.328209: Epoch 6029 +2024-11-22 20:18:17.328327: Current learning rate: 0.00283 +2024-11-22 20:18:37.790114: train_loss -0.8028 +2024-11-22 20:18:37.806212: val_loss -0.7835 +2024-11-22 20:18:37.806363: Pseudo dice [0.8524] +2024-11-22 20:18:37.806475: Epoch time: 20.46 s +2024-11-22 20:18:38.849798: +2024-11-22 20:18:38.851349: Epoch 6030 +2024-11-22 20:18:38.851484: Current learning rate: 0.00283 +2024-11-22 20:18:58.713440: train_loss -0.8084 +2024-11-22 20:18:58.721782: val_loss -0.7523 +2024-11-22 20:18:58.721943: Pseudo dice [0.8658] +2024-11-22 20:18:58.722069: Epoch time: 19.86 s +2024-11-22 20:18:59.666549: +2024-11-22 20:18:59.667576: Epoch 6031 +2024-11-22 20:18:59.667702: Current learning rate: 0.00283 +2024-11-22 20:19:19.836112: train_loss -0.8041 +2024-11-22 20:19:19.843127: val_loss -0.7692 +2024-11-22 20:19:19.846800: Pseudo dice [0.856] +2024-11-22 20:19:19.846913: Epoch time: 20.17 s +2024-11-22 20:19:20.907740: +2024-11-22 20:19:20.909032: Epoch 6032 +2024-11-22 20:19:20.909163: Current learning rate: 0.00283 +2024-11-22 20:19:40.758527: train_loss -0.8057 +2024-11-22 20:19:40.763586: val_loss -0.7875 +2024-11-22 20:19:40.763709: Pseudo dice [0.8724] +2024-11-22 20:19:40.763795: Epoch time: 19.85 s +2024-11-22 20:19:41.768159: +2024-11-22 20:19:41.768616: Epoch 6033 +2024-11-22 20:19:41.768750: Current learning rate: 0.00283 +2024-11-22 20:20:01.900432: train_loss -0.8114 +2024-11-22 20:20:01.906680: val_loss -0.7652 +2024-11-22 20:20:01.906808: Pseudo dice [0.8504] +2024-11-22 20:20:01.906993: Epoch time: 20.13 s +2024-11-22 20:20:03.040642: +2024-11-22 20:20:03.041426: Epoch 6034 +2024-11-22 20:20:03.041553: Current learning rate: 0.00283 +2024-11-22 20:20:22.714265: train_loss -0.7962 +2024-11-22 20:20:22.733899: val_loss -0.7681 +2024-11-22 20:20:22.734052: Pseudo dice [0.8578] +2024-11-22 20:20:22.734157: Epoch time: 19.67 s +2024-11-22 20:20:23.681033: +2024-11-22 20:20:23.682977: Epoch 6035 +2024-11-22 20:20:23.683107: Current learning rate: 0.00283 +2024-11-22 20:20:43.306497: train_loss -0.8106 +2024-11-22 20:20:43.312652: val_loss -0.7697 +2024-11-22 20:20:43.312791: Pseudo dice [0.8518] +2024-11-22 20:20:43.312919: Epoch time: 19.63 s +2024-11-22 20:20:44.219233: +2024-11-22 20:20:44.220123: Epoch 6036 +2024-11-22 20:20:44.220263: Current learning rate: 0.00283 +2024-11-22 20:21:03.618991: train_loss -0.8089 +2024-11-22 20:21:03.624796: val_loss -0.776 +2024-11-22 20:21:03.624991: Pseudo dice [0.8637] +2024-11-22 20:21:03.625093: Epoch time: 19.4 s +2024-11-22 20:21:04.508835: +2024-11-22 20:21:04.509359: Epoch 6037 +2024-11-22 20:21:04.509497: Current learning rate: 0.00282 +2024-11-22 20:21:24.151040: train_loss -0.8025 +2024-11-22 20:21:24.159948: val_loss -0.7774 +2024-11-22 20:21:24.160169: Pseudo dice [0.8578] +2024-11-22 20:21:24.160488: Epoch time: 19.64 s +2024-11-22 20:21:25.084749: +2024-11-22 20:21:25.086149: Epoch 6038 +2024-11-22 20:21:25.086277: Current learning rate: 0.00282 +2024-11-22 20:21:43.940104: train_loss -0.7937 +2024-11-22 20:21:43.947382: val_loss -0.7968 +2024-11-22 20:21:43.947537: Pseudo dice [0.8521] +2024-11-22 20:21:43.947647: Epoch time: 18.86 s +2024-11-22 20:21:44.871716: +2024-11-22 20:21:44.872983: Epoch 6039 +2024-11-22 20:21:44.873152: Current learning rate: 0.00282 +2024-11-22 20:22:03.850419: train_loss -0.8036 +2024-11-22 20:22:03.865202: val_loss -0.7755 +2024-11-22 20:22:03.865337: Pseudo dice [0.8487] +2024-11-22 20:22:03.865446: Epoch time: 18.98 s +2024-11-22 20:22:05.113901: +2024-11-22 20:22:05.115561: Epoch 6040 +2024-11-22 20:22:05.115689: Current learning rate: 0.00282 +2024-11-22 20:22:24.031280: train_loss -0.7959 +2024-11-22 20:22:24.037678: val_loss -0.7549 +2024-11-22 20:22:24.037870: Pseudo dice [0.8474] +2024-11-22 20:22:24.037976: Epoch time: 18.92 s +2024-11-22 20:22:24.946596: +2024-11-22 20:22:24.947943: Epoch 6041 +2024-11-22 20:22:24.948090: Current learning rate: 0.00282 +2024-11-22 20:22:44.356582: train_loss -0.7943 +2024-11-22 20:22:44.362868: val_loss -0.7559 +2024-11-22 20:22:44.363037: Pseudo dice [0.8569] +2024-11-22 20:22:44.363165: Epoch time: 19.41 s +2024-11-22 20:22:45.268223: +2024-11-22 20:22:45.269199: Epoch 6042 +2024-11-22 20:22:45.269323: Current learning rate: 0.00282 +2024-11-22 20:23:05.672603: train_loss -0.7906 +2024-11-22 20:23:05.688513: val_loss -0.7957 +2024-11-22 20:23:05.688686: Pseudo dice [0.8655] +2024-11-22 20:23:05.688794: Epoch time: 20.41 s +2024-11-22 20:23:07.111296: +2024-11-22 20:23:07.112612: Epoch 6043 +2024-11-22 20:23:07.112731: Current learning rate: 0.00282 +2024-11-22 20:23:27.174430: train_loss -0.8 +2024-11-22 20:23:27.184515: val_loss -0.7736 +2024-11-22 20:23:27.184650: Pseudo dice [0.8517] +2024-11-22 20:23:27.184766: Epoch time: 20.06 s +2024-11-22 20:23:28.134487: +2024-11-22 20:23:28.135019: Epoch 6044 +2024-11-22 20:23:28.135156: Current learning rate: 0.00281 +2024-11-22 20:23:47.842887: train_loss -0.7993 +2024-11-22 20:23:47.849650: val_loss -0.774 +2024-11-22 20:23:47.849769: Pseudo dice [0.8516] +2024-11-22 20:23:47.849887: Epoch time: 19.71 s +2024-11-22 20:23:49.021698: +2024-11-22 20:23:49.023247: Epoch 6045 +2024-11-22 20:23:49.023386: Current learning rate: 0.00281 +2024-11-22 20:24:09.068084: train_loss -0.794 +2024-11-22 20:24:09.074140: val_loss -0.7794 +2024-11-22 20:24:09.074287: Pseudo dice [0.856] +2024-11-22 20:24:09.074411: Epoch time: 20.05 s +2024-11-22 20:24:09.968585: +2024-11-22 20:24:09.969938: Epoch 6046 +2024-11-22 20:24:09.970115: Current learning rate: 0.00281 +2024-11-22 20:24:30.190211: train_loss -0.7917 +2024-11-22 20:24:30.197046: val_loss -0.7677 +2024-11-22 20:24:30.197204: Pseudo dice [0.856] +2024-11-22 20:24:30.197342: Epoch time: 20.22 s +2024-11-22 20:24:31.098991: +2024-11-22 20:24:31.099454: Epoch 6047 +2024-11-22 20:24:31.099592: Current learning rate: 0.00281 +2024-11-22 20:24:50.444302: train_loss -0.7989 +2024-11-22 20:24:50.464493: val_loss -0.762 +2024-11-22 20:24:50.464656: Pseudo dice [0.8493] +2024-11-22 20:24:50.464766: Epoch time: 19.35 s +2024-11-22 20:24:51.373348: +2024-11-22 20:24:51.374124: Epoch 6048 +2024-11-22 20:24:51.374250: Current learning rate: 0.00281 +2024-11-22 20:25:10.434958: train_loss -0.7986 +2024-11-22 20:25:10.439184: val_loss -0.765 +2024-11-22 20:25:10.439305: Pseudo dice [0.8531] +2024-11-22 20:25:10.439394: Epoch time: 19.06 s +2024-11-22 20:25:11.316732: +2024-11-22 20:25:11.318029: Epoch 6049 +2024-11-22 20:25:11.318166: Current learning rate: 0.00281 +2024-11-22 20:25:30.279223: train_loss -0.8033 +2024-11-22 20:25:30.283741: val_loss -0.7721 +2024-11-22 20:25:30.283862: Pseudo dice [0.849] +2024-11-22 20:25:30.283951: Epoch time: 18.96 s +2024-11-22 20:25:31.484591: +2024-11-22 20:25:31.486311: Epoch 6050 +2024-11-22 20:25:31.486453: Current learning rate: 0.00281 +2024-11-22 20:25:51.239114: train_loss -0.8058 +2024-11-22 20:25:51.255222: val_loss -0.7625 +2024-11-22 20:25:51.255400: Pseudo dice [0.8553] +2024-11-22 20:25:51.255521: Epoch time: 19.76 s +2024-11-22 20:25:52.337041: +2024-11-22 20:25:52.338935: Epoch 6051 +2024-11-22 20:25:52.339075: Current learning rate: 0.00281 +2024-11-22 20:26:11.129975: train_loss -0.811 +2024-11-22 20:26:11.137005: val_loss -0.7738 +2024-11-22 20:26:11.137150: Pseudo dice [0.8551] +2024-11-22 20:26:11.137244: Epoch time: 18.79 s +2024-11-22 20:26:12.046487: +2024-11-22 20:26:12.048153: Epoch 6052 +2024-11-22 20:26:12.048273: Current learning rate: 0.0028 +2024-11-22 20:26:30.963546: train_loss -0.8063 +2024-11-22 20:26:30.969979: val_loss -0.7743 +2024-11-22 20:26:30.970132: Pseudo dice [0.8582] +2024-11-22 20:26:30.970231: Epoch time: 18.92 s +2024-11-22 20:26:31.991251: +2024-11-22 20:26:31.991680: Epoch 6053 +2024-11-22 20:26:31.991800: Current learning rate: 0.0028 +2024-11-22 20:26:51.564489: train_loss -0.7975 +2024-11-22 20:26:51.571360: val_loss -0.7638 +2024-11-22 20:26:51.571489: Pseudo dice [0.8414] +2024-11-22 20:26:51.571602: Epoch time: 19.57 s +2024-11-22 20:26:52.502252: +2024-11-22 20:26:52.504294: Epoch 6054 +2024-11-22 20:26:52.504417: Current learning rate: 0.0028 +2024-11-22 20:27:11.873302: train_loss -0.7859 +2024-11-22 20:27:11.881419: val_loss -0.7487 +2024-11-22 20:27:11.881588: Pseudo dice [0.8442] +2024-11-22 20:27:11.881692: Epoch time: 19.37 s +2024-11-22 20:27:12.879433: +2024-11-22 20:27:12.881637: Epoch 6055 +2024-11-22 20:27:12.881776: Current learning rate: 0.0028 +2024-11-22 20:27:32.751785: train_loss -0.7971 +2024-11-22 20:27:32.756360: val_loss -0.7649 +2024-11-22 20:27:32.756500: Pseudo dice [0.8459] +2024-11-22 20:27:32.756603: Epoch time: 19.87 s +2024-11-22 20:27:33.665032: +2024-11-22 20:27:33.665807: Epoch 6056 +2024-11-22 20:27:33.665946: Current learning rate: 0.0028 +2024-11-22 20:27:52.679094: train_loss -0.7872 +2024-11-22 20:27:52.697136: val_loss -0.776 +2024-11-22 20:27:52.697280: Pseudo dice [0.8499] +2024-11-22 20:27:52.697396: Epoch time: 19.01 s +2024-11-22 20:27:53.774375: +2024-11-22 20:27:53.775873: Epoch 6057 +2024-11-22 20:27:53.776010: Current learning rate: 0.0028 +2024-11-22 20:28:12.562558: train_loss -0.7905 +2024-11-22 20:28:12.570657: val_loss -0.7639 +2024-11-22 20:28:12.570811: Pseudo dice [0.8595] +2024-11-22 20:28:12.570913: Epoch time: 18.79 s +2024-11-22 20:28:13.580047: +2024-11-22 20:28:13.581015: Epoch 6058 +2024-11-22 20:28:13.581145: Current learning rate: 0.0028 +2024-11-22 20:28:33.258135: train_loss -0.7937 +2024-11-22 20:28:33.266460: val_loss -0.7483 +2024-11-22 20:28:33.266590: Pseudo dice [0.8294] +2024-11-22 20:28:33.266714: Epoch time: 19.68 s +2024-11-22 20:28:34.273479: +2024-11-22 20:28:34.274246: Epoch 6059 +2024-11-22 20:28:34.274375: Current learning rate: 0.0028 +2024-11-22 20:28:53.079884: train_loss -0.7906 +2024-11-22 20:28:53.088191: val_loss -0.7694 +2024-11-22 20:28:53.088353: Pseudo dice [0.863] +2024-11-22 20:28:53.088514: Epoch time: 18.81 s +2024-11-22 20:28:54.177781: +2024-11-22 20:28:54.178620: Epoch 6060 +2024-11-22 20:28:54.178749: Current learning rate: 0.00279 +2024-11-22 20:29:12.466940: train_loss -0.7944 +2024-11-22 20:29:12.474017: val_loss -0.7832 +2024-11-22 20:29:12.474170: Pseudo dice [0.8593] +2024-11-22 20:29:12.474268: Epoch time: 18.29 s +2024-11-22 20:29:13.354340: +2024-11-22 20:29:13.355254: Epoch 6061 +2024-11-22 20:29:13.355389: Current learning rate: 0.00279 +2024-11-22 20:29:32.466561: train_loss -0.804 +2024-11-22 20:29:32.478065: val_loss -0.7525 +2024-11-22 20:29:32.478204: Pseudo dice [0.8542] +2024-11-22 20:29:32.478301: Epoch time: 19.11 s +2024-11-22 20:29:33.571792: +2024-11-22 20:29:33.573672: Epoch 6062 +2024-11-22 20:29:33.573792: Current learning rate: 0.00279 +2024-11-22 20:29:52.817731: train_loss -0.7966 +2024-11-22 20:29:52.824662: val_loss -0.7736 +2024-11-22 20:29:52.824813: Pseudo dice [0.849] +2024-11-22 20:29:52.824927: Epoch time: 19.25 s +2024-11-22 20:29:53.968858: +2024-11-22 20:29:53.970255: Epoch 6063 +2024-11-22 20:29:53.994439: Current learning rate: 0.00279 +2024-11-22 20:30:13.065606: train_loss -0.8022 +2024-11-22 20:30:13.071362: val_loss -0.7883 +2024-11-22 20:30:13.071518: Pseudo dice [0.8594] +2024-11-22 20:30:13.071628: Epoch time: 19.1 s +2024-11-22 20:30:13.974741: +2024-11-22 20:30:13.976891: Epoch 6064 +2024-11-22 20:30:13.977048: Current learning rate: 0.00279 +2024-11-22 20:30:32.474714: train_loss -0.8045 +2024-11-22 20:30:32.481906: val_loss -0.7984 +2024-11-22 20:30:32.482173: Pseudo dice [0.8468] +2024-11-22 20:30:32.482339: Epoch time: 18.5 s +2024-11-22 20:30:33.393789: +2024-11-22 20:30:33.394544: Epoch 6065 +2024-11-22 20:30:33.394672: Current learning rate: 0.00279 +2024-11-22 20:30:52.889631: train_loss -0.8039 +2024-11-22 20:30:52.895462: val_loss -0.774 +2024-11-22 20:30:52.895622: Pseudo dice [0.8492] +2024-11-22 20:30:52.895730: Epoch time: 19.5 s +2024-11-22 20:30:54.317422: +2024-11-22 20:30:54.318676: Epoch 6066 +2024-11-22 20:30:54.318799: Current learning rate: 0.00279 +2024-11-22 20:31:13.591629: train_loss -0.8023 +2024-11-22 20:31:13.610715: val_loss -0.7932 +2024-11-22 20:31:13.610933: Pseudo dice [0.8486] +2024-11-22 20:31:13.611053: Epoch time: 19.28 s +2024-11-22 20:31:14.521876: +2024-11-22 20:31:14.523546: Epoch 6067 +2024-11-22 20:31:14.523676: Current learning rate: 0.00279 +2024-11-22 20:31:34.290682: train_loss -0.8086 +2024-11-22 20:31:34.296618: val_loss -0.7738 +2024-11-22 20:31:34.296737: Pseudo dice [0.8623] +2024-11-22 20:31:34.296839: Epoch time: 19.77 s +2024-11-22 20:31:35.283625: +2024-11-22 20:31:35.284683: Epoch 6068 +2024-11-22 20:31:35.284803: Current learning rate: 0.00278 +2024-11-22 20:31:54.847053: train_loss -0.8072 +2024-11-22 20:31:54.851230: val_loss -0.7663 +2024-11-22 20:31:54.851367: Pseudo dice [0.8533] +2024-11-22 20:31:54.851451: Epoch time: 19.56 s +2024-11-22 20:31:55.772325: +2024-11-22 20:31:55.772539: Epoch 6069 +2024-11-22 20:31:55.772653: Current learning rate: 0.00278 +2024-11-22 20:32:14.435986: train_loss -0.8035 +2024-11-22 20:32:14.436498: val_loss -0.7671 +2024-11-22 20:32:14.436602: Pseudo dice [0.8543] +2024-11-22 20:32:14.436693: Epoch time: 18.66 s +2024-11-22 20:32:15.328602: +2024-11-22 20:32:15.328837: Epoch 6070 +2024-11-22 20:32:15.328964: Current learning rate: 0.00278 +2024-11-22 20:32:33.748188: train_loss -0.807 +2024-11-22 20:32:33.755635: val_loss -0.7852 +2024-11-22 20:32:33.755772: Pseudo dice [0.8761] +2024-11-22 20:32:33.755893: Epoch time: 18.42 s +2024-11-22 20:32:34.670290: +2024-11-22 20:32:34.670510: Epoch 6071 +2024-11-22 20:32:34.670632: Current learning rate: 0.00278 +2024-11-22 20:32:53.388616: train_loss -0.8013 +2024-11-22 20:32:53.395909: val_loss -0.7747 +2024-11-22 20:32:53.396067: Pseudo dice [0.8583] +2024-11-22 20:32:53.396153: Epoch time: 18.72 s +2024-11-22 20:32:54.298203: +2024-11-22 20:32:54.298414: Epoch 6072 +2024-11-22 20:32:54.298533: Current learning rate: 0.00278 +2024-11-22 20:33:13.003691: train_loss -0.8073 +2024-11-22 20:33:13.005476: val_loss -0.7675 +2024-11-22 20:33:13.005634: Pseudo dice [0.8412] +2024-11-22 20:33:13.005728: Epoch time: 18.71 s +2024-11-22 20:33:13.905169: +2024-11-22 20:33:13.905399: Epoch 6073 +2024-11-22 20:33:13.905526: Current learning rate: 0.00278 +2024-11-22 20:33:32.355548: train_loss -0.805 +2024-11-22 20:33:32.359489: val_loss -0.7996 +2024-11-22 20:33:32.359631: Pseudo dice [0.8652] +2024-11-22 20:33:32.359744: Epoch time: 18.45 s +2024-11-22 20:33:33.257521: +2024-11-22 20:33:33.257766: Epoch 6074 +2024-11-22 20:33:33.257921: Current learning rate: 0.00278 +2024-11-22 20:33:51.563879: train_loss -0.8104 +2024-11-22 20:33:51.569855: val_loss -0.7689 +2024-11-22 20:33:51.569996: Pseudo dice [0.8468] +2024-11-22 20:33:51.570104: Epoch time: 18.31 s +2024-11-22 20:33:52.474929: +2024-11-22 20:33:52.475141: Epoch 6075 +2024-11-22 20:33:52.475266: Current learning rate: 0.00277 +2024-11-22 20:34:11.442651: train_loss -0.7982 +2024-11-22 20:34:11.443567: val_loss -0.7644 +2024-11-22 20:34:11.443697: Pseudo dice [0.8605] +2024-11-22 20:34:11.443805: Epoch time: 18.97 s +2024-11-22 20:34:12.432684: +2024-11-22 20:34:12.432919: Epoch 6076 +2024-11-22 20:34:12.433040: Current learning rate: 0.00277 +2024-11-22 20:34:30.599188: train_loss -0.7986 +2024-11-22 20:34:30.604958: val_loss -0.789 +2024-11-22 20:34:30.605100: Pseudo dice [0.8455] +2024-11-22 20:34:30.605192: Epoch time: 18.17 s +2024-11-22 20:34:31.541538: +2024-11-22 20:34:31.541735: Epoch 6077 +2024-11-22 20:34:31.541867: Current learning rate: 0.00277 +2024-11-22 20:34:51.365580: train_loss -0.7956 +2024-11-22 20:34:51.373582: val_loss -0.7867 +2024-11-22 20:34:51.373721: Pseudo dice [0.8593] +2024-11-22 20:34:51.374786: Epoch time: 19.82 s +2024-11-22 20:34:52.247894: +2024-11-22 20:34:52.248345: Epoch 6078 +2024-11-22 20:34:52.248461: Current learning rate: 0.00277 +2024-11-22 20:35:11.580087: train_loss -0.8046 +2024-11-22 20:35:11.588125: val_loss -0.7776 +2024-11-22 20:35:11.588248: Pseudo dice [0.8456] +2024-11-22 20:35:11.588343: Epoch time: 19.33 s +2024-11-22 20:35:12.634571: +2024-11-22 20:35:12.635523: Epoch 6079 +2024-11-22 20:35:12.635659: Current learning rate: 0.00277 +2024-11-22 20:35:30.789337: train_loss -0.8022 +2024-11-22 20:35:30.799881: val_loss -0.7777 +2024-11-22 20:35:30.800057: Pseudo dice [0.8542] +2024-11-22 20:35:30.800168: Epoch time: 18.16 s +2024-11-22 20:35:31.689830: +2024-11-22 20:35:31.690665: Epoch 6080 +2024-11-22 20:35:31.690801: Current learning rate: 0.00277 +2024-11-22 20:35:52.475780: train_loss -0.7997 +2024-11-22 20:35:52.488751: val_loss -0.7731 +2024-11-22 20:35:52.488878: Pseudo dice [0.8575] +2024-11-22 20:35:52.488982: Epoch time: 20.79 s +2024-11-22 20:35:53.436441: +2024-11-22 20:35:53.437773: Epoch 6081 +2024-11-22 20:35:53.437891: Current learning rate: 0.00277 +2024-11-22 20:36:12.740348: train_loss -0.8002 +2024-11-22 20:36:12.743110: val_loss -0.7369 +2024-11-22 20:36:12.743231: Pseudo dice [0.8522] +2024-11-22 20:36:12.743334: Epoch time: 19.3 s +2024-11-22 20:36:13.748532: +2024-11-22 20:36:13.750121: Epoch 6082 +2024-11-22 20:36:13.750248: Current learning rate: 0.00277 +2024-11-22 20:36:34.329420: train_loss -0.7926 +2024-11-22 20:36:34.332655: val_loss -0.7544 +2024-11-22 20:36:34.332794: Pseudo dice [0.8424] +2024-11-22 20:36:34.332888: Epoch time: 20.58 s +2024-11-22 20:36:35.597378: +2024-11-22 20:36:35.598722: Epoch 6083 +2024-11-22 20:36:35.598851: Current learning rate: 0.00276 +2024-11-22 20:36:55.732214: train_loss -0.7917 +2024-11-22 20:36:55.740356: val_loss -0.7815 +2024-11-22 20:36:55.740495: Pseudo dice [0.8559] +2024-11-22 20:36:55.740575: Epoch time: 20.14 s +2024-11-22 20:36:56.659643: +2024-11-22 20:36:56.660649: Epoch 6084 +2024-11-22 20:36:56.660770: Current learning rate: 0.00276 +2024-11-22 20:37:16.710116: train_loss -0.8002 +2024-11-22 20:37:16.715106: val_loss -0.7629 +2024-11-22 20:37:16.715238: Pseudo dice [0.856] +2024-11-22 20:37:16.715319: Epoch time: 20.05 s +2024-11-22 20:37:17.781441: +2024-11-22 20:37:17.781919: Epoch 6085 +2024-11-22 20:37:17.782056: Current learning rate: 0.00276 +2024-11-22 20:37:37.192137: train_loss -0.7882 +2024-11-22 20:37:37.219793: val_loss -0.7585 +2024-11-22 20:37:37.219994: Pseudo dice [0.85] +2024-11-22 20:37:37.220130: Epoch time: 19.41 s +2024-11-22 20:37:38.197900: +2024-11-22 20:37:38.199543: Epoch 6086 +2024-11-22 20:37:38.199670: Current learning rate: 0.00276 +2024-11-22 20:37:59.099380: train_loss -0.8049 +2024-11-22 20:37:59.108880: val_loss -0.7799 +2024-11-22 20:37:59.109040: Pseudo dice [0.8604] +2024-11-22 20:37:59.109139: Epoch time: 20.9 s +2024-11-22 20:37:59.993803: +2024-11-22 20:37:59.995413: Epoch 6087 +2024-11-22 20:37:59.995532: Current learning rate: 0.00276 +2024-11-22 20:38:19.901941: train_loss -0.8007 +2024-11-22 20:38:19.908449: val_loss -0.7578 +2024-11-22 20:38:19.908604: Pseudo dice [0.8461] +2024-11-22 20:38:19.908710: Epoch time: 19.91 s +2024-11-22 20:38:20.802189: +2024-11-22 20:38:20.803339: Epoch 6088 +2024-11-22 20:38:20.803466: Current learning rate: 0.00276 +2024-11-22 20:38:39.554554: train_loss -0.8047 +2024-11-22 20:38:39.560126: val_loss -0.778 +2024-11-22 20:38:39.560467: Pseudo dice [0.8553] +2024-11-22 20:38:39.560585: Epoch time: 18.75 s +2024-11-22 20:38:40.898738: +2024-11-22 20:38:40.900252: Epoch 6089 +2024-11-22 20:38:40.900389: Current learning rate: 0.00276 +2024-11-22 20:39:00.051727: train_loss -0.7977 +2024-11-22 20:39:00.054757: val_loss -0.7673 +2024-11-22 20:39:00.054894: Pseudo dice [0.8498] +2024-11-22 20:39:00.055009: Epoch time: 19.15 s +2024-11-22 20:39:01.096404: +2024-11-22 20:39:01.098120: Epoch 6090 +2024-11-22 20:39:01.098251: Current learning rate: 0.00276 +2024-11-22 20:39:20.649377: train_loss -0.7951 +2024-11-22 20:39:20.663404: val_loss -0.7916 +2024-11-22 20:39:20.663534: Pseudo dice [0.8513] +2024-11-22 20:39:20.663629: Epoch time: 19.55 s +2024-11-22 20:39:21.737919: +2024-11-22 20:39:21.739524: Epoch 6091 +2024-11-22 20:39:21.739649: Current learning rate: 0.00275 +2024-11-22 20:39:40.267092: train_loss -0.7972 +2024-11-22 20:39:40.282662: val_loss -0.7603 +2024-11-22 20:39:40.282806: Pseudo dice [0.8542] +2024-11-22 20:39:40.282932: Epoch time: 18.53 s +2024-11-22 20:39:41.363091: +2024-11-22 20:39:41.364389: Epoch 6092 +2024-11-22 20:39:41.364516: Current learning rate: 0.00275 +2024-11-22 20:40:00.541437: train_loss -0.8046 +2024-11-22 20:40:00.548752: val_loss -0.7613 +2024-11-22 20:40:00.548901: Pseudo dice [0.8513] +2024-11-22 20:40:00.548999: Epoch time: 19.18 s +2024-11-22 20:40:01.451154: +2024-11-22 20:40:01.453472: Epoch 6093 +2024-11-22 20:40:01.453612: Current learning rate: 0.00275 +2024-11-22 20:40:19.626994: train_loss -0.7991 +2024-11-22 20:40:19.639008: val_loss -0.7764 +2024-11-22 20:40:19.639179: Pseudo dice [0.8608] +2024-11-22 20:40:19.639295: Epoch time: 18.18 s +2024-11-22 20:40:20.657147: +2024-11-22 20:40:20.659269: Epoch 6094 +2024-11-22 20:40:20.659433: Current learning rate: 0.00275 +2024-11-22 20:40:40.209023: train_loss -0.8052 +2024-11-22 20:40:40.211284: val_loss -0.7899 +2024-11-22 20:40:40.211418: Pseudo dice [0.8657] +2024-11-22 20:40:40.211502: Epoch time: 19.55 s +2024-11-22 20:40:41.434640: +2024-11-22 20:40:41.436405: Epoch 6095 +2024-11-22 20:40:41.436531: Current learning rate: 0.00275 +2024-11-22 20:40:59.856138: train_loss -0.8066 +2024-11-22 20:40:59.862103: val_loss -0.7835 +2024-11-22 20:40:59.862236: Pseudo dice [0.859] +2024-11-22 20:40:59.862349: Epoch time: 18.42 s +2024-11-22 20:41:00.965572: +2024-11-22 20:41:00.966903: Epoch 6096 +2024-11-22 20:41:00.967034: Current learning rate: 0.00275 +2024-11-22 20:41:21.254786: train_loss -0.8089 +2024-11-22 20:41:21.260884: val_loss -0.7858 +2024-11-22 20:41:21.261009: Pseudo dice [0.8731] +2024-11-22 20:41:21.261106: Epoch time: 20.29 s +2024-11-22 20:41:22.163155: +2024-11-22 20:41:22.163933: Epoch 6097 +2024-11-22 20:41:22.164070: Current learning rate: 0.00275 +2024-11-22 20:41:41.089488: train_loss -0.8177 +2024-11-22 20:41:41.098157: val_loss -0.7836 +2024-11-22 20:41:41.098284: Pseudo dice [0.8445] +2024-11-22 20:41:41.098394: Epoch time: 18.93 s +2024-11-22 20:41:42.083616: +2024-11-22 20:41:42.084389: Epoch 6098 +2024-11-22 20:41:42.084508: Current learning rate: 0.00274 +2024-11-22 20:42:01.660737: train_loss -0.7971 +2024-11-22 20:42:01.668211: val_loss -0.754 +2024-11-22 20:42:01.668353: Pseudo dice [0.8482] +2024-11-22 20:42:01.668467: Epoch time: 19.58 s +2024-11-22 20:42:02.587642: +2024-11-22 20:42:02.589577: Epoch 6099 +2024-11-22 20:42:02.589715: Current learning rate: 0.00274 +2024-11-22 20:42:22.937223: train_loss -0.7963 +2024-11-22 20:42:22.958056: val_loss -0.7915 +2024-11-22 20:42:22.958251: Pseudo dice [0.8559] +2024-11-22 20:42:22.958375: Epoch time: 20.35 s +2024-11-22 20:42:24.664861: +2024-11-22 20:42:24.666124: Epoch 6100 +2024-11-22 20:42:24.666275: Current learning rate: 0.00274 +2024-11-22 20:42:43.189829: train_loss -0.8021 +2024-11-22 20:42:43.198197: val_loss -0.7671 +2024-11-22 20:42:43.198344: Pseudo dice [0.8545] +2024-11-22 20:42:43.198437: Epoch time: 18.53 s +2024-11-22 20:42:44.244885: +2024-11-22 20:42:44.245389: Epoch 6101 +2024-11-22 20:42:44.245520: Current learning rate: 0.00274 +2024-11-22 20:43:04.233881: train_loss -0.7985 +2024-11-22 20:43:04.252662: val_loss -0.7751 +2024-11-22 20:43:04.252847: Pseudo dice [0.8544] +2024-11-22 20:43:04.252973: Epoch time: 19.99 s +2024-11-22 20:43:05.284908: +2024-11-22 20:43:05.286224: Epoch 6102 +2024-11-22 20:43:05.286369: Current learning rate: 0.00274 +2024-11-22 20:43:24.026887: train_loss -0.8001 +2024-11-22 20:43:24.028899: val_loss -0.7743 +2024-11-22 20:43:24.029008: Pseudo dice [0.8489] +2024-11-22 20:43:24.029100: Epoch time: 18.74 s +2024-11-22 20:43:25.073468: +2024-11-22 20:43:25.074538: Epoch 6103 +2024-11-22 20:43:25.074670: Current learning rate: 0.00274 +2024-11-22 20:43:44.753424: train_loss -0.8038 +2024-11-22 20:43:44.758847: val_loss -0.7678 +2024-11-22 20:43:44.758991: Pseudo dice [0.8598] +2024-11-22 20:43:44.759103: Epoch time: 19.68 s +2024-11-22 20:43:45.713510: +2024-11-22 20:43:45.713729: Epoch 6104 +2024-11-22 20:43:45.713848: Current learning rate: 0.00274 +2024-11-22 20:44:04.250565: train_loss -0.8043 +2024-11-22 20:44:04.256951: val_loss -0.7874 +2024-11-22 20:44:04.257098: Pseudo dice [0.8518] +2024-11-22 20:44:04.257185: Epoch time: 18.54 s +2024-11-22 20:44:05.216513: +2024-11-22 20:44:05.217916: Epoch 6105 +2024-11-22 20:44:05.218068: Current learning rate: 0.00274 +2024-11-22 20:44:25.831851: train_loss -0.8035 +2024-11-22 20:44:25.835892: val_loss -0.7841 +2024-11-22 20:44:25.836072: Pseudo dice [0.8555] +2024-11-22 20:44:25.836239: Epoch time: 20.62 s +2024-11-22 20:44:26.745288: +2024-11-22 20:44:26.746510: Epoch 6106 +2024-11-22 20:44:26.746642: Current learning rate: 0.00273 +2024-11-22 20:44:45.552808: train_loss -0.8122 +2024-11-22 20:44:45.565383: val_loss -0.7916 +2024-11-22 20:44:45.565536: Pseudo dice [0.8565] +2024-11-22 20:44:45.565649: Epoch time: 18.81 s +2024-11-22 20:44:46.527383: +2024-11-22 20:44:46.527834: Epoch 6107 +2024-11-22 20:44:46.527966: Current learning rate: 0.00273 +2024-11-22 20:45:05.599891: train_loss -0.8143 +2024-11-22 20:45:05.608237: val_loss -0.7937 +2024-11-22 20:45:05.608388: Pseudo dice [0.8607] +2024-11-22 20:45:05.608487: Epoch time: 19.07 s +2024-11-22 20:45:06.621104: +2024-11-22 20:45:06.621600: Epoch 6108 +2024-11-22 20:45:06.621752: Current learning rate: 0.00273 +2024-11-22 20:45:25.933969: train_loss -0.806 +2024-11-22 20:45:25.938232: val_loss -0.784 +2024-11-22 20:45:25.938362: Pseudo dice [0.8587] +2024-11-22 20:45:25.938459: Epoch time: 19.31 s +2024-11-22 20:45:27.009648: +2024-11-22 20:45:27.011657: Epoch 6109 +2024-11-22 20:45:27.011789: Current learning rate: 0.00273 +2024-11-22 20:45:46.570960: train_loss -0.8046 +2024-11-22 20:45:46.577194: val_loss -0.7768 +2024-11-22 20:45:46.577348: Pseudo dice [0.8556] +2024-11-22 20:45:46.577458: Epoch time: 19.56 s +2024-11-22 20:45:47.577433: +2024-11-22 20:45:47.577926: Epoch 6110 +2024-11-22 20:45:47.578042: Current learning rate: 0.00273 +2024-11-22 20:46:06.995031: train_loss -0.7963 +2024-11-22 20:46:06.997057: val_loss -0.7864 +2024-11-22 20:46:06.997219: Pseudo dice [0.8518] +2024-11-22 20:46:06.997326: Epoch time: 19.42 s +2024-11-22 20:46:07.916388: +2024-11-22 20:46:07.917825: Epoch 6111 +2024-11-22 20:46:07.917949: Current learning rate: 0.00273 +2024-11-22 20:46:26.856695: train_loss -0.8006 +2024-11-22 20:46:26.861074: val_loss -0.7815 +2024-11-22 20:46:26.861190: Pseudo dice [0.8652] +2024-11-22 20:46:26.861279: Epoch time: 18.94 s +2024-11-22 20:46:27.861206: +2024-11-22 20:46:27.862479: Epoch 6112 +2024-11-22 20:46:27.862620: Current learning rate: 0.00273 +2024-11-22 20:46:48.527315: train_loss -0.8059 +2024-11-22 20:46:48.533428: val_loss -0.7643 +2024-11-22 20:46:48.533554: Pseudo dice [0.8445] +2024-11-22 20:46:48.533654: Epoch time: 20.67 s +2024-11-22 20:46:49.549238: +2024-11-22 20:46:49.551077: Epoch 6113 +2024-11-22 20:46:49.551198: Current learning rate: 0.00273 +2024-11-22 20:47:09.448631: train_loss -0.8016 +2024-11-22 20:47:09.459450: val_loss -0.7667 +2024-11-22 20:47:09.459689: Pseudo dice [0.855] +2024-11-22 20:47:09.459812: Epoch time: 19.9 s +2024-11-22 20:47:10.340418: +2024-11-22 20:47:10.340886: Epoch 6114 +2024-11-22 20:47:10.341071: Current learning rate: 0.00272 +2024-11-22 20:47:29.462923: train_loss -0.8168 +2024-11-22 20:47:29.469902: val_loss -0.7705 +2024-11-22 20:47:29.470047: Pseudo dice [0.8447] +2024-11-22 20:47:29.470155: Epoch time: 19.12 s +2024-11-22 20:47:30.550328: +2024-11-22 20:47:30.551002: Epoch 6115 +2024-11-22 20:47:30.551137: Current learning rate: 0.00272 +2024-11-22 20:47:51.043292: train_loss -0.8095 +2024-11-22 20:47:51.045714: val_loss -0.7723 +2024-11-22 20:47:51.045832: Pseudo dice [0.8591] +2024-11-22 20:47:51.045939: Epoch time: 20.49 s +2024-11-22 20:47:52.017777: +2024-11-22 20:47:52.019027: Epoch 6116 +2024-11-22 20:47:52.019152: Current learning rate: 0.00272 +2024-11-22 20:48:12.307539: train_loss -0.8041 +2024-11-22 20:48:12.318426: val_loss -0.7838 +2024-11-22 20:48:12.318600: Pseudo dice [0.8599] +2024-11-22 20:48:12.318710: Epoch time: 20.29 s +2024-11-22 20:48:13.304506: +2024-11-22 20:48:13.306012: Epoch 6117 +2024-11-22 20:48:13.306140: Current learning rate: 0.00272 +2024-11-22 20:48:32.929106: train_loss -0.8024 +2024-11-22 20:48:32.950383: val_loss -0.7842 +2024-11-22 20:48:32.950556: Pseudo dice [0.8486] +2024-11-22 20:48:32.950666: Epoch time: 19.63 s +2024-11-22 20:48:33.967216: +2024-11-22 20:48:33.969289: Epoch 6118 +2024-11-22 20:48:33.969476: Current learning rate: 0.00272 +2024-11-22 20:48:52.920495: train_loss -0.8061 +2024-11-22 20:48:52.924678: val_loss -0.7915 +2024-11-22 20:48:52.924817: Pseudo dice [0.8616] +2024-11-22 20:48:52.924938: Epoch time: 18.95 s +2024-11-22 20:48:53.829283: +2024-11-22 20:48:53.830119: Epoch 6119 +2024-11-22 20:48:53.830237: Current learning rate: 0.00272 +2024-11-22 20:49:13.480201: train_loss -0.8061 +2024-11-22 20:49:13.482365: val_loss -0.8021 +2024-11-22 20:49:13.482485: Pseudo dice [0.8747] +2024-11-22 20:49:13.482578: Epoch time: 19.65 s +2024-11-22 20:49:14.589013: +2024-11-22 20:49:14.590705: Epoch 6120 +2024-11-22 20:49:14.590827: Current learning rate: 0.00272 +2024-11-22 20:49:34.003556: train_loss -0.8045 +2024-11-22 20:49:34.022196: val_loss -0.7845 +2024-11-22 20:49:34.022336: Pseudo dice [0.8654] +2024-11-22 20:49:34.022430: Epoch time: 19.42 s +2024-11-22 20:49:34.984510: +2024-11-22 20:49:34.985886: Epoch 6121 +2024-11-22 20:49:34.986026: Current learning rate: 0.00271 +2024-11-22 20:49:53.170884: train_loss -0.8045 +2024-11-22 20:49:53.179884: val_loss -0.7838 +2024-11-22 20:49:53.180042: Pseudo dice [0.8621] +2024-11-22 20:49:53.180337: Epoch time: 18.19 s +2024-11-22 20:49:54.424401: +2024-11-22 20:49:54.426061: Epoch 6122 +2024-11-22 20:49:54.426193: Current learning rate: 0.00271 +2024-11-22 20:50:13.956962: train_loss -0.8064 +2024-11-22 20:50:13.960991: val_loss -0.7785 +2024-11-22 20:50:13.961145: Pseudo dice [0.8575] +2024-11-22 20:50:13.961246: Epoch time: 19.53 s +2024-11-22 20:50:15.324479: +2024-11-22 20:50:15.326282: Epoch 6123 +2024-11-22 20:50:15.326418: Current learning rate: 0.00271 +2024-11-22 20:50:34.863230: train_loss -0.8064 +2024-11-22 20:50:34.871027: val_loss -0.7574 +2024-11-22 20:50:34.871187: Pseudo dice [0.8684] +2024-11-22 20:50:34.871294: Epoch time: 19.54 s +2024-11-22 20:50:35.857489: +2024-11-22 20:50:35.859256: Epoch 6124 +2024-11-22 20:50:35.859389: Current learning rate: 0.00271 +2024-11-22 20:50:55.811990: train_loss -0.8113 +2024-11-22 20:50:55.814366: val_loss -0.7737 +2024-11-22 20:50:55.814505: Pseudo dice [0.8507] +2024-11-22 20:50:55.814598: Epoch time: 19.96 s +2024-11-22 20:50:56.692084: +2024-11-22 20:50:56.693354: Epoch 6125 +2024-11-22 20:50:56.693493: Current learning rate: 0.00271 +2024-11-22 20:51:16.623227: train_loss -0.8075 +2024-11-22 20:51:16.630550: val_loss -0.7792 +2024-11-22 20:51:16.630689: Pseudo dice [0.8683] +2024-11-22 20:51:16.630894: Epoch time: 19.93 s +2024-11-22 20:51:17.662292: +2024-11-22 20:51:17.663347: Epoch 6126 +2024-11-22 20:51:17.663468: Current learning rate: 0.00271 +2024-11-22 20:51:36.713727: train_loss -0.8013 +2024-11-22 20:51:36.719970: val_loss -0.7861 +2024-11-22 20:51:36.720445: Pseudo dice [0.8658] +2024-11-22 20:51:36.720573: Epoch time: 19.05 s +2024-11-22 20:51:37.744053: +2024-11-22 20:51:37.745822: Epoch 6127 +2024-11-22 20:51:37.745965: Current learning rate: 0.00271 +2024-11-22 20:51:57.276256: train_loss -0.8118 +2024-11-22 20:51:57.284303: val_loss -0.7924 +2024-11-22 20:51:57.284427: Pseudo dice [0.8634] +2024-11-22 20:51:57.284523: Epoch time: 19.53 s +2024-11-22 20:51:58.392556: +2024-11-22 20:51:58.394188: Epoch 6128 +2024-11-22 20:51:58.394339: Current learning rate: 0.00271 +2024-11-22 20:52:17.950263: train_loss -0.804 +2024-11-22 20:52:17.956998: val_loss -0.7643 +2024-11-22 20:52:17.957133: Pseudo dice [0.8511] +2024-11-22 20:52:17.957216: Epoch time: 19.56 s +2024-11-22 20:52:18.864847: +2024-11-22 20:52:18.865571: Epoch 6129 +2024-11-22 20:52:18.865698: Current learning rate: 0.0027 +2024-11-22 20:52:38.010235: train_loss -0.8006 +2024-11-22 20:52:38.016243: val_loss -0.7885 +2024-11-22 20:52:38.016374: Pseudo dice [0.8678] +2024-11-22 20:52:38.016464: Epoch time: 19.15 s +2024-11-22 20:52:39.091221: +2024-11-22 20:52:39.094429: Epoch 6130 +2024-11-22 20:52:39.094563: Current learning rate: 0.0027 +2024-11-22 20:52:58.134044: train_loss -0.8057 +2024-11-22 20:52:58.152832: val_loss -0.7624 +2024-11-22 20:52:58.152994: Pseudo dice [0.8471] +2024-11-22 20:52:58.153130: Epoch time: 19.04 s +2024-11-22 20:52:59.027533: +2024-11-22 20:52:59.029277: Epoch 6131 +2024-11-22 20:52:59.029421: Current learning rate: 0.0027 +2024-11-22 20:53:18.322884: train_loss -0.8123 +2024-11-22 20:53:18.327932: val_loss -0.77 +2024-11-22 20:53:18.328132: Pseudo dice [0.852] +2024-11-22 20:53:18.328262: Epoch time: 19.3 s +2024-11-22 20:53:19.202945: +2024-11-22 20:53:19.204198: Epoch 6132 +2024-11-22 20:53:19.204329: Current learning rate: 0.0027 +2024-11-22 20:53:37.988876: train_loss -0.8079 +2024-11-22 20:53:37.990816: val_loss -0.7675 +2024-11-22 20:53:37.990946: Pseudo dice [0.8446] +2024-11-22 20:53:37.991047: Epoch time: 18.79 s +2024-11-22 20:53:38.925283: +2024-11-22 20:53:38.926503: Epoch 6133 +2024-11-22 20:53:38.926653: Current learning rate: 0.0027 +2024-11-22 20:53:58.525150: train_loss -0.7989 +2024-11-22 20:53:58.533935: val_loss -0.7643 +2024-11-22 20:53:58.534140: Pseudo dice [0.8573] +2024-11-22 20:53:58.534246: Epoch time: 19.6 s +2024-11-22 20:53:59.900595: +2024-11-22 20:53:59.901886: Epoch 6134 +2024-11-22 20:53:59.902014: Current learning rate: 0.0027 +2024-11-22 20:54:19.324064: train_loss -0.8081 +2024-11-22 20:54:19.331587: val_loss -0.7734 +2024-11-22 20:54:19.331774: Pseudo dice [0.842] +2024-11-22 20:54:19.331898: Epoch time: 19.42 s +2024-11-22 20:54:20.257167: +2024-11-22 20:54:20.257793: Epoch 6135 +2024-11-22 20:54:20.257948: Current learning rate: 0.0027 +2024-11-22 20:54:39.116763: train_loss -0.8054 +2024-11-22 20:54:39.118884: val_loss -0.7954 +2024-11-22 20:54:39.119004: Pseudo dice [0.8622] +2024-11-22 20:54:39.119173: Epoch time: 18.86 s +2024-11-22 20:54:39.995941: +2024-11-22 20:54:39.997401: Epoch 6136 +2024-11-22 20:54:39.997535: Current learning rate: 0.0027 +2024-11-22 20:54:59.459685: train_loss -0.8049 +2024-11-22 20:54:59.472733: val_loss -0.7798 +2024-11-22 20:54:59.472875: Pseudo dice [0.8667] +2024-11-22 20:54:59.472973: Epoch time: 19.46 s +2024-11-22 20:55:00.532158: +2024-11-22 20:55:00.534115: Epoch 6137 +2024-11-22 20:55:00.534268: Current learning rate: 0.00269 +2024-11-22 20:55:18.909034: train_loss -0.801 +2024-11-22 20:55:18.923616: val_loss -0.7755 +2024-11-22 20:55:18.923798: Pseudo dice [0.8613] +2024-11-22 20:55:18.923910: Epoch time: 18.38 s +2024-11-22 20:55:19.889213: +2024-11-22 20:55:19.890530: Epoch 6138 +2024-11-22 20:55:19.890692: Current learning rate: 0.00269 +2024-11-22 20:55:39.308635: train_loss -0.7896 +2024-11-22 20:55:39.313557: val_loss -0.7707 +2024-11-22 20:55:39.313695: Pseudo dice [0.8668] +2024-11-22 20:55:39.313804: Epoch time: 19.42 s +2024-11-22 20:55:40.295914: +2024-11-22 20:55:40.297277: Epoch 6139 +2024-11-22 20:55:40.297429: Current learning rate: 0.00269 +2024-11-22 20:55:59.472414: train_loss -0.798 +2024-11-22 20:55:59.475486: val_loss -0.7815 +2024-11-22 20:55:59.481142: Pseudo dice [0.8571] +2024-11-22 20:55:59.481248: Epoch time: 19.18 s +2024-11-22 20:56:00.462727: +2024-11-22 20:56:00.463157: Epoch 6140 +2024-11-22 20:56:00.463294: Current learning rate: 0.00269 +2024-11-22 20:56:18.682517: train_loss -0.8036 +2024-11-22 20:56:18.688856: val_loss -0.7771 +2024-11-22 20:56:18.688982: Pseudo dice [0.8591] +2024-11-22 20:56:18.689075: Epoch time: 18.22 s +2024-11-22 20:56:19.564470: +2024-11-22 20:56:19.564887: Epoch 6141 +2024-11-22 20:56:19.565024: Current learning rate: 0.00269 +2024-11-22 20:56:38.293684: train_loss -0.7916 +2024-11-22 20:56:38.297150: val_loss -0.7467 +2024-11-22 20:56:38.297285: Pseudo dice [0.8414] +2024-11-22 20:56:38.297390: Epoch time: 18.73 s +2024-11-22 20:56:39.199471: +2024-11-22 20:56:39.199909: Epoch 6142 +2024-11-22 20:56:39.200069: Current learning rate: 0.00269 +2024-11-22 20:56:58.346426: train_loss -0.7909 +2024-11-22 20:56:58.347448: val_loss -0.7924 +2024-11-22 20:56:58.347570: Pseudo dice [0.8485] +2024-11-22 20:56:58.347676: Epoch time: 19.15 s +2024-11-22 20:56:59.235484: +2024-11-22 20:56:59.235919: Epoch 6143 +2024-11-22 20:56:59.236072: Current learning rate: 0.00269 +2024-11-22 20:57:17.978405: train_loss -0.8 +2024-11-22 20:57:17.981347: val_loss -0.7862 +2024-11-22 20:57:17.981479: Pseudo dice [0.8554] +2024-11-22 20:57:17.981577: Epoch time: 18.74 s +2024-11-22 20:57:18.915281: +2024-11-22 20:57:18.915725: Epoch 6144 +2024-11-22 20:57:18.915874: Current learning rate: 0.00268 +2024-11-22 20:57:37.534895: train_loss -0.804 +2024-11-22 20:57:37.537606: val_loss -0.7518 +2024-11-22 20:57:37.537730: Pseudo dice [0.8337] +2024-11-22 20:57:37.537833: Epoch time: 18.62 s +2024-11-22 20:57:38.540212: +2024-11-22 20:57:38.540411: Epoch 6145 +2024-11-22 20:57:38.540540: Current learning rate: 0.00268 +2024-11-22 20:57:56.795095: train_loss -0.7893 +2024-11-22 20:57:56.808894: val_loss -0.7904 +2024-11-22 20:57:56.809043: Pseudo dice [0.8668] +2024-11-22 20:57:56.809156: Epoch time: 18.26 s +2024-11-22 20:57:58.123192: +2024-11-22 20:57:58.123405: Epoch 6146 +2024-11-22 20:57:58.123531: Current learning rate: 0.00268 +2024-11-22 20:58:17.100538: train_loss -0.7986 +2024-11-22 20:58:17.103155: val_loss -0.7649 +2024-11-22 20:58:17.103297: Pseudo dice [0.8487] +2024-11-22 20:58:17.103388: Epoch time: 18.98 s +2024-11-22 20:58:18.140743: +2024-11-22 20:58:18.140991: Epoch 6147 +2024-11-22 20:58:18.141114: Current learning rate: 0.00268 +2024-11-22 20:58:37.801319: train_loss -0.7984 +2024-11-22 20:58:37.808510: val_loss -0.7853 +2024-11-22 20:58:37.808647: Pseudo dice [0.8643] +2024-11-22 20:58:37.808823: Epoch time: 19.66 s +2024-11-22 20:58:38.704202: +2024-11-22 20:58:38.704409: Epoch 6148 +2024-11-22 20:58:38.704540: Current learning rate: 0.00268 +2024-11-22 20:58:58.454213: train_loss -0.7913 +2024-11-22 20:58:58.456553: val_loss -0.7568 +2024-11-22 20:58:58.456659: Pseudo dice [0.8542] +2024-11-22 20:58:58.456771: Epoch time: 19.75 s +2024-11-22 20:58:59.346224: +2024-11-22 20:58:59.347224: Epoch 6149 +2024-11-22 20:58:59.347360: Current learning rate: 0.00268 +2024-11-22 20:59:18.935342: train_loss -0.8097 +2024-11-22 20:59:18.947922: val_loss -0.782 +2024-11-22 20:59:18.948077: Pseudo dice [0.8591] +2024-11-22 20:59:18.948188: Epoch time: 19.59 s +2024-11-22 20:59:20.162592: +2024-11-22 20:59:20.164082: Epoch 6150 +2024-11-22 20:59:20.164209: Current learning rate: 0.00268 +2024-11-22 20:59:40.240511: train_loss -0.806 +2024-11-22 20:59:40.246744: val_loss -0.7804 +2024-11-22 20:59:40.246881: Pseudo dice [0.8563] +2024-11-22 20:59:40.247057: Epoch time: 20.08 s +2024-11-22 20:59:41.277494: +2024-11-22 20:59:41.278255: Epoch 6151 +2024-11-22 20:59:41.278385: Current learning rate: 0.00268 +2024-11-22 21:00:00.511081: train_loss -0.8028 +2024-11-22 21:00:00.519368: val_loss -0.7693 +2024-11-22 21:00:00.519494: Pseudo dice [0.8494] +2024-11-22 21:00:00.519591: Epoch time: 19.23 s +2024-11-22 21:00:01.465698: +2024-11-22 21:00:01.467108: Epoch 6152 +2024-11-22 21:00:01.481534: Current learning rate: 0.00267 +2024-11-22 21:00:21.390141: train_loss -0.8024 +2024-11-22 21:00:21.402208: val_loss -0.8028 +2024-11-22 21:00:21.402337: Pseudo dice [0.871] +2024-11-22 21:00:21.402429: Epoch time: 19.93 s +2024-11-22 21:00:22.435107: +2024-11-22 21:00:22.436375: Epoch 6153 +2024-11-22 21:00:22.436498: Current learning rate: 0.00267 +2024-11-22 21:00:42.712093: train_loss -0.8094 +2024-11-22 21:00:42.730554: val_loss -0.7621 +2024-11-22 21:00:42.730878: Pseudo dice [0.8663] +2024-11-22 21:00:42.731011: Epoch time: 20.28 s +2024-11-22 21:00:43.675999: +2024-11-22 21:00:43.678000: Epoch 6154 +2024-11-22 21:00:43.678144: Current learning rate: 0.00267 +2024-11-22 21:01:03.471890: train_loss -0.8133 +2024-11-22 21:01:03.482484: val_loss -0.7913 +2024-11-22 21:01:03.482652: Pseudo dice [0.8669] +2024-11-22 21:01:03.482763: Epoch time: 19.8 s +2024-11-22 21:01:04.452836: +2024-11-22 21:01:04.454410: Epoch 6155 +2024-11-22 21:01:04.454537: Current learning rate: 0.00267 +2024-11-22 21:01:24.023750: train_loss -0.8077 +2024-11-22 21:01:24.031072: val_loss -0.7923 +2024-11-22 21:01:24.031215: Pseudo dice [0.8683] +2024-11-22 21:01:24.031303: Epoch time: 19.57 s +2024-11-22 21:01:24.955219: +2024-11-22 21:01:24.955739: Epoch 6156 +2024-11-22 21:01:24.955863: Current learning rate: 0.00267 +2024-11-22 21:01:44.882219: train_loss -0.8115 +2024-11-22 21:01:44.885329: val_loss -0.7797 +2024-11-22 21:01:44.885448: Pseudo dice [0.8554] +2024-11-22 21:01:44.885542: Epoch time: 19.93 s +2024-11-22 21:01:46.278663: +2024-11-22 21:01:46.279606: Epoch 6157 +2024-11-22 21:01:46.279745: Current learning rate: 0.00267 +2024-11-22 21:02:06.795608: train_loss -0.8055 +2024-11-22 21:02:06.807259: val_loss -0.7803 +2024-11-22 21:02:06.807402: Pseudo dice [0.8634] +2024-11-22 21:02:06.807514: Epoch time: 20.52 s +2024-11-22 21:02:08.268543: +2024-11-22 21:02:08.269842: Epoch 6158 +2024-11-22 21:02:08.269971: Current learning rate: 0.00267 +2024-11-22 21:02:27.781970: train_loss -0.8089 +2024-11-22 21:02:27.790266: val_loss -0.7662 +2024-11-22 21:02:27.790403: Pseudo dice [0.8536] +2024-11-22 21:02:27.790501: Epoch time: 19.51 s +2024-11-22 21:02:28.687760: +2024-11-22 21:02:28.689328: Epoch 6159 +2024-11-22 21:02:28.689444: Current learning rate: 0.00267 +2024-11-22 21:02:47.308825: train_loss -0.8099 +2024-11-22 21:02:47.313608: val_loss -0.782 +2024-11-22 21:02:47.313751: Pseudo dice [0.8534] +2024-11-22 21:02:47.313845: Epoch time: 18.62 s +2024-11-22 21:02:48.367487: +2024-11-22 21:02:48.368850: Epoch 6160 +2024-11-22 21:02:48.368994: Current learning rate: 0.00266 +2024-11-22 21:03:07.863183: train_loss -0.813 +2024-11-22 21:03:07.865861: val_loss -0.7924 +2024-11-22 21:03:07.865977: Pseudo dice [0.8617] +2024-11-22 21:03:07.866074: Epoch time: 19.5 s +2024-11-22 21:03:08.765984: +2024-11-22 21:03:08.767155: Epoch 6161 +2024-11-22 21:03:08.767290: Current learning rate: 0.00266 +2024-11-22 21:03:28.246277: train_loss -0.8029 +2024-11-22 21:03:28.256878: val_loss -0.7934 +2024-11-22 21:03:28.257024: Pseudo dice [0.8701] +2024-11-22 21:03:28.257139: Epoch time: 19.48 s +2024-11-22 21:03:29.175777: +2024-11-22 21:03:29.177219: Epoch 6162 +2024-11-22 21:03:29.177342: Current learning rate: 0.00266 +2024-11-22 21:03:49.233420: train_loss -0.8126 +2024-11-22 21:03:49.240392: val_loss -0.7747 +2024-11-22 21:03:49.240596: Pseudo dice [0.8665] +2024-11-22 21:03:49.240714: Epoch time: 20.06 s +2024-11-22 21:03:50.293440: +2024-11-22 21:03:50.295653: Epoch 6163 +2024-11-22 21:03:50.295780: Current learning rate: 0.00266 +2024-11-22 21:04:09.332006: train_loss -0.8154 +2024-11-22 21:04:09.348071: val_loss -0.7803 +2024-11-22 21:04:09.348203: Pseudo dice [0.8609] +2024-11-22 21:04:09.348331: Epoch time: 19.04 s +2024-11-22 21:04:10.300436: +2024-11-22 21:04:10.302547: Epoch 6164 +2024-11-22 21:04:10.302708: Current learning rate: 0.00266 +2024-11-22 21:04:29.226303: train_loss -0.8098 +2024-11-22 21:04:29.239852: val_loss -0.7863 +2024-11-22 21:04:29.239987: Pseudo dice [0.8624] +2024-11-22 21:04:29.265507: Epoch time: 18.93 s +2024-11-22 21:04:29.265679: Yayy! New best EMA pseudo Dice: 0.8607 +2024-11-22 21:04:30.579359: +2024-11-22 21:04:30.580720: Epoch 6165 +2024-11-22 21:04:30.580849: Current learning rate: 0.00266 +2024-11-22 21:04:49.619360: train_loss -0.8079 +2024-11-22 21:04:49.623726: val_loss -0.7647 +2024-11-22 21:04:49.623854: Pseudo dice [0.8656] +2024-11-22 21:04:49.623946: Epoch time: 19.04 s +2024-11-22 21:04:49.624037: Yayy! New best EMA pseudo Dice: 0.8612 +2024-11-22 21:04:50.817092: +2024-11-22 21:04:50.817857: Epoch 6166 +2024-11-22 21:04:50.817992: Current learning rate: 0.00266 +2024-11-22 21:05:10.098502: train_loss -0.8005 +2024-11-22 21:05:10.106326: val_loss -0.7789 +2024-11-22 21:05:10.106479: Pseudo dice [0.8708] +2024-11-22 21:05:10.106574: Epoch time: 19.28 s +2024-11-22 21:05:10.106658: Yayy! New best EMA pseudo Dice: 0.8622 +2024-11-22 21:05:11.333417: +2024-11-22 21:05:11.334631: Epoch 6167 +2024-11-22 21:05:11.334755: Current learning rate: 0.00266 +2024-11-22 21:05:29.982815: train_loss -0.8012 +2024-11-22 21:05:29.991865: val_loss -0.7611 +2024-11-22 21:05:29.995647: Pseudo dice [0.8478] +2024-11-22 21:05:29.995773: Epoch time: 18.65 s +2024-11-22 21:05:30.928136: +2024-11-22 21:05:30.928548: Epoch 6168 +2024-11-22 21:05:30.928662: Current learning rate: 0.00265 +2024-11-22 21:05:51.030007: train_loss -0.7995 +2024-11-22 21:05:51.032210: val_loss -0.7805 +2024-11-22 21:05:51.032377: Pseudo dice [0.8566] +2024-11-22 21:05:51.032478: Epoch time: 20.1 s +2024-11-22 21:05:51.913161: +2024-11-22 21:05:51.915865: Epoch 6169 +2024-11-22 21:05:51.916017: Current learning rate: 0.00265 +2024-11-22 21:06:12.329160: train_loss -0.8079 +2024-11-22 21:06:12.343045: val_loss -0.7563 +2024-11-22 21:06:12.343238: Pseudo dice [0.8435] +2024-11-22 21:06:12.343349: Epoch time: 20.42 s +2024-11-22 21:06:13.384895: +2024-11-22 21:06:13.385661: Epoch 6170 +2024-11-22 21:06:13.385794: Current learning rate: 0.00265 +2024-11-22 21:06:32.884126: train_loss -0.8017 +2024-11-22 21:06:32.886150: val_loss -0.7515 +2024-11-22 21:06:32.886309: Pseudo dice [0.838] +2024-11-22 21:06:32.886417: Epoch time: 19.5 s +2024-11-22 21:06:33.945399: +2024-11-22 21:06:33.947386: Epoch 6171 +2024-11-22 21:06:33.947523: Current learning rate: 0.00265 +2024-11-22 21:06:52.703726: train_loss -0.8029 +2024-11-22 21:06:52.705122: val_loss -0.785 +2024-11-22 21:06:52.705254: Pseudo dice [0.8601] +2024-11-22 21:06:52.705377: Epoch time: 18.76 s +2024-11-22 21:06:53.610425: +2024-11-22 21:06:53.611672: Epoch 6172 +2024-11-22 21:06:53.611804: Current learning rate: 0.00265 +2024-11-22 21:07:12.066211: train_loss -0.8111 +2024-11-22 21:07:12.075341: val_loss -0.7785 +2024-11-22 21:07:12.075489: Pseudo dice [0.8614] +2024-11-22 21:07:12.075595: Epoch time: 18.46 s +2024-11-22 21:07:13.087640: +2024-11-22 21:07:13.089854: Epoch 6173 +2024-11-22 21:07:13.089991: Current learning rate: 0.00265 +2024-11-22 21:07:33.162021: train_loss -0.8081 +2024-11-22 21:07:33.177832: val_loss -0.7693 +2024-11-22 21:07:33.177968: Pseudo dice [0.8484] +2024-11-22 21:07:33.178074: Epoch time: 20.08 s +2024-11-22 21:07:34.236638: +2024-11-22 21:07:34.238029: Epoch 6174 +2024-11-22 21:07:34.238179: Current learning rate: 0.00265 +2024-11-22 21:07:54.020797: train_loss -0.8112 +2024-11-22 21:07:54.022881: val_loss -0.7548 +2024-11-22 21:07:54.023011: Pseudo dice [0.8586] +2024-11-22 21:07:54.023119: Epoch time: 19.78 s +2024-11-22 21:07:55.009097: +2024-11-22 21:07:55.010581: Epoch 6175 +2024-11-22 21:07:55.010715: Current learning rate: 0.00264 +2024-11-22 21:08:14.556804: train_loss -0.8091 +2024-11-22 21:08:14.571559: val_loss -0.7786 +2024-11-22 21:08:14.571721: Pseudo dice [0.8524] +2024-11-22 21:08:14.571814: Epoch time: 19.55 s +2024-11-22 21:08:15.542021: +2024-11-22 21:08:15.543520: Epoch 6176 +2024-11-22 21:08:15.543694: Current learning rate: 0.00264 +2024-11-22 21:08:34.030446: train_loss -0.8104 +2024-11-22 21:08:34.033435: val_loss -0.7802 +2024-11-22 21:08:34.033579: Pseudo dice [0.8561] +2024-11-22 21:08:34.033670: Epoch time: 18.49 s +2024-11-22 21:08:34.929586: +2024-11-22 21:08:34.930402: Epoch 6177 +2024-11-22 21:08:34.930529: Current learning rate: 0.00264 +2024-11-22 21:08:54.018000: train_loss -0.8059 +2024-11-22 21:08:54.025583: val_loss -0.7732 +2024-11-22 21:08:54.025710: Pseudo dice [0.8534] +2024-11-22 21:08:54.025802: Epoch time: 19.09 s +2024-11-22 21:08:55.104991: +2024-11-22 21:08:55.106036: Epoch 6178 +2024-11-22 21:08:55.106182: Current learning rate: 0.00264 +2024-11-22 21:09:15.311594: train_loss -0.8052 +2024-11-22 21:09:15.315402: val_loss -0.7766 +2024-11-22 21:09:15.315534: Pseudo dice [0.8653] +2024-11-22 21:09:15.315623: Epoch time: 20.21 s +2024-11-22 21:09:16.454174: +2024-11-22 21:09:16.455730: Epoch 6179 +2024-11-22 21:09:16.455877: Current learning rate: 0.00264 +2024-11-22 21:09:36.710413: train_loss -0.8082 +2024-11-22 21:09:36.715905: val_loss -0.7796 +2024-11-22 21:09:36.716057: Pseudo dice [0.8536] +2024-11-22 21:09:36.716157: Epoch time: 20.26 s +2024-11-22 21:09:38.053333: +2024-11-22 21:09:38.055273: Epoch 6180 +2024-11-22 21:09:38.055403: Current learning rate: 0.00264 +2024-11-22 21:09:57.479409: train_loss -0.8085 +2024-11-22 21:09:57.486207: val_loss -0.7569 +2024-11-22 21:09:57.486361: Pseudo dice [0.8612] +2024-11-22 21:09:57.486464: Epoch time: 19.43 s +2024-11-22 21:09:58.367900: +2024-11-22 21:09:58.369145: Epoch 6181 +2024-11-22 21:09:58.369268: Current learning rate: 0.00264 +2024-11-22 21:10:18.232384: train_loss -0.7973 +2024-11-22 21:10:18.241181: val_loss -0.7698 +2024-11-22 21:10:18.241413: Pseudo dice [0.8511] +2024-11-22 21:10:18.241516: Epoch time: 19.87 s +2024-11-22 21:10:19.142496: +2024-11-22 21:10:19.143858: Epoch 6182 +2024-11-22 21:10:19.144013: Current learning rate: 0.00264 +2024-11-22 21:10:38.586132: train_loss -0.8056 +2024-11-22 21:10:38.591404: val_loss -0.759 +2024-11-22 21:10:38.591558: Pseudo dice [0.8474] +2024-11-22 21:10:38.591652: Epoch time: 19.44 s +2024-11-22 21:10:39.499276: +2024-11-22 21:10:39.499485: Epoch 6183 +2024-11-22 21:10:39.499615: Current learning rate: 0.00263 +2024-11-22 21:11:00.796727: train_loss -0.7955 +2024-11-22 21:11:00.807882: val_loss -0.7657 +2024-11-22 21:11:00.808041: Pseudo dice [0.8564] +2024-11-22 21:11:00.808175: Epoch time: 21.3 s +2024-11-22 21:11:01.715452: +2024-11-22 21:11:01.716298: Epoch 6184 +2024-11-22 21:11:01.716435: Current learning rate: 0.00263 +2024-11-22 21:11:21.131667: train_loss -0.8069 +2024-11-22 21:11:21.144980: val_loss -0.7726 +2024-11-22 21:11:21.145131: Pseudo dice [0.8503] +2024-11-22 21:11:21.145228: Epoch time: 19.42 s +2024-11-22 21:11:22.100421: +2024-11-22 21:11:22.101798: Epoch 6185 +2024-11-22 21:11:22.101921: Current learning rate: 0.00263 +2024-11-22 21:11:43.373232: train_loss -0.8058 +2024-11-22 21:11:43.380325: val_loss -0.7755 +2024-11-22 21:11:43.380469: Pseudo dice [0.8628] +2024-11-22 21:11:43.380567: Epoch time: 21.27 s +2024-11-22 21:11:44.265508: +2024-11-22 21:11:44.265765: Epoch 6186 +2024-11-22 21:11:44.265881: Current learning rate: 0.00263 +2024-11-22 21:12:03.383534: train_loss -0.8075 +2024-11-22 21:12:03.391681: val_loss -0.7864 +2024-11-22 21:12:03.391819: Pseudo dice [0.8503] +2024-11-22 21:12:03.391919: Epoch time: 19.12 s +2024-11-22 21:12:04.460875: +2024-11-22 21:12:04.462152: Epoch 6187 +2024-11-22 21:12:04.462295: Current learning rate: 0.00263 +2024-11-22 21:12:23.787394: train_loss -0.7982 +2024-11-22 21:12:23.800974: val_loss -0.7748 +2024-11-22 21:12:23.801104: Pseudo dice [0.8507] +2024-11-22 21:12:23.801211: Epoch time: 19.31 s +2024-11-22 21:12:24.729259: +2024-11-22 21:12:24.730114: Epoch 6188 +2024-11-22 21:12:24.730246: Current learning rate: 0.00263 +2024-11-22 21:12:44.746435: train_loss -0.8095 +2024-11-22 21:12:44.754629: val_loss -0.7512 +2024-11-22 21:12:44.754757: Pseudo dice [0.861] +2024-11-22 21:12:44.754865: Epoch time: 20.02 s +2024-11-22 21:12:45.666045: +2024-11-22 21:12:45.668016: Epoch 6189 +2024-11-22 21:12:45.668168: Current learning rate: 0.00263 +2024-11-22 21:13:04.284580: train_loss -0.8062 +2024-11-22 21:13:04.290841: val_loss -0.8027 +2024-11-22 21:13:04.291191: Pseudo dice [0.8556] +2024-11-22 21:13:04.291297: Epoch time: 18.62 s +2024-11-22 21:13:05.182622: +2024-11-22 21:13:05.184288: Epoch 6190 +2024-11-22 21:13:05.184424: Current learning rate: 0.00263 +2024-11-22 21:13:25.028616: train_loss -0.812 +2024-11-22 21:13:25.050432: val_loss -0.7725 +2024-11-22 21:13:25.050611: Pseudo dice [0.8674] +2024-11-22 21:13:25.050720: Epoch time: 19.85 s +2024-11-22 21:13:26.229507: +2024-11-22 21:13:26.230945: Epoch 6191 +2024-11-22 21:13:26.231089: Current learning rate: 0.00262 +2024-11-22 21:13:45.549434: train_loss -0.8113 +2024-11-22 21:13:45.555660: val_loss -0.7899 +2024-11-22 21:13:45.555785: Pseudo dice [0.8518] +2024-11-22 21:13:45.555892: Epoch time: 19.32 s +2024-11-22 21:13:46.663687: +2024-11-22 21:13:46.666321: Epoch 6192 +2024-11-22 21:13:46.666456: Current learning rate: 0.00262 +2024-11-22 21:14:06.879351: train_loss -0.8064 +2024-11-22 21:14:06.893545: val_loss -0.7673 +2024-11-22 21:14:06.893694: Pseudo dice [0.8513] +2024-11-22 21:14:06.893797: Epoch time: 20.22 s +2024-11-22 21:14:07.770846: +2024-11-22 21:14:07.772310: Epoch 6193 +2024-11-22 21:14:07.772474: Current learning rate: 0.00262 +2024-11-22 21:14:27.212597: train_loss -0.8047 +2024-11-22 21:14:27.219642: val_loss -0.7851 +2024-11-22 21:14:27.219784: Pseudo dice [0.8586] +2024-11-22 21:14:27.219873: Epoch time: 19.44 s +2024-11-22 21:14:28.263125: +2024-11-22 21:14:28.264921: Epoch 6194 +2024-11-22 21:14:28.265066: Current learning rate: 0.00262 +2024-11-22 21:14:48.194236: train_loss -0.8126 +2024-11-22 21:14:48.204497: val_loss -0.7839 +2024-11-22 21:14:48.204654: Pseudo dice [0.8597] +2024-11-22 21:14:48.204756: Epoch time: 19.93 s +2024-11-22 21:14:49.111199: +2024-11-22 21:14:49.136723: Epoch 6195 +2024-11-22 21:14:49.136872: Current learning rate: 0.00262 +2024-11-22 21:15:08.828495: train_loss -0.8052 +2024-11-22 21:15:08.834341: val_loss -0.7672 +2024-11-22 21:15:08.834489: Pseudo dice [0.8505] +2024-11-22 21:15:08.834594: Epoch time: 19.72 s +2024-11-22 21:15:09.916028: +2024-11-22 21:15:09.917303: Epoch 6196 +2024-11-22 21:15:09.917447: Current learning rate: 0.00262 +2024-11-22 21:15:30.010609: train_loss -0.8023 +2024-11-22 21:15:30.017949: val_loss -0.798 +2024-11-22 21:15:30.018100: Pseudo dice [0.8583] +2024-11-22 21:15:30.018200: Epoch time: 20.1 s +2024-11-22 21:15:30.970233: +2024-11-22 21:15:30.972038: Epoch 6197 +2024-11-22 21:15:30.972169: Current learning rate: 0.00262 +2024-11-22 21:15:50.709247: train_loss -0.8073 +2024-11-22 21:15:50.726572: val_loss -0.7761 +2024-11-22 21:15:50.726712: Pseudo dice [0.863] +2024-11-22 21:15:50.726797: Epoch time: 19.74 s +2024-11-22 21:15:51.791249: +2024-11-22 21:15:51.792864: Epoch 6198 +2024-11-22 21:15:51.793006: Current learning rate: 0.00261 +2024-11-22 21:16:12.034244: train_loss -0.8091 +2024-11-22 21:16:12.036880: val_loss -0.7602 +2024-11-22 21:16:12.037088: Pseudo dice [0.8497] +2024-11-22 21:16:12.037470: Epoch time: 20.24 s +2024-11-22 21:16:12.921117: +2024-11-22 21:16:12.922776: Epoch 6199 +2024-11-22 21:16:12.922907: Current learning rate: 0.00261 +2024-11-22 21:16:32.204532: train_loss -0.8111 +2024-11-22 21:16:32.208626: val_loss -0.7641 +2024-11-22 21:16:32.208751: Pseudo dice [0.8618] +2024-11-22 21:16:32.208908: Epoch time: 19.28 s +2024-11-22 21:16:33.404786: +2024-11-22 21:16:33.406435: Epoch 6200 +2024-11-22 21:16:33.406563: Current learning rate: 0.00261 +2024-11-22 21:16:52.217175: train_loss -0.8064 +2024-11-22 21:16:52.224218: val_loss -0.7858 +2024-11-22 21:16:52.224376: Pseudo dice [0.8513] +2024-11-22 21:16:52.224471: Epoch time: 18.81 s +2024-11-22 21:16:53.346995: +2024-11-22 21:16:53.349119: Epoch 6201 +2024-11-22 21:16:53.349269: Current learning rate: 0.00261 +2024-11-22 21:17:13.056475: train_loss -0.8065 +2024-11-22 21:17:13.065380: val_loss -0.7617 +2024-11-22 21:17:13.065523: Pseudo dice [0.8644] +2024-11-22 21:17:13.065611: Epoch time: 19.71 s +2024-11-22 21:17:14.124324: +2024-11-22 21:17:14.125038: Epoch 6202 +2024-11-22 21:17:14.125182: Current learning rate: 0.00261 +2024-11-22 21:17:34.293869: train_loss -0.8058 +2024-11-22 21:17:34.309455: val_loss -0.7667 +2024-11-22 21:17:34.309609: Pseudo dice [0.8423] +2024-11-22 21:17:34.309714: Epoch time: 20.17 s +2024-11-22 21:17:35.467996: +2024-11-22 21:17:35.468541: Epoch 6203 +2024-11-22 21:17:35.468674: Current learning rate: 0.00261 +2024-11-22 21:17:54.671513: train_loss -0.7924 +2024-11-22 21:17:54.676870: val_loss -0.801 +2024-11-22 21:17:54.677016: Pseudo dice [0.8681] +2024-11-22 21:17:54.677114: Epoch time: 19.2 s +2024-11-22 21:17:55.595986: +2024-11-22 21:17:55.597327: Epoch 6204 +2024-11-22 21:17:55.597462: Current learning rate: 0.00261 +2024-11-22 21:18:14.990396: train_loss -0.8088 +2024-11-22 21:18:14.999105: val_loss -0.7781 +2024-11-22 21:18:14.999231: Pseudo dice [0.8582] +2024-11-22 21:18:14.999333: Epoch time: 19.4 s +2024-11-22 21:18:15.911628: +2024-11-22 21:18:15.913085: Epoch 6205 +2024-11-22 21:18:15.913232: Current learning rate: 0.00261 +2024-11-22 21:18:34.428921: train_loss -0.8125 +2024-11-22 21:18:34.437594: val_loss -0.7883 +2024-11-22 21:18:34.437715: Pseudo dice [0.8509] +2024-11-22 21:18:34.437821: Epoch time: 18.52 s +2024-11-22 21:18:35.393887: +2024-11-22 21:18:35.395736: Epoch 6206 +2024-11-22 21:18:35.395864: Current learning rate: 0.0026 +2024-11-22 21:18:55.407894: train_loss -0.817 +2024-11-22 21:18:55.416502: val_loss -0.7829 +2024-11-22 21:18:55.416676: Pseudo dice [0.8653] +2024-11-22 21:18:55.416776: Epoch time: 20.01 s +2024-11-22 21:18:56.535114: +2024-11-22 21:18:56.536451: Epoch 6207 +2024-11-22 21:18:56.536590: Current learning rate: 0.0026 +2024-11-22 21:19:15.523040: train_loss -0.8154 +2024-11-22 21:19:15.533487: val_loss -0.7806 +2024-11-22 21:19:15.533625: Pseudo dice [0.8569] +2024-11-22 21:19:15.533731: Epoch time: 18.99 s +2024-11-22 21:19:16.576984: +2024-11-22 21:19:16.579051: Epoch 6208 +2024-11-22 21:19:16.579198: Current learning rate: 0.0026 +2024-11-22 21:19:35.719761: train_loss -0.7995 +2024-11-22 21:19:35.726309: val_loss -0.7886 +2024-11-22 21:19:35.726464: Pseudo dice [0.8706] +2024-11-22 21:19:35.726583: Epoch time: 19.14 s +2024-11-22 21:19:36.710815: +2024-11-22 21:19:36.712096: Epoch 6209 +2024-11-22 21:19:36.712239: Current learning rate: 0.0026 +2024-11-22 21:19:57.150535: train_loss -0.8053 +2024-11-22 21:19:57.159040: val_loss -0.7472 +2024-11-22 21:19:57.159229: Pseudo dice [0.8546] +2024-11-22 21:19:57.159334: Epoch time: 20.44 s +2024-11-22 21:19:58.293520: +2024-11-22 21:19:58.295042: Epoch 6210 +2024-11-22 21:19:58.295169: Current learning rate: 0.0026 +2024-11-22 21:20:16.896484: train_loss -0.7965 +2024-11-22 21:20:16.903785: val_loss -0.7848 +2024-11-22 21:20:16.903933: Pseudo dice [0.8603] +2024-11-22 21:20:16.904039: Epoch time: 18.6 s +2024-11-22 21:20:17.977880: +2024-11-22 21:20:17.978174: Epoch 6211 +2024-11-22 21:20:17.978310: Current learning rate: 0.0026 +2024-11-22 21:20:36.334529: train_loss -0.7948 +2024-11-22 21:20:36.337196: val_loss -0.7772 +2024-11-22 21:20:36.337341: Pseudo dice [0.842] +2024-11-22 21:20:36.337446: Epoch time: 18.36 s +2024-11-22 21:20:37.214540: +2024-11-22 21:20:37.214804: Epoch 6212 +2024-11-22 21:20:37.214936: Current learning rate: 0.0026 +2024-11-22 21:20:55.510990: train_loss -0.8056 +2024-11-22 21:20:55.515517: val_loss -0.7885 +2024-11-22 21:20:55.515666: Pseudo dice [0.865] +2024-11-22 21:20:55.515769: Epoch time: 18.3 s +2024-11-22 21:20:56.463646: +2024-11-22 21:20:56.463836: Epoch 6213 +2024-11-22 21:20:56.463951: Current learning rate: 0.00259 +2024-11-22 21:21:15.311171: train_loss -0.8063 +2024-11-22 21:21:15.317570: val_loss -0.8102 +2024-11-22 21:21:15.317719: Pseudo dice [0.8673] +2024-11-22 21:21:15.317814: Epoch time: 18.85 s +2024-11-22 21:21:16.612604: +2024-11-22 21:21:16.612809: Epoch 6214 +2024-11-22 21:21:16.612924: Current learning rate: 0.00259 +2024-11-22 21:21:35.065156: train_loss -0.8041 +2024-11-22 21:21:35.066357: val_loss -0.7802 +2024-11-22 21:21:35.066528: Pseudo dice [0.8623] +2024-11-22 21:21:35.066652: Epoch time: 18.45 s +2024-11-22 21:21:35.938980: +2024-11-22 21:21:35.939239: Epoch 6215 +2024-11-22 21:21:35.939381: Current learning rate: 0.00259 +2024-11-22 21:21:54.789639: train_loss -0.8106 +2024-11-22 21:21:54.794431: val_loss -0.7676 +2024-11-22 21:21:54.794618: Pseudo dice [0.8602] +2024-11-22 21:21:54.794708: Epoch time: 18.85 s +2024-11-22 21:21:55.823235: +2024-11-22 21:21:55.823454: Epoch 6216 +2024-11-22 21:21:55.823567: Current learning rate: 0.00259 +2024-11-22 21:22:14.805764: train_loss -0.8112 +2024-11-22 21:22:14.811141: val_loss -0.7764 +2024-11-22 21:22:14.811253: Pseudo dice [0.8514] +2024-11-22 21:22:14.811337: Epoch time: 18.98 s +2024-11-22 21:22:15.882820: +2024-11-22 21:22:15.883028: Epoch 6217 +2024-11-22 21:22:15.883142: Current learning rate: 0.00259 +2024-11-22 21:22:33.481456: train_loss -0.8032 +2024-11-22 21:22:33.499131: val_loss -0.7688 +2024-11-22 21:22:33.499259: Pseudo dice [0.8555] +2024-11-22 21:22:33.499363: Epoch time: 17.6 s +2024-11-22 21:22:34.647958: +2024-11-22 21:22:34.648173: Epoch 6218 +2024-11-22 21:22:34.648289: Current learning rate: 0.00259 +2024-11-22 21:22:53.924757: train_loss -0.8153 +2024-11-22 21:22:53.925844: val_loss -0.7771 +2024-11-22 21:22:53.925946: Pseudo dice [0.8604] +2024-11-22 21:22:53.926061: Epoch time: 19.28 s +2024-11-22 21:22:54.797419: +2024-11-22 21:22:54.797662: Epoch 6219 +2024-11-22 21:22:54.797795: Current learning rate: 0.00259 +2024-11-22 21:23:14.262051: train_loss -0.805 +2024-11-22 21:23:14.275325: val_loss -0.7763 +2024-11-22 21:23:14.275481: Pseudo dice [0.8688] +2024-11-22 21:23:14.275582: Epoch time: 19.47 s +2024-11-22 21:23:15.287178: +2024-11-22 21:23:15.288036: Epoch 6220 +2024-11-22 21:23:15.288168: Current learning rate: 0.00259 +2024-11-22 21:23:34.054213: train_loss -0.8062 +2024-11-22 21:23:34.065794: val_loss -0.7802 +2024-11-22 21:23:34.065936: Pseudo dice [0.8593] +2024-11-22 21:23:34.066031: Epoch time: 18.77 s +2024-11-22 21:23:35.158461: +2024-11-22 21:23:35.159685: Epoch 6221 +2024-11-22 21:23:35.159808: Current learning rate: 0.00258 +2024-11-22 21:23:53.824696: train_loss -0.8121 +2024-11-22 21:23:53.828793: val_loss -0.7908 +2024-11-22 21:23:53.828928: Pseudo dice [0.8509] +2024-11-22 21:23:53.829043: Epoch time: 18.67 s +2024-11-22 21:23:54.905517: +2024-11-22 21:23:54.906431: Epoch 6222 +2024-11-22 21:23:54.906566: Current learning rate: 0.00258 +2024-11-22 21:24:14.421179: train_loss -0.7961 +2024-11-22 21:24:14.428812: val_loss -0.786 +2024-11-22 21:24:14.428935: Pseudo dice [0.8574] +2024-11-22 21:24:14.429046: Epoch time: 19.52 s +2024-11-22 21:24:15.515218: +2024-11-22 21:24:15.515671: Epoch 6223 +2024-11-22 21:24:15.515809: Current learning rate: 0.00258 +2024-11-22 21:24:35.868421: train_loss -0.8044 +2024-11-22 21:24:35.870948: val_loss -0.7855 +2024-11-22 21:24:35.871074: Pseudo dice [0.8516] +2024-11-22 21:24:35.871181: Epoch time: 20.35 s +2024-11-22 21:24:36.753522: +2024-11-22 21:24:36.754701: Epoch 6224 +2024-11-22 21:24:36.754844: Current learning rate: 0.00258 +2024-11-22 21:24:56.239576: train_loss -0.8016 +2024-11-22 21:24:56.251372: val_loss -0.7887 +2024-11-22 21:24:56.251568: Pseudo dice [0.8561] +2024-11-22 21:24:56.251675: Epoch time: 19.49 s +2024-11-22 21:24:57.131353: +2024-11-22 21:24:57.132416: Epoch 6225 +2024-11-22 21:24:57.132599: Current learning rate: 0.00258 +2024-11-22 21:25:16.645357: train_loss -0.8146 +2024-11-22 21:25:16.654869: val_loss -0.7536 +2024-11-22 21:25:16.655076: Pseudo dice [0.8605] +2024-11-22 21:25:16.655179: Epoch time: 19.51 s +2024-11-22 21:25:17.538718: +2024-11-22 21:25:17.541173: Epoch 6226 +2024-11-22 21:25:17.541323: Current learning rate: 0.00258 +2024-11-22 21:25:37.951973: train_loss -0.8082 +2024-11-22 21:25:37.964129: val_loss -0.7795 +2024-11-22 21:25:37.964285: Pseudo dice [0.8592] +2024-11-22 21:25:37.964391: Epoch time: 20.41 s +2024-11-22 21:25:38.931754: +2024-11-22 21:25:38.933792: Epoch 6227 +2024-11-22 21:25:38.933922: Current learning rate: 0.00258 +2024-11-22 21:25:58.878531: train_loss -0.8052 +2024-11-22 21:25:58.885040: val_loss -0.7754 +2024-11-22 21:25:58.885379: Pseudo dice [0.8526] +2024-11-22 21:25:58.885476: Epoch time: 19.95 s +2024-11-22 21:25:59.805856: +2024-11-22 21:25:59.806659: Epoch 6228 +2024-11-22 21:25:59.806788: Current learning rate: 0.00258 +2024-11-22 21:26:20.277945: train_loss -0.8068 +2024-11-22 21:26:20.293107: val_loss -0.7838 +2024-11-22 21:26:20.293254: Pseudo dice [0.8669] +2024-11-22 21:26:20.293452: Epoch time: 20.47 s +2024-11-22 21:26:21.221888: +2024-11-22 21:26:21.223552: Epoch 6229 +2024-11-22 21:26:21.223691: Current learning rate: 0.00257 +2024-11-22 21:26:41.065115: train_loss -0.8106 +2024-11-22 21:26:41.067559: val_loss -0.7942 +2024-11-22 21:26:41.067702: Pseudo dice [0.8562] +2024-11-22 21:26:41.067809: Epoch time: 19.84 s +2024-11-22 21:26:41.960317: +2024-11-22 21:26:41.961984: Epoch 6230 +2024-11-22 21:26:41.962121: Current learning rate: 0.00257 +2024-11-22 21:27:02.225604: train_loss -0.809 +2024-11-22 21:27:02.245626: val_loss -0.7752 +2024-11-22 21:27:02.245784: Pseudo dice [0.8597] +2024-11-22 21:27:02.245893: Epoch time: 20.27 s +2024-11-22 21:27:03.285278: +2024-11-22 21:27:03.287039: Epoch 6231 +2024-11-22 21:27:03.287176: Current learning rate: 0.00257 +2024-11-22 21:27:21.935384: train_loss -0.8084 +2024-11-22 21:27:21.941991: val_loss -0.7889 +2024-11-22 21:27:21.942124: Pseudo dice [0.8668] +2024-11-22 21:27:21.942237: Epoch time: 18.65 s +2024-11-22 21:27:22.879501: +2024-11-22 21:27:22.880914: Epoch 6232 +2024-11-22 21:27:22.881053: Current learning rate: 0.00257 +2024-11-22 21:27:43.603899: train_loss -0.8061 +2024-11-22 21:27:43.619120: val_loss -0.7697 +2024-11-22 21:27:43.619281: Pseudo dice [0.8565] +2024-11-22 21:27:43.619391: Epoch time: 20.73 s +2024-11-22 21:27:44.753609: +2024-11-22 21:27:44.755348: Epoch 6233 +2024-11-22 21:27:44.755489: Current learning rate: 0.00257 +2024-11-22 21:28:04.835054: train_loss -0.8093 +2024-11-22 21:28:04.845345: val_loss -0.7685 +2024-11-22 21:28:04.845529: Pseudo dice [0.8551] +2024-11-22 21:28:04.845661: Epoch time: 20.08 s +2024-11-22 21:28:05.824207: +2024-11-22 21:28:05.825927: Epoch 6234 +2024-11-22 21:28:05.826050: Current learning rate: 0.00257 +2024-11-22 21:28:25.344279: train_loss -0.8146 +2024-11-22 21:28:25.355647: val_loss -0.7989 +2024-11-22 21:28:25.355810: Pseudo dice [0.8704] +2024-11-22 21:28:25.355910: Epoch time: 19.52 s +2024-11-22 21:28:26.356802: +2024-11-22 21:28:26.357513: Epoch 6235 +2024-11-22 21:28:26.357637: Current learning rate: 0.00257 +2024-11-22 21:28:46.338285: train_loss -0.809 +2024-11-22 21:28:46.347007: val_loss -0.7779 +2024-11-22 21:28:46.347273: Pseudo dice [0.8583] +2024-11-22 21:28:46.347382: Epoch time: 19.98 s +2024-11-22 21:28:47.356925: +2024-11-22 21:28:47.357930: Epoch 6236 +2024-11-22 21:28:47.358073: Current learning rate: 0.00256 +2024-11-22 21:29:06.998140: train_loss -0.8101 +2024-11-22 21:29:07.007396: val_loss -0.7644 +2024-11-22 21:29:07.007565: Pseudo dice [0.8682] +2024-11-22 21:29:07.007678: Epoch time: 19.64 s +2024-11-22 21:29:08.325775: +2024-11-22 21:29:08.327699: Epoch 6237 +2024-11-22 21:29:08.327839: Current learning rate: 0.00256 +2024-11-22 21:29:27.780403: train_loss -0.8061 +2024-11-22 21:29:27.786539: val_loss -0.7796 +2024-11-22 21:29:27.786687: Pseudo dice [0.8483] +2024-11-22 21:29:27.786787: Epoch time: 19.46 s +2024-11-22 21:29:28.776956: +2024-11-22 21:29:28.778103: Epoch 6238 +2024-11-22 21:29:28.778239: Current learning rate: 0.00256 +2024-11-22 21:29:48.349018: train_loss -0.8155 +2024-11-22 21:29:48.351107: val_loss -0.7788 +2024-11-22 21:29:48.351242: Pseudo dice [0.8571] +2024-11-22 21:29:48.351363: Epoch time: 19.57 s +2024-11-22 21:29:49.276433: +2024-11-22 21:29:49.277309: Epoch 6239 +2024-11-22 21:29:49.277433: Current learning rate: 0.00256 +2024-11-22 21:30:09.201300: train_loss -0.8079 +2024-11-22 21:30:09.208791: val_loss -0.7735 +2024-11-22 21:30:09.208937: Pseudo dice [0.8602] +2024-11-22 21:30:09.209082: Epoch time: 19.93 s +2024-11-22 21:30:10.128850: +2024-11-22 21:30:10.130289: Epoch 6240 +2024-11-22 21:30:10.130416: Current learning rate: 0.00256 +2024-11-22 21:30:29.394578: train_loss -0.8168 +2024-11-22 21:30:29.408424: val_loss -0.7799 +2024-11-22 21:30:29.408594: Pseudo dice [0.8717] +2024-11-22 21:30:29.408687: Epoch time: 19.27 s +2024-11-22 21:30:30.474417: +2024-11-22 21:30:30.475945: Epoch 6241 +2024-11-22 21:30:30.476089: Current learning rate: 0.00256 +2024-11-22 21:30:49.594554: train_loss -0.8102 +2024-11-22 21:30:49.602437: val_loss -0.7613 +2024-11-22 21:30:49.602576: Pseudo dice [0.848] +2024-11-22 21:30:49.602683: Epoch time: 19.12 s +2024-11-22 21:30:50.694026: +2024-11-22 21:30:50.695633: Epoch 6242 +2024-11-22 21:30:50.695770: Current learning rate: 0.00256 +2024-11-22 21:31:10.756271: train_loss -0.8042 +2024-11-22 21:31:10.762461: val_loss -0.7938 +2024-11-22 21:31:10.762595: Pseudo dice [0.8574] +2024-11-22 21:31:10.762684: Epoch time: 20.06 s +2024-11-22 21:31:11.681646: +2024-11-22 21:31:11.682367: Epoch 6243 +2024-11-22 21:31:11.682511: Current learning rate: 0.00256 +2024-11-22 21:31:30.874110: train_loss -0.8088 +2024-11-22 21:31:30.877433: val_loss -0.7722 +2024-11-22 21:31:30.877561: Pseudo dice [0.854] +2024-11-22 21:31:30.877662: Epoch time: 19.19 s +2024-11-22 21:31:31.771952: +2024-11-22 21:31:31.772402: Epoch 6244 +2024-11-22 21:31:31.772545: Current learning rate: 0.00255 +2024-11-22 21:31:51.389402: train_loss -0.8169 +2024-11-22 21:31:51.395968: val_loss -0.7764 +2024-11-22 21:31:51.396094: Pseudo dice [0.8569] +2024-11-22 21:31:51.396198: Epoch time: 19.62 s +2024-11-22 21:31:52.320787: +2024-11-22 21:31:52.322531: Epoch 6245 +2024-11-22 21:31:52.322676: Current learning rate: 0.00255 +2024-11-22 21:32:10.983137: train_loss -0.8136 +2024-11-22 21:32:10.989326: val_loss -0.7725 +2024-11-22 21:32:10.989482: Pseudo dice [0.8701] +2024-11-22 21:32:10.989598: Epoch time: 18.66 s +2024-11-22 21:32:12.028676: +2024-11-22 21:32:12.030217: Epoch 6246 +2024-11-22 21:32:12.030351: Current learning rate: 0.00255 +2024-11-22 21:32:31.596777: train_loss -0.8082 +2024-11-22 21:32:31.605175: val_loss -0.7756 +2024-11-22 21:32:31.605344: Pseudo dice [0.8565] +2024-11-22 21:32:31.605433: Epoch time: 19.57 s +2024-11-22 21:32:32.580168: +2024-11-22 21:32:32.580978: Epoch 6247 +2024-11-22 21:32:32.581117: Current learning rate: 0.00255 +2024-11-22 21:32:52.209902: train_loss -0.8114 +2024-11-22 21:32:52.214912: val_loss -0.7776 +2024-11-22 21:32:52.215048: Pseudo dice [0.8421] +2024-11-22 21:32:52.215158: Epoch time: 19.63 s +2024-11-22 21:32:53.373632: +2024-11-22 21:32:53.374921: Epoch 6248 +2024-11-22 21:32:53.375047: Current learning rate: 0.00255 +2024-11-22 21:33:13.587924: train_loss -0.801 +2024-11-22 21:33:13.590102: val_loss -0.7621 +2024-11-22 21:33:13.590243: Pseudo dice [0.8417] +2024-11-22 21:33:13.590332: Epoch time: 20.22 s +2024-11-22 21:33:14.548373: +2024-11-22 21:33:14.551016: Epoch 6249 +2024-11-22 21:33:14.551170: Current learning rate: 0.00255 +2024-11-22 21:33:33.529455: train_loss -0.8036 +2024-11-22 21:33:33.535625: val_loss -0.7849 +2024-11-22 21:33:33.535771: Pseudo dice [0.8522] +2024-11-22 21:33:33.535893: Epoch time: 18.98 s +2024-11-22 21:33:34.746505: +2024-11-22 21:33:34.747942: Epoch 6250 +2024-11-22 21:33:34.748091: Current learning rate: 0.00255 +2024-11-22 21:33:53.512581: train_loss -0.8074 +2024-11-22 21:33:53.519863: val_loss -0.7879 +2024-11-22 21:33:53.520004: Pseudo dice [0.8619] +2024-11-22 21:33:53.520235: Epoch time: 18.77 s +2024-11-22 21:33:54.445446: +2024-11-22 21:33:54.446268: Epoch 6251 +2024-11-22 21:33:54.446404: Current learning rate: 0.00255 +2024-11-22 21:34:13.650862: train_loss -0.8132 +2024-11-22 21:34:13.652826: val_loss -0.7765 +2024-11-22 21:34:13.652951: Pseudo dice [0.858] +2024-11-22 21:34:13.653050: Epoch time: 19.21 s +2024-11-22 21:34:14.532383: +2024-11-22 21:34:14.534406: Epoch 6252 +2024-11-22 21:34:14.534532: Current learning rate: 0.00254 +2024-11-22 21:34:34.219958: train_loss -0.8143 +2024-11-22 21:34:34.226766: val_loss -0.7593 +2024-11-22 21:34:34.226927: Pseudo dice [0.8641] +2024-11-22 21:34:34.227046: Epoch time: 19.69 s +2024-11-22 21:34:35.140348: +2024-11-22 21:34:35.156742: Epoch 6253 +2024-11-22 21:34:35.156877: Current learning rate: 0.00254 +2024-11-22 21:34:54.907619: train_loss -0.8026 +2024-11-22 21:34:54.911866: val_loss -0.7982 +2024-11-22 21:34:54.912014: Pseudo dice [0.8602] +2024-11-22 21:34:54.912146: Epoch time: 19.76 s +2024-11-22 21:34:56.003828: +2024-11-22 21:34:56.005343: Epoch 6254 +2024-11-22 21:34:56.005469: Current learning rate: 0.00254 +2024-11-22 21:35:14.548891: train_loss -0.8119 +2024-11-22 21:35:14.552793: val_loss -0.7839 +2024-11-22 21:35:14.552987: Pseudo dice [0.8638] +2024-11-22 21:35:14.553083: Epoch time: 18.55 s +2024-11-22 21:35:15.569903: +2024-11-22 21:35:15.571030: Epoch 6255 +2024-11-22 21:35:15.571160: Current learning rate: 0.00254 +2024-11-22 21:35:35.131415: train_loss -0.8153 +2024-11-22 21:35:35.145917: val_loss -0.7778 +2024-11-22 21:35:35.146069: Pseudo dice [0.8558] +2024-11-22 21:35:35.146171: Epoch time: 19.56 s +2024-11-22 21:35:36.095686: +2024-11-22 21:35:36.097035: Epoch 6256 +2024-11-22 21:35:36.097173: Current learning rate: 0.00254 +2024-11-22 21:35:56.319202: train_loss -0.8068 +2024-11-22 21:35:56.321420: val_loss -0.7953 +2024-11-22 21:35:56.321527: Pseudo dice [0.8563] +2024-11-22 21:35:56.321671: Epoch time: 20.22 s +2024-11-22 21:35:57.197030: +2024-11-22 21:35:57.197822: Epoch 6257 +2024-11-22 21:35:57.197956: Current learning rate: 0.00254 +2024-11-22 21:36:16.676623: train_loss -0.8037 +2024-11-22 21:36:16.681453: val_loss -0.791 +2024-11-22 21:36:16.681574: Pseudo dice [0.8542] +2024-11-22 21:36:16.681686: Epoch time: 19.48 s +2024-11-22 21:36:17.714206: +2024-11-22 21:36:17.715623: Epoch 6258 +2024-11-22 21:36:17.715759: Current learning rate: 0.00254 +2024-11-22 21:36:37.432533: train_loss -0.8096 +2024-11-22 21:36:37.437917: val_loss -0.7704 +2024-11-22 21:36:37.438064: Pseudo dice [0.8529] +2024-11-22 21:36:37.438154: Epoch time: 19.72 s +2024-11-22 21:36:38.433659: +2024-11-22 21:36:38.434894: Epoch 6259 +2024-11-22 21:36:38.435020: Current learning rate: 0.00253 +2024-11-22 21:36:57.559292: train_loss -0.801 +2024-11-22 21:36:57.561853: val_loss -0.7828 +2024-11-22 21:36:57.561988: Pseudo dice [0.8542] +2024-11-22 21:36:57.562083: Epoch time: 19.13 s +2024-11-22 21:36:58.581026: +2024-11-22 21:36:58.582751: Epoch 6260 +2024-11-22 21:36:58.582886: Current learning rate: 0.00253 +2024-11-22 21:37:17.935814: train_loss -0.8095 +2024-11-22 21:37:17.940323: val_loss -0.7762 +2024-11-22 21:37:17.940457: Pseudo dice [0.856] +2024-11-22 21:37:17.940573: Epoch time: 19.36 s +2024-11-22 21:37:18.903303: +2024-11-22 21:37:18.904876: Epoch 6261 +2024-11-22 21:37:18.905014: Current learning rate: 0.00253 +2024-11-22 21:37:38.427407: train_loss -0.8084 +2024-11-22 21:37:38.435282: val_loss -0.7684 +2024-11-22 21:37:38.435415: Pseudo dice [0.8529] +2024-11-22 21:37:38.435518: Epoch time: 19.52 s +2024-11-22 21:37:39.490634: +2024-11-22 21:37:39.491741: Epoch 6262 +2024-11-22 21:37:39.491887: Current learning rate: 0.00253 +2024-11-22 21:37:58.190318: train_loss -0.7977 +2024-11-22 21:37:58.193731: val_loss -0.7811 +2024-11-22 21:37:58.193878: Pseudo dice [0.8567] +2024-11-22 21:37:58.193967: Epoch time: 18.7 s +2024-11-22 21:37:59.153779: +2024-11-22 21:37:59.154204: Epoch 6263 +2024-11-22 21:37:59.154339: Current learning rate: 0.00253 +2024-11-22 21:38:19.097854: train_loss -0.7947 +2024-11-22 21:38:19.105927: val_loss -0.805 +2024-11-22 21:38:19.106076: Pseudo dice [0.8614] +2024-11-22 21:38:19.106191: Epoch time: 19.94 s +2024-11-22 21:38:20.066332: +2024-11-22 21:38:20.067653: Epoch 6264 +2024-11-22 21:38:20.067775: Current learning rate: 0.00253 +2024-11-22 21:38:40.477313: train_loss -0.7938 +2024-11-22 21:38:40.486023: val_loss -0.7638 +2024-11-22 21:38:40.486181: Pseudo dice [0.8495] +2024-11-22 21:38:40.486283: Epoch time: 20.41 s +2024-11-22 21:38:41.436336: +2024-11-22 21:38:41.439001: Epoch 6265 +2024-11-22 21:38:41.439150: Current learning rate: 0.00253 +2024-11-22 21:39:01.007135: train_loss -0.8009 +2024-11-22 21:39:01.012353: val_loss -0.7815 +2024-11-22 21:39:01.012489: Pseudo dice [0.8512] +2024-11-22 21:39:01.039287: Epoch time: 19.57 s +2024-11-22 21:39:02.030757: +2024-11-22 21:39:02.031185: Epoch 6266 +2024-11-22 21:39:02.031310: Current learning rate: 0.00253 +2024-11-22 21:39:21.909508: train_loss -0.7964 +2024-11-22 21:39:21.922665: val_loss -0.7744 +2024-11-22 21:39:21.922825: Pseudo dice [0.8532] +2024-11-22 21:39:21.922927: Epoch time: 19.88 s +2024-11-22 21:39:22.944390: +2024-11-22 21:39:22.945425: Epoch 6267 +2024-11-22 21:39:22.945554: Current learning rate: 0.00252 +2024-11-22 21:39:41.484337: train_loss -0.7993 +2024-11-22 21:39:41.515261: val_loss -0.7613 +2024-11-22 21:39:41.515452: Pseudo dice [0.85] +2024-11-22 21:39:41.515583: Epoch time: 18.54 s +2024-11-22 21:39:42.464927: +2024-11-22 21:39:42.465780: Epoch 6268 +2024-11-22 21:39:42.465912: Current learning rate: 0.00252 +2024-11-22 21:40:01.939360: train_loss -0.818 +2024-11-22 21:40:01.950595: val_loss -0.779 +2024-11-22 21:40:01.950742: Pseudo dice [0.8671] +2024-11-22 21:40:01.950843: Epoch time: 19.48 s +2024-11-22 21:40:03.023499: +2024-11-22 21:40:03.024955: Epoch 6269 +2024-11-22 21:40:03.025090: Current learning rate: 0.00252 +2024-11-22 21:40:23.122313: train_loss -0.8104 +2024-11-22 21:40:23.130984: val_loss -0.7598 +2024-11-22 21:40:23.131135: Pseudo dice [0.8486] +2024-11-22 21:40:23.131240: Epoch time: 20.1 s +2024-11-22 21:40:24.118169: +2024-11-22 21:40:24.119244: Epoch 6270 +2024-11-22 21:40:24.119387: Current learning rate: 0.00252 +2024-11-22 21:40:43.653500: train_loss -0.8081 +2024-11-22 21:40:43.673928: val_loss -0.7597 +2024-11-22 21:40:43.674099: Pseudo dice [0.8626] +2024-11-22 21:40:43.674189: Epoch time: 19.54 s +2024-11-22 21:40:44.965762: +2024-11-22 21:40:44.966805: Epoch 6271 +2024-11-22 21:40:44.966941: Current learning rate: 0.00252 +2024-11-22 21:41:04.133270: train_loss -0.8106 +2024-11-22 21:41:04.141789: val_loss -0.7835 +2024-11-22 21:41:04.141961: Pseudo dice [0.8442] +2024-11-22 21:41:04.142074: Epoch time: 19.17 s +2024-11-22 21:41:05.192669: +2024-11-22 21:41:05.195454: Epoch 6272 +2024-11-22 21:41:05.195577: Current learning rate: 0.00252 +2024-11-22 21:41:24.625040: train_loss -0.8071 +2024-11-22 21:41:24.640475: val_loss -0.7733 +2024-11-22 21:41:24.640622: Pseudo dice [0.8533] +2024-11-22 21:41:24.640714: Epoch time: 19.43 s +2024-11-22 21:41:25.615200: +2024-11-22 21:41:25.616624: Epoch 6273 +2024-11-22 21:41:25.616746: Current learning rate: 0.00252 +2024-11-22 21:41:45.235089: train_loss -0.8089 +2024-11-22 21:41:45.237285: val_loss -0.766 +2024-11-22 21:41:45.237408: Pseudo dice [0.8771] +2024-11-22 21:41:45.237510: Epoch time: 19.62 s +2024-11-22 21:41:46.178341: +2024-11-22 21:41:46.179451: Epoch 6274 +2024-11-22 21:41:46.179586: Current learning rate: 0.00252 +2024-11-22 21:42:06.312000: train_loss -0.8138 +2024-11-22 21:42:06.317095: val_loss -0.7882 +2024-11-22 21:42:06.317243: Pseudo dice [0.8589] +2024-11-22 21:42:06.318988: Epoch time: 20.13 s +2024-11-22 21:42:07.200847: +2024-11-22 21:42:07.201662: Epoch 6275 +2024-11-22 21:42:07.201801: Current learning rate: 0.00251 +2024-11-22 21:42:27.533460: train_loss -0.8138 +2024-11-22 21:42:27.548504: val_loss -0.7906 +2024-11-22 21:42:27.548671: Pseudo dice [0.8608] +2024-11-22 21:42:27.548787: Epoch time: 20.33 s +2024-11-22 21:42:28.447110: +2024-11-22 21:42:28.448475: Epoch 6276 +2024-11-22 21:42:28.448613: Current learning rate: 0.00251 +2024-11-22 21:42:47.915150: train_loss -0.8078 +2024-11-22 21:42:47.920976: val_loss -0.769 +2024-11-22 21:42:47.921130: Pseudo dice [0.8528] +2024-11-22 21:42:47.921487: Epoch time: 19.47 s +2024-11-22 21:42:48.857384: +2024-11-22 21:42:48.857868: Epoch 6277 +2024-11-22 21:42:48.858014: Current learning rate: 0.00251 +2024-11-22 21:43:08.446798: train_loss -0.8145 +2024-11-22 21:43:08.454523: val_loss -0.7966 +2024-11-22 21:43:08.455084: Pseudo dice [0.85] +2024-11-22 21:43:08.455254: Epoch time: 19.59 s +2024-11-22 21:43:09.394233: +2024-11-22 21:43:09.396338: Epoch 6278 +2024-11-22 21:43:09.396502: Current learning rate: 0.00251 +2024-11-22 21:43:29.139188: train_loss -0.7932 +2024-11-22 21:43:29.149625: val_loss -0.7482 +2024-11-22 21:43:29.149867: Pseudo dice [0.8485] +2024-11-22 21:43:29.149962: Epoch time: 19.75 s +2024-11-22 21:43:30.227726: +2024-11-22 21:43:30.229156: Epoch 6279 +2024-11-22 21:43:30.229295: Current learning rate: 0.00251 +2024-11-22 21:43:49.837802: train_loss -0.7807 +2024-11-22 21:43:49.840407: val_loss -0.7492 +2024-11-22 21:43:49.840523: Pseudo dice [0.8452] +2024-11-22 21:43:49.840625: Epoch time: 19.61 s +2024-11-22 21:43:50.762962: +2024-11-22 21:43:50.763413: Epoch 6280 +2024-11-22 21:43:50.763541: Current learning rate: 0.00251 +2024-11-22 21:44:10.303171: train_loss -0.7949 +2024-11-22 21:44:10.309483: val_loss -0.7651 +2024-11-22 21:44:10.309633: Pseudo dice [0.863] +2024-11-22 21:44:10.309721: Epoch time: 19.54 s +2024-11-22 21:44:11.237955: +2024-11-22 21:44:11.238167: Epoch 6281 +2024-11-22 21:44:11.238310: Current learning rate: 0.00251 +2024-11-22 21:44:30.832524: train_loss -0.7917 +2024-11-22 21:44:30.833882: val_loss -0.7695 +2024-11-22 21:44:30.833973: Pseudo dice [0.8488] +2024-11-22 21:44:30.834068: Epoch time: 19.6 s +2024-11-22 21:44:32.095457: +2024-11-22 21:44:32.095675: Epoch 6282 +2024-11-22 21:44:32.095818: Current learning rate: 0.0025 +2024-11-22 21:44:51.318960: train_loss -0.798 +2024-11-22 21:44:51.320465: val_loss -0.7798 +2024-11-22 21:44:51.320623: Pseudo dice [0.8709] +2024-11-22 21:44:51.320735: Epoch time: 19.22 s +2024-11-22 21:44:52.341053: +2024-11-22 21:44:52.341498: Epoch 6283 +2024-11-22 21:44:52.341651: Current learning rate: 0.0025 +2024-11-22 21:45:11.704074: train_loss -0.7949 +2024-11-22 21:45:11.705330: val_loss -0.765 +2024-11-22 21:45:11.705463: Pseudo dice [0.846] +2024-11-22 21:45:11.705556: Epoch time: 19.36 s +2024-11-22 21:45:12.587767: +2024-11-22 21:45:12.588241: Epoch 6284 +2024-11-22 21:45:12.588403: Current learning rate: 0.0025 +2024-11-22 21:45:30.956602: train_loss -0.7933 +2024-11-22 21:45:30.960239: val_loss -0.7539 +2024-11-22 21:45:30.960380: Pseudo dice [0.8497] +2024-11-22 21:45:30.960476: Epoch time: 18.37 s +2024-11-22 21:45:31.854945: +2024-11-22 21:45:31.855386: Epoch 6285 +2024-11-22 21:45:31.855519: Current learning rate: 0.0025 +2024-11-22 21:45:51.137985: train_loss -0.7998 +2024-11-22 21:45:51.141785: val_loss -0.7859 +2024-11-22 21:45:51.141910: Pseudo dice [0.8601] +2024-11-22 21:45:51.141999: Epoch time: 19.28 s +2024-11-22 21:45:52.025111: +2024-11-22 21:45:52.025538: Epoch 6286 +2024-11-22 21:45:52.025694: Current learning rate: 0.0025 +2024-11-22 21:46:10.714275: train_loss -0.8018 +2024-11-22 21:46:10.718830: val_loss -0.7849 +2024-11-22 21:46:10.718980: Pseudo dice [0.8638] +2024-11-22 21:46:10.719081: Epoch time: 18.69 s +2024-11-22 21:46:11.603362: +2024-11-22 21:46:11.603808: Epoch 6287 +2024-11-22 21:46:11.603955: Current learning rate: 0.0025 +2024-11-22 21:46:30.379200: train_loss -0.805 +2024-11-22 21:46:30.383532: val_loss -0.788 +2024-11-22 21:46:30.383668: Pseudo dice [0.8601] +2024-11-22 21:46:30.383765: Epoch time: 18.78 s +2024-11-22 21:46:31.257074: +2024-11-22 21:46:31.257486: Epoch 6288 +2024-11-22 21:46:31.257643: Current learning rate: 0.0025 +2024-11-22 21:46:50.129073: train_loss -0.8047 +2024-11-22 21:46:50.149404: val_loss -0.7649 +2024-11-22 21:46:50.149569: Pseudo dice [0.8471] +2024-11-22 21:46:50.149676: Epoch time: 18.87 s +2024-11-22 21:46:51.041219: +2024-11-22 21:46:51.042804: Epoch 6289 +2024-11-22 21:46:51.042946: Current learning rate: 0.0025 +2024-11-22 21:47:10.833724: train_loss -0.8017 +2024-11-22 21:47:10.836698: val_loss -0.7498 +2024-11-22 21:47:10.836857: Pseudo dice [0.8475] +2024-11-22 21:47:10.836972: Epoch time: 19.79 s +2024-11-22 21:47:11.903681: +2024-11-22 21:47:11.905505: Epoch 6290 +2024-11-22 21:47:11.905667: Current learning rate: 0.00249 +2024-11-22 21:47:31.301854: train_loss -0.8122 +2024-11-22 21:47:31.322285: val_loss -0.7833 +2024-11-22 21:47:31.322441: Pseudo dice [0.8626] +2024-11-22 21:47:31.322538: Epoch time: 19.4 s +2024-11-22 21:47:32.479619: +2024-11-22 21:47:32.481847: Epoch 6291 +2024-11-22 21:47:32.482295: Current learning rate: 0.00249 +2024-11-22 21:47:51.669240: train_loss -0.8078 +2024-11-22 21:47:51.680670: val_loss -0.7793 +2024-11-22 21:47:51.680811: Pseudo dice [0.8629] +2024-11-22 21:47:51.680911: Epoch time: 19.19 s +2024-11-22 21:47:52.616589: +2024-11-22 21:47:52.617946: Epoch 6292 +2024-11-22 21:47:52.618107: Current learning rate: 0.00249 +2024-11-22 21:48:11.878768: train_loss -0.8003 +2024-11-22 21:48:11.881423: val_loss -0.8094 +2024-11-22 21:48:11.881542: Pseudo dice [0.8714] +2024-11-22 21:48:11.881649: Epoch time: 19.26 s +2024-11-22 21:48:12.823015: +2024-11-22 21:48:12.834770: Epoch 6293 +2024-11-22 21:48:12.834944: Current learning rate: 0.00249 +2024-11-22 21:48:31.149893: train_loss -0.8012 +2024-11-22 21:48:31.152756: val_loss -0.7938 +2024-11-22 21:48:31.152915: Pseudo dice [0.8599] +2024-11-22 21:48:31.153027: Epoch time: 18.33 s +2024-11-22 21:48:32.425849: +2024-11-22 21:48:32.427257: Epoch 6294 +2024-11-22 21:48:32.427390: Current learning rate: 0.00249 +2024-11-22 21:48:51.561085: train_loss -0.8075 +2024-11-22 21:48:51.575003: val_loss -0.7862 +2024-11-22 21:48:51.575235: Pseudo dice [0.866] +2024-11-22 21:48:51.575366: Epoch time: 19.14 s +2024-11-22 21:48:52.455347: +2024-11-22 21:48:52.456690: Epoch 6295 +2024-11-22 21:48:52.456820: Current learning rate: 0.00249 +2024-11-22 21:49:11.123189: train_loss -0.8098 +2024-11-22 21:49:11.134357: val_loss -0.7725 +2024-11-22 21:49:11.134514: Pseudo dice [0.8506] +2024-11-22 21:49:11.134614: Epoch time: 18.67 s +2024-11-22 21:49:12.182084: +2024-11-22 21:49:12.184001: Epoch 6296 +2024-11-22 21:49:12.184130: Current learning rate: 0.00249 +2024-11-22 21:49:31.948559: train_loss -0.8019 +2024-11-22 21:49:31.962214: val_loss -0.8047 +2024-11-22 21:49:31.962415: Pseudo dice [0.8628] +2024-11-22 21:49:31.962527: Epoch time: 19.77 s +2024-11-22 21:49:32.857505: +2024-11-22 21:49:32.858776: Epoch 6297 +2024-11-22 21:49:32.858904: Current learning rate: 0.00248 +2024-11-22 21:49:51.457073: train_loss -0.8064 +2024-11-22 21:49:51.463417: val_loss -0.7625 +2024-11-22 21:49:51.463572: Pseudo dice [0.8625] +2024-11-22 21:49:51.463684: Epoch time: 18.6 s +2024-11-22 21:49:52.443728: +2024-11-22 21:49:52.445338: Epoch 6298 +2024-11-22 21:49:52.445465: Current learning rate: 0.00248 +2024-11-22 21:50:11.424448: train_loss -0.8032 +2024-11-22 21:50:11.431283: val_loss -0.7577 +2024-11-22 21:50:11.431412: Pseudo dice [0.8442] +2024-11-22 21:50:11.431507: Epoch time: 18.98 s +2024-11-22 21:50:12.441932: +2024-11-22 21:50:12.442344: Epoch 6299 +2024-11-22 21:50:12.442472: Current learning rate: 0.00248 +2024-11-22 21:50:32.389589: train_loss -0.8094 +2024-11-22 21:50:32.397021: val_loss -0.793 +2024-11-22 21:50:32.397174: Pseudo dice [0.8716] +2024-11-22 21:50:32.397277: Epoch time: 19.95 s +2024-11-22 21:50:33.609492: +2024-11-22 21:50:33.610798: Epoch 6300 +2024-11-22 21:50:33.610918: Current learning rate: 0.00248 +2024-11-22 21:50:54.445777: train_loss -0.8062 +2024-11-22 21:50:54.460823: val_loss -0.7781 +2024-11-22 21:50:54.460965: Pseudo dice [0.8669] +2024-11-22 21:50:54.461079: Epoch time: 20.84 s +2024-11-22 21:50:55.463514: +2024-11-22 21:50:55.465433: Epoch 6301 +2024-11-22 21:50:55.465570: Current learning rate: 0.00248 +2024-11-22 21:51:15.314271: train_loss -0.8019 +2024-11-22 21:51:15.320903: val_loss -0.7618 +2024-11-22 21:51:15.321050: Pseudo dice [0.8433] +2024-11-22 21:51:15.321169: Epoch time: 19.85 s +2024-11-22 21:51:16.379881: +2024-11-22 21:51:16.381201: Epoch 6302 +2024-11-22 21:51:16.381324: Current learning rate: 0.00248 +2024-11-22 21:51:35.940285: train_loss -0.801 +2024-11-22 21:51:35.960581: val_loss -0.7606 +2024-11-22 21:51:35.960959: Pseudo dice [0.8609] +2024-11-22 21:51:35.961073: Epoch time: 19.56 s +2024-11-22 21:51:37.080361: +2024-11-22 21:51:37.081645: Epoch 6303 +2024-11-22 21:51:37.081764: Current learning rate: 0.00248 +2024-11-22 21:51:56.513600: train_loss -0.8116 +2024-11-22 21:51:56.525197: val_loss -0.7693 +2024-11-22 21:51:56.525340: Pseudo dice [0.8466] +2024-11-22 21:51:56.525434: Epoch time: 19.43 s +2024-11-22 21:51:57.482263: +2024-11-22 21:51:57.483234: Epoch 6304 +2024-11-22 21:51:57.483383: Current learning rate: 0.00248 +2024-11-22 21:52:17.351142: train_loss -0.8035 +2024-11-22 21:52:17.355649: val_loss -0.7951 +2024-11-22 21:52:17.355798: Pseudo dice [0.8548] +2024-11-22 21:52:17.355941: Epoch time: 19.87 s +2024-11-22 21:52:18.241489: +2024-11-22 21:52:18.242414: Epoch 6305 +2024-11-22 21:52:18.242558: Current learning rate: 0.00247 +2024-11-22 21:52:38.326421: train_loss -0.792 +2024-11-22 21:52:38.329232: val_loss -0.7316 +2024-11-22 21:52:38.329364: Pseudo dice [0.8378] +2024-11-22 21:52:38.329475: Epoch time: 20.09 s +2024-11-22 21:52:39.223970: +2024-11-22 21:52:39.224409: Epoch 6306 +2024-11-22 21:52:39.224540: Current learning rate: 0.00247 +2024-11-22 21:52:59.253941: train_loss -0.7917 +2024-11-22 21:52:59.258696: val_loss -0.7617 +2024-11-22 21:52:59.258844: Pseudo dice [0.8501] +2024-11-22 21:52:59.258943: Epoch time: 20.03 s +2024-11-22 21:53:00.523151: +2024-11-22 21:53:00.524893: Epoch 6307 +2024-11-22 21:53:00.525049: Current learning rate: 0.00247 +2024-11-22 21:53:20.169983: train_loss -0.8019 +2024-11-22 21:53:20.187707: val_loss -0.7827 +2024-11-22 21:53:20.187858: Pseudo dice [0.8675] +2024-11-22 21:53:20.187975: Epoch time: 19.65 s +2024-11-22 21:53:21.269219: +2024-11-22 21:53:21.271545: Epoch 6308 +2024-11-22 21:53:21.271698: Current learning rate: 0.00247 +2024-11-22 21:53:40.941483: train_loss -0.8098 +2024-11-22 21:53:40.953382: val_loss -0.7753 +2024-11-22 21:53:40.953519: Pseudo dice [0.8623] +2024-11-22 21:53:40.953623: Epoch time: 19.67 s +2024-11-22 21:53:41.844801: +2024-11-22 21:53:41.846429: Epoch 6309 +2024-11-22 21:53:41.846584: Current learning rate: 0.00247 +2024-11-22 21:54:01.565910: train_loss -0.8001 +2024-11-22 21:54:01.571475: val_loss -0.7787 +2024-11-22 21:54:01.571616: Pseudo dice [0.8448] +2024-11-22 21:54:01.571730: Epoch time: 19.72 s +2024-11-22 21:54:02.512328: +2024-11-22 21:54:02.513414: Epoch 6310 +2024-11-22 21:54:02.513559: Current learning rate: 0.00247 +2024-11-22 21:54:21.091249: train_loss -0.7958 +2024-11-22 21:54:21.099287: val_loss -0.7377 +2024-11-22 21:54:21.099442: Pseudo dice [0.8397] +2024-11-22 21:54:21.099543: Epoch time: 18.58 s +2024-11-22 21:54:21.980544: +2024-11-22 21:54:21.981619: Epoch 6311 +2024-11-22 21:54:21.981787: Current learning rate: 0.00247 +2024-11-22 21:54:40.296967: train_loss -0.8023 +2024-11-22 21:54:40.305418: val_loss -0.7754 +2024-11-22 21:54:40.305620: Pseudo dice [0.8449] +2024-11-22 21:54:40.305724: Epoch time: 18.32 s +2024-11-22 21:54:41.226304: +2024-11-22 21:54:41.228200: Epoch 6312 +2024-11-22 21:54:41.228357: Current learning rate: 0.00247 +2024-11-22 21:55:00.060010: train_loss -0.7942 +2024-11-22 21:55:00.065916: val_loss -0.7849 +2024-11-22 21:55:00.066033: Pseudo dice [0.853] +2024-11-22 21:55:00.066129: Epoch time: 18.83 s +2024-11-22 21:55:00.960226: +2024-11-22 21:55:00.961275: Epoch 6313 +2024-11-22 21:55:00.961442: Current learning rate: 0.00246 +2024-11-22 21:55:20.624142: train_loss -0.7854 +2024-11-22 21:55:20.630405: val_loss -0.7757 +2024-11-22 21:55:20.630564: Pseudo dice [0.8565] +2024-11-22 21:55:20.630687: Epoch time: 19.66 s +2024-11-22 21:55:21.507603: +2024-11-22 21:55:21.508959: Epoch 6314 +2024-11-22 21:55:21.509111: Current learning rate: 0.00246 +2024-11-22 21:55:39.716896: train_loss -0.7917 +2024-11-22 21:55:39.719222: val_loss -0.7762 +2024-11-22 21:55:39.719328: Pseudo dice [0.8506] +2024-11-22 21:55:39.719481: Epoch time: 18.21 s +2024-11-22 21:55:40.592241: +2024-11-22 21:55:40.593545: Epoch 6315 +2024-11-22 21:55:40.593710: Current learning rate: 0.00246 +2024-11-22 21:55:59.432478: train_loss -0.7993 +2024-11-22 21:55:59.452353: val_loss -0.7752 +2024-11-22 21:55:59.452498: Pseudo dice [0.8473] +2024-11-22 21:55:59.452602: Epoch time: 18.84 s +2024-11-22 21:56:00.494487: +2024-11-22 21:56:00.495131: Epoch 6316 +2024-11-22 21:56:00.495282: Current learning rate: 0.00246 +2024-11-22 21:56:19.641668: train_loss -0.7989 +2024-11-22 21:56:19.644135: val_loss -0.7674 +2024-11-22 21:56:19.644424: Pseudo dice [0.851] +2024-11-22 21:56:19.644517: Epoch time: 19.15 s +2024-11-22 21:56:20.920018: +2024-11-22 21:56:20.921331: Epoch 6317 +2024-11-22 21:56:20.921486: Current learning rate: 0.00246 +2024-11-22 21:56:39.707889: train_loss -0.8046 +2024-11-22 21:56:39.726296: val_loss -0.7828 +2024-11-22 21:56:39.726462: Pseudo dice [0.8522] +2024-11-22 21:56:39.726582: Epoch time: 18.79 s +2024-11-22 21:56:40.741055: +2024-11-22 21:56:40.743439: Epoch 6318 +2024-11-22 21:56:40.743581: Current learning rate: 0.00246 +2024-11-22 21:57:00.179390: train_loss -0.8045 +2024-11-22 21:57:00.184451: val_loss -0.7775 +2024-11-22 21:57:00.184593: Pseudo dice [0.853] +2024-11-22 21:57:00.184697: Epoch time: 19.44 s +2024-11-22 21:57:01.148511: +2024-11-22 21:57:01.150219: Epoch 6319 +2024-11-22 21:57:01.150371: Current learning rate: 0.00246 +2024-11-22 21:57:20.368175: train_loss -0.7906 +2024-11-22 21:57:20.371788: val_loss -0.7716 +2024-11-22 21:57:20.371948: Pseudo dice [0.8318] +2024-11-22 21:57:20.372042: Epoch time: 19.22 s +2024-11-22 21:57:21.284775: +2024-11-22 21:57:21.285931: Epoch 6320 +2024-11-22 21:57:21.286069: Current learning rate: 0.00245 +2024-11-22 21:57:41.344131: train_loss -0.8019 +2024-11-22 21:57:41.350940: val_loss -0.7753 +2024-11-22 21:57:41.351180: Pseudo dice [0.8405] +2024-11-22 21:57:41.351265: Epoch time: 20.06 s +2024-11-22 21:57:42.353377: +2024-11-22 21:57:42.355611: Epoch 6321 +2024-11-22 21:57:42.355760: Current learning rate: 0.00245 +2024-11-22 21:58:02.856266: train_loss -0.8032 +2024-11-22 21:58:02.862752: val_loss -0.7897 +2024-11-22 21:58:02.862919: Pseudo dice [0.8536] +2024-11-22 21:58:02.863033: Epoch time: 20.5 s +2024-11-22 21:58:03.993562: +2024-11-22 21:58:03.995236: Epoch 6322 +2024-11-22 21:58:03.995361: Current learning rate: 0.00245 +2024-11-22 21:58:23.997502: train_loss -0.8032 +2024-11-22 21:58:24.010444: val_loss -0.795 +2024-11-22 21:58:24.010585: Pseudo dice [0.8532] +2024-11-22 21:58:24.010681: Epoch time: 20.0 s +2024-11-22 21:58:25.194993: +2024-11-22 21:58:25.196413: Epoch 6323 +2024-11-22 21:58:25.196536: Current learning rate: 0.00245 +2024-11-22 21:58:45.055961: train_loss -0.8015 +2024-11-22 21:58:45.062619: val_loss -0.7893 +2024-11-22 21:58:45.062790: Pseudo dice [0.8575] +2024-11-22 21:58:45.062958: Epoch time: 19.86 s +2024-11-22 21:58:45.988319: +2024-11-22 21:58:45.989809: Epoch 6324 +2024-11-22 21:58:45.989952: Current learning rate: 0.00245 +2024-11-22 21:59:05.921088: train_loss -0.8038 +2024-11-22 21:59:05.927688: val_loss -0.7678 +2024-11-22 21:59:05.927872: Pseudo dice [0.8562] +2024-11-22 21:59:05.927976: Epoch time: 19.93 s +2024-11-22 21:59:06.830976: +2024-11-22 21:59:06.832071: Epoch 6325 +2024-11-22 21:59:06.832211: Current learning rate: 0.00245 +2024-11-22 21:59:25.898250: train_loss -0.8039 +2024-11-22 21:59:25.902007: val_loss -0.8049 +2024-11-22 21:59:25.902163: Pseudo dice [0.8632] +2024-11-22 21:59:25.902282: Epoch time: 19.07 s +2024-11-22 21:59:26.904067: +2024-11-22 21:59:26.905667: Epoch 6326 +2024-11-22 21:59:26.905804: Current learning rate: 0.00245 +2024-11-22 21:59:45.466572: train_loss -0.8078 +2024-11-22 21:59:45.473158: val_loss -0.784 +2024-11-22 21:59:45.473304: Pseudo dice [0.8462] +2024-11-22 21:59:45.473412: Epoch time: 18.56 s +2024-11-22 21:59:46.408134: +2024-11-22 21:59:46.408992: Epoch 6327 +2024-11-22 21:59:46.409128: Current learning rate: 0.00245 +2024-11-22 22:00:06.849401: train_loss -0.8068 +2024-11-22 22:00:06.851982: val_loss -0.7874 +2024-11-22 22:00:06.852123: Pseudo dice [0.8598] +2024-11-22 22:00:06.852209: Epoch time: 20.44 s +2024-11-22 22:00:08.293674: +2024-11-22 22:00:08.295162: Epoch 6328 +2024-11-22 22:00:08.295299: Current learning rate: 0.00244 +2024-11-22 22:00:27.793484: train_loss -0.8075 +2024-11-22 22:00:27.810838: val_loss -0.7799 +2024-11-22 22:00:27.811347: Pseudo dice [0.8673] +2024-11-22 22:00:27.811525: Epoch time: 19.5 s +2024-11-22 22:00:28.814164: +2024-11-22 22:00:28.815847: Epoch 6329 +2024-11-22 22:00:28.815972: Current learning rate: 0.00244 +2024-11-22 22:00:49.131180: train_loss -0.8129 +2024-11-22 22:00:49.142365: val_loss -0.7815 +2024-11-22 22:00:49.142514: Pseudo dice [0.8644] +2024-11-22 22:00:49.142616: Epoch time: 20.32 s +2024-11-22 22:00:50.127640: +2024-11-22 22:00:50.128963: Epoch 6330 +2024-11-22 22:00:50.129101: Current learning rate: 0.00244 +2024-11-22 22:01:09.242253: train_loss -0.8094 +2024-11-22 22:01:09.264766: val_loss -0.7446 +2024-11-22 22:01:09.264918: Pseudo dice [0.8557] +2024-11-22 22:01:09.265019: Epoch time: 19.12 s +2024-11-22 22:01:10.399879: +2024-11-22 22:01:10.400924: Epoch 6331 +2024-11-22 22:01:10.401048: Current learning rate: 0.00244 +2024-11-22 22:01:31.116941: train_loss -0.799 +2024-11-22 22:01:31.125324: val_loss -0.7851 +2024-11-22 22:01:31.125540: Pseudo dice [0.8522] +2024-11-22 22:01:31.125638: Epoch time: 20.72 s +2024-11-22 22:01:32.032245: +2024-11-22 22:01:32.033397: Epoch 6332 +2024-11-22 22:01:32.033569: Current learning rate: 0.00244 +2024-11-22 22:01:52.264069: train_loss -0.805 +2024-11-22 22:01:52.269649: val_loss -0.8122 +2024-11-22 22:01:52.269787: Pseudo dice [0.863] +2024-11-22 22:01:52.269890: Epoch time: 20.23 s +2024-11-22 22:01:53.193125: +2024-11-22 22:01:53.193964: Epoch 6333 +2024-11-22 22:01:53.194093: Current learning rate: 0.00244 +2024-11-22 22:02:13.206698: train_loss -0.8011 +2024-11-22 22:02:13.210819: val_loss -0.747 +2024-11-22 22:02:13.210975: Pseudo dice [0.8527] +2024-11-22 22:02:13.211151: Epoch time: 20.01 s +2024-11-22 22:02:14.284404: +2024-11-22 22:02:14.286412: Epoch 6334 +2024-11-22 22:02:14.286548: Current learning rate: 0.00244 +2024-11-22 22:02:33.421170: train_loss -0.7993 +2024-11-22 22:02:33.431352: val_loss -0.7845 +2024-11-22 22:02:33.431485: Pseudo dice [0.8463] +2024-11-22 22:02:33.431594: Epoch time: 19.14 s +2024-11-22 22:02:34.487232: +2024-11-22 22:02:34.488319: Epoch 6335 +2024-11-22 22:02:34.488446: Current learning rate: 0.00243 +2024-11-22 22:02:53.795790: train_loss -0.8052 +2024-11-22 22:02:53.811239: val_loss -0.7765 +2024-11-22 22:02:53.811403: Pseudo dice [0.8732] +2024-11-22 22:02:53.811518: Epoch time: 19.31 s +2024-11-22 22:02:54.962076: +2024-11-22 22:02:54.963815: Epoch 6336 +2024-11-22 22:02:54.963949: Current learning rate: 0.00243 +2024-11-22 22:03:15.267267: train_loss -0.8047 +2024-11-22 22:03:15.293833: val_loss -0.7963 +2024-11-22 22:03:15.293960: Pseudo dice [0.863] +2024-11-22 22:03:15.294069: Epoch time: 20.31 s +2024-11-22 22:03:16.282661: +2024-11-22 22:03:16.284743: Epoch 6337 +2024-11-22 22:03:16.284916: Current learning rate: 0.00243 +2024-11-22 22:03:37.856813: train_loss -0.8051 +2024-11-22 22:03:37.862146: val_loss -0.7906 +2024-11-22 22:03:37.862288: Pseudo dice [0.8546] +2024-11-22 22:03:37.862386: Epoch time: 21.57 s +2024-11-22 22:03:38.743801: +2024-11-22 22:03:38.744612: Epoch 6338 +2024-11-22 22:03:38.744745: Current learning rate: 0.00243 +2024-11-22 22:03:58.024166: train_loss -0.8123 +2024-11-22 22:03:58.044116: val_loss -0.7947 +2024-11-22 22:03:58.044301: Pseudo dice [0.8645] +2024-11-22 22:03:58.044420: Epoch time: 19.28 s +2024-11-22 22:03:58.956461: +2024-11-22 22:03:58.957929: Epoch 6339 +2024-11-22 22:03:58.958050: Current learning rate: 0.00243 +2024-11-22 22:04:18.187714: train_loss -0.8098 +2024-11-22 22:04:18.195940: val_loss -0.7756 +2024-11-22 22:04:18.196084: Pseudo dice [0.8571] +2024-11-22 22:04:18.196283: Epoch time: 19.23 s +2024-11-22 22:04:19.752662: +2024-11-22 22:04:19.754500: Epoch 6340 +2024-11-22 22:04:19.754631: Current learning rate: 0.00243 +2024-11-22 22:04:39.135993: train_loss -0.8118 +2024-11-22 22:04:39.142131: val_loss -0.7651 +2024-11-22 22:04:39.142303: Pseudo dice [0.871] +2024-11-22 22:04:39.142395: Epoch time: 19.38 s +2024-11-22 22:04:40.330587: +2024-11-22 22:04:40.332500: Epoch 6341 +2024-11-22 22:04:40.332649: Current learning rate: 0.00243 +2024-11-22 22:05:00.209866: train_loss -0.8111 +2024-11-22 22:05:00.217319: val_loss -0.7591 +2024-11-22 22:05:00.217483: Pseudo dice [0.8502] +2024-11-22 22:05:00.217605: Epoch time: 19.88 s +2024-11-22 22:05:01.228218: +2024-11-22 22:05:01.229452: Epoch 6342 +2024-11-22 22:05:01.229581: Current learning rate: 0.00243 +2024-11-22 22:05:21.849188: train_loss -0.7992 +2024-11-22 22:05:21.851892: val_loss -0.7722 +2024-11-22 22:05:21.852010: Pseudo dice [0.8601] +2024-11-22 22:05:21.852119: Epoch time: 20.62 s +2024-11-22 22:05:22.778220: +2024-11-22 22:05:22.779361: Epoch 6343 +2024-11-22 22:05:22.779501: Current learning rate: 0.00242 +2024-11-22 22:05:42.735882: train_loss -0.8017 +2024-11-22 22:05:42.745332: val_loss -0.7817 +2024-11-22 22:05:42.745458: Pseudo dice [0.8644] +2024-11-22 22:05:42.745560: Epoch time: 19.96 s +2024-11-22 22:05:43.729937: +2024-11-22 22:05:43.730421: Epoch 6344 +2024-11-22 22:05:43.730548: Current learning rate: 0.00242 +2024-11-22 22:06:03.185694: train_loss -0.8106 +2024-11-22 22:06:03.188837: val_loss -0.7777 +2024-11-22 22:06:03.188989: Pseudo dice [0.8585] +2024-11-22 22:06:03.189085: Epoch time: 19.46 s +2024-11-22 22:06:04.119084: +2024-11-22 22:06:04.121167: Epoch 6345 +2024-11-22 22:06:04.121354: Current learning rate: 0.00242 +2024-11-22 22:06:23.036616: train_loss -0.8139 +2024-11-22 22:06:23.046216: val_loss -0.7608 +2024-11-22 22:06:23.046341: Pseudo dice [0.8624] +2024-11-22 22:06:23.046434: Epoch time: 18.92 s +2024-11-22 22:06:24.135845: +2024-11-22 22:06:24.137553: Epoch 6346 +2024-11-22 22:06:24.137684: Current learning rate: 0.00242 +2024-11-22 22:06:43.865866: train_loss -0.8072 +2024-11-22 22:06:43.874118: val_loss -0.8004 +2024-11-22 22:06:43.874260: Pseudo dice [0.8638] +2024-11-22 22:06:43.874354: Epoch time: 19.73 s +2024-11-22 22:06:45.082853: +2024-11-22 22:06:45.084763: Epoch 6347 +2024-11-22 22:06:45.084913: Current learning rate: 0.00242 +2024-11-22 22:07:04.520185: train_loss -0.8099 +2024-11-22 22:07:04.527447: val_loss -0.7629 +2024-11-22 22:07:04.527561: Pseudo dice [0.8505] +2024-11-22 22:07:04.527666: Epoch time: 19.44 s +2024-11-22 22:07:05.626434: +2024-11-22 22:07:05.627356: Epoch 6348 +2024-11-22 22:07:05.627478: Current learning rate: 0.00242 +2024-11-22 22:07:24.810970: train_loss -0.8081 +2024-11-22 22:07:24.820813: val_loss -0.7802 +2024-11-22 22:07:24.820987: Pseudo dice [0.8664] +2024-11-22 22:07:24.821110: Epoch time: 19.19 s +2024-11-22 22:07:25.884901: +2024-11-22 22:07:25.886743: Epoch 6349 +2024-11-22 22:07:25.886898: Current learning rate: 0.00242 +2024-11-22 22:07:44.432526: train_loss -0.8133 +2024-11-22 22:07:44.441124: val_loss -0.7876 +2024-11-22 22:07:44.441232: Pseudo dice [0.8564] +2024-11-22 22:07:44.441312: Epoch time: 18.55 s +2024-11-22 22:07:45.662001: +2024-11-22 22:07:45.662241: Epoch 6350 +2024-11-22 22:07:45.662362: Current learning rate: 0.00242 +2024-11-22 22:08:05.217036: train_loss -0.8158 +2024-11-22 22:08:05.219248: val_loss -0.7813 +2024-11-22 22:08:05.219339: Pseudo dice [0.8517] +2024-11-22 22:08:05.219418: Epoch time: 19.56 s +2024-11-22 22:08:06.084513: +2024-11-22 22:08:06.084751: Epoch 6351 +2024-11-22 22:08:06.084889: Current learning rate: 0.00241 +2024-11-22 22:08:24.994302: train_loss -0.8163 +2024-11-22 22:08:24.999990: val_loss -0.7747 +2024-11-22 22:08:25.000133: Pseudo dice [0.8665] +2024-11-22 22:08:25.000229: Epoch time: 18.91 s +2024-11-22 22:08:25.889393: +2024-11-22 22:08:25.889615: Epoch 6352 +2024-11-22 22:08:25.889762: Current learning rate: 0.00241 +2024-11-22 22:08:44.183896: train_loss -0.808 +2024-11-22 22:08:44.185188: val_loss -0.7699 +2024-11-22 22:08:44.185298: Pseudo dice [0.8493] +2024-11-22 22:08:44.185391: Epoch time: 18.3 s +2024-11-22 22:08:45.056747: +2024-11-22 22:08:45.056978: Epoch 6353 +2024-11-22 22:08:45.057111: Current learning rate: 0.00241 +2024-11-22 22:09:04.695443: train_loss -0.8092 +2024-11-22 22:09:04.695945: val_loss -0.7861 +2024-11-22 22:09:04.696039: Pseudo dice [0.8612] +2024-11-22 22:09:04.696144: Epoch time: 19.64 s +2024-11-22 22:09:05.704574: +2024-11-22 22:09:05.704790: Epoch 6354 +2024-11-22 22:09:05.704912: Current learning rate: 0.00241 +2024-11-22 22:09:23.543465: train_loss -0.8109 +2024-11-22 22:09:23.549289: val_loss -0.7622 +2024-11-22 22:09:23.565723: Pseudo dice [0.8587] +2024-11-22 22:09:23.567412: Epoch time: 17.84 s +2024-11-22 22:09:24.499286: +2024-11-22 22:09:24.499511: Epoch 6355 +2024-11-22 22:09:24.499647: Current learning rate: 0.00241 +2024-11-22 22:09:42.903765: train_loss -0.8099 +2024-11-22 22:09:42.906748: val_loss -0.7737 +2024-11-22 22:09:42.906898: Pseudo dice [0.8626] +2024-11-22 22:09:42.907005: Epoch time: 18.41 s +2024-11-22 22:09:43.786475: +2024-11-22 22:09:43.786678: Epoch 6356 +2024-11-22 22:09:43.786812: Current learning rate: 0.00241 +2024-11-22 22:10:02.944983: train_loss -0.8073 +2024-11-22 22:10:02.950168: val_loss -0.7725 +2024-11-22 22:10:02.950320: Pseudo dice [0.8658] +2024-11-22 22:10:02.950426: Epoch time: 19.16 s +2024-11-22 22:10:03.833129: +2024-11-22 22:10:03.833342: Epoch 6357 +2024-11-22 22:10:03.833461: Current learning rate: 0.00241 +2024-11-22 22:10:22.155212: train_loss -0.8147 +2024-11-22 22:10:22.159601: val_loss -0.7676 +2024-11-22 22:10:22.159729: Pseudo dice [0.8628] +2024-11-22 22:10:22.159813: Epoch time: 18.32 s +2024-11-22 22:10:23.065883: +2024-11-22 22:10:23.066085: Epoch 6358 +2024-11-22 22:10:23.066219: Current learning rate: 0.0024 +2024-11-22 22:10:41.417371: train_loss -0.8091 +2024-11-22 22:10:41.428275: val_loss -0.7813 +2024-11-22 22:10:41.428422: Pseudo dice [0.8564] +2024-11-22 22:10:41.428515: Epoch time: 18.35 s +2024-11-22 22:10:42.350209: +2024-11-22 22:10:42.352093: Epoch 6359 +2024-11-22 22:10:42.352224: Current learning rate: 0.0024 +2024-11-22 22:11:02.172280: train_loss -0.8101 +2024-11-22 22:11:02.174853: val_loss -0.7671 +2024-11-22 22:11:02.174982: Pseudo dice [0.8651] +2024-11-22 22:11:02.175081: Epoch time: 19.81 s +2024-11-22 22:11:03.446893: +2024-11-22 22:11:03.448217: Epoch 6360 +2024-11-22 22:11:03.448355: Current learning rate: 0.0024 +2024-11-22 22:11:23.146479: train_loss -0.8072 +2024-11-22 22:11:23.155008: val_loss -0.7861 +2024-11-22 22:11:23.155144: Pseudo dice [0.8562] +2024-11-22 22:11:23.155237: Epoch time: 19.7 s +2024-11-22 22:11:24.279253: +2024-11-22 22:11:24.281161: Epoch 6361 +2024-11-22 22:11:24.281301: Current learning rate: 0.0024 +2024-11-22 22:11:43.956909: train_loss -0.8039 +2024-11-22 22:11:43.967936: val_loss -0.7817 +2024-11-22 22:11:43.968110: Pseudo dice [0.8446] +2024-11-22 22:11:43.968201: Epoch time: 19.68 s +2024-11-22 22:11:44.862754: +2024-11-22 22:11:44.863611: Epoch 6362 +2024-11-22 22:11:44.863735: Current learning rate: 0.0024 +2024-11-22 22:12:04.884824: train_loss -0.816 +2024-11-22 22:12:04.889784: val_loss -0.795 +2024-11-22 22:12:04.889933: Pseudo dice [0.8549] +2024-11-22 22:12:04.890031: Epoch time: 20.02 s +2024-11-22 22:12:06.315367: +2024-11-22 22:12:06.316653: Epoch 6363 +2024-11-22 22:12:06.316794: Current learning rate: 0.0024 +2024-11-22 22:12:25.849794: train_loss -0.8167 +2024-11-22 22:12:25.852952: val_loss -0.7753 +2024-11-22 22:12:25.853097: Pseudo dice [0.8612] +2024-11-22 22:12:25.853344: Epoch time: 19.54 s +2024-11-22 22:12:26.730692: +2024-11-22 22:12:26.731493: Epoch 6364 +2024-11-22 22:12:26.731614: Current learning rate: 0.0024 +2024-11-22 22:12:47.237526: train_loss -0.8069 +2024-11-22 22:12:47.256301: val_loss -0.7819 +2024-11-22 22:12:47.256513: Pseudo dice [0.8597] +2024-11-22 22:12:47.256658: Epoch time: 20.51 s +2024-11-22 22:12:48.244710: +2024-11-22 22:12:48.246276: Epoch 6365 +2024-11-22 22:12:48.246398: Current learning rate: 0.0024 +2024-11-22 22:13:07.896439: train_loss -0.8017 +2024-11-22 22:13:07.898503: val_loss -0.7687 +2024-11-22 22:13:07.898626: Pseudo dice [0.8636] +2024-11-22 22:13:07.898726: Epoch time: 19.65 s +2024-11-22 22:13:08.786230: +2024-11-22 22:13:08.787741: Epoch 6366 +2024-11-22 22:13:08.787873: Current learning rate: 0.00239 +2024-11-22 22:13:28.267761: train_loss -0.812 +2024-11-22 22:13:28.278364: val_loss -0.7613 +2024-11-22 22:13:28.278567: Pseudo dice [0.8494] +2024-11-22 22:13:28.278680: Epoch time: 19.48 s +2024-11-22 22:13:29.267953: +2024-11-22 22:13:29.268713: Epoch 6367 +2024-11-22 22:13:29.268851: Current learning rate: 0.00239 +2024-11-22 22:13:48.686438: train_loss -0.8155 +2024-11-22 22:13:48.692984: val_loss -0.7576 +2024-11-22 22:13:48.693237: Pseudo dice [0.8474] +2024-11-22 22:13:48.693343: Epoch time: 19.42 s +2024-11-22 22:13:49.805984: +2024-11-22 22:13:49.807543: Epoch 6368 +2024-11-22 22:13:49.807667: Current learning rate: 0.00239 +2024-11-22 22:14:08.083749: train_loss -0.8194 +2024-11-22 22:14:08.096979: val_loss -0.7873 +2024-11-22 22:14:08.097180: Pseudo dice [0.8606] +2024-11-22 22:14:08.097275: Epoch time: 18.28 s +2024-11-22 22:14:09.072234: +2024-11-22 22:14:09.073550: Epoch 6369 +2024-11-22 22:14:09.073680: Current learning rate: 0.00239 +2024-11-22 22:14:29.277469: train_loss -0.8109 +2024-11-22 22:14:29.283624: val_loss -0.7742 +2024-11-22 22:14:29.283772: Pseudo dice [0.8647] +2024-11-22 22:14:29.283873: Epoch time: 20.21 s +2024-11-22 22:14:30.281741: +2024-11-22 22:14:30.283468: Epoch 6370 +2024-11-22 22:14:30.283605: Current learning rate: 0.00239 +2024-11-22 22:14:48.828460: train_loss -0.815 +2024-11-22 22:14:48.831202: val_loss -0.7841 +2024-11-22 22:14:48.831352: Pseudo dice [0.8612] +2024-11-22 22:14:48.831449: Epoch time: 18.55 s +2024-11-22 22:14:49.712974: +2024-11-22 22:14:49.714050: Epoch 6371 +2024-11-22 22:14:49.714192: Current learning rate: 0.00239 +2024-11-22 22:15:09.216633: train_loss -0.8117 +2024-11-22 22:15:09.218777: val_loss -0.7975 +2024-11-22 22:15:09.218892: Pseudo dice [0.8716] +2024-11-22 22:15:09.218999: Epoch time: 19.5 s +2024-11-22 22:15:10.118961: +2024-11-22 22:15:10.120037: Epoch 6372 +2024-11-22 22:15:10.120168: Current learning rate: 0.00239 +2024-11-22 22:15:29.504775: train_loss -0.8128 +2024-11-22 22:15:29.514388: val_loss -0.7735 +2024-11-22 22:15:29.514540: Pseudo dice [0.8686] +2024-11-22 22:15:29.514645: Epoch time: 19.39 s +2024-11-22 22:15:30.436567: +2024-11-22 22:15:30.437626: Epoch 6373 +2024-11-22 22:15:30.437766: Current learning rate: 0.00238 +2024-11-22 22:15:48.593652: train_loss -0.8131 +2024-11-22 22:15:48.595879: val_loss -0.7873 +2024-11-22 22:15:48.596009: Pseudo dice [0.8754] +2024-11-22 22:15:48.596122: Epoch time: 18.16 s +2024-11-22 22:15:49.575271: +2024-11-22 22:15:49.576667: Epoch 6374 +2024-11-22 22:15:49.576788: Current learning rate: 0.00238 +2024-11-22 22:16:09.765273: train_loss -0.8141 +2024-11-22 22:16:09.776908: val_loss -0.7862 +2024-11-22 22:16:09.777055: Pseudo dice [0.8661] +2024-11-22 22:16:09.777170: Epoch time: 20.19 s +2024-11-22 22:16:09.777250: Yayy! New best EMA pseudo Dice: 0.8624 +2024-11-22 22:16:11.059895: +2024-11-22 22:16:11.061502: Epoch 6375 +2024-11-22 22:16:11.061634: Current learning rate: 0.00238 +2024-11-22 22:16:31.069129: train_loss -0.8134 +2024-11-22 22:16:31.075247: val_loss -0.7914 +2024-11-22 22:16:31.075379: Pseudo dice [0.8683] +2024-11-22 22:16:31.075482: Epoch time: 20.01 s +2024-11-22 22:16:31.075575: Yayy! New best EMA pseudo Dice: 0.863 +2024-11-22 22:16:32.297092: +2024-11-22 22:16:32.298087: Epoch 6376 +2024-11-22 22:16:32.298207: Current learning rate: 0.00238 +2024-11-22 22:16:51.269724: train_loss -0.8118 +2024-11-22 22:16:51.277315: val_loss -0.7784 +2024-11-22 22:16:51.277460: Pseudo dice [0.8567] +2024-11-22 22:16:51.277571: Epoch time: 18.97 s +2024-11-22 22:16:52.178988: +2024-11-22 22:16:52.179978: Epoch 6377 +2024-11-22 22:16:52.180120: Current learning rate: 0.00238 +2024-11-22 22:17:11.699945: train_loss -0.8105 +2024-11-22 22:17:11.710120: val_loss -0.7829 +2024-11-22 22:17:11.710267: Pseudo dice [0.8702] +2024-11-22 22:17:11.710366: Epoch time: 19.52 s +2024-11-22 22:17:11.710480: Yayy! New best EMA pseudo Dice: 0.8632 +2024-11-22 22:17:12.915510: +2024-11-22 22:17:12.916997: Epoch 6378 +2024-11-22 22:17:12.917130: Current learning rate: 0.00238 +2024-11-22 22:17:32.646033: train_loss -0.8095 +2024-11-22 22:17:32.664174: val_loss -0.7873 +2024-11-22 22:17:32.664338: Pseudo dice [0.8613] +2024-11-22 22:17:32.664458: Epoch time: 19.73 s +2024-11-22 22:17:33.767364: +2024-11-22 22:17:33.768391: Epoch 6379 +2024-11-22 22:17:33.768515: Current learning rate: 0.00238 +2024-11-22 22:17:53.030073: train_loss -0.8128 +2024-11-22 22:17:53.034506: val_loss -0.7579 +2024-11-22 22:17:53.034644: Pseudo dice [0.8449] +2024-11-22 22:17:53.035035: Epoch time: 19.26 s +2024-11-22 22:17:54.181601: +2024-11-22 22:17:54.183033: Epoch 6380 +2024-11-22 22:17:54.183192: Current learning rate: 0.00238 +2024-11-22 22:18:13.722472: train_loss -0.8034 +2024-11-22 22:18:13.729232: val_loss -0.7755 +2024-11-22 22:18:13.729367: Pseudo dice [0.8521] +2024-11-22 22:18:13.729461: Epoch time: 19.54 s +2024-11-22 22:18:14.646082: +2024-11-22 22:18:14.647626: Epoch 6381 +2024-11-22 22:18:14.647763: Current learning rate: 0.00237 +2024-11-22 22:18:34.242928: train_loss -0.8062 +2024-11-22 22:18:34.257843: val_loss -0.7742 +2024-11-22 22:18:34.258020: Pseudo dice [0.8482] +2024-11-22 22:18:34.258154: Epoch time: 19.6 s +2024-11-22 22:18:35.287179: +2024-11-22 22:18:35.288751: Epoch 6382 +2024-11-22 22:18:35.288890: Current learning rate: 0.00237 +2024-11-22 22:18:54.239140: train_loss -0.812 +2024-11-22 22:18:54.247210: val_loss -0.7987 +2024-11-22 22:18:54.247361: Pseudo dice [0.8622] +2024-11-22 22:18:54.247463: Epoch time: 18.95 s +2024-11-22 22:18:55.242868: +2024-11-22 22:18:55.244822: Epoch 6383 +2024-11-22 22:18:55.244951: Current learning rate: 0.00237 +2024-11-22 22:19:14.622534: train_loss -0.8125 +2024-11-22 22:19:14.624883: val_loss -0.7942 +2024-11-22 22:19:14.625004: Pseudo dice [0.8606] +2024-11-22 22:19:14.625130: Epoch time: 19.38 s +2024-11-22 22:19:15.509066: +2024-11-22 22:19:15.510944: Epoch 6384 +2024-11-22 22:19:15.511074: Current learning rate: 0.00237 +2024-11-22 22:19:35.932572: train_loss -0.8182 +2024-11-22 22:19:35.943459: val_loss -0.7763 +2024-11-22 22:19:35.943617: Pseudo dice [0.8517] +2024-11-22 22:19:35.943708: Epoch time: 20.42 s +2024-11-22 22:19:37.527794: +2024-11-22 22:19:37.529430: Epoch 6385 +2024-11-22 22:19:37.529559: Current learning rate: 0.00237 +2024-11-22 22:19:56.710426: train_loss -0.8094 +2024-11-22 22:19:56.718986: val_loss -0.7928 +2024-11-22 22:19:56.719147: Pseudo dice [0.8582] +2024-11-22 22:19:56.719246: Epoch time: 19.18 s +2024-11-22 22:19:57.679419: +2024-11-22 22:19:57.680156: Epoch 6386 +2024-11-22 22:19:57.680283: Current learning rate: 0.00237 +2024-11-22 22:20:15.899784: train_loss -0.8077 +2024-11-22 22:20:15.906163: val_loss -0.7869 +2024-11-22 22:20:15.906317: Pseudo dice [0.8647] +2024-11-22 22:20:15.906423: Epoch time: 18.22 s +2024-11-22 22:20:16.929686: +2024-11-22 22:20:16.931055: Epoch 6387 +2024-11-22 22:20:16.931206: Current learning rate: 0.00237 +2024-11-22 22:20:35.721264: train_loss -0.8099 +2024-11-22 22:20:35.728620: val_loss -0.7767 +2024-11-22 22:20:35.728773: Pseudo dice [0.8503] +2024-11-22 22:20:35.728876: Epoch time: 18.79 s +2024-11-22 22:20:36.710565: +2024-11-22 22:20:36.712110: Epoch 6388 +2024-11-22 22:20:36.712240: Current learning rate: 0.00237 +2024-11-22 22:20:56.235755: train_loss -0.7994 +2024-11-22 22:20:56.242127: val_loss -0.7775 +2024-11-22 22:20:56.242274: Pseudo dice [0.8558] +2024-11-22 22:20:56.242378: Epoch time: 19.53 s +2024-11-22 22:20:57.387283: +2024-11-22 22:20:57.388595: Epoch 6389 +2024-11-22 22:20:57.388716: Current learning rate: 0.00236 +2024-11-22 22:21:16.475006: train_loss -0.8182 +2024-11-22 22:21:16.483924: val_loss -0.7944 +2024-11-22 22:21:16.484172: Pseudo dice [0.869] +2024-11-22 22:21:16.484291: Epoch time: 19.09 s +2024-11-22 22:21:17.504233: +2024-11-22 22:21:17.504732: Epoch 6390 +2024-11-22 22:21:17.504880: Current learning rate: 0.00236 +2024-11-22 22:21:35.977488: train_loss -0.8028 +2024-11-22 22:21:35.985542: val_loss -0.7708 +2024-11-22 22:21:35.985666: Pseudo dice [0.8481] +2024-11-22 22:21:35.985756: Epoch time: 18.47 s +2024-11-22 22:21:36.954866: +2024-11-22 22:21:36.955971: Epoch 6391 +2024-11-22 22:21:36.956116: Current learning rate: 0.00236 +2024-11-22 22:21:55.427295: train_loss -0.8134 +2024-11-22 22:21:55.429825: val_loss -0.7692 +2024-11-22 22:21:55.429953: Pseudo dice [0.8598] +2024-11-22 22:21:55.430046: Epoch time: 18.47 s +2024-11-22 22:21:56.312174: +2024-11-22 22:21:56.312612: Epoch 6392 +2024-11-22 22:21:56.312944: Current learning rate: 0.00236 +2024-11-22 22:22:16.369992: train_loss -0.8055 +2024-11-22 22:22:16.375182: val_loss -0.7556 +2024-11-22 22:22:16.375328: Pseudo dice [0.8516] +2024-11-22 22:22:16.375505: Epoch time: 20.06 s +2024-11-22 22:22:17.390448: +2024-11-22 22:22:17.392186: Epoch 6393 +2024-11-22 22:22:17.392325: Current learning rate: 0.00236 +2024-11-22 22:22:38.673589: train_loss -0.8106 +2024-11-22 22:22:38.701270: val_loss -0.7843 +2024-11-22 22:22:38.701449: Pseudo dice [0.8575] +2024-11-22 22:22:38.701542: Epoch time: 21.28 s +2024-11-22 22:22:39.746867: +2024-11-22 22:22:39.748614: Epoch 6394 +2024-11-22 22:22:39.748738: Current learning rate: 0.00236 +2024-11-22 22:22:59.557051: train_loss -0.8143 +2024-11-22 22:22:59.560905: val_loss -0.7745 +2024-11-22 22:22:59.561056: Pseudo dice [0.8586] +2024-11-22 22:22:59.561295: Epoch time: 19.81 s +2024-11-22 22:23:00.599471: +2024-11-22 22:23:00.601019: Epoch 6395 +2024-11-22 22:23:00.601169: Current learning rate: 0.00236 +2024-11-22 22:23:19.845130: train_loss -0.8115 +2024-11-22 22:23:19.861789: val_loss -0.7879 +2024-11-22 22:23:19.861932: Pseudo dice [0.8703] +2024-11-22 22:23:19.862052: Epoch time: 19.25 s +2024-11-22 22:23:21.152737: +2024-11-22 22:23:21.154405: Epoch 6396 +2024-11-22 22:23:21.154531: Current learning rate: 0.00235 +2024-11-22 22:23:39.495711: train_loss -0.8151 +2024-11-22 22:23:39.502048: val_loss -0.7937 +2024-11-22 22:23:39.502253: Pseudo dice [0.8661] +2024-11-22 22:23:39.502377: Epoch time: 18.34 s +2024-11-22 22:23:40.503362: +2024-11-22 22:23:40.505390: Epoch 6397 +2024-11-22 22:23:40.505517: Current learning rate: 0.00235 +2024-11-22 22:24:00.317910: train_loss -0.8024 +2024-11-22 22:24:00.332400: val_loss -0.7943 +2024-11-22 22:24:00.332556: Pseudo dice [0.8551] +2024-11-22 22:24:00.332663: Epoch time: 19.82 s +2024-11-22 22:24:01.340141: +2024-11-22 22:24:01.341607: Epoch 6398 +2024-11-22 22:24:01.341734: Current learning rate: 0.00235 +2024-11-22 22:24:22.094090: train_loss -0.8057 +2024-11-22 22:24:22.099910: val_loss -0.766 +2024-11-22 22:24:22.100021: Pseudo dice [0.8649] +2024-11-22 22:24:22.100126: Epoch time: 20.75 s +2024-11-22 22:24:23.073006: +2024-11-22 22:24:23.073766: Epoch 6399 +2024-11-22 22:24:23.073886: Current learning rate: 0.00235 +2024-11-22 22:24:42.294008: train_loss -0.8066 +2024-11-22 22:24:42.296637: val_loss -0.7804 +2024-11-22 22:24:42.296808: Pseudo dice [0.8595] +2024-11-22 22:24:42.296913: Epoch time: 19.22 s +2024-11-22 22:24:43.495190: +2024-11-22 22:24:43.497221: Epoch 6400 +2024-11-22 22:24:43.497386: Current learning rate: 0.00235 +2024-11-22 22:25:02.581300: train_loss -0.8101 +2024-11-22 22:25:02.589035: val_loss -0.7547 +2024-11-22 22:25:02.589217: Pseudo dice [0.8487] +2024-11-22 22:25:02.589304: Epoch time: 19.09 s +2024-11-22 22:25:03.710705: +2024-11-22 22:25:03.712227: Epoch 6401 +2024-11-22 22:25:03.712367: Current learning rate: 0.00235 +2024-11-22 22:25:24.029348: train_loss -0.8066 +2024-11-22 22:25:24.035463: val_loss -0.7826 +2024-11-22 22:25:24.035604: Pseudo dice [0.8661] +2024-11-22 22:25:24.035698: Epoch time: 20.32 s +2024-11-22 22:25:24.943907: +2024-11-22 22:25:24.944681: Epoch 6402 +2024-11-22 22:25:24.944809: Current learning rate: 0.00235 +2024-11-22 22:25:46.327005: train_loss -0.7977 +2024-11-22 22:25:46.333718: val_loss -0.7693 +2024-11-22 22:25:46.333836: Pseudo dice [0.8566] +2024-11-22 22:25:46.333943: Epoch time: 21.38 s +2024-11-22 22:25:47.493237: +2024-11-22 22:25:47.494591: Epoch 6403 +2024-11-22 22:25:47.494723: Current learning rate: 0.00235 +2024-11-22 22:26:08.215240: train_loss -0.8053 +2024-11-22 22:26:08.222093: val_loss -0.7651 +2024-11-22 22:26:08.222236: Pseudo dice [0.8687] +2024-11-22 22:26:08.222341: Epoch time: 20.72 s +2024-11-22 22:26:09.214018: +2024-11-22 22:26:09.215126: Epoch 6404 +2024-11-22 22:26:09.215261: Current learning rate: 0.00234 +2024-11-22 22:26:28.280428: train_loss -0.8097 +2024-11-22 22:26:28.285796: val_loss -0.7626 +2024-11-22 22:26:28.285939: Pseudo dice [0.8394] +2024-11-22 22:26:28.286248: Epoch time: 19.07 s +2024-11-22 22:26:29.187640: +2024-11-22 22:26:29.188783: Epoch 6405 +2024-11-22 22:26:29.188927: Current learning rate: 0.00234 +2024-11-22 22:26:48.363127: train_loss -0.8005 +2024-11-22 22:26:48.376926: val_loss -0.7748 +2024-11-22 22:26:48.377097: Pseudo dice [0.8448] +2024-11-22 22:26:48.377414: Epoch time: 19.18 s +2024-11-22 22:26:49.517045: +2024-11-22 22:26:49.517834: Epoch 6406 +2024-11-22 22:26:49.517986: Current learning rate: 0.00234 +2024-11-22 22:27:08.420775: train_loss -0.8013 +2024-11-22 22:27:08.427163: val_loss -0.7657 +2024-11-22 22:27:08.427312: Pseudo dice [0.8552] +2024-11-22 22:27:08.427458: Epoch time: 18.9 s +2024-11-22 22:27:09.331958: +2024-11-22 22:27:09.333072: Epoch 6407 +2024-11-22 22:27:09.333221: Current learning rate: 0.00234 +2024-11-22 22:27:28.952679: train_loss -0.7851 +2024-11-22 22:27:28.961304: val_loss -0.7866 +2024-11-22 22:27:28.961450: Pseudo dice [0.852] +2024-11-22 22:27:28.961553: Epoch time: 19.62 s +2024-11-22 22:27:30.336299: +2024-11-22 22:27:30.337937: Epoch 6408 +2024-11-22 22:27:30.338072: Current learning rate: 0.00234 +2024-11-22 22:27:49.449980: train_loss -0.7759 +2024-11-22 22:27:49.452669: val_loss -0.7554 +2024-11-22 22:27:49.452805: Pseudo dice [0.8473] +2024-11-22 22:27:49.452918: Epoch time: 19.11 s +2024-11-22 22:27:50.395540: +2024-11-22 22:27:50.396283: Epoch 6409 +2024-11-22 22:27:50.396411: Current learning rate: 0.00234 +2024-11-22 22:28:09.686960: train_loss -0.794 +2024-11-22 22:28:09.695252: val_loss -0.7653 +2024-11-22 22:28:09.695397: Pseudo dice [0.8426] +2024-11-22 22:28:09.695524: Epoch time: 19.29 s +2024-11-22 22:28:10.647980: +2024-11-22 22:28:10.649775: Epoch 6410 +2024-11-22 22:28:10.649914: Current learning rate: 0.00234 +2024-11-22 22:28:28.903803: train_loss -0.7919 +2024-11-22 22:28:28.912437: val_loss -0.759 +2024-11-22 22:28:28.912585: Pseudo dice [0.8497] +2024-11-22 22:28:28.912695: Epoch time: 18.26 s +2024-11-22 22:28:29.990613: +2024-11-22 22:28:29.992078: Epoch 6411 +2024-11-22 22:28:29.992204: Current learning rate: 0.00233 +2024-11-22 22:28:47.654499: train_loss -0.7885 +2024-11-22 22:28:47.665805: val_loss -0.7632 +2024-11-22 22:28:47.665987: Pseudo dice [0.8519] +2024-11-22 22:28:47.666104: Epoch time: 17.66 s +2024-11-22 22:28:48.587099: +2024-11-22 22:28:48.588055: Epoch 6412 +2024-11-22 22:28:48.588179: Current learning rate: 0.00233 +2024-11-22 22:29:07.887107: train_loss -0.802 +2024-11-22 22:29:07.900485: val_loss -0.7636 +2024-11-22 22:29:07.900704: Pseudo dice [0.8478] +2024-11-22 22:29:07.900800: Epoch time: 19.3 s +2024-11-22 22:29:08.935569: +2024-11-22 22:29:08.936857: Epoch 6413 +2024-11-22 22:29:08.936982: Current learning rate: 0.00233 +2024-11-22 22:29:28.401401: train_loss -0.7981 +2024-11-22 22:29:28.408251: val_loss -0.7714 +2024-11-22 22:29:28.408400: Pseudo dice [0.866] +2024-11-22 22:29:28.408568: Epoch time: 19.47 s +2024-11-22 22:29:29.501207: +2024-11-22 22:29:29.503154: Epoch 6414 +2024-11-22 22:29:29.503288: Current learning rate: 0.00233 +2024-11-22 22:29:49.166709: train_loss -0.8019 +2024-11-22 22:29:49.176137: val_loss -0.7921 +2024-11-22 22:29:49.176287: Pseudo dice [0.859] +2024-11-22 22:29:49.176397: Epoch time: 19.67 s +2024-11-22 22:29:50.061932: +2024-11-22 22:29:50.062699: Epoch 6415 +2024-11-22 22:29:50.062832: Current learning rate: 0.00233 +2024-11-22 22:30:09.487378: train_loss -0.8085 +2024-11-22 22:30:09.495668: val_loss -0.7964 +2024-11-22 22:30:09.495788: Pseudo dice [0.8675] +2024-11-22 22:30:09.495951: Epoch time: 19.43 s +2024-11-22 22:30:10.522570: +2024-11-22 22:30:10.524894: Epoch 6416 +2024-11-22 22:30:10.525038: Current learning rate: 0.00233 +2024-11-22 22:30:30.983972: train_loss -0.8008 +2024-11-22 22:30:30.994574: val_loss -0.7934 +2024-11-22 22:30:30.994721: Pseudo dice [0.8586] +2024-11-22 22:30:30.994840: Epoch time: 20.46 s +2024-11-22 22:30:32.097784: +2024-11-22 22:30:32.099433: Epoch 6417 +2024-11-22 22:30:32.099556: Current learning rate: 0.00233 +2024-11-22 22:30:52.238724: train_loss -0.8006 +2024-11-22 22:30:52.244101: val_loss -0.7723 +2024-11-22 22:30:52.244230: Pseudo dice [0.8705] +2024-11-22 22:30:52.244405: Epoch time: 20.14 s +2024-11-22 22:30:53.297282: +2024-11-22 22:30:53.299345: Epoch 6418 +2024-11-22 22:30:53.299484: Current learning rate: 0.00233 +2024-11-22 22:31:12.881567: train_loss -0.8082 +2024-11-22 22:31:12.885579: val_loss -0.789 +2024-11-22 22:31:12.885796: Pseudo dice [0.8606] +2024-11-22 22:31:12.885899: Epoch time: 19.58 s +2024-11-22 22:31:14.407105: +2024-11-22 22:31:14.408322: Epoch 6419 +2024-11-22 22:31:14.408442: Current learning rate: 0.00232 +2024-11-22 22:31:33.023000: train_loss -0.8175 +2024-11-22 22:31:33.029599: val_loss -0.7902 +2024-11-22 22:31:33.029783: Pseudo dice [0.8695] +2024-11-22 22:31:33.029889: Epoch time: 18.62 s +2024-11-22 22:31:33.937011: +2024-11-22 22:31:33.938342: Epoch 6420 +2024-11-22 22:31:33.938503: Current learning rate: 0.00232 +2024-11-22 22:31:53.058438: train_loss -0.8118 +2024-11-22 22:31:53.065259: val_loss -0.7925 +2024-11-22 22:31:53.065391: Pseudo dice [0.8562] +2024-11-22 22:31:53.065487: Epoch time: 19.12 s +2024-11-22 22:31:54.006758: +2024-11-22 22:31:54.007215: Epoch 6421 +2024-11-22 22:31:54.007371: Current learning rate: 0.00232 +2024-11-22 22:32:12.526634: train_loss -0.8113 +2024-11-22 22:32:12.534113: val_loss -0.7757 +2024-11-22 22:32:12.534269: Pseudo dice [0.8549] +2024-11-22 22:32:12.534375: Epoch time: 18.52 s +2024-11-22 22:32:13.571159: +2024-11-22 22:32:13.571600: Epoch 6422 +2024-11-22 22:32:13.571744: Current learning rate: 0.00232 +2024-11-22 22:32:31.874476: train_loss -0.8052 +2024-11-22 22:32:31.887352: val_loss -0.7632 +2024-11-22 22:32:31.887508: Pseudo dice [0.8401] +2024-11-22 22:32:31.887601: Epoch time: 18.3 s +2024-11-22 22:32:32.946016: +2024-11-22 22:32:32.946462: Epoch 6423 +2024-11-22 22:32:32.946612: Current learning rate: 0.00232 +2024-11-22 22:32:52.460827: train_loss -0.7998 +2024-11-22 22:32:52.461343: val_loss -0.7817 +2024-11-22 22:32:52.461489: Pseudo dice [0.8455] +2024-11-22 22:32:52.461584: Epoch time: 19.52 s +2024-11-22 22:32:53.341431: +2024-11-22 22:32:53.341852: Epoch 6424 +2024-11-22 22:32:53.341988: Current learning rate: 0.00232 +2024-11-22 22:33:11.411244: train_loss -0.7997 +2024-11-22 22:33:11.419657: val_loss -0.7847 +2024-11-22 22:33:11.419762: Pseudo dice [0.8446] +2024-11-22 22:33:11.419855: Epoch time: 18.07 s +2024-11-22 22:33:12.297751: +2024-11-22 22:33:12.298177: Epoch 6425 +2024-11-22 22:33:12.298322: Current learning rate: 0.00232 +2024-11-22 22:33:31.686303: train_loss -0.7943 +2024-11-22 22:33:31.688752: val_loss -0.7501 +2024-11-22 22:33:31.688886: Pseudo dice [0.8407] +2024-11-22 22:33:31.688982: Epoch time: 19.39 s +2024-11-22 22:33:32.663093: +2024-11-22 22:33:32.663504: Epoch 6426 +2024-11-22 22:33:32.663658: Current learning rate: 0.00231 +2024-11-22 22:33:51.145938: train_loss -0.8008 +2024-11-22 22:33:51.153038: val_loss -0.7493 +2024-11-22 22:33:51.153181: Pseudo dice [0.8507] +2024-11-22 22:33:51.153295: Epoch time: 18.48 s +2024-11-22 22:33:52.174308: +2024-11-22 22:33:52.174731: Epoch 6427 +2024-11-22 22:33:52.174880: Current learning rate: 0.00231 +2024-11-22 22:34:10.749928: train_loss -0.8015 +2024-11-22 22:34:10.752540: val_loss -0.7866 +2024-11-22 22:34:10.752679: Pseudo dice [0.8575] +2024-11-22 22:34:10.752789: Epoch time: 18.58 s +2024-11-22 22:34:11.677110: +2024-11-22 22:34:11.677526: Epoch 6428 +2024-11-22 22:34:11.677661: Current learning rate: 0.00231 +2024-11-22 22:34:30.019922: train_loss -0.8132 +2024-11-22 22:34:30.020883: val_loss -0.7839 +2024-11-22 22:34:30.021016: Pseudo dice [0.8553] +2024-11-22 22:34:30.021115: Epoch time: 18.34 s +2024-11-22 22:34:31.069176: +2024-11-22 22:34:31.069578: Epoch 6429 +2024-11-22 22:34:31.069721: Current learning rate: 0.00231 +2024-11-22 22:34:50.561980: train_loss -0.8089 +2024-11-22 22:34:50.569869: val_loss -0.7885 +2024-11-22 22:34:50.570027: Pseudo dice [0.8499] +2024-11-22 22:34:50.570147: Epoch time: 19.49 s +2024-11-22 22:34:51.486691: +2024-11-22 22:34:51.487338: Epoch 6430 +2024-11-22 22:34:51.487721: Current learning rate: 0.00231 +2024-11-22 22:35:11.626695: train_loss -0.798 +2024-11-22 22:35:11.633260: val_loss -0.7822 +2024-11-22 22:35:11.633415: Pseudo dice [0.8472] +2024-11-22 22:35:11.633515: Epoch time: 20.14 s +2024-11-22 22:35:12.957790: +2024-11-22 22:35:12.958797: Epoch 6431 +2024-11-22 22:35:12.958951: Current learning rate: 0.00231 +2024-11-22 22:35:31.355895: train_loss -0.8079 +2024-11-22 22:35:31.360673: val_loss -0.7877 +2024-11-22 22:35:31.361028: Pseudo dice [0.8578] +2024-11-22 22:35:31.361141: Epoch time: 18.4 s +2024-11-22 22:35:32.425024: +2024-11-22 22:35:32.425954: Epoch 6432 +2024-11-22 22:35:32.426101: Current learning rate: 0.00231 +2024-11-22 22:35:51.772033: train_loss -0.8141 +2024-11-22 22:35:51.779552: val_loss -0.7801 +2024-11-22 22:35:51.779679: Pseudo dice [0.8529] +2024-11-22 22:35:51.779851: Epoch time: 19.35 s +2024-11-22 22:35:52.823151: +2024-11-22 22:35:52.823844: Epoch 6433 +2024-11-22 22:35:52.823994: Current learning rate: 0.00231 +2024-11-22 22:36:12.687492: train_loss -0.802 +2024-11-22 22:36:12.695496: val_loss -0.7651 +2024-11-22 22:36:12.695618: Pseudo dice [0.871] +2024-11-22 22:36:12.695725: Epoch time: 19.87 s +2024-11-22 22:36:13.627775: +2024-11-22 22:36:13.628730: Epoch 6434 +2024-11-22 22:36:13.628889: Current learning rate: 0.0023 +2024-11-22 22:36:32.552041: train_loss -0.8124 +2024-11-22 22:36:32.563656: val_loss -0.7681 +2024-11-22 22:36:32.563799: Pseudo dice [0.8568] +2024-11-22 22:36:32.563918: Epoch time: 18.93 s +2024-11-22 22:36:33.484820: +2024-11-22 22:36:33.486541: Epoch 6435 +2024-11-22 22:36:33.486698: Current learning rate: 0.0023 +2024-11-22 22:36:53.325926: train_loss -0.8077 +2024-11-22 22:36:53.330121: val_loss -0.7749 +2024-11-22 22:36:53.330242: Pseudo dice [0.8623] +2024-11-22 22:36:53.330336: Epoch time: 19.84 s +2024-11-22 22:36:54.356888: +2024-11-22 22:36:54.358435: Epoch 6436 +2024-11-22 22:36:54.358581: Current learning rate: 0.0023 +2024-11-22 22:37:14.442787: train_loss -0.8123 +2024-11-22 22:37:14.445164: val_loss -0.7789 +2024-11-22 22:37:14.445288: Pseudo dice [0.8641] +2024-11-22 22:37:14.445384: Epoch time: 20.09 s +2024-11-22 22:37:15.324625: +2024-11-22 22:37:15.325671: Epoch 6437 +2024-11-22 22:37:15.325814: Current learning rate: 0.0023 +2024-11-22 22:37:34.372014: train_loss -0.8074 +2024-11-22 22:37:34.378196: val_loss -0.7798 +2024-11-22 22:37:34.378317: Pseudo dice [0.8549] +2024-11-22 22:37:34.378412: Epoch time: 19.05 s +2024-11-22 22:37:35.267303: +2024-11-22 22:37:35.268602: Epoch 6438 +2024-11-22 22:37:35.268759: Current learning rate: 0.0023 +2024-11-22 22:37:53.784855: train_loss -0.8057 +2024-11-22 22:37:53.799235: val_loss -0.7888 +2024-11-22 22:37:53.799474: Pseudo dice [0.8641] +2024-11-22 22:37:53.799595: Epoch time: 18.52 s +2024-11-22 22:37:54.896464: +2024-11-22 22:37:54.898225: Epoch 6439 +2024-11-22 22:37:54.898395: Current learning rate: 0.0023 +2024-11-22 22:38:15.248800: train_loss -0.806 +2024-11-22 22:38:15.253137: val_loss -0.7924 +2024-11-22 22:38:15.253250: Pseudo dice [0.8667] +2024-11-22 22:38:15.253430: Epoch time: 20.35 s +2024-11-22 22:38:16.288605: +2024-11-22 22:38:16.290357: Epoch 6440 +2024-11-22 22:38:16.290528: Current learning rate: 0.0023 +2024-11-22 22:38:37.537809: train_loss -0.8083 +2024-11-22 22:38:37.540218: val_loss -0.764 +2024-11-22 22:38:37.540345: Pseudo dice [0.8609] +2024-11-22 22:38:37.540433: Epoch time: 21.25 s +2024-11-22 22:38:38.499089: +2024-11-22 22:38:38.500653: Epoch 6441 +2024-11-22 22:38:38.500798: Current learning rate: 0.00229 +2024-11-22 22:38:58.057141: train_loss -0.8081 +2024-11-22 22:38:58.072088: val_loss -0.7614 +2024-11-22 22:38:58.072233: Pseudo dice [0.8596] +2024-11-22 22:38:58.072340: Epoch time: 19.56 s +2024-11-22 22:38:59.495692: +2024-11-22 22:38:59.498194: Epoch 6442 +2024-11-22 22:38:59.498343: Current learning rate: 0.00229 +2024-11-22 22:39:18.276522: train_loss -0.8172 +2024-11-22 22:39:18.288960: val_loss -0.7652 +2024-11-22 22:39:18.291758: Pseudo dice [0.8496] +2024-11-22 22:39:18.292259: Epoch time: 18.78 s +2024-11-22 22:39:19.253390: +2024-11-22 22:39:19.254958: Epoch 6443 +2024-11-22 22:39:19.255105: Current learning rate: 0.00229 +2024-11-22 22:39:39.914355: train_loss -0.8088 +2024-11-22 22:39:39.925766: val_loss -0.7725 +2024-11-22 22:39:39.925941: Pseudo dice [0.8614] +2024-11-22 22:39:39.926031: Epoch time: 20.66 s +2024-11-22 22:39:40.917073: +2024-11-22 22:39:40.918612: Epoch 6444 +2024-11-22 22:39:40.918751: Current learning rate: 0.00229 +2024-11-22 22:40:00.550727: train_loss -0.8072 +2024-11-22 22:40:00.555923: val_loss -0.7755 +2024-11-22 22:40:00.556045: Pseudo dice [0.846] +2024-11-22 22:40:00.556156: Epoch time: 19.63 s +2024-11-22 22:40:01.532708: +2024-11-22 22:40:01.533892: Epoch 6445 +2024-11-22 22:40:01.534008: Current learning rate: 0.00229 +2024-11-22 22:40:21.608720: train_loss -0.8052 +2024-11-22 22:40:21.614582: val_loss -0.7597 +2024-11-22 22:40:21.614706: Pseudo dice [0.843] +2024-11-22 22:40:21.614803: Epoch time: 20.08 s +2024-11-22 22:40:22.503128: +2024-11-22 22:40:22.503630: Epoch 6446 +2024-11-22 22:40:22.503763: Current learning rate: 0.00229 +2024-11-22 22:40:43.517654: train_loss -0.8147 +2024-11-22 22:40:43.523649: val_loss -0.7574 +2024-11-22 22:40:43.523794: Pseudo dice [0.8761] +2024-11-22 22:40:43.523912: Epoch time: 21.02 s +2024-11-22 22:40:44.446443: +2024-11-22 22:40:44.446924: Epoch 6447 +2024-11-22 22:40:44.447055: Current learning rate: 0.00229 +2024-11-22 22:41:03.804610: train_loss -0.8082 +2024-11-22 22:41:03.817907: val_loss -0.7864 +2024-11-22 22:41:03.824113: Pseudo dice [0.865] +2024-11-22 22:41:03.824236: Epoch time: 19.36 s +2024-11-22 22:41:04.885830: +2024-11-22 22:41:04.886262: Epoch 6448 +2024-11-22 22:41:04.886378: Current learning rate: 0.00229 +2024-11-22 22:41:25.182037: train_loss -0.8073 +2024-11-22 22:41:25.200909: val_loss -0.7707 +2024-11-22 22:41:25.201042: Pseudo dice [0.86] +2024-11-22 22:41:25.201151: Epoch time: 20.3 s +2024-11-22 22:41:26.099299: +2024-11-22 22:41:26.099750: Epoch 6449 +2024-11-22 22:41:26.099882: Current learning rate: 0.00228 +2024-11-22 22:41:46.150129: train_loss -0.8137 +2024-11-22 22:41:46.152653: val_loss -0.8008 +2024-11-22 22:41:46.152784: Pseudo dice [0.8647] +2024-11-22 22:41:46.152869: Epoch time: 20.05 s +2024-11-22 22:41:47.348761: +2024-11-22 22:41:47.349211: Epoch 6450 +2024-11-22 22:41:47.349336: Current learning rate: 0.00228 +2024-11-22 22:42:07.331295: train_loss -0.8091 +2024-11-22 22:42:07.345187: val_loss -0.7708 +2024-11-22 22:42:07.345378: Pseudo dice [0.8518] +2024-11-22 22:42:07.345479: Epoch time: 19.98 s +2024-11-22 22:42:08.279846: +2024-11-22 22:42:08.281297: Epoch 6451 +2024-11-22 22:42:08.281470: Current learning rate: 0.00228 +2024-11-22 22:42:27.497157: train_loss -0.8003 +2024-11-22 22:42:27.509823: val_loss -0.7618 +2024-11-22 22:42:27.509955: Pseudo dice [0.8533] +2024-11-22 22:42:27.510105: Epoch time: 19.22 s +2024-11-22 22:42:28.473026: +2024-11-22 22:42:28.474854: Epoch 6452 +2024-11-22 22:42:28.474990: Current learning rate: 0.00228 +2024-11-22 22:42:47.781035: train_loss -0.7993 +2024-11-22 22:42:47.791005: val_loss -0.7734 +2024-11-22 22:42:47.791154: Pseudo dice [0.8557] +2024-11-22 22:42:47.791258: Epoch time: 19.31 s +2024-11-22 22:42:48.801545: +2024-11-22 22:42:48.802683: Epoch 6453 +2024-11-22 22:42:48.802831: Current learning rate: 0.00228 +2024-11-22 22:43:08.004325: train_loss -0.8003 +2024-11-22 22:43:08.006486: val_loss -0.7637 +2024-11-22 22:43:08.006657: Pseudo dice [0.8568] +2024-11-22 22:43:08.006742: Epoch time: 19.2 s +2024-11-22 22:43:09.270397: +2024-11-22 22:43:09.271435: Epoch 6454 +2024-11-22 22:43:09.271563: Current learning rate: 0.00228 +2024-11-22 22:43:29.245901: train_loss -0.8029 +2024-11-22 22:43:29.251730: val_loss -0.7796 +2024-11-22 22:43:29.251888: Pseudo dice [0.8553] +2024-11-22 22:43:29.252011: Epoch time: 19.98 s +2024-11-22 22:43:30.140229: +2024-11-22 22:43:30.142017: Epoch 6455 +2024-11-22 22:43:30.142154: Current learning rate: 0.00228 +2024-11-22 22:43:49.837455: train_loss -0.8052 +2024-11-22 22:43:49.848962: val_loss -0.7793 +2024-11-22 22:43:49.869776: Pseudo dice [0.8429] +2024-11-22 22:43:49.869967: Epoch time: 19.7 s +2024-11-22 22:43:50.764190: +2024-11-22 22:43:50.765780: Epoch 6456 +2024-11-22 22:43:50.765899: Current learning rate: 0.00228 +2024-11-22 22:44:10.386598: train_loss -0.8063 +2024-11-22 22:44:10.399842: val_loss -0.7765 +2024-11-22 22:44:10.399968: Pseudo dice [0.8662] +2024-11-22 22:44:10.400120: Epoch time: 19.62 s +2024-11-22 22:44:11.439259: +2024-11-22 22:44:11.441028: Epoch 6457 +2024-11-22 22:44:11.441173: Current learning rate: 0.00227 +2024-11-22 22:44:30.821527: train_loss -0.8103 +2024-11-22 22:44:30.826297: val_loss -0.7863 +2024-11-22 22:44:30.826737: Pseudo dice [0.8638] +2024-11-22 22:44:30.826847: Epoch time: 19.38 s +2024-11-22 22:44:31.913217: +2024-11-22 22:44:31.914528: Epoch 6458 +2024-11-22 22:44:31.914672: Current learning rate: 0.00227 +2024-11-22 22:44:50.819507: train_loss -0.8043 +2024-11-22 22:44:50.832119: val_loss -0.7951 +2024-11-22 22:44:50.832261: Pseudo dice [0.8641] +2024-11-22 22:44:50.832368: Epoch time: 18.91 s +2024-11-22 22:44:51.716399: +2024-11-22 22:44:51.717549: Epoch 6459 +2024-11-22 22:44:51.717669: Current learning rate: 0.00227 +2024-11-22 22:45:11.708116: train_loss -0.8128 +2024-11-22 22:45:11.719216: val_loss -0.7896 +2024-11-22 22:45:11.719376: Pseudo dice [0.8472] +2024-11-22 22:45:11.719487: Epoch time: 19.99 s +2024-11-22 22:45:12.789361: +2024-11-22 22:45:12.790156: Epoch 6460 +2024-11-22 22:45:12.790287: Current learning rate: 0.00227 +2024-11-22 22:45:32.453564: train_loss -0.8106 +2024-11-22 22:45:32.460266: val_loss -0.7949 +2024-11-22 22:45:32.460407: Pseudo dice [0.8452] +2024-11-22 22:45:32.460498: Epoch time: 19.67 s +2024-11-22 22:45:33.399778: +2024-11-22 22:45:33.401024: Epoch 6461 +2024-11-22 22:45:33.401163: Current learning rate: 0.00227 +2024-11-22 22:45:53.790868: train_loss -0.8104 +2024-11-22 22:45:53.793175: val_loss -0.7617 +2024-11-22 22:45:53.793311: Pseudo dice [0.8637] +2024-11-22 22:45:53.793406: Epoch time: 20.39 s +2024-11-22 22:45:54.679876: +2024-11-22 22:45:54.680795: Epoch 6462 +2024-11-22 22:45:54.680925: Current learning rate: 0.00227 +2024-11-22 22:46:14.287103: train_loss -0.8125 +2024-11-22 22:46:14.289935: val_loss -0.7874 +2024-11-22 22:46:14.290091: Pseudo dice [0.8652] +2024-11-22 22:46:14.290192: Epoch time: 19.61 s +2024-11-22 22:46:15.220645: +2024-11-22 22:46:15.221829: Epoch 6463 +2024-11-22 22:46:15.221951: Current learning rate: 0.00227 +2024-11-22 22:46:34.985770: train_loss -0.8073 +2024-11-22 22:46:34.992087: val_loss -0.7874 +2024-11-22 22:46:34.992227: Pseudo dice [0.8549] +2024-11-22 22:46:34.992323: Epoch time: 19.77 s +2024-11-22 22:46:36.021010: +2024-11-22 22:46:36.022251: Epoch 6464 +2024-11-22 22:46:36.022375: Current learning rate: 0.00226 +2024-11-22 22:46:55.743744: train_loss -0.8156 +2024-11-22 22:46:55.750101: val_loss -0.7902 +2024-11-22 22:46:55.750244: Pseudo dice [0.8636] +2024-11-22 22:46:55.750335: Epoch time: 19.72 s +2024-11-22 22:46:57.158122: +2024-11-22 22:46:57.159800: Epoch 6465 +2024-11-22 22:46:57.159938: Current learning rate: 0.00226 +2024-11-22 22:47:15.311280: train_loss -0.8137 +2024-11-22 22:47:15.319234: val_loss -0.7722 +2024-11-22 22:47:15.319396: Pseudo dice [0.8458] +2024-11-22 22:47:15.319501: Epoch time: 18.15 s +2024-11-22 22:47:16.411227: +2024-11-22 22:47:16.413016: Epoch 6466 +2024-11-22 22:47:16.413139: Current learning rate: 0.00226 +2024-11-22 22:47:36.050673: train_loss -0.815 +2024-11-22 22:47:36.057495: val_loss -0.7783 +2024-11-22 22:47:36.057647: Pseudo dice [0.8629] +2024-11-22 22:47:36.057750: Epoch time: 19.64 s +2024-11-22 22:47:37.080865: +2024-11-22 22:47:37.081918: Epoch 6467 +2024-11-22 22:47:37.082037: Current learning rate: 0.00226 +2024-11-22 22:47:57.233387: train_loss -0.8004 +2024-11-22 22:47:57.251852: val_loss -0.7732 +2024-11-22 22:47:57.252005: Pseudo dice [0.8505] +2024-11-22 22:47:57.252120: Epoch time: 20.15 s +2024-11-22 22:47:58.424583: +2024-11-22 22:47:58.425867: Epoch 6468 +2024-11-22 22:47:58.425985: Current learning rate: 0.00226 +2024-11-22 22:48:17.637272: train_loss -0.7972 +2024-11-22 22:48:17.643705: val_loss -0.7747 +2024-11-22 22:48:17.643841: Pseudo dice [0.863] +2024-11-22 22:48:17.643929: Epoch time: 19.21 s +2024-11-22 22:48:18.604798: +2024-11-22 22:48:18.605621: Epoch 6469 +2024-11-22 22:48:18.605750: Current learning rate: 0.00226 +2024-11-22 22:48:38.499699: train_loss -0.8017 +2024-11-22 22:48:38.504894: val_loss -0.7851 +2024-11-22 22:48:38.505015: Pseudo dice [0.8521] +2024-11-22 22:48:38.505136: Epoch time: 19.9 s +2024-11-22 22:48:39.408204: +2024-11-22 22:48:39.409762: Epoch 6470 +2024-11-22 22:48:39.409889: Current learning rate: 0.00226 +2024-11-22 22:48:58.599707: train_loss -0.8146 +2024-11-22 22:48:58.612971: val_loss -0.7716 +2024-11-22 22:48:58.613119: Pseudo dice [0.8722] +2024-11-22 22:48:58.613212: Epoch time: 19.19 s +2024-11-22 22:48:59.668974: +2024-11-22 22:48:59.670805: Epoch 6471 +2024-11-22 22:48:59.670960: Current learning rate: 0.00226 +2024-11-22 22:49:19.582391: train_loss -0.8049 +2024-11-22 22:49:19.598678: val_loss -0.783 +2024-11-22 22:49:19.598815: Pseudo dice [0.8586] +2024-11-22 22:49:19.598907: Epoch time: 19.91 s +2024-11-22 22:49:20.498139: +2024-11-22 22:49:20.499196: Epoch 6472 +2024-11-22 22:49:20.499323: Current learning rate: 0.00225 +2024-11-22 22:49:40.178973: train_loss -0.8093 +2024-11-22 22:49:40.194936: val_loss -0.781 +2024-11-22 22:49:40.195078: Pseudo dice [0.8512] +2024-11-22 22:49:40.195174: Epoch time: 19.68 s +2024-11-22 22:49:41.122705: +2024-11-22 22:49:41.123132: Epoch 6473 +2024-11-22 22:49:41.123255: Current learning rate: 0.00225 +2024-11-22 22:49:59.139296: train_loss -0.8158 +2024-11-22 22:49:59.156340: val_loss -0.7693 +2024-11-22 22:49:59.156504: Pseudo dice [0.856] +2024-11-22 22:49:59.156602: Epoch time: 18.02 s +2024-11-22 22:50:00.097999: +2024-11-22 22:50:00.099393: Epoch 6474 +2024-11-22 22:50:00.099524: Current learning rate: 0.00225 +2024-11-22 22:50:18.992249: train_loss -0.8106 +2024-11-22 22:50:18.994445: val_loss -0.7867 +2024-11-22 22:50:18.994567: Pseudo dice [0.851] +2024-11-22 22:50:18.994673: Epoch time: 18.9 s +2024-11-22 22:50:19.915186: +2024-11-22 22:50:19.916006: Epoch 6475 +2024-11-22 22:50:19.916138: Current learning rate: 0.00225 +2024-11-22 22:50:40.488148: train_loss -0.8005 +2024-11-22 22:50:40.490287: val_loss -0.7626 +2024-11-22 22:50:40.490415: Pseudo dice [0.8607] +2024-11-22 22:50:40.490513: Epoch time: 20.57 s +2024-11-22 22:50:41.395534: +2024-11-22 22:50:41.396684: Epoch 6476 +2024-11-22 22:50:41.396815: Current learning rate: 0.00225 +2024-11-22 22:51:00.236661: train_loss -0.8142 +2024-11-22 22:51:00.246198: val_loss -0.7635 +2024-11-22 22:51:00.246339: Pseudo dice [0.8516] +2024-11-22 22:51:00.246429: Epoch time: 18.84 s +2024-11-22 22:51:01.716292: +2024-11-22 22:51:01.717814: Epoch 6477 +2024-11-22 22:51:01.717937: Current learning rate: 0.00225 +2024-11-22 22:51:21.767339: train_loss -0.8081 +2024-11-22 22:51:21.770119: val_loss -0.7701 +2024-11-22 22:51:21.770346: Pseudo dice [0.8553] +2024-11-22 22:51:21.770478: Epoch time: 20.05 s +2024-11-22 22:51:22.673645: +2024-11-22 22:51:22.674451: Epoch 6478 +2024-11-22 22:51:22.674569: Current learning rate: 0.00225 +2024-11-22 22:51:41.068488: train_loss -0.8108 +2024-11-22 22:51:41.090316: val_loss -0.7623 +2024-11-22 22:51:41.090463: Pseudo dice [0.8565] +2024-11-22 22:51:41.090569: Epoch time: 18.4 s +2024-11-22 22:51:42.159432: +2024-11-22 22:51:42.160724: Epoch 6479 +2024-11-22 22:51:42.160874: Current learning rate: 0.00224 +2024-11-22 22:52:01.514405: train_loss -0.8094 +2024-11-22 22:52:01.537826: val_loss -0.7747 +2024-11-22 22:52:01.538012: Pseudo dice [0.847] +2024-11-22 22:52:01.538120: Epoch time: 19.36 s +2024-11-22 22:52:02.566616: +2024-11-22 22:52:02.567386: Epoch 6480 +2024-11-22 22:52:02.567515: Current learning rate: 0.00224 +2024-11-22 22:52:22.572267: train_loss -0.807 +2024-11-22 22:52:22.576217: val_loss -0.7878 +2024-11-22 22:52:22.576354: Pseudo dice [0.8561] +2024-11-22 22:52:22.576465: Epoch time: 20.01 s +2024-11-22 22:52:23.571084: +2024-11-22 22:52:23.571736: Epoch 6481 +2024-11-22 22:52:23.571855: Current learning rate: 0.00224 +2024-11-22 22:52:44.113586: train_loss -0.8086 +2024-11-22 22:52:44.120136: val_loss -0.7639 +2024-11-22 22:52:44.120333: Pseudo dice [0.8567] +2024-11-22 22:52:44.120435: Epoch time: 20.54 s +2024-11-22 22:52:45.115099: +2024-11-22 22:52:45.115536: Epoch 6482 +2024-11-22 22:52:45.115653: Current learning rate: 0.00224 +2024-11-22 22:53:06.345891: train_loss -0.8054 +2024-11-22 22:53:06.354735: val_loss -0.7953 +2024-11-22 22:53:06.354880: Pseudo dice [0.8601] +2024-11-22 22:53:06.354979: Epoch time: 21.23 s +2024-11-22 22:53:07.312057: +2024-11-22 22:53:07.313415: Epoch 6483 +2024-11-22 22:53:07.313555: Current learning rate: 0.00224 +2024-11-22 22:53:26.794039: train_loss -0.8073 +2024-11-22 22:53:26.808039: val_loss -0.7723 +2024-11-22 22:53:26.808188: Pseudo dice [0.8695] +2024-11-22 22:53:26.808278: Epoch time: 19.48 s +2024-11-22 22:53:27.703989: +2024-11-22 22:53:27.704413: Epoch 6484 +2024-11-22 22:53:27.704528: Current learning rate: 0.00224 +2024-11-22 22:53:47.605466: train_loss -0.8114 +2024-11-22 22:53:47.616927: val_loss -0.7814 +2024-11-22 22:53:47.617071: Pseudo dice [0.8682] +2024-11-22 22:53:47.617190: Epoch time: 19.9 s +2024-11-22 22:53:48.496891: +2024-11-22 22:53:48.498627: Epoch 6485 +2024-11-22 22:53:48.498760: Current learning rate: 0.00224 +2024-11-22 22:54:08.205799: train_loss -0.8174 +2024-11-22 22:54:08.222926: val_loss -0.7923 +2024-11-22 22:54:08.224030: Pseudo dice [0.8515] +2024-11-22 22:54:08.224168: Epoch time: 19.71 s +2024-11-22 22:54:09.121150: +2024-11-22 22:54:09.122707: Epoch 6486 +2024-11-22 22:54:09.122845: Current learning rate: 0.00224 +2024-11-22 22:54:29.041779: train_loss -0.8104 +2024-11-22 22:54:29.048376: val_loss -0.7754 +2024-11-22 22:54:29.048532: Pseudo dice [0.8587] +2024-11-22 22:54:29.048649: Epoch time: 19.92 s +2024-11-22 22:54:29.943485: +2024-11-22 22:54:29.944319: Epoch 6487 +2024-11-22 22:54:29.944442: Current learning rate: 0.00223 +2024-11-22 22:54:49.520138: train_loss -0.8014 +2024-11-22 22:54:49.526994: val_loss -0.7756 +2024-11-22 22:54:49.527199: Pseudo dice [0.867] +2024-11-22 22:54:49.527289: Epoch time: 19.58 s +2024-11-22 22:54:50.855084: +2024-11-22 22:54:50.856489: Epoch 6488 +2024-11-22 22:54:50.856615: Current learning rate: 0.00223 +2024-11-22 22:55:10.344587: train_loss -0.8156 +2024-11-22 22:55:10.347598: val_loss -0.7453 +2024-11-22 22:55:10.347727: Pseudo dice [0.8531] +2024-11-22 22:55:10.347832: Epoch time: 19.49 s +2024-11-22 22:55:11.352134: +2024-11-22 22:55:11.353759: Epoch 6489 +2024-11-22 22:55:11.353904: Current learning rate: 0.00223 +2024-11-22 22:55:31.491152: train_loss -0.8065 +2024-11-22 22:55:31.501063: val_loss -0.7831 +2024-11-22 22:55:31.501195: Pseudo dice [0.8592] +2024-11-22 22:55:31.501304: Epoch time: 20.14 s +2024-11-22 22:55:32.422805: +2024-11-22 22:55:32.423886: Epoch 6490 +2024-11-22 22:55:32.424017: Current learning rate: 0.00223 +2024-11-22 22:55:51.129425: train_loss -0.8134 +2024-11-22 22:55:51.146326: val_loss -0.7817 +2024-11-22 22:55:51.146498: Pseudo dice [0.8605] +2024-11-22 22:55:51.146615: Epoch time: 18.71 s +2024-11-22 22:55:52.068050: +2024-11-22 22:55:52.069718: Epoch 6491 +2024-11-22 22:55:52.069853: Current learning rate: 0.00223 +2024-11-22 22:56:11.065662: train_loss -0.8135 +2024-11-22 22:56:11.071809: val_loss -0.7601 +2024-11-22 22:56:11.071945: Pseudo dice [0.8626] +2024-11-22 22:56:11.072042: Epoch time: 19.0 s +2024-11-22 22:56:12.016932: +2024-11-22 22:56:12.017226: Epoch 6492 +2024-11-22 22:56:12.017350: Current learning rate: 0.00223 +2024-11-22 22:56:30.683442: train_loss -0.8028 +2024-11-22 22:56:30.683958: val_loss -0.7797 +2024-11-22 22:56:30.684083: Pseudo dice [0.8559] +2024-11-22 22:56:30.684185: Epoch time: 18.67 s +2024-11-22 22:56:31.566690: +2024-11-22 22:56:31.566944: Epoch 6493 +2024-11-22 22:56:31.567072: Current learning rate: 0.00223 +2024-11-22 22:56:50.434113: train_loss -0.8105 +2024-11-22 22:56:50.435116: val_loss -0.7699 +2024-11-22 22:56:50.435257: Pseudo dice [0.865] +2024-11-22 22:56:50.437116: Epoch time: 18.87 s +2024-11-22 22:56:51.315028: +2024-11-22 22:56:51.315240: Epoch 6494 +2024-11-22 22:56:51.315360: Current learning rate: 0.00222 +2024-11-22 22:57:10.405712: train_loss -0.817 +2024-11-22 22:57:10.406201: val_loss -0.7804 +2024-11-22 22:57:10.406301: Pseudo dice [0.864] +2024-11-22 22:57:10.406385: Epoch time: 19.09 s +2024-11-22 22:57:11.282445: +2024-11-22 22:57:11.282642: Epoch 6495 +2024-11-22 22:57:11.282766: Current learning rate: 0.00222 +2024-11-22 22:57:30.066768: train_loss -0.8065 +2024-11-22 22:57:30.082686: val_loss -0.7828 +2024-11-22 22:57:30.082843: Pseudo dice [0.8509] +2024-11-22 22:57:30.082932: Epoch time: 18.79 s +2024-11-22 22:57:31.069106: +2024-11-22 22:57:31.069335: Epoch 6496 +2024-11-22 22:57:31.069461: Current learning rate: 0.00222 +2024-11-22 22:57:49.287977: train_loss -0.8122 +2024-11-22 22:57:49.288471: val_loss -0.768 +2024-11-22 22:57:49.288565: Pseudo dice [0.856] +2024-11-22 22:57:49.288662: Epoch time: 18.22 s +2024-11-22 22:57:50.169152: +2024-11-22 22:57:50.169414: Epoch 6497 +2024-11-22 22:57:50.169568: Current learning rate: 0.00222 +2024-11-22 22:58:09.233754: train_loss -0.8136 +2024-11-22 22:58:09.237657: val_loss -0.7858 +2024-11-22 22:58:09.237789: Pseudo dice [0.8626] +2024-11-22 22:58:09.237890: Epoch time: 19.07 s +2024-11-22 22:58:10.148386: +2024-11-22 22:58:10.148593: Epoch 6498 +2024-11-22 22:58:10.148722: Current learning rate: 0.00222 +2024-11-22 22:58:28.526640: train_loss -0.8161 +2024-11-22 22:58:28.535164: val_loss -0.7694 +2024-11-22 22:58:28.535375: Pseudo dice [0.8485] +2024-11-22 22:58:28.535480: Epoch time: 18.38 s +2024-11-22 22:58:29.418633: +2024-11-22 22:58:29.418849: Epoch 6499 +2024-11-22 22:58:29.418970: Current learning rate: 0.00222 +2024-11-22 22:58:48.953057: train_loss -0.8115 +2024-11-22 22:58:48.956372: val_loss -0.7933 +2024-11-22 22:58:48.956501: Pseudo dice [0.8593] +2024-11-22 22:58:48.956589: Epoch time: 19.54 s +2024-11-22 22:58:50.567713: +2024-11-22 22:58:50.567930: Epoch 6500 +2024-11-22 22:58:50.568053: Current learning rate: 0.00222 +2024-11-22 22:59:09.478985: train_loss -0.8129 +2024-11-22 22:59:09.481457: val_loss -0.7866 +2024-11-22 22:59:09.481583: Pseudo dice [0.8656] +2024-11-22 22:59:09.481681: Epoch time: 18.91 s +2024-11-22 22:59:10.354247: +2024-11-22 22:59:10.355163: Epoch 6501 +2024-11-22 22:59:10.355295: Current learning rate: 0.00222 +2024-11-22 22:59:29.592420: train_loss -0.8149 +2024-11-22 22:59:29.600832: val_loss -0.7714 +2024-11-22 22:59:29.600991: Pseudo dice [0.8593] +2024-11-22 22:59:29.601089: Epoch time: 19.24 s +2024-11-22 22:59:30.582924: +2024-11-22 22:59:30.584627: Epoch 6502 +2024-11-22 22:59:30.584764: Current learning rate: 0.00221 +2024-11-22 22:59:50.368343: train_loss -0.8154 +2024-11-22 22:59:50.376350: val_loss -0.7801 +2024-11-22 22:59:50.376522: Pseudo dice [0.8551] +2024-11-22 22:59:50.376616: Epoch time: 19.79 s +2024-11-22 22:59:51.650917: +2024-11-22 22:59:51.652101: Epoch 6503 +2024-11-22 22:59:51.652225: Current learning rate: 0.00221 +2024-11-22 23:00:10.529090: train_loss -0.8139 +2024-11-22 23:00:10.538234: val_loss -0.793 +2024-11-22 23:00:10.538382: Pseudo dice [0.8537] +2024-11-22 23:00:10.538480: Epoch time: 18.88 s +2024-11-22 23:00:11.476885: +2024-11-22 23:00:11.478270: Epoch 6504 +2024-11-22 23:00:11.478398: Current learning rate: 0.00221 +2024-11-22 23:00:30.607774: train_loss -0.8151 +2024-11-22 23:00:30.636069: val_loss -0.7901 +2024-11-22 23:00:30.636224: Pseudo dice [0.8582] +2024-11-22 23:00:30.636334: Epoch time: 19.13 s +2024-11-22 23:00:31.655514: +2024-11-22 23:00:31.656925: Epoch 6505 +2024-11-22 23:00:31.657102: Current learning rate: 0.00221 +2024-11-22 23:00:51.324663: train_loss -0.8139 +2024-11-22 23:00:51.328587: val_loss -0.7766 +2024-11-22 23:00:51.328700: Pseudo dice [0.8571] +2024-11-22 23:00:51.328867: Epoch time: 19.66 s +2024-11-22 23:00:52.538861: +2024-11-22 23:00:52.540192: Epoch 6506 +2024-11-22 23:00:52.540319: Current learning rate: 0.00221 +2024-11-22 23:01:12.391246: train_loss -0.8065 +2024-11-22 23:01:12.399260: val_loss -0.7945 +2024-11-22 23:01:12.399413: Pseudo dice [0.8757] +2024-11-22 23:01:12.399535: Epoch time: 19.85 s +2024-11-22 23:01:13.440698: +2024-11-22 23:01:13.441844: Epoch 6507 +2024-11-22 23:01:13.441964: Current learning rate: 0.00221 +2024-11-22 23:01:32.104629: train_loss -0.8129 +2024-11-22 23:01:32.115269: val_loss -0.7882 +2024-11-22 23:01:32.115422: Pseudo dice [0.8659] +2024-11-22 23:01:32.115516: Epoch time: 18.66 s +2024-11-22 23:01:33.069372: +2024-11-22 23:01:33.070237: Epoch 6508 +2024-11-22 23:01:33.070376: Current learning rate: 0.00221 +2024-11-22 23:01:52.538751: train_loss -0.8102 +2024-11-22 23:01:52.544169: val_loss -0.7814 +2024-11-22 23:01:52.544317: Pseudo dice [0.8562] +2024-11-22 23:01:52.544427: Epoch time: 19.47 s +2024-11-22 23:01:53.574629: +2024-11-22 23:01:53.575552: Epoch 6509 +2024-11-22 23:01:53.575723: Current learning rate: 0.0022 +2024-11-22 23:02:12.838879: train_loss -0.814 +2024-11-22 23:02:12.851366: val_loss -0.7812 +2024-11-22 23:02:12.851516: Pseudo dice [0.8606] +2024-11-22 23:02:12.851614: Epoch time: 19.27 s +2024-11-22 23:02:13.937172: +2024-11-22 23:02:13.938783: Epoch 6510 +2024-11-22 23:02:13.938910: Current learning rate: 0.0022 +2024-11-22 23:02:33.241662: train_loss -0.8094 +2024-11-22 23:02:33.250911: val_loss -0.7714 +2024-11-22 23:02:33.251082: Pseudo dice [0.8551] +2024-11-22 23:02:33.251182: Epoch time: 19.31 s +2024-11-22 23:02:34.586592: +2024-11-22 23:02:34.588031: Epoch 6511 +2024-11-22 23:02:34.588167: Current learning rate: 0.0022 +2024-11-22 23:02:53.231119: train_loss -0.8084 +2024-11-22 23:02:53.238797: val_loss -0.793 +2024-11-22 23:02:53.238902: Pseudo dice [0.8638] +2024-11-22 23:02:53.238996: Epoch time: 18.65 s +2024-11-22 23:02:54.135596: +2024-11-22 23:02:54.136036: Epoch 6512 +2024-11-22 23:02:54.136169: Current learning rate: 0.0022 +2024-11-22 23:03:13.858457: train_loss -0.8152 +2024-11-22 23:03:13.869739: val_loss -0.7954 +2024-11-22 23:03:13.869891: Pseudo dice [0.8559] +2024-11-22 23:03:13.869998: Epoch time: 19.72 s +2024-11-22 23:03:15.001921: +2024-11-22 23:03:15.003298: Epoch 6513 +2024-11-22 23:03:15.003438: Current learning rate: 0.0022 +2024-11-22 23:03:34.711147: train_loss -0.8081 +2024-11-22 23:03:34.716644: val_loss -0.811 +2024-11-22 23:03:34.716803: Pseudo dice [0.864] +2024-11-22 23:03:34.716919: Epoch time: 19.71 s +2024-11-22 23:03:35.632281: +2024-11-22 23:03:35.633603: Epoch 6514 +2024-11-22 23:03:35.633747: Current learning rate: 0.0022 +2024-11-22 23:03:56.271641: train_loss -0.8077 +2024-11-22 23:03:56.273988: val_loss -0.7899 +2024-11-22 23:03:56.274135: Pseudo dice [0.8596] +2024-11-22 23:03:56.274333: Epoch time: 20.64 s +2024-11-22 23:03:57.412278: +2024-11-22 23:03:57.413812: Epoch 6515 +2024-11-22 23:03:57.413948: Current learning rate: 0.0022 +2024-11-22 23:04:17.425663: train_loss -0.8076 +2024-11-22 23:04:17.431939: val_loss -0.7878 +2024-11-22 23:04:17.432081: Pseudo dice [0.8624] +2024-11-22 23:04:17.432187: Epoch time: 20.01 s +2024-11-22 23:04:18.321021: +2024-11-22 23:04:18.321485: Epoch 6516 +2024-11-22 23:04:18.321615: Current learning rate: 0.0022 +2024-11-22 23:04:37.282819: train_loss -0.8175 +2024-11-22 23:04:37.291068: val_loss -0.7812 +2024-11-22 23:04:37.291224: Pseudo dice [0.8736] +2024-11-22 23:04:37.291324: Epoch time: 18.96 s +2024-11-22 23:04:38.407033: +2024-11-22 23:04:38.408230: Epoch 6517 +2024-11-22 23:04:38.408375: Current learning rate: 0.00219 +2024-11-22 23:04:58.143789: train_loss -0.8174 +2024-11-22 23:04:58.149205: val_loss -0.7579 +2024-11-22 23:04:58.149334: Pseudo dice [0.8686] +2024-11-22 23:04:58.149437: Epoch time: 19.74 s +2024-11-22 23:04:59.082858: +2024-11-22 23:04:59.083345: Epoch 6518 +2024-11-22 23:04:59.083460: Current learning rate: 0.00219 +2024-11-22 23:05:18.211558: train_loss -0.8215 +2024-11-22 23:05:18.216570: val_loss -0.7727 +2024-11-22 23:05:18.216709: Pseudo dice [0.8659] +2024-11-22 23:05:18.216838: Epoch time: 19.13 s +2024-11-22 23:05:19.272250: +2024-11-22 23:05:19.273452: Epoch 6519 +2024-11-22 23:05:19.273751: Current learning rate: 0.00219 +2024-11-22 23:05:39.431202: train_loss -0.8085 +2024-11-22 23:05:39.438647: val_loss -0.7917 +2024-11-22 23:05:39.438781: Pseudo dice [0.8469] +2024-11-22 23:05:39.438887: Epoch time: 20.16 s +2024-11-22 23:05:40.465045: +2024-11-22 23:05:40.466242: Epoch 6520 +2024-11-22 23:05:40.466376: Current learning rate: 0.00219 +2024-11-22 23:06:00.226743: train_loss -0.8076 +2024-11-22 23:06:00.228901: val_loss -0.7831 +2024-11-22 23:06:00.229028: Pseudo dice [0.8665] +2024-11-22 23:06:00.229127: Epoch time: 19.76 s +2024-11-22 23:06:01.269393: +2024-11-22 23:06:01.270655: Epoch 6521 +2024-11-22 23:06:01.270796: Current learning rate: 0.00219 +2024-11-22 23:06:20.712346: train_loss -0.8058 +2024-11-22 23:06:20.720660: val_loss -0.7868 +2024-11-22 23:06:20.720876: Pseudo dice [0.8645] +2024-11-22 23:06:20.720994: Epoch time: 19.44 s +2024-11-22 23:06:22.003696: +2024-11-22 23:06:22.005046: Epoch 6522 +2024-11-22 23:06:22.005192: Current learning rate: 0.00219 +2024-11-22 23:06:41.046264: train_loss -0.8102 +2024-11-22 23:06:41.052446: val_loss -0.795 +2024-11-22 23:06:41.052618: Pseudo dice [0.8619] +2024-11-22 23:06:41.052748: Epoch time: 19.04 s +2024-11-22 23:06:42.057169: +2024-11-22 23:06:42.059949: Epoch 6523 +2024-11-22 23:06:42.060086: Current learning rate: 0.00219 +2024-11-22 23:07:02.452773: train_loss -0.8089 +2024-11-22 23:07:02.460315: val_loss -0.7789 +2024-11-22 23:07:02.460492: Pseudo dice [0.8564] +2024-11-22 23:07:02.460625: Epoch time: 20.4 s +2024-11-22 23:07:03.354450: +2024-11-22 23:07:03.355719: Epoch 6524 +2024-11-22 23:07:03.355850: Current learning rate: 0.00218 +2024-11-22 23:07:22.529998: train_loss -0.8172 +2024-11-22 23:07:22.540246: val_loss -0.795 +2024-11-22 23:07:22.540383: Pseudo dice [0.8643] +2024-11-22 23:07:22.540486: Epoch time: 19.18 s +2024-11-22 23:07:23.629997: +2024-11-22 23:07:23.631785: Epoch 6525 +2024-11-22 23:07:23.631934: Current learning rate: 0.00218 +2024-11-22 23:07:42.435126: train_loss -0.8175 +2024-11-22 23:07:42.437616: val_loss -0.7849 +2024-11-22 23:07:42.437749: Pseudo dice [0.8533] +2024-11-22 23:07:42.437940: Epoch time: 18.81 s +2024-11-22 23:07:43.450259: +2024-11-22 23:07:43.451891: Epoch 6526 +2024-11-22 23:07:43.452036: Current learning rate: 0.00218 +2024-11-22 23:08:02.180191: train_loss -0.8168 +2024-11-22 23:08:02.193252: val_loss -0.7623 +2024-11-22 23:08:02.193414: Pseudo dice [0.8544] +2024-11-22 23:08:02.193532: Epoch time: 18.73 s +2024-11-22 23:08:03.198366: +2024-11-22 23:08:03.199617: Epoch 6527 +2024-11-22 23:08:03.199746: Current learning rate: 0.00218 +2024-11-22 23:08:22.921995: train_loss -0.8108 +2024-11-22 23:08:22.930347: val_loss -0.77 +2024-11-22 23:08:22.930506: Pseudo dice [0.8573] +2024-11-22 23:08:22.930675: Epoch time: 19.72 s +2024-11-22 23:08:23.881681: +2024-11-22 23:08:23.883465: Epoch 6528 +2024-11-22 23:08:23.883591: Current learning rate: 0.00218 +2024-11-22 23:08:44.050495: train_loss -0.811 +2024-11-22 23:08:44.063234: val_loss -0.7826 +2024-11-22 23:08:44.063390: Pseudo dice [0.8464] +2024-11-22 23:08:44.063485: Epoch time: 20.17 s +2024-11-22 23:08:44.955296: +2024-11-22 23:08:44.956049: Epoch 6529 +2024-11-22 23:08:44.956183: Current learning rate: 0.00218 +2024-11-22 23:09:03.664951: train_loss -0.8172 +2024-11-22 23:09:03.670614: val_loss -0.7818 +2024-11-22 23:09:03.670768: Pseudo dice [0.8518] +2024-11-22 23:09:03.670866: Epoch time: 18.71 s +2024-11-22 23:09:04.564351: +2024-11-22 23:09:04.566041: Epoch 6530 +2024-11-22 23:09:04.566166: Current learning rate: 0.00218 +2024-11-22 23:09:23.951317: train_loss -0.7996 +2024-11-22 23:09:23.952901: val_loss -0.7833 +2024-11-22 23:09:23.953063: Pseudo dice [0.8443] +2024-11-22 23:09:23.953173: Epoch time: 19.39 s +2024-11-22 23:09:24.837143: +2024-11-22 23:09:24.837953: Epoch 6531 +2024-11-22 23:09:24.838095: Current learning rate: 0.00218 +2024-11-22 23:09:44.567226: train_loss -0.8186 +2024-11-22 23:09:44.568792: val_loss -0.7739 +2024-11-22 23:09:44.568936: Pseudo dice [0.8479] +2024-11-22 23:09:44.569303: Epoch time: 19.73 s +2024-11-22 23:09:45.492796: +2024-11-22 23:09:45.494508: Epoch 6532 +2024-11-22 23:09:45.494642: Current learning rate: 0.00217 +2024-11-22 23:10:04.388657: train_loss -0.815 +2024-11-22 23:10:04.395937: val_loss -0.8068 +2024-11-22 23:10:04.396070: Pseudo dice [0.8642] +2024-11-22 23:10:04.396158: Epoch time: 18.9 s +2024-11-22 23:10:05.504906: +2024-11-22 23:10:05.506688: Epoch 6533 +2024-11-22 23:10:05.506834: Current learning rate: 0.00217 +2024-11-22 23:10:24.796895: train_loss -0.8133 +2024-11-22 23:10:24.809446: val_loss -0.7863 +2024-11-22 23:10:24.809582: Pseudo dice [0.8609] +2024-11-22 23:10:24.809706: Epoch time: 19.29 s +2024-11-22 23:10:26.171236: +2024-11-22 23:10:26.172498: Epoch 6534 +2024-11-22 23:10:26.172625: Current learning rate: 0.00217 +2024-11-22 23:10:46.162796: train_loss -0.8124 +2024-11-22 23:10:46.181476: val_loss -0.7989 +2024-11-22 23:10:46.183552: Pseudo dice [0.8626] +2024-11-22 23:10:46.183702: Epoch time: 19.99 s +2024-11-22 23:10:47.113032: +2024-11-22 23:10:47.114524: Epoch 6535 +2024-11-22 23:10:47.114640: Current learning rate: 0.00217 +2024-11-22 23:11:07.498135: train_loss -0.8135 +2024-11-22 23:11:07.504070: val_loss -0.781 +2024-11-22 23:11:07.504208: Pseudo dice [0.867] +2024-11-22 23:11:07.504300: Epoch time: 20.39 s +2024-11-22 23:11:08.446066: +2024-11-22 23:11:08.447653: Epoch 6536 +2024-11-22 23:11:08.447786: Current learning rate: 0.00217 +2024-11-22 23:11:28.508661: train_loss -0.8103 +2024-11-22 23:11:28.516809: val_loss -0.7699 +2024-11-22 23:11:28.516933: Pseudo dice [0.8622] +2024-11-22 23:11:28.517034: Epoch time: 20.06 s +2024-11-22 23:11:29.493438: +2024-11-22 23:11:29.494981: Epoch 6537 +2024-11-22 23:11:29.495120: Current learning rate: 0.00217 +2024-11-22 23:11:47.493722: train_loss -0.8075 +2024-11-22 23:11:47.499303: val_loss -0.7709 +2024-11-22 23:11:47.499445: Pseudo dice [0.8703] +2024-11-22 23:11:47.499539: Epoch time: 18.0 s +2024-11-22 23:11:48.390264: +2024-11-22 23:11:48.391778: Epoch 6538 +2024-11-22 23:11:48.391907: Current learning rate: 0.00217 +2024-11-22 23:12:08.439360: train_loss -0.8101 +2024-11-22 23:12:08.447216: val_loss -0.7756 +2024-11-22 23:12:08.447334: Pseudo dice [0.8547] +2024-11-22 23:12:08.447446: Epoch time: 20.05 s +2024-11-22 23:12:09.372326: +2024-11-22 23:12:09.373842: Epoch 6539 +2024-11-22 23:12:09.373965: Current learning rate: 0.00216 +2024-11-22 23:12:30.063863: train_loss -0.8137 +2024-11-22 23:12:30.070233: val_loss -0.8046 +2024-11-22 23:12:30.070363: Pseudo dice [0.8668] +2024-11-22 23:12:30.070458: Epoch time: 20.69 s +2024-11-22 23:12:31.217043: +2024-11-22 23:12:31.218848: Epoch 6540 +2024-11-22 23:12:31.219014: Current learning rate: 0.00216 +2024-11-22 23:12:50.066679: train_loss -0.8141 +2024-11-22 23:12:50.075018: val_loss -0.7849 +2024-11-22 23:12:50.075164: Pseudo dice [0.8673] +2024-11-22 23:12:50.075267: Epoch time: 18.85 s +2024-11-22 23:12:51.250362: +2024-11-22 23:12:51.252048: Epoch 6541 +2024-11-22 23:12:51.252203: Current learning rate: 0.00216 +2024-11-22 23:13:11.317746: train_loss -0.8149 +2024-11-22 23:13:11.321683: val_loss -0.7795 +2024-11-22 23:13:11.321814: Pseudo dice [0.8458] +2024-11-22 23:13:11.321902: Epoch time: 20.07 s +2024-11-22 23:13:12.215249: +2024-11-22 23:13:12.216323: Epoch 6542 +2024-11-22 23:13:12.216454: Current learning rate: 0.00216 +2024-11-22 23:13:32.328871: train_loss -0.8171 +2024-11-22 23:13:32.334785: val_loss -0.7729 +2024-11-22 23:13:32.334907: Pseudo dice [0.851] +2024-11-22 23:13:32.335016: Epoch time: 20.11 s +2024-11-22 23:13:33.265703: +2024-11-22 23:13:33.267564: Epoch 6543 +2024-11-22 23:13:33.267692: Current learning rate: 0.00216 +2024-11-22 23:13:52.633075: train_loss -0.8163 +2024-11-22 23:13:52.636003: val_loss -0.7802 +2024-11-22 23:13:52.636138: Pseudo dice [0.8591] +2024-11-22 23:13:52.636228: Epoch time: 19.37 s +2024-11-22 23:13:53.671167: +2024-11-22 23:13:53.672482: Epoch 6544 +2024-11-22 23:13:53.672625: Current learning rate: 0.00216 +2024-11-22 23:14:12.628977: train_loss -0.8126 +2024-11-22 23:14:12.636934: val_loss -0.7829 +2024-11-22 23:14:12.637080: Pseudo dice [0.8564] +2024-11-22 23:14:12.637175: Epoch time: 18.96 s +2024-11-22 23:14:14.042686: +2024-11-22 23:14:14.043942: Epoch 6545 +2024-11-22 23:14:14.044072: Current learning rate: 0.00216 +2024-11-22 23:14:33.638145: train_loss -0.8167 +2024-11-22 23:14:33.652994: val_loss -0.7601 +2024-11-22 23:14:33.655360: Pseudo dice [0.8692] +2024-11-22 23:14:33.655519: Epoch time: 19.6 s +2024-11-22 23:14:34.596635: +2024-11-22 23:14:34.598340: Epoch 6546 +2024-11-22 23:14:34.598495: Current learning rate: 0.00216 +2024-11-22 23:14:53.990815: train_loss -0.8092 +2024-11-22 23:14:53.996646: val_loss -0.7836 +2024-11-22 23:14:53.996774: Pseudo dice [0.8637] +2024-11-22 23:14:53.996866: Epoch time: 19.4 s +2024-11-22 23:14:55.038989: +2024-11-22 23:14:55.040716: Epoch 6547 +2024-11-22 23:14:55.040872: Current learning rate: 0.00215 +2024-11-22 23:15:14.038205: train_loss -0.8085 +2024-11-22 23:15:14.040760: val_loss -0.764 +2024-11-22 23:15:14.040902: Pseudo dice [0.8551] +2024-11-22 23:15:14.040992: Epoch time: 19.0 s +2024-11-22 23:15:15.090204: +2024-11-22 23:15:15.090840: Epoch 6548 +2024-11-22 23:15:15.091017: Current learning rate: 0.00215 +2024-11-22 23:15:33.709964: train_loss -0.8142 +2024-11-22 23:15:33.718374: val_loss -0.7809 +2024-11-22 23:15:33.718516: Pseudo dice [0.8454] +2024-11-22 23:15:33.718630: Epoch time: 18.62 s +2024-11-22 23:15:34.632365: +2024-11-22 23:15:34.633532: Epoch 6549 +2024-11-22 23:15:34.633684: Current learning rate: 0.00215 +2024-11-22 23:15:55.342653: train_loss -0.8033 +2024-11-22 23:15:55.349932: val_loss -0.7897 +2024-11-22 23:15:55.350079: Pseudo dice [0.8637] +2024-11-22 23:15:55.350196: Epoch time: 20.71 s +2024-11-22 23:15:56.589561: +2024-11-22 23:15:56.591374: Epoch 6550 +2024-11-22 23:15:56.591525: Current learning rate: 0.00215 +2024-11-22 23:16:17.106673: train_loss -0.8126 +2024-11-22 23:16:17.117869: val_loss -0.7842 +2024-11-22 23:16:17.117998: Pseudo dice [0.8695] +2024-11-22 23:16:17.118092: Epoch time: 20.52 s +2024-11-22 23:16:18.293188: +2024-11-22 23:16:18.294569: Epoch 6551 +2024-11-22 23:16:18.294714: Current learning rate: 0.00215 +2024-11-22 23:16:37.949649: train_loss -0.7924 +2024-11-22 23:16:37.956735: val_loss -0.7888 +2024-11-22 23:16:37.956889: Pseudo dice [0.8633] +2024-11-22 23:16:37.956985: Epoch time: 19.66 s +2024-11-22 23:16:38.861341: +2024-11-22 23:16:38.863609: Epoch 6552 +2024-11-22 23:16:38.863760: Current learning rate: 0.00215 +2024-11-22 23:16:57.704638: train_loss -0.8099 +2024-11-22 23:16:57.719973: val_loss -0.7759 +2024-11-22 23:16:57.720135: Pseudo dice [0.8578] +2024-11-22 23:16:57.720272: Epoch time: 18.84 s +2024-11-22 23:16:58.642170: +2024-11-22 23:16:58.643615: Epoch 6553 +2024-11-22 23:16:58.643759: Current learning rate: 0.00215 +2024-11-22 23:17:18.581040: train_loss -0.7967 +2024-11-22 23:17:18.587748: val_loss -0.7499 +2024-11-22 23:17:18.587904: Pseudo dice [0.8395] +2024-11-22 23:17:18.588019: Epoch time: 19.94 s +2024-11-22 23:17:19.643291: +2024-11-22 23:17:19.644834: Epoch 6554 +2024-11-22 23:17:19.645011: Current learning rate: 0.00214 +2024-11-22 23:17:38.460934: train_loss -0.7985 +2024-11-22 23:17:38.476704: val_loss -0.7764 +2024-11-22 23:17:38.476847: Pseudo dice [0.8465] +2024-11-22 23:17:38.476966: Epoch time: 18.82 s +2024-11-22 23:17:39.353594: +2024-11-22 23:17:39.355228: Epoch 6555 +2024-11-22 23:17:39.355378: Current learning rate: 0.00214 +2024-11-22 23:17:59.069320: train_loss -0.7868 +2024-11-22 23:17:59.073284: val_loss -0.7612 +2024-11-22 23:17:59.073419: Pseudo dice [0.8283] +2024-11-22 23:17:59.073516: Epoch time: 19.72 s +2024-11-22 23:17:59.980003: +2024-11-22 23:17:59.982011: Epoch 6556 +2024-11-22 23:17:59.982173: Current learning rate: 0.00214 +2024-11-22 23:18:19.243446: train_loss -0.7998 +2024-11-22 23:18:19.251560: val_loss -0.7666 +2024-11-22 23:18:19.251698: Pseudo dice [0.8585] +2024-11-22 23:18:19.251781: Epoch time: 19.26 s +2024-11-22 23:18:20.702136: +2024-11-22 23:18:20.703176: Epoch 6557 +2024-11-22 23:18:20.703312: Current learning rate: 0.00214 +2024-11-22 23:18:39.743556: train_loss -0.8092 +2024-11-22 23:18:39.749530: val_loss -0.7947 +2024-11-22 23:18:39.749681: Pseudo dice [0.8652] +2024-11-22 23:18:39.749790: Epoch time: 19.04 s +2024-11-22 23:18:40.763584: +2024-11-22 23:18:40.765221: Epoch 6558 +2024-11-22 23:18:40.765359: Current learning rate: 0.00214 +2024-11-22 23:19:00.066602: train_loss -0.8131 +2024-11-22 23:19:00.082339: val_loss -0.7736 +2024-11-22 23:19:00.082534: Pseudo dice [0.8536] +2024-11-22 23:19:00.082628: Epoch time: 19.3 s +2024-11-22 23:19:00.997271: +2024-11-22 23:19:00.998700: Epoch 6559 +2024-11-22 23:19:00.998842: Current learning rate: 0.00214 +2024-11-22 23:19:21.346199: train_loss -0.81 +2024-11-22 23:19:21.352200: val_loss -0.7713 +2024-11-22 23:19:21.352351: Pseudo dice [0.8492] +2024-11-22 23:19:21.352460: Epoch time: 20.35 s +2024-11-22 23:19:22.251297: +2024-11-22 23:19:22.252956: Epoch 6560 +2024-11-22 23:19:22.253113: Current learning rate: 0.00214 +2024-11-22 23:19:41.105992: train_loss -0.7979 +2024-11-22 23:19:41.108453: val_loss -0.7834 +2024-11-22 23:19:41.108580: Pseudo dice [0.8537] +2024-11-22 23:19:41.108697: Epoch time: 18.86 s +2024-11-22 23:19:41.992594: +2024-11-22 23:19:41.994332: Epoch 6561 +2024-11-22 23:19:41.994457: Current learning rate: 0.00214 +2024-11-22 23:20:02.297771: train_loss -0.8074 +2024-11-22 23:20:02.304819: val_loss -0.7751 +2024-11-22 23:20:02.304999: Pseudo dice [0.8557] +2024-11-22 23:20:02.305120: Epoch time: 20.31 s +2024-11-22 23:20:03.274512: +2024-11-22 23:20:03.275729: Epoch 6562 +2024-11-22 23:20:03.275866: Current learning rate: 0.00213 +2024-11-22 23:20:23.487412: train_loss -0.8109 +2024-11-22 23:20:23.496781: val_loss -0.762 +2024-11-22 23:20:23.496922: Pseudo dice [0.8517] +2024-11-22 23:20:23.497023: Epoch time: 20.21 s +2024-11-22 23:20:24.452297: +2024-11-22 23:20:24.453356: Epoch 6563 +2024-11-22 23:20:24.453485: Current learning rate: 0.00213 +2024-11-22 23:20:43.473697: train_loss -0.8063 +2024-11-22 23:20:43.478916: val_loss -0.7863 +2024-11-22 23:20:43.479071: Pseudo dice [0.8677] +2024-11-22 23:20:43.479160: Epoch time: 19.02 s +2024-11-22 23:20:44.421054: +2024-11-22 23:20:44.421247: Epoch 6564 +2024-11-22 23:20:44.421367: Current learning rate: 0.00213 +2024-11-22 23:21:02.779194: train_loss -0.8155 +2024-11-22 23:21:02.786292: val_loss -0.7832 +2024-11-22 23:21:02.786410: Pseudo dice [0.8538] +2024-11-22 23:21:02.786515: Epoch time: 18.36 s +2024-11-22 23:21:03.780099: +2024-11-22 23:21:03.780297: Epoch 6565 +2024-11-22 23:21:03.780424: Current learning rate: 0.00213 +2024-11-22 23:21:21.659108: train_loss -0.8028 +2024-11-22 23:21:21.660077: val_loss -0.792 +2024-11-22 23:21:21.660192: Pseudo dice [0.8631] +2024-11-22 23:21:21.660290: Epoch time: 17.88 s +2024-11-22 23:21:22.547563: +2024-11-22 23:21:22.547758: Epoch 6566 +2024-11-22 23:21:22.547885: Current learning rate: 0.00213 +2024-11-22 23:21:40.931359: train_loss -0.8091 +2024-11-22 23:21:40.936696: val_loss -0.7871 +2024-11-22 23:21:40.936816: Pseudo dice [0.8633] +2024-11-22 23:21:40.936906: Epoch time: 18.38 s +2024-11-22 23:21:41.863789: +2024-11-22 23:21:41.864004: Epoch 6567 +2024-11-22 23:21:41.864132: Current learning rate: 0.00213 +2024-11-22 23:22:00.921848: train_loss -0.8009 +2024-11-22 23:22:00.922948: val_loss -0.7706 +2024-11-22 23:22:00.923069: Pseudo dice [0.8574] +2024-11-22 23:22:00.923159: Epoch time: 19.06 s +2024-11-22 23:22:02.311535: +2024-11-22 23:22:02.311738: Epoch 6568 +2024-11-22 23:22:02.311854: Current learning rate: 0.00213 +2024-11-22 23:22:20.803312: train_loss -0.8079 +2024-11-22 23:22:20.805879: val_loss -0.7801 +2024-11-22 23:22:20.806015: Pseudo dice [0.8466] +2024-11-22 23:22:20.806140: Epoch time: 18.49 s +2024-11-22 23:22:21.714379: +2024-11-22 23:22:21.714611: Epoch 6569 +2024-11-22 23:22:21.714733: Current learning rate: 0.00212 +2024-11-22 23:22:42.486095: train_loss -0.8064 +2024-11-22 23:22:42.489082: val_loss -0.785 +2024-11-22 23:22:42.489223: Pseudo dice [0.8613] +2024-11-22 23:22:42.489311: Epoch time: 20.77 s +2024-11-22 23:22:43.407845: +2024-11-22 23:22:43.408078: Epoch 6570 +2024-11-22 23:22:43.408204: Current learning rate: 0.00212 +2024-11-22 23:23:02.239089: train_loss -0.8102 +2024-11-22 23:23:02.243588: val_loss -0.7904 +2024-11-22 23:23:02.243718: Pseudo dice [0.8521] +2024-11-22 23:23:02.243807: Epoch time: 18.83 s +2024-11-22 23:23:03.205046: +2024-11-22 23:23:03.205259: Epoch 6571 +2024-11-22 23:23:03.205375: Current learning rate: 0.00212 +2024-11-22 23:23:22.034287: train_loss -0.8128 +2024-11-22 23:23:22.041486: val_loss -0.7815 +2024-11-22 23:23:22.041610: Pseudo dice [0.8476] +2024-11-22 23:23:22.041703: Epoch time: 18.83 s +2024-11-22 23:23:23.098812: +2024-11-22 23:23:23.099068: Epoch 6572 +2024-11-22 23:23:23.099197: Current learning rate: 0.00212 +2024-11-22 23:23:42.233587: train_loss -0.8152 +2024-11-22 23:23:42.234076: val_loss -0.7677 +2024-11-22 23:23:42.234184: Pseudo dice [0.8675] +2024-11-22 23:23:42.234284: Epoch time: 19.14 s +2024-11-22 23:23:43.112772: +2024-11-22 23:23:43.112992: Epoch 6573 +2024-11-22 23:23:43.113142: Current learning rate: 0.00212 +2024-11-22 23:24:01.094729: train_loss -0.8198 +2024-11-22 23:24:01.101217: val_loss -0.771 +2024-11-22 23:24:01.101377: Pseudo dice [0.8613] +2024-11-22 23:24:01.101466: Epoch time: 17.98 s +2024-11-22 23:24:02.161822: +2024-11-22 23:24:02.166277: Epoch 6574 +2024-11-22 23:24:02.166424: Current learning rate: 0.00212 +2024-11-22 23:24:20.518886: train_loss -0.807 +2024-11-22 23:24:20.524641: val_loss -0.7633 +2024-11-22 23:24:20.524803: Pseudo dice [0.841] +2024-11-22 23:24:20.524912: Epoch time: 18.36 s +2024-11-22 23:24:21.410368: +2024-11-22 23:24:21.410561: Epoch 6575 +2024-11-22 23:24:21.410679: Current learning rate: 0.00212 +2024-11-22 23:24:40.079001: train_loss -0.8046 +2024-11-22 23:24:40.088559: val_loss -0.7837 +2024-11-22 23:24:40.088706: Pseudo dice [0.8598] +2024-11-22 23:24:40.088802: Epoch time: 18.67 s +2024-11-22 23:24:41.364287: +2024-11-22 23:24:41.364505: Epoch 6576 +2024-11-22 23:24:41.364644: Current learning rate: 0.00212 +2024-11-22 23:25:01.070278: train_loss -0.803 +2024-11-22 23:25:01.071382: val_loss -0.7704 +2024-11-22 23:25:01.071474: Pseudo dice [0.8494] +2024-11-22 23:25:01.071577: Epoch time: 19.71 s +2024-11-22 23:25:01.950441: +2024-11-22 23:25:01.950650: Epoch 6577 +2024-11-22 23:25:01.950765: Current learning rate: 0.00211 +2024-11-22 23:25:20.317001: train_loss -0.8106 +2024-11-22 23:25:20.317958: val_loss -0.7653 +2024-11-22 23:25:20.318069: Pseudo dice [0.8517] +2024-11-22 23:25:20.318173: Epoch time: 18.37 s +2024-11-22 23:25:21.198073: +2024-11-22 23:25:21.198273: Epoch 6578 +2024-11-22 23:25:21.198387: Current learning rate: 0.00211 +2024-11-22 23:25:40.611421: train_loss -0.8132 +2024-11-22 23:25:40.611954: val_loss -0.7736 +2024-11-22 23:25:40.612067: Pseudo dice [0.8552] +2024-11-22 23:25:40.612167: Epoch time: 19.41 s +2024-11-22 23:25:41.484079: +2024-11-22 23:25:41.484271: Epoch 6579 +2024-11-22 23:25:41.484397: Current learning rate: 0.00211 +2024-11-22 23:26:00.405704: train_loss -0.8053 +2024-11-22 23:26:00.406942: val_loss -0.7757 +2024-11-22 23:26:00.407065: Pseudo dice [0.8544] +2024-11-22 23:26:00.407160: Epoch time: 18.92 s +2024-11-22 23:26:01.701613: +2024-11-22 23:26:01.701820: Epoch 6580 +2024-11-22 23:26:01.701947: Current learning rate: 0.00211 +2024-11-22 23:26:20.896047: train_loss -0.8091 +2024-11-22 23:26:20.898466: val_loss -0.7874 +2024-11-22 23:26:20.898612: Pseudo dice [0.8546] +2024-11-22 23:26:20.898715: Epoch time: 19.2 s +2024-11-22 23:26:21.873117: +2024-11-22 23:26:21.873386: Epoch 6581 +2024-11-22 23:26:21.873511: Current learning rate: 0.00211 +2024-11-22 23:26:40.998722: train_loss -0.8136 +2024-11-22 23:26:40.999257: val_loss -0.7751 +2024-11-22 23:26:40.999363: Pseudo dice [0.8582] +2024-11-22 23:26:40.999441: Epoch time: 19.13 s +2024-11-22 23:26:41.875426: +2024-11-22 23:26:41.875651: Epoch 6582 +2024-11-22 23:26:41.875770: Current learning rate: 0.00211 +2024-11-22 23:27:00.640400: train_loss -0.8176 +2024-11-22 23:27:00.640920: val_loss -0.7847 +2024-11-22 23:27:00.641212: Pseudo dice [0.8521] +2024-11-22 23:27:00.641316: Epoch time: 18.77 s +2024-11-22 23:27:01.532205: +2024-11-22 23:27:01.532471: Epoch 6583 +2024-11-22 23:27:01.532650: Current learning rate: 0.00211 +2024-11-22 23:27:20.294995: train_loss -0.8136 +2024-11-22 23:27:20.297680: val_loss -0.7915 +2024-11-22 23:27:20.299831: Pseudo dice [0.8673] +2024-11-22 23:27:20.299965: Epoch time: 18.76 s +2024-11-22 23:27:21.191641: +2024-11-22 23:27:21.191870: Epoch 6584 +2024-11-22 23:27:21.192005: Current learning rate: 0.0021 +2024-11-22 23:27:39.989828: train_loss -0.8129 +2024-11-22 23:27:39.996500: val_loss -0.7916 +2024-11-22 23:27:39.996665: Pseudo dice [0.8692] +2024-11-22 23:27:39.996767: Epoch time: 18.8 s +2024-11-22 23:27:41.036389: +2024-11-22 23:27:41.036593: Epoch 6585 +2024-11-22 23:27:41.036710: Current learning rate: 0.0021 +2024-11-22 23:27:59.319760: train_loss -0.8031 +2024-11-22 23:27:59.328108: val_loss -0.7879 +2024-11-22 23:27:59.328331: Pseudo dice [0.8572] +2024-11-22 23:27:59.328441: Epoch time: 18.28 s +2024-11-22 23:28:00.238459: +2024-11-22 23:28:00.238719: Epoch 6586 +2024-11-22 23:28:00.238844: Current learning rate: 0.0021 +2024-11-22 23:28:19.061651: train_loss -0.8032 +2024-11-22 23:28:19.062608: val_loss -0.767 +2024-11-22 23:28:19.062707: Pseudo dice [0.8519] +2024-11-22 23:28:19.062807: Epoch time: 18.82 s +2024-11-22 23:28:19.945321: +2024-11-22 23:28:19.945510: Epoch 6587 +2024-11-22 23:28:19.945848: Current learning rate: 0.0021 +2024-11-22 23:28:37.947681: train_loss -0.8084 +2024-11-22 23:28:37.947922: val_loss -0.7427 +2024-11-22 23:28:37.948017: Pseudo dice [0.8471] +2024-11-22 23:28:37.948110: Epoch time: 18.0 s +2024-11-22 23:28:38.819800: +2024-11-22 23:28:38.820010: Epoch 6588 +2024-11-22 23:28:38.820144: Current learning rate: 0.0021 +2024-11-22 23:28:56.422117: train_loss -0.8016 +2024-11-22 23:28:56.422328: val_loss -0.7755 +2024-11-22 23:28:56.422406: Pseudo dice [0.8505] +2024-11-22 23:28:56.422489: Epoch time: 17.6 s +2024-11-22 23:28:57.302030: +2024-11-22 23:28:57.302282: Epoch 6589 +2024-11-22 23:28:57.302412: Current learning rate: 0.0021 +2024-11-22 23:29:14.858196: train_loss -0.8079 +2024-11-22 23:29:14.858404: val_loss -0.7684 +2024-11-22 23:29:14.858482: Pseudo dice [0.8606] +2024-11-22 23:29:14.858555: Epoch time: 17.56 s +2024-11-22 23:29:15.754027: +2024-11-22 23:29:15.754227: Epoch 6590 +2024-11-22 23:29:15.754342: Current learning rate: 0.0021 +2024-11-22 23:29:34.512034: train_loss -0.8033 +2024-11-22 23:29:34.512246: val_loss -0.7654 +2024-11-22 23:29:34.512352: Pseudo dice [0.8419] +2024-11-22 23:29:34.512453: Epoch time: 18.76 s +2024-11-22 23:29:35.795354: +2024-11-22 23:29:35.795579: Epoch 6591 +2024-11-22 23:29:35.795708: Current learning rate: 0.0021 +2024-11-22 23:29:54.626202: train_loss -0.8013 +2024-11-22 23:29:54.626457: val_loss -0.7954 +2024-11-22 23:29:54.626537: Pseudo dice [0.8553] +2024-11-22 23:29:54.626616: Epoch time: 18.83 s +2024-11-22 23:29:55.602656: +2024-11-22 23:29:55.602895: Epoch 6592 +2024-11-22 23:29:55.603012: Current learning rate: 0.00209 +2024-11-22 23:30:14.370822: train_loss -0.8098 +2024-11-22 23:30:14.371057: val_loss -0.7732 +2024-11-22 23:30:14.371161: Pseudo dice [0.8709] +2024-11-22 23:30:14.371255: Epoch time: 18.77 s +2024-11-22 23:30:15.252542: +2024-11-22 23:30:15.252786: Epoch 6593 +2024-11-22 23:30:15.252902: Current learning rate: 0.00209 +2024-11-22 23:30:33.173244: train_loss -0.8135 +2024-11-22 23:30:33.173470: val_loss -0.7684 +2024-11-22 23:30:33.173625: Pseudo dice [0.8523] +2024-11-22 23:30:33.173719: Epoch time: 17.92 s +2024-11-22 23:30:34.050001: +2024-11-22 23:30:34.050227: Epoch 6594 +2024-11-22 23:30:34.050340: Current learning rate: 0.00209 +2024-11-22 23:30:51.895724: train_loss -0.8037 +2024-11-22 23:30:51.895992: val_loss -0.767 +2024-11-22 23:30:51.896076: Pseudo dice [0.859] +2024-11-22 23:30:51.896161: Epoch time: 17.85 s +2024-11-22 23:30:52.784970: +2024-11-22 23:30:52.785163: Epoch 6595 +2024-11-22 23:30:52.785276: Current learning rate: 0.00209 +2024-11-22 23:31:11.115760: train_loss -0.8093 +2024-11-22 23:31:11.116026: val_loss -0.7829 +2024-11-22 23:31:11.116118: Pseudo dice [0.8693] +2024-11-22 23:31:11.116196: Epoch time: 18.33 s +2024-11-22 23:31:11.994914: +2024-11-22 23:31:11.995138: Epoch 6596 +2024-11-22 23:31:11.995255: Current learning rate: 0.00209 +2024-11-22 23:31:30.313269: train_loss -0.8207 +2024-11-22 23:31:30.313482: val_loss -0.7918 +2024-11-22 23:31:30.313572: Pseudo dice [0.8536] +2024-11-22 23:31:30.313648: Epoch time: 18.32 s +2024-11-22 23:31:31.209307: +2024-11-22 23:31:31.209557: Epoch 6597 +2024-11-22 23:31:31.209681: Current learning rate: 0.00209 +2024-11-22 23:31:49.221920: train_loss -0.8131 +2024-11-22 23:31:49.222152: val_loss -0.7804 +2024-11-22 23:31:49.222234: Pseudo dice [0.8606] +2024-11-22 23:31:49.222319: Epoch time: 18.01 s +2024-11-22 23:31:50.101068: +2024-11-22 23:31:50.101295: Epoch 6598 +2024-11-22 23:31:50.101411: Current learning rate: 0.00209 +2024-11-22 23:32:08.854027: train_loss -0.8179 +2024-11-22 23:32:08.854282: val_loss -0.7996 +2024-11-22 23:32:08.854365: Pseudo dice [0.8683] +2024-11-22 23:32:08.854462: Epoch time: 18.75 s +2024-11-22 23:32:09.846064: +2024-11-22 23:32:09.846264: Epoch 6599 +2024-11-22 23:32:09.846371: Current learning rate: 0.00208 +2024-11-22 23:32:29.327103: train_loss -0.8125 +2024-11-22 23:32:29.327307: val_loss -0.7869 +2024-11-22 23:32:29.327401: Pseudo dice [0.8619] +2024-11-22 23:32:29.327485: Epoch time: 19.48 s +2024-11-22 23:32:30.537640: +2024-11-22 23:32:30.537841: Epoch 6600 +2024-11-22 23:32:30.537963: Current learning rate: 0.00208 +2024-11-22 23:32:48.672186: train_loss -0.8236 +2024-11-22 23:32:48.672405: val_loss -0.78 +2024-11-22 23:32:48.672494: Pseudo dice [0.8557] +2024-11-22 23:32:48.672577: Epoch time: 18.14 s +2024-11-22 23:32:49.603544: +2024-11-22 23:32:49.603763: Epoch 6601 +2024-11-22 23:32:49.603881: Current learning rate: 0.00208 +2024-11-22 23:33:07.710566: train_loss -0.8174 +2024-11-22 23:33:07.710801: val_loss -0.7799 +2024-11-22 23:33:07.710922: Pseudo dice [0.8538] +2024-11-22 23:33:07.711015: Epoch time: 18.11 s +2024-11-22 23:33:08.569051: +2024-11-22 23:33:08.569269: Epoch 6602 +2024-11-22 23:33:08.569397: Current learning rate: 0.00208 +2024-11-22 23:33:27.578753: train_loss -0.8171 +2024-11-22 23:33:27.578997: val_loss -0.7804 +2024-11-22 23:33:27.579097: Pseudo dice [0.8633] +2024-11-22 23:33:27.579200: Epoch time: 19.01 s +2024-11-22 23:33:28.883259: +2024-11-22 23:33:28.883513: Epoch 6603 +2024-11-22 23:33:28.883622: Current learning rate: 0.00208 +2024-11-22 23:33:45.903536: train_loss -0.8088 +2024-11-22 23:33:45.903746: val_loss -0.794 +2024-11-22 23:33:45.906073: Pseudo dice [0.87] +2024-11-22 23:33:45.906177: Epoch time: 17.02 s +2024-11-22 23:33:46.790219: +2024-11-22 23:33:46.790462: Epoch 6604 +2024-11-22 23:33:46.790594: Current learning rate: 0.00208 +2024-11-22 23:34:05.811331: train_loss -0.8082 +2024-11-22 23:34:05.811545: val_loss -0.7905 +2024-11-22 23:34:05.811638: Pseudo dice [0.8619] +2024-11-22 23:34:05.811729: Epoch time: 19.02 s +2024-11-22 23:34:06.717415: +2024-11-22 23:34:06.717623: Epoch 6605 +2024-11-22 23:34:06.717729: Current learning rate: 0.00208 +2024-11-22 23:34:24.166608: train_loss -0.8183 +2024-11-22 23:34:24.166854: val_loss -0.7869 +2024-11-22 23:34:24.166930: Pseudo dice [0.8624] +2024-11-22 23:34:24.167015: Epoch time: 17.45 s +2024-11-22 23:34:25.156498: +2024-11-22 23:34:25.156734: Epoch 6606 +2024-11-22 23:34:25.156853: Current learning rate: 0.00208 +2024-11-22 23:34:43.707916: train_loss -0.8141 +2024-11-22 23:34:43.708138: val_loss -0.769 +2024-11-22 23:34:43.708218: Pseudo dice [0.8612] +2024-11-22 23:34:43.708305: Epoch time: 18.55 s +2024-11-22 23:34:44.584676: +2024-11-22 23:34:44.584874: Epoch 6607 +2024-11-22 23:34:44.585000: Current learning rate: 0.00207 +2024-11-22 23:35:03.662210: train_loss -0.8117 +2024-11-22 23:35:03.662440: val_loss -0.7849 +2024-11-22 23:35:03.662519: Pseudo dice [0.8661] +2024-11-22 23:35:03.662607: Epoch time: 19.08 s +2024-11-22 23:35:04.704620: +2024-11-22 23:35:04.705304: Epoch 6608 +2024-11-22 23:35:04.705434: Current learning rate: 0.00207 +2024-11-22 23:35:22.455247: train_loss -0.8079 +2024-11-22 23:35:22.455468: val_loss -0.7505 +2024-11-22 23:35:22.455544: Pseudo dice [0.847] +2024-11-22 23:35:22.455619: Epoch time: 17.75 s +2024-11-22 23:35:23.336719: +2024-11-22 23:35:23.336931: Epoch 6609 +2024-11-22 23:35:23.337063: Current learning rate: 0.00207 +2024-11-22 23:35:40.621082: train_loss -0.8099 +2024-11-22 23:35:40.621293: val_loss -0.774 +2024-11-22 23:35:40.621374: Pseudo dice [0.8555] +2024-11-22 23:35:40.622362: Epoch time: 17.29 s +2024-11-22 23:35:41.790039: +2024-11-22 23:35:41.790265: Epoch 6610 +2024-11-22 23:35:41.790379: Current learning rate: 0.00207 +2024-11-22 23:36:00.790247: train_loss -0.807 +2024-11-22 23:36:00.790497: val_loss -0.7633 +2024-11-22 23:36:00.790578: Pseudo dice [0.8634] +2024-11-22 23:36:00.790661: Epoch time: 19.0 s +2024-11-22 23:36:01.839381: +2024-11-22 23:36:01.839588: Epoch 6611 +2024-11-22 23:36:01.839693: Current learning rate: 0.00207 +2024-11-22 23:36:21.159870: train_loss -0.8106 +2024-11-22 23:36:21.160107: val_loss -0.7593 +2024-11-22 23:36:21.160191: Pseudo dice [0.8566] +2024-11-22 23:36:21.160299: Epoch time: 19.32 s +2024-11-22 23:36:22.183888: +2024-11-22 23:36:22.184100: Epoch 6612 +2024-11-22 23:36:22.184217: Current learning rate: 0.00207 +2024-11-22 23:36:40.058249: train_loss -0.8148 +2024-11-22 23:36:40.058470: val_loss -0.7942 +2024-11-22 23:36:40.058548: Pseudo dice [0.8612] +2024-11-22 23:36:40.058637: Epoch time: 17.88 s +2024-11-22 23:36:41.007934: +2024-11-22 23:36:41.008154: Epoch 6613 +2024-11-22 23:36:41.008441: Current learning rate: 0.00207 +2024-11-22 23:36:59.249620: train_loss -0.7969 +2024-11-22 23:36:59.249848: val_loss -0.7804 +2024-11-22 23:36:59.249944: Pseudo dice [0.8442] +2024-11-22 23:36:59.250032: Epoch time: 18.24 s +2024-11-22 23:37:00.513268: +2024-11-22 23:37:00.513496: Epoch 6614 +2024-11-22 23:37:00.513622: Current learning rate: 0.00206 +2024-11-22 23:37:19.704662: train_loss -0.8004 +2024-11-22 23:37:19.704945: val_loss -0.7832 +2024-11-22 23:37:19.707245: Pseudo dice [0.8566] +2024-11-22 23:37:19.707352: Epoch time: 19.19 s +2024-11-22 23:37:20.621410: +2024-11-22 23:37:20.621617: Epoch 6615 +2024-11-22 23:37:20.621731: Current learning rate: 0.00206 +2024-11-22 23:37:38.351914: train_loss -0.8071 +2024-11-22 23:37:38.352150: val_loss -0.7801 +2024-11-22 23:37:38.352226: Pseudo dice [0.8555] +2024-11-22 23:37:38.352306: Epoch time: 17.73 s +2024-11-22 23:37:39.232804: +2024-11-22 23:37:39.233039: Epoch 6616 +2024-11-22 23:37:39.233166: Current learning rate: 0.00206 +2024-11-22 23:37:58.155373: train_loss -0.8117 +2024-11-22 23:37:58.155599: val_loss -0.7906 +2024-11-22 23:37:58.155683: Pseudo dice [0.8591] +2024-11-22 23:37:58.155761: Epoch time: 18.92 s +2024-11-22 23:37:59.034969: +2024-11-22 23:37:59.035190: Epoch 6617 +2024-11-22 23:37:59.035306: Current learning rate: 0.00206 +2024-11-22 23:38:18.040004: train_loss -0.8061 +2024-11-22 23:38:18.040255: val_loss -0.7881 +2024-11-22 23:38:18.040344: Pseudo dice [0.8547] +2024-11-22 23:38:18.040432: Epoch time: 19.01 s +2024-11-22 23:38:18.916447: +2024-11-22 23:38:18.916658: Epoch 6618 +2024-11-22 23:38:18.916779: Current learning rate: 0.00206 +2024-11-22 23:38:36.121421: train_loss -0.8179 +2024-11-22 23:38:36.121686: val_loss -0.7802 +2024-11-22 23:38:36.121778: Pseudo dice [0.8686] +2024-11-22 23:38:36.121880: Epoch time: 17.21 s +2024-11-22 23:38:37.140292: +2024-11-22 23:38:37.140520: Epoch 6619 +2024-11-22 23:38:37.140645: Current learning rate: 0.00206 +2024-11-22 23:38:54.758517: train_loss -0.8143 +2024-11-22 23:38:54.758729: val_loss -0.7799 +2024-11-22 23:38:54.758805: Pseudo dice [0.8593] +2024-11-22 23:38:54.758883: Epoch time: 17.62 s +2024-11-22 23:38:55.636079: +2024-11-22 23:38:55.636285: Epoch 6620 +2024-11-22 23:38:55.636406: Current learning rate: 0.00206 +2024-11-22 23:39:12.853892: train_loss -0.813 +2024-11-22 23:39:12.854127: val_loss -0.7634 +2024-11-22 23:39:12.854206: Pseudo dice [0.8608] +2024-11-22 23:39:12.854545: Epoch time: 17.22 s +2024-11-22 23:39:13.728281: +2024-11-22 23:39:13.728518: Epoch 6621 +2024-11-22 23:39:13.728649: Current learning rate: 0.00206 +2024-11-22 23:39:32.210303: train_loss -0.8099 +2024-11-22 23:39:32.210521: val_loss -0.7951 +2024-11-22 23:39:32.210597: Pseudo dice [0.865] +2024-11-22 23:39:32.210675: Epoch time: 18.48 s +2024-11-22 23:39:33.087717: +2024-11-22 23:39:33.087944: Epoch 6622 +2024-11-22 23:39:33.088094: Current learning rate: 0.00205 +2024-11-22 23:39:51.329304: train_loss -0.8137 +2024-11-22 23:39:51.343158: val_loss -0.7955 +2024-11-22 23:39:51.343258: Pseudo dice [0.8609] +2024-11-22 23:39:51.343345: Epoch time: 18.24 s +2024-11-22 23:39:52.307815: +2024-11-22 23:39:52.308019: Epoch 6623 +2024-11-22 23:39:52.308155: Current learning rate: 0.00205 +2024-11-22 23:40:11.358152: train_loss -0.8078 +2024-11-22 23:40:11.358378: val_loss -0.7796 +2024-11-22 23:40:11.358536: Pseudo dice [0.851] +2024-11-22 23:40:11.358662: Epoch time: 19.05 s +2024-11-22 23:40:12.343023: +2024-11-22 23:40:12.343238: Epoch 6624 +2024-11-22 23:40:12.343361: Current learning rate: 0.00205 +2024-11-22 23:40:29.830410: train_loss -0.8169 +2024-11-22 23:40:29.830639: val_loss -0.7734 +2024-11-22 23:40:29.830729: Pseudo dice [0.8461] +2024-11-22 23:40:29.830809: Epoch time: 17.49 s +2024-11-22 23:40:30.718556: +2024-11-22 23:40:30.718739: Epoch 6625 +2024-11-22 23:40:30.718882: Current learning rate: 0.00205 +2024-11-22 23:40:49.491419: train_loss -0.8199 +2024-11-22 23:40:49.491652: val_loss -0.7938 +2024-11-22 23:40:49.491730: Pseudo dice [0.862] +2024-11-22 23:40:49.491819: Epoch time: 18.77 s +2024-11-22 23:40:50.778597: +2024-11-22 23:40:50.778798: Epoch 6626 +2024-11-22 23:40:50.778919: Current learning rate: 0.00205 +2024-11-22 23:41:10.095819: train_loss -0.816 +2024-11-22 23:41:10.096055: val_loss -0.7828 +2024-11-22 23:41:10.096150: Pseudo dice [0.865] +2024-11-22 23:41:10.096236: Epoch time: 19.32 s +2024-11-22 23:41:11.080611: +2024-11-22 23:41:11.080829: Epoch 6627 +2024-11-22 23:41:11.080946: Current learning rate: 0.00205 +2024-11-22 23:41:30.097742: train_loss -0.8089 +2024-11-22 23:41:30.097955: val_loss -0.7729 +2024-11-22 23:41:30.098096: Pseudo dice [0.8486] +2024-11-22 23:41:30.098208: Epoch time: 19.02 s +2024-11-22 23:41:30.973829: +2024-11-22 23:41:30.974079: Epoch 6628 +2024-11-22 23:41:30.974192: Current learning rate: 0.00205 +2024-11-22 23:41:49.106787: train_loss -0.8025 +2024-11-22 23:41:49.112164: val_loss -0.7691 +2024-11-22 23:41:49.112281: Pseudo dice [0.8662] +2024-11-22 23:41:49.112362: Epoch time: 18.13 s +2024-11-22 23:41:50.096875: +2024-11-22 23:41:50.097088: Epoch 6629 +2024-11-22 23:41:50.097225: Current learning rate: 0.00204 +2024-11-22 23:42:08.795718: train_loss -0.8036 +2024-11-22 23:42:08.795960: val_loss -0.7541 +2024-11-22 23:42:08.796039: Pseudo dice [0.8401] +2024-11-22 23:42:08.796128: Epoch time: 18.7 s +2024-11-22 23:42:09.689203: +2024-11-22 23:42:09.689452: Epoch 6630 +2024-11-22 23:42:09.689567: Current learning rate: 0.00204 +2024-11-22 23:42:28.544919: train_loss -0.8083 +2024-11-22 23:42:28.545202: val_loss -0.786 +2024-11-22 23:42:28.545286: Pseudo dice [0.8472] +2024-11-22 23:42:28.545363: Epoch time: 18.86 s +2024-11-22 23:42:29.527229: +2024-11-22 23:42:29.527432: Epoch 6631 +2024-11-22 23:42:29.527557: Current learning rate: 0.00204 +2024-11-22 23:42:47.587677: train_loss -0.8072 +2024-11-22 23:42:47.587894: val_loss -0.797 +2024-11-22 23:42:47.587973: Pseudo dice [0.8572] +2024-11-22 23:42:47.588151: Epoch time: 18.06 s +2024-11-22 23:42:48.465577: +2024-11-22 23:42:48.465790: Epoch 6632 +2024-11-22 23:42:48.465920: Current learning rate: 0.00204 +2024-11-22 23:43:07.164875: train_loss -0.8079 +2024-11-22 23:43:07.165104: val_loss -0.7979 +2024-11-22 23:43:07.165183: Pseudo dice [0.8794] +2024-11-22 23:43:07.165268: Epoch time: 18.7 s +2024-11-22 23:43:08.147979: +2024-11-22 23:43:08.148184: Epoch 6633 +2024-11-22 23:43:08.148300: Current learning rate: 0.00204 +2024-11-22 23:43:26.780396: train_loss -0.8097 +2024-11-22 23:43:26.782016: val_loss -0.7754 +2024-11-22 23:43:26.782192: Pseudo dice [0.8421] +2024-11-22 23:43:26.782287: Epoch time: 18.63 s +2024-11-22 23:43:27.810630: +2024-11-22 23:43:27.810844: Epoch 6634 +2024-11-22 23:43:27.810977: Current learning rate: 0.00204 +2024-11-22 23:43:45.848529: train_loss -0.8068 +2024-11-22 23:43:45.848772: val_loss -0.7908 +2024-11-22 23:43:45.848861: Pseudo dice [0.8712] +2024-11-22 23:43:45.848938: Epoch time: 18.04 s +2024-11-22 23:43:46.722393: +2024-11-22 23:43:46.722603: Epoch 6635 +2024-11-22 23:43:46.722725: Current learning rate: 0.00204 +2024-11-22 23:44:05.762333: train_loss -0.8149 +2024-11-22 23:44:05.762551: val_loss -0.7773 +2024-11-22 23:44:05.762635: Pseudo dice [0.8622] +2024-11-22 23:44:05.762716: Epoch time: 19.04 s +2024-11-22 23:44:06.665001: +2024-11-22 23:44:06.665206: Epoch 6636 +2024-11-22 23:44:06.665318: Current learning rate: 0.00203 +2024-11-22 23:44:25.532127: train_loss -0.8176 +2024-11-22 23:44:25.532343: val_loss -0.7858 +2024-11-22 23:44:25.532434: Pseudo dice [0.8676] +2024-11-22 23:44:25.532514: Epoch time: 18.87 s +2024-11-22 23:44:26.817308: +2024-11-22 23:44:26.817516: Epoch 6637 +2024-11-22 23:44:26.817629: Current learning rate: 0.00203 +2024-11-22 23:44:44.700723: train_loss -0.8061 +2024-11-22 23:44:44.700982: val_loss -0.7727 +2024-11-22 23:44:44.701070: Pseudo dice [0.8512] +2024-11-22 23:44:44.701155: Epoch time: 17.88 s +2024-11-22 23:44:45.583890: +2024-11-22 23:44:45.584115: Epoch 6638 +2024-11-22 23:44:45.584232: Current learning rate: 0.00203 +2024-11-22 23:45:04.763297: train_loss -0.8137 +2024-11-22 23:45:04.763511: val_loss -0.7763 +2024-11-22 23:45:04.763611: Pseudo dice [0.8562] +2024-11-22 23:45:04.763697: Epoch time: 19.18 s +2024-11-22 23:45:05.645947: +2024-11-22 23:45:05.646448: Epoch 6639 +2024-11-22 23:45:05.646582: Current learning rate: 0.00203 +2024-11-22 23:45:24.772688: train_loss -0.8109 +2024-11-22 23:45:24.772904: val_loss -0.7575 +2024-11-22 23:45:24.772986: Pseudo dice [0.8514] +2024-11-22 23:45:24.773085: Epoch time: 19.13 s +2024-11-22 23:45:25.650884: +2024-11-22 23:45:25.651087: Epoch 6640 +2024-11-22 23:45:25.651204: Current learning rate: 0.00203 +2024-11-22 23:45:44.040152: train_loss -0.8083 +2024-11-22 23:45:44.040353: val_loss -0.7776 +2024-11-22 23:45:44.040431: Pseudo dice [0.8491] +2024-11-22 23:45:44.040513: Epoch time: 18.39 s +2024-11-22 23:45:45.048193: +2024-11-22 23:45:45.048387: Epoch 6641 +2024-11-22 23:45:45.048510: Current learning rate: 0.00203 +2024-11-22 23:46:03.004694: train_loss -0.7975 +2024-11-22 23:46:03.004947: val_loss -0.8003 +2024-11-22 23:46:03.005028: Pseudo dice [0.8651] +2024-11-22 23:46:03.005125: Epoch time: 17.96 s +2024-11-22 23:46:03.914175: +2024-11-22 23:46:03.914387: Epoch 6642 +2024-11-22 23:46:03.914501: Current learning rate: 0.00203 +2024-11-22 23:46:22.748764: train_loss -0.7988 +2024-11-22 23:46:22.748986: val_loss -0.7723 +2024-11-22 23:46:22.751242: Pseudo dice [0.852] +2024-11-22 23:46:22.751377: Epoch time: 18.84 s +2024-11-22 23:46:23.703012: +2024-11-22 23:46:23.703208: Epoch 6643 +2024-11-22 23:46:23.703328: Current learning rate: 0.00203 +2024-11-22 23:46:42.254733: train_loss -0.7979 +2024-11-22 23:46:42.254951: val_loss -0.78 +2024-11-22 23:46:42.255035: Pseudo dice [0.8556] +2024-11-22 23:46:42.255139: Epoch time: 18.55 s +2024-11-22 23:46:43.187701: +2024-11-22 23:46:43.187910: Epoch 6644 +2024-11-22 23:46:43.188025: Current learning rate: 0.00202 +2024-11-22 23:47:02.017097: train_loss -0.7996 +2024-11-22 23:47:02.017312: val_loss -0.786 +2024-11-22 23:47:02.017387: Pseudo dice [0.8568] +2024-11-22 23:47:02.017462: Epoch time: 18.83 s +2024-11-22 23:47:02.898305: +2024-11-22 23:47:02.898536: Epoch 6645 +2024-11-22 23:47:02.898654: Current learning rate: 0.00202 +2024-11-22 23:47:20.538156: train_loss -0.7871 +2024-11-22 23:47:20.538391: val_loss -0.7428 +2024-11-22 23:47:20.538474: Pseudo dice [0.8508] +2024-11-22 23:47:20.538568: Epoch time: 17.64 s +2024-11-22 23:47:21.437708: +2024-11-22 23:47:21.437921: Epoch 6646 +2024-11-22 23:47:21.448628: Current learning rate: 0.00202 +2024-11-22 23:47:38.984410: train_loss -0.801 +2024-11-22 23:47:38.984626: val_loss -0.7632 +2024-11-22 23:47:38.984708: Pseudo dice [0.8548] +2024-11-22 23:47:38.984794: Epoch time: 17.55 s +2024-11-22 23:47:39.857854: +2024-11-22 23:47:39.858088: Epoch 6647 +2024-11-22 23:47:39.858208: Current learning rate: 0.00202 +2024-11-22 23:47:58.285041: train_loss -0.8065 +2024-11-22 23:47:58.285266: val_loss -0.7676 +2024-11-22 23:47:58.285347: Pseudo dice [0.8656] +2024-11-22 23:47:58.285447: Epoch time: 18.43 s +2024-11-22 23:47:59.167416: +2024-11-22 23:47:59.167613: Epoch 6648 +2024-11-22 23:47:59.167747: Current learning rate: 0.00202 +2024-11-22 23:48:18.187476: train_loss -0.8018 +2024-11-22 23:48:18.187683: val_loss -0.7899 +2024-11-22 23:48:18.187771: Pseudo dice [0.8581] +2024-11-22 23:48:18.187868: Epoch time: 19.02 s +2024-11-22 23:48:19.499732: +2024-11-22 23:48:19.499920: Epoch 6649 +2024-11-22 23:48:19.500033: Current learning rate: 0.00202 +2024-11-22 23:48:37.624853: train_loss -0.8097 +2024-11-22 23:48:37.625108: val_loss -0.7875 +2024-11-22 23:48:37.625199: Pseudo dice [0.8595] +2024-11-22 23:48:37.625283: Epoch time: 18.13 s +2024-11-22 23:48:38.835192: +2024-11-22 23:48:38.835444: Epoch 6650 +2024-11-22 23:48:38.835559: Current learning rate: 0.00202 +2024-11-22 23:48:56.964338: train_loss -0.8105 +2024-11-22 23:48:56.964554: val_loss -0.7641 +2024-11-22 23:48:56.964642: Pseudo dice [0.8551] +2024-11-22 23:48:56.964723: Epoch time: 18.13 s +2024-11-22 23:48:57.843220: +2024-11-22 23:48:57.843456: Epoch 6651 +2024-11-22 23:48:57.843572: Current learning rate: 0.00201 +2024-11-22 23:49:16.562580: train_loss -0.8063 +2024-11-22 23:49:16.562799: val_loss -0.7739 +2024-11-22 23:49:16.562893: Pseudo dice [0.8574] +2024-11-22 23:49:16.562989: Epoch time: 18.72 s +2024-11-22 23:49:17.439979: +2024-11-22 23:49:17.440183: Epoch 6652 +2024-11-22 23:49:17.440317: Current learning rate: 0.00201 +2024-11-22 23:49:36.432706: train_loss -0.8118 +2024-11-22 23:49:36.432945: val_loss -0.7738 +2024-11-22 23:49:36.433028: Pseudo dice [0.8411] +2024-11-22 23:49:36.433120: Epoch time: 18.99 s +2024-11-22 23:49:37.314106: +2024-11-22 23:49:37.314393: Epoch 6653 +2024-11-22 23:49:37.314532: Current learning rate: 0.00201 +2024-11-22 23:49:55.793552: train_loss -0.8101 +2024-11-22 23:49:55.793763: val_loss -0.7934 +2024-11-22 23:49:55.793839: Pseudo dice [0.8644] +2024-11-22 23:49:55.793916: Epoch time: 18.48 s +2024-11-22 23:49:56.675355: +2024-11-22 23:49:56.675554: Epoch 6654 +2024-11-22 23:49:56.675683: Current learning rate: 0.00201 +2024-11-22 23:50:14.863981: train_loss -0.808 +2024-11-22 23:50:14.864239: val_loss -0.7837 +2024-11-22 23:50:14.864312: Pseudo dice [0.8587] +2024-11-22 23:50:14.864385: Epoch time: 18.19 s +2024-11-22 23:50:15.746492: +2024-11-22 23:50:15.746714: Epoch 6655 +2024-11-22 23:50:15.746837: Current learning rate: 0.00201 +2024-11-22 23:50:33.442029: train_loss -0.8144 +2024-11-22 23:50:33.442261: val_loss -0.7846 +2024-11-22 23:50:33.442344: Pseudo dice [0.8555] +2024-11-22 23:50:33.442423: Epoch time: 17.7 s +2024-11-22 23:50:34.413537: +2024-11-22 23:50:34.413791: Epoch 6656 +2024-11-22 23:50:34.413916: Current learning rate: 0.00201 +2024-11-22 23:50:51.848239: train_loss -0.8167 +2024-11-22 23:50:51.848460: val_loss -0.8103 +2024-11-22 23:50:51.848542: Pseudo dice [0.8718] +2024-11-22 23:50:51.848626: Epoch time: 17.44 s +2024-11-22 23:50:52.740454: +2024-11-22 23:50:52.740691: Epoch 6657 +2024-11-22 23:50:52.740818: Current learning rate: 0.00201 +2024-11-22 23:51:11.212039: train_loss -0.8172 +2024-11-22 23:51:11.212265: val_loss -0.7781 +2024-11-22 23:51:11.212348: Pseudo dice [0.865] +2024-11-22 23:51:11.212428: Epoch time: 18.47 s +2024-11-22 23:51:12.091856: +2024-11-22 23:51:12.092067: Epoch 6658 +2024-11-22 23:51:12.092188: Current learning rate: 0.00201 +2024-11-22 23:51:30.387489: train_loss -0.8096 +2024-11-22 23:51:30.387784: val_loss -0.7899 +2024-11-22 23:51:30.387871: Pseudo dice [0.8583] +2024-11-22 23:51:30.401133: Epoch time: 18.3 s +2024-11-22 23:51:31.357266: +2024-11-22 23:51:31.357482: Epoch 6659 +2024-11-22 23:51:31.357617: Current learning rate: 0.002 +2024-11-22 23:51:50.468585: train_loss -0.8057 +2024-11-22 23:51:50.468804: val_loss -0.7867 +2024-11-22 23:51:50.468881: Pseudo dice [0.859] +2024-11-22 23:51:50.468969: Epoch time: 19.11 s +2024-11-22 23:51:51.733735: +2024-11-22 23:51:51.733953: Epoch 6660 +2024-11-22 23:51:51.734080: Current learning rate: 0.002 +2024-11-22 23:52:10.425001: train_loss -0.8096 +2024-11-22 23:52:10.425277: val_loss -0.7785 +2024-11-22 23:52:10.425361: Pseudo dice [0.8635] +2024-11-22 23:52:10.425456: Epoch time: 18.69 s +2024-11-22 23:52:11.298310: +2024-11-22 23:52:11.298508: Epoch 6661 +2024-11-22 23:52:11.298620: Current learning rate: 0.002 +2024-11-22 23:52:29.846266: train_loss -0.8017 +2024-11-22 23:52:29.846488: val_loss -0.7725 +2024-11-22 23:52:29.846573: Pseudo dice [0.8669] +2024-11-22 23:52:29.846655: Epoch time: 18.55 s +2024-11-22 23:52:30.727516: +2024-11-22 23:52:30.727734: Epoch 6662 +2024-11-22 23:52:30.727850: Current learning rate: 0.002 +2024-11-22 23:52:47.670117: train_loss -0.8156 +2024-11-22 23:52:47.670327: val_loss -0.7762 +2024-11-22 23:52:47.670407: Pseudo dice [0.8415] +2024-11-22 23:52:47.670483: Epoch time: 16.94 s +2024-11-22 23:52:48.548110: +2024-11-22 23:52:48.548331: Epoch 6663 +2024-11-22 23:52:48.548447: Current learning rate: 0.002 +2024-11-22 23:53:07.181697: train_loss -0.8078 +2024-11-22 23:53:07.181945: val_loss -0.7714 +2024-11-22 23:53:07.182025: Pseudo dice [0.8535] +2024-11-22 23:53:07.182123: Epoch time: 18.63 s +2024-11-22 23:53:08.084850: +2024-11-22 23:53:08.085081: Epoch 6664 +2024-11-22 23:53:08.085193: Current learning rate: 0.002 +2024-11-22 23:53:26.725180: train_loss -0.8038 +2024-11-22 23:53:26.725426: val_loss -0.7605 +2024-11-22 23:53:26.725510: Pseudo dice [0.858] +2024-11-22 23:53:26.725593: Epoch time: 18.64 s +2024-11-22 23:53:27.599916: +2024-11-22 23:53:27.600145: Epoch 6665 +2024-11-22 23:53:27.600257: Current learning rate: 0.002 +2024-11-22 23:53:46.376806: train_loss -0.7863 +2024-11-22 23:53:46.377020: val_loss -0.7665 +2024-11-22 23:53:46.377105: Pseudo dice [0.8429] +2024-11-22 23:53:46.377192: Epoch time: 18.78 s +2024-11-22 23:53:47.247633: +2024-11-22 23:53:47.247869: Epoch 6666 +2024-11-22 23:53:47.247987: Current learning rate: 0.00199 +2024-11-22 23:54:06.458627: train_loss -0.7864 +2024-11-22 23:54:06.458860: val_loss -0.7455 +2024-11-22 23:54:06.458963: Pseudo dice [0.8446] +2024-11-22 23:54:06.459044: Epoch time: 19.21 s +2024-11-22 23:54:07.342537: +2024-11-22 23:54:07.342753: Epoch 6667 +2024-11-22 23:54:07.342877: Current learning rate: 0.00199 +2024-11-22 23:54:25.662579: train_loss -0.787 +2024-11-22 23:54:25.662792: val_loss -0.7572 +2024-11-22 23:54:25.662878: Pseudo dice [0.8438] +2024-11-22 23:54:25.662963: Epoch time: 18.32 s +2024-11-22 23:54:26.553843: +2024-11-22 23:54:26.554045: Epoch 6668 +2024-11-22 23:54:26.554175: Current learning rate: 0.00199 +2024-11-22 23:54:44.250736: train_loss -0.7902 +2024-11-22 23:54:44.250971: val_loss -0.7833 +2024-11-22 23:54:44.258708: Pseudo dice [0.8548] +2024-11-22 23:54:44.258832: Epoch time: 17.7 s +2024-11-22 23:54:45.139230: +2024-11-22 23:54:45.139436: Epoch 6669 +2024-11-22 23:54:45.139548: Current learning rate: 0.00199 +2024-11-22 23:55:03.823986: train_loss -0.8133 +2024-11-22 23:55:03.824225: val_loss -0.781 +2024-11-22 23:55:03.824303: Pseudo dice [0.8526] +2024-11-22 23:55:03.824381: Epoch time: 18.69 s +2024-11-22 23:55:04.744908: +2024-11-22 23:55:04.745129: Epoch 6670 +2024-11-22 23:55:04.745243: Current learning rate: 0.00199 +2024-11-22 23:55:23.887029: train_loss -0.8064 +2024-11-22 23:55:23.887260: val_loss -0.7703 +2024-11-22 23:55:23.887356: Pseudo dice [0.8526] +2024-11-22 23:55:23.887433: Epoch time: 19.14 s +2024-11-22 23:55:24.769612: +2024-11-22 23:55:24.769816: Epoch 6671 +2024-11-22 23:55:24.769951: Current learning rate: 0.00199 +2024-11-22 23:55:43.011639: train_loss -0.7832 +2024-11-22 23:55:43.011969: val_loss -0.7269 +2024-11-22 23:55:43.037718: Pseudo dice [0.8295] +2024-11-22 23:55:43.037910: Epoch time: 18.24 s +2024-11-22 23:55:44.374006: +2024-11-22 23:55:44.374230: Epoch 6672 +2024-11-22 23:55:44.374364: Current learning rate: 0.00199 +2024-11-22 23:56:02.756014: train_loss -0.7952 +2024-11-22 23:56:02.756239: val_loss -0.7768 +2024-11-22 23:56:02.756330: Pseudo dice [0.8524] +2024-11-22 23:56:02.756411: Epoch time: 18.38 s +2024-11-22 23:56:03.635451: +2024-11-22 23:56:03.635669: Epoch 6673 +2024-11-22 23:56:03.635789: Current learning rate: 0.00199 +2024-11-22 23:56:23.153330: train_loss -0.808 +2024-11-22 23:56:23.153538: val_loss -0.776 +2024-11-22 23:56:23.153621: Pseudo dice [0.8721] +2024-11-22 23:56:23.153708: Epoch time: 19.52 s +2024-11-22 23:56:24.011677: +2024-11-22 23:56:24.011898: Epoch 6674 +2024-11-22 23:56:24.012015: Current learning rate: 0.00198 +2024-11-22 23:56:42.413169: train_loss -0.8035 +2024-11-22 23:56:42.413367: val_loss -0.7769 +2024-11-22 23:56:42.413443: Pseudo dice [0.8534] +2024-11-22 23:56:42.413528: Epoch time: 18.4 s +2024-11-22 23:56:43.285935: +2024-11-22 23:56:43.286146: Epoch 6675 +2024-11-22 23:56:43.286277: Current learning rate: 0.00198 +2024-11-22 23:57:02.482277: train_loss -0.8089 +2024-11-22 23:57:02.482517: val_loss -0.764 +2024-11-22 23:57:02.482594: Pseudo dice [0.8702] +2024-11-22 23:57:02.482674: Epoch time: 19.2 s +2024-11-22 23:57:03.367634: +2024-11-22 23:57:03.367851: Epoch 6676 +2024-11-22 23:57:03.367972: Current learning rate: 0.00198 +2024-11-22 23:57:21.770477: train_loss -0.814 +2024-11-22 23:57:21.770667: val_loss -0.7823 +2024-11-22 23:57:21.770749: Pseudo dice [0.871] +2024-11-22 23:57:21.770831: Epoch time: 18.4 s +2024-11-22 23:57:22.652698: +2024-11-22 23:57:22.652905: Epoch 6677 +2024-11-22 23:57:22.653023: Current learning rate: 0.00198 +2024-11-22 23:57:42.035889: train_loss -0.8094 +2024-11-22 23:57:42.036105: val_loss -0.7396 +2024-11-22 23:57:42.036185: Pseudo dice [0.8506] +2024-11-22 23:57:42.036269: Epoch time: 19.38 s +2024-11-22 23:57:42.923736: +2024-11-22 23:57:42.923949: Epoch 6678 +2024-11-22 23:57:42.924078: Current learning rate: 0.00198 +2024-11-22 23:58:00.747960: train_loss -0.8118 +2024-11-22 23:58:00.748183: val_loss -0.7851 +2024-11-22 23:58:00.748270: Pseudo dice [0.8472] +2024-11-22 23:58:00.748413: Epoch time: 17.83 s +2024-11-22 23:58:01.634866: +2024-11-22 23:58:01.635071: Epoch 6679 +2024-11-22 23:58:01.635212: Current learning rate: 0.00198 +2024-11-22 23:58:19.386600: train_loss -0.8097 +2024-11-22 23:58:19.386834: val_loss -0.7964 +2024-11-22 23:58:19.386919: Pseudo dice [0.8691] +2024-11-22 23:58:19.387000: Epoch time: 17.75 s +2024-11-22 23:58:20.407323: +2024-11-22 23:58:20.407515: Epoch 6680 +2024-11-22 23:58:20.407629: Current learning rate: 0.00198 +2024-11-22 23:58:38.803777: train_loss -0.8165 +2024-11-22 23:58:38.803995: val_loss -0.7789 +2024-11-22 23:58:38.804091: Pseudo dice [0.8455] +2024-11-22 23:58:38.804179: Epoch time: 18.4 s +2024-11-22 23:58:39.687787: +2024-11-22 23:58:39.688001: Epoch 6681 +2024-11-22 23:58:39.688133: Current learning rate: 0.00197 +2024-11-22 23:58:57.920197: train_loss -0.8046 +2024-11-22 23:58:57.920414: val_loss -0.755 +2024-11-22 23:58:57.920501: Pseudo dice [0.8667] +2024-11-22 23:58:57.920582: Epoch time: 18.23 s +2024-11-22 23:58:58.797389: +2024-11-22 23:58:58.797603: Epoch 6682 +2024-11-22 23:58:58.797726: Current learning rate: 0.00197 +2024-11-22 23:59:17.127814: train_loss -0.8153 +2024-11-22 23:59:17.130107: val_loss -0.7709 +2024-11-22 23:59:17.130384: Pseudo dice [0.8399] +2024-11-22 23:59:17.130497: Epoch time: 18.33 s +2024-11-22 23:59:18.478517: +2024-11-22 23:59:18.478723: Epoch 6683 +2024-11-22 23:59:18.478835: Current learning rate: 0.00197 +2024-11-22 23:59:37.276779: train_loss -0.8145 +2024-11-22 23:59:37.277047: val_loss -0.7949 +2024-11-22 23:59:37.277156: Pseudo dice [0.8583] +2024-11-22 23:59:37.277242: Epoch time: 18.8 s +2024-11-22 23:59:38.158558: +2024-11-22 23:59:38.158779: Epoch 6684 +2024-11-22 23:59:38.158899: Current learning rate: 0.00197 +2024-11-22 23:59:57.562658: train_loss -0.8101 +2024-11-22 23:59:57.562904: val_loss -0.7731 +2024-11-22 23:59:57.562999: Pseudo dice [0.8547] +2024-11-22 23:59:57.563085: Epoch time: 19.4 s +2024-11-22 23:59:58.447298: +2024-11-22 23:59:58.447518: Epoch 6685 +2024-11-22 23:59:58.447639: Current learning rate: 0.00197 +2024-11-23 00:00:15.441531: train_loss -0.8125 +2024-11-23 00:00:15.441812: val_loss -0.7865 +2024-11-23 00:00:15.441906: Pseudo dice [0.8686] +2024-11-23 00:00:15.442011: Epoch time: 17.0 s +2024-11-23 00:00:16.435764: +2024-11-23 00:00:16.436010: Epoch 6686 +2024-11-23 00:00:16.436178: Current learning rate: 0.00197 +2024-11-23 00:00:34.002558: train_loss -0.8144 +2024-11-23 00:00:34.002781: val_loss -0.7743 +2024-11-23 00:00:34.002862: Pseudo dice [0.8591] +2024-11-23 00:00:34.005138: Epoch time: 17.57 s +2024-11-23 00:00:35.065669: +2024-11-23 00:00:35.065887: Epoch 6687 +2024-11-23 00:00:35.066012: Current learning rate: 0.00197 +2024-11-23 00:00:53.640151: train_loss -0.8166 +2024-11-23 00:00:53.640379: val_loss -0.7985 +2024-11-23 00:00:53.640476: Pseudo dice [0.8676] +2024-11-23 00:00:53.640568: Epoch time: 18.58 s +2024-11-23 00:00:54.740160: +2024-11-23 00:00:54.740369: Epoch 6688 +2024-11-23 00:00:54.740496: Current learning rate: 0.00196 +2024-11-23 00:01:13.450282: train_loss -0.8047 +2024-11-23 00:01:13.450492: val_loss -0.7833 +2024-11-23 00:01:13.450567: Pseudo dice [0.8514] +2024-11-23 00:01:13.450645: Epoch time: 18.71 s +2024-11-23 00:01:14.332335: +2024-11-23 00:01:14.332558: Epoch 6689 +2024-11-23 00:01:14.332675: Current learning rate: 0.00196 +2024-11-23 00:01:32.792613: train_loss -0.8152 +2024-11-23 00:01:32.792824: val_loss -0.781 +2024-11-23 00:01:32.795090: Pseudo dice [0.8604] +2024-11-23 00:01:32.795254: Epoch time: 18.46 s +2024-11-23 00:01:33.688560: +2024-11-23 00:01:33.688785: Epoch 6690 +2024-11-23 00:01:33.688899: Current learning rate: 0.00196 +2024-11-23 00:01:52.131139: train_loss -0.809 +2024-11-23 00:01:52.131403: val_loss -0.7928 +2024-11-23 00:01:52.131527: Pseudo dice [0.8516] +2024-11-23 00:01:52.131621: Epoch time: 18.44 s +2024-11-23 00:01:53.016140: +2024-11-23 00:01:53.016360: Epoch 6691 +2024-11-23 00:01:53.016479: Current learning rate: 0.00196 +2024-11-23 00:02:11.633732: train_loss -0.8188 +2024-11-23 00:02:11.639138: val_loss -0.7888 +2024-11-23 00:02:11.639313: Pseudo dice [0.8631] +2024-11-23 00:02:11.639395: Epoch time: 18.62 s +2024-11-23 00:02:12.545171: +2024-11-23 00:02:12.545393: Epoch 6692 +2024-11-23 00:02:12.545516: Current learning rate: 0.00196 +2024-11-23 00:02:30.948241: train_loss -0.8145 +2024-11-23 00:02:30.948449: val_loss -0.7877 +2024-11-23 00:02:30.948529: Pseudo dice [0.8543] +2024-11-23 00:02:30.948635: Epoch time: 18.4 s +2024-11-23 00:02:31.826972: +2024-11-23 00:02:31.827186: Epoch 6693 +2024-11-23 00:02:31.827317: Current learning rate: 0.00196 +2024-11-23 00:02:51.252916: train_loss -0.8192 +2024-11-23 00:02:51.255275: val_loss -0.7835 +2024-11-23 00:02:51.255400: Pseudo dice [0.8578] +2024-11-23 00:02:51.255489: Epoch time: 19.43 s +2024-11-23 00:02:52.231658: +2024-11-23 00:02:52.231867: Epoch 6694 +2024-11-23 00:02:52.231997: Current learning rate: 0.00196 +2024-11-23 00:03:11.269147: train_loss -0.8114 +2024-11-23 00:03:11.269392: val_loss -0.8088 +2024-11-23 00:03:11.269473: Pseudo dice [0.8698] +2024-11-23 00:03:11.269566: Epoch time: 19.04 s +2024-11-23 00:03:12.557559: +2024-11-23 00:03:12.557776: Epoch 6695 +2024-11-23 00:03:12.557891: Current learning rate: 0.00196 +2024-11-23 00:03:30.943683: train_loss -0.8185 +2024-11-23 00:03:30.943907: val_loss -0.7357 +2024-11-23 00:03:30.943997: Pseudo dice [0.8421] +2024-11-23 00:03:30.944081: Epoch time: 18.39 s +2024-11-23 00:03:31.846493: +2024-11-23 00:03:31.846715: Epoch 6696 +2024-11-23 00:03:31.846843: Current learning rate: 0.00195 +2024-11-23 00:03:50.007765: train_loss -0.8116 +2024-11-23 00:03:50.007990: val_loss -0.7843 +2024-11-23 00:03:50.008078: Pseudo dice [0.8571] +2024-11-23 00:03:50.013304: Epoch time: 18.16 s +2024-11-23 00:03:50.938877: +2024-11-23 00:03:50.939100: Epoch 6697 +2024-11-23 00:03:50.939223: Current learning rate: 0.00195 +2024-11-23 00:04:09.167913: train_loss -0.8175 +2024-11-23 00:04:09.168159: val_loss -0.7517 +2024-11-23 00:04:09.168243: Pseudo dice [0.863] +2024-11-23 00:04:09.168336: Epoch time: 18.23 s +2024-11-23 00:04:10.056215: +2024-11-23 00:04:10.056466: Epoch 6698 +2024-11-23 00:04:10.056584: Current learning rate: 0.00195 +2024-11-23 00:04:27.918777: train_loss -0.8134 +2024-11-23 00:04:27.918998: val_loss -0.7842 +2024-11-23 00:04:27.919109: Pseudo dice [0.8529] +2024-11-23 00:04:27.919185: Epoch time: 17.86 s +2024-11-23 00:04:28.803542: +2024-11-23 00:04:28.803750: Epoch 6699 +2024-11-23 00:04:28.803865: Current learning rate: 0.00195 +2024-11-23 00:04:46.322745: train_loss -0.8187 +2024-11-23 00:04:46.322959: val_loss -0.7766 +2024-11-23 00:04:46.323039: Pseudo dice [0.8563] +2024-11-23 00:04:46.323123: Epoch time: 17.52 s +2024-11-23 00:04:47.795732: +2024-11-23 00:04:47.795938: Epoch 6700 +2024-11-23 00:04:47.796056: Current learning rate: 0.00195 +2024-11-23 00:05:06.177679: train_loss -0.8161 +2024-11-23 00:05:06.177898: val_loss -0.7751 +2024-11-23 00:05:06.177984: Pseudo dice [0.858] +2024-11-23 00:05:06.178066: Epoch time: 18.38 s +2024-11-23 00:05:07.060915: +2024-11-23 00:05:07.061138: Epoch 6701 +2024-11-23 00:05:07.061259: Current learning rate: 0.00195 +2024-11-23 00:05:26.007954: train_loss -0.8226 +2024-11-23 00:05:26.008212: val_loss -0.7751 +2024-11-23 00:05:26.008312: Pseudo dice [0.8492] +2024-11-23 00:05:26.008401: Epoch time: 18.95 s +2024-11-23 00:05:26.975767: +2024-11-23 00:05:26.975974: Epoch 6702 +2024-11-23 00:05:26.976109: Current learning rate: 0.00195 +2024-11-23 00:05:45.641219: train_loss -0.8157 +2024-11-23 00:05:45.641429: val_loss -0.7741 +2024-11-23 00:05:45.641509: Pseudo dice [0.8561] +2024-11-23 00:05:45.641606: Epoch time: 18.67 s +2024-11-23 00:05:46.522177: +2024-11-23 00:05:46.522382: Epoch 6703 +2024-11-23 00:05:46.522496: Current learning rate: 0.00194 +2024-11-23 00:06:05.445362: train_loss -0.8148 +2024-11-23 00:06:05.445580: val_loss -0.7929 +2024-11-23 00:06:05.445668: Pseudo dice [0.8772] +2024-11-23 00:06:05.445748: Epoch time: 18.92 s +2024-11-23 00:06:06.330168: +2024-11-23 00:06:06.330382: Epoch 6704 +2024-11-23 00:06:06.330504: Current learning rate: 0.00194 +2024-11-23 00:06:24.148781: train_loss -0.8193 +2024-11-23 00:06:24.149012: val_loss -0.7849 +2024-11-23 00:06:24.149098: Pseudo dice [0.8426] +2024-11-23 00:06:24.149181: Epoch time: 17.82 s +2024-11-23 00:06:25.032014: +2024-11-23 00:06:25.032220: Epoch 6705 +2024-11-23 00:06:25.032337: Current learning rate: 0.00194 +2024-11-23 00:06:43.691780: train_loss -0.8127 +2024-11-23 00:06:43.692027: val_loss -0.7902 +2024-11-23 00:06:43.692128: Pseudo dice [0.8682] +2024-11-23 00:06:43.692211: Epoch time: 18.66 s +2024-11-23 00:06:44.971019: +2024-11-23 00:06:44.971238: Epoch 6706 +2024-11-23 00:06:44.971353: Current learning rate: 0.00194 +2024-11-23 00:07:04.641201: train_loss -0.812 +2024-11-23 00:07:04.643832: val_loss -0.7852 +2024-11-23 00:07:04.643937: Pseudo dice [0.8572] +2024-11-23 00:07:04.644016: Epoch time: 19.67 s +2024-11-23 00:07:05.772031: +2024-11-23 00:07:05.772257: Epoch 6707 +2024-11-23 00:07:05.772387: Current learning rate: 0.00194 +2024-11-23 00:07:25.149994: train_loss -0.8146 +2024-11-23 00:07:25.150232: val_loss -0.7753 +2024-11-23 00:07:25.150335: Pseudo dice [0.8541] +2024-11-23 00:07:25.150413: Epoch time: 19.38 s +2024-11-23 00:07:26.040333: +2024-11-23 00:07:26.040551: Epoch 6708 +2024-11-23 00:07:26.040679: Current learning rate: 0.00194 +2024-11-23 00:07:46.068421: train_loss -0.8099 +2024-11-23 00:07:46.068684: val_loss -0.792 +2024-11-23 00:07:46.068778: Pseudo dice [0.8655] +2024-11-23 00:07:46.068885: Epoch time: 20.03 s +2024-11-23 00:07:47.136439: +2024-11-23 00:07:47.136668: Epoch 6709 +2024-11-23 00:07:47.136805: Current learning rate: 0.00194 +2024-11-23 00:08:04.839794: train_loss -0.8113 +2024-11-23 00:08:04.840010: val_loss -0.7607 +2024-11-23 00:08:04.840104: Pseudo dice [0.8513] +2024-11-23 00:08:04.845400: Epoch time: 17.7 s +2024-11-23 00:08:05.767901: +2024-11-23 00:08:05.768143: Epoch 6710 +2024-11-23 00:08:05.768259: Current learning rate: 0.00194 +2024-11-23 00:08:24.683787: train_loss -0.8151 +2024-11-23 00:08:24.684019: val_loss -0.7695 +2024-11-23 00:08:24.684126: Pseudo dice [0.8558] +2024-11-23 00:08:24.684214: Epoch time: 18.92 s +2024-11-23 00:08:25.574532: +2024-11-23 00:08:25.574756: Epoch 6711 +2024-11-23 00:08:25.574874: Current learning rate: 0.00193 +2024-11-23 00:08:44.281098: train_loss -0.8096 +2024-11-23 00:08:44.281317: val_loss -0.7846 +2024-11-23 00:08:44.281400: Pseudo dice [0.8654] +2024-11-23 00:08:44.281492: Epoch time: 18.71 s +2024-11-23 00:08:45.199681: +2024-11-23 00:08:45.199893: Epoch 6712 +2024-11-23 00:08:45.200006: Current learning rate: 0.00193 +2024-11-23 00:09:03.171700: train_loss -0.8038 +2024-11-23 00:09:03.171928: val_loss -0.8058 +2024-11-23 00:09:03.172008: Pseudo dice [0.8644] +2024-11-23 00:09:03.172104: Epoch time: 17.97 s +2024-11-23 00:09:04.055989: +2024-11-23 00:09:04.056210: Epoch 6713 +2024-11-23 00:09:04.056332: Current learning rate: 0.00193 +2024-11-23 00:09:23.267271: train_loss -0.8129 +2024-11-23 00:09:23.267505: val_loss -0.7799 +2024-11-23 00:09:23.267584: Pseudo dice [0.8671] +2024-11-23 00:09:23.267676: Epoch time: 19.21 s +2024-11-23 00:09:24.151812: +2024-11-23 00:09:24.152035: Epoch 6714 +2024-11-23 00:09:24.152157: Current learning rate: 0.00193 +2024-11-23 00:09:41.936355: train_loss -0.8088 +2024-11-23 00:09:41.936558: val_loss -0.7823 +2024-11-23 00:09:41.936629: Pseudo dice [0.851] +2024-11-23 00:09:41.936710: Epoch time: 17.79 s +2024-11-23 00:09:42.885318: +2024-11-23 00:09:42.885538: Epoch 6715 +2024-11-23 00:09:42.885656: Current learning rate: 0.00193 +2024-11-23 00:10:01.226524: train_loss -0.8047 +2024-11-23 00:10:01.226728: val_loss -0.7645 +2024-11-23 00:10:01.226802: Pseudo dice [0.8562] +2024-11-23 00:10:01.226879: Epoch time: 18.34 s +2024-11-23 00:10:02.114179: +2024-11-23 00:10:02.114377: Epoch 6716 +2024-11-23 00:10:02.114501: Current learning rate: 0.00193 +2024-11-23 00:10:21.386405: train_loss -0.7997 +2024-11-23 00:10:21.386695: val_loss -0.7775 +2024-11-23 00:10:21.386793: Pseudo dice [0.8576] +2024-11-23 00:10:21.386895: Epoch time: 19.27 s +2024-11-23 00:10:22.682703: +2024-11-23 00:10:22.682923: Epoch 6717 +2024-11-23 00:10:22.683048: Current learning rate: 0.00193 +2024-11-23 00:10:41.845692: train_loss -0.804 +2024-11-23 00:10:41.845943: val_loss -0.7423 +2024-11-23 00:10:41.846034: Pseudo dice [0.8624] +2024-11-23 00:10:41.846138: Epoch time: 19.16 s +2024-11-23 00:10:42.742476: +2024-11-23 00:10:42.742704: Epoch 6718 +2024-11-23 00:10:42.742825: Current learning rate: 0.00192 +2024-11-23 00:11:01.355520: train_loss -0.7967 +2024-11-23 00:11:01.355738: val_loss -0.7768 +2024-11-23 00:11:01.355815: Pseudo dice [0.859] +2024-11-23 00:11:01.355893: Epoch time: 18.61 s +2024-11-23 00:11:02.344370: +2024-11-23 00:11:02.344583: Epoch 6719 +2024-11-23 00:11:02.344707: Current learning rate: 0.00192 +2024-11-23 00:11:20.490316: train_loss -0.8054 +2024-11-23 00:11:20.490533: val_loss -0.7799 +2024-11-23 00:11:20.490615: Pseudo dice [0.857] +2024-11-23 00:11:20.490696: Epoch time: 18.15 s +2024-11-23 00:11:21.369215: +2024-11-23 00:11:21.369426: Epoch 6720 +2024-11-23 00:11:21.369538: Current learning rate: 0.00192 +2024-11-23 00:11:40.270625: train_loss -0.8137 +2024-11-23 00:11:40.270870: val_loss -0.7704 +2024-11-23 00:11:40.270957: Pseudo dice [0.8578] +2024-11-23 00:11:40.271064: Epoch time: 18.9 s +2024-11-23 00:11:41.215827: +2024-11-23 00:11:41.216045: Epoch 6721 +2024-11-23 00:11:41.216185: Current learning rate: 0.00192 +2024-11-23 00:11:58.848693: train_loss -0.8106 +2024-11-23 00:11:58.848938: val_loss -0.7776 +2024-11-23 00:11:58.849018: Pseudo dice [0.8533] +2024-11-23 00:11:58.849113: Epoch time: 17.63 s +2024-11-23 00:11:59.732504: +2024-11-23 00:11:59.732746: Epoch 6722 +2024-11-23 00:11:59.732874: Current learning rate: 0.00192 +2024-11-23 00:12:18.822403: train_loss -0.805 +2024-11-23 00:12:18.822623: val_loss -0.7978 +2024-11-23 00:12:18.822716: Pseudo dice [0.8553] +2024-11-23 00:12:18.822803: Epoch time: 19.09 s +2024-11-23 00:12:19.716840: +2024-11-23 00:12:19.717050: Epoch 6723 +2024-11-23 00:12:19.717164: Current learning rate: 0.00192 +2024-11-23 00:12:37.917745: train_loss -0.8245 +2024-11-23 00:12:37.917974: val_loss -0.7853 +2024-11-23 00:12:37.918053: Pseudo dice [0.8692] +2024-11-23 00:12:37.918141: Epoch time: 18.2 s +2024-11-23 00:12:38.799442: +2024-11-23 00:12:38.799669: Epoch 6724 +2024-11-23 00:12:38.799787: Current learning rate: 0.00192 +2024-11-23 00:12:56.289570: train_loss -0.8118 +2024-11-23 00:12:56.289792: val_loss -0.792 +2024-11-23 00:12:56.289895: Pseudo dice [0.8599] +2024-11-23 00:12:56.289992: Epoch time: 17.49 s +2024-11-23 00:12:57.207793: +2024-11-23 00:12:57.208005: Epoch 6725 +2024-11-23 00:12:57.208133: Current learning rate: 0.00192 +2024-11-23 00:13:15.534049: train_loss -0.8133 +2024-11-23 00:13:15.534271: val_loss -0.7858 +2024-11-23 00:13:15.534346: Pseudo dice [0.8497] +2024-11-23 00:13:15.534435: Epoch time: 18.33 s +2024-11-23 00:13:16.415706: +2024-11-23 00:13:16.415915: Epoch 6726 +2024-11-23 00:13:16.416029: Current learning rate: 0.00191 +2024-11-23 00:13:36.470032: train_loss -0.8051 +2024-11-23 00:13:36.470259: val_loss -0.7671 +2024-11-23 00:13:36.470369: Pseudo dice [0.8508] +2024-11-23 00:13:36.470450: Epoch time: 20.06 s +2024-11-23 00:13:37.359626: +2024-11-23 00:13:37.359829: Epoch 6727 +2024-11-23 00:13:37.359954: Current learning rate: 0.00191 +2024-11-23 00:13:56.053180: train_loss -0.8184 +2024-11-23 00:13:56.060407: val_loss -0.7769 +2024-11-23 00:13:56.060540: Pseudo dice [0.8628] +2024-11-23 00:13:56.060638: Epoch time: 18.69 s +2024-11-23 00:13:57.349371: +2024-11-23 00:13:57.349619: Epoch 6728 +2024-11-23 00:13:57.349741: Current learning rate: 0.00191 +2024-11-23 00:14:16.192333: train_loss -0.811 +2024-11-23 00:14:16.192589: val_loss -0.7892 +2024-11-23 00:14:16.192673: Pseudo dice [0.853] +2024-11-23 00:14:16.192757: Epoch time: 18.84 s +2024-11-23 00:14:17.169926: +2024-11-23 00:14:17.170185: Epoch 6729 +2024-11-23 00:14:17.170344: Current learning rate: 0.00191 +2024-11-23 00:14:34.986823: train_loss -0.8012 +2024-11-23 00:14:34.987117: val_loss -0.7695 +2024-11-23 00:14:34.987208: Pseudo dice [0.8608] +2024-11-23 00:14:34.987311: Epoch time: 17.82 s +2024-11-23 00:14:35.873491: +2024-11-23 00:14:35.873732: Epoch 6730 +2024-11-23 00:14:35.873845: Current learning rate: 0.00191 +2024-11-23 00:14:54.429700: train_loss -0.8069 +2024-11-23 00:14:54.429915: val_loss -0.7797 +2024-11-23 00:14:54.429996: Pseudo dice [0.8625] +2024-11-23 00:14:54.430110: Epoch time: 18.56 s +2024-11-23 00:14:55.319397: +2024-11-23 00:14:55.319606: Epoch 6731 +2024-11-23 00:14:55.319722: Current learning rate: 0.00191 +2024-11-23 00:15:14.218751: train_loss -0.8074 +2024-11-23 00:15:14.218959: val_loss -0.7667 +2024-11-23 00:15:14.219039: Pseudo dice [0.8604] +2024-11-23 00:15:14.219144: Epoch time: 18.9 s +2024-11-23 00:15:15.230535: +2024-11-23 00:15:15.230752: Epoch 6732 +2024-11-23 00:15:15.230874: Current learning rate: 0.00191 +2024-11-23 00:15:33.468535: train_loss -0.8093 +2024-11-23 00:15:33.468771: val_loss -0.7769 +2024-11-23 00:15:33.468845: Pseudo dice [0.8563] +2024-11-23 00:15:33.468932: Epoch time: 18.24 s +2024-11-23 00:15:34.356822: +2024-11-23 00:15:34.357033: Epoch 6733 +2024-11-23 00:15:34.357153: Current learning rate: 0.0019 +2024-11-23 00:15:52.893883: train_loss -0.8008 +2024-11-23 00:15:52.894173: val_loss -0.7788 +2024-11-23 00:15:52.894255: Pseudo dice [0.8559] +2024-11-23 00:15:52.894350: Epoch time: 18.54 s +2024-11-23 00:15:53.782869: +2024-11-23 00:15:53.783078: Epoch 6734 +2024-11-23 00:15:53.783204: Current learning rate: 0.0019 +2024-11-23 00:16:11.772785: train_loss -0.7913 +2024-11-23 00:16:11.775175: val_loss -0.7657 +2024-11-23 00:16:11.775311: Pseudo dice [0.8598] +2024-11-23 00:16:11.775404: Epoch time: 17.99 s +2024-11-23 00:16:12.688867: +2024-11-23 00:16:12.689085: Epoch 6735 +2024-11-23 00:16:12.689222: Current learning rate: 0.0019 +2024-11-23 00:16:30.508266: train_loss -0.8057 +2024-11-23 00:16:30.508543: val_loss -0.7791 +2024-11-23 00:16:30.508625: Pseudo dice [0.849] +2024-11-23 00:16:30.508711: Epoch time: 17.82 s +2024-11-23 00:16:31.392478: +2024-11-23 00:16:31.392693: Epoch 6736 +2024-11-23 00:16:31.392820: Current learning rate: 0.0019 +2024-11-23 00:16:49.476128: train_loss -0.8172 +2024-11-23 00:16:49.476359: val_loss -0.7707 +2024-11-23 00:16:49.478661: Pseudo dice [0.8532] +2024-11-23 00:16:49.478769: Epoch time: 18.08 s +2024-11-23 00:16:50.384897: +2024-11-23 00:16:50.385110: Epoch 6737 +2024-11-23 00:16:50.385243: Current learning rate: 0.0019 +2024-11-23 00:17:09.294745: train_loss -0.805 +2024-11-23 00:17:09.294964: val_loss -0.7768 +2024-11-23 00:17:09.295048: Pseudo dice [0.872] +2024-11-23 00:17:09.295148: Epoch time: 18.91 s +2024-11-23 00:17:10.177516: +2024-11-23 00:17:10.177730: Epoch 6738 +2024-11-23 00:17:10.177841: Current learning rate: 0.0019 +2024-11-23 00:17:27.915345: train_loss -0.8112 +2024-11-23 00:17:27.915564: val_loss -0.763 +2024-11-23 00:17:27.915644: Pseudo dice [0.8683] +2024-11-23 00:17:27.915723: Epoch time: 17.74 s +2024-11-23 00:17:29.345251: +2024-11-23 00:17:29.345501: Epoch 6739 +2024-11-23 00:17:29.345623: Current learning rate: 0.0019 +2024-11-23 00:17:47.730493: train_loss -0.8089 +2024-11-23 00:17:47.730747: val_loss -0.7703 +2024-11-23 00:17:47.730837: Pseudo dice [0.8511] +2024-11-23 00:17:47.730919: Epoch time: 18.39 s +2024-11-23 00:17:48.612882: +2024-11-23 00:17:48.613162: Epoch 6740 +2024-11-23 00:17:48.613283: Current learning rate: 0.00189 +2024-11-23 00:18:07.432301: train_loss -0.8123 +2024-11-23 00:18:07.432517: val_loss -0.7783 +2024-11-23 00:18:07.432599: Pseudo dice [0.8555] +2024-11-23 00:18:07.432694: Epoch time: 18.82 s +2024-11-23 00:18:08.318622: +2024-11-23 00:18:08.318844: Epoch 6741 +2024-11-23 00:18:08.318962: Current learning rate: 0.00189 +2024-11-23 00:18:27.277277: train_loss -0.8205 +2024-11-23 00:18:27.277492: val_loss -0.7875 +2024-11-23 00:18:27.277583: Pseudo dice [0.8589] +2024-11-23 00:18:27.277672: Epoch time: 18.96 s +2024-11-23 00:18:28.163608: +2024-11-23 00:18:28.163832: Epoch 6742 +2024-11-23 00:18:28.163960: Current learning rate: 0.00189 +2024-11-23 00:18:46.536474: train_loss -0.8068 +2024-11-23 00:18:46.536687: val_loss -0.7646 +2024-11-23 00:18:46.536772: Pseudo dice [0.8669] +2024-11-23 00:18:46.542264: Epoch time: 18.37 s +2024-11-23 00:18:47.444487: +2024-11-23 00:18:47.444707: Epoch 6743 +2024-11-23 00:18:47.444849: Current learning rate: 0.00189 +2024-11-23 00:19:05.447608: train_loss -0.8143 +2024-11-23 00:19:05.447871: val_loss -0.7789 +2024-11-23 00:19:05.447962: Pseudo dice [0.8588] +2024-11-23 00:19:05.450270: Epoch time: 18.0 s +2024-11-23 00:19:06.465770: +2024-11-23 00:19:06.465980: Epoch 6744 +2024-11-23 00:19:06.466092: Current learning rate: 0.00189 +2024-11-23 00:19:25.052425: train_loss -0.7939 +2024-11-23 00:19:25.052634: val_loss -0.7847 +2024-11-23 00:19:25.052713: Pseudo dice [0.8512] +2024-11-23 00:19:25.052802: Epoch time: 18.59 s +2024-11-23 00:19:25.936094: +2024-11-23 00:19:25.936314: Epoch 6745 +2024-11-23 00:19:25.936430: Current learning rate: 0.00189 +2024-11-23 00:19:45.255262: train_loss -0.8112 +2024-11-23 00:19:45.255546: val_loss -0.762 +2024-11-23 00:19:45.255628: Pseudo dice [0.8503] +2024-11-23 00:19:45.255707: Epoch time: 19.32 s +2024-11-23 00:19:46.147859: +2024-11-23 00:19:46.148072: Epoch 6746 +2024-11-23 00:19:46.148191: Current learning rate: 0.00189 +2024-11-23 00:20:03.918541: train_loss -0.8106 +2024-11-23 00:20:03.918772: val_loss -0.7772 +2024-11-23 00:20:03.918853: Pseudo dice [0.8563] +2024-11-23 00:20:03.918929: Epoch time: 17.77 s +2024-11-23 00:20:04.803579: +2024-11-23 00:20:04.803810: Epoch 6747 +2024-11-23 00:20:04.803948: Current learning rate: 0.00189 +2024-11-23 00:20:22.535016: train_loss -0.8144 +2024-11-23 00:20:22.535278: val_loss -0.7976 +2024-11-23 00:20:22.535361: Pseudo dice [0.8638] +2024-11-23 00:20:22.535454: Epoch time: 17.73 s +2024-11-23 00:20:23.427394: +2024-11-23 00:20:23.427631: Epoch 6748 +2024-11-23 00:20:23.427746: Current learning rate: 0.00188 +2024-11-23 00:20:41.343291: train_loss -0.8122 +2024-11-23 00:20:41.343499: val_loss -0.8035 +2024-11-23 00:20:41.343607: Pseudo dice [0.8545] +2024-11-23 00:20:41.343727: Epoch time: 17.92 s +2024-11-23 00:20:42.228885: +2024-11-23 00:20:42.229100: Epoch 6749 +2024-11-23 00:20:42.229225: Current learning rate: 0.00188 +2024-11-23 00:21:00.358036: train_loss -0.8137 +2024-11-23 00:21:00.358311: val_loss -0.7606 +2024-11-23 00:21:00.358401: Pseudo dice [0.8666] +2024-11-23 00:21:00.358482: Epoch time: 18.13 s +2024-11-23 00:21:01.560401: +2024-11-23 00:21:01.560612: Epoch 6750 +2024-11-23 00:21:01.560740: Current learning rate: 0.00188 +2024-11-23 00:21:20.810793: train_loss -0.8152 +2024-11-23 00:21:20.812136: val_loss -0.7857 +2024-11-23 00:21:20.812260: Pseudo dice [0.8639] +2024-11-23 00:21:20.812363: Epoch time: 19.25 s +2024-11-23 00:21:21.721602: +2024-11-23 00:21:21.721814: Epoch 6751 +2024-11-23 00:21:21.721943: Current learning rate: 0.00188 +2024-11-23 00:21:39.442595: train_loss -0.8193 +2024-11-23 00:21:39.444375: val_loss -0.7808 +2024-11-23 00:21:39.444465: Pseudo dice [0.8483] +2024-11-23 00:21:39.444551: Epoch time: 17.72 s +2024-11-23 00:21:40.416799: +2024-11-23 00:21:40.417009: Epoch 6752 +2024-11-23 00:21:40.417142: Current learning rate: 0.00188 +2024-11-23 00:21:58.306569: train_loss -0.8057 +2024-11-23 00:21:58.306787: val_loss -0.7857 +2024-11-23 00:21:58.306865: Pseudo dice [0.8578] +2024-11-23 00:21:58.306962: Epoch time: 17.89 s +2024-11-23 00:21:59.311133: +2024-11-23 00:21:59.311358: Epoch 6753 +2024-11-23 00:21:59.311472: Current learning rate: 0.00188 +2024-11-23 00:22:17.140171: train_loss -0.8137 +2024-11-23 00:22:17.140387: val_loss -0.7833 +2024-11-23 00:22:17.140461: Pseudo dice [0.8563] +2024-11-23 00:22:17.140544: Epoch time: 17.83 s +2024-11-23 00:22:18.025591: +2024-11-23 00:22:18.025790: Epoch 6754 +2024-11-23 00:22:18.025906: Current learning rate: 0.00188 +2024-11-23 00:22:36.444554: train_loss -0.8154 +2024-11-23 00:22:36.444783: val_loss -0.7755 +2024-11-23 00:22:36.444871: Pseudo dice [0.8672] +2024-11-23 00:22:36.444963: Epoch time: 18.42 s +2024-11-23 00:22:37.335402: +2024-11-23 00:22:37.335691: Epoch 6755 +2024-11-23 00:22:37.335824: Current learning rate: 0.00187 +2024-11-23 00:22:56.666903: train_loss -0.8147 +2024-11-23 00:22:56.667129: val_loss -0.7882 +2024-11-23 00:22:56.667208: Pseudo dice [0.8637] +2024-11-23 00:22:56.667292: Epoch time: 19.33 s +2024-11-23 00:22:57.551137: +2024-11-23 00:22:57.551389: Epoch 6756 +2024-11-23 00:22:57.551512: Current learning rate: 0.00187 +2024-11-23 00:23:16.834600: train_loss -0.8175 +2024-11-23 00:23:16.834811: val_loss -0.77 +2024-11-23 00:23:16.834890: Pseudo dice [0.854] +2024-11-23 00:23:16.834980: Epoch time: 19.28 s +2024-11-23 00:23:17.722899: +2024-11-23 00:23:17.723110: Epoch 6757 +2024-11-23 00:23:17.723242: Current learning rate: 0.00187 +2024-11-23 00:23:36.250842: train_loss -0.8217 +2024-11-23 00:23:36.251056: val_loss -0.7757 +2024-11-23 00:23:36.256296: Pseudo dice [0.8623] +2024-11-23 00:23:36.256499: Epoch time: 18.53 s +2024-11-23 00:23:37.161827: +2024-11-23 00:23:37.162043: Epoch 6758 +2024-11-23 00:23:37.162166: Current learning rate: 0.00187 +2024-11-23 00:23:55.423465: train_loss -0.8124 +2024-11-23 00:23:55.423697: val_loss -0.765 +2024-11-23 00:23:55.423800: Pseudo dice [0.8565] +2024-11-23 00:23:55.423882: Epoch time: 18.26 s +2024-11-23 00:23:56.308127: +2024-11-23 00:23:56.308346: Epoch 6759 +2024-11-23 00:23:56.308465: Current learning rate: 0.00187 +2024-11-23 00:24:14.773792: train_loss -0.8167 +2024-11-23 00:24:14.774013: val_loss -0.7712 +2024-11-23 00:24:14.774102: Pseudo dice [0.8443] +2024-11-23 00:24:14.774188: Epoch time: 18.47 s +2024-11-23 00:24:15.656090: +2024-11-23 00:24:15.656321: Epoch 6760 +2024-11-23 00:24:15.656438: Current learning rate: 0.00187 +2024-11-23 00:24:34.116760: train_loss -0.8148 +2024-11-23 00:24:34.117015: val_loss -0.792 +2024-11-23 00:24:34.117105: Pseudo dice [0.8628] +2024-11-23 00:24:34.117182: Epoch time: 18.46 s +2024-11-23 00:24:35.373673: +2024-11-23 00:24:35.373877: Epoch 6761 +2024-11-23 00:24:35.374001: Current learning rate: 0.00187 +2024-11-23 00:24:53.578973: train_loss -0.818 +2024-11-23 00:24:53.579221: val_loss -0.7772 +2024-11-23 00:24:53.579304: Pseudo dice [0.8514] +2024-11-23 00:24:53.579389: Epoch time: 18.21 s +2024-11-23 00:24:54.642439: +2024-11-23 00:24:54.642654: Epoch 6762 +2024-11-23 00:24:54.642768: Current learning rate: 0.00186 +2024-11-23 00:25:13.882714: train_loss -0.8161 +2024-11-23 00:25:13.882973: val_loss -0.7759 +2024-11-23 00:25:13.883084: Pseudo dice [0.8469] +2024-11-23 00:25:13.883208: Epoch time: 19.24 s +2024-11-23 00:25:14.766099: +2024-11-23 00:25:14.766310: Epoch 6763 +2024-11-23 00:25:14.766424: Current learning rate: 0.00186 +2024-11-23 00:25:32.888847: train_loss -0.8165 +2024-11-23 00:25:32.889084: val_loss -0.7782 +2024-11-23 00:25:32.889186: Pseudo dice [0.8649] +2024-11-23 00:25:32.889278: Epoch time: 18.12 s +2024-11-23 00:25:33.777209: +2024-11-23 00:25:33.777420: Epoch 6764 +2024-11-23 00:25:33.777539: Current learning rate: 0.00186 +2024-11-23 00:25:53.581718: train_loss -0.8206 +2024-11-23 00:25:53.581989: val_loss -0.7989 +2024-11-23 00:25:53.582082: Pseudo dice [0.8635] +2024-11-23 00:25:53.582160: Epoch time: 19.81 s +2024-11-23 00:25:54.474601: +2024-11-23 00:25:54.474830: Epoch 6765 +2024-11-23 00:25:54.474971: Current learning rate: 0.00186 +2024-11-23 00:26:14.032459: train_loss -0.8073 +2024-11-23 00:26:14.032670: val_loss -0.7839 +2024-11-23 00:26:14.037930: Pseudo dice [0.8674] +2024-11-23 00:26:14.038044: Epoch time: 19.56 s +2024-11-23 00:26:14.974591: +2024-11-23 00:26:14.974825: Epoch 6766 +2024-11-23 00:26:14.974940: Current learning rate: 0.00186 +2024-11-23 00:26:33.067573: train_loss -0.8061 +2024-11-23 00:26:33.067814: val_loss -0.7929 +2024-11-23 00:26:33.067890: Pseudo dice [0.8674] +2024-11-23 00:26:33.067986: Epoch time: 18.09 s +2024-11-23 00:26:33.951729: +2024-11-23 00:26:33.951938: Epoch 6767 +2024-11-23 00:26:33.952071: Current learning rate: 0.00186 +2024-11-23 00:26:52.248755: train_loss -0.8144 +2024-11-23 00:26:52.248960: val_loss -0.7949 +2024-11-23 00:26:52.249115: Pseudo dice [0.8608] +2024-11-23 00:26:52.249207: Epoch time: 18.3 s +2024-11-23 00:26:53.133491: +2024-11-23 00:26:53.133703: Epoch 6768 +2024-11-23 00:26:53.133825: Current learning rate: 0.00186 +2024-11-23 00:27:11.720231: train_loss -0.8125 +2024-11-23 00:27:11.720452: val_loss -0.7919 +2024-11-23 00:27:11.720533: Pseudo dice [0.8562] +2024-11-23 00:27:11.720946: Epoch time: 18.59 s +2024-11-23 00:27:12.614099: +2024-11-23 00:27:12.614354: Epoch 6769 +2024-11-23 00:27:12.614474: Current learning rate: 0.00186 +2024-11-23 00:27:30.576588: train_loss -0.8073 +2024-11-23 00:27:30.576823: val_loss -0.7732 +2024-11-23 00:27:30.576909: Pseudo dice [0.8527] +2024-11-23 00:27:30.577002: Epoch time: 17.96 s +2024-11-23 00:27:31.474259: +2024-11-23 00:27:31.474495: Epoch 6770 +2024-11-23 00:27:31.474614: Current learning rate: 0.00185 +2024-11-23 00:27:50.590181: train_loss -0.8198 +2024-11-23 00:27:50.590416: val_loss -0.7788 +2024-11-23 00:27:50.590502: Pseudo dice [0.8543] +2024-11-23 00:27:50.590590: Epoch time: 19.12 s +2024-11-23 00:27:51.471125: +2024-11-23 00:27:51.471307: Epoch 6771 +2024-11-23 00:27:51.471418: Current learning rate: 0.00185 +2024-11-23 00:28:09.837206: train_loss -0.8088 +2024-11-23 00:28:09.837435: val_loss -0.7818 +2024-11-23 00:28:09.837519: Pseudo dice [0.8524] +2024-11-23 00:28:09.837598: Epoch time: 18.37 s +2024-11-23 00:28:10.713986: +2024-11-23 00:28:10.714191: Epoch 6772 +2024-11-23 00:28:10.714304: Current learning rate: 0.00185 +2024-11-23 00:28:29.704944: train_loss -0.8018 +2024-11-23 00:28:29.705170: val_loss -0.7737 +2024-11-23 00:28:29.705246: Pseudo dice [0.8667] +2024-11-23 00:28:29.705322: Epoch time: 18.99 s +2024-11-23 00:28:31.010978: +2024-11-23 00:28:31.011224: Epoch 6773 +2024-11-23 00:28:31.012534: Current learning rate: 0.00185 +2024-11-23 00:28:50.185578: train_loss -0.8201 +2024-11-23 00:28:50.185868: val_loss -0.7514 +2024-11-23 00:28:50.185965: Pseudo dice [0.8604] +2024-11-23 00:28:50.186049: Epoch time: 19.18 s +2024-11-23 00:28:51.077026: +2024-11-23 00:28:51.077297: Epoch 6774 +2024-11-23 00:28:51.077450: Current learning rate: 0.00185 +2024-11-23 00:29:08.104128: train_loss -0.8186 +2024-11-23 00:29:08.104359: val_loss -0.7948 +2024-11-23 00:29:08.104456: Pseudo dice [0.8623] +2024-11-23 00:29:08.104571: Epoch time: 17.03 s +2024-11-23 00:29:08.986753: +2024-11-23 00:29:08.986981: Epoch 6775 +2024-11-23 00:29:08.987111: Current learning rate: 0.00185 +2024-11-23 00:29:28.071411: train_loss -0.8167 +2024-11-23 00:29:28.071645: val_loss -0.7691 +2024-11-23 00:29:28.071721: Pseudo dice [0.846] +2024-11-23 00:29:28.071799: Epoch time: 19.09 s +2024-11-23 00:29:28.958692: +2024-11-23 00:29:28.958908: Epoch 6776 +2024-11-23 00:29:28.959029: Current learning rate: 0.00185 +2024-11-23 00:29:47.001264: train_loss -0.823 +2024-11-23 00:29:47.001474: val_loss -0.7728 +2024-11-23 00:29:47.001553: Pseudo dice [0.8659] +2024-11-23 00:29:47.001643: Epoch time: 18.04 s +2024-11-23 00:29:47.886344: +2024-11-23 00:29:47.886534: Epoch 6777 +2024-11-23 00:29:47.886648: Current learning rate: 0.00184 +2024-11-23 00:30:06.019962: train_loss -0.8181 +2024-11-23 00:30:06.020215: val_loss -0.8048 +2024-11-23 00:30:06.020296: Pseudo dice [0.8642] +2024-11-23 00:30:06.020389: Epoch time: 18.13 s +2024-11-23 00:30:06.914728: +2024-11-23 00:30:06.915002: Epoch 6778 +2024-11-23 00:30:06.915124: Current learning rate: 0.00184 +2024-11-23 00:30:25.646522: train_loss -0.8248 +2024-11-23 00:30:25.648934: val_loss -0.7757 +2024-11-23 00:30:25.649042: Pseudo dice [0.8448] +2024-11-23 00:30:25.649127: Epoch time: 18.73 s +2024-11-23 00:30:26.560213: +2024-11-23 00:30:26.560405: Epoch 6779 +2024-11-23 00:30:26.560513: Current learning rate: 0.00184 +2024-11-23 00:30:45.104180: train_loss -0.8155 +2024-11-23 00:30:45.104442: val_loss -0.7724 +2024-11-23 00:30:45.104519: Pseudo dice [0.8577] +2024-11-23 00:30:45.104592: Epoch time: 18.54 s +2024-11-23 00:30:45.989423: +2024-11-23 00:30:45.989629: Epoch 6780 +2024-11-23 00:30:45.989748: Current learning rate: 0.00184 +2024-11-23 00:31:04.545165: train_loss -0.8219 +2024-11-23 00:31:04.545383: val_loss -0.7888 +2024-11-23 00:31:04.545476: Pseudo dice [0.8598] +2024-11-23 00:31:04.545562: Epoch time: 18.56 s +2024-11-23 00:31:05.421360: +2024-11-23 00:31:05.421577: Epoch 6781 +2024-11-23 00:31:05.421701: Current learning rate: 0.00184 +2024-11-23 00:31:23.458892: train_loss -0.8247 +2024-11-23 00:31:23.459141: val_loss -0.7745 +2024-11-23 00:31:23.459237: Pseudo dice [0.8519] +2024-11-23 00:31:23.459340: Epoch time: 18.04 s +2024-11-23 00:31:24.344225: +2024-11-23 00:31:24.344429: Epoch 6782 +2024-11-23 00:31:24.344544: Current learning rate: 0.00184 +2024-11-23 00:31:42.571335: train_loss -0.8195 +2024-11-23 00:31:42.571551: val_loss -0.7922 +2024-11-23 00:31:42.571627: Pseudo dice [0.8596] +2024-11-23 00:31:42.571709: Epoch time: 18.23 s +2024-11-23 00:31:43.461456: +2024-11-23 00:31:43.461658: Epoch 6783 +2024-11-23 00:31:43.461774: Current learning rate: 0.00184 +2024-11-23 00:32:02.755272: train_loss -0.8179 +2024-11-23 00:32:02.755482: val_loss -0.8006 +2024-11-23 00:32:02.755560: Pseudo dice [0.8624] +2024-11-23 00:32:02.755635: Epoch time: 19.29 s +2024-11-23 00:32:04.028889: +2024-11-23 00:32:04.029130: Epoch 6784 +2024-11-23 00:32:04.029267: Current learning rate: 0.00184 +2024-11-23 00:32:23.436225: train_loss -0.8256 +2024-11-23 00:32:23.436488: val_loss -0.7898 +2024-11-23 00:32:23.436582: Pseudo dice [0.8418] +2024-11-23 00:32:23.436685: Epoch time: 19.41 s +2024-11-23 00:32:24.319930: +2024-11-23 00:32:24.320392: Epoch 6785 +2024-11-23 00:32:24.320536: Current learning rate: 0.00183 +2024-11-23 00:32:42.429679: train_loss -0.815 +2024-11-23 00:32:42.429915: val_loss -0.793 +2024-11-23 00:32:42.430006: Pseudo dice [0.8707] +2024-11-23 00:32:42.430099: Epoch time: 18.11 s +2024-11-23 00:32:43.319294: +2024-11-23 00:32:43.319719: Epoch 6786 +2024-11-23 00:32:43.319866: Current learning rate: 0.00183 +2024-11-23 00:33:01.552733: train_loss -0.8201 +2024-11-23 00:33:01.552952: val_loss -0.773 +2024-11-23 00:33:01.553034: Pseudo dice [0.8573] +2024-11-23 00:33:01.553172: Epoch time: 18.23 s +2024-11-23 00:33:02.475741: +2024-11-23 00:33:02.476205: Epoch 6787 +2024-11-23 00:33:02.476357: Current learning rate: 0.00183 +2024-11-23 00:33:21.330991: train_loss -0.8184 +2024-11-23 00:33:21.331233: val_loss -0.7915 +2024-11-23 00:33:21.331329: Pseudo dice [0.8649] +2024-11-23 00:33:21.331429: Epoch time: 18.86 s +2024-11-23 00:33:22.250012: +2024-11-23 00:33:22.250399: Epoch 6788 +2024-11-23 00:33:22.250533: Current learning rate: 0.00183 +2024-11-23 00:33:40.427776: train_loss -0.8279 +2024-11-23 00:33:40.427998: val_loss -0.772 +2024-11-23 00:33:40.428109: Pseudo dice [0.8511] +2024-11-23 00:33:40.428187: Epoch time: 18.18 s +2024-11-23 00:33:41.301861: +2024-11-23 00:33:41.302272: Epoch 6789 +2024-11-23 00:33:41.302406: Current learning rate: 0.00183 +2024-11-23 00:34:00.169585: train_loss -0.8138 +2024-11-23 00:34:00.169784: val_loss -0.7729 +2024-11-23 00:34:00.169864: Pseudo dice [0.8593] +2024-11-23 00:34:00.169955: Epoch time: 18.87 s +2024-11-23 00:34:01.039999: +2024-11-23 00:34:01.040405: Epoch 6790 +2024-11-23 00:34:01.040547: Current learning rate: 0.00183 +2024-11-23 00:34:19.881842: train_loss -0.8089 +2024-11-23 00:34:19.882042: val_loss -0.7897 +2024-11-23 00:34:19.882136: Pseudo dice [0.858] +2024-11-23 00:34:19.882236: Epoch time: 18.84 s +2024-11-23 00:34:20.753761: +2024-11-23 00:34:20.754222: Epoch 6791 +2024-11-23 00:34:20.754371: Current learning rate: 0.00183 +2024-11-23 00:34:39.507200: train_loss -0.8178 +2024-11-23 00:34:39.507444: val_loss -0.7684 +2024-11-23 00:34:39.507531: Pseudo dice [0.8512] +2024-11-23 00:34:39.507619: Epoch time: 18.75 s +2024-11-23 00:34:40.382399: +2024-11-23 00:34:40.382826: Epoch 6792 +2024-11-23 00:34:40.382971: Current learning rate: 0.00182 +2024-11-23 00:34:57.677223: train_loss -0.8237 +2024-11-23 00:34:57.677433: val_loss -0.8001 +2024-11-23 00:34:57.677515: Pseudo dice [0.8681] +2024-11-23 00:34:57.677612: Epoch time: 17.3 s +2024-11-23 00:34:58.558819: +2024-11-23 00:34:58.559245: Epoch 6793 +2024-11-23 00:34:58.559380: Current learning rate: 0.00182 +2024-11-23 00:35:16.208988: train_loss -0.8216 +2024-11-23 00:35:16.209293: val_loss -0.8017 +2024-11-23 00:35:16.209375: Pseudo dice [0.8541] +2024-11-23 00:35:16.209464: Epoch time: 17.65 s +2024-11-23 00:35:17.090882: +2024-11-23 00:35:17.091318: Epoch 6794 +2024-11-23 00:35:17.091453: Current learning rate: 0.00182 +2024-11-23 00:35:35.887428: train_loss -0.8203 +2024-11-23 00:35:35.887648: val_loss -0.768 +2024-11-23 00:35:35.888187: Pseudo dice [0.849] +2024-11-23 00:35:35.888291: Epoch time: 18.8 s +2024-11-23 00:35:36.794110: +2024-11-23 00:35:36.794531: Epoch 6795 +2024-11-23 00:35:36.794679: Current learning rate: 0.00182 +2024-11-23 00:35:55.528348: train_loss -0.8192 +2024-11-23 00:35:55.528577: val_loss -0.807 +2024-11-23 00:35:55.528655: Pseudo dice [0.8665] +2024-11-23 00:35:55.528737: Epoch time: 18.74 s +2024-11-23 00:35:56.720378: +2024-11-23 00:35:56.720576: Epoch 6796 +2024-11-23 00:35:56.720686: Current learning rate: 0.00182 +2024-11-23 00:36:15.683017: train_loss -0.8193 +2024-11-23 00:36:15.683256: val_loss -0.7878 +2024-11-23 00:36:15.683402: Pseudo dice [0.8569] +2024-11-23 00:36:15.683495: Epoch time: 18.96 s +2024-11-23 00:36:16.568694: +2024-11-23 00:36:16.568919: Epoch 6797 +2024-11-23 00:36:16.569040: Current learning rate: 0.00182 +2024-11-23 00:36:35.374544: train_loss -0.8128 +2024-11-23 00:36:35.374797: val_loss -0.7574 +2024-11-23 00:36:35.374931: Pseudo dice [0.8613] +2024-11-23 00:36:35.375016: Epoch time: 18.81 s +2024-11-23 00:36:36.238281: +2024-11-23 00:36:36.238500: Epoch 6798 +2024-11-23 00:36:36.238617: Current learning rate: 0.00182 +2024-11-23 00:36:54.672079: train_loss -0.8054 +2024-11-23 00:36:54.672395: val_loss -0.7902 +2024-11-23 00:36:54.672481: Pseudo dice [0.8575] +2024-11-23 00:36:54.672568: Epoch time: 18.43 s +2024-11-23 00:36:55.617680: +2024-11-23 00:36:55.617882: Epoch 6799 +2024-11-23 00:36:55.618002: Current learning rate: 0.00181 +2024-11-23 00:37:14.759754: train_loss -0.8117 +2024-11-23 00:37:14.759971: val_loss -0.7742 +2024-11-23 00:37:14.760051: Pseudo dice [0.8599] +2024-11-23 00:37:14.760138: Epoch time: 19.14 s +2024-11-23 00:37:15.975391: +2024-11-23 00:37:15.975609: Epoch 6800 +2024-11-23 00:37:15.975723: Current learning rate: 0.00181 +2024-11-23 00:37:33.366450: train_loss -0.8187 +2024-11-23 00:37:33.366673: val_loss -0.7667 +2024-11-23 00:37:33.366756: Pseudo dice [0.8526] +2024-11-23 00:37:33.366841: Epoch time: 17.39 s +2024-11-23 00:37:34.247974: +2024-11-23 00:37:34.248186: Epoch 6801 +2024-11-23 00:37:34.248299: Current learning rate: 0.00181 +2024-11-23 00:37:52.239521: train_loss -0.8144 +2024-11-23 00:37:52.239731: val_loss -0.7665 +2024-11-23 00:37:52.239808: Pseudo dice [0.8648] +2024-11-23 00:37:52.239882: Epoch time: 17.99 s +2024-11-23 00:37:53.152954: +2024-11-23 00:37:53.153178: Epoch 6802 +2024-11-23 00:37:53.153305: Current learning rate: 0.00181 +2024-11-23 00:38:13.440506: train_loss -0.8088 +2024-11-23 00:38:13.440722: val_loss -0.7909 +2024-11-23 00:38:13.440821: Pseudo dice [0.8599] +2024-11-23 00:38:13.440907: Epoch time: 20.29 s +2024-11-23 00:38:14.326630: +2024-11-23 00:38:14.326873: Epoch 6803 +2024-11-23 00:38:14.326995: Current learning rate: 0.00181 +2024-11-23 00:38:32.833330: train_loss -0.8142 +2024-11-23 00:38:32.833557: val_loss -0.7905 +2024-11-23 00:38:32.833645: Pseudo dice [0.8676] +2024-11-23 00:38:32.833728: Epoch time: 18.51 s +2024-11-23 00:38:33.717197: +2024-11-23 00:38:33.717432: Epoch 6804 +2024-11-23 00:38:33.717561: Current learning rate: 0.00181 +2024-11-23 00:38:51.726777: train_loss -0.8089 +2024-11-23 00:38:51.726978: val_loss -0.7848 +2024-11-23 00:38:51.727067: Pseudo dice [0.8516] +2024-11-23 00:38:51.727158: Epoch time: 18.01 s +2024-11-23 00:38:52.774915: +2024-11-23 00:38:52.775137: Epoch 6805 +2024-11-23 00:38:52.775255: Current learning rate: 0.00181 +2024-11-23 00:39:10.175570: train_loss -0.8143 +2024-11-23 00:39:10.175777: val_loss -0.8074 +2024-11-23 00:39:10.175852: Pseudo dice [0.8697] +2024-11-23 00:39:10.175933: Epoch time: 17.4 s +2024-11-23 00:39:11.069395: +2024-11-23 00:39:11.069599: Epoch 6806 +2024-11-23 00:39:11.069721: Current learning rate: 0.00181 +2024-11-23 00:39:30.555341: train_loss -0.8211 +2024-11-23 00:39:30.555611: val_loss -0.7922 +2024-11-23 00:39:30.555700: Pseudo dice [0.8698] +2024-11-23 00:39:30.555784: Epoch time: 19.49 s +2024-11-23 00:39:31.816931: +2024-11-23 00:39:31.817169: Epoch 6807 +2024-11-23 00:39:31.817323: Current learning rate: 0.0018 +2024-11-23 00:39:50.728338: train_loss -0.8163 +2024-11-23 00:39:50.728580: val_loss -0.7646 +2024-11-23 00:39:50.728663: Pseudo dice [0.86] +2024-11-23 00:39:50.728742: Epoch time: 18.91 s +2024-11-23 00:39:51.601912: +2024-11-23 00:39:51.602129: Epoch 6808 +2024-11-23 00:39:51.602243: Current learning rate: 0.0018 +2024-11-23 00:40:10.537144: train_loss -0.8104 +2024-11-23 00:40:10.537374: val_loss -0.779 +2024-11-23 00:40:10.537461: Pseudo dice [0.8553] +2024-11-23 00:40:10.537560: Epoch time: 18.94 s +2024-11-23 00:40:11.432993: +2024-11-23 00:40:11.433217: Epoch 6809 +2024-11-23 00:40:11.433331: Current learning rate: 0.0018 +2024-11-23 00:40:29.255632: train_loss -0.8142 +2024-11-23 00:40:29.255906: val_loss -0.7833 +2024-11-23 00:40:29.255998: Pseudo dice [0.8614] +2024-11-23 00:40:29.256078: Epoch time: 17.82 s +2024-11-23 00:40:30.235587: +2024-11-23 00:40:30.235786: Epoch 6810 +2024-11-23 00:40:30.235898: Current learning rate: 0.0018 +2024-11-23 00:40:48.191089: train_loss -0.8232 +2024-11-23 00:40:48.191337: val_loss -0.7626 +2024-11-23 00:40:48.191416: Pseudo dice [0.8543] +2024-11-23 00:40:48.191503: Epoch time: 17.96 s +2024-11-23 00:40:49.074696: +2024-11-23 00:40:49.074908: Epoch 6811 +2024-11-23 00:40:49.075025: Current learning rate: 0.0018 +2024-11-23 00:41:06.744324: train_loss -0.8216 +2024-11-23 00:41:06.744548: val_loss -0.7769 +2024-11-23 00:41:06.744634: Pseudo dice [0.8489] +2024-11-23 00:41:06.744715: Epoch time: 17.67 s +2024-11-23 00:41:07.734636: +2024-11-23 00:41:07.734864: Epoch 6812 +2024-11-23 00:41:07.734993: Current learning rate: 0.0018 +2024-11-23 00:41:26.629114: train_loss -0.8167 +2024-11-23 00:41:26.629329: val_loss -0.7873 +2024-11-23 00:41:26.629411: Pseudo dice [0.8558] +2024-11-23 00:41:26.629487: Epoch time: 18.9 s +2024-11-23 00:41:27.504014: +2024-11-23 00:41:27.504210: Epoch 6813 +2024-11-23 00:41:27.504308: Current learning rate: 0.0018 +2024-11-23 00:41:46.783599: train_loss -0.808 +2024-11-23 00:41:46.783829: val_loss -0.7731 +2024-11-23 00:41:46.783929: Pseudo dice [0.8576] +2024-11-23 00:41:46.784012: Epoch time: 19.28 s +2024-11-23 00:41:47.674894: +2024-11-23 00:41:47.675114: Epoch 6814 +2024-11-23 00:41:47.675251: Current learning rate: 0.00179 +2024-11-23 00:42:06.436519: train_loss -0.8156 +2024-11-23 00:42:06.436761: val_loss -0.782 +2024-11-23 00:42:06.436908: Pseudo dice [0.8413] +2024-11-23 00:42:06.437021: Epoch time: 18.76 s +2024-11-23 00:42:07.374916: +2024-11-23 00:42:07.375201: Epoch 6815 +2024-11-23 00:42:07.375321: Current learning rate: 0.00179 +2024-11-23 00:42:26.515732: train_loss -0.8182 +2024-11-23 00:42:26.515987: val_loss -0.7726 +2024-11-23 00:42:26.516076: Pseudo dice [0.8672] +2024-11-23 00:42:26.516153: Epoch time: 19.14 s +2024-11-23 00:42:27.397122: +2024-11-23 00:42:27.397325: Epoch 6816 +2024-11-23 00:42:27.397453: Current learning rate: 0.00179 +2024-11-23 00:42:44.805523: train_loss -0.8232 +2024-11-23 00:42:44.805739: val_loss -0.8006 +2024-11-23 00:42:44.805827: Pseudo dice [0.8563] +2024-11-23 00:42:44.805913: Epoch time: 17.41 s +2024-11-23 00:42:45.668651: +2024-11-23 00:42:45.668855: Epoch 6817 +2024-11-23 00:42:45.668974: Current learning rate: 0.00179 +2024-11-23 00:43:05.099772: train_loss -0.809 +2024-11-23 00:43:05.100011: val_loss -0.7781 +2024-11-23 00:43:05.100147: Pseudo dice [0.8563] +2024-11-23 00:43:05.100245: Epoch time: 19.43 s +2024-11-23 00:43:05.984420: +2024-11-23 00:43:05.984614: Epoch 6818 +2024-11-23 00:43:05.984726: Current learning rate: 0.00179 +2024-11-23 00:43:23.342173: train_loss -0.8141 +2024-11-23 00:43:23.342426: val_loss -0.7737 +2024-11-23 00:43:23.342508: Pseudo dice [0.8622] +2024-11-23 00:43:23.342591: Epoch time: 17.36 s +2024-11-23 00:43:24.568200: +2024-11-23 00:43:24.568403: Epoch 6819 +2024-11-23 00:43:24.568520: Current learning rate: 0.00179 +2024-11-23 00:43:43.464385: train_loss -0.8241 +2024-11-23 00:43:43.464602: val_loss -0.7812 +2024-11-23 00:43:43.464684: Pseudo dice [0.8656] +2024-11-23 00:43:43.464760: Epoch time: 18.9 s +2024-11-23 00:43:44.343200: +2024-11-23 00:43:44.343421: Epoch 6820 +2024-11-23 00:43:44.343542: Current learning rate: 0.00179 +2024-11-23 00:44:01.994947: train_loss -0.813 +2024-11-23 00:44:01.995164: val_loss -0.7906 +2024-11-23 00:44:01.995382: Pseudo dice [0.8629] +2024-11-23 00:44:01.995473: Epoch time: 17.65 s +2024-11-23 00:44:02.875428: +2024-11-23 00:44:02.875648: Epoch 6821 +2024-11-23 00:44:02.875762: Current learning rate: 0.00178 +2024-11-23 00:44:22.856050: train_loss -0.8101 +2024-11-23 00:44:22.856295: val_loss -0.7767 +2024-11-23 00:44:22.856378: Pseudo dice [0.8527] +2024-11-23 00:44:22.856474: Epoch time: 19.98 s +2024-11-23 00:44:23.850864: +2024-11-23 00:44:23.851075: Epoch 6822 +2024-11-23 00:44:23.851196: Current learning rate: 0.00178 +2024-11-23 00:44:42.505201: train_loss -0.8147 +2024-11-23 00:44:42.505426: val_loss -0.7857 +2024-11-23 00:44:42.505507: Pseudo dice [0.8608] +2024-11-23 00:44:42.505589: Epoch time: 18.66 s +2024-11-23 00:44:43.432232: +2024-11-23 00:44:43.432445: Epoch 6823 +2024-11-23 00:44:43.432576: Current learning rate: 0.00178 +2024-11-23 00:45:02.077106: train_loss -0.8126 +2024-11-23 00:45:02.079477: val_loss -0.7851 +2024-11-23 00:45:02.079578: Pseudo dice [0.8675] +2024-11-23 00:45:02.079664: Epoch time: 18.65 s +2024-11-23 00:45:03.180218: +2024-11-23 00:45:03.180449: Epoch 6824 +2024-11-23 00:45:03.180564: Current learning rate: 0.00178 +2024-11-23 00:45:22.227968: train_loss -0.8195 +2024-11-23 00:45:22.228181: val_loss -0.782 +2024-11-23 00:45:22.228309: Pseudo dice [0.8601] +2024-11-23 00:45:22.228387: Epoch time: 19.05 s +2024-11-23 00:45:23.114002: +2024-11-23 00:45:23.114218: Epoch 6825 +2024-11-23 00:45:23.114332: Current learning rate: 0.00178 +2024-11-23 00:45:41.027746: train_loss -0.8066 +2024-11-23 00:45:41.027956: val_loss -0.7841 +2024-11-23 00:45:41.028047: Pseudo dice [0.8672] +2024-11-23 00:45:41.028132: Epoch time: 17.91 s +2024-11-23 00:45:41.910876: +2024-11-23 00:45:41.911103: Epoch 6826 +2024-11-23 00:45:41.911240: Current learning rate: 0.00178 +2024-11-23 00:46:00.927813: train_loss -0.8125 +2024-11-23 00:46:00.928067: val_loss -0.7701 +2024-11-23 00:46:00.928151: Pseudo dice [0.8573] +2024-11-23 00:46:00.928308: Epoch time: 19.02 s +2024-11-23 00:46:01.915950: +2024-11-23 00:46:01.916178: Epoch 6827 +2024-11-23 00:46:01.916290: Current learning rate: 0.00178 +2024-11-23 00:46:20.673304: train_loss -0.8158 +2024-11-23 00:46:20.673520: val_loss -0.7761 +2024-11-23 00:46:20.673597: Pseudo dice [0.8592] +2024-11-23 00:46:20.673679: Epoch time: 18.76 s +2024-11-23 00:46:21.563081: +2024-11-23 00:46:21.563290: Epoch 6828 +2024-11-23 00:46:21.563401: Current learning rate: 0.00178 +2024-11-23 00:46:40.776005: train_loss -0.8127 +2024-11-23 00:46:40.776244: val_loss -0.7464 +2024-11-23 00:46:40.776334: Pseudo dice [0.8471] +2024-11-23 00:46:40.781605: Epoch time: 19.21 s +2024-11-23 00:46:41.742007: +2024-11-23 00:46:41.742218: Epoch 6829 +2024-11-23 00:46:41.742351: Current learning rate: 0.00177 +2024-11-23 00:47:00.375857: train_loss -0.8172 +2024-11-23 00:47:00.376083: val_loss -0.7864 +2024-11-23 00:47:00.376165: Pseudo dice [0.8699] +2024-11-23 00:47:00.376244: Epoch time: 18.63 s +2024-11-23 00:47:01.640461: +2024-11-23 00:47:01.640654: Epoch 6830 +2024-11-23 00:47:01.640776: Current learning rate: 0.00177 +2024-11-23 00:47:19.978671: train_loss -0.8183 +2024-11-23 00:47:19.978931: val_loss -0.7905 +2024-11-23 00:47:19.979029: Pseudo dice [0.8562] +2024-11-23 00:47:19.979121: Epoch time: 18.34 s +2024-11-23 00:47:20.959984: +2024-11-23 00:47:20.960200: Epoch 6831 +2024-11-23 00:47:20.960333: Current learning rate: 0.00177 +2024-11-23 00:47:40.161353: train_loss -0.8161 +2024-11-23 00:47:40.161626: val_loss -0.7886 +2024-11-23 00:47:40.161706: Pseudo dice [0.8507] +2024-11-23 00:47:40.161780: Epoch time: 19.2 s +2024-11-23 00:47:41.037871: +2024-11-23 00:47:41.038098: Epoch 6832 +2024-11-23 00:47:41.038211: Current learning rate: 0.00177 +2024-11-23 00:47:59.832545: train_loss -0.811 +2024-11-23 00:47:59.832768: val_loss -0.7764 +2024-11-23 00:47:59.835014: Pseudo dice [0.8472] +2024-11-23 00:47:59.835156: Epoch time: 18.8 s +2024-11-23 00:48:00.883246: +2024-11-23 00:48:00.883479: Epoch 6833 +2024-11-23 00:48:00.883593: Current learning rate: 0.00177 +2024-11-23 00:48:20.027010: train_loss -0.8108 +2024-11-23 00:48:20.027278: val_loss -0.7602 +2024-11-23 00:48:20.027359: Pseudo dice [0.8527] +2024-11-23 00:48:20.027444: Epoch time: 19.14 s +2024-11-23 00:48:20.911718: +2024-11-23 00:48:20.911935: Epoch 6834 +2024-11-23 00:48:20.912064: Current learning rate: 0.00177 +2024-11-23 00:48:39.200654: train_loss -0.8125 +2024-11-23 00:48:39.200898: val_loss -0.7679 +2024-11-23 00:48:39.200976: Pseudo dice [0.8453] +2024-11-23 00:48:39.201079: Epoch time: 18.29 s +2024-11-23 00:48:40.084468: +2024-11-23 00:48:40.084667: Epoch 6835 +2024-11-23 00:48:40.084794: Current learning rate: 0.00177 +2024-11-23 00:48:59.101311: train_loss -0.8077 +2024-11-23 00:48:59.101520: val_loss -0.7739 +2024-11-23 00:48:59.101598: Pseudo dice [0.8403] +2024-11-23 00:48:59.101679: Epoch time: 19.02 s +2024-11-23 00:48:59.982440: +2024-11-23 00:48:59.982656: Epoch 6836 +2024-11-23 00:48:59.982787: Current learning rate: 0.00176 +2024-11-23 00:49:18.289210: train_loss -0.8151 +2024-11-23 00:49:18.289422: val_loss -0.7861 +2024-11-23 00:49:18.289583: Pseudo dice [0.872] +2024-11-23 00:49:18.289668: Epoch time: 18.31 s +2024-11-23 00:49:19.170336: +2024-11-23 00:49:19.170541: Epoch 6837 +2024-11-23 00:49:19.170671: Current learning rate: 0.00176 +2024-11-23 00:49:38.376894: train_loss -0.8142 +2024-11-23 00:49:38.377134: val_loss -0.7816 +2024-11-23 00:49:38.377214: Pseudo dice [0.8534] +2024-11-23 00:49:38.377298: Epoch time: 19.21 s +2024-11-23 00:49:39.263414: +2024-11-23 00:49:39.263640: Epoch 6838 +2024-11-23 00:49:39.263754: Current learning rate: 0.00176 +2024-11-23 00:49:56.701691: train_loss -0.8043 +2024-11-23 00:49:56.701965: val_loss -0.7681 +2024-11-23 00:49:56.702080: Pseudo dice [0.8525] +2024-11-23 00:49:56.702170: Epoch time: 17.44 s +2024-11-23 00:49:57.581547: +2024-11-23 00:49:57.581756: Epoch 6839 +2024-11-23 00:49:57.581870: Current learning rate: 0.00176 +2024-11-23 00:50:15.262786: train_loss -0.8164 +2024-11-23 00:50:15.263010: val_loss -0.7705 +2024-11-23 00:50:15.263112: Pseudo dice [0.8582] +2024-11-23 00:50:15.263204: Epoch time: 17.68 s +2024-11-23 00:50:16.142691: +2024-11-23 00:50:16.142904: Epoch 6840 +2024-11-23 00:50:16.143019: Current learning rate: 0.00176 +2024-11-23 00:50:35.084469: train_loss -0.8175 +2024-11-23 00:50:35.084697: val_loss -0.7717 +2024-11-23 00:50:35.084782: Pseudo dice [0.8726] +2024-11-23 00:50:35.084862: Epoch time: 18.94 s +2024-11-23 00:50:36.069766: +2024-11-23 00:50:36.069995: Epoch 6841 +2024-11-23 00:50:36.070112: Current learning rate: 0.00176 +2024-11-23 00:50:55.092491: train_loss -0.8159 +2024-11-23 00:50:55.092802: val_loss -0.7527 +2024-11-23 00:50:55.092891: Pseudo dice [0.8496] +2024-11-23 00:50:55.092985: Epoch time: 19.02 s +2024-11-23 00:50:56.379971: +2024-11-23 00:50:56.380159: Epoch 6842 +2024-11-23 00:50:56.380271: Current learning rate: 0.00176 +2024-11-23 00:51:14.254624: train_loss -0.8182 +2024-11-23 00:51:14.254910: val_loss -0.7999 +2024-11-23 00:51:14.254995: Pseudo dice [0.8721] +2024-11-23 00:51:14.255079: Epoch time: 17.88 s +2024-11-23 00:51:15.133390: +2024-11-23 00:51:15.133638: Epoch 6843 +2024-11-23 00:51:15.133775: Current learning rate: 0.00175 +2024-11-23 00:51:34.459138: train_loss -0.8106 +2024-11-23 00:51:34.459380: val_loss -0.7684 +2024-11-23 00:51:34.459481: Pseudo dice [0.8532] +2024-11-23 00:51:34.459650: Epoch time: 19.33 s +2024-11-23 00:51:35.341211: +2024-11-23 00:51:35.341446: Epoch 6844 +2024-11-23 00:51:35.341563: Current learning rate: 0.00175 +2024-11-23 00:51:53.174671: train_loss -0.8142 +2024-11-23 00:51:53.174937: val_loss -0.7948 +2024-11-23 00:51:53.175041: Pseudo dice [0.8552] +2024-11-23 00:51:53.175156: Epoch time: 17.83 s +2024-11-23 00:51:54.055990: +2024-11-23 00:51:54.056207: Epoch 6845 +2024-11-23 00:51:54.056324: Current learning rate: 0.00175 +2024-11-23 00:52:13.485894: train_loss -0.8186 +2024-11-23 00:52:13.486113: val_loss -0.7531 +2024-11-23 00:52:13.486216: Pseudo dice [0.8634] +2024-11-23 00:52:13.486349: Epoch time: 19.43 s +2024-11-23 00:52:14.368327: +2024-11-23 00:52:14.368546: Epoch 6846 +2024-11-23 00:52:14.368675: Current learning rate: 0.00175 +2024-11-23 00:52:32.690939: train_loss -0.8116 +2024-11-23 00:52:32.691628: val_loss -0.788 +2024-11-23 00:52:32.691746: Pseudo dice [0.8579] +2024-11-23 00:52:32.691834: Epoch time: 18.32 s +2024-11-23 00:52:33.574384: +2024-11-23 00:52:33.574591: Epoch 6847 +2024-11-23 00:52:33.574716: Current learning rate: 0.00175 +2024-11-23 00:52:51.838310: train_loss -0.822 +2024-11-23 00:52:51.838521: val_loss -0.7715 +2024-11-23 00:52:51.838608: Pseudo dice [0.8566] +2024-11-23 00:52:51.838693: Epoch time: 18.26 s +2024-11-23 00:52:52.729652: +2024-11-23 00:52:52.729885: Epoch 6848 +2024-11-23 00:52:52.729998: Current learning rate: 0.00175 +2024-11-23 00:53:10.731277: train_loss -0.8154 +2024-11-23 00:53:10.731558: val_loss -0.7691 +2024-11-23 00:53:10.731637: Pseudo dice [0.8558] +2024-11-23 00:53:10.731714: Epoch time: 18.0 s +2024-11-23 00:53:11.613472: +2024-11-23 00:53:11.613709: Epoch 6849 +2024-11-23 00:53:11.613836: Current learning rate: 0.00175 +2024-11-23 00:53:29.814155: train_loss -0.8165 +2024-11-23 00:53:29.814418: val_loss -0.7656 +2024-11-23 00:53:29.814500: Pseudo dice [0.8516] +2024-11-23 00:53:29.814588: Epoch time: 18.2 s +2024-11-23 00:53:31.020256: +2024-11-23 00:53:31.020469: Epoch 6850 +2024-11-23 00:53:31.020586: Current learning rate: 0.00175 +2024-11-23 00:53:49.261234: train_loss -0.8167 +2024-11-23 00:53:49.261436: val_loss -0.7726 +2024-11-23 00:53:49.261511: Pseudo dice [0.8566] +2024-11-23 00:53:49.261591: Epoch time: 18.24 s +2024-11-23 00:53:50.149973: +2024-11-23 00:53:50.150188: Epoch 6851 +2024-11-23 00:53:50.150322: Current learning rate: 0.00174 +2024-11-23 00:54:08.768581: train_loss -0.8224 +2024-11-23 00:54:08.768793: val_loss -0.7897 +2024-11-23 00:54:08.768870: Pseudo dice [0.8577] +2024-11-23 00:54:08.768946: Epoch time: 18.62 s +2024-11-23 00:54:09.645090: +2024-11-23 00:54:09.645303: Epoch 6852 +2024-11-23 00:54:09.645434: Current learning rate: 0.00174 +2024-11-23 00:54:29.179349: train_loss -0.8167 +2024-11-23 00:54:29.179554: val_loss -0.7687 +2024-11-23 00:54:29.179630: Pseudo dice [0.8593] +2024-11-23 00:54:29.179704: Epoch time: 19.54 s +2024-11-23 00:54:30.437391: +2024-11-23 00:54:30.437595: Epoch 6853 +2024-11-23 00:54:30.437715: Current learning rate: 0.00174 +2024-11-23 00:54:49.167103: train_loss -0.8191 +2024-11-23 00:54:49.167357: val_loss -0.7833 +2024-11-23 00:54:49.167446: Pseudo dice [0.8683] +2024-11-23 00:54:49.167528: Epoch time: 18.73 s +2024-11-23 00:54:50.041681: +2024-11-23 00:54:50.041943: Epoch 6854 +2024-11-23 00:54:50.042070: Current learning rate: 0.00174 +2024-11-23 00:55:08.318564: train_loss -0.819 +2024-11-23 00:55:08.318781: val_loss -0.7746 +2024-11-23 00:55:08.318877: Pseudo dice [0.8457] +2024-11-23 00:55:08.318950: Epoch time: 18.28 s +2024-11-23 00:55:09.203205: +2024-11-23 00:55:09.203461: Epoch 6855 +2024-11-23 00:55:09.203573: Current learning rate: 0.00174 +2024-11-23 00:55:27.126940: train_loss -0.8255 +2024-11-23 00:55:27.127156: val_loss -0.7835 +2024-11-23 00:55:27.127238: Pseudo dice [0.8616] +2024-11-23 00:55:27.127316: Epoch time: 17.92 s +2024-11-23 00:55:28.006097: +2024-11-23 00:55:28.006303: Epoch 6856 +2024-11-23 00:55:28.006423: Current learning rate: 0.00174 +2024-11-23 00:55:46.463518: train_loss -0.807 +2024-11-23 00:55:46.463754: val_loss -0.7827 +2024-11-23 00:55:46.463840: Pseudo dice [0.8647] +2024-11-23 00:55:46.463945: Epoch time: 18.46 s +2024-11-23 00:55:47.346913: +2024-11-23 00:55:47.347147: Epoch 6857 +2024-11-23 00:55:47.347278: Current learning rate: 0.00174 +2024-11-23 00:56:04.960330: train_loss -0.8204 +2024-11-23 00:56:04.960545: val_loss -0.7651 +2024-11-23 00:56:04.960624: Pseudo dice [0.8586] +2024-11-23 00:56:04.960706: Epoch time: 17.61 s +2024-11-23 00:56:05.844268: +2024-11-23 00:56:05.844473: Epoch 6858 +2024-11-23 00:56:05.844589: Current learning rate: 0.00173 +2024-11-23 00:56:25.398133: train_loss -0.8196 +2024-11-23 00:56:25.398349: val_loss -0.7814 +2024-11-23 00:56:25.398432: Pseudo dice [0.8519] +2024-11-23 00:56:25.398517: Epoch time: 19.55 s +2024-11-23 00:56:26.278775: +2024-11-23 00:56:26.278982: Epoch 6859 +2024-11-23 00:56:26.279107: Current learning rate: 0.00173 +2024-11-23 00:56:45.540052: train_loss -0.823 +2024-11-23 00:56:45.540279: val_loss -0.7786 +2024-11-23 00:56:45.540358: Pseudo dice [0.8554] +2024-11-23 00:56:45.540445: Epoch time: 19.26 s +2024-11-23 00:56:46.423323: +2024-11-23 00:56:46.423549: Epoch 6860 +2024-11-23 00:56:46.423663: Current learning rate: 0.00173 +2024-11-23 00:57:04.773890: train_loss -0.8097 +2024-11-23 00:57:04.774148: val_loss -0.7955 +2024-11-23 00:57:04.774251: Pseudo dice [0.8558] +2024-11-23 00:57:04.774334: Epoch time: 18.35 s +2024-11-23 00:57:05.653864: +2024-11-23 00:57:05.654083: Epoch 6861 +2024-11-23 00:57:05.654197: Current learning rate: 0.00173 +2024-11-23 00:57:23.794739: train_loss -0.8158 +2024-11-23 00:57:23.794951: val_loss -0.749 +2024-11-23 00:57:23.795029: Pseudo dice [0.841] +2024-11-23 00:57:23.795117: Epoch time: 18.14 s +2024-11-23 00:57:24.780904: +2024-11-23 00:57:24.781152: Epoch 6862 +2024-11-23 00:57:24.781273: Current learning rate: 0.00173 +2024-11-23 00:57:43.799717: train_loss -0.8155 +2024-11-23 00:57:43.799944: val_loss -0.7581 +2024-11-23 00:57:43.800021: Pseudo dice [0.855] +2024-11-23 00:57:43.800106: Epoch time: 19.02 s +2024-11-23 00:57:44.852004: +2024-11-23 00:57:44.852212: Epoch 6863 +2024-11-23 00:57:44.852324: Current learning rate: 0.00173 +2024-11-23 00:58:03.516594: train_loss -0.8136 +2024-11-23 00:58:03.516834: val_loss -0.7891 +2024-11-23 00:58:03.516914: Pseudo dice [0.8645] +2024-11-23 00:58:03.517001: Epoch time: 18.67 s +2024-11-23 00:58:04.504391: +2024-11-23 00:58:04.504646: Epoch 6864 +2024-11-23 00:58:04.504759: Current learning rate: 0.00173 +2024-11-23 00:58:24.140896: train_loss -0.8125 +2024-11-23 00:58:24.141142: val_loss -0.7784 +2024-11-23 00:58:24.141223: Pseudo dice [0.8683] +2024-11-23 00:58:24.141302: Epoch time: 19.64 s +2024-11-23 00:58:25.464853: +2024-11-23 00:58:25.465088: Epoch 6865 +2024-11-23 00:58:25.465203: Current learning rate: 0.00172 +2024-11-23 00:58:44.038018: train_loss -0.8182 +2024-11-23 00:58:44.038258: val_loss -0.7754 +2024-11-23 00:58:44.038343: Pseudo dice [0.8685] +2024-11-23 00:58:44.038421: Epoch time: 18.57 s +2024-11-23 00:58:44.915505: +2024-11-23 00:58:44.915731: Epoch 6866 +2024-11-23 00:58:44.915858: Current learning rate: 0.00172 +2024-11-23 00:59:03.312149: train_loss -0.8202 +2024-11-23 00:59:03.312390: val_loss -0.7878 +2024-11-23 00:59:03.312493: Pseudo dice [0.8615] +2024-11-23 00:59:03.312594: Epoch time: 18.4 s +2024-11-23 00:59:04.299950: +2024-11-23 00:59:04.300201: Epoch 6867 +2024-11-23 00:59:04.300312: Current learning rate: 0.00172 +2024-11-23 00:59:22.099543: train_loss -0.8177 +2024-11-23 00:59:22.099785: val_loss -0.7629 +2024-11-23 00:59:22.099876: Pseudo dice [0.8654] +2024-11-23 00:59:22.099973: Epoch time: 17.8 s +2024-11-23 00:59:23.092761: +2024-11-23 00:59:23.092987: Epoch 6868 +2024-11-23 00:59:23.093109: Current learning rate: 0.00172 +2024-11-23 00:59:42.445993: train_loss -0.8047 +2024-11-23 00:59:42.446275: val_loss -0.7843 +2024-11-23 00:59:42.446356: Pseudo dice [0.8385] +2024-11-23 00:59:42.446431: Epoch time: 19.35 s +2024-11-23 00:59:43.327201: +2024-11-23 00:59:43.327413: Epoch 6869 +2024-11-23 00:59:43.327528: Current learning rate: 0.00172 +2024-11-23 01:00:01.656438: train_loss -0.8159 +2024-11-23 01:00:01.656655: val_loss -0.7753 +2024-11-23 01:00:01.656735: Pseudo dice [0.8592] +2024-11-23 01:00:01.656813: Epoch time: 18.33 s +2024-11-23 01:00:02.538018: +2024-11-23 01:00:02.538258: Epoch 6870 +2024-11-23 01:00:02.538377: Current learning rate: 0.00172 +2024-11-23 01:00:20.586249: train_loss -0.8105 +2024-11-23 01:00:20.586447: val_loss -0.7935 +2024-11-23 01:00:20.586523: Pseudo dice [0.8595] +2024-11-23 01:00:20.586595: Epoch time: 18.05 s +2024-11-23 01:00:21.470678: +2024-11-23 01:00:21.470917: Epoch 6871 +2024-11-23 01:00:21.471050: Current learning rate: 0.00172 +2024-11-23 01:00:40.526999: train_loss -0.8056 +2024-11-23 01:00:40.527253: val_loss -0.7903 +2024-11-23 01:00:40.527333: Pseudo dice [0.8558] +2024-11-23 01:00:40.527426: Epoch time: 19.06 s +2024-11-23 01:00:41.444375: +2024-11-23 01:00:41.444574: Epoch 6872 +2024-11-23 01:00:41.444695: Current learning rate: 0.00172 +2024-11-23 01:00:59.342049: train_loss -0.8117 +2024-11-23 01:00:59.342571: val_loss -0.7761 +2024-11-23 01:00:59.342664: Pseudo dice [0.8631] +2024-11-23 01:00:59.342754: Epoch time: 17.9 s +2024-11-23 01:01:00.273407: +2024-11-23 01:01:00.273620: Epoch 6873 +2024-11-23 01:01:00.273734: Current learning rate: 0.00171 +2024-11-23 01:01:17.737397: train_loss -0.8167 +2024-11-23 01:01:17.737607: val_loss -0.7954 +2024-11-23 01:01:17.737681: Pseudo dice [0.8612] +2024-11-23 01:01:17.737754: Epoch time: 17.46 s +2024-11-23 01:01:18.619130: +2024-11-23 01:01:18.619331: Epoch 6874 +2024-11-23 01:01:18.619465: Current learning rate: 0.00171 +2024-11-23 01:01:36.459760: train_loss -0.8124 +2024-11-23 01:01:36.459981: val_loss -0.7804 +2024-11-23 01:01:36.460066: Pseudo dice [0.8671] +2024-11-23 01:01:36.466911: Epoch time: 17.84 s +2024-11-23 01:01:37.349953: +2024-11-23 01:01:37.350171: Epoch 6875 +2024-11-23 01:01:37.350292: Current learning rate: 0.00171 +2024-11-23 01:01:55.672467: train_loss -0.8161 +2024-11-23 01:01:55.672707: val_loss -0.7816 +2024-11-23 01:01:55.672808: Pseudo dice [0.8724] +2024-11-23 01:01:55.672890: Epoch time: 18.32 s +2024-11-23 01:01:56.923123: +2024-11-23 01:01:56.923354: Epoch 6876 +2024-11-23 01:01:56.923488: Current learning rate: 0.00171 +2024-11-23 01:02:14.569706: train_loss -0.8149 +2024-11-23 01:02:14.569952: val_loss -0.7942 +2024-11-23 01:02:14.570033: Pseudo dice [0.8546] +2024-11-23 01:02:14.570115: Epoch time: 17.65 s +2024-11-23 01:02:15.552726: +2024-11-23 01:02:15.552968: Epoch 6877 +2024-11-23 01:02:15.553100: Current learning rate: 0.00171 +2024-11-23 01:02:33.328737: train_loss -0.8144 +2024-11-23 01:02:33.328970: val_loss -0.7861 +2024-11-23 01:02:33.329050: Pseudo dice [0.8702] +2024-11-23 01:02:33.329144: Epoch time: 17.78 s +2024-11-23 01:02:34.201279: +2024-11-23 01:02:34.201506: Epoch 6878 +2024-11-23 01:02:34.201622: Current learning rate: 0.00171 +2024-11-23 01:02:53.021617: train_loss -0.8148 +2024-11-23 01:02:53.021972: val_loss -0.7736 +2024-11-23 01:02:53.022077: Pseudo dice [0.8541] +2024-11-23 01:02:53.022174: Epoch time: 18.82 s +2024-11-23 01:02:53.912207: +2024-11-23 01:02:53.912435: Epoch 6879 +2024-11-23 01:02:53.912556: Current learning rate: 0.00171 +2024-11-23 01:03:12.311607: train_loss -0.8129 +2024-11-23 01:03:12.311816: val_loss -0.7859 +2024-11-23 01:03:12.311898: Pseudo dice [0.8508] +2024-11-23 01:03:12.311975: Epoch time: 18.4 s +2024-11-23 01:03:13.190703: +2024-11-23 01:03:13.190901: Epoch 6880 +2024-11-23 01:03:13.191017: Current learning rate: 0.0017 +2024-11-23 01:03:32.398522: train_loss -0.8087 +2024-11-23 01:03:32.398752: val_loss -0.7617 +2024-11-23 01:03:32.398835: Pseudo dice [0.8537] +2024-11-23 01:03:32.398922: Epoch time: 19.21 s +2024-11-23 01:03:33.284752: +2024-11-23 01:03:33.284987: Epoch 6881 +2024-11-23 01:03:33.285117: Current learning rate: 0.0017 +2024-11-23 01:03:51.897883: train_loss -0.8154 +2024-11-23 01:03:51.898117: val_loss -0.7743 +2024-11-23 01:03:51.898196: Pseudo dice [0.8397] +2024-11-23 01:03:51.898279: Epoch time: 18.61 s +2024-11-23 01:03:52.799416: +2024-11-23 01:03:52.799651: Epoch 6882 +2024-11-23 01:03:52.799773: Current learning rate: 0.0017 +2024-11-23 01:04:11.678199: train_loss -0.8097 +2024-11-23 01:04:11.678442: val_loss -0.7944 +2024-11-23 01:04:11.678521: Pseudo dice [0.8511] +2024-11-23 01:04:11.678612: Epoch time: 18.88 s +2024-11-23 01:04:12.584696: +2024-11-23 01:04:12.584897: Epoch 6883 +2024-11-23 01:04:12.585013: Current learning rate: 0.0017 +2024-11-23 01:04:30.285865: train_loss -0.8125 +2024-11-23 01:04:30.291266: val_loss -0.7956 +2024-11-23 01:04:30.291430: Pseudo dice [0.865] +2024-11-23 01:04:30.291519: Epoch time: 17.7 s +2024-11-23 01:04:31.311472: +2024-11-23 01:04:31.311678: Epoch 6884 +2024-11-23 01:04:31.311792: Current learning rate: 0.0017 +2024-11-23 01:04:50.025412: train_loss -0.8168 +2024-11-23 01:04:50.025644: val_loss -0.7719 +2024-11-23 01:04:50.025738: Pseudo dice [0.8656] +2024-11-23 01:04:50.025815: Epoch time: 18.71 s +2024-11-23 01:04:50.904031: +2024-11-23 01:04:50.904242: Epoch 6885 +2024-11-23 01:04:50.904354: Current learning rate: 0.0017 +2024-11-23 01:05:10.247611: train_loss -0.8085 +2024-11-23 01:05:10.247833: val_loss -0.7776 +2024-11-23 01:05:10.247913: Pseudo dice [0.8639] +2024-11-23 01:05:10.247991: Epoch time: 19.34 s +2024-11-23 01:05:11.167130: +2024-11-23 01:05:11.167355: Epoch 6886 +2024-11-23 01:05:11.167495: Current learning rate: 0.0017 +2024-11-23 01:05:30.955766: train_loss -0.8146 +2024-11-23 01:05:30.956020: val_loss -0.7607 +2024-11-23 01:05:30.956109: Pseudo dice [0.8516] +2024-11-23 01:05:30.956196: Epoch time: 19.79 s +2024-11-23 01:05:31.839451: +2024-11-23 01:05:31.839651: Epoch 6887 +2024-11-23 01:05:31.839777: Current learning rate: 0.00169 +2024-11-23 01:05:50.723104: train_loss -0.8116 +2024-11-23 01:05:50.723335: val_loss -0.7713 +2024-11-23 01:05:50.723438: Pseudo dice [0.862] +2024-11-23 01:05:50.723535: Epoch time: 18.88 s +2024-11-23 01:05:52.009601: +2024-11-23 01:05:52.009820: Epoch 6888 +2024-11-23 01:05:52.009936: Current learning rate: 0.00169 +2024-11-23 01:06:10.668343: train_loss -0.8211 +2024-11-23 01:06:10.668563: val_loss -0.794 +2024-11-23 01:06:10.670783: Pseudo dice [0.8611] +2024-11-23 01:06:10.670901: Epoch time: 18.66 s +2024-11-23 01:06:11.642232: +2024-11-23 01:06:11.642478: Epoch 6889 +2024-11-23 01:06:11.642593: Current learning rate: 0.00169 +2024-11-23 01:06:30.410978: train_loss -0.8143 +2024-11-23 01:06:30.411216: val_loss -0.7755 +2024-11-23 01:06:30.411319: Pseudo dice [0.8653] +2024-11-23 01:06:30.411409: Epoch time: 18.77 s +2024-11-23 01:06:31.294091: +2024-11-23 01:06:31.294307: Epoch 6890 +2024-11-23 01:06:31.294427: Current learning rate: 0.00169 +2024-11-23 01:06:49.768333: train_loss -0.8155 +2024-11-23 01:06:49.768584: val_loss -0.7687 +2024-11-23 01:06:49.768673: Pseudo dice [0.841] +2024-11-23 01:06:49.768756: Epoch time: 18.48 s +2024-11-23 01:06:50.651073: +2024-11-23 01:06:50.651293: Epoch 6891 +2024-11-23 01:06:50.651412: Current learning rate: 0.00169 +2024-11-23 01:07:08.705031: train_loss -0.8217 +2024-11-23 01:07:08.705250: val_loss -0.7773 +2024-11-23 01:07:08.705323: Pseudo dice [0.8646] +2024-11-23 01:07:08.705398: Epoch time: 18.05 s +2024-11-23 01:07:09.675797: +2024-11-23 01:07:09.676036: Epoch 6892 +2024-11-23 01:07:09.676189: Current learning rate: 0.00169 +2024-11-23 01:07:28.994052: train_loss -0.8124 +2024-11-23 01:07:28.994291: val_loss -0.7582 +2024-11-23 01:07:28.994385: Pseudo dice [0.8603] +2024-11-23 01:07:28.994462: Epoch time: 19.32 s +2024-11-23 01:07:29.883731: +2024-11-23 01:07:29.883949: Epoch 6893 +2024-11-23 01:07:29.884077: Current learning rate: 0.00169 +2024-11-23 01:07:47.677510: train_loss -0.8196 +2024-11-23 01:07:47.677733: val_loss -0.7804 +2024-11-23 01:07:47.677818: Pseudo dice [0.8612] +2024-11-23 01:07:47.677900: Epoch time: 17.79 s +2024-11-23 01:07:48.562712: +2024-11-23 01:07:48.562912: Epoch 6894 +2024-11-23 01:07:48.563020: Current learning rate: 0.00168 +2024-11-23 01:08:07.521942: train_loss -0.8081 +2024-11-23 01:08:07.522209: val_loss -0.775 +2024-11-23 01:08:07.522311: Pseudo dice [0.868] +2024-11-23 01:08:07.522420: Epoch time: 18.96 s +2024-11-23 01:08:08.441239: +2024-11-23 01:08:08.441448: Epoch 6895 +2024-11-23 01:08:08.441562: Current learning rate: 0.00168 +2024-11-23 01:08:27.421282: train_loss -0.8165 +2024-11-23 01:08:27.421489: val_loss -0.79 +2024-11-23 01:08:27.421566: Pseudo dice [0.8553] +2024-11-23 01:08:27.421644: Epoch time: 18.98 s +2024-11-23 01:08:28.296860: +2024-11-23 01:08:28.297077: Epoch 6896 +2024-11-23 01:08:28.297189: Current learning rate: 0.00168 +2024-11-23 01:08:46.160654: train_loss -0.8219 +2024-11-23 01:08:46.160863: val_loss -0.7568 +2024-11-23 01:08:46.160938: Pseudo dice [0.8614] +2024-11-23 01:08:46.161010: Epoch time: 17.86 s +2024-11-23 01:08:47.152709: +2024-11-23 01:08:47.152946: Epoch 6897 +2024-11-23 01:08:47.153083: Current learning rate: 0.00168 +2024-11-23 01:09:05.707295: train_loss -0.8093 +2024-11-23 01:09:05.707589: val_loss -0.7894 +2024-11-23 01:09:05.707675: Pseudo dice [0.8573] +2024-11-23 01:09:05.707756: Epoch time: 18.56 s +2024-11-23 01:09:06.587359: +2024-11-23 01:09:06.587575: Epoch 6898 +2024-11-23 01:09:06.587697: Current learning rate: 0.00168 +2024-11-23 01:09:24.548309: train_loss -0.8184 +2024-11-23 01:09:24.548545: val_loss -0.7895 +2024-11-23 01:09:24.548634: Pseudo dice [0.8671] +2024-11-23 01:09:24.548762: Epoch time: 17.96 s +2024-11-23 01:09:25.428382: +2024-11-23 01:09:25.428571: Epoch 6899 +2024-11-23 01:09:25.428697: Current learning rate: 0.00168 +2024-11-23 01:09:43.670139: train_loss -0.8194 +2024-11-23 01:09:43.670415: val_loss -0.7816 +2024-11-23 01:09:43.670498: Pseudo dice [0.8535] +2024-11-23 01:09:43.670573: Epoch time: 18.24 s +2024-11-23 01:09:44.890953: +2024-11-23 01:09:44.891205: Epoch 6900 +2024-11-23 01:09:44.891333: Current learning rate: 0.00168 +2024-11-23 01:10:02.412343: train_loss -0.812 +2024-11-23 01:10:02.412555: val_loss -0.7764 +2024-11-23 01:10:02.412638: Pseudo dice [0.8662] +2024-11-23 01:10:02.412734: Epoch time: 17.52 s +2024-11-23 01:10:03.290990: +2024-11-23 01:10:03.291203: Epoch 6901 +2024-11-23 01:10:03.291314: Current learning rate: 0.00168 +2024-11-23 01:10:21.475620: train_loss -0.8124 +2024-11-23 01:10:21.475914: val_loss -0.7787 +2024-11-23 01:10:21.475999: Pseudo dice [0.8715] +2024-11-23 01:10:21.476102: Epoch time: 18.19 s +2024-11-23 01:10:22.364639: +2024-11-23 01:10:22.364884: Epoch 6902 +2024-11-23 01:10:22.365007: Current learning rate: 0.00167 +2024-11-23 01:10:41.535829: train_loss -0.8174 +2024-11-23 01:10:41.536053: val_loss -0.7873 +2024-11-23 01:10:41.536164: Pseudo dice [0.8608] +2024-11-23 01:10:41.536265: Epoch time: 19.17 s +2024-11-23 01:10:42.426360: +2024-11-23 01:10:42.426582: Epoch 6903 +2024-11-23 01:10:42.426700: Current learning rate: 0.00167 +2024-11-23 01:11:01.704899: train_loss -0.8169 +2024-11-23 01:11:01.705186: val_loss -0.7594 +2024-11-23 01:11:01.705284: Pseudo dice [0.8615] +2024-11-23 01:11:01.705370: Epoch time: 19.28 s +2024-11-23 01:11:02.585201: +2024-11-23 01:11:02.585408: Epoch 6904 +2024-11-23 01:11:02.585532: Current learning rate: 0.00167 +2024-11-23 01:11:21.161922: train_loss -0.8223 +2024-11-23 01:11:21.162140: val_loss -0.7927 +2024-11-23 01:11:21.162215: Pseudo dice [0.8603] +2024-11-23 01:11:21.162290: Epoch time: 18.58 s +2024-11-23 01:11:22.047004: +2024-11-23 01:11:22.047225: Epoch 6905 +2024-11-23 01:11:22.047373: Current learning rate: 0.00167 +2024-11-23 01:11:41.141145: train_loss -0.8169 +2024-11-23 01:11:41.141401: val_loss -0.7892 +2024-11-23 01:11:41.141501: Pseudo dice [0.8711] +2024-11-23 01:11:41.141597: Epoch time: 19.09 s +2024-11-23 01:11:42.028754: +2024-11-23 01:11:42.028961: Epoch 6906 +2024-11-23 01:11:42.029105: Current learning rate: 0.00167 +2024-11-23 01:12:00.153377: train_loss -0.8185 +2024-11-23 01:12:00.153599: val_loss -0.775 +2024-11-23 01:12:00.153681: Pseudo dice [0.8486] +2024-11-23 01:12:00.153788: Epoch time: 18.13 s +2024-11-23 01:12:01.036278: +2024-11-23 01:12:01.036491: Epoch 6907 +2024-11-23 01:12:01.036604: Current learning rate: 0.00167 +2024-11-23 01:12:20.152525: train_loss -0.8148 +2024-11-23 01:12:20.152748: val_loss -0.7661 +2024-11-23 01:12:20.152825: Pseudo dice [0.8481] +2024-11-23 01:12:20.152899: Epoch time: 19.12 s +2024-11-23 01:12:21.034581: +2024-11-23 01:12:21.034786: Epoch 6908 +2024-11-23 01:12:21.034900: Current learning rate: 0.00167 +2024-11-23 01:12:39.994488: train_loss -0.8207 +2024-11-23 01:12:39.994707: val_loss -0.7675 +2024-11-23 01:12:39.994785: Pseudo dice [0.8531] +2024-11-23 01:12:39.994859: Epoch time: 18.96 s +2024-11-23 01:12:40.877122: +2024-11-23 01:12:40.877324: Epoch 6909 +2024-11-23 01:12:40.877446: Current learning rate: 0.00166 +2024-11-23 01:12:58.904376: train_loss -0.8173 +2024-11-23 01:12:58.904632: val_loss -0.7761 +2024-11-23 01:12:58.904750: Pseudo dice [0.8638] +2024-11-23 01:12:58.904838: Epoch time: 18.03 s +2024-11-23 01:13:00.149757: +2024-11-23 01:13:00.149959: Epoch 6910 +2024-11-23 01:13:00.150075: Current learning rate: 0.00166 +2024-11-23 01:13:18.427872: train_loss -0.8253 +2024-11-23 01:13:18.428183: val_loss -0.7737 +2024-11-23 01:13:18.428267: Pseudo dice [0.852] +2024-11-23 01:13:18.428350: Epoch time: 18.28 s +2024-11-23 01:13:19.302735: +2024-11-23 01:13:19.302947: Epoch 6911 +2024-11-23 01:13:19.303081: Current learning rate: 0.00166 +2024-11-23 01:13:37.880363: train_loss -0.8207 +2024-11-23 01:13:37.880569: val_loss -0.7905 +2024-11-23 01:13:37.880650: Pseudo dice [0.8495] +2024-11-23 01:13:37.880726: Epoch time: 18.58 s +2024-11-23 01:13:38.760962: +2024-11-23 01:13:38.761189: Epoch 6912 +2024-11-23 01:13:38.761309: Current learning rate: 0.00166 +2024-11-23 01:13:57.489128: train_loss -0.821 +2024-11-23 01:13:57.489371: val_loss -0.7943 +2024-11-23 01:13:57.489477: Pseudo dice [0.863] +2024-11-23 01:13:57.489606: Epoch time: 18.73 s +2024-11-23 01:13:58.366987: +2024-11-23 01:13:58.367205: Epoch 6913 +2024-11-23 01:13:58.367318: Current learning rate: 0.00166 +2024-11-23 01:14:17.961529: train_loss -0.8224 +2024-11-23 01:14:17.961775: val_loss -0.7998 +2024-11-23 01:14:17.961871: Pseudo dice [0.8637] +2024-11-23 01:14:17.961956: Epoch time: 19.6 s +2024-11-23 01:14:18.844481: +2024-11-23 01:14:18.844689: Epoch 6914 +2024-11-23 01:14:18.844800: Current learning rate: 0.00166 +2024-11-23 01:14:37.007691: train_loss -0.8197 +2024-11-23 01:14:37.007902: val_loss -0.7929 +2024-11-23 01:14:37.007977: Pseudo dice [0.8689] +2024-11-23 01:14:37.008056: Epoch time: 18.16 s +2024-11-23 01:14:37.899457: +2024-11-23 01:14:37.899676: Epoch 6915 +2024-11-23 01:14:37.899792: Current learning rate: 0.00166 +2024-11-23 01:14:56.388513: train_loss -0.8143 +2024-11-23 01:14:56.388718: val_loss -0.7899 +2024-11-23 01:14:56.388795: Pseudo dice [0.8567] +2024-11-23 01:14:56.388874: Epoch time: 18.49 s +2024-11-23 01:14:57.272231: +2024-11-23 01:14:57.272449: Epoch 6916 +2024-11-23 01:14:57.272566: Current learning rate: 0.00165 +2024-11-23 01:15:15.312792: train_loss -0.8191 +2024-11-23 01:15:15.313000: val_loss -0.7814 +2024-11-23 01:15:15.313085: Pseudo dice [0.8675] +2024-11-23 01:15:15.313179: Epoch time: 18.04 s +2024-11-23 01:15:16.190461: +2024-11-23 01:15:16.190673: Epoch 6917 +2024-11-23 01:15:16.190800: Current learning rate: 0.00165 +2024-11-23 01:15:34.644082: train_loss -0.8154 +2024-11-23 01:15:34.644320: val_loss -0.7871 +2024-11-23 01:15:34.644399: Pseudo dice [0.8496] +2024-11-23 01:15:34.644483: Epoch time: 18.45 s +2024-11-23 01:15:35.571799: +2024-11-23 01:15:35.572018: Epoch 6918 +2024-11-23 01:15:35.572157: Current learning rate: 0.00165 +2024-11-23 01:15:53.752295: train_loss -0.8149 +2024-11-23 01:15:53.752514: val_loss -0.7742 +2024-11-23 01:15:53.752592: Pseudo dice [0.8613] +2024-11-23 01:15:53.754900: Epoch time: 18.18 s +2024-11-23 01:15:54.658870: +2024-11-23 01:15:54.659100: Epoch 6919 +2024-11-23 01:15:54.659229: Current learning rate: 0.00165 +2024-11-23 01:16:13.092237: train_loss -0.8226 +2024-11-23 01:16:13.094639: val_loss -0.7798 +2024-11-23 01:16:13.094741: Pseudo dice [0.8539] +2024-11-23 01:16:13.094836: Epoch time: 18.43 s +2024-11-23 01:16:14.062740: +2024-11-23 01:16:14.062951: Epoch 6920 +2024-11-23 01:16:14.063082: Current learning rate: 0.00165 +2024-11-23 01:16:31.841916: train_loss -0.8191 +2024-11-23 01:16:31.842197: val_loss -0.7688 +2024-11-23 01:16:31.842290: Pseudo dice [0.8572] +2024-11-23 01:16:31.842392: Epoch time: 17.78 s +2024-11-23 01:16:32.756926: +2024-11-23 01:16:32.757132: Epoch 6921 +2024-11-23 01:16:32.757243: Current learning rate: 0.00165 +2024-11-23 01:16:51.774905: train_loss -0.8203 +2024-11-23 01:16:51.775205: val_loss -0.8004 +2024-11-23 01:16:51.775299: Pseudo dice [0.8516] +2024-11-23 01:16:51.775385: Epoch time: 19.02 s +2024-11-23 01:16:53.041642: +2024-11-23 01:16:53.041892: Epoch 6922 +2024-11-23 01:16:53.042007: Current learning rate: 0.00165 +2024-11-23 01:17:11.155911: train_loss -0.8184 +2024-11-23 01:17:11.156126: val_loss -0.7727 +2024-11-23 01:17:11.156212: Pseudo dice [0.8467] +2024-11-23 01:17:11.156293: Epoch time: 18.12 s +2024-11-23 01:17:12.028918: +2024-11-23 01:17:12.029190: Epoch 6923 +2024-11-23 01:17:12.029308: Current learning rate: 0.00165 +2024-11-23 01:17:29.892824: train_loss -0.8178 +2024-11-23 01:17:29.893046: val_loss -0.7946 +2024-11-23 01:17:29.893144: Pseudo dice [0.8703] +2024-11-23 01:17:29.893241: Epoch time: 17.86 s +2024-11-23 01:17:30.769649: +2024-11-23 01:17:30.769898: Epoch 6924 +2024-11-23 01:17:30.770034: Current learning rate: 0.00164 +2024-11-23 01:17:49.526460: train_loss -0.814 +2024-11-23 01:17:49.526693: val_loss -0.7982 +2024-11-23 01:17:49.529009: Pseudo dice [0.8634] +2024-11-23 01:17:49.529123: Epoch time: 18.76 s +2024-11-23 01:17:50.464298: +2024-11-23 01:17:50.464525: Epoch 6925 +2024-11-23 01:17:50.464646: Current learning rate: 0.00164 +2024-11-23 01:18:08.859434: train_loss -0.8213 +2024-11-23 01:18:08.859664: val_loss -0.7812 +2024-11-23 01:18:08.859741: Pseudo dice [0.8641] +2024-11-23 01:18:08.859825: Epoch time: 18.4 s +2024-11-23 01:18:09.810106: +2024-11-23 01:18:09.810318: Epoch 6926 +2024-11-23 01:18:09.810437: Current learning rate: 0.00164 +2024-11-23 01:18:27.983535: train_loss -0.8203 +2024-11-23 01:18:27.983778: val_loss -0.7967 +2024-11-23 01:18:27.983865: Pseudo dice [0.8725] +2024-11-23 01:18:27.983952: Epoch time: 18.17 s +2024-11-23 01:18:28.860662: +2024-11-23 01:18:28.860879: Epoch 6927 +2024-11-23 01:18:28.860991: Current learning rate: 0.00164 +2024-11-23 01:18:46.849185: train_loss -0.8242 +2024-11-23 01:18:46.849402: val_loss -0.7695 +2024-11-23 01:18:46.849479: Pseudo dice [0.8555] +2024-11-23 01:18:46.849557: Epoch time: 17.99 s +2024-11-23 01:18:47.730646: +2024-11-23 01:18:47.730868: Epoch 6928 +2024-11-23 01:18:47.730990: Current learning rate: 0.00164 +2024-11-23 01:19:05.278906: train_loss -0.8205 +2024-11-23 01:19:05.279141: val_loss -0.775 +2024-11-23 01:19:05.279232: Pseudo dice [0.8639] +2024-11-23 01:19:05.279317: Epoch time: 17.55 s +2024-11-23 01:19:06.168236: +2024-11-23 01:19:06.168475: Epoch 6929 +2024-11-23 01:19:06.168620: Current learning rate: 0.00164 +2024-11-23 01:19:24.015301: train_loss -0.8179 +2024-11-23 01:19:24.015534: val_loss -0.7594 +2024-11-23 01:19:24.015613: Pseudo dice [0.8536] +2024-11-23 01:19:24.015712: Epoch time: 17.85 s +2024-11-23 01:19:25.098271: +2024-11-23 01:19:25.098498: Epoch 6930 +2024-11-23 01:19:25.098618: Current learning rate: 0.00164 +2024-11-23 01:19:44.451010: train_loss -0.8204 +2024-11-23 01:19:44.451276: val_loss -0.766 +2024-11-23 01:19:44.451421: Pseudo dice [0.8681] +2024-11-23 01:19:44.451516: Epoch time: 19.35 s +2024-11-23 01:19:45.338420: +2024-11-23 01:19:45.338660: Epoch 6931 +2024-11-23 01:19:45.338787: Current learning rate: 0.00163 +2024-11-23 01:20:04.447404: train_loss -0.8183 +2024-11-23 01:20:04.447627: val_loss -0.7898 +2024-11-23 01:20:04.447704: Pseudo dice [0.8611] +2024-11-23 01:20:04.447784: Epoch time: 19.11 s +2024-11-23 01:20:05.470482: +2024-11-23 01:20:05.470683: Epoch 6932 +2024-11-23 01:20:05.470795: Current learning rate: 0.00163 +2024-11-23 01:20:22.797851: train_loss -0.8203 +2024-11-23 01:20:22.798080: val_loss -0.7871 +2024-11-23 01:20:22.798163: Pseudo dice [0.8716] +2024-11-23 01:20:22.798244: Epoch time: 17.33 s +2024-11-23 01:20:23.697328: +2024-11-23 01:20:23.697571: Epoch 6933 +2024-11-23 01:20:23.697719: Current learning rate: 0.00163 +2024-11-23 01:20:43.181341: train_loss -0.8231 +2024-11-23 01:20:43.181576: val_loss -0.7903 +2024-11-23 01:20:43.181652: Pseudo dice [0.8534] +2024-11-23 01:20:43.181732: Epoch time: 19.48 s +2024-11-23 01:20:44.058681: +2024-11-23 01:20:44.058901: Epoch 6934 +2024-11-23 01:20:44.059029: Current learning rate: 0.00163 +2024-11-23 01:21:02.226402: train_loss -0.8228 +2024-11-23 01:21:02.226624: val_loss -0.7953 +2024-11-23 01:21:02.226720: Pseudo dice [0.8537] +2024-11-23 01:21:02.226817: Epoch time: 18.17 s +2024-11-23 01:21:03.107841: +2024-11-23 01:21:03.108093: Epoch 6935 +2024-11-23 01:21:03.108223: Current learning rate: 0.00163 +2024-11-23 01:21:21.815715: train_loss -0.8132 +2024-11-23 01:21:21.815917: val_loss -0.7765 +2024-11-23 01:21:21.816000: Pseudo dice [0.8631] +2024-11-23 01:21:21.816087: Epoch time: 18.71 s +2024-11-23 01:21:22.713803: +2024-11-23 01:21:22.714083: Epoch 6936 +2024-11-23 01:21:22.714217: Current learning rate: 0.00163 +2024-11-23 01:21:42.061903: train_loss -0.8108 +2024-11-23 01:21:42.062172: val_loss -0.7889 +2024-11-23 01:21:42.062259: Pseudo dice [0.8441] +2024-11-23 01:21:42.062342: Epoch time: 19.35 s +2024-11-23 01:21:42.960539: +2024-11-23 01:21:42.960762: Epoch 6937 +2024-11-23 01:21:42.960897: Current learning rate: 0.00163 +2024-11-23 01:22:01.003356: train_loss -0.8172 +2024-11-23 01:22:01.003571: val_loss -0.7723 +2024-11-23 01:22:01.003698: Pseudo dice [0.8507] +2024-11-23 01:22:01.003780: Epoch time: 18.04 s +2024-11-23 01:22:01.882249: +2024-11-23 01:22:01.882457: Epoch 6938 +2024-11-23 01:22:01.882577: Current learning rate: 0.00162 +2024-11-23 01:22:20.968644: train_loss -0.819 +2024-11-23 01:22:20.968849: val_loss -0.7709 +2024-11-23 01:22:20.968930: Pseudo dice [0.8554] +2024-11-23 01:22:20.969012: Epoch time: 19.09 s +2024-11-23 01:22:21.851705: +2024-11-23 01:22:21.851921: Epoch 6939 +2024-11-23 01:22:21.852045: Current learning rate: 0.00162 +2024-11-23 01:22:39.575984: train_loss -0.8153 +2024-11-23 01:22:39.576239: val_loss -0.7774 +2024-11-23 01:22:39.576321: Pseudo dice [0.8469] +2024-11-23 01:22:39.576404: Epoch time: 17.73 s +2024-11-23 01:22:40.629890: +2024-11-23 01:22:40.630101: Epoch 6940 +2024-11-23 01:22:40.630215: Current learning rate: 0.00162 +2024-11-23 01:22:58.604325: train_loss -0.8134 +2024-11-23 01:22:58.604566: val_loss -0.7902 +2024-11-23 01:22:58.604655: Pseudo dice [0.8611] +2024-11-23 01:22:58.604745: Epoch time: 17.98 s +2024-11-23 01:22:59.487511: +2024-11-23 01:22:59.487725: Epoch 6941 +2024-11-23 01:22:59.487875: Current learning rate: 0.00162 +2024-11-23 01:23:17.905836: train_loss -0.8202 +2024-11-23 01:23:17.906057: val_loss -0.7927 +2024-11-23 01:23:17.906159: Pseudo dice [0.8637] +2024-11-23 01:23:17.906242: Epoch time: 18.42 s +2024-11-23 01:23:18.911288: +2024-11-23 01:23:18.911531: Epoch 6942 +2024-11-23 01:23:18.911667: Current learning rate: 0.00162 +2024-11-23 01:23:38.407618: train_loss -0.8184 +2024-11-23 01:23:38.407835: val_loss -0.7922 +2024-11-23 01:23:38.407919: Pseudo dice [0.867] +2024-11-23 01:23:38.408005: Epoch time: 19.5 s +2024-11-23 01:23:39.289228: +2024-11-23 01:23:39.289427: Epoch 6943 +2024-11-23 01:23:39.289539: Current learning rate: 0.00162 +2024-11-23 01:23:58.132004: train_loss -0.8166 +2024-11-23 01:23:58.132224: val_loss -0.7535 +2024-11-23 01:23:58.132301: Pseudo dice [0.8504] +2024-11-23 01:23:58.132377: Epoch time: 18.84 s +2024-11-23 01:23:59.018571: +2024-11-23 01:23:59.018768: Epoch 6944 +2024-11-23 01:23:59.018888: Current learning rate: 0.00162 +2024-11-23 01:24:17.799408: train_loss -0.8266 +2024-11-23 01:24:17.799714: val_loss -0.7938 +2024-11-23 01:24:17.799815: Pseudo dice [0.8608] +2024-11-23 01:24:17.799906: Epoch time: 18.78 s +2024-11-23 01:24:19.080309: +2024-11-23 01:24:19.080531: Epoch 6945 +2024-11-23 01:24:19.080652: Current learning rate: 0.00161 +2024-11-23 01:24:37.540936: train_loss -0.8152 +2024-11-23 01:24:37.541159: val_loss -0.771 +2024-11-23 01:24:37.541239: Pseudo dice [0.8483] +2024-11-23 01:24:37.541328: Epoch time: 18.46 s +2024-11-23 01:24:38.424353: +2024-11-23 01:24:38.424609: Epoch 6946 +2024-11-23 01:24:38.424723: Current learning rate: 0.00161 +2024-11-23 01:24:57.311646: train_loss -0.8117 +2024-11-23 01:24:57.311861: val_loss -0.7951 +2024-11-23 01:24:57.311944: Pseudo dice [0.8661] +2024-11-23 01:24:57.312032: Epoch time: 18.89 s +2024-11-23 01:24:58.197430: +2024-11-23 01:24:58.197671: Epoch 6947 +2024-11-23 01:24:58.197787: Current learning rate: 0.00161 +2024-11-23 01:25:16.391196: train_loss -0.8144 +2024-11-23 01:25:16.391441: val_loss -0.7177 +2024-11-23 01:25:16.391541: Pseudo dice [0.8434] +2024-11-23 01:25:16.391639: Epoch time: 18.19 s +2024-11-23 01:25:17.271813: +2024-11-23 01:25:17.272032: Epoch 6948 +2024-11-23 01:25:17.272154: Current learning rate: 0.00161 +2024-11-23 01:25:36.472476: train_loss -0.8076 +2024-11-23 01:25:36.474882: val_loss -0.7608 +2024-11-23 01:25:36.474982: Pseudo dice [0.8583] +2024-11-23 01:25:36.475074: Epoch time: 19.2 s +2024-11-23 01:25:37.396919: +2024-11-23 01:25:37.397144: Epoch 6949 +2024-11-23 01:25:37.397267: Current learning rate: 0.00161 +2024-11-23 01:25:55.472622: train_loss -0.8145 +2024-11-23 01:25:55.472840: val_loss -0.7873 +2024-11-23 01:25:55.472925: Pseudo dice [0.8667] +2024-11-23 01:25:55.473006: Epoch time: 18.08 s +2024-11-23 01:25:56.682936: +2024-11-23 01:25:56.683151: Epoch 6950 +2024-11-23 01:25:56.683380: Current learning rate: 0.00161 +2024-11-23 01:26:16.470298: train_loss -0.8144 +2024-11-23 01:26:16.470572: val_loss -0.7609 +2024-11-23 01:26:16.470651: Pseudo dice [0.8499] +2024-11-23 01:26:16.470731: Epoch time: 19.79 s +2024-11-23 01:26:17.388809: +2024-11-23 01:26:17.389016: Epoch 6951 +2024-11-23 01:26:17.389142: Current learning rate: 0.00161 +2024-11-23 01:26:36.177206: train_loss -0.8141 +2024-11-23 01:26:36.177475: val_loss -0.7839 +2024-11-23 01:26:36.177553: Pseudo dice [0.8623] +2024-11-23 01:26:36.177628: Epoch time: 18.79 s +2024-11-23 01:26:37.206260: +2024-11-23 01:26:37.206472: Epoch 6952 +2024-11-23 01:26:37.206581: Current learning rate: 0.00161 +2024-11-23 01:26:55.284940: train_loss -0.8184 +2024-11-23 01:26:55.285193: val_loss -0.7802 +2024-11-23 01:26:55.285287: Pseudo dice [0.8581] +2024-11-23 01:26:55.285381: Epoch time: 18.08 s +2024-11-23 01:26:56.167083: +2024-11-23 01:26:56.167333: Epoch 6953 +2024-11-23 01:26:56.167460: Current learning rate: 0.0016 +2024-11-23 01:27:14.721933: train_loss -0.8089 +2024-11-23 01:27:14.723922: val_loss -0.7616 +2024-11-23 01:27:14.724047: Pseudo dice [0.8593] +2024-11-23 01:27:14.724152: Epoch time: 18.56 s +2024-11-23 01:27:15.660390: +2024-11-23 01:27:15.660601: Epoch 6954 +2024-11-23 01:27:15.660744: Current learning rate: 0.0016 +2024-11-23 01:27:34.602573: train_loss -0.813 +2024-11-23 01:27:34.602798: val_loss -0.7583 +2024-11-23 01:27:34.602878: Pseudo dice [0.8517] +2024-11-23 01:27:34.602962: Epoch time: 18.94 s +2024-11-23 01:27:35.489855: +2024-11-23 01:27:35.490052: Epoch 6955 +2024-11-23 01:27:35.490179: Current learning rate: 0.0016 +2024-11-23 01:27:54.845247: train_loss -0.8066 +2024-11-23 01:27:54.845462: val_loss -0.7613 +2024-11-23 01:27:54.845538: Pseudo dice [0.849] +2024-11-23 01:27:54.845613: Epoch time: 19.36 s +2024-11-23 01:27:56.296086: +2024-11-23 01:27:56.296284: Epoch 6956 +2024-11-23 01:27:56.296398: Current learning rate: 0.0016 +2024-11-23 01:28:14.072631: train_loss -0.8064 +2024-11-23 01:28:14.072895: val_loss -0.7857 +2024-11-23 01:28:14.072978: Pseudo dice [0.8615] +2024-11-23 01:28:14.073073: Epoch time: 17.78 s +2024-11-23 01:28:14.950376: +2024-11-23 01:28:14.950618: Epoch 6957 +2024-11-23 01:28:14.950742: Current learning rate: 0.0016 +2024-11-23 01:28:32.907917: train_loss -0.8144 +2024-11-23 01:28:32.908148: val_loss -0.7784 +2024-11-23 01:28:32.908232: Pseudo dice [0.8438] +2024-11-23 01:28:32.908338: Epoch time: 17.96 s +2024-11-23 01:28:33.791981: +2024-11-23 01:28:33.792192: Epoch 6958 +2024-11-23 01:28:33.792310: Current learning rate: 0.0016 +2024-11-23 01:28:52.233235: train_loss -0.8152 +2024-11-23 01:28:52.233449: val_loss -0.7652 +2024-11-23 01:28:52.233526: Pseudo dice [0.867] +2024-11-23 01:28:52.233602: Epoch time: 18.44 s +2024-11-23 01:28:53.112875: +2024-11-23 01:28:53.113098: Epoch 6959 +2024-11-23 01:28:53.113220: Current learning rate: 0.0016 +2024-11-23 01:29:12.630352: train_loss -0.8092 +2024-11-23 01:29:12.630636: val_loss -0.7908 +2024-11-23 01:29:12.630718: Pseudo dice [0.8644] +2024-11-23 01:29:12.630799: Epoch time: 19.52 s +2024-11-23 01:29:13.519050: +2024-11-23 01:29:13.519255: Epoch 6960 +2024-11-23 01:29:13.519364: Current learning rate: 0.00159 +2024-11-23 01:29:31.782602: train_loss -0.8062 +2024-11-23 01:29:31.782846: val_loss -0.7731 +2024-11-23 01:29:31.782946: Pseudo dice [0.8597] +2024-11-23 01:29:31.783040: Epoch time: 18.26 s +2024-11-23 01:29:32.663075: +2024-11-23 01:29:32.663277: Epoch 6961 +2024-11-23 01:29:32.663388: Current learning rate: 0.00159 +2024-11-23 01:29:51.935856: train_loss -0.8072 +2024-11-23 01:29:51.936108: val_loss -0.7796 +2024-11-23 01:29:51.936201: Pseudo dice [0.8557] +2024-11-23 01:29:51.936291: Epoch time: 19.27 s +2024-11-23 01:29:52.820370: +2024-11-23 01:29:52.820584: Epoch 6962 +2024-11-23 01:29:52.820712: Current learning rate: 0.00159 +2024-11-23 01:30:11.199126: train_loss -0.8138 +2024-11-23 01:30:11.199348: val_loss -0.7846 +2024-11-23 01:30:11.199424: Pseudo dice [0.866] +2024-11-23 01:30:11.199516: Epoch time: 18.38 s +2024-11-23 01:30:12.101794: +2024-11-23 01:30:12.102002: Epoch 6963 +2024-11-23 01:30:12.102135: Current learning rate: 0.00159 +2024-11-23 01:30:30.077130: train_loss -0.8206 +2024-11-23 01:30:30.077393: val_loss -0.7852 +2024-11-23 01:30:30.077511: Pseudo dice [0.86] +2024-11-23 01:30:30.077596: Epoch time: 17.98 s +2024-11-23 01:30:30.969051: +2024-11-23 01:30:30.969305: Epoch 6964 +2024-11-23 01:30:30.969488: Current learning rate: 0.00159 +2024-11-23 01:30:48.443453: train_loss -0.8216 +2024-11-23 01:30:48.443667: val_loss -0.751 +2024-11-23 01:30:48.443747: Pseudo dice [0.8634] +2024-11-23 01:30:48.443835: Epoch time: 17.48 s +2024-11-23 01:30:49.320793: +2024-11-23 01:30:49.320998: Epoch 6965 +2024-11-23 01:30:49.321120: Current learning rate: 0.00159 +2024-11-23 01:31:08.148232: train_loss -0.8151 +2024-11-23 01:31:08.148520: val_loss -0.7822 +2024-11-23 01:31:08.148618: Pseudo dice [0.8573] +2024-11-23 01:31:08.148698: Epoch time: 18.83 s +2024-11-23 01:31:09.243505: +2024-11-23 01:31:09.243727: Epoch 6966 +2024-11-23 01:31:09.243857: Current learning rate: 0.00159 +2024-11-23 01:31:27.512778: train_loss -0.8068 +2024-11-23 01:31:27.512988: val_loss -0.7657 +2024-11-23 01:31:27.513072: Pseudo dice [0.8515] +2024-11-23 01:31:27.513145: Epoch time: 18.27 s +2024-11-23 01:31:28.497858: +2024-11-23 01:31:28.498070: Epoch 6967 +2024-11-23 01:31:28.498207: Current learning rate: 0.00158 +2024-11-23 01:31:46.270779: train_loss -0.8106 +2024-11-23 01:31:46.271044: val_loss -0.7942 +2024-11-23 01:31:46.271151: Pseudo dice [0.8666] +2024-11-23 01:31:46.271248: Epoch time: 17.77 s +2024-11-23 01:31:47.692963: +2024-11-23 01:31:47.693192: Epoch 6968 +2024-11-23 01:31:47.693333: Current learning rate: 0.00158 +2024-11-23 01:32:06.400563: train_loss -0.8118 +2024-11-23 01:32:06.400778: val_loss -0.7903 +2024-11-23 01:32:06.400860: Pseudo dice [0.8632] +2024-11-23 01:32:06.400955: Epoch time: 18.71 s +2024-11-23 01:32:07.280472: +2024-11-23 01:32:07.280710: Epoch 6969 +2024-11-23 01:32:07.280842: Current learning rate: 0.00158 +2024-11-23 01:32:25.184979: train_loss -0.8205 +2024-11-23 01:32:25.185199: val_loss -0.7581 +2024-11-23 01:32:25.185294: Pseudo dice [0.8627] +2024-11-23 01:32:25.185373: Epoch time: 17.91 s +2024-11-23 01:32:26.065183: +2024-11-23 01:32:26.065399: Epoch 6970 +2024-11-23 01:32:26.065516: Current learning rate: 0.00158 +2024-11-23 01:32:43.235978: train_loss -0.8224 +2024-11-23 01:32:43.236248: val_loss -0.794 +2024-11-23 01:32:43.236332: Pseudo dice [0.8567] +2024-11-23 01:32:43.236420: Epoch time: 17.17 s +2024-11-23 01:32:44.121901: +2024-11-23 01:32:44.122134: Epoch 6971 +2024-11-23 01:32:44.122265: Current learning rate: 0.00158 +2024-11-23 01:33:02.650529: train_loss -0.8148 +2024-11-23 01:33:02.650768: val_loss -0.7584 +2024-11-23 01:33:02.650877: Pseudo dice [0.8655] +2024-11-23 01:33:02.650963: Epoch time: 18.53 s +2024-11-23 01:33:03.536590: +2024-11-23 01:33:03.536809: Epoch 6972 +2024-11-23 01:33:03.536928: Current learning rate: 0.00158 +2024-11-23 01:33:21.551614: train_loss -0.8153 +2024-11-23 01:33:21.551880: val_loss -0.7718 +2024-11-23 01:33:21.551969: Pseudo dice [0.8654] +2024-11-23 01:33:21.552043: Epoch time: 18.02 s +2024-11-23 01:33:22.436393: +2024-11-23 01:33:22.436610: Epoch 6973 +2024-11-23 01:33:22.436731: Current learning rate: 0.00158 +2024-11-23 01:33:41.082730: train_loss -0.8206 +2024-11-23 01:33:41.082956: val_loss -0.7904 +2024-11-23 01:33:41.083051: Pseudo dice [0.8506] +2024-11-23 01:33:41.083143: Epoch time: 18.65 s +2024-11-23 01:33:41.960850: +2024-11-23 01:33:41.961094: Epoch 6974 +2024-11-23 01:33:41.961213: Current learning rate: 0.00157 +2024-11-23 01:34:00.123442: train_loss -0.821 +2024-11-23 01:34:00.123695: val_loss -0.7839 +2024-11-23 01:34:00.123772: Pseudo dice [0.8708] +2024-11-23 01:34:00.123857: Epoch time: 18.16 s +2024-11-23 01:34:01.003021: +2024-11-23 01:34:01.003257: Epoch 6975 +2024-11-23 01:34:01.003371: Current learning rate: 0.00157 +2024-11-23 01:34:18.988512: train_loss -0.8214 +2024-11-23 01:34:18.988720: val_loss -0.7862 +2024-11-23 01:34:18.988798: Pseudo dice [0.8684] +2024-11-23 01:34:18.991096: Epoch time: 17.99 s +2024-11-23 01:34:19.882644: +2024-11-23 01:34:19.883243: Epoch 6976 +2024-11-23 01:34:19.883412: Current learning rate: 0.00157 +2024-11-23 01:34:38.088016: train_loss -0.8171 +2024-11-23 01:34:38.088289: val_loss -0.7863 +2024-11-23 01:34:38.088376: Pseudo dice [0.8581] +2024-11-23 01:34:38.088496: Epoch time: 18.21 s +2024-11-23 01:34:38.976007: +2024-11-23 01:34:38.976210: Epoch 6977 +2024-11-23 01:34:38.976321: Current learning rate: 0.00157 +2024-11-23 01:34:56.388423: train_loss -0.8197 +2024-11-23 01:34:56.388661: val_loss -0.7529 +2024-11-23 01:34:56.388744: Pseudo dice [0.8506] +2024-11-23 01:34:56.388851: Epoch time: 17.41 s +2024-11-23 01:34:57.264671: +2024-11-23 01:34:57.264870: Epoch 6978 +2024-11-23 01:34:57.264995: Current learning rate: 0.00157 +2024-11-23 01:35:16.131116: train_loss -0.8133 +2024-11-23 01:35:16.131359: val_loss -0.7954 +2024-11-23 01:35:16.133676: Pseudo dice [0.8561] +2024-11-23 01:35:16.133781: Epoch time: 18.87 s +2024-11-23 01:35:17.441938: +2024-11-23 01:35:17.442139: Epoch 6979 +2024-11-23 01:35:17.442259: Current learning rate: 0.00157 +2024-11-23 01:35:35.759994: train_loss -0.8088 +2024-11-23 01:35:35.760239: val_loss -0.7849 +2024-11-23 01:35:35.760336: Pseudo dice [0.8554] +2024-11-23 01:35:35.760421: Epoch time: 18.32 s +2024-11-23 01:35:36.630235: +2024-11-23 01:35:36.630457: Epoch 6980 +2024-11-23 01:35:36.630574: Current learning rate: 0.00157 +2024-11-23 01:35:55.750525: train_loss -0.8163 +2024-11-23 01:35:55.750755: val_loss -0.7757 +2024-11-23 01:35:55.750839: Pseudo dice [0.8342] +2024-11-23 01:35:55.750933: Epoch time: 19.12 s +2024-11-23 01:35:56.695048: +2024-11-23 01:35:56.695251: Epoch 6981 +2024-11-23 01:35:56.695363: Current learning rate: 0.00157 +2024-11-23 01:36:15.234566: train_loss -0.812 +2024-11-23 01:36:15.234804: val_loss -0.7766 +2024-11-23 01:36:15.234891: Pseudo dice [0.8604] +2024-11-23 01:36:15.234981: Epoch time: 18.54 s +2024-11-23 01:36:16.320453: +2024-11-23 01:36:16.320677: Epoch 6982 +2024-11-23 01:36:16.320804: Current learning rate: 0.00156 +2024-11-23 01:36:34.465469: train_loss -0.8092 +2024-11-23 01:36:34.465726: val_loss -0.7761 +2024-11-23 01:36:34.465823: Pseudo dice [0.8605] +2024-11-23 01:36:34.465915: Epoch time: 18.15 s +2024-11-23 01:36:35.351106: +2024-11-23 01:36:35.351341: Epoch 6983 +2024-11-23 01:36:35.351454: Current learning rate: 0.00156 +2024-11-23 01:36:53.230141: train_loss -0.8182 +2024-11-23 01:36:53.230373: val_loss -0.781 +2024-11-23 01:36:53.230480: Pseudo dice [0.8693] +2024-11-23 01:36:53.230568: Epoch time: 17.88 s +2024-11-23 01:36:54.273700: +2024-11-23 01:36:54.273938: Epoch 6984 +2024-11-23 01:36:54.274076: Current learning rate: 0.00156 +2024-11-23 01:37:13.302154: train_loss -0.8175 +2024-11-23 01:37:13.302385: val_loss -0.7855 +2024-11-23 01:37:13.302475: Pseudo dice [0.8633] +2024-11-23 01:37:13.302577: Epoch time: 19.03 s +2024-11-23 01:37:14.217028: +2024-11-23 01:37:14.217229: Epoch 6985 +2024-11-23 01:37:14.217358: Current learning rate: 0.00156 +2024-11-23 01:37:32.364323: train_loss -0.8248 +2024-11-23 01:37:32.364557: val_loss -0.7564 +2024-11-23 01:37:32.364641: Pseudo dice [0.8655] +2024-11-23 01:37:32.364743: Epoch time: 18.15 s +2024-11-23 01:37:33.259368: +2024-11-23 01:37:33.259618: Epoch 6986 +2024-11-23 01:37:33.259733: Current learning rate: 0.00156 +2024-11-23 01:37:52.261527: train_loss -0.8226 +2024-11-23 01:37:52.261858: val_loss -0.7951 +2024-11-23 01:37:52.261951: Pseudo dice [0.8687] +2024-11-23 01:37:52.262040: Epoch time: 19.0 s +2024-11-23 01:37:53.146919: +2024-11-23 01:37:53.147131: Epoch 6987 +2024-11-23 01:37:53.147254: Current learning rate: 0.00156 +2024-11-23 01:38:11.453348: train_loss -0.8219 +2024-11-23 01:38:11.453572: val_loss -0.7949 +2024-11-23 01:38:11.453659: Pseudo dice [0.8597] +2024-11-23 01:38:11.453743: Epoch time: 18.31 s +2024-11-23 01:38:12.344437: +2024-11-23 01:38:12.344706: Epoch 6988 +2024-11-23 01:38:12.344826: Current learning rate: 0.00156 +2024-11-23 01:38:30.723618: train_loss -0.8231 +2024-11-23 01:38:30.723829: val_loss -0.7713 +2024-11-23 01:38:30.723905: Pseudo dice [0.8633] +2024-11-23 01:38:30.723987: Epoch time: 18.38 s +2024-11-23 01:38:31.607074: +2024-11-23 01:38:31.607275: Epoch 6989 +2024-11-23 01:38:31.607383: Current learning rate: 0.00155 +2024-11-23 01:38:49.913393: train_loss -0.8172 +2024-11-23 01:38:49.913614: val_loss -0.758 +2024-11-23 01:38:49.913691: Pseudo dice [0.858] +2024-11-23 01:38:49.913774: Epoch time: 18.31 s +2024-11-23 01:38:50.788446: +2024-11-23 01:38:50.788648: Epoch 6990 +2024-11-23 01:38:50.788767: Current learning rate: 0.00155 +2024-11-23 01:39:09.852813: train_loss -0.8146 +2024-11-23 01:39:09.853056: val_loss -0.7875 +2024-11-23 01:39:09.853153: Pseudo dice [0.8741] +2024-11-23 01:39:09.853269: Epoch time: 19.07 s +2024-11-23 01:39:11.136039: +2024-11-23 01:39:11.136283: Epoch 6991 +2024-11-23 01:39:11.136405: Current learning rate: 0.00155 +2024-11-23 01:39:29.909292: train_loss -0.8178 +2024-11-23 01:39:29.909530: val_loss -0.7782 +2024-11-23 01:39:29.909616: Pseudo dice [0.8506] +2024-11-23 01:39:29.909694: Epoch time: 18.77 s +2024-11-23 01:39:30.976815: +2024-11-23 01:39:30.977022: Epoch 6992 +2024-11-23 01:39:30.977149: Current learning rate: 0.00155 +2024-11-23 01:39:49.334117: train_loss -0.8147 +2024-11-23 01:39:49.334346: val_loss -0.7679 +2024-11-23 01:39:49.334422: Pseudo dice [0.8659] +2024-11-23 01:39:49.334497: Epoch time: 18.36 s +2024-11-23 01:39:50.214855: +2024-11-23 01:39:50.215071: Epoch 6993 +2024-11-23 01:39:50.215185: Current learning rate: 0.00155 +2024-11-23 01:40:07.726304: train_loss -0.8185 +2024-11-23 01:40:07.726558: val_loss -0.7995 +2024-11-23 01:40:07.726647: Pseudo dice [0.8577] +2024-11-23 01:40:07.726734: Epoch time: 17.51 s +2024-11-23 01:40:08.735352: +2024-11-23 01:40:08.735559: Epoch 6994 +2024-11-23 01:40:08.735668: Current learning rate: 0.00155 +2024-11-23 01:40:27.684307: train_loss -0.8226 +2024-11-23 01:40:27.684528: val_loss -0.7828 +2024-11-23 01:40:27.684608: Pseudo dice [0.8629] +2024-11-23 01:40:27.684693: Epoch time: 18.95 s +2024-11-23 01:40:28.569624: +2024-11-23 01:40:28.569836: Epoch 6995 +2024-11-23 01:40:28.569952: Current learning rate: 0.00155 +2024-11-23 01:40:48.059304: train_loss -0.8258 +2024-11-23 01:40:48.059523: val_loss -0.7631 +2024-11-23 01:40:48.059599: Pseudo dice [0.8567] +2024-11-23 01:40:48.059677: Epoch time: 19.49 s +2024-11-23 01:40:48.946063: +2024-11-23 01:40:48.946285: Epoch 6996 +2024-11-23 01:40:48.946403: Current learning rate: 0.00154 +2024-11-23 01:41:07.136161: train_loss -0.8185 +2024-11-23 01:41:07.136369: val_loss -0.7647 +2024-11-23 01:41:07.136459: Pseudo dice [0.8601] +2024-11-23 01:41:07.136544: Epoch time: 18.19 s +2024-11-23 01:41:08.019653: +2024-11-23 01:41:08.019867: Epoch 6997 +2024-11-23 01:41:08.019985: Current learning rate: 0.00154 +2024-11-23 01:41:26.043025: train_loss -0.8209 +2024-11-23 01:41:26.043254: val_loss -0.7583 +2024-11-23 01:41:26.043337: Pseudo dice [0.8534] +2024-11-23 01:41:26.043423: Epoch time: 18.02 s +2024-11-23 01:41:26.936434: +2024-11-23 01:41:26.936714: Epoch 6998 +2024-11-23 01:41:26.936864: Current learning rate: 0.00154 +2024-11-23 01:41:44.914620: train_loss -0.8228 +2024-11-23 01:41:44.914851: val_loss -0.7904 +2024-11-23 01:41:44.914945: Pseudo dice [0.8661] +2024-11-23 01:41:44.915025: Epoch time: 17.98 s +2024-11-23 01:41:45.822900: +2024-11-23 01:41:45.823124: Epoch 6999 +2024-11-23 01:41:45.823246: Current learning rate: 0.00154 +2024-11-23 01:42:04.293249: train_loss -0.8216 +2024-11-23 01:42:04.293489: val_loss -0.7755 +2024-11-23 01:42:04.293567: Pseudo dice [0.8476] +2024-11-23 01:42:04.293652: Epoch time: 18.47 s +2024-11-23 01:42:05.561509: +2024-11-23 01:42:05.561721: Epoch 7000 +2024-11-23 01:42:05.561847: Current learning rate: 0.00154 +2024-11-23 01:42:24.596291: train_loss -0.8168 +2024-11-23 01:42:24.596523: val_loss -0.7739 +2024-11-23 01:42:24.601755: Pseudo dice [0.8502] +2024-11-23 01:42:24.601889: Epoch time: 19.04 s +2024-11-23 01:42:25.499968: +2024-11-23 01:42:25.500163: Epoch 7001 +2024-11-23 01:42:25.500273: Current learning rate: 0.00154 +2024-11-23 01:42:45.245080: train_loss -0.8178 +2024-11-23 01:42:45.245395: val_loss -0.7802 +2024-11-23 01:42:45.245486: Pseudo dice [0.8621] +2024-11-23 01:42:45.245574: Epoch time: 19.75 s +2024-11-23 01:42:46.130176: +2024-11-23 01:42:46.130396: Epoch 7002 +2024-11-23 01:42:46.130517: Current learning rate: 0.00154 +2024-11-23 01:43:04.790383: train_loss -0.8102 +2024-11-23 01:43:04.790626: val_loss -0.7734 +2024-11-23 01:43:04.790711: Pseudo dice [0.8658] +2024-11-23 01:43:04.790794: Epoch time: 18.66 s +2024-11-23 01:43:05.674099: +2024-11-23 01:43:05.674316: Epoch 7003 +2024-11-23 01:43:05.674437: Current learning rate: 0.00153 +2024-11-23 01:43:23.600416: train_loss -0.8163 +2024-11-23 01:43:23.600622: val_loss -0.7973 +2024-11-23 01:43:23.600703: Pseudo dice [0.864] +2024-11-23 01:43:23.600788: Epoch time: 17.93 s +2024-11-23 01:43:24.481206: +2024-11-23 01:43:24.481449: Epoch 7004 +2024-11-23 01:43:24.481570: Current learning rate: 0.00153 +2024-11-23 01:43:43.196553: train_loss -0.8158 +2024-11-23 01:43:43.196780: val_loss -0.8018 +2024-11-23 01:43:43.196858: Pseudo dice [0.8668] +2024-11-23 01:43:43.196937: Epoch time: 18.72 s +2024-11-23 01:43:44.365320: +2024-11-23 01:43:44.365569: Epoch 7005 +2024-11-23 01:43:44.365699: Current learning rate: 0.00153 +2024-11-23 01:44:03.580505: train_loss -0.8136 +2024-11-23 01:44:03.580742: val_loss -0.7416 +2024-11-23 01:44:03.580822: Pseudo dice [0.8456] +2024-11-23 01:44:03.580948: Epoch time: 19.22 s +2024-11-23 01:44:04.466669: +2024-11-23 01:44:04.466914: Epoch 7006 +2024-11-23 01:44:04.467029: Current learning rate: 0.00153 +2024-11-23 01:44:23.545333: train_loss -0.8111 +2024-11-23 01:44:23.545556: val_loss -0.7682 +2024-11-23 01:44:23.545638: Pseudo dice [0.855] +2024-11-23 01:44:23.545713: Epoch time: 19.08 s +2024-11-23 01:44:24.452807: +2024-11-23 01:44:24.453011: Epoch 7007 +2024-11-23 01:44:24.453136: Current learning rate: 0.00153 +2024-11-23 01:44:43.234361: train_loss -0.8174 +2024-11-23 01:44:43.234586: val_loss -0.7741 +2024-11-23 01:44:43.234668: Pseudo dice [0.8556] +2024-11-23 01:44:43.234748: Epoch time: 18.78 s +2024-11-23 01:44:44.116736: +2024-11-23 01:44:44.116961: Epoch 7008 +2024-11-23 01:44:44.117101: Current learning rate: 0.00153 +2024-11-23 01:45:01.669863: train_loss -0.8169 +2024-11-23 01:45:01.670069: val_loss -0.7662 +2024-11-23 01:45:01.670145: Pseudo dice [0.8679] +2024-11-23 01:45:01.670226: Epoch time: 17.55 s +2024-11-23 01:45:02.549353: +2024-11-23 01:45:02.549557: Epoch 7009 +2024-11-23 01:45:02.549690: Current learning rate: 0.00153 +2024-11-23 01:45:19.813506: train_loss -0.8164 +2024-11-23 01:45:19.813820: val_loss -0.7866 +2024-11-23 01:45:19.813916: Pseudo dice [0.8685] +2024-11-23 01:45:19.814031: Epoch time: 17.26 s +2024-11-23 01:45:20.760165: +2024-11-23 01:45:20.760381: Epoch 7010 +2024-11-23 01:45:20.760500: Current learning rate: 0.00153 +2024-11-23 01:45:39.635156: train_loss -0.8199 +2024-11-23 01:45:39.635371: val_loss -0.7827 +2024-11-23 01:45:39.635470: Pseudo dice [0.8492] +2024-11-23 01:45:39.635554: Epoch time: 18.88 s +2024-11-23 01:45:40.526399: +2024-11-23 01:45:40.526610: Epoch 7011 +2024-11-23 01:45:40.526726: Current learning rate: 0.00152 +2024-11-23 01:45:59.389172: train_loss -0.8216 +2024-11-23 01:45:59.389406: val_loss -0.7746 +2024-11-23 01:45:59.389492: Pseudo dice [0.858] +2024-11-23 01:45:59.389573: Epoch time: 18.86 s +2024-11-23 01:46:00.268596: +2024-11-23 01:46:00.268830: Epoch 7012 +2024-11-23 01:46:00.268948: Current learning rate: 0.00152 +2024-11-23 01:46:18.232350: train_loss -0.8219 +2024-11-23 01:46:18.232558: val_loss -0.7792 +2024-11-23 01:46:18.232631: Pseudo dice [0.8461] +2024-11-23 01:46:18.232706: Epoch time: 17.96 s +2024-11-23 01:46:19.125463: +2024-11-23 01:46:19.125697: Epoch 7013 +2024-11-23 01:46:19.125818: Current learning rate: 0.00152 +2024-11-23 01:46:38.035942: train_loss -0.8143 +2024-11-23 01:46:38.041398: val_loss -0.7598 +2024-11-23 01:46:38.041530: Pseudo dice [0.8662] +2024-11-23 01:46:38.041631: Epoch time: 18.91 s +2024-11-23 01:46:39.422110: +2024-11-23 01:46:39.422350: Epoch 7014 +2024-11-23 01:46:39.422470: Current learning rate: 0.00152 +2024-11-23 01:46:57.654825: train_loss -0.8166 +2024-11-23 01:46:57.655043: val_loss -0.7596 +2024-11-23 01:46:57.655131: Pseudo dice [0.8526] +2024-11-23 01:46:57.657435: Epoch time: 18.23 s +2024-11-23 01:46:58.594926: +2024-11-23 01:46:58.595142: Epoch 7015 +2024-11-23 01:46:58.595252: Current learning rate: 0.00152 +2024-11-23 01:47:17.501745: train_loss -0.8154 +2024-11-23 01:47:17.501971: val_loss -0.7954 +2024-11-23 01:47:17.502054: Pseudo dice [0.876] +2024-11-23 01:47:17.502149: Epoch time: 18.91 s +2024-11-23 01:47:18.382426: +2024-11-23 01:47:18.382661: Epoch 7016 +2024-11-23 01:47:18.382779: Current learning rate: 0.00152 +2024-11-23 01:47:36.959115: train_loss -0.82 +2024-11-23 01:47:36.959359: val_loss -0.8002 +2024-11-23 01:47:36.959436: Pseudo dice [0.8743] +2024-11-23 01:47:36.959521: Epoch time: 18.58 s +2024-11-23 01:47:37.852321: +2024-11-23 01:47:37.852554: Epoch 7017 +2024-11-23 01:47:37.852669: Current learning rate: 0.00152 +2024-11-23 01:47:56.870619: train_loss -0.8155 +2024-11-23 01:47:56.870846: val_loss -0.774 +2024-11-23 01:47:56.870931: Pseudo dice [0.86] +2024-11-23 01:47:56.871026: Epoch time: 19.02 s +2024-11-23 01:47:57.772006: +2024-11-23 01:47:57.772226: Epoch 7018 +2024-11-23 01:47:57.772338: Current learning rate: 0.00151 +2024-11-23 01:48:15.751805: train_loss -0.8178 +2024-11-23 01:48:15.752025: val_loss -0.765 +2024-11-23 01:48:15.752117: Pseudo dice [0.8504] +2024-11-23 01:48:15.752200: Epoch time: 17.98 s +2024-11-23 01:48:16.630951: +2024-11-23 01:48:16.631167: Epoch 7019 +2024-11-23 01:48:16.631284: Current learning rate: 0.00151 +2024-11-23 01:48:35.997111: train_loss -0.8175 +2024-11-23 01:48:35.997330: val_loss -0.7754 +2024-11-23 01:48:35.997481: Pseudo dice [0.8567] +2024-11-23 01:48:35.997563: Epoch time: 19.37 s +2024-11-23 01:48:36.883369: +2024-11-23 01:48:36.883573: Epoch 7020 +2024-11-23 01:48:36.883687: Current learning rate: 0.00151 +2024-11-23 01:48:55.594102: train_loss -0.8218 +2024-11-23 01:48:55.594333: val_loss -0.7623 +2024-11-23 01:48:55.594414: Pseudo dice [0.8586] +2024-11-23 01:48:55.594504: Epoch time: 18.71 s +2024-11-23 01:48:56.478663: +2024-11-23 01:48:56.478897: Epoch 7021 +2024-11-23 01:48:56.479011: Current learning rate: 0.00151 +2024-11-23 01:49:14.956074: train_loss -0.8205 +2024-11-23 01:49:14.956292: val_loss -0.7824 +2024-11-23 01:49:14.956377: Pseudo dice [0.8688] +2024-11-23 01:49:14.956471: Epoch time: 18.48 s +2024-11-23 01:49:15.890818: +2024-11-23 01:49:15.891057: Epoch 7022 +2024-11-23 01:49:15.891191: Current learning rate: 0.00151 +2024-11-23 01:49:34.011013: train_loss -0.8194 +2024-11-23 01:49:34.011234: val_loss -0.7902 +2024-11-23 01:49:34.011315: Pseudo dice [0.86] +2024-11-23 01:49:34.011393: Epoch time: 18.12 s +2024-11-23 01:49:34.895881: +2024-11-23 01:49:34.896096: Epoch 7023 +2024-11-23 01:49:34.896210: Current learning rate: 0.00151 +2024-11-23 01:49:53.011205: train_loss -0.8204 +2024-11-23 01:49:53.011412: val_loss -0.7838 +2024-11-23 01:49:53.011531: Pseudo dice [0.8658] +2024-11-23 01:49:53.011618: Epoch time: 18.12 s +2024-11-23 01:49:54.099614: +2024-11-23 01:49:54.099833: Epoch 7024 +2024-11-23 01:49:54.099951: Current learning rate: 0.00151 +2024-11-23 01:50:12.523560: train_loss -0.8128 +2024-11-23 01:50:12.523798: val_loss -0.7692 +2024-11-23 01:50:12.523889: Pseudo dice [0.8642] +2024-11-23 01:50:12.523975: Epoch time: 18.42 s +2024-11-23 01:50:13.406777: +2024-11-23 01:50:13.406979: Epoch 7025 +2024-11-23 01:50:13.407100: Current learning rate: 0.0015 +2024-11-23 01:50:33.113273: train_loss -0.81 +2024-11-23 01:50:33.113511: val_loss -0.7756 +2024-11-23 01:50:33.113586: Pseudo dice [0.8564] +2024-11-23 01:50:33.113664: Epoch time: 19.71 s +2024-11-23 01:50:33.995855: +2024-11-23 01:50:33.996072: Epoch 7026 +2024-11-23 01:50:33.996192: Current learning rate: 0.0015 +2024-11-23 01:50:52.047571: train_loss -0.8215 +2024-11-23 01:50:52.047794: val_loss -0.7788 +2024-11-23 01:50:52.047906: Pseudo dice [0.8589] +2024-11-23 01:50:52.047997: Epoch time: 18.05 s +2024-11-23 01:50:53.002364: +2024-11-23 01:50:53.002594: Epoch 7027 +2024-11-23 01:50:53.002714: Current learning rate: 0.0015 +2024-11-23 01:51:12.230257: train_loss -0.8189 +2024-11-23 01:51:12.230471: val_loss -0.7991 +2024-11-23 01:51:12.230559: Pseudo dice [0.8584] +2024-11-23 01:51:12.230642: Epoch time: 19.23 s +2024-11-23 01:51:13.111352: +2024-11-23 01:51:13.111620: Epoch 7028 +2024-11-23 01:51:13.111794: Current learning rate: 0.0015 +2024-11-23 01:51:32.599323: train_loss -0.8122 +2024-11-23 01:51:32.599578: val_loss -0.7883 +2024-11-23 01:51:32.599736: Pseudo dice [0.8537] +2024-11-23 01:51:32.599834: Epoch time: 19.49 s +2024-11-23 01:51:33.485048: +2024-11-23 01:51:33.485289: Epoch 7029 +2024-11-23 01:51:33.485408: Current learning rate: 0.0015 +2024-11-23 01:51:51.611969: train_loss -0.8158 +2024-11-23 01:51:51.612188: val_loss -0.7712 +2024-11-23 01:51:51.612268: Pseudo dice [0.8471] +2024-11-23 01:51:51.612345: Epoch time: 18.13 s +2024-11-23 01:51:52.616651: +2024-11-23 01:51:52.616867: Epoch 7030 +2024-11-23 01:51:52.616985: Current learning rate: 0.0015 +2024-11-23 01:52:10.898054: train_loss -0.8176 +2024-11-23 01:52:10.898280: val_loss -0.7842 +2024-11-23 01:52:10.898360: Pseudo dice [0.8718] +2024-11-23 01:52:10.898438: Epoch time: 18.28 s +2024-11-23 01:52:11.776244: +2024-11-23 01:52:11.776464: Epoch 7031 +2024-11-23 01:52:11.776586: Current learning rate: 0.0015 +2024-11-23 01:52:30.238568: train_loss -0.8207 +2024-11-23 01:52:30.238777: val_loss -0.7703 +2024-11-23 01:52:30.238853: Pseudo dice [0.8533] +2024-11-23 01:52:30.238935: Epoch time: 18.46 s +2024-11-23 01:52:31.122413: +2024-11-23 01:52:31.122612: Epoch 7032 +2024-11-23 01:52:31.122735: Current learning rate: 0.00149 +2024-11-23 01:52:47.859263: train_loss -0.823 +2024-11-23 01:52:47.859514: val_loss -0.7895 +2024-11-23 01:52:47.859596: Pseudo dice [0.8745] +2024-11-23 01:52:47.859692: Epoch time: 16.74 s +2024-11-23 01:52:48.740372: +2024-11-23 01:52:48.740566: Epoch 7033 +2024-11-23 01:52:48.740681: Current learning rate: 0.00149 +2024-11-23 01:53:07.033946: train_loss -0.8236 +2024-11-23 01:53:07.034161: val_loss -0.7647 +2024-11-23 01:53:07.034247: Pseudo dice [0.8393] +2024-11-23 01:53:07.034338: Epoch time: 18.29 s +2024-11-23 01:53:07.912538: +2024-11-23 01:53:07.912760: Epoch 7034 +2024-11-23 01:53:07.912877: Current learning rate: 0.00149 +2024-11-23 01:53:26.566076: train_loss -0.8218 +2024-11-23 01:53:26.566301: val_loss -0.773 +2024-11-23 01:53:26.566390: Pseudo dice [0.8598] +2024-11-23 01:53:26.566471: Epoch time: 18.65 s +2024-11-23 01:53:27.546402: +2024-11-23 01:53:27.546602: Epoch 7035 +2024-11-23 01:53:27.546713: Current learning rate: 0.00149 +2024-11-23 01:53:46.124774: train_loss -0.816 +2024-11-23 01:53:46.124994: val_loss -0.7804 +2024-11-23 01:53:46.125098: Pseudo dice [0.8635] +2024-11-23 01:53:46.125197: Epoch time: 18.58 s +2024-11-23 01:53:47.007514: +2024-11-23 01:53:47.007718: Epoch 7036 +2024-11-23 01:53:47.007853: Current learning rate: 0.00149 +2024-11-23 01:54:05.937334: train_loss -0.8183 +2024-11-23 01:54:05.937571: val_loss -0.7985 +2024-11-23 01:54:05.937655: Pseudo dice [0.87] +2024-11-23 01:54:05.937775: Epoch time: 18.93 s +2024-11-23 01:54:07.227479: +2024-11-23 01:54:07.227705: Epoch 7037 +2024-11-23 01:54:07.227818: Current learning rate: 0.00149 +2024-11-23 01:54:26.046857: train_loss -0.822 +2024-11-23 01:54:26.047078: val_loss -0.77 +2024-11-23 01:54:26.047170: Pseudo dice [0.853] +2024-11-23 01:54:26.047247: Epoch time: 18.82 s +2024-11-23 01:54:26.924993: +2024-11-23 01:54:26.925222: Epoch 7038 +2024-11-23 01:54:26.925334: Current learning rate: 0.00149 +2024-11-23 01:54:44.660347: train_loss -0.8258 +2024-11-23 01:54:44.660560: val_loss -0.7639 +2024-11-23 01:54:44.660638: Pseudo dice [0.8576] +2024-11-23 01:54:44.660720: Epoch time: 17.74 s +2024-11-23 01:54:45.573444: +2024-11-23 01:54:45.573678: Epoch 7039 +2024-11-23 01:54:45.573798: Current learning rate: 0.00148 +2024-11-23 01:55:03.735828: train_loss -0.8214 +2024-11-23 01:55:03.736081: val_loss -0.7704 +2024-11-23 01:55:03.736176: Pseudo dice [0.8608] +2024-11-23 01:55:03.738517: Epoch time: 18.16 s +2024-11-23 01:55:04.670462: +2024-11-23 01:55:04.670683: Epoch 7040 +2024-11-23 01:55:04.670799: Current learning rate: 0.00148 +2024-11-23 01:55:23.719970: train_loss -0.815 +2024-11-23 01:55:23.720197: val_loss -0.7649 +2024-11-23 01:55:23.720279: Pseudo dice [0.8597] +2024-11-23 01:55:23.720358: Epoch time: 19.05 s +2024-11-23 01:55:24.604888: +2024-11-23 01:55:24.605106: Epoch 7041 +2024-11-23 01:55:24.605242: Current learning rate: 0.00148 +2024-11-23 01:55:41.951617: train_loss -0.8232 +2024-11-23 01:55:41.951900: val_loss -0.7947 +2024-11-23 01:55:41.951986: Pseudo dice [0.8561] +2024-11-23 01:55:41.952072: Epoch time: 17.35 s +2024-11-23 01:55:42.839374: +2024-11-23 01:55:42.839577: Epoch 7042 +2024-11-23 01:55:42.839699: Current learning rate: 0.00148 +2024-11-23 01:56:01.023706: train_loss -0.8146 +2024-11-23 01:56:01.023916: val_loss -0.7664 +2024-11-23 01:56:01.023992: Pseudo dice [0.8432] +2024-11-23 01:56:01.024078: Epoch time: 18.19 s +2024-11-23 01:56:01.910074: +2024-11-23 01:56:01.910283: Epoch 7043 +2024-11-23 01:56:01.910396: Current learning rate: 0.00148 +2024-11-23 01:56:19.365987: train_loss -0.8134 +2024-11-23 01:56:19.366242: val_loss -0.777 +2024-11-23 01:56:19.366330: Pseudo dice [0.8511] +2024-11-23 01:56:19.366420: Epoch time: 17.46 s +2024-11-23 01:56:20.274157: +2024-11-23 01:56:20.274388: Epoch 7044 +2024-11-23 01:56:20.274505: Current learning rate: 0.00148 +2024-11-23 01:56:38.210830: train_loss -0.8166 +2024-11-23 01:56:38.211033: val_loss -0.7544 +2024-11-23 01:56:38.211128: Pseudo dice [0.8486] +2024-11-23 01:56:38.211205: Epoch time: 17.94 s +2024-11-23 01:56:39.068285: +2024-11-23 01:56:39.068496: Epoch 7045 +2024-11-23 01:56:39.068626: Current learning rate: 0.00148 +2024-11-23 01:56:57.716997: train_loss -0.8211 +2024-11-23 01:56:57.717280: val_loss -0.7726 +2024-11-23 01:56:57.717366: Pseudo dice [0.8536] +2024-11-23 01:56:57.717463: Epoch time: 18.65 s +2024-11-23 01:56:58.600825: +2024-11-23 01:56:58.601048: Epoch 7046 +2024-11-23 01:56:58.601169: Current learning rate: 0.00148 +2024-11-23 01:57:17.930616: train_loss -0.8056 +2024-11-23 01:57:17.930834: val_loss -0.7687 +2024-11-23 01:57:17.930908: Pseudo dice [0.8503] +2024-11-23 01:57:17.930985: Epoch time: 19.33 s +2024-11-23 01:57:18.809865: +2024-11-23 01:57:18.810056: Epoch 7047 +2024-11-23 01:57:18.810179: Current learning rate: 0.00147 +2024-11-23 01:57:37.626706: train_loss -0.8149 +2024-11-23 01:57:37.626948: val_loss -0.7588 +2024-11-23 01:57:37.627048: Pseudo dice [0.8417] +2024-11-23 01:57:37.627157: Epoch time: 18.82 s +2024-11-23 01:57:38.911494: +2024-11-23 01:57:38.911708: Epoch 7048 +2024-11-23 01:57:38.911819: Current learning rate: 0.00147 +2024-11-23 01:57:57.443364: train_loss -0.8194 +2024-11-23 01:57:57.443620: val_loss -0.7884 +2024-11-23 01:57:57.443701: Pseudo dice [0.8605] +2024-11-23 01:57:57.443783: Epoch time: 18.53 s +2024-11-23 01:57:58.321730: +2024-11-23 01:57:58.321978: Epoch 7049 +2024-11-23 01:57:58.322095: Current learning rate: 0.00147 +2024-11-23 01:58:16.675569: train_loss -0.8146 +2024-11-23 01:58:16.675785: val_loss -0.7963 +2024-11-23 01:58:16.675864: Pseudo dice [0.8648] +2024-11-23 01:58:16.675942: Epoch time: 18.35 s +2024-11-23 01:58:17.900469: +2024-11-23 01:58:17.900682: Epoch 7050 +2024-11-23 01:58:17.900803: Current learning rate: 0.00147 +2024-11-23 01:58:35.784124: train_loss -0.8129 +2024-11-23 01:58:35.784367: val_loss -0.7548 +2024-11-23 01:58:35.784447: Pseudo dice [0.8605] +2024-11-23 01:58:35.784549: Epoch time: 17.88 s +2024-11-23 01:58:36.671329: +2024-11-23 01:58:36.671540: Epoch 7051 +2024-11-23 01:58:36.671654: Current learning rate: 0.00147 +2024-11-23 01:58:55.399598: train_loss -0.8223 +2024-11-23 01:58:55.399819: val_loss -0.7788 +2024-11-23 01:58:55.399902: Pseudo dice [0.8674] +2024-11-23 01:58:55.399981: Epoch time: 18.73 s +2024-11-23 01:58:56.362931: +2024-11-23 01:58:56.363138: Epoch 7052 +2024-11-23 01:58:56.363251: Current learning rate: 0.00147 +2024-11-23 01:59:14.569463: train_loss -0.8216 +2024-11-23 01:59:14.569664: val_loss -0.7838 +2024-11-23 01:59:14.569747: Pseudo dice [0.8519] +2024-11-23 01:59:14.569830: Epoch time: 18.21 s +2024-11-23 01:59:15.464183: +2024-11-23 01:59:15.464439: Epoch 7053 +2024-11-23 01:59:15.464568: Current learning rate: 0.00147 +2024-11-23 01:59:33.231103: train_loss -0.8184 +2024-11-23 01:59:33.231315: val_loss -0.7724 +2024-11-23 01:59:33.231407: Pseudo dice [0.8579] +2024-11-23 01:59:33.231700: Epoch time: 17.77 s +2024-11-23 01:59:34.121390: +2024-11-23 01:59:34.121609: Epoch 7054 +2024-11-23 01:59:34.121732: Current learning rate: 0.00146 +2024-11-23 01:59:53.036245: train_loss -0.8154 +2024-11-23 01:59:53.036509: val_loss -0.7588 +2024-11-23 01:59:53.036590: Pseudo dice [0.8567] +2024-11-23 01:59:53.036681: Epoch time: 18.92 s +2024-11-23 01:59:53.921010: +2024-11-23 01:59:53.921209: Epoch 7055 +2024-11-23 01:59:53.921332: Current learning rate: 0.00146 +2024-11-23 02:00:13.085521: train_loss -0.8185 +2024-11-23 02:00:13.085734: val_loss -0.784 +2024-11-23 02:00:13.085812: Pseudo dice [0.8684] +2024-11-23 02:00:13.085896: Epoch time: 19.17 s +2024-11-23 02:00:13.960426: +2024-11-23 02:00:13.960618: Epoch 7056 +2024-11-23 02:00:13.960732: Current learning rate: 0.00146 +2024-11-23 02:00:32.667718: train_loss -0.824 +2024-11-23 02:00:32.667929: val_loss -0.7813 +2024-11-23 02:00:32.668012: Pseudo dice [0.8655] +2024-11-23 02:00:32.668096: Epoch time: 18.71 s +2024-11-23 02:00:33.545651: +2024-11-23 02:00:33.545881: Epoch 7057 +2024-11-23 02:00:33.546012: Current learning rate: 0.00146 +2024-11-23 02:00:52.442300: train_loss -0.8178 +2024-11-23 02:00:52.442553: val_loss -0.7463 +2024-11-23 02:00:52.442660: Pseudo dice [0.8548] +2024-11-23 02:00:52.442756: Epoch time: 18.9 s +2024-11-23 02:00:53.341707: +2024-11-23 02:00:53.341912: Epoch 7058 +2024-11-23 02:00:53.342037: Current learning rate: 0.00146 +2024-11-23 02:01:12.952198: train_loss -0.8197 +2024-11-23 02:01:12.952430: val_loss -0.8012 +2024-11-23 02:01:12.952508: Pseudo dice [0.867] +2024-11-23 02:01:12.952592: Epoch time: 19.61 s +2024-11-23 02:01:13.833349: +2024-11-23 02:01:13.833542: Epoch 7059 +2024-11-23 02:01:13.833668: Current learning rate: 0.00146 +2024-11-23 02:01:32.849230: train_loss -0.8207 +2024-11-23 02:01:32.849489: val_loss -0.7798 +2024-11-23 02:01:32.849574: Pseudo dice [0.8589] +2024-11-23 02:01:32.849662: Epoch time: 19.02 s +2024-11-23 02:01:34.164862: +2024-11-23 02:01:34.165215: Epoch 7060 +2024-11-23 02:01:34.165331: Current learning rate: 0.00146 +2024-11-23 02:01:53.440359: train_loss -0.8222 +2024-11-23 02:01:53.440639: val_loss -0.786 +2024-11-23 02:01:53.440722: Pseudo dice [0.8606] +2024-11-23 02:01:53.440812: Epoch time: 19.28 s +2024-11-23 02:01:54.323705: +2024-11-23 02:01:54.323928: Epoch 7061 +2024-11-23 02:01:54.324053: Current learning rate: 0.00145 +2024-11-23 02:02:12.156558: train_loss -0.822 +2024-11-23 02:02:12.156806: val_loss -0.7715 +2024-11-23 02:02:12.156891: Pseudo dice [0.8594] +2024-11-23 02:02:12.156985: Epoch time: 17.83 s +2024-11-23 02:02:13.096640: +2024-11-23 02:02:13.096859: Epoch 7062 +2024-11-23 02:02:13.096989: Current learning rate: 0.00145 +2024-11-23 02:02:32.162224: train_loss -0.8208 +2024-11-23 02:02:32.162470: val_loss -0.7803 +2024-11-23 02:02:32.162560: Pseudo dice [0.8625] +2024-11-23 02:02:32.162657: Epoch time: 19.07 s +2024-11-23 02:02:33.046761: +2024-11-23 02:02:33.046980: Epoch 7063 +2024-11-23 02:02:33.047116: Current learning rate: 0.00145 +2024-11-23 02:02:50.852421: train_loss -0.8194 +2024-11-23 02:02:50.852654: val_loss -0.7643 +2024-11-23 02:02:50.852750: Pseudo dice [0.8557] +2024-11-23 02:02:50.852838: Epoch time: 17.81 s +2024-11-23 02:02:51.738663: +2024-11-23 02:02:51.738868: Epoch 7064 +2024-11-23 02:02:51.739000: Current learning rate: 0.00145 +2024-11-23 02:03:09.508742: train_loss -0.8287 +2024-11-23 02:03:09.508975: val_loss -0.7653 +2024-11-23 02:03:09.509053: Pseudo dice [0.8597] +2024-11-23 02:03:09.509134: Epoch time: 17.77 s +2024-11-23 02:03:10.395668: +2024-11-23 02:03:10.395883: Epoch 7065 +2024-11-23 02:03:10.395998: Current learning rate: 0.00145 +2024-11-23 02:03:29.952724: train_loss -0.8281 +2024-11-23 02:03:29.955141: val_loss -0.7926 +2024-11-23 02:03:29.955242: Pseudo dice [0.8765] +2024-11-23 02:03:29.955323: Epoch time: 19.56 s +2024-11-23 02:03:30.850454: +2024-11-23 02:03:30.850680: Epoch 7066 +2024-11-23 02:03:30.850802: Current learning rate: 0.00145 +2024-11-23 02:03:47.999470: train_loss -0.8192 +2024-11-23 02:03:47.999716: val_loss -0.7689 +2024-11-23 02:03:47.999798: Pseudo dice [0.8554] +2024-11-23 02:03:47.999886: Epoch time: 17.15 s +2024-11-23 02:03:48.880140: +2024-11-23 02:03:48.880350: Epoch 7067 +2024-11-23 02:03:48.880476: Current learning rate: 0.00145 +2024-11-23 02:04:06.776786: train_loss -0.8209 +2024-11-23 02:04:06.782186: val_loss -0.7927 +2024-11-23 02:04:06.782282: Pseudo dice [0.8593] +2024-11-23 02:04:06.782365: Epoch time: 17.9 s +2024-11-23 02:04:07.667970: +2024-11-23 02:04:07.668193: Epoch 7068 +2024-11-23 02:04:07.668322: Current learning rate: 0.00144 +2024-11-23 02:04:26.130002: train_loss -0.8188 +2024-11-23 02:04:26.130234: val_loss -0.7769 +2024-11-23 02:04:26.130340: Pseudo dice [0.873] +2024-11-23 02:04:26.130455: Epoch time: 18.46 s +2024-11-23 02:04:27.012134: +2024-11-23 02:04:27.012363: Epoch 7069 +2024-11-23 02:04:27.012487: Current learning rate: 0.00144 +2024-11-23 02:04:44.946521: train_loss -0.8205 +2024-11-23 02:04:44.946736: val_loss -0.7824 +2024-11-23 02:04:44.946820: Pseudo dice [0.8546] +2024-11-23 02:04:44.946910: Epoch time: 17.94 s +2024-11-23 02:04:45.829616: +2024-11-23 02:04:45.829817: Epoch 7070 +2024-11-23 02:04:45.829950: Current learning rate: 0.00144 +2024-11-23 02:05:03.480453: train_loss -0.8253 +2024-11-23 02:05:03.480685: val_loss -0.7677 +2024-11-23 02:05:03.480761: Pseudo dice [0.8482] +2024-11-23 02:05:03.480842: Epoch time: 17.65 s +2024-11-23 02:05:04.362772: +2024-11-23 02:05:04.362988: Epoch 7071 +2024-11-23 02:05:04.363129: Current learning rate: 0.00144 +2024-11-23 02:05:22.372112: train_loss -0.8205 +2024-11-23 02:05:22.374548: val_loss -0.7905 +2024-11-23 02:05:22.374660: Pseudo dice [0.854] +2024-11-23 02:05:22.374745: Epoch time: 18.01 s +2024-11-23 02:05:23.315683: +2024-11-23 02:05:23.315906: Epoch 7072 +2024-11-23 02:05:23.316020: Current learning rate: 0.00144 +2024-11-23 02:05:41.473304: train_loss -0.8117 +2024-11-23 02:05:41.473513: val_loss -0.7906 +2024-11-23 02:05:41.473588: Pseudo dice [0.8639] +2024-11-23 02:05:41.473665: Epoch time: 18.16 s +2024-11-23 02:05:42.363791: +2024-11-23 02:05:42.364033: Epoch 7073 +2024-11-23 02:05:42.364158: Current learning rate: 0.00144 +2024-11-23 02:06:01.390108: train_loss -0.8235 +2024-11-23 02:06:01.390362: val_loss -0.7976 +2024-11-23 02:06:01.390455: Pseudo dice [0.8572] +2024-11-23 02:06:01.390603: Epoch time: 19.03 s +2024-11-23 02:06:02.276813: +2024-11-23 02:06:02.277035: Epoch 7074 +2024-11-23 02:06:02.277149: Current learning rate: 0.00144 +2024-11-23 02:06:20.899436: train_loss -0.8223 +2024-11-23 02:06:20.899643: val_loss -0.7929 +2024-11-23 02:06:20.899739: Pseudo dice [0.8597] +2024-11-23 02:06:20.902007: Epoch time: 18.62 s +2024-11-23 02:06:21.857979: +2024-11-23 02:06:21.858193: Epoch 7075 +2024-11-23 02:06:21.858312: Current learning rate: 0.00143 +2024-11-23 02:06:40.079587: train_loss -0.8146 +2024-11-23 02:06:40.079798: val_loss -0.7971 +2024-11-23 02:06:40.079877: Pseudo dice [0.8616] +2024-11-23 02:06:40.079966: Epoch time: 18.22 s +2024-11-23 02:06:40.967291: +2024-11-23 02:06:40.967505: Epoch 7076 +2024-11-23 02:06:40.967623: Current learning rate: 0.00143 +2024-11-23 02:06:59.303576: train_loss -0.8247 +2024-11-23 02:06:59.303798: val_loss -0.791 +2024-11-23 02:06:59.303879: Pseudo dice [0.8553] +2024-11-23 02:06:59.303972: Epoch time: 18.34 s +2024-11-23 02:07:00.188257: +2024-11-23 02:07:00.188473: Epoch 7077 +2024-11-23 02:07:00.188596: Current learning rate: 0.00143 +2024-11-23 02:07:19.632480: train_loss -0.816 +2024-11-23 02:07:19.632717: val_loss -0.783 +2024-11-23 02:07:19.632802: Pseudo dice [0.8621] +2024-11-23 02:07:19.632898: Epoch time: 19.45 s +2024-11-23 02:07:20.517432: +2024-11-23 02:07:20.517665: Epoch 7078 +2024-11-23 02:07:20.517783: Current learning rate: 0.00143 +2024-11-23 02:07:38.607350: train_loss -0.8137 +2024-11-23 02:07:38.607571: val_loss -0.7866 +2024-11-23 02:07:38.607649: Pseudo dice [0.8724] +2024-11-23 02:07:38.607748: Epoch time: 18.09 s +2024-11-23 02:07:39.489416: +2024-11-23 02:07:39.489626: Epoch 7079 +2024-11-23 02:07:39.489763: Current learning rate: 0.00143 +2024-11-23 02:07:57.839343: train_loss -0.8226 +2024-11-23 02:07:57.839561: val_loss -0.7988 +2024-11-23 02:07:57.839642: Pseudo dice [0.8736] +2024-11-23 02:07:57.840127: Epoch time: 18.35 s +2024-11-23 02:07:58.718654: +2024-11-23 02:07:58.718920: Epoch 7080 +2024-11-23 02:07:58.719039: Current learning rate: 0.00143 +2024-11-23 02:08:17.764941: train_loss -0.8175 +2024-11-23 02:08:17.765164: val_loss -0.7628 +2024-11-23 02:08:17.765244: Pseudo dice [0.8568] +2024-11-23 02:08:17.770533: Epoch time: 19.05 s +2024-11-23 02:08:18.657187: +2024-11-23 02:08:18.657396: Epoch 7081 +2024-11-23 02:08:18.657510: Current learning rate: 0.00143 +2024-11-23 02:08:37.122562: train_loss -0.8092 +2024-11-23 02:08:37.122810: val_loss -0.7821 +2024-11-23 02:08:37.122898: Pseudo dice [0.8615] +2024-11-23 02:08:37.122984: Epoch time: 18.47 s +2024-11-23 02:08:38.003184: +2024-11-23 02:08:38.003400: Epoch 7082 +2024-11-23 02:08:38.003518: Current learning rate: 0.00142 +2024-11-23 02:08:57.639418: train_loss -0.8148 +2024-11-23 02:08:57.639642: val_loss -0.7814 +2024-11-23 02:08:57.639721: Pseudo dice [0.8655] +2024-11-23 02:08:57.639814: Epoch time: 19.64 s +2024-11-23 02:08:59.004991: +2024-11-23 02:08:59.005206: Epoch 7083 +2024-11-23 02:08:59.005334: Current learning rate: 0.00142 +2024-11-23 02:09:17.685066: train_loss -0.8073 +2024-11-23 02:09:17.685284: val_loss -0.7605 +2024-11-23 02:09:17.685365: Pseudo dice [0.8619] +2024-11-23 02:09:17.685446: Epoch time: 18.68 s +2024-11-23 02:09:18.568491: +2024-11-23 02:09:18.568714: Epoch 7084 +2024-11-23 02:09:18.568829: Current learning rate: 0.00142 +2024-11-23 02:09:36.709422: train_loss -0.8115 +2024-11-23 02:09:36.711916: val_loss -0.765 +2024-11-23 02:09:36.712033: Pseudo dice [0.856] +2024-11-23 02:09:36.712120: Epoch time: 18.14 s +2024-11-23 02:09:37.597280: +2024-11-23 02:09:37.597489: Epoch 7085 +2024-11-23 02:09:37.597606: Current learning rate: 0.00142 +2024-11-23 02:09:56.368316: train_loss -0.8149 +2024-11-23 02:09:56.368558: val_loss -0.7748 +2024-11-23 02:09:56.368655: Pseudo dice [0.8587] +2024-11-23 02:09:56.374022: Epoch time: 18.77 s +2024-11-23 02:09:57.302093: +2024-11-23 02:09:57.302312: Epoch 7086 +2024-11-23 02:09:57.302450: Current learning rate: 0.00142 +2024-11-23 02:10:14.527380: train_loss -0.8209 +2024-11-23 02:10:14.527584: val_loss -0.7905 +2024-11-23 02:10:14.527659: Pseudo dice [0.8579] +2024-11-23 02:10:14.527739: Epoch time: 17.23 s +2024-11-23 02:10:15.412940: +2024-11-23 02:10:15.413212: Epoch 7087 +2024-11-23 02:10:15.413327: Current learning rate: 0.00142 +2024-11-23 02:10:32.822051: train_loss -0.8267 +2024-11-23 02:10:32.822279: val_loss -0.7677 +2024-11-23 02:10:32.822359: Pseudo dice [0.8582] +2024-11-23 02:10:32.822439: Epoch time: 17.41 s +2024-11-23 02:10:33.711766: +2024-11-23 02:10:33.711987: Epoch 7088 +2024-11-23 02:10:33.712117: Current learning rate: 0.00142 +2024-11-23 02:10:52.971326: train_loss -0.8171 +2024-11-23 02:10:52.971557: val_loss -0.7647 +2024-11-23 02:10:52.971639: Pseudo dice [0.8596] +2024-11-23 02:10:52.971724: Epoch time: 19.26 s +2024-11-23 02:10:53.857718: +2024-11-23 02:10:53.857933: Epoch 7089 +2024-11-23 02:10:53.858049: Current learning rate: 0.00142 +2024-11-23 02:11:11.967970: train_loss -0.822 +2024-11-23 02:11:11.968277: val_loss -0.7927 +2024-11-23 02:11:11.968366: Pseudo dice [0.8682] +2024-11-23 02:11:11.968448: Epoch time: 18.11 s +2024-11-23 02:11:12.911052: +2024-11-23 02:11:12.911304: Epoch 7090 +2024-11-23 02:11:12.911437: Current learning rate: 0.00141 +2024-11-23 02:11:32.153777: train_loss -0.8205 +2024-11-23 02:11:32.154043: val_loss -0.7885 +2024-11-23 02:11:32.154136: Pseudo dice [0.8567] +2024-11-23 02:11:32.154216: Epoch time: 19.24 s +2024-11-23 02:11:33.048763: +2024-11-23 02:11:33.048960: Epoch 7091 +2024-11-23 02:11:33.049082: Current learning rate: 0.00141 +2024-11-23 02:11:50.738178: train_loss -0.8245 +2024-11-23 02:11:50.738395: val_loss -0.7749 +2024-11-23 02:11:50.738490: Pseudo dice [0.8528] +2024-11-23 02:11:50.738569: Epoch time: 17.69 s +2024-11-23 02:11:51.626163: +2024-11-23 02:11:51.626378: Epoch 7092 +2024-11-23 02:11:51.626491: Current learning rate: 0.00141 +2024-11-23 02:12:10.934030: train_loss -0.8229 +2024-11-23 02:12:10.934264: val_loss -0.7748 +2024-11-23 02:12:10.934351: Pseudo dice [0.8626] +2024-11-23 02:12:10.934437: Epoch time: 19.31 s +2024-11-23 02:12:11.819675: +2024-11-23 02:12:11.819894: Epoch 7093 +2024-11-23 02:12:11.820009: Current learning rate: 0.00141 +2024-11-23 02:12:30.853458: train_loss -0.821 +2024-11-23 02:12:30.853766: val_loss -0.7799 +2024-11-23 02:12:30.853849: Pseudo dice [0.863] +2024-11-23 02:12:30.853933: Epoch time: 19.03 s +2024-11-23 02:12:31.789935: +2024-11-23 02:12:31.790148: Epoch 7094 +2024-11-23 02:12:31.790267: Current learning rate: 0.00141 +2024-11-23 02:12:50.757915: train_loss -0.8198 +2024-11-23 02:12:50.758174: val_loss -0.8089 +2024-11-23 02:12:50.758260: Pseudo dice [0.8692] +2024-11-23 02:12:50.758403: Epoch time: 18.97 s +2024-11-23 02:12:51.641230: +2024-11-23 02:12:51.641459: Epoch 7095 +2024-11-23 02:12:51.641576: Current learning rate: 0.00141 +2024-11-23 02:13:10.618484: train_loss -0.817 +2024-11-23 02:13:10.618709: val_loss -0.7963 +2024-11-23 02:13:10.618795: Pseudo dice [0.8595] +2024-11-23 02:13:10.618874: Epoch time: 18.98 s +2024-11-23 02:13:11.501404: +2024-11-23 02:13:11.501654: Epoch 7096 +2024-11-23 02:13:11.501803: Current learning rate: 0.00141 +2024-11-23 02:13:30.964281: train_loss -0.822 +2024-11-23 02:13:30.964517: val_loss -0.7737 +2024-11-23 02:13:30.964598: Pseudo dice [0.8527] +2024-11-23 02:13:30.964677: Epoch time: 19.46 s +2024-11-23 02:13:31.886140: +2024-11-23 02:13:31.886397: Epoch 7097 +2024-11-23 02:13:31.886562: Current learning rate: 0.0014 +2024-11-23 02:13:50.062923: train_loss -0.8135 +2024-11-23 02:13:50.063138: val_loss -0.8043 +2024-11-23 02:13:50.063215: Pseudo dice [0.8729] +2024-11-23 02:13:50.063312: Epoch time: 18.18 s +2024-11-23 02:13:50.965784: +2024-11-23 02:13:50.965982: Epoch 7098 +2024-11-23 02:13:50.966101: Current learning rate: 0.0014 +2024-11-23 02:14:09.072445: train_loss -0.8232 +2024-11-23 02:14:09.072659: val_loss -0.7857 +2024-11-23 02:14:09.075383: Pseudo dice [0.8542] +2024-11-23 02:14:09.075482: Epoch time: 18.11 s +2024-11-23 02:14:09.979170: +2024-11-23 02:14:09.979407: Epoch 7099 +2024-11-23 02:14:09.979536: Current learning rate: 0.0014 +2024-11-23 02:14:28.220176: train_loss -0.8186 +2024-11-23 02:14:28.225574: val_loss -0.7773 +2024-11-23 02:14:28.225684: Pseudo dice [0.8548] +2024-11-23 02:14:28.225764: Epoch time: 18.24 s +2024-11-23 02:14:29.621411: +2024-11-23 02:14:29.621629: Epoch 7100 +2024-11-23 02:14:29.621738: Current learning rate: 0.0014 +2024-11-23 02:14:49.508839: train_loss -0.8086 +2024-11-23 02:14:49.509150: val_loss -0.7841 +2024-11-23 02:14:49.509231: Pseudo dice [0.8508] +2024-11-23 02:14:49.509336: Epoch time: 19.89 s +2024-11-23 02:14:50.400649: +2024-11-23 02:14:50.400866: Epoch 7101 +2024-11-23 02:14:50.400981: Current learning rate: 0.0014 +2024-11-23 02:15:09.052994: train_loss -0.8184 +2024-11-23 02:15:09.053293: val_loss -0.7711 +2024-11-23 02:15:09.053391: Pseudo dice [0.8533] +2024-11-23 02:15:09.053483: Epoch time: 18.65 s +2024-11-23 02:15:09.936705: +2024-11-23 02:15:09.936925: Epoch 7102 +2024-11-23 02:15:09.937048: Current learning rate: 0.0014 +2024-11-23 02:15:28.404574: train_loss -0.8214 +2024-11-23 02:15:28.404802: val_loss -0.7925 +2024-11-23 02:15:28.404891: Pseudo dice [0.861] +2024-11-23 02:15:28.405020: Epoch time: 18.47 s +2024-11-23 02:15:29.401450: +2024-11-23 02:15:29.401663: Epoch 7103 +2024-11-23 02:15:29.401793: Current learning rate: 0.0014 +2024-11-23 02:15:47.597676: train_loss -0.8235 +2024-11-23 02:15:47.597895: val_loss -0.7731 +2024-11-23 02:15:47.597973: Pseudo dice [0.8578] +2024-11-23 02:15:47.598054: Epoch time: 18.2 s +2024-11-23 02:15:48.495035: +2024-11-23 02:15:48.495250: Epoch 7104 +2024-11-23 02:15:48.495373: Current learning rate: 0.00139 +2024-11-23 02:16:06.963570: train_loss -0.8181 +2024-11-23 02:16:06.963827: val_loss -0.7741 +2024-11-23 02:16:06.963906: Pseudo dice [0.8485] +2024-11-23 02:16:06.969173: Epoch time: 18.47 s +2024-11-23 02:16:08.028635: +2024-11-23 02:16:08.028859: Epoch 7105 +2024-11-23 02:16:08.028973: Current learning rate: 0.00139 +2024-11-23 02:16:25.885934: train_loss -0.8205 +2024-11-23 02:16:25.886178: val_loss -0.7816 +2024-11-23 02:16:25.886274: Pseudo dice [0.8588] +2024-11-23 02:16:25.886452: Epoch time: 17.86 s +2024-11-23 02:16:26.766401: +2024-11-23 02:16:26.766624: Epoch 7106 +2024-11-23 02:16:26.766739: Current learning rate: 0.00139 +2024-11-23 02:16:46.012948: train_loss -0.8181 +2024-11-23 02:16:46.013171: val_loss -0.7722 +2024-11-23 02:16:46.013249: Pseudo dice [0.8609] +2024-11-23 02:16:46.013338: Epoch time: 19.25 s +2024-11-23 02:16:46.895087: +2024-11-23 02:16:46.895303: Epoch 7107 +2024-11-23 02:16:46.895413: Current learning rate: 0.00139 +2024-11-23 02:17:05.240775: train_loss -0.8271 +2024-11-23 02:17:05.240993: val_loss -0.7837 +2024-11-23 02:17:05.241081: Pseudo dice [0.8585] +2024-11-23 02:17:05.241162: Epoch time: 18.35 s +2024-11-23 02:17:06.164190: +2024-11-23 02:17:06.164417: Epoch 7108 +2024-11-23 02:17:06.164548: Current learning rate: 0.00139 +2024-11-23 02:17:24.834368: train_loss -0.8225 +2024-11-23 02:17:24.834608: val_loss -0.7886 +2024-11-23 02:17:24.834687: Pseudo dice [0.863] +2024-11-23 02:17:24.834771: Epoch time: 18.67 s +2024-11-23 02:17:25.714578: +2024-11-23 02:17:25.714825: Epoch 7109 +2024-11-23 02:17:25.714936: Current learning rate: 0.00139 +2024-11-23 02:17:43.392085: train_loss -0.8144 +2024-11-23 02:17:43.392295: val_loss -0.7753 +2024-11-23 02:17:43.392378: Pseudo dice [0.8607] +2024-11-23 02:17:43.392454: Epoch time: 17.68 s +2024-11-23 02:17:44.275963: +2024-11-23 02:17:44.276171: Epoch 7110 +2024-11-23 02:17:44.276285: Current learning rate: 0.00139 +2024-11-23 02:18:02.259511: train_loss -0.818 +2024-11-23 02:18:02.259727: val_loss -0.7813 +2024-11-23 02:18:02.259803: Pseudo dice [0.8671] +2024-11-23 02:18:02.259881: Epoch time: 17.98 s +2024-11-23 02:18:03.293529: +2024-11-23 02:18:03.293748: Epoch 7111 +2024-11-23 02:18:03.293865: Current learning rate: 0.00138 +2024-11-23 02:18:22.285470: train_loss -0.8237 +2024-11-23 02:18:22.285679: val_loss -0.7667 +2024-11-23 02:18:22.285757: Pseudo dice [0.8741] +2024-11-23 02:18:22.285832: Epoch time: 18.99 s +2024-11-23 02:18:23.169074: +2024-11-23 02:18:23.169312: Epoch 7112 +2024-11-23 02:18:23.169439: Current learning rate: 0.00138 +2024-11-23 02:18:42.296150: train_loss -0.8204 +2024-11-23 02:18:42.296392: val_loss -0.7777 +2024-11-23 02:18:42.296476: Pseudo dice [0.8668] +2024-11-23 02:18:42.296559: Epoch time: 19.13 s +2024-11-23 02:18:43.182979: +2024-11-23 02:18:43.183192: Epoch 7113 +2024-11-23 02:18:43.183326: Current learning rate: 0.00138 +2024-11-23 02:19:01.560122: train_loss -0.8202 +2024-11-23 02:19:01.560332: val_loss -0.7896 +2024-11-23 02:19:01.560413: Pseudo dice [0.8593] +2024-11-23 02:19:01.560503: Epoch time: 18.38 s +2024-11-23 02:19:02.511120: +2024-11-23 02:19:02.511369: Epoch 7114 +2024-11-23 02:19:02.511497: Current learning rate: 0.00138 +2024-11-23 02:19:20.557265: train_loss -0.8217 +2024-11-23 02:19:20.557475: val_loss -0.7918 +2024-11-23 02:19:20.557552: Pseudo dice [0.8628] +2024-11-23 02:19:20.557635: Epoch time: 18.05 s +2024-11-23 02:19:21.438781: +2024-11-23 02:19:21.438990: Epoch 7115 +2024-11-23 02:19:21.439108: Current learning rate: 0.00138 +2024-11-23 02:19:39.781571: train_loss -0.8239 +2024-11-23 02:19:39.781804: val_loss -0.7943 +2024-11-23 02:19:39.781901: Pseudo dice [0.865] +2024-11-23 02:19:39.781976: Epoch time: 18.34 s +2024-11-23 02:19:40.726897: +2024-11-23 02:19:40.727096: Epoch 7116 +2024-11-23 02:19:40.727212: Current learning rate: 0.00138 +2024-11-23 02:19:59.328044: train_loss -0.8175 +2024-11-23 02:19:59.328294: val_loss -0.7678 +2024-11-23 02:19:59.328382: Pseudo dice [0.8613] +2024-11-23 02:19:59.328481: Epoch time: 18.6 s +2024-11-23 02:20:00.596281: +2024-11-23 02:20:00.596467: Epoch 7117 +2024-11-23 02:20:00.596576: Current learning rate: 0.00138 +2024-11-23 02:20:19.038247: train_loss -0.8237 +2024-11-23 02:20:19.038466: val_loss -0.7771 +2024-11-23 02:20:19.038545: Pseudo dice [0.8514] +2024-11-23 02:20:19.038624: Epoch time: 18.44 s +2024-11-23 02:20:19.919449: +2024-11-23 02:20:19.919662: Epoch 7118 +2024-11-23 02:20:19.919779: Current learning rate: 0.00137 +2024-11-23 02:20:38.018878: train_loss -0.8206 +2024-11-23 02:20:38.019117: val_loss -0.784 +2024-11-23 02:20:38.019210: Pseudo dice [0.8638] +2024-11-23 02:20:38.024439: Epoch time: 18.1 s +2024-11-23 02:20:38.973380: +2024-11-23 02:20:38.973592: Epoch 7119 +2024-11-23 02:20:38.973703: Current learning rate: 0.00137 +2024-11-23 02:20:56.600048: train_loss -0.8174 +2024-11-23 02:20:56.600293: val_loss -0.8017 +2024-11-23 02:20:56.600429: Pseudo dice [0.8692] +2024-11-23 02:20:56.600512: Epoch time: 17.63 s +2024-11-23 02:20:57.483991: +2024-11-23 02:20:57.484226: Epoch 7120 +2024-11-23 02:20:57.484366: Current learning rate: 0.00137 +2024-11-23 02:21:15.596947: train_loss -0.8247 +2024-11-23 02:21:15.597208: val_loss -0.781 +2024-11-23 02:21:15.597291: Pseudo dice [0.8558] +2024-11-23 02:21:15.599474: Epoch time: 18.11 s +2024-11-23 02:21:16.495615: +2024-11-23 02:21:16.495837: Epoch 7121 +2024-11-23 02:21:16.495952: Current learning rate: 0.00137 +2024-11-23 02:21:34.404129: train_loss -0.8252 +2024-11-23 02:21:34.408966: val_loss -0.7771 +2024-11-23 02:21:34.409127: Pseudo dice [0.8619] +2024-11-23 02:21:34.409224: Epoch time: 17.91 s +2024-11-23 02:21:35.293222: +2024-11-23 02:21:35.293472: Epoch 7122 +2024-11-23 02:21:35.293594: Current learning rate: 0.00137 +2024-11-23 02:21:54.050419: train_loss -0.8218 +2024-11-23 02:21:54.050624: val_loss -0.776 +2024-11-23 02:21:54.050698: Pseudo dice [0.8541] +2024-11-23 02:21:54.050778: Epoch time: 18.76 s +2024-11-23 02:21:54.933746: +2024-11-23 02:21:54.933956: Epoch 7123 +2024-11-23 02:21:54.934069: Current learning rate: 0.00137 +2024-11-23 02:22:13.367451: train_loss -0.8285 +2024-11-23 02:22:13.367678: val_loss -0.786 +2024-11-23 02:22:13.367759: Pseudo dice [0.8723] +2024-11-23 02:22:13.367841: Epoch time: 18.43 s +2024-11-23 02:22:14.357190: +2024-11-23 02:22:14.357410: Epoch 7124 +2024-11-23 02:22:14.357523: Current learning rate: 0.00137 +2024-11-23 02:22:34.075093: train_loss -0.8174 +2024-11-23 02:22:34.075333: val_loss -0.7735 +2024-11-23 02:22:34.075427: Pseudo dice [0.856] +2024-11-23 02:22:34.075512: Epoch time: 19.72 s +2024-11-23 02:22:34.956783: +2024-11-23 02:22:34.956976: Epoch 7125 +2024-11-23 02:22:34.957094: Current learning rate: 0.00136 +2024-11-23 02:22:53.274839: train_loss -0.8218 +2024-11-23 02:22:53.275067: val_loss -0.781 +2024-11-23 02:22:53.275151: Pseudo dice [0.8573] +2024-11-23 02:22:53.275228: Epoch time: 18.32 s +2024-11-23 02:22:54.158498: +2024-11-23 02:22:54.158743: Epoch 7126 +2024-11-23 02:22:54.158859: Current learning rate: 0.00136 +2024-11-23 02:23:13.478726: train_loss -0.8202 +2024-11-23 02:23:13.478943: val_loss -0.7667 +2024-11-23 02:23:13.479028: Pseudo dice [0.8696] +2024-11-23 02:23:13.479109: Epoch time: 19.32 s +2024-11-23 02:23:14.361420: +2024-11-23 02:23:14.361644: Epoch 7127 +2024-11-23 02:23:14.361773: Current learning rate: 0.00136 +2024-11-23 02:23:33.219515: train_loss -0.8177 +2024-11-23 02:23:33.221909: val_loss -0.7778 +2024-11-23 02:23:33.222026: Pseudo dice [0.8642] +2024-11-23 02:23:33.222129: Epoch time: 18.85 s +2024-11-23 02:23:34.497298: +2024-11-23 02:23:34.497490: Epoch 7128 +2024-11-23 02:23:34.497598: Current learning rate: 0.00136 +2024-11-23 02:23:53.116662: train_loss -0.8232 +2024-11-23 02:23:53.116930: val_loss -0.7564 +2024-11-23 02:23:53.117062: Pseudo dice [0.858] +2024-11-23 02:23:53.117154: Epoch time: 18.62 s +2024-11-23 02:23:54.026705: +2024-11-23 02:23:54.026943: Epoch 7129 +2024-11-23 02:23:54.027068: Current learning rate: 0.00136 +2024-11-23 02:24:12.645728: train_loss -0.8266 +2024-11-23 02:24:12.645941: val_loss -0.7672 +2024-11-23 02:24:12.646020: Pseudo dice [0.8556] +2024-11-23 02:24:12.646111: Epoch time: 18.62 s +2024-11-23 02:24:13.528157: +2024-11-23 02:24:13.528375: Epoch 7130 +2024-11-23 02:24:13.528483: Current learning rate: 0.00136 +2024-11-23 02:24:30.559864: train_loss -0.8237 +2024-11-23 02:24:30.560127: val_loss -0.7924 +2024-11-23 02:24:30.560207: Pseudo dice [0.8673] +2024-11-23 02:24:30.560300: Epoch time: 17.03 s +2024-11-23 02:24:31.489730: +2024-11-23 02:24:31.489982: Epoch 7131 +2024-11-23 02:24:31.490108: Current learning rate: 0.00136 +2024-11-23 02:24:49.404383: train_loss -0.8185 +2024-11-23 02:24:49.404666: val_loss -0.7865 +2024-11-23 02:24:49.405092: Pseudo dice [0.858] +2024-11-23 02:24:49.405206: Epoch time: 17.92 s +2024-11-23 02:24:50.296328: +2024-11-23 02:24:50.296558: Epoch 7132 +2024-11-23 02:24:50.296671: Current learning rate: 0.00135 +2024-11-23 02:25:09.161064: train_loss -0.8302 +2024-11-23 02:25:09.163510: val_loss -0.7983 +2024-11-23 02:25:09.163624: Pseudo dice [0.8605] +2024-11-23 02:25:09.163715: Epoch time: 18.87 s +2024-11-23 02:25:10.063771: +2024-11-23 02:25:10.063972: Epoch 7133 +2024-11-23 02:25:10.064110: Current learning rate: 0.00135 +2024-11-23 02:25:27.911327: train_loss -0.8232 +2024-11-23 02:25:27.911583: val_loss -0.7464 +2024-11-23 02:25:27.911672: Pseudo dice [0.8466] +2024-11-23 02:25:27.911755: Epoch time: 17.85 s +2024-11-23 02:25:28.800878: +2024-11-23 02:25:28.801103: Epoch 7134 +2024-11-23 02:25:28.801231: Current learning rate: 0.00135 +2024-11-23 02:25:46.225379: train_loss -0.8331 +2024-11-23 02:25:46.225608: val_loss -0.7687 +2024-11-23 02:25:46.225700: Pseudo dice [0.861] +2024-11-23 02:25:46.225777: Epoch time: 17.43 s +2024-11-23 02:25:47.104640: +2024-11-23 02:25:47.104859: Epoch 7135 +2024-11-23 02:25:47.104977: Current learning rate: 0.00135 +2024-11-23 02:26:05.536204: train_loss -0.8211 +2024-11-23 02:26:05.536466: val_loss -0.8018 +2024-11-23 02:26:05.536548: Pseudo dice [0.8631] +2024-11-23 02:26:05.536634: Epoch time: 18.43 s +2024-11-23 02:26:06.421206: +2024-11-23 02:26:06.421413: Epoch 7136 +2024-11-23 02:26:06.421530: Current learning rate: 0.00135 +2024-11-23 02:26:25.246315: train_loss -0.8241 +2024-11-23 02:26:25.246526: val_loss -0.7766 +2024-11-23 02:26:25.246604: Pseudo dice [0.8632] +2024-11-23 02:26:25.246684: Epoch time: 18.83 s +2024-11-23 02:26:26.294582: +2024-11-23 02:26:26.294798: Epoch 7137 +2024-11-23 02:26:26.294914: Current learning rate: 0.00135 +2024-11-23 02:26:45.156979: train_loss -0.8179 +2024-11-23 02:26:45.157227: val_loss -0.7944 +2024-11-23 02:26:45.157329: Pseudo dice [0.8669] +2024-11-23 02:26:45.157417: Epoch time: 18.86 s +2024-11-23 02:26:46.061326: +2024-11-23 02:26:46.061533: Epoch 7138 +2024-11-23 02:26:46.061654: Current learning rate: 0.00135 +2024-11-23 02:27:06.326391: train_loss -0.8175 +2024-11-23 02:27:06.326615: val_loss -0.7621 +2024-11-23 02:27:06.326694: Pseudo dice [0.8597] +2024-11-23 02:27:06.326787: Epoch time: 20.27 s +2024-11-23 02:27:07.206080: +2024-11-23 02:27:07.206285: Epoch 7139 +2024-11-23 02:27:07.206412: Current learning rate: 0.00134 +2024-11-23 02:27:24.907598: train_loss -0.8204 +2024-11-23 02:27:24.909983: val_loss -0.7679 +2024-11-23 02:27:24.910104: Pseudo dice [0.873] +2024-11-23 02:27:24.911931: Epoch time: 17.7 s +2024-11-23 02:27:26.317600: +2024-11-23 02:27:26.317833: Epoch 7140 +2024-11-23 02:27:26.317954: Current learning rate: 0.00134 +2024-11-23 02:27:45.156662: train_loss -0.8162 +2024-11-23 02:27:45.157233: val_loss -0.7724 +2024-11-23 02:27:45.157338: Pseudo dice [0.8495] +2024-11-23 02:27:45.157423: Epoch time: 18.84 s +2024-11-23 02:27:46.041894: +2024-11-23 02:27:46.042336: Epoch 7141 +2024-11-23 02:27:46.042475: Current learning rate: 0.00134 +2024-11-23 02:28:03.439016: train_loss -0.8293 +2024-11-23 02:28:03.439238: val_loss -0.7817 +2024-11-23 02:28:03.439320: Pseudo dice [0.8653] +2024-11-23 02:28:03.439415: Epoch time: 17.4 s +2024-11-23 02:28:04.376807: +2024-11-23 02:28:04.377249: Epoch 7142 +2024-11-23 02:28:04.377382: Current learning rate: 0.00134 +2024-11-23 02:28:23.373695: train_loss -0.8171 +2024-11-23 02:28:23.373936: val_loss -0.78 +2024-11-23 02:28:23.374014: Pseudo dice [0.8688] +2024-11-23 02:28:23.374110: Epoch time: 19.0 s +2024-11-23 02:28:24.259860: +2024-11-23 02:28:24.260327: Epoch 7143 +2024-11-23 02:28:24.260505: Current learning rate: 0.00134 +2024-11-23 02:28:43.320231: train_loss -0.8138 +2024-11-23 02:28:43.333306: val_loss -0.7839 +2024-11-23 02:28:43.333469: Pseudo dice [0.8396] +2024-11-23 02:28:43.333582: Epoch time: 19.06 s +2024-11-23 02:28:44.228976: +2024-11-23 02:28:44.229433: Epoch 7144 +2024-11-23 02:28:44.229567: Current learning rate: 0.00134 +2024-11-23 02:29:03.168650: train_loss -0.8111 +2024-11-23 02:29:03.168854: val_loss -0.7879 +2024-11-23 02:29:03.168933: Pseudo dice [0.859] +2024-11-23 02:29:03.169008: Epoch time: 18.94 s +2024-11-23 02:29:04.055353: +2024-11-23 02:29:04.055789: Epoch 7145 +2024-11-23 02:29:04.055929: Current learning rate: 0.00134 +2024-11-23 02:29:21.782520: train_loss -0.8182 +2024-11-23 02:29:21.782738: val_loss -0.7805 +2024-11-23 02:29:21.782813: Pseudo dice [0.8619] +2024-11-23 02:29:21.782890: Epoch time: 17.73 s +2024-11-23 02:29:22.665548: +2024-11-23 02:29:22.665977: Epoch 7146 +2024-11-23 02:29:22.666120: Current learning rate: 0.00134 +2024-11-23 02:29:41.805521: train_loss -0.8179 +2024-11-23 02:29:41.805743: val_loss -0.7903 +2024-11-23 02:29:41.805879: Pseudo dice [0.8581] +2024-11-23 02:29:41.806006: Epoch time: 19.14 s +2024-11-23 02:29:42.694194: +2024-11-23 02:29:42.694634: Epoch 7147 +2024-11-23 02:29:42.694772: Current learning rate: 0.00133 +2024-11-23 02:30:01.402233: train_loss -0.8231 +2024-11-23 02:30:01.402451: val_loss -0.7825 +2024-11-23 02:30:01.402550: Pseudo dice [0.8701] +2024-11-23 02:30:01.402637: Epoch time: 18.71 s +2024-11-23 02:30:02.288069: +2024-11-23 02:30:02.288499: Epoch 7148 +2024-11-23 02:30:02.288647: Current learning rate: 0.00133 +2024-11-23 02:30:20.749748: train_loss -0.818 +2024-11-23 02:30:20.749960: val_loss -0.7559 +2024-11-23 02:30:20.750045: Pseudo dice [0.8556] +2024-11-23 02:30:20.750134: Epoch time: 18.46 s +2024-11-23 02:30:21.630107: +2024-11-23 02:30:21.630539: Epoch 7149 +2024-11-23 02:30:21.630696: Current learning rate: 0.00133 +2024-11-23 02:30:39.494369: train_loss -0.821 +2024-11-23 02:30:39.494577: val_loss -0.7768 +2024-11-23 02:30:39.494654: Pseudo dice [0.8479] +2024-11-23 02:30:39.494735: Epoch time: 17.87 s +2024-11-23 02:30:40.714410: +2024-11-23 02:30:40.714811: Epoch 7150 +2024-11-23 02:30:40.714953: Current learning rate: 0.00133 +2024-11-23 02:30:59.646762: train_loss -0.8152 +2024-11-23 02:30:59.647010: val_loss -0.7742 +2024-11-23 02:30:59.647100: Pseudo dice [0.8477] +2024-11-23 02:30:59.647195: Epoch time: 18.93 s +2024-11-23 02:31:00.540093: +2024-11-23 02:31:00.540307: Epoch 7151 +2024-11-23 02:31:00.540422: Current learning rate: 0.00133 +2024-11-23 02:31:19.192439: train_loss -0.8196 +2024-11-23 02:31:19.192670: val_loss -0.7965 +2024-11-23 02:31:19.192748: Pseudo dice [0.85] +2024-11-23 02:31:19.192823: Epoch time: 18.65 s +2024-11-23 02:31:20.068083: +2024-11-23 02:31:20.068535: Epoch 7152 +2024-11-23 02:31:20.068681: Current learning rate: 0.00133 +2024-11-23 02:31:38.758579: train_loss -0.8141 +2024-11-23 02:31:38.758808: val_loss -0.7599 +2024-11-23 02:31:38.758910: Pseudo dice [0.8555] +2024-11-23 02:31:38.758993: Epoch time: 18.69 s +2024-11-23 02:31:39.751846: +2024-11-23 02:31:39.752303: Epoch 7153 +2024-11-23 02:31:39.752442: Current learning rate: 0.00133 +2024-11-23 02:31:58.403750: train_loss -0.822 +2024-11-23 02:31:58.403972: val_loss -0.7982 +2024-11-23 02:31:58.404069: Pseudo dice [0.8742] +2024-11-23 02:31:58.404152: Epoch time: 18.65 s +2024-11-23 02:31:59.288786: +2024-11-23 02:31:59.289232: Epoch 7154 +2024-11-23 02:31:59.289366: Current learning rate: 0.00132 +2024-11-23 02:32:18.342936: train_loss -0.8206 +2024-11-23 02:32:18.343174: val_loss -0.772 +2024-11-23 02:32:18.343250: Pseudo dice [0.861] +2024-11-23 02:32:18.343337: Epoch time: 19.05 s +2024-11-23 02:32:19.227569: +2024-11-23 02:32:19.228002: Epoch 7155 +2024-11-23 02:32:19.228147: Current learning rate: 0.00132 +2024-11-23 02:32:36.766559: train_loss -0.828 +2024-11-23 02:32:36.766789: val_loss -0.8009 +2024-11-23 02:32:36.766870: Pseudo dice [0.8758] +2024-11-23 02:32:36.766964: Epoch time: 17.54 s +2024-11-23 02:32:37.715325: +2024-11-23 02:32:37.715752: Epoch 7156 +2024-11-23 02:32:37.715909: Current learning rate: 0.00132 +2024-11-23 02:32:57.775550: train_loss -0.8182 +2024-11-23 02:32:57.775767: val_loss -0.7933 +2024-11-23 02:32:57.775846: Pseudo dice [0.8564] +2024-11-23 02:32:57.775922: Epoch time: 20.06 s +2024-11-23 02:32:58.655934: +2024-11-23 02:32:58.656363: Epoch 7157 +2024-11-23 02:32:58.656504: Current learning rate: 0.00132 +2024-11-23 02:33:17.387486: train_loss -0.8301 +2024-11-23 02:33:17.387695: val_loss -0.7908 +2024-11-23 02:33:17.388030: Pseudo dice [0.8509] +2024-11-23 02:33:17.388121: Epoch time: 18.73 s +2024-11-23 02:33:18.286825: +2024-11-23 02:33:18.287258: Epoch 7158 +2024-11-23 02:33:18.287392: Current learning rate: 0.00132 +2024-11-23 02:33:37.709950: train_loss -0.8259 +2024-11-23 02:33:37.710190: val_loss -0.7863 +2024-11-23 02:33:37.710278: Pseudo dice [0.8569] +2024-11-23 02:33:37.710362: Epoch time: 19.42 s +2024-11-23 02:33:38.782958: +2024-11-23 02:33:38.783385: Epoch 7159 +2024-11-23 02:33:38.783530: Current learning rate: 0.00132 +2024-11-23 02:33:56.311118: train_loss -0.8183 +2024-11-23 02:33:56.311324: val_loss -0.8023 +2024-11-23 02:33:56.311402: Pseudo dice [0.8505] +2024-11-23 02:33:56.313659: Epoch time: 17.53 s +2024-11-23 02:33:57.250418: +2024-11-23 02:33:57.250842: Epoch 7160 +2024-11-23 02:33:57.250974: Current learning rate: 0.00132 +2024-11-23 02:34:16.577338: train_loss -0.8244 +2024-11-23 02:34:16.577560: val_loss -0.7809 +2024-11-23 02:34:16.577641: Pseudo dice [0.8611] +2024-11-23 02:34:16.577772: Epoch time: 19.33 s +2024-11-23 02:34:17.458892: +2024-11-23 02:34:17.459324: Epoch 7161 +2024-11-23 02:34:17.459479: Current learning rate: 0.00131 +2024-11-23 02:34:36.608873: train_loss -0.8209 +2024-11-23 02:34:36.609089: val_loss -0.784 +2024-11-23 02:34:36.609170: Pseudo dice [0.8526] +2024-11-23 02:34:36.609269: Epoch time: 19.15 s +2024-11-23 02:34:37.490169: +2024-11-23 02:34:37.490584: Epoch 7162 +2024-11-23 02:34:37.490730: Current learning rate: 0.00131 +2024-11-23 02:34:56.975780: train_loss -0.8259 +2024-11-23 02:34:56.976045: val_loss -0.8045 +2024-11-23 02:34:56.976192: Pseudo dice [0.878] +2024-11-23 02:34:56.976293: Epoch time: 19.49 s +2024-11-23 02:34:58.267446: +2024-11-23 02:34:58.267900: Epoch 7163 +2024-11-23 02:34:58.268050: Current learning rate: 0.00131 +2024-11-23 02:35:16.927198: train_loss -0.8259 +2024-11-23 02:35:16.927424: val_loss -0.7768 +2024-11-23 02:35:16.927504: Pseudo dice [0.8664] +2024-11-23 02:35:16.927587: Epoch time: 18.66 s +2024-11-23 02:35:17.807406: +2024-11-23 02:35:17.807835: Epoch 7164 +2024-11-23 02:35:17.807984: Current learning rate: 0.00131 +2024-11-23 02:35:36.656730: train_loss -0.8248 +2024-11-23 02:35:36.656943: val_loss -0.7578 +2024-11-23 02:35:36.657018: Pseudo dice [0.8609] +2024-11-23 02:35:36.662283: Epoch time: 18.85 s +2024-11-23 02:35:37.703951: +2024-11-23 02:35:37.704375: Epoch 7165 +2024-11-23 02:35:37.704525: Current learning rate: 0.00131 +2024-11-23 02:35:55.687416: train_loss -0.8165 +2024-11-23 02:35:55.687700: val_loss -0.7787 +2024-11-23 02:35:55.687782: Pseudo dice [0.86] +2024-11-23 02:35:55.687871: Epoch time: 17.98 s +2024-11-23 02:35:56.571297: +2024-11-23 02:35:56.571743: Epoch 7166 +2024-11-23 02:35:56.571879: Current learning rate: 0.00131 +2024-11-23 02:36:15.442062: train_loss -0.8197 +2024-11-23 02:36:15.442296: val_loss -0.7909 +2024-11-23 02:36:15.442375: Pseudo dice [0.8619] +2024-11-23 02:36:15.442474: Epoch time: 18.87 s +2024-11-23 02:36:16.325084: +2024-11-23 02:36:16.325499: Epoch 7167 +2024-11-23 02:36:16.325634: Current learning rate: 0.00131 +2024-11-23 02:36:34.932834: train_loss -0.8205 +2024-11-23 02:36:34.935253: val_loss -0.7921 +2024-11-23 02:36:34.935345: Pseudo dice [0.8638] +2024-11-23 02:36:34.935424: Epoch time: 18.61 s +2024-11-23 02:36:35.999403: +2024-11-23 02:36:35.999830: Epoch 7168 +2024-11-23 02:36:35.999973: Current learning rate: 0.0013 +2024-11-23 02:36:54.770769: train_loss -0.8221 +2024-11-23 02:36:54.770980: val_loss -0.7877 +2024-11-23 02:36:54.771057: Pseudo dice [0.8744] +2024-11-23 02:36:54.771145: Epoch time: 18.77 s +2024-11-23 02:36:55.661342: +2024-11-23 02:36:55.661801: Epoch 7169 +2024-11-23 02:36:55.661942: Current learning rate: 0.0013 +2024-11-23 02:37:14.877956: train_loss -0.8264 +2024-11-23 02:37:14.878196: val_loss -0.7911 +2024-11-23 02:37:14.878282: Pseudo dice [0.8648] +2024-11-23 02:37:14.878373: Epoch time: 19.22 s +2024-11-23 02:37:15.764584: +2024-11-23 02:37:15.765005: Epoch 7170 +2024-11-23 02:37:15.765153: Current learning rate: 0.0013 +2024-11-23 02:37:35.093142: train_loss -0.8213 +2024-11-23 02:37:35.093357: val_loss -0.7661 +2024-11-23 02:37:35.093435: Pseudo dice [0.8459] +2024-11-23 02:37:35.093516: Epoch time: 19.33 s +2024-11-23 02:37:35.977683: +2024-11-23 02:37:35.978115: Epoch 7171 +2024-11-23 02:37:35.978251: Current learning rate: 0.0013 +2024-11-23 02:37:55.012907: train_loss -0.8325 +2024-11-23 02:37:55.013130: val_loss -0.7811 +2024-11-23 02:37:55.013227: Pseudo dice [0.8653] +2024-11-23 02:37:55.013307: Epoch time: 19.04 s +2024-11-23 02:37:55.889715: +2024-11-23 02:37:55.890142: Epoch 7172 +2024-11-23 02:37:55.890280: Current learning rate: 0.0013 +2024-11-23 02:38:14.845932: train_loss -0.8223 +2024-11-23 02:38:14.846197: val_loss -0.7873 +2024-11-23 02:38:14.846282: Pseudo dice [0.8506] +2024-11-23 02:38:14.846424: Epoch time: 18.96 s +2024-11-23 02:38:15.722481: +2024-11-23 02:38:15.722890: Epoch 7173 +2024-11-23 02:38:15.723033: Current learning rate: 0.0013 +2024-11-23 02:38:34.562242: train_loss -0.8246 +2024-11-23 02:38:34.562468: val_loss -0.7875 +2024-11-23 02:38:34.562555: Pseudo dice [0.8685] +2024-11-23 02:38:34.562642: Epoch time: 18.84 s +2024-11-23 02:38:35.537731: +2024-11-23 02:38:35.537923: Epoch 7174 +2024-11-23 02:38:35.538040: Current learning rate: 0.0013 +2024-11-23 02:38:53.508491: train_loss -0.8174 +2024-11-23 02:38:53.508779: val_loss -0.7927 +2024-11-23 02:38:53.508877: Pseudo dice [0.8578] +2024-11-23 02:38:53.508957: Epoch time: 17.97 s +2024-11-23 02:38:54.399092: +2024-11-23 02:38:54.399486: Epoch 7175 +2024-11-23 02:38:54.399612: Current learning rate: 0.00129 +2024-11-23 02:39:13.116104: train_loss -0.8219 +2024-11-23 02:39:13.116595: val_loss -0.8025 +2024-11-23 02:39:13.116697: Pseudo dice [0.8632] +2024-11-23 02:39:13.116794: Epoch time: 18.72 s +2024-11-23 02:39:14.104779: +2024-11-23 02:39:14.104992: Epoch 7176 +2024-11-23 02:39:14.105106: Current learning rate: 0.00129 +2024-11-23 02:39:32.302075: train_loss -0.8177 +2024-11-23 02:39:32.302297: val_loss -0.8002 +2024-11-23 02:39:32.302372: Pseudo dice [0.8613] +2024-11-23 02:39:32.302454: Epoch time: 18.2 s +2024-11-23 02:39:33.187131: +2024-11-23 02:39:33.187348: Epoch 7177 +2024-11-23 02:39:33.187469: Current learning rate: 0.00129 +2024-11-23 02:39:51.251275: train_loss -0.8251 +2024-11-23 02:39:51.251577: val_loss -0.7953 +2024-11-23 02:39:51.251664: Pseudo dice [0.8653] +2024-11-23 02:39:51.251749: Epoch time: 18.06 s +2024-11-23 02:39:52.247744: +2024-11-23 02:39:52.247972: Epoch 7178 +2024-11-23 02:39:52.248116: Current learning rate: 0.00129 +2024-11-23 02:40:09.986624: train_loss -0.8203 +2024-11-23 02:40:09.986870: val_loss -0.7687 +2024-11-23 02:40:09.986984: Pseudo dice [0.8606] +2024-11-23 02:40:09.987085: Epoch time: 17.74 s +2024-11-23 02:40:11.073725: +2024-11-23 02:40:11.073965: Epoch 7179 +2024-11-23 02:40:11.074118: Current learning rate: 0.00129 +2024-11-23 02:40:28.757584: train_loss -0.8159 +2024-11-23 02:40:28.757804: val_loss -0.7754 +2024-11-23 02:40:28.762467: Pseudo dice [0.8669] +2024-11-23 02:40:28.762608: Epoch time: 17.68 s +2024-11-23 02:40:29.750514: +2024-11-23 02:40:29.750729: Epoch 7180 +2024-11-23 02:40:29.750845: Current learning rate: 0.00129 +2024-11-23 02:40:46.961566: train_loss -0.8244 +2024-11-23 02:40:46.961795: val_loss -0.7739 +2024-11-23 02:40:46.961878: Pseudo dice [0.8648] +2024-11-23 02:40:46.961957: Epoch time: 17.21 s +2024-11-23 02:40:47.845759: +2024-11-23 02:40:47.845953: Epoch 7181 +2024-11-23 02:40:47.846068: Current learning rate: 0.00129 +2024-11-23 02:41:06.237928: train_loss -0.8154 +2024-11-23 02:41:06.238236: val_loss -0.7832 +2024-11-23 02:41:06.238320: Pseudo dice [0.8623] +2024-11-23 02:41:06.238411: Epoch time: 18.39 s +2024-11-23 02:41:07.126250: +2024-11-23 02:41:07.126445: Epoch 7182 +2024-11-23 02:41:07.126555: Current learning rate: 0.00128 +2024-11-23 02:41:26.125449: train_loss -0.8111 +2024-11-23 02:41:26.125667: val_loss -0.7759 +2024-11-23 02:41:26.125744: Pseudo dice [0.8623] +2024-11-23 02:41:26.125827: Epoch time: 19.0 s +2024-11-23 02:41:27.055417: +2024-11-23 02:41:27.055646: Epoch 7183 +2024-11-23 02:41:27.055762: Current learning rate: 0.00128 +2024-11-23 02:41:45.867356: train_loss -0.8115 +2024-11-23 02:41:45.867920: val_loss -0.7512 +2024-11-23 02:41:45.868023: Pseudo dice [0.8473] +2024-11-23 02:41:45.868116: Epoch time: 18.81 s +2024-11-23 02:41:46.744872: +2024-11-23 02:41:46.745068: Epoch 7184 +2024-11-23 02:41:46.745184: Current learning rate: 0.00128 +2024-11-23 02:42:05.317151: train_loss -0.8157 +2024-11-23 02:42:05.317402: val_loss -0.7899 +2024-11-23 02:42:05.317482: Pseudo dice [0.8608] +2024-11-23 02:42:05.317572: Epoch time: 18.57 s +2024-11-23 02:42:06.201577: +2024-11-23 02:42:06.201790: Epoch 7185 +2024-11-23 02:42:06.201899: Current learning rate: 0.00128 +2024-11-23 02:42:24.349561: train_loss -0.8188 +2024-11-23 02:42:24.354987: val_loss -0.7801 +2024-11-23 02:42:24.355127: Pseudo dice [0.8549] +2024-11-23 02:42:24.355211: Epoch time: 18.15 s +2024-11-23 02:42:25.669599: +2024-11-23 02:42:25.669812: Epoch 7186 +2024-11-23 02:42:25.669946: Current learning rate: 0.00128 +2024-11-23 02:42:44.679328: train_loss -0.8194 +2024-11-23 02:42:44.679562: val_loss -0.8057 +2024-11-23 02:42:44.679639: Pseudo dice [0.8717] +2024-11-23 02:42:44.679732: Epoch time: 19.01 s +2024-11-23 02:42:45.574404: +2024-11-23 02:42:45.574595: Epoch 7187 +2024-11-23 02:42:45.574707: Current learning rate: 0.00128 +2024-11-23 02:43:04.802451: train_loss -0.8134 +2024-11-23 02:43:04.802679: val_loss -0.7816 +2024-11-23 02:43:04.802761: Pseudo dice [0.8573] +2024-11-23 02:43:04.802860: Epoch time: 19.23 s +2024-11-23 02:43:05.705382: +2024-11-23 02:43:05.705659: Epoch 7188 +2024-11-23 02:43:05.705817: Current learning rate: 0.00128 +2024-11-23 02:43:24.985995: train_loss -0.8188 +2024-11-23 02:43:24.986229: val_loss -0.7874 +2024-11-23 02:43:24.986316: Pseudo dice [0.875] +2024-11-23 02:43:24.986399: Epoch time: 19.28 s +2024-11-23 02:43:25.868350: +2024-11-23 02:43:25.868543: Epoch 7189 +2024-11-23 02:43:25.868659: Current learning rate: 0.00127 +2024-11-23 02:43:44.138180: train_loss -0.827 +2024-11-23 02:43:44.138410: val_loss -0.7874 +2024-11-23 02:43:44.138492: Pseudo dice [0.8525] +2024-11-23 02:43:44.138570: Epoch time: 18.27 s +2024-11-23 02:43:45.024591: +2024-11-23 02:43:45.024788: Epoch 7190 +2024-11-23 02:43:45.024909: Current learning rate: 0.00127 +2024-11-23 02:44:03.416403: train_loss -0.8183 +2024-11-23 02:44:03.416622: val_loss -0.7928 +2024-11-23 02:44:03.416701: Pseudo dice [0.8646] +2024-11-23 02:44:03.416775: Epoch time: 18.39 s +2024-11-23 02:44:04.341682: +2024-11-23 02:44:04.341898: Epoch 7191 +2024-11-23 02:44:04.342005: Current learning rate: 0.00127 +2024-11-23 02:44:23.012350: train_loss -0.8279 +2024-11-23 02:44:23.012569: val_loss -0.7845 +2024-11-23 02:44:23.012654: Pseudo dice [0.8669] +2024-11-23 02:44:23.012733: Epoch time: 18.67 s +2024-11-23 02:44:23.899001: +2024-11-23 02:44:23.899222: Epoch 7192 +2024-11-23 02:44:23.899329: Current learning rate: 0.00127 +2024-11-23 02:44:42.092202: train_loss -0.8247 +2024-11-23 02:44:42.092523: val_loss -0.7787 +2024-11-23 02:44:42.092617: Pseudo dice [0.8595] +2024-11-23 02:44:42.092715: Epoch time: 18.19 s +2024-11-23 02:44:42.972121: +2024-11-23 02:44:42.972342: Epoch 7193 +2024-11-23 02:44:42.972460: Current learning rate: 0.00127 +2024-11-23 02:45:02.331292: train_loss -0.8248 +2024-11-23 02:45:02.331508: val_loss -0.7553 +2024-11-23 02:45:02.331586: Pseudo dice [0.8639] +2024-11-23 02:45:02.331666: Epoch time: 19.36 s +2024-11-23 02:45:03.392618: +2024-11-23 02:45:03.392814: Epoch 7194 +2024-11-23 02:45:03.392929: Current learning rate: 0.00127 +2024-11-23 02:45:22.380577: train_loss -0.8259 +2024-11-23 02:45:22.380790: val_loss -0.7939 +2024-11-23 02:45:22.380866: Pseudo dice [0.859] +2024-11-23 02:45:22.383157: Epoch time: 18.99 s +2024-11-23 02:45:23.362471: +2024-11-23 02:45:23.362692: Epoch 7195 +2024-11-23 02:45:23.362815: Current learning rate: 0.00127 +2024-11-23 02:45:41.989885: train_loss -0.8217 +2024-11-23 02:45:41.990099: val_loss -0.7796 +2024-11-23 02:45:41.990177: Pseudo dice [0.8703] +2024-11-23 02:45:41.990256: Epoch time: 18.63 s +2024-11-23 02:45:42.876891: +2024-11-23 02:45:42.877102: Epoch 7196 +2024-11-23 02:45:42.877233: Current learning rate: 0.00126 +2024-11-23 02:46:00.916276: train_loss -0.8139 +2024-11-23 02:46:00.916514: val_loss -0.7666 +2024-11-23 02:46:00.916609: Pseudo dice [0.8646] +2024-11-23 02:46:00.916702: Epoch time: 18.04 s +2024-11-23 02:46:01.972588: +2024-11-23 02:46:01.973041: Epoch 7197 +2024-11-23 02:46:01.973181: Current learning rate: 0.00126 +2024-11-23 02:46:20.077741: train_loss -0.8133 +2024-11-23 02:46:20.077978: val_loss -0.768 +2024-11-23 02:46:20.078073: Pseudo dice [0.8589] +2024-11-23 02:46:20.078152: Epoch time: 18.11 s +2024-11-23 02:46:20.952519: +2024-11-23 02:46:20.952721: Epoch 7198 +2024-11-23 02:46:20.952836: Current learning rate: 0.00126 +2024-11-23 02:46:40.025645: train_loss -0.8152 +2024-11-23 02:46:40.025874: val_loss -0.805 +2024-11-23 02:46:40.025951: Pseudo dice [0.8632] +2024-11-23 02:46:40.026038: Epoch time: 19.07 s +2024-11-23 02:46:40.908871: +2024-11-23 02:46:40.909099: Epoch 7199 +2024-11-23 02:46:40.909222: Current learning rate: 0.00126 +2024-11-23 02:46:58.164521: train_loss -0.819 +2024-11-23 02:46:58.164770: val_loss -0.7578 +2024-11-23 02:46:58.164916: Pseudo dice [0.8477] +2024-11-23 02:46:58.165003: Epoch time: 17.26 s +2024-11-23 02:46:59.411409: +2024-11-23 02:46:59.411624: Epoch 7200 +2024-11-23 02:46:59.411762: Current learning rate: 0.00126 +2024-11-23 02:47:17.003386: train_loss -0.8218 +2024-11-23 02:47:17.008743: val_loss -0.7665 +2024-11-23 02:47:17.008918: Pseudo dice [0.8536] +2024-11-23 02:47:17.009011: Epoch time: 17.59 s +2024-11-23 02:47:18.105331: +2024-11-23 02:47:18.105559: Epoch 7201 +2024-11-23 02:47:18.105685: Current learning rate: 0.00126 +2024-11-23 02:47:38.396464: train_loss -0.8125 +2024-11-23 02:47:38.396678: val_loss -0.7885 +2024-11-23 02:47:38.396763: Pseudo dice [0.8496] +2024-11-23 02:47:38.396843: Epoch time: 20.29 s +2024-11-23 02:47:39.279583: +2024-11-23 02:47:39.279791: Epoch 7202 +2024-11-23 02:47:39.279906: Current learning rate: 0.00126 +2024-11-23 02:47:58.258035: train_loss -0.8226 +2024-11-23 02:47:58.258257: val_loss -0.7667 +2024-11-23 02:47:58.258338: Pseudo dice [0.8551] +2024-11-23 02:47:58.258413: Epoch time: 18.98 s +2024-11-23 02:47:59.136409: +2024-11-23 02:47:59.136605: Epoch 7203 +2024-11-23 02:47:59.136720: Current learning rate: 0.00125 +2024-11-23 02:48:17.850018: train_loss -0.8241 +2024-11-23 02:48:17.850272: val_loss -0.794 +2024-11-23 02:48:17.850350: Pseudo dice [0.8524] +2024-11-23 02:48:17.850434: Epoch time: 18.71 s +2024-11-23 02:48:18.734952: +2024-11-23 02:48:18.735169: Epoch 7204 +2024-11-23 02:48:18.735288: Current learning rate: 0.00125 +2024-11-23 02:48:36.844781: train_loss -0.8251 +2024-11-23 02:48:36.845016: val_loss -0.7852 +2024-11-23 02:48:36.845137: Pseudo dice [0.8592] +2024-11-23 02:48:36.845223: Epoch time: 18.11 s +2024-11-23 02:48:37.727947: +2024-11-23 02:48:37.728215: Epoch 7205 +2024-11-23 02:48:37.728340: Current learning rate: 0.00125 +2024-11-23 02:48:55.628941: train_loss -0.8157 +2024-11-23 02:48:55.629184: val_loss -0.7799 +2024-11-23 02:48:55.629264: Pseudo dice [0.8632] +2024-11-23 02:48:55.629347: Epoch time: 17.9 s +2024-11-23 02:48:56.883956: +2024-11-23 02:48:56.884205: Epoch 7206 +2024-11-23 02:48:56.884318: Current learning rate: 0.00125 +2024-11-23 02:49:14.855606: train_loss -0.8277 +2024-11-23 02:49:14.855897: val_loss -0.77 +2024-11-23 02:49:14.855989: Pseudo dice [0.8625] +2024-11-23 02:49:14.856075: Epoch time: 17.97 s +2024-11-23 02:49:15.740927: +2024-11-23 02:49:15.741164: Epoch 7207 +2024-11-23 02:49:15.741289: Current learning rate: 0.00125 +2024-11-23 02:49:34.048239: train_loss -0.8215 +2024-11-23 02:49:34.048476: val_loss -0.7755 +2024-11-23 02:49:34.048568: Pseudo dice [0.8682] +2024-11-23 02:49:34.050590: Epoch time: 18.31 s +2024-11-23 02:49:35.314758: +2024-11-23 02:49:35.314959: Epoch 7208 +2024-11-23 02:49:35.315073: Current learning rate: 0.00125 +2024-11-23 02:49:53.141719: train_loss -0.8174 +2024-11-23 02:49:53.141964: val_loss -0.7992 +2024-11-23 02:49:53.142052: Pseudo dice [0.8654] +2024-11-23 02:49:53.142139: Epoch time: 17.83 s +2024-11-23 02:49:54.015861: +2024-11-23 02:49:54.016091: Epoch 7209 +2024-11-23 02:49:54.016232: Current learning rate: 0.00125 +2024-11-23 02:50:12.983603: train_loss -0.8172 +2024-11-23 02:50:12.983908: val_loss -0.7617 +2024-11-23 02:50:12.984004: Pseudo dice [0.8666] +2024-11-23 02:50:12.984091: Epoch time: 18.97 s +2024-11-23 02:50:13.987452: +2024-11-23 02:50:13.987673: Epoch 7210 +2024-11-23 02:50:13.987796: Current learning rate: 0.00124 +2024-11-23 02:50:32.152787: train_loss -0.8214 +2024-11-23 02:50:32.153026: val_loss -0.7961 +2024-11-23 02:50:32.153112: Pseudo dice [0.8658] +2024-11-23 02:50:32.153198: Epoch time: 18.17 s +2024-11-23 02:50:33.043316: +2024-11-23 02:50:33.043539: Epoch 7211 +2024-11-23 02:50:33.043657: Current learning rate: 0.00124 +2024-11-23 02:50:51.845826: train_loss -0.8216 +2024-11-23 02:50:51.846042: val_loss -0.7962 +2024-11-23 02:50:51.846896: Pseudo dice [0.869] +2024-11-23 02:50:51.847018: Epoch time: 18.8 s +2024-11-23 02:50:52.727811: +2024-11-23 02:50:52.728029: Epoch 7212 +2024-11-23 02:50:52.728153: Current learning rate: 0.00124 +2024-11-23 02:51:11.103218: train_loss -0.8253 +2024-11-23 02:51:11.103437: val_loss -0.7701 +2024-11-23 02:51:11.103535: Pseudo dice [0.8568] +2024-11-23 02:51:11.103611: Epoch time: 18.38 s +2024-11-23 02:51:11.988713: +2024-11-23 02:51:11.988922: Epoch 7213 +2024-11-23 02:51:11.989049: Current learning rate: 0.00124 +2024-11-23 02:51:29.369726: train_loss -0.8245 +2024-11-23 02:51:29.369959: val_loss -0.7887 +2024-11-23 02:51:29.370056: Pseudo dice [0.8564] +2024-11-23 02:51:29.370145: Epoch time: 17.38 s +2024-11-23 02:51:30.255315: +2024-11-23 02:51:30.255518: Epoch 7214 +2024-11-23 02:51:30.255629: Current learning rate: 0.00124 +2024-11-23 02:51:49.781892: train_loss -0.8174 +2024-11-23 02:51:49.782122: val_loss -0.7988 +2024-11-23 02:51:49.782203: Pseudo dice [0.8589] +2024-11-23 02:51:49.782314: Epoch time: 19.53 s +2024-11-23 02:51:50.669816: +2024-11-23 02:51:50.670033: Epoch 7215 +2024-11-23 02:51:50.670157: Current learning rate: 0.00124 +2024-11-23 02:52:09.645577: train_loss -0.8292 +2024-11-23 02:52:09.645821: val_loss -0.7921 +2024-11-23 02:52:09.645929: Pseudo dice [0.8684] +2024-11-23 02:52:09.646023: Epoch time: 18.98 s +2024-11-23 02:52:10.529679: +2024-11-23 02:52:10.529882: Epoch 7216 +2024-11-23 02:52:10.529998: Current learning rate: 0.00124 +2024-11-23 02:52:30.150938: train_loss -0.8212 +2024-11-23 02:52:30.151224: val_loss -0.7819 +2024-11-23 02:52:30.151303: Pseudo dice [0.8593] +2024-11-23 02:52:30.151376: Epoch time: 19.62 s +2024-11-23 02:52:31.038299: +2024-11-23 02:52:31.038505: Epoch 7217 +2024-11-23 02:52:31.038616: Current learning rate: 0.00123 +2024-11-23 02:52:47.905895: train_loss -0.8303 +2024-11-23 02:52:47.906132: val_loss -0.7718 +2024-11-23 02:52:47.906212: Pseudo dice [0.8695] +2024-11-23 02:52:47.906291: Epoch time: 16.87 s +2024-11-23 02:52:48.785645: +2024-11-23 02:52:48.785895: Epoch 7218 +2024-11-23 02:52:48.786020: Current learning rate: 0.00123 +2024-11-23 02:53:06.319220: train_loss -0.8291 +2024-11-23 02:53:06.319472: val_loss -0.814 +2024-11-23 02:53:06.319566: Pseudo dice [0.8753] +2024-11-23 02:53:06.319654: Epoch time: 17.53 s +2024-11-23 02:53:06.319721: Yayy! New best EMA pseudo Dice: 0.8636 +2024-11-23 02:53:07.637363: +2024-11-23 02:53:07.637569: Epoch 7219 +2024-11-23 02:53:07.637681: Current learning rate: 0.00123 +2024-11-23 02:53:26.621369: train_loss -0.8205 +2024-11-23 02:53:26.621580: val_loss -0.7903 +2024-11-23 02:53:26.621662: Pseudo dice [0.8511] +2024-11-23 02:53:26.621742: Epoch time: 18.98 s +2024-11-23 02:53:27.940188: +2024-11-23 02:53:27.940428: Epoch 7220 +2024-11-23 02:53:27.940562: Current learning rate: 0.00123 +2024-11-23 02:53:46.728942: train_loss -0.8238 +2024-11-23 02:53:46.729162: val_loss -0.7879 +2024-11-23 02:53:46.729270: Pseudo dice [0.8614] +2024-11-23 02:53:46.729388: Epoch time: 18.79 s +2024-11-23 02:53:47.612924: +2024-11-23 02:53:47.613178: Epoch 7221 +2024-11-23 02:53:47.613294: Current learning rate: 0.00123 +2024-11-23 02:54:05.700191: train_loss -0.8204 +2024-11-23 02:54:05.700471: val_loss -0.7919 +2024-11-23 02:54:05.700565: Pseudo dice [0.8756] +2024-11-23 02:54:05.700677: Epoch time: 18.08 s +2024-11-23 02:54:06.693181: +2024-11-23 02:54:06.693424: Epoch 7222 +2024-11-23 02:54:06.693538: Current learning rate: 0.00123 +2024-11-23 02:54:24.912099: train_loss -0.822 +2024-11-23 02:54:24.912345: val_loss -0.7778 +2024-11-23 02:54:24.912433: Pseudo dice [0.8652] +2024-11-23 02:54:24.912519: Epoch time: 18.22 s +2024-11-23 02:54:24.912582: Yayy! New best EMA pseudo Dice: 0.8638 +2024-11-23 02:54:26.153967: +2024-11-23 02:54:26.154201: Epoch 7223 +2024-11-23 02:54:26.154320: Current learning rate: 0.00123 +2024-11-23 02:54:45.294335: train_loss -0.8212 +2024-11-23 02:54:45.294542: val_loss -0.779 +2024-11-23 02:54:45.294622: Pseudo dice [0.8633] +2024-11-23 02:54:45.294715: Epoch time: 19.14 s +2024-11-23 02:54:46.179605: +2024-11-23 02:54:46.179822: Epoch 7224 +2024-11-23 02:54:46.179983: Current learning rate: 0.00122 +2024-11-23 02:55:05.197782: train_loss -0.8188 +2024-11-23 02:55:05.198000: val_loss -0.765 +2024-11-23 02:55:05.198095: Pseudo dice [0.8683] +2024-11-23 02:55:05.198188: Epoch time: 19.02 s +2024-11-23 02:55:05.198250: Yayy! New best EMA pseudo Dice: 0.8642 +2024-11-23 02:55:06.427812: +2024-11-23 02:55:06.428033: Epoch 7225 +2024-11-23 02:55:06.428169: Current learning rate: 0.00122 +2024-11-23 02:55:25.213932: train_loss -0.8192 +2024-11-23 02:55:25.214172: val_loss -0.8034 +2024-11-23 02:55:25.214252: Pseudo dice [0.8753] +2024-11-23 02:55:25.214338: Epoch time: 18.79 s +2024-11-23 02:55:25.214401: Yayy! New best EMA pseudo Dice: 0.8653 +2024-11-23 02:55:26.445286: +2024-11-23 02:55:26.445512: Epoch 7226 +2024-11-23 02:55:26.445629: Current learning rate: 0.00122 +2024-11-23 02:55:44.466927: train_loss -0.8155 +2024-11-23 02:55:44.467179: val_loss -0.8037 +2024-11-23 02:55:44.467260: Pseudo dice [0.8678] +2024-11-23 02:55:44.467363: Epoch time: 18.02 s +2024-11-23 02:55:44.467431: Yayy! New best EMA pseudo Dice: 0.8655 +2024-11-23 02:55:45.709948: +2024-11-23 02:55:45.710178: Epoch 7227 +2024-11-23 02:55:45.710290: Current learning rate: 0.00122 +2024-11-23 02:56:05.303476: train_loss -0.8178 +2024-11-23 02:56:05.303682: val_loss -0.7824 +2024-11-23 02:56:05.303773: Pseudo dice [0.8482] +2024-11-23 02:56:05.303863: Epoch time: 19.59 s +2024-11-23 02:56:06.186355: +2024-11-23 02:56:06.186565: Epoch 7228 +2024-11-23 02:56:06.186678: Current learning rate: 0.00122 +2024-11-23 02:56:24.417928: train_loss -0.8157 +2024-11-23 02:56:24.418143: val_loss -0.7884 +2024-11-23 02:56:24.418232: Pseudo dice [0.8668] +2024-11-23 02:56:24.418320: Epoch time: 18.23 s +2024-11-23 02:56:25.310008: +2024-11-23 02:56:25.310260: Epoch 7229 +2024-11-23 02:56:25.310372: Current learning rate: 0.00122 +2024-11-23 02:56:43.667495: train_loss -0.8237 +2024-11-23 02:56:43.667719: val_loss -0.7806 +2024-11-23 02:56:43.667798: Pseudo dice [0.8526] +2024-11-23 02:56:43.667884: Epoch time: 18.36 s +2024-11-23 02:56:44.571257: +2024-11-23 02:56:44.571536: Epoch 7230 +2024-11-23 02:56:44.571666: Current learning rate: 0.00122 +2024-11-23 02:57:02.924492: train_loss -0.8201 +2024-11-23 02:57:02.924727: val_loss -0.7829 +2024-11-23 02:57:02.924808: Pseudo dice [0.8572] +2024-11-23 02:57:02.924890: Epoch time: 18.35 s +2024-11-23 02:57:04.208455: +2024-11-23 02:57:04.208669: Epoch 7231 +2024-11-23 02:57:04.208781: Current learning rate: 0.00121 +2024-11-23 02:57:22.275184: train_loss -0.8151 +2024-11-23 02:57:22.275459: val_loss -0.7834 +2024-11-23 02:57:22.275548: Pseudo dice [0.8649] +2024-11-23 02:57:22.275646: Epoch time: 18.07 s +2024-11-23 02:57:23.163241: +2024-11-23 02:57:23.163470: Epoch 7232 +2024-11-23 02:57:23.163579: Current learning rate: 0.00121 +2024-11-23 02:57:41.029959: train_loss -0.8202 +2024-11-23 02:57:41.030175: val_loss -0.8008 +2024-11-23 02:57:41.030258: Pseudo dice [0.8746] +2024-11-23 02:57:41.030348: Epoch time: 17.87 s +2024-11-23 02:57:41.910054: +2024-11-23 02:57:41.910299: Epoch 7233 +2024-11-23 02:57:41.910424: Current learning rate: 0.00121 +2024-11-23 02:58:00.421772: train_loss -0.8111 +2024-11-23 02:58:00.422001: val_loss -0.7924 +2024-11-23 02:58:00.422089: Pseudo dice [0.868] +2024-11-23 02:58:00.422172: Epoch time: 18.51 s +2024-11-23 02:58:01.306434: +2024-11-23 02:58:01.306651: Epoch 7234 +2024-11-23 02:58:01.306767: Current learning rate: 0.00121 +2024-11-23 02:58:19.290723: train_loss -0.8213 +2024-11-23 02:58:19.296130: val_loss -0.7744 +2024-11-23 02:58:19.296240: Pseudo dice [0.8556] +2024-11-23 02:58:19.296329: Epoch time: 17.99 s +2024-11-23 02:58:20.418327: +2024-11-23 02:58:20.418563: Epoch 7235 +2024-11-23 02:58:20.418683: Current learning rate: 0.00121 +2024-11-23 02:58:39.755318: train_loss -0.8101 +2024-11-23 02:58:39.755547: val_loss -0.7684 +2024-11-23 02:58:39.755624: Pseudo dice [0.8603] +2024-11-23 02:58:39.755737: Epoch time: 19.34 s +2024-11-23 02:58:40.644124: +2024-11-23 02:58:40.644332: Epoch 7236 +2024-11-23 02:58:40.644444: Current learning rate: 0.00121 +2024-11-23 02:58:59.774528: train_loss -0.8153 +2024-11-23 02:58:59.774741: val_loss -0.7996 +2024-11-23 02:58:59.774822: Pseudo dice [0.8818] +2024-11-23 02:58:59.774899: Epoch time: 19.13 s +2024-11-23 02:59:00.653852: +2024-11-23 02:59:00.654071: Epoch 7237 +2024-11-23 02:59:00.654208: Current learning rate: 0.00121 +2024-11-23 02:59:19.396617: train_loss -0.8165 +2024-11-23 02:59:19.396938: val_loss -0.7868 +2024-11-23 02:59:19.397025: Pseudo dice [0.8711] +2024-11-23 02:59:19.397116: Epoch time: 18.74 s +2024-11-23 02:59:19.397187: Yayy! New best EMA pseudo Dice: 0.8656 +2024-11-23 02:59:20.636640: +2024-11-23 02:59:20.636861: Epoch 7238 +2024-11-23 02:59:20.636981: Current learning rate: 0.0012 +2024-11-23 02:59:39.630577: train_loss -0.8142 +2024-11-23 02:59:39.630790: val_loss -0.7932 +2024-11-23 02:59:39.630870: Pseudo dice [0.8605] +2024-11-23 02:59:39.630968: Epoch time: 18.99 s +2024-11-23 02:59:40.514044: +2024-11-23 02:59:40.514276: Epoch 7239 +2024-11-23 02:59:40.514417: Current learning rate: 0.0012 +2024-11-23 03:00:00.015035: train_loss -0.8335 +2024-11-23 03:00:00.015253: val_loss -0.7847 +2024-11-23 03:00:00.015332: Pseudo dice [0.8671] +2024-11-23 03:00:00.015431: Epoch time: 19.5 s +2024-11-23 03:00:00.897345: +2024-11-23 03:00:00.897551: Epoch 7240 +2024-11-23 03:00:00.897668: Current learning rate: 0.0012 +2024-11-23 03:00:19.159500: train_loss -0.8175 +2024-11-23 03:00:19.159707: val_loss -0.778 +2024-11-23 03:00:19.159803: Pseudo dice [0.8458] +2024-11-23 03:00:19.159878: Epoch time: 18.26 s +2024-11-23 03:00:20.042653: +2024-11-23 03:00:20.042875: Epoch 7241 +2024-11-23 03:00:20.043003: Current learning rate: 0.0012 +2024-11-23 03:00:38.229863: train_loss -0.8256 +2024-11-23 03:00:38.230113: val_loss -0.7775 +2024-11-23 03:00:38.230194: Pseudo dice [0.8418] +2024-11-23 03:00:38.230276: Epoch time: 18.19 s +2024-11-23 03:00:39.121890: +2024-11-23 03:00:39.122085: Epoch 7242 +2024-11-23 03:00:39.122201: Current learning rate: 0.0012 +2024-11-23 03:00:57.826195: train_loss -0.8167 +2024-11-23 03:00:57.826430: val_loss -0.766 +2024-11-23 03:00:57.826525: Pseudo dice [0.8587] +2024-11-23 03:00:57.826620: Epoch time: 18.71 s +2024-11-23 03:00:58.707247: +2024-11-23 03:00:58.707462: Epoch 7243 +2024-11-23 03:00:58.707583: Current learning rate: 0.0012 +2024-11-23 03:01:17.020277: train_loss -0.8281 +2024-11-23 03:01:17.025922: val_loss -0.7918 +2024-11-23 03:01:17.026079: Pseudo dice [0.8659] +2024-11-23 03:01:17.026177: Epoch time: 18.31 s +2024-11-23 03:01:17.921607: +2024-11-23 03:01:17.921840: Epoch 7244 +2024-11-23 03:01:17.921957: Current learning rate: 0.0012 +2024-11-23 03:01:37.564808: train_loss -0.8231 +2024-11-23 03:01:37.565047: val_loss -0.7636 +2024-11-23 03:01:37.565140: Pseudo dice [0.8575] +2024-11-23 03:01:37.565223: Epoch time: 19.64 s +2024-11-23 03:01:38.450642: +2024-11-23 03:01:38.450881: Epoch 7245 +2024-11-23 03:01:38.451010: Current learning rate: 0.0012 +2024-11-23 03:01:57.233285: train_loss -0.8302 +2024-11-23 03:01:57.233534: val_loss -0.7679 +2024-11-23 03:01:57.233610: Pseudo dice [0.8604] +2024-11-23 03:01:57.233698: Epoch time: 18.78 s +2024-11-23 03:01:58.121392: +2024-11-23 03:01:58.121596: Epoch 7246 +2024-11-23 03:01:58.121714: Current learning rate: 0.00119 +2024-11-23 03:02:17.550776: train_loss -0.8248 +2024-11-23 03:02:17.551009: val_loss -0.7801 +2024-11-23 03:02:17.551114: Pseudo dice [0.8556] +2024-11-23 03:02:17.551206: Epoch time: 19.43 s +2024-11-23 03:02:18.439863: +2024-11-23 03:02:18.440078: Epoch 7247 +2024-11-23 03:02:18.440200: Current learning rate: 0.00119 +2024-11-23 03:02:37.101482: train_loss -0.8184 +2024-11-23 03:02:37.101696: val_loss -0.7848 +2024-11-23 03:02:37.101775: Pseudo dice [0.8687] +2024-11-23 03:02:37.101866: Epoch time: 18.66 s +2024-11-23 03:02:37.981505: +2024-11-23 03:02:37.981709: Epoch 7248 +2024-11-23 03:02:37.981828: Current learning rate: 0.00119 +2024-11-23 03:02:56.602252: train_loss -0.8191 +2024-11-23 03:02:56.602463: val_loss -0.7746 +2024-11-23 03:02:56.602558: Pseudo dice [0.8511] +2024-11-23 03:02:56.602636: Epoch time: 18.62 s +2024-11-23 03:02:57.490283: +2024-11-23 03:02:57.490492: Epoch 7249 +2024-11-23 03:02:57.490618: Current learning rate: 0.00119 +2024-11-23 03:03:16.298627: train_loss -0.8162 +2024-11-23 03:03:16.298879: val_loss -0.7911 +2024-11-23 03:03:16.298975: Pseudo dice [0.8617] +2024-11-23 03:03:16.299087: Epoch time: 18.81 s +2024-11-23 03:03:17.560358: +2024-11-23 03:03:17.560568: Epoch 7250 +2024-11-23 03:03:17.560685: Current learning rate: 0.00119 +2024-11-23 03:03:36.249706: train_loss -0.8158 +2024-11-23 03:03:36.249906: val_loss -0.7888 +2024-11-23 03:03:36.249999: Pseudo dice [0.8547] +2024-11-23 03:03:36.250085: Epoch time: 18.69 s +2024-11-23 03:03:37.120090: +2024-11-23 03:03:37.120299: Epoch 7251 +2024-11-23 03:03:37.120419: Current learning rate: 0.00119 +2024-11-23 03:03:55.929950: train_loss -0.817 +2024-11-23 03:03:55.930157: val_loss -0.7741 +2024-11-23 03:03:55.930243: Pseudo dice [0.8637] +2024-11-23 03:03:55.930321: Epoch time: 18.81 s +2024-11-23 03:03:56.793243: +2024-11-23 03:03:56.793440: Epoch 7252 +2024-11-23 03:03:56.793550: Current learning rate: 0.00119 +2024-11-23 03:04:15.665638: train_loss -0.8202 +2024-11-23 03:04:15.666093: val_loss -0.805 +2024-11-23 03:04:15.666215: Pseudo dice [0.849] +2024-11-23 03:04:15.666304: Epoch time: 18.87 s +2024-11-23 03:04:16.595842: +2024-11-23 03:04:16.596043: Epoch 7253 +2024-11-23 03:04:16.596159: Current learning rate: 0.00118 +2024-11-23 03:04:35.517034: train_loss -0.8223 +2024-11-23 03:04:35.517274: val_loss -0.7906 +2024-11-23 03:04:35.517353: Pseudo dice [0.8655] +2024-11-23 03:04:35.517436: Epoch time: 18.92 s +2024-11-23 03:04:36.405364: +2024-11-23 03:04:36.405607: Epoch 7254 +2024-11-23 03:04:36.405738: Current learning rate: 0.00118 +2024-11-23 03:04:53.990747: train_loss -0.8277 +2024-11-23 03:04:53.990999: val_loss -0.7763 +2024-11-23 03:04:53.991084: Pseudo dice [0.858] +2024-11-23 03:04:53.991166: Epoch time: 17.59 s +2024-11-23 03:04:54.875442: +2024-11-23 03:04:54.875659: Epoch 7255 +2024-11-23 03:04:54.875773: Current learning rate: 0.00118 +2024-11-23 03:05:13.893563: train_loss -0.8138 +2024-11-23 03:05:13.893779: val_loss -0.7752 +2024-11-23 03:05:13.893856: Pseudo dice [0.8606] +2024-11-23 03:05:13.893931: Epoch time: 19.02 s +2024-11-23 03:05:14.778759: +2024-11-23 03:05:14.778977: Epoch 7256 +2024-11-23 03:05:14.779094: Current learning rate: 0.00118 +2024-11-23 03:05:34.174634: train_loss -0.8215 +2024-11-23 03:05:34.174873: val_loss -0.7989 +2024-11-23 03:05:34.174977: Pseudo dice [0.8624] +2024-11-23 03:05:34.175093: Epoch time: 19.4 s +2024-11-23 03:05:35.059677: +2024-11-23 03:05:35.059906: Epoch 7257 +2024-11-23 03:05:35.060030: Current learning rate: 0.00118 +2024-11-23 03:05:53.923940: train_loss -0.827 +2024-11-23 03:05:53.924157: val_loss -0.798 +2024-11-23 03:05:53.924238: Pseudo dice [0.8636] +2024-11-23 03:05:53.924317: Epoch time: 18.87 s +2024-11-23 03:05:54.808661: +2024-11-23 03:05:54.808897: Epoch 7258 +2024-11-23 03:05:54.809021: Current learning rate: 0.00118 +2024-11-23 03:06:14.790658: train_loss -0.819 +2024-11-23 03:06:14.790879: val_loss -0.7996 +2024-11-23 03:06:14.790967: Pseudo dice [0.8707] +2024-11-23 03:06:14.791057: Epoch time: 19.98 s +2024-11-23 03:06:15.677432: +2024-11-23 03:06:15.677638: Epoch 7259 +2024-11-23 03:06:15.677754: Current learning rate: 0.00118 +2024-11-23 03:06:33.870003: train_loss -0.8202 +2024-11-23 03:06:33.870269: val_loss -0.7784 +2024-11-23 03:06:33.870352: Pseudo dice [0.8554] +2024-11-23 03:06:33.870431: Epoch time: 18.19 s +2024-11-23 03:06:34.782424: +2024-11-23 03:06:34.782629: Epoch 7260 +2024-11-23 03:06:34.782754: Current learning rate: 0.00117 +2024-11-23 03:06:51.996110: train_loss -0.8287 +2024-11-23 03:06:51.996356: val_loss -0.7768 +2024-11-23 03:06:51.996441: Pseudo dice [0.8541] +2024-11-23 03:06:51.996532: Epoch time: 17.21 s +2024-11-23 03:06:52.882457: +2024-11-23 03:06:52.882664: Epoch 7261 +2024-11-23 03:06:52.882783: Current learning rate: 0.00117 +2024-11-23 03:07:12.354500: train_loss -0.8299 +2024-11-23 03:07:12.354713: val_loss -0.7594 +2024-11-23 03:07:12.354792: Pseudo dice [0.8593] +2024-11-23 03:07:12.354877: Epoch time: 19.47 s +2024-11-23 03:07:13.240560: +2024-11-23 03:07:13.240785: Epoch 7262 +2024-11-23 03:07:13.240900: Current learning rate: 0.00117 +2024-11-23 03:07:31.967411: train_loss -0.823 +2024-11-23 03:07:31.967638: val_loss -0.7851 +2024-11-23 03:07:31.967722: Pseudo dice [0.8574] +2024-11-23 03:07:31.967811: Epoch time: 18.73 s +2024-11-23 03:07:32.853913: +2024-11-23 03:07:32.854132: Epoch 7263 +2024-11-23 03:07:32.854252: Current learning rate: 0.00117 +2024-11-23 03:07:51.877038: train_loss -0.8158 +2024-11-23 03:07:51.877260: val_loss -0.7894 +2024-11-23 03:07:51.877351: Pseudo dice [0.8691] +2024-11-23 03:07:51.877443: Epoch time: 19.02 s +2024-11-23 03:07:52.758787: +2024-11-23 03:07:52.759030: Epoch 7264 +2024-11-23 03:07:52.759156: Current learning rate: 0.00117 +2024-11-23 03:08:11.395055: train_loss -0.8199 +2024-11-23 03:08:11.395315: val_loss -0.7819 +2024-11-23 03:08:11.395392: Pseudo dice [0.8509] +2024-11-23 03:08:11.395480: Epoch time: 18.64 s +2024-11-23 03:08:12.782391: +2024-11-23 03:08:12.782599: Epoch 7265 +2024-11-23 03:08:12.782713: Current learning rate: 0.00117 +2024-11-23 03:08:32.083837: train_loss -0.8243 +2024-11-23 03:08:32.084069: val_loss -0.7741 +2024-11-23 03:08:32.084163: Pseudo dice [0.8661] +2024-11-23 03:08:32.084250: Epoch time: 19.3 s +2024-11-23 03:08:33.147021: +2024-11-23 03:08:33.147246: Epoch 7266 +2024-11-23 03:08:33.147371: Current learning rate: 0.00117 +2024-11-23 03:08:51.589933: train_loss -0.8182 +2024-11-23 03:08:51.590203: val_loss -0.7672 +2024-11-23 03:08:51.590285: Pseudo dice [0.8614] +2024-11-23 03:08:51.590367: Epoch time: 18.44 s +2024-11-23 03:08:52.479901: +2024-11-23 03:08:52.480125: Epoch 7267 +2024-11-23 03:08:52.480239: Current learning rate: 0.00116 +2024-11-23 03:09:09.826407: train_loss -0.8239 +2024-11-23 03:09:09.826659: val_loss -0.7947 +2024-11-23 03:09:09.826849: Pseudo dice [0.8606] +2024-11-23 03:09:09.826960: Epoch time: 17.35 s +2024-11-23 03:09:10.711872: +2024-11-23 03:09:10.712101: Epoch 7268 +2024-11-23 03:09:10.712238: Current learning rate: 0.00116 +2024-11-23 03:09:29.300635: train_loss -0.8285 +2024-11-23 03:09:29.300863: val_loss -0.7944 +2024-11-23 03:09:29.300948: Pseudo dice [0.8532] +2024-11-23 03:09:29.301042: Epoch time: 18.59 s +2024-11-23 03:09:30.187241: +2024-11-23 03:09:30.187465: Epoch 7269 +2024-11-23 03:09:30.187585: Current learning rate: 0.00116 +2024-11-23 03:09:48.718989: train_loss -0.8228 +2024-11-23 03:09:48.719210: val_loss -0.7869 +2024-11-23 03:09:48.719332: Pseudo dice [0.8652] +2024-11-23 03:09:48.719463: Epoch time: 18.53 s +2024-11-23 03:09:49.783995: +2024-11-23 03:09:49.784220: Epoch 7270 +2024-11-23 03:09:49.784340: Current learning rate: 0.00116 +2024-11-23 03:10:07.820430: train_loss -0.8283 +2024-11-23 03:10:07.824799: val_loss -0.7684 +2024-11-23 03:10:07.824954: Pseudo dice [0.8591] +2024-11-23 03:10:07.825049: Epoch time: 18.04 s +2024-11-23 03:10:08.712680: +2024-11-23 03:10:08.712893: Epoch 7271 +2024-11-23 03:10:08.713006: Current learning rate: 0.00116 +2024-11-23 03:10:26.755348: train_loss -0.8265 +2024-11-23 03:10:26.755580: val_loss -0.7734 +2024-11-23 03:10:26.755673: Pseudo dice [0.8705] +2024-11-23 03:10:26.755778: Epoch time: 18.04 s +2024-11-23 03:10:27.645785: +2024-11-23 03:10:27.646003: Epoch 7272 +2024-11-23 03:10:27.646137: Current learning rate: 0.00116 +2024-11-23 03:10:46.218071: train_loss -0.8247 +2024-11-23 03:10:46.218320: val_loss -0.7838 +2024-11-23 03:10:46.218411: Pseudo dice [0.8551] +2024-11-23 03:10:46.218510: Epoch time: 18.57 s +2024-11-23 03:10:47.104193: +2024-11-23 03:10:47.104420: Epoch 7273 +2024-11-23 03:10:47.104538: Current learning rate: 0.00116 +2024-11-23 03:11:05.437125: train_loss -0.8273 +2024-11-23 03:11:05.437343: val_loss -0.7728 +2024-11-23 03:11:05.437429: Pseudo dice [0.8615] +2024-11-23 03:11:05.437525: Epoch time: 18.33 s +2024-11-23 03:11:06.321633: +2024-11-23 03:11:06.321841: Epoch 7274 +2024-11-23 03:11:06.321970: Current learning rate: 0.00115 +2024-11-23 03:11:23.962267: train_loss -0.8268 +2024-11-23 03:11:23.967660: val_loss -0.7868 +2024-11-23 03:11:23.967746: Pseudo dice [0.8663] +2024-11-23 03:11:23.967827: Epoch time: 17.64 s +2024-11-23 03:11:25.069988: +2024-11-23 03:11:25.070213: Epoch 7275 +2024-11-23 03:11:25.070348: Current learning rate: 0.00115 +2024-11-23 03:11:42.543835: train_loss -0.8209 +2024-11-23 03:11:42.544079: val_loss -0.7647 +2024-11-23 03:11:42.544165: Pseudo dice [0.8656] +2024-11-23 03:11:42.544256: Epoch time: 17.47 s +2024-11-23 03:11:43.425422: +2024-11-23 03:11:43.425612: Epoch 7276 +2024-11-23 03:11:43.425724: Current learning rate: 0.00115 +2024-11-23 03:12:02.117042: train_loss -0.8203 +2024-11-23 03:12:02.117279: val_loss -0.789 +2024-11-23 03:12:02.117354: Pseudo dice [0.8712] +2024-11-23 03:12:02.117431: Epoch time: 18.69 s +2024-11-23 03:12:02.990748: +2024-11-23 03:12:02.990953: Epoch 7277 +2024-11-23 03:12:02.991073: Current learning rate: 0.00115 +2024-11-23 03:12:21.535367: train_loss -0.815 +2024-11-23 03:12:21.535568: val_loss -0.7878 +2024-11-23 03:12:21.535656: Pseudo dice [0.8687] +2024-11-23 03:12:21.535738: Epoch time: 18.55 s +2024-11-23 03:12:22.417259: +2024-11-23 03:12:22.417481: Epoch 7278 +2024-11-23 03:12:22.417598: Current learning rate: 0.00115 +2024-11-23 03:12:40.956096: train_loss -0.8227 +2024-11-23 03:12:40.956327: val_loss -0.7979 +2024-11-23 03:12:40.956408: Pseudo dice [0.8603] +2024-11-23 03:12:40.956489: Epoch time: 18.54 s +2024-11-23 03:12:41.843050: +2024-11-23 03:12:41.843275: Epoch 7279 +2024-11-23 03:12:41.843384: Current learning rate: 0.00115 +2024-11-23 03:13:00.056362: train_loss -0.8295 +2024-11-23 03:13:00.056607: val_loss -0.779 +2024-11-23 03:13:00.056687: Pseudo dice [0.8679] +2024-11-23 03:13:00.056775: Epoch time: 18.21 s +2024-11-23 03:13:00.940346: +2024-11-23 03:13:00.940587: Epoch 7280 +2024-11-23 03:13:00.940701: Current learning rate: 0.00115 +2024-11-23 03:13:18.814818: train_loss -0.8287 +2024-11-23 03:13:18.815020: val_loss -0.761 +2024-11-23 03:13:18.815133: Pseudo dice [0.8605] +2024-11-23 03:13:18.815212: Epoch time: 17.88 s +2024-11-23 03:13:19.700444: +2024-11-23 03:13:19.700657: Epoch 7281 +2024-11-23 03:13:19.700798: Current learning rate: 0.00114 +2024-11-23 03:13:38.421597: train_loss -0.8195 +2024-11-23 03:13:38.421806: val_loss -0.795 +2024-11-23 03:13:38.421947: Pseudo dice [0.8654] +2024-11-23 03:13:38.422029: Epoch time: 18.72 s +2024-11-23 03:13:39.306492: +2024-11-23 03:13:39.306700: Epoch 7282 +2024-11-23 03:13:39.306826: Current learning rate: 0.00114 +2024-11-23 03:13:57.168463: train_loss -0.8266 +2024-11-23 03:13:57.168698: val_loss -0.7924 +2024-11-23 03:13:57.168776: Pseudo dice [0.8611] +2024-11-23 03:13:57.168857: Epoch time: 17.86 s +2024-11-23 03:13:58.134725: +2024-11-23 03:13:58.134932: Epoch 7283 +2024-11-23 03:13:58.135068: Current learning rate: 0.00114 +2024-11-23 03:14:16.068768: train_loss -0.8243 +2024-11-23 03:14:16.069012: val_loss -0.7832 +2024-11-23 03:14:16.069106: Pseudo dice [0.8686] +2024-11-23 03:14:16.069196: Epoch time: 17.94 s +2024-11-23 03:14:16.949719: +2024-11-23 03:14:16.949921: Epoch 7284 +2024-11-23 03:14:16.950057: Current learning rate: 0.00114 +2024-11-23 03:14:35.420387: train_loss -0.8274 +2024-11-23 03:14:35.420605: val_loss -0.79 +2024-11-23 03:14:35.420698: Pseudo dice [0.8572] +2024-11-23 03:14:35.420792: Epoch time: 18.47 s +2024-11-23 03:14:36.295252: +2024-11-23 03:14:36.295474: Epoch 7285 +2024-11-23 03:14:36.295587: Current learning rate: 0.00114 +2024-11-23 03:14:55.428542: train_loss -0.8281 +2024-11-23 03:14:55.428762: val_loss -0.7942 +2024-11-23 03:14:55.428838: Pseudo dice [0.8608] +2024-11-23 03:14:55.428920: Epoch time: 19.13 s +2024-11-23 03:14:56.358597: +2024-11-23 03:14:56.358863: Epoch 7286 +2024-11-23 03:14:56.358981: Current learning rate: 0.00114 +2024-11-23 03:15:15.471860: train_loss -0.8277 +2024-11-23 03:15:15.472078: val_loss -0.7963 +2024-11-23 03:15:15.472157: Pseudo dice [0.8702] +2024-11-23 03:15:15.472250: Epoch time: 19.11 s +2024-11-23 03:15:16.470783: +2024-11-23 03:15:16.470991: Epoch 7287 +2024-11-23 03:15:16.471126: Current learning rate: 0.00114 +2024-11-23 03:15:35.249162: train_loss -0.8303 +2024-11-23 03:15:35.249422: val_loss -0.7914 +2024-11-23 03:15:35.249502: Pseudo dice [0.8587] +2024-11-23 03:15:35.255015: Epoch time: 18.78 s +2024-11-23 03:15:36.646145: +2024-11-23 03:15:36.646354: Epoch 7288 +2024-11-23 03:15:36.646472: Current learning rate: 0.00113 +2024-11-23 03:15:54.821408: train_loss -0.8194 +2024-11-23 03:15:54.821634: val_loss -0.7895 +2024-11-23 03:15:54.821711: Pseudo dice [0.8577] +2024-11-23 03:15:54.821912: Epoch time: 18.18 s +2024-11-23 03:15:55.708239: +2024-11-23 03:15:55.708439: Epoch 7289 +2024-11-23 03:15:55.708562: Current learning rate: 0.00113 +2024-11-23 03:16:14.155190: train_loss -0.8304 +2024-11-23 03:16:14.155409: val_loss -0.7754 +2024-11-23 03:16:14.155486: Pseudo dice [0.8614] +2024-11-23 03:16:14.155561: Epoch time: 18.45 s +2024-11-23 03:16:15.037127: +2024-11-23 03:16:15.037331: Epoch 7290 +2024-11-23 03:16:15.037454: Current learning rate: 0.00113 +2024-11-23 03:16:33.953081: train_loss -0.8194 +2024-11-23 03:16:33.953305: val_loss -0.7881 +2024-11-23 03:16:33.953392: Pseudo dice [0.8701] +2024-11-23 03:16:33.953485: Epoch time: 18.92 s +2024-11-23 03:16:34.845673: +2024-11-23 03:16:34.845879: Epoch 7291 +2024-11-23 03:16:34.846006: Current learning rate: 0.00113 +2024-11-23 03:16:53.881912: train_loss -0.8228 +2024-11-23 03:16:53.882181: val_loss -0.793 +2024-11-23 03:16:53.882269: Pseudo dice [0.858] +2024-11-23 03:16:53.882359: Epoch time: 19.04 s +2024-11-23 03:16:54.817690: +2024-11-23 03:16:54.817894: Epoch 7292 +2024-11-23 03:16:54.818022: Current learning rate: 0.00113 +2024-11-23 03:17:12.617134: train_loss -0.8244 +2024-11-23 03:17:12.617345: val_loss -0.785 +2024-11-23 03:17:12.617427: Pseudo dice [0.8547] +2024-11-23 03:17:12.617510: Epoch time: 17.8 s +2024-11-23 03:17:13.517342: +2024-11-23 03:17:13.517567: Epoch 7293 +2024-11-23 03:17:13.517694: Current learning rate: 0.00113 +2024-11-23 03:17:31.889357: train_loss -0.8238 +2024-11-23 03:17:31.889566: val_loss -0.7905 +2024-11-23 03:17:31.889640: Pseudo dice [0.8585] +2024-11-23 03:17:31.889719: Epoch time: 18.37 s +2024-11-23 03:17:32.774906: +2024-11-23 03:17:32.775150: Epoch 7294 +2024-11-23 03:17:32.775265: Current learning rate: 0.00112 +2024-11-23 03:17:50.157310: train_loss -0.8321 +2024-11-23 03:17:50.157553: val_loss -0.7858 +2024-11-23 03:17:50.157633: Pseudo dice [0.8635] +2024-11-23 03:17:50.157719: Epoch time: 17.38 s +2024-11-23 03:17:51.048259: +2024-11-23 03:17:51.048473: Epoch 7295 +2024-11-23 03:17:51.048582: Current learning rate: 0.00112 +2024-11-23 03:18:09.294456: train_loss -0.8261 +2024-11-23 03:18:09.294702: val_loss -0.7922 +2024-11-23 03:18:09.294842: Pseudo dice [0.8686] +2024-11-23 03:18:09.294928: Epoch time: 18.25 s +2024-11-23 03:18:10.183403: +2024-11-23 03:18:10.183617: Epoch 7296 +2024-11-23 03:18:10.183742: Current learning rate: 0.00112 +2024-11-23 03:18:28.430283: train_loss -0.8249 +2024-11-23 03:18:28.430561: val_loss -0.7562 +2024-11-23 03:18:28.430640: Pseudo dice [0.8632] +2024-11-23 03:18:28.430722: Epoch time: 18.25 s +2024-11-23 03:18:29.312777: +2024-11-23 03:18:29.312992: Epoch 7297 +2024-11-23 03:18:29.313110: Current learning rate: 0.00112 +2024-11-23 03:18:46.376528: train_loss -0.8217 +2024-11-23 03:18:46.376728: val_loss -0.7837 +2024-11-23 03:18:46.381967: Pseudo dice [0.8658] +2024-11-23 03:18:46.382165: Epoch time: 17.06 s +2024-11-23 03:18:47.314834: +2024-11-23 03:18:47.315042: Epoch 7298 +2024-11-23 03:18:47.315160: Current learning rate: 0.00112 +2024-11-23 03:19:05.239051: train_loss -0.8208 +2024-11-23 03:19:05.239285: val_loss -0.7917 +2024-11-23 03:19:05.239367: Pseudo dice [0.8589] +2024-11-23 03:19:05.239450: Epoch time: 17.93 s +2024-11-23 03:19:06.104146: +2024-11-23 03:19:06.104340: Epoch 7299 +2024-11-23 03:19:06.104456: Current learning rate: 0.00112 +2024-11-23 03:19:23.749889: train_loss -0.8194 +2024-11-23 03:19:23.750129: val_loss -0.7695 +2024-11-23 03:19:23.750218: Pseudo dice [0.8617] +2024-11-23 03:19:23.750318: Epoch time: 17.65 s +2024-11-23 03:19:24.989144: +2024-11-23 03:19:24.989382: Epoch 7300 +2024-11-23 03:19:24.989512: Current learning rate: 0.00112 +2024-11-23 03:19:44.183988: train_loss -0.8218 +2024-11-23 03:19:44.184200: val_loss -0.7894 +2024-11-23 03:19:44.184282: Pseudo dice [0.8593] +2024-11-23 03:19:44.184358: Epoch time: 19.2 s +2024-11-23 03:19:45.047876: +2024-11-23 03:19:45.048087: Epoch 7301 +2024-11-23 03:19:45.048204: Current learning rate: 0.00111 +2024-11-23 03:20:03.587287: train_loss -0.8276 +2024-11-23 03:20:03.587502: val_loss -0.781 +2024-11-23 03:20:03.587582: Pseudo dice [0.8588] +2024-11-23 03:20:03.587660: Epoch time: 18.54 s +2024-11-23 03:20:04.448752: +2024-11-23 03:20:04.448976: Epoch 7302 +2024-11-23 03:20:04.449090: Current learning rate: 0.00111 +2024-11-23 03:20:22.678377: train_loss -0.8207 +2024-11-23 03:20:22.683769: val_loss -0.7767 +2024-11-23 03:20:22.683947: Pseudo dice [0.86] +2024-11-23 03:20:22.684046: Epoch time: 18.23 s +2024-11-23 03:20:23.654418: +2024-11-23 03:20:23.654642: Epoch 7303 +2024-11-23 03:20:23.654760: Current learning rate: 0.00111 +2024-11-23 03:20:42.143831: train_loss -0.8234 +2024-11-23 03:20:42.144047: val_loss -0.7771 +2024-11-23 03:20:42.144149: Pseudo dice [0.8644] +2024-11-23 03:20:42.144242: Epoch time: 18.49 s +2024-11-23 03:20:43.087018: +2024-11-23 03:20:43.087251: Epoch 7304 +2024-11-23 03:20:43.087372: Current learning rate: 0.00111 +2024-11-23 03:21:01.746260: train_loss -0.8276 +2024-11-23 03:21:01.746470: val_loss -0.7981 +2024-11-23 03:21:01.746546: Pseudo dice [0.8727] +2024-11-23 03:21:01.746623: Epoch time: 18.66 s +2024-11-23 03:21:02.611375: +2024-11-23 03:21:02.611568: Epoch 7305 +2024-11-23 03:21:02.611683: Current learning rate: 0.00111 +2024-11-23 03:21:20.811373: train_loss -0.8287 +2024-11-23 03:21:20.811607: val_loss -0.7918 +2024-11-23 03:21:20.811718: Pseudo dice [0.8534] +2024-11-23 03:21:20.811831: Epoch time: 18.2 s +2024-11-23 03:21:21.692574: +2024-11-23 03:21:21.692776: Epoch 7306 +2024-11-23 03:21:21.692892: Current learning rate: 0.00111 +2024-11-23 03:21:41.524772: train_loss -0.8359 +2024-11-23 03:21:41.525004: val_loss -0.7879 +2024-11-23 03:21:41.525108: Pseudo dice [0.8692] +2024-11-23 03:21:41.525196: Epoch time: 19.83 s +2024-11-23 03:21:42.408226: +2024-11-23 03:21:42.408427: Epoch 7307 +2024-11-23 03:21:42.408545: Current learning rate: 0.00111 +2024-11-23 03:22:01.395369: train_loss -0.8218 +2024-11-23 03:22:01.400717: val_loss -0.7878 +2024-11-23 03:22:01.400887: Pseudo dice [0.864] +2024-11-23 03:22:01.400972: Epoch time: 18.99 s +2024-11-23 03:22:02.450116: +2024-11-23 03:22:02.450341: Epoch 7308 +2024-11-23 03:22:02.450456: Current learning rate: 0.0011 +2024-11-23 03:22:20.799869: train_loss -0.8258 +2024-11-23 03:22:20.800110: val_loss -0.7898 +2024-11-23 03:22:20.800192: Pseudo dice [0.8623] +2024-11-23 03:22:20.800291: Epoch time: 18.35 s +2024-11-23 03:22:21.681601: +2024-11-23 03:22:21.681795: Epoch 7309 +2024-11-23 03:22:21.681910: Current learning rate: 0.0011 +2024-11-23 03:22:40.034305: train_loss -0.8304 +2024-11-23 03:22:40.034514: val_loss -0.7767 +2024-11-23 03:22:40.034595: Pseudo dice [0.8561] +2024-11-23 03:22:40.034672: Epoch time: 18.35 s +2024-11-23 03:22:41.285877: +2024-11-23 03:22:41.286124: Epoch 7310 +2024-11-23 03:22:41.286258: Current learning rate: 0.0011 +2024-11-23 03:22:59.028032: train_loss -0.8258 +2024-11-23 03:22:59.028330: val_loss -0.8088 +2024-11-23 03:22:59.028421: Pseudo dice [0.8659] +2024-11-23 03:22:59.028508: Epoch time: 17.74 s +2024-11-23 03:22:59.904539: +2024-11-23 03:22:59.904763: Epoch 7311 +2024-11-23 03:22:59.904880: Current learning rate: 0.0011 +2024-11-23 03:23:18.554832: train_loss -0.83 +2024-11-23 03:23:18.555041: val_loss -0.7751 +2024-11-23 03:23:18.555119: Pseudo dice [0.8571] +2024-11-23 03:23:18.555282: Epoch time: 18.65 s +2024-11-23 03:23:19.438144: +2024-11-23 03:23:19.438357: Epoch 7312 +2024-11-23 03:23:19.438464: Current learning rate: 0.0011 +2024-11-23 03:23:38.039384: train_loss -0.808 +2024-11-23 03:23:38.041744: val_loss -0.7735 +2024-11-23 03:23:38.041859: Pseudo dice [0.8731] +2024-11-23 03:23:38.041963: Epoch time: 18.6 s +2024-11-23 03:23:38.928039: +2024-11-23 03:23:38.928263: Epoch 7313 +2024-11-23 03:23:38.928394: Current learning rate: 0.0011 +2024-11-23 03:23:57.965429: train_loss -0.819 +2024-11-23 03:23:57.965644: val_loss -0.7828 +2024-11-23 03:23:57.965725: Pseudo dice [0.8691] +2024-11-23 03:23:57.965812: Epoch time: 19.04 s +2024-11-23 03:23:58.854195: +2024-11-23 03:23:58.854409: Epoch 7314 +2024-11-23 03:23:58.854526: Current learning rate: 0.0011 +2024-11-23 03:24:16.568035: train_loss -0.8198 +2024-11-23 03:24:16.568269: val_loss -0.7785 +2024-11-23 03:24:16.568350: Pseudo dice [0.8511] +2024-11-23 03:24:16.568438: Epoch time: 17.71 s +2024-11-23 03:24:17.447982: +2024-11-23 03:24:17.448191: Epoch 7315 +2024-11-23 03:24:17.448323: Current learning rate: 0.00109 +2024-11-23 03:24:37.122833: train_loss -0.8235 +2024-11-23 03:24:37.123068: val_loss -0.7911 +2024-11-23 03:24:37.123148: Pseudo dice [0.8627] +2024-11-23 03:24:37.123227: Epoch time: 19.68 s +2024-11-23 03:24:38.007360: +2024-11-23 03:24:38.007573: Epoch 7316 +2024-11-23 03:24:38.007713: Current learning rate: 0.00109 +2024-11-23 03:24:57.544082: train_loss -0.8238 +2024-11-23 03:24:57.544308: val_loss -0.7859 +2024-11-23 03:24:57.544405: Pseudo dice [0.8673] +2024-11-23 03:24:57.544484: Epoch time: 19.54 s +2024-11-23 03:24:58.425505: +2024-11-23 03:24:58.425733: Epoch 7317 +2024-11-23 03:24:58.425847: Current learning rate: 0.00109 +2024-11-23 03:25:16.969570: train_loss -0.8253 +2024-11-23 03:25:16.969822: val_loss -0.7774 +2024-11-23 03:25:16.969907: Pseudo dice [0.8541] +2024-11-23 03:25:16.969987: Epoch time: 18.54 s +2024-11-23 03:25:17.858963: +2024-11-23 03:25:17.859173: Epoch 7318 +2024-11-23 03:25:17.859288: Current learning rate: 0.00109 +2024-11-23 03:25:36.768055: train_loss -0.8274 +2024-11-23 03:25:36.769841: val_loss -0.7831 +2024-11-23 03:25:36.769950: Pseudo dice [0.8723] +2024-11-23 03:25:36.770052: Epoch time: 18.91 s +2024-11-23 03:25:37.661975: +2024-11-23 03:25:37.662198: Epoch 7319 +2024-11-23 03:25:37.662311: Current learning rate: 0.00109 +2024-11-23 03:25:55.090957: train_loss -0.8296 +2024-11-23 03:25:55.091176: val_loss -0.7737 +2024-11-23 03:25:55.091265: Pseudo dice [0.8626] +2024-11-23 03:25:55.091347: Epoch time: 17.43 s +2024-11-23 03:25:56.026138: +2024-11-23 03:25:56.026346: Epoch 7320 +2024-11-23 03:25:56.026476: Current learning rate: 0.00109 +2024-11-23 03:26:14.105279: train_loss -0.8196 +2024-11-23 03:26:14.105490: val_loss -0.7701 +2024-11-23 03:26:14.105565: Pseudo dice [0.8465] +2024-11-23 03:26:14.105636: Epoch time: 18.08 s +2024-11-23 03:26:15.024549: +2024-11-23 03:26:15.024749: Epoch 7321 +2024-11-23 03:26:15.024877: Current learning rate: 0.00109 +2024-11-23 03:26:34.013958: train_loss -0.8189 +2024-11-23 03:26:34.014197: val_loss -0.7969 +2024-11-23 03:26:34.014284: Pseudo dice [0.8699] +2024-11-23 03:26:34.014372: Epoch time: 18.99 s +2024-11-23 03:26:35.327746: +2024-11-23 03:26:35.327952: Epoch 7322 +2024-11-23 03:26:35.328068: Current learning rate: 0.00108 +2024-11-23 03:26:54.120179: train_loss -0.8292 +2024-11-23 03:26:54.120409: val_loss -0.7979 +2024-11-23 03:26:54.120511: Pseudo dice [0.867] +2024-11-23 03:26:54.120589: Epoch time: 18.79 s +2024-11-23 03:26:55.159881: +2024-11-23 03:26:55.160101: Epoch 7323 +2024-11-23 03:26:55.160237: Current learning rate: 0.00108 +2024-11-23 03:27:14.747662: train_loss -0.8179 +2024-11-23 03:27:14.747889: val_loss -0.7811 +2024-11-23 03:27:14.747974: Pseudo dice [0.8664] +2024-11-23 03:27:14.748068: Epoch time: 19.59 s +2024-11-23 03:27:15.639287: +2024-11-23 03:27:15.639506: Epoch 7324 +2024-11-23 03:27:15.639624: Current learning rate: 0.00108 +2024-11-23 03:27:34.036977: train_loss -0.8136 +2024-11-23 03:27:34.037209: val_loss -0.7769 +2024-11-23 03:27:34.037293: Pseudo dice [0.8601] +2024-11-23 03:27:34.037375: Epoch time: 18.4 s +2024-11-23 03:27:34.945032: +2024-11-23 03:27:34.945266: Epoch 7325 +2024-11-23 03:27:34.945379: Current learning rate: 0.00108 +2024-11-23 03:27:55.755468: train_loss -0.8113 +2024-11-23 03:27:55.755697: val_loss -0.7626 +2024-11-23 03:27:55.755775: Pseudo dice [0.8482] +2024-11-23 03:27:55.755886: Epoch time: 20.81 s +2024-11-23 03:27:56.676269: +2024-11-23 03:27:56.676494: Epoch 7326 +2024-11-23 03:27:56.676608: Current learning rate: 0.00108 +2024-11-23 03:28:15.155678: train_loss -0.8214 +2024-11-23 03:28:15.155894: val_loss -0.7775 +2024-11-23 03:28:15.155973: Pseudo dice [0.8609] +2024-11-23 03:28:15.156047: Epoch time: 18.48 s +2024-11-23 03:28:16.039871: +2024-11-23 03:28:16.040093: Epoch 7327 +2024-11-23 03:28:16.040233: Current learning rate: 0.00108 +2024-11-23 03:28:34.257386: train_loss -0.8261 +2024-11-23 03:28:34.257631: val_loss -0.786 +2024-11-23 03:28:34.257729: Pseudo dice [0.8709] +2024-11-23 03:28:34.257824: Epoch time: 18.21 s +2024-11-23 03:28:35.150166: +2024-11-23 03:28:35.150402: Epoch 7328 +2024-11-23 03:28:35.150538: Current learning rate: 0.00108 +2024-11-23 03:28:54.050269: train_loss -0.8141 +2024-11-23 03:28:54.050512: val_loss -0.7936 +2024-11-23 03:28:54.050600: Pseudo dice [0.8549] +2024-11-23 03:28:54.050693: Epoch time: 18.9 s +2024-11-23 03:28:55.054226: +2024-11-23 03:28:55.054453: Epoch 7329 +2024-11-23 03:28:55.054580: Current learning rate: 0.00107 +2024-11-23 03:29:12.842595: train_loss -0.8146 +2024-11-23 03:29:12.842816: val_loss -0.7555 +2024-11-23 03:29:12.842896: Pseudo dice [0.8522] +2024-11-23 03:29:12.843037: Epoch time: 17.79 s +2024-11-23 03:29:13.719538: +2024-11-23 03:29:13.719779: Epoch 7330 +2024-11-23 03:29:13.719898: Current learning rate: 0.00107 +2024-11-23 03:29:33.493270: train_loss -0.8204 +2024-11-23 03:29:33.493476: val_loss -0.7896 +2024-11-23 03:29:33.493551: Pseudo dice [0.8669] +2024-11-23 03:29:33.493628: Epoch time: 19.77 s +2024-11-23 03:29:34.402175: +2024-11-23 03:29:34.402399: Epoch 7331 +2024-11-23 03:29:34.402532: Current learning rate: 0.00107 +2024-11-23 03:29:51.766027: train_loss -0.8196 +2024-11-23 03:29:51.766257: val_loss -0.7935 +2024-11-23 03:29:51.766340: Pseudo dice [0.8559] +2024-11-23 03:29:51.766427: Epoch time: 17.36 s +2024-11-23 03:29:52.643880: +2024-11-23 03:29:52.644086: Epoch 7332 +2024-11-23 03:29:52.644201: Current learning rate: 0.00107 +2024-11-23 03:30:11.620744: train_loss -0.8242 +2024-11-23 03:30:11.621040: val_loss -0.7962 +2024-11-23 03:30:11.621126: Pseudo dice [0.8582] +2024-11-23 03:30:11.621211: Epoch time: 18.98 s +2024-11-23 03:30:12.891444: +2024-11-23 03:30:12.891651: Epoch 7333 +2024-11-23 03:30:12.891771: Current learning rate: 0.00107 +2024-11-23 03:30:31.322450: train_loss -0.8255 +2024-11-23 03:30:31.322688: val_loss -0.7943 +2024-11-23 03:30:31.322782: Pseudo dice [0.8611] +2024-11-23 03:30:31.322862: Epoch time: 18.43 s +2024-11-23 03:30:32.201376: +2024-11-23 03:30:32.201578: Epoch 7334 +2024-11-23 03:30:32.201694: Current learning rate: 0.00107 +2024-11-23 03:30:50.591756: train_loss -0.8256 +2024-11-23 03:30:50.591962: val_loss -0.7877 +2024-11-23 03:30:50.592042: Pseudo dice [0.8674] +2024-11-23 03:30:50.592123: Epoch time: 18.39 s +2024-11-23 03:30:51.469441: +2024-11-23 03:30:51.469661: Epoch 7335 +2024-11-23 03:30:51.469774: Current learning rate: 0.00107 +2024-11-23 03:31:10.172611: train_loss -0.826 +2024-11-23 03:31:10.172822: val_loss -0.7661 +2024-11-23 03:31:10.172916: Pseudo dice [0.8598] +2024-11-23 03:31:10.173054: Epoch time: 18.7 s +2024-11-23 03:31:11.059113: +2024-11-23 03:31:11.059358: Epoch 7336 +2024-11-23 03:31:11.059498: Current learning rate: 0.00106 +2024-11-23 03:31:30.507507: train_loss -0.8178 +2024-11-23 03:31:30.507760: val_loss -0.7937 +2024-11-23 03:31:30.507839: Pseudo dice [0.8699] +2024-11-23 03:31:30.507930: Epoch time: 19.45 s +2024-11-23 03:31:31.434582: +2024-11-23 03:31:31.434797: Epoch 7337 +2024-11-23 03:31:31.434916: Current learning rate: 0.00106 +2024-11-23 03:31:51.366025: train_loss -0.8168 +2024-11-23 03:31:51.366241: val_loss -0.787 +2024-11-23 03:31:51.366327: Pseudo dice [0.8544] +2024-11-23 03:31:51.366651: Epoch time: 19.93 s +2024-11-23 03:31:52.254323: +2024-11-23 03:31:52.254525: Epoch 7338 +2024-11-23 03:31:52.254640: Current learning rate: 0.00106 +2024-11-23 03:32:11.109649: train_loss -0.8168 +2024-11-23 03:32:11.109922: val_loss -0.7777 +2024-11-23 03:32:11.110007: Pseudo dice [0.8598] +2024-11-23 03:32:11.110091: Epoch time: 18.86 s +2024-11-23 03:32:11.992602: +2024-11-23 03:32:11.992834: Epoch 7339 +2024-11-23 03:32:11.992946: Current learning rate: 0.00106 +2024-11-23 03:32:29.933558: train_loss -0.827 +2024-11-23 03:32:29.933800: val_loss -0.789 +2024-11-23 03:32:29.933892: Pseudo dice [0.8571] +2024-11-23 03:32:29.934063: Epoch time: 17.94 s +2024-11-23 03:32:30.889812: +2024-11-23 03:32:30.890020: Epoch 7340 +2024-11-23 03:32:30.890141: Current learning rate: 0.00106 +2024-11-23 03:32:48.924689: train_loss -0.8179 +2024-11-23 03:32:48.924943: val_loss -0.7792 +2024-11-23 03:32:48.925041: Pseudo dice [0.8626] +2024-11-23 03:32:48.925153: Epoch time: 18.04 s +2024-11-23 03:32:49.810934: +2024-11-23 03:32:49.811163: Epoch 7341 +2024-11-23 03:32:49.811289: Current learning rate: 0.00106 +2024-11-23 03:33:09.866297: train_loss -0.8273 +2024-11-23 03:33:09.866551: val_loss -0.7937 +2024-11-23 03:33:09.866639: Pseudo dice [0.8604] +2024-11-23 03:33:09.866787: Epoch time: 20.06 s +2024-11-23 03:33:10.751336: +2024-11-23 03:33:10.751574: Epoch 7342 +2024-11-23 03:33:10.751703: Current learning rate: 0.00106 +2024-11-23 03:33:29.784590: train_loss -0.8245 +2024-11-23 03:33:29.784817: val_loss -0.7829 +2024-11-23 03:33:29.784918: Pseudo dice [0.8623] +2024-11-23 03:33:29.784997: Epoch time: 19.03 s +2024-11-23 03:33:30.716961: +2024-11-23 03:33:30.717166: Epoch 7343 +2024-11-23 03:33:30.717284: Current learning rate: 0.00105 +2024-11-23 03:33:49.761870: train_loss -0.8338 +2024-11-23 03:33:49.762094: val_loss -0.7796 +2024-11-23 03:33:49.762185: Pseudo dice [0.8708] +2024-11-23 03:33:49.762271: Epoch time: 19.05 s +2024-11-23 03:33:50.652752: +2024-11-23 03:33:50.652992: Epoch 7344 +2024-11-23 03:33:50.653160: Current learning rate: 0.00105 +2024-11-23 03:34:09.729213: train_loss -0.8318 +2024-11-23 03:34:09.729426: val_loss -0.8003 +2024-11-23 03:34:09.729523: Pseudo dice [0.8601] +2024-11-23 03:34:09.729638: Epoch time: 19.08 s +2024-11-23 03:34:11.017690: +2024-11-23 03:34:11.017900: Epoch 7345 +2024-11-23 03:34:11.018016: Current learning rate: 0.00105 +2024-11-23 03:34:28.793941: train_loss -0.8283 +2024-11-23 03:34:28.794169: val_loss -0.7844 +2024-11-23 03:34:28.794248: Pseudo dice [0.8521] +2024-11-23 03:34:28.794327: Epoch time: 17.78 s +2024-11-23 03:34:29.692095: +2024-11-23 03:34:29.692343: Epoch 7346 +2024-11-23 03:34:29.692478: Current learning rate: 0.00105 +2024-11-23 03:34:47.632377: train_loss -0.8203 +2024-11-23 03:34:47.632599: val_loss -0.7539 +2024-11-23 03:34:47.632692: Pseudo dice [0.8478] +2024-11-23 03:34:47.632787: Epoch time: 17.94 s +2024-11-23 03:34:48.520567: +2024-11-23 03:34:48.520776: Epoch 7347 +2024-11-23 03:34:48.520886: Current learning rate: 0.00105 +2024-11-23 03:35:07.448936: train_loss -0.821 +2024-11-23 03:35:07.449187: val_loss -0.7768 +2024-11-23 03:35:07.449274: Pseudo dice [0.8614] +2024-11-23 03:35:07.449356: Epoch time: 18.93 s +2024-11-23 03:35:08.331123: +2024-11-23 03:35:08.331330: Epoch 7348 +2024-11-23 03:35:08.331448: Current learning rate: 0.00105 +2024-11-23 03:35:26.977485: train_loss -0.8245 +2024-11-23 03:35:26.977699: val_loss -0.8052 +2024-11-23 03:35:26.977771: Pseudo dice [0.8765] +2024-11-23 03:35:26.977848: Epoch time: 18.65 s +2024-11-23 03:35:27.866517: +2024-11-23 03:35:27.866745: Epoch 7349 +2024-11-23 03:35:27.866858: Current learning rate: 0.00105 +2024-11-23 03:35:45.296469: train_loss -0.8259 +2024-11-23 03:35:45.296690: val_loss -0.7868 +2024-11-23 03:35:45.296779: Pseudo dice [0.864] +2024-11-23 03:35:45.296856: Epoch time: 17.43 s +2024-11-23 03:35:46.524658: +2024-11-23 03:35:46.524872: Epoch 7350 +2024-11-23 03:35:46.524991: Current learning rate: 0.00104 +2024-11-23 03:36:05.068499: train_loss -0.8251 +2024-11-23 03:36:05.068715: val_loss -0.7937 +2024-11-23 03:36:05.068794: Pseudo dice [0.864] +2024-11-23 03:36:05.068887: Epoch time: 18.54 s +2024-11-23 03:36:05.948291: +2024-11-23 03:36:05.948502: Epoch 7351 +2024-11-23 03:36:05.948624: Current learning rate: 0.00104 +2024-11-23 03:36:23.310811: train_loss -0.8279 +2024-11-23 03:36:23.311064: val_loss -0.7626 +2024-11-23 03:36:23.311143: Pseudo dice [0.8493] +2024-11-23 03:36:23.311260: Epoch time: 17.36 s +2024-11-23 03:36:24.198148: +2024-11-23 03:36:24.198358: Epoch 7352 +2024-11-23 03:36:24.198469: Current learning rate: 0.00104 +2024-11-23 03:36:42.416742: train_loss -0.8184 +2024-11-23 03:36:42.416959: val_loss -0.7749 +2024-11-23 03:36:42.417048: Pseudo dice [0.8568] +2024-11-23 03:36:42.417190: Epoch time: 18.22 s +2024-11-23 03:36:43.298897: +2024-11-23 03:36:43.299127: Epoch 7353 +2024-11-23 03:36:43.299240: Current learning rate: 0.00104 +2024-11-23 03:37:01.573310: train_loss -0.8207 +2024-11-23 03:37:01.573518: val_loss -0.783 +2024-11-23 03:37:01.573601: Pseudo dice [0.8584] +2024-11-23 03:37:01.573688: Epoch time: 18.28 s +2024-11-23 03:37:02.459846: +2024-11-23 03:37:02.460076: Epoch 7354 +2024-11-23 03:37:02.460195: Current learning rate: 0.00104 +2024-11-23 03:37:21.391174: train_loss -0.8293 +2024-11-23 03:37:21.391388: val_loss -0.7852 +2024-11-23 03:37:21.393664: Pseudo dice [0.8606] +2024-11-23 03:37:21.393819: Epoch time: 18.93 s +2024-11-23 03:37:22.279260: +2024-11-23 03:37:22.279467: Epoch 7355 +2024-11-23 03:37:22.279588: Current learning rate: 0.00104 +2024-11-23 03:37:39.285032: train_loss -0.8298 +2024-11-23 03:37:39.285288: val_loss -0.7889 +2024-11-23 03:37:39.285371: Pseudo dice [0.8714] +2024-11-23 03:37:39.285470: Epoch time: 17.01 s +2024-11-23 03:37:40.160697: +2024-11-23 03:37:40.160904: Epoch 7356 +2024-11-23 03:37:40.161043: Current learning rate: 0.00104 +2024-11-23 03:37:58.469469: train_loss -0.82 +2024-11-23 03:37:58.469724: val_loss -0.7943 +2024-11-23 03:37:58.469808: Pseudo dice [0.8543] +2024-11-23 03:37:58.469899: Epoch time: 18.31 s +2024-11-23 03:37:59.353977: +2024-11-23 03:37:59.354205: Epoch 7357 +2024-11-23 03:37:59.354325: Current learning rate: 0.00103 +2024-11-23 03:38:17.676880: train_loss -0.8259 +2024-11-23 03:38:17.677101: val_loss -0.7738 +2024-11-23 03:38:17.677188: Pseudo dice [0.8524] +2024-11-23 03:38:17.677274: Epoch time: 18.32 s +2024-11-23 03:38:18.555104: +2024-11-23 03:38:18.555351: Epoch 7358 +2024-11-23 03:38:18.555475: Current learning rate: 0.00103 +2024-11-23 03:38:37.180533: train_loss -0.819 +2024-11-23 03:38:37.180757: val_loss -0.793 +2024-11-23 03:38:37.180850: Pseudo dice [0.8622] +2024-11-23 03:38:37.180932: Epoch time: 18.63 s +2024-11-23 03:38:38.068937: +2024-11-23 03:38:38.069208: Epoch 7359 +2024-11-23 03:38:38.069376: Current learning rate: 0.00103 +2024-11-23 03:38:56.706709: train_loss -0.8275 +2024-11-23 03:38:56.707005: val_loss -0.7757 +2024-11-23 03:38:56.707097: Pseudo dice [0.865] +2024-11-23 03:38:56.707177: Epoch time: 18.64 s +2024-11-23 03:38:57.616520: +2024-11-23 03:38:57.616740: Epoch 7360 +2024-11-23 03:38:57.616860: Current learning rate: 0.00103 +2024-11-23 03:39:17.398471: train_loss -0.8295 +2024-11-23 03:39:17.398709: val_loss -0.7901 +2024-11-23 03:39:17.401016: Pseudo dice [0.8704] +2024-11-23 03:39:17.401119: Epoch time: 19.78 s +2024-11-23 03:39:18.305055: +2024-11-23 03:39:18.305297: Epoch 7361 +2024-11-23 03:39:18.305414: Current learning rate: 0.00103 +2024-11-23 03:39:36.673122: train_loss -0.8244 +2024-11-23 03:39:36.673323: val_loss -0.7783 +2024-11-23 03:39:36.673404: Pseudo dice [0.8593] +2024-11-23 03:39:36.673486: Epoch time: 18.37 s +2024-11-23 03:39:37.555508: +2024-11-23 03:39:37.555734: Epoch 7362 +2024-11-23 03:39:37.555852: Current learning rate: 0.00103 +2024-11-23 03:39:56.098185: train_loss -0.822 +2024-11-23 03:39:56.100569: val_loss -0.7843 +2024-11-23 03:39:56.100689: Pseudo dice [0.8489] +2024-11-23 03:39:56.100779: Epoch time: 18.54 s +2024-11-23 03:39:56.989489: +2024-11-23 03:39:56.989708: Epoch 7363 +2024-11-23 03:39:56.989826: Current learning rate: 0.00103 +2024-11-23 03:40:15.816773: train_loss -0.8216 +2024-11-23 03:40:15.816986: val_loss -0.7902 +2024-11-23 03:40:15.817075: Pseudo dice [0.8551] +2024-11-23 03:40:15.822787: Epoch time: 18.83 s +2024-11-23 03:40:16.905930: +2024-11-23 03:40:16.906152: Epoch 7364 +2024-11-23 03:40:16.906295: Current learning rate: 0.00102 +2024-11-23 03:40:35.740701: train_loss -0.8204 +2024-11-23 03:40:35.740915: val_loss -0.7998 +2024-11-23 03:40:35.740995: Pseudo dice [0.8684] +2024-11-23 03:40:35.741096: Epoch time: 18.84 s +2024-11-23 03:40:36.620188: +2024-11-23 03:40:36.620410: Epoch 7365 +2024-11-23 03:40:36.620525: Current learning rate: 0.00102 +2024-11-23 03:40:56.416046: train_loss -0.8232 +2024-11-23 03:40:56.416277: val_loss -0.7706 +2024-11-23 03:40:56.416370: Pseudo dice [0.8722] +2024-11-23 03:40:56.416459: Epoch time: 19.8 s +2024-11-23 03:40:57.296181: +2024-11-23 03:40:57.296390: Epoch 7366 +2024-11-23 03:40:57.296505: Current learning rate: 0.00102 +2024-11-23 03:41:16.267575: train_loss -0.8211 +2024-11-23 03:41:16.267827: val_loss -0.7847 +2024-11-23 03:41:16.267906: Pseudo dice [0.8655] +2024-11-23 03:41:16.273275: Epoch time: 18.97 s +2024-11-23 03:41:17.189038: +2024-11-23 03:41:17.189261: Epoch 7367 +2024-11-23 03:41:17.189389: Current learning rate: 0.00102 +2024-11-23 03:41:35.775953: train_loss -0.8307 +2024-11-23 03:41:35.776223: val_loss -0.7826 +2024-11-23 03:41:35.776304: Pseudo dice [0.8579] +2024-11-23 03:41:35.776378: Epoch time: 18.59 s +2024-11-23 03:41:37.061810: +2024-11-23 03:41:37.062015: Epoch 7368 +2024-11-23 03:41:37.062135: Current learning rate: 0.00102 +2024-11-23 03:41:56.515993: train_loss -0.8229 +2024-11-23 03:41:56.518427: val_loss -0.7888 +2024-11-23 03:41:56.518519: Pseudo dice [0.8651] +2024-11-23 03:41:56.518606: Epoch time: 19.46 s +2024-11-23 03:41:57.418624: +2024-11-23 03:41:57.418853: Epoch 7369 +2024-11-23 03:41:57.418973: Current learning rate: 0.00102 +2024-11-23 03:42:15.336431: train_loss -0.8242 +2024-11-23 03:42:15.336655: val_loss -0.7967 +2024-11-23 03:42:15.336737: Pseudo dice [0.8702] +2024-11-23 03:42:15.336829: Epoch time: 17.92 s +2024-11-23 03:42:16.222034: +2024-11-23 03:42:16.222260: Epoch 7370 +2024-11-23 03:42:16.222394: Current learning rate: 0.00102 +2024-11-23 03:42:35.476498: train_loss -0.8306 +2024-11-23 03:42:35.476807: val_loss -0.7669 +2024-11-23 03:42:35.476894: Pseudo dice [0.8823] +2024-11-23 03:42:35.476981: Epoch time: 19.26 s +2024-11-23 03:42:36.366000: +2024-11-23 03:42:36.366250: Epoch 7371 +2024-11-23 03:42:36.366375: Current learning rate: 0.00101 +2024-11-23 03:42:54.095638: train_loss -0.8333 +2024-11-23 03:42:54.095850: val_loss -0.7764 +2024-11-23 03:42:54.095936: Pseudo dice [0.8609] +2024-11-23 03:42:54.099036: Epoch time: 17.73 s +2024-11-23 03:42:54.990617: +2024-11-23 03:42:54.990853: Epoch 7372 +2024-11-23 03:42:54.990991: Current learning rate: 0.00101 +2024-11-23 03:43:13.409112: train_loss -0.8302 +2024-11-23 03:43:13.409346: val_loss -0.789 +2024-11-23 03:43:13.409483: Pseudo dice [0.8681] +2024-11-23 03:43:13.424284: Epoch time: 18.42 s +2024-11-23 03:43:14.329103: +2024-11-23 03:43:14.329314: Epoch 7373 +2024-11-23 03:43:14.329437: Current learning rate: 0.00101 +2024-11-23 03:43:32.472844: train_loss -0.8213 +2024-11-23 03:43:32.473067: val_loss -0.7845 +2024-11-23 03:43:32.473157: Pseudo dice [0.863] +2024-11-23 03:43:32.473255: Epoch time: 18.14 s +2024-11-23 03:43:33.358120: +2024-11-23 03:43:33.358367: Epoch 7374 +2024-11-23 03:43:33.358491: Current learning rate: 0.00101 +2024-11-23 03:43:52.685568: train_loss -0.8246 +2024-11-23 03:43:52.685812: val_loss -0.7875 +2024-11-23 03:43:52.685904: Pseudo dice [0.8594] +2024-11-23 03:43:52.685987: Epoch time: 19.33 s +2024-11-23 03:43:53.574448: +2024-11-23 03:43:53.574730: Epoch 7375 +2024-11-23 03:43:53.574846: Current learning rate: 0.00101 +2024-11-23 03:44:10.965101: train_loss -0.8281 +2024-11-23 03:44:10.965333: val_loss -0.786 +2024-11-23 03:44:10.965419: Pseudo dice [0.875] +2024-11-23 03:44:10.965516: Epoch time: 17.39 s +2024-11-23 03:44:11.900254: +2024-11-23 03:44:11.900466: Epoch 7376 +2024-11-23 03:44:11.900580: Current learning rate: 0.00101 +2024-11-23 03:44:29.415836: train_loss -0.8252 +2024-11-23 03:44:29.416051: val_loss -0.7972 +2024-11-23 03:44:29.416134: Pseudo dice [0.8634] +2024-11-23 03:44:29.417604: Epoch time: 17.52 s +2024-11-23 03:44:30.349339: +2024-11-23 03:44:30.349574: Epoch 7377 +2024-11-23 03:44:30.349705: Current learning rate: 0.00101 +2024-11-23 03:44:48.703928: train_loss -0.8216 +2024-11-23 03:44:48.704163: val_loss -0.7423 +2024-11-23 03:44:48.704251: Pseudo dice [0.8597] +2024-11-23 03:44:48.704346: Epoch time: 18.36 s +2024-11-23 03:44:49.593500: +2024-11-23 03:44:49.593735: Epoch 7378 +2024-11-23 03:44:49.593865: Current learning rate: 0.001 +2024-11-23 03:45:08.629023: train_loss -0.8259 +2024-11-23 03:45:08.629318: val_loss -0.8067 +2024-11-23 03:45:08.629402: Pseudo dice [0.8578] +2024-11-23 03:45:08.629487: Epoch time: 19.04 s +2024-11-23 03:45:09.940867: +2024-11-23 03:45:09.941095: Epoch 7379 +2024-11-23 03:45:09.941213: Current learning rate: 0.001 +2024-11-23 03:45:27.487121: train_loss -0.8211 +2024-11-23 03:45:27.487348: val_loss -0.7747 +2024-11-23 03:45:27.487428: Pseudo dice [0.8647] +2024-11-23 03:45:27.487509: Epoch time: 17.55 s +2024-11-23 03:45:28.367237: +2024-11-23 03:45:28.367446: Epoch 7380 +2024-11-23 03:45:28.367557: Current learning rate: 0.001 +2024-11-23 03:45:45.854776: train_loss -0.8187 +2024-11-23 03:45:45.854999: val_loss -0.767 +2024-11-23 03:45:45.855086: Pseudo dice [0.8673] +2024-11-23 03:45:45.855160: Epoch time: 17.49 s +2024-11-23 03:45:46.735744: +2024-11-23 03:45:46.735975: Epoch 7381 +2024-11-23 03:45:46.736113: Current learning rate: 0.001 +2024-11-23 03:46:04.476196: train_loss -0.8256 +2024-11-23 03:46:04.476434: val_loss -0.7929 +2024-11-23 03:46:04.480852: Pseudo dice [0.8561] +2024-11-23 03:46:04.481011: Epoch time: 17.74 s +2024-11-23 03:46:05.542529: +2024-11-23 03:46:05.542758: Epoch 7382 +2024-11-23 03:46:05.542877: Current learning rate: 0.001 +2024-11-23 03:46:23.850769: train_loss -0.8324 +2024-11-23 03:46:23.851009: val_loss -0.8122 +2024-11-23 03:46:23.851094: Pseudo dice [0.8742] +2024-11-23 03:46:23.851171: Epoch time: 18.31 s +2024-11-23 03:46:24.747864: +2024-11-23 03:46:24.748074: Epoch 7383 +2024-11-23 03:46:24.748201: Current learning rate: 0.001 +2024-11-23 03:46:43.084167: train_loss -0.8276 +2024-11-23 03:46:43.084376: val_loss -0.7944 +2024-11-23 03:46:43.084461: Pseudo dice [0.8671] +2024-11-23 03:46:43.086713: Epoch time: 18.34 s +2024-11-23 03:46:43.987343: +2024-11-23 03:46:43.987559: Epoch 7384 +2024-11-23 03:46:43.987673: Current learning rate: 0.001 +2024-11-23 03:47:02.653163: train_loss -0.8219 +2024-11-23 03:47:02.653369: val_loss -0.7374 +2024-11-23 03:47:02.653447: Pseudo dice [0.8509] +2024-11-23 03:47:02.653529: Epoch time: 18.67 s +2024-11-23 03:47:03.539139: +2024-11-23 03:47:03.539360: Epoch 7385 +2024-11-23 03:47:03.539480: Current learning rate: 0.00099 +2024-11-23 03:47:21.367205: train_loss -0.834 +2024-11-23 03:47:21.367503: val_loss -0.7909 +2024-11-23 03:47:21.367599: Pseudo dice [0.8484] +2024-11-23 03:47:21.367706: Epoch time: 17.83 s +2024-11-23 03:47:22.257687: +2024-11-23 03:47:22.257904: Epoch 7386 +2024-11-23 03:47:22.258020: Current learning rate: 0.00099 +2024-11-23 03:47:41.098129: train_loss -0.8255 +2024-11-23 03:47:41.098360: val_loss -0.7963 +2024-11-23 03:47:41.098499: Pseudo dice [0.8653] +2024-11-23 03:47:41.098579: Epoch time: 18.84 s +2024-11-23 03:47:41.978185: +2024-11-23 03:47:41.978389: Epoch 7387 +2024-11-23 03:47:41.978543: Current learning rate: 0.00099 +2024-11-23 03:48:02.303908: train_loss -0.822 +2024-11-23 03:48:02.304204: val_loss -0.7664 +2024-11-23 03:48:02.304282: Pseudo dice [0.8608] +2024-11-23 03:48:02.304359: Epoch time: 20.33 s +2024-11-23 03:48:03.358036: +2024-11-23 03:48:03.358259: Epoch 7388 +2024-11-23 03:48:03.358402: Current learning rate: 0.00099 +2024-11-23 03:48:22.266901: train_loss -0.8319 +2024-11-23 03:48:22.267119: val_loss -0.781 +2024-11-23 03:48:22.267202: Pseudo dice [0.865] +2024-11-23 03:48:22.267281: Epoch time: 18.91 s +2024-11-23 03:48:23.155911: +2024-11-23 03:48:23.156123: Epoch 7389 +2024-11-23 03:48:23.156256: Current learning rate: 0.00099 +2024-11-23 03:48:42.102217: train_loss -0.8275 +2024-11-23 03:48:42.102464: val_loss -0.7684 +2024-11-23 03:48:42.102775: Pseudo dice [0.8516] +2024-11-23 03:48:42.102886: Epoch time: 18.95 s +2024-11-23 03:48:43.092001: +2024-11-23 03:48:43.092218: Epoch 7390 +2024-11-23 03:48:43.092343: Current learning rate: 0.00099 +2024-11-23 03:49:00.110379: train_loss -0.8307 +2024-11-23 03:49:00.110591: val_loss -0.7686 +2024-11-23 03:49:00.110680: Pseudo dice [0.8625] +2024-11-23 03:49:00.110760: Epoch time: 17.02 s +2024-11-23 03:49:01.386177: +2024-11-23 03:49:01.386397: Epoch 7391 +2024-11-23 03:49:01.386516: Current learning rate: 0.00098 +2024-11-23 03:49:19.837393: train_loss -0.8322 +2024-11-23 03:49:19.837647: val_loss -0.7762 +2024-11-23 03:49:19.837748: Pseudo dice [0.8516] +2024-11-23 03:49:19.837842: Epoch time: 18.45 s +2024-11-23 03:49:20.831913: +2024-11-23 03:49:20.832156: Epoch 7392 +2024-11-23 03:49:20.832273: Current learning rate: 0.00098 +2024-11-23 03:49:38.495595: train_loss -0.8325 +2024-11-23 03:49:38.495836: val_loss -0.807 +2024-11-23 03:49:38.495930: Pseudo dice [0.8673] +2024-11-23 03:49:38.496019: Epoch time: 17.66 s +2024-11-23 03:49:39.386862: +2024-11-23 03:49:39.387120: Epoch 7393 +2024-11-23 03:49:39.387239: Current learning rate: 0.00098 +2024-11-23 03:49:56.827762: train_loss -0.835 +2024-11-23 03:49:56.827988: val_loss -0.7856 +2024-11-23 03:49:56.828085: Pseudo dice [0.8791] +2024-11-23 03:49:56.828176: Epoch time: 17.44 s +2024-11-23 03:49:57.706547: +2024-11-23 03:49:57.706767: Epoch 7394 +2024-11-23 03:49:57.706887: Current learning rate: 0.00098 +2024-11-23 03:50:15.713510: train_loss -0.8342 +2024-11-23 03:50:15.713718: val_loss -0.7781 +2024-11-23 03:50:15.713801: Pseudo dice [0.8617] +2024-11-23 03:50:15.713883: Epoch time: 18.01 s +2024-11-23 03:50:16.599923: +2024-11-23 03:50:16.600156: Epoch 7395 +2024-11-23 03:50:16.600280: Current learning rate: 0.00098 +2024-11-23 03:50:35.274320: train_loss -0.8301 +2024-11-23 03:50:35.274529: val_loss -0.7787 +2024-11-23 03:50:35.274607: Pseudo dice [0.8796] +2024-11-23 03:50:35.274685: Epoch time: 18.68 s +2024-11-23 03:50:36.163291: +2024-11-23 03:50:36.163513: Epoch 7396 +2024-11-23 03:50:36.163629: Current learning rate: 0.00098 +2024-11-23 03:50:53.842088: train_loss -0.8329 +2024-11-23 03:50:53.842409: val_loss -0.8116 +2024-11-23 03:50:53.842501: Pseudo dice [0.856] +2024-11-23 03:50:53.842607: Epoch time: 17.68 s +2024-11-23 03:50:54.833533: +2024-11-23 03:50:54.833750: Epoch 7397 +2024-11-23 03:50:54.833864: Current learning rate: 0.00098 +2024-11-23 03:51:13.216147: train_loss -0.8249 +2024-11-23 03:51:13.219047: val_loss -0.785 +2024-11-23 03:51:13.219158: Pseudo dice [0.8605] +2024-11-23 03:51:13.219244: Epoch time: 18.38 s +2024-11-23 03:51:14.199930: +2024-11-23 03:51:14.200151: Epoch 7398 +2024-11-23 03:51:14.200264: Current learning rate: 0.00097 +2024-11-23 03:51:32.999398: train_loss -0.823 +2024-11-23 03:51:32.999631: val_loss -0.7878 +2024-11-23 03:51:32.999709: Pseudo dice [0.8586] +2024-11-23 03:51:32.999789: Epoch time: 18.8 s +2024-11-23 03:51:33.914180: +2024-11-23 03:51:33.914388: Epoch 7399 +2024-11-23 03:51:33.914503: Current learning rate: 0.00097 +2024-11-23 03:51:52.858333: train_loss -0.83 +2024-11-23 03:51:52.858697: val_loss -0.7853 +2024-11-23 03:51:52.858803: Pseudo dice [0.8622] +2024-11-23 03:51:52.858891: Epoch time: 18.94 s +2024-11-23 03:51:54.078676: +2024-11-23 03:51:54.078889: Epoch 7400 +2024-11-23 03:51:54.079010: Current learning rate: 0.00097 +2024-11-23 03:52:11.513733: train_loss -0.8298 +2024-11-23 03:52:11.516184: val_loss -0.7805 +2024-11-23 03:52:11.516302: Pseudo dice [0.8608] +2024-11-23 03:52:11.516411: Epoch time: 17.44 s +2024-11-23 03:52:12.509004: +2024-11-23 03:52:12.509217: Epoch 7401 +2024-11-23 03:52:12.509336: Current learning rate: 0.00097 +2024-11-23 03:52:31.600183: train_loss -0.8198 +2024-11-23 03:52:31.600466: val_loss -0.7775 +2024-11-23 03:52:31.600549: Pseudo dice [0.8675] +2024-11-23 03:52:31.600628: Epoch time: 19.09 s +2024-11-23 03:52:32.541632: +2024-11-23 03:52:32.541862: Epoch 7402 +2024-11-23 03:52:32.541998: Current learning rate: 0.00097 +2024-11-23 03:52:51.116745: train_loss -0.825 +2024-11-23 03:52:51.116968: val_loss -0.7847 +2024-11-23 03:52:51.117062: Pseudo dice [0.8447] +2024-11-23 03:52:51.117144: Epoch time: 18.58 s +2024-11-23 03:52:51.998191: +2024-11-23 03:52:51.998407: Epoch 7403 +2024-11-23 03:52:51.998520: Current learning rate: 0.00097 +2024-11-23 03:53:11.304290: train_loss -0.8244 +2024-11-23 03:53:11.304587: val_loss -0.7978 +2024-11-23 03:53:11.304701: Pseudo dice [0.8559] +2024-11-23 03:53:11.304794: Epoch time: 19.31 s +2024-11-23 03:53:12.190403: +2024-11-23 03:53:12.190629: Epoch 7404 +2024-11-23 03:53:12.190744: Current learning rate: 0.00097 +2024-11-23 03:53:29.808978: train_loss -0.8263 +2024-11-23 03:53:29.809199: val_loss -0.8076 +2024-11-23 03:53:29.809277: Pseudo dice [0.8584] +2024-11-23 03:53:29.809416: Epoch time: 17.62 s +2024-11-23 03:53:30.715528: +2024-11-23 03:53:30.715749: Epoch 7405 +2024-11-23 03:53:30.715875: Current learning rate: 0.00096 +2024-11-23 03:53:49.291297: train_loss -0.8249 +2024-11-23 03:53:49.291505: val_loss -0.8143 +2024-11-23 03:53:49.291579: Pseudo dice [0.8739] +2024-11-23 03:53:49.291655: Epoch time: 18.58 s +2024-11-23 03:53:50.184187: +2024-11-23 03:53:50.184433: Epoch 7406 +2024-11-23 03:53:50.184556: Current learning rate: 0.00096 +2024-11-23 03:54:08.694493: train_loss -0.8195 +2024-11-23 03:54:08.694703: val_loss -0.7937 +2024-11-23 03:54:08.694782: Pseudo dice [0.8701] +2024-11-23 03:54:08.694867: Epoch time: 18.51 s +2024-11-23 03:54:09.577132: +2024-11-23 03:54:09.577336: Epoch 7407 +2024-11-23 03:54:09.577456: Current learning rate: 0.00096 +2024-11-23 03:54:29.003579: train_loss -0.8243 +2024-11-23 03:54:29.003845: val_loss -0.8103 +2024-11-23 03:54:29.003931: Pseudo dice [0.8709] +2024-11-23 03:54:29.004034: Epoch time: 19.43 s +2024-11-23 03:54:29.897243: +2024-11-23 03:54:29.897474: Epoch 7408 +2024-11-23 03:54:29.897593: Current learning rate: 0.00096 +2024-11-23 03:54:49.075761: train_loss -0.8277 +2024-11-23 03:54:49.075982: val_loss -0.7722 +2024-11-23 03:54:49.076066: Pseudo dice [0.8767] +2024-11-23 03:54:49.076146: Epoch time: 19.18 s +2024-11-23 03:54:49.967229: +2024-11-23 03:54:49.967431: Epoch 7409 +2024-11-23 03:54:49.967546: Current learning rate: 0.00096 +2024-11-23 03:55:08.636260: train_loss -0.8254 +2024-11-23 03:55:08.636478: val_loss -0.7838 +2024-11-23 03:55:08.636557: Pseudo dice [0.8621] +2024-11-23 03:55:08.636642: Epoch time: 18.67 s +2024-11-23 03:55:09.517000: +2024-11-23 03:55:09.517212: Epoch 7410 +2024-11-23 03:55:09.517340: Current learning rate: 0.00096 +2024-11-23 03:55:27.601065: train_loss -0.8228 +2024-11-23 03:55:27.601287: val_loss -0.782 +2024-11-23 03:55:27.601369: Pseudo dice [0.8694] +2024-11-23 03:55:27.601466: Epoch time: 18.08 s +2024-11-23 03:55:28.482006: +2024-11-23 03:55:28.482238: Epoch 7411 +2024-11-23 03:55:28.482371: Current learning rate: 0.00096 +2024-11-23 03:55:46.547547: train_loss -0.8271 +2024-11-23 03:55:46.547787: val_loss -0.7924 +2024-11-23 03:55:46.547870: Pseudo dice [0.8677] +2024-11-23 03:55:46.547976: Epoch time: 18.07 s +2024-11-23 03:55:47.437603: +2024-11-23 03:55:47.437813: Epoch 7412 +2024-11-23 03:55:47.437937: Current learning rate: 0.00095 +2024-11-23 03:56:06.180077: train_loss -0.8277 +2024-11-23 03:56:06.180288: val_loss -0.8006 +2024-11-23 03:56:06.180366: Pseudo dice [0.8722] +2024-11-23 03:56:06.180463: Epoch time: 18.74 s +2024-11-23 03:56:06.180525: Yayy! New best EMA pseudo Dice: 0.866 +2024-11-23 03:56:07.764215: +2024-11-23 03:56:07.764441: Epoch 7413 +2024-11-23 03:56:07.764557: Current learning rate: 0.00095 +2024-11-23 03:56:26.211890: train_loss -0.8258 +2024-11-23 03:56:26.212155: val_loss -0.7765 +2024-11-23 03:56:26.212238: Pseudo dice [0.8718] +2024-11-23 03:56:26.212317: Epoch time: 18.45 s +2024-11-23 03:56:26.212383: Yayy! New best EMA pseudo Dice: 0.8666 +2024-11-23 03:56:27.431961: +2024-11-23 03:56:27.432174: Epoch 7414 +2024-11-23 03:56:27.432285: Current learning rate: 0.00095 +2024-11-23 03:56:45.352831: train_loss -0.8342 +2024-11-23 03:56:45.353052: val_loss -0.7941 +2024-11-23 03:56:45.353207: Pseudo dice [0.8571] +2024-11-23 03:56:45.353300: Epoch time: 17.92 s +2024-11-23 03:56:46.265534: +2024-11-23 03:56:46.265755: Epoch 7415 +2024-11-23 03:56:46.265874: Current learning rate: 0.00095 +2024-11-23 03:57:05.020791: train_loss -0.8277 +2024-11-23 03:57:05.021047: val_loss -0.7761 +2024-11-23 03:57:05.021157: Pseudo dice [0.8629] +2024-11-23 03:57:05.021238: Epoch time: 18.76 s +2024-11-23 03:57:06.012893: +2024-11-23 03:57:06.013156: Epoch 7416 +2024-11-23 03:57:06.013279: Current learning rate: 0.00095 +2024-11-23 03:57:24.798924: train_loss -0.8277 +2024-11-23 03:57:24.799143: val_loss -0.7884 +2024-11-23 03:57:24.799217: Pseudo dice [0.8624] +2024-11-23 03:57:24.799351: Epoch time: 18.79 s +2024-11-23 03:57:25.692560: +2024-11-23 03:57:25.692813: Epoch 7417 +2024-11-23 03:57:25.692946: Current learning rate: 0.00095 +2024-11-23 03:57:45.440286: train_loss -0.8208 +2024-11-23 03:57:45.440516: val_loss -0.7841 +2024-11-23 03:57:45.440599: Pseudo dice [0.8726] +2024-11-23 03:57:45.440691: Epoch time: 19.75 s +2024-11-23 03:57:46.421781: +2024-11-23 03:57:46.421997: Epoch 7418 +2024-11-23 03:57:46.422112: Current learning rate: 0.00095 +2024-11-23 03:58:05.967087: train_loss -0.8259 +2024-11-23 03:58:05.967299: val_loss -0.7768 +2024-11-23 03:58:05.967383: Pseudo dice [0.8692] +2024-11-23 03:58:05.967463: Epoch time: 19.55 s +2024-11-23 03:58:06.890511: +2024-11-23 03:58:06.890724: Epoch 7419 +2024-11-23 03:58:06.890843: Current learning rate: 0.00094 +2024-11-23 03:58:25.896112: train_loss -0.8263 +2024-11-23 03:58:25.896344: val_loss -0.7687 +2024-11-23 03:58:25.896441: Pseudo dice [0.8668] +2024-11-23 03:58:25.900889: Epoch time: 19.01 s +2024-11-23 03:58:26.813128: +2024-11-23 03:58:26.813339: Epoch 7420 +2024-11-23 03:58:26.813474: Current learning rate: 0.00094 +2024-11-23 03:58:45.215831: train_loss -0.8315 +2024-11-23 03:58:45.216044: val_loss -0.7665 +2024-11-23 03:58:45.216140: Pseudo dice [0.867] +2024-11-23 03:58:45.216216: Epoch time: 18.4 s +2024-11-23 03:58:46.099688: +2024-11-23 03:58:46.099900: Epoch 7421 +2024-11-23 03:58:46.100019: Current learning rate: 0.00094 +2024-11-23 03:59:03.312868: train_loss -0.8273 +2024-11-23 03:59:03.313097: val_loss -0.7712 +2024-11-23 03:59:03.313188: Pseudo dice [0.8458] +2024-11-23 03:59:03.313283: Epoch time: 17.21 s +2024-11-23 03:59:04.200272: +2024-11-23 03:59:04.200484: Epoch 7422 +2024-11-23 03:59:04.200601: Current learning rate: 0.00094 +2024-11-23 03:59:23.537493: train_loss -0.8323 +2024-11-23 03:59:23.537718: val_loss -0.7797 +2024-11-23 03:59:23.537817: Pseudo dice [0.8715] +2024-11-23 03:59:23.537931: Epoch time: 19.34 s +2024-11-23 03:59:24.416120: +2024-11-23 03:59:24.416337: Epoch 7423 +2024-11-23 03:59:24.416457: Current learning rate: 0.00094 +2024-11-23 03:59:42.850193: train_loss -0.8274 +2024-11-23 03:59:42.850435: val_loss -0.7901 +2024-11-23 03:59:42.850529: Pseudo dice [0.8628] +2024-11-23 03:59:42.850617: Epoch time: 18.43 s +2024-11-23 03:59:43.728003: +2024-11-23 03:59:43.728235: Epoch 7424 +2024-11-23 03:59:43.728366: Current learning rate: 0.00094 +2024-11-23 04:00:01.417804: train_loss -0.8236 +2024-11-23 04:00:01.420220: val_loss -0.7911 +2024-11-23 04:00:01.420334: Pseudo dice [0.8552] +2024-11-23 04:00:01.420423: Epoch time: 17.69 s +2024-11-23 04:00:02.749862: +2024-11-23 04:00:02.750080: Epoch 7425 +2024-11-23 04:00:02.750204: Current learning rate: 0.00094 +2024-11-23 04:00:21.866343: train_loss -0.8304 +2024-11-23 04:00:21.866561: val_loss -0.7742 +2024-11-23 04:00:21.866643: Pseudo dice [0.8472] +2024-11-23 04:00:21.866727: Epoch time: 19.12 s +2024-11-23 04:00:22.761765: +2024-11-23 04:00:22.762006: Epoch 7426 +2024-11-23 04:00:22.762135: Current learning rate: 0.00093 +2024-11-23 04:00:41.854196: train_loss -0.8318 +2024-11-23 04:00:41.854512: val_loss -0.7919 +2024-11-23 04:00:41.854598: Pseudo dice [0.8667] +2024-11-23 04:00:41.854686: Epoch time: 19.09 s +2024-11-23 04:00:42.854944: +2024-11-23 04:00:42.855187: Epoch 7427 +2024-11-23 04:00:42.855316: Current learning rate: 0.00093 +2024-11-23 04:01:01.880665: train_loss -0.834 +2024-11-23 04:01:01.880888: val_loss -0.7956 +2024-11-23 04:01:01.880991: Pseudo dice [0.8725] +2024-11-23 04:01:01.881084: Epoch time: 19.03 s +2024-11-23 04:01:02.859680: +2024-11-23 04:01:02.859915: Epoch 7428 +2024-11-23 04:01:02.860036: Current learning rate: 0.00093 +2024-11-23 04:01:21.851207: train_loss -0.828 +2024-11-23 04:01:21.851426: val_loss -0.7843 +2024-11-23 04:01:21.851517: Pseudo dice [0.8687] +2024-11-23 04:01:21.851597: Epoch time: 18.99 s +2024-11-23 04:01:22.744295: +2024-11-23 04:01:22.744504: Epoch 7429 +2024-11-23 04:01:22.744619: Current learning rate: 0.00093 +2024-11-23 04:01:41.097460: train_loss -0.8305 +2024-11-23 04:01:41.097682: val_loss -0.7915 +2024-11-23 04:01:41.097759: Pseudo dice [0.8613] +2024-11-23 04:01:41.097836: Epoch time: 18.35 s +2024-11-23 04:01:42.086391: +2024-11-23 04:01:42.086617: Epoch 7430 +2024-11-23 04:01:42.086744: Current learning rate: 0.00093 +2024-11-23 04:02:02.051327: train_loss -0.823 +2024-11-23 04:02:02.051612: val_loss -0.7802 +2024-11-23 04:02:02.051719: Pseudo dice [0.8477] +2024-11-23 04:02:02.051817: Epoch time: 19.97 s +2024-11-23 04:02:03.002043: +2024-11-23 04:02:03.002264: Epoch 7431 +2024-11-23 04:02:03.002389: Current learning rate: 0.00093 +2024-11-23 04:02:21.373401: train_loss -0.8317 +2024-11-23 04:02:21.373638: val_loss -0.7935 +2024-11-23 04:02:21.373719: Pseudo dice [0.8787] +2024-11-23 04:02:21.373818: Epoch time: 18.37 s +2024-11-23 04:02:22.354376: +2024-11-23 04:02:22.354589: Epoch 7432 +2024-11-23 04:02:22.354698: Current learning rate: 0.00092 +2024-11-23 04:02:40.092702: train_loss -0.8266 +2024-11-23 04:02:40.092965: val_loss -0.7976 +2024-11-23 04:02:40.093071: Pseudo dice [0.8587] +2024-11-23 04:02:40.093152: Epoch time: 17.74 s +2024-11-23 04:02:40.979448: +2024-11-23 04:02:40.979657: Epoch 7433 +2024-11-23 04:02:40.979775: Current learning rate: 0.00092 +2024-11-23 04:02:59.340855: train_loss -0.8218 +2024-11-23 04:02:59.341084: val_loss -0.8083 +2024-11-23 04:02:59.341181: Pseudo dice [0.8635] +2024-11-23 04:02:59.341266: Epoch time: 18.36 s +2024-11-23 04:03:00.223082: +2024-11-23 04:03:00.223299: Epoch 7434 +2024-11-23 04:03:00.223412: Current learning rate: 0.00092 +2024-11-23 04:03:19.511554: train_loss -0.8252 +2024-11-23 04:03:19.511771: val_loss -0.7723 +2024-11-23 04:03:19.511888: Pseudo dice [0.8638] +2024-11-23 04:03:19.511983: Epoch time: 19.29 s +2024-11-23 04:03:20.406339: +2024-11-23 04:03:20.406552: Epoch 7435 +2024-11-23 04:03:20.406674: Current learning rate: 0.00092 +2024-11-23 04:03:38.523483: train_loss -0.8173 +2024-11-23 04:03:38.523765: val_loss -0.7972 +2024-11-23 04:03:38.523854: Pseudo dice [0.8634] +2024-11-23 04:03:38.523948: Epoch time: 18.12 s +2024-11-23 04:03:39.440466: +2024-11-23 04:03:39.440659: Epoch 7436 +2024-11-23 04:03:39.440779: Current learning rate: 0.00092 +2024-11-23 04:03:57.751069: train_loss -0.8249 +2024-11-23 04:03:57.751316: val_loss -0.7804 +2024-11-23 04:03:57.751397: Pseudo dice [0.8561] +2024-11-23 04:03:57.751489: Epoch time: 18.31 s +2024-11-23 04:03:58.665184: +2024-11-23 04:03:58.665407: Epoch 7437 +2024-11-23 04:03:58.665523: Current learning rate: 0.00092 +2024-11-23 04:04:16.816388: train_loss -0.8235 +2024-11-23 04:04:16.816613: val_loss -0.8012 +2024-11-23 04:04:16.816695: Pseudo dice [0.864] +2024-11-23 04:04:16.816789: Epoch time: 18.15 s +2024-11-23 04:04:17.740183: +2024-11-23 04:04:17.740405: Epoch 7438 +2024-11-23 04:04:17.740522: Current learning rate: 0.00092 +2024-11-23 04:04:36.049523: train_loss -0.8231 +2024-11-23 04:04:36.049814: val_loss -0.7803 +2024-11-23 04:04:36.049911: Pseudo dice [0.8643] +2024-11-23 04:04:36.049994: Epoch time: 18.31 s +2024-11-23 04:04:36.939575: +2024-11-23 04:04:36.939797: Epoch 7439 +2024-11-23 04:04:36.939913: Current learning rate: 0.00091 +2024-11-23 04:04:54.744973: train_loss -0.8306 +2024-11-23 04:04:54.745188: val_loss -0.7813 +2024-11-23 04:04:54.745267: Pseudo dice [0.8705] +2024-11-23 04:04:54.745348: Epoch time: 17.81 s +2024-11-23 04:04:55.633574: +2024-11-23 04:04:55.633780: Epoch 7440 +2024-11-23 04:04:55.633895: Current learning rate: 0.00091 +2024-11-23 04:05:13.418391: train_loss -0.8328 +2024-11-23 04:05:13.418631: val_loss -0.78 +2024-11-23 04:05:13.418802: Pseudo dice [0.8691] +2024-11-23 04:05:13.418891: Epoch time: 17.79 s +2024-11-23 04:05:14.301400: +2024-11-23 04:05:14.301630: Epoch 7441 +2024-11-23 04:05:14.302083: Current learning rate: 0.00091 +2024-11-23 04:05:32.143020: train_loss -0.8243 +2024-11-23 04:05:32.143245: val_loss -0.7824 +2024-11-23 04:05:32.143319: Pseudo dice [0.8588] +2024-11-23 04:05:32.143399: Epoch time: 17.84 s +2024-11-23 04:05:33.030755: +2024-11-23 04:05:33.030971: Epoch 7442 +2024-11-23 04:05:33.031098: Current learning rate: 0.00091 +2024-11-23 04:05:51.751487: train_loss -0.8243 +2024-11-23 04:05:51.751775: val_loss -0.7861 +2024-11-23 04:05:51.751875: Pseudo dice [0.8654] +2024-11-23 04:05:51.751984: Epoch time: 18.72 s +2024-11-23 04:05:52.689303: +2024-11-23 04:05:52.689510: Epoch 7443 +2024-11-23 04:05:52.689635: Current learning rate: 0.00091 +2024-11-23 04:06:10.343084: train_loss -0.8314 +2024-11-23 04:06:10.343325: val_loss -0.7886 +2024-11-23 04:06:10.343412: Pseudo dice [0.8625] +2024-11-23 04:06:10.343495: Epoch time: 17.65 s +2024-11-23 04:06:11.283360: +2024-11-23 04:06:11.283584: Epoch 7444 +2024-11-23 04:06:11.283715: Current learning rate: 0.00091 +2024-11-23 04:06:29.072109: train_loss -0.8293 +2024-11-23 04:06:29.072332: val_loss -0.7927 +2024-11-23 04:06:29.072417: Pseudo dice [0.8701] +2024-11-23 04:06:29.072501: Epoch time: 17.79 s +2024-11-23 04:06:29.957160: +2024-11-23 04:06:29.957374: Epoch 7445 +2024-11-23 04:06:29.957491: Current learning rate: 0.00091 +2024-11-23 04:06:49.559016: train_loss -0.825 +2024-11-23 04:06:49.559310: val_loss -0.7786 +2024-11-23 04:06:49.559389: Pseudo dice [0.8636] +2024-11-23 04:06:49.559465: Epoch time: 19.6 s +2024-11-23 04:06:50.460297: +2024-11-23 04:06:50.460526: Epoch 7446 +2024-11-23 04:06:50.460657: Current learning rate: 0.0009 +2024-11-23 04:07:08.642897: train_loss -0.8267 +2024-11-23 04:07:08.643121: val_loss -0.792 +2024-11-23 04:07:08.643215: Pseudo dice [0.8689] +2024-11-23 04:07:08.643293: Epoch time: 18.18 s +2024-11-23 04:07:09.528380: +2024-11-23 04:07:09.528631: Epoch 7447 +2024-11-23 04:07:09.528786: Current learning rate: 0.0009 +2024-11-23 04:07:28.255267: train_loss -0.8295 +2024-11-23 04:07:28.255506: val_loss -0.7705 +2024-11-23 04:07:28.255673: Pseudo dice [0.861] +2024-11-23 04:07:28.255773: Epoch time: 18.73 s +2024-11-23 04:07:29.544977: +2024-11-23 04:07:29.545237: Epoch 7448 +2024-11-23 04:07:29.545348: Current learning rate: 0.0009 +2024-11-23 04:07:47.508250: train_loss -0.8157 +2024-11-23 04:07:47.508538: val_loss -0.7828 +2024-11-23 04:07:47.508629: Pseudo dice [0.852] +2024-11-23 04:07:47.508730: Epoch time: 17.96 s +2024-11-23 04:07:48.420444: +2024-11-23 04:07:48.420671: Epoch 7449 +2024-11-23 04:07:48.420784: Current learning rate: 0.0009 +2024-11-23 04:08:06.125184: train_loss -0.8287 +2024-11-23 04:08:06.125409: val_loss -0.7692 +2024-11-23 04:08:06.125510: Pseudo dice [0.8565] +2024-11-23 04:08:06.125610: Epoch time: 17.71 s +2024-11-23 04:08:07.366196: +2024-11-23 04:08:07.366454: Epoch 7450 +2024-11-23 04:08:07.366570: Current learning rate: 0.0009 +2024-11-23 04:08:26.184407: train_loss -0.8283 +2024-11-23 04:08:26.184644: val_loss -0.7677 +2024-11-23 04:08:26.186964: Pseudo dice [0.8582] +2024-11-23 04:08:26.187073: Epoch time: 18.82 s +2024-11-23 04:08:27.106729: +2024-11-23 04:08:27.106978: Epoch 7451 +2024-11-23 04:08:27.107106: Current learning rate: 0.0009 +2024-11-23 04:08:46.027610: train_loss -0.8222 +2024-11-23 04:08:46.027826: val_loss -0.7638 +2024-11-23 04:08:46.027902: Pseudo dice [0.8589] +2024-11-23 04:08:46.027979: Epoch time: 18.92 s +2024-11-23 04:08:46.911567: +2024-11-23 04:08:46.911788: Epoch 7452 +2024-11-23 04:08:46.911908: Current learning rate: 0.0009 +2024-11-23 04:09:05.107466: train_loss -0.828 +2024-11-23 04:09:05.107678: val_loss -0.8152 +2024-11-23 04:09:05.107756: Pseudo dice [0.8687] +2024-11-23 04:09:05.107834: Epoch time: 18.2 s +2024-11-23 04:09:05.992605: +2024-11-23 04:09:05.992813: Epoch 7453 +2024-11-23 04:09:05.992923: Current learning rate: 0.00089 +2024-11-23 04:09:24.373397: train_loss -0.8348 +2024-11-23 04:09:24.373639: val_loss -0.7945 +2024-11-23 04:09:24.373725: Pseudo dice [0.8646] +2024-11-23 04:09:24.373809: Epoch time: 18.38 s +2024-11-23 04:09:25.261125: +2024-11-23 04:09:25.261354: Epoch 7454 +2024-11-23 04:09:25.261491: Current learning rate: 0.00089 +2024-11-23 04:09:43.133799: train_loss -0.8293 +2024-11-23 04:09:43.134047: val_loss -0.7536 +2024-11-23 04:09:43.134139: Pseudo dice [0.8427] +2024-11-23 04:09:43.134224: Epoch time: 17.87 s +2024-11-23 04:09:44.018906: +2024-11-23 04:09:44.019118: Epoch 7455 +2024-11-23 04:09:44.019229: Current learning rate: 0.00089 +2024-11-23 04:10:02.501728: train_loss -0.8263 +2024-11-23 04:10:02.501960: val_loss -0.7918 +2024-11-23 04:10:02.502042: Pseudo dice [0.8607] +2024-11-23 04:10:02.502130: Epoch time: 18.48 s +2024-11-23 04:10:03.505716: +2024-11-23 04:10:03.505962: Epoch 7456 +2024-11-23 04:10:03.506093: Current learning rate: 0.00089 +2024-11-23 04:10:21.780336: train_loss -0.8279 +2024-11-23 04:10:21.780553: val_loss -0.7778 +2024-11-23 04:10:21.780644: Pseudo dice [0.8582] +2024-11-23 04:10:21.780726: Epoch time: 18.28 s +2024-11-23 04:10:22.665330: +2024-11-23 04:10:22.665547: Epoch 7457 +2024-11-23 04:10:22.665662: Current learning rate: 0.00089 +2024-11-23 04:10:40.815782: train_loss -0.8265 +2024-11-23 04:10:40.815984: val_loss -0.7883 +2024-11-23 04:10:40.816063: Pseudo dice [0.8589] +2024-11-23 04:10:40.816207: Epoch time: 18.15 s +2024-11-23 04:10:41.702009: +2024-11-23 04:10:41.702444: Epoch 7458 +2024-11-23 04:10:41.702584: Current learning rate: 0.00089 +2024-11-23 04:10:59.761589: train_loss -0.8288 +2024-11-23 04:10:59.761827: val_loss -0.7783 +2024-11-23 04:10:59.761911: Pseudo dice [0.8525] +2024-11-23 04:10:59.761991: Epoch time: 18.06 s +2024-11-23 04:11:00.642693: +2024-11-23 04:11:00.642920: Epoch 7459 +2024-11-23 04:11:00.643046: Current learning rate: 0.00089 +2024-11-23 04:11:19.548544: train_loss -0.8269 +2024-11-23 04:11:19.548791: val_loss -0.7758 +2024-11-23 04:11:19.548894: Pseudo dice [0.8664] +2024-11-23 04:11:19.548973: Epoch time: 18.91 s +2024-11-23 04:11:20.436892: +2024-11-23 04:11:20.437109: Epoch 7460 +2024-11-23 04:11:20.437223: Current learning rate: 0.00088 +2024-11-23 04:11:38.650022: train_loss -0.8296 +2024-11-23 04:11:38.650248: val_loss -0.7679 +2024-11-23 04:11:38.650340: Pseudo dice [0.867] +2024-11-23 04:11:38.650431: Epoch time: 18.21 s +2024-11-23 04:11:39.543080: +2024-11-23 04:11:39.543277: Epoch 7461 +2024-11-23 04:11:39.543406: Current learning rate: 0.00088 +2024-11-23 04:11:58.007464: train_loss -0.8363 +2024-11-23 04:11:58.007726: val_loss -0.7977 +2024-11-23 04:11:58.007815: Pseudo dice [0.8506] +2024-11-23 04:11:58.007905: Epoch time: 18.47 s +2024-11-23 04:11:59.027820: +2024-11-23 04:11:59.028044: Epoch 7462 +2024-11-23 04:11:59.028162: Current learning rate: 0.00088 +2024-11-23 04:12:19.113889: train_loss -0.828 +2024-11-23 04:12:19.114102: val_loss -0.7775 +2024-11-23 04:12:19.114187: Pseudo dice [0.8515] +2024-11-23 04:12:19.114269: Epoch time: 20.09 s +2024-11-23 04:12:20.000441: +2024-11-23 04:12:20.000661: Epoch 7463 +2024-11-23 04:12:20.000782: Current learning rate: 0.00088 +2024-11-23 04:12:38.226894: train_loss -0.8225 +2024-11-23 04:12:38.227127: val_loss -0.7919 +2024-11-23 04:12:38.227206: Pseudo dice [0.8586] +2024-11-23 04:12:38.227279: Epoch time: 18.23 s +2024-11-23 04:12:39.110440: +2024-11-23 04:12:39.110656: Epoch 7464 +2024-11-23 04:12:39.110767: Current learning rate: 0.00088 +2024-11-23 04:12:57.829338: train_loss -0.8319 +2024-11-23 04:12:57.829560: val_loss -0.7832 +2024-11-23 04:12:57.829651: Pseudo dice [0.8571] +2024-11-23 04:12:57.829732: Epoch time: 18.72 s +2024-11-23 04:12:58.714946: +2024-11-23 04:12:58.715188: Epoch 7465 +2024-11-23 04:12:58.715317: Current learning rate: 0.00088 +2024-11-23 04:13:16.625122: train_loss -0.8287 +2024-11-23 04:13:16.625374: val_loss -0.7655 +2024-11-23 04:13:16.625472: Pseudo dice [0.8574] +2024-11-23 04:13:16.625568: Epoch time: 17.91 s +2024-11-23 04:13:17.514581: +2024-11-23 04:13:17.514834: Epoch 7466 +2024-11-23 04:13:17.514948: Current learning rate: 0.00087 +2024-11-23 04:13:36.327743: train_loss -0.8235 +2024-11-23 04:13:36.328013: val_loss -0.7825 +2024-11-23 04:13:36.328109: Pseudo dice [0.8634] +2024-11-23 04:13:36.328196: Epoch time: 18.81 s +2024-11-23 04:13:37.230639: +2024-11-23 04:13:37.231107: Epoch 7467 +2024-11-23 04:13:37.231251: Current learning rate: 0.00087 +2024-11-23 04:13:55.362117: train_loss -0.8285 +2024-11-23 04:13:55.362397: val_loss -0.7529 +2024-11-23 04:13:55.362482: Pseudo dice [0.8538] +2024-11-23 04:13:55.362558: Epoch time: 18.13 s +2024-11-23 04:13:56.251812: +2024-11-23 04:13:56.252017: Epoch 7468 +2024-11-23 04:13:56.252131: Current learning rate: 0.00087 +2024-11-23 04:14:14.429734: train_loss -0.8294 +2024-11-23 04:14:14.429971: val_loss -0.7544 +2024-11-23 04:14:14.430052: Pseudo dice [0.8581] +2024-11-23 04:14:14.430134: Epoch time: 18.18 s +2024-11-23 04:14:15.317836: +2024-11-23 04:14:15.318034: Epoch 7469 +2024-11-23 04:14:15.318154: Current learning rate: 0.00087 +2024-11-23 04:14:33.706468: train_loss -0.8273 +2024-11-23 04:14:33.706690: val_loss -0.7663 +2024-11-23 04:14:33.708995: Pseudo dice [0.8646] +2024-11-23 04:14:33.709114: Epoch time: 18.39 s +2024-11-23 04:14:34.636185: +2024-11-23 04:14:34.636396: Epoch 7470 +2024-11-23 04:14:34.636510: Current learning rate: 0.00087 +2024-11-23 04:14:52.793973: train_loss -0.8311 +2024-11-23 04:14:52.794212: val_loss -0.7658 +2024-11-23 04:14:52.794300: Pseudo dice [0.8581] +2024-11-23 04:14:52.794381: Epoch time: 18.16 s +2024-11-23 04:14:54.060723: +2024-11-23 04:14:54.060948: Epoch 7471 +2024-11-23 04:14:54.061071: Current learning rate: 0.00087 +2024-11-23 04:15:12.215838: train_loss -0.8319 +2024-11-23 04:15:12.216064: val_loss -0.7822 +2024-11-23 04:15:12.216158: Pseudo dice [0.8713] +2024-11-23 04:15:12.216237: Epoch time: 18.16 s +2024-11-23 04:15:13.102170: +2024-11-23 04:15:13.102395: Epoch 7472 +2024-11-23 04:15:13.102527: Current learning rate: 0.00087 +2024-11-23 04:15:31.850599: train_loss -0.8339 +2024-11-23 04:15:31.850843: val_loss -0.8047 +2024-11-23 04:15:31.850933: Pseudo dice [0.8658] +2024-11-23 04:15:31.851011: Epoch time: 18.75 s +2024-11-23 04:15:32.733015: +2024-11-23 04:15:32.733252: Epoch 7473 +2024-11-23 04:15:32.733363: Current learning rate: 0.00086 +2024-11-23 04:15:50.774717: train_loss -0.8282 +2024-11-23 04:15:50.774962: val_loss -0.7765 +2024-11-23 04:15:50.775042: Pseudo dice [0.8508] +2024-11-23 04:15:50.775133: Epoch time: 18.04 s +2024-11-23 04:15:51.671803: +2024-11-23 04:15:51.672050: Epoch 7474 +2024-11-23 04:15:51.672189: Current learning rate: 0.00086 +2024-11-23 04:16:10.278135: train_loss -0.8297 +2024-11-23 04:16:10.278355: val_loss -0.7749 +2024-11-23 04:16:10.278436: Pseudo dice [0.8715] +2024-11-23 04:16:10.278532: Epoch time: 18.61 s +2024-11-23 04:16:11.164398: +2024-11-23 04:16:11.164618: Epoch 7475 +2024-11-23 04:16:11.164737: Current learning rate: 0.00086 +2024-11-23 04:16:30.511942: train_loss -0.8289 +2024-11-23 04:16:30.512160: val_loss -0.7729 +2024-11-23 04:16:30.512257: Pseudo dice [0.848] +2024-11-23 04:16:30.512331: Epoch time: 19.35 s +2024-11-23 04:16:31.395619: +2024-11-23 04:16:31.395831: Epoch 7476 +2024-11-23 04:16:31.395947: Current learning rate: 0.00086 +2024-11-23 04:16:50.114069: train_loss -0.8284 +2024-11-23 04:16:50.114279: val_loss -0.77 +2024-11-23 04:16:50.114353: Pseudo dice [0.8463] +2024-11-23 04:16:50.114449: Epoch time: 18.72 s +2024-11-23 04:16:50.998658: +2024-11-23 04:16:50.998877: Epoch 7477 +2024-11-23 04:16:50.999008: Current learning rate: 0.00086 +2024-11-23 04:17:09.333407: train_loss -0.8362 +2024-11-23 04:17:09.333646: val_loss -0.7829 +2024-11-23 04:17:09.333723: Pseudo dice [0.869] +2024-11-23 04:17:09.333803: Epoch time: 18.34 s +2024-11-23 04:17:10.228752: +2024-11-23 04:17:10.228984: Epoch 7478 +2024-11-23 04:17:10.229109: Current learning rate: 0.00086 +2024-11-23 04:17:28.142492: train_loss -0.8242 +2024-11-23 04:17:28.142704: val_loss -0.7754 +2024-11-23 04:17:28.142783: Pseudo dice [0.8512] +2024-11-23 04:17:28.142864: Epoch time: 17.91 s +2024-11-23 04:17:29.124251: +2024-11-23 04:17:29.124458: Epoch 7479 +2024-11-23 04:17:29.124577: Current learning rate: 0.00086 +2024-11-23 04:17:49.323471: train_loss -0.828 +2024-11-23 04:17:49.323699: val_loss -0.7872 +2024-11-23 04:17:49.323802: Pseudo dice [0.86] +2024-11-23 04:17:49.323893: Epoch time: 20.2 s +2024-11-23 04:17:50.203732: +2024-11-23 04:17:50.203925: Epoch 7480 +2024-11-23 04:17:50.204044: Current learning rate: 0.00085 +2024-11-23 04:18:08.219035: train_loss -0.829 +2024-11-23 04:18:08.219276: val_loss -0.7968 +2024-11-23 04:18:08.219355: Pseudo dice [0.8704] +2024-11-23 04:18:08.219433: Epoch time: 18.02 s +2024-11-23 04:18:09.103258: +2024-11-23 04:18:09.103684: Epoch 7481 +2024-11-23 04:18:09.103814: Current learning rate: 0.00085 +2024-11-23 04:18:27.941744: train_loss -0.8319 +2024-11-23 04:18:27.941982: val_loss -0.7911 +2024-11-23 04:18:27.942067: Pseudo dice [0.86] +2024-11-23 04:18:27.942156: Epoch time: 18.84 s +2024-11-23 04:18:29.335754: +2024-11-23 04:18:29.335994: Epoch 7482 +2024-11-23 04:18:29.336119: Current learning rate: 0.00085 +2024-11-23 04:18:47.332401: train_loss -0.8343 +2024-11-23 04:18:47.332634: val_loss -0.7785 +2024-11-23 04:18:47.332715: Pseudo dice [0.8702] +2024-11-23 04:18:47.335878: Epoch time: 18.0 s +2024-11-23 04:18:48.217981: +2024-11-23 04:18:48.218286: Epoch 7483 +2024-11-23 04:18:48.218418: Current learning rate: 0.00085 +2024-11-23 04:19:07.575418: train_loss -0.8316 +2024-11-23 04:19:07.575635: val_loss -0.7789 +2024-11-23 04:19:07.575722: Pseudo dice [0.8629] +2024-11-23 04:19:07.575796: Epoch time: 19.36 s +2024-11-23 04:19:08.458733: +2024-11-23 04:19:08.458941: Epoch 7484 +2024-11-23 04:19:08.459056: Current learning rate: 0.00085 +2024-11-23 04:19:26.198850: train_loss -0.8252 +2024-11-23 04:19:26.199104: val_loss -0.7916 +2024-11-23 04:19:26.199188: Pseudo dice [0.8867] +2024-11-23 04:19:26.199278: Epoch time: 17.74 s +2024-11-23 04:19:27.088441: +2024-11-23 04:19:27.088646: Epoch 7485 +2024-11-23 04:19:27.088768: Current learning rate: 0.00085 +2024-11-23 04:19:45.418718: train_loss -0.8308 +2024-11-23 04:19:45.418940: val_loss -0.8026 +2024-11-23 04:19:45.419025: Pseudo dice [0.872] +2024-11-23 04:19:45.419112: Epoch time: 18.33 s +2024-11-23 04:19:46.307015: +2024-11-23 04:19:46.307233: Epoch 7486 +2024-11-23 04:19:46.307350: Current learning rate: 0.00085 +2024-11-23 04:20:04.437911: train_loss -0.835 +2024-11-23 04:20:04.443316: val_loss -0.8136 +2024-11-23 04:20:04.443482: Pseudo dice [0.8664] +2024-11-23 04:20:04.443573: Epoch time: 18.13 s +2024-11-23 04:20:05.473258: +2024-11-23 04:20:05.473475: Epoch 7487 +2024-11-23 04:20:05.473592: Current learning rate: 0.00084 +2024-11-23 04:20:22.396874: train_loss -0.8334 +2024-11-23 04:20:22.397115: val_loss -0.7694 +2024-11-23 04:20:22.397197: Pseudo dice [0.8665] +2024-11-23 04:20:22.397275: Epoch time: 16.92 s +2024-11-23 04:20:23.400586: +2024-11-23 04:20:23.400803: Epoch 7488 +2024-11-23 04:20:23.400919: Current learning rate: 0.00084 +2024-11-23 04:20:42.085717: train_loss -0.8276 +2024-11-23 04:20:42.086016: val_loss -0.7693 +2024-11-23 04:20:42.086112: Pseudo dice [0.8709] +2024-11-23 04:20:42.086226: Epoch time: 18.69 s +2024-11-23 04:20:42.983389: +2024-11-23 04:20:42.983628: Epoch 7489 +2024-11-23 04:20:42.983740: Current learning rate: 0.00084 +2024-11-23 04:21:01.265162: train_loss -0.8347 +2024-11-23 04:21:01.265377: val_loss -0.8055 +2024-11-23 04:21:01.270613: Pseudo dice [0.8653] +2024-11-23 04:21:01.270770: Epoch time: 18.28 s +2024-11-23 04:21:02.157226: +2024-11-23 04:21:02.157432: Epoch 7490 +2024-11-23 04:21:02.157560: Current learning rate: 0.00084 +2024-11-23 04:21:20.334192: train_loss -0.8288 +2024-11-23 04:21:20.334405: val_loss -0.765 +2024-11-23 04:21:20.334488: Pseudo dice [0.8704] +2024-11-23 04:21:20.334573: Epoch time: 18.18 s +2024-11-23 04:21:21.234806: +2024-11-23 04:21:21.235026: Epoch 7491 +2024-11-23 04:21:21.235149: Current learning rate: 0.00084 +2024-11-23 04:21:39.553950: train_loss -0.8329 +2024-11-23 04:21:39.554161: val_loss -0.7733 +2024-11-23 04:21:39.554236: Pseudo dice [0.8548] +2024-11-23 04:21:39.554313: Epoch time: 18.32 s +2024-11-23 04:21:40.442122: +2024-11-23 04:21:40.442347: Epoch 7492 +2024-11-23 04:21:40.442482: Current learning rate: 0.00084 +2024-11-23 04:21:59.387597: train_loss -0.8265 +2024-11-23 04:21:59.387832: val_loss -0.7998 +2024-11-23 04:21:59.387927: Pseudo dice [0.876] +2024-11-23 04:21:59.388010: Epoch time: 18.95 s +2024-11-23 04:22:00.404055: +2024-11-23 04:22:00.404307: Epoch 7493 +2024-11-23 04:22:00.404427: Current learning rate: 0.00084 +2024-11-23 04:22:18.390045: train_loss -0.8301 +2024-11-23 04:22:18.390285: val_loss -0.7936 +2024-11-23 04:22:18.390374: Pseudo dice [0.8594] +2024-11-23 04:22:18.390451: Epoch time: 17.99 s +2024-11-23 04:22:19.715746: +2024-11-23 04:22:19.715958: Epoch 7494 +2024-11-23 04:22:19.716077: Current learning rate: 0.00083 +2024-11-23 04:22:37.926857: train_loss -0.8315 +2024-11-23 04:22:37.932283: val_loss -0.7801 +2024-11-23 04:22:37.932396: Pseudo dice [0.8603] +2024-11-23 04:22:37.932482: Epoch time: 18.21 s +2024-11-23 04:22:38.952566: +2024-11-23 04:22:38.952806: Epoch 7495 +2024-11-23 04:22:38.952931: Current learning rate: 0.00083 +2024-11-23 04:22:58.043888: train_loss -0.8228 +2024-11-23 04:22:58.044134: val_loss -0.7515 +2024-11-23 04:22:58.044226: Pseudo dice [0.8646] +2024-11-23 04:22:58.046567: Epoch time: 19.09 s +2024-11-23 04:22:58.961938: +2024-11-23 04:22:58.962174: Epoch 7496 +2024-11-23 04:22:58.962288: Current learning rate: 0.00083 +2024-11-23 04:23:16.644436: train_loss -0.8273 +2024-11-23 04:23:16.644663: val_loss -0.7793 +2024-11-23 04:23:16.644744: Pseudo dice [0.8704] +2024-11-23 04:23:16.644832: Epoch time: 17.68 s +2024-11-23 04:23:17.532457: +2024-11-23 04:23:17.532681: Epoch 7497 +2024-11-23 04:23:17.532797: Current learning rate: 0.00083 +2024-11-23 04:23:36.668905: train_loss -0.8315 +2024-11-23 04:23:36.669141: val_loss -0.7842 +2024-11-23 04:23:36.669244: Pseudo dice [0.8525] +2024-11-23 04:23:36.669322: Epoch time: 19.14 s +2024-11-23 04:23:37.558075: +2024-11-23 04:23:37.558268: Epoch 7498 +2024-11-23 04:23:37.558381: Current learning rate: 0.00083 +2024-11-23 04:23:56.035627: train_loss -0.8261 +2024-11-23 04:23:56.035846: val_loss -0.7897 +2024-11-23 04:23:56.035942: Pseudo dice [0.8565] +2024-11-23 04:23:56.036027: Epoch time: 18.48 s +2024-11-23 04:23:56.952899: +2024-11-23 04:23:56.953106: Epoch 7499 +2024-11-23 04:23:56.953230: Current learning rate: 0.00083 +2024-11-23 04:24:15.087109: train_loss -0.8287 +2024-11-23 04:24:15.088451: val_loss -0.7786 +2024-11-23 04:24:15.088587: Pseudo dice [0.8621] +2024-11-23 04:24:15.088685: Epoch time: 18.14 s +2024-11-23 04:24:16.353697: +2024-11-23 04:24:16.353916: Epoch 7500 +2024-11-23 04:24:16.354044: Current learning rate: 0.00082 +2024-11-23 04:24:34.246351: train_loss -0.8237 +2024-11-23 04:24:34.246668: val_loss -0.7774 +2024-11-23 04:24:34.246751: Pseudo dice [0.8658] +2024-11-23 04:24:34.246847: Epoch time: 17.89 s +2024-11-23 04:24:35.139042: +2024-11-23 04:24:35.139266: Epoch 7501 +2024-11-23 04:24:35.139377: Current learning rate: 0.00082 +2024-11-23 04:24:53.877710: train_loss -0.8344 +2024-11-23 04:24:53.877927: val_loss -0.7848 +2024-11-23 04:24:53.878001: Pseudo dice [0.8598] +2024-11-23 04:24:53.878093: Epoch time: 18.74 s +2024-11-23 04:24:54.768864: +2024-11-23 04:24:54.769069: Epoch 7502 +2024-11-23 04:24:54.769197: Current learning rate: 0.00082 +2024-11-23 04:25:13.151811: train_loss -0.8242 +2024-11-23 04:25:13.152031: val_loss -0.7819 +2024-11-23 04:25:13.152116: Pseudo dice [0.8711] +2024-11-23 04:25:13.152217: Epoch time: 18.38 s +2024-11-23 04:25:14.040851: +2024-11-23 04:25:14.041086: Epoch 7503 +2024-11-23 04:25:14.041215: Current learning rate: 0.00082 +2024-11-23 04:25:33.012625: train_loss -0.8226 +2024-11-23 04:25:33.012848: val_loss -0.7807 +2024-11-23 04:25:33.012928: Pseudo dice [0.8588] +2024-11-23 04:25:33.017318: Epoch time: 18.97 s +2024-11-23 04:25:33.908387: +2024-11-23 04:25:33.908841: Epoch 7504 +2024-11-23 04:25:33.908986: Current learning rate: 0.00082 +2024-11-23 04:25:53.273529: train_loss -0.8266 +2024-11-23 04:25:53.273825: val_loss -0.7774 +2024-11-23 04:25:53.273916: Pseudo dice [0.8593] +2024-11-23 04:25:53.274004: Epoch time: 19.37 s +2024-11-23 04:25:54.575845: +2024-11-23 04:25:54.576062: Epoch 7505 +2024-11-23 04:25:54.576184: Current learning rate: 0.00082 +2024-11-23 04:26:14.225942: train_loss -0.8268 +2024-11-23 04:26:14.226190: val_loss -0.7713 +2024-11-23 04:26:14.226281: Pseudo dice [0.8624] +2024-11-23 04:26:14.226367: Epoch time: 19.65 s +2024-11-23 04:26:15.114920: +2024-11-23 04:26:15.115140: Epoch 7506 +2024-11-23 04:26:15.115258: Current learning rate: 0.00082 +2024-11-23 04:26:33.193076: train_loss -0.8297 +2024-11-23 04:26:33.194279: val_loss -0.7941 +2024-11-23 04:26:33.194442: Pseudo dice [0.8584] +2024-11-23 04:26:33.194544: Epoch time: 18.08 s +2024-11-23 04:26:34.112337: +2024-11-23 04:26:34.112580: Epoch 7507 +2024-11-23 04:26:34.112697: Current learning rate: 0.00081 +2024-11-23 04:26:52.933354: train_loss -0.821 +2024-11-23 04:26:52.933599: val_loss -0.7778 +2024-11-23 04:26:52.933682: Pseudo dice [0.8607] +2024-11-23 04:26:52.933782: Epoch time: 18.82 s +2024-11-23 04:26:53.826807: +2024-11-23 04:26:53.827015: Epoch 7508 +2024-11-23 04:26:53.827133: Current learning rate: 0.00081 +2024-11-23 04:27:11.454041: train_loss -0.8315 +2024-11-23 04:27:11.454294: val_loss -0.779 +2024-11-23 04:27:11.454375: Pseudo dice [0.869] +2024-11-23 04:27:11.454465: Epoch time: 17.63 s +2024-11-23 04:27:12.378722: +2024-11-23 04:27:12.378944: Epoch 7509 +2024-11-23 04:27:12.379071: Current learning rate: 0.00081 +2024-11-23 04:27:31.050959: train_loss -0.8272 +2024-11-23 04:27:31.051171: val_loss -0.7795 +2024-11-23 04:27:31.051250: Pseudo dice [0.8524] +2024-11-23 04:27:31.051325: Epoch time: 18.67 s +2024-11-23 04:27:31.954559: +2024-11-23 04:27:31.954817: Epoch 7510 +2024-11-23 04:27:31.954961: Current learning rate: 0.00081 +2024-11-23 04:27:50.193463: train_loss -0.8322 +2024-11-23 04:27:50.193689: val_loss -0.7916 +2024-11-23 04:27:50.193777: Pseudo dice [0.861] +2024-11-23 04:27:50.193857: Epoch time: 18.24 s +2024-11-23 04:27:51.088031: +2024-11-23 04:27:51.088241: Epoch 7511 +2024-11-23 04:27:51.088353: Current learning rate: 0.00081 +2024-11-23 04:28:08.917261: train_loss -0.8266 +2024-11-23 04:28:08.917495: val_loss -0.7702 +2024-11-23 04:28:08.917577: Pseudo dice [0.8539] +2024-11-23 04:28:08.917672: Epoch time: 17.83 s +2024-11-23 04:28:09.801769: +2024-11-23 04:28:09.802002: Epoch 7512 +2024-11-23 04:28:09.802117: Current learning rate: 0.00081 +2024-11-23 04:28:28.342411: train_loss -0.8306 +2024-11-23 04:28:28.342647: val_loss -0.7845 +2024-11-23 04:28:28.342795: Pseudo dice [0.871] +2024-11-23 04:28:28.342900: Epoch time: 18.54 s +2024-11-23 04:28:29.257578: +2024-11-23 04:28:29.257793: Epoch 7513 +2024-11-23 04:28:29.257908: Current learning rate: 0.00081 +2024-11-23 04:28:47.886171: train_loss -0.8346 +2024-11-23 04:28:47.886423: val_loss -0.8011 +2024-11-23 04:28:47.886508: Pseudo dice [0.8558] +2024-11-23 04:28:47.886595: Epoch time: 18.63 s +2024-11-23 04:28:48.801513: +2024-11-23 04:28:48.801740: Epoch 7514 +2024-11-23 04:28:48.801853: Current learning rate: 0.0008 +2024-11-23 04:29:08.189190: train_loss -0.8348 +2024-11-23 04:29:08.189414: val_loss -0.7935 +2024-11-23 04:29:08.189513: Pseudo dice [0.8596] +2024-11-23 04:29:08.189597: Epoch time: 19.39 s +2024-11-23 04:29:09.180465: +2024-11-23 04:29:09.180653: Epoch 7515 +2024-11-23 04:29:09.180766: Current learning rate: 0.0008 +2024-11-23 04:29:26.528580: train_loss -0.8283 +2024-11-23 04:29:26.528816: val_loss -0.7938 +2024-11-23 04:29:26.528896: Pseudo dice [0.8617] +2024-11-23 04:29:26.528973: Epoch time: 17.35 s +2024-11-23 04:29:27.536483: +2024-11-23 04:29:27.536683: Epoch 7516 +2024-11-23 04:29:27.536800: Current learning rate: 0.0008 +2024-11-23 04:29:46.956944: train_loss -0.8299 +2024-11-23 04:29:46.957157: val_loss -0.7744 +2024-11-23 04:29:46.957265: Pseudo dice [0.866] +2024-11-23 04:29:46.957341: Epoch time: 19.42 s +2024-11-23 04:29:48.278353: +2024-11-23 04:29:48.278574: Epoch 7517 +2024-11-23 04:29:48.278688: Current learning rate: 0.0008 +2024-11-23 04:30:06.649692: train_loss -0.8326 +2024-11-23 04:30:06.649909: val_loss -0.7705 +2024-11-23 04:30:06.649992: Pseudo dice [0.8545] +2024-11-23 04:30:06.650083: Epoch time: 18.37 s +2024-11-23 04:30:07.537633: +2024-11-23 04:30:07.537860: Epoch 7518 +2024-11-23 04:30:07.537986: Current learning rate: 0.0008 +2024-11-23 04:30:25.518184: train_loss -0.8289 +2024-11-23 04:30:25.518412: val_loss -0.7917 +2024-11-23 04:30:25.518487: Pseudo dice [0.8635] +2024-11-23 04:30:25.518569: Epoch time: 17.98 s +2024-11-23 04:30:26.405141: +2024-11-23 04:30:26.405417: Epoch 7519 +2024-11-23 04:30:26.405591: Current learning rate: 0.0008 +2024-11-23 04:30:46.368228: train_loss -0.8289 +2024-11-23 04:30:46.368454: val_loss -0.7785 +2024-11-23 04:30:46.368540: Pseudo dice [0.8614] +2024-11-23 04:30:46.368631: Epoch time: 19.96 s +2024-11-23 04:30:47.257658: +2024-11-23 04:30:47.257875: Epoch 7520 +2024-11-23 04:30:47.258000: Current learning rate: 0.00079 +2024-11-23 04:31:05.243475: train_loss -0.8229 +2024-11-23 04:31:05.243704: val_loss -0.7897 +2024-11-23 04:31:05.243800: Pseudo dice [0.857] +2024-11-23 04:31:05.243880: Epoch time: 17.99 s +2024-11-23 04:31:06.143800: +2024-11-23 04:31:06.144033: Epoch 7521 +2024-11-23 04:31:06.144150: Current learning rate: 0.00079 +2024-11-23 04:31:24.704659: train_loss -0.8206 +2024-11-23 04:31:24.704865: val_loss -0.7931 +2024-11-23 04:31:24.704946: Pseudo dice [0.8595] +2024-11-23 04:31:24.705029: Epoch time: 18.56 s +2024-11-23 04:31:25.592435: +2024-11-23 04:31:25.592700: Epoch 7522 +2024-11-23 04:31:25.592817: Current learning rate: 0.00079 +2024-11-23 04:31:44.248946: train_loss -0.8218 +2024-11-23 04:31:44.249175: val_loss -0.7873 +2024-11-23 04:31:44.249269: Pseudo dice [0.8557] +2024-11-23 04:31:44.249439: Epoch time: 18.66 s +2024-11-23 04:31:45.142939: +2024-11-23 04:31:45.143159: Epoch 7523 +2024-11-23 04:31:45.143278: Current learning rate: 0.00079 +2024-11-23 04:32:04.432936: train_loss -0.8325 +2024-11-23 04:32:04.433182: val_loss -0.7843 +2024-11-23 04:32:04.433265: Pseudo dice [0.8575] +2024-11-23 04:32:04.433361: Epoch time: 19.29 s +2024-11-23 04:32:05.324071: +2024-11-23 04:32:05.324359: Epoch 7524 +2024-11-23 04:32:05.324476: Current learning rate: 0.00079 +2024-11-23 04:32:24.110629: train_loss -0.8294 +2024-11-23 04:32:24.110848: val_loss -0.7935 +2024-11-23 04:32:24.110930: Pseudo dice [0.8602] +2024-11-23 04:32:24.111014: Epoch time: 18.79 s +2024-11-23 04:32:25.145463: +2024-11-23 04:32:25.145684: Epoch 7525 +2024-11-23 04:32:25.145792: Current learning rate: 0.00079 +2024-11-23 04:32:42.683383: train_loss -0.8296 +2024-11-23 04:32:42.683595: val_loss -0.7777 +2024-11-23 04:32:42.683699: Pseudo dice [0.8589] +2024-11-23 04:32:42.683783: Epoch time: 17.54 s +2024-11-23 04:32:43.567265: +2024-11-23 04:32:43.567507: Epoch 7526 +2024-11-23 04:32:43.567658: Current learning rate: 0.00079 +2024-11-23 04:33:02.979782: train_loss -0.8253 +2024-11-23 04:33:02.980001: val_loss -0.774 +2024-11-23 04:33:02.980086: Pseudo dice [0.8679] +2024-11-23 04:33:02.980182: Epoch time: 19.41 s +2024-11-23 04:33:03.858875: +2024-11-23 04:33:03.859289: Epoch 7527 +2024-11-23 04:33:03.859423: Current learning rate: 0.00078 +2024-11-23 04:33:22.087173: train_loss -0.8296 +2024-11-23 04:33:22.087405: val_loss -0.7808 +2024-11-23 04:33:22.087482: Pseudo dice [0.8528] +2024-11-23 04:33:22.087584: Epoch time: 18.23 s +2024-11-23 04:33:23.358953: +2024-11-23 04:33:23.359201: Epoch 7528 +2024-11-23 04:33:23.359319: Current learning rate: 0.00078 +2024-11-23 04:33:41.765913: train_loss -0.8244 +2024-11-23 04:33:41.766165: val_loss -0.7815 +2024-11-23 04:33:41.766249: Pseudo dice [0.8588] +2024-11-23 04:33:41.766352: Epoch time: 18.41 s +2024-11-23 04:33:42.652318: +2024-11-23 04:33:42.652530: Epoch 7529 +2024-11-23 04:33:42.652642: Current learning rate: 0.00078 +2024-11-23 04:34:01.717360: train_loss -0.8361 +2024-11-23 04:34:01.717647: val_loss -0.7952 +2024-11-23 04:34:01.717729: Pseudo dice [0.8617] +2024-11-23 04:34:01.717804: Epoch time: 19.07 s +2024-11-23 04:34:02.602383: +2024-11-23 04:34:02.602603: Epoch 7530 +2024-11-23 04:34:02.602722: Current learning rate: 0.00078 +2024-11-23 04:34:21.181627: train_loss -0.8305 +2024-11-23 04:34:21.181865: val_loss -0.7988 +2024-11-23 04:34:21.181944: Pseudo dice [0.8539] +2024-11-23 04:34:21.182025: Epoch time: 18.58 s +2024-11-23 04:34:22.070086: +2024-11-23 04:34:22.070293: Epoch 7531 +2024-11-23 04:34:22.070428: Current learning rate: 0.00078 +2024-11-23 04:34:40.804926: train_loss -0.8368 +2024-11-23 04:34:40.805164: val_loss -0.7664 +2024-11-23 04:34:40.805248: Pseudo dice [0.8638] +2024-11-23 04:34:40.805366: Epoch time: 18.74 s +2024-11-23 04:34:41.697988: +2024-11-23 04:34:41.698205: Epoch 7532 +2024-11-23 04:34:41.698324: Current learning rate: 0.00078 +2024-11-23 04:35:00.094435: train_loss -0.8313 +2024-11-23 04:35:00.094659: val_loss -0.7733 +2024-11-23 04:35:00.094739: Pseudo dice [0.8574] +2024-11-23 04:35:00.094820: Epoch time: 18.4 s +2024-11-23 04:35:00.985860: +2024-11-23 04:35:00.986113: Epoch 7533 +2024-11-23 04:35:00.986236: Current learning rate: 0.00078 +2024-11-23 04:35:20.153456: train_loss -0.8306 +2024-11-23 04:35:20.153665: val_loss -0.7895 +2024-11-23 04:35:20.153741: Pseudo dice [0.8632] +2024-11-23 04:35:20.153825: Epoch time: 19.17 s +2024-11-23 04:35:21.038096: +2024-11-23 04:35:21.038324: Epoch 7534 +2024-11-23 04:35:21.038435: Current learning rate: 0.00077 +2024-11-23 04:35:38.758507: train_loss -0.8335 +2024-11-23 04:35:38.758748: val_loss -0.7681 +2024-11-23 04:35:38.758830: Pseudo dice [0.8636] +2024-11-23 04:35:38.758920: Epoch time: 17.72 s +2024-11-23 04:35:39.703099: +2024-11-23 04:35:39.703315: Epoch 7535 +2024-11-23 04:35:39.703444: Current learning rate: 0.00077 +2024-11-23 04:35:58.537343: train_loss -0.8357 +2024-11-23 04:35:58.537591: val_loss -0.7865 +2024-11-23 04:35:58.537680: Pseudo dice [0.87] +2024-11-23 04:35:58.537762: Epoch time: 18.84 s +2024-11-23 04:35:59.425914: +2024-11-23 04:35:59.426149: Epoch 7536 +2024-11-23 04:35:59.426268: Current learning rate: 0.00077 +2024-11-23 04:36:17.560023: train_loss -0.83 +2024-11-23 04:36:17.573260: val_loss -0.8035 +2024-11-23 04:36:17.573372: Pseudo dice [0.8729] +2024-11-23 04:36:17.573454: Epoch time: 18.13 s +2024-11-23 04:36:18.482867: +2024-11-23 04:36:18.483094: Epoch 7537 +2024-11-23 04:36:18.483222: Current learning rate: 0.00077 +2024-11-23 04:36:37.723372: train_loss -0.8333 +2024-11-23 04:36:37.723624: val_loss -0.8 +2024-11-23 04:36:37.723728: Pseudo dice [0.8592] +2024-11-23 04:36:37.723806: Epoch time: 19.24 s +2024-11-23 04:36:38.612305: +2024-11-23 04:36:38.612534: Epoch 7538 +2024-11-23 04:36:38.612650: Current learning rate: 0.00077 +2024-11-23 04:36:57.065085: train_loss -0.8309 +2024-11-23 04:36:57.065341: val_loss -0.7923 +2024-11-23 04:36:57.065433: Pseudo dice [0.8708] +2024-11-23 04:36:57.065523: Epoch time: 18.45 s +2024-11-23 04:36:57.993452: +2024-11-23 04:36:57.993850: Epoch 7539 +2024-11-23 04:36:57.993984: Current learning rate: 0.00077 +2024-11-23 04:37:16.092808: train_loss -0.8328 +2024-11-23 04:37:16.093019: val_loss -0.7911 +2024-11-23 04:37:16.093104: Pseudo dice [0.8635] +2024-11-23 04:37:16.093193: Epoch time: 18.1 s +2024-11-23 04:37:17.374724: +2024-11-23 04:37:17.374978: Epoch 7540 +2024-11-23 04:37:17.375115: Current learning rate: 0.00077 +2024-11-23 04:37:35.128046: train_loss -0.8371 +2024-11-23 04:37:35.133480: val_loss -0.8035 +2024-11-23 04:37:35.133628: Pseudo dice [0.8711] +2024-11-23 04:37:35.133729: Epoch time: 17.75 s +2024-11-23 04:37:36.118204: +2024-11-23 04:37:36.118442: Epoch 7541 +2024-11-23 04:37:36.118557: Current learning rate: 0.00076 +2024-11-23 04:37:54.376045: train_loss -0.8303 +2024-11-23 04:37:54.376257: val_loss -0.7893 +2024-11-23 04:37:54.376345: Pseudo dice [0.8582] +2024-11-23 04:37:54.376427: Epoch time: 18.26 s +2024-11-23 04:37:55.265818: +2024-11-23 04:37:55.266018: Epoch 7542 +2024-11-23 04:37:55.266148: Current learning rate: 0.00076 +2024-11-23 04:38:14.095510: train_loss -0.821 +2024-11-23 04:38:14.095801: val_loss -0.7944 +2024-11-23 04:38:14.095886: Pseudo dice [0.8557] +2024-11-23 04:38:14.096040: Epoch time: 18.83 s +2024-11-23 04:38:15.098753: +2024-11-23 04:38:15.099008: Epoch 7543 +2024-11-23 04:38:15.099136: Current learning rate: 0.00076 +2024-11-23 04:38:32.983579: train_loss -0.8344 +2024-11-23 04:38:32.983803: val_loss -0.7887 +2024-11-23 04:38:32.983907: Pseudo dice [0.8592] +2024-11-23 04:38:32.983986: Epoch time: 17.89 s +2024-11-23 04:38:33.883399: +2024-11-23 04:38:33.883640: Epoch 7544 +2024-11-23 04:38:33.883770: Current learning rate: 0.00076 +2024-11-23 04:38:51.272317: train_loss -0.8333 +2024-11-23 04:38:51.272550: val_loss -0.7705 +2024-11-23 04:38:51.272633: Pseudo dice [0.8647] +2024-11-23 04:38:51.272965: Epoch time: 17.39 s +2024-11-23 04:38:52.159765: +2024-11-23 04:38:52.159966: Epoch 7545 +2024-11-23 04:38:52.160087: Current learning rate: 0.00076 +2024-11-23 04:39:10.025751: train_loss -0.826 +2024-11-23 04:39:10.028178: val_loss -0.7771 +2024-11-23 04:39:10.028282: Pseudo dice [0.8646] +2024-11-23 04:39:10.028370: Epoch time: 17.87 s +2024-11-23 04:39:11.098949: +2024-11-23 04:39:11.099178: Epoch 7546 +2024-11-23 04:39:11.099297: Current learning rate: 0.00076 +2024-11-23 04:39:29.263731: train_loss -0.8269 +2024-11-23 04:39:29.264003: val_loss -0.7708 +2024-11-23 04:39:29.264094: Pseudo dice [0.8737] +2024-11-23 04:39:29.264183: Epoch time: 18.17 s +2024-11-23 04:39:30.250340: +2024-11-23 04:39:30.250570: Epoch 7547 +2024-11-23 04:39:30.250691: Current learning rate: 0.00075 +2024-11-23 04:39:49.187574: train_loss -0.8344 +2024-11-23 04:39:49.187778: val_loss -0.7833 +2024-11-23 04:39:49.187862: Pseudo dice [0.8627] +2024-11-23 04:39:49.187956: Epoch time: 18.94 s +2024-11-23 04:39:50.254192: +2024-11-23 04:39:50.254392: Epoch 7548 +2024-11-23 04:39:50.254511: Current learning rate: 0.00075 +2024-11-23 04:40:08.298867: train_loss -0.8371 +2024-11-23 04:40:08.299094: val_loss -0.783 +2024-11-23 04:40:08.299173: Pseudo dice [0.8507] +2024-11-23 04:40:08.301499: Epoch time: 18.05 s +2024-11-23 04:40:09.271071: +2024-11-23 04:40:09.271278: Epoch 7549 +2024-11-23 04:40:09.271406: Current learning rate: 0.00075 +2024-11-23 04:40:28.188220: train_loss -0.8238 +2024-11-23 04:40:28.188434: val_loss -0.7911 +2024-11-23 04:40:28.188522: Pseudo dice [0.8673] +2024-11-23 04:40:28.188615: Epoch time: 18.92 s +2024-11-23 04:40:29.427489: +2024-11-23 04:40:29.427910: Epoch 7550 +2024-11-23 04:40:29.428042: Current learning rate: 0.00075 +2024-11-23 04:40:48.406698: train_loss -0.8256 +2024-11-23 04:40:48.406979: val_loss -0.7799 +2024-11-23 04:40:48.407082: Pseudo dice [0.8641] +2024-11-23 04:40:48.407165: Epoch time: 18.98 s +2024-11-23 04:40:49.741755: +2024-11-23 04:40:49.741969: Epoch 7551 +2024-11-23 04:40:49.742104: Current learning rate: 0.00075 +2024-11-23 04:41:08.207857: train_loss -0.8325 +2024-11-23 04:41:08.208133: val_loss -0.7781 +2024-11-23 04:41:08.208215: Pseudo dice [0.8502] +2024-11-23 04:41:08.208298: Epoch time: 18.47 s +2024-11-23 04:41:09.102610: +2024-11-23 04:41:09.102846: Epoch 7552 +2024-11-23 04:41:09.102962: Current learning rate: 0.00075 +2024-11-23 04:41:27.485574: train_loss -0.8328 +2024-11-23 04:41:27.490942: val_loss -0.8009 +2024-11-23 04:41:27.491096: Pseudo dice [0.8691] +2024-11-23 04:41:27.491177: Epoch time: 18.38 s +2024-11-23 04:41:28.485865: +2024-11-23 04:41:28.486094: Epoch 7553 +2024-11-23 04:41:28.486203: Current learning rate: 0.00075 +2024-11-23 04:41:45.235862: train_loss -0.8309 +2024-11-23 04:41:45.236095: val_loss -0.7862 +2024-11-23 04:41:45.236188: Pseudo dice [0.8688] +2024-11-23 04:41:45.236276: Epoch time: 16.75 s +2024-11-23 04:41:46.224751: +2024-11-23 04:41:46.224970: Epoch 7554 +2024-11-23 04:41:46.225109: Current learning rate: 0.00074 +2024-11-23 04:42:04.779811: train_loss -0.8308 +2024-11-23 04:42:04.780038: val_loss -0.7897 +2024-11-23 04:42:04.780122: Pseudo dice [0.866] +2024-11-23 04:42:04.780212: Epoch time: 18.56 s +2024-11-23 04:42:05.663228: +2024-11-23 04:42:05.663431: Epoch 7555 +2024-11-23 04:42:05.663545: Current learning rate: 0.00074 +2024-11-23 04:42:25.177742: train_loss -0.8374 +2024-11-23 04:42:25.180159: val_loss -0.7814 +2024-11-23 04:42:25.180301: Pseudo dice [0.8612] +2024-11-23 04:42:25.180386: Epoch time: 19.52 s +2024-11-23 04:42:26.107410: +2024-11-23 04:42:26.107633: Epoch 7556 +2024-11-23 04:42:26.107742: Current learning rate: 0.00074 +2024-11-23 04:42:44.285852: train_loss -0.828 +2024-11-23 04:42:44.286097: val_loss -0.7686 +2024-11-23 04:42:44.286197: Pseudo dice [0.8581] +2024-11-23 04:42:44.286282: Epoch time: 18.17 s +2024-11-23 04:42:45.342940: +2024-11-23 04:42:45.343169: Epoch 7557 +2024-11-23 04:42:45.343284: Current learning rate: 0.00074 +2024-11-23 04:43:03.402183: train_loss -0.8291 +2024-11-23 04:43:03.402500: val_loss -0.7853 +2024-11-23 04:43:03.402605: Pseudo dice [0.861] +2024-11-23 04:43:03.402690: Epoch time: 18.06 s +2024-11-23 04:43:04.291973: +2024-11-23 04:43:04.292177: Epoch 7558 +2024-11-23 04:43:04.292294: Current learning rate: 0.00074 +2024-11-23 04:43:22.836539: train_loss -0.8278 +2024-11-23 04:43:22.838933: val_loss -0.7819 +2024-11-23 04:43:22.839034: Pseudo dice [0.8608] +2024-11-23 04:43:22.839135: Epoch time: 18.55 s +2024-11-23 04:43:23.753641: +2024-11-23 04:43:23.753850: Epoch 7559 +2024-11-23 04:43:23.753962: Current learning rate: 0.00074 +2024-11-23 04:43:41.547446: train_loss -0.8283 +2024-11-23 04:43:41.547658: val_loss -0.7807 +2024-11-23 04:43:41.547743: Pseudo dice [0.8631] +2024-11-23 04:43:41.547820: Epoch time: 17.79 s +2024-11-23 04:43:42.432389: +2024-11-23 04:43:42.432626: Epoch 7560 +2024-11-23 04:43:42.432762: Current learning rate: 0.00074 +2024-11-23 04:44:01.755489: train_loss -0.8312 +2024-11-23 04:44:01.755718: val_loss -0.7497 +2024-11-23 04:44:01.755844: Pseudo dice [0.8483] +2024-11-23 04:44:01.755929: Epoch time: 19.32 s +2024-11-23 04:44:02.640048: +2024-11-23 04:44:02.640484: Epoch 7561 +2024-11-23 04:44:02.640631: Current learning rate: 0.00073 +2024-11-23 04:44:21.953887: train_loss -0.8333 +2024-11-23 04:44:21.954213: val_loss -0.781 +2024-11-23 04:44:21.954295: Pseudo dice [0.8513] +2024-11-23 04:44:21.954382: Epoch time: 19.31 s +2024-11-23 04:44:23.237550: +2024-11-23 04:44:23.237747: Epoch 7562 +2024-11-23 04:44:23.237864: Current learning rate: 0.00073 +2024-11-23 04:44:40.775198: train_loss -0.8326 +2024-11-23 04:44:40.775432: val_loss -0.7725 +2024-11-23 04:44:40.775514: Pseudo dice [0.8496] +2024-11-23 04:44:40.775590: Epoch time: 17.54 s +2024-11-23 04:44:41.658217: +2024-11-23 04:44:41.658447: Epoch 7563 +2024-11-23 04:44:41.658561: Current learning rate: 0.00073 +2024-11-23 04:45:00.946393: train_loss -0.8269 +2024-11-23 04:45:00.946612: val_loss -0.7884 +2024-11-23 04:45:00.946698: Pseudo dice [0.8616] +2024-11-23 04:45:00.946777: Epoch time: 19.29 s +2024-11-23 04:45:01.829550: +2024-11-23 04:45:01.829760: Epoch 7564 +2024-11-23 04:45:01.829872: Current learning rate: 0.00073 +2024-11-23 04:45:20.856367: train_loss -0.8282 +2024-11-23 04:45:20.856659: val_loss -0.7972 +2024-11-23 04:45:20.856750: Pseudo dice [0.8701] +2024-11-23 04:45:20.856829: Epoch time: 19.03 s +2024-11-23 04:45:21.810546: +2024-11-23 04:45:21.810782: Epoch 7565 +2024-11-23 04:45:21.810899: Current learning rate: 0.00073 +2024-11-23 04:45:40.127512: train_loss -0.8339 +2024-11-23 04:45:40.127768: val_loss -0.7938 +2024-11-23 04:45:40.127852: Pseudo dice [0.8544] +2024-11-23 04:45:40.127961: Epoch time: 18.32 s +2024-11-23 04:45:41.016076: +2024-11-23 04:45:41.016355: Epoch 7566 +2024-11-23 04:45:41.016512: Current learning rate: 0.00073 +2024-11-23 04:45:59.934701: train_loss -0.8294 +2024-11-23 04:45:59.934912: val_loss -0.7602 +2024-11-23 04:45:59.934994: Pseudo dice [0.8553] +2024-11-23 04:45:59.935078: Epoch time: 18.92 s +2024-11-23 04:46:00.823092: +2024-11-23 04:46:00.823295: Epoch 7567 +2024-11-23 04:46:00.823408: Current learning rate: 0.00072 +2024-11-23 04:46:19.267462: train_loss -0.8341 +2024-11-23 04:46:19.267689: val_loss -0.7817 +2024-11-23 04:46:19.267766: Pseudo dice [0.8695] +2024-11-23 04:46:19.267841: Epoch time: 18.45 s +2024-11-23 04:46:20.266388: +2024-11-23 04:46:20.266624: Epoch 7568 +2024-11-23 04:46:20.266749: Current learning rate: 0.00072 +2024-11-23 04:46:39.808140: train_loss -0.8388 +2024-11-23 04:46:39.808346: val_loss -0.8017 +2024-11-23 04:46:39.808425: Pseudo dice [0.8713] +2024-11-23 04:46:39.808500: Epoch time: 19.54 s +2024-11-23 04:46:40.698334: +2024-11-23 04:46:40.698561: Epoch 7569 +2024-11-23 04:46:40.698675: Current learning rate: 0.00072 +2024-11-23 04:46:59.085001: train_loss -0.8324 +2024-11-23 04:46:59.085257: val_loss -0.7899 +2024-11-23 04:46:59.085338: Pseudo dice [0.8643] +2024-11-23 04:46:59.085419: Epoch time: 18.39 s +2024-11-23 04:46:59.976747: +2024-11-23 04:46:59.976979: Epoch 7570 +2024-11-23 04:46:59.977102: Current learning rate: 0.00072 +2024-11-23 04:47:17.645981: train_loss -0.8306 +2024-11-23 04:47:17.646244: val_loss -0.7687 +2024-11-23 04:47:17.646327: Pseudo dice [0.871] +2024-11-23 04:47:17.646642: Epoch time: 17.67 s +2024-11-23 04:47:18.553094: +2024-11-23 04:47:18.553345: Epoch 7571 +2024-11-23 04:47:18.553473: Current learning rate: 0.00072 +2024-11-23 04:47:36.614830: train_loss -0.8327 +2024-11-23 04:47:36.615049: val_loss -0.7633 +2024-11-23 04:47:36.615140: Pseudo dice [0.8549] +2024-11-23 04:47:36.615266: Epoch time: 18.06 s +2024-11-23 04:47:37.503481: +2024-11-23 04:47:37.503712: Epoch 7572 +2024-11-23 04:47:37.503832: Current learning rate: 0.00072 +2024-11-23 04:47:55.857942: train_loss -0.8306 +2024-11-23 04:47:55.859307: val_loss -0.7744 +2024-11-23 04:47:55.859422: Pseudo dice [0.8584] +2024-11-23 04:47:55.859517: Epoch time: 18.36 s +2024-11-23 04:47:56.801233: +2024-11-23 04:47:56.801444: Epoch 7573 +2024-11-23 04:47:56.801559: Current learning rate: 0.00072 +2024-11-23 04:48:16.137209: train_loss -0.8344 +2024-11-23 04:48:16.137504: val_loss -0.7716 +2024-11-23 04:48:16.137601: Pseudo dice [0.866] +2024-11-23 04:48:16.137693: Epoch time: 19.34 s +2024-11-23 04:48:17.502514: +2024-11-23 04:48:17.502740: Epoch 7574 +2024-11-23 04:48:17.502860: Current learning rate: 0.00071 +2024-11-23 04:48:36.378745: train_loss -0.8307 +2024-11-23 04:48:36.378979: val_loss -0.7975 +2024-11-23 04:48:36.379075: Pseudo dice [0.8702] +2024-11-23 04:48:36.379164: Epoch time: 18.88 s +2024-11-23 04:48:37.373033: +2024-11-23 04:48:37.373258: Epoch 7575 +2024-11-23 04:48:37.373370: Current learning rate: 0.00071 +2024-11-23 04:48:56.475053: train_loss -0.8328 +2024-11-23 04:48:56.475291: val_loss -0.7962 +2024-11-23 04:48:56.475370: Pseudo dice [0.8782] +2024-11-23 04:48:56.475472: Epoch time: 19.1 s +2024-11-23 04:48:57.468582: +2024-11-23 04:48:57.468794: Epoch 7576 +2024-11-23 04:48:57.468920: Current learning rate: 0.00071 +2024-11-23 04:49:15.781078: train_loss -0.8334 +2024-11-23 04:49:15.781330: val_loss -0.793 +2024-11-23 04:49:15.781418: Pseudo dice [0.8644] +2024-11-23 04:49:15.781520: Epoch time: 18.31 s +2024-11-23 04:49:16.683639: +2024-11-23 04:49:16.683851: Epoch 7577 +2024-11-23 04:49:16.683973: Current learning rate: 0.00071 +2024-11-23 04:49:35.248371: train_loss -0.8321 +2024-11-23 04:49:35.248607: val_loss -0.7737 +2024-11-23 04:49:35.248699: Pseudo dice [0.8524] +2024-11-23 04:49:35.248832: Epoch time: 18.57 s +2024-11-23 04:49:36.137201: +2024-11-23 04:49:36.137449: Epoch 7578 +2024-11-23 04:49:36.137568: Current learning rate: 0.00071 +2024-11-23 04:49:54.060896: train_loss -0.8303 +2024-11-23 04:49:54.061108: val_loss -0.7888 +2024-11-23 04:49:54.061190: Pseudo dice [0.8515] +2024-11-23 04:49:54.061265: Epoch time: 17.92 s +2024-11-23 04:49:54.945321: +2024-11-23 04:49:54.945534: Epoch 7579 +2024-11-23 04:49:54.945652: Current learning rate: 0.00071 +2024-11-23 04:50:13.640114: train_loss -0.8338 +2024-11-23 04:50:13.640361: val_loss -0.7855 +2024-11-23 04:50:13.640440: Pseudo dice [0.8652] +2024-11-23 04:50:13.640523: Epoch time: 18.69 s +2024-11-23 04:50:14.550783: +2024-11-23 04:50:14.551029: Epoch 7580 +2024-11-23 04:50:14.551152: Current learning rate: 0.0007 +2024-11-23 04:50:32.327118: train_loss -0.8339 +2024-11-23 04:50:32.327367: val_loss -0.7822 +2024-11-23 04:50:32.327445: Pseudo dice [0.8721] +2024-11-23 04:50:32.327537: Epoch time: 17.78 s +2024-11-23 04:50:33.244514: +2024-11-23 04:50:33.244724: Epoch 7581 +2024-11-23 04:50:33.244842: Current learning rate: 0.0007 +2024-11-23 04:50:52.361098: train_loss -0.8282 +2024-11-23 04:50:52.361300: val_loss -0.7727 +2024-11-23 04:50:52.361384: Pseudo dice [0.8636] +2024-11-23 04:50:52.361459: Epoch time: 19.12 s +2024-11-23 04:50:53.245625: +2024-11-23 04:50:53.245852: Epoch 7582 +2024-11-23 04:50:53.245979: Current learning rate: 0.0007 +2024-11-23 04:51:12.399868: train_loss -0.826 +2024-11-23 04:51:12.400085: val_loss -0.7808 +2024-11-23 04:51:12.400176: Pseudo dice [0.8573] +2024-11-23 04:51:12.400255: Epoch time: 19.16 s +2024-11-23 04:51:13.288856: +2024-11-23 04:51:13.289077: Epoch 7583 +2024-11-23 04:51:13.289186: Current learning rate: 0.0007 +2024-11-23 04:51:31.800692: train_loss -0.8319 +2024-11-23 04:51:31.800910: val_loss -0.7551 +2024-11-23 04:51:31.800986: Pseudo dice [0.8659] +2024-11-23 04:51:31.801069: Epoch time: 18.51 s +2024-11-23 04:51:32.863253: +2024-11-23 04:51:32.863465: Epoch 7584 +2024-11-23 04:51:32.863605: Current learning rate: 0.0007 +2024-11-23 04:51:51.410752: train_loss -0.8284 +2024-11-23 04:51:51.410988: val_loss -0.7702 +2024-11-23 04:51:51.416231: Pseudo dice [0.8558] +2024-11-23 04:51:51.416403: Epoch time: 18.55 s +2024-11-23 04:51:52.887632: +2024-11-23 04:51:52.887842: Epoch 7585 +2024-11-23 04:51:52.887955: Current learning rate: 0.0007 +2024-11-23 04:52:11.771199: train_loss -0.8326 +2024-11-23 04:52:11.771443: val_loss -0.775 +2024-11-23 04:52:11.771532: Pseudo dice [0.8788] +2024-11-23 04:52:11.774156: Epoch time: 18.88 s +2024-11-23 04:52:12.829076: +2024-11-23 04:52:12.829307: Epoch 7586 +2024-11-23 04:52:12.829422: Current learning rate: 0.0007 +2024-11-23 04:52:32.002600: train_loss -0.83 +2024-11-23 04:52:32.002810: val_loss -0.7997 +2024-11-23 04:52:32.002887: Pseudo dice [0.8661] +2024-11-23 04:52:32.002986: Epoch time: 19.17 s +2024-11-23 04:52:32.888197: +2024-11-23 04:52:32.888407: Epoch 7587 +2024-11-23 04:52:32.888538: Current learning rate: 0.00069 +2024-11-23 04:52:51.203602: train_loss -0.832 +2024-11-23 04:52:51.203813: val_loss -0.8101 +2024-11-23 04:52:51.204074: Pseudo dice [0.8719] +2024-11-23 04:52:51.204239: Epoch time: 18.32 s +2024-11-23 04:52:52.096953: +2024-11-23 04:52:52.097185: Epoch 7588 +2024-11-23 04:52:52.097311: Current learning rate: 0.00069 +2024-11-23 04:53:11.101040: train_loss -0.8303 +2024-11-23 04:53:11.101279: val_loss -0.7845 +2024-11-23 04:53:11.103552: Pseudo dice [0.8605] +2024-11-23 04:53:11.103657: Epoch time: 19.01 s +2024-11-23 04:53:12.018479: +2024-11-23 04:53:12.018687: Epoch 7589 +2024-11-23 04:53:12.018817: Current learning rate: 0.00069 +2024-11-23 04:53:31.131705: train_loss -0.835 +2024-11-23 04:53:31.131927: val_loss -0.7803 +2024-11-23 04:53:31.132012: Pseudo dice [0.878] +2024-11-23 04:53:31.132109: Epoch time: 19.11 s +2024-11-23 04:53:32.027585: +2024-11-23 04:53:32.027805: Epoch 7590 +2024-11-23 04:53:32.027936: Current learning rate: 0.00069 +2024-11-23 04:53:50.451786: train_loss -0.8311 +2024-11-23 04:53:50.451999: val_loss -0.8019 +2024-11-23 04:53:50.452150: Pseudo dice [0.8717] +2024-11-23 04:53:50.452261: Epoch time: 18.43 s +2024-11-23 04:53:51.347044: +2024-11-23 04:53:51.347268: Epoch 7591 +2024-11-23 04:53:51.347392: Current learning rate: 0.00069 +2024-11-23 04:54:10.772586: train_loss -0.8281 +2024-11-23 04:54:10.772806: val_loss -0.7897 +2024-11-23 04:54:10.772895: Pseudo dice [0.8674] +2024-11-23 04:54:10.772990: Epoch time: 19.43 s +2024-11-23 04:54:10.773056: Yayy! New best EMA pseudo Dice: 0.8666 +2024-11-23 04:54:12.010450: +2024-11-23 04:54:12.010661: Epoch 7592 +2024-11-23 04:54:12.010794: Current learning rate: 0.00069 +2024-11-23 04:54:30.835897: train_loss -0.837 +2024-11-23 04:54:30.836142: val_loss -0.7873 +2024-11-23 04:54:30.836236: Pseudo dice [0.8641] +2024-11-23 04:54:30.836318: Epoch time: 18.83 s +2024-11-23 04:54:31.723362: +2024-11-23 04:54:31.723549: Epoch 7593 +2024-11-23 04:54:31.723687: Current learning rate: 0.00069 +2024-11-23 04:54:50.182315: train_loss -0.8331 +2024-11-23 04:54:50.182540: val_loss -0.7812 +2024-11-23 04:54:50.182630: Pseudo dice [0.8497] +2024-11-23 04:54:50.182710: Epoch time: 18.46 s +2024-11-23 04:54:51.070352: +2024-11-23 04:54:51.070560: Epoch 7594 +2024-11-23 04:54:51.070691: Current learning rate: 0.00068 +2024-11-23 04:55:09.693418: train_loss -0.8303 +2024-11-23 04:55:09.693634: val_loss -0.7794 +2024-11-23 04:55:09.693721: Pseudo dice [0.8523] +2024-11-23 04:55:09.693801: Epoch time: 18.62 s +2024-11-23 04:55:10.578637: +2024-11-23 04:55:10.578860: Epoch 7595 +2024-11-23 04:55:10.579005: Current learning rate: 0.00068 +2024-11-23 04:55:29.504537: train_loss -0.8375 +2024-11-23 04:55:29.504812: val_loss -0.7715 +2024-11-23 04:55:29.504920: Pseudo dice [0.8598] +2024-11-23 04:55:29.505074: Epoch time: 18.93 s +2024-11-23 04:55:30.402124: +2024-11-23 04:55:30.402337: Epoch 7596 +2024-11-23 04:55:30.402452: Current learning rate: 0.00068 +2024-11-23 04:55:49.299329: train_loss -0.8349 +2024-11-23 04:55:49.299750: val_loss -0.8065 +2024-11-23 04:55:49.299848: Pseudo dice [0.8649] +2024-11-23 04:55:49.299934: Epoch time: 18.9 s +2024-11-23 04:55:50.588517: +2024-11-23 04:55:50.588746: Epoch 7597 +2024-11-23 04:55:50.588855: Current learning rate: 0.00068 +2024-11-23 04:56:09.964392: train_loss -0.8326 +2024-11-23 04:56:09.964605: val_loss -0.7951 +2024-11-23 04:56:09.964686: Pseudo dice [0.853] +2024-11-23 04:56:09.964760: Epoch time: 19.38 s +2024-11-23 04:56:10.846817: +2024-11-23 04:56:10.847034: Epoch 7598 +2024-11-23 04:56:10.847153: Current learning rate: 0.00068 +2024-11-23 04:56:30.197882: train_loss -0.8311 +2024-11-23 04:56:30.200243: val_loss -0.7867 +2024-11-23 04:56:30.200395: Pseudo dice [0.861] +2024-11-23 04:56:30.200478: Epoch time: 19.35 s +2024-11-23 04:56:31.126974: +2024-11-23 04:56:31.127198: Epoch 7599 +2024-11-23 04:56:31.127312: Current learning rate: 0.00068 +2024-11-23 04:56:49.919119: train_loss -0.8312 +2024-11-23 04:56:49.919362: val_loss -0.8078 +2024-11-23 04:56:49.919440: Pseudo dice [0.8645] +2024-11-23 04:56:49.919556: Epoch time: 18.79 s +2024-11-23 04:56:51.178638: +2024-11-23 04:56:51.178854: Epoch 7600 +2024-11-23 04:56:51.178980: Current learning rate: 0.00067 +2024-11-23 04:57:09.620393: train_loss -0.8249 +2024-11-23 04:57:09.620610: val_loss -0.7886 +2024-11-23 04:57:09.620695: Pseudo dice [0.8626] +2024-11-23 04:57:09.620779: Epoch time: 18.44 s +2024-11-23 04:57:10.513316: +2024-11-23 04:57:10.513514: Epoch 7601 +2024-11-23 04:57:10.513645: Current learning rate: 0.00067 +2024-11-23 04:57:29.575884: train_loss -0.831 +2024-11-23 04:57:29.576117: val_loss -0.7841 +2024-11-23 04:57:29.576195: Pseudo dice [0.8626] +2024-11-23 04:57:29.576275: Epoch time: 19.06 s +2024-11-23 04:57:30.668014: +2024-11-23 04:57:30.668232: Epoch 7602 +2024-11-23 04:57:30.668364: Current learning rate: 0.00067 +2024-11-23 04:57:48.793500: train_loss -0.8298 +2024-11-23 04:57:48.793811: val_loss -0.7887 +2024-11-23 04:57:48.793897: Pseudo dice [0.8723] +2024-11-23 04:57:48.793976: Epoch time: 18.13 s +2024-11-23 04:57:49.689686: +2024-11-23 04:57:49.689894: Epoch 7603 +2024-11-23 04:57:49.690019: Current learning rate: 0.00067 +2024-11-23 04:58:08.153373: train_loss -0.8221 +2024-11-23 04:58:08.153615: val_loss -0.7918 +2024-11-23 04:58:08.153710: Pseudo dice [0.8598] +2024-11-23 04:58:08.153816: Epoch time: 18.46 s +2024-11-23 04:58:09.042179: +2024-11-23 04:58:09.042388: Epoch 7604 +2024-11-23 04:58:09.042506: Current learning rate: 0.00067 +2024-11-23 04:58:27.311034: train_loss -0.8309 +2024-11-23 04:58:27.311251: val_loss -0.7814 +2024-11-23 04:58:27.311328: Pseudo dice [0.8657] +2024-11-23 04:58:27.311403: Epoch time: 18.27 s +2024-11-23 04:58:28.200538: +2024-11-23 04:58:28.200751: Epoch 7605 +2024-11-23 04:58:28.200866: Current learning rate: 0.00067 +2024-11-23 04:58:46.742921: train_loss -0.831 +2024-11-23 04:58:46.743141: val_loss -0.7861 +2024-11-23 04:58:46.743217: Pseudo dice [0.8498] +2024-11-23 04:58:46.743293: Epoch time: 18.54 s +2024-11-23 04:58:47.624872: +2024-11-23 04:58:47.625088: Epoch 7606 +2024-11-23 04:58:47.625200: Current learning rate: 0.00067 +2024-11-23 04:59:05.917512: train_loss -0.8388 +2024-11-23 04:59:05.917730: val_loss -0.799 +2024-11-23 04:59:05.917823: Pseudo dice [0.868] +2024-11-23 04:59:05.917899: Epoch time: 18.29 s +2024-11-23 04:59:06.837609: +2024-11-23 04:59:06.837895: Epoch 7607 +2024-11-23 04:59:06.838026: Current learning rate: 0.00066 +2024-11-23 04:59:26.035038: train_loss -0.8315 +2024-11-23 04:59:26.040491: val_loss -0.7799 +2024-11-23 04:59:26.040597: Pseudo dice [0.8545] +2024-11-23 04:59:26.040686: Epoch time: 19.2 s +2024-11-23 04:59:27.358211: +2024-11-23 04:59:27.358416: Epoch 7608 +2024-11-23 04:59:27.358546: Current learning rate: 0.00066 +2024-11-23 04:59:46.034018: train_loss -0.8326 +2024-11-23 04:59:46.034260: val_loss -0.7817 +2024-11-23 04:59:46.034348: Pseudo dice [0.8546] +2024-11-23 04:59:46.034427: Epoch time: 18.68 s +2024-11-23 04:59:46.919320: +2024-11-23 04:59:46.919532: Epoch 7609 +2024-11-23 04:59:46.919662: Current learning rate: 0.00066 +2024-11-23 05:00:05.339142: train_loss -0.8343 +2024-11-23 05:00:05.339367: val_loss -0.7919 +2024-11-23 05:00:05.339462: Pseudo dice [0.8627] +2024-11-23 05:00:05.339549: Epoch time: 18.42 s +2024-11-23 05:00:06.232693: +2024-11-23 05:00:06.232938: Epoch 7610 +2024-11-23 05:00:06.233053: Current learning rate: 0.00066 +2024-11-23 05:00:24.457303: train_loss -0.8326 +2024-11-23 05:00:24.457522: val_loss -0.7979 +2024-11-23 05:00:24.457599: Pseudo dice [0.8663] +2024-11-23 05:00:24.457682: Epoch time: 18.23 s +2024-11-23 05:00:25.349036: +2024-11-23 05:00:25.349307: Epoch 7611 +2024-11-23 05:00:25.349425: Current learning rate: 0.00066 +2024-11-23 05:00:42.824702: train_loss -0.8354 +2024-11-23 05:00:42.824951: val_loss -0.7692 +2024-11-23 05:00:42.825053: Pseudo dice [0.8601] +2024-11-23 05:00:42.825168: Epoch time: 17.48 s +2024-11-23 05:00:43.752187: +2024-11-23 05:00:43.752382: Epoch 7612 +2024-11-23 05:00:43.752497: Current learning rate: 0.00066 +2024-11-23 05:01:01.815369: train_loss -0.8357 +2024-11-23 05:01:01.815647: val_loss -0.7931 +2024-11-23 05:01:01.815735: Pseudo dice [0.8677] +2024-11-23 05:01:01.815817: Epoch time: 18.06 s +2024-11-23 05:01:02.707892: +2024-11-23 05:01:02.708110: Epoch 7613 +2024-11-23 05:01:02.708245: Current learning rate: 0.00065 +2024-11-23 05:01:20.634952: train_loss -0.833 +2024-11-23 05:01:20.635184: val_loss -0.7936 +2024-11-23 05:01:20.635274: Pseudo dice [0.8635] +2024-11-23 05:01:20.635351: Epoch time: 17.93 s +2024-11-23 05:01:21.546902: +2024-11-23 05:01:21.547133: Epoch 7614 +2024-11-23 05:01:21.547247: Current learning rate: 0.00065 +2024-11-23 05:01:39.522813: train_loss -0.8328 +2024-11-23 05:01:39.523048: val_loss -0.773 +2024-11-23 05:01:39.523147: Pseudo dice [0.8563] +2024-11-23 05:01:39.523239: Epoch time: 17.98 s +2024-11-23 05:01:40.415616: +2024-11-23 05:01:40.415841: Epoch 7615 +2024-11-23 05:01:40.415962: Current learning rate: 0.00065 +2024-11-23 05:01:59.133087: train_loss -0.839 +2024-11-23 05:01:59.133287: val_loss -0.793 +2024-11-23 05:01:59.133365: Pseudo dice [0.8719] +2024-11-23 05:01:59.133443: Epoch time: 18.72 s +2024-11-23 05:02:00.033125: +2024-11-23 05:02:00.033346: Epoch 7616 +2024-11-23 05:02:00.033464: Current learning rate: 0.00065 +2024-11-23 05:02:19.353001: train_loss -0.8339 +2024-11-23 05:02:19.353219: val_loss -0.7719 +2024-11-23 05:02:19.353304: Pseudo dice [0.8646] +2024-11-23 05:02:19.353457: Epoch time: 19.32 s +2024-11-23 05:02:20.237100: +2024-11-23 05:02:20.237318: Epoch 7617 +2024-11-23 05:02:20.237435: Current learning rate: 0.00065 +2024-11-23 05:02:38.759300: train_loss -0.8304 +2024-11-23 05:02:38.759513: val_loss -0.775 +2024-11-23 05:02:38.759592: Pseudo dice [0.8703] +2024-11-23 05:02:38.761848: Epoch time: 18.52 s +2024-11-23 05:02:39.758221: +2024-11-23 05:02:39.758435: Epoch 7618 +2024-11-23 05:02:39.758577: Current learning rate: 0.00065 +2024-11-23 05:02:58.552402: train_loss -0.8398 +2024-11-23 05:02:58.552650: val_loss -0.7768 +2024-11-23 05:02:58.552735: Pseudo dice [0.8658] +2024-11-23 05:02:58.552825: Epoch time: 18.8 s +2024-11-23 05:02:59.437289: +2024-11-23 05:02:59.437498: Epoch 7619 +2024-11-23 05:02:59.437608: Current learning rate: 0.00065 +2024-11-23 05:03:17.580883: train_loss -0.8309 +2024-11-23 05:03:17.581103: val_loss -0.7913 +2024-11-23 05:03:17.581180: Pseudo dice [0.8593] +2024-11-23 05:03:17.581257: Epoch time: 18.14 s +2024-11-23 05:03:18.868087: +2024-11-23 05:03:18.868306: Epoch 7620 +2024-11-23 05:03:18.868428: Current learning rate: 0.00064 +2024-11-23 05:03:37.015347: train_loss -0.8311 +2024-11-23 05:03:37.021017: val_loss -0.7865 +2024-11-23 05:03:37.021142: Pseudo dice [0.8727] +2024-11-23 05:03:37.021230: Epoch time: 18.15 s +2024-11-23 05:03:37.953041: +2024-11-23 05:03:37.953281: Epoch 7621 +2024-11-23 05:03:37.953402: Current learning rate: 0.00064 +2024-11-23 05:03:57.366606: train_loss -0.8346 +2024-11-23 05:03:57.366874: val_loss -0.7813 +2024-11-23 05:03:57.366967: Pseudo dice [0.8653] +2024-11-23 05:03:57.367066: Epoch time: 19.41 s +2024-11-23 05:03:58.261604: +2024-11-23 05:03:58.261827: Epoch 7622 +2024-11-23 05:03:58.261946: Current learning rate: 0.00064 +2024-11-23 05:04:17.501311: train_loss -0.8327 +2024-11-23 05:04:17.501542: val_loss -0.7824 +2024-11-23 05:04:17.501626: Pseudo dice [0.8683] +2024-11-23 05:04:17.501717: Epoch time: 19.24 s +2024-11-23 05:04:18.542531: +2024-11-23 05:04:18.542756: Epoch 7623 +2024-11-23 05:04:18.542875: Current learning rate: 0.00064 +2024-11-23 05:04:36.441701: train_loss -0.8317 +2024-11-23 05:04:36.441956: val_loss -0.7827 +2024-11-23 05:04:36.442045: Pseudo dice [0.8733] +2024-11-23 05:04:36.442136: Epoch time: 17.9 s +2024-11-23 05:04:37.337027: +2024-11-23 05:04:37.337252: Epoch 7624 +2024-11-23 05:04:37.337370: Current learning rate: 0.00064 +2024-11-23 05:04:55.916057: train_loss -0.8293 +2024-11-23 05:04:55.916291: val_loss -0.7899 +2024-11-23 05:04:55.916367: Pseudo dice [0.8654] +2024-11-23 05:04:55.916451: Epoch time: 18.58 s +2024-11-23 05:04:56.814209: +2024-11-23 05:04:56.814433: Epoch 7625 +2024-11-23 05:04:56.814560: Current learning rate: 0.00064 +2024-11-23 05:05:15.421185: train_loss -0.8348 +2024-11-23 05:05:15.421421: val_loss -0.7851 +2024-11-23 05:05:15.426739: Pseudo dice [0.8655] +2024-11-23 05:05:15.426878: Epoch time: 18.61 s +2024-11-23 05:05:16.372784: +2024-11-23 05:05:16.373027: Epoch 7626 +2024-11-23 05:05:16.373151: Current learning rate: 0.00064 +2024-11-23 05:05:34.145055: train_loss -0.8311 +2024-11-23 05:05:34.145274: val_loss -0.799 +2024-11-23 05:05:34.145365: Pseudo dice [0.8636] +2024-11-23 05:05:34.145451: Epoch time: 17.77 s +2024-11-23 05:05:35.041901: +2024-11-23 05:05:35.042130: Epoch 7627 +2024-11-23 05:05:35.042247: Current learning rate: 0.00063 +2024-11-23 05:05:53.324122: train_loss -0.8318 +2024-11-23 05:05:53.324339: val_loss -0.7756 +2024-11-23 05:05:53.324417: Pseudo dice [0.8768] +2024-11-23 05:05:53.324492: Epoch time: 18.28 s +2024-11-23 05:05:53.324566: Yayy! New best EMA pseudo Dice: 0.8666 +2024-11-23 05:05:54.570368: +2024-11-23 05:05:54.570611: Epoch 7628 +2024-11-23 05:05:54.570739: Current learning rate: 0.00063 +2024-11-23 05:06:12.964427: train_loss -0.8302 +2024-11-23 05:06:12.964646: val_loss -0.7773 +2024-11-23 05:06:12.964756: Pseudo dice [0.8626] +2024-11-23 05:06:12.964853: Epoch time: 18.39 s +2024-11-23 05:06:13.854749: +2024-11-23 05:06:13.854962: Epoch 7629 +2024-11-23 05:06:13.855090: Current learning rate: 0.00063 +2024-11-23 05:06:32.261159: train_loss -0.8347 +2024-11-23 05:06:32.261365: val_loss -0.7814 +2024-11-23 05:06:32.261448: Pseudo dice [0.8506] +2024-11-23 05:06:32.261580: Epoch time: 18.41 s +2024-11-23 05:06:33.157931: +2024-11-23 05:06:33.158181: Epoch 7630 +2024-11-23 05:06:33.158354: Current learning rate: 0.00063 +2024-11-23 05:06:50.898110: train_loss -0.8349 +2024-11-23 05:06:50.900511: val_loss -0.7854 +2024-11-23 05:06:50.900623: Pseudo dice [0.8556] +2024-11-23 05:06:50.900709: Epoch time: 17.74 s +2024-11-23 05:06:52.264342: +2024-11-23 05:06:52.264570: Epoch 7631 +2024-11-23 05:06:52.264703: Current learning rate: 0.00063 +2024-11-23 05:07:09.645144: train_loss -0.8318 +2024-11-23 05:07:09.645375: val_loss -0.7889 +2024-11-23 05:07:09.645458: Pseudo dice [0.8675] +2024-11-23 05:07:09.647740: Epoch time: 17.38 s +2024-11-23 05:07:10.552026: +2024-11-23 05:07:10.552248: Epoch 7632 +2024-11-23 05:07:10.552369: Current learning rate: 0.00063 +2024-11-23 05:07:29.703819: train_loss -0.8309 +2024-11-23 05:07:29.704117: val_loss -0.7901 +2024-11-23 05:07:29.704227: Pseudo dice [0.8577] +2024-11-23 05:07:29.704332: Epoch time: 19.15 s +2024-11-23 05:07:30.602460: +2024-11-23 05:07:30.602664: Epoch 7633 +2024-11-23 05:07:30.602775: Current learning rate: 0.00062 +2024-11-23 05:07:49.721666: train_loss -0.8296 +2024-11-23 05:07:49.721923: val_loss -0.7742 +2024-11-23 05:07:49.722025: Pseudo dice [0.8598] +2024-11-23 05:07:49.722122: Epoch time: 19.12 s +2024-11-23 05:07:50.615090: +2024-11-23 05:07:50.615327: Epoch 7634 +2024-11-23 05:07:50.615448: Current learning rate: 0.00062 +2024-11-23 05:08:08.719339: train_loss -0.8225 +2024-11-23 05:08:08.719566: val_loss -0.7852 +2024-11-23 05:08:08.719647: Pseudo dice [0.8809] +2024-11-23 05:08:08.719725: Epoch time: 18.11 s +2024-11-23 05:08:09.615044: +2024-11-23 05:08:09.615273: Epoch 7635 +2024-11-23 05:08:09.615398: Current learning rate: 0.00062 +2024-11-23 05:08:27.971829: train_loss -0.8278 +2024-11-23 05:08:27.972038: val_loss -0.7837 +2024-11-23 05:08:27.972190: Pseudo dice [0.8581] +2024-11-23 05:08:27.972279: Epoch time: 18.36 s +2024-11-23 05:08:28.865174: +2024-11-23 05:08:28.865419: Epoch 7636 +2024-11-23 05:08:28.865537: Current learning rate: 0.00062 +2024-11-23 05:08:46.712306: train_loss -0.8278 +2024-11-23 05:08:46.712525: val_loss -0.7857 +2024-11-23 05:08:46.712600: Pseudo dice [0.8553] +2024-11-23 05:08:46.712677: Epoch time: 17.85 s +2024-11-23 05:08:47.630551: +2024-11-23 05:08:47.630755: Epoch 7637 +2024-11-23 05:08:47.630872: Current learning rate: 0.00062 +2024-11-23 05:09:05.178992: train_loss -0.8348 +2024-11-23 05:09:05.179242: val_loss -0.795 +2024-11-23 05:09:05.184470: Pseudo dice [0.8666] +2024-11-23 05:09:05.184653: Epoch time: 17.55 s +2024-11-23 05:09:06.192605: +2024-11-23 05:09:06.192824: Epoch 7638 +2024-11-23 05:09:06.192945: Current learning rate: 0.00062 +2024-11-23 05:09:25.414190: train_loss -0.8346 +2024-11-23 05:09:25.414405: val_loss -0.7777 +2024-11-23 05:09:25.414490: Pseudo dice [0.8573] +2024-11-23 05:09:25.414564: Epoch time: 19.22 s +2024-11-23 05:09:26.304600: +2024-11-23 05:09:26.304822: Epoch 7639 +2024-11-23 05:09:26.304954: Current learning rate: 0.00062 +2024-11-23 05:09:44.456985: train_loss -0.8305 +2024-11-23 05:09:44.457195: val_loss -0.7758 +2024-11-23 05:09:44.457276: Pseudo dice [0.8673] +2024-11-23 05:09:44.457358: Epoch time: 18.15 s +2024-11-23 05:09:45.344304: +2024-11-23 05:09:45.344497: Epoch 7640 +2024-11-23 05:09:45.344611: Current learning rate: 0.00061 +2024-11-23 05:10:04.573372: train_loss -0.8302 +2024-11-23 05:10:04.573591: val_loss -0.7905 +2024-11-23 05:10:04.573674: Pseudo dice [0.8651] +2024-11-23 05:10:04.573751: Epoch time: 19.23 s +2024-11-23 05:10:05.591078: +2024-11-23 05:10:05.591271: Epoch 7641 +2024-11-23 05:10:05.591381: Current learning rate: 0.00061 +2024-11-23 05:10:23.959746: train_loss -0.8377 +2024-11-23 05:10:23.960019: val_loss -0.7932 +2024-11-23 05:10:23.960128: Pseudo dice [0.867] +2024-11-23 05:10:23.960216: Epoch time: 18.37 s +2024-11-23 05:10:25.259999: +2024-11-23 05:10:25.260225: Epoch 7642 +2024-11-23 05:10:25.260341: Current learning rate: 0.00061 +2024-11-23 05:10:44.890875: train_loss -0.8384 +2024-11-23 05:10:44.891119: val_loss -0.773 +2024-11-23 05:10:44.891211: Pseudo dice [0.8697] +2024-11-23 05:10:44.891286: Epoch time: 19.63 s +2024-11-23 05:10:45.781239: +2024-11-23 05:10:45.781465: Epoch 7643 +2024-11-23 05:10:45.781591: Current learning rate: 0.00061 +2024-11-23 05:11:04.703317: train_loss -0.83 +2024-11-23 05:11:04.703528: val_loss -0.7755 +2024-11-23 05:11:04.703609: Pseudo dice [0.8647] +2024-11-23 05:11:04.703685: Epoch time: 18.92 s +2024-11-23 05:11:05.616703: +2024-11-23 05:11:05.616924: Epoch 7644 +2024-11-23 05:11:05.617053: Current learning rate: 0.00061 +2024-11-23 05:11:24.350257: train_loss -0.8344 +2024-11-23 05:11:24.350544: val_loss -0.7893 +2024-11-23 05:11:24.350637: Pseudo dice [0.8676] +2024-11-23 05:11:24.350729: Epoch time: 18.73 s +2024-11-23 05:11:25.373985: +2024-11-23 05:11:25.374237: Epoch 7645 +2024-11-23 05:11:25.374360: Current learning rate: 0.00061 +2024-11-23 05:11:43.251757: train_loss -0.8341 +2024-11-23 05:11:43.251997: val_loss -0.7691 +2024-11-23 05:11:43.252088: Pseudo dice [0.8675] +2024-11-23 05:11:43.252181: Epoch time: 17.88 s +2024-11-23 05:11:44.155009: +2024-11-23 05:11:44.155237: Epoch 7646 +2024-11-23 05:11:44.155356: Current learning rate: 0.0006 +2024-11-23 05:12:02.385998: train_loss -0.8289 +2024-11-23 05:12:02.386208: val_loss -0.7804 +2024-11-23 05:12:02.386284: Pseudo dice [0.8639] +2024-11-23 05:12:02.386392: Epoch time: 18.23 s +2024-11-23 05:12:03.282750: +2024-11-23 05:12:03.282953: Epoch 7647 +2024-11-23 05:12:03.283071: Current learning rate: 0.0006 +2024-11-23 05:12:20.743228: train_loss -0.8337 +2024-11-23 05:12:20.743458: val_loss -0.8101 +2024-11-23 05:12:20.743536: Pseudo dice [0.8624] +2024-11-23 05:12:20.743614: Epoch time: 17.46 s +2024-11-23 05:12:21.643271: +2024-11-23 05:12:21.643695: Epoch 7648 +2024-11-23 05:12:21.643825: Current learning rate: 0.0006 +2024-11-23 05:12:40.086802: train_loss -0.8394 +2024-11-23 05:12:40.087043: val_loss -0.7652 +2024-11-23 05:12:40.087204: Pseudo dice [0.8593] +2024-11-23 05:12:40.087312: Epoch time: 18.44 s +2024-11-23 05:12:40.987151: +2024-11-23 05:12:40.987369: Epoch 7649 +2024-11-23 05:12:40.987499: Current learning rate: 0.0006 +2024-11-23 05:12:59.926924: train_loss -0.8309 +2024-11-23 05:12:59.927141: val_loss -0.7896 +2024-11-23 05:12:59.927222: Pseudo dice [0.8667] +2024-11-23 05:12:59.927318: Epoch time: 18.94 s +2024-11-23 05:13:01.164820: +2024-11-23 05:13:01.165039: Epoch 7650 +2024-11-23 05:13:01.165170: Current learning rate: 0.0006 +2024-11-23 05:13:19.324126: train_loss -0.8355 +2024-11-23 05:13:19.324362: val_loss -0.7843 +2024-11-23 05:13:19.324492: Pseudo dice [0.8548] +2024-11-23 05:13:19.324581: Epoch time: 18.16 s +2024-11-23 05:13:20.279590: +2024-11-23 05:13:20.279827: Epoch 7651 +2024-11-23 05:13:20.279953: Current learning rate: 0.0006 +2024-11-23 05:13:39.294338: train_loss -0.8312 +2024-11-23 05:13:39.294551: val_loss -0.7971 +2024-11-23 05:13:39.294636: Pseudo dice [0.8727] +2024-11-23 05:13:39.294725: Epoch time: 19.02 s +2024-11-23 05:13:40.187441: +2024-11-23 05:13:40.187643: Epoch 7652 +2024-11-23 05:13:40.187757: Current learning rate: 0.0006 +2024-11-23 05:13:58.582898: train_loss -0.842 +2024-11-23 05:13:58.583208: val_loss -0.7954 +2024-11-23 05:13:58.583293: Pseudo dice [0.8645] +2024-11-23 05:13:58.583385: Epoch time: 18.4 s +2024-11-23 05:13:59.931967: +2024-11-23 05:13:59.932191: Epoch 7653 +2024-11-23 05:13:59.932305: Current learning rate: 0.00059 +2024-11-23 05:14:18.735679: train_loss -0.8323 +2024-11-23 05:14:18.735923: val_loss -0.7772 +2024-11-23 05:14:18.736002: Pseudo dice [0.8624] +2024-11-23 05:14:18.736087: Epoch time: 18.8 s +2024-11-23 05:14:19.619564: +2024-11-23 05:14:19.619811: Epoch 7654 +2024-11-23 05:14:19.619923: Current learning rate: 0.00059 +2024-11-23 05:14:38.289829: train_loss -0.8284 +2024-11-23 05:14:38.290037: val_loss -0.8051 +2024-11-23 05:14:38.290133: Pseudo dice [0.8826] +2024-11-23 05:14:38.290209: Epoch time: 18.67 s +2024-11-23 05:14:39.181971: +2024-11-23 05:14:39.182227: Epoch 7655 +2024-11-23 05:14:39.182339: Current learning rate: 0.00059 +2024-11-23 05:14:58.219063: train_loss -0.8318 +2024-11-23 05:14:58.219285: val_loss -0.7991 +2024-11-23 05:14:58.219367: Pseudo dice [0.8657] +2024-11-23 05:14:58.219473: Epoch time: 19.04 s +2024-11-23 05:14:59.125440: +2024-11-23 05:14:59.125659: Epoch 7656 +2024-11-23 05:14:59.125777: Current learning rate: 0.00059 +2024-11-23 05:15:17.528225: train_loss -0.828 +2024-11-23 05:15:17.528436: val_loss -0.8004 +2024-11-23 05:15:17.528520: Pseudo dice [0.8616] +2024-11-23 05:15:17.528618: Epoch time: 18.4 s +2024-11-23 05:15:18.419729: +2024-11-23 05:15:18.419960: Epoch 7657 +2024-11-23 05:15:18.420081: Current learning rate: 0.00059 +2024-11-23 05:15:37.950520: train_loss -0.8352 +2024-11-23 05:15:37.950737: val_loss -0.8026 +2024-11-23 05:15:37.950816: Pseudo dice [0.873] +2024-11-23 05:15:37.950894: Epoch time: 19.53 s +2024-11-23 05:15:38.850374: +2024-11-23 05:15:38.850576: Epoch 7658 +2024-11-23 05:15:38.850695: Current learning rate: 0.00059 +2024-11-23 05:15:56.801871: train_loss -0.8383 +2024-11-23 05:15:56.802106: val_loss -0.7831 +2024-11-23 05:15:56.802208: Pseudo dice [0.8631] +2024-11-23 05:15:56.802308: Epoch time: 17.95 s +2024-11-23 05:15:57.726485: +2024-11-23 05:15:57.726690: Epoch 7659 +2024-11-23 05:15:57.726802: Current learning rate: 0.00058 +2024-11-23 05:16:16.674511: train_loss -0.8332 +2024-11-23 05:16:16.674775: val_loss -0.7904 +2024-11-23 05:16:16.674861: Pseudo dice [0.8662] +2024-11-23 05:16:16.674957: Epoch time: 18.95 s +2024-11-23 05:16:17.571503: +2024-11-23 05:16:17.571743: Epoch 7660 +2024-11-23 05:16:17.571872: Current learning rate: 0.00058 +2024-11-23 05:16:34.618435: train_loss -0.8334 +2024-11-23 05:16:34.618651: val_loss -0.7912 +2024-11-23 05:16:34.618735: Pseudo dice [0.8633] +2024-11-23 05:16:34.618823: Epoch time: 17.05 s +2024-11-23 05:16:35.521944: +2024-11-23 05:16:35.522177: Epoch 7661 +2024-11-23 05:16:35.522289: Current learning rate: 0.00058 +2024-11-23 05:16:53.782979: train_loss -0.8334 +2024-11-23 05:16:53.783195: val_loss -0.8023 +2024-11-23 05:16:53.783275: Pseudo dice [0.868] +2024-11-23 05:16:53.783351: Epoch time: 18.26 s +2024-11-23 05:16:54.676087: +2024-11-23 05:16:54.676287: Epoch 7662 +2024-11-23 05:16:54.676396: Current learning rate: 0.00058 +2024-11-23 05:17:12.906330: train_loss -0.8304 +2024-11-23 05:17:12.906555: val_loss -0.7865 +2024-11-23 05:17:12.906638: Pseudo dice [0.8621] +2024-11-23 05:17:12.906714: Epoch time: 18.23 s +2024-11-23 05:17:13.797045: +2024-11-23 05:17:13.797283: Epoch 7663 +2024-11-23 05:17:13.797412: Current learning rate: 0.00058 +2024-11-23 05:17:33.122519: train_loss -0.8409 +2024-11-23 05:17:33.122768: val_loss -0.7781 +2024-11-23 05:17:33.122857: Pseudo dice [0.854] +2024-11-23 05:17:33.122955: Epoch time: 19.33 s +2024-11-23 05:17:34.012729: +2024-11-23 05:17:34.012960: Epoch 7664 +2024-11-23 05:17:34.013078: Current learning rate: 0.00058 +2024-11-23 05:17:51.376002: train_loss -0.8318 +2024-11-23 05:17:51.376272: val_loss -0.8005 +2024-11-23 05:17:51.376352: Pseudo dice [0.8658] +2024-11-23 05:17:51.376441: Epoch time: 17.36 s +2024-11-23 05:17:52.726399: +2024-11-23 05:17:52.726633: Epoch 7665 +2024-11-23 05:17:52.726750: Current learning rate: 0.00058 +2024-11-23 05:18:11.317891: train_loss -0.8365 +2024-11-23 05:18:11.318127: val_loss -0.8039 +2024-11-23 05:18:11.318229: Pseudo dice [0.8637] +2024-11-23 05:18:11.318304: Epoch time: 18.59 s +2024-11-23 05:18:12.218880: +2024-11-23 05:18:12.219103: Epoch 7666 +2024-11-23 05:18:12.219213: Current learning rate: 0.00057 +2024-11-23 05:18:30.777482: train_loss -0.8294 +2024-11-23 05:18:30.777729: val_loss -0.8003 +2024-11-23 05:18:30.777822: Pseudo dice [0.853] +2024-11-23 05:18:30.777919: Epoch time: 18.56 s +2024-11-23 05:18:31.792896: +2024-11-23 05:18:31.793120: Epoch 7667 +2024-11-23 05:18:31.793236: Current learning rate: 0.00057 +2024-11-23 05:18:50.205848: train_loss -0.8297 +2024-11-23 05:18:50.206052: val_loss -0.7827 +2024-11-23 05:18:50.206139: Pseudo dice [0.8667] +2024-11-23 05:18:50.206220: Epoch time: 18.41 s +2024-11-23 05:18:51.095820: +2024-11-23 05:18:51.096034: Epoch 7668 +2024-11-23 05:18:51.096168: Current learning rate: 0.00057 +2024-11-23 05:19:10.458986: train_loss -0.8353 +2024-11-23 05:19:10.459198: val_loss -0.7741 +2024-11-23 05:19:10.459276: Pseudo dice [0.8543] +2024-11-23 05:19:10.459359: Epoch time: 19.36 s +2024-11-23 05:19:11.360607: +2024-11-23 05:19:11.360831: Epoch 7669 +2024-11-23 05:19:11.360947: Current learning rate: 0.00057 +2024-11-23 05:19:30.020245: train_loss -0.8387 +2024-11-23 05:19:30.020454: val_loss -0.7958 +2024-11-23 05:19:30.020531: Pseudo dice [0.8562] +2024-11-23 05:19:30.020612: Epoch time: 18.66 s +2024-11-23 05:19:30.918764: +2024-11-23 05:19:30.918987: Epoch 7670 +2024-11-23 05:19:30.919120: Current learning rate: 0.00057 +2024-11-23 05:19:49.652791: train_loss -0.8325 +2024-11-23 05:19:49.653016: val_loss -0.8006 +2024-11-23 05:19:49.653103: Pseudo dice [0.8575] +2024-11-23 05:19:49.653185: Epoch time: 18.73 s +2024-11-23 05:19:50.573571: +2024-11-23 05:19:50.573797: Epoch 7671 +2024-11-23 05:19:50.573927: Current learning rate: 0.00057 +2024-11-23 05:20:09.450937: train_loss -0.8335 +2024-11-23 05:20:09.451247: val_loss -0.785 +2024-11-23 05:20:09.451334: Pseudo dice [0.8691] +2024-11-23 05:20:09.451419: Epoch time: 18.88 s +2024-11-23 05:20:10.345415: +2024-11-23 05:20:10.345620: Epoch 7672 +2024-11-23 05:20:10.345730: Current learning rate: 0.00056 +2024-11-23 05:20:29.363293: train_loss -0.8355 +2024-11-23 05:20:29.363503: val_loss -0.7846 +2024-11-23 05:20:29.363574: Pseudo dice [0.8586] +2024-11-23 05:20:29.363647: Epoch time: 19.02 s +2024-11-23 05:20:30.294507: +2024-11-23 05:20:30.294710: Epoch 7673 +2024-11-23 05:20:30.294831: Current learning rate: 0.00056 +2024-11-23 05:20:49.305782: train_loss -0.835 +2024-11-23 05:20:49.306002: val_loss -0.8053 +2024-11-23 05:20:49.306090: Pseudo dice [0.8709] +2024-11-23 05:20:49.306171: Epoch time: 19.01 s +2024-11-23 05:20:50.312434: +2024-11-23 05:20:50.312684: Epoch 7674 +2024-11-23 05:20:50.312804: Current learning rate: 0.00056 +2024-11-23 05:21:09.353996: train_loss -0.8435 +2024-11-23 05:21:09.354264: val_loss -0.785 +2024-11-23 05:21:09.354371: Pseudo dice [0.866] +2024-11-23 05:21:09.354481: Epoch time: 19.04 s +2024-11-23 05:21:10.257073: +2024-11-23 05:21:10.257292: Epoch 7675 +2024-11-23 05:21:10.257406: Current learning rate: 0.00056 +2024-11-23 05:21:28.631309: train_loss -0.8259 +2024-11-23 05:21:28.631525: val_loss -0.7648 +2024-11-23 05:21:28.631628: Pseudo dice [0.8584] +2024-11-23 05:21:28.631716: Epoch time: 18.38 s +2024-11-23 05:21:29.936756: +2024-11-23 05:21:29.936962: Epoch 7676 +2024-11-23 05:21:29.937087: Current learning rate: 0.00056 +2024-11-23 05:21:49.447632: train_loss -0.8309 +2024-11-23 05:21:49.447865: val_loss -0.7962 +2024-11-23 05:21:49.448003: Pseudo dice [0.8576] +2024-11-23 05:21:49.448110: Epoch time: 19.51 s +2024-11-23 05:21:50.343057: +2024-11-23 05:21:50.343294: Epoch 7677 +2024-11-23 05:21:50.343428: Current learning rate: 0.00056 +2024-11-23 05:22:08.133249: train_loss -0.8285 +2024-11-23 05:22:08.133501: val_loss -0.7656 +2024-11-23 05:22:08.133589: Pseudo dice [0.859] +2024-11-23 05:22:08.133682: Epoch time: 17.79 s +2024-11-23 05:22:09.036700: +2024-11-23 05:22:09.036934: Epoch 7678 +2024-11-23 05:22:09.037056: Current learning rate: 0.00055 +2024-11-23 05:22:27.283862: train_loss -0.836 +2024-11-23 05:22:27.284112: val_loss -0.7942 +2024-11-23 05:22:27.284194: Pseudo dice [0.8704] +2024-11-23 05:22:27.284280: Epoch time: 18.25 s +2024-11-23 05:22:28.288303: +2024-11-23 05:22:28.288530: Epoch 7679 +2024-11-23 05:22:28.288646: Current learning rate: 0.00055 +2024-11-23 05:22:46.382584: train_loss -0.8375 +2024-11-23 05:22:46.382822: val_loss -0.7903 +2024-11-23 05:22:46.382914: Pseudo dice [0.8731] +2024-11-23 05:22:46.383013: Epoch time: 18.1 s +2024-11-23 05:22:47.282747: +2024-11-23 05:22:47.282962: Epoch 7680 +2024-11-23 05:22:47.283084: Current learning rate: 0.00055 +2024-11-23 05:23:06.505454: train_loss -0.8337 +2024-11-23 05:23:06.505726: val_loss -0.7778 +2024-11-23 05:23:06.505826: Pseudo dice [0.87] +2024-11-23 05:23:06.505918: Epoch time: 19.22 s +2024-11-23 05:23:07.404805: +2024-11-23 05:23:07.405032: Epoch 7681 +2024-11-23 05:23:07.405153: Current learning rate: 0.00055 +2024-11-23 05:23:25.471293: train_loss -0.839 +2024-11-23 05:23:25.471522: val_loss -0.785 +2024-11-23 05:23:25.471617: Pseudo dice [0.8718] +2024-11-23 05:23:25.471695: Epoch time: 18.07 s +2024-11-23 05:23:26.368169: +2024-11-23 05:23:26.368384: Epoch 7682 +2024-11-23 05:23:26.368504: Current learning rate: 0.00055 +2024-11-23 05:23:46.194602: train_loss -0.8343 +2024-11-23 05:23:46.194856: val_loss -0.7962 +2024-11-23 05:23:46.194949: Pseudo dice [0.8672] +2024-11-23 05:23:46.195032: Epoch time: 19.83 s +2024-11-23 05:23:47.098459: +2024-11-23 05:23:47.098714: Epoch 7683 +2024-11-23 05:23:47.098854: Current learning rate: 0.00055 +2024-11-23 05:24:05.568342: train_loss -0.8329 +2024-11-23 05:24:05.568557: val_loss -0.7543 +2024-11-23 05:24:05.568640: Pseudo dice [0.8657] +2024-11-23 05:24:05.568717: Epoch time: 18.47 s +2024-11-23 05:24:06.464020: +2024-11-23 05:24:06.464246: Epoch 7684 +2024-11-23 05:24:06.464365: Current learning rate: 0.00055 +2024-11-23 05:24:23.846723: train_loss -0.83 +2024-11-23 05:24:23.846940: val_loss -0.7644 +2024-11-23 05:24:23.847024: Pseudo dice [0.874] +2024-11-23 05:24:23.849363: Epoch time: 17.38 s +2024-11-23 05:24:24.754823: +2024-11-23 05:24:24.755053: Epoch 7685 +2024-11-23 05:24:24.755182: Current learning rate: 0.00054 +2024-11-23 05:24:43.176747: train_loss -0.8335 +2024-11-23 05:24:43.176968: val_loss -0.792 +2024-11-23 05:24:43.178279: Pseudo dice [0.8539] +2024-11-23 05:24:43.178399: Epoch time: 18.42 s +2024-11-23 05:24:44.081575: +2024-11-23 05:24:44.081793: Epoch 7686 +2024-11-23 05:24:44.081905: Current learning rate: 0.00054 +2024-11-23 05:25:02.301911: train_loss -0.8369 +2024-11-23 05:25:02.302165: val_loss -0.8049 +2024-11-23 05:25:02.302243: Pseudo dice [0.8735] +2024-11-23 05:25:02.302321: Epoch time: 18.22 s +2024-11-23 05:25:03.194109: +2024-11-23 05:25:03.194310: Epoch 7687 +2024-11-23 05:25:03.194446: Current learning rate: 0.00054 +2024-11-23 05:25:21.820913: train_loss -0.8402 +2024-11-23 05:25:21.821135: val_loss -0.7734 +2024-11-23 05:25:21.821222: Pseudo dice [0.8755] +2024-11-23 05:25:21.821320: Epoch time: 18.63 s +2024-11-23 05:25:21.821405: Yayy! New best EMA pseudo Dice: 0.8668 +2024-11-23 05:25:23.477713: +2024-11-23 05:25:23.477931: Epoch 7688 +2024-11-23 05:25:23.478045: Current learning rate: 0.00054 +2024-11-23 05:25:42.048896: train_loss -0.835 +2024-11-23 05:25:42.049181: val_loss -0.7783 +2024-11-23 05:25:42.049272: Pseudo dice [0.8731] +2024-11-23 05:25:42.049357: Epoch time: 18.57 s +2024-11-23 05:25:42.049421: Yayy! New best EMA pseudo Dice: 0.8674 +2024-11-23 05:25:43.299202: +2024-11-23 05:25:43.299428: Epoch 7689 +2024-11-23 05:25:43.299540: Current learning rate: 0.00054 +2024-11-23 05:26:02.055020: train_loss -0.832 +2024-11-23 05:26:02.055261: val_loss -0.7826 +2024-11-23 05:26:02.055343: Pseudo dice [0.8663] +2024-11-23 05:26:02.055432: Epoch time: 18.76 s +2024-11-23 05:26:02.953478: +2024-11-23 05:26:02.953693: Epoch 7690 +2024-11-23 05:26:02.953807: Current learning rate: 0.00054 +2024-11-23 05:26:21.930405: train_loss -0.8242 +2024-11-23 05:26:21.930620: val_loss -0.7877 +2024-11-23 05:26:21.930696: Pseudo dice [0.858] +2024-11-23 05:26:21.930771: Epoch time: 18.98 s +2024-11-23 05:26:22.820258: +2024-11-23 05:26:22.820482: Epoch 7691 +2024-11-23 05:26:22.820603: Current learning rate: 0.00053 +2024-11-23 05:26:41.604837: train_loss -0.8276 +2024-11-23 05:26:41.605078: val_loss -0.7957 +2024-11-23 05:26:41.605175: Pseudo dice [0.8594] +2024-11-23 05:26:41.605262: Epoch time: 18.79 s +2024-11-23 05:26:42.503630: +2024-11-23 05:26:42.503871: Epoch 7692 +2024-11-23 05:26:42.503986: Current learning rate: 0.00053 +2024-11-23 05:27:01.244538: train_loss -0.8323 +2024-11-23 05:27:01.244771: val_loss -0.817 +2024-11-23 05:27:01.244868: Pseudo dice [0.8641] +2024-11-23 05:27:01.244947: Epoch time: 18.74 s +2024-11-23 05:27:02.154720: +2024-11-23 05:27:02.154933: Epoch 7693 +2024-11-23 05:27:02.155053: Current learning rate: 0.00053 +2024-11-23 05:27:20.384275: train_loss -0.8283 +2024-11-23 05:27:20.384537: val_loss -0.7583 +2024-11-23 05:27:20.384633: Pseudo dice [0.8644] +2024-11-23 05:27:20.389893: Epoch time: 18.23 s +2024-11-23 05:27:21.382693: +2024-11-23 05:27:21.382909: Epoch 7694 +2024-11-23 05:27:21.383032: Current learning rate: 0.00053 +2024-11-23 05:27:39.642586: train_loss -0.8318 +2024-11-23 05:27:39.642862: val_loss -0.7758 +2024-11-23 05:27:39.642951: Pseudo dice [0.8503] +2024-11-23 05:27:39.643028: Epoch time: 18.26 s +2024-11-23 05:27:40.543944: +2024-11-23 05:27:40.544200: Epoch 7695 +2024-11-23 05:27:40.544322: Current learning rate: 0.00053 +2024-11-23 05:27:58.476177: train_loss -0.8397 +2024-11-23 05:27:58.476415: val_loss -0.7741 +2024-11-23 05:27:58.476495: Pseudo dice [0.869] +2024-11-23 05:27:58.476584: Epoch time: 17.93 s +2024-11-23 05:27:59.443834: +2024-11-23 05:27:59.444072: Epoch 7696 +2024-11-23 05:27:59.444191: Current learning rate: 0.00053 +2024-11-23 05:28:18.334605: train_loss -0.8396 +2024-11-23 05:28:18.334849: val_loss -0.7784 +2024-11-23 05:28:18.334925: Pseudo dice [0.877] +2024-11-23 05:28:18.335003: Epoch time: 18.89 s +2024-11-23 05:28:19.390410: +2024-11-23 05:28:19.390629: Epoch 7697 +2024-11-23 05:28:19.390749: Current learning rate: 0.00053 +2024-11-23 05:28:38.213536: train_loss -0.8317 +2024-11-23 05:28:38.213750: val_loss -0.783 +2024-11-23 05:28:38.213834: Pseudo dice [0.8697] +2024-11-23 05:28:38.215038: Epoch time: 18.82 s +2024-11-23 05:28:39.524924: +2024-11-23 05:28:39.525141: Epoch 7698 +2024-11-23 05:28:39.525273: Current learning rate: 0.00052 +2024-11-23 05:28:59.078653: train_loss -0.8376 +2024-11-23 05:28:59.078916: val_loss -0.8062 +2024-11-23 05:28:59.078997: Pseudo dice [0.8701] +2024-11-23 05:28:59.079083: Epoch time: 19.55 s +2024-11-23 05:29:00.051915: +2024-11-23 05:29:00.052132: Epoch 7699 +2024-11-23 05:29:00.052262: Current learning rate: 0.00052 +2024-11-23 05:29:18.691744: train_loss -0.8377 +2024-11-23 05:29:18.692041: val_loss -0.7777 +2024-11-23 05:29:18.692154: Pseudo dice [0.8511] +2024-11-23 05:29:18.692293: Epoch time: 18.64 s +2024-11-23 05:29:19.977858: +2024-11-23 05:29:19.978069: Epoch 7700 +2024-11-23 05:29:19.978177: Current learning rate: 0.00052 +2024-11-23 05:29:39.063823: train_loss -0.8274 +2024-11-23 05:29:39.064044: val_loss -0.7805 +2024-11-23 05:29:39.064150: Pseudo dice [0.8626] +2024-11-23 05:29:39.064241: Epoch time: 19.09 s +2024-11-23 05:29:39.962317: +2024-11-23 05:29:39.962554: Epoch 7701 +2024-11-23 05:29:39.962671: Current learning rate: 0.00052 +2024-11-23 05:29:58.082813: train_loss -0.8359 +2024-11-23 05:29:58.083101: val_loss -0.7956 +2024-11-23 05:29:58.083247: Pseudo dice [0.851] +2024-11-23 05:29:58.083337: Epoch time: 18.12 s +2024-11-23 05:29:58.986504: +2024-11-23 05:29:58.986720: Epoch 7702 +2024-11-23 05:29:58.986837: Current learning rate: 0.00052 +2024-11-23 05:30:17.693017: train_loss -0.8344 +2024-11-23 05:30:17.693239: val_loss -0.7853 +2024-11-23 05:30:17.693323: Pseudo dice [0.8654] +2024-11-23 05:30:17.693400: Epoch time: 18.71 s +2024-11-23 05:30:18.725317: +2024-11-23 05:30:18.725545: Epoch 7703 +2024-11-23 05:30:18.725662: Current learning rate: 0.00052 +2024-11-23 05:30:37.100650: train_loss -0.8342 +2024-11-23 05:30:37.101441: val_loss -0.7881 +2024-11-23 05:30:37.101545: Pseudo dice [0.8551] +2024-11-23 05:30:37.101630: Epoch time: 18.38 s +2024-11-23 05:30:38.108404: +2024-11-23 05:30:38.108595: Epoch 7704 +2024-11-23 05:30:38.108711: Current learning rate: 0.00051 +2024-11-23 05:30:55.819017: train_loss -0.8374 +2024-11-23 05:30:55.819263: val_loss -0.7865 +2024-11-23 05:30:55.819349: Pseudo dice [0.8607] +2024-11-23 05:30:55.819436: Epoch time: 17.71 s +2024-11-23 05:30:56.729360: +2024-11-23 05:30:56.729587: Epoch 7705 +2024-11-23 05:30:56.729703: Current learning rate: 0.00051 +2024-11-23 05:31:15.193226: train_loss -0.8343 +2024-11-23 05:31:15.193486: val_loss -0.7776 +2024-11-23 05:31:15.193567: Pseudo dice [0.8524] +2024-11-23 05:31:15.193666: Epoch time: 18.46 s +2024-11-23 05:31:16.283056: +2024-11-23 05:31:16.283266: Epoch 7706 +2024-11-23 05:31:16.283375: Current learning rate: 0.00051 +2024-11-23 05:31:35.447080: train_loss -0.8348 +2024-11-23 05:31:35.447318: val_loss -0.7879 +2024-11-23 05:31:35.447406: Pseudo dice [0.8703] +2024-11-23 05:31:35.447483: Epoch time: 19.16 s +2024-11-23 05:31:36.339770: +2024-11-23 05:31:36.339975: Epoch 7707 +2024-11-23 05:31:36.340093: Current learning rate: 0.00051 +2024-11-23 05:31:55.266623: train_loss -0.8353 +2024-11-23 05:31:55.266894: val_loss -0.7983 +2024-11-23 05:31:55.266990: Pseudo dice [0.8601] +2024-11-23 05:31:55.267092: Epoch time: 18.93 s +2024-11-23 05:31:56.190392: +2024-11-23 05:31:56.190617: Epoch 7708 +2024-11-23 05:31:56.190732: Current learning rate: 0.00051 +2024-11-23 05:32:14.829743: train_loss -0.8275 +2024-11-23 05:32:14.830022: val_loss -0.782 +2024-11-23 05:32:14.830112: Pseudo dice [0.8695] +2024-11-23 05:32:14.830196: Epoch time: 18.64 s +2024-11-23 05:32:16.109898: +2024-11-23 05:32:16.110113: Epoch 7709 +2024-11-23 05:32:16.110227: Current learning rate: 0.00051 +2024-11-23 05:32:34.447018: train_loss -0.8349 +2024-11-23 05:32:34.447297: val_loss -0.7576 +2024-11-23 05:32:34.447395: Pseudo dice [0.8592] +2024-11-23 05:32:34.447486: Epoch time: 18.34 s +2024-11-23 05:32:35.349584: +2024-11-23 05:32:35.349805: Epoch 7710 +2024-11-23 05:32:35.349915: Current learning rate: 0.00051 +2024-11-23 05:32:53.238361: train_loss -0.8233 +2024-11-23 05:32:53.238575: val_loss -0.7862 +2024-11-23 05:32:53.238657: Pseudo dice [0.8542] +2024-11-23 05:32:53.238751: Epoch time: 17.89 s +2024-11-23 05:32:54.129193: +2024-11-23 05:32:54.129406: Epoch 7711 +2024-11-23 05:32:54.129518: Current learning rate: 0.0005 +2024-11-23 05:33:12.533264: train_loss -0.8276 +2024-11-23 05:33:12.533471: val_loss -0.7925 +2024-11-23 05:33:12.533558: Pseudo dice [0.8665] +2024-11-23 05:33:12.533635: Epoch time: 18.4 s +2024-11-23 05:33:13.433113: +2024-11-23 05:33:13.433359: Epoch 7712 +2024-11-23 05:33:13.433484: Current learning rate: 0.0005 +2024-11-23 05:33:30.514258: train_loss -0.8376 +2024-11-23 05:33:30.514492: val_loss -0.7847 +2024-11-23 05:33:30.514590: Pseudo dice [0.856] +2024-11-23 05:33:30.514674: Epoch time: 17.08 s +2024-11-23 05:33:31.411256: +2024-11-23 05:33:31.411455: Epoch 7713 +2024-11-23 05:33:31.411581: Current learning rate: 0.0005 +2024-11-23 05:33:48.783763: train_loss -0.8342 +2024-11-23 05:33:48.783997: val_loss -0.7889 +2024-11-23 05:33:48.784085: Pseudo dice [0.8606] +2024-11-23 05:33:48.784163: Epoch time: 17.37 s +2024-11-23 05:33:49.677299: +2024-11-23 05:33:49.677517: Epoch 7714 +2024-11-23 05:33:49.677629: Current learning rate: 0.0005 +2024-11-23 05:34:08.636115: train_loss -0.8374 +2024-11-23 05:34:08.636326: val_loss -0.7515 +2024-11-23 05:34:08.636403: Pseudo dice [0.8522] +2024-11-23 05:34:08.636496: Epoch time: 18.96 s +2024-11-23 05:34:09.531501: +2024-11-23 05:34:09.531719: Epoch 7715 +2024-11-23 05:34:09.531834: Current learning rate: 0.0005 +2024-11-23 05:34:27.706613: train_loss -0.8358 +2024-11-23 05:34:27.706828: val_loss -0.7804 +2024-11-23 05:34:27.706918: Pseudo dice [0.854] +2024-11-23 05:34:27.706998: Epoch time: 18.18 s +2024-11-23 05:34:28.601091: +2024-11-23 05:34:28.601309: Epoch 7716 +2024-11-23 05:34:28.601429: Current learning rate: 0.0005 +2024-11-23 05:34:48.858331: train_loss -0.8346 +2024-11-23 05:34:48.858626: val_loss -0.7935 +2024-11-23 05:34:48.858711: Pseudo dice [0.8693] +2024-11-23 05:34:48.858789: Epoch time: 20.26 s +2024-11-23 05:34:49.761700: +2024-11-23 05:34:49.761914: Epoch 7717 +2024-11-23 05:34:49.762042: Current learning rate: 0.00049 +2024-11-23 05:35:08.018228: train_loss -0.8304 +2024-11-23 05:35:08.018465: val_loss -0.7741 +2024-11-23 05:35:08.018553: Pseudo dice [0.8704] +2024-11-23 05:35:08.018643: Epoch time: 18.26 s +2024-11-23 05:35:09.023766: +2024-11-23 05:35:09.023991: Epoch 7718 +2024-11-23 05:35:09.024123: Current learning rate: 0.00049 +2024-11-23 05:35:28.194451: train_loss -0.8383 +2024-11-23 05:35:28.194676: val_loss -0.792 +2024-11-23 05:35:28.194752: Pseudo dice [0.8586] +2024-11-23 05:35:28.194826: Epoch time: 19.17 s +2024-11-23 05:35:29.296822: +2024-11-23 05:35:29.297039: Epoch 7719 +2024-11-23 05:35:29.297163: Current learning rate: 0.00049 +2024-11-23 05:35:48.103281: train_loss -0.8386 +2024-11-23 05:35:48.103499: val_loss -0.7753 +2024-11-23 05:35:48.103585: Pseudo dice [0.8696] +2024-11-23 05:35:48.103665: Epoch time: 18.81 s +2024-11-23 05:35:49.059753: +2024-11-23 05:35:49.060004: Epoch 7720 +2024-11-23 05:35:49.060123: Current learning rate: 0.00049 +2024-11-23 05:36:07.589687: train_loss -0.8405 +2024-11-23 05:36:07.589923: val_loss -0.7906 +2024-11-23 05:36:07.590025: Pseudo dice [0.8659] +2024-11-23 05:36:07.590121: Epoch time: 18.53 s +2024-11-23 05:36:08.952790: +2024-11-23 05:36:08.953010: Epoch 7721 +2024-11-23 05:36:08.953137: Current learning rate: 0.00049 +2024-11-23 05:36:28.179844: train_loss -0.8386 +2024-11-23 05:36:28.180070: val_loss -0.7874 +2024-11-23 05:36:28.180150: Pseudo dice [0.8508] +2024-11-23 05:36:28.180232: Epoch time: 19.23 s +2024-11-23 05:36:29.075459: +2024-11-23 05:36:29.075679: Epoch 7722 +2024-11-23 05:36:29.075801: Current learning rate: 0.00049 +2024-11-23 05:36:48.200377: train_loss -0.8317 +2024-11-23 05:36:48.200592: val_loss -0.7713 +2024-11-23 05:36:48.200681: Pseudo dice [0.8637] +2024-11-23 05:36:48.200756: Epoch time: 19.13 s +2024-11-23 05:36:49.093368: +2024-11-23 05:36:49.093580: Epoch 7723 +2024-11-23 05:36:49.093697: Current learning rate: 0.00048 +2024-11-23 05:37:06.764553: train_loss -0.8345 +2024-11-23 05:37:06.764770: val_loss -0.7865 +2024-11-23 05:37:06.764873: Pseudo dice [0.8748] +2024-11-23 05:37:06.764973: Epoch time: 17.67 s +2024-11-23 05:37:07.663215: +2024-11-23 05:37:07.663437: Epoch 7724 +2024-11-23 05:37:07.663549: Current learning rate: 0.00048 +2024-11-23 05:37:26.636492: train_loss -0.8348 +2024-11-23 05:37:26.636746: val_loss -0.7799 +2024-11-23 05:37:26.636837: Pseudo dice [0.8762] +2024-11-23 05:37:26.636946: Epoch time: 18.97 s +2024-11-23 05:37:27.537730: +2024-11-23 05:37:27.537963: Epoch 7725 +2024-11-23 05:37:27.538086: Current learning rate: 0.00048 +2024-11-23 05:37:46.070909: train_loss -0.8336 +2024-11-23 05:37:46.071376: val_loss -0.7651 +2024-11-23 05:37:46.071476: Pseudo dice [0.868] +2024-11-23 05:37:46.071553: Epoch time: 18.53 s +2024-11-23 05:37:46.965953: +2024-11-23 05:37:46.966223: Epoch 7726 +2024-11-23 05:37:46.966351: Current learning rate: 0.00048 +2024-11-23 05:38:04.359972: train_loss -0.84 +2024-11-23 05:38:04.360193: val_loss -0.8032 +2024-11-23 05:38:04.360278: Pseudo dice [0.8699] +2024-11-23 05:38:04.360370: Epoch time: 17.39 s +2024-11-23 05:38:05.257766: +2024-11-23 05:38:05.257990: Epoch 7727 +2024-11-23 05:38:05.258105: Current learning rate: 0.00048 +2024-11-23 05:38:22.999463: train_loss -0.8321 +2024-11-23 05:38:22.999684: val_loss -0.8027 +2024-11-23 05:38:22.999763: Pseudo dice [0.8686] +2024-11-23 05:38:22.999840: Epoch time: 17.74 s +2024-11-23 05:38:23.894749: +2024-11-23 05:38:23.894984: Epoch 7728 +2024-11-23 05:38:23.895108: Current learning rate: 0.00048 +2024-11-23 05:38:42.451486: train_loss -0.8398 +2024-11-23 05:38:42.451732: val_loss -0.789 +2024-11-23 05:38:42.451872: Pseudo dice [0.8648] +2024-11-23 05:38:42.451997: Epoch time: 18.56 s +2024-11-23 05:38:43.348556: +2024-11-23 05:38:43.348790: Epoch 7729 +2024-11-23 05:38:43.348907: Current learning rate: 0.00048 +2024-11-23 05:39:01.876699: train_loss -0.8336 +2024-11-23 05:39:01.876907: val_loss -0.8027 +2024-11-23 05:39:01.876982: Pseudo dice [0.8633] +2024-11-23 05:39:01.877066: Epoch time: 18.53 s +2024-11-23 05:39:02.772178: +2024-11-23 05:39:02.772394: Epoch 7730 +2024-11-23 05:39:02.772511: Current learning rate: 0.00047 +2024-11-23 05:39:21.037459: train_loss -0.8358 +2024-11-23 05:39:21.037675: val_loss -0.784 +2024-11-23 05:39:21.037771: Pseudo dice [0.8636] +2024-11-23 05:39:21.037858: Epoch time: 18.27 s +2024-11-23 05:39:21.930755: +2024-11-23 05:39:21.930958: Epoch 7731 +2024-11-23 05:39:21.931076: Current learning rate: 0.00047 +2024-11-23 05:39:40.619950: train_loss -0.834 +2024-11-23 05:39:40.620205: val_loss -0.7985 +2024-11-23 05:39:40.620286: Pseudo dice [0.8661] +2024-11-23 05:39:40.620374: Epoch time: 18.69 s +2024-11-23 05:39:42.127665: +2024-11-23 05:39:42.127920: Epoch 7732 +2024-11-23 05:39:42.128037: Current learning rate: 0.00047 +2024-11-23 05:40:00.122389: train_loss -0.8334 +2024-11-23 05:40:00.122618: val_loss -0.8044 +2024-11-23 05:40:00.122701: Pseudo dice [0.8685] +2024-11-23 05:40:00.122780: Epoch time: 18.0 s +2024-11-23 05:40:01.017485: +2024-11-23 05:40:01.017724: Epoch 7733 +2024-11-23 05:40:01.017850: Current learning rate: 0.00047 +2024-11-23 05:40:19.823816: train_loss -0.8448 +2024-11-23 05:40:19.824029: val_loss -0.7726 +2024-11-23 05:40:19.824113: Pseudo dice [0.8649] +2024-11-23 05:40:19.824211: Epoch time: 18.81 s +2024-11-23 05:40:20.756989: +2024-11-23 05:40:20.757226: Epoch 7734 +2024-11-23 05:40:20.757347: Current learning rate: 0.00047 +2024-11-23 05:40:39.448847: train_loss -0.8304 +2024-11-23 05:40:39.449090: val_loss -0.7682 +2024-11-23 05:40:39.449182: Pseudo dice [0.8413] +2024-11-23 05:40:39.449277: Epoch time: 18.69 s +2024-11-23 05:40:40.344144: +2024-11-23 05:40:40.344378: Epoch 7735 +2024-11-23 05:40:40.344498: Current learning rate: 0.00047 +2024-11-23 05:41:00.392974: train_loss -0.8349 +2024-11-23 05:41:00.393210: val_loss -0.7936 +2024-11-23 05:41:00.393292: Pseudo dice [0.8547] +2024-11-23 05:41:00.393387: Epoch time: 20.05 s +2024-11-23 05:41:01.292510: +2024-11-23 05:41:01.292730: Epoch 7736 +2024-11-23 05:41:01.292842: Current learning rate: 0.00046 +2024-11-23 05:41:19.623526: train_loss -0.8398 +2024-11-23 05:41:19.623740: val_loss -0.803 +2024-11-23 05:41:19.623822: Pseudo dice [0.868] +2024-11-23 05:41:19.623911: Epoch time: 18.33 s +2024-11-23 05:41:20.521023: +2024-11-23 05:41:20.521233: Epoch 7737 +2024-11-23 05:41:20.521348: Current learning rate: 0.00046 +2024-11-23 05:41:39.737989: train_loss -0.8368 +2024-11-23 05:41:39.738200: val_loss -0.7937 +2024-11-23 05:41:39.738287: Pseudo dice [0.8581] +2024-11-23 05:41:39.738387: Epoch time: 19.22 s +2024-11-23 05:41:40.637461: +2024-11-23 05:41:40.637680: Epoch 7738 +2024-11-23 05:41:40.637806: Current learning rate: 0.00046 +2024-11-23 05:41:59.668830: train_loss -0.8326 +2024-11-23 05:41:59.669148: val_loss -0.7857 +2024-11-23 05:41:59.669238: Pseudo dice [0.8632] +2024-11-23 05:41:59.669343: Epoch time: 19.03 s +2024-11-23 05:42:00.570053: +2024-11-23 05:42:00.570276: Epoch 7739 +2024-11-23 05:42:00.570394: Current learning rate: 0.00046 +2024-11-23 05:42:20.207164: train_loss -0.8312 +2024-11-23 05:42:20.207366: val_loss -0.7965 +2024-11-23 05:42:20.207458: Pseudo dice [0.8737] +2024-11-23 05:42:20.207541: Epoch time: 19.64 s +2024-11-23 05:42:21.107723: +2024-11-23 05:42:21.107932: Epoch 7740 +2024-11-23 05:42:21.108046: Current learning rate: 0.00046 +2024-11-23 05:42:39.340844: train_loss -0.837 +2024-11-23 05:42:39.341067: val_loss -0.7994 +2024-11-23 05:42:39.341141: Pseudo dice [0.8825] +2024-11-23 05:42:39.341218: Epoch time: 18.23 s +2024-11-23 05:42:40.266752: +2024-11-23 05:42:40.266964: Epoch 7741 +2024-11-23 05:42:40.267086: Current learning rate: 0.00046 +2024-11-23 05:42:59.511253: train_loss -0.8322 +2024-11-23 05:42:59.511453: val_loss -0.7852 +2024-11-23 05:42:59.511543: Pseudo dice [0.8496] +2024-11-23 05:42:59.511619: Epoch time: 19.25 s +2024-11-23 05:43:00.411340: +2024-11-23 05:43:00.411549: Epoch 7742 +2024-11-23 05:43:00.411684: Current learning rate: 0.00045 +2024-11-23 05:43:18.315791: train_loss -0.832 +2024-11-23 05:43:18.316018: val_loss -0.7725 +2024-11-23 05:43:18.316103: Pseudo dice [0.8541] +2024-11-23 05:43:18.316208: Epoch time: 17.91 s +2024-11-23 05:43:19.209339: +2024-11-23 05:43:19.209780: Epoch 7743 +2024-11-23 05:43:19.209929: Current learning rate: 0.00045 +2024-11-23 05:43:37.466462: train_loss -0.8371 +2024-11-23 05:43:37.466699: val_loss -0.7907 +2024-11-23 05:43:37.466776: Pseudo dice [0.8575] +2024-11-23 05:43:37.466853: Epoch time: 18.26 s +2024-11-23 05:43:38.365637: +2024-11-23 05:43:38.365854: Epoch 7744 +2024-11-23 05:43:38.365974: Current learning rate: 0.00045 +2024-11-23 05:43:57.153552: train_loss -0.8352 +2024-11-23 05:43:57.153761: val_loss -0.7707 +2024-11-23 05:43:57.153847: Pseudo dice [0.8624] +2024-11-23 05:43:57.153940: Epoch time: 18.79 s +2024-11-23 05:43:58.034787: +2024-11-23 05:43:58.035006: Epoch 7745 +2024-11-23 05:43:58.035125: Current learning rate: 0.00045 +2024-11-23 05:44:16.542267: train_loss -0.8381 +2024-11-23 05:44:16.542475: val_loss -0.7846 +2024-11-23 05:44:16.542554: Pseudo dice [0.8579] +2024-11-23 05:44:16.542640: Epoch time: 18.51 s +2024-11-23 05:44:17.445110: +2024-11-23 05:44:17.445383: Epoch 7746 +2024-11-23 05:44:17.445525: Current learning rate: 0.00045 +2024-11-23 05:44:35.670065: train_loss -0.8377 +2024-11-23 05:44:35.670282: val_loss -0.7687 +2024-11-23 05:44:35.670360: Pseudo dice [0.8433] +2024-11-23 05:44:35.670508: Epoch time: 18.23 s +2024-11-23 05:44:36.573508: +2024-11-23 05:44:36.573746: Epoch 7747 +2024-11-23 05:44:36.573862: Current learning rate: 0.00045 +2024-11-23 05:44:55.101120: train_loss -0.8379 +2024-11-23 05:44:55.101338: val_loss -0.7923 +2024-11-23 05:44:55.101416: Pseudo dice [0.8626] +2024-11-23 05:44:55.101519: Epoch time: 18.53 s +2024-11-23 05:44:56.134455: +2024-11-23 05:44:56.134719: Epoch 7748 +2024-11-23 05:44:56.134835: Current learning rate: 0.00045 +2024-11-23 05:45:16.603453: train_loss -0.8354 +2024-11-23 05:45:16.603657: val_loss -0.7932 +2024-11-23 05:45:16.603737: Pseudo dice [0.8682] +2024-11-23 05:45:16.603818: Epoch time: 20.47 s +2024-11-23 05:45:17.483999: +2024-11-23 05:45:17.484231: Epoch 7749 +2024-11-23 05:45:17.484378: Current learning rate: 0.00044 +2024-11-23 05:45:35.722822: train_loss -0.8387 +2024-11-23 05:45:35.723033: val_loss -0.7877 +2024-11-23 05:45:35.723178: Pseudo dice [0.8621] +2024-11-23 05:45:35.723271: Epoch time: 18.24 s +2024-11-23 05:45:37.019532: +2024-11-23 05:45:37.019763: Epoch 7750 +2024-11-23 05:45:37.019875: Current learning rate: 0.00044 +2024-11-23 05:45:55.627034: train_loss -0.838 +2024-11-23 05:45:55.627291: val_loss -0.7676 +2024-11-23 05:45:55.627376: Pseudo dice [0.8607] +2024-11-23 05:45:55.627481: Epoch time: 18.61 s +2024-11-23 05:45:56.504679: +2024-11-23 05:45:56.504884: Epoch 7751 +2024-11-23 05:45:56.505003: Current learning rate: 0.00044 +2024-11-23 05:46:14.090264: train_loss -0.8386 +2024-11-23 05:46:14.090477: val_loss -0.7676 +2024-11-23 05:46:14.090559: Pseudo dice [0.8551] +2024-11-23 05:46:14.090643: Epoch time: 17.59 s +2024-11-23 05:46:14.995553: +2024-11-23 05:46:14.995780: Epoch 7752 +2024-11-23 05:46:14.995895: Current learning rate: 0.00044 +2024-11-23 05:46:32.878760: train_loss -0.8405 +2024-11-23 05:46:32.878983: val_loss -0.7894 +2024-11-23 05:46:32.879072: Pseudo dice [0.8518] +2024-11-23 05:46:32.879158: Epoch time: 17.88 s +2024-11-23 05:46:33.779385: +2024-11-23 05:46:33.779590: Epoch 7753 +2024-11-23 05:46:33.779720: Current learning rate: 0.00044 +2024-11-23 05:46:52.535329: train_loss -0.8426 +2024-11-23 05:46:52.535557: val_loss -0.7861 +2024-11-23 05:46:52.535716: Pseudo dice [0.8599] +2024-11-23 05:46:52.535820: Epoch time: 18.76 s +2024-11-23 05:46:53.975445: +2024-11-23 05:46:53.975682: Epoch 7754 +2024-11-23 05:46:53.975793: Current learning rate: 0.00044 +2024-11-23 05:47:12.238747: train_loss -0.8381 +2024-11-23 05:47:12.239014: val_loss -0.778 +2024-11-23 05:47:12.239102: Pseudo dice [0.8724] +2024-11-23 05:47:12.239189: Epoch time: 18.26 s +2024-11-23 05:47:13.141739: +2024-11-23 05:47:13.141969: Epoch 7755 +2024-11-23 05:47:13.142085: Current learning rate: 0.00043 +2024-11-23 05:47:31.468630: train_loss -0.8286 +2024-11-23 05:47:31.468839: val_loss -0.7794 +2024-11-23 05:47:31.468915: Pseudo dice [0.866] +2024-11-23 05:47:31.468993: Epoch time: 18.33 s +2024-11-23 05:47:32.362111: +2024-11-23 05:47:32.362338: Epoch 7756 +2024-11-23 05:47:32.362471: Current learning rate: 0.00043 +2024-11-23 05:47:51.878428: train_loss -0.8348 +2024-11-23 05:47:51.878640: val_loss -0.7725 +2024-11-23 05:47:51.878719: Pseudo dice [0.854] +2024-11-23 05:47:51.880973: Epoch time: 19.52 s +2024-11-23 05:47:52.835221: +2024-11-23 05:47:52.835438: Epoch 7757 +2024-11-23 05:47:52.835565: Current learning rate: 0.00043 +2024-11-23 05:48:10.565839: train_loss -0.8303 +2024-11-23 05:48:10.566076: val_loss -0.7931 +2024-11-23 05:48:10.566158: Pseudo dice [0.8714] +2024-11-23 05:48:10.566242: Epoch time: 17.73 s +2024-11-23 05:48:11.471205: +2024-11-23 05:48:11.471434: Epoch 7758 +2024-11-23 05:48:11.471567: Current learning rate: 0.00043 +2024-11-23 05:48:30.443001: train_loss -0.8386 +2024-11-23 05:48:30.443221: val_loss -0.8023 +2024-11-23 05:48:30.443299: Pseudo dice [0.8554] +2024-11-23 05:48:30.443394: Epoch time: 18.97 s +2024-11-23 05:48:31.339439: +2024-11-23 05:48:31.339654: Epoch 7759 +2024-11-23 05:48:31.339786: Current learning rate: 0.00043 +2024-11-23 05:48:49.703799: train_loss -0.8408 +2024-11-23 05:48:49.704032: val_loss -0.7995 +2024-11-23 05:48:49.704134: Pseudo dice [0.8566] +2024-11-23 05:48:49.704221: Epoch time: 18.37 s +2024-11-23 05:48:50.827658: +2024-11-23 05:48:50.827861: Epoch 7760 +2024-11-23 05:48:50.827990: Current learning rate: 0.00043 +2024-11-23 05:49:09.089644: train_loss -0.8385 +2024-11-23 05:49:09.089878: val_loss -0.7697 +2024-11-23 05:49:09.089957: Pseudo dice [0.8662] +2024-11-23 05:49:09.090040: Epoch time: 18.26 s +2024-11-23 05:49:09.989631: +2024-11-23 05:49:09.989856: Epoch 7761 +2024-11-23 05:49:09.989974: Current learning rate: 0.00042 +2024-11-23 05:49:27.794361: train_loss -0.8355 +2024-11-23 05:49:27.794652: val_loss -0.7832 +2024-11-23 05:49:27.794734: Pseudo dice [0.8671] +2024-11-23 05:49:27.794814: Epoch time: 17.81 s +2024-11-23 05:49:28.734879: +2024-11-23 05:49:28.735104: Epoch 7762 +2024-11-23 05:49:28.735227: Current learning rate: 0.00042 +2024-11-23 05:49:46.767802: train_loss -0.8324 +2024-11-23 05:49:46.768029: val_loss -0.7743 +2024-11-23 05:49:46.768111: Pseudo dice [0.8682] +2024-11-23 05:49:46.768185: Epoch time: 18.03 s +2024-11-23 05:49:47.670635: +2024-11-23 05:49:47.670842: Epoch 7763 +2024-11-23 05:49:47.670955: Current learning rate: 0.00042 +2024-11-23 05:50:06.882620: train_loss -0.8384 +2024-11-23 05:50:06.884974: val_loss -0.797 +2024-11-23 05:50:06.885184: Pseudo dice [0.8728] +2024-11-23 05:50:06.885291: Epoch time: 19.21 s +2024-11-23 05:50:07.813040: +2024-11-23 05:50:07.813254: Epoch 7764 +2024-11-23 05:50:07.813368: Current learning rate: 0.00042 +2024-11-23 05:50:26.191019: train_loss -0.8406 +2024-11-23 05:50:26.191352: val_loss -0.7661 +2024-11-23 05:50:26.191452: Pseudo dice [0.8616] +2024-11-23 05:50:26.191562: Epoch time: 18.38 s +2024-11-23 05:50:27.092223: +2024-11-23 05:50:27.092433: Epoch 7765 +2024-11-23 05:50:27.092545: Current learning rate: 0.00042 +2024-11-23 05:50:45.270214: train_loss -0.8417 +2024-11-23 05:50:45.270552: val_loss -0.7914 +2024-11-23 05:50:45.270643: Pseudo dice [0.8725] +2024-11-23 05:50:45.270751: Epoch time: 18.18 s +2024-11-23 05:50:46.164909: +2024-11-23 05:50:46.165129: Epoch 7766 +2024-11-23 05:50:46.165249: Current learning rate: 0.00042 +2024-11-23 05:51:05.133162: train_loss -0.8369 +2024-11-23 05:51:05.133377: val_loss -0.8082 +2024-11-23 05:51:05.133476: Pseudo dice [0.8695] +2024-11-23 05:51:05.133564: Epoch time: 18.97 s +2024-11-23 05:51:06.033602: +2024-11-23 05:51:06.033818: Epoch 7767 +2024-11-23 05:51:06.033948: Current learning rate: 0.00041 +2024-11-23 05:51:23.831728: train_loss -0.8387 +2024-11-23 05:51:23.832032: val_loss -0.7717 +2024-11-23 05:51:23.832126: Pseudo dice [0.8574] +2024-11-23 05:51:23.832215: Epoch time: 17.8 s +2024-11-23 05:51:24.730451: +2024-11-23 05:51:24.730709: Epoch 7768 +2024-11-23 05:51:24.730832: Current learning rate: 0.00041 +2024-11-23 05:51:42.624490: train_loss -0.8409 +2024-11-23 05:51:42.624752: val_loss -0.7656 +2024-11-23 05:51:42.624839: Pseudo dice [0.8561] +2024-11-23 05:51:42.624929: Epoch time: 17.89 s +2024-11-23 05:51:43.531793: +2024-11-23 05:51:43.532011: Epoch 7769 +2024-11-23 05:51:43.532135: Current learning rate: 0.00041 +2024-11-23 05:52:02.229870: train_loss -0.8334 +2024-11-23 05:52:02.230091: val_loss -0.7761 +2024-11-23 05:52:02.230170: Pseudo dice [0.8611] +2024-11-23 05:52:02.230261: Epoch time: 18.7 s +2024-11-23 05:52:03.127724: +2024-11-23 05:52:03.127996: Epoch 7770 +2024-11-23 05:52:03.128126: Current learning rate: 0.00041 +2024-11-23 05:52:21.903231: train_loss -0.8395 +2024-11-23 05:52:21.903446: val_loss -0.7982 +2024-11-23 05:52:21.903524: Pseudo dice [0.8644] +2024-11-23 05:52:21.903597: Epoch time: 18.78 s +2024-11-23 05:52:22.809535: +2024-11-23 05:52:22.809753: Epoch 7771 +2024-11-23 05:52:22.809883: Current learning rate: 0.00041 +2024-11-23 05:52:40.609927: train_loss -0.8338 +2024-11-23 05:52:40.610152: val_loss -0.7974 +2024-11-23 05:52:40.610235: Pseudo dice [0.8557] +2024-11-23 05:52:40.610324: Epoch time: 17.8 s +2024-11-23 05:52:41.517749: +2024-11-23 05:52:41.518000: Epoch 7772 +2024-11-23 05:52:41.518135: Current learning rate: 0.00041 +2024-11-23 05:53:00.231480: train_loss -0.8379 +2024-11-23 05:53:00.231718: val_loss -0.7995 +2024-11-23 05:53:00.231803: Pseudo dice [0.8687] +2024-11-23 05:53:00.234139: Epoch time: 18.71 s +2024-11-23 05:53:01.154599: +2024-11-23 05:53:01.154799: Epoch 7773 +2024-11-23 05:53:01.154919: Current learning rate: 0.00041 +2024-11-23 05:53:19.042415: train_loss -0.8415 +2024-11-23 05:53:19.042621: val_loss -0.7947 +2024-11-23 05:53:19.042701: Pseudo dice [0.8709] +2024-11-23 05:53:19.042778: Epoch time: 17.89 s +2024-11-23 05:53:20.009208: +2024-11-23 05:53:20.009417: Epoch 7774 +2024-11-23 05:53:20.009526: Current learning rate: 0.0004 +2024-11-23 05:53:37.998326: train_loss -0.8352 +2024-11-23 05:53:37.998528: val_loss -0.7796 +2024-11-23 05:53:37.998618: Pseudo dice [0.8634] +2024-11-23 05:53:37.998695: Epoch time: 17.99 s +2024-11-23 05:53:38.890420: +2024-11-23 05:53:38.890646: Epoch 7775 +2024-11-23 05:53:38.890757: Current learning rate: 0.0004 +2024-11-23 05:53:58.966043: train_loss -0.8336 +2024-11-23 05:53:58.968486: val_loss -0.7836 +2024-11-23 05:53:58.968629: Pseudo dice [0.8523] +2024-11-23 05:53:58.968729: Epoch time: 20.08 s +2024-11-23 05:54:00.386729: +2024-11-23 05:54:00.386978: Epoch 7776 +2024-11-23 05:54:00.387098: Current learning rate: 0.0004 +2024-11-23 05:54:19.254076: train_loss -0.8356 +2024-11-23 05:54:19.254331: val_loss -0.7819 +2024-11-23 05:54:19.254416: Pseudo dice [0.8522] +2024-11-23 05:54:19.254500: Epoch time: 18.87 s +2024-11-23 05:54:20.143292: +2024-11-23 05:54:20.143501: Epoch 7777 +2024-11-23 05:54:20.143623: Current learning rate: 0.0004 +2024-11-23 05:54:38.509714: train_loss -0.8384 +2024-11-23 05:54:38.509946: val_loss -0.7865 +2024-11-23 05:54:38.515247: Pseudo dice [0.8682] +2024-11-23 05:54:38.515373: Epoch time: 18.37 s +2024-11-23 05:54:39.469676: +2024-11-23 05:54:39.469927: Epoch 7778 +2024-11-23 05:54:39.470050: Current learning rate: 0.0004 +2024-11-23 05:54:58.284567: train_loss -0.8367 +2024-11-23 05:54:58.284781: val_loss -0.7937 +2024-11-23 05:54:58.284878: Pseudo dice [0.8658] +2024-11-23 05:54:58.284957: Epoch time: 18.82 s +2024-11-23 05:54:59.183041: +2024-11-23 05:54:59.183258: Epoch 7779 +2024-11-23 05:54:59.183386: Current learning rate: 0.0004 +2024-11-23 05:55:17.139616: train_loss -0.8463 +2024-11-23 05:55:17.139851: val_loss -0.7989 +2024-11-23 05:55:17.139941: Pseudo dice [0.8729] +2024-11-23 05:55:17.140026: Epoch time: 17.96 s +2024-11-23 05:55:18.045387: +2024-11-23 05:55:18.045588: Epoch 7780 +2024-11-23 05:55:18.045703: Current learning rate: 0.00039 +2024-11-23 05:55:36.960260: train_loss -0.8318 +2024-11-23 05:55:36.960524: val_loss -0.7895 +2024-11-23 05:55:36.960622: Pseudo dice [0.8549] +2024-11-23 05:55:36.960719: Epoch time: 18.92 s +2024-11-23 05:55:37.943295: +2024-11-23 05:55:37.943511: Epoch 7781 +2024-11-23 05:55:37.943647: Current learning rate: 0.00039 +2024-11-23 05:55:57.202773: train_loss -0.8375 +2024-11-23 05:55:57.202990: val_loss -0.7993 +2024-11-23 05:55:57.203078: Pseudo dice [0.8685] +2024-11-23 05:55:57.203193: Epoch time: 19.26 s +2024-11-23 05:55:58.100004: +2024-11-23 05:55:58.100226: Epoch 7782 +2024-11-23 05:55:58.100339: Current learning rate: 0.00039 +2024-11-23 05:56:16.470825: train_loss -0.8321 +2024-11-23 05:56:16.471052: val_loss -0.7631 +2024-11-23 05:56:16.471137: Pseudo dice [0.86] +2024-11-23 05:56:16.471211: Epoch time: 18.37 s +2024-11-23 05:56:17.368942: +2024-11-23 05:56:17.369167: Epoch 7783 +2024-11-23 05:56:17.369285: Current learning rate: 0.00039 +2024-11-23 05:56:36.929558: train_loss -0.8384 +2024-11-23 05:56:36.929772: val_loss -0.7611 +2024-11-23 05:56:36.929869: Pseudo dice [0.8647] +2024-11-23 05:56:36.929955: Epoch time: 19.56 s +2024-11-23 05:56:37.834951: +2024-11-23 05:56:37.835155: Epoch 7784 +2024-11-23 05:56:37.835273: Current learning rate: 0.00039 +2024-11-23 05:56:55.491161: train_loss -0.8396 +2024-11-23 05:56:55.491404: val_loss -0.8067 +2024-11-23 05:56:55.491486: Pseudo dice [0.8747] +2024-11-23 05:56:55.491573: Epoch time: 17.66 s +2024-11-23 05:56:56.391389: +2024-11-23 05:56:56.391597: Epoch 7785 +2024-11-23 05:56:56.391717: Current learning rate: 0.00039 +2024-11-23 05:57:15.210614: train_loss -0.83 +2024-11-23 05:57:15.210836: val_loss -0.7857 +2024-11-23 05:57:15.210925: Pseudo dice [0.8643] +2024-11-23 05:57:15.211016: Epoch time: 18.82 s +2024-11-23 05:57:16.112616: +2024-11-23 05:57:16.112826: Epoch 7786 +2024-11-23 05:57:16.112959: Current learning rate: 0.00038 +2024-11-23 05:57:35.274296: train_loss -0.8389 +2024-11-23 05:57:35.274519: val_loss -0.7836 +2024-11-23 05:57:35.274603: Pseudo dice [0.8493] +2024-11-23 05:57:35.275933: Epoch time: 19.16 s +2024-11-23 05:57:36.169579: +2024-11-23 05:57:36.169793: Epoch 7787 +2024-11-23 05:57:36.169915: Current learning rate: 0.00038 +2024-11-23 05:57:54.083537: train_loss -0.8367 +2024-11-23 05:57:54.083808: val_loss -0.801 +2024-11-23 05:57:54.083912: Pseudo dice [0.8646] +2024-11-23 05:57:54.084005: Epoch time: 17.91 s +2024-11-23 05:57:55.006782: +2024-11-23 05:57:55.007014: Epoch 7788 +2024-11-23 05:57:55.007141: Current learning rate: 0.00038 +2024-11-23 05:58:13.691140: train_loss -0.8362 +2024-11-23 05:58:13.691366: val_loss -0.7829 +2024-11-23 05:58:13.691461: Pseudo dice [0.8677] +2024-11-23 05:58:13.693791: Epoch time: 18.69 s +2024-11-23 05:58:14.603190: +2024-11-23 05:58:14.603412: Epoch 7789 +2024-11-23 05:58:14.603540: Current learning rate: 0.00038 +2024-11-23 05:58:33.372643: train_loss -0.8288 +2024-11-23 05:58:33.372864: val_loss -0.7966 +2024-11-23 05:58:33.372945: Pseudo dice [0.8624] +2024-11-23 05:58:33.373023: Epoch time: 18.77 s +2024-11-23 05:58:34.276108: +2024-11-23 05:58:34.276363: Epoch 7790 +2024-11-23 05:58:34.276483: Current learning rate: 0.00038 +2024-11-23 05:58:53.668196: train_loss -0.8355 +2024-11-23 05:58:53.668411: val_loss -0.7695 +2024-11-23 05:58:53.668493: Pseudo dice [0.8695] +2024-11-23 05:58:53.668586: Epoch time: 19.39 s +2024-11-23 05:58:54.675941: +2024-11-23 05:58:54.676197: Epoch 7791 +2024-11-23 05:58:54.676314: Current learning rate: 0.00038 +2024-11-23 05:59:12.811080: train_loss -0.8387 +2024-11-23 05:59:12.811310: val_loss -0.8072 +2024-11-23 05:59:12.811389: Pseudo dice [0.8649] +2024-11-23 05:59:12.811472: Epoch time: 18.14 s +2024-11-23 05:59:13.715463: +2024-11-23 05:59:13.715688: Epoch 7792 +2024-11-23 05:59:13.715821: Current learning rate: 0.00037 +2024-11-23 05:59:32.175287: train_loss -0.8382 +2024-11-23 05:59:32.175498: val_loss -0.7752 +2024-11-23 05:59:32.175584: Pseudo dice [0.8639] +2024-11-23 05:59:32.175661: Epoch time: 18.46 s +2024-11-23 05:59:33.081981: +2024-11-23 05:59:33.082200: Epoch 7793 +2024-11-23 05:59:33.082320: Current learning rate: 0.00037 +2024-11-23 05:59:51.913337: train_loss -0.8395 +2024-11-23 05:59:51.913559: val_loss -0.7949 +2024-11-23 05:59:51.913640: Pseudo dice [0.8701] +2024-11-23 05:59:51.913730: Epoch time: 18.83 s +2024-11-23 05:59:52.849274: +2024-11-23 05:59:52.849490: Epoch 7794 +2024-11-23 05:59:52.849613: Current learning rate: 0.00037 +2024-11-23 06:00:11.968792: train_loss -0.8369 +2024-11-23 06:00:11.974051: val_loss -0.7921 +2024-11-23 06:00:11.974156: Pseudo dice [0.8617] +2024-11-23 06:00:11.974240: Epoch time: 19.12 s +2024-11-23 06:00:12.941508: +2024-11-23 06:00:12.941774: Epoch 7795 +2024-11-23 06:00:12.941896: Current learning rate: 0.00037 +2024-11-23 06:00:31.673284: train_loss -0.8362 +2024-11-23 06:00:31.673501: val_loss -0.7779 +2024-11-23 06:00:31.673577: Pseudo dice [0.8606] +2024-11-23 06:00:31.673665: Epoch time: 18.73 s +2024-11-23 06:00:32.598439: +2024-11-23 06:00:32.598669: Epoch 7796 +2024-11-23 06:00:32.598786: Current learning rate: 0.00037 +2024-11-23 06:00:51.509893: train_loss -0.8385 +2024-11-23 06:00:51.510109: val_loss -0.7962 +2024-11-23 06:00:51.510189: Pseudo dice [0.8697] +2024-11-23 06:00:51.510276: Epoch time: 18.91 s +2024-11-23 06:00:52.409731: +2024-11-23 06:00:52.409940: Epoch 7797 +2024-11-23 06:00:52.410056: Current learning rate: 0.00037 +2024-11-23 06:01:10.597725: train_loss -0.8398 +2024-11-23 06:01:10.597943: val_loss -0.7901 +2024-11-23 06:01:10.598024: Pseudo dice [0.8764] +2024-11-23 06:01:10.598116: Epoch time: 18.19 s +2024-11-23 06:01:11.874014: +2024-11-23 06:01:11.874219: Epoch 7798 +2024-11-23 06:01:11.874330: Current learning rate: 0.00036 +2024-11-23 06:01:30.834409: train_loss -0.8378 +2024-11-23 06:01:30.834679: val_loss -0.7824 +2024-11-23 06:01:30.834776: Pseudo dice [0.8596] +2024-11-23 06:01:30.834867: Epoch time: 18.96 s +2024-11-23 06:01:31.736869: +2024-11-23 06:01:31.737101: Epoch 7799 +2024-11-23 06:01:31.737214: Current learning rate: 0.00036 +2024-11-23 06:01:51.506341: train_loss -0.8363 +2024-11-23 06:01:51.506576: val_loss -0.7782 +2024-11-23 06:01:51.506716: Pseudo dice [0.8661] +2024-11-23 06:01:51.506798: Epoch time: 19.77 s +2024-11-23 06:01:52.759137: +2024-11-23 06:01:52.759365: Epoch 7800 +2024-11-23 06:01:52.759478: Current learning rate: 0.00036 +2024-11-23 06:02:11.841334: train_loss -0.8376 +2024-11-23 06:02:11.841558: val_loss -0.7947 +2024-11-23 06:02:11.841648: Pseudo dice [0.8612] +2024-11-23 06:02:11.841727: Epoch time: 19.08 s +2024-11-23 06:02:12.764014: +2024-11-23 06:02:12.764260: Epoch 7801 +2024-11-23 06:02:12.764374: Current learning rate: 0.00036 +2024-11-23 06:02:30.697809: train_loss -0.8384 +2024-11-23 06:02:30.698033: val_loss -0.7831 +2024-11-23 06:02:30.703332: Pseudo dice [0.8626] +2024-11-23 06:02:30.703437: Epoch time: 17.93 s +2024-11-23 06:02:31.888928: +2024-11-23 06:02:31.889176: Epoch 7802 +2024-11-23 06:02:31.889301: Current learning rate: 0.00036 +2024-11-23 06:02:50.632292: train_loss -0.8332 +2024-11-23 06:02:50.632532: val_loss -0.7811 +2024-11-23 06:02:50.632621: Pseudo dice [0.8678] +2024-11-23 06:02:50.634936: Epoch time: 18.74 s +2024-11-23 06:02:51.706890: +2024-11-23 06:02:51.707169: Epoch 7803 +2024-11-23 06:02:51.707513: Current learning rate: 0.00036 +2024-11-23 06:03:10.236310: train_loss -0.8419 +2024-11-23 06:03:10.236536: val_loss -0.7997 +2024-11-23 06:03:10.236619: Pseudo dice [0.8732] +2024-11-23 06:03:10.236703: Epoch time: 18.53 s +2024-11-23 06:03:11.135567: +2024-11-23 06:03:11.135790: Epoch 7804 +2024-11-23 06:03:11.135901: Current learning rate: 0.00036 +2024-11-23 06:03:30.402708: train_loss -0.8359 +2024-11-23 06:03:30.402922: val_loss -0.7999 +2024-11-23 06:03:30.403007: Pseudo dice [0.8733] +2024-11-23 06:03:30.403090: Epoch time: 19.27 s +2024-11-23 06:03:31.299145: +2024-11-23 06:03:31.299358: Epoch 7805 +2024-11-23 06:03:31.299478: Current learning rate: 0.00035 +2024-11-23 06:03:49.165536: train_loss -0.8364 +2024-11-23 06:03:49.170933: val_loss -0.7971 +2024-11-23 06:03:49.171073: Pseudo dice [0.866] +2024-11-23 06:03:49.171166: Epoch time: 17.87 s +2024-11-23 06:03:50.295072: +2024-11-23 06:03:50.295366: Epoch 7806 +2024-11-23 06:03:50.295485: Current learning rate: 0.00035 +2024-11-23 06:04:09.883376: train_loss -0.8345 +2024-11-23 06:04:09.883620: val_loss -0.7793 +2024-11-23 06:04:09.883706: Pseudo dice [0.8721] +2024-11-23 06:04:09.883788: Epoch time: 19.59 s +2024-11-23 06:04:10.777457: +2024-11-23 06:04:10.777666: Epoch 7807 +2024-11-23 06:04:10.777795: Current learning rate: 0.00035 +2024-11-23 06:04:29.282033: train_loss -0.8326 +2024-11-23 06:04:29.282248: val_loss -0.7892 +2024-11-23 06:04:29.282328: Pseudo dice [0.8696] +2024-11-23 06:04:29.282403: Epoch time: 18.51 s +2024-11-23 06:04:30.180463: +2024-11-23 06:04:30.180683: Epoch 7808 +2024-11-23 06:04:30.180793: Current learning rate: 0.00035 +2024-11-23 06:04:47.991330: train_loss -0.8438 +2024-11-23 06:04:47.991539: val_loss -0.7823 +2024-11-23 06:04:47.991614: Pseudo dice [0.869] +2024-11-23 06:04:47.991686: Epoch time: 17.81 s +2024-11-23 06:04:47.991755: Yayy! New best EMA pseudo Dice: 0.8674 +2024-11-23 06:04:49.610334: +2024-11-23 06:04:49.610560: Epoch 7809 +2024-11-23 06:04:49.610679: Current learning rate: 0.00035 +2024-11-23 06:05:08.300439: train_loss -0.8395 +2024-11-23 06:05:08.302893: val_loss -0.7914 +2024-11-23 06:05:08.302987: Pseudo dice [0.8694] +2024-11-23 06:05:08.303102: Epoch time: 18.69 s +2024-11-23 06:05:08.303168: Yayy! New best EMA pseudo Dice: 0.8676 +2024-11-23 06:05:09.773717: +2024-11-23 06:05:09.773938: Epoch 7810 +2024-11-23 06:05:09.774050: Current learning rate: 0.00035 +2024-11-23 06:05:28.972002: train_loss -0.8382 +2024-11-23 06:05:28.972250: val_loss -0.7871 +2024-11-23 06:05:28.972345: Pseudo dice [0.8709] +2024-11-23 06:05:28.972440: Epoch time: 19.2 s +2024-11-23 06:05:28.972514: Yayy! New best EMA pseudo Dice: 0.868 +2024-11-23 06:05:30.215980: +2024-11-23 06:05:30.216216: Epoch 7811 +2024-11-23 06:05:30.216357: Current learning rate: 0.00034 +2024-11-23 06:05:48.534016: train_loss -0.84 +2024-11-23 06:05:48.534245: val_loss -0.7573 +2024-11-23 06:05:48.535990: Pseudo dice [0.8539] +2024-11-23 06:05:48.536080: Epoch time: 18.32 s +2024-11-23 06:05:49.546706: +2024-11-23 06:05:49.546937: Epoch 7812 +2024-11-23 06:05:49.547080: Current learning rate: 0.00034 +2024-11-23 06:06:06.936686: train_loss -0.8416 +2024-11-23 06:06:06.936899: val_loss -0.8115 +2024-11-23 06:06:06.936974: Pseudo dice [0.868] +2024-11-23 06:06:06.937050: Epoch time: 17.39 s +2024-11-23 06:06:07.841026: +2024-11-23 06:06:07.841229: Epoch 7813 +2024-11-23 06:06:07.841345: Current learning rate: 0.00034 +2024-11-23 06:06:26.107806: train_loss -0.8364 +2024-11-23 06:06:26.108052: val_loss -0.783 +2024-11-23 06:06:26.108140: Pseudo dice [0.8604] +2024-11-23 06:06:26.108235: Epoch time: 18.27 s +2024-11-23 06:06:27.020788: +2024-11-23 06:06:27.021011: Epoch 7814 +2024-11-23 06:06:27.021139: Current learning rate: 0.00034 +2024-11-23 06:06:46.231027: train_loss -0.8366 +2024-11-23 06:06:46.231237: val_loss -0.8091 +2024-11-23 06:06:46.231314: Pseudo dice [0.8695] +2024-11-23 06:06:46.231389: Epoch time: 19.21 s +2024-11-23 06:06:47.129077: +2024-11-23 06:06:47.129303: Epoch 7815 +2024-11-23 06:06:47.129419: Current learning rate: 0.00034 +2024-11-23 06:07:05.163486: train_loss -0.8447 +2024-11-23 06:07:05.163695: val_loss -0.7905 +2024-11-23 06:07:05.163825: Pseudo dice [0.865] +2024-11-23 06:07:05.163911: Epoch time: 18.04 s +2024-11-23 06:07:06.062476: +2024-11-23 06:07:06.062693: Epoch 7816 +2024-11-23 06:07:06.062809: Current learning rate: 0.00034 +2024-11-23 06:07:24.520605: train_loss -0.8371 +2024-11-23 06:07:24.520813: val_loss -0.7897 +2024-11-23 06:07:24.526095: Pseudo dice [0.8553] +2024-11-23 06:07:24.526271: Epoch time: 18.46 s +2024-11-23 06:07:25.439420: +2024-11-23 06:07:25.439649: Epoch 7817 +2024-11-23 06:07:25.439769: Current learning rate: 0.00033 +2024-11-23 06:07:42.655938: train_loss -0.8386 +2024-11-23 06:07:42.656176: val_loss -0.7974 +2024-11-23 06:07:42.656276: Pseudo dice [0.8603] +2024-11-23 06:07:42.656371: Epoch time: 17.22 s +2024-11-23 06:07:43.729483: +2024-11-23 06:07:43.729692: Epoch 7818 +2024-11-23 06:07:43.729807: Current learning rate: 0.00033 +2024-11-23 06:08:01.627308: train_loss -0.8388 +2024-11-23 06:08:01.627509: val_loss -0.7807 +2024-11-23 06:08:01.627624: Pseudo dice [0.8624] +2024-11-23 06:08:01.627720: Epoch time: 17.9 s +2024-11-23 06:08:02.504019: +2024-11-23 06:08:02.504228: Epoch 7819 +2024-11-23 06:08:02.504345: Current learning rate: 0.00033 +2024-11-23 06:08:21.511111: train_loss -0.8399 +2024-11-23 06:08:21.511323: val_loss -0.8148 +2024-11-23 06:08:21.511403: Pseudo dice [0.8648] +2024-11-23 06:08:21.511497: Epoch time: 19.01 s +2024-11-23 06:08:22.741254: +2024-11-23 06:08:22.741466: Epoch 7820 +2024-11-23 06:08:22.741593: Current learning rate: 0.00033 +2024-11-23 06:08:41.827754: train_loss -0.8346 +2024-11-23 06:08:41.827994: val_loss -0.8024 +2024-11-23 06:08:41.828077: Pseudo dice [0.8674] +2024-11-23 06:08:41.828160: Epoch time: 19.09 s +2024-11-23 06:08:42.715266: +2024-11-23 06:08:42.715482: Epoch 7821 +2024-11-23 06:08:42.715610: Current learning rate: 0.00033 +2024-11-23 06:09:00.433357: train_loss -0.8456 +2024-11-23 06:09:00.433588: val_loss -0.8013 +2024-11-23 06:09:00.433691: Pseudo dice [0.8669] +2024-11-23 06:09:00.433769: Epoch time: 17.72 s +2024-11-23 06:09:01.342879: +2024-11-23 06:09:01.343087: Epoch 7822 +2024-11-23 06:09:01.343185: Current learning rate: 0.00033 +2024-11-23 06:09:19.566876: train_loss -0.8426 +2024-11-23 06:09:19.567096: val_loss -0.8018 +2024-11-23 06:09:19.567178: Pseudo dice [0.8574] +2024-11-23 06:09:19.567260: Epoch time: 18.22 s +2024-11-23 06:09:20.465916: +2024-11-23 06:09:20.466132: Epoch 7823 +2024-11-23 06:09:20.466255: Current learning rate: 0.00032 +2024-11-23 06:09:38.968251: train_loss -0.8364 +2024-11-23 06:09:38.968469: val_loss -0.796 +2024-11-23 06:09:38.968549: Pseudo dice [0.8668] +2024-11-23 06:09:38.968645: Epoch time: 18.5 s +2024-11-23 06:09:40.022959: +2024-11-23 06:09:40.023177: Epoch 7824 +2024-11-23 06:09:40.023293: Current learning rate: 0.00032 +2024-11-23 06:09:59.374777: train_loss -0.827 +2024-11-23 06:09:59.375032: val_loss -0.7722 +2024-11-23 06:09:59.375141: Pseudo dice [0.863] +2024-11-23 06:09:59.375239: Epoch time: 19.35 s +2024-11-23 06:10:00.269756: +2024-11-23 06:10:00.269974: Epoch 7825 +2024-11-23 06:10:00.270092: Current learning rate: 0.00032 +2024-11-23 06:10:18.127115: train_loss -0.8286 +2024-11-23 06:10:18.127331: val_loss -0.7671 +2024-11-23 06:10:18.127416: Pseudo dice [0.8547] +2024-11-23 06:10:18.127496: Epoch time: 17.86 s +2024-11-23 06:10:19.031883: +2024-11-23 06:10:19.032109: Epoch 7826 +2024-11-23 06:10:19.032216: Current learning rate: 0.00032 +2024-11-23 06:10:37.877064: train_loss -0.8327 +2024-11-23 06:10:37.877279: val_loss -0.7602 +2024-11-23 06:10:37.877368: Pseudo dice [0.8597] +2024-11-23 06:10:37.877465: Epoch time: 18.85 s +2024-11-23 06:10:38.884142: +2024-11-23 06:10:38.884367: Epoch 7827 +2024-11-23 06:10:38.884480: Current learning rate: 0.00032 +2024-11-23 06:10:57.219085: train_loss -0.8376 +2024-11-23 06:10:57.219316: val_loss -0.7963 +2024-11-23 06:10:57.219396: Pseudo dice [0.876] +2024-11-23 06:10:57.219474: Epoch time: 18.34 s +2024-11-23 06:10:58.384733: +2024-11-23 06:10:58.384939: Epoch 7828 +2024-11-23 06:10:58.385064: Current learning rate: 0.00032 +2024-11-23 06:11:17.549122: train_loss -0.8344 +2024-11-23 06:11:17.549698: val_loss -0.7841 +2024-11-23 06:11:17.549792: Pseudo dice [0.8674] +2024-11-23 06:11:17.549885: Epoch time: 19.17 s +2024-11-23 06:11:18.537324: +2024-11-23 06:11:18.537591: Epoch 7829 +2024-11-23 06:11:18.537711: Current learning rate: 0.00031 +2024-11-23 06:11:36.987772: train_loss -0.8334 +2024-11-23 06:11:36.988007: val_loss -0.752 +2024-11-23 06:11:36.988113: Pseudo dice [0.8421] +2024-11-23 06:11:36.988195: Epoch time: 18.45 s +2024-11-23 06:11:37.883074: +2024-11-23 06:11:37.883324: Epoch 7830 +2024-11-23 06:11:37.883469: Current learning rate: 0.00031 +2024-11-23 06:11:56.414217: train_loss -0.8406 +2024-11-23 06:11:56.414447: val_loss -0.7754 +2024-11-23 06:11:56.414544: Pseudo dice [0.8592] +2024-11-23 06:11:56.414630: Epoch time: 18.53 s +2024-11-23 06:11:57.719708: +2024-11-23 06:11:57.719953: Epoch 7831 +2024-11-23 06:11:57.720081: Current learning rate: 0.00031 +2024-11-23 06:12:16.694787: train_loss -0.8342 +2024-11-23 06:12:16.697122: val_loss -0.8091 +2024-11-23 06:12:16.697253: Pseudo dice [0.8636] +2024-11-23 06:12:16.697343: Epoch time: 18.98 s +2024-11-23 06:12:17.623844: +2024-11-23 06:12:17.624088: Epoch 7832 +2024-11-23 06:12:17.624217: Current learning rate: 0.00031 +2024-11-23 06:12:35.520961: train_loss -0.8467 +2024-11-23 06:12:35.521184: val_loss -0.7945 +2024-11-23 06:12:35.521287: Pseudo dice [0.8594] +2024-11-23 06:12:35.521369: Epoch time: 17.9 s +2024-11-23 06:12:36.419717: +2024-11-23 06:12:36.419959: Epoch 7833 +2024-11-23 06:12:36.420079: Current learning rate: 0.00031 +2024-11-23 06:12:54.305684: train_loss -0.8399 +2024-11-23 06:12:54.305895: val_loss -0.7922 +2024-11-23 06:12:54.305989: Pseudo dice [0.8622] +2024-11-23 06:12:54.306072: Epoch time: 17.89 s +2024-11-23 06:12:55.207475: +2024-11-23 06:12:55.207685: Epoch 7834 +2024-11-23 06:12:55.207808: Current learning rate: 0.00031 +2024-11-23 06:13:14.253808: train_loss -0.8374 +2024-11-23 06:13:14.254040: val_loss -0.7905 +2024-11-23 06:13:14.254130: Pseudo dice [0.8638] +2024-11-23 06:13:14.254213: Epoch time: 19.05 s +2024-11-23 06:13:15.222249: +2024-11-23 06:13:15.222455: Epoch 7835 +2024-11-23 06:13:15.222572: Current learning rate: 0.0003 +2024-11-23 06:13:34.285863: train_loss -0.8381 +2024-11-23 06:13:34.286154: val_loss -0.7657 +2024-11-23 06:13:34.286244: Pseudo dice [0.865] +2024-11-23 06:13:34.286321: Epoch time: 19.06 s +2024-11-23 06:13:35.193384: +2024-11-23 06:13:35.193612: Epoch 7836 +2024-11-23 06:13:35.193729: Current learning rate: 0.0003 +2024-11-23 06:13:53.406956: train_loss -0.8371 +2024-11-23 06:13:53.407156: val_loss -0.7917 +2024-11-23 06:13:53.407233: Pseudo dice [0.8814] +2024-11-23 06:13:53.407328: Epoch time: 18.21 s +2024-11-23 06:13:54.419213: +2024-11-23 06:13:54.419448: Epoch 7837 +2024-11-23 06:13:54.419564: Current learning rate: 0.0003 +2024-11-23 06:14:12.727779: train_loss -0.8427 +2024-11-23 06:14:12.727996: val_loss -0.8009 +2024-11-23 06:14:12.728081: Pseudo dice [0.8734] +2024-11-23 06:14:12.728160: Epoch time: 18.31 s +2024-11-23 06:14:13.626938: +2024-11-23 06:14:13.627177: Epoch 7838 +2024-11-23 06:14:13.627305: Current learning rate: 0.0003 +2024-11-23 06:14:32.303494: train_loss -0.8357 +2024-11-23 06:14:32.305883: val_loss -0.783 +2024-11-23 06:14:32.305973: Pseudo dice [0.8695] +2024-11-23 06:14:32.306050: Epoch time: 18.68 s +2024-11-23 06:14:33.230506: +2024-11-23 06:14:33.230763: Epoch 7839 +2024-11-23 06:14:33.230896: Current learning rate: 0.0003 +2024-11-23 06:14:52.574983: train_loss -0.8336 +2024-11-23 06:14:52.575227: val_loss -0.7931 +2024-11-23 06:14:52.575332: Pseudo dice [0.8621] +2024-11-23 06:14:52.575436: Epoch time: 19.35 s +2024-11-23 06:14:53.471014: +2024-11-23 06:14:53.471246: Epoch 7840 +2024-11-23 06:14:53.471365: Current learning rate: 0.0003 +2024-11-23 06:15:12.292556: train_loss -0.8361 +2024-11-23 06:15:12.292771: val_loss -0.7881 +2024-11-23 06:15:12.292862: Pseudo dice [0.8583] +2024-11-23 06:15:12.292943: Epoch time: 18.82 s +2024-11-23 06:15:13.190424: +2024-11-23 06:15:13.190634: Epoch 7841 +2024-11-23 06:15:13.190764: Current learning rate: 0.00029 +2024-11-23 06:15:32.042057: train_loss -0.8373 +2024-11-23 06:15:32.042280: val_loss -0.782 +2024-11-23 06:15:32.042363: Pseudo dice [0.8621] +2024-11-23 06:15:32.042470: Epoch time: 18.85 s +2024-11-23 06:15:33.310161: +2024-11-23 06:15:33.310357: Epoch 7842 +2024-11-23 06:15:33.310486: Current learning rate: 0.00029 +2024-11-23 06:15:51.761708: train_loss -0.8399 +2024-11-23 06:15:51.762001: val_loss -0.8079 +2024-11-23 06:15:51.762088: Pseudo dice [0.8741] +2024-11-23 06:15:51.762171: Epoch time: 18.45 s +2024-11-23 06:15:52.675503: +2024-11-23 06:15:52.675726: Epoch 7843 +2024-11-23 06:15:52.675841: Current learning rate: 0.00029 +2024-11-23 06:16:11.883391: train_loss -0.8458 +2024-11-23 06:16:11.883633: val_loss -0.7767 +2024-11-23 06:16:11.883730: Pseudo dice [0.8744] +2024-11-23 06:16:11.883809: Epoch time: 19.21 s +2024-11-23 06:16:12.797262: +2024-11-23 06:16:12.797482: Epoch 7844 +2024-11-23 06:16:12.797595: Current learning rate: 0.00029 +2024-11-23 06:16:30.760069: train_loss -0.8455 +2024-11-23 06:16:30.760295: val_loss -0.7927 +2024-11-23 06:16:30.760371: Pseudo dice [0.8602] +2024-11-23 06:16:30.760447: Epoch time: 17.96 s +2024-11-23 06:16:31.678333: +2024-11-23 06:16:31.678540: Epoch 7845 +2024-11-23 06:16:31.678659: Current learning rate: 0.00029 +2024-11-23 06:16:50.061219: train_loss -0.8406 +2024-11-23 06:16:50.061444: val_loss -0.7882 +2024-11-23 06:16:50.061523: Pseudo dice [0.8684] +2024-11-23 06:16:50.061610: Epoch time: 18.38 s +2024-11-23 06:16:50.965618: +2024-11-23 06:16:50.965839: Epoch 7846 +2024-11-23 06:16:50.965951: Current learning rate: 0.00029 +2024-11-23 06:17:08.750229: train_loss -0.8452 +2024-11-23 06:17:08.750468: val_loss -0.7765 +2024-11-23 06:17:08.750548: Pseudo dice [0.8484] +2024-11-23 06:17:08.750633: Epoch time: 17.79 s +2024-11-23 06:17:09.650505: +2024-11-23 06:17:09.650712: Epoch 7847 +2024-11-23 06:17:09.650823: Current learning rate: 0.00028 +2024-11-23 06:17:28.778668: train_loss -0.8386 +2024-11-23 06:17:28.778890: val_loss -0.7851 +2024-11-23 06:17:28.778978: Pseudo dice [0.8543] +2024-11-23 06:17:28.779089: Epoch time: 19.13 s +2024-11-23 06:17:29.677549: +2024-11-23 06:17:29.677773: Epoch 7848 +2024-11-23 06:17:29.677899: Current learning rate: 0.00028 +2024-11-23 06:17:47.845674: train_loss -0.8331 +2024-11-23 06:17:47.845885: val_loss -0.7904 +2024-11-23 06:17:47.845963: Pseudo dice [0.8647] +2024-11-23 06:17:47.846040: Epoch time: 18.17 s +2024-11-23 06:17:48.751474: +2024-11-23 06:17:48.751685: Epoch 7849 +2024-11-23 06:17:48.751807: Current learning rate: 0.00028 +2024-11-23 06:18:05.973571: train_loss -0.8352 +2024-11-23 06:18:05.973786: val_loss -0.7745 +2024-11-23 06:18:05.973873: Pseudo dice [0.8637] +2024-11-23 06:18:05.973974: Epoch time: 17.22 s +2024-11-23 06:18:07.221863: +2024-11-23 06:18:07.222080: Epoch 7850 +2024-11-23 06:18:07.222203: Current learning rate: 0.00028 +2024-11-23 06:18:26.015344: train_loss -0.8393 +2024-11-23 06:18:26.015583: val_loss -0.7767 +2024-11-23 06:18:26.015664: Pseudo dice [0.8654] +2024-11-23 06:18:26.015758: Epoch time: 18.79 s +2024-11-23 06:18:26.921050: +2024-11-23 06:18:26.921271: Epoch 7851 +2024-11-23 06:18:26.921392: Current learning rate: 0.00028 +2024-11-23 06:18:44.860095: train_loss -0.8351 +2024-11-23 06:18:44.860305: val_loss -0.7899 +2024-11-23 06:18:44.860389: Pseudo dice [0.8586] +2024-11-23 06:18:44.860467: Epoch time: 17.94 s +2024-11-23 06:18:45.808650: +2024-11-23 06:18:45.808852: Epoch 7852 +2024-11-23 06:18:45.808979: Current learning rate: 0.00028 +2024-11-23 06:19:03.640275: train_loss -0.8372 +2024-11-23 06:19:03.640487: val_loss -0.7763 +2024-11-23 06:19:03.640571: Pseudo dice [0.8574] +2024-11-23 06:19:03.640662: Epoch time: 17.83 s +2024-11-23 06:19:05.041323: +2024-11-23 06:19:05.041515: Epoch 7853 +2024-11-23 06:19:05.041624: Current learning rate: 0.00027 +2024-11-23 06:19:25.941491: train_loss -0.8393 +2024-11-23 06:19:25.946969: val_loss -0.7915 +2024-11-23 06:19:25.947096: Pseudo dice [0.8635] +2024-11-23 06:19:25.947214: Epoch time: 20.9 s +2024-11-23 06:19:26.968499: +2024-11-23 06:19:26.968720: Epoch 7854 +2024-11-23 06:19:26.968837: Current learning rate: 0.00027 +2024-11-23 06:19:44.632685: train_loss -0.8387 +2024-11-23 06:19:44.632905: val_loss -0.8036 +2024-11-23 06:19:44.632981: Pseudo dice [0.8763] +2024-11-23 06:19:44.633055: Epoch time: 17.67 s +2024-11-23 06:19:45.535526: +2024-11-23 06:19:45.535745: Epoch 7855 +2024-11-23 06:19:45.535872: Current learning rate: 0.00027 +2024-11-23 06:20:04.296568: train_loss -0.8331 +2024-11-23 06:20:04.296799: val_loss -0.7836 +2024-11-23 06:20:04.296900: Pseudo dice [0.8619] +2024-11-23 06:20:04.296978: Epoch time: 18.76 s +2024-11-23 06:20:05.197103: +2024-11-23 06:20:05.197317: Epoch 7856 +2024-11-23 06:20:05.197440: Current learning rate: 0.00027 +2024-11-23 06:20:23.442463: train_loss -0.8434 +2024-11-23 06:20:23.442695: val_loss -0.763 +2024-11-23 06:20:23.442777: Pseudo dice [0.8578] +2024-11-23 06:20:23.442858: Epoch time: 18.25 s +2024-11-23 06:20:24.346071: +2024-11-23 06:20:24.346287: Epoch 7857 +2024-11-23 06:20:24.346404: Current learning rate: 0.00027 +2024-11-23 06:20:42.192286: train_loss -0.8294 +2024-11-23 06:20:42.192526: val_loss -0.7819 +2024-11-23 06:20:42.192651: Pseudo dice [0.8652] +2024-11-23 06:20:42.192743: Epoch time: 17.85 s +2024-11-23 06:20:43.095983: +2024-11-23 06:20:43.096215: Epoch 7858 +2024-11-23 06:20:43.096346: Current learning rate: 0.00027 +2024-11-23 06:21:01.540938: train_loss -0.846 +2024-11-23 06:21:01.541157: val_loss -0.7693 +2024-11-23 06:21:01.541240: Pseudo dice [0.8575] +2024-11-23 06:21:01.541319: Epoch time: 18.45 s +2024-11-23 06:21:02.440566: +2024-11-23 06:21:02.440770: Epoch 7859 +2024-11-23 06:21:02.440883: Current learning rate: 0.00026 +2024-11-23 06:21:21.317670: train_loss -0.8413 +2024-11-23 06:21:21.317894: val_loss -0.7675 +2024-11-23 06:21:21.317995: Pseudo dice [0.8814] +2024-11-23 06:21:21.318076: Epoch time: 18.88 s +2024-11-23 06:21:22.214951: +2024-11-23 06:21:22.215155: Epoch 7860 +2024-11-23 06:21:22.215275: Current learning rate: 0.00026 +2024-11-23 06:21:40.386515: train_loss -0.8446 +2024-11-23 06:21:40.386733: val_loss -0.7986 +2024-11-23 06:21:40.386811: Pseudo dice [0.8582] +2024-11-23 06:21:40.386894: Epoch time: 18.17 s +2024-11-23 06:21:41.292297: +2024-11-23 06:21:41.292532: Epoch 7861 +2024-11-23 06:21:41.292673: Current learning rate: 0.00026 +2024-11-23 06:22:00.305939: train_loss -0.8343 +2024-11-23 06:22:00.306228: val_loss -0.7943 +2024-11-23 06:22:00.306314: Pseudo dice [0.8723] +2024-11-23 06:22:00.306401: Epoch time: 19.01 s +2024-11-23 06:22:01.212418: +2024-11-23 06:22:01.212623: Epoch 7862 +2024-11-23 06:22:01.212738: Current learning rate: 0.00026 +2024-11-23 06:22:19.352463: train_loss -0.8421 +2024-11-23 06:22:19.352666: val_loss -0.7761 +2024-11-23 06:22:19.352742: Pseudo dice [0.8637] +2024-11-23 06:22:19.352818: Epoch time: 18.14 s +2024-11-23 06:22:20.251575: +2024-11-23 06:22:20.251788: Epoch 7863 +2024-11-23 06:22:20.251907: Current learning rate: 0.00026 +2024-11-23 06:22:37.592092: train_loss -0.8371 +2024-11-23 06:22:37.592337: val_loss -0.7976 +2024-11-23 06:22:37.592419: Pseudo dice [0.8589] +2024-11-23 06:22:37.592500: Epoch time: 17.34 s +2024-11-23 06:22:38.490629: +2024-11-23 06:22:38.490842: Epoch 7864 +2024-11-23 06:22:38.490977: Current learning rate: 0.00026 +2024-11-23 06:22:56.678917: train_loss -0.8448 +2024-11-23 06:22:56.679170: val_loss -0.7963 +2024-11-23 06:22:56.679271: Pseudo dice [0.8657] +2024-11-23 06:22:56.679353: Epoch time: 18.19 s +2024-11-23 06:22:57.576108: +2024-11-23 06:22:57.576359: Epoch 7865 +2024-11-23 06:22:57.576494: Current learning rate: 0.00025 +2024-11-23 06:23:15.853931: train_loss -0.8384 +2024-11-23 06:23:15.854152: val_loss -0.7949 +2024-11-23 06:23:15.854256: Pseudo dice [0.8667] +2024-11-23 06:23:15.854350: Epoch time: 18.28 s +2024-11-23 06:23:16.749523: +2024-11-23 06:23:16.749752: Epoch 7866 +2024-11-23 06:23:16.749864: Current learning rate: 0.00025 +2024-11-23 06:23:34.628431: train_loss -0.8377 +2024-11-23 06:23:34.628664: val_loss -0.8007 +2024-11-23 06:23:34.628764: Pseudo dice [0.8788] +2024-11-23 06:23:34.628876: Epoch time: 17.88 s +2024-11-23 06:23:35.526550: +2024-11-23 06:23:35.526780: Epoch 7867 +2024-11-23 06:23:35.526902: Current learning rate: 0.00025 +2024-11-23 06:23:53.884641: train_loss -0.84 +2024-11-23 06:23:53.884862: val_loss -0.7981 +2024-11-23 06:23:53.884941: Pseudo dice [0.8593] +2024-11-23 06:23:53.885021: Epoch time: 18.36 s +2024-11-23 06:23:54.784919: +2024-11-23 06:23:54.785151: Epoch 7868 +2024-11-23 06:23:54.785263: Current learning rate: 0.00025 +2024-11-23 06:24:13.582755: train_loss -0.8469 +2024-11-23 06:24:13.583009: val_loss -0.8037 +2024-11-23 06:24:13.583094: Pseudo dice [0.8568] +2024-11-23 06:24:13.583179: Epoch time: 18.8 s +2024-11-23 06:24:14.625109: +2024-11-23 06:24:14.625335: Epoch 7869 +2024-11-23 06:24:14.625450: Current learning rate: 0.00025 +2024-11-23 06:24:33.173222: train_loss -0.8401 +2024-11-23 06:24:33.173443: val_loss -0.7862 +2024-11-23 06:24:33.173548: Pseudo dice [0.8566] +2024-11-23 06:24:33.173652: Epoch time: 18.55 s +2024-11-23 06:24:34.256038: +2024-11-23 06:24:34.256245: Epoch 7870 +2024-11-23 06:24:34.256355: Current learning rate: 0.00025 +2024-11-23 06:24:52.652725: train_loss -0.835 +2024-11-23 06:24:52.652952: val_loss -0.7842 +2024-11-23 06:24:52.653031: Pseudo dice [0.8663] +2024-11-23 06:24:52.653112: Epoch time: 18.4 s +2024-11-23 06:24:53.552420: +2024-11-23 06:24:53.552621: Epoch 7871 +2024-11-23 06:24:53.552732: Current learning rate: 0.00024 +2024-11-23 06:25:11.818549: train_loss -0.8452 +2024-11-23 06:25:11.818781: val_loss -0.7943 +2024-11-23 06:25:11.818868: Pseudo dice [0.868] +2024-11-23 06:25:11.818968: Epoch time: 18.27 s +2024-11-23 06:25:12.791659: +2024-11-23 06:25:12.791889: Epoch 7872 +2024-11-23 06:25:12.792006: Current learning rate: 0.00024 +2024-11-23 06:25:32.703481: train_loss -0.8414 +2024-11-23 06:25:32.703775: val_loss -0.7914 +2024-11-23 06:25:32.703891: Pseudo dice [0.8612] +2024-11-23 06:25:32.703983: Epoch time: 19.91 s +2024-11-23 06:25:33.597715: +2024-11-23 06:25:33.597926: Epoch 7873 +2024-11-23 06:25:33.598051: Current learning rate: 0.00024 +2024-11-23 06:25:52.170009: train_loss -0.8408 +2024-11-23 06:25:52.170238: val_loss -0.7833 +2024-11-23 06:25:52.170332: Pseudo dice [0.8543] +2024-11-23 06:25:52.170416: Epoch time: 18.57 s +2024-11-23 06:25:53.182366: +2024-11-23 06:25:53.182574: Epoch 7874 +2024-11-23 06:25:53.182703: Current learning rate: 0.00024 +2024-11-23 06:26:12.280696: train_loss -0.8381 +2024-11-23 06:26:12.280916: val_loss -0.7981 +2024-11-23 06:26:12.281009: Pseudo dice [0.864] +2024-11-23 06:26:12.281101: Epoch time: 19.1 s +2024-11-23 06:26:13.558350: +2024-11-23 06:26:13.558564: Epoch 7875 +2024-11-23 06:26:13.558678: Current learning rate: 0.00024 +2024-11-23 06:26:31.878661: train_loss -0.8397 +2024-11-23 06:26:31.878959: val_loss -0.7943 +2024-11-23 06:26:31.879047: Pseudo dice [0.8725] +2024-11-23 06:26:31.879163: Epoch time: 18.32 s +2024-11-23 06:26:32.780430: +2024-11-23 06:26:32.780645: Epoch 7876 +2024-11-23 06:26:32.780771: Current learning rate: 0.00024 +2024-11-23 06:26:50.763056: train_loss -0.8405 +2024-11-23 06:26:50.763288: val_loss -0.7963 +2024-11-23 06:26:50.763399: Pseudo dice [0.8576] +2024-11-23 06:26:50.763497: Epoch time: 17.98 s +2024-11-23 06:26:51.662701: +2024-11-23 06:26:51.662969: Epoch 7877 +2024-11-23 06:26:51.663089: Current learning rate: 0.00023 +2024-11-23 06:27:09.942317: train_loss -0.8418 +2024-11-23 06:27:09.942534: val_loss -0.7803 +2024-11-23 06:27:09.942623: Pseudo dice [0.8734] +2024-11-23 06:27:09.942700: Epoch time: 18.28 s +2024-11-23 06:27:10.845883: +2024-11-23 06:27:10.846115: Epoch 7878 +2024-11-23 06:27:10.846229: Current learning rate: 0.00023 +2024-11-23 06:27:29.003617: train_loss -0.841 +2024-11-23 06:27:29.003827: val_loss -0.7922 +2024-11-23 06:27:29.003904: Pseudo dice [0.8662] +2024-11-23 06:27:29.003981: Epoch time: 18.16 s +2024-11-23 06:27:29.900812: +2024-11-23 06:27:29.901029: Epoch 7879 +2024-11-23 06:27:29.901156: Current learning rate: 0.00023 +2024-11-23 06:27:49.589414: train_loss -0.8466 +2024-11-23 06:27:49.589671: val_loss -0.7801 +2024-11-23 06:27:49.589756: Pseudo dice [0.8651] +2024-11-23 06:27:49.589847: Epoch time: 19.69 s +2024-11-23 06:27:50.489029: +2024-11-23 06:27:50.489239: Epoch 7880 +2024-11-23 06:27:50.489352: Current learning rate: 0.00023 +2024-11-23 06:28:08.936832: train_loss -0.8373 +2024-11-23 06:28:08.937068: val_loss -0.7387 +2024-11-23 06:28:08.937161: Pseudo dice [0.8767] +2024-11-23 06:28:08.937241: Epoch time: 18.45 s +2024-11-23 06:28:09.927760: +2024-11-23 06:28:09.927990: Epoch 7881 +2024-11-23 06:28:09.928110: Current learning rate: 0.00023 +2024-11-23 06:28:27.888155: train_loss -0.8402 +2024-11-23 06:28:27.888363: val_loss -0.8089 +2024-11-23 06:28:27.888447: Pseudo dice [0.8752] +2024-11-23 06:28:27.888527: Epoch time: 17.96 s +2024-11-23 06:28:28.789109: +2024-11-23 06:28:28.789314: Epoch 7882 +2024-11-23 06:28:28.789442: Current learning rate: 0.00022 +2024-11-23 06:28:48.782826: train_loss -0.8397 +2024-11-23 06:28:48.783072: val_loss -0.7677 +2024-11-23 06:28:48.783153: Pseudo dice [0.8554] +2024-11-23 06:28:48.783230: Epoch time: 19.99 s +2024-11-23 06:28:49.680288: +2024-11-23 06:28:49.680497: Epoch 7883 +2024-11-23 06:28:49.680622: Current learning rate: 0.00022 +2024-11-23 06:29:08.533081: train_loss -0.8477 +2024-11-23 06:29:08.533343: val_loss -0.7796 +2024-11-23 06:29:08.533429: Pseudo dice [0.8665] +2024-11-23 06:29:08.533517: Epoch time: 18.85 s +2024-11-23 06:29:09.435943: +2024-11-23 06:29:09.436151: Epoch 7884 +2024-11-23 06:29:09.436285: Current learning rate: 0.00022 +2024-11-23 06:29:28.567209: train_loss -0.838 +2024-11-23 06:29:28.567424: val_loss -0.7882 +2024-11-23 06:29:28.567521: Pseudo dice [0.8687] +2024-11-23 06:29:28.567614: Epoch time: 19.13 s +2024-11-23 06:29:29.464612: +2024-11-23 06:29:29.464854: Epoch 7885 +2024-11-23 06:29:29.464973: Current learning rate: 0.00022 +2024-11-23 06:29:48.274861: train_loss -0.84 +2024-11-23 06:29:48.275079: val_loss -0.7931 +2024-11-23 06:29:48.275155: Pseudo dice [0.8564] +2024-11-23 06:29:48.275232: Epoch time: 18.81 s +2024-11-23 06:29:49.169886: +2024-11-23 06:29:49.170326: Epoch 7886 +2024-11-23 06:29:49.170463: Current learning rate: 0.00022 +2024-11-23 06:30:06.806941: train_loss -0.8437 +2024-11-23 06:30:06.807193: val_loss -0.7887 +2024-11-23 06:30:06.807287: Pseudo dice [0.8672] +2024-11-23 06:30:06.807370: Epoch time: 17.64 s +2024-11-23 06:30:07.700323: +2024-11-23 06:30:07.700566: Epoch 7887 +2024-11-23 06:30:07.700699: Current learning rate: 0.00022 +2024-11-23 06:30:26.470037: train_loss -0.8369 +2024-11-23 06:30:26.470367: val_loss -0.7687 +2024-11-23 06:30:26.471746: Pseudo dice [0.8718] +2024-11-23 06:30:26.471888: Epoch time: 18.77 s +2024-11-23 06:30:27.558914: +2024-11-23 06:30:27.559142: Epoch 7888 +2024-11-23 06:30:27.559260: Current learning rate: 0.00021 +2024-11-23 06:30:46.271889: train_loss -0.8415 +2024-11-23 06:30:46.272105: val_loss -0.7491 +2024-11-23 06:30:46.272178: Pseudo dice [0.8668] +2024-11-23 06:30:46.272251: Epoch time: 18.71 s +2024-11-23 06:30:47.320240: +2024-11-23 06:30:47.320457: Epoch 7889 +2024-11-23 06:30:47.320581: Current learning rate: 0.00021 +2024-11-23 06:31:05.011197: train_loss -0.8421 +2024-11-23 06:31:05.011407: val_loss -0.8008 +2024-11-23 06:31:05.011489: Pseudo dice [0.8672] +2024-11-23 06:31:05.011576: Epoch time: 17.69 s +2024-11-23 06:31:05.957433: +2024-11-23 06:31:05.957660: Epoch 7890 +2024-11-23 06:31:05.957798: Current learning rate: 0.00021 +2024-11-23 06:31:24.528755: train_loss -0.8432 +2024-11-23 06:31:24.530174: val_loss -0.7885 +2024-11-23 06:31:24.530311: Pseudo dice [0.8551] +2024-11-23 06:31:24.530401: Epoch time: 18.57 s +2024-11-23 06:31:25.542928: +2024-11-23 06:31:25.543141: Epoch 7891 +2024-11-23 06:31:25.543256: Current learning rate: 0.00021 +2024-11-23 06:31:44.700538: train_loss -0.8437 +2024-11-23 06:31:44.702385: val_loss -0.7984 +2024-11-23 06:31:44.702483: Pseudo dice [0.8647] +2024-11-23 06:31:44.702589: Epoch time: 19.16 s +2024-11-23 06:31:45.625811: +2024-11-23 06:31:45.626050: Epoch 7892 +2024-11-23 06:31:45.626181: Current learning rate: 0.00021 +2024-11-23 06:32:03.870583: train_loss -0.8392 +2024-11-23 06:32:03.870797: val_loss -0.7833 +2024-11-23 06:32:03.870872: Pseudo dice [0.8634] +2024-11-23 06:32:03.870952: Epoch time: 18.25 s +2024-11-23 06:32:04.768913: +2024-11-23 06:32:04.769136: Epoch 7893 +2024-11-23 06:32:04.769253: Current learning rate: 0.00021 +2024-11-23 06:32:24.068403: train_loss -0.842 +2024-11-23 06:32:24.068617: val_loss -0.7823 +2024-11-23 06:32:24.068699: Pseudo dice [0.8586] +2024-11-23 06:32:24.068786: Epoch time: 19.3 s +2024-11-23 06:32:25.078730: +2024-11-23 06:32:25.078938: Epoch 7894 +2024-11-23 06:32:25.079076: Current learning rate: 0.0002 +2024-11-23 06:32:43.991123: train_loss -0.8401 +2024-11-23 06:32:43.991344: val_loss -0.7978 +2024-11-23 06:32:43.991433: Pseudo dice [0.856] +2024-11-23 06:32:43.991519: Epoch time: 18.91 s +2024-11-23 06:32:44.890380: +2024-11-23 06:32:44.890628: Epoch 7895 +2024-11-23 06:32:44.890768: Current learning rate: 0.0002 +2024-11-23 06:33:03.069164: train_loss -0.8435 +2024-11-23 06:33:03.069399: val_loss -0.787 +2024-11-23 06:33:03.069481: Pseudo dice [0.8559] +2024-11-23 06:33:03.069560: Epoch time: 18.18 s +2024-11-23 06:33:04.046070: +2024-11-23 06:33:04.046289: Epoch 7896 +2024-11-23 06:33:04.046421: Current learning rate: 0.0002 +2024-11-23 06:33:22.042907: train_loss -0.8419 +2024-11-23 06:33:22.043127: val_loss -0.7981 +2024-11-23 06:33:22.043203: Pseudo dice [0.8723] +2024-11-23 06:33:22.043283: Epoch time: 18.0 s +2024-11-23 06:33:23.315523: +2024-11-23 06:33:23.315723: Epoch 7897 +2024-11-23 06:33:23.315842: Current learning rate: 0.0002 +2024-11-23 06:33:42.519782: train_loss -0.833 +2024-11-23 06:33:42.520015: val_loss -0.7609 +2024-11-23 06:33:42.520102: Pseudo dice [0.8596] +2024-11-23 06:33:42.520183: Epoch time: 19.21 s +2024-11-23 06:33:43.411658: +2024-11-23 06:33:43.411868: Epoch 7898 +2024-11-23 06:33:43.411989: Current learning rate: 0.0002 +2024-11-23 06:34:01.804483: train_loss -0.8419 +2024-11-23 06:34:01.804725: val_loss -0.7882 +2024-11-23 06:34:01.804803: Pseudo dice [0.8708] +2024-11-23 06:34:01.804888: Epoch time: 18.39 s +2024-11-23 06:34:02.702673: +2024-11-23 06:34:02.702899: Epoch 7899 +2024-11-23 06:34:02.703032: Current learning rate: 0.0002 +2024-11-23 06:34:20.774220: train_loss -0.8405 +2024-11-23 06:34:20.774431: val_loss -0.8153 +2024-11-23 06:34:20.774512: Pseudo dice [0.8673] +2024-11-23 06:34:20.774603: Epoch time: 18.07 s +2024-11-23 06:34:22.039702: +2024-11-23 06:34:22.039942: Epoch 7900 +2024-11-23 06:34:22.040055: Current learning rate: 0.00019 +2024-11-23 06:34:40.244915: train_loss -0.8412 +2024-11-23 06:34:40.245131: val_loss -0.7909 +2024-11-23 06:34:40.245216: Pseudo dice [0.8592] +2024-11-23 06:34:40.245296: Epoch time: 18.21 s +2024-11-23 06:34:41.147037: +2024-11-23 06:34:41.147264: Epoch 7901 +2024-11-23 06:34:41.147384: Current learning rate: 0.00019 +2024-11-23 06:35:00.345549: train_loss -0.8355 +2024-11-23 06:35:00.347977: val_loss -0.7743 +2024-11-23 06:35:00.348079: Pseudo dice [0.8614] +2024-11-23 06:35:00.348163: Epoch time: 19.2 s +2024-11-23 06:35:01.250748: +2024-11-23 06:35:01.250993: Epoch 7902 +2024-11-23 06:35:01.251138: Current learning rate: 0.00019 +2024-11-23 06:35:20.117371: train_loss -0.8414 +2024-11-23 06:35:20.117622: val_loss -0.7813 +2024-11-23 06:35:20.117718: Pseudo dice [0.8437] +2024-11-23 06:35:20.117809: Epoch time: 18.87 s +2024-11-23 06:35:21.018711: +2024-11-23 06:35:21.018970: Epoch 7903 +2024-11-23 06:35:21.019090: Current learning rate: 0.00019 +2024-11-23 06:35:40.037692: train_loss -0.8443 +2024-11-23 06:35:40.037894: val_loss -0.787 +2024-11-23 06:35:40.037973: Pseudo dice [0.8575] +2024-11-23 06:35:40.038055: Epoch time: 19.02 s +2024-11-23 06:35:40.946847: +2024-11-23 06:35:40.947093: Epoch 7904 +2024-11-23 06:35:40.947206: Current learning rate: 0.00019 +2024-11-23 06:35:59.862919: train_loss -0.8428 +2024-11-23 06:35:59.863179: val_loss -0.7749 +2024-11-23 06:35:59.863267: Pseudo dice [0.8636] +2024-11-23 06:35:59.863348: Epoch time: 18.92 s +2024-11-23 06:36:00.765194: +2024-11-23 06:36:00.765409: Epoch 7905 +2024-11-23 06:36:00.765534: Current learning rate: 0.00018 +2024-11-23 06:36:19.643292: train_loss -0.837 +2024-11-23 06:36:19.643507: val_loss -0.7951 +2024-11-23 06:36:19.645823: Pseudo dice [0.8685] +2024-11-23 06:36:19.645925: Epoch time: 18.88 s +2024-11-23 06:36:20.552835: +2024-11-23 06:36:20.553080: Epoch 7906 +2024-11-23 06:36:20.553460: Current learning rate: 0.00018 +2024-11-23 06:36:38.926394: train_loss -0.8395 +2024-11-23 06:36:38.926641: val_loss -0.8025 +2024-11-23 06:36:38.926730: Pseudo dice [0.8845] +2024-11-23 06:36:38.926816: Epoch time: 18.37 s +2024-11-23 06:36:39.826359: +2024-11-23 06:36:39.826563: Epoch 7907 +2024-11-23 06:36:39.826691: Current learning rate: 0.00018 +2024-11-23 06:36:57.945050: train_loss -0.8428 +2024-11-23 06:36:57.945274: val_loss -0.7941 +2024-11-23 06:36:57.945354: Pseudo dice [0.8684] +2024-11-23 06:36:57.945456: Epoch time: 18.12 s +2024-11-23 06:36:59.272719: +2024-11-23 06:36:59.272926: Epoch 7908 +2024-11-23 06:36:59.273040: Current learning rate: 0.00018 +2024-11-23 06:37:17.031100: train_loss -0.8453 +2024-11-23 06:37:17.031352: val_loss -0.7852 +2024-11-23 06:37:17.031435: Pseudo dice [0.8516] +2024-11-23 06:37:17.031521: Epoch time: 17.76 s +2024-11-23 06:37:17.922644: +2024-11-23 06:37:17.922865: Epoch 7909 +2024-11-23 06:37:17.922975: Current learning rate: 0.00018 +2024-11-23 06:37:36.322253: train_loss -0.8427 +2024-11-23 06:37:36.322505: val_loss -0.7884 +2024-11-23 06:37:36.322594: Pseudo dice [0.8595] +2024-11-23 06:37:36.322700: Epoch time: 18.4 s +2024-11-23 06:37:37.221847: +2024-11-23 06:37:37.222080: Epoch 7910 +2024-11-23 06:37:37.222195: Current learning rate: 0.00018 +2024-11-23 06:37:54.942643: train_loss -0.8431 +2024-11-23 06:37:54.942878: val_loss -0.7908 +2024-11-23 06:37:54.942973: Pseudo dice [0.8637] +2024-11-23 06:37:54.943073: Epoch time: 17.72 s +2024-11-23 06:37:55.843067: +2024-11-23 06:37:55.843270: Epoch 7911 +2024-11-23 06:37:55.843384: Current learning rate: 0.00017 +2024-11-23 06:38:14.766664: train_loss -0.8443 +2024-11-23 06:38:14.767358: val_loss -0.7746 +2024-11-23 06:38:14.767449: Pseudo dice [0.8618] +2024-11-23 06:38:14.767541: Epoch time: 18.92 s +2024-11-23 06:38:15.806780: +2024-11-23 06:38:15.807003: Epoch 7912 +2024-11-23 06:38:15.807130: Current learning rate: 0.00017 +2024-11-23 06:38:34.617967: train_loss -0.8384 +2024-11-23 06:38:34.618188: val_loss -0.7814 +2024-11-23 06:38:34.618277: Pseudo dice [0.8599] +2024-11-23 06:38:34.618358: Epoch time: 18.81 s +2024-11-23 06:38:35.517984: +2024-11-23 06:38:35.518206: Epoch 7913 +2024-11-23 06:38:35.518322: Current learning rate: 0.00017 +2024-11-23 06:38:54.199285: train_loss -0.8463 +2024-11-23 06:38:54.199537: val_loss -0.7857 +2024-11-23 06:38:54.199618: Pseudo dice [0.8594] +2024-11-23 06:38:54.199722: Epoch time: 18.68 s +2024-11-23 06:38:55.104123: +2024-11-23 06:38:55.104374: Epoch 7914 +2024-11-23 06:38:55.104495: Current learning rate: 0.00017 +2024-11-23 06:39:13.821794: train_loss -0.8376 +2024-11-23 06:39:13.822075: val_loss -0.7939 +2024-11-23 06:39:13.822177: Pseudo dice [0.8678] +2024-11-23 06:39:13.822270: Epoch time: 18.72 s +2024-11-23 06:39:14.722001: +2024-11-23 06:39:14.722224: Epoch 7915 +2024-11-23 06:39:14.722338: Current learning rate: 0.00017 +2024-11-23 06:39:32.703799: train_loss -0.8338 +2024-11-23 06:39:32.704021: val_loss -0.7955 +2024-11-23 06:39:32.704127: Pseudo dice [0.8726] +2024-11-23 06:39:32.704204: Epoch time: 17.98 s +2024-11-23 06:39:33.602119: +2024-11-23 06:39:33.602333: Epoch 7916 +2024-11-23 06:39:33.602456: Current learning rate: 0.00017 +2024-11-23 06:39:51.912248: train_loss -0.8409 +2024-11-23 06:39:51.912464: val_loss -0.7945 +2024-11-23 06:39:51.912542: Pseudo dice [0.859] +2024-11-23 06:39:51.912624: Epoch time: 18.31 s +2024-11-23 06:39:52.812427: +2024-11-23 06:39:52.812635: Epoch 7917 +2024-11-23 06:39:52.812756: Current learning rate: 0.00016 +2024-11-23 06:40:10.531235: train_loss -0.8462 +2024-11-23 06:40:10.531478: val_loss -0.7983 +2024-11-23 06:40:10.531558: Pseudo dice [0.8592] +2024-11-23 06:40:10.531648: Epoch time: 17.72 s +2024-11-23 06:40:11.572489: +2024-11-23 06:40:11.572715: Epoch 7918 +2024-11-23 06:40:11.572834: Current learning rate: 0.00016 +2024-11-23 06:40:29.582989: train_loss -0.8436 +2024-11-23 06:40:29.583219: val_loss -0.794 +2024-11-23 06:40:29.583310: Pseudo dice [0.8751] +2024-11-23 06:40:29.583396: Epoch time: 18.01 s +2024-11-23 06:40:30.526078: +2024-11-23 06:40:30.526285: Epoch 7919 +2024-11-23 06:40:30.526407: Current learning rate: 0.00016 +2024-11-23 06:40:48.601730: train_loss -0.8398 +2024-11-23 06:40:48.601966: val_loss -0.7969 +2024-11-23 06:40:48.602050: Pseudo dice [0.8652] +2024-11-23 06:40:48.602136: Epoch time: 18.08 s +2024-11-23 06:40:49.499542: +2024-11-23 06:40:49.499781: Epoch 7920 +2024-11-23 06:40:49.499902: Current learning rate: 0.00016 +2024-11-23 06:41:08.076042: train_loss -0.8406 +2024-11-23 06:41:08.076272: val_loss -0.7972 +2024-11-23 06:41:08.076380: Pseudo dice [0.8743] +2024-11-23 06:41:08.076516: Epoch time: 18.58 s +2024-11-23 06:41:09.038932: +2024-11-23 06:41:09.039140: Epoch 7921 +2024-11-23 06:41:09.039254: Current learning rate: 0.00016 +2024-11-23 06:41:28.481631: train_loss -0.8396 +2024-11-23 06:41:28.481898: val_loss -0.7901 +2024-11-23 06:41:28.481981: Pseudo dice [0.8588] +2024-11-23 06:41:28.482071: Epoch time: 19.44 s +2024-11-23 06:41:29.383290: +2024-11-23 06:41:29.383518: Epoch 7922 +2024-11-23 06:41:29.383634: Current learning rate: 0.00015 +2024-11-23 06:41:47.688672: train_loss -0.8422 +2024-11-23 06:41:47.688903: val_loss -0.7748 +2024-11-23 06:41:47.688978: Pseudo dice [0.8751] +2024-11-23 06:41:47.689063: Epoch time: 18.31 s +2024-11-23 06:41:48.649937: +2024-11-23 06:41:48.650154: Epoch 7923 +2024-11-23 06:41:48.650285: Current learning rate: 0.00015 +2024-11-23 06:42:07.296470: train_loss -0.843 +2024-11-23 06:42:07.298862: val_loss -0.7985 +2024-11-23 06:42:07.299010: Pseudo dice [0.8728] +2024-11-23 06:42:07.299111: Epoch time: 18.65 s +2024-11-23 06:42:08.472352: +2024-11-23 06:42:08.472575: Epoch 7924 +2024-11-23 06:42:08.472710: Current learning rate: 0.00015 +2024-11-23 06:42:28.668309: train_loss -0.8403 +2024-11-23 06:42:28.670284: val_loss -0.8032 +2024-11-23 06:42:28.670399: Pseudo dice [0.8732] +2024-11-23 06:42:28.670479: Epoch time: 20.2 s +2024-11-23 06:42:29.588334: +2024-11-23 06:42:29.588536: Epoch 7925 +2024-11-23 06:42:29.588653: Current learning rate: 0.00015 +2024-11-23 06:42:48.217552: train_loss -0.8407 +2024-11-23 06:42:48.217798: val_loss -0.7832 +2024-11-23 06:42:48.217888: Pseudo dice [0.8476] +2024-11-23 06:42:48.217973: Epoch time: 18.63 s +2024-11-23 06:42:49.121216: +2024-11-23 06:42:49.121420: Epoch 7926 +2024-11-23 06:42:49.121540: Current learning rate: 0.00015 +2024-11-23 06:43:07.860692: train_loss -0.8425 +2024-11-23 06:43:07.860915: val_loss -0.7953 +2024-11-23 06:43:07.861013: Pseudo dice [0.8631] +2024-11-23 06:43:07.861100: Epoch time: 18.74 s +2024-11-23 06:43:08.761006: +2024-11-23 06:43:08.761212: Epoch 7927 +2024-11-23 06:43:08.761329: Current learning rate: 0.00015 +2024-11-23 06:43:26.219211: train_loss -0.8462 +2024-11-23 06:43:26.219441: val_loss -0.7938 +2024-11-23 06:43:26.219534: Pseudo dice [0.8635] +2024-11-23 06:43:26.219612: Epoch time: 17.46 s +2024-11-23 06:43:27.112025: +2024-11-23 06:43:27.112272: Epoch 7928 +2024-11-23 06:43:27.112387: Current learning rate: 0.00014 +2024-11-23 06:43:44.890234: train_loss -0.849 +2024-11-23 06:43:44.890455: val_loss -0.797 +2024-11-23 06:43:44.890550: Pseudo dice [0.8609] +2024-11-23 06:43:44.890630: Epoch time: 17.78 s +2024-11-23 06:43:45.788617: +2024-11-23 06:43:45.788817: Epoch 7929 +2024-11-23 06:43:45.788960: Current learning rate: 0.00014 +2024-11-23 06:44:04.651391: train_loss -0.8411 +2024-11-23 06:44:04.651629: val_loss -0.7823 +2024-11-23 06:44:04.651711: Pseudo dice [0.867] +2024-11-23 06:44:04.651806: Epoch time: 18.86 s +2024-11-23 06:44:05.959478: +2024-11-23 06:44:05.959723: Epoch 7930 +2024-11-23 06:44:05.959855: Current learning rate: 0.00014 +2024-11-23 06:44:24.600359: train_loss -0.8389 +2024-11-23 06:44:24.600596: val_loss -0.8022 +2024-11-23 06:44:24.600680: Pseudo dice [0.8723] +2024-11-23 06:44:24.600754: Epoch time: 18.64 s +2024-11-23 06:44:25.493261: +2024-11-23 06:44:25.493507: Epoch 7931 +2024-11-23 06:44:25.493626: Current learning rate: 0.00014 +2024-11-23 06:44:44.153734: train_loss -0.8389 +2024-11-23 06:44:44.153980: val_loss -0.7713 +2024-11-23 06:44:44.154073: Pseudo dice [0.8727] +2024-11-23 06:44:44.154147: Epoch time: 18.66 s +2024-11-23 06:44:45.080408: +2024-11-23 06:44:45.080635: Epoch 7932 +2024-11-23 06:44:45.080833: Current learning rate: 0.00014 +2024-11-23 06:45:02.462630: train_loss -0.8372 +2024-11-23 06:45:02.462851: val_loss -0.798 +2024-11-23 06:45:02.462944: Pseudo dice [0.859] +2024-11-23 06:45:02.463024: Epoch time: 17.38 s +2024-11-23 06:45:03.357802: +2024-11-23 06:45:03.358018: Epoch 7933 +2024-11-23 06:45:03.358150: Current learning rate: 0.00014 +2024-11-23 06:45:22.092487: train_loss -0.8418 +2024-11-23 06:45:22.092748: val_loss -0.7842 +2024-11-23 06:45:22.092835: Pseudo dice [0.8663] +2024-11-23 06:45:22.092923: Epoch time: 18.74 s +2024-11-23 06:45:22.987108: +2024-11-23 06:45:22.987326: Epoch 7934 +2024-11-23 06:45:22.987441: Current learning rate: 0.00013 +2024-11-23 06:45:41.300533: train_loss -0.8392 +2024-11-23 06:45:41.300761: val_loss -0.7673 +2024-11-23 06:45:41.300846: Pseudo dice [0.8605] +2024-11-23 06:45:41.300925: Epoch time: 18.31 s +2024-11-23 06:45:42.199502: +2024-11-23 06:45:42.199708: Epoch 7935 +2024-11-23 06:45:42.199828: Current learning rate: 0.00013 +2024-11-23 06:45:59.994486: train_loss -0.8476 +2024-11-23 06:45:59.994709: val_loss -0.7876 +2024-11-23 06:45:59.994787: Pseudo dice [0.8585] +2024-11-23 06:45:59.994862: Epoch time: 17.8 s +2024-11-23 06:46:00.899595: +2024-11-23 06:46:00.899780: Epoch 7936 +2024-11-23 06:46:00.899897: Current learning rate: 0.00013 +2024-11-23 06:46:20.394819: train_loss -0.8364 +2024-11-23 06:46:20.395048: val_loss -0.8027 +2024-11-23 06:46:20.395140: Pseudo dice [0.8546] +2024-11-23 06:46:20.395223: Epoch time: 19.5 s +2024-11-23 06:46:21.305227: +2024-11-23 06:46:21.305457: Epoch 7937 +2024-11-23 06:46:21.305576: Current learning rate: 0.00013 +2024-11-23 06:46:39.141772: train_loss -0.8462 +2024-11-23 06:46:39.144615: val_loss -0.7731 +2024-11-23 06:46:39.144706: Pseudo dice [0.8603] +2024-11-23 06:46:39.144789: Epoch time: 17.84 s +2024-11-23 06:46:40.055401: +2024-11-23 06:46:40.055626: Epoch 7938 +2024-11-23 06:46:40.055744: Current learning rate: 0.00013 +2024-11-23 06:46:58.032625: train_loss -0.8488 +2024-11-23 06:46:58.032851: val_loss -0.8072 +2024-11-23 06:46:58.032945: Pseudo dice [0.8719] +2024-11-23 06:46:58.033029: Epoch time: 17.98 s +2024-11-23 06:46:59.051430: +2024-11-23 06:46:59.051643: Epoch 7939 +2024-11-23 06:46:59.051759: Current learning rate: 0.00012 +2024-11-23 06:47:18.300297: train_loss -0.8378 +2024-11-23 06:47:18.300523: val_loss -0.7971 +2024-11-23 06:47:18.300624: Pseudo dice [0.8777] +2024-11-23 06:47:18.300703: Epoch time: 19.25 s +2024-11-23 06:47:19.196412: +2024-11-23 06:47:19.196634: Epoch 7940 +2024-11-23 06:47:19.196767: Current learning rate: 0.00012 +2024-11-23 06:47:37.368995: train_loss -0.8415 +2024-11-23 06:47:37.369285: val_loss -0.782 +2024-11-23 06:47:37.369361: Pseudo dice [0.853] +2024-11-23 06:47:37.369446: Epoch time: 18.17 s +2024-11-23 06:47:38.269412: +2024-11-23 06:47:38.269614: Epoch 7941 +2024-11-23 06:47:38.269731: Current learning rate: 0.00012 +2024-11-23 06:47:56.232776: train_loss -0.8414 +2024-11-23 06:47:56.233007: val_loss -0.7872 +2024-11-23 06:47:56.233091: Pseudo dice [0.8594] +2024-11-23 06:47:56.233169: Epoch time: 17.96 s +2024-11-23 06:47:57.125777: +2024-11-23 06:47:57.125996: Epoch 7942 +2024-11-23 06:47:57.126125: Current learning rate: 0.00012 +2024-11-23 06:48:15.527643: train_loss -0.8433 +2024-11-23 06:48:15.528159: val_loss -0.785 +2024-11-23 06:48:15.528257: Pseudo dice [0.861] +2024-11-23 06:48:15.528342: Epoch time: 18.4 s +2024-11-23 06:48:16.434090: +2024-11-23 06:48:16.434303: Epoch 7943 +2024-11-23 06:48:16.434417: Current learning rate: 0.00012 +2024-11-23 06:48:35.651069: train_loss -0.8424 +2024-11-23 06:48:35.651285: val_loss -0.7937 +2024-11-23 06:48:35.651363: Pseudo dice [0.8576] +2024-11-23 06:48:35.651443: Epoch time: 19.22 s +2024-11-23 06:48:36.551761: +2024-11-23 06:48:36.551970: Epoch 7944 +2024-11-23 06:48:36.552096: Current learning rate: 0.00011 +2024-11-23 06:48:54.779276: train_loss -0.8396 +2024-11-23 06:48:54.779517: val_loss -0.7962 +2024-11-23 06:48:54.779598: Pseudo dice [0.8367] +2024-11-23 06:48:54.779686: Epoch time: 18.23 s +2024-11-23 06:48:55.682489: +2024-11-23 06:48:55.682709: Epoch 7945 +2024-11-23 06:48:55.682829: Current learning rate: 0.00011 +2024-11-23 06:49:14.551561: train_loss -0.8396 +2024-11-23 06:49:14.551775: val_loss -0.7891 +2024-11-23 06:49:14.551868: Pseudo dice [0.8651] +2024-11-23 06:49:14.551953: Epoch time: 18.87 s +2024-11-23 06:49:15.456505: +2024-11-23 06:49:15.456720: Epoch 7946 +2024-11-23 06:49:15.456831: Current learning rate: 0.00011 +2024-11-23 06:49:33.505227: train_loss -0.841 +2024-11-23 06:49:33.505439: val_loss -0.786 +2024-11-23 06:49:33.505523: Pseudo dice [0.8522] +2024-11-23 06:49:33.505612: Epoch time: 18.05 s +2024-11-23 06:49:34.471580: +2024-11-23 06:49:34.471788: Epoch 7947 +2024-11-23 06:49:34.471905: Current learning rate: 0.00011 +2024-11-23 06:49:52.507956: train_loss -0.8389 +2024-11-23 06:49:52.508171: val_loss -0.7871 +2024-11-23 06:49:52.508248: Pseudo dice [0.8713] +2024-11-23 06:49:52.508324: Epoch time: 18.04 s +2024-11-23 06:49:53.406975: +2024-11-23 06:49:53.407200: Epoch 7948 +2024-11-23 06:49:53.407319: Current learning rate: 0.00011 +2024-11-23 06:50:10.428082: train_loss -0.8542 +2024-11-23 06:50:10.428324: val_loss -0.7819 +2024-11-23 06:50:10.428416: Pseudo dice [0.8442] +2024-11-23 06:50:10.428513: Epoch time: 17.02 s +2024-11-23 06:50:11.334765: +2024-11-23 06:50:11.334991: Epoch 7949 +2024-11-23 06:50:11.335135: Current learning rate: 0.00011 +2024-11-23 06:50:29.460758: train_loss -0.8423 +2024-11-23 06:50:29.460988: val_loss -0.7674 +2024-11-23 06:50:29.461081: Pseudo dice [0.864] +2024-11-23 06:50:29.461167: Epoch time: 18.13 s +2024-11-23 06:50:30.733346: +2024-11-23 06:50:30.733560: Epoch 7950 +2024-11-23 06:50:30.733699: Current learning rate: 0.0001 +2024-11-23 06:50:49.096625: train_loss -0.8434 +2024-11-23 06:50:49.096849: val_loss -0.7726 +2024-11-23 06:50:49.096930: Pseudo dice [0.8642] +2024-11-23 06:50:49.097009: Epoch time: 18.36 s +2024-11-23 06:50:49.998454: +2024-11-23 06:50:49.998662: Epoch 7951 +2024-11-23 06:50:49.998782: Current learning rate: 0.0001 +2024-11-23 06:51:08.936388: train_loss -0.8394 +2024-11-23 06:51:08.936603: val_loss -0.7929 +2024-11-23 06:51:08.936685: Pseudo dice [0.8636] +2024-11-23 06:51:08.936766: Epoch time: 18.94 s +2024-11-23 06:51:10.225122: +2024-11-23 06:51:10.225359: Epoch 7952 +2024-11-23 06:51:10.225490: Current learning rate: 0.0001 +2024-11-23 06:51:28.750172: train_loss -0.8433 +2024-11-23 06:51:28.750442: val_loss -0.7613 +2024-11-23 06:51:28.750541: Pseudo dice [0.864] +2024-11-23 06:51:28.750690: Epoch time: 18.53 s +2024-11-23 06:51:29.651861: +2024-11-23 06:51:29.652101: Epoch 7953 +2024-11-23 06:51:29.652211: Current learning rate: 0.0001 +2024-11-23 06:51:48.076115: train_loss -0.8477 +2024-11-23 06:51:48.076353: val_loss -0.7993 +2024-11-23 06:51:48.076431: Pseudo dice [0.8728] +2024-11-23 06:51:48.076508: Epoch time: 18.43 s +2024-11-23 06:51:49.029186: +2024-11-23 06:51:49.029412: Epoch 7954 +2024-11-23 06:51:49.029539: Current learning rate: 0.0001 +2024-11-23 06:52:07.424779: train_loss -0.8426 +2024-11-23 06:52:07.425013: val_loss -0.7689 +2024-11-23 06:52:07.425101: Pseudo dice [0.8575] +2024-11-23 06:52:07.425178: Epoch time: 18.4 s +2024-11-23 06:52:08.413048: +2024-11-23 06:52:08.413278: Epoch 7955 +2024-11-23 06:52:08.413401: Current learning rate: 9e-05 +2024-11-23 06:52:26.245729: train_loss -0.8417 +2024-11-23 06:52:26.245951: val_loss -0.8042 +2024-11-23 06:52:26.246147: Pseudo dice [0.8738] +2024-11-23 06:52:26.246257: Epoch time: 17.83 s +2024-11-23 06:52:27.152510: +2024-11-23 06:52:27.152768: Epoch 7956 +2024-11-23 06:52:27.152889: Current learning rate: 9e-05 +2024-11-23 06:52:45.881618: train_loss -0.84 +2024-11-23 06:52:45.881854: val_loss -0.7749 +2024-11-23 06:52:45.881949: Pseudo dice [0.8646] +2024-11-23 06:52:45.882032: Epoch time: 18.73 s +2024-11-23 06:52:46.787102: +2024-11-23 06:52:46.787318: Epoch 7957 +2024-11-23 06:52:46.787436: Current learning rate: 9e-05 +2024-11-23 06:53:06.432190: train_loss -0.837 +2024-11-23 06:53:06.432403: val_loss -0.8065 +2024-11-23 06:53:06.432567: Pseudo dice [0.8705] +2024-11-23 06:53:06.432648: Epoch time: 19.65 s +2024-11-23 06:53:07.325915: +2024-11-23 06:53:07.326127: Epoch 7958 +2024-11-23 06:53:07.326435: Current learning rate: 9e-05 +2024-11-23 06:53:25.549319: train_loss -0.8455 +2024-11-23 06:53:25.549528: val_loss -0.8007 +2024-11-23 06:53:25.549609: Pseudo dice [0.871] +2024-11-23 06:53:25.549699: Epoch time: 18.22 s +2024-11-23 06:53:26.455771: +2024-11-23 06:53:26.455983: Epoch 7959 +2024-11-23 06:53:26.456102: Current learning rate: 9e-05 +2024-11-23 06:53:44.660804: train_loss -0.8397 +2024-11-23 06:53:44.663190: val_loss -0.7921 +2024-11-23 06:53:44.663297: Pseudo dice [0.845] +2024-11-23 06:53:44.663382: Epoch time: 18.21 s +2024-11-23 06:53:45.719542: +2024-11-23 06:53:45.719748: Epoch 7960 +2024-11-23 06:53:45.719870: Current learning rate: 8e-05 +2024-11-23 06:54:04.435836: train_loss -0.8453 +2024-11-23 06:54:04.436071: val_loss -0.794 +2024-11-23 06:54:04.436153: Pseudo dice [0.8574] +2024-11-23 06:54:04.436233: Epoch time: 18.72 s +2024-11-23 06:54:05.313813: +2024-11-23 06:54:05.313995: Epoch 7961 +2024-11-23 06:54:05.314111: Current learning rate: 8e-05 +2024-11-23 06:54:24.309493: train_loss -0.8341 +2024-11-23 06:54:24.309690: val_loss -0.7724 +2024-11-23 06:54:24.309761: Pseudo dice [0.8648] +2024-11-23 06:54:24.309834: Epoch time: 19.0 s +2024-11-23 06:54:25.194799: +2024-11-23 06:54:25.194999: Epoch 7962 +2024-11-23 06:54:25.195130: Current learning rate: 8e-05 +2024-11-23 06:54:43.372614: train_loss -0.8357 +2024-11-23 06:54:43.372825: val_loss -0.7941 +2024-11-23 06:54:43.372909: Pseudo dice [0.8769] +2024-11-23 06:54:43.373009: Epoch time: 18.18 s +2024-11-23 06:54:44.262539: +2024-11-23 06:54:44.262749: Epoch 7963 +2024-11-23 06:54:44.262881: Current learning rate: 8e-05 +2024-11-23 06:55:03.159953: train_loss -0.8406 +2024-11-23 06:55:03.160267: val_loss -0.8178 +2024-11-23 06:55:03.160348: Pseudo dice [0.8788] +2024-11-23 06:55:03.160433: Epoch time: 18.9 s +2024-11-23 06:55:04.363806: +2024-11-23 06:55:04.364033: Epoch 7964 +2024-11-23 06:55:04.364163: Current learning rate: 8e-05 +2024-11-23 06:55:22.889024: train_loss -0.8458 +2024-11-23 06:55:22.889257: val_loss -0.799 +2024-11-23 06:55:22.889354: Pseudo dice [0.871] +2024-11-23 06:55:22.889451: Epoch time: 18.53 s +2024-11-23 06:55:23.783664: +2024-11-23 06:55:23.783859: Epoch 7965 +2024-11-23 06:55:23.783966: Current learning rate: 8e-05 +2024-11-23 06:55:41.543149: train_loss -0.8426 +2024-11-23 06:55:41.543401: val_loss -0.7659 +2024-11-23 06:55:41.543492: Pseudo dice [0.8666] +2024-11-23 06:55:41.543586: Epoch time: 17.76 s +2024-11-23 06:55:42.462042: +2024-11-23 06:55:42.462266: Epoch 7966 +2024-11-23 06:55:42.462380: Current learning rate: 7e-05 +2024-11-23 06:56:00.987316: train_loss -0.8417 +2024-11-23 06:56:00.987531: val_loss -0.8007 +2024-11-23 06:56:00.987615: Pseudo dice [0.8538] +2024-11-23 06:56:00.987697: Epoch time: 18.53 s +2024-11-23 06:56:01.892899: +2024-11-23 06:56:01.893131: Epoch 7967 +2024-11-23 06:56:01.893247: Current learning rate: 7e-05 +2024-11-23 06:56:20.036014: train_loss -0.8392 +2024-11-23 06:56:20.036262: val_loss -0.7838 +2024-11-23 06:56:20.036346: Pseudo dice [0.871] +2024-11-23 06:56:20.036458: Epoch time: 18.14 s +2024-11-23 06:56:21.049556: +2024-11-23 06:56:21.049773: Epoch 7968 +2024-11-23 06:56:21.049889: Current learning rate: 7e-05 +2024-11-23 06:56:37.843782: train_loss -0.8379 +2024-11-23 06:56:37.844027: val_loss -0.7706 +2024-11-23 06:56:37.844129: Pseudo dice [0.862] +2024-11-23 06:56:37.844208: Epoch time: 16.8 s +2024-11-23 06:56:38.748858: +2024-11-23 06:56:38.749089: Epoch 7969 +2024-11-23 06:56:38.749202: Current learning rate: 7e-05 +2024-11-23 06:56:56.223915: train_loss -0.8499 +2024-11-23 06:56:56.224162: val_loss -0.7932 +2024-11-23 06:56:56.224245: Pseudo dice [0.8706] +2024-11-23 06:56:56.224347: Epoch time: 17.48 s +2024-11-23 06:56:57.120053: +2024-11-23 06:56:57.120346: Epoch 7970 +2024-11-23 06:56:57.120485: Current learning rate: 7e-05 +2024-11-23 06:57:15.398917: train_loss -0.8421 +2024-11-23 06:57:15.399144: val_loss -0.7948 +2024-11-23 06:57:15.399237: Pseudo dice [0.8809] +2024-11-23 06:57:15.399325: Epoch time: 18.28 s +2024-11-23 06:57:16.319617: +2024-11-23 06:57:16.319856: Epoch 7971 +2024-11-23 06:57:16.319989: Current learning rate: 6e-05 +2024-11-23 06:57:35.161599: train_loss -0.841 +2024-11-23 06:57:35.166970: val_loss -0.797 +2024-11-23 06:57:35.167142: Pseudo dice [0.8695] +2024-11-23 06:57:35.167236: Epoch time: 18.84 s +2024-11-23 06:57:36.146690: +2024-11-23 06:57:36.146909: Epoch 7972 +2024-11-23 06:57:36.147023: Current learning rate: 6e-05 +2024-11-23 06:57:53.373008: train_loss -0.8409 +2024-11-23 06:57:53.373228: val_loss -0.7633 +2024-11-23 06:57:53.373306: Pseudo dice [0.8704] +2024-11-23 06:57:53.373387: Epoch time: 17.23 s +2024-11-23 06:57:54.278331: +2024-11-23 06:57:54.278544: Epoch 7973 +2024-11-23 06:57:54.278655: Current learning rate: 6e-05 +2024-11-23 06:58:13.437936: train_loss -0.8443 +2024-11-23 06:58:13.438228: val_loss -0.7969 +2024-11-23 06:58:13.438314: Pseudo dice [0.8717] +2024-11-23 06:58:13.438407: Epoch time: 19.16 s +2024-11-23 06:58:13.438476: Yayy! New best EMA pseudo Dice: 0.868 +2024-11-23 06:58:14.697777: +2024-11-23 06:58:14.697993: Epoch 7974 +2024-11-23 06:58:14.698130: Current learning rate: 6e-05 +2024-11-23 06:58:33.695018: train_loss -0.8357 +2024-11-23 06:58:33.695290: val_loss -0.7806 +2024-11-23 06:58:33.695369: Pseudo dice [0.8593] +2024-11-23 06:58:33.695449: Epoch time: 19.0 s +2024-11-23 06:58:34.972655: +2024-11-23 06:58:34.972876: Epoch 7975 +2024-11-23 06:58:34.972990: Current learning rate: 6e-05 +2024-11-23 06:58:52.588043: train_loss -0.8456 +2024-11-23 06:58:52.588282: val_loss -0.8058 +2024-11-23 06:58:52.588363: Pseudo dice [0.8651] +2024-11-23 06:58:52.588457: Epoch time: 17.62 s +2024-11-23 06:58:53.482702: +2024-11-23 06:58:53.482908: Epoch 7976 +2024-11-23 06:58:53.483028: Current learning rate: 5e-05 +2024-11-23 06:59:11.799976: train_loss -0.8441 +2024-11-23 06:59:11.800223: val_loss -0.7901 +2024-11-23 06:59:11.800301: Pseudo dice [0.8494] +2024-11-23 06:59:11.800389: Epoch time: 18.32 s +2024-11-23 06:59:12.701016: +2024-11-23 06:59:12.701250: Epoch 7977 +2024-11-23 06:59:12.701372: Current learning rate: 5e-05 +2024-11-23 06:59:31.409818: train_loss -0.8439 +2024-11-23 06:59:31.410041: val_loss -0.78 +2024-11-23 06:59:31.410129: Pseudo dice [0.8581] +2024-11-23 06:59:31.410221: Epoch time: 18.71 s +2024-11-23 06:59:32.312077: +2024-11-23 06:59:32.312313: Epoch 7978 +2024-11-23 06:59:32.312436: Current learning rate: 5e-05 +2024-11-23 06:59:50.597199: train_loss -0.847 +2024-11-23 06:59:50.610906: val_loss -0.7717 +2024-11-23 06:59:50.611034: Pseudo dice [0.8594] +2024-11-23 06:59:50.611134: Epoch time: 18.29 s +2024-11-23 06:59:51.757185: +2024-11-23 06:59:51.757394: Epoch 7979 +2024-11-23 06:59:51.757534: Current learning rate: 5e-05 +2024-11-23 07:00:11.778184: train_loss -0.8432 +2024-11-23 07:00:11.779176: val_loss -0.7949 +2024-11-23 07:00:11.779286: Pseudo dice [0.8593] +2024-11-23 07:00:11.779371: Epoch time: 20.02 s +2024-11-23 07:00:12.667476: +2024-11-23 07:00:12.667694: Epoch 7980 +2024-11-23 07:00:12.667812: Current learning rate: 5e-05 +2024-11-23 07:00:30.952516: train_loss -0.8492 +2024-11-23 07:00:30.952732: val_loss -0.7734 +2024-11-23 07:00:30.952812: Pseudo dice [0.8711] +2024-11-23 07:00:30.952885: Epoch time: 18.29 s +2024-11-23 07:00:31.992522: +2024-11-23 07:00:31.992726: Epoch 7981 +2024-11-23 07:00:31.992847: Current learning rate: 4e-05 +2024-11-23 07:00:49.813809: train_loss -0.8426 +2024-11-23 07:00:49.824893: val_loss -0.7879 +2024-11-23 07:00:49.825006: Pseudo dice [0.8632] +2024-11-23 07:00:49.825102: Epoch time: 17.82 s +2024-11-23 07:00:50.835514: +2024-11-23 07:00:50.835774: Epoch 7982 +2024-11-23 07:00:50.835895: Current learning rate: 4e-05 +2024-11-23 07:01:09.523395: train_loss -0.8449 +2024-11-23 07:01:09.523596: val_loss -0.7902 +2024-11-23 07:01:09.523680: Pseudo dice [0.8714] +2024-11-23 07:01:09.523767: Epoch time: 18.69 s +2024-11-23 07:01:10.405339: +2024-11-23 07:01:10.405538: Epoch 7983 +2024-11-23 07:01:10.405656: Current learning rate: 4e-05 +2024-11-23 07:01:27.859984: train_loss -0.8403 +2024-11-23 07:01:27.860197: val_loss -0.7779 +2024-11-23 07:01:27.860291: Pseudo dice [0.8628] +2024-11-23 07:01:27.860372: Epoch time: 17.46 s +2024-11-23 07:01:28.743789: +2024-11-23 07:01:28.744479: Epoch 7984 +2024-11-23 07:01:28.744648: Current learning rate: 4e-05 +2024-11-23 07:01:47.315207: train_loss -0.8385 +2024-11-23 07:01:47.319261: val_loss -0.7623 +2024-11-23 07:01:47.319411: Pseudo dice [0.85] +2024-11-23 07:01:47.319520: Epoch time: 18.57 s +2024-11-23 07:01:48.285901: +2024-11-23 07:01:48.286126: Epoch 7985 +2024-11-23 07:01:48.286252: Current learning rate: 4e-05 +2024-11-23 07:02:05.583333: train_loss -0.8418 +2024-11-23 07:02:05.583575: val_loss -0.8093 +2024-11-23 07:02:05.583660: Pseudo dice [0.8785] +2024-11-23 07:02:05.583747: Epoch time: 17.3 s +2024-11-23 07:02:06.743094: +2024-11-23 07:02:06.743277: Epoch 7986 +2024-11-23 07:02:06.743375: Current learning rate: 3e-05 +2024-11-23 07:02:24.450676: train_loss -0.8405 +2024-11-23 07:02:24.450898: val_loss -0.7762 +2024-11-23 07:02:24.450973: Pseudo dice [0.8623] +2024-11-23 07:02:24.451054: Epoch time: 17.71 s +2024-11-23 07:02:25.328538: +2024-11-23 07:02:25.328729: Epoch 7987 +2024-11-23 07:02:25.328848: Current learning rate: 3e-05 +2024-11-23 07:02:43.741022: train_loss -0.8453 +2024-11-23 07:02:43.741227: val_loss -0.7902 +2024-11-23 07:02:43.741305: Pseudo dice [0.8636] +2024-11-23 07:02:43.741393: Epoch time: 18.41 s +2024-11-23 07:02:44.615565: +2024-11-23 07:02:44.615756: Epoch 7988 +2024-11-23 07:02:44.615865: Current learning rate: 3e-05 +2024-11-23 07:03:01.930064: train_loss -0.8431 +2024-11-23 07:03:01.930277: val_loss -0.7909 +2024-11-23 07:03:01.930357: Pseudo dice [0.862] +2024-11-23 07:03:01.930439: Epoch time: 17.32 s +2024-11-23 07:03:02.813742: +2024-11-23 07:03:02.813936: Epoch 7989 +2024-11-23 07:03:02.814036: Current learning rate: 3e-05 +2024-11-23 07:03:20.112757: train_loss -0.8334 +2024-11-23 07:03:20.112985: val_loss -0.7796 +2024-11-23 07:03:20.113072: Pseudo dice [0.8649] +2024-11-23 07:03:20.113155: Epoch time: 17.3 s +2024-11-23 07:03:21.004836: +2024-11-23 07:03:21.005065: Epoch 7990 +2024-11-23 07:03:21.005184: Current learning rate: 2e-05 +2024-11-23 07:03:38.921668: train_loss -0.8413 +2024-11-23 07:03:38.921880: val_loss -0.7988 +2024-11-23 07:03:38.921960: Pseudo dice [0.8731] +2024-11-23 07:03:38.922038: Epoch time: 17.92 s +2024-11-23 07:03:39.798199: +2024-11-23 07:03:39.798380: Epoch 7991 +2024-11-23 07:03:39.798476: Current learning rate: 2e-05 +2024-11-23 07:03:58.617399: train_loss -0.8452 +2024-11-23 07:03:58.617602: val_loss -0.7759 +2024-11-23 07:03:58.617693: Pseudo dice [0.8576] +2024-11-23 07:03:58.617771: Epoch time: 18.82 s +2024-11-23 07:03:59.618453: +2024-11-23 07:03:59.618668: Epoch 7992 +2024-11-23 07:03:59.618785: Current learning rate: 2e-05 +2024-11-23 07:04:18.058240: train_loss -0.842 +2024-11-23 07:04:18.058476: val_loss -0.7751 +2024-11-23 07:04:18.058555: Pseudo dice [0.866] +2024-11-23 07:04:18.058643: Epoch time: 18.44 s +2024-11-23 07:04:18.943107: +2024-11-23 07:04:18.943323: Epoch 7993 +2024-11-23 07:04:18.943440: Current learning rate: 2e-05 +2024-11-23 07:04:36.741974: train_loss -0.8439 +2024-11-23 07:04:36.742193: val_loss -0.8052 +2024-11-23 07:04:36.742280: Pseudo dice [0.8682] +2024-11-23 07:04:36.742356: Epoch time: 17.8 s +2024-11-23 07:04:37.628837: +2024-11-23 07:04:37.629091: Epoch 7994 +2024-11-23 07:04:37.629211: Current learning rate: 2e-05 +2024-11-23 07:04:54.731487: train_loss -0.8433 +2024-11-23 07:04:54.731692: val_loss -0.7873 +2024-11-23 07:04:54.731772: Pseudo dice [0.8776] +2024-11-23 07:04:54.731865: Epoch time: 17.1 s +2024-11-23 07:04:55.602932: +2024-11-23 07:04:55.603121: Epoch 7995 +2024-11-23 07:04:55.603220: Current learning rate: 1e-05 +2024-11-23 07:05:12.664423: train_loss -0.8406 +2024-11-23 07:05:12.664632: val_loss -0.7811 +2024-11-23 07:05:12.664711: Pseudo dice [0.8598] +2024-11-23 07:05:12.664795: Epoch time: 17.06 s +2024-11-23 07:05:13.633577: +2024-11-23 07:05:13.633790: Epoch 7996 +2024-11-23 07:05:13.633922: Current learning rate: 1e-05 +2024-11-23 07:05:30.876697: train_loss -0.8449 +2024-11-23 07:05:30.876915: val_loss -0.7757 +2024-11-23 07:05:30.877012: Pseudo dice [0.868] +2024-11-23 07:05:30.877103: Epoch time: 17.24 s +2024-11-23 07:05:31.743884: +2024-11-23 07:05:31.744065: Epoch 7997 +2024-11-23 07:05:31.744168: Current learning rate: 1e-05 +2024-11-23 07:05:49.425022: train_loss -0.8403 +2024-11-23 07:05:49.425275: val_loss -0.7846 +2024-11-23 07:05:49.425358: Pseudo dice [0.8536] +2024-11-23 07:05:49.425462: Epoch time: 17.68 s +2024-11-23 07:05:50.347404: +2024-11-23 07:05:50.347653: Epoch 7998 +2024-11-23 07:05:50.347794: Current learning rate: 1e-05 +2024-11-23 07:06:08.685036: train_loss -0.8375 +2024-11-23 07:06:08.685265: val_loss -0.7767 +2024-11-23 07:06:08.685348: Pseudo dice [0.8535] +2024-11-23 07:06:08.685423: Epoch time: 18.34 s +2024-11-23 07:06:09.587844: +2024-11-23 07:06:09.588064: Epoch 7999 +2024-11-23 07:06:09.588183: Current learning rate: 0.0 +2024-11-23 07:06:27.736866: train_loss -0.8394 +2024-11-23 07:06:27.737106: val_loss -0.7993 +2024-11-23 07:06:27.737191: Pseudo dice [0.8654] +2024-11-23 07:06:27.737279: Epoch time: 18.15 s +2024-11-23 07:06:29.251011: Training done. +2024-11-23 07:06:29.263925: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-23 07:06:29.264787: The split file contains 5 splits. +2024-11-23 07:06:29.264874: Desired fold for training: 3 +2024-11-23 07:06:29.264936: This split has 535 training and 133 validation cases. +2024-11-23 07:06:29.265863: predicting FLAIR_002 +2024-11-23 07:06:29.272882: FLAIR_002, shape torch.Size([1, 132, 143, 190]), rank 0 +2024-11-23 07:06:36.378412: predicting FLAIR_008 +2024-11-23 07:06:36.398947: FLAIR_008, shape torch.Size([1, 133, 144, 189]), rank 0 +2024-11-23 07:06:36.988238: predicting FLAIR_009 +2024-11-23 07:06:37.002455: FLAIR_009, shape torch.Size([1, 144, 152, 207]), rank 0 +2024-11-23 07:06:37.585143: predicting FLAIR_014 +2024-11-23 07:06:37.595777: FLAIR_014, shape torch.Size([1, 120, 146, 177]), rank 0 +2024-11-23 07:06:38.265441: predicting FLAIR_015 +2024-11-23 07:06:38.297582: FLAIR_015, shape torch.Size([1, 127, 153, 194]), rank 0 +2024-11-23 07:06:38.960776: predicting FLAIR_016 +2024-11-23 07:06:38.989707: FLAIR_016, shape torch.Size([1, 135, 149, 192]), rank 0 +2024-11-23 07:06:39.736660: predicting FLAIR_022 +2024-11-23 07:06:39.760823: FLAIR_022, shape torch.Size([1, 126, 147, 173]), rank 0 +2024-11-23 07:06:40.361753: predicting FLAIR_027 +2024-11-23 07:06:40.383791: FLAIR_027, shape torch.Size([1, 135, 147, 193]), rank 0 +2024-11-23 07:06:40.993101: predicting FLAIR_038 +2024-11-23 07:06:41.029609: FLAIR_038, shape torch.Size([1, 127, 144, 182]), rank 0 +2024-11-23 07:06:41.654527: predicting FLAIR_040 +2024-11-23 07:06:41.678397: FLAIR_040, shape torch.Size([1, 125, 140, 199]), rank 0 +2024-11-23 07:06:42.281132: predicting FLAIR_043 +2024-11-23 07:06:42.293962: FLAIR_043, shape torch.Size([1, 131, 147, 191]), rank 0 +2024-11-23 07:06:42.879495: predicting FLAIR_045 +2024-11-23 07:06:42.897278: FLAIR_045, shape torch.Size([1, 132, 160, 201]), rank 0 +2024-11-23 07:06:43.478591: predicting FLAIR_046 +2024-11-23 07:06:43.491052: FLAIR_046, shape torch.Size([1, 133, 143, 194]), rank 0 +2024-11-23 07:06:44.076165: predicting FLAIR_048 +2024-11-23 07:06:44.088319: FLAIR_048, shape torch.Size([1, 137, 138, 187]), rank 0 +2024-11-23 07:06:44.679725: predicting FLAIR_054 +2024-11-23 07:06:44.692523: FLAIR_054, shape torch.Size([1, 132, 151, 194]), rank 0 +2024-11-23 07:06:45.271733: predicting FLAIR_062 +2024-11-23 07:06:45.284524: FLAIR_062, shape torch.Size([1, 132, 147, 190]), rank 0 +2024-11-23 07:06:45.863314: predicting FLAIR_072 +2024-11-23 07:06:45.876982: FLAIR_072, shape torch.Size([1, 131, 156, 196]), rank 0 +2024-11-23 07:06:46.456537: predicting FLAIR_080 +2024-11-23 07:06:46.470960: FLAIR_080, shape torch.Size([1, 145, 163, 189]), rank 0 +2024-11-23 07:06:47.052558: predicting FLAIR_081 +2024-11-23 07:06:47.065689: FLAIR_081, shape torch.Size([1, 138, 155, 179]), rank 0 +2024-11-23 07:06:47.651271: predicting FLAIR_083 +2024-11-23 07:06:47.678160: FLAIR_083, shape torch.Size([1, 142, 150, 187]), rank 0 +2024-11-23 07:06:48.280787: predicting FLAIR_093 +2024-11-23 07:06:48.293382: FLAIR_093, shape torch.Size([1, 131, 136, 170]), rank 0 +2024-11-23 07:06:48.895102: predicting FLAIR_099 +2024-11-23 07:06:48.906638: FLAIR_099, shape torch.Size([1, 137, 132, 179]), rank 0 +2024-11-23 07:06:49.523128: predicting FLAIR_103 +2024-11-23 07:06:49.542789: FLAIR_103, shape torch.Size([1, 142, 160, 182]), rank 0 +2024-11-23 07:06:50.201127: predicting FLAIR_105 +2024-11-23 07:06:50.214366: FLAIR_105, shape torch.Size([1, 137, 150, 195]), rank 0 +2024-11-23 07:06:50.806817: predicting FLAIR_115 +2024-11-23 07:06:50.821610: FLAIR_115, shape torch.Size([1, 142, 178, 208]), rank 0 +2024-11-23 07:06:51.431475: predicting FLAIR_118 +2024-11-23 07:06:51.446051: FLAIR_118, shape torch.Size([1, 132, 152, 186]), rank 0 +2024-11-23 07:06:52.056944: predicting FLAIR_123 +2024-11-23 07:06:52.078833: FLAIR_123, shape torch.Size([1, 141, 151, 178]), rank 0 +2024-11-23 07:06:52.725137: predicting FLAIR_128 +2024-11-23 07:06:52.752145: FLAIR_128, shape torch.Size([1, 125, 158, 194]), rank 0 +2024-11-23 07:06:53.378138: predicting FLAIR_132 +2024-11-23 07:06:53.400490: FLAIR_132, shape torch.Size([1, 141, 153, 175]), rank 0 +2024-11-23 07:06:54.038374: predicting FLAIR_141 +2024-11-23 07:06:54.054971: FLAIR_141, shape torch.Size([1, 126, 129, 175]), rank 0 +2024-11-23 07:06:55.471095: predicting FLAIR_142 +2024-11-23 07:06:55.484993: FLAIR_142, shape torch.Size([1, 136, 161, 187]), rank 0 +2024-11-23 07:06:56.129138: predicting FLAIR_143 +2024-11-23 07:06:56.141417: FLAIR_143, shape torch.Size([1, 135, 143, 181]), rank 0 +2024-11-23 07:06:56.793136: predicting FLAIR_146 +2024-11-23 07:06:56.819238: FLAIR_146, shape torch.Size([1, 138, 152, 189]), rank 0 +2024-11-23 07:06:57.471135: predicting FLAIR_150 +2024-11-23 07:06:57.485596: FLAIR_150, shape torch.Size([1, 147, 152, 191]), rank 0 +2024-11-23 07:06:58.122239: predicting FLAIR_152 +2024-11-23 07:06:58.135280: FLAIR_152, shape torch.Size([1, 137, 150, 195]), rank 0 +2024-11-23 07:06:58.737087: predicting FLAIR_166 +2024-11-23 07:06:58.751358: FLAIR_166, shape torch.Size([1, 142, 151, 213]), rank 0 +2024-11-23 07:06:59.349209: predicting FLAIR_171 +2024-11-23 07:06:59.363124: FLAIR_171, shape torch.Size([1, 142, 153, 199]), rank 0 +2024-11-23 07:06:59.951535: predicting FLAIR_172 +2024-11-23 07:06:59.997586: FLAIR_172, shape torch.Size([1, 136, 149, 197]), rank 0 +2024-11-23 07:07:00.609153: predicting FLAIR_174 +2024-11-23 07:07:00.640342: FLAIR_174, shape torch.Size([1, 144, 157, 200]), rank 0 +2024-11-23 07:07:01.248495: predicting FLAIR_175 +2024-11-23 07:07:01.262980: FLAIR_175, shape torch.Size([1, 139, 201, 162]), rank 0 +2024-11-23 07:07:02.150622: predicting FLAIR_190 +2024-11-23 07:07:02.165150: FLAIR_190, shape torch.Size([1, 135, 197, 156]), rank 0 +2024-11-23 07:07:02.633904: predicting FLAIR_201 +2024-11-23 07:07:02.657040: FLAIR_201, shape torch.Size([1, 126, 173, 148]), rank 0 +2024-11-23 07:07:02.969768: predicting FLAIR_203 +2024-11-23 07:07:02.982032: FLAIR_203, shape torch.Size([1, 135, 190, 138]), rank 0 +2024-11-23 07:07:03.289655: predicting FLAIR_210 +2024-11-23 07:07:03.316048: FLAIR_210, shape torch.Size([1, 142, 197, 160]), rank 0 +2024-11-23 07:07:03.788136: predicting FLAIR_211 +2024-11-23 07:07:03.810397: FLAIR_211, shape torch.Size([1, 133, 192, 153]), rank 0 +2024-11-23 07:07:04.159776: predicting FLAIR_219 +2024-11-23 07:07:04.175434: FLAIR_219, shape torch.Size([1, 133, 191, 166]), rank 0 +2024-11-23 07:07:04.763918: predicting FLAIR_223 +2024-11-23 07:07:04.802385: FLAIR_223, shape torch.Size([1, 138, 190, 149]), rank 0 +2024-11-23 07:07:05.111732: predicting FLAIR_226 +2024-11-23 07:07:05.134926: FLAIR_226, shape torch.Size([1, 127, 194, 154]), rank 0 +2024-11-23 07:07:05.589480: predicting FLAIR_236 +2024-11-23 07:07:05.602592: FLAIR_236, shape torch.Size([1, 130, 196, 151]), rank 0 +2024-11-23 07:07:06.069118: predicting FLAIR_238 +2024-11-23 07:07:06.081808: FLAIR_238, shape torch.Size([1, 128, 188, 151]), rank 0 +2024-11-23 07:07:06.397585: predicting FLAIR_244 +2024-11-23 07:07:06.411455: FLAIR_244, shape torch.Size([1, 141, 158, 206]), rank 0 +2024-11-23 07:07:06.994322: predicting FLAIR_249 +2024-11-23 07:07:07.015296: FLAIR_249, shape torch.Size([1, 122, 151, 188]), rank 0 +2024-11-23 07:07:07.612118: predicting FLAIR_250 +2024-11-23 07:07:07.626721: FLAIR_250, shape torch.Size([1, 141, 202, 160]), rank 0 +2024-11-23 07:07:08.093117: predicting FLAIR_257 +2024-11-23 07:07:08.106100: FLAIR_257, shape torch.Size([1, 132, 191, 156]), rank 0 +2024-11-23 07:07:08.427215: predicting FLAIR_263 +2024-11-23 07:07:08.439702: FLAIR_263, shape torch.Size([1, 127, 189, 156]), rank 0 +2024-11-23 07:07:08.773149: predicting FLAIR_266 +2024-11-23 07:07:08.797678: FLAIR_266, shape torch.Size([1, 138, 173, 150]), rank 0 +2024-11-23 07:07:09.124654: predicting FLAIR_272 +2024-11-23 07:07:09.137318: FLAIR_272, shape torch.Size([1, 133, 183, 154]), rank 0 +2024-11-23 07:07:09.450239: predicting FLAIR_274 +2024-11-23 07:07:09.464722: FLAIR_274, shape torch.Size([1, 137, 201, 154]), rank 0 +2024-11-23 07:07:09.917310: predicting FLAIR_291 +2024-11-23 07:07:09.929546: FLAIR_291, shape torch.Size([1, 134, 180, 148]), rank 0 +2024-11-23 07:07:10.230323: predicting FLAIR_313 +2024-11-23 07:07:10.245045: FLAIR_313, shape torch.Size([1, 139, 184, 153]), rank 0 +2024-11-23 07:07:10.573227: predicting FLAIR_314 +2024-11-23 07:07:10.595626: FLAIR_314, shape torch.Size([1, 138, 207, 160]), rank 0 +2024-11-23 07:07:11.091406: predicting FLAIR_317 +2024-11-23 07:07:11.134805: FLAIR_317, shape torch.Size([1, 134, 194, 151]), rank 0 +2024-11-23 07:07:11.577216: predicting FLAIR_321 +2024-11-23 07:07:11.613086: FLAIR_321, shape torch.Size([1, 150, 180, 160]), rank 0 +2024-11-23 07:07:11.940850: predicting FLAIR_326 +2024-11-23 07:07:11.955029: FLAIR_326, shape torch.Size([1, 137, 200, 159]), rank 0 +2024-11-23 07:07:12.406593: predicting FLAIR_327 +2024-11-23 07:07:12.448606: FLAIR_327, shape torch.Size([1, 133, 197, 156]), rank 0 +2024-11-23 07:07:12.909306: predicting FLAIR_332 +2024-11-23 07:07:12.934410: FLAIR_332, shape torch.Size([1, 134, 146, 187]), rank 0 +2024-11-23 07:07:13.533303: predicting FLAIR_333 +2024-11-23 07:07:13.556854: FLAIR_333, shape torch.Size([1, 129, 189, 151]), rank 0 +2024-11-23 07:07:13.865008: predicting FLAIR_337 +2024-11-23 07:07:13.901091: FLAIR_337, shape torch.Size([1, 138, 193, 158]), rank 0 +2024-11-23 07:07:14.366985: predicting FLAIR_346 +2024-11-23 07:07:14.392807: FLAIR_346, shape torch.Size([1, 128, 149, 191]), rank 0 +2024-11-23 07:07:14.990574: predicting FLAIR_350 +2024-11-23 07:07:15.014614: FLAIR_350, shape torch.Size([1, 122, 148, 175]), rank 0 +2024-11-23 07:07:15.604513: predicting FLAIR_353 +2024-11-23 07:07:15.627646: FLAIR_353, shape torch.Size([1, 126, 148, 176]), rank 0 +2024-11-23 07:07:16.235249: predicting FLAIR_355 +2024-11-23 07:07:16.247671: FLAIR_355, shape torch.Size([1, 130, 154, 176]), rank 0 +2024-11-23 07:07:16.838539: predicting FLAIR_361 +2024-11-23 07:07:16.850806: FLAIR_361, shape torch.Size([1, 126, 148, 189]), rank 0 +2024-11-23 07:07:17.435008: predicting FLAIR_363 +2024-11-23 07:07:17.472614: FLAIR_363, shape torch.Size([1, 133, 157, 188]), rank 0 +2024-11-23 07:07:18.058960: predicting FLAIR_377 +2024-11-23 07:07:18.073131: FLAIR_377, shape torch.Size([1, 130, 148, 188]), rank 0 +2024-11-23 07:07:18.654006: predicting FLAIR_379 +2024-11-23 07:07:18.682774: FLAIR_379, shape torch.Size([1, 134, 148, 185]), rank 0 +2024-11-23 07:07:19.275149: predicting FLAIR_380 +2024-11-23 07:07:19.299637: FLAIR_380, shape torch.Size([1, 134, 155, 183]), rank 0 +2024-11-23 07:07:19.891413: predicting FLAIR_384 +2024-11-23 07:07:19.905649: FLAIR_384, shape torch.Size([1, 145, 163, 206]), rank 0 +2024-11-23 07:07:20.497694: predicting FLAIR_397 +2024-11-23 07:07:20.512216: FLAIR_397, shape torch.Size([1, 134, 156, 195]), rank 0 +2024-11-23 07:07:21.112164: predicting FLAIR_398 +2024-11-23 07:07:21.124413: FLAIR_398, shape torch.Size([1, 136, 154, 194]), rank 0 +2024-11-23 07:07:21.730150: predicting FLAIR_407 +2024-11-23 07:07:21.743737: FLAIR_407, shape torch.Size([1, 132, 192, 153]), rank 0 +2024-11-23 07:07:22.072007: predicting FLAIR_408 +2024-11-23 07:07:22.086934: FLAIR_408, shape torch.Size([1, 144, 177, 164]), rank 0 +2024-11-23 07:07:22.697685: predicting FLAIR_409 +2024-11-23 07:07:22.726167: FLAIR_409, shape torch.Size([1, 135, 197, 154]), rank 0 +2024-11-23 07:07:23.218998: predicting FLAIR_413 +2024-11-23 07:07:23.230219: FLAIR_413, shape torch.Size([1, 126, 172, 147]), rank 0 +2024-11-23 07:07:23.535907: predicting FLAIR_416 +2024-11-23 07:07:23.562450: FLAIR_416, shape torch.Size([1, 143, 196, 159]), rank 0 +2024-11-23 07:07:24.052165: predicting FLAIR_419 +2024-11-23 07:07:24.063746: FLAIR_419, shape torch.Size([1, 127, 189, 140]), rank 0 +2024-11-23 07:07:24.377711: predicting FLAIR_433 +2024-11-23 07:07:24.389936: FLAIR_433, shape torch.Size([1, 137, 179, 142]), rank 0 +2024-11-23 07:07:24.706145: predicting FLAIR_434 +2024-11-23 07:07:24.720335: FLAIR_434, shape torch.Size([1, 141, 201, 158]), rank 0 +2024-11-23 07:07:25.190763: predicting FLAIR_437 +2024-11-23 07:07:25.211313: FLAIR_437, shape torch.Size([1, 148, 184, 148]), rank 0 +2024-11-23 07:07:25.531951: predicting FLAIR_438 +2024-11-23 07:07:25.544519: FLAIR_438, shape torch.Size([1, 128, 190, 156]), rank 0 +2024-11-23 07:07:25.854002: predicting FLAIR_445 +2024-11-23 07:07:25.876743: FLAIR_445, shape torch.Size([1, 132, 193, 148]), rank 0 +2024-11-23 07:07:26.326092: predicting FLAIR_459 +2024-11-23 07:07:26.361227: FLAIR_459, shape torch.Size([1, 139, 183, 153]), rank 0 +2024-11-23 07:07:26.696170: predicting FLAIR_461 +2024-11-23 07:07:26.714431: FLAIR_461, shape torch.Size([1, 149, 177, 158]), rank 0 +2024-11-23 07:07:27.061117: predicting FLAIR_462 +2024-11-23 07:07:27.074473: FLAIR_462, shape torch.Size([1, 131, 159, 198]), rank 0 +2024-11-23 07:07:27.666147: predicting FLAIR_465 +2024-11-23 07:07:27.680205: FLAIR_465, shape torch.Size([1, 137, 199, 159]), rank 0 +2024-11-23 07:07:28.145746: predicting FLAIR_481 +2024-11-23 07:07:28.181356: FLAIR_481, shape torch.Size([1, 130, 143, 193]), rank 0 +2024-11-23 07:07:28.779832: predicting FLAIR_485 +2024-11-23 07:07:28.805513: FLAIR_485, shape torch.Size([1, 130, 146, 186]), rank 0 +2024-11-23 07:07:29.396815: predicting FLAIR_494 +2024-11-23 07:07:29.408125: FLAIR_494, shape torch.Size([1, 125, 142, 177]), rank 0 +2024-11-23 07:07:29.984518: predicting FLAIR_496 +2024-11-23 07:07:29.997736: FLAIR_496, shape torch.Size([1, 138, 152, 190]), rank 0 +2024-11-23 07:07:30.577707: predicting FLAIR_500 +2024-11-23 07:07:30.605426: FLAIR_500, shape torch.Size([1, 133, 146, 191]), rank 0 +2024-11-23 07:07:31.215201: predicting FLAIR_501 +2024-11-23 07:07:31.233502: FLAIR_501, shape torch.Size([1, 134, 151, 194]), rank 0 +2024-11-23 07:07:31.867642: predicting FLAIR_506 +2024-11-23 07:07:31.889611: FLAIR_506, shape torch.Size([1, 124, 146, 189]), rank 0 +2024-11-23 07:07:32.531196: predicting FLAIR_510 +2024-11-23 07:07:32.558254: FLAIR_510, shape torch.Size([1, 133, 145, 196]), rank 0 +2024-11-23 07:07:33.218366: predicting FLAIR_520 +2024-11-23 07:07:33.260494: FLAIR_520, shape torch.Size([1, 135, 154, 194]), rank 0 +2024-11-23 07:07:33.863863: predicting FLAIR_521 +2024-11-23 07:07:33.876846: FLAIR_521, shape torch.Size([1, 128, 150, 184]), rank 0 +2024-11-23 07:07:34.474162: predicting FLAIR_529 +2024-11-23 07:07:34.496017: FLAIR_529, shape torch.Size([1, 128, 145, 189]), rank 0 +2024-11-23 07:07:35.099205: predicting FLAIR_533 +2024-11-23 07:07:35.113199: FLAIR_533, shape torch.Size([1, 135, 151, 196]), rank 0 +2024-11-23 07:07:35.716787: predicting FLAIR_535 +2024-11-23 07:07:35.729479: FLAIR_535, shape torch.Size([1, 133, 139, 191]), rank 0 +2024-11-23 07:07:39.434629: predicting FLAIR_536 +2024-11-23 07:07:39.448062: FLAIR_536, shape torch.Size([1, 138, 150, 194]), rank 0 +2024-11-23 07:07:40.245191: predicting FLAIR_538 +2024-11-23 07:07:40.274498: FLAIR_538, shape torch.Size([1, 134, 151, 198]), rank 0 +2024-11-23 07:07:40.952194: predicting FLAIR_543 +2024-11-23 07:07:40.979416: FLAIR_543, shape torch.Size([1, 135, 160, 209]), rank 0 +2024-11-23 07:07:41.650933: predicting FLAIR_544 +2024-11-23 07:07:41.672276: FLAIR_544, shape torch.Size([1, 136, 153, 190]), rank 0 +2024-11-23 07:07:42.288105: predicting FLAIR_549 +2024-11-23 07:07:42.302141: FLAIR_549, shape torch.Size([1, 131, 150, 194]), rank 0 +2024-11-23 07:07:42.918218: predicting FLAIR_550 +2024-11-23 07:07:42.937617: FLAIR_550, shape torch.Size([1, 135, 164, 201]), rank 0 +2024-11-23 07:07:43.581690: predicting FLAIR_551 +2024-11-23 07:07:43.601633: FLAIR_551, shape torch.Size([1, 136, 154, 196]), rank 0 +2024-11-23 07:07:44.239107: predicting FLAIR_552 +2024-11-23 07:07:44.259575: FLAIR_552, shape torch.Size([1, 139, 152, 193]), rank 0 +2024-11-23 07:07:47.198258: predicting FLAIR_558 +2024-11-23 07:07:47.212317: FLAIR_558, shape torch.Size([1, 136, 155, 195]), rank 0 +2024-11-23 07:07:47.984031: predicting FLAIR_562 +2024-11-23 07:07:48.022096: FLAIR_562, shape torch.Size([1, 136, 148, 185]), rank 0 +2024-11-23 07:07:48.702260: predicting FLAIR_565 +2024-11-23 07:07:48.728817: FLAIR_565, shape torch.Size([1, 125, 155, 190]), rank 0 +2024-11-23 07:07:50.098641: predicting FLAIR_568 +2024-11-23 07:07:50.111081: FLAIR_568, shape torch.Size([1, 134, 137, 185]), rank 0 +2024-11-23 07:07:50.696699: predicting FLAIR_571 +2024-11-23 07:07:50.710632: FLAIR_571, shape torch.Size([1, 138, 156, 209]), rank 0 +2024-11-23 07:07:51.313966: predicting FLAIR_572 +2024-11-23 07:07:51.328234: FLAIR_572, shape torch.Size([1, 135, 155, 201]), rank 0 +2024-11-23 07:07:51.939677: predicting FLAIR_583 +2024-11-23 07:07:51.953479: FLAIR_583, shape torch.Size([1, 131, 158, 193]), rank 0 +2024-11-23 07:07:52.624915: predicting FLAIR_594 +2024-11-23 07:07:52.669601: FLAIR_594, shape torch.Size([1, 129, 149, 187]), rank 0 +2024-11-23 07:07:56.635167: predicting FLAIR_615 +2024-11-23 07:07:56.647989: FLAIR_615, shape torch.Size([1, 132, 146, 192]), rank 0 +2024-11-23 07:07:57.238823: predicting FLAIR_630 +2024-11-23 07:07:57.254247: FLAIR_630, shape torch.Size([1, 144, 160, 206]), rank 0 +2024-11-23 07:07:57.855205: predicting FLAIR_643 +2024-11-23 07:07:57.867510: FLAIR_643, shape torch.Size([1, 129, 143, 187]), rank 0 +2024-11-23 07:07:58.476322: predicting FLAIR_646 +2024-11-23 07:07:58.499102: FLAIR_646, shape torch.Size([1, 143, 163, 208]), rank 0 +2024-11-23 07:07:59.161224: predicting FLAIR_647 +2024-11-23 07:07:59.183176: FLAIR_647, shape torch.Size([1, 126, 136, 193]), rank 0 +2024-11-23 07:07:59.838634: predicting FLAIR_649 +2024-11-23 07:07:59.867357: FLAIR_649, shape torch.Size([1, 136, 149, 185]), rank 0 +2024-11-23 07:08:00.526417: predicting FLAIR_659 +2024-11-23 07:08:00.542782: FLAIR_659, shape torch.Size([1, 143, 148, 183]), rank 0 +2024-11-23 07:08:02.140168: predicting FLAIR_660 +2024-11-23 07:08:02.152514: FLAIR_660, shape torch.Size([1, 123, 148, 190]), rank 0 +2024-11-23 07:08:02.974880: predicting FLAIR_666 +2024-11-23 07:08:02.999307: FLAIR_666, shape torch.Size([1, 132, 148, 188]), rank 0 +2024-11-23 07:08:27.284790: Validation complete +2024-11-23 07:08:27.286149: Mean Validation Dice: 0.8026924964103578 diff --git 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"num_input_channels": "1", + "num_iterations_per_epoch": "250", + "num_val_iterations_per_epoch": "50", + "optimizer": "SGD (\nParameter Group 0\n dampening: 0\n differentiable: False\n foreach: None\n initial_lr: 0.01\n lr: 0.01\n maximize: False\n momentum: 0.99\n nesterov: True\n weight_decay: 3e-05\n)", + "output_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4", + "output_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres", + "oversample_foreground_percent": "0.33", + "plans_manager": "{'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 106, 'patch_size': [160, 192], 'median_image_size_in_voxels': [154.0, 185.0], 'spacing': [0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}", + "preprocessed_dataset_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/nnUNetPlans_3d_fullres", + "preprocessed_dataset_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML", + "save_every": "50", + "torch_version": "2.1.2+cu121", + "unpack_dataset": "True", + "was_initialized": "True", + "weight_decay": "3e-05" +} \ No newline at end of file diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4/progress.png b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4/progress.png new file mode 100644 index 0000000000000000000000000000000000000000..b24059adf85ddfb462fd497111c0f9ab4f5372ac Binary files /dev/null and b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4/progress.png differ diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4/training_log_2024_11_21_10_40_22.txt b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4/training_log_2024_11_21_10_40_22.txt new file mode 100644 index 0000000000000000000000000000000000000000..c5f0fd066b24949f92783262cd3b5f745978ec56 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4/training_log_2024_11_21_10_40_22.txt @@ -0,0 +1,56435 @@ + +####################################################################### +Please cite the following paper when using nnU-Net: +Isensee, F., Jaeger, P. F., Kohl, S. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 18(2), 203-211. +####################################################################### + +2024-11-21 10:40:22.561305: do_dummy_2d_data_aug: False +2024-11-21 10:40:22.565481: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-21 10:40:22.566318: The split file contains 5 splits. +2024-11-21 10:40:22.566380: Desired fold for training: 4 +2024-11-21 10:40:22.566428: This split has 535 training and 133 validation cases. +2024-11-21 10:40:25.452839: Using torch.compile... + +This is the configuration used by this training: +Configuration name: 3d_fullres + {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False} + +These are the global plan.json settings: + {'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}} + +2024-11-21 10:40:26.458525: unpacking dataset... +2024-11-21 10:40:35.032246: unpacking done... +2024-11-21 10:40:35.043379: Unable to plot network architecture: nnUNet_compile is enabled! +2024-11-21 10:40:35.050742: +2024-11-21 10:40:35.050834: Epoch 0 +2024-11-21 10:40:35.050979: Current learning rate: 0.01 +2024-11-21 10:41:59.635014: train_loss -0.2265 +2024-11-21 10:41:59.647749: val_loss -0.4559 +2024-11-21 10:41:59.714403: Pseudo dice [0.5144] +2024-11-21 10:41:59.714539: Epoch time: 84.59 s +2024-11-21 10:41:59.714612: Yayy! New best EMA pseudo Dice: 0.5144 +2024-11-21 10:42:02.072441: +2024-11-21 10:42:02.073260: Epoch 1 +2024-11-21 10:42:02.073385: Current learning rate: 0.01 +2024-11-21 10:42:24.711163: train_loss -0.4714 +2024-11-21 10:42:24.739537: val_loss -0.5627 +2024-11-21 10:42:24.739629: Pseudo dice [0.6851] +2024-11-21 10:42:24.739915: Epoch time: 22.64 s +2024-11-21 10:42:24.739979: Yayy! New best EMA pseudo Dice: 0.5315 +2024-11-21 10:42:26.288609: +2024-11-21 10:42:26.380804: Epoch 2 +2024-11-21 10:42:26.380947: Current learning rate: 0.01 +2024-11-21 10:42:54.743290: train_loss -0.5361 +2024-11-21 10:42:54.765657: val_loss -0.5973 +2024-11-21 10:42:54.765805: Pseudo dice [0.7421] +2024-11-21 10:42:54.765896: Epoch time: 28.46 s +2024-11-21 10:42:54.765960: Yayy! New best EMA pseudo Dice: 0.5526 +2024-11-21 10:42:55.858124: +2024-11-21 10:42:55.858312: Epoch 3 +2024-11-21 10:42:55.858427: Current learning rate: 0.01 +2024-11-21 10:43:14.906735: train_loss -0.5683 +2024-11-21 10:43:14.922026: val_loss -0.6111 +2024-11-21 10:43:14.922164: Pseudo dice [0.7413] +2024-11-21 10:43:14.922260: Epoch time: 19.05 s +2024-11-21 10:43:14.922327: Yayy! New best EMA pseudo Dice: 0.5714 +2024-11-21 10:43:15.925138: +2024-11-21 10:43:15.925299: Epoch 4 +2024-11-21 10:43:15.925410: Current learning rate: 0.01 +2024-11-21 10:43:35.058130: train_loss -0.6052 +2024-11-21 10:43:35.063870: val_loss -0.6411 +2024-11-21 10:43:35.063993: Pseudo dice [0.7362] +2024-11-21 10:43:35.064081: Epoch time: 19.13 s +2024-11-21 10:43:35.064146: Yayy! New best EMA pseudo Dice: 0.5879 +2024-11-21 10:43:36.025272: +2024-11-21 10:43:36.025442: Epoch 5 +2024-11-21 10:43:36.025557: Current learning rate: 0.00999 +2024-11-21 10:43:55.866866: train_loss -0.6331 +2024-11-21 10:43:55.868942: val_loss -0.6633 +2024-11-21 10:43:55.869073: Pseudo dice [0.7997] +2024-11-21 10:43:55.869152: Epoch time: 19.84 s +2024-11-21 10:43:55.869215: Yayy! New best EMA pseudo Dice: 0.6091 +2024-11-21 10:43:56.835159: +2024-11-21 10:43:56.835331: Epoch 6 +2024-11-21 10:43:56.835439: Current learning rate: 0.00999 +2024-11-21 10:44:15.669434: train_loss -0.6461 +2024-11-21 10:44:15.671257: val_loss -0.6664 +2024-11-21 10:44:15.671366: Pseudo dice [0.796] +2024-11-21 10:44:15.671454: Epoch time: 18.84 s +2024-11-21 10:44:15.671527: Yayy! New best EMA pseudo Dice: 0.6278 +2024-11-21 10:44:16.702841: +2024-11-21 10:44:16.703023: Epoch 7 +2024-11-21 10:44:16.703145: Current learning rate: 0.00999 +2024-11-21 10:44:35.337648: train_loss -0.651 +2024-11-21 10:44:35.344577: val_loss -0.6887 +2024-11-21 10:44:35.344768: Pseudo dice [0.7898] +2024-11-21 10:44:35.344851: Epoch time: 18.64 s +2024-11-21 10:44:35.344916: Yayy! New best EMA pseudo Dice: 0.644 +2024-11-21 10:44:36.310054: +2024-11-21 10:44:36.310237: Epoch 8 +2024-11-21 10:44:36.310347: Current learning rate: 0.00999 +2024-11-21 10:44:55.069113: train_loss -0.6662 +2024-11-21 10:44:55.072233: val_loss -0.6937 +2024-11-21 10:44:55.072321: Pseudo dice [0.8069] +2024-11-21 10:44:55.072399: Epoch time: 18.76 s +2024-11-21 10:44:55.072460: Yayy! New best EMA pseudo Dice: 0.6603 +2024-11-21 10:44:56.050107: +2024-11-21 10:44:56.050314: Epoch 9 +2024-11-21 10:44:56.050435: Current learning rate: 0.00999 +2024-11-21 10:45:14.566991: train_loss -0.6652 +2024-11-21 10:45:14.568908: val_loss -0.6721 +2024-11-21 10:45:14.569020: Pseudo dice [0.7924] +2024-11-21 10:45:14.569108: Epoch time: 18.52 s +2024-11-21 10:45:14.569179: Yayy! New best EMA pseudo Dice: 0.6735 +2024-11-21 10:45:15.792550: +2024-11-21 10:45:15.792727: Epoch 10 +2024-11-21 10:45:15.792852: Current learning rate: 0.00999 +2024-11-21 10:45:35.394045: train_loss -0.6591 +2024-11-21 10:45:35.401608: val_loss -0.69 +2024-11-21 10:45:35.401738: Pseudo dice [0.828] +2024-11-21 10:45:35.401825: Epoch time: 19.6 s +2024-11-21 10:45:35.401893: Yayy! New best EMA pseudo Dice: 0.6889 +2024-11-21 10:45:36.387713: +2024-11-21 10:45:36.387898: Epoch 11 +2024-11-21 10:45:36.388008: Current learning rate: 0.00999 +2024-11-21 10:45:55.390162: train_loss -0.6699 +2024-11-21 10:45:55.395751: val_loss -0.6846 +2024-11-21 10:45:55.395880: Pseudo dice [0.7806] +2024-11-21 10:45:55.395956: Epoch time: 19.0 s +2024-11-21 10:45:55.396020: Yayy! New best EMA pseudo Dice: 0.6981 +2024-11-21 10:45:56.485406: +2024-11-21 10:45:56.485625: Epoch 12 +2024-11-21 10:45:56.485738: Current learning rate: 0.00999 +2024-11-21 10:46:14.493389: train_loss -0.664 +2024-11-21 10:46:14.495208: val_loss -0.6523 +2024-11-21 10:46:14.495305: Pseudo dice [0.802] +2024-11-21 10:46:14.495383: Epoch time: 18.01 s +2024-11-21 10:46:14.495466: Yayy! New best EMA pseudo Dice: 0.7085 +2024-11-21 10:46:15.713319: +2024-11-21 10:46:15.713494: Epoch 13 +2024-11-21 10:46:15.713609: Current learning rate: 0.00999 +2024-11-21 10:46:34.604870: train_loss -0.68 +2024-11-21 10:46:34.611176: val_loss -0.6883 +2024-11-21 10:46:34.611369: Pseudo dice [0.8071] +2024-11-21 10:46:34.611462: Epoch time: 18.89 s +2024-11-21 10:46:34.611532: Yayy! New best EMA pseudo Dice: 0.7184 +2024-11-21 10:46:35.595788: +2024-11-21 10:46:35.595979: Epoch 14 +2024-11-21 10:46:35.596087: Current learning rate: 0.00998 +2024-11-21 10:46:55.180158: train_loss -0.6889 +2024-11-21 10:46:55.187798: val_loss -0.6944 +2024-11-21 10:46:55.187932: Pseudo dice [0.8222] +2024-11-21 10:46:55.188025: Epoch time: 19.59 s +2024-11-21 10:46:55.188096: Yayy! New best EMA pseudo Dice: 0.7287 +2024-11-21 10:46:56.199861: +2024-11-21 10:46:56.200038: Epoch 15 +2024-11-21 10:46:56.200148: Current learning rate: 0.00998 +2024-11-21 10:47:15.659672: train_loss -0.6931 +2024-11-21 10:47:15.668840: val_loss -0.7475 +2024-11-21 10:47:15.668967: Pseudo dice [0.8241] +2024-11-21 10:47:15.669051: Epoch time: 19.46 s +2024-11-21 10:47:15.669126: Yayy! New best EMA pseudo Dice: 0.7383 +2024-11-21 10:47:16.677941: +2024-11-21 10:47:16.678106: Epoch 16 +2024-11-21 10:47:16.678218: Current learning rate: 0.00998 +2024-11-21 10:47:35.409681: train_loss -0.682 +2024-11-21 10:47:35.418861: val_loss -0.6752 +2024-11-21 10:47:35.419001: Pseudo dice [0.787] +2024-11-21 10:47:35.419093: Epoch time: 18.73 s +2024-11-21 10:47:35.419167: Yayy! New best EMA pseudo Dice: 0.7431 +2024-11-21 10:47:36.442827: +2024-11-21 10:47:36.443043: Epoch 17 +2024-11-21 10:47:36.443158: Current learning rate: 0.00998 +2024-11-21 10:47:56.099303: train_loss -0.6835 +2024-11-21 10:47:56.103431: val_loss -0.6842 +2024-11-21 10:47:56.103558: Pseudo dice [0.7994] +2024-11-21 10:47:56.103645: Epoch time: 19.66 s +2024-11-21 10:47:56.103709: Yayy! New best EMA pseudo Dice: 0.7488 +2024-11-21 10:47:57.090259: +2024-11-21 10:47:57.090451: Epoch 18 +2024-11-21 10:47:57.090558: Current learning rate: 0.00998 +2024-11-21 10:48:15.361692: train_loss -0.6861 +2024-11-21 10:48:15.364316: val_loss -0.7074 +2024-11-21 10:48:15.364408: Pseudo dice [0.8121] +2024-11-21 10:48:15.364490: Epoch time: 18.27 s +2024-11-21 10:48:15.364561: Yayy! New best EMA pseudo Dice: 0.7551 +2024-11-21 10:48:16.369257: +2024-11-21 10:48:16.369476: Epoch 19 +2024-11-21 10:48:16.369598: Current learning rate: 0.00998 +2024-11-21 10:48:35.516557: train_loss -0.6991 +2024-11-21 10:48:35.524667: val_loss -0.7481 +2024-11-21 10:48:35.524797: Pseudo dice [0.8161] +2024-11-21 10:48:35.524878: Epoch time: 19.15 s +2024-11-21 10:48:35.524948: Yayy! New best EMA pseudo Dice: 0.7612 +2024-11-21 10:48:36.524502: +2024-11-21 10:48:36.524680: Epoch 20 +2024-11-21 10:48:36.524794: Current learning rate: 0.00998 +2024-11-21 10:48:55.789825: train_loss -0.6997 +2024-11-21 10:48:55.797785: val_loss -0.7208 +2024-11-21 10:48:55.797934: Pseudo dice [0.8159] +2024-11-21 10:48:55.798023: Epoch time: 19.27 s +2024-11-21 10:48:55.798098: Yayy! New best EMA pseudo Dice: 0.7667 +2024-11-21 10:48:56.802804: +2024-11-21 10:48:56.802984: Epoch 21 +2024-11-21 10:48:56.803096: Current learning rate: 0.00998 +2024-11-21 10:49:15.905725: train_loss -0.7074 +2024-11-21 10:49:15.919301: val_loss -0.7247 +2024-11-21 10:49:15.919436: Pseudo dice [0.8234] +2024-11-21 10:49:15.919533: Epoch time: 19.1 s +2024-11-21 10:49:15.919603: Yayy! New best EMA pseudo Dice: 0.7724 +2024-11-21 10:49:16.952320: +2024-11-21 10:49:16.952528: Epoch 22 +2024-11-21 10:49:16.952652: Current learning rate: 0.00998 +2024-11-21 10:49:35.678149: train_loss -0.6925 +2024-11-21 10:49:35.683460: val_loss -0.6936 +2024-11-21 10:49:35.683573: Pseudo dice [0.8022] +2024-11-21 10:49:35.683655: Epoch time: 18.73 s +2024-11-21 10:49:35.683941: Yayy! New best EMA pseudo Dice: 0.7753 +2024-11-21 10:49:36.693777: +2024-11-21 10:49:36.693972: Epoch 23 +2024-11-21 10:49:36.694091: Current learning rate: 0.00997 +2024-11-21 10:49:56.291686: train_loss -0.6997 +2024-11-21 10:49:56.298486: val_loss -0.7132 +2024-11-21 10:49:56.298663: Pseudo dice [0.8219] +2024-11-21 10:49:56.298749: Epoch time: 19.6 s +2024-11-21 10:49:56.298820: Yayy! New best EMA pseudo Dice: 0.78 +2024-11-21 10:49:57.750156: +2024-11-21 10:49:57.750355: Epoch 24 +2024-11-21 10:49:57.750472: Current learning rate: 0.00997 +2024-11-21 10:50:16.779380: train_loss -0.709 +2024-11-21 10:50:16.784945: val_loss -0.7094 +2024-11-21 10:50:16.785085: Pseudo dice [0.8111] +2024-11-21 10:50:16.785186: Epoch time: 19.03 s +2024-11-21 10:50:16.785256: Yayy! New best EMA pseudo Dice: 0.7831 +2024-11-21 10:50:17.938660: +2024-11-21 10:50:17.938850: Epoch 25 +2024-11-21 10:50:17.938971: Current learning rate: 0.00997 +2024-11-21 10:50:37.668035: train_loss -0.7028 +2024-11-21 10:50:37.675191: val_loss -0.7507 +2024-11-21 10:50:37.675301: Pseudo dice [0.8312] +2024-11-21 10:50:37.675385: Epoch time: 19.73 s +2024-11-21 10:50:37.675451: Yayy! New best EMA pseudo Dice: 0.7879 +2024-11-21 10:50:38.752874: +2024-11-21 10:50:38.753073: Epoch 26 +2024-11-21 10:50:38.753191: Current learning rate: 0.00997 +2024-11-21 10:50:57.650103: train_loss -0.6954 +2024-11-21 10:50:57.657196: val_loss -0.742 +2024-11-21 10:50:57.657378: Pseudo dice [0.8176] +2024-11-21 10:50:57.657461: Epoch time: 18.9 s +2024-11-21 10:50:57.657526: Yayy! New best EMA pseudo Dice: 0.7909 +2024-11-21 10:50:58.646260: +2024-11-21 10:50:58.646435: Epoch 27 +2024-11-21 10:50:58.646548: Current learning rate: 0.00997 +2024-11-21 10:51:17.763141: train_loss -0.714 +2024-11-21 10:51:17.770616: val_loss -0.7157 +2024-11-21 10:51:17.770749: Pseudo dice [0.8311] +2024-11-21 10:51:17.770839: Epoch time: 19.12 s +2024-11-21 10:51:17.770908: Yayy! New best EMA pseudo Dice: 0.7949 +2024-11-21 10:51:18.874463: +2024-11-21 10:51:18.874652: Epoch 28 +2024-11-21 10:51:18.874762: Current learning rate: 0.00997 +2024-11-21 10:51:36.442286: train_loss -0.7045 +2024-11-21 10:51:36.444229: val_loss -0.7166 +2024-11-21 10:51:36.444325: Pseudo dice [0.8296] +2024-11-21 10:51:36.444407: Epoch time: 17.57 s +2024-11-21 10:51:36.444471: Yayy! New best EMA pseudo Dice: 0.7984 +2024-11-21 10:51:37.423883: +2024-11-21 10:51:37.424101: Epoch 29 +2024-11-21 10:51:37.424219: Current learning rate: 0.00997 +2024-11-21 10:51:56.487245: train_loss -0.7004 +2024-11-21 10:51:56.492554: val_loss -0.7429 +2024-11-21 10:51:56.492764: Pseudo dice [0.8291] +2024-11-21 10:51:56.492844: Epoch time: 19.06 s +2024-11-21 10:51:56.492908: Yayy! New best EMA pseudo Dice: 0.8014 +2024-11-21 10:51:57.508957: +2024-11-21 10:51:57.509165: Epoch 30 +2024-11-21 10:51:57.509283: Current learning rate: 0.00997 +2024-11-21 10:52:16.445072: train_loss -0.7047 +2024-11-21 10:52:16.447132: val_loss -0.7252 +2024-11-21 10:52:16.447226: Pseudo dice [0.8127] +2024-11-21 10:52:16.447305: Epoch time: 18.94 s +2024-11-21 10:52:16.447368: Yayy! New best EMA pseudo Dice: 0.8026 +2024-11-21 10:52:17.424812: +2024-11-21 10:52:17.425025: Epoch 31 +2024-11-21 10:52:17.425141: Current learning rate: 0.00997 +2024-11-21 10:52:36.874726: train_loss -0.7129 +2024-11-21 10:52:36.876756: val_loss -0.7256 +2024-11-21 10:52:36.876845: Pseudo dice [0.8208] +2024-11-21 10:52:36.876928: Epoch time: 19.45 s +2024-11-21 10:52:36.877008: Yayy! New best EMA pseudo Dice: 0.8044 +2024-11-21 10:52:37.853938: +2024-11-21 10:52:37.854127: Epoch 32 +2024-11-21 10:52:37.854239: Current learning rate: 0.00996 +2024-11-21 10:52:55.809803: train_loss -0.7137 +2024-11-21 10:52:55.823050: val_loss -0.7094 +2024-11-21 10:52:55.823200: Pseudo dice [0.8226] +2024-11-21 10:52:55.823287: Epoch time: 17.96 s +2024-11-21 10:52:55.823356: Yayy! New best EMA pseudo Dice: 0.8062 +2024-11-21 10:52:56.839900: +2024-11-21 10:52:56.840086: Epoch 33 +2024-11-21 10:52:56.840200: Current learning rate: 0.00996 +2024-11-21 10:53:16.254549: train_loss -0.7111 +2024-11-21 10:53:16.257296: val_loss -0.7236 +2024-11-21 10:53:16.257443: Pseudo dice [0.8247] +2024-11-21 10:53:16.257534: Epoch time: 19.42 s +2024-11-21 10:53:16.257643: Yayy! New best EMA pseudo Dice: 0.8081 +2024-11-21 10:53:17.225679: +2024-11-21 10:53:17.225857: Epoch 34 +2024-11-21 10:53:17.225976: Current learning rate: 0.00996 +2024-11-21 10:53:36.905927: train_loss -0.7079 +2024-11-21 10:53:36.913814: val_loss -0.7005 +2024-11-21 10:53:36.913932: Pseudo dice [0.8031] +2024-11-21 10:53:36.914016: Epoch time: 19.68 s +2024-11-21 10:53:38.375005: +2024-11-21 10:53:38.375205: Epoch 35 +2024-11-21 10:53:38.375319: Current learning rate: 0.00996 +2024-11-21 10:53:55.935382: train_loss -0.7138 +2024-11-21 10:53:55.937869: val_loss -0.7257 +2024-11-21 10:53:55.937976: Pseudo dice [0.8247] +2024-11-21 10:53:55.938064: Epoch time: 17.56 s +2024-11-21 10:53:55.938132: Yayy! New best EMA pseudo Dice: 0.8093 +2024-11-21 10:53:57.131546: +2024-11-21 10:53:57.131765: Epoch 36 +2024-11-21 10:53:57.131883: Current learning rate: 0.00996 +2024-11-21 10:54:15.893943: train_loss -0.714 +2024-11-21 10:54:15.900036: val_loss -0.7413 +2024-11-21 10:54:15.900172: Pseudo dice [0.8316] +2024-11-21 10:54:15.900255: Epoch time: 18.76 s +2024-11-21 10:54:15.900319: Yayy! New best EMA pseudo Dice: 0.8115 +2024-11-21 10:54:16.971455: +2024-11-21 10:54:16.971641: Epoch 37 +2024-11-21 10:54:16.971756: Current learning rate: 0.00996 +2024-11-21 10:54:35.356091: train_loss -0.7173 +2024-11-21 10:54:35.357877: val_loss -0.7328 +2024-11-21 10:54:35.357978: Pseudo dice [0.8326] +2024-11-21 10:54:35.358055: Epoch time: 18.39 s +2024-11-21 10:54:35.358124: Yayy! New best EMA pseudo Dice: 0.8136 +2024-11-21 10:54:36.359404: +2024-11-21 10:54:36.359590: Epoch 38 +2024-11-21 10:54:36.359704: Current learning rate: 0.00996 +2024-11-21 10:54:55.425312: train_loss -0.7167 +2024-11-21 10:54:55.428485: val_loss -0.7431 +2024-11-21 10:54:55.428601: Pseudo dice [0.8219] +2024-11-21 10:54:55.428688: Epoch time: 19.07 s +2024-11-21 10:54:55.428753: Yayy! New best EMA pseudo Dice: 0.8144 +2024-11-21 10:54:56.419503: +2024-11-21 10:54:56.419745: Epoch 39 +2024-11-21 10:54:56.419858: Current learning rate: 0.00996 +2024-11-21 10:55:14.812416: train_loss -0.7062 +2024-11-21 10:55:14.826065: val_loss -0.7168 +2024-11-21 10:55:14.826205: Pseudo dice [0.8342] +2024-11-21 10:55:14.826287: Epoch time: 18.39 s +2024-11-21 10:55:14.826355: Yayy! New best EMA pseudo Dice: 0.8164 +2024-11-21 10:55:15.834007: +2024-11-21 10:55:15.834243: Epoch 40 +2024-11-21 10:55:15.834361: Current learning rate: 0.00995 +2024-11-21 10:55:36.022810: train_loss -0.7006 +2024-11-21 10:55:36.024845: val_loss -0.6994 +2024-11-21 10:55:36.024978: Pseudo dice [0.8078] +2024-11-21 10:55:36.025067: Epoch time: 20.19 s +2024-11-21 10:55:36.815150: +2024-11-21 10:55:36.815344: Epoch 41 +2024-11-21 10:55:36.815456: Current learning rate: 0.00995 +2024-11-21 10:55:55.295791: train_loss -0.7218 +2024-11-21 10:55:55.302312: val_loss -0.7393 +2024-11-21 10:55:55.302422: Pseudo dice [0.8404] +2024-11-21 10:55:55.302499: Epoch time: 18.48 s +2024-11-21 10:55:55.302561: Yayy! New best EMA pseudo Dice: 0.8181 +2024-11-21 10:55:56.289744: +2024-11-21 10:55:56.289929: Epoch 42 +2024-11-21 10:55:56.290040: Current learning rate: 0.00995 +2024-11-21 10:56:14.509166: train_loss -0.7168 +2024-11-21 10:56:14.516278: val_loss -0.7253 +2024-11-21 10:56:14.516388: Pseudo dice [0.8177] +2024-11-21 10:56:14.516475: Epoch time: 18.22 s +2024-11-21 10:56:15.277400: +2024-11-21 10:56:15.277621: Epoch 43 +2024-11-21 10:56:15.277734: Current learning rate: 0.00995 +2024-11-21 10:56:34.731582: train_loss -0.7309 +2024-11-21 10:56:34.736529: val_loss -0.7281 +2024-11-21 10:56:34.736728: Pseudo dice [0.8241] +2024-11-21 10:56:34.736811: Epoch time: 19.46 s +2024-11-21 10:56:34.736879: Yayy! New best EMA pseudo Dice: 0.8186 +2024-11-21 10:56:35.702581: +2024-11-21 10:56:35.702773: Epoch 44 +2024-11-21 10:56:35.702888: Current learning rate: 0.00995 +2024-11-21 10:56:54.572015: train_loss -0.7368 +2024-11-21 10:56:54.585380: val_loss -0.734 +2024-11-21 10:56:54.585524: Pseudo dice [0.8275] +2024-11-21 10:56:54.585604: Epoch time: 18.87 s +2024-11-21 10:56:54.585667: Yayy! New best EMA pseudo Dice: 0.8195 +2024-11-21 10:56:55.659299: +2024-11-21 10:56:55.659462: Epoch 45 +2024-11-21 10:56:55.659574: Current learning rate: 0.00995 +2024-11-21 10:57:14.951786: train_loss -0.7158 +2024-11-21 10:57:14.954564: val_loss -0.7187 +2024-11-21 10:57:14.954691: Pseudo dice [0.8217] +2024-11-21 10:57:14.954772: Epoch time: 19.29 s +2024-11-21 10:57:14.954836: Yayy! New best EMA pseudo Dice: 0.8197 +2024-11-21 10:57:15.976507: +2024-11-21 10:57:15.976692: Epoch 46 +2024-11-21 10:57:15.976853: Current learning rate: 0.00995 +2024-11-21 10:57:34.414693: train_loss -0.7229 +2024-11-21 10:57:34.422390: val_loss -0.7 +2024-11-21 10:57:34.422500: Pseudo dice [0.8287] +2024-11-21 10:57:34.422579: Epoch time: 18.44 s +2024-11-21 10:57:34.422648: Yayy! New best EMA pseudo Dice: 0.8206 +2024-11-21 10:57:35.459696: +2024-11-21 10:57:35.459898: Epoch 47 +2024-11-21 10:57:35.460010: Current learning rate: 0.00995 +2024-11-21 10:57:54.617112: train_loss -0.716 +2024-11-21 10:57:54.622670: val_loss -0.7215 +2024-11-21 10:57:54.622803: Pseudo dice [0.826] +2024-11-21 10:57:54.622888: Epoch time: 19.16 s +2024-11-21 10:57:54.622958: Yayy! New best EMA pseudo Dice: 0.8212 +2024-11-21 10:57:55.591141: +2024-11-21 10:57:55.591356: Epoch 48 +2024-11-21 10:57:55.591474: Current learning rate: 0.00995 +2024-11-21 10:58:13.985447: train_loss -0.7096 +2024-11-21 10:58:13.996166: val_loss -0.7344 +2024-11-21 10:58:13.996314: Pseudo dice [0.8313] +2024-11-21 10:58:13.996397: Epoch time: 18.4 s +2024-11-21 10:58:13.996464: Yayy! New best EMA pseudo Dice: 0.8222 +2024-11-21 10:58:15.081680: +2024-11-21 10:58:15.081939: Epoch 49 +2024-11-21 10:58:15.082097: Current learning rate: 0.00994 +2024-11-21 10:58:33.605130: train_loss -0.7173 +2024-11-21 10:58:33.611892: val_loss -0.7264 +2024-11-21 10:58:33.612056: Pseudo dice [0.82] +2024-11-21 10:58:33.612160: Epoch time: 18.52 s +2024-11-21 10:58:34.639450: +2024-11-21 10:58:34.639644: Epoch 50 +2024-11-21 10:58:34.639755: Current learning rate: 0.00994 +2024-11-21 10:58:53.319479: train_loss -0.7075 +2024-11-21 10:58:53.326419: val_loss -0.7386 +2024-11-21 10:58:53.326531: Pseudo dice [0.8133] +2024-11-21 10:58:53.326615: Epoch time: 18.68 s +2024-11-21 10:58:54.302680: +2024-11-21 10:58:54.302862: Epoch 51 +2024-11-21 10:58:54.302977: Current learning rate: 0.00994 +2024-11-21 10:59:13.211870: train_loss -0.7328 +2024-11-21 10:59:13.219484: val_loss -0.7351 +2024-11-21 10:59:13.219609: Pseudo dice [0.8138] +2024-11-21 10:59:13.219685: Epoch time: 18.91 s +2024-11-21 10:59:14.141070: +2024-11-21 10:59:14.141248: Epoch 52 +2024-11-21 10:59:14.141354: Current learning rate: 0.00994 +2024-11-21 10:59:33.130362: train_loss -0.7233 +2024-11-21 10:59:33.136346: val_loss -0.7415 +2024-11-21 10:59:33.136477: Pseudo dice [0.8338] +2024-11-21 10:59:33.136564: Epoch time: 18.99 s +2024-11-21 10:59:34.007352: +2024-11-21 10:59:34.007543: Epoch 53 +2024-11-21 10:59:34.007654: Current learning rate: 0.00994 +2024-11-21 10:59:54.034500: train_loss -0.7077 +2024-11-21 10:59:54.036423: val_loss -0.7302 +2024-11-21 10:59:54.036529: Pseudo dice [0.8189] +2024-11-21 10:59:54.036613: Epoch time: 20.03 s +2024-11-21 10:59:54.858710: +2024-11-21 10:59:54.858889: Epoch 54 +2024-11-21 10:59:54.858999: Current learning rate: 0.00994 +2024-11-21 11:00:14.506871: train_loss -0.7083 +2024-11-21 11:00:14.509282: val_loss -0.7153 +2024-11-21 11:00:14.509395: Pseudo dice [0.8313] +2024-11-21 11:00:14.509474: Epoch time: 19.65 s +2024-11-21 11:00:14.509536: Yayy! New best EMA pseudo Dice: 0.8224 +2024-11-21 11:00:15.490593: +2024-11-21 11:00:15.490768: Epoch 55 +2024-11-21 11:00:15.490891: Current learning rate: 0.00994 +2024-11-21 11:00:34.949795: train_loss -0.7251 +2024-11-21 11:00:34.957352: val_loss -0.7267 +2024-11-21 11:00:34.957523: Pseudo dice [0.8255] +2024-11-21 11:00:34.957633: Epoch time: 19.46 s +2024-11-21 11:00:34.957959: Yayy! New best EMA pseudo Dice: 0.8227 +2024-11-21 11:00:35.972903: +2024-11-21 11:00:35.973135: Epoch 56 +2024-11-21 11:00:35.973259: Current learning rate: 0.00994 +2024-11-21 11:00:55.070155: train_loss -0.7218 +2024-11-21 11:00:55.076909: val_loss -0.7251 +2024-11-21 11:00:55.077038: Pseudo dice [0.8357] +2024-11-21 11:00:55.077129: Epoch time: 19.1 s +2024-11-21 11:00:55.077193: Yayy! New best EMA pseudo Dice: 0.824 +2024-11-21 11:00:56.132910: +2024-11-21 11:00:56.133106: Epoch 57 +2024-11-21 11:00:56.133222: Current learning rate: 0.00994 +2024-11-21 11:01:14.494495: train_loss -0.7322 +2024-11-21 11:01:14.496108: val_loss -0.7429 +2024-11-21 11:01:14.496212: Pseudo dice [0.8328] +2024-11-21 11:01:14.496305: Epoch time: 18.36 s +2024-11-21 11:01:14.496389: Yayy! New best EMA pseudo Dice: 0.8249 +2024-11-21 11:01:15.484288: +2024-11-21 11:01:15.484481: Epoch 58 +2024-11-21 11:01:15.484605: Current learning rate: 0.00993 +2024-11-21 11:01:35.655868: train_loss -0.7324 +2024-11-21 11:01:35.669974: val_loss -0.7364 +2024-11-21 11:01:35.670144: Pseudo dice [0.829] +2024-11-21 11:01:35.670240: Epoch time: 20.17 s +2024-11-21 11:01:35.670320: Yayy! New best EMA pseudo Dice: 0.8253 +2024-11-21 11:01:36.918477: +2024-11-21 11:01:36.918662: Epoch 59 +2024-11-21 11:01:36.918780: Current learning rate: 0.00993 +2024-11-21 11:01:57.102008: train_loss -0.7305 +2024-11-21 11:01:57.105691: val_loss -0.7406 +2024-11-21 11:01:57.105860: Pseudo dice [0.8299] +2024-11-21 11:01:57.105959: Epoch time: 20.18 s +2024-11-21 11:01:57.106034: Yayy! New best EMA pseudo Dice: 0.8258 +2024-11-21 11:01:58.148730: +2024-11-21 11:01:58.148919: Epoch 60 +2024-11-21 11:01:58.149048: Current learning rate: 0.00993 +2024-11-21 11:02:16.351119: train_loss -0.7249 +2024-11-21 11:02:16.352989: val_loss -0.7107 +2024-11-21 11:02:16.353088: Pseudo dice [0.7875] +2024-11-21 11:02:16.353177: Epoch time: 18.2 s +2024-11-21 11:02:17.138557: +2024-11-21 11:02:17.138767: Epoch 61 +2024-11-21 11:02:17.138884: Current learning rate: 0.00993 +2024-11-21 11:02:36.993407: train_loss -0.7132 +2024-11-21 11:02:36.999093: val_loss -0.7391 +2024-11-21 11:02:36.999249: Pseudo dice [0.822] +2024-11-21 11:02:36.999329: Epoch time: 19.86 s +2024-11-21 11:02:37.864069: +2024-11-21 11:02:37.864258: Epoch 62 +2024-11-21 11:02:37.864390: Current learning rate: 0.00993 +2024-11-21 11:02:56.273883: train_loss -0.7117 +2024-11-21 11:02:56.278686: val_loss -0.7431 +2024-11-21 11:02:56.278824: Pseudo dice [0.8283] +2024-11-21 11:02:56.278920: Epoch time: 18.41 s +2024-11-21 11:02:57.101232: +2024-11-21 11:02:57.101429: Epoch 63 +2024-11-21 11:02:57.101554: Current learning rate: 0.00993 +2024-11-21 11:03:16.522216: train_loss -0.7196 +2024-11-21 11:03:16.524070: val_loss -0.7362 +2024-11-21 11:03:16.524184: Pseudo dice [0.8374] +2024-11-21 11:03:16.524277: Epoch time: 19.42 s +2024-11-21 11:03:17.309746: +2024-11-21 11:03:17.309917: Epoch 64 +2024-11-21 11:03:17.310045: Current learning rate: 0.00993 +2024-11-21 11:03:36.356870: train_loss -0.7211 +2024-11-21 11:03:36.363788: val_loss -0.757 +2024-11-21 11:03:36.363905: Pseudo dice [0.8438] +2024-11-21 11:03:36.363982: Epoch time: 19.05 s +2024-11-21 11:03:36.364043: Yayy! New best EMA pseudo Dice: 0.826 +2024-11-21 11:03:37.381347: +2024-11-21 11:03:37.381551: Epoch 65 +2024-11-21 11:03:37.381674: Current learning rate: 0.00993 +2024-11-21 11:03:57.152932: train_loss -0.7262 +2024-11-21 11:03:57.155304: val_loss -0.7577 +2024-11-21 11:03:57.155396: Pseudo dice [0.8347] +2024-11-21 11:03:57.155473: Epoch time: 19.77 s +2024-11-21 11:03:57.155535: Yayy! New best EMA pseudo Dice: 0.8269 +2024-11-21 11:03:58.144239: +2024-11-21 11:03:58.144451: Epoch 66 +2024-11-21 11:03:58.144585: Current learning rate: 0.00993 +2024-11-21 11:04:16.694455: train_loss -0.7254 +2024-11-21 11:04:16.699979: val_loss -0.7574 +2024-11-21 11:04:16.700108: Pseudo dice [0.8383] +2024-11-21 11:04:16.700210: Epoch time: 18.55 s +2024-11-21 11:04:16.700288: Yayy! New best EMA pseudo Dice: 0.8281 +2024-11-21 11:04:17.785900: +2024-11-21 11:04:17.812529: Epoch 67 +2024-11-21 11:04:17.812680: Current learning rate: 0.00992 +2024-11-21 11:04:36.411211: train_loss -0.7382 +2024-11-21 11:04:36.413891: val_loss -0.7285 +2024-11-21 11:04:36.414027: Pseudo dice [0.8351] +2024-11-21 11:04:36.414140: Epoch time: 18.63 s +2024-11-21 11:04:36.414213: Yayy! New best EMA pseudo Dice: 0.8288 +2024-11-21 11:04:37.936972: +2024-11-21 11:04:37.937186: Epoch 68 +2024-11-21 11:04:37.937313: Current learning rate: 0.00992 +2024-11-21 11:04:56.645507: train_loss -0.7348 +2024-11-21 11:04:56.647725: val_loss -0.7469 +2024-11-21 11:04:56.647851: Pseudo dice [0.8449] +2024-11-21 11:04:56.647934: Epoch time: 18.71 s +2024-11-21 11:04:56.648012: Yayy! New best EMA pseudo Dice: 0.8304 +2024-11-21 11:04:57.685070: +2024-11-21 11:04:57.685306: Epoch 69 +2024-11-21 11:04:57.685435: Current learning rate: 0.00992 +2024-11-21 11:05:16.561687: train_loss -0.7274 +2024-11-21 11:05:16.563443: val_loss -0.709 +2024-11-21 11:05:16.563583: Pseudo dice [0.8232] +2024-11-21 11:05:16.563674: Epoch time: 18.88 s +2024-11-21 11:05:17.529670: +2024-11-21 11:05:17.529907: Epoch 70 +2024-11-21 11:05:17.530041: Current learning rate: 0.00992 +2024-11-21 11:05:37.353092: train_loss -0.7162 +2024-11-21 11:05:37.362134: val_loss -0.7401 +2024-11-21 11:05:37.362285: Pseudo dice [0.823] +2024-11-21 11:05:37.362391: Epoch time: 19.82 s +2024-11-21 11:05:38.277188: +2024-11-21 11:05:38.277414: Epoch 71 +2024-11-21 11:05:38.277544: Current learning rate: 0.00992 +2024-11-21 11:05:57.157303: train_loss -0.7288 +2024-11-21 11:05:57.159676: val_loss -0.7714 +2024-11-21 11:05:57.159801: Pseudo dice [0.8371] +2024-11-21 11:05:57.159890: Epoch time: 18.88 s +2024-11-21 11:05:57.957194: +2024-11-21 11:05:57.957394: Epoch 72 +2024-11-21 11:05:57.957519: Current learning rate: 0.00992 +2024-11-21 11:06:17.075327: train_loss -0.7283 +2024-11-21 11:06:17.077309: val_loss -0.7284 +2024-11-21 11:06:17.077416: Pseudo dice [0.8267] +2024-11-21 11:06:17.077513: Epoch time: 19.12 s +2024-11-21 11:06:17.866997: +2024-11-21 11:06:17.867191: Epoch 73 +2024-11-21 11:06:17.867311: Current learning rate: 0.00992 +2024-11-21 11:06:37.555376: train_loss -0.7263 +2024-11-21 11:06:37.560986: val_loss -0.7529 +2024-11-21 11:06:37.561110: Pseudo dice [0.8189] +2024-11-21 11:06:37.561215: Epoch time: 19.69 s +2024-11-21 11:06:38.431649: +2024-11-21 11:06:38.431836: Epoch 74 +2024-11-21 11:06:38.431967: Current learning rate: 0.00992 +2024-11-21 11:06:57.585338: train_loss -0.7293 +2024-11-21 11:06:57.587681: val_loss -0.7338 +2024-11-21 11:06:57.587821: Pseudo dice [0.8272] +2024-11-21 11:06:57.587915: Epoch time: 19.15 s +2024-11-21 11:06:58.506542: +2024-11-21 11:06:58.506752: Epoch 75 +2024-11-21 11:06:58.506908: Current learning rate: 0.00992 +2024-11-21 11:07:18.446519: train_loss -0.729 +2024-11-21 11:07:18.451633: val_loss -0.7541 +2024-11-21 11:07:18.451773: Pseudo dice [0.829] +2024-11-21 11:07:18.451874: Epoch time: 19.94 s +2024-11-21 11:07:19.243066: +2024-11-21 11:07:19.243249: Epoch 76 +2024-11-21 11:07:19.243378: Current learning rate: 0.00991 +2024-11-21 11:07:38.262249: train_loss -0.7332 +2024-11-21 11:07:38.273391: val_loss -0.751 +2024-11-21 11:07:38.273654: Pseudo dice [0.8449] +2024-11-21 11:07:38.273763: Epoch time: 19.02 s +2024-11-21 11:07:39.126834: +2024-11-21 11:07:39.127035: Epoch 77 +2024-11-21 11:07:39.127182: Current learning rate: 0.00991 +2024-11-21 11:07:58.509911: train_loss -0.7372 +2024-11-21 11:07:58.513057: val_loss -0.7612 +2024-11-21 11:07:58.513192: Pseudo dice [0.8309] +2024-11-21 11:07:58.513281: Epoch time: 19.38 s +2024-11-21 11:07:59.334676: +2024-11-21 11:07:59.334908: Epoch 78 +2024-11-21 11:07:59.335063: Current learning rate: 0.00991 +2024-11-21 11:08:19.077747: train_loss -0.7337 +2024-11-21 11:08:19.083105: val_loss -0.723 +2024-11-21 11:08:19.083233: Pseudo dice [0.8095] +2024-11-21 11:08:19.083325: Epoch time: 19.74 s +2024-11-21 11:08:20.367900: +2024-11-21 11:08:20.368121: Epoch 79 +2024-11-21 11:08:20.368252: Current learning rate: 0.00991 +2024-11-21 11:08:38.486188: train_loss -0.728 +2024-11-21 11:08:38.492632: val_loss -0.7378 +2024-11-21 11:08:38.492788: Pseudo dice [0.8382] +2024-11-21 11:08:38.492877: Epoch time: 18.12 s +2024-11-21 11:08:39.478763: +2024-11-21 11:08:39.478997: Epoch 80 +2024-11-21 11:08:39.479134: Current learning rate: 0.00991 +2024-11-21 11:08:58.224215: train_loss -0.7278 +2024-11-21 11:08:58.229634: val_loss -0.7455 +2024-11-21 11:08:58.229773: Pseudo dice [0.8425] +2024-11-21 11:08:58.229872: Epoch time: 18.75 s +2024-11-21 11:08:58.229943: Yayy! New best EMA pseudo Dice: 0.8304 +2024-11-21 11:08:59.270288: +2024-11-21 11:08:59.270468: Epoch 81 +2024-11-21 11:08:59.270595: Current learning rate: 0.00991 +2024-11-21 11:09:17.399602: train_loss -0.7265 +2024-11-21 11:09:17.406825: val_loss -0.7455 +2024-11-21 11:09:17.406941: Pseudo dice [0.8221] +2024-11-21 11:09:17.407028: Epoch time: 18.13 s +2024-11-21 11:09:18.241348: +2024-11-21 11:09:18.241567: Epoch 82 +2024-11-21 11:09:18.241714: Current learning rate: 0.00991 +2024-11-21 11:09:37.104213: train_loss -0.734 +2024-11-21 11:09:37.118263: val_loss -0.7414 +2024-11-21 11:09:37.118428: Pseudo dice [0.8246] +2024-11-21 11:09:37.118544: Epoch time: 18.86 s +2024-11-21 11:09:37.988859: +2024-11-21 11:09:37.989033: Epoch 83 +2024-11-21 11:09:37.989165: Current learning rate: 0.00991 +2024-11-21 11:09:57.925008: train_loss -0.7318 +2024-11-21 11:09:57.927319: val_loss -0.757 +2024-11-21 11:09:57.927455: Pseudo dice [0.8445] +2024-11-21 11:09:57.927538: Epoch time: 19.94 s +2024-11-21 11:09:57.927610: Yayy! New best EMA pseudo Dice: 0.8306 +2024-11-21 11:09:58.926672: +2024-11-21 11:09:58.926863: Epoch 84 +2024-11-21 11:09:58.926984: Current learning rate: 0.00991 +2024-11-21 11:10:18.329846: train_loss -0.7345 +2024-11-21 11:10:18.334709: val_loss -0.7284 +2024-11-21 11:10:18.334880: Pseudo dice [0.8335] +2024-11-21 11:10:18.334984: Epoch time: 19.4 s +2024-11-21 11:10:18.335068: Yayy! New best EMA pseudo Dice: 0.8309 +2024-11-21 11:10:19.349975: +2024-11-21 11:10:19.350168: Epoch 85 +2024-11-21 11:10:19.350302: Current learning rate: 0.0099 +2024-11-21 11:10:38.798083: train_loss -0.7281 +2024-11-21 11:10:38.804152: val_loss -0.7202 +2024-11-21 11:10:38.804286: Pseudo dice [0.8286] +2024-11-21 11:10:38.804377: Epoch time: 19.45 s +2024-11-21 11:10:39.582164: +2024-11-21 11:10:39.582345: Epoch 86 +2024-11-21 11:10:39.582469: Current learning rate: 0.0099 +2024-11-21 11:10:58.960223: train_loss -0.7303 +2024-11-21 11:10:58.967559: val_loss -0.7494 +2024-11-21 11:10:58.967700: Pseudo dice [0.8479] +2024-11-21 11:10:58.967802: Epoch time: 19.38 s +2024-11-21 11:10:58.967871: Yayy! New best EMA pseudo Dice: 0.8324 +2024-11-21 11:11:00.119179: +2024-11-21 11:11:00.119383: Epoch 87 +2024-11-21 11:11:00.119510: Current learning rate: 0.0099 +2024-11-21 11:11:19.448948: train_loss -0.7246 +2024-11-21 11:11:19.452985: val_loss -0.7312 +2024-11-21 11:11:19.453115: Pseudo dice [0.8167] +2024-11-21 11:11:19.453207: Epoch time: 19.33 s +2024-11-21 11:11:20.222475: +2024-11-21 11:11:20.222644: Epoch 88 +2024-11-21 11:11:20.222759: Current learning rate: 0.0099 +2024-11-21 11:11:38.155135: train_loss -0.7269 +2024-11-21 11:11:38.164341: val_loss -0.7516 +2024-11-21 11:11:38.164496: Pseudo dice [0.8363] +2024-11-21 11:11:38.164608: Epoch time: 17.93 s +2024-11-21 11:11:39.049791: +2024-11-21 11:11:39.049995: Epoch 89 +2024-11-21 11:11:39.050135: Current learning rate: 0.0099 +2024-11-21 11:11:57.880815: train_loss -0.7237 +2024-11-21 11:11:57.896671: val_loss -0.744 +2024-11-21 11:11:57.896796: Pseudo dice [0.8312] +2024-11-21 11:11:57.896903: Epoch time: 18.83 s +2024-11-21 11:11:58.677860: +2024-11-21 11:11:58.678056: Epoch 90 +2024-11-21 11:11:58.678199: Current learning rate: 0.0099 +2024-11-21 11:12:17.298354: train_loss -0.7343 +2024-11-21 11:12:17.321616: val_loss -0.7629 +2024-11-21 11:12:17.321793: Pseudo dice [0.8442] +2024-11-21 11:12:17.321904: Epoch time: 18.62 s +2024-11-21 11:12:17.322522: Yayy! New best EMA pseudo Dice: 0.8326 +2024-11-21 11:12:18.347209: +2024-11-21 11:12:18.347419: Epoch 91 +2024-11-21 11:12:18.347819: Current learning rate: 0.0099 +2024-11-21 11:12:37.944330: train_loss -0.7307 +2024-11-21 11:12:37.956398: val_loss -0.7575 +2024-11-21 11:12:37.956541: Pseudo dice [0.8264] +2024-11-21 11:12:37.956669: Epoch time: 19.6 s +2024-11-21 11:12:38.951145: +2024-11-21 11:12:38.951387: Epoch 92 +2024-11-21 11:12:38.951522: Current learning rate: 0.0099 +2024-11-21 11:12:58.305809: train_loss -0.7352 +2024-11-21 11:12:58.312812: val_loss -0.7139 +2024-11-21 11:12:58.313028: Pseudo dice [0.8284] +2024-11-21 11:12:58.313141: Epoch time: 19.36 s +2024-11-21 11:12:59.093009: +2024-11-21 11:12:59.093207: Epoch 93 +2024-11-21 11:12:59.093329: Current learning rate: 0.0099 +2024-11-21 11:13:18.157843: train_loss -0.7442 +2024-11-21 11:13:18.163393: val_loss -0.74 +2024-11-21 11:13:18.163515: Pseudo dice [0.8457] +2024-11-21 11:13:18.163609: Epoch time: 19.07 s +2024-11-21 11:13:18.163690: Yayy! New best EMA pseudo Dice: 0.8331 +2024-11-21 11:13:19.386344: +2024-11-21 11:13:19.386562: Epoch 94 +2024-11-21 11:13:19.386696: Current learning rate: 0.00989 +2024-11-21 11:13:37.950485: train_loss -0.7347 +2024-11-21 11:13:37.963117: val_loss -0.7569 +2024-11-21 11:13:37.963266: Pseudo dice [0.8362] +2024-11-21 11:13:37.963355: Epoch time: 18.56 s +2024-11-21 11:13:37.963428: Yayy! New best EMA pseudo Dice: 0.8334 +2024-11-21 11:13:39.129843: +2024-11-21 11:13:39.130038: Epoch 95 +2024-11-21 11:13:39.130171: Current learning rate: 0.00989 +2024-11-21 11:13:58.570438: train_loss -0.7342 +2024-11-21 11:13:58.577982: val_loss -0.7305 +2024-11-21 11:13:58.578132: Pseudo dice [0.8425] +2024-11-21 11:13:58.578218: Epoch time: 19.44 s +2024-11-21 11:13:58.578289: Yayy! New best EMA pseudo Dice: 0.8343 +2024-11-21 11:13:59.577267: +2024-11-21 11:13:59.577464: Epoch 96 +2024-11-21 11:13:59.577582: Current learning rate: 0.00989 +2024-11-21 11:14:17.992886: train_loss -0.7371 +2024-11-21 11:14:17.997738: val_loss -0.746 +2024-11-21 11:14:17.997868: Pseudo dice [0.8354] +2024-11-21 11:14:17.997961: Epoch time: 18.42 s +2024-11-21 11:14:17.998034: Yayy! New best EMA pseudo Dice: 0.8344 +2024-11-21 11:14:19.064499: +2024-11-21 11:14:19.064718: Epoch 97 +2024-11-21 11:14:19.064855: Current learning rate: 0.00989 +2024-11-21 11:14:38.382552: train_loss -0.7387 +2024-11-21 11:14:38.385370: val_loss -0.7446 +2024-11-21 11:14:38.385471: Pseudo dice [0.8274] +2024-11-21 11:14:38.385563: Epoch time: 19.32 s +2024-11-21 11:14:39.149336: +2024-11-21 11:14:39.149513: Epoch 98 +2024-11-21 11:14:39.149635: Current learning rate: 0.00989 +2024-11-21 11:14:57.652794: train_loss -0.7189 +2024-11-21 11:14:57.660195: val_loss -0.7401 +2024-11-21 11:14:57.660342: Pseudo dice [0.8266] +2024-11-21 11:14:57.660427: Epoch time: 18.5 s +2024-11-21 11:14:58.529045: +2024-11-21 11:14:58.529258: Epoch 99 +2024-11-21 11:14:58.529387: Current learning rate: 0.00989 +2024-11-21 11:15:17.935570: train_loss -0.7263 +2024-11-21 11:15:17.945925: val_loss -0.7319 +2024-11-21 11:15:17.946090: Pseudo dice [0.8312] +2024-11-21 11:15:17.946197: Epoch time: 19.41 s +2024-11-21 11:15:18.969009: +2024-11-21 11:15:18.969239: Epoch 100 +2024-11-21 11:15:18.969360: Current learning rate: 0.00989 +2024-11-21 11:15:38.075511: train_loss -0.7328 +2024-11-21 11:15:38.084817: val_loss -0.7429 +2024-11-21 11:15:38.089664: Pseudo dice [0.8284] +2024-11-21 11:15:38.089814: Epoch time: 19.11 s +2024-11-21 11:15:38.977871: +2024-11-21 11:15:38.978081: Epoch 101 +2024-11-21 11:15:38.978202: Current learning rate: 0.00989 +2024-11-21 11:15:59.382040: train_loss -0.7216 +2024-11-21 11:15:59.385345: val_loss -0.7415 +2024-11-21 11:15:59.385460: Pseudo dice [0.8475] +2024-11-21 11:15:59.385549: Epoch time: 20.4 s +2024-11-21 11:16:00.585170: +2024-11-21 11:16:00.585365: Epoch 102 +2024-11-21 11:16:00.585484: Current learning rate: 0.00989 +2024-11-21 11:16:18.941066: train_loss -0.7221 +2024-11-21 11:16:18.944860: val_loss -0.7076 +2024-11-21 11:16:18.945000: Pseudo dice [0.8249] +2024-11-21 11:16:18.945089: Epoch time: 18.36 s +2024-11-21 11:16:19.880322: +2024-11-21 11:16:19.880752: Epoch 103 +2024-11-21 11:16:19.880878: Current learning rate: 0.00988 +2024-11-21 11:16:39.902656: train_loss -0.7182 +2024-11-21 11:16:39.911552: val_loss -0.7484 +2024-11-21 11:16:39.911679: Pseudo dice [0.8381] +2024-11-21 11:16:39.911771: Epoch time: 20.02 s +2024-11-21 11:16:40.763659: +2024-11-21 11:16:40.763858: Epoch 104 +2024-11-21 11:16:40.763980: Current learning rate: 0.00988 +2024-11-21 11:16:59.292025: train_loss -0.7345 +2024-11-21 11:16:59.302701: val_loss -0.748 +2024-11-21 11:16:59.302851: Pseudo dice [0.8235] +2024-11-21 11:16:59.302949: Epoch time: 18.53 s +2024-11-21 11:17:00.206874: +2024-11-21 11:17:00.207065: Epoch 105 +2024-11-21 11:17:00.207203: Current learning rate: 0.00988 +2024-11-21 11:17:18.644684: train_loss -0.7307 +2024-11-21 11:17:18.654068: val_loss -0.7323 +2024-11-21 11:17:18.654220: Pseudo dice [0.8458] +2024-11-21 11:17:18.654312: Epoch time: 18.44 s +2024-11-21 11:17:19.435137: +2024-11-21 11:17:19.435331: Epoch 106 +2024-11-21 11:17:19.435441: Current learning rate: 0.00988 +2024-11-21 11:17:37.928206: train_loss -0.7295 +2024-11-21 11:17:37.935592: val_loss -0.7204 +2024-11-21 11:17:37.935717: Pseudo dice [0.8166] +2024-11-21 11:17:37.935823: Epoch time: 18.49 s +2024-11-21 11:17:38.720722: +2024-11-21 11:17:38.720932: Epoch 107 +2024-11-21 11:17:38.721051: Current learning rate: 0.00988 +2024-11-21 11:17:57.971703: train_loss -0.7363 +2024-11-21 11:17:57.974429: val_loss -0.7358 +2024-11-21 11:17:57.974537: Pseudo dice [0.825] +2024-11-21 11:17:57.974722: Epoch time: 19.25 s +2024-11-21 11:17:58.756414: +2024-11-21 11:17:58.756651: Epoch 108 +2024-11-21 11:17:58.756774: Current learning rate: 0.00988 +2024-11-21 11:18:17.846549: train_loss -0.7405 +2024-11-21 11:18:17.863349: val_loss -0.7589 +2024-11-21 11:18:17.863471: Pseudo dice [0.8311] +2024-11-21 11:18:17.863562: Epoch time: 19.09 s +2024-11-21 11:18:19.064473: +2024-11-21 11:18:19.064710: Epoch 109 +2024-11-21 11:18:19.064833: Current learning rate: 0.00988 +2024-11-21 11:18:38.083812: train_loss -0.744 +2024-11-21 11:18:38.086791: val_loss -0.7573 +2024-11-21 11:18:38.086931: Pseudo dice [0.8391] +2024-11-21 11:18:38.087023: Epoch time: 19.02 s +2024-11-21 11:18:38.962157: +2024-11-21 11:18:38.962376: Epoch 110 +2024-11-21 11:18:38.962512: Current learning rate: 0.00988 +2024-11-21 11:18:57.051686: train_loss -0.737 +2024-11-21 11:18:57.060963: val_loss -0.735 +2024-11-21 11:18:57.061096: Pseudo dice [0.8476] +2024-11-21 11:18:57.061184: Epoch time: 18.09 s +2024-11-21 11:18:58.052459: +2024-11-21 11:18:58.052647: Epoch 111 +2024-11-21 11:18:58.052767: Current learning rate: 0.00988 +2024-11-21 11:19:16.409043: train_loss -0.7287 +2024-11-21 11:19:16.414759: val_loss -0.7381 +2024-11-21 11:19:16.414905: Pseudo dice [0.8334] +2024-11-21 11:19:16.415009: Epoch time: 18.36 s +2024-11-21 11:19:17.191928: +2024-11-21 11:19:17.192156: Epoch 112 +2024-11-21 11:19:17.192291: Current learning rate: 0.00987 +2024-11-21 11:19:36.673980: train_loss -0.7299 +2024-11-21 11:19:36.679746: val_loss -0.7224 +2024-11-21 11:19:36.679896: Pseudo dice [0.8315] +2024-11-21 11:19:36.680015: Epoch time: 19.48 s +2024-11-21 11:19:37.471569: +2024-11-21 11:19:37.471777: Epoch 113 +2024-11-21 11:19:37.471920: Current learning rate: 0.00987 +2024-11-21 11:19:55.406788: train_loss -0.7343 +2024-11-21 11:19:55.419591: val_loss -0.7358 +2024-11-21 11:19:55.419817: Pseudo dice [0.823] +2024-11-21 11:19:55.419951: Epoch time: 17.94 s +2024-11-21 11:19:56.235388: +2024-11-21 11:19:56.235653: Epoch 114 +2024-11-21 11:19:56.235772: Current learning rate: 0.00987 +2024-11-21 11:20:15.089458: train_loss -0.7265 +2024-11-21 11:20:15.097708: val_loss -0.7275 +2024-11-21 11:20:15.097836: Pseudo dice [0.8308] +2024-11-21 11:20:15.097932: Epoch time: 18.86 s +2024-11-21 11:20:15.905293: +2024-11-21 11:20:15.905499: Epoch 115 +2024-11-21 11:20:15.905626: Current learning rate: 0.00987 +2024-11-21 11:20:35.006483: train_loss -0.7441 +2024-11-21 11:20:35.025858: val_loss -0.7426 +2024-11-21 11:20:35.026021: Pseudo dice [0.8463] +2024-11-21 11:20:35.026341: Epoch time: 19.1 s +2024-11-21 11:20:35.909452: +2024-11-21 11:20:35.909663: Epoch 116 +2024-11-21 11:20:35.909789: Current learning rate: 0.00987 +2024-11-21 11:20:54.968774: train_loss -0.7175 +2024-11-21 11:20:54.975952: val_loss -0.7471 +2024-11-21 11:20:54.976196: Pseudo dice [0.8356] +2024-11-21 11:20:54.976297: Epoch time: 19.06 s +2024-11-21 11:20:55.996036: +2024-11-21 11:20:55.996267: Epoch 117 +2024-11-21 11:20:55.996397: Current learning rate: 0.00987 +2024-11-21 11:21:14.150677: train_loss -0.7335 +2024-11-21 11:21:14.153615: val_loss -0.7321 +2024-11-21 11:21:14.153781: Pseudo dice [0.8293] +2024-11-21 11:21:14.153881: Epoch time: 18.16 s +2024-11-21 11:21:14.946847: +2024-11-21 11:21:14.947132: Epoch 118 +2024-11-21 11:21:14.947306: Current learning rate: 0.00987 +2024-11-21 11:21:33.986243: train_loss -0.742 +2024-11-21 11:21:33.992114: val_loss -0.7115 +2024-11-21 11:21:33.992270: Pseudo dice [0.8425] +2024-11-21 11:21:33.992380: Epoch time: 19.04 s +2024-11-21 11:21:34.816839: +2024-11-21 11:21:34.817019: Epoch 119 +2024-11-21 11:21:34.817181: Current learning rate: 0.00987 +2024-11-21 11:21:54.916706: train_loss -0.74 +2024-11-21 11:21:54.924109: val_loss -0.7586 +2024-11-21 11:21:54.924250: Pseudo dice [0.8248] +2024-11-21 11:21:54.924352: Epoch time: 20.1 s +2024-11-21 11:21:55.841297: +2024-11-21 11:21:55.841514: Epoch 120 +2024-11-21 11:21:55.841648: Current learning rate: 0.00986 +2024-11-21 11:22:15.781001: train_loss -0.7241 +2024-11-21 11:22:15.783375: val_loss -0.7667 +2024-11-21 11:22:15.783486: Pseudo dice [0.8376] +2024-11-21 11:22:15.783565: Epoch time: 19.94 s +2024-11-21 11:22:16.571780: +2024-11-21 11:22:16.571991: Epoch 121 +2024-11-21 11:22:16.572125: Current learning rate: 0.00986 +2024-11-21 11:22:34.472575: train_loss -0.7377 +2024-11-21 11:22:34.478670: val_loss -0.7438 +2024-11-21 11:22:34.478794: Pseudo dice [0.8306] +2024-11-21 11:22:34.478896: Epoch time: 17.9 s +2024-11-21 11:22:35.429710: +2024-11-21 11:22:35.429888: Epoch 122 +2024-11-21 11:22:35.430009: Current learning rate: 0.00986 +2024-11-21 11:22:53.471786: train_loss -0.7429 +2024-11-21 11:22:53.476109: val_loss -0.7469 +2024-11-21 11:22:53.476232: Pseudo dice [0.8456] +2024-11-21 11:22:53.476313: Epoch time: 18.04 s +2024-11-21 11:22:53.476387: Yayy! New best EMA pseudo Dice: 0.8347 +2024-11-21 11:22:54.517975: +2024-11-21 11:22:54.518185: Epoch 123 +2024-11-21 11:22:54.518317: Current learning rate: 0.00986 +2024-11-21 11:23:13.320606: train_loss -0.7401 +2024-11-21 11:23:13.335401: val_loss -0.7487 +2024-11-21 11:23:13.335535: Pseudo dice [0.8347] +2024-11-21 11:23:13.335644: Epoch time: 18.8 s +2024-11-21 11:23:13.335716: Yayy! New best EMA pseudo Dice: 0.8347 +2024-11-21 11:23:14.815361: +2024-11-21 11:23:14.815562: Epoch 124 +2024-11-21 11:23:14.815683: Current learning rate: 0.00986 +2024-11-21 11:23:33.795055: train_loss -0.7404 +2024-11-21 11:23:33.814744: val_loss -0.7616 +2024-11-21 11:23:33.814906: Pseudo dice [0.8367] +2024-11-21 11:23:33.815018: Epoch time: 18.98 s +2024-11-21 11:23:33.815101: Yayy! New best EMA pseudo Dice: 0.8349 +2024-11-21 11:23:34.933561: +2024-11-21 11:23:34.933763: Epoch 125 +2024-11-21 11:23:34.933892: Current learning rate: 0.00986 +2024-11-21 11:23:53.221738: train_loss -0.7498 +2024-11-21 11:23:53.224422: val_loss -0.7161 +2024-11-21 11:23:53.224542: Pseudo dice [0.8359] +2024-11-21 11:23:53.224643: Epoch time: 18.29 s +2024-11-21 11:23:53.224731: Yayy! New best EMA pseudo Dice: 0.835 +2024-11-21 11:23:54.235534: +2024-11-21 11:23:54.235752: Epoch 126 +2024-11-21 11:23:54.235876: Current learning rate: 0.00986 +2024-11-21 11:24:12.630361: train_loss -0.7442 +2024-11-21 11:24:12.633848: val_loss -0.7219 +2024-11-21 11:24:12.633955: Pseudo dice [0.8312] +2024-11-21 11:24:12.634040: Epoch time: 18.4 s +2024-11-21 11:24:13.426724: +2024-11-21 11:24:13.426947: Epoch 127 +2024-11-21 11:24:13.427082: Current learning rate: 0.00986 +2024-11-21 11:24:32.506699: train_loss -0.7365 +2024-11-21 11:24:32.509651: val_loss -0.7578 +2024-11-21 11:24:32.509783: Pseudo dice [0.836] +2024-11-21 11:24:32.510102: Epoch time: 19.08 s +2024-11-21 11:24:33.298930: +2024-11-21 11:24:33.299141: Epoch 128 +2024-11-21 11:24:33.299256: Current learning rate: 0.00986 +2024-11-21 11:24:51.548736: train_loss -0.7307 +2024-11-21 11:24:51.555438: val_loss -0.7403 +2024-11-21 11:24:51.555556: Pseudo dice [0.8404] +2024-11-21 11:24:51.555653: Epoch time: 18.25 s +2024-11-21 11:24:51.555763: Yayy! New best EMA pseudo Dice: 0.8353 +2024-11-21 11:24:52.727941: +2024-11-21 11:24:52.728154: Epoch 129 +2024-11-21 11:24:52.728268: Current learning rate: 0.00985 +2024-11-21 11:25:11.166285: train_loss -0.7404 +2024-11-21 11:25:11.171653: val_loss -0.7488 +2024-11-21 11:25:11.171780: Pseudo dice [0.8428] +2024-11-21 11:25:11.171880: Epoch time: 18.44 s +2024-11-21 11:25:11.171944: Yayy! New best EMA pseudo Dice: 0.836 +2024-11-21 11:25:12.181210: +2024-11-21 11:25:12.181435: Epoch 130 +2024-11-21 11:25:12.181562: Current learning rate: 0.00985 +2024-11-21 11:25:31.899296: train_loss -0.7337 +2024-11-21 11:25:31.901886: val_loss -0.7204 +2024-11-21 11:25:31.902013: Pseudo dice [0.8178] +2024-11-21 11:25:31.902102: Epoch time: 19.72 s +2024-11-21 11:25:32.801356: +2024-11-21 11:25:32.801561: Epoch 131 +2024-11-21 11:25:32.801698: Current learning rate: 0.00985 +2024-11-21 11:25:51.749131: train_loss -0.7429 +2024-11-21 11:25:51.755385: val_loss -0.7445 +2024-11-21 11:25:51.755535: Pseudo dice [0.8501] +2024-11-21 11:25:51.755646: Epoch time: 18.95 s +2024-11-21 11:25:52.555282: +2024-11-21 11:25:52.555493: Epoch 132 +2024-11-21 11:25:52.555631: Current learning rate: 0.00985 +2024-11-21 11:26:11.706431: train_loss -0.7374 +2024-11-21 11:26:11.711648: val_loss -0.7435 +2024-11-21 11:26:11.711790: Pseudo dice [0.844] +2024-11-21 11:26:11.711890: Epoch time: 19.15 s +2024-11-21 11:26:11.711957: Yayy! New best EMA pseudo Dice: 0.8366 +2024-11-21 11:26:12.720916: +2024-11-21 11:26:12.721126: Epoch 133 +2024-11-21 11:26:12.721249: Current learning rate: 0.00985 +2024-11-21 11:26:31.758181: train_loss -0.7343 +2024-11-21 11:26:31.764822: val_loss -0.7407 +2024-11-21 11:26:31.764979: Pseudo dice [0.84] +2024-11-21 11:26:31.765072: Epoch time: 19.04 s +2024-11-21 11:26:31.765154: Yayy! New best EMA pseudo Dice: 0.837 +2024-11-21 11:26:32.789446: +2024-11-21 11:26:32.789675: Epoch 134 +2024-11-21 11:26:32.789812: Current learning rate: 0.00985 +2024-11-21 11:26:51.899046: train_loss -0.7396 +2024-11-21 11:26:51.912785: val_loss -0.7554 +2024-11-21 11:26:51.912923: Pseudo dice [0.8426] +2024-11-21 11:26:51.913025: Epoch time: 19.11 s +2024-11-21 11:26:51.913113: Yayy! New best EMA pseudo Dice: 0.8375 +2024-11-21 11:26:53.320669: +2024-11-21 11:26:53.320879: Epoch 135 +2024-11-21 11:26:53.321002: Current learning rate: 0.00985 +2024-11-21 11:27:12.745512: train_loss -0.7439 +2024-11-21 11:27:12.752517: val_loss -0.7477 +2024-11-21 11:27:12.752658: Pseudo dice [0.8377] +2024-11-21 11:27:12.752752: Epoch time: 19.43 s +2024-11-21 11:27:12.752843: Yayy! New best EMA pseudo Dice: 0.8375 +2024-11-21 11:27:13.798878: +2024-11-21 11:27:13.799085: Epoch 136 +2024-11-21 11:27:13.799202: Current learning rate: 0.00985 +2024-11-21 11:27:32.347830: train_loss -0.7485 +2024-11-21 11:27:32.360396: val_loss -0.7554 +2024-11-21 11:27:32.360531: Pseudo dice [0.8392] +2024-11-21 11:27:32.360638: Epoch time: 18.55 s +2024-11-21 11:27:32.360724: Yayy! New best EMA pseudo Dice: 0.8377 +2024-11-21 11:27:33.552158: +2024-11-21 11:27:33.552352: Epoch 137 +2024-11-21 11:27:33.552484: Current learning rate: 0.00985 +2024-11-21 11:27:53.322680: train_loss -0.7372 +2024-11-21 11:27:53.330003: val_loss -0.7458 +2024-11-21 11:27:53.330183: Pseudo dice [0.8376] +2024-11-21 11:27:53.330267: Epoch time: 19.77 s +2024-11-21 11:27:54.150678: +2024-11-21 11:27:54.150876: Epoch 138 +2024-11-21 11:27:54.151011: Current learning rate: 0.00984 +2024-11-21 11:28:13.679344: train_loss -0.746 +2024-11-21 11:28:13.682512: val_loss -0.7397 +2024-11-21 11:28:13.682631: Pseudo dice [0.8484] +2024-11-21 11:28:13.682720: Epoch time: 19.53 s +2024-11-21 11:28:13.683011: Yayy! New best EMA pseudo Dice: 0.8388 +2024-11-21 11:28:14.706743: +2024-11-21 11:28:14.706950: Epoch 139 +2024-11-21 11:28:14.707101: Current learning rate: 0.00984 +2024-11-21 11:28:34.149128: train_loss -0.7349 +2024-11-21 11:28:34.158181: val_loss -0.7565 +2024-11-21 11:28:34.158337: Pseudo dice [0.8349] +2024-11-21 11:28:34.158454: Epoch time: 19.44 s +2024-11-21 11:28:34.983708: +2024-11-21 11:28:34.983899: Epoch 140 +2024-11-21 11:28:34.984013: Current learning rate: 0.00984 +2024-11-21 11:28:54.288721: train_loss -0.7442 +2024-11-21 11:28:54.308970: val_loss -0.7743 +2024-11-21 11:28:54.309116: Pseudo dice [0.8309] +2024-11-21 11:28:54.309202: Epoch time: 19.31 s +2024-11-21 11:28:55.195046: +2024-11-21 11:28:55.195272: Epoch 141 +2024-11-21 11:28:55.195407: Current learning rate: 0.00984 +2024-11-21 11:29:13.170415: train_loss -0.7474 +2024-11-21 11:29:13.176686: val_loss -0.7512 +2024-11-21 11:29:13.176918: Pseudo dice [0.8335] +2024-11-21 11:29:13.177027: Epoch time: 17.98 s +2024-11-21 11:29:14.063803: +2024-11-21 11:29:14.064032: Epoch 142 +2024-11-21 11:29:14.064150: Current learning rate: 0.00984 +2024-11-21 11:29:32.680278: train_loss -0.7385 +2024-11-21 11:29:32.687924: val_loss -0.7209 +2024-11-21 11:29:32.688078: Pseudo dice [0.8389] +2024-11-21 11:29:32.688222: Epoch time: 18.62 s +2024-11-21 11:29:33.493487: +2024-11-21 11:29:33.493676: Epoch 143 +2024-11-21 11:29:33.493801: Current learning rate: 0.00984 +2024-11-21 11:29:52.898877: train_loss -0.7436 +2024-11-21 11:29:52.908137: val_loss -0.7327 +2024-11-21 11:29:52.908266: Pseudo dice [0.8318] +2024-11-21 11:29:52.908358: Epoch time: 19.41 s +2024-11-21 11:29:53.887361: +2024-11-21 11:29:53.887552: Epoch 144 +2024-11-21 11:29:53.887676: Current learning rate: 0.00984 +2024-11-21 11:30:12.616567: train_loss -0.744 +2024-11-21 11:30:12.619089: val_loss -0.725 +2024-11-21 11:30:12.619195: Pseudo dice [0.844] +2024-11-21 11:30:12.619290: Epoch time: 18.73 s +2024-11-21 11:30:13.415820: +2024-11-21 11:30:13.416034: Epoch 145 +2024-11-21 11:30:13.416157: Current learning rate: 0.00984 +2024-11-21 11:30:31.659366: train_loss -0.7444 +2024-11-21 11:30:31.667118: val_loss -0.7292 +2024-11-21 11:30:31.667272: Pseudo dice [0.8315] +2024-11-21 11:30:31.667360: Epoch time: 18.24 s +2024-11-21 11:30:33.030953: +2024-11-21 11:30:33.031158: Epoch 146 +2024-11-21 11:30:33.031279: Current learning rate: 0.00984 +2024-11-21 11:30:52.489142: train_loss -0.7321 +2024-11-21 11:30:52.496332: val_loss -0.7513 +2024-11-21 11:30:52.496496: Pseudo dice [0.8476] +2024-11-21 11:30:52.496587: Epoch time: 19.46 s +2024-11-21 11:30:53.319247: +2024-11-21 11:30:53.319460: Epoch 147 +2024-11-21 11:30:53.319593: Current learning rate: 0.00983 +2024-11-21 11:31:12.417709: train_loss -0.7414 +2024-11-21 11:31:12.426608: val_loss -0.7385 +2024-11-21 11:31:12.426742: Pseudo dice [0.8466] +2024-11-21 11:31:12.426834: Epoch time: 19.1 s +2024-11-21 11:31:12.426923: Yayy! New best EMA pseudo Dice: 0.8389 +2024-11-21 11:31:13.552931: +2024-11-21 11:31:13.553113: Epoch 148 +2024-11-21 11:31:13.553247: Current learning rate: 0.00983 +2024-11-21 11:31:32.955258: train_loss -0.7476 +2024-11-21 11:31:32.958478: val_loss -0.7468 +2024-11-21 11:31:32.958593: Pseudo dice [0.8408] +2024-11-21 11:31:32.958680: Epoch time: 19.4 s +2024-11-21 11:31:32.958747: Yayy! New best EMA pseudo Dice: 0.8391 +2024-11-21 11:31:34.024451: +2024-11-21 11:31:34.024651: Epoch 149 +2024-11-21 11:31:34.024774: Current learning rate: 0.00983 +2024-11-21 11:31:52.848725: train_loss -0.7434 +2024-11-21 11:31:52.852413: val_loss -0.7611 +2024-11-21 11:31:52.852569: Pseudo dice [0.8533] +2024-11-21 11:31:52.852676: Epoch time: 18.83 s +2024-11-21 11:31:53.128758: Yayy! New best EMA pseudo Dice: 0.8405 +2024-11-21 11:31:54.145273: +2024-11-21 11:31:54.145467: Epoch 150 +2024-11-21 11:31:54.145585: Current learning rate: 0.00983 +2024-11-21 11:32:12.870296: train_loss -0.7506 +2024-11-21 11:32:12.873665: val_loss -0.7314 +2024-11-21 11:32:12.873796: Pseudo dice [0.8376] +2024-11-21 11:32:12.873888: Epoch time: 18.73 s +2024-11-21 11:32:13.699639: +2024-11-21 11:32:13.699836: Epoch 151 +2024-11-21 11:32:13.699967: Current learning rate: 0.00983 +2024-11-21 11:32:32.972339: train_loss -0.7302 +2024-11-21 11:32:32.979057: val_loss -0.7448 +2024-11-21 11:32:32.979215: Pseudo dice [0.8334] +2024-11-21 11:32:32.979353: Epoch time: 19.27 s +2024-11-21 11:32:33.818655: +2024-11-21 11:32:33.818859: Epoch 152 +2024-11-21 11:32:33.818974: Current learning rate: 0.00983 +2024-11-21 11:32:51.358747: train_loss -0.7476 +2024-11-21 11:32:51.365656: val_loss -0.724 +2024-11-21 11:32:51.365795: Pseudo dice [0.818] +2024-11-21 11:32:51.365898: Epoch time: 17.54 s +2024-11-21 11:32:52.203295: +2024-11-21 11:32:52.203543: Epoch 153 +2024-11-21 11:32:52.203679: Current learning rate: 0.00983 +2024-11-21 11:33:10.915487: train_loss -0.737 +2024-11-21 11:33:10.930830: val_loss -0.7542 +2024-11-21 11:33:10.930996: Pseudo dice [0.8395] +2024-11-21 11:33:10.931103: Epoch time: 18.71 s +2024-11-21 11:33:11.763832: +2024-11-21 11:33:11.764057: Epoch 154 +2024-11-21 11:33:11.764204: Current learning rate: 0.00983 +2024-11-21 11:33:30.643389: train_loss -0.7365 +2024-11-21 11:33:30.652548: val_loss -0.7304 +2024-11-21 11:33:30.652706: Pseudo dice [0.822] +2024-11-21 11:33:30.652799: Epoch time: 18.88 s +2024-11-21 11:33:31.504808: +2024-11-21 11:33:31.505030: Epoch 155 +2024-11-21 11:33:31.505152: Current learning rate: 0.00983 +2024-11-21 11:33:50.875123: train_loss -0.7354 +2024-11-21 11:33:50.881495: val_loss -0.7345 +2024-11-21 11:33:50.881624: Pseudo dice [0.8433] +2024-11-21 11:33:50.881710: Epoch time: 19.37 s +2024-11-21 11:33:52.251744: +2024-11-21 11:33:52.251934: Epoch 156 +2024-11-21 11:33:52.252057: Current learning rate: 0.00982 +2024-11-21 11:34:11.181878: train_loss -0.7446 +2024-11-21 11:34:11.188342: val_loss -0.7439 +2024-11-21 11:34:11.188488: Pseudo dice [0.8476] +2024-11-21 11:34:11.188590: Epoch time: 18.93 s +2024-11-21 11:34:11.997186: +2024-11-21 11:34:11.997388: Epoch 157 +2024-11-21 11:34:11.997509: Current learning rate: 0.00982 +2024-11-21 11:34:31.511958: train_loss -0.7379 +2024-11-21 11:34:31.518757: val_loss -0.7628 +2024-11-21 11:34:31.518899: Pseudo dice [0.8473] +2024-11-21 11:34:31.518996: Epoch time: 19.52 s +2024-11-21 11:34:32.481901: +2024-11-21 11:34:32.482085: Epoch 158 +2024-11-21 11:34:32.482227: Current learning rate: 0.00982 +2024-11-21 11:34:51.364940: train_loss -0.7252 +2024-11-21 11:34:51.372203: val_loss -0.7083 +2024-11-21 11:34:51.372344: Pseudo dice [0.8271] +2024-11-21 11:34:51.372443: Epoch time: 18.88 s +2024-11-21 11:34:52.535404: +2024-11-21 11:34:52.535604: Epoch 159 +2024-11-21 11:34:52.535728: Current learning rate: 0.00982 +2024-11-21 11:35:10.588480: train_loss -0.7401 +2024-11-21 11:35:10.591678: val_loss -0.753 +2024-11-21 11:35:10.591786: Pseudo dice [0.8415] +2024-11-21 11:35:10.591870: Epoch time: 18.05 s +2024-11-21 11:35:11.398725: +2024-11-21 11:35:11.398929: Epoch 160 +2024-11-21 11:35:11.399047: Current learning rate: 0.00982 +2024-11-21 11:35:31.169138: train_loss -0.7428 +2024-11-21 11:35:31.175215: val_loss -0.7436 +2024-11-21 11:35:31.175341: Pseudo dice [0.8337] +2024-11-21 11:35:31.175432: Epoch time: 19.77 s +2024-11-21 11:35:32.021934: +2024-11-21 11:35:32.022148: Epoch 161 +2024-11-21 11:35:32.022273: Current learning rate: 0.00982 +2024-11-21 11:35:51.131090: train_loss -0.7317 +2024-11-21 11:35:51.138466: val_loss -0.7535 +2024-11-21 11:35:51.138591: Pseudo dice [0.8489] +2024-11-21 11:35:51.138687: Epoch time: 19.11 s +2024-11-21 11:35:51.947785: +2024-11-21 11:35:51.947974: Epoch 162 +2024-11-21 11:35:51.948112: Current learning rate: 0.00982 +2024-11-21 11:36:11.053422: train_loss -0.7407 +2024-11-21 11:36:11.057457: val_loss -0.7587 +2024-11-21 11:36:11.057557: Pseudo dice [0.8331] +2024-11-21 11:36:11.057652: Epoch time: 19.11 s +2024-11-21 11:36:11.866556: +2024-11-21 11:36:11.866736: Epoch 163 +2024-11-21 11:36:11.866875: Current learning rate: 0.00982 +2024-11-21 11:36:30.546302: train_loss -0.7249 +2024-11-21 11:36:30.555720: val_loss -0.7304 +2024-11-21 11:36:30.570738: Pseudo dice [0.8251] +2024-11-21 11:36:30.570903: Epoch time: 18.68 s +2024-11-21 11:36:31.380252: +2024-11-21 11:36:31.380463: Epoch 164 +2024-11-21 11:36:31.380592: Current learning rate: 0.00982 +2024-11-21 11:36:51.009618: train_loss -0.7316 +2024-11-21 11:36:51.014222: val_loss -0.7446 +2024-11-21 11:36:51.014368: Pseudo dice [0.8256] +2024-11-21 11:36:51.014727: Epoch time: 19.63 s +2024-11-21 11:36:51.871783: +2024-11-21 11:36:51.871969: Epoch 165 +2024-11-21 11:36:51.872102: Current learning rate: 0.00981 +2024-11-21 11:37:10.653285: train_loss -0.7219 +2024-11-21 11:37:10.658715: val_loss -0.7513 +2024-11-21 11:37:10.658836: Pseudo dice [0.8335] +2024-11-21 11:37:10.658940: Epoch time: 18.78 s +2024-11-21 11:37:11.678563: +2024-11-21 11:37:11.678766: Epoch 166 +2024-11-21 11:37:11.678879: Current learning rate: 0.00981 +2024-11-21 11:37:30.514557: train_loss -0.7362 +2024-11-21 11:37:30.517551: val_loss -0.7304 +2024-11-21 11:37:30.517640: Pseudo dice [0.8373] +2024-11-21 11:37:30.517731: Epoch time: 18.84 s +2024-11-21 11:37:31.697710: +2024-11-21 11:37:31.697918: Epoch 167 +2024-11-21 11:37:31.698035: Current learning rate: 0.00981 +2024-11-21 11:37:50.130038: train_loss -0.7437 +2024-11-21 11:37:50.137835: val_loss -0.7533 +2024-11-21 11:37:50.137975: Pseudo dice [0.8404] +2024-11-21 11:37:50.138083: Epoch time: 18.43 s +2024-11-21 11:37:51.046067: +2024-11-21 11:37:51.046322: Epoch 168 +2024-11-21 11:37:51.046456: Current learning rate: 0.00981 +2024-11-21 11:38:10.587089: train_loss -0.7282 +2024-11-21 11:38:10.595819: val_loss -0.7457 +2024-11-21 11:38:10.595955: Pseudo dice [0.8508] +2024-11-21 11:38:10.596045: Epoch time: 19.54 s +2024-11-21 11:38:11.406026: +2024-11-21 11:38:11.406220: Epoch 169 +2024-11-21 11:38:11.406351: Current learning rate: 0.00981 +2024-11-21 11:38:30.333429: train_loss -0.7251 +2024-11-21 11:38:30.341887: val_loss -0.7511 +2024-11-21 11:38:30.342096: Pseudo dice [0.8314] +2024-11-21 11:38:30.342186: Epoch time: 18.93 s +2024-11-21 11:38:31.178595: +2024-11-21 11:38:31.178809: Epoch 170 +2024-11-21 11:38:31.178942: Current learning rate: 0.00981 +2024-11-21 11:38:50.515645: train_loss -0.7278 +2024-11-21 11:38:50.524023: val_loss -0.7297 +2024-11-21 11:38:50.524158: Pseudo dice [0.8398] +2024-11-21 11:38:50.524312: Epoch time: 19.34 s +2024-11-21 11:38:51.369560: +2024-11-21 11:38:51.369799: Epoch 171 +2024-11-21 11:38:51.369923: Current learning rate: 0.00981 +2024-11-21 11:39:10.662222: train_loss -0.7375 +2024-11-21 11:39:10.670394: val_loss -0.7518 +2024-11-21 11:39:10.670542: Pseudo dice [0.8309] +2024-11-21 11:39:10.670641: Epoch time: 19.29 s +2024-11-21 11:39:11.522031: +2024-11-21 11:39:11.522224: Epoch 172 +2024-11-21 11:39:11.522363: Current learning rate: 0.00981 +2024-11-21 11:39:30.711597: train_loss -0.7401 +2024-11-21 11:39:30.714275: val_loss -0.7565 +2024-11-21 11:39:30.714415: Pseudo dice [0.8525] +2024-11-21 11:39:30.714514: Epoch time: 19.19 s +2024-11-21 11:39:31.582367: +2024-11-21 11:39:31.582558: Epoch 173 +2024-11-21 11:39:31.582692: Current learning rate: 0.00981 +2024-11-21 11:39:50.394818: train_loss -0.7458 +2024-11-21 11:39:50.411264: val_loss -0.7605 +2024-11-21 11:39:50.411399: Pseudo dice [0.8332] +2024-11-21 11:39:50.411485: Epoch time: 18.81 s +2024-11-21 11:39:51.277073: +2024-11-21 11:39:51.277284: Epoch 174 +2024-11-21 11:39:51.277412: Current learning rate: 0.0098 +2024-11-21 11:40:10.168907: train_loss -0.748 +2024-11-21 11:40:10.176603: val_loss -0.7516 +2024-11-21 11:40:10.176757: Pseudo dice [0.8344] +2024-11-21 11:40:10.176856: Epoch time: 18.89 s +2024-11-21 11:40:10.987566: +2024-11-21 11:40:10.987790: Epoch 175 +2024-11-21 11:40:10.987914: Current learning rate: 0.0098 +2024-11-21 11:40:29.801942: train_loss -0.7485 +2024-11-21 11:40:29.805384: val_loss -0.7364 +2024-11-21 11:40:29.805505: Pseudo dice [0.8346] +2024-11-21 11:40:29.805607: Epoch time: 18.82 s +2024-11-21 11:40:30.613408: +2024-11-21 11:40:30.613610: Epoch 176 +2024-11-21 11:40:30.613725: Current learning rate: 0.0098 +2024-11-21 11:40:49.445640: train_loss -0.7487 +2024-11-21 11:40:49.448502: val_loss -0.7527 +2024-11-21 11:40:49.448609: Pseudo dice [0.8498] +2024-11-21 11:40:49.448705: Epoch time: 18.83 s +2024-11-21 11:40:50.251256: +2024-11-21 11:40:50.251460: Epoch 177 +2024-11-21 11:40:50.251595: Current learning rate: 0.0098 +2024-11-21 11:41:09.276363: train_loss -0.7481 +2024-11-21 11:41:09.279685: val_loss -0.7694 +2024-11-21 11:41:09.279817: Pseudo dice [0.8506] +2024-11-21 11:41:09.279913: Epoch time: 19.03 s +2024-11-21 11:41:10.480219: +2024-11-21 11:41:10.480456: Epoch 178 +2024-11-21 11:41:10.480583: Current learning rate: 0.0098 +2024-11-21 11:41:29.515071: train_loss -0.7396 +2024-11-21 11:41:29.528259: val_loss -0.7523 +2024-11-21 11:41:29.528395: Pseudo dice [0.834] +2024-11-21 11:41:29.528489: Epoch time: 19.04 s +2024-11-21 11:41:30.603960: +2024-11-21 11:41:30.604181: Epoch 179 +2024-11-21 11:41:30.604296: Current learning rate: 0.0098 +2024-11-21 11:41:49.464286: train_loss -0.7339 +2024-11-21 11:41:49.466977: val_loss -0.7679 +2024-11-21 11:41:49.467115: Pseudo dice [0.8247] +2024-11-21 11:41:49.467220: Epoch time: 18.86 s +2024-11-21 11:41:50.443292: +2024-11-21 11:41:50.443484: Epoch 180 +2024-11-21 11:41:50.443608: Current learning rate: 0.0098 +2024-11-21 11:42:10.015861: train_loss -0.7504 +2024-11-21 11:42:10.019630: val_loss -0.7431 +2024-11-21 11:42:10.019759: Pseudo dice [0.8411] +2024-11-21 11:42:10.019850: Epoch time: 19.57 s +2024-11-21 11:42:10.828891: +2024-11-21 11:42:10.829084: Epoch 181 +2024-11-21 11:42:10.829246: Current learning rate: 0.0098 +2024-11-21 11:42:29.319138: train_loss -0.7548 +2024-11-21 11:42:29.326098: val_loss -0.7479 +2024-11-21 11:42:29.326219: Pseudo dice [0.8221] +2024-11-21 11:42:29.326303: Epoch time: 18.49 s +2024-11-21 11:42:30.184851: +2024-11-21 11:42:30.185052: Epoch 182 +2024-11-21 11:42:30.185175: Current learning rate: 0.0098 +2024-11-21 11:42:48.473807: train_loss -0.736 +2024-11-21 11:42:48.479151: val_loss -0.7634 +2024-11-21 11:42:48.479307: Pseudo dice [0.8469] +2024-11-21 11:42:48.479421: Epoch time: 18.29 s +2024-11-21 11:42:49.281190: +2024-11-21 11:42:49.281384: Epoch 183 +2024-11-21 11:42:49.281515: Current learning rate: 0.00979 +2024-11-21 11:43:08.936180: train_loss -0.7289 +2024-11-21 11:43:08.943237: val_loss -0.7538 +2024-11-21 11:43:08.943379: Pseudo dice [0.838] +2024-11-21 11:43:08.943474: Epoch time: 19.66 s +2024-11-21 11:43:09.781897: +2024-11-21 11:43:09.782099: Epoch 184 +2024-11-21 11:43:09.782226: Current learning rate: 0.00979 +2024-11-21 11:43:28.210552: train_loss -0.7381 +2024-11-21 11:43:28.216957: val_loss -0.723 +2024-11-21 11:43:28.217105: Pseudo dice [0.8386] +2024-11-21 11:43:28.217196: Epoch time: 18.43 s +2024-11-21 11:43:29.023238: +2024-11-21 11:43:29.023427: Epoch 185 +2024-11-21 11:43:29.023554: Current learning rate: 0.00979 +2024-11-21 11:43:48.662199: train_loss -0.7332 +2024-11-21 11:43:48.668760: val_loss -0.7403 +2024-11-21 11:43:48.668899: Pseudo dice [0.8308] +2024-11-21 11:43:48.668988: Epoch time: 19.64 s +2024-11-21 11:43:49.474212: +2024-11-21 11:43:49.474441: Epoch 186 +2024-11-21 11:43:49.474587: Current learning rate: 0.00979 +2024-11-21 11:44:09.012310: train_loss -0.7406 +2024-11-21 11:44:09.031676: val_loss -0.7683 +2024-11-21 11:44:09.031825: Pseudo dice [0.8452] +2024-11-21 11:44:09.031928: Epoch time: 19.54 s +2024-11-21 11:44:09.846367: +2024-11-21 11:44:09.846554: Epoch 187 +2024-11-21 11:44:09.846676: Current learning rate: 0.00979 +2024-11-21 11:44:28.677546: train_loss -0.747 +2024-11-21 11:44:28.686123: val_loss -0.7803 +2024-11-21 11:44:28.686239: Pseudo dice [0.8469] +2024-11-21 11:44:28.686323: Epoch time: 18.83 s +2024-11-21 11:44:29.575649: +2024-11-21 11:44:29.575840: Epoch 188 +2024-11-21 11:44:29.575964: Current learning rate: 0.00979 +2024-11-21 11:44:48.169876: train_loss -0.7547 +2024-11-21 11:44:48.174692: val_loss -0.7531 +2024-11-21 11:44:48.174829: Pseudo dice [0.8561] +2024-11-21 11:44:48.174916: Epoch time: 18.6 s +2024-11-21 11:44:49.368417: +2024-11-21 11:44:49.368614: Epoch 189 +2024-11-21 11:44:49.368987: Current learning rate: 0.00979 +2024-11-21 11:45:08.284883: train_loss -0.7623 +2024-11-21 11:45:08.288522: val_loss -0.7623 +2024-11-21 11:45:08.288678: Pseudo dice [0.8394] +2024-11-21 11:45:08.288777: Epoch time: 18.92 s +2024-11-21 11:45:09.089387: +2024-11-21 11:45:09.089621: Epoch 190 +2024-11-21 11:45:09.089762: Current learning rate: 0.00979 +2024-11-21 11:45:28.266754: train_loss -0.7425 +2024-11-21 11:45:28.268887: val_loss -0.7672 +2024-11-21 11:45:28.269071: Pseudo dice [0.8368] +2024-11-21 11:45:28.269650: Epoch time: 19.18 s +2024-11-21 11:45:29.086051: +2024-11-21 11:45:29.086244: Epoch 191 +2024-11-21 11:45:29.086385: Current learning rate: 0.00978 +2024-11-21 11:45:47.035589: train_loss -0.7475 +2024-11-21 11:45:47.042625: val_loss -0.7554 +2024-11-21 11:45:47.042755: Pseudo dice [0.8455] +2024-11-21 11:45:47.042840: Epoch time: 17.95 s +2024-11-21 11:45:47.042910: Yayy! New best EMA pseudo Dice: 0.8405 +2024-11-21 11:45:48.142846: +2024-11-21 11:45:48.143078: Epoch 192 +2024-11-21 11:45:48.143199: Current learning rate: 0.00978 +2024-11-21 11:46:06.782613: train_loss -0.7462 +2024-11-21 11:46:06.790507: val_loss -0.742 +2024-11-21 11:46:06.790642: Pseudo dice [0.8453] +2024-11-21 11:46:06.790745: Epoch time: 18.64 s +2024-11-21 11:46:06.790824: Yayy! New best EMA pseudo Dice: 0.841 +2024-11-21 11:46:07.846407: +2024-11-21 11:46:07.846669: Epoch 193 +2024-11-21 11:46:07.846790: Current learning rate: 0.00978 +2024-11-21 11:46:26.719407: train_loss -0.7468 +2024-11-21 11:46:26.727714: val_loss -0.7601 +2024-11-21 11:46:26.727859: Pseudo dice [0.846] +2024-11-21 11:46:26.727957: Epoch time: 18.87 s +2024-11-21 11:46:26.728025: Yayy! New best EMA pseudo Dice: 0.8415 +2024-11-21 11:46:27.781738: +2024-11-21 11:46:27.781944: Epoch 194 +2024-11-21 11:46:27.782079: Current learning rate: 0.00978 +2024-11-21 11:46:46.496417: train_loss -0.7409 +2024-11-21 11:46:46.504192: val_loss -0.7101 +2024-11-21 11:46:46.504315: Pseudo dice [0.8374] +2024-11-21 11:46:46.504412: Epoch time: 18.72 s +2024-11-21 11:46:47.315453: +2024-11-21 11:46:47.315671: Epoch 195 +2024-11-21 11:46:47.315785: Current learning rate: 0.00978 +2024-11-21 11:47:05.905150: train_loss -0.7562 +2024-11-21 11:47:05.922376: val_loss -0.7702 +2024-11-21 11:47:05.922512: Pseudo dice [0.8499] +2024-11-21 11:47:05.922607: Epoch time: 18.59 s +2024-11-21 11:47:05.922684: Yayy! New best EMA pseudo Dice: 0.842 +2024-11-21 11:47:07.016111: +2024-11-21 11:47:07.016302: Epoch 196 +2024-11-21 11:47:07.016433: Current learning rate: 0.00978 +2024-11-21 11:47:26.113757: train_loss -0.7397 +2024-11-21 11:47:26.123979: val_loss -0.7302 +2024-11-21 11:47:26.124109: Pseudo dice [0.8291] +2024-11-21 11:47:26.124193: Epoch time: 19.1 s +2024-11-21 11:47:26.948417: +2024-11-21 11:47:26.948622: Epoch 197 +2024-11-21 11:47:26.948761: Current learning rate: 0.00978 +2024-11-21 11:47:45.584181: train_loss -0.7502 +2024-11-21 11:47:45.586533: val_loss -0.742 +2024-11-21 11:47:45.586645: Pseudo dice [0.8415] +2024-11-21 11:47:45.586751: Epoch time: 18.64 s +2024-11-21 11:47:46.391911: +2024-11-21 11:47:46.392104: Epoch 198 +2024-11-21 11:47:46.392233: Current learning rate: 0.00978 +2024-11-21 11:48:05.598940: train_loss -0.7504 +2024-11-21 11:48:05.601463: val_loss -0.7081 +2024-11-21 11:48:05.601571: Pseudo dice [0.8391] +2024-11-21 11:48:05.601653: Epoch time: 19.21 s +2024-11-21 11:48:06.400242: +2024-11-21 11:48:06.400429: Epoch 199 +2024-11-21 11:48:06.400558: Current learning rate: 0.00978 +2024-11-21 11:48:25.552171: train_loss -0.7333 +2024-11-21 11:48:25.556346: val_loss -0.7475 +2024-11-21 11:48:25.556528: Pseudo dice [0.8336] +2024-11-21 11:48:25.556617: Epoch time: 19.15 s +2024-11-21 11:48:27.051829: +2024-11-21 11:48:27.052024: Epoch 200 +2024-11-21 11:48:27.052158: Current learning rate: 0.00977 +2024-11-21 11:48:46.396363: train_loss -0.7432 +2024-11-21 11:48:46.398870: val_loss -0.7497 +2024-11-21 11:48:46.398996: Pseudo dice [0.8389] +2024-11-21 11:48:46.399093: Epoch time: 19.35 s +2024-11-21 11:48:47.206586: +2024-11-21 11:48:47.206834: Epoch 201 +2024-11-21 11:48:47.206972: Current learning rate: 0.00977 +2024-11-21 11:49:07.091717: train_loss -0.7405 +2024-11-21 11:49:07.103369: val_loss -0.7408 +2024-11-21 11:49:07.103533: Pseudo dice [0.8302] +2024-11-21 11:49:07.103647: Epoch time: 19.89 s +2024-11-21 11:49:07.948520: +2024-11-21 11:49:07.948753: Epoch 202 +2024-11-21 11:49:07.948893: Current learning rate: 0.00977 +2024-11-21 11:49:26.999733: train_loss -0.7524 +2024-11-21 11:49:27.008454: val_loss -0.7282 +2024-11-21 11:49:27.008582: Pseudo dice [0.8207] +2024-11-21 11:49:27.008713: Epoch time: 19.05 s +2024-11-21 11:49:27.827003: +2024-11-21 11:49:27.827229: Epoch 203 +2024-11-21 11:49:27.827345: Current learning rate: 0.00977 +2024-11-21 11:49:47.394281: train_loss -0.7484 +2024-11-21 11:49:47.422837: val_loss -0.7664 +2024-11-21 11:49:47.423011: Pseudo dice [0.8475] +2024-11-21 11:49:47.423122: Epoch time: 19.57 s +2024-11-21 11:49:48.229296: +2024-11-21 11:49:48.229485: Epoch 204 +2024-11-21 11:49:48.229605: Current learning rate: 0.00977 +2024-11-21 11:50:07.144453: train_loss -0.7292 +2024-11-21 11:50:07.148916: val_loss -0.7489 +2024-11-21 11:50:07.149047: Pseudo dice [0.8362] +2024-11-21 11:50:07.149147: Epoch time: 18.92 s +2024-11-21 11:50:07.989944: +2024-11-21 11:50:07.990158: Epoch 205 +2024-11-21 11:50:07.990316: Current learning rate: 0.00977 +2024-11-21 11:50:27.019698: train_loss -0.7258 +2024-11-21 11:50:27.027210: val_loss -0.75 +2024-11-21 11:50:27.027334: Pseudo dice [0.8446] +2024-11-21 11:50:27.027438: Epoch time: 19.03 s +2024-11-21 11:50:27.953354: +2024-11-21 11:50:27.953553: Epoch 206 +2024-11-21 11:50:27.953666: Current learning rate: 0.00977 +2024-11-21 11:50:46.693768: train_loss -0.7452 +2024-11-21 11:50:46.701346: val_loss -0.74 +2024-11-21 11:50:46.701496: Pseudo dice [0.8441] +2024-11-21 11:50:46.701586: Epoch time: 18.74 s +2024-11-21 11:50:47.533368: +2024-11-21 11:50:47.533556: Epoch 207 +2024-11-21 11:50:47.533683: Current learning rate: 0.00977 +2024-11-21 11:51:06.056810: train_loss -0.7502 +2024-11-21 11:51:06.064807: val_loss -0.764 +2024-11-21 11:51:06.064960: Pseudo dice [0.8378] +2024-11-21 11:51:06.065057: Epoch time: 18.52 s +2024-11-21 11:51:06.984642: +2024-11-21 11:51:06.984874: Epoch 208 +2024-11-21 11:51:06.985002: Current learning rate: 0.00977 +2024-11-21 11:51:25.457140: train_loss -0.7474 +2024-11-21 11:51:25.466319: val_loss -0.7668 +2024-11-21 11:51:25.466429: Pseudo dice [0.8478] +2024-11-21 11:51:25.466531: Epoch time: 18.47 s +2024-11-21 11:51:26.239369: +2024-11-21 11:51:26.239541: Epoch 209 +2024-11-21 11:51:26.239686: Current learning rate: 0.00976 +2024-11-21 11:51:45.149945: train_loss -0.756 +2024-11-21 11:51:45.155202: val_loss -0.752 +2024-11-21 11:51:45.155347: Pseudo dice [0.8434] +2024-11-21 11:51:45.155438: Epoch time: 18.91 s +2024-11-21 11:51:46.022321: +2024-11-21 11:51:46.022520: Epoch 210 +2024-11-21 11:51:46.022643: Current learning rate: 0.00976 +2024-11-21 11:52:05.342137: train_loss -0.7496 +2024-11-21 11:52:05.347847: val_loss -0.7602 +2024-11-21 11:52:05.347990: Pseudo dice [0.8375] +2024-11-21 11:52:05.348111: Epoch time: 19.32 s +2024-11-21 11:52:06.129736: +2024-11-21 11:52:06.129972: Epoch 211 +2024-11-21 11:52:06.130122: Current learning rate: 0.00976 +2024-11-21 11:52:26.212693: train_loss -0.7292 +2024-11-21 11:52:26.225583: val_loss -0.7509 +2024-11-21 11:52:26.225736: Pseudo dice [0.8353] +2024-11-21 11:52:26.225833: Epoch time: 20.08 s +2024-11-21 11:52:27.154533: +2024-11-21 11:52:27.154754: Epoch 212 +2024-11-21 11:52:27.154895: Current learning rate: 0.00976 +2024-11-21 11:52:47.121274: train_loss -0.7502 +2024-11-21 11:52:47.128051: val_loss -0.7541 +2024-11-21 11:52:47.128178: Pseudo dice [0.8468] +2024-11-21 11:52:47.128273: Epoch time: 19.97 s +2024-11-21 11:52:47.903525: +2024-11-21 11:52:47.903731: Epoch 213 +2024-11-21 11:52:47.903855: Current learning rate: 0.00976 +2024-11-21 11:53:06.298018: train_loss -0.7452 +2024-11-21 11:53:06.303559: val_loss -0.7384 +2024-11-21 11:53:06.303688: Pseudo dice [0.8426] +2024-11-21 11:53:06.304078: Epoch time: 18.4 s +2024-11-21 11:53:07.084431: +2024-11-21 11:53:07.084653: Epoch 214 +2024-11-21 11:53:07.084770: Current learning rate: 0.00976 +2024-11-21 11:53:26.653928: train_loss -0.7443 +2024-11-21 11:53:26.660145: val_loss -0.7433 +2024-11-21 11:53:26.660278: Pseudo dice [0.8256] +2024-11-21 11:53:26.660380: Epoch time: 19.57 s +2024-11-21 11:53:27.619076: +2024-11-21 11:53:27.619274: Epoch 215 +2024-11-21 11:53:27.619406: Current learning rate: 0.00976 +2024-11-21 11:53:45.608913: train_loss -0.7459 +2024-11-21 11:53:45.617011: val_loss -0.7746 +2024-11-21 11:53:45.617130: Pseudo dice [0.8533] +2024-11-21 11:53:45.617216: Epoch time: 17.99 s +2024-11-21 11:53:46.417601: +2024-11-21 11:53:46.418077: Epoch 216 +2024-11-21 11:53:46.418211: Current learning rate: 0.00976 +2024-11-21 11:54:05.390587: train_loss -0.7406 +2024-11-21 11:54:05.399322: val_loss -0.7431 +2024-11-21 11:54:05.399449: Pseudo dice [0.8289] +2024-11-21 11:54:05.399553: Epoch time: 18.97 s +2024-11-21 11:54:06.370131: +2024-11-21 11:54:06.370356: Epoch 217 +2024-11-21 11:54:06.370486: Current learning rate: 0.00976 +2024-11-21 11:54:26.072783: train_loss -0.7582 +2024-11-21 11:54:26.078379: val_loss -0.7524 +2024-11-21 11:54:26.078551: Pseudo dice [0.8426] +2024-11-21 11:54:26.078645: Epoch time: 19.7 s +2024-11-21 11:54:26.856473: +2024-11-21 11:54:26.856685: Epoch 218 +2024-11-21 11:54:26.856817: Current learning rate: 0.00975 +2024-11-21 11:54:45.289831: train_loss -0.7522 +2024-11-21 11:54:45.294280: val_loss -0.766 +2024-11-21 11:54:45.294402: Pseudo dice [0.8476] +2024-11-21 11:54:45.294539: Epoch time: 18.43 s +2024-11-21 11:54:46.075478: +2024-11-21 11:54:46.075706: Epoch 219 +2024-11-21 11:54:46.075838: Current learning rate: 0.00975 +2024-11-21 11:55:04.554816: train_loss -0.7384 +2024-11-21 11:55:04.572882: val_loss -0.7654 +2024-11-21 11:55:04.573047: Pseudo dice [0.8512] +2024-11-21 11:55:04.573145: Epoch time: 18.48 s +2024-11-21 11:55:05.360191: +2024-11-21 11:55:05.360398: Epoch 220 +2024-11-21 11:55:05.360526: Current learning rate: 0.00975 +2024-11-21 11:55:22.688449: train_loss -0.7514 +2024-11-21 11:55:22.695156: val_loss -0.7454 +2024-11-21 11:55:22.695279: Pseudo dice [0.8435] +2024-11-21 11:55:22.695381: Epoch time: 17.33 s +2024-11-21 11:55:23.714779: +2024-11-21 11:55:23.714966: Epoch 221 +2024-11-21 11:55:23.715105: Current learning rate: 0.00975 +2024-11-21 11:55:43.070569: train_loss -0.7493 +2024-11-21 11:55:43.089467: val_loss -0.7419 +2024-11-21 11:55:43.089619: Pseudo dice [0.8287] +2024-11-21 11:55:43.089735: Epoch time: 19.36 s +2024-11-21 11:55:44.005917: +2024-11-21 11:55:44.006147: Epoch 222 +2024-11-21 11:55:44.006281: Current learning rate: 0.00975 +2024-11-21 11:56:03.150744: train_loss -0.7515 +2024-11-21 11:56:03.155189: val_loss -0.7347 +2024-11-21 11:56:03.155292: Pseudo dice [0.8503] +2024-11-21 11:56:03.155376: Epoch time: 19.15 s +2024-11-21 11:56:04.339814: +2024-11-21 11:56:04.340015: Epoch 223 +2024-11-21 11:56:04.340152: Current learning rate: 0.00975 +2024-11-21 11:56:23.290057: train_loss -0.7451 +2024-11-21 11:56:23.297079: val_loss -0.7134 +2024-11-21 11:56:23.297221: Pseudo dice [0.8298] +2024-11-21 11:56:23.297317: Epoch time: 18.95 s +2024-11-21 11:56:24.086311: +2024-11-21 11:56:24.086550: Epoch 224 +2024-11-21 11:56:24.086699: Current learning rate: 0.00975 +2024-11-21 11:56:43.292741: train_loss -0.7506 +2024-11-21 11:56:43.314333: val_loss -0.7709 +2024-11-21 11:56:43.314499: Pseudo dice [0.8412] +2024-11-21 11:56:43.314600: Epoch time: 19.21 s +2024-11-21 11:56:44.317852: +2024-11-21 11:56:44.318092: Epoch 225 +2024-11-21 11:56:44.318210: Current learning rate: 0.00975 +2024-11-21 11:57:03.295286: train_loss -0.7505 +2024-11-21 11:57:03.314229: val_loss -0.7528 +2024-11-21 11:57:03.314404: Pseudo dice [0.848] +2024-11-21 11:57:03.314520: Epoch time: 18.98 s +2024-11-21 11:57:04.092661: +2024-11-21 11:57:04.092860: Epoch 226 +2024-11-21 11:57:04.092975: Current learning rate: 0.00975 +2024-11-21 11:57:23.115590: train_loss -0.7376 +2024-11-21 11:57:23.130978: val_loss -0.7491 +2024-11-21 11:57:23.131151: Pseudo dice [0.8363] +2024-11-21 11:57:23.131265: Epoch time: 19.02 s +2024-11-21 11:57:23.913999: +2024-11-21 11:57:23.914219: Epoch 227 +2024-11-21 11:57:23.914346: Current learning rate: 0.00974 +2024-11-21 11:57:43.278977: train_loss -0.7424 +2024-11-21 11:57:43.297371: val_loss -0.7594 +2024-11-21 11:57:43.297542: Pseudo dice [0.8368] +2024-11-21 11:57:43.297660: Epoch time: 19.37 s +2024-11-21 11:57:44.092916: +2024-11-21 11:57:44.093127: Epoch 228 +2024-11-21 11:57:44.093253: Current learning rate: 0.00974 +2024-11-21 11:58:02.760444: train_loss -0.7455 +2024-11-21 11:58:02.789134: val_loss -0.739 +2024-11-21 11:58:02.789259: Pseudo dice [0.8426] +2024-11-21 11:58:02.789346: Epoch time: 18.67 s +2024-11-21 11:58:03.571719: +2024-11-21 11:58:03.571911: Epoch 229 +2024-11-21 11:58:03.572030: Current learning rate: 0.00974 +2024-11-21 11:58:21.480580: train_loss -0.743 +2024-11-21 11:58:21.505742: val_loss -0.7438 +2024-11-21 11:58:21.505894: Pseudo dice [0.8284] +2024-11-21 11:58:21.505992: Epoch time: 17.91 s +2024-11-21 11:58:22.283581: +2024-11-21 11:58:22.283831: Epoch 230 +2024-11-21 11:58:22.283958: Current learning rate: 0.00974 +2024-11-21 11:58:40.764894: train_loss -0.7494 +2024-11-21 11:58:40.773614: val_loss -0.7785 +2024-11-21 11:58:40.773760: Pseudo dice [0.8383] +2024-11-21 11:58:40.773879: Epoch time: 18.48 s +2024-11-21 11:58:41.801948: +2024-11-21 11:58:41.802226: Epoch 231 +2024-11-21 11:58:41.802355: Current learning rate: 0.00974 +2024-11-21 11:59:00.446663: train_loss -0.7344 +2024-11-21 11:59:00.464103: val_loss -0.762 +2024-11-21 11:59:00.464269: Pseudo dice [0.849] +2024-11-21 11:59:00.464367: Epoch time: 18.65 s +2024-11-21 11:59:01.535415: +2024-11-21 11:59:01.535606: Epoch 232 +2024-11-21 11:59:01.535733: Current learning rate: 0.00974 +2024-11-21 11:59:21.058403: train_loss -0.7439 +2024-11-21 11:59:21.063554: val_loss -0.7332 +2024-11-21 11:59:21.063672: Pseudo dice [0.8439] +2024-11-21 11:59:21.063775: Epoch time: 19.52 s +2024-11-21 11:59:21.840356: +2024-11-21 11:59:21.840536: Epoch 233 +2024-11-21 11:59:21.840665: Current learning rate: 0.00974 +2024-11-21 11:59:41.375253: train_loss -0.7488 +2024-11-21 11:59:41.378384: val_loss -0.7514 +2024-11-21 11:59:41.378521: Pseudo dice [0.8538] +2024-11-21 11:59:41.378617: Epoch time: 19.54 s +2024-11-21 11:59:42.267769: +2024-11-21 11:59:42.267967: Epoch 234 +2024-11-21 11:59:42.268095: Current learning rate: 0.00974 +2024-11-21 12:00:01.358786: train_loss -0.7474 +2024-11-21 12:00:01.363601: val_loss -0.7537 +2024-11-21 12:00:01.363729: Pseudo dice [0.8497] +2024-11-21 12:00:01.363825: Epoch time: 19.09 s +2024-11-21 12:00:01.363897: Yayy! New best EMA pseudo Dice: 0.8426 +2024-11-21 12:00:02.348464: +2024-11-21 12:00:02.348683: Epoch 235 +2024-11-21 12:00:02.348812: Current learning rate: 0.00974 +2024-11-21 12:00:21.513268: train_loss -0.7501 +2024-11-21 12:00:21.527661: val_loss -0.7517 +2024-11-21 12:00:21.527801: Pseudo dice [0.8501] +2024-11-21 12:00:21.527921: Epoch time: 19.17 s +2024-11-21 12:00:21.528023: Yayy! New best EMA pseudo Dice: 0.8434 +2024-11-21 12:00:22.606122: +2024-11-21 12:00:22.606348: Epoch 236 +2024-11-21 12:00:22.606493: Current learning rate: 0.00973 +2024-11-21 12:00:40.946111: train_loss -0.7543 +2024-11-21 12:00:40.972490: val_loss -0.7636 +2024-11-21 12:00:40.972657: Pseudo dice [0.8523] +2024-11-21 12:00:40.972782: Epoch time: 18.34 s +2024-11-21 12:00:40.972853: Yayy! New best EMA pseudo Dice: 0.8443 +2024-11-21 12:00:42.130241: +2024-11-21 12:00:42.130440: Epoch 237 +2024-11-21 12:00:42.130555: Current learning rate: 0.00973 +2024-11-21 12:01:00.227670: train_loss -0.7485 +2024-11-21 12:01:00.239340: val_loss -0.7715 +2024-11-21 12:01:00.239505: Pseudo dice [0.854] +2024-11-21 12:01:00.239600: Epoch time: 18.1 s +2024-11-21 12:01:00.239672: Yayy! New best EMA pseudo Dice: 0.8452 +2024-11-21 12:01:01.263659: +2024-11-21 12:01:01.263868: Epoch 238 +2024-11-21 12:01:01.263984: Current learning rate: 0.00973 +2024-11-21 12:01:19.644450: train_loss -0.7529 +2024-11-21 12:01:19.664129: val_loss -0.7477 +2024-11-21 12:01:19.664304: Pseudo dice [0.8545] +2024-11-21 12:01:19.664402: Epoch time: 18.38 s +2024-11-21 12:01:19.664480: Yayy! New best EMA pseudo Dice: 0.8462 +2024-11-21 12:01:20.751514: +2024-11-21 12:01:20.751720: Epoch 239 +2024-11-21 12:01:20.751835: Current learning rate: 0.00973 +2024-11-21 12:01:39.475834: train_loss -0.76 +2024-11-21 12:01:39.497286: val_loss -0.7122 +2024-11-21 12:01:39.497449: Pseudo dice [0.848] +2024-11-21 12:01:39.497556: Epoch time: 18.73 s +2024-11-21 12:01:39.497626: Yayy! New best EMA pseudo Dice: 0.8464 +2024-11-21 12:01:40.525982: +2024-11-21 12:01:40.526193: Epoch 240 +2024-11-21 12:01:40.526323: Current learning rate: 0.00973 +2024-11-21 12:02:00.602966: train_loss -0.7457 +2024-11-21 12:02:00.611361: val_loss -0.749 +2024-11-21 12:02:00.611524: Pseudo dice [0.832] +2024-11-21 12:02:00.611876: Epoch time: 20.08 s +2024-11-21 12:02:01.409278: +2024-11-21 12:02:01.409471: Epoch 241 +2024-11-21 12:02:01.409586: Current learning rate: 0.00973 +2024-11-21 12:02:21.230318: train_loss -0.7395 +2024-11-21 12:02:21.237415: val_loss -0.7472 +2024-11-21 12:02:21.237543: Pseudo dice [0.8373] +2024-11-21 12:02:21.237637: Epoch time: 19.82 s +2024-11-21 12:02:22.131565: +2024-11-21 12:02:22.131776: Epoch 242 +2024-11-21 12:02:22.131909: Current learning rate: 0.00973 +2024-11-21 12:02:40.475918: train_loss -0.7559 +2024-11-21 12:02:40.496977: val_loss -0.7549 +2024-11-21 12:02:40.497164: Pseudo dice [0.8523] +2024-11-21 12:02:40.497262: Epoch time: 18.35 s +2024-11-21 12:02:41.291889: +2024-11-21 12:02:41.292075: Epoch 243 +2024-11-21 12:02:41.292196: Current learning rate: 0.00973 +2024-11-21 12:03:01.536773: train_loss -0.7532 +2024-11-21 12:03:01.546972: val_loss -0.727 +2024-11-21 12:03:01.547080: Pseudo dice [0.8301] +2024-11-21 12:03:01.547169: Epoch time: 20.25 s +2024-11-21 12:03:02.333684: +2024-11-21 12:03:02.333893: Epoch 244 +2024-11-21 12:03:02.334009: Current learning rate: 0.00973 +2024-11-21 12:03:20.808579: train_loss -0.7518 +2024-11-21 12:03:20.822013: val_loss -0.7181 +2024-11-21 12:03:20.822190: Pseudo dice [0.8257] +2024-11-21 12:03:20.822283: Epoch time: 18.48 s +2024-11-21 12:03:22.070756: +2024-11-21 12:03:22.070994: Epoch 245 +2024-11-21 12:03:22.071120: Current learning rate: 0.00972 +2024-11-21 12:03:41.540034: train_loss -0.7461 +2024-11-21 12:03:41.563696: val_loss -0.7408 +2024-11-21 12:03:41.563864: Pseudo dice [0.8122] +2024-11-21 12:03:41.563967: Epoch time: 19.47 s +2024-11-21 12:03:42.371877: +2024-11-21 12:03:42.372167: Epoch 246 +2024-11-21 12:03:42.372309: Current learning rate: 0.00972 +2024-11-21 12:04:01.059721: train_loss -0.7476 +2024-11-21 12:04:01.072046: val_loss -0.77 +2024-11-21 12:04:01.072232: Pseudo dice [0.852] +2024-11-21 12:04:01.072352: Epoch time: 18.69 s +2024-11-21 12:04:01.870485: +2024-11-21 12:04:01.870742: Epoch 247 +2024-11-21 12:04:01.870858: Current learning rate: 0.00972 +2024-11-21 12:04:20.467241: train_loss -0.7447 +2024-11-21 12:04:20.472895: val_loss -0.7541 +2024-11-21 12:04:20.473040: Pseudo dice [0.8231] +2024-11-21 12:04:20.473148: Epoch time: 18.6 s +2024-11-21 12:04:21.299899: +2024-11-21 12:04:21.300091: Epoch 248 +2024-11-21 12:04:21.300212: Current learning rate: 0.00972 +2024-11-21 12:04:39.711046: train_loss -0.743 +2024-11-21 12:04:39.717570: val_loss -0.7504 +2024-11-21 12:04:39.717724: Pseudo dice [0.8504] +2024-11-21 12:04:39.717824: Epoch time: 18.41 s +2024-11-21 12:04:40.535433: +2024-11-21 12:04:40.535627: Epoch 249 +2024-11-21 12:04:40.535756: Current learning rate: 0.00972 +2024-11-21 12:05:00.084089: train_loss -0.7532 +2024-11-21 12:05:00.092196: val_loss -0.7354 +2024-11-21 12:05:00.092335: Pseudo dice [0.8307] +2024-11-21 12:05:00.092430: Epoch time: 19.55 s +2024-11-21 12:05:01.202945: +2024-11-21 12:05:01.203140: Epoch 250 +2024-11-21 12:05:01.203255: Current learning rate: 0.00972 +2024-11-21 12:05:19.670461: train_loss -0.7444 +2024-11-21 12:05:19.687770: val_loss -0.7415 +2024-11-21 12:05:19.688167: Pseudo dice [0.8479] +2024-11-21 12:05:19.688300: Epoch time: 18.47 s +2024-11-21 12:05:20.513616: +2024-11-21 12:05:20.513812: Epoch 251 +2024-11-21 12:05:20.513936: Current learning rate: 0.00972 +2024-11-21 12:05:39.661061: train_loss -0.7479 +2024-11-21 12:05:39.712798: val_loss -0.7631 +2024-11-21 12:05:39.713077: Pseudo dice [0.8439] +2024-11-21 12:05:39.713190: Epoch time: 19.15 s +2024-11-21 12:05:40.793731: +2024-11-21 12:05:40.793941: Epoch 252 +2024-11-21 12:05:40.794077: Current learning rate: 0.00972 +2024-11-21 12:06:00.031088: train_loss -0.7387 +2024-11-21 12:06:00.056169: val_loss -0.7305 +2024-11-21 12:06:00.056317: Pseudo dice [0.8299] +2024-11-21 12:06:00.056425: Epoch time: 19.24 s +2024-11-21 12:06:00.925077: +2024-11-21 12:06:00.925267: Epoch 253 +2024-11-21 12:06:00.925382: Current learning rate: 0.00971 +2024-11-21 12:06:20.093293: train_loss -0.7394 +2024-11-21 12:06:20.101332: val_loss -0.7387 +2024-11-21 12:06:20.101472: Pseudo dice [0.8331] +2024-11-21 12:06:20.101566: Epoch time: 19.17 s +2024-11-21 12:06:21.050472: +2024-11-21 12:06:21.050678: Epoch 254 +2024-11-21 12:06:21.050803: Current learning rate: 0.00971 +2024-11-21 12:06:39.662735: train_loss -0.7472 +2024-11-21 12:06:39.679429: val_loss -0.7287 +2024-11-21 12:06:39.679546: Pseudo dice [0.8307] +2024-11-21 12:06:39.679650: Epoch time: 18.61 s +2024-11-21 12:06:40.475219: +2024-11-21 12:06:40.475402: Epoch 255 +2024-11-21 12:06:40.475526: Current learning rate: 0.00971 +2024-11-21 12:06:59.353372: train_loss -0.7447 +2024-11-21 12:06:59.359142: val_loss -0.7408 +2024-11-21 12:06:59.359269: Pseudo dice [0.8226] +2024-11-21 12:06:59.359370: Epoch time: 18.88 s +2024-11-21 12:07:00.183406: +2024-11-21 12:07:00.183627: Epoch 256 +2024-11-21 12:07:00.183767: Current learning rate: 0.00971 +2024-11-21 12:07:19.393466: train_loss -0.7541 +2024-11-21 12:07:19.400522: val_loss -0.7608 +2024-11-21 12:07:19.400676: Pseudo dice [0.855] +2024-11-21 12:07:19.400785: Epoch time: 19.21 s +2024-11-21 12:07:20.619654: +2024-11-21 12:07:20.619850: Epoch 257 +2024-11-21 12:07:20.619978: Current learning rate: 0.00971 +2024-11-21 12:07:39.743603: train_loss -0.7544 +2024-11-21 12:07:39.750790: val_loss -0.7657 +2024-11-21 12:07:39.750938: Pseudo dice [0.8448] +2024-11-21 12:07:39.751027: Epoch time: 19.12 s +2024-11-21 12:07:40.578656: +2024-11-21 12:07:40.578874: Epoch 258 +2024-11-21 12:07:40.578999: Current learning rate: 0.00971 +2024-11-21 12:07:59.427352: train_loss -0.742 +2024-11-21 12:07:59.438073: val_loss -0.7456 +2024-11-21 12:07:59.438209: Pseudo dice [0.843] +2024-11-21 12:07:59.438294: Epoch time: 18.85 s +2024-11-21 12:08:00.397191: +2024-11-21 12:08:00.397388: Epoch 259 +2024-11-21 12:08:00.397515: Current learning rate: 0.00971 +2024-11-21 12:08:19.149318: train_loss -0.7332 +2024-11-21 12:08:19.154497: val_loss -0.7527 +2024-11-21 12:08:19.154627: Pseudo dice [0.8427] +2024-11-21 12:08:19.154738: Epoch time: 18.75 s +2024-11-21 12:08:19.946276: +2024-11-21 12:08:19.946573: Epoch 260 +2024-11-21 12:08:19.946696: Current learning rate: 0.00971 +2024-11-21 12:08:37.900227: train_loss -0.7414 +2024-11-21 12:08:37.903949: val_loss -0.7382 +2024-11-21 12:08:37.904070: Pseudo dice [0.8306] +2024-11-21 12:08:37.904172: Epoch time: 17.95 s +2024-11-21 12:08:38.781190: +2024-11-21 12:08:38.781414: Epoch 261 +2024-11-21 12:08:38.781529: Current learning rate: 0.00971 +2024-11-21 12:08:57.498670: train_loss -0.7375 +2024-11-21 12:08:57.513154: val_loss -0.7418 +2024-11-21 12:08:57.513324: Pseudo dice [0.8452] +2024-11-21 12:08:57.513419: Epoch time: 18.72 s +2024-11-21 12:08:58.316774: +2024-11-21 12:08:58.316970: Epoch 262 +2024-11-21 12:08:58.317089: Current learning rate: 0.0097 +2024-11-21 12:09:16.587104: train_loss -0.7391 +2024-11-21 12:09:16.589071: val_loss -0.7509 +2024-11-21 12:09:16.589183: Pseudo dice [0.8341] +2024-11-21 12:09:16.589276: Epoch time: 18.27 s +2024-11-21 12:09:17.409554: +2024-11-21 12:09:17.409770: Epoch 263 +2024-11-21 12:09:17.409892: Current learning rate: 0.0097 +2024-11-21 12:09:35.870367: train_loss -0.7421 +2024-11-21 12:09:35.905616: val_loss -0.7459 +2024-11-21 12:09:35.905773: Pseudo dice [0.8238] +2024-11-21 12:09:35.905869: Epoch time: 18.46 s +2024-11-21 12:09:36.861124: +2024-11-21 12:09:36.861319: Epoch 264 +2024-11-21 12:09:36.861444: Current learning rate: 0.0097 +2024-11-21 12:09:55.591973: train_loss -0.7578 +2024-11-21 12:09:55.605767: val_loss -0.7648 +2024-11-21 12:09:55.605890: Pseudo dice [0.8574] +2024-11-21 12:09:55.605992: Epoch time: 18.73 s +2024-11-21 12:09:56.550109: +2024-11-21 12:09:56.550310: Epoch 265 +2024-11-21 12:09:56.550426: Current learning rate: 0.0097 +2024-11-21 12:10:16.153247: train_loss -0.7545 +2024-11-21 12:10:16.160393: val_loss -0.7431 +2024-11-21 12:10:16.160523: Pseudo dice [0.8435] +2024-11-21 12:10:16.160606: Epoch time: 19.6 s +2024-11-21 12:10:17.108245: +2024-11-21 12:10:17.108450: Epoch 266 +2024-11-21 12:10:17.108578: Current learning rate: 0.0097 +2024-11-21 12:10:36.004268: train_loss -0.7458 +2024-11-21 12:10:36.017395: val_loss -0.7576 +2024-11-21 12:10:36.017537: Pseudo dice [0.847] +2024-11-21 12:10:36.017807: Epoch time: 18.9 s +2024-11-21 12:10:36.839197: +2024-11-21 12:10:36.839391: Epoch 267 +2024-11-21 12:10:36.839520: Current learning rate: 0.0097 +2024-11-21 12:10:56.486755: train_loss -0.7453 +2024-11-21 12:10:56.514019: val_loss -0.7303 +2024-11-21 12:10:56.514223: Pseudo dice [0.8337] +2024-11-21 12:10:56.514331: Epoch time: 19.65 s +2024-11-21 12:10:57.703303: +2024-11-21 12:10:57.703521: Epoch 268 +2024-11-21 12:10:57.703664: Current learning rate: 0.0097 +2024-11-21 12:11:17.006413: train_loss -0.7358 +2024-11-21 12:11:17.013958: val_loss -0.7461 +2024-11-21 12:11:17.014081: Pseudo dice [0.8356] +2024-11-21 12:11:17.014174: Epoch time: 19.3 s +2024-11-21 12:11:18.047642: +2024-11-21 12:11:18.047857: Epoch 269 +2024-11-21 12:11:18.047977: Current learning rate: 0.0097 +2024-11-21 12:11:36.438134: train_loss -0.7437 +2024-11-21 12:11:36.463971: val_loss -0.7554 +2024-11-21 12:11:36.464141: Pseudo dice [0.8344] +2024-11-21 12:11:36.464237: Epoch time: 18.39 s +2024-11-21 12:11:37.302138: +2024-11-21 12:11:37.302367: Epoch 270 +2024-11-21 12:11:37.302496: Current learning rate: 0.0097 +2024-11-21 12:11:56.056268: train_loss -0.747 +2024-11-21 12:11:56.080646: val_loss -0.7425 +2024-11-21 12:11:56.080836: Pseudo dice [0.8343] +2024-11-21 12:11:56.080954: Epoch time: 18.75 s +2024-11-21 12:11:56.932436: +2024-11-21 12:11:56.932643: Epoch 271 +2024-11-21 12:11:56.932758: Current learning rate: 0.00969 +2024-11-21 12:12:16.911670: train_loss -0.7471 +2024-11-21 12:12:16.919980: val_loss -0.7102 +2024-11-21 12:12:16.920116: Pseudo dice [0.8288] +2024-11-21 12:12:16.920200: Epoch time: 19.98 s +2024-11-21 12:12:17.738689: +2024-11-21 12:12:17.738883: Epoch 272 +2024-11-21 12:12:17.739000: Current learning rate: 0.00969 +2024-11-21 12:12:36.189040: train_loss -0.758 +2024-11-21 12:12:36.197202: val_loss -0.7648 +2024-11-21 12:12:36.197358: Pseudo dice [0.8385] +2024-11-21 12:12:36.197443: Epoch time: 18.45 s +2024-11-21 12:12:37.000158: +2024-11-21 12:12:37.000393: Epoch 273 +2024-11-21 12:12:37.000522: Current learning rate: 0.00969 +2024-11-21 12:12:56.710198: train_loss -0.7635 +2024-11-21 12:12:56.716655: val_loss -0.7729 +2024-11-21 12:12:56.716802: Pseudo dice [0.8422] +2024-11-21 12:12:56.716922: Epoch time: 19.71 s +2024-11-21 12:12:57.537965: +2024-11-21 12:12:57.538173: Epoch 274 +2024-11-21 12:12:57.538318: Current learning rate: 0.00969 +2024-11-21 12:13:16.380064: train_loss -0.7459 +2024-11-21 12:13:16.405470: val_loss -0.7492 +2024-11-21 12:13:16.405673: Pseudo dice [0.8426] +2024-11-21 12:13:16.405792: Epoch time: 18.84 s +2024-11-21 12:13:17.266463: +2024-11-21 12:13:17.266664: Epoch 275 +2024-11-21 12:13:17.266802: Current learning rate: 0.00969 +2024-11-21 12:13:36.133305: train_loss -0.7524 +2024-11-21 12:13:36.147103: val_loss -0.722 +2024-11-21 12:13:36.147254: Pseudo dice [0.8253] +2024-11-21 12:13:36.147354: Epoch time: 18.87 s +2024-11-21 12:13:36.952241: +2024-11-21 12:13:36.952432: Epoch 276 +2024-11-21 12:13:36.956437: Current learning rate: 0.00969 +2024-11-21 12:13:56.481615: train_loss -0.7432 +2024-11-21 12:13:56.491944: val_loss -0.7635 +2024-11-21 12:13:56.492097: Pseudo dice [0.8422] +2024-11-21 12:13:56.492179: Epoch time: 19.53 s +2024-11-21 12:13:57.444808: +2024-11-21 12:13:57.444992: Epoch 277 +2024-11-21 12:13:57.445116: Current learning rate: 0.00969 +2024-11-21 12:14:16.388393: train_loss -0.7513 +2024-11-21 12:14:16.392030: val_loss -0.752 +2024-11-21 12:14:16.392179: Pseudo dice [0.8393] +2024-11-21 12:14:16.392294: Epoch time: 18.94 s +2024-11-21 12:14:17.320132: +2024-11-21 12:14:17.320307: Epoch 278 +2024-11-21 12:14:17.320458: Current learning rate: 0.00969 +2024-11-21 12:14:37.053367: train_loss -0.7455 +2024-11-21 12:14:37.060701: val_loss -0.7577 +2024-11-21 12:14:37.060852: Pseudo dice [0.851] +2024-11-21 12:14:37.060955: Epoch time: 19.73 s +2024-11-21 12:14:37.877439: +2024-11-21 12:14:37.877626: Epoch 279 +2024-11-21 12:14:37.877770: Current learning rate: 0.00969 +2024-11-21 12:14:56.504318: train_loss -0.7482 +2024-11-21 12:14:56.511974: val_loss -0.749 +2024-11-21 12:14:56.512109: Pseudo dice [0.8515] +2024-11-21 12:14:56.512218: Epoch time: 18.63 s +2024-11-21 12:14:57.718479: +2024-11-21 12:14:57.718668: Epoch 280 +2024-11-21 12:14:57.718787: Current learning rate: 0.00968 +2024-11-21 12:15:16.986349: train_loss -0.7487 +2024-11-21 12:15:16.994114: val_loss -0.7487 +2024-11-21 12:15:16.994227: Pseudo dice [0.8482] +2024-11-21 12:15:16.994324: Epoch time: 19.27 s +2024-11-21 12:15:17.911256: +2024-11-21 12:15:17.911470: Epoch 281 +2024-11-21 12:15:17.911593: Current learning rate: 0.00968 +2024-11-21 12:15:36.339227: train_loss -0.7463 +2024-11-21 12:15:36.344989: val_loss -0.7839 +2024-11-21 12:15:36.345123: Pseudo dice [0.8466] +2024-11-21 12:15:36.345217: Epoch time: 18.43 s +2024-11-21 12:15:37.193106: +2024-11-21 12:15:37.193295: Epoch 282 +2024-11-21 12:15:37.193417: Current learning rate: 0.00968 +2024-11-21 12:15:56.573443: train_loss -0.7522 +2024-11-21 12:15:56.579113: val_loss -0.761 +2024-11-21 12:15:56.579318: Pseudo dice [0.8422] +2024-11-21 12:15:56.579417: Epoch time: 19.38 s +2024-11-21 12:15:57.382847: +2024-11-21 12:15:57.383063: Epoch 283 +2024-11-21 12:15:57.383194: Current learning rate: 0.00968 +2024-11-21 12:16:15.647157: train_loss -0.7532 +2024-11-21 12:16:15.651680: val_loss -0.7639 +2024-11-21 12:16:15.651814: Pseudo dice [0.8581] +2024-11-21 12:16:15.651905: Epoch time: 18.27 s +2024-11-21 12:16:16.587366: +2024-11-21 12:16:16.587608: Epoch 284 +2024-11-21 12:16:16.587754: Current learning rate: 0.00968 +2024-11-21 12:16:35.878383: train_loss -0.7557 +2024-11-21 12:16:35.889142: val_loss -0.7495 +2024-11-21 12:16:35.889267: Pseudo dice [0.8307] +2024-11-21 12:16:35.889357: Epoch time: 19.29 s +2024-11-21 12:16:36.726149: +2024-11-21 12:16:36.726363: Epoch 285 +2024-11-21 12:16:36.726506: Current learning rate: 0.00968 +2024-11-21 12:16:56.402502: train_loss -0.7426 +2024-11-21 12:16:56.412150: val_loss -0.7738 +2024-11-21 12:16:56.412310: Pseudo dice [0.8505] +2024-11-21 12:16:56.412431: Epoch time: 19.68 s +2024-11-21 12:16:57.364817: +2024-11-21 12:16:57.365010: Epoch 286 +2024-11-21 12:16:57.365143: Current learning rate: 0.00968 +2024-11-21 12:17:16.881946: train_loss -0.747 +2024-11-21 12:17:16.891570: val_loss -0.7627 +2024-11-21 12:17:16.891725: Pseudo dice [0.8503] +2024-11-21 12:17:16.891808: Epoch time: 19.52 s +2024-11-21 12:17:17.995539: +2024-11-21 12:17:17.995755: Epoch 287 +2024-11-21 12:17:17.995872: Current learning rate: 0.00968 +2024-11-21 12:17:36.605757: train_loss -0.7476 +2024-11-21 12:17:36.610987: val_loss -0.7616 +2024-11-21 12:17:36.611135: Pseudo dice [0.8467] +2024-11-21 12:17:36.611244: Epoch time: 18.61 s +2024-11-21 12:17:37.421116: +2024-11-21 12:17:37.421301: Epoch 288 +2024-11-21 12:17:37.421438: Current learning rate: 0.00968 +2024-11-21 12:17:56.853399: train_loss -0.7454 +2024-11-21 12:17:56.856616: val_loss -0.7591 +2024-11-21 12:17:56.856768: Pseudo dice [0.8422] +2024-11-21 12:17:56.856864: Epoch time: 19.43 s +2024-11-21 12:17:57.661672: +2024-11-21 12:17:57.661870: Epoch 289 +2024-11-21 12:17:57.661989: Current learning rate: 0.00967 +2024-11-21 12:18:16.467860: train_loss -0.7404 +2024-11-21 12:18:16.472766: val_loss -0.7321 +2024-11-21 12:18:16.472884: Pseudo dice [0.8233] +2024-11-21 12:18:16.472998: Epoch time: 18.8 s +2024-11-21 12:18:17.448049: +2024-11-21 12:18:17.448232: Epoch 290 +2024-11-21 12:18:17.448360: Current learning rate: 0.00967 +2024-11-21 12:18:36.380586: train_loss -0.7494 +2024-11-21 12:18:36.393156: val_loss -0.7566 +2024-11-21 12:18:36.393286: Pseudo dice [0.8477] +2024-11-21 12:18:36.393381: Epoch time: 18.93 s +2024-11-21 12:18:37.607034: +2024-11-21 12:18:37.607225: Epoch 291 +2024-11-21 12:18:37.607347: Current learning rate: 0.00967 +2024-11-21 12:18:55.785312: train_loss -0.7444 +2024-11-21 12:18:55.799905: val_loss -0.7398 +2024-11-21 12:18:55.800051: Pseudo dice [0.8428] +2024-11-21 12:18:55.800145: Epoch time: 18.18 s +2024-11-21 12:18:56.637812: +2024-11-21 12:18:56.638020: Epoch 292 +2024-11-21 12:18:56.638149: Current learning rate: 0.00967 +2024-11-21 12:19:15.750072: train_loss -0.7482 +2024-11-21 12:19:15.758459: val_loss -0.7571 +2024-11-21 12:19:15.758781: Pseudo dice [0.8412] +2024-11-21 12:19:15.759199: Epoch time: 19.11 s +2024-11-21 12:19:16.732417: +2024-11-21 12:19:16.732668: Epoch 293 +2024-11-21 12:19:16.732807: Current learning rate: 0.00967 +2024-11-21 12:19:35.332515: train_loss -0.7513 +2024-11-21 12:19:35.336384: val_loss -0.7342 +2024-11-21 12:19:35.336491: Pseudo dice [0.8356] +2024-11-21 12:19:35.336576: Epoch time: 18.6 s +2024-11-21 12:19:36.138342: +2024-11-21 12:19:36.138540: Epoch 294 +2024-11-21 12:19:36.138686: Current learning rate: 0.00967 +2024-11-21 12:19:54.914738: train_loss -0.7538 +2024-11-21 12:19:54.920529: val_loss -0.7402 +2024-11-21 12:19:54.920679: Pseudo dice [0.8293] +2024-11-21 12:19:54.920768: Epoch time: 18.78 s +2024-11-21 12:19:55.751798: +2024-11-21 12:19:55.751998: Epoch 295 +2024-11-21 12:19:55.752120: Current learning rate: 0.00967 +2024-11-21 12:20:14.402962: train_loss -0.7521 +2024-11-21 12:20:14.405863: val_loss -0.7685 +2024-11-21 12:20:14.405977: Pseudo dice [0.8385] +2024-11-21 12:20:14.406080: Epoch time: 18.65 s +2024-11-21 12:20:15.209987: +2024-11-21 12:20:15.210175: Epoch 296 +2024-11-21 12:20:15.210291: Current learning rate: 0.00967 +2024-11-21 12:20:34.163352: train_loss -0.7349 +2024-11-21 12:20:34.167686: val_loss -0.7619 +2024-11-21 12:20:34.167809: Pseudo dice [0.8353] +2024-11-21 12:20:34.167898: Epoch time: 18.95 s +2024-11-21 12:20:34.984145: +2024-11-21 12:20:34.984347: Epoch 297 +2024-11-21 12:20:34.984483: Current learning rate: 0.00967 +2024-11-21 12:20:53.102777: train_loss -0.7277 +2024-11-21 12:20:53.114233: val_loss -0.7455 +2024-11-21 12:20:53.114375: Pseudo dice [0.8454] +2024-11-21 12:20:53.114465: Epoch time: 18.12 s +2024-11-21 12:20:54.045940: +2024-11-21 12:20:54.046128: Epoch 298 +2024-11-21 12:20:54.046252: Current learning rate: 0.00966 +2024-11-21 12:21:13.989558: train_loss -0.7526 +2024-11-21 12:21:14.001295: val_loss -0.7609 +2024-11-21 12:21:14.001431: Pseudo dice [0.8397] +2024-11-21 12:21:14.001538: Epoch time: 19.94 s +2024-11-21 12:21:14.883342: +2024-11-21 12:21:14.883528: Epoch 299 +2024-11-21 12:21:14.883664: Current learning rate: 0.00966 +2024-11-21 12:21:33.772235: train_loss -0.7309 +2024-11-21 12:21:33.776224: val_loss -0.7507 +2024-11-21 12:21:33.776354: Pseudo dice [0.845] +2024-11-21 12:21:33.776454: Epoch time: 18.89 s +2024-11-21 12:21:34.865877: +2024-11-21 12:21:34.866088: Epoch 300 +2024-11-21 12:21:34.866205: Current learning rate: 0.00966 +2024-11-21 12:21:53.797416: train_loss -0.7466 +2024-11-21 12:21:53.801373: val_loss -0.7567 +2024-11-21 12:21:53.801485: Pseudo dice [0.8529] +2024-11-21 12:21:53.801580: Epoch time: 18.93 s +2024-11-21 12:21:54.717639: +2024-11-21 12:21:54.717830: Epoch 301 +2024-11-21 12:21:54.717947: Current learning rate: 0.00966 +2024-11-21 12:22:13.225465: train_loss -0.7524 +2024-11-21 12:22:13.230892: val_loss -0.7446 +2024-11-21 12:22:13.231255: Pseudo dice [0.845] +2024-11-21 12:22:13.231352: Epoch time: 18.51 s +2024-11-21 12:22:14.559608: +2024-11-21 12:22:14.559844: Epoch 302 +2024-11-21 12:22:14.559973: Current learning rate: 0.00966 +2024-11-21 12:22:33.084203: train_loss -0.7565 +2024-11-21 12:22:33.087577: val_loss -0.7363 +2024-11-21 12:22:33.087717: Pseudo dice [0.8377] +2024-11-21 12:22:33.087811: Epoch time: 18.53 s +2024-11-21 12:22:33.909399: +2024-11-21 12:22:33.909611: Epoch 303 +2024-11-21 12:22:33.909721: Current learning rate: 0.00966 +2024-11-21 12:22:52.124699: train_loss -0.7475 +2024-11-21 12:22:52.133715: val_loss -0.7726 +2024-11-21 12:22:52.133861: Pseudo dice [0.8484] +2024-11-21 12:22:52.133972: Epoch time: 18.22 s +2024-11-21 12:22:52.980462: +2024-11-21 12:22:52.980696: Epoch 304 +2024-11-21 12:22:52.980832: Current learning rate: 0.00966 +2024-11-21 12:23:12.372461: train_loss -0.7411 +2024-11-21 12:23:12.381377: val_loss -0.7423 +2024-11-21 12:23:12.381506: Pseudo dice [0.8388] +2024-11-21 12:23:12.381610: Epoch time: 19.39 s +2024-11-21 12:23:13.196794: +2024-11-21 12:23:13.197012: Epoch 305 +2024-11-21 12:23:13.197135: Current learning rate: 0.00966 +2024-11-21 12:23:31.954511: train_loss -0.7513 +2024-11-21 12:23:31.964164: val_loss -0.7467 +2024-11-21 12:23:31.964306: Pseudo dice [0.8381] +2024-11-21 12:23:31.964411: Epoch time: 18.76 s +2024-11-21 12:23:32.974668: +2024-11-21 12:23:32.974884: Epoch 306 +2024-11-21 12:23:32.975011: Current learning rate: 0.00966 +2024-11-21 12:23:52.094348: train_loss -0.7536 +2024-11-21 12:23:52.112120: val_loss -0.7567 +2024-11-21 12:23:52.112254: Pseudo dice [0.8301] +2024-11-21 12:23:52.112355: Epoch time: 19.12 s +2024-11-21 12:23:53.181545: +2024-11-21 12:23:53.181743: Epoch 307 +2024-11-21 12:23:53.181863: Current learning rate: 0.00965 +2024-11-21 12:24:12.160031: train_loss -0.7531 +2024-11-21 12:24:12.166569: val_loss -0.7533 +2024-11-21 12:24:12.166711: Pseudo dice [0.8423] +2024-11-21 12:24:12.166843: Epoch time: 18.98 s +2024-11-21 12:24:12.980518: +2024-11-21 12:24:12.980709: Epoch 308 +2024-11-21 12:24:12.980821: Current learning rate: 0.00965 +2024-11-21 12:24:31.986055: train_loss -0.7543 +2024-11-21 12:24:31.994152: val_loss -0.734 +2024-11-21 12:24:31.994288: Pseudo dice [0.8341] +2024-11-21 12:24:31.994392: Epoch time: 19.01 s +2024-11-21 12:24:32.835569: +2024-11-21 12:24:32.835750: Epoch 309 +2024-11-21 12:24:32.835864: Current learning rate: 0.00965 +2024-11-21 12:24:51.969002: train_loss -0.756 +2024-11-21 12:24:51.971379: val_loss -0.7387 +2024-11-21 12:24:51.971481: Pseudo dice [0.8324] +2024-11-21 12:24:51.971571: Epoch time: 19.13 s +2024-11-21 12:24:52.775410: +2024-11-21 12:24:52.775601: Epoch 310 +2024-11-21 12:24:52.775718: Current learning rate: 0.00965 +2024-11-21 12:25:12.352417: train_loss -0.7491 +2024-11-21 12:25:12.372979: val_loss -0.7485 +2024-11-21 12:25:12.373134: Pseudo dice [0.8535] +2024-11-21 12:25:12.373240: Epoch time: 19.58 s +2024-11-21 12:25:13.257735: +2024-11-21 12:25:13.257972: Epoch 311 +2024-11-21 12:25:13.258099: Current learning rate: 0.00965 +2024-11-21 12:25:32.687912: train_loss -0.7502 +2024-11-21 12:25:32.689701: val_loss -0.7778 +2024-11-21 12:25:32.689814: Pseudo dice [0.8416] +2024-11-21 12:25:32.689909: Epoch time: 19.43 s +2024-11-21 12:25:33.477354: +2024-11-21 12:25:33.477530: Epoch 312 +2024-11-21 12:25:33.477633: Current learning rate: 0.00965 +2024-11-21 12:25:52.601828: train_loss -0.7481 +2024-11-21 12:25:52.610044: val_loss -0.7352 +2024-11-21 12:25:52.610193: Pseudo dice [0.8266] +2024-11-21 12:25:52.610291: Epoch time: 19.13 s +2024-11-21 12:25:53.835378: +2024-11-21 12:25:53.835582: Epoch 313 +2024-11-21 12:25:53.835743: Current learning rate: 0.00965 +2024-11-21 12:26:13.071278: train_loss -0.7387 +2024-11-21 12:26:13.084955: val_loss -0.7464 +2024-11-21 12:26:13.085105: Pseudo dice [0.8476] +2024-11-21 12:26:13.085200: Epoch time: 19.24 s +2024-11-21 12:26:14.018584: +2024-11-21 12:26:14.018819: Epoch 314 +2024-11-21 12:26:14.018951: Current learning rate: 0.00965 +2024-11-21 12:26:33.126510: train_loss -0.7406 +2024-11-21 12:26:33.136199: val_loss -0.7617 +2024-11-21 12:26:33.136319: Pseudo dice [0.8478] +2024-11-21 12:26:33.136415: Epoch time: 19.11 s +2024-11-21 12:26:33.998760: +2024-11-21 12:26:33.998961: Epoch 315 +2024-11-21 12:26:33.999107: Current learning rate: 0.00964 +2024-11-21 12:26:52.409608: train_loss -0.7519 +2024-11-21 12:26:52.420751: val_loss -0.759 +2024-11-21 12:26:52.420907: Pseudo dice [0.8408] +2024-11-21 12:26:52.421001: Epoch time: 18.41 s +2024-11-21 12:26:53.417050: +2024-11-21 12:26:53.417289: Epoch 316 +2024-11-21 12:26:53.417414: Current learning rate: 0.00964 +2024-11-21 12:27:11.731955: train_loss -0.7588 +2024-11-21 12:27:11.736354: val_loss -0.7277 +2024-11-21 12:27:11.736484: Pseudo dice [0.8447] +2024-11-21 12:27:11.736573: Epoch time: 18.32 s +2024-11-21 12:27:12.588997: +2024-11-21 12:27:12.589218: Epoch 317 +2024-11-21 12:27:12.589330: Current learning rate: 0.00964 +2024-11-21 12:27:31.623571: train_loss -0.7549 +2024-11-21 12:27:31.629639: val_loss -0.7346 +2024-11-21 12:27:31.629763: Pseudo dice [0.8312] +2024-11-21 12:27:31.629853: Epoch time: 19.04 s +2024-11-21 12:27:32.435461: +2024-11-21 12:27:32.435708: Epoch 318 +2024-11-21 12:27:32.435829: Current learning rate: 0.00964 +2024-11-21 12:27:50.705816: train_loss -0.758 +2024-11-21 12:27:50.716333: val_loss -0.7503 +2024-11-21 12:27:50.716462: Pseudo dice [0.8378] +2024-11-21 12:27:50.717275: Epoch time: 18.27 s +2024-11-21 12:27:51.650038: +2024-11-21 12:27:51.650257: Epoch 319 +2024-11-21 12:27:51.650372: Current learning rate: 0.00964 +2024-11-21 12:28:10.682375: train_loss -0.7558 +2024-11-21 12:28:10.687332: val_loss -0.7541 +2024-11-21 12:28:10.687486: Pseudo dice [0.8407] +2024-11-21 12:28:10.687587: Epoch time: 19.03 s +2024-11-21 12:28:11.616586: +2024-11-21 12:28:11.616790: Epoch 320 +2024-11-21 12:28:11.616910: Current learning rate: 0.00964 +2024-11-21 12:28:30.946910: train_loss -0.739 +2024-11-21 12:28:30.950345: val_loss -0.7658 +2024-11-21 12:28:30.950454: Pseudo dice [0.8425] +2024-11-21 12:28:30.950590: Epoch time: 19.33 s +2024-11-21 12:28:31.750958: +2024-11-21 12:28:31.751166: Epoch 321 +2024-11-21 12:28:31.751288: Current learning rate: 0.00964 +2024-11-21 12:28:51.069593: train_loss -0.746 +2024-11-21 12:28:51.079777: val_loss -0.7549 +2024-11-21 12:28:51.079915: Pseudo dice [0.8432] +2024-11-21 12:28:51.080022: Epoch time: 19.32 s +2024-11-21 12:28:51.884035: +2024-11-21 12:28:51.884215: Epoch 322 +2024-11-21 12:28:51.884366: Current learning rate: 0.00964 +2024-11-21 12:29:11.128872: train_loss -0.7541 +2024-11-21 12:29:11.132275: val_loss -0.7466 +2024-11-21 12:29:11.132374: Pseudo dice [0.8377] +2024-11-21 12:29:11.132486: Epoch time: 19.25 s +2024-11-21 12:29:11.938044: +2024-11-21 12:29:11.938241: Epoch 323 +2024-11-21 12:29:11.938364: Current learning rate: 0.00964 +2024-11-21 12:29:31.335487: train_loss -0.7727 +2024-11-21 12:29:31.339484: val_loss -0.7431 +2024-11-21 12:29:31.339576: Pseudo dice [0.8414] +2024-11-21 12:29:31.339660: Epoch time: 19.4 s +2024-11-21 12:29:32.531931: +2024-11-21 12:29:32.532145: Epoch 324 +2024-11-21 12:29:32.532273: Current learning rate: 0.00963 +2024-11-21 12:29:51.881823: train_loss -0.7603 +2024-11-21 12:29:51.886314: val_loss -0.7374 +2024-11-21 12:29:51.886446: Pseudo dice [0.8388] +2024-11-21 12:29:51.886564: Epoch time: 19.35 s +2024-11-21 12:29:52.712925: +2024-11-21 12:29:52.713172: Epoch 325 +2024-11-21 12:29:52.713288: Current learning rate: 0.00963 +2024-11-21 12:30:11.629666: train_loss -0.7451 +2024-11-21 12:30:11.633526: val_loss -0.7592 +2024-11-21 12:30:11.633667: Pseudo dice [0.8352] +2024-11-21 12:30:11.633762: Epoch time: 18.91 s +2024-11-21 12:30:12.612354: +2024-11-21 12:30:12.612584: Epoch 326 +2024-11-21 12:30:12.612709: Current learning rate: 0.00963 +2024-11-21 12:30:31.051580: train_loss -0.7484 +2024-11-21 12:30:31.067824: val_loss -0.7316 +2024-11-21 12:30:31.067960: Pseudo dice [0.8459] +2024-11-21 12:30:31.068056: Epoch time: 18.44 s +2024-11-21 12:30:31.985827: +2024-11-21 12:30:31.986027: Epoch 327 +2024-11-21 12:30:31.986634: Current learning rate: 0.00963 +2024-11-21 12:30:51.324340: train_loss -0.7554 +2024-11-21 12:30:51.330178: val_loss -0.7523 +2024-11-21 12:30:51.330322: Pseudo dice [0.828] +2024-11-21 12:30:51.330410: Epoch time: 19.34 s +2024-11-21 12:30:52.133864: +2024-11-21 12:30:52.134091: Epoch 328 +2024-11-21 12:30:52.134199: Current learning rate: 0.00963 +2024-11-21 12:31:10.275093: train_loss -0.7528 +2024-11-21 12:31:10.278976: val_loss -0.7441 +2024-11-21 12:31:10.279090: Pseudo dice [0.8448] +2024-11-21 12:31:10.279261: Epoch time: 18.14 s +2024-11-21 12:31:11.160505: +2024-11-21 12:31:11.160698: Epoch 329 +2024-11-21 12:31:11.160849: Current learning rate: 0.00963 +2024-11-21 12:31:29.029969: train_loss -0.7532 +2024-11-21 12:31:29.036639: val_loss -0.7759 +2024-11-21 12:31:29.036791: Pseudo dice [0.8507] +2024-11-21 12:31:29.036888: Epoch time: 17.87 s +2024-11-21 12:31:29.880146: +2024-11-21 12:31:29.880341: Epoch 330 +2024-11-21 12:31:29.880468: Current learning rate: 0.00963 +2024-11-21 12:31:48.447274: train_loss -0.7571 +2024-11-21 12:31:48.451429: val_loss -0.7587 +2024-11-21 12:31:48.451577: Pseudo dice [0.8313] +2024-11-21 12:31:48.451659: Epoch time: 18.57 s +2024-11-21 12:31:49.259110: +2024-11-21 12:31:49.259288: Epoch 331 +2024-11-21 12:31:49.259413: Current learning rate: 0.00963 +2024-11-21 12:32:07.947308: train_loss -0.7614 +2024-11-21 12:32:07.952668: val_loss -0.7509 +2024-11-21 12:32:07.952809: Pseudo dice [0.8467] +2024-11-21 12:32:07.952895: Epoch time: 18.69 s +2024-11-21 12:32:08.760120: +2024-11-21 12:32:08.760321: Epoch 332 +2024-11-21 12:32:08.760456: Current learning rate: 0.00963 +2024-11-21 12:32:27.398424: train_loss -0.7496 +2024-11-21 12:32:27.407334: val_loss -0.7614 +2024-11-21 12:32:27.407486: Pseudo dice [0.8481] +2024-11-21 12:32:27.407579: Epoch time: 18.64 s +2024-11-21 12:32:28.274922: +2024-11-21 12:32:28.275133: Epoch 333 +2024-11-21 12:32:28.275279: Current learning rate: 0.00962 +2024-11-21 12:32:47.187822: train_loss -0.7457 +2024-11-21 12:32:47.194874: val_loss -0.7656 +2024-11-21 12:32:47.195012: Pseudo dice [0.8236] +2024-11-21 12:32:47.195122: Epoch time: 18.91 s +2024-11-21 12:32:48.105862: +2024-11-21 12:32:48.106048: Epoch 334 +2024-11-21 12:32:48.106182: Current learning rate: 0.00962 +2024-11-21 12:33:07.961723: train_loss -0.7359 +2024-11-21 12:33:07.969329: val_loss -0.7526 +2024-11-21 12:33:07.969456: Pseudo dice [0.8299] +2024-11-21 12:33:07.969556: Epoch time: 19.86 s +2024-11-21 12:33:09.185848: +2024-11-21 12:33:09.186069: Epoch 335 +2024-11-21 12:33:09.186198: Current learning rate: 0.00962 +2024-11-21 12:33:28.461023: train_loss -0.7486 +2024-11-21 12:33:28.472213: val_loss -0.7669 +2024-11-21 12:33:28.472351: Pseudo dice [0.8441] +2024-11-21 12:33:28.472453: Epoch time: 19.28 s +2024-11-21 12:33:29.318243: +2024-11-21 12:33:29.318443: Epoch 336 +2024-11-21 12:33:29.318564: Current learning rate: 0.00962 +2024-11-21 12:33:49.026236: train_loss -0.7445 +2024-11-21 12:33:49.031432: val_loss -0.7464 +2024-11-21 12:33:49.031535: Pseudo dice [0.8516] +2024-11-21 12:33:49.031635: Epoch time: 19.71 s +2024-11-21 12:33:49.841091: +2024-11-21 12:33:49.841294: Epoch 337 +2024-11-21 12:33:49.841432: Current learning rate: 0.00962 +2024-11-21 12:34:09.380319: train_loss -0.7571 +2024-11-21 12:34:09.387208: val_loss -0.7685 +2024-11-21 12:34:09.387344: Pseudo dice [0.8565] +2024-11-21 12:34:09.387451: Epoch time: 19.54 s +2024-11-21 12:34:10.226413: +2024-11-21 12:34:10.226621: Epoch 338 +2024-11-21 12:34:10.226737: Current learning rate: 0.00962 +2024-11-21 12:34:29.061855: train_loss -0.7606 +2024-11-21 12:34:29.075108: val_loss -0.7428 +2024-11-21 12:34:29.075262: Pseudo dice [0.8517] +2024-11-21 12:34:29.075351: Epoch time: 18.84 s +2024-11-21 12:34:29.935011: +2024-11-21 12:34:29.935240: Epoch 339 +2024-11-21 12:34:29.935374: Current learning rate: 0.00962 +2024-11-21 12:34:49.289102: train_loss -0.7314 +2024-11-21 12:34:49.313005: val_loss -0.762 +2024-11-21 12:34:49.313148: Pseudo dice [0.8449] +2024-11-21 12:34:49.313240: Epoch time: 19.35 s +2024-11-21 12:34:50.310913: +2024-11-21 12:34:50.311123: Epoch 340 +2024-11-21 12:34:50.311247: Current learning rate: 0.00962 +2024-11-21 12:35:09.196638: train_loss -0.7462 +2024-11-21 12:35:09.199976: val_loss -0.7681 +2024-11-21 12:35:09.200107: Pseudo dice [0.8395] +2024-11-21 12:35:09.200198: Epoch time: 18.89 s +2024-11-21 12:35:10.016438: +2024-11-21 12:35:10.016657: Epoch 341 +2024-11-21 12:35:10.016774: Current learning rate: 0.00962 +2024-11-21 12:35:30.149388: train_loss -0.7523 +2024-11-21 12:35:30.153934: val_loss -0.745 +2024-11-21 12:35:30.154071: Pseudo dice [0.8257] +2024-11-21 12:35:30.154159: Epoch time: 20.13 s +2024-11-21 12:35:31.089657: +2024-11-21 12:35:31.089879: Epoch 342 +2024-11-21 12:35:31.090018: Current learning rate: 0.00961 +2024-11-21 12:35:50.539090: train_loss -0.7591 +2024-11-21 12:35:50.548595: val_loss -0.7577 +2024-11-21 12:35:50.548737: Pseudo dice [0.8434] +2024-11-21 12:35:50.548828: Epoch time: 19.45 s +2024-11-21 12:35:51.591140: +2024-11-21 12:35:51.591331: Epoch 343 +2024-11-21 12:35:51.591458: Current learning rate: 0.00961 +2024-11-21 12:36:09.710048: train_loss -0.7606 +2024-11-21 12:36:09.714936: val_loss -0.7467 +2024-11-21 12:36:09.715096: Pseudo dice [0.8595] +2024-11-21 12:36:09.715188: Epoch time: 18.12 s +2024-11-21 12:36:10.591312: +2024-11-21 12:36:10.591542: Epoch 344 +2024-11-21 12:36:10.591661: Current learning rate: 0.00961 +2024-11-21 12:36:29.761262: train_loss -0.7464 +2024-11-21 12:36:29.764318: val_loss -0.7538 +2024-11-21 12:36:29.764428: Pseudo dice [0.8425] +2024-11-21 12:36:29.764722: Epoch time: 19.17 s +2024-11-21 12:36:30.581513: +2024-11-21 12:36:30.581715: Epoch 345 +2024-11-21 12:36:30.581862: Current learning rate: 0.00961 +2024-11-21 12:36:48.862893: train_loss -0.7586 +2024-11-21 12:36:48.869583: val_loss -0.7666 +2024-11-21 12:36:48.869695: Pseudo dice [0.8474] +2024-11-21 12:36:48.869788: Epoch time: 18.28 s +2024-11-21 12:36:50.071571: +2024-11-21 12:36:50.072013: Epoch 346 +2024-11-21 12:36:50.072162: Current learning rate: 0.00961 +2024-11-21 12:37:09.065816: train_loss -0.7549 +2024-11-21 12:37:09.071158: val_loss -0.7603 +2024-11-21 12:37:09.071283: Pseudo dice [0.8512] +2024-11-21 12:37:09.071363: Epoch time: 19.0 s +2024-11-21 12:37:09.922600: +2024-11-21 12:37:09.922837: Epoch 347 +2024-11-21 12:37:09.922974: Current learning rate: 0.00961 +2024-11-21 12:37:28.541565: train_loss -0.7502 +2024-11-21 12:37:28.550206: val_loss -0.7433 +2024-11-21 12:37:28.550395: Pseudo dice [0.8453] +2024-11-21 12:37:28.550512: Epoch time: 18.62 s +2024-11-21 12:37:29.371336: +2024-11-21 12:37:29.371546: Epoch 348 +2024-11-21 12:37:29.371684: Current learning rate: 0.00961 +2024-11-21 12:37:48.466290: train_loss -0.7601 +2024-11-21 12:37:48.486326: val_loss -0.7455 +2024-11-21 12:37:48.486486: Pseudo dice [0.8255] +2024-11-21 12:37:48.486583: Epoch time: 19.1 s +2024-11-21 12:37:49.306267: +2024-11-21 12:37:49.306464: Epoch 349 +2024-11-21 12:37:49.306597: Current learning rate: 0.00961 +2024-11-21 12:38:07.287337: train_loss -0.7411 +2024-11-21 12:38:07.296063: val_loss -0.7393 +2024-11-21 12:38:07.306554: Pseudo dice [0.8432] +2024-11-21 12:38:07.306737: Epoch time: 17.98 s +2024-11-21 12:38:08.502976: +2024-11-21 12:38:08.503195: Epoch 350 +2024-11-21 12:38:08.503334: Current learning rate: 0.00961 +2024-11-21 12:38:27.735532: train_loss -0.7407 +2024-11-21 12:38:27.755543: val_loss -0.755 +2024-11-21 12:38:27.755759: Pseudo dice [0.8433] +2024-11-21 12:38:27.755871: Epoch time: 19.23 s +2024-11-21 12:38:28.733597: +2024-11-21 12:38:28.733817: Epoch 351 +2024-11-21 12:38:28.733933: Current learning rate: 0.0096 +2024-11-21 12:38:47.502450: train_loss -0.7511 +2024-11-21 12:38:47.506583: val_loss -0.7574 +2024-11-21 12:38:47.506706: Pseudo dice [0.8363] +2024-11-21 12:38:47.506813: Epoch time: 18.77 s +2024-11-21 12:38:48.323298: +2024-11-21 12:38:48.323474: Epoch 352 +2024-11-21 12:38:48.323591: Current learning rate: 0.0096 +2024-11-21 12:39:07.787126: train_loss -0.7679 +2024-11-21 12:39:07.792564: val_loss -0.7513 +2024-11-21 12:39:07.792918: Pseudo dice [0.8393] +2024-11-21 12:39:07.793002: Epoch time: 19.46 s +2024-11-21 12:39:08.856972: +2024-11-21 12:39:08.857173: Epoch 353 +2024-11-21 12:39:08.857284: Current learning rate: 0.0096 +2024-11-21 12:39:27.950343: train_loss -0.7537 +2024-11-21 12:39:27.953108: val_loss -0.7425 +2024-11-21 12:39:27.953214: Pseudo dice [0.839] +2024-11-21 12:39:27.953298: Epoch time: 19.09 s +2024-11-21 12:39:28.763269: +2024-11-21 12:39:28.763510: Epoch 354 +2024-11-21 12:39:28.763642: Current learning rate: 0.0096 +2024-11-21 12:39:47.206053: train_loss -0.753 +2024-11-21 12:39:47.210604: val_loss -0.7305 +2024-11-21 12:39:47.210739: Pseudo dice [0.8277] +2024-11-21 12:39:47.210825: Epoch time: 18.44 s +2024-11-21 12:39:48.049176: +2024-11-21 12:39:48.049387: Epoch 355 +2024-11-21 12:39:48.049528: Current learning rate: 0.0096 +2024-11-21 12:40:06.814797: train_loss -0.7481 +2024-11-21 12:40:06.822350: val_loss -0.746 +2024-11-21 12:40:06.822570: Pseudo dice [0.8478] +2024-11-21 12:40:06.822662: Epoch time: 18.77 s +2024-11-21 12:40:08.171334: +2024-11-21 12:40:08.171536: Epoch 356 +2024-11-21 12:40:08.171657: Current learning rate: 0.0096 +2024-11-21 12:40:26.407632: train_loss -0.7508 +2024-11-21 12:40:26.412748: val_loss -0.7248 +2024-11-21 12:40:26.412855: Pseudo dice [0.842] +2024-11-21 12:40:26.412940: Epoch time: 18.24 s +2024-11-21 12:40:27.223803: +2024-11-21 12:40:27.224012: Epoch 357 +2024-11-21 12:40:27.224143: Current learning rate: 0.0096 +2024-11-21 12:40:46.504735: train_loss -0.7605 +2024-11-21 12:40:46.513711: val_loss -0.7531 +2024-11-21 12:40:46.513831: Pseudo dice [0.8493] +2024-11-21 12:40:46.513916: Epoch time: 19.28 s +2024-11-21 12:40:47.323213: +2024-11-21 12:40:47.323416: Epoch 358 +2024-11-21 12:40:47.323531: Current learning rate: 0.0096 +2024-11-21 12:41:06.145041: train_loss -0.7467 +2024-11-21 12:41:06.160227: val_loss -0.7398 +2024-11-21 12:41:06.160383: Pseudo dice [0.8499] +2024-11-21 12:41:06.160486: Epoch time: 18.82 s +2024-11-21 12:41:07.014576: +2024-11-21 12:41:07.014795: Epoch 359 +2024-11-21 12:41:07.014905: Current learning rate: 0.0096 +2024-11-21 12:41:24.657128: train_loss -0.7568 +2024-11-21 12:41:24.694775: val_loss -0.7722 +2024-11-21 12:41:24.694940: Pseudo dice [0.8494] +2024-11-21 12:41:24.695040: Epoch time: 17.64 s +2024-11-21 12:41:25.539703: +2024-11-21 12:41:25.539901: Epoch 360 +2024-11-21 12:41:25.540031: Current learning rate: 0.00959 +2024-11-21 12:41:44.237298: train_loss -0.7494 +2024-11-21 12:41:44.243805: val_loss -0.7809 +2024-11-21 12:41:44.243944: Pseudo dice [0.8519] +2024-11-21 12:41:44.244045: Epoch time: 18.7 s +2024-11-21 12:41:45.070492: +2024-11-21 12:41:45.070828: Epoch 361 +2024-11-21 12:41:45.070963: Current learning rate: 0.00959 +2024-11-21 12:42:04.803991: train_loss -0.7468 +2024-11-21 12:42:04.814790: val_loss -0.7502 +2024-11-21 12:42:04.814947: Pseudo dice [0.837] +2024-11-21 12:42:04.815051: Epoch time: 19.73 s +2024-11-21 12:42:05.656710: +2024-11-21 12:42:05.656901: Epoch 362 +2024-11-21 12:42:05.657033: Current learning rate: 0.00959 +2024-11-21 12:42:24.534659: train_loss -0.753 +2024-11-21 12:42:24.545848: val_loss -0.7672 +2024-11-21 12:42:24.545977: Pseudo dice [0.8325] +2024-11-21 12:42:24.546076: Epoch time: 18.88 s +2024-11-21 12:42:25.602155: +2024-11-21 12:42:25.602376: Epoch 363 +2024-11-21 12:42:25.602492: Current learning rate: 0.00959 +2024-11-21 12:42:44.416454: train_loss -0.7446 +2024-11-21 12:42:44.424439: val_loss -0.7382 +2024-11-21 12:42:44.424589: Pseudo dice [0.8315] +2024-11-21 12:42:44.424680: Epoch time: 18.82 s +2024-11-21 12:42:45.271034: +2024-11-21 12:42:45.271235: Epoch 364 +2024-11-21 12:42:45.271349: Current learning rate: 0.00959 +2024-11-21 12:43:03.756526: train_loss -0.7676 +2024-11-21 12:43:03.768545: val_loss -0.7672 +2024-11-21 12:43:03.768694: Pseudo dice [0.8436] +2024-11-21 12:43:03.768799: Epoch time: 18.49 s +2024-11-21 12:43:04.597315: +2024-11-21 12:43:04.597506: Epoch 365 +2024-11-21 12:43:04.597637: Current learning rate: 0.00959 +2024-11-21 12:43:22.744190: train_loss -0.7599 +2024-11-21 12:43:22.750955: val_loss -0.7419 +2024-11-21 12:43:22.751084: Pseudo dice [0.845] +2024-11-21 12:43:22.751174: Epoch time: 18.15 s +2024-11-21 12:43:23.554902: +2024-11-21 12:43:23.555093: Epoch 366 +2024-11-21 12:43:23.555208: Current learning rate: 0.00959 +2024-11-21 12:43:42.328709: train_loss -0.7575 +2024-11-21 12:43:42.336136: val_loss -0.7575 +2024-11-21 12:43:42.336251: Pseudo dice [0.8481] +2024-11-21 12:43:42.336355: Epoch time: 18.77 s +2024-11-21 12:43:43.652877: +2024-11-21 12:43:43.653066: Epoch 367 +2024-11-21 12:43:43.653177: Current learning rate: 0.00959 +2024-11-21 12:44:03.207948: train_loss -0.7488 +2024-11-21 12:44:03.215798: val_loss -0.7379 +2024-11-21 12:44:03.215938: Pseudo dice [0.8416] +2024-11-21 12:44:03.216025: Epoch time: 19.56 s +2024-11-21 12:44:04.039909: +2024-11-21 12:44:04.040132: Epoch 368 +2024-11-21 12:44:04.040246: Current learning rate: 0.00959 +2024-11-21 12:44:22.639848: train_loss -0.7543 +2024-11-21 12:44:22.655203: val_loss -0.7554 +2024-11-21 12:44:22.655377: Pseudo dice [0.8599] +2024-11-21 12:44:22.655498: Epoch time: 18.6 s +2024-11-21 12:44:23.614278: +2024-11-21 12:44:23.614541: Epoch 369 +2024-11-21 12:44:23.614677: Current learning rate: 0.00958 +2024-11-21 12:44:42.339142: train_loss -0.7515 +2024-11-21 12:44:42.364798: val_loss -0.7638 +2024-11-21 12:44:42.364922: Pseudo dice [0.8476] +2024-11-21 12:44:42.365026: Epoch time: 18.73 s +2024-11-21 12:44:43.416478: +2024-11-21 12:44:43.416695: Epoch 370 +2024-11-21 12:44:43.416807: Current learning rate: 0.00958 +2024-11-21 12:45:02.213216: train_loss -0.7592 +2024-11-21 12:45:02.219753: val_loss -0.7823 +2024-11-21 12:45:02.219898: Pseudo dice [0.846] +2024-11-21 12:45:02.220324: Epoch time: 18.8 s +2024-11-21 12:45:03.046731: +2024-11-21 12:45:03.046936: Epoch 371 +2024-11-21 12:45:03.047063: Current learning rate: 0.00958 +2024-11-21 12:45:21.747070: train_loss -0.7618 +2024-11-21 12:45:21.753185: val_loss -0.7586 +2024-11-21 12:45:21.753332: Pseudo dice [0.8459] +2024-11-21 12:45:21.753463: Epoch time: 18.7 s +2024-11-21 12:45:22.670279: +2024-11-21 12:45:22.670476: Epoch 372 +2024-11-21 12:45:22.670607: Current learning rate: 0.00958 +2024-11-21 12:45:41.497151: train_loss -0.7516 +2024-11-21 12:45:41.507087: val_loss -0.7247 +2024-11-21 12:45:41.507216: Pseudo dice [0.8376] +2024-11-21 12:45:41.507303: Epoch time: 18.83 s +2024-11-21 12:45:42.380373: +2024-11-21 12:45:42.380562: Epoch 373 +2024-11-21 12:45:42.380686: Current learning rate: 0.00958 +2024-11-21 12:46:01.331337: train_loss -0.7525 +2024-11-21 12:46:01.338283: val_loss -0.7436 +2024-11-21 12:46:01.338413: Pseudo dice [0.8296] +2024-11-21 12:46:01.338511: Epoch time: 18.95 s +2024-11-21 12:46:02.162880: +2024-11-21 12:46:02.163080: Epoch 374 +2024-11-21 12:46:02.163192: Current learning rate: 0.00958 +2024-11-21 12:46:21.250587: train_loss -0.7594 +2024-11-21 12:46:21.257936: val_loss -0.7585 +2024-11-21 12:46:21.258065: Pseudo dice [0.8427] +2024-11-21 12:46:21.258151: Epoch time: 19.09 s +2024-11-21 12:46:22.059139: +2024-11-21 12:46:22.059349: Epoch 375 +2024-11-21 12:46:22.059465: Current learning rate: 0.00958 +2024-11-21 12:46:40.726681: train_loss -0.7545 +2024-11-21 12:46:40.731695: val_loss -0.739 +2024-11-21 12:46:40.731816: Pseudo dice [0.8304] +2024-11-21 12:46:40.731899: Epoch time: 18.67 s +2024-11-21 12:46:41.592945: +2024-11-21 12:46:41.593158: Epoch 376 +2024-11-21 12:46:41.593298: Current learning rate: 0.00958 +2024-11-21 12:47:01.011259: train_loss -0.7499 +2024-11-21 12:47:01.016479: val_loss -0.7589 +2024-11-21 12:47:01.016614: Pseudo dice [0.8499] +2024-11-21 12:47:01.016731: Epoch time: 19.42 s +2024-11-21 12:47:01.821262: +2024-11-21 12:47:01.821461: Epoch 377 +2024-11-21 12:47:01.821576: Current learning rate: 0.00957 +2024-11-21 12:47:21.041325: train_loss -0.7612 +2024-11-21 12:47:21.051738: val_loss -0.7519 +2024-11-21 12:47:21.051876: Pseudo dice [0.8476] +2024-11-21 12:47:21.051984: Epoch time: 19.22 s +2024-11-21 12:47:22.316407: +2024-11-21 12:47:22.331734: Epoch 378 +2024-11-21 12:47:22.331869: Current learning rate: 0.00957 +2024-11-21 12:47:41.219697: train_loss -0.7559 +2024-11-21 12:47:41.225421: val_loss -0.7582 +2024-11-21 12:47:41.225568: Pseudo dice [0.8373] +2024-11-21 12:47:41.225661: Epoch time: 18.9 s +2024-11-21 12:47:42.047047: +2024-11-21 12:47:42.047248: Epoch 379 +2024-11-21 12:47:42.047363: Current learning rate: 0.00957 +2024-11-21 12:48:00.750627: train_loss -0.7675 +2024-11-21 12:48:00.766271: val_loss -0.7781 +2024-11-21 12:48:00.766430: Pseudo dice [0.8413] +2024-11-21 12:48:00.766520: Epoch time: 18.7 s +2024-11-21 12:48:01.625489: +2024-11-21 12:48:01.625685: Epoch 380 +2024-11-21 12:48:01.625801: Current learning rate: 0.00957 +2024-11-21 12:48:20.632021: train_loss -0.7447 +2024-11-21 12:48:20.637614: val_loss -0.7498 +2024-11-21 12:48:20.637751: Pseudo dice [0.8422] +2024-11-21 12:48:20.637859: Epoch time: 19.01 s +2024-11-21 12:48:21.586374: +2024-11-21 12:48:21.586618: Epoch 381 +2024-11-21 12:48:21.586751: Current learning rate: 0.00957 +2024-11-21 12:48:41.075398: train_loss -0.738 +2024-11-21 12:48:41.087821: val_loss -0.7472 +2024-11-21 12:48:41.087946: Pseudo dice [0.8379] +2024-11-21 12:48:41.088050: Epoch time: 19.49 s +2024-11-21 12:48:41.904379: +2024-11-21 12:48:41.904575: Epoch 382 +2024-11-21 12:48:41.904695: Current learning rate: 0.00957 +2024-11-21 12:49:00.671970: train_loss -0.7472 +2024-11-21 12:49:00.679095: val_loss -0.7458 +2024-11-21 12:49:00.679234: Pseudo dice [0.8348] +2024-11-21 12:49:00.679345: Epoch time: 18.77 s +2024-11-21 12:49:01.665241: +2024-11-21 12:49:01.665523: Epoch 383 +2024-11-21 12:49:01.665641: Current learning rate: 0.00957 +2024-11-21 12:49:20.728300: train_loss -0.7543 +2024-11-21 12:49:20.731709: val_loss -0.7642 +2024-11-21 12:49:20.731849: Pseudo dice [0.8382] +2024-11-21 12:49:20.731943: Epoch time: 19.06 s +2024-11-21 12:49:21.653054: +2024-11-21 12:49:21.653273: Epoch 384 +2024-11-21 12:49:21.653384: Current learning rate: 0.00957 +2024-11-21 12:49:41.202381: train_loss -0.7485 +2024-11-21 12:49:41.210011: val_loss -0.7742 +2024-11-21 12:49:41.210178: Pseudo dice [0.85] +2024-11-21 12:49:41.210289: Epoch time: 19.55 s +2024-11-21 12:49:42.034715: +2024-11-21 12:49:42.034899: Epoch 385 +2024-11-21 12:49:42.035011: Current learning rate: 0.00957 +2024-11-21 12:50:01.205132: train_loss -0.7489 +2024-11-21 12:50:01.212506: val_loss -0.7714 +2024-11-21 12:50:01.212645: Pseudo dice [0.8515] +2024-11-21 12:50:01.212732: Epoch time: 19.17 s +2024-11-21 12:50:02.163187: +2024-11-21 12:50:02.163363: Epoch 386 +2024-11-21 12:50:02.163479: Current learning rate: 0.00956 +2024-11-21 12:50:21.870644: train_loss -0.7588 +2024-11-21 12:50:21.879079: val_loss -0.7712 +2024-11-21 12:50:21.879210: Pseudo dice [0.8488] +2024-11-21 12:50:21.879339: Epoch time: 19.71 s +2024-11-21 12:50:22.691009: +2024-11-21 12:50:22.691201: Epoch 387 +2024-11-21 12:50:22.691326: Current learning rate: 0.00956 +2024-11-21 12:50:41.265372: train_loss -0.7474 +2024-11-21 12:50:41.269964: val_loss -0.7594 +2024-11-21 12:50:41.270109: Pseudo dice [0.8395] +2024-11-21 12:50:41.270196: Epoch time: 18.58 s +2024-11-21 12:50:42.078978: +2024-11-21 12:50:42.079175: Epoch 388 +2024-11-21 12:50:42.079296: Current learning rate: 0.00956 +2024-11-21 12:51:01.310347: train_loss -0.7543 +2024-11-21 12:51:01.312845: val_loss -0.7465 +2024-11-21 12:51:01.312978: Pseudo dice [0.8394] +2024-11-21 12:51:01.313078: Epoch time: 19.23 s +2024-11-21 12:51:02.536413: +2024-11-21 12:51:02.536631: Epoch 389 +2024-11-21 12:51:02.536756: Current learning rate: 0.00956 +2024-11-21 12:51:23.154520: train_loss -0.7501 +2024-11-21 12:51:23.158512: val_loss -0.7606 +2024-11-21 12:51:23.158635: Pseudo dice [0.8273] +2024-11-21 12:51:23.158725: Epoch time: 20.62 s +2024-11-21 12:51:23.968065: +2024-11-21 12:51:23.968286: Epoch 390 +2024-11-21 12:51:23.968426: Current learning rate: 0.00956 +2024-11-21 12:51:43.079514: train_loss -0.7459 +2024-11-21 12:51:43.084162: val_loss -0.7368 +2024-11-21 12:51:43.084298: Pseudo dice [0.8401] +2024-11-21 12:51:43.084583: Epoch time: 19.11 s +2024-11-21 12:51:43.945760: +2024-11-21 12:51:43.945961: Epoch 391 +2024-11-21 12:51:43.946089: Current learning rate: 0.00956 +2024-11-21 12:52:02.606765: train_loss -0.7422 +2024-11-21 12:52:02.611522: val_loss -0.7431 +2024-11-21 12:52:02.611681: Pseudo dice [0.8341] +2024-11-21 12:52:02.611789: Epoch time: 18.66 s +2024-11-21 12:52:03.556723: +2024-11-21 12:52:03.556934: Epoch 392 +2024-11-21 12:52:03.557076: Current learning rate: 0.00956 +2024-11-21 12:52:21.482402: train_loss -0.7417 +2024-11-21 12:52:21.492328: val_loss -0.7486 +2024-11-21 12:52:21.492460: Pseudo dice [0.8377] +2024-11-21 12:52:21.492560: Epoch time: 17.93 s +2024-11-21 12:52:22.380971: +2024-11-21 12:52:22.381201: Epoch 393 +2024-11-21 12:52:22.381328: Current learning rate: 0.00956 +2024-11-21 12:52:41.439378: train_loss -0.7405 +2024-11-21 12:52:41.443301: val_loss -0.7395 +2024-11-21 12:52:41.443410: Pseudo dice [0.84] +2024-11-21 12:52:41.443487: Epoch time: 19.06 s +2024-11-21 12:52:42.254690: +2024-11-21 12:52:42.254873: Epoch 394 +2024-11-21 12:52:42.254991: Current learning rate: 0.00956 +2024-11-21 12:53:00.779756: train_loss -0.7531 +2024-11-21 12:53:00.788491: val_loss -0.7699 +2024-11-21 12:53:00.788674: Pseudo dice [0.8526] +2024-11-21 12:53:00.788783: Epoch time: 18.53 s +2024-11-21 12:53:01.653280: +2024-11-21 12:53:01.653487: Epoch 395 +2024-11-21 12:53:01.653620: Current learning rate: 0.00955 +2024-11-21 12:53:20.307517: train_loss -0.7473 +2024-11-21 12:53:20.313299: val_loss -0.7374 +2024-11-21 12:53:20.313432: Pseudo dice [0.8436] +2024-11-21 12:53:20.313514: Epoch time: 18.66 s +2024-11-21 12:53:21.129699: +2024-11-21 12:53:21.129879: Epoch 396 +2024-11-21 12:53:21.129995: Current learning rate: 0.00955 +2024-11-21 12:53:40.888837: train_loss -0.7521 +2024-11-21 12:53:40.896457: val_loss -0.7461 +2024-11-21 12:53:40.896599: Pseudo dice [0.8478] +2024-11-21 12:53:40.896895: Epoch time: 19.76 s +2024-11-21 12:53:41.869441: +2024-11-21 12:53:41.869708: Epoch 397 +2024-11-21 12:53:41.869844: Current learning rate: 0.00955 +2024-11-21 12:54:00.506108: train_loss -0.7487 +2024-11-21 12:54:00.510715: val_loss -0.7598 +2024-11-21 12:54:00.510847: Pseudo dice [0.8363] +2024-11-21 12:54:00.510959: Epoch time: 18.64 s +2024-11-21 12:54:01.685871: +2024-11-21 12:54:01.686050: Epoch 398 +2024-11-21 12:54:01.686170: Current learning rate: 0.00955 +2024-11-21 12:54:21.691355: train_loss -0.7436 +2024-11-21 12:54:21.701905: val_loss -0.7546 +2024-11-21 12:54:21.702071: Pseudo dice [0.8364] +2024-11-21 12:54:21.702171: Epoch time: 20.01 s +2024-11-21 12:54:22.540878: +2024-11-21 12:54:22.541076: Epoch 399 +2024-11-21 12:54:22.541195: Current learning rate: 0.00955 +2024-11-21 12:54:41.230463: train_loss -0.7469 +2024-11-21 12:54:41.237355: val_loss -0.765 +2024-11-21 12:54:41.237503: Pseudo dice [0.8501] +2024-11-21 12:54:41.237600: Epoch time: 18.69 s +2024-11-21 12:54:42.698967: +2024-11-21 12:54:42.699156: Epoch 400 +2024-11-21 12:54:42.699270: Current learning rate: 0.00955 +2024-11-21 12:55:01.450577: train_loss -0.7526 +2024-11-21 12:55:01.454911: val_loss -0.7668 +2024-11-21 12:55:01.455043: Pseudo dice [0.8454] +2024-11-21 12:55:01.455142: Epoch time: 18.75 s +2024-11-21 12:55:02.263361: +2024-11-21 12:55:02.263564: Epoch 401 +2024-11-21 12:55:02.263680: Current learning rate: 0.00955 +2024-11-21 12:55:21.796973: train_loss -0.7414 +2024-11-21 12:55:21.802472: val_loss -0.7553 +2024-11-21 12:55:21.802699: Pseudo dice [0.8481] +2024-11-21 12:55:21.802807: Epoch time: 19.53 s +2024-11-21 12:55:22.844340: +2024-11-21 12:55:22.844560: Epoch 402 +2024-11-21 12:55:22.844677: Current learning rate: 0.00955 +2024-11-21 12:55:42.938009: train_loss -0.7439 +2024-11-21 12:55:42.954834: val_loss -0.7341 +2024-11-21 12:55:42.954991: Pseudo dice [0.8383] +2024-11-21 12:55:42.955088: Epoch time: 20.09 s +2024-11-21 12:55:43.851365: +2024-11-21 12:55:43.851554: Epoch 403 +2024-11-21 12:55:43.851670: Current learning rate: 0.00955 +2024-11-21 12:56:02.771951: train_loss -0.7436 +2024-11-21 12:56:02.780774: val_loss -0.7615 +2024-11-21 12:56:02.781161: Pseudo dice [0.8421] +2024-11-21 12:56:02.781283: Epoch time: 18.92 s +2024-11-21 12:56:03.600406: +2024-11-21 12:56:03.600598: Epoch 404 +2024-11-21 12:56:03.600741: Current learning rate: 0.00954 +2024-11-21 12:56:22.380687: train_loss -0.7489 +2024-11-21 12:56:22.387520: val_loss -0.7468 +2024-11-21 12:56:22.387697: Pseudo dice [0.8445] +2024-11-21 12:56:22.387787: Epoch time: 18.78 s +2024-11-21 12:56:23.271744: +2024-11-21 12:56:23.271949: Epoch 405 +2024-11-21 12:56:23.272080: Current learning rate: 0.00954 +2024-11-21 12:56:42.140578: train_loss -0.7556 +2024-11-21 12:56:42.148390: val_loss -0.7691 +2024-11-21 12:56:42.148546: Pseudo dice [0.841] +2024-11-21 12:56:42.148651: Epoch time: 18.87 s +2024-11-21 12:56:43.115290: +2024-11-21 12:56:43.115505: Epoch 406 +2024-11-21 12:56:43.115628: Current learning rate: 0.00954 +2024-11-21 12:57:02.029593: train_loss -0.7445 +2024-11-21 12:57:02.043758: val_loss -0.7432 +2024-11-21 12:57:02.043918: Pseudo dice [0.8559] +2024-11-21 12:57:02.044017: Epoch time: 18.92 s +2024-11-21 12:57:02.882905: +2024-11-21 12:57:02.883110: Epoch 407 +2024-11-21 12:57:02.883239: Current learning rate: 0.00954 +2024-11-21 12:57:21.498299: train_loss -0.7511 +2024-11-21 12:57:21.515408: val_loss -0.7494 +2024-11-21 12:57:21.515555: Pseudo dice [0.8372] +2024-11-21 12:57:21.515665: Epoch time: 18.62 s +2024-11-21 12:57:22.433516: +2024-11-21 12:57:22.433686: Epoch 408 +2024-11-21 12:57:22.433807: Current learning rate: 0.00954 +2024-11-21 12:57:41.368955: train_loss -0.7508 +2024-11-21 12:57:41.371644: val_loss -0.7526 +2024-11-21 12:57:41.371745: Pseudo dice [0.85] +2024-11-21 12:57:41.371845: Epoch time: 18.94 s +2024-11-21 12:57:42.186431: +2024-11-21 12:57:42.186610: Epoch 409 +2024-11-21 12:57:42.186733: Current learning rate: 0.00954 +2024-11-21 12:58:01.406841: train_loss -0.7478 +2024-11-21 12:58:01.416677: val_loss -0.7256 +2024-11-21 12:58:01.416826: Pseudo dice [0.8362] +2024-11-21 12:58:01.416914: Epoch time: 19.22 s +2024-11-21 12:58:02.321118: +2024-11-21 12:58:02.321311: Epoch 410 +2024-11-21 12:58:02.321444: Current learning rate: 0.00954 +2024-11-21 12:58:21.589325: train_loss -0.758 +2024-11-21 12:58:21.596861: val_loss -0.7508 +2024-11-21 12:58:21.596996: Pseudo dice [0.8418] +2024-11-21 12:58:21.597116: Epoch time: 19.27 s +2024-11-21 12:58:22.819631: +2024-11-21 12:58:22.819870: Epoch 411 +2024-11-21 12:58:22.819986: Current learning rate: 0.00954 +2024-11-21 12:58:41.601762: train_loss -0.7598 +2024-11-21 12:58:41.610796: val_loss -0.7614 +2024-11-21 12:58:41.610916: Pseudo dice [0.8413] +2024-11-21 12:58:41.611007: Epoch time: 18.78 s +2024-11-21 12:58:42.557673: +2024-11-21 12:58:42.557875: Epoch 412 +2024-11-21 12:58:42.557995: Current learning rate: 0.00954 +2024-11-21 12:59:01.779742: train_loss -0.7447 +2024-11-21 12:59:01.787888: val_loss -0.7284 +2024-11-21 12:59:01.788026: Pseudo dice [0.8288] +2024-11-21 12:59:01.788129: Epoch time: 19.22 s +2024-11-21 12:59:02.597962: +2024-11-21 12:59:02.598164: Epoch 413 +2024-11-21 12:59:02.598292: Current learning rate: 0.00953 +2024-11-21 12:59:21.862075: train_loss -0.7511 +2024-11-21 12:59:21.869595: val_loss -0.7588 +2024-11-21 12:59:21.869720: Pseudo dice [0.844] +2024-11-21 12:59:21.869819: Epoch time: 19.26 s +2024-11-21 12:59:22.692324: +2024-11-21 12:59:22.692547: Epoch 414 +2024-11-21 12:59:22.692726: Current learning rate: 0.00953 +2024-11-21 12:59:42.608053: train_loss -0.7246 +2024-11-21 12:59:42.621977: val_loss -0.6962 +2024-11-21 12:59:42.622142: Pseudo dice [0.8229] +2024-11-21 12:59:42.622258: Epoch time: 19.92 s +2024-11-21 12:59:43.515968: +2024-11-21 12:59:43.516154: Epoch 415 +2024-11-21 12:59:43.516270: Current learning rate: 0.00953 +2024-11-21 13:00:02.601909: train_loss -0.7366 +2024-11-21 13:00:02.608764: val_loss -0.7123 +2024-11-21 13:00:02.608900: Pseudo dice [0.8259] +2024-11-21 13:00:02.608991: Epoch time: 19.09 s +2024-11-21 13:00:03.435288: +2024-11-21 13:00:03.435486: Epoch 416 +2024-11-21 13:00:03.435638: Current learning rate: 0.00953 +2024-11-21 13:00:22.515803: train_loss -0.7484 +2024-11-21 13:00:22.529441: val_loss -0.7383 +2024-11-21 13:00:22.529579: Pseudo dice [0.836] +2024-11-21 13:00:22.529692: Epoch time: 19.08 s +2024-11-21 13:00:23.367235: +2024-11-21 13:00:23.367408: Epoch 417 +2024-11-21 13:00:23.367517: Current learning rate: 0.00953 +2024-11-21 13:00:42.361239: train_loss -0.7545 +2024-11-21 13:00:42.370983: val_loss -0.7447 +2024-11-21 13:00:42.371157: Pseudo dice [0.8379] +2024-11-21 13:00:42.371268: Epoch time: 18.99 s +2024-11-21 13:00:43.169679: +2024-11-21 13:00:43.169867: Epoch 418 +2024-11-21 13:00:43.169987: Current learning rate: 0.00953 +2024-11-21 13:01:02.146625: train_loss -0.7447 +2024-11-21 13:01:02.158432: val_loss -0.7615 +2024-11-21 13:01:02.158575: Pseudo dice [0.8525] +2024-11-21 13:01:02.158692: Epoch time: 18.98 s +2024-11-21 13:01:03.003360: +2024-11-21 13:01:03.003548: Epoch 419 +2024-11-21 13:01:03.003661: Current learning rate: 0.00953 +2024-11-21 13:01:22.566077: train_loss -0.7547 +2024-11-21 13:01:22.580258: val_loss -0.7381 +2024-11-21 13:01:22.580415: Pseudo dice [0.8483] +2024-11-21 13:01:22.580508: Epoch time: 19.56 s +2024-11-21 13:01:23.491166: +2024-11-21 13:01:23.491365: Epoch 420 +2024-11-21 13:01:23.491498: Current learning rate: 0.00953 +2024-11-21 13:01:42.560440: train_loss -0.7479 +2024-11-21 13:01:42.568947: val_loss -0.7577 +2024-11-21 13:01:42.569080: Pseudo dice [0.8322] +2024-11-21 13:01:42.569274: Epoch time: 19.07 s +2024-11-21 13:01:43.404944: +2024-11-21 13:01:43.405196: Epoch 421 +2024-11-21 13:01:43.405321: Current learning rate: 0.00953 +2024-11-21 13:02:01.724875: train_loss -0.7446 +2024-11-21 13:02:01.731241: val_loss -0.7324 +2024-11-21 13:02:01.731397: Pseudo dice [0.8383] +2024-11-21 13:02:01.731506: Epoch time: 18.32 s +2024-11-21 13:02:02.518649: +2024-11-21 13:02:02.518842: Epoch 422 +2024-11-21 13:02:02.518955: Current learning rate: 0.00952 +2024-11-21 13:02:21.567245: train_loss -0.7557 +2024-11-21 13:02:21.579349: val_loss -0.7631 +2024-11-21 13:02:21.579489: Pseudo dice [0.8455] +2024-11-21 13:02:21.579660: Epoch time: 19.05 s +2024-11-21 13:02:22.564086: +2024-11-21 13:02:22.564302: Epoch 423 +2024-11-21 13:02:22.564425: Current learning rate: 0.00952 +2024-11-21 13:02:41.660702: train_loss -0.7412 +2024-11-21 13:02:41.668575: val_loss -0.7429 +2024-11-21 13:02:41.668731: Pseudo dice [0.8235] +2024-11-21 13:02:41.668822: Epoch time: 19.1 s +2024-11-21 13:02:42.531704: +2024-11-21 13:02:42.531937: Epoch 424 +2024-11-21 13:02:42.532077: Current learning rate: 0.00952 +2024-11-21 13:03:01.186981: train_loss -0.7518 +2024-11-21 13:03:01.192195: val_loss -0.7634 +2024-11-21 13:03:01.192338: Pseudo dice [0.8458] +2024-11-21 13:03:01.192436: Epoch time: 18.66 s +2024-11-21 13:03:01.983145: +2024-11-21 13:03:01.983330: Epoch 425 +2024-11-21 13:03:01.983450: Current learning rate: 0.00952 +2024-11-21 13:03:20.956826: train_loss -0.747 +2024-11-21 13:03:20.960993: val_loss -0.7423 +2024-11-21 13:03:20.961133: Pseudo dice [0.8282] +2024-11-21 13:03:20.961230: Epoch time: 18.97 s +2024-11-21 13:03:21.808613: +2024-11-21 13:03:21.808810: Epoch 426 +2024-11-21 13:03:21.808939: Current learning rate: 0.00952 +2024-11-21 13:03:40.423512: train_loss -0.7366 +2024-11-21 13:03:40.429789: val_loss -0.7632 +2024-11-21 13:03:40.429929: Pseudo dice [0.8486] +2024-11-21 13:03:40.430037: Epoch time: 18.62 s +2024-11-21 13:03:41.344249: +2024-11-21 13:03:41.344434: Epoch 427 +2024-11-21 13:03:41.344552: Current learning rate: 0.00952 +2024-11-21 13:04:00.554087: train_loss -0.7535 +2024-11-21 13:04:00.567890: val_loss -0.7794 +2024-11-21 13:04:00.568017: Pseudo dice [0.8466] +2024-11-21 13:04:00.568127: Epoch time: 19.21 s +2024-11-21 13:04:01.607152: +2024-11-21 13:04:01.607383: Epoch 428 +2024-11-21 13:04:01.607511: Current learning rate: 0.00952 +2024-11-21 13:04:20.446079: train_loss -0.7591 +2024-11-21 13:04:20.451551: val_loss -0.7517 +2024-11-21 13:04:20.451684: Pseudo dice [0.8524] +2024-11-21 13:04:20.451768: Epoch time: 18.84 s +2024-11-21 13:04:21.408968: +2024-11-21 13:04:21.409393: Epoch 429 +2024-11-21 13:04:21.409518: Current learning rate: 0.00952 +2024-11-21 13:04:40.455855: train_loss -0.7603 +2024-11-21 13:04:40.460948: val_loss -0.7517 +2024-11-21 13:04:40.461102: Pseudo dice [0.8473] +2024-11-21 13:04:40.461197: Epoch time: 19.05 s +2024-11-21 13:04:41.297675: +2024-11-21 13:04:41.297916: Epoch 430 +2024-11-21 13:04:41.298050: Current learning rate: 0.00951 +2024-11-21 13:05:00.239779: train_loss -0.7481 +2024-11-21 13:05:00.245188: val_loss -0.7394 +2024-11-21 13:05:00.245340: Pseudo dice [0.8433] +2024-11-21 13:05:00.245431: Epoch time: 18.94 s +2024-11-21 13:05:01.048921: +2024-11-21 13:05:01.049134: Epoch 431 +2024-11-21 13:05:01.049253: Current learning rate: 0.00951 +2024-11-21 13:05:19.747893: train_loss -0.7411 +2024-11-21 13:05:19.751475: val_loss -0.7441 +2024-11-21 13:05:19.751591: Pseudo dice [0.8369] +2024-11-21 13:05:19.751696: Epoch time: 18.7 s +2024-11-21 13:05:20.594426: +2024-11-21 13:05:20.594674: Epoch 432 +2024-11-21 13:05:20.594788: Current learning rate: 0.00951 +2024-11-21 13:05:40.661684: train_loss -0.7434 +2024-11-21 13:05:40.663755: val_loss -0.7696 +2024-11-21 13:05:40.663849: Pseudo dice [0.8356] +2024-11-21 13:05:40.663931: Epoch time: 20.07 s +2024-11-21 13:05:41.448039: +2024-11-21 13:05:41.448261: Epoch 433 +2024-11-21 13:05:41.448396: Current learning rate: 0.00951 +2024-11-21 13:06:00.599814: train_loss -0.7535 +2024-11-21 13:06:00.603205: val_loss -0.7614 +2024-11-21 13:06:00.603316: Pseudo dice [0.8479] +2024-11-21 13:06:00.603401: Epoch time: 19.15 s +2024-11-21 13:06:01.689818: +2024-11-21 13:06:01.690011: Epoch 434 +2024-11-21 13:06:01.690124: Current learning rate: 0.00951 +2024-11-21 13:06:20.008117: train_loss -0.76 +2024-11-21 13:06:20.016392: val_loss -0.7779 +2024-11-21 13:06:20.016514: Pseudo dice [0.8464] +2024-11-21 13:06:20.016608: Epoch time: 18.32 s +2024-11-21 13:06:20.875698: +2024-11-21 13:06:20.875938: Epoch 435 +2024-11-21 13:06:20.876082: Current learning rate: 0.00951 +2024-11-21 13:06:39.948418: train_loss -0.7547 +2024-11-21 13:06:39.953499: val_loss -0.7497 +2024-11-21 13:06:39.953650: Pseudo dice [0.8363] +2024-11-21 13:06:39.953739: Epoch time: 19.07 s +2024-11-21 13:06:40.809265: +2024-11-21 13:06:40.809470: Epoch 436 +2024-11-21 13:06:40.809593: Current learning rate: 0.00951 +2024-11-21 13:07:00.124295: train_loss -0.7565 +2024-11-21 13:07:00.131543: val_loss -0.7619 +2024-11-21 13:07:00.131680: Pseudo dice [0.8403] +2024-11-21 13:07:00.131764: Epoch time: 19.32 s +2024-11-21 13:07:00.953345: +2024-11-21 13:07:00.953557: Epoch 437 +2024-11-21 13:07:00.953684: Current learning rate: 0.00951 +2024-11-21 13:07:20.087788: train_loss -0.7573 +2024-11-21 13:07:20.090896: val_loss -0.7503 +2024-11-21 13:07:20.091035: Pseudo dice [0.8402] +2024-11-21 13:07:20.091122: Epoch time: 19.14 s +2024-11-21 13:07:20.874724: +2024-11-21 13:07:20.874916: Epoch 438 +2024-11-21 13:07:20.875034: Current learning rate: 0.00951 +2024-11-21 13:07:40.349729: train_loss -0.7552 +2024-11-21 13:07:40.355187: val_loss -0.7589 +2024-11-21 13:07:40.355350: Pseudo dice [0.8446] +2024-11-21 13:07:40.355454: Epoch time: 19.48 s +2024-11-21 13:07:41.144372: +2024-11-21 13:07:41.144585: Epoch 439 +2024-11-21 13:07:41.144701: Current learning rate: 0.0095 +2024-11-21 13:08:01.890191: train_loss -0.7568 +2024-11-21 13:08:01.892021: val_loss -0.7587 +2024-11-21 13:08:01.892160: Pseudo dice [0.8435] +2024-11-21 13:08:01.892252: Epoch time: 20.75 s +2024-11-21 13:08:02.703585: +2024-11-21 13:08:02.703772: Epoch 440 +2024-11-21 13:08:02.703904: Current learning rate: 0.0095 +2024-11-21 13:08:22.017075: train_loss -0.76 +2024-11-21 13:08:22.024282: val_loss -0.7543 +2024-11-21 13:08:22.024425: Pseudo dice [0.8432] +2024-11-21 13:08:22.024517: Epoch time: 19.31 s +2024-11-21 13:08:22.986250: +2024-11-21 13:08:22.986448: Epoch 441 +2024-11-21 13:08:22.986582: Current learning rate: 0.0095 +2024-11-21 13:08:41.064440: train_loss -0.7592 +2024-11-21 13:08:41.070821: val_loss -0.7614 +2024-11-21 13:08:41.070973: Pseudo dice [0.8418] +2024-11-21 13:08:41.071354: Epoch time: 18.08 s +2024-11-21 13:08:42.037735: +2024-11-21 13:08:42.037941: Epoch 442 +2024-11-21 13:08:42.038076: Current learning rate: 0.0095 +2024-11-21 13:09:02.233529: train_loss -0.7584 +2024-11-21 13:09:02.237632: val_loss -0.7394 +2024-11-21 13:09:02.237757: Pseudo dice [0.8223] +2024-11-21 13:09:02.237865: Epoch time: 20.2 s +2024-11-21 13:09:03.208236: +2024-11-21 13:09:03.208416: Epoch 443 +2024-11-21 13:09:03.208545: Current learning rate: 0.0095 +2024-11-21 13:09:22.296865: train_loss -0.7439 +2024-11-21 13:09:22.298872: val_loss -0.7552 +2024-11-21 13:09:22.299019: Pseudo dice [0.8466] +2024-11-21 13:09:22.299110: Epoch time: 19.09 s +2024-11-21 13:09:23.145690: +2024-11-21 13:09:23.145858: Epoch 444 +2024-11-21 13:09:23.145974: Current learning rate: 0.0095 +2024-11-21 13:09:42.772751: train_loss -0.7587 +2024-11-21 13:09:42.782248: val_loss -0.7769 +2024-11-21 13:09:42.782372: Pseudo dice [0.8569] +2024-11-21 13:09:42.782451: Epoch time: 19.63 s +2024-11-21 13:09:43.566728: +2024-11-21 13:09:43.566918: Epoch 445 +2024-11-21 13:09:43.567041: Current learning rate: 0.0095 +2024-11-21 13:10:02.624970: train_loss -0.7564 +2024-11-21 13:10:02.630157: val_loss -0.773 +2024-11-21 13:10:02.630327: Pseudo dice [0.839] +2024-11-21 13:10:02.630426: Epoch time: 19.06 s +2024-11-21 13:10:03.451893: +2024-11-21 13:10:03.452122: Epoch 446 +2024-11-21 13:10:03.452242: Current learning rate: 0.0095 +2024-11-21 13:10:22.673446: train_loss -0.769 +2024-11-21 13:10:22.678886: val_loss -0.7739 +2024-11-21 13:10:22.679039: Pseudo dice [0.8227] +2024-11-21 13:10:22.679141: Epoch time: 19.22 s +2024-11-21 13:10:23.461857: +2024-11-21 13:10:23.462067: Epoch 447 +2024-11-21 13:10:23.462193: Current learning rate: 0.0095 +2024-11-21 13:10:41.944870: train_loss -0.7565 +2024-11-21 13:10:41.950070: val_loss -0.7633 +2024-11-21 13:10:41.950210: Pseudo dice [0.8481] +2024-11-21 13:10:41.950301: Epoch time: 18.48 s +2024-11-21 13:10:42.751143: +2024-11-21 13:10:42.751355: Epoch 448 +2024-11-21 13:10:42.751488: Current learning rate: 0.00949 +2024-11-21 13:11:02.066221: train_loss -0.7535 +2024-11-21 13:11:02.067806: val_loss -0.7625 +2024-11-21 13:11:02.067945: Pseudo dice [0.843] +2024-11-21 13:11:02.068202: Epoch time: 19.32 s +2024-11-21 13:11:03.002510: +2024-11-21 13:11:03.002726: Epoch 449 +2024-11-21 13:11:03.002872: Current learning rate: 0.00949 +2024-11-21 13:11:21.406853: train_loss -0.7536 +2024-11-21 13:11:21.408768: val_loss -0.7436 +2024-11-21 13:11:21.408877: Pseudo dice [0.845] +2024-11-21 13:11:21.408990: Epoch time: 18.41 s +2024-11-21 13:11:22.449337: +2024-11-21 13:11:22.449560: Epoch 450 +2024-11-21 13:11:22.449677: Current learning rate: 0.00949 +2024-11-21 13:11:42.066764: train_loss -0.7558 +2024-11-21 13:11:42.072191: val_loss -0.7862 +2024-11-21 13:11:42.072345: Pseudo dice [0.8548] +2024-11-21 13:11:42.072431: Epoch time: 19.62 s +2024-11-21 13:11:42.881437: +2024-11-21 13:11:42.881639: Epoch 451 +2024-11-21 13:11:42.881754: Current learning rate: 0.00949 +2024-11-21 13:12:03.034936: train_loss -0.7464 +2024-11-21 13:12:03.036517: val_loss -0.7634 +2024-11-21 13:12:03.036608: Pseudo dice [0.8368] +2024-11-21 13:12:03.036695: Epoch time: 20.15 s +2024-11-21 13:12:03.818222: +2024-11-21 13:12:03.818418: Epoch 452 +2024-11-21 13:12:03.818540: Current learning rate: 0.00949 +2024-11-21 13:12:22.788481: train_loss -0.7528 +2024-11-21 13:12:22.790140: val_loss -0.7307 +2024-11-21 13:12:22.790239: Pseudo dice [0.8434] +2024-11-21 13:12:22.790319: Epoch time: 18.97 s +2024-11-21 13:12:23.579827: +2024-11-21 13:12:23.580033: Epoch 453 +2024-11-21 13:12:23.580155: Current learning rate: 0.00949 +2024-11-21 13:12:42.339360: train_loss -0.7594 +2024-11-21 13:12:42.341123: val_loss -0.7534 +2024-11-21 13:12:42.341228: Pseudo dice [0.8527] +2024-11-21 13:12:42.341319: Epoch time: 18.76 s +2024-11-21 13:12:43.130258: +2024-11-21 13:12:43.130443: Epoch 454 +2024-11-21 13:12:43.130554: Current learning rate: 0.00949 +2024-11-21 13:13:02.494700: train_loss -0.7481 +2024-11-21 13:13:02.500274: val_loss -0.7588 +2024-11-21 13:13:02.500412: Pseudo dice [0.8417] +2024-11-21 13:13:02.500507: Epoch time: 19.37 s +2024-11-21 13:13:03.290479: +2024-11-21 13:13:03.290680: Epoch 455 +2024-11-21 13:13:03.290824: Current learning rate: 0.00949 +2024-11-21 13:13:22.577545: train_loss -0.7577 +2024-11-21 13:13:22.583326: val_loss -0.7663 +2024-11-21 13:13:22.583473: Pseudo dice [0.8467] +2024-11-21 13:13:22.583596: Epoch time: 19.29 s +2024-11-21 13:13:23.441285: +2024-11-21 13:13:23.441461: Epoch 456 +2024-11-21 13:13:23.441578: Current learning rate: 0.00949 +2024-11-21 13:13:43.984066: train_loss -0.762 +2024-11-21 13:13:44.007323: val_loss -0.7328 +2024-11-21 13:13:44.007466: Pseudo dice [0.8275] +2024-11-21 13:13:44.007557: Epoch time: 20.54 s +2024-11-21 13:13:45.211183: +2024-11-21 13:13:45.211390: Epoch 457 +2024-11-21 13:13:45.211531: Current learning rate: 0.00948 +2024-11-21 13:14:04.404125: train_loss -0.7467 +2024-11-21 13:14:04.406612: val_loss -0.7184 +2024-11-21 13:14:04.406751: Pseudo dice [0.8262] +2024-11-21 13:14:04.406858: Epoch time: 19.19 s +2024-11-21 13:14:05.192342: +2024-11-21 13:14:05.192588: Epoch 458 +2024-11-21 13:14:05.192713: Current learning rate: 0.00948 +2024-11-21 13:14:24.634385: train_loss -0.7389 +2024-11-21 13:14:24.639906: val_loss -0.7464 +2024-11-21 13:14:24.640036: Pseudo dice [0.8365] +2024-11-21 13:14:24.640166: Epoch time: 19.44 s +2024-11-21 13:14:25.545932: +2024-11-21 13:14:25.546166: Epoch 459 +2024-11-21 13:14:25.546280: Current learning rate: 0.00948 +2024-11-21 13:14:43.598087: train_loss -0.7444 +2024-11-21 13:14:43.604312: val_loss -0.7539 +2024-11-21 13:14:43.604493: Pseudo dice [0.8474] +2024-11-21 13:14:43.604595: Epoch time: 18.05 s +2024-11-21 13:14:44.388205: +2024-11-21 13:14:44.388405: Epoch 460 +2024-11-21 13:14:44.388540: Current learning rate: 0.00948 +2024-11-21 13:15:03.634670: train_loss -0.7533 +2024-11-21 13:15:03.638950: val_loss -0.7332 +2024-11-21 13:15:03.639096: Pseudo dice [0.8391] +2024-11-21 13:15:03.639190: Epoch time: 19.25 s +2024-11-21 13:15:04.564820: +2024-11-21 13:15:04.565046: Epoch 461 +2024-11-21 13:15:04.565176: Current learning rate: 0.00948 +2024-11-21 13:15:23.693569: train_loss -0.7441 +2024-11-21 13:15:23.699758: val_loss -0.7669 +2024-11-21 13:15:23.699888: Pseudo dice [0.844] +2024-11-21 13:15:23.699989: Epoch time: 19.13 s +2024-11-21 13:15:24.579879: +2024-11-21 13:15:24.580070: Epoch 462 +2024-11-21 13:15:24.580189: Current learning rate: 0.00948 +2024-11-21 13:15:43.532639: train_loss -0.7569 +2024-11-21 13:15:43.535408: val_loss -0.742 +2024-11-21 13:15:43.535531: Pseudo dice [0.8356] +2024-11-21 13:15:43.535636: Epoch time: 18.95 s +2024-11-21 13:15:44.332537: +2024-11-21 13:15:44.332739: Epoch 463 +2024-11-21 13:15:44.332858: Current learning rate: 0.00948 +2024-11-21 13:16:03.178385: train_loss -0.7614 +2024-11-21 13:16:03.184329: val_loss -0.7671 +2024-11-21 13:16:03.184487: Pseudo dice [0.8507] +2024-11-21 13:16:03.184595: Epoch time: 18.85 s +2024-11-21 13:16:04.144150: +2024-11-21 13:16:04.144340: Epoch 464 +2024-11-21 13:16:04.144466: Current learning rate: 0.00948 +2024-11-21 13:16:22.210195: train_loss -0.7646 +2024-11-21 13:16:22.221802: val_loss -0.7534 +2024-11-21 13:16:22.221920: Pseudo dice [0.834] +2024-11-21 13:16:22.222019: Epoch time: 18.07 s +2024-11-21 13:16:23.048418: +2024-11-21 13:16:23.048612: Epoch 465 +2024-11-21 13:16:23.048748: Current learning rate: 0.00948 +2024-11-21 13:16:43.036782: train_loss -0.763 +2024-11-21 13:16:43.041957: val_loss -0.7405 +2024-11-21 13:16:43.042129: Pseudo dice [0.8388] +2024-11-21 13:16:43.042263: Epoch time: 19.99 s +2024-11-21 13:16:43.854242: +2024-11-21 13:16:43.854452: Epoch 466 +2024-11-21 13:16:43.854577: Current learning rate: 0.00947 +2024-11-21 13:17:03.270278: train_loss -0.7647 +2024-11-21 13:17:03.284451: val_loss -0.7485 +2024-11-21 13:17:03.284609: Pseudo dice [0.8382] +2024-11-21 13:17:03.284717: Epoch time: 19.42 s +2024-11-21 13:17:04.073677: +2024-11-21 13:17:04.073862: Epoch 467 +2024-11-21 13:17:04.073987: Current learning rate: 0.00947 +2024-11-21 13:17:23.669260: train_loss -0.7567 +2024-11-21 13:17:23.676031: val_loss -0.7475 +2024-11-21 13:17:23.676166: Pseudo dice [0.8467] +2024-11-21 13:17:23.676251: Epoch time: 19.6 s +2024-11-21 13:17:24.470738: +2024-11-21 13:17:24.470920: Epoch 468 +2024-11-21 13:17:24.471037: Current learning rate: 0.00947 +2024-11-21 13:17:43.101323: train_loss -0.7624 +2024-11-21 13:17:43.103204: val_loss -0.7423 +2024-11-21 13:17:43.103308: Pseudo dice [0.8529] +2024-11-21 13:17:43.103388: Epoch time: 18.63 s +2024-11-21 13:17:43.889433: +2024-11-21 13:17:43.889632: Epoch 469 +2024-11-21 13:17:43.889759: Current learning rate: 0.00947 +2024-11-21 13:18:03.074455: train_loss -0.7532 +2024-11-21 13:18:03.079902: val_loss -0.7231 +2024-11-21 13:18:03.080052: Pseudo dice [0.8218] +2024-11-21 13:18:03.080147: Epoch time: 19.19 s +2024-11-21 13:18:04.163393: +2024-11-21 13:18:04.163596: Epoch 470 +2024-11-21 13:18:04.163711: Current learning rate: 0.00947 +2024-11-21 13:18:22.277921: train_loss -0.7579 +2024-11-21 13:18:22.292789: val_loss -0.7344 +2024-11-21 13:18:22.292929: Pseudo dice [0.8139] +2024-11-21 13:18:22.293025: Epoch time: 18.12 s +2024-11-21 13:18:23.243601: +2024-11-21 13:18:23.243804: Epoch 471 +2024-11-21 13:18:23.243945: Current learning rate: 0.00947 +2024-11-21 13:18:41.756992: train_loss -0.7653 +2024-11-21 13:18:41.764176: val_loss -0.7546 +2024-11-21 13:18:41.764317: Pseudo dice [0.8356] +2024-11-21 13:18:41.764409: Epoch time: 18.51 s +2024-11-21 13:18:42.571803: +2024-11-21 13:18:42.571985: Epoch 472 +2024-11-21 13:18:42.572122: Current learning rate: 0.00947 +2024-11-21 13:19:02.792681: train_loss -0.7615 +2024-11-21 13:19:02.801398: val_loss -0.7708 +2024-11-21 13:19:02.801544: Pseudo dice [0.839] +2024-11-21 13:19:02.801693: Epoch time: 20.22 s +2024-11-21 13:19:03.603992: +2024-11-21 13:19:03.604179: Epoch 473 +2024-11-21 13:19:03.604304: Current learning rate: 0.00947 +2024-11-21 13:19:22.359177: train_loss -0.7572 +2024-11-21 13:19:22.370363: val_loss -0.7691 +2024-11-21 13:19:22.370504: Pseudo dice [0.853] +2024-11-21 13:19:22.370609: Epoch time: 18.76 s +2024-11-21 13:19:23.173392: +2024-11-21 13:19:23.173656: Epoch 474 +2024-11-21 13:19:23.173793: Current learning rate: 0.00947 +2024-11-21 13:19:43.050818: train_loss -0.751 +2024-11-21 13:19:43.054399: val_loss -0.7819 +2024-11-21 13:19:43.054549: Pseudo dice [0.8542] +2024-11-21 13:19:43.054866: Epoch time: 19.88 s +2024-11-21 13:19:43.845380: +2024-11-21 13:19:43.845572: Epoch 475 +2024-11-21 13:19:43.845705: Current learning rate: 0.00946 +2024-11-21 13:20:03.846382: train_loss -0.756 +2024-11-21 13:20:03.854200: val_loss -0.7304 +2024-11-21 13:20:03.854321: Pseudo dice [0.8493] +2024-11-21 13:20:03.854408: Epoch time: 20.0 s +2024-11-21 13:20:04.694524: +2024-11-21 13:20:04.694730: Epoch 476 +2024-11-21 13:20:04.694857: Current learning rate: 0.00946 +2024-11-21 13:20:22.847018: train_loss -0.7602 +2024-11-21 13:20:22.854606: val_loss -0.7501 +2024-11-21 13:20:22.854759: Pseudo dice [0.8517] +2024-11-21 13:20:22.854849: Epoch time: 18.15 s +2024-11-21 13:20:23.838536: +2024-11-21 13:20:23.838758: Epoch 477 +2024-11-21 13:20:23.838886: Current learning rate: 0.00946 +2024-11-21 13:20:42.679608: train_loss -0.7663 +2024-11-21 13:20:42.686750: val_loss -0.7564 +2024-11-21 13:20:42.686890: Pseudo dice [0.8426] +2024-11-21 13:20:42.686979: Epoch time: 18.84 s +2024-11-21 13:20:43.560009: +2024-11-21 13:20:43.560197: Epoch 478 +2024-11-21 13:20:43.560318: Current learning rate: 0.00946 +2024-11-21 13:21:01.909359: train_loss -0.7615 +2024-11-21 13:21:01.911664: val_loss -0.75 +2024-11-21 13:21:01.911759: Pseudo dice [0.837] +2024-11-21 13:21:01.911849: Epoch time: 18.35 s +2024-11-21 13:21:02.696218: +2024-11-21 13:21:02.696408: Epoch 479 +2024-11-21 13:21:02.696518: Current learning rate: 0.00946 +2024-11-21 13:21:22.257460: train_loss -0.7613 +2024-11-21 13:21:22.264748: val_loss -0.7731 +2024-11-21 13:21:22.264918: Pseudo dice [0.8633] +2024-11-21 13:21:22.265014: Epoch time: 19.56 s +2024-11-21 13:21:23.451324: +2024-11-21 13:21:23.472214: Epoch 480 +2024-11-21 13:21:23.472396: Current learning rate: 0.00946 +2024-11-21 13:21:42.387893: train_loss -0.7598 +2024-11-21 13:21:42.392955: val_loss -0.737 +2024-11-21 13:21:42.393071: Pseudo dice [0.84] +2024-11-21 13:21:42.393177: Epoch time: 18.94 s +2024-11-21 13:21:43.191404: +2024-11-21 13:21:43.191624: Epoch 481 +2024-11-21 13:21:43.191739: Current learning rate: 0.00946 +2024-11-21 13:22:03.287537: train_loss -0.7642 +2024-11-21 13:22:03.294306: val_loss -0.7564 +2024-11-21 13:22:03.294442: Pseudo dice [0.8401] +2024-11-21 13:22:03.294556: Epoch time: 20.1 s +2024-11-21 13:22:04.117446: +2024-11-21 13:22:04.117684: Epoch 482 +2024-11-21 13:22:04.117824: Current learning rate: 0.00946 +2024-11-21 13:22:23.414558: train_loss -0.7654 +2024-11-21 13:22:23.420441: val_loss -0.7653 +2024-11-21 13:22:23.420570: Pseudo dice [0.8421] +2024-11-21 13:22:23.420673: Epoch time: 19.3 s +2024-11-21 13:22:24.284663: +2024-11-21 13:22:24.284894: Epoch 483 +2024-11-21 13:22:24.285014: Current learning rate: 0.00945 +2024-11-21 13:22:43.971648: train_loss -0.7381 +2024-11-21 13:22:43.975525: val_loss -0.749 +2024-11-21 13:22:43.975659: Pseudo dice [0.8374] +2024-11-21 13:22:43.975754: Epoch time: 19.69 s +2024-11-21 13:22:44.841767: +2024-11-21 13:22:44.841982: Epoch 484 +2024-11-21 13:22:44.842111: Current learning rate: 0.00945 +2024-11-21 13:23:03.262466: train_loss -0.7473 +2024-11-21 13:23:03.265672: val_loss -0.7629 +2024-11-21 13:23:03.265808: Pseudo dice [0.8509] +2024-11-21 13:23:03.265990: Epoch time: 18.42 s +2024-11-21 13:23:04.195699: +2024-11-21 13:23:04.211288: Epoch 485 +2024-11-21 13:23:04.211412: Current learning rate: 0.00945 +2024-11-21 13:23:23.219036: train_loss -0.7571 +2024-11-21 13:23:23.227997: val_loss -0.7401 +2024-11-21 13:23:23.228130: Pseudo dice [0.8203] +2024-11-21 13:23:23.228225: Epoch time: 19.02 s +2024-11-21 13:23:24.025466: +2024-11-21 13:23:24.025675: Epoch 486 +2024-11-21 13:23:24.025794: Current learning rate: 0.00945 +2024-11-21 13:23:44.165986: train_loss -0.7577 +2024-11-21 13:23:44.172204: val_loss -0.7678 +2024-11-21 13:23:44.172390: Pseudo dice [0.8414] +2024-11-21 13:23:44.172494: Epoch time: 20.14 s +2024-11-21 13:23:44.977087: +2024-11-21 13:23:44.977348: Epoch 487 +2024-11-21 13:23:44.977482: Current learning rate: 0.00945 +2024-11-21 13:24:04.200504: train_loss -0.7545 +2024-11-21 13:24:04.212366: val_loss -0.7405 +2024-11-21 13:24:04.212492: Pseudo dice [0.835] +2024-11-21 13:24:04.212592: Epoch time: 19.22 s +2024-11-21 13:24:05.229325: +2024-11-21 13:24:05.229547: Epoch 488 +2024-11-21 13:24:05.229686: Current learning rate: 0.00945 +2024-11-21 13:24:24.550150: train_loss -0.7545 +2024-11-21 13:24:24.575332: val_loss -0.7644 +2024-11-21 13:24:24.575519: Pseudo dice [0.8462] +2024-11-21 13:24:24.575638: Epoch time: 19.32 s +2024-11-21 13:24:25.523837: +2024-11-21 13:24:25.524027: Epoch 489 +2024-11-21 13:24:25.524149: Current learning rate: 0.00945 +2024-11-21 13:24:44.993207: train_loss -0.7595 +2024-11-21 13:24:45.011827: val_loss -0.7496 +2024-11-21 13:24:45.011973: Pseudo dice [0.8454] +2024-11-21 13:24:45.012088: Epoch time: 19.47 s +2024-11-21 13:24:45.806221: +2024-11-21 13:24:45.806409: Epoch 490 +2024-11-21 13:24:45.806522: Current learning rate: 0.00945 +2024-11-21 13:25:03.697526: train_loss -0.7591 +2024-11-21 13:25:03.710742: val_loss -0.763 +2024-11-21 13:25:03.710876: Pseudo dice [0.8332] +2024-11-21 13:25:03.710977: Epoch time: 17.89 s +2024-11-21 13:25:04.977429: +2024-11-21 13:25:04.977634: Epoch 491 +2024-11-21 13:25:04.977751: Current learning rate: 0.00945 +2024-11-21 13:25:24.179807: train_loss -0.739 +2024-11-21 13:25:24.188649: val_loss -0.7559 +2024-11-21 13:25:24.188772: Pseudo dice [0.8475] +2024-11-21 13:25:24.188861: Epoch time: 19.2 s +2024-11-21 13:25:25.029619: +2024-11-21 13:25:25.029894: Epoch 492 +2024-11-21 13:25:25.030040: Current learning rate: 0.00944 +2024-11-21 13:25:43.412909: train_loss -0.7487 +2024-11-21 13:25:43.415996: val_loss -0.7543 +2024-11-21 13:25:43.416130: Pseudo dice [0.8531] +2024-11-21 13:25:43.416433: Epoch time: 18.38 s +2024-11-21 13:25:44.213893: +2024-11-21 13:25:44.215682: Epoch 493 +2024-11-21 13:25:44.215815: Current learning rate: 0.00944 +2024-11-21 13:26:03.053531: train_loss -0.7572 +2024-11-21 13:26:03.059649: val_loss -0.7143 +2024-11-21 13:26:03.059806: Pseudo dice [0.8373] +2024-11-21 13:26:03.059914: Epoch time: 18.84 s +2024-11-21 13:26:03.881044: +2024-11-21 13:26:03.881254: Epoch 494 +2024-11-21 13:26:03.881374: Current learning rate: 0.00944 +2024-11-21 13:26:22.764335: train_loss -0.7587 +2024-11-21 13:26:22.772691: val_loss -0.7447 +2024-11-21 13:26:22.772820: Pseudo dice [0.845] +2024-11-21 13:26:22.772913: Epoch time: 18.88 s +2024-11-21 13:26:23.573728: +2024-11-21 13:26:23.573937: Epoch 495 +2024-11-21 13:26:23.574076: Current learning rate: 0.00944 +2024-11-21 13:26:42.716395: train_loss -0.7638 +2024-11-21 13:26:42.723473: val_loss -0.7837 +2024-11-21 13:26:42.723588: Pseudo dice [0.8498] +2024-11-21 13:26:42.723683: Epoch time: 19.14 s +2024-11-21 13:26:43.674071: +2024-11-21 13:26:43.674267: Epoch 496 +2024-11-21 13:26:43.674388: Current learning rate: 0.00944 +2024-11-21 13:27:02.920786: train_loss -0.7627 +2024-11-21 13:27:02.924435: val_loss -0.7461 +2024-11-21 13:27:02.924555: Pseudo dice [0.8476] +2024-11-21 13:27:02.924695: Epoch time: 19.25 s +2024-11-21 13:27:03.718334: +2024-11-21 13:27:03.718555: Epoch 497 +2024-11-21 13:27:03.718678: Current learning rate: 0.00944 +2024-11-21 13:27:23.167750: train_loss -0.7553 +2024-11-21 13:27:23.174829: val_loss -0.7683 +2024-11-21 13:27:23.174970: Pseudo dice [0.8496] +2024-11-21 13:27:23.175077: Epoch time: 19.45 s +2024-11-21 13:27:23.963619: +2024-11-21 13:27:23.963814: Epoch 498 +2024-11-21 13:27:23.963936: Current learning rate: 0.00944 +2024-11-21 13:27:43.420870: train_loss -0.7552 +2024-11-21 13:27:43.424541: val_loss -0.7851 +2024-11-21 13:27:43.424673: Pseudo dice [0.8487] +2024-11-21 13:27:43.424779: Epoch time: 19.46 s +2024-11-21 13:27:44.267297: +2024-11-21 13:27:44.267496: Epoch 499 +2024-11-21 13:27:44.267605: Current learning rate: 0.00944 +2024-11-21 13:28:04.106433: train_loss -0.7551 +2024-11-21 13:28:04.114320: val_loss -0.7279 +2024-11-21 13:28:04.114456: Pseudo dice [0.8371] +2024-11-21 13:28:04.114547: Epoch time: 19.84 s +2024-11-21 13:28:05.141956: +2024-11-21 13:28:05.142155: Epoch 500 +2024-11-21 13:28:05.142283: Current learning rate: 0.00944 +2024-11-21 13:28:23.576016: train_loss -0.7593 +2024-11-21 13:28:23.580079: val_loss -0.6967 +2024-11-21 13:28:23.580241: Pseudo dice [0.8079] +2024-11-21 13:28:23.580556: Epoch time: 18.43 s +2024-11-21 13:28:24.374391: +2024-11-21 13:28:24.374577: Epoch 501 +2024-11-21 13:28:24.374689: Current learning rate: 0.00943 +2024-11-21 13:28:43.338014: train_loss -0.7477 +2024-11-21 13:28:43.346110: val_loss -0.7391 +2024-11-21 13:28:43.346237: Pseudo dice [0.8369] +2024-11-21 13:28:43.346341: Epoch time: 18.96 s +2024-11-21 13:28:44.181855: +2024-11-21 13:28:44.182069: Epoch 502 +2024-11-21 13:28:44.182195: Current learning rate: 0.00943 +2024-11-21 13:29:03.489704: train_loss -0.748 +2024-11-21 13:29:03.497569: val_loss -0.7435 +2024-11-21 13:29:03.497708: Pseudo dice [0.8178] +2024-11-21 13:29:03.497807: Epoch time: 19.31 s +2024-11-21 13:29:04.737521: +2024-11-21 13:29:04.737721: Epoch 503 +2024-11-21 13:29:04.737855: Current learning rate: 0.00943 +2024-11-21 13:29:24.005469: train_loss -0.7506 +2024-11-21 13:29:24.012259: val_loss -0.7552 +2024-11-21 13:29:24.012398: Pseudo dice [0.8309] +2024-11-21 13:29:24.012488: Epoch time: 19.27 s +2024-11-21 13:29:24.840458: +2024-11-21 13:29:24.840671: Epoch 504 +2024-11-21 13:29:24.840794: Current learning rate: 0.00943 +2024-11-21 13:29:44.512076: train_loss -0.7541 +2024-11-21 13:29:44.531714: val_loss -0.751 +2024-11-21 13:29:44.531891: Pseudo dice [0.8483] +2024-11-21 13:29:44.531996: Epoch time: 19.67 s +2024-11-21 13:29:45.693576: +2024-11-21 13:29:45.693849: Epoch 505 +2024-11-21 13:29:45.693999: Current learning rate: 0.00943 +2024-11-21 13:30:06.094645: train_loss -0.7459 +2024-11-21 13:30:06.102470: val_loss -0.757 +2024-11-21 13:30:06.102630: Pseudo dice [0.8478] +2024-11-21 13:30:06.102728: Epoch time: 20.4 s +2024-11-21 13:30:06.898804: +2024-11-21 13:30:06.899031: Epoch 506 +2024-11-21 13:30:06.899156: Current learning rate: 0.00943 +2024-11-21 13:30:26.325861: train_loss -0.7692 +2024-11-21 13:30:26.345948: val_loss -0.7445 +2024-11-21 13:30:26.346119: Pseudo dice [0.8357] +2024-11-21 13:30:26.346232: Epoch time: 19.43 s +2024-11-21 13:30:27.142848: +2024-11-21 13:30:27.143149: Epoch 507 +2024-11-21 13:30:27.143278: Current learning rate: 0.00943 +2024-11-21 13:30:46.569134: train_loss -0.7483 +2024-11-21 13:30:46.571803: val_loss -0.7589 +2024-11-21 13:30:46.571944: Pseudo dice [0.8449] +2024-11-21 13:30:46.572045: Epoch time: 19.43 s +2024-11-21 13:30:47.380486: +2024-11-21 13:30:47.380669: Epoch 508 +2024-11-21 13:30:47.380783: Current learning rate: 0.00943 +2024-11-21 13:31:06.127187: train_loss -0.7586 +2024-11-21 13:31:06.130158: val_loss -0.7813 +2024-11-21 13:31:06.130263: Pseudo dice [0.8541] +2024-11-21 13:31:06.130351: Epoch time: 18.75 s +2024-11-21 13:31:06.932534: +2024-11-21 13:31:06.932724: Epoch 509 +2024-11-21 13:31:06.932863: Current learning rate: 0.00943 +2024-11-21 13:31:26.178989: train_loss -0.7502 +2024-11-21 13:31:26.185084: val_loss -0.755 +2024-11-21 13:31:26.185246: Pseudo dice [0.8512] +2024-11-21 13:31:26.185354: Epoch time: 19.25 s +2024-11-21 13:31:27.069329: +2024-11-21 13:31:27.069541: Epoch 510 +2024-11-21 13:31:27.069668: Current learning rate: 0.00942 +2024-11-21 13:31:46.709029: train_loss -0.7627 +2024-11-21 13:31:46.713987: val_loss -0.7704 +2024-11-21 13:31:46.714116: Pseudo dice [0.8448] +2024-11-21 13:31:46.714211: Epoch time: 19.64 s +2024-11-21 13:31:47.524625: +2024-11-21 13:31:47.524807: Epoch 511 +2024-11-21 13:31:47.524925: Current learning rate: 0.00942 +2024-11-21 13:32:07.050781: train_loss -0.7392 +2024-11-21 13:32:07.071632: val_loss -0.7416 +2024-11-21 13:32:07.071808: Pseudo dice [0.8335] +2024-11-21 13:32:07.071913: Epoch time: 19.53 s +2024-11-21 13:32:08.007540: +2024-11-21 13:32:08.007720: Epoch 512 +2024-11-21 13:32:08.007845: Current learning rate: 0.00942 +2024-11-21 13:32:27.243927: train_loss -0.7298 +2024-11-21 13:32:27.252935: val_loss -0.7411 +2024-11-21 13:32:27.253085: Pseudo dice [0.8243] +2024-11-21 13:32:27.253325: Epoch time: 19.24 s +2024-11-21 13:32:28.069052: +2024-11-21 13:32:28.069258: Epoch 513 +2024-11-21 13:32:28.069397: Current learning rate: 0.00942 +2024-11-21 13:32:47.978822: train_loss -0.7558 +2024-11-21 13:32:47.987883: val_loss -0.7618 +2024-11-21 13:32:47.988026: Pseudo dice [0.8323] +2024-11-21 13:32:47.988149: Epoch time: 19.91 s +2024-11-21 13:32:49.213727: +2024-11-21 13:32:49.213937: Epoch 514 +2024-11-21 13:32:49.214072: Current learning rate: 0.00942 +2024-11-21 13:33:08.760901: train_loss -0.759 +2024-11-21 13:33:08.776948: val_loss -0.7557 +2024-11-21 13:33:08.777112: Pseudo dice [0.852] +2024-11-21 13:33:08.777226: Epoch time: 19.55 s +2024-11-21 13:33:09.752322: +2024-11-21 13:33:09.752532: Epoch 515 +2024-11-21 13:33:09.752660: Current learning rate: 0.00942 +2024-11-21 13:33:29.049122: train_loss -0.765 +2024-11-21 13:33:29.054798: val_loss -0.7453 +2024-11-21 13:33:29.054976: Pseudo dice [0.8481] +2024-11-21 13:33:29.055076: Epoch time: 19.3 s +2024-11-21 13:33:29.940256: +2024-11-21 13:33:29.940467: Epoch 516 +2024-11-21 13:33:29.940586: Current learning rate: 0.00942 +2024-11-21 13:33:50.025927: train_loss -0.7525 +2024-11-21 13:33:50.029147: val_loss -0.7603 +2024-11-21 13:33:50.029276: Pseudo dice [0.8449] +2024-11-21 13:33:50.029389: Epoch time: 20.09 s +2024-11-21 13:33:50.833640: +2024-11-21 13:33:50.833848: Epoch 517 +2024-11-21 13:33:50.833962: Current learning rate: 0.00942 +2024-11-21 13:34:09.446795: train_loss -0.7507 +2024-11-21 13:34:09.455118: val_loss -0.7613 +2024-11-21 13:34:09.455500: Pseudo dice [0.8413] +2024-11-21 13:34:09.455636: Epoch time: 18.61 s +2024-11-21 13:34:10.310148: +2024-11-21 13:34:10.310370: Epoch 518 +2024-11-21 13:34:10.310517: Current learning rate: 0.00942 +2024-11-21 13:34:29.796305: train_loss -0.7619 +2024-11-21 13:34:29.808233: val_loss -0.7562 +2024-11-21 13:34:29.808395: Pseudo dice [0.8479] +2024-11-21 13:34:29.808497: Epoch time: 19.49 s +2024-11-21 13:34:30.800321: +2024-11-21 13:34:30.800517: Epoch 519 +2024-11-21 13:34:30.800646: Current learning rate: 0.00941 +2024-11-21 13:34:50.355051: train_loss -0.7562 +2024-11-21 13:34:50.380408: val_loss -0.7648 +2024-11-21 13:34:50.380575: Pseudo dice [0.8546] +2024-11-21 13:34:50.380678: Epoch time: 19.56 s +2024-11-21 13:34:51.343695: +2024-11-21 13:34:51.343881: Epoch 520 +2024-11-21 13:34:51.344007: Current learning rate: 0.00941 +2024-11-21 13:35:11.487684: train_loss -0.754 +2024-11-21 13:35:11.495299: val_loss -0.7498 +2024-11-21 13:35:11.495430: Pseudo dice [0.8376] +2024-11-21 13:35:11.495531: Epoch time: 20.14 s +2024-11-21 13:35:12.333572: +2024-11-21 13:35:12.333792: Epoch 521 +2024-11-21 13:35:12.333906: Current learning rate: 0.00941 +2024-11-21 13:35:31.150630: train_loss -0.7386 +2024-11-21 13:35:31.158083: val_loss -0.7462 +2024-11-21 13:35:31.158222: Pseudo dice [0.8321] +2024-11-21 13:35:31.158336: Epoch time: 18.82 s +2024-11-21 13:35:32.038472: +2024-11-21 13:35:32.038672: Epoch 522 +2024-11-21 13:35:32.038785: Current learning rate: 0.00941 +2024-11-21 13:35:50.391358: train_loss -0.7463 +2024-11-21 13:35:50.398507: val_loss -0.7597 +2024-11-21 13:35:50.398630: Pseudo dice [0.8481] +2024-11-21 13:35:50.398712: Epoch time: 18.35 s +2024-11-21 13:35:51.324133: +2024-11-21 13:35:51.324322: Epoch 523 +2024-11-21 13:35:51.324450: Current learning rate: 0.00941 +2024-11-21 13:36:10.527112: train_loss -0.739 +2024-11-21 13:36:10.536795: val_loss -0.7243 +2024-11-21 13:36:10.536954: Pseudo dice [0.8296] +2024-11-21 13:36:10.537045: Epoch time: 19.2 s +2024-11-21 13:36:11.403951: +2024-11-21 13:36:11.404170: Epoch 524 +2024-11-21 13:36:11.404286: Current learning rate: 0.00941 +2024-11-21 13:36:28.522533: train_loss -0.7385 +2024-11-21 13:36:28.525437: val_loss -0.761 +2024-11-21 13:36:28.525574: Pseudo dice [0.8318] +2024-11-21 13:36:28.525665: Epoch time: 17.12 s +2024-11-21 13:36:29.339048: +2024-11-21 13:36:29.339217: Epoch 525 +2024-11-21 13:36:29.339329: Current learning rate: 0.00941 +2024-11-21 13:36:47.719383: train_loss -0.7559 +2024-11-21 13:36:47.725455: val_loss -0.7334 +2024-11-21 13:36:47.725601: Pseudo dice [0.8299] +2024-11-21 13:36:47.725691: Epoch time: 18.38 s +2024-11-21 13:36:48.967082: +2024-11-21 13:36:48.967296: Epoch 526 +2024-11-21 13:36:48.967425: Current learning rate: 0.00941 +2024-11-21 13:37:08.925493: train_loss -0.7592 +2024-11-21 13:37:08.950066: val_loss -0.7451 +2024-11-21 13:37:08.950216: Pseudo dice [0.8441] +2024-11-21 13:37:08.950384: Epoch time: 19.96 s +2024-11-21 13:37:09.973937: +2024-11-21 13:37:09.974144: Epoch 527 +2024-11-21 13:37:09.974268: Current learning rate: 0.00941 +2024-11-21 13:37:29.801357: train_loss -0.7472 +2024-11-21 13:37:29.805675: val_loss -0.7528 +2024-11-21 13:37:29.805831: Pseudo dice [0.836] +2024-11-21 13:37:29.805963: Epoch time: 19.83 s +2024-11-21 13:37:30.651683: +2024-11-21 13:37:30.651876: Epoch 528 +2024-11-21 13:37:30.651992: Current learning rate: 0.0094 +2024-11-21 13:37:49.275228: train_loss -0.7515 +2024-11-21 13:37:49.280679: val_loss -0.7622 +2024-11-21 13:37:49.280812: Pseudo dice [0.8439] +2024-11-21 13:37:49.280900: Epoch time: 18.62 s +2024-11-21 13:37:50.107834: +2024-11-21 13:37:50.108037: Epoch 529 +2024-11-21 13:37:50.108171: Current learning rate: 0.0094 +2024-11-21 13:38:09.683642: train_loss -0.74 +2024-11-21 13:38:09.688842: val_loss -0.7312 +2024-11-21 13:38:09.688961: Pseudo dice [0.8357] +2024-11-21 13:38:09.689066: Epoch time: 19.58 s +2024-11-21 13:38:10.583914: +2024-11-21 13:38:10.584101: Epoch 530 +2024-11-21 13:38:10.584224: Current learning rate: 0.0094 +2024-11-21 13:38:29.129632: train_loss -0.7527 +2024-11-21 13:38:29.137034: val_loss -0.7598 +2024-11-21 13:38:29.137172: Pseudo dice [0.8375] +2024-11-21 13:38:29.137266: Epoch time: 18.55 s +2024-11-21 13:38:30.119315: +2024-11-21 13:38:30.119511: Epoch 531 +2024-11-21 13:38:30.119639: Current learning rate: 0.0094 +2024-11-21 13:38:50.246017: train_loss -0.752 +2024-11-21 13:38:50.251876: val_loss -0.7736 +2024-11-21 13:38:50.252020: Pseudo dice [0.8445] +2024-11-21 13:38:50.252128: Epoch time: 20.13 s +2024-11-21 13:38:51.059739: +2024-11-21 13:38:51.059925: Epoch 532 +2024-11-21 13:38:51.060034: Current learning rate: 0.0094 +2024-11-21 13:39:10.686890: train_loss -0.7495 +2024-11-21 13:39:10.688336: val_loss -0.7569 +2024-11-21 13:39:10.688463: Pseudo dice [0.8328] +2024-11-21 13:39:10.688564: Epoch time: 19.63 s +2024-11-21 13:39:11.486299: +2024-11-21 13:39:11.486503: Epoch 533 +2024-11-21 13:39:11.486628: Current learning rate: 0.0094 +2024-11-21 13:39:31.026260: train_loss -0.7577 +2024-11-21 13:39:31.035861: val_loss -0.7679 +2024-11-21 13:39:31.035994: Pseudo dice [0.833] +2024-11-21 13:39:31.036078: Epoch time: 19.54 s +2024-11-21 13:39:31.832020: +2024-11-21 13:39:31.832202: Epoch 534 +2024-11-21 13:39:31.832324: Current learning rate: 0.0094 +2024-11-21 13:39:50.807671: train_loss -0.7729 +2024-11-21 13:39:50.811297: val_loss -0.751 +2024-11-21 13:39:50.811449: Pseudo dice [0.8285] +2024-11-21 13:39:50.811557: Epoch time: 18.98 s +2024-11-21 13:39:51.742580: +2024-11-21 13:39:51.742788: Epoch 535 +2024-11-21 13:39:51.742905: Current learning rate: 0.0094 +2024-11-21 13:40:10.511535: train_loss -0.7263 +2024-11-21 13:40:10.513780: val_loss -0.7441 +2024-11-21 13:40:10.513883: Pseudo dice [0.8184] +2024-11-21 13:40:10.514052: Epoch time: 18.77 s +2024-11-21 13:40:11.308253: +2024-11-21 13:40:11.308465: Epoch 536 +2024-11-21 13:40:11.308585: Current learning rate: 0.00939 +2024-11-21 13:40:29.124711: train_loss -0.723 +2024-11-21 13:40:29.126368: val_loss -0.7265 +2024-11-21 13:40:29.126476: Pseudo dice [0.8324] +2024-11-21 13:40:29.126563: Epoch time: 17.82 s +2024-11-21 13:40:30.319057: +2024-11-21 13:40:30.319293: Epoch 537 +2024-11-21 13:40:30.319425: Current learning rate: 0.00939 +2024-11-21 13:40:49.490992: train_loss -0.715 +2024-11-21 13:40:49.505688: val_loss -0.7066 +2024-11-21 13:40:49.505846: Pseudo dice [0.8254] +2024-11-21 13:40:49.505949: Epoch time: 19.17 s +2024-11-21 13:40:50.311574: +2024-11-21 13:40:50.311778: Epoch 538 +2024-11-21 13:40:50.311921: Current learning rate: 0.00939 +2024-11-21 13:41:09.071643: train_loss -0.7356 +2024-11-21 13:41:09.075649: val_loss -0.7785 +2024-11-21 13:41:09.075788: Pseudo dice [0.8423] +2024-11-21 13:41:09.076113: Epoch time: 18.76 s +2024-11-21 13:41:09.901634: +2024-11-21 13:41:09.901849: Epoch 539 +2024-11-21 13:41:09.901979: Current learning rate: 0.00939 +2024-11-21 13:41:28.413671: train_loss -0.7433 +2024-11-21 13:41:28.421188: val_loss -0.7397 +2024-11-21 13:41:28.421318: Pseudo dice [0.844] +2024-11-21 13:41:28.421407: Epoch time: 18.51 s +2024-11-21 13:41:29.315681: +2024-11-21 13:41:29.315902: Epoch 540 +2024-11-21 13:41:29.316026: Current learning rate: 0.00939 +2024-11-21 13:41:47.454021: train_loss -0.7555 +2024-11-21 13:41:47.464247: val_loss -0.7633 +2024-11-21 13:41:47.464362: Pseudo dice [0.8397] +2024-11-21 13:41:47.464446: Epoch time: 18.14 s +2024-11-21 13:41:48.395861: +2024-11-21 13:41:48.396042: Epoch 541 +2024-11-21 13:41:48.396160: Current learning rate: 0.00939 +2024-11-21 13:42:07.379607: train_loss -0.7544 +2024-11-21 13:42:07.383063: val_loss -0.7745 +2024-11-21 13:42:07.383163: Pseudo dice [0.8502] +2024-11-21 13:42:07.383280: Epoch time: 18.98 s +2024-11-21 13:42:08.189154: +2024-11-21 13:42:08.189348: Epoch 542 +2024-11-21 13:42:08.189479: Current learning rate: 0.00939 +2024-11-21 13:42:27.349378: train_loss -0.7598 +2024-11-21 13:42:27.355983: val_loss -0.7379 +2024-11-21 13:42:27.356188: Pseudo dice [0.8414] +2024-11-21 13:42:27.356294: Epoch time: 19.16 s +2024-11-21 13:42:28.180542: +2024-11-21 13:42:28.180743: Epoch 543 +2024-11-21 13:42:28.180874: Current learning rate: 0.00939 +2024-11-21 13:42:47.574482: train_loss -0.7484 +2024-11-21 13:42:47.576449: val_loss -0.7542 +2024-11-21 13:42:47.576560: Pseudo dice [0.8551] +2024-11-21 13:42:47.576889: Epoch time: 19.39 s +2024-11-21 13:42:48.368130: +2024-11-21 13:42:48.368327: Epoch 544 +2024-11-21 13:42:48.368455: Current learning rate: 0.00939 +2024-11-21 13:43:07.014066: train_loss -0.7602 +2024-11-21 13:43:07.018239: val_loss -0.789 +2024-11-21 13:43:07.018371: Pseudo dice [0.8344] +2024-11-21 13:43:07.018451: Epoch time: 18.65 s +2024-11-21 13:43:07.958121: +2024-11-21 13:43:07.958318: Epoch 545 +2024-11-21 13:43:07.958446: Current learning rate: 0.00938 +2024-11-21 13:43:26.459680: train_loss -0.7562 +2024-11-21 13:43:26.466533: val_loss -0.7566 +2024-11-21 13:43:26.466672: Pseudo dice [0.8383] +2024-11-21 13:43:26.466773: Epoch time: 18.5 s +2024-11-21 13:43:27.374774: +2024-11-21 13:43:27.375020: Epoch 546 +2024-11-21 13:43:27.375165: Current learning rate: 0.00938 +2024-11-21 13:43:45.288480: train_loss -0.7419 +2024-11-21 13:43:45.294973: val_loss -0.7529 +2024-11-21 13:43:45.295116: Pseudo dice [0.8357] +2024-11-21 13:43:45.295211: Epoch time: 17.91 s +2024-11-21 13:43:46.094240: +2024-11-21 13:43:46.094415: Epoch 547 +2024-11-21 13:43:46.094532: Current learning rate: 0.00938 +2024-11-21 13:44:04.327480: train_loss -0.7549 +2024-11-21 13:44:04.331509: val_loss -0.7404 +2024-11-21 13:44:04.331666: Pseudo dice [0.8476] +2024-11-21 13:44:04.331755: Epoch time: 18.23 s +2024-11-21 13:44:05.135737: +2024-11-21 13:44:05.136002: Epoch 548 +2024-11-21 13:44:05.136137: Current learning rate: 0.00938 +2024-11-21 13:44:25.804409: train_loss -0.7585 +2024-11-21 13:44:25.809871: val_loss -0.765 +2024-11-21 13:44:25.810021: Pseudo dice [0.8412] +2024-11-21 13:44:25.810114: Epoch time: 20.67 s +2024-11-21 13:44:27.024545: +2024-11-21 13:44:27.024759: Epoch 549 +2024-11-21 13:44:27.024868: Current learning rate: 0.00938 +2024-11-21 13:44:46.704857: train_loss -0.7583 +2024-11-21 13:44:46.707188: val_loss -0.7484 +2024-11-21 13:44:46.707303: Pseudo dice [0.8402] +2024-11-21 13:44:46.707422: Epoch time: 19.68 s +2024-11-21 13:44:47.752697: +2024-11-21 13:44:47.752887: Epoch 550 +2024-11-21 13:44:47.753015: Current learning rate: 0.00938 +2024-11-21 13:45:07.147465: train_loss -0.7543 +2024-11-21 13:45:07.149663: val_loss -0.7756 +2024-11-21 13:45:07.149756: Pseudo dice [0.8535] +2024-11-21 13:45:07.149833: Epoch time: 19.4 s +2024-11-21 13:45:07.948977: +2024-11-21 13:45:07.949208: Epoch 551 +2024-11-21 13:45:07.949341: Current learning rate: 0.00938 +2024-11-21 13:45:27.431002: train_loss -0.7554 +2024-11-21 13:45:27.438851: val_loss -0.7553 +2024-11-21 13:45:27.438979: Pseudo dice [0.8459] +2024-11-21 13:45:27.439076: Epoch time: 19.48 s +2024-11-21 13:45:28.288038: +2024-11-21 13:45:28.288247: Epoch 552 +2024-11-21 13:45:28.288371: Current learning rate: 0.00938 +2024-11-21 13:45:46.716136: train_loss -0.7648 +2024-11-21 13:45:46.727075: val_loss -0.7574 +2024-11-21 13:45:46.727238: Pseudo dice [0.8505] +2024-11-21 13:45:46.727599: Epoch time: 18.43 s +2024-11-21 13:45:47.558070: +2024-11-21 13:45:47.558312: Epoch 553 +2024-11-21 13:45:47.558456: Current learning rate: 0.00938 +2024-11-21 13:46:05.628839: train_loss -0.7681 +2024-11-21 13:46:05.636641: val_loss -0.7528 +2024-11-21 13:46:05.636771: Pseudo dice [0.8341] +2024-11-21 13:46:05.636880: Epoch time: 18.07 s +2024-11-21 13:46:06.480869: +2024-11-21 13:46:06.481069: Epoch 554 +2024-11-21 13:46:06.481193: Current learning rate: 0.00937 +2024-11-21 13:46:25.312650: train_loss -0.7553 +2024-11-21 13:46:25.319524: val_loss -0.7469 +2024-11-21 13:46:25.319652: Pseudo dice [0.8467] +2024-11-21 13:46:25.319737: Epoch time: 18.83 s +2024-11-21 13:46:26.128476: +2024-11-21 13:46:26.128696: Epoch 555 +2024-11-21 13:46:26.128828: Current learning rate: 0.00937 +2024-11-21 13:46:45.618964: train_loss -0.753 +2024-11-21 13:46:45.626695: val_loss -0.7552 +2024-11-21 13:46:45.626820: Pseudo dice [0.8456] +2024-11-21 13:46:45.626910: Epoch time: 19.49 s +2024-11-21 13:46:46.487152: +2024-11-21 13:46:46.487370: Epoch 556 +2024-11-21 13:46:46.487499: Current learning rate: 0.00937 +2024-11-21 13:47:05.696869: train_loss -0.756 +2024-11-21 13:47:05.701345: val_loss -0.7439 +2024-11-21 13:47:05.701500: Pseudo dice [0.839] +2024-11-21 13:47:05.701614: Epoch time: 19.21 s +2024-11-21 13:47:06.734456: +2024-11-21 13:47:06.734640: Epoch 557 +2024-11-21 13:47:06.734760: Current learning rate: 0.00937 +2024-11-21 13:47:25.209685: train_loss -0.7546 +2024-11-21 13:47:25.218237: val_loss -0.76 +2024-11-21 13:47:25.218407: Pseudo dice [0.8504] +2024-11-21 13:47:25.218515: Epoch time: 18.48 s +2024-11-21 13:47:26.217400: +2024-11-21 13:47:26.217585: Epoch 558 +2024-11-21 13:47:26.217716: Current learning rate: 0.00937 +2024-11-21 13:47:46.240256: train_loss -0.7619 +2024-11-21 13:47:46.243598: val_loss -0.7366 +2024-11-21 13:47:46.243742: Pseudo dice [0.8478] +2024-11-21 13:47:46.243837: Epoch time: 20.02 s +2024-11-21 13:47:47.149265: +2024-11-21 13:47:47.149444: Epoch 559 +2024-11-21 13:47:47.149550: Current learning rate: 0.00937 +2024-11-21 13:48:06.221950: train_loss -0.7638 +2024-11-21 13:48:06.235453: val_loss -0.7696 +2024-11-21 13:48:06.235580: Pseudo dice [0.8681] +2024-11-21 13:48:06.235726: Epoch time: 19.07 s +2024-11-21 13:48:07.431520: +2024-11-21 13:48:07.431795: Epoch 560 +2024-11-21 13:48:07.431923: Current learning rate: 0.00937 +2024-11-21 13:48:25.002032: train_loss -0.7566 +2024-11-21 13:48:25.012826: val_loss -0.768 +2024-11-21 13:48:25.012977: Pseudo dice [0.8407] +2024-11-21 13:48:25.013078: Epoch time: 17.57 s +2024-11-21 13:48:25.842287: +2024-11-21 13:48:25.842497: Epoch 561 +2024-11-21 13:48:25.842628: Current learning rate: 0.00937 +2024-11-21 13:48:44.653378: train_loss -0.7558 +2024-11-21 13:48:44.656354: val_loss -0.751 +2024-11-21 13:48:44.656461: Pseudo dice [0.8564] +2024-11-21 13:48:44.656549: Epoch time: 18.81 s +2024-11-21 13:48:44.656630: Yayy! New best EMA pseudo Dice: 0.8465 +2024-11-21 13:48:45.670739: +2024-11-21 13:48:45.670951: Epoch 562 +2024-11-21 13:48:45.671076: Current learning rate: 0.00937 +2024-11-21 13:49:04.584071: train_loss -0.7607 +2024-11-21 13:49:04.588221: val_loss -0.7606 +2024-11-21 13:49:04.588333: Pseudo dice [0.8578] +2024-11-21 13:49:04.588414: Epoch time: 18.91 s +2024-11-21 13:49:04.588490: Yayy! New best EMA pseudo Dice: 0.8476 +2024-11-21 13:49:05.615710: +2024-11-21 13:49:05.615925: Epoch 563 +2024-11-21 13:49:05.616037: Current learning rate: 0.00936 +2024-11-21 13:49:23.849038: train_loss -0.7442 +2024-11-21 13:49:23.851950: val_loss -0.7414 +2024-11-21 13:49:23.852075: Pseudo dice [0.8477] +2024-11-21 13:49:23.852170: Epoch time: 18.23 s +2024-11-21 13:49:23.852236: Yayy! New best EMA pseudo Dice: 0.8476 +2024-11-21 13:49:24.927787: +2024-11-21 13:49:24.927981: Epoch 564 +2024-11-21 13:49:24.928099: Current learning rate: 0.00936 +2024-11-21 13:49:44.497307: train_loss -0.7546 +2024-11-21 13:49:44.506248: val_loss -0.7654 +2024-11-21 13:49:44.506413: Pseudo dice [0.8478] +2024-11-21 13:49:44.506525: Epoch time: 19.57 s +2024-11-21 13:49:44.506600: Yayy! New best EMA pseudo Dice: 0.8477 +2024-11-21 13:49:45.543064: +2024-11-21 13:49:45.543255: Epoch 565 +2024-11-21 13:49:45.543370: Current learning rate: 0.00936 +2024-11-21 13:50:04.429658: train_loss -0.7567 +2024-11-21 13:50:04.482913: val_loss -0.7721 +2024-11-21 13:50:04.483100: Pseudo dice [0.852] +2024-11-21 13:50:04.483187: Epoch time: 18.89 s +2024-11-21 13:50:04.483255: Yayy! New best EMA pseudo Dice: 0.8481 +2024-11-21 13:50:05.647052: +2024-11-21 13:50:05.647269: Epoch 566 +2024-11-21 13:50:05.647386: Current learning rate: 0.00936 +2024-11-21 13:50:24.850103: train_loss -0.7551 +2024-11-21 13:50:24.855740: val_loss -0.7895 +2024-11-21 13:50:24.855886: Pseudo dice [0.852] +2024-11-21 13:50:24.855999: Epoch time: 19.2 s +2024-11-21 13:50:24.856100: Yayy! New best EMA pseudo Dice: 0.8485 +2024-11-21 13:50:25.968338: +2024-11-21 13:50:25.968546: Epoch 567 +2024-11-21 13:50:25.968680: Current learning rate: 0.00936 +2024-11-21 13:50:45.742511: train_loss -0.7382 +2024-11-21 13:50:45.748821: val_loss -0.7221 +2024-11-21 13:50:45.748958: Pseudo dice [0.8262] +2024-11-21 13:50:45.749043: Epoch time: 19.77 s +2024-11-21 13:50:46.587713: +2024-11-21 13:50:46.587902: Epoch 568 +2024-11-21 13:50:46.588042: Current learning rate: 0.00936 +2024-11-21 13:51:06.426143: train_loss -0.7478 +2024-11-21 13:51:06.433140: val_loss -0.7351 +2024-11-21 13:51:06.433290: Pseudo dice [0.8291] +2024-11-21 13:51:06.433401: Epoch time: 19.84 s +2024-11-21 13:51:07.244936: +2024-11-21 13:51:07.245143: Epoch 569 +2024-11-21 13:51:07.245261: Current learning rate: 0.00936 +2024-11-21 13:51:26.652905: train_loss -0.7545 +2024-11-21 13:51:26.660281: val_loss -0.7397 +2024-11-21 13:51:26.660420: Pseudo dice [0.8193] +2024-11-21 13:51:26.660501: Epoch time: 19.41 s +2024-11-21 13:51:27.953142: +2024-11-21 13:51:27.953355: Epoch 570 +2024-11-21 13:51:27.953481: Current learning rate: 0.00936 +2024-11-21 13:51:47.275117: train_loss -0.7601 +2024-11-21 13:51:47.288167: val_loss -0.7547 +2024-11-21 13:51:47.288314: Pseudo dice [0.8397] +2024-11-21 13:51:47.288419: Epoch time: 19.32 s +2024-11-21 13:51:48.125629: +2024-11-21 13:51:48.125865: Epoch 571 +2024-11-21 13:51:48.125981: Current learning rate: 0.00936 +2024-11-21 13:52:08.342575: train_loss -0.7504 +2024-11-21 13:52:08.347109: val_loss -0.7609 +2024-11-21 13:52:08.347221: Pseudo dice [0.8378] +2024-11-21 13:52:08.347351: Epoch time: 20.22 s +2024-11-21 13:52:09.154436: +2024-11-21 13:52:09.154628: Epoch 572 +2024-11-21 13:52:09.154753: Current learning rate: 0.00935 +2024-11-21 13:52:28.780878: train_loss -0.7476 +2024-11-21 13:52:28.792782: val_loss -0.7514 +2024-11-21 13:52:28.792921: Pseudo dice [0.8456] +2024-11-21 13:52:28.793018: Epoch time: 19.63 s +2024-11-21 13:52:29.747264: +2024-11-21 13:52:29.747478: Epoch 573 +2024-11-21 13:52:29.747614: Current learning rate: 0.00935 +2024-11-21 13:52:49.567249: train_loss -0.7646 +2024-11-21 13:52:49.573506: val_loss -0.7651 +2024-11-21 13:52:49.573653: Pseudo dice [0.8412] +2024-11-21 13:52:49.573746: Epoch time: 19.82 s +2024-11-21 13:52:50.422289: +2024-11-21 13:52:50.422488: Epoch 574 +2024-11-21 13:52:50.422617: Current learning rate: 0.00935 +2024-11-21 13:53:10.330722: train_loss -0.7654 +2024-11-21 13:53:10.334368: val_loss -0.7324 +2024-11-21 13:53:10.334478: Pseudo dice [0.837] +2024-11-21 13:53:10.334563: Epoch time: 19.91 s +2024-11-21 13:53:11.140454: +2024-11-21 13:53:11.140658: Epoch 575 +2024-11-21 13:53:11.140801: Current learning rate: 0.00935 +2024-11-21 13:53:30.994697: train_loss -0.7601 +2024-11-21 13:53:31.008287: val_loss -0.762 +2024-11-21 13:53:31.008453: Pseudo dice [0.8604] +2024-11-21 13:53:31.008557: Epoch time: 19.86 s +2024-11-21 13:53:32.091672: +2024-11-21 13:53:32.091882: Epoch 576 +2024-11-21 13:53:32.091997: Current learning rate: 0.00935 +2024-11-21 13:53:52.374604: train_loss -0.7527 +2024-11-21 13:53:52.383686: val_loss -0.7503 +2024-11-21 13:53:52.383838: Pseudo dice [0.8431] +2024-11-21 13:53:52.383937: Epoch time: 20.28 s +2024-11-21 13:53:53.197123: +2024-11-21 13:53:53.197312: Epoch 577 +2024-11-21 13:53:53.197437: Current learning rate: 0.00935 +2024-11-21 13:54:12.477564: train_loss -0.7434 +2024-11-21 13:54:12.489482: val_loss -0.7544 +2024-11-21 13:54:12.489630: Pseudo dice [0.8337] +2024-11-21 13:54:12.489722: Epoch time: 19.28 s +2024-11-21 13:54:13.320434: +2024-11-21 13:54:13.320652: Epoch 578 +2024-11-21 13:54:13.320794: Current learning rate: 0.00935 +2024-11-21 13:54:32.966024: train_loss -0.7389 +2024-11-21 13:54:32.977724: val_loss -0.7191 +2024-11-21 13:54:32.977867: Pseudo dice [0.8076] +2024-11-21 13:54:32.977992: Epoch time: 19.65 s +2024-11-21 13:54:34.020985: +2024-11-21 13:54:34.021172: Epoch 579 +2024-11-21 13:54:34.021294: Current learning rate: 0.00935 +2024-11-21 13:54:52.612959: train_loss -0.7524 +2024-11-21 13:54:52.619344: val_loss -0.7767 +2024-11-21 13:54:52.619479: Pseudo dice [0.8472] +2024-11-21 13:54:52.619584: Epoch time: 18.59 s +2024-11-21 13:54:53.596133: +2024-11-21 13:54:53.596334: Epoch 580 +2024-11-21 13:54:53.596455: Current learning rate: 0.00935 +2024-11-21 13:55:11.808077: train_loss -0.7433 +2024-11-21 13:55:11.833164: val_loss -0.7459 +2024-11-21 13:55:11.842914: Pseudo dice [0.8418] +2024-11-21 13:55:11.843075: Epoch time: 18.21 s +2024-11-21 13:55:13.107744: +2024-11-21 13:55:13.107985: Epoch 581 +2024-11-21 13:55:13.108110: Current learning rate: 0.00934 +2024-11-21 13:55:32.133555: train_loss -0.7437 +2024-11-21 13:55:32.135471: val_loss -0.7705 +2024-11-21 13:55:32.135600: Pseudo dice [0.8425] +2024-11-21 13:55:32.135689: Epoch time: 19.03 s +2024-11-21 13:55:33.119975: +2024-11-21 13:55:33.120193: Epoch 582 +2024-11-21 13:55:33.120325: Current learning rate: 0.00934 +2024-11-21 13:55:52.377399: train_loss -0.7588 +2024-11-21 13:55:52.388704: val_loss -0.727 +2024-11-21 13:55:52.388855: Pseudo dice [0.8485] +2024-11-21 13:55:52.388969: Epoch time: 19.26 s +2024-11-21 13:55:53.217944: +2024-11-21 13:55:53.218166: Epoch 583 +2024-11-21 13:55:53.218312: Current learning rate: 0.00934 +2024-11-21 13:56:12.000772: train_loss -0.7442 +2024-11-21 13:56:12.009776: val_loss -0.7435 +2024-11-21 13:56:12.009947: Pseudo dice [0.8563] +2024-11-21 13:56:12.010034: Epoch time: 18.78 s +2024-11-21 13:56:12.829941: +2024-11-21 13:56:12.830139: Epoch 584 +2024-11-21 13:56:12.830262: Current learning rate: 0.00934 +2024-11-21 13:56:31.846144: train_loss -0.7519 +2024-11-21 13:56:31.848759: val_loss -0.753 +2024-11-21 13:56:31.848898: Pseudo dice [0.8391] +2024-11-21 13:56:31.849008: Epoch time: 19.02 s +2024-11-21 13:56:32.917036: +2024-11-21 13:56:32.917245: Epoch 585 +2024-11-21 13:56:32.917369: Current learning rate: 0.00934 +2024-11-21 13:56:51.892638: train_loss -0.768 +2024-11-21 13:56:51.899703: val_loss -0.767 +2024-11-21 13:56:51.899833: Pseudo dice [0.8452] +2024-11-21 13:56:51.899928: Epoch time: 18.98 s +2024-11-21 13:56:52.957214: +2024-11-21 13:56:52.957431: Epoch 586 +2024-11-21 13:56:52.957550: Current learning rate: 0.00934 +2024-11-21 13:57:11.365684: train_loss -0.7448 +2024-11-21 13:57:11.380260: val_loss -0.7636 +2024-11-21 13:57:11.382292: Pseudo dice [0.8345] +2024-11-21 13:57:11.382448: Epoch time: 18.41 s +2024-11-21 13:57:12.266770: +2024-11-21 13:57:12.266969: Epoch 587 +2024-11-21 13:57:12.267109: Current learning rate: 0.00934 +2024-11-21 13:57:31.040525: train_loss -0.7543 +2024-11-21 13:57:31.042387: val_loss -0.7502 +2024-11-21 13:57:31.042477: Pseudo dice [0.8501] +2024-11-21 13:57:31.042557: Epoch time: 18.77 s +2024-11-21 13:57:31.846087: +2024-11-21 13:57:31.846264: Epoch 588 +2024-11-21 13:57:31.846378: Current learning rate: 0.00934 +2024-11-21 13:57:51.108968: train_loss -0.7604 +2024-11-21 13:57:51.114940: val_loss -0.7715 +2024-11-21 13:57:51.115086: Pseudo dice [0.8497] +2024-11-21 13:57:51.115189: Epoch time: 19.26 s +2024-11-21 13:57:51.924021: +2024-11-21 13:57:51.924221: Epoch 589 +2024-11-21 13:57:51.924355: Current learning rate: 0.00933 +2024-11-21 13:58:11.015451: train_loss -0.7614 +2024-11-21 13:58:11.020718: val_loss -0.7461 +2024-11-21 13:58:11.020842: Pseudo dice [0.8529] +2024-11-21 13:58:11.020929: Epoch time: 19.09 s +2024-11-21 13:58:11.886216: +2024-11-21 13:58:11.886400: Epoch 590 +2024-11-21 13:58:11.886515: Current learning rate: 0.00933 +2024-11-21 13:58:31.483126: train_loss -0.7578 +2024-11-21 13:58:31.490415: val_loss -0.7589 +2024-11-21 13:58:31.490563: Pseudo dice [0.858] +2024-11-21 13:58:31.490672: Epoch time: 19.6 s +2024-11-21 13:58:32.417772: +2024-11-21 13:58:32.417955: Epoch 591 +2024-11-21 13:58:32.418082: Current learning rate: 0.00933 +2024-11-21 13:58:51.176874: train_loss -0.7477 +2024-11-21 13:58:51.184286: val_loss -0.7341 +2024-11-21 13:58:51.184439: Pseudo dice [0.8461] +2024-11-21 13:58:51.184539: Epoch time: 18.76 s +2024-11-21 13:58:52.680903: +2024-11-21 13:58:52.681131: Epoch 592 +2024-11-21 13:58:52.681266: Current learning rate: 0.00933 +2024-11-21 13:59:11.224509: train_loss -0.7619 +2024-11-21 13:59:11.229949: val_loss -0.7654 +2024-11-21 13:59:11.230088: Pseudo dice [0.8412] +2024-11-21 13:59:11.230180: Epoch time: 18.54 s +2024-11-21 13:59:12.201885: +2024-11-21 13:59:12.202134: Epoch 593 +2024-11-21 13:59:12.202256: Current learning rate: 0.00933 +2024-11-21 13:59:31.313107: train_loss -0.7512 +2024-11-21 13:59:31.327470: val_loss -0.7528 +2024-11-21 13:59:31.327624: Pseudo dice [0.8423] +2024-11-21 13:59:31.327734: Epoch time: 19.11 s +2024-11-21 13:59:32.277445: +2024-11-21 13:59:32.277647: Epoch 594 +2024-11-21 13:59:32.277762: Current learning rate: 0.00933 +2024-11-21 13:59:53.111519: train_loss -0.762 +2024-11-21 13:59:53.116165: val_loss -0.7558 +2024-11-21 13:59:53.116287: Pseudo dice [0.8439] +2024-11-21 13:59:53.116441: Epoch time: 20.83 s +2024-11-21 13:59:54.067029: +2024-11-21 13:59:54.067246: Epoch 595 +2024-11-21 13:59:54.067370: Current learning rate: 0.00933 +2024-11-21 14:00:13.911439: train_loss -0.742 +2024-11-21 14:00:13.919163: val_loss -0.7494 +2024-11-21 14:00:13.919292: Pseudo dice [0.8467] +2024-11-21 14:00:13.919378: Epoch time: 19.85 s +2024-11-21 14:00:14.736480: +2024-11-21 14:00:14.736661: Epoch 596 +2024-11-21 14:00:14.736787: Current learning rate: 0.00933 +2024-11-21 14:00:32.643020: train_loss -0.749 +2024-11-21 14:00:32.651445: val_loss -0.7573 +2024-11-21 14:00:32.651585: Pseudo dice [0.8467] +2024-11-21 14:00:32.651694: Epoch time: 17.91 s +2024-11-21 14:00:33.620009: +2024-11-21 14:00:33.620209: Epoch 597 +2024-11-21 14:00:33.620342: Current learning rate: 0.00933 +2024-11-21 14:00:52.218890: train_loss -0.7589 +2024-11-21 14:00:52.224923: val_loss -0.7537 +2024-11-21 14:00:52.233279: Pseudo dice [0.844] +2024-11-21 14:00:52.235609: Epoch time: 18.6 s +2024-11-21 14:00:53.088479: +2024-11-21 14:00:53.088699: Epoch 598 +2024-11-21 14:00:53.088811: Current learning rate: 0.00932 +2024-11-21 14:01:11.991021: train_loss -0.755 +2024-11-21 14:01:12.003150: val_loss -0.75 +2024-11-21 14:01:12.003284: Pseudo dice [0.8571] +2024-11-21 14:01:12.003372: Epoch time: 18.9 s +2024-11-21 14:01:12.838790: +2024-11-21 14:01:12.838981: Epoch 599 +2024-11-21 14:01:12.839110: Current learning rate: 0.00932 +2024-11-21 14:01:31.245181: train_loss -0.7638 +2024-11-21 14:01:31.269175: val_loss -0.7511 +2024-11-21 14:01:31.269326: Pseudo dice [0.8441] +2024-11-21 14:01:31.269437: Epoch time: 18.41 s +2024-11-21 14:01:32.443637: +2024-11-21 14:01:32.443836: Epoch 600 +2024-11-21 14:01:32.443955: Current learning rate: 0.00932 +2024-11-21 14:01:50.971898: train_loss -0.7632 +2024-11-21 14:01:50.974926: val_loss -0.7624 +2024-11-21 14:01:50.975043: Pseudo dice [0.8426] +2024-11-21 14:01:50.975150: Epoch time: 18.53 s +2024-11-21 14:01:51.785506: +2024-11-21 14:01:51.785699: Epoch 601 +2024-11-21 14:01:51.785820: Current learning rate: 0.00932 +2024-11-21 14:02:11.437214: train_loss -0.7496 +2024-11-21 14:02:11.444541: val_loss -0.7543 +2024-11-21 14:02:11.444687: Pseudo dice [0.8471] +2024-11-21 14:02:11.444861: Epoch time: 19.65 s +2024-11-21 14:02:12.357427: +2024-11-21 14:02:12.357654: Epoch 602 +2024-11-21 14:02:12.357789: Current learning rate: 0.00932 +2024-11-21 14:02:31.287506: train_loss -0.7562 +2024-11-21 14:02:31.290846: val_loss -0.7718 +2024-11-21 14:02:31.290947: Pseudo dice [0.8462] +2024-11-21 14:02:31.291063: Epoch time: 18.93 s +2024-11-21 14:02:32.523034: +2024-11-21 14:02:32.523245: Epoch 603 +2024-11-21 14:02:32.523378: Current learning rate: 0.00932 +2024-11-21 14:02:51.215657: train_loss -0.75 +2024-11-21 14:02:51.221875: val_loss -0.7577 +2024-11-21 14:02:51.222029: Pseudo dice [0.8478] +2024-11-21 14:02:51.222123: Epoch time: 18.69 s +2024-11-21 14:02:52.046142: +2024-11-21 14:02:52.046370: Epoch 604 +2024-11-21 14:02:52.046488: Current learning rate: 0.00932 +2024-11-21 14:03:11.431802: train_loss -0.7686 +2024-11-21 14:03:11.437665: val_loss -0.757 +2024-11-21 14:03:11.437801: Pseudo dice [0.8498] +2024-11-21 14:03:11.437943: Epoch time: 19.39 s +2024-11-21 14:03:12.261188: +2024-11-21 14:03:12.261381: Epoch 605 +2024-11-21 14:03:12.261505: Current learning rate: 0.00932 +2024-11-21 14:03:30.915823: train_loss -0.7672 +2024-11-21 14:03:30.922946: val_loss -0.7537 +2024-11-21 14:03:30.923086: Pseudo dice [0.8433] +2024-11-21 14:03:30.923172: Epoch time: 18.66 s +2024-11-21 14:03:31.733350: +2024-11-21 14:03:31.733532: Epoch 606 +2024-11-21 14:03:31.733872: Current learning rate: 0.00932 +2024-11-21 14:03:50.865512: train_loss -0.752 +2024-11-21 14:03:50.869461: val_loss -0.7523 +2024-11-21 14:03:50.869577: Pseudo dice [0.8311] +2024-11-21 14:03:50.869662: Epoch time: 19.13 s +2024-11-21 14:03:51.680826: +2024-11-21 14:03:51.681821: Epoch 607 +2024-11-21 14:03:51.681942: Current learning rate: 0.00931 +2024-11-21 14:04:10.954982: train_loss -0.7498 +2024-11-21 14:04:10.960882: val_loss -0.7784 +2024-11-21 14:04:10.961005: Pseudo dice [0.8513] +2024-11-21 14:04:10.961104: Epoch time: 19.27 s +2024-11-21 14:04:11.993545: +2024-11-21 14:04:11.993737: Epoch 608 +2024-11-21 14:04:11.993858: Current learning rate: 0.00931 +2024-11-21 14:04:30.935966: train_loss -0.7671 +2024-11-21 14:04:30.942727: val_loss -0.7676 +2024-11-21 14:04:30.942879: Pseudo dice [0.8496] +2024-11-21 14:04:30.942988: Epoch time: 18.94 s +2024-11-21 14:04:31.974368: +2024-11-21 14:04:31.974573: Epoch 609 +2024-11-21 14:04:31.974686: Current learning rate: 0.00931 +2024-11-21 14:04:51.029651: train_loss -0.7573 +2024-11-21 14:04:51.036163: val_loss -0.7661 +2024-11-21 14:04:51.036317: Pseudo dice [0.8403] +2024-11-21 14:04:51.036402: Epoch time: 19.06 s +2024-11-21 14:04:51.866564: +2024-11-21 14:04:51.866895: Epoch 610 +2024-11-21 14:04:51.867018: Current learning rate: 0.00931 +2024-11-21 14:05:11.127181: train_loss -0.7624 +2024-11-21 14:05:11.134650: val_loss -0.76 +2024-11-21 14:05:11.134784: Pseudo dice [0.8488] +2024-11-21 14:05:11.134874: Epoch time: 19.26 s +2024-11-21 14:05:12.066326: +2024-11-21 14:05:12.066564: Epoch 611 +2024-11-21 14:05:12.066682: Current learning rate: 0.00931 +2024-11-21 14:05:31.113142: train_loss -0.7574 +2024-11-21 14:05:31.119915: val_loss -0.7687 +2024-11-21 14:05:31.120043: Pseudo dice [0.8491] +2024-11-21 14:05:31.120142: Epoch time: 19.05 s +2024-11-21 14:05:32.167462: +2024-11-21 14:05:32.167649: Epoch 612 +2024-11-21 14:05:32.167769: Current learning rate: 0.00931 +2024-11-21 14:05:50.603542: train_loss -0.7496 +2024-11-21 14:05:50.611966: val_loss -0.7101 +2024-11-21 14:05:50.612093: Pseudo dice [0.8246] +2024-11-21 14:05:50.612187: Epoch time: 18.44 s +2024-11-21 14:05:51.559655: +2024-11-21 14:05:51.559841: Epoch 613 +2024-11-21 14:05:51.559964: Current learning rate: 0.00931 +2024-11-21 14:06:10.840042: train_loss -0.7594 +2024-11-21 14:06:10.846030: val_loss -0.7576 +2024-11-21 14:06:10.846214: Pseudo dice [0.8438] +2024-11-21 14:06:10.846320: Epoch time: 19.28 s +2024-11-21 14:06:12.125418: +2024-11-21 14:06:12.125621: Epoch 614 +2024-11-21 14:06:12.125743: Current learning rate: 0.00931 +2024-11-21 14:06:31.069222: train_loss -0.7569 +2024-11-21 14:06:31.090670: val_loss -0.7801 +2024-11-21 14:06:31.090814: Pseudo dice [0.8542] +2024-11-21 14:06:31.090963: Epoch time: 18.94 s +2024-11-21 14:06:31.941886: +2024-11-21 14:06:31.942139: Epoch 615 +2024-11-21 14:06:31.942254: Current learning rate: 0.00931 +2024-11-21 14:06:52.146260: train_loss -0.7707 +2024-11-21 14:06:52.151460: val_loss -0.745 +2024-11-21 14:06:52.151721: Pseudo dice [0.8381] +2024-11-21 14:06:52.151835: Epoch time: 20.21 s +2024-11-21 14:06:52.964743: +2024-11-21 14:06:52.964946: Epoch 616 +2024-11-21 14:06:52.965065: Current learning rate: 0.0093 +2024-11-21 14:07:11.098875: train_loss -0.757 +2024-11-21 14:07:11.104502: val_loss -0.7629 +2024-11-21 14:07:11.104659: Pseudo dice [0.8464] +2024-11-21 14:07:11.104779: Epoch time: 18.13 s +2024-11-21 14:07:12.024150: +2024-11-21 14:07:12.024368: Epoch 617 +2024-11-21 14:07:12.024485: Current learning rate: 0.0093 +2024-11-21 14:07:30.355911: train_loss -0.7383 +2024-11-21 14:07:30.368958: val_loss -0.7622 +2024-11-21 14:07:30.369127: Pseudo dice [0.8591] +2024-11-21 14:07:30.369233: Epoch time: 18.33 s +2024-11-21 14:07:31.369700: +2024-11-21 14:07:31.369892: Epoch 618 +2024-11-21 14:07:31.370026: Current learning rate: 0.0093 +2024-11-21 14:07:50.427788: train_loss -0.7479 +2024-11-21 14:07:50.436201: val_loss -0.753 +2024-11-21 14:07:50.436384: Pseudo dice [0.8439] +2024-11-21 14:07:50.436508: Epoch time: 19.06 s +2024-11-21 14:07:51.344699: +2024-11-21 14:07:51.344917: Epoch 619 +2024-11-21 14:07:51.345026: Current learning rate: 0.0093 +2024-11-21 14:08:10.325705: train_loss -0.755 +2024-11-21 14:08:10.332378: val_loss -0.7752 +2024-11-21 14:08:10.332513: Pseudo dice [0.8487] +2024-11-21 14:08:10.332622: Epoch time: 18.98 s +2024-11-21 14:08:11.186792: +2024-11-21 14:08:11.187012: Epoch 620 +2024-11-21 14:08:11.187143: Current learning rate: 0.0093 +2024-11-21 14:08:29.981132: train_loss -0.7615 +2024-11-21 14:08:29.995339: val_loss -0.7386 +2024-11-21 14:08:29.995494: Pseudo dice [0.8268] +2024-11-21 14:08:29.995589: Epoch time: 18.8 s +2024-11-21 14:08:30.929953: +2024-11-21 14:08:30.930179: Epoch 621 +2024-11-21 14:08:30.930304: Current learning rate: 0.0093 +2024-11-21 14:08:51.140435: train_loss -0.7593 +2024-11-21 14:08:51.144396: val_loss -0.7422 +2024-11-21 14:08:51.144519: Pseudo dice [0.8416] +2024-11-21 14:08:51.144633: Epoch time: 20.21 s +2024-11-21 14:08:52.096145: +2024-11-21 14:08:52.096339: Epoch 622 +2024-11-21 14:08:52.096455: Current learning rate: 0.0093 +2024-11-21 14:09:11.727536: train_loss -0.757 +2024-11-21 14:09:11.732120: val_loss -0.7901 +2024-11-21 14:09:11.732253: Pseudo dice [0.8412] +2024-11-21 14:09:11.732360: Epoch time: 19.63 s +2024-11-21 14:09:12.579330: +2024-11-21 14:09:12.579545: Epoch 623 +2024-11-21 14:09:12.579665: Current learning rate: 0.0093 +2024-11-21 14:09:31.961546: train_loss -0.7666 +2024-11-21 14:09:31.967655: val_loss -0.7649 +2024-11-21 14:09:31.967783: Pseudo dice [0.8439] +2024-11-21 14:09:31.967948: Epoch time: 19.38 s +2024-11-21 14:09:32.971739: +2024-11-21 14:09:32.971956: Epoch 624 +2024-11-21 14:09:32.972100: Current learning rate: 0.0093 +2024-11-21 14:09:52.171935: train_loss -0.7668 +2024-11-21 14:09:52.185529: val_loss -0.7526 +2024-11-21 14:09:52.185666: Pseudo dice [0.8486] +2024-11-21 14:09:52.185757: Epoch time: 19.2 s +2024-11-21 14:09:53.455947: +2024-11-21 14:09:53.456421: Epoch 625 +2024-11-21 14:09:53.456546: Current learning rate: 0.00929 +2024-11-21 14:10:13.311052: train_loss -0.7479 +2024-11-21 14:10:13.314192: val_loss -0.7544 +2024-11-21 14:10:13.314297: Pseudo dice [0.8336] +2024-11-21 14:10:13.314399: Epoch time: 19.86 s +2024-11-21 14:10:14.138052: +2024-11-21 14:10:14.138257: Epoch 626 +2024-11-21 14:10:14.138373: Current learning rate: 0.00929 +2024-11-21 14:10:33.807661: train_loss -0.7498 +2024-11-21 14:10:33.832942: val_loss -0.7357 +2024-11-21 14:10:33.833094: Pseudo dice [0.8375] +2024-11-21 14:10:33.833225: Epoch time: 19.67 s +2024-11-21 14:10:34.747547: +2024-11-21 14:10:34.747753: Epoch 627 +2024-11-21 14:10:34.747877: Current learning rate: 0.00929 +2024-11-21 14:10:55.053511: train_loss -0.7674 +2024-11-21 14:10:55.061098: val_loss -0.7523 +2024-11-21 14:10:55.061211: Pseudo dice [0.8297] +2024-11-21 14:10:55.061293: Epoch time: 20.31 s +2024-11-21 14:10:56.031374: +2024-11-21 14:10:56.031585: Epoch 628 +2024-11-21 14:10:56.031706: Current learning rate: 0.00929 +2024-11-21 14:11:14.508388: train_loss -0.7737 +2024-11-21 14:11:14.513148: val_loss -0.7425 +2024-11-21 14:11:14.513366: Pseudo dice [0.8376] +2024-11-21 14:11:14.513481: Epoch time: 18.48 s +2024-11-21 14:11:15.368335: +2024-11-21 14:11:15.368538: Epoch 629 +2024-11-21 14:11:15.368657: Current learning rate: 0.00929 +2024-11-21 14:11:35.067482: train_loss -0.7586 +2024-11-21 14:11:35.097786: val_loss -0.7603 +2024-11-21 14:11:35.097937: Pseudo dice [0.8564] +2024-11-21 14:11:35.098032: Epoch time: 19.7 s +2024-11-21 14:11:35.998615: +2024-11-21 14:11:35.998821: Epoch 630 +2024-11-21 14:11:35.998948: Current learning rate: 0.00929 +2024-11-21 14:11:55.069220: train_loss -0.7709 +2024-11-21 14:11:55.070873: val_loss -0.735 +2024-11-21 14:11:55.070999: Pseudo dice [0.8454] +2024-11-21 14:11:55.071099: Epoch time: 19.07 s +2024-11-21 14:11:55.917270: +2024-11-21 14:11:55.917477: Epoch 631 +2024-11-21 14:11:55.917592: Current learning rate: 0.00929 +2024-11-21 14:12:15.309285: train_loss -0.7639 +2024-11-21 14:12:15.317644: val_loss -0.7536 +2024-11-21 14:12:15.317984: Pseudo dice [0.844] +2024-11-21 14:12:15.318086: Epoch time: 19.39 s +2024-11-21 14:12:16.149923: +2024-11-21 14:12:16.150155: Epoch 632 +2024-11-21 14:12:16.150293: Current learning rate: 0.00929 +2024-11-21 14:12:35.382608: train_loss -0.7469 +2024-11-21 14:12:35.385509: val_loss -0.7502 +2024-11-21 14:12:35.385609: Pseudo dice [0.8454] +2024-11-21 14:12:35.385715: Epoch time: 19.23 s +2024-11-21 14:12:36.198690: +2024-11-21 14:12:36.198907: Epoch 633 +2024-11-21 14:12:36.199019: Current learning rate: 0.00928 +2024-11-21 14:12:54.007435: train_loss -0.7478 +2024-11-21 14:12:54.014832: val_loss -0.7534 +2024-11-21 14:12:54.014982: Pseudo dice [0.8468] +2024-11-21 14:12:54.015112: Epoch time: 17.81 s +2024-11-21 14:12:54.833131: +2024-11-21 14:12:54.833323: Epoch 634 +2024-11-21 14:12:54.833447: Current learning rate: 0.00928 +2024-11-21 14:13:13.636100: train_loss -0.7571 +2024-11-21 14:13:13.641672: val_loss -0.7567 +2024-11-21 14:13:13.641803: Pseudo dice [0.8427] +2024-11-21 14:13:13.641910: Epoch time: 18.8 s +2024-11-21 14:13:14.615788: +2024-11-21 14:13:14.616069: Epoch 635 +2024-11-21 14:13:14.616180: Current learning rate: 0.00928 +2024-11-21 14:13:33.575386: train_loss -0.7556 +2024-11-21 14:13:33.577956: val_loss -0.7447 +2024-11-21 14:13:33.578058: Pseudo dice [0.8354] +2024-11-21 14:13:33.578151: Epoch time: 18.96 s +2024-11-21 14:13:34.783953: +2024-11-21 14:13:34.784198: Epoch 636 +2024-11-21 14:13:34.784319: Current learning rate: 0.00928 +2024-11-21 14:13:53.715578: train_loss -0.7491 +2024-11-21 14:13:53.721930: val_loss -0.7529 +2024-11-21 14:13:53.722087: Pseudo dice [0.8445] +2024-11-21 14:13:53.722189: Epoch time: 18.93 s +2024-11-21 14:13:54.589809: +2024-11-21 14:13:54.590024: Epoch 637 +2024-11-21 14:13:54.590153: Current learning rate: 0.00928 +2024-11-21 14:14:13.983096: train_loss -0.7458 +2024-11-21 14:14:14.002110: val_loss -0.7554 +2024-11-21 14:14:14.002262: Pseudo dice [0.8522] +2024-11-21 14:14:14.002369: Epoch time: 19.39 s +2024-11-21 14:14:14.855207: +2024-11-21 14:14:14.855402: Epoch 638 +2024-11-21 14:14:14.855514: Current learning rate: 0.00928 +2024-11-21 14:14:33.970013: train_loss -0.7554 +2024-11-21 14:14:33.978921: val_loss -0.756 +2024-11-21 14:14:33.979077: Pseudo dice [0.8325] +2024-11-21 14:14:33.979179: Epoch time: 19.12 s +2024-11-21 14:14:34.883419: +2024-11-21 14:14:34.883601: Epoch 639 +2024-11-21 14:14:34.883712: Current learning rate: 0.00928 +2024-11-21 14:14:53.516188: train_loss -0.7619 +2024-11-21 14:14:53.519122: val_loss -0.7351 +2024-11-21 14:14:53.519232: Pseudo dice [0.8394] +2024-11-21 14:14:53.519316: Epoch time: 18.63 s +2024-11-21 14:14:54.333610: +2024-11-21 14:14:54.333807: Epoch 640 +2024-11-21 14:14:54.333919: Current learning rate: 0.00928 +2024-11-21 14:15:12.586511: train_loss -0.7448 +2024-11-21 14:15:12.597995: val_loss -0.7746 +2024-11-21 14:15:12.598159: Pseudo dice [0.851] +2024-11-21 14:15:12.598270: Epoch time: 18.25 s +2024-11-21 14:15:13.689559: +2024-11-21 14:15:13.689749: Epoch 641 +2024-11-21 14:15:13.689865: Current learning rate: 0.00928 +2024-11-21 14:15:34.411416: train_loss -0.7442 +2024-11-21 14:15:34.426904: val_loss -0.7279 +2024-11-21 14:15:34.427023: Pseudo dice [0.8333] +2024-11-21 14:15:34.427129: Epoch time: 20.72 s +2024-11-21 14:15:35.343219: +2024-11-21 14:15:35.343416: Epoch 642 +2024-11-21 14:15:35.343544: Current learning rate: 0.00927 +2024-11-21 14:15:54.466566: train_loss -0.753 +2024-11-21 14:15:54.475633: val_loss -0.7753 +2024-11-21 14:15:54.475772: Pseudo dice [0.8517] +2024-11-21 14:15:54.475869: Epoch time: 19.12 s +2024-11-21 14:15:55.365458: +2024-11-21 14:15:55.365682: Epoch 643 +2024-11-21 14:15:55.365820: Current learning rate: 0.00927 +2024-11-21 14:16:14.237515: train_loss -0.7565 +2024-11-21 14:16:14.245566: val_loss -0.7676 +2024-11-21 14:16:14.245701: Pseudo dice [0.8534] +2024-11-21 14:16:14.245795: Epoch time: 18.87 s +2024-11-21 14:16:15.091645: +2024-11-21 14:16:15.091907: Epoch 644 +2024-11-21 14:16:15.092086: Current learning rate: 0.00927 +2024-11-21 14:16:34.226699: train_loss -0.7623 +2024-11-21 14:16:34.231440: val_loss -0.7327 +2024-11-21 14:16:34.231579: Pseudo dice [0.8401] +2024-11-21 14:16:34.231688: Epoch time: 19.14 s +2024-11-21 14:16:35.054323: +2024-11-21 14:16:35.054528: Epoch 645 +2024-11-21 14:16:35.054647: Current learning rate: 0.00927 +2024-11-21 14:16:53.837613: train_loss -0.7554 +2024-11-21 14:16:53.843755: val_loss -0.76 +2024-11-21 14:16:53.843887: Pseudo dice [0.8355] +2024-11-21 14:16:53.843983: Epoch time: 18.78 s +2024-11-21 14:16:54.664975: +2024-11-21 14:16:54.665191: Epoch 646 +2024-11-21 14:16:54.665335: Current learning rate: 0.00927 +2024-11-21 14:17:14.587051: train_loss -0.7533 +2024-11-21 14:17:14.593155: val_loss -0.7584 +2024-11-21 14:17:14.593275: Pseudo dice [0.8462] +2024-11-21 14:17:14.593371: Epoch time: 19.92 s +2024-11-21 14:17:16.199278: +2024-11-21 14:17:16.199491: Epoch 647 +2024-11-21 14:17:16.199633: Current learning rate: 0.00927 +2024-11-21 14:17:35.391072: train_loss -0.7498 +2024-11-21 14:17:35.398843: val_loss -0.7508 +2024-11-21 14:17:35.398977: Pseudo dice [0.8465] +2024-11-21 14:17:35.399086: Epoch time: 19.19 s +2024-11-21 14:17:36.215072: +2024-11-21 14:17:36.215273: Epoch 648 +2024-11-21 14:17:36.215388: Current learning rate: 0.00927 +2024-11-21 14:17:54.336970: train_loss -0.7534 +2024-11-21 14:17:54.346559: val_loss -0.7815 +2024-11-21 14:17:54.346693: Pseudo dice [0.8443] +2024-11-21 14:17:54.346779: Epoch time: 18.12 s +2024-11-21 14:17:55.281797: +2024-11-21 14:17:55.281985: Epoch 649 +2024-11-21 14:17:55.282125: Current learning rate: 0.00927 +2024-11-21 14:18:13.488171: train_loss -0.7622 +2024-11-21 14:18:13.491544: val_loss -0.7685 +2024-11-21 14:18:13.491649: Pseudo dice [0.8527] +2024-11-21 14:18:13.491744: Epoch time: 18.21 s +2024-11-21 14:18:14.508123: +2024-11-21 14:18:14.508327: Epoch 650 +2024-11-21 14:18:14.508458: Current learning rate: 0.00927 +2024-11-21 14:18:33.490330: train_loss -0.7659 +2024-11-21 14:18:33.493107: val_loss -0.744 +2024-11-21 14:18:33.493275: Pseudo dice [0.8491] +2024-11-21 14:18:33.493383: Epoch time: 18.98 s +2024-11-21 14:18:34.309261: +2024-11-21 14:18:34.309445: Epoch 651 +2024-11-21 14:18:34.309576: Current learning rate: 0.00926 +2024-11-21 14:18:54.504933: train_loss -0.7588 +2024-11-21 14:18:54.512057: val_loss -0.7784 +2024-11-21 14:18:54.512189: Pseudo dice [0.8449] +2024-11-21 14:18:54.512278: Epoch time: 20.2 s +2024-11-21 14:18:55.340808: +2024-11-21 14:18:55.341018: Epoch 652 +2024-11-21 14:18:55.341154: Current learning rate: 0.00926 +2024-11-21 14:19:13.773314: train_loss -0.7495 +2024-11-21 14:19:13.785595: val_loss -0.7729 +2024-11-21 14:19:13.785726: Pseudo dice [0.8471] +2024-11-21 14:19:13.785811: Epoch time: 18.43 s +2024-11-21 14:19:14.680473: +2024-11-21 14:19:14.680681: Epoch 653 +2024-11-21 14:19:14.680792: Current learning rate: 0.00926 +2024-11-21 14:19:34.177020: train_loss -0.7605 +2024-11-21 14:19:34.180605: val_loss -0.75 +2024-11-21 14:19:34.180720: Pseudo dice [0.8356] +2024-11-21 14:19:34.180819: Epoch time: 19.5 s +2024-11-21 14:19:34.998365: +2024-11-21 14:19:34.998585: Epoch 654 +2024-11-21 14:19:34.998735: Current learning rate: 0.00926 +2024-11-21 14:19:53.832449: train_loss -0.7597 +2024-11-21 14:19:53.843172: val_loss -0.7727 +2024-11-21 14:19:53.843319: Pseudo dice [0.8343] +2024-11-21 14:19:53.843413: Epoch time: 18.84 s +2024-11-21 14:19:54.822377: +2024-11-21 14:19:54.822562: Epoch 655 +2024-11-21 14:19:54.822695: Current learning rate: 0.00926 +2024-11-21 14:20:13.619661: train_loss -0.7651 +2024-11-21 14:20:13.624780: val_loss -0.7573 +2024-11-21 14:20:13.624924: Pseudo dice [0.8525] +2024-11-21 14:20:13.625029: Epoch time: 18.8 s +2024-11-21 14:20:14.432763: +2024-11-21 14:20:14.432986: Epoch 656 +2024-11-21 14:20:14.433109: Current learning rate: 0.00926 +2024-11-21 14:20:34.028980: train_loss -0.7573 +2024-11-21 14:20:34.040324: val_loss -0.761 +2024-11-21 14:20:34.040460: Pseudo dice [0.8515] +2024-11-21 14:20:34.040559: Epoch time: 19.6 s +2024-11-21 14:20:34.857164: +2024-11-21 14:20:34.857362: Epoch 657 +2024-11-21 14:20:34.857749: Current learning rate: 0.00926 +2024-11-21 14:20:53.518569: train_loss -0.7598 +2024-11-21 14:20:53.525452: val_loss -0.7554 +2024-11-21 14:20:53.525589: Pseudo dice [0.8282] +2024-11-21 14:20:53.525685: Epoch time: 18.66 s +2024-11-21 14:20:54.810263: +2024-11-21 14:20:54.810536: Epoch 658 +2024-11-21 14:20:54.810668: Current learning rate: 0.00926 +2024-11-21 14:21:13.397689: train_loss -0.7503 +2024-11-21 14:21:13.424013: val_loss -0.766 +2024-11-21 14:21:13.424175: Pseudo dice [0.84] +2024-11-21 14:21:13.424278: Epoch time: 18.59 s +2024-11-21 14:21:14.298067: +2024-11-21 14:21:14.298276: Epoch 659 +2024-11-21 14:21:14.298398: Current learning rate: 0.00926 +2024-11-21 14:21:32.468632: train_loss -0.765 +2024-11-21 14:21:32.474053: val_loss -0.7638 +2024-11-21 14:21:32.474254: Pseudo dice [0.8422] +2024-11-21 14:21:32.474349: Epoch time: 18.17 s +2024-11-21 14:21:33.402318: +2024-11-21 14:21:33.402523: Epoch 660 +2024-11-21 14:21:33.402637: Current learning rate: 0.00925 +2024-11-21 14:21:53.734421: train_loss -0.7482 +2024-11-21 14:21:53.736973: val_loss -0.7524 +2024-11-21 14:21:53.737072: Pseudo dice [0.8462] +2024-11-21 14:21:53.737168: Epoch time: 20.33 s +2024-11-21 14:21:54.546506: +2024-11-21 14:21:54.546703: Epoch 661 +2024-11-21 14:21:54.546853: Current learning rate: 0.00925 +2024-11-21 14:22:12.899136: train_loss -0.7627 +2024-11-21 14:22:12.922715: val_loss -0.7675 +2024-11-21 14:22:12.922867: Pseudo dice [0.8456] +2024-11-21 14:22:12.922975: Epoch time: 18.35 s +2024-11-21 14:22:14.024215: +2024-11-21 14:22:14.024412: Epoch 662 +2024-11-21 14:22:14.024537: Current learning rate: 0.00925 +2024-11-21 14:22:33.196946: train_loss -0.7622 +2024-11-21 14:22:33.200809: val_loss -0.7444 +2024-11-21 14:22:33.200955: Pseudo dice [0.8507] +2024-11-21 14:22:33.201039: Epoch time: 19.17 s +2024-11-21 14:22:34.009333: +2024-11-21 14:22:34.009533: Epoch 663 +2024-11-21 14:22:34.009665: Current learning rate: 0.00925 +2024-11-21 14:22:53.140277: train_loss -0.7577 +2024-11-21 14:22:53.146572: val_loss -0.7625 +2024-11-21 14:22:53.146704: Pseudo dice [0.8447] +2024-11-21 14:22:53.146791: Epoch time: 19.13 s +2024-11-21 14:22:54.015101: +2024-11-21 14:22:54.015317: Epoch 664 +2024-11-21 14:22:54.015437: Current learning rate: 0.00925 +2024-11-21 14:23:12.415156: train_loss -0.7603 +2024-11-21 14:23:12.422341: val_loss -0.7755 +2024-11-21 14:23:12.422463: Pseudo dice [0.8426] +2024-11-21 14:23:12.422551: Epoch time: 18.4 s +2024-11-21 14:23:13.384703: +2024-11-21 14:23:13.384955: Epoch 665 +2024-11-21 14:23:13.385101: Current learning rate: 0.00925 +2024-11-21 14:23:33.565698: train_loss -0.7441 +2024-11-21 14:23:33.571992: val_loss -0.7383 +2024-11-21 14:23:33.572119: Pseudo dice [0.8371] +2024-11-21 14:23:33.572228: Epoch time: 20.18 s +2024-11-21 14:23:34.472321: +2024-11-21 14:23:34.472497: Epoch 666 +2024-11-21 14:23:34.472616: Current learning rate: 0.00925 +2024-11-21 14:23:52.176841: train_loss -0.7496 +2024-11-21 14:23:52.182788: val_loss -0.7307 +2024-11-21 14:23:52.182932: Pseudo dice [0.8285] +2024-11-21 14:23:52.183030: Epoch time: 17.71 s +2024-11-21 14:23:53.267436: +2024-11-21 14:23:53.267616: Epoch 667 +2024-11-21 14:23:53.267749: Current learning rate: 0.00925 +2024-11-21 14:24:12.986758: train_loss -0.7548 +2024-11-21 14:24:12.995632: val_loss -0.7577 +2024-11-21 14:24:12.995841: Pseudo dice [0.8441] +2024-11-21 14:24:12.995934: Epoch time: 19.72 s +2024-11-21 14:24:13.889560: +2024-11-21 14:24:13.889740: Epoch 668 +2024-11-21 14:24:13.889858: Current learning rate: 0.00925 +2024-11-21 14:24:32.236756: train_loss -0.7705 +2024-11-21 14:24:32.244173: val_loss -0.7381 +2024-11-21 14:24:32.244299: Pseudo dice [0.8526] +2024-11-21 14:24:32.244411: Epoch time: 18.35 s +2024-11-21 14:24:33.591482: +2024-11-21 14:24:33.591688: Epoch 669 +2024-11-21 14:24:33.591808: Current learning rate: 0.00924 +2024-11-21 14:24:52.286647: train_loss -0.7662 +2024-11-21 14:24:52.295009: val_loss -0.7436 +2024-11-21 14:24:52.295175: Pseudo dice [0.8504] +2024-11-21 14:24:52.295268: Epoch time: 18.7 s +2024-11-21 14:24:53.163945: +2024-11-21 14:24:53.164155: Epoch 670 +2024-11-21 14:24:53.164286: Current learning rate: 0.00924 +2024-11-21 14:25:12.505837: train_loss -0.7549 +2024-11-21 14:25:12.522214: val_loss -0.766 +2024-11-21 14:25:12.522368: Pseudo dice [0.8489] +2024-11-21 14:25:12.522461: Epoch time: 19.34 s +2024-11-21 14:25:13.400282: +2024-11-21 14:25:13.400505: Epoch 671 +2024-11-21 14:25:13.400630: Current learning rate: 0.00924 +2024-11-21 14:25:31.628733: train_loss -0.7482 +2024-11-21 14:25:31.638370: val_loss -0.7566 +2024-11-21 14:25:31.638515: Pseudo dice [0.8456] +2024-11-21 14:25:31.638601: Epoch time: 18.23 s +2024-11-21 14:25:32.472983: +2024-11-21 14:25:32.473204: Epoch 672 +2024-11-21 14:25:32.473324: Current learning rate: 0.00924 +2024-11-21 14:25:51.733716: train_loss -0.7474 +2024-11-21 14:25:51.743417: val_loss -0.745 +2024-11-21 14:25:51.743561: Pseudo dice [0.8482] +2024-11-21 14:25:51.743656: Epoch time: 19.26 s +2024-11-21 14:25:52.605270: +2024-11-21 14:25:52.605496: Epoch 673 +2024-11-21 14:25:52.605614: Current learning rate: 0.00924 +2024-11-21 14:26:11.740662: train_loss -0.7486 +2024-11-21 14:26:11.745384: val_loss -0.7545 +2024-11-21 14:26:11.745490: Pseudo dice [0.8455] +2024-11-21 14:26:11.745581: Epoch time: 19.14 s +2024-11-21 14:26:12.566440: +2024-11-21 14:26:12.566710: Epoch 674 +2024-11-21 14:26:12.566841: Current learning rate: 0.00924 +2024-11-21 14:26:31.449639: train_loss -0.7483 +2024-11-21 14:26:31.476213: val_loss -0.7694 +2024-11-21 14:26:31.476379: Pseudo dice [0.851] +2024-11-21 14:26:31.476474: Epoch time: 18.88 s +2024-11-21 14:26:32.383739: +2024-11-21 14:26:32.383929: Epoch 675 +2024-11-21 14:26:32.384073: Current learning rate: 0.00924 +2024-11-21 14:26:51.507251: train_loss -0.7566 +2024-11-21 14:26:51.521511: val_loss -0.7463 +2024-11-21 14:26:51.521709: Pseudo dice [0.8427] +2024-11-21 14:26:51.521806: Epoch time: 19.12 s +2024-11-21 14:26:52.345827: +2024-11-21 14:26:52.346082: Epoch 676 +2024-11-21 14:26:52.346202: Current learning rate: 0.00924 +2024-11-21 14:27:10.616493: train_loss -0.7489 +2024-11-21 14:27:10.627432: val_loss -0.7458 +2024-11-21 14:27:10.627571: Pseudo dice [0.844] +2024-11-21 14:27:10.627669: Epoch time: 18.27 s +2024-11-21 14:27:11.595993: +2024-11-21 14:27:11.596202: Epoch 677 +2024-11-21 14:27:11.596335: Current learning rate: 0.00924 +2024-11-21 14:27:30.751542: train_loss -0.7519 +2024-11-21 14:27:30.758637: val_loss -0.7415 +2024-11-21 14:27:30.758764: Pseudo dice [0.8484] +2024-11-21 14:27:30.758850: Epoch time: 19.16 s +2024-11-21 14:27:31.677882: +2024-11-21 14:27:31.678056: Epoch 678 +2024-11-21 14:27:31.678176: Current learning rate: 0.00923 +2024-11-21 14:27:50.231685: train_loss -0.7539 +2024-11-21 14:27:50.248877: val_loss -0.7375 +2024-11-21 14:27:50.249091: Pseudo dice [0.84] +2024-11-21 14:27:50.249199: Epoch time: 18.55 s +2024-11-21 14:27:51.398931: +2024-11-21 14:27:51.399131: Epoch 679 +2024-11-21 14:27:51.399250: Current learning rate: 0.00923 +2024-11-21 14:28:10.628475: train_loss -0.7496 +2024-11-21 14:28:10.640439: val_loss -0.7419 +2024-11-21 14:28:10.640584: Pseudo dice [0.8272] +2024-11-21 14:28:10.640701: Epoch time: 19.23 s +2024-11-21 14:28:11.915361: +2024-11-21 14:28:11.915564: Epoch 680 +2024-11-21 14:28:11.915701: Current learning rate: 0.00923 +2024-11-21 14:28:32.215133: train_loss -0.7574 +2024-11-21 14:28:32.221086: val_loss -0.7718 +2024-11-21 14:28:32.221222: Pseudo dice [0.849] +2024-11-21 14:28:32.221320: Epoch time: 20.3 s +2024-11-21 14:28:33.061375: +2024-11-21 14:28:33.061586: Epoch 681 +2024-11-21 14:28:33.061701: Current learning rate: 0.00923 +2024-11-21 14:28:53.192981: train_loss -0.7588 +2024-11-21 14:28:53.204919: val_loss -0.7614 +2024-11-21 14:28:53.205095: Pseudo dice [0.8414] +2024-11-21 14:28:53.205188: Epoch time: 20.13 s +2024-11-21 14:28:54.237961: +2024-11-21 14:28:54.238179: Epoch 682 +2024-11-21 14:28:54.238318: Current learning rate: 0.00923 +2024-11-21 14:29:14.261312: train_loss -0.763 +2024-11-21 14:29:14.264465: val_loss -0.7733 +2024-11-21 14:29:14.282017: Pseudo dice [0.8367] +2024-11-21 14:29:14.282201: Epoch time: 20.02 s +2024-11-21 14:29:15.106153: +2024-11-21 14:29:15.106366: Epoch 683 +2024-11-21 14:29:15.106489: Current learning rate: 0.00923 +2024-11-21 14:29:33.864305: train_loss -0.7595 +2024-11-21 14:29:33.866078: val_loss -0.7636 +2024-11-21 14:29:33.866189: Pseudo dice [0.853] +2024-11-21 14:29:33.866276: Epoch time: 18.76 s +2024-11-21 14:29:34.675617: +2024-11-21 14:29:34.675820: Epoch 684 +2024-11-21 14:29:34.675952: Current learning rate: 0.00923 +2024-11-21 14:29:53.495307: train_loss -0.7627 +2024-11-21 14:29:53.500858: val_loss -0.7882 +2024-11-21 14:29:53.500991: Pseudo dice [0.8435] +2024-11-21 14:29:53.501077: Epoch time: 18.82 s +2024-11-21 14:29:54.379300: +2024-11-21 14:29:54.379485: Epoch 685 +2024-11-21 14:29:54.379618: Current learning rate: 0.00923 +2024-11-21 14:30:13.774151: train_loss -0.749 +2024-11-21 14:30:13.787745: val_loss -0.7653 +2024-11-21 14:30:13.787874: Pseudo dice [0.8493] +2024-11-21 14:30:13.787965: Epoch time: 19.4 s +2024-11-21 14:30:14.708802: +2024-11-21 14:30:14.709005: Epoch 686 +2024-11-21 14:30:14.709142: Current learning rate: 0.00922 +2024-11-21 14:30:33.119638: train_loss -0.753 +2024-11-21 14:30:33.125736: val_loss -0.7675 +2024-11-21 14:30:33.125880: Pseudo dice [0.8417] +2024-11-21 14:30:33.125983: Epoch time: 18.41 s +2024-11-21 14:30:33.965475: +2024-11-21 14:30:33.965665: Epoch 687 +2024-11-21 14:30:33.965806: Current learning rate: 0.00922 +2024-11-21 14:30:53.407147: train_loss -0.7615 +2024-11-21 14:30:53.416701: val_loss -0.7722 +2024-11-21 14:30:53.416814: Pseudo dice [0.8562] +2024-11-21 14:30:53.416915: Epoch time: 19.44 s +2024-11-21 14:30:54.422390: +2024-11-21 14:30:54.422606: Epoch 688 +2024-11-21 14:30:54.422733: Current learning rate: 0.00922 +2024-11-21 14:31:14.073036: train_loss -0.7626 +2024-11-21 14:31:14.077521: val_loss -0.7616 +2024-11-21 14:31:14.077634: Pseudo dice [0.8421] +2024-11-21 14:31:14.077722: Epoch time: 19.65 s +2024-11-21 14:31:15.154405: +2024-11-21 14:31:15.154688: Epoch 689 +2024-11-21 14:31:15.154806: Current learning rate: 0.00922 +2024-11-21 14:31:34.457052: train_loss -0.762 +2024-11-21 14:31:34.459365: val_loss -0.7657 +2024-11-21 14:31:34.459480: Pseudo dice [0.8524] +2024-11-21 14:31:34.459578: Epoch time: 19.3 s +2024-11-21 14:31:35.348072: +2024-11-21 14:31:35.348278: Epoch 690 +2024-11-21 14:31:35.348400: Current learning rate: 0.00922 +2024-11-21 14:31:54.062297: train_loss -0.7279 +2024-11-21 14:31:54.063962: val_loss -0.6986 +2024-11-21 14:31:54.064093: Pseudo dice [0.8065] +2024-11-21 14:31:54.064194: Epoch time: 18.72 s +2024-11-21 14:31:55.300674: +2024-11-21 14:31:55.300900: Epoch 691 +2024-11-21 14:31:55.301022: Current learning rate: 0.00922 +2024-11-21 14:32:14.106505: train_loss -0.7223 +2024-11-21 14:32:14.111661: val_loss -0.745 +2024-11-21 14:32:14.111806: Pseudo dice [0.836] +2024-11-21 14:32:14.111916: Epoch time: 18.81 s +2024-11-21 14:32:15.050956: +2024-11-21 14:32:15.051195: Epoch 692 +2024-11-21 14:32:15.051330: Current learning rate: 0.00922 +2024-11-21 14:32:34.577393: train_loss -0.7255 +2024-11-21 14:32:34.580898: val_loss -0.7519 +2024-11-21 14:32:34.581041: Pseudo dice [0.8295] +2024-11-21 14:32:34.581159: Epoch time: 19.53 s +2024-11-21 14:32:35.403593: +2024-11-21 14:32:35.403795: Epoch 693 +2024-11-21 14:32:35.403923: Current learning rate: 0.00922 +2024-11-21 14:32:53.864992: train_loss -0.7291 +2024-11-21 14:32:53.870964: val_loss -0.7191 +2024-11-21 14:32:53.871103: Pseudo dice [0.8294] +2024-11-21 14:32:53.871200: Epoch time: 18.46 s +2024-11-21 14:32:54.854243: +2024-11-21 14:32:54.854480: Epoch 694 +2024-11-21 14:32:54.854616: Current learning rate: 0.00922 +2024-11-21 14:33:13.884553: train_loss -0.7368 +2024-11-21 14:33:13.890250: val_loss -0.7646 +2024-11-21 14:33:13.890391: Pseudo dice [0.8474] +2024-11-21 14:33:13.890495: Epoch time: 19.03 s +2024-11-21 14:33:14.721363: +2024-11-21 14:33:14.721608: Epoch 695 +2024-11-21 14:33:14.721744: Current learning rate: 0.00921 +2024-11-21 14:33:34.861710: train_loss -0.7523 +2024-11-21 14:33:34.870483: val_loss -0.7469 +2024-11-21 14:33:34.870642: Pseudo dice [0.8387] +2024-11-21 14:33:34.870744: Epoch time: 20.14 s +2024-11-21 14:33:35.736337: +2024-11-21 14:33:35.736537: Epoch 696 +2024-11-21 14:33:35.736650: Current learning rate: 0.00921 +2024-11-21 14:33:53.835943: train_loss -0.7629 +2024-11-21 14:33:53.839698: val_loss -0.7721 +2024-11-21 14:33:53.839833: Pseudo dice [0.8504] +2024-11-21 14:33:53.839921: Epoch time: 18.1 s +2024-11-21 14:33:54.684300: +2024-11-21 14:33:54.684498: Epoch 697 +2024-11-21 14:33:54.684611: Current learning rate: 0.00921 +2024-11-21 14:34:13.552582: train_loss -0.7535 +2024-11-21 14:34:13.568536: val_loss -0.765 +2024-11-21 14:34:13.568703: Pseudo dice [0.8435] +2024-11-21 14:34:13.568801: Epoch time: 18.87 s +2024-11-21 14:34:14.446595: +2024-11-21 14:34:14.446809: Epoch 698 +2024-11-21 14:34:14.446926: Current learning rate: 0.00921 +2024-11-21 14:34:31.932912: train_loss -0.7543 +2024-11-21 14:34:31.943671: val_loss -0.7131 +2024-11-21 14:34:31.943809: Pseudo dice [0.8253] +2024-11-21 14:34:31.943900: Epoch time: 17.49 s +2024-11-21 14:34:32.791505: +2024-11-21 14:34:32.791699: Epoch 699 +2024-11-21 14:34:32.791825: Current learning rate: 0.00921 +2024-11-21 14:34:50.919662: train_loss -0.7479 +2024-11-21 14:34:50.923636: val_loss -0.7754 +2024-11-21 14:34:50.923769: Pseudo dice [0.8377] +2024-11-21 14:34:50.923857: Epoch time: 18.13 s +2024-11-21 14:34:51.945971: +2024-11-21 14:34:51.946176: Epoch 700 +2024-11-21 14:34:51.946290: Current learning rate: 0.00921 +2024-11-21 14:35:10.911558: train_loss -0.7541 +2024-11-21 14:35:10.914045: val_loss -0.7762 +2024-11-21 14:35:10.914195: Pseudo dice [0.8563] +2024-11-21 14:35:10.914288: Epoch time: 18.97 s +2024-11-21 14:35:11.759854: +2024-11-21 14:35:11.760060: Epoch 701 +2024-11-21 14:35:11.760185: Current learning rate: 0.00921 +2024-11-21 14:35:31.221015: train_loss -0.7533 +2024-11-21 14:35:31.223011: val_loss -0.7239 +2024-11-21 14:35:31.223105: Pseudo dice [0.8338] +2024-11-21 14:35:31.223198: Epoch time: 19.46 s +2024-11-21 14:35:32.436977: +2024-11-21 14:35:32.437183: Epoch 702 +2024-11-21 14:35:32.437325: Current learning rate: 0.00921 +2024-11-21 14:35:50.628284: train_loss -0.766 +2024-11-21 14:35:50.631937: val_loss -0.7561 +2024-11-21 14:35:50.632107: Pseudo dice [0.8532] +2024-11-21 14:35:50.632226: Epoch time: 18.19 s +2024-11-21 14:35:51.469649: +2024-11-21 14:35:51.469875: Epoch 703 +2024-11-21 14:35:51.470000: Current learning rate: 0.00921 +2024-11-21 14:36:10.277250: train_loss -0.7612 +2024-11-21 14:36:10.283215: val_loss -0.7579 +2024-11-21 14:36:10.283368: Pseudo dice [0.8402] +2024-11-21 14:36:10.283459: Epoch time: 18.81 s +2024-11-21 14:36:11.124012: +2024-11-21 14:36:11.124218: Epoch 704 +2024-11-21 14:36:11.124341: Current learning rate: 0.0092 +2024-11-21 14:36:30.502051: train_loss -0.7517 +2024-11-21 14:36:30.509668: val_loss -0.7551 +2024-11-21 14:36:30.509838: Pseudo dice [0.8421] +2024-11-21 14:36:30.509943: Epoch time: 19.38 s +2024-11-21 14:36:31.463896: +2024-11-21 14:36:31.464125: Epoch 705 +2024-11-21 14:36:31.464242: Current learning rate: 0.0092 +2024-11-21 14:36:50.521038: train_loss -0.7567 +2024-11-21 14:36:50.522716: val_loss -0.7311 +2024-11-21 14:36:50.522837: Pseudo dice [0.8494] +2024-11-21 14:36:50.522933: Epoch time: 19.06 s +2024-11-21 14:36:51.347918: +2024-11-21 14:36:51.348104: Epoch 706 +2024-11-21 14:36:51.348233: Current learning rate: 0.0092 +2024-11-21 14:37:10.342558: train_loss -0.7548 +2024-11-21 14:37:10.348346: val_loss -0.7549 +2024-11-21 14:37:10.348488: Pseudo dice [0.829] +2024-11-21 14:37:10.348701: Epoch time: 19.0 s +2024-11-21 14:37:11.337219: +2024-11-21 14:37:11.337431: Epoch 707 +2024-11-21 14:37:11.337566: Current learning rate: 0.0092 +2024-11-21 14:37:30.914127: train_loss -0.7471 +2024-11-21 14:37:30.922732: val_loss -0.7555 +2024-11-21 14:37:30.922870: Pseudo dice [0.8381] +2024-11-21 14:37:30.922957: Epoch time: 19.58 s +2024-11-21 14:37:31.756833: +2024-11-21 14:37:31.757048: Epoch 708 +2024-11-21 14:37:31.757390: Current learning rate: 0.0092 +2024-11-21 14:37:51.779722: train_loss -0.7665 +2024-11-21 14:37:51.781772: val_loss -0.7702 +2024-11-21 14:37:51.781871: Pseudo dice [0.8439] +2024-11-21 14:37:51.781965: Epoch time: 20.02 s +2024-11-21 14:37:52.609170: +2024-11-21 14:37:52.609416: Epoch 709 +2024-11-21 14:37:52.609548: Current learning rate: 0.0092 +2024-11-21 14:38:11.307716: train_loss -0.7652 +2024-11-21 14:38:11.315040: val_loss -0.7788 +2024-11-21 14:38:11.315198: Pseudo dice [0.8409] +2024-11-21 14:38:11.315293: Epoch time: 18.7 s +2024-11-21 14:38:12.176987: +2024-11-21 14:38:12.177174: Epoch 710 +2024-11-21 14:38:12.177340: Current learning rate: 0.0092 +2024-11-21 14:38:31.920245: train_loss -0.7584 +2024-11-21 14:38:31.923553: val_loss -0.7411 +2024-11-21 14:38:31.923686: Pseudo dice [0.8548] +2024-11-21 14:38:31.923773: Epoch time: 19.74 s +2024-11-21 14:38:32.743422: +2024-11-21 14:38:32.743623: Epoch 711 +2024-11-21 14:38:32.743762: Current learning rate: 0.0092 +2024-11-21 14:38:51.859875: train_loss -0.7499 +2024-11-21 14:38:51.867268: val_loss -0.7608 +2024-11-21 14:38:51.867418: Pseudo dice [0.8559] +2024-11-21 14:38:51.867535: Epoch time: 19.12 s +2024-11-21 14:38:52.838011: +2024-11-21 14:38:52.838201: Epoch 712 +2024-11-21 14:38:52.838327: Current learning rate: 0.0092 +2024-11-21 14:39:11.836053: train_loss -0.7568 +2024-11-21 14:39:11.838177: val_loss -0.7373 +2024-11-21 14:39:11.838286: Pseudo dice [0.8433] +2024-11-21 14:39:11.838378: Epoch time: 19.0 s +2024-11-21 14:39:13.059723: +2024-11-21 14:39:13.059944: Epoch 713 +2024-11-21 14:39:13.060084: Current learning rate: 0.00919 +2024-11-21 14:39:31.414733: train_loss -0.76 +2024-11-21 14:39:31.416726: val_loss -0.7739 +2024-11-21 14:39:31.416860: Pseudo dice [0.8396] +2024-11-21 14:39:31.416956: Epoch time: 18.36 s +2024-11-21 14:39:32.265873: +2024-11-21 14:39:32.266083: Epoch 714 +2024-11-21 14:39:32.266214: Current learning rate: 0.00919 +2024-11-21 14:39:51.985816: train_loss -0.7616 +2024-11-21 14:39:51.987781: val_loss -0.7637 +2024-11-21 14:39:51.987885: Pseudo dice [0.8458] +2024-11-21 14:39:51.987982: Epoch time: 19.72 s +2024-11-21 14:39:52.807995: +2024-11-21 14:39:52.808198: Epoch 715 +2024-11-21 14:39:52.808312: Current learning rate: 0.00919 +2024-11-21 14:40:12.617746: train_loss -0.7583 +2024-11-21 14:40:12.619423: val_loss -0.7618 +2024-11-21 14:40:12.619576: Pseudo dice [0.8526] +2024-11-21 14:40:12.619675: Epoch time: 19.81 s +2024-11-21 14:40:13.448676: +2024-11-21 14:40:13.448894: Epoch 716 +2024-11-21 14:40:13.449013: Current learning rate: 0.00919 +2024-11-21 14:40:31.760764: train_loss -0.7619 +2024-11-21 14:40:31.765952: val_loss -0.7635 +2024-11-21 14:40:31.766121: Pseudo dice [0.8433] +2024-11-21 14:40:31.766217: Epoch time: 18.31 s +2024-11-21 14:40:32.597957: +2024-11-21 14:40:32.598176: Epoch 717 +2024-11-21 14:40:32.598298: Current learning rate: 0.00919 +2024-11-21 14:40:51.796643: train_loss -0.7631 +2024-11-21 14:40:51.803844: val_loss -0.7458 +2024-11-21 14:40:51.803978: Pseudo dice [0.8417] +2024-11-21 14:40:51.804078: Epoch time: 19.2 s +2024-11-21 14:40:52.638292: +2024-11-21 14:40:52.638505: Epoch 718 +2024-11-21 14:40:52.638640: Current learning rate: 0.00919 +2024-11-21 14:41:12.410529: train_loss -0.7634 +2024-11-21 14:41:12.416663: val_loss -0.7604 +2024-11-21 14:41:12.416811: Pseudo dice [0.853] +2024-11-21 14:41:12.417034: Epoch time: 19.77 s +2024-11-21 14:41:13.231371: +2024-11-21 14:41:13.231560: Epoch 719 +2024-11-21 14:41:13.231677: Current learning rate: 0.00919 +2024-11-21 14:41:31.684265: train_loss -0.7645 +2024-11-21 14:41:31.686370: val_loss -0.7647 +2024-11-21 14:41:31.686481: Pseudo dice [0.8664] +2024-11-21 14:41:31.686570: Epoch time: 18.45 s +2024-11-21 14:41:32.502967: +2024-11-21 14:41:32.503166: Epoch 720 +2024-11-21 14:41:32.503285: Current learning rate: 0.00919 +2024-11-21 14:41:50.814308: train_loss -0.7653 +2024-11-21 14:41:50.815842: val_loss -0.7526 +2024-11-21 14:41:50.815948: Pseudo dice [0.8396] +2024-11-21 14:41:50.816041: Epoch time: 18.31 s +2024-11-21 14:41:51.635830: +2024-11-21 14:41:51.636022: Epoch 721 +2024-11-21 14:41:51.636165: Current learning rate: 0.00919 +2024-11-21 14:42:11.589897: train_loss -0.7593 +2024-11-21 14:42:11.597430: val_loss -0.7545 +2024-11-21 14:42:11.597566: Pseudo dice [0.8507] +2024-11-21 14:42:11.597654: Epoch time: 19.95 s +2024-11-21 14:42:12.456955: +2024-11-21 14:42:12.457231: Epoch 722 +2024-11-21 14:42:12.457354: Current learning rate: 0.00918 +2024-11-21 14:42:32.076922: train_loss -0.7554 +2024-11-21 14:42:32.105489: val_loss -0.7731 +2024-11-21 14:42:32.105690: Pseudo dice [0.8399] +2024-11-21 14:42:32.105792: Epoch time: 19.62 s +2024-11-21 14:42:33.010399: +2024-11-21 14:42:33.010614: Epoch 723 +2024-11-21 14:42:33.010744: Current learning rate: 0.00918 +2024-11-21 14:42:51.864099: train_loss -0.7639 +2024-11-21 14:42:51.869325: val_loss -0.7352 +2024-11-21 14:42:51.869493: Pseudo dice [0.8282] +2024-11-21 14:42:51.869612: Epoch time: 18.85 s +2024-11-21 14:42:53.074069: +2024-11-21 14:42:53.074289: Epoch 724 +2024-11-21 14:42:53.074461: Current learning rate: 0.00918 +2024-11-21 14:43:11.811635: train_loss -0.7526 +2024-11-21 14:43:11.818860: val_loss -0.7498 +2024-11-21 14:43:11.819003: Pseudo dice [0.8415] +2024-11-21 14:43:11.819155: Epoch time: 18.74 s +2024-11-21 14:43:12.804091: +2024-11-21 14:43:12.804309: Epoch 725 +2024-11-21 14:43:12.804430: Current learning rate: 0.00918 +2024-11-21 14:43:31.858215: train_loss -0.7508 +2024-11-21 14:43:31.860366: val_loss -0.7319 +2024-11-21 14:43:31.860498: Pseudo dice [0.839] +2024-11-21 14:43:31.860591: Epoch time: 19.05 s +2024-11-21 14:43:32.884672: +2024-11-21 14:43:32.884869: Epoch 726 +2024-11-21 14:43:32.884984: Current learning rate: 0.00918 +2024-11-21 14:43:52.077346: train_loss -0.766 +2024-11-21 14:43:52.081854: val_loss -0.7674 +2024-11-21 14:43:52.081997: Pseudo dice [0.8366] +2024-11-21 14:43:52.082103: Epoch time: 19.19 s +2024-11-21 14:43:52.905352: +2024-11-21 14:43:52.905588: Epoch 727 +2024-11-21 14:43:52.905726: Current learning rate: 0.00918 +2024-11-21 14:44:12.464988: train_loss -0.7656 +2024-11-21 14:44:12.470487: val_loss -0.791 +2024-11-21 14:44:12.470630: Pseudo dice [0.8506] +2024-11-21 14:44:12.470716: Epoch time: 19.56 s +2024-11-21 14:44:13.394811: +2024-11-21 14:44:13.395027: Epoch 728 +2024-11-21 14:44:13.395166: Current learning rate: 0.00918 +2024-11-21 14:44:32.384724: train_loss -0.766 +2024-11-21 14:44:32.389938: val_loss -0.7515 +2024-11-21 14:44:32.390067: Pseudo dice [0.8468] +2024-11-21 14:44:32.390153: Epoch time: 18.99 s +2024-11-21 14:44:33.241755: +2024-11-21 14:44:33.241970: Epoch 729 +2024-11-21 14:44:33.242091: Current learning rate: 0.00918 +2024-11-21 14:44:52.392223: train_loss -0.7583 +2024-11-21 14:44:52.401036: val_loss -0.7594 +2024-11-21 14:44:52.401185: Pseudo dice [0.8457] +2024-11-21 14:44:52.401285: Epoch time: 19.15 s +2024-11-21 14:44:53.444625: +2024-11-21 14:44:53.444828: Epoch 730 +2024-11-21 14:44:53.444956: Current learning rate: 0.00917 +2024-11-21 14:45:13.009661: train_loss -0.7609 +2024-11-21 14:45:13.021090: val_loss -0.7551 +2024-11-21 14:45:13.021230: Pseudo dice [0.8514] +2024-11-21 14:45:13.021335: Epoch time: 19.57 s +2024-11-21 14:45:14.014189: +2024-11-21 14:45:14.014407: Epoch 731 +2024-11-21 14:45:14.014530: Current learning rate: 0.00917 +2024-11-21 14:45:33.843085: train_loss -0.7536 +2024-11-21 14:45:33.846202: val_loss -0.7647 +2024-11-21 14:45:33.846341: Pseudo dice [0.842] +2024-11-21 14:45:33.846458: Epoch time: 19.83 s +2024-11-21 14:45:34.659866: +2024-11-21 14:45:34.660077: Epoch 732 +2024-11-21 14:45:34.660197: Current learning rate: 0.00917 +2024-11-21 14:45:52.421880: train_loss -0.7672 +2024-11-21 14:45:52.431294: val_loss -0.7425 +2024-11-21 14:45:52.431452: Pseudo dice [0.8433] +2024-11-21 14:45:52.431542: Epoch time: 17.76 s +2024-11-21 14:45:53.379167: +2024-11-21 14:45:53.379382: Epoch 733 +2024-11-21 14:45:53.379529: Current learning rate: 0.00917 +2024-11-21 14:46:12.083669: train_loss -0.7584 +2024-11-21 14:46:12.088588: val_loss -0.7863 +2024-11-21 14:46:12.088988: Pseudo dice [0.8449] +2024-11-21 14:46:12.089125: Epoch time: 18.71 s +2024-11-21 14:46:12.925888: +2024-11-21 14:46:12.926118: Epoch 734 +2024-11-21 14:46:12.926247: Current learning rate: 0.00917 +2024-11-21 14:46:32.679931: train_loss -0.77 +2024-11-21 14:46:32.681928: val_loss -0.7529 +2024-11-21 14:46:32.682047: Pseudo dice [0.8378] +2024-11-21 14:46:32.682154: Epoch time: 19.75 s +2024-11-21 14:46:33.967645: +2024-11-21 14:46:33.967864: Epoch 735 +2024-11-21 14:46:33.968001: Current learning rate: 0.00917 +2024-11-21 14:46:53.074929: train_loss -0.764 +2024-11-21 14:46:53.080179: val_loss -0.7645 +2024-11-21 14:46:53.080298: Pseudo dice [0.8392] +2024-11-21 14:46:53.080383: Epoch time: 19.11 s +2024-11-21 14:46:53.950917: +2024-11-21 14:46:53.951137: Epoch 736 +2024-11-21 14:46:53.951272: Current learning rate: 0.00917 +2024-11-21 14:47:13.748596: train_loss -0.7518 +2024-11-21 14:47:13.753973: val_loss -0.7463 +2024-11-21 14:47:13.754122: Pseudo dice [0.8452] +2024-11-21 14:47:13.754212: Epoch time: 19.8 s +2024-11-21 14:47:14.591898: +2024-11-21 14:47:14.592128: Epoch 737 +2024-11-21 14:47:14.592259: Current learning rate: 0.00917 +2024-11-21 14:47:33.723790: train_loss -0.7597 +2024-11-21 14:47:33.729845: val_loss -0.724 +2024-11-21 14:47:33.729994: Pseudo dice [0.8398] +2024-11-21 14:47:33.730100: Epoch time: 19.13 s +2024-11-21 14:47:34.848528: +2024-11-21 14:47:34.848726: Epoch 738 +2024-11-21 14:47:34.848862: Current learning rate: 0.00917 +2024-11-21 14:47:55.122087: train_loss -0.7543 +2024-11-21 14:47:55.130481: val_loss -0.7576 +2024-11-21 14:47:55.130619: Pseudo dice [0.8488] +2024-11-21 14:47:55.130699: Epoch time: 20.27 s +2024-11-21 14:47:55.957029: +2024-11-21 14:47:55.957243: Epoch 739 +2024-11-21 14:47:55.957367: Current learning rate: 0.00916 +2024-11-21 14:48:15.042100: train_loss -0.7579 +2024-11-21 14:48:15.044210: val_loss -0.7289 +2024-11-21 14:48:15.044314: Pseudo dice [0.8348] +2024-11-21 14:48:15.044408: Epoch time: 19.09 s +2024-11-21 14:48:15.859529: +2024-11-21 14:48:15.859781: Epoch 740 +2024-11-21 14:48:15.859909: Current learning rate: 0.00916 +2024-11-21 14:48:35.851105: train_loss -0.7542 +2024-11-21 14:48:35.857953: val_loss -0.7647 +2024-11-21 14:48:35.858102: Pseudo dice [0.8497] +2024-11-21 14:48:35.858194: Epoch time: 19.99 s +2024-11-21 14:48:36.682489: +2024-11-21 14:48:36.682691: Epoch 741 +2024-11-21 14:48:36.682822: Current learning rate: 0.00916 +2024-11-21 14:48:55.456999: train_loss -0.7623 +2024-11-21 14:48:55.458287: val_loss -0.7345 +2024-11-21 14:48:55.458394: Pseudo dice [0.8441] +2024-11-21 14:48:55.458482: Epoch time: 18.78 s +2024-11-21 14:48:56.309648: +2024-11-21 14:48:56.309834: Epoch 742 +2024-11-21 14:48:56.309962: Current learning rate: 0.00916 +2024-11-21 14:49:15.307002: train_loss -0.7556 +2024-11-21 14:49:15.311697: val_loss -0.7674 +2024-11-21 14:49:15.311831: Pseudo dice [0.849] +2024-11-21 14:49:15.311932: Epoch time: 19.0 s +2024-11-21 14:49:16.124817: +2024-11-21 14:49:16.125025: Epoch 743 +2024-11-21 14:49:16.125166: Current learning rate: 0.00916 +2024-11-21 14:49:36.075775: train_loss -0.7432 +2024-11-21 14:49:36.085169: val_loss -0.7288 +2024-11-21 14:49:36.085301: Pseudo dice [0.8497] +2024-11-21 14:49:36.085390: Epoch time: 19.95 s +2024-11-21 14:49:36.957219: +2024-11-21 14:49:36.957418: Epoch 744 +2024-11-21 14:49:36.957546: Current learning rate: 0.00916 +2024-11-21 14:49:56.143089: train_loss -0.7634 +2024-11-21 14:49:56.146591: val_loss -0.7723 +2024-11-21 14:49:56.146691: Pseudo dice [0.8392] +2024-11-21 14:49:56.146808: Epoch time: 19.19 s +2024-11-21 14:49:56.958491: +2024-11-21 14:49:56.958670: Epoch 745 +2024-11-21 14:49:56.958783: Current learning rate: 0.00916 +2024-11-21 14:50:15.489181: train_loss -0.753 +2024-11-21 14:50:15.505255: val_loss -0.7404 +2024-11-21 14:50:15.505392: Pseudo dice [0.8483] +2024-11-21 14:50:15.505536: Epoch time: 18.53 s +2024-11-21 14:50:16.820808: +2024-11-21 14:50:16.821013: Epoch 746 +2024-11-21 14:50:16.821135: Current learning rate: 0.00916 +2024-11-21 14:50:35.546435: train_loss -0.7633 +2024-11-21 14:50:35.552618: val_loss -0.7482 +2024-11-21 14:50:35.552835: Pseudo dice [0.8337] +2024-11-21 14:50:35.552945: Epoch time: 18.73 s +2024-11-21 14:50:36.440893: +2024-11-21 14:50:36.441119: Epoch 747 +2024-11-21 14:50:36.441253: Current learning rate: 0.00916 +2024-11-21 14:50:55.232102: train_loss -0.7587 +2024-11-21 14:50:55.251102: val_loss -0.7309 +2024-11-21 14:50:55.251249: Pseudo dice [0.8263] +2024-11-21 14:50:55.251357: Epoch time: 18.79 s +2024-11-21 14:50:56.144886: +2024-11-21 14:50:56.145140: Epoch 748 +2024-11-21 14:50:56.145300: Current learning rate: 0.00915 +2024-11-21 14:51:14.739729: train_loss -0.7583 +2024-11-21 14:51:14.747637: val_loss -0.7364 +2024-11-21 14:51:14.747791: Pseudo dice [0.8427] +2024-11-21 14:51:14.747903: Epoch time: 18.6 s +2024-11-21 14:51:15.600821: +2024-11-21 14:51:15.601015: Epoch 749 +2024-11-21 14:51:15.601139: Current learning rate: 0.00915 +2024-11-21 14:51:35.773424: train_loss -0.7496 +2024-11-21 14:51:35.775557: val_loss -0.7442 +2024-11-21 14:51:35.775646: Pseudo dice [0.8395] +2024-11-21 14:51:35.775736: Epoch time: 20.17 s +2024-11-21 14:51:36.808092: +2024-11-21 14:51:36.808298: Epoch 750 +2024-11-21 14:51:36.808415: Current learning rate: 0.00915 +2024-11-21 14:51:55.884526: train_loss -0.7568 +2024-11-21 14:51:55.887246: val_loss -0.7613 +2024-11-21 14:51:55.887364: Pseudo dice [0.8484] +2024-11-21 14:51:55.887463: Epoch time: 19.08 s +2024-11-21 14:51:56.707298: +2024-11-21 14:51:56.707466: Epoch 751 +2024-11-21 14:51:56.707621: Current learning rate: 0.00915 +2024-11-21 14:52:16.642714: train_loss -0.7614 +2024-11-21 14:52:16.645584: val_loss -0.7585 +2024-11-21 14:52:16.645708: Pseudo dice [0.8467] +2024-11-21 14:52:16.645809: Epoch time: 19.94 s +2024-11-21 14:52:17.461501: +2024-11-21 14:52:17.461684: Epoch 752 +2024-11-21 14:52:17.461802: Current learning rate: 0.00915 +2024-11-21 14:52:36.531472: train_loss -0.7583 +2024-11-21 14:52:36.538181: val_loss -0.7483 +2024-11-21 14:52:36.538314: Pseudo dice [0.8492] +2024-11-21 14:52:36.538416: Epoch time: 19.07 s +2024-11-21 14:52:37.549448: +2024-11-21 14:52:37.549663: Epoch 753 +2024-11-21 14:52:37.549787: Current learning rate: 0.00915 +2024-11-21 14:52:55.481631: train_loss -0.7618 +2024-11-21 14:52:55.488237: val_loss -0.7578 +2024-11-21 14:52:55.488384: Pseudo dice [0.8369] +2024-11-21 14:52:55.488485: Epoch time: 17.93 s +2024-11-21 14:52:56.502479: +2024-11-21 14:52:56.502671: Epoch 754 +2024-11-21 14:52:56.502796: Current learning rate: 0.00915 +2024-11-21 14:53:16.034710: train_loss -0.7536 +2024-11-21 14:53:16.050322: val_loss -0.754 +2024-11-21 14:53:16.050549: Pseudo dice [0.8511] +2024-11-21 14:53:16.050635: Epoch time: 19.53 s +2024-11-21 14:53:16.864134: +2024-11-21 14:53:16.864326: Epoch 755 +2024-11-21 14:53:16.864442: Current learning rate: 0.00915 +2024-11-21 14:53:37.351016: train_loss -0.7572 +2024-11-21 14:53:37.359699: val_loss -0.7546 +2024-11-21 14:53:37.359845: Pseudo dice [0.8235] +2024-11-21 14:53:37.359946: Epoch time: 20.49 s +2024-11-21 14:53:38.176416: +2024-11-21 14:53:38.176617: Epoch 756 +2024-11-21 14:53:38.176785: Current learning rate: 0.00915 +2024-11-21 14:53:55.774432: train_loss -0.7629 +2024-11-21 14:53:55.793036: val_loss -0.7505 +2024-11-21 14:53:55.793190: Pseudo dice [0.8491] +2024-11-21 14:53:55.793276: Epoch time: 17.6 s +2024-11-21 14:53:57.005197: +2024-11-21 14:53:57.005392: Epoch 757 +2024-11-21 14:53:57.005520: Current learning rate: 0.00914 +2024-11-21 14:54:16.310514: train_loss -0.7616 +2024-11-21 14:54:16.317241: val_loss -0.758 +2024-11-21 14:54:16.317387: Pseudo dice [0.849] +2024-11-21 14:54:16.317483: Epoch time: 19.31 s +2024-11-21 14:54:17.183420: +2024-11-21 14:54:17.183669: Epoch 758 +2024-11-21 14:54:17.183792: Current learning rate: 0.00914 +2024-11-21 14:54:35.927476: train_loss -0.7587 +2024-11-21 14:54:35.934865: val_loss -0.7392 +2024-11-21 14:54:35.935008: Pseudo dice [0.8332] +2024-11-21 14:54:35.935112: Epoch time: 18.74 s +2024-11-21 14:54:36.957105: +2024-11-21 14:54:36.957315: Epoch 759 +2024-11-21 14:54:36.957721: Current learning rate: 0.00914 +2024-11-21 14:54:55.513584: train_loss -0.7548 +2024-11-21 14:54:55.516995: val_loss -0.7791 +2024-11-21 14:54:55.517118: Pseudo dice [0.8479] +2024-11-21 14:54:55.517203: Epoch time: 18.56 s +2024-11-21 14:54:56.442328: +2024-11-21 14:54:56.442508: Epoch 760 +2024-11-21 14:54:56.442625: Current learning rate: 0.00914 +2024-11-21 14:55:14.646172: train_loss -0.7539 +2024-11-21 14:55:14.648750: val_loss -0.7746 +2024-11-21 14:55:14.648890: Pseudo dice [0.8446] +2024-11-21 14:55:14.648987: Epoch time: 18.2 s +2024-11-21 14:55:15.641944: +2024-11-21 14:55:15.642148: Epoch 761 +2024-11-21 14:55:15.642282: Current learning rate: 0.00914 +2024-11-21 14:55:35.208055: train_loss -0.7642 +2024-11-21 14:55:35.213359: val_loss -0.7612 +2024-11-21 14:55:35.213502: Pseudo dice [0.8512] +2024-11-21 14:55:35.213600: Epoch time: 19.57 s +2024-11-21 14:55:36.028741: +2024-11-21 14:55:36.028941: Epoch 762 +2024-11-21 14:55:36.029068: Current learning rate: 0.00914 +2024-11-21 14:55:56.094816: train_loss -0.7541 +2024-11-21 14:55:56.096985: val_loss -0.7528 +2024-11-21 14:55:56.097138: Pseudo dice [0.8306] +2024-11-21 14:55:56.097249: Epoch time: 20.07 s +2024-11-21 14:55:57.092175: +2024-11-21 14:55:57.092419: Epoch 763 +2024-11-21 14:55:57.092549: Current learning rate: 0.00914 +2024-11-21 14:56:16.744495: train_loss -0.7515 +2024-11-21 14:56:16.749645: val_loss -0.7569 +2024-11-21 14:56:16.749787: Pseudo dice [0.8445] +2024-11-21 14:56:16.749924: Epoch time: 19.65 s +2024-11-21 14:56:17.610788: +2024-11-21 14:56:17.611011: Epoch 764 +2024-11-21 14:56:17.611140: Current learning rate: 0.00914 +2024-11-21 14:56:37.006960: train_loss -0.7612 +2024-11-21 14:56:37.011598: val_loss -0.7297 +2024-11-21 14:56:37.011723: Pseudo dice [0.8343] +2024-11-21 14:56:37.011809: Epoch time: 19.4 s +2024-11-21 14:56:37.834903: +2024-11-21 14:56:37.835083: Epoch 765 +2024-11-21 14:56:37.835238: Current learning rate: 0.00914 +2024-11-21 14:56:58.167225: train_loss -0.7473 +2024-11-21 14:56:58.169576: val_loss -0.7565 +2024-11-21 14:56:58.169677: Pseudo dice [0.8484] +2024-11-21 14:56:58.169765: Epoch time: 20.33 s +2024-11-21 14:56:58.989834: +2024-11-21 14:56:58.990028: Epoch 766 +2024-11-21 14:56:58.990165: Current learning rate: 0.00913 +2024-11-21 14:57:18.866061: train_loss -0.7592 +2024-11-21 14:57:18.870738: val_loss -0.7545 +2024-11-21 14:57:18.870883: Pseudo dice [0.8445] +2024-11-21 14:57:18.870991: Epoch time: 19.88 s +2024-11-21 14:57:19.703238: +2024-11-21 14:57:19.703420: Epoch 767 +2024-11-21 14:57:19.703537: Current learning rate: 0.00913 +2024-11-21 14:57:39.614088: train_loss -0.7495 +2024-11-21 14:57:39.622915: val_loss -0.7813 +2024-11-21 14:57:39.623047: Pseudo dice [0.8444] +2024-11-21 14:57:39.623147: Epoch time: 19.91 s +2024-11-21 14:57:40.966857: +2024-11-21 14:57:40.967057: Epoch 768 +2024-11-21 14:57:40.967181: Current learning rate: 0.00913 +2024-11-21 14:58:01.529615: train_loss -0.7516 +2024-11-21 14:58:01.532533: val_loss -0.7291 +2024-11-21 14:58:01.532647: Pseudo dice [0.8381] +2024-11-21 14:58:01.532729: Epoch time: 20.56 s +2024-11-21 14:58:02.513553: +2024-11-21 14:58:02.513754: Epoch 769 +2024-11-21 14:58:02.513882: Current learning rate: 0.00913 +2024-11-21 14:58:22.236324: train_loss -0.7642 +2024-11-21 14:58:22.245492: val_loss -0.755 +2024-11-21 14:58:22.245638: Pseudo dice [0.8321] +2024-11-21 14:58:22.245730: Epoch time: 19.72 s +2024-11-21 14:58:23.078513: +2024-11-21 14:58:23.078803: Epoch 770 +2024-11-21 14:58:23.078964: Current learning rate: 0.00913 +2024-11-21 14:58:42.961475: train_loss -0.7477 +2024-11-21 14:58:42.969369: val_loss -0.7469 +2024-11-21 14:58:42.969484: Pseudo dice [0.8484] +2024-11-21 14:58:42.969577: Epoch time: 19.88 s +2024-11-21 14:58:43.864950: +2024-11-21 14:58:43.865167: Epoch 771 +2024-11-21 14:58:43.865292: Current learning rate: 0.00913 +2024-11-21 14:59:02.938378: train_loss -0.7485 +2024-11-21 14:59:02.944450: val_loss -0.7458 +2024-11-21 14:59:02.944581: Pseudo dice [0.834] +2024-11-21 14:59:02.944674: Epoch time: 19.07 s +2024-11-21 14:59:03.790220: +2024-11-21 14:59:03.790416: Epoch 772 +2024-11-21 14:59:03.790540: Current learning rate: 0.00913 +2024-11-21 14:59:22.624820: train_loss -0.7507 +2024-11-21 14:59:22.635762: val_loss -0.789 +2024-11-21 14:59:22.635877: Pseudo dice [0.8474] +2024-11-21 14:59:22.635965: Epoch time: 18.84 s +2024-11-21 14:59:23.672213: +2024-11-21 14:59:23.672432: Epoch 773 +2024-11-21 14:59:23.672554: Current learning rate: 0.00913 +2024-11-21 14:59:43.760027: train_loss -0.7573 +2024-11-21 14:59:43.767689: val_loss -0.7184 +2024-11-21 14:59:43.767812: Pseudo dice [0.8417] +2024-11-21 14:59:43.767906: Epoch time: 20.09 s +2024-11-21 14:59:44.786816: +2024-11-21 14:59:44.787048: Epoch 774 +2024-11-21 14:59:44.787190: Current learning rate: 0.00912 +2024-11-21 15:00:03.272755: train_loss -0.7551 +2024-11-21 15:00:03.275100: val_loss -0.7447 +2024-11-21 15:00:03.275220: Pseudo dice [0.838] +2024-11-21 15:00:03.275314: Epoch time: 18.49 s +2024-11-21 15:00:04.177325: +2024-11-21 15:00:04.177573: Epoch 775 +2024-11-21 15:00:04.177708: Current learning rate: 0.00912 +2024-11-21 15:00:23.550928: train_loss -0.7625 +2024-11-21 15:00:23.558921: val_loss -0.7474 +2024-11-21 15:00:23.559069: Pseudo dice [0.8491] +2024-11-21 15:00:23.559171: Epoch time: 19.37 s +2024-11-21 15:00:24.401418: +2024-11-21 15:00:24.401592: Epoch 776 +2024-11-21 15:00:24.401712: Current learning rate: 0.00912 +2024-11-21 15:00:43.869809: train_loss -0.7575 +2024-11-21 15:00:43.876674: val_loss -0.7611 +2024-11-21 15:00:43.876815: Pseudo dice [0.8386] +2024-11-21 15:00:43.876923: Epoch time: 19.47 s +2024-11-21 15:00:44.711817: +2024-11-21 15:00:44.712007: Epoch 777 +2024-11-21 15:00:44.712129: Current learning rate: 0.00912 +2024-11-21 15:01:04.476418: train_loss -0.7601 +2024-11-21 15:01:04.497233: val_loss -0.7807 +2024-11-21 15:01:04.497357: Pseudo dice [0.8568] +2024-11-21 15:01:04.497452: Epoch time: 19.77 s +2024-11-21 15:01:05.444210: +2024-11-21 15:01:05.444428: Epoch 778 +2024-11-21 15:01:05.444563: Current learning rate: 0.00912 +2024-11-21 15:01:24.252268: train_loss -0.7551 +2024-11-21 15:01:24.259459: val_loss -0.7461 +2024-11-21 15:01:24.259602: Pseudo dice [0.8527] +2024-11-21 15:01:24.259687: Epoch time: 18.81 s +2024-11-21 15:01:25.506514: +2024-11-21 15:01:25.506699: Epoch 779 +2024-11-21 15:01:25.506815: Current learning rate: 0.00912 +2024-11-21 15:01:44.493189: train_loss -0.7653 +2024-11-21 15:01:44.499094: val_loss -0.7522 +2024-11-21 15:01:44.499237: Pseudo dice [0.8572] +2024-11-21 15:01:44.499337: Epoch time: 18.99 s +2024-11-21 15:01:45.344327: +2024-11-21 15:01:45.344510: Epoch 780 +2024-11-21 15:01:45.344632: Current learning rate: 0.00912 +2024-11-21 15:02:04.061817: train_loss -0.7553 +2024-11-21 15:02:04.064191: val_loss -0.781 +2024-11-21 15:02:04.064341: Pseudo dice [0.847] +2024-11-21 15:02:04.064445: Epoch time: 18.72 s +2024-11-21 15:02:04.904994: +2024-11-21 15:02:04.905215: Epoch 781 +2024-11-21 15:02:04.905355: Current learning rate: 0.00912 +2024-11-21 15:02:24.097623: train_loss -0.7607 +2024-11-21 15:02:24.103744: val_loss -0.7476 +2024-11-21 15:02:24.103891: Pseudo dice [0.8535] +2024-11-21 15:02:24.103986: Epoch time: 19.19 s +2024-11-21 15:02:24.991355: +2024-11-21 15:02:24.991551: Epoch 782 +2024-11-21 15:02:24.991676: Current learning rate: 0.00912 +2024-11-21 15:02:44.558653: train_loss -0.7606 +2024-11-21 15:02:44.564553: val_loss -0.7731 +2024-11-21 15:02:44.564687: Pseudo dice [0.8444] +2024-11-21 15:02:44.564782: Epoch time: 19.57 s +2024-11-21 15:02:45.393927: +2024-11-21 15:02:45.394128: Epoch 783 +2024-11-21 15:02:45.394250: Current learning rate: 0.00911 +2024-11-21 15:03:03.772754: train_loss -0.7511 +2024-11-21 15:03:03.799509: val_loss -0.741 +2024-11-21 15:03:03.799660: Pseudo dice [0.856] +2024-11-21 15:03:03.799749: Epoch time: 18.38 s +2024-11-21 15:03:04.671513: +2024-11-21 15:03:04.671695: Epoch 784 +2024-11-21 15:03:04.671827: Current learning rate: 0.00911 +2024-11-21 15:03:22.533807: train_loss -0.7632 +2024-11-21 15:03:22.535407: val_loss -0.7863 +2024-11-21 15:03:22.560467: Pseudo dice [0.8547] +2024-11-21 15:03:22.560606: Epoch time: 17.86 s +2024-11-21 15:03:23.381589: +2024-11-21 15:03:23.381812: Epoch 785 +2024-11-21 15:03:23.381934: Current learning rate: 0.00911 +2024-11-21 15:03:41.960163: train_loss -0.7654 +2024-11-21 15:03:41.967364: val_loss -0.7548 +2024-11-21 15:03:41.967505: Pseudo dice [0.8585] +2024-11-21 15:03:41.967595: Epoch time: 18.58 s +2024-11-21 15:03:41.967671: Yayy! New best EMA pseudo Dice: 0.849 +2024-11-21 15:03:43.171243: +2024-11-21 15:03:43.171439: Epoch 786 +2024-11-21 15:03:43.171566: Current learning rate: 0.00911 +2024-11-21 15:04:02.251369: train_loss -0.7694 +2024-11-21 15:04:02.258293: val_loss -0.7636 +2024-11-21 15:04:02.258428: Pseudo dice [0.8463] +2024-11-21 15:04:02.258523: Epoch time: 19.08 s +2024-11-21 15:04:03.215899: +2024-11-21 15:04:03.216093: Epoch 787 +2024-11-21 15:04:03.216218: Current learning rate: 0.00911 +2024-11-21 15:04:21.276472: train_loss -0.7656 +2024-11-21 15:04:21.281226: val_loss -0.754 +2024-11-21 15:04:21.281374: Pseudo dice [0.843] +2024-11-21 15:04:21.281464: Epoch time: 18.06 s +2024-11-21 15:04:22.121336: +2024-11-21 15:04:22.121525: Epoch 788 +2024-11-21 15:04:22.121654: Current learning rate: 0.00911 +2024-11-21 15:04:41.239309: train_loss -0.7599 +2024-11-21 15:04:41.243799: val_loss -0.7603 +2024-11-21 15:04:41.243964: Pseudo dice [0.8447] +2024-11-21 15:04:41.244096: Epoch time: 19.12 s +2024-11-21 15:04:42.462747: +2024-11-21 15:04:42.462960: Epoch 789 +2024-11-21 15:04:42.463082: Current learning rate: 0.00911 +2024-11-21 15:05:00.727700: train_loss -0.763 +2024-11-21 15:05:00.735299: val_loss -0.7282 +2024-11-21 15:05:00.735409: Pseudo dice [0.8292] +2024-11-21 15:05:00.735486: Epoch time: 18.27 s +2024-11-21 15:05:01.561409: +2024-11-21 15:05:01.561617: Epoch 790 +2024-11-21 15:05:01.561732: Current learning rate: 0.00911 +2024-11-21 15:05:21.027262: train_loss -0.757 +2024-11-21 15:05:21.032886: val_loss -0.7459 +2024-11-21 15:05:21.033109: Pseudo dice [0.8523] +2024-11-21 15:05:21.033211: Epoch time: 19.47 s +2024-11-21 15:05:22.048360: +2024-11-21 15:05:22.048562: Epoch 791 +2024-11-21 15:05:22.048694: Current learning rate: 0.00911 +2024-11-21 15:05:41.540961: train_loss -0.7603 +2024-11-21 15:05:41.543661: val_loss -0.7482 +2024-11-21 15:05:41.549164: Pseudo dice [0.8414] +2024-11-21 15:05:41.549289: Epoch time: 19.49 s +2024-11-21 15:05:42.551836: +2024-11-21 15:05:42.552030: Epoch 792 +2024-11-21 15:05:42.552171: Current learning rate: 0.0091 +2024-11-21 15:06:01.285931: train_loss -0.75 +2024-11-21 15:06:01.287935: val_loss -0.7383 +2024-11-21 15:06:01.288086: Pseudo dice [0.8453] +2024-11-21 15:06:01.288170: Epoch time: 18.73 s +2024-11-21 15:06:02.106682: +2024-11-21 15:06:02.106896: Epoch 793 +2024-11-21 15:06:02.107033: Current learning rate: 0.0091 +2024-11-21 15:06:21.344069: train_loss -0.7614 +2024-11-21 15:06:21.346067: val_loss -0.7514 +2024-11-21 15:06:21.346210: Pseudo dice [0.8463] +2024-11-21 15:06:21.346354: Epoch time: 19.24 s +2024-11-21 15:06:22.271349: +2024-11-21 15:06:22.271550: Epoch 794 +2024-11-21 15:06:22.271681: Current learning rate: 0.0091 +2024-11-21 15:06:41.860312: train_loss -0.7578 +2024-11-21 15:06:41.865740: val_loss -0.7391 +2024-11-21 15:06:41.865885: Pseudo dice [0.8415] +2024-11-21 15:06:41.865978: Epoch time: 19.59 s +2024-11-21 15:06:42.831159: +2024-11-21 15:06:42.831356: Epoch 795 +2024-11-21 15:06:42.831480: Current learning rate: 0.0091 +2024-11-21 15:07:01.967017: train_loss -0.7694 +2024-11-21 15:07:01.975841: val_loss -0.764 +2024-11-21 15:07:01.975973: Pseudo dice [0.8287] +2024-11-21 15:07:01.976069: Epoch time: 19.14 s +2024-11-21 15:07:02.843270: +2024-11-21 15:07:02.843504: Epoch 796 +2024-11-21 15:07:02.843615: Current learning rate: 0.0091 +2024-11-21 15:07:20.564556: train_loss -0.755 +2024-11-21 15:07:20.571572: val_loss -0.7487 +2024-11-21 15:07:20.571707: Pseudo dice [0.84] +2024-11-21 15:07:20.571806: Epoch time: 17.72 s +2024-11-21 15:07:21.575514: +2024-11-21 15:07:21.575728: Epoch 797 +2024-11-21 15:07:21.576090: Current learning rate: 0.0091 +2024-11-21 15:07:40.493039: train_loss -0.7496 +2024-11-21 15:07:40.505950: val_loss -0.759 +2024-11-21 15:07:40.506100: Pseudo dice [0.8471] +2024-11-21 15:07:40.506195: Epoch time: 18.92 s +2024-11-21 15:07:41.433420: +2024-11-21 15:07:41.433638: Epoch 798 +2024-11-21 15:07:41.433759: Current learning rate: 0.0091 +2024-11-21 15:07:59.960097: train_loss -0.7673 +2024-11-21 15:07:59.965247: val_loss -0.7485 +2024-11-21 15:07:59.965397: Pseudo dice [0.8393] +2024-11-21 15:07:59.965495: Epoch time: 18.53 s +2024-11-21 15:08:01.020806: +2024-11-21 15:08:01.021041: Epoch 799 +2024-11-21 15:08:01.021176: Current learning rate: 0.0091 +2024-11-21 15:08:20.842736: train_loss -0.7555 +2024-11-21 15:08:20.849678: val_loss -0.7677 +2024-11-21 15:08:20.849823: Pseudo dice [0.8415] +2024-11-21 15:08:20.849921: Epoch time: 19.82 s +2024-11-21 15:08:22.533577: +2024-11-21 15:08:22.533813: Epoch 800 +2024-11-21 15:08:22.533946: Current learning rate: 0.0091 +2024-11-21 15:08:42.088583: train_loss -0.7642 +2024-11-21 15:08:42.093700: val_loss -0.7432 +2024-11-21 15:08:42.093843: Pseudo dice [0.8335] +2024-11-21 15:08:42.093941: Epoch time: 19.56 s +2024-11-21 15:08:42.920874: +2024-11-21 15:08:42.921086: Epoch 801 +2024-11-21 15:08:42.921222: Current learning rate: 0.00909 +2024-11-21 15:09:02.197585: train_loss -0.7679 +2024-11-21 15:09:02.204575: val_loss -0.7237 +2024-11-21 15:09:02.204707: Pseudo dice [0.8436] +2024-11-21 15:09:02.204819: Epoch time: 19.28 s +2024-11-21 15:09:03.135403: +2024-11-21 15:09:03.135635: Epoch 802 +2024-11-21 15:09:03.135752: Current learning rate: 0.00909 +2024-11-21 15:09:23.474595: train_loss -0.7609 +2024-11-21 15:09:23.480375: val_loss -0.7474 +2024-11-21 15:09:23.480524: Pseudo dice [0.8507] +2024-11-21 15:09:23.480636: Epoch time: 20.34 s +2024-11-21 15:09:24.439893: +2024-11-21 15:09:24.440108: Epoch 803 +2024-11-21 15:09:24.440222: Current learning rate: 0.00909 +2024-11-21 15:09:42.068993: train_loss -0.7685 +2024-11-21 15:09:42.073292: val_loss -0.7339 +2024-11-21 15:09:42.073447: Pseudo dice [0.8299] +2024-11-21 15:09:42.073537: Epoch time: 17.63 s +2024-11-21 15:09:42.915107: +2024-11-21 15:09:42.915330: Epoch 804 +2024-11-21 15:09:42.915465: Current learning rate: 0.00909 +2024-11-21 15:10:01.182576: train_loss -0.7547 +2024-11-21 15:10:01.188634: val_loss -0.7566 +2024-11-21 15:10:01.188776: Pseudo dice [0.8524] +2024-11-21 15:10:01.188867: Epoch time: 18.27 s +2024-11-21 15:10:02.079852: +2024-11-21 15:10:02.080092: Epoch 805 +2024-11-21 15:10:02.080231: Current learning rate: 0.00909 +2024-11-21 15:10:20.731672: train_loss -0.7689 +2024-11-21 15:10:20.737933: val_loss -0.7677 +2024-11-21 15:10:20.738107: Pseudo dice [0.8335] +2024-11-21 15:10:20.738215: Epoch time: 18.65 s +2024-11-21 15:10:21.790625: +2024-11-21 15:10:21.790825: Epoch 806 +2024-11-21 15:10:21.790962: Current learning rate: 0.00909 +2024-11-21 15:10:40.934613: train_loss -0.7591 +2024-11-21 15:10:40.941482: val_loss -0.7484 +2024-11-21 15:10:40.941600: Pseudo dice [0.8207] +2024-11-21 15:10:40.941724: Epoch time: 19.14 s +2024-11-21 15:10:41.770678: +2024-11-21 15:10:41.770884: Epoch 807 +2024-11-21 15:10:41.771024: Current learning rate: 0.00909 +2024-11-21 15:11:00.655924: train_loss -0.7602 +2024-11-21 15:11:00.662482: val_loss -0.7565 +2024-11-21 15:11:00.662610: Pseudo dice [0.851] +2024-11-21 15:11:00.662706: Epoch time: 18.89 s +2024-11-21 15:11:01.766247: +2024-11-21 15:11:01.766464: Epoch 808 +2024-11-21 15:11:01.766577: Current learning rate: 0.00909 +2024-11-21 15:11:22.772387: train_loss -0.7636 +2024-11-21 15:11:22.783748: val_loss -0.7681 +2024-11-21 15:11:22.783898: Pseudo dice [0.8567] +2024-11-21 15:11:22.783978: Epoch time: 21.01 s +2024-11-21 15:11:23.625745: +2024-11-21 15:11:23.626052: Epoch 809 +2024-11-21 15:11:23.626179: Current learning rate: 0.00909 +2024-11-21 15:11:42.681643: train_loss -0.7671 +2024-11-21 15:11:42.688631: val_loss -0.7633 +2024-11-21 15:11:42.688766: Pseudo dice [0.8427] +2024-11-21 15:11:42.688871: Epoch time: 19.06 s +2024-11-21 15:11:43.530754: +2024-11-21 15:11:43.531301: Epoch 810 +2024-11-21 15:11:43.531429: Current learning rate: 0.00908 +2024-11-21 15:12:02.814477: train_loss -0.7618 +2024-11-21 15:12:02.817809: val_loss -0.7528 +2024-11-21 15:12:02.817905: Pseudo dice [0.8525] +2024-11-21 15:12:02.818003: Epoch time: 19.28 s +2024-11-21 15:12:04.055726: +2024-11-21 15:12:04.055962: Epoch 811 +2024-11-21 15:12:04.056088: Current learning rate: 0.00908 +2024-11-21 15:12:23.234073: train_loss -0.7701 +2024-11-21 15:12:23.249283: val_loss -0.7545 +2024-11-21 15:12:23.249416: Pseudo dice [0.8565] +2024-11-21 15:12:23.249517: Epoch time: 19.18 s +2024-11-21 15:12:24.210888: +2024-11-21 15:12:24.211118: Epoch 812 +2024-11-21 15:12:24.211248: Current learning rate: 0.00908 +2024-11-21 15:12:42.637557: train_loss -0.7665 +2024-11-21 15:12:42.640530: val_loss -0.7453 +2024-11-21 15:12:42.640636: Pseudo dice [0.8426] +2024-11-21 15:12:42.640722: Epoch time: 18.43 s +2024-11-21 15:12:43.472491: +2024-11-21 15:12:43.472703: Epoch 813 +2024-11-21 15:12:43.472829: Current learning rate: 0.00908 +2024-11-21 15:13:01.808769: train_loss -0.7675 +2024-11-21 15:13:01.818622: val_loss -0.759 +2024-11-21 15:13:01.818761: Pseudo dice [0.8394] +2024-11-21 15:13:01.818847: Epoch time: 18.34 s +2024-11-21 15:13:02.820559: +2024-11-21 15:13:02.820764: Epoch 814 +2024-11-21 15:13:02.820886: Current learning rate: 0.00908 +2024-11-21 15:13:22.022694: train_loss -0.7622 +2024-11-21 15:13:22.031603: val_loss -0.7581 +2024-11-21 15:13:22.031741: Pseudo dice [0.8337] +2024-11-21 15:13:22.031838: Epoch time: 19.2 s +2024-11-21 15:13:22.890226: +2024-11-21 15:13:22.890440: Epoch 815 +2024-11-21 15:13:22.890566: Current learning rate: 0.00908 +2024-11-21 15:13:41.761022: train_loss -0.77 +2024-11-21 15:13:41.769329: val_loss -0.7538 +2024-11-21 15:13:41.769455: Pseudo dice [0.8482] +2024-11-21 15:13:41.769553: Epoch time: 18.87 s +2024-11-21 15:13:42.771507: +2024-11-21 15:13:42.771775: Epoch 816 +2024-11-21 15:13:42.771900: Current learning rate: 0.00908 +2024-11-21 15:14:01.244395: train_loss -0.7608 +2024-11-21 15:14:01.252692: val_loss -0.7697 +2024-11-21 15:14:01.252838: Pseudo dice [0.8503] +2024-11-21 15:14:01.252933: Epoch time: 18.47 s +2024-11-21 15:14:02.135273: +2024-11-21 15:14:02.135486: Epoch 817 +2024-11-21 15:14:02.135611: Current learning rate: 0.00908 +2024-11-21 15:14:20.498760: train_loss -0.7662 +2024-11-21 15:14:20.516981: val_loss -0.7641 +2024-11-21 15:14:20.517148: Pseudo dice [0.8394] +2024-11-21 15:14:20.517267: Epoch time: 18.36 s +2024-11-21 15:14:21.375124: +2024-11-21 15:14:21.375359: Epoch 818 +2024-11-21 15:14:21.375481: Current learning rate: 0.00907 +2024-11-21 15:14:41.344488: train_loss -0.7585 +2024-11-21 15:14:41.368408: val_loss -0.7618 +2024-11-21 15:14:41.368576: Pseudo dice [0.8414] +2024-11-21 15:14:41.368683: Epoch time: 19.97 s +2024-11-21 15:14:42.214280: +2024-11-21 15:14:42.214477: Epoch 819 +2024-11-21 15:14:42.214611: Current learning rate: 0.00907 +2024-11-21 15:15:01.410001: train_loss -0.7624 +2024-11-21 15:15:01.416394: val_loss -0.7546 +2024-11-21 15:15:01.416517: Pseudo dice [0.8449] +2024-11-21 15:15:01.416613: Epoch time: 19.2 s +2024-11-21 15:15:02.211575: +2024-11-21 15:15:02.211746: Epoch 820 +2024-11-21 15:15:02.211867: Current learning rate: 0.00907 +2024-11-21 15:15:21.648750: train_loss -0.7661 +2024-11-21 15:15:21.655481: val_loss -0.7661 +2024-11-21 15:15:21.655622: Pseudo dice [0.8531] +2024-11-21 15:15:21.655730: Epoch time: 19.44 s +2024-11-21 15:15:22.479605: +2024-11-21 15:15:22.479809: Epoch 821 +2024-11-21 15:15:22.479925: Current learning rate: 0.00907 +2024-11-21 15:15:42.334509: train_loss -0.765 +2024-11-21 15:15:42.340315: val_loss -0.7658 +2024-11-21 15:15:42.340461: Pseudo dice [0.8464] +2024-11-21 15:15:42.340564: Epoch time: 19.86 s +2024-11-21 15:15:43.534641: +2024-11-21 15:15:43.534855: Epoch 822 +2024-11-21 15:15:43.534982: Current learning rate: 0.00907 +2024-11-21 15:16:02.629742: train_loss -0.7651 +2024-11-21 15:16:02.636379: val_loss -0.7315 +2024-11-21 15:16:02.636774: Pseudo dice [0.852] +2024-11-21 15:16:02.636957: Epoch time: 19.1 s +2024-11-21 15:16:03.568533: +2024-11-21 15:16:03.568793: Epoch 823 +2024-11-21 15:16:03.568921: Current learning rate: 0.00907 +2024-11-21 15:16:23.034919: train_loss -0.7653 +2024-11-21 15:16:23.038531: val_loss -0.746 +2024-11-21 15:16:23.038652: Pseudo dice [0.839] +2024-11-21 15:16:23.038753: Epoch time: 19.47 s +2024-11-21 15:16:23.842754: +2024-11-21 15:16:23.842970: Epoch 824 +2024-11-21 15:16:23.843096: Current learning rate: 0.00907 +2024-11-21 15:16:43.532022: train_loss -0.761 +2024-11-21 15:16:43.535375: val_loss -0.7536 +2024-11-21 15:16:43.535483: Pseudo dice [0.8394] +2024-11-21 15:16:43.535575: Epoch time: 19.69 s +2024-11-21 15:16:44.351510: +2024-11-21 15:16:44.351706: Epoch 825 +2024-11-21 15:16:44.351816: Current learning rate: 0.00907 +2024-11-21 15:17:03.455379: train_loss -0.7587 +2024-11-21 15:17:03.464398: val_loss -0.7506 +2024-11-21 15:17:03.464511: Pseudo dice [0.83] +2024-11-21 15:17:03.464610: Epoch time: 19.1 s +2024-11-21 15:17:04.518524: +2024-11-21 15:17:04.518726: Epoch 826 +2024-11-21 15:17:04.518859: Current learning rate: 0.00907 +2024-11-21 15:17:24.215281: train_loss -0.7527 +2024-11-21 15:17:24.223675: val_loss -0.7552 +2024-11-21 15:17:24.223818: Pseudo dice [0.8577] +2024-11-21 15:17:24.223930: Epoch time: 19.7 s +2024-11-21 15:17:25.048299: +2024-11-21 15:17:25.048504: Epoch 827 +2024-11-21 15:17:25.048620: Current learning rate: 0.00906 +2024-11-21 15:17:43.703539: train_loss -0.7449 +2024-11-21 15:17:43.706935: val_loss -0.7519 +2024-11-21 15:17:43.707072: Pseudo dice [0.8489] +2024-11-21 15:17:43.707187: Epoch time: 18.66 s +2024-11-21 15:17:44.558874: +2024-11-21 15:17:44.559113: Epoch 828 +2024-11-21 15:17:44.559242: Current learning rate: 0.00906 +2024-11-21 15:18:03.035209: train_loss -0.758 +2024-11-21 15:18:03.038629: val_loss -0.7126 +2024-11-21 15:18:03.038739: Pseudo dice [0.8303] +2024-11-21 15:18:03.038832: Epoch time: 18.48 s +2024-11-21 15:18:03.830068: +2024-11-21 15:18:03.830287: Epoch 829 +2024-11-21 15:18:03.830402: Current learning rate: 0.00906 +2024-11-21 15:18:23.532764: train_loss -0.7418 +2024-11-21 15:18:23.538432: val_loss -0.7541 +2024-11-21 15:18:23.538544: Pseudo dice [0.8329] +2024-11-21 15:18:23.538641: Epoch time: 19.7 s +2024-11-21 15:18:24.383755: +2024-11-21 15:18:24.383964: Epoch 830 +2024-11-21 15:18:24.384092: Current learning rate: 0.00906 +2024-11-21 15:18:43.604736: train_loss -0.7437 +2024-11-21 15:18:43.612408: val_loss -0.7159 +2024-11-21 15:18:43.612622: Pseudo dice [0.8356] +2024-11-21 15:18:43.612726: Epoch time: 19.22 s +2024-11-21 15:18:44.463803: +2024-11-21 15:18:44.463998: Epoch 831 +2024-11-21 15:18:44.464140: Current learning rate: 0.00906 +2024-11-21 15:19:03.677082: train_loss -0.7521 +2024-11-21 15:19:03.680414: val_loss -0.7368 +2024-11-21 15:19:03.680533: Pseudo dice [0.8178] +2024-11-21 15:19:03.680634: Epoch time: 19.21 s +2024-11-21 15:19:04.481000: +2024-11-21 15:19:04.481192: Epoch 832 +2024-11-21 15:19:04.481329: Current learning rate: 0.00906 +2024-11-21 15:19:24.355948: train_loss -0.7443 +2024-11-21 15:19:24.364165: val_loss -0.7587 +2024-11-21 15:19:24.364292: Pseudo dice [0.8326] +2024-11-21 15:19:24.364403: Epoch time: 19.88 s +2024-11-21 15:19:25.250342: +2024-11-21 15:19:25.250528: Epoch 833 +2024-11-21 15:19:25.250654: Current learning rate: 0.00906 +2024-11-21 15:19:44.224818: train_loss -0.7442 +2024-11-21 15:19:44.230996: val_loss -0.7268 +2024-11-21 15:19:44.231142: Pseudo dice [0.8411] +2024-11-21 15:19:44.231237: Epoch time: 18.98 s +2024-11-21 15:19:45.029166: +2024-11-21 15:19:45.029400: Epoch 834 +2024-11-21 15:19:45.029543: Current learning rate: 0.00906 +2024-11-21 15:20:04.050717: train_loss -0.7572 +2024-11-21 15:20:04.061941: val_loss -0.7589 +2024-11-21 15:20:04.062100: Pseudo dice [0.8421] +2024-11-21 15:20:04.062193: Epoch time: 19.02 s +2024-11-21 15:20:04.954139: +2024-11-21 15:20:04.954333: Epoch 835 +2024-11-21 15:20:04.954463: Current learning rate: 0.00906 +2024-11-21 15:20:24.156525: train_loss -0.7502 +2024-11-21 15:20:24.161992: val_loss -0.749 +2024-11-21 15:20:24.162134: Pseudo dice [0.8366] +2024-11-21 15:20:24.162224: Epoch time: 19.2 s +2024-11-21 15:20:25.031410: +2024-11-21 15:20:25.031621: Epoch 836 +2024-11-21 15:20:25.031738: Current learning rate: 0.00905 +2024-11-21 15:20:44.035460: train_loss -0.7628 +2024-11-21 15:20:44.042579: val_loss -0.7432 +2024-11-21 15:20:44.042745: Pseudo dice [0.8339] +2024-11-21 15:20:44.042854: Epoch time: 19.0 s +2024-11-21 15:20:44.841359: +2024-11-21 15:20:44.841556: Epoch 837 +2024-11-21 15:20:44.841669: Current learning rate: 0.00905 +2024-11-21 15:21:04.123080: train_loss -0.7638 +2024-11-21 15:21:04.129822: val_loss -0.7468 +2024-11-21 15:21:04.129986: Pseudo dice [0.8571] +2024-11-21 15:21:04.130097: Epoch time: 19.28 s +2024-11-21 15:21:04.933850: +2024-11-21 15:21:04.934088: Epoch 838 +2024-11-21 15:21:04.934251: Current learning rate: 0.00905 +2024-11-21 15:21:24.757419: train_loss -0.7625 +2024-11-21 15:21:24.762443: val_loss -0.7637 +2024-11-21 15:21:24.762553: Pseudo dice [0.8397] +2024-11-21 15:21:24.762641: Epoch time: 19.82 s +2024-11-21 15:21:25.716141: +2024-11-21 15:21:25.716374: Epoch 839 +2024-11-21 15:21:25.716503: Current learning rate: 0.00905 +2024-11-21 15:21:44.209072: train_loss -0.7695 +2024-11-21 15:21:44.212075: val_loss -0.768 +2024-11-21 15:21:44.212238: Pseudo dice [0.8455] +2024-11-21 15:21:44.212328: Epoch time: 18.49 s +2024-11-21 15:21:45.005414: +2024-11-21 15:21:45.005615: Epoch 840 +2024-11-21 15:21:45.005728: Current learning rate: 0.00905 +2024-11-21 15:22:04.661521: train_loss -0.7689 +2024-11-21 15:22:04.668490: val_loss -0.756 +2024-11-21 15:22:04.668637: Pseudo dice [0.8552] +2024-11-21 15:22:04.668728: Epoch time: 19.66 s +2024-11-21 15:22:05.469017: +2024-11-21 15:22:05.469218: Epoch 841 +2024-11-21 15:22:05.469358: Current learning rate: 0.00905 +2024-11-21 15:22:24.797470: train_loss -0.7663 +2024-11-21 15:22:24.800598: val_loss -0.7358 +2024-11-21 15:22:24.800740: Pseudo dice [0.8337] +2024-11-21 15:22:24.800835: Epoch time: 19.33 s +2024-11-21 15:22:25.749413: +2024-11-21 15:22:25.749585: Epoch 842 +2024-11-21 15:22:25.749722: Current learning rate: 0.00905 +2024-11-21 15:22:44.924881: train_loss -0.7716 +2024-11-21 15:22:44.927646: val_loss -0.7499 +2024-11-21 15:22:44.927750: Pseudo dice [0.837] +2024-11-21 15:22:44.927849: Epoch time: 19.18 s +2024-11-21 15:22:45.732129: +2024-11-21 15:22:45.732317: Epoch 843 +2024-11-21 15:22:45.732449: Current learning rate: 0.00905 +2024-11-21 15:23:05.269772: train_loss -0.7617 +2024-11-21 15:23:05.278193: val_loss -0.7587 +2024-11-21 15:23:05.278404: Pseudo dice [0.8346] +2024-11-21 15:23:05.278511: Epoch time: 19.54 s +2024-11-21 15:23:06.131581: +2024-11-21 15:23:06.131764: Epoch 844 +2024-11-21 15:23:06.131898: Current learning rate: 0.00905 +2024-11-21 15:23:24.847623: train_loss -0.7679 +2024-11-21 15:23:24.854238: val_loss -0.7627 +2024-11-21 15:23:24.854379: Pseudo dice [0.8472] +2024-11-21 15:23:24.854471: Epoch time: 18.72 s +2024-11-21 15:23:26.056940: +2024-11-21 15:23:26.057179: Epoch 845 +2024-11-21 15:23:26.057314: Current learning rate: 0.00904 +2024-11-21 15:23:44.840594: train_loss -0.7624 +2024-11-21 15:23:44.848092: val_loss -0.7534 +2024-11-21 15:23:44.848209: Pseudo dice [0.8495] +2024-11-21 15:23:44.848312: Epoch time: 18.78 s +2024-11-21 15:23:45.808920: +2024-11-21 15:23:45.809232: Epoch 846 +2024-11-21 15:23:45.809374: Current learning rate: 0.00904 +2024-11-21 15:24:05.445194: train_loss -0.7628 +2024-11-21 15:24:05.453619: val_loss -0.7633 +2024-11-21 15:24:05.453738: Pseudo dice [0.8478] +2024-11-21 15:24:05.453874: Epoch time: 19.64 s +2024-11-21 15:24:06.444198: +2024-11-21 15:24:06.444413: Epoch 847 +2024-11-21 15:24:06.444540: Current learning rate: 0.00904 +2024-11-21 15:24:25.729301: train_loss -0.7623 +2024-11-21 15:24:25.732637: val_loss -0.7948 +2024-11-21 15:24:25.732776: Pseudo dice [0.8568] +2024-11-21 15:24:25.732870: Epoch time: 19.29 s +2024-11-21 15:24:26.971744: +2024-11-21 15:24:26.971968: Epoch 848 +2024-11-21 15:24:26.972316: Current learning rate: 0.00904 +2024-11-21 15:24:45.019261: train_loss -0.7542 +2024-11-21 15:24:45.024217: val_loss -0.7265 +2024-11-21 15:24:45.024361: Pseudo dice [0.822] +2024-11-21 15:24:45.024477: Epoch time: 18.05 s +2024-11-21 15:24:45.940496: +2024-11-21 15:24:45.940708: Epoch 849 +2024-11-21 15:24:45.940824: Current learning rate: 0.00904 +2024-11-21 15:25:04.296247: train_loss -0.7612 +2024-11-21 15:25:04.304507: val_loss -0.7708 +2024-11-21 15:25:04.304633: Pseudo dice [0.8444] +2024-11-21 15:25:04.304791: Epoch time: 18.36 s +2024-11-21 15:25:05.428642: +2024-11-21 15:25:05.428841: Epoch 850 +2024-11-21 15:25:05.428978: Current learning rate: 0.00904 +2024-11-21 15:25:24.466937: train_loss -0.7569 +2024-11-21 15:25:24.471647: val_loss -0.7816 +2024-11-21 15:25:24.471797: Pseudo dice [0.8458] +2024-11-21 15:25:24.471906: Epoch time: 19.04 s +2024-11-21 15:25:25.271738: +2024-11-21 15:25:25.271931: Epoch 851 +2024-11-21 15:25:25.272052: Current learning rate: 0.00904 +2024-11-21 15:25:44.561066: train_loss -0.7534 +2024-11-21 15:25:44.570729: val_loss -0.75 +2024-11-21 15:25:44.570851: Pseudo dice [0.8445] +2024-11-21 15:25:44.570939: Epoch time: 19.29 s +2024-11-21 15:25:45.570526: +2024-11-21 15:25:45.570717: Epoch 852 +2024-11-21 15:25:45.570863: Current learning rate: 0.00904 +2024-11-21 15:26:04.566071: train_loss -0.7642 +2024-11-21 15:26:04.568980: val_loss -0.7543 +2024-11-21 15:26:04.569120: Pseudo dice [0.8441] +2024-11-21 15:26:04.569213: Epoch time: 19.0 s +2024-11-21 15:26:05.567926: +2024-11-21 15:26:05.568124: Epoch 853 +2024-11-21 15:26:05.568240: Current learning rate: 0.00904 +2024-11-21 15:26:24.483644: train_loss -0.7564 +2024-11-21 15:26:24.489680: val_loss -0.7372 +2024-11-21 15:26:24.489814: Pseudo dice [0.8389] +2024-11-21 15:26:24.489924: Epoch time: 18.92 s +2024-11-21 15:26:25.424191: +2024-11-21 15:26:25.424372: Epoch 854 +2024-11-21 15:26:25.424491: Current learning rate: 0.00903 +2024-11-21 15:26:45.141774: train_loss -0.7455 +2024-11-21 15:26:45.148109: val_loss -0.7483 +2024-11-21 15:26:45.148240: Pseudo dice [0.8465] +2024-11-21 15:26:45.148325: Epoch time: 19.72 s +2024-11-21 15:26:45.984017: +2024-11-21 15:26:45.984193: Epoch 855 +2024-11-21 15:26:45.984306: Current learning rate: 0.00903 +2024-11-21 15:27:05.101381: train_loss -0.7636 +2024-11-21 15:27:05.105950: val_loss -0.7342 +2024-11-21 15:27:05.106070: Pseudo dice [0.8421] +2024-11-21 15:27:05.106172: Epoch time: 19.12 s +2024-11-21 15:27:05.902632: +2024-11-21 15:27:05.902803: Epoch 856 +2024-11-21 15:27:05.902913: Current learning rate: 0.00903 +2024-11-21 15:27:25.805609: train_loss -0.76 +2024-11-21 15:27:25.811554: val_loss -0.7645 +2024-11-21 15:27:25.811756: Pseudo dice [0.8456] +2024-11-21 15:27:25.811855: Epoch time: 19.9 s +2024-11-21 15:27:26.623988: +2024-11-21 15:27:26.624206: Epoch 857 +2024-11-21 15:27:26.624331: Current learning rate: 0.00903 +2024-11-21 15:27:45.160099: train_loss -0.768 +2024-11-21 15:27:45.166956: val_loss -0.7501 +2024-11-21 15:27:45.167146: Pseudo dice [0.8342] +2024-11-21 15:27:45.167245: Epoch time: 18.54 s +2024-11-21 15:27:46.009770: +2024-11-21 15:27:46.009975: Epoch 858 +2024-11-21 15:27:46.010101: Current learning rate: 0.00903 +2024-11-21 15:28:05.014050: train_loss -0.7663 +2024-11-21 15:28:05.018009: val_loss -0.7688 +2024-11-21 15:28:05.018127: Pseudo dice [0.8557] +2024-11-21 15:28:05.018254: Epoch time: 19.01 s +2024-11-21 15:28:05.821477: +2024-11-21 15:28:05.821775: Epoch 859 +2024-11-21 15:28:05.821898: Current learning rate: 0.00903 +2024-11-21 15:28:24.197325: train_loss -0.7614 +2024-11-21 15:28:24.212847: val_loss -0.7412 +2024-11-21 15:28:24.212986: Pseudo dice [0.8451] +2024-11-21 15:28:24.213103: Epoch time: 18.38 s +2024-11-21 15:28:25.042936: +2024-11-21 15:28:25.043132: Epoch 860 +2024-11-21 15:28:25.043247: Current learning rate: 0.00903 +2024-11-21 15:28:43.979335: train_loss -0.7682 +2024-11-21 15:28:43.982796: val_loss -0.7665 +2024-11-21 15:28:43.982952: Pseudo dice [0.845] +2024-11-21 15:28:43.983075: Epoch time: 18.94 s +2024-11-21 15:28:44.783920: +2024-11-21 15:28:44.784146: Epoch 861 +2024-11-21 15:28:44.784279: Current learning rate: 0.00903 +2024-11-21 15:29:04.895028: train_loss -0.7614 +2024-11-21 15:29:04.907357: val_loss -0.7631 +2024-11-21 15:29:04.907492: Pseudo dice [0.8434] +2024-11-21 15:29:04.907653: Epoch time: 20.11 s +2024-11-21 15:29:05.758102: +2024-11-21 15:29:05.758306: Epoch 862 +2024-11-21 15:29:05.758442: Current learning rate: 0.00902 +2024-11-21 15:29:24.268129: train_loss -0.7602 +2024-11-21 15:29:24.274702: val_loss -0.7854 +2024-11-21 15:29:24.274926: Pseudo dice [0.8452] +2024-11-21 15:29:24.275019: Epoch time: 18.51 s +2024-11-21 15:29:25.077787: +2024-11-21 15:29:25.077985: Epoch 863 +2024-11-21 15:29:25.078113: Current learning rate: 0.00902 +2024-11-21 15:29:44.166249: train_loss -0.7622 +2024-11-21 15:29:44.170204: val_loss -0.7942 +2024-11-21 15:29:44.170357: Pseudo dice [0.8477] +2024-11-21 15:29:44.170454: Epoch time: 19.09 s +2024-11-21 15:29:45.002516: +2024-11-21 15:29:45.002724: Epoch 864 +2024-11-21 15:29:45.002833: Current learning rate: 0.00902 +2024-11-21 15:30:05.263130: train_loss -0.7565 +2024-11-21 15:30:05.270467: val_loss -0.7578 +2024-11-21 15:30:05.270611: Pseudo dice [0.8319] +2024-11-21 15:30:05.270725: Epoch time: 20.26 s +2024-11-21 15:30:06.091204: +2024-11-21 15:30:06.091401: Epoch 865 +2024-11-21 15:30:06.091519: Current learning rate: 0.00902 +2024-11-21 15:30:24.712825: train_loss -0.7611 +2024-11-21 15:30:24.722595: val_loss -0.7582 +2024-11-21 15:30:24.722735: Pseudo dice [0.8265] +2024-11-21 15:30:24.722823: Epoch time: 18.62 s +2024-11-21 15:30:25.590202: +2024-11-21 15:30:25.590398: Epoch 866 +2024-11-21 15:30:25.590573: Current learning rate: 0.00902 +2024-11-21 15:30:44.273233: train_loss -0.7609 +2024-11-21 15:30:44.279607: val_loss -0.757 +2024-11-21 15:30:44.279747: Pseudo dice [0.8279] +2024-11-21 15:30:44.279861: Epoch time: 18.68 s +2024-11-21 15:30:45.199376: +2024-11-21 15:30:45.199554: Epoch 867 +2024-11-21 15:30:45.199722: Current learning rate: 0.00902 +2024-11-21 15:31:04.828089: train_loss -0.7597 +2024-11-21 15:31:04.832365: val_loss -0.7645 +2024-11-21 15:31:04.832508: Pseudo dice [0.8505] +2024-11-21 15:31:04.832667: Epoch time: 19.63 s +2024-11-21 15:31:06.019472: +2024-11-21 15:31:06.019698: Epoch 868 +2024-11-21 15:31:06.019841: Current learning rate: 0.00902 +2024-11-21 15:31:25.534002: train_loss -0.7595 +2024-11-21 15:31:25.542565: val_loss -0.7672 +2024-11-21 15:31:25.542763: Pseudo dice [0.842] +2024-11-21 15:31:25.542854: Epoch time: 19.52 s +2024-11-21 15:31:26.458413: +2024-11-21 15:31:26.458620: Epoch 869 +2024-11-21 15:31:26.458753: Current learning rate: 0.00902 +2024-11-21 15:31:45.172478: train_loss -0.7628 +2024-11-21 15:31:45.175159: val_loss -0.7703 +2024-11-21 15:31:45.175260: Pseudo dice [0.847] +2024-11-21 15:31:45.175349: Epoch time: 18.71 s +2024-11-21 15:31:45.973657: +2024-11-21 15:31:45.973863: Epoch 870 +2024-11-21 15:31:45.974005: Current learning rate: 0.00902 +2024-11-21 15:32:05.039562: train_loss -0.7591 +2024-11-21 15:32:05.048224: val_loss -0.7665 +2024-11-21 15:32:05.048368: Pseudo dice [0.8424] +2024-11-21 15:32:05.048457: Epoch time: 19.07 s +2024-11-21 15:32:05.980032: +2024-11-21 15:32:05.980278: Epoch 871 +2024-11-21 15:32:05.980397: Current learning rate: 0.00901 +2024-11-21 15:32:24.903937: train_loss -0.7642 +2024-11-21 15:32:24.917099: val_loss -0.7534 +2024-11-21 15:32:24.917232: Pseudo dice [0.8322] +2024-11-21 15:32:24.917332: Epoch time: 18.92 s +2024-11-21 15:32:25.773588: +2024-11-21 15:32:25.773775: Epoch 872 +2024-11-21 15:32:25.773894: Current learning rate: 0.00901 +2024-11-21 15:32:44.858957: train_loss -0.7627 +2024-11-21 15:32:44.864590: val_loss -0.7787 +2024-11-21 15:32:44.864727: Pseudo dice [0.847] +2024-11-21 15:32:44.864812: Epoch time: 19.09 s +2024-11-21 15:32:45.661994: +2024-11-21 15:32:45.662205: Epoch 873 +2024-11-21 15:32:45.662332: Current learning rate: 0.00901 +2024-11-21 15:33:05.022722: train_loss -0.7497 +2024-11-21 15:33:05.025500: val_loss -0.7387 +2024-11-21 15:33:05.041539: Pseudo dice [0.8479] +2024-11-21 15:33:05.041744: Epoch time: 19.36 s +2024-11-21 15:33:05.841509: +2024-11-21 15:33:05.841722: Epoch 874 +2024-11-21 15:33:05.841845: Current learning rate: 0.00901 +2024-11-21 15:33:24.849087: train_loss -0.767 +2024-11-21 15:33:24.852567: val_loss -0.7493 +2024-11-21 15:33:24.852664: Pseudo dice [0.8497] +2024-11-21 15:33:24.852751: Epoch time: 19.01 s +2024-11-21 15:33:25.655416: +2024-11-21 15:33:25.655590: Epoch 875 +2024-11-21 15:33:25.655708: Current learning rate: 0.00901 +2024-11-21 15:33:46.468229: train_loss -0.7602 +2024-11-21 15:33:46.474828: val_loss -0.744 +2024-11-21 15:33:46.474972: Pseudo dice [0.8328] +2024-11-21 15:33:46.475100: Epoch time: 20.81 s +2024-11-21 15:33:47.360506: +2024-11-21 15:33:47.360728: Epoch 876 +2024-11-21 15:33:47.360846: Current learning rate: 0.00901 +2024-11-21 15:34:06.874592: train_loss -0.7629 +2024-11-21 15:34:06.882398: val_loss -0.7613 +2024-11-21 15:34:06.882551: Pseudo dice [0.8659] +2024-11-21 15:34:06.882642: Epoch time: 19.51 s +2024-11-21 15:34:07.701446: +2024-11-21 15:34:07.701652: Epoch 877 +2024-11-21 15:34:07.701786: Current learning rate: 0.00901 +2024-11-21 15:34:27.641442: train_loss -0.7635 +2024-11-21 15:34:27.644134: val_loss -0.7458 +2024-11-21 15:34:27.644280: Pseudo dice [0.8397] +2024-11-21 15:34:27.644362: Epoch time: 19.94 s +2024-11-21 15:34:28.449378: +2024-11-21 15:34:28.449587: Epoch 878 +2024-11-21 15:34:28.449714: Current learning rate: 0.00901 +2024-11-21 15:34:47.668162: train_loss -0.7628 +2024-11-21 15:34:47.671630: val_loss -0.7624 +2024-11-21 15:34:47.671733: Pseudo dice [0.8569] +2024-11-21 15:34:47.671839: Epoch time: 19.22 s +2024-11-21 15:34:48.473256: +2024-11-21 15:34:48.473525: Epoch 879 +2024-11-21 15:34:48.473656: Current learning rate: 0.00901 +2024-11-21 15:35:07.115535: train_loss -0.7578 +2024-11-21 15:35:07.118939: val_loss -0.7537 +2024-11-21 15:35:07.119070: Pseudo dice [0.8444] +2024-11-21 15:35:07.119175: Epoch time: 18.64 s +2024-11-21 15:35:07.916034: +2024-11-21 15:35:07.916244: Epoch 880 +2024-11-21 15:35:07.916386: Current learning rate: 0.009 +2024-11-21 15:35:26.704404: train_loss -0.7488 +2024-11-21 15:35:26.706990: val_loss -0.762 +2024-11-21 15:35:26.707106: Pseudo dice [0.8544] +2024-11-21 15:35:26.707206: Epoch time: 18.79 s +2024-11-21 15:35:27.507593: +2024-11-21 15:35:27.507787: Epoch 881 +2024-11-21 15:35:27.507921: Current learning rate: 0.009 +2024-11-21 15:35:46.063163: train_loss -0.7428 +2024-11-21 15:35:46.066036: val_loss -0.7412 +2024-11-21 15:35:46.066160: Pseudo dice [0.8279] +2024-11-21 15:35:46.066247: Epoch time: 18.56 s +2024-11-21 15:35:46.954935: +2024-11-21 15:35:46.955141: Epoch 882 +2024-11-21 15:35:46.955266: Current learning rate: 0.009 +2024-11-21 15:36:06.014141: train_loss -0.7623 +2024-11-21 15:36:06.018710: val_loss -0.731 +2024-11-21 15:36:06.018847: Pseudo dice [0.8425] +2024-11-21 15:36:06.018944: Epoch time: 19.06 s +2024-11-21 15:36:06.896348: +2024-11-21 15:36:06.896565: Epoch 883 +2024-11-21 15:36:06.896687: Current learning rate: 0.009 +2024-11-21 15:36:25.140033: train_loss -0.762 +2024-11-21 15:36:25.142681: val_loss -0.7479 +2024-11-21 15:36:25.142793: Pseudo dice [0.8512] +2024-11-21 15:36:25.142886: Epoch time: 18.24 s +2024-11-21 15:36:26.055326: +2024-11-21 15:36:26.055523: Epoch 884 +2024-11-21 15:36:26.055646: Current learning rate: 0.009 +2024-11-21 15:36:44.613701: train_loss -0.7686 +2024-11-21 15:36:44.618932: val_loss -0.7479 +2024-11-21 15:36:44.619069: Pseudo dice [0.8365] +2024-11-21 15:36:44.619160: Epoch time: 18.56 s +2024-11-21 15:36:45.422129: +2024-11-21 15:36:45.422339: Epoch 885 +2024-11-21 15:36:45.422451: Current learning rate: 0.009 +2024-11-21 15:37:04.458683: train_loss -0.7594 +2024-11-21 15:37:04.467240: val_loss -0.7395 +2024-11-21 15:37:04.467459: Pseudo dice [0.8535] +2024-11-21 15:37:04.467577: Epoch time: 19.04 s +2024-11-21 15:37:05.274758: +2024-11-21 15:37:05.274957: Epoch 886 +2024-11-21 15:37:05.275092: Current learning rate: 0.009 +2024-11-21 15:37:22.731852: train_loss -0.7627 +2024-11-21 15:37:22.738694: val_loss -0.7677 +2024-11-21 15:37:22.738819: Pseudo dice [0.858] +2024-11-21 15:37:22.738916: Epoch time: 17.46 s +2024-11-21 15:37:23.587231: +2024-11-21 15:37:23.587430: Epoch 887 +2024-11-21 15:37:23.587563: Current learning rate: 0.009 +2024-11-21 15:37:42.605022: train_loss -0.7683 +2024-11-21 15:37:42.618635: val_loss -0.7482 +2024-11-21 15:37:42.618797: Pseudo dice [0.8217] +2024-11-21 15:37:42.618909: Epoch time: 19.02 s +2024-11-21 15:37:43.418589: +2024-11-21 15:37:43.418779: Epoch 888 +2024-11-21 15:37:43.418922: Current learning rate: 0.009 +2024-11-21 15:38:01.175377: train_loss -0.7614 +2024-11-21 15:38:01.183141: val_loss -0.7733 +2024-11-21 15:38:01.183292: Pseudo dice [0.8529] +2024-11-21 15:38:01.183414: Epoch time: 17.75 s +2024-11-21 15:38:02.064807: +2024-11-21 15:38:02.064997: Epoch 889 +2024-11-21 15:38:02.065114: Current learning rate: 0.00899 +2024-11-21 15:38:20.323869: train_loss -0.7712 +2024-11-21 15:38:20.327320: val_loss -0.7567 +2024-11-21 15:38:20.327427: Pseudo dice [0.8406] +2024-11-21 15:38:20.327532: Epoch time: 18.26 s +2024-11-21 15:38:21.121702: +2024-11-21 15:38:21.121888: Epoch 890 +2024-11-21 15:38:21.122021: Current learning rate: 0.00899 +2024-11-21 15:38:40.415764: train_loss -0.7441 +2024-11-21 15:38:40.423589: val_loss -0.7483 +2024-11-21 15:38:40.423730: Pseudo dice [0.8393] +2024-11-21 15:38:40.423824: Epoch time: 19.29 s +2024-11-21 15:38:41.635823: +2024-11-21 15:38:41.636026: Epoch 891 +2024-11-21 15:38:41.636158: Current learning rate: 0.00899 +2024-11-21 15:39:02.409401: train_loss -0.7587 +2024-11-21 15:39:02.417092: val_loss -0.7834 +2024-11-21 15:39:02.417273: Pseudo dice [0.8455] +2024-11-21 15:39:02.417374: Epoch time: 20.77 s +2024-11-21 15:39:03.214877: +2024-11-21 15:39:03.215083: Epoch 892 +2024-11-21 15:39:03.215203: Current learning rate: 0.00899 +2024-11-21 15:39:22.197882: train_loss -0.7678 +2024-11-21 15:39:22.207508: val_loss -0.7358 +2024-11-21 15:39:22.207630: Pseudo dice [0.8379] +2024-11-21 15:39:22.207718: Epoch time: 18.98 s +2024-11-21 15:39:23.020824: +2024-11-21 15:39:23.021072: Epoch 893 +2024-11-21 15:39:23.021202: Current learning rate: 0.00899 +2024-11-21 15:39:42.477224: train_loss -0.7542 +2024-11-21 15:39:42.480080: val_loss -0.7704 +2024-11-21 15:39:42.480217: Pseudo dice [0.8499] +2024-11-21 15:39:42.480301: Epoch time: 19.46 s +2024-11-21 15:39:43.422331: +2024-11-21 15:39:43.422536: Epoch 894 +2024-11-21 15:39:43.422655: Current learning rate: 0.00899 +2024-11-21 15:40:02.960759: train_loss -0.7783 +2024-11-21 15:40:02.966762: val_loss -0.7599 +2024-11-21 15:40:02.966894: Pseudo dice [0.8424] +2024-11-21 15:40:02.966979: Epoch time: 19.54 s +2024-11-21 15:40:03.874236: +2024-11-21 15:40:03.874440: Epoch 895 +2024-11-21 15:40:03.874568: Current learning rate: 0.00899 +2024-11-21 15:40:22.465365: train_loss -0.7619 +2024-11-21 15:40:22.478688: val_loss -0.7778 +2024-11-21 15:40:22.478819: Pseudo dice [0.8502] +2024-11-21 15:40:22.478919: Epoch time: 18.59 s +2024-11-21 15:40:23.325310: +2024-11-21 15:40:23.325536: Epoch 896 +2024-11-21 15:40:23.325653: Current learning rate: 0.00899 +2024-11-21 15:40:42.648772: train_loss -0.7634 +2024-11-21 15:40:42.651715: val_loss -0.7644 +2024-11-21 15:40:42.651855: Pseudo dice [0.8197] +2024-11-21 15:40:42.651949: Epoch time: 19.32 s +2024-11-21 15:40:43.449164: +2024-11-21 15:40:43.449342: Epoch 897 +2024-11-21 15:40:43.449466: Current learning rate: 0.00898 +2024-11-21 15:41:02.657298: train_loss -0.7614 +2024-11-21 15:41:02.660393: val_loss -0.7652 +2024-11-21 15:41:02.660491: Pseudo dice [0.8414] +2024-11-21 15:41:02.660572: Epoch time: 19.21 s +2024-11-21 15:41:03.458166: +2024-11-21 15:41:03.458372: Epoch 898 +2024-11-21 15:41:03.458498: Current learning rate: 0.00898 +2024-11-21 15:41:22.106428: train_loss -0.7719 +2024-11-21 15:41:22.113753: val_loss -0.7507 +2024-11-21 15:41:22.113871: Pseudo dice [0.8259] +2024-11-21 15:41:22.113951: Epoch time: 18.65 s +2024-11-21 15:41:23.009412: +2024-11-21 15:41:23.009611: Epoch 899 +2024-11-21 15:41:23.010009: Current learning rate: 0.00898 +2024-11-21 15:41:42.045715: train_loss -0.7594 +2024-11-21 15:41:42.052074: val_loss -0.7606 +2024-11-21 15:41:42.052212: Pseudo dice [0.8493] +2024-11-21 15:41:42.052318: Epoch time: 19.04 s +2024-11-21 15:41:43.085701: +2024-11-21 15:41:43.085912: Epoch 900 +2024-11-21 15:41:43.086030: Current learning rate: 0.00898 +2024-11-21 15:42:01.659920: train_loss -0.765 +2024-11-21 15:42:01.666432: val_loss -0.7673 +2024-11-21 15:42:01.666569: Pseudo dice [0.8412] +2024-11-21 15:42:01.666658: Epoch time: 18.58 s +2024-11-21 15:42:02.536384: +2024-11-21 15:42:02.536606: Epoch 901 +2024-11-21 15:42:02.536747: Current learning rate: 0.00898 +2024-11-21 15:42:20.809366: train_loss -0.7535 +2024-11-21 15:42:20.812920: val_loss -0.7442 +2024-11-21 15:42:20.813024: Pseudo dice [0.841] +2024-11-21 15:42:20.813122: Epoch time: 18.27 s +2024-11-21 15:42:21.643564: +2024-11-21 15:42:21.643765: Epoch 902 +2024-11-21 15:42:21.643908: Current learning rate: 0.00898 +2024-11-21 15:42:41.602495: train_loss -0.7718 +2024-11-21 15:42:41.618701: val_loss -0.7493 +2024-11-21 15:42:41.618872: Pseudo dice [0.8411] +2024-11-21 15:42:41.618991: Epoch time: 19.96 s +2024-11-21 15:42:42.573034: +2024-11-21 15:42:42.573282: Epoch 903 +2024-11-21 15:42:42.573410: Current learning rate: 0.00898 +2024-11-21 15:43:01.289789: train_loss -0.7512 +2024-11-21 15:43:01.292654: val_loss -0.7567 +2024-11-21 15:43:01.292747: Pseudo dice [0.8504] +2024-11-21 15:43:01.292829: Epoch time: 18.72 s +2024-11-21 15:43:02.084426: +2024-11-21 15:43:02.084615: Epoch 904 +2024-11-21 15:43:02.084737: Current learning rate: 0.00898 +2024-11-21 15:43:20.873613: train_loss -0.7589 +2024-11-21 15:43:20.878494: val_loss -0.7358 +2024-11-21 15:43:20.878647: Pseudo dice [0.8506] +2024-11-21 15:43:20.878751: Epoch time: 18.79 s +2024-11-21 15:43:21.748404: +2024-11-21 15:43:21.748607: Epoch 905 +2024-11-21 15:43:21.748737: Current learning rate: 0.00898 +2024-11-21 15:43:41.019675: train_loss -0.7323 +2024-11-21 15:43:41.022468: val_loss -0.7533 +2024-11-21 15:43:41.022590: Pseudo dice [0.8352] +2024-11-21 15:43:41.022686: Epoch time: 19.27 s +2024-11-21 15:43:41.974667: +2024-11-21 15:43:41.974866: Epoch 906 +2024-11-21 15:43:41.975008: Current learning rate: 0.00897 +2024-11-21 15:44:01.126219: train_loss -0.759 +2024-11-21 15:44:01.134834: val_loss -0.754 +2024-11-21 15:44:01.134977: Pseudo dice [0.8471] +2024-11-21 15:44:01.135100: Epoch time: 19.15 s +2024-11-21 15:44:02.053413: +2024-11-21 15:44:02.053598: Epoch 907 +2024-11-21 15:44:02.053719: Current learning rate: 0.00897 +2024-11-21 15:44:22.306815: train_loss -0.7565 +2024-11-21 15:44:22.318129: val_loss -0.7467 +2024-11-21 15:44:22.320328: Pseudo dice [0.8237] +2024-11-21 15:44:22.320435: Epoch time: 20.25 s +2024-11-21 15:44:23.121273: +2024-11-21 15:44:23.121471: Epoch 908 +2024-11-21 15:44:23.121616: Current learning rate: 0.00897 +2024-11-21 15:44:40.957925: train_loss -0.7576 +2024-11-21 15:44:40.967209: val_loss -0.7548 +2024-11-21 15:44:40.967346: Pseudo dice [0.8471] +2024-11-21 15:44:40.967448: Epoch time: 17.84 s +2024-11-21 15:44:41.779960: +2024-11-21 15:44:41.780158: Epoch 909 +2024-11-21 15:44:41.780298: Current learning rate: 0.00897 +2024-11-21 15:45:01.724516: train_loss -0.7675 +2024-11-21 15:45:01.738455: val_loss -0.7608 +2024-11-21 15:45:01.738587: Pseudo dice [0.8413] +2024-11-21 15:45:01.738680: Epoch time: 19.95 s +2024-11-21 15:45:02.542019: +2024-11-21 15:45:02.542220: Epoch 910 +2024-11-21 15:45:02.542350: Current learning rate: 0.00897 +2024-11-21 15:45:22.371783: train_loss -0.7523 +2024-11-21 15:45:22.389200: val_loss -0.7811 +2024-11-21 15:45:22.389392: Pseudo dice [0.8547] +2024-11-21 15:45:22.389516: Epoch time: 19.83 s +2024-11-21 15:45:23.209118: +2024-11-21 15:45:23.209329: Epoch 911 +2024-11-21 15:45:23.209441: Current learning rate: 0.00897 +2024-11-21 15:45:41.723143: train_loss -0.7785 +2024-11-21 15:45:41.732123: val_loss -0.7415 +2024-11-21 15:45:41.732281: Pseudo dice [0.8515] +2024-11-21 15:45:41.732369: Epoch time: 18.51 s +2024-11-21 15:45:42.557301: +2024-11-21 15:45:42.557496: Epoch 912 +2024-11-21 15:45:42.557606: Current learning rate: 0.00897 +2024-11-21 15:46:01.200126: train_loss -0.7702 +2024-11-21 15:46:01.209644: val_loss -0.7776 +2024-11-21 15:46:01.209783: Pseudo dice [0.8637] +2024-11-21 15:46:01.209886: Epoch time: 18.64 s +2024-11-21 15:46:02.263668: +2024-11-21 15:46:02.263868: Epoch 913 +2024-11-21 15:46:02.264005: Current learning rate: 0.00897 +2024-11-21 15:46:21.813600: train_loss -0.7655 +2024-11-21 15:46:21.823361: val_loss -0.774 +2024-11-21 15:46:21.823543: Pseudo dice [0.8442] +2024-11-21 15:46:21.823638: Epoch time: 19.55 s +2024-11-21 15:46:23.042294: +2024-11-21 15:46:23.042499: Epoch 914 +2024-11-21 15:46:23.042628: Current learning rate: 0.00897 +2024-11-21 15:46:41.726472: train_loss -0.7466 +2024-11-21 15:46:41.729027: val_loss -0.7355 +2024-11-21 15:46:41.729133: Pseudo dice [0.8259] +2024-11-21 15:46:41.729235: Epoch time: 18.69 s +2024-11-21 15:46:42.533699: +2024-11-21 15:46:42.533896: Epoch 915 +2024-11-21 15:46:42.534019: Current learning rate: 0.00896 +2024-11-21 15:47:01.757684: train_loss -0.7545 +2024-11-21 15:47:01.772136: val_loss -0.7617 +2024-11-21 15:47:01.772262: Pseudo dice [0.8511] +2024-11-21 15:47:01.772352: Epoch time: 19.22 s +2024-11-21 15:47:02.633004: +2024-11-21 15:47:02.633236: Epoch 916 +2024-11-21 15:47:02.633374: Current learning rate: 0.00896 +2024-11-21 15:47:20.809821: train_loss -0.7602 +2024-11-21 15:47:20.813251: val_loss -0.7307 +2024-11-21 15:47:20.813384: Pseudo dice [0.8303] +2024-11-21 15:47:20.813474: Epoch time: 18.18 s +2024-11-21 15:47:21.625254: +2024-11-21 15:47:21.625447: Epoch 917 +2024-11-21 15:47:21.625567: Current learning rate: 0.00896 +2024-11-21 15:47:40.089476: train_loss -0.7647 +2024-11-21 15:47:40.096041: val_loss -0.7675 +2024-11-21 15:47:40.096184: Pseudo dice [0.8484] +2024-11-21 15:47:40.096303: Epoch time: 18.47 s +2024-11-21 15:47:40.897103: +2024-11-21 15:47:40.897330: Epoch 918 +2024-11-21 15:47:40.897456: Current learning rate: 0.00896 +2024-11-21 15:47:59.623932: train_loss -0.7613 +2024-11-21 15:47:59.632293: val_loss -0.7657 +2024-11-21 15:47:59.632433: Pseudo dice [0.8551] +2024-11-21 15:47:59.632532: Epoch time: 18.73 s +2024-11-21 15:48:00.473202: +2024-11-21 15:48:00.473399: Epoch 919 +2024-11-21 15:48:00.473530: Current learning rate: 0.00896 +2024-11-21 15:48:19.049129: train_loss -0.7666 +2024-11-21 15:48:19.052454: val_loss -0.7576 +2024-11-21 15:48:19.052562: Pseudo dice [0.8571] +2024-11-21 15:48:19.052655: Epoch time: 18.58 s +2024-11-21 15:48:19.854265: +2024-11-21 15:48:19.854463: Epoch 920 +2024-11-21 15:48:19.854602: Current learning rate: 0.00896 +2024-11-21 15:48:39.620438: train_loss -0.7649 +2024-11-21 15:48:39.630605: val_loss -0.7562 +2024-11-21 15:48:39.630736: Pseudo dice [0.8547] +2024-11-21 15:48:39.630846: Epoch time: 19.77 s +2024-11-21 15:48:40.430460: +2024-11-21 15:48:40.430674: Epoch 921 +2024-11-21 15:48:40.430797: Current learning rate: 0.00896 +2024-11-21 15:48:58.890952: train_loss -0.7633 +2024-11-21 15:48:58.899338: val_loss -0.751 +2024-11-21 15:48:58.899478: Pseudo dice [0.8523] +2024-11-21 15:48:58.899644: Epoch time: 18.46 s +2024-11-21 15:48:59.775795: +2024-11-21 15:48:59.775990: Epoch 922 +2024-11-21 15:48:59.776110: Current learning rate: 0.00896 +2024-11-21 15:49:19.303200: train_loss -0.7613 +2024-11-21 15:49:19.310463: val_loss -0.7483 +2024-11-21 15:49:19.310671: Pseudo dice [0.8464] +2024-11-21 15:49:19.310781: Epoch time: 19.53 s +2024-11-21 15:49:20.191212: +2024-11-21 15:49:20.191404: Epoch 923 +2024-11-21 15:49:20.191519: Current learning rate: 0.00896 +2024-11-21 15:49:39.222067: train_loss -0.7596 +2024-11-21 15:49:39.235269: val_loss -0.7788 +2024-11-21 15:49:39.235424: Pseudo dice [0.8552] +2024-11-21 15:49:39.235524: Epoch time: 19.03 s +2024-11-21 15:49:40.144433: +2024-11-21 15:49:40.144624: Epoch 924 +2024-11-21 15:49:40.144735: Current learning rate: 0.00895 +2024-11-21 15:49:59.449033: train_loss -0.754 +2024-11-21 15:49:59.458296: val_loss -0.7276 +2024-11-21 15:49:59.458663: Pseudo dice [0.8308] +2024-11-21 15:49:59.458763: Epoch time: 19.31 s +2024-11-21 15:50:00.259466: +2024-11-21 15:50:00.259663: Epoch 925 +2024-11-21 15:50:00.259786: Current learning rate: 0.00895 +2024-11-21 15:50:18.756944: train_loss -0.7574 +2024-11-21 15:50:18.776938: val_loss -0.7383 +2024-11-21 15:50:18.777124: Pseudo dice [0.8395] +2024-11-21 15:50:18.777235: Epoch time: 18.5 s +2024-11-21 15:50:19.586906: +2024-11-21 15:50:19.587122: Epoch 926 +2024-11-21 15:50:19.587261: Current learning rate: 0.00895 +2024-11-21 15:50:38.852417: train_loss -0.7537 +2024-11-21 15:50:38.863039: val_loss -0.7704 +2024-11-21 15:50:38.863183: Pseudo dice [0.8451] +2024-11-21 15:50:38.863286: Epoch time: 19.27 s +2024-11-21 15:50:39.835204: +2024-11-21 15:50:39.835430: Epoch 927 +2024-11-21 15:50:39.835567: Current learning rate: 0.00895 +2024-11-21 15:50:59.037261: train_loss -0.7689 +2024-11-21 15:50:59.074258: val_loss -0.7752 +2024-11-21 15:50:59.074424: Pseudo dice [0.8531] +2024-11-21 15:50:59.074518: Epoch time: 19.2 s +2024-11-21 15:50:59.949218: +2024-11-21 15:50:59.949426: Epoch 928 +2024-11-21 15:50:59.949540: Current learning rate: 0.00895 +2024-11-21 15:51:20.453265: train_loss -0.7631 +2024-11-21 15:51:20.465852: val_loss -0.7675 +2024-11-21 15:51:20.465984: Pseudo dice [0.8472] +2024-11-21 15:51:20.466092: Epoch time: 20.5 s +2024-11-21 15:51:21.271951: +2024-11-21 15:51:21.272148: Epoch 929 +2024-11-21 15:51:21.272269: Current learning rate: 0.00895 +2024-11-21 15:51:40.293873: train_loss -0.7608 +2024-11-21 15:51:40.310132: val_loss -0.7645 +2024-11-21 15:51:40.310306: Pseudo dice [0.8395] +2024-11-21 15:51:40.310417: Epoch time: 19.02 s +2024-11-21 15:51:41.196294: +2024-11-21 15:51:41.196514: Epoch 930 +2024-11-21 15:51:41.196648: Current learning rate: 0.00895 +2024-11-21 15:52:00.587030: train_loss -0.7641 +2024-11-21 15:52:00.590446: val_loss -0.7691 +2024-11-21 15:52:00.590549: Pseudo dice [0.8396] +2024-11-21 15:52:00.590666: Epoch time: 19.39 s +2024-11-21 15:52:01.389011: +2024-11-21 15:52:01.389219: Epoch 931 +2024-11-21 15:52:01.389340: Current learning rate: 0.00895 +2024-11-21 15:52:20.963657: train_loss -0.7599 +2024-11-21 15:52:20.971235: val_loss -0.7703 +2024-11-21 15:52:20.971370: Pseudo dice [0.8506] +2024-11-21 15:52:20.971452: Epoch time: 19.58 s +2024-11-21 15:52:21.902122: +2024-11-21 15:52:21.902328: Epoch 932 +2024-11-21 15:52:21.902445: Current learning rate: 0.00895 +2024-11-21 15:52:41.991939: train_loss -0.7502 +2024-11-21 15:52:41.995368: val_loss -0.7595 +2024-11-21 15:52:41.995506: Pseudo dice [0.8437] +2024-11-21 15:52:41.995599: Epoch time: 20.09 s +2024-11-21 15:52:42.795357: +2024-11-21 15:52:42.795575: Epoch 933 +2024-11-21 15:52:42.795703: Current learning rate: 0.00894 +2024-11-21 15:53:01.373799: train_loss -0.7597 +2024-11-21 15:53:01.389979: val_loss -0.7475 +2024-11-21 15:53:01.390124: Pseudo dice [0.8406] +2024-11-21 15:53:01.390216: Epoch time: 18.58 s +2024-11-21 15:53:02.264432: +2024-11-21 15:53:02.264637: Epoch 934 +2024-11-21 15:53:02.264765: Current learning rate: 0.00894 +2024-11-21 15:53:20.633821: train_loss -0.7695 +2024-11-21 15:53:20.645352: val_loss -0.7399 +2024-11-21 15:53:20.645496: Pseudo dice [0.8468] +2024-11-21 15:53:20.645600: Epoch time: 18.37 s +2024-11-21 15:53:21.554491: +2024-11-21 15:53:21.554683: Epoch 935 +2024-11-21 15:53:21.554801: Current learning rate: 0.00894 +2024-11-21 15:53:39.362927: train_loss -0.7603 +2024-11-21 15:53:39.384988: val_loss -0.7517 +2024-11-21 15:53:39.385154: Pseudo dice [0.8319] +2024-11-21 15:53:39.385256: Epoch time: 17.81 s +2024-11-21 15:53:40.227871: +2024-11-21 15:53:40.228064: Epoch 936 +2024-11-21 15:53:40.228180: Current learning rate: 0.00894 +2024-11-21 15:53:59.219035: train_loss -0.7472 +2024-11-21 15:53:59.226370: val_loss -0.7537 +2024-11-21 15:53:59.226511: Pseudo dice [0.8401] +2024-11-21 15:53:59.226609: Epoch time: 18.99 s +2024-11-21 15:54:00.524585: +2024-11-21 15:54:00.524775: Epoch 937 +2024-11-21 15:54:00.524896: Current learning rate: 0.00894 +2024-11-21 15:54:18.475404: train_loss -0.765 +2024-11-21 15:54:18.483068: val_loss -0.736 +2024-11-21 15:54:18.483218: Pseudo dice [0.8414] +2024-11-21 15:54:18.483305: Epoch time: 17.95 s +2024-11-21 15:54:19.317613: +2024-11-21 15:54:19.317830: Epoch 938 +2024-11-21 15:54:19.317953: Current learning rate: 0.00894 +2024-11-21 15:54:38.858876: train_loss -0.7665 +2024-11-21 15:54:38.862416: val_loss -0.7589 +2024-11-21 15:54:38.862540: Pseudo dice [0.8596] +2024-11-21 15:54:38.862630: Epoch time: 19.54 s +2024-11-21 15:54:39.732044: +2024-11-21 15:54:39.732247: Epoch 939 +2024-11-21 15:54:39.732377: Current learning rate: 0.00894 +2024-11-21 15:54:59.246122: train_loss -0.7697 +2024-11-21 15:54:59.249045: val_loss -0.7932 +2024-11-21 15:54:59.249154: Pseudo dice [0.8572] +2024-11-21 15:54:59.249250: Epoch time: 19.51 s +2024-11-21 15:55:00.050952: +2024-11-21 15:55:00.051137: Epoch 940 +2024-11-21 15:55:00.051265: Current learning rate: 0.00894 +2024-11-21 15:55:19.526001: train_loss -0.7648 +2024-11-21 15:55:19.546984: val_loss -0.7718 +2024-11-21 15:55:19.547161: Pseudo dice [0.8412] +2024-11-21 15:55:19.547256: Epoch time: 19.48 s +2024-11-21 15:55:20.462743: +2024-11-21 15:55:20.462973: Epoch 941 +2024-11-21 15:55:20.463111: Current learning rate: 0.00893 +2024-11-21 15:55:39.112978: train_loss -0.7516 +2024-11-21 15:55:39.120741: val_loss -0.7636 +2024-11-21 15:55:39.120884: Pseudo dice [0.845] +2024-11-21 15:55:39.120972: Epoch time: 18.65 s +2024-11-21 15:55:40.092241: +2024-11-21 15:55:40.092427: Epoch 942 +2024-11-21 15:55:40.092565: Current learning rate: 0.00893 +2024-11-21 15:55:58.670278: train_loss -0.7648 +2024-11-21 15:55:58.693204: val_loss -0.7646 +2024-11-21 15:55:58.693369: Pseudo dice [0.8345] +2024-11-21 15:55:58.693458: Epoch time: 18.58 s +2024-11-21 15:55:59.538274: +2024-11-21 15:55:59.538488: Epoch 943 +2024-11-21 15:55:59.538620: Current learning rate: 0.00893 +2024-11-21 15:56:17.332182: train_loss -0.7638 +2024-11-21 15:56:17.339312: val_loss -0.7651 +2024-11-21 15:56:17.339434: Pseudo dice [0.8412] +2024-11-21 15:56:17.339528: Epoch time: 17.79 s +2024-11-21 15:56:18.168375: +2024-11-21 15:56:18.168574: Epoch 944 +2024-11-21 15:56:18.168705: Current learning rate: 0.00893 +2024-11-21 15:56:37.587340: train_loss -0.7617 +2024-11-21 15:56:37.594823: val_loss -0.7739 +2024-11-21 15:56:37.594983: Pseudo dice [0.8539] +2024-11-21 15:56:37.595087: Epoch time: 19.42 s +2024-11-21 15:56:38.393187: +2024-11-21 15:56:38.393380: Epoch 945 +2024-11-21 15:56:38.393512: Current learning rate: 0.00893 +2024-11-21 15:56:55.944086: train_loss -0.7632 +2024-11-21 15:56:55.953309: val_loss -0.7534 +2024-11-21 15:56:55.953461: Pseudo dice [0.8373] +2024-11-21 15:56:55.953577: Epoch time: 17.55 s +2024-11-21 15:56:56.929303: +2024-11-21 15:56:56.929496: Epoch 946 +2024-11-21 15:56:56.929624: Current learning rate: 0.00893 +2024-11-21 15:57:17.229942: train_loss -0.7654 +2024-11-21 15:57:17.245272: val_loss -0.7506 +2024-11-21 15:57:17.245415: Pseudo dice [0.8469] +2024-11-21 15:57:17.245507: Epoch time: 20.3 s +2024-11-21 15:57:18.209747: +2024-11-21 15:57:18.209929: Epoch 947 +2024-11-21 15:57:18.210057: Current learning rate: 0.00893 +2024-11-21 15:57:36.860692: train_loss -0.7667 +2024-11-21 15:57:36.868234: val_loss -0.7534 +2024-11-21 15:57:36.868376: Pseudo dice [0.853] +2024-11-21 15:57:36.868480: Epoch time: 18.65 s +2024-11-21 15:57:37.727173: +2024-11-21 15:57:37.727376: Epoch 948 +2024-11-21 15:57:37.727501: Current learning rate: 0.00893 +2024-11-21 15:57:57.277864: train_loss -0.766 +2024-11-21 15:57:57.297575: val_loss -0.7525 +2024-11-21 15:57:57.297702: Pseudo dice [0.8478] +2024-11-21 15:57:57.297789: Epoch time: 19.55 s +2024-11-21 15:57:58.185041: +2024-11-21 15:57:58.185277: Epoch 949 +2024-11-21 15:57:58.185403: Current learning rate: 0.00893 +2024-11-21 15:58:17.375962: train_loss -0.7679 +2024-11-21 15:58:17.393020: val_loss -0.7723 +2024-11-21 15:58:17.393188: Pseudo dice [0.8559] +2024-11-21 15:58:17.393290: Epoch time: 19.19 s +2024-11-21 15:58:18.527237: +2024-11-21 15:58:18.527670: Epoch 950 +2024-11-21 15:58:18.527797: Current learning rate: 0.00892 +2024-11-21 15:58:38.211530: train_loss -0.7656 +2024-11-21 15:58:38.220412: val_loss -0.7576 +2024-11-21 15:58:38.220560: Pseudo dice [0.8495] +2024-11-21 15:58:38.220654: Epoch time: 19.69 s +2024-11-21 15:58:39.159662: +2024-11-21 15:58:39.159923: Epoch 951 +2024-11-21 15:58:39.160041: Current learning rate: 0.00892 +2024-11-21 15:58:57.945028: train_loss -0.7555 +2024-11-21 15:58:57.947735: val_loss -0.7522 +2024-11-21 15:58:57.947927: Pseudo dice [0.8441] +2024-11-21 15:58:57.948039: Epoch time: 18.79 s +2024-11-21 15:58:58.750039: +2024-11-21 15:58:58.750243: Epoch 952 +2024-11-21 15:58:58.750358: Current learning rate: 0.00892 +2024-11-21 15:59:17.461761: train_loss -0.76 +2024-11-21 15:59:17.468586: val_loss -0.7894 +2024-11-21 15:59:17.468718: Pseudo dice [0.8516] +2024-11-21 15:59:17.468827: Epoch time: 18.71 s +2024-11-21 15:59:18.361978: +2024-11-21 15:59:18.362178: Epoch 953 +2024-11-21 15:59:18.362296: Current learning rate: 0.00892 +2024-11-21 15:59:36.771754: train_loss -0.7584 +2024-11-21 15:59:36.779495: val_loss -0.7715 +2024-11-21 15:59:36.779634: Pseudo dice [0.845] +2024-11-21 15:59:36.779727: Epoch time: 18.41 s +2024-11-21 15:59:37.733892: +2024-11-21 15:59:37.734109: Epoch 954 +2024-11-21 15:59:37.734228: Current learning rate: 0.00892 +2024-11-21 15:59:56.435294: train_loss -0.7604 +2024-11-21 15:59:56.442039: val_loss -0.7814 +2024-11-21 15:59:56.442190: Pseudo dice [0.86] +2024-11-21 15:59:56.442303: Epoch time: 18.7 s +2024-11-21 15:59:57.401991: +2024-11-21 15:59:57.402215: Epoch 955 +2024-11-21 15:59:57.402348: Current learning rate: 0.00892 +2024-11-21 16:00:16.900838: train_loss -0.7692 +2024-11-21 16:00:16.905387: val_loss -0.7443 +2024-11-21 16:00:16.905515: Pseudo dice [0.8516] +2024-11-21 16:00:16.905627: Epoch time: 19.5 s +2024-11-21 16:00:17.711270: +2024-11-21 16:00:17.711470: Epoch 956 +2024-11-21 16:00:17.711594: Current learning rate: 0.00892 +2024-11-21 16:00:36.286438: train_loss -0.7755 +2024-11-21 16:00:36.292134: val_loss -0.7811 +2024-11-21 16:00:36.292259: Pseudo dice [0.8446] +2024-11-21 16:00:36.292350: Epoch time: 18.58 s +2024-11-21 16:00:37.156802: +2024-11-21 16:00:37.156997: Epoch 957 +2024-11-21 16:00:37.157149: Current learning rate: 0.00892 +2024-11-21 16:00:56.881801: train_loss -0.7729 +2024-11-21 16:00:56.891207: val_loss -0.7771 +2024-11-21 16:00:56.891338: Pseudo dice [0.8377] +2024-11-21 16:00:56.891438: Epoch time: 19.73 s +2024-11-21 16:00:57.741029: +2024-11-21 16:00:57.741316: Epoch 958 +2024-11-21 16:00:57.741460: Current learning rate: 0.00892 +2024-11-21 16:01:16.042559: train_loss -0.7593 +2024-11-21 16:01:16.045599: val_loss -0.7426 +2024-11-21 16:01:16.045731: Pseudo dice [0.8413] +2024-11-21 16:01:16.045830: Epoch time: 18.3 s +2024-11-21 16:01:16.851875: +2024-11-21 16:01:16.852075: Epoch 959 +2024-11-21 16:01:16.852207: Current learning rate: 0.00891 +2024-11-21 16:01:35.279527: train_loss -0.7606 +2024-11-21 16:01:35.287194: val_loss -0.7484 +2024-11-21 16:01:35.287328: Pseudo dice [0.8452] +2024-11-21 16:01:35.287425: Epoch time: 18.43 s +2024-11-21 16:01:36.165751: +2024-11-21 16:01:36.165980: Epoch 960 +2024-11-21 16:01:36.166112: Current learning rate: 0.00891 +2024-11-21 16:01:56.131488: train_loss -0.7703 +2024-11-21 16:01:56.143991: val_loss -0.7813 +2024-11-21 16:01:56.144138: Pseudo dice [0.845] +2024-11-21 16:01:56.144242: Epoch time: 19.97 s +2024-11-21 16:01:57.111907: +2024-11-21 16:01:57.112122: Epoch 961 +2024-11-21 16:01:57.112241: Current learning rate: 0.00891 +2024-11-21 16:02:17.178705: train_loss -0.7641 +2024-11-21 16:02:17.182328: val_loss -0.7679 +2024-11-21 16:02:17.182444: Pseudo dice [0.8335] +2024-11-21 16:02:17.182543: Epoch time: 20.07 s +2024-11-21 16:02:17.992600: +2024-11-21 16:02:17.992842: Epoch 962 +2024-11-21 16:02:17.992964: Current learning rate: 0.00891 +2024-11-21 16:02:37.052334: train_loss -0.7563 +2024-11-21 16:02:37.059382: val_loss -0.7783 +2024-11-21 16:02:37.059531: Pseudo dice [0.8546] +2024-11-21 16:02:37.059837: Epoch time: 19.06 s +2024-11-21 16:02:37.935477: +2024-11-21 16:02:37.935713: Epoch 963 +2024-11-21 16:02:37.935845: Current learning rate: 0.00891 +2024-11-21 16:02:55.735044: train_loss -0.7552 +2024-11-21 16:02:55.743233: val_loss -0.7346 +2024-11-21 16:02:55.743349: Pseudo dice [0.8518] +2024-11-21 16:02:55.743435: Epoch time: 17.8 s +2024-11-21 16:02:56.737684: +2024-11-21 16:02:56.737872: Epoch 964 +2024-11-21 16:02:56.737980: Current learning rate: 0.00891 +2024-11-21 16:03:15.871845: train_loss -0.76 +2024-11-21 16:03:15.879953: val_loss -0.7372 +2024-11-21 16:03:15.880088: Pseudo dice [0.8532] +2024-11-21 16:03:15.880193: Epoch time: 19.13 s +2024-11-21 16:03:16.691374: +2024-11-21 16:03:16.691578: Epoch 965 +2024-11-21 16:03:16.691715: Current learning rate: 0.00891 +2024-11-21 16:03:35.725213: train_loss -0.7704 +2024-11-21 16:03:35.732401: val_loss -0.7521 +2024-11-21 16:03:35.732546: Pseudo dice [0.8447] +2024-11-21 16:03:35.732657: Epoch time: 19.03 s +2024-11-21 16:03:36.627371: +2024-11-21 16:03:36.627600: Epoch 966 +2024-11-21 16:03:36.627717: Current learning rate: 0.00891 +2024-11-21 16:03:56.242334: train_loss -0.7677 +2024-11-21 16:03:56.251932: val_loss -0.7588 +2024-11-21 16:03:56.252089: Pseudo dice [0.8286] +2024-11-21 16:03:56.252186: Epoch time: 19.62 s +2024-11-21 16:03:57.206234: +2024-11-21 16:03:57.206413: Epoch 967 +2024-11-21 16:03:57.206551: Current learning rate: 0.00891 +2024-11-21 16:04:16.122091: train_loss -0.7659 +2024-11-21 16:04:16.134021: val_loss -0.7408 +2024-11-21 16:04:16.134155: Pseudo dice [0.8393] +2024-11-21 16:04:16.134318: Epoch time: 18.92 s +2024-11-21 16:04:16.966689: +2024-11-21 16:04:16.966865: Epoch 968 +2024-11-21 16:04:16.967000: Current learning rate: 0.0089 +2024-11-21 16:04:36.476129: train_loss -0.7624 +2024-11-21 16:04:36.498121: val_loss -0.7223 +2024-11-21 16:04:36.498258: Pseudo dice [0.845] +2024-11-21 16:04:36.498349: Epoch time: 19.51 s +2024-11-21 16:04:37.369973: +2024-11-21 16:04:37.370209: Epoch 969 +2024-11-21 16:04:37.370355: Current learning rate: 0.0089 +2024-11-21 16:04:57.075269: train_loss -0.7636 +2024-11-21 16:04:57.079392: val_loss -0.775 +2024-11-21 16:04:57.079522: Pseudo dice [0.8459] +2024-11-21 16:04:57.079618: Epoch time: 19.71 s +2024-11-21 16:04:57.909497: +2024-11-21 16:04:57.909716: Epoch 970 +2024-11-21 16:04:57.909834: Current learning rate: 0.0089 +2024-11-21 16:05:17.511848: train_loss -0.7598 +2024-11-21 16:05:17.517772: val_loss -0.7618 +2024-11-21 16:05:17.517884: Pseudo dice [0.8393] +2024-11-21 16:05:17.517977: Epoch time: 19.6 s +2024-11-21 16:05:18.402918: +2024-11-21 16:05:18.403123: Epoch 971 +2024-11-21 16:05:18.403252: Current learning rate: 0.0089 +2024-11-21 16:05:37.106346: train_loss -0.7715 +2024-11-21 16:05:37.131228: val_loss -0.7659 +2024-11-21 16:05:37.131391: Pseudo dice [0.8387] +2024-11-21 16:05:37.131493: Epoch time: 18.7 s +2024-11-21 16:05:38.002442: +2024-11-21 16:05:38.002658: Epoch 972 +2024-11-21 16:05:38.002797: Current learning rate: 0.0089 +2024-11-21 16:05:58.010550: train_loss -0.7681 +2024-11-21 16:05:58.018309: val_loss -0.769 +2024-11-21 16:05:58.018468: Pseudo dice [0.8431] +2024-11-21 16:05:58.018588: Epoch time: 20.01 s +2024-11-21 16:05:58.894188: +2024-11-21 16:05:58.894406: Epoch 973 +2024-11-21 16:05:58.894551: Current learning rate: 0.0089 +2024-11-21 16:06:17.809633: train_loss -0.7737 +2024-11-21 16:06:17.815621: val_loss -0.7586 +2024-11-21 16:06:17.815735: Pseudo dice [0.8545] +2024-11-21 16:06:17.815827: Epoch time: 18.92 s +2024-11-21 16:06:18.628036: +2024-11-21 16:06:18.628265: Epoch 974 +2024-11-21 16:06:18.628395: Current learning rate: 0.0089 +2024-11-21 16:06:37.897204: train_loss -0.7617 +2024-11-21 16:06:37.907859: val_loss -0.7644 +2024-11-21 16:06:37.907986: Pseudo dice [0.8518] +2024-11-21 16:06:37.908098: Epoch time: 19.27 s +2024-11-21 16:06:38.730054: +2024-11-21 16:06:38.730253: Epoch 975 +2024-11-21 16:06:38.730387: Current learning rate: 0.0089 +2024-11-21 16:06:57.537323: train_loss -0.7744 +2024-11-21 16:06:57.550279: val_loss -0.772 +2024-11-21 16:06:57.550634: Pseudo dice [0.8469] +2024-11-21 16:06:57.550733: Epoch time: 18.81 s +2024-11-21 16:06:58.524832: +2024-11-21 16:06:58.525022: Epoch 976 +2024-11-21 16:06:58.525145: Current learning rate: 0.00889 +2024-11-21 16:07:17.966635: train_loss -0.7627 +2024-11-21 16:07:17.975688: val_loss -0.7809 +2024-11-21 16:07:17.975822: Pseudo dice [0.8457] +2024-11-21 16:07:17.975944: Epoch time: 19.44 s +2024-11-21 16:07:18.883744: +2024-11-21 16:07:18.883955: Epoch 977 +2024-11-21 16:07:18.884093: Current learning rate: 0.00889 +2024-11-21 16:07:38.422223: train_loss -0.7596 +2024-11-21 16:07:38.427100: val_loss -0.7522 +2024-11-21 16:07:38.427225: Pseudo dice [0.84] +2024-11-21 16:07:38.427320: Epoch time: 19.54 s +2024-11-21 16:07:39.267910: +2024-11-21 16:07:39.268098: Epoch 978 +2024-11-21 16:07:39.268220: Current learning rate: 0.00889 +2024-11-21 16:07:58.601769: train_loss -0.7734 +2024-11-21 16:07:58.611261: val_loss -0.7615 +2024-11-21 16:07:58.611395: Pseudo dice [0.8428] +2024-11-21 16:07:58.611498: Epoch time: 19.33 s +2024-11-21 16:07:59.688123: +2024-11-21 16:07:59.688334: Epoch 979 +2024-11-21 16:07:59.688472: Current learning rate: 0.00889 +2024-11-21 16:08:18.280643: train_loss -0.7658 +2024-11-21 16:08:18.287107: val_loss -0.7621 +2024-11-21 16:08:18.287245: Pseudo dice [0.8453] +2024-11-21 16:08:18.287352: Epoch time: 18.59 s +2024-11-21 16:08:19.230972: +2024-11-21 16:08:19.231179: Epoch 980 +2024-11-21 16:08:19.231303: Current learning rate: 0.00889 +2024-11-21 16:08:38.259326: train_loss -0.7641 +2024-11-21 16:08:38.267635: val_loss -0.7406 +2024-11-21 16:08:38.267770: Pseudo dice [0.8345] +2024-11-21 16:08:38.267897: Epoch time: 19.03 s +2024-11-21 16:08:39.253178: +2024-11-21 16:08:39.253415: Epoch 981 +2024-11-21 16:08:39.253550: Current learning rate: 0.00889 +2024-11-21 16:08:57.372572: train_loss -0.7724 +2024-11-21 16:08:57.405048: val_loss -0.7722 +2024-11-21 16:08:57.405208: Pseudo dice [0.8473] +2024-11-21 16:08:57.405309: Epoch time: 18.12 s +2024-11-21 16:08:58.627441: +2024-11-21 16:08:58.627661: Epoch 982 +2024-11-21 16:08:58.627790: Current learning rate: 0.00889 +2024-11-21 16:09:18.217853: train_loss -0.7635 +2024-11-21 16:09:18.223958: val_loss -0.7655 +2024-11-21 16:09:18.224113: Pseudo dice [0.849] +2024-11-21 16:09:18.224209: Epoch time: 19.59 s +2024-11-21 16:09:19.134074: +2024-11-21 16:09:19.134279: Epoch 983 +2024-11-21 16:09:19.134395: Current learning rate: 0.00889 +2024-11-21 16:09:39.118850: train_loss -0.7476 +2024-11-21 16:09:39.127792: val_loss -0.7459 +2024-11-21 16:09:39.127925: Pseudo dice [0.828] +2024-11-21 16:09:39.128081: Epoch time: 19.99 s +2024-11-21 16:09:40.105692: +2024-11-21 16:09:40.105942: Epoch 984 +2024-11-21 16:09:40.106127: Current learning rate: 0.00889 +2024-11-21 16:09:58.654746: train_loss -0.734 +2024-11-21 16:09:58.672364: val_loss -0.7592 +2024-11-21 16:09:58.672517: Pseudo dice [0.849] +2024-11-21 16:09:58.672611: Epoch time: 18.55 s +2024-11-21 16:09:59.624418: +2024-11-21 16:09:59.624628: Epoch 985 +2024-11-21 16:09:59.624757: Current learning rate: 0.00888 +2024-11-21 16:10:19.245159: train_loss -0.7531 +2024-11-21 16:10:19.258627: val_loss -0.7589 +2024-11-21 16:10:19.258793: Pseudo dice [0.8392] +2024-11-21 16:10:19.258891: Epoch time: 19.62 s +2024-11-21 16:10:20.248596: +2024-11-21 16:10:20.248806: Epoch 986 +2024-11-21 16:10:20.248935: Current learning rate: 0.00888 +2024-11-21 16:10:39.624835: train_loss -0.7558 +2024-11-21 16:10:39.631323: val_loss -0.76 +2024-11-21 16:10:39.631449: Pseudo dice [0.8456] +2024-11-21 16:10:39.631532: Epoch time: 19.38 s +2024-11-21 16:10:40.481945: +2024-11-21 16:10:40.482128: Epoch 987 +2024-11-21 16:10:40.482258: Current learning rate: 0.00888 +2024-11-21 16:10:59.655240: train_loss -0.7552 +2024-11-21 16:10:59.661378: val_loss -0.736 +2024-11-21 16:10:59.661544: Pseudo dice [0.857] +2024-11-21 16:10:59.661650: Epoch time: 19.17 s +2024-11-21 16:11:00.781117: +2024-11-21 16:11:00.781317: Epoch 988 +2024-11-21 16:11:00.781432: Current learning rate: 0.00888 +2024-11-21 16:11:21.262767: train_loss -0.7613 +2024-11-21 16:11:21.267371: val_loss -0.7534 +2024-11-21 16:11:21.267493: Pseudo dice [0.8481] +2024-11-21 16:11:21.267583: Epoch time: 20.48 s +2024-11-21 16:11:22.088958: +2024-11-21 16:11:22.089192: Epoch 989 +2024-11-21 16:11:22.089333: Current learning rate: 0.00888 +2024-11-21 16:11:41.272198: train_loss -0.761 +2024-11-21 16:11:41.278617: val_loss -0.7487 +2024-11-21 16:11:41.278764: Pseudo dice [0.832] +2024-11-21 16:11:41.278859: Epoch time: 19.18 s +2024-11-21 16:11:42.094545: +2024-11-21 16:11:42.094727: Epoch 990 +2024-11-21 16:11:42.094858: Current learning rate: 0.00888 +2024-11-21 16:12:01.664082: train_loss -0.7618 +2024-11-21 16:12:01.668622: val_loss -0.7236 +2024-11-21 16:12:01.668763: Pseudo dice [0.8379] +2024-11-21 16:12:01.668864: Epoch time: 19.57 s +2024-11-21 16:12:02.516641: +2024-11-21 16:12:02.516880: Epoch 991 +2024-11-21 16:12:02.516999: Current learning rate: 0.00888 +2024-11-21 16:12:22.819027: train_loss -0.7157 +2024-11-21 16:12:22.824416: val_loss -0.7093 +2024-11-21 16:12:22.824565: Pseudo dice [0.819] +2024-11-21 16:12:22.824682: Epoch time: 20.3 s +2024-11-21 16:12:23.650455: +2024-11-21 16:12:23.650675: Epoch 992 +2024-11-21 16:12:23.650811: Current learning rate: 0.00888 +2024-11-21 16:12:44.188528: train_loss -0.7206 +2024-11-21 16:12:44.202265: val_loss -0.7525 +2024-11-21 16:12:44.202410: Pseudo dice [0.8206] +2024-11-21 16:12:44.202500: Epoch time: 20.54 s +2024-11-21 16:12:45.434231: +2024-11-21 16:12:45.434448: Epoch 993 +2024-11-21 16:12:45.434571: Current learning rate: 0.00888 +2024-11-21 16:13:05.119273: train_loss -0.7364 +2024-11-21 16:13:05.123030: val_loss -0.7478 +2024-11-21 16:13:05.123170: Pseudo dice [0.8446] +2024-11-21 16:13:05.123275: Epoch time: 19.69 s +2024-11-21 16:13:05.940681: +2024-11-21 16:13:05.940893: Epoch 994 +2024-11-21 16:13:05.941012: Current learning rate: 0.00887 +2024-11-21 16:13:24.326285: train_loss -0.7535 +2024-11-21 16:13:24.331895: val_loss -0.7079 +2024-11-21 16:13:24.332025: Pseudo dice [0.8312] +2024-11-21 16:13:24.332175: Epoch time: 18.39 s +2024-11-21 16:13:25.148694: +2024-11-21 16:13:25.148904: Epoch 995 +2024-11-21 16:13:25.149027: Current learning rate: 0.00887 +2024-11-21 16:13:44.445410: train_loss -0.7343 +2024-11-21 16:13:44.453605: val_loss -0.7593 +2024-11-21 16:13:44.453746: Pseudo dice [0.8507] +2024-11-21 16:13:44.453839: Epoch time: 19.3 s +2024-11-21 16:13:45.296924: +2024-11-21 16:13:45.297140: Epoch 996 +2024-11-21 16:13:45.297268: Current learning rate: 0.00887 +2024-11-21 16:14:04.553741: train_loss -0.762 +2024-11-21 16:14:04.560445: val_loss -0.7433 +2024-11-21 16:14:04.560591: Pseudo dice [0.8465] +2024-11-21 16:14:04.560694: Epoch time: 19.26 s +2024-11-21 16:14:05.570553: +2024-11-21 16:14:05.570779: Epoch 997 +2024-11-21 16:14:05.570912: Current learning rate: 0.00887 +2024-11-21 16:14:24.631984: train_loss -0.7364 +2024-11-21 16:14:24.641737: val_loss -0.7392 +2024-11-21 16:14:24.641880: Pseudo dice [0.8285] +2024-11-21 16:14:24.641969: Epoch time: 19.06 s +2024-11-21 16:14:25.711069: +2024-11-21 16:14:25.711281: Epoch 998 +2024-11-21 16:14:25.711401: Current learning rate: 0.00887 +2024-11-21 16:14:45.561842: train_loss -0.7214 +2024-11-21 16:14:45.572024: val_loss -0.7466 +2024-11-21 16:14:45.572171: Pseudo dice [0.842] +2024-11-21 16:14:45.572266: Epoch time: 19.85 s +2024-11-21 16:14:46.446218: +2024-11-21 16:14:46.446433: Epoch 999 +2024-11-21 16:14:46.446566: Current learning rate: 0.00887 +2024-11-21 16:15:04.973815: train_loss -0.7419 +2024-11-21 16:15:04.976798: val_loss -0.7406 +2024-11-21 16:15:04.976914: Pseudo dice [0.8413] +2024-11-21 16:15:04.977019: Epoch time: 18.53 s +2024-11-21 16:15:06.053501: +2024-11-21 16:15:06.053792: Epoch 1000 +2024-11-21 16:15:06.053912: Current learning rate: 0.00887 +2024-11-21 16:15:26.108553: train_loss -0.7625 +2024-11-21 16:15:26.111314: val_loss -0.7405 +2024-11-21 16:15:26.111440: Pseudo dice [0.8319] +2024-11-21 16:15:26.111534: Epoch time: 20.06 s +2024-11-21 16:15:26.927794: +2024-11-21 16:15:26.928261: Epoch 1001 +2024-11-21 16:15:26.928399: Current learning rate: 0.00887 +2024-11-21 16:15:45.872040: train_loss -0.7566 +2024-11-21 16:15:45.879161: val_loss -0.7546 +2024-11-21 16:15:45.879331: Pseudo dice [0.8397] +2024-11-21 16:15:45.879527: Epoch time: 18.95 s +2024-11-21 16:15:46.815285: +2024-11-21 16:15:46.815479: Epoch 1002 +2024-11-21 16:15:46.815596: Current learning rate: 0.00887 +2024-11-21 16:16:05.223874: train_loss -0.7639 +2024-11-21 16:16:05.229212: val_loss -0.7613 +2024-11-21 16:16:05.229343: Pseudo dice [0.8432] +2024-11-21 16:16:05.229449: Epoch time: 18.41 s +2024-11-21 16:16:06.178890: +2024-11-21 16:16:06.179096: Epoch 1003 +2024-11-21 16:16:06.179233: Current learning rate: 0.00886 +2024-11-21 16:16:25.207260: train_loss -0.7624 +2024-11-21 16:16:25.214401: val_loss -0.7588 +2024-11-21 16:16:25.214543: Pseudo dice [0.8435] +2024-11-21 16:16:25.214630: Epoch time: 19.03 s +2024-11-21 16:16:26.031292: +2024-11-21 16:16:26.031501: Epoch 1004 +2024-11-21 16:16:26.031634: Current learning rate: 0.00886 +2024-11-21 16:16:46.177549: train_loss -0.7527 +2024-11-21 16:16:46.185161: val_loss -0.7397 +2024-11-21 16:16:46.185327: Pseudo dice [0.8537] +2024-11-21 16:16:46.185418: Epoch time: 20.15 s +2024-11-21 16:16:47.451312: +2024-11-21 16:16:47.451543: Epoch 1005 +2024-11-21 16:16:47.451659: Current learning rate: 0.00886 +2024-11-21 16:17:06.979921: train_loss -0.7525 +2024-11-21 16:17:06.983216: val_loss -0.7757 +2024-11-21 16:17:06.983349: Pseudo dice [0.8464] +2024-11-21 16:17:06.983451: Epoch time: 19.52 s +2024-11-21 16:17:08.078664: +2024-11-21 16:17:08.078896: Epoch 1006 +2024-11-21 16:17:08.079016: Current learning rate: 0.00886 +2024-11-21 16:17:27.230504: train_loss -0.7644 +2024-11-21 16:17:27.234258: val_loss -0.7347 +2024-11-21 16:17:27.234357: Pseudo dice [0.8255] +2024-11-21 16:17:27.234442: Epoch time: 19.15 s +2024-11-21 16:17:28.033152: +2024-11-21 16:17:28.033364: Epoch 1007 +2024-11-21 16:17:28.033495: Current learning rate: 0.00886 +2024-11-21 16:17:48.160990: train_loss -0.7675 +2024-11-21 16:17:48.168095: val_loss -0.7616 +2024-11-21 16:17:48.168224: Pseudo dice [0.8421] +2024-11-21 16:17:48.168307: Epoch time: 20.13 s +2024-11-21 16:17:48.987229: +2024-11-21 16:17:48.987458: Epoch 1008 +2024-11-21 16:17:48.987585: Current learning rate: 0.00886 +2024-11-21 16:18:07.672116: train_loss -0.7583 +2024-11-21 16:18:07.675460: val_loss -0.7563 +2024-11-21 16:18:07.675567: Pseudo dice [0.8464] +2024-11-21 16:18:07.675666: Epoch time: 18.69 s +2024-11-21 16:18:08.484010: +2024-11-21 16:18:08.484225: Epoch 1009 +2024-11-21 16:18:08.484343: Current learning rate: 0.00886 +2024-11-21 16:18:28.267798: train_loss -0.7567 +2024-11-21 16:18:28.275576: val_loss -0.7591 +2024-11-21 16:18:28.275702: Pseudo dice [0.8456] +2024-11-21 16:18:28.275825: Epoch time: 19.78 s +2024-11-21 16:18:29.276698: +2024-11-21 16:18:29.276919: Epoch 1010 +2024-11-21 16:18:29.277050: Current learning rate: 0.00886 +2024-11-21 16:18:48.679903: train_loss -0.7711 +2024-11-21 16:18:48.689320: val_loss -0.7575 +2024-11-21 16:18:48.689464: Pseudo dice [0.8485] +2024-11-21 16:18:48.689555: Epoch time: 19.4 s +2024-11-21 16:18:49.655401: +2024-11-21 16:18:49.655621: Epoch 1011 +2024-11-21 16:18:49.655750: Current learning rate: 0.00886 +2024-11-21 16:19:08.751009: train_loss -0.7523 +2024-11-21 16:19:08.759282: val_loss -0.7332 +2024-11-21 16:19:08.759444: Pseudo dice [0.8508] +2024-11-21 16:19:08.759541: Epoch time: 19.1 s +2024-11-21 16:19:09.590692: +2024-11-21 16:19:09.591000: Epoch 1012 +2024-11-21 16:19:09.591145: Current learning rate: 0.00885 +2024-11-21 16:19:28.584812: train_loss -0.7613 +2024-11-21 16:19:28.587853: val_loss -0.747 +2024-11-21 16:19:28.587954: Pseudo dice [0.8471] +2024-11-21 16:19:28.588055: Epoch time: 18.99 s +2024-11-21 16:19:29.404961: +2024-11-21 16:19:29.405155: Epoch 1013 +2024-11-21 16:19:29.405275: Current learning rate: 0.00885 +2024-11-21 16:19:48.724484: train_loss -0.7599 +2024-11-21 16:19:48.732937: val_loss -0.7571 +2024-11-21 16:19:48.733069: Pseudo dice [0.8433] +2024-11-21 16:19:48.733373: Epoch time: 19.32 s +2024-11-21 16:19:49.594909: +2024-11-21 16:19:49.595096: Epoch 1014 +2024-11-21 16:19:49.595209: Current learning rate: 0.00885 +2024-11-21 16:20:08.391778: train_loss -0.7603 +2024-11-21 16:20:08.395266: val_loss -0.7674 +2024-11-21 16:20:08.395387: Pseudo dice [0.8525] +2024-11-21 16:20:08.395472: Epoch time: 18.8 s +2024-11-21 16:20:09.214113: +2024-11-21 16:20:09.214324: Epoch 1015 +2024-11-21 16:20:09.214463: Current learning rate: 0.00885 +2024-11-21 16:20:29.050163: train_loss -0.7619 +2024-11-21 16:20:29.057258: val_loss -0.7721 +2024-11-21 16:20:29.057460: Pseudo dice [0.849] +2024-11-21 16:20:29.057563: Epoch time: 19.84 s +2024-11-21 16:20:30.395833: +2024-11-21 16:20:30.396137: Epoch 1016 +2024-11-21 16:20:30.396258: Current learning rate: 0.00885 +2024-11-21 16:20:49.184803: train_loss -0.7643 +2024-11-21 16:20:49.197514: val_loss -0.7629 +2024-11-21 16:20:49.197644: Pseudo dice [0.8553] +2024-11-21 16:20:49.197737: Epoch time: 18.79 s +2024-11-21 16:20:50.081397: +2024-11-21 16:20:50.081654: Epoch 1017 +2024-11-21 16:20:50.081784: Current learning rate: 0.00885 +2024-11-21 16:21:09.149417: train_loss -0.7683 +2024-11-21 16:21:09.171979: val_loss -0.7703 +2024-11-21 16:21:09.172158: Pseudo dice [0.8418] +2024-11-21 16:21:09.172250: Epoch time: 19.07 s +2024-11-21 16:21:10.056774: +2024-11-21 16:21:10.057013: Epoch 1018 +2024-11-21 16:21:10.057142: Current learning rate: 0.00885 +2024-11-21 16:21:27.863468: train_loss -0.773 +2024-11-21 16:21:27.891607: val_loss -0.7861 +2024-11-21 16:21:27.891798: Pseudo dice [0.8581] +2024-11-21 16:21:27.891897: Epoch time: 17.81 s +2024-11-21 16:21:28.754948: +2024-11-21 16:21:28.755238: Epoch 1019 +2024-11-21 16:21:28.755367: Current learning rate: 0.00885 +2024-11-21 16:21:48.021895: train_loss -0.7681 +2024-11-21 16:21:48.040805: val_loss -0.7588 +2024-11-21 16:21:48.040956: Pseudo dice [0.8466] +2024-11-21 16:21:48.041037: Epoch time: 19.27 s +2024-11-21 16:21:48.948356: +2024-11-21 16:21:48.948580: Epoch 1020 +2024-11-21 16:21:48.948713: Current learning rate: 0.00884 +2024-11-21 16:22:07.526648: train_loss -0.7679 +2024-11-21 16:22:07.531100: val_loss -0.7695 +2024-11-21 16:22:07.531246: Pseudo dice [0.8458] +2024-11-21 16:22:07.531366: Epoch time: 18.58 s +2024-11-21 16:22:08.561879: +2024-11-21 16:22:08.562075: Epoch 1021 +2024-11-21 16:22:08.562200: Current learning rate: 0.00884 +2024-11-21 16:22:26.949811: train_loss -0.7592 +2024-11-21 16:22:26.958701: val_loss -0.7608 +2024-11-21 16:22:26.958832: Pseudo dice [0.8452] +2024-11-21 16:22:26.958930: Epoch time: 18.39 s +2024-11-21 16:22:27.801971: +2024-11-21 16:22:27.802181: Epoch 1022 +2024-11-21 16:22:27.802301: Current learning rate: 0.00884 +2024-11-21 16:22:46.443425: train_loss -0.7755 +2024-11-21 16:22:46.445967: val_loss -0.782 +2024-11-21 16:22:46.446101: Pseudo dice [0.8521] +2024-11-21 16:22:46.446201: Epoch time: 18.64 s +2024-11-21 16:22:47.435575: +2024-11-21 16:22:47.435758: Epoch 1023 +2024-11-21 16:22:47.435891: Current learning rate: 0.00884 +2024-11-21 16:23:05.481427: train_loss -0.7585 +2024-11-21 16:23:05.488661: val_loss -0.7781 +2024-11-21 16:23:05.488805: Pseudo dice [0.8518] +2024-11-21 16:23:05.488898: Epoch time: 18.05 s +2024-11-21 16:23:06.326229: +2024-11-21 16:23:06.326427: Epoch 1024 +2024-11-21 16:23:06.326539: Current learning rate: 0.00884 +2024-11-21 16:23:25.207484: train_loss -0.7481 +2024-11-21 16:23:25.212937: val_loss -0.7337 +2024-11-21 16:23:25.213110: Pseudo dice [0.8372] +2024-11-21 16:23:25.213205: Epoch time: 18.88 s +2024-11-21 16:23:26.026380: +2024-11-21 16:23:26.026592: Epoch 1025 +2024-11-21 16:23:26.026746: Current learning rate: 0.00884 +2024-11-21 16:23:45.265295: train_loss -0.7589 +2024-11-21 16:23:45.268243: val_loss -0.7571 +2024-11-21 16:23:45.268345: Pseudo dice [0.8472] +2024-11-21 16:23:45.268426: Epoch time: 19.24 s +2024-11-21 16:23:46.078645: +2024-11-21 16:23:46.078900: Epoch 1026 +2024-11-21 16:23:46.079024: Current learning rate: 0.00884 +2024-11-21 16:24:04.675746: train_loss -0.7725 +2024-11-21 16:24:04.682328: val_loss -0.7445 +2024-11-21 16:24:04.682503: Pseudo dice [0.8554] +2024-11-21 16:24:04.682589: Epoch time: 18.6 s +2024-11-21 16:24:05.497983: +2024-11-21 16:24:05.498189: Epoch 1027 +2024-11-21 16:24:05.498313: Current learning rate: 0.00884 +2024-11-21 16:24:24.187608: train_loss -0.7631 +2024-11-21 16:24:24.193934: val_loss -0.7734 +2024-11-21 16:24:24.194048: Pseudo dice [0.8475] +2024-11-21 16:24:24.194154: Epoch time: 18.69 s +2024-11-21 16:24:25.455232: +2024-11-21 16:24:25.455439: Epoch 1028 +2024-11-21 16:24:25.455572: Current learning rate: 0.00884 +2024-11-21 16:24:44.317458: train_loss -0.7683 +2024-11-21 16:24:44.325332: val_loss -0.7543 +2024-11-21 16:24:44.325463: Pseudo dice [0.8337] +2024-11-21 16:24:44.325570: Epoch time: 18.86 s +2024-11-21 16:24:45.312480: +2024-11-21 16:24:45.312697: Epoch 1029 +2024-11-21 16:24:45.312816: Current learning rate: 0.00883 +2024-11-21 16:25:04.591095: train_loss -0.7434 +2024-11-21 16:25:04.598131: val_loss -0.7503 +2024-11-21 16:25:04.598270: Pseudo dice [0.8366] +2024-11-21 16:25:04.598373: Epoch time: 19.28 s +2024-11-21 16:25:05.483379: +2024-11-21 16:25:05.483605: Epoch 1030 +2024-11-21 16:25:05.483719: Current learning rate: 0.00883 +2024-11-21 16:25:24.256851: train_loss -0.7609 +2024-11-21 16:25:24.268841: val_loss -0.7637 +2024-11-21 16:25:24.268984: Pseudo dice [0.845] +2024-11-21 16:25:24.269086: Epoch time: 18.77 s +2024-11-21 16:25:25.156382: +2024-11-21 16:25:25.156594: Epoch 1031 +2024-11-21 16:25:25.156725: Current learning rate: 0.00883 +2024-11-21 16:25:43.700586: train_loss -0.7616 +2024-11-21 16:25:43.727388: val_loss -0.7688 +2024-11-21 16:25:43.727545: Pseudo dice [0.852] +2024-11-21 16:25:43.727639: Epoch time: 18.55 s +2024-11-21 16:25:44.755372: +2024-11-21 16:25:44.755591: Epoch 1032 +2024-11-21 16:25:44.755726: Current learning rate: 0.00883 +2024-11-21 16:26:03.822744: train_loss -0.7743 +2024-11-21 16:26:03.824919: val_loss -0.7551 +2024-11-21 16:26:03.825011: Pseudo dice [0.8302] +2024-11-21 16:26:03.825110: Epoch time: 19.07 s +2024-11-21 16:26:04.637561: +2024-11-21 16:26:04.637755: Epoch 1033 +2024-11-21 16:26:04.637888: Current learning rate: 0.00883 +2024-11-21 16:26:23.587227: train_loss -0.7725 +2024-11-21 16:26:23.611488: val_loss -0.7594 +2024-11-21 16:26:23.611653: Pseudo dice [0.8376] +2024-11-21 16:26:23.611753: Epoch time: 18.95 s +2024-11-21 16:26:24.510234: +2024-11-21 16:26:24.510527: Epoch 1034 +2024-11-21 16:26:24.510659: Current learning rate: 0.00883 +2024-11-21 16:26:42.891606: train_loss -0.7655 +2024-11-21 16:26:42.896415: val_loss -0.7622 +2024-11-21 16:26:42.896537: Pseudo dice [0.8427] +2024-11-21 16:26:42.896628: Epoch time: 18.38 s +2024-11-21 16:26:44.009912: +2024-11-21 16:26:44.010148: Epoch 1035 +2024-11-21 16:26:44.010288: Current learning rate: 0.00883 +2024-11-21 16:27:02.458289: train_loss -0.7733 +2024-11-21 16:27:02.459805: val_loss -0.7792 +2024-11-21 16:27:02.459912: Pseudo dice [0.8548] +2024-11-21 16:27:02.460000: Epoch time: 18.45 s +2024-11-21 16:27:03.275146: +2024-11-21 16:27:03.275405: Epoch 1036 +2024-11-21 16:27:03.275534: Current learning rate: 0.00883 +2024-11-21 16:27:21.618159: train_loss -0.7597 +2024-11-21 16:27:21.619967: val_loss -0.7892 +2024-11-21 16:27:21.620074: Pseudo dice [0.8601] +2024-11-21 16:27:21.620161: Epoch time: 18.34 s +2024-11-21 16:27:22.462222: +2024-11-21 16:27:22.462420: Epoch 1037 +2024-11-21 16:27:22.462536: Current learning rate: 0.00883 +2024-11-21 16:27:41.672769: train_loss -0.7587 +2024-11-21 16:27:41.678882: val_loss -0.7592 +2024-11-21 16:27:41.679020: Pseudo dice [0.843] +2024-11-21 16:27:41.679129: Epoch time: 19.21 s +2024-11-21 16:27:42.614674: +2024-11-21 16:27:42.614866: Epoch 1038 +2024-11-21 16:27:42.614989: Current learning rate: 0.00882 +2024-11-21 16:28:01.297594: train_loss -0.7748 +2024-11-21 16:28:01.305491: val_loss -0.7711 +2024-11-21 16:28:01.305634: Pseudo dice [0.8475] +2024-11-21 16:28:01.305738: Epoch time: 18.68 s +2024-11-21 16:28:02.627503: +2024-11-21 16:28:02.627706: Epoch 1039 +2024-11-21 16:28:02.628068: Current learning rate: 0.00882 +2024-11-21 16:28:21.677652: train_loss -0.7735 +2024-11-21 16:28:21.684424: val_loss -0.7803 +2024-11-21 16:28:21.684556: Pseudo dice [0.8443] +2024-11-21 16:28:21.684646: Epoch time: 19.05 s +2024-11-21 16:28:22.504589: +2024-11-21 16:28:22.504793: Epoch 1040 +2024-11-21 16:28:22.504913: Current learning rate: 0.00882 +2024-11-21 16:28:42.108234: train_loss -0.7646 +2024-11-21 16:28:42.110717: val_loss -0.7585 +2024-11-21 16:28:42.110816: Pseudo dice [0.8519] +2024-11-21 16:28:42.110900: Epoch time: 19.6 s +2024-11-21 16:28:42.920929: +2024-11-21 16:28:42.921153: Epoch 1041 +2024-11-21 16:28:42.921276: Current learning rate: 0.00882 +2024-11-21 16:29:02.228838: train_loss -0.7661 +2024-11-21 16:29:02.234882: val_loss -0.7581 +2024-11-21 16:29:02.235014: Pseudo dice [0.8505] +2024-11-21 16:29:02.235144: Epoch time: 19.31 s +2024-11-21 16:29:03.061481: +2024-11-21 16:29:03.061723: Epoch 1042 +2024-11-21 16:29:03.061844: Current learning rate: 0.00882 +2024-11-21 16:29:21.807762: train_loss -0.7629 +2024-11-21 16:29:21.809706: val_loss -0.7457 +2024-11-21 16:29:21.809804: Pseudo dice [0.8414] +2024-11-21 16:29:21.809914: Epoch time: 18.75 s +2024-11-21 16:29:22.628392: +2024-11-21 16:29:22.628596: Epoch 1043 +2024-11-21 16:29:22.628719: Current learning rate: 0.00882 +2024-11-21 16:29:41.736749: train_loss -0.7573 +2024-11-21 16:29:41.743863: val_loss -0.7576 +2024-11-21 16:29:41.743998: Pseudo dice [0.8317] +2024-11-21 16:29:41.744109: Epoch time: 19.11 s +2024-11-21 16:29:42.802055: +2024-11-21 16:29:42.802263: Epoch 1044 +2024-11-21 16:29:42.802383: Current learning rate: 0.00882 +2024-11-21 16:30:01.153037: train_loss -0.768 +2024-11-21 16:30:01.158067: val_loss -0.7738 +2024-11-21 16:30:01.158207: Pseudo dice [0.85] +2024-11-21 16:30:01.158295: Epoch time: 18.35 s +2024-11-21 16:30:02.221098: +2024-11-21 16:30:02.221314: Epoch 1045 +2024-11-21 16:30:02.221437: Current learning rate: 0.00882 +2024-11-21 16:30:22.059436: train_loss -0.7665 +2024-11-21 16:30:22.061812: val_loss -0.7609 +2024-11-21 16:30:22.061918: Pseudo dice [0.8386] +2024-11-21 16:30:22.062010: Epoch time: 19.84 s +2024-11-21 16:30:22.877702: +2024-11-21 16:30:22.877919: Epoch 1046 +2024-11-21 16:30:22.878055: Current learning rate: 0.00882 +2024-11-21 16:30:41.971418: train_loss -0.7681 +2024-11-21 16:30:41.976773: val_loss -0.7475 +2024-11-21 16:30:41.976897: Pseudo dice [0.8438] +2024-11-21 16:30:41.976981: Epoch time: 19.09 s +2024-11-21 16:30:42.908312: +2024-11-21 16:30:42.908497: Epoch 1047 +2024-11-21 16:30:42.908618: Current learning rate: 0.00881 +2024-11-21 16:31:02.478812: train_loss -0.765 +2024-11-21 16:31:02.487008: val_loss -0.7688 +2024-11-21 16:31:02.487155: Pseudo dice [0.84] +2024-11-21 16:31:02.487253: Epoch time: 19.57 s +2024-11-21 16:31:03.349251: +2024-11-21 16:31:03.349483: Epoch 1048 +2024-11-21 16:31:03.349621: Current learning rate: 0.00881 +2024-11-21 16:31:22.050216: train_loss -0.7651 +2024-11-21 16:31:22.055019: val_loss -0.7278 +2024-11-21 16:31:22.055162: Pseudo dice [0.8563] +2024-11-21 16:31:22.055271: Epoch time: 18.7 s +2024-11-21 16:31:22.930868: +2024-11-21 16:31:22.931087: Epoch 1049 +2024-11-21 16:31:22.931214: Current learning rate: 0.00881 +2024-11-21 16:31:41.995000: train_loss -0.7749 +2024-11-21 16:31:41.999658: val_loss -0.771 +2024-11-21 16:31:41.999822: Pseudo dice [0.8532] +2024-11-21 16:31:41.999924: Epoch time: 19.06 s +2024-11-21 16:31:43.107701: +2024-11-21 16:31:43.107906: Epoch 1050 +2024-11-21 16:31:43.108033: Current learning rate: 0.00881 +2024-11-21 16:32:02.714593: train_loss -0.7788 +2024-11-21 16:32:02.721187: val_loss -0.7653 +2024-11-21 16:32:02.721338: Pseudo dice [0.8504] +2024-11-21 16:32:02.721446: Epoch time: 19.61 s +2024-11-21 16:32:03.620728: +2024-11-21 16:32:03.620942: Epoch 1051 +2024-11-21 16:32:03.621078: Current learning rate: 0.00881 +2024-11-21 16:32:22.433656: train_loss -0.7656 +2024-11-21 16:32:22.435534: val_loss -0.7612 +2024-11-21 16:32:22.435631: Pseudo dice [0.8529] +2024-11-21 16:32:22.435721: Epoch time: 18.81 s +2024-11-21 16:32:23.243885: +2024-11-21 16:32:23.244110: Epoch 1052 +2024-11-21 16:32:23.244238: Current learning rate: 0.00881 +2024-11-21 16:32:42.021478: train_loss -0.7646 +2024-11-21 16:32:42.027890: val_loss -0.752 +2024-11-21 16:32:42.028029: Pseudo dice [0.8525] +2024-11-21 16:32:42.028141: Epoch time: 18.78 s +2024-11-21 16:32:42.944292: +2024-11-21 16:32:42.944514: Epoch 1053 +2024-11-21 16:32:42.944624: Current learning rate: 0.00881 +2024-11-21 16:33:01.975652: train_loss -0.759 +2024-11-21 16:33:01.987969: val_loss -0.7498 +2024-11-21 16:33:01.988144: Pseudo dice [0.8416] +2024-11-21 16:33:01.988233: Epoch time: 19.03 s +2024-11-21 16:33:02.970620: +2024-11-21 16:33:02.970863: Epoch 1054 +2024-11-21 16:33:02.970998: Current learning rate: 0.00881 +2024-11-21 16:33:22.163039: train_loss -0.7499 +2024-11-21 16:33:22.170507: val_loss -0.7593 +2024-11-21 16:33:22.170637: Pseudo dice [0.8379] +2024-11-21 16:33:22.170722: Epoch time: 19.19 s +2024-11-21 16:33:23.069701: +2024-11-21 16:33:23.069951: Epoch 1055 +2024-11-21 16:33:23.070083: Current learning rate: 0.0088 +2024-11-21 16:33:41.819378: train_loss -0.764 +2024-11-21 16:33:41.828711: val_loss -0.7462 +2024-11-21 16:33:41.828940: Pseudo dice [0.8314] +2024-11-21 16:33:41.829051: Epoch time: 18.75 s +2024-11-21 16:33:42.653503: +2024-11-21 16:33:42.653711: Epoch 1056 +2024-11-21 16:33:42.653844: Current learning rate: 0.0088 +2024-11-21 16:34:01.195015: train_loss -0.7589 +2024-11-21 16:34:01.205929: val_loss -0.7551 +2024-11-21 16:34:01.206094: Pseudo dice [0.8464] +2024-11-21 16:34:01.206202: Epoch time: 18.54 s +2024-11-21 16:34:02.274832: +2024-11-21 16:34:02.275037: Epoch 1057 +2024-11-21 16:34:02.275156: Current learning rate: 0.0088 +2024-11-21 16:34:20.927095: train_loss -0.7624 +2024-11-21 16:34:20.930360: val_loss -0.7557 +2024-11-21 16:34:20.930492: Pseudo dice [0.8471] +2024-11-21 16:34:20.930601: Epoch time: 18.65 s +2024-11-21 16:34:21.744596: +2024-11-21 16:34:21.744806: Epoch 1058 +2024-11-21 16:34:21.744929: Current learning rate: 0.0088 +2024-11-21 16:34:40.818813: train_loss -0.765 +2024-11-21 16:34:40.825001: val_loss -0.7484 +2024-11-21 16:34:40.825127: Pseudo dice [0.8506] +2024-11-21 16:34:40.825213: Epoch time: 19.07 s +2024-11-21 16:34:41.815135: +2024-11-21 16:34:41.815351: Epoch 1059 +2024-11-21 16:34:41.815487: Current learning rate: 0.0088 +2024-11-21 16:35:00.485295: train_loss -0.7648 +2024-11-21 16:35:00.490307: val_loss -0.7781 +2024-11-21 16:35:00.490457: Pseudo dice [0.8499] +2024-11-21 16:35:00.490558: Epoch time: 18.67 s +2024-11-21 16:35:01.450164: +2024-11-21 16:35:01.450398: Epoch 1060 +2024-11-21 16:35:01.450553: Current learning rate: 0.0088 +2024-11-21 16:35:20.163591: train_loss -0.7729 +2024-11-21 16:35:20.171631: val_loss -0.7401 +2024-11-21 16:35:20.171787: Pseudo dice [0.833] +2024-11-21 16:35:20.171882: Epoch time: 18.71 s +2024-11-21 16:35:21.513327: +2024-11-21 16:35:21.513563: Epoch 1061 +2024-11-21 16:35:21.513688: Current learning rate: 0.0088 +2024-11-21 16:35:39.998029: train_loss -0.7295 +2024-11-21 16:35:40.001297: val_loss -0.7114 +2024-11-21 16:35:40.001470: Pseudo dice [0.8364] +2024-11-21 16:35:40.001581: Epoch time: 18.49 s +2024-11-21 16:35:40.850629: +2024-11-21 16:35:40.850885: Epoch 1062 +2024-11-21 16:35:40.851032: Current learning rate: 0.0088 +2024-11-21 16:35:59.582171: train_loss -0.741 +2024-11-21 16:35:59.591312: val_loss -0.7676 +2024-11-21 16:35:59.591434: Pseudo dice [0.8416] +2024-11-21 16:35:59.591528: Epoch time: 18.73 s +2024-11-21 16:36:00.556813: +2024-11-21 16:36:00.557021: Epoch 1063 +2024-11-21 16:36:00.557164: Current learning rate: 0.0088 +2024-11-21 16:36:19.522408: train_loss -0.751 +2024-11-21 16:36:19.531394: val_loss -0.748 +2024-11-21 16:36:19.531535: Pseudo dice [0.8371] +2024-11-21 16:36:19.531635: Epoch time: 18.97 s +2024-11-21 16:36:20.391689: +2024-11-21 16:36:20.391937: Epoch 1064 +2024-11-21 16:36:20.392083: Current learning rate: 0.00879 +2024-11-21 16:36:39.566734: train_loss -0.7514 +2024-11-21 16:36:39.571935: val_loss -0.7591 +2024-11-21 16:36:39.572320: Pseudo dice [0.8445] +2024-11-21 16:36:39.572425: Epoch time: 19.18 s +2024-11-21 16:36:40.395336: +2024-11-21 16:36:40.395545: Epoch 1065 +2024-11-21 16:36:40.395685: Current learning rate: 0.00879 +2024-11-21 16:37:00.319774: train_loss -0.7531 +2024-11-21 16:37:00.328272: val_loss -0.7618 +2024-11-21 16:37:00.328488: Pseudo dice [0.841] +2024-11-21 16:37:00.328575: Epoch time: 19.93 s +2024-11-21 16:37:01.310415: +2024-11-21 16:37:01.310621: Epoch 1066 +2024-11-21 16:37:01.310731: Current learning rate: 0.00879 +2024-11-21 16:37:20.240084: train_loss -0.7637 +2024-11-21 16:37:20.247103: val_loss -0.7351 +2024-11-21 16:37:20.247252: Pseudo dice [0.841] +2024-11-21 16:37:20.247340: Epoch time: 18.93 s +2024-11-21 16:37:21.165324: +2024-11-21 16:37:21.165538: Epoch 1067 +2024-11-21 16:37:21.165651: Current learning rate: 0.00879 +2024-11-21 16:37:41.247114: train_loss -0.751 +2024-11-21 16:37:41.253211: val_loss -0.7633 +2024-11-21 16:37:41.253371: Pseudo dice [0.8454] +2024-11-21 16:37:41.253472: Epoch time: 20.08 s +2024-11-21 16:37:42.120692: +2024-11-21 16:37:42.120924: Epoch 1068 +2024-11-21 16:37:42.121043: Current learning rate: 0.00879 +2024-11-21 16:38:01.888705: train_loss -0.771 +2024-11-21 16:38:01.890336: val_loss -0.7634 +2024-11-21 16:38:01.890455: Pseudo dice [0.8455] +2024-11-21 16:38:01.890539: Epoch time: 19.77 s +2024-11-21 16:38:02.860314: +2024-11-21 16:38:02.860510: Epoch 1069 +2024-11-21 16:38:02.860644: Current learning rate: 0.00879 +2024-11-21 16:38:21.797588: train_loss -0.7646 +2024-11-21 16:38:21.802636: val_loss -0.7721 +2024-11-21 16:38:21.802786: Pseudo dice [0.8535] +2024-11-21 16:38:21.802889: Epoch time: 18.94 s +2024-11-21 16:38:22.739180: +2024-11-21 16:38:22.739378: Epoch 1070 +2024-11-21 16:38:22.739505: Current learning rate: 0.00879 +2024-11-21 16:38:43.051981: train_loss -0.7612 +2024-11-21 16:38:43.054071: val_loss -0.7443 +2024-11-21 16:38:43.054188: Pseudo dice [0.8316] +2024-11-21 16:38:43.054303: Epoch time: 20.31 s +2024-11-21 16:38:43.872477: +2024-11-21 16:38:43.872742: Epoch 1071 +2024-11-21 16:38:43.872878: Current learning rate: 0.00879 +2024-11-21 16:39:03.631868: train_loss -0.7737 +2024-11-21 16:39:03.634590: val_loss -0.7645 +2024-11-21 16:39:03.634719: Pseudo dice [0.8362] +2024-11-21 16:39:03.634810: Epoch time: 19.76 s +2024-11-21 16:39:04.452802: +2024-11-21 16:39:04.453026: Epoch 1072 +2024-11-21 16:39:04.453159: Current learning rate: 0.00879 +2024-11-21 16:39:24.022180: train_loss -0.7641 +2024-11-21 16:39:24.029970: val_loss -0.7644 +2024-11-21 16:39:24.030122: Pseudo dice [0.8605] +2024-11-21 16:39:24.030211: Epoch time: 19.57 s +2024-11-21 16:39:25.241032: +2024-11-21 16:39:25.241282: Epoch 1073 +2024-11-21 16:39:25.241415: Current learning rate: 0.00878 +2024-11-21 16:39:43.855128: train_loss -0.7715 +2024-11-21 16:39:43.862429: val_loss -0.7546 +2024-11-21 16:39:43.862566: Pseudo dice [0.8375] +2024-11-21 16:39:43.862662: Epoch time: 18.61 s +2024-11-21 16:39:44.814081: +2024-11-21 16:39:44.814294: Epoch 1074 +2024-11-21 16:39:44.814415: Current learning rate: 0.00878 +2024-11-21 16:40:04.661673: train_loss -0.7594 +2024-11-21 16:40:04.667538: val_loss -0.7518 +2024-11-21 16:40:04.667659: Pseudo dice [0.8395] +2024-11-21 16:40:04.667760: Epoch time: 19.85 s +2024-11-21 16:40:05.591884: +2024-11-21 16:40:05.592117: Epoch 1075 +2024-11-21 16:40:05.592254: Current learning rate: 0.00878 +2024-11-21 16:40:25.145305: train_loss -0.7666 +2024-11-21 16:40:25.150684: val_loss -0.7646 +2024-11-21 16:40:25.150836: Pseudo dice [0.8381] +2024-11-21 16:40:25.150927: Epoch time: 19.55 s +2024-11-21 16:40:26.097760: +2024-11-21 16:40:26.097960: Epoch 1076 +2024-11-21 16:40:26.098084: Current learning rate: 0.00878 +2024-11-21 16:40:44.402379: train_loss -0.7628 +2024-11-21 16:40:44.412893: val_loss -0.7536 +2024-11-21 16:40:44.413042: Pseudo dice [0.8459] +2024-11-21 16:40:44.413144: Epoch time: 18.31 s +2024-11-21 16:40:45.242798: +2024-11-21 16:40:45.243055: Epoch 1077 +2024-11-21 16:40:45.243199: Current learning rate: 0.00878 +2024-11-21 16:41:04.601234: train_loss -0.7613 +2024-11-21 16:41:04.608347: val_loss -0.7411 +2024-11-21 16:41:04.608458: Pseudo dice [0.8369] +2024-11-21 16:41:04.608553: Epoch time: 19.36 s +2024-11-21 16:41:05.466641: +2024-11-21 16:41:05.466924: Epoch 1078 +2024-11-21 16:41:05.467068: Current learning rate: 0.00878 +2024-11-21 16:41:24.920086: train_loss -0.774 +2024-11-21 16:41:24.927238: val_loss -0.7318 +2024-11-21 16:41:24.927380: Pseudo dice [0.8425] +2024-11-21 16:41:24.927466: Epoch time: 19.45 s +2024-11-21 16:41:25.751956: +2024-11-21 16:41:25.752190: Epoch 1079 +2024-11-21 16:41:25.752338: Current learning rate: 0.00878 +2024-11-21 16:41:44.855319: train_loss -0.7597 +2024-11-21 16:41:44.860982: val_loss -0.7444 +2024-11-21 16:41:44.861106: Pseudo dice [0.8405] +2024-11-21 16:41:44.861268: Epoch time: 19.1 s +2024-11-21 16:41:45.678417: +2024-11-21 16:41:45.678630: Epoch 1080 +2024-11-21 16:41:45.678736: Current learning rate: 0.00878 +2024-11-21 16:42:05.144651: train_loss -0.7496 +2024-11-21 16:42:05.153032: val_loss -0.7595 +2024-11-21 16:42:05.153179: Pseudo dice [0.8447] +2024-11-21 16:42:05.153276: Epoch time: 19.47 s +2024-11-21 16:42:05.992172: +2024-11-21 16:42:05.992395: Epoch 1081 +2024-11-21 16:42:05.992513: Current learning rate: 0.00878 +2024-11-21 16:42:25.155323: train_loss -0.7604 +2024-11-21 16:42:25.162232: val_loss -0.746 +2024-11-21 16:42:25.162429: Pseudo dice [0.8426] +2024-11-21 16:42:25.162535: Epoch time: 19.16 s +2024-11-21 16:42:26.099235: +2024-11-21 16:42:26.099435: Epoch 1082 +2024-11-21 16:42:26.099563: Current learning rate: 0.00877 +2024-11-21 16:42:45.108852: train_loss -0.7601 +2024-11-21 16:42:45.114848: val_loss -0.7759 +2024-11-21 16:42:45.114986: Pseudo dice [0.8613] +2024-11-21 16:42:45.115099: Epoch time: 19.01 s +2024-11-21 16:42:46.075740: +2024-11-21 16:42:46.075957: Epoch 1083 +2024-11-21 16:42:46.076080: Current learning rate: 0.00877 +2024-11-21 16:43:05.269836: train_loss -0.7671 +2024-11-21 16:43:05.277539: val_loss -0.7749 +2024-11-21 16:43:05.277680: Pseudo dice [0.8548] +2024-11-21 16:43:05.277771: Epoch time: 19.19 s +2024-11-21 16:43:06.860698: +2024-11-21 16:43:06.860904: Epoch 1084 +2024-11-21 16:43:06.861124: Current learning rate: 0.00877 +2024-11-21 16:43:25.202032: train_loss -0.7642 +2024-11-21 16:43:25.211198: val_loss -0.7686 +2024-11-21 16:43:25.211329: Pseudo dice [0.8496] +2024-11-21 16:43:25.211437: Epoch time: 18.34 s +2024-11-21 16:43:26.171323: +2024-11-21 16:43:26.171522: Epoch 1085 +2024-11-21 16:43:26.171653: Current learning rate: 0.00877 +2024-11-21 16:43:45.989204: train_loss -0.7591 +2024-11-21 16:43:45.995097: val_loss -0.7583 +2024-11-21 16:43:45.995236: Pseudo dice [0.8472] +2024-11-21 16:43:45.995323: Epoch time: 19.82 s +2024-11-21 16:43:46.811297: +2024-11-21 16:43:46.811536: Epoch 1086 +2024-11-21 16:43:46.811653: Current learning rate: 0.00877 +2024-11-21 16:44:06.094512: train_loss -0.7527 +2024-11-21 16:44:06.102554: val_loss -0.7592 +2024-11-21 16:44:06.102686: Pseudo dice [0.8436] +2024-11-21 16:44:06.102770: Epoch time: 19.28 s +2024-11-21 16:44:06.947420: +2024-11-21 16:44:06.947629: Epoch 1087 +2024-11-21 16:44:06.947750: Current learning rate: 0.00877 +2024-11-21 16:44:25.589236: train_loss -0.7294 +2024-11-21 16:44:25.591817: val_loss -0.7663 +2024-11-21 16:44:25.591930: Pseudo dice [0.8414] +2024-11-21 16:44:25.592026: Epoch time: 18.64 s +2024-11-21 16:44:26.407189: +2024-11-21 16:44:26.407429: Epoch 1088 +2024-11-21 16:44:26.407569: Current learning rate: 0.00877 +2024-11-21 16:44:45.658897: train_loss -0.7542 +2024-11-21 16:44:45.663476: val_loss -0.7627 +2024-11-21 16:44:45.663620: Pseudo dice [0.8434] +2024-11-21 16:44:45.663712: Epoch time: 19.25 s +2024-11-21 16:44:46.481032: +2024-11-21 16:44:46.481244: Epoch 1089 +2024-11-21 16:44:46.481384: Current learning rate: 0.00877 +2024-11-21 16:45:04.816938: train_loss -0.7464 +2024-11-21 16:45:04.822040: val_loss -0.7642 +2024-11-21 16:45:04.822238: Pseudo dice [0.8485] +2024-11-21 16:45:04.822343: Epoch time: 18.34 s +2024-11-21 16:45:05.654455: +2024-11-21 16:45:05.654689: Epoch 1090 +2024-11-21 16:45:05.654803: Current learning rate: 0.00876 +2024-11-21 16:45:25.301490: train_loss -0.7572 +2024-11-21 16:45:25.307259: val_loss -0.7495 +2024-11-21 16:45:25.307370: Pseudo dice [0.8341] +2024-11-21 16:45:25.307476: Epoch time: 19.65 s +2024-11-21 16:45:26.159802: +2024-11-21 16:45:26.159990: Epoch 1091 +2024-11-21 16:45:26.160147: Current learning rate: 0.00876 +2024-11-21 16:45:45.076720: train_loss -0.7654 +2024-11-21 16:45:45.109026: val_loss -0.7385 +2024-11-21 16:45:45.109203: Pseudo dice [0.8503] +2024-11-21 16:45:45.109300: Epoch time: 18.92 s +2024-11-21 16:45:46.192452: +2024-11-21 16:45:46.192641: Epoch 1092 +2024-11-21 16:45:46.192782: Current learning rate: 0.00876 +2024-11-21 16:46:04.617405: train_loss -0.7618 +2024-11-21 16:46:04.625087: val_loss -0.7289 +2024-11-21 16:46:04.625203: Pseudo dice [0.8334] +2024-11-21 16:46:04.625304: Epoch time: 18.43 s +2024-11-21 16:46:05.625638: +2024-11-21 16:46:05.625824: Epoch 1093 +2024-11-21 16:46:05.625935: Current learning rate: 0.00876 +2024-11-21 16:46:24.584461: train_loss -0.7634 +2024-11-21 16:46:24.586776: val_loss -0.7206 +2024-11-21 16:46:24.586915: Pseudo dice [0.8314] +2024-11-21 16:46:24.587017: Epoch time: 18.96 s +2024-11-21 16:46:25.397377: +2024-11-21 16:46:25.397606: Epoch 1094 +2024-11-21 16:46:25.397732: Current learning rate: 0.00876 +2024-11-21 16:46:44.426364: train_loss -0.7662 +2024-11-21 16:46:44.431016: val_loss -0.7762 +2024-11-21 16:46:44.431162: Pseudo dice [0.8476] +2024-11-21 16:46:44.431254: Epoch time: 19.03 s +2024-11-21 16:46:45.269338: +2024-11-21 16:46:45.269555: Epoch 1095 +2024-11-21 16:46:45.269666: Current learning rate: 0.00876 +2024-11-21 16:47:04.134822: train_loss -0.7704 +2024-11-21 16:47:04.158673: val_loss -0.7568 +2024-11-21 16:47:04.158846: Pseudo dice [0.8408] +2024-11-21 16:47:04.158940: Epoch time: 18.87 s +2024-11-21 16:47:05.402682: +2024-11-21 16:47:05.402891: Epoch 1096 +2024-11-21 16:47:05.403021: Current learning rate: 0.00876 +2024-11-21 16:47:25.606213: train_loss -0.7677 +2024-11-21 16:47:25.612296: val_loss -0.75 +2024-11-21 16:47:25.612430: Pseudo dice [0.836] +2024-11-21 16:47:25.612524: Epoch time: 20.2 s +2024-11-21 16:47:26.511025: +2024-11-21 16:47:26.511238: Epoch 1097 +2024-11-21 16:47:26.511476: Current learning rate: 0.00876 +2024-11-21 16:47:45.652519: train_loss -0.7653 +2024-11-21 16:47:45.666964: val_loss -0.7612 +2024-11-21 16:47:45.667110: Pseudo dice [0.8448] +2024-11-21 16:47:45.667194: Epoch time: 19.14 s +2024-11-21 16:47:46.503528: +2024-11-21 16:47:46.503744: Epoch 1098 +2024-11-21 16:47:46.503854: Current learning rate: 0.00876 +2024-11-21 16:48:06.788299: train_loss -0.7586 +2024-11-21 16:48:06.792032: val_loss -0.755 +2024-11-21 16:48:06.792152: Pseudo dice [0.8474] +2024-11-21 16:48:06.792237: Epoch time: 20.29 s +2024-11-21 16:48:07.605719: +2024-11-21 16:48:07.605969: Epoch 1099 +2024-11-21 16:48:07.606104: Current learning rate: 0.00875 +2024-11-21 16:48:26.376972: train_loss -0.7514 +2024-11-21 16:48:26.385770: val_loss -0.7618 +2024-11-21 16:48:26.386007: Pseudo dice [0.8555] +2024-11-21 16:48:26.386113: Epoch time: 18.77 s +2024-11-21 16:48:27.510482: +2024-11-21 16:48:27.510693: Epoch 1100 +2024-11-21 16:48:27.510826: Current learning rate: 0.00875 +2024-11-21 16:48:45.812052: train_loss -0.7663 +2024-11-21 16:48:45.817053: val_loss -0.7697 +2024-11-21 16:48:45.817183: Pseudo dice [0.8439] +2024-11-21 16:48:45.817296: Epoch time: 18.3 s +2024-11-21 16:48:46.720535: +2024-11-21 16:48:46.720747: Epoch 1101 +2024-11-21 16:48:46.720873: Current learning rate: 0.00875 +2024-11-21 16:49:05.520660: train_loss -0.7621 +2024-11-21 16:49:05.529596: val_loss -0.7378 +2024-11-21 16:49:05.529750: Pseudo dice [0.8542] +2024-11-21 16:49:05.529838: Epoch time: 18.8 s +2024-11-21 16:49:06.373034: +2024-11-21 16:49:06.373268: Epoch 1102 +2024-11-21 16:49:06.373401: Current learning rate: 0.00875 +2024-11-21 16:49:25.965677: train_loss -0.75 +2024-11-21 16:49:25.972122: val_loss -0.7335 +2024-11-21 16:49:25.972474: Pseudo dice [0.83] +2024-11-21 16:49:25.972564: Epoch time: 19.59 s +2024-11-21 16:49:26.841327: +2024-11-21 16:49:26.841536: Epoch 1103 +2024-11-21 16:49:26.841666: Current learning rate: 0.00875 +2024-11-21 16:49:45.240431: train_loss -0.7521 +2024-11-21 16:49:45.247595: val_loss -0.753 +2024-11-21 16:49:45.247741: Pseudo dice [0.8331] +2024-11-21 16:49:45.247849: Epoch time: 18.4 s +2024-11-21 16:49:46.225192: +2024-11-21 16:49:46.225415: Epoch 1104 +2024-11-21 16:49:46.225542: Current learning rate: 0.00875 +2024-11-21 16:50:05.094811: train_loss -0.7622 +2024-11-21 16:50:05.098505: val_loss -0.7459 +2024-11-21 16:50:05.098616: Pseudo dice [0.8537] +2024-11-21 16:50:05.098712: Epoch time: 18.87 s +2024-11-21 16:50:05.906880: +2024-11-21 16:50:05.907109: Epoch 1105 +2024-11-21 16:50:05.907220: Current learning rate: 0.00875 +2024-11-21 16:50:24.907397: train_loss -0.7603 +2024-11-21 16:50:24.925328: val_loss -0.7743 +2024-11-21 16:50:24.925480: Pseudo dice [0.8399] +2024-11-21 16:50:24.925575: Epoch time: 19.0 s +2024-11-21 16:50:25.879849: +2024-11-21 16:50:25.880096: Epoch 1106 +2024-11-21 16:50:25.880230: Current learning rate: 0.00875 +2024-11-21 16:50:44.417506: train_loss -0.7687 +2024-11-21 16:50:44.423465: val_loss -0.7491 +2024-11-21 16:50:44.423622: Pseudo dice [0.8377] +2024-11-21 16:50:44.423720: Epoch time: 18.54 s +2024-11-21 16:50:45.793025: +2024-11-21 16:50:45.793255: Epoch 1107 +2024-11-21 16:50:45.793378: Current learning rate: 0.00875 +2024-11-21 16:51:03.958097: train_loss -0.7687 +2024-11-21 16:51:03.975318: val_loss -0.753 +2024-11-21 16:51:03.975495: Pseudo dice [0.854] +2024-11-21 16:51:03.975591: Epoch time: 18.17 s +2024-11-21 16:51:04.825798: +2024-11-21 16:51:04.826040: Epoch 1108 +2024-11-21 16:51:04.826185: Current learning rate: 0.00874 +2024-11-21 16:51:22.700278: train_loss -0.7683 +2024-11-21 16:51:22.705694: val_loss -0.7499 +2024-11-21 16:51:22.705826: Pseudo dice [0.8466] +2024-11-21 16:51:22.705931: Epoch time: 17.88 s +2024-11-21 16:51:23.520416: +2024-11-21 16:51:23.520696: Epoch 1109 +2024-11-21 16:51:23.520819: Current learning rate: 0.00874 +2024-11-21 16:51:42.039795: train_loss -0.7551 +2024-11-21 16:51:42.054209: val_loss -0.7684 +2024-11-21 16:51:42.054346: Pseudo dice [0.8489] +2024-11-21 16:51:42.054445: Epoch time: 18.52 s +2024-11-21 16:51:43.052751: +2024-11-21 16:51:43.052971: Epoch 1110 +2024-11-21 16:51:43.053094: Current learning rate: 0.00874 +2024-11-21 16:52:01.697448: train_loss -0.7623 +2024-11-21 16:52:01.716743: val_loss -0.7637 +2024-11-21 16:52:01.716904: Pseudo dice [0.8488] +2024-11-21 16:52:01.717016: Epoch time: 18.64 s +2024-11-21 16:52:02.671254: +2024-11-21 16:52:02.671467: Epoch 1111 +2024-11-21 16:52:02.671592: Current learning rate: 0.00874 +2024-11-21 16:52:21.623844: train_loss -0.7572 +2024-11-21 16:52:21.630358: val_loss -0.7741 +2024-11-21 16:52:21.630487: Pseudo dice [0.8483] +2024-11-21 16:52:21.630588: Epoch time: 18.95 s +2024-11-21 16:52:22.540052: +2024-11-21 16:52:22.540280: Epoch 1112 +2024-11-21 16:52:22.540403: Current learning rate: 0.00874 +2024-11-21 16:52:42.464535: train_loss -0.7558 +2024-11-21 16:52:42.467911: val_loss -0.7682 +2024-11-21 16:52:42.468010: Pseudo dice [0.854] +2024-11-21 16:52:42.468104: Epoch time: 19.93 s +2024-11-21 16:52:43.280456: +2024-11-21 16:52:43.280691: Epoch 1113 +2024-11-21 16:52:43.280801: Current learning rate: 0.00874 +2024-11-21 16:53:02.057750: train_loss -0.7494 +2024-11-21 16:53:02.063766: val_loss -0.7831 +2024-11-21 16:53:02.063912: Pseudo dice [0.8629] +2024-11-21 16:53:02.064018: Epoch time: 18.78 s +2024-11-21 16:53:03.038363: +2024-11-21 16:53:03.038569: Epoch 1114 +2024-11-21 16:53:03.038702: Current learning rate: 0.00874 +2024-11-21 16:53:21.813502: train_loss -0.7638 +2024-11-21 16:53:21.818827: val_loss -0.7705 +2024-11-21 16:53:21.818960: Pseudo dice [0.8453] +2024-11-21 16:53:21.819069: Epoch time: 18.78 s +2024-11-21 16:53:22.654026: +2024-11-21 16:53:22.654237: Epoch 1115 +2024-11-21 16:53:22.654361: Current learning rate: 0.00874 +2024-11-21 16:53:42.219417: train_loss -0.742 +2024-11-21 16:53:42.223933: val_loss -0.7233 +2024-11-21 16:53:42.224082: Pseudo dice [0.8177] +2024-11-21 16:53:42.224193: Epoch time: 19.57 s +2024-11-21 16:53:43.287468: +2024-11-21 16:53:43.287741: Epoch 1116 +2024-11-21 16:53:43.287875: Current learning rate: 0.00874 +2024-11-21 16:54:02.784652: train_loss -0.7221 +2024-11-21 16:54:02.790478: val_loss -0.7486 +2024-11-21 16:54:02.790601: Pseudo dice [0.8533] +2024-11-21 16:54:02.790694: Epoch time: 19.5 s +2024-11-21 16:54:03.648240: +2024-11-21 16:54:03.648464: Epoch 1117 +2024-11-21 16:54:03.648584: Current learning rate: 0.00873 +2024-11-21 16:54:22.002396: train_loss -0.7463 +2024-11-21 16:54:22.009919: val_loss -0.752 +2024-11-21 16:54:22.010071: Pseudo dice [0.8304] +2024-11-21 16:54:22.010169: Epoch time: 18.35 s +2024-11-21 16:54:23.458962: +2024-11-21 16:54:23.459194: Epoch 1118 +2024-11-21 16:54:23.459310: Current learning rate: 0.00873 +2024-11-21 16:54:42.061100: train_loss -0.7485 +2024-11-21 16:54:42.068416: val_loss -0.7504 +2024-11-21 16:54:42.068564: Pseudo dice [0.8353] +2024-11-21 16:54:42.068657: Epoch time: 18.6 s +2024-11-21 16:54:42.930036: +2024-11-21 16:54:42.930299: Epoch 1119 +2024-11-21 16:54:42.930421: Current learning rate: 0.00873 +2024-11-21 16:55:02.869366: train_loss -0.7546 +2024-11-21 16:55:02.891561: val_loss -0.7401 +2024-11-21 16:55:02.891685: Pseudo dice [0.8344] +2024-11-21 16:55:02.891768: Epoch time: 19.94 s +2024-11-21 16:55:03.702539: +2024-11-21 16:55:03.702737: Epoch 1120 +2024-11-21 16:55:03.702853: Current learning rate: 0.00873 +2024-11-21 16:55:23.076256: train_loss -0.7416 +2024-11-21 16:55:23.089522: val_loss -0.7533 +2024-11-21 16:55:23.089681: Pseudo dice [0.8428] +2024-11-21 16:55:23.089799: Epoch time: 19.37 s +2024-11-21 16:55:24.025759: +2024-11-21 16:55:24.025960: Epoch 1121 +2024-11-21 16:55:24.026081: Current learning rate: 0.00873 +2024-11-21 16:55:43.189591: train_loss -0.7634 +2024-11-21 16:55:43.208217: val_loss -0.7505 +2024-11-21 16:55:43.208373: Pseudo dice [0.8375] +2024-11-21 16:55:43.208471: Epoch time: 19.16 s +2024-11-21 16:55:44.026860: +2024-11-21 16:55:44.027068: Epoch 1122 +2024-11-21 16:55:44.027193: Current learning rate: 0.00873 +2024-11-21 16:56:04.322428: train_loss -0.7623 +2024-11-21 16:56:04.330018: val_loss -0.7585 +2024-11-21 16:56:04.330161: Pseudo dice [0.8398] +2024-11-21 16:56:04.330273: Epoch time: 20.3 s +2024-11-21 16:56:05.427937: +2024-11-21 16:56:05.428387: Epoch 1123 +2024-11-21 16:56:05.428524: Current learning rate: 0.00873 +2024-11-21 16:56:25.251907: train_loss -0.7601 +2024-11-21 16:56:25.258091: val_loss -0.7609 +2024-11-21 16:56:25.258230: Pseudo dice [0.8452] +2024-11-21 16:56:25.258325: Epoch time: 19.82 s +2024-11-21 16:56:26.216369: +2024-11-21 16:56:26.216577: Epoch 1124 +2024-11-21 16:56:26.216702: Current learning rate: 0.00873 +2024-11-21 16:56:45.705360: train_loss -0.7608 +2024-11-21 16:56:45.712669: val_loss -0.768 +2024-11-21 16:56:45.712815: Pseudo dice [0.8508] +2024-11-21 16:56:45.712914: Epoch time: 19.49 s +2024-11-21 16:56:46.575419: +2024-11-21 16:56:46.576093: Epoch 1125 +2024-11-21 16:56:46.576226: Current learning rate: 0.00872 +2024-11-21 16:57:06.438314: train_loss -0.7536 +2024-11-21 16:57:06.449683: val_loss -0.7355 +2024-11-21 16:57:06.449843: Pseudo dice [0.8237] +2024-11-21 16:57:06.449960: Epoch time: 19.86 s +2024-11-21 16:57:07.293594: +2024-11-21 16:57:07.293831: Epoch 1126 +2024-11-21 16:57:07.293956: Current learning rate: 0.00872 +2024-11-21 16:57:25.605168: train_loss -0.7532 +2024-11-21 16:57:25.611993: val_loss -0.7599 +2024-11-21 16:57:25.612198: Pseudo dice [0.8427] +2024-11-21 16:57:25.612292: Epoch time: 18.31 s +2024-11-21 16:57:26.428080: +2024-11-21 16:57:26.428279: Epoch 1127 +2024-11-21 16:57:26.428400: Current learning rate: 0.00872 +2024-11-21 16:57:45.665785: train_loss -0.7512 +2024-11-21 16:57:45.683614: val_loss -0.7688 +2024-11-21 16:57:45.683761: Pseudo dice [0.838] +2024-11-21 16:57:45.683848: Epoch time: 19.24 s +2024-11-21 16:57:46.498632: +2024-11-21 16:57:46.498821: Epoch 1128 +2024-11-21 16:57:46.499166: Current learning rate: 0.00872 +2024-11-21 16:58:05.175325: train_loss -0.7622 +2024-11-21 16:58:05.182810: val_loss -0.7449 +2024-11-21 16:58:05.182926: Pseudo dice [0.8397] +2024-11-21 16:58:05.183015: Epoch time: 18.68 s +2024-11-21 16:58:06.404442: +2024-11-21 16:58:06.404649: Epoch 1129 +2024-11-21 16:58:06.404770: Current learning rate: 0.00872 +2024-11-21 16:58:25.858348: train_loss -0.7622 +2024-11-21 16:58:25.862401: val_loss -0.7719 +2024-11-21 16:58:25.862579: Pseudo dice [0.8347] +2024-11-21 16:58:25.862675: Epoch time: 19.45 s +2024-11-21 16:58:26.708176: +2024-11-21 16:58:26.708393: Epoch 1130 +2024-11-21 16:58:26.708518: Current learning rate: 0.00872 +2024-11-21 16:58:45.862271: train_loss -0.7581 +2024-11-21 16:58:45.869786: val_loss -0.7486 +2024-11-21 16:58:45.869934: Pseudo dice [0.833] +2024-11-21 16:58:45.870014: Epoch time: 19.15 s +2024-11-21 16:58:46.799540: +2024-11-21 16:58:46.799785: Epoch 1131 +2024-11-21 16:58:46.799915: Current learning rate: 0.00872 +2024-11-21 16:59:05.356594: train_loss -0.7737 +2024-11-21 16:59:05.358482: val_loss -0.7702 +2024-11-21 16:59:05.358596: Pseudo dice [0.8491] +2024-11-21 16:59:05.358703: Epoch time: 18.56 s +2024-11-21 16:59:06.180344: +2024-11-21 16:59:06.180561: Epoch 1132 +2024-11-21 16:59:06.180696: Current learning rate: 0.00872 +2024-11-21 16:59:25.814572: train_loss -0.7571 +2024-11-21 16:59:25.821499: val_loss -0.7587 +2024-11-21 16:59:25.821629: Pseudo dice [0.8399] +2024-11-21 16:59:25.821722: Epoch time: 19.64 s +2024-11-21 16:59:26.661118: +2024-11-21 16:59:26.661324: Epoch 1133 +2024-11-21 16:59:26.661451: Current learning rate: 0.00872 +2024-11-21 16:59:44.893260: train_loss -0.767 +2024-11-21 16:59:44.966065: val_loss -0.7676 +2024-11-21 16:59:44.966257: Pseudo dice [0.8456] +2024-11-21 16:59:44.966351: Epoch time: 18.23 s +2024-11-21 16:59:45.961039: +2024-11-21 16:59:45.961288: Epoch 1134 +2024-11-21 16:59:45.961417: Current learning rate: 0.00871 +2024-11-21 17:00:04.266577: train_loss -0.7617 +2024-11-21 17:00:04.290903: val_loss -0.7659 +2024-11-21 17:00:04.291088: Pseudo dice [0.8348] +2024-11-21 17:00:04.291199: Epoch time: 18.31 s +2024-11-21 17:00:05.136006: +2024-11-21 17:00:05.136610: Epoch 1135 +2024-11-21 17:00:05.136723: Current learning rate: 0.00871 +2024-11-21 17:00:25.038435: train_loss -0.7598 +2024-11-21 17:00:25.057671: val_loss -0.7648 +2024-11-21 17:00:25.057860: Pseudo dice [0.8452] +2024-11-21 17:00:25.057981: Epoch time: 19.9 s +2024-11-21 17:00:25.881862: +2024-11-21 17:00:25.882130: Epoch 1136 +2024-11-21 17:00:25.882260: Current learning rate: 0.00871 +2024-11-21 17:00:45.419980: train_loss -0.7712 +2024-11-21 17:00:45.491046: val_loss -0.7524 +2024-11-21 17:00:45.491213: Pseudo dice [0.8396] +2024-11-21 17:00:45.491309: Epoch time: 19.54 s +2024-11-21 17:00:46.423057: +2024-11-21 17:00:46.423304: Epoch 1137 +2024-11-21 17:00:46.423419: Current learning rate: 0.00871 +2024-11-21 17:01:06.002213: train_loss -0.7693 +2024-11-21 17:01:06.016008: val_loss -0.7642 +2024-11-21 17:01:06.016181: Pseudo dice [0.8454] +2024-11-21 17:01:06.016279: Epoch time: 19.58 s +2024-11-21 17:01:06.836752: +2024-11-21 17:01:06.836999: Epoch 1138 +2024-11-21 17:01:06.837142: Current learning rate: 0.00871 +2024-11-21 17:01:24.821129: train_loss -0.7643 +2024-11-21 17:01:24.823951: val_loss -0.7841 +2024-11-21 17:01:24.824186: Pseudo dice [0.8481] +2024-11-21 17:01:24.824301: Epoch time: 17.99 s +2024-11-21 17:01:25.644481: +2024-11-21 17:01:25.644678: Epoch 1139 +2024-11-21 17:01:25.644805: Current learning rate: 0.00871 +2024-11-21 17:01:44.727764: train_loss -0.7619 +2024-11-21 17:01:44.741019: val_loss -0.7793 +2024-11-21 17:01:44.741252: Pseudo dice [0.8532] +2024-11-21 17:01:44.741355: Epoch time: 19.08 s +2024-11-21 17:01:45.564496: +2024-11-21 17:01:45.564717: Epoch 1140 +2024-11-21 17:01:45.564855: Current learning rate: 0.00871 +2024-11-21 17:02:05.719546: train_loss -0.7623 +2024-11-21 17:02:05.732739: val_loss -0.7523 +2024-11-21 17:02:05.732887: Pseudo dice [0.8458] +2024-11-21 17:02:05.733218: Epoch time: 20.16 s +2024-11-21 17:02:07.118955: +2024-11-21 17:02:07.119215: Epoch 1141 +2024-11-21 17:02:07.119336: Current learning rate: 0.00871 +2024-11-21 17:02:26.232371: train_loss -0.7652 +2024-11-21 17:02:26.257863: val_loss -0.7567 +2024-11-21 17:02:26.258054: Pseudo dice [0.8263] +2024-11-21 17:02:26.258178: Epoch time: 19.11 s +2024-11-21 17:02:27.095594: +2024-11-21 17:02:27.095810: Epoch 1142 +2024-11-21 17:02:27.095950: Current learning rate: 0.00871 +2024-11-21 17:02:46.790158: train_loss -0.7606 +2024-11-21 17:02:46.807700: val_loss -0.7546 +2024-11-21 17:02:46.807886: Pseudo dice [0.8344] +2024-11-21 17:02:46.807995: Epoch time: 19.7 s +2024-11-21 17:02:47.795733: +2024-11-21 17:02:47.795957: Epoch 1143 +2024-11-21 17:02:47.796071: Current learning rate: 0.0087 +2024-11-21 17:03:05.494112: train_loss -0.7585 +2024-11-21 17:03:05.524406: val_loss -0.7836 +2024-11-21 17:03:05.524580: Pseudo dice [0.8472] +2024-11-21 17:03:05.524690: Epoch time: 17.7 s +2024-11-21 17:03:06.424687: +2024-11-21 17:03:06.424890: Epoch 1144 +2024-11-21 17:03:06.425005: Current learning rate: 0.0087 +2024-11-21 17:03:25.715197: train_loss -0.7701 +2024-11-21 17:03:25.732553: val_loss -0.7644 +2024-11-21 17:03:25.732702: Pseudo dice [0.8493] +2024-11-21 17:03:25.732782: Epoch time: 19.29 s +2024-11-21 17:03:26.657627: +2024-11-21 17:03:26.657850: Epoch 1145 +2024-11-21 17:03:26.657976: Current learning rate: 0.0087 +2024-11-21 17:03:45.281698: train_loss -0.7547 +2024-11-21 17:03:45.299241: val_loss -0.7562 +2024-11-21 17:03:45.299412: Pseudo dice [0.8264] +2024-11-21 17:03:45.299502: Epoch time: 18.62 s +2024-11-21 17:03:46.133044: +2024-11-21 17:03:46.133280: Epoch 1146 +2024-11-21 17:03:46.133419: Current learning rate: 0.0087 +2024-11-21 17:04:05.203425: train_loss -0.765 +2024-11-21 17:04:05.210665: val_loss -0.7565 +2024-11-21 17:04:05.210793: Pseudo dice [0.845] +2024-11-21 17:04:05.210888: Epoch time: 19.07 s +2024-11-21 17:04:06.256092: +2024-11-21 17:04:06.256344: Epoch 1147 +2024-11-21 17:04:06.256507: Current learning rate: 0.0087 +2024-11-21 17:04:24.831697: train_loss -0.7646 +2024-11-21 17:04:24.832810: val_loss -0.7437 +2024-11-21 17:04:24.832921: Pseudo dice [0.8432] +2024-11-21 17:04:24.833025: Epoch time: 18.58 s +2024-11-21 17:04:25.653246: +2024-11-21 17:04:25.653486: Epoch 1148 +2024-11-21 17:04:25.653599: Current learning rate: 0.0087 +2024-11-21 17:04:44.320819: train_loss -0.7584 +2024-11-21 17:04:44.327397: val_loss -0.7539 +2024-11-21 17:04:44.327564: Pseudo dice [0.8441] +2024-11-21 17:04:44.327668: Epoch time: 18.67 s +2024-11-21 17:04:45.185783: +2024-11-21 17:04:45.186013: Epoch 1149 +2024-11-21 17:04:45.186134: Current learning rate: 0.0087 +2024-11-21 17:05:04.532047: train_loss -0.7713 +2024-11-21 17:05:04.540819: val_loss -0.7625 +2024-11-21 17:05:04.540997: Pseudo dice [0.8463] +2024-11-21 17:05:04.541130: Epoch time: 19.35 s +2024-11-21 17:05:05.661544: +2024-11-21 17:05:05.661744: Epoch 1150 +2024-11-21 17:05:05.661862: Current learning rate: 0.0087 +2024-11-21 17:05:23.549512: train_loss -0.7738 +2024-11-21 17:05:23.566754: val_loss -0.7811 +2024-11-21 17:05:23.566922: Pseudo dice [0.8417] +2024-11-21 17:05:23.567016: Epoch time: 17.89 s +2024-11-21 17:05:24.793508: +2024-11-21 17:05:24.793720: Epoch 1151 +2024-11-21 17:05:24.793840: Current learning rate: 0.0087 +2024-11-21 17:05:44.641103: train_loss -0.7571 +2024-11-21 17:05:44.674126: val_loss -0.7676 +2024-11-21 17:05:44.674283: Pseudo dice [0.8355] +2024-11-21 17:05:44.674371: Epoch time: 19.85 s +2024-11-21 17:05:46.013299: +2024-11-21 17:05:46.013511: Epoch 1152 +2024-11-21 17:05:46.013631: Current learning rate: 0.00869 +2024-11-21 17:06:04.764390: train_loss -0.7565 +2024-11-21 17:06:04.766294: val_loss -0.7639 +2024-11-21 17:06:04.766414: Pseudo dice [0.8411] +2024-11-21 17:06:04.766512: Epoch time: 18.75 s +2024-11-21 17:06:05.582198: +2024-11-21 17:06:05.582396: Epoch 1153 +2024-11-21 17:06:05.582513: Current learning rate: 0.00869 +2024-11-21 17:06:24.718037: train_loss -0.7576 +2024-11-21 17:06:24.725148: val_loss -0.7683 +2024-11-21 17:06:24.725335: Pseudo dice [0.8614] +2024-11-21 17:06:24.725443: Epoch time: 19.14 s +2024-11-21 17:06:25.580386: +2024-11-21 17:06:25.580613: Epoch 1154 +2024-11-21 17:06:25.580746: Current learning rate: 0.00869 +2024-11-21 17:06:45.004483: train_loss -0.7619 +2024-11-21 17:06:45.024159: val_loss -0.7682 +2024-11-21 17:06:45.024320: Pseudo dice [0.852] +2024-11-21 17:06:45.024417: Epoch time: 19.42 s +2024-11-21 17:06:46.101542: +2024-11-21 17:06:46.101786: Epoch 1155 +2024-11-21 17:06:46.101919: Current learning rate: 0.00869 +2024-11-21 17:07:05.824813: train_loss -0.758 +2024-11-21 17:07:05.840643: val_loss -0.7727 +2024-11-21 17:07:05.840812: Pseudo dice [0.8397] +2024-11-21 17:07:05.840902: Epoch time: 19.72 s +2024-11-21 17:07:06.724860: +2024-11-21 17:07:06.725152: Epoch 1156 +2024-11-21 17:07:06.725277: Current learning rate: 0.00869 +2024-11-21 17:07:25.057192: train_loss -0.7596 +2024-11-21 17:07:25.064305: val_loss -0.7674 +2024-11-21 17:07:25.064444: Pseudo dice [0.8357] +2024-11-21 17:07:25.064550: Epoch time: 18.33 s +2024-11-21 17:07:25.909255: +2024-11-21 17:07:25.909478: Epoch 1157 +2024-11-21 17:07:25.909603: Current learning rate: 0.00869 +2024-11-21 17:07:44.400073: train_loss -0.7688 +2024-11-21 17:07:44.423866: val_loss -0.7317 +2024-11-21 17:07:44.424028: Pseudo dice [0.8386] +2024-11-21 17:07:44.424143: Epoch time: 18.49 s +2024-11-21 17:07:45.264161: +2024-11-21 17:07:45.264354: Epoch 1158 +2024-11-21 17:07:45.264474: Current learning rate: 0.00869 +2024-11-21 17:08:03.368008: train_loss -0.7666 +2024-11-21 17:08:03.390547: val_loss -0.7491 +2024-11-21 17:08:03.390716: Pseudo dice [0.8415] +2024-11-21 17:08:03.390811: Epoch time: 18.1 s +2024-11-21 17:08:04.321279: +2024-11-21 17:08:04.321484: Epoch 1159 +2024-11-21 17:08:04.321599: Current learning rate: 0.00869 +2024-11-21 17:08:22.367337: train_loss -0.744 +2024-11-21 17:08:22.370673: val_loss -0.7573 +2024-11-21 17:08:22.370799: Pseudo dice [0.8422] +2024-11-21 17:08:22.370907: Epoch time: 18.05 s +2024-11-21 17:08:23.198138: +2024-11-21 17:08:23.198367: Epoch 1160 +2024-11-21 17:08:23.198492: Current learning rate: 0.00868 +2024-11-21 17:08:41.916328: train_loss -0.7558 +2024-11-21 17:08:41.921615: val_loss -0.733 +2024-11-21 17:08:41.921732: Pseudo dice [0.8491] +2024-11-21 17:08:41.921830: Epoch time: 18.72 s +2024-11-21 17:08:42.751485: +2024-11-21 17:08:42.751701: Epoch 1161 +2024-11-21 17:08:42.751824: Current learning rate: 0.00868 +2024-11-21 17:09:01.607601: train_loss -0.767 +2024-11-21 17:09:01.614558: val_loss -0.7472 +2024-11-21 17:09:01.614741: Pseudo dice [0.8404] +2024-11-21 17:09:01.614839: Epoch time: 18.86 s +2024-11-21 17:09:02.556997: +2024-11-21 17:09:02.557209: Epoch 1162 +2024-11-21 17:09:02.557333: Current learning rate: 0.00868 +2024-11-21 17:09:20.821527: train_loss -0.7651 +2024-11-21 17:09:20.828720: val_loss -0.763 +2024-11-21 17:09:20.828860: Pseudo dice [0.8449] +2024-11-21 17:09:20.828945: Epoch time: 18.27 s +2024-11-21 17:09:22.050433: +2024-11-21 17:09:22.050639: Epoch 1163 +2024-11-21 17:09:22.050754: Current learning rate: 0.00868 +2024-11-21 17:09:40.129094: train_loss -0.7647 +2024-11-21 17:09:40.148769: val_loss -0.7474 +2024-11-21 17:09:40.148872: Pseudo dice [0.8481] +2024-11-21 17:09:40.148956: Epoch time: 18.08 s +2024-11-21 17:09:40.966458: +2024-11-21 17:09:40.966661: Epoch 1164 +2024-11-21 17:09:40.966774: Current learning rate: 0.00868 +2024-11-21 17:09:59.694817: train_loss -0.7752 +2024-11-21 17:09:59.707155: val_loss -0.784 +2024-11-21 17:09:59.707292: Pseudo dice [0.8559] +2024-11-21 17:09:59.707398: Epoch time: 18.73 s +2024-11-21 17:10:00.629940: +2024-11-21 17:10:00.630140: Epoch 1165 +2024-11-21 17:10:00.630263: Current learning rate: 0.00868 +2024-11-21 17:10:19.401775: train_loss -0.7683 +2024-11-21 17:10:19.409891: val_loss -0.7779 +2024-11-21 17:10:19.410052: Pseudo dice [0.8453] +2024-11-21 17:10:19.410158: Epoch time: 18.77 s +2024-11-21 17:10:20.339584: +2024-11-21 17:10:20.339792: Epoch 1166 +2024-11-21 17:10:20.340185: Current learning rate: 0.00868 +2024-11-21 17:10:39.865907: train_loss -0.7676 +2024-11-21 17:10:39.890478: val_loss -0.7367 +2024-11-21 17:10:39.890647: Pseudo dice [0.8335] +2024-11-21 17:10:39.890754: Epoch time: 19.53 s +2024-11-21 17:10:40.725233: +2024-11-21 17:10:40.725469: Epoch 1167 +2024-11-21 17:10:40.725607: Current learning rate: 0.00868 +2024-11-21 17:10:59.792037: train_loss -0.7585 +2024-11-21 17:10:59.796787: val_loss -0.7548 +2024-11-21 17:10:59.796906: Pseudo dice [0.843] +2024-11-21 17:10:59.797004: Epoch time: 19.07 s +2024-11-21 17:11:00.618174: +2024-11-21 17:11:00.618421: Epoch 1168 +2024-11-21 17:11:00.618546: Current learning rate: 0.00868 +2024-11-21 17:11:19.390903: train_loss -0.7583 +2024-11-21 17:11:19.406949: val_loss -0.7554 +2024-11-21 17:11:19.407069: Pseudo dice [0.8459] +2024-11-21 17:11:19.407173: Epoch time: 18.77 s +2024-11-21 17:11:20.229441: +2024-11-21 17:11:20.229667: Epoch 1169 +2024-11-21 17:11:20.229787: Current learning rate: 0.00867 +2024-11-21 17:11:39.670535: train_loss -0.7693 +2024-11-21 17:11:39.693184: val_loss -0.7453 +2024-11-21 17:11:39.693341: Pseudo dice [0.8395] +2024-11-21 17:11:39.693433: Epoch time: 19.44 s +2024-11-21 17:11:40.630190: +2024-11-21 17:11:40.630400: Epoch 1170 +2024-11-21 17:11:40.630533: Current learning rate: 0.00867 +2024-11-21 17:12:00.503629: train_loss -0.7579 +2024-11-21 17:12:00.523547: val_loss -0.7457 +2024-11-21 17:12:00.523723: Pseudo dice [0.8457] +2024-11-21 17:12:00.523822: Epoch time: 19.87 s +2024-11-21 17:12:01.456325: +2024-11-21 17:12:01.456545: Epoch 1171 +2024-11-21 17:12:01.456669: Current learning rate: 0.00867 +2024-11-21 17:12:19.286652: train_loss -0.7624 +2024-11-21 17:12:19.298558: val_loss -0.7667 +2024-11-21 17:12:19.298749: Pseudo dice [0.844] +2024-11-21 17:12:19.298850: Epoch time: 17.83 s +2024-11-21 17:12:20.136803: +2024-11-21 17:12:20.137036: Epoch 1172 +2024-11-21 17:12:20.137172: Current learning rate: 0.00867 +2024-11-21 17:12:38.195354: train_loss -0.7571 +2024-11-21 17:12:38.204591: val_loss -0.7695 +2024-11-21 17:12:38.204731: Pseudo dice [0.8457] +2024-11-21 17:12:38.204881: Epoch time: 18.06 s +2024-11-21 17:12:39.129541: +2024-11-21 17:12:39.129743: Epoch 1173 +2024-11-21 17:12:39.129863: Current learning rate: 0.00867 +2024-11-21 17:12:58.341118: train_loss -0.7681 +2024-11-21 17:12:58.356743: val_loss -0.7442 +2024-11-21 17:12:58.356914: Pseudo dice [0.8376] +2024-11-21 17:12:58.357014: Epoch time: 19.21 s +2024-11-21 17:12:59.571873: +2024-11-21 17:12:59.572111: Epoch 1174 +2024-11-21 17:12:59.572225: Current learning rate: 0.00867 +2024-11-21 17:13:18.021098: train_loss -0.7738 +2024-11-21 17:13:18.040014: val_loss -0.7645 +2024-11-21 17:13:18.040188: Pseudo dice [0.8498] +2024-11-21 17:13:18.040296: Epoch time: 18.45 s +2024-11-21 17:13:18.936239: +2024-11-21 17:13:18.936447: Epoch 1175 +2024-11-21 17:13:18.936574: Current learning rate: 0.00867 +2024-11-21 17:13:38.299884: train_loss -0.7633 +2024-11-21 17:13:38.323292: val_loss -0.7796 +2024-11-21 17:13:38.323450: Pseudo dice [0.8562] +2024-11-21 17:13:38.323557: Epoch time: 19.36 s +2024-11-21 17:13:39.158102: +2024-11-21 17:13:39.158325: Epoch 1176 +2024-11-21 17:13:39.158448: Current learning rate: 0.00867 +2024-11-21 17:13:58.395142: train_loss -0.7452 +2024-11-21 17:13:58.397796: val_loss -0.773 +2024-11-21 17:13:58.397913: Pseudo dice [0.8342] +2024-11-21 17:13:58.398003: Epoch time: 19.24 s +2024-11-21 17:13:59.227620: +2024-11-21 17:13:59.227837: Epoch 1177 +2024-11-21 17:13:59.227972: Current learning rate: 0.00867 +2024-11-21 17:14:16.935356: train_loss -0.7817 +2024-11-21 17:14:16.956498: val_loss -0.7485 +2024-11-21 17:14:16.956678: Pseudo dice [0.8391] +2024-11-21 17:14:16.956808: Epoch time: 17.71 s +2024-11-21 17:14:17.786208: +2024-11-21 17:14:17.786477: Epoch 1178 +2024-11-21 17:14:17.786600: Current learning rate: 0.00866 +2024-11-21 17:14:37.581233: train_loss -0.7735 +2024-11-21 17:14:37.610175: val_loss -0.7639 +2024-11-21 17:14:37.610322: Pseudo dice [0.8537] +2024-11-21 17:14:37.610457: Epoch time: 19.8 s +2024-11-21 17:14:38.652127: +2024-11-21 17:14:38.652326: Epoch 1179 +2024-11-21 17:14:38.652444: Current learning rate: 0.00866 +2024-11-21 17:14:57.372858: train_loss -0.7436 +2024-11-21 17:14:57.414875: val_loss -0.7193 +2024-11-21 17:14:57.415050: Pseudo dice [0.8339] +2024-11-21 17:14:57.415160: Epoch time: 18.72 s +2024-11-21 17:14:58.287401: +2024-11-21 17:14:58.287603: Epoch 1180 +2024-11-21 17:14:58.287724: Current learning rate: 0.00866 +2024-11-21 17:15:17.851354: train_loss -0.7579 +2024-11-21 17:15:17.873051: val_loss -0.759 +2024-11-21 17:15:17.873218: Pseudo dice [0.8493] +2024-11-21 17:15:17.873314: Epoch time: 19.56 s +2024-11-21 17:15:19.110931: +2024-11-21 17:15:19.111152: Epoch 1181 +2024-11-21 17:15:19.111267: Current learning rate: 0.00866 +2024-11-21 17:15:39.013231: train_loss -0.7656 +2024-11-21 17:15:39.026512: val_loss -0.7395 +2024-11-21 17:15:39.026672: Pseudo dice [0.8414] +2024-11-21 17:15:39.026761: Epoch time: 19.9 s +2024-11-21 17:15:40.076934: +2024-11-21 17:15:40.077159: Epoch 1182 +2024-11-21 17:15:40.077302: Current learning rate: 0.00866 +2024-11-21 17:15:59.794265: train_loss -0.7631 +2024-11-21 17:15:59.814580: val_loss -0.7699 +2024-11-21 17:15:59.814757: Pseudo dice [0.852] +2024-11-21 17:15:59.814859: Epoch time: 19.72 s +2024-11-21 17:16:00.698042: +2024-11-21 17:16:00.698266: Epoch 1183 +2024-11-21 17:16:00.698389: Current learning rate: 0.00866 +2024-11-21 17:16:20.134850: train_loss -0.7465 +2024-11-21 17:16:20.145890: val_loss -0.7544 +2024-11-21 17:16:20.146025: Pseudo dice [0.8355] +2024-11-21 17:16:20.146135: Epoch time: 19.44 s +2024-11-21 17:16:20.971561: +2024-11-21 17:16:20.971786: Epoch 1184 +2024-11-21 17:16:20.971915: Current learning rate: 0.00866 +2024-11-21 17:16:40.328467: train_loss -0.7493 +2024-11-21 17:16:40.333160: val_loss -0.7397 +2024-11-21 17:16:40.333288: Pseudo dice [0.84] +2024-11-21 17:16:40.333370: Epoch time: 19.36 s +2024-11-21 17:16:41.636672: +2024-11-21 17:16:41.636887: Epoch 1185 +2024-11-21 17:16:41.637019: Current learning rate: 0.00866 +2024-11-21 17:17:00.472738: train_loss -0.7527 +2024-11-21 17:17:00.497877: val_loss -0.7598 +2024-11-21 17:17:00.498044: Pseudo dice [0.8482] +2024-11-21 17:17:00.498149: Epoch time: 18.84 s +2024-11-21 17:17:01.468577: +2024-11-21 17:17:01.468802: Epoch 1186 +2024-11-21 17:17:01.468935: Current learning rate: 0.00866 +2024-11-21 17:17:20.579876: train_loss -0.7545 +2024-11-21 17:17:20.597810: val_loss -0.7431 +2024-11-21 17:17:20.597980: Pseudo dice [0.8435] +2024-11-21 17:17:20.598094: Epoch time: 19.11 s +2024-11-21 17:17:21.439177: +2024-11-21 17:17:21.439373: Epoch 1187 +2024-11-21 17:17:21.439492: Current learning rate: 0.00865 +2024-11-21 17:17:40.525751: train_loss -0.7544 +2024-11-21 17:17:40.547773: val_loss -0.7587 +2024-11-21 17:17:40.547932: Pseudo dice [0.8512] +2024-11-21 17:17:40.548027: Epoch time: 19.09 s +2024-11-21 17:17:41.530302: +2024-11-21 17:17:41.530502: Epoch 1188 +2024-11-21 17:17:41.530625: Current learning rate: 0.00865 +2024-11-21 17:18:00.686248: train_loss -0.7569 +2024-11-21 17:18:00.705922: val_loss -0.7202 +2024-11-21 17:18:00.706108: Pseudo dice [0.8227] +2024-11-21 17:18:00.706229: Epoch time: 19.16 s +2024-11-21 17:18:01.723178: +2024-11-21 17:18:01.723404: Epoch 1189 +2024-11-21 17:18:01.723524: Current learning rate: 0.00865 +2024-11-21 17:18:21.023082: train_loss -0.7624 +2024-11-21 17:18:21.029270: val_loss -0.7667 +2024-11-21 17:18:21.029422: Pseudo dice [0.8486] +2024-11-21 17:18:21.029546: Epoch time: 19.3 s +2024-11-21 17:18:21.872538: +2024-11-21 17:18:21.872761: Epoch 1190 +2024-11-21 17:18:21.872894: Current learning rate: 0.00865 +2024-11-21 17:18:40.664102: train_loss -0.7639 +2024-11-21 17:18:40.697521: val_loss -0.7497 +2024-11-21 17:18:40.697685: Pseudo dice [0.8543] +2024-11-21 17:18:40.697791: Epoch time: 18.79 s +2024-11-21 17:18:41.544638: +2024-11-21 17:18:41.544835: Epoch 1191 +2024-11-21 17:18:41.544950: Current learning rate: 0.00865 +2024-11-21 17:18:59.539231: train_loss -0.7634 +2024-11-21 17:18:59.546768: val_loss -0.7371 +2024-11-21 17:18:59.558025: Pseudo dice [0.8446] +2024-11-21 17:18:59.558199: Epoch time: 18.0 s +2024-11-21 17:19:00.544845: +2024-11-21 17:19:00.545052: Epoch 1192 +2024-11-21 17:19:00.545190: Current learning rate: 0.00865 +2024-11-21 17:19:19.831633: train_loss -0.7668 +2024-11-21 17:19:19.838276: val_loss -0.7616 +2024-11-21 17:19:19.838473: Pseudo dice [0.8351] +2024-11-21 17:19:19.838576: Epoch time: 19.29 s +2024-11-21 17:19:20.799803: +2024-11-21 17:19:20.800045: Epoch 1193 +2024-11-21 17:19:20.800167: Current learning rate: 0.00865 +2024-11-21 17:19:39.478196: train_loss -0.7534 +2024-11-21 17:19:39.481372: val_loss -0.7354 +2024-11-21 17:19:39.481480: Pseudo dice [0.8314] +2024-11-21 17:19:39.481682: Epoch time: 18.68 s +2024-11-21 17:19:40.304878: +2024-11-21 17:19:40.305122: Epoch 1194 +2024-11-21 17:19:40.305255: Current learning rate: 0.00865 +2024-11-21 17:19:59.433915: train_loss -0.7741 +2024-11-21 17:19:59.440502: val_loss -0.7671 +2024-11-21 17:19:59.440627: Pseudo dice [0.8561] +2024-11-21 17:19:59.440712: Epoch time: 19.13 s +2024-11-21 17:20:00.429652: +2024-11-21 17:20:00.429929: Epoch 1195 +2024-11-21 17:20:00.430077: Current learning rate: 0.00864 +2024-11-21 17:20:20.312861: train_loss -0.7618 +2024-11-21 17:20:20.316451: val_loss -0.7704 +2024-11-21 17:20:20.316571: Pseudo dice [0.8491] +2024-11-21 17:20:20.316655: Epoch time: 19.88 s +2024-11-21 17:20:21.524720: +2024-11-21 17:20:21.524966: Epoch 1196 +2024-11-21 17:20:21.525094: Current learning rate: 0.00864 +2024-11-21 17:20:40.717484: train_loss -0.7634 +2024-11-21 17:20:40.721190: val_loss -0.7563 +2024-11-21 17:20:40.721395: Pseudo dice [0.8494] +2024-11-21 17:20:40.721494: Epoch time: 19.19 s +2024-11-21 17:20:41.604637: +2024-11-21 17:20:41.604896: Epoch 1197 +2024-11-21 17:20:41.605037: Current learning rate: 0.00864 +2024-11-21 17:21:00.981199: train_loss -0.7598 +2024-11-21 17:21:01.003687: val_loss -0.755 +2024-11-21 17:21:01.003813: Pseudo dice [0.8446] +2024-11-21 17:21:01.003917: Epoch time: 19.38 s +2024-11-21 17:21:01.832357: +2024-11-21 17:21:01.832591: Epoch 1198 +2024-11-21 17:21:01.832719: Current learning rate: 0.00864 +2024-11-21 17:21:20.958168: train_loss -0.7641 +2024-11-21 17:21:20.961977: val_loss -0.7361 +2024-11-21 17:21:20.962114: Pseudo dice [0.8457] +2024-11-21 17:21:20.962210: Epoch time: 19.13 s +2024-11-21 17:21:21.902706: +2024-11-21 17:21:21.902918: Epoch 1199 +2024-11-21 17:21:21.903056: Current learning rate: 0.00864 +2024-11-21 17:21:40.287419: train_loss -0.7574 +2024-11-21 17:21:40.294730: val_loss -0.7666 +2024-11-21 17:21:40.294884: Pseudo dice [0.835] +2024-11-21 17:21:40.294968: Epoch time: 18.39 s +2024-11-21 17:21:41.560799: +2024-11-21 17:21:41.561017: Epoch 1200 +2024-11-21 17:21:41.561158: Current learning rate: 0.00864 +2024-11-21 17:22:01.108379: train_loss -0.7665 +2024-11-21 17:22:01.116435: val_loss -0.7654 +2024-11-21 17:22:01.116575: Pseudo dice [0.8432] +2024-11-21 17:22:01.116994: Epoch time: 19.55 s +2024-11-21 17:22:02.039027: +2024-11-21 17:22:02.039252: Epoch 1201 +2024-11-21 17:22:02.039376: Current learning rate: 0.00864 +2024-11-21 17:22:20.631908: train_loss -0.7696 +2024-11-21 17:22:20.638588: val_loss -0.7525 +2024-11-21 17:22:20.638758: Pseudo dice [0.8623] +2024-11-21 17:22:20.638893: Epoch time: 18.59 s +2024-11-21 17:22:21.467609: +2024-11-21 17:22:21.467819: Epoch 1202 +2024-11-21 17:22:21.467942: Current learning rate: 0.00864 +2024-11-21 17:22:40.284836: train_loss -0.7691 +2024-11-21 17:22:40.293954: val_loss -0.7685 +2024-11-21 17:22:40.294081: Pseudo dice [0.8461] +2024-11-21 17:22:40.294169: Epoch time: 18.82 s +2024-11-21 17:22:41.309254: +2024-11-21 17:22:41.309457: Epoch 1203 +2024-11-21 17:22:41.309590: Current learning rate: 0.00864 +2024-11-21 17:23:00.181127: train_loss -0.7693 +2024-11-21 17:23:00.184309: val_loss -0.7418 +2024-11-21 17:23:00.184451: Pseudo dice [0.8363] +2024-11-21 17:23:00.184539: Epoch time: 18.87 s +2024-11-21 17:23:01.191749: +2024-11-21 17:23:01.191979: Epoch 1204 +2024-11-21 17:23:01.192141: Current learning rate: 0.00863 +2024-11-21 17:23:19.560427: train_loss -0.7766 +2024-11-21 17:23:19.566075: val_loss -0.7511 +2024-11-21 17:23:19.566209: Pseudo dice [0.8483] +2024-11-21 17:23:19.566309: Epoch time: 18.37 s +2024-11-21 17:23:20.453894: +2024-11-21 17:23:20.454091: Epoch 1205 +2024-11-21 17:23:20.454211: Current learning rate: 0.00863 +2024-11-21 17:23:39.451711: train_loss -0.7695 +2024-11-21 17:23:39.460050: val_loss -0.7644 +2024-11-21 17:23:39.460198: Pseudo dice [0.8525] +2024-11-21 17:23:39.460282: Epoch time: 19.0 s +2024-11-21 17:23:40.285830: +2024-11-21 17:23:40.286073: Epoch 1206 +2024-11-21 17:23:40.286201: Current learning rate: 0.00863 +2024-11-21 17:23:59.252301: train_loss -0.7781 +2024-11-21 17:23:59.284630: val_loss -0.7734 +2024-11-21 17:23:59.284748: Pseudo dice [0.8512] +2024-11-21 17:23:59.284849: Epoch time: 18.97 s +2024-11-21 17:24:00.471716: +2024-11-21 17:24:00.471922: Epoch 1207 +2024-11-21 17:24:00.472054: Current learning rate: 0.00863 +2024-11-21 17:24:20.119873: train_loss -0.7717 +2024-11-21 17:24:20.126894: val_loss -0.776 +2024-11-21 17:24:20.127018: Pseudo dice [0.8534] +2024-11-21 17:24:20.127134: Epoch time: 19.65 s +2024-11-21 17:24:20.993439: +2024-11-21 17:24:20.993661: Epoch 1208 +2024-11-21 17:24:20.993797: Current learning rate: 0.00863 +2024-11-21 17:24:39.287555: train_loss -0.7745 +2024-11-21 17:24:39.298834: val_loss -0.756 +2024-11-21 17:24:39.298975: Pseudo dice [0.8349] +2024-11-21 17:24:39.299080: Epoch time: 18.29 s +2024-11-21 17:24:40.160467: +2024-11-21 17:24:40.160699: Epoch 1209 +2024-11-21 17:24:40.160835: Current learning rate: 0.00863 +2024-11-21 17:24:58.714362: train_loss -0.7658 +2024-11-21 17:24:58.720516: val_loss -0.7643 +2024-11-21 17:24:58.720660: Pseudo dice [0.856] +2024-11-21 17:24:58.720749: Epoch time: 18.55 s +2024-11-21 17:24:59.586731: +2024-11-21 17:24:59.586952: Epoch 1210 +2024-11-21 17:24:59.587091: Current learning rate: 0.00863 +2024-11-21 17:25:18.053751: train_loss -0.7569 +2024-11-21 17:25:18.059850: val_loss -0.7678 +2024-11-21 17:25:18.059978: Pseudo dice [0.8465] +2024-11-21 17:25:18.060073: Epoch time: 18.47 s +2024-11-21 17:25:19.023485: +2024-11-21 17:25:19.023680: Epoch 1211 +2024-11-21 17:25:19.023811: Current learning rate: 0.00863 +2024-11-21 17:25:38.139605: train_loss -0.7678 +2024-11-21 17:25:38.142462: val_loss -0.7406 +2024-11-21 17:25:38.142554: Pseudo dice [0.8284] +2024-11-21 17:25:38.142648: Epoch time: 19.12 s +2024-11-21 17:25:38.970450: +2024-11-21 17:25:38.970685: Epoch 1212 +2024-11-21 17:25:38.970814: Current learning rate: 0.00863 +2024-11-21 17:25:57.948398: train_loss -0.7579 +2024-11-21 17:25:57.952428: val_loss -0.7657 +2024-11-21 17:25:57.952576: Pseudo dice [0.8419] +2024-11-21 17:25:57.952664: Epoch time: 18.98 s +2024-11-21 17:25:58.848876: +2024-11-21 17:25:58.849080: Epoch 1213 +2024-11-21 17:25:58.849199: Current learning rate: 0.00862 +2024-11-21 17:26:18.381873: train_loss -0.7634 +2024-11-21 17:26:18.385300: val_loss -0.7497 +2024-11-21 17:26:18.385396: Pseudo dice [0.8508] +2024-11-21 17:26:18.385487: Epoch time: 19.53 s +2024-11-21 17:26:19.214657: +2024-11-21 17:26:19.214883: Epoch 1214 +2024-11-21 17:26:19.215001: Current learning rate: 0.00862 +2024-11-21 17:26:37.580976: train_loss -0.7705 +2024-11-21 17:26:37.587988: val_loss -0.7564 +2024-11-21 17:26:37.588126: Pseudo dice [0.8392] +2024-11-21 17:26:37.588208: Epoch time: 18.37 s +2024-11-21 17:26:38.411628: +2024-11-21 17:26:38.411832: Epoch 1215 +2024-11-21 17:26:38.411941: Current learning rate: 0.00862 +2024-11-21 17:26:57.529634: train_loss -0.7613 +2024-11-21 17:26:57.532366: val_loss -0.757 +2024-11-21 17:26:57.532534: Pseudo dice [0.8488] +2024-11-21 17:26:57.532623: Epoch time: 19.12 s +2024-11-21 17:26:58.355436: +2024-11-21 17:26:58.355642: Epoch 1216 +2024-11-21 17:26:58.355777: Current learning rate: 0.00862 +2024-11-21 17:27:16.722945: train_loss -0.7688 +2024-11-21 17:27:16.729327: val_loss -0.7703 +2024-11-21 17:27:16.729464: Pseudo dice [0.8505] +2024-11-21 17:27:16.729567: Epoch time: 18.37 s +2024-11-21 17:27:17.706355: +2024-11-21 17:27:17.706538: Epoch 1217 +2024-11-21 17:27:17.706652: Current learning rate: 0.00862 +2024-11-21 17:27:35.734744: train_loss -0.7562 +2024-11-21 17:27:35.743885: val_loss -0.7552 +2024-11-21 17:27:35.744024: Pseudo dice [0.8305] +2024-11-21 17:27:35.744131: Epoch time: 18.03 s +2024-11-21 17:27:37.009841: +2024-11-21 17:27:37.010062: Epoch 1218 +2024-11-21 17:27:37.010196: Current learning rate: 0.00862 +2024-11-21 17:27:56.503660: train_loss -0.7738 +2024-11-21 17:27:56.513771: val_loss -0.7756 +2024-11-21 17:27:56.513903: Pseudo dice [0.8436] +2024-11-21 17:27:56.514001: Epoch time: 19.49 s +2024-11-21 17:27:57.548331: +2024-11-21 17:27:57.548546: Epoch 1219 +2024-11-21 17:27:57.548672: Current learning rate: 0.00862 +2024-11-21 17:28:16.939881: train_loss -0.7603 +2024-11-21 17:28:16.944649: val_loss -0.7607 +2024-11-21 17:28:16.944773: Pseudo dice [0.844] +2024-11-21 17:28:16.944866: Epoch time: 19.39 s +2024-11-21 17:28:17.930690: +2024-11-21 17:28:17.930913: Epoch 1220 +2024-11-21 17:28:17.931026: Current learning rate: 0.00862 +2024-11-21 17:28:37.594076: train_loss -0.7662 +2024-11-21 17:28:37.611752: val_loss -0.7623 +2024-11-21 17:28:37.611890: Pseudo dice [0.8374] +2024-11-21 17:28:37.611978: Epoch time: 19.66 s +2024-11-21 17:28:38.501642: +2024-11-21 17:28:38.501907: Epoch 1221 +2024-11-21 17:28:38.502033: Current learning rate: 0.00862 +2024-11-21 17:28:55.730913: train_loss -0.7658 +2024-11-21 17:28:55.734665: val_loss -0.744 +2024-11-21 17:28:55.734782: Pseudo dice [0.8217] +2024-11-21 17:28:55.734862: Epoch time: 17.23 s +2024-11-21 17:28:56.560459: +2024-11-21 17:28:56.560680: Epoch 1222 +2024-11-21 17:28:56.560810: Current learning rate: 0.00861 +2024-11-21 17:29:15.520310: train_loss -0.7622 +2024-11-21 17:29:15.527562: val_loss -0.7658 +2024-11-21 17:29:15.527712: Pseudo dice [0.8488] +2024-11-21 17:29:15.527827: Epoch time: 18.96 s +2024-11-21 17:29:16.381329: +2024-11-21 17:29:16.381568: Epoch 1223 +2024-11-21 17:29:16.381701: Current learning rate: 0.00861 +2024-11-21 17:29:35.786414: train_loss -0.7652 +2024-11-21 17:29:35.789888: val_loss -0.7584 +2024-11-21 17:29:35.790019: Pseudo dice [0.8258] +2024-11-21 17:29:35.790110: Epoch time: 19.41 s +2024-11-21 17:29:36.613482: +2024-11-21 17:29:36.613706: Epoch 1224 +2024-11-21 17:29:36.613832: Current learning rate: 0.00861 +2024-11-21 17:29:55.822663: train_loss -0.7645 +2024-11-21 17:29:55.846541: val_loss -0.7526 +2024-11-21 17:29:55.846709: Pseudo dice [0.8392] +2024-11-21 17:29:55.846817: Epoch time: 19.21 s +2024-11-21 17:29:56.674278: +2024-11-21 17:29:56.674476: Epoch 1225 +2024-11-21 17:29:56.674603: Current learning rate: 0.00861 +2024-11-21 17:30:16.292725: train_loss -0.7594 +2024-11-21 17:30:16.300351: val_loss -0.751 +2024-11-21 17:30:16.300468: Pseudo dice [0.8533] +2024-11-21 17:30:16.300578: Epoch time: 19.62 s +2024-11-21 17:30:17.373606: +2024-11-21 17:30:17.373811: Epoch 1226 +2024-11-21 17:30:17.373938: Current learning rate: 0.00861 +2024-11-21 17:30:36.896548: train_loss -0.7589 +2024-11-21 17:30:36.917778: val_loss -0.7345 +2024-11-21 17:30:36.917946: Pseudo dice [0.8486] +2024-11-21 17:30:36.918314: Epoch time: 19.52 s +2024-11-21 17:30:37.748173: +2024-11-21 17:30:37.748391: Epoch 1227 +2024-11-21 17:30:37.748510: Current learning rate: 0.00861 +2024-11-21 17:30:56.973796: train_loss -0.7599 +2024-11-21 17:30:56.982723: val_loss -0.7378 +2024-11-21 17:30:56.982873: Pseudo dice [0.8449] +2024-11-21 17:30:56.983043: Epoch time: 19.23 s +2024-11-21 17:30:57.815963: +2024-11-21 17:30:57.816192: Epoch 1228 +2024-11-21 17:30:57.816313: Current learning rate: 0.00861 +2024-11-21 17:31:16.602008: train_loss -0.7607 +2024-11-21 17:31:16.607405: val_loss -0.7698 +2024-11-21 17:31:16.607552: Pseudo dice [0.8534] +2024-11-21 17:31:16.607640: Epoch time: 18.79 s +2024-11-21 17:31:17.955694: +2024-11-21 17:31:17.955937: Epoch 1229 +2024-11-21 17:31:17.956067: Current learning rate: 0.00861 +2024-11-21 17:31:37.705135: train_loss -0.7656 +2024-11-21 17:31:37.712643: val_loss -0.7409 +2024-11-21 17:31:37.712978: Pseudo dice [0.8493] +2024-11-21 17:31:37.713078: Epoch time: 19.75 s +2024-11-21 17:31:38.698939: +2024-11-21 17:31:38.699156: Epoch 1230 +2024-11-21 17:31:38.699270: Current learning rate: 0.0086 +2024-11-21 17:31:56.923964: train_loss -0.7712 +2024-11-21 17:31:56.928594: val_loss -0.7518 +2024-11-21 17:31:56.928709: Pseudo dice [0.8428] +2024-11-21 17:31:56.928854: Epoch time: 18.23 s +2024-11-21 17:31:57.755350: +2024-11-21 17:31:57.755556: Epoch 1231 +2024-11-21 17:31:57.755689: Current learning rate: 0.0086 +2024-11-21 17:32:17.635135: train_loss -0.7526 +2024-11-21 17:32:17.638101: val_loss -0.7704 +2024-11-21 17:32:17.638214: Pseudo dice [0.8547] +2024-11-21 17:32:17.638308: Epoch time: 19.88 s +2024-11-21 17:32:18.463719: +2024-11-21 17:32:18.463934: Epoch 1232 +2024-11-21 17:32:18.464053: Current learning rate: 0.0086 +2024-11-21 17:32:38.109917: train_loss -0.7667 +2024-11-21 17:32:38.117095: val_loss -0.7567 +2024-11-21 17:32:38.117228: Pseudo dice [0.8413] +2024-11-21 17:32:38.117325: Epoch time: 19.65 s +2024-11-21 17:32:39.078937: +2024-11-21 17:32:39.079150: Epoch 1233 +2024-11-21 17:32:39.079275: Current learning rate: 0.0086 +2024-11-21 17:32:58.759461: train_loss -0.7669 +2024-11-21 17:32:58.777192: val_loss -0.7437 +2024-11-21 17:32:58.777355: Pseudo dice [0.8335] +2024-11-21 17:32:58.777471: Epoch time: 19.68 s +2024-11-21 17:32:59.659370: +2024-11-21 17:32:59.659660: Epoch 1234 +2024-11-21 17:32:59.659787: Current learning rate: 0.0086 +2024-11-21 17:33:18.548868: train_loss -0.7739 +2024-11-21 17:33:18.551655: val_loss -0.7551 +2024-11-21 17:33:18.551778: Pseudo dice [0.8378] +2024-11-21 17:33:18.551880: Epoch time: 18.89 s +2024-11-21 17:33:19.424072: +2024-11-21 17:33:19.424289: Epoch 1235 +2024-11-21 17:33:19.424417: Current learning rate: 0.0086 +2024-11-21 17:33:38.450368: train_loss -0.7755 +2024-11-21 17:33:38.458956: val_loss -0.7776 +2024-11-21 17:33:38.459111: Pseudo dice [0.8458] +2024-11-21 17:33:38.459246: Epoch time: 19.03 s +2024-11-21 17:33:39.413452: +2024-11-21 17:33:39.413677: Epoch 1236 +2024-11-21 17:33:39.413788: Current learning rate: 0.0086 +2024-11-21 17:33:58.147489: train_loss -0.7724 +2024-11-21 17:33:58.156543: val_loss -0.7583 +2024-11-21 17:33:58.156760: Pseudo dice [0.8481] +2024-11-21 17:33:58.156865: Epoch time: 18.73 s +2024-11-21 17:33:59.031480: +2024-11-21 17:33:59.031673: Epoch 1237 +2024-11-21 17:33:59.031787: Current learning rate: 0.0086 +2024-11-21 17:34:18.573805: train_loss -0.7636 +2024-11-21 17:34:18.579437: val_loss -0.7612 +2024-11-21 17:34:18.579565: Pseudo dice [0.8329] +2024-11-21 17:34:18.579675: Epoch time: 19.54 s +2024-11-21 17:34:19.669972: +2024-11-21 17:34:19.670180: Epoch 1238 +2024-11-21 17:34:19.670297: Current learning rate: 0.0086 +2024-11-21 17:34:38.530491: train_loss -0.7673 +2024-11-21 17:34:38.538090: val_loss -0.7584 +2024-11-21 17:34:38.538209: Pseudo dice [0.8384] +2024-11-21 17:34:38.538311: Epoch time: 18.86 s +2024-11-21 17:34:39.501038: +2024-11-21 17:34:39.501242: Epoch 1239 +2024-11-21 17:34:39.501360: Current learning rate: 0.00859 +2024-11-21 17:34:58.062675: train_loss -0.7641 +2024-11-21 17:34:58.070124: val_loss -0.7698 +2024-11-21 17:34:58.070279: Pseudo dice [0.8455] +2024-11-21 17:34:58.070393: Epoch time: 18.56 s +2024-11-21 17:34:59.301787: +2024-11-21 17:34:59.302066: Epoch 1240 +2024-11-21 17:34:59.302208: Current learning rate: 0.00859 +2024-11-21 17:35:17.704733: train_loss -0.7643 +2024-11-21 17:35:17.707581: val_loss -0.762 +2024-11-21 17:35:17.707721: Pseudo dice [0.8374] +2024-11-21 17:35:17.707834: Epoch time: 18.4 s +2024-11-21 17:35:18.826056: +2024-11-21 17:35:18.826330: Epoch 1241 +2024-11-21 17:35:18.826448: Current learning rate: 0.00859 +2024-11-21 17:35:38.172455: train_loss -0.7611 +2024-11-21 17:35:38.186599: val_loss -0.7674 +2024-11-21 17:35:38.186726: Pseudo dice [0.8532] +2024-11-21 17:35:38.186818: Epoch time: 19.35 s +2024-11-21 17:35:39.167138: +2024-11-21 17:35:39.167409: Epoch 1242 +2024-11-21 17:35:39.167523: Current learning rate: 0.00859 +2024-11-21 17:35:58.113126: train_loss -0.7522 +2024-11-21 17:35:58.125822: val_loss -0.755 +2024-11-21 17:35:58.125969: Pseudo dice [0.8424] +2024-11-21 17:35:58.126120: Epoch time: 18.95 s +2024-11-21 17:35:59.030001: +2024-11-21 17:35:59.030216: Epoch 1243 +2024-11-21 17:35:59.030334: Current learning rate: 0.00859 +2024-11-21 17:36:18.443941: train_loss -0.7675 +2024-11-21 17:36:18.469914: val_loss -0.7556 +2024-11-21 17:36:18.470068: Pseudo dice [0.8492] +2024-11-21 17:36:18.470159: Epoch time: 19.41 s +2024-11-21 17:36:19.365038: +2024-11-21 17:36:19.365270: Epoch 1244 +2024-11-21 17:36:19.365392: Current learning rate: 0.00859 +2024-11-21 17:36:37.760558: train_loss -0.7565 +2024-11-21 17:36:37.767973: val_loss -0.7375 +2024-11-21 17:36:37.768106: Pseudo dice [0.8528] +2024-11-21 17:36:37.768209: Epoch time: 18.4 s +2024-11-21 17:36:38.621789: +2024-11-21 17:36:38.622018: Epoch 1245 +2024-11-21 17:36:38.622144: Current learning rate: 0.00859 +2024-11-21 17:36:58.383130: train_loss -0.7569 +2024-11-21 17:36:58.387977: val_loss -0.7403 +2024-11-21 17:36:58.388126: Pseudo dice [0.8339] +2024-11-21 17:36:58.388229: Epoch time: 19.76 s +2024-11-21 17:36:59.232381: +2024-11-21 17:36:59.232585: Epoch 1246 +2024-11-21 17:36:59.232734: Current learning rate: 0.00859 +2024-11-21 17:37:18.700148: train_loss -0.7641 +2024-11-21 17:37:18.707798: val_loss -0.7476 +2024-11-21 17:37:18.707938: Pseudo dice [0.8434] +2024-11-21 17:37:18.708024: Epoch time: 19.47 s +2024-11-21 17:37:19.672616: +2024-11-21 17:37:19.672833: Epoch 1247 +2024-11-21 17:37:19.672944: Current learning rate: 0.00859 +2024-11-21 17:37:38.644175: train_loss -0.7631 +2024-11-21 17:37:38.646605: val_loss -0.7623 +2024-11-21 17:37:38.646709: Pseudo dice [0.8447] +2024-11-21 17:37:38.646811: Epoch time: 18.97 s +2024-11-21 17:37:39.473585: +2024-11-21 17:37:39.473812: Epoch 1248 +2024-11-21 17:37:39.473960: Current learning rate: 0.00858 +2024-11-21 17:37:59.690524: train_loss -0.7645 +2024-11-21 17:37:59.695656: val_loss -0.7564 +2024-11-21 17:37:59.695793: Pseudo dice [0.8363] +2024-11-21 17:37:59.695911: Epoch time: 20.22 s +2024-11-21 17:38:00.541499: +2024-11-21 17:38:00.541709: Epoch 1249 +2024-11-21 17:38:00.541831: Current learning rate: 0.00858 +2024-11-21 17:38:20.012860: train_loss -0.7748 +2024-11-21 17:38:20.023553: val_loss -0.7768 +2024-11-21 17:38:20.023700: Pseudo dice [0.8588] +2024-11-21 17:38:20.023790: Epoch time: 19.47 s +2024-11-21 17:38:21.072340: +2024-11-21 17:38:21.072572: Epoch 1250 +2024-11-21 17:38:21.072690: Current learning rate: 0.00858 +2024-11-21 17:38:40.830620: train_loss -0.7732 +2024-11-21 17:38:40.835902: val_loss -0.7367 +2024-11-21 17:38:40.836020: Pseudo dice [0.8413] +2024-11-21 17:38:40.836110: Epoch time: 19.76 s +2024-11-21 17:38:42.162005: +2024-11-21 17:38:42.162247: Epoch 1251 +2024-11-21 17:38:42.162369: Current learning rate: 0.00858 +2024-11-21 17:39:02.447199: train_loss -0.7643 +2024-11-21 17:39:02.454079: val_loss -0.7688 +2024-11-21 17:39:02.454203: Pseudo dice [0.8486] +2024-11-21 17:39:02.454297: Epoch time: 20.29 s +2024-11-21 17:39:03.336423: +2024-11-21 17:39:03.336679: Epoch 1252 +2024-11-21 17:39:03.336816: Current learning rate: 0.00858 +2024-11-21 17:39:22.114599: train_loss -0.7655 +2024-11-21 17:39:22.125572: val_loss -0.7661 +2024-11-21 17:39:22.125961: Pseudo dice [0.8371] +2024-11-21 17:39:22.126092: Epoch time: 18.78 s +2024-11-21 17:39:23.027771: +2024-11-21 17:39:23.027976: Epoch 1253 +2024-11-21 17:39:23.028096: Current learning rate: 0.00858 +2024-11-21 17:39:41.801402: train_loss -0.7625 +2024-11-21 17:39:41.808606: val_loss -0.7472 +2024-11-21 17:39:41.808748: Pseudo dice [0.8481] +2024-11-21 17:39:41.808845: Epoch time: 18.77 s +2024-11-21 17:39:42.715478: +2024-11-21 17:39:42.715728: Epoch 1254 +2024-11-21 17:39:42.715858: Current learning rate: 0.00858 +2024-11-21 17:40:01.485667: train_loss -0.767 +2024-11-21 17:40:01.487832: val_loss -0.7385 +2024-11-21 17:40:01.487936: Pseudo dice [0.8446] +2024-11-21 17:40:01.488028: Epoch time: 18.77 s +2024-11-21 17:40:02.330825: +2024-11-21 17:40:02.331376: Epoch 1255 +2024-11-21 17:40:02.331517: Current learning rate: 0.00858 +2024-11-21 17:40:21.951046: train_loss -0.7548 +2024-11-21 17:40:21.954051: val_loss -0.7509 +2024-11-21 17:40:21.954188: Pseudo dice [0.8324] +2024-11-21 17:40:21.954284: Epoch time: 19.62 s +2024-11-21 17:40:22.819292: +2024-11-21 17:40:22.819522: Epoch 1256 +2024-11-21 17:40:22.819642: Current learning rate: 0.00858 +2024-11-21 17:40:41.357419: train_loss -0.7557 +2024-11-21 17:40:41.359633: val_loss -0.7455 +2024-11-21 17:40:41.359815: Pseudo dice [0.8312] +2024-11-21 17:40:41.359913: Epoch time: 18.54 s +2024-11-21 17:40:42.226527: +2024-11-21 17:40:42.226744: Epoch 1257 +2024-11-21 17:40:42.226893: Current learning rate: 0.00857 +2024-11-21 17:41:00.875719: train_loss -0.7577 +2024-11-21 17:41:00.883102: val_loss -0.7608 +2024-11-21 17:41:00.883253: Pseudo dice [0.8545] +2024-11-21 17:41:00.883373: Epoch time: 18.65 s +2024-11-21 17:41:01.718565: +2024-11-21 17:41:01.718782: Epoch 1258 +2024-11-21 17:41:01.718911: Current learning rate: 0.00857 +2024-11-21 17:41:20.022573: train_loss -0.766 +2024-11-21 17:41:20.032734: val_loss -0.7668 +2024-11-21 17:41:20.032865: Pseudo dice [0.8509] +2024-11-21 17:41:20.032944: Epoch time: 18.3 s +2024-11-21 17:41:21.101125: +2024-11-21 17:41:21.101348: Epoch 1259 +2024-11-21 17:41:21.101497: Current learning rate: 0.00857 +2024-11-21 17:41:39.619989: train_loss -0.7635 +2024-11-21 17:41:39.622366: val_loss -0.7484 +2024-11-21 17:41:39.622513: Pseudo dice [0.8582] +2024-11-21 17:41:39.622609: Epoch time: 18.52 s +2024-11-21 17:41:40.448714: +2024-11-21 17:41:40.448905: Epoch 1260 +2024-11-21 17:41:40.449027: Current learning rate: 0.00857 +2024-11-21 17:41:59.904040: train_loss -0.7568 +2024-11-21 17:41:59.908676: val_loss -0.7433 +2024-11-21 17:41:59.908793: Pseudo dice [0.8501] +2024-11-21 17:41:59.908895: Epoch time: 19.46 s +2024-11-21 17:42:00.735028: +2024-11-21 17:42:00.735260: Epoch 1261 +2024-11-21 17:42:00.735386: Current learning rate: 0.00857 +2024-11-21 17:42:20.120523: train_loss -0.7694 +2024-11-21 17:42:20.127109: val_loss -0.7426 +2024-11-21 17:42:20.127236: Pseudo dice [0.8522] +2024-11-21 17:42:20.127327: Epoch time: 19.39 s +2024-11-21 17:42:21.403503: +2024-11-21 17:42:21.403710: Epoch 1262 +2024-11-21 17:42:21.403838: Current learning rate: 0.00857 +2024-11-21 17:42:40.642689: train_loss -0.7545 +2024-11-21 17:42:40.649889: val_loss -0.7491 +2024-11-21 17:42:40.650035: Pseudo dice [0.8322] +2024-11-21 17:42:40.650149: Epoch time: 19.24 s +2024-11-21 17:42:41.642965: +2024-11-21 17:42:41.643179: Epoch 1263 +2024-11-21 17:42:41.643300: Current learning rate: 0.00857 +2024-11-21 17:43:01.485927: train_loss -0.7703 +2024-11-21 17:43:01.501496: val_loss -0.7662 +2024-11-21 17:43:01.501653: Pseudo dice [0.8394] +2024-11-21 17:43:01.501746: Epoch time: 19.84 s +2024-11-21 17:43:02.392178: +2024-11-21 17:43:02.392391: Epoch 1264 +2024-11-21 17:43:02.392524: Current learning rate: 0.00857 +2024-11-21 17:43:23.172104: train_loss -0.7712 +2024-11-21 17:43:23.180124: val_loss -0.7768 +2024-11-21 17:43:23.180284: Pseudo dice [0.8609] +2024-11-21 17:43:23.180372: Epoch time: 20.78 s +2024-11-21 17:43:24.018858: +2024-11-21 17:43:24.019077: Epoch 1265 +2024-11-21 17:43:24.019195: Current learning rate: 0.00856 +2024-11-21 17:43:43.036292: train_loss -0.7653 +2024-11-21 17:43:43.040549: val_loss -0.7668 +2024-11-21 17:43:43.040671: Pseudo dice [0.8389] +2024-11-21 17:43:43.040754: Epoch time: 19.02 s +2024-11-21 17:43:43.985689: +2024-11-21 17:43:43.985914: Epoch 1266 +2024-11-21 17:43:43.986037: Current learning rate: 0.00856 +2024-11-21 17:44:03.386305: train_loss -0.7732 +2024-11-21 17:44:03.389636: val_loss -0.7813 +2024-11-21 17:44:03.389787: Pseudo dice [0.8436] +2024-11-21 17:44:03.389902: Epoch time: 19.4 s +2024-11-21 17:44:04.267206: +2024-11-21 17:44:04.267475: Epoch 1267 +2024-11-21 17:44:04.267591: Current learning rate: 0.00856 +2024-11-21 17:44:23.380450: train_loss -0.7623 +2024-11-21 17:44:23.390143: val_loss -0.7822 +2024-11-21 17:44:23.390285: Pseudo dice [0.853] +2024-11-21 17:44:23.390621: Epoch time: 19.11 s +2024-11-21 17:44:24.234367: +2024-11-21 17:44:24.234568: Epoch 1268 +2024-11-21 17:44:24.234685: Current learning rate: 0.00856 +2024-11-21 17:44:43.703572: train_loss -0.768 +2024-11-21 17:44:43.710848: val_loss -0.7507 +2024-11-21 17:44:43.711017: Pseudo dice [0.8507] +2024-11-21 17:44:43.711115: Epoch time: 19.47 s +2024-11-21 17:44:44.682169: +2024-11-21 17:44:44.682380: Epoch 1269 +2024-11-21 17:44:44.682523: Current learning rate: 0.00856 +2024-11-21 17:45:02.919704: train_loss -0.7599 +2024-11-21 17:45:02.926304: val_loss -0.7805 +2024-11-21 17:45:02.926523: Pseudo dice [0.8398] +2024-11-21 17:45:02.926625: Epoch time: 18.24 s +2024-11-21 17:45:03.829480: +2024-11-21 17:45:03.829694: Epoch 1270 +2024-11-21 17:45:03.829827: Current learning rate: 0.00856 +2024-11-21 17:45:23.820413: train_loss -0.7622 +2024-11-21 17:45:23.826324: val_loss -0.7382 +2024-11-21 17:45:23.826457: Pseudo dice [0.8374] +2024-11-21 17:45:23.826565: Epoch time: 19.99 s +2024-11-21 17:45:24.689273: +2024-11-21 17:45:24.689478: Epoch 1271 +2024-11-21 17:45:24.689596: Current learning rate: 0.00856 +2024-11-21 17:45:44.704376: train_loss -0.772 +2024-11-21 17:45:44.712961: val_loss -0.7426 +2024-11-21 17:45:44.713114: Pseudo dice [0.8322] +2024-11-21 17:45:44.713224: Epoch time: 20.02 s +2024-11-21 17:45:45.563538: +2024-11-21 17:45:45.563724: Epoch 1272 +2024-11-21 17:45:45.563831: Current learning rate: 0.00856 +2024-11-21 17:46:04.844241: train_loss -0.7557 +2024-11-21 17:46:04.850194: val_loss -0.7597 +2024-11-21 17:46:04.850325: Pseudo dice [0.8381] +2024-11-21 17:46:04.850422: Epoch time: 19.28 s +2024-11-21 17:46:06.144195: +2024-11-21 17:46:06.144398: Epoch 1273 +2024-11-21 17:46:06.144528: Current learning rate: 0.00856 +2024-11-21 17:46:26.527187: train_loss -0.7625 +2024-11-21 17:46:26.531795: val_loss -0.7548 +2024-11-21 17:46:26.531913: Pseudo dice [0.8461] +2024-11-21 17:46:26.532048: Epoch time: 20.38 s +2024-11-21 17:46:27.354567: +2024-11-21 17:46:27.354814: Epoch 1274 +2024-11-21 17:46:27.354944: Current learning rate: 0.00855 +2024-11-21 17:46:46.315904: train_loss -0.7705 +2024-11-21 17:46:46.326544: val_loss -0.7232 +2024-11-21 17:46:46.326698: Pseudo dice [0.8294] +2024-11-21 17:46:46.326804: Epoch time: 18.96 s +2024-11-21 17:46:47.289283: +2024-11-21 17:46:47.289512: Epoch 1275 +2024-11-21 17:46:47.289633: Current learning rate: 0.00855 +2024-11-21 17:47:06.565811: train_loss -0.7622 +2024-11-21 17:47:06.592110: val_loss -0.766 +2024-11-21 17:47:06.592241: Pseudo dice [0.8326] +2024-11-21 17:47:06.592331: Epoch time: 19.28 s +2024-11-21 17:47:07.460779: +2024-11-21 17:47:07.461008: Epoch 1276 +2024-11-21 17:47:07.461130: Current learning rate: 0.00855 +2024-11-21 17:47:27.444906: train_loss -0.7617 +2024-11-21 17:47:27.455215: val_loss -0.7623 +2024-11-21 17:47:27.455358: Pseudo dice [0.8435] +2024-11-21 17:47:27.455446: Epoch time: 19.98 s +2024-11-21 17:47:28.329488: +2024-11-21 17:47:28.329745: Epoch 1277 +2024-11-21 17:47:28.329890: Current learning rate: 0.00855 +2024-11-21 17:47:47.763564: train_loss -0.7554 +2024-11-21 17:47:47.772070: val_loss -0.7634 +2024-11-21 17:47:47.772191: Pseudo dice [0.8455] +2024-11-21 17:47:47.772295: Epoch time: 19.43 s +2024-11-21 17:47:48.627977: +2024-11-21 17:47:48.628236: Epoch 1278 +2024-11-21 17:47:48.628370: Current learning rate: 0.00855 +2024-11-21 17:48:08.166578: train_loss -0.7616 +2024-11-21 17:48:08.172092: val_loss -0.7554 +2024-11-21 17:48:08.172437: Pseudo dice [0.8587] +2024-11-21 17:48:08.172563: Epoch time: 19.54 s +2024-11-21 17:48:08.995094: +2024-11-21 17:48:08.995304: Epoch 1279 +2024-11-21 17:48:08.995425: Current learning rate: 0.00855 +2024-11-21 17:48:27.855234: train_loss -0.7649 +2024-11-21 17:48:27.868208: val_loss -0.7664 +2024-11-21 17:48:27.868357: Pseudo dice [0.8581] +2024-11-21 17:48:27.868451: Epoch time: 18.86 s +2024-11-21 17:48:28.804876: +2024-11-21 17:48:28.805091: Epoch 1280 +2024-11-21 17:48:28.805228: Current learning rate: 0.00855 +2024-11-21 17:48:48.215513: train_loss -0.767 +2024-11-21 17:48:48.242224: val_loss -0.7717 +2024-11-21 17:48:48.242393: Pseudo dice [0.8534] +2024-11-21 17:48:48.242494: Epoch time: 19.41 s +2024-11-21 17:48:49.178168: +2024-11-21 17:48:49.178375: Epoch 1281 +2024-11-21 17:48:49.178495: Current learning rate: 0.00855 +2024-11-21 17:49:08.199883: train_loss -0.7628 +2024-11-21 17:49:08.216105: val_loss -0.7478 +2024-11-21 17:49:08.216254: Pseudo dice [0.8347] +2024-11-21 17:49:08.216368: Epoch time: 19.02 s +2024-11-21 17:49:09.044285: +2024-11-21 17:49:09.044506: Epoch 1282 +2024-11-21 17:49:09.044631: Current learning rate: 0.00855 +2024-11-21 17:49:27.217579: train_loss -0.774 +2024-11-21 17:49:27.221147: val_loss -0.7458 +2024-11-21 17:49:27.221269: Pseudo dice [0.8487] +2024-11-21 17:49:27.221359: Epoch time: 18.17 s +2024-11-21 17:49:28.046456: +2024-11-21 17:49:28.046665: Epoch 1283 +2024-11-21 17:49:28.046788: Current learning rate: 0.00854 +2024-11-21 17:49:46.217516: train_loss -0.7688 +2024-11-21 17:49:46.223805: val_loss -0.7626 +2024-11-21 17:49:46.223969: Pseudo dice [0.8417] +2024-11-21 17:49:46.224077: Epoch time: 18.17 s +2024-11-21 17:49:47.546047: +2024-11-21 17:49:47.546341: Epoch 1284 +2024-11-21 17:49:47.546467: Current learning rate: 0.00854 +2024-11-21 17:50:06.205862: train_loss -0.7748 +2024-11-21 17:50:06.217955: val_loss -0.7638 +2024-11-21 17:50:06.218096: Pseudo dice [0.842] +2024-11-21 17:50:06.218199: Epoch time: 18.66 s +2024-11-21 17:50:07.538610: +2024-11-21 17:50:07.538861: Epoch 1285 +2024-11-21 17:50:07.539018: Current learning rate: 0.00854 +2024-11-21 17:50:28.601679: train_loss -0.7585 +2024-11-21 17:50:28.605854: val_loss -0.7442 +2024-11-21 17:50:28.606008: Pseudo dice [0.844] +2024-11-21 17:50:28.606100: Epoch time: 21.06 s +2024-11-21 17:50:29.465925: +2024-11-21 17:50:29.466156: Epoch 1286 +2024-11-21 17:50:29.466282: Current learning rate: 0.00854 +2024-11-21 17:50:48.052838: train_loss -0.7535 +2024-11-21 17:50:48.060398: val_loss -0.7617 +2024-11-21 17:50:48.060537: Pseudo dice [0.8439] +2024-11-21 17:50:48.060630: Epoch time: 18.59 s +2024-11-21 17:50:48.979676: +2024-11-21 17:50:48.979947: Epoch 1287 +2024-11-21 17:50:48.980071: Current learning rate: 0.00854 +2024-11-21 17:51:07.998280: train_loss -0.7498 +2024-11-21 17:51:08.004183: val_loss -0.762 +2024-11-21 17:51:08.004311: Pseudo dice [0.8371] +2024-11-21 17:51:08.004396: Epoch time: 19.02 s +2024-11-21 17:51:08.832504: +2024-11-21 17:51:08.832746: Epoch 1288 +2024-11-21 17:51:08.832889: Current learning rate: 0.00854 +2024-11-21 17:51:28.061247: train_loss -0.7516 +2024-11-21 17:51:28.069073: val_loss -0.7603 +2024-11-21 17:51:28.069217: Pseudo dice [0.8487] +2024-11-21 17:51:28.069320: Epoch time: 19.23 s +2024-11-21 17:51:29.064390: +2024-11-21 17:51:29.064598: Epoch 1289 +2024-11-21 17:51:29.064725: Current learning rate: 0.00854 +2024-11-21 17:51:48.836305: train_loss -0.7527 +2024-11-21 17:51:48.868900: val_loss -0.7643 +2024-11-21 17:51:48.869072: Pseudo dice [0.8353] +2024-11-21 17:51:48.869163: Epoch time: 19.77 s +2024-11-21 17:51:49.816312: +2024-11-21 17:51:49.816523: Epoch 1290 +2024-11-21 17:51:49.816650: Current learning rate: 0.00854 +2024-11-21 17:52:10.149130: train_loss -0.7658 +2024-11-21 17:52:10.152607: val_loss -0.7567 +2024-11-21 17:52:10.152733: Pseudo dice [0.8369] +2024-11-21 17:52:10.152843: Epoch time: 20.33 s +2024-11-21 17:52:10.983179: +2024-11-21 17:52:10.983388: Epoch 1291 +2024-11-21 17:52:10.983505: Current learning rate: 0.00854 +2024-11-21 17:52:29.824527: train_loss -0.7566 +2024-11-21 17:52:29.833102: val_loss -0.7374 +2024-11-21 17:52:29.833314: Pseudo dice [0.8584] +2024-11-21 17:52:29.833421: Epoch time: 18.84 s +2024-11-21 17:52:30.714226: +2024-11-21 17:52:30.714433: Epoch 1292 +2024-11-21 17:52:30.714548: Current learning rate: 0.00853 +2024-11-21 17:52:49.466434: train_loss -0.7698 +2024-11-21 17:52:49.475775: val_loss -0.7467 +2024-11-21 17:52:49.475905: Pseudo dice [0.8467] +2024-11-21 17:52:49.476029: Epoch time: 18.75 s +2024-11-21 17:52:50.362423: +2024-11-21 17:52:50.362626: Epoch 1293 +2024-11-21 17:52:50.377357: Current learning rate: 0.00853 +2024-11-21 17:53:09.636580: train_loss -0.7566 +2024-11-21 17:53:09.642490: val_loss -0.7415 +2024-11-21 17:53:09.642604: Pseudo dice [0.8437] +2024-11-21 17:53:09.642714: Epoch time: 19.27 s +2024-11-21 17:53:10.549363: +2024-11-21 17:53:10.549591: Epoch 1294 +2024-11-21 17:53:10.549725: Current learning rate: 0.00853 +2024-11-21 17:53:30.981692: train_loss -0.7687 +2024-11-21 17:53:30.987926: val_loss -0.7611 +2024-11-21 17:53:30.988068: Pseudo dice [0.8566] +2024-11-21 17:53:30.988172: Epoch time: 20.43 s +2024-11-21 17:53:32.424253: +2024-11-21 17:53:32.424463: Epoch 1295 +2024-11-21 17:53:32.424578: Current learning rate: 0.00853 +2024-11-21 17:53:50.499165: train_loss -0.7701 +2024-11-21 17:53:50.508464: val_loss -0.7744 +2024-11-21 17:53:50.508604: Pseudo dice [0.8611] +2024-11-21 17:53:50.508719: Epoch time: 18.08 s +2024-11-21 17:53:51.535276: +2024-11-21 17:53:51.535515: Epoch 1296 +2024-11-21 17:53:51.535646: Current learning rate: 0.00853 +2024-11-21 17:54:11.182224: train_loss -0.7717 +2024-11-21 17:54:11.189485: val_loss -0.7478 +2024-11-21 17:54:11.189693: Pseudo dice [0.8581] +2024-11-21 17:54:11.189781: Epoch time: 19.65 s +2024-11-21 17:54:12.023882: +2024-11-21 17:54:12.024103: Epoch 1297 +2024-11-21 17:54:12.024230: Current learning rate: 0.00853 +2024-11-21 17:54:31.103356: train_loss -0.761 +2024-11-21 17:54:31.118705: val_loss -0.7618 +2024-11-21 17:54:31.118857: Pseudo dice [0.8476] +2024-11-21 17:54:31.118953: Epoch time: 19.08 s +2024-11-21 17:54:32.279175: +2024-11-21 17:54:32.279384: Epoch 1298 +2024-11-21 17:54:32.279507: Current learning rate: 0.00853 +2024-11-21 17:54:51.765245: train_loss -0.7758 +2024-11-21 17:54:51.773717: val_loss -0.781 +2024-11-21 17:54:51.773851: Pseudo dice [0.8376] +2024-11-21 17:54:51.773945: Epoch time: 19.49 s +2024-11-21 17:54:52.682953: +2024-11-21 17:54:52.683181: Epoch 1299 +2024-11-21 17:54:52.683313: Current learning rate: 0.00853 +2024-11-21 17:55:10.747126: train_loss -0.7623 +2024-11-21 17:55:10.756074: val_loss -0.7436 +2024-11-21 17:55:10.756216: Pseudo dice [0.8385] +2024-11-21 17:55:10.756326: Epoch time: 18.06 s +2024-11-21 17:55:11.869805: +2024-11-21 17:55:11.870029: Epoch 1300 +2024-11-21 17:55:11.870147: Current learning rate: 0.00852 +2024-11-21 17:55:30.207504: train_loss -0.7687 +2024-11-21 17:55:30.215605: val_loss -0.7376 +2024-11-21 17:55:30.215751: Pseudo dice [0.8534] +2024-11-21 17:55:30.215836: Epoch time: 18.34 s +2024-11-21 17:55:31.076656: +2024-11-21 17:55:31.076864: Epoch 1301 +2024-11-21 17:55:31.077020: Current learning rate: 0.00852 +2024-11-21 17:55:49.486050: train_loss -0.7633 +2024-11-21 17:55:49.488404: val_loss -0.7411 +2024-11-21 17:55:49.488517: Pseudo dice [0.8456] +2024-11-21 17:55:49.488609: Epoch time: 18.41 s +2024-11-21 17:55:50.310927: +2024-11-21 17:55:50.311150: Epoch 1302 +2024-11-21 17:55:50.311276: Current learning rate: 0.00852 +2024-11-21 17:56:10.264356: train_loss -0.7719 +2024-11-21 17:56:10.267648: val_loss -0.7397 +2024-11-21 17:56:10.267780: Pseudo dice [0.8398] +2024-11-21 17:56:10.267870: Epoch time: 19.95 s +2024-11-21 17:56:11.215979: +2024-11-21 17:56:11.216241: Epoch 1303 +2024-11-21 17:56:11.216396: Current learning rate: 0.00852 +2024-11-21 17:56:29.724870: train_loss -0.7624 +2024-11-21 17:56:29.732720: val_loss -0.7632 +2024-11-21 17:56:29.732877: Pseudo dice [0.8571] +2024-11-21 17:56:29.732978: Epoch time: 18.51 s +2024-11-21 17:56:30.739668: +2024-11-21 17:56:30.739874: Epoch 1304 +2024-11-21 17:56:30.739987: Current learning rate: 0.00852 +2024-11-21 17:56:49.763916: train_loss -0.7624 +2024-11-21 17:56:49.771611: val_loss -0.7394 +2024-11-21 17:56:49.771740: Pseudo dice [0.8374] +2024-11-21 17:56:49.771826: Epoch time: 19.03 s +2024-11-21 17:56:50.634371: +2024-11-21 17:56:50.634590: Epoch 1305 +2024-11-21 17:56:50.634719: Current learning rate: 0.00852 +2024-11-21 17:57:10.825572: train_loss -0.7614 +2024-11-21 17:57:10.832805: val_loss -0.7438 +2024-11-21 17:57:10.832983: Pseudo dice [0.8346] +2024-11-21 17:57:10.833093: Epoch time: 20.19 s +2024-11-21 17:57:12.074942: +2024-11-21 17:57:12.075174: Epoch 1306 +2024-11-21 17:57:12.075302: Current learning rate: 0.00852 +2024-11-21 17:57:31.245574: train_loss -0.7729 +2024-11-21 17:57:31.248867: val_loss -0.7792 +2024-11-21 17:57:31.248970: Pseudo dice [0.8521] +2024-11-21 17:57:31.249055: Epoch time: 19.17 s +2024-11-21 17:57:32.078630: +2024-11-21 17:57:32.078901: Epoch 1307 +2024-11-21 17:57:32.079057: Current learning rate: 0.00852 +2024-11-21 17:57:51.180945: train_loss -0.7649 +2024-11-21 17:57:51.186055: val_loss -0.7545 +2024-11-21 17:57:51.186210: Pseudo dice [0.8475] +2024-11-21 17:57:51.186312: Epoch time: 19.1 s +2024-11-21 17:57:52.060317: +2024-11-21 17:57:52.060603: Epoch 1308 +2024-11-21 17:57:52.060725: Current learning rate: 0.00852 +2024-11-21 17:58:11.873341: train_loss -0.7663 +2024-11-21 17:58:11.881035: val_loss -0.7748 +2024-11-21 17:58:11.881282: Pseudo dice [0.844] +2024-11-21 17:58:11.881382: Epoch time: 19.81 s +2024-11-21 17:58:12.743260: +2024-11-21 17:58:12.743445: Epoch 1309 +2024-11-21 17:58:12.743564: Current learning rate: 0.00851 +2024-11-21 17:58:32.206213: train_loss -0.7775 +2024-11-21 17:58:32.211998: val_loss -0.7356 +2024-11-21 17:58:32.212146: Pseudo dice [0.8307] +2024-11-21 17:58:32.212245: Epoch time: 19.46 s +2024-11-21 17:58:33.048284: +2024-11-21 17:58:33.048496: Epoch 1310 +2024-11-21 17:58:33.048614: Current learning rate: 0.00851 +2024-11-21 17:58:51.247219: train_loss -0.7678 +2024-11-21 17:58:51.255400: val_loss -0.7575 +2024-11-21 17:58:51.255547: Pseudo dice [0.851] +2024-11-21 17:58:51.255651: Epoch time: 18.2 s +2024-11-21 17:58:52.093483: +2024-11-21 17:58:52.093685: Epoch 1311 +2024-11-21 17:58:52.093827: Current learning rate: 0.00851 +2024-11-21 17:59:11.142505: train_loss -0.7615 +2024-11-21 17:59:11.147674: val_loss -0.7305 +2024-11-21 17:59:11.147817: Pseudo dice [0.8449] +2024-11-21 17:59:11.147996: Epoch time: 19.05 s +2024-11-21 17:59:12.156596: +2024-11-21 17:59:12.156800: Epoch 1312 +2024-11-21 17:59:12.156937: Current learning rate: 0.00851 +2024-11-21 17:59:30.937127: train_loss -0.7628 +2024-11-21 17:59:30.946312: val_loss -0.7601 +2024-11-21 17:59:30.946457: Pseudo dice [0.8441] +2024-11-21 17:59:30.946547: Epoch time: 18.78 s +2024-11-21 17:59:31.807247: +2024-11-21 17:59:31.807458: Epoch 1313 +2024-11-21 17:59:31.807574: Current learning rate: 0.00851 +2024-11-21 17:59:49.976557: train_loss -0.7598 +2024-11-21 17:59:49.989590: val_loss -0.7552 +2024-11-21 17:59:49.989743: Pseudo dice [0.834] +2024-11-21 17:59:49.989828: Epoch time: 18.17 s +2024-11-21 17:59:50.875620: +2024-11-21 17:59:50.875861: Epoch 1314 +2024-11-21 17:59:50.875985: Current learning rate: 0.00851 +2024-11-21 18:00:10.321903: train_loss -0.7575 +2024-11-21 18:00:10.331122: val_loss -0.7424 +2024-11-21 18:00:10.331277: Pseudo dice [0.837] +2024-11-21 18:00:10.331387: Epoch time: 19.45 s +2024-11-21 18:00:11.192793: +2024-11-21 18:00:11.192995: Epoch 1315 +2024-11-21 18:00:11.193134: Current learning rate: 0.00851 +2024-11-21 18:00:31.218224: train_loss -0.7499 +2024-11-21 18:00:31.222139: val_loss -0.7698 +2024-11-21 18:00:31.222259: Pseudo dice [0.8359] +2024-11-21 18:00:31.222371: Epoch time: 20.03 s +2024-11-21 18:00:32.039657: +2024-11-21 18:00:32.039852: Epoch 1316 +2024-11-21 18:00:32.039976: Current learning rate: 0.00851 +2024-11-21 18:00:50.914564: train_loss -0.7615 +2024-11-21 18:00:50.917540: val_loss -0.7593 +2024-11-21 18:00:50.917642: Pseudo dice [0.8518] +2024-11-21 18:00:50.917733: Epoch time: 18.88 s +2024-11-21 18:00:52.125311: +2024-11-21 18:00:52.125523: Epoch 1317 +2024-11-21 18:00:52.125647: Current learning rate: 0.00851 +2024-11-21 18:01:10.798152: train_loss -0.7454 +2024-11-21 18:01:10.804357: val_loss -0.7469 +2024-11-21 18:01:10.804488: Pseudo dice [0.8418] +2024-11-21 18:01:10.804587: Epoch time: 18.67 s +2024-11-21 18:01:11.835172: +2024-11-21 18:01:11.835398: Epoch 1318 +2024-11-21 18:01:11.835515: Current learning rate: 0.0085 +2024-11-21 18:01:31.519961: train_loss -0.7498 +2024-11-21 18:01:31.527426: val_loss -0.7717 +2024-11-21 18:01:31.528163: Pseudo dice [0.8555] +2024-11-21 18:01:31.528311: Epoch time: 19.69 s +2024-11-21 18:01:32.353291: +2024-11-21 18:01:32.353500: Epoch 1319 +2024-11-21 18:01:32.353626: Current learning rate: 0.0085 +2024-11-21 18:01:51.177478: train_loss -0.7615 +2024-11-21 18:01:51.184986: val_loss -0.7299 +2024-11-21 18:01:51.185110: Pseudo dice [0.8387] +2024-11-21 18:01:51.185204: Epoch time: 18.82 s +2024-11-21 18:01:52.142700: +2024-11-21 18:01:52.142966: Epoch 1320 +2024-11-21 18:01:52.143092: Current learning rate: 0.0085 +2024-11-21 18:02:11.797439: train_loss -0.7412 +2024-11-21 18:02:11.801062: val_loss -0.7715 +2024-11-21 18:02:11.801193: Pseudo dice [0.8463] +2024-11-21 18:02:11.801288: Epoch time: 19.66 s +2024-11-21 18:02:12.628852: +2024-11-21 18:02:12.629071: Epoch 1321 +2024-11-21 18:02:12.629186: Current learning rate: 0.0085 +2024-11-21 18:02:31.118413: train_loss -0.7417 +2024-11-21 18:02:31.126608: val_loss -0.7668 +2024-11-21 18:02:31.126749: Pseudo dice [0.8288] +2024-11-21 18:02:31.126843: Epoch time: 18.49 s +2024-11-21 18:02:32.127341: +2024-11-21 18:02:32.127543: Epoch 1322 +2024-11-21 18:02:32.127664: Current learning rate: 0.0085 +2024-11-21 18:02:51.815427: train_loss -0.7605 +2024-11-21 18:02:51.821685: val_loss -0.765 +2024-11-21 18:02:51.821848: Pseudo dice [0.8501] +2024-11-21 18:02:51.821940: Epoch time: 19.69 s +2024-11-21 18:02:52.649867: +2024-11-21 18:02:52.650074: Epoch 1323 +2024-11-21 18:02:52.650198: Current learning rate: 0.0085 +2024-11-21 18:03:11.619102: train_loss -0.7569 +2024-11-21 18:03:11.622298: val_loss -0.7523 +2024-11-21 18:03:11.622431: Pseudo dice [0.8519] +2024-11-21 18:03:11.622522: Epoch time: 18.97 s +2024-11-21 18:03:12.563268: +2024-11-21 18:03:12.563485: Epoch 1324 +2024-11-21 18:03:12.563621: Current learning rate: 0.0085 +2024-11-21 18:03:31.936856: train_loss -0.7661 +2024-11-21 18:03:31.949948: val_loss -0.7504 +2024-11-21 18:03:31.950097: Pseudo dice [0.8394] +2024-11-21 18:03:31.950192: Epoch time: 19.37 s +2024-11-21 18:03:32.891159: +2024-11-21 18:03:32.891373: Epoch 1325 +2024-11-21 18:03:32.891497: Current learning rate: 0.0085 +2024-11-21 18:03:50.965065: train_loss -0.7681 +2024-11-21 18:03:50.972143: val_loss -0.7666 +2024-11-21 18:03:50.972276: Pseudo dice [0.84] +2024-11-21 18:03:50.972362: Epoch time: 18.07 s +2024-11-21 18:03:51.821280: +2024-11-21 18:03:51.821492: Epoch 1326 +2024-11-21 18:03:51.821666: Current learning rate: 0.0085 +2024-11-21 18:04:11.853416: train_loss -0.7649 +2024-11-21 18:04:11.858605: val_loss -0.7545 +2024-11-21 18:04:11.858734: Pseudo dice [0.8341] +2024-11-21 18:04:11.858818: Epoch time: 20.03 s +2024-11-21 18:04:12.792342: +2024-11-21 18:04:12.792548: Epoch 1327 +2024-11-21 18:04:12.792660: Current learning rate: 0.00849 +2024-11-21 18:04:30.905104: train_loss -0.7558 +2024-11-21 18:04:30.912736: val_loss -0.7129 +2024-11-21 18:04:30.912963: Pseudo dice [0.8243] +2024-11-21 18:04:30.913075: Epoch time: 18.11 s +2024-11-21 18:04:32.359045: +2024-11-21 18:04:32.359258: Epoch 1328 +2024-11-21 18:04:32.359381: Current learning rate: 0.00849 +2024-11-21 18:04:52.671603: train_loss -0.7503 +2024-11-21 18:04:52.676990: val_loss -0.7674 +2024-11-21 18:04:52.677154: Pseudo dice [0.8593] +2024-11-21 18:04:52.677294: Epoch time: 20.31 s +2024-11-21 18:04:53.586006: +2024-11-21 18:04:53.586254: Epoch 1329 +2024-11-21 18:04:53.586371: Current learning rate: 0.00849 +2024-11-21 18:05:12.769172: train_loss -0.7661 +2024-11-21 18:05:12.774398: val_loss -0.759 +2024-11-21 18:05:12.774535: Pseudo dice [0.8418] +2024-11-21 18:05:12.774626: Epoch time: 19.18 s +2024-11-21 18:05:13.622547: +2024-11-21 18:05:13.622783: Epoch 1330 +2024-11-21 18:05:13.622916: Current learning rate: 0.00849 +2024-11-21 18:05:32.508415: train_loss -0.7519 +2024-11-21 18:05:32.515949: val_loss -0.7718 +2024-11-21 18:05:32.516097: Pseudo dice [0.8384] +2024-11-21 18:05:32.516199: Epoch time: 18.89 s +2024-11-21 18:05:33.420944: +2024-11-21 18:05:33.421168: Epoch 1331 +2024-11-21 18:05:33.421286: Current learning rate: 0.00849 +2024-11-21 18:05:52.462917: train_loss -0.7633 +2024-11-21 18:05:52.469923: val_loss -0.7594 +2024-11-21 18:05:52.470041: Pseudo dice [0.8475] +2024-11-21 18:05:52.470151: Epoch time: 19.04 s +2024-11-21 18:05:53.418516: +2024-11-21 18:05:53.418734: Epoch 1332 +2024-11-21 18:05:53.418855: Current learning rate: 0.00849 +2024-11-21 18:06:12.258491: train_loss -0.7648 +2024-11-21 18:06:12.271085: val_loss -0.7528 +2024-11-21 18:06:12.271253: Pseudo dice [0.8449] +2024-11-21 18:06:12.271364: Epoch time: 18.84 s +2024-11-21 18:06:13.117459: +2024-11-21 18:06:13.117666: Epoch 1333 +2024-11-21 18:06:13.117795: Current learning rate: 0.00849 +2024-11-21 18:06:32.253289: train_loss -0.7724 +2024-11-21 18:06:32.269342: val_loss -0.7638 +2024-11-21 18:06:32.269482: Pseudo dice [0.8449] +2024-11-21 18:06:32.269564: Epoch time: 19.14 s +2024-11-21 18:06:33.110999: +2024-11-21 18:06:33.111217: Epoch 1334 +2024-11-21 18:06:33.111359: Current learning rate: 0.00849 +2024-11-21 18:06:51.856357: train_loss -0.7756 +2024-11-21 18:06:51.875149: val_loss -0.7317 +2024-11-21 18:06:51.875288: Pseudo dice [0.8239] +2024-11-21 18:06:51.875384: Epoch time: 18.75 s +2024-11-21 18:06:52.838736: +2024-11-21 18:06:52.838939: Epoch 1335 +2024-11-21 18:06:52.839051: Current learning rate: 0.00848 +2024-11-21 18:07:11.511546: train_loss -0.7679 +2024-11-21 18:07:11.518827: val_loss -0.7759 +2024-11-21 18:07:11.518972: Pseudo dice [0.8617] +2024-11-21 18:07:11.519076: Epoch time: 18.67 s +2024-11-21 18:07:12.416381: +2024-11-21 18:07:12.416571: Epoch 1336 +2024-11-21 18:07:12.416691: Current learning rate: 0.00848 +2024-11-21 18:07:32.779811: train_loss -0.762 +2024-11-21 18:07:32.787997: val_loss -0.7493 +2024-11-21 18:07:32.788142: Pseudo dice [0.847] +2024-11-21 18:07:32.788232: Epoch time: 20.36 s +2024-11-21 18:07:33.641328: +2024-11-21 18:07:33.641537: Epoch 1337 +2024-11-21 18:07:33.641669: Current learning rate: 0.00848 +2024-11-21 18:07:52.058594: train_loss -0.7641 +2024-11-21 18:07:52.067306: val_loss -0.7477 +2024-11-21 18:07:52.067426: Pseudo dice [0.8427] +2024-11-21 18:07:52.067519: Epoch time: 18.42 s +2024-11-21 18:07:53.126246: +2024-11-21 18:07:53.126473: Epoch 1338 +2024-11-21 18:07:53.126609: Current learning rate: 0.00848 +2024-11-21 18:08:12.749178: train_loss -0.7627 +2024-11-21 18:08:12.760722: val_loss -0.7582 +2024-11-21 18:08:12.760838: Pseudo dice [0.8384] +2024-11-21 18:08:12.760927: Epoch time: 19.62 s +2024-11-21 18:08:14.038013: +2024-11-21 18:08:14.038223: Epoch 1339 +2024-11-21 18:08:14.038347: Current learning rate: 0.00848 +2024-11-21 18:08:32.542692: train_loss -0.7682 +2024-11-21 18:08:32.551651: val_loss -0.7612 +2024-11-21 18:08:32.551790: Pseudo dice [0.8511] +2024-11-21 18:08:32.551883: Epoch time: 18.51 s +2024-11-21 18:08:33.401574: +2024-11-21 18:08:33.401784: Epoch 1340 +2024-11-21 18:08:33.401920: Current learning rate: 0.00848 +2024-11-21 18:08:51.589723: train_loss -0.7662 +2024-11-21 18:08:51.606726: val_loss -0.7561 +2024-11-21 18:08:51.606889: Pseudo dice [0.8358] +2024-11-21 18:08:51.606982: Epoch time: 18.19 s +2024-11-21 18:08:52.442323: +2024-11-21 18:08:52.442529: Epoch 1341 +2024-11-21 18:08:52.442660: Current learning rate: 0.00848 +2024-11-21 18:09:11.486948: train_loss -0.7616 +2024-11-21 18:09:11.497332: val_loss -0.7726 +2024-11-21 18:09:11.497463: Pseudo dice [0.8441] +2024-11-21 18:09:11.497554: Epoch time: 19.05 s +2024-11-21 18:09:12.400310: +2024-11-21 18:09:12.400582: Epoch 1342 +2024-11-21 18:09:12.400703: Current learning rate: 0.00848 +2024-11-21 18:09:32.374624: train_loss -0.7681 +2024-11-21 18:09:32.395205: val_loss -0.7609 +2024-11-21 18:09:32.395372: Pseudo dice [0.848] +2024-11-21 18:09:32.395478: Epoch time: 19.98 s +2024-11-21 18:09:33.258254: +2024-11-21 18:09:33.258469: Epoch 1343 +2024-11-21 18:09:33.258584: Current learning rate: 0.00848 +2024-11-21 18:09:52.736885: train_loss -0.7707 +2024-11-21 18:09:52.743013: val_loss -0.7476 +2024-11-21 18:09:52.743151: Pseudo dice [0.8567] +2024-11-21 18:09:52.743296: Epoch time: 19.48 s +2024-11-21 18:09:53.584728: +2024-11-21 18:09:53.584940: Epoch 1344 +2024-11-21 18:09:53.585076: Current learning rate: 0.00847 +2024-11-21 18:10:12.354602: train_loss -0.7701 +2024-11-21 18:10:12.362734: val_loss -0.768 +2024-11-21 18:10:12.362871: Pseudo dice [0.8516] +2024-11-21 18:10:12.362954: Epoch time: 18.77 s +2024-11-21 18:10:13.423998: +2024-11-21 18:10:13.424225: Epoch 1345 +2024-11-21 18:10:13.424362: Current learning rate: 0.00847 +2024-11-21 18:10:31.976955: train_loss -0.7633 +2024-11-21 18:10:31.982269: val_loss -0.7577 +2024-11-21 18:10:31.982414: Pseudo dice [0.8355] +2024-11-21 18:10:31.982500: Epoch time: 18.55 s +2024-11-21 18:10:32.826554: +2024-11-21 18:10:32.826737: Epoch 1346 +2024-11-21 18:10:32.826847: Current learning rate: 0.00847 +2024-11-21 18:10:52.313136: train_loss -0.766 +2024-11-21 18:10:52.320401: val_loss -0.7599 +2024-11-21 18:10:52.320523: Pseudo dice [0.8381] +2024-11-21 18:10:52.320612: Epoch time: 19.49 s +2024-11-21 18:10:53.164359: +2024-11-21 18:10:53.164577: Epoch 1347 +2024-11-21 18:10:53.164713: Current learning rate: 0.00847 +2024-11-21 18:11:13.074609: train_loss -0.7612 +2024-11-21 18:11:13.088658: val_loss -0.7597 +2024-11-21 18:11:13.088802: Pseudo dice [0.8404] +2024-11-21 18:11:13.088897: Epoch time: 19.91 s +2024-11-21 18:11:14.078824: +2024-11-21 18:11:14.079035: Epoch 1348 +2024-11-21 18:11:14.079173: Current learning rate: 0.00847 +2024-11-21 18:11:32.737150: train_loss -0.7638 +2024-11-21 18:11:32.743325: val_loss -0.7649 +2024-11-21 18:11:32.743475: Pseudo dice [0.8413] +2024-11-21 18:11:32.743572: Epoch time: 18.66 s +2024-11-21 18:11:33.575643: +2024-11-21 18:11:33.575836: Epoch 1349 +2024-11-21 18:11:33.575959: Current learning rate: 0.00847 +2024-11-21 18:11:53.459295: train_loss -0.7668 +2024-11-21 18:11:53.466763: val_loss -0.7345 +2024-11-21 18:11:53.466897: Pseudo dice [0.8414] +2024-11-21 18:11:53.466992: Epoch time: 19.88 s +2024-11-21 18:11:54.995936: +2024-11-21 18:11:54.996160: Epoch 1350 +2024-11-21 18:11:54.996276: Current learning rate: 0.00847 +2024-11-21 18:12:13.899020: train_loss -0.765 +2024-11-21 18:12:13.906290: val_loss -0.7799 +2024-11-21 18:12:13.906437: Pseudo dice [0.851] +2024-11-21 18:12:13.906541: Epoch time: 18.9 s +2024-11-21 18:12:14.908350: +2024-11-21 18:12:14.908557: Epoch 1351 +2024-11-21 18:12:14.908670: Current learning rate: 0.00847 +2024-11-21 18:12:34.172462: train_loss -0.7652 +2024-11-21 18:12:34.177334: val_loss -0.7415 +2024-11-21 18:12:34.177471: Pseudo dice [0.8224] +2024-11-21 18:12:34.177557: Epoch time: 19.26 s +2024-11-21 18:12:35.012427: +2024-11-21 18:12:35.012647: Epoch 1352 +2024-11-21 18:12:35.012769: Current learning rate: 0.00847 +2024-11-21 18:12:53.687414: train_loss -0.7662 +2024-11-21 18:12:53.693082: val_loss -0.7593 +2024-11-21 18:12:53.693232: Pseudo dice [0.8374] +2024-11-21 18:12:53.693331: Epoch time: 18.68 s +2024-11-21 18:12:54.536751: +2024-11-21 18:12:54.536956: Epoch 1353 +2024-11-21 18:12:54.537070: Current learning rate: 0.00846 +2024-11-21 18:13:14.446353: train_loss -0.7626 +2024-11-21 18:13:14.452205: val_loss -0.7456 +2024-11-21 18:13:14.452329: Pseudo dice [0.8461] +2024-11-21 18:13:14.452433: Epoch time: 19.91 s +2024-11-21 18:13:15.435991: +2024-11-21 18:13:15.436210: Epoch 1354 +2024-11-21 18:13:15.436335: Current learning rate: 0.00846 +2024-11-21 18:13:34.672919: train_loss -0.7657 +2024-11-21 18:13:34.675695: val_loss -0.7426 +2024-11-21 18:13:34.675833: Pseudo dice [0.8442] +2024-11-21 18:13:34.675928: Epoch time: 19.24 s +2024-11-21 18:13:35.602664: +2024-11-21 18:13:35.602876: Epoch 1355 +2024-11-21 18:13:35.602996: Current learning rate: 0.00846 +2024-11-21 18:13:55.154626: train_loss -0.761 +2024-11-21 18:13:55.178445: val_loss -0.7772 +2024-11-21 18:13:55.178629: Pseudo dice [0.8394] +2024-11-21 18:13:55.178716: Epoch time: 19.55 s +2024-11-21 18:13:56.149685: +2024-11-21 18:13:56.149909: Epoch 1356 +2024-11-21 18:13:56.150032: Current learning rate: 0.00846 +2024-11-21 18:14:14.920327: train_loss -0.7594 +2024-11-21 18:14:14.928198: val_loss -0.762 +2024-11-21 18:14:14.928546: Pseudo dice [0.8398] +2024-11-21 18:14:14.928663: Epoch time: 18.77 s +2024-11-21 18:14:15.785502: +2024-11-21 18:14:15.785696: Epoch 1357 +2024-11-21 18:14:15.785815: Current learning rate: 0.00846 +2024-11-21 18:14:35.328713: train_loss -0.7486 +2024-11-21 18:14:35.337829: val_loss -0.7477 +2024-11-21 18:14:35.337978: Pseudo dice [0.8522] +2024-11-21 18:14:35.338077: Epoch time: 19.54 s +2024-11-21 18:14:36.216771: +2024-11-21 18:14:36.216982: Epoch 1358 +2024-11-21 18:14:36.217107: Current learning rate: 0.00846 +2024-11-21 18:14:55.149574: train_loss -0.7632 +2024-11-21 18:14:55.157623: val_loss -0.7501 +2024-11-21 18:14:55.157753: Pseudo dice [0.8491] +2024-11-21 18:14:55.157853: Epoch time: 18.93 s +2024-11-21 18:14:56.054962: +2024-11-21 18:14:56.055230: Epoch 1359 +2024-11-21 18:14:56.055367: Current learning rate: 0.00846 +2024-11-21 18:15:14.930863: train_loss -0.7632 +2024-11-21 18:15:14.939631: val_loss -0.7402 +2024-11-21 18:15:14.939806: Pseudo dice [0.8552] +2024-11-21 18:15:14.939910: Epoch time: 18.88 s +2024-11-21 18:15:16.244439: +2024-11-21 18:15:16.244659: Epoch 1360 +2024-11-21 18:15:16.244779: Current learning rate: 0.00846 +2024-11-21 18:15:36.554404: train_loss -0.7672 +2024-11-21 18:15:36.556745: val_loss -0.774 +2024-11-21 18:15:36.556852: Pseudo dice [0.8515] +2024-11-21 18:15:36.556944: Epoch time: 20.31 s +2024-11-21 18:15:37.388661: +2024-11-21 18:15:37.388906: Epoch 1361 +2024-11-21 18:15:37.389036: Current learning rate: 0.00845 +2024-11-21 18:15:56.834717: train_loss -0.7619 +2024-11-21 18:15:56.840778: val_loss -0.755 +2024-11-21 18:15:56.840900: Pseudo dice [0.8506] +2024-11-21 18:15:56.841009: Epoch time: 19.45 s +2024-11-21 18:15:57.703674: +2024-11-21 18:15:57.703878: Epoch 1362 +2024-11-21 18:15:57.704010: Current learning rate: 0.00845 +2024-11-21 18:16:16.755720: train_loss -0.7689 +2024-11-21 18:16:16.765517: val_loss -0.7718 +2024-11-21 18:16:16.765749: Pseudo dice [0.8496] +2024-11-21 18:16:16.765868: Epoch time: 19.05 s +2024-11-21 18:16:17.602325: +2024-11-21 18:16:17.602543: Epoch 1363 +2024-11-21 18:16:17.602674: Current learning rate: 0.00845 +2024-11-21 18:16:36.665593: train_loss -0.7722 +2024-11-21 18:16:36.670930: val_loss -0.7537 +2024-11-21 18:16:36.677690: Pseudo dice [0.8404] +2024-11-21 18:16:36.677820: Epoch time: 19.06 s +2024-11-21 18:16:37.689159: +2024-11-21 18:16:37.689376: Epoch 1364 +2024-11-21 18:16:37.689507: Current learning rate: 0.00845 +2024-11-21 18:16:56.980696: train_loss -0.7608 +2024-11-21 18:16:56.996258: val_loss -0.7635 +2024-11-21 18:16:56.996414: Pseudo dice [0.8516] +2024-11-21 18:16:56.996507: Epoch time: 19.29 s +2024-11-21 18:16:57.863414: +2024-11-21 18:16:57.863622: Epoch 1365 +2024-11-21 18:16:57.863745: Current learning rate: 0.00845 +2024-11-21 18:17:16.465598: train_loss -0.7672 +2024-11-21 18:17:16.479620: val_loss -0.7596 +2024-11-21 18:17:16.479752: Pseudo dice [0.8418] +2024-11-21 18:17:16.479853: Epoch time: 18.6 s +2024-11-21 18:17:17.529759: +2024-11-21 18:17:17.529972: Epoch 1366 +2024-11-21 18:17:17.530096: Current learning rate: 0.00845 +2024-11-21 18:17:37.555667: train_loss -0.7688 +2024-11-21 18:17:37.566832: val_loss -0.76 +2024-11-21 18:17:37.566998: Pseudo dice [0.8344] +2024-11-21 18:17:37.567112: Epoch time: 20.03 s +2024-11-21 18:17:38.464196: +2024-11-21 18:17:38.464404: Epoch 1367 +2024-11-21 18:17:38.464531: Current learning rate: 0.00845 +2024-11-21 18:17:56.368174: train_loss -0.7787 +2024-11-21 18:17:56.383189: val_loss -0.7422 +2024-11-21 18:17:56.383337: Pseudo dice [0.8301] +2024-11-21 18:17:56.383434: Epoch time: 17.9 s +2024-11-21 18:17:57.318809: +2024-11-21 18:17:57.319094: Epoch 1368 +2024-11-21 18:17:57.319221: Current learning rate: 0.00845 +2024-11-21 18:18:15.865521: train_loss -0.7668 +2024-11-21 18:18:15.868662: val_loss -0.7543 +2024-11-21 18:18:15.868804: Pseudo dice [0.8422] +2024-11-21 18:18:15.868909: Epoch time: 18.55 s +2024-11-21 18:18:16.728683: +2024-11-21 18:18:16.728935: Epoch 1369 +2024-11-21 18:18:16.729056: Current learning rate: 0.00845 +2024-11-21 18:18:35.764408: train_loss -0.7562 +2024-11-21 18:18:35.769255: val_loss -0.7778 +2024-11-21 18:18:35.769396: Pseudo dice [0.8498] +2024-11-21 18:18:35.769494: Epoch time: 19.04 s +2024-11-21 18:18:36.702457: +2024-11-21 18:18:36.702654: Epoch 1370 +2024-11-21 18:18:36.702773: Current learning rate: 0.00844 +2024-11-21 18:18:55.703684: train_loss -0.7654 +2024-11-21 18:18:55.710597: val_loss -0.757 +2024-11-21 18:18:55.710721: Pseudo dice [0.8524] +2024-11-21 18:18:55.710822: Epoch time: 19.0 s +2024-11-21 18:18:57.035602: +2024-11-21 18:18:57.035801: Epoch 1371 +2024-11-21 18:18:57.035919: Current learning rate: 0.00844 +2024-11-21 18:19:17.240272: train_loss -0.7642 +2024-11-21 18:19:17.246710: val_loss -0.7624 +2024-11-21 18:19:17.246860: Pseudo dice [0.8518] +2024-11-21 18:19:17.247005: Epoch time: 20.21 s +2024-11-21 18:19:18.100294: +2024-11-21 18:19:18.100498: Epoch 1372 +2024-11-21 18:19:18.100617: Current learning rate: 0.00844 +2024-11-21 18:19:36.992971: train_loss -0.7426 +2024-11-21 18:19:37.002521: val_loss -0.7533 +2024-11-21 18:19:37.002667: Pseudo dice [0.8441] +2024-11-21 18:19:37.002768: Epoch time: 18.89 s +2024-11-21 18:19:38.040308: +2024-11-21 18:19:38.040517: Epoch 1373 +2024-11-21 18:19:38.040639: Current learning rate: 0.00844 +2024-11-21 18:19:57.217752: train_loss -0.7576 +2024-11-21 18:19:57.223951: val_loss -0.7478 +2024-11-21 18:19:57.224095: Pseudo dice [0.839] +2024-11-21 18:19:57.224205: Epoch time: 19.18 s +2024-11-21 18:19:58.072807: +2024-11-21 18:19:58.073031: Epoch 1374 +2024-11-21 18:19:58.073163: Current learning rate: 0.00844 +2024-11-21 18:20:15.538968: train_loss -0.7602 +2024-11-21 18:20:15.543842: val_loss -0.7633 +2024-11-21 18:20:15.543988: Pseudo dice [0.8461] +2024-11-21 18:20:15.544095: Epoch time: 17.47 s +2024-11-21 18:20:16.675012: +2024-11-21 18:20:16.675250: Epoch 1375 +2024-11-21 18:20:16.675379: Current learning rate: 0.00844 +2024-11-21 18:20:35.562548: train_loss -0.7676 +2024-11-21 18:20:35.568761: val_loss -0.7345 +2024-11-21 18:20:35.568920: Pseudo dice [0.8394] +2024-11-21 18:20:35.569012: Epoch time: 18.89 s +2024-11-21 18:20:36.408663: +2024-11-21 18:20:36.408862: Epoch 1376 +2024-11-21 18:20:36.408979: Current learning rate: 0.00844 +2024-11-21 18:20:55.099774: train_loss -0.7589 +2024-11-21 18:20:55.113292: val_loss -0.7377 +2024-11-21 18:20:55.113431: Pseudo dice [0.8319] +2024-11-21 18:20:55.113535: Epoch time: 18.69 s +2024-11-21 18:20:56.132908: +2024-11-21 18:20:56.133139: Epoch 1377 +2024-11-21 18:20:56.133272: Current learning rate: 0.00844 +2024-11-21 18:21:14.973590: train_loss -0.7564 +2024-11-21 18:21:14.979542: val_loss -0.7586 +2024-11-21 18:21:14.979666: Pseudo dice [0.8531] +2024-11-21 18:21:14.979764: Epoch time: 18.84 s +2024-11-21 18:21:15.925465: +2024-11-21 18:21:15.925695: Epoch 1378 +2024-11-21 18:21:15.925817: Current learning rate: 0.00844 +2024-11-21 18:21:35.426971: train_loss -0.7595 +2024-11-21 18:21:35.429885: val_loss -0.7513 +2024-11-21 18:21:35.429991: Pseudo dice [0.8254] +2024-11-21 18:21:35.430085: Epoch time: 19.5 s +2024-11-21 18:21:36.264074: +2024-11-21 18:21:36.264269: Epoch 1379 +2024-11-21 18:21:36.264393: Current learning rate: 0.00843 +2024-11-21 18:21:55.108541: train_loss -0.7558 +2024-11-21 18:21:55.119927: val_loss -0.7402 +2024-11-21 18:21:55.120130: Pseudo dice [0.8496] +2024-11-21 18:21:55.120246: Epoch time: 18.85 s +2024-11-21 18:21:55.967728: +2024-11-21 18:21:55.967945: Epoch 1380 +2024-11-21 18:21:55.968073: Current learning rate: 0.00843 +2024-11-21 18:22:13.909470: train_loss -0.7547 +2024-11-21 18:22:13.913430: val_loss -0.7384 +2024-11-21 18:22:13.913552: Pseudo dice [0.8297] +2024-11-21 18:22:13.913638: Epoch time: 17.94 s +2024-11-21 18:22:14.782579: +2024-11-21 18:22:14.782798: Epoch 1381 +2024-11-21 18:22:14.782924: Current learning rate: 0.00843 +2024-11-21 18:22:33.561317: train_loss -0.7675 +2024-11-21 18:22:33.573050: val_loss -0.7692 +2024-11-21 18:22:33.573192: Pseudo dice [0.8392] +2024-11-21 18:22:33.573291: Epoch time: 18.78 s +2024-11-21 18:22:34.824113: +2024-11-21 18:22:34.838630: Epoch 1382 +2024-11-21 18:22:34.838793: Current learning rate: 0.00843 +2024-11-21 18:22:53.676391: train_loss -0.7686 +2024-11-21 18:22:53.681083: val_loss -0.7473 +2024-11-21 18:22:53.681208: Pseudo dice [0.8384] +2024-11-21 18:22:53.681307: Epoch time: 18.85 s +2024-11-21 18:22:54.713336: +2024-11-21 18:22:54.713550: Epoch 1383 +2024-11-21 18:22:54.713671: Current learning rate: 0.00843 +2024-11-21 18:23:12.721726: train_loss -0.7647 +2024-11-21 18:23:12.744650: val_loss -0.748 +2024-11-21 18:23:12.744830: Pseudo dice [0.8449] +2024-11-21 18:23:12.744948: Epoch time: 18.01 s +2024-11-21 18:23:13.804414: +2024-11-21 18:23:13.804646: Epoch 1384 +2024-11-21 18:23:13.804779: Current learning rate: 0.00843 +2024-11-21 18:23:32.022728: train_loss -0.7645 +2024-11-21 18:23:32.024527: val_loss -0.7575 +2024-11-21 18:23:32.024642: Pseudo dice [0.8385] +2024-11-21 18:23:32.024728: Epoch time: 18.22 s +2024-11-21 18:23:32.862906: +2024-11-21 18:23:32.863137: Epoch 1385 +2024-11-21 18:23:32.863261: Current learning rate: 0.00843 +2024-11-21 18:23:52.505439: train_loss -0.7607 +2024-11-21 18:23:52.518250: val_loss -0.7673 +2024-11-21 18:23:52.518403: Pseudo dice [0.8474] +2024-11-21 18:23:52.518502: Epoch time: 19.64 s +2024-11-21 18:23:53.423088: +2024-11-21 18:23:53.423359: Epoch 1386 +2024-11-21 18:23:53.423473: Current learning rate: 0.00843 +2024-11-21 18:24:11.939757: train_loss -0.7705 +2024-11-21 18:24:11.945517: val_loss -0.7472 +2024-11-21 18:24:11.945663: Pseudo dice [0.8446] +2024-11-21 18:24:11.945757: Epoch time: 18.52 s +2024-11-21 18:24:12.918471: +2024-11-21 18:24:12.918685: Epoch 1387 +2024-11-21 18:24:12.918807: Current learning rate: 0.00843 +2024-11-21 18:24:32.860741: train_loss -0.7629 +2024-11-21 18:24:32.871393: val_loss -0.7644 +2024-11-21 18:24:32.871564: Pseudo dice [0.8566] +2024-11-21 18:24:32.871674: Epoch time: 19.94 s +2024-11-21 18:24:33.762634: +2024-11-21 18:24:33.762840: Epoch 1388 +2024-11-21 18:24:33.762969: Current learning rate: 0.00842 +2024-11-21 18:24:52.562892: train_loss -0.761 +2024-11-21 18:24:52.565063: val_loss -0.7663 +2024-11-21 18:24:52.565163: Pseudo dice [0.8377] +2024-11-21 18:24:52.565249: Epoch time: 18.8 s +2024-11-21 18:24:53.410437: +2024-11-21 18:24:53.410640: Epoch 1389 +2024-11-21 18:24:53.410754: Current learning rate: 0.00842 +2024-11-21 18:25:12.922369: train_loss -0.7703 +2024-11-21 18:25:12.928487: val_loss -0.7197 +2024-11-21 18:25:12.928624: Pseudo dice [0.836] +2024-11-21 18:25:12.928719: Epoch time: 19.51 s +2024-11-21 18:25:13.771765: +2024-11-21 18:25:13.771957: Epoch 1390 +2024-11-21 18:25:13.772094: Current learning rate: 0.00842 +2024-11-21 18:25:33.396437: train_loss -0.7687 +2024-11-21 18:25:33.401108: val_loss -0.7681 +2024-11-21 18:25:33.401241: Pseudo dice [0.8359] +2024-11-21 18:25:33.401322: Epoch time: 19.63 s +2024-11-21 18:25:34.323152: +2024-11-21 18:25:34.323370: Epoch 1391 +2024-11-21 18:25:34.323513: Current learning rate: 0.00842 +2024-11-21 18:25:54.592628: train_loss -0.7775 +2024-11-21 18:25:54.600508: val_loss -0.7614 +2024-11-21 18:25:54.600653: Pseudo dice [0.8428] +2024-11-21 18:25:54.600762: Epoch time: 20.27 s +2024-11-21 18:25:55.444237: +2024-11-21 18:25:55.444422: Epoch 1392 +2024-11-21 18:25:55.444538: Current learning rate: 0.00842 +2024-11-21 18:26:14.829588: train_loss -0.7688 +2024-11-21 18:26:14.838011: val_loss -0.7532 +2024-11-21 18:26:14.838159: Pseudo dice [0.836] +2024-11-21 18:26:14.838249: Epoch time: 19.39 s +2024-11-21 18:26:16.064376: +2024-11-21 18:26:16.064588: Epoch 1393 +2024-11-21 18:26:16.064707: Current learning rate: 0.00842 +2024-11-21 18:26:35.371491: train_loss -0.7749 +2024-11-21 18:26:35.385811: val_loss -0.7715 +2024-11-21 18:26:35.385961: Pseudo dice [0.8567] +2024-11-21 18:26:35.386053: Epoch time: 19.31 s +2024-11-21 18:26:36.230567: +2024-11-21 18:26:36.230774: Epoch 1394 +2024-11-21 18:26:36.230893: Current learning rate: 0.00842 +2024-11-21 18:26:55.538579: train_loss -0.7675 +2024-11-21 18:26:55.544910: val_loss -0.7463 +2024-11-21 18:26:55.545129: Pseudo dice [0.8366] +2024-11-21 18:26:55.566444: Epoch time: 19.31 s +2024-11-21 18:26:56.401685: +2024-11-21 18:26:56.401944: Epoch 1395 +2024-11-21 18:26:56.402067: Current learning rate: 0.00842 +2024-11-21 18:27:16.031335: train_loss -0.7589 +2024-11-21 18:27:16.038694: val_loss -0.7617 +2024-11-21 18:27:16.038875: Pseudo dice [0.8471] +2024-11-21 18:27:16.038970: Epoch time: 19.63 s +2024-11-21 18:27:16.893015: +2024-11-21 18:27:16.893270: Epoch 1396 +2024-11-21 18:27:16.893406: Current learning rate: 0.00841 +2024-11-21 18:27:35.154732: train_loss -0.7531 +2024-11-21 18:27:35.160670: val_loss -0.7717 +2024-11-21 18:27:35.160829: Pseudo dice [0.8509] +2024-11-21 18:27:35.160920: Epoch time: 18.26 s +2024-11-21 18:27:36.021125: +2024-11-21 18:27:36.021329: Epoch 1397 +2024-11-21 18:27:36.021444: Current learning rate: 0.00841 +2024-11-21 18:27:54.820028: train_loss -0.7614 +2024-11-21 18:27:54.827015: val_loss -0.7665 +2024-11-21 18:27:54.827167: Pseudo dice [0.8454] +2024-11-21 18:27:54.827268: Epoch time: 18.8 s +2024-11-21 18:27:55.686891: +2024-11-21 18:27:55.687104: Epoch 1398 +2024-11-21 18:27:55.687231: Current learning rate: 0.00841 +2024-11-21 18:28:15.250950: train_loss -0.7549 +2024-11-21 18:28:15.254804: val_loss -0.7673 +2024-11-21 18:28:15.254961: Pseudo dice [0.8561] +2024-11-21 18:28:15.255080: Epoch time: 19.56 s +2024-11-21 18:28:16.126331: +2024-11-21 18:28:16.126578: Epoch 1399 +2024-11-21 18:28:16.126710: Current learning rate: 0.00841 +2024-11-21 18:28:35.646906: train_loss -0.7594 +2024-11-21 18:28:35.652081: val_loss -0.765 +2024-11-21 18:28:35.652204: Pseudo dice [0.8372] +2024-11-21 18:28:35.652304: Epoch time: 19.52 s +2024-11-21 18:28:36.712584: +2024-11-21 18:28:36.712815: Epoch 1400 +2024-11-21 18:28:36.712932: Current learning rate: 0.00841 +2024-11-21 18:28:54.944351: train_loss -0.7672 +2024-11-21 18:28:54.971956: val_loss -0.7678 +2024-11-21 18:28:54.972132: Pseudo dice [0.8459] +2024-11-21 18:28:54.972228: Epoch time: 18.23 s +2024-11-21 18:28:55.840800: +2024-11-21 18:28:55.841006: Epoch 1401 +2024-11-21 18:28:55.841131: Current learning rate: 0.00841 +2024-11-21 18:29:14.203978: train_loss -0.7678 +2024-11-21 18:29:14.205921: val_loss -0.7581 +2024-11-21 18:29:14.206021: Pseudo dice [0.8576] +2024-11-21 18:29:14.206144: Epoch time: 18.36 s +2024-11-21 18:29:15.042960: +2024-11-21 18:29:15.043179: Epoch 1402 +2024-11-21 18:29:15.043312: Current learning rate: 0.00841 +2024-11-21 18:29:34.055771: train_loss -0.7622 +2024-11-21 18:29:34.059806: val_loss -0.7534 +2024-11-21 18:29:34.059956: Pseudo dice [0.8499] +2024-11-21 18:29:34.060055: Epoch time: 19.01 s +2024-11-21 18:29:34.897360: +2024-11-21 18:29:34.897543: Epoch 1403 +2024-11-21 18:29:34.897671: Current learning rate: 0.00841 +2024-11-21 18:29:53.742805: train_loss -0.7579 +2024-11-21 18:29:53.753237: val_loss -0.743 +2024-11-21 18:29:53.753377: Pseudo dice [0.8354] +2024-11-21 18:29:53.753462: Epoch time: 18.85 s +2024-11-21 18:29:55.013736: +2024-11-21 18:29:55.013937: Epoch 1404 +2024-11-21 18:29:55.014052: Current learning rate: 0.00841 +2024-11-21 18:30:13.424142: train_loss -0.7614 +2024-11-21 18:30:13.431455: val_loss -0.7717 +2024-11-21 18:30:13.431590: Pseudo dice [0.8426] +2024-11-21 18:30:13.431698: Epoch time: 18.41 s +2024-11-21 18:30:14.528815: +2024-11-21 18:30:14.529039: Epoch 1405 +2024-11-21 18:30:14.529192: Current learning rate: 0.0084 +2024-11-21 18:30:33.638713: train_loss -0.7699 +2024-11-21 18:30:33.645876: val_loss -0.7691 +2024-11-21 18:30:33.646004: Pseudo dice [0.8477] +2024-11-21 18:30:33.646107: Epoch time: 19.11 s +2024-11-21 18:30:34.744102: +2024-11-21 18:30:34.744388: Epoch 1406 +2024-11-21 18:30:34.744511: Current learning rate: 0.0084 +2024-11-21 18:30:54.111629: train_loss -0.7656 +2024-11-21 18:30:54.117048: val_loss -0.7827 +2024-11-21 18:30:54.117206: Pseudo dice [0.8495] +2024-11-21 18:30:54.117307: Epoch time: 19.37 s +2024-11-21 18:30:54.999820: +2024-11-21 18:30:55.000068: Epoch 1407 +2024-11-21 18:30:55.000183: Current learning rate: 0.0084 +2024-11-21 18:31:13.682168: train_loss -0.7673 +2024-11-21 18:31:13.690938: val_loss -0.7635 +2024-11-21 18:31:13.691102: Pseudo dice [0.847] +2024-11-21 18:31:13.691197: Epoch time: 18.68 s +2024-11-21 18:31:14.542867: +2024-11-21 18:31:14.543079: Epoch 1408 +2024-11-21 18:31:14.543429: Current learning rate: 0.0084 +2024-11-21 18:31:32.995707: train_loss -0.7725 +2024-11-21 18:31:33.001440: val_loss -0.7752 +2024-11-21 18:31:33.001578: Pseudo dice [0.8447] +2024-11-21 18:31:33.001662: Epoch time: 18.45 s +2024-11-21 18:31:33.882374: +2024-11-21 18:31:33.882577: Epoch 1409 +2024-11-21 18:31:33.882695: Current learning rate: 0.0084 +2024-11-21 18:31:52.637191: train_loss -0.7697 +2024-11-21 18:31:52.639529: val_loss -0.7399 +2024-11-21 18:31:52.639647: Pseudo dice [0.8383] +2024-11-21 18:31:52.639772: Epoch time: 18.76 s +2024-11-21 18:31:53.473836: +2024-11-21 18:31:53.474086: Epoch 1410 +2024-11-21 18:31:53.474204: Current learning rate: 0.0084 +2024-11-21 18:32:12.752812: train_loss -0.7661 +2024-11-21 18:32:12.756001: val_loss -0.7834 +2024-11-21 18:32:12.756115: Pseudo dice [0.8529] +2024-11-21 18:32:12.756208: Epoch time: 19.28 s +2024-11-21 18:32:13.592298: +2024-11-21 18:32:13.592488: Epoch 1411 +2024-11-21 18:32:13.592611: Current learning rate: 0.0084 +2024-11-21 18:32:34.141672: train_loss -0.7513 +2024-11-21 18:32:34.149381: val_loss -0.7299 +2024-11-21 18:32:34.149569: Pseudo dice [0.8279] +2024-11-21 18:32:34.149663: Epoch time: 20.55 s +2024-11-21 18:32:35.263851: +2024-11-21 18:32:35.264042: Epoch 1412 +2024-11-21 18:32:35.264179: Current learning rate: 0.0084 +2024-11-21 18:32:55.035037: train_loss -0.7708 +2024-11-21 18:32:55.041662: val_loss -0.75 +2024-11-21 18:32:55.041812: Pseudo dice [0.8472] +2024-11-21 18:32:55.041932: Epoch time: 19.77 s +2024-11-21 18:32:55.887531: +2024-11-21 18:32:55.887761: Epoch 1413 +2024-11-21 18:32:55.887887: Current learning rate: 0.0084 +2024-11-21 18:33:15.075719: train_loss -0.7709 +2024-11-21 18:33:15.082248: val_loss -0.7671 +2024-11-21 18:33:15.082394: Pseudo dice [0.8452] +2024-11-21 18:33:15.082502: Epoch time: 19.19 s +2024-11-21 18:33:16.004586: +2024-11-21 18:33:16.004790: Epoch 1414 +2024-11-21 18:33:16.004909: Current learning rate: 0.00839 +2024-11-21 18:33:35.326785: train_loss -0.7646 +2024-11-21 18:33:35.334759: val_loss -0.7683 +2024-11-21 18:33:35.334912: Pseudo dice [0.8518] +2024-11-21 18:33:35.335000: Epoch time: 19.32 s +2024-11-21 18:33:36.547301: +2024-11-21 18:33:36.547527: Epoch 1415 +2024-11-21 18:33:36.547641: Current learning rate: 0.00839 +2024-11-21 18:33:56.126705: train_loss -0.7743 +2024-11-21 18:33:56.139971: val_loss -0.7427 +2024-11-21 18:33:56.140116: Pseudo dice [0.8478] +2024-11-21 18:33:56.140216: Epoch time: 19.58 s +2024-11-21 18:33:57.409000: +2024-11-21 18:33:57.409233: Epoch 1416 +2024-11-21 18:33:57.409374: Current learning rate: 0.00839 +2024-11-21 18:34:16.257584: train_loss -0.7682 +2024-11-21 18:34:16.263330: val_loss -0.7704 +2024-11-21 18:34:16.263480: Pseudo dice [0.8579] +2024-11-21 18:34:16.263573: Epoch time: 18.85 s +2024-11-21 18:34:17.282690: +2024-11-21 18:34:17.282917: Epoch 1417 +2024-11-21 18:34:17.283048: Current learning rate: 0.00839 +2024-11-21 18:34:38.406753: train_loss -0.7709 +2024-11-21 18:34:38.409255: val_loss -0.7417 +2024-11-21 18:34:38.409363: Pseudo dice [0.8387] +2024-11-21 18:34:38.409469: Epoch time: 21.12 s +2024-11-21 18:34:39.360283: +2024-11-21 18:34:39.360512: Epoch 1418 +2024-11-21 18:34:39.360633: Current learning rate: 0.00839 +2024-11-21 18:34:58.550136: train_loss -0.7686 +2024-11-21 18:34:58.555398: val_loss -0.7366 +2024-11-21 18:34:58.555537: Pseudo dice [0.8377] +2024-11-21 18:34:58.555630: Epoch time: 19.19 s +2024-11-21 18:34:59.454747: +2024-11-21 18:34:59.454955: Epoch 1419 +2024-11-21 18:34:59.455080: Current learning rate: 0.00839 +2024-11-21 18:35:18.790580: train_loss -0.7678 +2024-11-21 18:35:18.794006: val_loss -0.7509 +2024-11-21 18:35:18.794140: Pseudo dice [0.8422] +2024-11-21 18:35:18.794243: Epoch time: 19.34 s +2024-11-21 18:35:19.630985: +2024-11-21 18:35:19.631217: Epoch 1420 +2024-11-21 18:35:19.631567: Current learning rate: 0.00839 +2024-11-21 18:35:37.825144: train_loss -0.7525 +2024-11-21 18:35:37.831610: val_loss -0.7598 +2024-11-21 18:35:37.831733: Pseudo dice [0.8558] +2024-11-21 18:35:37.831826: Epoch time: 18.19 s +2024-11-21 18:35:38.682021: +2024-11-21 18:35:38.682224: Epoch 1421 +2024-11-21 18:35:38.682364: Current learning rate: 0.00839 +2024-11-21 18:35:57.620858: train_loss -0.7666 +2024-11-21 18:35:57.623608: val_loss -0.7566 +2024-11-21 18:35:57.625448: Pseudo dice [0.8553] +2024-11-21 18:35:57.625552: Epoch time: 18.94 s +2024-11-21 18:35:58.465049: +2024-11-21 18:35:58.465275: Epoch 1422 +2024-11-21 18:35:58.465390: Current learning rate: 0.00839 +2024-11-21 18:36:17.838855: train_loss -0.773 +2024-11-21 18:36:17.867216: val_loss -0.7585 +2024-11-21 18:36:17.867356: Pseudo dice [0.8447] +2024-11-21 18:36:17.867441: Epoch time: 19.37 s +2024-11-21 18:36:18.847396: +2024-11-21 18:36:18.847605: Epoch 1423 +2024-11-21 18:36:18.847739: Current learning rate: 0.00838 +2024-11-21 18:36:39.542708: train_loss -0.7511 +2024-11-21 18:36:39.549228: val_loss -0.7629 +2024-11-21 18:36:39.549365: Pseudo dice [0.8408] +2024-11-21 18:36:39.549474: Epoch time: 20.7 s +2024-11-21 18:36:40.385501: +2024-11-21 18:36:40.385695: Epoch 1424 +2024-11-21 18:36:40.385811: Current learning rate: 0.00838 +2024-11-21 18:36:59.852526: train_loss -0.7513 +2024-11-21 18:36:59.860175: val_loss -0.7332 +2024-11-21 18:36:59.860354: Pseudo dice [0.8393] +2024-11-21 18:36:59.860446: Epoch time: 19.47 s +2024-11-21 18:37:00.793337: +2024-11-21 18:37:00.793533: Epoch 1425 +2024-11-21 18:37:00.793653: Current learning rate: 0.00838 +2024-11-21 18:37:20.139886: train_loss -0.7601 +2024-11-21 18:37:20.159551: val_loss -0.7533 +2024-11-21 18:37:20.159708: Pseudo dice [0.8589] +2024-11-21 18:37:20.159817: Epoch time: 19.35 s +2024-11-21 18:37:21.180728: +2024-11-21 18:37:21.180943: Epoch 1426 +2024-11-21 18:37:21.181081: Current learning rate: 0.00838 +2024-11-21 18:37:40.494551: train_loss -0.7671 +2024-11-21 18:37:40.498651: val_loss -0.7617 +2024-11-21 18:37:40.498758: Pseudo dice [0.8497] +2024-11-21 18:37:40.498877: Epoch time: 19.31 s +2024-11-21 18:37:41.333629: +2024-11-21 18:37:41.333865: Epoch 1427 +2024-11-21 18:37:41.333985: Current learning rate: 0.00838 +2024-11-21 18:37:59.919621: train_loss -0.7713 +2024-11-21 18:37:59.925857: val_loss -0.7596 +2024-11-21 18:37:59.925980: Pseudo dice [0.8521] +2024-11-21 18:37:59.926089: Epoch time: 18.59 s +2024-11-21 18:38:00.920025: +2024-11-21 18:38:00.920249: Epoch 1428 +2024-11-21 18:38:00.920387: Current learning rate: 0.00838 +2024-11-21 18:38:20.816549: train_loss -0.7707 +2024-11-21 18:38:20.824876: val_loss -0.7302 +2024-11-21 18:38:20.825005: Pseudo dice [0.8197] +2024-11-21 18:38:20.825186: Epoch time: 19.9 s +2024-11-21 18:38:21.667988: +2024-11-21 18:38:21.668251: Epoch 1429 +2024-11-21 18:38:21.668366: Current learning rate: 0.00838 +2024-11-21 18:38:40.274351: train_loss -0.7625 +2024-11-21 18:38:40.279587: val_loss -0.7674 +2024-11-21 18:38:40.279700: Pseudo dice [0.8578] +2024-11-21 18:38:40.279802: Epoch time: 18.61 s +2024-11-21 18:38:41.118444: +2024-11-21 18:38:41.118649: Epoch 1430 +2024-11-21 18:38:41.118787: Current learning rate: 0.00838 +2024-11-21 18:39:00.274245: train_loss -0.7646 +2024-11-21 18:39:00.281630: val_loss -0.7791 +2024-11-21 18:39:00.281759: Pseudo dice [0.8507] +2024-11-21 18:39:00.281842: Epoch time: 19.16 s +2024-11-21 18:39:01.164643: +2024-11-21 18:39:01.164850: Epoch 1431 +2024-11-21 18:39:01.164964: Current learning rate: 0.00837 +2024-11-21 18:39:19.430465: train_loss -0.7619 +2024-11-21 18:39:19.439897: val_loss -0.7734 +2024-11-21 18:39:19.440040: Pseudo dice [0.8468] +2024-11-21 18:39:19.440129: Epoch time: 18.27 s +2024-11-21 18:39:20.314317: +2024-11-21 18:39:20.314530: Epoch 1432 +2024-11-21 18:39:20.314650: Current learning rate: 0.00837 +2024-11-21 18:39:39.887732: train_loss -0.7602 +2024-11-21 18:39:39.892452: val_loss -0.7475 +2024-11-21 18:39:39.892561: Pseudo dice [0.8352] +2024-11-21 18:39:39.892649: Epoch time: 19.57 s +2024-11-21 18:39:40.766798: +2024-11-21 18:39:40.766999: Epoch 1433 +2024-11-21 18:39:40.767118: Current learning rate: 0.00837 +2024-11-21 18:39:59.756294: train_loss -0.7517 +2024-11-21 18:39:59.763017: val_loss -0.7639 +2024-11-21 18:39:59.763166: Pseudo dice [0.8386] +2024-11-21 18:39:59.763262: Epoch time: 18.99 s +2024-11-21 18:40:00.648646: +2024-11-21 18:40:00.648860: Epoch 1434 +2024-11-21 18:40:00.649164: Current learning rate: 0.00837 +2024-11-21 18:40:19.321775: train_loss -0.7742 +2024-11-21 18:40:19.324540: val_loss -0.7651 +2024-11-21 18:40:19.324661: Pseudo dice [0.8479] +2024-11-21 18:40:19.324808: Epoch time: 18.67 s +2024-11-21 18:40:20.196983: +2024-11-21 18:40:20.197192: Epoch 1435 +2024-11-21 18:40:20.197308: Current learning rate: 0.00837 +2024-11-21 18:40:40.331929: train_loss -0.7513 +2024-11-21 18:40:40.334930: val_loss -0.7799 +2024-11-21 18:40:40.335033: Pseudo dice [0.8665] +2024-11-21 18:40:40.335125: Epoch time: 20.14 s +2024-11-21 18:40:41.542290: +2024-11-21 18:40:41.542539: Epoch 1436 +2024-11-21 18:40:41.542667: Current learning rate: 0.00837 +2024-11-21 18:41:00.015423: train_loss -0.7746 +2024-11-21 18:41:00.022186: val_loss -0.7655 +2024-11-21 18:41:00.022300: Pseudo dice [0.8474] +2024-11-21 18:41:00.022379: Epoch time: 18.47 s +2024-11-21 18:41:01.119199: +2024-11-21 18:41:01.119418: Epoch 1437 +2024-11-21 18:41:01.119537: Current learning rate: 0.00837 +2024-11-21 18:41:20.330149: train_loss -0.768 +2024-11-21 18:41:20.335527: val_loss -0.7608 +2024-11-21 18:41:20.335712: Pseudo dice [0.8465] +2024-11-21 18:41:20.335819: Epoch time: 19.21 s +2024-11-21 18:41:21.354737: +2024-11-21 18:41:21.354975: Epoch 1438 +2024-11-21 18:41:21.355102: Current learning rate: 0.00837 +2024-11-21 18:41:40.279576: train_loss -0.7691 +2024-11-21 18:41:40.288838: val_loss -0.7578 +2024-11-21 18:41:40.288956: Pseudo dice [0.8362] +2024-11-21 18:41:40.289051: Epoch time: 18.93 s +2024-11-21 18:41:41.238133: +2024-11-21 18:41:41.238344: Epoch 1439 +2024-11-21 18:41:41.238473: Current learning rate: 0.00837 +2024-11-21 18:42:00.688357: train_loss -0.7727 +2024-11-21 18:42:00.714038: val_loss -0.749 +2024-11-21 18:42:00.714207: Pseudo dice [0.8447] +2024-11-21 18:42:00.714319: Epoch time: 19.45 s +2024-11-21 18:42:01.553785: +2024-11-21 18:42:01.554008: Epoch 1440 +2024-11-21 18:42:01.554143: Current learning rate: 0.00836 +2024-11-21 18:42:21.471106: train_loss -0.7709 +2024-11-21 18:42:21.478995: val_loss -0.7687 +2024-11-21 18:42:21.479209: Pseudo dice [0.8594] +2024-11-21 18:42:21.479312: Epoch time: 19.92 s +2024-11-21 18:42:22.334415: +2024-11-21 18:42:22.334639: Epoch 1441 +2024-11-21 18:42:22.334759: Current learning rate: 0.00836 +2024-11-21 18:42:42.044165: train_loss -0.7655 +2024-11-21 18:42:42.065794: val_loss -0.7606 +2024-11-21 18:42:42.065919: Pseudo dice [0.8298] +2024-11-21 18:42:42.066014: Epoch time: 19.71 s +2024-11-21 18:42:43.156289: +2024-11-21 18:42:43.156492: Epoch 1442 +2024-11-21 18:42:43.156626: Current learning rate: 0.00836 +2024-11-21 18:43:01.418174: train_loss -0.7698 +2024-11-21 18:43:01.426309: val_loss -0.7658 +2024-11-21 18:43:01.426468: Pseudo dice [0.8485] +2024-11-21 18:43:01.426571: Epoch time: 18.26 s +2024-11-21 18:43:02.301448: +2024-11-21 18:43:02.301694: Epoch 1443 +2024-11-21 18:43:02.301826: Current learning rate: 0.00836 +2024-11-21 18:43:21.835650: train_loss -0.7798 +2024-11-21 18:43:21.843667: val_loss -0.7843 +2024-11-21 18:43:21.843797: Pseudo dice [0.8446] +2024-11-21 18:43:21.843897: Epoch time: 19.54 s +2024-11-21 18:43:22.691193: +2024-11-21 18:43:22.691398: Epoch 1444 +2024-11-21 18:43:22.691514: Current learning rate: 0.00836 +2024-11-21 18:43:42.658674: train_loss -0.7705 +2024-11-21 18:43:42.666633: val_loss -0.7537 +2024-11-21 18:43:42.666773: Pseudo dice [0.839] +2024-11-21 18:43:42.666871: Epoch time: 19.97 s +2024-11-21 18:43:43.641545: +2024-11-21 18:43:43.641751: Epoch 1445 +2024-11-21 18:43:43.641877: Current learning rate: 0.00836 +2024-11-21 18:44:03.362043: train_loss -0.7726 +2024-11-21 18:44:03.369437: val_loss -0.7564 +2024-11-21 18:44:03.369583: Pseudo dice [0.8103] +2024-11-21 18:44:03.369694: Epoch time: 19.72 s +2024-11-21 18:44:04.259705: +2024-11-21 18:44:04.259911: Epoch 1446 +2024-11-21 18:44:04.260027: Current learning rate: 0.00836 +2024-11-21 18:44:23.631536: train_loss -0.7846 +2024-11-21 18:44:23.637446: val_loss -0.7722 +2024-11-21 18:44:23.637559: Pseudo dice [0.8508] +2024-11-21 18:44:23.637650: Epoch time: 19.37 s +2024-11-21 18:44:24.884713: +2024-11-21 18:44:24.885056: Epoch 1447 +2024-11-21 18:44:24.885193: Current learning rate: 0.00836 +2024-11-21 18:44:44.425754: train_loss -0.7641 +2024-11-21 18:44:44.432099: val_loss -0.7616 +2024-11-21 18:44:44.432297: Pseudo dice [0.8558] +2024-11-21 18:44:44.432386: Epoch time: 19.54 s +2024-11-21 18:44:45.282387: +2024-11-21 18:44:45.282645: Epoch 1448 +2024-11-21 18:44:45.282788: Current learning rate: 0.00836 +2024-11-21 18:45:03.500208: train_loss -0.7732 +2024-11-21 18:45:03.514427: val_loss -0.7699 +2024-11-21 18:45:03.514584: Pseudo dice [0.8426] +2024-11-21 18:45:03.514674: Epoch time: 18.22 s +2024-11-21 18:45:04.443167: +2024-11-21 18:45:04.443399: Epoch 1449 +2024-11-21 18:45:04.443522: Current learning rate: 0.00835 +2024-11-21 18:45:22.974516: train_loss -0.7746 +2024-11-21 18:45:22.977435: val_loss -0.7885 +2024-11-21 18:45:22.977563: Pseudo dice [0.8638] +2024-11-21 18:45:22.977668: Epoch time: 18.53 s +2024-11-21 18:45:24.052691: +2024-11-21 18:45:24.052899: Epoch 1450 +2024-11-21 18:45:24.053023: Current learning rate: 0.00835 +2024-11-21 18:45:43.125933: train_loss -0.7685 +2024-11-21 18:45:43.128409: val_loss -0.7832 +2024-11-21 18:45:43.128528: Pseudo dice [0.8453] +2024-11-21 18:45:43.128612: Epoch time: 19.07 s +2024-11-21 18:45:43.963342: +2024-11-21 18:45:43.963552: Epoch 1451 +2024-11-21 18:45:43.963667: Current learning rate: 0.00835 +2024-11-21 18:46:02.911798: train_loss -0.7615 +2024-11-21 18:46:02.916163: val_loss -0.7782 +2024-11-21 18:46:02.916324: Pseudo dice [0.8474] +2024-11-21 18:46:02.916431: Epoch time: 18.95 s +2024-11-21 18:46:03.791301: +2024-11-21 18:46:03.791499: Epoch 1452 +2024-11-21 18:46:03.791617: Current learning rate: 0.00835 +2024-11-21 18:46:23.006245: train_loss -0.7624 +2024-11-21 18:46:23.012509: val_loss -0.7876 +2024-11-21 18:46:23.012628: Pseudo dice [0.8438] +2024-11-21 18:46:23.012737: Epoch time: 19.22 s +2024-11-21 18:46:23.873412: +2024-11-21 18:46:23.873669: Epoch 1453 +2024-11-21 18:46:23.873792: Current learning rate: 0.00835 +2024-11-21 18:46:42.904305: train_loss -0.7602 +2024-11-21 18:46:42.913736: val_loss -0.7585 +2024-11-21 18:46:42.913862: Pseudo dice [0.8508] +2024-11-21 18:46:42.913955: Epoch time: 19.03 s +2024-11-21 18:46:43.761819: +2024-11-21 18:46:43.762033: Epoch 1454 +2024-11-21 18:46:43.762163: Current learning rate: 0.00835 +2024-11-21 18:47:02.346045: train_loss -0.7525 +2024-11-21 18:47:02.352257: val_loss -0.7414 +2024-11-21 18:47:02.352420: Pseudo dice [0.8361] +2024-11-21 18:47:02.352548: Epoch time: 18.59 s +2024-11-21 18:47:03.217236: +2024-11-21 18:47:03.217434: Epoch 1455 +2024-11-21 18:47:03.217557: Current learning rate: 0.00835 +2024-11-21 18:47:22.371923: train_loss -0.7582 +2024-11-21 18:47:22.377833: val_loss -0.7573 +2024-11-21 18:47:22.377975: Pseudo dice [0.83] +2024-11-21 18:47:22.378070: Epoch time: 19.16 s +2024-11-21 18:47:23.336331: +2024-11-21 18:47:23.336607: Epoch 1456 +2024-11-21 18:47:23.336720: Current learning rate: 0.00835 +2024-11-21 18:47:42.881146: train_loss -0.7656 +2024-11-21 18:47:42.895602: val_loss -0.7886 +2024-11-21 18:47:42.895721: Pseudo dice [0.8523] +2024-11-21 18:47:42.895830: Epoch time: 19.55 s +2024-11-21 18:47:43.915537: +2024-11-21 18:47:43.915757: Epoch 1457 +2024-11-21 18:47:43.915872: Current learning rate: 0.00834 +2024-11-21 18:48:02.872264: train_loss -0.7644 +2024-11-21 18:48:02.875136: val_loss -0.753 +2024-11-21 18:48:02.875270: Pseudo dice [0.842] +2024-11-21 18:48:02.875371: Epoch time: 18.96 s +2024-11-21 18:48:03.853125: +2024-11-21 18:48:03.853370: Epoch 1458 +2024-11-21 18:48:03.853489: Current learning rate: 0.00834 +2024-11-21 18:48:22.728964: train_loss -0.7651 +2024-11-21 18:48:22.745139: val_loss -0.7467 +2024-11-21 18:48:22.745297: Pseudo dice [0.8414] +2024-11-21 18:48:22.745390: Epoch time: 18.88 s +2024-11-21 18:48:23.640857: +2024-11-21 18:48:23.641103: Epoch 1459 +2024-11-21 18:48:23.641235: Current learning rate: 0.00834 +2024-11-21 18:48:42.538093: train_loss -0.7652 +2024-11-21 18:48:42.545538: val_loss -0.7493 +2024-11-21 18:48:42.545651: Pseudo dice [0.8425] +2024-11-21 18:48:42.545748: Epoch time: 18.9 s +2024-11-21 18:48:43.376383: +2024-11-21 18:48:43.376799: Epoch 1460 +2024-11-21 18:48:43.376923: Current learning rate: 0.00834 +2024-11-21 18:49:02.606102: train_loss -0.7622 +2024-11-21 18:49:02.614365: val_loss -0.7606 +2024-11-21 18:49:02.614522: Pseudo dice [0.8389] +2024-11-21 18:49:02.614632: Epoch time: 19.23 s +2024-11-21 18:49:03.473619: +2024-11-21 18:49:03.473831: Epoch 1461 +2024-11-21 18:49:03.473960: Current learning rate: 0.00834 +2024-11-21 18:49:22.823961: train_loss -0.7608 +2024-11-21 18:49:22.836852: val_loss -0.7577 +2024-11-21 18:49:22.836967: Pseudo dice [0.8438] +2024-11-21 18:49:22.837050: Epoch time: 19.35 s +2024-11-21 18:49:23.735590: +2024-11-21 18:49:23.735828: Epoch 1462 +2024-11-21 18:49:23.735955: Current learning rate: 0.00834 +2024-11-21 18:49:42.992161: train_loss -0.7585 +2024-11-21 18:49:42.998205: val_loss -0.7471 +2024-11-21 18:49:42.998340: Pseudo dice [0.8495] +2024-11-21 18:49:42.998456: Epoch time: 19.26 s +2024-11-21 18:49:43.843318: +2024-11-21 18:49:43.843520: Epoch 1463 +2024-11-21 18:49:43.843645: Current learning rate: 0.00834 +2024-11-21 18:50:03.317445: train_loss -0.7605 +2024-11-21 18:50:03.320141: val_loss -0.7649 +2024-11-21 18:50:03.320253: Pseudo dice [0.851] +2024-11-21 18:50:03.320336: Epoch time: 19.47 s +2024-11-21 18:50:04.154520: +2024-11-21 18:50:04.154745: Epoch 1464 +2024-11-21 18:50:04.154868: Current learning rate: 0.00834 +2024-11-21 18:50:23.137946: train_loss -0.7619 +2024-11-21 18:50:23.145290: val_loss -0.7331 +2024-11-21 18:50:23.145399: Pseudo dice [0.8437] +2024-11-21 18:50:23.145490: Epoch time: 18.98 s +2024-11-21 18:50:24.054522: +2024-11-21 18:50:24.054742: Epoch 1465 +2024-11-21 18:50:24.054872: Current learning rate: 0.00834 +2024-11-21 18:50:43.092492: train_loss -0.7633 +2024-11-21 18:50:43.099736: val_loss -0.7331 +2024-11-21 18:50:43.099886: Pseudo dice [0.8403] +2024-11-21 18:50:43.099989: Epoch time: 19.04 s +2024-11-21 18:50:43.934162: +2024-11-21 18:50:43.934369: Epoch 1466 +2024-11-21 18:50:43.934501: Current learning rate: 0.00833 +2024-11-21 18:51:01.607640: train_loss -0.7774 +2024-11-21 18:51:01.618988: val_loss -0.7437 +2024-11-21 18:51:01.619136: Pseudo dice [0.8456] +2024-11-21 18:51:01.619252: Epoch time: 17.67 s +2024-11-21 18:51:02.663657: +2024-11-21 18:51:02.663929: Epoch 1467 +2024-11-21 18:51:02.664070: Current learning rate: 0.00833 +2024-11-21 18:51:22.270489: train_loss -0.7522 +2024-11-21 18:51:22.282283: val_loss -0.761 +2024-11-21 18:51:22.282427: Pseudo dice [0.8446] +2024-11-21 18:51:22.282543: Epoch time: 19.61 s +2024-11-21 18:51:23.687372: +2024-11-21 18:51:23.687636: Epoch 1468 +2024-11-21 18:51:23.687765: Current learning rate: 0.00833 +2024-11-21 18:51:42.474133: train_loss -0.7597 +2024-11-21 18:51:42.476797: val_loss -0.7583 +2024-11-21 18:51:42.476936: Pseudo dice [0.846] +2024-11-21 18:51:42.477036: Epoch time: 18.79 s +2024-11-21 18:51:43.391869: +2024-11-21 18:51:43.392078: Epoch 1469 +2024-11-21 18:51:43.392197: Current learning rate: 0.00833 +2024-11-21 18:52:01.588991: train_loss -0.7681 +2024-11-21 18:52:01.594842: val_loss -0.7542 +2024-11-21 18:52:01.594996: Pseudo dice [0.8433] +2024-11-21 18:52:01.597332: Epoch time: 18.2 s +2024-11-21 18:52:02.440682: +2024-11-21 18:52:02.440920: Epoch 1470 +2024-11-21 18:52:02.441043: Current learning rate: 0.00833 +2024-11-21 18:52:21.170558: train_loss -0.7618 +2024-11-21 18:52:21.175122: val_loss -0.7319 +2024-11-21 18:52:21.175228: Pseudo dice [0.849] +2024-11-21 18:52:21.175305: Epoch time: 18.73 s +2024-11-21 18:52:22.005492: +2024-11-21 18:52:22.005706: Epoch 1471 +2024-11-21 18:52:22.005819: Current learning rate: 0.00833 +2024-11-21 18:52:41.692844: train_loss -0.7691 +2024-11-21 18:52:41.697793: val_loss -0.7648 +2024-11-21 18:52:41.697945: Pseudo dice [0.8471] +2024-11-21 18:52:41.698042: Epoch time: 19.69 s +2024-11-21 18:52:42.534915: +2024-11-21 18:52:42.535152: Epoch 1472 +2024-11-21 18:52:42.535279: Current learning rate: 0.00833 +2024-11-21 18:53:01.473598: train_loss -0.7626 +2024-11-21 18:53:01.488617: val_loss -0.7443 +2024-11-21 18:53:01.488752: Pseudo dice [0.8424] +2024-11-21 18:53:01.488850: Epoch time: 18.94 s +2024-11-21 18:53:02.492812: +2024-11-21 18:53:02.493067: Epoch 1473 +2024-11-21 18:53:02.493185: Current learning rate: 0.00833 +2024-11-21 18:53:21.954680: train_loss -0.7689 +2024-11-21 18:53:21.970719: val_loss -0.7417 +2024-11-21 18:53:21.970836: Pseudo dice [0.8509] +2024-11-21 18:53:21.970920: Epoch time: 19.46 s +2024-11-21 18:53:22.922745: +2024-11-21 18:53:22.922944: Epoch 1474 +2024-11-21 18:53:22.923077: Current learning rate: 0.00833 +2024-11-21 18:53:41.511462: train_loss -0.7657 +2024-11-21 18:53:41.522846: val_loss -0.7684 +2024-11-21 18:53:41.523001: Pseudo dice [0.8451] +2024-11-21 18:53:41.523109: Epoch time: 18.59 s +2024-11-21 18:53:42.368968: +2024-11-21 18:53:42.369185: Epoch 1475 +2024-11-21 18:53:42.369320: Current learning rate: 0.00832 +2024-11-21 18:54:00.440136: train_loss -0.7698 +2024-11-21 18:54:00.442554: val_loss -0.7803 +2024-11-21 18:54:00.442760: Pseudo dice [0.8546] +2024-11-21 18:54:00.442858: Epoch time: 18.07 s +2024-11-21 18:54:01.286739: +2024-11-21 18:54:01.286983: Epoch 1476 +2024-11-21 18:54:01.287123: Current learning rate: 0.00832 +2024-11-21 18:54:21.808960: train_loss -0.7689 +2024-11-21 18:54:21.816020: val_loss -0.781 +2024-11-21 18:54:21.816234: Pseudo dice [0.8497] +2024-11-21 18:54:21.816331: Epoch time: 20.52 s +2024-11-21 18:54:22.669336: +2024-11-21 18:54:22.669556: Epoch 1477 +2024-11-21 18:54:22.669680: Current learning rate: 0.00832 +2024-11-21 18:54:41.805218: train_loss -0.7727 +2024-11-21 18:54:41.813441: val_loss -0.7579 +2024-11-21 18:54:41.813564: Pseudo dice [0.8421] +2024-11-21 18:54:41.813650: Epoch time: 19.14 s +2024-11-21 18:54:42.678245: +2024-11-21 18:54:42.678449: Epoch 1478 +2024-11-21 18:54:42.678585: Current learning rate: 0.00832 +2024-11-21 18:55:01.787143: train_loss -0.7674 +2024-11-21 18:55:01.790335: val_loss -0.7711 +2024-11-21 18:55:01.790444: Pseudo dice [0.8591] +2024-11-21 18:55:01.790539: Epoch time: 19.11 s +2024-11-21 18:55:03.026588: +2024-11-21 18:55:03.026803: Epoch 1479 +2024-11-21 18:55:03.026913: Current learning rate: 0.00832 +2024-11-21 18:55:21.893336: train_loss -0.7658 +2024-11-21 18:55:21.899760: val_loss -0.7728 +2024-11-21 18:55:21.899904: Pseudo dice [0.8405] +2024-11-21 18:55:21.900057: Epoch time: 18.87 s +2024-11-21 18:55:22.759932: +2024-11-21 18:55:22.760143: Epoch 1480 +2024-11-21 18:55:22.760281: Current learning rate: 0.00832 +2024-11-21 18:55:41.427004: train_loss -0.7564 +2024-11-21 18:55:41.436430: val_loss -0.7611 +2024-11-21 18:55:41.436585: Pseudo dice [0.8472] +2024-11-21 18:55:41.436685: Epoch time: 18.67 s +2024-11-21 18:55:42.272323: +2024-11-21 18:55:42.272552: Epoch 1481 +2024-11-21 18:55:42.272686: Current learning rate: 0.00832 +2024-11-21 18:56:00.892164: train_loss -0.7588 +2024-11-21 18:56:00.900890: val_loss -0.781 +2024-11-21 18:56:00.901044: Pseudo dice [0.8375] +2024-11-21 18:56:00.901257: Epoch time: 18.62 s +2024-11-21 18:56:01.750341: +2024-11-21 18:56:01.750576: Epoch 1482 +2024-11-21 18:56:01.750703: Current learning rate: 0.00832 +2024-11-21 18:56:21.187653: train_loss -0.7764 +2024-11-21 18:56:21.193459: val_loss -0.7686 +2024-11-21 18:56:21.193592: Pseudo dice [0.8607] +2024-11-21 18:56:21.193699: Epoch time: 19.44 s +2024-11-21 18:56:22.036701: +2024-11-21 18:56:22.036934: Epoch 1483 +2024-11-21 18:56:22.037050: Current learning rate: 0.00831 +2024-11-21 18:56:40.986804: train_loss -0.7738 +2024-11-21 18:56:40.988857: val_loss -0.7813 +2024-11-21 18:56:41.005273: Pseudo dice [0.8575] +2024-11-21 18:56:41.005378: Epoch time: 18.95 s +2024-11-21 18:56:41.842598: +2024-11-21 18:56:41.842834: Epoch 1484 +2024-11-21 18:56:41.842954: Current learning rate: 0.00831 +2024-11-21 18:57:00.837816: train_loss -0.7742 +2024-11-21 18:57:00.855145: val_loss -0.7669 +2024-11-21 18:57:00.855298: Pseudo dice [0.8515] +2024-11-21 18:57:00.855396: Epoch time: 19.0 s +2024-11-21 18:57:01.693567: +2024-11-21 18:57:01.693780: Epoch 1485 +2024-11-21 18:57:01.693903: Current learning rate: 0.00831 +2024-11-21 18:57:20.923075: train_loss -0.7721 +2024-11-21 18:57:20.935112: val_loss -0.7894 +2024-11-21 18:57:20.935241: Pseudo dice [0.8608] +2024-11-21 18:57:20.935325: Epoch time: 19.23 s +2024-11-21 18:57:20.935602: Yayy! New best EMA pseudo Dice: 0.8499 +2024-11-21 18:57:21.966698: +2024-11-21 18:57:21.966933: Epoch 1486 +2024-11-21 18:57:21.967048: Current learning rate: 0.00831 +2024-11-21 18:57:41.394531: train_loss -0.7709 +2024-11-21 18:57:41.402099: val_loss -0.7526 +2024-11-21 18:57:41.402240: Pseudo dice [0.8463] +2024-11-21 18:57:41.402345: Epoch time: 19.43 s +2024-11-21 18:57:42.295808: +2024-11-21 18:57:42.296012: Epoch 1487 +2024-11-21 18:57:42.296139: Current learning rate: 0.00831 +2024-11-21 18:58:01.838118: train_loss -0.7483 +2024-11-21 18:58:01.840832: val_loss -0.739 +2024-11-21 18:58:01.840932: Pseudo dice [0.8335] +2024-11-21 18:58:01.841030: Epoch time: 19.54 s +2024-11-21 18:58:02.675821: +2024-11-21 18:58:02.676034: Epoch 1488 +2024-11-21 18:58:02.676167: Current learning rate: 0.00831 +2024-11-21 18:58:21.656650: train_loss -0.755 +2024-11-21 18:58:21.665259: val_loss -0.7602 +2024-11-21 18:58:21.665406: Pseudo dice [0.8489] +2024-11-21 18:58:21.665501: Epoch time: 18.98 s +2024-11-21 18:58:22.515282: +2024-11-21 18:58:22.515495: Epoch 1489 +2024-11-21 18:58:22.515615: Current learning rate: 0.00831 +2024-11-21 18:58:42.071689: train_loss -0.7682 +2024-11-21 18:58:42.074595: val_loss -0.7675 +2024-11-21 18:58:42.074706: Pseudo dice [0.8566] +2024-11-21 18:58:42.074799: Epoch time: 19.56 s +2024-11-21 18:58:43.302734: +2024-11-21 18:58:43.302949: Epoch 1490 +2024-11-21 18:58:43.303089: Current learning rate: 0.00831 +2024-11-21 18:59:01.499389: train_loss -0.7687 +2024-11-21 18:59:01.506668: val_loss -0.7452 +2024-11-21 18:59:01.506819: Pseudo dice [0.848] +2024-11-21 18:59:01.506920: Epoch time: 18.2 s +2024-11-21 18:59:02.499512: +2024-11-21 18:59:02.499726: Epoch 1491 +2024-11-21 18:59:02.499845: Current learning rate: 0.00831 +2024-11-21 18:59:22.030786: train_loss -0.763 +2024-11-21 18:59:22.046836: val_loss -0.7586 +2024-11-21 18:59:22.046986: Pseudo dice [0.8435] +2024-11-21 18:59:22.047089: Epoch time: 19.53 s +2024-11-21 18:59:23.010228: +2024-11-21 18:59:23.010483: Epoch 1492 +2024-11-21 18:59:23.010619: Current learning rate: 0.0083 +2024-11-21 18:59:42.533885: train_loss -0.7534 +2024-11-21 18:59:42.538517: val_loss -0.7759 +2024-11-21 18:59:42.538661: Pseudo dice [0.8406] +2024-11-21 18:59:42.538750: Epoch time: 19.52 s +2024-11-21 18:59:43.573998: +2024-11-21 18:59:43.574222: Epoch 1493 +2024-11-21 18:59:43.574344: Current learning rate: 0.0083 +2024-11-21 19:00:02.958121: train_loss -0.7449 +2024-11-21 19:00:02.962278: val_loss -0.7434 +2024-11-21 19:00:02.962418: Pseudo dice [0.8361] +2024-11-21 19:00:02.962531: Epoch time: 19.38 s +2024-11-21 19:00:03.844794: +2024-11-21 19:00:03.845032: Epoch 1494 +2024-11-21 19:00:03.845155: Current learning rate: 0.0083 +2024-11-21 19:00:22.638305: train_loss -0.7618 +2024-11-21 19:00:22.641529: val_loss -0.7439 +2024-11-21 19:00:22.641635: Pseudo dice [0.8438] +2024-11-21 19:00:22.641716: Epoch time: 18.79 s +2024-11-21 19:00:23.653330: +2024-11-21 19:00:23.653550: Epoch 1495 +2024-11-21 19:00:23.653700: Current learning rate: 0.0083 +2024-11-21 19:00:43.576123: train_loss -0.7655 +2024-11-21 19:00:43.579369: val_loss -0.7671 +2024-11-21 19:00:43.579492: Pseudo dice [0.8279] +2024-11-21 19:00:43.579577: Epoch time: 19.92 s +2024-11-21 19:00:44.511127: +2024-11-21 19:00:44.511353: Epoch 1496 +2024-11-21 19:00:44.540014: Current learning rate: 0.0083 +2024-11-21 19:01:04.333344: train_loss -0.7682 +2024-11-21 19:01:04.340195: val_loss -0.7732 +2024-11-21 19:01:04.340344: Pseudo dice [0.8636] +2024-11-21 19:01:04.340452: Epoch time: 19.82 s +2024-11-21 19:01:05.355345: +2024-11-21 19:01:05.355542: Epoch 1497 +2024-11-21 19:01:05.355665: Current learning rate: 0.0083 +2024-11-21 19:01:24.928522: train_loss -0.7676 +2024-11-21 19:01:24.931769: val_loss -0.7614 +2024-11-21 19:01:24.931928: Pseudo dice [0.8593] +2024-11-21 19:01:24.932018: Epoch time: 19.57 s +2024-11-21 19:01:25.830492: +2024-11-21 19:01:25.830686: Epoch 1498 +2024-11-21 19:01:25.830807: Current learning rate: 0.0083 +2024-11-21 19:01:45.068442: train_loss -0.7709 +2024-11-21 19:01:45.075583: val_loss -0.7589 +2024-11-21 19:01:45.075712: Pseudo dice [0.8444] +2024-11-21 19:01:45.075803: Epoch time: 19.24 s +2024-11-21 19:01:45.932652: +2024-11-21 19:01:45.932851: Epoch 1499 +2024-11-21 19:01:45.932979: Current learning rate: 0.0083 +2024-11-21 19:02:04.725574: train_loss -0.7677 +2024-11-21 19:02:04.730252: val_loss -0.7522 +2024-11-21 19:02:04.730374: Pseudo dice [0.838] +2024-11-21 19:02:04.730475: Epoch time: 18.79 s +2024-11-21 19:02:05.755486: +2024-11-21 19:02:05.755685: Epoch 1500 +2024-11-21 19:02:05.755808: Current learning rate: 0.0083 +2024-11-21 19:02:24.531255: train_loss -0.764 +2024-11-21 19:02:24.544906: val_loss -0.7577 +2024-11-21 19:02:24.545057: Pseudo dice [0.8401] +2024-11-21 19:02:24.545154: Epoch time: 18.78 s +2024-11-21 19:02:25.497268: +2024-11-21 19:02:25.497476: Epoch 1501 +2024-11-21 19:02:25.497593: Current learning rate: 0.00829 +2024-11-21 19:02:44.555773: train_loss -0.7613 +2024-11-21 19:02:44.571817: val_loss -0.7289 +2024-11-21 19:02:44.571946: Pseudo dice [0.8318] +2024-11-21 19:02:44.572034: Epoch time: 19.06 s +2024-11-21 19:02:45.600738: +2024-11-21 19:02:45.600976: Epoch 1502 +2024-11-21 19:02:45.601092: Current learning rate: 0.00829 +2024-11-21 19:03:04.757468: train_loss -0.7709 +2024-11-21 19:03:04.767561: val_loss -0.7611 +2024-11-21 19:03:04.767706: Pseudo dice [0.8478] +2024-11-21 19:03:04.767801: Epoch time: 19.16 s +2024-11-21 19:03:05.695651: +2024-11-21 19:03:05.695858: Epoch 1503 +2024-11-21 19:03:05.695977: Current learning rate: 0.00829 +2024-11-21 19:03:25.218300: train_loss -0.7734 +2024-11-21 19:03:25.225889: val_loss -0.7584 +2024-11-21 19:03:25.226016: Pseudo dice [0.849] +2024-11-21 19:03:25.226132: Epoch time: 19.52 s +2024-11-21 19:03:26.130467: +2024-11-21 19:03:26.130700: Epoch 1504 +2024-11-21 19:03:26.130819: Current learning rate: 0.00829 +2024-11-21 19:03:45.772642: train_loss -0.7647 +2024-11-21 19:03:45.779188: val_loss -0.7491 +2024-11-21 19:03:45.779325: Pseudo dice [0.8415] +2024-11-21 19:03:45.779429: Epoch time: 19.64 s +2024-11-21 19:03:46.617036: +2024-11-21 19:03:46.617264: Epoch 1505 +2024-11-21 19:03:46.617386: Current learning rate: 0.00829 +2024-11-21 19:04:06.421449: train_loss -0.7684 +2024-11-21 19:04:06.423754: val_loss -0.7616 +2024-11-21 19:04:06.423858: Pseudo dice [0.8474] +2024-11-21 19:04:06.423957: Epoch time: 19.81 s +2024-11-21 19:04:07.259965: +2024-11-21 19:04:07.260193: Epoch 1506 +2024-11-21 19:04:07.260313: Current learning rate: 0.00829 +2024-11-21 19:04:25.305521: train_loss -0.777 +2024-11-21 19:04:25.313435: val_loss -0.7756 +2024-11-21 19:04:25.313550: Pseudo dice [0.8607] +2024-11-21 19:04:25.313630: Epoch time: 18.05 s +2024-11-21 19:04:26.341912: +2024-11-21 19:04:26.342133: Epoch 1507 +2024-11-21 19:04:26.342257: Current learning rate: 0.00829 +2024-11-21 19:04:43.754981: train_loss -0.7706 +2024-11-21 19:04:43.762299: val_loss -0.7758 +2024-11-21 19:04:43.762455: Pseudo dice [0.8437] +2024-11-21 19:04:43.762552: Epoch time: 17.41 s +2024-11-21 19:04:44.794451: +2024-11-21 19:04:44.794667: Epoch 1508 +2024-11-21 19:04:44.794810: Current learning rate: 0.00829 +2024-11-21 19:05:03.150982: train_loss -0.7656 +2024-11-21 19:05:03.161795: val_loss -0.7603 +2024-11-21 19:05:03.161960: Pseudo dice [0.8508] +2024-11-21 19:05:03.162674: Epoch time: 18.36 s +2024-11-21 19:05:04.308831: +2024-11-21 19:05:04.309028: Epoch 1509 +2024-11-21 19:05:04.309164: Current learning rate: 0.00829 +2024-11-21 19:05:23.473166: train_loss -0.7681 +2024-11-21 19:05:23.480651: val_loss -0.7707 +2024-11-21 19:05:23.480794: Pseudo dice [0.8575] +2024-11-21 19:05:23.480910: Epoch time: 19.17 s +2024-11-21 19:05:24.411654: +2024-11-21 19:05:24.411837: Epoch 1510 +2024-11-21 19:05:24.411968: Current learning rate: 0.00828 +2024-11-21 19:05:42.612459: train_loss -0.7563 +2024-11-21 19:05:42.617038: val_loss -0.7607 +2024-11-21 19:05:42.617203: Pseudo dice [0.8458] +2024-11-21 19:05:42.617292: Epoch time: 18.2 s +2024-11-21 19:05:43.837701: +2024-11-21 19:05:43.837903: Epoch 1511 +2024-11-21 19:05:43.838023: Current learning rate: 0.00828 +2024-11-21 19:06:02.267659: train_loss -0.7549 +2024-11-21 19:06:02.274467: val_loss -0.7826 +2024-11-21 19:06:02.274585: Pseudo dice [0.8486] +2024-11-21 19:06:02.274819: Epoch time: 18.43 s +2024-11-21 19:06:03.313632: +2024-11-21 19:06:03.313912: Epoch 1512 +2024-11-21 19:06:03.314037: Current learning rate: 0.00828 +2024-11-21 19:06:22.881316: train_loss -0.769 +2024-11-21 19:06:22.891968: val_loss -0.7385 +2024-11-21 19:06:22.892219: Pseudo dice [0.8505] +2024-11-21 19:06:22.892373: Epoch time: 19.57 s +2024-11-21 19:06:23.755174: +2024-11-21 19:06:23.755390: Epoch 1513 +2024-11-21 19:06:23.755505: Current learning rate: 0.00828 +2024-11-21 19:06:43.552216: train_loss -0.7763 +2024-11-21 19:06:43.558998: val_loss -0.7781 +2024-11-21 19:06:43.559127: Pseudo dice [0.8533] +2024-11-21 19:06:43.559210: Epoch time: 19.8 s +2024-11-21 19:06:44.417950: +2024-11-21 19:06:44.418176: Epoch 1514 +2024-11-21 19:06:44.418311: Current learning rate: 0.00828 +2024-11-21 19:07:03.137009: train_loss -0.7812 +2024-11-21 19:07:03.144205: val_loss -0.7697 +2024-11-21 19:07:03.144422: Pseudo dice [0.8563] +2024-11-21 19:07:03.144524: Epoch time: 18.72 s +2024-11-21 19:07:04.091492: +2024-11-21 19:07:04.091718: Epoch 1515 +2024-11-21 19:07:04.091855: Current learning rate: 0.00828 +2024-11-21 19:07:23.291054: train_loss -0.7748 +2024-11-21 19:07:23.297150: val_loss -0.7486 +2024-11-21 19:07:23.297300: Pseudo dice [0.8261] +2024-11-21 19:07:23.297402: Epoch time: 19.2 s +2024-11-21 19:07:24.135301: +2024-11-21 19:07:24.135507: Epoch 1516 +2024-11-21 19:07:24.135643: Current learning rate: 0.00828 +2024-11-21 19:07:44.070249: train_loss -0.7671 +2024-11-21 19:07:44.084057: val_loss -0.7452 +2024-11-21 19:07:44.084217: Pseudo dice [0.8406] +2024-11-21 19:07:44.084312: Epoch time: 19.94 s +2024-11-21 19:07:45.123658: +2024-11-21 19:07:45.123907: Epoch 1517 +2024-11-21 19:07:45.124033: Current learning rate: 0.00828 +2024-11-21 19:08:03.618494: train_loss -0.7649 +2024-11-21 19:08:03.624393: val_loss -0.7537 +2024-11-21 19:08:03.624548: Pseudo dice [0.8445] +2024-11-21 19:08:03.624643: Epoch time: 18.5 s +2024-11-21 19:08:04.491512: +2024-11-21 19:08:04.491716: Epoch 1518 +2024-11-21 19:08:04.491832: Current learning rate: 0.00827 +2024-11-21 19:08:24.554302: train_loss -0.7582 +2024-11-21 19:08:24.560693: val_loss -0.7535 +2024-11-21 19:08:24.560844: Pseudo dice [0.8448] +2024-11-21 19:08:24.561018: Epoch time: 20.06 s +2024-11-21 19:08:25.395823: +2024-11-21 19:08:25.396045: Epoch 1519 +2024-11-21 19:08:25.396171: Current learning rate: 0.00827 +2024-11-21 19:08:45.615946: train_loss -0.7536 +2024-11-21 19:08:45.627556: val_loss -0.7646 +2024-11-21 19:08:45.627701: Pseudo dice [0.846] +2024-11-21 19:08:45.627791: Epoch time: 20.22 s +2024-11-21 19:08:46.501933: +2024-11-21 19:08:46.502131: Epoch 1520 +2024-11-21 19:08:46.502251: Current learning rate: 0.00827 +2024-11-21 19:09:05.357511: train_loss -0.758 +2024-11-21 19:09:05.361856: val_loss -0.7697 +2024-11-21 19:09:05.361987: Pseudo dice [0.8507] +2024-11-21 19:09:05.362113: Epoch time: 18.86 s +2024-11-21 19:09:06.198523: +2024-11-21 19:09:06.198744: Epoch 1521 +2024-11-21 19:09:06.198884: Current learning rate: 0.00827 +2024-11-21 19:09:25.760000: train_loss -0.7728 +2024-11-21 19:09:25.767799: val_loss -0.7559 +2024-11-21 19:09:25.767953: Pseudo dice [0.8404] +2024-11-21 19:09:25.768070: Epoch time: 19.56 s +2024-11-21 19:09:27.021376: +2024-11-21 19:09:27.021596: Epoch 1522 +2024-11-21 19:09:27.021728: Current learning rate: 0.00827 +2024-11-21 19:09:44.877565: train_loss -0.7759 +2024-11-21 19:09:44.885693: val_loss -0.7636 +2024-11-21 19:09:44.885839: Pseudo dice [0.8465] +2024-11-21 19:09:44.885952: Epoch time: 17.86 s +2024-11-21 19:09:45.909836: +2024-11-21 19:09:45.910076: Epoch 1523 +2024-11-21 19:09:45.910206: Current learning rate: 0.00827 +2024-11-21 19:10:06.552236: train_loss -0.7746 +2024-11-21 19:10:06.559368: val_loss -0.7529 +2024-11-21 19:10:06.559559: Pseudo dice [0.8547] +2024-11-21 19:10:06.559641: Epoch time: 20.64 s +2024-11-21 19:10:07.437555: +2024-11-21 19:10:07.437777: Epoch 1524 +2024-11-21 19:10:07.437898: Current learning rate: 0.00827 +2024-11-21 19:10:25.717397: train_loss -0.7758 +2024-11-21 19:10:25.720125: val_loss -0.7947 +2024-11-21 19:10:25.720268: Pseudo dice [0.8666] +2024-11-21 19:10:25.720392: Epoch time: 18.28 s +2024-11-21 19:10:26.597524: +2024-11-21 19:10:26.597767: Epoch 1525 +2024-11-21 19:10:26.597908: Current learning rate: 0.00827 +2024-11-21 19:10:45.366247: train_loss -0.7644 +2024-11-21 19:10:45.373052: val_loss -0.7453 +2024-11-21 19:10:45.373200: Pseudo dice [0.8409] +2024-11-21 19:10:45.373303: Epoch time: 18.77 s +2024-11-21 19:10:46.467591: +2024-11-21 19:10:46.467823: Epoch 1526 +2024-11-21 19:10:46.467967: Current learning rate: 0.00827 +2024-11-21 19:11:05.879674: train_loss -0.7661 +2024-11-21 19:11:05.884680: val_loss -0.751 +2024-11-21 19:11:05.884861: Pseudo dice [0.8408] +2024-11-21 19:11:05.884953: Epoch time: 19.41 s +2024-11-21 19:11:06.748263: +2024-11-21 19:11:06.748489: Epoch 1527 +2024-11-21 19:11:06.748612: Current learning rate: 0.00826 +2024-11-21 19:11:25.736957: train_loss -0.7562 +2024-11-21 19:11:25.739858: val_loss -0.7502 +2024-11-21 19:11:25.739964: Pseudo dice [0.8306] +2024-11-21 19:11:25.740047: Epoch time: 18.99 s +2024-11-21 19:11:26.581346: +2024-11-21 19:11:26.581564: Epoch 1528 +2024-11-21 19:11:26.581673: Current learning rate: 0.00826 +2024-11-21 19:11:45.878863: train_loss -0.7639 +2024-11-21 19:11:45.881503: val_loss -0.7407 +2024-11-21 19:11:45.881598: Pseudo dice [0.8574] +2024-11-21 19:11:45.881680: Epoch time: 19.3 s +2024-11-21 19:11:46.716300: +2024-11-21 19:11:46.716502: Epoch 1529 +2024-11-21 19:11:46.716616: Current learning rate: 0.00826 +2024-11-21 19:12:05.144944: train_loss -0.7544 +2024-11-21 19:12:05.150417: val_loss -0.746 +2024-11-21 19:12:05.150563: Pseudo dice [0.8432] +2024-11-21 19:12:05.150713: Epoch time: 18.43 s +2024-11-21 19:12:06.046799: +2024-11-21 19:12:06.047026: Epoch 1530 +2024-11-21 19:12:06.047156: Current learning rate: 0.00826 +2024-11-21 19:12:26.590528: train_loss -0.7672 +2024-11-21 19:12:26.595659: val_loss -0.7799 +2024-11-21 19:12:26.595813: Pseudo dice [0.8574] +2024-11-21 19:12:26.595909: Epoch time: 20.54 s +2024-11-21 19:12:27.440690: +2024-11-21 19:12:27.440905: Epoch 1531 +2024-11-21 19:12:27.441028: Current learning rate: 0.00826 +2024-11-21 19:12:47.530316: train_loss -0.7678 +2024-11-21 19:12:47.532968: val_loss -0.7577 +2024-11-21 19:12:47.533115: Pseudo dice [0.8485] +2024-11-21 19:12:47.533229: Epoch time: 20.09 s +2024-11-21 19:12:48.368884: +2024-11-21 19:12:48.369126: Epoch 1532 +2024-11-21 19:12:48.369252: Current learning rate: 0.00826 +2024-11-21 19:13:08.637415: train_loss -0.7646 +2024-11-21 19:13:08.640504: val_loss -0.7453 +2024-11-21 19:13:08.640636: Pseudo dice [0.8524] +2024-11-21 19:13:08.640725: Epoch time: 20.27 s +2024-11-21 19:13:09.531232: +2024-11-21 19:13:09.531445: Epoch 1533 +2024-11-21 19:13:09.531575: Current learning rate: 0.00826 +2024-11-21 19:13:29.331388: train_loss -0.7528 +2024-11-21 19:13:29.339952: val_loss -0.7632 +2024-11-21 19:13:29.340120: Pseudo dice [0.8317] +2024-11-21 19:13:29.340225: Epoch time: 19.8 s +2024-11-21 19:13:30.279865: +2024-11-21 19:13:30.280089: Epoch 1534 +2024-11-21 19:13:30.280225: Current learning rate: 0.00826 +2024-11-21 19:13:49.155801: train_loss -0.7571 +2024-11-21 19:13:49.162481: val_loss -0.7723 +2024-11-21 19:13:49.162602: Pseudo dice [0.8467] +2024-11-21 19:13:49.162685: Epoch time: 18.88 s +2024-11-21 19:13:50.094410: +2024-11-21 19:13:50.094630: Epoch 1535 +2024-11-21 19:13:50.094744: Current learning rate: 0.00826 +2024-11-21 19:14:09.198701: train_loss -0.7694 +2024-11-21 19:14:09.201316: val_loss -0.7811 +2024-11-21 19:14:09.201412: Pseudo dice [0.8396] +2024-11-21 19:14:09.201503: Epoch time: 19.11 s +2024-11-21 19:14:10.041212: +2024-11-21 19:14:10.041426: Epoch 1536 +2024-11-21 19:14:10.041547: Current learning rate: 0.00825 +2024-11-21 19:14:29.941746: train_loss -0.7737 +2024-11-21 19:14:29.947975: val_loss -0.7411 +2024-11-21 19:14:29.948137: Pseudo dice [0.858] +2024-11-21 19:14:29.948228: Epoch time: 19.9 s +2024-11-21 19:14:30.797864: +2024-11-21 19:14:30.798091: Epoch 1537 +2024-11-21 19:14:30.798216: Current learning rate: 0.00825 +2024-11-21 19:14:48.850569: train_loss -0.7716 +2024-11-21 19:14:48.862528: val_loss -0.7753 +2024-11-21 19:14:48.862908: Pseudo dice [0.854] +2024-11-21 19:14:48.863035: Epoch time: 18.05 s +2024-11-21 19:14:49.722677: +2024-11-21 19:14:49.722892: Epoch 1538 +2024-11-21 19:14:49.723020: Current learning rate: 0.00825 +2024-11-21 19:15:08.655011: train_loss -0.7677 +2024-11-21 19:15:08.673772: val_loss -0.7538 +2024-11-21 19:15:08.673928: Pseudo dice [0.8334] +2024-11-21 19:15:08.674020: Epoch time: 18.93 s +2024-11-21 19:15:09.636929: +2024-11-21 19:15:09.637134: Epoch 1539 +2024-11-21 19:15:09.637253: Current learning rate: 0.00825 +2024-11-21 19:15:27.381968: train_loss -0.7622 +2024-11-21 19:15:27.390583: val_loss -0.7489 +2024-11-21 19:15:27.390728: Pseudo dice [0.842] +2024-11-21 19:15:27.390853: Epoch time: 17.75 s +2024-11-21 19:15:28.302366: +2024-11-21 19:15:28.302568: Epoch 1540 +2024-11-21 19:15:28.302701: Current learning rate: 0.00825 +2024-11-21 19:15:46.468554: train_loss -0.7815 +2024-11-21 19:15:46.473412: val_loss -0.757 +2024-11-21 19:15:46.473540: Pseudo dice [0.8385] +2024-11-21 19:15:46.473634: Epoch time: 18.17 s +2024-11-21 19:15:47.335434: +2024-11-21 19:15:47.335641: Epoch 1541 +2024-11-21 19:15:47.335749: Current learning rate: 0.00825 +2024-11-21 19:16:06.906648: train_loss -0.7775 +2024-11-21 19:16:06.912854: val_loss -0.7732 +2024-11-21 19:16:06.912986: Pseudo dice [0.848] +2024-11-21 19:16:06.913076: Epoch time: 19.57 s +2024-11-21 19:16:07.829701: +2024-11-21 19:16:07.829907: Epoch 1542 +2024-11-21 19:16:07.830018: Current learning rate: 0.00825 +2024-11-21 19:16:25.758627: train_loss -0.7667 +2024-11-21 19:16:25.772235: val_loss -0.7847 +2024-11-21 19:16:25.772363: Pseudo dice [0.8465] +2024-11-21 19:16:25.772466: Epoch time: 17.93 s +2024-11-21 19:16:27.067675: +2024-11-21 19:16:27.067908: Epoch 1543 +2024-11-21 19:16:27.068038: Current learning rate: 0.00825 +2024-11-21 19:16:45.290974: train_loss -0.7766 +2024-11-21 19:16:45.308193: val_loss -0.7448 +2024-11-21 19:16:45.308342: Pseudo dice [0.8467] +2024-11-21 19:16:45.308440: Epoch time: 18.22 s +2024-11-21 19:16:46.186826: +2024-11-21 19:16:46.187086: Epoch 1544 +2024-11-21 19:16:46.187227: Current learning rate: 0.00824 +2024-11-21 19:17:05.495497: train_loss -0.7743 +2024-11-21 19:17:05.497844: val_loss -0.7512 +2024-11-21 19:17:05.497940: Pseudo dice [0.8356] +2024-11-21 19:17:05.498031: Epoch time: 19.31 s +2024-11-21 19:17:06.342822: +2024-11-21 19:17:06.343079: Epoch 1545 +2024-11-21 19:17:06.343216: Current learning rate: 0.00824 +2024-11-21 19:17:25.681588: train_loss -0.7641 +2024-11-21 19:17:25.697656: val_loss -0.7599 +2024-11-21 19:17:25.697793: Pseudo dice [0.8548] +2024-11-21 19:17:25.697884: Epoch time: 19.34 s +2024-11-21 19:17:26.570366: +2024-11-21 19:17:26.570585: Epoch 1546 +2024-11-21 19:17:26.570700: Current learning rate: 0.00824 +2024-11-21 19:17:46.391206: train_loss -0.7757 +2024-11-21 19:17:46.399573: val_loss -0.7405 +2024-11-21 19:17:46.399717: Pseudo dice [0.8398] +2024-11-21 19:17:46.399814: Epoch time: 19.82 s +2024-11-21 19:17:47.571578: +2024-11-21 19:17:47.571822: Epoch 1547 +2024-11-21 19:17:47.571944: Current learning rate: 0.00824 +2024-11-21 19:18:06.883708: train_loss -0.7568 +2024-11-21 19:18:06.891695: val_loss -0.7578 +2024-11-21 19:18:06.891823: Pseudo dice [0.8517] +2024-11-21 19:18:06.891924: Epoch time: 19.31 s +2024-11-21 19:18:07.781649: +2024-11-21 19:18:07.781894: Epoch 1548 +2024-11-21 19:18:07.782022: Current learning rate: 0.00824 +2024-11-21 19:18:27.045842: train_loss -0.7615 +2024-11-21 19:18:27.054810: val_loss -0.751 +2024-11-21 19:18:27.054998: Pseudo dice [0.8451] +2024-11-21 19:18:27.055106: Epoch time: 19.27 s +2024-11-21 19:18:27.914317: +2024-11-21 19:18:27.914512: Epoch 1549 +2024-11-21 19:18:27.914630: Current learning rate: 0.00824 +2024-11-21 19:18:47.371932: train_loss -0.7682 +2024-11-21 19:18:47.380176: val_loss -0.7446 +2024-11-21 19:18:47.380322: Pseudo dice [0.8446] +2024-11-21 19:18:47.380405: Epoch time: 19.46 s +2024-11-21 19:18:48.435343: +2024-11-21 19:18:48.435565: Epoch 1550 +2024-11-21 19:18:48.435699: Current learning rate: 0.00824 +2024-11-21 19:19:08.567762: train_loss -0.7653 +2024-11-21 19:19:08.573865: val_loss -0.7784 +2024-11-21 19:19:08.573997: Pseudo dice [0.8479] +2024-11-21 19:19:08.574111: Epoch time: 20.13 s +2024-11-21 19:19:09.575101: +2024-11-21 19:19:09.575305: Epoch 1551 +2024-11-21 19:19:09.575433: Current learning rate: 0.00824 +2024-11-21 19:19:27.636867: train_loss -0.7662 +2024-11-21 19:19:27.645533: val_loss -0.7775 +2024-11-21 19:19:27.645694: Pseudo dice [0.8482] +2024-11-21 19:19:27.645785: Epoch time: 18.06 s +2024-11-21 19:19:28.601130: +2024-11-21 19:19:28.601357: Epoch 1552 +2024-11-21 19:19:28.601474: Current learning rate: 0.00824 +2024-11-21 19:19:46.942729: train_loss -0.769 +2024-11-21 19:19:46.949507: val_loss -0.7658 +2024-11-21 19:19:46.949642: Pseudo dice [0.8639] +2024-11-21 19:19:46.949744: Epoch time: 18.34 s +2024-11-21 19:19:48.175440: +2024-11-21 19:19:48.175714: Epoch 1553 +2024-11-21 19:19:48.175848: Current learning rate: 0.00823 +2024-11-21 19:20:06.827780: train_loss -0.7722 +2024-11-21 19:20:06.835301: val_loss -0.7636 +2024-11-21 19:20:06.835517: Pseudo dice [0.8438] +2024-11-21 19:20:06.835606: Epoch time: 18.65 s +2024-11-21 19:20:07.698811: +2024-11-21 19:20:07.699421: Epoch 1554 +2024-11-21 19:20:07.699552: Current learning rate: 0.00823 +2024-11-21 19:20:26.777109: train_loss -0.7743 +2024-11-21 19:20:26.783093: val_loss -0.7595 +2024-11-21 19:20:26.783242: Pseudo dice [0.8588] +2024-11-21 19:20:26.783354: Epoch time: 19.08 s +2024-11-21 19:20:27.627998: +2024-11-21 19:20:27.628255: Epoch 1555 +2024-11-21 19:20:27.628385: Current learning rate: 0.00823 +2024-11-21 19:20:47.352316: train_loss -0.7729 +2024-11-21 19:20:47.361626: val_loss -0.7579 +2024-11-21 19:20:47.361781: Pseudo dice [0.852] +2024-11-21 19:20:47.361905: Epoch time: 19.73 s +2024-11-21 19:20:48.405746: +2024-11-21 19:20:48.405978: Epoch 1556 +2024-11-21 19:20:48.406113: Current learning rate: 0.00823 +2024-11-21 19:21:07.504845: train_loss -0.7798 +2024-11-21 19:21:07.512255: val_loss -0.7353 +2024-11-21 19:21:07.512391: Pseudo dice [0.8248] +2024-11-21 19:21:07.512498: Epoch time: 19.1 s +2024-11-21 19:21:08.450941: +2024-11-21 19:21:08.451196: Epoch 1557 +2024-11-21 19:21:08.451332: Current learning rate: 0.00823 +2024-11-21 19:21:26.423967: train_loss -0.7703 +2024-11-21 19:21:26.430172: val_loss -0.7478 +2024-11-21 19:21:26.430339: Pseudo dice [0.842] +2024-11-21 19:21:26.430434: Epoch time: 17.97 s +2024-11-21 19:21:27.391471: +2024-11-21 19:21:27.391695: Epoch 1558 +2024-11-21 19:21:27.391809: Current learning rate: 0.00823 +2024-11-21 19:21:46.955954: train_loss -0.7747 +2024-11-21 19:21:46.962588: val_loss -0.7629 +2024-11-21 19:21:46.962796: Pseudo dice [0.8502] +2024-11-21 19:21:46.962883: Epoch time: 19.57 s +2024-11-21 19:21:47.917708: +2024-11-21 19:21:47.917953: Epoch 1559 +2024-11-21 19:21:47.918071: Current learning rate: 0.00823 +2024-11-21 19:22:08.249019: train_loss -0.7749 +2024-11-21 19:22:08.252033: val_loss -0.7656 +2024-11-21 19:22:08.252374: Pseudo dice [0.8398] +2024-11-21 19:22:08.252476: Epoch time: 20.33 s +2024-11-21 19:22:09.209633: +2024-11-21 19:22:09.209850: Epoch 1560 +2024-11-21 19:22:09.209971: Current learning rate: 0.00823 +2024-11-21 19:22:28.092836: train_loss -0.7632 +2024-11-21 19:22:28.105494: val_loss -0.7246 +2024-11-21 19:22:28.105641: Pseudo dice [0.8342] +2024-11-21 19:22:28.105731: Epoch time: 18.88 s +2024-11-21 19:22:29.142612: +2024-11-21 19:22:29.142869: Epoch 1561 +2024-11-21 19:22:29.142995: Current learning rate: 0.00823 +2024-11-21 19:22:47.107507: train_loss -0.7757 +2024-11-21 19:22:47.112988: val_loss -0.7505 +2024-11-21 19:22:47.113124: Pseudo dice [0.8276] +2024-11-21 19:22:47.113218: Epoch time: 17.97 s +2024-11-21 19:22:47.960798: +2024-11-21 19:22:47.960999: Epoch 1562 +2024-11-21 19:22:47.961126: Current learning rate: 0.00822 +2024-11-21 19:23:08.467361: train_loss -0.7699 +2024-11-21 19:23:08.475498: val_loss -0.7703 +2024-11-21 19:23:08.475625: Pseudo dice [0.8495] +2024-11-21 19:23:08.475715: Epoch time: 20.51 s +2024-11-21 19:23:09.320335: +2024-11-21 19:23:09.320541: Epoch 1563 +2024-11-21 19:23:09.320660: Current learning rate: 0.00822 +2024-11-21 19:23:27.566679: train_loss -0.7663 +2024-11-21 19:23:27.569464: val_loss -0.7393 +2024-11-21 19:23:27.569772: Pseudo dice [0.8499] +2024-11-21 19:23:27.569867: Epoch time: 18.25 s +2024-11-21 19:23:28.802740: +2024-11-21 19:23:28.802996: Epoch 1564 +2024-11-21 19:23:28.803128: Current learning rate: 0.00822 +2024-11-21 19:23:47.642526: train_loss -0.7601 +2024-11-21 19:23:47.647986: val_loss -0.7611 +2024-11-21 19:23:47.648117: Pseudo dice [0.8427] +2024-11-21 19:23:47.648218: Epoch time: 18.84 s +2024-11-21 19:23:48.493652: +2024-11-21 19:23:48.493887: Epoch 1565 +2024-11-21 19:23:48.494000: Current learning rate: 0.00822 +2024-11-21 19:24:08.785377: train_loss -0.775 +2024-11-21 19:24:08.789672: val_loss -0.7539 +2024-11-21 19:24:08.789795: Pseudo dice [0.8468] +2024-11-21 19:24:08.789880: Epoch time: 20.29 s +2024-11-21 19:24:09.804934: +2024-11-21 19:24:09.805166: Epoch 1566 +2024-11-21 19:24:09.805288: Current learning rate: 0.00822 +2024-11-21 19:24:28.978320: train_loss -0.7722 +2024-11-21 19:24:28.985254: val_loss -0.788 +2024-11-21 19:24:28.985394: Pseudo dice [0.8501] +2024-11-21 19:24:28.985544: Epoch time: 19.17 s +2024-11-21 19:24:29.847985: +2024-11-21 19:24:29.848192: Epoch 1567 +2024-11-21 19:24:29.848304: Current learning rate: 0.00822 +2024-11-21 19:24:48.810215: train_loss -0.7678 +2024-11-21 19:24:48.818350: val_loss -0.752 +2024-11-21 19:24:48.818480: Pseudo dice [0.8452] +2024-11-21 19:24:48.818577: Epoch time: 18.96 s +2024-11-21 19:24:49.812733: +2024-11-21 19:24:49.812956: Epoch 1568 +2024-11-21 19:24:49.813077: Current learning rate: 0.00822 +2024-11-21 19:25:08.737818: train_loss -0.7594 +2024-11-21 19:25:08.744524: val_loss -0.7527 +2024-11-21 19:25:08.744724: Pseudo dice [0.8457] +2024-11-21 19:25:08.744830: Epoch time: 18.93 s +2024-11-21 19:25:09.618117: +2024-11-21 19:25:09.618370: Epoch 1569 +2024-11-21 19:25:09.618479: Current learning rate: 0.00822 +2024-11-21 19:25:28.327668: train_loss -0.7722 +2024-11-21 19:25:28.336299: val_loss -0.7621 +2024-11-21 19:25:28.336452: Pseudo dice [0.8587] +2024-11-21 19:25:28.336537: Epoch time: 18.71 s +2024-11-21 19:25:29.186716: +2024-11-21 19:25:29.186908: Epoch 1570 +2024-11-21 19:25:29.187035: Current learning rate: 0.00822 +2024-11-21 19:25:48.075680: train_loss -0.7717 +2024-11-21 19:25:48.088021: val_loss -0.7505 +2024-11-21 19:25:48.088161: Pseudo dice [0.8471] +2024-11-21 19:25:48.088264: Epoch time: 18.89 s +2024-11-21 19:25:49.062329: +2024-11-21 19:25:49.062562: Epoch 1571 +2024-11-21 19:25:49.062690: Current learning rate: 0.00821 +2024-11-21 19:26:08.719762: train_loss -0.767 +2024-11-21 19:26:08.732792: val_loss -0.7616 +2024-11-21 19:26:08.732935: Pseudo dice [0.8438] +2024-11-21 19:26:08.733033: Epoch time: 19.66 s +2024-11-21 19:26:09.581280: +2024-11-21 19:26:09.581491: Epoch 1572 +2024-11-21 19:26:09.581626: Current learning rate: 0.00821 +2024-11-21 19:26:29.033969: train_loss -0.7597 +2024-11-21 19:26:29.038007: val_loss -0.7626 +2024-11-21 19:26:29.038146: Pseudo dice [0.8432] +2024-11-21 19:26:29.038234: Epoch time: 19.45 s +2024-11-21 19:26:29.907447: +2024-11-21 19:26:29.907644: Epoch 1573 +2024-11-21 19:26:29.907779: Current learning rate: 0.00821 +2024-11-21 19:26:49.075525: train_loss -0.7762 +2024-11-21 19:26:49.081095: val_loss -0.7442 +2024-11-21 19:26:49.081245: Pseudo dice [0.8471] +2024-11-21 19:26:49.081342: Epoch time: 19.17 s +2024-11-21 19:26:49.943326: +2024-11-21 19:26:49.943533: Epoch 1574 +2024-11-21 19:26:49.943650: Current learning rate: 0.00821 +2024-11-21 19:27:08.800698: train_loss -0.7689 +2024-11-21 19:27:08.812004: val_loss -0.775 +2024-11-21 19:27:08.812205: Pseudo dice [0.8593] +2024-11-21 19:27:08.812333: Epoch time: 18.86 s +2024-11-21 19:27:09.682245: +2024-11-21 19:27:09.682477: Epoch 1575 +2024-11-21 19:27:09.682626: Current learning rate: 0.00821 +2024-11-21 19:27:28.364110: train_loss -0.7694 +2024-11-21 19:27:28.369656: val_loss -0.7543 +2024-11-21 19:27:28.369808: Pseudo dice [0.848] +2024-11-21 19:27:28.369902: Epoch time: 18.68 s +2024-11-21 19:27:29.219608: +2024-11-21 19:27:29.219826: Epoch 1576 +2024-11-21 19:27:29.219944: Current learning rate: 0.00821 +2024-11-21 19:27:48.358728: train_loss -0.7606 +2024-11-21 19:27:48.366007: val_loss -0.7731 +2024-11-21 19:27:48.366131: Pseudo dice [0.8521] +2024-11-21 19:27:48.366215: Epoch time: 19.14 s +2024-11-21 19:27:49.351473: +2024-11-21 19:27:49.351719: Epoch 1577 +2024-11-21 19:27:49.351845: Current learning rate: 0.00821 +2024-11-21 19:28:09.047869: train_loss -0.7703 +2024-11-21 19:28:09.053713: val_loss -0.7289 +2024-11-21 19:28:09.053859: Pseudo dice [0.8362] +2024-11-21 19:28:09.053942: Epoch time: 19.7 s +2024-11-21 19:28:09.945266: +2024-11-21 19:28:09.945478: Epoch 1578 +2024-11-21 19:28:09.945596: Current learning rate: 0.00821 +2024-11-21 19:28:28.776212: train_loss -0.761 +2024-11-21 19:28:28.783676: val_loss -0.7563 +2024-11-21 19:28:28.783844: Pseudo dice [0.8344] +2024-11-21 19:28:28.783945: Epoch time: 18.83 s +2024-11-21 19:28:29.675126: +2024-11-21 19:28:29.675338: Epoch 1579 +2024-11-21 19:28:29.675460: Current learning rate: 0.0082 +2024-11-21 19:28:49.186255: train_loss -0.7549 +2024-11-21 19:28:49.189515: val_loss -0.7459 +2024-11-21 19:28:49.189627: Pseudo dice [0.8391] +2024-11-21 19:28:49.189724: Epoch time: 19.51 s +2024-11-21 19:28:50.030136: +2024-11-21 19:28:50.030374: Epoch 1580 +2024-11-21 19:28:50.030490: Current learning rate: 0.0082 +2024-11-21 19:29:08.594811: train_loss -0.7597 +2024-11-21 19:29:08.596391: val_loss -0.7514 +2024-11-21 19:29:08.596517: Pseudo dice [0.8441] +2024-11-21 19:29:08.596602: Epoch time: 18.57 s +2024-11-21 19:29:09.438528: +2024-11-21 19:29:09.438734: Epoch 1581 +2024-11-21 19:29:09.438880: Current learning rate: 0.0082 +2024-11-21 19:29:29.383461: train_loss -0.7703 +2024-11-21 19:29:29.389606: val_loss -0.7476 +2024-11-21 19:29:29.389748: Pseudo dice [0.8479] +2024-11-21 19:29:29.389838: Epoch time: 19.95 s +2024-11-21 19:29:30.245363: +2024-11-21 19:29:30.245558: Epoch 1582 +2024-11-21 19:29:30.245683: Current learning rate: 0.0082 +2024-11-21 19:29:49.923027: train_loss -0.7751 +2024-11-21 19:29:49.931608: val_loss -0.7892 +2024-11-21 19:29:49.931770: Pseudo dice [0.8598] +2024-11-21 19:29:49.931922: Epoch time: 19.68 s +2024-11-21 19:29:50.772741: +2024-11-21 19:29:50.772949: Epoch 1583 +2024-11-21 19:29:50.773096: Current learning rate: 0.0082 +2024-11-21 19:30:10.051353: train_loss -0.7685 +2024-11-21 19:30:10.053649: val_loss -0.7577 +2024-11-21 19:30:10.053744: Pseudo dice [0.8404] +2024-11-21 19:30:10.053852: Epoch time: 19.28 s +2024-11-21 19:30:10.893627: +2024-11-21 19:30:10.893832: Epoch 1584 +2024-11-21 19:30:10.893947: Current learning rate: 0.0082 +2024-11-21 19:30:30.279100: train_loss -0.7809 +2024-11-21 19:30:30.280842: val_loss -0.7694 +2024-11-21 19:30:30.280950: Pseudo dice [0.8587] +2024-11-21 19:30:30.281045: Epoch time: 19.39 s +2024-11-21 19:30:31.503294: +2024-11-21 19:30:31.516373: Epoch 1585 +2024-11-21 19:30:31.516516: Current learning rate: 0.0082 +2024-11-21 19:30:50.900256: train_loss -0.7731 +2024-11-21 19:30:50.904610: val_loss -0.7547 +2024-11-21 19:30:50.904742: Pseudo dice [0.8569] +2024-11-21 19:30:50.904832: Epoch time: 19.4 s +2024-11-21 19:30:51.776229: +2024-11-21 19:30:51.776439: Epoch 1586 +2024-11-21 19:30:51.776565: Current learning rate: 0.0082 +2024-11-21 19:31:11.752495: train_loss -0.7722 +2024-11-21 19:31:11.760407: val_loss -0.7435 +2024-11-21 19:31:11.760541: Pseudo dice [0.8413] +2024-11-21 19:31:11.760628: Epoch time: 19.98 s +2024-11-21 19:31:12.796247: +2024-11-21 19:31:12.796463: Epoch 1587 +2024-11-21 19:31:12.796604: Current learning rate: 0.0082 +2024-11-21 19:31:31.801189: train_loss -0.7734 +2024-11-21 19:31:31.809145: val_loss -0.7573 +2024-11-21 19:31:31.809278: Pseudo dice [0.8414] +2024-11-21 19:31:31.809372: Epoch time: 19.01 s +2024-11-21 19:31:32.744239: +2024-11-21 19:31:32.744492: Epoch 1588 +2024-11-21 19:31:32.744614: Current learning rate: 0.00819 +2024-11-21 19:31:51.443767: train_loss -0.7781 +2024-11-21 19:31:51.448801: val_loss -0.7591 +2024-11-21 19:31:51.448971: Pseudo dice [0.8586] +2024-11-21 19:31:51.449093: Epoch time: 18.7 s +2024-11-21 19:31:52.291812: +2024-11-21 19:31:52.292003: Epoch 1589 +2024-11-21 19:31:52.292132: Current learning rate: 0.00819 +2024-11-21 19:32:10.501984: train_loss -0.7721 +2024-11-21 19:32:10.509004: val_loss -0.755 +2024-11-21 19:32:10.509168: Pseudo dice [0.8501] +2024-11-21 19:32:10.509287: Epoch time: 18.21 s +2024-11-21 19:32:11.354741: +2024-11-21 19:32:11.354951: Epoch 1590 +2024-11-21 19:32:11.355091: Current learning rate: 0.00819 +2024-11-21 19:32:31.081126: train_loss -0.7723 +2024-11-21 19:32:31.092262: val_loss -0.7621 +2024-11-21 19:32:31.092402: Pseudo dice [0.8428] +2024-11-21 19:32:31.092493: Epoch time: 19.73 s +2024-11-21 19:32:32.008617: +2024-11-21 19:32:32.008831: Epoch 1591 +2024-11-21 19:32:32.008964: Current learning rate: 0.00819 +2024-11-21 19:32:50.481845: train_loss -0.7604 +2024-11-21 19:32:50.490376: val_loss -0.7428 +2024-11-21 19:32:50.490571: Pseudo dice [0.8445] +2024-11-21 19:32:50.490669: Epoch time: 18.47 s +2024-11-21 19:32:51.329403: +2024-11-21 19:32:51.329606: Epoch 1592 +2024-11-21 19:32:51.329744: Current learning rate: 0.00819 +2024-11-21 19:33:11.018640: train_loss -0.7582 +2024-11-21 19:33:11.029878: val_loss -0.7636 +2024-11-21 19:33:11.030025: Pseudo dice [0.842] +2024-11-21 19:33:11.030140: Epoch time: 19.69 s +2024-11-21 19:33:11.929865: +2024-11-21 19:33:11.930069: Epoch 1593 +2024-11-21 19:33:11.930184: Current learning rate: 0.00819 +2024-11-21 19:33:30.461139: train_loss -0.7633 +2024-11-21 19:33:30.468693: val_loss -0.7636 +2024-11-21 19:33:30.468837: Pseudo dice [0.8513] +2024-11-21 19:33:30.468932: Epoch time: 18.53 s +2024-11-21 19:33:31.499190: +2024-11-21 19:33:31.499390: Epoch 1594 +2024-11-21 19:33:31.499509: Current learning rate: 0.00819 +2024-11-21 19:33:51.179514: train_loss -0.7529 +2024-11-21 19:33:51.185438: val_loss -0.7663 +2024-11-21 19:33:51.185573: Pseudo dice [0.84] +2024-11-21 19:33:51.185664: Epoch time: 19.68 s +2024-11-21 19:33:52.666056: +2024-11-21 19:33:52.666324: Epoch 1595 +2024-11-21 19:33:52.666452: Current learning rate: 0.00819 +2024-11-21 19:34:12.008042: train_loss -0.7608 +2024-11-21 19:34:12.013595: val_loss -0.7781 +2024-11-21 19:34:12.013737: Pseudo dice [0.8434] +2024-11-21 19:34:12.013841: Epoch time: 19.34 s +2024-11-21 19:34:12.906315: +2024-11-21 19:34:12.906565: Epoch 1596 +2024-11-21 19:34:12.906674: Current learning rate: 0.00819 +2024-11-21 19:34:33.567511: train_loss -0.7735 +2024-11-21 19:34:33.570201: val_loss -0.7801 +2024-11-21 19:34:33.570329: Pseudo dice [0.8542] +2024-11-21 19:34:33.570431: Epoch time: 20.66 s +2024-11-21 19:34:34.473490: +2024-11-21 19:34:34.473699: Epoch 1597 +2024-11-21 19:34:34.473817: Current learning rate: 0.00818 +2024-11-21 19:34:53.633440: train_loss -0.7653 +2024-11-21 19:34:53.644951: val_loss -0.7815 +2024-11-21 19:34:53.645088: Pseudo dice [0.8527] +2024-11-21 19:34:53.667661: Epoch time: 19.16 s +2024-11-21 19:34:54.538054: +2024-11-21 19:34:54.538270: Epoch 1598 +2024-11-21 19:34:54.538397: Current learning rate: 0.00818 +2024-11-21 19:35:14.213096: train_loss -0.7701 +2024-11-21 19:35:14.218743: val_loss -0.7503 +2024-11-21 19:35:14.218894: Pseudo dice [0.8364] +2024-11-21 19:35:14.218994: Epoch time: 19.68 s +2024-11-21 19:35:15.107137: +2024-11-21 19:35:15.107349: Epoch 1599 +2024-11-21 19:35:15.107471: Current learning rate: 0.00818 +2024-11-21 19:35:35.302332: train_loss -0.7602 +2024-11-21 19:35:35.305001: val_loss -0.7424 +2024-11-21 19:35:35.305138: Pseudo dice [0.8399] +2024-11-21 19:35:35.305235: Epoch time: 20.2 s +2024-11-21 19:35:36.366525: +2024-11-21 19:35:36.366734: Epoch 1600 +2024-11-21 19:35:36.366846: Current learning rate: 0.00818 +2024-11-21 19:35:56.017971: train_loss -0.7728 +2024-11-21 19:35:56.025524: val_loss -0.7485 +2024-11-21 19:35:56.025698: Pseudo dice [0.8445] +2024-11-21 19:35:56.025793: Epoch time: 19.65 s +2024-11-21 19:35:56.893984: +2024-11-21 19:35:56.894197: Epoch 1601 +2024-11-21 19:35:56.894309: Current learning rate: 0.00818 +2024-11-21 19:36:16.557405: train_loss -0.7601 +2024-11-21 19:36:16.562831: val_loss -0.7497 +2024-11-21 19:36:16.562970: Pseudo dice [0.849] +2024-11-21 19:36:16.563077: Epoch time: 19.66 s +2024-11-21 19:36:17.407751: +2024-11-21 19:36:17.407954: Epoch 1602 +2024-11-21 19:36:17.408092: Current learning rate: 0.00818 +2024-11-21 19:36:36.114199: train_loss -0.7636 +2024-11-21 19:36:36.117372: val_loss -0.7763 +2024-11-21 19:36:36.117512: Pseudo dice [0.8492] +2024-11-21 19:36:36.117596: Epoch time: 18.71 s +2024-11-21 19:36:36.965138: +2024-11-21 19:36:36.965340: Epoch 1603 +2024-11-21 19:36:36.965457: Current learning rate: 0.00818 +2024-11-21 19:36:55.846529: train_loss -0.7751 +2024-11-21 19:36:55.854861: val_loss -0.7593 +2024-11-21 19:36:55.855000: Pseudo dice [0.8386] +2024-11-21 19:36:55.855110: Epoch time: 18.88 s +2024-11-21 19:36:56.749030: +2024-11-21 19:36:56.749242: Epoch 1604 +2024-11-21 19:36:56.749360: Current learning rate: 0.00818 +2024-11-21 19:37:16.482459: train_loss -0.7672 +2024-11-21 19:37:16.488885: val_loss -0.7882 +2024-11-21 19:37:16.489013: Pseudo dice [0.849] +2024-11-21 19:37:16.489107: Epoch time: 19.73 s +2024-11-21 19:37:17.374017: +2024-11-21 19:37:17.374262: Epoch 1605 +2024-11-21 19:37:17.374382: Current learning rate: 0.00817 +2024-11-21 19:37:37.227433: train_loss -0.7678 +2024-11-21 19:37:37.235481: val_loss -0.7226 +2024-11-21 19:37:37.235613: Pseudo dice [0.8519] +2024-11-21 19:37:37.235707: Epoch time: 19.85 s +2024-11-21 19:37:38.487066: +2024-11-21 19:37:38.487319: Epoch 1606 +2024-11-21 19:37:38.487434: Current learning rate: 0.00817 +2024-11-21 19:37:57.781498: train_loss -0.7578 +2024-11-21 19:37:57.784603: val_loss -0.7633 +2024-11-21 19:37:57.784726: Pseudo dice [0.8467] +2024-11-21 19:37:57.784833: Epoch time: 19.3 s +2024-11-21 19:37:58.624377: +2024-11-21 19:37:58.624602: Epoch 1607 +2024-11-21 19:37:58.624729: Current learning rate: 0.00817 +2024-11-21 19:38:16.681310: train_loss -0.7697 +2024-11-21 19:38:16.685739: val_loss -0.7701 +2024-11-21 19:38:16.685879: Pseudo dice [0.856] +2024-11-21 19:38:16.685985: Epoch time: 18.06 s +2024-11-21 19:38:17.579182: +2024-11-21 19:38:17.579390: Epoch 1608 +2024-11-21 19:38:17.579508: Current learning rate: 0.00817 +2024-11-21 19:38:36.476578: train_loss -0.7628 +2024-11-21 19:38:36.483989: val_loss -0.7476 +2024-11-21 19:38:36.484168: Pseudo dice [0.8538] +2024-11-21 19:38:36.484272: Epoch time: 18.9 s +2024-11-21 19:38:37.333122: +2024-11-21 19:38:37.333334: Epoch 1609 +2024-11-21 19:38:37.333451: Current learning rate: 0.00817 +2024-11-21 19:38:57.394053: train_loss -0.7663 +2024-11-21 19:38:57.400538: val_loss -0.7656 +2024-11-21 19:38:57.400664: Pseudo dice [0.8504] +2024-11-21 19:38:57.400769: Epoch time: 20.06 s +2024-11-21 19:38:58.348824: +2024-11-21 19:38:58.349048: Epoch 1610 +2024-11-21 19:38:58.349196: Current learning rate: 0.00817 +2024-11-21 19:39:16.254327: train_loss -0.7689 +2024-11-21 19:39:16.257859: val_loss -0.7731 +2024-11-21 19:39:16.258050: Pseudo dice [0.8498] +2024-11-21 19:39:16.258159: Epoch time: 17.91 s +2024-11-21 19:39:17.104074: +2024-11-21 19:39:17.104295: Epoch 1611 +2024-11-21 19:39:17.104421: Current learning rate: 0.00817 +2024-11-21 19:39:35.789160: train_loss -0.7744 +2024-11-21 19:39:35.799412: val_loss -0.7592 +2024-11-21 19:39:35.799546: Pseudo dice [0.85] +2024-11-21 19:39:35.799635: Epoch time: 18.69 s +2024-11-21 19:39:36.644597: +2024-11-21 19:39:36.644795: Epoch 1612 +2024-11-21 19:39:36.644915: Current learning rate: 0.00817 +2024-11-21 19:39:54.801260: train_loss -0.7692 +2024-11-21 19:39:54.809529: val_loss -0.7663 +2024-11-21 19:39:54.809666: Pseudo dice [0.8433] +2024-11-21 19:39:54.809767: Epoch time: 18.16 s +2024-11-21 19:39:55.716493: +2024-11-21 19:39:55.716700: Epoch 1613 +2024-11-21 19:39:55.716823: Current learning rate: 0.00817 +2024-11-21 19:40:15.952908: train_loss -0.7615 +2024-11-21 19:40:15.965056: val_loss -0.7705 +2024-11-21 19:40:15.965203: Pseudo dice [0.8503] +2024-11-21 19:40:15.965308: Epoch time: 20.24 s +2024-11-21 19:40:16.834207: +2024-11-21 19:40:16.834443: Epoch 1614 +2024-11-21 19:40:16.834567: Current learning rate: 0.00816 +2024-11-21 19:40:35.923762: train_loss -0.7672 +2024-11-21 19:40:35.925489: val_loss -0.7568 +2024-11-21 19:40:35.925605: Pseudo dice [0.846] +2024-11-21 19:40:35.925698: Epoch time: 19.09 s +2024-11-21 19:40:36.783034: +2024-11-21 19:40:36.783247: Epoch 1615 +2024-11-21 19:40:36.783380: Current learning rate: 0.00816 +2024-11-21 19:40:55.579774: train_loss -0.765 +2024-11-21 19:40:55.588708: val_loss -0.7604 +2024-11-21 19:40:55.588857: Pseudo dice [0.8447] +2024-11-21 19:40:55.588955: Epoch time: 18.8 s +2024-11-21 19:40:56.545162: +2024-11-21 19:40:56.545370: Epoch 1616 +2024-11-21 19:40:56.545503: Current learning rate: 0.00816 +2024-11-21 19:41:15.562694: train_loss -0.7718 +2024-11-21 19:41:15.570650: val_loss -0.7523 +2024-11-21 19:41:15.570801: Pseudo dice [0.8388] +2024-11-21 19:41:15.570907: Epoch time: 19.02 s +2024-11-21 19:41:16.699021: +2024-11-21 19:41:16.699251: Epoch 1617 +2024-11-21 19:41:16.699370: Current learning rate: 0.00816 +2024-11-21 19:41:36.262245: train_loss -0.7691 +2024-11-21 19:41:36.264692: val_loss -0.7615 +2024-11-21 19:41:36.264794: Pseudo dice [0.8432] +2024-11-21 19:41:36.264877: Epoch time: 19.56 s +2024-11-21 19:41:37.102386: +2024-11-21 19:41:37.102630: Epoch 1618 +2024-11-21 19:41:37.102744: Current learning rate: 0.00816 +2024-11-21 19:41:56.739140: train_loss -0.7671 +2024-11-21 19:41:56.742073: val_loss -0.7383 +2024-11-21 19:41:56.742216: Pseudo dice [0.8376] +2024-11-21 19:41:56.742317: Epoch time: 19.64 s +2024-11-21 19:41:57.623528: +2024-11-21 19:41:57.623740: Epoch 1619 +2024-11-21 19:41:57.623859: Current learning rate: 0.00816 +2024-11-21 19:42:16.439897: train_loss -0.7556 +2024-11-21 19:42:16.443284: val_loss -0.7549 +2024-11-21 19:42:16.443387: Pseudo dice [0.8465] +2024-11-21 19:42:16.443469: Epoch time: 18.82 s +2024-11-21 19:42:17.283833: +2024-11-21 19:42:17.284066: Epoch 1620 +2024-11-21 19:42:17.284194: Current learning rate: 0.00816 +2024-11-21 19:42:37.217152: train_loss -0.7727 +2024-11-21 19:42:37.242797: val_loss -0.7538 +2024-11-21 19:42:37.242945: Pseudo dice [0.8565] +2024-11-21 19:42:37.243053: Epoch time: 19.93 s +2024-11-21 19:42:38.098845: +2024-11-21 19:42:38.099063: Epoch 1621 +2024-11-21 19:42:38.099183: Current learning rate: 0.00816 +2024-11-21 19:42:58.216890: train_loss -0.7631 +2024-11-21 19:42:58.219122: val_loss -0.7531 +2024-11-21 19:42:58.219266: Pseudo dice [0.8387] +2024-11-21 19:42:58.219358: Epoch time: 20.12 s +2024-11-21 19:42:59.209541: +2024-11-21 19:42:59.209750: Epoch 1622 +2024-11-21 19:42:59.209868: Current learning rate: 0.00816 +2024-11-21 19:43:18.077827: train_loss -0.7554 +2024-11-21 19:43:18.082692: val_loss -0.7344 +2024-11-21 19:43:18.082827: Pseudo dice [0.8368] +2024-11-21 19:43:18.082923: Epoch time: 18.87 s +2024-11-21 19:43:19.037770: +2024-11-21 19:43:19.038042: Epoch 1623 +2024-11-21 19:43:19.038400: Current learning rate: 0.00815 +2024-11-21 19:43:37.847362: train_loss -0.7648 +2024-11-21 19:43:37.853161: val_loss -0.7776 +2024-11-21 19:43:37.853351: Pseudo dice [0.8373] +2024-11-21 19:43:37.853488: Epoch time: 18.81 s +2024-11-21 19:43:38.696459: +2024-11-21 19:43:38.696684: Epoch 1624 +2024-11-21 19:43:38.696801: Current learning rate: 0.00815 +2024-11-21 19:43:57.811030: train_loss -0.7617 +2024-11-21 19:43:57.820628: val_loss -0.7486 +2024-11-21 19:43:57.820767: Pseudo dice [0.8407] +2024-11-21 19:43:57.820856: Epoch time: 19.12 s +2024-11-21 19:43:58.659112: +2024-11-21 19:43:58.659332: Epoch 1625 +2024-11-21 19:43:58.659469: Current learning rate: 0.00815 +2024-11-21 19:44:17.008430: train_loss -0.7734 +2024-11-21 19:44:17.014035: val_loss -0.7576 +2024-11-21 19:44:17.014210: Pseudo dice [0.8386] +2024-11-21 19:44:17.014311: Epoch time: 18.35 s +2024-11-21 19:44:17.872414: +2024-11-21 19:44:17.872625: Epoch 1626 +2024-11-21 19:44:17.872754: Current learning rate: 0.00815 +2024-11-21 19:44:38.003454: train_loss -0.762 +2024-11-21 19:44:38.008528: val_loss -0.7661 +2024-11-21 19:44:38.008662: Pseudo dice [0.8615] +2024-11-21 19:44:38.008770: Epoch time: 20.13 s +2024-11-21 19:44:39.286322: +2024-11-21 19:44:39.286540: Epoch 1627 +2024-11-21 19:44:39.286653: Current learning rate: 0.00815 +2024-11-21 19:44:57.975213: train_loss -0.7752 +2024-11-21 19:44:57.985425: val_loss -0.7695 +2024-11-21 19:44:57.985572: Pseudo dice [0.8524] +2024-11-21 19:44:57.985667: Epoch time: 18.69 s +2024-11-21 19:44:58.826757: +2024-11-21 19:44:58.826974: Epoch 1628 +2024-11-21 19:44:58.827091: Current learning rate: 0.00815 +2024-11-21 19:45:17.201781: train_loss -0.7629 +2024-11-21 19:45:17.208866: val_loss -0.7297 +2024-11-21 19:45:17.209006: Pseudo dice [0.841] +2024-11-21 19:45:17.209114: Epoch time: 18.38 s +2024-11-21 19:45:18.136077: +2024-11-21 19:45:18.136306: Epoch 1629 +2024-11-21 19:45:18.136439: Current learning rate: 0.00815 +2024-11-21 19:45:37.652174: train_loss -0.7591 +2024-11-21 19:45:37.653884: val_loss -0.7642 +2024-11-21 19:45:37.654002: Pseudo dice [0.863] +2024-11-21 19:45:37.654094: Epoch time: 19.52 s +2024-11-21 19:45:38.496623: +2024-11-21 19:45:38.496833: Epoch 1630 +2024-11-21 19:45:38.496965: Current learning rate: 0.00815 +2024-11-21 19:45:57.657413: train_loss -0.7712 +2024-11-21 19:45:57.664105: val_loss -0.7716 +2024-11-21 19:45:57.664230: Pseudo dice [0.8528] +2024-11-21 19:45:57.664332: Epoch time: 19.16 s +2024-11-21 19:45:58.511247: +2024-11-21 19:45:58.511456: Epoch 1631 +2024-11-21 19:45:58.511570: Current learning rate: 0.00814 +2024-11-21 19:46:18.899842: train_loss -0.773 +2024-11-21 19:46:18.905911: val_loss -0.7547 +2024-11-21 19:46:18.906037: Pseudo dice [0.8445] +2024-11-21 19:46:18.906157: Epoch time: 20.39 s +2024-11-21 19:46:19.782238: +2024-11-21 19:46:19.782476: Epoch 1632 +2024-11-21 19:46:19.782605: Current learning rate: 0.00814 +2024-11-21 19:46:37.551762: train_loss -0.7732 +2024-11-21 19:46:37.557266: val_loss -0.7464 +2024-11-21 19:46:37.557384: Pseudo dice [0.8353] +2024-11-21 19:46:37.557481: Epoch time: 17.77 s +2024-11-21 19:46:38.398364: +2024-11-21 19:46:38.398581: Epoch 1633 +2024-11-21 19:46:38.398697: Current learning rate: 0.00814 +2024-11-21 19:46:56.731457: train_loss -0.7743 +2024-11-21 19:46:56.756289: val_loss -0.777 +2024-11-21 19:46:56.756449: Pseudo dice [0.8585] +2024-11-21 19:46:56.756551: Epoch time: 18.33 s +2024-11-21 19:46:57.685429: +2024-11-21 19:46:57.685632: Epoch 1634 +2024-11-21 19:46:57.685757: Current learning rate: 0.00814 +2024-11-21 19:47:17.673925: train_loss -0.7691 +2024-11-21 19:47:17.680856: val_loss -0.7595 +2024-11-21 19:47:17.681009: Pseudo dice [0.8399] +2024-11-21 19:47:17.681109: Epoch time: 19.99 s +2024-11-21 19:47:18.564213: +2024-11-21 19:47:18.564441: Epoch 1635 +2024-11-21 19:47:18.564563: Current learning rate: 0.00814 +2024-11-21 19:47:37.098445: train_loss -0.7782 +2024-11-21 19:47:37.115764: val_loss -0.7627 +2024-11-21 19:47:37.115922: Pseudo dice [0.8554] +2024-11-21 19:47:37.116293: Epoch time: 18.54 s +2024-11-21 19:47:38.112485: +2024-11-21 19:47:38.112697: Epoch 1636 +2024-11-21 19:47:38.112813: Current learning rate: 0.00814 +2024-11-21 19:47:56.834055: train_loss -0.7788 +2024-11-21 19:47:56.854250: val_loss -0.7559 +2024-11-21 19:47:56.854424: Pseudo dice [0.8464] +2024-11-21 19:47:56.854534: Epoch time: 18.72 s +2024-11-21 19:47:58.189779: +2024-11-21 19:47:58.190042: Epoch 1637 +2024-11-21 19:47:58.190187: Current learning rate: 0.00814 +2024-11-21 19:48:18.161841: train_loss -0.7775 +2024-11-21 19:48:18.163806: val_loss -0.7608 +2024-11-21 19:48:18.163913: Pseudo dice [0.8484] +2024-11-21 19:48:18.164011: Epoch time: 19.97 s +2024-11-21 19:48:18.991990: +2024-11-21 19:48:18.992216: Epoch 1638 +2024-11-21 19:48:18.992347: Current learning rate: 0.00814 +2024-11-21 19:48:37.885549: train_loss -0.7793 +2024-11-21 19:48:37.891359: val_loss -0.7603 +2024-11-21 19:48:37.891488: Pseudo dice [0.847] +2024-11-21 19:48:37.891575: Epoch time: 18.89 s +2024-11-21 19:48:38.911700: +2024-11-21 19:48:38.911940: Epoch 1639 +2024-11-21 19:48:38.912081: Current learning rate: 0.00814 +2024-11-21 19:48:56.926732: train_loss -0.7682 +2024-11-21 19:48:56.934251: val_loss -0.7647 +2024-11-21 19:48:56.934379: Pseudo dice [0.8227] +2024-11-21 19:48:56.934487: Epoch time: 18.02 s +2024-11-21 19:48:57.867621: +2024-11-21 19:48:57.867862: Epoch 1640 +2024-11-21 19:48:57.867979: Current learning rate: 0.00813 +2024-11-21 19:49:16.894507: train_loss -0.7739 +2024-11-21 19:49:16.898965: val_loss -0.7647 +2024-11-21 19:49:16.899160: Pseudo dice [0.8484] +2024-11-21 19:49:16.899264: Epoch time: 19.03 s +2024-11-21 19:49:17.852129: +2024-11-21 19:49:17.852354: Epoch 1641 +2024-11-21 19:49:17.852470: Current learning rate: 0.00813 +2024-11-21 19:49:36.459818: train_loss -0.7637 +2024-11-21 19:49:36.462315: val_loss -0.7435 +2024-11-21 19:49:36.462431: Pseudo dice [0.8411] +2024-11-21 19:49:36.462540: Epoch time: 18.61 s +2024-11-21 19:49:37.294433: +2024-11-21 19:49:37.294638: Epoch 1642 +2024-11-21 19:49:37.294765: Current learning rate: 0.00813 +2024-11-21 19:49:55.913522: train_loss -0.7762 +2024-11-21 19:49:55.916118: val_loss -0.7427 +2024-11-21 19:49:55.916237: Pseudo dice [0.8511] +2024-11-21 19:49:55.916336: Epoch time: 18.62 s +2024-11-21 19:49:56.741158: +2024-11-21 19:49:56.741369: Epoch 1643 +2024-11-21 19:49:56.741491: Current learning rate: 0.00813 +2024-11-21 19:50:16.047545: train_loss -0.7748 +2024-11-21 19:50:16.054141: val_loss -0.7815 +2024-11-21 19:50:16.054299: Pseudo dice [0.8622] +2024-11-21 19:50:16.054406: Epoch time: 19.31 s +2024-11-21 19:50:16.932977: +2024-11-21 19:50:16.933195: Epoch 1644 +2024-11-21 19:50:16.933337: Current learning rate: 0.00813 +2024-11-21 19:50:35.687813: train_loss -0.7688 +2024-11-21 19:50:35.694022: val_loss -0.7592 +2024-11-21 19:50:35.694158: Pseudo dice [0.8312] +2024-11-21 19:50:35.694256: Epoch time: 18.76 s +2024-11-21 19:50:36.617736: +2024-11-21 19:50:36.617959: Epoch 1645 +2024-11-21 19:50:36.618093: Current learning rate: 0.00813 +2024-11-21 19:50:55.976485: train_loss -0.7624 +2024-11-21 19:50:55.982497: val_loss -0.77 +2024-11-21 19:50:55.982636: Pseudo dice [0.8373] +2024-11-21 19:50:55.982727: Epoch time: 19.36 s +2024-11-21 19:50:56.867927: +2024-11-21 19:50:56.868211: Epoch 1646 +2024-11-21 19:50:56.868347: Current learning rate: 0.00813 +2024-11-21 19:51:15.003052: train_loss -0.7669 +2024-11-21 19:51:15.006056: val_loss -0.7805 +2024-11-21 19:51:15.006168: Pseudo dice [0.8408] +2024-11-21 19:51:15.006270: Epoch time: 18.14 s +2024-11-21 19:51:15.826985: +2024-11-21 19:51:15.827180: Epoch 1647 +2024-11-21 19:51:15.827299: Current learning rate: 0.00813 +2024-11-21 19:51:35.836883: train_loss -0.7643 +2024-11-21 19:51:35.839446: val_loss -0.7587 +2024-11-21 19:51:35.839548: Pseudo dice [0.838] +2024-11-21 19:51:35.839644: Epoch time: 20.01 s +2024-11-21 19:51:37.055294: +2024-11-21 19:51:37.055502: Epoch 1648 +2024-11-21 19:51:37.055623: Current learning rate: 0.00813 +2024-11-21 19:51:55.928656: train_loss -0.761 +2024-11-21 19:51:55.937866: val_loss -0.7595 +2024-11-21 19:51:55.937992: Pseudo dice [0.8384] +2024-11-21 19:51:55.938084: Epoch time: 18.87 s +2024-11-21 19:51:56.830814: +2024-11-21 19:51:56.831063: Epoch 1649 +2024-11-21 19:51:56.831190: Current learning rate: 0.00812 +2024-11-21 19:52:15.591239: train_loss -0.7685 +2024-11-21 19:52:15.597459: val_loss -0.7641 +2024-11-21 19:52:15.597591: Pseudo dice [0.8404] +2024-11-21 19:52:15.597684: Epoch time: 18.76 s +2024-11-21 19:52:16.654474: +2024-11-21 19:52:16.654695: Epoch 1650 +2024-11-21 19:52:16.654809: Current learning rate: 0.00812 +2024-11-21 19:52:35.411124: train_loss -0.7664 +2024-11-21 19:52:35.416847: val_loss -0.7522 +2024-11-21 19:52:35.416984: Pseudo dice [0.8483] +2024-11-21 19:52:35.417089: Epoch time: 18.76 s +2024-11-21 19:52:36.250747: +2024-11-21 19:52:36.251009: Epoch 1651 +2024-11-21 19:52:36.251137: Current learning rate: 0.00812 +2024-11-21 19:52:55.073350: train_loss -0.7647 +2024-11-21 19:52:55.079818: val_loss -0.7743 +2024-11-21 19:52:55.079961: Pseudo dice [0.8447] +2024-11-21 19:52:55.080052: Epoch time: 18.82 s +2024-11-21 19:52:56.105984: +2024-11-21 19:52:56.106211: Epoch 1652 +2024-11-21 19:52:56.106335: Current learning rate: 0.00812 +2024-11-21 19:53:15.503708: train_loss -0.7668 +2024-11-21 19:53:15.509676: val_loss -0.7805 +2024-11-21 19:53:15.509805: Pseudo dice [0.8555] +2024-11-21 19:53:15.509907: Epoch time: 19.4 s +2024-11-21 19:53:16.377921: +2024-11-21 19:53:16.378131: Epoch 1653 +2024-11-21 19:53:16.378245: Current learning rate: 0.00812 +2024-11-21 19:53:35.883504: train_loss -0.7691 +2024-11-21 19:53:35.911443: val_loss -0.7653 +2024-11-21 19:53:35.911575: Pseudo dice [0.866] +2024-11-21 19:53:35.911736: Epoch time: 19.51 s +2024-11-21 19:53:36.915620: +2024-11-21 19:53:36.915840: Epoch 1654 +2024-11-21 19:53:36.915959: Current learning rate: 0.00812 +2024-11-21 19:53:55.910754: train_loss -0.7676 +2024-11-21 19:53:55.918996: val_loss -0.7654 +2024-11-21 19:53:55.919130: Pseudo dice [0.8355] +2024-11-21 19:53:55.919220: Epoch time: 19.0 s +2024-11-21 19:53:56.848314: +2024-11-21 19:53:56.848524: Epoch 1655 +2024-11-21 19:53:56.848647: Current learning rate: 0.00812 +2024-11-21 19:54:16.134110: train_loss -0.7517 +2024-11-21 19:54:16.139768: val_loss -0.7415 +2024-11-21 19:54:16.139911: Pseudo dice [0.8327] +2024-11-21 19:54:16.140023: Epoch time: 19.29 s +2024-11-21 19:54:17.008709: +2024-11-21 19:54:17.008929: Epoch 1656 +2024-11-21 19:54:17.009069: Current learning rate: 0.00812 +2024-11-21 19:54:36.278274: train_loss -0.7541 +2024-11-21 19:54:36.286205: val_loss -0.7358 +2024-11-21 19:54:36.286345: Pseudo dice [0.845] +2024-11-21 19:54:36.286449: Epoch time: 19.27 s +2024-11-21 19:54:37.227200: +2024-11-21 19:54:37.227403: Epoch 1657 +2024-11-21 19:54:37.227518: Current learning rate: 0.00811 +2024-11-21 19:54:56.172055: train_loss -0.7624 +2024-11-21 19:54:56.177460: val_loss -0.7785 +2024-11-21 19:54:56.177585: Pseudo dice [0.8585] +2024-11-21 19:54:56.177673: Epoch time: 18.95 s +2024-11-21 19:54:57.010721: +2024-11-21 19:54:57.010916: Epoch 1658 +2024-11-21 19:54:57.011037: Current learning rate: 0.00811 +2024-11-21 19:55:16.841677: train_loss -0.7628 +2024-11-21 19:55:16.847493: val_loss -0.751 +2024-11-21 19:55:16.847622: Pseudo dice [0.8423] +2024-11-21 19:55:16.847719: Epoch time: 19.83 s +2024-11-21 19:55:18.077515: +2024-11-21 19:55:18.077728: Epoch 1659 +2024-11-21 19:55:18.077839: Current learning rate: 0.00811 +2024-11-21 19:55:37.051872: train_loss -0.7677 +2024-11-21 19:55:37.059019: val_loss -0.7579 +2024-11-21 19:55:37.059163: Pseudo dice [0.8427] +2024-11-21 19:55:37.059267: Epoch time: 18.98 s +2024-11-21 19:55:37.949009: +2024-11-21 19:55:37.949258: Epoch 1660 +2024-11-21 19:55:37.949378: Current learning rate: 0.00811 +2024-11-21 19:55:56.861101: train_loss -0.7711 +2024-11-21 19:55:56.868893: val_loss -0.7671 +2024-11-21 19:55:56.869021: Pseudo dice [0.8412] +2024-11-21 19:55:56.869126: Epoch time: 18.91 s +2024-11-21 19:55:57.730889: +2024-11-21 19:55:57.731135: Epoch 1661 +2024-11-21 19:55:57.731260: Current learning rate: 0.00811 +2024-11-21 19:56:16.944671: train_loss -0.7636 +2024-11-21 19:56:16.959488: val_loss -0.7506 +2024-11-21 19:56:16.959629: Pseudo dice [0.8543] +2024-11-21 19:56:16.959723: Epoch time: 19.21 s +2024-11-21 19:56:17.973975: +2024-11-21 19:56:17.974243: Epoch 1662 +2024-11-21 19:56:17.974379: Current learning rate: 0.00811 +2024-11-21 19:56:39.319076: train_loss -0.7601 +2024-11-21 19:56:39.322018: val_loss -0.7628 +2024-11-21 19:56:39.322135: Pseudo dice [0.8404] +2024-11-21 19:56:39.322239: Epoch time: 21.35 s +2024-11-21 19:56:40.150122: +2024-11-21 19:56:40.150319: Epoch 1663 +2024-11-21 19:56:40.150457: Current learning rate: 0.00811 +2024-11-21 19:56:59.505749: train_loss -0.7705 +2024-11-21 19:56:59.508874: val_loss -0.7471 +2024-11-21 19:56:59.508968: Pseudo dice [0.8399] +2024-11-21 19:56:59.509078: Epoch time: 19.36 s +2024-11-21 19:57:00.332969: +2024-11-21 19:57:00.333212: Epoch 1664 +2024-11-21 19:57:00.333352: Current learning rate: 0.00811 +2024-11-21 19:57:19.258538: train_loss -0.7699 +2024-11-21 19:57:19.268185: val_loss -0.7705 +2024-11-21 19:57:19.268342: Pseudo dice [0.8457] +2024-11-21 19:57:19.268430: Epoch time: 18.93 s +2024-11-21 19:57:20.222939: +2024-11-21 19:57:20.223141: Epoch 1665 +2024-11-21 19:57:20.223274: Current learning rate: 0.00811 +2024-11-21 19:57:39.511094: train_loss -0.7722 +2024-11-21 19:57:39.519758: val_loss -0.7826 +2024-11-21 19:57:39.519970: Pseudo dice [0.8494] +2024-11-21 19:57:39.520078: Epoch time: 19.29 s +2024-11-21 19:57:40.525565: +2024-11-21 19:57:40.525832: Epoch 1666 +2024-11-21 19:57:40.525959: Current learning rate: 0.0081 +2024-11-21 19:57:59.805189: train_loss -0.7674 +2024-11-21 19:57:59.816626: val_loss -0.7405 +2024-11-21 19:57:59.816826: Pseudo dice [0.836] +2024-11-21 19:57:59.816931: Epoch time: 19.28 s +2024-11-21 19:58:00.666439: +2024-11-21 19:58:00.666649: Epoch 1667 +2024-11-21 19:58:00.666781: Current learning rate: 0.0081 +2024-11-21 19:58:20.376381: train_loss -0.765 +2024-11-21 19:58:20.379987: val_loss -0.7646 +2024-11-21 19:58:20.380109: Pseudo dice [0.8485] +2024-11-21 19:58:20.380190: Epoch time: 19.71 s +2024-11-21 19:58:21.215769: +2024-11-21 19:58:21.215974: Epoch 1668 +2024-11-21 19:58:21.216116: Current learning rate: 0.0081 +2024-11-21 19:58:39.695889: train_loss -0.7676 +2024-11-21 19:58:39.707686: val_loss -0.7574 +2024-11-21 19:58:39.707818: Pseudo dice [0.853] +2024-11-21 19:58:39.707916: Epoch time: 18.48 s +2024-11-21 19:58:40.621842: +2024-11-21 19:58:40.622052: Epoch 1669 +2024-11-21 19:58:40.622175: Current learning rate: 0.0081 +2024-11-21 19:58:58.993014: train_loss -0.7748 +2024-11-21 19:58:58.999204: val_loss -0.7434 +2024-11-21 19:58:58.999336: Pseudo dice [0.8319] +2024-11-21 19:58:58.999443: Epoch time: 18.37 s +2024-11-21 19:59:00.354204: +2024-11-21 19:59:00.354453: Epoch 1670 +2024-11-21 19:59:00.354590: Current learning rate: 0.0081 +2024-11-21 19:59:20.301780: train_loss -0.7559 +2024-11-21 19:59:20.307971: val_loss -0.7466 +2024-11-21 19:59:20.308103: Pseudo dice [0.8264] +2024-11-21 19:59:20.308222: Epoch time: 19.95 s +2024-11-21 19:59:21.291245: +2024-11-21 19:59:21.291499: Epoch 1671 +2024-11-21 19:59:21.291643: Current learning rate: 0.0081 +2024-11-21 19:59:39.769692: train_loss -0.7711 +2024-11-21 19:59:39.777940: val_loss -0.7707 +2024-11-21 19:59:39.778083: Pseudo dice [0.8528] +2024-11-21 19:59:39.778169: Epoch time: 18.48 s +2024-11-21 19:59:40.634467: +2024-11-21 19:59:40.634696: Epoch 1672 +2024-11-21 19:59:40.634827: Current learning rate: 0.0081 +2024-11-21 19:59:59.685342: train_loss -0.7761 +2024-11-21 19:59:59.691125: val_loss -0.7527 +2024-11-21 19:59:59.691279: Pseudo dice [0.8527] +2024-11-21 19:59:59.691381: Epoch time: 19.05 s +2024-11-21 20:00:00.640429: +2024-11-21 20:00:00.640660: Epoch 1673 +2024-11-21 20:00:00.640802: Current learning rate: 0.0081 +2024-11-21 20:00:20.582914: train_loss -0.7814 +2024-11-21 20:00:20.587923: val_loss -0.7661 +2024-11-21 20:00:20.588084: Pseudo dice [0.8607] +2024-11-21 20:00:20.588166: Epoch time: 19.94 s +2024-11-21 20:00:21.593223: +2024-11-21 20:00:21.593418: Epoch 1674 +2024-11-21 20:00:21.593539: Current learning rate: 0.0081 +2024-11-21 20:00:40.623977: train_loss -0.7718 +2024-11-21 20:00:40.633814: val_loss -0.7808 +2024-11-21 20:00:40.633963: Pseudo dice [0.8593] +2024-11-21 20:00:40.634064: Epoch time: 19.03 s +2024-11-21 20:00:41.482672: +2024-11-21 20:00:41.482875: Epoch 1675 +2024-11-21 20:00:41.482989: Current learning rate: 0.00809 +2024-11-21 20:01:00.650185: train_loss -0.7693 +2024-11-21 20:01:00.656175: val_loss -0.7575 +2024-11-21 20:01:00.656286: Pseudo dice [0.8572] +2024-11-21 20:01:00.656370: Epoch time: 19.17 s +2024-11-21 20:01:01.652551: +2024-11-21 20:01:01.652790: Epoch 1676 +2024-11-21 20:01:01.652914: Current learning rate: 0.00809 +2024-11-21 20:01:20.046362: train_loss -0.7742 +2024-11-21 20:01:20.052113: val_loss -0.7628 +2024-11-21 20:01:20.052260: Pseudo dice [0.863] +2024-11-21 20:01:20.052367: Epoch time: 18.39 s +2024-11-21 20:01:20.901469: +2024-11-21 20:01:20.901717: Epoch 1677 +2024-11-21 20:01:20.901856: Current learning rate: 0.00809 +2024-11-21 20:01:40.012667: train_loss -0.7623 +2024-11-21 20:01:40.016781: val_loss -0.7797 +2024-11-21 20:01:40.016920: Pseudo dice [0.8608] +2024-11-21 20:01:40.017020: Epoch time: 19.11 s +2024-11-21 20:01:40.017104: Yayy! New best EMA pseudo Dice: 0.8509 +2024-11-21 20:01:41.089165: +2024-11-21 20:01:41.089358: Epoch 1678 +2024-11-21 20:01:41.089473: Current learning rate: 0.00809 +2024-11-21 20:02:00.646736: train_loss -0.7677 +2024-11-21 20:02:00.653749: val_loss -0.7524 +2024-11-21 20:02:00.653876: Pseudo dice [0.8476] +2024-11-21 20:02:00.653982: Epoch time: 19.56 s +2024-11-21 20:02:01.519993: +2024-11-21 20:02:01.520221: Epoch 1679 +2024-11-21 20:02:01.520345: Current learning rate: 0.00809 +2024-11-21 20:02:20.800663: train_loss -0.7724 +2024-11-21 20:02:20.808044: val_loss -0.7719 +2024-11-21 20:02:20.808199: Pseudo dice [0.8427] +2024-11-21 20:02:20.808305: Epoch time: 19.28 s +2024-11-21 20:02:21.822285: +2024-11-21 20:02:21.822470: Epoch 1680 +2024-11-21 20:02:21.822586: Current learning rate: 0.00809 +2024-11-21 20:02:40.438401: train_loss -0.7682 +2024-11-21 20:02:40.443497: val_loss -0.7457 +2024-11-21 20:02:40.443639: Pseudo dice [0.8318] +2024-11-21 20:02:40.443745: Epoch time: 18.62 s +2024-11-21 20:02:41.745576: +2024-11-21 20:02:41.745822: Epoch 1681 +2024-11-21 20:02:41.745950: Current learning rate: 0.00809 +2024-11-21 20:03:00.858107: train_loss -0.7682 +2024-11-21 20:03:00.865880: val_loss -0.7821 +2024-11-21 20:03:00.866002: Pseudo dice [0.8474] +2024-11-21 20:03:00.866127: Epoch time: 19.11 s +2024-11-21 20:03:01.713025: +2024-11-21 20:03:01.713236: Epoch 1682 +2024-11-21 20:03:01.713355: Current learning rate: 0.00809 +2024-11-21 20:03:21.311693: train_loss -0.7668 +2024-11-21 20:03:21.317644: val_loss -0.7362 +2024-11-21 20:03:21.317765: Pseudo dice [0.8249] +2024-11-21 20:03:21.317859: Epoch time: 19.6 s +2024-11-21 20:03:22.154341: +2024-11-21 20:03:22.154534: Epoch 1683 +2024-11-21 20:03:22.154644: Current learning rate: 0.00808 +2024-11-21 20:03:41.319603: train_loss -0.7442 +2024-11-21 20:03:41.328681: val_loss -0.7183 +2024-11-21 20:03:41.328856: Pseudo dice [0.8335] +2024-11-21 20:03:41.328966: Epoch time: 19.17 s +2024-11-21 20:03:42.171297: +2024-11-21 20:03:42.171544: Epoch 1684 +2024-11-21 20:03:42.171662: Current learning rate: 0.00808 +2024-11-21 20:04:01.072194: train_loss -0.7224 +2024-11-21 20:04:01.077450: val_loss -0.7423 +2024-11-21 20:04:01.077573: Pseudo dice [0.831] +2024-11-21 20:04:01.077658: Epoch time: 18.9 s +2024-11-21 20:04:01.938484: +2024-11-21 20:04:01.938681: Epoch 1685 +2024-11-21 20:04:01.938813: Current learning rate: 0.00808 +2024-11-21 20:04:21.934339: train_loss -0.7566 +2024-11-21 20:04:21.939009: val_loss -0.7447 +2024-11-21 20:04:21.939148: Pseudo dice [0.8327] +2024-11-21 20:04:21.939245: Epoch time: 20.0 s +2024-11-21 20:04:23.111695: +2024-11-21 20:04:23.111906: Epoch 1686 +2024-11-21 20:04:23.112028: Current learning rate: 0.00808 +2024-11-21 20:04:42.519017: train_loss -0.7564 +2024-11-21 20:04:42.543687: val_loss -0.772 +2024-11-21 20:04:42.543835: Pseudo dice [0.8417] +2024-11-21 20:04:42.543931: Epoch time: 19.41 s +2024-11-21 20:04:43.383934: +2024-11-21 20:04:43.384146: Epoch 1687 +2024-11-21 20:04:43.384268: Current learning rate: 0.00808 +2024-11-21 20:05:02.958966: train_loss -0.7546 +2024-11-21 20:05:02.965045: val_loss -0.7684 +2024-11-21 20:05:02.965187: Pseudo dice [0.8533] +2024-11-21 20:05:02.965288: Epoch time: 19.58 s +2024-11-21 20:05:03.828639: +2024-11-21 20:05:03.828877: Epoch 1688 +2024-11-21 20:05:03.828989: Current learning rate: 0.00808 +2024-11-21 20:05:22.632751: train_loss -0.7719 +2024-11-21 20:05:22.634807: val_loss -0.7781 +2024-11-21 20:05:22.634943: Pseudo dice [0.8502] +2024-11-21 20:05:22.635052: Epoch time: 18.8 s +2024-11-21 20:05:23.467976: +2024-11-21 20:05:23.468179: Epoch 1689 +2024-11-21 20:05:23.468315: Current learning rate: 0.00808 +2024-11-21 20:05:42.799408: train_loss -0.762 +2024-11-21 20:05:42.806903: val_loss -0.7285 +2024-11-21 20:05:42.807049: Pseudo dice [0.8572] +2024-11-21 20:05:42.807145: Epoch time: 19.33 s +2024-11-21 20:05:43.670399: +2024-11-21 20:05:43.670609: Epoch 1690 +2024-11-21 20:05:43.670733: Current learning rate: 0.00808 +2024-11-21 20:06:02.474923: train_loss -0.7489 +2024-11-21 20:06:02.481246: val_loss -0.7403 +2024-11-21 20:06:02.481373: Pseudo dice [0.8306] +2024-11-21 20:06:02.481473: Epoch time: 18.81 s +2024-11-21 20:06:03.368851: +2024-11-21 20:06:03.369068: Epoch 1691 +2024-11-21 20:06:03.369191: Current learning rate: 0.00808 +2024-11-21 20:06:22.487509: train_loss -0.7631 +2024-11-21 20:06:22.505692: val_loss -0.7736 +2024-11-21 20:06:22.505853: Pseudo dice [0.8512] +2024-11-21 20:06:22.505955: Epoch time: 19.12 s +2024-11-21 20:06:23.391931: +2024-11-21 20:06:23.392139: Epoch 1692 +2024-11-21 20:06:23.392253: Current learning rate: 0.00807 +2024-11-21 20:06:42.786038: train_loss -0.7585 +2024-11-21 20:06:42.801196: val_loss -0.7748 +2024-11-21 20:06:42.801342: Pseudo dice [0.8512] +2024-11-21 20:06:42.801429: Epoch time: 19.39 s +2024-11-21 20:06:43.686454: +2024-11-21 20:06:43.686758: Epoch 1693 +2024-11-21 20:06:43.686882: Current learning rate: 0.00807 +2024-11-21 20:07:01.619329: train_loss -0.7648 +2024-11-21 20:07:01.624876: val_loss -0.7738 +2024-11-21 20:07:01.625036: Pseudo dice [0.8476] +2024-11-21 20:07:01.625160: Epoch time: 17.93 s +2024-11-21 20:07:02.569838: +2024-11-21 20:07:02.570122: Epoch 1694 +2024-11-21 20:07:02.570265: Current learning rate: 0.00807 +2024-11-21 20:07:22.758288: train_loss -0.7651 +2024-11-21 20:07:22.765879: val_loss -0.7572 +2024-11-21 20:07:22.766000: Pseudo dice [0.8542] +2024-11-21 20:07:22.766090: Epoch time: 20.19 s +2024-11-21 20:07:23.774893: +2024-11-21 20:07:23.775111: Epoch 1695 +2024-11-21 20:07:23.775230: Current learning rate: 0.00807 +2024-11-21 20:07:41.900229: train_loss -0.78 +2024-11-21 20:07:41.906389: val_loss -0.748 +2024-11-21 20:07:41.906513: Pseudo dice [0.8591] +2024-11-21 20:07:41.906602: Epoch time: 18.13 s +2024-11-21 20:07:42.791633: +2024-11-21 20:07:42.791825: Epoch 1696 +2024-11-21 20:07:42.791942: Current learning rate: 0.00807 +2024-11-21 20:08:02.431093: train_loss -0.7648 +2024-11-21 20:08:02.438302: val_loss -0.7565 +2024-11-21 20:08:02.438457: Pseudo dice [0.8519] +2024-11-21 20:08:02.438545: Epoch time: 19.64 s +2024-11-21 20:08:03.339526: +2024-11-21 20:08:03.339749: Epoch 1697 +2024-11-21 20:08:03.339877: Current learning rate: 0.00807 +2024-11-21 20:08:21.486093: train_loss -0.7674 +2024-11-21 20:08:21.493636: val_loss -0.7641 +2024-11-21 20:08:21.493803: Pseudo dice [0.8521] +2024-11-21 20:08:21.493906: Epoch time: 18.15 s +2024-11-21 20:08:22.490016: +2024-11-21 20:08:22.490256: Epoch 1698 +2024-11-21 20:08:22.490391: Current learning rate: 0.00807 +2024-11-21 20:08:41.833001: train_loss -0.7706 +2024-11-21 20:08:41.835139: val_loss -0.7533 +2024-11-21 20:08:41.835283: Pseudo dice [0.8546] +2024-11-21 20:08:41.835374: Epoch time: 19.34 s +2024-11-21 20:08:42.670565: +2024-11-21 20:08:42.670761: Epoch 1699 +2024-11-21 20:08:42.682814: Current learning rate: 0.00807 +2024-11-21 20:09:01.549983: train_loss -0.7731 +2024-11-21 20:09:01.551778: val_loss -0.7618 +2024-11-21 20:09:01.551896: Pseudo dice [0.8329] +2024-11-21 20:09:01.551986: Epoch time: 18.88 s +2024-11-21 20:09:02.582261: +2024-11-21 20:09:02.582468: Epoch 1700 +2024-11-21 20:09:02.582588: Current learning rate: 0.00807 +2024-11-21 20:09:21.938151: train_loss -0.7577 +2024-11-21 20:09:21.940416: val_loss -0.7494 +2024-11-21 20:09:21.940576: Pseudo dice [0.8481] +2024-11-21 20:09:21.940694: Epoch time: 19.36 s +2024-11-21 20:09:22.790490: +2024-11-21 20:09:22.790720: Epoch 1701 +2024-11-21 20:09:22.790849: Current learning rate: 0.00806 +2024-11-21 20:09:43.268713: train_loss -0.7682 +2024-11-21 20:09:43.275194: val_loss -0.7743 +2024-11-21 20:09:43.275337: Pseudo dice [0.8638] +2024-11-21 20:09:43.275449: Epoch time: 20.48 s +2024-11-21 20:09:44.542664: +2024-11-21 20:09:44.543095: Epoch 1702 +2024-11-21 20:09:44.543226: Current learning rate: 0.00806 +2024-11-21 20:10:03.093442: train_loss -0.7688 +2024-11-21 20:10:03.101084: val_loss -0.7589 +2024-11-21 20:10:03.101221: Pseudo dice [0.8505] +2024-11-21 20:10:03.101312: Epoch time: 18.55 s +2024-11-21 20:10:04.001331: +2024-11-21 20:10:04.001755: Epoch 1703 +2024-11-21 20:10:04.001899: Current learning rate: 0.00806 +2024-11-21 20:10:23.092472: train_loss -0.7696 +2024-11-21 20:10:23.099987: val_loss -0.7718 +2024-11-21 20:10:23.100134: Pseudo dice [0.8552] +2024-11-21 20:10:23.100245: Epoch time: 19.09 s +2024-11-21 20:10:24.047180: +2024-11-21 20:10:24.047612: Epoch 1704 +2024-11-21 20:10:24.047767: Current learning rate: 0.00806 +2024-11-21 20:10:43.012873: train_loss -0.7729 +2024-11-21 20:10:43.018338: val_loss -0.7733 +2024-11-21 20:10:43.018458: Pseudo dice [0.8415] +2024-11-21 20:10:43.018551: Epoch time: 18.97 s +2024-11-21 20:10:44.013630: +2024-11-21 20:10:44.014053: Epoch 1705 +2024-11-21 20:10:44.014199: Current learning rate: 0.00806 +2024-11-21 20:11:02.283252: train_loss -0.777 +2024-11-21 20:11:02.284940: val_loss -0.7609 +2024-11-21 20:11:02.285037: Pseudo dice [0.8479] +2024-11-21 20:11:02.285154: Epoch time: 18.27 s +2024-11-21 20:11:03.128315: +2024-11-21 20:11:03.128734: Epoch 1706 +2024-11-21 20:11:03.128872: Current learning rate: 0.00806 +2024-11-21 20:11:22.278343: train_loss -0.773 +2024-11-21 20:11:22.280266: val_loss -0.7617 +2024-11-21 20:11:22.280357: Pseudo dice [0.8481] +2024-11-21 20:11:22.280441: Epoch time: 19.15 s +2024-11-21 20:11:23.114895: +2024-11-21 20:11:23.115328: Epoch 1707 +2024-11-21 20:11:23.115474: Current learning rate: 0.00806 +2024-11-21 20:11:41.534268: train_loss -0.7728 +2024-11-21 20:11:41.543069: val_loss -0.7715 +2024-11-21 20:11:41.543225: Pseudo dice [0.8452] +2024-11-21 20:11:41.543318: Epoch time: 18.42 s +2024-11-21 20:11:42.421764: +2024-11-21 20:11:42.422168: Epoch 1708 +2024-11-21 20:11:42.422323: Current learning rate: 0.00806 +2024-11-21 20:12:02.059341: train_loss -0.7555 +2024-11-21 20:12:02.065414: val_loss -0.7571 +2024-11-21 20:12:02.065565: Pseudo dice [0.8384] +2024-11-21 20:12:02.065679: Epoch time: 19.64 s +2024-11-21 20:12:03.068165: +2024-11-21 20:12:03.068601: Epoch 1709 +2024-11-21 20:12:03.068746: Current learning rate: 0.00806 +2024-11-21 20:12:22.603874: train_loss -0.7696 +2024-11-21 20:12:22.608883: val_loss -0.7421 +2024-11-21 20:12:22.609032: Pseudo dice [0.8383] +2024-11-21 20:12:22.609130: Epoch time: 19.54 s +2024-11-21 20:12:23.477475: +2024-11-21 20:12:23.477886: Epoch 1710 +2024-11-21 20:12:23.478032: Current learning rate: 0.00805 +2024-11-21 20:12:43.602915: train_loss -0.7659 +2024-11-21 20:12:43.606501: val_loss -0.7452 +2024-11-21 20:12:43.606652: Pseudo dice [0.8515] +2024-11-21 20:12:43.606734: Epoch time: 20.13 s +2024-11-21 20:12:44.579742: +2024-11-21 20:12:44.580171: Epoch 1711 +2024-11-21 20:12:44.580314: Current learning rate: 0.00805 +2024-11-21 20:13:04.026928: train_loss -0.7726 +2024-11-21 20:13:04.034478: val_loss -0.7776 +2024-11-21 20:13:04.034632: Pseudo dice [0.8466] +2024-11-21 20:13:04.034998: Epoch time: 19.45 s +2024-11-21 20:13:04.876919: +2024-11-21 20:13:04.877356: Epoch 1712 +2024-11-21 20:13:04.877501: Current learning rate: 0.00805 +2024-11-21 20:13:24.401824: train_loss -0.7435 +2024-11-21 20:13:24.414586: val_loss -0.7615 +2024-11-21 20:13:24.414731: Pseudo dice [0.8397] +2024-11-21 20:13:24.414847: Epoch time: 19.53 s +2024-11-21 20:13:25.711275: +2024-11-21 20:13:25.711694: Epoch 1713 +2024-11-21 20:13:25.711836: Current learning rate: 0.00805 +2024-11-21 20:13:44.425230: train_loss -0.7569 +2024-11-21 20:13:44.431092: val_loss -0.757 +2024-11-21 20:13:44.431242: Pseudo dice [0.8514] +2024-11-21 20:13:44.431324: Epoch time: 18.71 s +2024-11-21 20:13:45.405053: +2024-11-21 20:13:45.405476: Epoch 1714 +2024-11-21 20:13:45.405605: Current learning rate: 0.00805 +2024-11-21 20:14:04.853267: train_loss -0.7586 +2024-11-21 20:14:04.866616: val_loss -0.7387 +2024-11-21 20:14:04.866749: Pseudo dice [0.8439] +2024-11-21 20:14:04.866834: Epoch time: 19.45 s +2024-11-21 20:14:05.895663: +2024-11-21 20:14:05.896123: Epoch 1715 +2024-11-21 20:14:05.896275: Current learning rate: 0.00805 +2024-11-21 20:14:24.681185: train_loss -0.7623 +2024-11-21 20:14:24.690198: val_loss -0.7463 +2024-11-21 20:14:24.690335: Pseudo dice [0.85] +2024-11-21 20:14:24.690434: Epoch time: 18.79 s +2024-11-21 20:14:25.558112: +2024-11-21 20:14:25.558515: Epoch 1716 +2024-11-21 20:14:25.558669: Current learning rate: 0.00805 +2024-11-21 20:14:44.245877: train_loss -0.7682 +2024-11-21 20:14:44.255379: val_loss -0.7552 +2024-11-21 20:14:44.255523: Pseudo dice [0.8479] +2024-11-21 20:14:44.255630: Epoch time: 18.69 s +2024-11-21 20:14:45.110767: +2024-11-21 20:14:45.111229: Epoch 1717 +2024-11-21 20:14:45.111386: Current learning rate: 0.00805 +2024-11-21 20:15:02.970791: train_loss -0.7607 +2024-11-21 20:15:02.975941: val_loss -0.7463 +2024-11-21 20:15:02.976087: Pseudo dice [0.8464] +2024-11-21 20:15:02.976174: Epoch time: 17.86 s +2024-11-21 20:15:03.825179: +2024-11-21 20:15:03.825587: Epoch 1718 +2024-11-21 20:15:03.825734: Current learning rate: 0.00804 +2024-11-21 20:15:23.719510: train_loss -0.7602 +2024-11-21 20:15:23.721714: val_loss -0.7723 +2024-11-21 20:15:23.721846: Pseudo dice [0.8576] +2024-11-21 20:15:23.721949: Epoch time: 19.9 s +2024-11-21 20:15:24.559905: +2024-11-21 20:15:24.560336: Epoch 1719 +2024-11-21 20:15:24.560483: Current learning rate: 0.00804 +2024-11-21 20:15:44.353308: train_loss -0.7703 +2024-11-21 20:15:44.360520: val_loss -0.7366 +2024-11-21 20:15:44.360669: Pseudo dice [0.8411] +2024-11-21 20:15:44.360781: Epoch time: 19.79 s +2024-11-21 20:15:45.432431: +2024-11-21 20:15:45.432872: Epoch 1720 +2024-11-21 20:15:45.433015: Current learning rate: 0.00804 +2024-11-21 20:16:05.402546: train_loss -0.7778 +2024-11-21 20:16:05.412293: val_loss -0.77 +2024-11-21 20:16:05.412432: Pseudo dice [0.8531] +2024-11-21 20:16:05.412534: Epoch time: 19.97 s +2024-11-21 20:16:06.507161: +2024-11-21 20:16:06.507576: Epoch 1721 +2024-11-21 20:16:06.507736: Current learning rate: 0.00804 +2024-11-21 20:16:26.760630: train_loss -0.7545 +2024-11-21 20:16:26.766668: val_loss -0.7521 +2024-11-21 20:16:26.766794: Pseudo dice [0.8439] +2024-11-21 20:16:26.766882: Epoch time: 20.25 s +2024-11-21 20:16:27.746398: +2024-11-21 20:16:27.746851: Epoch 1722 +2024-11-21 20:16:27.746998: Current learning rate: 0.00804 +2024-11-21 20:16:46.779356: train_loss -0.763 +2024-11-21 20:16:46.781250: val_loss -0.7779 +2024-11-21 20:16:46.781384: Pseudo dice [0.8491] +2024-11-21 20:16:46.781476: Epoch time: 19.03 s +2024-11-21 20:16:47.723299: +2024-11-21 20:16:47.723691: Epoch 1723 +2024-11-21 20:16:47.723835: Current learning rate: 0.00804 +2024-11-21 20:17:06.730218: train_loss -0.7613 +2024-11-21 20:17:06.741930: val_loss -0.7678 +2024-11-21 20:17:06.742057: Pseudo dice [0.862] +2024-11-21 20:17:06.742164: Epoch time: 19.01 s +2024-11-21 20:17:07.978832: +2024-11-21 20:17:07.979298: Epoch 1724 +2024-11-21 20:17:07.979438: Current learning rate: 0.00804 +2024-11-21 20:17:26.381740: train_loss -0.7742 +2024-11-21 20:17:26.387902: val_loss -0.7755 +2024-11-21 20:17:26.388043: Pseudo dice [0.8552] +2024-11-21 20:17:26.388143: Epoch time: 18.4 s +2024-11-21 20:17:27.264576: +2024-11-21 20:17:27.265100: Epoch 1725 +2024-11-21 20:17:27.265245: Current learning rate: 0.00804 +2024-11-21 20:17:45.489706: train_loss -0.7753 +2024-11-21 20:17:45.500210: val_loss -0.7799 +2024-11-21 20:17:45.500352: Pseudo dice [0.8565] +2024-11-21 20:17:45.500439: Epoch time: 18.23 s +2024-11-21 20:17:46.401488: +2024-11-21 20:17:46.401914: Epoch 1726 +2024-11-21 20:17:46.402067: Current learning rate: 0.00804 +2024-11-21 20:18:05.032817: train_loss -0.7644 +2024-11-21 20:18:05.040881: val_loss -0.7591 +2024-11-21 20:18:05.041028: Pseudo dice [0.8365] +2024-11-21 20:18:05.041135: Epoch time: 18.63 s +2024-11-21 20:18:05.972228: +2024-11-21 20:18:05.972688: Epoch 1727 +2024-11-21 20:18:05.972847: Current learning rate: 0.00803 +2024-11-21 20:18:24.933547: train_loss -0.7678 +2024-11-21 20:18:24.947390: val_loss -0.7535 +2024-11-21 20:18:24.947547: Pseudo dice [0.8457] +2024-11-21 20:18:24.947641: Epoch time: 18.96 s +2024-11-21 20:18:26.103238: +2024-11-21 20:18:26.103703: Epoch 1728 +2024-11-21 20:18:26.103838: Current learning rate: 0.00803 +2024-11-21 20:18:46.206521: train_loss -0.7582 +2024-11-21 20:18:46.209743: val_loss -0.7314 +2024-11-21 20:18:46.209875: Pseudo dice [0.8418] +2024-11-21 20:18:46.209977: Epoch time: 20.1 s +2024-11-21 20:18:47.131188: +2024-11-21 20:18:47.131603: Epoch 1729 +2024-11-21 20:18:47.131747: Current learning rate: 0.00803 +2024-11-21 20:19:05.760312: train_loss -0.7732 +2024-11-21 20:19:05.762310: val_loss -0.8006 +2024-11-21 20:19:05.762415: Pseudo dice [0.858] +2024-11-21 20:19:05.762496: Epoch time: 18.63 s +2024-11-21 20:19:06.599739: +2024-11-21 20:19:06.600173: Epoch 1730 +2024-11-21 20:19:06.600311: Current learning rate: 0.00803 +2024-11-21 20:19:24.031952: train_loss -0.7729 +2024-11-21 20:19:24.039624: val_loss -0.7671 +2024-11-21 20:19:24.039788: Pseudo dice [0.8525] +2024-11-21 20:19:24.039892: Epoch time: 17.43 s +2024-11-21 20:19:25.076170: +2024-11-21 20:19:25.076560: Epoch 1731 +2024-11-21 20:19:25.076705: Current learning rate: 0.00803 +2024-11-21 20:19:42.611118: train_loss -0.7539 +2024-11-21 20:19:42.618245: val_loss -0.7688 +2024-11-21 20:19:42.618404: Pseudo dice [0.8517] +2024-11-21 20:19:42.618515: Epoch time: 17.54 s +2024-11-21 20:19:43.491992: +2024-11-21 20:19:43.492430: Epoch 1732 +2024-11-21 20:19:43.492594: Current learning rate: 0.00803 +2024-11-21 20:20:00.591216: train_loss -0.7664 +2024-11-21 20:20:00.600640: val_loss -0.7547 +2024-11-21 20:20:00.600894: Pseudo dice [0.8471] +2024-11-21 20:20:00.601082: Epoch time: 17.1 s +2024-11-21 20:20:01.469416: +2024-11-21 20:20:01.469827: Epoch 1733 +2024-11-21 20:20:01.469965: Current learning rate: 0.00803 +2024-11-21 20:20:21.017156: train_loss -0.7854 +2024-11-21 20:20:21.019872: val_loss -0.7677 +2024-11-21 20:20:21.019972: Pseudo dice [0.8362] +2024-11-21 20:20:21.020071: Epoch time: 19.55 s +2024-11-21 20:20:21.850591: +2024-11-21 20:20:21.851027: Epoch 1734 +2024-11-21 20:20:21.851176: Current learning rate: 0.00803 +2024-11-21 20:20:39.855190: train_loss -0.7758 +2024-11-21 20:20:39.868626: val_loss -0.732 +2024-11-21 20:20:39.868775: Pseudo dice [0.8287] +2024-11-21 20:20:39.868888: Epoch time: 18.01 s +2024-11-21 20:20:41.212071: +2024-11-21 20:20:41.212513: Epoch 1735 +2024-11-21 20:20:41.212669: Current learning rate: 0.00803 +2024-11-21 20:20:59.951575: train_loss -0.7745 +2024-11-21 20:20:59.958158: val_loss -0.7399 +2024-11-21 20:20:59.958303: Pseudo dice [0.847] +2024-11-21 20:20:59.958395: Epoch time: 18.74 s +2024-11-21 20:21:01.006683: +2024-11-21 20:21:01.006923: Epoch 1736 +2024-11-21 20:21:01.007055: Current learning rate: 0.00802 +2024-11-21 20:21:20.268939: train_loss -0.7725 +2024-11-21 20:21:20.276363: val_loss -0.7378 +2024-11-21 20:21:20.276525: Pseudo dice [0.8421] +2024-11-21 20:21:20.276680: Epoch time: 19.26 s +2024-11-21 20:21:21.400607: +2024-11-21 20:21:21.400832: Epoch 1737 +2024-11-21 20:21:21.400960: Current learning rate: 0.00802 +2024-11-21 20:21:39.534740: train_loss -0.7754 +2024-11-21 20:21:39.537212: val_loss -0.7533 +2024-11-21 20:21:39.537315: Pseudo dice [0.8577] +2024-11-21 20:21:39.537415: Epoch time: 18.13 s +2024-11-21 20:21:40.373004: +2024-11-21 20:21:40.373212: Epoch 1738 +2024-11-21 20:21:40.373339: Current learning rate: 0.00802 +2024-11-21 20:21:59.722978: train_loss -0.7684 +2024-11-21 20:21:59.728653: val_loss -0.775 +2024-11-21 20:21:59.728802: Pseudo dice [0.8544] +2024-11-21 20:21:59.728920: Epoch time: 19.35 s +2024-11-21 20:22:00.631651: +2024-11-21 20:22:00.631878: Epoch 1739 +2024-11-21 20:22:00.632010: Current learning rate: 0.00802 +2024-11-21 20:22:19.614926: train_loss -0.7679 +2024-11-21 20:22:19.622756: val_loss -0.7551 +2024-11-21 20:22:19.622890: Pseudo dice [0.8415] +2024-11-21 20:22:19.622980: Epoch time: 18.98 s +2024-11-21 20:22:20.509929: +2024-11-21 20:22:20.510132: Epoch 1740 +2024-11-21 20:22:20.510250: Current learning rate: 0.00802 +2024-11-21 20:22:39.566370: train_loss -0.7791 +2024-11-21 20:22:39.573413: val_loss -0.7159 +2024-11-21 20:22:39.573538: Pseudo dice [0.8416] +2024-11-21 20:22:39.573623: Epoch time: 19.06 s +2024-11-21 20:22:40.436802: +2024-11-21 20:22:40.437010: Epoch 1741 +2024-11-21 20:22:40.437151: Current learning rate: 0.00802 +2024-11-21 20:22:59.692328: train_loss -0.7541 +2024-11-21 20:22:59.694967: val_loss -0.7649 +2024-11-21 20:22:59.695098: Pseudo dice [0.8523] +2024-11-21 20:22:59.695192: Epoch time: 19.26 s +2024-11-21 20:23:00.536078: +2024-11-21 20:23:00.536309: Epoch 1742 +2024-11-21 20:23:00.536452: Current learning rate: 0.00802 +2024-11-21 20:23:19.174578: train_loss -0.7684 +2024-11-21 20:23:19.178134: val_loss -0.7649 +2024-11-21 20:23:19.178281: Pseudo dice [0.8529] +2024-11-21 20:23:19.178384: Epoch time: 18.64 s +2024-11-21 20:23:20.299424: +2024-11-21 20:23:20.299634: Epoch 1743 +2024-11-21 20:23:20.299753: Current learning rate: 0.00802 +2024-11-21 20:23:39.576035: train_loss -0.7618 +2024-11-21 20:23:39.583519: val_loss -0.7477 +2024-11-21 20:23:39.583661: Pseudo dice [0.8537] +2024-11-21 20:23:39.583772: Epoch time: 19.28 s +2024-11-21 20:23:40.608677: +2024-11-21 20:23:40.608899: Epoch 1744 +2024-11-21 20:23:40.609021: Current learning rate: 0.00801 +2024-11-21 20:23:58.678741: train_loss -0.7575 +2024-11-21 20:23:58.685632: val_loss -0.7907 +2024-11-21 20:23:58.685768: Pseudo dice [0.8574] +2024-11-21 20:23:58.685867: Epoch time: 18.07 s +2024-11-21 20:23:59.527869: +2024-11-21 20:23:59.528085: Epoch 1745 +2024-11-21 20:23:59.528211: Current learning rate: 0.00801 +2024-11-21 20:24:18.130763: train_loss -0.7677 +2024-11-21 20:24:18.133281: val_loss -0.7551 +2024-11-21 20:24:18.133393: Pseudo dice [0.8528] +2024-11-21 20:24:18.133472: Epoch time: 18.6 s +2024-11-21 20:24:18.965390: +2024-11-21 20:24:18.965620: Epoch 1746 +2024-11-21 20:24:18.965748: Current learning rate: 0.00801 +2024-11-21 20:24:37.872944: train_loss -0.7772 +2024-11-21 20:24:37.879355: val_loss -0.7877 +2024-11-21 20:24:37.879561: Pseudo dice [0.8548] +2024-11-21 20:24:37.879651: Epoch time: 18.91 s +2024-11-21 20:24:38.851435: +2024-11-21 20:24:38.851659: Epoch 1747 +2024-11-21 20:24:38.851809: Current learning rate: 0.00801 +2024-11-21 20:24:58.507589: train_loss -0.7662 +2024-11-21 20:24:58.511176: val_loss -0.7287 +2024-11-21 20:24:58.511276: Pseudo dice [0.8469] +2024-11-21 20:24:58.511365: Epoch time: 19.66 s +2024-11-21 20:24:59.339493: +2024-11-21 20:24:59.339721: Epoch 1748 +2024-11-21 20:24:59.339846: Current learning rate: 0.00801 +2024-11-21 20:25:16.871039: train_loss -0.7715 +2024-11-21 20:25:16.878867: val_loss -0.7563 +2024-11-21 20:25:16.878988: Pseudo dice [0.8529] +2024-11-21 20:25:16.879105: Epoch time: 17.53 s +2024-11-21 20:25:17.795676: +2024-11-21 20:25:17.795893: Epoch 1749 +2024-11-21 20:25:17.796018: Current learning rate: 0.00801 +2024-11-21 20:25:37.742725: train_loss -0.7726 +2024-11-21 20:25:37.748947: val_loss -0.7751 +2024-11-21 20:25:37.749074: Pseudo dice [0.8558] +2024-11-21 20:25:37.749166: Epoch time: 19.95 s +2024-11-21 20:25:39.113291: +2024-11-21 20:25:39.113495: Epoch 1750 +2024-11-21 20:25:39.113605: Current learning rate: 0.00801 +2024-11-21 20:25:58.075919: train_loss -0.7773 +2024-11-21 20:25:58.082411: val_loss -0.7388 +2024-11-21 20:25:58.082570: Pseudo dice [0.8388] +2024-11-21 20:25:58.082669: Epoch time: 18.96 s +2024-11-21 20:25:59.054101: +2024-11-21 20:25:59.054332: Epoch 1751 +2024-11-21 20:25:59.054446: Current learning rate: 0.00801 +2024-11-21 20:26:17.131243: train_loss -0.7642 +2024-11-21 20:26:17.138110: val_loss -0.7474 +2024-11-21 20:26:17.138245: Pseudo dice [0.862] +2024-11-21 20:26:17.138335: Epoch time: 18.08 s +2024-11-21 20:26:18.162632: +2024-11-21 20:26:18.162824: Epoch 1752 +2024-11-21 20:26:18.162937: Current learning rate: 0.00801 +2024-11-21 20:26:36.498369: train_loss -0.7803 +2024-11-21 20:26:36.501100: val_loss -0.7445 +2024-11-21 20:26:36.501230: Pseudo dice [0.8518] +2024-11-21 20:26:36.501323: Epoch time: 18.34 s +2024-11-21 20:26:37.454051: +2024-11-21 20:26:37.454281: Epoch 1753 +2024-11-21 20:26:37.454407: Current learning rate: 0.008 +2024-11-21 20:26:57.101064: train_loss -0.7699 +2024-11-21 20:26:57.106968: val_loss -0.7621 +2024-11-21 20:26:57.107104: Pseudo dice [0.8543] +2024-11-21 20:26:57.107189: Epoch time: 19.65 s +2024-11-21 20:26:57.107280: Yayy! New best EMA pseudo Dice: 0.8512 +2024-11-21 20:26:58.143542: +2024-11-21 20:26:58.143754: Epoch 1754 +2024-11-21 20:26:58.143882: Current learning rate: 0.008 +2024-11-21 20:27:17.342646: train_loss -0.7669 +2024-11-21 20:27:17.349853: val_loss -0.7497 +2024-11-21 20:27:17.350048: Pseudo dice [0.8501] +2024-11-21 20:27:17.350153: Epoch time: 19.2 s +2024-11-21 20:27:18.196893: +2024-11-21 20:27:18.197142: Epoch 1755 +2024-11-21 20:27:18.197268: Current learning rate: 0.008 +2024-11-21 20:27:36.774282: train_loss -0.7734 +2024-11-21 20:27:36.782261: val_loss -0.778 +2024-11-21 20:27:36.782392: Pseudo dice [0.8666] +2024-11-21 20:27:36.782496: Epoch time: 18.58 s +2024-11-21 20:27:36.782583: Yayy! New best EMA pseudo Dice: 0.8526 +2024-11-21 20:27:38.329921: +2024-11-21 20:27:38.330167: Epoch 1756 +2024-11-21 20:27:38.330291: Current learning rate: 0.008 +2024-11-21 20:27:57.350631: train_loss -0.7704 +2024-11-21 20:27:57.356613: val_loss -0.7771 +2024-11-21 20:27:57.356770: Pseudo dice [0.8437] +2024-11-21 20:27:57.356879: Epoch time: 19.02 s +2024-11-21 20:27:58.200473: +2024-11-21 20:27:58.200701: Epoch 1757 +2024-11-21 20:27:58.200826: Current learning rate: 0.008 +2024-11-21 20:28:18.580759: train_loss -0.765 +2024-11-21 20:28:18.586838: val_loss -0.7569 +2024-11-21 20:28:18.586969: Pseudo dice [0.8501] +2024-11-21 20:28:18.587077: Epoch time: 20.38 s +2024-11-21 20:28:19.426505: +2024-11-21 20:28:19.426713: Epoch 1758 +2024-11-21 20:28:19.426827: Current learning rate: 0.008 +2024-11-21 20:28:38.796574: train_loss -0.7666 +2024-11-21 20:28:38.807822: val_loss -0.7629 +2024-11-21 20:28:38.807966: Pseudo dice [0.8453] +2024-11-21 20:28:38.808049: Epoch time: 19.37 s +2024-11-21 20:28:39.816969: +2024-11-21 20:28:39.817218: Epoch 1759 +2024-11-21 20:28:39.817346: Current learning rate: 0.008 +2024-11-21 20:28:57.556524: train_loss -0.7691 +2024-11-21 20:28:57.560606: val_loss -0.7445 +2024-11-21 20:28:57.560719: Pseudo dice [0.8373] +2024-11-21 20:28:57.560815: Epoch time: 17.74 s +2024-11-21 20:28:58.399982: +2024-11-21 20:28:58.400199: Epoch 1760 +2024-11-21 20:28:58.400331: Current learning rate: 0.008 +2024-11-21 20:29:16.817413: train_loss -0.769 +2024-11-21 20:29:16.823386: val_loss -0.7592 +2024-11-21 20:29:16.823525: Pseudo dice [0.8389] +2024-11-21 20:29:16.823643: Epoch time: 18.42 s +2024-11-21 20:29:17.817532: +2024-11-21 20:29:17.817768: Epoch 1761 +2024-11-21 20:29:17.817887: Current learning rate: 0.008 +2024-11-21 20:29:37.172603: train_loss -0.7662 +2024-11-21 20:29:37.200124: val_loss -0.7591 +2024-11-21 20:29:37.200262: Pseudo dice [0.8334] +2024-11-21 20:29:37.200348: Epoch time: 19.36 s +2024-11-21 20:29:38.210817: +2024-11-21 20:29:38.211034: Epoch 1762 +2024-11-21 20:29:38.211161: Current learning rate: 0.00799 +2024-11-21 20:29:57.645571: train_loss -0.7557 +2024-11-21 20:29:57.651709: val_loss -0.7605 +2024-11-21 20:29:57.651847: Pseudo dice [0.8523] +2024-11-21 20:29:57.651940: Epoch time: 19.44 s +2024-11-21 20:29:58.509447: +2024-11-21 20:29:58.509684: Epoch 1763 +2024-11-21 20:29:58.509802: Current learning rate: 0.00799 +2024-11-21 20:30:17.011832: train_loss -0.7716 +2024-11-21 20:30:17.016023: val_loss -0.7608 +2024-11-21 20:30:17.016155: Pseudo dice [0.8516] +2024-11-21 20:30:17.016321: Epoch time: 18.5 s +2024-11-21 20:30:17.918445: +2024-11-21 20:30:17.918651: Epoch 1764 +2024-11-21 20:30:17.918766: Current learning rate: 0.00799 +2024-11-21 20:30:37.392103: train_loss -0.7708 +2024-11-21 20:30:37.405216: val_loss -0.7462 +2024-11-21 20:30:37.405386: Pseudo dice [0.8469] +2024-11-21 20:30:37.405483: Epoch time: 19.47 s +2024-11-21 20:30:38.352034: +2024-11-21 20:30:38.352250: Epoch 1765 +2024-11-21 20:30:38.352372: Current learning rate: 0.00799 +2024-11-21 20:30:57.002193: train_loss -0.7671 +2024-11-21 20:30:57.015272: val_loss -0.7482 +2024-11-21 20:30:57.015404: Pseudo dice [0.8472] +2024-11-21 20:30:57.015502: Epoch time: 18.65 s +2024-11-21 20:30:58.361140: +2024-11-21 20:30:58.361338: Epoch 1766 +2024-11-21 20:30:58.361475: Current learning rate: 0.00799 +2024-11-21 20:31:17.485323: train_loss -0.7696 +2024-11-21 20:31:17.492103: val_loss -0.7603 +2024-11-21 20:31:17.492339: Pseudo dice [0.8383] +2024-11-21 20:31:17.492443: Epoch time: 19.12 s +2024-11-21 20:31:18.528163: +2024-11-21 20:31:18.528379: Epoch 1767 +2024-11-21 20:31:18.528494: Current learning rate: 0.00799 +2024-11-21 20:31:37.333244: train_loss -0.776 +2024-11-21 20:31:37.340214: val_loss -0.7625 +2024-11-21 20:31:37.340343: Pseudo dice [0.8379] +2024-11-21 20:31:37.340449: Epoch time: 18.81 s +2024-11-21 20:31:38.197592: +2024-11-21 20:31:38.197865: Epoch 1768 +2024-11-21 20:31:38.197982: Current learning rate: 0.00799 +2024-11-21 20:31:58.014243: train_loss -0.7647 +2024-11-21 20:31:58.018709: val_loss -0.7844 +2024-11-21 20:31:58.018861: Pseudo dice [0.8487] +2024-11-21 20:31:58.018951: Epoch time: 19.82 s +2024-11-21 20:31:58.961494: +2024-11-21 20:31:58.961708: Epoch 1769 +2024-11-21 20:31:58.961828: Current learning rate: 0.00799 +2024-11-21 20:32:16.488398: train_loss -0.7634 +2024-11-21 20:32:16.496395: val_loss -0.7463 +2024-11-21 20:32:16.496531: Pseudo dice [0.8495] +2024-11-21 20:32:16.496629: Epoch time: 17.53 s +2024-11-21 20:32:17.753543: +2024-11-21 20:32:17.753837: Epoch 1770 +2024-11-21 20:32:17.753999: Current learning rate: 0.00798 +2024-11-21 20:32:36.142343: train_loss -0.772 +2024-11-21 20:32:36.147924: val_loss -0.7578 +2024-11-21 20:32:36.148149: Pseudo dice [0.8344] +2024-11-21 20:32:36.148257: Epoch time: 18.39 s +2024-11-21 20:32:37.118796: +2024-11-21 20:32:37.119009: Epoch 1771 +2024-11-21 20:32:37.119130: Current learning rate: 0.00798 +2024-11-21 20:32:55.476167: train_loss -0.7691 +2024-11-21 20:32:55.490099: val_loss -0.7444 +2024-11-21 20:32:55.490238: Pseudo dice [0.8428] +2024-11-21 20:32:55.490336: Epoch time: 18.36 s +2024-11-21 20:32:56.492638: +2024-11-21 20:32:56.492862: Epoch 1772 +2024-11-21 20:32:56.492990: Current learning rate: 0.00798 +2024-11-21 20:33:16.628775: train_loss -0.7712 +2024-11-21 20:33:16.638908: val_loss -0.755 +2024-11-21 20:33:16.639067: Pseudo dice [0.8492] +2024-11-21 20:33:16.639171: Epoch time: 20.14 s +2024-11-21 20:33:17.512965: +2024-11-21 20:33:17.513178: Epoch 1773 +2024-11-21 20:33:17.513290: Current learning rate: 0.00798 +2024-11-21 20:33:36.024049: train_loss -0.7747 +2024-11-21 20:33:36.045792: val_loss -0.7829 +2024-11-21 20:33:36.045935: Pseudo dice [0.8517] +2024-11-21 20:33:36.046029: Epoch time: 18.51 s +2024-11-21 20:33:37.006081: +2024-11-21 20:33:37.006306: Epoch 1774 +2024-11-21 20:33:37.006444: Current learning rate: 0.00798 +2024-11-21 20:33:56.791977: train_loss -0.7665 +2024-11-21 20:33:56.798271: val_loss -0.7561 +2024-11-21 20:33:56.798412: Pseudo dice [0.854] +2024-11-21 20:33:56.798502: Epoch time: 19.79 s +2024-11-21 20:33:57.676585: +2024-11-21 20:33:57.676836: Epoch 1775 +2024-11-21 20:33:57.676950: Current learning rate: 0.00798 +2024-11-21 20:34:17.043809: train_loss -0.7681 +2024-11-21 20:34:17.056836: val_loss -0.7603 +2024-11-21 20:34:17.056972: Pseudo dice [0.8489] +2024-11-21 20:34:17.057080: Epoch time: 19.37 s +2024-11-21 20:34:18.055753: +2024-11-21 20:34:18.056035: Epoch 1776 +2024-11-21 20:34:18.056161: Current learning rate: 0.00798 +2024-11-21 20:34:36.653809: train_loss -0.7817 +2024-11-21 20:34:36.661822: val_loss -0.7533 +2024-11-21 20:34:36.661964: Pseudo dice [0.8513] +2024-11-21 20:34:36.662048: Epoch time: 18.6 s +2024-11-21 20:34:37.977584: +2024-11-21 20:34:37.977786: Epoch 1777 +2024-11-21 20:34:37.977919: Current learning rate: 0.00798 +2024-11-21 20:34:57.760658: train_loss -0.765 +2024-11-21 20:34:57.765600: val_loss -0.7643 +2024-11-21 20:34:57.765723: Pseudo dice [0.8505] +2024-11-21 20:34:57.765843: Epoch time: 19.78 s +2024-11-21 20:34:58.870305: +2024-11-21 20:34:58.870551: Epoch 1778 +2024-11-21 20:34:58.870669: Current learning rate: 0.00798 +2024-11-21 20:35:18.608612: train_loss -0.7753 +2024-11-21 20:35:18.615327: val_loss -0.749 +2024-11-21 20:35:18.615487: Pseudo dice [0.847] +2024-11-21 20:35:18.615576: Epoch time: 19.74 s +2024-11-21 20:35:19.599339: +2024-11-21 20:35:19.599569: Epoch 1779 +2024-11-21 20:35:19.599683: Current learning rate: 0.00797 +2024-11-21 20:35:39.592147: train_loss -0.7668 +2024-11-21 20:35:39.595443: val_loss -0.7816 +2024-11-21 20:35:39.595582: Pseudo dice [0.8524] +2024-11-21 20:35:39.595672: Epoch time: 19.99 s +2024-11-21 20:35:40.454456: +2024-11-21 20:35:40.454659: Epoch 1780 +2024-11-21 20:35:40.454781: Current learning rate: 0.00797 +2024-11-21 20:36:00.857898: train_loss -0.77 +2024-11-21 20:36:00.868161: val_loss -0.7527 +2024-11-21 20:36:00.868295: Pseudo dice [0.8352] +2024-11-21 20:36:00.868381: Epoch time: 20.4 s +2024-11-21 20:36:01.772392: +2024-11-21 20:36:01.772595: Epoch 1781 +2024-11-21 20:36:01.772724: Current learning rate: 0.00797 +2024-11-21 20:36:21.164848: train_loss -0.7557 +2024-11-21 20:36:21.173017: val_loss -0.7669 +2024-11-21 20:36:21.173154: Pseudo dice [0.8401] +2024-11-21 20:36:21.173264: Epoch time: 19.39 s +2024-11-21 20:36:22.146479: +2024-11-21 20:36:22.146721: Epoch 1782 +2024-11-21 20:36:22.146836: Current learning rate: 0.00797 +2024-11-21 20:36:41.341321: train_loss -0.7673 +2024-11-21 20:36:41.348041: val_loss -0.7615 +2024-11-21 20:36:41.348157: Pseudo dice [0.8515] +2024-11-21 20:36:41.348242: Epoch time: 19.2 s +2024-11-21 20:36:42.304424: +2024-11-21 20:36:42.304620: Epoch 1783 +2024-11-21 20:36:42.304739: Current learning rate: 0.00797 +2024-11-21 20:37:01.119313: train_loss -0.7752 +2024-11-21 20:37:01.122200: val_loss -0.7541 +2024-11-21 20:37:01.122313: Pseudo dice [0.8486] +2024-11-21 20:37:01.122438: Epoch time: 18.82 s +2024-11-21 20:37:01.955547: +2024-11-21 20:37:01.955747: Epoch 1784 +2024-11-21 20:37:01.955860: Current learning rate: 0.00797 +2024-11-21 20:37:20.593346: train_loss -0.7753 +2024-11-21 20:37:20.608770: val_loss -0.7705 +2024-11-21 20:37:20.608910: Pseudo dice [0.8511] +2024-11-21 20:37:20.609014: Epoch time: 18.64 s +2024-11-21 20:37:21.581596: +2024-11-21 20:37:21.581804: Epoch 1785 +2024-11-21 20:37:21.581934: Current learning rate: 0.00797 +2024-11-21 20:37:40.719491: train_loss -0.7743 +2024-11-21 20:37:40.725263: val_loss -0.776 +2024-11-21 20:37:40.725394: Pseudo dice [0.841] +2024-11-21 20:37:40.725486: Epoch time: 19.14 s +2024-11-21 20:37:41.674657: +2024-11-21 20:37:41.674869: Epoch 1786 +2024-11-21 20:37:41.674986: Current learning rate: 0.00797 +2024-11-21 20:38:01.801647: train_loss -0.7755 +2024-11-21 20:38:01.808695: val_loss -0.7638 +2024-11-21 20:38:01.808855: Pseudo dice [0.8593] +2024-11-21 20:38:01.808943: Epoch time: 20.13 s +2024-11-21 20:38:02.674354: +2024-11-21 20:38:02.674555: Epoch 1787 +2024-11-21 20:38:02.674677: Current learning rate: 0.00797 +2024-11-21 20:38:21.482407: train_loss -0.7749 +2024-11-21 20:38:21.494933: val_loss -0.7688 +2024-11-21 20:38:21.495473: Pseudo dice [0.8544] +2024-11-21 20:38:21.495604: Epoch time: 18.81 s +2024-11-21 20:38:22.811801: +2024-11-21 20:38:22.812037: Epoch 1788 +2024-11-21 20:38:22.812204: Current learning rate: 0.00796 +2024-11-21 20:38:41.714472: train_loss -0.7672 +2024-11-21 20:38:41.721658: val_loss -0.7755 +2024-11-21 20:38:41.721793: Pseudo dice [0.8506] +2024-11-21 20:38:41.721890: Epoch time: 18.9 s +2024-11-21 20:38:42.579680: +2024-11-21 20:38:42.579928: Epoch 1789 +2024-11-21 20:38:42.580052: Current learning rate: 0.00796 +2024-11-21 20:38:59.938403: train_loss -0.7781 +2024-11-21 20:38:59.951435: val_loss -0.7336 +2024-11-21 20:38:59.951614: Pseudo dice [0.8512] +2024-11-21 20:38:59.951711: Epoch time: 17.36 s +2024-11-21 20:39:00.824265: +2024-11-21 20:39:00.824513: Epoch 1790 +2024-11-21 20:39:00.824649: Current learning rate: 0.00796 +2024-11-21 20:39:19.223169: train_loss -0.7698 +2024-11-21 20:39:19.237676: val_loss -0.77 +2024-11-21 20:39:19.237830: Pseudo dice [0.8387] +2024-11-21 20:39:19.237932: Epoch time: 18.4 s +2024-11-21 20:39:20.076096: +2024-11-21 20:39:20.076373: Epoch 1791 +2024-11-21 20:39:20.076504: Current learning rate: 0.00796 +2024-11-21 20:39:39.685548: train_loss -0.7648 +2024-11-21 20:39:39.699028: val_loss -0.7835 +2024-11-21 20:39:39.699182: Pseudo dice [0.8549] +2024-11-21 20:39:39.699281: Epoch time: 19.61 s +2024-11-21 20:39:40.722795: +2024-11-21 20:39:40.723027: Epoch 1792 +2024-11-21 20:39:40.723162: Current learning rate: 0.00796 +2024-11-21 20:39:59.093635: train_loss -0.7675 +2024-11-21 20:39:59.095110: val_loss -0.7716 +2024-11-21 20:39:59.095238: Pseudo dice [0.8555] +2024-11-21 20:39:59.095335: Epoch time: 18.37 s +2024-11-21 20:39:59.942025: +2024-11-21 20:39:59.942256: Epoch 1793 +2024-11-21 20:39:59.942371: Current learning rate: 0.00796 +2024-11-21 20:40:19.811612: train_loss -0.7631 +2024-11-21 20:40:19.814819: val_loss -0.7714 +2024-11-21 20:40:19.814952: Pseudo dice [0.8616] +2024-11-21 20:40:19.815034: Epoch time: 19.87 s +2024-11-21 20:40:20.664527: +2024-11-21 20:40:20.664728: Epoch 1794 +2024-11-21 20:40:20.664841: Current learning rate: 0.00796 +2024-11-21 20:40:38.986938: train_loss -0.7713 +2024-11-21 20:40:38.991466: val_loss -0.7534 +2024-11-21 20:40:38.991676: Pseudo dice [0.8388] +2024-11-21 20:40:38.991779: Epoch time: 18.32 s +2024-11-21 20:40:39.904765: +2024-11-21 20:40:39.904979: Epoch 1795 +2024-11-21 20:40:39.905099: Current learning rate: 0.00796 +2024-11-21 20:40:58.840985: train_loss -0.7678 +2024-11-21 20:40:58.853392: val_loss -0.7597 +2024-11-21 20:40:58.853551: Pseudo dice [0.86] +2024-11-21 20:40:58.853662: Epoch time: 18.94 s +2024-11-21 20:40:59.723225: +2024-11-21 20:40:59.723787: Epoch 1796 +2024-11-21 20:40:59.723923: Current learning rate: 0.00795 +2024-11-21 20:41:19.075341: train_loss -0.7811 +2024-11-21 20:41:19.078491: val_loss -0.7782 +2024-11-21 20:41:19.078594: Pseudo dice [0.8453] +2024-11-21 20:41:19.078689: Epoch time: 19.35 s +2024-11-21 20:41:19.910295: +2024-11-21 20:41:19.910521: Epoch 1797 +2024-11-21 20:41:19.910641: Current learning rate: 0.00795 +2024-11-21 20:41:38.479854: train_loss -0.7714 +2024-11-21 20:41:38.484687: val_loss -0.7719 +2024-11-21 20:41:38.484820: Pseudo dice [0.8497] +2024-11-21 20:41:38.484915: Epoch time: 18.57 s +2024-11-21 20:41:39.488569: +2024-11-21 20:41:39.488797: Epoch 1798 +2024-11-21 20:41:39.488931: Current learning rate: 0.00795 +2024-11-21 20:41:58.917158: train_loss -0.7644 +2024-11-21 20:41:58.926311: val_loss -0.7785 +2024-11-21 20:41:58.926450: Pseudo dice [0.8345] +2024-11-21 20:41:58.926542: Epoch time: 19.43 s +2024-11-21 20:42:00.241952: +2024-11-21 20:42:00.242232: Epoch 1799 +2024-11-21 20:42:00.242354: Current learning rate: 0.00795 +2024-11-21 20:42:18.942599: train_loss -0.7793 +2024-11-21 20:42:18.950502: val_loss -0.7774 +2024-11-21 20:42:18.950663: Pseudo dice [0.8569] +2024-11-21 20:42:18.950779: Epoch time: 18.7 s +2024-11-21 20:42:20.187350: +2024-11-21 20:42:20.187566: Epoch 1800 +2024-11-21 20:42:20.187686: Current learning rate: 0.00795 +2024-11-21 20:42:39.673358: train_loss -0.769 +2024-11-21 20:42:39.680831: val_loss -0.7519 +2024-11-21 20:42:39.680953: Pseudo dice [0.8514] +2024-11-21 20:42:39.681049: Epoch time: 19.49 s +2024-11-21 20:42:40.570306: +2024-11-21 20:42:40.570535: Epoch 1801 +2024-11-21 20:42:40.570660: Current learning rate: 0.00795 +2024-11-21 20:42:59.035554: train_loss -0.7714 +2024-11-21 20:42:59.040813: val_loss -0.7704 +2024-11-21 20:42:59.040938: Pseudo dice [0.8405] +2024-11-21 20:42:59.041036: Epoch time: 18.47 s +2024-11-21 20:42:59.872128: +2024-11-21 20:42:59.872354: Epoch 1802 +2024-11-21 20:42:59.872475: Current learning rate: 0.00795 +2024-11-21 20:43:19.251171: train_loss -0.7674 +2024-11-21 20:43:19.256798: val_loss -0.7472 +2024-11-21 20:43:19.256919: Pseudo dice [0.8513] +2024-11-21 20:43:19.257021: Epoch time: 19.38 s +2024-11-21 20:43:20.195898: +2024-11-21 20:43:20.196133: Epoch 1803 +2024-11-21 20:43:20.196259: Current learning rate: 0.00795 +2024-11-21 20:43:37.793886: train_loss -0.7809 +2024-11-21 20:43:37.799770: val_loss -0.7783 +2024-11-21 20:43:37.799888: Pseudo dice [0.8542] +2024-11-21 20:43:37.799974: Epoch time: 17.6 s +2024-11-21 20:43:38.672763: +2024-11-21 20:43:38.672977: Epoch 1804 +2024-11-21 20:43:38.673100: Current learning rate: 0.00795 +2024-11-21 20:43:58.987826: train_loss -0.7685 +2024-11-21 20:43:58.989603: val_loss -0.7729 +2024-11-21 20:43:58.989714: Pseudo dice [0.8517] +2024-11-21 20:43:58.989808: Epoch time: 20.32 s +2024-11-21 20:43:59.822166: +2024-11-21 20:43:59.822403: Epoch 1805 +2024-11-21 20:43:59.822532: Current learning rate: 0.00794 +2024-11-21 20:44:19.759750: train_loss -0.7651 +2024-11-21 20:44:19.762052: val_loss -0.7518 +2024-11-21 20:44:19.762213: Pseudo dice [0.8302] +2024-11-21 20:44:19.762314: Epoch time: 19.94 s +2024-11-21 20:44:20.598378: +2024-11-21 20:44:20.598640: Epoch 1806 +2024-11-21 20:44:20.598761: Current learning rate: 0.00794 +2024-11-21 20:44:39.043691: train_loss -0.7696 +2024-11-21 20:44:39.051355: val_loss -0.7533 +2024-11-21 20:44:39.051493: Pseudo dice [0.8357] +2024-11-21 20:44:39.051581: Epoch time: 18.45 s +2024-11-21 20:44:40.060972: +2024-11-21 20:44:40.061214: Epoch 1807 +2024-11-21 20:44:40.061348: Current learning rate: 0.00794 +2024-11-21 20:44:59.441615: train_loss -0.7758 +2024-11-21 20:44:59.445349: val_loss -0.763 +2024-11-21 20:44:59.445494: Pseudo dice [0.8527] +2024-11-21 20:44:59.445580: Epoch time: 19.38 s +2024-11-21 20:45:00.361981: +2024-11-21 20:45:00.362174: Epoch 1808 +2024-11-21 20:45:00.362313: Current learning rate: 0.00794 +2024-11-21 20:45:20.246353: train_loss -0.7749 +2024-11-21 20:45:20.253467: val_loss -0.7672 +2024-11-21 20:45:20.253608: Pseudo dice [0.8406] +2024-11-21 20:45:20.253704: Epoch time: 19.89 s +2024-11-21 20:45:21.140891: +2024-11-21 20:45:21.141101: Epoch 1809 +2024-11-21 20:45:21.141231: Current learning rate: 0.00794 +2024-11-21 20:45:40.784003: train_loss -0.7678 +2024-11-21 20:45:40.793099: val_loss -0.7462 +2024-11-21 20:45:40.793245: Pseudo dice [0.8518] +2024-11-21 20:45:40.793346: Epoch time: 19.64 s +2024-11-21 20:45:42.046485: +2024-11-21 20:45:42.046711: Epoch 1810 +2024-11-21 20:45:42.046862: Current learning rate: 0.00794 +2024-11-21 20:46:01.065494: train_loss -0.7826 +2024-11-21 20:46:01.072128: val_loss -0.7568 +2024-11-21 20:46:01.072266: Pseudo dice [0.8456] +2024-11-21 20:46:01.072354: Epoch time: 19.02 s +2024-11-21 20:46:02.088972: +2024-11-21 20:46:02.089189: Epoch 1811 +2024-11-21 20:46:02.089303: Current learning rate: 0.00794 +2024-11-21 20:46:22.013112: train_loss -0.7856 +2024-11-21 20:46:22.021618: val_loss -0.7616 +2024-11-21 20:46:22.021742: Pseudo dice [0.8437] +2024-11-21 20:46:22.021844: Epoch time: 19.92 s +2024-11-21 20:46:22.891540: +2024-11-21 20:46:22.891782: Epoch 1812 +2024-11-21 20:46:22.891905: Current learning rate: 0.00794 +2024-11-21 20:46:42.448343: train_loss -0.764 +2024-11-21 20:46:42.454788: val_loss -0.7697 +2024-11-21 20:46:42.454920: Pseudo dice [0.8565] +2024-11-21 20:46:42.455025: Epoch time: 19.56 s +2024-11-21 20:46:43.496104: +2024-11-21 20:46:43.496581: Epoch 1813 +2024-11-21 20:46:43.496702: Current learning rate: 0.00794 +2024-11-21 20:47:02.694896: train_loss -0.7778 +2024-11-21 20:47:02.697907: val_loss -0.7805 +2024-11-21 20:47:02.698014: Pseudo dice [0.8528] +2024-11-21 20:47:02.698105: Epoch time: 19.2 s +2024-11-21 20:47:03.531105: +2024-11-21 20:47:03.531302: Epoch 1814 +2024-11-21 20:47:03.531422: Current learning rate: 0.00793 +2024-11-21 20:47:23.090381: train_loss -0.7757 +2024-11-21 20:47:23.097974: val_loss -0.7924 +2024-11-21 20:47:23.098133: Pseudo dice [0.8476] +2024-11-21 20:47:23.098230: Epoch time: 19.56 s +2024-11-21 20:47:23.934628: +2024-11-21 20:47:23.934831: Epoch 1815 +2024-11-21 20:47:23.934964: Current learning rate: 0.00793 +2024-11-21 20:47:42.184007: train_loss -0.7698 +2024-11-21 20:47:42.194719: val_loss -0.7857 +2024-11-21 20:47:42.194873: Pseudo dice [0.8445] +2024-11-21 20:47:42.195032: Epoch time: 18.25 s +2024-11-21 20:47:43.125183: +2024-11-21 20:47:43.125392: Epoch 1816 +2024-11-21 20:47:43.125507: Current learning rate: 0.00793 +2024-11-21 20:48:03.341462: train_loss -0.7799 +2024-11-21 20:48:03.346733: val_loss -0.7748 +2024-11-21 20:48:03.346840: Pseudo dice [0.8447] +2024-11-21 20:48:03.346933: Epoch time: 20.22 s +2024-11-21 20:48:04.253831: +2024-11-21 20:48:04.254074: Epoch 1817 +2024-11-21 20:48:04.254259: Current learning rate: 0.00793 +2024-11-21 20:48:24.362565: train_loss -0.7696 +2024-11-21 20:48:24.365601: val_loss -0.7534 +2024-11-21 20:48:24.365710: Pseudo dice [0.8387] +2024-11-21 20:48:24.365807: Epoch time: 20.11 s +2024-11-21 20:48:25.191843: +2024-11-21 20:48:25.192074: Epoch 1818 +2024-11-21 20:48:25.192187: Current learning rate: 0.00793 +2024-11-21 20:48:43.441296: train_loss -0.7769 +2024-11-21 20:48:43.443975: val_loss -0.7754 +2024-11-21 20:48:43.444122: Pseudo dice [0.8513] +2024-11-21 20:48:43.444211: Epoch time: 18.25 s +2024-11-21 20:48:44.371701: +2024-11-21 20:48:44.371904: Epoch 1819 +2024-11-21 20:48:44.372035: Current learning rate: 0.00793 +2024-11-21 20:49:03.222624: train_loss -0.7793 +2024-11-21 20:49:03.226211: val_loss -0.7506 +2024-11-21 20:49:03.226347: Pseudo dice [0.8377] +2024-11-21 20:49:03.226438: Epoch time: 18.85 s +2024-11-21 20:49:04.184700: +2024-11-21 20:49:04.184913: Epoch 1820 +2024-11-21 20:49:04.185040: Current learning rate: 0.00793 +2024-11-21 20:49:21.927318: train_loss -0.7674 +2024-11-21 20:49:21.929614: val_loss -0.7464 +2024-11-21 20:49:21.929724: Pseudo dice [0.8535] +2024-11-21 20:49:21.929809: Epoch time: 17.74 s +2024-11-21 20:49:23.153923: +2024-11-21 20:49:23.154140: Epoch 1821 +2024-11-21 20:49:23.154260: Current learning rate: 0.00793 +2024-11-21 20:49:41.775458: train_loss -0.7771 +2024-11-21 20:49:41.782901: val_loss -0.7704 +2024-11-21 20:49:41.783072: Pseudo dice [0.8558] +2024-11-21 20:49:41.783177: Epoch time: 18.62 s +2024-11-21 20:49:42.642546: +2024-11-21 20:49:42.642762: Epoch 1822 +2024-11-21 20:49:42.642907: Current learning rate: 0.00792 +2024-11-21 20:50:01.487474: train_loss -0.7798 +2024-11-21 20:50:01.496515: val_loss -0.779 +2024-11-21 20:50:01.496686: Pseudo dice [0.8496] +2024-11-21 20:50:01.496778: Epoch time: 18.85 s +2024-11-21 20:50:02.345417: +2024-11-21 20:50:02.345630: Epoch 1823 +2024-11-21 20:50:02.345758: Current learning rate: 0.00792 +2024-11-21 20:50:22.455479: train_loss -0.7608 +2024-11-21 20:50:22.464362: val_loss -0.7485 +2024-11-21 20:50:22.464511: Pseudo dice [0.8403] +2024-11-21 20:50:22.464608: Epoch time: 20.11 s +2024-11-21 20:50:23.497505: +2024-11-21 20:50:23.497724: Epoch 1824 +2024-11-21 20:50:23.497843: Current learning rate: 0.00792 +2024-11-21 20:50:42.285533: train_loss -0.759 +2024-11-21 20:50:42.290967: val_loss -0.7542 +2024-11-21 20:50:42.291113: Pseudo dice [0.8425] +2024-11-21 20:50:42.291223: Epoch time: 18.79 s +2024-11-21 20:50:43.142721: +2024-11-21 20:50:43.142931: Epoch 1825 +2024-11-21 20:50:43.143049: Current learning rate: 0.00792 +2024-11-21 20:51:01.523902: train_loss -0.7713 +2024-11-21 20:51:01.530631: val_loss -0.7483 +2024-11-21 20:51:01.530792: Pseudo dice [0.8468] +2024-11-21 20:51:01.544695: Epoch time: 18.38 s +2024-11-21 20:51:02.379912: +2024-11-21 20:51:02.380140: Epoch 1826 +2024-11-21 20:51:02.380259: Current learning rate: 0.00792 +2024-11-21 20:51:20.672386: train_loss -0.7866 +2024-11-21 20:51:20.678772: val_loss -0.7749 +2024-11-21 20:51:20.678924: Pseudo dice [0.8445] +2024-11-21 20:51:20.679015: Epoch time: 18.29 s +2024-11-21 20:51:21.578919: +2024-11-21 20:51:21.579127: Epoch 1827 +2024-11-21 20:51:21.579259: Current learning rate: 0.00792 +2024-11-21 20:51:39.962346: train_loss -0.7783 +2024-11-21 20:51:39.968550: val_loss -0.7706 +2024-11-21 20:51:39.968697: Pseudo dice [0.8541] +2024-11-21 20:51:39.968807: Epoch time: 18.38 s +2024-11-21 20:51:40.987889: +2024-11-21 20:51:40.988126: Epoch 1828 +2024-11-21 20:51:40.988268: Current learning rate: 0.00792 +2024-11-21 20:52:00.509381: train_loss -0.768 +2024-11-21 20:52:00.518632: val_loss -0.7543 +2024-11-21 20:52:00.518782: Pseudo dice [0.8085] +2024-11-21 20:52:00.518877: Epoch time: 19.52 s +2024-11-21 20:52:01.385664: +2024-11-21 20:52:01.385873: Epoch 1829 +2024-11-21 20:52:01.385997: Current learning rate: 0.00792 +2024-11-21 20:52:21.276758: train_loss -0.7585 +2024-11-21 20:52:21.280406: val_loss -0.7663 +2024-11-21 20:52:21.280505: Pseudo dice [0.8503] +2024-11-21 20:52:21.280595: Epoch time: 19.89 s +2024-11-21 20:52:22.109852: +2024-11-21 20:52:22.110044: Epoch 1830 +2024-11-21 20:52:22.110159: Current learning rate: 0.00792 +2024-11-21 20:52:40.263296: train_loss -0.7643 +2024-11-21 20:52:40.264814: val_loss -0.7512 +2024-11-21 20:52:40.264958: Pseudo dice [0.8339] +2024-11-21 20:52:40.265121: Epoch time: 18.15 s +2024-11-21 20:52:41.137574: +2024-11-21 20:52:41.138015: Epoch 1831 +2024-11-21 20:52:41.138161: Current learning rate: 0.00791 +2024-11-21 20:53:00.100734: train_loss -0.7715 +2024-11-21 20:53:00.102432: val_loss -0.7564 +2024-11-21 20:53:00.102530: Pseudo dice [0.8357] +2024-11-21 20:53:00.102616: Epoch time: 18.96 s +2024-11-21 20:53:01.349485: +2024-11-21 20:53:01.349735: Epoch 1832 +2024-11-21 20:53:01.349856: Current learning rate: 0.00791 +2024-11-21 20:53:20.525365: train_loss -0.7766 +2024-11-21 20:53:20.528089: val_loss -0.7806 +2024-11-21 20:53:20.528232: Pseudo dice [0.8518] +2024-11-21 20:53:20.528310: Epoch time: 19.18 s +2024-11-21 20:53:21.386833: +2024-11-21 20:53:21.387072: Epoch 1833 +2024-11-21 20:53:21.387219: Current learning rate: 0.00791 +2024-11-21 20:53:41.579924: train_loss -0.7648 +2024-11-21 20:53:41.584425: val_loss -0.7608 +2024-11-21 20:53:41.584587: Pseudo dice [0.8478] +2024-11-21 20:53:41.584671: Epoch time: 20.19 s +2024-11-21 20:53:42.478675: +2024-11-21 20:53:42.478928: Epoch 1834 +2024-11-21 20:53:42.479051: Current learning rate: 0.00791 +2024-11-21 20:54:00.934126: train_loss -0.7546 +2024-11-21 20:54:00.940171: val_loss -0.7699 +2024-11-21 20:54:00.940281: Pseudo dice [0.8512] +2024-11-21 20:54:00.940379: Epoch time: 18.46 s +2024-11-21 20:54:01.884136: +2024-11-21 20:54:01.884350: Epoch 1835 +2024-11-21 20:54:01.884465: Current learning rate: 0.00791 +2024-11-21 20:54:22.147239: train_loss -0.7794 +2024-11-21 20:54:22.153053: val_loss -0.7563 +2024-11-21 20:54:22.153208: Pseudo dice [0.8575] +2024-11-21 20:54:22.153310: Epoch time: 20.26 s +2024-11-21 20:54:23.014494: +2024-11-21 20:54:23.014695: Epoch 1836 +2024-11-21 20:54:23.014825: Current learning rate: 0.00791 +2024-11-21 20:54:41.960130: train_loss -0.7724 +2024-11-21 20:54:41.968397: val_loss -0.7796 +2024-11-21 20:54:41.968513: Pseudo dice [0.8597] +2024-11-21 20:54:41.968594: Epoch time: 18.95 s +2024-11-21 20:54:42.848133: +2024-11-21 20:54:42.848350: Epoch 1837 +2024-11-21 20:54:42.848466: Current learning rate: 0.00791 +2024-11-21 20:55:01.932181: train_loss -0.7623 +2024-11-21 20:55:01.949275: val_loss -0.7396 +2024-11-21 20:55:01.949419: Pseudo dice [0.8494] +2024-11-21 20:55:01.949507: Epoch time: 19.08 s +2024-11-21 20:55:02.924232: +2024-11-21 20:55:02.924420: Epoch 1838 +2024-11-21 20:55:02.924546: Current learning rate: 0.00791 +2024-11-21 20:55:22.672641: train_loss -0.7767 +2024-11-21 20:55:22.692262: val_loss -0.7884 +2024-11-21 20:55:22.692441: Pseudo dice [0.8456] +2024-11-21 20:55:22.692553: Epoch time: 19.75 s +2024-11-21 20:55:23.538181: +2024-11-21 20:55:23.538377: Epoch 1839 +2024-11-21 20:55:23.538505: Current learning rate: 0.00791 +2024-11-21 20:55:42.509832: train_loss -0.758 +2024-11-21 20:55:42.517417: val_loss -0.7612 +2024-11-21 20:55:42.517565: Pseudo dice [0.8418] +2024-11-21 20:55:42.517678: Epoch time: 18.97 s +2024-11-21 20:55:43.395544: +2024-11-21 20:55:43.395753: Epoch 1840 +2024-11-21 20:55:43.395880: Current learning rate: 0.0079 +2024-11-21 20:56:03.559077: train_loss -0.7728 +2024-11-21 20:56:03.565533: val_loss -0.7649 +2024-11-21 20:56:03.565653: Pseudo dice [0.8418] +2024-11-21 20:56:03.565735: Epoch time: 20.16 s +2024-11-21 20:56:04.439887: +2024-11-21 20:56:04.440315: Epoch 1841 +2024-11-21 20:56:04.440463: Current learning rate: 0.0079 +2024-11-21 20:56:22.590163: train_loss -0.787 +2024-11-21 20:56:22.599411: val_loss -0.7794 +2024-11-21 20:56:22.599526: Pseudo dice [0.8489] +2024-11-21 20:56:22.599613: Epoch time: 18.15 s +2024-11-21 20:56:23.433542: +2024-11-21 20:56:23.433751: Epoch 1842 +2024-11-21 20:56:23.433873: Current learning rate: 0.0079 +2024-11-21 20:56:42.275197: train_loss -0.7611 +2024-11-21 20:56:42.282877: val_loss -0.7725 +2024-11-21 20:56:42.283000: Pseudo dice [0.8573] +2024-11-21 20:56:42.283121: Epoch time: 18.84 s +2024-11-21 20:56:43.562012: +2024-11-21 20:56:43.562254: Epoch 1843 +2024-11-21 20:56:43.562384: Current learning rate: 0.0079 +2024-11-21 20:57:02.293995: train_loss -0.7686 +2024-11-21 20:57:02.296108: val_loss -0.7481 +2024-11-21 20:57:02.296218: Pseudo dice [0.8444] +2024-11-21 20:57:02.296305: Epoch time: 18.73 s +2024-11-21 20:57:03.320744: +2024-11-21 20:57:03.320969: Epoch 1844 +2024-11-21 20:57:03.321095: Current learning rate: 0.0079 +2024-11-21 20:57:22.198621: train_loss -0.7747 +2024-11-21 20:57:22.201972: val_loss -0.7305 +2024-11-21 20:57:22.202118: Pseudo dice [0.8395] +2024-11-21 20:57:22.202203: Epoch time: 18.88 s +2024-11-21 20:57:23.071308: +2024-11-21 20:57:23.071535: Epoch 1845 +2024-11-21 20:57:23.071653: Current learning rate: 0.0079 +2024-11-21 20:57:42.193730: train_loss -0.771 +2024-11-21 20:57:42.199208: val_loss -0.7689 +2024-11-21 20:57:42.199327: Pseudo dice [0.8574] +2024-11-21 20:57:42.199420: Epoch time: 19.12 s +2024-11-21 20:57:43.041564: +2024-11-21 20:57:43.041770: Epoch 1846 +2024-11-21 20:57:43.041883: Current learning rate: 0.0079 +2024-11-21 20:58:02.742942: train_loss -0.7677 +2024-11-21 20:58:02.745920: val_loss -0.7631 +2024-11-21 20:58:02.746014: Pseudo dice [0.8579] +2024-11-21 20:58:02.746099: Epoch time: 19.7 s +2024-11-21 20:58:03.573207: +2024-11-21 20:58:03.573406: Epoch 1847 +2024-11-21 20:58:03.573528: Current learning rate: 0.0079 +2024-11-21 20:58:22.758025: train_loss -0.765 +2024-11-21 20:58:22.765462: val_loss -0.7552 +2024-11-21 20:58:22.765607: Pseudo dice [0.8413] +2024-11-21 20:58:22.765702: Epoch time: 19.19 s +2024-11-21 20:58:23.761238: +2024-11-21 20:58:23.761450: Epoch 1848 +2024-11-21 20:58:23.761784: Current learning rate: 0.00789 +2024-11-21 20:58:42.267552: train_loss -0.775 +2024-11-21 20:58:42.275619: val_loss -0.7578 +2024-11-21 20:58:42.275766: Pseudo dice [0.8416] +2024-11-21 20:58:42.275852: Epoch time: 18.51 s +2024-11-21 20:58:43.158686: +2024-11-21 20:58:43.158886: Epoch 1849 +2024-11-21 20:58:43.159002: Current learning rate: 0.00789 +2024-11-21 20:59:01.267659: train_loss -0.7763 +2024-11-21 20:59:01.274869: val_loss -0.7429 +2024-11-21 20:59:01.275004: Pseudo dice [0.8557] +2024-11-21 20:59:01.275126: Epoch time: 18.11 s +2024-11-21 20:59:02.332485: +2024-11-21 20:59:02.332716: Epoch 1850 +2024-11-21 20:59:02.332849: Current learning rate: 0.00789 +2024-11-21 20:59:20.350222: train_loss -0.7734 +2024-11-21 20:59:20.367631: val_loss -0.7786 +2024-11-21 20:59:20.367777: Pseudo dice [0.8647] +2024-11-21 20:59:20.367863: Epoch time: 18.02 s +2024-11-21 20:59:21.207535: +2024-11-21 20:59:21.207730: Epoch 1851 +2024-11-21 20:59:21.208083: Current learning rate: 0.00789 +2024-11-21 20:59:40.717616: train_loss -0.7724 +2024-11-21 20:59:40.719798: val_loss -0.7584 +2024-11-21 20:59:40.719913: Pseudo dice [0.8392] +2024-11-21 20:59:40.720008: Epoch time: 19.51 s +2024-11-21 20:59:41.550243: +2024-11-21 20:59:41.550645: Epoch 1852 +2024-11-21 20:59:41.550794: Current learning rate: 0.00789 +2024-11-21 20:59:59.887389: train_loss -0.7746 +2024-11-21 20:59:59.888900: val_loss -0.7738 +2024-11-21 20:59:59.889007: Pseudo dice [0.8498] +2024-11-21 20:59:59.889154: Epoch time: 18.34 s +2024-11-21 21:00:00.720120: +2024-11-21 21:00:00.720312: Epoch 1853 +2024-11-21 21:00:00.720435: Current learning rate: 0.00789 +2024-11-21 21:00:18.346823: train_loss -0.7629 +2024-11-21 21:00:18.351687: val_loss -0.7501 +2024-11-21 21:00:18.351838: Pseudo dice [0.8372] +2024-11-21 21:00:18.351931: Epoch time: 17.63 s +2024-11-21 21:00:19.693283: +2024-11-21 21:00:19.693520: Epoch 1854 +2024-11-21 21:00:19.693639: Current learning rate: 0.00789 +2024-11-21 21:00:39.414485: train_loss -0.7667 +2024-11-21 21:00:39.420055: val_loss -0.7762 +2024-11-21 21:00:39.420199: Pseudo dice [0.8372] +2024-11-21 21:00:39.420290: Epoch time: 19.72 s +2024-11-21 21:00:40.256371: +2024-11-21 21:00:40.256620: Epoch 1855 +2024-11-21 21:00:40.256750: Current learning rate: 0.00789 +2024-11-21 21:00:58.840864: train_loss -0.7701 +2024-11-21 21:00:58.842637: val_loss -0.7738 +2024-11-21 21:00:58.842735: Pseudo dice [0.8586] +2024-11-21 21:00:58.842835: Epoch time: 18.59 s +2024-11-21 21:00:59.671610: +2024-11-21 21:00:59.671833: Epoch 1856 +2024-11-21 21:00:59.671976: Current learning rate: 0.00789 +2024-11-21 21:01:18.593762: train_loss -0.78 +2024-11-21 21:01:18.595423: val_loss -0.7727 +2024-11-21 21:01:18.595578: Pseudo dice [0.8457] +2024-11-21 21:01:18.595673: Epoch time: 18.92 s +2024-11-21 21:01:19.472679: +2024-11-21 21:01:19.472912: Epoch 1857 +2024-11-21 21:01:19.473067: Current learning rate: 0.00788 +2024-11-21 21:01:38.275376: train_loss -0.7793 +2024-11-21 21:01:38.281425: val_loss -0.757 +2024-11-21 21:01:38.281561: Pseudo dice [0.8405] +2024-11-21 21:01:38.281658: Epoch time: 18.8 s +2024-11-21 21:01:39.250874: +2024-11-21 21:01:39.251086: Epoch 1858 +2024-11-21 21:01:39.251207: Current learning rate: 0.00788 +2024-11-21 21:01:59.122691: train_loss -0.7766 +2024-11-21 21:01:59.127649: val_loss -0.7656 +2024-11-21 21:01:59.127797: Pseudo dice [0.8517] +2024-11-21 21:01:59.127902: Epoch time: 19.87 s +2024-11-21 21:02:00.082841: +2024-11-21 21:02:00.083103: Epoch 1859 +2024-11-21 21:02:00.083220: Current learning rate: 0.00788 +2024-11-21 21:02:19.036420: train_loss -0.7719 +2024-11-21 21:02:19.043850: val_loss -0.7538 +2024-11-21 21:02:19.043972: Pseudo dice [0.8399] +2024-11-21 21:02:19.044051: Epoch time: 18.95 s +2024-11-21 21:02:19.895065: +2024-11-21 21:02:19.895267: Epoch 1860 +2024-11-21 21:02:19.895408: Current learning rate: 0.00788 +2024-11-21 21:02:39.901248: train_loss -0.7743 +2024-11-21 21:02:39.907853: val_loss -0.7501 +2024-11-21 21:02:39.908010: Pseudo dice [0.8386] +2024-11-21 21:02:39.908118: Epoch time: 20.01 s +2024-11-21 21:02:40.763838: +2024-11-21 21:02:40.764018: Epoch 1861 +2024-11-21 21:02:40.764154: Current learning rate: 0.00788 +2024-11-21 21:03:00.277970: train_loss -0.7609 +2024-11-21 21:03:00.284846: val_loss -0.7808 +2024-11-21 21:03:00.284997: Pseudo dice [0.8534] +2024-11-21 21:03:00.285109: Epoch time: 19.51 s +2024-11-21 21:03:01.117784: +2024-11-21 21:03:01.118010: Epoch 1862 +2024-11-21 21:03:01.118146: Current learning rate: 0.00788 +2024-11-21 21:03:21.078680: train_loss -0.7665 +2024-11-21 21:03:21.081345: val_loss -0.7527 +2024-11-21 21:03:21.081477: Pseudo dice [0.8602] +2024-11-21 21:03:21.081568: Epoch time: 19.96 s +2024-11-21 21:03:22.021395: +2024-11-21 21:03:22.021839: Epoch 1863 +2024-11-21 21:03:22.021982: Current learning rate: 0.00788 +2024-11-21 21:03:40.561584: train_loss -0.7627 +2024-11-21 21:03:40.567601: val_loss -0.7507 +2024-11-21 21:03:40.567741: Pseudo dice [0.8455] +2024-11-21 21:03:40.568068: Epoch time: 18.54 s +2024-11-21 21:03:41.704701: +2024-11-21 21:03:41.704905: Epoch 1864 +2024-11-21 21:03:41.705030: Current learning rate: 0.00788 +2024-11-21 21:04:01.113262: train_loss -0.7619 +2024-11-21 21:04:01.125723: val_loss -0.7617 +2024-11-21 21:04:01.125843: Pseudo dice [0.8321] +2024-11-21 21:04:01.125946: Epoch time: 19.41 s +2024-11-21 21:04:02.421554: +2024-11-21 21:04:02.421777: Epoch 1865 +2024-11-21 21:04:02.421918: Current learning rate: 0.00788 +2024-11-21 21:04:20.957471: train_loss -0.7731 +2024-11-21 21:04:20.962131: val_loss -0.7774 +2024-11-21 21:04:20.962260: Pseudo dice [0.8495] +2024-11-21 21:04:20.962361: Epoch time: 18.54 s +2024-11-21 21:04:21.869960: +2024-11-21 21:04:21.870188: Epoch 1866 +2024-11-21 21:04:21.870306: Current learning rate: 0.00787 +2024-11-21 21:04:41.193194: train_loss -0.7689 +2024-11-21 21:04:41.199053: val_loss -0.7681 +2024-11-21 21:04:41.199196: Pseudo dice [0.8422] +2024-11-21 21:04:41.199289: Epoch time: 19.32 s +2024-11-21 21:04:42.065095: +2024-11-21 21:04:42.065291: Epoch 1867 +2024-11-21 21:04:42.065411: Current learning rate: 0.00787 +2024-11-21 21:05:02.042418: train_loss -0.7689 +2024-11-21 21:05:02.044538: val_loss -0.761 +2024-11-21 21:05:02.044654: Pseudo dice [0.8411] +2024-11-21 21:05:02.044746: Epoch time: 19.98 s +2024-11-21 21:05:02.878985: +2024-11-21 21:05:02.879214: Epoch 1868 +2024-11-21 21:05:02.879350: Current learning rate: 0.00787 +2024-11-21 21:05:23.155740: train_loss -0.7642 +2024-11-21 21:05:23.158121: val_loss -0.7578 +2024-11-21 21:05:23.158214: Pseudo dice [0.8542] +2024-11-21 21:05:23.158305: Epoch time: 20.28 s +2024-11-21 21:05:23.987524: +2024-11-21 21:05:23.987769: Epoch 1869 +2024-11-21 21:05:23.987898: Current learning rate: 0.00787 +2024-11-21 21:05:43.185852: train_loss -0.7652 +2024-11-21 21:05:43.188435: val_loss -0.7466 +2024-11-21 21:05:43.188580: Pseudo dice [0.8291] +2024-11-21 21:05:43.188667: Epoch time: 19.2 s +2024-11-21 21:05:44.042107: +2024-11-21 21:05:44.042332: Epoch 1870 +2024-11-21 21:05:44.042469: Current learning rate: 0.00787 +2024-11-21 21:06:03.071803: train_loss -0.758 +2024-11-21 21:06:03.075174: val_loss -0.7473 +2024-11-21 21:06:03.075289: Pseudo dice [0.8543] +2024-11-21 21:06:03.075379: Epoch time: 19.03 s +2024-11-21 21:06:04.055697: +2024-11-21 21:06:04.055925: Epoch 1871 +2024-11-21 21:06:04.056070: Current learning rate: 0.00787 +2024-11-21 21:06:22.630200: train_loss -0.7592 +2024-11-21 21:06:22.639386: val_loss -0.7663 +2024-11-21 21:06:22.639527: Pseudo dice [0.8432] +2024-11-21 21:06:22.639621: Epoch time: 18.58 s +2024-11-21 21:06:23.476067: +2024-11-21 21:06:23.476275: Epoch 1872 +2024-11-21 21:06:23.476397: Current learning rate: 0.00787 +2024-11-21 21:06:42.862070: train_loss -0.7619 +2024-11-21 21:06:42.867486: val_loss -0.7692 +2024-11-21 21:06:42.867627: Pseudo dice [0.8584] +2024-11-21 21:06:42.867723: Epoch time: 19.39 s +2024-11-21 21:06:43.712226: +2024-11-21 21:06:43.712485: Epoch 1873 +2024-11-21 21:06:43.712600: Current learning rate: 0.00787 +2024-11-21 21:07:02.729585: train_loss -0.7542 +2024-11-21 21:07:02.743016: val_loss -0.7671 +2024-11-21 21:07:02.743168: Pseudo dice [0.8482] +2024-11-21 21:07:02.743261: Epoch time: 19.02 s +2024-11-21 21:07:03.654140: +2024-11-21 21:07:03.654335: Epoch 1874 +2024-11-21 21:07:03.654644: Current learning rate: 0.00786 +2024-11-21 21:07:23.704230: train_loss -0.7583 +2024-11-21 21:07:23.706779: val_loss -0.7403 +2024-11-21 21:07:23.706884: Pseudo dice [0.8333] +2024-11-21 21:07:23.706997: Epoch time: 20.05 s +2024-11-21 21:07:24.543248: +2024-11-21 21:07:24.543436: Epoch 1875 +2024-11-21 21:07:24.543565: Current learning rate: 0.00786 +2024-11-21 21:07:44.750077: train_loss -0.7541 +2024-11-21 21:07:44.753258: val_loss -0.7484 +2024-11-21 21:07:44.753403: Pseudo dice [0.841] +2024-11-21 21:07:44.753504: Epoch time: 20.21 s +2024-11-21 21:07:46.126001: +2024-11-21 21:07:46.126227: Epoch 1876 +2024-11-21 21:07:46.126348: Current learning rate: 0.00786 +2024-11-21 21:08:05.481169: train_loss -0.7646 +2024-11-21 21:08:05.484952: val_loss -0.7682 +2024-11-21 21:08:05.485110: Pseudo dice [0.8438] +2024-11-21 21:08:05.485197: Epoch time: 19.36 s +2024-11-21 21:08:06.314966: +2024-11-21 21:08:06.315277: Epoch 1877 +2024-11-21 21:08:06.315416: Current learning rate: 0.00786 +2024-11-21 21:08:25.250565: train_loss -0.7726 +2024-11-21 21:08:25.255282: val_loss -0.7697 +2024-11-21 21:08:25.255404: Pseudo dice [0.842] +2024-11-21 21:08:25.255501: Epoch time: 18.94 s +2024-11-21 21:08:26.093193: +2024-11-21 21:08:26.093417: Epoch 1878 +2024-11-21 21:08:26.093538: Current learning rate: 0.00786 +2024-11-21 21:08:43.356914: train_loss -0.7801 +2024-11-21 21:08:43.361852: val_loss -0.7437 +2024-11-21 21:08:43.361971: Pseudo dice [0.8476] +2024-11-21 21:08:43.362086: Epoch time: 17.26 s +2024-11-21 21:08:44.194942: +2024-11-21 21:08:44.195189: Epoch 1879 +2024-11-21 21:08:44.195310: Current learning rate: 0.00786 +2024-11-21 21:09:03.015477: train_loss -0.7687 +2024-11-21 21:09:03.022683: val_loss -0.7671 +2024-11-21 21:09:03.022830: Pseudo dice [0.85] +2024-11-21 21:09:03.022916: Epoch time: 18.82 s +2024-11-21 21:09:03.868286: +2024-11-21 21:09:03.868489: Epoch 1880 +2024-11-21 21:09:03.868620: Current learning rate: 0.00786 +2024-11-21 21:09:22.369079: train_loss -0.7648 +2024-11-21 21:09:22.375969: val_loss -0.7874 +2024-11-21 21:09:22.376103: Pseudo dice [0.8431] +2024-11-21 21:09:22.376204: Epoch time: 18.5 s +2024-11-21 21:09:23.297813: +2024-11-21 21:09:23.298030: Epoch 1881 +2024-11-21 21:09:23.298152: Current learning rate: 0.00786 +2024-11-21 21:09:43.504526: train_loss -0.7729 +2024-11-21 21:09:43.508171: val_loss -0.7797 +2024-11-21 21:09:43.508295: Pseudo dice [0.8555] +2024-11-21 21:09:43.508386: Epoch time: 20.21 s +2024-11-21 21:09:44.386507: +2024-11-21 21:09:44.386704: Epoch 1882 +2024-11-21 21:09:44.386825: Current learning rate: 0.00786 +2024-11-21 21:10:03.485621: train_loss -0.7659 +2024-11-21 21:10:03.487857: val_loss -0.7632 +2024-11-21 21:10:03.487983: Pseudo dice [0.8512] +2024-11-21 21:10:03.488078: Epoch time: 19.1 s +2024-11-21 21:10:04.317402: +2024-11-21 21:10:04.317632: Epoch 1883 +2024-11-21 21:10:04.317755: Current learning rate: 0.00785 +2024-11-21 21:10:23.280242: train_loss -0.7676 +2024-11-21 21:10:23.309432: val_loss -0.7603 +2024-11-21 21:10:23.309575: Pseudo dice [0.8563] +2024-11-21 21:10:23.309662: Epoch time: 18.96 s +2024-11-21 21:10:24.343034: +2024-11-21 21:10:24.343243: Epoch 1884 +2024-11-21 21:10:24.343358: Current learning rate: 0.00785 +2024-11-21 21:10:41.707355: train_loss -0.7727 +2024-11-21 21:10:41.711858: val_loss -0.7499 +2024-11-21 21:10:41.712012: Pseudo dice [0.8526] +2024-11-21 21:10:41.712105: Epoch time: 17.37 s +2024-11-21 21:10:42.551975: +2024-11-21 21:10:42.552179: Epoch 1885 +2024-11-21 21:10:42.552305: Current learning rate: 0.00785 +2024-11-21 21:11:01.385376: train_loss -0.7739 +2024-11-21 21:11:01.397304: val_loss -0.7934 +2024-11-21 21:11:01.397440: Pseudo dice [0.8512] +2024-11-21 21:11:01.397559: Epoch time: 18.83 s +2024-11-21 21:11:02.260239: +2024-11-21 21:11:02.260480: Epoch 1886 +2024-11-21 21:11:02.260613: Current learning rate: 0.00785 +2024-11-21 21:11:23.352134: train_loss -0.7715 +2024-11-21 21:11:23.358670: val_loss -0.7731 +2024-11-21 21:11:23.358803: Pseudo dice [0.8552] +2024-11-21 21:11:23.358895: Epoch time: 21.09 s +2024-11-21 21:11:24.664118: +2024-11-21 21:11:24.664318: Epoch 1887 +2024-11-21 21:11:24.664445: Current learning rate: 0.00785 +2024-11-21 21:11:45.475369: train_loss -0.7668 +2024-11-21 21:11:45.478285: val_loss -0.7759 +2024-11-21 21:11:45.478400: Pseudo dice [0.8572] +2024-11-21 21:11:45.478501: Epoch time: 20.81 s +2024-11-21 21:11:46.305782: +2024-11-21 21:11:46.306026: Epoch 1888 +2024-11-21 21:11:46.306150: Current learning rate: 0.00785 +2024-11-21 21:12:05.936964: train_loss -0.7765 +2024-11-21 21:12:05.939253: val_loss -0.7659 +2024-11-21 21:12:05.939373: Pseudo dice [0.8479] +2024-11-21 21:12:05.939456: Epoch time: 19.63 s +2024-11-21 21:12:06.773949: +2024-11-21 21:12:06.774260: Epoch 1889 +2024-11-21 21:12:06.774379: Current learning rate: 0.00785 +2024-11-21 21:12:24.982907: train_loss -0.7728 +2024-11-21 21:12:24.988842: val_loss -0.7584 +2024-11-21 21:12:24.988964: Pseudo dice [0.857] +2024-11-21 21:12:24.989050: Epoch time: 18.21 s +2024-11-21 21:12:25.826691: +2024-11-21 21:12:25.826913: Epoch 1890 +2024-11-21 21:12:25.827038: Current learning rate: 0.00785 +2024-11-21 21:12:45.222556: train_loss -0.7781 +2024-11-21 21:12:45.225336: val_loss -0.7957 +2024-11-21 21:12:45.225475: Pseudo dice [0.8538] +2024-11-21 21:12:45.225580: Epoch time: 19.4 s +2024-11-21 21:12:46.076391: +2024-11-21 21:12:46.076712: Epoch 1891 +2024-11-21 21:12:46.076829: Current learning rate: 0.00784 +2024-11-21 21:13:05.951278: train_loss -0.7712 +2024-11-21 21:13:05.954235: val_loss -0.7752 +2024-11-21 21:13:05.954374: Pseudo dice [0.8588] +2024-11-21 21:13:05.954465: Epoch time: 19.88 s +2024-11-21 21:13:07.175930: +2024-11-21 21:13:07.176153: Epoch 1892 +2024-11-21 21:13:07.176285: Current learning rate: 0.00784 +2024-11-21 21:13:26.472755: train_loss -0.7598 +2024-11-21 21:13:26.486286: val_loss -0.7731 +2024-11-21 21:13:26.486408: Pseudo dice [0.8497] +2024-11-21 21:13:26.486508: Epoch time: 19.3 s +2024-11-21 21:13:27.401601: +2024-11-21 21:13:27.401935: Epoch 1893 +2024-11-21 21:13:27.402073: Current learning rate: 0.00784 +2024-11-21 21:13:46.229655: train_loss -0.7798 +2024-11-21 21:13:46.236547: val_loss -0.7786 +2024-11-21 21:13:46.236694: Pseudo dice [0.8565] +2024-11-21 21:13:46.236786: Epoch time: 18.83 s +2024-11-21 21:13:47.378070: +2024-11-21 21:13:47.378282: Epoch 1894 +2024-11-21 21:13:47.378414: Current learning rate: 0.00784 +2024-11-21 21:14:06.162214: train_loss -0.7802 +2024-11-21 21:14:06.168367: val_loss -0.7628 +2024-11-21 21:14:06.168524: Pseudo dice [0.8451] +2024-11-21 21:14:06.168629: Epoch time: 18.78 s +2024-11-21 21:14:07.022328: +2024-11-21 21:14:07.022550: Epoch 1895 +2024-11-21 21:14:07.022680: Current learning rate: 0.00784 +2024-11-21 21:14:25.390426: train_loss -0.7747 +2024-11-21 21:14:25.396326: val_loss -0.7483 +2024-11-21 21:14:25.396445: Pseudo dice [0.8381] +2024-11-21 21:14:25.396523: Epoch time: 18.37 s +2024-11-21 21:14:26.242928: +2024-11-21 21:14:26.243151: Epoch 1896 +2024-11-21 21:14:26.243288: Current learning rate: 0.00784 +2024-11-21 21:14:45.291633: train_loss -0.7586 +2024-11-21 21:14:45.296032: val_loss -0.7263 +2024-11-21 21:14:45.296154: Pseudo dice [0.844] +2024-11-21 21:14:45.296262: Epoch time: 19.05 s +2024-11-21 21:14:46.159299: +2024-11-21 21:14:46.159562: Epoch 1897 +2024-11-21 21:14:46.159705: Current learning rate: 0.00784 +2024-11-21 21:15:05.670189: train_loss -0.7509 +2024-11-21 21:15:05.673162: val_loss -0.7316 +2024-11-21 21:15:05.673278: Pseudo dice [0.836] +2024-11-21 21:15:05.673362: Epoch time: 19.51 s +2024-11-21 21:15:06.918565: +2024-11-21 21:15:06.918769: Epoch 1898 +2024-11-21 21:15:06.918890: Current learning rate: 0.00784 +2024-11-21 21:15:25.439122: train_loss -0.7601 +2024-11-21 21:15:25.446254: val_loss -0.7618 +2024-11-21 21:15:25.446388: Pseudo dice [0.8592] +2024-11-21 21:15:25.446479: Epoch time: 18.52 s +2024-11-21 21:15:26.340241: +2024-11-21 21:15:26.340507: Epoch 1899 +2024-11-21 21:15:26.340636: Current learning rate: 0.00784 +2024-11-21 21:15:44.880683: train_loss -0.7648 +2024-11-21 21:15:44.885997: val_loss -0.7451 +2024-11-21 21:15:44.886134: Pseudo dice [0.8249] +2024-11-21 21:15:44.886230: Epoch time: 18.54 s +2024-11-21 21:15:45.957313: +2024-11-21 21:15:45.957751: Epoch 1900 +2024-11-21 21:15:45.957883: Current learning rate: 0.00783 +2024-11-21 21:16:04.054881: train_loss -0.7351 +2024-11-21 21:16:04.058921: val_loss -0.7518 +2024-11-21 21:16:04.059070: Pseudo dice [0.8429] +2024-11-21 21:16:04.059187: Epoch time: 18.1 s +2024-11-21 21:16:04.996381: +2024-11-21 21:16:04.996588: Epoch 1901 +2024-11-21 21:16:04.996704: Current learning rate: 0.00783 +2024-11-21 21:16:23.115269: train_loss -0.747 +2024-11-21 21:16:23.136111: val_loss -0.7404 +2024-11-21 21:16:23.136239: Pseudo dice [0.8443] +2024-11-21 21:16:23.136337: Epoch time: 18.12 s +2024-11-21 21:16:24.146255: +2024-11-21 21:16:24.146458: Epoch 1902 +2024-11-21 21:16:24.146592: Current learning rate: 0.00783 +2024-11-21 21:16:42.820083: train_loss -0.7516 +2024-11-21 21:16:42.826081: val_loss -0.7457 +2024-11-21 21:16:42.826200: Pseudo dice [0.8187] +2024-11-21 21:16:42.826294: Epoch time: 18.67 s +2024-11-21 21:16:43.854803: +2024-11-21 21:16:43.855007: Epoch 1903 +2024-11-21 21:16:43.855129: Current learning rate: 0.00783 +2024-11-21 21:17:03.496706: train_loss -0.7528 +2024-11-21 21:17:03.504028: val_loss -0.7699 +2024-11-21 21:17:03.504197: Pseudo dice [0.8561] +2024-11-21 21:17:03.504301: Epoch time: 19.64 s +2024-11-21 21:17:04.590064: +2024-11-21 21:17:04.590289: Epoch 1904 +2024-11-21 21:17:04.590409: Current learning rate: 0.00783 +2024-11-21 21:17:23.657043: train_loss -0.7622 +2024-11-21 21:17:23.658793: val_loss -0.7764 +2024-11-21 21:17:23.658887: Pseudo dice [0.8439] +2024-11-21 21:17:23.658978: Epoch time: 19.07 s +2024-11-21 21:17:24.491671: +2024-11-21 21:17:24.491861: Epoch 1905 +2024-11-21 21:17:24.491974: Current learning rate: 0.00783 +2024-11-21 21:17:44.447463: train_loss -0.7632 +2024-11-21 21:17:44.455118: val_loss -0.7548 +2024-11-21 21:17:44.455266: Pseudo dice [0.8609] +2024-11-21 21:17:44.455360: Epoch time: 19.96 s +2024-11-21 21:17:45.385869: +2024-11-21 21:17:45.386082: Epoch 1906 +2024-11-21 21:17:45.386206: Current learning rate: 0.00783 +2024-11-21 21:18:04.575354: train_loss -0.7517 +2024-11-21 21:18:04.577543: val_loss -0.7668 +2024-11-21 21:18:04.577664: Pseudo dice [0.8502] +2024-11-21 21:18:04.577753: Epoch time: 19.19 s +2024-11-21 21:18:05.429672: +2024-11-21 21:18:05.429885: Epoch 1907 +2024-11-21 21:18:05.430002: Current learning rate: 0.00783 +2024-11-21 21:18:24.199726: train_loss -0.7618 +2024-11-21 21:18:24.201843: val_loss -0.7586 +2024-11-21 21:18:24.202000: Pseudo dice [0.8461] +2024-11-21 21:18:24.202115: Epoch time: 18.77 s +2024-11-21 21:18:25.069612: +2024-11-21 21:18:25.069844: Epoch 1908 +2024-11-21 21:18:25.069970: Current learning rate: 0.00783 +2024-11-21 21:18:44.171054: train_loss -0.7636 +2024-11-21 21:18:44.172618: val_loss -0.7831 +2024-11-21 21:18:44.172719: Pseudo dice [0.8477] +2024-11-21 21:18:44.172800: Epoch time: 19.1 s +2024-11-21 21:18:45.562515: +2024-11-21 21:18:45.562734: Epoch 1909 +2024-11-21 21:18:45.562866: Current learning rate: 0.00782 +2024-11-21 21:19:04.648157: train_loss -0.77 +2024-11-21 21:19:04.650048: val_loss -0.756 +2024-11-21 21:19:04.650144: Pseudo dice [0.8332] +2024-11-21 21:19:04.650249: Epoch time: 19.09 s +2024-11-21 21:19:05.488286: +2024-11-21 21:19:05.488486: Epoch 1910 +2024-11-21 21:19:05.488622: Current learning rate: 0.00782 +2024-11-21 21:19:24.489534: train_loss -0.7674 +2024-11-21 21:19:24.497077: val_loss -0.7662 +2024-11-21 21:19:24.497209: Pseudo dice [0.8476] +2024-11-21 21:19:24.497324: Epoch time: 19.0 s +2024-11-21 21:19:25.360701: +2024-11-21 21:19:25.360913: Epoch 1911 +2024-11-21 21:19:25.361030: Current learning rate: 0.00782 +2024-11-21 21:19:44.518404: train_loss -0.7825 +2024-11-21 21:19:44.526619: val_loss -0.7699 +2024-11-21 21:19:44.526774: Pseudo dice [0.8416] +2024-11-21 21:19:44.526883: Epoch time: 19.16 s +2024-11-21 21:19:45.529562: +2024-11-21 21:19:45.529824: Epoch 1912 +2024-11-21 21:19:45.529953: Current learning rate: 0.00782 +2024-11-21 21:20:03.756766: train_loss -0.7718 +2024-11-21 21:20:03.764302: val_loss -0.7444 +2024-11-21 21:20:03.764443: Pseudo dice [0.8403] +2024-11-21 21:20:03.764543: Epoch time: 18.23 s +2024-11-21 21:20:04.843981: +2024-11-21 21:20:04.844213: Epoch 1913 +2024-11-21 21:20:04.844326: Current learning rate: 0.00782 +2024-11-21 21:20:23.679751: train_loss -0.764 +2024-11-21 21:20:23.685848: val_loss -0.7719 +2024-11-21 21:20:23.685992: Pseudo dice [0.8437] +2024-11-21 21:20:23.686080: Epoch time: 18.84 s +2024-11-21 21:20:24.529104: +2024-11-21 21:20:24.529311: Epoch 1914 +2024-11-21 21:20:24.529434: Current learning rate: 0.00782 +2024-11-21 21:20:43.485594: train_loss -0.7761 +2024-11-21 21:20:43.498595: val_loss -0.7777 +2024-11-21 21:20:43.498986: Pseudo dice [0.8498] +2024-11-21 21:20:43.499099: Epoch time: 18.96 s +2024-11-21 21:20:44.503239: +2024-11-21 21:20:44.503478: Epoch 1915 +2024-11-21 21:20:44.503620: Current learning rate: 0.00782 +2024-11-21 21:21:03.178762: train_loss -0.7787 +2024-11-21 21:21:03.184527: val_loss -0.7573 +2024-11-21 21:21:03.184718: Pseudo dice [0.8355] +2024-11-21 21:21:03.184842: Epoch time: 18.68 s +2024-11-21 21:21:04.098548: +2024-11-21 21:21:04.098753: Epoch 1916 +2024-11-21 21:21:04.098864: Current learning rate: 0.00782 +2024-11-21 21:21:21.723815: train_loss -0.7789 +2024-11-21 21:21:21.730016: val_loss -0.7626 +2024-11-21 21:21:21.730160: Pseudo dice [0.8453] +2024-11-21 21:21:21.730264: Epoch time: 17.63 s +2024-11-21 21:21:22.591327: +2024-11-21 21:21:22.591571: Epoch 1917 +2024-11-21 21:21:22.591702: Current learning rate: 0.00781 +2024-11-21 21:21:41.090355: train_loss -0.7674 +2024-11-21 21:21:41.092249: val_loss -0.761 +2024-11-21 21:21:41.092366: Pseudo dice [0.8633] +2024-11-21 21:21:41.092458: Epoch time: 18.5 s +2024-11-21 21:21:41.931088: +2024-11-21 21:21:41.931309: Epoch 1918 +2024-11-21 21:21:41.931451: Current learning rate: 0.00781 +2024-11-21 21:22:01.290728: train_loss -0.7753 +2024-11-21 21:22:01.335714: val_loss -0.7726 +2024-11-21 21:22:01.335870: Pseudo dice [0.853] +2024-11-21 21:22:01.335973: Epoch time: 19.36 s +2024-11-21 21:22:02.363231: +2024-11-21 21:22:02.363448: Epoch 1919 +2024-11-21 21:22:02.363569: Current learning rate: 0.00781 +2024-11-21 21:22:22.152082: train_loss -0.7711 +2024-11-21 21:22:22.158408: val_loss -0.7751 +2024-11-21 21:22:22.158526: Pseudo dice [0.8608] +2024-11-21 21:22:22.158628: Epoch time: 19.79 s +2024-11-21 21:22:23.454675: +2024-11-21 21:22:23.454883: Epoch 1920 +2024-11-21 21:22:23.455009: Current learning rate: 0.00781 +2024-11-21 21:22:43.285255: train_loss -0.764 +2024-11-21 21:22:43.296848: val_loss -0.7666 +2024-11-21 21:22:43.296971: Pseudo dice [0.8414] +2024-11-21 21:22:43.297067: Epoch time: 19.83 s +2024-11-21 21:22:44.548912: +2024-11-21 21:22:44.549128: Epoch 1921 +2024-11-21 21:22:44.549243: Current learning rate: 0.00781 +2024-11-21 21:23:03.757577: train_loss -0.77 +2024-11-21 21:23:03.765460: val_loss -0.7453 +2024-11-21 21:23:03.765576: Pseudo dice [0.855] +2024-11-21 21:23:03.765677: Epoch time: 19.21 s +2024-11-21 21:23:04.615817: +2024-11-21 21:23:04.616028: Epoch 1922 +2024-11-21 21:23:04.616168: Current learning rate: 0.00781 +2024-11-21 21:23:24.828588: train_loss -0.7732 +2024-11-21 21:23:24.835604: val_loss -0.7454 +2024-11-21 21:23:24.835761: Pseudo dice [0.8582] +2024-11-21 21:23:24.835851: Epoch time: 20.21 s +2024-11-21 21:23:25.678230: +2024-11-21 21:23:25.678437: Epoch 1923 +2024-11-21 21:23:25.678569: Current learning rate: 0.00781 +2024-11-21 21:23:44.649679: train_loss -0.7636 +2024-11-21 21:23:44.651968: val_loss -0.7553 +2024-11-21 21:23:44.652098: Pseudo dice [0.8354] +2024-11-21 21:23:44.652189: Epoch time: 18.97 s +2024-11-21 21:23:45.529746: +2024-11-21 21:23:45.529969: Epoch 1924 +2024-11-21 21:23:45.530113: Current learning rate: 0.00781 +2024-11-21 21:24:04.556943: train_loss -0.7716 +2024-11-21 21:24:04.563017: val_loss -0.7898 +2024-11-21 21:24:04.563176: Pseudo dice [0.8583] +2024-11-21 21:24:04.563289: Epoch time: 19.03 s +2024-11-21 21:24:05.415799: +2024-11-21 21:24:05.416023: Epoch 1925 +2024-11-21 21:24:05.416155: Current learning rate: 0.00781 +2024-11-21 21:24:24.077506: train_loss -0.7714 +2024-11-21 21:24:24.085639: val_loss -0.7441 +2024-11-21 21:24:24.085760: Pseudo dice [0.8486] +2024-11-21 21:24:24.085849: Epoch time: 18.66 s +2024-11-21 21:24:25.075512: +2024-11-21 21:24:25.075745: Epoch 1926 +2024-11-21 21:24:25.075882: Current learning rate: 0.0078 +2024-11-21 21:24:43.875619: train_loss -0.7687 +2024-11-21 21:24:43.878386: val_loss -0.7875 +2024-11-21 21:24:43.878505: Pseudo dice [0.8563] +2024-11-21 21:24:43.878617: Epoch time: 18.8 s +2024-11-21 21:24:44.719640: +2024-11-21 21:24:44.719864: Epoch 1927 +2024-11-21 21:24:44.719985: Current learning rate: 0.0078 +2024-11-21 21:25:03.818222: train_loss -0.7745 +2024-11-21 21:25:03.820581: val_loss -0.7761 +2024-11-21 21:25:03.820700: Pseudo dice [0.8685] +2024-11-21 21:25:03.820798: Epoch time: 19.1 s +2024-11-21 21:25:04.699815: +2024-11-21 21:25:04.700042: Epoch 1928 +2024-11-21 21:25:04.700174: Current learning rate: 0.0078 +2024-11-21 21:25:25.123356: train_loss -0.7724 +2024-11-21 21:25:25.127049: val_loss -0.7416 +2024-11-21 21:25:25.127199: Pseudo dice [0.8339] +2024-11-21 21:25:25.127307: Epoch time: 20.42 s +2024-11-21 21:25:25.979657: +2024-11-21 21:25:25.979877: Epoch 1929 +2024-11-21 21:25:25.979998: Current learning rate: 0.0078 +2024-11-21 21:25:44.537554: train_loss -0.7779 +2024-11-21 21:25:44.539958: val_loss -0.761 +2024-11-21 21:25:44.540088: Pseudo dice [0.8509] +2024-11-21 21:25:44.540198: Epoch time: 18.56 s +2024-11-21 21:25:45.378458: +2024-11-21 21:25:45.378682: Epoch 1930 +2024-11-21 21:25:45.378815: Current learning rate: 0.0078 +2024-11-21 21:26:05.323413: train_loss -0.7657 +2024-11-21 21:26:05.325177: val_loss -0.7597 +2024-11-21 21:26:05.325324: Pseudo dice [0.8503] +2024-11-21 21:26:05.325414: Epoch time: 19.95 s +2024-11-21 21:26:06.579919: +2024-11-21 21:26:06.580345: Epoch 1931 +2024-11-21 21:26:06.580481: Current learning rate: 0.0078 +2024-11-21 21:26:25.389000: train_loss -0.7622 +2024-11-21 21:26:25.394463: val_loss -0.7551 +2024-11-21 21:26:25.394575: Pseudo dice [0.8535] +2024-11-21 21:26:25.394683: Epoch time: 18.8 s +2024-11-21 21:26:26.257536: +2024-11-21 21:26:26.257958: Epoch 1932 +2024-11-21 21:26:26.258104: Current learning rate: 0.0078 +2024-11-21 21:26:44.833417: train_loss -0.7739 +2024-11-21 21:26:44.840119: val_loss -0.789 +2024-11-21 21:26:44.840271: Pseudo dice [0.8586] +2024-11-21 21:26:44.840379: Epoch time: 18.58 s +2024-11-21 21:26:45.783875: +2024-11-21 21:26:45.784319: Epoch 1933 +2024-11-21 21:26:45.784465: Current learning rate: 0.0078 +2024-11-21 21:27:05.179235: train_loss -0.7741 +2024-11-21 21:27:05.182918: val_loss -0.7541 +2024-11-21 21:27:05.183015: Pseudo dice [0.8619] +2024-11-21 21:27:05.183105: Epoch time: 19.4 s +2024-11-21 21:27:06.020939: +2024-11-21 21:27:06.021401: Epoch 1934 +2024-11-21 21:27:06.021543: Current learning rate: 0.0078 +2024-11-21 21:27:24.951488: train_loss -0.7709 +2024-11-21 21:27:24.957223: val_loss -0.7609 +2024-11-21 21:27:24.957349: Pseudo dice [0.8527] +2024-11-21 21:27:24.957449: Epoch time: 18.93 s +2024-11-21 21:27:25.995030: +2024-11-21 21:27:25.995429: Epoch 1935 +2024-11-21 21:27:25.995569: Current learning rate: 0.00779 +2024-11-21 21:27:44.594917: train_loss -0.7612 +2024-11-21 21:27:44.603565: val_loss -0.7799 +2024-11-21 21:27:44.603745: Pseudo dice [0.8512] +2024-11-21 21:27:44.603855: Epoch time: 18.6 s +2024-11-21 21:27:45.698294: +2024-11-21 21:27:45.698713: Epoch 1936 +2024-11-21 21:27:45.698847: Current learning rate: 0.00779 +2024-11-21 21:28:05.518587: train_loss -0.7736 +2024-11-21 21:28:05.530816: val_loss -0.7557 +2024-11-21 21:28:05.530956: Pseudo dice [0.8287] +2024-11-21 21:28:05.531049: Epoch time: 19.82 s +2024-11-21 21:28:06.376070: +2024-11-21 21:28:06.376493: Epoch 1937 +2024-11-21 21:28:06.376635: Current learning rate: 0.00779 +2024-11-21 21:28:24.590222: train_loss -0.7687 +2024-11-21 21:28:24.603468: val_loss -0.7646 +2024-11-21 21:28:24.603580: Pseudo dice [0.8429] +2024-11-21 21:28:24.603674: Epoch time: 18.21 s +2024-11-21 21:28:25.503003: +2024-11-21 21:28:25.503414: Epoch 1938 +2024-11-21 21:28:25.503550: Current learning rate: 0.00779 +2024-11-21 21:28:45.138055: train_loss -0.7748 +2024-11-21 21:28:45.144516: val_loss -0.7723 +2024-11-21 21:28:45.144693: Pseudo dice [0.8488] +2024-11-21 21:28:45.144786: Epoch time: 19.64 s +2024-11-21 21:28:46.142787: +2024-11-21 21:28:46.143243: Epoch 1939 +2024-11-21 21:28:46.143379: Current learning rate: 0.00779 +2024-11-21 21:29:05.980882: train_loss -0.7727 +2024-11-21 21:29:05.984428: val_loss -0.7449 +2024-11-21 21:29:05.984565: Pseudo dice [0.8384] +2024-11-21 21:29:05.984651: Epoch time: 19.84 s +2024-11-21 21:29:06.826593: +2024-11-21 21:29:06.827219: Epoch 1940 +2024-11-21 21:29:06.827380: Current learning rate: 0.00779 +2024-11-21 21:29:25.927113: train_loss -0.7851 +2024-11-21 21:29:25.935192: val_loss -0.7415 +2024-11-21 21:29:25.935338: Pseudo dice [0.8471] +2024-11-21 21:29:25.935460: Epoch time: 19.1 s +2024-11-21 21:29:26.776711: +2024-11-21 21:29:26.776968: Epoch 1941 +2024-11-21 21:29:26.777098: Current learning rate: 0.00779 +2024-11-21 21:29:46.382325: train_loss -0.7768 +2024-11-21 21:29:46.385944: val_loss -0.7493 +2024-11-21 21:29:46.386068: Pseudo dice [0.8455] +2024-11-21 21:29:46.386159: Epoch time: 19.61 s +2024-11-21 21:29:47.665071: +2024-11-21 21:29:47.665303: Epoch 1942 +2024-11-21 21:29:47.665418: Current learning rate: 0.00779 +2024-11-21 21:30:07.192304: train_loss -0.773 +2024-11-21 21:30:07.200776: val_loss -0.7824 +2024-11-21 21:30:07.200895: Pseudo dice [0.855] +2024-11-21 21:30:07.200994: Epoch time: 19.53 s +2024-11-21 21:30:08.050822: +2024-11-21 21:30:08.051071: Epoch 1943 +2024-11-21 21:30:08.051197: Current learning rate: 0.00778 +2024-11-21 21:30:27.431063: train_loss -0.774 +2024-11-21 21:30:27.448387: val_loss -0.7663 +2024-11-21 21:30:27.448551: Pseudo dice [0.8505] +2024-11-21 21:30:27.448652: Epoch time: 19.38 s +2024-11-21 21:30:28.400404: +2024-11-21 21:30:28.400662: Epoch 1944 +2024-11-21 21:30:28.400792: Current learning rate: 0.00778 +2024-11-21 21:30:47.696539: train_loss -0.7676 +2024-11-21 21:30:47.702667: val_loss -0.7519 +2024-11-21 21:30:47.702783: Pseudo dice [0.8455] +2024-11-21 21:30:47.702879: Epoch time: 19.3 s +2024-11-21 21:30:48.547621: +2024-11-21 21:30:48.547820: Epoch 1945 +2024-11-21 21:30:48.547938: Current learning rate: 0.00778 +2024-11-21 21:31:08.298883: train_loss -0.7718 +2024-11-21 21:31:08.313139: val_loss -0.7511 +2024-11-21 21:31:08.313298: Pseudo dice [0.8371] +2024-11-21 21:31:08.313411: Epoch time: 19.75 s +2024-11-21 21:31:09.167811: +2024-11-21 21:31:09.168018: Epoch 1946 +2024-11-21 21:31:09.168137: Current learning rate: 0.00778 +2024-11-21 21:31:28.903414: train_loss -0.7746 +2024-11-21 21:31:28.909214: val_loss -0.745 +2024-11-21 21:31:28.909338: Pseudo dice [0.8386] +2024-11-21 21:31:28.909451: Epoch time: 19.74 s +2024-11-21 21:31:29.819555: +2024-11-21 21:31:29.819771: Epoch 1947 +2024-11-21 21:31:29.819906: Current learning rate: 0.00778 +2024-11-21 21:31:48.399343: train_loss -0.7742 +2024-11-21 21:31:48.407606: val_loss -0.7399 +2024-11-21 21:31:48.407741: Pseudo dice [0.8206] +2024-11-21 21:31:48.407828: Epoch time: 18.58 s +2024-11-21 21:31:49.590968: +2024-11-21 21:31:49.591185: Epoch 1948 +2024-11-21 21:31:49.591313: Current learning rate: 0.00778 +2024-11-21 21:32:07.469052: train_loss -0.7688 +2024-11-21 21:32:07.472078: val_loss -0.7422 +2024-11-21 21:32:07.472186: Pseudo dice [0.844] +2024-11-21 21:32:07.472281: Epoch time: 17.88 s +2024-11-21 21:32:08.313816: +2024-11-21 21:32:08.314013: Epoch 1949 +2024-11-21 21:32:08.314132: Current learning rate: 0.00778 +2024-11-21 21:32:28.043525: train_loss -0.7591 +2024-11-21 21:32:28.050892: val_loss -0.7747 +2024-11-21 21:32:28.051039: Pseudo dice [0.8405] +2024-11-21 21:32:28.051131: Epoch time: 19.73 s +2024-11-21 21:32:29.231690: +2024-11-21 21:32:29.231891: Epoch 1950 +2024-11-21 21:32:29.232023: Current learning rate: 0.00778 +2024-11-21 21:32:49.070372: train_loss -0.776 +2024-11-21 21:32:49.073950: val_loss -0.7691 +2024-11-21 21:32:49.074072: Pseudo dice [0.8399] +2024-11-21 21:32:49.074171: Epoch time: 19.84 s +2024-11-21 21:32:50.080588: +2024-11-21 21:32:50.080788: Epoch 1951 +2024-11-21 21:32:50.080916: Current learning rate: 0.00778 +2024-11-21 21:33:09.942909: train_loss -0.7656 +2024-11-21 21:33:09.950782: val_loss -0.7766 +2024-11-21 21:33:09.950950: Pseudo dice [0.8456] +2024-11-21 21:33:09.951051: Epoch time: 19.86 s +2024-11-21 21:33:11.237380: +2024-11-21 21:33:11.237616: Epoch 1952 +2024-11-21 21:33:11.237761: Current learning rate: 0.00777 +2024-11-21 21:33:30.801460: train_loss -0.7716 +2024-11-21 21:33:30.803918: val_loss -0.7805 +2024-11-21 21:33:30.804027: Pseudo dice [0.8434] +2024-11-21 21:33:30.804314: Epoch time: 19.56 s +2024-11-21 21:33:31.634626: +2024-11-21 21:33:31.634840: Epoch 1953 +2024-11-21 21:33:31.634961: Current learning rate: 0.00777 +2024-11-21 21:33:51.570453: train_loss -0.7777 +2024-11-21 21:33:51.572486: val_loss -0.7622 +2024-11-21 21:33:51.572597: Pseudo dice [0.8437] +2024-11-21 21:33:51.572680: Epoch time: 19.94 s +2024-11-21 21:33:52.401316: +2024-11-21 21:33:52.401541: Epoch 1954 +2024-11-21 21:33:52.401686: Current learning rate: 0.00777 +2024-11-21 21:34:11.995100: train_loss -0.765 +2024-11-21 21:34:12.002613: val_loss -0.7451 +2024-11-21 21:34:12.002756: Pseudo dice [0.8367] +2024-11-21 21:34:12.002849: Epoch time: 19.59 s +2024-11-21 21:34:12.841250: +2024-11-21 21:34:12.841470: Epoch 1955 +2024-11-21 21:34:12.841607: Current learning rate: 0.00777 +2024-11-21 21:34:32.378909: train_loss -0.7691 +2024-11-21 21:34:32.380555: val_loss -0.7575 +2024-11-21 21:34:32.380701: Pseudo dice [0.8474] +2024-11-21 21:34:32.380809: Epoch time: 19.54 s +2024-11-21 21:34:33.314754: +2024-11-21 21:34:33.315007: Epoch 1956 +2024-11-21 21:34:33.315143: Current learning rate: 0.00777 +2024-11-21 21:34:52.686805: train_loss -0.7531 +2024-11-21 21:34:52.694434: val_loss -0.7561 +2024-11-21 21:34:52.694590: Pseudo dice [0.8336] +2024-11-21 21:34:52.694676: Epoch time: 19.37 s +2024-11-21 21:34:53.569251: +2024-11-21 21:34:53.569532: Epoch 1957 +2024-11-21 21:34:53.569672: Current learning rate: 0.00777 +2024-11-21 21:35:12.831914: train_loss -0.7486 +2024-11-21 21:35:12.833427: val_loss -0.7424 +2024-11-21 21:35:12.833530: Pseudo dice [0.8449] +2024-11-21 21:35:12.833622: Epoch time: 19.26 s +2024-11-21 21:35:13.669781: +2024-11-21 21:35:13.669997: Epoch 1958 +2024-11-21 21:35:13.670127: Current learning rate: 0.00777 +2024-11-21 21:35:32.235688: train_loss -0.7661 +2024-11-21 21:35:32.243024: val_loss -0.763 +2024-11-21 21:35:32.243146: Pseudo dice [0.8489] +2024-11-21 21:35:32.243236: Epoch time: 18.57 s +2024-11-21 21:35:33.259411: +2024-11-21 21:35:33.259616: Epoch 1959 +2024-11-21 21:35:33.259742: Current learning rate: 0.00777 +2024-11-21 21:35:52.929007: train_loss -0.7724 +2024-11-21 21:35:52.931727: val_loss -0.77 +2024-11-21 21:35:52.931837: Pseudo dice [0.8484] +2024-11-21 21:35:52.931935: Epoch time: 19.67 s +2024-11-21 21:35:53.772588: +2024-11-21 21:35:53.772790: Epoch 1960 +2024-11-21 21:35:53.772908: Current learning rate: 0.00777 +2024-11-21 21:36:13.170902: train_loss -0.7659 +2024-11-21 21:36:13.175414: val_loss -0.7538 +2024-11-21 21:36:13.175542: Pseudo dice [0.8324] +2024-11-21 21:36:13.175629: Epoch time: 19.4 s +2024-11-21 21:36:14.143751: +2024-11-21 21:36:14.143962: Epoch 1961 +2024-11-21 21:36:14.144107: Current learning rate: 0.00776 +2024-11-21 21:36:33.516790: train_loss -0.7815 +2024-11-21 21:36:33.524228: val_loss -0.7679 +2024-11-21 21:36:33.524354: Pseudo dice [0.847] +2024-11-21 21:36:33.524440: Epoch time: 19.37 s +2024-11-21 21:36:34.369529: +2024-11-21 21:36:34.369746: Epoch 1962 +2024-11-21 21:36:34.369874: Current learning rate: 0.00776 +2024-11-21 21:36:53.880839: train_loss -0.7619 +2024-11-21 21:36:53.889227: val_loss -0.7849 +2024-11-21 21:36:53.889380: Pseudo dice [0.8464] +2024-11-21 21:36:53.889486: Epoch time: 19.51 s +2024-11-21 21:36:55.299292: +2024-11-21 21:36:55.299512: Epoch 1963 +2024-11-21 21:36:55.299629: Current learning rate: 0.00776 +2024-11-21 21:37:15.114508: train_loss -0.7556 +2024-11-21 21:37:15.120389: val_loss -0.7628 +2024-11-21 21:37:15.120532: Pseudo dice [0.8428] +2024-11-21 21:37:15.120641: Epoch time: 19.82 s +2024-11-21 21:37:16.003431: +2024-11-21 21:37:16.003676: Epoch 1964 +2024-11-21 21:37:16.003803: Current learning rate: 0.00776 +2024-11-21 21:37:35.263235: train_loss -0.7596 +2024-11-21 21:37:35.270901: val_loss -0.7632 +2024-11-21 21:37:35.271038: Pseudo dice [0.8538] +2024-11-21 21:37:35.271146: Epoch time: 19.26 s +2024-11-21 21:37:36.267848: +2024-11-21 21:37:36.268067: Epoch 1965 +2024-11-21 21:37:36.268201: Current learning rate: 0.00776 +2024-11-21 21:37:54.732502: train_loss -0.7564 +2024-11-21 21:37:54.747694: val_loss -0.7594 +2024-11-21 21:37:54.747847: Pseudo dice [0.8428] +2024-11-21 21:37:54.747947: Epoch time: 18.47 s +2024-11-21 21:37:55.724586: +2024-11-21 21:37:55.724827: Epoch 1966 +2024-11-21 21:37:55.724967: Current learning rate: 0.00776 +2024-11-21 21:38:15.604603: train_loss -0.7646 +2024-11-21 21:38:15.609416: val_loss -0.7516 +2024-11-21 21:38:15.609556: Pseudo dice [0.8379] +2024-11-21 21:38:15.609656: Epoch time: 19.88 s +2024-11-21 21:38:16.592842: +2024-11-21 21:38:16.593040: Epoch 1967 +2024-11-21 21:38:16.593172: Current learning rate: 0.00776 +2024-11-21 21:38:36.060432: train_loss -0.7712 +2024-11-21 21:38:36.066224: val_loss -0.7632 +2024-11-21 21:38:36.066357: Pseudo dice [0.8514] +2024-11-21 21:38:36.066445: Epoch time: 19.47 s +2024-11-21 21:38:36.916606: +2024-11-21 21:38:36.916812: Epoch 1968 +2024-11-21 21:38:36.916931: Current learning rate: 0.00776 +2024-11-21 21:38:56.370372: train_loss -0.7696 +2024-11-21 21:38:56.378453: val_loss -0.7542 +2024-11-21 21:38:56.378580: Pseudo dice [0.8437] +2024-11-21 21:38:56.378667: Epoch time: 19.45 s +2024-11-21 21:38:57.314734: +2024-11-21 21:38:57.314993: Epoch 1969 +2024-11-21 21:38:57.315138: Current learning rate: 0.00775 +2024-11-21 21:39:17.405614: train_loss -0.7759 +2024-11-21 21:39:17.407298: val_loss -0.7668 +2024-11-21 21:39:17.407396: Pseudo dice [0.8411] +2024-11-21 21:39:17.407483: Epoch time: 20.09 s +2024-11-21 21:39:18.253531: +2024-11-21 21:39:18.253775: Epoch 1970 +2024-11-21 21:39:18.253912: Current learning rate: 0.00775 +2024-11-21 21:39:37.763779: train_loss -0.7715 +2024-11-21 21:39:37.765321: val_loss -0.7561 +2024-11-21 21:39:37.765451: Pseudo dice [0.8284] +2024-11-21 21:39:37.765629: Epoch time: 19.51 s +2024-11-21 21:39:38.892941: +2024-11-21 21:39:38.893163: Epoch 1971 +2024-11-21 21:39:38.893282: Current learning rate: 0.00775 +2024-11-21 21:39:57.233650: train_loss -0.7659 +2024-11-21 21:39:57.239441: val_loss -0.7534 +2024-11-21 21:39:57.239585: Pseudo dice [0.8471] +2024-11-21 21:39:57.239671: Epoch time: 18.34 s +2024-11-21 21:39:58.098361: +2024-11-21 21:39:58.098571: Epoch 1972 +2024-11-21 21:39:58.098711: Current learning rate: 0.00775 +2024-11-21 21:40:17.654045: train_loss -0.7813 +2024-11-21 21:40:17.659448: val_loss -0.7576 +2024-11-21 21:40:17.659578: Pseudo dice [0.8435] +2024-11-21 21:40:17.659667: Epoch time: 19.56 s +2024-11-21 21:40:18.703010: +2024-11-21 21:40:18.703238: Epoch 1973 +2024-11-21 21:40:18.703369: Current learning rate: 0.00775 +2024-11-21 21:40:37.680459: train_loss -0.7728 +2024-11-21 21:40:37.683669: val_loss -0.7693 +2024-11-21 21:40:37.683795: Pseudo dice [0.851] +2024-11-21 21:40:37.683891: Epoch time: 18.98 s +2024-11-21 21:40:39.068718: +2024-11-21 21:40:39.068953: Epoch 1974 +2024-11-21 21:40:39.069075: Current learning rate: 0.00775 +2024-11-21 21:40:57.685225: train_loss -0.783 +2024-11-21 21:40:57.690703: val_loss -0.7569 +2024-11-21 21:40:57.690846: Pseudo dice [0.8461] +2024-11-21 21:40:57.690933: Epoch time: 18.62 s +2024-11-21 21:40:58.529638: +2024-11-21 21:40:58.529873: Epoch 1975 +2024-11-21 21:40:58.530009: Current learning rate: 0.00775 +2024-11-21 21:41:16.842323: train_loss -0.7766 +2024-11-21 21:41:16.849664: val_loss -0.7609 +2024-11-21 21:41:16.849820: Pseudo dice [0.8523] +2024-11-21 21:41:16.849908: Epoch time: 18.31 s +2024-11-21 21:41:17.693349: +2024-11-21 21:41:17.693577: Epoch 1976 +2024-11-21 21:41:17.693696: Current learning rate: 0.00775 +2024-11-21 21:41:37.151890: train_loss -0.7746 +2024-11-21 21:41:37.159414: val_loss -0.7589 +2024-11-21 21:41:37.159546: Pseudo dice [0.8476] +2024-11-21 21:41:37.159637: Epoch time: 19.46 s +2024-11-21 21:41:38.030313: +2024-11-21 21:41:38.030533: Epoch 1977 +2024-11-21 21:41:38.030661: Current learning rate: 0.00775 +2024-11-21 21:41:56.885921: train_loss -0.7706 +2024-11-21 21:41:56.889967: val_loss -0.7492 +2024-11-21 21:41:56.890094: Pseudo dice [0.8412] +2024-11-21 21:41:56.890191: Epoch time: 18.86 s +2024-11-21 21:41:57.760288: +2024-11-21 21:41:57.760524: Epoch 1978 +2024-11-21 21:41:57.760909: Current learning rate: 0.00774 +2024-11-21 21:42:17.763926: train_loss -0.7673 +2024-11-21 21:42:17.765551: val_loss -0.7766 +2024-11-21 21:42:17.765660: Pseudo dice [0.8391] +2024-11-21 21:42:17.765735: Epoch time: 20.0 s +2024-11-21 21:42:18.605182: +2024-11-21 21:42:18.605379: Epoch 1979 +2024-11-21 21:42:18.605499: Current learning rate: 0.00774 +2024-11-21 21:42:38.407395: train_loss -0.7603 +2024-11-21 21:42:38.413414: val_loss -0.7654 +2024-11-21 21:42:38.413557: Pseudo dice [0.8431] +2024-11-21 21:42:38.413643: Epoch time: 19.8 s +2024-11-21 21:42:39.258979: +2024-11-21 21:42:39.259191: Epoch 1980 +2024-11-21 21:42:39.259334: Current learning rate: 0.00774 +2024-11-21 21:42:57.206570: train_loss -0.7676 +2024-11-21 21:42:57.212202: val_loss -0.7476 +2024-11-21 21:42:57.212317: Pseudo dice [0.8392] +2024-11-21 21:42:57.212411: Epoch time: 17.95 s +2024-11-21 21:42:58.190069: +2024-11-21 21:42:58.190294: Epoch 1981 +2024-11-21 21:42:58.190435: Current learning rate: 0.00774 +2024-11-21 21:43:16.863367: train_loss -0.7708 +2024-11-21 21:43:16.877446: val_loss -0.7722 +2024-11-21 21:43:16.877578: Pseudo dice [0.8487] +2024-11-21 21:43:16.877672: Epoch time: 18.67 s +2024-11-21 21:43:17.927067: +2024-11-21 21:43:17.927260: Epoch 1982 +2024-11-21 21:43:17.927396: Current learning rate: 0.00774 +2024-11-21 21:43:37.313921: train_loss -0.7682 +2024-11-21 21:43:37.316778: val_loss -0.7054 +2024-11-21 21:43:37.316889: Pseudo dice [0.8442] +2024-11-21 21:43:37.316973: Epoch time: 19.39 s +2024-11-21 21:43:38.324021: +2024-11-21 21:43:38.324244: Epoch 1983 +2024-11-21 21:43:38.324388: Current learning rate: 0.00774 +2024-11-21 21:43:57.108670: train_loss -0.7636 +2024-11-21 21:43:57.123225: val_loss -0.7762 +2024-11-21 21:43:57.123393: Pseudo dice [0.8498] +2024-11-21 21:43:57.123485: Epoch time: 18.79 s +2024-11-21 21:43:58.073449: +2024-11-21 21:43:58.073633: Epoch 1984 +2024-11-21 21:43:58.073753: Current learning rate: 0.00774 +2024-11-21 21:44:18.023126: train_loss -0.7734 +2024-11-21 21:44:18.043153: val_loss -0.7571 +2024-11-21 21:44:18.043308: Pseudo dice [0.8518] +2024-11-21 21:44:18.043401: Epoch time: 19.95 s +2024-11-21 21:44:19.296932: +2024-11-21 21:44:19.297135: Epoch 1985 +2024-11-21 21:44:19.297265: Current learning rate: 0.00774 +2024-11-21 21:44:38.178817: train_loss -0.7598 +2024-11-21 21:44:38.181322: val_loss -0.7374 +2024-11-21 21:44:38.181455: Pseudo dice [0.835] +2024-11-21 21:44:38.181556: Epoch time: 18.88 s +2024-11-21 21:44:39.008544: +2024-11-21 21:44:39.008757: Epoch 1986 +2024-11-21 21:44:39.008881: Current learning rate: 0.00774 +2024-11-21 21:44:58.081922: train_loss -0.7579 +2024-11-21 21:44:58.090612: val_loss -0.759 +2024-11-21 21:44:58.090756: Pseudo dice [0.8338] +2024-11-21 21:44:58.090855: Epoch time: 19.07 s +2024-11-21 21:44:58.937318: +2024-11-21 21:44:58.937522: Epoch 1987 +2024-11-21 21:44:58.937639: Current learning rate: 0.00773 +2024-11-21 21:45:17.460311: train_loss -0.7713 +2024-11-21 21:45:17.467442: val_loss -0.7542 +2024-11-21 21:45:17.467580: Pseudo dice [0.8385] +2024-11-21 21:45:17.467688: Epoch time: 18.52 s +2024-11-21 21:45:18.452678: +2024-11-21 21:45:18.452892: Epoch 1988 +2024-11-21 21:45:18.453022: Current learning rate: 0.00773 +2024-11-21 21:45:37.139390: train_loss -0.7611 +2024-11-21 21:45:37.145626: val_loss -0.7719 +2024-11-21 21:45:37.145754: Pseudo dice [0.8531] +2024-11-21 21:45:37.145854: Epoch time: 18.69 s +2024-11-21 21:45:38.014678: +2024-11-21 21:45:38.014917: Epoch 1989 +2024-11-21 21:45:38.015038: Current learning rate: 0.00773 +2024-11-21 21:45:56.879880: train_loss -0.7462 +2024-11-21 21:45:56.893933: val_loss -0.7567 +2024-11-21 21:45:56.894098: Pseudo dice [0.8343] +2024-11-21 21:45:56.894193: Epoch time: 18.87 s +2024-11-21 21:45:57.882115: +2024-11-21 21:45:57.882325: Epoch 1990 +2024-11-21 21:45:57.882440: Current learning rate: 0.00773 +2024-11-21 21:46:17.643237: train_loss -0.7651 +2024-11-21 21:46:17.647799: val_loss -0.7591 +2024-11-21 21:46:17.647916: Pseudo dice [0.8402] +2024-11-21 21:46:17.648001: Epoch time: 19.76 s +2024-11-21 21:46:18.504093: +2024-11-21 21:46:18.504312: Epoch 1991 +2024-11-21 21:46:18.504466: Current learning rate: 0.00773 +2024-11-21 21:46:37.813393: train_loss -0.7626 +2024-11-21 21:46:37.819479: val_loss -0.7571 +2024-11-21 21:46:37.819619: Pseudo dice [0.8343] +2024-11-21 21:46:37.819717: Epoch time: 19.31 s +2024-11-21 21:46:38.801427: +2024-11-21 21:46:38.801668: Epoch 1992 +2024-11-21 21:46:38.801779: Current learning rate: 0.00773 +2024-11-21 21:46:57.937880: train_loss -0.7713 +2024-11-21 21:46:57.945341: val_loss -0.7717 +2024-11-21 21:46:57.945479: Pseudo dice [0.8392] +2024-11-21 21:46:57.945571: Epoch time: 19.14 s +2024-11-21 21:46:58.884839: +2024-11-21 21:46:58.885087: Epoch 1993 +2024-11-21 21:46:58.885234: Current learning rate: 0.00773 +2024-11-21 21:47:18.210171: train_loss -0.7784 +2024-11-21 21:47:18.214555: val_loss -0.7612 +2024-11-21 21:47:18.214733: Pseudo dice [0.8563] +2024-11-21 21:47:18.214827: Epoch time: 19.33 s +2024-11-21 21:47:19.057682: +2024-11-21 21:47:19.057893: Epoch 1994 +2024-11-21 21:47:19.058010: Current learning rate: 0.00773 +2024-11-21 21:47:37.266944: train_loss -0.775 +2024-11-21 21:47:37.274157: val_loss -0.7645 +2024-11-21 21:47:37.274314: Pseudo dice [0.8463] +2024-11-21 21:47:37.274486: Epoch time: 18.21 s +2024-11-21 21:47:38.117362: +2024-11-21 21:47:38.117550: Epoch 1995 +2024-11-21 21:47:38.117684: Current learning rate: 0.00772 +2024-11-21 21:47:57.735099: train_loss -0.7651 +2024-11-21 21:47:57.741194: val_loss -0.7724 +2024-11-21 21:47:57.741318: Pseudo dice [0.8428] +2024-11-21 21:47:57.741410: Epoch time: 19.62 s +2024-11-21 21:47:59.159366: +2024-11-21 21:47:59.159600: Epoch 1996 +2024-11-21 21:47:59.159722: Current learning rate: 0.00772 +2024-11-21 21:48:17.799134: train_loss -0.7533 +2024-11-21 21:48:17.805223: val_loss -0.7748 +2024-11-21 21:48:17.805352: Pseudo dice [0.8475] +2024-11-21 21:48:17.805452: Epoch time: 18.64 s +2024-11-21 21:48:18.732347: +2024-11-21 21:48:18.732567: Epoch 1997 +2024-11-21 21:48:18.732686: Current learning rate: 0.00772 +2024-11-21 21:48:37.354363: train_loss -0.7671 +2024-11-21 21:48:37.359409: val_loss -0.7723 +2024-11-21 21:48:37.359546: Pseudo dice [0.8481] +2024-11-21 21:48:37.359627: Epoch time: 18.62 s +2024-11-21 21:48:38.252412: +2024-11-21 21:48:38.252657: Epoch 1998 +2024-11-21 21:48:38.252793: Current learning rate: 0.00772 +2024-11-21 21:48:58.148972: train_loss -0.7722 +2024-11-21 21:48:58.158997: val_loss -0.7614 +2024-11-21 21:48:58.159168: Pseudo dice [0.8468] +2024-11-21 21:48:58.159420: Epoch time: 19.9 s +2024-11-21 21:48:59.008309: +2024-11-21 21:48:59.008538: Epoch 1999 +2024-11-21 21:48:59.008652: Current learning rate: 0.00772 +2024-11-21 21:49:17.758104: train_loss -0.7679 +2024-11-21 21:49:17.768647: val_loss -0.7553 +2024-11-21 21:49:17.768781: Pseudo dice [0.8485] +2024-11-21 21:49:17.768871: Epoch time: 18.75 s +2024-11-21 21:49:18.822511: +2024-11-21 21:49:18.822758: Epoch 2000 +2024-11-21 21:49:18.822881: Current learning rate: 0.00772 +2024-11-21 21:49:38.096648: train_loss -0.7744 +2024-11-21 21:49:38.103723: val_loss -0.7619 +2024-11-21 21:49:38.103846: Pseudo dice [0.8501] +2024-11-21 21:49:38.103934: Epoch time: 19.27 s +2024-11-21 21:49:38.991609: +2024-11-21 21:49:38.991816: Epoch 2001 +2024-11-21 21:49:38.991950: Current learning rate: 0.00772 +2024-11-21 21:49:58.426787: train_loss -0.7689 +2024-11-21 21:49:58.429849: val_loss -0.775 +2024-11-21 21:49:58.429992: Pseudo dice [0.852] +2024-11-21 21:49:58.430091: Epoch time: 19.44 s +2024-11-21 21:49:59.308890: +2024-11-21 21:49:59.309098: Epoch 2002 +2024-11-21 21:49:59.309218: Current learning rate: 0.00772 +2024-11-21 21:50:18.828117: train_loss -0.7633 +2024-11-21 21:50:18.834545: val_loss -0.7569 +2024-11-21 21:50:18.834684: Pseudo dice [0.8481] +2024-11-21 21:50:18.834774: Epoch time: 19.52 s +2024-11-21 21:50:19.720907: +2024-11-21 21:50:19.721132: Epoch 2003 +2024-11-21 21:50:19.721263: Current learning rate: 0.00772 +2024-11-21 21:50:38.768005: train_loss -0.7818 +2024-11-21 21:50:38.774933: val_loss -0.771 +2024-11-21 21:50:38.791217: Pseudo dice [0.8378] +2024-11-21 21:50:38.792164: Epoch time: 19.05 s +2024-11-21 21:50:39.690334: +2024-11-21 21:50:39.690561: Epoch 2004 +2024-11-21 21:50:39.690685: Current learning rate: 0.00771 +2024-11-21 21:50:58.006245: train_loss -0.785 +2024-11-21 21:50:58.013755: val_loss -0.7669 +2024-11-21 21:50:58.013886: Pseudo dice [0.8526] +2024-11-21 21:50:58.013975: Epoch time: 18.32 s +2024-11-21 21:50:58.854196: +2024-11-21 21:50:58.854395: Epoch 2005 +2024-11-21 21:50:58.854532: Current learning rate: 0.00771 +2024-11-21 21:51:17.630769: train_loss -0.7679 +2024-11-21 21:51:17.633359: val_loss -0.7425 +2024-11-21 21:51:17.633472: Pseudo dice [0.8395] +2024-11-21 21:51:17.633576: Epoch time: 18.78 s +2024-11-21 21:51:18.469488: +2024-11-21 21:51:18.469707: Epoch 2006 +2024-11-21 21:51:18.469834: Current learning rate: 0.00771 +2024-11-21 21:51:38.061411: train_loss -0.7795 +2024-11-21 21:51:38.064005: val_loss -0.7795 +2024-11-21 21:51:38.064109: Pseudo dice [0.8603] +2024-11-21 21:51:38.064200: Epoch time: 19.59 s +2024-11-21 21:51:39.305555: +2024-11-21 21:51:39.305770: Epoch 2007 +2024-11-21 21:51:39.305910: Current learning rate: 0.00771 +2024-11-21 21:51:58.507464: train_loss -0.765 +2024-11-21 21:51:58.518621: val_loss -0.7573 +2024-11-21 21:51:58.518759: Pseudo dice [0.8455] +2024-11-21 21:51:58.518857: Epoch time: 19.2 s +2024-11-21 21:51:59.488181: +2024-11-21 21:51:59.488397: Epoch 2008 +2024-11-21 21:51:59.488530: Current learning rate: 0.00771 +2024-11-21 21:52:18.927354: train_loss -0.7733 +2024-11-21 21:52:18.933677: val_loss -0.7473 +2024-11-21 21:52:18.933805: Pseudo dice [0.8496] +2024-11-21 21:52:18.933891: Epoch time: 19.44 s +2024-11-21 21:52:20.023698: +2024-11-21 21:52:20.023901: Epoch 2009 +2024-11-21 21:52:20.024015: Current learning rate: 0.00771 +2024-11-21 21:52:39.882205: train_loss -0.7751 +2024-11-21 21:52:39.891217: val_loss -0.7613 +2024-11-21 21:52:39.891372: Pseudo dice [0.8334] +2024-11-21 21:52:39.891471: Epoch time: 19.86 s +2024-11-21 21:52:40.908038: +2024-11-21 21:52:40.908242: Epoch 2010 +2024-11-21 21:52:40.908361: Current learning rate: 0.00771 +2024-11-21 21:52:59.982295: train_loss -0.7803 +2024-11-21 21:52:59.988173: val_loss -0.7622 +2024-11-21 21:52:59.988307: Pseudo dice [0.8479] +2024-11-21 21:52:59.988411: Epoch time: 19.08 s +2024-11-21 21:53:00.847185: +2024-11-21 21:53:00.847394: Epoch 2011 +2024-11-21 21:53:00.847514: Current learning rate: 0.00771 +2024-11-21 21:53:19.684136: train_loss -0.7633 +2024-11-21 21:53:19.690001: val_loss -0.7593 +2024-11-21 21:53:19.690154: Pseudo dice [0.8598] +2024-11-21 21:53:19.690257: Epoch time: 18.84 s +2024-11-21 21:53:20.650227: +2024-11-21 21:53:20.650433: Epoch 2012 +2024-11-21 21:53:20.650560: Current learning rate: 0.0077 +2024-11-21 21:53:38.645391: train_loss -0.7724 +2024-11-21 21:53:38.652554: val_loss -0.7486 +2024-11-21 21:53:38.652673: Pseudo dice [0.8571] +2024-11-21 21:53:38.653118: Epoch time: 18.0 s +2024-11-21 21:53:39.660332: +2024-11-21 21:53:39.660538: Epoch 2013 +2024-11-21 21:53:39.660727: Current learning rate: 0.0077 +2024-11-21 21:53:58.396086: train_loss -0.7754 +2024-11-21 21:53:58.399424: val_loss -0.77 +2024-11-21 21:53:58.399580: Pseudo dice [0.8631] +2024-11-21 21:53:58.399692: Epoch time: 18.74 s +2024-11-21 21:53:59.374957: +2024-11-21 21:53:59.375194: Epoch 2014 +2024-11-21 21:53:59.375320: Current learning rate: 0.0077 +2024-11-21 21:54:18.145923: train_loss -0.7773 +2024-11-21 21:54:18.149867: val_loss -0.7679 +2024-11-21 21:54:18.149981: Pseudo dice [0.8584] +2024-11-21 21:54:18.150078: Epoch time: 18.77 s +2024-11-21 21:54:19.109466: +2024-11-21 21:54:19.109653: Epoch 2015 +2024-11-21 21:54:19.109783: Current learning rate: 0.0077 +2024-11-21 21:54:37.988190: train_loss -0.7806 +2024-11-21 21:54:37.995684: val_loss -0.7711 +2024-11-21 21:54:37.995835: Pseudo dice [0.8387] +2024-11-21 21:54:37.996002: Epoch time: 18.88 s +2024-11-21 21:54:38.890994: +2024-11-21 21:54:38.891509: Epoch 2016 +2024-11-21 21:54:38.891646: Current learning rate: 0.0077 +2024-11-21 21:54:58.378719: train_loss -0.7624 +2024-11-21 21:54:58.387296: val_loss -0.7373 +2024-11-21 21:54:58.387465: Pseudo dice [0.8452] +2024-11-21 21:54:58.387551: Epoch time: 19.49 s +2024-11-21 21:54:59.390488: +2024-11-21 21:54:59.390719: Epoch 2017 +2024-11-21 21:54:59.390848: Current learning rate: 0.0077 +2024-11-21 21:55:19.559304: train_loss -0.7709 +2024-11-21 21:55:19.565131: val_loss -0.7621 +2024-11-21 21:55:19.565258: Pseudo dice [0.8523] +2024-11-21 21:55:19.565350: Epoch time: 20.17 s +2024-11-21 21:55:20.846268: +2024-11-21 21:55:20.846467: Epoch 2018 +2024-11-21 21:55:20.846608: Current learning rate: 0.0077 +2024-11-21 21:55:40.698722: train_loss -0.7743 +2024-11-21 21:55:40.700886: val_loss -0.7634 +2024-11-21 21:55:40.700974: Pseudo dice [0.8606] +2024-11-21 21:55:40.701062: Epoch time: 19.85 s +2024-11-21 21:55:41.536017: +2024-11-21 21:55:41.536272: Epoch 2019 +2024-11-21 21:55:41.536389: Current learning rate: 0.0077 +2024-11-21 21:56:00.876125: train_loss -0.7838 +2024-11-21 21:56:00.885202: val_loss -0.8031 +2024-11-21 21:56:00.885344: Pseudo dice [0.8584] +2024-11-21 21:56:00.885446: Epoch time: 19.34 s +2024-11-21 21:56:01.822110: +2024-11-21 21:56:01.822333: Epoch 2020 +2024-11-21 21:56:01.822450: Current learning rate: 0.0077 +2024-11-21 21:56:22.222013: train_loss -0.7727 +2024-11-21 21:56:22.232919: val_loss -0.7689 +2024-11-21 21:56:22.233086: Pseudo dice [0.8528] +2024-11-21 21:56:22.233181: Epoch time: 20.4 s +2024-11-21 21:56:23.183857: +2024-11-21 21:56:23.184089: Epoch 2021 +2024-11-21 21:56:23.184212: Current learning rate: 0.00769 +2024-11-21 21:56:41.762679: train_loss -0.7737 +2024-11-21 21:56:41.765723: val_loss -0.7621 +2024-11-21 21:56:41.765872: Pseudo dice [0.8629] +2024-11-21 21:56:41.765987: Epoch time: 18.58 s +2024-11-21 21:56:42.640678: +2024-11-21 21:56:42.640882: Epoch 2022 +2024-11-21 21:56:42.640996: Current learning rate: 0.00769 +2024-11-21 21:57:00.355351: train_loss -0.784 +2024-11-21 21:57:00.379324: val_loss -0.7688 +2024-11-21 21:57:00.379512: Pseudo dice [0.8423] +2024-11-21 21:57:00.379632: Epoch time: 17.72 s +2024-11-21 21:57:01.382693: +2024-11-21 21:57:01.382935: Epoch 2023 +2024-11-21 21:57:01.383063: Current learning rate: 0.00769 +2024-11-21 21:57:20.222490: train_loss -0.7762 +2024-11-21 21:57:20.229939: val_loss -0.7757 +2024-11-21 21:57:20.230091: Pseudo dice [0.8451] +2024-11-21 21:57:20.230179: Epoch time: 18.84 s +2024-11-21 21:57:21.214276: +2024-11-21 21:57:21.214489: Epoch 2024 +2024-11-21 21:57:21.214607: Current learning rate: 0.00769 +2024-11-21 21:57:39.359049: train_loss -0.7768 +2024-11-21 21:57:39.366109: val_loss -0.7431 +2024-11-21 21:57:39.366314: Pseudo dice [0.848] +2024-11-21 21:57:39.366416: Epoch time: 18.15 s +2024-11-21 21:57:40.334251: +2024-11-21 21:57:40.334479: Epoch 2025 +2024-11-21 21:57:40.334598: Current learning rate: 0.00769 +2024-11-21 21:57:59.522502: train_loss -0.7748 +2024-11-21 21:57:59.525093: val_loss -0.7818 +2024-11-21 21:57:59.525204: Pseudo dice [0.8444] +2024-11-21 21:57:59.525284: Epoch time: 19.19 s +2024-11-21 21:58:00.361501: +2024-11-21 21:58:00.361696: Epoch 2026 +2024-11-21 21:58:00.361830: Current learning rate: 0.00769 +2024-11-21 21:58:19.613209: train_loss -0.7737 +2024-11-21 21:58:19.621034: val_loss -0.7772 +2024-11-21 21:58:19.621162: Pseudo dice [0.8483] +2024-11-21 21:58:19.621242: Epoch time: 19.25 s +2024-11-21 21:58:20.528159: +2024-11-21 21:58:20.528597: Epoch 2027 +2024-11-21 21:58:20.528734: Current learning rate: 0.00769 +2024-11-21 21:58:39.369862: train_loss -0.7709 +2024-11-21 21:58:39.375940: val_loss -0.7604 +2024-11-21 21:58:39.376070: Pseudo dice [0.8484] +2024-11-21 21:58:39.376158: Epoch time: 18.84 s +2024-11-21 21:58:40.218413: +2024-11-21 21:58:40.218638: Epoch 2028 +2024-11-21 21:58:40.218763: Current learning rate: 0.00769 +2024-11-21 21:58:59.985309: train_loss -0.7623 +2024-11-21 21:58:59.989742: val_loss -0.7641 +2024-11-21 21:58:59.989873: Pseudo dice [0.8493] +2024-11-21 21:58:59.989983: Epoch time: 19.76 s +2024-11-21 21:59:01.328326: +2024-11-21 21:59:01.328537: Epoch 2029 +2024-11-21 21:59:01.328665: Current learning rate: 0.00769 +2024-11-21 21:59:19.030693: train_loss -0.7622 +2024-11-21 21:59:19.048071: val_loss -0.76 +2024-11-21 21:59:19.048211: Pseudo dice [0.8531] +2024-11-21 21:59:19.048370: Epoch time: 17.7 s +2024-11-21 21:59:19.959418: +2024-11-21 21:59:19.959623: Epoch 2030 +2024-11-21 21:59:19.959755: Current learning rate: 0.00768 +2024-11-21 21:59:38.258069: train_loss -0.7669 +2024-11-21 21:59:38.264159: val_loss -0.7654 +2024-11-21 21:59:38.264298: Pseudo dice [0.8466] +2024-11-21 21:59:38.264457: Epoch time: 18.3 s +2024-11-21 21:59:39.151336: +2024-11-21 21:59:39.151533: Epoch 2031 +2024-11-21 21:59:39.151648: Current learning rate: 0.00768 +2024-11-21 21:59:58.532649: train_loss -0.7616 +2024-11-21 21:59:58.540968: val_loss -0.7611 +2024-11-21 21:59:58.541121: Pseudo dice [0.8357] +2024-11-21 21:59:58.541295: Epoch time: 19.38 s +2024-11-21 21:59:59.493761: +2024-11-21 21:59:59.494005: Epoch 2032 +2024-11-21 21:59:59.494128: Current learning rate: 0.00768 +2024-11-21 22:00:19.040670: train_loss -0.7735 +2024-11-21 22:00:19.054775: val_loss -0.7539 +2024-11-21 22:00:19.054942: Pseudo dice [0.84] +2024-11-21 22:00:19.055050: Epoch time: 19.55 s +2024-11-21 22:00:20.066043: +2024-11-21 22:00:20.066309: Epoch 2033 +2024-11-21 22:00:20.066442: Current learning rate: 0.00768 +2024-11-21 22:00:39.270883: train_loss -0.7751 +2024-11-21 22:00:39.272917: val_loss -0.7662 +2024-11-21 22:00:39.273018: Pseudo dice [0.8436] +2024-11-21 22:00:39.273113: Epoch time: 19.21 s +2024-11-21 22:00:40.260006: +2024-11-21 22:00:40.260265: Epoch 2034 +2024-11-21 22:00:40.260397: Current learning rate: 0.00768 +2024-11-21 22:00:59.248510: train_loss -0.7709 +2024-11-21 22:00:59.254524: val_loss -0.7709 +2024-11-21 22:00:59.254649: Pseudo dice [0.8545] +2024-11-21 22:00:59.254745: Epoch time: 18.99 s +2024-11-21 22:01:00.196042: +2024-11-21 22:01:00.196266: Epoch 2035 +2024-11-21 22:01:00.196387: Current learning rate: 0.00768 +2024-11-21 22:01:18.545377: train_loss -0.7749 +2024-11-21 22:01:18.552992: val_loss -0.7644 +2024-11-21 22:01:18.553120: Pseudo dice [0.8392] +2024-11-21 22:01:18.553222: Epoch time: 18.35 s +2024-11-21 22:01:19.541741: +2024-11-21 22:01:19.541984: Epoch 2036 +2024-11-21 22:01:19.542131: Current learning rate: 0.00768 +2024-11-21 22:01:38.611845: train_loss -0.7767 +2024-11-21 22:01:38.635981: val_loss -0.7656 +2024-11-21 22:01:38.636139: Pseudo dice [0.8507] +2024-11-21 22:01:38.636240: Epoch time: 19.07 s +2024-11-21 22:01:39.482648: +2024-11-21 22:01:39.482886: Epoch 2037 +2024-11-21 22:01:39.482998: Current learning rate: 0.00768 +2024-11-21 22:01:57.782069: train_loss -0.7811 +2024-11-21 22:01:57.800689: val_loss -0.769 +2024-11-21 22:01:57.800867: Pseudo dice [0.8418] +2024-11-21 22:01:57.800957: Epoch time: 18.3 s +2024-11-21 22:01:58.728721: +2024-11-21 22:01:58.729131: Epoch 2038 +2024-11-21 22:01:58.729275: Current learning rate: 0.00767 +2024-11-21 22:02:16.490013: train_loss -0.7814 +2024-11-21 22:02:16.510096: val_loss -0.7568 +2024-11-21 22:02:16.510245: Pseudo dice [0.848] +2024-11-21 22:02:16.510335: Epoch time: 17.76 s +2024-11-21 22:02:17.447444: +2024-11-21 22:02:17.447663: Epoch 2039 +2024-11-21 22:02:17.447795: Current learning rate: 0.00767 +2024-11-21 22:02:36.191140: train_loss -0.7703 +2024-11-21 22:02:36.198790: val_loss -0.778 +2024-11-21 22:02:36.198943: Pseudo dice [0.8605] +2024-11-21 22:02:36.199048: Epoch time: 18.74 s +2024-11-21 22:02:37.501734: +2024-11-21 22:02:37.501944: Epoch 2040 +2024-11-21 22:02:37.502066: Current learning rate: 0.00767 +2024-11-21 22:02:55.989230: train_loss -0.7826 +2024-11-21 22:02:56.000841: val_loss -0.7536 +2024-11-21 22:02:56.001001: Pseudo dice [0.8482] +2024-11-21 22:02:56.001136: Epoch time: 18.49 s +2024-11-21 22:02:57.010911: +2024-11-21 22:02:57.011150: Epoch 2041 +2024-11-21 22:02:57.011268: Current learning rate: 0.00767 +2024-11-21 22:03:15.712829: train_loss -0.7827 +2024-11-21 22:03:15.723862: val_loss -0.7475 +2024-11-21 22:03:15.724232: Pseudo dice [0.8447] +2024-11-21 22:03:15.724333: Epoch time: 18.7 s +2024-11-21 22:03:16.565434: +2024-11-21 22:03:16.565695: Epoch 2042 +2024-11-21 22:03:16.565836: Current learning rate: 0.00767 +2024-11-21 22:03:34.622621: train_loss -0.7699 +2024-11-21 22:03:34.626594: val_loss -0.7728 +2024-11-21 22:03:34.626754: Pseudo dice [0.8576] +2024-11-21 22:03:34.626861: Epoch time: 18.06 s +2024-11-21 22:03:35.475986: +2024-11-21 22:03:35.476224: Epoch 2043 +2024-11-21 22:03:35.476343: Current learning rate: 0.00767 +2024-11-21 22:03:54.771598: train_loss -0.783 +2024-11-21 22:03:54.778861: val_loss -0.7674 +2024-11-21 22:03:54.778996: Pseudo dice [0.8535] +2024-11-21 22:03:54.779235: Epoch time: 19.3 s +2024-11-21 22:03:55.637780: +2024-11-21 22:03:55.638002: Epoch 2044 +2024-11-21 22:03:55.638126: Current learning rate: 0.00767 +2024-11-21 22:04:14.485275: train_loss -0.7584 +2024-11-21 22:04:14.487067: val_loss -0.7509 +2024-11-21 22:04:14.487222: Pseudo dice [0.8375] +2024-11-21 22:04:14.487329: Epoch time: 18.85 s +2024-11-21 22:04:15.552337: +2024-11-21 22:04:15.552587: Epoch 2045 +2024-11-21 22:04:15.552714: Current learning rate: 0.00767 +2024-11-21 22:04:34.177077: train_loss -0.7787 +2024-11-21 22:04:34.184869: val_loss -0.747 +2024-11-21 22:04:34.185015: Pseudo dice [0.8348] +2024-11-21 22:04:34.185110: Epoch time: 18.63 s +2024-11-21 22:04:35.281742: +2024-11-21 22:04:35.281951: Epoch 2046 +2024-11-21 22:04:35.282081: Current learning rate: 0.00767 +2024-11-21 22:04:54.098586: train_loss -0.7815 +2024-11-21 22:04:54.112157: val_loss -0.7489 +2024-11-21 22:04:54.112323: Pseudo dice [0.8415] +2024-11-21 22:04:54.112424: Epoch time: 18.82 s +2024-11-21 22:04:55.096494: +2024-11-21 22:04:55.096690: Epoch 2047 +2024-11-21 22:04:55.096805: Current learning rate: 0.00766 +2024-11-21 22:05:13.640053: train_loss -0.7833 +2024-11-21 22:05:13.653647: val_loss -0.7815 +2024-11-21 22:05:13.653802: Pseudo dice [0.8427] +2024-11-21 22:05:13.653898: Epoch time: 18.54 s +2024-11-21 22:05:14.511379: +2024-11-21 22:05:14.511594: Epoch 2048 +2024-11-21 22:05:14.511729: Current learning rate: 0.00766 +2024-11-21 22:05:33.198747: train_loss -0.7728 +2024-11-21 22:05:33.211997: val_loss -0.7524 +2024-11-21 22:05:33.212143: Pseudo dice [0.8303] +2024-11-21 22:05:33.212227: Epoch time: 18.69 s +2024-11-21 22:05:34.238226: +2024-11-21 22:05:34.238646: Epoch 2049 +2024-11-21 22:05:34.238800: Current learning rate: 0.00766 +2024-11-21 22:05:53.090988: train_loss -0.7678 +2024-11-21 22:05:53.098930: val_loss -0.7667 +2024-11-21 22:05:53.099083: Pseudo dice [0.85] +2024-11-21 22:05:53.099187: Epoch time: 18.85 s +2024-11-21 22:05:54.196342: +2024-11-21 22:05:54.196570: Epoch 2050 +2024-11-21 22:05:54.196700: Current learning rate: 0.00766 +2024-11-21 22:06:12.000627: train_loss -0.77 +2024-11-21 22:06:12.006772: val_loss -0.7628 +2024-11-21 22:06:12.006917: Pseudo dice [0.8474] +2024-11-21 22:06:12.007014: Epoch time: 17.81 s +2024-11-21 22:06:13.216030: +2024-11-21 22:06:13.216326: Epoch 2051 +2024-11-21 22:06:13.216455: Current learning rate: 0.00766 +2024-11-21 22:06:31.677302: train_loss -0.7751 +2024-11-21 22:06:31.684852: val_loss -0.7591 +2024-11-21 22:06:31.684987: Pseudo dice [0.8459] +2024-11-21 22:06:31.685079: Epoch time: 18.46 s +2024-11-21 22:06:32.535645: +2024-11-21 22:06:32.535911: Epoch 2052 +2024-11-21 22:06:32.536046: Current learning rate: 0.00766 +2024-11-21 22:06:51.912793: train_loss -0.7649 +2024-11-21 22:06:51.916452: val_loss -0.7576 +2024-11-21 22:06:51.916574: Pseudo dice [0.8465] +2024-11-21 22:06:51.916681: Epoch time: 19.38 s +2024-11-21 22:06:52.728238: +2024-11-21 22:06:52.728458: Epoch 2053 +2024-11-21 22:06:52.728573: Current learning rate: 0.00766 +2024-11-21 22:07:11.216174: train_loss -0.7729 +2024-11-21 22:07:11.222818: val_loss -0.7702 +2024-11-21 22:07:11.222948: Pseudo dice [0.848] +2024-11-21 22:07:11.223052: Epoch time: 18.49 s +2024-11-21 22:07:12.222750: +2024-11-21 22:07:12.222971: Epoch 2054 +2024-11-21 22:07:12.223094: Current learning rate: 0.00766 +2024-11-21 22:07:31.978340: train_loss -0.7798 +2024-11-21 22:07:31.985949: val_loss -0.7438 +2024-11-21 22:07:31.986107: Pseudo dice [0.8615] +2024-11-21 22:07:31.986217: Epoch time: 19.76 s +2024-11-21 22:07:32.800750: +2024-11-21 22:07:32.800996: Epoch 2055 +2024-11-21 22:07:32.801130: Current learning rate: 0.00766 +2024-11-21 22:07:52.113291: train_loss -0.7761 +2024-11-21 22:07:52.119822: val_loss -0.7628 +2024-11-21 22:07:52.120227: Pseudo dice [0.8355] +2024-11-21 22:07:52.120327: Epoch time: 19.31 s +2024-11-21 22:07:52.978338: +2024-11-21 22:07:52.978546: Epoch 2056 +2024-11-21 22:07:52.978671: Current learning rate: 0.00765 +2024-11-21 22:08:11.082143: train_loss -0.7291 +2024-11-21 22:08:11.110958: val_loss -0.7529 +2024-11-21 22:08:11.111107: Pseudo dice [0.8292] +2024-11-21 22:08:11.111213: Epoch time: 18.1 s +2024-11-21 22:08:12.112432: +2024-11-21 22:08:12.112620: Epoch 2057 +2024-11-21 22:08:12.112740: Current learning rate: 0.00765 +2024-11-21 22:08:30.521717: train_loss -0.747 +2024-11-21 22:08:30.533911: val_loss -0.7467 +2024-11-21 22:08:30.534043: Pseudo dice [0.8441] +2024-11-21 22:08:30.534151: Epoch time: 18.41 s +2024-11-21 22:08:31.393504: +2024-11-21 22:08:31.393714: Epoch 2058 +2024-11-21 22:08:31.393830: Current learning rate: 0.00765 +2024-11-21 22:08:50.609568: train_loss -0.7629 +2024-11-21 22:08:50.614716: val_loss -0.737 +2024-11-21 22:08:50.614873: Pseudo dice [0.8436] +2024-11-21 22:08:50.614964: Epoch time: 19.22 s +2024-11-21 22:08:51.461558: +2024-11-21 22:08:51.461817: Epoch 2059 +2024-11-21 22:08:51.461933: Current learning rate: 0.00765 +2024-11-21 22:09:10.645590: train_loss -0.7718 +2024-11-21 22:09:10.671113: val_loss -0.7465 +2024-11-21 22:09:10.671297: Pseudo dice [0.8452] +2024-11-21 22:09:10.671414: Epoch time: 19.18 s +2024-11-21 22:09:11.587032: +2024-11-21 22:09:11.587463: Epoch 2060 +2024-11-21 22:09:11.587599: Current learning rate: 0.00765 +2024-11-21 22:09:29.704618: train_loss -0.7709 +2024-11-21 22:09:29.707201: val_loss -0.7748 +2024-11-21 22:09:29.707304: Pseudo dice [0.8517] +2024-11-21 22:09:29.707412: Epoch time: 18.12 s +2024-11-21 22:09:30.516837: +2024-11-21 22:09:30.517104: Epoch 2061 +2024-11-21 22:09:30.517230: Current learning rate: 0.00765 +2024-11-21 22:09:49.742097: train_loss -0.7789 +2024-11-21 22:09:49.745415: val_loss -0.7619 +2024-11-21 22:09:49.745567: Pseudo dice [0.8477] +2024-11-21 22:09:49.745677: Epoch time: 19.23 s +2024-11-21 22:09:50.557436: +2024-11-21 22:09:50.557664: Epoch 2062 +2024-11-21 22:09:50.557782: Current learning rate: 0.00765 +2024-11-21 22:10:09.341740: train_loss -0.7721 +2024-11-21 22:10:09.344579: val_loss -0.7604 +2024-11-21 22:10:09.344711: Pseudo dice [0.8518] +2024-11-21 22:10:09.344803: Epoch time: 18.79 s +2024-11-21 22:10:10.602251: +2024-11-21 22:10:10.602475: Epoch 2063 +2024-11-21 22:10:10.602602: Current learning rate: 0.00765 +2024-11-21 22:10:29.429324: train_loss -0.7687 +2024-11-21 22:10:29.436325: val_loss -0.7416 +2024-11-21 22:10:29.436479: Pseudo dice [0.8354] +2024-11-21 22:10:29.436589: Epoch time: 18.83 s +2024-11-21 22:10:30.312423: +2024-11-21 22:10:30.312642: Epoch 2064 +2024-11-21 22:10:30.312763: Current learning rate: 0.00764 +2024-11-21 22:10:48.689409: train_loss -0.762 +2024-11-21 22:10:48.694619: val_loss -0.7627 +2024-11-21 22:10:48.694772: Pseudo dice [0.8402] +2024-11-21 22:10:48.694880: Epoch time: 18.38 s +2024-11-21 22:10:49.755148: +2024-11-21 22:10:49.755407: Epoch 2065 +2024-11-21 22:10:49.755571: Current learning rate: 0.00764 +2024-11-21 22:11:08.625980: train_loss -0.768 +2024-11-21 22:11:08.632019: val_loss -0.7593 +2024-11-21 22:11:08.632143: Pseudo dice [0.8288] +2024-11-21 22:11:08.632249: Epoch time: 18.87 s +2024-11-21 22:11:09.639254: +2024-11-21 22:11:09.639496: Epoch 2066 +2024-11-21 22:11:09.639624: Current learning rate: 0.00764 +2024-11-21 22:11:29.480730: train_loss -0.7788 +2024-11-21 22:11:29.483299: val_loss -0.7446 +2024-11-21 22:11:29.483410: Pseudo dice [0.8411] +2024-11-21 22:11:29.483496: Epoch time: 19.84 s +2024-11-21 22:11:30.293536: +2024-11-21 22:11:30.294001: Epoch 2067 +2024-11-21 22:11:30.294139: Current learning rate: 0.00764 +2024-11-21 22:11:49.517265: train_loss -0.7709 +2024-11-21 22:11:49.525601: val_loss -0.7597 +2024-11-21 22:11:49.525739: Pseudo dice [0.8545] +2024-11-21 22:11:49.525836: Epoch time: 19.22 s +2024-11-21 22:11:50.356791: +2024-11-21 22:11:50.357043: Epoch 2068 +2024-11-21 22:11:50.357158: Current learning rate: 0.00764 +2024-11-21 22:12:09.953811: train_loss -0.7501 +2024-11-21 22:12:09.963754: val_loss -0.7649 +2024-11-21 22:12:09.963884: Pseudo dice [0.8307] +2024-11-21 22:12:09.963987: Epoch time: 19.6 s +2024-11-21 22:12:10.799649: +2024-11-21 22:12:10.799847: Epoch 2069 +2024-11-21 22:12:10.799990: Current learning rate: 0.00764 +2024-11-21 22:12:31.347142: train_loss -0.7599 +2024-11-21 22:12:31.355458: val_loss -0.7597 +2024-11-21 22:12:31.355639: Pseudo dice [0.8454] +2024-11-21 22:12:31.355738: Epoch time: 20.55 s +2024-11-21 22:12:32.274726: +2024-11-21 22:12:32.274987: Epoch 2070 +2024-11-21 22:12:32.275112: Current learning rate: 0.00764 +2024-11-21 22:12:51.975178: train_loss -0.7738 +2024-11-21 22:12:51.997149: val_loss -0.7631 +2024-11-21 22:12:51.997320: Pseudo dice [0.8485] +2024-11-21 22:12:51.997406: Epoch time: 19.7 s +2024-11-21 22:12:52.842350: +2024-11-21 22:12:52.842569: Epoch 2071 +2024-11-21 22:12:52.842715: Current learning rate: 0.00764 +2024-11-21 22:13:11.737335: train_loss -0.7738 +2024-11-21 22:13:11.744730: val_loss -0.7518 +2024-11-21 22:13:11.744883: Pseudo dice [0.853] +2024-11-21 22:13:11.744972: Epoch time: 18.9 s +2024-11-21 22:13:12.592050: +2024-11-21 22:13:12.592265: Epoch 2072 +2024-11-21 22:13:12.592381: Current learning rate: 0.00764 +2024-11-21 22:13:32.830164: train_loss -0.7666 +2024-11-21 22:13:32.836876: val_loss -0.7396 +2024-11-21 22:13:32.837017: Pseudo dice [0.8299] +2024-11-21 22:13:32.837121: Epoch time: 20.24 s +2024-11-21 22:13:33.676963: +2024-11-21 22:13:33.677157: Epoch 2073 +2024-11-21 22:13:33.677299: Current learning rate: 0.00763 +2024-11-21 22:13:51.856442: train_loss -0.7645 +2024-11-21 22:13:51.870159: val_loss -0.7598 +2024-11-21 22:13:51.870291: Pseudo dice [0.8475] +2024-11-21 22:13:51.870384: Epoch time: 18.18 s +2024-11-21 22:13:52.755712: +2024-11-21 22:13:52.755918: Epoch 2074 +2024-11-21 22:13:52.760409: Current learning rate: 0.00763 +2024-11-21 22:14:11.431479: train_loss -0.7557 +2024-11-21 22:14:11.443788: val_loss -0.7167 +2024-11-21 22:14:11.443952: Pseudo dice [0.8279] +2024-11-21 22:14:11.444045: Epoch time: 18.68 s +2024-11-21 22:14:12.334493: +2024-11-21 22:14:12.334695: Epoch 2075 +2024-11-21 22:14:12.334811: Current learning rate: 0.00763 +2024-11-21 22:14:30.562263: train_loss -0.7657 +2024-11-21 22:14:30.570394: val_loss -0.7696 +2024-11-21 22:14:30.579918: Pseudo dice [0.8405] +2024-11-21 22:14:30.580037: Epoch time: 18.23 s +2024-11-21 22:14:31.415197: +2024-11-21 22:14:31.415417: Epoch 2076 +2024-11-21 22:14:31.415543: Current learning rate: 0.00763 +2024-11-21 22:14:49.479262: train_loss -0.7699 +2024-11-21 22:14:49.486442: val_loss -0.7561 +2024-11-21 22:14:49.486586: Pseudo dice [0.8153] +2024-11-21 22:14:49.486676: Epoch time: 18.06 s +2024-11-21 22:14:50.336111: +2024-11-21 22:14:50.336332: Epoch 2077 +2024-11-21 22:14:50.336465: Current learning rate: 0.00763 +2024-11-21 22:15:09.590211: train_loss -0.7792 +2024-11-21 22:15:09.596764: val_loss -0.7763 +2024-11-21 22:15:09.596897: Pseudo dice [0.8488] +2024-11-21 22:15:09.596983: Epoch time: 19.25 s +2024-11-21 22:15:10.433297: +2024-11-21 22:15:10.433501: Epoch 2078 +2024-11-21 22:15:10.433645: Current learning rate: 0.00763 +2024-11-21 22:15:28.449759: train_loss -0.7778 +2024-11-21 22:15:28.484124: val_loss -0.7582 +2024-11-21 22:15:28.484309: Pseudo dice [0.8507] +2024-11-21 22:15:28.484413: Epoch time: 18.02 s +2024-11-21 22:15:29.495125: +2024-11-21 22:15:29.495335: Epoch 2079 +2024-11-21 22:15:29.495479: Current learning rate: 0.00763 +2024-11-21 22:15:48.154247: train_loss -0.7659 +2024-11-21 22:15:48.175231: val_loss -0.7764 +2024-11-21 22:15:48.175371: Pseudo dice [0.8537] +2024-11-21 22:15:48.175787: Epoch time: 18.66 s +2024-11-21 22:15:49.051521: +2024-11-21 22:15:49.051723: Epoch 2080 +2024-11-21 22:15:49.051858: Current learning rate: 0.00763 +2024-11-21 22:16:08.845213: train_loss -0.7754 +2024-11-21 22:16:08.852698: val_loss -0.7787 +2024-11-21 22:16:08.852839: Pseudo dice [0.8522] +2024-11-21 22:16:08.852939: Epoch time: 19.79 s +2024-11-21 22:16:09.727717: +2024-11-21 22:16:09.727916: Epoch 2081 +2024-11-21 22:16:09.728028: Current learning rate: 0.00763 +2024-11-21 22:16:28.815320: train_loss -0.7695 +2024-11-21 22:16:28.841376: val_loss -0.7578 +2024-11-21 22:16:28.841770: Pseudo dice [0.8475] +2024-11-21 22:16:28.841875: Epoch time: 19.09 s +2024-11-21 22:16:29.681705: +2024-11-21 22:16:29.681908: Epoch 2082 +2024-11-21 22:16:29.682021: Current learning rate: 0.00762 +2024-11-21 22:16:48.328158: train_loss -0.7752 +2024-11-21 22:16:48.360452: val_loss -0.7581 +2024-11-21 22:16:48.360614: Pseudo dice [0.8421] +2024-11-21 22:16:48.360709: Epoch time: 18.64 s +2024-11-21 22:16:49.199739: +2024-11-21 22:16:49.199942: Epoch 2083 +2024-11-21 22:16:49.200071: Current learning rate: 0.00762 +2024-11-21 22:17:07.985656: train_loss -0.7722 +2024-11-21 22:17:08.004578: val_loss -0.7634 +2024-11-21 22:17:08.004752: Pseudo dice [0.8502] +2024-11-21 22:17:08.004856: Epoch time: 18.79 s +2024-11-21 22:17:08.841888: +2024-11-21 22:17:08.842131: Epoch 2084 +2024-11-21 22:17:08.842307: Current learning rate: 0.00762 +2024-11-21 22:17:28.144935: train_loss -0.7779 +2024-11-21 22:17:28.148820: val_loss -0.7656 +2024-11-21 22:17:28.148967: Pseudo dice [0.8468] +2024-11-21 22:17:28.149079: Epoch time: 19.3 s +2024-11-21 22:17:29.136926: +2024-11-21 22:17:29.137119: Epoch 2085 +2024-11-21 22:17:29.137228: Current learning rate: 0.00762 +2024-11-21 22:17:48.754774: train_loss -0.773 +2024-11-21 22:17:48.800872: val_loss -0.753 +2024-11-21 22:17:48.801064: Pseudo dice [0.8519] +2024-11-21 22:17:48.801156: Epoch time: 19.62 s +2024-11-21 22:17:50.034145: +2024-11-21 22:17:50.034353: Epoch 2086 +2024-11-21 22:17:50.034469: Current learning rate: 0.00762 +2024-11-21 22:18:09.216326: train_loss -0.7698 +2024-11-21 22:18:09.225198: val_loss -0.7725 +2024-11-21 22:18:09.225332: Pseudo dice [0.8574] +2024-11-21 22:18:09.225428: Epoch time: 19.18 s +2024-11-21 22:18:10.061927: +2024-11-21 22:18:10.062137: Epoch 2087 +2024-11-21 22:18:10.062253: Current learning rate: 0.00762 +2024-11-21 22:18:29.401040: train_loss -0.766 +2024-11-21 22:18:29.403804: val_loss -0.719 +2024-11-21 22:18:29.403912: Pseudo dice [0.8477] +2024-11-21 22:18:29.404024: Epoch time: 19.34 s +2024-11-21 22:18:30.217220: +2024-11-21 22:18:30.217428: Epoch 2088 +2024-11-21 22:18:30.217559: Current learning rate: 0.00762 +2024-11-21 22:18:49.503235: train_loss -0.7729 +2024-11-21 22:18:49.506101: val_loss -0.7662 +2024-11-21 22:18:49.506198: Pseudo dice [0.8405] +2024-11-21 22:18:49.506283: Epoch time: 19.29 s +2024-11-21 22:18:50.324637: +2024-11-21 22:18:50.324859: Epoch 2089 +2024-11-21 22:18:50.324981: Current learning rate: 0.00762 +2024-11-21 22:19:09.789629: train_loss -0.7771 +2024-11-21 22:19:09.795397: val_loss -0.7689 +2024-11-21 22:19:09.795551: Pseudo dice [0.8489] +2024-11-21 22:19:09.795659: Epoch time: 19.47 s +2024-11-21 22:19:10.723178: +2024-11-21 22:19:10.723395: Epoch 2090 +2024-11-21 22:19:10.723522: Current learning rate: 0.00761 +2024-11-21 22:19:28.719259: train_loss -0.7793 +2024-11-21 22:19:28.725323: val_loss -0.7533 +2024-11-21 22:19:28.725471: Pseudo dice [0.8494] +2024-11-21 22:19:28.725574: Epoch time: 18.0 s +2024-11-21 22:19:29.642885: +2024-11-21 22:19:29.643107: Epoch 2091 +2024-11-21 22:19:29.643234: Current learning rate: 0.00761 +2024-11-21 22:19:48.858231: train_loss -0.7805 +2024-11-21 22:19:48.864622: val_loss -0.7621 +2024-11-21 22:19:48.864754: Pseudo dice [0.8554] +2024-11-21 22:19:48.864862: Epoch time: 19.22 s +2024-11-21 22:19:49.698802: +2024-11-21 22:19:49.699018: Epoch 2092 +2024-11-21 22:19:49.699142: Current learning rate: 0.00761 +2024-11-21 22:20:09.018741: train_loss -0.7865 +2024-11-21 22:20:09.034403: val_loss -0.7597 +2024-11-21 22:20:09.034571: Pseudo dice [0.8454] +2024-11-21 22:20:09.034676: Epoch time: 19.32 s +2024-11-21 22:20:09.853463: +2024-11-21 22:20:09.853654: Epoch 2093 +2024-11-21 22:20:09.853764: Current learning rate: 0.00761 +2024-11-21 22:20:29.020023: train_loss -0.7804 +2024-11-21 22:20:29.026602: val_loss -0.771 +2024-11-21 22:20:29.026721: Pseudo dice [0.8595] +2024-11-21 22:20:29.026826: Epoch time: 19.17 s +2024-11-21 22:20:29.883537: +2024-11-21 22:20:29.883780: Epoch 2094 +2024-11-21 22:20:29.883897: Current learning rate: 0.00761 +2024-11-21 22:20:48.558529: train_loss -0.7857 +2024-11-21 22:20:48.564628: val_loss -0.7728 +2024-11-21 22:20:48.564771: Pseudo dice [0.8528] +2024-11-21 22:20:48.564854: Epoch time: 18.68 s +2024-11-21 22:20:49.388857: +2024-11-21 22:20:49.389052: Epoch 2095 +2024-11-21 22:20:49.389174: Current learning rate: 0.00761 +2024-11-21 22:21:07.763767: train_loss -0.771 +2024-11-21 22:21:07.769773: val_loss -0.7654 +2024-11-21 22:21:07.769911: Pseudo dice [0.8427] +2024-11-21 22:21:07.770017: Epoch time: 18.38 s +2024-11-21 22:21:08.628724: +2024-11-21 22:21:08.628937: Epoch 2096 +2024-11-21 22:21:08.629054: Current learning rate: 0.00761 +2024-11-21 22:21:28.837198: train_loss -0.7781 +2024-11-21 22:21:28.847286: val_loss -0.7655 +2024-11-21 22:21:28.847435: Pseudo dice [0.8416] +2024-11-21 22:21:28.847548: Epoch time: 20.21 s +2024-11-21 22:21:29.771467: +2024-11-21 22:21:29.771667: Epoch 2097 +2024-11-21 22:21:29.771777: Current learning rate: 0.00761 +2024-11-21 22:21:49.495108: train_loss -0.7732 +2024-11-21 22:21:49.500495: val_loss -0.7692 +2024-11-21 22:21:49.500629: Pseudo dice [0.8559] +2024-11-21 22:21:49.500740: Epoch time: 19.72 s +2024-11-21 22:21:50.334923: +2024-11-21 22:21:50.335130: Epoch 2098 +2024-11-21 22:21:50.335263: Current learning rate: 0.00761 +2024-11-21 22:22:09.161637: train_loss -0.7795 +2024-11-21 22:22:09.184594: val_loss -0.7619 +2024-11-21 22:22:09.184733: Pseudo dice [0.8567] +2024-11-21 22:22:09.184835: Epoch time: 18.83 s +2024-11-21 22:22:10.083863: +2024-11-21 22:22:10.084085: Epoch 2099 +2024-11-21 22:22:10.084214: Current learning rate: 0.0076 +2024-11-21 22:22:28.604303: train_loss -0.7733 +2024-11-21 22:22:28.612922: val_loss -0.7531 +2024-11-21 22:22:28.613154: Pseudo dice [0.854] +2024-11-21 22:22:28.613261: Epoch time: 18.52 s +2024-11-21 22:22:29.786461: +2024-11-21 22:22:29.786664: Epoch 2100 +2024-11-21 22:22:29.786803: Current learning rate: 0.0076 +2024-11-21 22:22:49.803880: train_loss -0.7757 +2024-11-21 22:22:49.811129: val_loss -0.7693 +2024-11-21 22:22:49.811268: Pseudo dice [0.8535] +2024-11-21 22:22:49.811364: Epoch time: 20.02 s +2024-11-21 22:22:50.638350: +2024-11-21 22:22:50.638568: Epoch 2101 +2024-11-21 22:22:50.638689: Current learning rate: 0.0076 +2024-11-21 22:23:08.505283: train_loss -0.7818 +2024-11-21 22:23:08.514354: val_loss -0.7536 +2024-11-21 22:23:08.514482: Pseudo dice [0.855] +2024-11-21 22:23:08.514591: Epoch time: 17.87 s +2024-11-21 22:23:09.675433: +2024-11-21 22:23:09.675638: Epoch 2102 +2024-11-21 22:23:09.675765: Current learning rate: 0.0076 +2024-11-21 22:23:29.186959: train_loss -0.7749 +2024-11-21 22:23:29.193252: val_loss -0.7655 +2024-11-21 22:23:29.193392: Pseudo dice [0.8493] +2024-11-21 22:23:29.193498: Epoch time: 19.51 s +2024-11-21 22:23:30.009408: +2024-11-21 22:23:30.009623: Epoch 2103 +2024-11-21 22:23:30.009733: Current learning rate: 0.0076 +2024-11-21 22:23:50.383929: train_loss -0.7769 +2024-11-21 22:23:50.402222: val_loss -0.7702 +2024-11-21 22:23:50.402380: Pseudo dice [0.8533] +2024-11-21 22:23:50.402477: Epoch time: 20.38 s +2024-11-21 22:23:51.303250: +2024-11-21 22:23:51.303495: Epoch 2104 +2024-11-21 22:23:51.303617: Current learning rate: 0.0076 +2024-11-21 22:24:10.366398: train_loss -0.774 +2024-11-21 22:24:10.375973: val_loss -0.7671 +2024-11-21 22:24:10.376149: Pseudo dice [0.8401] +2024-11-21 22:24:10.376260: Epoch time: 19.06 s +2024-11-21 22:24:11.265115: +2024-11-21 22:24:11.265300: Epoch 2105 +2024-11-21 22:24:11.289673: Current learning rate: 0.0076 +2024-11-21 22:24:29.712419: train_loss -0.7707 +2024-11-21 22:24:29.714984: val_loss -0.7584 +2024-11-21 22:24:29.715127: Pseudo dice [0.8519] +2024-11-21 22:24:29.715217: Epoch time: 18.45 s +2024-11-21 22:24:30.527649: +2024-11-21 22:24:30.527862: Epoch 2106 +2024-11-21 22:24:30.527984: Current learning rate: 0.0076 +2024-11-21 22:24:49.215270: train_loss -0.7681 +2024-11-21 22:24:49.220450: val_loss -0.7589 +2024-11-21 22:24:49.220590: Pseudo dice [0.8379] +2024-11-21 22:24:49.220683: Epoch time: 18.69 s +2024-11-21 22:24:50.109220: +2024-11-21 22:24:50.109439: Epoch 2107 +2024-11-21 22:24:50.109568: Current learning rate: 0.00759 +2024-11-21 22:25:08.691527: train_loss -0.7502 +2024-11-21 22:25:08.697243: val_loss -0.7763 +2024-11-21 22:25:08.697404: Pseudo dice [0.8385] +2024-11-21 22:25:08.697505: Epoch time: 18.58 s +2024-11-21 22:25:09.599583: +2024-11-21 22:25:09.599789: Epoch 2108 +2024-11-21 22:25:09.599940: Current learning rate: 0.00759 +2024-11-21 22:25:27.675682: train_loss -0.7554 +2024-11-21 22:25:27.680991: val_loss -0.7467 +2024-11-21 22:25:27.681125: Pseudo dice [0.8451] +2024-11-21 22:25:27.681245: Epoch time: 18.08 s +2024-11-21 22:25:28.886895: +2024-11-21 22:25:28.887118: Epoch 2109 +2024-11-21 22:25:28.887243: Current learning rate: 0.00759 +2024-11-21 22:25:48.350675: train_loss -0.7589 +2024-11-21 22:25:48.353918: val_loss -0.7586 +2024-11-21 22:25:48.354036: Pseudo dice [0.8328] +2024-11-21 22:25:48.354130: Epoch time: 19.46 s +2024-11-21 22:25:49.456775: +2024-11-21 22:25:49.457009: Epoch 2110 +2024-11-21 22:25:49.457142: Current learning rate: 0.00759 +2024-11-21 22:26:07.982000: train_loss -0.761 +2024-11-21 22:26:07.987974: val_loss -0.7437 +2024-11-21 22:26:07.988119: Pseudo dice [0.8286] +2024-11-21 22:26:07.988215: Epoch time: 18.53 s +2024-11-21 22:26:08.807315: +2024-11-21 22:26:08.807619: Epoch 2111 +2024-11-21 22:26:08.807745: Current learning rate: 0.00759 +2024-11-21 22:26:26.925569: train_loss -0.7686 +2024-11-21 22:26:26.932526: val_loss -0.7573 +2024-11-21 22:26:26.932652: Pseudo dice [0.8436] +2024-11-21 22:26:26.932756: Epoch time: 18.12 s +2024-11-21 22:26:27.944841: +2024-11-21 22:26:27.945079: Epoch 2112 +2024-11-21 22:26:27.945194: Current learning rate: 0.00759 +2024-11-21 22:26:46.619194: train_loss -0.7717 +2024-11-21 22:26:46.626314: val_loss -0.7846 +2024-11-21 22:26:46.626483: Pseudo dice [0.8512] +2024-11-21 22:26:46.626576: Epoch time: 18.68 s +2024-11-21 22:26:47.472220: +2024-11-21 22:26:47.472671: Epoch 2113 +2024-11-21 22:26:47.472792: Current learning rate: 0.00759 +2024-11-21 22:27:07.010561: train_loss -0.7817 +2024-11-21 22:27:07.018116: val_loss -0.7649 +2024-11-21 22:27:07.018243: Pseudo dice [0.8481] +2024-11-21 22:27:07.018351: Epoch time: 19.54 s +2024-11-21 22:27:07.975394: +2024-11-21 22:27:07.975596: Epoch 2114 +2024-11-21 22:27:07.975714: Current learning rate: 0.00759 +2024-11-21 22:27:26.279392: train_loss -0.7695 +2024-11-21 22:27:26.288564: val_loss -0.7688 +2024-11-21 22:27:26.288706: Pseudo dice [0.8526] +2024-11-21 22:27:26.288813: Epoch time: 18.3 s +2024-11-21 22:27:27.151503: +2024-11-21 22:27:27.151690: Epoch 2115 +2024-11-21 22:27:27.151814: Current learning rate: 0.00759 +2024-11-21 22:27:46.277586: train_loss -0.7713 +2024-11-21 22:27:46.284448: val_loss -0.7811 +2024-11-21 22:27:46.284600: Pseudo dice [0.8582] +2024-11-21 22:27:46.284692: Epoch time: 19.13 s +2024-11-21 22:27:47.102943: +2024-11-21 22:27:47.103150: Epoch 2116 +2024-11-21 22:27:47.103285: Current learning rate: 0.00758 +2024-11-21 22:28:06.685952: train_loss -0.7583 +2024-11-21 22:28:06.691776: val_loss -0.7848 +2024-11-21 22:28:06.691937: Pseudo dice [0.8583] +2024-11-21 22:28:06.692039: Epoch time: 19.58 s +2024-11-21 22:28:07.643796: +2024-11-21 22:28:07.643987: Epoch 2117 +2024-11-21 22:28:07.644104: Current learning rate: 0.00758 +2024-11-21 22:28:26.712014: train_loss -0.7786 +2024-11-21 22:28:26.717388: val_loss -0.7508 +2024-11-21 22:28:26.717504: Pseudo dice [0.8458] +2024-11-21 22:28:26.717607: Epoch time: 19.07 s +2024-11-21 22:28:27.603978: +2024-11-21 22:28:27.604206: Epoch 2118 +2024-11-21 22:28:27.604335: Current learning rate: 0.00758 +2024-11-21 22:28:46.172800: train_loss -0.7674 +2024-11-21 22:28:46.178492: val_loss -0.7581 +2024-11-21 22:28:46.178627: Pseudo dice [0.8487] +2024-11-21 22:28:46.178727: Epoch time: 18.57 s +2024-11-21 22:28:46.994584: +2024-11-21 22:28:46.994791: Epoch 2119 +2024-11-21 22:28:46.994917: Current learning rate: 0.00758 +2024-11-21 22:29:06.878406: train_loss -0.7649 +2024-11-21 22:29:06.883938: val_loss -0.7528 +2024-11-21 22:29:06.884076: Pseudo dice [0.8338] +2024-11-21 22:29:06.884179: Epoch time: 19.88 s +2024-11-21 22:29:07.723591: +2024-11-21 22:29:07.723780: Epoch 2120 +2024-11-21 22:29:07.723908: Current learning rate: 0.00758 +2024-11-21 22:29:26.333235: train_loss -0.7795 +2024-11-21 22:29:26.339128: val_loss -0.7732 +2024-11-21 22:29:26.339279: Pseudo dice [0.8572] +2024-11-21 22:29:26.339368: Epoch time: 18.61 s +2024-11-21 22:29:27.147578: +2024-11-21 22:29:27.147780: Epoch 2121 +2024-11-21 22:29:27.147892: Current learning rate: 0.00758 +2024-11-21 22:29:45.643103: train_loss -0.7669 +2024-11-21 22:29:45.649838: val_loss -0.7558 +2024-11-21 22:29:45.649994: Pseudo dice [0.8524] +2024-11-21 22:29:45.650102: Epoch time: 18.5 s +2024-11-21 22:29:46.472805: +2024-11-21 22:29:46.473039: Epoch 2122 +2024-11-21 22:29:46.473167: Current learning rate: 0.00758 +2024-11-21 22:30:06.485762: train_loss -0.7778 +2024-11-21 22:30:06.493888: val_loss -0.7628 +2024-11-21 22:30:06.494031: Pseudo dice [0.8426] +2024-11-21 22:30:06.494151: Epoch time: 20.01 s +2024-11-21 22:30:07.323545: +2024-11-21 22:30:07.323743: Epoch 2123 +2024-11-21 22:30:07.323859: Current learning rate: 0.00758 +2024-11-21 22:30:27.059537: train_loss -0.7761 +2024-11-21 22:30:27.062112: val_loss -0.762 +2024-11-21 22:30:27.062262: Pseudo dice [0.8422] +2024-11-21 22:30:27.062351: Epoch time: 19.74 s +2024-11-21 22:30:28.050843: +2024-11-21 22:30:28.051064: Epoch 2124 +2024-11-21 22:30:28.051190: Current learning rate: 0.00758 +2024-11-21 22:30:47.602629: train_loss -0.7672 +2024-11-21 22:30:47.610120: val_loss -0.7816 +2024-11-21 22:30:47.610243: Pseudo dice [0.8467] +2024-11-21 22:30:47.610335: Epoch time: 19.55 s +2024-11-21 22:30:48.423830: +2024-11-21 22:30:48.424037: Epoch 2125 +2024-11-21 22:30:48.424152: Current learning rate: 0.00757 +2024-11-21 22:31:08.350537: train_loss -0.7661 +2024-11-21 22:31:08.356912: val_loss -0.7609 +2024-11-21 22:31:08.357033: Pseudo dice [0.844] +2024-11-21 22:31:08.357136: Epoch time: 19.93 s +2024-11-21 22:31:09.169277: +2024-11-21 22:31:09.169473: Epoch 2126 +2024-11-21 22:31:09.169595: Current learning rate: 0.00757 +2024-11-21 22:31:27.050802: train_loss -0.7622 +2024-11-21 22:31:27.056245: val_loss -0.7407 +2024-11-21 22:31:27.056358: Pseudo dice [0.8346] +2024-11-21 22:31:27.056450: Epoch time: 17.88 s +2024-11-21 22:31:27.877935: +2024-11-21 22:31:27.878197: Epoch 2127 +2024-11-21 22:31:27.878334: Current learning rate: 0.00757 +2024-11-21 22:31:48.278831: train_loss -0.752 +2024-11-21 22:31:48.298864: val_loss -0.7633 +2024-11-21 22:31:48.299021: Pseudo dice [0.8502] +2024-11-21 22:31:48.299126: Epoch time: 20.4 s +2024-11-21 22:31:49.141723: +2024-11-21 22:31:49.141920: Epoch 2128 +2024-11-21 22:31:49.142041: Current learning rate: 0.00757 +2024-11-21 22:32:07.537707: train_loss -0.7702 +2024-11-21 22:32:07.541423: val_loss -0.7487 +2024-11-21 22:32:07.541558: Pseudo dice [0.8458] +2024-11-21 22:32:07.541651: Epoch time: 18.4 s +2024-11-21 22:32:08.353485: +2024-11-21 22:32:08.353761: Epoch 2129 +2024-11-21 22:32:08.353878: Current learning rate: 0.00757 +2024-11-21 22:32:27.810834: train_loss -0.7815 +2024-11-21 22:32:27.822823: val_loss -0.7692 +2024-11-21 22:32:27.822989: Pseudo dice [0.8527] +2024-11-21 22:32:27.823129: Epoch time: 19.46 s +2024-11-21 22:32:28.639193: +2024-11-21 22:32:28.639432: Epoch 2130 +2024-11-21 22:32:28.639560: Current learning rate: 0.00757 +2024-11-21 22:32:47.252214: train_loss -0.7783 +2024-11-21 22:32:47.257555: val_loss -0.7597 +2024-11-21 22:32:47.258003: Pseudo dice [0.8449] +2024-11-21 22:32:47.258214: Epoch time: 18.61 s +2024-11-21 22:32:48.080304: +2024-11-21 22:32:48.080522: Epoch 2131 +2024-11-21 22:32:48.080663: Current learning rate: 0.00757 +2024-11-21 22:33:06.719167: train_loss -0.7758 +2024-11-21 22:33:06.726007: val_loss -0.7616 +2024-11-21 22:33:06.726151: Pseudo dice [0.8382] +2024-11-21 22:33:06.726261: Epoch time: 18.64 s +2024-11-21 22:33:08.012550: +2024-11-21 22:33:08.012756: Epoch 2132 +2024-11-21 22:33:08.012869: Current learning rate: 0.00757 +2024-11-21 22:33:25.660458: train_loss -0.7713 +2024-11-21 22:33:25.662161: val_loss -0.7541 +2024-11-21 22:33:25.662255: Pseudo dice [0.8406] +2024-11-21 22:33:25.662354: Epoch time: 17.65 s +2024-11-21 22:33:26.474835: +2024-11-21 22:33:26.475062: Epoch 2133 +2024-11-21 22:33:26.475178: Current learning rate: 0.00756 +2024-11-21 22:33:46.447145: train_loss -0.7616 +2024-11-21 22:33:46.449302: val_loss -0.7549 +2024-11-21 22:33:46.449425: Pseudo dice [0.8522] +2024-11-21 22:33:46.449512: Epoch time: 19.97 s +2024-11-21 22:33:47.266380: +2024-11-21 22:33:47.266588: Epoch 2134 +2024-11-21 22:33:47.266709: Current learning rate: 0.00756 +2024-11-21 22:34:05.333879: train_loss -0.7797 +2024-11-21 22:34:05.341136: val_loss -0.7857 +2024-11-21 22:34:05.341275: Pseudo dice [0.8405] +2024-11-21 22:34:05.341364: Epoch time: 18.07 s +2024-11-21 22:34:06.171998: +2024-11-21 22:34:06.172282: Epoch 2135 +2024-11-21 22:34:06.172413: Current learning rate: 0.00756 +2024-11-21 22:34:25.020177: train_loss -0.7691 +2024-11-21 22:34:25.027352: val_loss -0.7884 +2024-11-21 22:34:25.027534: Pseudo dice [0.8525] +2024-11-21 22:34:25.027622: Epoch time: 18.85 s +2024-11-21 22:34:25.980952: +2024-11-21 22:34:25.981203: Epoch 2136 +2024-11-21 22:34:25.981321: Current learning rate: 0.00756 +2024-11-21 22:34:44.798904: train_loss -0.7744 +2024-11-21 22:34:44.804910: val_loss -0.7734 +2024-11-21 22:34:44.805055: Pseudo dice [0.8498] +2024-11-21 22:34:44.805150: Epoch time: 18.82 s +2024-11-21 22:34:45.630607: +2024-11-21 22:34:45.630849: Epoch 2137 +2024-11-21 22:34:45.630965: Current learning rate: 0.00756 +2024-11-21 22:35:03.674729: train_loss -0.776 +2024-11-21 22:35:03.679093: val_loss -0.771 +2024-11-21 22:35:03.679221: Pseudo dice [0.85] +2024-11-21 22:35:03.679338: Epoch time: 18.04 s +2024-11-21 22:35:04.544796: +2024-11-21 22:35:04.545028: Epoch 2138 +2024-11-21 22:35:04.545150: Current learning rate: 0.00756 +2024-11-21 22:35:23.884251: train_loss -0.7606 +2024-11-21 22:35:23.890105: val_loss -0.7729 +2024-11-21 22:35:23.890250: Pseudo dice [0.8421] +2024-11-21 22:35:23.890357: Epoch time: 19.34 s +2024-11-21 22:35:24.792257: +2024-11-21 22:35:24.792437: Epoch 2139 +2024-11-21 22:35:24.792564: Current learning rate: 0.00756 +2024-11-21 22:35:43.657175: train_loss -0.7591 +2024-11-21 22:35:43.663624: val_loss -0.7493 +2024-11-21 22:35:43.663759: Pseudo dice [0.8333] +2024-11-21 22:35:43.663852: Epoch time: 18.87 s +2024-11-21 22:35:44.475251: +2024-11-21 22:35:44.475515: Epoch 2140 +2024-11-21 22:35:44.475638: Current learning rate: 0.00756 +2024-11-21 22:36:03.701793: train_loss -0.7655 +2024-11-21 22:36:03.708333: val_loss -0.7762 +2024-11-21 22:36:03.708487: Pseudo dice [0.853] +2024-11-21 22:36:03.708583: Epoch time: 19.23 s +2024-11-21 22:36:04.861847: +2024-11-21 22:36:04.862051: Epoch 2141 +2024-11-21 22:36:04.862169: Current learning rate: 0.00756 +2024-11-21 22:36:23.925833: train_loss -0.7679 +2024-11-21 22:36:23.931957: val_loss -0.7696 +2024-11-21 22:36:23.932221: Pseudo dice [0.8518] +2024-11-21 22:36:23.932319: Epoch time: 19.06 s +2024-11-21 22:36:24.765368: +2024-11-21 22:36:24.765596: Epoch 2142 +2024-11-21 22:36:24.765721: Current learning rate: 0.00755 +2024-11-21 22:36:43.835957: train_loss -0.7749 +2024-11-21 22:36:43.841851: val_loss -0.7675 +2024-11-21 22:36:43.842038: Pseudo dice [0.8471] +2024-11-21 22:36:43.842156: Epoch time: 19.07 s +2024-11-21 22:36:44.779580: +2024-11-21 22:36:44.779975: Epoch 2143 +2024-11-21 22:36:44.780121: Current learning rate: 0.00755 +2024-11-21 22:37:03.844688: train_loss -0.7643 +2024-11-21 22:37:03.847363: val_loss -0.7501 +2024-11-21 22:37:03.847507: Pseudo dice [0.8435] +2024-11-21 22:37:03.847612: Epoch time: 19.07 s +2024-11-21 22:37:04.790282: +2024-11-21 22:37:04.790513: Epoch 2144 +2024-11-21 22:37:04.790634: Current learning rate: 0.00755 +2024-11-21 22:37:23.191883: train_loss -0.7574 +2024-11-21 22:37:23.194029: val_loss -0.7578 +2024-11-21 22:37:23.194144: Pseudo dice [0.8276] +2024-11-21 22:37:23.194237: Epoch time: 18.4 s +2024-11-21 22:37:24.009694: +2024-11-21 22:37:24.009910: Epoch 2145 +2024-11-21 22:37:24.010029: Current learning rate: 0.00755 +2024-11-21 22:37:44.521906: train_loss -0.7644 +2024-11-21 22:37:44.536418: val_loss -0.753 +2024-11-21 22:37:44.536560: Pseudo dice [0.8459] +2024-11-21 22:37:44.536650: Epoch time: 20.51 s +2024-11-21 22:37:45.460122: +2024-11-21 22:37:45.460323: Epoch 2146 +2024-11-21 22:37:45.460442: Current learning rate: 0.00755 +2024-11-21 22:38:04.013502: train_loss -0.7686 +2024-11-21 22:38:04.015409: val_loss -0.7477 +2024-11-21 22:38:04.015508: Pseudo dice [0.8505] +2024-11-21 22:38:04.015597: Epoch time: 18.55 s +2024-11-21 22:38:04.827947: +2024-11-21 22:38:04.828179: Epoch 2147 +2024-11-21 22:38:04.828303: Current learning rate: 0.00755 +2024-11-21 22:38:23.954604: train_loss -0.7716 +2024-11-21 22:38:23.975962: val_loss -0.7558 +2024-11-21 22:38:23.976138: Pseudo dice [0.8401] +2024-11-21 22:38:23.976238: Epoch time: 19.13 s +2024-11-21 22:38:25.094514: +2024-11-21 22:38:25.094757: Epoch 2148 +2024-11-21 22:38:25.094876: Current learning rate: 0.00755 +2024-11-21 22:38:44.616438: train_loss -0.7714 +2024-11-21 22:38:44.624045: val_loss -0.7574 +2024-11-21 22:38:44.624195: Pseudo dice [0.8515] +2024-11-21 22:38:44.624288: Epoch time: 19.52 s +2024-11-21 22:38:45.439232: +2024-11-21 22:38:45.439439: Epoch 2149 +2024-11-21 22:38:45.439570: Current learning rate: 0.00755 +2024-11-21 22:39:04.825104: train_loss -0.7743 +2024-11-21 22:39:04.839433: val_loss -0.7663 +2024-11-21 22:39:04.839597: Pseudo dice [0.8447] +2024-11-21 22:39:04.839688: Epoch time: 19.39 s +2024-11-21 22:39:06.000453: +2024-11-21 22:39:06.000671: Epoch 2150 +2024-11-21 22:39:06.000794: Current learning rate: 0.00755 +2024-11-21 22:39:25.312360: train_loss -0.784 +2024-11-21 22:39:25.320092: val_loss -0.7548 +2024-11-21 22:39:25.320205: Pseudo dice [0.8526] +2024-11-21 22:39:25.320289: Epoch time: 19.31 s +2024-11-21 22:39:26.414539: +2024-11-21 22:39:26.414750: Epoch 2151 +2024-11-21 22:39:26.414881: Current learning rate: 0.00754 +2024-11-21 22:39:44.732507: train_loss -0.7805 +2024-11-21 22:39:44.737746: val_loss -0.7486 +2024-11-21 22:39:44.737869: Pseudo dice [0.8519] +2024-11-21 22:39:44.737962: Epoch time: 18.32 s +2024-11-21 22:39:45.615641: +2024-11-21 22:39:45.615870: Epoch 2152 +2024-11-21 22:39:45.615990: Current learning rate: 0.00754 +2024-11-21 22:40:04.408895: train_loss -0.7753 +2024-11-21 22:40:04.410434: val_loss -0.7751 +2024-11-21 22:40:04.410555: Pseudo dice [0.852] +2024-11-21 22:40:04.410673: Epoch time: 18.79 s +2024-11-21 22:40:05.297895: +2024-11-21 22:40:05.298162: Epoch 2153 +2024-11-21 22:40:05.298291: Current learning rate: 0.00754 +2024-11-21 22:40:24.686929: train_loss -0.7671 +2024-11-21 22:40:24.696554: val_loss -0.75 +2024-11-21 22:40:24.696682: Pseudo dice [0.8557] +2024-11-21 22:40:24.696774: Epoch time: 19.39 s +2024-11-21 22:40:25.515034: +2024-11-21 22:40:25.515248: Epoch 2154 +2024-11-21 22:40:25.515370: Current learning rate: 0.00754 +2024-11-21 22:40:45.467982: train_loss -0.7842 +2024-11-21 22:40:45.473811: val_loss -0.7595 +2024-11-21 22:40:45.473967: Pseudo dice [0.8426] +2024-11-21 22:40:45.474066: Epoch time: 19.95 s +2024-11-21 22:40:46.814198: +2024-11-21 22:40:46.814449: Epoch 2155 +2024-11-21 22:40:46.814569: Current learning rate: 0.00754 +2024-11-21 22:41:06.482545: train_loss -0.7808 +2024-11-21 22:41:06.488368: val_loss -0.7685 +2024-11-21 22:41:06.488485: Pseudo dice [0.8453] +2024-11-21 22:41:06.488592: Epoch time: 19.67 s +2024-11-21 22:41:07.582118: +2024-11-21 22:41:07.582407: Epoch 2156 +2024-11-21 22:41:07.582568: Current learning rate: 0.00754 +2024-11-21 22:41:26.776580: train_loss -0.7753 +2024-11-21 22:41:26.783097: val_loss -0.7581 +2024-11-21 22:41:26.783304: Pseudo dice [0.8298] +2024-11-21 22:41:26.783397: Epoch time: 19.2 s +2024-11-21 22:41:27.645833: +2024-11-21 22:41:27.646051: Epoch 2157 +2024-11-21 22:41:27.646187: Current learning rate: 0.00754 +2024-11-21 22:41:46.507363: train_loss -0.7815 +2024-11-21 22:41:46.509570: val_loss -0.7753 +2024-11-21 22:41:46.509691: Pseudo dice [0.8409] +2024-11-21 22:41:46.509794: Epoch time: 18.86 s +2024-11-21 22:41:47.325078: +2024-11-21 22:41:47.325303: Epoch 2158 +2024-11-21 22:41:47.325419: Current learning rate: 0.00754 +2024-11-21 22:42:06.122768: train_loss -0.781 +2024-11-21 22:42:06.145612: val_loss -0.7665 +2024-11-21 22:42:06.145764: Pseudo dice [0.8529] +2024-11-21 22:42:06.145868: Epoch time: 18.8 s +2024-11-21 22:42:07.316758: +2024-11-21 22:42:07.316961: Epoch 2159 +2024-11-21 22:42:07.317095: Current learning rate: 0.00753 +2024-11-21 22:42:26.459369: train_loss -0.7784 +2024-11-21 22:42:26.468498: val_loss -0.7763 +2024-11-21 22:42:26.468652: Pseudo dice [0.854] +2024-11-21 22:42:26.468752: Epoch time: 19.14 s +2024-11-21 22:42:27.300928: +2024-11-21 22:42:27.301152: Epoch 2160 +2024-11-21 22:42:27.301289: Current learning rate: 0.00753 +2024-11-21 22:42:46.900075: train_loss -0.7731 +2024-11-21 22:42:46.905655: val_loss -0.7836 +2024-11-21 22:42:46.905800: Pseudo dice [0.8511] +2024-11-21 22:42:46.905895: Epoch time: 19.6 s +2024-11-21 22:42:47.868263: +2024-11-21 22:42:47.868521: Epoch 2161 +2024-11-21 22:42:47.868649: Current learning rate: 0.00753 +2024-11-21 22:43:07.163146: train_loss -0.7627 +2024-11-21 22:43:07.165133: val_loss -0.7698 +2024-11-21 22:43:07.165276: Pseudo dice [0.8438] +2024-11-21 22:43:07.165364: Epoch time: 19.3 s +2024-11-21 22:43:08.308926: +2024-11-21 22:43:08.309126: Epoch 2162 +2024-11-21 22:43:08.309244: Current learning rate: 0.00753 +2024-11-21 22:43:27.346566: train_loss -0.7744 +2024-11-21 22:43:27.353701: val_loss -0.7456 +2024-11-21 22:43:27.353832: Pseudo dice [0.8583] +2024-11-21 22:43:27.353925: Epoch time: 19.04 s +2024-11-21 22:43:28.182586: +2024-11-21 22:43:28.182788: Epoch 2163 +2024-11-21 22:43:28.182919: Current learning rate: 0.00753 +2024-11-21 22:43:47.062427: train_loss -0.773 +2024-11-21 22:43:47.066566: val_loss -0.7725 +2024-11-21 22:43:47.066701: Pseudo dice [0.8487] +2024-11-21 22:43:47.066806: Epoch time: 18.88 s +2024-11-21 22:43:47.958158: +2024-11-21 22:43:47.958391: Epoch 2164 +2024-11-21 22:43:47.958533: Current learning rate: 0.00753 +2024-11-21 22:44:05.440206: train_loss -0.7761 +2024-11-21 22:44:05.445446: val_loss -0.7495 +2024-11-21 22:44:05.445587: Pseudo dice [0.8437] +2024-11-21 22:44:05.445704: Epoch time: 17.48 s +2024-11-21 22:44:06.264316: +2024-11-21 22:44:06.264519: Epoch 2165 +2024-11-21 22:44:06.264640: Current learning rate: 0.00753 +2024-11-21 22:44:24.723567: train_loss -0.769 +2024-11-21 22:44:24.733527: val_loss -0.7473 +2024-11-21 22:44:24.733658: Pseudo dice [0.8532] +2024-11-21 22:44:24.733756: Epoch time: 18.46 s +2024-11-21 22:44:25.683267: +2024-11-21 22:44:25.683475: Epoch 2166 +2024-11-21 22:44:25.683598: Current learning rate: 0.00753 +2024-11-21 22:44:44.448030: train_loss -0.7683 +2024-11-21 22:44:44.459454: val_loss -0.753 +2024-11-21 22:44:44.459614: Pseudo dice [0.848] +2024-11-21 22:44:44.459711: Epoch time: 18.77 s +2024-11-21 22:44:45.315098: +2024-11-21 22:44:45.315335: Epoch 2167 +2024-11-21 22:44:45.315470: Current learning rate: 0.00753 +2024-11-21 22:45:04.415581: train_loss -0.7749 +2024-11-21 22:45:04.420921: val_loss -0.7886 +2024-11-21 22:45:04.421118: Pseudo dice [0.8616] +2024-11-21 22:45:04.421218: Epoch time: 19.1 s +2024-11-21 22:45:05.374994: +2024-11-21 22:45:05.375283: Epoch 2168 +2024-11-21 22:45:05.375416: Current learning rate: 0.00752 +2024-11-21 22:45:23.822800: train_loss -0.7739 +2024-11-21 22:45:23.828897: val_loss -0.7459 +2024-11-21 22:45:23.829008: Pseudo dice [0.8603] +2024-11-21 22:45:23.829284: Epoch time: 18.45 s +2024-11-21 22:45:24.679609: +2024-11-21 22:45:24.679817: Epoch 2169 +2024-11-21 22:45:24.679955: Current learning rate: 0.00752 +2024-11-21 22:45:44.041924: train_loss -0.773 +2024-11-21 22:45:44.046335: val_loss -0.7579 +2024-11-21 22:45:44.046449: Pseudo dice [0.8527] +2024-11-21 22:45:44.046557: Epoch time: 19.36 s +2024-11-21 22:45:45.003073: +2024-11-21 22:45:45.003316: Epoch 2170 +2024-11-21 22:45:45.003448: Current learning rate: 0.00752 +2024-11-21 22:46:05.075381: train_loss -0.7769 +2024-11-21 22:46:05.081903: val_loss -0.7577 +2024-11-21 22:46:05.082048: Pseudo dice [0.8465] +2024-11-21 22:46:05.082171: Epoch time: 20.07 s +2024-11-21 22:46:05.963243: +2024-11-21 22:46:05.963506: Epoch 2171 +2024-11-21 22:46:05.963630: Current learning rate: 0.00752 +2024-11-21 22:46:24.825439: train_loss -0.7801 +2024-11-21 22:46:24.833403: val_loss -0.7596 +2024-11-21 22:46:24.833541: Pseudo dice [0.8512] +2024-11-21 22:46:24.833635: Epoch time: 18.86 s +2024-11-21 22:46:25.679232: +2024-11-21 22:46:25.679437: Epoch 2172 +2024-11-21 22:46:25.679559: Current learning rate: 0.00752 +2024-11-21 22:46:44.734102: train_loss -0.7778 +2024-11-21 22:46:44.735751: val_loss -0.7845 +2024-11-21 22:46:44.735857: Pseudo dice [0.8575] +2024-11-21 22:46:44.735940: Epoch time: 19.06 s +2024-11-21 22:46:45.756243: +2024-11-21 22:46:45.756463: Epoch 2173 +2024-11-21 22:46:45.756584: Current learning rate: 0.00752 +2024-11-21 22:47:05.122505: train_loss -0.7765 +2024-11-21 22:47:05.129537: val_loss -0.7817 +2024-11-21 22:47:05.129659: Pseudo dice [0.8534] +2024-11-21 22:47:05.129769: Epoch time: 19.37 s +2024-11-21 22:47:06.097958: +2024-11-21 22:47:06.098160: Epoch 2174 +2024-11-21 22:47:06.098277: Current learning rate: 0.00752 +2024-11-21 22:47:25.562783: train_loss -0.7732 +2024-11-21 22:47:25.569293: val_loss -0.7556 +2024-11-21 22:47:25.569431: Pseudo dice [0.8368] +2024-11-21 22:47:25.569534: Epoch time: 19.47 s +2024-11-21 22:47:26.424505: +2024-11-21 22:47:26.424706: Epoch 2175 +2024-11-21 22:47:26.424827: Current learning rate: 0.00752 +2024-11-21 22:47:45.701166: train_loss -0.7789 +2024-11-21 22:47:45.707527: val_loss -0.7601 +2024-11-21 22:47:45.707662: Pseudo dice [0.8347] +2024-11-21 22:47:45.707767: Epoch time: 19.28 s +2024-11-21 22:47:46.732910: +2024-11-21 22:47:46.733117: Epoch 2176 +2024-11-21 22:47:46.733238: Current learning rate: 0.00751 +2024-11-21 22:48:05.413958: train_loss -0.788 +2024-11-21 22:48:05.418514: val_loss -0.7742 +2024-11-21 22:48:05.418639: Pseudo dice [0.8557] +2024-11-21 22:48:05.418725: Epoch time: 18.68 s +2024-11-21 22:48:06.343844: +2024-11-21 22:48:06.344062: Epoch 2177 +2024-11-21 22:48:06.344189: Current learning rate: 0.00751 +2024-11-21 22:48:24.091000: train_loss -0.7784 +2024-11-21 22:48:24.099361: val_loss -0.7764 +2024-11-21 22:48:24.099502: Pseudo dice [0.8601] +2024-11-21 22:48:24.099593: Epoch time: 17.75 s +2024-11-21 22:48:25.367761: +2024-11-21 22:48:25.367968: Epoch 2178 +2024-11-21 22:48:25.368087: Current learning rate: 0.00751 +2024-11-21 22:48:44.422909: train_loss -0.7863 +2024-11-21 22:48:44.431852: val_loss -0.7884 +2024-11-21 22:48:44.432014: Pseudo dice [0.8579] +2024-11-21 22:48:44.432140: Epoch time: 19.06 s +2024-11-21 22:48:45.297379: +2024-11-21 22:48:45.297605: Epoch 2179 +2024-11-21 22:48:45.297724: Current learning rate: 0.00751 +2024-11-21 22:49:04.596902: train_loss -0.7741 +2024-11-21 22:49:04.600198: val_loss -0.7759 +2024-11-21 22:49:04.600308: Pseudo dice [0.847] +2024-11-21 22:49:04.600411: Epoch time: 19.3 s +2024-11-21 22:49:05.413735: +2024-11-21 22:49:05.413965: Epoch 2180 +2024-11-21 22:49:05.414089: Current learning rate: 0.00751 +2024-11-21 22:49:24.387274: train_loss -0.7696 +2024-11-21 22:49:24.393269: val_loss -0.788 +2024-11-21 22:49:24.393420: Pseudo dice [0.8551] +2024-11-21 22:49:24.393516: Epoch time: 18.97 s +2024-11-21 22:49:25.293266: +2024-11-21 22:49:25.293502: Epoch 2181 +2024-11-21 22:49:25.293624: Current learning rate: 0.00751 +2024-11-21 22:49:43.912069: train_loss -0.7745 +2024-11-21 22:49:43.938184: val_loss -0.7846 +2024-11-21 22:49:43.938338: Pseudo dice [0.8473] +2024-11-21 22:49:43.938449: Epoch time: 18.62 s +2024-11-21 22:49:44.834791: +2024-11-21 22:49:44.835019: Epoch 2182 +2024-11-21 22:49:44.835145: Current learning rate: 0.00751 +2024-11-21 22:50:03.542255: train_loss -0.7653 +2024-11-21 22:50:03.556420: val_loss -0.7453 +2024-11-21 22:50:03.556543: Pseudo dice [0.8421] +2024-11-21 22:50:03.556635: Epoch time: 18.71 s +2024-11-21 22:50:04.551851: +2024-11-21 22:50:04.552045: Epoch 2183 +2024-11-21 22:50:04.552201: Current learning rate: 0.00751 +2024-11-21 22:50:24.300940: train_loss -0.7671 +2024-11-21 22:50:24.328279: val_loss -0.7436 +2024-11-21 22:50:24.328439: Pseudo dice [0.8252] +2024-11-21 22:50:24.328532: Epoch time: 19.75 s +2024-11-21 22:50:25.153097: +2024-11-21 22:50:25.153300: Epoch 2184 +2024-11-21 22:50:25.153410: Current learning rate: 0.00751 +2024-11-21 22:50:44.312018: train_loss -0.7512 +2024-11-21 22:50:44.316734: val_loss -0.7744 +2024-11-21 22:50:44.316859: Pseudo dice [0.8398] +2024-11-21 22:50:44.316943: Epoch time: 19.16 s +2024-11-21 22:50:45.267645: +2024-11-21 22:50:45.267850: Epoch 2185 +2024-11-21 22:50:45.267994: Current learning rate: 0.0075 +2024-11-21 22:51:04.269937: train_loss -0.7628 +2024-11-21 22:51:04.291177: val_loss -0.7564 +2024-11-21 22:51:04.291320: Pseudo dice [0.841] +2024-11-21 22:51:04.291417: Epoch time: 19.0 s +2024-11-21 22:51:05.182732: +2024-11-21 22:51:05.182979: Epoch 2186 +2024-11-21 22:51:05.183137: Current learning rate: 0.0075 +2024-11-21 22:51:24.794425: train_loss -0.7731 +2024-11-21 22:51:24.802531: val_loss -0.786 +2024-11-21 22:51:24.802678: Pseudo dice [0.854] +2024-11-21 22:51:24.802776: Epoch time: 19.61 s +2024-11-21 22:51:25.641018: +2024-11-21 22:51:25.641224: Epoch 2187 +2024-11-21 22:51:25.641338: Current learning rate: 0.0075 +2024-11-21 22:51:44.653611: train_loss -0.7741 +2024-11-21 22:51:44.664960: val_loss -0.7666 +2024-11-21 22:51:44.665091: Pseudo dice [0.8464] +2024-11-21 22:51:44.665175: Epoch time: 19.01 s +2024-11-21 22:51:45.489402: +2024-11-21 22:51:45.489607: Epoch 2188 +2024-11-21 22:51:45.489738: Current learning rate: 0.0075 +2024-11-21 22:52:04.744658: train_loss -0.7764 +2024-11-21 22:52:04.756588: val_loss -0.7759 +2024-11-21 22:52:04.756731: Pseudo dice [0.8537] +2024-11-21 22:52:04.756819: Epoch time: 19.26 s +2024-11-21 22:52:05.601034: +2024-11-21 22:52:05.601255: Epoch 2189 +2024-11-21 22:52:05.601384: Current learning rate: 0.0075 +2024-11-21 22:52:25.054689: train_loss -0.777 +2024-11-21 22:52:25.064777: val_loss -0.7612 +2024-11-21 22:52:25.064920: Pseudo dice [0.8554] +2024-11-21 22:52:25.065021: Epoch time: 19.45 s +2024-11-21 22:52:25.996945: +2024-11-21 22:52:25.997186: Epoch 2190 +2024-11-21 22:52:25.997312: Current learning rate: 0.0075 +2024-11-21 22:52:45.678591: train_loss -0.7744 +2024-11-21 22:52:45.681210: val_loss -0.7395 +2024-11-21 22:52:45.681341: Pseudo dice [0.8356] +2024-11-21 22:52:45.681426: Epoch time: 19.68 s +2024-11-21 22:52:46.594126: +2024-11-21 22:52:46.594354: Epoch 2191 +2024-11-21 22:52:46.594485: Current learning rate: 0.0075 +2024-11-21 22:53:06.303603: train_loss -0.7647 +2024-11-21 22:53:06.310279: val_loss -0.757 +2024-11-21 22:53:06.310427: Pseudo dice [0.8386] +2024-11-21 22:53:06.310515: Epoch time: 19.71 s +2024-11-21 22:53:07.233068: +2024-11-21 22:53:07.233282: Epoch 2192 +2024-11-21 22:53:07.233405: Current learning rate: 0.0075 +2024-11-21 22:53:26.703278: train_loss -0.7592 +2024-11-21 22:53:26.705966: val_loss -0.7581 +2024-11-21 22:53:26.706080: Pseudo dice [0.8271] +2024-11-21 22:53:26.706166: Epoch time: 19.47 s +2024-11-21 22:53:27.519340: +2024-11-21 22:53:27.519562: Epoch 2193 +2024-11-21 22:53:27.519686: Current learning rate: 0.0075 +2024-11-21 22:53:45.153052: train_loss -0.7553 +2024-11-21 22:53:45.159780: val_loss -0.7511 +2024-11-21 22:53:45.159900: Pseudo dice [0.8335] +2024-11-21 22:53:45.159999: Epoch time: 17.63 s +2024-11-21 22:53:46.171675: +2024-11-21 22:53:46.171881: Epoch 2194 +2024-11-21 22:53:46.187557: Current learning rate: 0.00749 +2024-11-21 22:54:04.424900: train_loss -0.7652 +2024-11-21 22:54:04.431487: val_loss -0.7626 +2024-11-21 22:54:04.431599: Pseudo dice [0.8564] +2024-11-21 22:54:04.431693: Epoch time: 18.25 s +2024-11-21 22:54:05.268697: +2024-11-21 22:54:05.268911: Epoch 2195 +2024-11-21 22:54:05.269049: Current learning rate: 0.00749 +2024-11-21 22:54:23.770502: train_loss -0.7742 +2024-11-21 22:54:23.778664: val_loss -0.7592 +2024-11-21 22:54:23.778799: Pseudo dice [0.843] +2024-11-21 22:54:23.778889: Epoch time: 18.5 s +2024-11-21 22:54:24.994733: +2024-11-21 22:54:24.994930: Epoch 2196 +2024-11-21 22:54:24.995048: Current learning rate: 0.00749 +2024-11-21 22:54:43.852720: train_loss -0.7754 +2024-11-21 22:54:43.859416: val_loss -0.7642 +2024-11-21 22:54:43.859579: Pseudo dice [0.8375] +2024-11-21 22:54:43.859736: Epoch time: 18.86 s +2024-11-21 22:54:44.934575: +2024-11-21 22:54:44.934789: Epoch 2197 +2024-11-21 22:54:44.934909: Current learning rate: 0.00749 +2024-11-21 22:55:02.630056: train_loss -0.7682 +2024-11-21 22:55:02.637079: val_loss -0.7729 +2024-11-21 22:55:02.637221: Pseudo dice [0.8577] +2024-11-21 22:55:02.637314: Epoch time: 17.7 s +2024-11-21 22:55:03.551282: +2024-11-21 22:55:03.551493: Epoch 2198 +2024-11-21 22:55:03.551623: Current learning rate: 0.00749 +2024-11-21 22:55:21.698907: train_loss -0.7846 +2024-11-21 22:55:21.705789: val_loss -0.7732 +2024-11-21 22:55:21.705912: Pseudo dice [0.8542] +2024-11-21 22:55:21.706013: Epoch time: 18.15 s +2024-11-21 22:55:22.575100: +2024-11-21 22:55:22.575320: Epoch 2199 +2024-11-21 22:55:22.575444: Current learning rate: 0.00749 +2024-11-21 22:55:42.289134: train_loss -0.7654 +2024-11-21 22:55:42.302395: val_loss -0.7742 +2024-11-21 22:55:42.302523: Pseudo dice [0.8598] +2024-11-21 22:55:42.302628: Epoch time: 19.71 s +2024-11-21 22:55:43.480154: +2024-11-21 22:55:43.480344: Epoch 2200 +2024-11-21 22:55:43.480466: Current learning rate: 0.00749 +2024-11-21 22:56:02.198675: train_loss -0.7749 +2024-11-21 22:56:02.207273: val_loss -0.714 +2024-11-21 22:56:02.207398: Pseudo dice [0.8261] +2024-11-21 22:56:02.207510: Epoch time: 18.72 s +2024-11-21 22:56:03.478381: +2024-11-21 22:56:03.478614: Epoch 2201 +2024-11-21 22:56:03.478733: Current learning rate: 0.00749 +2024-11-21 22:56:23.053291: train_loss -0.7667 +2024-11-21 22:56:23.061597: val_loss -0.7637 +2024-11-21 22:56:23.061748: Pseudo dice [0.8502] +2024-11-21 22:56:23.061833: Epoch time: 19.58 s +2024-11-21 22:56:23.880316: +2024-11-21 22:56:23.880533: Epoch 2202 +2024-11-21 22:56:23.880674: Current learning rate: 0.00748 +2024-11-21 22:56:43.618542: train_loss -0.7696 +2024-11-21 22:56:43.627313: val_loss -0.7568 +2024-11-21 22:56:43.627458: Pseudo dice [0.843] +2024-11-21 22:56:43.627635: Epoch time: 19.74 s +2024-11-21 22:56:44.450956: +2024-11-21 22:56:44.451159: Epoch 2203 +2024-11-21 22:56:44.451274: Current learning rate: 0.00748 +2024-11-21 22:57:03.336667: train_loss -0.7792 +2024-11-21 22:57:03.338776: val_loss -0.774 +2024-11-21 22:57:03.338875: Pseudo dice [0.8482] +2024-11-21 22:57:03.338969: Epoch time: 18.89 s +2024-11-21 22:57:04.153392: +2024-11-21 22:57:04.153612: Epoch 2204 +2024-11-21 22:57:04.153733: Current learning rate: 0.00748 +2024-11-21 22:57:23.228893: train_loss -0.7646 +2024-11-21 22:57:23.233680: val_loss -0.7577 +2024-11-21 22:57:23.233816: Pseudo dice [0.8318] +2024-11-21 22:57:23.233955: Epoch time: 19.08 s +2024-11-21 22:57:24.205971: +2024-11-21 22:57:24.206203: Epoch 2205 +2024-11-21 22:57:24.206325: Current learning rate: 0.00748 +2024-11-21 22:57:43.022915: train_loss -0.7837 +2024-11-21 22:57:43.033039: val_loss -0.7582 +2024-11-21 22:57:43.033205: Pseudo dice [0.8468] +2024-11-21 22:57:43.033303: Epoch time: 18.82 s +2024-11-21 22:57:43.985934: +2024-11-21 22:57:43.986155: Epoch 2206 +2024-11-21 22:57:43.986290: Current learning rate: 0.00748 +2024-11-21 22:58:03.548232: train_loss -0.7827 +2024-11-21 22:58:03.554599: val_loss -0.7554 +2024-11-21 22:58:03.554804: Pseudo dice [0.844] +2024-11-21 22:58:03.571412: Epoch time: 19.56 s +2024-11-21 22:58:04.619268: +2024-11-21 22:58:04.619461: Epoch 2207 +2024-11-21 22:58:04.619585: Current learning rate: 0.00748 +2024-11-21 22:58:22.164965: train_loss -0.7831 +2024-11-21 22:58:22.171470: val_loss -0.7513 +2024-11-21 22:58:22.171603: Pseudo dice [0.8394] +2024-11-21 22:58:22.171691: Epoch time: 17.55 s +2024-11-21 22:58:23.031304: +2024-11-21 22:58:23.031527: Epoch 2208 +2024-11-21 22:58:23.031646: Current learning rate: 0.00748 +2024-11-21 22:58:42.258893: train_loss -0.7863 +2024-11-21 22:58:42.264358: val_loss -0.7722 +2024-11-21 22:58:42.264481: Pseudo dice [0.8461] +2024-11-21 22:58:42.264635: Epoch time: 19.23 s +2024-11-21 22:58:43.084256: +2024-11-21 22:58:43.084467: Epoch 2209 +2024-11-21 22:58:43.084596: Current learning rate: 0.00748 +2024-11-21 22:59:02.489856: train_loss -0.7599 +2024-11-21 22:59:02.492398: val_loss -0.7381 +2024-11-21 22:59:02.492542: Pseudo dice [0.8462] +2024-11-21 22:59:02.492629: Epoch time: 19.41 s +2024-11-21 22:59:03.384023: +2024-11-21 22:59:03.384265: Epoch 2210 +2024-11-21 22:59:03.384396: Current learning rate: 0.00748 +2024-11-21 22:59:21.806289: train_loss -0.7624 +2024-11-21 22:59:21.832295: val_loss -0.7789 +2024-11-21 22:59:21.832458: Pseudo dice [0.8515] +2024-11-21 22:59:21.832542: Epoch time: 18.42 s +2024-11-21 22:59:22.778773: +2024-11-21 22:59:22.778973: Epoch 2211 +2024-11-21 22:59:22.779265: Current learning rate: 0.00747 +2024-11-21 22:59:42.198352: train_loss -0.7651 +2024-11-21 22:59:42.219575: val_loss -0.7489 +2024-11-21 22:59:42.219744: Pseudo dice [0.8368] +2024-11-21 22:59:42.219842: Epoch time: 19.42 s +2024-11-21 22:59:43.097909: +2024-11-21 22:59:43.098114: Epoch 2212 +2024-11-21 22:59:43.098256: Current learning rate: 0.00747 +2024-11-21 23:00:02.363389: train_loss -0.7613 +2024-11-21 23:00:02.366930: val_loss -0.7778 +2024-11-21 23:00:02.367101: Pseudo dice [0.849] +2024-11-21 23:00:02.367212: Epoch time: 19.27 s +2024-11-21 23:00:03.710361: +2024-11-21 23:00:03.710563: Epoch 2213 +2024-11-21 23:00:03.710692: Current learning rate: 0.00747 +2024-11-21 23:00:22.973601: train_loss -0.7573 +2024-11-21 23:00:22.976178: val_loss -0.7616 +2024-11-21 23:00:22.976301: Pseudo dice [0.8594] +2024-11-21 23:00:22.976391: Epoch time: 19.26 s +2024-11-21 23:00:23.790024: +2024-11-21 23:00:23.790249: Epoch 2214 +2024-11-21 23:00:23.790381: Current learning rate: 0.00747 +2024-11-21 23:00:41.987507: train_loss -0.7663 +2024-11-21 23:00:41.997678: val_loss -0.7578 +2024-11-21 23:00:41.997825: Pseudo dice [0.8555] +2024-11-21 23:00:41.997917: Epoch time: 18.2 s +2024-11-21 23:00:43.164210: +2024-11-21 23:00:43.164422: Epoch 2215 +2024-11-21 23:00:43.164546: Current learning rate: 0.00747 +2024-11-21 23:01:02.494450: train_loss -0.7746 +2024-11-21 23:01:02.498399: val_loss -0.7576 +2024-11-21 23:01:02.498545: Pseudo dice [0.8529] +2024-11-21 23:01:02.498641: Epoch time: 19.33 s +2024-11-21 23:01:03.447927: +2024-11-21 23:01:03.448149: Epoch 2216 +2024-11-21 23:01:03.448278: Current learning rate: 0.00747 +2024-11-21 23:01:22.497852: train_loss -0.7689 +2024-11-21 23:01:22.503503: val_loss -0.7632 +2024-11-21 23:01:22.503640: Pseudo dice [0.8524] +2024-11-21 23:01:22.503734: Epoch time: 19.05 s +2024-11-21 23:01:23.331511: +2024-11-21 23:01:23.331693: Epoch 2217 +2024-11-21 23:01:23.331810: Current learning rate: 0.00747 +2024-11-21 23:01:41.578328: train_loss -0.7708 +2024-11-21 23:01:41.587074: val_loss -0.7817 +2024-11-21 23:01:41.587233: Pseudo dice [0.8576] +2024-11-21 23:01:41.587320: Epoch time: 18.25 s +2024-11-21 23:01:42.549185: +2024-11-21 23:01:42.549393: Epoch 2218 +2024-11-21 23:01:42.549542: Current learning rate: 0.00747 +2024-11-21 23:02:01.171132: train_loss -0.769 +2024-11-21 23:02:01.177833: val_loss -0.7739 +2024-11-21 23:02:01.178045: Pseudo dice [0.8426] +2024-11-21 23:02:01.178148: Epoch time: 18.62 s +2024-11-21 23:02:02.016200: +2024-11-21 23:02:02.016425: Epoch 2219 +2024-11-21 23:02:02.016561: Current learning rate: 0.00746 +2024-11-21 23:02:22.226557: train_loss -0.7694 +2024-11-21 23:02:22.229868: val_loss -0.7829 +2024-11-21 23:02:22.229964: Pseudo dice [0.8554] +2024-11-21 23:02:22.230053: Epoch time: 20.21 s +2024-11-21 23:02:23.044943: +2024-11-21 23:02:23.045142: Epoch 2220 +2024-11-21 23:02:23.045256: Current learning rate: 0.00746 +2024-11-21 23:02:42.341589: train_loss -0.7746 +2024-11-21 23:02:42.352480: val_loss -0.7723 +2024-11-21 23:02:42.352632: Pseudo dice [0.8256] +2024-11-21 23:02:42.352715: Epoch time: 19.3 s +2024-11-21 23:02:43.170538: +2024-11-21 23:02:43.170742: Epoch 2221 +2024-11-21 23:02:43.170867: Current learning rate: 0.00746 +2024-11-21 23:03:01.531435: train_loss -0.7699 +2024-11-21 23:03:01.538671: val_loss -0.7793 +2024-11-21 23:03:01.538818: Pseudo dice [0.8392] +2024-11-21 23:03:01.538903: Epoch time: 18.36 s +2024-11-21 23:03:02.509843: +2024-11-21 23:03:02.510056: Epoch 2222 +2024-11-21 23:03:02.510170: Current learning rate: 0.00746 +2024-11-21 23:03:21.231886: train_loss -0.7662 +2024-11-21 23:03:21.236018: val_loss -0.7575 +2024-11-21 23:03:21.236220: Pseudo dice [0.849] +2024-11-21 23:03:21.236318: Epoch time: 18.72 s +2024-11-21 23:03:22.102531: +2024-11-21 23:03:22.102733: Epoch 2223 +2024-11-21 23:03:22.102848: Current learning rate: 0.00746 +2024-11-21 23:03:41.682213: train_loss -0.77 +2024-11-21 23:03:41.684624: val_loss -0.7576 +2024-11-21 23:03:41.684739: Pseudo dice [0.8406] +2024-11-21 23:03:41.684863: Epoch time: 19.58 s +2024-11-21 23:03:42.498736: +2024-11-21 23:03:42.498948: Epoch 2224 +2024-11-21 23:03:42.499081: Current learning rate: 0.00746 +2024-11-21 23:04:01.783524: train_loss -0.77 +2024-11-21 23:04:01.792710: val_loss -0.7617 +2024-11-21 23:04:01.792857: Pseudo dice [0.8478] +2024-11-21 23:04:01.792957: Epoch time: 19.29 s +2024-11-21 23:04:02.731003: +2024-11-21 23:04:02.731202: Epoch 2225 +2024-11-21 23:04:02.731313: Current learning rate: 0.00746 +2024-11-21 23:04:20.996011: train_loss -0.7657 +2024-11-21 23:04:21.004681: val_loss -0.7727 +2024-11-21 23:04:21.004805: Pseudo dice [0.8528] +2024-11-21 23:04:21.004909: Epoch time: 18.27 s +2024-11-21 23:04:21.915448: +2024-11-21 23:04:21.915729: Epoch 2226 +2024-11-21 23:04:21.915895: Current learning rate: 0.00746 +2024-11-21 23:04:39.635714: train_loss -0.7695 +2024-11-21 23:04:39.639912: val_loss -0.7658 +2024-11-21 23:04:39.640056: Pseudo dice [0.8468] +2024-11-21 23:04:39.640157: Epoch time: 17.72 s +2024-11-21 23:04:40.475870: +2024-11-21 23:04:40.476082: Epoch 2227 +2024-11-21 23:04:40.476211: Current learning rate: 0.00746 +2024-11-21 23:05:00.026047: train_loss -0.772 +2024-11-21 23:05:00.031462: val_loss -0.7381 +2024-11-21 23:05:00.031605: Pseudo dice [0.847] +2024-11-21 23:05:00.031704: Epoch time: 19.55 s +2024-11-21 23:05:00.950603: +2024-11-21 23:05:00.950822: Epoch 2228 +2024-11-21 23:05:00.950938: Current learning rate: 0.00745 +2024-11-21 23:05:19.225903: train_loss -0.777 +2024-11-21 23:05:19.233763: val_loss -0.7696 +2024-11-21 23:05:19.233900: Pseudo dice [0.8502] +2024-11-21 23:05:19.234011: Epoch time: 18.28 s +2024-11-21 23:05:20.235551: +2024-11-21 23:05:20.235772: Epoch 2229 +2024-11-21 23:05:20.235891: Current learning rate: 0.00745 +2024-11-21 23:05:40.065529: train_loss -0.7681 +2024-11-21 23:05:40.091189: val_loss -0.7541 +2024-11-21 23:05:40.091357: Pseudo dice [0.8385] +2024-11-21 23:05:40.091470: Epoch time: 19.83 s +2024-11-21 23:05:40.953645: +2024-11-21 23:05:40.953879: Epoch 2230 +2024-11-21 23:05:40.954010: Current learning rate: 0.00745 +2024-11-21 23:06:00.639110: train_loss -0.7787 +2024-11-21 23:06:00.648182: val_loss -0.779 +2024-11-21 23:06:00.648321: Pseudo dice [0.8366] +2024-11-21 23:06:00.648407: Epoch time: 19.69 s +2024-11-21 23:06:01.519268: +2024-11-21 23:06:01.519521: Epoch 2231 +2024-11-21 23:06:01.519637: Current learning rate: 0.00745 +2024-11-21 23:06:20.947929: train_loss -0.7833 +2024-11-21 23:06:20.951096: val_loss -0.7846 +2024-11-21 23:06:20.951229: Pseudo dice [0.8519] +2024-11-21 23:06:20.951325: Epoch time: 19.43 s +2024-11-21 23:06:21.761840: +2024-11-21 23:06:21.762026: Epoch 2232 +2024-11-21 23:06:21.762147: Current learning rate: 0.00745 +2024-11-21 23:06:41.276281: train_loss -0.7627 +2024-11-21 23:06:41.280068: val_loss -0.7659 +2024-11-21 23:06:41.280212: Pseudo dice [0.8468] +2024-11-21 23:06:41.280319: Epoch time: 19.52 s +2024-11-21 23:06:42.234409: +2024-11-21 23:06:42.234675: Epoch 2233 +2024-11-21 23:06:42.234816: Current learning rate: 0.00745 +2024-11-21 23:07:01.490427: train_loss -0.77 +2024-11-21 23:07:01.493394: val_loss -0.7665 +2024-11-21 23:07:01.493507: Pseudo dice [0.8439] +2024-11-21 23:07:01.493728: Epoch time: 19.26 s +2024-11-21 23:07:02.306662: +2024-11-21 23:07:02.306854: Epoch 2234 +2024-11-21 23:07:02.306986: Current learning rate: 0.00745 +2024-11-21 23:07:21.098555: train_loss -0.7722 +2024-11-21 23:07:21.136751: val_loss -0.7592 +2024-11-21 23:07:21.136943: Pseudo dice [0.8449] +2024-11-21 23:07:21.137040: Epoch time: 18.79 s +2024-11-21 23:07:22.155290: +2024-11-21 23:07:22.155512: Epoch 2235 +2024-11-21 23:07:22.155637: Current learning rate: 0.00745 +2024-11-21 23:07:41.180679: train_loss -0.7681 +2024-11-21 23:07:41.184099: val_loss -0.7751 +2024-11-21 23:07:41.184234: Pseudo dice [0.8539] +2024-11-21 23:07:41.184319: Epoch time: 19.03 s +2024-11-21 23:07:42.419384: +2024-11-21 23:07:42.419603: Epoch 2236 +2024-11-21 23:07:42.419718: Current learning rate: 0.00745 +2024-11-21 23:08:01.690605: train_loss -0.7679 +2024-11-21 23:08:01.696996: val_loss -0.7728 +2024-11-21 23:08:01.697138: Pseudo dice [0.8575] +2024-11-21 23:08:01.697253: Epoch time: 19.27 s +2024-11-21 23:08:02.546239: +2024-11-21 23:08:02.546447: Epoch 2237 +2024-11-21 23:08:02.546827: Current learning rate: 0.00744 +2024-11-21 23:08:22.886794: train_loss -0.7811 +2024-11-21 23:08:22.892377: val_loss -0.7502 +2024-11-21 23:08:22.892503: Pseudo dice [0.8497] +2024-11-21 23:08:22.892593: Epoch time: 20.34 s +2024-11-21 23:08:23.724104: +2024-11-21 23:08:23.724319: Epoch 2238 +2024-11-21 23:08:23.724446: Current learning rate: 0.00744 +2024-11-21 23:08:43.522435: train_loss -0.7675 +2024-11-21 23:08:43.530331: val_loss -0.757 +2024-11-21 23:08:43.530483: Pseudo dice [0.8447] +2024-11-21 23:08:43.530570: Epoch time: 19.8 s +2024-11-21 23:08:44.363005: +2024-11-21 23:08:44.363242: Epoch 2239 +2024-11-21 23:08:44.363355: Current learning rate: 0.00744 +2024-11-21 23:09:03.243440: train_loss -0.7863 +2024-11-21 23:09:03.252486: val_loss -0.7734 +2024-11-21 23:09:03.252622: Pseudo dice [0.8527] +2024-11-21 23:09:03.252703: Epoch time: 18.88 s +2024-11-21 23:09:04.338437: +2024-11-21 23:09:04.338656: Epoch 2240 +2024-11-21 23:09:04.338773: Current learning rate: 0.00744 +2024-11-21 23:09:24.056410: train_loss -0.7779 +2024-11-21 23:09:24.063915: val_loss -0.7671 +2024-11-21 23:09:24.064037: Pseudo dice [0.8517] +2024-11-21 23:09:24.064141: Epoch time: 19.72 s +2024-11-21 23:09:25.078697: +2024-11-21 23:09:25.078902: Epoch 2241 +2024-11-21 23:09:25.079022: Current learning rate: 0.00744 +2024-11-21 23:09:43.972486: train_loss -0.7739 +2024-11-21 23:09:43.980986: val_loss -0.7722 +2024-11-21 23:09:43.981133: Pseudo dice [0.8412] +2024-11-21 23:09:43.981235: Epoch time: 18.89 s +2024-11-21 23:09:44.889106: +2024-11-21 23:09:44.889327: Epoch 2242 +2024-11-21 23:09:44.889453: Current learning rate: 0.00744 +2024-11-21 23:10:03.866331: train_loss -0.7757 +2024-11-21 23:10:03.889975: val_loss -0.7664 +2024-11-21 23:10:03.890153: Pseudo dice [0.8502] +2024-11-21 23:10:03.890270: Epoch time: 18.98 s +2024-11-21 23:10:04.779412: +2024-11-21 23:10:04.779666: Epoch 2243 +2024-11-21 23:10:04.779784: Current learning rate: 0.00744 +2024-11-21 23:10:22.928400: train_loss -0.7781 +2024-11-21 23:10:22.931409: val_loss -0.7702 +2024-11-21 23:10:22.931520: Pseudo dice [0.8496] +2024-11-21 23:10:22.931620: Epoch time: 18.15 s +2024-11-21 23:10:23.749713: +2024-11-21 23:10:23.749922: Epoch 2244 +2024-11-21 23:10:23.750041: Current learning rate: 0.00744 +2024-11-21 23:10:42.969181: train_loss -0.7685 +2024-11-21 23:10:42.976036: val_loss -0.7585 +2024-11-21 23:10:42.976256: Pseudo dice [0.8527] +2024-11-21 23:10:42.976373: Epoch time: 19.22 s +2024-11-21 23:10:44.000039: +2024-11-21 23:10:44.000237: Epoch 2245 +2024-11-21 23:10:44.000355: Current learning rate: 0.00743 +2024-11-21 23:11:02.097799: train_loss -0.7585 +2024-11-21 23:11:02.106344: val_loss -0.7425 +2024-11-21 23:11:02.106500: Pseudo dice [0.8426] +2024-11-21 23:11:02.106658: Epoch time: 18.1 s +2024-11-21 23:11:02.983761: +2024-11-21 23:11:02.983953: Epoch 2246 +2024-11-21 23:11:02.984084: Current learning rate: 0.00743 +2024-11-21 23:11:22.853238: train_loss -0.7643 +2024-11-21 23:11:22.858242: val_loss -0.7881 +2024-11-21 23:11:22.858371: Pseudo dice [0.8545] +2024-11-21 23:11:22.858478: Epoch time: 19.87 s +2024-11-21 23:11:23.708186: +2024-11-21 23:11:23.708395: Epoch 2247 +2024-11-21 23:11:23.708523: Current learning rate: 0.00743 +2024-11-21 23:11:42.697420: train_loss -0.7773 +2024-11-21 23:11:42.702224: val_loss -0.7636 +2024-11-21 23:11:42.702358: Pseudo dice [0.8623] +2024-11-21 23:11:42.702446: Epoch time: 18.99 s +2024-11-21 23:11:43.526122: +2024-11-21 23:11:43.526339: Epoch 2248 +2024-11-21 23:11:43.526453: Current learning rate: 0.00743 +2024-11-21 23:12:03.156906: train_loss -0.7719 +2024-11-21 23:12:03.163740: val_loss -0.7576 +2024-11-21 23:12:03.163883: Pseudo dice [0.8497] +2024-11-21 23:12:03.163980: Epoch time: 19.63 s +2024-11-21 23:12:03.981738: +2024-11-21 23:12:03.981942: Epoch 2249 +2024-11-21 23:12:03.982075: Current learning rate: 0.00743 +2024-11-21 23:12:23.360463: train_loss -0.7711 +2024-11-21 23:12:23.373550: val_loss -0.7687 +2024-11-21 23:12:23.373695: Pseudo dice [0.8464] +2024-11-21 23:12:23.373786: Epoch time: 19.38 s +2024-11-21 23:12:24.642278: +2024-11-21 23:12:24.642502: Epoch 2250 +2024-11-21 23:12:24.642621: Current learning rate: 0.00743 +2024-11-21 23:12:44.431536: train_loss -0.775 +2024-11-21 23:12:44.437323: val_loss -0.758 +2024-11-21 23:12:44.437452: Pseudo dice [0.8499] +2024-11-21 23:12:44.437536: Epoch time: 19.79 s +2024-11-21 23:12:45.279368: +2024-11-21 23:12:45.279583: Epoch 2251 +2024-11-21 23:12:45.279696: Current learning rate: 0.00743 +2024-11-21 23:13:03.698183: train_loss -0.7727 +2024-11-21 23:13:03.711703: val_loss -0.7516 +2024-11-21 23:13:03.711849: Pseudo dice [0.8527] +2024-11-21 23:13:03.711954: Epoch time: 18.42 s +2024-11-21 23:13:04.599885: +2024-11-21 23:13:04.600127: Epoch 2252 +2024-11-21 23:13:04.600272: Current learning rate: 0.00743 +2024-11-21 23:13:24.331433: train_loss -0.7708 +2024-11-21 23:13:24.340331: val_loss -0.7865 +2024-11-21 23:13:24.340484: Pseudo dice [0.8585] +2024-11-21 23:13:24.340584: Epoch time: 19.73 s +2024-11-21 23:13:25.271322: +2024-11-21 23:13:25.271515: Epoch 2253 +2024-11-21 23:13:25.271636: Current learning rate: 0.00743 +2024-11-21 23:13:45.532258: train_loss -0.7664 +2024-11-21 23:13:45.538915: val_loss -0.7473 +2024-11-21 23:13:45.539057: Pseudo dice [0.8593] +2024-11-21 23:13:45.539156: Epoch time: 20.26 s +2024-11-21 23:13:46.527065: +2024-11-21 23:13:46.527270: Epoch 2254 +2024-11-21 23:13:46.527384: Current learning rate: 0.00742 +2024-11-21 23:14:05.811254: train_loss -0.7713 +2024-11-21 23:14:05.812973: val_loss -0.7713 +2024-11-21 23:14:05.813115: Pseudo dice [0.8509] +2024-11-21 23:14:05.813254: Epoch time: 19.28 s +2024-11-21 23:14:06.637196: +2024-11-21 23:14:06.637430: Epoch 2255 +2024-11-21 23:14:06.637544: Current learning rate: 0.00742 +2024-11-21 23:14:25.819946: train_loss -0.7822 +2024-11-21 23:14:25.826603: val_loss -0.7479 +2024-11-21 23:14:25.826711: Pseudo dice [0.8574] +2024-11-21 23:14:25.826801: Epoch time: 19.18 s +2024-11-21 23:14:26.816706: +2024-11-21 23:14:26.816918: Epoch 2256 +2024-11-21 23:14:26.817039: Current learning rate: 0.00742 +2024-11-21 23:14:45.817512: train_loss -0.7744 +2024-11-21 23:14:45.830038: val_loss -0.7686 +2024-11-21 23:14:45.830193: Pseudo dice [0.8568] +2024-11-21 23:14:45.830273: Epoch time: 19.0 s +2024-11-21 23:14:46.734217: +2024-11-21 23:14:46.734436: Epoch 2257 +2024-11-21 23:14:46.734570: Current learning rate: 0.00742 +2024-11-21 23:15:06.509324: train_loss -0.7763 +2024-11-21 23:15:06.511066: val_loss -0.723 +2024-11-21 23:15:06.511416: Pseudo dice [0.8484] +2024-11-21 23:15:06.511516: Epoch time: 19.78 s +2024-11-21 23:15:07.325635: +2024-11-21 23:15:07.325826: Epoch 2258 +2024-11-21 23:15:07.325950: Current learning rate: 0.00742 +2024-11-21 23:15:24.803787: train_loss -0.7722 +2024-11-21 23:15:24.809905: val_loss -0.7298 +2024-11-21 23:15:24.810027: Pseudo dice [0.847] +2024-11-21 23:15:24.810133: Epoch time: 17.48 s +2024-11-21 23:15:26.066596: +2024-11-21 23:15:26.066811: Epoch 2259 +2024-11-21 23:15:26.066928: Current learning rate: 0.00742 +2024-11-21 23:15:44.995321: train_loss -0.7746 +2024-11-21 23:15:44.997916: val_loss -0.7911 +2024-11-21 23:15:44.998043: Pseudo dice [0.861] +2024-11-21 23:15:44.998134: Epoch time: 18.93 s +2024-11-21 23:15:45.819891: +2024-11-21 23:15:45.820100: Epoch 2260 +2024-11-21 23:15:45.820218: Current learning rate: 0.00742 +2024-11-21 23:16:04.495926: train_loss -0.7684 +2024-11-21 23:16:04.502389: val_loss -0.7372 +2024-11-21 23:16:04.502530: Pseudo dice [0.8332] +2024-11-21 23:16:04.502641: Epoch time: 18.68 s +2024-11-21 23:16:05.615530: +2024-11-21 23:16:05.615734: Epoch 2261 +2024-11-21 23:16:05.615872: Current learning rate: 0.00742 +2024-11-21 23:16:24.345803: train_loss -0.769 +2024-11-21 23:16:24.347542: val_loss -0.7428 +2024-11-21 23:16:24.347645: Pseudo dice [0.8374] +2024-11-21 23:16:24.347723: Epoch time: 18.73 s +2024-11-21 23:16:25.224896: +2024-11-21 23:16:25.225094: Epoch 2262 +2024-11-21 23:16:25.225204: Current learning rate: 0.00741 +2024-11-21 23:16:43.739331: train_loss -0.7708 +2024-11-21 23:16:43.760056: val_loss -0.787 +2024-11-21 23:16:43.760225: Pseudo dice [0.8428] +2024-11-21 23:16:43.760321: Epoch time: 18.52 s +2024-11-21 23:16:44.614173: +2024-11-21 23:16:44.614579: Epoch 2263 +2024-11-21 23:16:44.614707: Current learning rate: 0.00741 +2024-11-21 23:17:03.661704: train_loss -0.7804 +2024-11-21 23:17:03.664422: val_loss -0.774 +2024-11-21 23:17:03.664560: Pseudo dice [0.8482] +2024-11-21 23:17:03.664644: Epoch time: 19.05 s +2024-11-21 23:17:04.487340: +2024-11-21 23:17:04.487540: Epoch 2264 +2024-11-21 23:17:04.487661: Current learning rate: 0.00741 +2024-11-21 23:17:23.921954: train_loss -0.7717 +2024-11-21 23:17:23.930353: val_loss -0.7583 +2024-11-21 23:17:23.930556: Pseudo dice [0.843] +2024-11-21 23:17:23.930654: Epoch time: 19.44 s +2024-11-21 23:17:24.780265: +2024-11-21 23:17:24.780467: Epoch 2265 +2024-11-21 23:17:24.780588: Current learning rate: 0.00741 +2024-11-21 23:17:44.191386: train_loss -0.7748 +2024-11-21 23:17:44.200102: val_loss -0.7705 +2024-11-21 23:17:44.200224: Pseudo dice [0.8374] +2024-11-21 23:17:44.200316: Epoch time: 19.41 s +2024-11-21 23:17:45.016885: +2024-11-21 23:17:45.017125: Epoch 2266 +2024-11-21 23:17:45.017256: Current learning rate: 0.00741 +2024-11-21 23:18:04.530793: train_loss -0.7845 +2024-11-21 23:18:04.535663: val_loss -0.7539 +2024-11-21 23:18:04.535786: Pseudo dice [0.8589] +2024-11-21 23:18:04.535897: Epoch time: 19.51 s +2024-11-21 23:18:05.355237: +2024-11-21 23:18:05.355447: Epoch 2267 +2024-11-21 23:18:05.355598: Current learning rate: 0.00741 +2024-11-21 23:18:23.724519: train_loss -0.7648 +2024-11-21 23:18:23.730631: val_loss -0.7718 +2024-11-21 23:18:23.730770: Pseudo dice [0.8595] +2024-11-21 23:18:23.730863: Epoch time: 18.37 s +2024-11-21 23:18:24.672229: +2024-11-21 23:18:24.672428: Epoch 2268 +2024-11-21 23:18:24.672562: Current learning rate: 0.00741 +2024-11-21 23:18:43.136395: train_loss -0.774 +2024-11-21 23:18:43.142513: val_loss -0.7713 +2024-11-21 23:18:43.142662: Pseudo dice [0.848] +2024-11-21 23:18:43.142810: Epoch time: 18.46 s +2024-11-21 23:18:43.962754: +2024-11-21 23:18:43.962989: Epoch 2269 +2024-11-21 23:18:43.963138: Current learning rate: 0.00741 +2024-11-21 23:19:02.364691: train_loss -0.7696 +2024-11-21 23:19:02.371414: val_loss -0.7567 +2024-11-21 23:19:02.371555: Pseudo dice [0.8495] +2024-11-21 23:19:02.371643: Epoch time: 18.4 s +2024-11-21 23:19:03.237888: +2024-11-21 23:19:03.238120: Epoch 2270 +2024-11-21 23:19:03.238253: Current learning rate: 0.00741 +2024-11-21 23:19:22.128578: train_loss -0.7829 +2024-11-21 23:19:22.137319: val_loss -0.7644 +2024-11-21 23:19:22.137465: Pseudo dice [0.8582] +2024-11-21 23:19:22.137555: Epoch time: 18.89 s +2024-11-21 23:19:23.246750: +2024-11-21 23:19:23.246978: Epoch 2271 +2024-11-21 23:19:23.247115: Current learning rate: 0.0074 +2024-11-21 23:19:41.644906: train_loss -0.776 +2024-11-21 23:19:41.676190: val_loss -0.7446 +2024-11-21 23:19:41.676357: Pseudo dice [0.8458] +2024-11-21 23:19:41.676457: Epoch time: 18.4 s +2024-11-21 23:19:42.560751: +2024-11-21 23:19:42.560982: Epoch 2272 +2024-11-21 23:19:42.561106: Current learning rate: 0.0074 +2024-11-21 23:20:02.387704: train_loss -0.7747 +2024-11-21 23:20:02.395360: val_loss -0.7598 +2024-11-21 23:20:02.395495: Pseudo dice [0.8474] +2024-11-21 23:20:02.395586: Epoch time: 19.83 s +2024-11-21 23:20:03.250641: +2024-11-21 23:20:03.250892: Epoch 2273 +2024-11-21 23:20:03.251024: Current learning rate: 0.0074 +2024-11-21 23:20:23.059899: train_loss -0.7809 +2024-11-21 23:20:23.073916: val_loss -0.7837 +2024-11-21 23:20:23.074066: Pseudo dice [0.8471] +2024-11-21 23:20:23.074153: Epoch time: 19.81 s +2024-11-21 23:20:23.907269: +2024-11-21 23:20:23.907466: Epoch 2274 +2024-11-21 23:20:23.907588: Current learning rate: 0.0074 +2024-11-21 23:20:44.517668: train_loss -0.7786 +2024-11-21 23:20:44.520945: val_loss -0.7961 +2024-11-21 23:20:44.521076: Pseudo dice [0.8588] +2024-11-21 23:20:44.521178: Epoch time: 20.61 s +2024-11-21 23:20:45.464127: +2024-11-21 23:20:45.464356: Epoch 2275 +2024-11-21 23:20:45.464484: Current learning rate: 0.0074 +2024-11-21 23:21:03.601923: train_loss -0.7802 +2024-11-21 23:21:03.610404: val_loss -0.7675 +2024-11-21 23:21:03.610572: Pseudo dice [0.8523] +2024-11-21 23:21:03.610659: Epoch time: 18.14 s +2024-11-21 23:21:04.446653: +2024-11-21 23:21:04.446837: Epoch 2276 +2024-11-21 23:21:04.446954: Current learning rate: 0.0074 +2024-11-21 23:21:23.642044: train_loss -0.772 +2024-11-21 23:21:23.652158: val_loss -0.7763 +2024-11-21 23:21:23.652302: Pseudo dice [0.8498] +2024-11-21 23:21:23.652402: Epoch time: 19.2 s +2024-11-21 23:21:24.470759: +2024-11-21 23:21:24.470971: Epoch 2277 +2024-11-21 23:21:24.471092: Current learning rate: 0.0074 +2024-11-21 23:21:43.795833: train_loss -0.7695 +2024-11-21 23:21:43.804795: val_loss -0.7601 +2024-11-21 23:21:43.804925: Pseudo dice [0.8543] +2024-11-21 23:21:43.805027: Epoch time: 19.33 s +2024-11-21 23:21:44.640321: +2024-11-21 23:21:44.640548: Epoch 2278 +2024-11-21 23:21:44.640716: Current learning rate: 0.0074 +2024-11-21 23:22:03.355402: train_loss -0.7716 +2024-11-21 23:22:03.370436: val_loss -0.7594 +2024-11-21 23:22:03.370587: Pseudo dice [0.8336] +2024-11-21 23:22:03.370803: Epoch time: 18.72 s +2024-11-21 23:22:04.228273: +2024-11-21 23:22:04.228493: Epoch 2279 +2024-11-21 23:22:04.228611: Current learning rate: 0.0074 +2024-11-21 23:22:23.429515: train_loss -0.7748 +2024-11-21 23:22:23.448128: val_loss -0.7602 +2024-11-21 23:22:23.448265: Pseudo dice [0.849] +2024-11-21 23:22:23.448355: Epoch time: 19.2 s +2024-11-21 23:22:24.307878: +2024-11-21 23:22:24.308076: Epoch 2280 +2024-11-21 23:22:24.308188: Current learning rate: 0.00739 +2024-11-21 23:22:44.673762: train_loss -0.7678 +2024-11-21 23:22:44.680406: val_loss -0.7701 +2024-11-21 23:22:44.680529: Pseudo dice [0.8427] +2024-11-21 23:22:44.680638: Epoch time: 20.37 s +2024-11-21 23:22:45.517856: +2024-11-21 23:22:45.518087: Epoch 2281 +2024-11-21 23:22:45.518207: Current learning rate: 0.00739 +2024-11-21 23:23:05.484261: train_loss -0.7563 +2024-11-21 23:23:05.491648: val_loss -0.7414 +2024-11-21 23:23:05.491840: Pseudo dice [0.8542] +2024-11-21 23:23:05.491956: Epoch time: 19.97 s +2024-11-21 23:23:06.836194: +2024-11-21 23:23:06.836408: Epoch 2282 +2024-11-21 23:23:06.836517: Current learning rate: 0.00739 +2024-11-21 23:23:25.493207: train_loss -0.7797 +2024-11-21 23:23:25.507415: val_loss -0.7269 +2024-11-21 23:23:25.507565: Pseudo dice [0.8287] +2024-11-21 23:23:25.507651: Epoch time: 18.66 s +2024-11-21 23:23:26.493722: +2024-11-21 23:23:26.494203: Epoch 2283 +2024-11-21 23:23:26.494333: Current learning rate: 0.00739 +2024-11-21 23:23:45.020699: train_loss -0.7706 +2024-11-21 23:23:45.027294: val_loss -0.7553 +2024-11-21 23:23:45.027430: Pseudo dice [0.8419] +2024-11-21 23:23:45.027514: Epoch time: 18.53 s +2024-11-21 23:23:45.932264: +2024-11-21 23:23:45.932467: Epoch 2284 +2024-11-21 23:23:45.932587: Current learning rate: 0.00739 +2024-11-21 23:24:05.138489: train_loss -0.7706 +2024-11-21 23:24:05.145305: val_loss -0.7736 +2024-11-21 23:24:05.145446: Pseudo dice [0.854] +2024-11-21 23:24:05.145533: Epoch time: 19.21 s +2024-11-21 23:24:06.227822: +2024-11-21 23:24:06.228072: Epoch 2285 +2024-11-21 23:24:06.228204: Current learning rate: 0.00739 +2024-11-21 23:24:24.562919: train_loss -0.7695 +2024-11-21 23:24:24.568643: val_loss -0.7591 +2024-11-21 23:24:24.568795: Pseudo dice [0.8401] +2024-11-21 23:24:24.568903: Epoch time: 18.34 s +2024-11-21 23:24:25.386863: +2024-11-21 23:24:25.387106: Epoch 2286 +2024-11-21 23:24:25.387238: Current learning rate: 0.00739 +2024-11-21 23:24:43.038724: train_loss -0.7691 +2024-11-21 23:24:43.045616: val_loss -0.7527 +2024-11-21 23:24:43.045746: Pseudo dice [0.8472] +2024-11-21 23:24:43.045827: Epoch time: 17.65 s +2024-11-21 23:24:43.880591: +2024-11-21 23:24:43.880794: Epoch 2287 +2024-11-21 23:24:43.880912: Current learning rate: 0.00739 +2024-11-21 23:25:03.240208: train_loss -0.7695 +2024-11-21 23:25:03.255913: val_loss -0.7549 +2024-11-21 23:25:03.256078: Pseudo dice [0.8385] +2024-11-21 23:25:03.256178: Epoch time: 19.36 s +2024-11-21 23:25:04.107326: +2024-11-21 23:25:04.107547: Epoch 2288 +2024-11-21 23:25:04.107667: Current learning rate: 0.00738 +2024-11-21 23:25:22.514009: train_loss -0.7717 +2024-11-21 23:25:22.516283: val_loss -0.7255 +2024-11-21 23:25:22.516386: Pseudo dice [0.8311] +2024-11-21 23:25:22.516477: Epoch time: 18.41 s +2024-11-21 23:25:23.332921: +2024-11-21 23:25:23.333138: Epoch 2289 +2024-11-21 23:25:23.333265: Current learning rate: 0.00738 +2024-11-21 23:25:43.187637: train_loss -0.7678 +2024-11-21 23:25:43.201163: val_loss -0.7484 +2024-11-21 23:25:43.201305: Pseudo dice [0.8494] +2024-11-21 23:25:43.201407: Epoch time: 19.86 s +2024-11-21 23:25:44.027250: +2024-11-21 23:25:44.027450: Epoch 2290 +2024-11-21 23:25:44.027566: Current learning rate: 0.00738 +2024-11-21 23:26:03.294616: train_loss -0.7318 +2024-11-21 23:26:03.302328: val_loss -0.711 +2024-11-21 23:26:03.302463: Pseudo dice [0.8126] +2024-11-21 23:26:03.302559: Epoch time: 19.27 s +2024-11-21 23:26:04.148729: +2024-11-21 23:26:04.149020: Epoch 2291 +2024-11-21 23:26:04.149148: Current learning rate: 0.00738 +2024-11-21 23:26:24.218999: train_loss -0.7413 +2024-11-21 23:26:24.226242: val_loss -0.7194 +2024-11-21 23:26:24.226377: Pseudo dice [0.8382] +2024-11-21 23:26:24.226481: Epoch time: 20.07 s +2024-11-21 23:26:25.332835: +2024-11-21 23:26:25.333030: Epoch 2292 +2024-11-21 23:26:25.333163: Current learning rate: 0.00738 +2024-11-21 23:26:43.942331: train_loss -0.7574 +2024-11-21 23:26:43.951011: val_loss -0.767 +2024-11-21 23:26:43.951213: Pseudo dice [0.8529] +2024-11-21 23:26:43.951317: Epoch time: 18.61 s +2024-11-21 23:26:44.783993: +2024-11-21 23:26:44.784241: Epoch 2293 +2024-11-21 23:26:44.784362: Current learning rate: 0.00738 +2024-11-21 23:27:03.925441: train_loss -0.7609 +2024-11-21 23:27:03.930068: val_loss -0.7472 +2024-11-21 23:27:03.930208: Pseudo dice [0.8299] +2024-11-21 23:27:03.930308: Epoch time: 19.14 s +2024-11-21 23:27:04.879439: +2024-11-21 23:27:04.879683: Epoch 2294 +2024-11-21 23:27:04.879817: Current learning rate: 0.00738 +2024-11-21 23:27:24.538216: train_loss -0.7567 +2024-11-21 23:27:24.544363: val_loss -0.7507 +2024-11-21 23:27:24.544513: Pseudo dice [0.8206] +2024-11-21 23:27:24.544627: Epoch time: 19.66 s +2024-11-21 23:27:25.541560: +2024-11-21 23:27:25.541756: Epoch 2295 +2024-11-21 23:27:25.541871: Current learning rate: 0.00738 +2024-11-21 23:27:44.809258: train_loss -0.7507 +2024-11-21 23:27:44.816473: val_loss -0.7507 +2024-11-21 23:27:44.816602: Pseudo dice [0.8408] +2024-11-21 23:27:44.833506: Epoch time: 19.27 s +2024-11-21 23:27:45.795631: +2024-11-21 23:27:45.795900: Epoch 2296 +2024-11-21 23:27:45.796023: Current learning rate: 0.00738 +2024-11-21 23:28:04.730684: train_loss -0.7565 +2024-11-21 23:28:04.736600: val_loss -0.771 +2024-11-21 23:28:04.736727: Pseudo dice [0.8537] +2024-11-21 23:28:04.736828: Epoch time: 18.94 s +2024-11-21 23:28:05.580424: +2024-11-21 23:28:05.580620: Epoch 2297 +2024-11-21 23:28:05.580758: Current learning rate: 0.00737 +2024-11-21 23:28:25.323758: train_loss -0.7581 +2024-11-21 23:28:25.327567: val_loss -0.7625 +2024-11-21 23:28:25.327665: Pseudo dice [0.8463] +2024-11-21 23:28:25.327768: Epoch time: 19.74 s +2024-11-21 23:28:26.144541: +2024-11-21 23:28:26.144777: Epoch 2298 +2024-11-21 23:28:26.144912: Current learning rate: 0.00737 +2024-11-21 23:28:44.732674: train_loss -0.7583 +2024-11-21 23:28:44.737482: val_loss -0.7545 +2024-11-21 23:28:44.737628: Pseudo dice [0.8418] +2024-11-21 23:28:44.737710: Epoch time: 18.59 s +2024-11-21 23:28:45.626314: +2024-11-21 23:28:45.626510: Epoch 2299 +2024-11-21 23:28:45.626643: Current learning rate: 0.00737 +2024-11-21 23:29:03.551486: train_loss -0.7648 +2024-11-21 23:29:03.556664: val_loss -0.7654 +2024-11-21 23:29:03.556788: Pseudo dice [0.8367] +2024-11-21 23:29:03.556889: Epoch time: 17.93 s +2024-11-21 23:29:04.725966: +2024-11-21 23:29:04.726168: Epoch 2300 +2024-11-21 23:29:04.726301: Current learning rate: 0.00737 +2024-11-21 23:29:23.718362: train_loss -0.7726 +2024-11-21 23:29:23.721025: val_loss -0.7321 +2024-11-21 23:29:23.721130: Pseudo dice [0.8383] +2024-11-21 23:29:23.721221: Epoch time: 18.99 s +2024-11-21 23:29:24.543237: +2024-11-21 23:29:24.543454: Epoch 2301 +2024-11-21 23:29:24.543568: Current learning rate: 0.00737 +2024-11-21 23:29:44.283114: train_loss -0.7632 +2024-11-21 23:29:44.288781: val_loss -0.7651 +2024-11-21 23:29:44.288924: Pseudo dice [0.8405] +2024-11-21 23:29:44.289034: Epoch time: 19.74 s +2024-11-21 23:29:45.137539: +2024-11-21 23:29:45.137742: Epoch 2302 +2024-11-21 23:29:45.137862: Current learning rate: 0.00737 +2024-11-21 23:30:04.023854: train_loss -0.7683 +2024-11-21 23:30:04.039422: val_loss -0.7534 +2024-11-21 23:30:04.039573: Pseudo dice [0.8487] +2024-11-21 23:30:04.039670: Epoch time: 18.89 s +2024-11-21 23:30:04.923504: +2024-11-21 23:30:04.923761: Epoch 2303 +2024-11-21 23:30:04.923877: Current learning rate: 0.00737 +2024-11-21 23:30:24.130108: train_loss -0.7759 +2024-11-21 23:30:24.140080: val_loss -0.7542 +2024-11-21 23:30:24.140238: Pseudo dice [0.8487] +2024-11-21 23:30:24.140347: Epoch time: 19.21 s +2024-11-21 23:30:25.032544: +2024-11-21 23:30:25.032941: Epoch 2304 +2024-11-21 23:30:25.033087: Current learning rate: 0.00737 +2024-11-21 23:30:44.841079: train_loss -0.7904 +2024-11-21 23:30:44.849202: val_loss -0.7709 +2024-11-21 23:30:44.849344: Pseudo dice [0.8603] +2024-11-21 23:30:44.849435: Epoch time: 19.81 s +2024-11-21 23:30:46.112478: +2024-11-21 23:30:46.112671: Epoch 2305 +2024-11-21 23:30:46.112785: Current learning rate: 0.00736 +2024-11-21 23:31:05.000355: train_loss -0.7811 +2024-11-21 23:31:05.003054: val_loss -0.7718 +2024-11-21 23:31:05.003184: Pseudo dice [0.8403] +2024-11-21 23:31:05.003271: Epoch time: 18.89 s +2024-11-21 23:31:05.818205: +2024-11-21 23:31:05.818423: Epoch 2306 +2024-11-21 23:31:05.818556: Current learning rate: 0.00736 +2024-11-21 23:31:25.318817: train_loss -0.777 +2024-11-21 23:31:25.326761: val_loss -0.7654 +2024-11-21 23:31:25.326878: Pseudo dice [0.8412] +2024-11-21 23:31:25.326968: Epoch time: 19.5 s +2024-11-21 23:31:26.219703: +2024-11-21 23:31:26.219904: Epoch 2307 +2024-11-21 23:31:26.220034: Current learning rate: 0.00736 +2024-11-21 23:31:44.482204: train_loss -0.7766 +2024-11-21 23:31:44.489836: val_loss -0.7263 +2024-11-21 23:31:44.489972: Pseudo dice [0.8523] +2024-11-21 23:31:44.490073: Epoch time: 18.26 s +2024-11-21 23:31:45.327962: +2024-11-21 23:31:45.328198: Epoch 2308 +2024-11-21 23:31:45.328329: Current learning rate: 0.00736 +2024-11-21 23:32:05.037959: train_loss -0.7847 +2024-11-21 23:32:05.060284: val_loss -0.7523 +2024-11-21 23:32:05.060445: Pseudo dice [0.8359] +2024-11-21 23:32:05.060542: Epoch time: 19.71 s +2024-11-21 23:32:05.899613: +2024-11-21 23:32:05.899802: Epoch 2309 +2024-11-21 23:32:05.899933: Current learning rate: 0.00736 +2024-11-21 23:32:26.529065: train_loss -0.7817 +2024-11-21 23:32:26.537645: val_loss -0.739 +2024-11-21 23:32:26.537776: Pseudo dice [0.849] +2024-11-21 23:32:26.537864: Epoch time: 20.63 s +2024-11-21 23:32:27.407364: +2024-11-21 23:32:27.407859: Epoch 2310 +2024-11-21 23:32:27.407975: Current learning rate: 0.00736 +2024-11-21 23:32:46.637867: train_loss -0.7691 +2024-11-21 23:32:46.644042: val_loss -0.7645 +2024-11-21 23:32:46.644276: Pseudo dice [0.8459] +2024-11-21 23:32:46.644397: Epoch time: 19.23 s +2024-11-21 23:32:47.561692: +2024-11-21 23:32:47.561888: Epoch 2311 +2024-11-21 23:32:47.562029: Current learning rate: 0.00736 +2024-11-21 23:33:05.974846: train_loss -0.777 +2024-11-21 23:33:05.981957: val_loss -0.7355 +2024-11-21 23:33:05.982099: Pseudo dice [0.8352] +2024-11-21 23:33:05.982206: Epoch time: 18.41 s +2024-11-21 23:33:06.824838: +2024-11-21 23:33:06.825074: Epoch 2312 +2024-11-21 23:33:06.825210: Current learning rate: 0.00736 +2024-11-21 23:33:26.255105: train_loss -0.7757 +2024-11-21 23:33:26.263588: val_loss -0.7803 +2024-11-21 23:33:26.263722: Pseudo dice [0.8501] +2024-11-21 23:33:26.263819: Epoch time: 19.43 s +2024-11-21 23:33:27.270082: +2024-11-21 23:33:27.270292: Epoch 2313 +2024-11-21 23:33:27.270406: Current learning rate: 0.00736 +2024-11-21 23:33:46.838410: train_loss -0.7608 +2024-11-21 23:33:46.840541: val_loss -0.7566 +2024-11-21 23:33:46.840634: Pseudo dice [0.8388] +2024-11-21 23:33:46.840730: Epoch time: 19.57 s +2024-11-21 23:33:47.649873: +2024-11-21 23:33:47.650129: Epoch 2314 +2024-11-21 23:33:47.650267: Current learning rate: 0.00735 +2024-11-21 23:34:06.712278: train_loss -0.7665 +2024-11-21 23:34:06.725734: val_loss -0.7326 +2024-11-21 23:34:06.725896: Pseudo dice [0.8507] +2024-11-21 23:34:06.726012: Epoch time: 19.06 s +2024-11-21 23:34:07.701930: +2024-11-21 23:34:07.702199: Epoch 2315 +2024-11-21 23:34:07.702328: Current learning rate: 0.00735 +2024-11-21 23:34:26.578197: train_loss -0.7783 +2024-11-21 23:34:26.589886: val_loss -0.7848 +2024-11-21 23:34:26.590028: Pseudo dice [0.8502] +2024-11-21 23:34:26.590132: Epoch time: 18.88 s +2024-11-21 23:34:27.546837: +2024-11-21 23:34:27.547035: Epoch 2316 +2024-11-21 23:34:27.547158: Current learning rate: 0.00735 +2024-11-21 23:34:46.862619: train_loss -0.769 +2024-11-21 23:34:46.870247: val_loss -0.749 +2024-11-21 23:34:46.870399: Pseudo dice [0.8383] +2024-11-21 23:34:46.870485: Epoch time: 19.32 s +2024-11-21 23:34:47.741765: +2024-11-21 23:34:47.742011: Epoch 2317 +2024-11-21 23:34:47.742140: Current learning rate: 0.00735 +2024-11-21 23:35:07.014185: train_loss -0.777 +2024-11-21 23:35:07.016583: val_loss -0.7657 +2024-11-21 23:35:07.016696: Pseudo dice [0.8542] +2024-11-21 23:35:07.016798: Epoch time: 19.27 s +2024-11-21 23:35:07.829509: +2024-11-21 23:35:07.829724: Epoch 2318 +2024-11-21 23:35:07.829849: Current learning rate: 0.00735 +2024-11-21 23:35:28.042860: train_loss -0.7778 +2024-11-21 23:35:28.044709: val_loss -0.7565 +2024-11-21 23:35:28.044821: Pseudo dice [0.8478] +2024-11-21 23:35:28.044923: Epoch time: 20.21 s +2024-11-21 23:35:28.858084: +2024-11-21 23:35:28.858314: Epoch 2319 +2024-11-21 23:35:28.858433: Current learning rate: 0.00735 +2024-11-21 23:35:48.374036: train_loss -0.7821 +2024-11-21 23:35:48.376986: val_loss -0.7575 +2024-11-21 23:35:48.377177: Pseudo dice [0.8412] +2024-11-21 23:35:48.377362: Epoch time: 19.52 s +2024-11-21 23:35:49.289905: +2024-11-21 23:35:49.290121: Epoch 2320 +2024-11-21 23:35:49.290251: Current learning rate: 0.00735 +2024-11-21 23:36:09.162361: train_loss -0.7795 +2024-11-21 23:36:09.169954: val_loss -0.7857 +2024-11-21 23:36:09.170112: Pseudo dice [0.8538] +2024-11-21 23:36:09.170205: Epoch time: 19.87 s +2024-11-21 23:36:10.012277: +2024-11-21 23:36:10.012504: Epoch 2321 +2024-11-21 23:36:10.012894: Current learning rate: 0.00735 +2024-11-21 23:36:29.624067: train_loss -0.7778 +2024-11-21 23:36:29.633701: val_loss -0.7522 +2024-11-21 23:36:29.633857: Pseudo dice [0.8523] +2024-11-21 23:36:29.633988: Epoch time: 19.61 s +2024-11-21 23:36:30.617725: +2024-11-21 23:36:30.617943: Epoch 2322 +2024-11-21 23:36:30.618082: Current learning rate: 0.00735 +2024-11-21 23:36:49.648623: train_loss -0.7673 +2024-11-21 23:36:49.655607: val_loss -0.7485 +2024-11-21 23:36:49.655758: Pseudo dice [0.848] +2024-11-21 23:36:49.655856: Epoch time: 19.03 s +2024-11-21 23:36:50.530287: +2024-11-21 23:36:50.530481: Epoch 2323 +2024-11-21 23:36:50.530605: Current learning rate: 0.00734 +2024-11-21 23:37:09.168012: train_loss -0.7609 +2024-11-21 23:37:09.193827: val_loss -0.7566 +2024-11-21 23:37:09.194001: Pseudo dice [0.8479] +2024-11-21 23:37:09.194111: Epoch time: 18.64 s +2024-11-21 23:37:10.154427: +2024-11-21 23:37:10.154628: Epoch 2324 +2024-11-21 23:37:10.154742: Current learning rate: 0.00734 +2024-11-21 23:37:28.963299: train_loss -0.7555 +2024-11-21 23:37:28.970915: val_loss -0.7589 +2024-11-21 23:37:28.971043: Pseudo dice [0.8403] +2024-11-21 23:37:28.971160: Epoch time: 18.81 s +2024-11-21 23:37:29.871125: +2024-11-21 23:37:29.871358: Epoch 2325 +2024-11-21 23:37:29.871502: Current learning rate: 0.00734 +2024-11-21 23:37:48.431746: train_loss -0.7641 +2024-11-21 23:37:48.438463: val_loss -0.7766 +2024-11-21 23:37:48.438601: Pseudo dice [0.8569] +2024-11-21 23:37:48.438693: Epoch time: 18.56 s +2024-11-21 23:37:49.261551: +2024-11-21 23:37:49.261742: Epoch 2326 +2024-11-21 23:37:49.261855: Current learning rate: 0.00734 +2024-11-21 23:38:08.263833: train_loss -0.7702 +2024-11-21 23:38:08.269374: val_loss -0.7498 +2024-11-21 23:38:08.269493: Pseudo dice [0.8549] +2024-11-21 23:38:08.269588: Epoch time: 19.0 s +2024-11-21 23:38:09.079475: +2024-11-21 23:38:09.079684: Epoch 2327 +2024-11-21 23:38:09.079814: Current learning rate: 0.00734 +2024-11-21 23:38:26.934603: train_loss -0.7813 +2024-11-21 23:38:26.936255: val_loss -0.7757 +2024-11-21 23:38:26.936348: Pseudo dice [0.8504] +2024-11-21 23:38:26.936441: Epoch time: 17.86 s +2024-11-21 23:38:28.116942: +2024-11-21 23:38:28.117154: Epoch 2328 +2024-11-21 23:38:28.117271: Current learning rate: 0.00734 +2024-11-21 23:38:47.228398: train_loss -0.7684 +2024-11-21 23:38:47.241171: val_loss -0.7647 +2024-11-21 23:38:47.241349: Pseudo dice [0.8293] +2024-11-21 23:38:47.241444: Epoch time: 19.11 s +2024-11-21 23:38:48.108346: +2024-11-21 23:38:48.108570: Epoch 2329 +2024-11-21 23:38:48.108710: Current learning rate: 0.00734 +2024-11-21 23:39:08.109734: train_loss -0.7699 +2024-11-21 23:39:08.112450: val_loss -0.765 +2024-11-21 23:39:08.112545: Pseudo dice [0.8425] +2024-11-21 23:39:08.112626: Epoch time: 20.0 s +2024-11-21 23:39:08.924901: +2024-11-21 23:39:08.925108: Epoch 2330 +2024-11-21 23:39:08.925228: Current learning rate: 0.00734 +2024-11-21 23:39:28.673478: train_loss -0.7721 +2024-11-21 23:39:28.681227: val_loss -0.7689 +2024-11-21 23:39:28.681372: Pseudo dice [0.8543] +2024-11-21 23:39:28.681452: Epoch time: 19.75 s +2024-11-21 23:39:29.777286: +2024-11-21 23:39:29.777504: Epoch 2331 +2024-11-21 23:39:29.777629: Current learning rate: 0.00733 +2024-11-21 23:39:48.989817: train_loss -0.7705 +2024-11-21 23:39:48.997432: val_loss -0.7615 +2024-11-21 23:39:48.997561: Pseudo dice [0.8413] +2024-11-21 23:39:48.997645: Epoch time: 19.21 s +2024-11-21 23:39:49.907986: +2024-11-21 23:39:49.908206: Epoch 2332 +2024-11-21 23:39:49.908338: Current learning rate: 0.00733 +2024-11-21 23:40:09.767139: train_loss -0.7765 +2024-11-21 23:40:09.781887: val_loss -0.7748 +2024-11-21 23:40:09.782037: Pseudo dice [0.8412] +2024-11-21 23:40:09.782137: Epoch time: 19.86 s +2024-11-21 23:40:10.638012: +2024-11-21 23:40:10.638244: Epoch 2333 +2024-11-21 23:40:10.638374: Current learning rate: 0.00733 +2024-11-21 23:40:29.167095: train_loss -0.785 +2024-11-21 23:40:29.171510: val_loss -0.7773 +2024-11-21 23:40:29.171672: Pseudo dice [0.8493] +2024-11-21 23:40:29.172009: Epoch time: 18.53 s +2024-11-21 23:40:30.082812: +2024-11-21 23:40:30.083043: Epoch 2334 +2024-11-21 23:40:30.083179: Current learning rate: 0.00733 +2024-11-21 23:40:49.298299: train_loss -0.779 +2024-11-21 23:40:49.312105: val_loss -0.7452 +2024-11-21 23:40:49.312240: Pseudo dice [0.8505] +2024-11-21 23:40:49.312337: Epoch time: 19.22 s +2024-11-21 23:40:50.312095: +2024-11-21 23:40:50.312308: Epoch 2335 +2024-11-21 23:40:50.312438: Current learning rate: 0.00733 +2024-11-21 23:41:09.103772: train_loss -0.7692 +2024-11-21 23:41:09.111850: val_loss -0.7633 +2024-11-21 23:41:09.111982: Pseudo dice [0.8441] +2024-11-21 23:41:09.112074: Epoch time: 18.79 s +2024-11-21 23:41:10.111403: +2024-11-21 23:41:10.111597: Epoch 2336 +2024-11-21 23:41:10.111745: Current learning rate: 0.00733 +2024-11-21 23:41:28.373575: train_loss -0.7795 +2024-11-21 23:41:28.379185: val_loss -0.7342 +2024-11-21 23:41:28.379327: Pseudo dice [0.8368] +2024-11-21 23:41:28.379435: Epoch time: 18.26 s +2024-11-21 23:41:29.270644: +2024-11-21 23:41:29.270860: Epoch 2337 +2024-11-21 23:41:29.270977: Current learning rate: 0.00733 +2024-11-21 23:41:49.056053: train_loss -0.7819 +2024-11-21 23:41:49.058065: val_loss -0.76 +2024-11-21 23:41:49.058161: Pseudo dice [0.8418] +2024-11-21 23:41:49.058246: Epoch time: 19.79 s +2024-11-21 23:41:49.869676: +2024-11-21 23:41:49.869870: Epoch 2338 +2024-11-21 23:41:49.869986: Current learning rate: 0.00733 +2024-11-21 23:42:09.216235: train_loss -0.7808 +2024-11-21 23:42:09.221561: val_loss -0.7456 +2024-11-21 23:42:09.221699: Pseudo dice [0.842] +2024-11-21 23:42:09.221787: Epoch time: 19.35 s +2024-11-21 23:42:10.104179: +2024-11-21 23:42:10.104375: Epoch 2339 +2024-11-21 23:42:10.104491: Current learning rate: 0.00733 +2024-11-21 23:42:28.914595: train_loss -0.7723 +2024-11-21 23:42:28.916835: val_loss -0.756 +2024-11-21 23:42:28.916994: Pseudo dice [0.84] +2024-11-21 23:42:28.917124: Epoch time: 18.81 s +2024-11-21 23:42:29.720960: +2024-11-21 23:42:29.721172: Epoch 2340 +2024-11-21 23:42:29.721300: Current learning rate: 0.00732 +2024-11-21 23:42:48.207828: train_loss -0.7896 +2024-11-21 23:42:48.212896: val_loss -0.7797 +2024-11-21 23:42:48.213056: Pseudo dice [0.8509] +2024-11-21 23:42:48.213764: Epoch time: 18.49 s +2024-11-21 23:42:49.027478: +2024-11-21 23:42:49.027697: Epoch 2341 +2024-11-21 23:42:49.027816: Current learning rate: 0.00732 +2024-11-21 23:43:08.588301: train_loss -0.7705 +2024-11-21 23:43:08.592843: val_loss -0.7446 +2024-11-21 23:43:08.593000: Pseudo dice [0.828] +2024-11-21 23:43:08.593107: Epoch time: 19.56 s +2024-11-21 23:43:09.458270: +2024-11-21 23:43:09.458477: Epoch 2342 +2024-11-21 23:43:09.458604: Current learning rate: 0.00732 +2024-11-21 23:43:29.751557: train_loss -0.7569 +2024-11-21 23:43:29.759354: val_loss -0.7654 +2024-11-21 23:43:29.759476: Pseudo dice [0.8392] +2024-11-21 23:43:29.759579: Epoch time: 20.29 s +2024-11-21 23:43:30.594457: +2024-11-21 23:43:30.594685: Epoch 2343 +2024-11-21 23:43:30.594807: Current learning rate: 0.00732 +2024-11-21 23:43:50.391857: train_loss -0.7673 +2024-11-21 23:43:50.393522: val_loss -0.7533 +2024-11-21 23:43:50.393621: Pseudo dice [0.8452] +2024-11-21 23:43:50.393723: Epoch time: 19.8 s +2024-11-21 23:43:51.212440: +2024-11-21 23:43:51.212730: Epoch 2344 +2024-11-21 23:43:51.212849: Current learning rate: 0.00732 +2024-11-21 23:44:09.413596: train_loss -0.7764 +2024-11-21 23:44:09.424435: val_loss -0.772 +2024-11-21 23:44:09.424612: Pseudo dice [0.8423] +2024-11-21 23:44:09.424715: Epoch time: 18.2 s +2024-11-21 23:44:10.412588: +2024-11-21 23:44:10.412795: Epoch 2345 +2024-11-21 23:44:10.412925: Current learning rate: 0.00732 +2024-11-21 23:44:28.756632: train_loss -0.7733 +2024-11-21 23:44:28.762381: val_loss -0.7786 +2024-11-21 23:44:28.762520: Pseudo dice [0.8635] +2024-11-21 23:44:28.762601: Epoch time: 18.34 s +2024-11-21 23:44:29.574556: +2024-11-21 23:44:29.574753: Epoch 2346 +2024-11-21 23:44:29.574877: Current learning rate: 0.00732 +2024-11-21 23:44:49.038054: train_loss -0.7761 +2024-11-21 23:44:49.048669: val_loss -0.7573 +2024-11-21 23:44:49.049070: Pseudo dice [0.8424] +2024-11-21 23:44:49.049169: Epoch time: 19.46 s +2024-11-21 23:44:49.915071: +2024-11-21 23:44:49.915272: Epoch 2347 +2024-11-21 23:44:49.915391: Current learning rate: 0.00732 +2024-11-21 23:45:09.137354: train_loss -0.7711 +2024-11-21 23:45:09.144688: val_loss -0.7654 +2024-11-21 23:45:09.144833: Pseudo dice [0.839] +2024-11-21 23:45:09.144938: Epoch time: 19.22 s +2024-11-21 23:45:09.975783: +2024-11-21 23:45:09.975992: Epoch 2348 +2024-11-21 23:45:09.976112: Current learning rate: 0.00731 +2024-11-21 23:45:28.604459: train_loss -0.7731 +2024-11-21 23:45:28.616805: val_loss -0.7654 +2024-11-21 23:45:28.616958: Pseudo dice [0.836] +2024-11-21 23:45:28.617049: Epoch time: 18.63 s +2024-11-21 23:45:29.665953: +2024-11-21 23:45:29.666183: Epoch 2349 +2024-11-21 23:45:29.666319: Current learning rate: 0.00731 +2024-11-21 23:45:48.662845: train_loss -0.7709 +2024-11-21 23:45:48.671567: val_loss -0.7568 +2024-11-21 23:45:48.671714: Pseudo dice [0.8448] +2024-11-21 23:45:48.671800: Epoch time: 19.0 s +2024-11-21 23:45:49.714494: +2024-11-21 23:45:49.714738: Epoch 2350 +2024-11-21 23:45:49.714877: Current learning rate: 0.00731 +2024-11-21 23:46:08.005713: train_loss -0.7625 +2024-11-21 23:46:08.011762: val_loss -0.7626 +2024-11-21 23:46:08.011879: Pseudo dice [0.8487] +2024-11-21 23:46:08.011959: Epoch time: 18.29 s +2024-11-21 23:46:09.500406: +2024-11-21 23:46:09.500625: Epoch 2351 +2024-11-21 23:46:09.500745: Current learning rate: 0.00731 +2024-11-21 23:46:28.479365: train_loss -0.7763 +2024-11-21 23:46:28.481324: val_loss -0.7885 +2024-11-21 23:46:28.481438: Pseudo dice [0.8519] +2024-11-21 23:46:28.481597: Epoch time: 18.98 s +2024-11-21 23:46:29.304173: +2024-11-21 23:46:29.304393: Epoch 2352 +2024-11-21 23:46:29.304513: Current learning rate: 0.00731 +2024-11-21 23:46:48.642316: train_loss -0.774 +2024-11-21 23:46:48.644532: val_loss -0.7719 +2024-11-21 23:46:48.644652: Pseudo dice [0.8544] +2024-11-21 23:46:48.644749: Epoch time: 19.34 s +2024-11-21 23:46:49.461298: +2024-11-21 23:46:49.461499: Epoch 2353 +2024-11-21 23:46:49.461616: Current learning rate: 0.00731 +2024-11-21 23:47:07.621147: train_loss -0.772 +2024-11-21 23:47:07.626449: val_loss -0.7827 +2024-11-21 23:47:07.626588: Pseudo dice [0.8568] +2024-11-21 23:47:07.626695: Epoch time: 18.16 s +2024-11-21 23:47:08.472496: +2024-11-21 23:47:08.472700: Epoch 2354 +2024-11-21 23:47:08.472811: Current learning rate: 0.00731 +2024-11-21 23:47:28.029969: train_loss -0.7742 +2024-11-21 23:47:28.035855: val_loss -0.7656 +2024-11-21 23:47:28.036009: Pseudo dice [0.8489] +2024-11-21 23:47:28.036119: Epoch time: 19.56 s +2024-11-21 23:47:28.908237: +2024-11-21 23:47:28.908440: Epoch 2355 +2024-11-21 23:47:28.908556: Current learning rate: 0.00731 +2024-11-21 23:47:48.268051: train_loss -0.7779 +2024-11-21 23:47:48.275788: val_loss -0.765 +2024-11-21 23:47:48.275915: Pseudo dice [0.8485] +2024-11-21 23:47:48.276011: Epoch time: 19.36 s +2024-11-21 23:47:49.103365: +2024-11-21 23:47:49.103571: Epoch 2356 +2024-11-21 23:47:49.103688: Current learning rate: 0.00731 +2024-11-21 23:48:08.405005: train_loss -0.7776 +2024-11-21 23:48:08.411269: val_loss -0.7696 +2024-11-21 23:48:08.411387: Pseudo dice [0.8605] +2024-11-21 23:48:08.411492: Epoch time: 19.3 s +2024-11-21 23:48:09.354428: +2024-11-21 23:48:09.354629: Epoch 2357 +2024-11-21 23:48:09.354767: Current learning rate: 0.0073 +2024-11-21 23:48:27.609044: train_loss -0.7828 +2024-11-21 23:48:27.614989: val_loss -0.7769 +2024-11-21 23:48:27.615115: Pseudo dice [0.8466] +2024-11-21 23:48:27.615212: Epoch time: 18.26 s +2024-11-21 23:48:28.560238: +2024-11-21 23:48:28.560439: Epoch 2358 +2024-11-21 23:48:28.560553: Current learning rate: 0.0073 +2024-11-21 23:48:47.296798: train_loss -0.7782 +2024-11-21 23:48:47.300554: val_loss -0.7582 +2024-11-21 23:48:47.300660: Pseudo dice [0.8473] +2024-11-21 23:48:47.300745: Epoch time: 18.74 s +2024-11-21 23:48:48.123668: +2024-11-21 23:48:48.123903: Epoch 2359 +2024-11-21 23:48:48.124038: Current learning rate: 0.0073 +2024-11-21 23:49:06.855296: train_loss -0.7736 +2024-11-21 23:49:06.862118: val_loss -0.7459 +2024-11-21 23:49:06.862272: Pseudo dice [0.8295] +2024-11-21 23:49:06.862386: Epoch time: 18.73 s +2024-11-21 23:49:07.681761: +2024-11-21 23:49:07.681964: Epoch 2360 +2024-11-21 23:49:07.682084: Current learning rate: 0.0073 +2024-11-21 23:49:26.329762: train_loss -0.7765 +2024-11-21 23:49:26.345432: val_loss -0.7754 +2024-11-21 23:49:26.345651: Pseudo dice [0.8501] +2024-11-21 23:49:26.345737: Epoch time: 18.65 s +2024-11-21 23:49:27.158530: +2024-11-21 23:49:27.158727: Epoch 2361 +2024-11-21 23:49:27.158841: Current learning rate: 0.0073 +2024-11-21 23:49:45.222942: train_loss -0.7854 +2024-11-21 23:49:45.244344: val_loss -0.7776 +2024-11-21 23:49:45.244484: Pseudo dice [0.85] +2024-11-21 23:49:45.244568: Epoch time: 18.07 s +2024-11-21 23:49:46.240228: +2024-11-21 23:49:46.240429: Epoch 2362 +2024-11-21 23:49:46.240543: Current learning rate: 0.0073 +2024-11-21 23:50:05.577228: train_loss -0.7735 +2024-11-21 23:50:05.584775: val_loss -0.788 +2024-11-21 23:50:05.584903: Pseudo dice [0.8496] +2024-11-21 23:50:05.585005: Epoch time: 19.34 s +2024-11-21 23:50:06.486744: +2024-11-21 23:50:06.486964: Epoch 2363 +2024-11-21 23:50:06.487087: Current learning rate: 0.0073 +2024-11-21 23:50:25.896646: train_loss -0.7923 +2024-11-21 23:50:25.921688: val_loss -0.7757 +2024-11-21 23:50:25.921839: Pseudo dice [0.852] +2024-11-21 23:50:25.921973: Epoch time: 19.41 s +2024-11-21 23:50:26.741425: +2024-11-21 23:50:26.741663: Epoch 2364 +2024-11-21 23:50:26.741796: Current learning rate: 0.0073 +2024-11-21 23:50:45.569419: train_loss -0.7896 +2024-11-21 23:50:45.570982: val_loss -0.7568 +2024-11-21 23:50:45.571083: Pseudo dice [0.8538] +2024-11-21 23:50:45.571168: Epoch time: 18.83 s +2024-11-21 23:50:46.374243: +2024-11-21 23:50:46.374445: Epoch 2365 +2024-11-21 23:50:46.374561: Current learning rate: 0.00729 +2024-11-21 23:51:05.461736: train_loss -0.7701 +2024-11-21 23:51:05.469472: val_loss -0.7676 +2024-11-21 23:51:05.469592: Pseudo dice [0.8577] +2024-11-21 23:51:05.469688: Epoch time: 19.09 s +2024-11-21 23:51:06.449319: +2024-11-21 23:51:06.449514: Epoch 2366 +2024-11-21 23:51:06.449649: Current learning rate: 0.00729 +2024-11-21 23:51:24.565258: train_loss -0.7511 +2024-11-21 23:51:24.572458: val_loss -0.7393 +2024-11-21 23:51:24.572603: Pseudo dice [0.8427] +2024-11-21 23:51:24.572997: Epoch time: 18.12 s +2024-11-21 23:51:25.516640: +2024-11-21 23:51:25.516861: Epoch 2367 +2024-11-21 23:51:25.516975: Current learning rate: 0.00729 +2024-11-21 23:51:44.991929: train_loss -0.7356 +2024-11-21 23:51:45.009806: val_loss -0.7593 +2024-11-21 23:51:45.009960: Pseudo dice [0.8465] +2024-11-21 23:51:45.010054: Epoch time: 19.48 s +2024-11-21 23:51:46.085786: +2024-11-21 23:51:46.086001: Epoch 2368 +2024-11-21 23:51:46.086146: Current learning rate: 0.00729 +2024-11-21 23:52:05.261758: train_loss -0.7596 +2024-11-21 23:52:05.270470: val_loss -0.752 +2024-11-21 23:52:05.270606: Pseudo dice [0.8339] +2024-11-21 23:52:05.270690: Epoch time: 19.18 s +2024-11-21 23:52:06.204912: +2024-11-21 23:52:06.205107: Epoch 2369 +2024-11-21 23:52:06.205225: Current learning rate: 0.00729 +2024-11-21 23:52:25.635922: train_loss -0.7563 +2024-11-21 23:52:25.637991: val_loss -0.7391 +2024-11-21 23:52:25.638126: Pseudo dice [0.8314] +2024-11-21 23:52:25.638207: Epoch time: 19.43 s +2024-11-21 23:52:26.570660: +2024-11-21 23:52:26.570866: Epoch 2370 +2024-11-21 23:52:26.570990: Current learning rate: 0.00729 +2024-11-21 23:52:44.831515: train_loss -0.7347 +2024-11-21 23:52:44.836607: val_loss -0.7484 +2024-11-21 23:52:44.836715: Pseudo dice [0.8401] +2024-11-21 23:52:44.836813: Epoch time: 18.26 s +2024-11-21 23:52:45.655768: +2024-11-21 23:52:45.655982: Epoch 2371 +2024-11-21 23:52:45.656105: Current learning rate: 0.00729 +2024-11-21 23:53:06.165552: train_loss -0.7624 +2024-11-21 23:53:06.175276: val_loss -0.7803 +2024-11-21 23:53:06.175413: Pseudo dice [0.8449] +2024-11-21 23:53:06.175504: Epoch time: 20.51 s +2024-11-21 23:53:07.007093: +2024-11-21 23:53:07.007286: Epoch 2372 +2024-11-21 23:53:07.007414: Current learning rate: 0.00729 +2024-11-21 23:53:26.756227: train_loss -0.768 +2024-11-21 23:53:26.761512: val_loss -0.7554 +2024-11-21 23:53:26.761658: Pseudo dice [0.8497] +2024-11-21 23:53:26.761743: Epoch time: 19.75 s +2024-11-21 23:53:27.581234: +2024-11-21 23:53:27.581445: Epoch 2373 +2024-11-21 23:53:27.581577: Current learning rate: 0.00729 +2024-11-21 23:53:45.945617: train_loss -0.7699 +2024-11-21 23:53:45.951362: val_loss -0.7481 +2024-11-21 23:53:45.951505: Pseudo dice [0.8362] +2024-11-21 23:53:45.951588: Epoch time: 18.37 s +2024-11-21 23:53:47.144742: +2024-11-21 23:53:47.144947: Epoch 2374 +2024-11-21 23:53:47.145082: Current learning rate: 0.00728 +2024-11-21 23:54:06.685373: train_loss -0.7722 +2024-11-21 23:54:06.701349: val_loss -0.7797 +2024-11-21 23:54:06.701505: Pseudo dice [0.8664] +2024-11-21 23:54:06.701616: Epoch time: 19.54 s +2024-11-21 23:54:07.526914: +2024-11-21 23:54:07.527163: Epoch 2375 +2024-11-21 23:54:07.527276: Current learning rate: 0.00728 +2024-11-21 23:54:26.631830: train_loss -0.7782 +2024-11-21 23:54:26.639695: val_loss -0.7621 +2024-11-21 23:54:26.639849: Pseudo dice [0.8296] +2024-11-21 23:54:26.639974: Epoch time: 19.11 s +2024-11-21 23:54:27.613363: +2024-11-21 23:54:27.613632: Epoch 2376 +2024-11-21 23:54:27.613751: Current learning rate: 0.00728 +2024-11-21 23:54:46.502209: train_loss -0.7728 +2024-11-21 23:54:46.504843: val_loss -0.7555 +2024-11-21 23:54:46.504971: Pseudo dice [0.8448] +2024-11-21 23:54:46.505063: Epoch time: 18.89 s +2024-11-21 23:54:47.402629: +2024-11-21 23:54:47.402872: Epoch 2377 +2024-11-21 23:54:47.402997: Current learning rate: 0.00728 +2024-11-21 23:55:06.372442: train_loss -0.7729 +2024-11-21 23:55:06.380122: val_loss -0.749 +2024-11-21 23:55:06.380253: Pseudo dice [0.8299] +2024-11-21 23:55:06.380342: Epoch time: 18.97 s +2024-11-21 23:55:07.328905: +2024-11-21 23:55:07.329111: Epoch 2378 +2024-11-21 23:55:07.329252: Current learning rate: 0.00728 +2024-11-21 23:55:26.936015: train_loss -0.7646 +2024-11-21 23:55:26.941732: val_loss -0.77 +2024-11-21 23:55:26.941871: Pseudo dice [0.8444] +2024-11-21 23:55:26.941962: Epoch time: 19.61 s +2024-11-21 23:55:27.939892: +2024-11-21 23:55:27.940079: Epoch 2379 +2024-11-21 23:55:27.940192: Current learning rate: 0.00728 +2024-11-21 23:55:48.149176: train_loss -0.7676 +2024-11-21 23:55:48.154903: val_loss -0.7739 +2024-11-21 23:55:48.155027: Pseudo dice [0.8516] +2024-11-21 23:55:48.155125: Epoch time: 20.21 s +2024-11-21 23:55:49.205553: +2024-11-21 23:55:49.205749: Epoch 2380 +2024-11-21 23:55:49.205870: Current learning rate: 0.00728 +2024-11-21 23:56:08.200256: train_loss -0.7786 +2024-11-21 23:56:08.209313: val_loss -0.7603 +2024-11-21 23:56:08.209469: Pseudo dice [0.8358] +2024-11-21 23:56:08.209581: Epoch time: 19.0 s +2024-11-21 23:56:09.087199: +2024-11-21 23:56:09.087404: Epoch 2381 +2024-11-21 23:56:09.087513: Current learning rate: 0.00728 +2024-11-21 23:56:28.117974: train_loss -0.7822 +2024-11-21 23:56:28.120575: val_loss -0.7514 +2024-11-21 23:56:28.126216: Pseudo dice [0.8578] +2024-11-21 23:56:28.126357: Epoch time: 19.03 s +2024-11-21 23:56:28.951538: +2024-11-21 23:56:28.951742: Epoch 2382 +2024-11-21 23:56:28.951869: Current learning rate: 0.00728 +2024-11-21 23:56:47.924116: train_loss -0.7698 +2024-11-21 23:56:47.935199: val_loss -0.7912 +2024-11-21 23:56:47.935367: Pseudo dice [0.8442] +2024-11-21 23:56:47.935474: Epoch time: 18.97 s +2024-11-21 23:56:48.911273: +2024-11-21 23:56:48.911479: Epoch 2383 +2024-11-21 23:56:48.911599: Current learning rate: 0.00727 +2024-11-21 23:57:07.979106: train_loss -0.7696 +2024-11-21 23:57:07.997815: val_loss -0.7652 +2024-11-21 23:57:07.998007: Pseudo dice [0.839] +2024-11-21 23:57:07.998121: Epoch time: 19.07 s +2024-11-21 23:57:08.830781: +2024-11-21 23:57:08.830983: Epoch 2384 +2024-11-21 23:57:08.831137: Current learning rate: 0.00727 +2024-11-21 23:57:28.329729: train_loss -0.77 +2024-11-21 23:57:28.337494: val_loss -0.7456 +2024-11-21 23:57:28.337889: Pseudo dice [0.8412] +2024-11-21 23:57:28.338041: Epoch time: 19.5 s +2024-11-21 23:57:29.820599: +2024-11-21 23:57:29.820795: Epoch 2385 +2024-11-21 23:57:29.820930: Current learning rate: 0.00727 +2024-11-21 23:57:49.890614: train_loss -0.77 +2024-11-21 23:57:49.895942: val_loss -0.7599 +2024-11-21 23:57:49.896099: Pseudo dice [0.8532] +2024-11-21 23:57:49.896196: Epoch time: 20.07 s +2024-11-21 23:57:50.752778: +2024-11-21 23:57:50.753013: Epoch 2386 +2024-11-21 23:57:50.753125: Current learning rate: 0.00727 +2024-11-21 23:58:09.687705: train_loss -0.7701 +2024-11-21 23:58:09.700119: val_loss -0.7524 +2024-11-21 23:58:09.700793: Pseudo dice [0.849] +2024-11-21 23:58:09.701109: Epoch time: 18.94 s +2024-11-21 23:58:10.644879: +2024-11-21 23:58:10.645133: Epoch 2387 +2024-11-21 23:58:10.645276: Current learning rate: 0.00727 +2024-11-21 23:58:29.467891: train_loss -0.7744 +2024-11-21 23:58:29.481628: val_loss -0.7748 +2024-11-21 23:58:29.481773: Pseudo dice [0.8499] +2024-11-21 23:58:29.481864: Epoch time: 18.82 s +2024-11-21 23:58:30.453478: +2024-11-21 23:58:30.453684: Epoch 2388 +2024-11-21 23:58:30.453808: Current learning rate: 0.00727 +2024-11-21 23:58:49.223787: train_loss -0.7645 +2024-11-21 23:58:49.229192: val_loss -0.7502 +2024-11-21 23:58:49.229327: Pseudo dice [0.8532] +2024-11-21 23:58:49.229434: Epoch time: 18.77 s +2024-11-21 23:58:50.055859: +2024-11-21 23:58:50.056068: Epoch 2389 +2024-11-21 23:58:50.056186: Current learning rate: 0.00727 +2024-11-21 23:59:09.679306: train_loss -0.7713 +2024-11-21 23:59:09.684786: val_loss -0.7636 +2024-11-21 23:59:09.684910: Pseudo dice [0.8551] +2024-11-21 23:59:09.685007: Epoch time: 19.62 s +2024-11-21 23:59:10.539554: +2024-11-21 23:59:10.539798: Epoch 2390 +2024-11-21 23:59:10.539930: Current learning rate: 0.00727 +2024-11-21 23:59:29.124603: train_loss -0.7698 +2024-11-21 23:59:29.130934: val_loss -0.7663 +2024-11-21 23:59:29.131072: Pseudo dice [0.8473] +2024-11-21 23:59:29.131157: Epoch time: 18.59 s +2024-11-21 23:59:30.052833: +2024-11-21 23:59:30.053139: Epoch 2391 +2024-11-21 23:59:30.053265: Current learning rate: 0.00726 +2024-11-21 23:59:49.731980: train_loss -0.7755 +2024-11-21 23:59:49.733900: val_loss -0.7586 +2024-11-21 23:59:49.734044: Pseudo dice [0.8408] +2024-11-21 23:59:49.734157: Epoch time: 19.68 s +2024-11-21 23:59:50.554039: +2024-11-21 23:59:50.554246: Epoch 2392 +2024-11-21 23:59:50.554365: Current learning rate: 0.00726 +2024-11-22 00:00:09.690614: train_loss -0.7719 +2024-11-22 00:00:09.697697: val_loss -0.7512 +2024-11-22 00:00:09.697849: Pseudo dice [0.856] +2024-11-22 00:00:09.698220: Epoch time: 19.14 s +2024-11-22 00:00:10.564214: +2024-11-22 00:00:10.564418: Epoch 2393 +2024-11-22 00:00:10.564545: Current learning rate: 0.00726 +2024-11-22 00:00:30.443371: train_loss -0.7682 +2024-11-22 00:00:30.445796: val_loss -0.7626 +2024-11-22 00:00:30.445922: Pseudo dice [0.8437] +2024-11-22 00:00:30.446006: Epoch time: 19.88 s +2024-11-22 00:00:31.268499: +2024-11-22 00:00:31.268698: Epoch 2394 +2024-11-22 00:00:31.268822: Current learning rate: 0.00726 +2024-11-22 00:00:50.605911: train_loss -0.7732 +2024-11-22 00:00:50.613276: val_loss -0.7529 +2024-11-22 00:00:50.613414: Pseudo dice [0.8346] +2024-11-22 00:00:50.613507: Epoch time: 19.34 s +2024-11-22 00:00:51.448498: +2024-11-22 00:00:51.448696: Epoch 2395 +2024-11-22 00:00:51.448824: Current learning rate: 0.00726 +2024-11-22 00:01:09.628823: train_loss -0.7753 +2024-11-22 00:01:09.634656: val_loss -0.7769 +2024-11-22 00:01:09.634812: Pseudo dice [0.8484] +2024-11-22 00:01:09.634913: Epoch time: 18.18 s +2024-11-22 00:01:10.664827: +2024-11-22 00:01:10.665035: Epoch 2396 +2024-11-22 00:01:10.665179: Current learning rate: 0.00726 +2024-11-22 00:01:30.191756: train_loss -0.7707 +2024-11-22 00:01:30.201132: val_loss -0.7811 +2024-11-22 00:01:30.201279: Pseudo dice [0.8554] +2024-11-22 00:01:30.201379: Epoch time: 19.53 s +2024-11-22 00:01:31.677334: +2024-11-22 00:01:31.677536: Epoch 2397 +2024-11-22 00:01:31.677750: Current learning rate: 0.00726 +2024-11-22 00:01:50.732646: train_loss -0.7538 +2024-11-22 00:01:50.737948: val_loss -0.7492 +2024-11-22 00:01:50.738074: Pseudo dice [0.824] +2024-11-22 00:01:50.738157: Epoch time: 19.06 s +2024-11-22 00:01:51.651392: +2024-11-22 00:01:51.651632: Epoch 2398 +2024-11-22 00:01:51.651758: Current learning rate: 0.00726 +2024-11-22 00:02:10.096472: train_loss -0.7512 +2024-11-22 00:02:10.104284: val_loss -0.7698 +2024-11-22 00:02:10.104432: Pseudo dice [0.8407] +2024-11-22 00:02:10.104523: Epoch time: 18.45 s +2024-11-22 00:02:11.127729: +2024-11-22 00:02:11.127955: Epoch 2399 +2024-11-22 00:02:11.128091: Current learning rate: 0.00726 +2024-11-22 00:02:29.370053: train_loss -0.7714 +2024-11-22 00:02:29.373881: val_loss -0.7607 +2024-11-22 00:02:29.374016: Pseudo dice [0.8562] +2024-11-22 00:02:29.374118: Epoch time: 18.24 s +2024-11-22 00:02:30.651181: +2024-11-22 00:02:30.651392: Epoch 2400 +2024-11-22 00:02:30.651517: Current learning rate: 0.00725 +2024-11-22 00:02:49.773587: train_loss -0.7599 +2024-11-22 00:02:49.775804: val_loss -0.7664 +2024-11-22 00:02:49.775907: Pseudo dice [0.8434] +2024-11-22 00:02:49.775994: Epoch time: 19.12 s +2024-11-22 00:02:50.603129: +2024-11-22 00:02:50.603356: Epoch 2401 +2024-11-22 00:02:50.603487: Current learning rate: 0.00725 +2024-11-22 00:03:09.631823: train_loss -0.7693 +2024-11-22 00:03:09.633806: val_loss -0.75 +2024-11-22 00:03:09.633927: Pseudo dice [0.8403] +2024-11-22 00:03:09.634014: Epoch time: 19.03 s +2024-11-22 00:03:10.450796: +2024-11-22 00:03:10.450992: Epoch 2402 +2024-11-22 00:03:10.451128: Current learning rate: 0.00725 +2024-11-22 00:03:29.686703: train_loss -0.7731 +2024-11-22 00:03:29.691962: val_loss -0.7843 +2024-11-22 00:03:29.692087: Pseudo dice [0.8626] +2024-11-22 00:03:29.692195: Epoch time: 19.24 s +2024-11-22 00:03:30.533521: +2024-11-22 00:03:30.533765: Epoch 2403 +2024-11-22 00:03:30.533910: Current learning rate: 0.00725 +2024-11-22 00:03:49.514985: train_loss -0.7755 +2024-11-22 00:03:49.516800: val_loss -0.7512 +2024-11-22 00:03:49.516935: Pseudo dice [0.8549] +2024-11-22 00:03:49.517043: Epoch time: 18.98 s +2024-11-22 00:03:50.370440: +2024-11-22 00:03:50.370653: Epoch 2404 +2024-11-22 00:03:50.370787: Current learning rate: 0.00725 +2024-11-22 00:04:08.615833: train_loss -0.7705 +2024-11-22 00:04:08.625216: val_loss -0.7632 +2024-11-22 00:04:08.625355: Pseudo dice [0.8505] +2024-11-22 00:04:08.625453: Epoch time: 18.25 s +2024-11-22 00:04:09.566198: +2024-11-22 00:04:09.566397: Epoch 2405 +2024-11-22 00:04:09.566531: Current learning rate: 0.00725 +2024-11-22 00:04:28.090471: train_loss -0.776 +2024-11-22 00:04:28.096895: val_loss -0.7888 +2024-11-22 00:04:28.097038: Pseudo dice [0.854] +2024-11-22 00:04:28.097150: Epoch time: 18.53 s +2024-11-22 00:04:29.005848: +2024-11-22 00:04:29.006051: Epoch 2406 +2024-11-22 00:04:29.006182: Current learning rate: 0.00725 +2024-11-22 00:04:48.670596: train_loss -0.7631 +2024-11-22 00:04:48.672487: val_loss -0.78 +2024-11-22 00:04:48.672583: Pseudo dice [0.8538] +2024-11-22 00:04:48.672677: Epoch time: 19.67 s +2024-11-22 00:04:49.495983: +2024-11-22 00:04:49.496178: Epoch 2407 +2024-11-22 00:04:49.496309: Current learning rate: 0.00725 +2024-11-22 00:05:08.828032: train_loss -0.7706 +2024-11-22 00:05:08.831683: val_loss -0.7714 +2024-11-22 00:05:08.831805: Pseudo dice [0.8281] +2024-11-22 00:05:08.831885: Epoch time: 19.33 s +2024-11-22 00:05:10.079809: +2024-11-22 00:05:10.080016: Epoch 2408 +2024-11-22 00:05:10.080140: Current learning rate: 0.00724 +2024-11-22 00:05:30.687142: train_loss -0.7656 +2024-11-22 00:05:30.691056: val_loss -0.7643 +2024-11-22 00:05:30.691180: Pseudo dice [0.8387] +2024-11-22 00:05:30.691271: Epoch time: 20.61 s +2024-11-22 00:05:31.507752: +2024-11-22 00:05:31.507982: Epoch 2409 +2024-11-22 00:05:31.508122: Current learning rate: 0.00724 +2024-11-22 00:05:50.150992: train_loss -0.7764 +2024-11-22 00:05:50.157195: val_loss -0.7766 +2024-11-22 00:05:50.157339: Pseudo dice [0.842] +2024-11-22 00:05:50.157447: Epoch time: 18.64 s +2024-11-22 00:05:51.009177: +2024-11-22 00:05:51.028710: Epoch 2410 +2024-11-22 00:05:51.028866: Current learning rate: 0.00724 +2024-11-22 00:06:10.982675: train_loss -0.7739 +2024-11-22 00:06:10.993495: val_loss -0.7898 +2024-11-22 00:06:10.993660: Pseudo dice [0.855] +2024-11-22 00:06:10.993804: Epoch time: 19.97 s +2024-11-22 00:06:11.905500: +2024-11-22 00:06:11.905713: Epoch 2411 +2024-11-22 00:06:11.905832: Current learning rate: 0.00724 +2024-11-22 00:06:31.549575: train_loss -0.7757 +2024-11-22 00:06:31.555438: val_loss -0.752 +2024-11-22 00:06:31.555567: Pseudo dice [0.847] +2024-11-22 00:06:31.555660: Epoch time: 19.64 s +2024-11-22 00:06:32.400875: +2024-11-22 00:06:32.401077: Epoch 2412 +2024-11-22 00:06:32.401212: Current learning rate: 0.00724 +2024-11-22 00:06:51.577571: train_loss -0.7716 +2024-11-22 00:06:51.584545: val_loss -0.7495 +2024-11-22 00:06:51.584680: Pseudo dice [0.8341] +2024-11-22 00:06:51.584778: Epoch time: 19.18 s +2024-11-22 00:06:52.409862: +2024-11-22 00:06:52.410073: Epoch 2413 +2024-11-22 00:06:52.410193: Current learning rate: 0.00724 +2024-11-22 00:07:12.865343: train_loss -0.7651 +2024-11-22 00:07:12.867439: val_loss -0.7702 +2024-11-22 00:07:12.867573: Pseudo dice [0.8371] +2024-11-22 00:07:12.867682: Epoch time: 20.46 s +2024-11-22 00:07:13.841485: +2024-11-22 00:07:13.841704: Epoch 2414 +2024-11-22 00:07:13.841833: Current learning rate: 0.00724 +2024-11-22 00:07:32.448078: train_loss -0.7673 +2024-11-22 00:07:32.454268: val_loss -0.7708 +2024-11-22 00:07:32.454405: Pseudo dice [0.8623] +2024-11-22 00:07:32.454508: Epoch time: 18.61 s +2024-11-22 00:07:33.433100: +2024-11-22 00:07:33.433300: Epoch 2415 +2024-11-22 00:07:33.433433: Current learning rate: 0.00724 +2024-11-22 00:07:52.942878: train_loss -0.7725 +2024-11-22 00:07:52.949674: val_loss -0.7731 +2024-11-22 00:07:52.949809: Pseudo dice [0.85] +2024-11-22 00:07:52.949892: Epoch time: 19.51 s +2024-11-22 00:07:53.784708: +2024-11-22 00:07:53.784909: Epoch 2416 +2024-11-22 00:07:53.785027: Current learning rate: 0.00724 +2024-11-22 00:08:12.896081: train_loss -0.782 +2024-11-22 00:08:12.899780: val_loss -0.7515 +2024-11-22 00:08:12.899915: Pseudo dice [0.8408] +2024-11-22 00:08:12.900015: Epoch time: 19.11 s +2024-11-22 00:08:13.734083: +2024-11-22 00:08:13.734288: Epoch 2417 +2024-11-22 00:08:13.734415: Current learning rate: 0.00723 +2024-11-22 00:08:33.590160: train_loss -0.7795 +2024-11-22 00:08:33.594673: val_loss -0.7724 +2024-11-22 00:08:33.594872: Pseudo dice [0.8555] +2024-11-22 00:08:33.594971: Epoch time: 19.86 s +2024-11-22 00:08:34.504840: +2024-11-22 00:08:34.505054: Epoch 2418 +2024-11-22 00:08:34.505170: Current learning rate: 0.00723 +2024-11-22 00:08:52.279539: train_loss -0.7808 +2024-11-22 00:08:52.285171: val_loss -0.7747 +2024-11-22 00:08:52.285315: Pseudo dice [0.8452] +2024-11-22 00:08:52.285617: Epoch time: 17.78 s +2024-11-22 00:08:53.133561: +2024-11-22 00:08:53.134000: Epoch 2419 +2024-11-22 00:08:53.134158: Current learning rate: 0.00723 +2024-11-22 00:09:13.529976: train_loss -0.7907 +2024-11-22 00:09:13.537823: val_loss -0.7629 +2024-11-22 00:09:13.537955: Pseudo dice [0.8407] +2024-11-22 00:09:13.538054: Epoch time: 20.4 s +2024-11-22 00:09:14.851122: +2024-11-22 00:09:14.851331: Epoch 2420 +2024-11-22 00:09:14.851452: Current learning rate: 0.00723 +2024-11-22 00:09:34.073064: train_loss -0.7847 +2024-11-22 00:09:34.075843: val_loss -0.7393 +2024-11-22 00:09:34.076001: Pseudo dice [0.843] +2024-11-22 00:09:34.076120: Epoch time: 19.22 s +2024-11-22 00:09:35.035820: +2024-11-22 00:09:35.036033: Epoch 2421 +2024-11-22 00:09:35.036151: Current learning rate: 0.00723 +2024-11-22 00:09:53.694637: train_loss -0.788 +2024-11-22 00:09:53.702307: val_loss -0.7515 +2024-11-22 00:09:53.702546: Pseudo dice [0.847] +2024-11-22 00:09:53.702669: Epoch time: 18.66 s +2024-11-22 00:09:54.540245: +2024-11-22 00:09:54.540478: Epoch 2422 +2024-11-22 00:09:54.540590: Current learning rate: 0.00723 +2024-11-22 00:10:13.240864: train_loss -0.7803 +2024-11-22 00:10:13.263864: val_loss -0.7685 +2024-11-22 00:10:13.264036: Pseudo dice [0.8515] +2024-11-22 00:10:13.264377: Epoch time: 18.7 s +2024-11-22 00:10:14.091909: +2024-11-22 00:10:14.092142: Epoch 2423 +2024-11-22 00:10:14.092267: Current learning rate: 0.00723 +2024-11-22 00:10:33.256864: train_loss -0.7775 +2024-11-22 00:10:33.263532: val_loss -0.753 +2024-11-22 00:10:33.263669: Pseudo dice [0.8395] +2024-11-22 00:10:33.263766: Epoch time: 19.17 s +2024-11-22 00:10:34.178654: +2024-11-22 00:10:34.178891: Epoch 2424 +2024-11-22 00:10:34.179019: Current learning rate: 0.00723 +2024-11-22 00:10:53.547025: train_loss -0.7659 +2024-11-22 00:10:53.553208: val_loss -0.7748 +2024-11-22 00:10:53.553358: Pseudo dice [0.8485] +2024-11-22 00:10:53.553453: Epoch time: 19.37 s +2024-11-22 00:10:54.464119: +2024-11-22 00:10:54.464341: Epoch 2425 +2024-11-22 00:10:54.464476: Current learning rate: 0.00723 +2024-11-22 00:11:13.314477: train_loss -0.777 +2024-11-22 00:11:13.321268: val_loss -0.7772 +2024-11-22 00:11:13.321465: Pseudo dice [0.8563] +2024-11-22 00:11:13.321556: Epoch time: 18.85 s +2024-11-22 00:11:14.149242: +2024-11-22 00:11:14.149471: Epoch 2426 +2024-11-22 00:11:14.149589: Current learning rate: 0.00722 +2024-11-22 00:11:33.246570: train_loss -0.7743 +2024-11-22 00:11:33.248983: val_loss -0.7478 +2024-11-22 00:11:33.249114: Pseudo dice [0.8434] +2024-11-22 00:11:33.249201: Epoch time: 19.1 s +2024-11-22 00:11:34.220548: +2024-11-22 00:11:34.220750: Epoch 2427 +2024-11-22 00:11:34.220866: Current learning rate: 0.00722 +2024-11-22 00:11:53.553617: train_loss -0.7717 +2024-11-22 00:11:53.562314: val_loss -0.7457 +2024-11-22 00:11:53.562466: Pseudo dice [0.8546] +2024-11-22 00:11:53.562567: Epoch time: 19.33 s +2024-11-22 00:11:54.421491: +2024-11-22 00:11:54.421705: Epoch 2428 +2024-11-22 00:11:54.421822: Current learning rate: 0.00722 +2024-11-22 00:12:14.242434: train_loss -0.7795 +2024-11-22 00:12:14.248821: val_loss -0.759 +2024-11-22 00:12:14.249012: Pseudo dice [0.8377] +2024-11-22 00:12:14.249126: Epoch time: 19.82 s +2024-11-22 00:12:15.397528: +2024-11-22 00:12:15.397740: Epoch 2429 +2024-11-22 00:12:15.397866: Current learning rate: 0.00722 +2024-11-22 00:12:33.995419: train_loss -0.7818 +2024-11-22 00:12:34.001039: val_loss -0.7555 +2024-11-22 00:12:34.001232: Pseudo dice [0.8489] +2024-11-22 00:12:34.001327: Epoch time: 18.6 s +2024-11-22 00:12:34.828259: +2024-11-22 00:12:34.828488: Epoch 2430 +2024-11-22 00:12:34.828605: Current learning rate: 0.00722 +2024-11-22 00:12:52.675526: train_loss -0.7765 +2024-11-22 00:12:52.677877: val_loss -0.78 +2024-11-22 00:12:52.677982: Pseudo dice [0.8573] +2024-11-22 00:12:52.678082: Epoch time: 17.85 s +2024-11-22 00:12:53.882411: +2024-11-22 00:12:53.882638: Epoch 2431 +2024-11-22 00:12:53.882789: Current learning rate: 0.00722 +2024-11-22 00:13:13.413402: train_loss -0.7732 +2024-11-22 00:13:13.420254: val_loss -0.7786 +2024-11-22 00:13:13.420402: Pseudo dice [0.845] +2024-11-22 00:13:13.420497: Epoch time: 19.53 s +2024-11-22 00:13:14.270591: +2024-11-22 00:13:14.270809: Epoch 2432 +2024-11-22 00:13:14.270935: Current learning rate: 0.00722 +2024-11-22 00:13:32.884039: train_loss -0.7796 +2024-11-22 00:13:32.890032: val_loss -0.7401 +2024-11-22 00:13:32.890201: Pseudo dice [0.8359] +2024-11-22 00:13:32.890287: Epoch time: 18.61 s +2024-11-22 00:13:33.713726: +2024-11-22 00:13:33.713990: Epoch 2433 +2024-11-22 00:13:33.714123: Current learning rate: 0.00722 +2024-11-22 00:13:53.258496: train_loss -0.7757 +2024-11-22 00:13:53.268724: val_loss -0.7824 +2024-11-22 00:13:53.268843: Pseudo dice [0.8638] +2024-11-22 00:13:53.268926: Epoch time: 19.55 s +2024-11-22 00:13:54.347219: +2024-11-22 00:13:54.347424: Epoch 2434 +2024-11-22 00:13:54.347554: Current learning rate: 0.00721 +2024-11-22 00:14:14.662837: train_loss -0.7767 +2024-11-22 00:14:14.670067: val_loss -0.7596 +2024-11-22 00:14:14.670212: Pseudo dice [0.8366] +2024-11-22 00:14:14.670307: Epoch time: 20.32 s +2024-11-22 00:14:15.645983: +2024-11-22 00:14:15.646191: Epoch 2435 +2024-11-22 00:14:15.646307: Current learning rate: 0.00721 +2024-11-22 00:14:35.134230: train_loss -0.778 +2024-11-22 00:14:35.140453: val_loss -0.767 +2024-11-22 00:14:35.140593: Pseudo dice [0.8393] +2024-11-22 00:14:35.140707: Epoch time: 19.49 s +2024-11-22 00:14:36.058771: +2024-11-22 00:14:36.059004: Epoch 2436 +2024-11-22 00:14:36.059140: Current learning rate: 0.00721 +2024-11-22 00:14:55.047580: train_loss -0.7754 +2024-11-22 00:14:55.052897: val_loss -0.7671 +2024-11-22 00:14:55.053094: Pseudo dice [0.8479] +2024-11-22 00:14:55.053196: Epoch time: 18.99 s +2024-11-22 00:14:55.881899: +2024-11-22 00:14:55.882132: Epoch 2437 +2024-11-22 00:14:55.882261: Current learning rate: 0.00721 +2024-11-22 00:15:14.406251: train_loss -0.7768 +2024-11-22 00:15:14.409399: val_loss -0.7718 +2024-11-22 00:15:14.409586: Pseudo dice [0.8496] +2024-11-22 00:15:14.409679: Epoch time: 18.53 s +2024-11-22 00:15:15.235088: +2024-11-22 00:15:15.235288: Epoch 2438 +2024-11-22 00:15:15.235401: Current learning rate: 0.00721 +2024-11-22 00:15:34.541564: train_loss -0.7832 +2024-11-22 00:15:34.544304: val_loss -0.7579 +2024-11-22 00:15:34.544419: Pseudo dice [0.8469] +2024-11-22 00:15:34.544522: Epoch time: 19.31 s +2024-11-22 00:15:35.367414: +2024-11-22 00:15:35.367656: Epoch 2439 +2024-11-22 00:15:35.367780: Current learning rate: 0.00721 +2024-11-22 00:15:55.451027: train_loss -0.7619 +2024-11-22 00:15:55.458093: val_loss -0.7657 +2024-11-22 00:15:55.458225: Pseudo dice [0.8524] +2024-11-22 00:15:55.458314: Epoch time: 20.08 s +2024-11-22 00:15:56.332802: +2024-11-22 00:15:56.332993: Epoch 2440 +2024-11-22 00:15:56.333119: Current learning rate: 0.00721 +2024-11-22 00:16:16.056620: train_loss -0.7686 +2024-11-22 00:16:16.065504: val_loss -0.7675 +2024-11-22 00:16:16.065646: Pseudo dice [0.8402] +2024-11-22 00:16:16.065734: Epoch time: 19.72 s +2024-11-22 00:16:17.062665: +2024-11-22 00:16:17.062874: Epoch 2441 +2024-11-22 00:16:17.062991: Current learning rate: 0.00721 +2024-11-22 00:16:36.869737: train_loss -0.7649 +2024-11-22 00:16:36.877299: val_loss -0.7842 +2024-11-22 00:16:36.877439: Pseudo dice [0.8601] +2024-11-22 00:16:36.877543: Epoch time: 19.81 s +2024-11-22 00:16:37.711669: +2024-11-22 00:16:37.711886: Epoch 2442 +2024-11-22 00:16:37.712009: Current learning rate: 0.00721 +2024-11-22 00:16:57.306420: train_loss -0.7682 +2024-11-22 00:16:57.314447: val_loss -0.7536 +2024-11-22 00:16:57.314560: Pseudo dice [0.8439] +2024-11-22 00:16:57.314650: Epoch time: 19.6 s +2024-11-22 00:16:58.532324: +2024-11-22 00:16:58.532530: Epoch 2443 +2024-11-22 00:16:58.532643: Current learning rate: 0.0072 +2024-11-22 00:17:18.375857: train_loss -0.7595 +2024-11-22 00:17:18.383301: val_loss -0.7423 +2024-11-22 00:17:18.383438: Pseudo dice [0.8297] +2024-11-22 00:17:18.383536: Epoch time: 19.84 s +2024-11-22 00:17:19.226805: +2024-11-22 00:17:19.227019: Epoch 2444 +2024-11-22 00:17:19.227164: Current learning rate: 0.0072 +2024-11-22 00:17:38.172534: train_loss -0.7677 +2024-11-22 00:17:38.178303: val_loss -0.7611 +2024-11-22 00:17:38.178514: Pseudo dice [0.8486] +2024-11-22 00:17:38.178628: Epoch time: 18.95 s +2024-11-22 00:17:39.000510: +2024-11-22 00:17:39.000812: Epoch 2445 +2024-11-22 00:17:39.000946: Current learning rate: 0.0072 +2024-11-22 00:17:58.599606: train_loss -0.773 +2024-11-22 00:17:58.612190: val_loss -0.7804 +2024-11-22 00:17:58.612341: Pseudo dice [0.8502] +2024-11-22 00:17:58.612426: Epoch time: 19.6 s +2024-11-22 00:17:59.485674: +2024-11-22 00:17:59.485895: Epoch 2446 +2024-11-22 00:17:59.486031: Current learning rate: 0.0072 +2024-11-22 00:18:18.389705: train_loss -0.777 +2024-11-22 00:18:18.404694: val_loss -0.7633 +2024-11-22 00:18:18.404844: Pseudo dice [0.844] +2024-11-22 00:18:18.404953: Epoch time: 18.9 s +2024-11-22 00:18:19.381036: +2024-11-22 00:18:19.381252: Epoch 2447 +2024-11-22 00:18:19.381376: Current learning rate: 0.0072 +2024-11-22 00:18:39.281958: train_loss -0.7691 +2024-11-22 00:18:39.289155: val_loss -0.7721 +2024-11-22 00:18:39.289283: Pseudo dice [0.8562] +2024-11-22 00:18:39.289384: Epoch time: 19.9 s +2024-11-22 00:18:40.273169: +2024-11-22 00:18:40.273379: Epoch 2448 +2024-11-22 00:18:40.273509: Current learning rate: 0.0072 +2024-11-22 00:18:59.552085: train_loss -0.7727 +2024-11-22 00:18:59.558611: val_loss -0.7457 +2024-11-22 00:18:59.558738: Pseudo dice [0.828] +2024-11-22 00:18:59.558826: Epoch time: 19.28 s +2024-11-22 00:19:00.417175: +2024-11-22 00:19:00.417376: Epoch 2449 +2024-11-22 00:19:00.417496: Current learning rate: 0.0072 +2024-11-22 00:19:18.968351: train_loss -0.7745 +2024-11-22 00:19:18.974638: val_loss -0.7832 +2024-11-22 00:19:18.974787: Pseudo dice [0.847] +2024-11-22 00:19:18.974877: Epoch time: 18.55 s +2024-11-22 00:19:20.027784: +2024-11-22 00:19:20.028038: Epoch 2450 +2024-11-22 00:19:20.028178: Current learning rate: 0.0072 +2024-11-22 00:19:38.701928: train_loss -0.7683 +2024-11-22 00:19:38.708375: val_loss -0.7472 +2024-11-22 00:19:38.708529: Pseudo dice [0.8471] +2024-11-22 00:19:38.708624: Epoch time: 18.68 s +2024-11-22 00:19:39.836542: +2024-11-22 00:19:39.836747: Epoch 2451 +2024-11-22 00:19:39.836862: Current learning rate: 0.00719 +2024-11-22 00:19:58.831335: train_loss -0.7633 +2024-11-22 00:19:58.838349: val_loss -0.7795 +2024-11-22 00:19:58.838490: Pseudo dice [0.8412] +2024-11-22 00:19:58.838577: Epoch time: 19.0 s +2024-11-22 00:19:59.658729: +2024-11-22 00:19:59.658932: Epoch 2452 +2024-11-22 00:19:59.659076: Current learning rate: 0.00719 +2024-11-22 00:20:19.363801: train_loss -0.7722 +2024-11-22 00:20:19.368162: val_loss -0.7333 +2024-11-22 00:20:19.368317: Pseudo dice [0.8487] +2024-11-22 00:20:19.368402: Epoch time: 19.71 s +2024-11-22 00:20:20.214053: +2024-11-22 00:20:20.214285: Epoch 2453 +2024-11-22 00:20:20.214428: Current learning rate: 0.00719 +2024-11-22 00:20:38.440108: train_loss -0.7832 +2024-11-22 00:20:38.458262: val_loss -0.7472 +2024-11-22 00:20:38.458449: Pseudo dice [0.8686] +2024-11-22 00:20:38.458549: Epoch time: 18.22 s +2024-11-22 00:20:39.850673: +2024-11-22 00:20:39.850897: Epoch 2454 +2024-11-22 00:20:39.851032: Current learning rate: 0.00719 +2024-11-22 00:20:58.656987: train_loss -0.772 +2024-11-22 00:20:58.667437: val_loss -0.75 +2024-11-22 00:20:58.667581: Pseudo dice [0.8488] +2024-11-22 00:20:58.667674: Epoch time: 18.81 s +2024-11-22 00:20:59.498806: +2024-11-22 00:20:59.499024: Epoch 2455 +2024-11-22 00:20:59.499154: Current learning rate: 0.00719 +2024-11-22 00:21:17.775539: train_loss -0.7763 +2024-11-22 00:21:17.782604: val_loss -0.7797 +2024-11-22 00:21:17.782747: Pseudo dice [0.8568] +2024-11-22 00:21:17.782839: Epoch time: 18.28 s +2024-11-22 00:21:18.613455: +2024-11-22 00:21:18.613667: Epoch 2456 +2024-11-22 00:21:18.613778: Current learning rate: 0.00719 +2024-11-22 00:21:37.764875: train_loss -0.7649 +2024-11-22 00:21:37.773265: val_loss -0.7423 +2024-11-22 00:21:37.773411: Pseudo dice [0.8519] +2024-11-22 00:21:37.773516: Epoch time: 19.15 s +2024-11-22 00:21:38.622225: +2024-11-22 00:21:38.622431: Epoch 2457 +2024-11-22 00:21:38.622555: Current learning rate: 0.00719 +2024-11-22 00:21:57.846130: train_loss -0.7813 +2024-11-22 00:21:57.850220: val_loss -0.7877 +2024-11-22 00:21:57.850358: Pseudo dice [0.8528] +2024-11-22 00:21:57.850473: Epoch time: 19.22 s +2024-11-22 00:21:58.706905: +2024-11-22 00:21:58.707173: Epoch 2458 +2024-11-22 00:21:58.707297: Current learning rate: 0.00719 +2024-11-22 00:22:18.354478: train_loss -0.7763 +2024-11-22 00:22:18.360591: val_loss -0.734 +2024-11-22 00:22:18.360772: Pseudo dice [0.8469] +2024-11-22 00:22:18.360873: Epoch time: 19.65 s +2024-11-22 00:22:19.203489: +2024-11-22 00:22:19.203677: Epoch 2459 +2024-11-22 00:22:19.203798: Current learning rate: 0.00719 +2024-11-22 00:22:39.382849: train_loss -0.7817 +2024-11-22 00:22:39.385294: val_loss -0.7503 +2024-11-22 00:22:39.385446: Pseudo dice [0.8555] +2024-11-22 00:22:39.385590: Epoch time: 20.18 s +2024-11-22 00:22:40.213607: +2024-11-22 00:22:40.213808: Epoch 2460 +2024-11-22 00:22:40.213947: Current learning rate: 0.00718 +2024-11-22 00:22:59.513552: train_loss -0.7806 +2024-11-22 00:22:59.520055: val_loss -0.7504 +2024-11-22 00:22:59.520180: Pseudo dice [0.8504] +2024-11-22 00:22:59.520274: Epoch time: 19.3 s +2024-11-22 00:23:00.436671: +2024-11-22 00:23:00.436882: Epoch 2461 +2024-11-22 00:23:00.437015: Current learning rate: 0.00718 +2024-11-22 00:23:18.979393: train_loss -0.7775 +2024-11-22 00:23:18.983510: val_loss -0.7825 +2024-11-22 00:23:18.983715: Pseudo dice [0.842] +2024-11-22 00:23:18.983807: Epoch time: 18.54 s +2024-11-22 00:23:19.921751: +2024-11-22 00:23:19.921984: Epoch 2462 +2024-11-22 00:23:19.922108: Current learning rate: 0.00718 +2024-11-22 00:23:39.593738: train_loss -0.7723 +2024-11-22 00:23:39.607606: val_loss -0.7574 +2024-11-22 00:23:39.607738: Pseudo dice [0.8505] +2024-11-22 00:23:39.607827: Epoch time: 19.67 s +2024-11-22 00:23:40.440672: +2024-11-22 00:23:40.440906: Epoch 2463 +2024-11-22 00:23:40.441029: Current learning rate: 0.00718 +2024-11-22 00:23:58.872440: train_loss -0.7729 +2024-11-22 00:23:58.878239: val_loss -0.7317 +2024-11-22 00:23:58.878370: Pseudo dice [0.8405] +2024-11-22 00:23:58.878464: Epoch time: 18.43 s +2024-11-22 00:23:59.708549: +2024-11-22 00:23:59.708751: Epoch 2464 +2024-11-22 00:23:59.708887: Current learning rate: 0.00718 +2024-11-22 00:24:18.381324: train_loss -0.7704 +2024-11-22 00:24:18.385298: val_loss -0.7702 +2024-11-22 00:24:18.385415: Pseudo dice [0.854] +2024-11-22 00:24:18.385514: Epoch time: 18.67 s +2024-11-22 00:24:19.618937: +2024-11-22 00:24:19.619177: Epoch 2465 +2024-11-22 00:24:19.619318: Current learning rate: 0.00718 +2024-11-22 00:24:38.678661: train_loss -0.7765 +2024-11-22 00:24:38.699203: val_loss -0.7557 +2024-11-22 00:24:38.699351: Pseudo dice [0.8399] +2024-11-22 00:24:38.699449: Epoch time: 19.06 s +2024-11-22 00:24:39.696725: +2024-11-22 00:24:39.696960: Epoch 2466 +2024-11-22 00:24:39.697097: Current learning rate: 0.00718 +2024-11-22 00:24:57.955527: train_loss -0.7735 +2024-11-22 00:24:57.964275: val_loss -0.7582 +2024-11-22 00:24:57.964407: Pseudo dice [0.8623] +2024-11-22 00:24:57.964506: Epoch time: 18.26 s +2024-11-22 00:24:58.984719: +2024-11-22 00:24:58.984945: Epoch 2467 +2024-11-22 00:24:58.985065: Current learning rate: 0.00718 +2024-11-22 00:25:17.341191: train_loss -0.7498 +2024-11-22 00:25:17.347632: val_loss -0.7356 +2024-11-22 00:25:17.347768: Pseudo dice [0.8357] +2024-11-22 00:25:17.347916: Epoch time: 18.36 s +2024-11-22 00:25:18.306692: +2024-11-22 00:25:18.306955: Epoch 2468 +2024-11-22 00:25:18.307087: Current learning rate: 0.00717 +2024-11-22 00:25:37.512210: train_loss -0.7607 +2024-11-22 00:25:37.533245: val_loss -0.7622 +2024-11-22 00:25:37.533386: Pseudo dice [0.8332] +2024-11-22 00:25:37.533477: Epoch time: 19.21 s +2024-11-22 00:25:38.403536: +2024-11-22 00:25:38.403744: Epoch 2469 +2024-11-22 00:25:38.403861: Current learning rate: 0.00717 +2024-11-22 00:25:57.450188: train_loss -0.7602 +2024-11-22 00:25:57.453413: val_loss -0.7625 +2024-11-22 00:25:57.453543: Pseudo dice [0.845] +2024-11-22 00:25:57.453651: Epoch time: 19.05 s +2024-11-22 00:25:58.277200: +2024-11-22 00:25:58.277410: Epoch 2470 +2024-11-22 00:25:58.277538: Current learning rate: 0.00717 +2024-11-22 00:26:17.586726: train_loss -0.7586 +2024-11-22 00:26:17.593898: val_loss -0.7734 +2024-11-22 00:26:17.594257: Pseudo dice [0.8511] +2024-11-22 00:26:17.594364: Epoch time: 19.31 s +2024-11-22 00:26:18.582711: +2024-11-22 00:26:18.582915: Epoch 2471 +2024-11-22 00:26:18.583035: Current learning rate: 0.00717 +2024-11-22 00:26:37.711385: train_loss -0.7637 +2024-11-22 00:26:37.726135: val_loss -0.7626 +2024-11-22 00:26:37.726275: Pseudo dice [0.8509] +2024-11-22 00:26:37.726450: Epoch time: 19.13 s +2024-11-22 00:26:38.627867: +2024-11-22 00:26:38.628109: Epoch 2472 +2024-11-22 00:26:38.628247: Current learning rate: 0.00717 +2024-11-22 00:26:58.672516: train_loss -0.7643 +2024-11-22 00:26:58.694684: val_loss -0.7737 +2024-11-22 00:26:58.694805: Pseudo dice [0.8497] +2024-11-22 00:26:58.694904: Epoch time: 20.05 s +2024-11-22 00:26:59.779219: +2024-11-22 00:26:59.779414: Epoch 2473 +2024-11-22 00:26:59.779531: Current learning rate: 0.00717 +2024-11-22 00:27:19.024032: train_loss -0.7657 +2024-11-22 00:27:19.030095: val_loss -0.7622 +2024-11-22 00:27:19.030443: Pseudo dice [0.8432] +2024-11-22 00:27:19.030535: Epoch time: 19.25 s +2024-11-22 00:27:19.857694: +2024-11-22 00:27:19.857905: Epoch 2474 +2024-11-22 00:27:19.858033: Current learning rate: 0.00717 +2024-11-22 00:27:39.163635: train_loss -0.7779 +2024-11-22 00:27:39.165575: val_loss -0.7611 +2024-11-22 00:27:39.165694: Pseudo dice [0.8441] +2024-11-22 00:27:39.165781: Epoch time: 19.31 s +2024-11-22 00:27:39.988023: +2024-11-22 00:27:39.988216: Epoch 2475 +2024-11-22 00:27:39.988339: Current learning rate: 0.00717 +2024-11-22 00:27:58.343027: train_loss -0.7783 +2024-11-22 00:27:58.348786: val_loss -0.7578 +2024-11-22 00:27:58.348925: Pseudo dice [0.8501] +2024-11-22 00:27:58.349029: Epoch time: 18.36 s +2024-11-22 00:27:59.304226: +2024-11-22 00:27:59.304416: Epoch 2476 +2024-11-22 00:27:59.304534: Current learning rate: 0.00717 +2024-11-22 00:28:17.782024: train_loss -0.7752 +2024-11-22 00:28:17.788322: val_loss -0.7606 +2024-11-22 00:28:17.788446: Pseudo dice [0.8351] +2024-11-22 00:28:17.788552: Epoch time: 18.48 s +2024-11-22 00:28:19.092719: +2024-11-22 00:28:19.092952: Epoch 2477 +2024-11-22 00:28:19.093077: Current learning rate: 0.00716 +2024-11-22 00:28:38.077923: train_loss -0.7756 +2024-11-22 00:28:38.080644: val_loss -0.7605 +2024-11-22 00:28:38.080739: Pseudo dice [0.8419] +2024-11-22 00:28:38.080825: Epoch time: 18.99 s +2024-11-22 00:28:38.911770: +2024-11-22 00:28:38.911993: Epoch 2478 +2024-11-22 00:28:38.912128: Current learning rate: 0.00716 +2024-11-22 00:28:57.093374: train_loss -0.7715 +2024-11-22 00:28:57.099617: val_loss -0.7574 +2024-11-22 00:28:57.099831: Pseudo dice [0.8506] +2024-11-22 00:28:57.099927: Epoch time: 18.18 s +2024-11-22 00:28:58.125331: +2024-11-22 00:28:58.125569: Epoch 2479 +2024-11-22 00:28:58.125701: Current learning rate: 0.00716 +2024-11-22 00:29:16.677039: train_loss -0.7773 +2024-11-22 00:29:16.689028: val_loss -0.7617 +2024-11-22 00:29:16.689179: Pseudo dice [0.8518] +2024-11-22 00:29:16.689269: Epoch time: 18.55 s +2024-11-22 00:29:17.527995: +2024-11-22 00:29:17.528232: Epoch 2480 +2024-11-22 00:29:17.528380: Current learning rate: 0.00716 +2024-11-22 00:29:37.813593: train_loss -0.7854 +2024-11-22 00:29:37.825194: val_loss -0.7617 +2024-11-22 00:29:37.825337: Pseudo dice [0.8375] +2024-11-22 00:29:37.825422: Epoch time: 20.29 s +2024-11-22 00:29:38.651561: +2024-11-22 00:29:38.651741: Epoch 2481 +2024-11-22 00:29:38.651872: Current learning rate: 0.00716 +2024-11-22 00:29:58.870630: train_loss -0.7732 +2024-11-22 00:29:58.877168: val_loss -0.7589 +2024-11-22 00:29:58.877320: Pseudo dice [0.8476] +2024-11-22 00:29:58.877421: Epoch time: 20.22 s +2024-11-22 00:29:59.838550: +2024-11-22 00:29:59.838761: Epoch 2482 +2024-11-22 00:29:59.838901: Current learning rate: 0.00716 +2024-11-22 00:30:20.038375: train_loss -0.7743 +2024-11-22 00:30:20.051272: val_loss -0.7718 +2024-11-22 00:30:20.051450: Pseudo dice [0.8646] +2024-11-22 00:30:20.051559: Epoch time: 20.2 s +2024-11-22 00:30:21.113349: +2024-11-22 00:30:21.113561: Epoch 2483 +2024-11-22 00:30:21.113689: Current learning rate: 0.00716 +2024-11-22 00:30:39.786613: train_loss -0.78 +2024-11-22 00:30:39.791580: val_loss -0.7512 +2024-11-22 00:30:39.791732: Pseudo dice [0.8427] +2024-11-22 00:30:39.791821: Epoch time: 18.67 s +2024-11-22 00:30:40.694807: +2024-11-22 00:30:40.695008: Epoch 2484 +2024-11-22 00:30:40.695196: Current learning rate: 0.00716 +2024-11-22 00:31:00.296441: train_loss -0.7622 +2024-11-22 00:31:00.298885: val_loss -0.7443 +2024-11-22 00:31:00.298998: Pseudo dice [0.8375] +2024-11-22 00:31:00.299085: Epoch time: 19.6 s +2024-11-22 00:31:01.121867: +2024-11-22 00:31:01.122126: Epoch 2485 +2024-11-22 00:31:01.122258: Current learning rate: 0.00716 +2024-11-22 00:31:20.864858: train_loss -0.7672 +2024-11-22 00:31:20.871366: val_loss -0.7864 +2024-11-22 00:31:20.871565: Pseudo dice [0.8574] +2024-11-22 00:31:20.871670: Epoch time: 19.74 s +2024-11-22 00:31:21.797608: +2024-11-22 00:31:21.797807: Epoch 2486 +2024-11-22 00:31:21.797931: Current learning rate: 0.00715 +2024-11-22 00:31:40.919511: train_loss -0.7664 +2024-11-22 00:31:40.925608: val_loss -0.7664 +2024-11-22 00:31:40.925745: Pseudo dice [0.8428] +2024-11-22 00:31:40.925839: Epoch time: 19.12 s +2024-11-22 00:31:41.853124: +2024-11-22 00:31:41.853338: Epoch 2487 +2024-11-22 00:31:41.853471: Current learning rate: 0.00715 +2024-11-22 00:32:01.616786: train_loss -0.7676 +2024-11-22 00:32:01.625314: val_loss -0.7777 +2024-11-22 00:32:01.625458: Pseudo dice [0.8441] +2024-11-22 00:32:01.625556: Epoch time: 19.76 s +2024-11-22 00:32:03.115184: +2024-11-22 00:32:03.115425: Epoch 2488 +2024-11-22 00:32:03.115553: Current learning rate: 0.00715 +2024-11-22 00:32:22.139708: train_loss -0.7639 +2024-11-22 00:32:22.146717: val_loss -0.7672 +2024-11-22 00:32:22.146857: Pseudo dice [0.8413] +2024-11-22 00:32:22.146943: Epoch time: 19.03 s +2024-11-22 00:32:22.996893: +2024-11-22 00:32:22.997115: Epoch 2489 +2024-11-22 00:32:22.997244: Current learning rate: 0.00715 +2024-11-22 00:32:41.221810: train_loss -0.7647 +2024-11-22 00:32:41.228127: val_loss -0.766 +2024-11-22 00:32:41.228281: Pseudo dice [0.8397] +2024-11-22 00:32:41.228381: Epoch time: 18.23 s +2024-11-22 00:32:42.060200: +2024-11-22 00:32:42.060453: Epoch 2490 +2024-11-22 00:32:42.060580: Current learning rate: 0.00715 +2024-11-22 00:33:01.229337: train_loss -0.7743 +2024-11-22 00:33:01.232471: val_loss -0.7657 +2024-11-22 00:33:01.232596: Pseudo dice [0.8578] +2024-11-22 00:33:01.232674: Epoch time: 19.17 s +2024-11-22 00:33:02.213650: +2024-11-22 00:33:02.213876: Epoch 2491 +2024-11-22 00:33:02.213998: Current learning rate: 0.00715 +2024-11-22 00:33:20.757524: train_loss -0.7758 +2024-11-22 00:33:20.759682: val_loss -0.7791 +2024-11-22 00:33:20.759786: Pseudo dice [0.858] +2024-11-22 00:33:20.759876: Epoch time: 18.54 s +2024-11-22 00:33:21.585709: +2024-11-22 00:33:21.585928: Epoch 2492 +2024-11-22 00:33:21.586046: Current learning rate: 0.00715 +2024-11-22 00:33:39.912007: train_loss -0.7793 +2024-11-22 00:33:39.920771: val_loss -0.7757 +2024-11-22 00:33:39.920907: Pseudo dice [0.8573] +2024-11-22 00:33:39.920992: Epoch time: 18.33 s +2024-11-22 00:33:40.829337: +2024-11-22 00:33:40.829540: Epoch 2493 +2024-11-22 00:33:40.829672: Current learning rate: 0.00715 +2024-11-22 00:34:00.196852: train_loss -0.7756 +2024-11-22 00:34:00.214035: val_loss -0.7785 +2024-11-22 00:34:00.214196: Pseudo dice [0.8653] +2024-11-22 00:34:00.214296: Epoch time: 19.37 s +2024-11-22 00:34:01.321680: +2024-11-22 00:34:01.321880: Epoch 2494 +2024-11-22 00:34:01.321996: Current learning rate: 0.00714 +2024-11-22 00:34:21.717931: train_loss -0.7775 +2024-11-22 00:34:21.720649: val_loss -0.7657 +2024-11-22 00:34:21.720781: Pseudo dice [0.8511] +2024-11-22 00:34:21.720882: Epoch time: 20.4 s +2024-11-22 00:34:22.546284: +2024-11-22 00:34:22.546507: Epoch 2495 +2024-11-22 00:34:22.546643: Current learning rate: 0.00714 +2024-11-22 00:34:40.513108: train_loss -0.7661 +2024-11-22 00:34:40.515976: val_loss -0.7529 +2024-11-22 00:34:40.516113: Pseudo dice [0.8352] +2024-11-22 00:34:40.516202: Epoch time: 17.97 s +2024-11-22 00:34:41.530527: +2024-11-22 00:34:41.530719: Epoch 2496 +2024-11-22 00:34:41.530841: Current learning rate: 0.00714 +2024-11-22 00:34:59.780196: train_loss -0.7571 +2024-11-22 00:34:59.787186: val_loss -0.7572 +2024-11-22 00:34:59.787513: Pseudo dice [0.8438] +2024-11-22 00:34:59.787616: Epoch time: 18.25 s +2024-11-22 00:35:00.700871: +2024-11-22 00:35:00.701076: Epoch 2497 +2024-11-22 00:35:00.701222: Current learning rate: 0.00714 +2024-11-22 00:35:20.018300: train_loss -0.75 +2024-11-22 00:35:20.047912: val_loss -0.7701 +2024-11-22 00:35:20.048063: Pseudo dice [0.854] +2024-11-22 00:35:20.048165: Epoch time: 19.32 s +2024-11-22 00:35:21.051747: +2024-11-22 00:35:21.051954: Epoch 2498 +2024-11-22 00:35:21.052074: Current learning rate: 0.00714 +2024-11-22 00:35:39.166234: train_loss -0.7656 +2024-11-22 00:35:39.179972: val_loss -0.7696 +2024-11-22 00:35:39.180139: Pseudo dice [0.845] +2024-11-22 00:35:39.180236: Epoch time: 18.12 s +2024-11-22 00:35:40.279836: +2024-11-22 00:35:40.297895: Epoch 2499 +2024-11-22 00:35:40.298045: Current learning rate: 0.00714 +2024-11-22 00:35:59.334446: train_loss -0.7774 +2024-11-22 00:35:59.344049: val_loss -0.7507 +2024-11-22 00:35:59.344202: Pseudo dice [0.8526] +2024-11-22 00:35:59.346195: Epoch time: 19.06 s +2024-11-22 00:36:00.971527: +2024-11-22 00:36:00.971735: Epoch 2500 +2024-11-22 00:36:00.971851: Current learning rate: 0.00714 +2024-11-22 00:36:19.499940: train_loss -0.773 +2024-11-22 00:36:19.503490: val_loss -0.7598 +2024-11-22 00:36:19.503588: Pseudo dice [0.8533] +2024-11-22 00:36:19.503690: Epoch time: 18.53 s +2024-11-22 00:36:20.342634: +2024-11-22 00:36:20.342875: Epoch 2501 +2024-11-22 00:36:20.343004: Current learning rate: 0.00714 +2024-11-22 00:36:40.543541: train_loss -0.7775 +2024-11-22 00:36:40.551132: val_loss -0.7644 +2024-11-22 00:36:40.551333: Pseudo dice [0.8516] +2024-11-22 00:36:40.551445: Epoch time: 20.2 s +2024-11-22 00:36:41.395978: +2024-11-22 00:36:41.396205: Epoch 2502 +2024-11-22 00:36:41.396329: Current learning rate: 0.00714 +2024-11-22 00:37:00.774225: train_loss -0.7764 +2024-11-22 00:37:00.777018: val_loss -0.7531 +2024-11-22 00:37:00.777149: Pseudo dice [0.8472] +2024-11-22 00:37:00.777254: Epoch time: 19.38 s +2024-11-22 00:37:01.605693: +2024-11-22 00:37:01.605909: Epoch 2503 +2024-11-22 00:37:01.606038: Current learning rate: 0.00713 +2024-11-22 00:37:20.221468: train_loss -0.7827 +2024-11-22 00:37:20.229041: val_loss -0.7434 +2024-11-22 00:37:20.229191: Pseudo dice [0.8553] +2024-11-22 00:37:20.229359: Epoch time: 18.62 s +2024-11-22 00:37:21.069557: +2024-11-22 00:37:21.069776: Epoch 2504 +2024-11-22 00:37:21.069899: Current learning rate: 0.00713 +2024-11-22 00:37:40.348336: train_loss -0.7707 +2024-11-22 00:37:40.354919: val_loss -0.7525 +2024-11-22 00:37:40.355056: Pseudo dice [0.838] +2024-11-22 00:37:40.355158: Epoch time: 19.28 s +2024-11-22 00:37:41.300476: +2024-11-22 00:37:41.300676: Epoch 2505 +2024-11-22 00:37:41.300809: Current learning rate: 0.00713 +2024-11-22 00:37:59.586202: train_loss -0.7708 +2024-11-22 00:37:59.591583: val_loss -0.7574 +2024-11-22 00:37:59.591722: Pseudo dice [0.8603] +2024-11-22 00:37:59.591909: Epoch time: 18.29 s +2024-11-22 00:38:00.574875: +2024-11-22 00:38:00.575099: Epoch 2506 +2024-11-22 00:38:00.575232: Current learning rate: 0.00713 +2024-11-22 00:38:18.585867: train_loss -0.7817 +2024-11-22 00:38:18.592972: val_loss -0.7392 +2024-11-22 00:38:18.593169: Pseudo dice [0.8421] +2024-11-22 00:38:18.593277: Epoch time: 18.01 s +2024-11-22 00:38:19.547347: +2024-11-22 00:38:19.547567: Epoch 2507 +2024-11-22 00:38:19.547688: Current learning rate: 0.00713 +2024-11-22 00:38:38.503748: train_loss -0.7637 +2024-11-22 00:38:38.506230: val_loss -0.768 +2024-11-22 00:38:38.506325: Pseudo dice [0.8497] +2024-11-22 00:38:38.506433: Epoch time: 18.96 s +2024-11-22 00:38:39.337181: +2024-11-22 00:38:39.337400: Epoch 2508 +2024-11-22 00:38:39.337520: Current learning rate: 0.00713 +2024-11-22 00:38:58.026074: train_loss -0.7629 +2024-11-22 00:38:58.027944: val_loss -0.7575 +2024-11-22 00:38:58.028050: Pseudo dice [0.8349] +2024-11-22 00:38:58.028148: Epoch time: 18.69 s +2024-11-22 00:38:58.850793: +2024-11-22 00:38:58.850992: Epoch 2509 +2024-11-22 00:38:58.851130: Current learning rate: 0.00713 +2024-11-22 00:39:18.587576: train_loss -0.7694 +2024-11-22 00:39:18.590240: val_loss -0.7493 +2024-11-22 00:39:18.590333: Pseudo dice [0.849] +2024-11-22 00:39:18.590414: Epoch time: 19.74 s +2024-11-22 00:39:19.415968: +2024-11-22 00:39:19.416171: Epoch 2510 +2024-11-22 00:39:19.416289: Current learning rate: 0.00713 +2024-11-22 00:39:38.370298: train_loss -0.7724 +2024-11-22 00:39:38.376684: val_loss -0.7892 +2024-11-22 00:39:38.376820: Pseudo dice [0.8662] +2024-11-22 00:39:38.376906: Epoch time: 18.96 s +2024-11-22 00:39:39.639596: +2024-11-22 00:39:39.639817: Epoch 2511 +2024-11-22 00:39:39.639941: Current learning rate: 0.00712 +2024-11-22 00:39:58.802816: train_loss -0.7782 +2024-11-22 00:39:58.815845: val_loss -0.7793 +2024-11-22 00:39:58.815993: Pseudo dice [0.849] +2024-11-22 00:39:58.845505: Epoch time: 19.16 s +2024-11-22 00:39:59.765360: +2024-11-22 00:39:59.765631: Epoch 2512 +2024-11-22 00:39:59.765760: Current learning rate: 0.00712 +2024-11-22 00:40:19.632799: train_loss -0.7709 +2024-11-22 00:40:19.636482: val_loss -0.7738 +2024-11-22 00:40:19.636613: Pseudo dice [0.8375] +2024-11-22 00:40:19.636698: Epoch time: 19.87 s +2024-11-22 00:40:20.618901: +2024-11-22 00:40:20.619110: Epoch 2513 +2024-11-22 00:40:20.619238: Current learning rate: 0.00712 +2024-11-22 00:40:39.773365: train_loss -0.7747 +2024-11-22 00:40:39.779582: val_loss -0.7465 +2024-11-22 00:40:39.779790: Pseudo dice [0.8436] +2024-11-22 00:40:39.779899: Epoch time: 19.16 s +2024-11-22 00:40:40.722756: +2024-11-22 00:40:40.722964: Epoch 2514 +2024-11-22 00:40:40.723085: Current learning rate: 0.00712 +2024-11-22 00:40:59.704908: train_loss -0.7827 +2024-11-22 00:40:59.707213: val_loss -0.7867 +2024-11-22 00:40:59.707303: Pseudo dice [0.8665] +2024-11-22 00:40:59.707400: Epoch time: 18.98 s +2024-11-22 00:41:00.536220: +2024-11-22 00:41:00.536420: Epoch 2515 +2024-11-22 00:41:00.536539: Current learning rate: 0.00712 +2024-11-22 00:41:20.064183: train_loss -0.7709 +2024-11-22 00:41:20.069650: val_loss -0.769 +2024-11-22 00:41:20.069828: Pseudo dice [0.8621] +2024-11-22 00:41:20.069930: Epoch time: 19.53 s +2024-11-22 00:41:20.903763: +2024-11-22 00:41:20.903973: Epoch 2516 +2024-11-22 00:41:20.904088: Current learning rate: 0.00712 +2024-11-22 00:41:39.577624: train_loss -0.7828 +2024-11-22 00:41:39.583506: val_loss -0.781 +2024-11-22 00:41:39.583717: Pseudo dice [0.8593] +2024-11-22 00:41:39.583811: Epoch time: 18.67 s +2024-11-22 00:41:40.524855: +2024-11-22 00:41:40.525076: Epoch 2517 +2024-11-22 00:41:40.525194: Current learning rate: 0.00712 +2024-11-22 00:42:00.565088: train_loss -0.7821 +2024-11-22 00:42:00.567911: val_loss -0.7509 +2024-11-22 00:42:00.568019: Pseudo dice [0.8493] +2024-11-22 00:42:00.568118: Epoch time: 20.04 s +2024-11-22 00:42:01.397071: +2024-11-22 00:42:01.397269: Epoch 2518 +2024-11-22 00:42:01.397388: Current learning rate: 0.00712 +2024-11-22 00:42:19.511248: train_loss -0.7878 +2024-11-22 00:42:19.522536: val_loss -0.7811 +2024-11-22 00:42:19.522692: Pseudo dice [0.8578] +2024-11-22 00:42:19.522784: Epoch time: 18.12 s +2024-11-22 00:42:20.387381: +2024-11-22 00:42:20.387584: Epoch 2519 +2024-11-22 00:42:20.387707: Current learning rate: 0.00712 +2024-11-22 00:42:38.846671: train_loss -0.7697 +2024-11-22 00:42:38.850474: val_loss -0.77 +2024-11-22 00:42:38.850594: Pseudo dice [0.8302] +2024-11-22 00:42:38.850692: Epoch time: 18.46 s +2024-11-22 00:42:39.684453: +2024-11-22 00:42:39.684656: Epoch 2520 +2024-11-22 00:42:39.684780: Current learning rate: 0.00711 +2024-11-22 00:42:58.859879: train_loss -0.7816 +2024-11-22 00:42:58.867498: val_loss -0.7539 +2024-11-22 00:42:58.867632: Pseudo dice [0.85] +2024-11-22 00:42:58.867722: Epoch time: 19.18 s +2024-11-22 00:42:59.881436: +2024-11-22 00:42:59.881644: Epoch 2521 +2024-11-22 00:42:59.881766: Current learning rate: 0.00711 +2024-11-22 00:43:18.171870: train_loss -0.778 +2024-11-22 00:43:18.177917: val_loss -0.7521 +2024-11-22 00:43:18.178053: Pseudo dice [0.8455] +2024-11-22 00:43:18.178145: Epoch time: 18.29 s +2024-11-22 00:43:19.481993: +2024-11-22 00:43:19.482203: Epoch 2522 +2024-11-22 00:43:19.482317: Current learning rate: 0.00711 +2024-11-22 00:43:37.775871: train_loss -0.7786 +2024-11-22 00:43:37.778376: val_loss -0.7747 +2024-11-22 00:43:37.778498: Pseudo dice [0.849] +2024-11-22 00:43:37.778592: Epoch time: 18.29 s +2024-11-22 00:43:38.611159: +2024-11-22 00:43:38.611370: Epoch 2523 +2024-11-22 00:43:38.611487: Current learning rate: 0.00711 +2024-11-22 00:43:58.888283: train_loss -0.7782 +2024-11-22 00:43:58.893240: val_loss -0.7784 +2024-11-22 00:43:58.893360: Pseudo dice [0.8467] +2024-11-22 00:43:58.893447: Epoch time: 20.28 s +2024-11-22 00:43:59.720195: +2024-11-22 00:43:59.720470: Epoch 2524 +2024-11-22 00:43:59.720594: Current learning rate: 0.00711 +2024-11-22 00:44:18.509392: train_loss -0.7582 +2024-11-22 00:44:18.516824: val_loss -0.7781 +2024-11-22 00:44:18.516968: Pseudo dice [0.8496] +2024-11-22 00:44:18.517087: Epoch time: 18.79 s +2024-11-22 00:44:19.351359: +2024-11-22 00:44:19.351581: Epoch 2525 +2024-11-22 00:44:19.351718: Current learning rate: 0.00711 +2024-11-22 00:44:38.357534: train_loss -0.7802 +2024-11-22 00:44:38.371385: val_loss -0.7654 +2024-11-22 00:44:38.371538: Pseudo dice [0.8567] +2024-11-22 00:44:38.371644: Epoch time: 19.01 s +2024-11-22 00:44:39.432034: +2024-11-22 00:44:39.432284: Epoch 2526 +2024-11-22 00:44:39.432425: Current learning rate: 0.00711 +2024-11-22 00:44:58.947708: train_loss -0.7784 +2024-11-22 00:44:58.950089: val_loss -0.7265 +2024-11-22 00:44:58.950211: Pseudo dice [0.8492] +2024-11-22 00:44:58.950300: Epoch time: 19.52 s +2024-11-22 00:44:59.783357: +2024-11-22 00:44:59.783562: Epoch 2527 +2024-11-22 00:44:59.783690: Current learning rate: 0.00711 +2024-11-22 00:45:19.334921: train_loss -0.7736 +2024-11-22 00:45:19.341908: val_loss -0.747 +2024-11-22 00:45:19.342019: Pseudo dice [0.8472] +2024-11-22 00:45:19.342111: Epoch time: 19.55 s +2024-11-22 00:45:20.324485: +2024-11-22 00:45:20.324677: Epoch 2528 +2024-11-22 00:45:20.324794: Current learning rate: 0.0071 +2024-11-22 00:45:39.664384: train_loss -0.7821 +2024-11-22 00:45:39.670169: val_loss -0.7737 +2024-11-22 00:45:39.670307: Pseudo dice [0.863] +2024-11-22 00:45:39.670409: Epoch time: 19.34 s +2024-11-22 00:45:40.598940: +2024-11-22 00:45:40.599135: Epoch 2529 +2024-11-22 00:45:40.599253: Current learning rate: 0.0071 +2024-11-22 00:45:59.617346: train_loss -0.7805 +2024-11-22 00:45:59.621864: val_loss -0.7617 +2024-11-22 00:45:59.622066: Pseudo dice [0.8433] +2024-11-22 00:45:59.622173: Epoch time: 19.02 s +2024-11-22 00:46:00.458629: +2024-11-22 00:46:00.458840: Epoch 2530 +2024-11-22 00:46:00.458951: Current learning rate: 0.0071 +2024-11-22 00:46:19.474649: train_loss -0.7768 +2024-11-22 00:46:19.479320: val_loss -0.7789 +2024-11-22 00:46:19.479501: Pseudo dice [0.8533] +2024-11-22 00:46:19.479607: Epoch time: 19.02 s +2024-11-22 00:46:20.425132: +2024-11-22 00:46:20.425336: Epoch 2531 +2024-11-22 00:46:20.425493: Current learning rate: 0.0071 +2024-11-22 00:46:39.698251: train_loss -0.7661 +2024-11-22 00:46:39.704192: val_loss -0.7541 +2024-11-22 00:46:39.704412: Pseudo dice [0.8375] +2024-11-22 00:46:39.704526: Epoch time: 19.27 s +2024-11-22 00:46:40.802092: +2024-11-22 00:46:40.802364: Epoch 2532 +2024-11-22 00:46:40.802494: Current learning rate: 0.0071 +2024-11-22 00:46:59.130133: train_loss -0.7848 +2024-11-22 00:46:59.135184: val_loss -0.7786 +2024-11-22 00:46:59.135314: Pseudo dice [0.8333] +2024-11-22 00:46:59.135412: Epoch time: 18.33 s +2024-11-22 00:46:59.997516: +2024-11-22 00:46:59.997722: Epoch 2533 +2024-11-22 00:46:59.997850: Current learning rate: 0.0071 +2024-11-22 00:47:18.204321: train_loss -0.7779 +2024-11-22 00:47:18.220985: val_loss -0.7631 +2024-11-22 00:47:18.221142: Pseudo dice [0.8177] +2024-11-22 00:47:18.221244: Epoch time: 18.21 s +2024-11-22 00:47:19.699164: +2024-11-22 00:47:19.699390: Epoch 2534 +2024-11-22 00:47:19.699516: Current learning rate: 0.0071 +2024-11-22 00:47:39.665679: train_loss -0.7795 +2024-11-22 00:47:39.672351: val_loss -0.795 +2024-11-22 00:47:39.672478: Pseudo dice [0.8559] +2024-11-22 00:47:39.672587: Epoch time: 19.97 s +2024-11-22 00:47:40.567154: +2024-11-22 00:47:40.567385: Epoch 2535 +2024-11-22 00:47:40.567512: Current learning rate: 0.0071 +2024-11-22 00:48:01.422221: train_loss -0.7694 +2024-11-22 00:48:01.425489: val_loss -0.7579 +2024-11-22 00:48:01.425593: Pseudo dice [0.8442] +2024-11-22 00:48:01.425692: Epoch time: 20.86 s +2024-11-22 00:48:02.256925: +2024-11-22 00:48:02.257197: Epoch 2536 +2024-11-22 00:48:02.257315: Current learning rate: 0.0071 +2024-11-22 00:48:22.094890: train_loss -0.7863 +2024-11-22 00:48:22.104280: val_loss -0.7646 +2024-11-22 00:48:22.104407: Pseudo dice [0.8655] +2024-11-22 00:48:22.104497: Epoch time: 19.84 s +2024-11-22 00:48:23.049787: +2024-11-22 00:48:23.049995: Epoch 2537 +2024-11-22 00:48:23.050367: Current learning rate: 0.00709 +2024-11-22 00:48:43.183443: train_loss -0.7731 +2024-11-22 00:48:43.190788: val_loss -0.7892 +2024-11-22 00:48:43.190951: Pseudo dice [0.8528] +2024-11-22 00:48:43.191074: Epoch time: 20.13 s +2024-11-22 00:48:44.053552: +2024-11-22 00:48:44.053762: Epoch 2538 +2024-11-22 00:48:44.053883: Current learning rate: 0.00709 +2024-11-22 00:49:01.964938: train_loss -0.7847 +2024-11-22 00:49:01.971766: val_loss -0.7657 +2024-11-22 00:49:01.971913: Pseudo dice [0.8467] +2024-11-22 00:49:01.972082: Epoch time: 17.91 s +2024-11-22 00:49:02.858112: +2024-11-22 00:49:02.858321: Epoch 2539 +2024-11-22 00:49:02.858433: Current learning rate: 0.00709 +2024-11-22 00:49:21.633324: train_loss -0.7794 +2024-11-22 00:49:21.635852: val_loss -0.7632 +2024-11-22 00:49:21.635963: Pseudo dice [0.8467] +2024-11-22 00:49:21.636064: Epoch time: 18.78 s +2024-11-22 00:49:22.472369: +2024-11-22 00:49:22.472618: Epoch 2540 +2024-11-22 00:49:22.472746: Current learning rate: 0.00709 +2024-11-22 00:49:41.934762: train_loss -0.7843 +2024-11-22 00:49:41.947152: val_loss -0.7682 +2024-11-22 00:49:41.947288: Pseudo dice [0.8509] +2024-11-22 00:49:41.947374: Epoch time: 19.46 s +2024-11-22 00:49:42.786983: +2024-11-22 00:49:42.787182: Epoch 2541 +2024-11-22 00:49:42.787322: Current learning rate: 0.00709 +2024-11-22 00:50:02.873028: train_loss -0.7729 +2024-11-22 00:50:02.881661: val_loss -0.7569 +2024-11-22 00:50:02.881854: Pseudo dice [0.8473] +2024-11-22 00:50:02.881944: Epoch time: 20.09 s +2024-11-22 00:50:03.730413: +2024-11-22 00:50:03.730609: Epoch 2542 +2024-11-22 00:50:03.730727: Current learning rate: 0.00709 +2024-11-22 00:50:23.004333: train_loss -0.7754 +2024-11-22 00:50:23.012331: val_loss -0.7705 +2024-11-22 00:50:23.012456: Pseudo dice [0.8469] +2024-11-22 00:50:23.012561: Epoch time: 19.27 s +2024-11-22 00:50:23.839250: +2024-11-22 00:50:23.839450: Epoch 2543 +2024-11-22 00:50:23.839587: Current learning rate: 0.00709 +2024-11-22 00:50:42.407828: train_loss -0.7708 +2024-11-22 00:50:42.414281: val_loss -0.7581 +2024-11-22 00:50:42.414481: Pseudo dice [0.8405] +2024-11-22 00:50:42.414575: Epoch time: 18.57 s +2024-11-22 00:50:43.294540: +2024-11-22 00:50:43.294762: Epoch 2544 +2024-11-22 00:50:43.294899: Current learning rate: 0.00709 +2024-11-22 00:51:02.778832: train_loss -0.763 +2024-11-22 00:51:02.787818: val_loss -0.7402 +2024-11-22 00:51:02.787961: Pseudo dice [0.8523] +2024-11-22 00:51:02.788084: Epoch time: 19.49 s +2024-11-22 00:51:04.194943: +2024-11-22 00:51:04.195198: Epoch 2545 +2024-11-22 00:51:04.195333: Current learning rate: 0.00708 +2024-11-22 00:51:22.838450: train_loss -0.7703 +2024-11-22 00:51:22.841530: val_loss -0.7758 +2024-11-22 00:51:22.841670: Pseudo dice [0.845] +2024-11-22 00:51:22.841758: Epoch time: 18.64 s +2024-11-22 00:51:23.774610: +2024-11-22 00:51:23.774912: Epoch 2546 +2024-11-22 00:51:23.775037: Current learning rate: 0.00708 +2024-11-22 00:51:42.311366: train_loss -0.7655 +2024-11-22 00:51:42.316983: val_loss -0.7694 +2024-11-22 00:51:42.317145: Pseudo dice [0.8437] +2024-11-22 00:51:42.317232: Epoch time: 18.54 s +2024-11-22 00:51:43.147005: +2024-11-22 00:51:43.147210: Epoch 2547 +2024-11-22 00:51:43.147338: Current learning rate: 0.00708 +2024-11-22 00:52:03.293169: train_loss -0.7677 +2024-11-22 00:52:03.316638: val_loss -0.7621 +2024-11-22 00:52:03.316769: Pseudo dice [0.8439] +2024-11-22 00:52:03.316863: Epoch time: 20.15 s +2024-11-22 00:52:04.261595: +2024-11-22 00:52:04.261809: Epoch 2548 +2024-11-22 00:52:04.261945: Current learning rate: 0.00708 +2024-11-22 00:52:23.598307: train_loss -0.7692 +2024-11-22 00:52:23.605648: val_loss -0.7857 +2024-11-22 00:52:23.605848: Pseudo dice [0.8656] +2024-11-22 00:52:23.605940: Epoch time: 19.34 s +2024-11-22 00:52:24.444160: +2024-11-22 00:52:24.444445: Epoch 2549 +2024-11-22 00:52:24.444584: Current learning rate: 0.00708 +2024-11-22 00:52:44.809464: train_loss -0.7749 +2024-11-22 00:52:44.811805: val_loss -0.778 +2024-11-22 00:52:44.811900: Pseudo dice [0.8403] +2024-11-22 00:52:44.812252: Epoch time: 20.37 s +2024-11-22 00:52:45.871278: +2024-11-22 00:52:45.871494: Epoch 2550 +2024-11-22 00:52:45.871628: Current learning rate: 0.00708 +2024-11-22 00:53:05.522478: train_loss -0.7738 +2024-11-22 00:53:05.529720: val_loss -0.7728 +2024-11-22 00:53:05.529848: Pseudo dice [0.8514] +2024-11-22 00:53:05.529927: Epoch time: 19.65 s +2024-11-22 00:53:06.530839: +2024-11-22 00:53:06.531037: Epoch 2551 +2024-11-22 00:53:06.531158: Current learning rate: 0.00708 +2024-11-22 00:53:25.843585: train_loss -0.7703 +2024-11-22 00:53:25.850175: val_loss -0.7367 +2024-11-22 00:53:25.850315: Pseudo dice [0.8388] +2024-11-22 00:53:25.850398: Epoch time: 19.31 s +2024-11-22 00:53:26.690989: +2024-11-22 00:53:26.691192: Epoch 2552 +2024-11-22 00:53:26.691318: Current learning rate: 0.00708 +2024-11-22 00:53:43.870148: train_loss -0.7606 +2024-11-22 00:53:43.878781: val_loss -0.7318 +2024-11-22 00:53:43.878920: Pseudo dice [0.849] +2024-11-22 00:53:43.879037: Epoch time: 17.18 s +2024-11-22 00:53:44.865047: +2024-11-22 00:53:44.865261: Epoch 2553 +2024-11-22 00:53:44.865392: Current learning rate: 0.00708 +2024-11-22 00:54:02.825442: train_loss -0.7686 +2024-11-22 00:54:02.832045: val_loss -0.7755 +2024-11-22 00:54:02.832220: Pseudo dice [0.8544] +2024-11-22 00:54:02.832310: Epoch time: 17.96 s +2024-11-22 00:54:03.671010: +2024-11-22 00:54:03.671235: Epoch 2554 +2024-11-22 00:54:03.671358: Current learning rate: 0.00707 +2024-11-22 00:54:23.286406: train_loss -0.7789 +2024-11-22 00:54:23.293343: val_loss -0.7922 +2024-11-22 00:54:23.293480: Pseudo dice [0.8572] +2024-11-22 00:54:23.293579: Epoch time: 19.62 s +2024-11-22 00:54:24.144847: +2024-11-22 00:54:24.145049: Epoch 2555 +2024-11-22 00:54:24.145166: Current learning rate: 0.00707 +2024-11-22 00:54:42.422347: train_loss -0.7765 +2024-11-22 00:54:42.431028: val_loss -0.7694 +2024-11-22 00:54:42.431245: Pseudo dice [0.8534] +2024-11-22 00:54:42.431359: Epoch time: 18.28 s +2024-11-22 00:54:43.263179: +2024-11-22 00:54:43.263608: Epoch 2556 +2024-11-22 00:54:43.263752: Current learning rate: 0.00707 +2024-11-22 00:55:01.798555: train_loss -0.7737 +2024-11-22 00:55:01.807259: val_loss -0.7681 +2024-11-22 00:55:01.807425: Pseudo dice [0.8466] +2024-11-22 00:55:01.807516: Epoch time: 18.54 s +2024-11-22 00:55:02.705154: +2024-11-22 00:55:02.705356: Epoch 2557 +2024-11-22 00:55:02.705486: Current learning rate: 0.00707 +2024-11-22 00:55:22.149455: train_loss -0.7689 +2024-11-22 00:55:22.155357: val_loss -0.7492 +2024-11-22 00:55:22.155496: Pseudo dice [0.8398] +2024-11-22 00:55:22.155582: Epoch time: 19.45 s +2024-11-22 00:55:23.098560: +2024-11-22 00:55:23.098767: Epoch 2558 +2024-11-22 00:55:23.098884: Current learning rate: 0.00707 +2024-11-22 00:55:41.979615: train_loss -0.7726 +2024-11-22 00:55:41.985957: val_loss -0.775 +2024-11-22 00:55:41.986155: Pseudo dice [0.8464] +2024-11-22 00:55:41.986260: Epoch time: 18.88 s +2024-11-22 00:55:42.884479: +2024-11-22 00:55:42.884716: Epoch 2559 +2024-11-22 00:55:42.884836: Current learning rate: 0.00707 +2024-11-22 00:56:00.983274: train_loss -0.7698 +2024-11-22 00:56:00.987393: val_loss -0.7845 +2024-11-22 00:56:00.987545: Pseudo dice [0.8547] +2024-11-22 00:56:00.987645: Epoch time: 18.1 s +2024-11-22 00:56:01.975340: +2024-11-22 00:56:01.975567: Epoch 2560 +2024-11-22 00:56:01.975699: Current learning rate: 0.00707 +2024-11-22 00:56:20.310529: train_loss -0.7725 +2024-11-22 00:56:20.319579: val_loss -0.7628 +2024-11-22 00:56:20.319713: Pseudo dice [0.8493] +2024-11-22 00:56:20.319796: Epoch time: 18.34 s +2024-11-22 00:56:21.354287: +2024-11-22 00:56:21.354486: Epoch 2561 +2024-11-22 00:56:21.354617: Current learning rate: 0.00707 +2024-11-22 00:56:40.311244: train_loss -0.7831 +2024-11-22 00:56:40.321988: val_loss -0.7496 +2024-11-22 00:56:40.322161: Pseudo dice [0.8391] +2024-11-22 00:56:40.322266: Epoch time: 18.96 s +2024-11-22 00:56:41.170860: +2024-11-22 00:56:41.171067: Epoch 2562 +2024-11-22 00:56:41.171186: Current learning rate: 0.00707 +2024-11-22 00:57:00.372416: train_loss -0.7759 +2024-11-22 00:57:00.382935: val_loss -0.763 +2024-11-22 00:57:00.383116: Pseudo dice [0.8428] +2024-11-22 00:57:00.383225: Epoch time: 19.2 s +2024-11-22 00:57:01.214630: +2024-11-22 00:57:01.214845: Epoch 2563 +2024-11-22 00:57:01.214973: Current learning rate: 0.00706 +2024-11-22 00:57:20.688634: train_loss -0.7826 +2024-11-22 00:57:20.726943: val_loss -0.7566 +2024-11-22 00:57:20.727137: Pseudo dice [0.8481] +2024-11-22 00:57:20.727243: Epoch time: 19.47 s +2024-11-22 00:57:21.659186: +2024-11-22 00:57:21.659376: Epoch 2564 +2024-11-22 00:57:21.659497: Current learning rate: 0.00706 +2024-11-22 00:57:40.535587: train_loss -0.7773 +2024-11-22 00:57:40.554487: val_loss -0.7673 +2024-11-22 00:57:40.554659: Pseudo dice [0.8486] +2024-11-22 00:57:40.554771: Epoch time: 18.88 s +2024-11-22 00:57:41.575223: +2024-11-22 00:57:41.575428: Epoch 2565 +2024-11-22 00:57:41.575549: Current learning rate: 0.00706 +2024-11-22 00:58:01.659267: train_loss -0.7716 +2024-11-22 00:58:01.715056: val_loss -0.7825 +2024-11-22 00:58:01.715246: Pseudo dice [0.8517] +2024-11-22 00:58:01.715348: Epoch time: 20.08 s +2024-11-22 00:58:02.662146: +2024-11-22 00:58:02.662352: Epoch 2566 +2024-11-22 00:58:02.662466: Current learning rate: 0.00706 +2024-11-22 00:58:21.359634: train_loss -0.7818 +2024-11-22 00:58:21.384307: val_loss -0.7656 +2024-11-22 00:58:21.384480: Pseudo dice [0.8507] +2024-11-22 00:58:21.384587: Epoch time: 18.7 s +2024-11-22 00:58:22.728297: +2024-11-22 00:58:22.728513: Epoch 2567 +2024-11-22 00:58:22.728648: Current learning rate: 0.00706 +2024-11-22 00:58:41.137626: train_loss -0.7735 +2024-11-22 00:58:41.161999: val_loss -0.7402 +2024-11-22 00:58:41.162175: Pseudo dice [0.8415] +2024-11-22 00:58:41.162292: Epoch time: 18.41 s +2024-11-22 00:58:42.014889: +2024-11-22 00:58:42.015125: Epoch 2568 +2024-11-22 00:58:42.015242: Current learning rate: 0.00706 +2024-11-22 00:59:01.485450: train_loss -0.7756 +2024-11-22 00:59:01.506567: val_loss -0.7711 +2024-11-22 00:59:01.506723: Pseudo dice [0.8524] +2024-11-22 00:59:01.506821: Epoch time: 19.47 s +2024-11-22 00:59:02.510678: +2024-11-22 00:59:02.510888: Epoch 2569 +2024-11-22 00:59:02.511004: Current learning rate: 0.00706 +2024-11-22 00:59:20.244395: train_loss -0.7761 +2024-11-22 00:59:20.254839: val_loss -0.7809 +2024-11-22 00:59:20.254971: Pseudo dice [0.8431] +2024-11-22 00:59:20.255084: Epoch time: 17.73 s +2024-11-22 00:59:21.167942: +2024-11-22 00:59:21.168157: Epoch 2570 +2024-11-22 00:59:21.168277: Current learning rate: 0.00706 +2024-11-22 00:59:40.207726: train_loss -0.7712 +2024-11-22 00:59:40.210061: val_loss -0.7731 +2024-11-22 00:59:40.210160: Pseudo dice [0.8524] +2024-11-22 00:59:40.210257: Epoch time: 19.04 s +2024-11-22 00:59:41.052616: +2024-11-22 00:59:41.052831: Epoch 2571 +2024-11-22 00:59:41.052960: Current learning rate: 0.00705 +2024-11-22 00:59:59.396558: train_loss -0.7732 +2024-11-22 00:59:59.414225: val_loss -0.7622 +2024-11-22 00:59:59.414372: Pseudo dice [0.8507] +2024-11-22 00:59:59.414473: Epoch time: 18.34 s +2024-11-22 01:00:00.248835: +2024-11-22 01:00:00.249033: Epoch 2572 +2024-11-22 01:00:00.249164: Current learning rate: 0.00705 +2024-11-22 01:00:19.242378: train_loss -0.7765 +2024-11-22 01:00:19.249294: val_loss -0.7661 +2024-11-22 01:00:19.249448: Pseudo dice [0.8511] +2024-11-22 01:00:19.249541: Epoch time: 18.99 s +2024-11-22 01:00:20.109516: +2024-11-22 01:00:20.109738: Epoch 2573 +2024-11-22 01:00:20.109872: Current learning rate: 0.00705 +2024-11-22 01:00:39.459289: train_loss -0.7774 +2024-11-22 01:00:39.465537: val_loss -0.7629 +2024-11-22 01:00:39.465656: Pseudo dice [0.8594] +2024-11-22 01:00:39.465759: Epoch time: 19.35 s +2024-11-22 01:00:40.296081: +2024-11-22 01:00:40.296295: Epoch 2574 +2024-11-22 01:00:40.296407: Current learning rate: 0.00705 +2024-11-22 01:00:59.362135: train_loss -0.7788 +2024-11-22 01:00:59.372312: val_loss -0.7714 +2024-11-22 01:00:59.372458: Pseudo dice [0.8541] +2024-11-22 01:00:59.372555: Epoch time: 19.07 s +2024-11-22 01:01:00.220186: +2024-11-22 01:01:00.220408: Epoch 2575 +2024-11-22 01:01:00.220526: Current learning rate: 0.00705 +2024-11-22 01:01:19.566995: train_loss -0.762 +2024-11-22 01:01:19.579552: val_loss -0.7653 +2024-11-22 01:01:19.579776: Pseudo dice [0.8562] +2024-11-22 01:01:19.579867: Epoch time: 19.35 s +2024-11-22 01:01:20.422553: +2024-11-22 01:01:20.422759: Epoch 2576 +2024-11-22 01:01:20.422897: Current learning rate: 0.00705 +2024-11-22 01:01:38.520585: train_loss -0.762 +2024-11-22 01:01:38.537291: val_loss -0.739 +2024-11-22 01:01:38.537437: Pseudo dice [0.8374] +2024-11-22 01:01:38.537519: Epoch time: 18.1 s +2024-11-22 01:01:39.464262: +2024-11-22 01:01:39.464479: Epoch 2577 +2024-11-22 01:01:39.464612: Current learning rate: 0.00705 +2024-11-22 01:01:57.807571: train_loss -0.7432 +2024-11-22 01:01:57.814285: val_loss -0.7794 +2024-11-22 01:01:57.814478: Pseudo dice [0.8434] +2024-11-22 01:01:57.814604: Epoch time: 18.34 s +2024-11-22 01:01:58.700750: +2024-11-22 01:01:58.700958: Epoch 2578 +2024-11-22 01:01:58.701093: Current learning rate: 0.00705 +2024-11-22 01:02:18.698572: train_loss -0.7653 +2024-11-22 01:02:18.707408: val_loss -0.7681 +2024-11-22 01:02:18.707581: Pseudo dice [0.8489] +2024-11-22 01:02:18.707691: Epoch time: 20.0 s +2024-11-22 01:02:19.958497: +2024-11-22 01:02:19.958747: Epoch 2579 +2024-11-22 01:02:19.958878: Current learning rate: 0.00705 +2024-11-22 01:02:39.055235: train_loss -0.7728 +2024-11-22 01:02:39.061979: val_loss -0.7705 +2024-11-22 01:02:39.062110: Pseudo dice [0.8567] +2024-11-22 01:02:39.062202: Epoch time: 19.1 s +2024-11-22 01:02:39.903754: +2024-11-22 01:02:39.903978: Epoch 2580 +2024-11-22 01:02:39.904116: Current learning rate: 0.00704 +2024-11-22 01:02:59.559943: train_loss -0.765 +2024-11-22 01:02:59.568546: val_loss -0.7472 +2024-11-22 01:02:59.568713: Pseudo dice [0.8477] +2024-11-22 01:02:59.568804: Epoch time: 19.66 s +2024-11-22 01:03:00.540401: +2024-11-22 01:03:00.540597: Epoch 2581 +2024-11-22 01:03:00.540715: Current learning rate: 0.00704 +2024-11-22 01:03:19.588877: train_loss -0.7805 +2024-11-22 01:03:19.592259: val_loss -0.7521 +2024-11-22 01:03:19.592389: Pseudo dice [0.8471] +2024-11-22 01:03:19.592549: Epoch time: 19.05 s +2024-11-22 01:03:20.643077: +2024-11-22 01:03:20.643290: Epoch 2582 +2024-11-22 01:03:20.643415: Current learning rate: 0.00704 +2024-11-22 01:03:38.861651: train_loss -0.7668 +2024-11-22 01:03:38.866165: val_loss -0.7638 +2024-11-22 01:03:38.866354: Pseudo dice [0.8472] +2024-11-22 01:03:38.866444: Epoch time: 18.22 s +2024-11-22 01:03:39.781825: +2024-11-22 01:03:39.782037: Epoch 2583 +2024-11-22 01:03:39.782164: Current learning rate: 0.00704 +2024-11-22 01:03:59.128169: train_loss -0.7741 +2024-11-22 01:03:59.130914: val_loss -0.7732 +2024-11-22 01:03:59.131016: Pseudo dice [0.8546] +2024-11-22 01:03:59.131109: Epoch time: 19.35 s +2024-11-22 01:03:59.960258: +2024-11-22 01:03:59.960448: Epoch 2584 +2024-11-22 01:03:59.960564: Current learning rate: 0.00704 +2024-11-22 01:04:19.437160: train_loss -0.7684 +2024-11-22 01:04:19.447718: val_loss -0.7606 +2024-11-22 01:04:19.447862: Pseudo dice [0.8411] +2024-11-22 01:04:19.447966: Epoch time: 19.48 s +2024-11-22 01:04:20.279197: +2024-11-22 01:04:20.279420: Epoch 2585 +2024-11-22 01:04:20.279545: Current learning rate: 0.00704 +2024-11-22 01:04:39.755748: train_loss -0.775 +2024-11-22 01:04:39.764538: val_loss -0.7753 +2024-11-22 01:04:39.764694: Pseudo dice [0.8363] +2024-11-22 01:04:39.764789: Epoch time: 19.48 s +2024-11-22 01:04:40.713551: +2024-11-22 01:04:40.713758: Epoch 2586 +2024-11-22 01:04:40.713897: Current learning rate: 0.00704 +2024-11-22 01:05:00.631842: train_loss -0.7746 +2024-11-22 01:05:00.640790: val_loss -0.7603 +2024-11-22 01:05:00.640917: Pseudo dice [0.8544] +2024-11-22 01:05:00.641016: Epoch time: 19.92 s +2024-11-22 01:05:01.530319: +2024-11-22 01:05:01.530519: Epoch 2587 +2024-11-22 01:05:01.530643: Current learning rate: 0.00704 +2024-11-22 01:05:21.836169: train_loss -0.7678 +2024-11-22 01:05:21.842862: val_loss -0.7566 +2024-11-22 01:05:21.842984: Pseudo dice [0.8534] +2024-11-22 01:05:21.843088: Epoch time: 20.31 s +2024-11-22 01:05:22.787398: +2024-11-22 01:05:22.787611: Epoch 2588 +2024-11-22 01:05:22.787754: Current learning rate: 0.00703 +2024-11-22 01:05:41.205900: train_loss -0.7847 +2024-11-22 01:05:41.223629: val_loss -0.7713 +2024-11-22 01:05:41.223785: Pseudo dice [0.851] +2024-11-22 01:05:41.223884: Epoch time: 18.42 s +2024-11-22 01:05:42.050432: +2024-11-22 01:05:42.050646: Epoch 2589 +2024-11-22 01:05:42.050772: Current learning rate: 0.00703 +2024-11-22 01:06:02.144284: train_loss -0.7862 +2024-11-22 01:06:02.167576: val_loss -0.766 +2024-11-22 01:06:02.167755: Pseudo dice [0.8516] +2024-11-22 01:06:02.167852: Epoch time: 20.09 s +2024-11-22 01:06:03.422208: +2024-11-22 01:06:03.422455: Epoch 2590 +2024-11-22 01:06:03.422573: Current learning rate: 0.00703 +2024-11-22 01:06:22.576694: train_loss -0.7801 +2024-11-22 01:06:22.594952: val_loss -0.7516 +2024-11-22 01:06:22.595121: Pseudo dice [0.848] +2024-11-22 01:06:22.595213: Epoch time: 19.16 s +2024-11-22 01:06:23.426711: +2024-11-22 01:06:23.426924: Epoch 2591 +2024-11-22 01:06:23.427042: Current learning rate: 0.00703 +2024-11-22 01:06:42.332854: train_loss -0.7774 +2024-11-22 01:06:42.372625: val_loss -0.7439 +2024-11-22 01:06:42.372794: Pseudo dice [0.8223] +2024-11-22 01:06:42.372904: Epoch time: 18.91 s +2024-11-22 01:06:43.238820: +2024-11-22 01:06:43.239056: Epoch 2592 +2024-11-22 01:06:43.239180: Current learning rate: 0.00703 +2024-11-22 01:07:02.894819: train_loss -0.7721 +2024-11-22 01:07:02.933332: val_loss -0.7544 +2024-11-22 01:07:02.933523: Pseudo dice [0.8489] +2024-11-22 01:07:02.933636: Epoch time: 19.66 s +2024-11-22 01:07:03.808029: +2024-11-22 01:07:03.808246: Epoch 2593 +2024-11-22 01:07:03.808382: Current learning rate: 0.00703 +2024-11-22 01:07:21.996791: train_loss -0.7715 +2024-11-22 01:07:22.002398: val_loss -0.7805 +2024-11-22 01:07:22.002549: Pseudo dice [0.8559] +2024-11-22 01:07:22.002653: Epoch time: 18.19 s +2024-11-22 01:07:22.895252: +2024-11-22 01:07:22.895489: Epoch 2594 +2024-11-22 01:07:22.895617: Current learning rate: 0.00703 +2024-11-22 01:07:41.841235: train_loss -0.7894 +2024-11-22 01:07:41.863721: val_loss -0.7819 +2024-11-22 01:07:41.863881: Pseudo dice [0.8386] +2024-11-22 01:07:41.863971: Epoch time: 18.95 s +2024-11-22 01:07:42.759252: +2024-11-22 01:07:42.759827: Epoch 2595 +2024-11-22 01:07:42.759957: Current learning rate: 0.00703 +2024-11-22 01:08:01.224367: train_loss -0.7849 +2024-11-22 01:08:01.227304: val_loss -0.7933 +2024-11-22 01:08:01.227458: Pseudo dice [0.8686] +2024-11-22 01:08:01.227550: Epoch time: 18.47 s +2024-11-22 01:08:02.175950: +2024-11-22 01:08:02.176506: Epoch 2596 +2024-11-22 01:08:02.176623: Current learning rate: 0.00703 +2024-11-22 01:08:21.366876: train_loss -0.7747 +2024-11-22 01:08:21.402284: val_loss -0.776 +2024-11-22 01:08:21.402501: Pseudo dice [0.8517] +2024-11-22 01:08:21.402605: Epoch time: 19.19 s +2024-11-22 01:08:22.338413: +2024-11-22 01:08:22.338602: Epoch 2597 +2024-11-22 01:08:22.338712: Current learning rate: 0.00702 +2024-11-22 01:08:41.294027: train_loss -0.7717 +2024-11-22 01:08:41.304747: val_loss -0.7311 +2024-11-22 01:08:41.304896: Pseudo dice [0.8408] +2024-11-22 01:08:41.304998: Epoch time: 18.96 s +2024-11-22 01:08:42.283418: +2024-11-22 01:08:42.283615: Epoch 2598 +2024-11-22 01:08:42.283734: Current learning rate: 0.00702 +2024-11-22 01:09:01.152184: train_loss -0.748 +2024-11-22 01:09:01.174134: val_loss -0.7449 +2024-11-22 01:09:01.174287: Pseudo dice [0.8372] +2024-11-22 01:09:01.174392: Epoch time: 18.87 s +2024-11-22 01:09:02.254285: +2024-11-22 01:09:02.254498: Epoch 2599 +2024-11-22 01:09:02.254637: Current learning rate: 0.00702 +2024-11-22 01:09:21.369053: train_loss -0.7663 +2024-11-22 01:09:21.371504: val_loss -0.7697 +2024-11-22 01:09:21.371662: Pseudo dice [0.8435] +2024-11-22 01:09:21.371769: Epoch time: 19.12 s +2024-11-22 01:09:22.417582: +2024-11-22 01:09:22.417795: Epoch 2600 +2024-11-22 01:09:22.417911: Current learning rate: 0.00702 +2024-11-22 01:09:42.426927: train_loss -0.7728 +2024-11-22 01:09:42.480879: val_loss -0.759 +2024-11-22 01:09:42.487177: Pseudo dice [0.8443] +2024-11-22 01:09:42.487326: Epoch time: 20.01 s +2024-11-22 01:09:43.374664: +2024-11-22 01:09:43.374913: Epoch 2601 +2024-11-22 01:09:43.375028: Current learning rate: 0.00702 +2024-11-22 01:10:01.827817: train_loss -0.7664 +2024-11-22 01:10:01.836424: val_loss -0.7535 +2024-11-22 01:10:01.836547: Pseudo dice [0.8549] +2024-11-22 01:10:01.836653: Epoch time: 18.45 s +2024-11-22 01:10:02.918814: +2024-11-22 01:10:02.919012: Epoch 2602 +2024-11-22 01:10:02.919140: Current learning rate: 0.00702 +2024-11-22 01:10:21.565663: train_loss -0.7738 +2024-11-22 01:10:21.568323: val_loss -0.7683 +2024-11-22 01:10:21.568434: Pseudo dice [0.8415] +2024-11-22 01:10:21.568535: Epoch time: 18.65 s +2024-11-22 01:10:22.397615: +2024-11-22 01:10:22.397832: Epoch 2603 +2024-11-22 01:10:22.397956: Current learning rate: 0.00702 +2024-11-22 01:10:40.928472: train_loss -0.7715 +2024-11-22 01:10:40.937198: val_loss -0.7525 +2024-11-22 01:10:40.937420: Pseudo dice [0.8451] +2024-11-22 01:10:40.937511: Epoch time: 18.53 s +2024-11-22 01:10:42.058215: +2024-11-22 01:10:42.058427: Epoch 2604 +2024-11-22 01:10:42.058556: Current learning rate: 0.00702 +2024-11-22 01:11:01.325666: train_loss -0.777 +2024-11-22 01:11:01.364463: val_loss -0.7589 +2024-11-22 01:11:01.364641: Pseudo dice [0.8407] +2024-11-22 01:11:01.364739: Epoch time: 19.27 s +2024-11-22 01:11:02.269717: +2024-11-22 01:11:02.269956: Epoch 2605 +2024-11-22 01:11:02.270083: Current learning rate: 0.00701 +2024-11-22 01:11:22.033552: train_loss -0.778 +2024-11-22 01:11:22.039693: val_loss -0.7797 +2024-11-22 01:11:22.039822: Pseudo dice [0.85] +2024-11-22 01:11:22.039931: Epoch time: 19.76 s +2024-11-22 01:11:23.012434: +2024-11-22 01:11:23.012658: Epoch 2606 +2024-11-22 01:11:23.012781: Current learning rate: 0.00701 +2024-11-22 01:11:41.705521: train_loss -0.7669 +2024-11-22 01:11:41.716404: val_loss -0.7545 +2024-11-22 01:11:41.716556: Pseudo dice [0.8348] +2024-11-22 01:11:41.716647: Epoch time: 18.69 s +2024-11-22 01:11:42.559834: +2024-11-22 01:11:42.560039: Epoch 2607 +2024-11-22 01:11:42.560179: Current learning rate: 0.00701 +2024-11-22 01:12:02.597367: train_loss -0.7771 +2024-11-22 01:12:02.601089: val_loss -0.751 +2024-11-22 01:12:02.601233: Pseudo dice [0.8497] +2024-11-22 01:12:02.601320: Epoch time: 20.04 s +2024-11-22 01:12:03.555664: +2024-11-22 01:12:03.555861: Epoch 2608 +2024-11-22 01:12:03.555995: Current learning rate: 0.00701 +2024-11-22 01:12:22.264753: train_loss -0.782 +2024-11-22 01:12:22.271640: val_loss -0.7671 +2024-11-22 01:12:22.271774: Pseudo dice [0.8537] +2024-11-22 01:12:22.271877: Epoch time: 18.71 s +2024-11-22 01:12:23.255317: +2024-11-22 01:12:23.255546: Epoch 2609 +2024-11-22 01:12:23.255666: Current learning rate: 0.00701 +2024-11-22 01:12:42.471504: train_loss -0.7651 +2024-11-22 01:12:42.480016: val_loss -0.7306 +2024-11-22 01:12:42.480181: Pseudo dice [0.8376] +2024-11-22 01:12:42.480285: Epoch time: 19.22 s +2024-11-22 01:12:43.415612: +2024-11-22 01:12:43.415796: Epoch 2610 +2024-11-22 01:12:43.415927: Current learning rate: 0.00701 +2024-11-22 01:13:03.620071: train_loss -0.769 +2024-11-22 01:13:03.637291: val_loss -0.7288 +2024-11-22 01:13:03.637400: Pseudo dice [0.845] +2024-11-22 01:13:03.637487: Epoch time: 20.21 s +2024-11-22 01:13:04.457785: +2024-11-22 01:13:04.457993: Epoch 2611 +2024-11-22 01:13:04.458106: Current learning rate: 0.00701 +2024-11-22 01:13:24.637604: train_loss -0.7853 +2024-11-22 01:13:24.640025: val_loss -0.7791 +2024-11-22 01:13:24.640121: Pseudo dice [0.8565] +2024-11-22 01:13:24.640201: Epoch time: 20.18 s +2024-11-22 01:13:25.835846: +2024-11-22 01:13:25.836066: Epoch 2612 +2024-11-22 01:13:25.836187: Current learning rate: 0.00701 +2024-11-22 01:13:44.739220: train_loss -0.7721 +2024-11-22 01:13:44.745634: val_loss -0.7584 +2024-11-22 01:13:44.745865: Pseudo dice [0.8468] +2024-11-22 01:13:44.745975: Epoch time: 18.9 s +2024-11-22 01:13:45.761847: +2024-11-22 01:13:45.762046: Epoch 2613 +2024-11-22 01:13:45.762186: Current learning rate: 0.00701 +2024-11-22 01:14:03.486686: train_loss -0.7726 +2024-11-22 01:14:03.516557: val_loss -0.7772 +2024-11-22 01:14:03.516736: Pseudo dice [0.8564] +2024-11-22 01:14:03.516846: Epoch time: 17.72 s +2024-11-22 01:14:04.422560: +2024-11-22 01:14:04.422778: Epoch 2614 +2024-11-22 01:14:04.422907: Current learning rate: 0.007 +2024-11-22 01:14:22.458269: train_loss -0.7725 +2024-11-22 01:14:22.477705: val_loss -0.7768 +2024-11-22 01:14:22.477859: Pseudo dice [0.8374] +2024-11-22 01:14:22.478132: Epoch time: 18.04 s +2024-11-22 01:14:23.371537: +2024-11-22 01:14:23.371742: Epoch 2615 +2024-11-22 01:14:23.371855: Current learning rate: 0.007 +2024-11-22 01:14:43.063374: train_loss -0.7816 +2024-11-22 01:14:43.080107: val_loss -0.769 +2024-11-22 01:14:43.080260: Pseudo dice [0.8619] +2024-11-22 01:14:43.080348: Epoch time: 19.69 s +2024-11-22 01:14:44.081480: +2024-11-22 01:14:44.081697: Epoch 2616 +2024-11-22 01:14:44.081814: Current learning rate: 0.007 +2024-11-22 01:15:03.669749: train_loss -0.7751 +2024-11-22 01:15:03.707495: val_loss -0.7552 +2024-11-22 01:15:03.707678: Pseudo dice [0.8435] +2024-11-22 01:15:03.707786: Epoch time: 19.59 s +2024-11-22 01:15:04.611782: +2024-11-22 01:15:04.611978: Epoch 2617 +2024-11-22 01:15:04.612102: Current learning rate: 0.007 +2024-11-22 01:15:23.700696: train_loss -0.7647 +2024-11-22 01:15:23.713536: val_loss -0.7694 +2024-11-22 01:15:23.713675: Pseudo dice [0.8507] +2024-11-22 01:15:23.713777: Epoch time: 19.09 s +2024-11-22 01:15:24.687682: +2024-11-22 01:15:24.687931: Epoch 2618 +2024-11-22 01:15:24.688077: Current learning rate: 0.007 +2024-11-22 01:15:44.255251: train_loss -0.7626 +2024-11-22 01:15:44.268290: val_loss -0.7679 +2024-11-22 01:15:44.268438: Pseudo dice [0.8476] +2024-11-22 01:15:44.268532: Epoch time: 19.57 s +2024-11-22 01:15:45.282004: +2024-11-22 01:15:45.282233: Epoch 2619 +2024-11-22 01:15:45.282361: Current learning rate: 0.007 +2024-11-22 01:16:05.676064: train_loss -0.7641 +2024-11-22 01:16:05.680113: val_loss -0.7884 +2024-11-22 01:16:05.680274: Pseudo dice [0.8604] +2024-11-22 01:16:05.680374: Epoch time: 20.39 s +2024-11-22 01:16:06.606759: +2024-11-22 01:16:06.606961: Epoch 2620 +2024-11-22 01:16:06.607099: Current learning rate: 0.007 +2024-11-22 01:16:24.912863: train_loss -0.7749 +2024-11-22 01:16:24.934078: val_loss -0.7651 +2024-11-22 01:16:24.934225: Pseudo dice [0.8384] +2024-11-22 01:16:24.934328: Epoch time: 18.31 s +2024-11-22 01:16:25.930406: +2024-11-22 01:16:25.930655: Epoch 2621 +2024-11-22 01:16:25.930801: Current learning rate: 0.007 +2024-11-22 01:16:45.410464: train_loss -0.7765 +2024-11-22 01:16:45.413319: val_loss -0.7685 +2024-11-22 01:16:45.413428: Pseudo dice [0.846] +2024-11-22 01:16:45.413515: Epoch time: 19.48 s +2024-11-22 01:16:46.244145: +2024-11-22 01:16:46.244350: Epoch 2622 +2024-11-22 01:16:46.244461: Current learning rate: 0.00699 +2024-11-22 01:17:03.920483: train_loss -0.7808 +2024-11-22 01:17:03.926233: val_loss -0.7547 +2024-11-22 01:17:03.926373: Pseudo dice [0.8513] +2024-11-22 01:17:03.926459: Epoch time: 17.68 s +2024-11-22 01:17:04.790893: +2024-11-22 01:17:04.791097: Epoch 2623 +2024-11-22 01:17:04.791229: Current learning rate: 0.00699 +2024-11-22 01:17:23.126994: train_loss -0.7819 +2024-11-22 01:17:23.135425: val_loss -0.7801 +2024-11-22 01:17:23.135596: Pseudo dice [0.8603] +2024-11-22 01:17:23.135729: Epoch time: 18.34 s +2024-11-22 01:17:24.421656: +2024-11-22 01:17:24.421857: Epoch 2624 +2024-11-22 01:17:24.421976: Current learning rate: 0.00699 +2024-11-22 01:17:43.988635: train_loss -0.786 +2024-11-22 01:17:44.011217: val_loss -0.7679 +2024-11-22 01:17:44.011374: Pseudo dice [0.8473] +2024-11-22 01:17:44.011466: Epoch time: 19.57 s +2024-11-22 01:17:44.904113: +2024-11-22 01:17:44.904355: Epoch 2625 +2024-11-22 01:17:44.904473: Current learning rate: 0.00699 +2024-11-22 01:18:03.344650: train_loss -0.778 +2024-11-22 01:18:03.352131: val_loss -0.775 +2024-11-22 01:18:03.352264: Pseudo dice [0.8537] +2024-11-22 01:18:03.352350: Epoch time: 18.44 s +2024-11-22 01:18:04.179105: +2024-11-22 01:18:04.179574: Epoch 2626 +2024-11-22 01:18:04.179705: Current learning rate: 0.00699 +2024-11-22 01:18:23.296938: train_loss -0.7843 +2024-11-22 01:18:23.299413: val_loss -0.7752 +2024-11-22 01:18:23.299516: Pseudo dice [0.8526] +2024-11-22 01:18:23.299614: Epoch time: 19.12 s +2024-11-22 01:18:24.136498: +2024-11-22 01:18:24.136721: Epoch 2627 +2024-11-22 01:18:24.136848: Current learning rate: 0.00699 +2024-11-22 01:18:43.072446: train_loss -0.7785 +2024-11-22 01:18:43.105752: val_loss -0.7582 +2024-11-22 01:18:43.105916: Pseudo dice [0.8529] +2024-11-22 01:18:43.106031: Epoch time: 18.94 s +2024-11-22 01:18:44.033537: +2024-11-22 01:18:44.033746: Epoch 2628 +2024-11-22 01:18:44.033882: Current learning rate: 0.00699 +2024-11-22 01:19:02.790575: train_loss -0.7798 +2024-11-22 01:19:02.795517: val_loss -0.7692 +2024-11-22 01:19:02.795657: Pseudo dice [0.8481] +2024-11-22 01:19:02.795755: Epoch time: 18.76 s +2024-11-22 01:19:03.648288: +2024-11-22 01:19:03.648524: Epoch 2629 +2024-11-22 01:19:03.648663: Current learning rate: 0.00699 +2024-11-22 01:19:23.016567: train_loss -0.7834 +2024-11-22 01:19:23.027418: val_loss -0.7526 +2024-11-22 01:19:23.027573: Pseudo dice [0.8498] +2024-11-22 01:19:23.027654: Epoch time: 19.37 s +2024-11-22 01:19:23.963766: +2024-11-22 01:19:23.963959: Epoch 2630 +2024-11-22 01:19:23.964085: Current learning rate: 0.00699 +2024-11-22 01:19:42.989821: train_loss -0.778 +2024-11-22 01:19:42.997341: val_loss -0.7574 +2024-11-22 01:19:42.997521: Pseudo dice [0.8438] +2024-11-22 01:19:42.997659: Epoch time: 19.03 s +2024-11-22 01:19:43.831770: +2024-11-22 01:19:43.831964: Epoch 2631 +2024-11-22 01:19:43.832184: Current learning rate: 0.00698 +2024-11-22 01:20:02.692754: train_loss -0.7785 +2024-11-22 01:20:02.696080: val_loss -0.7295 +2024-11-22 01:20:02.696194: Pseudo dice [0.8503] +2024-11-22 01:20:02.696301: Epoch time: 18.86 s +2024-11-22 01:20:03.531675: +2024-11-22 01:20:03.531907: Epoch 2632 +2024-11-22 01:20:03.532040: Current learning rate: 0.00698 +2024-11-22 01:20:22.573764: train_loss -0.7795 +2024-11-22 01:20:22.582371: val_loss -0.75 +2024-11-22 01:20:22.582523: Pseudo dice [0.8431] +2024-11-22 01:20:22.582650: Epoch time: 19.04 s +2024-11-22 01:20:23.566289: +2024-11-22 01:20:23.566477: Epoch 2633 +2024-11-22 01:20:23.566589: Current learning rate: 0.00698 +2024-11-22 01:20:42.829143: train_loss -0.783 +2024-11-22 01:20:42.839566: val_loss -0.773 +2024-11-22 01:20:42.839688: Pseudo dice [0.8552] +2024-11-22 01:20:42.839777: Epoch time: 19.26 s +2024-11-22 01:20:43.696048: +2024-11-22 01:20:43.696254: Epoch 2634 +2024-11-22 01:20:43.696386: Current learning rate: 0.00698 +2024-11-22 01:21:03.130158: train_loss -0.7611 +2024-11-22 01:21:03.138149: val_loss -0.7578 +2024-11-22 01:21:03.138289: Pseudo dice [0.8404] +2024-11-22 01:21:03.138394: Epoch time: 19.43 s +2024-11-22 01:21:04.421380: +2024-11-22 01:21:04.421625: Epoch 2635 +2024-11-22 01:21:04.421741: Current learning rate: 0.00698 +2024-11-22 01:21:23.304824: train_loss -0.7774 +2024-11-22 01:21:23.307612: val_loss -0.7774 +2024-11-22 01:21:23.307743: Pseudo dice [0.8574] +2024-11-22 01:21:23.307840: Epoch time: 18.88 s +2024-11-22 01:21:24.258229: +2024-11-22 01:21:24.258452: Epoch 2636 +2024-11-22 01:21:24.258587: Current learning rate: 0.00698 +2024-11-22 01:21:42.207000: train_loss -0.785 +2024-11-22 01:21:42.213727: val_loss -0.7638 +2024-11-22 01:21:42.213891: Pseudo dice [0.8441] +2024-11-22 01:21:42.213993: Epoch time: 17.95 s +2024-11-22 01:21:43.142159: +2024-11-22 01:21:43.142368: Epoch 2637 +2024-11-22 01:21:43.142487: Current learning rate: 0.00698 +2024-11-22 01:22:02.285595: train_loss -0.7853 +2024-11-22 01:22:02.288327: val_loss -0.7661 +2024-11-22 01:22:02.288452: Pseudo dice [0.8471] +2024-11-22 01:22:02.288539: Epoch time: 19.14 s +2024-11-22 01:22:03.263081: +2024-11-22 01:22:03.263295: Epoch 2638 +2024-11-22 01:22:03.263421: Current learning rate: 0.00698 +2024-11-22 01:22:21.244925: train_loss -0.7695 +2024-11-22 01:22:21.259793: val_loss -0.735 +2024-11-22 01:22:21.259959: Pseudo dice [0.8396] +2024-11-22 01:22:21.260402: Epoch time: 17.98 s +2024-11-22 01:22:22.125677: +2024-11-22 01:22:22.125905: Epoch 2639 +2024-11-22 01:22:22.126022: Current learning rate: 0.00697 +2024-11-22 01:22:39.982521: train_loss -0.7699 +2024-11-22 01:22:39.984403: val_loss -0.7428 +2024-11-22 01:22:39.984517: Pseudo dice [0.8525] +2024-11-22 01:22:39.984613: Epoch time: 17.86 s +2024-11-22 01:22:40.821407: +2024-11-22 01:22:40.821608: Epoch 2640 +2024-11-22 01:22:40.821734: Current learning rate: 0.00697 +2024-11-22 01:22:59.762444: train_loss -0.7725 +2024-11-22 01:22:59.768865: val_loss -0.7586 +2024-11-22 01:22:59.769027: Pseudo dice [0.846] +2024-11-22 01:22:59.769148: Epoch time: 18.94 s +2024-11-22 01:23:00.612217: +2024-11-22 01:23:00.612423: Epoch 2641 +2024-11-22 01:23:00.612555: Current learning rate: 0.00697 +2024-11-22 01:23:20.228670: train_loss -0.7572 +2024-11-22 01:23:20.234275: val_loss -0.7784 +2024-11-22 01:23:20.234473: Pseudo dice [0.8546] +2024-11-22 01:23:20.234579: Epoch time: 19.62 s +2024-11-22 01:23:21.101150: +2024-11-22 01:23:21.101371: Epoch 2642 +2024-11-22 01:23:21.101509: Current learning rate: 0.00697 +2024-11-22 01:23:39.140537: train_loss -0.7826 +2024-11-22 01:23:39.147893: val_loss -0.7866 +2024-11-22 01:23:39.148015: Pseudo dice [0.8487] +2024-11-22 01:23:39.148178: Epoch time: 18.04 s +2024-11-22 01:23:40.000558: +2024-11-22 01:23:40.000747: Epoch 2643 +2024-11-22 01:23:40.000873: Current learning rate: 0.00697 +2024-11-22 01:23:58.096343: train_loss -0.771 +2024-11-22 01:23:58.103717: val_loss -0.7728 +2024-11-22 01:23:58.103854: Pseudo dice [0.8475] +2024-11-22 01:23:58.103956: Epoch time: 18.1 s +2024-11-22 01:23:58.949680: +2024-11-22 01:23:58.949885: Epoch 2644 +2024-11-22 01:23:58.950004: Current learning rate: 0.00697 +2024-11-22 01:24:18.694516: train_loss -0.7831 +2024-11-22 01:24:18.702241: val_loss -0.75 +2024-11-22 01:24:18.702373: Pseudo dice [0.8551] +2024-11-22 01:24:18.702465: Epoch time: 19.75 s +2024-11-22 01:24:19.559161: +2024-11-22 01:24:19.559370: Epoch 2645 +2024-11-22 01:24:19.559519: Current learning rate: 0.00697 +2024-11-22 01:24:38.720082: train_loss -0.7791 +2024-11-22 01:24:38.735669: val_loss -0.7616 +2024-11-22 01:24:38.735839: Pseudo dice [0.8516] +2024-11-22 01:24:38.735929: Epoch time: 19.16 s +2024-11-22 01:24:39.569783: +2024-11-22 01:24:39.569998: Epoch 2646 +2024-11-22 01:24:39.570128: Current learning rate: 0.00697 +2024-11-22 01:24:58.712497: train_loss -0.7668 +2024-11-22 01:24:58.719129: val_loss -0.7524 +2024-11-22 01:24:58.719283: Pseudo dice [0.8385] +2024-11-22 01:24:58.719375: Epoch time: 19.14 s +2024-11-22 01:24:59.955536: +2024-11-22 01:24:59.955751: Epoch 2647 +2024-11-22 01:24:59.955871: Current learning rate: 0.00697 +2024-11-22 01:25:18.787018: train_loss -0.7711 +2024-11-22 01:25:18.789793: val_loss -0.7867 +2024-11-22 01:25:18.789907: Pseudo dice [0.8529] +2024-11-22 01:25:18.790000: Epoch time: 18.83 s +2024-11-22 01:25:19.616825: +2024-11-22 01:25:19.617034: Epoch 2648 +2024-11-22 01:25:19.617165: Current learning rate: 0.00696 +2024-11-22 01:25:38.656777: train_loss -0.7806 +2024-11-22 01:25:38.665105: val_loss -0.7817 +2024-11-22 01:25:38.665251: Pseudo dice [0.8601] +2024-11-22 01:25:38.665414: Epoch time: 19.04 s +2024-11-22 01:25:39.578702: +2024-11-22 01:25:39.579251: Epoch 2649 +2024-11-22 01:25:39.579380: Current learning rate: 0.00696 +2024-11-22 01:25:58.557868: train_loss -0.7733 +2024-11-22 01:25:58.562453: val_loss -0.7708 +2024-11-22 01:25:58.562599: Pseudo dice [0.8438] +2024-11-22 01:25:58.562699: Epoch time: 18.98 s +2024-11-22 01:25:59.699481: +2024-11-22 01:25:59.699729: Epoch 2650 +2024-11-22 01:25:59.699868: Current learning rate: 0.00696 +2024-11-22 01:26:19.451975: train_loss -0.7788 +2024-11-22 01:26:19.463987: val_loss -0.7664 +2024-11-22 01:26:19.464140: Pseudo dice [0.8449] +2024-11-22 01:26:19.464244: Epoch time: 19.75 s +2024-11-22 01:26:20.471448: +2024-11-22 01:26:20.471638: Epoch 2651 +2024-11-22 01:26:20.471762: Current learning rate: 0.00696 +2024-11-22 01:26:39.691737: train_loss -0.774 +2024-11-22 01:26:39.700746: val_loss -0.752 +2024-11-22 01:26:39.700891: Pseudo dice [0.8494] +2024-11-22 01:26:39.700990: Epoch time: 19.22 s +2024-11-22 01:26:40.636187: +2024-11-22 01:26:40.636413: Epoch 2652 +2024-11-22 01:26:40.636528: Current learning rate: 0.00696 +2024-11-22 01:27:00.047494: train_loss -0.7714 +2024-11-22 01:27:00.055537: val_loss -0.7577 +2024-11-22 01:27:00.055701: Pseudo dice [0.8318] +2024-11-22 01:27:00.055801: Epoch time: 19.41 s +2024-11-22 01:27:00.912657: +2024-11-22 01:27:00.912849: Epoch 2653 +2024-11-22 01:27:00.912967: Current learning rate: 0.00696 +2024-11-22 01:27:20.188619: train_loss -0.7756 +2024-11-22 01:27:20.194740: val_loss -0.7414 +2024-11-22 01:27:20.194889: Pseudo dice [0.8445] +2024-11-22 01:27:20.194988: Epoch time: 19.28 s +2024-11-22 01:27:21.028335: +2024-11-22 01:27:21.028531: Epoch 2654 +2024-11-22 01:27:21.028658: Current learning rate: 0.00696 +2024-11-22 01:27:39.449369: train_loss -0.7866 +2024-11-22 01:27:39.467233: val_loss -0.7788 +2024-11-22 01:27:39.467381: Pseudo dice [0.8655] +2024-11-22 01:27:39.467475: Epoch time: 18.42 s +2024-11-22 01:27:40.334042: +2024-11-22 01:27:40.334274: Epoch 2655 +2024-11-22 01:27:40.334386: Current learning rate: 0.00696 +2024-11-22 01:27:59.510183: train_loss -0.7849 +2024-11-22 01:27:59.524525: val_loss -0.7739 +2024-11-22 01:27:59.524668: Pseudo dice [0.8471] +2024-11-22 01:27:59.524756: Epoch time: 19.18 s +2024-11-22 01:28:00.425374: +2024-11-22 01:28:00.425600: Epoch 2656 +2024-11-22 01:28:00.425724: Current learning rate: 0.00696 +2024-11-22 01:28:19.890785: train_loss -0.7736 +2024-11-22 01:28:19.898757: val_loss -0.7599 +2024-11-22 01:28:19.898920: Pseudo dice [0.8454] +2024-11-22 01:28:19.899028: Epoch time: 19.47 s +2024-11-22 01:28:20.741328: +2024-11-22 01:28:20.741563: Epoch 2657 +2024-11-22 01:28:20.741697: Current learning rate: 0.00695 +2024-11-22 01:28:39.942366: train_loss -0.7754 +2024-11-22 01:28:39.951519: val_loss -0.7851 +2024-11-22 01:28:39.951680: Pseudo dice [0.8621] +2024-11-22 01:28:39.951787: Epoch time: 19.2 s +2024-11-22 01:28:41.199347: +2024-11-22 01:28:41.199564: Epoch 2658 +2024-11-22 01:28:41.199681: Current learning rate: 0.00695 +2024-11-22 01:29:00.563623: train_loss -0.7861 +2024-11-22 01:29:00.571156: val_loss -0.7614 +2024-11-22 01:29:00.571308: Pseudo dice [0.8522] +2024-11-22 01:29:00.571393: Epoch time: 19.37 s +2024-11-22 01:29:01.665103: +2024-11-22 01:29:01.665322: Epoch 2659 +2024-11-22 01:29:01.665443: Current learning rate: 0.00695 +2024-11-22 01:29:20.428525: train_loss -0.776 +2024-11-22 01:29:20.434569: val_loss -0.768 +2024-11-22 01:29:20.434717: Pseudo dice [0.8477] +2024-11-22 01:29:20.434820: Epoch time: 18.76 s +2024-11-22 01:29:21.317865: +2024-11-22 01:29:21.318090: Epoch 2660 +2024-11-22 01:29:21.318225: Current learning rate: 0.00695 +2024-11-22 01:29:40.869213: train_loss -0.7702 +2024-11-22 01:29:40.882920: val_loss -0.7741 +2024-11-22 01:29:40.883056: Pseudo dice [0.8448] +2024-11-22 01:29:40.883158: Epoch time: 19.55 s +2024-11-22 01:29:41.759414: +2024-11-22 01:29:41.759640: Epoch 2661 +2024-11-22 01:29:41.759764: Current learning rate: 0.00695 +2024-11-22 01:29:59.755474: train_loss -0.7751 +2024-11-22 01:29:59.758216: val_loss -0.7553 +2024-11-22 01:29:59.758385: Pseudo dice [0.8359] +2024-11-22 01:29:59.758491: Epoch time: 18.0 s +2024-11-22 01:30:00.582156: +2024-11-22 01:30:00.582378: Epoch 2662 +2024-11-22 01:30:00.582522: Current learning rate: 0.00695 +2024-11-22 01:30:19.639550: train_loss -0.7726 +2024-11-22 01:30:19.648172: val_loss -0.7629 +2024-11-22 01:30:19.648407: Pseudo dice [0.8467] +2024-11-22 01:30:19.648532: Epoch time: 19.06 s +2024-11-22 01:30:20.503185: +2024-11-22 01:30:20.503426: Epoch 2663 +2024-11-22 01:30:20.503556: Current learning rate: 0.00695 +2024-11-22 01:30:39.405151: train_loss -0.767 +2024-11-22 01:30:39.415083: val_loss -0.7697 +2024-11-22 01:30:39.415225: Pseudo dice [0.8515] +2024-11-22 01:30:39.415321: Epoch time: 18.9 s +2024-11-22 01:30:40.435218: +2024-11-22 01:30:40.435454: Epoch 2664 +2024-11-22 01:30:40.435838: Current learning rate: 0.00695 +2024-11-22 01:31:00.681497: train_loss -0.7703 +2024-11-22 01:31:00.686513: val_loss -0.7494 +2024-11-22 01:31:00.686623: Pseudo dice [0.8323] +2024-11-22 01:31:00.686707: Epoch time: 20.25 s +2024-11-22 01:31:01.524579: +2024-11-22 01:31:01.524794: Epoch 2665 +2024-11-22 01:31:01.524920: Current learning rate: 0.00694 +2024-11-22 01:31:19.717428: train_loss -0.7665 +2024-11-22 01:31:19.724373: val_loss -0.7626 +2024-11-22 01:31:19.724520: Pseudo dice [0.8527] +2024-11-22 01:31:19.724614: Epoch time: 18.19 s +2024-11-22 01:31:20.554874: +2024-11-22 01:31:20.555079: Epoch 2666 +2024-11-22 01:31:20.555212: Current learning rate: 0.00694 +2024-11-22 01:31:39.289304: train_loss -0.7781 +2024-11-22 01:31:39.302256: val_loss -0.7539 +2024-11-22 01:31:39.302410: Pseudo dice [0.8426] +2024-11-22 01:31:39.302498: Epoch time: 18.74 s +2024-11-22 01:31:40.144003: +2024-11-22 01:31:40.144227: Epoch 2667 +2024-11-22 01:31:40.144353: Current learning rate: 0.00694 +2024-11-22 01:31:59.706213: train_loss -0.7856 +2024-11-22 01:31:59.712969: val_loss -0.7638 +2024-11-22 01:31:59.713109: Pseudo dice [0.841] +2024-11-22 01:31:59.713264: Epoch time: 19.56 s +2024-11-22 01:32:00.687970: +2024-11-22 01:32:00.688182: Epoch 2668 +2024-11-22 01:32:00.688314: Current learning rate: 0.00694 +2024-11-22 01:32:19.396350: train_loss -0.7829 +2024-11-22 01:32:19.405512: val_loss -0.756 +2024-11-22 01:32:19.405723: Pseudo dice [0.8483] +2024-11-22 01:32:19.405813: Epoch time: 18.71 s +2024-11-22 01:32:20.798497: +2024-11-22 01:32:20.798729: Epoch 2669 +2024-11-22 01:32:20.798851: Current learning rate: 0.00694 +2024-11-22 01:32:40.933758: train_loss -0.7831 +2024-11-22 01:32:40.939480: val_loss -0.7689 +2024-11-22 01:32:40.939604: Pseudo dice [0.857] +2024-11-22 01:32:40.939698: Epoch time: 20.14 s +2024-11-22 01:32:41.924807: +2024-11-22 01:32:41.925045: Epoch 2670 +2024-11-22 01:32:41.925189: Current learning rate: 0.00694 +2024-11-22 01:33:00.944379: train_loss -0.7786 +2024-11-22 01:33:00.953044: val_loss -0.7554 +2024-11-22 01:33:00.953178: Pseudo dice [0.8609] +2024-11-22 01:33:00.953280: Epoch time: 19.02 s +2024-11-22 01:33:01.812662: +2024-11-22 01:33:01.812885: Epoch 2671 +2024-11-22 01:33:01.813001: Current learning rate: 0.00694 +2024-11-22 01:33:20.173336: train_loss -0.7798 +2024-11-22 01:33:20.188526: val_loss -0.7808 +2024-11-22 01:33:20.188645: Pseudo dice [0.8469] +2024-11-22 01:33:20.188742: Epoch time: 18.36 s +2024-11-22 01:33:21.120463: +2024-11-22 01:33:21.120680: Epoch 2672 +2024-11-22 01:33:21.120797: Current learning rate: 0.00694 +2024-11-22 01:33:40.072288: train_loss -0.7769 +2024-11-22 01:33:40.086036: val_loss -0.7832 +2024-11-22 01:33:40.086182: Pseudo dice [0.8464] +2024-11-22 01:33:40.086280: Epoch time: 18.95 s +2024-11-22 01:33:41.120711: +2024-11-22 01:33:41.120928: Epoch 2673 +2024-11-22 01:33:41.121040: Current learning rate: 0.00694 +2024-11-22 01:33:59.843570: train_loss -0.7835 +2024-11-22 01:33:59.850005: val_loss -0.756 +2024-11-22 01:33:59.850133: Pseudo dice [0.8468] +2024-11-22 01:33:59.850221: Epoch time: 18.72 s +2024-11-22 01:34:00.724316: +2024-11-22 01:34:00.724583: Epoch 2674 +2024-11-22 01:34:00.724725: Current learning rate: 0.00693 +2024-11-22 01:34:18.867010: train_loss -0.7857 +2024-11-22 01:34:18.873724: val_loss -0.7669 +2024-11-22 01:34:18.873881: Pseudo dice [0.8604] +2024-11-22 01:34:18.873977: Epoch time: 18.14 s +2024-11-22 01:34:19.746925: +2024-11-22 01:34:19.747148: Epoch 2675 +2024-11-22 01:34:19.747264: Current learning rate: 0.00693 +2024-11-22 01:34:39.740573: train_loss -0.7784 +2024-11-22 01:34:39.743088: val_loss -0.759 +2024-11-22 01:34:39.743229: Pseudo dice [0.8496] +2024-11-22 01:34:39.743399: Epoch time: 19.99 s +2024-11-22 01:34:40.571164: +2024-11-22 01:34:40.571354: Epoch 2676 +2024-11-22 01:34:40.571473: Current learning rate: 0.00693 +2024-11-22 01:34:59.615599: train_loss -0.7811 +2024-11-22 01:34:59.622370: val_loss -0.7899 +2024-11-22 01:34:59.622523: Pseudo dice [0.8569] +2024-11-22 01:34:59.622602: Epoch time: 19.05 s +2024-11-22 01:35:00.480376: +2024-11-22 01:35:00.480590: Epoch 2677 +2024-11-22 01:35:00.480721: Current learning rate: 0.00693 +2024-11-22 01:35:19.262292: train_loss -0.7935 +2024-11-22 01:35:19.269612: val_loss -0.7467 +2024-11-22 01:35:19.269754: Pseudo dice [0.8398] +2024-11-22 01:35:19.269854: Epoch time: 18.78 s +2024-11-22 01:35:20.098116: +2024-11-22 01:35:20.098326: Epoch 2678 +2024-11-22 01:35:20.098606: Current learning rate: 0.00693 +2024-11-22 01:35:39.099447: train_loss -0.7866 +2024-11-22 01:35:39.102727: val_loss -0.7786 +2024-11-22 01:35:39.102843: Pseudo dice [0.8602] +2024-11-22 01:35:39.102952: Epoch time: 19.0 s +2024-11-22 01:35:39.941797: +2024-11-22 01:35:39.942014: Epoch 2679 +2024-11-22 01:35:39.942142: Current learning rate: 0.00693 +2024-11-22 01:35:59.383413: train_loss -0.7829 +2024-11-22 01:35:59.391814: val_loss -0.7493 +2024-11-22 01:35:59.399380: Pseudo dice [0.8608] +2024-11-22 01:35:59.399497: Epoch time: 19.44 s +2024-11-22 01:36:00.349773: +2024-11-22 01:36:00.349991: Epoch 2680 +2024-11-22 01:36:00.350117: Current learning rate: 0.00693 +2024-11-22 01:36:20.072017: train_loss -0.7801 +2024-11-22 01:36:20.080181: val_loss -0.7636 +2024-11-22 01:36:20.080328: Pseudo dice [0.8352] +2024-11-22 01:36:20.080435: Epoch time: 19.72 s +2024-11-22 01:36:21.524114: +2024-11-22 01:36:21.524388: Epoch 2681 +2024-11-22 01:36:21.524523: Current learning rate: 0.00693 +2024-11-22 01:36:41.489711: train_loss -0.7801 +2024-11-22 01:36:41.496413: val_loss -0.769 +2024-11-22 01:36:41.496603: Pseudo dice [0.8474] +2024-11-22 01:36:41.496754: Epoch time: 19.97 s +2024-11-22 01:36:42.436970: +2024-11-22 01:36:42.437230: Epoch 2682 +2024-11-22 01:36:42.437383: Current learning rate: 0.00692 +2024-11-22 01:37:00.872893: train_loss -0.7854 +2024-11-22 01:37:00.880665: val_loss -0.7343 +2024-11-22 01:37:00.880805: Pseudo dice [0.8444] +2024-11-22 01:37:00.880905: Epoch time: 18.44 s +2024-11-22 01:37:01.716798: +2024-11-22 01:37:01.717013: Epoch 2683 +2024-11-22 01:37:01.717153: Current learning rate: 0.00692 +2024-11-22 01:37:20.819585: train_loss -0.7704 +2024-11-22 01:37:20.826337: val_loss -0.7493 +2024-11-22 01:37:20.826533: Pseudo dice [0.8578] +2024-11-22 01:37:20.826641: Epoch time: 19.1 s +2024-11-22 01:37:21.718770: +2024-11-22 01:37:21.718995: Epoch 2684 +2024-11-22 01:37:21.719137: Current learning rate: 0.00692 +2024-11-22 01:37:41.307047: train_loss -0.783 +2024-11-22 01:37:41.315746: val_loss -0.7526 +2024-11-22 01:37:41.322089: Pseudo dice [0.8489] +2024-11-22 01:37:41.322208: Epoch time: 19.59 s +2024-11-22 01:37:42.162357: +2024-11-22 01:37:42.162563: Epoch 2685 +2024-11-22 01:37:42.162677: Current learning rate: 0.00692 +2024-11-22 01:38:02.196954: train_loss -0.7647 +2024-11-22 01:38:02.206004: val_loss -0.7361 +2024-11-22 01:38:02.206145: Pseudo dice [0.8509] +2024-11-22 01:38:02.206237: Epoch time: 20.04 s +2024-11-22 01:38:03.065053: +2024-11-22 01:38:03.065269: Epoch 2686 +2024-11-22 01:38:03.065400: Current learning rate: 0.00692 +2024-11-22 01:38:21.794835: train_loss -0.7833 +2024-11-22 01:38:21.797777: val_loss -0.7759 +2024-11-22 01:38:21.797886: Pseudo dice [0.8581] +2024-11-22 01:38:21.797969: Epoch time: 18.73 s +2024-11-22 01:38:22.624111: +2024-11-22 01:38:22.624335: Epoch 2687 +2024-11-22 01:38:22.624475: Current learning rate: 0.00692 +2024-11-22 01:38:42.424775: train_loss -0.7786 +2024-11-22 01:38:42.428479: val_loss -0.7474 +2024-11-22 01:38:42.428599: Pseudo dice [0.8528] +2024-11-22 01:38:42.428696: Epoch time: 19.8 s +2024-11-22 01:38:43.265309: +2024-11-22 01:38:43.265498: Epoch 2688 +2024-11-22 01:38:43.265621: Current learning rate: 0.00692 +2024-11-22 01:39:01.843291: train_loss -0.7854 +2024-11-22 01:39:01.852215: val_loss -0.7595 +2024-11-22 01:39:01.852361: Pseudo dice [0.8538] +2024-11-22 01:39:01.852458: Epoch time: 18.58 s +2024-11-22 01:39:02.820304: +2024-11-22 01:39:02.820513: Epoch 2689 +2024-11-22 01:39:02.820628: Current learning rate: 0.00692 +2024-11-22 01:39:21.200569: train_loss -0.7781 +2024-11-22 01:39:21.208735: val_loss -0.7782 +2024-11-22 01:39:21.209611: Pseudo dice [0.8524] +2024-11-22 01:39:21.209752: Epoch time: 18.38 s +2024-11-22 01:39:22.287352: +2024-11-22 01:39:22.287551: Epoch 2690 +2024-11-22 01:39:22.287683: Current learning rate: 0.00692 +2024-11-22 01:39:41.098163: train_loss -0.7829 +2024-11-22 01:39:41.104217: val_loss -0.757 +2024-11-22 01:39:41.104363: Pseudo dice [0.8489] +2024-11-22 01:39:41.104459: Epoch time: 18.81 s +2024-11-22 01:39:41.942630: +2024-11-22 01:39:41.942825: Epoch 2691 +2024-11-22 01:39:41.942947: Current learning rate: 0.00691 +2024-11-22 01:40:01.522919: train_loss -0.7767 +2024-11-22 01:40:01.528062: val_loss -0.766 +2024-11-22 01:40:01.528198: Pseudo dice [0.8547] +2024-11-22 01:40:01.528277: Epoch time: 19.58 s +2024-11-22 01:40:02.751593: +2024-11-22 01:40:02.751858: Epoch 2692 +2024-11-22 01:40:02.751980: Current learning rate: 0.00691 +2024-11-22 01:40:21.124408: train_loss -0.7863 +2024-11-22 01:40:21.131233: val_loss -0.7512 +2024-11-22 01:40:21.131374: Pseudo dice [0.8432] +2024-11-22 01:40:21.131498: Epoch time: 18.37 s +2024-11-22 01:40:22.019392: +2024-11-22 01:40:22.019693: Epoch 2693 +2024-11-22 01:40:22.019813: Current learning rate: 0.00691 +2024-11-22 01:40:40.939977: train_loss -0.7791 +2024-11-22 01:40:40.945349: val_loss -0.7877 +2024-11-22 01:40:40.945493: Pseudo dice [0.8498] +2024-11-22 01:40:40.945642: Epoch time: 18.92 s +2024-11-22 01:40:41.834357: +2024-11-22 01:40:41.834572: Epoch 2694 +2024-11-22 01:40:41.834697: Current learning rate: 0.00691 +2024-11-22 01:41:00.496648: train_loss -0.7888 +2024-11-22 01:41:00.502727: val_loss -0.7454 +2024-11-22 01:41:00.502847: Pseudo dice [0.841] +2024-11-22 01:41:00.502951: Epoch time: 18.66 s +2024-11-22 01:41:01.606308: +2024-11-22 01:41:01.606538: Epoch 2695 +2024-11-22 01:41:01.606653: Current learning rate: 0.00691 +2024-11-22 01:41:19.715597: train_loss -0.7819 +2024-11-22 01:41:19.717897: val_loss -0.7473 +2024-11-22 01:41:19.718013: Pseudo dice [0.8474] +2024-11-22 01:41:19.718108: Epoch time: 18.11 s +2024-11-22 01:41:20.772751: +2024-11-22 01:41:20.772981: Epoch 2696 +2024-11-22 01:41:20.773123: Current learning rate: 0.00691 +2024-11-22 01:41:40.116564: train_loss -0.7835 +2024-11-22 01:41:40.122316: val_loss -0.7485 +2024-11-22 01:41:40.122481: Pseudo dice [0.8511] +2024-11-22 01:41:40.122578: Epoch time: 19.34 s +2024-11-22 01:41:40.968959: +2024-11-22 01:41:40.969176: Epoch 2697 +2024-11-22 01:41:40.969287: Current learning rate: 0.00691 +2024-11-22 01:41:59.928602: train_loss -0.7906 +2024-11-22 01:41:59.934944: val_loss -0.7965 +2024-11-22 01:41:59.935082: Pseudo dice [0.8616] +2024-11-22 01:41:59.935168: Epoch time: 18.96 s +2024-11-22 01:42:00.778414: +2024-11-22 01:42:00.778600: Epoch 2698 +2024-11-22 01:42:00.778721: Current learning rate: 0.00691 +2024-11-22 01:42:20.506086: train_loss -0.7837 +2024-11-22 01:42:20.510490: val_loss -0.8055 +2024-11-22 01:42:20.510614: Pseudo dice [0.8469] +2024-11-22 01:42:20.510713: Epoch time: 19.73 s +2024-11-22 01:42:21.341968: +2024-11-22 01:42:21.342183: Epoch 2699 +2024-11-22 01:42:21.342306: Current learning rate: 0.0069 +2024-11-22 01:42:39.731228: train_loss -0.7844 +2024-11-22 01:42:39.738695: val_loss -0.7609 +2024-11-22 01:42:39.738829: Pseudo dice [0.8419] +2024-11-22 01:42:39.738944: Epoch time: 18.39 s +2024-11-22 01:42:40.826028: +2024-11-22 01:42:40.826236: Epoch 2700 +2024-11-22 01:42:40.826358: Current learning rate: 0.0069 +2024-11-22 01:42:59.779971: train_loss -0.7859 +2024-11-22 01:42:59.782563: val_loss -0.7759 +2024-11-22 01:42:59.782663: Pseudo dice [0.8534] +2024-11-22 01:42:59.782746: Epoch time: 18.95 s +2024-11-22 01:43:00.616326: +2024-11-22 01:43:00.616588: Epoch 2701 +2024-11-22 01:43:00.616714: Current learning rate: 0.0069 +2024-11-22 01:43:19.875009: train_loss -0.7846 +2024-11-22 01:43:19.881375: val_loss -0.7693 +2024-11-22 01:43:19.881526: Pseudo dice [0.8505] +2024-11-22 01:43:19.881615: Epoch time: 19.26 s +2024-11-22 01:43:20.720714: +2024-11-22 01:43:20.720956: Epoch 2702 +2024-11-22 01:43:20.721090: Current learning rate: 0.0069 +2024-11-22 01:43:41.659885: train_loss -0.7614 +2024-11-22 01:43:41.667198: val_loss -0.7575 +2024-11-22 01:43:41.667356: Pseudo dice [0.8387] +2024-11-22 01:43:41.667469: Epoch time: 20.94 s +2024-11-22 01:43:42.589865: +2024-11-22 01:43:42.590117: Epoch 2703 +2024-11-22 01:43:42.590244: Current learning rate: 0.0069 +2024-11-22 01:44:01.298114: train_loss -0.7748 +2024-11-22 01:44:01.301264: val_loss -0.7748 +2024-11-22 01:44:01.301391: Pseudo dice [0.8446] +2024-11-22 01:44:01.301493: Epoch time: 18.71 s +2024-11-22 01:44:02.348841: +2024-11-22 01:44:02.349192: Epoch 2704 +2024-11-22 01:44:02.349339: Current learning rate: 0.0069 +2024-11-22 01:44:21.846900: train_loss -0.7661 +2024-11-22 01:44:21.849199: val_loss -0.7628 +2024-11-22 01:44:21.849332: Pseudo dice [0.8373] +2024-11-22 01:44:21.849428: Epoch time: 19.5 s +2024-11-22 01:44:22.713163: +2024-11-22 01:44:22.713381: Epoch 2705 +2024-11-22 01:44:22.713498: Current learning rate: 0.0069 +2024-11-22 01:44:41.974796: train_loss -0.775 +2024-11-22 01:44:41.982611: val_loss -0.7631 +2024-11-22 01:44:41.982761: Pseudo dice [0.8501] +2024-11-22 01:44:41.982850: Epoch time: 19.26 s +2024-11-22 01:44:42.840148: +2024-11-22 01:44:42.840344: Epoch 2706 +2024-11-22 01:44:42.840460: Current learning rate: 0.0069 +2024-11-22 01:45:02.892229: train_loss -0.7714 +2024-11-22 01:45:02.898220: val_loss -0.7489 +2024-11-22 01:45:02.898358: Pseudo dice [0.8472] +2024-11-22 01:45:02.898453: Epoch time: 20.05 s +2024-11-22 01:45:03.729553: +2024-11-22 01:45:03.729819: Epoch 2707 +2024-11-22 01:45:03.729937: Current learning rate: 0.0069 +2024-11-22 01:45:22.778843: train_loss -0.7737 +2024-11-22 01:45:22.787461: val_loss -0.7566 +2024-11-22 01:45:22.787597: Pseudo dice [0.8595] +2024-11-22 01:45:22.787718: Epoch time: 19.05 s +2024-11-22 01:45:23.651826: +2024-11-22 01:45:23.652031: Epoch 2708 +2024-11-22 01:45:23.652160: Current learning rate: 0.00689 +2024-11-22 01:45:42.621782: train_loss -0.7774 +2024-11-22 01:45:42.629976: val_loss -0.7547 +2024-11-22 01:45:42.630106: Pseudo dice [0.8561] +2024-11-22 01:45:42.630197: Epoch time: 18.97 s +2024-11-22 01:45:43.601167: +2024-11-22 01:45:43.601384: Epoch 2709 +2024-11-22 01:45:43.601516: Current learning rate: 0.00689 +2024-11-22 01:46:02.173377: train_loss -0.7548 +2024-11-22 01:46:02.179199: val_loss -0.7384 +2024-11-22 01:46:02.179311: Pseudo dice [0.8426] +2024-11-22 01:46:02.179398: Epoch time: 18.57 s +2024-11-22 01:46:03.025256: +2024-11-22 01:46:03.025454: Epoch 2710 +2024-11-22 01:46:03.025573: Current learning rate: 0.00689 +2024-11-22 01:46:21.122179: train_loss -0.7668 +2024-11-22 01:46:21.126001: val_loss -0.7463 +2024-11-22 01:46:21.126123: Pseudo dice [0.8343] +2024-11-22 01:46:21.126223: Epoch time: 18.1 s +2024-11-22 01:46:21.967753: +2024-11-22 01:46:21.967989: Epoch 2711 +2024-11-22 01:46:21.968115: Current learning rate: 0.00689 +2024-11-22 01:46:40.578370: train_loss -0.7569 +2024-11-22 01:46:40.589986: val_loss -0.7583 +2024-11-22 01:46:40.590145: Pseudo dice [0.848] +2024-11-22 01:46:40.590252: Epoch time: 18.61 s +2024-11-22 01:46:41.628093: +2024-11-22 01:46:41.628305: Epoch 2712 +2024-11-22 01:46:41.628420: Current learning rate: 0.00689 +2024-11-22 01:47:00.546568: train_loss -0.7698 +2024-11-22 01:47:00.549733: val_loss -0.7517 +2024-11-22 01:47:00.549858: Pseudo dice [0.843] +2024-11-22 01:47:00.549945: Epoch time: 18.92 s +2024-11-22 01:47:01.377899: +2024-11-22 01:47:01.378119: Epoch 2713 +2024-11-22 01:47:01.378249: Current learning rate: 0.00689 +2024-11-22 01:47:20.547239: train_loss -0.7672 +2024-11-22 01:47:20.550031: val_loss -0.7587 +2024-11-22 01:47:20.550178: Pseudo dice [0.8545] +2024-11-22 01:47:20.550356: Epoch time: 19.17 s +2024-11-22 01:47:21.725191: +2024-11-22 01:47:21.725466: Epoch 2714 +2024-11-22 01:47:21.725589: Current learning rate: 0.00689 +2024-11-22 01:47:41.087283: train_loss -0.7693 +2024-11-22 01:47:41.089717: val_loss -0.7656 +2024-11-22 01:47:41.089820: Pseudo dice [0.8563] +2024-11-22 01:47:41.089935: Epoch time: 19.36 s +2024-11-22 01:47:41.919301: +2024-11-22 01:47:41.944428: Epoch 2715 +2024-11-22 01:47:41.944589: Current learning rate: 0.00689 +2024-11-22 01:48:00.760540: train_loss -0.7789 +2024-11-22 01:48:00.771201: val_loss -0.7642 +2024-11-22 01:48:00.771330: Pseudo dice [0.8521] +2024-11-22 01:48:00.771444: Epoch time: 18.84 s +2024-11-22 01:48:01.676502: +2024-11-22 01:48:01.676758: Epoch 2716 +2024-11-22 01:48:01.676898: Current learning rate: 0.00688 +2024-11-22 01:48:20.008108: train_loss -0.7752 +2024-11-22 01:48:20.015301: val_loss -0.7549 +2024-11-22 01:48:20.015455: Pseudo dice [0.8546] +2024-11-22 01:48:20.015550: Epoch time: 18.33 s +2024-11-22 01:48:20.851022: +2024-11-22 01:48:20.851235: Epoch 2717 +2024-11-22 01:48:20.851381: Current learning rate: 0.00688 +2024-11-22 01:48:39.118378: train_loss -0.7818 +2024-11-22 01:48:39.124775: val_loss -0.7801 +2024-11-22 01:48:39.124897: Pseudo dice [0.8553] +2024-11-22 01:48:39.124986: Epoch time: 18.27 s +2024-11-22 01:48:40.047376: +2024-11-22 01:48:40.047627: Epoch 2718 +2024-11-22 01:48:40.047763: Current learning rate: 0.00688 +2024-11-22 01:48:58.679679: train_loss -0.7794 +2024-11-22 01:48:58.684871: val_loss -0.7289 +2024-11-22 01:48:58.685014: Pseudo dice [0.8457] +2024-11-22 01:48:58.685121: Epoch time: 18.63 s +2024-11-22 01:48:59.741525: +2024-11-22 01:48:59.741762: Epoch 2719 +2024-11-22 01:48:59.741888: Current learning rate: 0.00688 +2024-11-22 01:49:18.714100: train_loss -0.7794 +2024-11-22 01:49:18.719540: val_loss -0.7645 +2024-11-22 01:49:18.719723: Pseudo dice [0.8449] +2024-11-22 01:49:18.719825: Epoch time: 18.97 s +2024-11-22 01:49:19.604665: +2024-11-22 01:49:19.604882: Epoch 2720 +2024-11-22 01:49:19.605015: Current learning rate: 0.00688 +2024-11-22 01:49:38.484248: train_loss -0.7717 +2024-11-22 01:49:38.495300: val_loss -0.7629 +2024-11-22 01:49:38.495428: Pseudo dice [0.8468] +2024-11-22 01:49:38.495510: Epoch time: 18.88 s +2024-11-22 01:49:39.491002: +2024-11-22 01:49:39.491219: Epoch 2721 +2024-11-22 01:49:39.491336: Current learning rate: 0.00688 +2024-11-22 01:49:58.336646: train_loss -0.7753 +2024-11-22 01:49:58.351686: val_loss -0.7615 +2024-11-22 01:49:58.351850: Pseudo dice [0.8554] +2024-11-22 01:49:58.351960: Epoch time: 18.85 s +2024-11-22 01:49:59.202622: +2024-11-22 01:49:59.202823: Epoch 2722 +2024-11-22 01:49:59.202940: Current learning rate: 0.00688 +2024-11-22 01:50:18.732723: train_loss -0.7686 +2024-11-22 01:50:18.739635: val_loss -0.7717 +2024-11-22 01:50:18.739757: Pseudo dice [0.8579] +2024-11-22 01:50:18.739868: Epoch time: 19.53 s +2024-11-22 01:50:19.593133: +2024-11-22 01:50:19.593339: Epoch 2723 +2024-11-22 01:50:19.593453: Current learning rate: 0.00688 +2024-11-22 01:50:38.334241: train_loss -0.7817 +2024-11-22 01:50:38.337855: val_loss -0.7579 +2024-11-22 01:50:38.337985: Pseudo dice [0.8502] +2024-11-22 01:50:38.338091: Epoch time: 18.74 s +2024-11-22 01:50:39.170111: +2024-11-22 01:50:39.170306: Epoch 2724 +2024-11-22 01:50:39.170441: Current learning rate: 0.00688 +2024-11-22 01:50:57.139334: train_loss -0.7795 +2024-11-22 01:50:57.144951: val_loss -0.7671 +2024-11-22 01:50:57.145092: Pseudo dice [0.8429] +2024-11-22 01:50:57.145182: Epoch time: 17.97 s +2024-11-22 01:50:58.043387: +2024-11-22 01:50:58.043617: Epoch 2725 +2024-11-22 01:50:58.043729: Current learning rate: 0.00687 +2024-11-22 01:51:17.195220: train_loss -0.77 +2024-11-22 01:51:17.201439: val_loss -0.7732 +2024-11-22 01:51:17.201586: Pseudo dice [0.8414] +2024-11-22 01:51:17.201687: Epoch time: 19.15 s +2024-11-22 01:51:18.439629: +2024-11-22 01:51:18.439856: Epoch 2726 +2024-11-22 01:51:18.439990: Current learning rate: 0.00687 +2024-11-22 01:51:36.891756: train_loss -0.7802 +2024-11-22 01:51:36.897811: val_loss -0.7595 +2024-11-22 01:51:36.897945: Pseudo dice [0.8435] +2024-11-22 01:51:36.898034: Epoch time: 18.45 s +2024-11-22 01:51:37.731939: +2024-11-22 01:51:37.732153: Epoch 2727 +2024-11-22 01:51:37.732273: Current learning rate: 0.00687 +2024-11-22 01:51:56.679196: train_loss -0.7817 +2024-11-22 01:51:56.686368: val_loss -0.758 +2024-11-22 01:51:56.686787: Pseudo dice [0.853] +2024-11-22 01:51:56.686895: Epoch time: 18.95 s +2024-11-22 01:51:57.598676: +2024-11-22 01:51:57.598873: Epoch 2728 +2024-11-22 01:51:57.598989: Current learning rate: 0.00687 +2024-11-22 01:52:16.242950: train_loss -0.7785 +2024-11-22 01:52:16.251849: val_loss -0.7766 +2024-11-22 01:52:16.251971: Pseudo dice [0.8501] +2024-11-22 01:52:16.252054: Epoch time: 18.65 s +2024-11-22 01:52:17.105732: +2024-11-22 01:52:17.105982: Epoch 2729 +2024-11-22 01:52:17.106109: Current learning rate: 0.00687 +2024-11-22 01:52:35.424905: train_loss -0.7727 +2024-11-22 01:52:35.427202: val_loss -0.7596 +2024-11-22 01:52:35.427309: Pseudo dice [0.8402] +2024-11-22 01:52:35.427446: Epoch time: 18.32 s +2024-11-22 01:52:36.261393: +2024-11-22 01:52:36.261610: Epoch 2730 +2024-11-22 01:52:36.261741: Current learning rate: 0.00687 +2024-11-22 01:52:55.246440: train_loss -0.7836 +2024-11-22 01:52:55.249949: val_loss -0.7778 +2024-11-22 01:52:55.250089: Pseudo dice [0.8436] +2024-11-22 01:52:55.250316: Epoch time: 18.99 s +2024-11-22 01:52:56.086784: +2024-11-22 01:52:56.086987: Epoch 2731 +2024-11-22 01:52:56.087112: Current learning rate: 0.00687 +2024-11-22 01:53:14.796049: train_loss -0.7771 +2024-11-22 01:53:14.801517: val_loss -0.7499 +2024-11-22 01:53:14.801645: Pseudo dice [0.8458] +2024-11-22 01:53:14.801756: Epoch time: 18.71 s +2024-11-22 01:53:15.666826: +2024-11-22 01:53:15.667048: Epoch 2732 +2024-11-22 01:53:15.667195: Current learning rate: 0.00687 +2024-11-22 01:53:35.816672: train_loss -0.7729 +2024-11-22 01:53:35.819932: val_loss -0.7656 +2024-11-22 01:53:35.820026: Pseudo dice [0.8486] +2024-11-22 01:53:35.820113: Epoch time: 20.15 s +2024-11-22 01:53:36.647375: +2024-11-22 01:53:36.647564: Epoch 2733 +2024-11-22 01:53:36.647678: Current learning rate: 0.00686 +2024-11-22 01:53:55.788413: train_loss -0.7897 +2024-11-22 01:53:55.793599: val_loss -0.7721 +2024-11-22 01:53:55.793710: Pseudo dice [0.8459] +2024-11-22 01:53:55.793814: Epoch time: 19.14 s +2024-11-22 01:53:56.627793: +2024-11-22 01:53:56.628025: Epoch 2734 +2024-11-22 01:53:56.628156: Current learning rate: 0.00686 +2024-11-22 01:54:15.388101: train_loss -0.7799 +2024-11-22 01:54:15.413357: val_loss -0.773 +2024-11-22 01:54:15.413523: Pseudo dice [0.8547] +2024-11-22 01:54:15.413608: Epoch time: 18.76 s +2024-11-22 01:54:16.372907: +2024-11-22 01:54:16.373143: Epoch 2735 +2024-11-22 01:54:16.373267: Current learning rate: 0.00686 +2024-11-22 01:54:35.843687: train_loss -0.782 +2024-11-22 01:54:35.850758: val_loss -0.7336 +2024-11-22 01:54:35.850885: Pseudo dice [0.8502] +2024-11-22 01:54:35.850975: Epoch time: 19.47 s +2024-11-22 01:54:36.786673: +2024-11-22 01:54:36.786862: Epoch 2736 +2024-11-22 01:54:36.786988: Current learning rate: 0.00686 +2024-11-22 01:54:55.157910: train_loss -0.7765 +2024-11-22 01:54:55.160536: val_loss -0.772 +2024-11-22 01:54:55.160651: Pseudo dice [0.8519] +2024-11-22 01:54:55.160751: Epoch time: 18.37 s +2024-11-22 01:54:56.386461: +2024-11-22 01:54:56.386697: Epoch 2737 +2024-11-22 01:54:56.386819: Current learning rate: 0.00686 +2024-11-22 01:55:15.038775: train_loss -0.7586 +2024-11-22 01:55:15.044414: val_loss -0.7354 +2024-11-22 01:55:15.044567: Pseudo dice [0.83] +2024-11-22 01:55:15.044674: Epoch time: 18.65 s +2024-11-22 01:55:15.937971: +2024-11-22 01:55:15.938281: Epoch 2738 +2024-11-22 01:55:15.938402: Current learning rate: 0.00686 +2024-11-22 01:55:35.095312: train_loss -0.7643 +2024-11-22 01:55:35.099200: val_loss -0.77 +2024-11-22 01:55:35.099314: Pseudo dice [0.8494] +2024-11-22 01:55:35.099435: Epoch time: 19.16 s +2024-11-22 01:55:35.931871: +2024-11-22 01:55:35.932081: Epoch 2739 +2024-11-22 01:55:35.932197: Current learning rate: 0.00686 +2024-11-22 01:55:56.090672: train_loss -0.768 +2024-11-22 01:55:56.095462: val_loss -0.7486 +2024-11-22 01:55:56.095696: Pseudo dice [0.8452] +2024-11-22 01:55:56.095803: Epoch time: 20.16 s +2024-11-22 01:55:56.927714: +2024-11-22 01:55:56.927917: Epoch 2740 +2024-11-22 01:55:56.928035: Current learning rate: 0.00686 +2024-11-22 01:56:16.480611: train_loss -0.7682 +2024-11-22 01:56:16.489978: val_loss -0.7451 +2024-11-22 01:56:16.490121: Pseudo dice [0.852] +2024-11-22 01:56:16.490204: Epoch time: 19.55 s +2024-11-22 01:56:17.361582: +2024-11-22 01:56:17.361796: Epoch 2741 +2024-11-22 01:56:17.361914: Current learning rate: 0.00686 +2024-11-22 01:56:37.627885: train_loss -0.7676 +2024-11-22 01:56:37.636550: val_loss -0.7592 +2024-11-22 01:56:37.636672: Pseudo dice [0.8401] +2024-11-22 01:56:37.636771: Epoch time: 20.27 s +2024-11-22 01:56:38.578625: +2024-11-22 01:56:38.578871: Epoch 2742 +2024-11-22 01:56:38.579026: Current learning rate: 0.00685 +2024-11-22 01:56:57.255269: train_loss -0.7642 +2024-11-22 01:56:57.262999: val_loss -0.7368 +2024-11-22 01:56:57.263138: Pseudo dice [0.8497] +2024-11-22 01:56:57.263221: Epoch time: 18.68 s +2024-11-22 01:56:58.252643: +2024-11-22 01:56:58.252903: Epoch 2743 +2024-11-22 01:56:58.253039: Current learning rate: 0.00685 +2024-11-22 01:57:16.686467: train_loss -0.7665 +2024-11-22 01:57:16.689762: val_loss -0.746 +2024-11-22 01:57:16.689907: Pseudo dice [0.8576] +2024-11-22 01:57:16.690002: Epoch time: 18.43 s +2024-11-22 01:57:17.645910: +2024-11-22 01:57:17.646123: Epoch 2744 +2024-11-22 01:57:17.646248: Current learning rate: 0.00685 +2024-11-22 01:57:36.602917: train_loss -0.7731 +2024-11-22 01:57:36.610087: val_loss -0.7585 +2024-11-22 01:57:36.610224: Pseudo dice [0.8534] +2024-11-22 01:57:36.610313: Epoch time: 18.96 s +2024-11-22 01:57:37.447311: +2024-11-22 01:57:37.447516: Epoch 2745 +2024-11-22 01:57:37.447658: Current learning rate: 0.00685 +2024-11-22 01:57:55.878409: train_loss -0.7787 +2024-11-22 01:57:55.885447: val_loss -0.7602 +2024-11-22 01:57:55.885581: Pseudo dice [0.8533] +2024-11-22 01:57:55.885682: Epoch time: 18.43 s +2024-11-22 01:57:56.850821: +2024-11-22 01:57:56.851018: Epoch 2746 +2024-11-22 01:57:56.851138: Current learning rate: 0.00685 +2024-11-22 01:58:16.170393: train_loss -0.7699 +2024-11-22 01:58:16.177911: val_loss -0.7689 +2024-11-22 01:58:16.178046: Pseudo dice [0.8489] +2024-11-22 01:58:16.178169: Epoch time: 19.32 s +2024-11-22 01:58:17.134258: +2024-11-22 01:58:17.134470: Epoch 2747 +2024-11-22 01:58:17.134585: Current learning rate: 0.00685 +2024-11-22 01:58:36.111569: train_loss -0.7745 +2024-11-22 01:58:36.114148: val_loss -0.7589 +2024-11-22 01:58:36.114252: Pseudo dice [0.8631] +2024-11-22 01:58:36.114343: Epoch time: 18.98 s +2024-11-22 01:58:36.949202: +2024-11-22 01:58:36.949394: Epoch 2748 +2024-11-22 01:58:36.949513: Current learning rate: 0.00685 +2024-11-22 01:58:56.496504: train_loss -0.7796 +2024-11-22 01:58:56.505164: val_loss -0.7724 +2024-11-22 01:58:56.505305: Pseudo dice [0.8546] +2024-11-22 01:58:56.505391: Epoch time: 19.54 s +2024-11-22 01:58:57.832407: +2024-11-22 01:58:57.832601: Epoch 2749 +2024-11-22 01:58:57.832718: Current learning rate: 0.00685 +2024-11-22 01:59:16.798016: train_loss -0.7663 +2024-11-22 01:59:16.810738: val_loss -0.7593 +2024-11-22 01:59:16.810870: Pseudo dice [0.8247] +2024-11-22 01:59:16.810971: Epoch time: 18.97 s +2024-11-22 01:59:17.936503: +2024-11-22 01:59:17.936703: Epoch 2750 +2024-11-22 01:59:17.936821: Current learning rate: 0.00684 +2024-11-22 01:59:37.852156: train_loss -0.7808 +2024-11-22 01:59:37.863359: val_loss -0.7684 +2024-11-22 01:59:37.863504: Pseudo dice [0.8472] +2024-11-22 01:59:37.863599: Epoch time: 19.92 s +2024-11-22 01:59:38.877870: +2024-11-22 01:59:38.878109: Epoch 2751 +2024-11-22 01:59:38.878244: Current learning rate: 0.00684 +2024-11-22 01:59:57.873867: train_loss -0.775 +2024-11-22 01:59:57.879416: val_loss -0.7235 +2024-11-22 01:59:57.879545: Pseudo dice [0.8473] +2024-11-22 01:59:57.879627: Epoch time: 19.0 s +2024-11-22 01:59:58.792709: +2024-11-22 01:59:58.792932: Epoch 2752 +2024-11-22 01:59:58.793065: Current learning rate: 0.00684 +2024-11-22 02:00:16.034922: train_loss -0.7773 +2024-11-22 02:00:16.041001: val_loss -0.7926 +2024-11-22 02:00:16.041155: Pseudo dice [0.8542] +2024-11-22 02:00:16.041271: Epoch time: 17.24 s +2024-11-22 02:00:16.895277: +2024-11-22 02:00:16.895485: Epoch 2753 +2024-11-22 02:00:16.895806: Current learning rate: 0.00684 +2024-11-22 02:00:36.774288: train_loss -0.7886 +2024-11-22 02:00:36.781232: val_loss -0.7607 +2024-11-22 02:00:36.781387: Pseudo dice [0.8344] +2024-11-22 02:00:36.781488: Epoch time: 19.88 s +2024-11-22 02:00:37.693941: +2024-11-22 02:00:37.694183: Epoch 2754 +2024-11-22 02:00:37.694312: Current learning rate: 0.00684 +2024-11-22 02:00:55.936281: train_loss -0.7854 +2024-11-22 02:00:55.941885: val_loss -0.7536 +2024-11-22 02:00:55.942015: Pseudo dice [0.8486] +2024-11-22 02:00:55.942116: Epoch time: 18.24 s +2024-11-22 02:00:56.930350: +2024-11-22 02:00:56.930914: Epoch 2755 +2024-11-22 02:00:56.931037: Current learning rate: 0.00684 +2024-11-22 02:01:15.547779: train_loss -0.7791 +2024-11-22 02:01:15.563133: val_loss -0.7912 +2024-11-22 02:01:15.563295: Pseudo dice [0.8504] +2024-11-22 02:01:15.563427: Epoch time: 18.62 s +2024-11-22 02:01:16.412501: +2024-11-22 02:01:16.412789: Epoch 2756 +2024-11-22 02:01:16.412910: Current learning rate: 0.00684 +2024-11-22 02:01:34.712403: train_loss -0.7891 +2024-11-22 02:01:34.721376: val_loss -0.7732 +2024-11-22 02:01:34.721499: Pseudo dice [0.852] +2024-11-22 02:01:34.721601: Epoch time: 18.3 s +2024-11-22 02:01:35.789238: +2024-11-22 02:01:35.789463: Epoch 2757 +2024-11-22 02:01:35.789580: Current learning rate: 0.00684 +2024-11-22 02:01:54.262674: train_loss -0.7888 +2024-11-22 02:01:54.269726: val_loss -0.7749 +2024-11-22 02:01:54.269870: Pseudo dice [0.8488] +2024-11-22 02:01:54.269970: Epoch time: 18.47 s +2024-11-22 02:01:55.101898: +2024-11-22 02:01:55.102120: Epoch 2758 +2024-11-22 02:01:55.102255: Current learning rate: 0.00684 +2024-11-22 02:02:14.009341: train_loss -0.7806 +2024-11-22 02:02:14.012418: val_loss -0.7491 +2024-11-22 02:02:14.012633: Pseudo dice [0.8343] +2024-11-22 02:02:14.012734: Epoch time: 18.91 s +2024-11-22 02:02:14.957508: +2024-11-22 02:02:14.957711: Epoch 2759 +2024-11-22 02:02:14.957833: Current learning rate: 0.00683 +2024-11-22 02:02:34.310532: train_loss -0.7685 +2024-11-22 02:02:34.317292: val_loss -0.7807 +2024-11-22 02:02:34.317435: Pseudo dice [0.856] +2024-11-22 02:02:34.317533: Epoch time: 19.35 s +2024-11-22 02:02:35.625713: +2024-11-22 02:02:35.625969: Epoch 2760 +2024-11-22 02:02:35.626107: Current learning rate: 0.00683 +2024-11-22 02:02:54.617565: train_loss -0.7727 +2024-11-22 02:02:54.623966: val_loss -0.7667 +2024-11-22 02:02:54.624104: Pseudo dice [0.8407] +2024-11-22 02:02:54.624206: Epoch time: 18.99 s +2024-11-22 02:02:55.451051: +2024-11-22 02:02:55.451253: Epoch 2761 +2024-11-22 02:02:55.451367: Current learning rate: 0.00683 +2024-11-22 02:03:14.428766: train_loss -0.7306 +2024-11-22 02:03:14.436411: val_loss -0.7433 +2024-11-22 02:03:14.436537: Pseudo dice [0.8384] +2024-11-22 02:03:14.436632: Epoch time: 18.98 s +2024-11-22 02:03:15.306143: +2024-11-22 02:03:15.306370: Epoch 2762 +2024-11-22 02:03:15.306496: Current learning rate: 0.00683 +2024-11-22 02:03:34.668758: train_loss -0.7624 +2024-11-22 02:03:34.675250: val_loss -0.7471 +2024-11-22 02:03:34.675387: Pseudo dice [0.8373] +2024-11-22 02:03:34.675501: Epoch time: 19.36 s +2024-11-22 02:03:35.547907: +2024-11-22 02:03:35.548128: Epoch 2763 +2024-11-22 02:03:35.548245: Current learning rate: 0.00683 +2024-11-22 02:03:55.313097: train_loss -0.7574 +2024-11-22 02:03:55.319731: val_loss -0.7313 +2024-11-22 02:03:55.319881: Pseudo dice [0.8402] +2024-11-22 02:03:55.319998: Epoch time: 19.77 s +2024-11-22 02:03:56.164951: +2024-11-22 02:03:56.165166: Epoch 2764 +2024-11-22 02:03:56.165298: Current learning rate: 0.00683 +2024-11-22 02:04:15.417012: train_loss -0.7689 +2024-11-22 02:04:15.419789: val_loss -0.7443 +2024-11-22 02:04:15.419885: Pseudo dice [0.8226] +2024-11-22 02:04:15.419973: Epoch time: 19.25 s +2024-11-22 02:04:16.255594: +2024-11-22 02:04:16.255795: Epoch 2765 +2024-11-22 02:04:16.255914: Current learning rate: 0.00683 +2024-11-22 02:04:34.711196: train_loss -0.7613 +2024-11-22 02:04:34.718596: val_loss -0.7688 +2024-11-22 02:04:34.718770: Pseudo dice [0.8563] +2024-11-22 02:04:34.719088: Epoch time: 18.46 s +2024-11-22 02:04:35.587343: +2024-11-22 02:04:35.587589: Epoch 2766 +2024-11-22 02:04:35.587720: Current learning rate: 0.00683 +2024-11-22 02:04:53.437440: train_loss -0.7722 +2024-11-22 02:04:53.440863: val_loss -0.7763 +2024-11-22 02:04:53.441002: Pseudo dice [0.8583] +2024-11-22 02:04:53.441105: Epoch time: 17.85 s +2024-11-22 02:04:54.275506: +2024-11-22 02:04:54.283301: Epoch 2767 +2024-11-22 02:04:54.283453: Current learning rate: 0.00682 +2024-11-22 02:05:14.074932: train_loss -0.7431 +2024-11-22 02:05:14.079075: val_loss -0.7586 +2024-11-22 02:05:14.079219: Pseudo dice [0.8446] +2024-11-22 02:05:14.079408: Epoch time: 19.8 s +2024-11-22 02:05:14.919664: +2024-11-22 02:05:14.919908: Epoch 2768 +2024-11-22 02:05:14.920026: Current learning rate: 0.00682 +2024-11-22 02:05:34.154694: train_loss -0.7653 +2024-11-22 02:05:34.163946: val_loss -0.7572 +2024-11-22 02:05:34.164090: Pseudo dice [0.8471] +2024-11-22 02:05:34.164195: Epoch time: 19.24 s +2024-11-22 02:05:34.991938: +2024-11-22 02:05:34.992147: Epoch 2769 +2024-11-22 02:05:34.992276: Current learning rate: 0.00682 +2024-11-22 02:05:54.551894: train_loss -0.7589 +2024-11-22 02:05:54.558722: val_loss -0.754 +2024-11-22 02:05:54.558873: Pseudo dice [0.8426] +2024-11-22 02:05:54.558978: Epoch time: 19.56 s +2024-11-22 02:05:55.504024: +2024-11-22 02:05:55.504228: Epoch 2770 +2024-11-22 02:05:55.504351: Current learning rate: 0.00682 +2024-11-22 02:06:14.572045: train_loss -0.7723 +2024-11-22 02:06:14.573900: val_loss -0.723 +2024-11-22 02:06:14.574012: Pseudo dice [0.8425] +2024-11-22 02:06:14.574114: Epoch time: 19.07 s +2024-11-22 02:06:15.795572: +2024-11-22 02:06:15.795781: Epoch 2771 +2024-11-22 02:06:15.795903: Current learning rate: 0.00682 +2024-11-22 02:06:34.209300: train_loss -0.766 +2024-11-22 02:06:34.211772: val_loss -0.7648 +2024-11-22 02:06:34.211911: Pseudo dice [0.8533] +2024-11-22 02:06:34.211998: Epoch time: 18.41 s +2024-11-22 02:06:35.035587: +2024-11-22 02:06:35.035794: Epoch 2772 +2024-11-22 02:06:35.035914: Current learning rate: 0.00682 +2024-11-22 02:06:55.082732: train_loss -0.7685 +2024-11-22 02:06:55.094770: val_loss -0.7299 +2024-11-22 02:06:55.094900: Pseudo dice [0.822] +2024-11-22 02:06:55.095002: Epoch time: 20.05 s +2024-11-22 02:06:55.992137: +2024-11-22 02:06:55.992381: Epoch 2773 +2024-11-22 02:06:55.992504: Current learning rate: 0.00682 +2024-11-22 02:07:15.063278: train_loss -0.7625 +2024-11-22 02:07:15.065623: val_loss -0.7644 +2024-11-22 02:07:15.065753: Pseudo dice [0.849] +2024-11-22 02:07:15.065842: Epoch time: 19.07 s +2024-11-22 02:07:16.082496: +2024-11-22 02:07:16.082685: Epoch 2774 +2024-11-22 02:07:16.082821: Current learning rate: 0.00682 +2024-11-22 02:07:34.394145: train_loss -0.7752 +2024-11-22 02:07:34.400707: val_loss -0.7719 +2024-11-22 02:07:34.400861: Pseudo dice [0.8428] +2024-11-22 02:07:34.400979: Epoch time: 18.31 s +2024-11-22 02:07:35.371376: +2024-11-22 02:07:35.371595: Epoch 2775 +2024-11-22 02:07:35.371708: Current learning rate: 0.00682 +2024-11-22 02:07:53.597948: train_loss -0.7697 +2024-11-22 02:07:53.602944: val_loss -0.7655 +2024-11-22 02:07:53.603083: Pseudo dice [0.846] +2024-11-22 02:07:53.603174: Epoch time: 18.23 s +2024-11-22 02:07:54.464334: +2024-11-22 02:07:54.464544: Epoch 2776 +2024-11-22 02:07:54.464672: Current learning rate: 0.00681 +2024-11-22 02:08:13.868486: train_loss -0.7729 +2024-11-22 02:08:13.880723: val_loss -0.7696 +2024-11-22 02:08:13.880854: Pseudo dice [0.8513] +2024-11-22 02:08:13.880955: Epoch time: 19.4 s +2024-11-22 02:08:14.961982: +2024-11-22 02:08:14.962201: Epoch 2777 +2024-11-22 02:08:14.962319: Current learning rate: 0.00681 +2024-11-22 02:08:34.604964: train_loss -0.7828 +2024-11-22 02:08:34.610429: val_loss -0.7854 +2024-11-22 02:08:34.610557: Pseudo dice [0.8483] +2024-11-22 02:08:34.610640: Epoch time: 19.64 s +2024-11-22 02:08:35.453737: +2024-11-22 02:08:35.453967: Epoch 2778 +2024-11-22 02:08:35.454092: Current learning rate: 0.00681 +2024-11-22 02:08:54.359754: train_loss -0.7768 +2024-11-22 02:08:54.363739: val_loss -0.7526 +2024-11-22 02:08:54.363901: Pseudo dice [0.8409] +2024-11-22 02:08:54.363988: Epoch time: 18.91 s +2024-11-22 02:08:55.315159: +2024-11-22 02:08:55.315403: Epoch 2779 +2024-11-22 02:08:55.315533: Current learning rate: 0.00681 +2024-11-22 02:09:15.339358: train_loss -0.7785 +2024-11-22 02:09:15.348730: val_loss -0.7682 +2024-11-22 02:09:15.348854: Pseudo dice [0.8536] +2024-11-22 02:09:15.348938: Epoch time: 20.03 s +2024-11-22 02:09:16.205968: +2024-11-22 02:09:16.206168: Epoch 2780 +2024-11-22 02:09:16.206295: Current learning rate: 0.00681 +2024-11-22 02:09:35.634037: train_loss -0.779 +2024-11-22 02:09:35.636857: val_loss -0.7668 +2024-11-22 02:09:35.636956: Pseudo dice [0.8521] +2024-11-22 02:09:35.637066: Epoch time: 19.43 s +2024-11-22 02:09:36.471256: +2024-11-22 02:09:36.471448: Epoch 2781 +2024-11-22 02:09:36.471572: Current learning rate: 0.00681 +2024-11-22 02:09:55.765574: train_loss -0.776 +2024-11-22 02:09:55.767818: val_loss -0.7534 +2024-11-22 02:09:55.767904: Pseudo dice [0.8531] +2024-11-22 02:09:55.768199: Epoch time: 19.3 s +2024-11-22 02:09:56.596757: +2024-11-22 02:09:56.596993: Epoch 2782 +2024-11-22 02:09:56.597128: Current learning rate: 0.00681 +2024-11-22 02:10:15.257843: train_loss -0.7738 +2024-11-22 02:10:15.263182: val_loss -0.7694 +2024-11-22 02:10:15.263374: Pseudo dice [0.8507] +2024-11-22 02:10:15.263475: Epoch time: 18.66 s +2024-11-22 02:10:16.567711: +2024-11-22 02:10:16.567924: Epoch 2783 +2024-11-22 02:10:16.568042: Current learning rate: 0.00681 +2024-11-22 02:10:35.916824: train_loss -0.7706 +2024-11-22 02:10:35.920537: val_loss -0.7685 +2024-11-22 02:10:35.920682: Pseudo dice [0.8598] +2024-11-22 02:10:35.920771: Epoch time: 19.35 s +2024-11-22 02:10:36.898692: +2024-11-22 02:10:36.898961: Epoch 2784 +2024-11-22 02:10:36.899131: Current learning rate: 0.0068 +2024-11-22 02:10:56.342013: train_loss -0.7715 +2024-11-22 02:10:56.351814: val_loss -0.7544 +2024-11-22 02:10:56.351985: Pseudo dice [0.8495] +2024-11-22 02:10:56.352088: Epoch time: 19.44 s +2024-11-22 02:10:57.185640: +2024-11-22 02:10:57.185858: Epoch 2785 +2024-11-22 02:10:57.185968: Current learning rate: 0.0068 +2024-11-22 02:11:15.445311: train_loss -0.7801 +2024-11-22 02:11:15.448698: val_loss -0.7622 +2024-11-22 02:11:15.448829: Pseudo dice [0.845] +2024-11-22 02:11:15.448924: Epoch time: 18.26 s +2024-11-22 02:11:16.308646: +2024-11-22 02:11:16.308849: Epoch 2786 +2024-11-22 02:11:16.308969: Current learning rate: 0.0068 +2024-11-22 02:11:37.463210: train_loss -0.7727 +2024-11-22 02:11:37.465427: val_loss -0.7714 +2024-11-22 02:11:37.465579: Pseudo dice [0.858] +2024-11-22 02:11:37.465672: Epoch time: 21.16 s +2024-11-22 02:11:38.342441: +2024-11-22 02:11:38.342652: Epoch 2787 +2024-11-22 02:11:38.342771: Current learning rate: 0.0068 +2024-11-22 02:11:58.206932: train_loss -0.779 +2024-11-22 02:11:58.209342: val_loss -0.7573 +2024-11-22 02:11:58.209445: Pseudo dice [0.8401] +2024-11-22 02:11:58.209554: Epoch time: 19.87 s +2024-11-22 02:11:59.040365: +2024-11-22 02:11:59.040578: Epoch 2788 +2024-11-22 02:11:59.040696: Current learning rate: 0.0068 +2024-11-22 02:12:18.749880: train_loss -0.7673 +2024-11-22 02:12:18.756948: val_loss -0.7727 +2024-11-22 02:12:18.757153: Pseudo dice [0.8454] +2024-11-22 02:12:18.757246: Epoch time: 19.71 s +2024-11-22 02:12:19.607358: +2024-11-22 02:12:19.607566: Epoch 2789 +2024-11-22 02:12:19.607704: Current learning rate: 0.0068 +2024-11-22 02:12:38.264990: train_loss -0.7771 +2024-11-22 02:12:38.267416: val_loss -0.7942 +2024-11-22 02:12:38.267517: Pseudo dice [0.8489] +2024-11-22 02:12:38.267632: Epoch time: 18.66 s +2024-11-22 02:12:39.098631: +2024-11-22 02:12:39.098901: Epoch 2790 +2024-11-22 02:12:39.099028: Current learning rate: 0.0068 +2024-11-22 02:12:58.498431: train_loss -0.7855 +2024-11-22 02:12:58.506777: val_loss -0.7739 +2024-11-22 02:12:58.506910: Pseudo dice [0.8555] +2024-11-22 02:12:58.507000: Epoch time: 19.4 s +2024-11-22 02:12:59.484425: +2024-11-22 02:12:59.484628: Epoch 2791 +2024-11-22 02:12:59.484971: Current learning rate: 0.0068 +2024-11-22 02:13:18.600015: train_loss -0.7715 +2024-11-22 02:13:18.604122: val_loss -0.7743 +2024-11-22 02:13:18.604239: Pseudo dice [0.8505] +2024-11-22 02:13:18.604334: Epoch time: 19.12 s +2024-11-22 02:13:19.438183: +2024-11-22 02:13:19.438433: Epoch 2792 +2024-11-22 02:13:19.438558: Current learning rate: 0.0068 +2024-11-22 02:13:39.044839: train_loss -0.7738 +2024-11-22 02:13:39.051641: val_loss -0.7742 +2024-11-22 02:13:39.051786: Pseudo dice [0.8401] +2024-11-22 02:13:39.051889: Epoch time: 19.61 s +2024-11-22 02:13:39.901576: +2024-11-22 02:13:39.901801: Epoch 2793 +2024-11-22 02:13:39.901952: Current learning rate: 0.00679 +2024-11-22 02:13:58.540446: train_loss -0.7684 +2024-11-22 02:13:58.554037: val_loss -0.7528 +2024-11-22 02:13:58.554168: Pseudo dice [0.8404] +2024-11-22 02:13:58.554248: Epoch time: 18.64 s +2024-11-22 02:13:59.937484: +2024-11-22 02:13:59.937718: Epoch 2794 +2024-11-22 02:13:59.937840: Current learning rate: 0.00679 +2024-11-22 02:14:18.120711: train_loss -0.7599 +2024-11-22 02:14:18.133403: val_loss -0.7593 +2024-11-22 02:14:18.133563: Pseudo dice [0.8515] +2024-11-22 02:14:18.133665: Epoch time: 18.18 s +2024-11-22 02:14:19.032242: +2024-11-22 02:14:19.032515: Epoch 2795 +2024-11-22 02:14:19.032637: Current learning rate: 0.00679 +2024-11-22 02:14:38.224981: train_loss -0.7744 +2024-11-22 02:14:38.232742: val_loss -0.7647 +2024-11-22 02:14:38.232900: Pseudo dice [0.8526] +2024-11-22 02:14:38.233010: Epoch time: 19.19 s +2024-11-22 02:14:39.092577: +2024-11-22 02:14:39.092797: Epoch 2796 +2024-11-22 02:14:39.092915: Current learning rate: 0.00679 +2024-11-22 02:14:58.265765: train_loss -0.7677 +2024-11-22 02:14:58.273209: val_loss -0.7656 +2024-11-22 02:14:58.273349: Pseudo dice [0.8582] +2024-11-22 02:14:58.273439: Epoch time: 19.17 s +2024-11-22 02:14:59.213813: +2024-11-22 02:14:59.214339: Epoch 2797 +2024-11-22 02:14:59.214453: Current learning rate: 0.00679 +2024-11-22 02:15:18.928533: train_loss -0.7611 +2024-11-22 02:15:18.930736: val_loss -0.771 +2024-11-22 02:15:18.930868: Pseudo dice [0.8551] +2024-11-22 02:15:18.930979: Epoch time: 19.72 s +2024-11-22 02:15:19.767453: +2024-11-22 02:15:19.767699: Epoch 2798 +2024-11-22 02:15:19.767841: Current learning rate: 0.00679 +2024-11-22 02:15:39.327733: train_loss -0.7671 +2024-11-22 02:15:39.335051: val_loss -0.7678 +2024-11-22 02:15:39.335210: Pseudo dice [0.8485] +2024-11-22 02:15:39.335309: Epoch time: 19.56 s +2024-11-22 02:15:40.212641: +2024-11-22 02:15:40.212844: Epoch 2799 +2024-11-22 02:15:40.212973: Current learning rate: 0.00679 +2024-11-22 02:15:58.226274: train_loss -0.7678 +2024-11-22 02:15:58.232375: val_loss -0.7348 +2024-11-22 02:15:58.232500: Pseudo dice [0.8286] +2024-11-22 02:15:58.232643: Epoch time: 18.01 s +2024-11-22 02:15:59.324662: +2024-11-22 02:15:59.324874: Epoch 2800 +2024-11-22 02:15:59.325026: Current learning rate: 0.00679 +2024-11-22 02:16:17.510382: train_loss -0.7601 +2024-11-22 02:16:17.512672: val_loss -0.7682 +2024-11-22 02:16:17.512775: Pseudo dice [0.8438] +2024-11-22 02:16:17.512855: Epoch time: 18.19 s +2024-11-22 02:16:18.344226: +2024-11-22 02:16:18.344455: Epoch 2801 +2024-11-22 02:16:18.344591: Current learning rate: 0.00678 +2024-11-22 02:16:37.879875: train_loss -0.773 +2024-11-22 02:16:37.887800: val_loss -0.7719 +2024-11-22 02:16:37.887949: Pseudo dice [0.8606] +2024-11-22 02:16:37.888050: Epoch time: 19.54 s +2024-11-22 02:16:38.770315: +2024-11-22 02:16:38.770525: Epoch 2802 +2024-11-22 02:16:38.770645: Current learning rate: 0.00678 +2024-11-22 02:16:58.085083: train_loss -0.7752 +2024-11-22 02:16:58.095094: val_loss -0.7806 +2024-11-22 02:16:58.095253: Pseudo dice [0.8608] +2024-11-22 02:16:58.095341: Epoch time: 19.32 s +2024-11-22 02:16:58.993597: +2024-11-22 02:16:58.993804: Epoch 2803 +2024-11-22 02:16:58.993918: Current learning rate: 0.00678 +2024-11-22 02:17:18.229479: train_loss -0.7869 +2024-11-22 02:17:18.233026: val_loss -0.7745 +2024-11-22 02:17:18.233159: Pseudo dice [0.843] +2024-11-22 02:17:18.233249: Epoch time: 19.24 s +2024-11-22 02:17:19.155470: +2024-11-22 02:17:19.155695: Epoch 2804 +2024-11-22 02:17:19.155825: Current learning rate: 0.00678 +2024-11-22 02:17:38.916661: train_loss -0.7739 +2024-11-22 02:17:38.926111: val_loss -0.7678 +2024-11-22 02:17:38.926237: Pseudo dice [0.8568] +2024-11-22 02:17:38.926332: Epoch time: 19.76 s +2024-11-22 02:17:39.787765: +2024-11-22 02:17:39.787978: Epoch 2805 +2024-11-22 02:17:39.788116: Current learning rate: 0.00678 +2024-11-22 02:17:59.010355: train_loss -0.7772 +2024-11-22 02:17:59.018772: val_loss -0.7576 +2024-11-22 02:17:59.025465: Pseudo dice [0.8481] +2024-11-22 02:17:59.025613: Epoch time: 19.22 s +2024-11-22 02:17:59.989506: +2024-11-22 02:17:59.989725: Epoch 2806 +2024-11-22 02:17:59.989843: Current learning rate: 0.00678 +2024-11-22 02:18:18.816388: train_loss -0.7773 +2024-11-22 02:18:18.820713: val_loss -0.7519 +2024-11-22 02:18:18.820857: Pseudo dice [0.8433] +2024-11-22 02:18:18.820955: Epoch time: 18.83 s +2024-11-22 02:18:19.657573: +2024-11-22 02:18:19.657780: Epoch 2807 +2024-11-22 02:18:19.657901: Current learning rate: 0.00678 +2024-11-22 02:18:39.277268: train_loss -0.7683 +2024-11-22 02:18:39.286994: val_loss -0.7685 +2024-11-22 02:18:39.287139: Pseudo dice [0.8376] +2024-11-22 02:18:39.287324: Epoch time: 19.62 s +2024-11-22 02:18:40.155749: +2024-11-22 02:18:40.155948: Epoch 2808 +2024-11-22 02:18:40.156070: Current learning rate: 0.00678 +2024-11-22 02:18:59.150217: train_loss -0.7616 +2024-11-22 02:18:59.155141: val_loss -0.7587 +2024-11-22 02:18:59.155298: Pseudo dice [0.844] +2024-11-22 02:18:59.155407: Epoch time: 19.0 s +2024-11-22 02:19:00.113273: +2024-11-22 02:19:00.113482: Epoch 2809 +2024-11-22 02:19:00.113612: Current learning rate: 0.00678 +2024-11-22 02:19:19.657863: train_loss -0.7767 +2024-11-22 02:19:19.665076: val_loss -0.7771 +2024-11-22 02:19:19.665219: Pseudo dice [0.8467] +2024-11-22 02:19:19.665338: Epoch time: 19.55 s +2024-11-22 02:19:20.520544: +2024-11-22 02:19:20.520781: Epoch 2810 +2024-11-22 02:19:20.520898: Current learning rate: 0.00677 +2024-11-22 02:19:39.791255: train_loss -0.7805 +2024-11-22 02:19:39.797578: val_loss -0.7761 +2024-11-22 02:19:39.797708: Pseudo dice [0.8533] +2024-11-22 02:19:39.797805: Epoch time: 19.27 s +2024-11-22 02:19:40.814945: +2024-11-22 02:19:40.815188: Epoch 2811 +2024-11-22 02:19:40.815312: Current learning rate: 0.00677 +2024-11-22 02:20:00.025147: train_loss -0.7793 +2024-11-22 02:20:00.030976: val_loss -0.774 +2024-11-22 02:20:00.031109: Pseudo dice [0.855] +2024-11-22 02:20:00.031195: Epoch time: 19.21 s +2024-11-22 02:20:00.949193: +2024-11-22 02:20:00.949381: Epoch 2812 +2024-11-22 02:20:00.949495: Current learning rate: 0.00677 +2024-11-22 02:20:20.042953: train_loss -0.7771 +2024-11-22 02:20:20.052015: val_loss -0.7655 +2024-11-22 02:20:20.052154: Pseudo dice [0.8497] +2024-11-22 02:20:20.052256: Epoch time: 19.09 s +2024-11-22 02:20:20.992190: +2024-11-22 02:20:20.992417: Epoch 2813 +2024-11-22 02:20:20.992546: Current learning rate: 0.00677 +2024-11-22 02:20:40.387414: train_loss -0.7703 +2024-11-22 02:20:40.394845: val_loss -0.7607 +2024-11-22 02:20:40.394965: Pseudo dice [0.8299] +2024-11-22 02:20:40.395055: Epoch time: 19.4 s +2024-11-22 02:20:41.244186: +2024-11-22 02:20:41.244395: Epoch 2814 +2024-11-22 02:20:41.244528: Current learning rate: 0.00677 +2024-11-22 02:21:01.387423: train_loss -0.7874 +2024-11-22 02:21:01.391205: val_loss -0.757 +2024-11-22 02:21:01.391348: Pseudo dice [0.8511] +2024-11-22 02:21:01.391440: Epoch time: 20.14 s +2024-11-22 02:21:02.326197: +2024-11-22 02:21:02.326434: Epoch 2815 +2024-11-22 02:21:02.326559: Current learning rate: 0.00677 +2024-11-22 02:21:21.460860: train_loss -0.79 +2024-11-22 02:21:21.462653: val_loss -0.7784 +2024-11-22 02:21:21.462769: Pseudo dice [0.8491] +2024-11-22 02:21:21.462875: Epoch time: 19.14 s +2024-11-22 02:21:22.677521: +2024-11-22 02:21:22.677868: Epoch 2816 +2024-11-22 02:21:22.678033: Current learning rate: 0.00677 +2024-11-22 02:21:41.797962: train_loss -0.777 +2024-11-22 02:21:41.801905: val_loss -0.7841 +2024-11-22 02:21:41.829703: Pseudo dice [0.8555] +2024-11-22 02:21:41.829875: Epoch time: 19.12 s +2024-11-22 02:21:42.731108: +2024-11-22 02:21:42.731311: Epoch 2817 +2024-11-22 02:21:42.731431: Current learning rate: 0.00677 +2024-11-22 02:22:00.380860: train_loss -0.7783 +2024-11-22 02:22:00.383446: val_loss -0.7399 +2024-11-22 02:22:00.383554: Pseudo dice [0.8551] +2024-11-22 02:22:00.383651: Epoch time: 17.65 s +2024-11-22 02:22:01.213188: +2024-11-22 02:22:01.213389: Epoch 2818 +2024-11-22 02:22:01.213520: Current learning rate: 0.00676 +2024-11-22 02:22:18.888147: train_loss -0.7851 +2024-11-22 02:22:18.893248: val_loss -0.7596 +2024-11-22 02:22:18.893381: Pseudo dice [0.8363] +2024-11-22 02:22:18.893515: Epoch time: 17.68 s +2024-11-22 02:22:19.730828: +2024-11-22 02:22:19.731040: Epoch 2819 +2024-11-22 02:22:19.731164: Current learning rate: 0.00676 +2024-11-22 02:22:38.283594: train_loss -0.779 +2024-11-22 02:22:38.295824: val_loss -0.7474 +2024-11-22 02:22:38.296010: Pseudo dice [0.843] +2024-11-22 02:22:38.296118: Epoch time: 18.55 s +2024-11-22 02:22:39.157659: +2024-11-22 02:22:39.157906: Epoch 2820 +2024-11-22 02:22:39.158028: Current learning rate: 0.00676 +2024-11-22 02:22:58.164685: train_loss -0.7671 +2024-11-22 02:22:58.171014: val_loss -0.777 +2024-11-22 02:22:58.171175: Pseudo dice [0.8563] +2024-11-22 02:22:58.171273: Epoch time: 19.01 s +2024-11-22 02:22:59.033536: +2024-11-22 02:22:59.033725: Epoch 2821 +2024-11-22 02:22:59.033859: Current learning rate: 0.00676 +2024-11-22 02:23:18.508373: train_loss -0.7727 +2024-11-22 02:23:18.514240: val_loss -0.7625 +2024-11-22 02:23:18.514428: Pseudo dice [0.8571] +2024-11-22 02:23:18.514538: Epoch time: 19.48 s +2024-11-22 02:23:19.346362: +2024-11-22 02:23:19.346602: Epoch 2822 +2024-11-22 02:23:19.346740: Current learning rate: 0.00676 +2024-11-22 02:23:37.473783: train_loss -0.7821 +2024-11-22 02:23:37.481126: val_loss -0.7648 +2024-11-22 02:23:37.481284: Pseudo dice [0.8569] +2024-11-22 02:23:37.481377: Epoch time: 18.13 s +2024-11-22 02:23:38.322547: +2024-11-22 02:23:38.322754: Epoch 2823 +2024-11-22 02:23:38.322888: Current learning rate: 0.00676 +2024-11-22 02:23:57.324007: train_loss -0.7787 +2024-11-22 02:23:57.329191: val_loss -0.7619 +2024-11-22 02:23:57.329341: Pseudo dice [0.8529] +2024-11-22 02:23:57.329431: Epoch time: 19.0 s +2024-11-22 02:23:58.177078: +2024-11-22 02:23:58.177274: Epoch 2824 +2024-11-22 02:23:58.177394: Current learning rate: 0.00676 +2024-11-22 02:24:16.987460: train_loss -0.7797 +2024-11-22 02:24:16.994076: val_loss -0.7684 +2024-11-22 02:24:16.994227: Pseudo dice [0.8571] +2024-11-22 02:24:16.994322: Epoch time: 18.81 s +2024-11-22 02:24:17.823437: +2024-11-22 02:24:17.823662: Epoch 2825 +2024-11-22 02:24:17.823779: Current learning rate: 0.00676 +2024-11-22 02:24:35.823930: train_loss -0.7764 +2024-11-22 02:24:35.830683: val_loss -0.7464 +2024-11-22 02:24:35.830817: Pseudo dice [0.8497] +2024-11-22 02:24:35.830921: Epoch time: 18.0 s +2024-11-22 02:24:36.672010: +2024-11-22 02:24:36.672247: Epoch 2826 +2024-11-22 02:24:36.672363: Current learning rate: 0.00676 +2024-11-22 02:24:56.254854: train_loss -0.7724 +2024-11-22 02:24:56.260433: val_loss -0.7832 +2024-11-22 02:24:56.260589: Pseudo dice [0.8466] +2024-11-22 02:24:56.260686: Epoch time: 19.58 s +2024-11-22 02:24:57.102394: +2024-11-22 02:24:57.102591: Epoch 2827 +2024-11-22 02:24:57.102719: Current learning rate: 0.00675 +2024-11-22 02:25:15.239784: train_loss -0.7823 +2024-11-22 02:25:15.245715: val_loss -0.7681 +2024-11-22 02:25:15.245848: Pseudo dice [0.8479] +2024-11-22 02:25:15.245938: Epoch time: 18.14 s +2024-11-22 02:25:16.659624: +2024-11-22 02:25:16.659821: Epoch 2828 +2024-11-22 02:25:16.659956: Current learning rate: 0.00675 +2024-11-22 02:25:36.871135: train_loss -0.7715 +2024-11-22 02:25:36.877360: val_loss -0.7623 +2024-11-22 02:25:36.877505: Pseudo dice [0.8482] +2024-11-22 02:25:36.877591: Epoch time: 20.21 s +2024-11-22 02:25:37.742633: +2024-11-22 02:25:37.742851: Epoch 2829 +2024-11-22 02:25:37.742980: Current learning rate: 0.00675 +2024-11-22 02:25:55.812160: train_loss -0.7799 +2024-11-22 02:25:55.823272: val_loss -0.7794 +2024-11-22 02:25:55.823411: Pseudo dice [0.8489] +2024-11-22 02:25:55.823518: Epoch time: 18.07 s +2024-11-22 02:25:56.849395: +2024-11-22 02:25:56.849611: Epoch 2830 +2024-11-22 02:25:56.849722: Current learning rate: 0.00675 +2024-11-22 02:26:16.237127: train_loss -0.7769 +2024-11-22 02:26:16.240229: val_loss -0.7619 +2024-11-22 02:26:16.240356: Pseudo dice [0.8525] +2024-11-22 02:26:16.240463: Epoch time: 19.39 s +2024-11-22 02:26:17.076339: +2024-11-22 02:26:17.076556: Epoch 2831 +2024-11-22 02:26:17.076673: Current learning rate: 0.00675 +2024-11-22 02:26:36.634045: train_loss -0.7711 +2024-11-22 02:26:36.639980: val_loss -0.7515 +2024-11-22 02:26:36.640116: Pseudo dice [0.8393] +2024-11-22 02:26:36.640229: Epoch time: 19.56 s +2024-11-22 02:26:37.492095: +2024-11-22 02:26:37.492358: Epoch 2832 +2024-11-22 02:26:37.492476: Current learning rate: 0.00675 +2024-11-22 02:26:56.399758: train_loss -0.7706 +2024-11-22 02:26:56.402041: val_loss -0.7729 +2024-11-22 02:26:56.402182: Pseudo dice [0.8336] +2024-11-22 02:26:56.402272: Epoch time: 18.91 s +2024-11-22 02:26:57.355874: +2024-11-22 02:26:57.356107: Epoch 2833 +2024-11-22 02:26:57.356223: Current learning rate: 0.00675 +2024-11-22 02:27:16.215932: train_loss -0.7863 +2024-11-22 02:27:16.220544: val_loss -0.7535 +2024-11-22 02:27:16.221021: Pseudo dice [0.8521] +2024-11-22 02:27:16.221164: Epoch time: 18.86 s +2024-11-22 02:27:17.148146: +2024-11-22 02:27:17.148343: Epoch 2834 +2024-11-22 02:27:17.148464: Current learning rate: 0.00675 +2024-11-22 02:27:37.435799: train_loss -0.7881 +2024-11-22 02:27:37.445863: val_loss -0.7397 +2024-11-22 02:27:37.446000: Pseudo dice [0.8526] +2024-11-22 02:27:37.446115: Epoch time: 20.29 s +2024-11-22 02:27:38.296280: +2024-11-22 02:27:38.296472: Epoch 2835 +2024-11-22 02:27:38.296616: Current learning rate: 0.00675 +2024-11-22 02:27:57.522000: train_loss -0.771 +2024-11-22 02:27:57.527558: val_loss -0.7686 +2024-11-22 02:27:57.527703: Pseudo dice [0.8636] +2024-11-22 02:27:57.527813: Epoch time: 19.23 s +2024-11-22 02:27:58.417258: +2024-11-22 02:27:58.417477: Epoch 2836 +2024-11-22 02:27:58.417600: Current learning rate: 0.00674 +2024-11-22 02:28:16.489363: train_loss -0.7716 +2024-11-22 02:28:16.504479: val_loss -0.7831 +2024-11-22 02:28:16.504639: Pseudo dice [0.8578] +2024-11-22 02:28:16.504748: Epoch time: 18.07 s +2024-11-22 02:28:17.440963: +2024-11-22 02:28:17.441160: Epoch 2837 +2024-11-22 02:28:17.441313: Current learning rate: 0.00674 +2024-11-22 02:28:36.387855: train_loss -0.7786 +2024-11-22 02:28:36.389662: val_loss -0.7267 +2024-11-22 02:28:36.389763: Pseudo dice [0.8498] +2024-11-22 02:28:36.389862: Epoch time: 18.95 s +2024-11-22 02:28:37.225539: +2024-11-22 02:28:37.225742: Epoch 2838 +2024-11-22 02:28:37.225863: Current learning rate: 0.00674 +2024-11-22 02:28:55.381422: train_loss -0.7845 +2024-11-22 02:28:55.391221: val_loss -0.7574 +2024-11-22 02:28:55.391388: Pseudo dice [0.8567] +2024-11-22 02:28:55.391488: Epoch time: 18.16 s +2024-11-22 02:28:56.624764: +2024-11-22 02:28:56.625002: Epoch 2839 +2024-11-22 02:28:56.625153: Current learning rate: 0.00674 +2024-11-22 02:29:15.934537: train_loss -0.7767 +2024-11-22 02:29:15.936475: val_loss -0.7407 +2024-11-22 02:29:15.936615: Pseudo dice [0.8569] +2024-11-22 02:29:15.936710: Epoch time: 19.31 s +2024-11-22 02:29:16.769627: +2024-11-22 02:29:16.769844: Epoch 2840 +2024-11-22 02:29:16.769957: Current learning rate: 0.00674 +2024-11-22 02:29:35.471800: train_loss -0.7876 +2024-11-22 02:29:35.473237: val_loss -0.7581 +2024-11-22 02:29:35.473332: Pseudo dice [0.8471] +2024-11-22 02:29:35.473427: Epoch time: 18.7 s +2024-11-22 02:29:36.300530: +2024-11-22 02:29:36.300739: Epoch 2841 +2024-11-22 02:29:36.300855: Current learning rate: 0.00674 +2024-11-22 02:29:56.309294: train_loss -0.7781 +2024-11-22 02:29:56.316425: val_loss -0.7657 +2024-11-22 02:29:56.316579: Pseudo dice [0.8539] +2024-11-22 02:29:56.316671: Epoch time: 20.01 s +2024-11-22 02:29:57.221970: +2024-11-22 02:29:57.243700: Epoch 2842 +2024-11-22 02:29:57.243836: Current learning rate: 0.00674 +2024-11-22 02:30:16.850082: train_loss -0.7799 +2024-11-22 02:30:16.854160: val_loss -0.7635 +2024-11-22 02:30:16.854305: Pseudo dice [0.8493] +2024-11-22 02:30:16.854410: Epoch time: 19.63 s +2024-11-22 02:30:17.687402: +2024-11-22 02:30:17.687614: Epoch 2843 +2024-11-22 02:30:17.687732: Current learning rate: 0.00674 +2024-11-22 02:30:35.701531: train_loss -0.7715 +2024-11-22 02:30:35.706509: val_loss -0.763 +2024-11-22 02:30:35.706646: Pseudo dice [0.8565] +2024-11-22 02:30:35.706742: Epoch time: 18.01 s +2024-11-22 02:30:36.719364: +2024-11-22 02:30:36.719573: Epoch 2844 +2024-11-22 02:30:36.719705: Current learning rate: 0.00673 +2024-11-22 02:30:55.582176: train_loss -0.7653 +2024-11-22 02:30:55.584443: val_loss -0.7452 +2024-11-22 02:30:55.584569: Pseudo dice [0.8306] +2024-11-22 02:30:55.584685: Epoch time: 18.86 s +2024-11-22 02:30:56.527497: +2024-11-22 02:30:56.527690: Epoch 2845 +2024-11-22 02:30:56.527817: Current learning rate: 0.00673 +2024-11-22 02:31:15.014918: train_loss -0.77 +2024-11-22 02:31:15.022122: val_loss -0.7573 +2024-11-22 02:31:15.022248: Pseudo dice [0.8561] +2024-11-22 02:31:15.022338: Epoch time: 18.49 s +2024-11-22 02:31:15.914729: +2024-11-22 02:31:15.914942: Epoch 2846 +2024-11-22 02:31:15.915072: Current learning rate: 0.00673 +2024-11-22 02:31:33.837549: train_loss -0.7808 +2024-11-22 02:31:33.843244: val_loss -0.7889 +2024-11-22 02:31:33.843361: Pseudo dice [0.8528] +2024-11-22 02:31:33.843454: Epoch time: 17.92 s +2024-11-22 02:31:34.687533: +2024-11-22 02:31:34.687763: Epoch 2847 +2024-11-22 02:31:34.687886: Current learning rate: 0.00673 +2024-11-22 02:31:53.210187: train_loss -0.7874 +2024-11-22 02:31:53.215180: val_loss -0.7569 +2024-11-22 02:31:53.215304: Pseudo dice [0.858] +2024-11-22 02:31:53.215383: Epoch time: 18.52 s +2024-11-22 02:31:54.044271: +2024-11-22 02:31:54.044472: Epoch 2848 +2024-11-22 02:31:54.044600: Current learning rate: 0.00673 +2024-11-22 02:32:12.600915: train_loss -0.775 +2024-11-22 02:32:12.609812: val_loss -0.7655 +2024-11-22 02:32:12.609938: Pseudo dice [0.8466] +2024-11-22 02:32:12.610031: Epoch time: 18.56 s +2024-11-22 02:32:13.577801: +2024-11-22 02:32:13.577990: Epoch 2849 +2024-11-22 02:32:13.578106: Current learning rate: 0.00673 +2024-11-22 02:32:33.328533: train_loss -0.7824 +2024-11-22 02:32:33.336207: val_loss -0.7537 +2024-11-22 02:32:33.336356: Pseudo dice [0.8625] +2024-11-22 02:32:33.336442: Epoch time: 19.75 s +2024-11-22 02:32:34.383486: +2024-11-22 02:32:34.383690: Epoch 2850 +2024-11-22 02:32:34.383807: Current learning rate: 0.00673 +2024-11-22 02:32:53.883502: train_loss -0.782 +2024-11-22 02:32:53.888690: val_loss -0.7821 +2024-11-22 02:32:53.888847: Pseudo dice [0.8483] +2024-11-22 02:32:53.888945: Epoch time: 19.5 s +2024-11-22 02:32:54.725471: +2024-11-22 02:32:54.725680: Epoch 2851 +2024-11-22 02:32:54.725802: Current learning rate: 0.00673 +2024-11-22 02:33:13.670177: train_loss -0.7772 +2024-11-22 02:33:13.679309: val_loss -0.7415 +2024-11-22 02:33:13.679433: Pseudo dice [0.8583] +2024-11-22 02:33:13.679531: Epoch time: 18.95 s +2024-11-22 02:33:14.542849: +2024-11-22 02:33:14.543045: Epoch 2852 +2024-11-22 02:33:14.543165: Current learning rate: 0.00673 +2024-11-22 02:33:33.705768: train_loss -0.7705 +2024-11-22 02:33:33.711694: val_loss -0.7503 +2024-11-22 02:33:33.711894: Pseudo dice [0.8523] +2024-11-22 02:33:33.711992: Epoch time: 19.16 s +2024-11-22 02:33:34.603680: +2024-11-22 02:33:34.603878: Epoch 2853 +2024-11-22 02:33:34.603999: Current learning rate: 0.00672 +2024-11-22 02:33:53.069105: train_loss -0.7758 +2024-11-22 02:33:53.070672: val_loss -0.7596 +2024-11-22 02:33:53.070779: Pseudo dice [0.8556] +2024-11-22 02:33:53.070878: Epoch time: 18.47 s +2024-11-22 02:33:53.070951: Yayy! New best EMA pseudo Dice: 0.8527 +2024-11-22 02:33:54.133946: +2024-11-22 02:33:54.134173: Epoch 2854 +2024-11-22 02:33:54.134307: Current learning rate: 0.00672 +2024-11-22 02:34:12.843235: train_loss -0.7854 +2024-11-22 02:34:12.848712: val_loss -0.7937 +2024-11-22 02:34:12.848826: Pseudo dice [0.8545] +2024-11-22 02:34:12.848914: Epoch time: 18.71 s +2024-11-22 02:34:12.848982: Yayy! New best EMA pseudo Dice: 0.8528 +2024-11-22 02:34:14.162268: +2024-11-22 02:34:14.162481: Epoch 2855 +2024-11-22 02:34:14.162599: Current learning rate: 0.00672 +2024-11-22 02:34:33.008593: train_loss -0.7765 +2024-11-22 02:34:33.015876: val_loss -0.7782 +2024-11-22 02:34:33.015999: Pseudo dice [0.8626] +2024-11-22 02:34:33.016107: Epoch time: 18.85 s +2024-11-22 02:34:33.016186: Yayy! New best EMA pseudo Dice: 0.8538 +2024-11-22 02:34:34.274747: +2024-11-22 02:34:34.274986: Epoch 2856 +2024-11-22 02:34:34.275116: Current learning rate: 0.00672 +2024-11-22 02:34:54.594968: train_loss -0.7848 +2024-11-22 02:34:54.599068: val_loss -0.7678 +2024-11-22 02:34:54.599192: Pseudo dice [0.8602] +2024-11-22 02:34:54.599288: Epoch time: 20.32 s +2024-11-22 02:34:54.599366: Yayy! New best EMA pseudo Dice: 0.8545 +2024-11-22 02:34:55.655328: +2024-11-22 02:34:55.655545: Epoch 2857 +2024-11-22 02:34:55.655685: Current learning rate: 0.00672 +2024-11-22 02:35:15.094590: train_loss -0.7721 +2024-11-22 02:35:15.107619: val_loss -0.7725 +2024-11-22 02:35:15.107769: Pseudo dice [0.8397] +2024-11-22 02:35:15.107864: Epoch time: 19.44 s +2024-11-22 02:35:15.953092: +2024-11-22 02:35:15.953295: Epoch 2858 +2024-11-22 02:35:15.953413: Current learning rate: 0.00672 +2024-11-22 02:35:34.403181: train_loss -0.7771 +2024-11-22 02:35:34.408830: val_loss -0.7781 +2024-11-22 02:35:34.408973: Pseudo dice [0.8614] +2024-11-22 02:35:34.409342: Epoch time: 18.45 s +2024-11-22 02:35:35.254328: +2024-11-22 02:35:35.254547: Epoch 2859 +2024-11-22 02:35:35.254684: Current learning rate: 0.00672 +2024-11-22 02:35:55.028035: train_loss -0.7851 +2024-11-22 02:35:55.034175: val_loss -0.778 +2024-11-22 02:35:55.034281: Pseudo dice [0.8417] +2024-11-22 02:35:55.034376: Epoch time: 19.77 s +2024-11-22 02:35:55.962062: +2024-11-22 02:35:55.962261: Epoch 2860 +2024-11-22 02:35:55.962389: Current learning rate: 0.00672 +2024-11-22 02:36:14.972511: train_loss -0.7759 +2024-11-22 02:36:14.978253: val_loss -0.7797 +2024-11-22 02:36:14.978377: Pseudo dice [0.8455] +2024-11-22 02:36:14.978459: Epoch time: 19.01 s +2024-11-22 02:36:16.222364: +2024-11-22 02:36:16.222579: Epoch 2861 +2024-11-22 02:36:16.222708: Current learning rate: 0.00671 +2024-11-22 02:36:34.450782: train_loss -0.7863 +2024-11-22 02:36:34.455312: val_loss -0.7682 +2024-11-22 02:36:34.455434: Pseudo dice [0.8557] +2024-11-22 02:36:34.455529: Epoch time: 18.23 s +2024-11-22 02:36:35.482935: +2024-11-22 02:36:35.483188: Epoch 2862 +2024-11-22 02:36:35.483311: Current learning rate: 0.00671 +2024-11-22 02:36:55.025172: train_loss -0.7845 +2024-11-22 02:36:55.031179: val_loss -0.7802 +2024-11-22 02:36:55.031334: Pseudo dice [0.8469] +2024-11-22 02:36:55.031436: Epoch time: 19.54 s +2024-11-22 02:36:55.976595: +2024-11-22 02:36:55.976828: Epoch 2863 +2024-11-22 02:36:55.976962: Current learning rate: 0.00671 +2024-11-22 02:37:15.598619: train_loss -0.7767 +2024-11-22 02:37:15.604319: val_loss -0.7711 +2024-11-22 02:37:15.604447: Pseudo dice [0.8481] +2024-11-22 02:37:15.604543: Epoch time: 19.62 s +2024-11-22 02:37:16.455882: +2024-11-22 02:37:16.456096: Epoch 2864 +2024-11-22 02:37:16.456216: Current learning rate: 0.00671 +2024-11-22 02:37:35.994928: train_loss -0.7875 +2024-11-22 02:37:35.999565: val_loss -0.7691 +2024-11-22 02:37:35.999696: Pseudo dice [0.8619] +2024-11-22 02:37:35.999798: Epoch time: 19.54 s +2024-11-22 02:37:36.839524: +2024-11-22 02:37:36.839735: Epoch 2865 +2024-11-22 02:37:36.839873: Current learning rate: 0.00671 +2024-11-22 02:37:56.108018: train_loss -0.7764 +2024-11-22 02:37:56.114227: val_loss -0.767 +2024-11-22 02:37:56.114384: Pseudo dice [0.8604] +2024-11-22 02:37:56.114482: Epoch time: 19.27 s +2024-11-22 02:37:56.979947: +2024-11-22 02:37:56.980158: Epoch 2866 +2024-11-22 02:37:56.980281: Current learning rate: 0.00671 +2024-11-22 02:38:17.295079: train_loss -0.7803 +2024-11-22 02:38:17.319333: val_loss -0.7754 +2024-11-22 02:38:17.320159: Pseudo dice [0.8432] +2024-11-22 02:38:17.320292: Epoch time: 20.32 s +2024-11-22 02:38:18.300825: +2024-11-22 02:38:18.301069: Epoch 2867 +2024-11-22 02:38:18.301188: Current learning rate: 0.00671 +2024-11-22 02:38:36.639199: train_loss -0.7814 +2024-11-22 02:38:36.648111: val_loss -0.7623 +2024-11-22 02:38:36.648258: Pseudo dice [0.8534] +2024-11-22 02:38:36.648353: Epoch time: 18.34 s +2024-11-22 02:38:37.537692: +2024-11-22 02:38:37.537934: Epoch 2868 +2024-11-22 02:38:37.538066: Current learning rate: 0.00671 +2024-11-22 02:38:55.272658: train_loss -0.7855 +2024-11-22 02:38:55.283734: val_loss -0.7759 +2024-11-22 02:38:55.283874: Pseudo dice [0.8521] +2024-11-22 02:38:55.283978: Epoch time: 17.74 s +2024-11-22 02:38:56.177197: +2024-11-22 02:38:56.177425: Epoch 2869 +2024-11-22 02:38:56.177577: Current learning rate: 0.00671 +2024-11-22 02:39:13.894868: train_loss -0.7821 +2024-11-22 02:39:13.896573: val_loss -0.774 +2024-11-22 02:39:13.896671: Pseudo dice [0.8512] +2024-11-22 02:39:13.896789: Epoch time: 17.72 s +2024-11-22 02:39:14.735128: +2024-11-22 02:39:14.735332: Epoch 2870 +2024-11-22 02:39:14.735466: Current learning rate: 0.0067 +2024-11-22 02:39:33.963793: train_loss -0.7857 +2024-11-22 02:39:33.970911: val_loss -0.78 +2024-11-22 02:39:33.971078: Pseudo dice [0.8554] +2024-11-22 02:39:33.971236: Epoch time: 19.23 s +2024-11-22 02:39:34.815947: +2024-11-22 02:39:34.816149: Epoch 2871 +2024-11-22 02:39:34.816266: Current learning rate: 0.0067 +2024-11-22 02:39:53.631437: train_loss -0.7798 +2024-11-22 02:39:53.638836: val_loss -0.7531 +2024-11-22 02:39:53.638977: Pseudo dice [0.8469] +2024-11-22 02:39:53.639071: Epoch time: 18.82 s +2024-11-22 02:39:55.008469: +2024-11-22 02:39:55.008669: Epoch 2872 +2024-11-22 02:39:55.008804: Current learning rate: 0.0067 +2024-11-22 02:40:12.878831: train_loss -0.7775 +2024-11-22 02:40:12.880478: val_loss -0.7727 +2024-11-22 02:40:12.880587: Pseudo dice [0.8465] +2024-11-22 02:40:12.880686: Epoch time: 17.87 s +2024-11-22 02:40:13.717219: +2024-11-22 02:40:13.717428: Epoch 2873 +2024-11-22 02:40:13.717541: Current learning rate: 0.0067 +2024-11-22 02:40:32.568554: train_loss -0.7806 +2024-11-22 02:40:32.573749: val_loss -0.7714 +2024-11-22 02:40:32.573894: Pseudo dice [0.8642] +2024-11-22 02:40:32.573994: Epoch time: 18.85 s +2024-11-22 02:40:33.532214: +2024-11-22 02:40:33.532471: Epoch 2874 +2024-11-22 02:40:33.532605: Current learning rate: 0.0067 +2024-11-22 02:40:53.044607: train_loss -0.7766 +2024-11-22 02:40:53.049070: val_loss -0.7602 +2024-11-22 02:40:53.049977: Pseudo dice [0.8349] +2024-11-22 02:40:53.050106: Epoch time: 19.51 s +2024-11-22 02:40:53.930714: +2024-11-22 02:40:53.930954: Epoch 2875 +2024-11-22 02:40:53.931093: Current learning rate: 0.0067 +2024-11-22 02:41:12.495013: train_loss -0.773 +2024-11-22 02:41:12.505713: val_loss -0.7333 +2024-11-22 02:41:12.505854: Pseudo dice [0.8391] +2024-11-22 02:41:12.505954: Epoch time: 18.57 s +2024-11-22 02:41:13.352340: +2024-11-22 02:41:13.352593: Epoch 2876 +2024-11-22 02:41:13.352759: Current learning rate: 0.0067 +2024-11-22 02:41:31.450765: train_loss -0.7742 +2024-11-22 02:41:31.452339: val_loss -0.7722 +2024-11-22 02:41:31.452449: Pseudo dice [0.8492] +2024-11-22 02:41:31.452543: Epoch time: 18.1 s +2024-11-22 02:41:32.296124: +2024-11-22 02:41:32.296323: Epoch 2877 +2024-11-22 02:41:32.296445: Current learning rate: 0.0067 +2024-11-22 02:41:51.528316: train_loss -0.7823 +2024-11-22 02:41:51.536801: val_loss -0.7656 +2024-11-22 02:41:51.536955: Pseudo dice [0.8463] +2024-11-22 02:41:51.537068: Epoch time: 19.23 s +2024-11-22 02:41:52.376292: +2024-11-22 02:41:52.376498: Epoch 2878 +2024-11-22 02:41:52.376629: Current learning rate: 0.00669 +2024-11-22 02:42:11.047422: train_loss -0.782 +2024-11-22 02:42:11.052110: val_loss -0.7645 +2024-11-22 02:42:11.052278: Pseudo dice [0.8522] +2024-11-22 02:42:11.052391: Epoch time: 18.67 s +2024-11-22 02:42:11.902221: +2024-11-22 02:42:11.902456: Epoch 2879 +2024-11-22 02:42:11.902597: Current learning rate: 0.00669 +2024-11-22 02:42:31.755003: train_loss -0.777 +2024-11-22 02:42:31.757057: val_loss -0.7699 +2024-11-22 02:42:31.757195: Pseudo dice [0.8489] +2024-11-22 02:42:31.757302: Epoch time: 19.85 s +2024-11-22 02:42:32.804856: +2024-11-22 02:42:32.805049: Epoch 2880 +2024-11-22 02:42:32.805171: Current learning rate: 0.00669 +2024-11-22 02:42:52.152464: train_loss -0.7796 +2024-11-22 02:42:52.154511: val_loss -0.7847 +2024-11-22 02:42:52.154604: Pseudo dice [0.8461] +2024-11-22 02:42:52.154679: Epoch time: 19.35 s +2024-11-22 02:42:52.982400: +2024-11-22 02:42:52.982644: Epoch 2881 +2024-11-22 02:42:52.982760: Current learning rate: 0.00669 +2024-11-22 02:43:11.680857: train_loss -0.7688 +2024-11-22 02:43:11.693773: val_loss -0.7787 +2024-11-22 02:43:11.693901: Pseudo dice [0.8471] +2024-11-22 02:43:11.693982: Epoch time: 18.7 s +2024-11-22 02:43:12.769410: +2024-11-22 02:43:12.769604: Epoch 2882 +2024-11-22 02:43:12.769734: Current learning rate: 0.00669 +2024-11-22 02:43:30.842067: train_loss -0.7758 +2024-11-22 02:43:30.844896: val_loss -0.7598 +2024-11-22 02:43:30.845034: Pseudo dice [0.8377] +2024-11-22 02:43:30.845181: Epoch time: 18.07 s +2024-11-22 02:43:32.152073: +2024-11-22 02:43:32.152298: Epoch 2883 +2024-11-22 02:43:32.152431: Current learning rate: 0.00669 +2024-11-22 02:43:49.814180: train_loss -0.778 +2024-11-22 02:43:49.817359: val_loss -0.7439 +2024-11-22 02:43:49.817497: Pseudo dice [0.8425] +2024-11-22 02:43:49.817599: Epoch time: 17.66 s +2024-11-22 02:43:50.818093: +2024-11-22 02:43:50.818291: Epoch 2884 +2024-11-22 02:43:50.818408: Current learning rate: 0.00669 +2024-11-22 02:44:10.562310: train_loss -0.7855 +2024-11-22 02:44:10.569734: val_loss -0.7816 +2024-11-22 02:44:10.570016: Pseudo dice [0.8573] +2024-11-22 02:44:10.570132: Epoch time: 19.75 s +2024-11-22 02:44:11.434428: +2024-11-22 02:44:11.434666: Epoch 2885 +2024-11-22 02:44:11.434800: Current learning rate: 0.00669 +2024-11-22 02:44:30.950420: train_loss -0.7867 +2024-11-22 02:44:30.959057: val_loss -0.7645 +2024-11-22 02:44:30.959195: Pseudo dice [0.8466] +2024-11-22 02:44:30.959296: Epoch time: 19.52 s +2024-11-22 02:44:31.864310: +2024-11-22 02:44:31.864534: Epoch 2886 +2024-11-22 02:44:31.864656: Current learning rate: 0.00669 +2024-11-22 02:44:51.075259: train_loss -0.7902 +2024-11-22 02:44:51.086582: val_loss -0.8002 +2024-11-22 02:44:51.086730: Pseudo dice [0.8672] +2024-11-22 02:44:51.086847: Epoch time: 19.21 s +2024-11-22 02:44:52.012511: +2024-11-22 02:44:52.012733: Epoch 2887 +2024-11-22 02:44:52.012850: Current learning rate: 0.00668 +2024-11-22 02:45:11.357159: train_loss -0.7724 +2024-11-22 02:45:11.365657: val_loss -0.7027 +2024-11-22 02:45:11.365783: Pseudo dice [0.8346] +2024-11-22 02:45:11.365895: Epoch time: 19.35 s +2024-11-22 02:45:12.212426: +2024-11-22 02:45:12.212641: Epoch 2888 +2024-11-22 02:45:12.212754: Current learning rate: 0.00668 +2024-11-22 02:45:31.300432: train_loss -0.7763 +2024-11-22 02:45:31.307000: val_loss -0.7569 +2024-11-22 02:45:31.307161: Pseudo dice [0.8483] +2024-11-22 02:45:31.307314: Epoch time: 19.09 s +2024-11-22 02:45:32.232839: +2024-11-22 02:45:32.233044: Epoch 2889 +2024-11-22 02:45:32.233189: Current learning rate: 0.00668 +2024-11-22 02:45:50.916256: train_loss -0.7735 +2024-11-22 02:45:50.932433: val_loss -0.7749 +2024-11-22 02:45:50.932564: Pseudo dice [0.8444] +2024-11-22 02:45:50.932651: Epoch time: 18.68 s +2024-11-22 02:45:51.822425: +2024-11-22 02:45:51.822628: Epoch 2890 +2024-11-22 02:45:51.822753: Current learning rate: 0.00668 +2024-11-22 02:46:10.989540: train_loss -0.7673 +2024-11-22 02:46:10.997093: val_loss -0.7707 +2024-11-22 02:46:10.997328: Pseudo dice [0.8502] +2024-11-22 02:46:10.997438: Epoch time: 19.17 s +2024-11-22 02:46:11.842709: +2024-11-22 02:46:11.842904: Epoch 2891 +2024-11-22 02:46:11.843027: Current learning rate: 0.00668 +2024-11-22 02:46:30.234910: train_loss -0.7692 +2024-11-22 02:46:30.237105: val_loss -0.7594 +2024-11-22 02:46:30.237211: Pseudo dice [0.842] +2024-11-22 02:46:30.237362: Epoch time: 18.39 s +2024-11-22 02:46:31.090515: +2024-11-22 02:46:31.090749: Epoch 2892 +2024-11-22 02:46:31.090880: Current learning rate: 0.00668 +2024-11-22 02:46:50.229481: train_loss -0.773 +2024-11-22 02:46:50.238327: val_loss -0.7716 +2024-11-22 02:46:50.238478: Pseudo dice [0.8476] +2024-11-22 02:46:50.238633: Epoch time: 19.14 s +2024-11-22 02:46:51.114425: +2024-11-22 02:46:51.114635: Epoch 2893 +2024-11-22 02:46:51.114764: Current learning rate: 0.00668 +2024-11-22 02:47:11.365566: train_loss -0.774 +2024-11-22 02:47:11.372591: val_loss -0.7472 +2024-11-22 02:47:11.372706: Pseudo dice [0.8581] +2024-11-22 02:47:11.372801: Epoch time: 20.25 s +2024-11-22 02:47:12.671947: +2024-11-22 02:47:12.672148: Epoch 2894 +2024-11-22 02:47:12.672265: Current learning rate: 0.00668 +2024-11-22 02:47:32.596484: train_loss -0.7747 +2024-11-22 02:47:32.599248: val_loss -0.7534 +2024-11-22 02:47:32.599361: Pseudo dice [0.8416] +2024-11-22 02:47:32.599524: Epoch time: 19.93 s +2024-11-22 02:47:33.440132: +2024-11-22 02:47:33.440331: Epoch 2895 +2024-11-22 02:47:33.440440: Current learning rate: 0.00667 +2024-11-22 02:47:52.762457: train_loss -0.7811 +2024-11-22 02:47:52.771200: val_loss -0.7611 +2024-11-22 02:47:52.771380: Pseudo dice [0.8445] +2024-11-22 02:47:52.771467: Epoch time: 19.32 s +2024-11-22 02:47:53.728199: +2024-11-22 02:47:53.728417: Epoch 2896 +2024-11-22 02:47:53.728540: Current learning rate: 0.00667 +2024-11-22 02:48:11.905591: train_loss -0.791 +2024-11-22 02:48:11.913066: val_loss -0.7752 +2024-11-22 02:48:11.913202: Pseudo dice [0.8554] +2024-11-22 02:48:11.913302: Epoch time: 18.18 s +2024-11-22 02:48:13.048429: +2024-11-22 02:48:13.048636: Epoch 2897 +2024-11-22 02:48:13.048767: Current learning rate: 0.00667 +2024-11-22 02:48:32.507083: train_loss -0.7797 +2024-11-22 02:48:32.509570: val_loss -0.7518 +2024-11-22 02:48:32.509675: Pseudo dice [0.8473] +2024-11-22 02:48:32.509768: Epoch time: 19.46 s +2024-11-22 02:48:33.401608: +2024-11-22 02:48:33.401829: Epoch 2898 +2024-11-22 02:48:33.401952: Current learning rate: 0.00667 +2024-11-22 02:48:52.768579: train_loss -0.7642 +2024-11-22 02:48:52.777098: val_loss -0.7552 +2024-11-22 02:48:52.777229: Pseudo dice [0.8503] +2024-11-22 02:48:52.777325: Epoch time: 19.37 s +2024-11-22 02:48:53.700396: +2024-11-22 02:48:53.700607: Epoch 2899 +2024-11-22 02:48:53.700739: Current learning rate: 0.00667 +2024-11-22 02:49:12.986668: train_loss -0.7809 +2024-11-22 02:49:12.989259: val_loss -0.768 +2024-11-22 02:49:12.989383: Pseudo dice [0.8481] +2024-11-22 02:49:12.989473: Epoch time: 19.29 s +2024-11-22 02:49:14.177301: +2024-11-22 02:49:14.177505: Epoch 2900 +2024-11-22 02:49:14.177626: Current learning rate: 0.00667 +2024-11-22 02:49:33.037650: train_loss -0.7754 +2024-11-22 02:49:33.043882: val_loss -0.7546 +2024-11-22 02:49:33.043996: Pseudo dice [0.8515] +2024-11-22 02:49:33.044085: Epoch time: 18.86 s +2024-11-22 02:49:33.940804: +2024-11-22 02:49:33.941021: Epoch 2901 +2024-11-22 02:49:33.941143: Current learning rate: 0.00667 +2024-11-22 02:49:53.903948: train_loss -0.7745 +2024-11-22 02:49:53.908751: val_loss -0.7565 +2024-11-22 02:49:53.908888: Pseudo dice [0.8506] +2024-11-22 02:49:53.908999: Epoch time: 19.96 s +2024-11-22 02:49:54.910718: +2024-11-22 02:49:54.910901: Epoch 2902 +2024-11-22 02:49:54.911030: Current learning rate: 0.00667 +2024-11-22 02:50:14.894912: train_loss -0.7787 +2024-11-22 02:50:14.909006: val_loss -0.7643 +2024-11-22 02:50:14.909157: Pseudo dice [0.8391] +2024-11-22 02:50:14.909246: Epoch time: 19.98 s +2024-11-22 02:50:15.947627: +2024-11-22 02:50:15.947820: Epoch 2903 +2024-11-22 02:50:15.947942: Current learning rate: 0.00667 +2024-11-22 02:50:35.305289: train_loss -0.7847 +2024-11-22 02:50:35.310789: val_loss -0.7725 +2024-11-22 02:50:35.310893: Pseudo dice [0.8607] +2024-11-22 02:50:35.310979: Epoch time: 19.36 s +2024-11-22 02:50:36.420109: +2024-11-22 02:50:36.420347: Epoch 2904 +2024-11-22 02:50:36.420469: Current learning rate: 0.00666 +2024-11-22 02:50:54.849017: train_loss -0.776 +2024-11-22 02:50:54.854311: val_loss -0.7753 +2024-11-22 02:50:54.872564: Pseudo dice [0.8613] +2024-11-22 02:50:54.872749: Epoch time: 18.43 s +2024-11-22 02:50:56.291355: +2024-11-22 02:50:56.291579: Epoch 2905 +2024-11-22 02:50:56.291702: Current learning rate: 0.00666 +2024-11-22 02:51:15.830465: train_loss -0.7732 +2024-11-22 02:51:15.837773: val_loss -0.771 +2024-11-22 02:51:15.837903: Pseudo dice [0.856] +2024-11-22 02:51:15.837993: Epoch time: 19.54 s +2024-11-22 02:51:16.803181: +2024-11-22 02:51:16.803414: Epoch 2906 +2024-11-22 02:51:16.803544: Current learning rate: 0.00666 +2024-11-22 02:51:36.140275: train_loss -0.7798 +2024-11-22 02:51:36.142366: val_loss -0.739 +2024-11-22 02:51:36.142503: Pseudo dice [0.832] +2024-11-22 02:51:36.142606: Epoch time: 19.34 s +2024-11-22 02:51:37.039637: +2024-11-22 02:51:37.039854: Epoch 2907 +2024-11-22 02:51:37.039988: Current learning rate: 0.00666 +2024-11-22 02:51:56.383879: train_loss -0.7832 +2024-11-22 02:51:56.387553: val_loss -0.7574 +2024-11-22 02:51:56.387703: Pseudo dice [0.847] +2024-11-22 02:51:56.387806: Epoch time: 19.35 s +2024-11-22 02:51:57.246771: +2024-11-22 02:51:57.246984: Epoch 2908 +2024-11-22 02:51:57.247132: Current learning rate: 0.00666 +2024-11-22 02:52:16.349666: train_loss -0.7715 +2024-11-22 02:52:16.365293: val_loss -0.7745 +2024-11-22 02:52:16.365426: Pseudo dice [0.8462] +2024-11-22 02:52:16.365512: Epoch time: 19.1 s +2024-11-22 02:52:17.348820: +2024-11-22 02:52:17.349033: Epoch 2909 +2024-11-22 02:52:17.349152: Current learning rate: 0.00666 +2024-11-22 02:52:36.917570: train_loss -0.7766 +2024-11-22 02:52:36.930941: val_loss -0.7668 +2024-11-22 02:52:36.931087: Pseudo dice [0.8507] +2024-11-22 02:52:36.931198: Epoch time: 19.57 s +2024-11-22 02:52:37.821668: +2024-11-22 02:52:37.821863: Epoch 2910 +2024-11-22 02:52:37.821978: Current learning rate: 0.00666 +2024-11-22 02:52:57.600735: train_loss -0.7845 +2024-11-22 02:52:57.608231: val_loss -0.7481 +2024-11-22 02:52:57.608608: Pseudo dice [0.8322] +2024-11-22 02:52:57.608707: Epoch time: 19.78 s +2024-11-22 02:52:58.538198: +2024-11-22 02:52:58.538397: Epoch 2911 +2024-11-22 02:52:58.538521: Current learning rate: 0.00666 +2024-11-22 02:53:16.591242: train_loss -0.7789 +2024-11-22 02:53:16.597807: val_loss -0.7765 +2024-11-22 02:53:16.597946: Pseudo dice [0.8311] +2024-11-22 02:53:16.598043: Epoch time: 18.05 s +2024-11-22 02:53:17.443227: +2024-11-22 02:53:17.443433: Epoch 2912 +2024-11-22 02:53:17.443553: Current learning rate: 0.00665 +2024-11-22 02:53:36.180934: train_loss -0.7752 +2024-11-22 02:53:36.187877: val_loss -0.7566 +2024-11-22 02:53:36.188006: Pseudo dice [0.8481] +2024-11-22 02:53:36.188114: Epoch time: 18.74 s +2024-11-22 02:53:37.229311: +2024-11-22 02:53:37.229513: Epoch 2913 +2024-11-22 02:53:37.229648: Current learning rate: 0.00665 +2024-11-22 02:53:56.311534: train_loss -0.7846 +2024-11-22 02:53:56.329996: val_loss -0.7666 +2024-11-22 02:53:56.330129: Pseudo dice [0.8421] +2024-11-22 02:53:56.330247: Epoch time: 19.08 s +2024-11-22 02:53:57.355799: +2024-11-22 02:53:57.356033: Epoch 2914 +2024-11-22 02:53:57.356161: Current learning rate: 0.00665 +2024-11-22 02:54:15.531759: train_loss -0.7862 +2024-11-22 02:54:15.537676: val_loss -0.7795 +2024-11-22 02:54:15.537819: Pseudo dice [0.8565] +2024-11-22 02:54:15.537916: Epoch time: 18.18 s +2024-11-22 02:54:16.444162: +2024-11-22 02:54:16.444380: Epoch 2915 +2024-11-22 02:54:16.444519: Current learning rate: 0.00665 +2024-11-22 02:54:35.315383: train_loss -0.7759 +2024-11-22 02:54:35.317171: val_loss -0.7584 +2024-11-22 02:54:35.317270: Pseudo dice [0.8592] +2024-11-22 02:54:35.317373: Epoch time: 18.87 s +2024-11-22 02:54:36.579693: +2024-11-22 02:54:36.579905: Epoch 2916 +2024-11-22 02:54:36.580024: Current learning rate: 0.00665 +2024-11-22 02:54:55.837242: train_loss -0.7715 +2024-11-22 02:54:55.843707: val_loss -0.7696 +2024-11-22 02:54:55.843902: Pseudo dice [0.8502] +2024-11-22 02:54:55.844009: Epoch time: 19.26 s +2024-11-22 02:54:57.081452: +2024-11-22 02:54:57.081699: Epoch 2917 +2024-11-22 02:54:57.081818: Current learning rate: 0.00665 +2024-11-22 02:55:15.306817: train_loss -0.7832 +2024-11-22 02:55:15.309023: val_loss -0.7707 +2024-11-22 02:55:15.309143: Pseudo dice [0.8484] +2024-11-22 02:55:15.309320: Epoch time: 18.23 s +2024-11-22 02:55:16.250982: +2024-11-22 02:55:16.251181: Epoch 2918 +2024-11-22 02:55:16.251304: Current learning rate: 0.00665 +2024-11-22 02:55:35.514426: train_loss -0.7768 +2024-11-22 02:55:35.519541: val_loss -0.7596 +2024-11-22 02:55:35.519669: Pseudo dice [0.8394] +2024-11-22 02:55:35.519764: Epoch time: 19.26 s +2024-11-22 02:55:36.381354: +2024-11-22 02:55:36.381555: Epoch 2919 +2024-11-22 02:55:36.381674: Current learning rate: 0.00665 +2024-11-22 02:55:54.504274: train_loss -0.7797 +2024-11-22 02:55:54.506714: val_loss -0.7816 +2024-11-22 02:55:54.506811: Pseudo dice [0.8539] +2024-11-22 02:55:54.506894: Epoch time: 18.12 s +2024-11-22 02:55:55.346733: +2024-11-22 02:55:55.346946: Epoch 2920 +2024-11-22 02:55:55.347076: Current learning rate: 0.00665 +2024-11-22 02:56:14.120537: train_loss -0.7736 +2024-11-22 02:56:14.127671: val_loss -0.7564 +2024-11-22 02:56:14.127798: Pseudo dice [0.8592] +2024-11-22 02:56:14.127900: Epoch time: 18.77 s +2024-11-22 02:56:15.045159: +2024-11-22 02:56:15.045369: Epoch 2921 +2024-11-22 02:56:15.045489: Current learning rate: 0.00664 +2024-11-22 02:56:34.181823: train_loss -0.7617 +2024-11-22 02:56:34.191773: val_loss -0.7403 +2024-11-22 02:56:34.191917: Pseudo dice [0.825] +2024-11-22 02:56:34.192002: Epoch time: 19.14 s +2024-11-22 02:56:35.224386: +2024-11-22 02:56:35.224602: Epoch 2922 +2024-11-22 02:56:35.224753: Current learning rate: 0.00664 +2024-11-22 02:56:55.274457: train_loss -0.7621 +2024-11-22 02:56:55.277797: val_loss -0.7506 +2024-11-22 02:56:55.277935: Pseudo dice [0.8379] +2024-11-22 02:56:55.278053: Epoch time: 20.05 s +2024-11-22 02:56:56.120796: +2024-11-22 02:56:56.121018: Epoch 2923 +2024-11-22 02:56:56.121136: Current learning rate: 0.00664 +2024-11-22 02:57:14.973895: train_loss -0.758 +2024-11-22 02:57:14.975559: val_loss -0.7579 +2024-11-22 02:57:14.975668: Pseudo dice [0.8497] +2024-11-22 02:57:14.975769: Epoch time: 18.85 s +2024-11-22 02:57:15.813686: +2024-11-22 02:57:15.813886: Epoch 2924 +2024-11-22 02:57:15.814011: Current learning rate: 0.00664 +2024-11-22 02:57:35.278928: train_loss -0.7732 +2024-11-22 02:57:35.286076: val_loss -0.7799 +2024-11-22 02:57:35.286219: Pseudo dice [0.846] +2024-11-22 02:57:35.286329: Epoch time: 19.47 s +2024-11-22 02:57:36.270613: +2024-11-22 02:57:36.270811: Epoch 2925 +2024-11-22 02:57:36.270924: Current learning rate: 0.00664 +2024-11-22 02:57:55.069965: train_loss -0.7755 +2024-11-22 02:57:55.072599: val_loss -0.7485 +2024-11-22 02:57:55.072734: Pseudo dice [0.8426] +2024-11-22 02:57:55.072827: Epoch time: 18.8 s +2024-11-22 02:57:56.116519: +2024-11-22 02:57:56.116742: Epoch 2926 +2024-11-22 02:57:56.116889: Current learning rate: 0.00664 +2024-11-22 02:58:15.105866: train_loss -0.7871 +2024-11-22 02:58:15.110962: val_loss -0.7844 +2024-11-22 02:58:15.111105: Pseudo dice [0.8576] +2024-11-22 02:58:15.111189: Epoch time: 18.99 s +2024-11-22 02:58:16.463657: +2024-11-22 02:58:16.463904: Epoch 2927 +2024-11-22 02:58:16.464055: Current learning rate: 0.00664 +2024-11-22 02:58:36.176088: train_loss -0.771 +2024-11-22 02:58:36.189168: val_loss -0.7663 +2024-11-22 02:58:36.189287: Pseudo dice [0.8333] +2024-11-22 02:58:36.189394: Epoch time: 19.71 s +2024-11-22 02:58:37.066232: +2024-11-22 02:58:37.066440: Epoch 2928 +2024-11-22 02:58:37.066563: Current learning rate: 0.00664 +2024-11-22 02:58:56.500316: train_loss -0.7786 +2024-11-22 02:58:56.505756: val_loss -0.776 +2024-11-22 02:58:56.505870: Pseudo dice [0.832] +2024-11-22 02:58:56.506031: Epoch time: 19.43 s +2024-11-22 02:58:57.347576: +2024-11-22 02:58:57.347783: Epoch 2929 +2024-11-22 02:58:57.347914: Current learning rate: 0.00663 +2024-11-22 02:59:15.809710: train_loss -0.7839 +2024-11-22 02:59:15.818498: val_loss -0.7664 +2024-11-22 02:59:15.818629: Pseudo dice [0.8569] +2024-11-22 02:59:15.818733: Epoch time: 18.46 s +2024-11-22 02:59:16.702089: +2024-11-22 02:59:16.702528: Epoch 2930 +2024-11-22 02:59:16.702657: Current learning rate: 0.00663 +2024-11-22 02:59:36.638233: train_loss -0.7777 +2024-11-22 02:59:36.650903: val_loss -0.7624 +2024-11-22 02:59:36.651135: Pseudo dice [0.8453] +2024-11-22 02:59:36.651246: Epoch time: 19.94 s +2024-11-22 02:59:37.501300: +2024-11-22 02:59:37.501509: Epoch 2931 +2024-11-22 02:59:37.501622: Current learning rate: 0.00663 +2024-11-22 02:59:56.803471: train_loss -0.7817 +2024-11-22 02:59:56.806032: val_loss -0.7694 +2024-11-22 02:59:56.806171: Pseudo dice [0.8596] +2024-11-22 02:59:56.806273: Epoch time: 19.3 s +2024-11-22 02:59:57.695284: +2024-11-22 02:59:57.695585: Epoch 2932 +2024-11-22 02:59:57.695724: Current learning rate: 0.00663 +2024-11-22 03:00:16.567429: train_loss -0.784 +2024-11-22 03:00:16.571257: val_loss -0.7551 +2024-11-22 03:00:16.571392: Pseudo dice [0.8512] +2024-11-22 03:00:16.571484: Epoch time: 18.87 s +2024-11-22 03:00:17.414963: +2024-11-22 03:00:17.415175: Epoch 2933 +2024-11-22 03:00:17.415310: Current learning rate: 0.00663 +2024-11-22 03:00:35.901384: train_loss -0.7725 +2024-11-22 03:00:35.907259: val_loss -0.7689 +2024-11-22 03:00:35.907431: Pseudo dice [0.8491] +2024-11-22 03:00:35.907518: Epoch time: 18.49 s +2024-11-22 03:00:36.763936: +2024-11-22 03:00:36.764149: Epoch 2934 +2024-11-22 03:00:36.764273: Current learning rate: 0.00663 +2024-11-22 03:00:55.747804: train_loss -0.769 +2024-11-22 03:00:55.749359: val_loss -0.7515 +2024-11-22 03:00:55.749464: Pseudo dice [0.8475] +2024-11-22 03:00:55.749566: Epoch time: 18.98 s +2024-11-22 03:00:56.597322: +2024-11-22 03:00:56.597513: Epoch 2935 +2024-11-22 03:00:56.597644: Current learning rate: 0.00663 +2024-11-22 03:01:15.626976: train_loss -0.777 +2024-11-22 03:01:15.630235: val_loss -0.7723 +2024-11-22 03:01:15.630508: Pseudo dice [0.844] +2024-11-22 03:01:15.630661: Epoch time: 19.03 s +2024-11-22 03:01:16.481097: +2024-11-22 03:01:16.481290: Epoch 2936 +2024-11-22 03:01:16.481404: Current learning rate: 0.00663 +2024-11-22 03:01:36.049609: train_loss -0.7796 +2024-11-22 03:01:36.055967: val_loss -0.7465 +2024-11-22 03:01:36.056177: Pseudo dice [0.8531] +2024-11-22 03:01:36.056267: Epoch time: 19.57 s +2024-11-22 03:01:36.905729: +2024-11-22 03:01:36.905971: Epoch 2937 +2024-11-22 03:01:36.906098: Current learning rate: 0.00663 +2024-11-22 03:01:55.291067: train_loss -0.7855 +2024-11-22 03:01:55.296052: val_loss -0.755 +2024-11-22 03:01:55.296174: Pseudo dice [0.8538] +2024-11-22 03:01:55.296259: Epoch time: 18.39 s +2024-11-22 03:01:56.771046: +2024-11-22 03:01:56.771251: Epoch 2938 +2024-11-22 03:01:56.771366: Current learning rate: 0.00662 +2024-11-22 03:02:15.486305: train_loss -0.7816 +2024-11-22 03:02:15.492025: val_loss -0.7806 +2024-11-22 03:02:15.492162: Pseudo dice [0.842] +2024-11-22 03:02:15.492264: Epoch time: 18.72 s +2024-11-22 03:02:16.654364: +2024-11-22 03:02:16.654579: Epoch 2939 +2024-11-22 03:02:16.654697: Current learning rate: 0.00662 +2024-11-22 03:02:34.859893: train_loss -0.776 +2024-11-22 03:02:34.867840: val_loss -0.7842 +2024-11-22 03:02:34.867969: Pseudo dice [0.8543] +2024-11-22 03:02:34.868054: Epoch time: 18.21 s +2024-11-22 03:02:35.784421: +2024-11-22 03:02:35.784636: Epoch 2940 +2024-11-22 03:02:35.784765: Current learning rate: 0.00662 +2024-11-22 03:02:54.908234: train_loss -0.7771 +2024-11-22 03:02:54.915309: val_loss -0.7465 +2024-11-22 03:02:54.915451: Pseudo dice [0.8488] +2024-11-22 03:02:54.915540: Epoch time: 19.12 s +2024-11-22 03:02:55.753825: +2024-11-22 03:02:55.754046: Epoch 2941 +2024-11-22 03:02:55.754179: Current learning rate: 0.00662 +2024-11-22 03:03:15.650975: train_loss -0.7696 +2024-11-22 03:03:15.654934: val_loss -0.7517 +2024-11-22 03:03:15.655086: Pseudo dice [0.8329] +2024-11-22 03:03:15.655187: Epoch time: 19.9 s +2024-11-22 03:03:16.569824: +2024-11-22 03:03:16.570039: Epoch 2942 +2024-11-22 03:03:16.570177: Current learning rate: 0.00662 +2024-11-22 03:03:36.170241: train_loss -0.7733 +2024-11-22 03:03:36.172319: val_loss -0.7675 +2024-11-22 03:03:36.172457: Pseudo dice [0.8517] +2024-11-22 03:03:36.172779: Epoch time: 19.6 s +2024-11-22 03:03:37.048326: +2024-11-22 03:03:37.048545: Epoch 2943 +2024-11-22 03:03:37.048666: Current learning rate: 0.00662 +2024-11-22 03:03:56.444558: train_loss -0.7713 +2024-11-22 03:03:56.452027: val_loss -0.7711 +2024-11-22 03:03:56.452140: Pseudo dice [0.844] +2024-11-22 03:03:56.452228: Epoch time: 19.4 s +2024-11-22 03:03:57.470214: +2024-11-22 03:03:57.470424: Epoch 2944 +2024-11-22 03:03:57.470548: Current learning rate: 0.00662 +2024-11-22 03:04:16.783000: train_loss -0.7721 +2024-11-22 03:04:16.790675: val_loss -0.7624 +2024-11-22 03:04:16.790798: Pseudo dice [0.8515] +2024-11-22 03:04:16.790885: Epoch time: 19.31 s +2024-11-22 03:04:17.800134: +2024-11-22 03:04:17.800344: Epoch 2945 +2024-11-22 03:04:17.800465: Current learning rate: 0.00662 +2024-11-22 03:04:36.259177: train_loss -0.7815 +2024-11-22 03:04:36.274791: val_loss -0.7683 +2024-11-22 03:04:36.275029: Pseudo dice [0.8544] +2024-11-22 03:04:36.275157: Epoch time: 18.46 s +2024-11-22 03:04:37.181649: +2024-11-22 03:04:37.181854: Epoch 2946 +2024-11-22 03:04:37.181969: Current learning rate: 0.00661 +2024-11-22 03:04:56.136134: train_loss -0.7822 +2024-11-22 03:04:56.143880: val_loss -0.7771 +2024-11-22 03:04:56.144023: Pseudo dice [0.8575] +2024-11-22 03:04:56.144132: Epoch time: 18.96 s +2024-11-22 03:04:56.994919: +2024-11-22 03:04:56.995115: Epoch 2947 +2024-11-22 03:04:56.995230: Current learning rate: 0.00661 +2024-11-22 03:05:15.381701: train_loss -0.7909 +2024-11-22 03:05:15.388520: val_loss -0.7678 +2024-11-22 03:05:15.388674: Pseudo dice [0.8529] +2024-11-22 03:05:15.388778: Epoch time: 18.39 s +2024-11-22 03:05:16.299328: +2024-11-22 03:05:16.299527: Epoch 2948 +2024-11-22 03:05:16.299661: Current learning rate: 0.00661 +2024-11-22 03:05:33.843326: train_loss -0.7782 +2024-11-22 03:05:33.844771: val_loss -0.7704 +2024-11-22 03:05:33.844873: Pseudo dice [0.849] +2024-11-22 03:05:33.844963: Epoch time: 17.54 s +2024-11-22 03:05:35.068377: +2024-11-22 03:05:35.068572: Epoch 2949 +2024-11-22 03:05:35.068685: Current learning rate: 0.00661 +2024-11-22 03:05:53.999790: train_loss -0.778 +2024-11-22 03:05:54.001797: val_loss -0.7889 +2024-11-22 03:05:54.001925: Pseudo dice [0.8536] +2024-11-22 03:05:54.002064: Epoch time: 18.93 s +2024-11-22 03:05:55.264644: +2024-11-22 03:05:55.264857: Epoch 2950 +2024-11-22 03:05:55.264975: Current learning rate: 0.00661 +2024-11-22 03:06:13.803653: train_loss -0.7741 +2024-11-22 03:06:13.807390: val_loss -0.7715 +2024-11-22 03:06:13.807503: Pseudo dice [0.864] +2024-11-22 03:06:13.807615: Epoch time: 18.54 s +2024-11-22 03:06:14.659133: +2024-11-22 03:06:14.659383: Epoch 2951 +2024-11-22 03:06:14.659509: Current learning rate: 0.00661 +2024-11-22 03:06:33.924506: train_loss -0.7859 +2024-11-22 03:06:33.930506: val_loss -0.7501 +2024-11-22 03:06:33.930625: Pseudo dice [0.8482] +2024-11-22 03:06:33.930724: Epoch time: 19.27 s +2024-11-22 03:06:34.868529: +2024-11-22 03:06:34.868739: Epoch 2952 +2024-11-22 03:06:34.868859: Current learning rate: 0.00661 +2024-11-22 03:06:54.805590: train_loss -0.7829 +2024-11-22 03:06:54.811757: val_loss -0.7669 +2024-11-22 03:06:54.811885: Pseudo dice [0.8388] +2024-11-22 03:06:54.811984: Epoch time: 19.94 s +2024-11-22 03:06:55.676274: +2024-11-22 03:06:55.676484: Epoch 2953 +2024-11-22 03:06:55.676620: Current learning rate: 0.00661 +2024-11-22 03:07:14.119118: train_loss -0.779 +2024-11-22 03:07:14.125339: val_loss -0.7605 +2024-11-22 03:07:14.125463: Pseudo dice [0.8464] +2024-11-22 03:07:14.125559: Epoch time: 18.44 s +2024-11-22 03:07:15.081870: +2024-11-22 03:07:15.082057: Epoch 2954 +2024-11-22 03:07:15.082179: Current learning rate: 0.0066 +2024-11-22 03:07:35.119343: train_loss -0.7828 +2024-11-22 03:07:35.126707: val_loss -0.7725 +2024-11-22 03:07:35.126839: Pseudo dice [0.8633] +2024-11-22 03:07:35.126941: Epoch time: 20.04 s +2024-11-22 03:07:35.990657: +2024-11-22 03:07:35.990893: Epoch 2955 +2024-11-22 03:07:35.991025: Current learning rate: 0.0066 +2024-11-22 03:07:54.513547: train_loss -0.7835 +2024-11-22 03:07:54.515616: val_loss -0.7745 +2024-11-22 03:07:54.515774: Pseudo dice [0.8606] +2024-11-22 03:07:54.515913: Epoch time: 18.52 s +2024-11-22 03:07:55.377522: +2024-11-22 03:07:55.377729: Epoch 2956 +2024-11-22 03:07:55.377866: Current learning rate: 0.0066 +2024-11-22 03:08:14.983828: train_loss -0.7815 +2024-11-22 03:08:14.991288: val_loss -0.7759 +2024-11-22 03:08:14.991421: Pseudo dice [0.843] +2024-11-22 03:08:14.991518: Epoch time: 19.61 s +2024-11-22 03:08:15.864796: +2024-11-22 03:08:15.864999: Epoch 2957 +2024-11-22 03:08:15.865141: Current learning rate: 0.0066 +2024-11-22 03:08:34.826857: train_loss -0.7695 +2024-11-22 03:08:34.830384: val_loss -0.7624 +2024-11-22 03:08:34.830522: Pseudo dice [0.8478] +2024-11-22 03:08:34.830612: Epoch time: 18.96 s +2024-11-22 03:08:35.712214: +2024-11-22 03:08:35.712405: Epoch 2958 +2024-11-22 03:08:35.712528: Current learning rate: 0.0066 +2024-11-22 03:08:54.948956: train_loss -0.7762 +2024-11-22 03:08:54.958717: val_loss -0.7804 +2024-11-22 03:08:54.958871: Pseudo dice [0.8467] +2024-11-22 03:08:54.958982: Epoch time: 19.24 s +2024-11-22 03:08:55.882619: +2024-11-22 03:08:55.882816: Epoch 2959 +2024-11-22 03:08:55.882936: Current learning rate: 0.0066 +2024-11-22 03:09:14.172982: train_loss -0.7781 +2024-11-22 03:09:14.180846: val_loss -0.7534 +2024-11-22 03:09:14.180989: Pseudo dice [0.8536] +2024-11-22 03:09:14.181083: Epoch time: 18.29 s +2024-11-22 03:09:15.571845: +2024-11-22 03:09:15.572067: Epoch 2960 +2024-11-22 03:09:15.572207: Current learning rate: 0.0066 +2024-11-22 03:09:33.767038: train_loss -0.778 +2024-11-22 03:09:33.768541: val_loss -0.7743 +2024-11-22 03:09:33.768647: Pseudo dice [0.8602] +2024-11-22 03:09:33.768742: Epoch time: 18.2 s +2024-11-22 03:09:34.616854: +2024-11-22 03:09:34.617065: Epoch 2961 +2024-11-22 03:09:34.617188: Current learning rate: 0.0066 +2024-11-22 03:09:53.727071: train_loss -0.7812 +2024-11-22 03:09:53.732625: val_loss -0.7734 +2024-11-22 03:09:53.732749: Pseudo dice [0.8536] +2024-11-22 03:09:53.732857: Epoch time: 19.11 s +2024-11-22 03:09:54.579266: +2024-11-22 03:09:54.579473: Epoch 2962 +2024-11-22 03:09:54.579583: Current learning rate: 0.0066 +2024-11-22 03:10:14.374055: train_loss -0.7771 +2024-11-22 03:10:14.382085: val_loss -0.7781 +2024-11-22 03:10:14.382235: Pseudo dice [0.825] +2024-11-22 03:10:14.382335: Epoch time: 19.8 s +2024-11-22 03:10:15.449821: +2024-11-22 03:10:15.450081: Epoch 2963 +2024-11-22 03:10:15.450214: Current learning rate: 0.00659 +2024-11-22 03:10:34.450621: train_loss -0.7649 +2024-11-22 03:10:34.463807: val_loss -0.7603 +2024-11-22 03:10:34.463924: Pseudo dice [0.8472] +2024-11-22 03:10:34.464012: Epoch time: 19.0 s +2024-11-22 03:10:35.312985: +2024-11-22 03:10:35.313207: Epoch 2964 +2024-11-22 03:10:35.313340: Current learning rate: 0.00659 +2024-11-22 03:10:54.376136: train_loss -0.7767 +2024-11-22 03:10:54.378052: val_loss -0.7686 +2024-11-22 03:10:54.378155: Pseudo dice [0.8484] +2024-11-22 03:10:54.378259: Epoch time: 19.06 s +2024-11-22 03:10:55.223236: +2024-11-22 03:10:55.223439: Epoch 2965 +2024-11-22 03:10:55.223558: Current learning rate: 0.00659 +2024-11-22 03:11:14.141768: train_loss -0.7714 +2024-11-22 03:11:14.145665: val_loss -0.7642 +2024-11-22 03:11:14.145780: Pseudo dice [0.8544] +2024-11-22 03:11:14.145863: Epoch time: 18.92 s +2024-11-22 03:11:15.115877: +2024-11-22 03:11:15.116105: Epoch 2966 +2024-11-22 03:11:15.116231: Current learning rate: 0.00659 +2024-11-22 03:11:33.032948: train_loss -0.7773 +2024-11-22 03:11:33.034408: val_loss -0.7707 +2024-11-22 03:11:33.034516: Pseudo dice [0.8495] +2024-11-22 03:11:33.034616: Epoch time: 17.92 s +2024-11-22 03:11:33.879006: +2024-11-22 03:11:33.879237: Epoch 2967 +2024-11-22 03:11:33.879363: Current learning rate: 0.00659 +2024-11-22 03:11:53.597051: train_loss -0.7659 +2024-11-22 03:11:53.604758: val_loss -0.7645 +2024-11-22 03:11:53.604877: Pseudo dice [0.851] +2024-11-22 03:11:53.604993: Epoch time: 19.72 s +2024-11-22 03:11:54.528298: +2024-11-22 03:11:54.528491: Epoch 2968 +2024-11-22 03:11:54.528812: Current learning rate: 0.00659 +2024-11-22 03:12:14.149107: train_loss -0.7726 +2024-11-22 03:12:14.156138: val_loss -0.7648 +2024-11-22 03:12:14.156269: Pseudo dice [0.8451] +2024-11-22 03:12:14.156376: Epoch time: 19.62 s +2024-11-22 03:12:15.213205: +2024-11-22 03:12:15.213430: Epoch 2969 +2024-11-22 03:12:15.213542: Current learning rate: 0.00659 +2024-11-22 03:12:33.954912: train_loss -0.7633 +2024-11-22 03:12:33.962313: val_loss -0.7644 +2024-11-22 03:12:33.962447: Pseudo dice [0.855] +2024-11-22 03:12:33.962557: Epoch time: 18.74 s +2024-11-22 03:12:34.948262: +2024-11-22 03:12:34.948473: Epoch 2970 +2024-11-22 03:12:34.948600: Current learning rate: 0.00659 +2024-11-22 03:12:52.569862: train_loss -0.7847 +2024-11-22 03:12:52.574948: val_loss -0.7808 +2024-11-22 03:12:52.575091: Pseudo dice [0.8662] +2024-11-22 03:12:52.575180: Epoch time: 17.62 s +2024-11-22 03:12:54.071867: +2024-11-22 03:12:54.072078: Epoch 2971 +2024-11-22 03:12:54.072203: Current learning rate: 0.00658 +2024-11-22 03:13:12.643788: train_loss -0.7853 +2024-11-22 03:13:12.649832: val_loss -0.7651 +2024-11-22 03:13:12.649975: Pseudo dice [0.8486] +2024-11-22 03:13:12.650076: Epoch time: 18.57 s +2024-11-22 03:13:13.518087: +2024-11-22 03:13:13.518339: Epoch 2972 +2024-11-22 03:13:13.518479: Current learning rate: 0.00658 +2024-11-22 03:13:32.321931: train_loss -0.7657 +2024-11-22 03:13:32.325820: val_loss -0.7737 +2024-11-22 03:13:32.325956: Pseudo dice [0.8497] +2024-11-22 03:13:32.326051: Epoch time: 18.8 s +2024-11-22 03:13:33.211688: +2024-11-22 03:13:33.211907: Epoch 2973 +2024-11-22 03:13:33.212036: Current learning rate: 0.00658 +2024-11-22 03:13:53.142366: train_loss -0.7752 +2024-11-22 03:13:53.144026: val_loss -0.7539 +2024-11-22 03:13:53.144130: Pseudo dice [0.8382] +2024-11-22 03:13:53.144210: Epoch time: 19.93 s +2024-11-22 03:13:53.990929: +2024-11-22 03:13:53.991182: Epoch 2974 +2024-11-22 03:13:53.991320: Current learning rate: 0.00658 +2024-11-22 03:14:12.353105: train_loss -0.7775 +2024-11-22 03:14:12.361831: val_loss -0.7692 +2024-11-22 03:14:12.361965: Pseudo dice [0.8615] +2024-11-22 03:14:12.362066: Epoch time: 18.36 s +2024-11-22 03:14:13.358811: +2024-11-22 03:14:13.359038: Epoch 2975 +2024-11-22 03:14:13.359163: Current learning rate: 0.00658 +2024-11-22 03:14:33.659099: train_loss -0.7696 +2024-11-22 03:14:33.665345: val_loss -0.743 +2024-11-22 03:14:33.665492: Pseudo dice [0.8497] +2024-11-22 03:14:33.665602: Epoch time: 20.3 s +2024-11-22 03:14:34.534561: +2024-11-22 03:14:34.534764: Epoch 2976 +2024-11-22 03:14:34.534885: Current learning rate: 0.00658 +2024-11-22 03:14:53.305872: train_loss -0.7554 +2024-11-22 03:14:53.311289: val_loss -0.7665 +2024-11-22 03:14:53.311432: Pseudo dice [0.8399] +2024-11-22 03:14:53.311520: Epoch time: 18.77 s +2024-11-22 03:14:54.207014: +2024-11-22 03:14:54.207266: Epoch 2977 +2024-11-22 03:14:54.207387: Current learning rate: 0.00658 +2024-11-22 03:15:13.625989: train_loss -0.7603 +2024-11-22 03:15:13.631300: val_loss -0.7804 +2024-11-22 03:15:13.631445: Pseudo dice [0.8536] +2024-11-22 03:15:13.631544: Epoch time: 19.42 s +2024-11-22 03:15:14.479087: +2024-11-22 03:15:14.479314: Epoch 2978 +2024-11-22 03:15:14.479450: Current learning rate: 0.00658 +2024-11-22 03:15:34.150787: train_loss -0.773 +2024-11-22 03:15:34.152658: val_loss -0.7862 +2024-11-22 03:15:34.152796: Pseudo dice [0.8572] +2024-11-22 03:15:34.152890: Epoch time: 19.67 s +2024-11-22 03:15:35.126244: +2024-11-22 03:15:35.126501: Epoch 2979 +2024-11-22 03:15:35.126620: Current learning rate: 0.00658 +2024-11-22 03:15:54.031500: train_loss -0.7719 +2024-11-22 03:15:54.034987: val_loss -0.7568 +2024-11-22 03:15:54.035141: Pseudo dice [0.8489] +2024-11-22 03:15:54.035244: Epoch time: 18.91 s +2024-11-22 03:15:54.922681: +2024-11-22 03:15:54.922941: Epoch 2980 +2024-11-22 03:15:54.923069: Current learning rate: 0.00657 +2024-11-22 03:16:13.518980: train_loss -0.7839 +2024-11-22 03:16:13.523248: val_loss -0.7685 +2024-11-22 03:16:13.523437: Pseudo dice [0.8603] +2024-11-22 03:16:13.523518: Epoch time: 18.6 s +2024-11-22 03:16:14.383064: +2024-11-22 03:16:14.383289: Epoch 2981 +2024-11-22 03:16:14.383406: Current learning rate: 0.00657 +2024-11-22 03:16:34.602763: train_loss -0.7755 +2024-11-22 03:16:34.606913: val_loss -0.764 +2024-11-22 03:16:34.607068: Pseudo dice [0.8488] +2024-11-22 03:16:34.607158: Epoch time: 20.22 s +2024-11-22 03:16:35.951252: +2024-11-22 03:16:35.951455: Epoch 2982 +2024-11-22 03:16:35.951583: Current learning rate: 0.00657 +2024-11-22 03:16:53.294083: train_loss -0.7722 +2024-11-22 03:16:53.302609: val_loss -0.742 +2024-11-22 03:16:53.302754: Pseudo dice [0.8368] +2024-11-22 03:16:53.302856: Epoch time: 17.34 s +2024-11-22 03:16:54.180823: +2024-11-22 03:16:54.181056: Epoch 2983 +2024-11-22 03:16:54.181195: Current learning rate: 0.00657 +2024-11-22 03:17:14.030751: train_loss -0.7784 +2024-11-22 03:17:14.044798: val_loss -0.7832 +2024-11-22 03:17:14.044927: Pseudo dice [0.8387] +2024-11-22 03:17:14.045032: Epoch time: 19.85 s +2024-11-22 03:17:14.903367: +2024-11-22 03:17:14.903585: Epoch 2984 +2024-11-22 03:17:14.903716: Current learning rate: 0.00657 +2024-11-22 03:17:33.671091: train_loss -0.7771 +2024-11-22 03:17:33.678683: val_loss -0.7689 +2024-11-22 03:17:33.678794: Pseudo dice [0.8463] +2024-11-22 03:17:33.678883: Epoch time: 18.77 s +2024-11-22 03:17:34.688999: +2024-11-22 03:17:34.689229: Epoch 2985 +2024-11-22 03:17:34.689360: Current learning rate: 0.00657 +2024-11-22 03:17:53.099410: train_loss -0.7724 +2024-11-22 03:17:53.103785: val_loss -0.7355 +2024-11-22 03:17:53.103900: Pseudo dice [0.8487] +2024-11-22 03:17:53.103995: Epoch time: 18.41 s +2024-11-22 03:17:54.188259: +2024-11-22 03:17:54.188493: Epoch 2986 +2024-11-22 03:17:54.188602: Current learning rate: 0.00657 +2024-11-22 03:18:12.717524: train_loss -0.7794 +2024-11-22 03:18:12.724731: val_loss -0.765 +2024-11-22 03:18:12.724851: Pseudo dice [0.8354] +2024-11-22 03:18:12.724947: Epoch time: 18.53 s +2024-11-22 03:18:13.684592: +2024-11-22 03:18:13.684798: Epoch 2987 +2024-11-22 03:18:13.684932: Current learning rate: 0.00657 +2024-11-22 03:18:32.836099: train_loss -0.7886 +2024-11-22 03:18:32.837897: val_loss -0.7745 +2024-11-22 03:18:32.838024: Pseudo dice [0.8544] +2024-11-22 03:18:32.838130: Epoch time: 19.15 s +2024-11-22 03:18:33.681750: +2024-11-22 03:18:33.681977: Epoch 2988 +2024-11-22 03:18:33.682100: Current learning rate: 0.00656 +2024-11-22 03:18:53.099365: train_loss -0.7584 +2024-11-22 03:18:53.102751: val_loss -0.7468 +2024-11-22 03:18:53.102918: Pseudo dice [0.837] +2024-11-22 03:18:53.103007: Epoch time: 19.42 s +2024-11-22 03:18:53.945332: +2024-11-22 03:18:53.945542: Epoch 2989 +2024-11-22 03:18:53.945661: Current learning rate: 0.00656 +2024-11-22 03:19:13.976718: train_loss -0.7814 +2024-11-22 03:19:13.983843: val_loss -0.7616 +2024-11-22 03:19:13.983974: Pseudo dice [0.8521] +2024-11-22 03:19:13.984082: Epoch time: 20.03 s +2024-11-22 03:19:14.863317: +2024-11-22 03:19:14.863550: Epoch 2990 +2024-11-22 03:19:14.863677: Current learning rate: 0.00656 +2024-11-22 03:19:34.269912: train_loss -0.7751 +2024-11-22 03:19:34.276991: val_loss -0.7441 +2024-11-22 03:19:34.277153: Pseudo dice [0.8438] +2024-11-22 03:19:34.277264: Epoch time: 19.41 s +2024-11-22 03:19:35.262586: +2024-11-22 03:19:35.262779: Epoch 2991 +2024-11-22 03:19:35.262906: Current learning rate: 0.00656 +2024-11-22 03:19:54.357985: train_loss -0.7792 +2024-11-22 03:19:54.365075: val_loss -0.7686 +2024-11-22 03:19:54.365211: Pseudo dice [0.8367] +2024-11-22 03:19:54.365316: Epoch time: 19.1 s +2024-11-22 03:19:55.266484: +2024-11-22 03:19:55.266727: Epoch 2992 +2024-11-22 03:19:55.266852: Current learning rate: 0.00656 +2024-11-22 03:20:15.250504: train_loss -0.7733 +2024-11-22 03:20:15.255735: val_loss -0.7609 +2024-11-22 03:20:15.255860: Pseudo dice [0.8455] +2024-11-22 03:20:15.256021: Epoch time: 19.98 s +2024-11-22 03:20:16.524044: +2024-11-22 03:20:16.524294: Epoch 2993 +2024-11-22 03:20:16.524423: Current learning rate: 0.00656 +2024-11-22 03:20:35.543085: train_loss -0.7741 +2024-11-22 03:20:35.549334: val_loss -0.7345 +2024-11-22 03:20:35.549672: Pseudo dice [0.8376] +2024-11-22 03:20:35.549790: Epoch time: 19.02 s +2024-11-22 03:20:36.449672: +2024-11-22 03:20:36.449897: Epoch 2994 +2024-11-22 03:20:36.450023: Current learning rate: 0.00656 +2024-11-22 03:20:55.755496: train_loss -0.7828 +2024-11-22 03:20:55.757095: val_loss -0.7663 +2024-11-22 03:20:55.757222: Pseudo dice [0.8486] +2024-11-22 03:20:55.757318: Epoch time: 19.31 s +2024-11-22 03:20:56.602571: +2024-11-22 03:20:56.602782: Epoch 2995 +2024-11-22 03:20:56.602910: Current learning rate: 0.00656 +2024-11-22 03:21:15.642097: train_loss -0.7743 +2024-11-22 03:21:15.649577: val_loss -0.7619 +2024-11-22 03:21:15.649709: Pseudo dice [0.8528] +2024-11-22 03:21:15.649817: Epoch time: 19.04 s +2024-11-22 03:21:16.573863: +2024-11-22 03:21:16.574117: Epoch 2996 +2024-11-22 03:21:16.574237: Current learning rate: 0.00656 +2024-11-22 03:21:35.660453: train_loss -0.7835 +2024-11-22 03:21:35.663298: val_loss -0.7454 +2024-11-22 03:21:35.663429: Pseudo dice [0.8498] +2024-11-22 03:21:35.663510: Epoch time: 19.09 s +2024-11-22 03:21:36.613239: +2024-11-22 03:21:36.613437: Epoch 2997 +2024-11-22 03:21:36.613577: Current learning rate: 0.00655 +2024-11-22 03:21:55.325557: train_loss -0.7811 +2024-11-22 03:21:55.331329: val_loss -0.7825 +2024-11-22 03:21:55.331458: Pseudo dice [0.8573] +2024-11-22 03:21:55.331568: Epoch time: 18.71 s +2024-11-22 03:21:56.191048: +2024-11-22 03:21:56.191262: Epoch 2998 +2024-11-22 03:21:56.191386: Current learning rate: 0.00655 +2024-11-22 03:22:14.297154: train_loss -0.7821 +2024-11-22 03:22:14.304897: val_loss -0.7657 +2024-11-22 03:22:14.305042: Pseudo dice [0.8433] +2024-11-22 03:22:14.305148: Epoch time: 18.11 s +2024-11-22 03:22:15.202874: +2024-11-22 03:22:15.203099: Epoch 2999 +2024-11-22 03:22:15.203219: Current learning rate: 0.00655 +2024-11-22 03:22:33.054153: train_loss -0.7893 +2024-11-22 03:22:33.059464: val_loss -0.7686 +2024-11-22 03:22:33.059589: Pseudo dice [0.8577] +2024-11-22 03:22:33.059672: Epoch time: 17.85 s +2024-11-22 03:22:34.146890: +2024-11-22 03:22:34.147131: Epoch 3000 +2024-11-22 03:22:34.147259: Current learning rate: 0.00655 +2024-11-22 03:22:52.563680: train_loss -0.7816 +2024-11-22 03:22:52.570686: val_loss -0.7472 +2024-11-22 03:22:52.570821: Pseudo dice [0.8506] +2024-11-22 03:22:52.570920: Epoch time: 18.42 s +2024-11-22 03:22:53.444660: +2024-11-22 03:22:53.444861: Epoch 3001 +2024-11-22 03:22:53.444991: Current learning rate: 0.00655 +2024-11-22 03:23:12.358394: train_loss -0.7862 +2024-11-22 03:23:12.363761: val_loss -0.7538 +2024-11-22 03:23:12.363903: Pseudo dice [0.839] +2024-11-22 03:23:12.363998: Epoch time: 18.91 s +2024-11-22 03:23:13.305612: +2024-11-22 03:23:13.305821: Epoch 3002 +2024-11-22 03:23:13.305959: Current learning rate: 0.00655 +2024-11-22 03:23:32.564353: train_loss -0.7694 +2024-11-22 03:23:32.576396: val_loss -0.7574 +2024-11-22 03:23:32.576527: Pseudo dice [0.8448] +2024-11-22 03:23:32.576615: Epoch time: 19.26 s +2024-11-22 03:23:33.424530: +2024-11-22 03:23:33.424727: Epoch 3003 +2024-11-22 03:23:33.424845: Current learning rate: 0.00655 +2024-11-22 03:23:52.880268: train_loss -0.7682 +2024-11-22 03:23:52.883769: val_loss -0.7725 +2024-11-22 03:23:52.883882: Pseudo dice [0.8676] +2024-11-22 03:23:52.883965: Epoch time: 19.46 s +2024-11-22 03:23:54.138137: +2024-11-22 03:23:54.138347: Epoch 3004 +2024-11-22 03:23:54.138465: Current learning rate: 0.00655 +2024-11-22 03:24:13.902580: train_loss -0.7759 +2024-11-22 03:24:13.905674: val_loss -0.7722 +2024-11-22 03:24:13.905785: Pseudo dice [0.8584] +2024-11-22 03:24:13.905881: Epoch time: 19.77 s +2024-11-22 03:24:14.788638: +2024-11-22 03:24:14.788845: Epoch 3005 +2024-11-22 03:24:14.788965: Current learning rate: 0.00654 +2024-11-22 03:24:34.999507: train_loss -0.7766 +2024-11-22 03:24:35.006892: val_loss -0.7602 +2024-11-22 03:24:35.007008: Pseudo dice [0.8523] +2024-11-22 03:24:35.007107: Epoch time: 20.21 s +2024-11-22 03:24:35.932827: +2024-11-22 03:24:35.933091: Epoch 3006 +2024-11-22 03:24:35.933220: Current learning rate: 0.00654 +2024-11-22 03:24:54.173079: train_loss -0.7762 +2024-11-22 03:24:54.174620: val_loss -0.7668 +2024-11-22 03:24:54.174763: Pseudo dice [0.8498] +2024-11-22 03:24:54.174848: Epoch time: 18.24 s +2024-11-22 03:24:55.159051: +2024-11-22 03:24:55.159261: Epoch 3007 +2024-11-22 03:24:55.159389: Current learning rate: 0.00654 +2024-11-22 03:25:14.940098: train_loss -0.7827 +2024-11-22 03:25:14.941790: val_loss -0.7759 +2024-11-22 03:25:14.941897: Pseudo dice [0.8538] +2024-11-22 03:25:14.942000: Epoch time: 19.78 s +2024-11-22 03:25:15.789628: +2024-11-22 03:25:15.789861: Epoch 3008 +2024-11-22 03:25:15.790012: Current learning rate: 0.00654 +2024-11-22 03:25:34.793258: train_loss -0.7781 +2024-11-22 03:25:34.794961: val_loss -0.7576 +2024-11-22 03:25:34.795111: Pseudo dice [0.8529] +2024-11-22 03:25:34.795207: Epoch time: 19.0 s +2024-11-22 03:25:35.750252: +2024-11-22 03:25:35.750458: Epoch 3009 +2024-11-22 03:25:35.750570: Current learning rate: 0.00654 +2024-11-22 03:25:54.772418: train_loss -0.7815 +2024-11-22 03:25:54.783433: val_loss -0.7783 +2024-11-22 03:25:54.783623: Pseudo dice [0.8571] +2024-11-22 03:25:54.783729: Epoch time: 19.02 s +2024-11-22 03:25:55.738175: +2024-11-22 03:25:55.738399: Epoch 3010 +2024-11-22 03:25:55.738517: Current learning rate: 0.00654 +2024-11-22 03:26:14.653208: train_loss -0.7908 +2024-11-22 03:26:14.656696: val_loss -0.7833 +2024-11-22 03:26:14.656815: Pseudo dice [0.8578] +2024-11-22 03:26:14.656909: Epoch time: 18.92 s +2024-11-22 03:26:15.643054: +2024-11-22 03:26:15.643269: Epoch 3011 +2024-11-22 03:26:15.643389: Current learning rate: 0.00654 +2024-11-22 03:26:35.347991: train_loss -0.7781 +2024-11-22 03:26:35.356551: val_loss -0.7773 +2024-11-22 03:26:35.356697: Pseudo dice [0.8538] +2024-11-22 03:26:35.356817: Epoch time: 19.71 s +2024-11-22 03:26:36.205006: +2024-11-22 03:26:36.205214: Epoch 3012 +2024-11-22 03:26:36.205342: Current learning rate: 0.00654 +2024-11-22 03:26:54.865177: train_loss -0.7785 +2024-11-22 03:26:54.871132: val_loss -0.7668 +2024-11-22 03:26:54.871269: Pseudo dice [0.8397] +2024-11-22 03:26:54.871357: Epoch time: 18.66 s +2024-11-22 03:26:55.739657: +2024-11-22 03:26:55.739865: Epoch 3013 +2024-11-22 03:26:55.739981: Current learning rate: 0.00654 +2024-11-22 03:27:14.282809: train_loss -0.7753 +2024-11-22 03:27:14.288409: val_loss -0.7335 +2024-11-22 03:27:14.288547: Pseudo dice [0.8424] +2024-11-22 03:27:14.288630: Epoch time: 18.54 s +2024-11-22 03:27:15.293440: +2024-11-22 03:27:15.293640: Epoch 3014 +2024-11-22 03:27:15.293753: Current learning rate: 0.00653 +2024-11-22 03:27:33.676476: train_loss -0.7855 +2024-11-22 03:27:33.678502: val_loss -0.7647 +2024-11-22 03:27:33.678639: Pseudo dice [0.8434] +2024-11-22 03:27:33.678726: Epoch time: 18.38 s +2024-11-22 03:27:34.942024: +2024-11-22 03:27:34.942269: Epoch 3015 +2024-11-22 03:27:34.942379: Current learning rate: 0.00653 +2024-11-22 03:27:54.695879: train_loss -0.7894 +2024-11-22 03:27:54.698202: val_loss -0.7545 +2024-11-22 03:27:54.698344: Pseudo dice [0.8529] +2024-11-22 03:27:54.698439: Epoch time: 19.75 s +2024-11-22 03:27:55.624555: +2024-11-22 03:27:55.624757: Epoch 3016 +2024-11-22 03:27:55.624870: Current learning rate: 0.00653 +2024-11-22 03:28:13.848457: train_loss -0.7829 +2024-11-22 03:28:13.849900: val_loss -0.7792 +2024-11-22 03:28:13.849988: Pseudo dice [0.856] +2024-11-22 03:28:13.850070: Epoch time: 18.22 s +2024-11-22 03:28:14.689979: +2024-11-22 03:28:14.690228: Epoch 3017 +2024-11-22 03:28:14.690343: Current learning rate: 0.00653 +2024-11-22 03:28:33.688830: train_loss -0.7801 +2024-11-22 03:28:33.694166: val_loss -0.774 +2024-11-22 03:28:33.694297: Pseudo dice [0.8445] +2024-11-22 03:28:33.694381: Epoch time: 19.0 s +2024-11-22 03:28:34.553977: +2024-11-22 03:28:34.554220: Epoch 3018 +2024-11-22 03:28:34.554339: Current learning rate: 0.00653 +2024-11-22 03:28:54.030627: train_loss -0.791 +2024-11-22 03:28:54.032049: val_loss -0.7671 +2024-11-22 03:28:54.032155: Pseudo dice [0.8518] +2024-11-22 03:28:54.032240: Epoch time: 19.48 s +2024-11-22 03:28:54.897213: +2024-11-22 03:28:54.897477: Epoch 3019 +2024-11-22 03:28:54.897592: Current learning rate: 0.00653 +2024-11-22 03:29:13.614622: train_loss -0.7814 +2024-11-22 03:29:13.636908: val_loss -0.77 +2024-11-22 03:29:13.637051: Pseudo dice [0.8624] +2024-11-22 03:29:13.637182: Epoch time: 18.72 s +2024-11-22 03:29:14.557815: +2024-11-22 03:29:14.558015: Epoch 3020 +2024-11-22 03:29:14.558137: Current learning rate: 0.00653 +2024-11-22 03:29:34.258403: train_loss -0.7847 +2024-11-22 03:29:34.265859: val_loss -0.7558 +2024-11-22 03:29:34.265993: Pseudo dice [0.8419] +2024-11-22 03:29:34.266080: Epoch time: 19.7 s +2024-11-22 03:29:35.137290: +2024-11-22 03:29:35.137512: Epoch 3021 +2024-11-22 03:29:35.137628: Current learning rate: 0.00653 +2024-11-22 03:29:54.140401: train_loss -0.7851 +2024-11-22 03:29:54.142210: val_loss -0.754 +2024-11-22 03:29:54.142299: Pseudo dice [0.8491] +2024-11-22 03:29:54.142377: Epoch time: 19.0 s +2024-11-22 03:29:54.981526: +2024-11-22 03:29:54.981730: Epoch 3022 +2024-11-22 03:29:54.981848: Current learning rate: 0.00652 +2024-11-22 03:30:14.399180: train_loss -0.787 +2024-11-22 03:30:14.404614: val_loss -0.7711 +2024-11-22 03:30:14.404740: Pseudo dice [0.8434] +2024-11-22 03:30:14.404820: Epoch time: 19.42 s +2024-11-22 03:30:15.358836: +2024-11-22 03:30:15.359049: Epoch 3023 +2024-11-22 03:30:15.359164: Current learning rate: 0.00652 +2024-11-22 03:30:33.627762: train_loss -0.7702 +2024-11-22 03:30:33.629493: val_loss -0.7557 +2024-11-22 03:30:33.629607: Pseudo dice [0.8505] +2024-11-22 03:30:33.629697: Epoch time: 18.27 s +2024-11-22 03:30:34.481729: +2024-11-22 03:30:34.481934: Epoch 3024 +2024-11-22 03:30:34.482050: Current learning rate: 0.00652 +2024-11-22 03:30:54.085726: train_loss -0.7803 +2024-11-22 03:30:54.088336: val_loss -0.7454 +2024-11-22 03:30:54.088458: Pseudo dice [0.8452] +2024-11-22 03:30:54.088569: Epoch time: 19.6 s +2024-11-22 03:30:55.037168: +2024-11-22 03:30:55.037405: Epoch 3025 +2024-11-22 03:30:55.037514: Current learning rate: 0.00652 +2024-11-22 03:31:13.772458: train_loss -0.785 +2024-11-22 03:31:13.776943: val_loss -0.7798 +2024-11-22 03:31:13.777073: Pseudo dice [0.8528] +2024-11-22 03:31:13.777165: Epoch time: 18.74 s +2024-11-22 03:31:15.020929: +2024-11-22 03:31:15.021152: Epoch 3026 +2024-11-22 03:31:15.021271: Current learning rate: 0.00652 +2024-11-22 03:31:34.030043: train_loss -0.7786 +2024-11-22 03:31:34.037205: val_loss -0.7543 +2024-11-22 03:31:34.037315: Pseudo dice [0.8427] +2024-11-22 03:31:34.037405: Epoch time: 19.01 s +2024-11-22 03:31:34.949077: +2024-11-22 03:31:34.949296: Epoch 3027 +2024-11-22 03:31:34.949409: Current learning rate: 0.00652 +2024-11-22 03:31:55.426680: train_loss -0.7783 +2024-11-22 03:31:55.428833: val_loss -0.7671 +2024-11-22 03:31:55.428933: Pseudo dice [0.8391] +2024-11-22 03:31:55.429019: Epoch time: 20.48 s +2024-11-22 03:31:56.265805: +2024-11-22 03:31:56.266026: Epoch 3028 +2024-11-22 03:31:56.266149: Current learning rate: 0.00652 +2024-11-22 03:32:14.643931: train_loss -0.7785 +2024-11-22 03:32:14.647873: val_loss -0.7962 +2024-11-22 03:32:14.647979: Pseudo dice [0.8527] +2024-11-22 03:32:14.648065: Epoch time: 18.38 s +2024-11-22 03:32:15.498906: +2024-11-22 03:32:15.499135: Epoch 3029 +2024-11-22 03:32:15.499253: Current learning rate: 0.00652 +2024-11-22 03:32:34.706096: train_loss -0.7839 +2024-11-22 03:32:34.711887: val_loss -0.7685 +2024-11-22 03:32:34.712012: Pseudo dice [0.8494] +2024-11-22 03:32:34.712097: Epoch time: 19.21 s +2024-11-22 03:32:35.563728: +2024-11-22 03:32:35.563942: Epoch 3030 +2024-11-22 03:32:35.564055: Current learning rate: 0.00652 +2024-11-22 03:32:54.835964: train_loss -0.7809 +2024-11-22 03:32:54.840494: val_loss -0.7637 +2024-11-22 03:32:54.840612: Pseudo dice [0.8601] +2024-11-22 03:32:54.840702: Epoch time: 19.27 s +2024-11-22 03:32:55.865338: +2024-11-22 03:32:55.865546: Epoch 3031 +2024-11-22 03:32:55.865658: Current learning rate: 0.00651 +2024-11-22 03:33:14.482105: train_loss -0.7746 +2024-11-22 03:33:14.489450: val_loss -0.7808 +2024-11-22 03:33:14.489578: Pseudo dice [0.8564] +2024-11-22 03:33:14.506362: Epoch time: 18.62 s +2024-11-22 03:33:15.391417: +2024-11-22 03:33:15.391621: Epoch 3032 +2024-11-22 03:33:15.391734: Current learning rate: 0.00651 +2024-11-22 03:33:34.416430: train_loss -0.7745 +2024-11-22 03:33:34.417996: val_loss -0.7636 +2024-11-22 03:33:34.418197: Pseudo dice [0.8579] +2024-11-22 03:33:34.418280: Epoch time: 19.03 s +2024-11-22 03:33:35.302170: +2024-11-22 03:33:35.302371: Epoch 3033 +2024-11-22 03:33:35.302483: Current learning rate: 0.00651 +2024-11-22 03:33:54.817828: train_loss -0.7864 +2024-11-22 03:33:54.824750: val_loss -0.7726 +2024-11-22 03:33:54.824876: Pseudo dice [0.8545] +2024-11-22 03:33:54.824955: Epoch time: 19.52 s +2024-11-22 03:33:55.708808: +2024-11-22 03:33:55.709008: Epoch 3034 +2024-11-22 03:33:55.709127: Current learning rate: 0.00651 +2024-11-22 03:34:13.511097: train_loss -0.7809 +2024-11-22 03:34:13.521353: val_loss -0.7568 +2024-11-22 03:34:13.521493: Pseudo dice [0.8433] +2024-11-22 03:34:13.521589: Epoch time: 17.8 s +2024-11-22 03:34:14.394500: +2024-11-22 03:34:14.394705: Epoch 3035 +2024-11-22 03:34:14.394817: Current learning rate: 0.00651 +2024-11-22 03:34:33.212893: train_loss -0.7841 +2024-11-22 03:34:33.220117: val_loss -0.7208 +2024-11-22 03:34:33.220236: Pseudo dice [0.8472] +2024-11-22 03:34:33.220320: Epoch time: 18.82 s +2024-11-22 03:34:34.168549: +2024-11-22 03:34:34.168764: Epoch 3036 +2024-11-22 03:34:34.168878: Current learning rate: 0.00651 +2024-11-22 03:34:53.543915: train_loss -0.7832 +2024-11-22 03:34:53.547935: val_loss -0.7767 +2024-11-22 03:34:53.548064: Pseudo dice [0.8634] +2024-11-22 03:34:53.548149: Epoch time: 19.38 s +2024-11-22 03:34:54.898871: +2024-11-22 03:34:54.899073: Epoch 3037 +2024-11-22 03:34:54.899191: Current learning rate: 0.00651 +2024-11-22 03:35:13.614946: train_loss -0.7651 +2024-11-22 03:35:13.618271: val_loss -0.7556 +2024-11-22 03:35:13.618385: Pseudo dice [0.8192] +2024-11-22 03:35:13.618477: Epoch time: 18.71 s +2024-11-22 03:35:14.623691: +2024-11-22 03:35:14.623901: Epoch 3038 +2024-11-22 03:35:14.624015: Current learning rate: 0.00651 +2024-11-22 03:35:34.545030: train_loss -0.7744 +2024-11-22 03:35:34.551401: val_loss -0.7614 +2024-11-22 03:35:34.551542: Pseudo dice [0.8424] +2024-11-22 03:35:34.551626: Epoch time: 19.92 s +2024-11-22 03:35:35.464507: +2024-11-22 03:35:35.464712: Epoch 3039 +2024-11-22 03:35:35.464822: Current learning rate: 0.0065 +2024-11-22 03:35:54.631130: train_loss -0.7643 +2024-11-22 03:35:54.638610: val_loss -0.7814 +2024-11-22 03:35:54.638754: Pseudo dice [0.8648] +2024-11-22 03:35:54.638835: Epoch time: 19.17 s +2024-11-22 03:35:55.497331: +2024-11-22 03:35:55.497539: Epoch 3040 +2024-11-22 03:35:55.497648: Current learning rate: 0.0065 +2024-11-22 03:36:14.322561: train_loss -0.7802 +2024-11-22 03:36:14.328877: val_loss -0.7719 +2024-11-22 03:36:14.328990: Pseudo dice [0.8603] +2024-11-22 03:36:14.329080: Epoch time: 18.83 s +2024-11-22 03:36:15.186571: +2024-11-22 03:36:15.186777: Epoch 3041 +2024-11-22 03:36:15.186898: Current learning rate: 0.0065 +2024-11-22 03:36:34.969714: train_loss -0.7787 +2024-11-22 03:36:34.977334: val_loss -0.7509 +2024-11-22 03:36:34.977445: Pseudo dice [0.8529] +2024-11-22 03:36:34.977528: Epoch time: 19.78 s +2024-11-22 03:36:35.989213: +2024-11-22 03:36:35.989444: Epoch 3042 +2024-11-22 03:36:35.989558: Current learning rate: 0.0065 +2024-11-22 03:36:55.149439: train_loss -0.7686 +2024-11-22 03:36:55.155187: val_loss -0.7526 +2024-11-22 03:36:55.155313: Pseudo dice [0.8462] +2024-11-22 03:36:55.155397: Epoch time: 19.16 s +2024-11-22 03:36:56.123311: +2024-11-22 03:36:56.123506: Epoch 3043 +2024-11-22 03:36:56.123620: Current learning rate: 0.0065 +2024-11-22 03:37:15.869636: train_loss -0.7691 +2024-11-22 03:37:15.876843: val_loss -0.7662 +2024-11-22 03:37:15.876976: Pseudo dice [0.8497] +2024-11-22 03:37:15.877064: Epoch time: 19.75 s +2024-11-22 03:37:16.845477: +2024-11-22 03:37:16.845709: Epoch 3044 +2024-11-22 03:37:16.845835: Current learning rate: 0.0065 +2024-11-22 03:37:35.825659: train_loss -0.7834 +2024-11-22 03:37:35.833124: val_loss -0.7771 +2024-11-22 03:37:35.833253: Pseudo dice [0.8582] +2024-11-22 03:37:35.833350: Epoch time: 18.98 s +2024-11-22 03:37:36.822843: +2024-11-22 03:37:36.823084: Epoch 3045 +2024-11-22 03:37:36.823200: Current learning rate: 0.0065 +2024-11-22 03:37:55.508574: train_loss -0.7779 +2024-11-22 03:37:55.511662: val_loss -0.772 +2024-11-22 03:37:55.511784: Pseudo dice [0.8569] +2024-11-22 03:37:55.511863: Epoch time: 18.69 s +2024-11-22 03:37:56.393379: +2024-11-22 03:37:56.393591: Epoch 3046 +2024-11-22 03:37:56.393712: Current learning rate: 0.0065 +2024-11-22 03:38:15.507946: train_loss -0.7795 +2024-11-22 03:38:15.527872: val_loss -0.7866 +2024-11-22 03:38:15.527993: Pseudo dice [0.8602] +2024-11-22 03:38:15.528082: Epoch time: 19.12 s +2024-11-22 03:38:16.379900: +2024-11-22 03:38:16.380117: Epoch 3047 +2024-11-22 03:38:16.380234: Current learning rate: 0.0065 +2024-11-22 03:38:35.744269: train_loss -0.7792 +2024-11-22 03:38:35.757233: val_loss -0.7603 +2024-11-22 03:38:35.757403: Pseudo dice [0.8482] +2024-11-22 03:38:35.757500: Epoch time: 19.37 s +2024-11-22 03:38:37.230368: +2024-11-22 03:38:37.230580: Epoch 3048 +2024-11-22 03:38:37.230696: Current learning rate: 0.00649 +2024-11-22 03:38:55.199204: train_loss -0.7487 +2024-11-22 03:38:55.201924: val_loss -0.7458 +2024-11-22 03:38:55.202024: Pseudo dice [0.847] +2024-11-22 03:38:55.202112: Epoch time: 17.97 s +2024-11-22 03:38:56.046095: +2024-11-22 03:38:56.046300: Epoch 3049 +2024-11-22 03:38:56.046413: Current learning rate: 0.00649 +2024-11-22 03:39:14.264159: train_loss -0.7672 +2024-11-22 03:39:14.269536: val_loss -0.7756 +2024-11-22 03:39:14.269661: Pseudo dice [0.8465] +2024-11-22 03:39:14.269742: Epoch time: 18.22 s +2024-11-22 03:39:15.347264: +2024-11-22 03:39:15.347483: Epoch 3050 +2024-11-22 03:39:15.347592: Current learning rate: 0.00649 +2024-11-22 03:39:35.119380: train_loss -0.7658 +2024-11-22 03:39:35.127292: val_loss -0.7503 +2024-11-22 03:39:35.127421: Pseudo dice [0.8285] +2024-11-22 03:39:35.127500: Epoch time: 19.77 s +2024-11-22 03:39:36.006587: +2024-11-22 03:39:36.006787: Epoch 3051 +2024-11-22 03:39:36.006898: Current learning rate: 0.00649 +2024-11-22 03:39:54.488123: train_loss -0.769 +2024-11-22 03:39:54.492081: val_loss -0.7672 +2024-11-22 03:39:54.492190: Pseudo dice [0.8552] +2024-11-22 03:39:54.492274: Epoch time: 18.48 s +2024-11-22 03:39:55.359911: +2024-11-22 03:39:55.360126: Epoch 3052 +2024-11-22 03:39:55.360241: Current learning rate: 0.00649 +2024-11-22 03:40:14.701486: train_loss -0.7698 +2024-11-22 03:40:14.703140: val_loss -0.7646 +2024-11-22 03:40:14.703231: Pseudo dice [0.8421] +2024-11-22 03:40:14.703316: Epoch time: 19.34 s +2024-11-22 03:40:15.544613: +2024-11-22 03:40:15.544822: Epoch 3053 +2024-11-22 03:40:15.544949: Current learning rate: 0.00649 +2024-11-22 03:40:35.169548: train_loss -0.7464 +2024-11-22 03:40:35.175312: val_loss -0.7585 +2024-11-22 03:40:35.175436: Pseudo dice [0.8355] +2024-11-22 03:40:35.175519: Epoch time: 19.63 s +2024-11-22 03:40:36.053977: +2024-11-22 03:40:36.054180: Epoch 3054 +2024-11-22 03:40:36.054289: Current learning rate: 0.00649 +2024-11-22 03:40:54.785148: train_loss -0.7486 +2024-11-22 03:40:54.792012: val_loss -0.7488 +2024-11-22 03:40:54.792153: Pseudo dice [0.8467] +2024-11-22 03:40:54.792233: Epoch time: 18.73 s +2024-11-22 03:40:55.631833: +2024-11-22 03:40:55.632033: Epoch 3055 +2024-11-22 03:40:55.632152: Current learning rate: 0.00649 +2024-11-22 03:41:14.196375: train_loss -0.7713 +2024-11-22 03:41:14.204084: val_loss -0.7748 +2024-11-22 03:41:14.204214: Pseudo dice [0.8595] +2024-11-22 03:41:14.204319: Epoch time: 18.57 s +2024-11-22 03:41:15.176877: +2024-11-22 03:41:15.177090: Epoch 3056 +2024-11-22 03:41:15.177202: Current learning rate: 0.00648 +2024-11-22 03:41:34.500932: train_loss -0.7795 +2024-11-22 03:41:34.511362: val_loss -0.7584 +2024-11-22 03:41:34.511487: Pseudo dice [0.8606] +2024-11-22 03:41:34.511571: Epoch time: 19.32 s +2024-11-22 03:41:35.352593: +2024-11-22 03:41:35.352789: Epoch 3057 +2024-11-22 03:41:35.353208: Current learning rate: 0.00648 +2024-11-22 03:41:53.856278: train_loss -0.7877 +2024-11-22 03:41:53.862296: val_loss -0.7958 +2024-11-22 03:41:53.862412: Pseudo dice [0.8648] +2024-11-22 03:41:53.862495: Epoch time: 18.5 s +2024-11-22 03:41:54.884199: +2024-11-22 03:41:54.884416: Epoch 3058 +2024-11-22 03:41:54.884529: Current learning rate: 0.00648 +2024-11-22 03:42:13.809203: train_loss -0.7922 +2024-11-22 03:42:13.812084: val_loss -0.7799 +2024-11-22 03:42:13.812205: Pseudo dice [0.8556] +2024-11-22 03:42:13.812283: Epoch time: 18.93 s +2024-11-22 03:42:15.041308: +2024-11-22 03:42:15.041532: Epoch 3059 +2024-11-22 03:42:15.041648: Current learning rate: 0.00648 +2024-11-22 03:42:33.641644: train_loss -0.7734 +2024-11-22 03:42:33.644941: val_loss -0.7765 +2024-11-22 03:42:33.645032: Pseudo dice [0.8541] +2024-11-22 03:42:33.645118: Epoch time: 18.6 s +2024-11-22 03:42:34.486965: +2024-11-22 03:42:34.487180: Epoch 3060 +2024-11-22 03:42:34.487292: Current learning rate: 0.00648 +2024-11-22 03:42:54.147795: train_loss -0.7743 +2024-11-22 03:42:54.152251: val_loss -0.7786 +2024-11-22 03:42:54.152371: Pseudo dice [0.8573] +2024-11-22 03:42:54.152493: Epoch time: 19.66 s +2024-11-22 03:42:55.047722: +2024-11-22 03:42:55.047931: Epoch 3061 +2024-11-22 03:42:55.048044: Current learning rate: 0.00648 +2024-11-22 03:43:14.591115: train_loss -0.775 +2024-11-22 03:43:14.593345: val_loss -0.7457 +2024-11-22 03:43:14.593471: Pseudo dice [0.8411] +2024-11-22 03:43:14.593555: Epoch time: 19.54 s +2024-11-22 03:43:15.457582: +2024-11-22 03:43:15.457804: Epoch 3062 +2024-11-22 03:43:15.457917: Current learning rate: 0.00648 +2024-11-22 03:43:33.919441: train_loss -0.7678 +2024-11-22 03:43:33.931588: val_loss -0.7482 +2024-11-22 03:43:33.931710: Pseudo dice [0.849] +2024-11-22 03:43:33.931795: Epoch time: 18.46 s +2024-11-22 03:43:34.934879: +2024-11-22 03:43:34.935101: Epoch 3063 +2024-11-22 03:43:34.935217: Current learning rate: 0.00648 +2024-11-22 03:43:54.653107: train_loss -0.7764 +2024-11-22 03:43:54.660401: val_loss -0.7687 +2024-11-22 03:43:54.660529: Pseudo dice [0.8602] +2024-11-22 03:43:54.660625: Epoch time: 19.72 s +2024-11-22 03:43:55.578900: +2024-11-22 03:43:55.579143: Epoch 3064 +2024-11-22 03:43:55.579253: Current learning rate: 0.00648 +2024-11-22 03:44:13.934685: train_loss -0.7593 +2024-11-22 03:44:13.940925: val_loss -0.7242 +2024-11-22 03:44:13.941074: Pseudo dice [0.8335] +2024-11-22 03:44:13.941162: Epoch time: 18.36 s +2024-11-22 03:44:14.786090: +2024-11-22 03:44:14.786304: Epoch 3065 +2024-11-22 03:44:14.786413: Current learning rate: 0.00647 +2024-11-22 03:44:33.474542: train_loss -0.769 +2024-11-22 03:44:33.486115: val_loss -0.744 +2024-11-22 03:44:33.486261: Pseudo dice [0.8201] +2024-11-22 03:44:33.486342: Epoch time: 18.69 s +2024-11-22 03:44:34.344572: +2024-11-22 03:44:34.344774: Epoch 3066 +2024-11-22 03:44:34.345078: Current learning rate: 0.00647 +2024-11-22 03:44:53.474380: train_loss -0.7666 +2024-11-22 03:44:53.481505: val_loss -0.7643 +2024-11-22 03:44:53.481647: Pseudo dice [0.8476] +2024-11-22 03:44:53.481729: Epoch time: 19.13 s +2024-11-22 03:44:54.429464: +2024-11-22 03:44:54.429710: Epoch 3067 +2024-11-22 03:44:54.429820: Current learning rate: 0.00647 +2024-11-22 03:45:13.499119: train_loss -0.7695 +2024-11-22 03:45:13.503696: val_loss -0.7577 +2024-11-22 03:45:13.503812: Pseudo dice [0.8422] +2024-11-22 03:45:13.503925: Epoch time: 19.07 s +2024-11-22 03:45:14.353765: +2024-11-22 03:45:14.353996: Epoch 3068 +2024-11-22 03:45:14.354114: Current learning rate: 0.00647 +2024-11-22 03:45:33.497988: train_loss -0.7673 +2024-11-22 03:45:33.502054: val_loss -0.7687 +2024-11-22 03:45:33.502162: Pseudo dice [0.8469] +2024-11-22 03:45:33.502248: Epoch time: 19.15 s +2024-11-22 03:45:34.347270: +2024-11-22 03:45:34.347472: Epoch 3069 +2024-11-22 03:45:34.347588: Current learning rate: 0.00647 +2024-11-22 03:45:52.839974: train_loss -0.7836 +2024-11-22 03:45:52.842582: val_loss -0.7861 +2024-11-22 03:45:52.842709: Pseudo dice [0.8631] +2024-11-22 03:45:52.842998: Epoch time: 18.49 s +2024-11-22 03:45:54.218312: +2024-11-22 03:45:54.218564: Epoch 3070 +2024-11-22 03:45:54.218678: Current learning rate: 0.00647 +2024-11-22 03:46:13.374763: train_loss -0.7718 +2024-11-22 03:46:13.379617: val_loss -0.7443 +2024-11-22 03:46:13.379759: Pseudo dice [0.8475] +2024-11-22 03:46:13.379858: Epoch time: 19.16 s +2024-11-22 03:46:14.233265: +2024-11-22 03:46:14.233508: Epoch 3071 +2024-11-22 03:46:14.233621: Current learning rate: 0.00647 +2024-11-22 03:46:32.387534: train_loss -0.7766 +2024-11-22 03:46:32.390952: val_loss -0.7644 +2024-11-22 03:46:32.391068: Pseudo dice [0.8556] +2024-11-22 03:46:32.391150: Epoch time: 18.16 s +2024-11-22 03:46:33.386227: +2024-11-22 03:46:33.386456: Epoch 3072 +2024-11-22 03:46:33.386572: Current learning rate: 0.00647 +2024-11-22 03:46:51.625063: train_loss -0.7744 +2024-11-22 03:46:51.627739: val_loss -0.7815 +2024-11-22 03:46:51.627828: Pseudo dice [0.8554] +2024-11-22 03:46:51.627907: Epoch time: 18.24 s +2024-11-22 03:46:52.469038: +2024-11-22 03:46:52.469260: Epoch 3073 +2024-11-22 03:46:52.469379: Current learning rate: 0.00646 +2024-11-22 03:47:11.936515: train_loss -0.7813 +2024-11-22 03:47:11.938756: val_loss -0.7432 +2024-11-22 03:47:11.938866: Pseudo dice [0.8548] +2024-11-22 03:47:11.938979: Epoch time: 19.47 s +2024-11-22 03:47:12.796819: +2024-11-22 03:47:12.797026: Epoch 3074 +2024-11-22 03:47:12.797142: Current learning rate: 0.00646 +2024-11-22 03:47:30.672320: train_loss -0.7883 +2024-11-22 03:47:30.680342: val_loss -0.7749 +2024-11-22 03:47:30.680480: Pseudo dice [0.8512] +2024-11-22 03:47:30.680567: Epoch time: 17.88 s +2024-11-22 03:47:31.634844: +2024-11-22 03:47:31.635118: Epoch 3075 +2024-11-22 03:47:31.635228: Current learning rate: 0.00646 +2024-11-22 03:47:51.439090: train_loss -0.7825 +2024-11-22 03:47:51.448792: val_loss -0.7772 +2024-11-22 03:47:51.448917: Pseudo dice [0.8648] +2024-11-22 03:47:51.448996: Epoch time: 19.81 s +2024-11-22 03:47:52.295036: +2024-11-22 03:47:52.295254: Epoch 3076 +2024-11-22 03:47:52.295380: Current learning rate: 0.00646 +2024-11-22 03:48:12.179653: train_loss -0.7845 +2024-11-22 03:48:12.189540: val_loss -0.7688 +2024-11-22 03:48:12.189647: Pseudo dice [0.8522] +2024-11-22 03:48:12.189728: Epoch time: 19.89 s +2024-11-22 03:48:13.096443: +2024-11-22 03:48:13.096649: Epoch 3077 +2024-11-22 03:48:13.096766: Current learning rate: 0.00646 +2024-11-22 03:48:32.288896: train_loss -0.7808 +2024-11-22 03:48:32.296827: val_loss -0.7733 +2024-11-22 03:48:32.296954: Pseudo dice [0.8417] +2024-11-22 03:48:32.297045: Epoch time: 19.19 s +2024-11-22 03:48:33.164077: +2024-11-22 03:48:33.164268: Epoch 3078 +2024-11-22 03:48:33.164380: Current learning rate: 0.00646 +2024-11-22 03:48:52.326802: train_loss -0.7745 +2024-11-22 03:48:52.334516: val_loss -0.7642 +2024-11-22 03:48:52.334632: Pseudo dice [0.8497] +2024-11-22 03:48:52.334717: Epoch time: 19.16 s +2024-11-22 03:48:53.300900: +2024-11-22 03:48:53.301108: Epoch 3079 +2024-11-22 03:48:53.301220: Current learning rate: 0.00646 +2024-11-22 03:49:12.607033: train_loss -0.7799 +2024-11-22 03:49:12.609357: val_loss -0.7955 +2024-11-22 03:49:12.609488: Pseudo dice [0.8551] +2024-11-22 03:49:12.609564: Epoch time: 19.31 s +2024-11-22 03:49:13.469327: +2024-11-22 03:49:13.469515: Epoch 3080 +2024-11-22 03:49:13.469623: Current learning rate: 0.00646 +2024-11-22 03:49:32.849620: train_loss -0.7782 +2024-11-22 03:49:32.862874: val_loss -0.7701 +2024-11-22 03:49:32.863015: Pseudo dice [0.8552] +2024-11-22 03:49:32.863101: Epoch time: 19.38 s +2024-11-22 03:49:34.445565: +2024-11-22 03:49:34.445787: Epoch 3081 +2024-11-22 03:49:34.445899: Current learning rate: 0.00646 +2024-11-22 03:49:53.017023: train_loss -0.7842 +2024-11-22 03:49:53.022839: val_loss -0.7609 +2024-11-22 03:49:53.022975: Pseudo dice [0.8478] +2024-11-22 03:49:53.023108: Epoch time: 18.57 s +2024-11-22 03:49:53.878375: +2024-11-22 03:49:53.878608: Epoch 3082 +2024-11-22 03:49:53.878717: Current learning rate: 0.00645 +2024-11-22 03:50:13.509868: train_loss -0.7847 +2024-11-22 03:50:13.518416: val_loss -0.7543 +2024-11-22 03:50:13.518542: Pseudo dice [0.8435] +2024-11-22 03:50:13.518622: Epoch time: 19.63 s +2024-11-22 03:50:14.368754: +2024-11-22 03:50:14.368944: Epoch 3083 +2024-11-22 03:50:14.369051: Current learning rate: 0.00645 +2024-11-22 03:50:33.685507: train_loss -0.7776 +2024-11-22 03:50:33.688524: val_loss -0.7652 +2024-11-22 03:50:33.688629: Pseudo dice [0.8574] +2024-11-22 03:50:33.688712: Epoch time: 19.32 s +2024-11-22 03:50:34.534939: +2024-11-22 03:50:34.535178: Epoch 3084 +2024-11-22 03:50:34.535288: Current learning rate: 0.00645 +2024-11-22 03:50:54.119990: train_loss -0.7739 +2024-11-22 03:50:54.125871: val_loss -0.77 +2024-11-22 03:50:54.125996: Pseudo dice [0.8546] +2024-11-22 03:50:54.126090: Epoch time: 19.59 s +2024-11-22 03:50:55.051770: +2024-11-22 03:50:55.051975: Epoch 3085 +2024-11-22 03:50:55.052094: Current learning rate: 0.00645 +2024-11-22 03:51:14.239888: train_loss -0.774 +2024-11-22 03:51:14.242332: val_loss -0.7425 +2024-11-22 03:51:14.242423: Pseudo dice [0.8382] +2024-11-22 03:51:14.242504: Epoch time: 19.19 s +2024-11-22 03:51:15.094012: +2024-11-22 03:51:15.094216: Epoch 3086 +2024-11-22 03:51:15.094338: Current learning rate: 0.00645 +2024-11-22 03:51:33.053369: train_loss -0.7838 +2024-11-22 03:51:33.056350: val_loss -0.7543 +2024-11-22 03:51:33.056444: Pseudo dice [0.8516] +2024-11-22 03:51:33.056521: Epoch time: 17.96 s +2024-11-22 03:51:33.897767: +2024-11-22 03:51:33.898011: Epoch 3087 +2024-11-22 03:51:33.898124: Current learning rate: 0.00645 +2024-11-22 03:51:51.811234: train_loss -0.778 +2024-11-22 03:51:51.815950: val_loss -0.7779 +2024-11-22 03:51:51.816089: Pseudo dice [0.8364] +2024-11-22 03:51:51.816174: Epoch time: 17.91 s +2024-11-22 03:51:52.697024: +2024-11-22 03:51:52.697224: Epoch 3088 +2024-11-22 03:51:52.697342: Current learning rate: 0.00645 +2024-11-22 03:52:11.754323: train_loss -0.7816 +2024-11-22 03:52:11.760981: val_loss -0.754 +2024-11-22 03:52:11.761130: Pseudo dice [0.8447] +2024-11-22 03:52:11.761213: Epoch time: 19.06 s +2024-11-22 03:52:12.624151: +2024-11-22 03:52:12.624347: Epoch 3089 +2024-11-22 03:52:12.624462: Current learning rate: 0.00645 +2024-11-22 03:52:31.200802: train_loss -0.7703 +2024-11-22 03:52:31.207840: val_loss -0.7901 +2024-11-22 03:52:31.207969: Pseudo dice [0.855] +2024-11-22 03:52:31.208083: Epoch time: 18.58 s +2024-11-22 03:52:32.054034: +2024-11-22 03:52:32.054240: Epoch 3090 +2024-11-22 03:52:32.054351: Current learning rate: 0.00644 +2024-11-22 03:52:52.373576: train_loss -0.7744 +2024-11-22 03:52:52.379917: val_loss -0.7799 +2024-11-22 03:52:52.380026: Pseudo dice [0.8558] +2024-11-22 03:52:52.380113: Epoch time: 20.32 s +2024-11-22 03:52:53.271704: +2024-11-22 03:52:53.271904: Epoch 3091 +2024-11-22 03:52:53.272025: Current learning rate: 0.00644 +2024-11-22 03:53:12.577996: train_loss -0.7838 +2024-11-22 03:53:12.581619: val_loss -0.7516 +2024-11-22 03:53:12.581728: Pseudo dice [0.849] +2024-11-22 03:53:12.581812: Epoch time: 19.31 s +2024-11-22 03:53:13.843792: +2024-11-22 03:53:13.844026: Epoch 3092 +2024-11-22 03:53:13.844226: Current learning rate: 0.00644 +2024-11-22 03:53:33.039529: train_loss -0.7835 +2024-11-22 03:53:33.048182: val_loss -0.7606 +2024-11-22 03:53:33.048300: Pseudo dice [0.8392] +2024-11-22 03:53:33.048396: Epoch time: 19.2 s +2024-11-22 03:53:33.913468: +2024-11-22 03:53:33.913683: Epoch 3093 +2024-11-22 03:53:33.913798: Current learning rate: 0.00644 +2024-11-22 03:53:52.175275: train_loss -0.7807 +2024-11-22 03:53:52.178416: val_loss -0.7905 +2024-11-22 03:53:52.178530: Pseudo dice [0.8563] +2024-11-22 03:53:52.178618: Epoch time: 18.26 s +2024-11-22 03:53:53.060948: +2024-11-22 03:53:53.061145: Epoch 3094 +2024-11-22 03:53:53.061257: Current learning rate: 0.00644 +2024-11-22 03:54:11.841598: train_loss -0.7724 +2024-11-22 03:54:11.849948: val_loss -0.7641 +2024-11-22 03:54:11.850096: Pseudo dice [0.8463] +2024-11-22 03:54:11.850184: Epoch time: 18.78 s +2024-11-22 03:54:12.916027: +2024-11-22 03:54:12.916239: Epoch 3095 +2024-11-22 03:54:12.916609: Current learning rate: 0.00644 +2024-11-22 03:54:32.087955: train_loss -0.7762 +2024-11-22 03:54:32.091938: val_loss -0.761 +2024-11-22 03:54:32.092044: Pseudo dice [0.8463] +2024-11-22 03:54:32.092148: Epoch time: 19.17 s +2024-11-22 03:54:32.937599: +2024-11-22 03:54:32.937796: Epoch 3096 +2024-11-22 03:54:32.937909: Current learning rate: 0.00644 +2024-11-22 03:54:52.300146: train_loss -0.7781 +2024-11-22 03:54:52.307679: val_loss -0.7465 +2024-11-22 03:54:52.307799: Pseudo dice [0.8496] +2024-11-22 03:54:52.307887: Epoch time: 19.36 s +2024-11-22 03:54:53.153462: +2024-11-22 03:54:53.153704: Epoch 3097 +2024-11-22 03:54:53.153817: Current learning rate: 0.00644 +2024-11-22 03:55:11.841049: train_loss -0.7873 +2024-11-22 03:55:11.848764: val_loss -0.7608 +2024-11-22 03:55:11.848890: Pseudo dice [0.8475] +2024-11-22 03:55:11.848969: Epoch time: 18.69 s +2024-11-22 03:55:12.780168: +2024-11-22 03:55:12.780366: Epoch 3098 +2024-11-22 03:55:12.780479: Current learning rate: 0.00644 +2024-11-22 03:55:30.845731: train_loss -0.7722 +2024-11-22 03:55:30.848183: val_loss -0.7475 +2024-11-22 03:55:30.848274: Pseudo dice [0.8514] +2024-11-22 03:55:30.848353: Epoch time: 18.07 s +2024-11-22 03:55:31.690985: +2024-11-22 03:55:31.691188: Epoch 3099 +2024-11-22 03:55:31.691301: Current learning rate: 0.00643 +2024-11-22 03:55:49.850593: train_loss -0.7761 +2024-11-22 03:55:49.860015: val_loss -0.7553 +2024-11-22 03:55:49.860148: Pseudo dice [0.8484] +2024-11-22 03:55:49.860229: Epoch time: 18.16 s +2024-11-22 03:55:50.958333: +2024-11-22 03:55:50.958558: Epoch 3100 +2024-11-22 03:55:50.958674: Current learning rate: 0.00643 +2024-11-22 03:56:09.651096: train_loss -0.7827 +2024-11-22 03:56:09.655494: val_loss -0.7691 +2024-11-22 03:56:09.655636: Pseudo dice [0.8523] +2024-11-22 03:56:09.655728: Epoch time: 18.69 s +2024-11-22 03:56:10.500468: +2024-11-22 03:56:10.500680: Epoch 3101 +2024-11-22 03:56:10.500797: Current learning rate: 0.00643 +2024-11-22 03:56:29.703607: train_loss -0.7783 +2024-11-22 03:56:29.706103: val_loss -0.7708 +2024-11-22 03:56:29.706191: Pseudo dice [0.8491] +2024-11-22 03:56:29.706268: Epoch time: 19.2 s +2024-11-22 03:56:30.547750: +2024-11-22 03:56:30.547954: Epoch 3102 +2024-11-22 03:56:30.548084: Current learning rate: 0.00643 +2024-11-22 03:56:50.159765: train_loss -0.7887 +2024-11-22 03:56:50.168183: val_loss -0.7735 +2024-11-22 03:56:50.168379: Pseudo dice [0.8399] +2024-11-22 03:56:50.168458: Epoch time: 19.61 s +2024-11-22 03:56:51.505799: +2024-11-22 03:56:51.506037: Epoch 3103 +2024-11-22 03:56:51.506150: Current learning rate: 0.00643 +2024-11-22 03:57:10.331013: train_loss -0.7861 +2024-11-22 03:57:10.333178: val_loss -0.7862 +2024-11-22 03:57:10.333284: Pseudo dice [0.8516] +2024-11-22 03:57:10.333364: Epoch time: 18.83 s +2024-11-22 03:57:11.179856: +2024-11-22 03:57:11.180068: Epoch 3104 +2024-11-22 03:57:11.180180: Current learning rate: 0.00643 +2024-11-22 03:57:29.293814: train_loss -0.787 +2024-11-22 03:57:29.306098: val_loss -0.7661 +2024-11-22 03:57:29.306228: Pseudo dice [0.8421] +2024-11-22 03:57:29.306318: Epoch time: 18.11 s +2024-11-22 03:57:30.222018: +2024-11-22 03:57:30.222226: Epoch 3105 +2024-11-22 03:57:30.222348: Current learning rate: 0.00643 +2024-11-22 03:57:49.230767: train_loss -0.788 +2024-11-22 03:57:49.239052: val_loss -0.7886 +2024-11-22 03:57:49.239235: Pseudo dice [0.8461] +2024-11-22 03:57:49.239324: Epoch time: 19.01 s +2024-11-22 03:57:50.109395: +2024-11-22 03:57:50.109611: Epoch 3106 +2024-11-22 03:57:50.109722: Current learning rate: 0.00643 +2024-11-22 03:58:08.234831: train_loss -0.7866 +2024-11-22 03:58:08.237346: val_loss -0.7572 +2024-11-22 03:58:08.237432: Pseudo dice [0.857] +2024-11-22 03:58:08.237525: Epoch time: 18.13 s +2024-11-22 03:58:09.080659: +2024-11-22 03:58:09.080873: Epoch 3107 +2024-11-22 03:58:09.080988: Current learning rate: 0.00642 +2024-11-22 03:58:29.706858: train_loss -0.7855 +2024-11-22 03:58:29.717774: val_loss -0.7679 +2024-11-22 03:58:29.717902: Pseudo dice [0.8503] +2024-11-22 03:58:29.717990: Epoch time: 20.63 s +2024-11-22 03:58:30.584041: +2024-11-22 03:58:30.584249: Epoch 3108 +2024-11-22 03:58:30.584362: Current learning rate: 0.00642 +2024-11-22 03:58:49.946173: train_loss -0.7856 +2024-11-22 03:58:49.948902: val_loss -0.7798 +2024-11-22 03:58:49.949006: Pseudo dice [0.8488] +2024-11-22 03:58:49.949140: Epoch time: 19.36 s +2024-11-22 03:58:50.797094: +2024-11-22 03:58:50.797301: Epoch 3109 +2024-11-22 03:58:50.797410: Current learning rate: 0.00642 +2024-11-22 03:59:09.144594: train_loss -0.7794 +2024-11-22 03:59:09.152131: val_loss -0.77 +2024-11-22 03:59:09.152255: Pseudo dice [0.8549] +2024-11-22 03:59:09.152345: Epoch time: 18.35 s +2024-11-22 03:59:10.024437: +2024-11-22 03:59:10.024621: Epoch 3110 +2024-11-22 03:59:10.024729: Current learning rate: 0.00642 +2024-11-22 03:59:29.132891: train_loss -0.7766 +2024-11-22 03:59:29.138154: val_loss -0.7765 +2024-11-22 03:59:29.138275: Pseudo dice [0.8431] +2024-11-22 03:59:29.138352: Epoch time: 19.11 s +2024-11-22 03:59:30.012473: +2024-11-22 03:59:30.012722: Epoch 3111 +2024-11-22 03:59:30.012837: Current learning rate: 0.00642 +2024-11-22 03:59:48.610874: train_loss -0.7755 +2024-11-22 03:59:48.615224: val_loss -0.7819 +2024-11-22 03:59:48.615337: Pseudo dice [0.8435] +2024-11-22 03:59:48.615428: Epoch time: 18.6 s +2024-11-22 03:59:49.478621: +2024-11-22 03:59:49.478837: Epoch 3112 +2024-11-22 03:59:49.478944: Current learning rate: 0.00642 +2024-11-22 04:00:07.546463: train_loss -0.7741 +2024-11-22 04:00:07.551976: val_loss -0.7505 +2024-11-22 04:00:07.552095: Pseudo dice [0.8284] +2024-11-22 04:00:07.552175: Epoch time: 18.07 s +2024-11-22 04:00:08.417315: +2024-11-22 04:00:08.417516: Epoch 3113 +2024-11-22 04:00:08.417627: Current learning rate: 0.00642 +2024-11-22 04:00:27.895843: train_loss -0.7802 +2024-11-22 04:00:27.901865: val_loss -0.7406 +2024-11-22 04:00:27.902014: Pseudo dice [0.8424] +2024-11-22 04:00:27.902099: Epoch time: 19.48 s +2024-11-22 04:00:29.214887: +2024-11-22 04:00:29.215084: Epoch 3114 +2024-11-22 04:00:29.215196: Current learning rate: 0.00642 +2024-11-22 04:00:47.841290: train_loss -0.7609 +2024-11-22 04:00:47.856176: val_loss -0.7551 +2024-11-22 04:00:47.856366: Pseudo dice [0.8364] +2024-11-22 04:00:47.856457: Epoch time: 18.63 s +2024-11-22 04:00:48.710526: +2024-11-22 04:00:48.710754: Epoch 3115 +2024-11-22 04:00:48.710867: Current learning rate: 0.00642 +2024-11-22 04:01:07.123618: train_loss -0.7674 +2024-11-22 04:01:07.125484: val_loss -0.7801 +2024-11-22 04:01:07.125572: Pseudo dice [0.8534] +2024-11-22 04:01:07.125648: Epoch time: 18.41 s +2024-11-22 04:01:07.967434: +2024-11-22 04:01:07.967644: Epoch 3116 +2024-11-22 04:01:07.967755: Current learning rate: 0.00641 +2024-11-22 04:01:26.905306: train_loss -0.777 +2024-11-22 04:01:26.908323: val_loss -0.784 +2024-11-22 04:01:26.908451: Pseudo dice [0.8556] +2024-11-22 04:01:26.908527: Epoch time: 18.94 s +2024-11-22 04:01:27.849191: +2024-11-22 04:01:27.849391: Epoch 3117 +2024-11-22 04:01:27.849501: Current learning rate: 0.00641 +2024-11-22 04:01:46.170571: train_loss -0.7738 +2024-11-22 04:01:46.173147: val_loss -0.7704 +2024-11-22 04:01:46.173278: Pseudo dice [0.8489] +2024-11-22 04:01:46.173356: Epoch time: 18.32 s +2024-11-22 04:01:47.025144: +2024-11-22 04:01:47.025528: Epoch 3118 +2024-11-22 04:01:47.025648: Current learning rate: 0.00641 +2024-11-22 04:02:04.977808: train_loss -0.7754 +2024-11-22 04:02:04.987602: val_loss -0.7366 +2024-11-22 04:02:04.987746: Pseudo dice [0.8478] +2024-11-22 04:02:04.987833: Epoch time: 17.95 s +2024-11-22 04:02:05.849498: +2024-11-22 04:02:05.849724: Epoch 3119 +2024-11-22 04:02:05.849845: Current learning rate: 0.00641 +2024-11-22 04:02:24.988286: train_loss -0.7667 +2024-11-22 04:02:25.002023: val_loss -0.7736 +2024-11-22 04:02:25.002172: Pseudo dice [0.8462] +2024-11-22 04:02:25.002261: Epoch time: 19.14 s +2024-11-22 04:02:25.919182: +2024-11-22 04:02:25.919399: Epoch 3120 +2024-11-22 04:02:25.919510: Current learning rate: 0.00641 +2024-11-22 04:02:44.646808: train_loss -0.7778 +2024-11-22 04:02:44.649244: val_loss -0.7589 +2024-11-22 04:02:44.672731: Pseudo dice [0.8598] +2024-11-22 04:02:44.672850: Epoch time: 18.73 s +2024-11-22 04:02:45.517618: +2024-11-22 04:02:45.517824: Epoch 3121 +2024-11-22 04:02:45.517938: Current learning rate: 0.00641 +2024-11-22 04:03:03.959482: train_loss -0.7723 +2024-11-22 04:03:03.966482: val_loss -0.7483 +2024-11-22 04:03:03.966622: Pseudo dice [0.8416] +2024-11-22 04:03:03.966707: Epoch time: 18.44 s +2024-11-22 04:03:04.851202: +2024-11-22 04:03:04.851408: Epoch 3122 +2024-11-22 04:03:04.851530: Current learning rate: 0.00641 +2024-11-22 04:03:24.381407: train_loss -0.7814 +2024-11-22 04:03:24.383206: val_loss -0.7625 +2024-11-22 04:03:24.383292: Pseudo dice [0.8553] +2024-11-22 04:03:24.383373: Epoch time: 19.53 s +2024-11-22 04:03:25.220382: +2024-11-22 04:03:25.220588: Epoch 3123 +2024-11-22 04:03:25.220705: Current learning rate: 0.00641 +2024-11-22 04:03:43.255478: train_loss -0.7711 +2024-11-22 04:03:43.258098: val_loss -0.777 +2024-11-22 04:03:43.258202: Pseudo dice [0.8315] +2024-11-22 04:03:43.258293: Epoch time: 18.04 s +2024-11-22 04:03:44.118373: +2024-11-22 04:03:44.118581: Epoch 3124 +2024-11-22 04:03:44.118698: Current learning rate: 0.0064 +2024-11-22 04:04:02.278589: train_loss -0.7723 +2024-11-22 04:04:02.286281: val_loss -0.744 +2024-11-22 04:04:02.286419: Pseudo dice [0.8643] +2024-11-22 04:04:02.286505: Epoch time: 18.16 s +2024-11-22 04:04:03.557597: +2024-11-22 04:04:03.557811: Epoch 3125 +2024-11-22 04:04:03.557920: Current learning rate: 0.0064 +2024-11-22 04:04:22.655866: train_loss -0.7762 +2024-11-22 04:04:22.672618: val_loss -0.7665 +2024-11-22 04:04:22.672764: Pseudo dice [0.8408] +2024-11-22 04:04:22.672852: Epoch time: 19.1 s +2024-11-22 04:04:23.605168: +2024-11-22 04:04:23.605397: Epoch 3126 +2024-11-22 04:04:23.605509: Current learning rate: 0.0064 +2024-11-22 04:04:42.153945: train_loss -0.7844 +2024-11-22 04:04:42.162044: val_loss -0.7613 +2024-11-22 04:04:42.162167: Pseudo dice [0.8561] +2024-11-22 04:04:42.162244: Epoch time: 18.55 s +2024-11-22 04:04:43.214788: +2024-11-22 04:04:43.214997: Epoch 3127 +2024-11-22 04:04:43.215122: Current learning rate: 0.0064 +2024-11-22 04:05:03.624500: train_loss -0.7879 +2024-11-22 04:05:03.630764: val_loss -0.7689 +2024-11-22 04:05:03.630888: Pseudo dice [0.8424] +2024-11-22 04:05:03.630974: Epoch time: 20.41 s +2024-11-22 04:05:04.486975: +2024-11-22 04:05:04.487216: Epoch 3128 +2024-11-22 04:05:04.487329: Current learning rate: 0.0064 +2024-11-22 04:05:23.599027: train_loss -0.7749 +2024-11-22 04:05:23.601719: val_loss -0.7437 +2024-11-22 04:05:23.601824: Pseudo dice [0.8401] +2024-11-22 04:05:23.601902: Epoch time: 19.11 s +2024-11-22 04:05:24.451218: +2024-11-22 04:05:24.451448: Epoch 3129 +2024-11-22 04:05:24.451568: Current learning rate: 0.0064 +2024-11-22 04:05:44.615349: train_loss -0.7787 +2024-11-22 04:05:44.623711: val_loss -0.781 +2024-11-22 04:05:44.623839: Pseudo dice [0.8509] +2024-11-22 04:05:44.623926: Epoch time: 20.17 s +2024-11-22 04:05:45.624329: +2024-11-22 04:05:45.624546: Epoch 3130 +2024-11-22 04:05:45.624667: Current learning rate: 0.0064 +2024-11-22 04:06:04.162571: train_loss -0.7786 +2024-11-22 04:06:04.171161: val_loss -0.7344 +2024-11-22 04:06:04.171293: Pseudo dice [0.8473] +2024-11-22 04:06:04.171379: Epoch time: 18.54 s +2024-11-22 04:06:05.032731: +2024-11-22 04:06:05.032939: Epoch 3131 +2024-11-22 04:06:05.033050: Current learning rate: 0.0064 +2024-11-22 04:06:23.875816: train_loss -0.7829 +2024-11-22 04:06:23.882645: val_loss -0.7629 +2024-11-22 04:06:23.882782: Pseudo dice [0.8493] +2024-11-22 04:06:23.882869: Epoch time: 18.84 s +2024-11-22 04:06:24.772037: +2024-11-22 04:06:24.772246: Epoch 3132 +2024-11-22 04:06:24.772357: Current learning rate: 0.00639 +2024-11-22 04:06:44.340675: train_loss -0.7801 +2024-11-22 04:06:44.347304: val_loss -0.7697 +2024-11-22 04:06:44.347414: Pseudo dice [0.8564] +2024-11-22 04:06:44.347502: Epoch time: 19.57 s +2024-11-22 04:06:45.238991: +2024-11-22 04:06:45.239226: Epoch 3133 +2024-11-22 04:06:45.239337: Current learning rate: 0.00639 +2024-11-22 04:07:04.223343: train_loss -0.7759 +2024-11-22 04:07:04.228991: val_loss -0.7692 +2024-11-22 04:07:04.229113: Pseudo dice [0.8507] +2024-11-22 04:07:04.229193: Epoch time: 18.99 s +2024-11-22 04:07:05.214267: +2024-11-22 04:07:05.214540: Epoch 3134 +2024-11-22 04:07:05.214653: Current learning rate: 0.00639 +2024-11-22 04:07:23.470581: train_loss -0.7786 +2024-11-22 04:07:23.477582: val_loss -0.7826 +2024-11-22 04:07:23.477701: Pseudo dice [0.8398] +2024-11-22 04:07:23.477782: Epoch time: 18.26 s +2024-11-22 04:07:24.330286: +2024-11-22 04:07:24.330481: Epoch 3135 +2024-11-22 04:07:24.330597: Current learning rate: 0.00639 +2024-11-22 04:07:44.178684: train_loss -0.7872 +2024-11-22 04:07:44.188583: val_loss -0.7589 +2024-11-22 04:07:44.188747: Pseudo dice [0.8607] +2024-11-22 04:07:44.188829: Epoch time: 19.85 s +2024-11-22 04:07:45.524985: +2024-11-22 04:07:45.525218: Epoch 3136 +2024-11-22 04:07:45.525326: Current learning rate: 0.00639 +2024-11-22 04:08:04.735914: train_loss -0.7692 +2024-11-22 04:08:04.738901: val_loss -0.7587 +2024-11-22 04:08:04.739004: Pseudo dice [0.8423] +2024-11-22 04:08:04.739099: Epoch time: 19.21 s +2024-11-22 04:08:05.585287: +2024-11-22 04:08:05.585497: Epoch 3137 +2024-11-22 04:08:05.585606: Current learning rate: 0.00639 +2024-11-22 04:08:23.775551: train_loss -0.7706 +2024-11-22 04:08:23.779185: val_loss -0.7508 +2024-11-22 04:08:23.779299: Pseudo dice [0.8396] +2024-11-22 04:08:23.779385: Epoch time: 18.19 s +2024-11-22 04:08:24.696622: +2024-11-22 04:08:24.696859: Epoch 3138 +2024-11-22 04:08:24.696971: Current learning rate: 0.00639 +2024-11-22 04:08:43.345759: train_loss -0.7678 +2024-11-22 04:08:43.347844: val_loss -0.779 +2024-11-22 04:08:43.347934: Pseudo dice [0.8563] +2024-11-22 04:08:43.348008: Epoch time: 18.65 s +2024-11-22 04:08:44.191330: +2024-11-22 04:08:44.191537: Epoch 3139 +2024-11-22 04:08:44.191662: Current learning rate: 0.00639 +2024-11-22 04:09:02.180931: train_loss -0.7712 +2024-11-22 04:09:02.189459: val_loss -0.7657 +2024-11-22 04:09:02.189605: Pseudo dice [0.8513] +2024-11-22 04:09:02.189688: Epoch time: 17.99 s +2024-11-22 04:09:03.064620: +2024-11-22 04:09:03.064829: Epoch 3140 +2024-11-22 04:09:03.064940: Current learning rate: 0.00639 +2024-11-22 04:09:22.578363: train_loss -0.7676 +2024-11-22 04:09:22.581656: val_loss -0.7678 +2024-11-22 04:09:22.581787: Pseudo dice [0.8556] +2024-11-22 04:09:22.581939: Epoch time: 19.51 s +2024-11-22 04:09:23.457450: +2024-11-22 04:09:23.457669: Epoch 3141 +2024-11-22 04:09:23.457787: Current learning rate: 0.00638 +2024-11-22 04:09:41.836744: train_loss -0.7739 +2024-11-22 04:09:41.843369: val_loss -0.7635 +2024-11-22 04:09:41.843497: Pseudo dice [0.8507] +2024-11-22 04:09:41.843584: Epoch time: 18.38 s +2024-11-22 04:09:42.702408: +2024-11-22 04:09:42.702629: Epoch 3142 +2024-11-22 04:09:42.702744: Current learning rate: 0.00638 +2024-11-22 04:10:02.202965: train_loss -0.7711 +2024-11-22 04:10:02.205354: val_loss -0.7724 +2024-11-22 04:10:02.205449: Pseudo dice [0.8589] +2024-11-22 04:10:02.205529: Epoch time: 19.5 s +2024-11-22 04:10:03.049675: +2024-11-22 04:10:03.049883: Epoch 3143 +2024-11-22 04:10:03.050000: Current learning rate: 0.00638 +2024-11-22 04:10:21.733353: train_loss -0.7741 +2024-11-22 04:10:21.746987: val_loss -0.7754 +2024-11-22 04:10:21.747137: Pseudo dice [0.8474] +2024-11-22 04:10:21.747223: Epoch time: 18.68 s +2024-11-22 04:10:22.729366: +2024-11-22 04:10:22.729573: Epoch 3144 +2024-11-22 04:10:22.729681: Current learning rate: 0.00638 +2024-11-22 04:10:41.523651: train_loss -0.7938 +2024-11-22 04:10:41.532186: val_loss -0.7671 +2024-11-22 04:10:41.532373: Pseudo dice [0.8587] +2024-11-22 04:10:41.532470: Epoch time: 18.8 s +2024-11-22 04:10:42.410809: +2024-11-22 04:10:42.410990: Epoch 3145 +2024-11-22 04:10:42.411103: Current learning rate: 0.00638 +2024-11-22 04:11:01.148606: train_loss -0.7857 +2024-11-22 04:11:01.150893: val_loss -0.7876 +2024-11-22 04:11:01.150983: Pseudo dice [0.8466] +2024-11-22 04:11:01.151069: Epoch time: 18.74 s +2024-11-22 04:11:01.993975: +2024-11-22 04:11:01.994177: Epoch 3146 +2024-11-22 04:11:01.994287: Current learning rate: 0.00638 +2024-11-22 04:11:19.601908: train_loss -0.7869 +2024-11-22 04:11:19.604109: val_loss -0.7659 +2024-11-22 04:11:19.604204: Pseudo dice [0.8547] +2024-11-22 04:11:19.604284: Epoch time: 17.61 s +2024-11-22 04:11:20.842263: +2024-11-22 04:11:20.842464: Epoch 3147 +2024-11-22 04:11:20.842580: Current learning rate: 0.00638 +2024-11-22 04:11:39.567139: train_loss -0.7866 +2024-11-22 04:11:39.573928: val_loss -0.762 +2024-11-22 04:11:39.574066: Pseudo dice [0.844] +2024-11-22 04:11:39.574155: Epoch time: 18.73 s +2024-11-22 04:11:40.422730: +2024-11-22 04:11:40.422995: Epoch 3148 +2024-11-22 04:11:40.423131: Current learning rate: 0.00638 +2024-11-22 04:11:59.268160: train_loss -0.7905 +2024-11-22 04:11:59.269755: val_loss -0.7688 +2024-11-22 04:11:59.269861: Pseudo dice [0.8658] +2024-11-22 04:11:59.270011: Epoch time: 18.85 s +2024-11-22 04:12:00.137095: +2024-11-22 04:12:00.137327: Epoch 3149 +2024-11-22 04:12:00.137441: Current learning rate: 0.00637 +2024-11-22 04:12:19.063637: train_loss -0.789 +2024-11-22 04:12:19.065643: val_loss -0.7629 +2024-11-22 04:12:19.065748: Pseudo dice [0.8434] +2024-11-22 04:12:19.065825: Epoch time: 18.93 s +2024-11-22 04:12:20.145879: +2024-11-22 04:12:20.146080: Epoch 3150 +2024-11-22 04:12:20.146191: Current learning rate: 0.00637 +2024-11-22 04:12:38.789322: train_loss -0.7868 +2024-11-22 04:12:38.791414: val_loss -0.7856 +2024-11-22 04:12:38.791512: Pseudo dice [0.861] +2024-11-22 04:12:38.791592: Epoch time: 18.64 s +2024-11-22 04:12:39.639571: +2024-11-22 04:12:39.639770: Epoch 3151 +2024-11-22 04:12:39.639884: Current learning rate: 0.00637 +2024-11-22 04:12:58.536150: train_loss -0.7858 +2024-11-22 04:12:58.540049: val_loss -0.7825 +2024-11-22 04:12:58.540175: Pseudo dice [0.8556] +2024-11-22 04:12:58.540264: Epoch time: 18.9 s +2024-11-22 04:12:59.468532: +2024-11-22 04:12:59.468767: Epoch 3152 +2024-11-22 04:12:59.468883: Current learning rate: 0.00637 +2024-11-22 04:13:18.344055: train_loss -0.789 +2024-11-22 04:13:18.359105: val_loss -0.7757 +2024-11-22 04:13:18.359247: Pseudo dice [0.8591] +2024-11-22 04:13:18.359329: Epoch time: 18.88 s +2024-11-22 04:13:19.329549: +2024-11-22 04:13:19.329757: Epoch 3153 +2024-11-22 04:13:19.329875: Current learning rate: 0.00637 +2024-11-22 04:13:39.245600: train_loss -0.7806 +2024-11-22 04:13:39.268203: val_loss -0.7636 +2024-11-22 04:13:39.268332: Pseudo dice [0.8506] +2024-11-22 04:13:39.268413: Epoch time: 19.92 s +2024-11-22 04:13:40.135419: +2024-11-22 04:13:40.135640: Epoch 3154 +2024-11-22 04:13:40.135749: Current learning rate: 0.00637 +2024-11-22 04:13:59.658206: train_loss -0.7806 +2024-11-22 04:13:59.660876: val_loss -0.774 +2024-11-22 04:13:59.661009: Pseudo dice [0.8563] +2024-11-22 04:13:59.661099: Epoch time: 19.52 s +2024-11-22 04:14:00.510374: +2024-11-22 04:14:00.510577: Epoch 3155 +2024-11-22 04:14:00.510686: Current learning rate: 0.00637 +2024-11-22 04:14:19.925640: train_loss -0.7861 +2024-11-22 04:14:19.933854: val_loss -0.774 +2024-11-22 04:14:19.933979: Pseudo dice [0.848] +2024-11-22 04:14:19.934069: Epoch time: 19.42 s +2024-11-22 04:14:20.834334: +2024-11-22 04:14:20.834531: Epoch 3156 +2024-11-22 04:14:20.834644: Current learning rate: 0.00637 +2024-11-22 04:14:38.792182: train_loss -0.7856 +2024-11-22 04:14:38.799800: val_loss -0.7785 +2024-11-22 04:14:38.799921: Pseudo dice [0.8567] +2024-11-22 04:14:38.800005: Epoch time: 17.96 s +2024-11-22 04:14:39.723919: +2024-11-22 04:14:39.724129: Epoch 3157 +2024-11-22 04:14:39.724243: Current learning rate: 0.00637 +2024-11-22 04:14:59.534109: train_loss -0.789 +2024-11-22 04:14:59.539016: val_loss -0.7423 +2024-11-22 04:14:59.539142: Pseudo dice [0.84] +2024-11-22 04:14:59.539222: Epoch time: 19.81 s +2024-11-22 04:15:00.913845: +2024-11-22 04:15:00.914075: Epoch 3158 +2024-11-22 04:15:00.914188: Current learning rate: 0.00636 +2024-11-22 04:15:20.143319: train_loss -0.7801 +2024-11-22 04:15:20.155755: val_loss -0.7345 +2024-11-22 04:15:20.155897: Pseudo dice [0.8338] +2024-11-22 04:15:20.178313: Epoch time: 19.23 s +2024-11-22 04:15:21.023873: +2024-11-22 04:15:21.024081: Epoch 3159 +2024-11-22 04:15:21.024199: Current learning rate: 0.00636 +2024-11-22 04:15:39.668117: train_loss -0.7834 +2024-11-22 04:15:39.676178: val_loss -0.7786 +2024-11-22 04:15:39.676323: Pseudo dice [0.8452] +2024-11-22 04:15:39.676406: Epoch time: 18.65 s +2024-11-22 04:15:40.527941: +2024-11-22 04:15:40.528178: Epoch 3160 +2024-11-22 04:15:40.528290: Current learning rate: 0.00636 +2024-11-22 04:15:59.157036: train_loss -0.791 +2024-11-22 04:15:59.162903: val_loss -0.7699 +2024-11-22 04:15:59.163010: Pseudo dice [0.8519] +2024-11-22 04:15:59.163100: Epoch time: 18.63 s +2024-11-22 04:16:00.067879: +2024-11-22 04:16:00.068079: Epoch 3161 +2024-11-22 04:16:00.068196: Current learning rate: 0.00636 +2024-11-22 04:16:19.529289: train_loss -0.7876 +2024-11-22 04:16:19.537553: val_loss -0.7684 +2024-11-22 04:16:19.537665: Pseudo dice [0.8371] +2024-11-22 04:16:19.537746: Epoch time: 19.46 s +2024-11-22 04:16:20.432756: +2024-11-22 04:16:20.432974: Epoch 3162 +2024-11-22 04:16:20.433104: Current learning rate: 0.00636 +2024-11-22 04:16:39.959089: train_loss -0.7851 +2024-11-22 04:16:39.975684: val_loss -0.7194 +2024-11-22 04:16:39.975816: Pseudo dice [0.8451] +2024-11-22 04:16:39.975908: Epoch time: 19.53 s +2024-11-22 04:16:41.011812: +2024-11-22 04:16:41.012010: Epoch 3163 +2024-11-22 04:16:41.012125: Current learning rate: 0.00636 +2024-11-22 04:17:00.145155: train_loss -0.7872 +2024-11-22 04:17:00.151352: val_loss -0.7596 +2024-11-22 04:17:00.151462: Pseudo dice [0.8563] +2024-11-22 04:17:00.151549: Epoch time: 19.13 s +2024-11-22 04:17:01.103827: +2024-11-22 04:17:01.104044: Epoch 3164 +2024-11-22 04:17:01.104160: Current learning rate: 0.00636 +2024-11-22 04:17:19.685055: train_loss -0.7882 +2024-11-22 04:17:19.687297: val_loss -0.7718 +2024-11-22 04:17:19.687379: Pseudo dice [0.8544] +2024-11-22 04:17:19.687454: Epoch time: 18.58 s +2024-11-22 04:17:20.528304: +2024-11-22 04:17:20.528519: Epoch 3165 +2024-11-22 04:17:20.528635: Current learning rate: 0.00636 +2024-11-22 04:17:39.018565: train_loss -0.7971 +2024-11-22 04:17:39.020434: val_loss -0.7564 +2024-11-22 04:17:39.020527: Pseudo dice [0.8438] +2024-11-22 04:17:39.020613: Epoch time: 18.49 s +2024-11-22 04:17:39.864838: +2024-11-22 04:17:39.865031: Epoch 3166 +2024-11-22 04:17:39.865150: Current learning rate: 0.00635 +2024-11-22 04:17:57.794709: train_loss -0.7884 +2024-11-22 04:17:57.796537: val_loss -0.7766 +2024-11-22 04:17:57.796628: Pseudo dice [0.8451] +2024-11-22 04:17:57.796704: Epoch time: 17.93 s +2024-11-22 04:17:58.638421: +2024-11-22 04:17:58.638616: Epoch 3167 +2024-11-22 04:17:58.638729: Current learning rate: 0.00635 +2024-11-22 04:18:17.446440: train_loss -0.7797 +2024-11-22 04:18:17.454268: val_loss -0.763 +2024-11-22 04:18:17.454408: Pseudo dice [0.855] +2024-11-22 04:18:17.454494: Epoch time: 18.81 s +2024-11-22 04:18:18.341213: +2024-11-22 04:18:18.341416: Epoch 3168 +2024-11-22 04:18:18.341531: Current learning rate: 0.00635 +2024-11-22 04:18:38.003285: train_loss -0.7731 +2024-11-22 04:18:38.005770: val_loss -0.7676 +2024-11-22 04:18:38.005900: Pseudo dice [0.8431] +2024-11-22 04:18:38.005986: Epoch time: 19.66 s +2024-11-22 04:18:39.376693: +2024-11-22 04:18:39.376932: Epoch 3169 +2024-11-22 04:18:39.377044: Current learning rate: 0.00635 +2024-11-22 04:18:58.664239: train_loss -0.7846 +2024-11-22 04:18:58.665976: val_loss -0.7607 +2024-11-22 04:18:58.666080: Pseudo dice [0.8586] +2024-11-22 04:18:58.666165: Epoch time: 19.29 s +2024-11-22 04:18:59.516209: +2024-11-22 04:18:59.516425: Epoch 3170 +2024-11-22 04:18:59.516537: Current learning rate: 0.00635 +2024-11-22 04:19:18.245572: train_loss -0.7856 +2024-11-22 04:19:18.253026: val_loss -0.7539 +2024-11-22 04:19:18.253153: Pseudo dice [0.843] +2024-11-22 04:19:18.253243: Epoch time: 18.73 s +2024-11-22 04:19:19.144812: +2024-11-22 04:19:19.145022: Epoch 3171 +2024-11-22 04:19:19.145139: Current learning rate: 0.00635 +2024-11-22 04:19:37.700594: train_loss -0.7883 +2024-11-22 04:19:37.708859: val_loss -0.7472 +2024-11-22 04:19:37.708989: Pseudo dice [0.8332] +2024-11-22 04:19:37.709086: Epoch time: 18.56 s +2024-11-22 04:19:38.605196: +2024-11-22 04:19:38.605413: Epoch 3172 +2024-11-22 04:19:38.605526: Current learning rate: 0.00635 +2024-11-22 04:19:57.706572: train_loss -0.773 +2024-11-22 04:19:57.711095: val_loss -0.7481 +2024-11-22 04:19:57.711204: Pseudo dice [0.8449] +2024-11-22 04:19:57.711283: Epoch time: 19.1 s +2024-11-22 04:19:58.716625: +2024-11-22 04:19:58.716865: Epoch 3173 +2024-11-22 04:19:58.716998: Current learning rate: 0.00635 +2024-11-22 04:20:17.746910: train_loss -0.7697 +2024-11-22 04:20:17.756911: val_loss -0.7706 +2024-11-22 04:20:17.757032: Pseudo dice [0.845] +2024-11-22 04:20:17.757121: Epoch time: 19.03 s +2024-11-22 04:20:18.655197: +2024-11-22 04:20:18.655397: Epoch 3174 +2024-11-22 04:20:18.655510: Current learning rate: 0.00635 +2024-11-22 04:20:38.327546: train_loss -0.7782 +2024-11-22 04:20:38.336302: val_loss -0.7603 +2024-11-22 04:20:38.336425: Pseudo dice [0.8417] +2024-11-22 04:20:38.336510: Epoch time: 19.67 s +2024-11-22 04:20:39.318675: +2024-11-22 04:20:39.318887: Epoch 3175 +2024-11-22 04:20:39.319002: Current learning rate: 0.00634 +2024-11-22 04:20:58.428002: train_loss -0.7713 +2024-11-22 04:20:58.434217: val_loss -0.7553 +2024-11-22 04:20:58.434351: Pseudo dice [0.83] +2024-11-22 04:20:58.434439: Epoch time: 19.11 s +2024-11-22 04:20:59.283969: +2024-11-22 04:20:59.284174: Epoch 3176 +2024-11-22 04:20:59.284285: Current learning rate: 0.00634 +2024-11-22 04:21:19.527794: train_loss -0.7573 +2024-11-22 04:21:19.530203: val_loss -0.7788 +2024-11-22 04:21:19.530299: Pseudo dice [0.8497] +2024-11-22 04:21:19.530392: Epoch time: 20.24 s +2024-11-22 04:21:20.378397: +2024-11-22 04:21:20.378590: Epoch 3177 +2024-11-22 04:21:20.378699: Current learning rate: 0.00634 +2024-11-22 04:21:39.770964: train_loss -0.7773 +2024-11-22 04:21:39.777652: val_loss -0.7657 +2024-11-22 04:21:39.777775: Pseudo dice [0.8524] +2024-11-22 04:21:39.777882: Epoch time: 19.39 s +2024-11-22 04:21:40.736406: +2024-11-22 04:21:40.736609: Epoch 3178 +2024-11-22 04:21:40.736724: Current learning rate: 0.00634 +2024-11-22 04:21:59.186117: train_loss -0.7847 +2024-11-22 04:21:59.188916: val_loss -0.7656 +2024-11-22 04:21:59.189007: Pseudo dice [0.8421] +2024-11-22 04:21:59.189092: Epoch time: 18.45 s +2024-11-22 04:22:00.029227: +2024-11-22 04:22:00.029432: Epoch 3179 +2024-11-22 04:22:00.029547: Current learning rate: 0.00634 +2024-11-22 04:22:20.025807: train_loss -0.7889 +2024-11-22 04:22:20.029954: val_loss -0.7761 +2024-11-22 04:22:20.030102: Pseudo dice [0.8472] +2024-11-22 04:22:20.030190: Epoch time: 20.0 s +2024-11-22 04:22:21.306545: +2024-11-22 04:22:21.306807: Epoch 3180 +2024-11-22 04:22:21.306919: Current learning rate: 0.00634 +2024-11-22 04:22:40.354666: train_loss -0.7863 +2024-11-22 04:22:40.361932: val_loss -0.7592 +2024-11-22 04:22:40.362069: Pseudo dice [0.8541] +2024-11-22 04:22:40.362157: Epoch time: 19.05 s +2024-11-22 04:22:41.326511: +2024-11-22 04:22:41.326734: Epoch 3181 +2024-11-22 04:22:41.326846: Current learning rate: 0.00634 +2024-11-22 04:23:01.925871: train_loss -0.7836 +2024-11-22 04:23:01.939449: val_loss -0.7763 +2024-11-22 04:23:01.939562: Pseudo dice [0.8569] +2024-11-22 04:23:01.939658: Epoch time: 20.6 s +2024-11-22 04:23:02.795379: +2024-11-22 04:23:02.795584: Epoch 3182 +2024-11-22 04:23:02.795698: Current learning rate: 0.00634 +2024-11-22 04:23:22.038172: train_loss -0.7799 +2024-11-22 04:23:22.047610: val_loss -0.7899 +2024-11-22 04:23:22.047738: Pseudo dice [0.86] +2024-11-22 04:23:22.047819: Epoch time: 19.24 s +2024-11-22 04:23:22.892290: +2024-11-22 04:23:22.892504: Epoch 3183 +2024-11-22 04:23:22.892616: Current learning rate: 0.00633 +2024-11-22 04:23:42.122154: train_loss -0.7711 +2024-11-22 04:23:42.124846: val_loss -0.7776 +2024-11-22 04:23:42.124933: Pseudo dice [0.8547] +2024-11-22 04:23:42.125013: Epoch time: 19.23 s +2024-11-22 04:23:42.974025: +2024-11-22 04:23:42.974255: Epoch 3184 +2024-11-22 04:23:42.974672: Current learning rate: 0.00633 +2024-11-22 04:24:01.083230: train_loss -0.7843 +2024-11-22 04:24:01.087510: val_loss -0.7678 +2024-11-22 04:24:01.087643: Pseudo dice [0.8589] +2024-11-22 04:24:01.087731: Epoch time: 18.1 s +2024-11-22 04:24:01.944430: +2024-11-22 04:24:01.944627: Epoch 3185 +2024-11-22 04:24:01.944739: Current learning rate: 0.00633 +2024-11-22 04:24:21.313081: train_loss -0.7869 +2024-11-22 04:24:21.319052: val_loss -0.7639 +2024-11-22 04:24:21.319181: Pseudo dice [0.8441] +2024-11-22 04:24:21.319262: Epoch time: 19.37 s +2024-11-22 04:24:22.389729: +2024-11-22 04:24:22.389925: Epoch 3186 +2024-11-22 04:24:22.390038: Current learning rate: 0.00633 +2024-11-22 04:24:42.284466: train_loss -0.7748 +2024-11-22 04:24:42.289997: val_loss -0.7565 +2024-11-22 04:24:42.290117: Pseudo dice [0.8576] +2024-11-22 04:24:42.290208: Epoch time: 19.9 s +2024-11-22 04:24:43.314858: +2024-11-22 04:24:43.315067: Epoch 3187 +2024-11-22 04:24:43.315178: Current learning rate: 0.00633 +2024-11-22 04:25:02.770993: train_loss -0.7603 +2024-11-22 04:25:02.773539: val_loss -0.7792 +2024-11-22 04:25:02.773653: Pseudo dice [0.8477] +2024-11-22 04:25:02.773732: Epoch time: 19.46 s +2024-11-22 04:25:03.633013: +2024-11-22 04:25:03.633253: Epoch 3188 +2024-11-22 04:25:03.633364: Current learning rate: 0.00633 +2024-11-22 04:25:22.357578: train_loss -0.7759 +2024-11-22 04:25:22.360162: val_loss -0.7954 +2024-11-22 04:25:22.360265: Pseudo dice [0.8559] +2024-11-22 04:25:22.360346: Epoch time: 18.73 s +2024-11-22 04:25:23.210666: +2024-11-22 04:25:23.210899: Epoch 3189 +2024-11-22 04:25:23.211016: Current learning rate: 0.00633 +2024-11-22 04:25:43.349857: train_loss -0.7835 +2024-11-22 04:25:43.353849: val_loss -0.7801 +2024-11-22 04:25:43.353958: Pseudo dice [0.8536] +2024-11-22 04:25:43.354042: Epoch time: 20.14 s +2024-11-22 04:25:44.201380: +2024-11-22 04:25:44.201615: Epoch 3190 +2024-11-22 04:25:44.201742: Current learning rate: 0.00633 +2024-11-22 04:26:03.574577: train_loss -0.786 +2024-11-22 04:26:03.577166: val_loss -0.7562 +2024-11-22 04:26:03.577275: Pseudo dice [0.8377] +2024-11-22 04:26:03.577357: Epoch time: 19.37 s +2024-11-22 04:26:04.778767: +2024-11-22 04:26:04.779027: Epoch 3191 +2024-11-22 04:26:04.779148: Current learning rate: 0.00633 +2024-11-22 04:26:24.643272: train_loss -0.7769 +2024-11-22 04:26:24.649827: val_loss -0.768 +2024-11-22 04:26:24.649941: Pseudo dice [0.8498] +2024-11-22 04:26:24.650028: Epoch time: 19.87 s +2024-11-22 04:26:25.529038: +2024-11-22 04:26:25.529276: Epoch 3192 +2024-11-22 04:26:25.529392: Current learning rate: 0.00632 +2024-11-22 04:26:46.342558: train_loss -0.7793 +2024-11-22 04:26:46.347554: val_loss -0.7581 +2024-11-22 04:26:46.347678: Pseudo dice [0.8554] +2024-11-22 04:26:46.347759: Epoch time: 20.81 s +2024-11-22 04:26:47.223546: +2024-11-22 04:26:47.223772: Epoch 3193 +2024-11-22 04:26:47.223886: Current learning rate: 0.00632 +2024-11-22 04:27:06.022844: train_loss -0.7764 +2024-11-22 04:27:06.029779: val_loss -0.7796 +2024-11-22 04:27:06.029961: Pseudo dice [0.8516] +2024-11-22 04:27:06.030043: Epoch time: 18.8 s +2024-11-22 04:27:06.900842: +2024-11-22 04:27:06.901082: Epoch 3194 +2024-11-22 04:27:06.901200: Current learning rate: 0.00632 +2024-11-22 04:27:25.624207: train_loss -0.7768 +2024-11-22 04:27:25.630752: val_loss -0.7643 +2024-11-22 04:27:25.630874: Pseudo dice [0.855] +2024-11-22 04:27:25.631019: Epoch time: 18.72 s +2024-11-22 04:27:26.478618: +2024-11-22 04:27:26.478847: Epoch 3195 +2024-11-22 04:27:26.478959: Current learning rate: 0.00632 +2024-11-22 04:27:45.416809: train_loss -0.7806 +2024-11-22 04:27:45.419180: val_loss -0.7585 +2024-11-22 04:27:45.419282: Pseudo dice [0.8494] +2024-11-22 04:27:45.419664: Epoch time: 18.94 s +2024-11-22 04:27:46.271805: +2024-11-22 04:27:46.272035: Epoch 3196 +2024-11-22 04:27:46.272161: Current learning rate: 0.00632 +2024-11-22 04:28:06.262422: train_loss -0.7921 +2024-11-22 04:28:06.267446: val_loss -0.7699 +2024-11-22 04:28:06.267562: Pseudo dice [0.8501] +2024-11-22 04:28:06.267836: Epoch time: 19.99 s +2024-11-22 04:28:07.183028: +2024-11-22 04:28:07.183258: Epoch 3197 +2024-11-22 04:28:07.183371: Current learning rate: 0.00632 +2024-11-22 04:28:26.399040: train_loss -0.783 +2024-11-22 04:28:26.406343: val_loss -0.7731 +2024-11-22 04:28:26.406514: Pseudo dice [0.8566] +2024-11-22 04:28:26.406594: Epoch time: 19.22 s +2024-11-22 04:28:27.502332: +2024-11-22 04:28:27.502523: Epoch 3198 +2024-11-22 04:28:27.502636: Current learning rate: 0.00632 +2024-11-22 04:28:46.967507: train_loss -0.7729 +2024-11-22 04:28:46.975276: val_loss -0.755 +2024-11-22 04:28:46.975406: Pseudo dice [0.8461] +2024-11-22 04:28:46.975494: Epoch time: 19.47 s +2024-11-22 04:28:48.058609: +2024-11-22 04:28:48.058816: Epoch 3199 +2024-11-22 04:28:48.058934: Current learning rate: 0.00632 +2024-11-22 04:29:07.443763: train_loss -0.7767 +2024-11-22 04:29:07.447709: val_loss -0.7808 +2024-11-22 04:29:07.447819: Pseudo dice [0.8615] +2024-11-22 04:29:07.447906: Epoch time: 19.39 s +2024-11-22 04:29:08.536383: +2024-11-22 04:29:08.536651: Epoch 3200 +2024-11-22 04:29:08.536782: Current learning rate: 0.00631 +2024-11-22 04:29:28.562805: train_loss -0.7729 +2024-11-22 04:29:28.579392: val_loss -0.7677 +2024-11-22 04:29:28.579617: Pseudo dice [0.8549] +2024-11-22 04:29:28.579764: Epoch time: 20.03 s +2024-11-22 04:29:29.441598: +2024-11-22 04:29:29.441790: Epoch 3201 +2024-11-22 04:29:29.441900: Current learning rate: 0.00631 +2024-11-22 04:29:47.862530: train_loss -0.7891 +2024-11-22 04:29:47.868195: val_loss -0.7686 +2024-11-22 04:29:47.868326: Pseudo dice [0.8549] +2024-11-22 04:29:47.868410: Epoch time: 18.42 s +2024-11-22 04:29:49.143142: +2024-11-22 04:29:49.143358: Epoch 3202 +2024-11-22 04:29:49.143472: Current learning rate: 0.00631 +2024-11-22 04:30:07.352206: train_loss -0.7895 +2024-11-22 04:30:07.359034: val_loss -0.7685 +2024-11-22 04:30:07.359146: Pseudo dice [0.8548] +2024-11-22 04:30:07.359231: Epoch time: 18.21 s +2024-11-22 04:30:08.218014: +2024-11-22 04:30:08.218214: Epoch 3203 +2024-11-22 04:30:08.218327: Current learning rate: 0.00631 +2024-11-22 04:30:27.678109: train_loss -0.785 +2024-11-22 04:30:27.691949: val_loss -0.7374 +2024-11-22 04:30:27.692095: Pseudo dice [0.8443] +2024-11-22 04:30:27.692184: Epoch time: 19.46 s +2024-11-22 04:30:28.649029: +2024-11-22 04:30:28.649253: Epoch 3204 +2024-11-22 04:30:28.649370: Current learning rate: 0.00631 +2024-11-22 04:30:47.723664: train_loss -0.7725 +2024-11-22 04:30:47.743098: val_loss -0.7672 +2024-11-22 04:30:47.743225: Pseudo dice [0.8333] +2024-11-22 04:30:47.743304: Epoch time: 19.08 s +2024-11-22 04:30:48.656271: +2024-11-22 04:30:48.656478: Epoch 3205 +2024-11-22 04:30:48.656595: Current learning rate: 0.00631 +2024-11-22 04:31:07.302205: train_loss -0.7761 +2024-11-22 04:31:07.305396: val_loss -0.7673 +2024-11-22 04:31:07.305483: Pseudo dice [0.8575] +2024-11-22 04:31:07.305561: Epoch time: 18.65 s +2024-11-22 04:31:08.148424: +2024-11-22 04:31:08.148646: Epoch 3206 +2024-11-22 04:31:08.148775: Current learning rate: 0.00631 +2024-11-22 04:31:26.829662: train_loss -0.7852 +2024-11-22 04:31:26.836784: val_loss -0.7595 +2024-11-22 04:31:26.836918: Pseudo dice [0.8473] +2024-11-22 04:31:26.837008: Epoch time: 18.68 s +2024-11-22 04:31:27.689395: +2024-11-22 04:31:27.689599: Epoch 3207 +2024-11-22 04:31:27.689720: Current learning rate: 0.00631 +2024-11-22 04:31:45.622484: train_loss -0.7824 +2024-11-22 04:31:45.629366: val_loss -0.7767 +2024-11-22 04:31:45.629478: Pseudo dice [0.8611] +2024-11-22 04:31:45.629561: Epoch time: 17.93 s +2024-11-22 04:31:46.634353: +2024-11-22 04:31:46.634555: Epoch 3208 +2024-11-22 04:31:46.634673: Current learning rate: 0.0063 +2024-11-22 04:32:05.873847: train_loss -0.7768 +2024-11-22 04:32:05.881412: val_loss -0.7733 +2024-11-22 04:32:05.881532: Pseudo dice [0.8615] +2024-11-22 04:32:05.881610: Epoch time: 19.24 s +2024-11-22 04:32:06.763639: +2024-11-22 04:32:06.763891: Epoch 3209 +2024-11-22 04:32:06.764002: Current learning rate: 0.0063 +2024-11-22 04:32:25.750011: train_loss -0.7814 +2024-11-22 04:32:25.764574: val_loss -0.7783 +2024-11-22 04:32:25.764676: Pseudo dice [0.8557] +2024-11-22 04:32:25.764760: Epoch time: 18.99 s +2024-11-22 04:32:26.610727: +2024-11-22 04:32:26.610942: Epoch 3210 +2024-11-22 04:32:26.611052: Current learning rate: 0.0063 +2024-11-22 04:32:45.799668: train_loss -0.7818 +2024-11-22 04:32:45.820127: val_loss -0.7632 +2024-11-22 04:32:45.820262: Pseudo dice [0.8409] +2024-11-22 04:32:45.820351: Epoch time: 19.19 s +2024-11-22 04:32:46.873207: +2024-11-22 04:32:46.873404: Epoch 3211 +2024-11-22 04:32:46.873519: Current learning rate: 0.0063 +2024-11-22 04:33:06.161936: train_loss -0.7655 +2024-11-22 04:33:06.165482: val_loss -0.7385 +2024-11-22 04:33:06.165602: Pseudo dice [0.8504] +2024-11-22 04:33:06.165720: Epoch time: 19.29 s +2024-11-22 04:33:07.030581: +2024-11-22 04:33:07.030769: Epoch 3212 +2024-11-22 04:33:07.030884: Current learning rate: 0.0063 +2024-11-22 04:33:25.784505: train_loss -0.7629 +2024-11-22 04:33:25.790035: val_loss -0.7506 +2024-11-22 04:33:25.790248: Pseudo dice [0.8436] +2024-11-22 04:33:25.790346: Epoch time: 18.75 s +2024-11-22 04:33:27.023457: +2024-11-22 04:33:27.023682: Epoch 3213 +2024-11-22 04:33:27.023797: Current learning rate: 0.0063 +2024-11-22 04:33:45.699072: train_loss -0.7689 +2024-11-22 04:33:45.702920: val_loss -0.7754 +2024-11-22 04:33:45.703093: Pseudo dice [0.8431] +2024-11-22 04:33:45.703177: Epoch time: 18.68 s +2024-11-22 04:33:46.718964: +2024-11-22 04:33:46.719186: Epoch 3214 +2024-11-22 04:33:46.719297: Current learning rate: 0.0063 +2024-11-22 04:34:05.659462: train_loss -0.7759 +2024-11-22 04:34:05.661719: val_loss -0.7755 +2024-11-22 04:34:05.661809: Pseudo dice [0.8464] +2024-11-22 04:34:05.661888: Epoch time: 18.94 s +2024-11-22 04:34:06.507272: +2024-11-22 04:34:06.507480: Epoch 3215 +2024-11-22 04:34:06.507596: Current learning rate: 0.0063 +2024-11-22 04:34:24.638566: train_loss -0.7875 +2024-11-22 04:34:24.646775: val_loss -0.7789 +2024-11-22 04:34:24.646916: Pseudo dice [0.838] +2024-11-22 04:34:24.646997: Epoch time: 18.13 s +2024-11-22 04:34:25.496234: +2024-11-22 04:34:25.496438: Epoch 3216 +2024-11-22 04:34:25.496557: Current learning rate: 0.0063 +2024-11-22 04:34:44.509091: train_loss -0.7883 +2024-11-22 04:34:44.511386: val_loss -0.7431 +2024-11-22 04:34:44.511470: Pseudo dice [0.853] +2024-11-22 04:34:44.511544: Epoch time: 19.01 s +2024-11-22 04:34:45.354614: +2024-11-22 04:34:45.354803: Epoch 3217 +2024-11-22 04:34:45.354913: Current learning rate: 0.00629 +2024-11-22 04:35:04.000647: train_loss -0.7871 +2024-11-22 04:35:04.003149: val_loss -0.7775 +2024-11-22 04:35:04.003246: Pseudo dice [0.8519] +2024-11-22 04:35:04.003332: Epoch time: 18.65 s +2024-11-22 04:35:04.854126: +2024-11-22 04:35:04.854386: Epoch 3218 +2024-11-22 04:35:04.854500: Current learning rate: 0.00629 +2024-11-22 04:35:23.551338: train_loss -0.7858 +2024-11-22 04:35:23.560853: val_loss -0.7661 +2024-11-22 04:35:23.560978: Pseudo dice [0.8473] +2024-11-22 04:35:23.561069: Epoch time: 18.7 s +2024-11-22 04:35:24.492556: +2024-11-22 04:35:24.492774: Epoch 3219 +2024-11-22 04:35:24.492887: Current learning rate: 0.00629 +2024-11-22 04:35:43.320928: train_loss -0.7978 +2024-11-22 04:35:43.323117: val_loss -0.7618 +2024-11-22 04:35:43.323200: Pseudo dice [0.845] +2024-11-22 04:35:43.323275: Epoch time: 18.83 s +2024-11-22 04:35:44.166234: +2024-11-22 04:35:44.166485: Epoch 3220 +2024-11-22 04:35:44.166601: Current learning rate: 0.00629 +2024-11-22 04:36:03.565121: train_loss -0.7844 +2024-11-22 04:36:03.581237: val_loss -0.7523 +2024-11-22 04:36:03.581398: Pseudo dice [0.8587] +2024-11-22 04:36:03.581491: Epoch time: 19.4 s +2024-11-22 04:36:04.440517: +2024-11-22 04:36:04.440727: Epoch 3221 +2024-11-22 04:36:04.440844: Current learning rate: 0.00629 +2024-11-22 04:36:22.839296: train_loss -0.7899 +2024-11-22 04:36:22.841730: val_loss -0.7629 +2024-11-22 04:36:22.841817: Pseudo dice [0.854] +2024-11-22 04:36:22.842113: Epoch time: 18.4 s +2024-11-22 04:36:23.681211: +2024-11-22 04:36:23.681392: Epoch 3222 +2024-11-22 04:36:23.681502: Current learning rate: 0.00629 +2024-11-22 04:36:41.922830: train_loss -0.7796 +2024-11-22 04:36:41.929160: val_loss -0.7653 +2024-11-22 04:36:41.929269: Pseudo dice [0.8498] +2024-11-22 04:36:41.929351: Epoch time: 18.24 s +2024-11-22 04:36:42.974317: +2024-11-22 04:36:42.974529: Epoch 3223 +2024-11-22 04:36:42.974641: Current learning rate: 0.00629 +2024-11-22 04:37:01.945573: train_loss -0.76 +2024-11-22 04:37:01.949163: val_loss -0.7712 +2024-11-22 04:37:01.949288: Pseudo dice [0.8499] +2024-11-22 04:37:01.949368: Epoch time: 18.97 s +2024-11-22 04:37:03.269085: +2024-11-22 04:37:03.269287: Epoch 3224 +2024-11-22 04:37:03.269401: Current learning rate: 0.00629 +2024-11-22 04:37:23.564860: train_loss -0.7837 +2024-11-22 04:37:23.569915: val_loss -0.7779 +2024-11-22 04:37:23.570045: Pseudo dice [0.8475] +2024-11-22 04:37:23.570142: Epoch time: 20.3 s +2024-11-22 04:37:24.422931: +2024-11-22 04:37:24.423195: Epoch 3225 +2024-11-22 04:37:24.423328: Current learning rate: 0.00628 +2024-11-22 04:37:42.672006: train_loss -0.7725 +2024-11-22 04:37:42.678585: val_loss -0.7594 +2024-11-22 04:37:42.678705: Pseudo dice [0.8387] +2024-11-22 04:37:42.678791: Epoch time: 18.25 s +2024-11-22 04:37:43.555990: +2024-11-22 04:37:43.556222: Epoch 3226 +2024-11-22 04:37:43.556334: Current learning rate: 0.00628 +2024-11-22 04:38:02.700695: train_loss -0.777 +2024-11-22 04:38:02.708574: val_loss -0.7559 +2024-11-22 04:38:02.708704: Pseudo dice [0.8459] +2024-11-22 04:38:02.708790: Epoch time: 19.15 s +2024-11-22 04:38:03.555762: +2024-11-22 04:38:03.555980: Epoch 3227 +2024-11-22 04:38:03.556096: Current learning rate: 0.00628 +2024-11-22 04:38:22.359913: train_loss -0.7672 +2024-11-22 04:38:22.362070: val_loss -0.7595 +2024-11-22 04:38:22.362187: Pseudo dice [0.8399] +2024-11-22 04:38:22.362269: Epoch time: 18.8 s +2024-11-22 04:38:23.545616: +2024-11-22 04:38:23.545827: Epoch 3228 +2024-11-22 04:38:23.545939: Current learning rate: 0.00628 +2024-11-22 04:38:41.845339: train_loss -0.7826 +2024-11-22 04:38:41.850939: val_loss -0.7713 +2024-11-22 04:38:41.851051: Pseudo dice [0.8521] +2024-11-22 04:38:41.851142: Epoch time: 18.3 s +2024-11-22 04:38:42.763330: +2024-11-22 04:38:42.763540: Epoch 3229 +2024-11-22 04:38:42.763655: Current learning rate: 0.00628 +2024-11-22 04:39:01.144849: train_loss -0.7809 +2024-11-22 04:39:01.146760: val_loss -0.7707 +2024-11-22 04:39:01.146862: Pseudo dice [0.8627] +2024-11-22 04:39:01.146942: Epoch time: 18.38 s +2024-11-22 04:39:01.993994: +2024-11-22 04:39:01.994212: Epoch 3230 +2024-11-22 04:39:01.994323: Current learning rate: 0.00628 +2024-11-22 04:39:20.997442: train_loss -0.7845 +2024-11-22 04:39:21.005157: val_loss -0.7775 +2024-11-22 04:39:21.005313: Pseudo dice [0.8496] +2024-11-22 04:39:21.005403: Epoch time: 19.0 s +2024-11-22 04:39:21.867340: +2024-11-22 04:39:21.867537: Epoch 3231 +2024-11-22 04:39:21.867663: Current learning rate: 0.00628 +2024-11-22 04:39:40.605559: train_loss -0.7813 +2024-11-22 04:39:40.612808: val_loss -0.7526 +2024-11-22 04:39:40.612940: Pseudo dice [0.84] +2024-11-22 04:39:40.613039: Epoch time: 18.74 s +2024-11-22 04:39:41.554207: +2024-11-22 04:39:41.554424: Epoch 3232 +2024-11-22 04:39:41.554553: Current learning rate: 0.00628 +2024-11-22 04:40:01.841993: train_loss -0.7792 +2024-11-22 04:40:01.848661: val_loss -0.7559 +2024-11-22 04:40:01.848788: Pseudo dice [0.8575] +2024-11-22 04:40:01.848904: Epoch time: 20.29 s +2024-11-22 04:40:02.745713: +2024-11-22 04:40:02.745931: Epoch 3233 +2024-11-22 04:40:02.746054: Current learning rate: 0.00628 +2024-11-22 04:40:22.148422: train_loss -0.7748 +2024-11-22 04:40:22.155850: val_loss -0.7683 +2024-11-22 04:40:22.155963: Pseudo dice [0.8586] +2024-11-22 04:40:22.156044: Epoch time: 19.4 s +2024-11-22 04:40:23.122648: +2024-11-22 04:40:23.122858: Epoch 3234 +2024-11-22 04:40:23.122982: Current learning rate: 0.00627 +2024-11-22 04:40:42.310609: train_loss -0.7639 +2024-11-22 04:40:42.312391: val_loss -0.7851 +2024-11-22 04:40:42.312485: Pseudo dice [0.8557] +2024-11-22 04:40:42.312568: Epoch time: 19.19 s +2024-11-22 04:40:43.554024: +2024-11-22 04:40:43.554244: Epoch 3235 +2024-11-22 04:40:43.554358: Current learning rate: 0.00627 +2024-11-22 04:41:02.404837: train_loss -0.7758 +2024-11-22 04:41:02.407085: val_loss -0.7695 +2024-11-22 04:41:02.407211: Pseudo dice [0.8424] +2024-11-22 04:41:02.407301: Epoch time: 18.85 s +2024-11-22 04:41:03.269622: +2024-11-22 04:41:03.269834: Epoch 3236 +2024-11-22 04:41:03.269946: Current learning rate: 0.00627 +2024-11-22 04:41:21.754459: train_loss -0.7777 +2024-11-22 04:41:21.758296: val_loss -0.7619 +2024-11-22 04:41:21.758428: Pseudo dice [0.8349] +2024-11-22 04:41:21.758508: Epoch time: 18.49 s +2024-11-22 04:41:22.602639: +2024-11-22 04:41:22.602864: Epoch 3237 +2024-11-22 04:41:22.602978: Current learning rate: 0.00627 +2024-11-22 04:41:41.628928: train_loss -0.7716 +2024-11-22 04:41:41.636247: val_loss -0.763 +2024-11-22 04:41:41.636360: Pseudo dice [0.8438] +2024-11-22 04:41:41.636443: Epoch time: 19.03 s +2024-11-22 04:41:42.510302: +2024-11-22 04:41:42.510510: Epoch 3238 +2024-11-22 04:41:42.510632: Current learning rate: 0.00627 +2024-11-22 04:42:00.356100: train_loss -0.7821 +2024-11-22 04:42:00.357659: val_loss -0.7436 +2024-11-22 04:42:00.357827: Pseudo dice [0.8491] +2024-11-22 04:42:00.357908: Epoch time: 17.85 s +2024-11-22 04:42:01.397230: +2024-11-22 04:42:01.397469: Epoch 3239 +2024-11-22 04:42:01.397586: Current learning rate: 0.00627 +2024-11-22 04:42:20.643918: train_loss -0.783 +2024-11-22 04:42:20.649327: val_loss -0.7551 +2024-11-22 04:42:20.649459: Pseudo dice [0.8487] +2024-11-22 04:42:20.649552: Epoch time: 19.25 s +2024-11-22 04:42:21.535556: +2024-11-22 04:42:21.535760: Epoch 3240 +2024-11-22 04:42:21.535874: Current learning rate: 0.00627 +2024-11-22 04:42:41.171576: train_loss -0.7894 +2024-11-22 04:42:41.177431: val_loss -0.7763 +2024-11-22 04:42:41.177561: Pseudo dice [0.8467] +2024-11-22 04:42:41.177646: Epoch time: 19.64 s +2024-11-22 04:42:42.123017: +2024-11-22 04:42:42.123245: Epoch 3241 +2024-11-22 04:42:42.123356: Current learning rate: 0.00627 +2024-11-22 04:43:00.643132: train_loss -0.7824 +2024-11-22 04:43:00.647249: val_loss -0.7992 +2024-11-22 04:43:00.647358: Pseudo dice [0.8619] +2024-11-22 04:43:00.647434: Epoch time: 18.52 s +2024-11-22 04:43:01.671226: +2024-11-22 04:43:01.671427: Epoch 3242 +2024-11-22 04:43:01.671542: Current learning rate: 0.00626 +2024-11-22 04:43:20.704437: train_loss -0.7872 +2024-11-22 04:43:20.710949: val_loss -0.7744 +2024-11-22 04:43:20.711056: Pseudo dice [0.8443] +2024-11-22 04:43:20.711144: Epoch time: 19.03 s +2024-11-22 04:43:21.606175: +2024-11-22 04:43:21.606395: Epoch 3243 +2024-11-22 04:43:21.606512: Current learning rate: 0.00626 +2024-11-22 04:43:39.662395: train_loss -0.7874 +2024-11-22 04:43:39.668967: val_loss -0.7774 +2024-11-22 04:43:39.669089: Pseudo dice [0.8544] +2024-11-22 04:43:39.669174: Epoch time: 18.06 s +2024-11-22 04:43:40.684120: +2024-11-22 04:43:40.684317: Epoch 3244 +2024-11-22 04:43:40.684448: Current learning rate: 0.00626 +2024-11-22 04:43:59.582946: train_loss -0.7888 +2024-11-22 04:43:59.584646: val_loss -0.7528 +2024-11-22 04:43:59.584736: Pseudo dice [0.8533] +2024-11-22 04:43:59.584816: Epoch time: 18.9 s +2024-11-22 04:44:00.426855: +2024-11-22 04:44:00.427047: Epoch 3245 +2024-11-22 04:44:00.427164: Current learning rate: 0.00626 +2024-11-22 04:44:19.760888: train_loss -0.7897 +2024-11-22 04:44:19.768868: val_loss -0.7551 +2024-11-22 04:44:19.768998: Pseudo dice [0.8484] +2024-11-22 04:44:19.769083: Epoch time: 19.33 s +2024-11-22 04:44:21.013072: +2024-11-22 04:44:21.013299: Epoch 3246 +2024-11-22 04:44:21.013410: Current learning rate: 0.00626 +2024-11-22 04:44:40.043482: train_loss -0.7833 +2024-11-22 04:44:40.047220: val_loss -0.7395 +2024-11-22 04:44:40.047338: Pseudo dice [0.8563] +2024-11-22 04:44:40.047429: Epoch time: 19.03 s +2024-11-22 04:44:40.897899: +2024-11-22 04:44:40.898103: Epoch 3247 +2024-11-22 04:44:40.898217: Current learning rate: 0.00626 +2024-11-22 04:45:01.263947: train_loss -0.7815 +2024-11-22 04:45:01.269049: val_loss -0.7526 +2024-11-22 04:45:01.269385: Pseudo dice [0.8615] +2024-11-22 04:45:01.269734: Epoch time: 20.37 s +2024-11-22 04:45:02.133465: +2024-11-22 04:45:02.133662: Epoch 3248 +2024-11-22 04:45:02.133769: Current learning rate: 0.00626 +2024-11-22 04:45:20.835246: train_loss -0.7934 +2024-11-22 04:45:20.839999: val_loss -0.7734 +2024-11-22 04:45:20.840116: Pseudo dice [0.8547] +2024-11-22 04:45:20.840197: Epoch time: 18.7 s +2024-11-22 04:45:21.694823: +2024-11-22 04:45:21.695099: Epoch 3249 +2024-11-22 04:45:21.695212: Current learning rate: 0.00626 +2024-11-22 04:45:41.433053: train_loss -0.7864 +2024-11-22 04:45:41.438586: val_loss -0.7705 +2024-11-22 04:45:41.438704: Pseudo dice [0.8525] +2024-11-22 04:45:41.438782: Epoch time: 19.74 s +2024-11-22 04:45:42.532224: +2024-11-22 04:45:42.532437: Epoch 3250 +2024-11-22 04:45:42.532550: Current learning rate: 0.00626 +2024-11-22 04:46:01.151269: train_loss -0.7881 +2024-11-22 04:46:01.152672: val_loss -0.758 +2024-11-22 04:46:01.152768: Pseudo dice [0.8493] +2024-11-22 04:46:01.152860: Epoch time: 18.62 s +2024-11-22 04:46:02.000370: +2024-11-22 04:46:02.000582: Epoch 3251 +2024-11-22 04:46:02.000695: Current learning rate: 0.00625 +2024-11-22 04:46:21.050303: train_loss -0.7846 +2024-11-22 04:46:21.054912: val_loss -0.7721 +2024-11-22 04:46:21.055044: Pseudo dice [0.8484] +2024-11-22 04:46:21.055130: Epoch time: 19.05 s +2024-11-22 04:46:22.019782: +2024-11-22 04:46:22.020010: Epoch 3252 +2024-11-22 04:46:22.020126: Current learning rate: 0.00625 +2024-11-22 04:46:41.224130: train_loss -0.7878 +2024-11-22 04:46:41.239896: val_loss -0.768 +2024-11-22 04:46:41.240048: Pseudo dice [0.8446] +2024-11-22 04:46:41.240144: Epoch time: 19.21 s +2024-11-22 04:46:42.184843: +2024-11-22 04:46:42.185120: Epoch 3253 +2024-11-22 04:46:42.185238: Current learning rate: 0.00625 +2024-11-22 04:47:01.704939: train_loss -0.7867 +2024-11-22 04:47:01.715693: val_loss -0.7827 +2024-11-22 04:47:01.715854: Pseudo dice [0.8491] +2024-11-22 04:47:01.715943: Epoch time: 19.52 s +2024-11-22 04:47:02.674127: +2024-11-22 04:47:02.674365: Epoch 3254 +2024-11-22 04:47:02.674479: Current learning rate: 0.00625 +2024-11-22 04:47:21.098620: train_loss -0.7891 +2024-11-22 04:47:21.100478: val_loss -0.7753 +2024-11-22 04:47:21.100578: Pseudo dice [0.8575] +2024-11-22 04:47:21.100660: Epoch time: 18.43 s +2024-11-22 04:47:21.953554: +2024-11-22 04:47:21.953769: Epoch 3255 +2024-11-22 04:47:21.953882: Current learning rate: 0.00625 +2024-11-22 04:47:40.120094: train_loss -0.7884 +2024-11-22 04:47:40.124103: val_loss -0.7524 +2024-11-22 04:47:40.124242: Pseudo dice [0.8494] +2024-11-22 04:47:40.124328: Epoch time: 18.17 s +2024-11-22 04:47:41.081506: +2024-11-22 04:47:41.081732: Epoch 3256 +2024-11-22 04:47:41.081845: Current learning rate: 0.00625 +2024-11-22 04:47:59.853000: train_loss -0.7808 +2024-11-22 04:47:59.858135: val_loss -0.7653 +2024-11-22 04:47:59.858246: Pseudo dice [0.8544] +2024-11-22 04:47:59.858330: Epoch time: 18.77 s +2024-11-22 04:48:01.107553: +2024-11-22 04:48:01.107750: Epoch 3257 +2024-11-22 04:48:01.107860: Current learning rate: 0.00625 +2024-11-22 04:48:19.138661: train_loss -0.7778 +2024-11-22 04:48:19.140276: val_loss -0.7863 +2024-11-22 04:48:19.140382: Pseudo dice [0.8621] +2024-11-22 04:48:19.140469: Epoch time: 18.03 s +2024-11-22 04:48:20.047706: +2024-11-22 04:48:20.047925: Epoch 3258 +2024-11-22 04:48:20.048038: Current learning rate: 0.00625 +2024-11-22 04:48:38.908738: train_loss -0.7843 +2024-11-22 04:48:38.916116: val_loss -0.7679 +2024-11-22 04:48:38.916223: Pseudo dice [0.8582] +2024-11-22 04:48:38.916300: Epoch time: 18.86 s +2024-11-22 04:48:39.916067: +2024-11-22 04:48:39.916270: Epoch 3259 +2024-11-22 04:48:39.916379: Current learning rate: 0.00624 +2024-11-22 04:48:58.869004: train_loss -0.7857 +2024-11-22 04:48:58.870549: val_loss -0.7492 +2024-11-22 04:48:58.870649: Pseudo dice [0.845] +2024-11-22 04:48:58.870725: Epoch time: 18.95 s +2024-11-22 04:48:59.775057: +2024-11-22 04:48:59.775310: Epoch 3260 +2024-11-22 04:48:59.775424: Current learning rate: 0.00624 +2024-11-22 04:49:19.054706: train_loss -0.7848 +2024-11-22 04:49:19.061801: val_loss -0.7806 +2024-11-22 04:49:19.061936: Pseudo dice [0.8468] +2024-11-22 04:49:19.062020: Epoch time: 19.28 s +2024-11-22 04:49:19.925381: +2024-11-22 04:49:19.925628: Epoch 3261 +2024-11-22 04:49:19.925757: Current learning rate: 0.00624 +2024-11-22 04:49:38.647948: train_loss -0.7782 +2024-11-22 04:49:38.655254: val_loss -0.7421 +2024-11-22 04:49:38.655395: Pseudo dice [0.8435] +2024-11-22 04:49:38.655486: Epoch time: 18.72 s +2024-11-22 04:49:39.590159: +2024-11-22 04:49:39.590400: Epoch 3262 +2024-11-22 04:49:39.590527: Current learning rate: 0.00624 +2024-11-22 04:49:59.115913: train_loss -0.7776 +2024-11-22 04:49:59.122952: val_loss -0.74 +2024-11-22 04:49:59.123081: Pseudo dice [0.8473] +2024-11-22 04:49:59.123170: Epoch time: 19.53 s +2024-11-22 04:49:59.979959: +2024-11-22 04:49:59.980156: Epoch 3263 +2024-11-22 04:49:59.980279: Current learning rate: 0.00624 +2024-11-22 04:50:19.188118: train_loss -0.7618 +2024-11-22 04:50:19.189641: val_loss -0.7335 +2024-11-22 04:50:19.189764: Pseudo dice [0.8143] +2024-11-22 04:50:19.189842: Epoch time: 19.21 s +2024-11-22 04:50:20.033994: +2024-11-22 04:50:20.034200: Epoch 3264 +2024-11-22 04:50:20.034309: Current learning rate: 0.00624 +2024-11-22 04:50:39.195286: train_loss -0.7658 +2024-11-22 04:50:39.197404: val_loss -0.7385 +2024-11-22 04:50:39.197539: Pseudo dice [0.8428] +2024-11-22 04:50:39.197622: Epoch time: 19.16 s +2024-11-22 04:50:40.050858: +2024-11-22 04:50:40.051071: Epoch 3265 +2024-11-22 04:50:40.051187: Current learning rate: 0.00624 +2024-11-22 04:50:58.862053: train_loss -0.7736 +2024-11-22 04:50:58.863490: val_loss -0.7561 +2024-11-22 04:50:58.863577: Pseudo dice [0.8401] +2024-11-22 04:50:58.863657: Epoch time: 18.81 s +2024-11-22 04:50:59.705362: +2024-11-22 04:50:59.705563: Epoch 3266 +2024-11-22 04:50:59.705677: Current learning rate: 0.00624 +2024-11-22 04:51:17.560475: train_loss -0.7739 +2024-11-22 04:51:17.564896: val_loss -0.7782 +2024-11-22 04:51:17.565006: Pseudo dice [0.8556] +2024-11-22 04:51:17.565092: Epoch time: 17.86 s +2024-11-22 04:51:18.547379: +2024-11-22 04:51:18.547591: Epoch 3267 +2024-11-22 04:51:18.547705: Current learning rate: 0.00624 +2024-11-22 04:51:37.874638: train_loss -0.7567 +2024-11-22 04:51:37.880005: val_loss -0.7353 +2024-11-22 04:51:37.880142: Pseudo dice [0.8473] +2024-11-22 04:51:37.880222: Epoch time: 19.33 s +2024-11-22 04:51:39.384802: +2024-11-22 04:51:39.385009: Epoch 3268 +2024-11-22 04:51:39.385128: Current learning rate: 0.00623 +2024-11-22 04:51:58.184816: train_loss -0.7783 +2024-11-22 04:51:58.191943: val_loss -0.7489 +2024-11-22 04:51:58.192079: Pseudo dice [0.8535] +2024-11-22 04:51:58.192166: Epoch time: 18.8 s +2024-11-22 04:51:59.094509: +2024-11-22 04:51:59.094702: Epoch 3269 +2024-11-22 04:51:59.094811: Current learning rate: 0.00623 +2024-11-22 04:52:17.829666: train_loss -0.7851 +2024-11-22 04:52:17.835282: val_loss -0.7737 +2024-11-22 04:52:17.835404: Pseudo dice [0.8389] +2024-11-22 04:52:17.835486: Epoch time: 18.74 s +2024-11-22 04:52:18.700305: +2024-11-22 04:52:18.700530: Epoch 3270 +2024-11-22 04:52:18.700644: Current learning rate: 0.00623 +2024-11-22 04:52:37.675586: train_loss -0.7879 +2024-11-22 04:52:37.677452: val_loss -0.7484 +2024-11-22 04:52:37.677537: Pseudo dice [0.8432] +2024-11-22 04:52:37.677612: Epoch time: 18.98 s +2024-11-22 04:52:38.517408: +2024-11-22 04:52:38.517609: Epoch 3271 +2024-11-22 04:52:38.517720: Current learning rate: 0.00623 +2024-11-22 04:52:58.230315: train_loss -0.7713 +2024-11-22 04:52:58.233662: val_loss -0.7922 +2024-11-22 04:52:58.233788: Pseudo dice [0.8611] +2024-11-22 04:52:58.233869: Epoch time: 19.71 s +2024-11-22 04:52:59.183333: +2024-11-22 04:52:59.183553: Epoch 3272 +2024-11-22 04:52:59.183662: Current learning rate: 0.00623 +2024-11-22 04:53:18.080191: train_loss -0.7754 +2024-11-22 04:53:18.087156: val_loss -0.7655 +2024-11-22 04:53:18.087315: Pseudo dice [0.8613] +2024-11-22 04:53:18.087507: Epoch time: 18.9 s +2024-11-22 04:53:18.948114: +2024-11-22 04:53:18.948538: Epoch 3273 +2024-11-22 04:53:18.948659: Current learning rate: 0.00623 +2024-11-22 04:53:37.377738: train_loss -0.7771 +2024-11-22 04:53:37.380708: val_loss -0.7418 +2024-11-22 04:53:37.381071: Pseudo dice [0.8517] +2024-11-22 04:53:37.381161: Epoch time: 18.43 s +2024-11-22 04:53:38.247918: +2024-11-22 04:53:38.248142: Epoch 3274 +2024-11-22 04:53:38.248254: Current learning rate: 0.00623 +2024-11-22 04:53:57.083151: train_loss -0.7719 +2024-11-22 04:53:57.084570: val_loss -0.7843 +2024-11-22 04:53:57.084656: Pseudo dice [0.855] +2024-11-22 04:53:57.084730: Epoch time: 18.84 s +2024-11-22 04:53:57.923271: +2024-11-22 04:53:57.923497: Epoch 3275 +2024-11-22 04:53:57.923613: Current learning rate: 0.00623 +2024-11-22 04:54:16.231973: train_loss -0.7781 +2024-11-22 04:54:16.237462: val_loss -0.7544 +2024-11-22 04:54:16.237595: Pseudo dice [0.8541] +2024-11-22 04:54:16.237683: Epoch time: 18.31 s +2024-11-22 04:54:17.250869: +2024-11-22 04:54:17.251146: Epoch 3276 +2024-11-22 04:54:17.251259: Current learning rate: 0.00622 +2024-11-22 04:54:36.297867: train_loss -0.7795 +2024-11-22 04:54:36.299727: val_loss -0.7528 +2024-11-22 04:54:36.299858: Pseudo dice [0.8535] +2024-11-22 04:54:36.299951: Epoch time: 19.05 s +2024-11-22 04:54:37.144780: +2024-11-22 04:54:37.145007: Epoch 3277 +2024-11-22 04:54:37.145128: Current learning rate: 0.00622 +2024-11-22 04:54:55.663559: train_loss -0.7801 +2024-11-22 04:54:55.669746: val_loss -0.7539 +2024-11-22 04:54:55.669859: Pseudo dice [0.835] +2024-11-22 04:54:55.669937: Epoch time: 18.52 s +2024-11-22 04:54:56.628912: +2024-11-22 04:54:56.629124: Epoch 3278 +2024-11-22 04:54:56.629242: Current learning rate: 0.00622 +2024-11-22 04:55:14.863162: train_loss -0.776 +2024-11-22 04:55:14.865418: val_loss -0.7627 +2024-11-22 04:55:14.865549: Pseudo dice [0.8385] +2024-11-22 04:55:14.865627: Epoch time: 18.24 s +2024-11-22 04:55:16.107627: +2024-11-22 04:55:16.107827: Epoch 3279 +2024-11-22 04:55:16.107943: Current learning rate: 0.00622 +2024-11-22 04:55:34.988581: train_loss -0.7752 +2024-11-22 04:55:34.995544: val_loss -0.7777 +2024-11-22 04:55:34.995752: Pseudo dice [0.8486] +2024-11-22 04:55:34.995841: Epoch time: 18.88 s +2024-11-22 04:55:35.856119: +2024-11-22 04:55:35.856378: Epoch 3280 +2024-11-22 04:55:35.856504: Current learning rate: 0.00622 +2024-11-22 04:55:55.798898: train_loss -0.7769 +2024-11-22 04:55:55.800375: val_loss -0.7649 +2024-11-22 04:55:55.800470: Pseudo dice [0.8454] +2024-11-22 04:55:55.800632: Epoch time: 19.94 s +2024-11-22 04:55:56.646033: +2024-11-22 04:55:56.646268: Epoch 3281 +2024-11-22 04:55:56.646378: Current learning rate: 0.00622 +2024-11-22 04:56:15.614568: train_loss -0.7803 +2024-11-22 04:56:15.624982: val_loss -0.7845 +2024-11-22 04:56:15.625120: Pseudo dice [0.8477] +2024-11-22 04:56:15.625202: Epoch time: 18.97 s +2024-11-22 04:56:16.589113: +2024-11-22 04:56:16.589321: Epoch 3282 +2024-11-22 04:56:16.589437: Current learning rate: 0.00622 +2024-11-22 04:56:35.092423: train_loss -0.793 +2024-11-22 04:56:35.099644: val_loss -0.7693 +2024-11-22 04:56:35.099766: Pseudo dice [0.8544] +2024-11-22 04:56:35.099843: Epoch time: 18.5 s +2024-11-22 04:56:36.096462: +2024-11-22 04:56:36.096663: Epoch 3283 +2024-11-22 04:56:36.096777: Current learning rate: 0.00622 +2024-11-22 04:56:55.079550: train_loss -0.7687 +2024-11-22 04:56:55.081437: val_loss -0.7655 +2024-11-22 04:56:55.081560: Pseudo dice [0.8461] +2024-11-22 04:56:55.081645: Epoch time: 18.98 s +2024-11-22 04:56:56.035553: +2024-11-22 04:56:56.035769: Epoch 3284 +2024-11-22 04:56:56.035883: Current learning rate: 0.00621 +2024-11-22 04:57:14.465174: train_loss -0.7768 +2024-11-22 04:57:14.486488: val_loss -0.7504 +2024-11-22 04:57:14.486616: Pseudo dice [0.8627] +2024-11-22 04:57:14.486700: Epoch time: 18.43 s +2024-11-22 04:57:15.351108: +2024-11-22 04:57:15.351350: Epoch 3285 +2024-11-22 04:57:15.351469: Current learning rate: 0.00621 +2024-11-22 04:57:33.356970: train_loss -0.7862 +2024-11-22 04:57:33.365899: val_loss -0.7562 +2024-11-22 04:57:33.366017: Pseudo dice [0.852] +2024-11-22 04:57:33.366337: Epoch time: 18.01 s +2024-11-22 04:57:34.231702: +2024-11-22 04:57:34.231908: Epoch 3286 +2024-11-22 04:57:34.232018: Current learning rate: 0.00621 +2024-11-22 04:57:51.867940: train_loss -0.7865 +2024-11-22 04:57:51.876615: val_loss -0.7786 +2024-11-22 04:57:51.876768: Pseudo dice [0.8577] +2024-11-22 04:57:51.876854: Epoch time: 17.64 s +2024-11-22 04:57:52.908948: +2024-11-22 04:57:52.909158: Epoch 3287 +2024-11-22 04:57:52.909278: Current learning rate: 0.00621 +2024-11-22 04:58:12.088484: train_loss -0.7834 +2024-11-22 04:58:12.094054: val_loss -0.783 +2024-11-22 04:58:12.094217: Pseudo dice [0.8538] +2024-11-22 04:58:12.094337: Epoch time: 19.18 s +2024-11-22 04:58:12.953904: +2024-11-22 04:58:12.954123: Epoch 3288 +2024-11-22 04:58:12.954241: Current learning rate: 0.00621 +2024-11-22 04:58:31.578827: train_loss -0.7941 +2024-11-22 04:58:31.581306: val_loss -0.7828 +2024-11-22 04:58:31.581418: Pseudo dice [0.8592] +2024-11-22 04:58:31.581495: Epoch time: 18.62 s +2024-11-22 04:58:32.615314: +2024-11-22 04:58:32.615534: Epoch 3289 +2024-11-22 04:58:32.615645: Current learning rate: 0.00621 +2024-11-22 04:58:51.602175: train_loss -0.7755 +2024-11-22 04:58:51.614028: val_loss -0.7708 +2024-11-22 04:58:51.614153: Pseudo dice [0.8468] +2024-11-22 04:58:51.614236: Epoch time: 18.99 s +2024-11-22 04:58:53.009243: +2024-11-22 04:58:53.009460: Epoch 3290 +2024-11-22 04:58:53.009578: Current learning rate: 0.00621 +2024-11-22 04:59:12.107508: train_loss -0.774 +2024-11-22 04:59:12.115124: val_loss -0.7733 +2024-11-22 04:59:12.115234: Pseudo dice [0.8542] +2024-11-22 04:59:12.115324: Epoch time: 19.1 s +2024-11-22 04:59:12.965110: +2024-11-22 04:59:12.965309: Epoch 3291 +2024-11-22 04:59:12.965420: Current learning rate: 0.00621 +2024-11-22 04:59:31.050225: train_loss -0.7756 +2024-11-22 04:59:31.060245: val_loss -0.7805 +2024-11-22 04:59:31.060363: Pseudo dice [0.8404] +2024-11-22 04:59:31.060443: Epoch time: 18.09 s +2024-11-22 04:59:32.127947: +2024-11-22 04:59:32.128166: Epoch 3292 +2024-11-22 04:59:32.128278: Current learning rate: 0.00621 +2024-11-22 04:59:50.894411: train_loss -0.7817 +2024-11-22 04:59:50.900954: val_loss -0.7908 +2024-11-22 04:59:50.901127: Pseudo dice [0.8556] +2024-11-22 04:59:50.901210: Epoch time: 18.77 s +2024-11-22 04:59:51.760773: +2024-11-22 04:59:51.760975: Epoch 3293 +2024-11-22 04:59:51.761092: Current learning rate: 0.0062 +2024-11-22 05:00:10.467713: train_loss -0.7762 +2024-11-22 05:00:10.476005: val_loss -0.7713 +2024-11-22 05:00:10.476139: Pseudo dice [0.8677] +2024-11-22 05:00:10.476269: Epoch time: 18.71 s +2024-11-22 05:00:11.409917: +2024-11-22 05:00:11.410148: Epoch 3294 +2024-11-22 05:00:11.410285: Current learning rate: 0.0062 +2024-11-22 05:00:29.769457: train_loss -0.7766 +2024-11-22 05:00:29.778389: val_loss -0.7737 +2024-11-22 05:00:29.778522: Pseudo dice [0.841] +2024-11-22 05:00:29.778611: Epoch time: 18.36 s +2024-11-22 05:00:30.636913: +2024-11-22 05:00:30.637157: Epoch 3295 +2024-11-22 05:00:30.637265: Current learning rate: 0.0062 +2024-11-22 05:00:50.421793: train_loss -0.7798 +2024-11-22 05:00:50.434139: val_loss -0.7672 +2024-11-22 05:00:50.434268: Pseudo dice [0.8589] +2024-11-22 05:00:50.434347: Epoch time: 19.79 s +2024-11-22 05:00:51.287323: +2024-11-22 05:00:51.287513: Epoch 3296 +2024-11-22 05:00:51.287626: Current learning rate: 0.0062 +2024-11-22 05:01:11.082831: train_loss -0.777 +2024-11-22 05:01:11.095276: val_loss -0.7715 +2024-11-22 05:01:11.095399: Pseudo dice [0.8546] +2024-11-22 05:01:11.095483: Epoch time: 19.8 s +2024-11-22 05:01:11.942276: +2024-11-22 05:01:11.942505: Epoch 3297 +2024-11-22 05:01:11.942614: Current learning rate: 0.0062 +2024-11-22 05:01:30.733291: train_loss -0.793 +2024-11-22 05:01:30.739074: val_loss -0.7876 +2024-11-22 05:01:30.739192: Pseudo dice [0.8474] +2024-11-22 05:01:30.739277: Epoch time: 18.79 s +2024-11-22 05:01:31.585716: +2024-11-22 05:01:31.585964: Epoch 3298 +2024-11-22 05:01:31.586080: Current learning rate: 0.0062 +2024-11-22 05:01:49.844647: train_loss -0.7751 +2024-11-22 05:01:49.847119: val_loss -0.7682 +2024-11-22 05:01:49.847207: Pseudo dice [0.8439] +2024-11-22 05:01:49.847284: Epoch time: 18.26 s +2024-11-22 05:01:50.697953: +2024-11-22 05:01:50.698171: Epoch 3299 +2024-11-22 05:01:50.698284: Current learning rate: 0.0062 +2024-11-22 05:02:08.960729: train_loss -0.7767 +2024-11-22 05:02:08.966362: val_loss -0.7892 +2024-11-22 05:02:08.966714: Pseudo dice [0.8512] +2024-11-22 05:02:08.966806: Epoch time: 18.26 s +2024-11-22 05:02:10.122457: +2024-11-22 05:02:10.122682: Epoch 3300 +2024-11-22 05:02:10.122793: Current learning rate: 0.0062 +2024-11-22 05:02:29.184354: train_loss -0.7817 +2024-11-22 05:02:29.191023: val_loss -0.7748 +2024-11-22 05:02:29.191213: Pseudo dice [0.8463] +2024-11-22 05:02:29.191308: Epoch time: 19.06 s +2024-11-22 05:02:30.794784: +2024-11-22 05:02:30.794984: Epoch 3301 +2024-11-22 05:02:30.795108: Current learning rate: 0.00619 +2024-11-22 05:02:49.267420: train_loss -0.7879 +2024-11-22 05:02:49.274545: val_loss -0.7724 +2024-11-22 05:02:49.274660: Pseudo dice [0.8508] +2024-11-22 05:02:49.274746: Epoch time: 18.47 s +2024-11-22 05:02:50.204098: +2024-11-22 05:02:50.204324: Epoch 3302 +2024-11-22 05:02:50.204435: Current learning rate: 0.00619 +2024-11-22 05:03:08.325974: train_loss -0.7845 +2024-11-22 05:03:08.335390: val_loss -0.7672 +2024-11-22 05:03:08.335515: Pseudo dice [0.8683] +2024-11-22 05:03:08.335604: Epoch time: 18.12 s +2024-11-22 05:03:09.183386: +2024-11-22 05:03:09.183616: Epoch 3303 +2024-11-22 05:03:09.183727: Current learning rate: 0.00619 +2024-11-22 05:03:28.384618: train_loss -0.7871 +2024-11-22 05:03:28.391145: val_loss -0.762 +2024-11-22 05:03:28.391270: Pseudo dice [0.843] +2024-11-22 05:03:28.391355: Epoch time: 19.2 s +2024-11-22 05:03:29.333331: +2024-11-22 05:03:29.333565: Epoch 3304 +2024-11-22 05:03:29.333679: Current learning rate: 0.00619 +2024-11-22 05:03:48.507531: train_loss -0.7804 +2024-11-22 05:03:48.515961: val_loss -0.7751 +2024-11-22 05:03:48.516083: Pseudo dice [0.8635] +2024-11-22 05:03:48.516162: Epoch time: 19.17 s +2024-11-22 05:03:49.492294: +2024-11-22 05:03:49.492496: Epoch 3305 +2024-11-22 05:03:49.492608: Current learning rate: 0.00619 +2024-11-22 05:04:08.915287: train_loss -0.7745 +2024-11-22 05:04:08.923615: val_loss -0.7479 +2024-11-22 05:04:08.923728: Pseudo dice [0.85] +2024-11-22 05:04:08.923826: Epoch time: 19.42 s +2024-11-22 05:04:10.310997: +2024-11-22 05:04:10.311194: Epoch 3306 +2024-11-22 05:04:10.311309: Current learning rate: 0.00619 +2024-11-22 05:04:29.972251: train_loss -0.7742 +2024-11-22 05:04:29.975091: val_loss -0.764 +2024-11-22 05:04:29.975209: Pseudo dice [0.8438] +2024-11-22 05:04:29.975288: Epoch time: 19.66 s +2024-11-22 05:04:30.826709: +2024-11-22 05:04:30.826916: Epoch 3307 +2024-11-22 05:04:30.827030: Current learning rate: 0.00619 +2024-11-22 05:04:49.153428: train_loss -0.7783 +2024-11-22 05:04:49.160778: val_loss -0.7817 +2024-11-22 05:04:49.160905: Pseudo dice [0.8506] +2024-11-22 05:04:49.160983: Epoch time: 18.33 s +2024-11-22 05:04:50.029562: +2024-11-22 05:04:50.029789: Epoch 3308 +2024-11-22 05:04:50.029914: Current learning rate: 0.00619 +2024-11-22 05:05:09.568949: train_loss -0.7772 +2024-11-22 05:05:09.576976: val_loss -0.758 +2024-11-22 05:05:09.577143: Pseudo dice [0.8475] +2024-11-22 05:05:09.577229: Epoch time: 19.54 s +2024-11-22 05:05:10.554704: +2024-11-22 05:05:10.554913: Epoch 3309 +2024-11-22 05:05:10.555020: Current learning rate: 0.00619 +2024-11-22 05:05:29.562170: train_loss -0.7817 +2024-11-22 05:05:29.568158: val_loss -0.8 +2024-11-22 05:05:29.568277: Pseudo dice [0.8632] +2024-11-22 05:05:29.568358: Epoch time: 19.01 s +2024-11-22 05:05:30.435997: +2024-11-22 05:05:30.436203: Epoch 3310 +2024-11-22 05:05:30.436318: Current learning rate: 0.00618 +2024-11-22 05:05:50.028376: train_loss -0.7751 +2024-11-22 05:05:50.031487: val_loss -0.7659 +2024-11-22 05:05:50.031620: Pseudo dice [0.8495] +2024-11-22 05:05:50.031701: Epoch time: 19.59 s +2024-11-22 05:05:50.890299: +2024-11-22 05:05:50.890511: Epoch 3311 +2024-11-22 05:05:50.902605: Current learning rate: 0.00618 +2024-11-22 05:06:09.250307: train_loss -0.7895 +2024-11-22 05:06:09.254827: val_loss -0.7879 +2024-11-22 05:06:09.254945: Pseudo dice [0.8519] +2024-11-22 05:06:09.255028: Epoch time: 18.36 s +2024-11-22 05:06:10.726775: +2024-11-22 05:06:10.726993: Epoch 3312 +2024-11-22 05:06:10.727109: Current learning rate: 0.00618 +2024-11-22 05:06:30.411003: train_loss -0.7871 +2024-11-22 05:06:30.413111: val_loss -0.7597 +2024-11-22 05:06:30.413196: Pseudo dice [0.8366] +2024-11-22 05:06:30.413274: Epoch time: 19.69 s +2024-11-22 05:06:31.263149: +2024-11-22 05:06:31.263357: Epoch 3313 +2024-11-22 05:06:31.263465: Current learning rate: 0.00618 +2024-11-22 05:06:50.802253: train_loss -0.7757 +2024-11-22 05:06:50.813311: val_loss -0.7672 +2024-11-22 05:06:50.813423: Pseudo dice [0.8531] +2024-11-22 05:06:50.813505: Epoch time: 19.54 s +2024-11-22 05:06:51.662493: +2024-11-22 05:06:51.662692: Epoch 3314 +2024-11-22 05:06:51.662801: Current learning rate: 0.00618 +2024-11-22 05:07:10.500816: train_loss -0.776 +2024-11-22 05:07:10.506097: val_loss -0.7835 +2024-11-22 05:07:10.506203: Pseudo dice [0.8422] +2024-11-22 05:07:10.506288: Epoch time: 18.84 s +2024-11-22 05:07:11.644236: +2024-11-22 05:07:11.644435: Epoch 3315 +2024-11-22 05:07:11.644553: Current learning rate: 0.00618 +2024-11-22 05:07:31.034682: train_loss -0.7816 +2024-11-22 05:07:31.036492: val_loss -0.762 +2024-11-22 05:07:31.036610: Pseudo dice [0.8596] +2024-11-22 05:07:31.036711: Epoch time: 19.39 s +2024-11-22 05:07:31.894040: +2024-11-22 05:07:31.894246: Epoch 3316 +2024-11-22 05:07:31.894359: Current learning rate: 0.00618 +2024-11-22 05:07:51.253565: train_loss -0.7811 +2024-11-22 05:07:51.260649: val_loss -0.7756 +2024-11-22 05:07:51.260775: Pseudo dice [0.8545] +2024-11-22 05:07:51.260867: Epoch time: 19.36 s +2024-11-22 05:07:52.108361: +2024-11-22 05:07:52.108587: Epoch 3317 +2024-11-22 05:07:52.108701: Current learning rate: 0.00618 +2024-11-22 05:08:11.188568: train_loss -0.79 +2024-11-22 05:08:11.190120: val_loss -0.7671 +2024-11-22 05:08:11.190212: Pseudo dice [0.8486] +2024-11-22 05:08:11.190286: Epoch time: 19.08 s +2024-11-22 05:08:12.041778: +2024-11-22 05:08:12.042016: Epoch 3318 +2024-11-22 05:08:12.042135: Current learning rate: 0.00617 +2024-11-22 05:08:30.524271: train_loss -0.786 +2024-11-22 05:08:30.525241: val_loss -0.7711 +2024-11-22 05:08:30.525325: Pseudo dice [0.8591] +2024-11-22 05:08:30.525403: Epoch time: 18.48 s +2024-11-22 05:08:31.366498: +2024-11-22 05:08:31.366713: Epoch 3319 +2024-11-22 05:08:31.366828: Current learning rate: 0.00617 +2024-11-22 05:08:49.849661: train_loss -0.7857 +2024-11-22 05:08:49.852666: val_loss -0.7774 +2024-11-22 05:08:49.852774: Pseudo dice [0.8491] +2024-11-22 05:08:49.852854: Epoch time: 18.48 s +2024-11-22 05:08:50.732277: +2024-11-22 05:08:50.732486: Epoch 3320 +2024-11-22 05:08:50.732599: Current learning rate: 0.00617 +2024-11-22 05:09:10.616225: train_loss -0.7745 +2024-11-22 05:09:10.621526: val_loss -0.7651 +2024-11-22 05:09:10.621637: Pseudo dice [0.838] +2024-11-22 05:09:10.621729: Epoch time: 19.88 s +2024-11-22 05:09:11.535612: +2024-11-22 05:09:11.535909: Epoch 3321 +2024-11-22 05:09:11.536028: Current learning rate: 0.00617 +2024-11-22 05:09:30.895658: train_loss -0.7842 +2024-11-22 05:09:30.904150: val_loss -0.7665 +2024-11-22 05:09:30.904295: Pseudo dice [0.8605] +2024-11-22 05:09:30.904380: Epoch time: 19.36 s +2024-11-22 05:09:31.798649: +2024-11-22 05:09:31.798856: Epoch 3322 +2024-11-22 05:09:31.798972: Current learning rate: 0.00617 +2024-11-22 05:09:49.924598: train_loss -0.7861 +2024-11-22 05:09:49.932083: val_loss -0.7836 +2024-11-22 05:09:49.932214: Pseudo dice [0.8457] +2024-11-22 05:09:49.932296: Epoch time: 18.13 s +2024-11-22 05:09:51.224185: +2024-11-22 05:09:51.224386: Epoch 3323 +2024-11-22 05:09:51.224500: Current learning rate: 0.00617 +2024-11-22 05:10:10.374096: train_loss -0.7836 +2024-11-22 05:10:10.383751: val_loss -0.7812 +2024-11-22 05:10:10.383891: Pseudo dice [0.8614] +2024-11-22 05:10:10.383980: Epoch time: 19.15 s +2024-11-22 05:10:11.266446: +2024-11-22 05:10:11.266642: Epoch 3324 +2024-11-22 05:10:11.266752: Current learning rate: 0.00617 +2024-11-22 05:10:30.067922: train_loss -0.7814 +2024-11-22 05:10:30.075577: val_loss -0.799 +2024-11-22 05:10:30.075709: Pseudo dice [0.8591] +2024-11-22 05:10:30.075799: Epoch time: 18.8 s +2024-11-22 05:10:31.085377: +2024-11-22 05:10:31.085589: Epoch 3325 +2024-11-22 05:10:31.085703: Current learning rate: 0.00617 +2024-11-22 05:10:50.437139: train_loss -0.7918 +2024-11-22 05:10:50.442904: val_loss -0.7664 +2024-11-22 05:10:50.443047: Pseudo dice [0.8544] +2024-11-22 05:10:50.443135: Epoch time: 19.35 s +2024-11-22 05:10:51.299258: +2024-11-22 05:10:51.299520: Epoch 3326 +2024-11-22 05:10:51.299635: Current learning rate: 0.00617 +2024-11-22 05:11:12.054319: train_loss -0.7817 +2024-11-22 05:11:12.056261: val_loss -0.7741 +2024-11-22 05:11:12.056351: Pseudo dice [0.8422] +2024-11-22 05:11:12.056456: Epoch time: 20.76 s +2024-11-22 05:11:12.901399: +2024-11-22 05:11:12.901602: Epoch 3327 +2024-11-22 05:11:12.901712: Current learning rate: 0.00616 +2024-11-22 05:11:32.127919: train_loss -0.7815 +2024-11-22 05:11:32.134898: val_loss -0.7674 +2024-11-22 05:11:32.135039: Pseudo dice [0.8374] +2024-11-22 05:11:32.135181: Epoch time: 19.23 s +2024-11-22 05:11:33.013387: +2024-11-22 05:11:33.013611: Epoch 3328 +2024-11-22 05:11:33.013726: Current learning rate: 0.00616 +2024-11-22 05:11:51.261549: train_loss -0.7814 +2024-11-22 05:11:51.269613: val_loss -0.7658 +2024-11-22 05:11:51.269744: Pseudo dice [0.859] +2024-11-22 05:11:51.269823: Epoch time: 18.25 s +2024-11-22 05:11:52.121775: +2024-11-22 05:11:52.122023: Epoch 3329 +2024-11-22 05:11:52.122138: Current learning rate: 0.00616 +2024-11-22 05:12:11.074178: train_loss -0.7703 +2024-11-22 05:12:11.080364: val_loss -0.7677 +2024-11-22 05:12:11.080496: Pseudo dice [0.8403] +2024-11-22 05:12:11.080595: Epoch time: 18.95 s +2024-11-22 05:12:12.091413: +2024-11-22 05:12:12.091635: Epoch 3330 +2024-11-22 05:12:12.091750: Current learning rate: 0.00616 +2024-11-22 05:12:30.817317: train_loss -0.7915 +2024-11-22 05:12:30.824446: val_loss -0.7662 +2024-11-22 05:12:30.824574: Pseudo dice [0.8564] +2024-11-22 05:12:30.824660: Epoch time: 18.73 s +2024-11-22 05:12:31.782133: +2024-11-22 05:12:31.782315: Epoch 3331 +2024-11-22 05:12:31.782429: Current learning rate: 0.00616 +2024-11-22 05:12:50.559726: train_loss -0.7753 +2024-11-22 05:12:50.566711: val_loss -0.7661 +2024-11-22 05:12:50.566862: Pseudo dice [0.8517] +2024-11-22 05:12:50.566952: Epoch time: 18.78 s +2024-11-22 05:12:51.421863: +2024-11-22 05:12:51.422076: Epoch 3332 +2024-11-22 05:12:51.422182: Current learning rate: 0.00616 +2024-11-22 05:13:09.989121: train_loss -0.7726 +2024-11-22 05:13:09.996264: val_loss -0.7625 +2024-11-22 05:13:09.996379: Pseudo dice [0.8336] +2024-11-22 05:13:09.996459: Epoch time: 18.57 s +2024-11-22 05:13:11.001307: +2024-11-22 05:13:11.001551: Epoch 3333 +2024-11-22 05:13:11.001667: Current learning rate: 0.00616 +2024-11-22 05:13:29.842031: train_loss -0.7674 +2024-11-22 05:13:29.847754: val_loss -0.7521 +2024-11-22 05:13:29.847868: Pseudo dice [0.8507] +2024-11-22 05:13:29.847946: Epoch time: 18.84 s +2024-11-22 05:13:31.235786: +2024-11-22 05:13:31.236010: Epoch 3334 +2024-11-22 05:13:31.236128: Current learning rate: 0.00616 +2024-11-22 05:13:50.378440: train_loss -0.7664 +2024-11-22 05:13:50.380295: val_loss -0.7604 +2024-11-22 05:13:50.380386: Pseudo dice [0.8518] +2024-11-22 05:13:50.380470: Epoch time: 19.14 s +2024-11-22 05:13:51.238173: +2024-11-22 05:13:51.238388: Epoch 3335 +2024-11-22 05:13:51.238506: Current learning rate: 0.00615 +2024-11-22 05:14:09.947457: train_loss -0.7791 +2024-11-22 05:14:09.949535: val_loss -0.7683 +2024-11-22 05:14:09.949627: Pseudo dice [0.8351] +2024-11-22 05:14:09.949718: Epoch time: 18.71 s +2024-11-22 05:14:10.806338: +2024-11-22 05:14:10.806572: Epoch 3336 +2024-11-22 05:14:10.806683: Current learning rate: 0.00615 +2024-11-22 05:14:29.551752: train_loss -0.7696 +2024-11-22 05:14:29.558219: val_loss -0.769 +2024-11-22 05:14:29.558356: Pseudo dice [0.8516] +2024-11-22 05:14:29.558434: Epoch time: 18.75 s +2024-11-22 05:14:30.417564: +2024-11-22 05:14:30.417789: Epoch 3337 +2024-11-22 05:14:30.417901: Current learning rate: 0.00615 +2024-11-22 05:14:49.800118: train_loss -0.7825 +2024-11-22 05:14:49.807343: val_loss -0.7808 +2024-11-22 05:14:49.807463: Pseudo dice [0.8512] +2024-11-22 05:14:49.807547: Epoch time: 19.38 s +2024-11-22 05:14:50.831453: +2024-11-22 05:14:50.831674: Epoch 3338 +2024-11-22 05:14:50.831787: Current learning rate: 0.00615 +2024-11-22 05:15:10.874870: train_loss -0.7783 +2024-11-22 05:15:10.882273: val_loss -0.7667 +2024-11-22 05:15:10.882386: Pseudo dice [0.8373] +2024-11-22 05:15:10.882475: Epoch time: 20.04 s +2024-11-22 05:15:11.839456: +2024-11-22 05:15:11.839661: Epoch 3339 +2024-11-22 05:15:11.839774: Current learning rate: 0.00615 +2024-11-22 05:15:30.573468: train_loss -0.7713 +2024-11-22 05:15:30.599121: val_loss -0.7576 +2024-11-22 05:15:30.599287: Pseudo dice [0.842] +2024-11-22 05:15:30.599378: Epoch time: 18.73 s +2024-11-22 05:15:31.592525: +2024-11-22 05:15:31.592765: Epoch 3340 +2024-11-22 05:15:31.592877: Current learning rate: 0.00615 +2024-11-22 05:15:49.824386: train_loss -0.7731 +2024-11-22 05:15:49.830031: val_loss -0.7502 +2024-11-22 05:15:49.830164: Pseudo dice [0.8403] +2024-11-22 05:15:49.830246: Epoch time: 18.23 s +2024-11-22 05:15:50.692862: +2024-11-22 05:15:50.693170: Epoch 3341 +2024-11-22 05:15:50.693283: Current learning rate: 0.00615 +2024-11-22 05:16:09.608691: train_loss -0.7732 +2024-11-22 05:16:09.617436: val_loss -0.776 +2024-11-22 05:16:09.617649: Pseudo dice [0.8536] +2024-11-22 05:16:09.617771: Epoch time: 18.92 s +2024-11-22 05:16:10.509764: +2024-11-22 05:16:10.509991: Epoch 3342 +2024-11-22 05:16:10.510108: Current learning rate: 0.00615 +2024-11-22 05:16:28.991288: train_loss -0.788 +2024-11-22 05:16:28.998290: val_loss -0.7679 +2024-11-22 05:16:28.998425: Pseudo dice [0.8497] +2024-11-22 05:16:28.998513: Epoch time: 18.48 s +2024-11-22 05:16:29.993218: +2024-11-22 05:16:29.993425: Epoch 3343 +2024-11-22 05:16:29.993536: Current learning rate: 0.00614 +2024-11-22 05:16:49.198457: train_loss -0.7865 +2024-11-22 05:16:49.204781: val_loss -0.7701 +2024-11-22 05:16:49.204891: Pseudo dice [0.8553] +2024-11-22 05:16:49.204969: Epoch time: 19.21 s +2024-11-22 05:16:50.131866: +2024-11-22 05:16:50.132079: Epoch 3344 +2024-11-22 05:16:50.132196: Current learning rate: 0.00614 +2024-11-22 05:17:10.319652: train_loss -0.7954 +2024-11-22 05:17:10.321297: val_loss -0.7656 +2024-11-22 05:17:10.321398: Pseudo dice [0.8505] +2024-11-22 05:17:10.321482: Epoch time: 20.19 s +2024-11-22 05:17:11.573184: +2024-11-22 05:17:11.573391: Epoch 3345 +2024-11-22 05:17:11.573501: Current learning rate: 0.00614 +2024-11-22 05:17:30.115543: train_loss -0.7787 +2024-11-22 05:17:30.122861: val_loss -0.7798 +2024-11-22 05:17:30.122978: Pseudo dice [0.8652] +2024-11-22 05:17:30.123069: Epoch time: 18.54 s +2024-11-22 05:17:30.983056: +2024-11-22 05:17:30.983277: Epoch 3346 +2024-11-22 05:17:30.983386: Current learning rate: 0.00614 +2024-11-22 05:17:50.271821: train_loss -0.7777 +2024-11-22 05:17:50.276110: val_loss -0.7827 +2024-11-22 05:17:50.276217: Pseudo dice [0.8447] +2024-11-22 05:17:50.276324: Epoch time: 19.29 s +2024-11-22 05:17:51.138729: +2024-11-22 05:17:51.138953: Epoch 3347 +2024-11-22 05:17:51.139072: Current learning rate: 0.00614 +2024-11-22 05:18:10.376876: train_loss -0.7816 +2024-11-22 05:18:10.387354: val_loss -0.7757 +2024-11-22 05:18:10.387477: Pseudo dice [0.8454] +2024-11-22 05:18:10.387563: Epoch time: 19.24 s +2024-11-22 05:18:11.238411: +2024-11-22 05:18:11.238640: Epoch 3348 +2024-11-22 05:18:11.238754: Current learning rate: 0.00614 +2024-11-22 05:18:30.813369: train_loss -0.7912 +2024-11-22 05:18:30.820697: val_loss -0.7697 +2024-11-22 05:18:30.820824: Pseudo dice [0.852] +2024-11-22 05:18:30.820904: Epoch time: 19.58 s +2024-11-22 05:18:31.691374: +2024-11-22 05:18:31.691555: Epoch 3349 +2024-11-22 05:18:31.691670: Current learning rate: 0.00614 +2024-11-22 05:18:50.951173: train_loss -0.7781 +2024-11-22 05:18:50.952820: val_loss -0.7699 +2024-11-22 05:18:50.952907: Pseudo dice [0.8461] +2024-11-22 05:18:50.952991: Epoch time: 19.26 s +2024-11-22 05:18:52.046469: +2024-11-22 05:18:52.046690: Epoch 3350 +2024-11-22 05:18:52.046803: Current learning rate: 0.00614 +2024-11-22 05:19:11.335037: train_loss -0.7855 +2024-11-22 05:19:11.342642: val_loss -0.7786 +2024-11-22 05:19:11.342775: Pseudo dice [0.8722] +2024-11-22 05:19:11.342859: Epoch time: 19.29 s +2024-11-22 05:19:12.211499: +2024-11-22 05:19:12.211730: Epoch 3351 +2024-11-22 05:19:12.211846: Current learning rate: 0.00614 +2024-11-22 05:19:31.429433: train_loss -0.7796 +2024-11-22 05:19:31.431014: val_loss -0.7675 +2024-11-22 05:19:31.431123: Pseudo dice [0.8269] +2024-11-22 05:19:31.431206: Epoch time: 19.22 s +2024-11-22 05:19:32.277574: +2024-11-22 05:19:32.277789: Epoch 3352 +2024-11-22 05:19:32.277900: Current learning rate: 0.00613 +2024-11-22 05:19:51.260934: train_loss -0.7878 +2024-11-22 05:19:51.268204: val_loss -0.773 +2024-11-22 05:19:51.268341: Pseudo dice [0.8574] +2024-11-22 05:19:51.268420: Epoch time: 18.98 s +2024-11-22 05:19:52.139091: +2024-11-22 05:19:52.139280: Epoch 3353 +2024-11-22 05:19:52.139395: Current learning rate: 0.00613 +2024-11-22 05:20:11.250402: train_loss -0.7808 +2024-11-22 05:20:11.256179: val_loss -0.7886 +2024-11-22 05:20:11.256307: Pseudo dice [0.8375] +2024-11-22 05:20:11.256396: Epoch time: 19.11 s +2024-11-22 05:20:12.124936: +2024-11-22 05:20:12.125156: Epoch 3354 +2024-11-22 05:20:12.125267: Current learning rate: 0.00613 +2024-11-22 05:20:31.572170: train_loss -0.7828 +2024-11-22 05:20:31.579221: val_loss -0.7767 +2024-11-22 05:20:31.579325: Pseudo dice [0.8672] +2024-11-22 05:20:31.579404: Epoch time: 19.45 s +2024-11-22 05:20:32.852039: +2024-11-22 05:20:32.852274: Epoch 3355 +2024-11-22 05:20:32.852396: Current learning rate: 0.00613 +2024-11-22 05:20:51.616424: train_loss -0.7846 +2024-11-22 05:20:51.623232: val_loss -0.7616 +2024-11-22 05:20:51.623348: Pseudo dice [0.8547] +2024-11-22 05:20:51.623432: Epoch time: 18.77 s +2024-11-22 05:20:52.473412: +2024-11-22 05:20:52.473630: Epoch 3356 +2024-11-22 05:20:52.473744: Current learning rate: 0.00613 +2024-11-22 05:21:11.923400: train_loss -0.7763 +2024-11-22 05:21:11.926010: val_loss -0.763 +2024-11-22 05:21:11.926156: Pseudo dice [0.8325] +2024-11-22 05:21:11.926246: Epoch time: 19.45 s +2024-11-22 05:21:12.790731: +2024-11-22 05:21:12.790928: Epoch 3357 +2024-11-22 05:21:12.791038: Current learning rate: 0.00613 +2024-11-22 05:21:31.152403: train_loss -0.7777 +2024-11-22 05:21:31.154190: val_loss -0.7756 +2024-11-22 05:21:31.154310: Pseudo dice [0.8489] +2024-11-22 05:21:31.154390: Epoch time: 18.36 s +2024-11-22 05:21:32.052747: +2024-11-22 05:21:32.052952: Epoch 3358 +2024-11-22 05:21:32.053076: Current learning rate: 0.00613 +2024-11-22 05:21:51.215907: train_loss -0.7865 +2024-11-22 05:21:51.221606: val_loss -0.7905 +2024-11-22 05:21:51.221735: Pseudo dice [0.8602] +2024-11-22 05:21:51.221820: Epoch time: 19.16 s +2024-11-22 05:21:52.093290: +2024-11-22 05:21:52.093530: Epoch 3359 +2024-11-22 05:21:52.093642: Current learning rate: 0.00613 +2024-11-22 05:22:10.923196: train_loss -0.7812 +2024-11-22 05:22:10.929377: val_loss -0.7488 +2024-11-22 05:22:10.929502: Pseudo dice [0.8569] +2024-11-22 05:22:10.929583: Epoch time: 18.83 s +2024-11-22 05:22:11.840723: +2024-11-22 05:22:11.840957: Epoch 3360 +2024-11-22 05:22:11.841091: Current learning rate: 0.00612 +2024-11-22 05:22:32.285462: train_loss -0.7847 +2024-11-22 05:22:32.290713: val_loss -0.7534 +2024-11-22 05:22:32.290845: Pseudo dice [0.8484] +2024-11-22 05:22:32.290932: Epoch time: 20.45 s +2024-11-22 05:22:33.152967: +2024-11-22 05:22:33.153181: Epoch 3361 +2024-11-22 05:22:33.153295: Current learning rate: 0.00612 +2024-11-22 05:22:51.304806: train_loss -0.7829 +2024-11-22 05:22:51.306557: val_loss -0.7801 +2024-11-22 05:22:51.306679: Pseudo dice [0.8487] +2024-11-22 05:22:51.306765: Epoch time: 18.15 s +2024-11-22 05:22:52.260570: +2024-11-22 05:22:52.260808: Epoch 3362 +2024-11-22 05:22:52.260923: Current learning rate: 0.00612 +2024-11-22 05:23:10.299406: train_loss -0.782 +2024-11-22 05:23:10.302309: val_loss -0.7503 +2024-11-22 05:23:10.302441: Pseudo dice [0.8439] +2024-11-22 05:23:10.302529: Epoch time: 18.04 s +2024-11-22 05:23:11.189891: +2024-11-22 05:23:11.190135: Epoch 3363 +2024-11-22 05:23:11.190251: Current learning rate: 0.00612 +2024-11-22 05:23:29.539110: train_loss -0.7957 +2024-11-22 05:23:29.540599: val_loss -0.7621 +2024-11-22 05:23:29.540680: Pseudo dice [0.8502] +2024-11-22 05:23:29.540756: Epoch time: 18.35 s +2024-11-22 05:23:30.383916: +2024-11-22 05:23:30.384153: Epoch 3364 +2024-11-22 05:23:30.384266: Current learning rate: 0.00612 +2024-11-22 05:23:49.773005: train_loss -0.7882 +2024-11-22 05:23:49.774672: val_loss -0.7778 +2024-11-22 05:23:49.774788: Pseudo dice [0.8591] +2024-11-22 05:23:49.774884: Epoch time: 19.39 s +2024-11-22 05:23:50.633739: +2024-11-22 05:23:50.633942: Epoch 3365 +2024-11-22 05:23:50.634054: Current learning rate: 0.00612 +2024-11-22 05:24:09.476658: train_loss -0.7947 +2024-11-22 05:24:09.478395: val_loss -0.7689 +2024-11-22 05:24:09.478517: Pseudo dice [0.8609] +2024-11-22 05:24:09.478591: Epoch time: 18.84 s +2024-11-22 05:24:10.870647: +2024-11-22 05:24:10.870849: Epoch 3366 +2024-11-22 05:24:10.870961: Current learning rate: 0.00612 +2024-11-22 05:24:29.784745: train_loss -0.7723 +2024-11-22 05:24:29.786386: val_loss -0.7935 +2024-11-22 05:24:29.786524: Pseudo dice [0.8612] +2024-11-22 05:24:29.786608: Epoch time: 18.91 s +2024-11-22 05:24:30.672779: +2024-11-22 05:24:30.673012: Epoch 3367 +2024-11-22 05:24:30.673128: Current learning rate: 0.00612 +2024-11-22 05:24:50.113996: train_loss -0.7885 +2024-11-22 05:24:50.121145: val_loss -0.7769 +2024-11-22 05:24:50.121262: Pseudo dice [0.8618] +2024-11-22 05:24:50.121348: Epoch time: 19.44 s +2024-11-22 05:24:51.128487: +2024-11-22 05:24:51.128687: Epoch 3368 +2024-11-22 05:24:51.128797: Current learning rate: 0.00612 +2024-11-22 05:25:10.644593: train_loss -0.779 +2024-11-22 05:25:10.649600: val_loss -0.7403 +2024-11-22 05:25:10.649711: Pseudo dice [0.8463] +2024-11-22 05:25:10.649795: Epoch time: 19.52 s +2024-11-22 05:25:11.511455: +2024-11-22 05:25:11.511649: Epoch 3369 +2024-11-22 05:25:11.511758: Current learning rate: 0.00611 +2024-11-22 05:25:31.388361: train_loss -0.7882 +2024-11-22 05:25:31.394844: val_loss -0.7585 +2024-11-22 05:25:31.394971: Pseudo dice [0.859] +2024-11-22 05:25:31.395056: Epoch time: 19.88 s +2024-11-22 05:25:32.260788: +2024-11-22 05:25:32.261021: Epoch 3370 +2024-11-22 05:25:32.261146: Current learning rate: 0.00611 +2024-11-22 05:25:50.733629: train_loss -0.7819 +2024-11-22 05:25:50.737502: val_loss -0.7596 +2024-11-22 05:25:50.737672: Pseudo dice [0.8692] +2024-11-22 05:25:50.737762: Epoch time: 18.47 s +2024-11-22 05:25:50.737862: Yayy! New best EMA pseudo Dice: 0.855 +2024-11-22 05:25:52.072288: +2024-11-22 05:25:52.072531: Epoch 3371 +2024-11-22 05:25:52.072651: Current learning rate: 0.00611 +2024-11-22 05:26:10.285475: train_loss -0.7856 +2024-11-22 05:26:10.286982: val_loss -0.7681 +2024-11-22 05:26:10.287071: Pseudo dice [0.8562] +2024-11-22 05:26:10.287145: Epoch time: 18.21 s +2024-11-22 05:26:10.287208: Yayy! New best EMA pseudo Dice: 0.8552 +2024-11-22 05:26:11.375643: +2024-11-22 05:26:11.375856: Epoch 3372 +2024-11-22 05:26:11.375968: Current learning rate: 0.00611 +2024-11-22 05:26:29.264174: train_loss -0.7836 +2024-11-22 05:26:29.285291: val_loss -0.7786 +2024-11-22 05:26:29.285422: Pseudo dice [0.8456] +2024-11-22 05:26:29.285511: Epoch time: 17.89 s +2024-11-22 05:26:30.376915: +2024-11-22 05:26:30.377134: Epoch 3373 +2024-11-22 05:26:30.377251: Current learning rate: 0.00611 +2024-11-22 05:26:49.813125: train_loss -0.7787 +2024-11-22 05:26:49.821191: val_loss -0.7785 +2024-11-22 05:26:49.821307: Pseudo dice [0.849] +2024-11-22 05:26:49.821388: Epoch time: 19.44 s +2024-11-22 05:26:50.952530: +2024-11-22 05:26:50.952732: Epoch 3374 +2024-11-22 05:26:50.953053: Current learning rate: 0.00611 +2024-11-22 05:27:10.285856: train_loss -0.7653 +2024-11-22 05:27:10.288486: val_loss -0.7486 +2024-11-22 05:27:10.288610: Pseudo dice [0.8467] +2024-11-22 05:27:10.288694: Epoch time: 19.33 s +2024-11-22 05:27:11.192902: +2024-11-22 05:27:11.193118: Epoch 3375 +2024-11-22 05:27:11.193226: Current learning rate: 0.00611 +2024-11-22 05:27:28.838968: train_loss -0.779 +2024-11-22 05:27:28.844972: val_loss -0.7586 +2024-11-22 05:27:28.845090: Pseudo dice [0.858] +2024-11-22 05:27:28.845171: Epoch time: 17.65 s +2024-11-22 05:27:29.782751: +2024-11-22 05:27:29.782941: Epoch 3376 +2024-11-22 05:27:29.783050: Current learning rate: 0.00611 +2024-11-22 05:27:48.417975: train_loss -0.7722 +2024-11-22 05:27:48.421174: val_loss -0.7399 +2024-11-22 05:27:48.421289: Pseudo dice [0.8501] +2024-11-22 05:27:48.421366: Epoch time: 18.64 s +2024-11-22 05:27:49.888771: +2024-11-22 05:27:49.888971: Epoch 3377 +2024-11-22 05:27:49.889088: Current learning rate: 0.0061 +2024-11-22 05:28:09.044054: train_loss -0.7751 +2024-11-22 05:28:09.049894: val_loss -0.7744 +2024-11-22 05:28:09.050002: Pseudo dice [0.8474] +2024-11-22 05:28:09.050094: Epoch time: 19.16 s +2024-11-22 05:28:10.091041: +2024-11-22 05:28:10.091249: Epoch 3378 +2024-11-22 05:28:10.091362: Current learning rate: 0.0061 +2024-11-22 05:28:30.345961: train_loss -0.7792 +2024-11-22 05:28:30.348826: val_loss -0.7757 +2024-11-22 05:28:30.348979: Pseudo dice [0.8592] +2024-11-22 05:28:30.349064: Epoch time: 20.26 s +2024-11-22 05:28:31.206460: +2024-11-22 05:28:31.206724: Epoch 3379 +2024-11-22 05:28:31.206838: Current learning rate: 0.0061 +2024-11-22 05:28:49.410643: train_loss -0.7876 +2024-11-22 05:28:49.416023: val_loss -0.7624 +2024-11-22 05:28:49.416152: Pseudo dice [0.8464] +2024-11-22 05:28:49.416231: Epoch time: 18.2 s +2024-11-22 05:28:50.304513: +2024-11-22 05:28:50.304709: Epoch 3380 +2024-11-22 05:28:50.304816: Current learning rate: 0.0061 +2024-11-22 05:29:08.557821: train_loss -0.7832 +2024-11-22 05:29:08.572050: val_loss -0.7593 +2024-11-22 05:29:08.572175: Pseudo dice [0.8461] +2024-11-22 05:29:08.572259: Epoch time: 18.25 s +2024-11-22 05:29:09.611120: +2024-11-22 05:29:09.611317: Epoch 3381 +2024-11-22 05:29:09.611430: Current learning rate: 0.0061 +2024-11-22 05:29:28.766325: train_loss -0.7824 +2024-11-22 05:29:28.771706: val_loss -0.7404 +2024-11-22 05:29:28.771908: Pseudo dice [0.843] +2024-11-22 05:29:28.772004: Epoch time: 19.16 s +2024-11-22 05:29:29.629899: +2024-11-22 05:29:29.630114: Epoch 3382 +2024-11-22 05:29:29.630227: Current learning rate: 0.0061 +2024-11-22 05:29:48.689455: train_loss -0.7893 +2024-11-22 05:29:48.690943: val_loss -0.7717 +2024-11-22 05:29:48.691035: Pseudo dice [0.8503] +2024-11-22 05:29:48.691122: Epoch time: 19.06 s +2024-11-22 05:29:49.547379: +2024-11-22 05:29:49.547600: Epoch 3383 +2024-11-22 05:29:49.547720: Current learning rate: 0.0061 +2024-11-22 05:30:09.038861: train_loss -0.7793 +2024-11-22 05:30:09.040566: val_loss -0.7779 +2024-11-22 05:30:09.040726: Pseudo dice [0.8623] +2024-11-22 05:30:09.040817: Epoch time: 19.49 s +2024-11-22 05:30:10.175791: +2024-11-22 05:30:10.176023: Epoch 3384 +2024-11-22 05:30:10.176139: Current learning rate: 0.0061 +2024-11-22 05:30:28.615393: train_loss -0.7866 +2024-11-22 05:30:28.617539: val_loss -0.7564 +2024-11-22 05:30:28.617665: Pseudo dice [0.8412] +2024-11-22 05:30:28.617753: Epoch time: 18.44 s +2024-11-22 05:30:29.537648: +2024-11-22 05:30:29.537849: Epoch 3385 +2024-11-22 05:30:29.537962: Current learning rate: 0.00609 +2024-11-22 05:30:47.193350: train_loss -0.7901 +2024-11-22 05:30:47.199807: val_loss -0.7651 +2024-11-22 05:30:47.199931: Pseudo dice [0.8349] +2024-11-22 05:30:47.200014: Epoch time: 17.66 s +2024-11-22 05:30:48.067002: +2024-11-22 05:30:48.067240: Epoch 3386 +2024-11-22 05:30:48.067354: Current learning rate: 0.00609 +2024-11-22 05:31:07.419570: train_loss -0.7933 +2024-11-22 05:31:07.424860: val_loss -0.7718 +2024-11-22 05:31:07.424981: Pseudo dice [0.8557] +2024-11-22 05:31:07.425057: Epoch time: 19.35 s +2024-11-22 05:31:08.333870: +2024-11-22 05:31:08.334063: Epoch 3387 +2024-11-22 05:31:08.334174: Current learning rate: 0.00609 +2024-11-22 05:31:27.841997: train_loss -0.7828 +2024-11-22 05:31:27.847485: val_loss -0.7663 +2024-11-22 05:31:27.847605: Pseudo dice [0.8529] +2024-11-22 05:31:27.847689: Epoch time: 19.51 s +2024-11-22 05:31:29.054577: +2024-11-22 05:31:29.054793: Epoch 3388 +2024-11-22 05:31:29.054910: Current learning rate: 0.00609 +2024-11-22 05:31:47.915371: train_loss -0.7913 +2024-11-22 05:31:47.920559: val_loss -0.7767 +2024-11-22 05:31:47.920693: Pseudo dice [0.8571] +2024-11-22 05:31:47.920783: Epoch time: 18.86 s +2024-11-22 05:31:48.769089: +2024-11-22 05:31:48.769310: Epoch 3389 +2024-11-22 05:31:48.769424: Current learning rate: 0.00609 +2024-11-22 05:32:07.292245: train_loss -0.7836 +2024-11-22 05:32:07.297784: val_loss -0.771 +2024-11-22 05:32:07.297952: Pseudo dice [0.8503] +2024-11-22 05:32:07.298043: Epoch time: 18.52 s +2024-11-22 05:32:08.336341: +2024-11-22 05:32:08.336571: Epoch 3390 +2024-11-22 05:32:08.336681: Current learning rate: 0.00609 +2024-11-22 05:32:26.884241: train_loss -0.7917 +2024-11-22 05:32:26.886900: val_loss -0.7619 +2024-11-22 05:32:26.886991: Pseudo dice [0.8537] +2024-11-22 05:32:26.887077: Epoch time: 18.55 s +2024-11-22 05:32:27.743171: +2024-11-22 05:32:27.743366: Epoch 3391 +2024-11-22 05:32:27.743477: Current learning rate: 0.00609 +2024-11-22 05:32:45.990035: train_loss -0.7871 +2024-11-22 05:32:45.998833: val_loss -0.7816 +2024-11-22 05:32:45.999012: Pseudo dice [0.862] +2024-11-22 05:32:45.999104: Epoch time: 18.25 s +2024-11-22 05:32:46.872117: +2024-11-22 05:32:46.872322: Epoch 3392 +2024-11-22 05:32:46.872437: Current learning rate: 0.00609 +2024-11-22 05:33:06.165124: train_loss -0.7783 +2024-11-22 05:33:06.168938: val_loss -0.7743 +2024-11-22 05:33:06.169027: Pseudo dice [0.8601] +2024-11-22 05:33:06.169110: Epoch time: 19.29 s +2024-11-22 05:33:07.025877: +2024-11-22 05:33:07.026111: Epoch 3393 +2024-11-22 05:33:07.026223: Current learning rate: 0.00609 +2024-11-22 05:33:24.574882: train_loss -0.7868 +2024-11-22 05:33:24.578228: val_loss -0.7614 +2024-11-22 05:33:24.578363: Pseudo dice [0.8497] +2024-11-22 05:33:24.578443: Epoch time: 17.55 s +2024-11-22 05:33:25.430344: +2024-11-22 05:33:25.430538: Epoch 3394 +2024-11-22 05:33:25.430647: Current learning rate: 0.00608 +2024-11-22 05:33:43.966107: train_loss -0.7847 +2024-11-22 05:33:43.972874: val_loss -0.7686 +2024-11-22 05:33:43.972991: Pseudo dice [0.8413] +2024-11-22 05:33:43.973081: Epoch time: 18.54 s +2024-11-22 05:33:44.837622: +2024-11-22 05:33:44.837841: Epoch 3395 +2024-11-22 05:33:44.837958: Current learning rate: 0.00608 +2024-11-22 05:34:03.513655: train_loss -0.7813 +2024-11-22 05:34:03.520638: val_loss -0.7781 +2024-11-22 05:34:03.520746: Pseudo dice [0.8662] +2024-11-22 05:34:03.520820: Epoch time: 18.68 s +2024-11-22 05:34:04.608953: +2024-11-22 05:34:04.609183: Epoch 3396 +2024-11-22 05:34:04.609306: Current learning rate: 0.00608 +2024-11-22 05:34:23.947175: train_loss -0.7884 +2024-11-22 05:34:23.953263: val_loss -0.7665 +2024-11-22 05:34:23.953401: Pseudo dice [0.8425] +2024-11-22 05:34:23.953485: Epoch time: 19.34 s +2024-11-22 05:34:24.918692: +2024-11-22 05:34:24.918901: Epoch 3397 +2024-11-22 05:34:24.919016: Current learning rate: 0.00608 +2024-11-22 05:34:44.133966: train_loss -0.7816 +2024-11-22 05:34:44.136696: val_loss -0.7499 +2024-11-22 05:34:44.136799: Pseudo dice [0.8508] +2024-11-22 05:34:44.136883: Epoch time: 19.22 s +2024-11-22 05:34:44.987602: +2024-11-22 05:34:44.987804: Epoch 3398 +2024-11-22 05:34:44.987921: Current learning rate: 0.00608 +2024-11-22 05:35:04.298801: train_loss -0.7848 +2024-11-22 05:35:04.307510: val_loss -0.765 +2024-11-22 05:35:04.307623: Pseudo dice [0.8492] +2024-11-22 05:35:04.307709: Epoch time: 19.31 s +2024-11-22 05:35:05.621100: +2024-11-22 05:35:05.621305: Epoch 3399 +2024-11-22 05:35:05.621417: Current learning rate: 0.00608 +2024-11-22 05:35:24.061622: train_loss -0.7775 +2024-11-22 05:35:24.069175: val_loss -0.768 +2024-11-22 05:35:24.069510: Pseudo dice [0.8561] +2024-11-22 05:35:24.069607: Epoch time: 18.44 s +2024-11-22 05:35:25.215370: +2024-11-22 05:35:25.215592: Epoch 3400 +2024-11-22 05:35:25.215708: Current learning rate: 0.00608 +2024-11-22 05:35:43.542122: train_loss -0.7939 +2024-11-22 05:35:43.548108: val_loss -0.7613 +2024-11-22 05:35:43.548272: Pseudo dice [0.852] +2024-11-22 05:35:43.548362: Epoch time: 18.33 s +2024-11-22 05:35:44.417712: +2024-11-22 05:35:44.417921: Epoch 3401 +2024-11-22 05:35:44.418031: Current learning rate: 0.00608 +2024-11-22 05:36:03.641095: train_loss -0.7905 +2024-11-22 05:36:03.648895: val_loss -0.7602 +2024-11-22 05:36:03.649025: Pseudo dice [0.8569] +2024-11-22 05:36:03.649163: Epoch time: 19.22 s +2024-11-22 05:36:04.529389: +2024-11-22 05:36:04.529595: Epoch 3402 +2024-11-22 05:36:04.529716: Current learning rate: 0.00607 +2024-11-22 05:36:22.981985: train_loss -0.7781 +2024-11-22 05:36:22.984228: val_loss -0.7925 +2024-11-22 05:36:22.984328: Pseudo dice [0.8561] +2024-11-22 05:36:22.984592: Epoch time: 18.45 s +2024-11-22 05:36:23.855155: +2024-11-22 05:36:23.855357: Epoch 3403 +2024-11-22 05:36:23.855471: Current learning rate: 0.00607 +2024-11-22 05:36:42.854807: train_loss -0.7841 +2024-11-22 05:36:42.860704: val_loss -0.7583 +2024-11-22 05:36:42.860832: Pseudo dice [0.8509] +2024-11-22 05:36:42.860925: Epoch time: 19.0 s +2024-11-22 05:36:43.719527: +2024-11-22 05:36:43.719755: Epoch 3404 +2024-11-22 05:36:43.719872: Current learning rate: 0.00607 +2024-11-22 05:37:01.666564: train_loss -0.788 +2024-11-22 05:37:01.669820: val_loss -0.7808 +2024-11-22 05:37:01.669916: Pseudo dice [0.8448] +2024-11-22 05:37:01.669994: Epoch time: 17.95 s +2024-11-22 05:37:02.527200: +2024-11-22 05:37:02.527415: Epoch 3405 +2024-11-22 05:37:02.527524: Current learning rate: 0.00607 +2024-11-22 05:37:22.320513: train_loss -0.7854 +2024-11-22 05:37:22.322911: val_loss -0.7731 +2024-11-22 05:37:22.323004: Pseudo dice [0.8571] +2024-11-22 05:37:22.323088: Epoch time: 19.79 s +2024-11-22 05:37:23.173752: +2024-11-22 05:37:23.173943: Epoch 3406 +2024-11-22 05:37:23.174054: Current learning rate: 0.00607 +2024-11-22 05:37:41.417747: train_loss -0.7873 +2024-11-22 05:37:41.426376: val_loss -0.7752 +2024-11-22 05:37:41.426534: Pseudo dice [0.8373] +2024-11-22 05:37:41.426638: Epoch time: 18.24 s +2024-11-22 05:37:42.305373: +2024-11-22 05:37:42.305557: Epoch 3407 +2024-11-22 05:37:42.305673: Current learning rate: 0.00607 +2024-11-22 05:38:01.264547: train_loss -0.7843 +2024-11-22 05:38:01.267335: val_loss -0.7958 +2024-11-22 05:38:01.267464: Pseudo dice [0.8678] +2024-11-22 05:38:01.267553: Epoch time: 18.96 s +2024-11-22 05:38:02.370606: +2024-11-22 05:38:02.370826: Epoch 3408 +2024-11-22 05:38:02.370942: Current learning rate: 0.00607 +2024-11-22 05:38:22.328684: train_loss -0.7909 +2024-11-22 05:38:22.342908: val_loss -0.7695 +2024-11-22 05:38:22.343038: Pseudo dice [0.8463] +2024-11-22 05:38:22.343136: Epoch time: 19.96 s +2024-11-22 05:38:23.772474: +2024-11-22 05:38:23.772705: Epoch 3409 +2024-11-22 05:38:23.772819: Current learning rate: 0.00607 +2024-11-22 05:38:42.332314: train_loss -0.7865 +2024-11-22 05:38:42.339330: val_loss -0.777 +2024-11-22 05:38:42.339465: Pseudo dice [0.8632] +2024-11-22 05:38:42.339551: Epoch time: 18.56 s +2024-11-22 05:38:43.335464: +2024-11-22 05:38:43.335706: Epoch 3410 +2024-11-22 05:38:43.335817: Current learning rate: 0.00607 +2024-11-22 05:39:01.777108: train_loss -0.7832 +2024-11-22 05:39:01.785176: val_loss -0.7612 +2024-11-22 05:39:01.785402: Pseudo dice [0.847] +2024-11-22 05:39:01.785501: Epoch time: 18.44 s +2024-11-22 05:39:02.684728: +2024-11-22 05:39:02.684992: Epoch 3411 +2024-11-22 05:39:02.685119: Current learning rate: 0.00606 +2024-11-22 05:39:20.882723: train_loss -0.7877 +2024-11-22 05:39:20.889055: val_loss -0.7749 +2024-11-22 05:39:20.889201: Pseudo dice [0.85] +2024-11-22 05:39:20.889285: Epoch time: 18.2 s +2024-11-22 05:39:21.747399: +2024-11-22 05:39:21.747646: Epoch 3412 +2024-11-22 05:39:21.747759: Current learning rate: 0.00606 +2024-11-22 05:39:41.022475: train_loss -0.7797 +2024-11-22 05:39:41.028039: val_loss -0.7601 +2024-11-22 05:39:41.028167: Pseudo dice [0.8442] +2024-11-22 05:39:41.028244: Epoch time: 19.28 s +2024-11-22 05:39:41.918247: +2024-11-22 05:39:41.918483: Epoch 3413 +2024-11-22 05:39:41.918602: Current learning rate: 0.00606 +2024-11-22 05:40:01.366328: train_loss -0.7823 +2024-11-22 05:40:01.373784: val_loss -0.7603 +2024-11-22 05:40:01.373923: Pseudo dice [0.8491] +2024-11-22 05:40:01.374004: Epoch time: 19.45 s +2024-11-22 05:40:02.266044: +2024-11-22 05:40:02.266266: Epoch 3414 +2024-11-22 05:40:02.266386: Current learning rate: 0.00606 +2024-11-22 05:40:21.412680: train_loss -0.7769 +2024-11-22 05:40:21.422680: val_loss -0.7359 +2024-11-22 05:40:21.422807: Pseudo dice [0.8415] +2024-11-22 05:40:21.422892: Epoch time: 19.15 s +2024-11-22 05:40:22.296243: +2024-11-22 05:40:22.296473: Epoch 3415 +2024-11-22 05:40:22.296585: Current learning rate: 0.00606 +2024-11-22 05:40:40.466257: train_loss -0.7804 +2024-11-22 05:40:40.467822: val_loss -0.7649 +2024-11-22 05:40:40.467918: Pseudo dice [0.8554] +2024-11-22 05:40:40.467995: Epoch time: 18.17 s +2024-11-22 05:40:41.349970: +2024-11-22 05:40:41.350190: Epoch 3416 +2024-11-22 05:40:41.350305: Current learning rate: 0.00606 +2024-11-22 05:41:00.059245: train_loss -0.7763 +2024-11-22 05:41:00.069961: val_loss -0.7676 +2024-11-22 05:41:00.070106: Pseudo dice [0.8427] +2024-11-22 05:41:00.070194: Epoch time: 18.71 s +2024-11-22 05:41:01.078955: +2024-11-22 05:41:01.079189: Epoch 3417 +2024-11-22 05:41:01.079301: Current learning rate: 0.00606 +2024-11-22 05:41:19.746095: train_loss -0.7824 +2024-11-22 05:41:19.748678: val_loss -0.7688 +2024-11-22 05:41:19.748801: Pseudo dice [0.86] +2024-11-22 05:41:19.748889: Epoch time: 18.67 s +2024-11-22 05:41:20.820585: +2024-11-22 05:41:20.820774: Epoch 3418 +2024-11-22 05:41:20.820885: Current learning rate: 0.00606 +2024-11-22 05:41:40.220114: train_loss -0.7902 +2024-11-22 05:41:40.226487: val_loss -0.7716 +2024-11-22 05:41:40.226614: Pseudo dice [0.8559] +2024-11-22 05:41:40.226695: Epoch time: 19.4 s +2024-11-22 05:41:41.149501: +2024-11-22 05:41:41.149704: Epoch 3419 +2024-11-22 05:41:41.149816: Current learning rate: 0.00605 +2024-11-22 05:42:01.479484: train_loss -0.7786 +2024-11-22 05:42:01.482623: val_loss -0.7843 +2024-11-22 05:42:01.482716: Pseudo dice [0.8593] +2024-11-22 05:42:01.482796: Epoch time: 20.33 s +2024-11-22 05:42:02.745674: +2024-11-22 05:42:02.745894: Epoch 3420 +2024-11-22 05:42:02.746010: Current learning rate: 0.00605 +2024-11-22 05:42:21.884904: train_loss -0.7852 +2024-11-22 05:42:21.891112: val_loss -0.7694 +2024-11-22 05:42:21.891223: Pseudo dice [0.854] +2024-11-22 05:42:21.891306: Epoch time: 19.14 s +2024-11-22 05:42:22.804093: +2024-11-22 05:42:22.804319: Epoch 3421 +2024-11-22 05:42:22.804432: Current learning rate: 0.00605 +2024-11-22 05:42:41.558029: train_loss -0.79 +2024-11-22 05:42:41.560524: val_loss -0.7973 +2024-11-22 05:42:41.560629: Pseudo dice [0.8534] +2024-11-22 05:42:41.560715: Epoch time: 18.75 s +2024-11-22 05:42:42.413640: +2024-11-22 05:42:42.413866: Epoch 3422 +2024-11-22 05:42:42.413979: Current learning rate: 0.00605 +2024-11-22 05:43:01.375287: train_loss -0.7875 +2024-11-22 05:43:01.377508: val_loss -0.781 +2024-11-22 05:43:01.377621: Pseudo dice [0.8492] +2024-11-22 05:43:01.377716: Epoch time: 18.96 s +2024-11-22 05:43:02.328012: +2024-11-22 05:43:02.328221: Epoch 3423 +2024-11-22 05:43:02.328331: Current learning rate: 0.00605 +2024-11-22 05:43:21.252383: train_loss -0.7894 +2024-11-22 05:43:21.256986: val_loss -0.7625 +2024-11-22 05:43:21.257121: Pseudo dice [0.837] +2024-11-22 05:43:21.259144: Epoch time: 18.93 s +2024-11-22 05:43:22.119523: +2024-11-22 05:43:22.120000: Epoch 3424 +2024-11-22 05:43:22.120114: Current learning rate: 0.00605 +2024-11-22 05:43:40.322054: train_loss -0.7791 +2024-11-22 05:43:40.329135: val_loss -0.776 +2024-11-22 05:43:40.329319: Pseudo dice [0.8478] +2024-11-22 05:43:40.329410: Epoch time: 18.2 s +2024-11-22 05:43:41.231249: +2024-11-22 05:43:41.253032: Epoch 3425 +2024-11-22 05:43:41.253176: Current learning rate: 0.00605 +2024-11-22 05:44:00.180961: train_loss -0.7832 +2024-11-22 05:44:00.186418: val_loss -0.777 +2024-11-22 05:44:00.186535: Pseudo dice [0.8472] +2024-11-22 05:44:00.186617: Epoch time: 18.95 s +2024-11-22 05:44:01.050665: +2024-11-22 05:44:01.050869: Epoch 3426 +2024-11-22 05:44:01.050983: Current learning rate: 0.00605 +2024-11-22 05:44:20.775407: train_loss -0.7815 +2024-11-22 05:44:20.781408: val_loss -0.7504 +2024-11-22 05:44:20.781544: Pseudo dice [0.837] +2024-11-22 05:44:20.781629: Epoch time: 19.73 s +2024-11-22 05:44:21.821701: +2024-11-22 05:44:21.821912: Epoch 3427 +2024-11-22 05:44:21.822022: Current learning rate: 0.00605 +2024-11-22 05:44:40.510981: train_loss -0.7913 +2024-11-22 05:44:40.517681: val_loss -0.7752 +2024-11-22 05:44:40.517789: Pseudo dice [0.8365] +2024-11-22 05:44:40.517872: Epoch time: 18.69 s +2024-11-22 05:44:41.430404: +2024-11-22 05:44:41.430656: Epoch 3428 +2024-11-22 05:44:41.430773: Current learning rate: 0.00604 +2024-11-22 05:44:59.072841: train_loss -0.7865 +2024-11-22 05:44:59.079317: val_loss -0.7531 +2024-11-22 05:44:59.079494: Pseudo dice [0.8407] +2024-11-22 05:44:59.079859: Epoch time: 17.64 s +2024-11-22 05:44:59.990222: +2024-11-22 05:44:59.990476: Epoch 3429 +2024-11-22 05:44:59.990594: Current learning rate: 0.00604 +2024-11-22 05:45:19.027218: train_loss -0.7774 +2024-11-22 05:45:19.031834: val_loss -0.7858 +2024-11-22 05:45:19.031938: Pseudo dice [0.8612] +2024-11-22 05:45:19.032015: Epoch time: 19.03 s +2024-11-22 05:45:20.017637: +2024-11-22 05:45:20.017841: Epoch 3430 +2024-11-22 05:45:20.017955: Current learning rate: 0.00604 +2024-11-22 05:45:38.741597: train_loss -0.781 +2024-11-22 05:45:38.744244: val_loss -0.7668 +2024-11-22 05:45:38.744373: Pseudo dice [0.8607] +2024-11-22 05:45:38.744453: Epoch time: 18.72 s +2024-11-22 05:45:40.037934: +2024-11-22 05:45:40.038142: Epoch 3431 +2024-11-22 05:45:40.038252: Current learning rate: 0.00604 +2024-11-22 05:45:58.924024: train_loss -0.7787 +2024-11-22 05:45:58.932184: val_loss -0.7824 +2024-11-22 05:45:58.932308: Pseudo dice [0.8559] +2024-11-22 05:45:58.932405: Epoch time: 18.89 s +2024-11-22 05:45:59.947362: +2024-11-22 05:45:59.947570: Epoch 3432 +2024-11-22 05:45:59.947686: Current learning rate: 0.00604 +2024-11-22 05:46:18.750735: train_loss -0.7765 +2024-11-22 05:46:18.756942: val_loss -0.773 +2024-11-22 05:46:18.757082: Pseudo dice [0.8551] +2024-11-22 05:46:18.757166: Epoch time: 18.8 s +2024-11-22 05:46:19.655373: +2024-11-22 05:46:19.655593: Epoch 3433 +2024-11-22 05:46:19.655707: Current learning rate: 0.00604 +2024-11-22 05:46:39.340479: train_loss -0.7787 +2024-11-22 05:46:39.349723: val_loss -0.754 +2024-11-22 05:46:39.349834: Pseudo dice [0.8454] +2024-11-22 05:46:39.349918: Epoch time: 19.69 s +2024-11-22 05:46:40.203507: +2024-11-22 05:46:40.203748: Epoch 3434 +2024-11-22 05:46:40.203871: Current learning rate: 0.00604 +2024-11-22 05:46:58.475066: train_loss -0.783 +2024-11-22 05:46:58.482066: val_loss -0.7471 +2024-11-22 05:46:58.482217: Pseudo dice [0.8514] +2024-11-22 05:46:58.482386: Epoch time: 18.27 s +2024-11-22 05:46:59.342757: +2024-11-22 05:46:59.342968: Epoch 3435 +2024-11-22 05:46:59.343089: Current learning rate: 0.00604 +2024-11-22 05:47:18.201296: train_loss -0.7779 +2024-11-22 05:47:18.208220: val_loss -0.7708 +2024-11-22 05:47:18.208352: Pseudo dice [0.8515] +2024-11-22 05:47:18.208532: Epoch time: 18.86 s +2024-11-22 05:47:19.142211: +2024-11-22 05:47:19.142401: Epoch 3436 +2024-11-22 05:47:19.142511: Current learning rate: 0.00603 +2024-11-22 05:47:37.899166: train_loss -0.7751 +2024-11-22 05:47:37.904881: val_loss -0.7466 +2024-11-22 05:47:37.905006: Pseudo dice [0.8445] +2024-11-22 05:47:37.905092: Epoch time: 18.76 s +2024-11-22 05:47:38.779418: +2024-11-22 05:47:38.779641: Epoch 3437 +2024-11-22 05:47:38.779760: Current learning rate: 0.00603 +2024-11-22 05:47:57.795824: train_loss -0.7738 +2024-11-22 05:47:57.797988: val_loss -0.7631 +2024-11-22 05:47:57.798096: Pseudo dice [0.8459] +2024-11-22 05:47:57.798381: Epoch time: 19.02 s +2024-11-22 05:47:58.810738: +2024-11-22 05:47:58.810949: Epoch 3438 +2024-11-22 05:47:58.811064: Current learning rate: 0.00603 +2024-11-22 05:48:19.018470: train_loss -0.7666 +2024-11-22 05:48:19.025031: val_loss -0.7482 +2024-11-22 05:48:19.025158: Pseudo dice [0.8243] +2024-11-22 05:48:19.025268: Epoch time: 20.21 s +2024-11-22 05:48:19.973752: +2024-11-22 05:48:19.973991: Epoch 3439 +2024-11-22 05:48:19.974113: Current learning rate: 0.00603 +2024-11-22 05:48:39.807436: train_loss -0.7763 +2024-11-22 05:48:39.810066: val_loss -0.7697 +2024-11-22 05:48:39.810193: Pseudo dice [0.8554] +2024-11-22 05:48:39.810289: Epoch time: 19.83 s +2024-11-22 05:48:40.672593: +2024-11-22 05:48:40.673023: Epoch 3440 +2024-11-22 05:48:40.673187: Current learning rate: 0.00603 +2024-11-22 05:48:59.733351: train_loss -0.7826 +2024-11-22 05:48:59.735890: val_loss -0.7641 +2024-11-22 05:48:59.736037: Pseudo dice [0.8496] +2024-11-22 05:48:59.736132: Epoch time: 19.06 s +2024-11-22 05:49:00.592694: +2024-11-22 05:49:00.592919: Epoch 3441 +2024-11-22 05:49:00.593030: Current learning rate: 0.00603 +2024-11-22 05:49:18.903039: train_loss -0.79 +2024-11-22 05:49:18.908950: val_loss -0.7898 +2024-11-22 05:49:18.909072: Pseudo dice [0.8546] +2024-11-22 05:49:18.909152: Epoch time: 18.31 s +2024-11-22 05:49:20.205972: +2024-11-22 05:49:20.206180: Epoch 3442 +2024-11-22 05:49:20.206290: Current learning rate: 0.00603 +2024-11-22 05:49:38.051474: train_loss -0.7873 +2024-11-22 05:49:38.057565: val_loss -0.79 +2024-11-22 05:49:38.057688: Pseudo dice [0.8586] +2024-11-22 05:49:38.057782: Epoch time: 17.85 s +2024-11-22 05:49:38.929998: +2024-11-22 05:49:38.930319: Epoch 3443 +2024-11-22 05:49:38.930448: Current learning rate: 0.00603 +2024-11-22 05:49:57.302101: train_loss -0.7882 +2024-11-22 05:49:57.305255: val_loss -0.766 +2024-11-22 05:49:57.305357: Pseudo dice [0.8448] +2024-11-22 05:49:57.305437: Epoch time: 18.37 s +2024-11-22 05:49:58.165705: +2024-11-22 05:49:58.165929: Epoch 3444 +2024-11-22 05:49:58.166041: Current learning rate: 0.00602 +2024-11-22 05:50:16.338415: train_loss -0.7818 +2024-11-22 05:50:16.343160: val_loss -0.7803 +2024-11-22 05:50:16.343284: Pseudo dice [0.859] +2024-11-22 05:50:16.343384: Epoch time: 18.17 s +2024-11-22 05:50:17.214495: +2024-11-22 05:50:17.214940: Epoch 3445 +2024-11-22 05:50:17.215063: Current learning rate: 0.00602 +2024-11-22 05:50:36.373534: train_loss -0.7751 +2024-11-22 05:50:36.381907: val_loss -0.7759 +2024-11-22 05:50:36.382032: Pseudo dice [0.8547] +2024-11-22 05:50:36.382120: Epoch time: 19.16 s +2024-11-22 05:50:37.328511: +2024-11-22 05:50:37.328736: Epoch 3446 +2024-11-22 05:50:37.328855: Current learning rate: 0.00602 +2024-11-22 05:50:56.376090: train_loss -0.7751 +2024-11-22 05:50:56.383621: val_loss -0.7431 +2024-11-22 05:50:56.383722: Pseudo dice [0.8374] +2024-11-22 05:50:56.383809: Epoch time: 19.05 s +2024-11-22 05:50:57.253286: +2024-11-22 05:50:57.253474: Epoch 3447 +2024-11-22 05:50:57.253589: Current learning rate: 0.00602 +2024-11-22 05:51:16.306270: train_loss -0.7823 +2024-11-22 05:51:16.308513: val_loss -0.7876 +2024-11-22 05:51:16.308653: Pseudo dice [0.8628] +2024-11-22 05:51:16.308737: Epoch time: 19.05 s +2024-11-22 05:51:17.160923: +2024-11-22 05:51:17.161148: Epoch 3448 +2024-11-22 05:51:17.161268: Current learning rate: 0.00602 +2024-11-22 05:51:35.157727: train_loss -0.7759 +2024-11-22 05:51:35.164364: val_loss -0.7442 +2024-11-22 05:51:35.164488: Pseudo dice [0.8603] +2024-11-22 05:51:35.164575: Epoch time: 18.0 s +2024-11-22 05:51:36.027981: +2024-11-22 05:51:36.028206: Epoch 3449 +2024-11-22 05:51:36.028320: Current learning rate: 0.00602 +2024-11-22 05:51:53.867360: train_loss -0.7793 +2024-11-22 05:51:53.873244: val_loss -0.7621 +2024-11-22 05:51:53.873377: Pseudo dice [0.8541] +2024-11-22 05:51:53.873460: Epoch time: 17.84 s +2024-11-22 05:51:55.049933: +2024-11-22 05:51:55.050189: Epoch 3450 +2024-11-22 05:51:55.050305: Current learning rate: 0.00602 +2024-11-22 05:52:14.403833: train_loss -0.7756 +2024-11-22 05:52:14.406090: val_loss -0.7662 +2024-11-22 05:52:14.406204: Pseudo dice [0.843] +2024-11-22 05:52:14.406296: Epoch time: 19.35 s +2024-11-22 05:52:15.265890: +2024-11-22 05:52:15.266110: Epoch 3451 +2024-11-22 05:52:15.266223: Current learning rate: 0.00602 +2024-11-22 05:52:34.678405: train_loss -0.7508 +2024-11-22 05:52:34.685501: val_loss -0.7589 +2024-11-22 05:52:34.685607: Pseudo dice [0.8472] +2024-11-22 05:52:34.685688: Epoch time: 19.41 s +2024-11-22 05:52:35.684896: +2024-11-22 05:52:35.685311: Epoch 3452 +2024-11-22 05:52:35.685447: Current learning rate: 0.00602 +2024-11-22 05:52:54.545611: train_loss -0.7611 +2024-11-22 05:52:54.552909: val_loss -0.7405 +2024-11-22 05:52:54.553019: Pseudo dice [0.8423] +2024-11-22 05:52:54.553107: Epoch time: 18.86 s +2024-11-22 05:52:55.893097: +2024-11-22 05:52:55.893291: Epoch 3453 +2024-11-22 05:52:55.893403: Current learning rate: 0.00601 +2024-11-22 05:53:15.212641: train_loss -0.7658 +2024-11-22 05:53:15.218497: val_loss -0.7724 +2024-11-22 05:53:15.218617: Pseudo dice [0.8501] +2024-11-22 05:53:15.218707: Epoch time: 19.32 s +2024-11-22 05:53:16.202594: +2024-11-22 05:53:16.202793: Epoch 3454 +2024-11-22 05:53:16.202911: Current learning rate: 0.00601 +2024-11-22 05:53:34.670211: train_loss -0.7781 +2024-11-22 05:53:34.678305: val_loss -0.7553 +2024-11-22 05:53:34.678432: Pseudo dice [0.8513] +2024-11-22 05:53:34.678775: Epoch time: 18.47 s +2024-11-22 05:53:35.535069: +2024-11-22 05:53:35.535311: Epoch 3455 +2024-11-22 05:53:35.535421: Current learning rate: 0.00601 +2024-11-22 05:53:54.526803: train_loss -0.7736 +2024-11-22 05:53:54.532565: val_loss -0.7591 +2024-11-22 05:53:54.532710: Pseudo dice [0.84] +2024-11-22 05:53:54.532791: Epoch time: 18.99 s +2024-11-22 05:53:55.422788: +2024-11-22 05:53:55.423007: Epoch 3456 +2024-11-22 05:53:55.423126: Current learning rate: 0.00601 +2024-11-22 05:54:14.745379: train_loss -0.7729 +2024-11-22 05:54:14.773710: val_loss -0.7723 +2024-11-22 05:54:14.773867: Pseudo dice [0.8476] +2024-11-22 05:54:14.773955: Epoch time: 19.32 s +2024-11-22 05:54:15.873203: +2024-11-22 05:54:15.873418: Epoch 3457 +2024-11-22 05:54:15.873545: Current learning rate: 0.00601 +2024-11-22 05:54:34.899909: train_loss -0.769 +2024-11-22 05:54:34.908042: val_loss -0.7801 +2024-11-22 05:54:34.908176: Pseudo dice [0.849] +2024-11-22 05:54:34.908310: Epoch time: 19.03 s +2024-11-22 05:54:35.907969: +2024-11-22 05:54:35.908245: Epoch 3458 +2024-11-22 05:54:35.908360: Current learning rate: 0.00601 +2024-11-22 05:54:56.146124: train_loss -0.7742 +2024-11-22 05:54:56.151849: val_loss -0.758 +2024-11-22 05:54:56.151961: Pseudo dice [0.8491] +2024-11-22 05:54:56.152039: Epoch time: 20.24 s +2024-11-22 05:54:57.029046: +2024-11-22 05:54:57.029273: Epoch 3459 +2024-11-22 05:54:57.029396: Current learning rate: 0.00601 +2024-11-22 05:55:15.850614: train_loss -0.7801 +2024-11-22 05:55:15.858380: val_loss -0.742 +2024-11-22 05:55:15.858489: Pseudo dice [0.8551] +2024-11-22 05:55:15.858577: Epoch time: 18.82 s +2024-11-22 05:55:16.921101: +2024-11-22 05:55:16.921294: Epoch 3460 +2024-11-22 05:55:16.921407: Current learning rate: 0.00601 +2024-11-22 05:55:36.187603: train_loss -0.7804 +2024-11-22 05:55:36.201425: val_loss -0.757 +2024-11-22 05:55:36.201575: Pseudo dice [0.847] +2024-11-22 05:55:36.201662: Epoch time: 19.27 s +2024-11-22 05:55:37.166667: +2024-11-22 05:55:37.166870: Epoch 3461 +2024-11-22 05:55:37.166992: Current learning rate: 0.006 +2024-11-22 05:55:55.504236: train_loss -0.7867 +2024-11-22 05:55:55.506966: val_loss -0.7742 +2024-11-22 05:55:55.507088: Pseudo dice [0.8585] +2024-11-22 05:55:55.507180: Epoch time: 18.34 s +2024-11-22 05:55:56.435878: +2024-11-22 05:55:56.436328: Epoch 3462 +2024-11-22 05:55:56.436462: Current learning rate: 0.006 +2024-11-22 05:56:16.708875: train_loss -0.7883 +2024-11-22 05:56:16.715221: val_loss -0.7656 +2024-11-22 05:56:16.715335: Pseudo dice [0.8389] +2024-11-22 05:56:16.715422: Epoch time: 20.27 s +2024-11-22 05:56:17.623624: +2024-11-22 05:56:17.623889: Epoch 3463 +2024-11-22 05:56:17.624260: Current learning rate: 0.006 +2024-11-22 05:56:36.099314: train_loss -0.7847 +2024-11-22 05:56:36.105592: val_loss -0.757 +2024-11-22 05:56:36.105705: Pseudo dice [0.8519] +2024-11-22 05:56:36.105824: Epoch time: 18.48 s +2024-11-22 05:56:37.664909: +2024-11-22 05:56:37.665214: Epoch 3464 +2024-11-22 05:56:37.665326: Current learning rate: 0.006 +2024-11-22 05:56:57.158099: train_loss -0.7803 +2024-11-22 05:56:57.160171: val_loss -0.766 +2024-11-22 05:56:57.160258: Pseudo dice [0.8499] +2024-11-22 05:56:57.160338: Epoch time: 19.49 s +2024-11-22 05:56:58.018295: +2024-11-22 05:56:58.018483: Epoch 3465 +2024-11-22 05:56:58.018594: Current learning rate: 0.006 +2024-11-22 05:57:18.006280: train_loss -0.7851 +2024-11-22 05:57:18.011745: val_loss -0.7831 +2024-11-22 05:57:18.011863: Pseudo dice [0.8544] +2024-11-22 05:57:18.011954: Epoch time: 19.99 s +2024-11-22 05:57:18.937370: +2024-11-22 05:57:18.937574: Epoch 3466 +2024-11-22 05:57:18.937688: Current learning rate: 0.006 +2024-11-22 05:57:37.531728: train_loss -0.7761 +2024-11-22 05:57:37.539197: val_loss -0.7739 +2024-11-22 05:57:37.539337: Pseudo dice [0.8471] +2024-11-22 05:57:37.539434: Epoch time: 18.6 s +2024-11-22 05:57:38.417904: +2024-11-22 05:57:38.418119: Epoch 3467 +2024-11-22 05:57:38.418235: Current learning rate: 0.006 +2024-11-22 05:57:57.456223: train_loss -0.7742 +2024-11-22 05:57:57.463532: val_loss -0.7714 +2024-11-22 05:57:57.463663: Pseudo dice [0.8467] +2024-11-22 05:57:57.463745: Epoch time: 19.04 s +2024-11-22 05:57:58.449490: +2024-11-22 05:57:58.449699: Epoch 3468 +2024-11-22 05:57:58.449813: Current learning rate: 0.006 +2024-11-22 05:58:17.095275: train_loss -0.7756 +2024-11-22 05:58:17.097831: val_loss -0.7716 +2024-11-22 05:58:17.097985: Pseudo dice [0.8535] +2024-11-22 05:58:17.098085: Epoch time: 18.65 s +2024-11-22 05:58:17.958649: +2024-11-22 05:58:17.958844: Epoch 3469 +2024-11-22 05:58:17.958952: Current learning rate: 0.006 +2024-11-22 05:58:35.996807: train_loss -0.7852 +2024-11-22 05:58:36.005726: val_loss -0.7504 +2024-11-22 05:58:36.005840: Pseudo dice [0.8526] +2024-11-22 05:58:36.005924: Epoch time: 18.04 s +2024-11-22 05:58:36.901324: +2024-11-22 05:58:36.901597: Epoch 3470 +2024-11-22 05:58:36.901712: Current learning rate: 0.00599 +2024-11-22 05:58:55.478111: train_loss -0.7812 +2024-11-22 05:58:55.480194: val_loss -0.784 +2024-11-22 05:58:55.480279: Pseudo dice [0.8588] +2024-11-22 05:58:55.480356: Epoch time: 18.58 s +2024-11-22 05:58:56.331480: +2024-11-22 05:58:56.331681: Epoch 3471 +2024-11-22 05:58:56.331795: Current learning rate: 0.00599 +2024-11-22 05:59:15.806642: train_loss -0.7857 +2024-11-22 05:59:15.812685: val_loss -0.7773 +2024-11-22 05:59:15.812800: Pseudo dice [0.8479] +2024-11-22 05:59:15.812896: Epoch time: 19.48 s +2024-11-22 05:59:16.781713: +2024-11-22 05:59:16.781899: Epoch 3472 +2024-11-22 05:59:16.782010: Current learning rate: 0.00599 +2024-11-22 05:59:35.920128: train_loss -0.7919 +2024-11-22 05:59:35.924355: val_loss -0.7625 +2024-11-22 05:59:35.924488: Pseudo dice [0.8561] +2024-11-22 05:59:35.924574: Epoch time: 19.14 s +2024-11-22 05:59:36.783113: +2024-11-22 05:59:36.783331: Epoch 3473 +2024-11-22 05:59:36.783438: Current learning rate: 0.00599 +2024-11-22 05:59:55.130841: train_loss -0.7827 +2024-11-22 05:59:55.132865: val_loss -0.7572 +2024-11-22 05:59:55.132980: Pseudo dice [0.8486] +2024-11-22 05:59:55.133065: Epoch time: 18.35 s +2024-11-22 05:59:56.030775: +2024-11-22 05:59:56.031011: Epoch 3474 +2024-11-22 05:59:56.031133: Current learning rate: 0.00599 +2024-11-22 06:00:15.656180: train_loss -0.7778 +2024-11-22 06:00:15.663313: val_loss -0.7593 +2024-11-22 06:00:15.663437: Pseudo dice [0.8449] +2024-11-22 06:00:15.663519: Epoch time: 19.63 s +2024-11-22 06:00:16.985260: +2024-11-22 06:00:16.985469: Epoch 3475 +2024-11-22 06:00:16.985578: Current learning rate: 0.00599 +2024-11-22 06:00:36.601980: train_loss -0.7815 +2024-11-22 06:00:36.607286: val_loss -0.7719 +2024-11-22 06:00:36.607422: Pseudo dice [0.8427] +2024-11-22 06:00:36.607512: Epoch time: 19.62 s +2024-11-22 06:00:37.498654: +2024-11-22 06:00:37.498894: Epoch 3476 +2024-11-22 06:00:37.499008: Current learning rate: 0.00599 +2024-11-22 06:00:56.581634: train_loss -0.7837 +2024-11-22 06:00:56.585628: val_loss -0.7649 +2024-11-22 06:00:56.585753: Pseudo dice [0.8512] +2024-11-22 06:00:56.585832: Epoch time: 19.08 s +2024-11-22 06:00:57.562937: +2024-11-22 06:00:57.563154: Epoch 3477 +2024-11-22 06:00:57.563265: Current learning rate: 0.00599 +2024-11-22 06:01:16.053729: train_loss -0.7865 +2024-11-22 06:01:16.059556: val_loss -0.7635 +2024-11-22 06:01:16.059680: Pseudo dice [0.8465] +2024-11-22 06:01:16.059757: Epoch time: 18.49 s +2024-11-22 06:01:17.035550: +2024-11-22 06:01:17.035757: Epoch 3478 +2024-11-22 06:01:17.035874: Current learning rate: 0.00598 +2024-11-22 06:01:35.425574: train_loss -0.7959 +2024-11-22 06:01:35.434446: val_loss -0.7856 +2024-11-22 06:01:35.434564: Pseudo dice [0.8624] +2024-11-22 06:01:35.434649: Epoch time: 18.39 s +2024-11-22 06:01:36.301835: +2024-11-22 06:01:36.302057: Epoch 3479 +2024-11-22 06:01:36.302179: Current learning rate: 0.00598 +2024-11-22 06:01:55.300937: train_loss -0.7844 +2024-11-22 06:01:55.308111: val_loss -0.7846 +2024-11-22 06:01:55.308259: Pseudo dice [0.8559] +2024-11-22 06:01:55.308343: Epoch time: 19.0 s +2024-11-22 06:01:56.328249: +2024-11-22 06:01:56.328486: Epoch 3480 +2024-11-22 06:01:56.328601: Current learning rate: 0.00598 +2024-11-22 06:02:15.506635: train_loss -0.7915 +2024-11-22 06:02:15.512115: val_loss -0.7762 +2024-11-22 06:02:15.512237: Pseudo dice [0.8498] +2024-11-22 06:02:15.512573: Epoch time: 19.18 s +2024-11-22 06:02:16.379842: +2024-11-22 06:02:16.380068: Epoch 3481 +2024-11-22 06:02:16.380179: Current learning rate: 0.00598 +2024-11-22 06:02:33.651839: train_loss -0.7852 +2024-11-22 06:02:33.666435: val_loss -0.7566 +2024-11-22 06:02:33.666565: Pseudo dice [0.8443] +2024-11-22 06:02:33.666718: Epoch time: 17.27 s +2024-11-22 06:02:34.803827: +2024-11-22 06:02:34.804034: Epoch 3482 +2024-11-22 06:02:34.804152: Current learning rate: 0.00598 +2024-11-22 06:02:54.334521: train_loss -0.786 +2024-11-22 06:02:54.339273: val_loss -0.7642 +2024-11-22 06:02:54.339390: Pseudo dice [0.8432] +2024-11-22 06:02:54.339477: Epoch time: 19.53 s +2024-11-22 06:02:55.197248: +2024-11-22 06:02:55.197469: Epoch 3483 +2024-11-22 06:02:55.197598: Current learning rate: 0.00598 +2024-11-22 06:03:14.360367: train_loss -0.7894 +2024-11-22 06:03:14.362602: val_loss -0.7421 +2024-11-22 06:03:14.362696: Pseudo dice [0.8485] +2024-11-22 06:03:14.362777: Epoch time: 19.16 s +2024-11-22 06:03:15.230013: +2024-11-22 06:03:15.230216: Epoch 3484 +2024-11-22 06:03:15.230331: Current learning rate: 0.00598 +2024-11-22 06:03:34.876115: train_loss -0.7909 +2024-11-22 06:03:34.883092: val_loss -0.7789 +2024-11-22 06:03:34.883226: Pseudo dice [0.8448] +2024-11-22 06:03:34.883307: Epoch time: 19.65 s +2024-11-22 06:03:35.779209: +2024-11-22 06:03:35.779429: Epoch 3485 +2024-11-22 06:03:35.779540: Current learning rate: 0.00598 +2024-11-22 06:03:55.496295: train_loss -0.7922 +2024-11-22 06:03:55.503028: val_loss -0.7547 +2024-11-22 06:03:55.503161: Pseudo dice [0.859] +2024-11-22 06:03:55.503245: Epoch time: 19.72 s +2024-11-22 06:03:56.861293: +2024-11-22 06:03:56.861502: Epoch 3486 +2024-11-22 06:03:56.861617: Current learning rate: 0.00597 +2024-11-22 06:04:16.203799: train_loss -0.7878 +2024-11-22 06:04:16.213634: val_loss -0.7601 +2024-11-22 06:04:16.213758: Pseudo dice [0.8564] +2024-11-22 06:04:16.213846: Epoch time: 19.34 s +2024-11-22 06:04:17.181747: +2024-11-22 06:04:17.181962: Epoch 3487 +2024-11-22 06:04:17.182079: Current learning rate: 0.00597 +2024-11-22 06:04:36.187287: train_loss -0.771 +2024-11-22 06:04:36.193574: val_loss -0.7445 +2024-11-22 06:04:36.193697: Pseudo dice [0.8514] +2024-11-22 06:04:36.193783: Epoch time: 19.01 s +2024-11-22 06:04:37.051626: +2024-11-22 06:04:37.051825: Epoch 3488 +2024-11-22 06:04:37.051938: Current learning rate: 0.00597 +2024-11-22 06:04:55.276346: train_loss -0.7855 +2024-11-22 06:04:55.289597: val_loss -0.7563 +2024-11-22 06:04:55.290004: Pseudo dice [0.849] +2024-11-22 06:04:55.290126: Epoch time: 18.23 s +2024-11-22 06:04:56.299165: +2024-11-22 06:04:56.299381: Epoch 3489 +2024-11-22 06:04:56.299498: Current learning rate: 0.00597 +2024-11-22 06:05:15.211363: train_loss -0.7795 +2024-11-22 06:05:15.213396: val_loss -0.7566 +2024-11-22 06:05:15.213506: Pseudo dice [0.8472] +2024-11-22 06:05:15.213586: Epoch time: 18.91 s +2024-11-22 06:05:16.071281: +2024-11-22 06:05:16.071481: Epoch 3490 +2024-11-22 06:05:16.071600: Current learning rate: 0.00597 +2024-11-22 06:05:35.906527: train_loss -0.7841 +2024-11-22 06:05:35.912117: val_loss -0.7561 +2024-11-22 06:05:35.912242: Pseudo dice [0.8486] +2024-11-22 06:05:35.912330: Epoch time: 19.84 s +2024-11-22 06:05:36.813870: +2024-11-22 06:05:36.814090: Epoch 3491 +2024-11-22 06:05:36.814207: Current learning rate: 0.00597 +2024-11-22 06:05:55.348205: train_loss -0.7784 +2024-11-22 06:05:55.350867: val_loss -0.7698 +2024-11-22 06:05:55.350989: Pseudo dice [0.8665] +2024-11-22 06:05:55.351077: Epoch time: 18.54 s +2024-11-22 06:05:56.215315: +2024-11-22 06:05:56.215525: Epoch 3492 +2024-11-22 06:05:56.215642: Current learning rate: 0.00597 +2024-11-22 06:06:15.608016: train_loss -0.7771 +2024-11-22 06:06:15.615194: val_loss -0.7676 +2024-11-22 06:06:15.615320: Pseudo dice [0.856] +2024-11-22 06:06:15.615415: Epoch time: 19.39 s +2024-11-22 06:06:16.473052: +2024-11-22 06:06:16.473276: Epoch 3493 +2024-11-22 06:06:16.473400: Current learning rate: 0.00597 +2024-11-22 06:06:35.372504: train_loss -0.7958 +2024-11-22 06:06:35.375176: val_loss -0.7664 +2024-11-22 06:06:35.375267: Pseudo dice [0.8524] +2024-11-22 06:06:35.375349: Epoch time: 18.9 s +2024-11-22 06:06:36.229190: +2024-11-22 06:06:36.229398: Epoch 3494 +2024-11-22 06:06:36.229512: Current learning rate: 0.00597 +2024-11-22 06:06:54.742329: train_loss -0.7862 +2024-11-22 06:06:54.750849: val_loss -0.7762 +2024-11-22 06:06:54.751028: Pseudo dice [0.8515] +2024-11-22 06:06:54.751126: Epoch time: 18.51 s +2024-11-22 06:06:55.642840: +2024-11-22 06:06:55.643042: Epoch 3495 +2024-11-22 06:06:55.643156: Current learning rate: 0.00596 +2024-11-22 06:07:15.663310: train_loss -0.7803 +2024-11-22 06:07:15.668782: val_loss -0.7825 +2024-11-22 06:07:15.668959: Pseudo dice [0.8535] +2024-11-22 06:07:15.669047: Epoch time: 20.02 s +2024-11-22 06:07:16.582137: +2024-11-22 06:07:16.582334: Epoch 3496 +2024-11-22 06:07:16.582452: Current learning rate: 0.00596 +2024-11-22 06:07:35.325922: train_loss -0.7818 +2024-11-22 06:07:35.328365: val_loss -0.7625 +2024-11-22 06:07:35.328450: Pseudo dice [0.8524] +2024-11-22 06:07:35.328523: Epoch time: 18.74 s +2024-11-22 06:07:36.563830: +2024-11-22 06:07:36.564032: Epoch 3497 +2024-11-22 06:07:36.564152: Current learning rate: 0.00596 +2024-11-22 06:07:54.584975: train_loss -0.7897 +2024-11-22 06:07:54.590333: val_loss -0.786 +2024-11-22 06:07:54.590443: Pseudo dice [0.8547] +2024-11-22 06:07:54.590528: Epoch time: 18.02 s +2024-11-22 06:07:55.649747: +2024-11-22 06:07:55.649969: Epoch 3498 +2024-11-22 06:07:55.650097: Current learning rate: 0.00596 +2024-11-22 06:08:14.373219: train_loss -0.7778 +2024-11-22 06:08:14.380110: val_loss -0.7742 +2024-11-22 06:08:14.380220: Pseudo dice [0.8465] +2024-11-22 06:08:14.380314: Epoch time: 18.72 s +2024-11-22 06:08:15.466688: +2024-11-22 06:08:15.466902: Epoch 3499 +2024-11-22 06:08:15.467012: Current learning rate: 0.00596 +2024-11-22 06:08:34.325775: train_loss -0.7923 +2024-11-22 06:08:34.332541: val_loss -0.7605 +2024-11-22 06:08:34.332670: Pseudo dice [0.8537] +2024-11-22 06:08:34.332752: Epoch time: 18.86 s +2024-11-22 06:08:35.445157: +2024-11-22 06:08:35.445356: Epoch 3500 +2024-11-22 06:08:35.445466: Current learning rate: 0.00596 +2024-11-22 06:08:54.019186: train_loss -0.7874 +2024-11-22 06:08:54.025301: val_loss -0.7386 +2024-11-22 06:08:54.025427: Pseudo dice [0.8492] +2024-11-22 06:08:54.025508: Epoch time: 18.57 s +2024-11-22 06:08:54.982784: +2024-11-22 06:08:54.983003: Epoch 3501 +2024-11-22 06:08:54.983134: Current learning rate: 0.00596 +2024-11-22 06:09:13.168733: train_loss -0.783 +2024-11-22 06:09:13.171121: val_loss -0.7634 +2024-11-22 06:09:13.171238: Pseudo dice [0.8404] +2024-11-22 06:09:13.171330: Epoch time: 18.19 s +2024-11-22 06:09:14.055280: +2024-11-22 06:09:14.055494: Epoch 3502 +2024-11-22 06:09:14.055605: Current learning rate: 0.00596 +2024-11-22 06:09:32.358539: train_loss -0.7869 +2024-11-22 06:09:32.365053: val_loss -0.7779 +2024-11-22 06:09:32.365165: Pseudo dice [0.8596] +2024-11-22 06:09:32.365245: Epoch time: 18.3 s +2024-11-22 06:09:33.380526: +2024-11-22 06:09:33.380727: Epoch 3503 +2024-11-22 06:09:33.380841: Current learning rate: 0.00595 +2024-11-22 06:09:52.420944: train_loss -0.787 +2024-11-22 06:09:52.442403: val_loss -0.7551 +2024-11-22 06:09:52.442532: Pseudo dice [0.842] +2024-11-22 06:09:52.442612: Epoch time: 19.04 s +2024-11-22 06:09:53.507716: +2024-11-22 06:09:53.507928: Epoch 3504 +2024-11-22 06:09:53.508040: Current learning rate: 0.00595 +2024-11-22 06:10:12.314452: train_loss -0.786 +2024-11-22 06:10:12.321708: val_loss -0.7855 +2024-11-22 06:10:12.321831: Pseudo dice [0.8546] +2024-11-22 06:10:12.321923: Epoch time: 18.81 s +2024-11-22 06:10:13.203437: +2024-11-22 06:10:13.203639: Epoch 3505 +2024-11-22 06:10:13.203753: Current learning rate: 0.00595 +2024-11-22 06:10:32.239350: train_loss -0.7854 +2024-11-22 06:10:32.242452: val_loss -0.7654 +2024-11-22 06:10:32.242564: Pseudo dice [0.8464] +2024-11-22 06:10:32.242647: Epoch time: 19.04 s +2024-11-22 06:10:33.203918: +2024-11-22 06:10:33.204127: Epoch 3506 +2024-11-22 06:10:33.204243: Current learning rate: 0.00595 +2024-11-22 06:10:53.601828: train_loss -0.7845 +2024-11-22 06:10:53.604015: val_loss -0.7503 +2024-11-22 06:10:53.604309: Pseudo dice [0.8524] +2024-11-22 06:10:53.604397: Epoch time: 20.4 s +2024-11-22 06:10:54.856536: +2024-11-22 06:10:54.856765: Epoch 3507 +2024-11-22 06:10:54.856875: Current learning rate: 0.00595 +2024-11-22 06:11:14.412361: train_loss -0.7926 +2024-11-22 06:11:14.418161: val_loss -0.7488 +2024-11-22 06:11:14.418293: Pseudo dice [0.8429] +2024-11-22 06:11:14.418379: Epoch time: 19.56 s +2024-11-22 06:11:15.351540: +2024-11-22 06:11:15.351733: Epoch 3508 +2024-11-22 06:11:15.351846: Current learning rate: 0.00595 +2024-11-22 06:11:34.192591: train_loss -0.7798 +2024-11-22 06:11:34.197583: val_loss -0.7674 +2024-11-22 06:11:34.197714: Pseudo dice [0.8592] +2024-11-22 06:11:34.197803: Epoch time: 18.84 s +2024-11-22 06:11:35.100710: +2024-11-22 06:11:35.100914: Epoch 3509 +2024-11-22 06:11:35.101022: Current learning rate: 0.00595 +2024-11-22 06:11:54.191862: train_loss -0.7752 +2024-11-22 06:11:54.194071: val_loss -0.7636 +2024-11-22 06:11:54.194157: Pseudo dice [0.8416] +2024-11-22 06:11:54.194239: Epoch time: 19.09 s +2024-11-22 06:11:55.051663: +2024-11-22 06:11:55.051873: Epoch 3510 +2024-11-22 06:11:55.051981: Current learning rate: 0.00595 +2024-11-22 06:12:14.676337: train_loss -0.7851 +2024-11-22 06:12:14.682405: val_loss -0.7709 +2024-11-22 06:12:14.682512: Pseudo dice [0.853] +2024-11-22 06:12:14.682592: Epoch time: 19.63 s +2024-11-22 06:12:15.660526: +2024-11-22 06:12:15.660755: Epoch 3511 +2024-11-22 06:12:15.660869: Current learning rate: 0.00595 +2024-11-22 06:12:34.036277: train_loss -0.7757 +2024-11-22 06:12:34.040621: val_loss -0.7548 +2024-11-22 06:12:34.040759: Pseudo dice [0.8292] +2024-11-22 06:12:34.040854: Epoch time: 18.38 s +2024-11-22 06:12:35.077997: +2024-11-22 06:12:35.078268: Epoch 3512 +2024-11-22 06:12:35.078380: Current learning rate: 0.00594 +2024-11-22 06:12:53.656589: train_loss -0.7811 +2024-11-22 06:12:53.658585: val_loss -0.7764 +2024-11-22 06:12:53.658699: Pseudo dice [0.8442] +2024-11-22 06:12:53.658780: Epoch time: 18.58 s +2024-11-22 06:12:54.520746: +2024-11-22 06:12:54.520983: Epoch 3513 +2024-11-22 06:12:54.521097: Current learning rate: 0.00594 +2024-11-22 06:13:14.583375: train_loss -0.7846 +2024-11-22 06:13:14.591198: val_loss -0.7623 +2024-11-22 06:13:14.591305: Pseudo dice [0.8532] +2024-11-22 06:13:14.591388: Epoch time: 20.06 s +2024-11-22 06:13:15.464785: +2024-11-22 06:13:15.464987: Epoch 3514 +2024-11-22 06:13:15.465107: Current learning rate: 0.00594 +2024-11-22 06:13:35.011714: train_loss -0.7808 +2024-11-22 06:13:35.014508: val_loss -0.7519 +2024-11-22 06:13:35.014605: Pseudo dice [0.863] +2024-11-22 06:13:35.014688: Epoch time: 19.55 s +2024-11-22 06:13:35.866068: +2024-11-22 06:13:35.866264: Epoch 3515 +2024-11-22 06:13:35.866372: Current learning rate: 0.00594 +2024-11-22 06:13:56.047545: train_loss -0.7881 +2024-11-22 06:13:56.073211: val_loss -0.7752 +2024-11-22 06:13:56.073387: Pseudo dice [0.8488] +2024-11-22 06:13:56.073494: Epoch time: 20.18 s +2024-11-22 06:13:56.933771: +2024-11-22 06:13:56.933960: Epoch 3516 +2024-11-22 06:13:56.934074: Current learning rate: 0.00594 +2024-11-22 06:14:15.939805: train_loss -0.7778 +2024-11-22 06:14:15.947258: val_loss -0.7434 +2024-11-22 06:14:15.947364: Pseudo dice [0.8491] +2024-11-22 06:14:15.947446: Epoch time: 19.01 s +2024-11-22 06:14:16.812962: +2024-11-22 06:14:16.813147: Epoch 3517 +2024-11-22 06:14:16.813265: Current learning rate: 0.00594 +2024-11-22 06:14:36.955703: train_loss -0.7807 +2024-11-22 06:14:36.961878: val_loss -0.7661 +2024-11-22 06:14:36.962036: Pseudo dice [0.8511] +2024-11-22 06:14:36.962132: Epoch time: 20.14 s +2024-11-22 06:14:38.227376: +2024-11-22 06:14:38.227647: Epoch 3518 +2024-11-22 06:14:38.227782: Current learning rate: 0.00594 +2024-11-22 06:14:58.007648: train_loss -0.7819 +2024-11-22 06:14:58.010054: val_loss -0.7464 +2024-11-22 06:14:58.010155: Pseudo dice [0.8384] +2024-11-22 06:14:58.010238: Epoch time: 19.78 s +2024-11-22 06:14:58.870434: +2024-11-22 06:14:58.870642: Epoch 3519 +2024-11-22 06:14:58.870753: Current learning rate: 0.00594 +2024-11-22 06:15:18.507966: train_loss -0.7739 +2024-11-22 06:15:18.516912: val_loss -0.7659 +2024-11-22 06:15:18.517046: Pseudo dice [0.8491] +2024-11-22 06:15:18.517139: Epoch time: 19.64 s +2024-11-22 06:15:19.411695: +2024-11-22 06:15:19.411918: Epoch 3520 +2024-11-22 06:15:19.412033: Current learning rate: 0.00593 +2024-11-22 06:15:38.695703: train_loss -0.7831 +2024-11-22 06:15:38.704016: val_loss -0.7506 +2024-11-22 06:15:38.704228: Pseudo dice [0.8336] +2024-11-22 06:15:38.704310: Epoch time: 19.28 s +2024-11-22 06:15:39.704648: +2024-11-22 06:15:39.704888: Epoch 3521 +2024-11-22 06:15:39.705003: Current learning rate: 0.00593 +2024-11-22 06:15:58.212248: train_loss -0.7873 +2024-11-22 06:15:58.226338: val_loss -0.7674 +2024-11-22 06:15:58.226460: Pseudo dice [0.8616] +2024-11-22 06:15:58.226538: Epoch time: 18.51 s +2024-11-22 06:15:59.330560: +2024-11-22 06:15:59.330780: Epoch 3522 +2024-11-22 06:15:59.330896: Current learning rate: 0.00593 +2024-11-22 06:16:17.820988: train_loss -0.7814 +2024-11-22 06:16:17.824344: val_loss -0.7765 +2024-11-22 06:16:17.824449: Pseudo dice [0.8495] +2024-11-22 06:16:17.824538: Epoch time: 18.49 s +2024-11-22 06:16:18.722627: +2024-11-22 06:16:18.722851: Epoch 3523 +2024-11-22 06:16:18.722967: Current learning rate: 0.00593 +2024-11-22 06:16:37.683981: train_loss -0.772 +2024-11-22 06:16:37.689356: val_loss -0.7495 +2024-11-22 06:16:37.689486: Pseudo dice [0.8533] +2024-11-22 06:16:37.689564: Epoch time: 18.96 s +2024-11-22 06:16:38.555740: +2024-11-22 06:16:38.555954: Epoch 3524 +2024-11-22 06:16:38.556084: Current learning rate: 0.00593 +2024-11-22 06:16:57.561396: train_loss -0.7703 +2024-11-22 06:16:57.570810: val_loss -0.7706 +2024-11-22 06:16:57.570940: Pseudo dice [0.8526] +2024-11-22 06:16:57.571026: Epoch time: 19.01 s +2024-11-22 06:16:58.441352: +2024-11-22 06:16:58.441558: Epoch 3525 +2024-11-22 06:16:58.441669: Current learning rate: 0.00593 +2024-11-22 06:17:17.304415: train_loss -0.7739 +2024-11-22 06:17:17.310289: val_loss -0.7475 +2024-11-22 06:17:17.310405: Pseudo dice [0.8376] +2024-11-22 06:17:17.310483: Epoch time: 18.86 s +2024-11-22 06:17:18.216817: +2024-11-22 06:17:18.217021: Epoch 3526 +2024-11-22 06:17:18.217143: Current learning rate: 0.00593 +2024-11-22 06:17:37.133526: train_loss -0.7831 +2024-11-22 06:17:37.135848: val_loss -0.7663 +2024-11-22 06:17:37.161490: Pseudo dice [0.8584] +2024-11-22 06:17:37.161625: Epoch time: 18.92 s +2024-11-22 06:17:38.023652: +2024-11-22 06:17:38.023864: Epoch 3527 +2024-11-22 06:17:38.023974: Current learning rate: 0.00593 +2024-11-22 06:17:57.215116: train_loss -0.775 +2024-11-22 06:17:57.216820: val_loss -0.7851 +2024-11-22 06:17:57.216919: Pseudo dice [0.8462] +2024-11-22 06:17:57.216997: Epoch time: 19.19 s +2024-11-22 06:17:58.067353: +2024-11-22 06:17:58.067543: Epoch 3528 +2024-11-22 06:17:58.067664: Current learning rate: 0.00592 +2024-11-22 06:18:15.860341: train_loss -0.7822 +2024-11-22 06:18:15.869057: val_loss -0.7779 +2024-11-22 06:18:15.869190: Pseudo dice [0.8392] +2024-11-22 06:18:15.869269: Epoch time: 17.79 s +2024-11-22 06:18:17.176584: +2024-11-22 06:18:17.176799: Epoch 3529 +2024-11-22 06:18:17.176911: Current learning rate: 0.00592 +2024-11-22 06:18:35.374974: train_loss -0.7838 +2024-11-22 06:18:35.376897: val_loss -0.7835 +2024-11-22 06:18:35.376995: Pseudo dice [0.8543] +2024-11-22 06:18:35.377086: Epoch time: 18.2 s +2024-11-22 06:18:36.236609: +2024-11-22 06:18:36.236814: Epoch 3530 +2024-11-22 06:18:36.236936: Current learning rate: 0.00592 +2024-11-22 06:18:54.447580: train_loss -0.7849 +2024-11-22 06:18:54.457302: val_loss -0.7691 +2024-11-22 06:18:54.457416: Pseudo dice [0.8494] +2024-11-22 06:18:54.457500: Epoch time: 18.21 s +2024-11-22 06:18:55.402118: +2024-11-22 06:18:55.402362: Epoch 3531 +2024-11-22 06:18:55.402473: Current learning rate: 0.00592 +2024-11-22 06:19:14.098226: train_loss -0.7778 +2024-11-22 06:19:14.112485: val_loss -0.7527 +2024-11-22 06:19:14.112619: Pseudo dice [0.8521] +2024-11-22 06:19:14.112697: Epoch time: 18.7 s +2024-11-22 06:19:14.991526: +2024-11-22 06:19:14.991754: Epoch 3532 +2024-11-22 06:19:14.991866: Current learning rate: 0.00592 +2024-11-22 06:19:33.963584: train_loss -0.7897 +2024-11-22 06:19:33.968516: val_loss -0.7824 +2024-11-22 06:19:33.968883: Pseudo dice [0.8421] +2024-11-22 06:19:33.968976: Epoch time: 18.97 s +2024-11-22 06:19:34.860654: +2024-11-22 06:19:34.860869: Epoch 3533 +2024-11-22 06:19:34.860985: Current learning rate: 0.00592 +2024-11-22 06:19:53.803271: train_loss -0.7895 +2024-11-22 06:19:53.806891: val_loss -0.7647 +2024-11-22 06:19:53.807014: Pseudo dice [0.8524] +2024-11-22 06:19:53.807102: Epoch time: 18.94 s +2024-11-22 06:19:54.675638: +2024-11-22 06:19:54.675848: Epoch 3534 +2024-11-22 06:19:54.675962: Current learning rate: 0.00592 +2024-11-22 06:20:13.911506: train_loss -0.7872 +2024-11-22 06:20:13.916714: val_loss -0.7947 +2024-11-22 06:20:13.916860: Pseudo dice [0.8573] +2024-11-22 06:20:13.916948: Epoch time: 19.24 s +2024-11-22 06:20:14.884350: +2024-11-22 06:20:14.884573: Epoch 3535 +2024-11-22 06:20:14.884685: Current learning rate: 0.00592 +2024-11-22 06:20:32.901242: train_loss -0.7832 +2024-11-22 06:20:32.905622: val_loss -0.7554 +2024-11-22 06:20:32.905732: Pseudo dice [0.8546] +2024-11-22 06:20:32.905814: Epoch time: 18.02 s +2024-11-22 06:20:33.909360: +2024-11-22 06:20:33.909571: Epoch 3536 +2024-11-22 06:20:33.909687: Current learning rate: 0.00592 +2024-11-22 06:20:53.034057: train_loss -0.7861 +2024-11-22 06:20:53.035559: val_loss -0.7551 +2024-11-22 06:20:53.035645: Pseudo dice [0.8391] +2024-11-22 06:20:53.035726: Epoch time: 19.13 s +2024-11-22 06:20:53.876673: +2024-11-22 06:20:53.876877: Epoch 3537 +2024-11-22 06:20:53.876986: Current learning rate: 0.00591 +2024-11-22 06:21:13.511707: train_loss -0.7886 +2024-11-22 06:21:13.519139: val_loss -0.7702 +2024-11-22 06:21:13.519268: Pseudo dice [0.8545] +2024-11-22 06:21:13.519349: Epoch time: 19.64 s +2024-11-22 06:21:14.511584: +2024-11-22 06:21:14.511794: Epoch 3538 +2024-11-22 06:21:14.511918: Current learning rate: 0.00591 +2024-11-22 06:21:34.621734: train_loss -0.782 +2024-11-22 06:21:34.630805: val_loss -0.7297 +2024-11-22 06:21:34.630934: Pseudo dice [0.8325] +2024-11-22 06:21:34.631016: Epoch time: 20.11 s +2024-11-22 06:21:35.507705: +2024-11-22 06:21:35.507924: Epoch 3539 +2024-11-22 06:21:35.508037: Current learning rate: 0.00591 +2024-11-22 06:21:54.744284: train_loss -0.7852 +2024-11-22 06:21:54.751498: val_loss -0.762 +2024-11-22 06:21:54.751624: Pseudo dice [0.839] +2024-11-22 06:21:54.751717: Epoch time: 19.24 s +2024-11-22 06:21:56.074588: +2024-11-22 06:21:56.074888: Epoch 3540 +2024-11-22 06:21:56.075009: Current learning rate: 0.00591 +2024-11-22 06:22:14.959784: train_loss -0.7869 +2024-11-22 06:22:14.961369: val_loss -0.7664 +2024-11-22 06:22:14.961451: Pseudo dice [0.8493] +2024-11-22 06:22:14.961526: Epoch time: 18.89 s +2024-11-22 06:22:15.818760: +2024-11-22 06:22:15.818988: Epoch 3541 +2024-11-22 06:22:15.819108: Current learning rate: 0.00591 +2024-11-22 06:22:34.729444: train_loss -0.7827 +2024-11-22 06:22:34.731425: val_loss -0.7589 +2024-11-22 06:22:34.731558: Pseudo dice [0.8533] +2024-11-22 06:22:34.731781: Epoch time: 18.91 s +2024-11-22 06:22:35.584944: +2024-11-22 06:22:35.585152: Epoch 3542 +2024-11-22 06:22:35.585264: Current learning rate: 0.00591 +2024-11-22 06:22:54.887133: train_loss -0.745 +2024-11-22 06:22:54.890543: val_loss -0.7446 +2024-11-22 06:22:54.890680: Pseudo dice [0.8225] +2024-11-22 06:22:54.890768: Epoch time: 19.3 s +2024-11-22 06:22:55.738904: +2024-11-22 06:22:55.739102: Epoch 3543 +2024-11-22 06:22:55.739216: Current learning rate: 0.00591 +2024-11-22 06:23:14.700124: train_loss -0.7573 +2024-11-22 06:23:14.702460: val_loss -0.7525 +2024-11-22 06:23:14.702573: Pseudo dice [0.8456] +2024-11-22 06:23:14.702654: Epoch time: 18.96 s +2024-11-22 06:23:15.552113: +2024-11-22 06:23:15.552335: Epoch 3544 +2024-11-22 06:23:15.552449: Current learning rate: 0.00591 +2024-11-22 06:23:34.643699: train_loss -0.7707 +2024-11-22 06:23:34.649874: val_loss -0.7871 +2024-11-22 06:23:34.649996: Pseudo dice [0.8581] +2024-11-22 06:23:34.650082: Epoch time: 19.09 s +2024-11-22 06:23:35.605152: +2024-11-22 06:23:35.605372: Epoch 3545 +2024-11-22 06:23:35.605492: Current learning rate: 0.0059 +2024-11-22 06:23:54.627154: train_loss -0.7731 +2024-11-22 06:23:54.630965: val_loss -0.7717 +2024-11-22 06:23:54.631073: Pseudo dice [0.8479] +2024-11-22 06:23:54.631165: Epoch time: 19.02 s +2024-11-22 06:23:55.667488: +2024-11-22 06:23:55.667689: Epoch 3546 +2024-11-22 06:23:55.667803: Current learning rate: 0.0059 +2024-11-22 06:24:13.492785: train_loss -0.7675 +2024-11-22 06:24:13.494939: val_loss -0.7667 +2024-11-22 06:24:13.495077: Pseudo dice [0.8527] +2024-11-22 06:24:13.495162: Epoch time: 17.83 s +2024-11-22 06:24:14.349293: +2024-11-22 06:24:14.349486: Epoch 3547 +2024-11-22 06:24:14.349599: Current learning rate: 0.0059 +2024-11-22 06:24:32.861353: train_loss -0.785 +2024-11-22 06:24:32.864171: val_loss -0.7701 +2024-11-22 06:24:32.864273: Pseudo dice [0.8546] +2024-11-22 06:24:32.864357: Epoch time: 18.51 s +2024-11-22 06:24:33.770383: +2024-11-22 06:24:33.770581: Epoch 3548 +2024-11-22 06:24:33.770694: Current learning rate: 0.0059 +2024-11-22 06:24:52.819272: train_loss -0.7818 +2024-11-22 06:24:52.824630: val_loss -0.7636 +2024-11-22 06:24:52.824748: Pseudo dice [0.852] +2024-11-22 06:24:52.824825: Epoch time: 19.05 s +2024-11-22 06:24:53.705806: +2024-11-22 06:24:53.706017: Epoch 3549 +2024-11-22 06:24:53.706145: Current learning rate: 0.0059 +2024-11-22 06:25:13.120879: train_loss -0.7856 +2024-11-22 06:25:13.127076: val_loss -0.745 +2024-11-22 06:25:13.127202: Pseudo dice [0.851] +2024-11-22 06:25:13.127279: Epoch time: 19.42 s +2024-11-22 06:25:14.232927: +2024-11-22 06:25:14.233124: Epoch 3550 +2024-11-22 06:25:14.233239: Current learning rate: 0.0059 +2024-11-22 06:25:32.925512: train_loss -0.7854 +2024-11-22 06:25:32.930513: val_loss -0.7662 +2024-11-22 06:25:32.930665: Pseudo dice [0.8521] +2024-11-22 06:25:32.930762: Epoch time: 18.69 s +2024-11-22 06:25:33.785051: +2024-11-22 06:25:33.785264: Epoch 3551 +2024-11-22 06:25:33.785382: Current learning rate: 0.0059 +2024-11-22 06:25:52.550589: train_loss -0.7836 +2024-11-22 06:25:52.557317: val_loss -0.7684 +2024-11-22 06:25:52.557453: Pseudo dice [0.847] +2024-11-22 06:25:52.557537: Epoch time: 18.77 s +2024-11-22 06:25:53.406080: +2024-11-22 06:25:53.406282: Epoch 3552 +2024-11-22 06:25:53.406643: Current learning rate: 0.0059 +2024-11-22 06:26:11.841224: train_loss -0.7832 +2024-11-22 06:26:11.859590: val_loss -0.7706 +2024-11-22 06:26:11.859731: Pseudo dice [0.8594] +2024-11-22 06:26:11.859815: Epoch time: 18.44 s +2024-11-22 06:26:12.760589: +2024-11-22 06:26:12.760814: Epoch 3553 +2024-11-22 06:26:12.760936: Current learning rate: 0.00589 +2024-11-22 06:26:31.680635: train_loss -0.7841 +2024-11-22 06:26:31.689201: val_loss -0.772 +2024-11-22 06:26:31.689332: Pseudo dice [0.8532] +2024-11-22 06:26:31.689425: Epoch time: 18.92 s +2024-11-22 06:26:32.544639: +2024-11-22 06:26:32.544839: Epoch 3554 +2024-11-22 06:26:32.544950: Current learning rate: 0.00589 +2024-11-22 06:26:51.916073: train_loss -0.7598 +2024-11-22 06:26:51.922869: val_loss -0.7744 +2024-11-22 06:26:51.922979: Pseudo dice [0.8501] +2024-11-22 06:26:51.923057: Epoch time: 19.37 s +2024-11-22 06:26:52.794857: +2024-11-22 06:26:52.795112: Epoch 3555 +2024-11-22 06:26:52.795227: Current learning rate: 0.00589 +2024-11-22 06:27:11.010674: train_loss -0.7867 +2024-11-22 06:27:11.019277: val_loss -0.7476 +2024-11-22 06:27:11.019408: Pseudo dice [0.8382] +2024-11-22 06:27:11.019487: Epoch time: 18.22 s +2024-11-22 06:27:11.885122: +2024-11-22 06:27:11.885328: Epoch 3556 +2024-11-22 06:27:11.885443: Current learning rate: 0.00589 +2024-11-22 06:27:30.686089: train_loss -0.7826 +2024-11-22 06:27:30.688155: val_loss -0.779 +2024-11-22 06:27:30.688246: Pseudo dice [0.8602] +2024-11-22 06:27:30.688325: Epoch time: 18.8 s +2024-11-22 06:27:31.536574: +2024-11-22 06:27:31.536772: Epoch 3557 +2024-11-22 06:27:31.536892: Current learning rate: 0.00589 +2024-11-22 06:27:50.894803: train_loss -0.7918 +2024-11-22 06:27:50.897674: val_loss -0.7659 +2024-11-22 06:27:50.897814: Pseudo dice [0.8524] +2024-11-22 06:27:50.897906: Epoch time: 19.36 s +2024-11-22 06:27:51.804085: +2024-11-22 06:27:51.804311: Epoch 3558 +2024-11-22 06:27:51.804421: Current learning rate: 0.00589 +2024-11-22 06:28:09.920752: train_loss -0.7816 +2024-11-22 06:28:09.927481: val_loss -0.7821 +2024-11-22 06:28:09.927701: Pseudo dice [0.8509] +2024-11-22 06:28:09.927789: Epoch time: 18.12 s +2024-11-22 06:28:10.958964: +2024-11-22 06:28:10.959150: Epoch 3559 +2024-11-22 06:28:10.959262: Current learning rate: 0.00589 +2024-11-22 06:28:30.745254: train_loss -0.7787 +2024-11-22 06:28:30.747678: val_loss -0.7559 +2024-11-22 06:28:30.747791: Pseudo dice [0.8706] +2024-11-22 06:28:30.747877: Epoch time: 19.79 s +2024-11-22 06:28:31.600232: +2024-11-22 06:28:31.600427: Epoch 3560 +2024-11-22 06:28:31.600543: Current learning rate: 0.00589 +2024-11-22 06:28:50.490381: train_loss -0.7811 +2024-11-22 06:28:50.492578: val_loss -0.7695 +2024-11-22 06:28:50.492671: Pseudo dice [0.835] +2024-11-22 06:28:50.492754: Epoch time: 18.89 s +2024-11-22 06:28:51.340921: +2024-11-22 06:28:51.341141: Epoch 3561 +2024-11-22 06:28:51.341278: Current learning rate: 0.00589 +2024-11-22 06:29:09.366366: train_loss -0.7837 +2024-11-22 06:29:09.368911: val_loss -0.7762 +2024-11-22 06:29:09.369004: Pseudo dice [0.8601] +2024-11-22 06:29:09.369088: Epoch time: 18.03 s +2024-11-22 06:29:10.609648: +2024-11-22 06:29:10.609860: Epoch 3562 +2024-11-22 06:29:10.609978: Current learning rate: 0.00588 +2024-11-22 06:29:30.724608: train_loss -0.7783 +2024-11-22 06:29:30.733948: val_loss -0.763 +2024-11-22 06:29:30.734090: Pseudo dice [0.8556] +2024-11-22 06:29:30.734176: Epoch time: 20.12 s +2024-11-22 06:29:31.611753: +2024-11-22 06:29:31.611952: Epoch 3563 +2024-11-22 06:29:31.612071: Current learning rate: 0.00588 +2024-11-22 06:29:50.084645: train_loss -0.7794 +2024-11-22 06:29:50.091272: val_loss -0.76 +2024-11-22 06:29:50.091524: Pseudo dice [0.8566] +2024-11-22 06:29:50.091681: Epoch time: 18.47 s +2024-11-22 06:29:50.945634: +2024-11-22 06:29:50.945842: Epoch 3564 +2024-11-22 06:29:50.945950: Current learning rate: 0.00588 +2024-11-22 06:30:09.220649: train_loss -0.7861 +2024-11-22 06:30:09.228978: val_loss -0.7573 +2024-11-22 06:30:09.229135: Pseudo dice [0.8463] +2024-11-22 06:30:09.229506: Epoch time: 18.28 s +2024-11-22 06:30:10.091103: +2024-11-22 06:30:10.091349: Epoch 3565 +2024-11-22 06:30:10.091480: Current learning rate: 0.00588 +2024-11-22 06:30:29.511449: train_loss -0.7913 +2024-11-22 06:30:29.519158: val_loss -0.7763 +2024-11-22 06:30:29.519270: Pseudo dice [0.84] +2024-11-22 06:30:29.519350: Epoch time: 19.42 s +2024-11-22 06:30:30.650306: +2024-11-22 06:30:30.650542: Epoch 3566 +2024-11-22 06:30:30.650652: Current learning rate: 0.00588 +2024-11-22 06:30:47.659476: train_loss -0.7877 +2024-11-22 06:30:47.667072: val_loss -0.7802 +2024-11-22 06:30:47.667180: Pseudo dice [0.862] +2024-11-22 06:30:47.667262: Epoch time: 17.01 s +2024-11-22 06:30:48.563387: +2024-11-22 06:30:48.563595: Epoch 3567 +2024-11-22 06:30:48.563707: Current learning rate: 0.00588 +2024-11-22 06:31:08.031220: train_loss -0.7942 +2024-11-22 06:31:08.037479: val_loss -0.772 +2024-11-22 06:31:08.037605: Pseudo dice [0.8564] +2024-11-22 06:31:08.037688: Epoch time: 19.47 s +2024-11-22 06:31:09.013133: +2024-11-22 06:31:09.013331: Epoch 3568 +2024-11-22 06:31:09.013443: Current learning rate: 0.00588 +2024-11-22 06:31:28.204772: train_loss -0.7888 +2024-11-22 06:31:28.208471: val_loss -0.769 +2024-11-22 06:31:28.208580: Pseudo dice [0.8563] +2024-11-22 06:31:28.208670: Epoch time: 19.19 s +2024-11-22 06:31:29.061888: +2024-11-22 06:31:29.062094: Epoch 3569 +2024-11-22 06:31:29.062209: Current learning rate: 0.00588 +2024-11-22 06:31:48.373295: train_loss -0.7786 +2024-11-22 06:31:48.375415: val_loss -0.7541 +2024-11-22 06:31:48.375506: Pseudo dice [0.8369] +2024-11-22 06:31:48.375583: Epoch time: 19.31 s +2024-11-22 06:31:49.230367: +2024-11-22 06:31:49.230556: Epoch 3570 +2024-11-22 06:31:49.230668: Current learning rate: 0.00587 +2024-11-22 06:32:08.104547: train_loss -0.781 +2024-11-22 06:32:08.110768: val_loss -0.7718 +2024-11-22 06:32:08.110879: Pseudo dice [0.8564] +2024-11-22 06:32:08.110955: Epoch time: 18.87 s +2024-11-22 06:32:09.089119: +2024-11-22 06:32:09.089336: Epoch 3571 +2024-11-22 06:32:09.089454: Current learning rate: 0.00587 +2024-11-22 06:32:28.848567: train_loss -0.7728 +2024-11-22 06:32:28.859899: val_loss -0.764 +2024-11-22 06:32:28.860024: Pseudo dice [0.8474] +2024-11-22 06:32:28.860122: Epoch time: 19.76 s +2024-11-22 06:32:29.728967: +2024-11-22 06:32:29.729172: Epoch 3572 +2024-11-22 06:32:29.729286: Current learning rate: 0.00587 +2024-11-22 06:32:48.208465: train_loss -0.7772 +2024-11-22 06:32:48.210852: val_loss -0.7736 +2024-11-22 06:32:48.210957: Pseudo dice [0.8494] +2024-11-22 06:32:48.211045: Epoch time: 18.48 s +2024-11-22 06:32:49.459890: +2024-11-22 06:32:49.460130: Epoch 3573 +2024-11-22 06:32:49.460243: Current learning rate: 0.00587 +2024-11-22 06:33:09.690405: train_loss -0.7872 +2024-11-22 06:33:09.702732: val_loss -0.771 +2024-11-22 06:33:09.702858: Pseudo dice [0.8564] +2024-11-22 06:33:09.702950: Epoch time: 20.23 s +2024-11-22 06:33:10.557873: +2024-11-22 06:33:10.558102: Epoch 3574 +2024-11-22 06:33:10.558222: Current learning rate: 0.00587 +2024-11-22 06:33:29.439206: train_loss -0.7691 +2024-11-22 06:33:29.444587: val_loss -0.7619 +2024-11-22 06:33:29.444714: Pseudo dice [0.8429] +2024-11-22 06:33:29.444802: Epoch time: 18.88 s +2024-11-22 06:33:30.444596: +2024-11-22 06:33:30.444814: Epoch 3575 +2024-11-22 06:33:30.444926: Current learning rate: 0.00587 +2024-11-22 06:33:49.011282: train_loss -0.7924 +2024-11-22 06:33:49.021243: val_loss -0.7507 +2024-11-22 06:33:49.021387: Pseudo dice [0.8426] +2024-11-22 06:33:49.021477: Epoch time: 18.57 s +2024-11-22 06:33:49.883830: +2024-11-22 06:33:49.884023: Epoch 3576 +2024-11-22 06:33:49.884140: Current learning rate: 0.00587 +2024-11-22 06:34:09.478338: train_loss -0.7787 +2024-11-22 06:34:09.485855: val_loss -0.7723 +2024-11-22 06:34:09.485983: Pseudo dice [0.8532] +2024-11-22 06:34:09.486067: Epoch time: 19.6 s +2024-11-22 06:34:10.413525: +2024-11-22 06:34:10.413779: Epoch 3577 +2024-11-22 06:34:10.413889: Current learning rate: 0.00587 +2024-11-22 06:34:28.787036: train_loss -0.7793 +2024-11-22 06:34:28.789322: val_loss -0.7968 +2024-11-22 06:34:28.789448: Pseudo dice [0.8591] +2024-11-22 06:34:28.789528: Epoch time: 18.37 s +2024-11-22 06:34:29.639443: +2024-11-22 06:34:29.639635: Epoch 3578 +2024-11-22 06:34:29.639747: Current learning rate: 0.00587 +2024-11-22 06:34:48.228665: train_loss -0.7845 +2024-11-22 06:34:48.242245: val_loss -0.7966 +2024-11-22 06:34:48.242372: Pseudo dice [0.8553] +2024-11-22 06:34:48.242450: Epoch time: 18.59 s +2024-11-22 06:34:49.097961: +2024-11-22 06:34:49.098200: Epoch 3579 +2024-11-22 06:34:49.098313: Current learning rate: 0.00586 +2024-11-22 06:35:08.191941: train_loss -0.7937 +2024-11-22 06:35:08.198508: val_loss -0.785 +2024-11-22 06:35:08.198640: Pseudo dice [0.8469] +2024-11-22 06:35:08.198738: Epoch time: 19.09 s +2024-11-22 06:35:09.057180: +2024-11-22 06:35:09.057400: Epoch 3580 +2024-11-22 06:35:09.057514: Current learning rate: 0.00586 +2024-11-22 06:35:28.344964: train_loss -0.7928 +2024-11-22 06:35:28.355984: val_loss -0.7739 +2024-11-22 06:35:28.356130: Pseudo dice [0.8456] +2024-11-22 06:35:28.356212: Epoch time: 19.29 s +2024-11-22 06:35:29.212852: +2024-11-22 06:35:29.213067: Epoch 3581 +2024-11-22 06:35:29.213180: Current learning rate: 0.00586 +2024-11-22 06:35:47.779402: train_loss -0.7877 +2024-11-22 06:35:47.785347: val_loss -0.7695 +2024-11-22 06:35:47.785455: Pseudo dice [0.8611] +2024-11-22 06:35:47.785534: Epoch time: 18.57 s +2024-11-22 06:35:48.827897: +2024-11-22 06:35:48.828085: Epoch 3582 +2024-11-22 06:35:48.828198: Current learning rate: 0.00586 +2024-11-22 06:36:08.032292: train_loss -0.7866 +2024-11-22 06:36:08.034500: val_loss -0.7719 +2024-11-22 06:36:08.034610: Pseudo dice [0.8499] +2024-11-22 06:36:08.034689: Epoch time: 19.21 s +2024-11-22 06:36:08.891797: +2024-11-22 06:36:08.891999: Epoch 3583 +2024-11-22 06:36:08.892121: Current learning rate: 0.00586 +2024-11-22 06:36:27.711251: train_loss -0.7879 +2024-11-22 06:36:27.725146: val_loss -0.7711 +2024-11-22 06:36:27.725288: Pseudo dice [0.8463] +2024-11-22 06:36:27.725375: Epoch time: 18.82 s +2024-11-22 06:36:29.172141: +2024-11-22 06:36:29.172363: Epoch 3584 +2024-11-22 06:36:29.172474: Current learning rate: 0.00586 +2024-11-22 06:36:47.929319: train_loss -0.783 +2024-11-22 06:36:47.933856: val_loss -0.7768 +2024-11-22 06:36:47.934045: Pseudo dice [0.8455] +2024-11-22 06:36:47.934135: Epoch time: 18.76 s +2024-11-22 06:36:48.805695: +2024-11-22 06:36:48.805894: Epoch 3585 +2024-11-22 06:36:48.806010: Current learning rate: 0.00586 +2024-11-22 06:37:06.428660: train_loss -0.7841 +2024-11-22 06:37:06.435636: val_loss -0.7316 +2024-11-22 06:37:06.435761: Pseudo dice [0.8336] +2024-11-22 06:37:06.435843: Epoch time: 17.62 s +2024-11-22 06:37:07.289674: +2024-11-22 06:37:07.289884: Epoch 3586 +2024-11-22 06:37:07.289992: Current learning rate: 0.00586 +2024-11-22 06:37:25.573838: train_loss -0.7835 +2024-11-22 06:37:25.575372: val_loss -0.7579 +2024-11-22 06:37:25.575461: Pseudo dice [0.8494] +2024-11-22 06:37:25.575546: Epoch time: 18.28 s +2024-11-22 06:37:26.431136: +2024-11-22 06:37:26.431413: Epoch 3587 +2024-11-22 06:37:26.431534: Current learning rate: 0.00585 +2024-11-22 06:37:46.201114: train_loss -0.8012 +2024-11-22 06:37:46.204350: val_loss -0.7768 +2024-11-22 06:37:46.204515: Pseudo dice [0.8491] +2024-11-22 06:37:46.204598: Epoch time: 19.77 s +2024-11-22 06:37:47.173870: +2024-11-22 06:37:47.174076: Epoch 3588 +2024-11-22 06:37:47.174190: Current learning rate: 0.00585 +2024-11-22 06:38:05.509278: train_loss -0.7876 +2024-11-22 06:38:05.512812: val_loss -0.7746 +2024-11-22 06:38:05.512952: Pseudo dice [0.837] +2024-11-22 06:38:05.513036: Epoch time: 18.34 s +2024-11-22 06:38:06.372187: +2024-11-22 06:38:06.372403: Epoch 3589 +2024-11-22 06:38:06.372512: Current learning rate: 0.00585 +2024-11-22 06:38:25.225142: train_loss -0.7886 +2024-11-22 06:38:25.232518: val_loss -0.7717 +2024-11-22 06:38:25.232654: Pseudo dice [0.8515] +2024-11-22 06:38:25.232744: Epoch time: 18.85 s +2024-11-22 06:38:26.111667: +2024-11-22 06:38:26.111891: Epoch 3590 +2024-11-22 06:38:26.124116: Current learning rate: 0.00585 +2024-11-22 06:38:46.486692: train_loss -0.7839 +2024-11-22 06:38:46.488661: val_loss -0.7645 +2024-11-22 06:38:46.488752: Pseudo dice [0.8517] +2024-11-22 06:38:46.488838: Epoch time: 20.38 s +2024-11-22 06:38:47.347395: +2024-11-22 06:38:47.347593: Epoch 3591 +2024-11-22 06:38:47.347706: Current learning rate: 0.00585 +2024-11-22 06:39:07.134139: train_loss -0.7838 +2024-11-22 06:39:07.139758: val_loss -0.7731 +2024-11-22 06:39:07.139879: Pseudo dice [0.8496] +2024-11-22 06:39:07.139964: Epoch time: 19.79 s +2024-11-22 06:39:08.201963: +2024-11-22 06:39:08.202172: Epoch 3592 +2024-11-22 06:39:08.202282: Current learning rate: 0.00585 +2024-11-22 06:39:27.724739: train_loss -0.7775 +2024-11-22 06:39:27.727281: val_loss -0.7468 +2024-11-22 06:39:27.727420: Pseudo dice [0.845] +2024-11-22 06:39:27.727498: Epoch time: 19.52 s +2024-11-22 06:39:28.616832: +2024-11-22 06:39:28.617033: Epoch 3593 +2024-11-22 06:39:28.617152: Current learning rate: 0.00585 +2024-11-22 06:39:47.476080: train_loss -0.7861 +2024-11-22 06:39:47.478516: val_loss -0.7598 +2024-11-22 06:39:47.478649: Pseudo dice [0.8346] +2024-11-22 06:39:47.478735: Epoch time: 18.86 s +2024-11-22 06:39:48.339139: +2024-11-22 06:39:48.339332: Epoch 3594 +2024-11-22 06:39:48.339441: Current learning rate: 0.00585 +2024-11-22 06:40:08.567266: train_loss -0.7833 +2024-11-22 06:40:08.576989: val_loss -0.7712 +2024-11-22 06:40:08.577126: Pseudo dice [0.8432] +2024-11-22 06:40:08.577217: Epoch time: 20.23 s +2024-11-22 06:40:09.916801: +2024-11-22 06:40:09.917012: Epoch 3595 +2024-11-22 06:40:09.917130: Current learning rate: 0.00584 +2024-11-22 06:40:28.214743: train_loss -0.7775 +2024-11-22 06:40:28.226616: val_loss -0.7645 +2024-11-22 06:40:28.226748: Pseudo dice [0.8444] +2024-11-22 06:40:28.226825: Epoch time: 18.3 s +2024-11-22 06:40:29.194816: +2024-11-22 06:40:29.195019: Epoch 3596 +2024-11-22 06:40:29.195134: Current learning rate: 0.00584 +2024-11-22 06:40:48.074337: train_loss -0.7869 +2024-11-22 06:40:48.079586: val_loss -0.7685 +2024-11-22 06:40:48.079691: Pseudo dice [0.8416] +2024-11-22 06:40:48.079771: Epoch time: 18.88 s +2024-11-22 06:40:48.953842: +2024-11-22 06:40:48.954072: Epoch 3597 +2024-11-22 06:40:48.954187: Current learning rate: 0.00584 +2024-11-22 06:41:07.138741: train_loss -0.7877 +2024-11-22 06:41:07.143656: val_loss -0.7777 +2024-11-22 06:41:07.143789: Pseudo dice [0.849] +2024-11-22 06:41:07.143879: Epoch time: 18.19 s +2024-11-22 06:41:08.100637: +2024-11-22 06:41:08.100869: Epoch 3598 +2024-11-22 06:41:08.100985: Current learning rate: 0.00584 +2024-11-22 06:41:28.038421: train_loss -0.7941 +2024-11-22 06:41:28.039871: val_loss -0.7876 +2024-11-22 06:41:28.039965: Pseudo dice [0.8584] +2024-11-22 06:41:28.040046: Epoch time: 19.94 s +2024-11-22 06:41:28.907516: +2024-11-22 06:41:28.907715: Epoch 3599 +2024-11-22 06:41:28.907821: Current learning rate: 0.00584 +2024-11-22 06:41:47.144571: train_loss -0.7726 +2024-11-22 06:41:47.157320: val_loss -0.7677 +2024-11-22 06:41:47.157447: Pseudo dice [0.8505] +2024-11-22 06:41:47.157532: Epoch time: 18.24 s +2024-11-22 06:41:48.418406: +2024-11-22 06:41:48.418637: Epoch 3600 +2024-11-22 06:41:48.418754: Current learning rate: 0.00584 +2024-11-22 06:42:07.287320: train_loss -0.7799 +2024-11-22 06:42:07.293805: val_loss -0.7688 +2024-11-22 06:42:07.293923: Pseudo dice [0.8293] +2024-11-22 06:42:07.294001: Epoch time: 18.87 s +2024-11-22 06:42:08.147975: +2024-11-22 06:42:08.148211: Epoch 3601 +2024-11-22 06:42:08.148322: Current learning rate: 0.00584 +2024-11-22 06:42:26.920250: train_loss -0.7867 +2024-11-22 06:42:26.923786: val_loss -0.7989 +2024-11-22 06:42:26.923893: Pseudo dice [0.865] +2024-11-22 06:42:26.923982: Epoch time: 18.77 s +2024-11-22 06:42:27.823925: +2024-11-22 06:42:27.824139: Epoch 3602 +2024-11-22 06:42:27.824247: Current learning rate: 0.00584 +2024-11-22 06:42:46.406658: train_loss -0.7911 +2024-11-22 06:42:46.408916: val_loss -0.781 +2024-11-22 06:42:46.409016: Pseudo dice [0.8535] +2024-11-22 06:42:46.409097: Epoch time: 18.58 s +2024-11-22 06:42:47.262860: +2024-11-22 06:42:47.263052: Epoch 3603 +2024-11-22 06:42:47.263166: Current learning rate: 0.00584 +2024-11-22 06:43:05.440577: train_loss -0.7878 +2024-11-22 06:43:05.443678: val_loss -0.7833 +2024-11-22 06:43:05.443803: Pseudo dice [0.855] +2024-11-22 06:43:05.443887: Epoch time: 18.18 s +2024-11-22 06:43:06.302413: +2024-11-22 06:43:06.302612: Epoch 3604 +2024-11-22 06:43:06.302726: Current learning rate: 0.00583 +2024-11-22 06:43:24.358701: train_loss -0.7774 +2024-11-22 06:43:24.360561: val_loss -0.7905 +2024-11-22 06:43:24.360652: Pseudo dice [0.8624] +2024-11-22 06:43:24.360738: Epoch time: 18.06 s +2024-11-22 06:43:25.213069: +2024-11-22 06:43:25.213274: Epoch 3605 +2024-11-22 06:43:25.213390: Current learning rate: 0.00583 +2024-11-22 06:43:44.058428: train_loss -0.7805 +2024-11-22 06:43:44.063984: val_loss -0.7762 +2024-11-22 06:43:44.064115: Pseudo dice [0.8555] +2024-11-22 06:43:44.064196: Epoch time: 18.85 s +2024-11-22 06:43:45.420995: +2024-11-22 06:43:45.421191: Epoch 3606 +2024-11-22 06:43:45.421303: Current learning rate: 0.00583 +2024-11-22 06:44:04.227044: train_loss -0.7879 +2024-11-22 06:44:04.231327: val_loss -0.7633 +2024-11-22 06:44:04.231446: Pseudo dice [0.8497] +2024-11-22 06:44:04.231526: Epoch time: 18.81 s +2024-11-22 06:44:05.086456: +2024-11-22 06:44:05.086711: Epoch 3607 +2024-11-22 06:44:05.086824: Current learning rate: 0.00583 +2024-11-22 06:44:23.801685: train_loss -0.7807 +2024-11-22 06:44:23.803445: val_loss -0.7692 +2024-11-22 06:44:23.803547: Pseudo dice [0.842] +2024-11-22 06:44:23.803623: Epoch time: 18.72 s +2024-11-22 06:44:24.827268: +2024-11-22 06:44:24.827495: Epoch 3608 +2024-11-22 06:44:24.827605: Current learning rate: 0.00583 +2024-11-22 06:44:44.220851: train_loss -0.7761 +2024-11-22 06:44:44.236372: val_loss -0.7695 +2024-11-22 06:44:44.236519: Pseudo dice [0.8501] +2024-11-22 06:44:44.236607: Epoch time: 19.39 s +2024-11-22 06:44:45.353594: +2024-11-22 06:44:45.353819: Epoch 3609 +2024-11-22 06:44:45.353934: Current learning rate: 0.00583 +2024-11-22 06:45:05.138019: train_loss -0.7783 +2024-11-22 06:45:05.145510: val_loss -0.7638 +2024-11-22 06:45:05.145632: Pseudo dice [0.8548] +2024-11-22 06:45:05.145714: Epoch time: 19.79 s +2024-11-22 06:45:06.249646: +2024-11-22 06:45:06.249849: Epoch 3610 +2024-11-22 06:45:06.249959: Current learning rate: 0.00583 +2024-11-22 06:45:24.333751: train_loss -0.7912 +2024-11-22 06:45:24.341382: val_loss -0.7589 +2024-11-22 06:45:24.341516: Pseudo dice [0.8564] +2024-11-22 06:45:24.341596: Epoch time: 18.08 s +2024-11-22 06:45:25.400974: +2024-11-22 06:45:25.401199: Epoch 3611 +2024-11-22 06:45:25.401314: Current learning rate: 0.00583 +2024-11-22 06:45:43.915197: train_loss -0.7966 +2024-11-22 06:45:43.918012: val_loss -0.7852 +2024-11-22 06:45:43.918134: Pseudo dice [0.852] +2024-11-22 06:45:43.918226: Epoch time: 18.52 s +2024-11-22 06:45:44.771576: +2024-11-22 06:45:44.771776: Epoch 3612 +2024-11-22 06:45:44.771891: Current learning rate: 0.00582 +2024-11-22 06:46:03.959629: train_loss -0.7898 +2024-11-22 06:46:03.967123: val_loss -0.7767 +2024-11-22 06:46:03.967247: Pseudo dice [0.8598] +2024-11-22 06:46:03.967335: Epoch time: 19.19 s +2024-11-22 06:46:04.974684: +2024-11-22 06:46:04.974886: Epoch 3613 +2024-11-22 06:46:04.975000: Current learning rate: 0.00582 +2024-11-22 06:46:24.111743: train_loss -0.7737 +2024-11-22 06:46:24.118965: val_loss -0.7574 +2024-11-22 06:46:24.119081: Pseudo dice [0.8486] +2024-11-22 06:46:24.119163: Epoch time: 19.14 s +2024-11-22 06:46:25.123862: +2024-11-22 06:46:25.124063: Epoch 3614 +2024-11-22 06:46:25.124175: Current learning rate: 0.00582 +2024-11-22 06:46:43.967916: train_loss -0.7799 +2024-11-22 06:46:43.973448: val_loss -0.7611 +2024-11-22 06:46:43.973566: Pseudo dice [0.8406] +2024-11-22 06:46:43.973646: Epoch time: 18.84 s +2024-11-22 06:46:44.976967: +2024-11-22 06:46:44.977163: Epoch 3615 +2024-11-22 06:46:44.977274: Current learning rate: 0.00582 +2024-11-22 06:47:03.173005: train_loss -0.7872 +2024-11-22 06:47:03.177493: val_loss -0.7649 +2024-11-22 06:47:03.191068: Pseudo dice [0.8443] +2024-11-22 06:47:03.191222: Epoch time: 18.2 s +2024-11-22 06:47:04.115608: +2024-11-22 06:47:04.115834: Epoch 3616 +2024-11-22 06:47:04.115943: Current learning rate: 0.00582 +2024-11-22 06:47:22.345078: train_loss -0.7877 +2024-11-22 06:47:22.352468: val_loss -0.7859 +2024-11-22 06:47:22.352604: Pseudo dice [0.8537] +2024-11-22 06:47:22.352690: Epoch time: 18.23 s +2024-11-22 06:47:23.736907: +2024-11-22 06:47:23.737126: Epoch 3617 +2024-11-22 06:47:23.737236: Current learning rate: 0.00582 +2024-11-22 06:47:43.487619: train_loss -0.7808 +2024-11-22 06:47:43.494727: val_loss -0.7977 +2024-11-22 06:47:43.494835: Pseudo dice [0.8532] +2024-11-22 06:47:43.494916: Epoch time: 19.75 s +2024-11-22 06:47:44.360074: +2024-11-22 06:47:44.360286: Epoch 3618 +2024-11-22 06:47:44.360400: Current learning rate: 0.00582 +2024-11-22 06:48:04.571499: train_loss -0.7768 +2024-11-22 06:48:04.575461: val_loss -0.7553 +2024-11-22 06:48:04.575576: Pseudo dice [0.8569] +2024-11-22 06:48:04.575663: Epoch time: 20.21 s +2024-11-22 06:48:05.478698: +2024-11-22 06:48:05.478891: Epoch 3619 +2024-11-22 06:48:05.479002: Current learning rate: 0.00582 +2024-11-22 06:48:23.182757: train_loss -0.7922 +2024-11-22 06:48:23.187483: val_loss -0.7606 +2024-11-22 06:48:23.187615: Pseudo dice [0.8601] +2024-11-22 06:48:23.187704: Epoch time: 17.7 s +2024-11-22 06:48:24.110446: +2024-11-22 06:48:24.110714: Epoch 3620 +2024-11-22 06:48:24.110832: Current learning rate: 0.00581 +2024-11-22 06:48:42.798998: train_loss -0.793 +2024-11-22 06:48:42.804454: val_loss -0.7711 +2024-11-22 06:48:42.804574: Pseudo dice [0.84] +2024-11-22 06:48:42.804654: Epoch time: 18.69 s +2024-11-22 06:48:43.725958: +2024-11-22 06:48:43.726192: Epoch 3621 +2024-11-22 06:48:43.726304: Current learning rate: 0.00581 +2024-11-22 06:49:01.587762: train_loss -0.7864 +2024-11-22 06:49:01.591022: val_loss -0.7865 +2024-11-22 06:49:01.591156: Pseudo dice [0.8591] +2024-11-22 06:49:01.591243: Epoch time: 17.86 s +2024-11-22 06:49:02.624294: +2024-11-22 06:49:02.624501: Epoch 3622 +2024-11-22 06:49:02.624618: Current learning rate: 0.00581 +2024-11-22 06:49:21.816308: train_loss -0.7828 +2024-11-22 06:49:21.818630: val_loss -0.7593 +2024-11-22 06:49:21.818756: Pseudo dice [0.8425] +2024-11-22 06:49:21.818843: Epoch time: 19.19 s +2024-11-22 06:49:22.678839: +2024-11-22 06:49:22.679101: Epoch 3623 +2024-11-22 06:49:22.679227: Current learning rate: 0.00581 +2024-11-22 06:49:42.703873: train_loss -0.801 +2024-11-22 06:49:42.709063: val_loss -0.7663 +2024-11-22 06:49:42.709228: Pseudo dice [0.847] +2024-11-22 06:49:42.709314: Epoch time: 20.03 s +2024-11-22 06:49:43.590197: +2024-11-22 06:49:43.590444: Epoch 3624 +2024-11-22 06:49:43.590563: Current learning rate: 0.00581 +2024-11-22 06:50:02.154238: train_loss -0.7854 +2024-11-22 06:50:02.159890: val_loss -0.7757 +2024-11-22 06:50:02.160025: Pseudo dice [0.8585] +2024-11-22 06:50:02.160115: Epoch time: 18.56 s +2024-11-22 06:50:03.107883: +2024-11-22 06:50:03.108113: Epoch 3625 +2024-11-22 06:50:03.108223: Current learning rate: 0.00581 +2024-11-22 06:50:22.201460: train_loss -0.7841 +2024-11-22 06:50:22.206413: val_loss -0.7454 +2024-11-22 06:50:22.206537: Pseudo dice [0.8452] +2024-11-22 06:50:22.206615: Epoch time: 19.09 s +2024-11-22 06:50:23.225109: +2024-11-22 06:50:23.225351: Epoch 3626 +2024-11-22 06:50:23.225467: Current learning rate: 0.00581 +2024-11-22 06:50:42.559814: train_loss -0.7896 +2024-11-22 06:50:42.566032: val_loss -0.7685 +2024-11-22 06:50:42.566166: Pseudo dice [0.8468] +2024-11-22 06:50:42.566254: Epoch time: 19.34 s +2024-11-22 06:50:43.500883: +2024-11-22 06:50:43.501095: Epoch 3627 +2024-11-22 06:50:43.501207: Current learning rate: 0.00581 +2024-11-22 06:51:01.940008: train_loss -0.7882 +2024-11-22 06:51:01.942937: val_loss -0.7683 +2024-11-22 06:51:01.943033: Pseudo dice [0.8463] +2024-11-22 06:51:01.943119: Epoch time: 18.44 s +2024-11-22 06:51:03.184886: +2024-11-22 06:51:03.185098: Epoch 3628 +2024-11-22 06:51:03.185215: Current learning rate: 0.00581 +2024-11-22 06:51:22.042392: train_loss -0.785 +2024-11-22 06:51:22.049541: val_loss -0.751 +2024-11-22 06:51:22.049667: Pseudo dice [0.8423] +2024-11-22 06:51:22.049751: Epoch time: 18.86 s +2024-11-22 06:51:23.196898: +2024-11-22 06:51:23.197110: Epoch 3629 +2024-11-22 06:51:23.197226: Current learning rate: 0.0058 +2024-11-22 06:51:42.451985: train_loss -0.7818 +2024-11-22 06:51:42.457405: val_loss -0.7601 +2024-11-22 06:51:42.457535: Pseudo dice [0.8353] +2024-11-22 06:51:42.457630: Epoch time: 19.26 s +2024-11-22 06:51:43.322928: +2024-11-22 06:51:43.323169: Epoch 3630 +2024-11-22 06:51:43.323281: Current learning rate: 0.0058 +2024-11-22 06:52:02.286177: train_loss -0.7856 +2024-11-22 06:52:02.289342: val_loss -0.7351 +2024-11-22 06:52:02.289444: Pseudo dice [0.8303] +2024-11-22 06:52:02.289526: Epoch time: 18.96 s +2024-11-22 06:52:03.235578: +2024-11-22 06:52:03.235785: Epoch 3631 +2024-11-22 06:52:03.235898: Current learning rate: 0.0058 +2024-11-22 06:52:22.213736: train_loss -0.788 +2024-11-22 06:52:22.219118: val_loss -0.763 +2024-11-22 06:52:22.219229: Pseudo dice [0.8577] +2024-11-22 06:52:22.219310: Epoch time: 18.98 s +2024-11-22 06:52:23.083458: +2024-11-22 06:52:23.083667: Epoch 3632 +2024-11-22 06:52:23.083776: Current learning rate: 0.0058 +2024-11-22 06:52:41.817203: train_loss -0.7911 +2024-11-22 06:52:41.826219: val_loss -0.7733 +2024-11-22 06:52:41.826474: Pseudo dice [0.8594] +2024-11-22 06:52:41.826619: Epoch time: 18.73 s +2024-11-22 06:52:42.683796: +2024-11-22 06:52:42.684046: Epoch 3633 +2024-11-22 06:52:42.684160: Current learning rate: 0.0058 +2024-11-22 06:53:01.370705: train_loss -0.7906 +2024-11-22 06:53:01.377080: val_loss -0.7488 +2024-11-22 06:53:01.377196: Pseudo dice [0.8512] +2024-11-22 06:53:01.377281: Epoch time: 18.69 s +2024-11-22 06:53:02.442301: +2024-11-22 06:53:02.442522: Epoch 3634 +2024-11-22 06:53:02.442676: Current learning rate: 0.0058 +2024-11-22 06:53:21.498173: train_loss -0.7827 +2024-11-22 06:53:21.503925: val_loss -0.7748 +2024-11-22 06:53:21.504057: Pseudo dice [0.8562] +2024-11-22 06:53:21.504153: Epoch time: 19.06 s +2024-11-22 06:53:22.410401: +2024-11-22 06:53:22.410597: Epoch 3635 +2024-11-22 06:53:22.410714: Current learning rate: 0.0058 +2024-11-22 06:53:40.860082: train_loss -0.7867 +2024-11-22 06:53:40.862927: val_loss -0.7474 +2024-11-22 06:53:40.863063: Pseudo dice [0.8495] +2024-11-22 06:53:40.863141: Epoch time: 18.45 s +2024-11-22 06:53:41.733202: +2024-11-22 06:53:41.733405: Epoch 3636 +2024-11-22 06:53:41.733517: Current learning rate: 0.0058 +2024-11-22 06:54:00.990933: train_loss -0.7868 +2024-11-22 06:54:01.001163: val_loss -0.7678 +2024-11-22 06:54:01.001323: Pseudo dice [0.8606] +2024-11-22 06:54:01.002628: Epoch time: 19.26 s +2024-11-22 06:54:01.861596: +2024-11-22 06:54:01.861830: Epoch 3637 +2024-11-22 06:54:01.861959: Current learning rate: 0.00579 +2024-11-22 06:54:20.946471: train_loss -0.7824 +2024-11-22 06:54:20.953812: val_loss -0.7763 +2024-11-22 06:54:20.953945: Pseudo dice [0.8565] +2024-11-22 06:54:20.954030: Epoch time: 19.09 s +2024-11-22 06:54:21.829184: +2024-11-22 06:54:21.829463: Epoch 3638 +2024-11-22 06:54:21.829578: Current learning rate: 0.00579 +2024-11-22 06:54:40.945934: train_loss -0.7936 +2024-11-22 06:54:40.953162: val_loss -0.7918 +2024-11-22 06:54:40.953290: Pseudo dice [0.8645] +2024-11-22 06:54:40.953370: Epoch time: 19.12 s +2024-11-22 06:54:42.211126: +2024-11-22 06:54:42.211350: Epoch 3639 +2024-11-22 06:54:42.211465: Current learning rate: 0.00579 +2024-11-22 06:55:01.465816: train_loss -0.7861 +2024-11-22 06:55:01.471075: val_loss -0.7747 +2024-11-22 06:55:01.471212: Pseudo dice [0.8607] +2024-11-22 06:55:01.471301: Epoch time: 19.26 s +2024-11-22 06:55:02.333721: +2024-11-22 06:55:02.333936: Epoch 3640 +2024-11-22 06:55:02.334048: Current learning rate: 0.00579 +2024-11-22 06:55:21.007905: train_loss -0.7807 +2024-11-22 06:55:21.015257: val_loss -0.7646 +2024-11-22 06:55:21.015393: Pseudo dice [0.8485] +2024-11-22 06:55:21.015479: Epoch time: 18.68 s +2024-11-22 06:55:21.928558: +2024-11-22 06:55:21.929087: Epoch 3641 +2024-11-22 06:55:21.929207: Current learning rate: 0.00579 +2024-11-22 06:55:40.494057: train_loss -0.7914 +2024-11-22 06:55:40.500302: val_loss -0.7714 +2024-11-22 06:55:40.500422: Pseudo dice [0.8448] +2024-11-22 06:55:40.500504: Epoch time: 18.57 s +2024-11-22 06:55:41.402017: +2024-11-22 06:55:41.402246: Epoch 3642 +2024-11-22 06:55:41.402361: Current learning rate: 0.00579 +2024-11-22 06:56:00.244779: train_loss -0.7921 +2024-11-22 06:56:00.249613: val_loss -0.7679 +2024-11-22 06:56:00.249750: Pseudo dice [0.8472] +2024-11-22 06:56:00.249831: Epoch time: 18.84 s +2024-11-22 06:56:01.111203: +2024-11-22 06:56:01.111435: Epoch 3643 +2024-11-22 06:56:01.111555: Current learning rate: 0.00579 +2024-11-22 06:56:19.785549: train_loss -0.7829 +2024-11-22 06:56:19.799205: val_loss -0.7585 +2024-11-22 06:56:19.799342: Pseudo dice [0.8434] +2024-11-22 06:56:19.799433: Epoch time: 18.68 s +2024-11-22 06:56:20.683575: +2024-11-22 06:56:20.683825: Epoch 3644 +2024-11-22 06:56:20.683942: Current learning rate: 0.00579 +2024-11-22 06:56:38.222673: train_loss -0.7799 +2024-11-22 06:56:38.223624: val_loss -0.7531 +2024-11-22 06:56:38.223709: Pseudo dice [0.8506] +2024-11-22 06:56:38.223784: Epoch time: 17.54 s +2024-11-22 06:56:39.072213: +2024-11-22 06:56:39.072419: Epoch 3645 +2024-11-22 06:56:39.072539: Current learning rate: 0.00579 +2024-11-22 06:56:58.325659: train_loss -0.7889 +2024-11-22 06:56:58.327693: val_loss -0.7501 +2024-11-22 06:56:58.327811: Pseudo dice [0.8469] +2024-11-22 06:56:58.327894: Epoch time: 19.25 s +2024-11-22 06:56:59.179857: +2024-11-22 06:56:59.180070: Epoch 3646 +2024-11-22 06:56:59.180186: Current learning rate: 0.00578 +2024-11-22 06:57:19.673053: train_loss -0.7841 +2024-11-22 06:57:19.674722: val_loss -0.7736 +2024-11-22 06:57:19.674813: Pseudo dice [0.8668] +2024-11-22 06:57:19.674897: Epoch time: 20.49 s +2024-11-22 06:57:20.526503: +2024-11-22 06:57:20.526712: Epoch 3647 +2024-11-22 06:57:20.526829: Current learning rate: 0.00578 +2024-11-22 06:57:39.511355: train_loss -0.7817 +2024-11-22 06:57:39.517771: val_loss -0.7967 +2024-11-22 06:57:39.517886: Pseudo dice [0.8533] +2024-11-22 06:57:39.517976: Epoch time: 18.99 s +2024-11-22 06:57:40.488341: +2024-11-22 06:57:40.488554: Epoch 3648 +2024-11-22 06:57:40.488667: Current learning rate: 0.00578 +2024-11-22 06:57:59.125592: train_loss -0.7852 +2024-11-22 06:57:59.127775: val_loss -0.7646 +2024-11-22 06:57:59.127884: Pseudo dice [0.8577] +2024-11-22 06:57:59.127963: Epoch time: 18.64 s +2024-11-22 06:57:59.976998: +2024-11-22 06:57:59.977206: Epoch 3649 +2024-11-22 06:57:59.977316: Current learning rate: 0.00578 +2024-11-22 06:58:18.586144: train_loss -0.7894 +2024-11-22 06:58:18.590437: val_loss -0.7631 +2024-11-22 06:58:18.590539: Pseudo dice [0.8367] +2024-11-22 06:58:18.590618: Epoch time: 18.61 s +2024-11-22 06:58:20.121589: +2024-11-22 06:58:20.121798: Epoch 3650 +2024-11-22 06:58:20.121908: Current learning rate: 0.00578 +2024-11-22 06:58:39.383838: train_loss -0.7937 +2024-11-22 06:58:39.388720: val_loss -0.7761 +2024-11-22 06:58:39.388857: Pseudo dice [0.8548] +2024-11-22 06:58:39.388942: Epoch time: 19.26 s +2024-11-22 06:58:40.255256: +2024-11-22 06:58:40.255491: Epoch 3651 +2024-11-22 06:58:40.255628: Current learning rate: 0.00578 +2024-11-22 06:58:57.952367: train_loss -0.794 +2024-11-22 06:58:57.954037: val_loss -0.7794 +2024-11-22 06:58:57.954140: Pseudo dice [0.8565] +2024-11-22 06:58:57.954223: Epoch time: 17.7 s +2024-11-22 06:58:58.809705: +2024-11-22 06:58:58.809914: Epoch 3652 +2024-11-22 06:58:58.810024: Current learning rate: 0.00578 +2024-11-22 06:59:18.009745: train_loss -0.7833 +2024-11-22 06:59:18.024545: val_loss -0.768 +2024-11-22 06:59:18.026259: Pseudo dice [0.8528] +2024-11-22 06:59:18.026386: Epoch time: 19.2 s +2024-11-22 06:59:18.938617: +2024-11-22 06:59:18.938817: Epoch 3653 +2024-11-22 06:59:18.938928: Current learning rate: 0.00578 +2024-11-22 06:59:37.787035: train_loss -0.7885 +2024-11-22 06:59:37.793021: val_loss -0.7768 +2024-11-22 06:59:37.793151: Pseudo dice [0.8547] +2024-11-22 06:59:37.814907: Epoch time: 18.85 s +2024-11-22 06:59:38.703576: +2024-11-22 06:59:38.703867: Epoch 3654 +2024-11-22 06:59:38.703985: Current learning rate: 0.00577 +2024-11-22 06:59:58.007542: train_loss -0.7931 +2024-11-22 06:59:58.032574: val_loss -0.7659 +2024-11-22 06:59:58.032742: Pseudo dice [0.8645] +2024-11-22 06:59:58.032846: Epoch time: 19.3 s +2024-11-22 06:59:59.011253: +2024-11-22 06:59:59.011455: Epoch 3655 +2024-11-22 06:59:59.011570: Current learning rate: 0.00577 +2024-11-22 07:00:18.230335: train_loss -0.7868 +2024-11-22 07:00:18.235902: val_loss -0.7653 +2024-11-22 07:00:18.236019: Pseudo dice [0.859] +2024-11-22 07:00:18.236103: Epoch time: 19.22 s +2024-11-22 07:00:19.122099: +2024-11-22 07:00:19.122332: Epoch 3656 +2024-11-22 07:00:19.122446: Current learning rate: 0.00577 +2024-11-22 07:00:37.893182: train_loss -0.7794 +2024-11-22 07:00:37.900498: val_loss -0.7768 +2024-11-22 07:00:37.900609: Pseudo dice [0.8513] +2024-11-22 07:00:37.900691: Epoch time: 18.77 s +2024-11-22 07:00:38.890518: +2024-11-22 07:00:38.890752: Epoch 3657 +2024-11-22 07:00:38.890863: Current learning rate: 0.00577 +2024-11-22 07:00:57.028430: train_loss -0.7771 +2024-11-22 07:00:57.033420: val_loss -0.783 +2024-11-22 07:00:57.033523: Pseudo dice [0.8561] +2024-11-22 07:00:57.033601: Epoch time: 18.14 s +2024-11-22 07:00:57.876882: +2024-11-22 07:00:57.877089: Epoch 3658 +2024-11-22 07:00:57.877205: Current learning rate: 0.00577 +2024-11-22 07:01:15.297860: train_loss -0.7732 +2024-11-22 07:01:15.309324: val_loss -0.7665 +2024-11-22 07:01:15.309444: Pseudo dice [0.8534] +2024-11-22 07:01:15.309531: Epoch time: 17.42 s +2024-11-22 07:01:16.395988: +2024-11-22 07:01:16.396230: Epoch 3659 +2024-11-22 07:01:16.396340: Current learning rate: 0.00577 +2024-11-22 07:01:34.370134: train_loss -0.7758 +2024-11-22 07:01:34.372035: val_loss -0.7635 +2024-11-22 07:01:34.372127: Pseudo dice [0.8439] +2024-11-22 07:01:34.372205: Epoch time: 17.97 s +2024-11-22 07:01:35.222048: +2024-11-22 07:01:35.222253: Epoch 3660 +2024-11-22 07:01:35.222363: Current learning rate: 0.00577 +2024-11-22 07:01:53.730184: train_loss -0.7841 +2024-11-22 07:01:53.736401: val_loss -0.777 +2024-11-22 07:01:53.736511: Pseudo dice [0.8458] +2024-11-22 07:01:53.736587: Epoch time: 18.51 s +2024-11-22 07:01:55.169858: +2024-11-22 07:01:55.170074: Epoch 3661 +2024-11-22 07:01:55.170192: Current learning rate: 0.00577 +2024-11-22 07:02:14.266403: train_loss -0.7727 +2024-11-22 07:02:14.273710: val_loss -0.736 +2024-11-22 07:02:14.273834: Pseudo dice [0.8318] +2024-11-22 07:02:14.273927: Epoch time: 19.1 s +2024-11-22 07:02:15.156434: +2024-11-22 07:02:15.156644: Epoch 3662 +2024-11-22 07:02:15.156755: Current learning rate: 0.00576 +2024-11-22 07:02:33.753866: train_loss -0.7798 +2024-11-22 07:02:33.762712: val_loss -0.7671 +2024-11-22 07:02:33.762860: Pseudo dice [0.8598] +2024-11-22 07:02:33.762949: Epoch time: 18.6 s +2024-11-22 07:02:34.770685: +2024-11-22 07:02:34.770955: Epoch 3663 +2024-11-22 07:02:34.771074: Current learning rate: 0.00576 +2024-11-22 07:02:54.592835: train_loss -0.7765 +2024-11-22 07:02:54.597819: val_loss -0.7838 +2024-11-22 07:02:54.597936: Pseudo dice [0.8431] +2024-11-22 07:02:54.598026: Epoch time: 19.82 s +2024-11-22 07:02:55.512991: +2024-11-22 07:02:55.513191: Epoch 3664 +2024-11-22 07:02:55.513301: Current learning rate: 0.00576 +2024-11-22 07:03:15.384576: train_loss -0.7845 +2024-11-22 07:03:15.392899: val_loss -0.783 +2024-11-22 07:03:15.393028: Pseudo dice [0.853] +2024-11-22 07:03:15.393121: Epoch time: 19.87 s +2024-11-22 07:03:16.379543: +2024-11-22 07:03:16.379763: Epoch 3665 +2024-11-22 07:03:16.379872: Current learning rate: 0.00576 +2024-11-22 07:03:35.340940: train_loss -0.7671 +2024-11-22 07:03:35.343421: val_loss -0.7713 +2024-11-22 07:03:35.343560: Pseudo dice [0.8454] +2024-11-22 07:03:35.343654: Epoch time: 18.96 s +2024-11-22 07:03:36.244892: +2024-11-22 07:03:36.245101: Epoch 3666 +2024-11-22 07:03:36.245205: Current learning rate: 0.00576 +2024-11-22 07:03:54.536825: train_loss -0.7684 +2024-11-22 07:03:54.539427: val_loss -0.7647 +2024-11-22 07:03:54.539574: Pseudo dice [0.8412] +2024-11-22 07:03:54.539665: Epoch time: 18.29 s +2024-11-22 07:03:55.487370: +2024-11-22 07:03:55.487593: Epoch 3667 +2024-11-22 07:03:55.487704: Current learning rate: 0.00576 +2024-11-22 07:04:14.094555: train_loss -0.7848 +2024-11-22 07:04:14.103412: val_loss -0.7688 +2024-11-22 07:04:14.103603: Pseudo dice [0.8375] +2024-11-22 07:04:14.103691: Epoch time: 18.61 s +2024-11-22 07:04:15.017511: +2024-11-22 07:04:15.017726: Epoch 3668 +2024-11-22 07:04:15.017843: Current learning rate: 0.00576 +2024-11-22 07:04:33.267826: train_loss -0.7768 +2024-11-22 07:04:33.276392: val_loss -0.769 +2024-11-22 07:04:33.276540: Pseudo dice [0.8529] +2024-11-22 07:04:33.276622: Epoch time: 18.25 s +2024-11-22 07:04:34.128100: +2024-11-22 07:04:34.128320: Epoch 3669 +2024-11-22 07:04:34.128435: Current learning rate: 0.00576 +2024-11-22 07:04:52.769659: train_loss -0.785 +2024-11-22 07:04:52.775858: val_loss -0.751 +2024-11-22 07:04:52.775983: Pseudo dice [0.8273] +2024-11-22 07:04:52.776079: Epoch time: 18.64 s +2024-11-22 07:04:53.756310: +2024-11-22 07:04:53.756512: Epoch 3670 +2024-11-22 07:04:53.756632: Current learning rate: 0.00576 +2024-11-22 07:05:12.658825: train_loss -0.785 +2024-11-22 07:05:12.665920: val_loss -0.7807 +2024-11-22 07:05:12.666034: Pseudo dice [0.8608] +2024-11-22 07:05:12.666119: Epoch time: 18.9 s +2024-11-22 07:05:13.519990: +2024-11-22 07:05:13.520193: Epoch 3671 +2024-11-22 07:05:13.520308: Current learning rate: 0.00575 +2024-11-22 07:05:32.537387: train_loss -0.7829 +2024-11-22 07:05:32.545659: val_loss -0.7767 +2024-11-22 07:05:32.545783: Pseudo dice [0.8669] +2024-11-22 07:05:32.545865: Epoch time: 19.02 s +2024-11-22 07:05:33.836663: +2024-11-22 07:05:33.837131: Epoch 3672 +2024-11-22 07:05:33.837275: Current learning rate: 0.00575 +2024-11-22 07:05:52.626281: train_loss -0.7736 +2024-11-22 07:05:52.628521: val_loss -0.7565 +2024-11-22 07:05:52.628619: Pseudo dice [0.844] +2024-11-22 07:05:52.628742: Epoch time: 18.79 s +2024-11-22 07:05:53.478683: +2024-11-22 07:05:53.479105: Epoch 3673 +2024-11-22 07:05:53.479235: Current learning rate: 0.00575 +2024-11-22 07:06:12.154909: train_loss -0.7828 +2024-11-22 07:06:12.161710: val_loss -0.7705 +2024-11-22 07:06:12.161827: Pseudo dice [0.8549] +2024-11-22 07:06:12.161935: Epoch time: 18.68 s +2024-11-22 07:06:13.017757: +2024-11-22 07:06:13.018272: Epoch 3674 +2024-11-22 07:06:13.018405: Current learning rate: 0.00575 +2024-11-22 07:06:31.661758: train_loss -0.784 +2024-11-22 07:06:31.667143: val_loss -0.7923 +2024-11-22 07:06:31.667261: Pseudo dice [0.8569] +2024-11-22 07:06:31.667345: Epoch time: 18.64 s +2024-11-22 07:06:32.568438: +2024-11-22 07:06:32.568862: Epoch 3675 +2024-11-22 07:06:32.568997: Current learning rate: 0.00575 +2024-11-22 07:06:50.298234: train_loss -0.7847 +2024-11-22 07:06:50.305354: val_loss -0.7766 +2024-11-22 07:06:50.305494: Pseudo dice [0.8511] +2024-11-22 07:06:50.305576: Epoch time: 17.73 s +2024-11-22 07:06:51.198515: +2024-11-22 07:06:51.198931: Epoch 3676 +2024-11-22 07:06:51.199065: Current learning rate: 0.00575 +2024-11-22 07:07:08.756896: train_loss -0.7965 +2024-11-22 07:07:08.759173: val_loss -0.7477 +2024-11-22 07:07:08.759267: Pseudo dice [0.8642] +2024-11-22 07:07:08.759347: Epoch time: 17.56 s +2024-11-22 07:07:09.610424: +2024-11-22 07:07:09.610860: Epoch 3677 +2024-11-22 07:07:09.610992: Current learning rate: 0.00575 +2024-11-22 07:07:29.282906: train_loss -0.7897 +2024-11-22 07:07:29.285196: val_loss -0.7768 +2024-11-22 07:07:29.285292: Pseudo dice [0.8578] +2024-11-22 07:07:29.285376: Epoch time: 19.67 s +2024-11-22 07:07:30.136019: +2024-11-22 07:07:30.136526: Epoch 3678 +2024-11-22 07:07:30.136662: Current learning rate: 0.00575 +2024-11-22 07:07:49.126074: train_loss -0.7847 +2024-11-22 07:07:49.130949: val_loss -0.7719 +2024-11-22 07:07:49.131067: Pseudo dice [0.8412] +2024-11-22 07:07:49.131148: Epoch time: 18.99 s +2024-11-22 07:07:50.104561: +2024-11-22 07:07:50.105069: Epoch 3679 +2024-11-22 07:07:50.105407: Current learning rate: 0.00574 +2024-11-22 07:08:08.804525: train_loss -0.7786 +2024-11-22 07:08:08.806639: val_loss -0.7793 +2024-11-22 07:08:08.806738: Pseudo dice [0.8499] +2024-11-22 07:08:08.806822: Epoch time: 18.7 s +2024-11-22 07:08:09.662810: +2024-11-22 07:08:09.663246: Epoch 3680 +2024-11-22 07:08:09.663383: Current learning rate: 0.00574 +2024-11-22 07:08:28.348178: train_loss -0.788 +2024-11-22 07:08:28.356624: val_loss -0.7598 +2024-11-22 07:08:28.356750: Pseudo dice [0.8524] +2024-11-22 07:08:28.356830: Epoch time: 18.69 s +2024-11-22 07:08:29.360745: +2024-11-22 07:08:29.361184: Epoch 3681 +2024-11-22 07:08:29.361325: Current learning rate: 0.00574 +2024-11-22 07:08:47.910110: train_loss -0.7886 +2024-11-22 07:08:47.922669: val_loss -0.7531 +2024-11-22 07:08:47.922802: Pseudo dice [0.8561] +2024-11-22 07:08:47.922889: Epoch time: 18.55 s +2024-11-22 07:08:49.022611: +2024-11-22 07:08:49.023030: Epoch 3682 +2024-11-22 07:08:49.023182: Current learning rate: 0.00574 +2024-11-22 07:09:07.730587: train_loss -0.7755 +2024-11-22 07:09:07.733030: val_loss -0.7704 +2024-11-22 07:09:07.733136: Pseudo dice [0.8548] +2024-11-22 07:09:07.733226: Epoch time: 18.71 s +2024-11-22 07:09:08.979459: +2024-11-22 07:09:08.979678: Epoch 3683 +2024-11-22 07:09:08.979792: Current learning rate: 0.00574 +2024-11-22 07:09:26.933211: train_loss -0.7818 +2024-11-22 07:09:26.939305: val_loss -0.7923 +2024-11-22 07:09:26.939442: Pseudo dice [0.8608] +2024-11-22 07:09:26.939536: Epoch time: 17.95 s +2024-11-22 07:09:27.797219: +2024-11-22 07:09:27.797440: Epoch 3684 +2024-11-22 07:09:27.797549: Current learning rate: 0.00574 +2024-11-22 07:09:46.733510: train_loss -0.7834 +2024-11-22 07:09:46.735969: val_loss -0.7908 +2024-11-22 07:09:46.736068: Pseudo dice [0.8622] +2024-11-22 07:09:46.736151: Epoch time: 18.94 s +2024-11-22 07:09:47.589348: +2024-11-22 07:09:47.589577: Epoch 3685 +2024-11-22 07:09:47.589686: Current learning rate: 0.00574 +2024-11-22 07:10:07.084917: train_loss -0.7925 +2024-11-22 07:10:07.086967: val_loss -0.7751 +2024-11-22 07:10:07.087055: Pseudo dice [0.8496] +2024-11-22 07:10:07.087137: Epoch time: 19.5 s +2024-11-22 07:10:07.942056: +2024-11-22 07:10:07.942309: Epoch 3686 +2024-11-22 07:10:07.942425: Current learning rate: 0.00574 +2024-11-22 07:10:27.753483: train_loss -0.7917 +2024-11-22 07:10:27.758743: val_loss -0.7646 +2024-11-22 07:10:27.758868: Pseudo dice [0.8508] +2024-11-22 07:10:27.758951: Epoch time: 19.81 s +2024-11-22 07:10:28.642802: +2024-11-22 07:10:28.643037: Epoch 3687 +2024-11-22 07:10:28.643171: Current learning rate: 0.00573 +2024-11-22 07:10:47.451462: train_loss -0.7944 +2024-11-22 07:10:47.456542: val_loss -0.7531 +2024-11-22 07:10:47.456673: Pseudo dice [0.8373] +2024-11-22 07:10:47.456759: Epoch time: 18.81 s +2024-11-22 07:10:48.419761: +2024-11-22 07:10:48.419996: Epoch 3688 +2024-11-22 07:10:48.420348: Current learning rate: 0.00573 +2024-11-22 07:11:08.086441: train_loss -0.7874 +2024-11-22 07:11:08.088638: val_loss -0.7617 +2024-11-22 07:11:08.088728: Pseudo dice [0.8466] +2024-11-22 07:11:08.088806: Epoch time: 19.67 s +2024-11-22 07:11:08.948078: +2024-11-22 07:11:08.948275: Epoch 3689 +2024-11-22 07:11:08.948391: Current learning rate: 0.00573 +2024-11-22 07:11:29.126736: train_loss -0.7874 +2024-11-22 07:11:29.129039: val_loss -0.7555 +2024-11-22 07:11:29.129162: Pseudo dice [0.8514] +2024-11-22 07:11:29.129244: Epoch time: 20.18 s +2024-11-22 07:11:29.988264: +2024-11-22 07:11:29.988502: Epoch 3690 +2024-11-22 07:11:29.988619: Current learning rate: 0.00573 +2024-11-22 07:11:48.432429: train_loss -0.7886 +2024-11-22 07:11:48.434423: val_loss -0.764 +2024-11-22 07:11:48.434536: Pseudo dice [0.846] +2024-11-22 07:11:48.434618: Epoch time: 18.44 s +2024-11-22 07:11:49.426688: +2024-11-22 07:11:49.426913: Epoch 3691 +2024-11-22 07:11:49.427032: Current learning rate: 0.00573 +2024-11-22 07:12:08.391832: train_loss -0.7835 +2024-11-22 07:12:08.400407: val_loss -0.7813 +2024-11-22 07:12:08.400537: Pseudo dice [0.8606] +2024-11-22 07:12:08.400918: Epoch time: 18.97 s +2024-11-22 07:12:09.273105: +2024-11-22 07:12:09.273314: Epoch 3692 +2024-11-22 07:12:09.273429: Current learning rate: 0.00573 +2024-11-22 07:12:28.297513: train_loss -0.7881 +2024-11-22 07:12:28.306849: val_loss -0.7636 +2024-11-22 07:12:28.306985: Pseudo dice [0.8447] +2024-11-22 07:12:28.307074: Epoch time: 19.03 s +2024-11-22 07:12:29.170801: +2024-11-22 07:12:29.171007: Epoch 3693 +2024-11-22 07:12:29.171122: Current learning rate: 0.00573 +2024-11-22 07:12:48.111893: train_loss -0.78 +2024-11-22 07:12:48.114152: val_loss -0.7794 +2024-11-22 07:12:48.114239: Pseudo dice [0.8532] +2024-11-22 07:12:48.114319: Epoch time: 18.94 s +2024-11-22 07:12:49.348208: +2024-11-22 07:12:49.348436: Epoch 3694 +2024-11-22 07:12:49.348549: Current learning rate: 0.00573 +2024-11-22 07:13:08.407709: train_loss -0.7684 +2024-11-22 07:13:08.420648: val_loss -0.7789 +2024-11-22 07:13:08.420796: Pseudo dice [0.8469] +2024-11-22 07:13:08.420895: Epoch time: 19.06 s +2024-11-22 07:13:09.443880: +2024-11-22 07:13:09.444110: Epoch 3695 +2024-11-22 07:13:09.444218: Current learning rate: 0.00573 +2024-11-22 07:13:26.646083: train_loss -0.7834 +2024-11-22 07:13:26.651467: val_loss -0.7435 +2024-11-22 07:13:26.651595: Pseudo dice [0.8444] +2024-11-22 07:13:26.651738: Epoch time: 17.2 s +2024-11-22 07:13:27.527471: +2024-11-22 07:13:27.527683: Epoch 3696 +2024-11-22 07:13:27.527797: Current learning rate: 0.00572 +2024-11-22 07:13:46.957637: train_loss -0.7868 +2024-11-22 07:13:46.964043: val_loss -0.7968 +2024-11-22 07:13:46.964162: Pseudo dice [0.8544] +2024-11-22 07:13:46.964239: Epoch time: 19.43 s +2024-11-22 07:13:47.848621: +2024-11-22 07:13:47.848830: Epoch 3697 +2024-11-22 07:13:47.848945: Current learning rate: 0.00572 +2024-11-22 07:14:07.768843: train_loss -0.7907 +2024-11-22 07:14:07.771894: val_loss -0.7794 +2024-11-22 07:14:07.771999: Pseudo dice [0.8531] +2024-11-22 07:14:07.772118: Epoch time: 19.92 s +2024-11-22 07:14:08.631361: +2024-11-22 07:14:08.631570: Epoch 3698 +2024-11-22 07:14:08.631682: Current learning rate: 0.00572 +2024-11-22 07:14:27.185759: train_loss -0.7873 +2024-11-22 07:14:27.193892: val_loss -0.7386 +2024-11-22 07:14:27.194008: Pseudo dice [0.8539] +2024-11-22 07:14:27.194102: Epoch time: 18.56 s +2024-11-22 07:14:28.301610: +2024-11-22 07:14:28.301804: Epoch 3699 +2024-11-22 07:14:28.301912: Current learning rate: 0.00572 +2024-11-22 07:14:47.564569: train_loss -0.7693 +2024-11-22 07:14:47.571625: val_loss -0.747 +2024-11-22 07:14:47.571749: Pseudo dice [0.8358] +2024-11-22 07:14:47.571882: Epoch time: 19.26 s +2024-11-22 07:14:48.768039: +2024-11-22 07:14:48.768237: Epoch 3700 +2024-11-22 07:14:48.768347: Current learning rate: 0.00572 +2024-11-22 07:15:08.060664: train_loss -0.7759 +2024-11-22 07:15:08.073670: val_loss -0.7699 +2024-11-22 07:15:08.073807: Pseudo dice [0.8495] +2024-11-22 07:15:08.073885: Epoch time: 19.29 s +2024-11-22 07:15:08.938826: +2024-11-22 07:15:08.939154: Epoch 3701 +2024-11-22 07:15:08.939270: Current learning rate: 0.00572 +2024-11-22 07:15:28.404410: train_loss -0.7825 +2024-11-22 07:15:28.410530: val_loss -0.7791 +2024-11-22 07:15:28.410662: Pseudo dice [0.8474] +2024-11-22 07:15:28.410746: Epoch time: 19.47 s +2024-11-22 07:15:29.267492: +2024-11-22 07:15:29.267695: Epoch 3702 +2024-11-22 07:15:29.267808: Current learning rate: 0.00572 +2024-11-22 07:15:48.028342: train_loss -0.7757 +2024-11-22 07:15:48.035615: val_loss -0.7713 +2024-11-22 07:15:48.035729: Pseudo dice [0.8681] +2024-11-22 07:15:48.035821: Epoch time: 18.76 s +2024-11-22 07:15:48.914808: +2024-11-22 07:15:48.915010: Epoch 3703 +2024-11-22 07:15:48.915126: Current learning rate: 0.00572 +2024-11-22 07:16:07.927545: train_loss -0.777 +2024-11-22 07:16:07.933721: val_loss -0.7668 +2024-11-22 07:16:07.933859: Pseudo dice [0.8419] +2024-11-22 07:16:07.933944: Epoch time: 19.01 s +2024-11-22 07:16:08.792828: +2024-11-22 07:16:08.793036: Epoch 3704 +2024-11-22 07:16:08.793154: Current learning rate: 0.00571 +2024-11-22 07:16:27.665019: train_loss -0.7738 +2024-11-22 07:16:27.669289: val_loss -0.7654 +2024-11-22 07:16:27.669410: Pseudo dice [0.8604] +2024-11-22 07:16:27.669490: Epoch time: 18.87 s +2024-11-22 07:16:29.355153: +2024-11-22 07:16:29.355360: Epoch 3705 +2024-11-22 07:16:29.355472: Current learning rate: 0.00571 +2024-11-22 07:16:48.258607: train_loss -0.7781 +2024-11-22 07:16:48.265699: val_loss -0.7747 +2024-11-22 07:16:48.265841: Pseudo dice [0.8598] +2024-11-22 07:16:48.265941: Epoch time: 18.9 s +2024-11-22 07:16:49.121992: +2024-11-22 07:16:49.122218: Epoch 3706 +2024-11-22 07:16:49.122328: Current learning rate: 0.00571 +2024-11-22 07:17:08.103908: train_loss -0.7809 +2024-11-22 07:17:08.106880: val_loss -0.7791 +2024-11-22 07:17:08.107005: Pseudo dice [0.8602] +2024-11-22 07:17:08.107095: Epoch time: 18.98 s +2024-11-22 07:17:08.990246: +2024-11-22 07:17:08.990489: Epoch 3707 +2024-11-22 07:17:08.990603: Current learning rate: 0.00571 +2024-11-22 07:17:27.977835: train_loss -0.7848 +2024-11-22 07:17:27.980048: val_loss -0.7361 +2024-11-22 07:17:27.980179: Pseudo dice [0.8398] +2024-11-22 07:17:27.980261: Epoch time: 18.99 s +2024-11-22 07:17:28.849956: +2024-11-22 07:17:28.850174: Epoch 3708 +2024-11-22 07:17:28.850293: Current learning rate: 0.00571 +2024-11-22 07:17:47.686596: train_loss -0.7815 +2024-11-22 07:17:47.690141: val_loss -0.7595 +2024-11-22 07:17:47.690265: Pseudo dice [0.8519] +2024-11-22 07:17:47.690340: Epoch time: 18.84 s +2024-11-22 07:17:48.552167: +2024-11-22 07:17:48.552378: Epoch 3709 +2024-11-22 07:17:48.552488: Current learning rate: 0.00571 +2024-11-22 07:18:07.374618: train_loss -0.7882 +2024-11-22 07:18:07.382282: val_loss -0.7635 +2024-11-22 07:18:07.382408: Pseudo dice [0.868] +2024-11-22 07:18:07.382501: Epoch time: 18.82 s +2024-11-22 07:18:08.247262: +2024-11-22 07:18:08.247474: Epoch 3710 +2024-11-22 07:18:08.247589: Current learning rate: 0.00571 +2024-11-22 07:18:27.179731: train_loss -0.7902 +2024-11-22 07:18:27.189738: val_loss -0.7664 +2024-11-22 07:18:27.189852: Pseudo dice [0.8469] +2024-11-22 07:18:27.189929: Epoch time: 18.93 s +2024-11-22 07:18:28.053537: +2024-11-22 07:18:28.053806: Epoch 3711 +2024-11-22 07:18:28.053916: Current learning rate: 0.00571 +2024-11-22 07:18:47.362824: train_loss -0.7867 +2024-11-22 07:18:47.371091: val_loss -0.7482 +2024-11-22 07:18:47.371289: Pseudo dice [0.8479] +2024-11-22 07:18:47.371374: Epoch time: 19.31 s +2024-11-22 07:18:48.261054: +2024-11-22 07:18:48.261326: Epoch 3712 +2024-11-22 07:18:48.261441: Current learning rate: 0.0057 +2024-11-22 07:19:06.942468: train_loss -0.7872 +2024-11-22 07:19:06.945246: val_loss -0.7643 +2024-11-22 07:19:06.945347: Pseudo dice [0.8536] +2024-11-22 07:19:06.945438: Epoch time: 18.68 s +2024-11-22 07:19:07.805520: +2024-11-22 07:19:07.805725: Epoch 3713 +2024-11-22 07:19:07.805842: Current learning rate: 0.0057 +2024-11-22 07:19:27.836303: train_loss -0.7852 +2024-11-22 07:19:27.838957: val_loss -0.7616 +2024-11-22 07:19:27.839097: Pseudo dice [0.832] +2024-11-22 07:19:27.839191: Epoch time: 20.03 s +2024-11-22 07:19:28.714432: +2024-11-22 07:19:28.714647: Epoch 3714 +2024-11-22 07:19:28.715201: Current learning rate: 0.0057 +2024-11-22 07:19:48.084941: train_loss -0.7843 +2024-11-22 07:19:48.091547: val_loss -0.7512 +2024-11-22 07:19:48.091655: Pseudo dice [0.8606] +2024-11-22 07:19:48.091734: Epoch time: 19.37 s +2024-11-22 07:19:49.021882: +2024-11-22 07:19:49.022125: Epoch 3715 +2024-11-22 07:19:49.022239: Current learning rate: 0.0057 +2024-11-22 07:20:08.310718: train_loss -0.7829 +2024-11-22 07:20:08.317857: val_loss -0.7682 +2024-11-22 07:20:08.317984: Pseudo dice [0.8533] +2024-11-22 07:20:08.318068: Epoch time: 19.29 s +2024-11-22 07:20:09.611558: +2024-11-22 07:20:09.611773: Epoch 3716 +2024-11-22 07:20:09.611889: Current learning rate: 0.0057 +2024-11-22 07:20:27.762067: train_loss -0.7745 +2024-11-22 07:20:27.768515: val_loss -0.7607 +2024-11-22 07:20:27.768644: Pseudo dice [0.8434] +2024-11-22 07:20:27.768735: Epoch time: 18.15 s +2024-11-22 07:20:28.655774: +2024-11-22 07:20:28.655996: Epoch 3717 +2024-11-22 07:20:28.656117: Current learning rate: 0.0057 +2024-11-22 07:20:47.706243: train_loss -0.7551 +2024-11-22 07:20:47.713352: val_loss -0.7584 +2024-11-22 07:20:47.713472: Pseudo dice [0.8558] +2024-11-22 07:20:47.713553: Epoch time: 19.05 s +2024-11-22 07:20:48.706254: +2024-11-22 07:20:48.706469: Epoch 3718 +2024-11-22 07:20:48.706581: Current learning rate: 0.0057 +2024-11-22 07:21:07.106246: train_loss -0.7868 +2024-11-22 07:21:07.112832: val_loss -0.7696 +2024-11-22 07:21:07.112977: Pseudo dice [0.859] +2024-11-22 07:21:07.113150: Epoch time: 18.4 s +2024-11-22 07:21:08.052896: +2024-11-22 07:21:08.053124: Epoch 3719 +2024-11-22 07:21:08.053236: Current learning rate: 0.0057 +2024-11-22 07:21:27.669859: train_loss -0.7885 +2024-11-22 07:21:27.672536: val_loss -0.7769 +2024-11-22 07:21:27.672706: Pseudo dice [0.8509] +2024-11-22 07:21:27.672822: Epoch time: 19.62 s +2024-11-22 07:21:28.529636: +2024-11-22 07:21:28.529859: Epoch 3720 +2024-11-22 07:21:28.529970: Current learning rate: 0.0057 +2024-11-22 07:21:47.605318: train_loss -0.7775 +2024-11-22 07:21:47.609512: val_loss -0.7818 +2024-11-22 07:21:47.609635: Pseudo dice [0.8501] +2024-11-22 07:21:47.609747: Epoch time: 19.08 s +2024-11-22 07:21:48.490501: +2024-11-22 07:21:48.490707: Epoch 3721 +2024-11-22 07:21:48.490826: Current learning rate: 0.00569 +2024-11-22 07:22:06.395763: train_loss -0.7683 +2024-11-22 07:22:06.405958: val_loss -0.78 +2024-11-22 07:22:06.406074: Pseudo dice [0.8619] +2024-11-22 07:22:06.406157: Epoch time: 17.91 s +2024-11-22 07:22:07.512332: +2024-11-22 07:22:07.512528: Epoch 3722 +2024-11-22 07:22:07.512641: Current learning rate: 0.00569 +2024-11-22 07:22:27.478605: train_loss -0.7583 +2024-11-22 07:22:27.488203: val_loss -0.7302 +2024-11-22 07:22:27.488333: Pseudo dice [0.8456] +2024-11-22 07:22:27.488421: Epoch time: 19.97 s +2024-11-22 07:22:28.504675: +2024-11-22 07:22:28.504880: Epoch 3723 +2024-11-22 07:22:28.505006: Current learning rate: 0.00569 +2024-11-22 07:22:47.995336: train_loss -0.7724 +2024-11-22 07:22:48.004677: val_loss -0.7524 +2024-11-22 07:22:48.004825: Pseudo dice [0.8407] +2024-11-22 07:22:48.004914: Epoch time: 19.49 s +2024-11-22 07:22:48.875164: +2024-11-22 07:22:48.875421: Epoch 3724 +2024-11-22 07:22:48.875557: Current learning rate: 0.00569 +2024-11-22 07:23:07.991326: train_loss -0.7808 +2024-11-22 07:23:07.997714: val_loss -0.7557 +2024-11-22 07:23:07.997847: Pseudo dice [0.8349] +2024-11-22 07:23:07.997936: Epoch time: 19.12 s +2024-11-22 07:23:09.038285: +2024-11-22 07:23:09.038518: Epoch 3725 +2024-11-22 07:23:09.038627: Current learning rate: 0.00569 +2024-11-22 07:23:27.401292: train_loss -0.7828 +2024-11-22 07:23:27.407660: val_loss -0.7777 +2024-11-22 07:23:27.407781: Pseudo dice [0.8477] +2024-11-22 07:23:27.407862: Epoch time: 18.36 s +2024-11-22 07:23:28.261589: +2024-11-22 07:23:28.261789: Epoch 3726 +2024-11-22 07:23:28.261897: Current learning rate: 0.00569 +2024-11-22 07:23:47.693051: train_loss -0.7906 +2024-11-22 07:23:47.700019: val_loss -0.7739 +2024-11-22 07:23:47.700137: Pseudo dice [0.8615] +2024-11-22 07:23:47.700218: Epoch time: 19.43 s +2024-11-22 07:23:49.038244: +2024-11-22 07:23:49.038464: Epoch 3727 +2024-11-22 07:23:49.038581: Current learning rate: 0.00569 +2024-11-22 07:24:08.271950: train_loss -0.7885 +2024-11-22 07:24:08.274612: val_loss -0.7983 +2024-11-22 07:24:08.274733: Pseudo dice [0.8619] +2024-11-22 07:24:08.274822: Epoch time: 19.23 s +2024-11-22 07:24:09.148674: +2024-11-22 07:24:09.148867: Epoch 3728 +2024-11-22 07:24:09.148974: Current learning rate: 0.00569 +2024-11-22 07:24:28.883232: train_loss -0.786 +2024-11-22 07:24:28.886247: val_loss -0.7737 +2024-11-22 07:24:28.886361: Pseudo dice [0.8566] +2024-11-22 07:24:28.886441: Epoch time: 19.74 s +2024-11-22 07:24:29.907048: +2024-11-22 07:24:29.907278: Epoch 3729 +2024-11-22 07:24:29.907387: Current learning rate: 0.00568 +2024-11-22 07:24:48.105370: train_loss -0.7899 +2024-11-22 07:24:48.107548: val_loss -0.7718 +2024-11-22 07:24:48.107644: Pseudo dice [0.8567] +2024-11-22 07:24:48.107720: Epoch time: 18.2 s +2024-11-22 07:24:48.983086: +2024-11-22 07:24:48.983312: Epoch 3730 +2024-11-22 07:24:48.983425: Current learning rate: 0.00568 +2024-11-22 07:25:07.495710: train_loss -0.782 +2024-11-22 07:25:07.506297: val_loss -0.7799 +2024-11-22 07:25:07.506418: Pseudo dice [0.8513] +2024-11-22 07:25:07.506504: Epoch time: 18.51 s +2024-11-22 07:25:08.369708: +2024-11-22 07:25:08.369908: Epoch 3731 +2024-11-22 07:25:08.370021: Current learning rate: 0.00568 +2024-11-22 07:25:26.796827: train_loss -0.7883 +2024-11-22 07:25:26.799803: val_loss -0.7792 +2024-11-22 07:25:26.799915: Pseudo dice [0.8646] +2024-11-22 07:25:26.799999: Epoch time: 18.43 s +2024-11-22 07:25:27.798535: +2024-11-22 07:25:27.798794: Epoch 3732 +2024-11-22 07:25:27.798908: Current learning rate: 0.00568 +2024-11-22 07:25:45.924819: train_loss -0.7837 +2024-11-22 07:25:45.932603: val_loss -0.7747 +2024-11-22 07:25:45.932719: Pseudo dice [0.8561] +2024-11-22 07:25:45.932803: Epoch time: 18.13 s +2024-11-22 07:25:46.816724: +2024-11-22 07:25:46.816916: Epoch 3733 +2024-11-22 07:25:46.817032: Current learning rate: 0.00568 +2024-11-22 07:26:05.480524: train_loss -0.7858 +2024-11-22 07:26:05.483006: val_loss -0.7828 +2024-11-22 07:26:05.483132: Pseudo dice [0.8457] +2024-11-22 07:26:05.483213: Epoch time: 18.66 s +2024-11-22 07:26:06.340888: +2024-11-22 07:26:06.341102: Epoch 3734 +2024-11-22 07:26:06.341219: Current learning rate: 0.00568 +2024-11-22 07:26:25.627069: train_loss -0.7792 +2024-11-22 07:26:25.635910: val_loss -0.7623 +2024-11-22 07:26:25.636075: Pseudo dice [0.8405] +2024-11-22 07:26:25.636165: Epoch time: 19.29 s +2024-11-22 07:26:26.503277: +2024-11-22 07:26:26.503505: Epoch 3735 +2024-11-22 07:26:26.503618: Current learning rate: 0.00568 +2024-11-22 07:26:44.386991: train_loss -0.7781 +2024-11-22 07:26:44.389409: val_loss -0.7616 +2024-11-22 07:26:44.389534: Pseudo dice [0.8579] +2024-11-22 07:26:44.389628: Epoch time: 17.88 s +2024-11-22 07:26:45.259741: +2024-11-22 07:26:45.259941: Epoch 3736 +2024-11-22 07:26:45.260056: Current learning rate: 0.00568 +2024-11-22 07:27:05.089589: train_loss -0.786 +2024-11-22 07:27:05.093666: val_loss -0.7807 +2024-11-22 07:27:05.093856: Pseudo dice [0.8448] +2024-11-22 07:27:05.093944: Epoch time: 19.83 s +2024-11-22 07:27:06.145248: +2024-11-22 07:27:06.145463: Epoch 3737 +2024-11-22 07:27:06.145582: Current learning rate: 0.00567 +2024-11-22 07:27:24.290056: train_loss -0.7886 +2024-11-22 07:27:24.293543: val_loss -0.7668 +2024-11-22 07:27:24.293655: Pseudo dice [0.8467] +2024-11-22 07:27:24.293739: Epoch time: 18.15 s +2024-11-22 07:27:25.638905: +2024-11-22 07:27:25.639114: Epoch 3738 +2024-11-22 07:27:25.639221: Current learning rate: 0.00567 +2024-11-22 07:27:43.942165: train_loss -0.8019 +2024-11-22 07:27:43.944874: val_loss -0.779 +2024-11-22 07:27:43.944962: Pseudo dice [0.869] +2024-11-22 07:27:43.945044: Epoch time: 18.3 s +2024-11-22 07:27:44.797626: +2024-11-22 07:27:44.797825: Epoch 3739 +2024-11-22 07:27:44.797934: Current learning rate: 0.00567 +2024-11-22 07:28:04.857930: train_loss -0.7868 +2024-11-22 07:28:04.864799: val_loss -0.7666 +2024-11-22 07:28:04.864919: Pseudo dice [0.8517] +2024-11-22 07:28:04.865009: Epoch time: 20.06 s +2024-11-22 07:28:05.719798: +2024-11-22 07:28:05.720224: Epoch 3740 +2024-11-22 07:28:05.720346: Current learning rate: 0.00567 +2024-11-22 07:28:24.741610: train_loss -0.7831 +2024-11-22 07:28:24.749119: val_loss -0.7782 +2024-11-22 07:28:24.749225: Pseudo dice [0.8588] +2024-11-22 07:28:24.749310: Epoch time: 19.02 s +2024-11-22 07:28:25.688005: +2024-11-22 07:28:25.688228: Epoch 3741 +2024-11-22 07:28:25.688343: Current learning rate: 0.00567 +2024-11-22 07:28:44.420124: train_loss -0.7705 +2024-11-22 07:28:44.422530: val_loss -0.7526 +2024-11-22 07:28:44.422641: Pseudo dice [0.8427] +2024-11-22 07:28:44.422743: Epoch time: 18.73 s +2024-11-22 07:28:45.401371: +2024-11-22 07:28:45.401563: Epoch 3742 +2024-11-22 07:28:45.401674: Current learning rate: 0.00567 +2024-11-22 07:29:04.450312: train_loss -0.7692 +2024-11-22 07:29:04.456929: val_loss -0.7547 +2024-11-22 07:29:04.457283: Pseudo dice [0.8474] +2024-11-22 07:29:04.457431: Epoch time: 19.05 s +2024-11-22 07:29:05.314611: +2024-11-22 07:29:05.314840: Epoch 3743 +2024-11-22 07:29:05.314951: Current learning rate: 0.00567 +2024-11-22 07:29:23.937029: train_loss -0.7673 +2024-11-22 07:29:23.939865: val_loss -0.7637 +2024-11-22 07:29:23.939973: Pseudo dice [0.8458] +2024-11-22 07:29:23.940064: Epoch time: 18.62 s +2024-11-22 07:29:24.949784: +2024-11-22 07:29:24.950007: Epoch 3744 +2024-11-22 07:29:24.950121: Current learning rate: 0.00567 +2024-11-22 07:29:42.515114: train_loss -0.7715 +2024-11-22 07:29:42.521743: val_loss -0.7585 +2024-11-22 07:29:42.521866: Pseudo dice [0.8587] +2024-11-22 07:29:42.522000: Epoch time: 17.57 s +2024-11-22 07:29:43.397928: +2024-11-22 07:29:43.398151: Epoch 3745 +2024-11-22 07:29:43.398259: Current learning rate: 0.00567 +2024-11-22 07:30:00.600313: train_loss -0.7797 +2024-11-22 07:30:00.606946: val_loss -0.7614 +2024-11-22 07:30:00.607080: Pseudo dice [0.84] +2024-11-22 07:30:00.607160: Epoch time: 17.2 s +2024-11-22 07:30:01.464339: +2024-11-22 07:30:01.464545: Epoch 3746 +2024-11-22 07:30:01.464660: Current learning rate: 0.00566 +2024-11-22 07:30:19.864808: train_loss -0.7928 +2024-11-22 07:30:19.871433: val_loss -0.7691 +2024-11-22 07:30:19.871556: Pseudo dice [0.8611] +2024-11-22 07:30:19.871649: Epoch time: 18.4 s +2024-11-22 07:30:20.918494: +2024-11-22 07:30:20.918705: Epoch 3747 +2024-11-22 07:30:20.918821: Current learning rate: 0.00566 +2024-11-22 07:30:40.213230: train_loss -0.7831 +2024-11-22 07:30:40.219452: val_loss -0.7721 +2024-11-22 07:30:40.219581: Pseudo dice [0.8563] +2024-11-22 07:30:40.219663: Epoch time: 19.3 s +2024-11-22 07:30:41.356979: +2024-11-22 07:30:41.357172: Epoch 3748 +2024-11-22 07:30:41.357290: Current learning rate: 0.00566 +2024-11-22 07:31:00.336708: train_loss -0.7852 +2024-11-22 07:31:00.342034: val_loss -0.7569 +2024-11-22 07:31:00.342143: Pseudo dice [0.8604] +2024-11-22 07:31:00.342220: Epoch time: 18.98 s +2024-11-22 07:31:01.651289: +2024-11-22 07:31:01.651501: Epoch 3749 +2024-11-22 07:31:01.651610: Current learning rate: 0.00566 +2024-11-22 07:31:19.597628: train_loss -0.7577 +2024-11-22 07:31:19.608555: val_loss -0.7596 +2024-11-22 07:31:19.608690: Pseudo dice [0.8407] +2024-11-22 07:31:19.608779: Epoch time: 17.95 s +2024-11-22 07:31:20.745608: +2024-11-22 07:31:20.745815: Epoch 3750 +2024-11-22 07:31:20.745932: Current learning rate: 0.00566 +2024-11-22 07:31:39.882241: train_loss -0.7745 +2024-11-22 07:31:39.923689: val_loss -0.7599 +2024-11-22 07:31:39.923859: Pseudo dice [0.8398] +2024-11-22 07:31:39.923952: Epoch time: 19.14 s +2024-11-22 07:31:40.783482: +2024-11-22 07:31:40.783697: Epoch 3751 +2024-11-22 07:31:40.783813: Current learning rate: 0.00566 +2024-11-22 07:31:58.972762: train_loss -0.7759 +2024-11-22 07:31:58.980385: val_loss -0.7718 +2024-11-22 07:31:58.980517: Pseudo dice [0.8533] +2024-11-22 07:31:58.980600: Epoch time: 18.19 s +2024-11-22 07:31:59.956361: +2024-11-22 07:31:59.956601: Epoch 3752 +2024-11-22 07:31:59.956708: Current learning rate: 0.00566 +2024-11-22 07:32:19.091541: train_loss -0.7969 +2024-11-22 07:32:19.100365: val_loss -0.7709 +2024-11-22 07:32:19.100496: Pseudo dice [0.852] +2024-11-22 07:32:19.100576: Epoch time: 19.14 s +2024-11-22 07:32:19.960008: +2024-11-22 07:32:19.960247: Epoch 3753 +2024-11-22 07:32:19.960361: Current learning rate: 0.00566 +2024-11-22 07:32:39.101143: train_loss -0.7933 +2024-11-22 07:32:39.107301: val_loss -0.7576 +2024-11-22 07:32:39.107437: Pseudo dice [0.8422] +2024-11-22 07:32:39.107529: Epoch time: 19.14 s +2024-11-22 07:32:40.009550: +2024-11-22 07:32:40.009746: Epoch 3754 +2024-11-22 07:32:40.009861: Current learning rate: 0.00565 +2024-11-22 07:32:58.912055: train_loss -0.7905 +2024-11-22 07:32:58.917387: val_loss -0.77 +2024-11-22 07:32:58.917518: Pseudo dice [0.8499] +2024-11-22 07:32:58.917600: Epoch time: 18.9 s +2024-11-22 07:32:59.832989: +2024-11-22 07:32:59.833214: Epoch 3755 +2024-11-22 07:32:59.833330: Current learning rate: 0.00565 +2024-11-22 07:33:19.516408: train_loss -0.7875 +2024-11-22 07:33:19.520570: val_loss -0.7754 +2024-11-22 07:33:19.520695: Pseudo dice [0.8528] +2024-11-22 07:33:19.520780: Epoch time: 19.68 s +2024-11-22 07:33:20.390822: +2024-11-22 07:33:20.391055: Epoch 3756 +2024-11-22 07:33:20.391176: Current learning rate: 0.00565 +2024-11-22 07:33:40.277008: train_loss -0.7779 +2024-11-22 07:33:40.284224: val_loss -0.7598 +2024-11-22 07:33:40.284340: Pseudo dice [0.8426] +2024-11-22 07:33:40.284422: Epoch time: 19.89 s +2024-11-22 07:33:41.421480: +2024-11-22 07:33:41.421682: Epoch 3757 +2024-11-22 07:33:41.421793: Current learning rate: 0.00565 +2024-11-22 07:34:00.242592: train_loss -0.7765 +2024-11-22 07:34:00.247920: val_loss -0.7756 +2024-11-22 07:34:00.248053: Pseudo dice [0.8606] +2024-11-22 07:34:00.248143: Epoch time: 18.82 s +2024-11-22 07:34:01.115194: +2024-11-22 07:34:01.115403: Epoch 3758 +2024-11-22 07:34:01.115519: Current learning rate: 0.00565 +2024-11-22 07:34:19.559378: train_loss -0.7779 +2024-11-22 07:34:19.566150: val_loss -0.7785 +2024-11-22 07:34:19.566257: Pseudo dice [0.8484] +2024-11-22 07:34:19.566336: Epoch time: 18.44 s +2024-11-22 07:34:20.435755: +2024-11-22 07:34:20.435968: Epoch 3759 +2024-11-22 07:34:20.436084: Current learning rate: 0.00565 +2024-11-22 07:34:39.468886: train_loss -0.7827 +2024-11-22 07:34:39.474801: val_loss -0.7357 +2024-11-22 07:34:39.474949: Pseudo dice [0.8289] +2024-11-22 07:34:39.475039: Epoch time: 19.03 s +2024-11-22 07:34:40.344849: +2024-11-22 07:34:40.345047: Epoch 3760 +2024-11-22 07:34:40.345162: Current learning rate: 0.00565 +2024-11-22 07:34:58.816106: train_loss -0.7761 +2024-11-22 07:34:58.818307: val_loss -0.7446 +2024-11-22 07:34:58.818428: Pseudo dice [0.851] +2024-11-22 07:34:58.818516: Epoch time: 18.47 s +2024-11-22 07:34:59.668210: +2024-11-22 07:34:59.668415: Epoch 3761 +2024-11-22 07:34:59.668528: Current learning rate: 0.00565 +2024-11-22 07:35:17.756877: train_loss -0.7803 +2024-11-22 07:35:17.769721: val_loss -0.7777 +2024-11-22 07:35:17.769842: Pseudo dice [0.8454] +2024-11-22 07:35:17.769921: Epoch time: 18.09 s +2024-11-22 07:35:18.752328: +2024-11-22 07:35:18.752557: Epoch 3762 +2024-11-22 07:35:18.752673: Current learning rate: 0.00564 +2024-11-22 07:35:36.584810: train_loss -0.788 +2024-11-22 07:35:36.586465: val_loss -0.7427 +2024-11-22 07:35:36.586571: Pseudo dice [0.8457] +2024-11-22 07:35:36.586648: Epoch time: 17.83 s +2024-11-22 07:35:37.643975: +2024-11-22 07:35:37.644180: Epoch 3763 +2024-11-22 07:35:37.644292: Current learning rate: 0.00564 +2024-11-22 07:35:56.757838: train_loss -0.7858 +2024-11-22 07:35:56.763865: val_loss -0.7818 +2024-11-22 07:35:56.763984: Pseudo dice [0.8605] +2024-11-22 07:35:56.764081: Epoch time: 19.11 s +2024-11-22 07:35:57.640677: +2024-11-22 07:35:57.640889: Epoch 3764 +2024-11-22 07:35:57.641001: Current learning rate: 0.00564 +2024-11-22 07:36:15.735837: train_loss -0.7902 +2024-11-22 07:36:15.737339: val_loss -0.7521 +2024-11-22 07:36:15.737433: Pseudo dice [0.8391] +2024-11-22 07:36:15.737519: Epoch time: 18.1 s +2024-11-22 07:36:16.596699: +2024-11-22 07:36:16.596939: Epoch 3765 +2024-11-22 07:36:16.597051: Current learning rate: 0.00564 +2024-11-22 07:36:35.964342: train_loss -0.7835 +2024-11-22 07:36:35.969371: val_loss -0.7574 +2024-11-22 07:36:35.969474: Pseudo dice [0.843] +2024-11-22 07:36:35.969553: Epoch time: 19.37 s +2024-11-22 07:36:36.989428: +2024-11-22 07:36:36.989641: Epoch 3766 +2024-11-22 07:36:36.989755: Current learning rate: 0.00564 +2024-11-22 07:36:55.504369: train_loss -0.784 +2024-11-22 07:36:55.506147: val_loss -0.7677 +2024-11-22 07:36:55.506283: Pseudo dice [0.8519] +2024-11-22 07:36:55.506408: Epoch time: 18.52 s +2024-11-22 07:36:56.361959: +2024-11-22 07:36:56.362177: Epoch 3767 +2024-11-22 07:36:56.362292: Current learning rate: 0.00564 +2024-11-22 07:37:14.775445: train_loss -0.7896 +2024-11-22 07:37:14.776855: val_loss -0.7753 +2024-11-22 07:37:14.776942: Pseudo dice [0.8603] +2024-11-22 07:37:14.777013: Epoch time: 18.41 s +2024-11-22 07:37:15.617289: +2024-11-22 07:37:15.617698: Epoch 3768 +2024-11-22 07:37:15.617814: Current learning rate: 0.00564 +2024-11-22 07:37:34.592731: train_loss -0.7786 +2024-11-22 07:37:34.594749: val_loss -0.7612 +2024-11-22 07:37:34.594848: Pseudo dice [0.8611] +2024-11-22 07:37:34.594936: Epoch time: 18.98 s +2024-11-22 07:37:35.452767: +2024-11-22 07:37:35.452958: Epoch 3769 +2024-11-22 07:37:35.453070: Current learning rate: 0.00564 +2024-11-22 07:37:54.586631: train_loss -0.7908 +2024-11-22 07:37:54.595963: val_loss -0.7679 +2024-11-22 07:37:54.596086: Pseudo dice [0.8484] +2024-11-22 07:37:54.596169: Epoch time: 19.13 s +2024-11-22 07:37:55.556813: +2024-11-22 07:37:55.557026: Epoch 3770 +2024-11-22 07:37:55.557149: Current learning rate: 0.00564 +2024-11-22 07:38:15.082000: train_loss -0.7868 +2024-11-22 07:38:15.087427: val_loss -0.7695 +2024-11-22 07:38:15.087535: Pseudo dice [0.8444] +2024-11-22 07:38:15.087614: Epoch time: 19.53 s +2024-11-22 07:38:16.485583: +2024-11-22 07:38:16.485800: Epoch 3771 +2024-11-22 07:38:16.485916: Current learning rate: 0.00563 +2024-11-22 07:38:36.737196: train_loss -0.7834 +2024-11-22 07:38:36.744036: val_loss -0.7471 +2024-11-22 07:38:36.744187: Pseudo dice [0.8417] +2024-11-22 07:38:36.744276: Epoch time: 20.25 s +2024-11-22 07:38:37.626584: +2024-11-22 07:38:37.626783: Epoch 3772 +2024-11-22 07:38:37.626896: Current learning rate: 0.00563 +2024-11-22 07:38:56.134608: train_loss -0.7948 +2024-11-22 07:38:56.141902: val_loss -0.7863 +2024-11-22 07:38:56.142039: Pseudo dice [0.8527] +2024-11-22 07:38:56.142133: Epoch time: 18.51 s +2024-11-22 07:38:57.011610: +2024-11-22 07:38:57.011815: Epoch 3773 +2024-11-22 07:38:57.011929: Current learning rate: 0.00563 +2024-11-22 07:39:15.942189: train_loss -0.7809 +2024-11-22 07:39:15.947925: val_loss -0.7735 +2024-11-22 07:39:15.948071: Pseudo dice [0.8445] +2024-11-22 07:39:15.948154: Epoch time: 18.93 s +2024-11-22 07:39:16.916136: +2024-11-22 07:39:16.916325: Epoch 3774 +2024-11-22 07:39:16.916433: Current learning rate: 0.00563 +2024-11-22 07:39:35.260502: train_loss -0.7851 +2024-11-22 07:39:35.267673: val_loss -0.7626 +2024-11-22 07:39:35.267783: Pseudo dice [0.8461] +2024-11-22 07:39:35.267864: Epoch time: 18.35 s +2024-11-22 07:39:36.260955: +2024-11-22 07:39:36.261175: Epoch 3775 +2024-11-22 07:39:36.261289: Current learning rate: 0.00563 +2024-11-22 07:39:54.896126: train_loss -0.7799 +2024-11-22 07:39:54.907535: val_loss -0.7746 +2024-11-22 07:39:54.907666: Pseudo dice [0.8389] +2024-11-22 07:39:54.907751: Epoch time: 18.64 s +2024-11-22 07:39:55.769197: +2024-11-22 07:39:55.769418: Epoch 3776 +2024-11-22 07:39:55.769528: Current learning rate: 0.00563 +2024-11-22 07:40:14.592286: train_loss -0.778 +2024-11-22 07:40:14.603309: val_loss -0.7605 +2024-11-22 07:40:14.603429: Pseudo dice [0.8428] +2024-11-22 07:40:14.603516: Epoch time: 18.82 s +2024-11-22 07:40:15.462400: +2024-11-22 07:40:15.462619: Epoch 3777 +2024-11-22 07:40:15.462733: Current learning rate: 0.00563 +2024-11-22 07:40:34.906095: train_loss -0.7815 +2024-11-22 07:40:34.913558: val_loss -0.7732 +2024-11-22 07:40:34.913677: Pseudo dice [0.8441] +2024-11-22 07:40:34.913757: Epoch time: 19.44 s +2024-11-22 07:40:35.772344: +2024-11-22 07:40:35.772551: Epoch 3778 +2024-11-22 07:40:35.772664: Current learning rate: 0.00563 +2024-11-22 07:40:54.686698: train_loss -0.7762 +2024-11-22 07:40:54.694162: val_loss -0.7641 +2024-11-22 07:40:54.694342: Pseudo dice [0.8555] +2024-11-22 07:40:54.694429: Epoch time: 18.92 s +2024-11-22 07:40:55.867463: +2024-11-22 07:40:55.867663: Epoch 3779 +2024-11-22 07:40:55.867775: Current learning rate: 0.00562 +2024-11-22 07:41:14.920599: train_loss -0.7781 +2024-11-22 07:41:14.928973: val_loss -0.7783 +2024-11-22 07:41:14.929117: Pseudo dice [0.8555] +2024-11-22 07:41:14.929215: Epoch time: 19.05 s +2024-11-22 07:41:15.788049: +2024-11-22 07:41:15.788275: Epoch 3780 +2024-11-22 07:41:15.788387: Current learning rate: 0.00562 +2024-11-22 07:41:34.858241: train_loss -0.778 +2024-11-22 07:41:34.861841: val_loss -0.7576 +2024-11-22 07:41:34.861971: Pseudo dice [0.8444] +2024-11-22 07:41:34.862387: Epoch time: 19.07 s +2024-11-22 07:41:35.724251: +2024-11-22 07:41:35.724454: Epoch 3781 +2024-11-22 07:41:35.724556: Current learning rate: 0.00562 +2024-11-22 07:41:54.208843: train_loss -0.7786 +2024-11-22 07:41:54.215539: val_loss -0.7672 +2024-11-22 07:41:54.215762: Pseudo dice [0.8536] +2024-11-22 07:41:54.215842: Epoch time: 18.49 s +2024-11-22 07:41:55.583177: +2024-11-22 07:41:55.583392: Epoch 3782 +2024-11-22 07:41:55.583506: Current learning rate: 0.00562 +2024-11-22 07:42:14.944876: train_loss -0.7838 +2024-11-22 07:42:14.950425: val_loss -0.7655 +2024-11-22 07:42:14.950535: Pseudo dice [0.863] +2024-11-22 07:42:14.950628: Epoch time: 19.36 s +2024-11-22 07:42:15.823063: +2024-11-22 07:42:15.823250: Epoch 3783 +2024-11-22 07:42:15.823359: Current learning rate: 0.00562 +2024-11-22 07:42:33.707806: train_loss -0.781 +2024-11-22 07:42:33.709506: val_loss -0.7785 +2024-11-22 07:42:33.709594: Pseudo dice [0.8564] +2024-11-22 07:42:33.709670: Epoch time: 17.89 s +2024-11-22 07:42:34.564744: +2024-11-22 07:42:34.565006: Epoch 3784 +2024-11-22 07:42:34.565125: Current learning rate: 0.00562 +2024-11-22 07:42:53.371067: train_loss -0.7875 +2024-11-22 07:42:53.379265: val_loss -0.7574 +2024-11-22 07:42:53.379402: Pseudo dice [0.8413] +2024-11-22 07:42:53.379488: Epoch time: 18.81 s +2024-11-22 07:42:54.425391: +2024-11-22 07:42:54.425664: Epoch 3785 +2024-11-22 07:42:54.425775: Current learning rate: 0.00562 +2024-11-22 07:43:12.103974: train_loss -0.7814 +2024-11-22 07:43:12.111557: val_loss -0.7671 +2024-11-22 07:43:12.111736: Pseudo dice [0.8586] +2024-11-22 07:43:12.111829: Epoch time: 17.68 s +2024-11-22 07:43:13.081652: +2024-11-22 07:43:13.081878: Epoch 3786 +2024-11-22 07:43:13.082001: Current learning rate: 0.00562 +2024-11-22 07:43:31.872463: train_loss -0.7903 +2024-11-22 07:43:31.877972: val_loss -0.7518 +2024-11-22 07:43:31.878158: Pseudo dice [0.847] +2024-11-22 07:43:31.878254: Epoch time: 18.79 s +2024-11-22 07:43:32.742564: +2024-11-22 07:43:32.742804: Epoch 3787 +2024-11-22 07:43:32.742915: Current learning rate: 0.00562 +2024-11-22 07:43:50.765570: train_loss -0.7822 +2024-11-22 07:43:50.774005: val_loss -0.7852 +2024-11-22 07:43:50.774124: Pseudo dice [0.8564] +2024-11-22 07:43:50.774203: Epoch time: 18.02 s +2024-11-22 07:43:51.676097: +2024-11-22 07:43:51.676357: Epoch 3788 +2024-11-22 07:43:51.676467: Current learning rate: 0.00561 +2024-11-22 07:44:10.871372: train_loss -0.7828 +2024-11-22 07:44:10.878644: val_loss -0.7512 +2024-11-22 07:44:10.878777: Pseudo dice [0.8303] +2024-11-22 07:44:10.878864: Epoch time: 19.2 s +2024-11-22 07:44:11.740123: +2024-11-22 07:44:11.740333: Epoch 3789 +2024-11-22 07:44:11.740450: Current learning rate: 0.00561 +2024-11-22 07:44:31.241765: train_loss -0.7779 +2024-11-22 07:44:31.247593: val_loss -0.7586 +2024-11-22 07:44:31.247709: Pseudo dice [0.8401] +2024-11-22 07:44:31.247798: Epoch time: 19.5 s +2024-11-22 07:44:32.104899: +2024-11-22 07:44:32.105155: Epoch 3790 +2024-11-22 07:44:32.105276: Current learning rate: 0.00561 +2024-11-22 07:44:50.150220: train_loss -0.7754 +2024-11-22 07:44:50.157527: val_loss -0.7877 +2024-11-22 07:44:50.157661: Pseudo dice [0.8614] +2024-11-22 07:44:50.157745: Epoch time: 18.05 s +2024-11-22 07:44:51.020455: +2024-11-22 07:44:51.020647: Epoch 3791 +2024-11-22 07:44:51.020758: Current learning rate: 0.00561 +2024-11-22 07:45:10.223834: train_loss -0.7827 +2024-11-22 07:45:10.229121: val_loss -0.7591 +2024-11-22 07:45:10.229234: Pseudo dice [0.8439] +2024-11-22 07:45:10.229315: Epoch time: 19.2 s +2024-11-22 07:45:11.086068: +2024-11-22 07:45:11.086276: Epoch 3792 +2024-11-22 07:45:11.086393: Current learning rate: 0.00561 +2024-11-22 07:45:31.085501: train_loss -0.7844 +2024-11-22 07:45:31.088871: val_loss -0.7678 +2024-11-22 07:45:31.089002: Pseudo dice [0.8426] +2024-11-22 07:45:31.089085: Epoch time: 20.0 s +2024-11-22 07:45:32.476377: +2024-11-22 07:45:32.476605: Epoch 3793 +2024-11-22 07:45:32.476713: Current learning rate: 0.00561 +2024-11-22 07:45:51.118706: train_loss -0.7773 +2024-11-22 07:45:51.126842: val_loss -0.7679 +2024-11-22 07:45:51.126968: Pseudo dice [0.8396] +2024-11-22 07:45:51.127066: Epoch time: 18.64 s +2024-11-22 07:45:52.040421: +2024-11-22 07:45:52.040649: Epoch 3794 +2024-11-22 07:45:52.040765: Current learning rate: 0.00561 +2024-11-22 07:46:10.884178: train_loss -0.7894 +2024-11-22 07:46:10.890479: val_loss -0.7856 +2024-11-22 07:46:10.890617: Pseudo dice [0.8507] +2024-11-22 07:46:10.890704: Epoch time: 18.84 s +2024-11-22 07:46:11.750831: +2024-11-22 07:46:11.751034: Epoch 3795 +2024-11-22 07:46:11.751147: Current learning rate: 0.00561 +2024-11-22 07:46:31.610735: train_loss -0.7885 +2024-11-22 07:46:31.617204: val_loss -0.7659 +2024-11-22 07:46:31.617326: Pseudo dice [0.848] +2024-11-22 07:46:31.617401: Epoch time: 19.86 s +2024-11-22 07:46:32.474714: +2024-11-22 07:46:32.474904: Epoch 3796 +2024-11-22 07:46:32.475018: Current learning rate: 0.0056 +2024-11-22 07:46:50.735335: train_loss -0.7855 +2024-11-22 07:46:50.742326: val_loss -0.7897 +2024-11-22 07:46:50.742451: Pseudo dice [0.8585] +2024-11-22 07:46:50.742533: Epoch time: 18.26 s +2024-11-22 07:46:51.621336: +2024-11-22 07:46:51.621558: Epoch 3797 +2024-11-22 07:46:51.621670: Current learning rate: 0.0056 +2024-11-22 07:47:11.023351: train_loss -0.7913 +2024-11-22 07:47:11.029155: val_loss -0.7778 +2024-11-22 07:47:11.029270: Pseudo dice [0.8727] +2024-11-22 07:47:11.029362: Epoch time: 19.4 s +2024-11-22 07:47:11.982633: +2024-11-22 07:47:11.982846: Epoch 3798 +2024-11-22 07:47:11.982961: Current learning rate: 0.0056 +2024-11-22 07:47:31.228343: train_loss -0.7788 +2024-11-22 07:47:31.235466: val_loss -0.7517 +2024-11-22 07:47:31.235586: Pseudo dice [0.8474] +2024-11-22 07:47:31.235667: Epoch time: 19.25 s +2024-11-22 07:47:32.112579: +2024-11-22 07:47:32.112776: Epoch 3799 +2024-11-22 07:47:32.112889: Current learning rate: 0.0056 +2024-11-22 07:47:51.179030: train_loss -0.7971 +2024-11-22 07:47:51.180706: val_loss -0.7737 +2024-11-22 07:47:51.180822: Pseudo dice [0.8508] +2024-11-22 07:47:51.180904: Epoch time: 19.07 s +2024-11-22 07:47:52.303489: +2024-11-22 07:47:52.303698: Epoch 3800 +2024-11-22 07:47:52.303813: Current learning rate: 0.0056 +2024-11-22 07:48:10.596694: train_loss -0.7887 +2024-11-22 07:48:10.599595: val_loss -0.7837 +2024-11-22 07:48:10.599693: Pseudo dice [0.8584] +2024-11-22 07:48:10.606373: Epoch time: 18.29 s +2024-11-22 07:48:11.455493: +2024-11-22 07:48:11.455699: Epoch 3801 +2024-11-22 07:48:11.455814: Current learning rate: 0.0056 +2024-11-22 07:48:30.143623: train_loss -0.7957 +2024-11-22 07:48:30.150410: val_loss -0.7589 +2024-11-22 07:48:30.150532: Pseudo dice [0.8429] +2024-11-22 07:48:30.150621: Epoch time: 18.69 s +2024-11-22 07:48:31.082051: +2024-11-22 07:48:31.082259: Epoch 3802 +2024-11-22 07:48:31.082367: Current learning rate: 0.0056 +2024-11-22 07:48:48.701404: train_loss -0.7896 +2024-11-22 07:48:48.705386: val_loss -0.7649 +2024-11-22 07:48:48.705489: Pseudo dice [0.8601] +2024-11-22 07:48:48.705566: Epoch time: 17.62 s +2024-11-22 07:48:49.569030: +2024-11-22 07:48:49.569271: Epoch 3803 +2024-11-22 07:48:49.569383: Current learning rate: 0.0056 +2024-11-22 07:49:09.354957: train_loss -0.7894 +2024-11-22 07:49:09.357324: val_loss -0.7776 +2024-11-22 07:49:09.357416: Pseudo dice [0.8531] +2024-11-22 07:49:09.357497: Epoch time: 19.79 s +2024-11-22 07:49:10.651839: +2024-11-22 07:49:10.652045: Epoch 3804 +2024-11-22 07:49:10.652164: Current learning rate: 0.00559 +2024-11-22 07:49:28.578600: train_loss -0.7847 +2024-11-22 07:49:28.584598: val_loss -0.7492 +2024-11-22 07:49:28.584732: Pseudo dice [0.8483] +2024-11-22 07:49:28.584828: Epoch time: 17.93 s +2024-11-22 07:49:29.508856: +2024-11-22 07:49:29.509134: Epoch 3805 +2024-11-22 07:49:29.509251: Current learning rate: 0.00559 +2024-11-22 07:49:47.420154: train_loss -0.7816 +2024-11-22 07:49:47.424816: val_loss -0.7897 +2024-11-22 07:49:47.424944: Pseudo dice [0.8544] +2024-11-22 07:49:47.425024: Epoch time: 17.91 s +2024-11-22 07:49:48.310792: +2024-11-22 07:49:48.311004: Epoch 3806 +2024-11-22 07:49:48.311360: Current learning rate: 0.00559 +2024-11-22 07:50:07.661744: train_loss -0.7875 +2024-11-22 07:50:07.664025: val_loss -0.7578 +2024-11-22 07:50:07.664122: Pseudo dice [0.8416] +2024-11-22 07:50:07.664199: Epoch time: 19.35 s +2024-11-22 07:50:08.517055: +2024-11-22 07:50:08.517260: Epoch 3807 +2024-11-22 07:50:08.517373: Current learning rate: 0.00559 +2024-11-22 07:50:27.374642: train_loss -0.7782 +2024-11-22 07:50:27.380210: val_loss -0.7608 +2024-11-22 07:50:27.380343: Pseudo dice [0.8449] +2024-11-22 07:50:27.380470: Epoch time: 18.86 s +2024-11-22 07:50:28.255846: +2024-11-22 07:50:28.256073: Epoch 3808 +2024-11-22 07:50:28.256185: Current learning rate: 0.00559 +2024-11-22 07:50:46.090582: train_loss -0.783 +2024-11-22 07:50:46.095738: val_loss -0.7778 +2024-11-22 07:50:46.095874: Pseudo dice [0.8518] +2024-11-22 07:50:46.095963: Epoch time: 17.84 s +2024-11-22 07:50:46.962573: +2024-11-22 07:50:46.962794: Epoch 3809 +2024-11-22 07:50:46.962906: Current learning rate: 0.00559 +2024-11-22 07:51:06.490703: train_loss -0.7881 +2024-11-22 07:51:06.494187: val_loss -0.7762 +2024-11-22 07:51:06.494295: Pseudo dice [0.851] +2024-11-22 07:51:06.494460: Epoch time: 19.53 s +2024-11-22 07:51:07.539444: +2024-11-22 07:51:07.539655: Epoch 3810 +2024-11-22 07:51:07.539773: Current learning rate: 0.00559 +2024-11-22 07:51:26.298905: train_loss -0.7852 +2024-11-22 07:51:26.304921: val_loss -0.7888 +2024-11-22 07:51:26.305043: Pseudo dice [0.8529] +2024-11-22 07:51:26.305132: Epoch time: 18.76 s +2024-11-22 07:51:27.290262: +2024-11-22 07:51:27.290474: Epoch 3811 +2024-11-22 07:51:27.290589: Current learning rate: 0.00559 +2024-11-22 07:51:46.709430: train_loss -0.7924 +2024-11-22 07:51:46.717966: val_loss -0.7556 +2024-11-22 07:51:46.718095: Pseudo dice [0.8591] +2024-11-22 07:51:46.718240: Epoch time: 19.42 s +2024-11-22 07:51:47.763443: +2024-11-22 07:51:47.763646: Epoch 3812 +2024-11-22 07:51:47.763758: Current learning rate: 0.00559 +2024-11-22 07:52:07.068425: train_loss -0.7896 +2024-11-22 07:52:07.074619: val_loss -0.7978 +2024-11-22 07:52:07.074749: Pseudo dice [0.8549] +2024-11-22 07:52:07.074899: Epoch time: 19.31 s +2024-11-22 07:52:08.116962: +2024-11-22 07:52:08.117180: Epoch 3813 +2024-11-22 07:52:08.117297: Current learning rate: 0.00558 +2024-11-22 07:52:27.097630: train_loss -0.7843 +2024-11-22 07:52:27.104379: val_loss -0.7694 +2024-11-22 07:52:27.104507: Pseudo dice [0.839] +2024-11-22 07:52:27.104586: Epoch time: 18.98 s +2024-11-22 07:52:28.091472: +2024-11-22 07:52:28.091696: Epoch 3814 +2024-11-22 07:52:28.091815: Current learning rate: 0.00558 +2024-11-22 07:52:46.747372: train_loss -0.7922 +2024-11-22 07:52:46.750210: val_loss -0.7937 +2024-11-22 07:52:46.750316: Pseudo dice [0.8491] +2024-11-22 07:52:46.750401: Epoch time: 18.66 s +2024-11-22 07:52:48.037510: +2024-11-22 07:52:48.037948: Epoch 3815 +2024-11-22 07:52:48.038062: Current learning rate: 0.00558 +2024-11-22 07:53:06.580402: train_loss -0.7904 +2024-11-22 07:53:06.582682: val_loss -0.7504 +2024-11-22 07:53:06.582772: Pseudo dice [0.8444] +2024-11-22 07:53:06.582859: Epoch time: 18.54 s +2024-11-22 07:53:07.440968: +2024-11-22 07:53:07.441169: Epoch 3816 +2024-11-22 07:53:07.441277: Current learning rate: 0.00558 +2024-11-22 07:53:26.535811: train_loss -0.7891 +2024-11-22 07:53:26.543898: val_loss -0.7631 +2024-11-22 07:53:26.544013: Pseudo dice [0.8566] +2024-11-22 07:53:26.544098: Epoch time: 19.1 s +2024-11-22 07:53:27.548165: +2024-11-22 07:53:27.548404: Epoch 3817 +2024-11-22 07:53:27.548523: Current learning rate: 0.00558 +2024-11-22 07:53:46.626761: train_loss -0.7886 +2024-11-22 07:53:46.632236: val_loss -0.7745 +2024-11-22 07:53:46.632442: Pseudo dice [0.842] +2024-11-22 07:53:46.633006: Epoch time: 19.08 s +2024-11-22 07:53:47.629721: +2024-11-22 07:53:47.629930: Epoch 3818 +2024-11-22 07:53:47.630040: Current learning rate: 0.00558 +2024-11-22 07:54:06.835925: train_loss -0.7824 +2024-11-22 07:54:06.843656: val_loss -0.7864 +2024-11-22 07:54:06.843779: Pseudo dice [0.8513] +2024-11-22 07:54:06.866555: Epoch time: 19.21 s +2024-11-22 07:54:07.881397: +2024-11-22 07:54:07.881664: Epoch 3819 +2024-11-22 07:54:07.881805: Current learning rate: 0.00558 +2024-11-22 07:54:27.954853: train_loss -0.7887 +2024-11-22 07:54:27.961833: val_loss -0.7775 +2024-11-22 07:54:27.961970: Pseudo dice [0.8546] +2024-11-22 07:54:27.962057: Epoch time: 20.07 s +2024-11-22 07:54:28.829834: +2024-11-22 07:54:28.830281: Epoch 3820 +2024-11-22 07:54:28.830396: Current learning rate: 0.00558 +2024-11-22 07:54:49.382143: train_loss -0.7824 +2024-11-22 07:54:49.384818: val_loss -0.7877 +2024-11-22 07:54:49.384996: Pseudo dice [0.8611] +2024-11-22 07:54:49.385081: Epoch time: 20.55 s +2024-11-22 07:54:50.246818: +2024-11-22 07:54:50.247012: Epoch 3821 +2024-11-22 07:54:50.247131: Current learning rate: 0.00557 +2024-11-22 07:55:10.133730: train_loss -0.7977 +2024-11-22 07:55:10.140972: val_loss -0.7733 +2024-11-22 07:55:10.141108: Pseudo dice [0.85] +2024-11-22 07:55:10.141193: Epoch time: 19.89 s +2024-11-22 07:55:10.997797: +2024-11-22 07:55:10.997993: Epoch 3822 +2024-11-22 07:55:10.998116: Current learning rate: 0.00557 +2024-11-22 07:55:29.322421: train_loss -0.7876 +2024-11-22 07:55:29.335704: val_loss -0.7564 +2024-11-22 07:55:29.335898: Pseudo dice [0.8553] +2024-11-22 07:55:29.335995: Epoch time: 18.33 s +2024-11-22 07:55:30.189641: +2024-11-22 07:55:30.189861: Epoch 3823 +2024-11-22 07:55:30.189973: Current learning rate: 0.00557 +2024-11-22 07:55:51.053726: train_loss -0.7802 +2024-11-22 07:55:51.060819: val_loss -0.7757 +2024-11-22 07:55:51.060955: Pseudo dice [0.8559] +2024-11-22 07:55:51.061047: Epoch time: 20.86 s +2024-11-22 07:55:51.930490: +2024-11-22 07:55:51.930698: Epoch 3824 +2024-11-22 07:55:51.930813: Current learning rate: 0.00557 +2024-11-22 07:56:10.825882: train_loss -0.7924 +2024-11-22 07:56:10.832920: val_loss -0.766 +2024-11-22 07:56:10.833056: Pseudo dice [0.8377] +2024-11-22 07:56:10.833149: Epoch time: 18.9 s +2024-11-22 07:56:11.693023: +2024-11-22 07:56:11.693218: Epoch 3825 +2024-11-22 07:56:11.693330: Current learning rate: 0.00557 +2024-11-22 07:56:30.669392: train_loss -0.7891 +2024-11-22 07:56:30.676467: val_loss -0.7581 +2024-11-22 07:56:30.676577: Pseudo dice [0.8392] +2024-11-22 07:56:30.676661: Epoch time: 18.98 s +2024-11-22 07:56:31.978295: +2024-11-22 07:56:31.978524: Epoch 3826 +2024-11-22 07:56:31.978638: Current learning rate: 0.00557 +2024-11-22 07:56:50.579911: train_loss -0.7939 +2024-11-22 07:56:50.585431: val_loss -0.7561 +2024-11-22 07:56:50.585563: Pseudo dice [0.8382] +2024-11-22 07:56:50.585650: Epoch time: 18.6 s +2024-11-22 07:56:51.597786: +2024-11-22 07:56:51.597999: Epoch 3827 +2024-11-22 07:56:51.598114: Current learning rate: 0.00557 +2024-11-22 07:57:10.985470: train_loss -0.7866 +2024-11-22 07:57:10.987263: val_loss -0.7593 +2024-11-22 07:57:10.987383: Pseudo dice [0.846] +2024-11-22 07:57:10.987467: Epoch time: 19.39 s +2024-11-22 07:57:12.156280: +2024-11-22 07:57:12.156567: Epoch 3828 +2024-11-22 07:57:12.156686: Current learning rate: 0.00557 +2024-11-22 07:57:30.007169: train_loss -0.7899 +2024-11-22 07:57:30.012553: val_loss -0.7844 +2024-11-22 07:57:30.012670: Pseudo dice [0.8614] +2024-11-22 07:57:30.012758: Epoch time: 17.85 s +2024-11-22 07:57:30.881128: +2024-11-22 07:57:30.881351: Epoch 3829 +2024-11-22 07:57:30.881459: Current learning rate: 0.00556 +2024-11-22 07:57:49.133801: train_loss -0.7808 +2024-11-22 07:57:49.135316: val_loss -0.766 +2024-11-22 07:57:49.135452: Pseudo dice [0.8597] +2024-11-22 07:57:49.135537: Epoch time: 18.25 s +2024-11-22 07:57:50.149737: +2024-11-22 07:57:50.149978: Epoch 3830 +2024-11-22 07:57:50.150095: Current learning rate: 0.00556 +2024-11-22 07:58:09.988617: train_loss -0.7825 +2024-11-22 07:58:09.995595: val_loss -0.7689 +2024-11-22 07:58:09.995727: Pseudo dice [0.8434] +2024-11-22 07:58:09.995821: Epoch time: 19.84 s +2024-11-22 07:58:10.867746: +2024-11-22 07:58:10.867989: Epoch 3831 +2024-11-22 07:58:10.868110: Current learning rate: 0.00556 +2024-11-22 07:58:30.427428: train_loss -0.7691 +2024-11-22 07:58:30.467459: val_loss -0.7411 +2024-11-22 07:58:30.467635: Pseudo dice [0.8278] +2024-11-22 07:58:30.467719: Epoch time: 19.56 s +2024-11-22 07:58:31.389896: +2024-11-22 07:58:31.390115: Epoch 3832 +2024-11-22 07:58:31.390225: Current learning rate: 0.00556 +2024-11-22 07:58:50.937143: train_loss -0.7715 +2024-11-22 07:58:50.938889: val_loss -0.7838 +2024-11-22 07:58:50.938976: Pseudo dice [0.8456] +2024-11-22 07:58:50.939056: Epoch time: 19.55 s +2024-11-22 07:58:51.799744: +2024-11-22 07:58:51.799952: Epoch 3833 +2024-11-22 07:58:51.800071: Current learning rate: 0.00556 +2024-11-22 07:59:11.384041: train_loss -0.7755 +2024-11-22 07:59:11.387285: val_loss -0.7559 +2024-11-22 07:59:11.387392: Pseudo dice [0.849] +2024-11-22 07:59:11.387472: Epoch time: 19.59 s +2024-11-22 07:59:12.504820: +2024-11-22 07:59:12.505062: Epoch 3834 +2024-11-22 07:59:12.505186: Current learning rate: 0.00556 +2024-11-22 07:59:32.072756: train_loss -0.7786 +2024-11-22 07:59:32.077739: val_loss -0.7527 +2024-11-22 07:59:32.077865: Pseudo dice [0.8493] +2024-11-22 07:59:32.077960: Epoch time: 19.57 s +2024-11-22 07:59:32.973165: +2024-11-22 07:59:32.973356: Epoch 3835 +2024-11-22 07:59:32.973477: Current learning rate: 0.00556 +2024-11-22 07:59:52.601953: train_loss -0.7711 +2024-11-22 07:59:52.608607: val_loss -0.7659 +2024-11-22 07:59:52.608729: Pseudo dice [0.8512] +2024-11-22 07:59:52.608815: Epoch time: 19.63 s +2024-11-22 07:59:53.594037: +2024-11-22 07:59:53.594244: Epoch 3836 +2024-11-22 07:59:53.594361: Current learning rate: 0.00556 +2024-11-22 08:00:12.839495: train_loss -0.7772 +2024-11-22 08:00:12.869234: val_loss -0.7752 +2024-11-22 08:00:12.869380: Pseudo dice [0.8427] +2024-11-22 08:00:12.869470: Epoch time: 19.25 s +2024-11-22 08:00:14.342755: +2024-11-22 08:00:14.342968: Epoch 3837 +2024-11-22 08:00:14.343085: Current learning rate: 0.00556 +2024-11-22 08:00:32.440945: train_loss -0.787 +2024-11-22 08:00:32.446348: val_loss -0.767 +2024-11-22 08:00:32.446565: Pseudo dice [0.8511] +2024-11-22 08:00:32.446697: Epoch time: 18.1 s +2024-11-22 08:00:33.323905: +2024-11-22 08:00:33.324159: Epoch 3838 +2024-11-22 08:00:33.324288: Current learning rate: 0.00555 +2024-11-22 08:00:52.680474: train_loss -0.7866 +2024-11-22 08:00:52.683141: val_loss -0.7399 +2024-11-22 08:00:52.683270: Pseudo dice [0.8576] +2024-11-22 08:00:52.683350: Epoch time: 19.36 s +2024-11-22 08:00:53.667736: +2024-11-22 08:00:53.668004: Epoch 3839 +2024-11-22 08:00:53.668119: Current learning rate: 0.00555 +2024-11-22 08:01:11.963343: train_loss -0.7861 +2024-11-22 08:01:11.970996: val_loss -0.7538 +2024-11-22 08:01:11.971116: Pseudo dice [0.8418] +2024-11-22 08:01:11.971198: Epoch time: 18.3 s +2024-11-22 08:01:12.938138: +2024-11-22 08:01:12.938337: Epoch 3840 +2024-11-22 08:01:12.938455: Current learning rate: 0.00555 +2024-11-22 08:01:33.047715: train_loss -0.7856 +2024-11-22 08:01:33.052997: val_loss -0.7658 +2024-11-22 08:01:33.053117: Pseudo dice [0.8556] +2024-11-22 08:01:33.053197: Epoch time: 20.11 s +2024-11-22 08:01:34.031736: +2024-11-22 08:01:34.031979: Epoch 3841 +2024-11-22 08:01:34.032101: Current learning rate: 0.00555 +2024-11-22 08:01:53.243190: train_loss -0.7795 +2024-11-22 08:01:53.249527: val_loss -0.7864 +2024-11-22 08:01:53.249707: Pseudo dice [0.8535] +2024-11-22 08:01:53.249809: Epoch time: 19.21 s +2024-11-22 08:01:54.242646: +2024-11-22 08:01:54.242888: Epoch 3842 +2024-11-22 08:01:54.243000: Current learning rate: 0.00555 +2024-11-22 08:02:13.881936: train_loss -0.7827 +2024-11-22 08:02:13.887834: val_loss -0.7714 +2024-11-22 08:02:13.887989: Pseudo dice [0.8544] +2024-11-22 08:02:13.888124: Epoch time: 19.64 s +2024-11-22 08:02:14.762936: +2024-11-22 08:02:14.763136: Epoch 3843 +2024-11-22 08:02:14.763256: Current learning rate: 0.00555 +2024-11-22 08:02:34.628211: train_loss -0.7905 +2024-11-22 08:02:34.636827: val_loss -0.7581 +2024-11-22 08:02:34.636942: Pseudo dice [0.8622] +2024-11-22 08:02:34.637260: Epoch time: 19.87 s +2024-11-22 08:02:35.542073: +2024-11-22 08:02:35.542279: Epoch 3844 +2024-11-22 08:02:35.542395: Current learning rate: 0.00555 +2024-11-22 08:02:54.058296: train_loss -0.772 +2024-11-22 08:02:54.060826: val_loss -0.746 +2024-11-22 08:02:54.060939: Pseudo dice [0.843] +2024-11-22 08:02:54.061023: Epoch time: 18.52 s +2024-11-22 08:02:54.921406: +2024-11-22 08:02:54.921613: Epoch 3845 +2024-11-22 08:02:54.921724: Current learning rate: 0.00555 +2024-11-22 08:03:13.790254: train_loss -0.7811 +2024-11-22 08:03:13.795774: val_loss -0.7781 +2024-11-22 08:03:13.795910: Pseudo dice [0.8578] +2024-11-22 08:03:13.795996: Epoch time: 18.87 s +2024-11-22 08:03:14.658656: +2024-11-22 08:03:14.658844: Epoch 3846 +2024-11-22 08:03:14.658957: Current learning rate: 0.00554 +2024-11-22 08:03:33.962277: train_loss -0.7858 +2024-11-22 08:03:33.968165: val_loss -0.763 +2024-11-22 08:03:33.968299: Pseudo dice [0.8497] +2024-11-22 08:03:33.968382: Epoch time: 19.3 s +2024-11-22 08:03:34.858718: +2024-11-22 08:03:34.858930: Epoch 3847 +2024-11-22 08:03:34.859042: Current learning rate: 0.00554 +2024-11-22 08:03:53.119747: train_loss -0.7843 +2024-11-22 08:03:53.124863: val_loss -0.7722 +2024-11-22 08:03:53.124973: Pseudo dice [0.8422] +2024-11-22 08:03:53.125052: Epoch time: 18.26 s +2024-11-22 08:03:54.400470: +2024-11-22 08:03:54.400687: Epoch 3848 +2024-11-22 08:03:54.400804: Current learning rate: 0.00554 +2024-11-22 08:04:13.074292: train_loss -0.7834 +2024-11-22 08:04:13.079944: val_loss -0.78 +2024-11-22 08:04:13.080161: Pseudo dice [0.849] +2024-11-22 08:04:13.080261: Epoch time: 18.67 s +2024-11-22 08:04:13.963737: +2024-11-22 08:04:13.963941: Epoch 3849 +2024-11-22 08:04:13.964051: Current learning rate: 0.00554 +2024-11-22 08:04:33.237386: train_loss -0.7862 +2024-11-22 08:04:33.250154: val_loss -0.7531 +2024-11-22 08:04:33.250286: Pseudo dice [0.8465] +2024-11-22 08:04:33.250374: Epoch time: 19.27 s +2024-11-22 08:04:34.415390: +2024-11-22 08:04:34.415631: Epoch 3850 +2024-11-22 08:04:34.415749: Current learning rate: 0.00554 +2024-11-22 08:04:54.632765: train_loss -0.7823 +2024-11-22 08:04:54.637760: val_loss -0.7674 +2024-11-22 08:04:54.637874: Pseudo dice [0.8554] +2024-11-22 08:04:54.637959: Epoch time: 20.22 s +2024-11-22 08:04:55.616512: +2024-11-22 08:04:55.616743: Epoch 3851 +2024-11-22 08:04:55.616857: Current learning rate: 0.00554 +2024-11-22 08:05:14.895910: train_loss -0.7855 +2024-11-22 08:05:14.898159: val_loss -0.7638 +2024-11-22 08:05:14.898270: Pseudo dice [0.8389] +2024-11-22 08:05:14.898352: Epoch time: 19.28 s +2024-11-22 08:05:15.785477: +2024-11-22 08:05:15.785684: Epoch 3852 +2024-11-22 08:05:15.785805: Current learning rate: 0.00554 +2024-11-22 08:05:34.731187: train_loss -0.7913 +2024-11-22 08:05:34.735490: val_loss -0.7649 +2024-11-22 08:05:34.735603: Pseudo dice [0.8465] +2024-11-22 08:05:34.735694: Epoch time: 18.95 s +2024-11-22 08:05:35.799692: +2024-11-22 08:05:35.799899: Epoch 3853 +2024-11-22 08:05:35.800009: Current learning rate: 0.00554 +2024-11-22 08:05:53.847722: train_loss -0.7866 +2024-11-22 08:05:53.854831: val_loss -0.7412 +2024-11-22 08:05:53.854953: Pseudo dice [0.851] +2024-11-22 08:05:53.855038: Epoch time: 18.05 s +2024-11-22 08:05:54.742429: +2024-11-22 08:05:54.742633: Epoch 3854 +2024-11-22 08:05:54.742742: Current learning rate: 0.00553 +2024-11-22 08:06:11.922683: train_loss -0.7855 +2024-11-22 08:06:11.923934: val_loss -0.7665 +2024-11-22 08:06:11.924020: Pseudo dice [0.8593] +2024-11-22 08:06:11.924104: Epoch time: 17.18 s +2024-11-22 08:06:12.781317: +2024-11-22 08:06:12.781547: Epoch 3855 +2024-11-22 08:06:12.781663: Current learning rate: 0.00553 +2024-11-22 08:06:32.204472: train_loss -0.7867 +2024-11-22 08:06:32.212041: val_loss -0.749 +2024-11-22 08:06:32.212185: Pseudo dice [0.8377] +2024-11-22 08:06:32.212266: Epoch time: 19.42 s +2024-11-22 08:06:33.114964: +2024-11-22 08:06:33.115188: Epoch 3856 +2024-11-22 08:06:33.115302: Current learning rate: 0.00553 +2024-11-22 08:06:51.571720: train_loss -0.7888 +2024-11-22 08:06:51.578861: val_loss -0.7545 +2024-11-22 08:06:51.578989: Pseudo dice [0.8634] +2024-11-22 08:06:51.579235: Epoch time: 18.46 s +2024-11-22 08:06:52.464894: +2024-11-22 08:06:52.465364: Epoch 3857 +2024-11-22 08:06:52.465503: Current learning rate: 0.00553 +2024-11-22 08:07:11.465903: train_loss -0.7834 +2024-11-22 08:07:11.472127: val_loss -0.7777 +2024-11-22 08:07:11.472232: Pseudo dice [0.8536] +2024-11-22 08:07:11.472308: Epoch time: 19.0 s +2024-11-22 08:07:12.353686: +2024-11-22 08:07:12.353880: Epoch 3858 +2024-11-22 08:07:12.353991: Current learning rate: 0.00553 +2024-11-22 08:07:31.140307: train_loss -0.7724 +2024-11-22 08:07:31.145792: val_loss -0.7735 +2024-11-22 08:07:31.145918: Pseudo dice [0.8451] +2024-11-22 08:07:31.146003: Epoch time: 18.79 s +2024-11-22 08:07:32.526926: +2024-11-22 08:07:32.527364: Epoch 3859 +2024-11-22 08:07:32.527481: Current learning rate: 0.00553 +2024-11-22 08:07:51.723647: train_loss -0.7909 +2024-11-22 08:07:51.725399: val_loss -0.7657 +2024-11-22 08:07:51.725493: Pseudo dice [0.8654] +2024-11-22 08:07:51.725570: Epoch time: 19.2 s +2024-11-22 08:07:52.623431: +2024-11-22 08:07:52.623651: Epoch 3860 +2024-11-22 08:07:52.623768: Current learning rate: 0.00553 +2024-11-22 08:08:12.184852: train_loss -0.7896 +2024-11-22 08:08:12.187919: val_loss -0.767 +2024-11-22 08:08:12.188026: Pseudo dice [0.8555] +2024-11-22 08:08:12.188118: Epoch time: 19.56 s +2024-11-22 08:08:13.049671: +2024-11-22 08:08:13.049895: Epoch 3861 +2024-11-22 08:08:13.050009: Current learning rate: 0.00553 +2024-11-22 08:08:32.248978: train_loss -0.7881 +2024-11-22 08:08:32.250563: val_loss -0.7775 +2024-11-22 08:08:32.250644: Pseudo dice [0.8576] +2024-11-22 08:08:32.250719: Epoch time: 19.2 s +2024-11-22 08:08:33.106702: +2024-11-22 08:08:33.106927: Epoch 3862 +2024-11-22 08:08:33.107045: Current learning rate: 0.00552 +2024-11-22 08:08:51.948788: train_loss -0.7902 +2024-11-22 08:08:51.950610: val_loss -0.7554 +2024-11-22 08:08:51.950712: Pseudo dice [0.8485] +2024-11-22 08:08:51.950790: Epoch time: 18.84 s +2024-11-22 08:08:52.819090: +2024-11-22 08:08:52.819297: Epoch 3863 +2024-11-22 08:08:52.819407: Current learning rate: 0.00552 +2024-11-22 08:09:11.254297: train_loss -0.7892 +2024-11-22 08:09:11.259211: val_loss -0.794 +2024-11-22 08:09:11.259346: Pseudo dice [0.8646] +2024-11-22 08:09:11.259437: Epoch time: 18.44 s +2024-11-22 08:09:12.125562: +2024-11-22 08:09:12.125792: Epoch 3864 +2024-11-22 08:09:12.125898: Current learning rate: 0.00552 +2024-11-22 08:09:30.964305: train_loss -0.7897 +2024-11-22 08:09:30.987020: val_loss -0.7567 +2024-11-22 08:09:30.987169: Pseudo dice [0.8536] +2024-11-22 08:09:30.987252: Epoch time: 18.84 s +2024-11-22 08:09:31.882617: +2024-11-22 08:09:31.882825: Epoch 3865 +2024-11-22 08:09:31.882929: Current learning rate: 0.00552 +2024-11-22 08:09:50.366349: train_loss -0.7961 +2024-11-22 08:09:50.374624: val_loss -0.7925 +2024-11-22 08:09:50.374745: Pseudo dice [0.8514] +2024-11-22 08:09:50.374826: Epoch time: 18.48 s +2024-11-22 08:09:51.254993: +2024-11-22 08:09:51.255190: Epoch 3866 +2024-11-22 08:09:51.255303: Current learning rate: 0.00552 +2024-11-22 08:10:11.015665: train_loss -0.7878 +2024-11-22 08:10:11.021239: val_loss -0.781 +2024-11-22 08:10:11.021349: Pseudo dice [0.8602] +2024-11-22 08:10:11.021439: Epoch time: 19.76 s +2024-11-22 08:10:12.008877: +2024-11-22 08:10:12.009100: Epoch 3867 +2024-11-22 08:10:12.009216: Current learning rate: 0.00552 +2024-11-22 08:10:31.765952: train_loss -0.7785 +2024-11-22 08:10:31.767846: val_loss -0.7746 +2024-11-22 08:10:31.767949: Pseudo dice [0.8551] +2024-11-22 08:10:31.768036: Epoch time: 19.76 s +2024-11-22 08:10:32.625055: +2024-11-22 08:10:32.625261: Epoch 3868 +2024-11-22 08:10:32.625378: Current learning rate: 0.00552 +2024-11-22 08:10:51.583928: train_loss -0.79 +2024-11-22 08:10:51.589956: val_loss -0.7528 +2024-11-22 08:10:51.590076: Pseudo dice [0.8513] +2024-11-22 08:10:51.590158: Epoch time: 18.96 s +2024-11-22 08:10:52.487159: +2024-11-22 08:10:52.487372: Epoch 3869 +2024-11-22 08:10:52.487488: Current learning rate: 0.00552 +2024-11-22 08:11:11.734983: train_loss -0.7874 +2024-11-22 08:11:11.736486: val_loss -0.7534 +2024-11-22 08:11:11.736828: Pseudo dice [0.851] +2024-11-22 08:11:11.737118: Epoch time: 19.25 s +2024-11-22 08:11:12.968318: +2024-11-22 08:11:12.968530: Epoch 3870 +2024-11-22 08:11:12.968643: Current learning rate: 0.00552 +2024-11-22 08:11:32.044431: train_loss -0.7929 +2024-11-22 08:11:32.046282: val_loss -0.7913 +2024-11-22 08:11:32.046381: Pseudo dice [0.8685] +2024-11-22 08:11:32.046469: Epoch time: 19.08 s +2024-11-22 08:11:32.909316: +2024-11-22 08:11:32.909538: Epoch 3871 +2024-11-22 08:11:32.909650: Current learning rate: 0.00551 +2024-11-22 08:11:51.343316: train_loss -0.775 +2024-11-22 08:11:51.346882: val_loss -0.7602 +2024-11-22 08:11:51.346998: Pseudo dice [0.8532] +2024-11-22 08:11:51.347145: Epoch time: 18.43 s +2024-11-22 08:11:52.385171: +2024-11-22 08:11:52.385389: Epoch 3872 +2024-11-22 08:11:52.385509: Current learning rate: 0.00551 +2024-11-22 08:12:11.211995: train_loss -0.7917 +2024-11-22 08:12:11.217655: val_loss -0.7674 +2024-11-22 08:12:11.217777: Pseudo dice [0.8472] +2024-11-22 08:12:11.217854: Epoch time: 18.83 s +2024-11-22 08:12:12.090723: +2024-11-22 08:12:12.090923: Epoch 3873 +2024-11-22 08:12:12.091032: Current learning rate: 0.00551 +2024-11-22 08:12:29.944782: train_loss -0.7821 +2024-11-22 08:12:29.952275: val_loss -0.787 +2024-11-22 08:12:29.952394: Pseudo dice [0.8508] +2024-11-22 08:12:29.952477: Epoch time: 17.85 s +2024-11-22 08:12:30.825954: +2024-11-22 08:12:30.826177: Epoch 3874 +2024-11-22 08:12:30.826283: Current learning rate: 0.00551 +2024-11-22 08:12:49.870391: train_loss -0.7895 +2024-11-22 08:12:49.876897: val_loss -0.806 +2024-11-22 08:12:49.877026: Pseudo dice [0.8603] +2024-11-22 08:12:49.877122: Epoch time: 19.05 s +2024-11-22 08:12:50.828482: +2024-11-22 08:12:50.828705: Epoch 3875 +2024-11-22 08:12:50.828816: Current learning rate: 0.00551 +2024-11-22 08:13:09.908273: train_loss -0.7871 +2024-11-22 08:13:09.914127: val_loss -0.7693 +2024-11-22 08:13:09.914276: Pseudo dice [0.8542] +2024-11-22 08:13:09.914371: Epoch time: 19.08 s +2024-11-22 08:13:10.778364: +2024-11-22 08:13:10.778584: Epoch 3876 +2024-11-22 08:13:10.778699: Current learning rate: 0.00551 +2024-11-22 08:13:29.237185: train_loss -0.7922 +2024-11-22 08:13:29.243848: val_loss -0.7549 +2024-11-22 08:13:29.243958: Pseudo dice [0.8491] +2024-11-22 08:13:29.244129: Epoch time: 18.46 s +2024-11-22 08:13:30.403643: +2024-11-22 08:13:30.403854: Epoch 3877 +2024-11-22 08:13:30.403970: Current learning rate: 0.00551 +2024-11-22 08:13:49.265347: train_loss -0.7932 +2024-11-22 08:13:49.270894: val_loss -0.7647 +2024-11-22 08:13:49.271023: Pseudo dice [0.8449] +2024-11-22 08:13:49.271117: Epoch time: 18.86 s +2024-11-22 08:13:50.154337: +2024-11-22 08:13:50.154585: Epoch 3878 +2024-11-22 08:13:50.154695: Current learning rate: 0.00551 +2024-11-22 08:14:08.262725: train_loss -0.7871 +2024-11-22 08:14:08.270180: val_loss -0.7634 +2024-11-22 08:14:08.270294: Pseudo dice [0.8579] +2024-11-22 08:14:08.270384: Epoch time: 18.11 s +2024-11-22 08:14:09.242434: +2024-11-22 08:14:09.242651: Epoch 3879 +2024-11-22 08:14:09.242764: Current learning rate: 0.0055 +2024-11-22 08:14:28.510642: train_loss -0.789 +2024-11-22 08:14:28.518816: val_loss -0.7462 +2024-11-22 08:14:28.518951: Pseudo dice [0.8387] +2024-11-22 08:14:28.519037: Epoch time: 19.27 s +2024-11-22 08:14:29.419176: +2024-11-22 08:14:29.419389: Epoch 3880 +2024-11-22 08:14:29.419504: Current learning rate: 0.0055 +2024-11-22 08:14:49.475464: train_loss -0.7886 +2024-11-22 08:14:49.479406: val_loss -0.7782 +2024-11-22 08:14:49.479537: Pseudo dice [0.8585] +2024-11-22 08:14:49.479618: Epoch time: 20.06 s +2024-11-22 08:14:50.953912: +2024-11-22 08:14:50.954123: Epoch 3881 +2024-11-22 08:14:50.954236: Current learning rate: 0.0055 +2024-11-22 08:15:10.032370: train_loss -0.7848 +2024-11-22 08:15:10.034086: val_loss -0.7916 +2024-11-22 08:15:10.034204: Pseudo dice [0.8489] +2024-11-22 08:15:10.034308: Epoch time: 19.08 s +2024-11-22 08:15:11.010931: +2024-11-22 08:15:11.011135: Epoch 3882 +2024-11-22 08:15:11.011245: Current learning rate: 0.0055 +2024-11-22 08:15:31.150503: train_loss -0.7794 +2024-11-22 08:15:31.151918: val_loss -0.7628 +2024-11-22 08:15:31.152021: Pseudo dice [0.8346] +2024-11-22 08:15:31.152110: Epoch time: 20.14 s +2024-11-22 08:15:32.232275: +2024-11-22 08:15:32.232512: Epoch 3883 +2024-11-22 08:15:32.232628: Current learning rate: 0.0055 +2024-11-22 08:15:50.527498: train_loss -0.7844 +2024-11-22 08:15:50.535298: val_loss -0.7908 +2024-11-22 08:15:50.535421: Pseudo dice [0.8614] +2024-11-22 08:15:50.535508: Epoch time: 18.3 s +2024-11-22 08:15:51.425286: +2024-11-22 08:15:51.425498: Epoch 3884 +2024-11-22 08:15:51.425619: Current learning rate: 0.0055 +2024-11-22 08:16:09.950067: train_loss -0.7884 +2024-11-22 08:16:09.951546: val_loss -0.7915 +2024-11-22 08:16:09.951649: Pseudo dice [0.8614] +2024-11-22 08:16:09.951729: Epoch time: 18.53 s +2024-11-22 08:16:10.904711: +2024-11-22 08:16:10.904922: Epoch 3885 +2024-11-22 08:16:10.905045: Current learning rate: 0.0055 +2024-11-22 08:16:29.294717: train_loss -0.7885 +2024-11-22 08:16:29.297032: val_loss -0.7716 +2024-11-22 08:16:29.297132: Pseudo dice [0.854] +2024-11-22 08:16:29.297219: Epoch time: 18.39 s +2024-11-22 08:16:30.162805: +2024-11-22 08:16:30.163004: Epoch 3886 +2024-11-22 08:16:30.163118: Current learning rate: 0.0055 +2024-11-22 08:16:49.369634: train_loss -0.7769 +2024-11-22 08:16:49.372386: val_loss -0.7809 +2024-11-22 08:16:49.372487: Pseudo dice [0.8558] +2024-11-22 08:16:49.372569: Epoch time: 19.21 s +2024-11-22 08:16:50.233240: +2024-11-22 08:16:50.233439: Epoch 3887 +2024-11-22 08:16:50.233548: Current learning rate: 0.00549 +2024-11-22 08:17:09.032616: train_loss -0.781 +2024-11-22 08:17:09.035177: val_loss -0.7852 +2024-11-22 08:17:09.035299: Pseudo dice [0.8596] +2024-11-22 08:17:09.035382: Epoch time: 18.8 s +2024-11-22 08:17:09.952634: +2024-11-22 08:17:09.952845: Epoch 3888 +2024-11-22 08:17:09.952956: Current learning rate: 0.00549 +2024-11-22 08:17:28.330953: train_loss -0.7712 +2024-11-22 08:17:28.343301: val_loss -0.7632 +2024-11-22 08:17:28.343423: Pseudo dice [0.8499] +2024-11-22 08:17:28.343531: Epoch time: 18.38 s +2024-11-22 08:17:29.210214: +2024-11-22 08:17:29.210416: Epoch 3889 +2024-11-22 08:17:29.210526: Current learning rate: 0.00549 +2024-11-22 08:17:48.411806: train_loss -0.7837 +2024-11-22 08:17:48.414385: val_loss -0.7483 +2024-11-22 08:17:48.414565: Pseudo dice [0.8477] +2024-11-22 08:17:48.414660: Epoch time: 19.2 s +2024-11-22 08:17:49.276930: +2024-11-22 08:17:49.277132: Epoch 3890 +2024-11-22 08:17:49.277243: Current learning rate: 0.00549 +2024-11-22 08:18:08.144560: train_loss -0.7678 +2024-11-22 08:18:08.162606: val_loss -0.7276 +2024-11-22 08:18:08.162737: Pseudo dice [0.816] +2024-11-22 08:18:08.162820: Epoch time: 18.87 s +2024-11-22 08:18:09.063937: +2024-11-22 08:18:09.064140: Epoch 3891 +2024-11-22 08:18:09.064259: Current learning rate: 0.00549 +2024-11-22 08:18:27.180480: train_loss -0.7635 +2024-11-22 08:18:27.182255: val_loss -0.7652 +2024-11-22 08:18:27.182342: Pseudo dice [0.8532] +2024-11-22 08:18:27.182418: Epoch time: 18.12 s +2024-11-22 08:18:28.416575: +2024-11-22 08:18:28.416845: Epoch 3892 +2024-11-22 08:18:28.416964: Current learning rate: 0.00549 +2024-11-22 08:18:48.107164: train_loss -0.7814 +2024-11-22 08:18:48.113489: val_loss -0.7616 +2024-11-22 08:18:48.113625: Pseudo dice [0.8529] +2024-11-22 08:18:48.113715: Epoch time: 19.69 s +2024-11-22 08:18:48.996434: +2024-11-22 08:18:48.996675: Epoch 3893 +2024-11-22 08:18:48.996810: Current learning rate: 0.00549 +2024-11-22 08:19:08.336046: train_loss -0.7733 +2024-11-22 08:19:08.338608: val_loss -0.7461 +2024-11-22 08:19:08.338701: Pseudo dice [0.8339] +2024-11-22 08:19:08.338787: Epoch time: 19.34 s +2024-11-22 08:19:09.200751: +2024-11-22 08:19:09.200968: Epoch 3894 +2024-11-22 08:19:09.201092: Current learning rate: 0.00549 +2024-11-22 08:19:28.909116: train_loss -0.7757 +2024-11-22 08:19:28.911798: val_loss -0.7757 +2024-11-22 08:19:28.911895: Pseudo dice [0.846] +2024-11-22 08:19:28.911977: Epoch time: 19.71 s +2024-11-22 08:19:29.773691: +2024-11-22 08:19:29.774147: Epoch 3895 +2024-11-22 08:19:29.774260: Current learning rate: 0.00549 +2024-11-22 08:19:48.872651: train_loss -0.7762 +2024-11-22 08:19:48.878032: val_loss -0.7576 +2024-11-22 08:19:48.878474: Pseudo dice [0.8413] +2024-11-22 08:19:48.878584: Epoch time: 19.1 s +2024-11-22 08:19:49.876476: +2024-11-22 08:19:49.876693: Epoch 3896 +2024-11-22 08:19:49.876803: Current learning rate: 0.00548 +2024-11-22 08:20:08.613078: train_loss -0.7822 +2024-11-22 08:20:08.621021: val_loss -0.7664 +2024-11-22 08:20:08.621176: Pseudo dice [0.842] +2024-11-22 08:20:08.621272: Epoch time: 18.74 s +2024-11-22 08:20:09.586423: +2024-11-22 08:20:09.586632: Epoch 3897 +2024-11-22 08:20:09.586743: Current learning rate: 0.00548 +2024-11-22 08:20:28.619281: train_loss -0.7687 +2024-11-22 08:20:28.626580: val_loss -0.7581 +2024-11-22 08:20:28.626709: Pseudo dice [0.8511] +2024-11-22 08:20:28.626795: Epoch time: 19.03 s +2024-11-22 08:20:29.502877: +2024-11-22 08:20:29.503094: Epoch 3898 +2024-11-22 08:20:29.503209: Current learning rate: 0.00548 +2024-11-22 08:20:49.099547: train_loss -0.7823 +2024-11-22 08:20:49.108118: val_loss -0.7772 +2024-11-22 08:20:49.108304: Pseudo dice [0.8464] +2024-11-22 08:20:49.108387: Epoch time: 19.6 s +2024-11-22 08:20:50.163263: +2024-11-22 08:20:50.163493: Epoch 3899 +2024-11-22 08:20:50.163608: Current learning rate: 0.00548 +2024-11-22 08:21:09.031681: train_loss -0.7914 +2024-11-22 08:21:09.034730: val_loss -0.7546 +2024-11-22 08:21:09.034868: Pseudo dice [0.8544] +2024-11-22 08:21:09.034963: Epoch time: 18.87 s +2024-11-22 08:21:10.167569: +2024-11-22 08:21:10.167775: Epoch 3900 +2024-11-22 08:21:10.167886: Current learning rate: 0.00548 +2024-11-22 08:21:29.076629: train_loss -0.7907 +2024-11-22 08:21:29.081287: val_loss -0.7729 +2024-11-22 08:21:29.081407: Pseudo dice [0.8556] +2024-11-22 08:21:29.081494: Epoch time: 18.91 s +2024-11-22 08:21:29.949444: +2024-11-22 08:21:29.949637: Epoch 3901 +2024-11-22 08:21:29.949752: Current learning rate: 0.00548 +2024-11-22 08:21:48.406489: train_loss -0.7923 +2024-11-22 08:21:48.412673: val_loss -0.7453 +2024-11-22 08:21:48.412819: Pseudo dice [0.8344] +2024-11-22 08:21:48.412905: Epoch time: 18.46 s +2024-11-22 08:21:49.332362: +2024-11-22 08:21:49.332547: Epoch 3902 +2024-11-22 08:21:49.332659: Current learning rate: 0.00548 +2024-11-22 08:22:08.065906: train_loss -0.791 +2024-11-22 08:22:08.075110: val_loss -0.7722 +2024-11-22 08:22:08.075243: Pseudo dice [0.864] +2024-11-22 08:22:08.075323: Epoch time: 18.73 s +2024-11-22 08:22:08.958732: +2024-11-22 08:22:08.958936: Epoch 3903 +2024-11-22 08:22:08.959047: Current learning rate: 0.00548 +2024-11-22 08:22:28.057657: train_loss -0.7947 +2024-11-22 08:22:28.069136: val_loss -0.7853 +2024-11-22 08:22:28.069256: Pseudo dice [0.859] +2024-11-22 08:22:28.069345: Epoch time: 19.1 s +2024-11-22 08:22:29.078533: +2024-11-22 08:22:29.078743: Epoch 3904 +2024-11-22 08:22:29.078861: Current learning rate: 0.00547 +2024-11-22 08:22:48.495987: train_loss -0.7869 +2024-11-22 08:22:48.503996: val_loss -0.7667 +2024-11-22 08:22:48.504140: Pseudo dice [0.8515] +2024-11-22 08:22:48.504225: Epoch time: 19.42 s +2024-11-22 08:22:49.377109: +2024-11-22 08:22:49.377305: Epoch 3905 +2024-11-22 08:22:49.377416: Current learning rate: 0.00547 +2024-11-22 08:23:09.054820: train_loss -0.7765 +2024-11-22 08:23:09.059253: val_loss -0.7583 +2024-11-22 08:23:09.059370: Pseudo dice [0.845] +2024-11-22 08:23:09.059449: Epoch time: 19.68 s +2024-11-22 08:23:10.085382: +2024-11-22 08:23:10.085624: Epoch 3906 +2024-11-22 08:23:10.085740: Current learning rate: 0.00547 +2024-11-22 08:23:28.685228: train_loss -0.7808 +2024-11-22 08:23:28.692758: val_loss -0.7723 +2024-11-22 08:23:28.692901: Pseudo dice [0.8503] +2024-11-22 08:23:28.692999: Epoch time: 18.6 s +2024-11-22 08:23:29.620548: +2024-11-22 08:23:29.620797: Epoch 3907 +2024-11-22 08:23:29.620914: Current learning rate: 0.00547 +2024-11-22 08:23:47.427546: train_loss -0.7825 +2024-11-22 08:23:47.435870: val_loss -0.7865 +2024-11-22 08:23:47.436011: Pseudo dice [0.8509] +2024-11-22 08:23:47.436517: Epoch time: 17.81 s +2024-11-22 08:23:48.459999: +2024-11-22 08:23:48.460212: Epoch 3908 +2024-11-22 08:23:48.460324: Current learning rate: 0.00547 +2024-11-22 08:24:07.811501: train_loss -0.7897 +2024-11-22 08:24:07.844839: val_loss -0.7666 +2024-11-22 08:24:07.844990: Pseudo dice [0.8414] +2024-11-22 08:24:07.845079: Epoch time: 19.35 s +2024-11-22 08:24:08.723176: +2024-11-22 08:24:08.723371: Epoch 3909 +2024-11-22 08:24:08.723480: Current learning rate: 0.00547 +2024-11-22 08:24:28.168827: train_loss -0.7825 +2024-11-22 08:24:28.174777: val_loss -0.7822 +2024-11-22 08:24:28.174884: Pseudo dice [0.8511] +2024-11-22 08:24:28.174960: Epoch time: 19.45 s +2024-11-22 08:24:29.054694: +2024-11-22 08:24:29.054935: Epoch 3910 +2024-11-22 08:24:29.055048: Current learning rate: 0.00547 +2024-11-22 08:24:48.113892: train_loss -0.7845 +2024-11-22 08:24:48.123779: val_loss -0.7736 +2024-11-22 08:24:48.123919: Pseudo dice [0.865] +2024-11-22 08:24:48.124011: Epoch time: 19.06 s +2024-11-22 08:24:48.989759: +2024-11-22 08:24:48.989977: Epoch 3911 +2024-11-22 08:24:48.990100: Current learning rate: 0.00547 +2024-11-22 08:25:07.621576: train_loss -0.7874 +2024-11-22 08:25:07.624721: val_loss -0.7406 +2024-11-22 08:25:07.624814: Pseudo dice [0.8436] +2024-11-22 08:25:07.624894: Epoch time: 18.63 s +2024-11-22 08:25:08.481079: +2024-11-22 08:25:08.481278: Epoch 3912 +2024-11-22 08:25:08.481396: Current learning rate: 0.00546 +2024-11-22 08:25:27.490452: train_loss -0.774 +2024-11-22 08:25:27.496385: val_loss -0.7735 +2024-11-22 08:25:27.496505: Pseudo dice [0.8546] +2024-11-22 08:25:27.496629: Epoch time: 19.01 s +2024-11-22 08:25:28.748857: +2024-11-22 08:25:28.749052: Epoch 3913 +2024-11-22 08:25:28.749175: Current learning rate: 0.00546 +2024-11-22 08:25:47.746644: train_loss -0.777 +2024-11-22 08:25:47.753453: val_loss -0.7795 +2024-11-22 08:25:47.753596: Pseudo dice [0.8597] +2024-11-22 08:25:47.753675: Epoch time: 19.0 s +2024-11-22 08:25:48.613337: +2024-11-22 08:25:48.613553: Epoch 3914 +2024-11-22 08:25:48.613669: Current learning rate: 0.00546 +2024-11-22 08:26:07.833423: train_loss -0.7703 +2024-11-22 08:26:07.838906: val_loss -0.7431 +2024-11-22 08:26:07.839025: Pseudo dice [0.837] +2024-11-22 08:26:07.839117: Epoch time: 19.22 s +2024-11-22 08:26:08.729109: +2024-11-22 08:26:08.729335: Epoch 3915 +2024-11-22 08:26:08.729452: Current learning rate: 0.00546 +2024-11-22 08:26:27.482853: train_loss -0.7516 +2024-11-22 08:26:27.489498: val_loss -0.7236 +2024-11-22 08:26:27.489635: Pseudo dice [0.8272] +2024-11-22 08:26:27.489720: Epoch time: 18.75 s +2024-11-22 08:26:28.410733: +2024-11-22 08:26:28.410958: Epoch 3916 +2024-11-22 08:26:28.411080: Current learning rate: 0.00546 +2024-11-22 08:26:47.270639: train_loss -0.7361 +2024-11-22 08:26:47.273714: val_loss -0.7552 +2024-11-22 08:26:47.273854: Pseudo dice [0.8323] +2024-11-22 08:26:47.273939: Epoch time: 18.86 s +2024-11-22 08:26:48.170844: +2024-11-22 08:26:48.171049: Epoch 3917 +2024-11-22 08:26:48.171171: Current learning rate: 0.00546 +2024-11-22 08:27:07.577145: train_loss -0.767 +2024-11-22 08:27:07.579988: val_loss -0.7522 +2024-11-22 08:27:07.580104: Pseudo dice [0.8476] +2024-11-22 08:27:07.580283: Epoch time: 19.41 s +2024-11-22 08:27:08.448854: +2024-11-22 08:27:08.449081: Epoch 3918 +2024-11-22 08:27:08.449201: Current learning rate: 0.00546 +2024-11-22 08:27:27.993249: train_loss -0.773 +2024-11-22 08:27:28.000354: val_loss -0.7618 +2024-11-22 08:27:28.000497: Pseudo dice [0.856] +2024-11-22 08:27:28.000602: Epoch time: 19.55 s +2024-11-22 08:27:29.061366: +2024-11-22 08:27:29.061568: Epoch 3919 +2024-11-22 08:27:29.061678: Current learning rate: 0.00546 +2024-11-22 08:27:47.080936: train_loss -0.7806 +2024-11-22 08:27:47.085283: val_loss -0.7606 +2024-11-22 08:27:47.085415: Pseudo dice [0.852] +2024-11-22 08:27:47.085496: Epoch time: 18.02 s +2024-11-22 08:27:48.129583: +2024-11-22 08:27:48.129784: Epoch 3920 +2024-11-22 08:27:48.129896: Current learning rate: 0.00546 +2024-11-22 08:28:08.015835: train_loss -0.7598 +2024-11-22 08:28:08.031278: val_loss -0.7674 +2024-11-22 08:28:08.031398: Pseudo dice [0.8547] +2024-11-22 08:28:08.031483: Epoch time: 19.89 s +2024-11-22 08:28:08.898360: +2024-11-22 08:28:08.898556: Epoch 3921 +2024-11-22 08:28:08.898666: Current learning rate: 0.00545 +2024-11-22 08:28:28.190850: train_loss -0.7835 +2024-11-22 08:28:28.194874: val_loss -0.7742 +2024-11-22 08:28:28.195239: Pseudo dice [0.8558] +2024-11-22 08:28:28.195352: Epoch time: 19.29 s +2024-11-22 08:28:29.086524: +2024-11-22 08:28:29.086778: Epoch 3922 +2024-11-22 08:28:29.086901: Current learning rate: 0.00545 +2024-11-22 08:28:48.289243: train_loss -0.7741 +2024-11-22 08:28:48.295162: val_loss -0.7616 +2024-11-22 08:28:48.295286: Pseudo dice [0.8439] +2024-11-22 08:28:48.295375: Epoch time: 19.2 s +2024-11-22 08:28:49.223467: +2024-11-22 08:28:49.223691: Epoch 3923 +2024-11-22 08:28:49.223808: Current learning rate: 0.00545 +2024-11-22 08:29:07.292232: train_loss -0.7881 +2024-11-22 08:29:07.305002: val_loss -0.7763 +2024-11-22 08:29:07.305125: Pseudo dice [0.8477] +2024-11-22 08:29:07.305212: Epoch time: 18.07 s +2024-11-22 08:29:08.579112: +2024-11-22 08:29:08.579354: Epoch 3924 +2024-11-22 08:29:08.579479: Current learning rate: 0.00545 +2024-11-22 08:29:27.493185: train_loss -0.776 +2024-11-22 08:29:27.496266: val_loss -0.7536 +2024-11-22 08:29:27.496395: Pseudo dice [0.841] +2024-11-22 08:29:27.496477: Epoch time: 18.91 s +2024-11-22 08:29:28.571396: +2024-11-22 08:29:28.571594: Epoch 3925 +2024-11-22 08:29:28.571703: Current learning rate: 0.00545 +2024-11-22 08:29:47.369076: train_loss -0.7805 +2024-11-22 08:29:47.375260: val_loss -0.7866 +2024-11-22 08:29:47.375397: Pseudo dice [0.8488] +2024-11-22 08:29:47.375489: Epoch time: 18.8 s +2024-11-22 08:29:48.277026: +2024-11-22 08:29:48.277242: Epoch 3926 +2024-11-22 08:29:48.277359: Current learning rate: 0.00545 +2024-11-22 08:30:06.877624: train_loss -0.7669 +2024-11-22 08:30:06.880472: val_loss -0.7547 +2024-11-22 08:30:06.880592: Pseudo dice [0.8402] +2024-11-22 08:30:06.880670: Epoch time: 18.6 s +2024-11-22 08:30:07.943604: +2024-11-22 08:30:07.943860: Epoch 3927 +2024-11-22 08:30:07.943969: Current learning rate: 0.00545 +2024-11-22 08:30:26.233510: train_loss -0.7778 +2024-11-22 08:30:26.240939: val_loss -0.7419 +2024-11-22 08:30:26.241072: Pseudo dice [0.8499] +2024-11-22 08:30:26.241148: Epoch time: 18.29 s +2024-11-22 08:30:27.243773: +2024-11-22 08:30:27.244024: Epoch 3928 +2024-11-22 08:30:27.244138: Current learning rate: 0.00545 +2024-11-22 08:30:45.759881: train_loss -0.7751 +2024-11-22 08:30:45.766794: val_loss -0.7642 +2024-11-22 08:30:45.766914: Pseudo dice [0.8459] +2024-11-22 08:30:45.766992: Epoch time: 18.52 s +2024-11-22 08:30:46.750828: +2024-11-22 08:30:46.751037: Epoch 3929 +2024-11-22 08:30:46.751150: Current learning rate: 0.00544 +2024-11-22 08:31:05.552253: train_loss -0.7706 +2024-11-22 08:31:05.565495: val_loss -0.7641 +2024-11-22 08:31:05.565624: Pseudo dice [0.8542] +2024-11-22 08:31:05.565714: Epoch time: 18.8 s +2024-11-22 08:31:06.434028: +2024-11-22 08:31:06.434241: Epoch 3930 +2024-11-22 08:31:06.434365: Current learning rate: 0.00544 +2024-11-22 08:31:25.592757: train_loss -0.7808 +2024-11-22 08:31:25.605971: val_loss -0.7803 +2024-11-22 08:31:25.606101: Pseudo dice [0.8537] +2024-11-22 08:31:25.606184: Epoch time: 19.16 s +2024-11-22 08:31:26.719652: +2024-11-22 08:31:26.719872: Epoch 3931 +2024-11-22 08:31:26.719982: Current learning rate: 0.00544 +2024-11-22 08:31:46.045705: train_loss -0.7793 +2024-11-22 08:31:46.052744: val_loss -0.7653 +2024-11-22 08:31:46.052931: Pseudo dice [0.8452] +2024-11-22 08:31:46.053022: Epoch time: 19.33 s +2024-11-22 08:31:46.923873: +2024-11-22 08:31:46.924092: Epoch 3932 +2024-11-22 08:31:46.924208: Current learning rate: 0.00544 +2024-11-22 08:32:04.451749: train_loss -0.7776 +2024-11-22 08:32:04.457750: val_loss -0.7412 +2024-11-22 08:32:04.457883: Pseudo dice [0.8292] +2024-11-22 08:32:04.457988: Epoch time: 17.53 s +2024-11-22 08:32:05.332133: +2024-11-22 08:32:05.332343: Epoch 3933 +2024-11-22 08:32:05.356345: Current learning rate: 0.00544 +2024-11-22 08:32:23.233147: train_loss -0.7791 +2024-11-22 08:32:23.239848: val_loss -0.7809 +2024-11-22 08:32:23.240036: Pseudo dice [0.8568] +2024-11-22 08:32:23.240128: Epoch time: 17.9 s +2024-11-22 08:32:24.238720: +2024-11-22 08:32:24.238916: Epoch 3934 +2024-11-22 08:32:24.239029: Current learning rate: 0.00544 +2024-11-22 08:32:43.805406: train_loss -0.7829 +2024-11-22 08:32:43.810437: val_loss -0.7556 +2024-11-22 08:32:43.810566: Pseudo dice [0.8467] +2024-11-22 08:32:43.810647: Epoch time: 19.57 s +2024-11-22 08:32:45.071217: +2024-11-22 08:32:45.071426: Epoch 3935 +2024-11-22 08:32:45.071541: Current learning rate: 0.00544 +2024-11-22 08:33:05.541893: train_loss -0.784 +2024-11-22 08:33:05.556289: val_loss -0.7812 +2024-11-22 08:33:05.556418: Pseudo dice [0.8562] +2024-11-22 08:33:05.556510: Epoch time: 20.47 s +2024-11-22 08:33:06.430366: +2024-11-22 08:33:06.430603: Epoch 3936 +2024-11-22 08:33:06.430717: Current learning rate: 0.00544 +2024-11-22 08:33:25.258992: train_loss -0.7785 +2024-11-22 08:33:25.262173: val_loss -0.758 +2024-11-22 08:33:25.262282: Pseudo dice [0.8408] +2024-11-22 08:33:25.262424: Epoch time: 18.83 s +2024-11-22 08:33:26.126764: +2024-11-22 08:33:26.126986: Epoch 3937 +2024-11-22 08:33:26.127098: Current learning rate: 0.00543 +2024-11-22 08:33:44.087386: train_loss -0.7766 +2024-11-22 08:33:44.090365: val_loss -0.7628 +2024-11-22 08:33:44.090458: Pseudo dice [0.8516] +2024-11-22 08:33:44.090534: Epoch time: 17.96 s +2024-11-22 08:33:44.950628: +2024-11-22 08:33:44.950840: Epoch 3938 +2024-11-22 08:33:44.950949: Current learning rate: 0.00543 +2024-11-22 08:34:03.286921: train_loss -0.789 +2024-11-22 08:34:03.294600: val_loss -0.7499 +2024-11-22 08:34:03.294723: Pseudo dice [0.8557] +2024-11-22 08:34:03.294805: Epoch time: 18.34 s +2024-11-22 08:34:04.318653: +2024-11-22 08:34:04.318863: Epoch 3939 +2024-11-22 08:34:04.318971: Current learning rate: 0.00543 +2024-11-22 08:34:23.406223: train_loss -0.7802 +2024-11-22 08:34:23.412510: val_loss -0.754 +2024-11-22 08:34:23.412638: Pseudo dice [0.844] +2024-11-22 08:34:23.412727: Epoch time: 19.09 s +2024-11-22 08:34:24.289253: +2024-11-22 08:34:24.289468: Epoch 3940 +2024-11-22 08:34:24.289584: Current learning rate: 0.00543 +2024-11-22 08:34:43.457916: train_loss -0.7811 +2024-11-22 08:34:43.464849: val_loss -0.766 +2024-11-22 08:34:43.464976: Pseudo dice [0.8456] +2024-11-22 08:34:43.465055: Epoch time: 19.17 s +2024-11-22 08:34:44.364941: +2024-11-22 08:34:44.365221: Epoch 3941 +2024-11-22 08:34:44.365336: Current learning rate: 0.00543 +2024-11-22 08:35:02.928430: train_loss -0.7877 +2024-11-22 08:35:02.935213: val_loss -0.7616 +2024-11-22 08:35:02.935353: Pseudo dice [0.855] +2024-11-22 08:35:02.935439: Epoch time: 18.56 s +2024-11-22 08:35:03.837475: +2024-11-22 08:35:03.837690: Epoch 3942 +2024-11-22 08:35:03.837801: Current learning rate: 0.00543 +2024-11-22 08:35:23.033559: train_loss -0.7882 +2024-11-22 08:35:23.036753: val_loss -0.7784 +2024-11-22 08:35:23.036875: Pseudo dice [0.8711] +2024-11-22 08:35:23.036951: Epoch time: 19.2 s +2024-11-22 08:35:23.916419: +2024-11-22 08:35:23.916627: Epoch 3943 +2024-11-22 08:35:23.916743: Current learning rate: 0.00543 +2024-11-22 08:35:42.553366: train_loss -0.7849 +2024-11-22 08:35:42.559528: val_loss -0.78 +2024-11-22 08:35:42.559658: Pseudo dice [0.8589] +2024-11-22 08:35:42.559752: Epoch time: 18.64 s +2024-11-22 08:35:43.554765: +2024-11-22 08:35:43.555038: Epoch 3944 +2024-11-22 08:35:43.555171: Current learning rate: 0.00543 +2024-11-22 08:36:03.118095: train_loss -0.7878 +2024-11-22 08:36:03.120606: val_loss -0.7829 +2024-11-22 08:36:03.120696: Pseudo dice [0.8552] +2024-11-22 08:36:03.120779: Epoch time: 19.56 s +2024-11-22 08:36:03.978831: +2024-11-22 08:36:03.979037: Epoch 3945 +2024-11-22 08:36:03.979153: Current learning rate: 0.00543 +2024-11-22 08:36:23.221713: train_loss -0.7888 +2024-11-22 08:36:23.229257: val_loss -0.7895 +2024-11-22 08:36:23.229370: Pseudo dice [0.8433] +2024-11-22 08:36:23.229455: Epoch time: 19.24 s +2024-11-22 08:36:24.722996: +2024-11-22 08:36:24.723194: Epoch 3946 +2024-11-22 08:36:24.723307: Current learning rate: 0.00542 +2024-11-22 08:36:43.104236: train_loss -0.7904 +2024-11-22 08:36:43.112293: val_loss -0.771 +2024-11-22 08:36:43.112404: Pseudo dice [0.8564] +2024-11-22 08:36:43.112492: Epoch time: 18.38 s +2024-11-22 08:36:44.139242: +2024-11-22 08:36:44.139481: Epoch 3947 +2024-11-22 08:36:44.139616: Current learning rate: 0.00542 +2024-11-22 08:37:03.206363: train_loss -0.7931 +2024-11-22 08:37:03.212430: val_loss -0.7581 +2024-11-22 08:37:03.212824: Pseudo dice [0.8446] +2024-11-22 08:37:03.212924: Epoch time: 19.07 s +2024-11-22 08:37:04.086835: +2024-11-22 08:37:04.087043: Epoch 3948 +2024-11-22 08:37:04.087158: Current learning rate: 0.00542 +2024-11-22 08:37:22.824397: train_loss -0.7965 +2024-11-22 08:37:22.828225: val_loss -0.7811 +2024-11-22 08:37:22.828357: Pseudo dice [0.8486] +2024-11-22 08:37:22.828444: Epoch time: 18.74 s +2024-11-22 08:37:23.837735: +2024-11-22 08:37:23.837956: Epoch 3949 +2024-11-22 08:37:23.838074: Current learning rate: 0.00542 +2024-11-22 08:37:42.696467: train_loss -0.7786 +2024-11-22 08:37:42.703509: val_loss -0.7729 +2024-11-22 08:37:42.703650: Pseudo dice [0.8462] +2024-11-22 08:37:42.703771: Epoch time: 18.86 s +2024-11-22 08:37:43.858331: +2024-11-22 08:37:43.858527: Epoch 3950 +2024-11-22 08:37:43.858641: Current learning rate: 0.00542 +2024-11-22 08:38:03.371972: train_loss -0.7987 +2024-11-22 08:38:03.380602: val_loss -0.7796 +2024-11-22 08:38:03.380727: Pseudo dice [0.835] +2024-11-22 08:38:03.380816: Epoch time: 19.51 s +2024-11-22 08:38:04.324929: +2024-11-22 08:38:04.325124: Epoch 3951 +2024-11-22 08:38:04.325231: Current learning rate: 0.00542 +2024-11-22 08:38:23.913554: train_loss -0.7881 +2024-11-22 08:38:23.920448: val_loss -0.7719 +2024-11-22 08:38:23.920584: Pseudo dice [0.8411] +2024-11-22 08:38:23.920670: Epoch time: 19.59 s +2024-11-22 08:38:24.787310: +2024-11-22 08:38:24.787520: Epoch 3952 +2024-11-22 08:38:24.787631: Current learning rate: 0.00542 +2024-11-22 08:38:44.238470: train_loss -0.7915 +2024-11-22 08:38:44.240553: val_loss -0.7676 +2024-11-22 08:38:44.240653: Pseudo dice [0.8514] +2024-11-22 08:38:44.240735: Epoch time: 19.45 s +2024-11-22 08:38:45.100678: +2024-11-22 08:38:45.100875: Epoch 3953 +2024-11-22 08:38:45.100993: Current learning rate: 0.00542 +2024-11-22 08:39:03.847070: train_loss -0.7836 +2024-11-22 08:39:03.853959: val_loss -0.7892 +2024-11-22 08:39:03.854088: Pseudo dice [0.854] +2024-11-22 08:39:03.854251: Epoch time: 18.75 s +2024-11-22 08:39:04.775842: +2024-11-22 08:39:04.776055: Epoch 3954 +2024-11-22 08:39:04.776175: Current learning rate: 0.00541 +2024-11-22 08:39:23.048687: train_loss -0.7939 +2024-11-22 08:39:23.053900: val_loss -0.7837 +2024-11-22 08:39:23.054049: Pseudo dice [0.8619] +2024-11-22 08:39:23.054151: Epoch time: 18.27 s +2024-11-22 08:39:23.920506: +2024-11-22 08:39:23.920694: Epoch 3955 +2024-11-22 08:39:23.920806: Current learning rate: 0.00541 +2024-11-22 08:39:42.479168: train_loss -0.7916 +2024-11-22 08:39:42.481727: val_loss -0.7954 +2024-11-22 08:39:42.481864: Pseudo dice [0.8656] +2024-11-22 08:39:42.481945: Epoch time: 18.56 s +2024-11-22 08:39:43.781616: +2024-11-22 08:39:43.781848: Epoch 3956 +2024-11-22 08:39:43.781965: Current learning rate: 0.00541 +2024-11-22 08:40:01.765970: train_loss -0.7813 +2024-11-22 08:40:01.767741: val_loss -0.776 +2024-11-22 08:40:01.767831: Pseudo dice [0.8574] +2024-11-22 08:40:01.767909: Epoch time: 17.99 s +2024-11-22 08:40:02.626926: +2024-11-22 08:40:02.627149: Epoch 3957 +2024-11-22 08:40:02.627260: Current learning rate: 0.00541 +2024-11-22 08:40:20.331365: train_loss -0.7935 +2024-11-22 08:40:20.335587: val_loss -0.768 +2024-11-22 08:40:20.335692: Pseudo dice [0.8609] +2024-11-22 08:40:20.335781: Epoch time: 17.71 s +2024-11-22 08:40:21.294653: +2024-11-22 08:40:21.294886: Epoch 3958 +2024-11-22 08:40:21.295006: Current learning rate: 0.00541 +2024-11-22 08:40:39.896748: train_loss -0.7921 +2024-11-22 08:40:39.900100: val_loss -0.7793 +2024-11-22 08:40:39.900771: Pseudo dice [0.8489] +2024-11-22 08:40:39.900853: Epoch time: 18.6 s +2024-11-22 08:40:40.757458: +2024-11-22 08:40:40.757728: Epoch 3959 +2024-11-22 08:40:40.757837: Current learning rate: 0.00541 +2024-11-22 08:40:59.827971: train_loss -0.7894 +2024-11-22 08:40:59.833258: val_loss -0.7716 +2024-11-22 08:40:59.833359: Pseudo dice [0.8522] +2024-11-22 08:40:59.833434: Epoch time: 19.07 s +2024-11-22 08:41:00.797601: +2024-11-22 08:41:00.797817: Epoch 3960 +2024-11-22 08:41:00.797926: Current learning rate: 0.00541 +2024-11-22 08:41:20.306870: train_loss -0.7849 +2024-11-22 08:41:20.316010: val_loss -0.7735 +2024-11-22 08:41:20.316154: Pseudo dice [0.8385] +2024-11-22 08:41:20.316235: Epoch time: 19.51 s +2024-11-22 08:41:21.271444: +2024-11-22 08:41:21.271648: Epoch 3961 +2024-11-22 08:41:21.271765: Current learning rate: 0.00541 +2024-11-22 08:41:40.453136: train_loss -0.7835 +2024-11-22 08:41:40.460447: val_loss -0.7693 +2024-11-22 08:41:40.460570: Pseudo dice [0.8522] +2024-11-22 08:41:40.460661: Epoch time: 19.18 s +2024-11-22 08:41:41.336145: +2024-11-22 08:41:41.336344: Epoch 3962 +2024-11-22 08:41:41.336454: Current learning rate: 0.0054 +2024-11-22 08:41:59.893352: train_loss -0.7878 +2024-11-22 08:41:59.913517: val_loss -0.7403 +2024-11-22 08:41:59.913663: Pseudo dice [0.8528] +2024-11-22 08:41:59.913749: Epoch time: 18.56 s +2024-11-22 08:42:00.807771: +2024-11-22 08:42:00.808023: Epoch 3963 +2024-11-22 08:42:00.808146: Current learning rate: 0.0054 +2024-11-22 08:42:20.040829: train_loss -0.79 +2024-11-22 08:42:20.047567: val_loss -0.7851 +2024-11-22 08:42:20.047701: Pseudo dice [0.8461] +2024-11-22 08:42:20.047782: Epoch time: 19.23 s +2024-11-22 08:42:21.062593: +2024-11-22 08:42:21.062819: Epoch 3964 +2024-11-22 08:42:21.062936: Current learning rate: 0.0054 +2024-11-22 08:42:39.453631: train_loss -0.7955 +2024-11-22 08:42:39.459662: val_loss -0.7816 +2024-11-22 08:42:39.459801: Pseudo dice [0.8618] +2024-11-22 08:42:39.459892: Epoch time: 18.39 s +2024-11-22 08:42:40.326096: +2024-11-22 08:42:40.326279: Epoch 3965 +2024-11-22 08:42:40.326399: Current learning rate: 0.0054 +2024-11-22 08:42:58.429437: train_loss -0.7923 +2024-11-22 08:42:58.432100: val_loss -0.7852 +2024-11-22 08:42:58.432234: Pseudo dice [0.8561] +2024-11-22 08:42:58.432315: Epoch time: 18.1 s +2024-11-22 08:42:59.349148: +2024-11-22 08:42:59.349355: Epoch 3966 +2024-11-22 08:42:59.349470: Current learning rate: 0.0054 +2024-11-22 08:43:18.326825: train_loss -0.7888 +2024-11-22 08:43:18.329052: val_loss -0.7781 +2024-11-22 08:43:18.329144: Pseudo dice [0.8674] +2024-11-22 08:43:18.329238: Epoch time: 18.98 s +2024-11-22 08:43:19.586462: +2024-11-22 08:43:19.586684: Epoch 3967 +2024-11-22 08:43:19.586794: Current learning rate: 0.0054 +2024-11-22 08:43:37.390068: train_loss -0.7861 +2024-11-22 08:43:37.390622: val_loss -0.7531 +2024-11-22 08:43:37.390702: Pseudo dice [0.8452] +2024-11-22 08:43:37.390779: Epoch time: 17.8 s +2024-11-22 08:43:38.248537: +2024-11-22 08:43:38.248808: Epoch 3968 +2024-11-22 08:43:38.248983: Current learning rate: 0.0054 +2024-11-22 08:43:55.913078: train_loss -0.7943 +2024-11-22 08:43:55.913293: val_loss -0.7554 +2024-11-22 08:43:55.913366: Pseudo dice [0.8475] +2024-11-22 08:43:55.913440: Epoch time: 17.67 s +2024-11-22 08:43:56.911271: +2024-11-22 08:43:56.911470: Epoch 3969 +2024-11-22 08:43:56.911577: Current learning rate: 0.0054 +2024-11-22 08:44:16.068707: train_loss -0.7899 +2024-11-22 08:44:16.068916: val_loss -0.7692 +2024-11-22 08:44:16.068989: Pseudo dice [0.8552] +2024-11-22 08:44:16.069068: Epoch time: 19.16 s +2024-11-22 08:44:16.925528: +2024-11-22 08:44:16.925733: Epoch 3970 +2024-11-22 08:44:16.925850: Current learning rate: 0.0054 +2024-11-22 08:44:36.190053: train_loss -0.7861 +2024-11-22 08:44:36.190326: val_loss -0.7417 +2024-11-22 08:44:36.190406: Pseudo dice [0.8544] +2024-11-22 08:44:36.190486: Epoch time: 19.27 s +2024-11-22 08:44:37.040958: +2024-11-22 08:44:37.041176: Epoch 3971 +2024-11-22 08:44:37.041283: Current learning rate: 0.00539 +2024-11-22 08:44:55.096087: train_loss -0.7781 +2024-11-22 08:44:55.096329: val_loss -0.7656 +2024-11-22 08:44:55.096406: Pseudo dice [0.85] +2024-11-22 08:44:55.096486: Epoch time: 18.06 s +2024-11-22 08:44:55.949995: +2024-11-22 08:44:55.950205: Epoch 3972 +2024-11-22 08:44:55.950314: Current learning rate: 0.00539 +2024-11-22 08:45:13.854831: train_loss -0.7913 +2024-11-22 08:45:13.855036: val_loss -0.7607 +2024-11-22 08:45:13.855114: Pseudo dice [0.844] +2024-11-22 08:45:13.855188: Epoch time: 17.91 s +2024-11-22 08:45:14.725681: +2024-11-22 08:45:14.725903: Epoch 3973 +2024-11-22 08:45:14.726011: Current learning rate: 0.00539 +2024-11-22 08:45:34.246105: train_loss -0.7898 +2024-11-22 08:45:34.246524: val_loss -0.7512 +2024-11-22 08:45:34.246614: Pseudo dice [0.8511] +2024-11-22 08:45:34.246688: Epoch time: 19.52 s +2024-11-22 08:45:35.094683: +2024-11-22 08:45:35.094881: Epoch 3974 +2024-11-22 08:45:35.094989: Current learning rate: 0.00539 +2024-11-22 08:45:53.396330: train_loss -0.7943 +2024-11-22 08:45:53.396624: val_loss -0.7491 +2024-11-22 08:45:53.396703: Pseudo dice [0.8462] +2024-11-22 08:45:53.396785: Epoch time: 18.3 s +2024-11-22 08:45:54.245977: +2024-11-22 08:45:54.246166: Epoch 3975 +2024-11-22 08:45:54.246259: Current learning rate: 0.00539 +2024-11-22 08:46:12.869359: train_loss -0.7829 +2024-11-22 08:46:12.869574: val_loss -0.7639 +2024-11-22 08:46:12.869654: Pseudo dice [0.8592] +2024-11-22 08:46:12.869729: Epoch time: 18.62 s +2024-11-22 08:46:13.722130: +2024-11-22 08:46:13.722308: Epoch 3976 +2024-11-22 08:46:13.722417: Current learning rate: 0.00539 +2024-11-22 08:46:32.445570: train_loss -0.771 +2024-11-22 08:46:32.445779: val_loss -0.7805 +2024-11-22 08:46:32.445855: Pseudo dice [0.843] +2024-11-22 08:46:32.445930: Epoch time: 18.72 s +2024-11-22 08:46:33.311114: +2024-11-22 08:46:33.311327: Epoch 3977 +2024-11-22 08:46:33.311436: Current learning rate: 0.00539 +2024-11-22 08:46:51.785698: train_loss -0.7692 +2024-11-22 08:46:51.785919: val_loss -0.7912 +2024-11-22 08:46:51.785998: Pseudo dice [0.8636] +2024-11-22 08:46:51.786084: Epoch time: 18.48 s +2024-11-22 08:46:53.106996: +2024-11-22 08:46:53.107265: Epoch 3978 +2024-11-22 08:46:53.107382: Current learning rate: 0.00539 +2024-11-22 08:47:12.178820: train_loss -0.7851 +2024-11-22 08:47:12.179072: val_loss -0.7601 +2024-11-22 08:47:12.179149: Pseudo dice [0.8491] +2024-11-22 08:47:12.181348: Epoch time: 19.07 s +2024-11-22 08:47:13.087616: +2024-11-22 08:47:13.087824: Epoch 3979 +2024-11-22 08:47:13.087938: Current learning rate: 0.00538 +2024-11-22 08:47:31.782130: train_loss -0.7922 +2024-11-22 08:47:31.782337: val_loss -0.7768 +2024-11-22 08:47:31.782415: Pseudo dice [0.8567] +2024-11-22 08:47:31.782490: Epoch time: 18.7 s +2024-11-22 08:47:32.646515: +2024-11-22 08:47:32.646762: Epoch 3980 +2024-11-22 08:47:32.646879: Current learning rate: 0.00538 +2024-11-22 08:47:51.633742: train_loss -0.7843 +2024-11-22 08:47:51.633954: val_loss -0.7681 +2024-11-22 08:47:51.634028: Pseudo dice [0.8505] +2024-11-22 08:47:51.634107: Epoch time: 18.99 s +2024-11-22 08:47:52.596818: +2024-11-22 08:47:52.597034: Epoch 3981 +2024-11-22 08:47:52.597149: Current learning rate: 0.00538 +2024-11-22 08:48:11.865185: train_loss -0.7752 +2024-11-22 08:48:11.865411: val_loss -0.76 +2024-11-22 08:48:11.865571: Pseudo dice [0.8589] +2024-11-22 08:48:11.865654: Epoch time: 19.27 s +2024-11-22 08:48:12.732765: +2024-11-22 08:48:12.732982: Epoch 3982 +2024-11-22 08:48:12.733095: Current learning rate: 0.00538 +2024-11-22 08:48:31.100732: train_loss -0.7846 +2024-11-22 08:48:31.100966: val_loss -0.7741 +2024-11-22 08:48:31.101042: Pseudo dice [0.8494] +2024-11-22 08:48:31.101125: Epoch time: 18.37 s +2024-11-22 08:48:31.957309: +2024-11-22 08:48:31.957506: Epoch 3983 +2024-11-22 08:48:31.957620: Current learning rate: 0.00538 +2024-11-22 08:48:50.692457: train_loss -0.7716 +2024-11-22 08:48:50.692667: val_loss -0.7284 +2024-11-22 08:48:50.692743: Pseudo dice [0.8369] +2024-11-22 08:48:50.692817: Epoch time: 18.74 s +2024-11-22 08:48:51.551193: +2024-11-22 08:48:51.552025: Epoch 3984 +2024-11-22 08:48:51.552140: Current learning rate: 0.00538 +2024-11-22 08:49:10.191045: train_loss -0.7562 +2024-11-22 08:49:10.191255: val_loss -0.7374 +2024-11-22 08:49:10.191353: Pseudo dice [0.8443] +2024-11-22 08:49:10.191427: Epoch time: 18.64 s +2024-11-22 08:49:11.051088: +2024-11-22 08:49:11.051289: Epoch 3985 +2024-11-22 08:49:11.051396: Current learning rate: 0.00538 +2024-11-22 08:49:29.230905: train_loss -0.7789 +2024-11-22 08:49:29.231123: val_loss -0.7549 +2024-11-22 08:49:29.231200: Pseudo dice [0.8281] +2024-11-22 08:49:29.231275: Epoch time: 18.18 s +2024-11-22 08:49:30.093067: +2024-11-22 08:49:30.093274: Epoch 3986 +2024-11-22 08:49:30.093383: Current learning rate: 0.00538 +2024-11-22 08:49:48.392159: train_loss -0.788 +2024-11-22 08:49:48.392397: val_loss -0.766 +2024-11-22 08:49:48.392473: Pseudo dice [0.8547] +2024-11-22 08:49:48.392555: Epoch time: 18.3 s +2024-11-22 08:49:49.252287: +2024-11-22 08:49:49.252494: Epoch 3987 +2024-11-22 08:49:49.252605: Current learning rate: 0.00537 +2024-11-22 08:50:07.059270: train_loss -0.7899 +2024-11-22 08:50:07.059471: val_loss -0.7504 +2024-11-22 08:50:07.059545: Pseudo dice [0.844] +2024-11-22 08:50:07.059616: Epoch time: 17.81 s +2024-11-22 08:50:07.919292: +2024-11-22 08:50:07.919489: Epoch 3988 +2024-11-22 08:50:07.919598: Current learning rate: 0.00537 +2024-11-22 08:50:25.721283: train_loss -0.793 +2024-11-22 08:50:25.721488: val_loss -0.753 +2024-11-22 08:50:25.721564: Pseudo dice [0.8541] +2024-11-22 08:50:25.721641: Epoch time: 17.8 s +2024-11-22 08:50:27.019225: +2024-11-22 08:50:27.019421: Epoch 3989 +2024-11-22 08:50:27.019533: Current learning rate: 0.00537 +2024-11-22 08:50:45.620231: train_loss -0.785 +2024-11-22 08:50:45.620475: val_loss -0.7594 +2024-11-22 08:50:45.620553: Pseudo dice [0.8479] +2024-11-22 08:50:45.620635: Epoch time: 18.6 s +2024-11-22 08:50:46.653063: +2024-11-22 08:50:46.653259: Epoch 3990 +2024-11-22 08:50:46.653368: Current learning rate: 0.00537 +2024-11-22 08:51:05.758974: train_loss -0.7742 +2024-11-22 08:51:05.759206: val_loss -0.7646 +2024-11-22 08:51:05.759284: Pseudo dice [0.8459] +2024-11-22 08:51:05.759357: Epoch time: 19.11 s +2024-11-22 08:51:06.607408: +2024-11-22 08:51:06.607629: Epoch 3991 +2024-11-22 08:51:06.607742: Current learning rate: 0.00537 +2024-11-22 08:51:24.280502: train_loss -0.792 +2024-11-22 08:51:24.280710: val_loss -0.7565 +2024-11-22 08:51:24.280784: Pseudo dice [0.861] +2024-11-22 08:51:24.280856: Epoch time: 17.67 s +2024-11-22 08:51:25.156729: +2024-11-22 08:51:25.156942: Epoch 3992 +2024-11-22 08:51:25.157050: Current learning rate: 0.00537 +2024-11-22 08:51:44.313660: train_loss -0.7856 +2024-11-22 08:51:44.313869: val_loss -0.7669 +2024-11-22 08:51:44.313946: Pseudo dice [0.8616] +2024-11-22 08:51:44.314083: Epoch time: 19.16 s +2024-11-22 08:51:45.176969: +2024-11-22 08:51:45.177193: Epoch 3993 +2024-11-22 08:51:45.177301: Current learning rate: 0.00537 +2024-11-22 08:52:03.327757: train_loss -0.7885 +2024-11-22 08:52:03.328043: val_loss -0.7711 +2024-11-22 08:52:03.328122: Pseudo dice [0.8554] +2024-11-22 08:52:03.328205: Epoch time: 18.15 s +2024-11-22 08:52:04.224184: +2024-11-22 08:52:04.224380: Epoch 3994 +2024-11-22 08:52:04.224489: Current learning rate: 0.00537 +2024-11-22 08:52:21.625652: train_loss -0.7869 +2024-11-22 08:52:21.625870: val_loss -0.7664 +2024-11-22 08:52:21.625946: Pseudo dice [0.8639] +2024-11-22 08:52:21.626022: Epoch time: 17.4 s +2024-11-22 08:52:22.493981: +2024-11-22 08:52:22.494195: Epoch 3995 +2024-11-22 08:52:22.494306: Current learning rate: 0.00536 +2024-11-22 08:52:41.213516: train_loss -0.7869 +2024-11-22 08:52:41.213751: val_loss -0.7635 +2024-11-22 08:52:41.213825: Pseudo dice [0.8476] +2024-11-22 08:52:41.213900: Epoch time: 18.72 s +2024-11-22 08:52:42.080018: +2024-11-22 08:52:42.080227: Epoch 3996 +2024-11-22 08:52:42.080338: Current learning rate: 0.00536 +2024-11-22 08:53:00.055648: train_loss -0.7987 +2024-11-22 08:53:00.055863: val_loss -0.7497 +2024-11-22 08:53:00.055940: Pseudo dice [0.8344] +2024-11-22 08:53:00.056652: Epoch time: 17.98 s +2024-11-22 08:53:00.909162: +2024-11-22 08:53:00.909377: Epoch 3997 +2024-11-22 08:53:00.909489: Current learning rate: 0.00536 +2024-11-22 08:53:18.576360: train_loss -0.7965 +2024-11-22 08:53:18.576599: val_loss -0.7565 +2024-11-22 08:53:18.576678: Pseudo dice [0.8597] +2024-11-22 08:53:18.576759: Epoch time: 17.67 s +2024-11-22 08:53:19.444180: +2024-11-22 08:53:19.444396: Epoch 3998 +2024-11-22 08:53:19.444521: Current learning rate: 0.00536 +2024-11-22 08:53:36.797019: train_loss -0.7931 +2024-11-22 08:53:36.797241: val_loss -0.7612 +2024-11-22 08:53:36.797318: Pseudo dice [0.8541] +2024-11-22 08:53:36.797394: Epoch time: 17.35 s +2024-11-22 08:53:37.654803: +2024-11-22 08:53:37.655006: Epoch 3999 +2024-11-22 08:53:37.655116: Current learning rate: 0.00536 +2024-11-22 08:53:56.130635: train_loss -0.8024 +2024-11-22 08:53:56.131042: val_loss -0.7755 +2024-11-22 08:53:56.131136: Pseudo dice [0.856] +2024-11-22 08:53:56.131215: Epoch time: 18.48 s +2024-11-22 08:53:57.668370: +2024-11-22 08:53:57.668555: Epoch 4000 +2024-11-22 08:53:57.668662: Current learning rate: 0.00536 +2024-11-22 08:54:16.056545: train_loss -0.782 +2024-11-22 08:54:16.056797: val_loss -0.7376 +2024-11-22 08:54:16.056873: Pseudo dice [0.8451] +2024-11-22 08:54:16.062151: Epoch time: 18.39 s +2024-11-22 08:54:17.006346: +2024-11-22 08:54:17.006565: Epoch 4001 +2024-11-22 08:54:17.006676: Current learning rate: 0.00536 +2024-11-22 08:54:35.803417: train_loss -0.7847 +2024-11-22 08:54:35.803637: val_loss -0.7576 +2024-11-22 08:54:35.803717: Pseudo dice [0.8523] +2024-11-22 08:54:35.803793: Epoch time: 18.8 s +2024-11-22 08:54:36.774442: +2024-11-22 08:54:36.774672: Epoch 4002 +2024-11-22 08:54:36.774781: Current learning rate: 0.00536 +2024-11-22 08:54:55.400766: train_loss -0.7904 +2024-11-22 08:54:55.400975: val_loss -0.7652 +2024-11-22 08:54:55.401051: Pseudo dice [0.8562] +2024-11-22 08:54:55.401129: Epoch time: 18.63 s +2024-11-22 08:54:56.264901: +2024-11-22 08:54:56.265106: Epoch 4003 +2024-11-22 08:54:56.265219: Current learning rate: 0.00536 +2024-11-22 08:55:15.309077: train_loss -0.7785 +2024-11-22 08:55:15.309300: val_loss -0.7342 +2024-11-22 08:55:15.309377: Pseudo dice [0.8539] +2024-11-22 08:55:15.311677: Epoch time: 19.04 s +2024-11-22 08:55:16.444790: +2024-11-22 08:55:16.445010: Epoch 4004 +2024-11-22 08:55:16.445130: Current learning rate: 0.00535 +2024-11-22 08:55:34.464972: train_loss -0.7795 +2024-11-22 08:55:34.465219: val_loss -0.7604 +2024-11-22 08:55:34.465299: Pseudo dice [0.8602] +2024-11-22 08:55:34.465384: Epoch time: 18.02 s +2024-11-22 08:55:35.337493: +2024-11-22 08:55:35.337708: Epoch 4005 +2024-11-22 08:55:35.337823: Current learning rate: 0.00535 +2024-11-22 08:55:52.819609: train_loss -0.7806 +2024-11-22 08:55:52.819818: val_loss -0.7643 +2024-11-22 08:55:52.819891: Pseudo dice [0.8504] +2024-11-22 08:55:52.819964: Epoch time: 17.48 s +2024-11-22 08:55:53.680529: +2024-11-22 08:55:53.680765: Epoch 4006 +2024-11-22 08:55:53.680873: Current learning rate: 0.00535 +2024-11-22 08:56:12.371138: train_loss -0.7831 +2024-11-22 08:56:12.371355: val_loss -0.7571 +2024-11-22 08:56:12.371433: Pseudo dice [0.843] +2024-11-22 08:56:12.371504: Epoch time: 18.69 s +2024-11-22 08:56:13.262990: +2024-11-22 08:56:13.263215: Epoch 4007 +2024-11-22 08:56:13.263322: Current learning rate: 0.00535 +2024-11-22 08:56:31.277901: train_loss -0.7883 +2024-11-22 08:56:31.278187: val_loss -0.7615 +2024-11-22 08:56:31.278270: Pseudo dice [0.8407] +2024-11-22 08:56:31.278347: Epoch time: 18.02 s +2024-11-22 08:56:32.247996: +2024-11-22 08:56:32.248174: Epoch 4008 +2024-11-22 08:56:32.248284: Current learning rate: 0.00535 +2024-11-22 08:56:50.961316: train_loss -0.7857 +2024-11-22 08:56:50.966725: val_loss -0.7666 +2024-11-22 08:56:50.966906: Pseudo dice [0.8466] +2024-11-22 08:56:50.967001: Epoch time: 18.71 s +2024-11-22 08:56:52.004453: +2024-11-22 08:56:52.004661: Epoch 4009 +2024-11-22 08:56:52.004775: Current learning rate: 0.00535 +2024-11-22 08:57:10.025769: train_loss -0.7854 +2024-11-22 08:57:10.026587: val_loss -0.7764 +2024-11-22 08:57:10.026704: Pseudo dice [0.8654] +2024-11-22 08:57:10.026782: Epoch time: 18.02 s +2024-11-22 08:57:10.883780: +2024-11-22 08:57:10.884211: Epoch 4010 +2024-11-22 08:57:10.884346: Current learning rate: 0.00535 +2024-11-22 08:57:29.627449: train_loss -0.7953 +2024-11-22 08:57:29.627711: val_loss -0.7698 +2024-11-22 08:57:29.627784: Pseudo dice [0.8559] +2024-11-22 08:57:29.627857: Epoch time: 18.74 s +2024-11-22 08:57:30.962283: +2024-11-22 08:57:30.962489: Epoch 4011 +2024-11-22 08:57:30.962601: Current learning rate: 0.00535 +2024-11-22 08:57:48.721944: train_loss -0.7932 +2024-11-22 08:57:48.722199: val_loss -0.7731 +2024-11-22 08:57:48.722276: Pseudo dice [0.8493] +2024-11-22 08:57:48.722358: Epoch time: 17.76 s +2024-11-22 08:57:49.583683: +2024-11-22 08:57:49.583879: Epoch 4012 +2024-11-22 08:57:49.583990: Current learning rate: 0.00534 +2024-11-22 08:58:07.629074: train_loss -0.7848 +2024-11-22 08:58:07.629294: val_loss -0.7832 +2024-11-22 08:58:07.629370: Pseudo dice [0.8469] +2024-11-22 08:58:07.629457: Epoch time: 18.05 s +2024-11-22 08:58:08.491500: +2024-11-22 08:58:08.491705: Epoch 4013 +2024-11-22 08:58:08.491815: Current learning rate: 0.00534 +2024-11-22 08:58:27.141171: train_loss -0.7818 +2024-11-22 08:58:27.141383: val_loss -0.7799 +2024-11-22 08:58:27.141461: Pseudo dice [0.8499] +2024-11-22 08:58:27.141533: Epoch time: 18.65 s +2024-11-22 08:58:28.004175: +2024-11-22 08:58:28.004378: Epoch 4014 +2024-11-22 08:58:28.004492: Current learning rate: 0.00534 +2024-11-22 08:58:46.013994: train_loss -0.7831 +2024-11-22 08:58:46.016420: val_loss -0.7859 +2024-11-22 08:58:46.016516: Pseudo dice [0.8607] +2024-11-22 08:58:46.016598: Epoch time: 18.01 s +2024-11-22 08:58:46.916125: +2024-11-22 08:58:46.916343: Epoch 4015 +2024-11-22 08:58:46.916453: Current learning rate: 0.00534 +2024-11-22 08:59:05.525335: train_loss -0.7759 +2024-11-22 08:59:05.525644: val_loss -0.7797 +2024-11-22 08:59:05.525725: Pseudo dice [0.861] +2024-11-22 08:59:05.525807: Epoch time: 18.61 s +2024-11-22 08:59:06.411278: +2024-11-22 08:59:06.411485: Epoch 4016 +2024-11-22 08:59:06.411596: Current learning rate: 0.00534 +2024-11-22 08:59:24.882462: train_loss -0.7801 +2024-11-22 08:59:24.882678: val_loss -0.7736 +2024-11-22 08:59:24.882757: Pseudo dice [0.8482] +2024-11-22 08:59:24.882835: Epoch time: 18.47 s +2024-11-22 08:59:25.740049: +2024-11-22 08:59:25.740271: Epoch 4017 +2024-11-22 08:59:25.740383: Current learning rate: 0.00534 +2024-11-22 08:59:44.769462: train_loss -0.7771 +2024-11-22 08:59:44.769675: val_loss -0.7543 +2024-11-22 08:59:44.769749: Pseudo dice [0.8457] +2024-11-22 08:59:44.769824: Epoch time: 19.03 s +2024-11-22 08:59:45.630952: +2024-11-22 08:59:45.631138: Epoch 4018 +2024-11-22 08:59:45.631250: Current learning rate: 0.00534 +2024-11-22 09:00:03.545293: train_loss -0.7879 +2024-11-22 09:00:03.545516: val_loss -0.7936 +2024-11-22 09:00:03.545589: Pseudo dice [0.8553] +2024-11-22 09:00:03.545664: Epoch time: 17.92 s +2024-11-22 09:00:04.450222: +2024-11-22 09:00:04.450430: Epoch 4019 +2024-11-22 09:00:04.450547: Current learning rate: 0.00534 +2024-11-22 09:00:22.695009: train_loss -0.7882 +2024-11-22 09:00:22.695328: val_loss -0.7312 +2024-11-22 09:00:22.695407: Pseudo dice [0.8452] +2024-11-22 09:00:22.695483: Epoch time: 18.25 s +2024-11-22 09:00:23.561957: +2024-11-22 09:00:23.562211: Epoch 4020 +2024-11-22 09:00:23.562325: Current learning rate: 0.00533 +2024-11-22 09:00:41.670342: train_loss -0.7935 +2024-11-22 09:00:41.670551: val_loss -0.764 +2024-11-22 09:00:41.670624: Pseudo dice [0.8483] +2024-11-22 09:00:41.670697: Epoch time: 18.11 s +2024-11-22 09:00:42.523957: +2024-11-22 09:00:42.524152: Epoch 4021 +2024-11-22 09:00:42.524264: Current learning rate: 0.00533 +2024-11-22 09:01:00.946496: train_loss -0.7946 +2024-11-22 09:01:00.946771: val_loss -0.7751 +2024-11-22 09:01:00.946849: Pseudo dice [0.8627] +2024-11-22 09:01:00.946927: Epoch time: 18.42 s +2024-11-22 09:01:02.203806: +2024-11-22 09:01:02.204010: Epoch 4022 +2024-11-22 09:01:02.219292: Current learning rate: 0.00533 +2024-11-22 09:01:20.647188: train_loss -0.7918 +2024-11-22 09:01:20.649629: val_loss -0.7812 +2024-11-22 09:01:20.649714: Pseudo dice [0.8609] +2024-11-22 09:01:20.649795: Epoch time: 18.44 s +2024-11-22 09:01:21.614267: +2024-11-22 09:01:21.614478: Epoch 4023 +2024-11-22 09:01:21.614589: Current learning rate: 0.00533 +2024-11-22 09:01:39.820886: train_loss -0.7947 +2024-11-22 09:01:39.821110: val_loss -0.7762 +2024-11-22 09:01:39.821185: Pseudo dice [0.8472] +2024-11-22 09:01:39.821258: Epoch time: 18.21 s +2024-11-22 09:01:40.799443: +2024-11-22 09:01:40.799654: Epoch 4024 +2024-11-22 09:01:40.799763: Current learning rate: 0.00533 +2024-11-22 09:02:00.234999: train_loss -0.7797 +2024-11-22 09:02:00.235217: val_loss -0.7495 +2024-11-22 09:02:00.235304: Pseudo dice [0.8456] +2024-11-22 09:02:00.235438: Epoch time: 19.44 s +2024-11-22 09:02:01.201864: +2024-11-22 09:02:01.202085: Epoch 4025 +2024-11-22 09:02:01.202198: Current learning rate: 0.00533 +2024-11-22 09:02:19.563206: train_loss -0.7831 +2024-11-22 09:02:19.563553: val_loss -0.7611 +2024-11-22 09:02:19.563635: Pseudo dice [0.8499] +2024-11-22 09:02:19.563710: Epoch time: 18.36 s +2024-11-22 09:02:20.524971: +2024-11-22 09:02:20.525176: Epoch 4026 +2024-11-22 09:02:20.525285: Current learning rate: 0.00533 +2024-11-22 09:02:39.376286: train_loss -0.7833 +2024-11-22 09:02:39.376528: val_loss -0.7718 +2024-11-22 09:02:39.376604: Pseudo dice [0.8365] +2024-11-22 09:02:39.376683: Epoch time: 18.85 s +2024-11-22 09:02:40.268711: +2024-11-22 09:02:40.268940: Epoch 4027 +2024-11-22 09:02:40.269055: Current learning rate: 0.00533 +2024-11-22 09:02:59.158690: train_loss -0.7972 +2024-11-22 09:02:59.158896: val_loss -0.765 +2024-11-22 09:02:59.158969: Pseudo dice [0.8571] +2024-11-22 09:02:59.159040: Epoch time: 18.89 s +2024-11-22 09:03:00.018090: +2024-11-22 09:03:00.018297: Epoch 4028 +2024-11-22 09:03:00.018411: Current learning rate: 0.00533 +2024-11-22 09:03:19.031714: train_loss -0.781 +2024-11-22 09:03:19.031932: val_loss -0.7857 +2024-11-22 09:03:19.032010: Pseudo dice [0.8458] +2024-11-22 09:03:19.032091: Epoch time: 19.01 s +2024-11-22 09:03:19.933356: +2024-11-22 09:03:19.933594: Epoch 4029 +2024-11-22 09:03:19.933706: Current learning rate: 0.00532 +2024-11-22 09:03:38.249708: train_loss -0.7883 +2024-11-22 09:03:38.249930: val_loss -0.7877 +2024-11-22 09:03:38.250011: Pseudo dice [0.8451] +2024-11-22 09:03:38.250099: Epoch time: 18.32 s +2024-11-22 09:03:39.111775: +2024-11-22 09:03:39.112014: Epoch 4030 +2024-11-22 09:03:39.112128: Current learning rate: 0.00532 +2024-11-22 09:03:58.597571: train_loss -0.7797 +2024-11-22 09:03:58.597811: val_loss -0.7716 +2024-11-22 09:03:58.597888: Pseudo dice [0.852] +2024-11-22 09:03:58.597971: Epoch time: 19.49 s +2024-11-22 09:03:59.460592: +2024-11-22 09:03:59.460801: Epoch 4031 +2024-11-22 09:03:59.460912: Current learning rate: 0.00532 +2024-11-22 09:04:18.593818: train_loss -0.7749 +2024-11-22 09:04:18.594023: val_loss -0.7641 +2024-11-22 09:04:18.594102: Pseudo dice [0.8524] +2024-11-22 09:04:18.594174: Epoch time: 19.13 s +2024-11-22 09:04:19.453564: +2024-11-22 09:04:19.453766: Epoch 4032 +2024-11-22 09:04:19.453880: Current learning rate: 0.00532 +2024-11-22 09:04:37.596990: train_loss -0.7777 +2024-11-22 09:04:37.597206: val_loss -0.7555 +2024-11-22 09:04:37.597286: Pseudo dice [0.8417] +2024-11-22 09:04:37.597360: Epoch time: 18.14 s +2024-11-22 09:04:38.848405: +2024-11-22 09:04:38.848616: Epoch 4033 +2024-11-22 09:04:38.848730: Current learning rate: 0.00532 +2024-11-22 09:04:56.875365: train_loss -0.7847 +2024-11-22 09:04:56.875609: val_loss -0.7643 +2024-11-22 09:04:56.875687: Pseudo dice [0.8604] +2024-11-22 09:04:56.875765: Epoch time: 18.03 s +2024-11-22 09:04:57.739985: +2024-11-22 09:04:57.740189: Epoch 4034 +2024-11-22 09:04:57.740299: Current learning rate: 0.00532 +2024-11-22 09:05:15.848356: train_loss -0.7814 +2024-11-22 09:05:15.848645: val_loss -0.7385 +2024-11-22 09:05:15.848724: Pseudo dice [0.8449] +2024-11-22 09:05:15.872581: Epoch time: 18.11 s +2024-11-22 09:05:16.742111: +2024-11-22 09:05:16.742322: Epoch 4035 +2024-11-22 09:05:16.742431: Current learning rate: 0.00532 +2024-11-22 09:05:34.365036: train_loss -0.7789 +2024-11-22 09:05:34.365322: val_loss -0.7585 +2024-11-22 09:05:34.365401: Pseudo dice [0.8554] +2024-11-22 09:05:34.365477: Epoch time: 17.62 s +2024-11-22 09:05:35.257807: +2024-11-22 09:05:35.257998: Epoch 4036 +2024-11-22 09:05:35.258116: Current learning rate: 0.00532 +2024-11-22 09:05:54.331705: train_loss -0.7772 +2024-11-22 09:05:54.331913: val_loss -0.7649 +2024-11-22 09:05:54.332047: Pseudo dice [0.854] +2024-11-22 09:05:54.332129: Epoch time: 19.07 s +2024-11-22 09:05:55.204804: +2024-11-22 09:05:55.205027: Epoch 4037 +2024-11-22 09:05:55.205149: Current learning rate: 0.00531 +2024-11-22 09:06:13.784862: train_loss -0.7711 +2024-11-22 09:06:13.785109: val_loss -0.7668 +2024-11-22 09:06:13.785185: Pseudo dice [0.8707] +2024-11-22 09:06:13.785262: Epoch time: 18.58 s +2024-11-22 09:06:14.651361: +2024-11-22 09:06:14.651558: Epoch 4038 +2024-11-22 09:06:14.651669: Current learning rate: 0.00531 +2024-11-22 09:06:32.823702: train_loss -0.7843 +2024-11-22 09:06:32.823918: val_loss -0.7601 +2024-11-22 09:06:32.823992: Pseudo dice [0.8469] +2024-11-22 09:06:32.824073: Epoch time: 18.17 s +2024-11-22 09:06:33.777930: +2024-11-22 09:06:33.778146: Epoch 4039 +2024-11-22 09:06:33.778258: Current learning rate: 0.00531 +2024-11-22 09:06:52.834634: train_loss -0.7733 +2024-11-22 09:06:52.834843: val_loss -0.7481 +2024-11-22 09:06:52.834916: Pseudo dice [0.8466] +2024-11-22 09:06:52.834991: Epoch time: 19.06 s +2024-11-22 09:06:53.719994: +2024-11-22 09:06:53.720224: Epoch 4040 +2024-11-22 09:06:53.720344: Current learning rate: 0.00531 +2024-11-22 09:07:11.791879: train_loss -0.7792 +2024-11-22 09:07:11.792111: val_loss -0.7721 +2024-11-22 09:07:11.792189: Pseudo dice [0.8442] +2024-11-22 09:07:11.792267: Epoch time: 18.07 s +2024-11-22 09:07:12.873296: +2024-11-22 09:07:12.873519: Epoch 4041 +2024-11-22 09:07:12.873632: Current learning rate: 0.00531 +2024-11-22 09:07:31.796535: train_loss -0.7759 +2024-11-22 09:07:31.796833: val_loss -0.7421 +2024-11-22 09:07:31.796915: Pseudo dice [0.8426] +2024-11-22 09:07:31.796993: Epoch time: 18.92 s +2024-11-22 09:07:32.664403: +2024-11-22 09:07:32.664598: Epoch 4042 +2024-11-22 09:07:32.664713: Current learning rate: 0.00531 +2024-11-22 09:07:50.852528: train_loss -0.788 +2024-11-22 09:07:50.852739: val_loss -0.7427 +2024-11-22 09:07:50.852811: Pseudo dice [0.8453] +2024-11-22 09:07:50.852885: Epoch time: 18.19 s +2024-11-22 09:07:51.713931: +2024-11-22 09:07:51.714144: Epoch 4043 +2024-11-22 09:07:51.714263: Current learning rate: 0.00531 +2024-11-22 09:08:09.729892: train_loss -0.792 +2024-11-22 09:08:09.730119: val_loss -0.763 +2024-11-22 09:08:09.730193: Pseudo dice [0.8491] +2024-11-22 09:08:09.730267: Epoch time: 18.02 s +2024-11-22 09:08:11.192324: +2024-11-22 09:08:11.192527: Epoch 4044 +2024-11-22 09:08:11.192637: Current learning rate: 0.00531 +2024-11-22 09:08:29.460130: train_loss -0.7882 +2024-11-22 09:08:29.460357: val_loss -0.7761 +2024-11-22 09:08:29.460432: Pseudo dice [0.8538] +2024-11-22 09:08:29.460517: Epoch time: 18.27 s +2024-11-22 09:08:30.319142: +2024-11-22 09:08:30.319342: Epoch 4045 +2024-11-22 09:08:30.319451: Current learning rate: 0.0053 +2024-11-22 09:08:49.456011: train_loss -0.7891 +2024-11-22 09:08:49.456250: val_loss -0.7849 +2024-11-22 09:08:49.456397: Pseudo dice [0.8513] +2024-11-22 09:08:49.456476: Epoch time: 19.14 s +2024-11-22 09:08:50.317321: +2024-11-22 09:08:50.317545: Epoch 4046 +2024-11-22 09:08:50.317660: Current learning rate: 0.0053 +2024-11-22 09:09:09.871886: train_loss -0.7867 +2024-11-22 09:09:09.872100: val_loss -0.7673 +2024-11-22 09:09:09.872174: Pseudo dice [0.8476] +2024-11-22 09:09:09.872247: Epoch time: 19.56 s +2024-11-22 09:09:10.748387: +2024-11-22 09:09:10.748607: Epoch 4047 +2024-11-22 09:09:10.748714: Current learning rate: 0.0053 +2024-11-22 09:09:29.838215: train_loss -0.7952 +2024-11-22 09:09:29.838413: val_loss -0.7631 +2024-11-22 09:09:29.838487: Pseudo dice [0.8612] +2024-11-22 09:09:29.838562: Epoch time: 19.09 s +2024-11-22 09:09:30.680136: +2024-11-22 09:09:30.680370: Epoch 4048 +2024-11-22 09:09:30.680480: Current learning rate: 0.0053 +2024-11-22 09:09:49.039801: train_loss -0.7921 +2024-11-22 09:09:49.040033: val_loss -0.7788 +2024-11-22 09:09:49.040114: Pseudo dice [0.8598] +2024-11-22 09:09:49.040197: Epoch time: 18.36 s +2024-11-22 09:09:49.956598: +2024-11-22 09:09:49.956807: Epoch 4049 +2024-11-22 09:09:49.956921: Current learning rate: 0.0053 +2024-11-22 09:10:08.116734: train_loss -0.7933 +2024-11-22 09:10:08.116940: val_loss -0.7616 +2024-11-22 09:10:08.117013: Pseudo dice [0.8313] +2024-11-22 09:10:08.117092: Epoch time: 18.16 s +2024-11-22 09:10:09.255884: +2024-11-22 09:10:09.256094: Epoch 4050 +2024-11-22 09:10:09.256205: Current learning rate: 0.0053 +2024-11-22 09:10:27.462694: train_loss -0.7871 +2024-11-22 09:10:27.462893: val_loss -0.7451 +2024-11-22 09:10:27.462967: Pseudo dice [0.8417] +2024-11-22 09:10:27.471255: Epoch time: 18.21 s +2024-11-22 09:10:28.330148: +2024-11-22 09:10:28.330333: Epoch 4051 +2024-11-22 09:10:28.330443: Current learning rate: 0.0053 +2024-11-22 09:10:46.818425: train_loss -0.7758 +2024-11-22 09:10:46.818629: val_loss -0.7725 +2024-11-22 09:10:46.818705: Pseudo dice [0.8473] +2024-11-22 09:10:46.818779: Epoch time: 18.49 s +2024-11-22 09:10:47.675608: +2024-11-22 09:10:47.675787: Epoch 4052 +2024-11-22 09:10:47.675898: Current learning rate: 0.0053 +2024-11-22 09:11:06.206273: train_loss -0.784 +2024-11-22 09:11:06.206503: val_loss -0.7667 +2024-11-22 09:11:06.206577: Pseudo dice [0.8535] +2024-11-22 09:11:06.206658: Epoch time: 18.53 s +2024-11-22 09:11:07.072105: +2024-11-22 09:11:07.072333: Epoch 4053 +2024-11-22 09:11:07.072446: Current learning rate: 0.00529 +2024-11-22 09:11:25.565611: train_loss -0.781 +2024-11-22 09:11:25.565814: val_loss -0.7698 +2024-11-22 09:11:25.565889: Pseudo dice [0.8527] +2024-11-22 09:11:25.565963: Epoch time: 18.49 s +2024-11-22 09:11:26.653777: +2024-11-22 09:11:26.653979: Epoch 4054 +2024-11-22 09:11:26.654096: Current learning rate: 0.00529 +2024-11-22 09:11:45.355833: train_loss -0.7991 +2024-11-22 09:11:45.356037: val_loss -0.7651 +2024-11-22 09:11:45.356120: Pseudo dice [0.855] +2024-11-22 09:11:45.356194: Epoch time: 18.7 s +2024-11-22 09:11:46.474632: +2024-11-22 09:11:46.474827: Epoch 4055 +2024-11-22 09:11:46.474940: Current learning rate: 0.00529 +2024-11-22 09:12:04.398418: train_loss -0.7958 +2024-11-22 09:12:04.398639: val_loss -0.7844 +2024-11-22 09:12:04.398716: Pseudo dice [0.8618] +2024-11-22 09:12:04.398794: Epoch time: 17.92 s +2024-11-22 09:12:05.319569: +2024-11-22 09:12:05.319806: Epoch 4056 +2024-11-22 09:12:05.319918: Current learning rate: 0.00529 +2024-11-22 09:12:23.224038: train_loss -0.784 +2024-11-22 09:12:23.224248: val_loss -0.7776 +2024-11-22 09:12:23.224323: Pseudo dice [0.8523] +2024-11-22 09:12:23.224396: Epoch time: 17.91 s +2024-11-22 09:12:24.079888: +2024-11-22 09:12:24.080087: Epoch 4057 +2024-11-22 09:12:24.080199: Current learning rate: 0.00529 +2024-11-22 09:12:42.822433: train_loss -0.7827 +2024-11-22 09:12:42.822639: val_loss -0.7727 +2024-11-22 09:12:42.822711: Pseudo dice [0.8643] +2024-11-22 09:12:42.822782: Epoch time: 18.74 s +2024-11-22 09:12:43.676222: +2024-11-22 09:12:43.676431: Epoch 4058 +2024-11-22 09:12:43.676548: Current learning rate: 0.00529 +2024-11-22 09:13:02.954670: train_loss -0.7867 +2024-11-22 09:13:02.954879: val_loss -0.7653 +2024-11-22 09:13:02.954954: Pseudo dice [0.8395] +2024-11-22 09:13:02.955034: Epoch time: 19.28 s +2024-11-22 09:13:03.820503: +2024-11-22 09:13:03.820721: Epoch 4059 +2024-11-22 09:13:03.820838: Current learning rate: 0.00529 +2024-11-22 09:13:21.878179: train_loss -0.7814 +2024-11-22 09:13:21.878415: val_loss -0.7641 +2024-11-22 09:13:21.878491: Pseudo dice [0.8448] +2024-11-22 09:13:21.878568: Epoch time: 18.06 s +2024-11-22 09:13:22.801568: +2024-11-22 09:13:22.801784: Epoch 4060 +2024-11-22 09:13:22.801893: Current learning rate: 0.00529 +2024-11-22 09:13:40.902626: train_loss -0.784 +2024-11-22 09:13:40.902839: val_loss -0.7591 +2024-11-22 09:13:40.902942: Pseudo dice [0.8328] +2024-11-22 09:13:40.903014: Epoch time: 18.1 s +2024-11-22 09:13:41.756329: +2024-11-22 09:13:41.756526: Epoch 4061 +2024-11-22 09:13:41.756635: Current learning rate: 0.00529 +2024-11-22 09:14:00.934322: train_loss -0.7805 +2024-11-22 09:14:00.934560: val_loss -0.781 +2024-11-22 09:14:00.934641: Pseudo dice [0.8398] +2024-11-22 09:14:00.934715: Epoch time: 19.18 s +2024-11-22 09:14:01.799173: +2024-11-22 09:14:01.799425: Epoch 4062 +2024-11-22 09:14:01.799547: Current learning rate: 0.00528 +2024-11-22 09:14:21.123698: train_loss -0.7954 +2024-11-22 09:14:21.123915: val_loss -0.7751 +2024-11-22 09:14:21.123989: Pseudo dice [0.8574] +2024-11-22 09:14:21.124073: Epoch time: 19.33 s +2024-11-22 09:14:21.994182: +2024-11-22 09:14:21.994432: Epoch 4063 +2024-11-22 09:14:21.994584: Current learning rate: 0.00528 +2024-11-22 09:14:39.564624: train_loss -0.7908 +2024-11-22 09:14:39.564839: val_loss -0.7734 +2024-11-22 09:14:39.564915: Pseudo dice [0.8492] +2024-11-22 09:14:39.564991: Epoch time: 17.57 s +2024-11-22 09:14:40.424940: +2024-11-22 09:14:40.425136: Epoch 4064 +2024-11-22 09:14:40.425247: Current learning rate: 0.00528 +2024-11-22 09:14:59.043229: train_loss -0.7845 +2024-11-22 09:14:59.043435: val_loss -0.7424 +2024-11-22 09:14:59.043510: Pseudo dice [0.8537] +2024-11-22 09:14:59.043586: Epoch time: 18.62 s +2024-11-22 09:14:59.907896: +2024-11-22 09:14:59.908089: Epoch 4065 +2024-11-22 09:14:59.908201: Current learning rate: 0.00528 +2024-11-22 09:15:18.307651: train_loss -0.7903 +2024-11-22 09:15:18.307854: val_loss -0.7532 +2024-11-22 09:15:18.307928: Pseudo dice [0.8383] +2024-11-22 09:15:18.308000: Epoch time: 18.4 s +2024-11-22 09:15:19.506584: +2024-11-22 09:15:19.506790: Epoch 4066 +2024-11-22 09:15:19.506902: Current learning rate: 0.00528 +2024-11-22 09:15:37.753387: train_loss -0.7951 +2024-11-22 09:15:37.753620: val_loss -0.7825 +2024-11-22 09:15:37.753699: Pseudo dice [0.864] +2024-11-22 09:15:37.753778: Epoch time: 18.25 s +2024-11-22 09:15:38.601632: +2024-11-22 09:15:38.601849: Epoch 4067 +2024-11-22 09:15:38.601957: Current learning rate: 0.00528 +2024-11-22 09:15:58.146633: train_loss -0.7777 +2024-11-22 09:15:58.146852: val_loss -0.7658 +2024-11-22 09:15:58.146930: Pseudo dice [0.8528] +2024-11-22 09:15:58.147007: Epoch time: 19.55 s +2024-11-22 09:15:59.013449: +2024-11-22 09:15:59.013678: Epoch 4068 +2024-11-22 09:15:59.013788: Current learning rate: 0.00528 +2024-11-22 09:16:16.841380: train_loss -0.7985 +2024-11-22 09:16:16.841591: val_loss -0.7797 +2024-11-22 09:16:16.841666: Pseudo dice [0.8498] +2024-11-22 09:16:16.841744: Epoch time: 17.83 s +2024-11-22 09:16:17.690924: +2024-11-22 09:16:17.691137: Epoch 4069 +2024-11-22 09:16:17.691251: Current learning rate: 0.00528 +2024-11-22 09:16:36.379254: train_loss -0.7944 +2024-11-22 09:16:36.379460: val_loss -0.7885 +2024-11-22 09:16:36.379537: Pseudo dice [0.8607] +2024-11-22 09:16:36.379611: Epoch time: 18.69 s +2024-11-22 09:16:37.252039: +2024-11-22 09:16:37.252237: Epoch 4070 +2024-11-22 09:16:37.252347: Current learning rate: 0.00527 +2024-11-22 09:16:55.750871: train_loss -0.7928 +2024-11-22 09:16:55.751123: val_loss -0.7874 +2024-11-22 09:16:55.751204: Pseudo dice [0.8471] +2024-11-22 09:16:55.751287: Epoch time: 18.5 s +2024-11-22 09:16:56.613017: +2024-11-22 09:16:56.613244: Epoch 4071 +2024-11-22 09:16:56.613350: Current learning rate: 0.00527 +2024-11-22 09:17:14.997205: train_loss -0.7853 +2024-11-22 09:17:14.997414: val_loss -0.7645 +2024-11-22 09:17:14.997490: Pseudo dice [0.8415] +2024-11-22 09:17:14.997565: Epoch time: 18.38 s +2024-11-22 09:17:15.882150: +2024-11-22 09:17:15.882375: Epoch 4072 +2024-11-22 09:17:15.882488: Current learning rate: 0.00527 +2024-11-22 09:17:34.826763: train_loss -0.776 +2024-11-22 09:17:34.827006: val_loss -0.7707 +2024-11-22 09:17:34.827093: Pseudo dice [0.8578] +2024-11-22 09:17:34.827168: Epoch time: 18.95 s +2024-11-22 09:17:35.689044: +2024-11-22 09:17:35.689252: Epoch 4073 +2024-11-22 09:17:35.689367: Current learning rate: 0.00527 +2024-11-22 09:17:53.905518: train_loss -0.781 +2024-11-22 09:17:53.905804: val_loss -0.7464 +2024-11-22 09:17:53.905889: Pseudo dice [0.851] +2024-11-22 09:17:53.905969: Epoch time: 18.22 s +2024-11-22 09:17:54.881135: +2024-11-22 09:17:54.881349: Epoch 4074 +2024-11-22 09:17:54.881464: Current learning rate: 0.00527 +2024-11-22 09:18:13.484120: train_loss -0.7845 +2024-11-22 09:18:13.484338: val_loss -0.748 +2024-11-22 09:18:13.484410: Pseudo dice [0.8331] +2024-11-22 09:18:13.484485: Epoch time: 18.6 s +2024-11-22 09:18:14.342681: +2024-11-22 09:18:14.342869: Epoch 4075 +2024-11-22 09:18:14.342985: Current learning rate: 0.00527 +2024-11-22 09:18:32.931399: train_loss -0.788 +2024-11-22 09:18:32.931614: val_loss -0.7775 +2024-11-22 09:18:32.931688: Pseudo dice [0.86] +2024-11-22 09:18:32.931762: Epoch time: 18.59 s +2024-11-22 09:18:33.814597: +2024-11-22 09:18:33.814805: Epoch 4076 +2024-11-22 09:18:33.814920: Current learning rate: 0.00527 +2024-11-22 09:18:51.956565: train_loss -0.7922 +2024-11-22 09:18:51.956777: val_loss -0.7809 +2024-11-22 09:18:51.956856: Pseudo dice [0.849] +2024-11-22 09:18:51.956928: Epoch time: 18.14 s +2024-11-22 09:18:53.242510: +2024-11-22 09:18:53.242756: Epoch 4077 +2024-11-22 09:18:53.242871: Current learning rate: 0.00527 +2024-11-22 09:19:11.341267: train_loss -0.7892 +2024-11-22 09:19:11.341504: val_loss -0.7771 +2024-11-22 09:19:11.341579: Pseudo dice [0.8621] +2024-11-22 09:19:11.341661: Epoch time: 18.1 s +2024-11-22 09:19:12.342248: +2024-11-22 09:19:12.342520: Epoch 4078 +2024-11-22 09:19:12.342649: Current learning rate: 0.00526 +2024-11-22 09:19:30.788587: train_loss -0.7933 +2024-11-22 09:19:30.788799: val_loss -0.7788 +2024-11-22 09:19:30.788871: Pseudo dice [0.8489] +2024-11-22 09:19:30.788941: Epoch time: 18.45 s +2024-11-22 09:19:31.654788: +2024-11-22 09:19:31.655012: Epoch 4079 +2024-11-22 09:19:31.655123: Current learning rate: 0.00526 +2024-11-22 09:19:50.455543: train_loss -0.7876 +2024-11-22 09:19:50.455750: val_loss -0.7768 +2024-11-22 09:19:50.455826: Pseudo dice [0.8638] +2024-11-22 09:19:50.455898: Epoch time: 18.8 s +2024-11-22 09:19:51.320204: +2024-11-22 09:19:51.320453: Epoch 4080 +2024-11-22 09:19:51.320565: Current learning rate: 0.00526 +2024-11-22 09:20:09.953372: train_loss -0.7884 +2024-11-22 09:20:09.953605: val_loss -0.774 +2024-11-22 09:20:09.953682: Pseudo dice [0.8485] +2024-11-22 09:20:09.953758: Epoch time: 18.63 s +2024-11-22 09:20:10.955022: +2024-11-22 09:20:10.955266: Epoch 4081 +2024-11-22 09:20:10.955386: Current learning rate: 0.00526 +2024-11-22 09:20:29.263656: train_loss -0.7801 +2024-11-22 09:20:29.263900: val_loss -0.7569 +2024-11-22 09:20:29.263981: Pseudo dice [0.8556] +2024-11-22 09:20:29.264073: Epoch time: 18.31 s +2024-11-22 09:20:30.245171: +2024-11-22 09:20:30.245380: Epoch 4082 +2024-11-22 09:20:30.245489: Current learning rate: 0.00526 +2024-11-22 09:20:48.448300: train_loss -0.7883 +2024-11-22 09:20:48.448532: val_loss -0.7712 +2024-11-22 09:20:48.448612: Pseudo dice [0.8456] +2024-11-22 09:20:48.448726: Epoch time: 18.2 s +2024-11-22 09:20:49.316267: +2024-11-22 09:20:49.316472: Epoch 4083 +2024-11-22 09:20:49.316584: Current learning rate: 0.00526 +2024-11-22 09:21:07.585872: train_loss -0.7829 +2024-11-22 09:21:07.586089: val_loss -0.785 +2024-11-22 09:21:07.586167: Pseudo dice [0.8328] +2024-11-22 09:21:07.586245: Epoch time: 18.27 s +2024-11-22 09:21:08.451547: +2024-11-22 09:21:08.451749: Epoch 4084 +2024-11-22 09:21:08.451865: Current learning rate: 0.00526 +2024-11-22 09:21:27.537570: train_loss -0.787 +2024-11-22 09:21:27.537778: val_loss -0.7667 +2024-11-22 09:21:27.537850: Pseudo dice [0.8602] +2024-11-22 09:21:27.537924: Epoch time: 19.09 s +2024-11-22 09:21:28.557008: +2024-11-22 09:21:28.557209: Epoch 4085 +2024-11-22 09:21:28.557318: Current learning rate: 0.00526 +2024-11-22 09:21:47.278092: train_loss -0.7785 +2024-11-22 09:21:47.278336: val_loss -0.7379 +2024-11-22 09:21:47.278414: Pseudo dice [0.8615] +2024-11-22 09:21:47.278494: Epoch time: 18.72 s +2024-11-22 09:21:48.252649: +2024-11-22 09:21:48.252853: Epoch 4086 +2024-11-22 09:21:48.252965: Current learning rate: 0.00526 +2024-11-22 09:22:06.887126: train_loss -0.7874 +2024-11-22 09:22:06.887345: val_loss -0.7528 +2024-11-22 09:22:06.887419: Pseudo dice [0.8532] +2024-11-22 09:22:06.887492: Epoch time: 18.64 s +2024-11-22 09:22:07.752488: +2024-11-22 09:22:07.752687: Epoch 4087 +2024-11-22 09:22:07.752799: Current learning rate: 0.00525 +2024-11-22 09:22:26.392052: train_loss -0.7834 +2024-11-22 09:22:26.392270: val_loss -0.7797 +2024-11-22 09:22:26.392348: Pseudo dice [0.8563] +2024-11-22 09:22:26.392426: Epoch time: 18.64 s +2024-11-22 09:22:27.648737: +2024-11-22 09:22:27.648941: Epoch 4088 +2024-11-22 09:22:27.649051: Current learning rate: 0.00525 +2024-11-22 09:22:45.840157: train_loss -0.7911 +2024-11-22 09:22:45.840436: val_loss -0.7493 +2024-11-22 09:22:45.840513: Pseudo dice [0.8451] +2024-11-22 09:22:45.840591: Epoch time: 18.19 s +2024-11-22 09:22:46.706985: +2024-11-22 09:22:46.707282: Epoch 4089 +2024-11-22 09:22:46.707393: Current learning rate: 0.00525 +2024-11-22 09:23:04.813646: train_loss -0.7739 +2024-11-22 09:23:04.813858: val_loss -0.7825 +2024-11-22 09:23:04.813937: Pseudo dice [0.8557] +2024-11-22 09:23:04.814012: Epoch time: 18.11 s +2024-11-22 09:23:05.674386: +2024-11-22 09:23:05.674627: Epoch 4090 +2024-11-22 09:23:05.674740: Current learning rate: 0.00525 +2024-11-22 09:23:23.095167: train_loss -0.7672 +2024-11-22 09:23:23.095384: val_loss -0.7512 +2024-11-22 09:23:23.095461: Pseudo dice [0.8428] +2024-11-22 09:23:23.095535: Epoch time: 17.42 s +2024-11-22 09:23:23.957711: +2024-11-22 09:23:23.957933: Epoch 4091 +2024-11-22 09:23:23.958049: Current learning rate: 0.00525 +2024-11-22 09:23:43.021785: train_loss -0.7823 +2024-11-22 09:23:43.021995: val_loss -0.7711 +2024-11-22 09:23:43.022076: Pseudo dice [0.852] +2024-11-22 09:23:43.022151: Epoch time: 19.06 s +2024-11-22 09:23:43.856230: +2024-11-22 09:23:43.856452: Epoch 4092 +2024-11-22 09:23:43.856560: Current learning rate: 0.00525 +2024-11-22 09:24:01.613550: train_loss -0.7836 +2024-11-22 09:24:01.613793: val_loss -0.755 +2024-11-22 09:24:01.613878: Pseudo dice [0.8519] +2024-11-22 09:24:01.613958: Epoch time: 17.76 s +2024-11-22 09:24:02.453081: +2024-11-22 09:24:02.453283: Epoch 4093 +2024-11-22 09:24:02.453390: Current learning rate: 0.00525 +2024-11-22 09:24:20.945902: train_loss -0.7854 +2024-11-22 09:24:20.946111: val_loss -0.7716 +2024-11-22 09:24:20.946187: Pseudo dice [0.8561] +2024-11-22 09:24:20.946258: Epoch time: 18.49 s +2024-11-22 09:24:21.778317: +2024-11-22 09:24:21.778576: Epoch 4094 +2024-11-22 09:24:21.778727: Current learning rate: 0.00525 +2024-11-22 09:24:40.518478: train_loss -0.7826 +2024-11-22 09:24:40.518686: val_loss -0.7601 +2024-11-22 09:24:40.518763: Pseudo dice [0.8452] +2024-11-22 09:24:40.518839: Epoch time: 18.74 s +2024-11-22 09:24:41.354668: +2024-11-22 09:24:41.354891: Epoch 4095 +2024-11-22 09:24:41.355003: Current learning rate: 0.00524 +2024-11-22 09:24:59.445676: train_loss -0.7886 +2024-11-22 09:24:59.446273: val_loss -0.7832 +2024-11-22 09:24:59.446368: Pseudo dice [0.8482] +2024-11-22 09:24:59.446446: Epoch time: 18.09 s +2024-11-22 09:25:00.366859: +2024-11-22 09:25:00.367055: Epoch 4096 +2024-11-22 09:25:00.367174: Current learning rate: 0.00524 +2024-11-22 09:25:18.823280: train_loss -0.7844 +2024-11-22 09:25:18.823581: val_loss -0.7842 +2024-11-22 09:25:18.823655: Pseudo dice [0.8435] +2024-11-22 09:25:18.823734: Epoch time: 18.46 s +2024-11-22 09:25:19.654929: +2024-11-22 09:25:19.655146: Epoch 4097 +2024-11-22 09:25:19.655264: Current learning rate: 0.00524 +2024-11-22 09:25:37.783781: train_loss -0.7851 +2024-11-22 09:25:37.784117: val_loss -0.7455 +2024-11-22 09:25:37.784199: Pseudo dice [0.8464] +2024-11-22 09:25:37.784274: Epoch time: 18.13 s +2024-11-22 09:25:38.619830: +2024-11-22 09:25:38.620034: Epoch 4098 +2024-11-22 09:25:38.620158: Current learning rate: 0.00524 +2024-11-22 09:25:56.400163: train_loss -0.7814 +2024-11-22 09:25:56.400384: val_loss -0.7887 +2024-11-22 09:25:56.400459: Pseudo dice [0.8581] +2024-11-22 09:25:56.400534: Epoch time: 17.78 s +2024-11-22 09:25:57.329653: +2024-11-22 09:25:57.329866: Epoch 4099 +2024-11-22 09:25:57.329974: Current learning rate: 0.00524 +2024-11-22 09:26:15.566406: train_loss -0.7936 +2024-11-22 09:26:15.566616: val_loss -0.7635 +2024-11-22 09:26:15.566695: Pseudo dice [0.8485] +2024-11-22 09:26:15.566772: Epoch time: 18.24 s +2024-11-22 09:26:17.085339: +2024-11-22 09:26:17.085546: Epoch 4100 +2024-11-22 09:26:17.085659: Current learning rate: 0.00524 +2024-11-22 09:26:35.561622: train_loss -0.7867 +2024-11-22 09:26:35.562124: val_loss -0.7781 +2024-11-22 09:26:35.562224: Pseudo dice [0.8461] +2024-11-22 09:26:35.562305: Epoch time: 18.48 s +2024-11-22 09:26:36.389403: +2024-11-22 09:26:36.389644: Epoch 4101 +2024-11-22 09:26:36.389755: Current learning rate: 0.00524 +2024-11-22 09:26:54.622916: train_loss -0.7914 +2024-11-22 09:26:54.623147: val_loss -0.7414 +2024-11-22 09:26:54.623221: Pseudo dice [0.8584] +2024-11-22 09:26:54.623296: Epoch time: 18.23 s +2024-11-22 09:26:55.472227: +2024-11-22 09:26:55.472422: Epoch 4102 +2024-11-22 09:26:55.472533: Current learning rate: 0.00524 +2024-11-22 09:27:14.075933: train_loss -0.7941 +2024-11-22 09:27:14.076158: val_loss -0.7674 +2024-11-22 09:27:14.076238: Pseudo dice [0.865] +2024-11-22 09:27:14.076312: Epoch time: 18.6 s +2024-11-22 09:27:14.957415: +2024-11-22 09:27:14.957638: Epoch 4103 +2024-11-22 09:27:14.957877: Current learning rate: 0.00523 +2024-11-22 09:27:33.627153: train_loss -0.7814 +2024-11-22 09:27:33.627397: val_loss -0.7591 +2024-11-22 09:27:33.627475: Pseudo dice [0.853] +2024-11-22 09:27:33.627556: Epoch time: 18.67 s +2024-11-22 09:27:34.465536: +2024-11-22 09:27:34.465745: Epoch 4104 +2024-11-22 09:27:34.465858: Current learning rate: 0.00523 +2024-11-22 09:27:52.855434: train_loss -0.7944 +2024-11-22 09:27:52.855711: val_loss -0.771 +2024-11-22 09:27:52.855789: Pseudo dice [0.8613] +2024-11-22 09:27:52.855865: Epoch time: 18.39 s +2024-11-22 09:27:53.788746: +2024-11-22 09:27:53.788958: Epoch 4105 +2024-11-22 09:27:53.789076: Current learning rate: 0.00523 +2024-11-22 09:28:12.520787: train_loss -0.7972 +2024-11-22 09:28:12.521009: val_loss -0.7934 +2024-11-22 09:28:12.521099: Pseudo dice [0.8649] +2024-11-22 09:28:12.521184: Epoch time: 18.73 s +2024-11-22 09:28:13.358808: +2024-11-22 09:28:13.359036: Epoch 4106 +2024-11-22 09:28:13.359152: Current learning rate: 0.00523 +2024-11-22 09:28:32.217457: train_loss -0.7915 +2024-11-22 09:28:32.217667: val_loss -0.7798 +2024-11-22 09:28:32.217740: Pseudo dice [0.857] +2024-11-22 09:28:32.217812: Epoch time: 18.86 s +2024-11-22 09:28:33.250751: +2024-11-22 09:28:33.250969: Epoch 4107 +2024-11-22 09:28:33.251085: Current learning rate: 0.00523 +2024-11-22 09:28:51.458575: train_loss -0.7915 +2024-11-22 09:28:51.464005: val_loss -0.7868 +2024-11-22 09:28:51.464133: Pseudo dice [0.8624] +2024-11-22 09:28:51.464216: Epoch time: 18.21 s +2024-11-22 09:28:51.464280: Yayy! New best EMA pseudo Dice: 0.8554 +2024-11-22 09:28:52.805355: +2024-11-22 09:28:52.805578: Epoch 4108 +2024-11-22 09:28:52.805699: Current learning rate: 0.00523 +2024-11-22 09:29:11.749107: train_loss -0.7943 +2024-11-22 09:29:11.749326: val_loss -0.7379 +2024-11-22 09:29:11.749407: Pseudo dice [0.847] +2024-11-22 09:29:11.749480: Epoch time: 18.94 s +2024-11-22 09:29:12.693606: +2024-11-22 09:29:12.693809: Epoch 4109 +2024-11-22 09:29:12.693917: Current learning rate: 0.00523 +2024-11-22 09:29:32.090482: train_loss -0.7816 +2024-11-22 09:29:32.090764: val_loss -0.779 +2024-11-22 09:29:32.090844: Pseudo dice [0.8578] +2024-11-22 09:29:32.090921: Epoch time: 19.4 s +2024-11-22 09:29:32.937578: +2024-11-22 09:29:32.937788: Epoch 4110 +2024-11-22 09:29:32.937902: Current learning rate: 0.00523 +2024-11-22 09:29:50.122042: train_loss -0.783 +2024-11-22 09:29:50.122261: val_loss -0.7921 +2024-11-22 09:29:50.122344: Pseudo dice [0.8611] +2024-11-22 09:29:50.122420: Epoch time: 17.19 s +2024-11-22 09:29:50.122484: Yayy! New best EMA pseudo Dice: 0.8555 +2024-11-22 09:29:51.614677: +2024-11-22 09:29:51.614899: Epoch 4111 +2024-11-22 09:29:51.615011: Current learning rate: 0.00522 +2024-11-22 09:30:10.442461: train_loss -0.783 +2024-11-22 09:30:10.442743: val_loss -0.7673 +2024-11-22 09:30:10.442822: Pseudo dice [0.8599] +2024-11-22 09:30:10.442899: Epoch time: 18.83 s +2024-11-22 09:30:10.442961: Yayy! New best EMA pseudo Dice: 0.8559 +2024-11-22 09:30:11.540197: +2024-11-22 09:30:11.540403: Epoch 4112 +2024-11-22 09:30:11.540514: Current learning rate: 0.00522 +2024-11-22 09:30:29.670304: train_loss -0.7841 +2024-11-22 09:30:29.670515: val_loss -0.7664 +2024-11-22 09:30:29.670592: Pseudo dice [0.8535] +2024-11-22 09:30:29.670667: Epoch time: 18.13 s +2024-11-22 09:30:30.506049: +2024-11-22 09:30:30.506257: Epoch 4113 +2024-11-22 09:30:30.506370: Current learning rate: 0.00522 +2024-11-22 09:30:48.388533: train_loss -0.7829 +2024-11-22 09:30:48.388743: val_loss -0.7748 +2024-11-22 09:30:48.388822: Pseudo dice [0.8357] +2024-11-22 09:30:48.388896: Epoch time: 17.88 s +2024-11-22 09:30:49.224476: +2024-11-22 09:30:49.224679: Epoch 4114 +2024-11-22 09:30:49.224792: Current learning rate: 0.00522 +2024-11-22 09:31:06.601888: train_loss -0.7837 +2024-11-22 09:31:06.602164: val_loss -0.7666 +2024-11-22 09:31:06.602242: Pseudo dice [0.8325] +2024-11-22 09:31:06.602323: Epoch time: 17.38 s +2024-11-22 09:31:07.548411: +2024-11-22 09:31:07.548636: Epoch 4115 +2024-11-22 09:31:07.548749: Current learning rate: 0.00522 +2024-11-22 09:31:25.698852: train_loss -0.7999 +2024-11-22 09:31:25.699078: val_loss -0.7774 +2024-11-22 09:31:25.699153: Pseudo dice [0.8576] +2024-11-22 09:31:25.699227: Epoch time: 18.15 s +2024-11-22 09:31:26.539600: +2024-11-22 09:31:26.539832: Epoch 4116 +2024-11-22 09:31:26.539946: Current learning rate: 0.00522 +2024-11-22 09:31:44.679140: train_loss -0.8001 +2024-11-22 09:31:44.679361: val_loss -0.8005 +2024-11-22 09:31:44.679443: Pseudo dice [0.8651] +2024-11-22 09:31:44.679515: Epoch time: 18.14 s +2024-11-22 09:31:45.515466: +2024-11-22 09:31:45.515728: Epoch 4117 +2024-11-22 09:31:45.515839: Current learning rate: 0.00522 +2024-11-22 09:32:04.693824: train_loss -0.7929 +2024-11-22 09:32:04.694068: val_loss -0.7636 +2024-11-22 09:32:04.694143: Pseudo dice [0.8401] +2024-11-22 09:32:04.694223: Epoch time: 19.18 s +2024-11-22 09:32:05.555320: +2024-11-22 09:32:05.555515: Epoch 4118 +2024-11-22 09:32:05.555624: Current learning rate: 0.00522 +2024-11-22 09:32:24.122053: train_loss -0.7831 +2024-11-22 09:32:24.122270: val_loss -0.7859 +2024-11-22 09:32:24.122345: Pseudo dice [0.8558] +2024-11-22 09:32:24.122417: Epoch time: 18.57 s +2024-11-22 09:32:24.982649: +2024-11-22 09:32:24.982851: Epoch 4119 +2024-11-22 09:32:24.982961: Current learning rate: 0.00522 +2024-11-22 09:32:44.883710: train_loss -0.7819 +2024-11-22 09:32:44.898217: val_loss -0.7735 +2024-11-22 09:32:44.898347: Pseudo dice [0.8448] +2024-11-22 09:32:44.898426: Epoch time: 19.9 s +2024-11-22 09:32:45.754221: +2024-11-22 09:32:45.754425: Epoch 4120 +2024-11-22 09:32:45.754538: Current learning rate: 0.00521 +2024-11-22 09:33:03.680054: train_loss -0.795 +2024-11-22 09:33:03.680272: val_loss -0.7832 +2024-11-22 09:33:03.680349: Pseudo dice [0.869] +2024-11-22 09:33:03.680424: Epoch time: 17.93 s +2024-11-22 09:33:04.523767: +2024-11-22 09:33:04.524001: Epoch 4121 +2024-11-22 09:33:04.524118: Current learning rate: 0.00521 +2024-11-22 09:33:22.880574: train_loss -0.779 +2024-11-22 09:33:22.880790: val_loss -0.757 +2024-11-22 09:33:22.880867: Pseudo dice [0.8386] +2024-11-22 09:33:22.880946: Epoch time: 18.36 s +2024-11-22 09:33:23.712883: +2024-11-22 09:33:23.713080: Epoch 4122 +2024-11-22 09:33:23.713191: Current learning rate: 0.00521 +2024-11-22 09:33:42.434869: train_loss -0.7878 +2024-11-22 09:33:42.435335: val_loss -0.77 +2024-11-22 09:33:42.435457: Pseudo dice [0.8611] +2024-11-22 09:33:42.435545: Epoch time: 18.72 s +2024-11-22 09:33:43.284912: +2024-11-22 09:33:43.285127: Epoch 4123 +2024-11-22 09:33:43.285237: Current learning rate: 0.00521 +2024-11-22 09:34:01.886964: train_loss -0.7917 +2024-11-22 09:34:01.887193: val_loss -0.7812 +2024-11-22 09:34:01.887273: Pseudo dice [0.8519] +2024-11-22 09:34:01.887351: Epoch time: 18.6 s +2024-11-22 09:34:02.730590: +2024-11-22 09:34:02.730790: Epoch 4124 +2024-11-22 09:34:02.730902: Current learning rate: 0.00521 +2024-11-22 09:34:21.382213: train_loss -0.7861 +2024-11-22 09:34:21.382505: val_loss -0.7656 +2024-11-22 09:34:21.382590: Pseudo dice [0.8451] +2024-11-22 09:34:21.382671: Epoch time: 18.65 s +2024-11-22 09:34:22.214067: +2024-11-22 09:34:22.214287: Epoch 4125 +2024-11-22 09:34:22.214406: Current learning rate: 0.00521 +2024-11-22 09:34:39.975788: train_loss -0.782 +2024-11-22 09:34:39.975991: val_loss -0.7687 +2024-11-22 09:34:39.976070: Pseudo dice [0.8552] +2024-11-22 09:34:39.976155: Epoch time: 17.76 s +2024-11-22 09:34:40.813499: +2024-11-22 09:34:40.813703: Epoch 4126 +2024-11-22 09:34:40.813817: Current learning rate: 0.00521 +2024-11-22 09:34:58.947842: train_loss -0.7815 +2024-11-22 09:34:58.948133: val_loss -0.7647 +2024-11-22 09:34:58.948210: Pseudo dice [0.845] +2024-11-22 09:34:58.948287: Epoch time: 18.14 s +2024-11-22 09:34:59.795416: +2024-11-22 09:34:59.795638: Epoch 4127 +2024-11-22 09:34:59.795755: Current learning rate: 0.00521 +2024-11-22 09:35:19.325325: train_loss -0.7685 +2024-11-22 09:35:19.325537: val_loss -0.7626 +2024-11-22 09:35:19.325612: Pseudo dice [0.8454] +2024-11-22 09:35:19.325685: Epoch time: 19.53 s +2024-11-22 09:35:20.160264: +2024-11-22 09:35:20.160455: Epoch 4128 +2024-11-22 09:35:20.160567: Current learning rate: 0.0052 +2024-11-22 09:35:38.112216: train_loss -0.7614 +2024-11-22 09:35:38.112743: val_loss -0.769 +2024-11-22 09:35:38.112827: Pseudo dice [0.8529] +2024-11-22 09:35:38.112907: Epoch time: 17.95 s +2024-11-22 09:35:38.951294: +2024-11-22 09:35:38.951469: Epoch 4129 +2024-11-22 09:35:38.951577: Current learning rate: 0.0052 +2024-11-22 09:35:57.255165: train_loss -0.7717 +2024-11-22 09:35:57.255376: val_loss -0.7727 +2024-11-22 09:35:57.255449: Pseudo dice [0.8464] +2024-11-22 09:35:57.255521: Epoch time: 18.3 s +2024-11-22 09:35:58.090827: +2024-11-22 09:35:58.091029: Epoch 4130 +2024-11-22 09:35:58.091142: Current learning rate: 0.0052 +2024-11-22 09:36:16.590718: train_loss -0.7551 +2024-11-22 09:36:16.590916: val_loss -0.7747 +2024-11-22 09:36:16.590989: Pseudo dice [0.8402] +2024-11-22 09:36:16.591070: Epoch time: 18.5 s +2024-11-22 09:36:17.420973: +2024-11-22 09:36:17.421182: Epoch 4131 +2024-11-22 09:36:17.421290: Current learning rate: 0.0052 +2024-11-22 09:36:35.991424: train_loss -0.7747 +2024-11-22 09:36:35.991641: val_loss -0.7822 +2024-11-22 09:36:35.991718: Pseudo dice [0.8575] +2024-11-22 09:36:35.991794: Epoch time: 18.57 s +2024-11-22 09:36:36.848503: +2024-11-22 09:36:36.848714: Epoch 4132 +2024-11-22 09:36:36.848828: Current learning rate: 0.0052 +2024-11-22 09:36:55.202668: train_loss -0.7909 +2024-11-22 09:36:55.202922: val_loss -0.7774 +2024-11-22 09:36:55.202997: Pseudo dice [0.8484] +2024-11-22 09:36:55.203082: Epoch time: 18.36 s +2024-11-22 09:36:56.178695: +2024-11-22 09:36:56.178898: Epoch 4133 +2024-11-22 09:36:56.179004: Current learning rate: 0.0052 +2024-11-22 09:37:15.106910: train_loss -0.7773 +2024-11-22 09:37:15.107144: val_loss -0.7526 +2024-11-22 09:37:15.107227: Pseudo dice [0.8656] +2024-11-22 09:37:15.107302: Epoch time: 18.93 s +2024-11-22 09:37:16.379966: +2024-11-22 09:37:16.380172: Epoch 4134 +2024-11-22 09:37:16.380284: Current learning rate: 0.0052 +2024-11-22 09:37:34.986959: train_loss -0.7872 +2024-11-22 09:37:34.987172: val_loss -0.7572 +2024-11-22 09:37:34.987250: Pseudo dice [0.854] +2024-11-22 09:37:34.987325: Epoch time: 18.61 s +2024-11-22 09:37:35.921188: +2024-11-22 09:37:35.921400: Epoch 4135 +2024-11-22 09:37:35.921509: Current learning rate: 0.0052 +2024-11-22 09:37:54.387067: train_loss -0.7907 +2024-11-22 09:37:54.387274: val_loss -0.7781 +2024-11-22 09:37:54.387350: Pseudo dice [0.8614] +2024-11-22 09:37:54.387427: Epoch time: 18.47 s +2024-11-22 09:37:55.228316: +2024-11-22 09:37:55.228542: Epoch 4136 +2024-11-22 09:37:55.228706: Current learning rate: 0.00519 +2024-11-22 09:38:13.561705: train_loss -0.7898 +2024-11-22 09:38:13.564104: val_loss -0.7595 +2024-11-22 09:38:13.564229: Pseudo dice [0.8428] +2024-11-22 09:38:13.564312: Epoch time: 18.33 s +2024-11-22 09:38:14.571574: +2024-11-22 09:38:14.571795: Epoch 4137 +2024-11-22 09:38:14.571903: Current learning rate: 0.00519 +2024-11-22 09:38:33.729724: train_loss -0.7821 +2024-11-22 09:38:33.729943: val_loss -0.7865 +2024-11-22 09:38:33.730020: Pseudo dice [0.8564] +2024-11-22 09:38:33.730100: Epoch time: 19.16 s +2024-11-22 09:38:34.576699: +2024-11-22 09:38:34.576938: Epoch 4138 +2024-11-22 09:38:34.577053: Current learning rate: 0.00519 +2024-11-22 09:38:51.898288: train_loss -0.7829 +2024-11-22 09:38:51.898494: val_loss -0.7804 +2024-11-22 09:38:51.900657: Pseudo dice [0.8464] +2024-11-22 09:38:51.900826: Epoch time: 17.32 s +2024-11-22 09:38:52.891806: +2024-11-22 09:38:52.892009: Epoch 4139 +2024-11-22 09:38:52.892123: Current learning rate: 0.00519 +2024-11-22 09:39:11.503419: train_loss -0.7941 +2024-11-22 09:39:11.503643: val_loss -0.7749 +2024-11-22 09:39:11.503720: Pseudo dice [0.8554] +2024-11-22 09:39:11.503796: Epoch time: 18.61 s +2024-11-22 09:39:12.347851: +2024-11-22 09:39:12.348057: Epoch 4140 +2024-11-22 09:39:12.348174: Current learning rate: 0.00519 +2024-11-22 09:39:30.672472: train_loss -0.7932 +2024-11-22 09:39:30.672716: val_loss -0.7862 +2024-11-22 09:39:30.672791: Pseudo dice [0.8558] +2024-11-22 09:39:30.672870: Epoch time: 18.33 s +2024-11-22 09:39:31.508465: +2024-11-22 09:39:31.508643: Epoch 4141 +2024-11-22 09:39:31.508756: Current learning rate: 0.00519 +2024-11-22 09:39:48.985950: train_loss -0.7924 +2024-11-22 09:39:48.986165: val_loss -0.7542 +2024-11-22 09:39:48.986239: Pseudo dice [0.8512] +2024-11-22 09:39:48.986315: Epoch time: 17.48 s +2024-11-22 09:39:49.818931: +2024-11-22 09:39:49.819145: Epoch 4142 +2024-11-22 09:39:49.819253: Current learning rate: 0.00519 +2024-11-22 09:40:08.472847: train_loss -0.7924 +2024-11-22 09:40:08.473053: val_loss -0.7644 +2024-11-22 09:40:08.473133: Pseudo dice [0.8455] +2024-11-22 09:40:08.473206: Epoch time: 18.65 s +2024-11-22 09:40:09.311266: +2024-11-22 09:40:09.311480: Epoch 4143 +2024-11-22 09:40:09.311599: Current learning rate: 0.00519 +2024-11-22 09:40:28.600666: train_loss -0.7851 +2024-11-22 09:40:28.600909: val_loss -0.7603 +2024-11-22 09:40:28.600989: Pseudo dice [0.8403] +2024-11-22 09:40:28.601081: Epoch time: 19.29 s +2024-11-22 09:40:29.591852: +2024-11-22 09:40:29.592032: Epoch 4144 +2024-11-22 09:40:29.592148: Current learning rate: 0.00518 +2024-11-22 09:40:48.625370: train_loss -0.7851 +2024-11-22 09:40:48.625584: val_loss -0.7678 +2024-11-22 09:40:48.625663: Pseudo dice [0.8531] +2024-11-22 09:40:48.625742: Epoch time: 19.03 s +2024-11-22 09:40:49.463828: +2024-11-22 09:40:49.464039: Epoch 4145 +2024-11-22 09:40:49.464153: Current learning rate: 0.00518 +2024-11-22 09:41:07.054095: train_loss -0.7874 +2024-11-22 09:41:07.054626: val_loss -0.7626 +2024-11-22 09:41:07.054723: Pseudo dice [0.8457] +2024-11-22 09:41:07.054799: Epoch time: 17.59 s +2024-11-22 09:41:07.933900: +2024-11-22 09:41:07.934120: Epoch 4146 +2024-11-22 09:41:07.934230: Current learning rate: 0.00518 +2024-11-22 09:41:25.919573: train_loss -0.7813 +2024-11-22 09:41:25.920081: val_loss -0.7622 +2024-11-22 09:41:25.920183: Pseudo dice [0.8517] +2024-11-22 09:41:25.920285: Epoch time: 17.99 s +2024-11-22 09:41:26.758788: +2024-11-22 09:41:26.758983: Epoch 4147 +2024-11-22 09:41:26.759100: Current learning rate: 0.00518 +2024-11-22 09:41:44.626042: train_loss -0.7883 +2024-11-22 09:41:44.626330: val_loss -0.798 +2024-11-22 09:41:44.626404: Pseudo dice [0.8626] +2024-11-22 09:41:44.626481: Epoch time: 17.87 s +2024-11-22 09:41:45.538473: +2024-11-22 09:41:45.538691: Epoch 4148 +2024-11-22 09:41:45.538804: Current learning rate: 0.00518 +2024-11-22 09:42:03.539125: train_loss -0.7846 +2024-11-22 09:42:03.539392: val_loss -0.7804 +2024-11-22 09:42:03.539471: Pseudo dice [0.8596] +2024-11-22 09:42:03.539546: Epoch time: 18.0 s +2024-11-22 09:42:04.395603: +2024-11-22 09:42:04.395832: Epoch 4149 +2024-11-22 09:42:04.395957: Current learning rate: 0.00518 +2024-11-22 09:42:22.362233: train_loss -0.7877 +2024-11-22 09:42:22.362449: val_loss -0.7702 +2024-11-22 09:42:22.362523: Pseudo dice [0.8428] +2024-11-22 09:42:22.362598: Epoch time: 17.97 s +2024-11-22 09:42:23.464824: +2024-11-22 09:42:23.465032: Epoch 4150 +2024-11-22 09:42:23.465151: Current learning rate: 0.00518 +2024-11-22 09:42:41.613208: train_loss -0.7824 +2024-11-22 09:42:41.613435: val_loss -0.7528 +2024-11-22 09:42:41.613514: Pseudo dice [0.8408] +2024-11-22 09:42:41.613601: Epoch time: 18.15 s +2024-11-22 09:42:42.454533: +2024-11-22 09:42:42.454761: Epoch 4151 +2024-11-22 09:42:42.454870: Current learning rate: 0.00518 +2024-11-22 09:43:00.612067: train_loss -0.7901 +2024-11-22 09:43:00.612311: val_loss -0.7631 +2024-11-22 09:43:00.612387: Pseudo dice [0.8476] +2024-11-22 09:43:00.617603: Epoch time: 18.16 s +2024-11-22 09:43:01.466763: +2024-11-22 09:43:01.466959: Epoch 4152 +2024-11-22 09:43:01.467075: Current learning rate: 0.00518 +2024-11-22 09:43:20.242888: train_loss -0.7862 +2024-11-22 09:43:20.243099: val_loss -0.771 +2024-11-22 09:43:20.243221: Pseudo dice [0.8648] +2024-11-22 09:43:20.243295: Epoch time: 18.78 s +2024-11-22 09:43:21.083021: +2024-11-22 09:43:21.083218: Epoch 4153 +2024-11-22 09:43:21.083358: Current learning rate: 0.00517 +2024-11-22 09:43:40.227529: train_loss -0.7881 +2024-11-22 09:43:40.227735: val_loss -0.7713 +2024-11-22 09:43:40.227818: Pseudo dice [0.8586] +2024-11-22 09:43:40.227892: Epoch time: 19.15 s +2024-11-22 09:43:41.085231: +2024-11-22 09:43:41.085448: Epoch 4154 +2024-11-22 09:43:41.085557: Current learning rate: 0.00517 +2024-11-22 09:43:59.602170: train_loss -0.7958 +2024-11-22 09:43:59.602381: val_loss -0.7465 +2024-11-22 09:43:59.602458: Pseudo dice [0.8454] +2024-11-22 09:43:59.602534: Epoch time: 18.52 s +2024-11-22 09:44:00.471106: +2024-11-22 09:44:00.471354: Epoch 4155 +2024-11-22 09:44:00.471505: Current learning rate: 0.00517 +2024-11-22 09:44:19.303811: train_loss -0.785 +2024-11-22 09:44:19.304025: val_loss -0.7747 +2024-11-22 09:44:19.304103: Pseudo dice [0.857] +2024-11-22 09:44:19.304178: Epoch time: 18.83 s +2024-11-22 09:44:20.156458: +2024-11-22 09:44:20.156667: Epoch 4156 +2024-11-22 09:44:20.156780: Current learning rate: 0.00517 +2024-11-22 09:44:38.442911: train_loss -0.7854 +2024-11-22 09:44:38.443123: val_loss -0.7679 +2024-11-22 09:44:38.443197: Pseudo dice [0.8529] +2024-11-22 09:44:38.443269: Epoch time: 18.29 s +2024-11-22 09:44:39.658097: +2024-11-22 09:44:39.658322: Epoch 4157 +2024-11-22 09:44:39.658435: Current learning rate: 0.00517 +2024-11-22 09:44:57.744216: train_loss -0.7925 +2024-11-22 09:44:57.744481: val_loss -0.7828 +2024-11-22 09:44:57.744563: Pseudo dice [0.8545] +2024-11-22 09:44:57.744673: Epoch time: 18.09 s +2024-11-22 09:44:58.587509: +2024-11-22 09:44:58.587774: Epoch 4158 +2024-11-22 09:44:58.587932: Current learning rate: 0.00517 +2024-11-22 09:45:16.754860: train_loss -0.7965 +2024-11-22 09:45:16.755082: val_loss -0.7717 +2024-11-22 09:45:16.755160: Pseudo dice [0.8426] +2024-11-22 09:45:16.755236: Epoch time: 18.17 s +2024-11-22 09:45:17.593355: +2024-11-22 09:45:17.593548: Epoch 4159 +2024-11-22 09:45:17.593658: Current learning rate: 0.00517 +2024-11-22 09:45:36.045789: train_loss -0.7943 +2024-11-22 09:45:36.045997: val_loss -0.7782 +2024-11-22 09:45:36.046087: Pseudo dice [0.8529] +2024-11-22 09:45:36.046166: Epoch time: 18.45 s +2024-11-22 09:45:36.877550: +2024-11-22 09:45:36.877767: Epoch 4160 +2024-11-22 09:45:36.877881: Current learning rate: 0.00517 +2024-11-22 09:45:55.526540: train_loss -0.7864 +2024-11-22 09:45:55.526769: val_loss -0.7662 +2024-11-22 09:45:55.526846: Pseudo dice [0.8442] +2024-11-22 09:45:55.526920: Epoch time: 18.65 s +2024-11-22 09:45:56.382300: +2024-11-22 09:45:56.382525: Epoch 4161 +2024-11-22 09:45:56.382640: Current learning rate: 0.00516 +2024-11-22 09:46:14.913635: train_loss -0.7933 +2024-11-22 09:46:14.913899: val_loss -0.768 +2024-11-22 09:46:14.913981: Pseudo dice [0.8462] +2024-11-22 09:46:14.914063: Epoch time: 18.53 s +2024-11-22 09:46:15.754020: +2024-11-22 09:46:15.754225: Epoch 4162 +2024-11-22 09:46:15.754339: Current learning rate: 0.00516 +2024-11-22 09:46:34.219625: train_loss -0.7899 +2024-11-22 09:46:34.219881: val_loss -0.7823 +2024-11-22 09:46:34.219955: Pseudo dice [0.853] +2024-11-22 09:46:34.220034: Epoch time: 18.47 s +2024-11-22 09:46:35.080828: +2024-11-22 09:46:35.081034: Epoch 4163 +2024-11-22 09:46:35.081149: Current learning rate: 0.00516 +2024-11-22 09:46:53.047539: train_loss -0.7928 +2024-11-22 09:46:53.047756: val_loss -0.7841 +2024-11-22 09:46:53.047831: Pseudo dice [0.8588] +2024-11-22 09:46:53.047908: Epoch time: 17.97 s +2024-11-22 09:46:53.921401: +2024-11-22 09:46:53.921587: Epoch 4164 +2024-11-22 09:46:53.921696: Current learning rate: 0.00516 +2024-11-22 09:47:12.245441: train_loss -0.796 +2024-11-22 09:47:12.245717: val_loss -0.7806 +2024-11-22 09:47:12.245794: Pseudo dice [0.8637] +2024-11-22 09:47:12.245872: Epoch time: 18.32 s +2024-11-22 09:47:13.082783: +2024-11-22 09:47:13.082977: Epoch 4165 +2024-11-22 09:47:13.083093: Current learning rate: 0.00516 +2024-11-22 09:47:32.194470: train_loss -0.7889 +2024-11-22 09:47:32.194697: val_loss -0.7529 +2024-11-22 09:47:32.194770: Pseudo dice [0.8364] +2024-11-22 09:47:32.194849: Epoch time: 19.11 s +2024-11-22 09:47:33.029154: +2024-11-22 09:47:33.029384: Epoch 4166 +2024-11-22 09:47:33.029498: Current learning rate: 0.00516 +2024-11-22 09:47:51.357410: train_loss -0.784 +2024-11-22 09:47:51.357613: val_loss -0.767 +2024-11-22 09:47:51.357697: Pseudo dice [0.8618] +2024-11-22 09:47:51.357774: Epoch time: 18.33 s +2024-11-22 09:47:52.190298: +2024-11-22 09:47:52.190519: Epoch 4167 +2024-11-22 09:47:52.190630: Current learning rate: 0.00516 +2024-11-22 09:48:09.953963: train_loss -0.7996 +2024-11-22 09:48:09.954179: val_loss -0.7815 +2024-11-22 09:48:09.954252: Pseudo dice [0.8623] +2024-11-22 09:48:09.954329: Epoch time: 17.76 s +2024-11-22 09:48:10.786288: +2024-11-22 09:48:10.786504: Epoch 4168 +2024-11-22 09:48:10.786621: Current learning rate: 0.00516 +2024-11-22 09:48:29.943244: train_loss -0.7938 +2024-11-22 09:48:29.943744: val_loss -0.776 +2024-11-22 09:48:29.943845: Pseudo dice [0.8481] +2024-11-22 09:48:29.943921: Epoch time: 19.16 s +2024-11-22 09:48:30.781654: +2024-11-22 09:48:30.781879: Epoch 4169 +2024-11-22 09:48:30.781994: Current learning rate: 0.00515 +2024-11-22 09:48:49.046061: train_loss -0.7803 +2024-11-22 09:48:49.046348: val_loss -0.7595 +2024-11-22 09:48:49.046461: Pseudo dice [0.8553] +2024-11-22 09:48:49.046540: Epoch time: 18.27 s +2024-11-22 09:48:49.887443: +2024-11-22 09:48:49.887669: Epoch 4170 +2024-11-22 09:48:49.887779: Current learning rate: 0.00515 +2024-11-22 09:49:08.130708: train_loss -0.7903 +2024-11-22 09:49:08.130924: val_loss -0.745 +2024-11-22 09:49:08.130998: Pseudo dice [0.8495] +2024-11-22 09:49:08.131075: Epoch time: 18.24 s +2024-11-22 09:49:08.983188: +2024-11-22 09:49:08.983417: Epoch 4171 +2024-11-22 09:49:08.983532: Current learning rate: 0.00515 +2024-11-22 09:49:27.211727: train_loss -0.7895 +2024-11-22 09:49:27.212014: val_loss -0.7937 +2024-11-22 09:49:27.212098: Pseudo dice [0.8556] +2024-11-22 09:49:27.212173: Epoch time: 18.23 s +2024-11-22 09:49:28.049054: +2024-11-22 09:49:28.049281: Epoch 4172 +2024-11-22 09:49:28.049392: Current learning rate: 0.00515 +2024-11-22 09:49:46.127238: train_loss -0.7894 +2024-11-22 09:49:46.127548: val_loss -0.7809 +2024-11-22 09:49:46.127629: Pseudo dice [0.8515] +2024-11-22 09:49:46.127711: Epoch time: 18.08 s +2024-11-22 09:49:46.968492: +2024-11-22 09:49:46.968690: Epoch 4173 +2024-11-22 09:49:46.968802: Current learning rate: 0.00515 +2024-11-22 09:50:06.174824: train_loss -0.7967 +2024-11-22 09:50:06.175126: val_loss -0.7702 +2024-11-22 09:50:06.175205: Pseudo dice [0.8503] +2024-11-22 09:50:06.175282: Epoch time: 19.21 s +2024-11-22 09:50:07.045446: +2024-11-22 09:50:07.045673: Epoch 4174 +2024-11-22 09:50:07.045785: Current learning rate: 0.00515 +2024-11-22 09:50:25.502609: train_loss -0.7939 +2024-11-22 09:50:25.502819: val_loss -0.7834 +2024-11-22 09:50:25.502892: Pseudo dice [0.8639] +2024-11-22 09:50:25.502962: Epoch time: 18.46 s +2024-11-22 09:50:26.356679: +2024-11-22 09:50:26.356900: Epoch 4175 +2024-11-22 09:50:26.357010: Current learning rate: 0.00515 +2024-11-22 09:50:44.806637: train_loss -0.7978 +2024-11-22 09:50:44.806851: val_loss -0.7538 +2024-11-22 09:50:44.806934: Pseudo dice [0.8458] +2024-11-22 09:50:44.807014: Epoch time: 18.45 s +2024-11-22 09:50:45.652638: +2024-11-22 09:50:45.652911: Epoch 4176 +2024-11-22 09:50:45.653071: Current learning rate: 0.00515 +2024-11-22 09:51:04.375818: train_loss -0.8043 +2024-11-22 09:51:04.376033: val_loss -0.7922 +2024-11-22 09:51:04.376119: Pseudo dice [0.8702] +2024-11-22 09:51:04.376195: Epoch time: 18.72 s +2024-11-22 09:51:05.351151: +2024-11-22 09:51:05.351346: Epoch 4177 +2024-11-22 09:51:05.351456: Current learning rate: 0.00514 +2024-11-22 09:51:23.336911: train_loss -0.8018 +2024-11-22 09:51:23.337135: val_loss -0.7912 +2024-11-22 09:51:23.337211: Pseudo dice [0.8585] +2024-11-22 09:51:23.337287: Epoch time: 17.99 s +2024-11-22 09:51:24.168666: +2024-11-22 09:51:24.168870: Epoch 4178 +2024-11-22 09:51:24.168987: Current learning rate: 0.00514 +2024-11-22 09:51:43.111166: train_loss -0.7976 +2024-11-22 09:51:43.111372: val_loss -0.7639 +2024-11-22 09:51:43.111465: Pseudo dice [0.8652] +2024-11-22 09:51:43.111541: Epoch time: 18.94 s +2024-11-22 09:51:43.111626: Yayy! New best EMA pseudo Dice: 0.856 +2024-11-22 09:51:44.202156: +2024-11-22 09:51:44.202357: Epoch 4179 +2024-11-22 09:51:44.202474: Current learning rate: 0.00514 +2024-11-22 09:52:02.217688: train_loss -0.7954 +2024-11-22 09:52:02.217938: val_loss -0.7758 +2024-11-22 09:52:02.218016: Pseudo dice [0.8598] +2024-11-22 09:52:02.218101: Epoch time: 18.02 s +2024-11-22 09:52:02.218161: Yayy! New best EMA pseudo Dice: 0.8564 +2024-11-22 09:52:03.759263: +2024-11-22 09:52:03.759459: Epoch 4180 +2024-11-22 09:52:03.759568: Current learning rate: 0.00514 +2024-11-22 09:52:22.058391: train_loss -0.7904 +2024-11-22 09:52:22.058601: val_loss -0.7603 +2024-11-22 09:52:22.058674: Pseudo dice [0.8614] +2024-11-22 09:52:22.058749: Epoch time: 18.3 s +2024-11-22 09:52:22.058869: Yayy! New best EMA pseudo Dice: 0.8569 +2024-11-22 09:52:23.164983: +2024-11-22 09:52:23.165271: Epoch 4181 +2024-11-22 09:52:23.165382: Current learning rate: 0.00514 +2024-11-22 09:52:41.628017: train_loss -0.789 +2024-11-22 09:52:41.628305: val_loss -0.7672 +2024-11-22 09:52:41.628385: Pseudo dice [0.8461] +2024-11-22 09:52:41.628460: Epoch time: 18.46 s +2024-11-22 09:52:42.470278: +2024-11-22 09:52:42.470488: Epoch 4182 +2024-11-22 09:52:42.470598: Current learning rate: 0.00514 +2024-11-22 09:53:01.038891: train_loss -0.7909 +2024-11-22 09:53:01.039140: val_loss -0.7472 +2024-11-22 09:53:01.039217: Pseudo dice [0.8385] +2024-11-22 09:53:01.039298: Epoch time: 18.57 s +2024-11-22 09:53:01.882901: +2024-11-22 09:53:01.883126: Epoch 4183 +2024-11-22 09:53:01.883243: Current learning rate: 0.00514 +2024-11-22 09:53:19.587273: train_loss -0.7801 +2024-11-22 09:53:19.587509: val_loss -0.7698 +2024-11-22 09:53:19.587585: Pseudo dice [0.8465] +2024-11-22 09:53:19.587663: Epoch time: 17.71 s +2024-11-22 09:53:20.422569: +2024-11-22 09:53:20.422748: Epoch 4184 +2024-11-22 09:53:20.422906: Current learning rate: 0.00514 +2024-11-22 09:53:38.086648: train_loss -0.7791 +2024-11-22 09:53:38.086871: val_loss -0.7737 +2024-11-22 09:53:38.086948: Pseudo dice [0.8506] +2024-11-22 09:53:38.087027: Epoch time: 17.66 s +2024-11-22 09:53:39.024525: +2024-11-22 09:53:39.024709: Epoch 4185 +2024-11-22 09:53:39.024850: Current learning rate: 0.00514 +2024-11-22 09:53:56.648690: train_loss -0.7708 +2024-11-22 09:53:56.648913: val_loss -0.769 +2024-11-22 09:53:56.648993: Pseudo dice [0.8524] +2024-11-22 09:53:56.649074: Epoch time: 17.62 s +2024-11-22 09:53:57.482093: +2024-11-22 09:53:57.482292: Epoch 4186 +2024-11-22 09:53:57.482399: Current learning rate: 0.00513 +2024-11-22 09:54:15.319373: train_loss -0.7847 +2024-11-22 09:54:15.322161: val_loss -0.7729 +2024-11-22 09:54:15.322259: Pseudo dice [0.8597] +2024-11-22 09:54:15.324114: Epoch time: 17.84 s +2024-11-22 09:54:16.175422: +2024-11-22 09:54:16.175618: Epoch 4187 +2024-11-22 09:54:16.175732: Current learning rate: 0.00513 +2024-11-22 09:54:34.575744: train_loss -0.7804 +2024-11-22 09:54:34.575975: val_loss -0.7545 +2024-11-22 09:54:34.576049: Pseudo dice [0.8611] +2024-11-22 09:54:34.576134: Epoch time: 18.4 s +2024-11-22 09:54:35.407117: +2024-11-22 09:54:35.407300: Epoch 4188 +2024-11-22 09:54:35.407407: Current learning rate: 0.00513 +2024-11-22 09:54:53.408368: train_loss -0.7866 +2024-11-22 09:54:53.408601: val_loss -0.7741 +2024-11-22 09:54:53.408737: Pseudo dice [0.8482] +2024-11-22 09:54:53.408813: Epoch time: 18.0 s +2024-11-22 09:54:54.243624: +2024-11-22 09:54:54.243819: Epoch 4189 +2024-11-22 09:54:54.243929: Current learning rate: 0.00513 +2024-11-22 09:55:12.445363: train_loss -0.7829 +2024-11-22 09:55:12.445572: val_loss -0.7873 +2024-11-22 09:55:12.445649: Pseudo dice [0.8391] +2024-11-22 09:55:12.445731: Epoch time: 18.2 s +2024-11-22 09:55:13.281802: +2024-11-22 09:55:13.281962: Epoch 4190 +2024-11-22 09:55:13.282080: Current learning rate: 0.00513 +2024-11-22 09:55:31.347274: train_loss -0.788 +2024-11-22 09:55:31.347488: val_loss -0.7631 +2024-11-22 09:55:31.347563: Pseudo dice [0.8655] +2024-11-22 09:55:31.347638: Epoch time: 18.07 s +2024-11-22 09:55:32.575270: +2024-11-22 09:55:32.575487: Epoch 4191 +2024-11-22 09:55:32.575599: Current learning rate: 0.00513 +2024-11-22 09:55:51.208135: train_loss -0.7853 +2024-11-22 09:55:51.208389: val_loss -0.7751 +2024-11-22 09:55:51.208474: Pseudo dice [0.8587] +2024-11-22 09:55:51.208560: Epoch time: 18.63 s +2024-11-22 09:55:52.148886: +2024-11-22 09:55:52.149113: Epoch 4192 +2024-11-22 09:55:52.149224: Current learning rate: 0.00513 +2024-11-22 09:56:09.797382: train_loss -0.7846 +2024-11-22 09:56:09.797590: val_loss -0.7641 +2024-11-22 09:56:09.797667: Pseudo dice [0.8491] +2024-11-22 09:56:09.797742: Epoch time: 17.65 s +2024-11-22 09:56:10.631308: +2024-11-22 09:56:10.631507: Epoch 4193 +2024-11-22 09:56:10.631618: Current learning rate: 0.00513 +2024-11-22 09:56:28.424154: train_loss -0.7626 +2024-11-22 09:56:28.424378: val_loss -0.7201 +2024-11-22 09:56:28.424453: Pseudo dice [0.8281] +2024-11-22 09:56:28.424539: Epoch time: 17.79 s +2024-11-22 09:56:29.292852: +2024-11-22 09:56:29.293098: Epoch 4194 +2024-11-22 09:56:29.293213: Current learning rate: 0.00512 +2024-11-22 09:56:48.297909: train_loss -0.7703 +2024-11-22 09:56:48.298164: val_loss -0.7787 +2024-11-22 09:56:48.298260: Pseudo dice [0.8547] +2024-11-22 09:56:48.298342: Epoch time: 19.01 s +2024-11-22 09:56:49.136451: +2024-11-22 09:56:49.136679: Epoch 4195 +2024-11-22 09:56:49.136794: Current learning rate: 0.00512 +2024-11-22 09:57:07.681692: train_loss -0.7694 +2024-11-22 09:57:07.681934: val_loss -0.7581 +2024-11-22 09:57:07.682012: Pseudo dice [0.8484] +2024-11-22 09:57:07.682097: Epoch time: 18.55 s +2024-11-22 09:57:08.545829: +2024-11-22 09:57:08.546034: Epoch 4196 +2024-11-22 09:57:08.546149: Current learning rate: 0.00512 +2024-11-22 09:57:27.543999: train_loss -0.7791 +2024-11-22 09:57:27.544209: val_loss -0.765 +2024-11-22 09:57:27.544283: Pseudo dice [0.8559] +2024-11-22 09:57:27.544355: Epoch time: 19.0 s +2024-11-22 09:57:28.383500: +2024-11-22 09:57:28.383676: Epoch 4197 +2024-11-22 09:57:28.383785: Current learning rate: 0.00512 +2024-11-22 09:57:46.773430: train_loss -0.7799 +2024-11-22 09:57:46.773649: val_loss -0.7699 +2024-11-22 09:57:46.773724: Pseudo dice [0.8542] +2024-11-22 09:57:46.773802: Epoch time: 18.39 s +2024-11-22 09:57:47.612317: +2024-11-22 09:57:47.612529: Epoch 4198 +2024-11-22 09:57:47.612647: Current learning rate: 0.00512 +2024-11-22 09:58:06.220107: train_loss -0.7941 +2024-11-22 09:58:06.220333: val_loss -0.7649 +2024-11-22 09:58:06.220407: Pseudo dice [0.8464] +2024-11-22 09:58:06.220520: Epoch time: 18.61 s +2024-11-22 09:58:07.062763: +2024-11-22 09:58:07.062984: Epoch 4199 +2024-11-22 09:58:07.063097: Current learning rate: 0.00512 +2024-11-22 09:58:25.563287: train_loss -0.7884 +2024-11-22 09:58:25.563501: val_loss -0.7788 +2024-11-22 09:58:25.563579: Pseudo dice [0.856] +2024-11-22 09:58:25.563655: Epoch time: 18.5 s +2024-11-22 09:58:26.655460: +2024-11-22 09:58:26.655672: Epoch 4200 +2024-11-22 09:58:26.655789: Current learning rate: 0.00512 +2024-11-22 09:58:45.321558: train_loss -0.7864 +2024-11-22 09:58:45.321768: val_loss -0.7739 +2024-11-22 09:58:45.321842: Pseudo dice [0.8587] +2024-11-22 09:58:45.321915: Epoch time: 18.67 s +2024-11-22 09:58:46.349989: +2024-11-22 09:58:46.350198: Epoch 4201 +2024-11-22 09:58:46.350311: Current learning rate: 0.00512 +2024-11-22 09:59:04.993379: train_loss -0.8002 +2024-11-22 09:59:04.993579: val_loss -0.7774 +2024-11-22 09:59:04.993649: Pseudo dice [0.8539] +2024-11-22 09:59:04.993720: Epoch time: 18.64 s +2024-11-22 09:59:05.839332: +2024-11-22 09:59:05.839537: Epoch 4202 +2024-11-22 09:59:05.839648: Current learning rate: 0.00511 +2024-11-22 09:59:23.999622: train_loss -0.7856 +2024-11-22 09:59:24.000136: val_loss -0.7874 +2024-11-22 09:59:24.000234: Pseudo dice [0.8637] +2024-11-22 09:59:24.000312: Epoch time: 18.16 s +2024-11-22 09:59:24.834743: +2024-11-22 09:59:24.834962: Epoch 4203 +2024-11-22 09:59:24.835080: Current learning rate: 0.00511 +2024-11-22 09:59:43.519351: train_loss -0.7942 +2024-11-22 09:59:43.519593: val_loss -0.755 +2024-11-22 09:59:43.519670: Pseudo dice [0.8494] +2024-11-22 09:59:43.519742: Epoch time: 18.69 s +2024-11-22 09:59:44.351422: +2024-11-22 09:59:44.351685: Epoch 4204 +2024-11-22 09:59:44.351794: Current learning rate: 0.00511 +2024-11-22 10:00:02.186848: train_loss -0.7902 +2024-11-22 10:00:02.187070: val_loss -0.7852 +2024-11-22 10:00:02.187146: Pseudo dice [0.8557] +2024-11-22 10:00:02.187216: Epoch time: 17.84 s +2024-11-22 10:00:03.111556: +2024-11-22 10:00:03.111758: Epoch 4205 +2024-11-22 10:00:03.111869: Current learning rate: 0.00511 +2024-11-22 10:00:21.749705: train_loss -0.7933 +2024-11-22 10:00:21.750140: val_loss -0.7792 +2024-11-22 10:00:21.750239: Pseudo dice [0.8638] +2024-11-22 10:00:21.750315: Epoch time: 18.64 s +2024-11-22 10:00:22.585937: +2024-11-22 10:00:22.586122: Epoch 4206 +2024-11-22 10:00:22.586268: Current learning rate: 0.00511 +2024-11-22 10:00:40.418977: train_loss -0.7927 +2024-11-22 10:00:40.421388: val_loss -0.7596 +2024-11-22 10:00:40.421508: Pseudo dice [0.8536] +2024-11-22 10:00:40.421594: Epoch time: 17.83 s +2024-11-22 10:00:41.410882: +2024-11-22 10:00:41.411069: Epoch 4207 +2024-11-22 10:00:41.411182: Current learning rate: 0.00511 +2024-11-22 10:01:00.232264: train_loss -0.7844 +2024-11-22 10:01:00.232484: val_loss -0.7572 +2024-11-22 10:01:00.232559: Pseudo dice [0.8412] +2024-11-22 10:01:00.232635: Epoch time: 18.82 s +2024-11-22 10:01:01.176350: +2024-11-22 10:01:01.176572: Epoch 4208 +2024-11-22 10:01:01.176680: Current learning rate: 0.00511 +2024-11-22 10:01:19.382747: train_loss -0.777 +2024-11-22 10:01:19.388162: val_loss -0.7525 +2024-11-22 10:01:19.388278: Pseudo dice [0.8311] +2024-11-22 10:01:19.388356: Epoch time: 18.21 s +2024-11-22 10:01:20.306036: +2024-11-22 10:01:20.306248: Epoch 4209 +2024-11-22 10:01:20.306361: Current learning rate: 0.00511 +2024-11-22 10:01:38.927548: train_loss -0.7943 +2024-11-22 10:01:38.927762: val_loss -0.744 +2024-11-22 10:01:38.927838: Pseudo dice [0.8414] +2024-11-22 10:01:38.927917: Epoch time: 18.62 s +2024-11-22 10:01:39.851222: +2024-11-22 10:01:39.851425: Epoch 4210 +2024-11-22 10:01:39.851536: Current learning rate: 0.0051 +2024-11-22 10:01:58.958785: train_loss -0.7926 +2024-11-22 10:01:58.959028: val_loss -0.7445 +2024-11-22 10:01:58.959113: Pseudo dice [0.8543] +2024-11-22 10:01:58.959194: Epoch time: 19.11 s +2024-11-22 10:02:00.259584: +2024-11-22 10:02:00.259786: Epoch 4211 +2024-11-22 10:02:00.259896: Current learning rate: 0.0051 +2024-11-22 10:02:17.677245: train_loss -0.7919 +2024-11-22 10:02:17.677450: val_loss -0.7597 +2024-11-22 10:02:17.677526: Pseudo dice [0.8508] +2024-11-22 10:02:17.677600: Epoch time: 17.42 s +2024-11-22 10:02:18.511206: +2024-11-22 10:02:18.511410: Epoch 4212 +2024-11-22 10:02:18.511517: Current learning rate: 0.0051 +2024-11-22 10:02:36.656082: train_loss -0.7858 +2024-11-22 10:02:36.656300: val_loss -0.7731 +2024-11-22 10:02:36.656376: Pseudo dice [0.8652] +2024-11-22 10:02:36.656450: Epoch time: 18.15 s +2024-11-22 10:02:37.493078: +2024-11-22 10:02:37.493273: Epoch 4213 +2024-11-22 10:02:37.493387: Current learning rate: 0.0051 +2024-11-22 10:02:55.320620: train_loss -0.7718 +2024-11-22 10:02:55.320862: val_loss -0.7771 +2024-11-22 10:02:55.320938: Pseudo dice [0.841] +2024-11-22 10:02:55.321022: Epoch time: 17.83 s +2024-11-22 10:02:56.559234: +2024-11-22 10:02:56.559438: Epoch 4214 +2024-11-22 10:02:56.559545: Current learning rate: 0.0051 +2024-11-22 10:03:14.708168: train_loss -0.7852 +2024-11-22 10:03:14.708381: val_loss -0.755 +2024-11-22 10:03:14.708457: Pseudo dice [0.8525] +2024-11-22 10:03:14.708534: Epoch time: 18.15 s +2024-11-22 10:03:15.656119: +2024-11-22 10:03:15.656324: Epoch 4215 +2024-11-22 10:03:15.656439: Current learning rate: 0.0051 +2024-11-22 10:03:34.261893: train_loss -0.7951 +2024-11-22 10:03:34.262110: val_loss -0.7592 +2024-11-22 10:03:34.262186: Pseudo dice [0.8523] +2024-11-22 10:03:34.262261: Epoch time: 18.61 s +2024-11-22 10:03:35.096469: +2024-11-22 10:03:35.096681: Epoch 4216 +2024-11-22 10:03:35.096791: Current learning rate: 0.0051 +2024-11-22 10:03:52.629446: train_loss -0.7753 +2024-11-22 10:03:52.629735: val_loss -0.7706 +2024-11-22 10:03:52.629817: Pseudo dice [0.8592] +2024-11-22 10:03:52.629893: Epoch time: 17.53 s +2024-11-22 10:03:53.461938: +2024-11-22 10:03:53.462152: Epoch 4217 +2024-11-22 10:03:53.462263: Current learning rate: 0.0051 +2024-11-22 10:04:11.372441: train_loss -0.7806 +2024-11-22 10:04:11.372679: val_loss -0.7922 +2024-11-22 10:04:11.372760: Pseudo dice [0.8633] +2024-11-22 10:04:11.372842: Epoch time: 17.91 s +2024-11-22 10:04:12.210613: +2024-11-22 10:04:12.210814: Epoch 4218 +2024-11-22 10:04:12.210920: Current learning rate: 0.0051 +2024-11-22 10:04:30.603399: train_loss -0.7883 +2024-11-22 10:04:30.603584: val_loss -0.7547 +2024-11-22 10:04:30.603713: Pseudo dice [0.8514] +2024-11-22 10:04:30.603789: Epoch time: 18.39 s +2024-11-22 10:04:31.437540: +2024-11-22 10:04:31.437749: Epoch 4219 +2024-11-22 10:04:31.437858: Current learning rate: 0.00509 +2024-11-22 10:04:50.023276: train_loss -0.7876 +2024-11-22 10:04:50.023485: val_loss -0.7875 +2024-11-22 10:04:50.023563: Pseudo dice [0.8606] +2024-11-22 10:04:50.023635: Epoch time: 18.59 s +2024-11-22 10:04:50.853011: +2024-11-22 10:04:50.853218: Epoch 4220 +2024-11-22 10:04:50.853321: Current learning rate: 0.00509 +2024-11-22 10:05:10.075229: train_loss -0.7824 +2024-11-22 10:05:10.075451: val_loss -0.7681 +2024-11-22 10:05:10.075534: Pseudo dice [0.8557] +2024-11-22 10:05:10.075612: Epoch time: 19.22 s +2024-11-22 10:05:10.896688: +2024-11-22 10:05:10.896881: Epoch 4221 +2024-11-22 10:05:10.896989: Current learning rate: 0.00509 +2024-11-22 10:05:29.658790: train_loss -0.7851 +2024-11-22 10:05:29.664160: val_loss -0.7686 +2024-11-22 10:05:29.664344: Pseudo dice [0.854] +2024-11-22 10:05:29.664437: Epoch time: 18.76 s +2024-11-22 10:05:30.507683: +2024-11-22 10:05:30.507874: Epoch 4222 +2024-11-22 10:05:30.507981: Current learning rate: 0.00509 +2024-11-22 10:05:49.077008: train_loss -0.7878 +2024-11-22 10:05:49.077282: val_loss -0.7618 +2024-11-22 10:05:49.077363: Pseudo dice [0.8645] +2024-11-22 10:05:49.077440: Epoch time: 18.57 s +2024-11-22 10:05:49.966661: +2024-11-22 10:05:49.966835: Epoch 4223 +2024-11-22 10:05:49.966944: Current learning rate: 0.00509 +2024-11-22 10:06:08.282326: train_loss -0.79 +2024-11-22 10:06:08.282542: val_loss -0.7886 +2024-11-22 10:06:08.282618: Pseudo dice [0.8503] +2024-11-22 10:06:08.282691: Epoch time: 18.32 s +2024-11-22 10:06:09.116169: +2024-11-22 10:06:09.116381: Epoch 4224 +2024-11-22 10:06:09.116498: Current learning rate: 0.00509 +2024-11-22 10:06:26.657640: train_loss -0.7873 +2024-11-22 10:06:26.657853: val_loss -0.7807 +2024-11-22 10:06:26.657953: Pseudo dice [0.8639] +2024-11-22 10:06:26.658040: Epoch time: 17.54 s +2024-11-22 10:06:27.539192: +2024-11-22 10:06:27.539390: Epoch 4225 +2024-11-22 10:06:27.539500: Current learning rate: 0.00509 +2024-11-22 10:06:46.839217: train_loss -0.787 +2024-11-22 10:06:46.839700: val_loss -0.7718 +2024-11-22 10:06:46.839798: Pseudo dice [0.8549] +2024-11-22 10:06:46.839876: Epoch time: 19.3 s +2024-11-22 10:06:47.858068: +2024-11-22 10:06:47.858280: Epoch 4226 +2024-11-22 10:06:47.858391: Current learning rate: 0.00509 +2024-11-22 10:07:07.149028: train_loss -0.7894 +2024-11-22 10:07:07.149257: val_loss -0.7886 +2024-11-22 10:07:07.149340: Pseudo dice [0.8615] +2024-11-22 10:07:07.149420: Epoch time: 19.29 s +2024-11-22 10:07:07.988614: +2024-11-22 10:07:07.988843: Epoch 4227 +2024-11-22 10:07:07.988964: Current learning rate: 0.00508 +2024-11-22 10:07:25.528066: train_loss -0.7974 +2024-11-22 10:07:25.528286: val_loss -0.7597 +2024-11-22 10:07:25.528360: Pseudo dice [0.8502] +2024-11-22 10:07:25.528435: Epoch time: 17.54 s +2024-11-22 10:07:26.359985: +2024-11-22 10:07:26.360199: Epoch 4228 +2024-11-22 10:07:26.360311: Current learning rate: 0.00508 +2024-11-22 10:07:45.166657: train_loss -0.7896 +2024-11-22 10:07:45.166873: val_loss -0.7465 +2024-11-22 10:07:45.166950: Pseudo dice [0.8357] +2024-11-22 10:07:45.167029: Epoch time: 18.81 s +2024-11-22 10:07:46.014152: +2024-11-22 10:07:46.014361: Epoch 4229 +2024-11-22 10:07:46.014476: Current learning rate: 0.00508 +2024-11-22 10:08:04.636724: train_loss -0.7897 +2024-11-22 10:08:04.636962: val_loss -0.7637 +2024-11-22 10:08:04.637039: Pseudo dice [0.8621] +2024-11-22 10:08:04.637125: Epoch time: 18.62 s +2024-11-22 10:08:05.583291: +2024-11-22 10:08:05.583485: Epoch 4230 +2024-11-22 10:08:05.583592: Current learning rate: 0.00508 +2024-11-22 10:08:23.910794: train_loss -0.7946 +2024-11-22 10:08:23.911002: val_loss -0.7771 +2024-11-22 10:08:23.911081: Pseudo dice [0.8519] +2024-11-22 10:08:23.911156: Epoch time: 18.33 s +2024-11-22 10:08:24.748070: +2024-11-22 10:08:24.748274: Epoch 4231 +2024-11-22 10:08:24.748387: Current learning rate: 0.00508 +2024-11-22 10:08:42.420697: train_loss -0.796 +2024-11-22 10:08:42.421769: val_loss -0.7856 +2024-11-22 10:08:42.421854: Pseudo dice [0.8522] +2024-11-22 10:08:42.421929: Epoch time: 17.67 s +2024-11-22 10:08:43.270966: +2024-11-22 10:08:43.271168: Epoch 4232 +2024-11-22 10:08:43.271275: Current learning rate: 0.00508 +2024-11-22 10:09:02.857739: train_loss -0.7968 +2024-11-22 10:09:02.857951: val_loss -0.7462 +2024-11-22 10:09:02.858027: Pseudo dice [0.8638] +2024-11-22 10:09:02.858110: Epoch time: 19.59 s +2024-11-22 10:09:03.686176: +2024-11-22 10:09:03.686423: Epoch 4233 +2024-11-22 10:09:03.686574: Current learning rate: 0.00508 +2024-11-22 10:09:21.589171: train_loss -0.7948 +2024-11-22 10:09:21.589413: val_loss -0.7648 +2024-11-22 10:09:21.589491: Pseudo dice [0.8503] +2024-11-22 10:09:21.589569: Epoch time: 17.9 s +2024-11-22 10:09:22.457897: +2024-11-22 10:09:22.458074: Epoch 4234 +2024-11-22 10:09:22.458182: Current learning rate: 0.00508 +2024-11-22 10:09:40.126727: train_loss -0.7891 +2024-11-22 10:09:40.126996: val_loss -0.756 +2024-11-22 10:09:40.127096: Pseudo dice [0.8522] +2024-11-22 10:09:40.127174: Epoch time: 17.67 s +2024-11-22 10:09:40.966827: +2024-11-22 10:09:40.967034: Epoch 4235 +2024-11-22 10:09:40.967148: Current learning rate: 0.00507 +2024-11-22 10:09:59.781410: train_loss -0.7891 +2024-11-22 10:09:59.781621: val_loss -0.7839 +2024-11-22 10:09:59.781695: Pseudo dice [0.8429] +2024-11-22 10:09:59.781771: Epoch time: 18.82 s +2024-11-22 10:10:00.615529: +2024-11-22 10:10:00.615743: Epoch 4236 +2024-11-22 10:10:00.615853: Current learning rate: 0.00507 +2024-11-22 10:10:18.816752: train_loss -0.7875 +2024-11-22 10:10:18.816992: val_loss -0.7666 +2024-11-22 10:10:18.817076: Pseudo dice [0.8516] +2024-11-22 10:10:18.821587: Epoch time: 18.2 s +2024-11-22 10:10:20.103203: +2024-11-22 10:10:20.103403: Epoch 4237 +2024-11-22 10:10:20.103511: Current learning rate: 0.00507 +2024-11-22 10:10:38.631538: train_loss -0.7928 +2024-11-22 10:10:38.631792: val_loss -0.7618 +2024-11-22 10:10:38.631866: Pseudo dice [0.8523] +2024-11-22 10:10:38.631940: Epoch time: 18.53 s +2024-11-22 10:10:39.613892: +2024-11-22 10:10:39.614108: Epoch 4238 +2024-11-22 10:10:39.614219: Current learning rate: 0.00507 +2024-11-22 10:10:58.625531: train_loss -0.7862 +2024-11-22 10:10:58.625746: val_loss -0.783 +2024-11-22 10:10:58.625820: Pseudo dice [0.8489] +2024-11-22 10:10:58.625892: Epoch time: 19.01 s +2024-11-22 10:10:59.466091: +2024-11-22 10:10:59.466322: Epoch 4239 +2024-11-22 10:10:59.466432: Current learning rate: 0.00507 +2024-11-22 10:11:17.153898: train_loss -0.7801 +2024-11-22 10:11:17.154109: val_loss -0.788 +2024-11-22 10:11:17.154185: Pseudo dice [0.8517] +2024-11-22 10:11:17.154259: Epoch time: 17.69 s +2024-11-22 10:11:17.991581: +2024-11-22 10:11:17.991785: Epoch 4240 +2024-11-22 10:11:17.991895: Current learning rate: 0.00507 +2024-11-22 10:11:36.251726: train_loss -0.8018 +2024-11-22 10:11:36.251969: val_loss -0.7702 +2024-11-22 10:11:36.252046: Pseudo dice [0.8561] +2024-11-22 10:11:36.252137: Epoch time: 18.26 s +2024-11-22 10:11:37.096110: +2024-11-22 10:11:37.096319: Epoch 4241 +2024-11-22 10:11:37.096431: Current learning rate: 0.00507 +2024-11-22 10:11:55.738013: train_loss -0.7881 +2024-11-22 10:11:55.738251: val_loss -0.7791 +2024-11-22 10:11:55.738333: Pseudo dice [0.8627] +2024-11-22 10:11:55.738418: Epoch time: 18.64 s +2024-11-22 10:11:56.580417: +2024-11-22 10:11:56.580614: Epoch 4242 +2024-11-22 10:11:56.580729: Current learning rate: 0.00507 +2024-11-22 10:12:14.825583: train_loss -0.7856 +2024-11-22 10:12:14.825794: val_loss -0.7728 +2024-11-22 10:12:14.825878: Pseudo dice [0.8509] +2024-11-22 10:12:14.825957: Epoch time: 18.25 s +2024-11-22 10:12:15.663401: +2024-11-22 10:12:15.663620: Epoch 4243 +2024-11-22 10:12:15.663729: Current learning rate: 0.00506 +2024-11-22 10:12:34.946854: train_loss -0.7926 +2024-11-22 10:12:34.947083: val_loss -0.7814 +2024-11-22 10:12:34.947155: Pseudo dice [0.8408] +2024-11-22 10:12:34.947294: Epoch time: 19.28 s +2024-11-22 10:12:35.797179: +2024-11-22 10:12:35.797394: Epoch 4244 +2024-11-22 10:12:35.797504: Current learning rate: 0.00506 +2024-11-22 10:12:54.330320: train_loss -0.781 +2024-11-22 10:12:54.330549: val_loss -0.7818 +2024-11-22 10:12:54.330624: Pseudo dice [0.8485] +2024-11-22 10:12:54.330704: Epoch time: 18.53 s +2024-11-22 10:12:55.171318: +2024-11-22 10:12:55.171574: Epoch 4245 +2024-11-22 10:12:55.171689: Current learning rate: 0.00506 +2024-11-22 10:13:14.200590: train_loss -0.791 +2024-11-22 10:13:14.200799: val_loss -0.7613 +2024-11-22 10:13:14.200871: Pseudo dice [0.8354] +2024-11-22 10:13:14.200944: Epoch time: 19.03 s +2024-11-22 10:13:15.036879: +2024-11-22 10:13:15.037080: Epoch 4246 +2024-11-22 10:13:15.037195: Current learning rate: 0.00506 +2024-11-22 10:13:33.543571: train_loss -0.8021 +2024-11-22 10:13:33.543790: val_loss -0.7793 +2024-11-22 10:13:33.543867: Pseudo dice [0.8668] +2024-11-22 10:13:33.543942: Epoch time: 18.51 s +2024-11-22 10:13:34.387679: +2024-11-22 10:13:34.387880: Epoch 4247 +2024-11-22 10:13:34.387993: Current learning rate: 0.00506 +2024-11-22 10:13:52.890965: train_loss -0.7762 +2024-11-22 10:13:52.891186: val_loss -0.7988 +2024-11-22 10:13:52.891263: Pseudo dice [0.8628] +2024-11-22 10:13:52.891340: Epoch time: 18.5 s +2024-11-22 10:13:53.802695: +2024-11-22 10:13:53.802950: Epoch 4248 +2024-11-22 10:13:53.803118: Current learning rate: 0.00506 +2024-11-22 10:14:12.833829: train_loss -0.7891 +2024-11-22 10:14:12.834295: val_loss -0.7861 +2024-11-22 10:14:12.834389: Pseudo dice [0.8511] +2024-11-22 10:14:12.834466: Epoch time: 19.03 s +2024-11-22 10:14:13.854849: +2024-11-22 10:14:13.855093: Epoch 4249 +2024-11-22 10:14:13.855205: Current learning rate: 0.00506 +2024-11-22 10:14:32.863743: train_loss -0.7859 +2024-11-22 10:14:32.863961: val_loss -0.7659 +2024-11-22 10:14:32.864037: Pseudo dice [0.8471] +2024-11-22 10:14:32.864118: Epoch time: 19.01 s +2024-11-22 10:14:34.054853: +2024-11-22 10:14:34.055051: Epoch 4250 +2024-11-22 10:14:34.055163: Current learning rate: 0.00506 +2024-11-22 10:14:52.123165: train_loss -0.7947 +2024-11-22 10:14:52.123384: val_loss -0.7853 +2024-11-22 10:14:52.123461: Pseudo dice [0.8604] +2024-11-22 10:14:52.123537: Epoch time: 18.07 s +2024-11-22 10:14:52.965566: +2024-11-22 10:14:52.965778: Epoch 4251 +2024-11-22 10:14:52.965891: Current learning rate: 0.00506 +2024-11-22 10:15:11.213696: train_loss -0.7989 +2024-11-22 10:15:11.213961: val_loss -0.7699 +2024-11-22 10:15:11.214036: Pseudo dice [0.8472] +2024-11-22 10:15:11.214118: Epoch time: 18.25 s +2024-11-22 10:15:12.061030: +2024-11-22 10:15:12.061277: Epoch 4252 +2024-11-22 10:15:12.061408: Current learning rate: 0.00505 +2024-11-22 10:15:29.873781: train_loss -0.794 +2024-11-22 10:15:29.874075: val_loss -0.7892 +2024-11-22 10:15:29.874158: Pseudo dice [0.862] +2024-11-22 10:15:29.874234: Epoch time: 17.81 s +2024-11-22 10:15:30.716088: +2024-11-22 10:15:30.716318: Epoch 4253 +2024-11-22 10:15:30.716429: Current learning rate: 0.00505 +2024-11-22 10:15:49.332572: train_loss -0.7834 +2024-11-22 10:15:49.332788: val_loss -0.746 +2024-11-22 10:15:49.332909: Pseudo dice [0.8538] +2024-11-22 10:15:49.332987: Epoch time: 18.62 s +2024-11-22 10:15:50.278083: +2024-11-22 10:15:50.278306: Epoch 4254 +2024-11-22 10:15:50.278415: Current learning rate: 0.00505 +2024-11-22 10:16:09.157459: train_loss -0.7921 +2024-11-22 10:16:09.157674: val_loss -0.7793 +2024-11-22 10:16:09.157754: Pseudo dice [0.8646] +2024-11-22 10:16:09.157831: Epoch time: 18.88 s +2024-11-22 10:16:10.038267: +2024-11-22 10:16:10.038457: Epoch 4255 +2024-11-22 10:16:10.038576: Current learning rate: 0.00505 +2024-11-22 10:16:28.724028: train_loss -0.7841 +2024-11-22 10:16:28.724275: val_loss -0.7629 +2024-11-22 10:16:28.724352: Pseudo dice [0.8479] +2024-11-22 10:16:28.724433: Epoch time: 18.69 s +2024-11-22 10:16:29.568923: +2024-11-22 10:16:29.569123: Epoch 4256 +2024-11-22 10:16:29.569237: Current learning rate: 0.00505 +2024-11-22 10:16:47.076586: train_loss -0.7853 +2024-11-22 10:16:47.076795: val_loss -0.7742 +2024-11-22 10:16:47.076867: Pseudo dice [0.8523] +2024-11-22 10:16:47.076943: Epoch time: 17.51 s +2024-11-22 10:16:47.925615: +2024-11-22 10:16:47.925833: Epoch 4257 +2024-11-22 10:16:47.925945: Current learning rate: 0.00505 +2024-11-22 10:17:06.860245: train_loss -0.7948 +2024-11-22 10:17:06.860693: val_loss -0.7605 +2024-11-22 10:17:06.860782: Pseudo dice [0.8518] +2024-11-22 10:17:06.860858: Epoch time: 18.94 s +2024-11-22 10:17:07.695072: +2024-11-22 10:17:07.695288: Epoch 4258 +2024-11-22 10:17:07.695408: Current learning rate: 0.00505 +2024-11-22 10:17:25.593129: train_loss -0.798 +2024-11-22 10:17:25.593343: val_loss -0.7825 +2024-11-22 10:17:25.593418: Pseudo dice [0.8614] +2024-11-22 10:17:25.593496: Epoch time: 17.9 s +2024-11-22 10:17:26.456489: +2024-11-22 10:17:26.456694: Epoch 4259 +2024-11-22 10:17:26.456805: Current learning rate: 0.00505 +2024-11-22 10:17:44.273817: train_loss -0.7898 +2024-11-22 10:17:44.274054: val_loss -0.7499 +2024-11-22 10:17:44.274140: Pseudo dice [0.8441] +2024-11-22 10:17:44.274225: Epoch time: 17.82 s +2024-11-22 10:17:45.520916: +2024-11-22 10:17:45.521144: Epoch 4260 +2024-11-22 10:17:45.521254: Current learning rate: 0.00504 +2024-11-22 10:18:02.767732: train_loss -0.7836 +2024-11-22 10:18:02.767949: val_loss -0.7875 +2024-11-22 10:18:02.768025: Pseudo dice [0.8421] +2024-11-22 10:18:02.768110: Epoch time: 17.25 s +2024-11-22 10:18:03.719003: +2024-11-22 10:18:03.719236: Epoch 4261 +2024-11-22 10:18:03.719348: Current learning rate: 0.00504 +2024-11-22 10:18:21.164564: train_loss -0.7867 +2024-11-22 10:18:21.164780: val_loss -0.7772 +2024-11-22 10:18:21.164856: Pseudo dice [0.8503] +2024-11-22 10:18:21.164927: Epoch time: 17.45 s +2024-11-22 10:18:22.003628: +2024-11-22 10:18:22.003840: Epoch 4262 +2024-11-22 10:18:22.003949: Current learning rate: 0.00504 +2024-11-22 10:18:40.959598: train_loss -0.7887 +2024-11-22 10:18:40.959819: val_loss -0.7924 +2024-11-22 10:18:40.959896: Pseudo dice [0.8538] +2024-11-22 10:18:40.959973: Epoch time: 18.96 s +2024-11-22 10:18:41.810288: +2024-11-22 10:18:41.810484: Epoch 4263 +2024-11-22 10:18:41.810596: Current learning rate: 0.00504 +2024-11-22 10:19:00.443637: train_loss -0.7902 +2024-11-22 10:19:00.443884: val_loss -0.7612 +2024-11-22 10:19:00.443963: Pseudo dice [0.8485] +2024-11-22 10:19:00.444042: Epoch time: 18.63 s +2024-11-22 10:19:01.283761: +2024-11-22 10:19:01.283972: Epoch 4264 +2024-11-22 10:19:01.284093: Current learning rate: 0.00504 +2024-11-22 10:19:19.414956: train_loss -0.7923 +2024-11-22 10:19:19.415234: val_loss -0.7768 +2024-11-22 10:19:19.415310: Pseudo dice [0.8591] +2024-11-22 10:19:19.415383: Epoch time: 18.13 s +2024-11-22 10:19:20.346164: +2024-11-22 10:19:20.346400: Epoch 4265 +2024-11-22 10:19:20.346511: Current learning rate: 0.00504 +2024-11-22 10:19:39.992273: train_loss -0.7909 +2024-11-22 10:19:39.992481: val_loss -0.7779 +2024-11-22 10:19:39.992555: Pseudo dice [0.8481] +2024-11-22 10:19:39.992628: Epoch time: 19.65 s +2024-11-22 10:19:40.831287: +2024-11-22 10:19:40.831493: Epoch 4266 +2024-11-22 10:19:40.831613: Current learning rate: 0.00504 +2024-11-22 10:19:59.165401: train_loss -0.7926 +2024-11-22 10:19:59.165648: val_loss -0.7678 +2024-11-22 10:19:59.165728: Pseudo dice [0.8486] +2024-11-22 10:19:59.165810: Epoch time: 18.33 s +2024-11-22 10:20:00.009893: +2024-11-22 10:20:00.010096: Epoch 4267 +2024-11-22 10:20:00.010212: Current learning rate: 0.00504 +2024-11-22 10:20:19.252884: train_loss -0.7944 +2024-11-22 10:20:19.253096: val_loss -0.7579 +2024-11-22 10:20:19.255324: Pseudo dice [0.8529] +2024-11-22 10:20:19.255416: Epoch time: 19.24 s +2024-11-22 10:20:20.128359: +2024-11-22 10:20:20.128555: Epoch 4268 +2024-11-22 10:20:20.128667: Current learning rate: 0.00503 +2024-11-22 10:20:40.489323: train_loss -0.7879 +2024-11-22 10:20:40.489537: val_loss -0.7662 +2024-11-22 10:20:40.489618: Pseudo dice [0.8516] +2024-11-22 10:20:40.489695: Epoch time: 20.36 s +2024-11-22 10:20:41.326345: +2024-11-22 10:20:41.326544: Epoch 4269 +2024-11-22 10:20:41.326658: Current learning rate: 0.00503 +2024-11-22 10:20:59.788513: train_loss -0.7887 +2024-11-22 10:20:59.788754: val_loss -0.7918 +2024-11-22 10:20:59.788836: Pseudo dice [0.8594] +2024-11-22 10:20:59.788936: Epoch time: 18.46 s +2024-11-22 10:21:00.627803: +2024-11-22 10:21:00.628026: Epoch 4270 +2024-11-22 10:21:00.628154: Current learning rate: 0.00503 +2024-11-22 10:21:19.391004: train_loss -0.7948 +2024-11-22 10:21:19.391253: val_loss -0.7828 +2024-11-22 10:21:19.391325: Pseudo dice [0.8554] +2024-11-22 10:21:19.391404: Epoch time: 18.76 s +2024-11-22 10:21:20.230832: +2024-11-22 10:21:20.231030: Epoch 4271 +2024-11-22 10:21:20.231145: Current learning rate: 0.00503 +2024-11-22 10:21:38.201568: train_loss -0.7901 +2024-11-22 10:21:38.202160: val_loss -0.7732 +2024-11-22 10:21:38.202258: Pseudo dice [0.8482] +2024-11-22 10:21:38.202334: Epoch time: 17.97 s +2024-11-22 10:21:39.043801: +2024-11-22 10:21:39.044012: Epoch 4272 +2024-11-22 10:21:39.044128: Current learning rate: 0.00503 +2024-11-22 10:21:56.159838: train_loss -0.7759 +2024-11-22 10:21:56.160298: val_loss -0.7702 +2024-11-22 10:21:56.160397: Pseudo dice [0.8546] +2024-11-22 10:21:56.160475: Epoch time: 17.12 s +2024-11-22 10:21:56.995674: +2024-11-22 10:21:56.995897: Epoch 4273 +2024-11-22 10:21:56.996009: Current learning rate: 0.00503 +2024-11-22 10:22:14.821260: train_loss -0.785 +2024-11-22 10:22:14.821499: val_loss -0.7578 +2024-11-22 10:22:14.821571: Pseudo dice [0.8558] +2024-11-22 10:22:14.821652: Epoch time: 17.83 s +2024-11-22 10:22:15.678588: +2024-11-22 10:22:15.678831: Epoch 4274 +2024-11-22 10:22:15.678945: Current learning rate: 0.00503 +2024-11-22 10:22:34.235191: train_loss -0.7865 +2024-11-22 10:22:34.235404: val_loss -0.7597 +2024-11-22 10:22:34.235478: Pseudo dice [0.8455] +2024-11-22 10:22:34.235552: Epoch time: 18.56 s +2024-11-22 10:22:35.077211: +2024-11-22 10:22:35.077434: Epoch 4275 +2024-11-22 10:22:35.077543: Current learning rate: 0.00503 +2024-11-22 10:22:52.338802: train_loss -0.792 +2024-11-22 10:22:52.339009: val_loss -0.7485 +2024-11-22 10:22:52.339110: Pseudo dice [0.8423] +2024-11-22 10:22:52.339187: Epoch time: 17.26 s +2024-11-22 10:22:53.174735: +2024-11-22 10:22:53.174936: Epoch 4276 +2024-11-22 10:22:53.175047: Current learning rate: 0.00502 +2024-11-22 10:23:12.475400: train_loss -0.7873 +2024-11-22 10:23:12.475608: val_loss -0.7736 +2024-11-22 10:23:12.475679: Pseudo dice [0.8622] +2024-11-22 10:23:12.475754: Epoch time: 19.3 s +2024-11-22 10:23:13.315443: +2024-11-22 10:23:13.315635: Epoch 4277 +2024-11-22 10:23:13.315749: Current learning rate: 0.00502 +2024-11-22 10:23:31.699667: train_loss -0.7855 +2024-11-22 10:23:31.699913: val_loss -0.7251 +2024-11-22 10:23:31.699988: Pseudo dice [0.8333] +2024-11-22 10:23:31.700074: Epoch time: 18.39 s +2024-11-22 10:23:32.541347: +2024-11-22 10:23:32.541569: Epoch 4278 +2024-11-22 10:23:32.541687: Current learning rate: 0.00502 +2024-11-22 10:23:50.544583: train_loss -0.791 +2024-11-22 10:23:50.544790: val_loss -0.781 +2024-11-22 10:23:50.544863: Pseudo dice [0.8529] +2024-11-22 10:23:50.544935: Epoch time: 18.0 s +2024-11-22 10:23:51.410537: +2024-11-22 10:23:51.410729: Epoch 4279 +2024-11-22 10:23:51.410839: Current learning rate: 0.00502 +2024-11-22 10:24:09.488283: train_loss -0.7895 +2024-11-22 10:24:09.488494: val_loss -0.7682 +2024-11-22 10:24:09.488574: Pseudo dice [0.8398] +2024-11-22 10:24:09.488652: Epoch time: 18.08 s +2024-11-22 10:24:10.328939: +2024-11-22 10:24:10.329155: Epoch 4280 +2024-11-22 10:24:10.329267: Current learning rate: 0.00502 +2024-11-22 10:24:29.100542: train_loss -0.7857 +2024-11-22 10:24:29.100748: val_loss -0.7883 +2024-11-22 10:24:29.100823: Pseudo dice [0.866] +2024-11-22 10:24:29.100899: Epoch time: 18.77 s +2024-11-22 10:24:29.934933: +2024-11-22 10:24:29.935114: Epoch 4281 +2024-11-22 10:24:29.935221: Current learning rate: 0.00502 +2024-11-22 10:24:49.788675: train_loss -0.7803 +2024-11-22 10:24:49.788903: val_loss -0.7696 +2024-11-22 10:24:49.788985: Pseudo dice [0.8412] +2024-11-22 10:24:49.789070: Epoch time: 19.85 s +2024-11-22 10:24:50.643207: +2024-11-22 10:24:50.643457: Epoch 4282 +2024-11-22 10:24:50.643566: Current learning rate: 0.00502 +2024-11-22 10:25:08.566787: train_loss -0.7795 +2024-11-22 10:25:08.566997: val_loss -0.7883 +2024-11-22 10:25:08.568415: Pseudo dice [0.8565] +2024-11-22 10:25:08.570806: Epoch time: 17.92 s +2024-11-22 10:25:09.843959: +2024-11-22 10:25:09.844185: Epoch 4283 +2024-11-22 10:25:09.844299: Current learning rate: 0.00502 +2024-11-22 10:25:28.332871: train_loss -0.7881 +2024-11-22 10:25:28.333094: val_loss -0.7593 +2024-11-22 10:25:28.333170: Pseudo dice [0.8423] +2024-11-22 10:25:28.333242: Epoch time: 18.49 s +2024-11-22 10:25:29.169647: +2024-11-22 10:25:29.169868: Epoch 4284 +2024-11-22 10:25:29.169984: Current learning rate: 0.00502 +2024-11-22 10:25:47.058548: train_loss -0.7871 +2024-11-22 10:25:47.058767: val_loss -0.76 +2024-11-22 10:25:47.058849: Pseudo dice [0.843] +2024-11-22 10:25:47.058927: Epoch time: 17.89 s +2024-11-22 10:25:47.896886: +2024-11-22 10:25:47.897101: Epoch 4285 +2024-11-22 10:25:47.897210: Current learning rate: 0.00501 +2024-11-22 10:26:05.978833: train_loss -0.7804 +2024-11-22 10:26:05.984275: val_loss -0.7714 +2024-11-22 10:26:05.984387: Pseudo dice [0.8611] +2024-11-22 10:26:05.984472: Epoch time: 18.08 s +2024-11-22 10:26:06.963457: +2024-11-22 10:26:06.963658: Epoch 4286 +2024-11-22 10:26:06.963772: Current learning rate: 0.00501 +2024-11-22 10:26:24.719434: train_loss -0.7893 +2024-11-22 10:26:24.719651: val_loss -0.7965 +2024-11-22 10:26:24.719729: Pseudo dice [0.8538] +2024-11-22 10:26:24.719804: Epoch time: 17.76 s +2024-11-22 10:26:25.553763: +2024-11-22 10:26:25.554023: Epoch 4287 +2024-11-22 10:26:25.554143: Current learning rate: 0.00501 +2024-11-22 10:26:44.499701: train_loss -0.796 +2024-11-22 10:26:44.499918: val_loss -0.7502 +2024-11-22 10:26:44.499994: Pseudo dice [0.8453] +2024-11-22 10:26:44.500074: Epoch time: 18.95 s +2024-11-22 10:26:45.341415: +2024-11-22 10:26:45.341622: Epoch 4288 +2024-11-22 10:26:45.341740: Current learning rate: 0.00501 +2024-11-22 10:27:03.339520: train_loss -0.7892 +2024-11-22 10:27:03.339725: val_loss -0.768 +2024-11-22 10:27:03.339800: Pseudo dice [0.8553] +2024-11-22 10:27:03.339875: Epoch time: 18.0 s +2024-11-22 10:27:04.180364: +2024-11-22 10:27:04.180582: Epoch 4289 +2024-11-22 10:27:04.180695: Current learning rate: 0.00501 +2024-11-22 10:27:22.567632: train_loss -0.7905 +2024-11-22 10:27:22.567892: val_loss -0.7812 +2024-11-22 10:27:22.567968: Pseudo dice [0.8625] +2024-11-22 10:27:22.568050: Epoch time: 18.39 s +2024-11-22 10:27:23.408081: +2024-11-22 10:27:23.408279: Epoch 4290 +2024-11-22 10:27:23.408395: Current learning rate: 0.00501 +2024-11-22 10:27:42.009546: train_loss -0.7824 +2024-11-22 10:27:42.009752: val_loss -0.7783 +2024-11-22 10:27:42.009824: Pseudo dice [0.8516] +2024-11-22 10:27:42.009898: Epoch time: 18.6 s +2024-11-22 10:27:42.851486: +2024-11-22 10:27:42.851705: Epoch 4291 +2024-11-22 10:27:42.851815: Current learning rate: 0.00501 +2024-11-22 10:28:00.971201: train_loss -0.7839 +2024-11-22 10:28:00.971419: val_loss -0.7741 +2024-11-22 10:28:00.971494: Pseudo dice [0.8578] +2024-11-22 10:28:00.971570: Epoch time: 18.12 s +2024-11-22 10:28:01.827534: +2024-11-22 10:28:01.827761: Epoch 4292 +2024-11-22 10:28:01.827872: Current learning rate: 0.00501 +2024-11-22 10:28:20.596174: train_loss -0.7833 +2024-11-22 10:28:20.596392: val_loss -0.7539 +2024-11-22 10:28:20.596472: Pseudo dice [0.8463] +2024-11-22 10:28:20.596550: Epoch time: 18.77 s +2024-11-22 10:28:21.528701: +2024-11-22 10:28:21.528900: Epoch 4293 +2024-11-22 10:28:21.529018: Current learning rate: 0.005 +2024-11-22 10:28:39.670264: train_loss -0.7876 +2024-11-22 10:28:39.670498: val_loss -0.7788 +2024-11-22 10:28:39.670573: Pseudo dice [0.8555] +2024-11-22 10:28:39.670650: Epoch time: 18.14 s +2024-11-22 10:28:40.532644: +2024-11-22 10:28:40.532839: Epoch 4294 +2024-11-22 10:28:40.532949: Current learning rate: 0.005 +2024-11-22 10:28:59.305547: train_loss -0.7859 +2024-11-22 10:28:59.306002: val_loss -0.7717 +2024-11-22 10:28:59.306109: Pseudo dice [0.8542] +2024-11-22 10:28:59.306182: Epoch time: 18.77 s +2024-11-22 10:29:00.138399: +2024-11-22 10:29:00.138598: Epoch 4295 +2024-11-22 10:29:00.138707: Current learning rate: 0.005 +2024-11-22 10:29:18.718616: train_loss -0.7923 +2024-11-22 10:29:18.718842: val_loss -0.7368 +2024-11-22 10:29:18.718922: Pseudo dice [0.8541] +2024-11-22 10:29:18.719001: Epoch time: 18.58 s +2024-11-22 10:29:19.555225: +2024-11-22 10:29:19.555454: Epoch 4296 +2024-11-22 10:29:19.555562: Current learning rate: 0.005 +2024-11-22 10:29:38.274837: train_loss -0.7849 +2024-11-22 10:29:38.275087: val_loss -0.7337 +2024-11-22 10:29:38.275167: Pseudo dice [0.8443] +2024-11-22 10:29:38.275255: Epoch time: 18.72 s +2024-11-22 10:29:39.113826: +2024-11-22 10:29:39.114044: Epoch 4297 +2024-11-22 10:29:39.114160: Current learning rate: 0.005 +2024-11-22 10:29:58.543918: train_loss -0.7836 +2024-11-22 10:29:58.544139: val_loss -0.7595 +2024-11-22 10:29:58.544215: Pseudo dice [0.8536] +2024-11-22 10:29:58.544289: Epoch time: 19.43 s +2024-11-22 10:29:59.386024: +2024-11-22 10:29:59.386254: Epoch 4298 +2024-11-22 10:29:59.386368: Current learning rate: 0.005 +2024-11-22 10:30:18.306469: train_loss -0.7825 +2024-11-22 10:30:18.306676: val_loss -0.7565 +2024-11-22 10:30:18.306755: Pseudo dice [0.8479] +2024-11-22 10:30:18.306832: Epoch time: 18.92 s +2024-11-22 10:30:19.140995: +2024-11-22 10:30:19.141185: Epoch 4299 +2024-11-22 10:30:19.141295: Current learning rate: 0.005 +2024-11-22 10:30:36.831879: train_loss -0.795 +2024-11-22 10:30:36.832099: val_loss -0.7582 +2024-11-22 10:30:36.832174: Pseudo dice [0.8489] +2024-11-22 10:30:36.832247: Epoch time: 17.69 s +2024-11-22 10:30:37.988617: +2024-11-22 10:30:37.988839: Epoch 4300 +2024-11-22 10:30:37.988952: Current learning rate: 0.005 +2024-11-22 10:30:56.628305: train_loss -0.7889 +2024-11-22 10:30:56.628553: val_loss -0.7641 +2024-11-22 10:30:56.628634: Pseudo dice [0.8562] +2024-11-22 10:30:56.628725: Epoch time: 18.64 s +2024-11-22 10:30:57.470282: +2024-11-22 10:30:57.470480: Epoch 4301 +2024-11-22 10:30:57.470589: Current learning rate: 0.00499 +2024-11-22 10:31:14.967911: train_loss -0.7908 +2024-11-22 10:31:14.968120: val_loss -0.785 +2024-11-22 10:31:14.968199: Pseudo dice [0.8538] +2024-11-22 10:31:14.968274: Epoch time: 17.5 s +2024-11-22 10:31:15.829156: +2024-11-22 10:31:15.829351: Epoch 4302 +2024-11-22 10:31:15.829463: Current learning rate: 0.00499 +2024-11-22 10:31:34.522099: train_loss -0.7914 +2024-11-22 10:31:34.522313: val_loss -0.7675 +2024-11-22 10:31:34.522386: Pseudo dice [0.8534] +2024-11-22 10:31:34.522460: Epoch time: 18.69 s +2024-11-22 10:31:35.360956: +2024-11-22 10:31:35.361157: Epoch 4303 +2024-11-22 10:31:35.361266: Current learning rate: 0.00499 +2024-11-22 10:31:53.329138: train_loss -0.7898 +2024-11-22 10:31:53.329373: val_loss -0.7774 +2024-11-22 10:31:53.329449: Pseudo dice [0.849] +2024-11-22 10:31:53.329531: Epoch time: 17.97 s +2024-11-22 10:31:54.169686: +2024-11-22 10:31:54.169885: Epoch 4304 +2024-11-22 10:31:54.169993: Current learning rate: 0.00499 +2024-11-22 10:32:11.496099: train_loss -0.7831 +2024-11-22 10:32:11.496312: val_loss -0.7666 +2024-11-22 10:32:11.496390: Pseudo dice [0.8535] +2024-11-22 10:32:11.496466: Epoch time: 17.33 s +2024-11-22 10:32:12.407820: +2024-11-22 10:32:12.408034: Epoch 4305 +2024-11-22 10:32:12.408155: Current learning rate: 0.00499 +2024-11-22 10:32:30.912113: train_loss -0.7882 +2024-11-22 10:32:30.912321: val_loss -0.7921 +2024-11-22 10:32:30.912397: Pseudo dice [0.8568] +2024-11-22 10:32:30.912473: Epoch time: 18.51 s +2024-11-22 10:32:32.165870: +2024-11-22 10:32:32.166090: Epoch 4306 +2024-11-22 10:32:32.166200: Current learning rate: 0.00499 +2024-11-22 10:32:52.239161: train_loss -0.7933 +2024-11-22 10:32:52.239384: val_loss -0.7635 +2024-11-22 10:32:52.239462: Pseudo dice [0.8439] +2024-11-22 10:32:52.239544: Epoch time: 20.07 s +2024-11-22 10:32:53.074180: +2024-11-22 10:32:53.074381: Epoch 4307 +2024-11-22 10:32:53.074492: Current learning rate: 0.00499 +2024-11-22 10:33:11.325541: train_loss -0.7924 +2024-11-22 10:33:11.325773: val_loss -0.7597 +2024-11-22 10:33:11.325850: Pseudo dice [0.8414] +2024-11-22 10:33:11.326022: Epoch time: 18.25 s +2024-11-22 10:33:12.183838: +2024-11-22 10:33:12.184049: Epoch 4308 +2024-11-22 10:33:12.184164: Current learning rate: 0.00499 +2024-11-22 10:33:31.186487: train_loss -0.786 +2024-11-22 10:33:31.186699: val_loss -0.766 +2024-11-22 10:33:31.186815: Pseudo dice [0.8568] +2024-11-22 10:33:31.186891: Epoch time: 19.0 s +2024-11-22 10:33:32.021634: +2024-11-22 10:33:32.021849: Epoch 4309 +2024-11-22 10:33:32.021958: Current learning rate: 0.00498 +2024-11-22 10:33:51.814348: train_loss -0.7896 +2024-11-22 10:33:51.814558: val_loss -0.7766 +2024-11-22 10:33:51.814632: Pseudo dice [0.8462] +2024-11-22 10:33:51.814705: Epoch time: 19.79 s +2024-11-22 10:33:52.653204: +2024-11-22 10:33:52.653404: Epoch 4310 +2024-11-22 10:33:52.653514: Current learning rate: 0.00498 +2024-11-22 10:34:12.383140: train_loss -0.7969 +2024-11-22 10:34:12.383344: val_loss -0.792 +2024-11-22 10:34:12.383420: Pseudo dice [0.8628] +2024-11-22 10:34:12.383498: Epoch time: 19.73 s +2024-11-22 10:34:13.218770: +2024-11-22 10:34:13.219014: Epoch 4311 +2024-11-22 10:34:13.219185: Current learning rate: 0.00498 +2024-11-22 10:34:31.515050: train_loss -0.7888 +2024-11-22 10:34:31.515265: val_loss -0.7561 +2024-11-22 10:34:31.515341: Pseudo dice [0.8335] +2024-11-22 10:34:31.515420: Epoch time: 18.3 s +2024-11-22 10:34:32.359598: +2024-11-22 10:34:32.359842: Epoch 4312 +2024-11-22 10:34:32.359955: Current learning rate: 0.00498 +2024-11-22 10:34:51.077023: train_loss -0.7828 +2024-11-22 10:34:51.077235: val_loss -0.7651 +2024-11-22 10:34:51.077312: Pseudo dice [0.8508] +2024-11-22 10:34:51.077389: Epoch time: 18.72 s +2024-11-22 10:34:52.154805: +2024-11-22 10:34:52.155017: Epoch 4313 +2024-11-22 10:34:52.155138: Current learning rate: 0.00498 +2024-11-22 10:35:10.946716: train_loss -0.7738 +2024-11-22 10:35:10.946923: val_loss -0.7516 +2024-11-22 10:35:10.947000: Pseudo dice [0.8422] +2024-11-22 10:35:10.947091: Epoch time: 18.79 s +2024-11-22 10:35:11.891383: +2024-11-22 10:35:11.891554: Epoch 4314 +2024-11-22 10:35:11.891662: Current learning rate: 0.00498 +2024-11-22 10:35:31.562945: train_loss -0.7721 +2024-11-22 10:35:31.563180: val_loss -0.7676 +2024-11-22 10:35:31.563260: Pseudo dice [0.8607] +2024-11-22 10:35:31.563341: Epoch time: 19.67 s +2024-11-22 10:35:32.547954: +2024-11-22 10:35:32.548182: Epoch 4315 +2024-11-22 10:35:32.548295: Current learning rate: 0.00498 +2024-11-22 10:35:51.842003: train_loss -0.7774 +2024-11-22 10:35:51.842231: val_loss -0.7639 +2024-11-22 10:35:51.842307: Pseudo dice [0.844] +2024-11-22 10:35:51.842382: Epoch time: 19.29 s +2024-11-22 10:35:52.675383: +2024-11-22 10:35:52.675567: Epoch 4316 +2024-11-22 10:35:52.675677: Current learning rate: 0.00498 +2024-11-22 10:36:11.121598: train_loss -0.7925 +2024-11-22 10:36:11.121808: val_loss -0.7636 +2024-11-22 10:36:11.121995: Pseudo dice [0.8588] +2024-11-22 10:36:11.122079: Epoch time: 18.45 s +2024-11-22 10:36:11.956433: +2024-11-22 10:36:11.956652: Epoch 4317 +2024-11-22 10:36:11.956764: Current learning rate: 0.00498 +2024-11-22 10:36:30.188211: train_loss -0.7913 +2024-11-22 10:36:30.188667: val_loss -0.7662 +2024-11-22 10:36:30.188762: Pseudo dice [0.8527] +2024-11-22 10:36:30.188838: Epoch time: 18.23 s +2024-11-22 10:36:31.021052: +2024-11-22 10:36:31.021261: Epoch 4318 +2024-11-22 10:36:31.021370: Current learning rate: 0.00497 +2024-11-22 10:36:49.786234: train_loss -0.7931 +2024-11-22 10:36:49.786524: val_loss -0.765 +2024-11-22 10:36:49.786613: Pseudo dice [0.8588] +2024-11-22 10:36:49.786696: Epoch time: 18.77 s +2024-11-22 10:36:50.624355: +2024-11-22 10:36:50.624578: Epoch 4319 +2024-11-22 10:36:50.624686: Current learning rate: 0.00497 +2024-11-22 10:37:09.051795: train_loss -0.7852 +2024-11-22 10:37:09.051999: val_loss -0.7767 +2024-11-22 10:37:09.052080: Pseudo dice [0.8472] +2024-11-22 10:37:09.052155: Epoch time: 18.43 s +2024-11-22 10:37:09.891118: +2024-11-22 10:37:09.891335: Epoch 4320 +2024-11-22 10:37:09.891456: Current learning rate: 0.00497 +2024-11-22 10:37:28.122867: train_loss -0.7868 +2024-11-22 10:37:28.123108: val_loss -0.7702 +2024-11-22 10:37:28.123188: Pseudo dice [0.8594] +2024-11-22 10:37:28.123264: Epoch time: 18.23 s +2024-11-22 10:37:28.984889: +2024-11-22 10:37:28.985103: Epoch 4321 +2024-11-22 10:37:28.985215: Current learning rate: 0.00497 +2024-11-22 10:37:48.872476: train_loss -0.784 +2024-11-22 10:37:48.872720: val_loss -0.7734 +2024-11-22 10:37:48.872797: Pseudo dice [0.8501] +2024-11-22 10:37:48.872879: Epoch time: 19.89 s +2024-11-22 10:37:49.714040: +2024-11-22 10:37:49.714268: Epoch 4322 +2024-11-22 10:37:49.714381: Current learning rate: 0.00497 +2024-11-22 10:38:08.767276: train_loss -0.7865 +2024-11-22 10:38:08.767486: val_loss -0.766 +2024-11-22 10:38:08.767580: Pseudo dice [0.8486] +2024-11-22 10:38:08.767660: Epoch time: 19.05 s +2024-11-22 10:38:09.607057: +2024-11-22 10:38:09.607283: Epoch 4323 +2024-11-22 10:38:09.607395: Current learning rate: 0.00497 +2024-11-22 10:38:27.120216: train_loss -0.788 +2024-11-22 10:38:27.126924: val_loss -0.7755 +2024-11-22 10:38:27.127022: Pseudo dice [0.8595] +2024-11-22 10:38:27.127105: Epoch time: 17.51 s +2024-11-22 10:38:28.055664: +2024-11-22 10:38:28.055858: Epoch 4324 +2024-11-22 10:38:28.055970: Current learning rate: 0.00497 +2024-11-22 10:38:45.946705: train_loss -0.7911 +2024-11-22 10:38:45.946918: val_loss -0.7698 +2024-11-22 10:38:45.946993: Pseudo dice [0.8449] +2024-11-22 10:38:45.947071: Epoch time: 17.89 s +2024-11-22 10:38:46.785218: +2024-11-22 10:38:46.785418: Epoch 4325 +2024-11-22 10:38:46.785528: Current learning rate: 0.00497 +2024-11-22 10:39:04.807182: train_loss -0.786 +2024-11-22 10:39:04.807419: val_loss -0.7649 +2024-11-22 10:39:04.807492: Pseudo dice [0.857] +2024-11-22 10:39:04.807574: Epoch time: 18.02 s +2024-11-22 10:39:05.649388: +2024-11-22 10:39:05.649604: Epoch 4326 +2024-11-22 10:39:05.649718: Current learning rate: 0.00496 +2024-11-22 10:39:24.695690: train_loss -0.7912 +2024-11-22 10:39:24.695910: val_loss -0.767 +2024-11-22 10:39:24.695986: Pseudo dice [0.8521] +2024-11-22 10:39:24.696065: Epoch time: 19.05 s +2024-11-22 10:39:25.651228: +2024-11-22 10:39:25.651444: Epoch 4327 +2024-11-22 10:39:25.651556: Current learning rate: 0.00496 +2024-11-22 10:39:42.996080: train_loss -0.7943 +2024-11-22 10:39:42.996293: val_loss -0.7559 +2024-11-22 10:39:42.996364: Pseudo dice [0.8395] +2024-11-22 10:39:42.996434: Epoch time: 17.35 s +2024-11-22 10:39:43.835440: +2024-11-22 10:39:43.835638: Epoch 4328 +2024-11-22 10:39:43.835748: Current learning rate: 0.00496 +2024-11-22 10:40:00.881165: train_loss -0.797 +2024-11-22 10:40:00.881376: val_loss -0.7855 +2024-11-22 10:40:00.881455: Pseudo dice [0.8454] +2024-11-22 10:40:00.881557: Epoch time: 17.05 s +2024-11-22 10:40:02.104302: +2024-11-22 10:40:02.104720: Epoch 4329 +2024-11-22 10:40:02.104853: Current learning rate: 0.00496 +2024-11-22 10:40:22.392365: train_loss -0.7825 +2024-11-22 10:40:22.392608: val_loss -0.7696 +2024-11-22 10:40:22.392687: Pseudo dice [0.8389] +2024-11-22 10:40:22.392765: Epoch time: 20.29 s +2024-11-22 10:40:23.232905: +2024-11-22 10:40:23.233389: Epoch 4330 +2024-11-22 10:40:23.233519: Current learning rate: 0.00496 +2024-11-22 10:40:41.164742: train_loss -0.7792 +2024-11-22 10:40:41.164958: val_loss -0.767 +2024-11-22 10:40:41.165034: Pseudo dice [0.8574] +2024-11-22 10:40:41.165114: Epoch time: 17.93 s +2024-11-22 10:40:41.997109: +2024-11-22 10:40:41.997519: Epoch 4331 +2024-11-22 10:40:41.997645: Current learning rate: 0.00496 +2024-11-22 10:40:59.708678: train_loss -0.7906 +2024-11-22 10:40:59.708891: val_loss -0.7815 +2024-11-22 10:40:59.708968: Pseudo dice [0.855] +2024-11-22 10:40:59.709041: Epoch time: 17.71 s +2024-11-22 10:41:00.543980: +2024-11-22 10:41:00.544412: Epoch 4332 +2024-11-22 10:41:00.544546: Current learning rate: 0.00496 +2024-11-22 10:41:17.111602: train_loss -0.7953 +2024-11-22 10:41:17.111809: val_loss -0.7824 +2024-11-22 10:41:17.111890: Pseudo dice [0.8427] +2024-11-22 10:41:17.111968: Epoch time: 16.57 s +2024-11-22 10:41:17.945896: +2024-11-22 10:41:17.946323: Epoch 4333 +2024-11-22 10:41:17.946458: Current learning rate: 0.00496 +2024-11-22 10:41:37.530549: train_loss -0.7834 +2024-11-22 10:41:37.530785: val_loss -0.7589 +2024-11-22 10:41:37.530864: Pseudo dice [0.8577] +2024-11-22 10:41:37.530943: Epoch time: 19.59 s +2024-11-22 10:41:38.369133: +2024-11-22 10:41:38.369547: Epoch 4334 +2024-11-22 10:41:38.369680: Current learning rate: 0.00495 +2024-11-22 10:41:57.000502: train_loss -0.7975 +2024-11-22 10:41:57.000720: val_loss -0.7632 +2024-11-22 10:41:57.000795: Pseudo dice [0.8481] +2024-11-22 10:41:57.000869: Epoch time: 18.63 s +2024-11-22 10:41:57.879493: +2024-11-22 10:41:57.879930: Epoch 4335 +2024-11-22 10:41:57.880072: Current learning rate: 0.00495 +2024-11-22 10:42:16.198699: train_loss -0.7859 +2024-11-22 10:42:16.198925: val_loss -0.7727 +2024-11-22 10:42:16.199000: Pseudo dice [0.8459] +2024-11-22 10:42:16.199078: Epoch time: 18.32 s +2024-11-22 10:42:17.070931: +2024-11-22 10:42:17.071355: Epoch 4336 +2024-11-22 10:42:17.071489: Current learning rate: 0.00495 +2024-11-22 10:42:34.826130: train_loss -0.7908 +2024-11-22 10:42:34.826368: val_loss -0.7989 +2024-11-22 10:42:34.826448: Pseudo dice [0.8607] +2024-11-22 10:42:34.826531: Epoch time: 17.76 s +2024-11-22 10:42:35.669542: +2024-11-22 10:42:35.669945: Epoch 4337 +2024-11-22 10:42:35.670080: Current learning rate: 0.00495 +2024-11-22 10:42:54.099314: train_loss -0.7875 +2024-11-22 10:42:54.099521: val_loss -0.7636 +2024-11-22 10:42:54.099597: Pseudo dice [0.8599] +2024-11-22 10:42:54.099671: Epoch time: 18.43 s +2024-11-22 10:42:54.923069: +2024-11-22 10:42:54.923469: Epoch 4338 +2024-11-22 10:42:54.923596: Current learning rate: 0.00495 +2024-11-22 10:43:13.857760: train_loss -0.799 +2024-11-22 10:43:13.859211: val_loss -0.7493 +2024-11-22 10:43:13.859297: Pseudo dice [0.8552] +2024-11-22 10:43:13.859370: Epoch time: 18.94 s +2024-11-22 10:43:14.689129: +2024-11-22 10:43:14.689319: Epoch 4339 +2024-11-22 10:43:14.689431: Current learning rate: 0.00495 +2024-11-22 10:43:33.332160: train_loss -0.7965 +2024-11-22 10:43:33.332359: val_loss -0.7477 +2024-11-22 10:43:33.332432: Pseudo dice [0.8539] +2024-11-22 10:43:33.332507: Epoch time: 18.64 s +2024-11-22 10:43:34.163531: +2024-11-22 10:43:34.163713: Epoch 4340 +2024-11-22 10:43:34.163821: Current learning rate: 0.00495 +2024-11-22 10:43:52.968581: train_loss -0.7977 +2024-11-22 10:43:52.969072: val_loss -0.7668 +2024-11-22 10:43:52.969169: Pseudo dice [0.8641] +2024-11-22 10:43:52.969248: Epoch time: 18.81 s +2024-11-22 10:43:54.049987: +2024-11-22 10:43:54.050186: Epoch 4341 +2024-11-22 10:43:54.050302: Current learning rate: 0.00495 +2024-11-22 10:44:13.014606: train_loss -0.7947 +2024-11-22 10:44:13.014804: val_loss -0.7853 +2024-11-22 10:44:13.014875: Pseudo dice [0.8564] +2024-11-22 10:44:13.014948: Epoch time: 18.97 s +2024-11-22 10:44:13.834375: +2024-11-22 10:44:13.834609: Epoch 4342 +2024-11-22 10:44:13.834718: Current learning rate: 0.00494 +2024-11-22 10:44:31.590195: train_loss -0.7816 +2024-11-22 10:44:31.590398: val_loss -0.7686 +2024-11-22 10:44:31.590472: Pseudo dice [0.8492] +2024-11-22 10:44:31.590543: Epoch time: 17.76 s +2024-11-22 10:44:32.425867: +2024-11-22 10:44:32.426047: Epoch 4343 +2024-11-22 10:44:32.426162: Current learning rate: 0.00494 +2024-11-22 10:44:51.212302: train_loss -0.7918 +2024-11-22 10:44:51.212555: val_loss -0.7774 +2024-11-22 10:44:51.212632: Pseudo dice [0.8579] +2024-11-22 10:44:51.212711: Epoch time: 18.79 s +2024-11-22 10:44:52.045875: +2024-11-22 10:44:52.046105: Epoch 4344 +2024-11-22 10:44:52.046217: Current learning rate: 0.00494 +2024-11-22 10:45:10.856895: train_loss -0.7871 +2024-11-22 10:45:10.857125: val_loss -0.7594 +2024-11-22 10:45:10.857198: Pseudo dice [0.8551] +2024-11-22 10:45:10.857272: Epoch time: 18.81 s +2024-11-22 10:45:11.684306: +2024-11-22 10:45:11.684497: Epoch 4345 +2024-11-22 10:45:11.684604: Current learning rate: 0.00494 +2024-11-22 10:45:29.811489: train_loss -0.7939 +2024-11-22 10:45:29.811760: val_loss -0.776 +2024-11-22 10:45:29.811842: Pseudo dice [0.8566] +2024-11-22 10:45:29.811916: Epoch time: 18.13 s +2024-11-22 10:45:30.637496: +2024-11-22 10:45:30.637693: Epoch 4346 +2024-11-22 10:45:30.637801: Current learning rate: 0.00494 +2024-11-22 10:45:49.676630: train_loss -0.7915 +2024-11-22 10:45:49.676839: val_loss -0.7617 +2024-11-22 10:45:49.676914: Pseudo dice [0.8548] +2024-11-22 10:45:49.676991: Epoch time: 19.04 s +2024-11-22 10:45:50.512695: +2024-11-22 10:45:50.512893: Epoch 4347 +2024-11-22 10:45:50.513003: Current learning rate: 0.00494 +2024-11-22 10:46:08.494869: train_loss -0.7806 +2024-11-22 10:46:08.495098: val_loss -0.7631 +2024-11-22 10:46:08.495177: Pseudo dice [0.8498] +2024-11-22 10:46:08.495258: Epoch time: 17.98 s +2024-11-22 10:46:09.462672: +2024-11-22 10:46:09.462873: Epoch 4348 +2024-11-22 10:46:09.462978: Current learning rate: 0.00494 +2024-11-22 10:46:28.107343: train_loss -0.7865 +2024-11-22 10:46:28.107583: val_loss -0.7542 +2024-11-22 10:46:28.107664: Pseudo dice [0.8365] +2024-11-22 10:46:28.107741: Epoch time: 18.65 s +2024-11-22 10:46:28.954542: +2024-11-22 10:46:28.954720: Epoch 4349 +2024-11-22 10:46:28.954830: Current learning rate: 0.00494 +2024-11-22 10:46:48.104584: train_loss -0.781 +2024-11-22 10:46:48.104802: val_loss -0.7796 +2024-11-22 10:46:48.104876: Pseudo dice [0.8498] +2024-11-22 10:46:48.104953: Epoch time: 19.15 s +2024-11-22 10:46:49.203568: +2024-11-22 10:46:49.203779: Epoch 4350 +2024-11-22 10:46:49.203894: Current learning rate: 0.00493 +2024-11-22 10:47:08.919586: train_loss -0.7837 +2024-11-22 10:47:08.919790: val_loss -0.7475 +2024-11-22 10:47:08.919864: Pseudo dice [0.845] +2024-11-22 10:47:08.919936: Epoch time: 19.72 s +2024-11-22 10:47:09.758328: +2024-11-22 10:47:09.758570: Epoch 4351 +2024-11-22 10:47:09.758683: Current learning rate: 0.00493 +2024-11-22 10:47:28.919698: train_loss -0.7891 +2024-11-22 10:47:28.919937: val_loss -0.7717 +2024-11-22 10:47:28.920012: Pseudo dice [0.8652] +2024-11-22 10:47:28.920097: Epoch time: 19.16 s +2024-11-22 10:47:30.168966: +2024-11-22 10:47:30.169175: Epoch 4352 +2024-11-22 10:47:30.169283: Current learning rate: 0.00493 +2024-11-22 10:47:48.152515: train_loss -0.7887 +2024-11-22 10:47:48.152745: val_loss -0.7863 +2024-11-22 10:47:48.152825: Pseudo dice [0.8592] +2024-11-22 10:47:48.152902: Epoch time: 17.98 s +2024-11-22 10:47:49.072892: +2024-11-22 10:47:49.073100: Epoch 4353 +2024-11-22 10:47:49.073212: Current learning rate: 0.00493 +2024-11-22 10:48:07.675510: train_loss -0.7942 +2024-11-22 10:48:07.675725: val_loss -0.7695 +2024-11-22 10:48:07.675798: Pseudo dice [0.8661] +2024-11-22 10:48:07.675871: Epoch time: 18.6 s +2024-11-22 10:48:08.511036: +2024-11-22 10:48:08.511270: Epoch 4354 +2024-11-22 10:48:08.511383: Current learning rate: 0.00493 +2024-11-22 10:48:26.589560: train_loss -0.796 +2024-11-22 10:48:26.589770: val_loss -0.7733 +2024-11-22 10:48:26.589844: Pseudo dice [0.8548] +2024-11-22 10:48:26.589916: Epoch time: 18.08 s +2024-11-22 10:48:27.421638: +2024-11-22 10:48:27.421875: Epoch 4355 +2024-11-22 10:48:27.421984: Current learning rate: 0.00493 +2024-11-22 10:48:45.849856: train_loss -0.7852 +2024-11-22 10:48:45.852275: val_loss -0.7905 +2024-11-22 10:48:45.852361: Pseudo dice [0.8504] +2024-11-22 10:48:45.852442: Epoch time: 18.43 s +2024-11-22 10:48:46.725959: +2024-11-22 10:48:46.726160: Epoch 4356 +2024-11-22 10:48:46.726270: Current learning rate: 0.00493 +2024-11-22 10:49:06.464393: train_loss -0.7878 +2024-11-22 10:49:06.464612: val_loss -0.7653 +2024-11-22 10:49:06.464688: Pseudo dice [0.8486] +2024-11-22 10:49:06.464761: Epoch time: 19.74 s +2024-11-22 10:49:07.306166: +2024-11-22 10:49:07.306345: Epoch 4357 +2024-11-22 10:49:07.306480: Current learning rate: 0.00493 +2024-11-22 10:49:26.805707: train_loss -0.7899 +2024-11-22 10:49:26.805920: val_loss -0.7704 +2024-11-22 10:49:26.805997: Pseudo dice [0.8513] +2024-11-22 10:49:26.806078: Epoch time: 19.5 s +2024-11-22 10:49:27.822373: +2024-11-22 10:49:27.822570: Epoch 4358 +2024-11-22 10:49:27.822682: Current learning rate: 0.00493 +2024-11-22 10:49:47.270168: train_loss -0.7895 +2024-11-22 10:49:47.270383: val_loss -0.7856 +2024-11-22 10:49:47.270509: Pseudo dice [0.8597] +2024-11-22 10:49:47.270615: Epoch time: 19.45 s +2024-11-22 10:49:48.115402: +2024-11-22 10:49:48.115614: Epoch 4359 +2024-11-22 10:49:48.115723: Current learning rate: 0.00492 +2024-11-22 10:50:06.156518: train_loss -0.7917 +2024-11-22 10:50:06.156760: val_loss -0.7784 +2024-11-22 10:50:06.156881: Pseudo dice [0.8572] +2024-11-22 10:50:06.156974: Epoch time: 18.04 s +2024-11-22 10:50:06.997937: +2024-11-22 10:50:06.998145: Epoch 4360 +2024-11-22 10:50:06.998259: Current learning rate: 0.00492 +2024-11-22 10:50:25.810219: train_loss -0.7951 +2024-11-22 10:50:25.810437: val_loss -0.7645 +2024-11-22 10:50:25.810518: Pseudo dice [0.8513] +2024-11-22 10:50:25.810594: Epoch time: 18.81 s +2024-11-22 10:50:26.650714: +2024-11-22 10:50:26.650900: Epoch 4361 +2024-11-22 10:50:26.651216: Current learning rate: 0.00492 +2024-11-22 10:50:45.008219: train_loss -0.7906 +2024-11-22 10:50:45.008435: val_loss -0.766 +2024-11-22 10:50:45.008509: Pseudo dice [0.855] +2024-11-22 10:50:45.008582: Epoch time: 18.36 s +2024-11-22 10:50:45.846869: +2024-11-22 10:50:45.847067: Epoch 4362 +2024-11-22 10:50:45.847177: Current learning rate: 0.00492 +2024-11-22 10:51:05.192766: train_loss -0.7938 +2024-11-22 10:51:05.192985: val_loss -0.7566 +2024-11-22 10:51:05.193067: Pseudo dice [0.8554] +2024-11-22 10:51:05.193143: Epoch time: 19.35 s +2024-11-22 10:51:06.027359: +2024-11-22 10:51:06.027567: Epoch 4363 +2024-11-22 10:51:06.027679: Current learning rate: 0.00492 +2024-11-22 10:51:24.285455: train_loss -0.7919 +2024-11-22 10:51:24.285694: val_loss -0.7677 +2024-11-22 10:51:24.285767: Pseudo dice [0.8463] +2024-11-22 10:51:24.285846: Epoch time: 18.26 s +2024-11-22 10:51:25.588207: +2024-11-22 10:51:25.588404: Epoch 4364 +2024-11-22 10:51:25.588515: Current learning rate: 0.00492 +2024-11-22 10:51:43.554152: train_loss -0.7811 +2024-11-22 10:51:43.554364: val_loss -0.779 +2024-11-22 10:51:43.554495: Pseudo dice [0.8601] +2024-11-22 10:51:43.554570: Epoch time: 17.97 s +2024-11-22 10:51:44.390090: +2024-11-22 10:51:44.390299: Epoch 4365 +2024-11-22 10:51:44.390409: Current learning rate: 0.00492 +2024-11-22 10:52:03.196745: train_loss -0.7903 +2024-11-22 10:52:03.197033: val_loss -0.7937 +2024-11-22 10:52:03.197114: Pseudo dice [0.8624] +2024-11-22 10:52:03.197187: Epoch time: 18.81 s +2024-11-22 10:52:04.034375: +2024-11-22 10:52:04.034573: Epoch 4366 +2024-11-22 10:52:04.034686: Current learning rate: 0.00492 +2024-11-22 10:52:21.519992: train_loss -0.7974 +2024-11-22 10:52:21.520268: val_loss -0.7848 +2024-11-22 10:52:21.520345: Pseudo dice [0.8512] +2024-11-22 10:52:21.520422: Epoch time: 17.49 s +2024-11-22 10:52:22.385433: +2024-11-22 10:52:22.385653: Epoch 4367 +2024-11-22 10:52:22.385763: Current learning rate: 0.00491 +2024-11-22 10:52:40.312428: train_loss -0.7877 +2024-11-22 10:52:40.312660: val_loss -0.7464 +2024-11-22 10:52:40.312735: Pseudo dice [0.8476] +2024-11-22 10:52:40.312816: Epoch time: 17.93 s +2024-11-22 10:52:41.155360: +2024-11-22 10:52:41.155572: Epoch 4368 +2024-11-22 10:52:41.155685: Current learning rate: 0.00491 +2024-11-22 10:53:00.640284: train_loss -0.7737 +2024-11-22 10:53:00.642660: val_loss -0.7777 +2024-11-22 10:53:00.642788: Pseudo dice [0.849] +2024-11-22 10:53:00.642866: Epoch time: 19.49 s +2024-11-22 10:53:01.550116: +2024-11-22 10:53:01.550321: Epoch 4369 +2024-11-22 10:53:01.550432: Current learning rate: 0.00491 +2024-11-22 10:53:20.484371: train_loss -0.7888 +2024-11-22 10:53:20.484587: val_loss -0.7572 +2024-11-22 10:53:20.484662: Pseudo dice [0.8483] +2024-11-22 10:53:20.484736: Epoch time: 18.94 s +2024-11-22 10:53:21.337198: +2024-11-22 10:53:21.337426: Epoch 4370 +2024-11-22 10:53:21.337542: Current learning rate: 0.00491 +2024-11-22 10:53:40.356969: train_loss -0.7839 +2024-11-22 10:53:40.357225: val_loss -0.7573 +2024-11-22 10:53:40.357302: Pseudo dice [0.8505] +2024-11-22 10:53:40.357380: Epoch time: 19.02 s +2024-11-22 10:53:41.204909: +2024-11-22 10:53:41.205163: Epoch 4371 +2024-11-22 10:53:41.205282: Current learning rate: 0.00491 +2024-11-22 10:54:00.332549: train_loss -0.7851 +2024-11-22 10:54:00.332758: val_loss -0.7717 +2024-11-22 10:54:00.332833: Pseudo dice [0.8599] +2024-11-22 10:54:00.332908: Epoch time: 19.13 s +2024-11-22 10:54:01.243490: +2024-11-22 10:54:01.243697: Epoch 4372 +2024-11-22 10:54:01.243818: Current learning rate: 0.00491 +2024-11-22 10:54:21.041000: train_loss -0.7902 +2024-11-22 10:54:21.041217: val_loss -0.7793 +2024-11-22 10:54:21.041295: Pseudo dice [0.8578] +2024-11-22 10:54:21.041368: Epoch time: 19.8 s +2024-11-22 10:54:21.877013: +2024-11-22 10:54:21.877209: Epoch 4373 +2024-11-22 10:54:21.877320: Current learning rate: 0.00491 +2024-11-22 10:54:40.655105: train_loss -0.7917 +2024-11-22 10:54:40.655315: val_loss -0.7755 +2024-11-22 10:54:40.655389: Pseudo dice [0.858] +2024-11-22 10:54:40.655464: Epoch time: 18.78 s +2024-11-22 10:54:41.491597: +2024-11-22 10:54:41.491846: Epoch 4374 +2024-11-22 10:54:41.491963: Current learning rate: 0.00491 +2024-11-22 10:54:59.591793: train_loss -0.7868 +2024-11-22 10:54:59.592028: val_loss -0.7834 +2024-11-22 10:54:59.592114: Pseudo dice [0.8584] +2024-11-22 10:54:59.592195: Epoch time: 18.1 s +2024-11-22 10:55:00.459062: +2024-11-22 10:55:00.459456: Epoch 4375 +2024-11-22 10:55:00.459585: Current learning rate: 0.0049 +2024-11-22 10:55:18.702732: train_loss -0.7776 +2024-11-22 10:55:18.703252: val_loss -0.7698 +2024-11-22 10:55:18.703347: Pseudo dice [0.8521] +2024-11-22 10:55:18.703423: Epoch time: 18.24 s +2024-11-22 10:55:19.556784: +2024-11-22 10:55:19.556986: Epoch 4376 +2024-11-22 10:55:19.557101: Current learning rate: 0.0049 +2024-11-22 10:55:38.417176: train_loss -0.7729 +2024-11-22 10:55:38.417398: val_loss -0.7837 +2024-11-22 10:55:38.422639: Pseudo dice [0.8477] +2024-11-22 10:55:38.422795: Epoch time: 18.86 s +2024-11-22 10:55:39.342840: +2024-11-22 10:55:39.343065: Epoch 4377 +2024-11-22 10:55:39.343179: Current learning rate: 0.0049 +2024-11-22 10:55:58.717189: train_loss -0.7758 +2024-11-22 10:55:58.717432: val_loss -0.7742 +2024-11-22 10:55:58.717509: Pseudo dice [0.8534] +2024-11-22 10:55:58.717589: Epoch time: 19.38 s +2024-11-22 10:55:59.562840: +2024-11-22 10:55:59.563056: Epoch 4378 +2024-11-22 10:55:59.563186: Current learning rate: 0.0049 +2024-11-22 10:56:17.647842: train_loss -0.776 +2024-11-22 10:56:17.648052: val_loss -0.7627 +2024-11-22 10:56:17.648138: Pseudo dice [0.8417] +2024-11-22 10:56:17.653356: Epoch time: 18.09 s +2024-11-22 10:56:18.632073: +2024-11-22 10:56:18.632273: Epoch 4379 +2024-11-22 10:56:18.632393: Current learning rate: 0.0049 +2024-11-22 10:56:36.956366: train_loss -0.7775 +2024-11-22 10:56:36.956569: val_loss -0.7693 +2024-11-22 10:56:36.956643: Pseudo dice [0.8435] +2024-11-22 10:56:36.956715: Epoch time: 18.33 s +2024-11-22 10:56:37.815065: +2024-11-22 10:56:37.815284: Epoch 4380 +2024-11-22 10:56:37.815392: Current learning rate: 0.0049 +2024-11-22 10:56:56.014226: train_loss -0.7825 +2024-11-22 10:56:56.014436: val_loss -0.7865 +2024-11-22 10:56:56.014510: Pseudo dice [0.8461] +2024-11-22 10:56:56.014583: Epoch time: 18.2 s +2024-11-22 10:56:56.989242: +2024-11-22 10:56:56.989445: Epoch 4381 +2024-11-22 10:56:56.989554: Current learning rate: 0.0049 +2024-11-22 10:57:16.335719: train_loss -0.7894 +2024-11-22 10:57:16.335930: val_loss -0.7827 +2024-11-22 10:57:16.336007: Pseudo dice [0.8493] +2024-11-22 10:57:16.336162: Epoch time: 19.35 s +2024-11-22 10:57:17.177029: +2024-11-22 10:57:17.177226: Epoch 4382 +2024-11-22 10:57:17.177341: Current learning rate: 0.0049 +2024-11-22 10:57:35.812628: train_loss -0.7695 +2024-11-22 10:57:35.812855: val_loss -0.7752 +2024-11-22 10:57:35.812924: Pseudo dice [0.8394] +2024-11-22 10:57:35.815182: Epoch time: 18.64 s +2024-11-22 10:57:36.713734: +2024-11-22 10:57:36.713963: Epoch 4383 +2024-11-22 10:57:36.714086: Current learning rate: 0.00489 +2024-11-22 10:57:54.423309: train_loss -0.7808 +2024-11-22 10:57:54.423522: val_loss -0.7568 +2024-11-22 10:57:54.423601: Pseudo dice [0.8421] +2024-11-22 10:57:54.423674: Epoch time: 17.71 s +2024-11-22 10:57:55.342890: +2024-11-22 10:57:55.343079: Epoch 4384 +2024-11-22 10:57:55.343189: Current learning rate: 0.00489 +2024-11-22 10:58:13.777632: train_loss -0.7922 +2024-11-22 10:58:13.777847: val_loss -0.7484 +2024-11-22 10:58:13.777922: Pseudo dice [0.8359] +2024-11-22 10:58:13.777997: Epoch time: 18.44 s +2024-11-22 10:58:14.612648: +2024-11-22 10:58:14.612847: Epoch 4385 +2024-11-22 10:58:14.612958: Current learning rate: 0.00489 +2024-11-22 10:58:32.319804: train_loss -0.7682 +2024-11-22 10:58:32.320037: val_loss -0.7778 +2024-11-22 10:58:32.320118: Pseudo dice [0.8503] +2024-11-22 10:58:32.320199: Epoch time: 17.71 s +2024-11-22 10:58:33.157032: +2024-11-22 10:58:33.157235: Epoch 4386 +2024-11-22 10:58:33.157347: Current learning rate: 0.00489 +2024-11-22 10:58:51.106239: train_loss -0.7723 +2024-11-22 10:58:51.106445: val_loss -0.7815 +2024-11-22 10:58:51.106522: Pseudo dice [0.8514] +2024-11-22 10:58:51.106595: Epoch time: 17.95 s +2024-11-22 10:58:52.298823: +2024-11-22 10:58:52.299081: Epoch 4387 +2024-11-22 10:58:52.299205: Current learning rate: 0.00489 +2024-11-22 10:59:10.468578: train_loss -0.7747 +2024-11-22 10:59:10.468795: val_loss -0.7674 +2024-11-22 10:59:10.468870: Pseudo dice [0.8504] +2024-11-22 10:59:10.468944: Epoch time: 18.17 s +2024-11-22 10:59:11.308418: +2024-11-22 10:59:11.308624: Epoch 4388 +2024-11-22 10:59:11.308736: Current learning rate: 0.00489 +2024-11-22 10:59:30.000365: train_loss -0.7717 +2024-11-22 10:59:30.000576: val_loss -0.7836 +2024-11-22 10:59:30.000651: Pseudo dice [0.8591] +2024-11-22 10:59:30.000723: Epoch time: 18.69 s +2024-11-22 10:59:30.841810: +2024-11-22 10:59:30.842016: Epoch 4389 +2024-11-22 10:59:30.842131: Current learning rate: 0.00489 +2024-11-22 10:59:48.819157: train_loss -0.7728 +2024-11-22 10:59:48.819391: val_loss -0.767 +2024-11-22 10:59:48.819470: Pseudo dice [0.8597] +2024-11-22 10:59:48.819561: Epoch time: 17.98 s +2024-11-22 10:59:49.661773: +2024-11-22 10:59:49.662000: Epoch 4390 +2024-11-22 10:59:49.662116: Current learning rate: 0.00489 +2024-11-22 11:00:07.766029: train_loss -0.774 +2024-11-22 11:00:07.766245: val_loss -0.7467 +2024-11-22 11:00:07.766318: Pseudo dice [0.8335] +2024-11-22 11:00:07.766391: Epoch time: 18.11 s +2024-11-22 11:00:08.606961: +2024-11-22 11:00:08.607189: Epoch 4391 +2024-11-22 11:00:08.607299: Current learning rate: 0.00489 +2024-11-22 11:00:27.016506: train_loss -0.7766 +2024-11-22 11:00:27.016717: val_loss -0.7551 +2024-11-22 11:00:27.016791: Pseudo dice [0.8565] +2024-11-22 11:00:27.016866: Epoch time: 18.41 s +2024-11-22 11:00:27.859132: +2024-11-22 11:00:27.859317: Epoch 4392 +2024-11-22 11:00:27.859430: Current learning rate: 0.00488 +2024-11-22 11:00:47.697204: train_loss -0.7878 +2024-11-22 11:00:47.697422: val_loss -0.7697 +2024-11-22 11:00:47.697503: Pseudo dice [0.8556] +2024-11-22 11:00:47.697581: Epoch time: 19.84 s +2024-11-22 11:00:48.544158: +2024-11-22 11:00:48.544367: Epoch 4393 +2024-11-22 11:00:48.544482: Current learning rate: 0.00488 +2024-11-22 11:01:07.169873: train_loss -0.7847 +2024-11-22 11:01:07.170116: val_loss -0.7778 +2024-11-22 11:01:07.170189: Pseudo dice [0.8415] +2024-11-22 11:01:07.170270: Epoch time: 18.63 s +2024-11-22 11:01:08.122847: +2024-11-22 11:01:08.123050: Epoch 4394 +2024-11-22 11:01:08.123163: Current learning rate: 0.00488 +2024-11-22 11:01:27.988766: train_loss -0.7826 +2024-11-22 11:01:27.988972: val_loss -0.7517 +2024-11-22 11:01:27.989046: Pseudo dice [0.8508] +2024-11-22 11:01:27.989126: Epoch time: 19.87 s +2024-11-22 11:01:28.846703: +2024-11-22 11:01:28.846925: Epoch 4395 +2024-11-22 11:01:28.847040: Current learning rate: 0.00488 +2024-11-22 11:01:47.011854: train_loss -0.7767 +2024-11-22 11:01:47.012074: val_loss -0.7826 +2024-11-22 11:01:47.012150: Pseudo dice [0.8533] +2024-11-22 11:01:47.012237: Epoch time: 18.17 s +2024-11-22 11:01:47.842586: +2024-11-22 11:01:47.842802: Epoch 4396 +2024-11-22 11:01:47.842909: Current learning rate: 0.00488 +2024-11-22 11:02:06.437471: train_loss -0.7795 +2024-11-22 11:02:06.437706: val_loss -0.7677 +2024-11-22 11:02:06.437781: Pseudo dice [0.8483] +2024-11-22 11:02:06.437862: Epoch time: 18.6 s +2024-11-22 11:02:07.403481: +2024-11-22 11:02:07.403690: Epoch 4397 +2024-11-22 11:02:07.403797: Current learning rate: 0.00488 +2024-11-22 11:02:25.917073: train_loss -0.7741 +2024-11-22 11:02:25.917318: val_loss -0.7493 +2024-11-22 11:02:25.917397: Pseudo dice [0.8437] +2024-11-22 11:02:25.917470: Epoch time: 18.51 s +2024-11-22 11:02:26.755770: +2024-11-22 11:02:26.755982: Epoch 4398 +2024-11-22 11:02:26.756096: Current learning rate: 0.00488 +2024-11-22 11:02:44.986360: train_loss -0.7782 +2024-11-22 11:02:44.986850: val_loss -0.7882 +2024-11-22 11:02:44.986947: Pseudo dice [0.849] +2024-11-22 11:02:44.987022: Epoch time: 18.23 s +2024-11-22 11:02:45.823175: +2024-11-22 11:02:45.823383: Epoch 4399 +2024-11-22 11:02:45.823497: Current learning rate: 0.00488 +2024-11-22 11:03:04.656975: train_loss -0.7854 +2024-11-22 11:03:04.657269: val_loss -0.7806 +2024-11-22 11:03:04.657347: Pseudo dice [0.8526] +2024-11-22 11:03:04.657427: Epoch time: 18.83 s +2024-11-22 11:03:05.786761: +2024-11-22 11:03:05.786955: Epoch 4400 +2024-11-22 11:03:05.787075: Current learning rate: 0.00487 +2024-11-22 11:03:24.596781: train_loss -0.7707 +2024-11-22 11:03:24.597027: val_loss -0.7454 +2024-11-22 11:03:24.597107: Pseudo dice [0.8501] +2024-11-22 11:03:24.597185: Epoch time: 18.81 s +2024-11-22 11:03:25.434265: +2024-11-22 11:03:25.434489: Epoch 4401 +2024-11-22 11:03:25.434596: Current learning rate: 0.00487 +2024-11-22 11:03:44.329222: train_loss -0.7631 +2024-11-22 11:03:44.329432: val_loss -0.7748 +2024-11-22 11:03:44.329506: Pseudo dice [0.8386] +2024-11-22 11:03:44.329580: Epoch time: 18.9 s +2024-11-22 11:03:45.175551: +2024-11-22 11:03:45.175764: Epoch 4402 +2024-11-22 11:03:45.175871: Current learning rate: 0.00487 +2024-11-22 11:04:03.179993: train_loss -0.7769 +2024-11-22 11:04:03.180208: val_loss -0.7791 +2024-11-22 11:04:03.180283: Pseudo dice [0.8537] +2024-11-22 11:04:03.180356: Epoch time: 18.01 s +2024-11-22 11:04:04.018165: +2024-11-22 11:04:04.018390: Epoch 4403 +2024-11-22 11:04:04.018512: Current learning rate: 0.00487 +2024-11-22 11:04:22.903389: train_loss -0.7721 +2024-11-22 11:04:22.908784: val_loss -0.7731 +2024-11-22 11:04:22.908927: Pseudo dice [0.8427] +2024-11-22 11:04:22.909015: Epoch time: 18.89 s +2024-11-22 11:04:23.879227: +2024-11-22 11:04:23.879418: Epoch 4404 +2024-11-22 11:04:23.879529: Current learning rate: 0.00487 +2024-11-22 11:04:42.834769: train_loss -0.7808 +2024-11-22 11:04:42.834993: val_loss -0.7698 +2024-11-22 11:04:42.835072: Pseudo dice [0.8428] +2024-11-22 11:04:42.835150: Epoch time: 18.96 s +2024-11-22 11:04:43.713113: +2024-11-22 11:04:43.713316: Epoch 4405 +2024-11-22 11:04:43.713428: Current learning rate: 0.00487 +2024-11-22 11:05:02.275816: train_loss -0.7798 +2024-11-22 11:05:02.276027: val_loss -0.7646 +2024-11-22 11:05:02.276111: Pseudo dice [0.848] +2024-11-22 11:05:02.276191: Epoch time: 18.56 s +2024-11-22 11:05:03.115781: +2024-11-22 11:05:03.116003: Epoch 4406 +2024-11-22 11:05:03.116122: Current learning rate: 0.00487 +2024-11-22 11:05:21.046397: train_loss -0.7823 +2024-11-22 11:05:21.046608: val_loss -0.7435 +2024-11-22 11:05:21.046684: Pseudo dice [0.8415] +2024-11-22 11:05:21.046763: Epoch time: 17.93 s +2024-11-22 11:05:21.891360: +2024-11-22 11:05:21.891553: Epoch 4407 +2024-11-22 11:05:21.891666: Current learning rate: 0.00487 +2024-11-22 11:05:40.285230: train_loss -0.7863 +2024-11-22 11:05:40.285862: val_loss -0.765 +2024-11-22 11:05:40.285944: Pseudo dice [0.8586] +2024-11-22 11:05:40.286020: Epoch time: 18.39 s +2024-11-22 11:05:41.127587: +2024-11-22 11:05:41.127778: Epoch 4408 +2024-11-22 11:05:41.127891: Current learning rate: 0.00486 +2024-11-22 11:05:58.852178: train_loss -0.7878 +2024-11-22 11:05:58.852401: val_loss -0.779 +2024-11-22 11:05:58.852476: Pseudo dice [0.8573] +2024-11-22 11:05:58.852552: Epoch time: 17.73 s +2024-11-22 11:05:59.687234: +2024-11-22 11:05:59.687443: Epoch 4409 +2024-11-22 11:05:59.687551: Current learning rate: 0.00486 +2024-11-22 11:06:18.505623: train_loss -0.7847 +2024-11-22 11:06:18.505825: val_loss -0.7837 +2024-11-22 11:06:18.505899: Pseudo dice [0.8631] +2024-11-22 11:06:18.505972: Epoch time: 18.82 s +2024-11-22 11:06:19.744947: +2024-11-22 11:06:19.745223: Epoch 4410 +2024-11-22 11:06:19.745335: Current learning rate: 0.00486 +2024-11-22 11:06:37.591149: train_loss -0.7867 +2024-11-22 11:06:37.591409: val_loss -0.7534 +2024-11-22 11:06:37.591491: Pseudo dice [0.8471] +2024-11-22 11:06:37.591588: Epoch time: 17.85 s +2024-11-22 11:06:38.427797: +2024-11-22 11:06:38.428004: Epoch 4411 +2024-11-22 11:06:38.428120: Current learning rate: 0.00486 +2024-11-22 11:06:56.777725: train_loss -0.8029 +2024-11-22 11:06:56.777943: val_loss -0.7674 +2024-11-22 11:06:56.778019: Pseudo dice [0.8457] +2024-11-22 11:06:56.778098: Epoch time: 18.35 s +2024-11-22 11:06:57.634566: +2024-11-22 11:06:57.634800: Epoch 4412 +2024-11-22 11:06:57.634910: Current learning rate: 0.00486 +2024-11-22 11:07:15.187827: train_loss -0.7977 +2024-11-22 11:07:15.188026: val_loss -0.7794 +2024-11-22 11:07:15.188143: Pseudo dice [0.8633] +2024-11-22 11:07:15.188221: Epoch time: 17.55 s +2024-11-22 11:07:16.190049: +2024-11-22 11:07:16.190276: Epoch 4413 +2024-11-22 11:07:16.190390: Current learning rate: 0.00486 +2024-11-22 11:07:34.736522: train_loss -0.8068 +2024-11-22 11:07:34.736715: val_loss -0.8004 +2024-11-22 11:07:34.736783: Pseudo dice [0.8492] +2024-11-22 11:07:34.736856: Epoch time: 18.55 s +2024-11-22 11:07:35.590498: +2024-11-22 11:07:35.590710: Epoch 4414 +2024-11-22 11:07:35.590820: Current learning rate: 0.00486 +2024-11-22 11:07:53.260223: train_loss -0.7847 +2024-11-22 11:07:53.260523: val_loss -0.7717 +2024-11-22 11:07:53.260602: Pseudo dice [0.8607] +2024-11-22 11:07:53.260684: Epoch time: 17.67 s +2024-11-22 11:07:54.101419: +2024-11-22 11:07:54.101610: Epoch 4415 +2024-11-22 11:07:54.101728: Current learning rate: 0.00486 +2024-11-22 11:08:12.297691: train_loss -0.79 +2024-11-22 11:08:12.297904: val_loss -0.7582 +2024-11-22 11:08:12.297982: Pseudo dice [0.8586] +2024-11-22 11:08:12.298070: Epoch time: 18.2 s +2024-11-22 11:08:13.135338: +2024-11-22 11:08:13.135544: Epoch 4416 +2024-11-22 11:08:13.135654: Current learning rate: 0.00485 +2024-11-22 11:08:32.084028: train_loss -0.8001 +2024-11-22 11:08:32.084247: val_loss -0.7833 +2024-11-22 11:08:32.084320: Pseudo dice [0.8407] +2024-11-22 11:08:32.084399: Epoch time: 18.95 s +2024-11-22 11:08:33.067451: +2024-11-22 11:08:33.067671: Epoch 4417 +2024-11-22 11:08:33.067785: Current learning rate: 0.00485 +2024-11-22 11:08:51.648476: train_loss -0.7862 +2024-11-22 11:08:51.648693: val_loss -0.7711 +2024-11-22 11:08:51.648771: Pseudo dice [0.8426] +2024-11-22 11:08:51.648847: Epoch time: 18.58 s +2024-11-22 11:08:52.493737: +2024-11-22 11:08:52.493940: Epoch 4418 +2024-11-22 11:08:52.494050: Current learning rate: 0.00485 +2024-11-22 11:09:11.630708: train_loss -0.7897 +2024-11-22 11:09:11.631009: val_loss -0.7507 +2024-11-22 11:09:11.631094: Pseudo dice [0.8456] +2024-11-22 11:09:11.631175: Epoch time: 19.14 s +2024-11-22 11:09:12.468122: +2024-11-22 11:09:12.468307: Epoch 4419 +2024-11-22 11:09:12.468418: Current learning rate: 0.00485 +2024-11-22 11:09:31.158121: train_loss -0.7917 +2024-11-22 11:09:31.158335: val_loss -0.7684 +2024-11-22 11:09:31.158417: Pseudo dice [0.8408] +2024-11-22 11:09:31.158493: Epoch time: 18.69 s +2024-11-22 11:09:31.994780: +2024-11-22 11:09:31.994977: Epoch 4420 +2024-11-22 11:09:31.995097: Current learning rate: 0.00485 +2024-11-22 11:09:49.976467: train_loss -0.7952 +2024-11-22 11:09:49.976681: val_loss -0.7709 +2024-11-22 11:09:49.976804: Pseudo dice [0.8379] +2024-11-22 11:09:49.976887: Epoch time: 17.98 s +2024-11-22 11:09:50.819968: +2024-11-22 11:09:50.820191: Epoch 4421 +2024-11-22 11:09:50.820306: Current learning rate: 0.00485 +2024-11-22 11:10:09.528181: train_loss -0.7957 +2024-11-22 11:10:09.528685: val_loss -0.7855 +2024-11-22 11:10:09.528781: Pseudo dice [0.8594] +2024-11-22 11:10:09.528865: Epoch time: 18.71 s +2024-11-22 11:10:10.372020: +2024-11-22 11:10:10.372231: Epoch 4422 +2024-11-22 11:10:10.372341: Current learning rate: 0.00485 +2024-11-22 11:10:28.338609: train_loss -0.7907 +2024-11-22 11:10:28.338837: val_loss -0.7725 +2024-11-22 11:10:28.338911: Pseudo dice [0.8576] +2024-11-22 11:10:28.338986: Epoch time: 17.97 s +2024-11-22 11:10:29.175515: +2024-11-22 11:10:29.175775: Epoch 4423 +2024-11-22 11:10:29.175886: Current learning rate: 0.00485 +2024-11-22 11:10:47.453674: train_loss -0.7923 +2024-11-22 11:10:47.453889: val_loss -0.7846 +2024-11-22 11:10:47.453966: Pseudo dice [0.8514] +2024-11-22 11:10:47.454040: Epoch time: 18.28 s +2024-11-22 11:10:48.293119: +2024-11-22 11:10:48.293390: Epoch 4424 +2024-11-22 11:10:48.293505: Current learning rate: 0.00484 +2024-11-22 11:11:07.344499: train_loss -0.7943 +2024-11-22 11:11:07.344709: val_loss -0.7745 +2024-11-22 11:11:07.344782: Pseudo dice [0.8574] +2024-11-22 11:11:07.344859: Epoch time: 19.05 s +2024-11-22 11:11:08.188381: +2024-11-22 11:11:08.188604: Epoch 4425 +2024-11-22 11:11:08.188717: Current learning rate: 0.00484 +2024-11-22 11:11:27.035325: train_loss -0.799 +2024-11-22 11:11:27.035609: val_loss -0.7796 +2024-11-22 11:11:27.035690: Pseudo dice [0.8582] +2024-11-22 11:11:27.035775: Epoch time: 18.85 s +2024-11-22 11:11:27.880907: +2024-11-22 11:11:27.881100: Epoch 4426 +2024-11-22 11:11:27.881205: Current learning rate: 0.00484 +2024-11-22 11:11:47.587816: train_loss -0.7898 +2024-11-22 11:11:47.588029: val_loss -0.768 +2024-11-22 11:11:47.588109: Pseudo dice [0.8521] +2024-11-22 11:11:47.588180: Epoch time: 19.71 s +2024-11-22 11:11:48.430210: +2024-11-22 11:11:48.430420: Epoch 4427 +2024-11-22 11:11:48.430528: Current learning rate: 0.00484 +2024-11-22 11:12:07.500686: train_loss -0.7932 +2024-11-22 11:12:07.500937: val_loss -0.7895 +2024-11-22 11:12:07.501021: Pseudo dice [0.8614] +2024-11-22 11:12:07.501105: Epoch time: 19.07 s +2024-11-22 11:12:08.344286: +2024-11-22 11:12:08.344486: Epoch 4428 +2024-11-22 11:12:08.344597: Current learning rate: 0.00484 +2024-11-22 11:12:26.435730: train_loss -0.7976 +2024-11-22 11:12:26.435950: val_loss -0.7911 +2024-11-22 11:12:26.436023: Pseudo dice [0.8653] +2024-11-22 11:12:26.436106: Epoch time: 18.09 s +2024-11-22 11:12:27.434982: +2024-11-22 11:12:27.435197: Epoch 4429 +2024-11-22 11:12:27.435311: Current learning rate: 0.00484 +2024-11-22 11:12:45.885559: train_loss -0.7967 +2024-11-22 11:12:45.885802: val_loss -0.7739 +2024-11-22 11:12:45.885876: Pseudo dice [0.847] +2024-11-22 11:12:45.885958: Epoch time: 18.45 s +2024-11-22 11:12:46.729806: +2024-11-22 11:12:46.730025: Epoch 4430 +2024-11-22 11:12:46.730144: Current learning rate: 0.00484 +2024-11-22 11:13:04.929934: train_loss -0.8008 +2024-11-22 11:13:04.932269: val_loss -0.7744 +2024-11-22 11:13:04.932383: Pseudo dice [0.8417] +2024-11-22 11:13:04.932461: Epoch time: 18.2 s +2024-11-22 11:13:05.849588: +2024-11-22 11:13:05.849797: Epoch 4431 +2024-11-22 11:13:05.849909: Current learning rate: 0.00484 +2024-11-22 11:13:24.971843: train_loss -0.7974 +2024-11-22 11:13:24.972082: val_loss -0.7746 +2024-11-22 11:13:24.972177: Pseudo dice [0.8457] +2024-11-22 11:13:24.972254: Epoch time: 19.12 s +2024-11-22 11:13:25.807744: +2024-11-22 11:13:25.807943: Epoch 4432 +2024-11-22 11:13:25.808053: Current learning rate: 0.00484 +2024-11-22 11:13:44.626789: train_loss -0.7846 +2024-11-22 11:13:44.627012: val_loss -0.7801 +2024-11-22 11:13:44.627108: Pseudo dice [0.8528] +2024-11-22 11:13:44.627190: Epoch time: 18.82 s +2024-11-22 11:13:45.883859: +2024-11-22 11:13:45.884113: Epoch 4433 +2024-11-22 11:13:45.884224: Current learning rate: 0.00483 +2024-11-22 11:14:03.571358: train_loss -0.7987 +2024-11-22 11:14:03.571600: val_loss -0.7513 +2024-11-22 11:14:03.571689: Pseudo dice [0.8483] +2024-11-22 11:14:03.571808: Epoch time: 17.69 s +2024-11-22 11:14:04.416444: +2024-11-22 11:14:04.416664: Epoch 4434 +2024-11-22 11:14:04.416776: Current learning rate: 0.00483 +2024-11-22 11:14:22.691727: train_loss -0.7834 +2024-11-22 11:14:22.706258: val_loss -0.7751 +2024-11-22 11:14:22.706365: Pseudo dice [0.8526] +2024-11-22 11:14:22.706481: Epoch time: 18.28 s +2024-11-22 11:14:23.542016: +2024-11-22 11:14:23.542237: Epoch 4435 +2024-11-22 11:14:23.542347: Current learning rate: 0.00483 +2024-11-22 11:14:41.902167: train_loss -0.796 +2024-11-22 11:14:41.902381: val_loss -0.7922 +2024-11-22 11:14:41.902456: Pseudo dice [0.8629] +2024-11-22 11:14:41.902541: Epoch time: 18.36 s +2024-11-22 11:14:42.841652: +2024-11-22 11:14:42.841889: Epoch 4436 +2024-11-22 11:14:42.842001: Current learning rate: 0.00483 +2024-11-22 11:15:01.485753: train_loss -0.7978 +2024-11-22 11:15:01.486019: val_loss -0.7707 +2024-11-22 11:15:01.486099: Pseudo dice [0.8613] +2024-11-22 11:15:01.486176: Epoch time: 18.64 s +2024-11-22 11:15:02.336202: +2024-11-22 11:15:02.336413: Epoch 4437 +2024-11-22 11:15:02.336527: Current learning rate: 0.00483 +2024-11-22 11:15:20.607213: train_loss -0.7844 +2024-11-22 11:15:20.609586: val_loss -0.7714 +2024-11-22 11:15:20.609740: Pseudo dice [0.8445] +2024-11-22 11:15:20.609823: Epoch time: 18.27 s +2024-11-22 11:15:21.469457: +2024-11-22 11:15:21.469683: Epoch 4438 +2024-11-22 11:15:21.469803: Current learning rate: 0.00483 +2024-11-22 11:15:39.986736: train_loss -0.7932 +2024-11-22 11:15:39.986951: val_loss -0.7813 +2024-11-22 11:15:39.987024: Pseudo dice [0.8521] +2024-11-22 11:15:39.987103: Epoch time: 18.52 s +2024-11-22 11:15:40.818177: +2024-11-22 11:15:40.818365: Epoch 4439 +2024-11-22 11:15:40.818473: Current learning rate: 0.00483 +2024-11-22 11:15:58.753394: train_loss -0.7915 +2024-11-22 11:15:58.753607: val_loss -0.7621 +2024-11-22 11:15:58.753681: Pseudo dice [0.8502] +2024-11-22 11:15:58.753756: Epoch time: 17.94 s +2024-11-22 11:15:59.652853: +2024-11-22 11:15:59.654273: Epoch 4440 +2024-11-22 11:15:59.654394: Current learning rate: 0.00483 +2024-11-22 11:16:18.231913: train_loss -0.7975 +2024-11-22 11:16:18.232228: val_loss -0.772 +2024-11-22 11:16:18.232311: Pseudo dice [0.8522] +2024-11-22 11:16:18.232391: Epoch time: 18.58 s +2024-11-22 11:16:19.083291: +2024-11-22 11:16:19.083544: Epoch 4441 +2024-11-22 11:16:19.083659: Current learning rate: 0.00482 +2024-11-22 11:16:38.291164: train_loss -0.7911 +2024-11-22 11:16:38.291385: val_loss -0.7894 +2024-11-22 11:16:38.291465: Pseudo dice [0.8699] +2024-11-22 11:16:38.291539: Epoch time: 19.21 s +2024-11-22 11:16:39.128455: +2024-11-22 11:16:39.128673: Epoch 4442 +2024-11-22 11:16:39.128787: Current learning rate: 0.00482 +2024-11-22 11:16:57.248385: train_loss -0.786 +2024-11-22 11:16:57.248613: val_loss -0.7558 +2024-11-22 11:16:57.248688: Pseudo dice [0.8417] +2024-11-22 11:16:57.248762: Epoch time: 18.12 s +2024-11-22 11:16:58.295290: +2024-11-22 11:16:58.295497: Epoch 4443 +2024-11-22 11:16:58.295603: Current learning rate: 0.00482 +2024-11-22 11:17:17.612805: train_loss -0.7925 +2024-11-22 11:17:17.613018: val_loss -0.7473 +2024-11-22 11:17:17.613101: Pseudo dice [0.8397] +2024-11-22 11:17:17.613176: Epoch time: 19.32 s +2024-11-22 11:17:18.450012: +2024-11-22 11:17:18.450223: Epoch 4444 +2024-11-22 11:17:18.450336: Current learning rate: 0.00482 +2024-11-22 11:17:37.397131: train_loss -0.7999 +2024-11-22 11:17:37.402738: val_loss -0.7652 +2024-11-22 11:17:37.402854: Pseudo dice [0.8579] +2024-11-22 11:17:37.402939: Epoch time: 18.95 s +2024-11-22 11:17:38.347331: +2024-11-22 11:17:38.347580: Epoch 4445 +2024-11-22 11:17:38.347692: Current learning rate: 0.00482 +2024-11-22 11:17:57.854022: train_loss -0.7896 +2024-11-22 11:17:57.854242: val_loss -0.767 +2024-11-22 11:17:57.854317: Pseudo dice [0.8684] +2024-11-22 11:17:57.854394: Epoch time: 19.51 s +2024-11-22 11:17:58.872096: +2024-11-22 11:17:58.872329: Epoch 4446 +2024-11-22 11:17:58.872441: Current learning rate: 0.00482 +2024-11-22 11:18:18.774251: train_loss -0.7822 +2024-11-22 11:18:18.774483: val_loss -0.7807 +2024-11-22 11:18:18.774560: Pseudo dice [0.8459] +2024-11-22 11:18:18.774642: Epoch time: 19.9 s +2024-11-22 11:18:19.612448: +2024-11-22 11:18:19.612659: Epoch 4447 +2024-11-22 11:18:19.612773: Current learning rate: 0.00482 +2024-11-22 11:18:37.637401: train_loss -0.7849 +2024-11-22 11:18:37.637624: val_loss -0.7814 +2024-11-22 11:18:37.637697: Pseudo dice [0.8545] +2024-11-22 11:18:37.637779: Epoch time: 18.03 s +2024-11-22 11:18:38.485099: +2024-11-22 11:18:38.485316: Epoch 4448 +2024-11-22 11:18:38.485429: Current learning rate: 0.00482 +2024-11-22 11:18:56.085320: train_loss -0.7884 +2024-11-22 11:18:56.085551: val_loss -0.7523 +2024-11-22 11:18:56.085626: Pseudo dice [0.8516] +2024-11-22 11:18:56.085703: Epoch time: 17.6 s +2024-11-22 11:18:56.946103: +2024-11-22 11:18:56.946288: Epoch 4449 +2024-11-22 11:18:56.946401: Current learning rate: 0.00481 +2024-11-22 11:19:15.677619: train_loss -0.7926 +2024-11-22 11:19:15.677841: val_loss -0.7656 +2024-11-22 11:19:15.677916: Pseudo dice [0.8547] +2024-11-22 11:19:15.677990: Epoch time: 18.73 s +2024-11-22 11:19:16.799675: +2024-11-22 11:19:16.799885: Epoch 4450 +2024-11-22 11:19:16.799992: Current learning rate: 0.00481 +2024-11-22 11:19:34.853324: train_loss -0.7935 +2024-11-22 11:19:34.853537: val_loss -0.7658 +2024-11-22 11:19:34.853610: Pseudo dice [0.8482] +2024-11-22 11:19:34.853684: Epoch time: 18.05 s +2024-11-22 11:19:35.696454: +2024-11-22 11:19:35.696655: Epoch 4451 +2024-11-22 11:19:35.696763: Current learning rate: 0.00481 +2024-11-22 11:19:54.605439: train_loss -0.7848 +2024-11-22 11:19:54.605678: val_loss -0.785 +2024-11-22 11:19:54.605752: Pseudo dice [0.8442] +2024-11-22 11:19:54.605832: Epoch time: 18.91 s +2024-11-22 11:19:55.443500: +2024-11-22 11:19:55.443737: Epoch 4452 +2024-11-22 11:19:55.443854: Current learning rate: 0.00481 +2024-11-22 11:20:13.617102: train_loss -0.7975 +2024-11-22 11:20:13.617324: val_loss -0.7553 +2024-11-22 11:20:13.617429: Pseudo dice [0.85] +2024-11-22 11:20:13.617505: Epoch time: 18.17 s +2024-11-22 11:20:14.459854: +2024-11-22 11:20:14.460076: Epoch 4453 +2024-11-22 11:20:14.460191: Current learning rate: 0.00481 +2024-11-22 11:20:33.973393: train_loss -0.7934 +2024-11-22 11:20:33.973679: val_loss -0.7346 +2024-11-22 11:20:33.973758: Pseudo dice [0.8326] +2024-11-22 11:20:33.973840: Epoch time: 19.51 s +2024-11-22 11:20:34.919528: +2024-11-22 11:20:34.919760: Epoch 4454 +2024-11-22 11:20:34.919872: Current learning rate: 0.00481 +2024-11-22 11:20:53.470953: train_loss -0.7873 +2024-11-22 11:20:53.471148: val_loss -0.7577 +2024-11-22 11:20:53.471220: Pseudo dice [0.8545] +2024-11-22 11:20:53.471294: Epoch time: 18.55 s +2024-11-22 11:20:54.398222: +2024-11-22 11:20:54.398407: Epoch 4455 +2024-11-22 11:20:54.398518: Current learning rate: 0.00481 +2024-11-22 11:21:14.683868: train_loss -0.7835 +2024-11-22 11:21:14.686285: val_loss -0.758 +2024-11-22 11:21:14.686451: Pseudo dice [0.8499] +2024-11-22 11:21:14.686548: Epoch time: 20.29 s +2024-11-22 11:21:15.982383: +2024-11-22 11:21:15.982583: Epoch 4456 +2024-11-22 11:21:15.982688: Current learning rate: 0.00481 +2024-11-22 11:21:34.325168: train_loss -0.7986 +2024-11-22 11:21:34.325397: val_loss -0.7534 +2024-11-22 11:21:34.325477: Pseudo dice [0.8475] +2024-11-22 11:21:34.325554: Epoch time: 18.34 s +2024-11-22 11:21:35.167145: +2024-11-22 11:21:35.167338: Epoch 4457 +2024-11-22 11:21:35.167452: Current learning rate: 0.0048 +2024-11-22 11:21:53.561954: train_loss -0.7865 +2024-11-22 11:21:53.562213: val_loss -0.7674 +2024-11-22 11:21:53.562286: Pseudo dice [0.8524] +2024-11-22 11:21:53.562358: Epoch time: 18.4 s +2024-11-22 11:21:54.401935: +2024-11-22 11:21:54.402159: Epoch 4458 +2024-11-22 11:21:54.402267: Current learning rate: 0.0048 +2024-11-22 11:22:12.847372: train_loss -0.7948 +2024-11-22 11:22:12.847580: val_loss -0.7704 +2024-11-22 11:22:12.847656: Pseudo dice [0.8464] +2024-11-22 11:22:12.847731: Epoch time: 18.45 s +2024-11-22 11:22:13.687539: +2024-11-22 11:22:13.687739: Epoch 4459 +2024-11-22 11:22:13.687854: Current learning rate: 0.0048 +2024-11-22 11:22:32.611702: train_loss -0.7872 +2024-11-22 11:22:32.611941: val_loss -0.7459 +2024-11-22 11:22:32.612020: Pseudo dice [0.8398] +2024-11-22 11:22:32.612109: Epoch time: 18.92 s +2024-11-22 11:22:33.453856: +2024-11-22 11:22:33.454074: Epoch 4460 +2024-11-22 11:22:33.454185: Current learning rate: 0.0048 +2024-11-22 11:22:52.010131: train_loss -0.7998 +2024-11-22 11:22:52.010368: val_loss -0.7719 +2024-11-22 11:22:52.010442: Pseudo dice [0.8606] +2024-11-22 11:22:52.010516: Epoch time: 18.56 s +2024-11-22 11:22:52.851565: +2024-11-22 11:22:52.851760: Epoch 4461 +2024-11-22 11:22:52.851876: Current learning rate: 0.0048 +2024-11-22 11:23:11.178851: train_loss -0.7954 +2024-11-22 11:23:11.179053: val_loss -0.7501 +2024-11-22 11:23:11.179134: Pseudo dice [0.8422] +2024-11-22 11:23:11.179206: Epoch time: 18.33 s +2024-11-22 11:23:12.015008: +2024-11-22 11:23:12.015270: Epoch 4462 +2024-11-22 11:23:12.015386: Current learning rate: 0.0048 +2024-11-22 11:23:30.492035: train_loss -0.7927 +2024-11-22 11:23:30.492260: val_loss -0.7703 +2024-11-22 11:23:30.492337: Pseudo dice [0.8594] +2024-11-22 11:23:30.492419: Epoch time: 18.48 s +2024-11-22 11:23:31.334576: +2024-11-22 11:23:31.334782: Epoch 4463 +2024-11-22 11:23:31.334891: Current learning rate: 0.0048 +2024-11-22 11:23:50.427262: train_loss -0.8004 +2024-11-22 11:23:50.427500: val_loss -0.7608 +2024-11-22 11:23:50.427574: Pseudo dice [0.8678] +2024-11-22 11:23:50.427652: Epoch time: 19.09 s +2024-11-22 11:23:51.362644: +2024-11-22 11:23:51.362841: Epoch 4464 +2024-11-22 11:23:51.362952: Current learning rate: 0.0048 +2024-11-22 11:24:10.358146: train_loss -0.796 +2024-11-22 11:24:10.358348: val_loss -0.769 +2024-11-22 11:24:10.358420: Pseudo dice [0.8496] +2024-11-22 11:24:10.358679: Epoch time: 19.0 s +2024-11-22 11:24:11.199834: +2024-11-22 11:24:11.200006: Epoch 4465 +2024-11-22 11:24:11.200116: Current learning rate: 0.00479 +2024-11-22 11:24:29.367389: train_loss -0.7905 +2024-11-22 11:24:29.367603: val_loss -0.7668 +2024-11-22 11:24:29.367678: Pseudo dice [0.8545] +2024-11-22 11:24:29.367753: Epoch time: 18.17 s +2024-11-22 11:24:30.370075: +2024-11-22 11:24:30.370292: Epoch 4466 +2024-11-22 11:24:30.370404: Current learning rate: 0.00479 +2024-11-22 11:24:49.364853: train_loss -0.7856 +2024-11-22 11:24:49.365097: val_loss -0.7861 +2024-11-22 11:24:49.365173: Pseudo dice [0.8597] +2024-11-22 11:24:49.365255: Epoch time: 19.0 s +2024-11-22 11:24:50.201267: +2024-11-22 11:24:50.201471: Epoch 4467 +2024-11-22 11:24:50.201581: Current learning rate: 0.00479 +2024-11-22 11:25:08.241426: train_loss -0.8084 +2024-11-22 11:25:08.241896: val_loss -0.7718 +2024-11-22 11:25:08.241996: Pseudo dice [0.8638] +2024-11-22 11:25:08.242081: Epoch time: 18.04 s +2024-11-22 11:25:09.074629: +2024-11-22 11:25:09.074826: Epoch 4468 +2024-11-22 11:25:09.074940: Current learning rate: 0.00479 +2024-11-22 11:25:26.363764: train_loss -0.7923 +2024-11-22 11:25:26.363994: val_loss -0.7723 +2024-11-22 11:25:26.364077: Pseudo dice [0.8561] +2024-11-22 11:25:26.364167: Epoch time: 17.29 s +2024-11-22 11:25:27.204558: +2024-11-22 11:25:27.204772: Epoch 4469 +2024-11-22 11:25:27.204884: Current learning rate: 0.00479 +2024-11-22 11:25:45.601297: train_loss -0.7973 +2024-11-22 11:25:45.601512: val_loss -0.7651 +2024-11-22 11:25:45.601588: Pseudo dice [0.8459] +2024-11-22 11:25:45.601664: Epoch time: 18.4 s +2024-11-22 11:25:46.439081: +2024-11-22 11:25:46.439278: Epoch 4470 +2024-11-22 11:25:46.439389: Current learning rate: 0.00479 +2024-11-22 11:26:04.221724: train_loss -0.7999 +2024-11-22 11:26:04.221967: val_loss -0.7727 +2024-11-22 11:26:04.222043: Pseudo dice [0.863] +2024-11-22 11:26:04.222129: Epoch time: 17.78 s +2024-11-22 11:26:05.064336: +2024-11-22 11:26:05.064526: Epoch 4471 +2024-11-22 11:26:05.064634: Current learning rate: 0.00479 +2024-11-22 11:26:23.929488: train_loss -0.7849 +2024-11-22 11:26:23.929699: val_loss -0.7711 +2024-11-22 11:26:23.929773: Pseudo dice [0.8569] +2024-11-22 11:26:23.929846: Epoch time: 18.87 s +2024-11-22 11:26:24.774808: +2024-11-22 11:26:24.774984: Epoch 4472 +2024-11-22 11:26:24.775104: Current learning rate: 0.00479 +2024-11-22 11:26:42.857228: train_loss -0.7922 +2024-11-22 11:26:42.857448: val_loss -0.7663 +2024-11-22 11:26:42.857524: Pseudo dice [0.8576] +2024-11-22 11:26:42.857601: Epoch time: 18.08 s +2024-11-22 11:26:43.890029: +2024-11-22 11:26:43.890278: Epoch 4473 +2024-11-22 11:26:43.890392: Current learning rate: 0.00479 +2024-11-22 11:27:02.052562: train_loss -0.7949 +2024-11-22 11:27:02.052785: val_loss -0.7809 +2024-11-22 11:27:02.052863: Pseudo dice [0.8542] +2024-11-22 11:27:02.052942: Epoch time: 18.16 s +2024-11-22 11:27:02.893622: +2024-11-22 11:27:02.893815: Epoch 4474 +2024-11-22 11:27:02.893925: Current learning rate: 0.00478 +2024-11-22 11:27:21.081530: train_loss -0.7935 +2024-11-22 11:27:21.081865: val_loss -0.78 +2024-11-22 11:27:21.081953: Pseudo dice [0.8503] +2024-11-22 11:27:21.082040: Epoch time: 18.19 s +2024-11-22 11:27:22.037319: +2024-11-22 11:27:22.037525: Epoch 4475 +2024-11-22 11:27:22.037643: Current learning rate: 0.00478 +2024-11-22 11:27:40.025144: train_loss -0.7994 +2024-11-22 11:27:40.025350: val_loss -0.7635 +2024-11-22 11:27:40.025422: Pseudo dice [0.8463] +2024-11-22 11:27:40.025496: Epoch time: 17.99 s +2024-11-22 11:27:40.859272: +2024-11-22 11:27:40.859463: Epoch 4476 +2024-11-22 11:27:40.859576: Current learning rate: 0.00478 +2024-11-22 11:27:59.339027: train_loss -0.7839 +2024-11-22 11:27:59.339305: val_loss -0.7836 +2024-11-22 11:27:59.339388: Pseudo dice [0.8613] +2024-11-22 11:27:59.339463: Epoch time: 18.48 s +2024-11-22 11:28:00.186641: +2024-11-22 11:28:00.186836: Epoch 4477 +2024-11-22 11:28:00.186951: Current learning rate: 0.00478 +2024-11-22 11:28:18.719007: train_loss -0.7853 +2024-11-22 11:28:18.719280: val_loss -0.7829 +2024-11-22 11:28:18.719358: Pseudo dice [0.848] +2024-11-22 11:28:18.719434: Epoch time: 18.53 s +2024-11-22 11:28:19.559347: +2024-11-22 11:28:19.559559: Epoch 4478 +2024-11-22 11:28:19.559667: Current learning rate: 0.00478 +2024-11-22 11:28:38.238782: train_loss -0.7879 +2024-11-22 11:28:38.239017: val_loss -0.7556 +2024-11-22 11:28:38.239103: Pseudo dice [0.847] +2024-11-22 11:28:38.239185: Epoch time: 18.68 s +2024-11-22 11:28:39.443478: +2024-11-22 11:28:39.443686: Epoch 4479 +2024-11-22 11:28:39.443796: Current learning rate: 0.00478 +2024-11-22 11:28:57.335050: train_loss -0.7885 +2024-11-22 11:28:57.335266: val_loss -0.7851 +2024-11-22 11:28:57.335343: Pseudo dice [0.8614] +2024-11-22 11:28:57.335416: Epoch time: 17.89 s +2024-11-22 11:28:58.171294: +2024-11-22 11:28:58.171517: Epoch 4480 +2024-11-22 11:28:58.171628: Current learning rate: 0.00478 +2024-11-22 11:29:17.205336: train_loss -0.7884 +2024-11-22 11:29:17.205548: val_loss -0.7766 +2024-11-22 11:29:17.205626: Pseudo dice [0.8464] +2024-11-22 11:29:17.205700: Epoch time: 19.03 s +2024-11-22 11:29:18.040365: +2024-11-22 11:29:18.040599: Epoch 4481 +2024-11-22 11:29:18.040717: Current learning rate: 0.00478 +2024-11-22 11:29:37.343412: train_loss -0.7946 +2024-11-22 11:29:37.343626: val_loss -0.7804 +2024-11-22 11:29:37.343703: Pseudo dice [0.8552] +2024-11-22 11:29:37.343780: Epoch time: 19.3 s +2024-11-22 11:29:38.185336: +2024-11-22 11:29:38.185560: Epoch 4482 +2024-11-22 11:29:38.185675: Current learning rate: 0.00477 +2024-11-22 11:29:56.551328: train_loss -0.789 +2024-11-22 11:29:56.551558: val_loss -0.776 +2024-11-22 11:29:56.551633: Pseudo dice [0.8458] +2024-11-22 11:29:56.551708: Epoch time: 18.37 s +2024-11-22 11:29:57.389655: +2024-11-22 11:29:57.389850: Epoch 4483 +2024-11-22 11:29:57.389963: Current learning rate: 0.00477 +2024-11-22 11:30:15.762298: train_loss -0.7989 +2024-11-22 11:30:15.762559: val_loss -0.7835 +2024-11-22 11:30:15.762638: Pseudo dice [0.8492] +2024-11-22 11:30:15.762712: Epoch time: 18.37 s +2024-11-22 11:30:16.606078: +2024-11-22 11:30:16.606271: Epoch 4484 +2024-11-22 11:30:16.606382: Current learning rate: 0.00477 +2024-11-22 11:30:34.849248: train_loss -0.7917 +2024-11-22 11:30:34.849458: val_loss -0.7884 +2024-11-22 11:30:34.849534: Pseudo dice [0.8626] +2024-11-22 11:30:34.849643: Epoch time: 18.24 s +2024-11-22 11:30:35.694484: +2024-11-22 11:30:35.694673: Epoch 4485 +2024-11-22 11:30:35.694782: Current learning rate: 0.00477 +2024-11-22 11:30:54.583441: train_loss -0.7896 +2024-11-22 11:30:54.583661: val_loss -0.778 +2024-11-22 11:30:54.583737: Pseudo dice [0.8603] +2024-11-22 11:30:54.583818: Epoch time: 18.89 s +2024-11-22 11:30:55.431394: +2024-11-22 11:30:55.431599: Epoch 4486 +2024-11-22 11:30:55.431710: Current learning rate: 0.00477 +2024-11-22 11:31:13.850686: train_loss -0.7909 +2024-11-22 11:31:13.850934: val_loss -0.7479 +2024-11-22 11:31:13.851018: Pseudo dice [0.8544] +2024-11-22 11:31:13.851111: Epoch time: 18.42 s +2024-11-22 11:31:14.693897: +2024-11-22 11:31:14.694143: Epoch 4487 +2024-11-22 11:31:14.694256: Current learning rate: 0.00477 +2024-11-22 11:31:33.620241: train_loss -0.796 +2024-11-22 11:31:33.620451: val_loss -0.7819 +2024-11-22 11:31:33.620524: Pseudo dice [0.8528] +2024-11-22 11:31:33.620598: Epoch time: 18.93 s +2024-11-22 11:31:34.545024: +2024-11-22 11:31:34.545228: Epoch 4488 +2024-11-22 11:31:34.545341: Current learning rate: 0.00477 +2024-11-22 11:31:53.508737: train_loss -0.7877 +2024-11-22 11:31:53.508944: val_loss -0.7601 +2024-11-22 11:31:53.509019: Pseudo dice [0.8483] +2024-11-22 11:31:53.509124: Epoch time: 18.96 s +2024-11-22 11:31:54.348435: +2024-11-22 11:31:54.348654: Epoch 4489 +2024-11-22 11:31:54.348763: Current learning rate: 0.00477 +2024-11-22 11:32:12.397936: train_loss -0.7992 +2024-11-22 11:32:12.398182: val_loss -0.7445 +2024-11-22 11:32:12.398261: Pseudo dice [0.8349] +2024-11-22 11:32:12.398345: Epoch time: 18.05 s +2024-11-22 11:32:13.235246: +2024-11-22 11:32:13.235435: Epoch 4490 +2024-11-22 11:32:13.235549: Current learning rate: 0.00476 +2024-11-22 11:32:31.317530: train_loss -0.7862 +2024-11-22 11:32:31.318012: val_loss -0.7564 +2024-11-22 11:32:31.318117: Pseudo dice [0.8497] +2024-11-22 11:32:31.318269: Epoch time: 18.08 s +2024-11-22 11:32:32.158816: +2024-11-22 11:32:32.159036: Epoch 4491 +2024-11-22 11:32:32.159159: Current learning rate: 0.00476 +2024-11-22 11:32:52.057715: train_loss -0.7945 +2024-11-22 11:32:52.057932: val_loss -0.7609 +2024-11-22 11:32:52.058006: Pseudo dice [0.8614] +2024-11-22 11:32:52.058087: Epoch time: 19.9 s +2024-11-22 11:32:52.895169: +2024-11-22 11:32:52.895368: Epoch 4492 +2024-11-22 11:32:52.895478: Current learning rate: 0.00476 +2024-11-22 11:33:11.479709: train_loss -0.7863 +2024-11-22 11:33:11.479931: val_loss -0.7655 +2024-11-22 11:33:11.480011: Pseudo dice [0.8573] +2024-11-22 11:33:11.480093: Epoch time: 18.59 s +2024-11-22 11:33:12.319899: +2024-11-22 11:33:12.320136: Epoch 4493 +2024-11-22 11:33:12.320253: Current learning rate: 0.00476 +2024-11-22 11:33:31.237363: train_loss -0.7873 +2024-11-22 11:33:31.237608: val_loss -0.7717 +2024-11-22 11:33:31.237689: Pseudo dice [0.8482] +2024-11-22 11:33:31.237770: Epoch time: 18.92 s +2024-11-22 11:33:32.082882: +2024-11-22 11:33:32.083087: Epoch 4494 +2024-11-22 11:33:32.083197: Current learning rate: 0.00476 +2024-11-22 11:33:51.414418: train_loss -0.7819 +2024-11-22 11:33:51.414652: val_loss -0.7572 +2024-11-22 11:33:51.414729: Pseudo dice [0.8414] +2024-11-22 11:33:51.414856: Epoch time: 19.33 s +2024-11-22 11:33:52.299575: +2024-11-22 11:33:52.299793: Epoch 4495 +2024-11-22 11:33:52.299913: Current learning rate: 0.00476 +2024-11-22 11:34:10.781172: train_loss -0.7937 +2024-11-22 11:34:10.781414: val_loss -0.7765 +2024-11-22 11:34:10.781489: Pseudo dice [0.8582] +2024-11-22 11:34:10.781565: Epoch time: 18.48 s +2024-11-22 11:34:11.623699: +2024-11-22 11:34:11.623930: Epoch 4496 +2024-11-22 11:34:11.624044: Current learning rate: 0.00476 +2024-11-22 11:34:30.093198: train_loss -0.7854 +2024-11-22 11:34:30.093426: val_loss -0.7672 +2024-11-22 11:34:30.093507: Pseudo dice [0.8515] +2024-11-22 11:34:30.093587: Epoch time: 18.47 s +2024-11-22 11:34:30.933358: +2024-11-22 11:34:30.933583: Epoch 4497 +2024-11-22 11:34:30.933692: Current learning rate: 0.00476 +2024-11-22 11:34:50.000916: train_loss -0.7918 +2024-11-22 11:34:50.001167: val_loss -0.7738 +2024-11-22 11:34:50.001246: Pseudo dice [0.8488] +2024-11-22 11:34:50.001328: Epoch time: 19.07 s +2024-11-22 11:34:50.852771: +2024-11-22 11:34:50.852994: Epoch 4498 +2024-11-22 11:34:50.853107: Current learning rate: 0.00475 +2024-11-22 11:35:08.243727: train_loss -0.7644 +2024-11-22 11:35:08.243938: val_loss -0.7405 +2024-11-22 11:35:08.244014: Pseudo dice [0.8419] +2024-11-22 11:35:08.244094: Epoch time: 17.39 s +2024-11-22 11:35:09.080144: +2024-11-22 11:35:09.080335: Epoch 4499 +2024-11-22 11:35:09.080446: Current learning rate: 0.00475 +2024-11-22 11:35:27.302749: train_loss -0.7707 +2024-11-22 11:35:27.302965: val_loss -0.7787 +2024-11-22 11:35:27.303146: Pseudo dice [0.8518] +2024-11-22 11:35:27.303225: Epoch time: 18.22 s +2024-11-22 11:35:28.398335: +2024-11-22 11:35:28.398541: Epoch 4500 +2024-11-22 11:35:28.398652: Current learning rate: 0.00475 +2024-11-22 11:35:47.180268: train_loss -0.7807 +2024-11-22 11:35:47.180518: val_loss -0.7726 +2024-11-22 11:35:47.189735: Pseudo dice [0.8513] +2024-11-22 11:35:47.189868: Epoch time: 18.78 s +2024-11-22 11:35:48.114726: +2024-11-22 11:35:48.114963: Epoch 4501 +2024-11-22 11:35:48.115096: Current learning rate: 0.00475 +2024-11-22 11:36:06.349307: train_loss -0.7775 +2024-11-22 11:36:06.349551: val_loss -0.7715 +2024-11-22 11:36:06.349626: Pseudo dice [0.8614] +2024-11-22 11:36:06.349699: Epoch time: 18.24 s +2024-11-22 11:36:07.590329: +2024-11-22 11:36:07.590554: Epoch 4502 +2024-11-22 11:36:07.590664: Current learning rate: 0.00475 +2024-11-22 11:36:25.906586: train_loss -0.7848 +2024-11-22 11:36:25.906802: val_loss -0.7823 +2024-11-22 11:36:25.906904: Pseudo dice [0.858] +2024-11-22 11:36:25.906984: Epoch time: 18.32 s +2024-11-22 11:36:26.740855: +2024-11-22 11:36:26.741066: Epoch 4503 +2024-11-22 11:36:26.741176: Current learning rate: 0.00475 +2024-11-22 11:36:44.134675: train_loss -0.7897 +2024-11-22 11:36:44.134905: val_loss -0.7757 +2024-11-22 11:36:44.134986: Pseudo dice [0.8548] +2024-11-22 11:36:44.135071: Epoch time: 17.39 s +2024-11-22 11:36:44.975306: +2024-11-22 11:36:44.975513: Epoch 4504 +2024-11-22 11:36:44.975623: Current learning rate: 0.00475 +2024-11-22 11:37:04.502231: train_loss -0.7812 +2024-11-22 11:37:04.502469: val_loss -0.764 +2024-11-22 11:37:04.502546: Pseudo dice [0.8517] +2024-11-22 11:37:04.502627: Epoch time: 19.53 s +2024-11-22 11:37:05.345365: +2024-11-22 11:37:05.345567: Epoch 4505 +2024-11-22 11:37:05.345677: Current learning rate: 0.00475 +2024-11-22 11:37:24.340482: train_loss -0.796 +2024-11-22 11:37:24.340693: val_loss -0.7685 +2024-11-22 11:37:24.340766: Pseudo dice [0.8526] +2024-11-22 11:37:24.340838: Epoch time: 19.0 s +2024-11-22 11:37:25.180309: +2024-11-22 11:37:25.180514: Epoch 4506 +2024-11-22 11:37:25.180623: Current learning rate: 0.00474 +2024-11-22 11:37:43.128579: train_loss -0.7996 +2024-11-22 11:37:43.128807: val_loss -0.7748 +2024-11-22 11:37:43.128941: Pseudo dice [0.8525] +2024-11-22 11:37:43.129017: Epoch time: 17.95 s +2024-11-22 11:37:43.974847: +2024-11-22 11:37:43.975054: Epoch 4507 +2024-11-22 11:37:43.975174: Current learning rate: 0.00474 +2024-11-22 11:38:02.793184: train_loss -0.7974 +2024-11-22 11:38:02.793414: val_loss -0.7623 +2024-11-22 11:38:02.795716: Pseudo dice [0.8329] +2024-11-22 11:38:02.795818: Epoch time: 18.82 s +2024-11-22 11:38:03.833201: +2024-11-22 11:38:03.833401: Epoch 4508 +2024-11-22 11:38:03.833515: Current learning rate: 0.00474 +2024-11-22 11:38:22.215756: train_loss -0.7913 +2024-11-22 11:38:22.216005: val_loss -0.7707 +2024-11-22 11:38:22.216088: Pseudo dice [0.8547] +2024-11-22 11:38:22.216172: Epoch time: 18.38 s +2024-11-22 11:38:23.177076: +2024-11-22 11:38:23.177271: Epoch 4509 +2024-11-22 11:38:23.177381: Current learning rate: 0.00474 +2024-11-22 11:38:42.378011: train_loss -0.7915 +2024-11-22 11:38:42.378227: val_loss -0.7619 +2024-11-22 11:38:42.378304: Pseudo dice [0.854] +2024-11-22 11:38:42.378377: Epoch time: 19.2 s +2024-11-22 11:38:43.213649: +2024-11-22 11:38:43.213860: Epoch 4510 +2024-11-22 11:38:43.213972: Current learning rate: 0.00474 +2024-11-22 11:39:01.212688: train_loss -0.7922 +2024-11-22 11:39:01.212893: val_loss -0.793 +2024-11-22 11:39:01.212966: Pseudo dice [0.8612] +2024-11-22 11:39:01.213039: Epoch time: 18.0 s +2024-11-22 11:39:02.079880: +2024-11-22 11:39:02.080109: Epoch 4511 +2024-11-22 11:39:02.080218: Current learning rate: 0.00474 +2024-11-22 11:39:20.175475: train_loss -0.7907 +2024-11-22 11:39:20.175748: val_loss -0.7533 +2024-11-22 11:39:20.175828: Pseudo dice [0.8514] +2024-11-22 11:39:20.175906: Epoch time: 18.1 s +2024-11-22 11:39:21.056547: +2024-11-22 11:39:21.056732: Epoch 4512 +2024-11-22 11:39:21.056841: Current learning rate: 0.00474 +2024-11-22 11:39:40.023694: train_loss -0.7992 +2024-11-22 11:39:40.023938: val_loss -0.7494 +2024-11-22 11:39:40.024014: Pseudo dice [0.8489] +2024-11-22 11:39:40.024097: Epoch time: 18.97 s +2024-11-22 11:39:40.863252: +2024-11-22 11:39:40.863445: Epoch 4513 +2024-11-22 11:39:40.863557: Current learning rate: 0.00474 +2024-11-22 11:39:58.681845: train_loss -0.7912 +2024-11-22 11:39:58.682377: val_loss -0.7889 +2024-11-22 11:39:58.684690: Pseudo dice [0.8579] +2024-11-22 11:39:58.684788: Epoch time: 17.82 s +2024-11-22 11:39:59.572906: +2024-11-22 11:39:59.573102: Epoch 4514 +2024-11-22 11:39:59.573215: Current learning rate: 0.00473 +2024-11-22 11:40:18.586747: train_loss -0.778 +2024-11-22 11:40:18.586962: val_loss -0.7653 +2024-11-22 11:40:18.587037: Pseudo dice [0.8467] +2024-11-22 11:40:18.587115: Epoch time: 19.01 s +2024-11-22 11:40:19.424484: +2024-11-22 11:40:19.424690: Epoch 4515 +2024-11-22 11:40:19.424801: Current learning rate: 0.00473 +2024-11-22 11:40:36.941545: train_loss -0.7909 +2024-11-22 11:40:36.941782: val_loss -0.7697 +2024-11-22 11:40:36.941924: Pseudo dice [0.8577] +2024-11-22 11:40:36.942010: Epoch time: 17.52 s +2024-11-22 11:40:37.782229: +2024-11-22 11:40:37.782429: Epoch 4516 +2024-11-22 11:40:37.782555: Current learning rate: 0.00473 +2024-11-22 11:40:55.651724: train_loss -0.8003 +2024-11-22 11:40:55.651960: val_loss -0.7671 +2024-11-22 11:40:55.652036: Pseudo dice [0.8559] +2024-11-22 11:40:55.652399: Epoch time: 17.87 s +2024-11-22 11:40:56.490769: +2024-11-22 11:40:56.490961: Epoch 4517 +2024-11-22 11:40:56.491077: Current learning rate: 0.00473 +2024-11-22 11:41:15.575280: train_loss -0.7955 +2024-11-22 11:41:15.576290: val_loss -0.7753 +2024-11-22 11:41:15.576385: Pseudo dice [0.8562] +2024-11-22 11:41:15.576460: Epoch time: 19.09 s +2024-11-22 11:41:16.464185: +2024-11-22 11:41:16.464413: Epoch 4518 +2024-11-22 11:41:16.464529: Current learning rate: 0.00473 +2024-11-22 11:41:35.150441: train_loss -0.7858 +2024-11-22 11:41:35.150656: val_loss -0.7706 +2024-11-22 11:41:35.150753: Pseudo dice [0.8508] +2024-11-22 11:41:35.150825: Epoch time: 18.69 s +2024-11-22 11:41:36.009950: +2024-11-22 11:41:36.010146: Epoch 4519 +2024-11-22 11:41:36.010257: Current learning rate: 0.00473 +2024-11-22 11:41:53.767260: train_loss -0.7983 +2024-11-22 11:41:53.767496: val_loss -0.7664 +2024-11-22 11:41:53.767570: Pseudo dice [0.8485] +2024-11-22 11:41:53.767651: Epoch time: 17.76 s +2024-11-22 11:41:54.707839: +2024-11-22 11:41:54.708093: Epoch 4520 +2024-11-22 11:41:54.708205: Current learning rate: 0.00473 +2024-11-22 11:42:13.495978: train_loss -0.7915 +2024-11-22 11:42:13.496196: val_loss -0.7533 +2024-11-22 11:42:13.496271: Pseudo dice [0.867] +2024-11-22 11:42:13.496343: Epoch time: 18.79 s +2024-11-22 11:42:14.335380: +2024-11-22 11:42:14.335593: Epoch 4521 +2024-11-22 11:42:14.335703: Current learning rate: 0.00473 +2024-11-22 11:42:33.121655: train_loss -0.7947 +2024-11-22 11:42:33.121868: val_loss -0.7804 +2024-11-22 11:42:33.121944: Pseudo dice [0.8552] +2024-11-22 11:42:33.122033: Epoch time: 18.79 s +2024-11-22 11:42:33.956110: +2024-11-22 11:42:33.956284: Epoch 4522 +2024-11-22 11:42:33.956397: Current learning rate: 0.00473 +2024-11-22 11:42:53.291194: train_loss -0.7946 +2024-11-22 11:42:53.291402: val_loss -0.7841 +2024-11-22 11:42:53.291476: Pseudo dice [0.8583] +2024-11-22 11:42:53.291549: Epoch time: 19.34 s +2024-11-22 11:42:54.129936: +2024-11-22 11:42:54.130162: Epoch 4523 +2024-11-22 11:42:54.130274: Current learning rate: 0.00472 +2024-11-22 11:43:11.495867: train_loss -0.8 +2024-11-22 11:43:11.496119: val_loss -0.7703 +2024-11-22 11:43:11.496198: Pseudo dice [0.858] +2024-11-22 11:43:11.496279: Epoch time: 17.37 s +2024-11-22 11:43:12.334950: +2024-11-22 11:43:12.335170: Epoch 4524 +2024-11-22 11:43:12.335287: Current learning rate: 0.00472 +2024-11-22 11:43:31.257051: train_loss -0.7967 +2024-11-22 11:43:31.257270: val_loss -0.7234 +2024-11-22 11:43:31.257348: Pseudo dice [0.8449] +2024-11-22 11:43:31.257420: Epoch time: 18.92 s +2024-11-22 11:43:32.510631: +2024-11-22 11:43:32.510866: Epoch 4525 +2024-11-22 11:43:32.510977: Current learning rate: 0.00472 +2024-11-22 11:43:51.476635: train_loss -0.7968 +2024-11-22 11:43:51.476854: val_loss -0.7755 +2024-11-22 11:43:51.476928: Pseudo dice [0.8572] +2024-11-22 11:43:51.477001: Epoch time: 18.97 s +2024-11-22 11:43:52.314620: +2024-11-22 11:43:52.314847: Epoch 4526 +2024-11-22 11:43:52.314956: Current learning rate: 0.00472 +2024-11-22 11:44:11.320229: train_loss -0.794 +2024-11-22 11:44:11.320444: val_loss -0.7607 +2024-11-22 11:44:11.320518: Pseudo dice [0.8441] +2024-11-22 11:44:11.320594: Epoch time: 19.01 s +2024-11-22 11:44:12.157649: +2024-11-22 11:44:12.157854: Epoch 4527 +2024-11-22 11:44:12.157966: Current learning rate: 0.00472 +2024-11-22 11:44:30.119754: train_loss -0.801 +2024-11-22 11:44:30.119992: val_loss -0.7832 +2024-11-22 11:44:30.120144: Pseudo dice [0.8596] +2024-11-22 11:44:30.120258: Epoch time: 17.96 s +2024-11-22 11:44:30.963379: +2024-11-22 11:44:30.963606: Epoch 4528 +2024-11-22 11:44:30.963716: Current learning rate: 0.00472 +2024-11-22 11:44:50.127862: train_loss -0.7928 +2024-11-22 11:44:50.128091: val_loss -0.7514 +2024-11-22 11:44:50.128168: Pseudo dice [0.8578] +2024-11-22 11:44:50.128243: Epoch time: 19.17 s +2024-11-22 11:44:50.966190: +2024-11-22 11:44:50.966391: Epoch 4529 +2024-11-22 11:44:50.966503: Current learning rate: 0.00472 +2024-11-22 11:45:09.213046: train_loss -0.7925 +2024-11-22 11:45:09.213261: val_loss -0.7449 +2024-11-22 11:45:09.213357: Pseudo dice [0.8427] +2024-11-22 11:45:09.213434: Epoch time: 18.25 s +2024-11-22 11:45:10.054731: +2024-11-22 11:45:10.054931: Epoch 4530 +2024-11-22 11:45:10.055048: Current learning rate: 0.00472 +2024-11-22 11:45:27.917588: train_loss -0.8013 +2024-11-22 11:45:27.917814: val_loss -0.7723 +2024-11-22 11:45:27.917890: Pseudo dice [0.8554] +2024-11-22 11:45:27.917967: Epoch time: 17.86 s +2024-11-22 11:45:28.760439: +2024-11-22 11:45:28.760631: Epoch 4531 +2024-11-22 11:45:28.760742: Current learning rate: 0.00471 +2024-11-22 11:45:47.253255: train_loss -0.8042 +2024-11-22 11:45:47.253497: val_loss -0.7662 +2024-11-22 11:45:47.253572: Pseudo dice [0.8451] +2024-11-22 11:45:47.253649: Epoch time: 18.49 s +2024-11-22 11:45:48.095219: +2024-11-22 11:45:48.095412: Epoch 4532 +2024-11-22 11:45:48.095527: Current learning rate: 0.00471 +2024-11-22 11:46:06.796130: train_loss -0.7915 +2024-11-22 11:46:06.796335: val_loss -0.7844 +2024-11-22 11:46:06.796408: Pseudo dice [0.8532] +2024-11-22 11:46:06.796480: Epoch time: 18.7 s +2024-11-22 11:46:07.641931: +2024-11-22 11:46:07.642164: Epoch 4533 +2024-11-22 11:46:07.642271: Current learning rate: 0.00471 +2024-11-22 11:46:25.003281: train_loss -0.7909 +2024-11-22 11:46:25.003504: val_loss -0.7751 +2024-11-22 11:46:25.003580: Pseudo dice [0.8601] +2024-11-22 11:46:25.003658: Epoch time: 17.36 s +2024-11-22 11:46:25.874764: +2024-11-22 11:46:25.874957: Epoch 4534 +2024-11-22 11:46:25.875078: Current learning rate: 0.00471 +2024-11-22 11:46:44.293068: train_loss -0.7887 +2024-11-22 11:46:44.293313: val_loss -0.7821 +2024-11-22 11:46:44.293387: Pseudo dice [0.855] +2024-11-22 11:46:44.293464: Epoch time: 18.42 s +2024-11-22 11:46:45.178582: +2024-11-22 11:46:45.178801: Epoch 4535 +2024-11-22 11:46:45.178914: Current learning rate: 0.00471 +2024-11-22 11:47:03.826091: train_loss -0.7911 +2024-11-22 11:47:03.826364: val_loss -0.7782 +2024-11-22 11:47:03.826442: Pseudo dice [0.8524] +2024-11-22 11:47:03.826514: Epoch time: 18.65 s +2024-11-22 11:47:04.684166: +2024-11-22 11:47:04.684376: Epoch 4536 +2024-11-22 11:47:04.684486: Current learning rate: 0.00471 +2024-11-22 11:47:22.709177: train_loss -0.7874 +2024-11-22 11:47:22.709612: val_loss -0.7615 +2024-11-22 11:47:22.709710: Pseudo dice [0.8484] +2024-11-22 11:47:22.709785: Epoch time: 18.03 s +2024-11-22 11:47:23.551809: +2024-11-22 11:47:23.552022: Epoch 4537 +2024-11-22 11:47:23.552139: Current learning rate: 0.00471 +2024-11-22 11:47:42.597278: train_loss -0.7856 +2024-11-22 11:47:42.597524: val_loss -0.778 +2024-11-22 11:47:42.597600: Pseudo dice [0.8628] +2024-11-22 11:47:42.597694: Epoch time: 19.05 s +2024-11-22 11:47:43.446081: +2024-11-22 11:47:43.446295: Epoch 4538 +2024-11-22 11:47:43.446402: Current learning rate: 0.00471 +2024-11-22 11:48:02.633960: train_loss -0.7936 +2024-11-22 11:48:02.634168: val_loss -0.7711 +2024-11-22 11:48:02.634242: Pseudo dice [0.8539] +2024-11-22 11:48:02.634314: Epoch time: 19.19 s +2024-11-22 11:48:03.473533: +2024-11-22 11:48:03.473757: Epoch 4539 +2024-11-22 11:48:03.473868: Current learning rate: 0.0047 +2024-11-22 11:48:21.339588: train_loss -0.7899 +2024-11-22 11:48:21.339791: val_loss -0.7755 +2024-11-22 11:48:21.339866: Pseudo dice [0.8498] +2024-11-22 11:48:21.339939: Epoch time: 17.87 s +2024-11-22 11:48:22.175561: +2024-11-22 11:48:22.175777: Epoch 4540 +2024-11-22 11:48:22.175884: Current learning rate: 0.0047 +2024-11-22 11:48:41.150160: train_loss -0.7891 +2024-11-22 11:48:41.150386: val_loss -0.7725 +2024-11-22 11:48:41.150469: Pseudo dice [0.8447] +2024-11-22 11:48:41.150548: Epoch time: 18.98 s +2024-11-22 11:48:41.992942: +2024-11-22 11:48:41.993145: Epoch 4541 +2024-11-22 11:48:41.993255: Current learning rate: 0.0047 +2024-11-22 11:48:59.700804: train_loss -0.7802 +2024-11-22 11:48:59.701044: val_loss -0.7867 +2024-11-22 11:48:59.702413: Pseudo dice [0.8604] +2024-11-22 11:48:59.702508: Epoch time: 17.71 s +2024-11-22 11:49:00.543489: +2024-11-22 11:49:00.543709: Epoch 4542 +2024-11-22 11:49:00.543828: Current learning rate: 0.0047 +2024-11-22 11:49:18.599201: train_loss -0.7903 +2024-11-22 11:49:18.599408: val_loss -0.7999 +2024-11-22 11:49:18.599721: Pseudo dice [0.8657] +2024-11-22 11:49:18.599803: Epoch time: 18.06 s +2024-11-22 11:49:19.437714: +2024-11-22 11:49:19.437915: Epoch 4543 +2024-11-22 11:49:19.438026: Current learning rate: 0.0047 +2024-11-22 11:49:39.045105: train_loss -0.7848 +2024-11-22 11:49:39.045327: val_loss -0.7707 +2024-11-22 11:49:39.045397: Pseudo dice [0.8476] +2024-11-22 11:49:39.045474: Epoch time: 19.61 s +2024-11-22 11:49:39.988556: +2024-11-22 11:49:39.988745: Epoch 4544 +2024-11-22 11:49:39.988856: Current learning rate: 0.0047 +2024-11-22 11:49:58.833888: train_loss -0.7821 +2024-11-22 11:49:58.834180: val_loss -0.7509 +2024-11-22 11:49:58.834263: Pseudo dice [0.8631] +2024-11-22 11:49:58.834343: Epoch time: 18.85 s +2024-11-22 11:49:59.679591: +2024-11-22 11:49:59.679811: Epoch 4545 +2024-11-22 11:49:59.679925: Current learning rate: 0.0047 +2024-11-22 11:50:17.221912: train_loss -0.7845 +2024-11-22 11:50:17.222152: val_loss -0.772 +2024-11-22 11:50:17.222227: Pseudo dice [0.8486] +2024-11-22 11:50:17.222301: Epoch time: 17.54 s +2024-11-22 11:50:18.062741: +2024-11-22 11:50:18.062946: Epoch 4546 +2024-11-22 11:50:18.063052: Current learning rate: 0.0047 +2024-11-22 11:50:36.632858: train_loss -0.7875 +2024-11-22 11:50:36.633081: val_loss -0.7669 +2024-11-22 11:50:36.633161: Pseudo dice [0.8523] +2024-11-22 11:50:36.633236: Epoch time: 18.57 s +2024-11-22 11:50:37.579726: +2024-11-22 11:50:37.579947: Epoch 4547 +2024-11-22 11:50:37.580065: Current learning rate: 0.00469 +2024-11-22 11:50:56.685989: train_loss -0.7776 +2024-11-22 11:50:56.686211: val_loss -0.7534 +2024-11-22 11:50:56.686285: Pseudo dice [0.8522] +2024-11-22 11:50:56.686360: Epoch time: 19.11 s +2024-11-22 11:50:57.937476: +2024-11-22 11:50:57.937660: Epoch 4548 +2024-11-22 11:50:57.937771: Current learning rate: 0.00469 +2024-11-22 11:51:15.761027: train_loss -0.783 +2024-11-22 11:51:15.761254: val_loss -0.7938 +2024-11-22 11:51:15.761333: Pseudo dice [0.8546] +2024-11-22 11:51:15.761413: Epoch time: 17.82 s +2024-11-22 11:51:16.606642: +2024-11-22 11:51:16.606852: Epoch 4549 +2024-11-22 11:51:16.606967: Current learning rate: 0.00469 +2024-11-22 11:51:35.782183: train_loss -0.7921 +2024-11-22 11:51:35.782417: val_loss -0.7826 +2024-11-22 11:51:35.782490: Pseudo dice [0.8489] +2024-11-22 11:51:35.782563: Epoch time: 19.18 s +2024-11-22 11:51:36.895269: +2024-11-22 11:51:36.895468: Epoch 4550 +2024-11-22 11:51:36.895578: Current learning rate: 0.00469 +2024-11-22 11:51:54.810766: train_loss -0.7883 +2024-11-22 11:51:54.810976: val_loss -0.7679 +2024-11-22 11:51:54.811049: Pseudo dice [0.8567] +2024-11-22 11:51:54.811149: Epoch time: 17.92 s +2024-11-22 11:51:55.654812: +2024-11-22 11:51:55.655033: Epoch 4551 +2024-11-22 11:51:55.655150: Current learning rate: 0.00469 +2024-11-22 11:52:14.954208: train_loss -0.7863 +2024-11-22 11:52:14.954421: val_loss -0.774 +2024-11-22 11:52:14.954502: Pseudo dice [0.8625] +2024-11-22 11:52:14.954577: Epoch time: 19.3 s +2024-11-22 11:52:15.803572: +2024-11-22 11:52:15.803791: Epoch 4552 +2024-11-22 11:52:15.803901: Current learning rate: 0.00469 +2024-11-22 11:52:34.584897: train_loss -0.7801 +2024-11-22 11:52:34.585151: val_loss -0.7715 +2024-11-22 11:52:34.585225: Pseudo dice [0.8383] +2024-11-22 11:52:34.585307: Epoch time: 18.78 s +2024-11-22 11:52:35.477490: +2024-11-22 11:52:35.477700: Epoch 4553 +2024-11-22 11:52:35.477815: Current learning rate: 0.00469 +2024-11-22 11:52:54.601918: train_loss -0.7842 +2024-11-22 11:52:54.602138: val_loss -0.7609 +2024-11-22 11:52:54.602211: Pseudo dice [0.8552] +2024-11-22 11:52:54.602284: Epoch time: 19.13 s +2024-11-22 11:52:55.447151: +2024-11-22 11:52:55.447366: Epoch 4554 +2024-11-22 11:52:55.447477: Current learning rate: 0.00469 +2024-11-22 11:53:14.581525: train_loss -0.7936 +2024-11-22 11:53:14.581735: val_loss -0.7504 +2024-11-22 11:53:14.581809: Pseudo dice [0.8584] +2024-11-22 11:53:14.581883: Epoch time: 19.14 s +2024-11-22 11:53:15.434072: +2024-11-22 11:53:15.434283: Epoch 4555 +2024-11-22 11:53:15.434394: Current learning rate: 0.00468 +2024-11-22 11:53:34.891820: train_loss -0.7883 +2024-11-22 11:53:34.892038: val_loss -0.7813 +2024-11-22 11:53:34.892121: Pseudo dice [0.8562] +2024-11-22 11:53:34.892201: Epoch time: 19.46 s +2024-11-22 11:53:35.740752: +2024-11-22 11:53:35.740994: Epoch 4556 +2024-11-22 11:53:35.741114: Current learning rate: 0.00468 +2024-11-22 11:53:55.342633: train_loss -0.7901 +2024-11-22 11:53:55.342846: val_loss -0.7856 +2024-11-22 11:53:55.342920: Pseudo dice [0.8716] +2024-11-22 11:53:55.342994: Epoch time: 19.6 s +2024-11-22 11:53:56.321005: +2024-11-22 11:53:56.321214: Epoch 4557 +2024-11-22 11:53:56.321328: Current learning rate: 0.00468 +2024-11-22 11:54:14.272799: train_loss -0.7881 +2024-11-22 11:54:14.273074: val_loss -0.7733 +2024-11-22 11:54:14.273152: Pseudo dice [0.8733] +2024-11-22 11:54:14.273235: Epoch time: 17.95 s +2024-11-22 11:54:14.273299: Yayy! New best EMA pseudo Dice: 0.8575 +2024-11-22 11:54:15.398230: +2024-11-22 11:54:15.398440: Epoch 4558 +2024-11-22 11:54:15.398552: Current learning rate: 0.00468 +2024-11-22 11:54:34.087308: train_loss -0.7932 +2024-11-22 11:54:34.087524: val_loss -0.7797 +2024-11-22 11:54:34.087598: Pseudo dice [0.8442] +2024-11-22 11:54:34.087672: Epoch time: 18.69 s +2024-11-22 11:54:35.341769: +2024-11-22 11:54:35.341988: Epoch 4559 +2024-11-22 11:54:35.342099: Current learning rate: 0.00468 +2024-11-22 11:54:54.828809: train_loss -0.7929 +2024-11-22 11:54:54.829028: val_loss -0.7556 +2024-11-22 11:54:54.829109: Pseudo dice [0.8532] +2024-11-22 11:54:54.829188: Epoch time: 19.49 s +2024-11-22 11:54:55.674134: +2024-11-22 11:54:55.674385: Epoch 4560 +2024-11-22 11:54:55.674501: Current learning rate: 0.00468 +2024-11-22 11:55:15.051052: train_loss -0.7863 +2024-11-22 11:55:15.051261: val_loss -0.7702 +2024-11-22 11:55:15.051334: Pseudo dice [0.8635] +2024-11-22 11:55:15.051406: Epoch time: 19.38 s +2024-11-22 11:55:15.881943: +2024-11-22 11:55:15.882148: Epoch 4561 +2024-11-22 11:55:15.882258: Current learning rate: 0.00468 +2024-11-22 11:55:33.171374: train_loss -0.787 +2024-11-22 11:55:33.171581: val_loss -0.7462 +2024-11-22 11:55:33.171654: Pseudo dice [0.8547] +2024-11-22 11:55:33.171725: Epoch time: 17.29 s +2024-11-22 11:55:34.028653: +2024-11-22 11:55:34.028869: Epoch 4562 +2024-11-22 11:55:34.028977: Current learning rate: 0.00468 +2024-11-22 11:55:52.276117: train_loss -0.7919 +2024-11-22 11:55:52.276326: val_loss -0.7804 +2024-11-22 11:55:52.276400: Pseudo dice [0.8427] +2024-11-22 11:55:52.276473: Epoch time: 18.25 s +2024-11-22 11:55:53.190272: +2024-11-22 11:55:53.190491: Epoch 4563 +2024-11-22 11:55:53.190601: Current learning rate: 0.00467 +2024-11-22 11:56:11.261978: train_loss -0.7883 +2024-11-22 11:56:11.262217: val_loss -0.7816 +2024-11-22 11:56:11.262293: Pseudo dice [0.8451] +2024-11-22 11:56:11.262374: Epoch time: 18.07 s +2024-11-22 11:56:12.126667: +2024-11-22 11:56:12.126862: Epoch 4564 +2024-11-22 11:56:12.126979: Current learning rate: 0.00467 +2024-11-22 11:56:31.158264: train_loss -0.7968 +2024-11-22 11:56:31.158553: val_loss -0.7689 +2024-11-22 11:56:31.158633: Pseudo dice [0.8405] +2024-11-22 11:56:31.158716: Epoch time: 19.03 s +2024-11-22 11:56:32.001373: +2024-11-22 11:56:32.001577: Epoch 4565 +2024-11-22 11:56:32.001684: Current learning rate: 0.00467 +2024-11-22 11:56:49.515033: train_loss -0.7889 +2024-11-22 11:56:49.515247: val_loss -0.7554 +2024-11-22 11:56:49.515320: Pseudo dice [0.8461] +2024-11-22 11:56:49.515393: Epoch time: 17.51 s +2024-11-22 11:56:50.360772: +2024-11-22 11:56:50.360971: Epoch 4566 +2024-11-22 11:56:50.361089: Current learning rate: 0.00467 +2024-11-22 11:57:09.304582: train_loss -0.8004 +2024-11-22 11:57:09.304791: val_loss -0.7833 +2024-11-22 11:57:09.304868: Pseudo dice [0.8685] +2024-11-22 11:57:09.304944: Epoch time: 18.94 s +2024-11-22 11:57:10.155507: +2024-11-22 11:57:10.155747: Epoch 4567 +2024-11-22 11:57:10.155894: Current learning rate: 0.00467 +2024-11-22 11:57:29.242844: train_loss -0.7984 +2024-11-22 11:57:29.243090: val_loss -0.7997 +2024-11-22 11:57:29.243172: Pseudo dice [0.8682] +2024-11-22 11:57:29.243257: Epoch time: 19.09 s +2024-11-22 11:57:30.083005: +2024-11-22 11:57:30.083180: Epoch 4568 +2024-11-22 11:57:30.083287: Current learning rate: 0.00467 +2024-11-22 11:57:48.215204: train_loss -0.7966 +2024-11-22 11:57:48.215429: val_loss -0.7604 +2024-11-22 11:57:48.215513: Pseudo dice [0.8499] +2024-11-22 11:57:48.215585: Epoch time: 18.13 s +2024-11-22 11:57:49.053891: +2024-11-22 11:57:49.054120: Epoch 4569 +2024-11-22 11:57:49.054230: Current learning rate: 0.00467 +2024-11-22 11:58:07.726213: train_loss -0.7891 +2024-11-22 11:58:07.726433: val_loss -0.7782 +2024-11-22 11:58:07.726511: Pseudo dice [0.8565] +2024-11-22 11:58:07.726587: Epoch time: 18.67 s +2024-11-22 11:58:08.562767: +2024-11-22 11:58:08.562989: Epoch 4570 +2024-11-22 11:58:08.563102: Current learning rate: 0.00467 +2024-11-22 11:58:28.071171: train_loss -0.7927 +2024-11-22 11:58:28.071381: val_loss -0.7691 +2024-11-22 11:58:28.071457: Pseudo dice [0.8488] +2024-11-22 11:58:28.071575: Epoch time: 19.51 s +2024-11-22 11:58:29.375256: +2024-11-22 11:58:29.375479: Epoch 4571 +2024-11-22 11:58:29.375591: Current learning rate: 0.00467 +2024-11-22 11:58:46.765687: train_loss -0.7642 +2024-11-22 11:58:46.765944: val_loss -0.7573 +2024-11-22 11:58:46.766019: Pseudo dice [0.8448] +2024-11-22 11:58:46.766102: Epoch time: 17.39 s +2024-11-22 11:58:47.605686: +2024-11-22 11:58:47.605921: Epoch 4572 +2024-11-22 11:58:47.606036: Current learning rate: 0.00466 +2024-11-22 11:59:05.991138: train_loss -0.7651 +2024-11-22 11:59:05.991354: val_loss -0.7652 +2024-11-22 11:59:05.991436: Pseudo dice [0.8359] +2024-11-22 11:59:05.991512: Epoch time: 18.39 s +2024-11-22 11:59:06.830557: +2024-11-22 11:59:06.830762: Epoch 4573 +2024-11-22 11:59:06.830871: Current learning rate: 0.00466 +2024-11-22 11:59:24.906128: train_loss -0.7828 +2024-11-22 11:59:24.906406: val_loss -0.7759 +2024-11-22 11:59:24.906490: Pseudo dice [0.8609] +2024-11-22 11:59:24.906629: Epoch time: 18.08 s +2024-11-22 11:59:25.746993: +2024-11-22 11:59:25.747231: Epoch 4574 +2024-11-22 11:59:25.747347: Current learning rate: 0.00466 +2024-11-22 11:59:44.486142: train_loss -0.7864 +2024-11-22 11:59:44.486373: val_loss -0.7702 +2024-11-22 11:59:44.486449: Pseudo dice [0.8362] +2024-11-22 11:59:44.486527: Epoch time: 18.74 s +2024-11-22 11:59:45.512055: +2024-11-22 11:59:45.512283: Epoch 4575 +2024-11-22 11:59:45.512418: Current learning rate: 0.00466 +2024-11-22 12:00:03.487907: train_loss -0.7907 +2024-11-22 12:00:03.488133: val_loss -0.7424 +2024-11-22 12:00:03.488207: Pseudo dice [0.8571] +2024-11-22 12:00:03.488282: Epoch time: 17.98 s +2024-11-22 12:00:04.471793: +2024-11-22 12:00:04.472010: Epoch 4576 +2024-11-22 12:00:04.472129: Current learning rate: 0.00466 +2024-11-22 12:00:23.551240: train_loss -0.7788 +2024-11-22 12:00:23.551452: val_loss -0.7624 +2024-11-22 12:00:23.551527: Pseudo dice [0.8544] +2024-11-22 12:00:23.551601: Epoch time: 19.08 s +2024-11-22 12:00:24.409567: +2024-11-22 12:00:24.409789: Epoch 4577 +2024-11-22 12:00:24.409901: Current learning rate: 0.00466 +2024-11-22 12:00:42.134052: train_loss -0.7878 +2024-11-22 12:00:42.134276: val_loss -0.754 +2024-11-22 12:00:42.134353: Pseudo dice [0.845] +2024-11-22 12:00:42.134429: Epoch time: 17.73 s +2024-11-22 12:00:42.969954: +2024-11-22 12:00:42.970147: Epoch 4578 +2024-11-22 12:00:42.970258: Current learning rate: 0.00466 +2024-11-22 12:01:01.807966: train_loss -0.7738 +2024-11-22 12:01:01.808226: val_loss -0.7599 +2024-11-22 12:01:01.808307: Pseudo dice [0.8519] +2024-11-22 12:01:01.808392: Epoch time: 18.84 s +2024-11-22 12:01:02.658811: +2024-11-22 12:01:02.659005: Epoch 4579 +2024-11-22 12:01:02.659122: Current learning rate: 0.00466 +2024-11-22 12:01:20.748062: train_loss -0.7764 +2024-11-22 12:01:20.748274: val_loss -0.763 +2024-11-22 12:01:20.748349: Pseudo dice [0.8447] +2024-11-22 12:01:20.748425: Epoch time: 18.09 s +2024-11-22 12:01:21.879853: +2024-11-22 12:01:21.880050: Epoch 4580 +2024-11-22 12:01:21.880163: Current learning rate: 0.00465 +2024-11-22 12:01:39.582917: train_loss -0.7808 +2024-11-22 12:01:39.583134: val_loss -0.764 +2024-11-22 12:01:39.583210: Pseudo dice [0.85] +2024-11-22 12:01:39.583284: Epoch time: 17.7 s +2024-11-22 12:01:40.429220: +2024-11-22 12:01:40.429434: Epoch 4581 +2024-11-22 12:01:40.429542: Current learning rate: 0.00465 +2024-11-22 12:01:58.625014: train_loss -0.7895 +2024-11-22 12:01:58.625236: val_loss -0.7798 +2024-11-22 12:01:58.625314: Pseudo dice [0.8621] +2024-11-22 12:01:58.625393: Epoch time: 18.2 s +2024-11-22 12:01:59.537217: +2024-11-22 12:01:59.537434: Epoch 4582 +2024-11-22 12:01:59.537546: Current learning rate: 0.00465 +2024-11-22 12:02:19.020491: train_loss -0.7889 +2024-11-22 12:02:19.023146: val_loss -0.7788 +2024-11-22 12:02:19.023245: Pseudo dice [0.8497] +2024-11-22 12:02:19.023321: Epoch time: 19.48 s +2024-11-22 12:02:19.892407: +2024-11-22 12:02:19.892638: Epoch 4583 +2024-11-22 12:02:19.892747: Current learning rate: 0.00465 +2024-11-22 12:02:39.358538: train_loss -0.7815 +2024-11-22 12:02:39.358748: val_loss -0.7545 +2024-11-22 12:02:39.358827: Pseudo dice [0.8451] +2024-11-22 12:02:39.358902: Epoch time: 19.47 s +2024-11-22 12:02:40.214189: +2024-11-22 12:02:40.214405: Epoch 4584 +2024-11-22 12:02:40.214516: Current learning rate: 0.00465 +2024-11-22 12:02:57.823078: train_loss -0.7807 +2024-11-22 12:02:57.823299: val_loss -0.7667 +2024-11-22 12:02:57.823373: Pseudo dice [0.8495] +2024-11-22 12:02:57.823448: Epoch time: 17.61 s +2024-11-22 12:02:58.673720: +2024-11-22 12:02:58.673950: Epoch 4585 +2024-11-22 12:02:58.674063: Current learning rate: 0.00465 +2024-11-22 12:03:17.272289: train_loss -0.7986 +2024-11-22 12:03:17.272505: val_loss -0.7745 +2024-11-22 12:03:17.272580: Pseudo dice [0.8482] +2024-11-22 12:03:17.272708: Epoch time: 18.6 s +2024-11-22 12:03:18.166393: +2024-11-22 12:03:18.166622: Epoch 4586 +2024-11-22 12:03:18.166733: Current learning rate: 0.00465 +2024-11-22 12:03:36.175690: train_loss -0.7941 +2024-11-22 12:03:36.175926: val_loss -0.7638 +2024-11-22 12:03:36.176003: Pseudo dice [0.8492] +2024-11-22 12:03:36.176109: Epoch time: 18.01 s +2024-11-22 12:03:37.023503: +2024-11-22 12:03:37.023717: Epoch 4587 +2024-11-22 12:03:37.023826: Current learning rate: 0.00465 +2024-11-22 12:03:55.465002: train_loss -0.7917 +2024-11-22 12:03:55.465240: val_loss -0.7612 +2024-11-22 12:03:55.465324: Pseudo dice [0.8516] +2024-11-22 12:03:55.465401: Epoch time: 18.44 s +2024-11-22 12:03:56.330545: +2024-11-22 12:03:56.330764: Epoch 4588 +2024-11-22 12:03:56.330871: Current learning rate: 0.00464 +2024-11-22 12:04:15.063154: train_loss -0.7945 +2024-11-22 12:04:15.063365: val_loss -0.7874 +2024-11-22 12:04:15.063437: Pseudo dice [0.8609] +2024-11-22 12:04:15.063511: Epoch time: 18.73 s +2024-11-22 12:04:15.908902: +2024-11-22 12:04:15.909099: Epoch 4589 +2024-11-22 12:04:15.909209: Current learning rate: 0.00464 +2024-11-22 12:04:33.852183: train_loss -0.7896 +2024-11-22 12:04:33.852391: val_loss -0.7645 +2024-11-22 12:04:33.852467: Pseudo dice [0.8467] +2024-11-22 12:04:33.852542: Epoch time: 17.94 s +2024-11-22 12:04:34.702155: +2024-11-22 12:04:34.702478: Epoch 4590 +2024-11-22 12:04:34.702596: Current learning rate: 0.00464 +2024-11-22 12:04:53.082685: train_loss -0.7914 +2024-11-22 12:04:53.082906: val_loss -0.7723 +2024-11-22 12:04:53.082988: Pseudo dice [0.8437] +2024-11-22 12:04:53.083070: Epoch time: 18.38 s +2024-11-22 12:04:53.994661: +2024-11-22 12:04:53.994845: Epoch 4591 +2024-11-22 12:04:53.994952: Current learning rate: 0.00464 +2024-11-22 12:05:12.429309: train_loss -0.7876 +2024-11-22 12:05:12.429517: val_loss -0.765 +2024-11-22 12:05:12.429658: Pseudo dice [0.8569] +2024-11-22 12:05:12.429738: Epoch time: 18.44 s +2024-11-22 12:05:13.264096: +2024-11-22 12:05:13.264289: Epoch 4592 +2024-11-22 12:05:13.264401: Current learning rate: 0.00464 +2024-11-22 12:05:31.960320: train_loss -0.783 +2024-11-22 12:05:31.960536: val_loss -0.7543 +2024-11-22 12:05:31.960608: Pseudo dice [0.8547] +2024-11-22 12:05:31.960680: Epoch time: 18.7 s +2024-11-22 12:05:32.805001: +2024-11-22 12:05:32.805209: Epoch 4593 +2024-11-22 12:05:32.805318: Current learning rate: 0.00464 +2024-11-22 12:05:51.154153: train_loss -0.7884 +2024-11-22 12:05:51.154433: val_loss -0.7668 +2024-11-22 12:05:51.154521: Pseudo dice [0.8467] +2024-11-22 12:05:51.154616: Epoch time: 18.35 s +2024-11-22 12:05:52.386645: +2024-11-22 12:05:52.386881: Epoch 4594 +2024-11-22 12:05:52.386995: Current learning rate: 0.00464 +2024-11-22 12:06:11.445662: train_loss -0.7881 +2024-11-22 12:06:11.445937: val_loss -0.784 +2024-11-22 12:06:11.446015: Pseudo dice [0.8548] +2024-11-22 12:06:11.446094: Epoch time: 19.06 s +2024-11-22 12:06:12.286470: +2024-11-22 12:06:12.286683: Epoch 4595 +2024-11-22 12:06:12.286793: Current learning rate: 0.00464 +2024-11-22 12:06:31.047907: train_loss -0.7903 +2024-11-22 12:06:31.048123: val_loss -0.7814 +2024-11-22 12:06:31.048201: Pseudo dice [0.856] +2024-11-22 12:06:31.048275: Epoch time: 18.76 s +2024-11-22 12:06:31.886733: +2024-11-22 12:06:31.886937: Epoch 4596 +2024-11-22 12:06:31.887048: Current learning rate: 0.00463 +2024-11-22 12:06:49.654866: train_loss -0.7833 +2024-11-22 12:06:49.655088: val_loss -0.7811 +2024-11-22 12:06:49.655164: Pseudo dice [0.8545] +2024-11-22 12:06:49.655238: Epoch time: 17.77 s +2024-11-22 12:06:50.669381: +2024-11-22 12:06:50.669573: Epoch 4597 +2024-11-22 12:06:50.669683: Current learning rate: 0.00463 +2024-11-22 12:07:09.030402: train_loss -0.7983 +2024-11-22 12:07:09.030649: val_loss -0.7761 +2024-11-22 12:07:09.030726: Pseudo dice [0.8645] +2024-11-22 12:07:09.030844: Epoch time: 18.36 s +2024-11-22 12:07:09.908135: +2024-11-22 12:07:09.908348: Epoch 4598 +2024-11-22 12:07:09.908461: Current learning rate: 0.00463 +2024-11-22 12:07:28.166589: train_loss -0.7965 +2024-11-22 12:07:28.166806: val_loss -0.7789 +2024-11-22 12:07:28.166889: Pseudo dice [0.8471] +2024-11-22 12:07:28.166969: Epoch time: 18.26 s +2024-11-22 12:07:29.010499: +2024-11-22 12:07:29.010720: Epoch 4599 +2024-11-22 12:07:29.010837: Current learning rate: 0.00463 +2024-11-22 12:07:47.565526: train_loss -0.7872 +2024-11-22 12:07:47.565776: val_loss -0.7564 +2024-11-22 12:07:47.565851: Pseudo dice [0.84] +2024-11-22 12:07:47.565925: Epoch time: 18.56 s +2024-11-22 12:07:48.676551: +2024-11-22 12:07:48.676756: Epoch 4600 +2024-11-22 12:07:48.676867: Current learning rate: 0.00463 +2024-11-22 12:08:08.855289: train_loss -0.7867 +2024-11-22 12:08:08.855502: val_loss -0.778 +2024-11-22 12:08:08.855572: Pseudo dice [0.8545] +2024-11-22 12:08:08.855645: Epoch time: 20.18 s +2024-11-22 12:08:09.720141: +2024-11-22 12:08:09.720345: Epoch 4601 +2024-11-22 12:08:09.720458: Current learning rate: 0.00463 +2024-11-22 12:08:28.014618: train_loss -0.7981 +2024-11-22 12:08:28.014857: val_loss -0.7735 +2024-11-22 12:08:28.017126: Pseudo dice [0.8553] +2024-11-22 12:08:28.017219: Epoch time: 18.3 s +2024-11-22 12:08:28.871152: +2024-11-22 12:08:28.871351: Epoch 4602 +2024-11-22 12:08:28.871460: Current learning rate: 0.00463 +2024-11-22 12:08:47.309620: train_loss -0.79 +2024-11-22 12:08:47.309895: val_loss -0.7688 +2024-11-22 12:08:47.309976: Pseudo dice [0.8485] +2024-11-22 12:08:47.310050: Epoch time: 18.44 s +2024-11-22 12:08:48.148525: +2024-11-22 12:08:48.148714: Epoch 4603 +2024-11-22 12:08:48.148832: Current learning rate: 0.00463 +2024-11-22 12:09:06.940442: train_loss -0.788 +2024-11-22 12:09:06.940666: val_loss -0.8018 +2024-11-22 12:09:06.940744: Pseudo dice [0.8601] +2024-11-22 12:09:06.940818: Epoch time: 18.79 s +2024-11-22 12:09:07.794654: +2024-11-22 12:09:07.794852: Epoch 4604 +2024-11-22 12:09:07.794963: Current learning rate: 0.00462 +2024-11-22 12:09:25.172819: train_loss -0.7933 +2024-11-22 12:09:25.173032: val_loss -0.7672 +2024-11-22 12:09:25.173116: Pseudo dice [0.8559] +2024-11-22 12:09:25.173191: Epoch time: 17.38 s +2024-11-22 12:09:26.049355: +2024-11-22 12:09:26.049551: Epoch 4605 +2024-11-22 12:09:26.049658: Current learning rate: 0.00462 +2024-11-22 12:09:45.266197: train_loss -0.7947 +2024-11-22 12:09:45.266692: val_loss -0.7851 +2024-11-22 12:09:45.266789: Pseudo dice [0.8521] +2024-11-22 12:09:45.266874: Epoch time: 19.22 s +2024-11-22 12:09:46.140957: +2024-11-22 12:09:46.141190: Epoch 4606 +2024-11-22 12:09:46.141303: Current learning rate: 0.00462 +2024-11-22 12:10:04.499454: train_loss -0.7868 +2024-11-22 12:10:04.499658: val_loss -0.7885 +2024-11-22 12:10:04.499732: Pseudo dice [0.8589] +2024-11-22 12:10:04.499806: Epoch time: 18.36 s +2024-11-22 12:10:05.336996: +2024-11-22 12:10:05.337219: Epoch 4607 +2024-11-22 12:10:05.337329: Current learning rate: 0.00462 +2024-11-22 12:10:24.412433: train_loss -0.7886 +2024-11-22 12:10:24.412644: val_loss -0.7681 +2024-11-22 12:10:24.412721: Pseudo dice [0.8608] +2024-11-22 12:10:24.412796: Epoch time: 19.08 s +2024-11-22 12:10:25.257010: +2024-11-22 12:10:25.257213: Epoch 4608 +2024-11-22 12:10:25.257322: Current learning rate: 0.00462 +2024-11-22 12:10:43.165232: train_loss -0.7914 +2024-11-22 12:10:43.165453: val_loss -0.7268 +2024-11-22 12:10:43.165532: Pseudo dice [0.8538] +2024-11-22 12:10:43.165616: Epoch time: 17.91 s +2024-11-22 12:10:44.008997: +2024-11-22 12:10:44.009260: Epoch 4609 +2024-11-22 12:10:44.009369: Current learning rate: 0.00462 +2024-11-22 12:11:02.761519: train_loss -0.7979 +2024-11-22 12:11:02.761749: val_loss -0.7713 +2024-11-22 12:11:02.761825: Pseudo dice [0.8446] +2024-11-22 12:11:02.761900: Epoch time: 18.75 s +2024-11-22 12:11:03.605559: +2024-11-22 12:11:03.605774: Epoch 4610 +2024-11-22 12:11:03.605884: Current learning rate: 0.00462 +2024-11-22 12:11:22.105879: train_loss -0.7873 +2024-11-22 12:11:22.106101: val_loss -0.7654 +2024-11-22 12:11:22.106183: Pseudo dice [0.8512] +2024-11-22 12:11:22.106258: Epoch time: 18.5 s +2024-11-22 12:11:22.954113: +2024-11-22 12:11:22.954308: Epoch 4611 +2024-11-22 12:11:22.954414: Current learning rate: 0.00462 +2024-11-22 12:11:40.716444: train_loss -0.7978 +2024-11-22 12:11:40.716653: val_loss -0.7846 +2024-11-22 12:11:40.716729: Pseudo dice [0.8628] +2024-11-22 12:11:40.716804: Epoch time: 17.76 s +2024-11-22 12:11:41.689086: +2024-11-22 12:11:41.689277: Epoch 4612 +2024-11-22 12:11:41.689388: Current learning rate: 0.00461 +2024-11-22 12:12:00.087164: train_loss -0.7843 +2024-11-22 12:12:00.087413: val_loss -0.7634 +2024-11-22 12:12:00.087487: Pseudo dice [0.8637] +2024-11-22 12:12:00.087567: Epoch time: 18.4 s +2024-11-22 12:12:00.938344: +2024-11-22 12:12:00.938547: Epoch 4613 +2024-11-22 12:12:00.938661: Current learning rate: 0.00461 +2024-11-22 12:12:18.829743: train_loss -0.7872 +2024-11-22 12:12:18.829949: val_loss -0.7828 +2024-11-22 12:12:18.830021: Pseudo dice [0.8489] +2024-11-22 12:12:18.830099: Epoch time: 17.89 s +2024-11-22 12:12:19.767468: +2024-11-22 12:12:19.767646: Epoch 4614 +2024-11-22 12:12:19.767758: Current learning rate: 0.00461 +2024-11-22 12:12:38.273162: train_loss -0.7901 +2024-11-22 12:12:38.273374: val_loss -0.7501 +2024-11-22 12:12:38.273446: Pseudo dice [0.8527] +2024-11-22 12:12:38.273522: Epoch time: 18.51 s +2024-11-22 12:12:39.120773: +2024-11-22 12:12:39.120968: Epoch 4615 +2024-11-22 12:12:39.121079: Current learning rate: 0.00461 +2024-11-22 12:12:57.986899: train_loss -0.7919 +2024-11-22 12:12:57.987106: val_loss -0.764 +2024-11-22 12:12:57.987187: Pseudo dice [0.8552] +2024-11-22 12:12:57.987262: Epoch time: 18.87 s +2024-11-22 12:12:58.820075: +2024-11-22 12:12:58.820267: Epoch 4616 +2024-11-22 12:12:58.820373: Current learning rate: 0.00461 +2024-11-22 12:13:16.563673: train_loss -0.7884 +2024-11-22 12:13:16.563937: val_loss -0.7705 +2024-11-22 12:13:16.564021: Pseudo dice [0.8542] +2024-11-22 12:13:16.564110: Epoch time: 17.74 s +2024-11-22 12:13:17.846672: +2024-11-22 12:13:17.846895: Epoch 4617 +2024-11-22 12:13:17.847007: Current learning rate: 0.00461 +2024-11-22 12:13:36.876948: train_loss -0.7862 +2024-11-22 12:13:36.877177: val_loss -0.7311 +2024-11-22 12:13:36.877253: Pseudo dice [0.852] +2024-11-22 12:13:36.877328: Epoch time: 19.03 s +2024-11-22 12:13:37.715831: +2024-11-22 12:13:37.716038: Epoch 4618 +2024-11-22 12:13:37.716153: Current learning rate: 0.00461 +2024-11-22 12:13:56.843079: train_loss -0.7889 +2024-11-22 12:13:56.843315: val_loss -0.7546 +2024-11-22 12:13:56.843392: Pseudo dice [0.8495] +2024-11-22 12:13:56.843466: Epoch time: 19.13 s +2024-11-22 12:13:57.790935: +2024-11-22 12:13:57.791162: Epoch 4619 +2024-11-22 12:13:57.791272: Current learning rate: 0.00461 +2024-11-22 12:14:16.804076: train_loss -0.7925 +2024-11-22 12:14:16.804296: val_loss -0.7901 +2024-11-22 12:14:16.804375: Pseudo dice [0.8598] +2024-11-22 12:14:16.804485: Epoch time: 19.01 s +2024-11-22 12:14:17.657775: +2024-11-22 12:14:17.657991: Epoch 4620 +2024-11-22 12:14:17.658426: Current learning rate: 0.00461 +2024-11-22 12:14:36.411514: train_loss -0.7857 +2024-11-22 12:14:36.417092: val_loss -0.7869 +2024-11-22 12:14:36.417218: Pseudo dice [0.8634] +2024-11-22 12:14:36.417305: Epoch time: 18.75 s +2024-11-22 12:14:37.568480: +2024-11-22 12:14:37.568683: Epoch 4621 +2024-11-22 12:14:37.568816: Current learning rate: 0.0046 +2024-11-22 12:14:56.208230: train_loss -0.7846 +2024-11-22 12:14:56.228527: val_loss -0.75 +2024-11-22 12:14:56.228671: Pseudo dice [0.8568] +2024-11-22 12:14:56.228763: Epoch time: 18.64 s +2024-11-22 12:14:57.469080: +2024-11-22 12:14:57.469284: Epoch 4622 +2024-11-22 12:14:57.469400: Current learning rate: 0.0046 +2024-11-22 12:15:16.498509: train_loss -0.7752 +2024-11-22 12:15:16.502871: val_loss -0.7586 +2024-11-22 12:15:16.502976: Pseudo dice [0.8491] +2024-11-22 12:15:16.503054: Epoch time: 19.03 s +2024-11-22 12:15:17.489342: +2024-11-22 12:15:17.489555: Epoch 4623 +2024-11-22 12:15:17.489668: Current learning rate: 0.0046 +2024-11-22 12:15:36.252751: train_loss -0.784 +2024-11-22 12:15:36.252960: val_loss -0.7875 +2024-11-22 12:15:36.253039: Pseudo dice [0.8669] +2024-11-22 12:15:36.255312: Epoch time: 18.76 s +2024-11-22 12:15:37.240606: +2024-11-22 12:15:37.240823: Epoch 4624 +2024-11-22 12:15:37.240947: Current learning rate: 0.0046 +2024-11-22 12:15:56.540179: train_loss -0.7986 +2024-11-22 12:15:56.551069: val_loss -0.7776 +2024-11-22 12:15:56.551190: Pseudo dice [0.8533] +2024-11-22 12:15:56.551286: Epoch time: 19.3 s +2024-11-22 12:15:57.406695: +2024-11-22 12:15:57.406909: Epoch 4625 +2024-11-22 12:15:57.407021: Current learning rate: 0.0046 +2024-11-22 12:16:15.638748: train_loss -0.7987 +2024-11-22 12:16:15.644290: val_loss -0.8003 +2024-11-22 12:16:15.644396: Pseudo dice [0.8624] +2024-11-22 12:16:15.644606: Epoch time: 18.23 s +2024-11-22 12:16:16.496599: +2024-11-22 12:16:16.497181: Epoch 4626 +2024-11-22 12:16:16.497292: Current learning rate: 0.0046 +2024-11-22 12:16:35.721824: train_loss -0.7849 +2024-11-22 12:16:35.740703: val_loss -0.7745 +2024-11-22 12:16:35.740865: Pseudo dice [0.8569] +2024-11-22 12:16:35.740953: Epoch time: 19.23 s +2024-11-22 12:16:36.852665: +2024-11-22 12:16:36.852880: Epoch 4627 +2024-11-22 12:16:36.852999: Current learning rate: 0.0046 +2024-11-22 12:16:55.439433: train_loss -0.7916 +2024-11-22 12:16:55.453992: val_loss -0.7619 +2024-11-22 12:16:55.454108: Pseudo dice [0.8536] +2024-11-22 12:16:55.454199: Epoch time: 18.59 s +2024-11-22 12:16:56.423150: +2024-11-22 12:16:56.423364: Epoch 4628 +2024-11-22 12:16:56.423475: Current learning rate: 0.0046 +2024-11-22 12:17:15.998579: train_loss -0.786 +2024-11-22 12:17:16.003767: val_loss -0.7817 +2024-11-22 12:17:16.003886: Pseudo dice [0.8531] +2024-11-22 12:17:16.003981: Epoch time: 19.58 s +2024-11-22 12:17:16.856775: +2024-11-22 12:17:16.857418: Epoch 4629 +2024-11-22 12:17:16.857549: Current learning rate: 0.00459 +2024-11-22 12:17:34.685568: train_loss -0.7957 +2024-11-22 12:17:34.690854: val_loss -0.773 +2024-11-22 12:17:34.690994: Pseudo dice [0.861] +2024-11-22 12:17:34.691091: Epoch time: 17.83 s +2024-11-22 12:17:35.539222: +2024-11-22 12:17:35.539634: Epoch 4630 +2024-11-22 12:17:35.539754: Current learning rate: 0.00459 +2024-11-22 12:17:53.987720: train_loss -0.7961 +2024-11-22 12:17:53.996426: val_loss -0.7816 +2024-11-22 12:17:53.996561: Pseudo dice [0.8613] +2024-11-22 12:17:53.996642: Epoch time: 18.45 s +2024-11-22 12:17:54.854560: +2024-11-22 12:17:54.855116: Epoch 4631 +2024-11-22 12:17:54.855234: Current learning rate: 0.00459 +2024-11-22 12:18:15.048143: train_loss -0.7952 +2024-11-22 12:18:15.063095: val_loss -0.7889 +2024-11-22 12:18:15.063234: Pseudo dice [0.8612] +2024-11-22 12:18:15.063324: Epoch time: 20.19 s +2024-11-22 12:18:16.044244: +2024-11-22 12:18:16.044430: Epoch 4632 +2024-11-22 12:18:16.044540: Current learning rate: 0.00459 +2024-11-22 12:18:35.539981: train_loss -0.794 +2024-11-22 12:18:35.554269: val_loss -0.7616 +2024-11-22 12:18:35.554406: Pseudo dice [0.8613] +2024-11-22 12:18:35.554489: Epoch time: 19.5 s +2024-11-22 12:18:35.554555: Yayy! New best EMA pseudo Dice: 0.8577 +2024-11-22 12:18:36.692012: +2024-11-22 12:18:36.692456: Epoch 4633 +2024-11-22 12:18:36.692586: Current learning rate: 0.00459 +2024-11-22 12:18:54.977314: train_loss -0.8041 +2024-11-22 12:18:54.982768: val_loss -0.7583 +2024-11-22 12:18:54.982900: Pseudo dice [0.8437] +2024-11-22 12:18:54.982994: Epoch time: 18.29 s +2024-11-22 12:18:56.075900: +2024-11-22 12:18:56.076426: Epoch 4634 +2024-11-22 12:18:56.076543: Current learning rate: 0.00459 +2024-11-22 12:19:15.569026: train_loss -0.795 +2024-11-22 12:19:15.584029: val_loss -0.7768 +2024-11-22 12:19:15.584174: Pseudo dice [0.8607] +2024-11-22 12:19:15.584255: Epoch time: 19.49 s +2024-11-22 12:19:16.451212: +2024-11-22 12:19:16.452276: Epoch 4635 +2024-11-22 12:19:16.452393: Current learning rate: 0.00459 +2024-11-22 12:19:36.091824: train_loss -0.7938 +2024-11-22 12:19:36.107635: val_loss -0.7506 +2024-11-22 12:19:36.107780: Pseudo dice [0.842] +2024-11-22 12:19:36.107892: Epoch time: 19.64 s +2024-11-22 12:19:37.079352: +2024-11-22 12:19:37.079902: Epoch 4636 +2024-11-22 12:19:37.080034: Current learning rate: 0.00459 +2024-11-22 12:19:55.748919: train_loss -0.7881 +2024-11-22 12:19:55.758699: val_loss -0.7524 +2024-11-22 12:19:55.758814: Pseudo dice [0.8548] +2024-11-22 12:19:55.758895: Epoch time: 18.67 s +2024-11-22 12:19:56.786356: +2024-11-22 12:19:56.786906: Epoch 4637 +2024-11-22 12:19:56.787029: Current learning rate: 0.00458 +2024-11-22 12:20:15.707927: train_loss -0.793 +2024-11-22 12:20:15.730985: val_loss -0.7689 +2024-11-22 12:20:15.731123: Pseudo dice [0.8618] +2024-11-22 12:20:15.731258: Epoch time: 18.92 s +2024-11-22 12:20:16.814957: +2024-11-22 12:20:16.816471: Epoch 4638 +2024-11-22 12:20:16.816593: Current learning rate: 0.00458 +2024-11-22 12:20:36.836210: train_loss -0.7974 +2024-11-22 12:20:36.842689: val_loss -0.7377 +2024-11-22 12:20:36.842835: Pseudo dice [0.8329] +2024-11-22 12:20:36.842933: Epoch time: 20.02 s +2024-11-22 12:20:37.893468: +2024-11-22 12:20:37.894873: Epoch 4639 +2024-11-22 12:20:37.894990: Current learning rate: 0.00458 +2024-11-22 12:20:58.582710: train_loss -0.7896 +2024-11-22 12:20:58.596151: val_loss -0.7729 +2024-11-22 12:20:58.596281: Pseudo dice [0.8619] +2024-11-22 12:20:58.596380: Epoch time: 20.69 s +2024-11-22 12:20:59.943790: +2024-11-22 12:20:59.946013: Epoch 4640 +2024-11-22 12:20:59.946145: Current learning rate: 0.00458 +2024-11-22 12:21:20.376644: train_loss -0.7873 +2024-11-22 12:21:20.382243: val_loss -0.7932 +2024-11-22 12:21:20.382388: Pseudo dice [0.8513] +2024-11-22 12:21:20.382473: Epoch time: 20.43 s +2024-11-22 12:21:21.263282: +2024-11-22 12:21:21.263511: Epoch 4641 +2024-11-22 12:21:21.263628: Current learning rate: 0.00458 +2024-11-22 12:21:41.051554: train_loss -0.7831 +2024-11-22 12:21:41.054649: val_loss -0.7759 +2024-11-22 12:21:41.054761: Pseudo dice [0.8585] +2024-11-22 12:21:41.054863: Epoch time: 19.79 s +2024-11-22 12:21:41.896076: +2024-11-22 12:21:41.896285: Epoch 4642 +2024-11-22 12:21:41.896392: Current learning rate: 0.00458 +2024-11-22 12:22:01.399005: train_loss -0.7877 +2024-11-22 12:22:01.408671: val_loss -0.7375 +2024-11-22 12:22:01.408806: Pseudo dice [0.8572] +2024-11-22 12:22:01.408909: Epoch time: 19.5 s +2024-11-22 12:22:02.494362: +2024-11-22 12:22:02.494565: Epoch 4643 +2024-11-22 12:22:02.494675: Current learning rate: 0.00458 +2024-11-22 12:22:21.628800: train_loss -0.7849 +2024-11-22 12:22:21.643680: val_loss -0.7442 +2024-11-22 12:22:21.643806: Pseudo dice [0.8582] +2024-11-22 12:22:21.643888: Epoch time: 19.14 s +2024-11-22 12:22:22.677259: +2024-11-22 12:22:22.677461: Epoch 4644 +2024-11-22 12:22:22.677584: Current learning rate: 0.00458 +2024-11-22 12:22:42.973806: train_loss -0.7937 +2024-11-22 12:22:42.983448: val_loss -0.7751 +2024-11-22 12:22:42.983573: Pseudo dice [0.8615] +2024-11-22 12:22:42.983667: Epoch time: 20.3 s +2024-11-22 12:22:44.071987: +2024-11-22 12:22:44.072209: Epoch 4645 +2024-11-22 12:22:44.072326: Current learning rate: 0.00457 +2024-11-22 12:23:04.284079: train_loss -0.798 +2024-11-22 12:23:04.294397: val_loss -0.7698 +2024-11-22 12:23:04.294555: Pseudo dice [0.8505] +2024-11-22 12:23:04.294657: Epoch time: 20.21 s +2024-11-22 12:23:05.138731: +2024-11-22 12:23:05.139764: Epoch 4646 +2024-11-22 12:23:05.139900: Current learning rate: 0.00457 +2024-11-22 12:23:23.085056: train_loss -0.7928 +2024-11-22 12:23:23.112303: val_loss -0.7574 +2024-11-22 12:23:23.112445: Pseudo dice [0.8505] +2024-11-22 12:23:23.112534: Epoch time: 17.95 s +2024-11-22 12:23:24.081429: +2024-11-22 12:23:24.082081: Epoch 4647 +2024-11-22 12:23:24.082201: Current learning rate: 0.00457 +2024-11-22 12:23:43.475407: train_loss -0.8036 +2024-11-22 12:23:43.502412: val_loss -0.7686 +2024-11-22 12:23:43.502541: Pseudo dice [0.8533] +2024-11-22 12:23:43.502626: Epoch time: 19.39 s +2024-11-22 12:23:44.521997: +2024-11-22 12:23:44.522216: Epoch 4648 +2024-11-22 12:23:44.522344: Current learning rate: 0.00457 +2024-11-22 12:24:03.424428: train_loss -0.794 +2024-11-22 12:24:03.440169: val_loss -0.7869 +2024-11-22 12:24:03.440297: Pseudo dice [0.8479] +2024-11-22 12:24:03.440389: Epoch time: 18.9 s +2024-11-22 12:24:04.310459: +2024-11-22 12:24:04.310663: Epoch 4649 +2024-11-22 12:24:04.310786: Current learning rate: 0.00457 +2024-11-22 12:24:23.115119: train_loss -0.8052 +2024-11-22 12:24:23.131876: val_loss -0.7565 +2024-11-22 12:24:23.132000: Pseudo dice [0.8475] +2024-11-22 12:24:23.132091: Epoch time: 18.81 s +2024-11-22 12:24:24.367326: +2024-11-22 12:24:24.367843: Epoch 4650 +2024-11-22 12:24:24.367958: Current learning rate: 0.00457 +2024-11-22 12:24:43.841794: train_loss -0.7942 +2024-11-22 12:24:43.855375: val_loss -0.7524 +2024-11-22 12:24:43.855528: Pseudo dice [0.8461] +2024-11-22 12:24:43.855629: Epoch time: 19.48 s +2024-11-22 12:24:44.755771: +2024-11-22 12:24:44.755990: Epoch 4651 +2024-11-22 12:24:44.756113: Current learning rate: 0.00457 +2024-11-22 12:25:05.597047: train_loss -0.8036 +2024-11-22 12:25:05.611642: val_loss -0.7764 +2024-11-22 12:25:05.611765: Pseudo dice [0.8564] +2024-11-22 12:25:05.611847: Epoch time: 20.84 s +2024-11-22 12:25:06.615695: +2024-11-22 12:25:06.616131: Epoch 4652 +2024-11-22 12:25:06.616275: Current learning rate: 0.00457 +2024-11-22 12:25:25.482915: train_loss -0.7966 +2024-11-22 12:25:25.488072: val_loss -0.7707 +2024-11-22 12:25:25.488229: Pseudo dice [0.8556] +2024-11-22 12:25:25.488326: Epoch time: 18.87 s +2024-11-22 12:25:26.345963: +2024-11-22 12:25:26.346658: Epoch 4653 +2024-11-22 12:25:26.346795: Current learning rate: 0.00456 +2024-11-22 12:25:46.879312: train_loss -0.8009 +2024-11-22 12:25:46.884783: val_loss -0.7891 +2024-11-22 12:25:46.884914: Pseudo dice [0.8626] +2024-11-22 12:25:46.885007: Epoch time: 20.53 s +2024-11-22 12:25:47.780203: +2024-11-22 12:25:47.780637: Epoch 4654 +2024-11-22 12:25:47.780771: Current learning rate: 0.00456 +2024-11-22 12:26:06.651085: train_loss -0.8007 +2024-11-22 12:26:06.660390: val_loss -0.7803 +2024-11-22 12:26:06.660525: Pseudo dice [0.8633] +2024-11-22 12:26:06.660632: Epoch time: 18.87 s +2024-11-22 12:26:07.620422: +2024-11-22 12:26:07.620850: Epoch 4655 +2024-11-22 12:26:07.620989: Current learning rate: 0.00456 +2024-11-22 12:26:26.159729: train_loss -0.7954 +2024-11-22 12:26:26.163893: val_loss -0.7856 +2024-11-22 12:26:26.164172: Pseudo dice [0.8524] +2024-11-22 12:26:26.164256: Epoch time: 18.54 s +2024-11-22 12:26:27.015460: +2024-11-22 12:26:27.017000: Epoch 4656 +2024-11-22 12:26:27.017158: Current learning rate: 0.00456 +2024-11-22 12:26:46.154790: train_loss -0.7946 +2024-11-22 12:26:46.168261: val_loss -0.7747 +2024-11-22 12:26:46.168399: Pseudo dice [0.8502] +2024-11-22 12:26:46.168478: Epoch time: 19.14 s +2024-11-22 12:26:47.272717: +2024-11-22 12:26:47.273342: Epoch 4657 +2024-11-22 12:26:47.273479: Current learning rate: 0.00456 +2024-11-22 12:27:06.235789: train_loss -0.7961 +2024-11-22 12:27:06.240112: val_loss -0.7422 +2024-11-22 12:27:06.240232: Pseudo dice [0.8568] +2024-11-22 12:27:06.240343: Epoch time: 18.96 s +2024-11-22 12:27:07.083591: +2024-11-22 12:27:07.084232: Epoch 4658 +2024-11-22 12:27:07.084365: Current learning rate: 0.00456 +2024-11-22 12:27:26.088944: train_loss -0.7991 +2024-11-22 12:27:26.101012: val_loss -0.748 +2024-11-22 12:27:26.101177: Pseudo dice [0.8592] +2024-11-22 12:27:26.101275: Epoch time: 19.01 s +2024-11-22 12:27:27.122131: +2024-11-22 12:27:27.122560: Epoch 4659 +2024-11-22 12:27:27.122690: Current learning rate: 0.00456 +2024-11-22 12:27:46.964391: train_loss -0.8029 +2024-11-22 12:27:46.977955: val_loss -0.7757 +2024-11-22 12:27:46.978112: Pseudo dice [0.8512] +2024-11-22 12:27:46.978198: Epoch time: 19.84 s +2024-11-22 12:27:48.031163: +2024-11-22 12:27:48.031858: Epoch 4660 +2024-11-22 12:27:48.032001: Current learning rate: 0.00456 +2024-11-22 12:28:07.547083: train_loss -0.8027 +2024-11-22 12:28:07.551420: val_loss -0.7743 +2024-11-22 12:28:07.551526: Pseudo dice [0.8437] +2024-11-22 12:28:07.551611: Epoch time: 19.52 s +2024-11-22 12:28:08.399495: +2024-11-22 12:28:08.401547: Epoch 4661 +2024-11-22 12:28:08.401706: Current learning rate: 0.00455 +2024-11-22 12:28:27.668818: train_loss -0.7994 +2024-11-22 12:28:27.677378: val_loss -0.7618 +2024-11-22 12:28:27.677483: Pseudo dice [0.8511] +2024-11-22 12:28:27.677568: Epoch time: 19.27 s +2024-11-22 12:28:28.528018: +2024-11-22 12:28:28.528389: Epoch 4662 +2024-11-22 12:28:28.528526: Current learning rate: 0.00455 +2024-11-22 12:28:48.498444: train_loss -0.8007 +2024-11-22 12:28:48.501649: val_loss -0.7824 +2024-11-22 12:28:48.501784: Pseudo dice [0.8621] +2024-11-22 12:28:48.501884: Epoch time: 19.97 s +2024-11-22 12:28:49.674016: +2024-11-22 12:28:49.674729: Epoch 4663 +2024-11-22 12:28:49.674875: Current learning rate: 0.00455 +2024-11-22 12:29:08.088454: train_loss -0.7941 +2024-11-22 12:29:08.094222: val_loss -0.7681 +2024-11-22 12:29:08.094355: Pseudo dice [0.8493] +2024-11-22 12:29:08.094437: Epoch time: 18.42 s +2024-11-22 12:29:08.922619: +2024-11-22 12:29:08.923253: Epoch 4664 +2024-11-22 12:29:08.923401: Current learning rate: 0.00455 +2024-11-22 12:29:28.287317: train_loss -0.7914 +2024-11-22 12:29:28.290536: val_loss -0.7645 +2024-11-22 12:29:28.290702: Pseudo dice [0.854] +2024-11-22 12:29:28.290793: Epoch time: 19.37 s +2024-11-22 12:29:29.157833: +2024-11-22 12:29:29.158905: Epoch 4665 +2024-11-22 12:29:29.159051: Current learning rate: 0.00455 +2024-11-22 12:29:49.298529: train_loss -0.7963 +2024-11-22 12:29:49.304111: val_loss -0.7555 +2024-11-22 12:29:49.304240: Pseudo dice [0.8526] +2024-11-22 12:29:49.304323: Epoch time: 20.14 s +2024-11-22 12:29:50.194554: +2024-11-22 12:29:50.194947: Epoch 4666 +2024-11-22 12:29:50.195089: Current learning rate: 0.00455 +2024-11-22 12:30:09.699866: train_loss -0.7994 +2024-11-22 12:30:09.712270: val_loss -0.7671 +2024-11-22 12:30:09.718210: Pseudo dice [0.8614] +2024-11-22 12:30:09.718358: Epoch time: 19.51 s +2024-11-22 12:30:10.734542: +2024-11-22 12:30:10.735211: Epoch 4667 +2024-11-22 12:30:10.735368: Current learning rate: 0.00455 +2024-11-22 12:30:30.527534: train_loss -0.7805 +2024-11-22 12:30:30.533322: val_loss -0.778 +2024-11-22 12:30:30.533521: Pseudo dice [0.8561] +2024-11-22 12:30:30.533615: Epoch time: 19.79 s +2024-11-22 12:30:31.516280: +2024-11-22 12:30:31.517014: Epoch 4668 +2024-11-22 12:30:31.517161: Current learning rate: 0.00455 +2024-11-22 12:30:51.549375: train_loss -0.7916 +2024-11-22 12:30:51.559264: val_loss -0.7771 +2024-11-22 12:30:51.559389: Pseudo dice [0.8551] +2024-11-22 12:30:51.559480: Epoch time: 20.03 s +2024-11-22 12:30:52.566185: +2024-11-22 12:30:52.566905: Epoch 4669 +2024-11-22 12:30:52.567042: Current learning rate: 0.00455 +2024-11-22 12:31:13.470956: train_loss -0.7813 +2024-11-22 12:31:13.495214: val_loss -0.7937 +2024-11-22 12:31:13.495377: Pseudo dice [0.8489] +2024-11-22 12:31:13.495472: Epoch time: 20.91 s +2024-11-22 12:31:14.445319: +2024-11-22 12:31:14.446304: Epoch 4670 +2024-11-22 12:31:14.446437: Current learning rate: 0.00454 +2024-11-22 12:31:33.588844: train_loss -0.796 +2024-11-22 12:31:33.596872: val_loss -0.7689 +2024-11-22 12:31:33.597019: Pseudo dice [0.8578] +2024-11-22 12:31:33.597118: Epoch time: 19.14 s +2024-11-22 12:31:34.453253: +2024-11-22 12:31:34.453681: Epoch 4671 +2024-11-22 12:31:34.453833: Current learning rate: 0.00454 +2024-11-22 12:31:54.539936: train_loss -0.7929 +2024-11-22 12:31:54.566686: val_loss -0.7705 +2024-11-22 12:31:54.566846: Pseudo dice [0.8593] +2024-11-22 12:31:54.566929: Epoch time: 20.09 s +2024-11-22 12:31:55.563093: +2024-11-22 12:31:55.563557: Epoch 4672 +2024-11-22 12:31:55.563693: Current learning rate: 0.00454 +2024-11-22 12:32:15.203154: train_loss -0.7822 +2024-11-22 12:32:15.209280: val_loss -0.7797 +2024-11-22 12:32:15.209397: Pseudo dice [0.8579] +2024-11-22 12:32:15.209493: Epoch time: 19.64 s +2024-11-22 12:32:16.066114: +2024-11-22 12:32:16.067193: Epoch 4673 +2024-11-22 12:32:16.067339: Current learning rate: 0.00454 +2024-11-22 12:32:35.157189: train_loss -0.7945 +2024-11-22 12:32:35.161816: val_loss -0.7656 +2024-11-22 12:32:35.161943: Pseudo dice [0.8507] +2024-11-22 12:32:35.162035: Epoch time: 19.09 s +2024-11-22 12:32:36.019799: +2024-11-22 12:32:36.019996: Epoch 4674 +2024-11-22 12:32:36.020118: Current learning rate: 0.00454 +2024-11-22 12:32:55.286442: train_loss -0.795 +2024-11-22 12:32:55.293241: val_loss -0.7786 +2024-11-22 12:32:55.293377: Pseudo dice [0.8532] +2024-11-22 12:32:55.293468: Epoch time: 19.27 s +2024-11-22 12:32:56.202993: +2024-11-22 12:32:56.203220: Epoch 4675 +2024-11-22 12:32:56.203334: Current learning rate: 0.00454 +2024-11-22 12:33:14.585252: train_loss -0.8015 +2024-11-22 12:33:14.591833: val_loss -0.7654 +2024-11-22 12:33:14.591965: Pseudo dice [0.866] +2024-11-22 12:33:14.592064: Epoch time: 18.38 s +2024-11-22 12:33:15.512182: +2024-11-22 12:33:15.512425: Epoch 4676 +2024-11-22 12:33:15.512536: Current learning rate: 0.00454 +2024-11-22 12:33:35.111566: train_loss -0.7923 +2024-11-22 12:33:35.120235: val_loss -0.7862 +2024-11-22 12:33:35.120368: Pseudo dice [0.8557] +2024-11-22 12:33:35.120449: Epoch time: 19.6 s +2024-11-22 12:33:36.000843: +2024-11-22 12:33:36.001572: Epoch 4677 +2024-11-22 12:33:36.001708: Current learning rate: 0.00454 +2024-11-22 12:33:53.970644: train_loss -0.7886 +2024-11-22 12:33:53.980520: val_loss -0.7464 +2024-11-22 12:33:53.980653: Pseudo dice [0.8554] +2024-11-22 12:33:53.980753: Epoch time: 17.97 s +2024-11-22 12:33:54.856250: +2024-11-22 12:33:54.856658: Epoch 4678 +2024-11-22 12:33:54.856794: Current learning rate: 0.00453 +2024-11-22 12:34:13.834180: train_loss -0.8027 +2024-11-22 12:34:13.838270: val_loss -0.7593 +2024-11-22 12:34:13.838420: Pseudo dice [0.8389] +2024-11-22 12:34:13.838524: Epoch time: 18.98 s +2024-11-22 12:34:14.693509: +2024-11-22 12:34:14.693949: Epoch 4679 +2024-11-22 12:34:14.694093: Current learning rate: 0.00453 +2024-11-22 12:34:34.153131: train_loss -0.7913 +2024-11-22 12:34:34.159200: val_loss -0.7718 +2024-11-22 12:34:34.159326: Pseudo dice [0.8678] +2024-11-22 12:34:34.159412: Epoch time: 19.46 s +2024-11-22 12:34:35.309250: +2024-11-22 12:34:35.309828: Epoch 4680 +2024-11-22 12:34:35.309973: Current learning rate: 0.00453 +2024-11-22 12:34:54.923464: train_loss -0.7894 +2024-11-22 12:34:54.931099: val_loss -0.7726 +2024-11-22 12:34:54.931293: Pseudo dice [0.858] +2024-11-22 12:34:54.931389: Epoch time: 19.62 s +2024-11-22 12:34:55.937646: +2024-11-22 12:34:55.938398: Epoch 4681 +2024-11-22 12:34:55.938530: Current learning rate: 0.00453 +2024-11-22 12:35:14.328867: train_loss -0.7875 +2024-11-22 12:35:14.332919: val_loss -0.7812 +2024-11-22 12:35:14.333048: Pseudo dice [0.8589] +2024-11-22 12:35:14.333148: Epoch time: 18.39 s +2024-11-22 12:35:15.261252: +2024-11-22 12:35:15.261660: Epoch 4682 +2024-11-22 12:35:15.261809: Current learning rate: 0.00453 +2024-11-22 12:35:33.829931: train_loss -0.7981 +2024-11-22 12:35:33.835778: val_loss -0.7668 +2024-11-22 12:35:33.835974: Pseudo dice [0.849] +2024-11-22 12:35:33.836064: Epoch time: 18.57 s +2024-11-22 12:35:34.820333: +2024-11-22 12:35:34.820748: Epoch 4683 +2024-11-22 12:35:34.820881: Current learning rate: 0.00453 +2024-11-22 12:35:52.433128: train_loss -0.7962 +2024-11-22 12:35:52.439999: val_loss -0.7692 +2024-11-22 12:35:52.440155: Pseudo dice [0.8467] +2024-11-22 12:35:52.440234: Epoch time: 17.61 s +2024-11-22 12:35:53.352668: +2024-11-22 12:35:53.353144: Epoch 4684 +2024-11-22 12:35:53.353289: Current learning rate: 0.00453 +2024-11-22 12:36:13.244479: train_loss -0.7882 +2024-11-22 12:36:13.275262: val_loss -0.7408 +2024-11-22 12:36:13.275404: Pseudo dice [0.8416] +2024-11-22 12:36:13.275499: Epoch time: 19.89 s +2024-11-22 12:36:14.367488: +2024-11-22 12:36:14.367896: Epoch 4685 +2024-11-22 12:36:14.368033: Current learning rate: 0.00453 +2024-11-22 12:36:32.875219: train_loss -0.8023 +2024-11-22 12:36:32.881684: val_loss -0.768 +2024-11-22 12:36:32.881820: Pseudo dice [0.861] +2024-11-22 12:36:32.881915: Epoch time: 18.51 s +2024-11-22 12:36:34.292924: +2024-11-22 12:36:34.293336: Epoch 4686 +2024-11-22 12:36:34.293460: Current learning rate: 0.00452 +2024-11-22 12:36:52.352012: train_loss -0.7885 +2024-11-22 12:36:52.358444: val_loss -0.7598 +2024-11-22 12:36:52.358573: Pseudo dice [0.8411] +2024-11-22 12:36:52.358653: Epoch time: 18.06 s +2024-11-22 12:36:53.223530: +2024-11-22 12:36:53.224195: Epoch 4687 +2024-11-22 12:36:53.224326: Current learning rate: 0.00452 +2024-11-22 12:37:13.267228: train_loss -0.7913 +2024-11-22 12:37:13.276628: val_loss -0.769 +2024-11-22 12:37:13.276763: Pseudo dice [0.8577] +2024-11-22 12:37:13.276855: Epoch time: 20.04 s +2024-11-22 12:37:14.315857: +2024-11-22 12:37:14.316315: Epoch 4688 +2024-11-22 12:37:14.316466: Current learning rate: 0.00452 +2024-11-22 12:37:32.910979: train_loss -0.7945 +2024-11-22 12:37:32.918605: val_loss -0.7482 +2024-11-22 12:37:32.918731: Pseudo dice [0.8314] +2024-11-22 12:37:32.918813: Epoch time: 18.6 s +2024-11-22 12:37:33.804798: +2024-11-22 12:37:33.805226: Epoch 4689 +2024-11-22 12:37:33.805357: Current learning rate: 0.00452 +2024-11-22 12:37:53.454190: train_loss -0.7851 +2024-11-22 12:37:53.460885: val_loss -0.7718 +2024-11-22 12:37:53.461033: Pseudo dice [0.8462] +2024-11-22 12:37:53.461119: Epoch time: 19.65 s +2024-11-22 12:37:54.340516: +2024-11-22 12:37:54.340915: Epoch 4690 +2024-11-22 12:37:54.341057: Current learning rate: 0.00452 +2024-11-22 12:38:12.485544: train_loss -0.7782 +2024-11-22 12:38:12.495366: val_loss -0.7588 +2024-11-22 12:38:12.495503: Pseudo dice [0.8518] +2024-11-22 12:38:12.495599: Epoch time: 18.15 s +2024-11-22 12:38:13.449982: +2024-11-22 12:38:13.450392: Epoch 4691 +2024-11-22 12:38:13.450531: Current learning rate: 0.00452 +2024-11-22 12:38:34.011953: train_loss -0.7901 +2024-11-22 12:38:34.022726: val_loss -0.7756 +2024-11-22 12:38:34.022857: Pseudo dice [0.8561] +2024-11-22 12:38:34.022941: Epoch time: 20.56 s +2024-11-22 12:38:35.065772: +2024-11-22 12:38:35.066179: Epoch 4692 +2024-11-22 12:38:35.066306: Current learning rate: 0.00452 +2024-11-22 12:38:53.678057: train_loss -0.7954 +2024-11-22 12:38:53.729270: val_loss -0.7567 +2024-11-22 12:38:53.729421: Pseudo dice [0.8453] +2024-11-22 12:38:53.729519: Epoch time: 18.61 s +2024-11-22 12:38:54.572014: +2024-11-22 12:38:54.572419: Epoch 4693 +2024-11-22 12:38:54.572559: Current learning rate: 0.00452 +2024-11-22 12:39:12.878569: train_loss -0.796 +2024-11-22 12:39:12.895268: val_loss -0.7696 +2024-11-22 12:39:12.895652: Pseudo dice [0.8567] +2024-11-22 12:39:12.895785: Epoch time: 18.31 s +2024-11-22 12:39:13.852512: +2024-11-22 12:39:13.852925: Epoch 4694 +2024-11-22 12:39:13.853074: Current learning rate: 0.00451 +2024-11-22 12:39:33.592004: train_loss -0.7835 +2024-11-22 12:39:33.601657: val_loss -0.7611 +2024-11-22 12:39:33.601776: Pseudo dice [0.8561] +2024-11-22 12:39:33.601870: Epoch time: 19.74 s +2024-11-22 12:39:34.524793: +2024-11-22 12:39:34.525202: Epoch 4695 +2024-11-22 12:39:34.525336: Current learning rate: 0.00451 +2024-11-22 12:39:54.128123: train_loss -0.7913 +2024-11-22 12:39:54.137426: val_loss -0.7669 +2024-11-22 12:39:54.137556: Pseudo dice [0.8605] +2024-11-22 12:39:54.137644: Epoch time: 19.6 s +2024-11-22 12:39:55.032096: +2024-11-22 12:39:55.032489: Epoch 4696 +2024-11-22 12:39:55.032625: Current learning rate: 0.00451 +2024-11-22 12:40:14.390456: train_loss -0.7868 +2024-11-22 12:40:14.400240: val_loss -0.7389 +2024-11-22 12:40:14.400355: Pseudo dice [0.8597] +2024-11-22 12:40:14.400443: Epoch time: 19.36 s +2024-11-22 12:40:15.259617: +2024-11-22 12:40:15.259804: Epoch 4697 +2024-11-22 12:40:15.259922: Current learning rate: 0.00451 +2024-11-22 12:40:34.869017: train_loss -0.7927 +2024-11-22 12:40:34.879751: val_loss -0.7577 +2024-11-22 12:40:34.879880: Pseudo dice [0.8496] +2024-11-22 12:40:34.880048: Epoch time: 19.61 s +2024-11-22 12:40:35.748788: +2024-11-22 12:40:35.748989: Epoch 4698 +2024-11-22 12:40:35.749134: Current learning rate: 0.00451 +2024-11-22 12:40:54.475782: train_loss -0.7901 +2024-11-22 12:40:54.480259: val_loss -0.7643 +2024-11-22 12:40:54.480387: Pseudo dice [0.8651] +2024-11-22 12:40:54.480485: Epoch time: 18.73 s +2024-11-22 12:40:55.339945: +2024-11-22 12:40:55.340151: Epoch 4699 +2024-11-22 12:40:55.340263: Current learning rate: 0.00451 +2024-11-22 12:41:13.792178: train_loss -0.7975 +2024-11-22 12:41:13.803168: val_loss -0.7613 +2024-11-22 12:41:13.803303: Pseudo dice [0.8406] +2024-11-22 12:41:13.803393: Epoch time: 18.45 s +2024-11-22 12:41:15.000139: +2024-11-22 12:41:15.000861: Epoch 4700 +2024-11-22 12:41:15.000975: Current learning rate: 0.00451 +2024-11-22 12:41:33.311359: train_loss -0.7914 +2024-11-22 12:41:33.322929: val_loss -0.7732 +2024-11-22 12:41:33.323051: Pseudo dice [0.8585] +2024-11-22 12:41:33.323158: Epoch time: 18.31 s +2024-11-22 12:41:34.214002: +2024-11-22 12:41:34.214247: Epoch 4701 +2024-11-22 12:41:34.214368: Current learning rate: 0.00451 +2024-11-22 12:41:53.207824: train_loss -0.7814 +2024-11-22 12:41:53.210665: val_loss -0.7646 +2024-11-22 12:41:53.210763: Pseudo dice [0.8509] +2024-11-22 12:41:53.210859: Epoch time: 18.99 s +2024-11-22 12:41:54.064765: +2024-11-22 12:41:54.065303: Epoch 4702 +2024-11-22 12:41:54.065420: Current learning rate: 0.0045 +2024-11-22 12:42:13.197773: train_loss -0.7872 +2024-11-22 12:42:13.201460: val_loss -0.7656 +2024-11-22 12:42:13.201591: Pseudo dice [0.8566] +2024-11-22 12:42:13.201685: Epoch time: 19.13 s +2024-11-22 12:42:14.130595: +2024-11-22 12:42:14.131205: Epoch 4703 +2024-11-22 12:42:14.131345: Current learning rate: 0.0045 +2024-11-22 12:42:33.745907: train_loss -0.7889 +2024-11-22 12:42:33.757384: val_loss -0.7615 +2024-11-22 12:42:33.757534: Pseudo dice [0.8402] +2024-11-22 12:42:33.757637: Epoch time: 19.62 s +2024-11-22 12:42:34.817252: +2024-11-22 12:42:34.817870: Epoch 4704 +2024-11-22 12:42:34.817987: Current learning rate: 0.0045 +2024-11-22 12:42:54.659101: train_loss -0.7885 +2024-11-22 12:42:54.665815: val_loss -0.774 +2024-11-22 12:42:54.665933: Pseudo dice [0.864] +2024-11-22 12:42:54.666027: Epoch time: 19.84 s +2024-11-22 12:42:55.551938: +2024-11-22 12:42:55.552141: Epoch 4705 +2024-11-22 12:42:55.552253: Current learning rate: 0.0045 +2024-11-22 12:43:15.940663: train_loss -0.7951 +2024-11-22 12:43:15.949111: val_loss -0.7729 +2024-11-22 12:43:15.949247: Pseudo dice [0.8504] +2024-11-22 12:43:15.949340: Epoch time: 20.39 s +2024-11-22 12:43:16.886698: +2024-11-22 12:43:16.886919: Epoch 4706 +2024-11-22 12:43:16.887042: Current learning rate: 0.0045 +2024-11-22 12:43:35.158743: train_loss -0.7927 +2024-11-22 12:43:35.169460: val_loss -0.7808 +2024-11-22 12:43:35.169605: Pseudo dice [0.8551] +2024-11-22 12:43:35.169694: Epoch time: 18.27 s +2024-11-22 12:43:36.032555: +2024-11-22 12:43:36.032768: Epoch 4707 +2024-11-22 12:43:36.032900: Current learning rate: 0.0045 +2024-11-22 12:43:55.634371: train_loss -0.7973 +2024-11-22 12:43:55.639215: val_loss -0.786 +2024-11-22 12:43:55.639330: Pseudo dice [0.8594] +2024-11-22 12:43:55.639428: Epoch time: 19.6 s +2024-11-22 12:43:56.548766: +2024-11-22 12:43:56.550260: Epoch 4708 +2024-11-22 12:43:56.550377: Current learning rate: 0.0045 +2024-11-22 12:44:15.156551: train_loss -0.7956 +2024-11-22 12:44:15.164852: val_loss -0.7528 +2024-11-22 12:44:15.164989: Pseudo dice [0.8513] +2024-11-22 12:44:15.165091: Epoch time: 18.61 s +2024-11-22 12:44:16.581679: +2024-11-22 12:44:16.583606: Epoch 4709 +2024-11-22 12:44:16.583734: Current learning rate: 0.0045 +2024-11-22 12:44:35.257492: train_loss -0.7943 +2024-11-22 12:44:35.262111: val_loss -0.7674 +2024-11-22 12:44:35.262239: Pseudo dice [0.8515] +2024-11-22 12:44:35.262335: Epoch time: 18.68 s +2024-11-22 12:44:36.116177: +2024-11-22 12:44:36.116390: Epoch 4710 +2024-11-22 12:44:36.116504: Current learning rate: 0.00449 +2024-11-22 12:44:56.277838: train_loss -0.7971 +2024-11-22 12:44:56.286929: val_loss -0.7869 +2024-11-22 12:44:56.287045: Pseudo dice [0.8623] +2024-11-22 12:44:56.287151: Epoch time: 20.16 s +2024-11-22 12:44:57.273077: +2024-11-22 12:44:57.273903: Epoch 4711 +2024-11-22 12:44:57.274019: Current learning rate: 0.00449 +2024-11-22 12:45:16.339323: train_loss -0.8019 +2024-11-22 12:45:16.345948: val_loss -0.7699 +2024-11-22 12:45:16.346084: Pseudo dice [0.8477] +2024-11-22 12:45:16.346173: Epoch time: 19.07 s +2024-11-22 12:45:17.221866: +2024-11-22 12:45:17.222087: Epoch 4712 +2024-11-22 12:45:17.222203: Current learning rate: 0.00449 +2024-11-22 12:45:37.859462: train_loss -0.7897 +2024-11-22 12:45:37.875759: val_loss -0.751 +2024-11-22 12:45:37.875912: Pseudo dice [0.8472] +2024-11-22 12:45:37.876013: Epoch time: 20.64 s +2024-11-22 12:45:38.814201: +2024-11-22 12:45:38.815038: Epoch 4713 +2024-11-22 12:45:38.815166: Current learning rate: 0.00449 +2024-11-22 12:45:59.133627: train_loss -0.7874 +2024-11-22 12:45:59.148108: val_loss -0.7815 +2024-11-22 12:45:59.148248: Pseudo dice [0.8449] +2024-11-22 12:45:59.148342: Epoch time: 20.32 s +2024-11-22 12:46:00.091459: +2024-11-22 12:46:00.092087: Epoch 4714 +2024-11-22 12:46:00.092203: Current learning rate: 0.00449 +2024-11-22 12:46:19.423277: train_loss -0.7916 +2024-11-22 12:46:19.431794: val_loss -0.788 +2024-11-22 12:46:19.431955: Pseudo dice [0.8617] +2024-11-22 12:46:19.432044: Epoch time: 19.33 s +2024-11-22 12:46:20.463794: +2024-11-22 12:46:20.464320: Epoch 4715 +2024-11-22 12:46:20.464448: Current learning rate: 0.00449 +2024-11-22 12:46:40.548426: train_loss -0.7895 +2024-11-22 12:46:40.555274: val_loss -0.7638 +2024-11-22 12:46:40.555429: Pseudo dice [0.8568] +2024-11-22 12:46:40.555516: Epoch time: 20.09 s +2024-11-22 12:46:41.430345: +2024-11-22 12:46:41.430899: Epoch 4716 +2024-11-22 12:46:41.431018: Current learning rate: 0.00449 +2024-11-22 12:46:59.946947: train_loss -0.7937 +2024-11-22 12:46:59.952487: val_loss -0.7755 +2024-11-22 12:46:59.952606: Pseudo dice [0.8456] +2024-11-22 12:46:59.952727: Epoch time: 18.52 s +2024-11-22 12:47:00.881418: +2024-11-22 12:47:00.882182: Epoch 4717 +2024-11-22 12:47:00.882313: Current learning rate: 0.00449 +2024-11-22 12:47:20.233596: train_loss -0.7856 +2024-11-22 12:47:20.243465: val_loss -0.7761 +2024-11-22 12:47:20.243613: Pseudo dice [0.8398] +2024-11-22 12:47:20.243714: Epoch time: 19.35 s +2024-11-22 12:47:21.269156: +2024-11-22 12:47:21.269743: Epoch 4718 +2024-11-22 12:47:21.269867: Current learning rate: 0.00448 +2024-11-22 12:47:40.120728: train_loss -0.7922 +2024-11-22 12:47:40.125507: val_loss -0.7614 +2024-11-22 12:47:40.125615: Pseudo dice [0.8565] +2024-11-22 12:47:40.125700: Epoch time: 18.85 s +2024-11-22 12:47:40.990368: +2024-11-22 12:47:40.990812: Epoch 4719 +2024-11-22 12:47:40.990926: Current learning rate: 0.00448 +2024-11-22 12:48:00.160732: train_loss -0.7985 +2024-11-22 12:48:00.161572: val_loss -0.7694 +2024-11-22 12:48:00.161669: Pseudo dice [0.8523] +2024-11-22 12:48:00.161781: Epoch time: 19.17 s +2024-11-22 12:48:01.003309: +2024-11-22 12:48:01.003486: Epoch 4720 +2024-11-22 12:48:01.003600: Current learning rate: 0.00448 +2024-11-22 12:48:20.132520: train_loss -0.7937 +2024-11-22 12:48:20.136388: val_loss -0.7847 +2024-11-22 12:48:20.136523: Pseudo dice [0.8576] +2024-11-22 12:48:20.136617: Epoch time: 19.13 s +2024-11-22 12:48:20.994476: +2024-11-22 12:48:20.994690: Epoch 4721 +2024-11-22 12:48:20.994810: Current learning rate: 0.00448 +2024-11-22 12:48:39.596562: train_loss -0.8056 +2024-11-22 12:48:39.596818: val_loss -0.7762 +2024-11-22 12:48:39.596904: Pseudo dice [0.8534] +2024-11-22 12:48:39.596989: Epoch time: 18.6 s +2024-11-22 12:48:40.492413: +2024-11-22 12:48:40.492659: Epoch 4722 +2024-11-22 12:48:40.492785: Current learning rate: 0.00448 +2024-11-22 12:48:59.108591: train_loss -0.8008 +2024-11-22 12:48:59.111323: val_loss -0.7825 +2024-11-22 12:48:59.111461: Pseudo dice [0.8567] +2024-11-22 12:48:59.111550: Epoch time: 18.62 s +2024-11-22 12:48:59.959960: +2024-11-22 12:48:59.960191: Epoch 4723 +2024-11-22 12:48:59.960317: Current learning rate: 0.00448 +2024-11-22 12:49:18.144772: train_loss -0.8007 +2024-11-22 12:49:18.147271: val_loss -0.7915 +2024-11-22 12:49:18.147408: Pseudo dice [0.855] +2024-11-22 12:49:18.148288: Epoch time: 18.19 s +2024-11-22 12:49:19.020465: +2024-11-22 12:49:19.020683: Epoch 4724 +2024-11-22 12:49:19.020812: Current learning rate: 0.00448 +2024-11-22 12:49:37.970755: train_loss -0.7869 +2024-11-22 12:49:37.973957: val_loss -0.7751 +2024-11-22 12:49:37.974085: Pseudo dice [0.8442] +2024-11-22 12:49:37.974168: Epoch time: 18.95 s +2024-11-22 12:49:38.852790: +2024-11-22 12:49:38.852992: Epoch 4725 +2024-11-22 12:49:38.853132: Current learning rate: 0.00448 +2024-11-22 12:49:57.421918: train_loss -0.7825 +2024-11-22 12:49:57.424617: val_loss -0.777 +2024-11-22 12:49:57.424797: Pseudo dice [0.8534] +2024-11-22 12:49:57.424885: Epoch time: 18.57 s +2024-11-22 12:49:58.275489: +2024-11-22 12:49:58.275689: Epoch 4726 +2024-11-22 12:49:58.275815: Current learning rate: 0.00447 +2024-11-22 12:50:14.802095: train_loss -0.7899 +2024-11-22 12:50:14.807022: val_loss -0.7429 +2024-11-22 12:50:14.807190: Pseudo dice [0.8562] +2024-11-22 12:50:14.807281: Epoch time: 16.53 s +2024-11-22 12:50:15.749139: +2024-11-22 12:50:15.749345: Epoch 4727 +2024-11-22 12:50:15.749475: Current learning rate: 0.00447 +2024-11-22 12:50:34.962271: train_loss -0.7966 +2024-11-22 12:50:34.962805: val_loss -0.7692 +2024-11-22 12:50:34.962903: Pseudo dice [0.8534] +2024-11-22 12:50:34.963008: Epoch time: 19.21 s +2024-11-22 12:50:35.807442: +2024-11-22 12:50:35.807632: Epoch 4728 +2024-11-22 12:50:35.807748: Current learning rate: 0.00447 +2024-11-22 12:50:54.262435: train_loss -0.7989 +2024-11-22 12:50:54.281517: val_loss -0.7739 +2024-11-22 12:50:54.281662: Pseudo dice [0.8499] +2024-11-22 12:50:54.281767: Epoch time: 18.46 s +2024-11-22 12:50:55.267642: +2024-11-22 12:50:55.269349: Epoch 4729 +2024-11-22 12:50:55.269474: Current learning rate: 0.00447 +2024-11-22 12:51:15.473229: train_loss -0.7964 +2024-11-22 12:51:15.483010: val_loss -0.7559 +2024-11-22 12:51:15.483146: Pseudo dice [0.8583] +2024-11-22 12:51:15.483233: Epoch time: 20.2 s +2024-11-22 12:51:16.422782: +2024-11-22 12:51:16.423850: Epoch 4730 +2024-11-22 12:51:16.423985: Current learning rate: 0.00447 +2024-11-22 12:51:34.822570: train_loss -0.7989 +2024-11-22 12:51:34.830001: val_loss -0.7931 +2024-11-22 12:51:34.830164: Pseudo dice [0.8629] +2024-11-22 12:51:34.830323: Epoch time: 18.4 s +2024-11-22 12:51:35.879621: +2024-11-22 12:51:35.880824: Epoch 4731 +2024-11-22 12:51:35.880947: Current learning rate: 0.00447 +2024-11-22 12:51:57.277206: train_loss -0.8045 +2024-11-22 12:51:57.282627: val_loss -0.7878 +2024-11-22 12:51:57.282735: Pseudo dice [0.8599] +2024-11-22 12:51:57.303681: Epoch time: 21.4 s +2024-11-22 12:51:58.748104: +2024-11-22 12:51:58.749873: Epoch 4732 +2024-11-22 12:51:58.749998: Current learning rate: 0.00447 +2024-11-22 12:52:18.429734: train_loss -0.7784 +2024-11-22 12:52:18.439540: val_loss -0.7741 +2024-11-22 12:52:18.439671: Pseudo dice [0.854] +2024-11-22 12:52:18.439762: Epoch time: 19.68 s +2024-11-22 12:52:19.369580: +2024-11-22 12:52:19.370323: Epoch 4733 +2024-11-22 12:52:19.370443: Current learning rate: 0.00447 +2024-11-22 12:52:38.882962: train_loss -0.7725 +2024-11-22 12:52:38.885923: val_loss -0.7749 +2024-11-22 12:52:38.886019: Pseudo dice [0.8485] +2024-11-22 12:52:38.886115: Epoch time: 19.51 s +2024-11-22 12:52:39.729081: +2024-11-22 12:52:39.729298: Epoch 4734 +2024-11-22 12:52:39.729415: Current learning rate: 0.00447 +2024-11-22 12:52:58.797565: train_loss -0.775 +2024-11-22 12:52:58.802978: val_loss -0.7316 +2024-11-22 12:52:58.803114: Pseudo dice [0.8317] +2024-11-22 12:52:58.803232: Epoch time: 19.07 s +2024-11-22 12:52:59.759207: +2024-11-22 12:52:59.759799: Epoch 4735 +2024-11-22 12:52:59.759923: Current learning rate: 0.00446 +2024-11-22 12:53:18.946428: train_loss -0.7915 +2024-11-22 12:53:18.956518: val_loss -0.7719 +2024-11-22 12:53:18.956644: Pseudo dice [0.8455] +2024-11-22 12:53:18.956747: Epoch time: 19.19 s +2024-11-22 12:53:19.822378: +2024-11-22 12:53:19.823405: Epoch 4736 +2024-11-22 12:53:19.823521: Current learning rate: 0.00446 +2024-11-22 12:53:38.822150: train_loss -0.7865 +2024-11-22 12:53:38.828717: val_loss -0.7722 +2024-11-22 12:53:38.828834: Pseudo dice [0.8496] +2024-11-22 12:53:38.828920: Epoch time: 19.0 s +2024-11-22 12:53:39.713298: +2024-11-22 12:53:39.713896: Epoch 4737 +2024-11-22 12:53:39.714008: Current learning rate: 0.00446 +2024-11-22 12:53:58.467887: train_loss -0.7963 +2024-11-22 12:53:58.490762: val_loss -0.7514 +2024-11-22 12:53:58.490894: Pseudo dice [0.8404] +2024-11-22 12:53:58.490987: Epoch time: 18.76 s +2024-11-22 12:53:59.342952: +2024-11-22 12:53:59.343703: Epoch 4738 +2024-11-22 12:53:59.343820: Current learning rate: 0.00446 +2024-11-22 12:54:19.514052: train_loss -0.78 +2024-11-22 12:54:19.522041: val_loss -0.7807 +2024-11-22 12:54:19.522207: Pseudo dice [0.8575] +2024-11-22 12:54:19.522300: Epoch time: 20.17 s +2024-11-22 12:54:20.371255: +2024-11-22 12:54:20.371862: Epoch 4739 +2024-11-22 12:54:20.371975: Current learning rate: 0.00446 +2024-11-22 12:54:38.902217: train_loss -0.792 +2024-11-22 12:54:38.907058: val_loss -0.7754 +2024-11-22 12:54:38.907157: Pseudo dice [0.8387] +2024-11-22 12:54:38.907248: Epoch time: 18.53 s +2024-11-22 12:54:39.762522: +2024-11-22 12:54:39.762976: Epoch 4740 +2024-11-22 12:54:39.763097: Current learning rate: 0.00446 +2024-11-22 12:54:57.693894: train_loss -0.7912 +2024-11-22 12:54:57.702857: val_loss -0.7641 +2024-11-22 12:54:57.702985: Pseudo dice [0.8648] +2024-11-22 12:54:57.703083: Epoch time: 17.93 s +2024-11-22 12:54:58.618429: +2024-11-22 12:54:58.618623: Epoch 4741 +2024-11-22 12:54:58.618745: Current learning rate: 0.00446 +2024-11-22 12:55:18.084212: train_loss -0.7894 +2024-11-22 12:55:18.099519: val_loss -0.7769 +2024-11-22 12:55:18.099662: Pseudo dice [0.8608] +2024-11-22 12:55:18.099760: Epoch time: 19.47 s +2024-11-22 12:55:18.985073: +2024-11-22 12:55:18.985530: Epoch 4742 +2024-11-22 12:55:18.985646: Current learning rate: 0.00446 +2024-11-22 12:55:38.121596: train_loss -0.7964 +2024-11-22 12:55:38.130043: val_loss -0.7741 +2024-11-22 12:55:38.130239: Pseudo dice [0.8594] +2024-11-22 12:55:38.130336: Epoch time: 19.14 s +2024-11-22 12:55:39.065738: +2024-11-22 12:55:39.066328: Epoch 4743 +2024-11-22 12:55:39.066444: Current learning rate: 0.00445 +2024-11-22 12:55:59.433736: train_loss -0.8076 +2024-11-22 12:55:59.438828: val_loss -0.7766 +2024-11-22 12:55:59.438964: Pseudo dice [0.8555] +2024-11-22 12:55:59.439052: Epoch time: 20.37 s +2024-11-22 12:56:00.288806: +2024-11-22 12:56:00.289029: Epoch 4744 +2024-11-22 12:56:00.289147: Current learning rate: 0.00445 +2024-11-22 12:56:19.949128: train_loss -0.801 +2024-11-22 12:56:19.991241: val_loss -0.7687 +2024-11-22 12:56:19.991415: Pseudo dice [0.8383] +2024-11-22 12:56:19.991501: Epoch time: 19.66 s +2024-11-22 12:56:21.043552: +2024-11-22 12:56:21.044007: Epoch 4745 +2024-11-22 12:56:21.044127: Current learning rate: 0.00445 +2024-11-22 12:56:41.064582: train_loss -0.7987 +2024-11-22 12:56:41.069316: val_loss -0.7682 +2024-11-22 12:56:41.069438: Pseudo dice [0.8424] +2024-11-22 12:56:41.069521: Epoch time: 20.02 s +2024-11-22 12:56:42.124494: +2024-11-22 12:56:42.125113: Epoch 4746 +2024-11-22 12:56:42.125237: Current learning rate: 0.00445 +2024-11-22 12:57:01.871801: train_loss -0.7984 +2024-11-22 12:57:01.881595: val_loss -0.7792 +2024-11-22 12:57:01.881738: Pseudo dice [0.8513] +2024-11-22 12:57:01.881835: Epoch time: 19.75 s +2024-11-22 12:57:02.873785: +2024-11-22 12:57:02.874556: Epoch 4747 +2024-11-22 12:57:02.874678: Current learning rate: 0.00445 +2024-11-22 12:57:22.015713: train_loss -0.7954 +2024-11-22 12:57:22.024874: val_loss -0.773 +2024-11-22 12:57:22.025018: Pseudo dice [0.8537] +2024-11-22 12:57:22.025115: Epoch time: 19.14 s +2024-11-22 12:57:22.968734: +2024-11-22 12:57:22.970186: Epoch 4748 +2024-11-22 12:57:22.970312: Current learning rate: 0.00445 +2024-11-22 12:57:42.022273: train_loss -0.7954 +2024-11-22 12:57:42.026075: val_loss -0.8041 +2024-11-22 12:57:42.026207: Pseudo dice [0.8727] +2024-11-22 12:57:42.026315: Epoch time: 19.05 s +2024-11-22 12:57:43.124987: +2024-11-22 12:57:43.125923: Epoch 4749 +2024-11-22 12:57:43.126044: Current learning rate: 0.00445 +2024-11-22 12:58:01.451860: train_loss -0.8001 +2024-11-22 12:58:01.461543: val_loss -0.7865 +2024-11-22 12:58:01.461963: Pseudo dice [0.8562] +2024-11-22 12:58:01.462070: Epoch time: 18.33 s +2024-11-22 12:58:02.688248: +2024-11-22 12:58:02.688918: Epoch 4750 +2024-11-22 12:58:02.689052: Current learning rate: 0.00445 +2024-11-22 12:58:21.471798: train_loss -0.7988 +2024-11-22 12:58:21.480837: val_loss -0.788 +2024-11-22 12:58:21.480983: Pseudo dice [0.8528] +2024-11-22 12:58:21.481079: Epoch time: 18.78 s +2024-11-22 12:58:22.401138: +2024-11-22 12:58:22.401721: Epoch 4751 +2024-11-22 12:58:22.401840: Current learning rate: 0.00444 +2024-11-22 12:58:41.922932: train_loss -0.7899 +2024-11-22 12:58:41.926661: val_loss -0.759 +2024-11-22 12:58:41.926787: Pseudo dice [0.8665] +2024-11-22 12:58:41.926881: Epoch time: 19.52 s +2024-11-22 12:58:42.780941: +2024-11-22 12:58:42.781711: Epoch 4752 +2024-11-22 12:58:42.781826: Current learning rate: 0.00444 +2024-11-22 12:59:02.146054: train_loss -0.7915 +2024-11-22 12:59:02.171435: val_loss -0.7565 +2024-11-22 12:59:02.171591: Pseudo dice [0.8406] +2024-11-22 12:59:02.171682: Epoch time: 19.37 s +2024-11-22 12:59:03.154476: +2024-11-22 12:59:03.156930: Epoch 4753 +2024-11-22 12:59:03.157068: Current learning rate: 0.00444 +2024-11-22 12:59:22.508656: train_loss -0.7783 +2024-11-22 12:59:22.511756: val_loss -0.7676 +2024-11-22 12:59:22.511900: Pseudo dice [0.8364] +2024-11-22 12:59:22.511985: Epoch time: 19.35 s +2024-11-22 12:59:23.440318: +2024-11-22 12:59:23.440516: Epoch 4754 +2024-11-22 12:59:23.440629: Current learning rate: 0.00444 +2024-11-22 12:59:42.562114: train_loss -0.788 +2024-11-22 12:59:42.569354: val_loss -0.7994 +2024-11-22 12:59:42.569504: Pseudo dice [0.8622] +2024-11-22 12:59:42.569602: Epoch time: 19.12 s +2024-11-22 12:59:43.826660: +2024-11-22 12:59:43.827146: Epoch 4755 +2024-11-22 12:59:43.827265: Current learning rate: 0.00444 +2024-11-22 13:00:02.556761: train_loss -0.7989 +2024-11-22 13:00:02.560290: val_loss -0.7753 +2024-11-22 13:00:02.560412: Pseudo dice [0.8619] +2024-11-22 13:00:02.560500: Epoch time: 18.73 s +2024-11-22 13:00:03.411458: +2024-11-22 13:00:03.412000: Epoch 4756 +2024-11-22 13:00:03.412118: Current learning rate: 0.00444 +2024-11-22 13:00:22.538898: train_loss -0.7962 +2024-11-22 13:00:22.550581: val_loss -0.7856 +2024-11-22 13:00:22.550717: Pseudo dice [0.8569] +2024-11-22 13:00:22.550812: Epoch time: 19.13 s +2024-11-22 13:00:23.452179: +2024-11-22 13:00:23.452395: Epoch 4757 +2024-11-22 13:00:23.452709: Current learning rate: 0.00444 +2024-11-22 13:00:42.596418: train_loss -0.7964 +2024-11-22 13:00:42.603693: val_loss -0.7883 +2024-11-22 13:00:42.603812: Pseudo dice [0.8583] +2024-11-22 13:00:42.603913: Epoch time: 19.15 s +2024-11-22 13:00:43.765193: +2024-11-22 13:00:43.765678: Epoch 4758 +2024-11-22 13:00:43.765810: Current learning rate: 0.00444 +2024-11-22 13:01:03.910738: train_loss -0.7983 +2024-11-22 13:01:03.912891: val_loss -0.7885 +2024-11-22 13:01:03.913016: Pseudo dice [0.8519] +2024-11-22 13:01:03.913118: Epoch time: 20.15 s +2024-11-22 13:01:04.847967: +2024-11-22 13:01:04.848628: Epoch 4759 +2024-11-22 13:01:04.848749: Current learning rate: 0.00443 +2024-11-22 13:01:25.149533: train_loss -0.7977 +2024-11-22 13:01:25.161812: val_loss -0.7693 +2024-11-22 13:01:25.161952: Pseudo dice [0.8602] +2024-11-22 13:01:25.162049: Epoch time: 20.3 s +2024-11-22 13:01:26.072181: +2024-11-22 13:01:26.072393: Epoch 4760 +2024-11-22 13:01:26.072513: Current learning rate: 0.00443 +2024-11-22 13:01:44.564404: train_loss -0.7922 +2024-11-22 13:01:44.576256: val_loss -0.7712 +2024-11-22 13:01:44.576376: Pseudo dice [0.8534] +2024-11-22 13:01:44.576472: Epoch time: 18.49 s +2024-11-22 13:01:45.520452: +2024-11-22 13:01:45.520649: Epoch 4761 +2024-11-22 13:01:45.520775: Current learning rate: 0.00443 +2024-11-22 13:02:05.373508: train_loss -0.7908 +2024-11-22 13:02:05.380075: val_loss -0.7446 +2024-11-22 13:02:05.380188: Pseudo dice [0.8462] +2024-11-22 13:02:05.380270: Epoch time: 19.85 s +2024-11-22 13:02:06.367177: +2024-11-22 13:02:06.367392: Epoch 4762 +2024-11-22 13:02:06.367515: Current learning rate: 0.00443 +2024-11-22 13:02:26.199046: train_loss -0.7968 +2024-11-22 13:02:26.200863: val_loss -0.7709 +2024-11-22 13:02:26.200963: Pseudo dice [0.8553] +2024-11-22 13:02:26.201054: Epoch time: 19.83 s +2024-11-22 13:02:27.062140: +2024-11-22 13:02:27.063337: Epoch 4763 +2024-11-22 13:02:27.063463: Current learning rate: 0.00443 +2024-11-22 13:02:47.143407: train_loss -0.7967 +2024-11-22 13:02:47.158638: val_loss -0.7975 +2024-11-22 13:02:47.158839: Pseudo dice [0.8565] +2024-11-22 13:02:47.158938: Epoch time: 20.08 s +2024-11-22 13:02:48.047570: +2024-11-22 13:02:48.048450: Epoch 4764 +2024-11-22 13:02:48.048579: Current learning rate: 0.00443 +2024-11-22 13:03:08.836858: train_loss -0.7994 +2024-11-22 13:03:08.850450: val_loss -0.7812 +2024-11-22 13:03:08.850646: Pseudo dice [0.8534] +2024-11-22 13:03:08.850765: Epoch time: 20.79 s +2024-11-22 13:03:09.830630: +2024-11-22 13:03:09.831295: Epoch 4765 +2024-11-22 13:03:09.831421: Current learning rate: 0.00443 +2024-11-22 13:03:30.189902: train_loss -0.7989 +2024-11-22 13:03:30.196235: val_loss -0.7868 +2024-11-22 13:03:30.196348: Pseudo dice [0.8581] +2024-11-22 13:03:30.196439: Epoch time: 20.36 s +2024-11-22 13:03:31.603318: +2024-11-22 13:03:31.605014: Epoch 4766 +2024-11-22 13:03:31.605180: Current learning rate: 0.00443 +2024-11-22 13:03:52.036739: train_loss -0.7784 +2024-11-22 13:03:52.052112: val_loss -0.7524 +2024-11-22 13:03:52.052277: Pseudo dice [0.836] +2024-11-22 13:03:52.052384: Epoch time: 20.43 s +2024-11-22 13:03:52.984916: +2024-11-22 13:03:52.985141: Epoch 4767 +2024-11-22 13:03:52.985272: Current learning rate: 0.00442 +2024-11-22 13:04:11.668319: train_loss -0.7762 +2024-11-22 13:04:11.681394: val_loss -0.7501 +2024-11-22 13:04:11.681626: Pseudo dice [0.8298] +2024-11-22 13:04:11.681797: Epoch time: 18.68 s +2024-11-22 13:04:12.596628: +2024-11-22 13:04:12.598424: Epoch 4768 +2024-11-22 13:04:12.598549: Current learning rate: 0.00442 +2024-11-22 13:04:30.286089: train_loss -0.7707 +2024-11-22 13:04:30.292737: val_loss -0.7763 +2024-11-22 13:04:30.292866: Pseudo dice [0.8554] +2024-11-22 13:04:30.292948: Epoch time: 17.69 s +2024-11-22 13:04:31.157720: +2024-11-22 13:04:31.158582: Epoch 4769 +2024-11-22 13:04:31.158698: Current learning rate: 0.00442 +2024-11-22 13:04:49.404057: train_loss -0.7752 +2024-11-22 13:04:49.405540: val_loss -0.7862 +2024-11-22 13:04:49.405647: Pseudo dice [0.8594] +2024-11-22 13:04:49.406354: Epoch time: 18.25 s +2024-11-22 13:04:50.291465: +2024-11-22 13:04:50.291679: Epoch 4770 +2024-11-22 13:04:50.291799: Current learning rate: 0.00442 +2024-11-22 13:05:09.429763: train_loss -0.791 +2024-11-22 13:05:09.436257: val_loss -0.7712 +2024-11-22 13:05:09.436401: Pseudo dice [0.862] +2024-11-22 13:05:09.436497: Epoch time: 19.14 s +2024-11-22 13:05:10.400412: +2024-11-22 13:05:10.401307: Epoch 4771 +2024-11-22 13:05:10.401428: Current learning rate: 0.00442 +2024-11-22 13:05:29.472704: train_loss -0.7868 +2024-11-22 13:05:29.478639: val_loss -0.7382 +2024-11-22 13:05:29.478764: Pseudo dice [0.8386] +2024-11-22 13:05:29.478848: Epoch time: 19.07 s +2024-11-22 13:05:30.426415: +2024-11-22 13:05:30.426634: Epoch 4772 +2024-11-22 13:05:30.426757: Current learning rate: 0.00442 +2024-11-22 13:05:50.553139: train_loss -0.775 +2024-11-22 13:05:50.561820: val_loss -0.7598 +2024-11-22 13:05:50.561946: Pseudo dice [0.856] +2024-11-22 13:05:50.562032: Epoch time: 20.13 s +2024-11-22 13:05:51.589278: +2024-11-22 13:05:51.589483: Epoch 4773 +2024-11-22 13:05:51.589606: Current learning rate: 0.00442 +2024-11-22 13:06:10.459229: train_loss -0.7961 +2024-11-22 13:06:10.466871: val_loss -0.7677 +2024-11-22 13:06:10.467006: Pseudo dice [0.8439] +2024-11-22 13:06:10.467103: Epoch time: 18.87 s +2024-11-22 13:06:11.350865: +2024-11-22 13:06:11.352338: Epoch 4774 +2024-11-22 13:06:11.352511: Current learning rate: 0.00442 +2024-11-22 13:06:31.094700: train_loss -0.7959 +2024-11-22 13:06:31.097739: val_loss -0.7757 +2024-11-22 13:06:31.097843: Pseudo dice [0.8667] +2024-11-22 13:06:31.097933: Epoch time: 19.74 s +2024-11-22 13:06:31.945192: +2024-11-22 13:06:31.945400: Epoch 4775 +2024-11-22 13:06:31.945516: Current learning rate: 0.00441 +2024-11-22 13:06:50.676668: train_loss -0.791 +2024-11-22 13:06:50.689503: val_loss -0.7771 +2024-11-22 13:06:50.689827: Pseudo dice [0.8585] +2024-11-22 13:06:50.689928: Epoch time: 18.73 s +2024-11-22 13:06:51.704585: +2024-11-22 13:06:51.705034: Epoch 4776 +2024-11-22 13:06:51.705158: Current learning rate: 0.00441 +2024-11-22 13:07:10.801637: train_loss -0.7953 +2024-11-22 13:07:10.810843: val_loss -0.7585 +2024-11-22 13:07:10.810981: Pseudo dice [0.8497] +2024-11-22 13:07:10.811086: Epoch time: 19.1 s +2024-11-22 13:07:11.725564: +2024-11-22 13:07:11.726194: Epoch 4777 +2024-11-22 13:07:11.726310: Current learning rate: 0.00441 +2024-11-22 13:07:31.503792: train_loss -0.7952 +2024-11-22 13:07:31.509588: val_loss -0.7682 +2024-11-22 13:07:31.509709: Pseudo dice [0.8611] +2024-11-22 13:07:31.509829: Epoch time: 19.78 s +2024-11-22 13:07:32.806571: +2024-11-22 13:07:32.807804: Epoch 4778 +2024-11-22 13:07:32.807924: Current learning rate: 0.00441 +2024-11-22 13:07:53.895119: train_loss -0.7868 +2024-11-22 13:07:53.897553: val_loss -0.7529 +2024-11-22 13:07:53.897671: Pseudo dice [0.8415] +2024-11-22 13:07:53.897769: Epoch time: 21.09 s +2024-11-22 13:07:54.751693: +2024-11-22 13:07:54.752557: Epoch 4779 +2024-11-22 13:07:54.752673: Current learning rate: 0.00441 +2024-11-22 13:08:13.874582: train_loss -0.8014 +2024-11-22 13:08:13.884344: val_loss -0.7707 +2024-11-22 13:08:13.884486: Pseudo dice [0.8483] +2024-11-22 13:08:13.884575: Epoch time: 19.12 s +2024-11-22 13:08:14.804077: +2024-11-22 13:08:14.804664: Epoch 4780 +2024-11-22 13:08:14.804792: Current learning rate: 0.00441 +2024-11-22 13:08:34.585850: train_loss -0.7782 +2024-11-22 13:08:34.592324: val_loss -0.7717 +2024-11-22 13:08:34.592456: Pseudo dice [0.8285] +2024-11-22 13:08:34.592546: Epoch time: 19.78 s +2024-11-22 13:08:35.709088: +2024-11-22 13:08:35.710441: Epoch 4781 +2024-11-22 13:08:35.710574: Current learning rate: 0.00441 +2024-11-22 13:08:55.328359: train_loss -0.7879 +2024-11-22 13:08:55.335389: val_loss -0.7735 +2024-11-22 13:08:55.335539: Pseudo dice [0.8642] +2024-11-22 13:08:55.335640: Epoch time: 19.62 s +2024-11-22 13:08:56.195920: +2024-11-22 13:08:56.196954: Epoch 4782 +2024-11-22 13:08:56.197080: Current learning rate: 0.00441 +2024-11-22 13:09:14.800127: train_loss -0.7954 +2024-11-22 13:09:14.802923: val_loss -0.7494 +2024-11-22 13:09:14.803112: Pseudo dice [0.8522] +2024-11-22 13:09:14.803200: Epoch time: 18.61 s +2024-11-22 13:09:15.814709: +2024-11-22 13:09:15.815830: Epoch 4783 +2024-11-22 13:09:15.815951: Current learning rate: 0.0044 +2024-11-22 13:09:33.736824: train_loss -0.7942 +2024-11-22 13:09:33.744106: val_loss -0.7718 +2024-11-22 13:09:33.744245: Pseudo dice [0.8405] +2024-11-22 13:09:33.744365: Epoch time: 17.92 s +2024-11-22 13:09:34.894359: +2024-11-22 13:09:34.895187: Epoch 4784 +2024-11-22 13:09:34.895303: Current learning rate: 0.0044 +2024-11-22 13:09:53.941921: train_loss -0.7908 +2024-11-22 13:09:53.947975: val_loss -0.7616 +2024-11-22 13:09:53.948113: Pseudo dice [0.8517] +2024-11-22 13:09:53.948212: Epoch time: 19.05 s +2024-11-22 13:09:55.006444: +2024-11-22 13:09:55.006979: Epoch 4785 +2024-11-22 13:09:55.007104: Current learning rate: 0.0044 +2024-11-22 13:10:13.585973: train_loss -0.7969 +2024-11-22 13:10:13.594261: val_loss -0.7851 +2024-11-22 13:10:13.594394: Pseudo dice [0.8589] +2024-11-22 13:10:13.594496: Epoch time: 18.58 s +2024-11-22 13:10:14.488839: +2024-11-22 13:10:14.490922: Epoch 4786 +2024-11-22 13:10:14.491091: Current learning rate: 0.0044 +2024-11-22 13:10:32.727599: train_loss -0.796 +2024-11-22 13:10:32.734869: val_loss -0.7455 +2024-11-22 13:10:32.734979: Pseudo dice [0.8566] +2024-11-22 13:10:32.735068: Epoch time: 18.24 s +2024-11-22 13:10:33.726285: +2024-11-22 13:10:33.727148: Epoch 4787 +2024-11-22 13:10:33.727272: Current learning rate: 0.0044 +2024-11-22 13:10:53.449069: train_loss -0.7996 +2024-11-22 13:10:53.463147: val_loss -0.7964 +2024-11-22 13:10:53.463267: Pseudo dice [0.8554] +2024-11-22 13:10:53.463364: Epoch time: 19.72 s +2024-11-22 13:10:54.475653: +2024-11-22 13:10:54.476851: Epoch 4788 +2024-11-22 13:10:54.476984: Current learning rate: 0.0044 +2024-11-22 13:11:13.809173: train_loss -0.7972 +2024-11-22 13:11:13.812325: val_loss -0.7757 +2024-11-22 13:11:13.812426: Pseudo dice [0.8471] +2024-11-22 13:11:13.812521: Epoch time: 19.33 s +2024-11-22 13:11:15.102275: +2024-11-22 13:11:15.102833: Epoch 4789 +2024-11-22 13:11:15.102962: Current learning rate: 0.0044 +2024-11-22 13:11:35.604185: train_loss -0.7987 +2024-11-22 13:11:35.614201: val_loss -0.7746 +2024-11-22 13:11:35.614342: Pseudo dice [0.8525] +2024-11-22 13:11:35.614445: Epoch time: 20.5 s +2024-11-22 13:11:36.662407: +2024-11-22 13:11:36.663412: Epoch 4790 +2024-11-22 13:11:36.663541: Current learning rate: 0.0044 +2024-11-22 13:11:56.210843: train_loss -0.8061 +2024-11-22 13:11:56.216388: val_loss -0.7778 +2024-11-22 13:11:56.216501: Pseudo dice [0.8578] +2024-11-22 13:11:56.216588: Epoch time: 19.55 s +2024-11-22 13:11:57.123322: +2024-11-22 13:11:57.124235: Epoch 4791 +2024-11-22 13:11:57.124369: Current learning rate: 0.00439 +2024-11-22 13:12:16.456465: train_loss -0.794 +2024-11-22 13:12:16.463645: val_loss -0.7894 +2024-11-22 13:12:16.463753: Pseudo dice [0.8594] +2024-11-22 13:12:16.463834: Epoch time: 19.33 s +2024-11-22 13:12:17.447328: +2024-11-22 13:12:17.448228: Epoch 4792 +2024-11-22 13:12:17.448353: Current learning rate: 0.00439 +2024-11-22 13:12:37.121637: train_loss -0.7791 +2024-11-22 13:12:37.125589: val_loss -0.7693 +2024-11-22 13:12:37.125698: Pseudo dice [0.8532] +2024-11-22 13:12:37.125845: Epoch time: 19.67 s +2024-11-22 13:12:37.989478: +2024-11-22 13:12:37.990879: Epoch 4793 +2024-11-22 13:12:37.990999: Current learning rate: 0.00439 +2024-11-22 13:12:58.530340: train_loss -0.7797 +2024-11-22 13:12:58.538769: val_loss -0.7741 +2024-11-22 13:12:58.538914: Pseudo dice [0.846] +2024-11-22 13:12:58.539011: Epoch time: 20.54 s +2024-11-22 13:12:59.427575: +2024-11-22 13:12:59.428142: Epoch 4794 +2024-11-22 13:12:59.428255: Current learning rate: 0.00439 +2024-11-22 13:13:18.571475: train_loss -0.7835 +2024-11-22 13:13:18.575850: val_loss -0.7662 +2024-11-22 13:13:18.575989: Pseudo dice [0.8584] +2024-11-22 13:13:18.576092: Epoch time: 19.14 s +2024-11-22 13:13:19.487655: +2024-11-22 13:13:19.487863: Epoch 4795 +2024-11-22 13:13:19.487989: Current learning rate: 0.00439 +2024-11-22 13:13:40.735972: train_loss -0.7792 +2024-11-22 13:13:40.736717: val_loss -0.7709 +2024-11-22 13:13:40.736850: Pseudo dice [0.8352] +2024-11-22 13:13:40.736949: Epoch time: 21.25 s +2024-11-22 13:13:41.583468: +2024-11-22 13:13:41.583671: Epoch 4796 +2024-11-22 13:13:41.583789: Current learning rate: 0.00439 +2024-11-22 13:14:00.530772: train_loss -0.7785 +2024-11-22 13:14:00.530993: val_loss -0.7844 +2024-11-22 13:14:00.531092: Pseudo dice [0.8474] +2024-11-22 13:14:00.531170: Epoch time: 18.95 s +2024-11-22 13:14:01.450586: +2024-11-22 13:14:01.450791: Epoch 4797 +2024-11-22 13:14:01.450916: Current learning rate: 0.00439 +2024-11-22 13:14:19.380842: train_loss -0.7926 +2024-11-22 13:14:19.381564: val_loss -0.8029 +2024-11-22 13:14:19.381665: Pseudo dice [0.8593] +2024-11-22 13:14:19.381752: Epoch time: 17.93 s +2024-11-22 13:14:20.236412: +2024-11-22 13:14:20.236602: Epoch 4798 +2024-11-22 13:14:20.236724: Current learning rate: 0.00439 +2024-11-22 13:14:38.534288: train_loss -0.7969 +2024-11-22 13:14:38.534755: val_loss -0.7604 +2024-11-22 13:14:38.534842: Pseudo dice [0.8519] +2024-11-22 13:14:38.534922: Epoch time: 18.3 s +2024-11-22 13:14:39.388025: +2024-11-22 13:14:39.388233: Epoch 4799 +2024-11-22 13:14:39.388358: Current learning rate: 0.00439 +2024-11-22 13:14:57.704052: train_loss -0.7966 +2024-11-22 13:14:57.704593: val_loss -0.7921 +2024-11-22 13:14:57.704678: Pseudo dice [0.8556] +2024-11-22 13:14:57.704759: Epoch time: 18.32 s +2024-11-22 13:14:58.847008: +2024-11-22 13:14:58.847192: Epoch 4800 +2024-11-22 13:14:58.847312: Current learning rate: 0.00438 +2024-11-22 13:15:17.835916: train_loss -0.7913 +2024-11-22 13:15:17.836468: val_loss -0.7956 +2024-11-22 13:15:17.836594: Pseudo dice [0.8706] +2024-11-22 13:15:17.836695: Epoch time: 18.99 s +2024-11-22 13:15:19.132584: +2024-11-22 13:15:19.132826: Epoch 4801 +2024-11-22 13:15:19.132957: Current learning rate: 0.00438 +2024-11-22 13:15:37.634017: train_loss -0.794 +2024-11-22 13:15:37.639560: val_loss -0.793 +2024-11-22 13:15:37.639694: Pseudo dice [0.8611] +2024-11-22 13:15:37.639775: Epoch time: 18.5 s +2024-11-22 13:15:38.686807: +2024-11-22 13:15:38.687026: Epoch 4802 +2024-11-22 13:15:38.687167: Current learning rate: 0.00438 +2024-11-22 13:15:56.622877: train_loss -0.7908 +2024-11-22 13:15:56.629535: val_loss -0.7611 +2024-11-22 13:15:56.629646: Pseudo dice [0.869] +2024-11-22 13:15:56.629733: Epoch time: 17.94 s +2024-11-22 13:15:57.549562: +2024-11-22 13:15:57.552028: Epoch 4803 +2024-11-22 13:15:57.552148: Current learning rate: 0.00438 +2024-11-22 13:16:17.242242: train_loss -0.7952 +2024-11-22 13:16:17.246127: val_loss -0.7682 +2024-11-22 13:16:17.246241: Pseudo dice [0.8583] +2024-11-22 13:16:17.246325: Epoch time: 19.69 s +2024-11-22 13:16:18.106014: +2024-11-22 13:16:18.106479: Epoch 4804 +2024-11-22 13:16:18.106598: Current learning rate: 0.00438 +2024-11-22 13:16:38.255932: train_loss -0.79 +2024-11-22 13:16:38.261892: val_loss -0.7814 +2024-11-22 13:16:38.262040: Pseudo dice [0.8436] +2024-11-22 13:16:38.262142: Epoch time: 20.15 s +2024-11-22 13:16:39.280399: +2024-11-22 13:16:39.281746: Epoch 4805 +2024-11-22 13:16:39.281888: Current learning rate: 0.00438 +2024-11-22 13:16:59.067213: train_loss -0.7896 +2024-11-22 13:16:59.079579: val_loss -0.7775 +2024-11-22 13:16:59.079706: Pseudo dice [0.8534] +2024-11-22 13:16:59.079793: Epoch time: 19.79 s +2024-11-22 13:16:59.956488: +2024-11-22 13:16:59.956698: Epoch 4806 +2024-11-22 13:16:59.956817: Current learning rate: 0.00438 +2024-11-22 13:17:20.514044: train_loss -0.7908 +2024-11-22 13:17:20.521026: val_loss -0.7837 +2024-11-22 13:17:20.521164: Pseudo dice [0.8457] +2024-11-22 13:17:20.521257: Epoch time: 20.56 s +2024-11-22 13:17:21.431860: +2024-11-22 13:17:21.433287: Epoch 4807 +2024-11-22 13:17:21.433416: Current learning rate: 0.00438 +2024-11-22 13:17:40.816865: train_loss -0.7966 +2024-11-22 13:17:40.825296: val_loss -0.7884 +2024-11-22 13:17:40.825436: Pseudo dice [0.862] +2024-11-22 13:17:40.825524: Epoch time: 19.39 s +2024-11-22 13:17:41.837607: +2024-11-22 13:17:41.838811: Epoch 4808 +2024-11-22 13:17:41.838929: Current learning rate: 0.00437 +2024-11-22 13:18:01.686579: train_loss -0.7884 +2024-11-22 13:18:01.700044: val_loss -0.7622 +2024-11-22 13:18:01.700209: Pseudo dice [0.8352] +2024-11-22 13:18:01.700330: Epoch time: 19.85 s +2024-11-22 13:18:02.822582: +2024-11-22 13:18:02.823840: Epoch 4809 +2024-11-22 13:18:02.823965: Current learning rate: 0.00437 +2024-11-22 13:18:21.848352: train_loss -0.7983 +2024-11-22 13:18:21.861857: val_loss -0.763 +2024-11-22 13:18:21.862021: Pseudo dice [0.8509] +2024-11-22 13:18:21.862127: Epoch time: 19.03 s +2024-11-22 13:18:22.931841: +2024-11-22 13:18:22.932477: Epoch 4810 +2024-11-22 13:18:22.932603: Current learning rate: 0.00437 +2024-11-22 13:18:42.506727: train_loss -0.7973 +2024-11-22 13:18:42.514244: val_loss -0.7782 +2024-11-22 13:18:42.514364: Pseudo dice [0.8489] +2024-11-22 13:18:42.514447: Epoch time: 19.58 s +2024-11-22 13:18:43.382557: +2024-11-22 13:18:43.383401: Epoch 4811 +2024-11-22 13:18:43.383525: Current learning rate: 0.00437 +2024-11-22 13:19:02.234043: train_loss -0.8022 +2024-11-22 13:19:02.241182: val_loss -0.7644 +2024-11-22 13:19:02.241331: Pseudo dice [0.8439] +2024-11-22 13:19:02.241417: Epoch time: 18.85 s +2024-11-22 13:19:03.561416: +2024-11-22 13:19:03.563114: Epoch 4812 +2024-11-22 13:19:03.563242: Current learning rate: 0.00437 +2024-11-22 13:19:22.760725: train_loss -0.8006 +2024-11-22 13:19:22.767864: val_loss -0.7638 +2024-11-22 13:19:22.768002: Pseudo dice [0.8436] +2024-11-22 13:19:22.768111: Epoch time: 19.2 s +2024-11-22 13:19:23.759091: +2024-11-22 13:19:23.760592: Epoch 4813 +2024-11-22 13:19:23.760714: Current learning rate: 0.00437 +2024-11-22 13:19:42.501123: train_loss -0.7967 +2024-11-22 13:19:42.506999: val_loss -0.7698 +2024-11-22 13:19:42.507113: Pseudo dice [0.8559] +2024-11-22 13:19:42.507195: Epoch time: 18.74 s +2024-11-22 13:19:43.517774: +2024-11-22 13:19:43.519551: Epoch 4814 +2024-11-22 13:19:43.519671: Current learning rate: 0.00437 +2024-11-22 13:20:02.295961: train_loss -0.7922 +2024-11-22 13:20:02.303220: val_loss -0.7947 +2024-11-22 13:20:02.303425: Pseudo dice [0.8663] +2024-11-22 13:20:02.303543: Epoch time: 18.78 s +2024-11-22 13:20:03.174954: +2024-11-22 13:20:03.176199: Epoch 4815 +2024-11-22 13:20:03.176319: Current learning rate: 0.00437 +2024-11-22 13:20:22.773821: train_loss -0.7944 +2024-11-22 13:20:22.777624: val_loss -0.7815 +2024-11-22 13:20:22.777746: Pseudo dice [0.865] +2024-11-22 13:20:22.777833: Epoch time: 19.6 s +2024-11-22 13:20:23.652646: +2024-11-22 13:20:23.653475: Epoch 4816 +2024-11-22 13:20:23.653596: Current learning rate: 0.00436 +2024-11-22 13:20:42.601389: train_loss -0.8004 +2024-11-22 13:20:42.619901: val_loss -0.794 +2024-11-22 13:20:42.620040: Pseudo dice [0.8648] +2024-11-22 13:20:42.620144: Epoch time: 18.95 s +2024-11-22 13:20:43.589051: +2024-11-22 13:20:43.590730: Epoch 4817 +2024-11-22 13:20:43.590854: Current learning rate: 0.00436 +2024-11-22 13:21:02.836616: train_loss -0.7985 +2024-11-22 13:21:02.838960: val_loss -0.7825 +2024-11-22 13:21:02.839132: Pseudo dice [0.8499] +2024-11-22 13:21:02.839246: Epoch time: 19.25 s +2024-11-22 13:21:03.691547: +2024-11-22 13:21:03.692062: Epoch 4818 +2024-11-22 13:21:03.692182: Current learning rate: 0.00436 +2024-11-22 13:21:22.909825: train_loss -0.7969 +2024-11-22 13:21:22.914901: val_loss -0.7847 +2024-11-22 13:21:22.915019: Pseudo dice [0.8721] +2024-11-22 13:21:22.915121: Epoch time: 19.22 s +2024-11-22 13:21:23.920763: +2024-11-22 13:21:23.920954: Epoch 4819 +2024-11-22 13:21:23.921088: Current learning rate: 0.00436 +2024-11-22 13:21:44.250839: train_loss -0.8057 +2024-11-22 13:21:44.258970: val_loss -0.7881 +2024-11-22 13:21:44.259118: Pseudo dice [0.8468] +2024-11-22 13:21:44.259210: Epoch time: 20.33 s +2024-11-22 13:21:45.136149: +2024-11-22 13:21:45.137743: Epoch 4820 +2024-11-22 13:21:45.137870: Current learning rate: 0.00436 +2024-11-22 13:22:03.584047: train_loss -0.8041 +2024-11-22 13:22:03.590190: val_loss -0.7924 +2024-11-22 13:22:03.590525: Pseudo dice [0.8451] +2024-11-22 13:22:03.590640: Epoch time: 18.45 s +2024-11-22 13:22:04.449316: +2024-11-22 13:22:04.450345: Epoch 4821 +2024-11-22 13:22:04.450466: Current learning rate: 0.00436 +2024-11-22 13:22:24.044845: train_loss -0.7886 +2024-11-22 13:22:24.052448: val_loss -0.773 +2024-11-22 13:22:24.052589: Pseudo dice [0.8562] +2024-11-22 13:22:24.052687: Epoch time: 19.6 s +2024-11-22 13:22:24.970948: +2024-11-22 13:22:24.971338: Epoch 4822 +2024-11-22 13:22:24.971468: Current learning rate: 0.00436 +2024-11-22 13:22:45.334339: train_loss -0.7954 +2024-11-22 13:22:45.340877: val_loss -0.7637 +2024-11-22 13:22:45.341017: Pseudo dice [0.8413] +2024-11-22 13:22:45.341137: Epoch time: 20.36 s +2024-11-22 13:22:46.201464: +2024-11-22 13:22:46.202190: Epoch 4823 +2024-11-22 13:22:46.202302: Current learning rate: 0.00436 +2024-11-22 13:23:05.856657: train_loss -0.791 +2024-11-22 13:23:05.862486: val_loss -0.7787 +2024-11-22 13:23:05.862640: Pseudo dice [0.8644] +2024-11-22 13:23:05.862741: Epoch time: 19.66 s +2024-11-22 13:23:07.154066: +2024-11-22 13:23:07.155370: Epoch 4824 +2024-11-22 13:23:07.155483: Current learning rate: 0.00435 +2024-11-22 13:23:25.993592: train_loss -0.7906 +2024-11-22 13:23:26.001763: val_loss -0.784 +2024-11-22 13:23:26.001892: Pseudo dice [0.8649] +2024-11-22 13:23:26.002013: Epoch time: 18.84 s +2024-11-22 13:23:26.945169: +2024-11-22 13:23:26.945938: Epoch 4825 +2024-11-22 13:23:26.946065: Current learning rate: 0.00435 +2024-11-22 13:23:47.191834: train_loss -0.791 +2024-11-22 13:23:47.199280: val_loss -0.7684 +2024-11-22 13:23:47.199411: Pseudo dice [0.8499] +2024-11-22 13:23:47.199504: Epoch time: 20.25 s +2024-11-22 13:23:48.117438: +2024-11-22 13:23:48.118242: Epoch 4826 +2024-11-22 13:23:48.118373: Current learning rate: 0.00435 +2024-11-22 13:24:07.221040: train_loss -0.7875 +2024-11-22 13:24:07.223408: val_loss -0.7704 +2024-11-22 13:24:07.227320: Pseudo dice [0.8508] +2024-11-22 13:24:07.227451: Epoch time: 19.1 s +2024-11-22 13:24:08.098238: +2024-11-22 13:24:08.098849: Epoch 4827 +2024-11-22 13:24:08.098980: Current learning rate: 0.00435 +2024-11-22 13:24:28.150858: train_loss -0.7762 +2024-11-22 13:24:28.159199: val_loss -0.7433 +2024-11-22 13:24:28.159400: Pseudo dice [0.859] +2024-11-22 13:24:28.159497: Epoch time: 20.05 s +2024-11-22 13:24:29.137662: +2024-11-22 13:24:29.137866: Epoch 4828 +2024-11-22 13:24:29.137982: Current learning rate: 0.00435 +2024-11-22 13:24:48.675456: train_loss -0.7781 +2024-11-22 13:24:48.678762: val_loss -0.7809 +2024-11-22 13:24:48.678891: Pseudo dice [0.8409] +2024-11-22 13:24:48.678977: Epoch time: 19.54 s +2024-11-22 13:24:49.606923: +2024-11-22 13:24:49.607512: Epoch 4829 +2024-11-22 13:24:49.607625: Current learning rate: 0.00435 +2024-11-22 13:25:09.538684: train_loss -0.7946 +2024-11-22 13:25:09.546732: val_loss -0.7744 +2024-11-22 13:25:09.546848: Pseudo dice [0.8619] +2024-11-22 13:25:09.546929: Epoch time: 19.93 s +2024-11-22 13:25:10.538116: +2024-11-22 13:25:10.539327: Epoch 4830 +2024-11-22 13:25:10.539447: Current learning rate: 0.00435 +2024-11-22 13:25:30.125188: train_loss -0.7968 +2024-11-22 13:25:30.146795: val_loss -0.7969 +2024-11-22 13:25:30.146940: Pseudo dice [0.8583] +2024-11-22 13:25:30.147028: Epoch time: 19.59 s +2024-11-22 13:25:31.200260: +2024-11-22 13:25:31.201925: Epoch 4831 +2024-11-22 13:25:31.202049: Current learning rate: 0.00435 +2024-11-22 13:25:50.789474: train_loss -0.7931 +2024-11-22 13:25:50.797582: val_loss -0.7732 +2024-11-22 13:25:50.797724: Pseudo dice [0.8606] +2024-11-22 13:25:50.797822: Epoch time: 19.59 s +2024-11-22 13:25:51.704506: +2024-11-22 13:25:51.704926: Epoch 4832 +2024-11-22 13:25:51.705040: Current learning rate: 0.00434 +2024-11-22 13:26:10.831880: train_loss -0.7942 +2024-11-22 13:26:10.838705: val_loss -0.745 +2024-11-22 13:26:10.838840: Pseudo dice [0.8518] +2024-11-22 13:26:10.838942: Epoch time: 19.13 s +2024-11-22 13:26:11.849944: +2024-11-22 13:26:11.850369: Epoch 4833 +2024-11-22 13:26:11.850497: Current learning rate: 0.00434 +2024-11-22 13:26:31.400520: train_loss -0.7944 +2024-11-22 13:26:31.413990: val_loss -0.7809 +2024-11-22 13:26:31.414149: Pseudo dice [0.8576] +2024-11-22 13:26:31.414237: Epoch time: 19.55 s +2024-11-22 13:26:32.395621: +2024-11-22 13:26:32.396034: Epoch 4834 +2024-11-22 13:26:32.396160: Current learning rate: 0.00434 +2024-11-22 13:26:52.179368: train_loss -0.7914 +2024-11-22 13:26:52.184931: val_loss -0.7602 +2024-11-22 13:26:52.185046: Pseudo dice [0.8603] +2024-11-22 13:26:52.185143: Epoch time: 19.78 s +2024-11-22 13:26:53.529500: +2024-11-22 13:26:53.531419: Epoch 4835 +2024-11-22 13:26:53.531540: Current learning rate: 0.00434 +2024-11-22 13:27:12.575855: train_loss -0.7952 +2024-11-22 13:27:12.587980: val_loss -0.786 +2024-11-22 13:27:12.588101: Pseudo dice [0.8558] +2024-11-22 13:27:12.588195: Epoch time: 19.05 s +2024-11-22 13:27:13.471185: +2024-11-22 13:27:13.472186: Epoch 4836 +2024-11-22 13:27:13.472299: Current learning rate: 0.00434 +2024-11-22 13:27:33.051668: train_loss -0.7957 +2024-11-22 13:27:33.067098: val_loss -0.7574 +2024-11-22 13:27:33.067227: Pseudo dice [0.85] +2024-11-22 13:27:33.067319: Epoch time: 19.58 s +2024-11-22 13:27:34.138554: +2024-11-22 13:27:34.139323: Epoch 4837 +2024-11-22 13:27:34.139449: Current learning rate: 0.00434 +2024-11-22 13:27:54.062815: train_loss -0.7905 +2024-11-22 13:27:54.068800: val_loss -0.7675 +2024-11-22 13:27:54.068920: Pseudo dice [0.8619] +2024-11-22 13:27:54.069013: Epoch time: 19.93 s +2024-11-22 13:27:54.981927: +2024-11-22 13:27:54.982476: Epoch 4838 +2024-11-22 13:27:54.982601: Current learning rate: 0.00434 +2024-11-22 13:28:15.165511: train_loss -0.7932 +2024-11-22 13:28:15.171413: val_loss -0.7801 +2024-11-22 13:28:15.171567: Pseudo dice [0.8457] +2024-11-22 13:28:15.171657: Epoch time: 20.18 s +2024-11-22 13:28:16.233626: +2024-11-22 13:28:16.234417: Epoch 4839 +2024-11-22 13:28:16.234535: Current learning rate: 0.00434 +2024-11-22 13:28:35.212769: train_loss -0.8039 +2024-11-22 13:28:35.215907: val_loss -0.7648 +2024-11-22 13:28:35.216022: Pseudo dice [0.8622] +2024-11-22 13:28:35.216125: Epoch time: 18.98 s +2024-11-22 13:28:36.073945: +2024-11-22 13:28:36.075075: Epoch 4840 +2024-11-22 13:28:36.075199: Current learning rate: 0.00433 +2024-11-22 13:28:55.245750: train_loss -0.8013 +2024-11-22 13:28:55.253498: val_loss -0.7772 +2024-11-22 13:28:55.253644: Pseudo dice [0.839] +2024-11-22 13:28:55.253729: Epoch time: 19.17 s +2024-11-22 13:28:56.272952: +2024-11-22 13:28:56.274367: Epoch 4841 +2024-11-22 13:28:56.274498: Current learning rate: 0.00433 +2024-11-22 13:29:15.851699: train_loss -0.7931 +2024-11-22 13:29:15.864787: val_loss -0.7607 +2024-11-22 13:29:15.864916: Pseudo dice [0.8477] +2024-11-22 13:29:15.865004: Epoch time: 19.58 s +2024-11-22 13:29:16.728410: +2024-11-22 13:29:16.729167: Epoch 4842 +2024-11-22 13:29:16.729283: Current learning rate: 0.00433 +2024-11-22 13:29:35.774538: train_loss -0.8022 +2024-11-22 13:29:35.777522: val_loss -0.7655 +2024-11-22 13:29:35.777648: Pseudo dice [0.8417] +2024-11-22 13:29:35.777761: Epoch time: 19.05 s +2024-11-22 13:29:36.640609: +2024-11-22 13:29:36.641471: Epoch 4843 +2024-11-22 13:29:36.641600: Current learning rate: 0.00433 +2024-11-22 13:29:56.851240: train_loss -0.7993 +2024-11-22 13:29:56.856810: val_loss -0.7912 +2024-11-22 13:29:56.856923: Pseudo dice [0.8643] +2024-11-22 13:29:56.857003: Epoch time: 20.21 s +2024-11-22 13:29:57.719681: +2024-11-22 13:29:57.719882: Epoch 4844 +2024-11-22 13:29:57.720011: Current learning rate: 0.00433 +2024-11-22 13:30:17.281174: train_loss -0.8 +2024-11-22 13:30:17.293515: val_loss -0.7763 +2024-11-22 13:30:17.293634: Pseudo dice [0.8548] +2024-11-22 13:30:17.293736: Epoch time: 19.56 s +2024-11-22 13:30:18.220340: +2024-11-22 13:30:18.221070: Epoch 4845 +2024-11-22 13:30:18.221200: Current learning rate: 0.00433 +2024-11-22 13:30:37.230294: train_loss -0.7967 +2024-11-22 13:30:37.236587: val_loss -0.7838 +2024-11-22 13:30:37.236733: Pseudo dice [0.8597] +2024-11-22 13:30:37.236832: Epoch time: 19.01 s +2024-11-22 13:30:38.186800: +2024-11-22 13:30:38.217783: Epoch 4846 +2024-11-22 13:30:38.217978: Current learning rate: 0.00433 +2024-11-22 13:30:57.886465: train_loss -0.7954 +2024-11-22 13:30:57.893529: val_loss -0.7746 +2024-11-22 13:30:57.893670: Pseudo dice [0.8591] +2024-11-22 13:30:57.893761: Epoch time: 19.7 s +2024-11-22 13:30:59.179142: +2024-11-22 13:30:59.180865: Epoch 4847 +2024-11-22 13:30:59.180994: Current learning rate: 0.00433 +2024-11-22 13:31:18.790770: train_loss -0.7993 +2024-11-22 13:31:18.792534: val_loss -0.7892 +2024-11-22 13:31:18.792647: Pseudo dice [0.8535] +2024-11-22 13:31:18.792743: Epoch time: 19.61 s +2024-11-22 13:31:19.672548: +2024-11-22 13:31:19.673745: Epoch 4848 +2024-11-22 13:31:19.673871: Current learning rate: 0.00432 +2024-11-22 13:31:41.028912: train_loss -0.7981 +2024-11-22 13:31:41.036938: val_loss -0.7716 +2024-11-22 13:31:41.037069: Pseudo dice [0.8552] +2024-11-22 13:31:41.037167: Epoch time: 21.36 s +2024-11-22 13:31:41.973105: +2024-11-22 13:31:41.974113: Epoch 4849 +2024-11-22 13:31:41.974227: Current learning rate: 0.00432 +2024-11-22 13:32:01.480812: train_loss -0.7958 +2024-11-22 13:32:01.488726: val_loss -0.7773 +2024-11-22 13:32:01.488862: Pseudo dice [0.8539] +2024-11-22 13:32:01.488955: Epoch time: 19.51 s +2024-11-22 13:32:02.772902: +2024-11-22 13:32:02.774394: Epoch 4850 +2024-11-22 13:32:02.774517: Current learning rate: 0.00432 +2024-11-22 13:32:22.694439: train_loss -0.7931 +2024-11-22 13:32:22.698731: val_loss -0.7611 +2024-11-22 13:32:22.698875: Pseudo dice [0.8398] +2024-11-22 13:32:22.698965: Epoch time: 19.92 s +2024-11-22 13:32:23.850463: +2024-11-22 13:32:23.852020: Epoch 4851 +2024-11-22 13:32:23.852150: Current learning rate: 0.00432 +2024-11-22 13:32:44.511009: train_loss -0.7923 +2024-11-22 13:32:44.513514: val_loss -0.7723 +2024-11-22 13:32:44.513628: Pseudo dice [0.8347] +2024-11-22 13:32:44.513714: Epoch time: 20.66 s +2024-11-22 13:32:45.372879: +2024-11-22 13:32:45.373099: Epoch 4852 +2024-11-22 13:32:45.373228: Current learning rate: 0.00432 +2024-11-22 13:33:05.100417: train_loss -0.7896 +2024-11-22 13:33:05.110406: val_loss -0.7743 +2024-11-22 13:33:05.110535: Pseudo dice [0.8591] +2024-11-22 13:33:05.110616: Epoch time: 19.73 s +2024-11-22 13:33:06.015521: +2024-11-22 13:33:06.015917: Epoch 4853 +2024-11-22 13:33:06.016028: Current learning rate: 0.00432 +2024-11-22 13:33:26.011290: train_loss -0.7853 +2024-11-22 13:33:26.016102: val_loss -0.7801 +2024-11-22 13:33:26.016270: Pseudo dice [0.8593] +2024-11-22 13:33:26.016367: Epoch time: 20.0 s +2024-11-22 13:33:27.008489: +2024-11-22 13:33:27.009980: Epoch 4854 +2024-11-22 13:33:27.010116: Current learning rate: 0.00432 +2024-11-22 13:33:46.788595: train_loss -0.7979 +2024-11-22 13:33:46.791337: val_loss -0.7599 +2024-11-22 13:33:46.792834: Pseudo dice [0.852] +2024-11-22 13:33:46.792935: Epoch time: 19.78 s +2024-11-22 13:33:47.682781: +2024-11-22 13:33:47.683814: Epoch 4855 +2024-11-22 13:33:47.683933: Current learning rate: 0.00432 +2024-11-22 13:34:06.812291: train_loss -0.7982 +2024-11-22 13:34:06.822568: val_loss -0.7848 +2024-11-22 13:34:06.822721: Pseudo dice [0.8528] +2024-11-22 13:34:06.822817: Epoch time: 19.13 s +2024-11-22 13:34:07.709553: +2024-11-22 13:34:07.711041: Epoch 4856 +2024-11-22 13:34:07.711167: Current learning rate: 0.00431 +2024-11-22 13:34:27.412620: train_loss -0.7926 +2024-11-22 13:34:27.416186: val_loss -0.7717 +2024-11-22 13:34:27.416296: Pseudo dice [0.8621] +2024-11-22 13:34:27.416378: Epoch time: 19.7 s +2024-11-22 13:34:28.286194: +2024-11-22 13:34:28.286769: Epoch 4857 +2024-11-22 13:34:28.286915: Current learning rate: 0.00431 +2024-11-22 13:34:47.947125: train_loss -0.7762 +2024-11-22 13:34:47.953190: val_loss -0.7614 +2024-11-22 13:34:47.953370: Pseudo dice [0.8527] +2024-11-22 13:34:47.953502: Epoch time: 19.66 s +2024-11-22 13:34:49.232718: +2024-11-22 13:34:49.234766: Epoch 4858 +2024-11-22 13:34:49.234891: Current learning rate: 0.00431 +2024-11-22 13:35:08.101430: train_loss -0.7952 +2024-11-22 13:35:08.110459: val_loss -0.7976 +2024-11-22 13:35:08.110603: Pseudo dice [0.8618] +2024-11-22 13:35:08.128117: Epoch time: 18.87 s +2024-11-22 13:35:09.141669: +2024-11-22 13:35:09.143683: Epoch 4859 +2024-11-22 13:35:09.143799: Current learning rate: 0.00431 +2024-11-22 13:35:29.746191: train_loss -0.79 +2024-11-22 13:35:29.752881: val_loss -0.785 +2024-11-22 13:35:29.753035: Pseudo dice [0.8662] +2024-11-22 13:35:29.753180: Epoch time: 20.61 s +2024-11-22 13:35:30.857267: +2024-11-22 13:35:30.858184: Epoch 4860 +2024-11-22 13:35:30.858312: Current learning rate: 0.00431 +2024-11-22 13:35:50.337807: train_loss -0.7965 +2024-11-22 13:35:50.343603: val_loss -0.7557 +2024-11-22 13:35:50.343738: Pseudo dice [0.8426] +2024-11-22 13:35:50.343830: Epoch time: 19.48 s +2024-11-22 13:35:51.211189: +2024-11-22 13:35:51.211824: Epoch 4861 +2024-11-22 13:35:51.211944: Current learning rate: 0.00431 +2024-11-22 13:36:10.517219: train_loss -0.7918 +2024-11-22 13:36:10.520591: val_loss -0.7721 +2024-11-22 13:36:10.520707: Pseudo dice [0.8561] +2024-11-22 13:36:10.520813: Epoch time: 19.31 s +2024-11-22 13:36:11.392725: +2024-11-22 13:36:11.393126: Epoch 4862 +2024-11-22 13:36:11.393257: Current learning rate: 0.00431 +2024-11-22 13:36:30.814964: train_loss -0.7977 +2024-11-22 13:36:30.819191: val_loss -0.7798 +2024-11-22 13:36:30.819330: Pseudo dice [0.8552] +2024-11-22 13:36:30.819417: Epoch time: 19.42 s +2024-11-22 13:36:31.680945: +2024-11-22 13:36:31.681867: Epoch 4863 +2024-11-22 13:36:31.681997: Current learning rate: 0.00431 +2024-11-22 13:36:49.691312: train_loss -0.7875 +2024-11-22 13:36:49.699330: val_loss -0.7612 +2024-11-22 13:36:49.699455: Pseudo dice [0.8416] +2024-11-22 13:36:49.699550: Epoch time: 18.01 s +2024-11-22 13:36:50.824827: +2024-11-22 13:36:50.825590: Epoch 4864 +2024-11-22 13:36:50.825706: Current learning rate: 0.0043 +2024-11-22 13:37:10.965047: train_loss -0.7844 +2024-11-22 13:37:10.969101: val_loss -0.7493 +2024-11-22 13:37:10.969259: Pseudo dice [0.8523] +2024-11-22 13:37:10.969382: Epoch time: 20.14 s +2024-11-22 13:37:11.827782: +2024-11-22 13:37:11.829054: Epoch 4865 +2024-11-22 13:37:11.829182: Current learning rate: 0.0043 +2024-11-22 13:37:30.235386: train_loss -0.7979 +2024-11-22 13:37:30.238231: val_loss -0.7903 +2024-11-22 13:37:30.238364: Pseudo dice [0.8543] +2024-11-22 13:37:30.238461: Epoch time: 18.41 s +2024-11-22 13:37:31.221450: +2024-11-22 13:37:31.221667: Epoch 4866 +2024-11-22 13:37:31.221787: Current learning rate: 0.0043 +2024-11-22 13:37:50.433843: train_loss -0.7853 +2024-11-22 13:37:50.436426: val_loss -0.7653 +2024-11-22 13:37:50.436571: Pseudo dice [0.8384] +2024-11-22 13:37:50.436671: Epoch time: 19.21 s +2024-11-22 13:37:51.365639: +2024-11-22 13:37:51.365848: Epoch 4867 +2024-11-22 13:37:51.365963: Current learning rate: 0.0043 +2024-11-22 13:38:10.089223: train_loss -0.7915 +2024-11-22 13:38:10.089717: val_loss -0.7587 +2024-11-22 13:38:10.089809: Pseudo dice [0.8472] +2024-11-22 13:38:10.089885: Epoch time: 18.72 s +2024-11-22 13:38:10.944348: +2024-11-22 13:38:10.944560: Epoch 4868 +2024-11-22 13:38:10.944673: Current learning rate: 0.0043 +2024-11-22 13:38:29.876084: train_loss -0.7966 +2024-11-22 13:38:29.876333: val_loss -0.7543 +2024-11-22 13:38:29.876425: Pseudo dice [0.8458] +2024-11-22 13:38:29.882077: Epoch time: 18.93 s +2024-11-22 13:38:30.754925: +2024-11-22 13:38:30.755132: Epoch 4869 +2024-11-22 13:38:30.755259: Current learning rate: 0.0043 +2024-11-22 13:38:49.217810: train_loss -0.7835 +2024-11-22 13:38:49.222543: val_loss -0.7677 +2024-11-22 13:38:49.222670: Pseudo dice [0.8528] +2024-11-22 13:38:49.222756: Epoch time: 18.46 s +2024-11-22 13:38:50.703659: +2024-11-22 13:38:50.703881: Epoch 4870 +2024-11-22 13:38:50.703997: Current learning rate: 0.0043 +2024-11-22 13:39:10.300345: train_loss -0.7858 +2024-11-22 13:39:10.300844: val_loss -0.7569 +2024-11-22 13:39:10.300927: Pseudo dice [0.8499] +2024-11-22 13:39:10.301014: Epoch time: 19.6 s +2024-11-22 13:39:11.153836: +2024-11-22 13:39:11.154074: Epoch 4871 +2024-11-22 13:39:11.154195: Current learning rate: 0.0043 +2024-11-22 13:39:30.319702: train_loss -0.7915 +2024-11-22 13:39:30.322781: val_loss -0.7724 +2024-11-22 13:39:30.322909: Pseudo dice [0.8635] +2024-11-22 13:39:30.323005: Epoch time: 19.17 s +2024-11-22 13:39:31.277333: +2024-11-22 13:39:31.277547: Epoch 4872 +2024-11-22 13:39:31.277669: Current learning rate: 0.00429 +2024-11-22 13:39:49.701798: train_loss -0.7918 +2024-11-22 13:39:49.702027: val_loss -0.7552 +2024-11-22 13:39:49.702127: Pseudo dice [0.847] +2024-11-22 13:39:49.702203: Epoch time: 18.43 s +2024-11-22 13:39:50.675464: +2024-11-22 13:39:50.675666: Epoch 4873 +2024-11-22 13:39:50.675790: Current learning rate: 0.00429 +2024-11-22 13:40:08.905480: train_loss -0.7861 +2024-11-22 13:40:08.912922: val_loss -0.7804 +2024-11-22 13:40:08.913078: Pseudo dice [0.8393] +2024-11-22 13:40:08.913176: Epoch time: 18.23 s +2024-11-22 13:40:09.775740: +2024-11-22 13:40:09.775930: Epoch 4874 +2024-11-22 13:40:09.776049: Current learning rate: 0.00429 +2024-11-22 13:40:27.491602: train_loss -0.7968 +2024-11-22 13:40:27.496825: val_loss -0.783 +2024-11-22 13:40:27.496953: Pseudo dice [0.8442] +2024-11-22 13:40:27.497042: Epoch time: 17.71 s +2024-11-22 13:40:28.394972: +2024-11-22 13:40:28.396057: Epoch 4875 +2024-11-22 13:40:28.396193: Current learning rate: 0.00429 +2024-11-22 13:40:48.234213: train_loss -0.7902 +2024-11-22 13:40:48.238429: val_loss -0.7867 +2024-11-22 13:40:48.238639: Pseudo dice [0.849] +2024-11-22 13:40:48.238732: Epoch time: 19.84 s +2024-11-22 13:40:49.108264: +2024-11-22 13:40:49.108694: Epoch 4876 +2024-11-22 13:40:49.108826: Current learning rate: 0.00429 +2024-11-22 13:41:07.998213: train_loss -0.7892 +2024-11-22 13:41:08.007123: val_loss -0.7439 +2024-11-22 13:41:08.007257: Pseudo dice [0.8428] +2024-11-22 13:41:08.007348: Epoch time: 18.89 s +2024-11-22 13:41:09.072966: +2024-11-22 13:41:09.073716: Epoch 4877 +2024-11-22 13:41:09.073839: Current learning rate: 0.00429 +2024-11-22 13:41:28.803426: train_loss -0.7973 +2024-11-22 13:41:28.816209: val_loss -0.7839 +2024-11-22 13:41:28.816361: Pseudo dice [0.8619] +2024-11-22 13:41:28.816460: Epoch time: 19.73 s +2024-11-22 13:41:29.748725: +2024-11-22 13:41:29.749332: Epoch 4878 +2024-11-22 13:41:29.749450: Current learning rate: 0.00429 +2024-11-22 13:41:50.013983: train_loss -0.7941 +2024-11-22 13:41:50.023797: val_loss -0.7504 +2024-11-22 13:41:50.023953: Pseudo dice [0.8272] +2024-11-22 13:41:50.024045: Epoch time: 20.27 s +2024-11-22 13:41:51.040483: +2024-11-22 13:41:51.041081: Epoch 4879 +2024-11-22 13:41:51.041207: Current learning rate: 0.00429 +2024-11-22 13:42:11.347244: train_loss -0.7977 +2024-11-22 13:42:11.353766: val_loss -0.7868 +2024-11-22 13:42:11.353866: Pseudo dice [0.8557] +2024-11-22 13:42:11.353959: Epoch time: 20.31 s +2024-11-22 13:42:12.204066: +2024-11-22 13:42:12.205234: Epoch 4880 +2024-11-22 13:42:12.205375: Current learning rate: 0.00429 +2024-11-22 13:42:30.894910: train_loss -0.7973 +2024-11-22 13:42:30.902352: val_loss -0.7601 +2024-11-22 13:42:30.902495: Pseudo dice [0.8494] +2024-11-22 13:42:30.902586: Epoch time: 18.69 s +2024-11-22 13:42:32.307488: +2024-11-22 13:42:32.309568: Epoch 4881 +2024-11-22 13:42:32.309694: Current learning rate: 0.00428 +2024-11-22 13:42:51.724369: train_loss -0.7879 +2024-11-22 13:42:51.727727: val_loss -0.7503 +2024-11-22 13:42:51.727865: Pseudo dice [0.8509] +2024-11-22 13:42:51.727950: Epoch time: 19.42 s +2024-11-22 13:42:52.707267: +2024-11-22 13:42:52.708128: Epoch 4882 +2024-11-22 13:42:52.708249: Current learning rate: 0.00428 +2024-11-22 13:43:12.394260: train_loss -0.7896 +2024-11-22 13:43:12.398540: val_loss -0.7893 +2024-11-22 13:43:12.398660: Pseudo dice [0.8578] +2024-11-22 13:43:12.398746: Epoch time: 19.69 s +2024-11-22 13:43:13.317612: +2024-11-22 13:43:13.319072: Epoch 4883 +2024-11-22 13:43:13.319201: Current learning rate: 0.00428 +2024-11-22 13:43:32.380259: train_loss -0.7932 +2024-11-22 13:43:32.386318: val_loss -0.7989 +2024-11-22 13:43:32.386457: Pseudo dice [0.8528] +2024-11-22 13:43:32.386546: Epoch time: 19.06 s +2024-11-22 13:43:33.309693: +2024-11-22 13:43:33.310367: Epoch 4884 +2024-11-22 13:43:33.310678: Current learning rate: 0.00428 +2024-11-22 13:43:52.570743: train_loss -0.7966 +2024-11-22 13:43:52.576531: val_loss -0.7795 +2024-11-22 13:43:52.576646: Pseudo dice [0.8593] +2024-11-22 13:43:52.576742: Epoch time: 19.26 s +2024-11-22 13:43:53.445735: +2024-11-22 13:43:53.446928: Epoch 4885 +2024-11-22 13:43:53.447071: Current learning rate: 0.00428 +2024-11-22 13:44:12.595347: train_loss -0.7922 +2024-11-22 13:44:12.602571: val_loss -0.7794 +2024-11-22 13:44:12.602709: Pseudo dice [0.8628] +2024-11-22 13:44:12.602797: Epoch time: 19.15 s +2024-11-22 13:44:13.538337: +2024-11-22 13:44:13.539115: Epoch 4886 +2024-11-22 13:44:13.539253: Current learning rate: 0.00428 +2024-11-22 13:44:32.846022: train_loss -0.7925 +2024-11-22 13:44:32.857744: val_loss -0.7843 +2024-11-22 13:44:32.857864: Pseudo dice [0.8593] +2024-11-22 13:44:32.857959: Epoch time: 19.31 s +2024-11-22 13:44:33.996464: +2024-11-22 13:44:33.996672: Epoch 4887 +2024-11-22 13:44:33.996802: Current learning rate: 0.00428 +2024-11-22 13:44:52.463954: train_loss -0.8023 +2024-11-22 13:44:52.470604: val_loss -0.7814 +2024-11-22 13:44:52.470742: Pseudo dice [0.8651] +2024-11-22 13:44:52.470836: Epoch time: 18.47 s +2024-11-22 13:44:53.356562: +2024-11-22 13:44:53.356781: Epoch 4888 +2024-11-22 13:44:53.356906: Current learning rate: 0.00428 +2024-11-22 13:45:11.932554: train_loss -0.7959 +2024-11-22 13:45:11.938497: val_loss -0.7778 +2024-11-22 13:45:11.938613: Pseudo dice [0.8656] +2024-11-22 13:45:11.938710: Epoch time: 18.58 s +2024-11-22 13:45:12.803644: +2024-11-22 13:45:12.803844: Epoch 4889 +2024-11-22 13:45:12.803964: Current learning rate: 0.00427 +2024-11-22 13:45:32.251593: train_loss -0.7968 +2024-11-22 13:45:32.256789: val_loss -0.7482 +2024-11-22 13:45:32.256921: Pseudo dice [0.8439] +2024-11-22 13:45:32.257016: Epoch time: 19.45 s +2024-11-22 13:45:33.175351: +2024-11-22 13:45:33.175572: Epoch 4890 +2024-11-22 13:45:33.175693: Current learning rate: 0.00427 +2024-11-22 13:45:52.600127: train_loss -0.8104 +2024-11-22 13:45:52.605985: val_loss -0.7562 +2024-11-22 13:45:52.606112: Pseudo dice [0.8574] +2024-11-22 13:45:52.606205: Epoch time: 19.43 s +2024-11-22 13:45:53.468461: +2024-11-22 13:45:53.469365: Epoch 4891 +2024-11-22 13:45:53.469488: Current learning rate: 0.00427 +2024-11-22 13:46:12.272719: train_loss -0.8029 +2024-11-22 13:46:12.277931: val_loss -0.7862 +2024-11-22 13:46:12.278053: Pseudo dice [0.8619] +2024-11-22 13:46:12.278157: Epoch time: 18.81 s +2024-11-22 13:46:13.282747: +2024-11-22 13:46:13.283486: Epoch 4892 +2024-11-22 13:46:13.283607: Current learning rate: 0.00427 +2024-11-22 13:46:33.252477: train_loss -0.7903 +2024-11-22 13:46:33.255010: val_loss -0.7612 +2024-11-22 13:46:33.255120: Pseudo dice [0.8495] +2024-11-22 13:46:33.255205: Epoch time: 19.97 s +2024-11-22 13:46:34.507918: +2024-11-22 13:46:34.510196: Epoch 4893 +2024-11-22 13:46:34.510336: Current learning rate: 0.00427 +2024-11-22 13:46:52.925157: train_loss -0.7998 +2024-11-22 13:46:52.931488: val_loss -0.7594 +2024-11-22 13:46:52.931618: Pseudo dice [0.8454] +2024-11-22 13:46:52.931721: Epoch time: 18.42 s +2024-11-22 13:46:53.867429: +2024-11-22 13:46:53.868464: Epoch 4894 +2024-11-22 13:46:53.868599: Current learning rate: 0.00427 +2024-11-22 13:47:13.504389: train_loss -0.7946 +2024-11-22 13:47:13.507137: val_loss -0.7789 +2024-11-22 13:47:13.507234: Pseudo dice [0.8573] +2024-11-22 13:47:13.507316: Epoch time: 19.64 s +2024-11-22 13:47:14.360932: +2024-11-22 13:47:14.362422: Epoch 4895 +2024-11-22 13:47:14.362573: Current learning rate: 0.00427 +2024-11-22 13:47:33.147032: train_loss -0.7961 +2024-11-22 13:47:33.149224: val_loss -0.7718 +2024-11-22 13:47:33.149342: Pseudo dice [0.8461] +2024-11-22 13:47:33.149448: Epoch time: 18.79 s +2024-11-22 13:47:34.010980: +2024-11-22 13:47:34.011579: Epoch 4896 +2024-11-22 13:47:34.011722: Current learning rate: 0.00427 +2024-11-22 13:47:53.046899: train_loss -0.7959 +2024-11-22 13:47:53.048491: val_loss -0.7775 +2024-11-22 13:47:53.048593: Pseudo dice [0.8573] +2024-11-22 13:47:53.048691: Epoch time: 19.04 s +2024-11-22 13:47:53.894191: +2024-11-22 13:47:53.894605: Epoch 4897 +2024-11-22 13:47:53.894741: Current learning rate: 0.00426 +2024-11-22 13:48:13.885597: train_loss -0.7996 +2024-11-22 13:48:13.891312: val_loss -0.7399 +2024-11-22 13:48:13.891431: Pseudo dice [0.8372] +2024-11-22 13:48:13.891523: Epoch time: 19.99 s +2024-11-22 13:48:14.833292: +2024-11-22 13:48:14.834067: Epoch 4898 +2024-11-22 13:48:14.834204: Current learning rate: 0.00426 +2024-11-22 13:48:33.697567: train_loss -0.7944 +2024-11-22 13:48:33.710784: val_loss -0.7921 +2024-11-22 13:48:33.710967: Pseudo dice [0.8664] +2024-11-22 13:48:33.711080: Epoch time: 18.87 s +2024-11-22 13:48:34.683200: +2024-11-22 13:48:34.683668: Epoch 4899 +2024-11-22 13:48:34.683806: Current learning rate: 0.00426 +2024-11-22 13:48:53.980895: train_loss -0.8041 +2024-11-22 13:48:53.994299: val_loss -0.7766 +2024-11-22 13:48:53.994445: Pseudo dice [0.8567] +2024-11-22 13:48:53.994537: Epoch time: 19.3 s +2024-11-22 13:48:55.169157: +2024-11-22 13:48:55.170802: Epoch 4900 +2024-11-22 13:48:55.170917: Current learning rate: 0.00426 +2024-11-22 13:49:13.835180: train_loss -0.7957 +2024-11-22 13:49:13.852365: val_loss -0.7553 +2024-11-22 13:49:13.852522: Pseudo dice [0.8599] +2024-11-22 13:49:13.852621: Epoch time: 18.67 s +2024-11-22 13:49:14.718641: +2024-11-22 13:49:14.719647: Epoch 4901 +2024-11-22 13:49:14.719798: Current learning rate: 0.00426 +2024-11-22 13:49:34.853807: train_loss -0.791 +2024-11-22 13:49:34.862026: val_loss -0.7694 +2024-11-22 13:49:34.862216: Pseudo dice [0.8565] +2024-11-22 13:49:34.862309: Epoch time: 20.14 s +2024-11-22 13:49:36.033335: +2024-11-22 13:49:36.034966: Epoch 4902 +2024-11-22 13:49:36.035125: Current learning rate: 0.00426 +2024-11-22 13:49:55.565735: train_loss -0.7936 +2024-11-22 13:49:55.570644: val_loss -0.8097 +2024-11-22 13:49:55.570775: Pseudo dice [0.8583] +2024-11-22 13:49:55.570863: Epoch time: 19.53 s +2024-11-22 13:49:56.508049: +2024-11-22 13:49:56.510177: Epoch 4903 +2024-11-22 13:49:56.510325: Current learning rate: 0.00426 +2024-11-22 13:50:15.408154: train_loss -0.7959 +2024-11-22 13:50:15.423795: val_loss -0.7604 +2024-11-22 13:50:15.423948: Pseudo dice [0.8507] +2024-11-22 13:50:15.424119: Epoch time: 18.9 s +2024-11-22 13:50:16.967500: +2024-11-22 13:50:16.969024: Epoch 4904 +2024-11-22 13:50:16.969177: Current learning rate: 0.00426 +2024-11-22 13:50:36.402184: train_loss -0.7929 +2024-11-22 13:50:36.438806: val_loss -0.7553 +2024-11-22 13:50:36.438951: Pseudo dice [0.8441] +2024-11-22 13:50:36.439069: Epoch time: 19.44 s +2024-11-22 13:50:37.318552: +2024-11-22 13:50:37.318962: Epoch 4905 +2024-11-22 13:50:37.319175: Current learning rate: 0.00425 +2024-11-22 13:50:57.304143: train_loss -0.8076 +2024-11-22 13:50:57.310985: val_loss -0.7575 +2024-11-22 13:50:57.311108: Pseudo dice [0.8591] +2024-11-22 13:50:57.311195: Epoch time: 19.99 s +2024-11-22 13:50:58.401456: +2024-11-22 13:50:58.402632: Epoch 4906 +2024-11-22 13:50:58.402784: Current learning rate: 0.00425 +2024-11-22 13:51:18.108498: train_loss -0.8047 +2024-11-22 13:51:18.111264: val_loss -0.7923 +2024-11-22 13:51:18.111376: Pseudo dice [0.8538] +2024-11-22 13:51:18.111465: Epoch time: 19.71 s +2024-11-22 13:51:18.987398: +2024-11-22 13:51:18.989074: Epoch 4907 +2024-11-22 13:51:18.989209: Current learning rate: 0.00425 +2024-11-22 13:51:39.133738: train_loss -0.7975 +2024-11-22 13:51:39.144296: val_loss -0.7857 +2024-11-22 13:51:39.144449: Pseudo dice [0.8617] +2024-11-22 13:51:39.144543: Epoch time: 20.15 s +2024-11-22 13:51:40.047832: +2024-11-22 13:51:40.048442: Epoch 4908 +2024-11-22 13:51:40.048581: Current learning rate: 0.00425 +2024-11-22 13:52:00.473274: train_loss -0.8027 +2024-11-22 13:52:00.488956: val_loss -0.7572 +2024-11-22 13:52:00.489103: Pseudo dice [0.8593] +2024-11-22 13:52:00.489200: Epoch time: 20.43 s +2024-11-22 13:52:01.417588: +2024-11-22 13:52:01.417998: Epoch 4909 +2024-11-22 13:52:01.418133: Current learning rate: 0.00425 +2024-11-22 13:52:20.542333: train_loss -0.8023 +2024-11-22 13:52:20.549927: val_loss -0.7699 +2024-11-22 13:52:20.550038: Pseudo dice [0.8584] +2024-11-22 13:52:20.550136: Epoch time: 19.13 s +2024-11-22 13:52:21.545822: +2024-11-22 13:52:21.546530: Epoch 4910 +2024-11-22 13:52:21.546681: Current learning rate: 0.00425 +2024-11-22 13:52:40.803347: train_loss -0.8013 +2024-11-22 13:52:40.807380: val_loss -0.7762 +2024-11-22 13:52:40.807507: Pseudo dice [0.8441] +2024-11-22 13:52:40.807603: Epoch time: 19.26 s +2024-11-22 13:52:41.704428: +2024-11-22 13:52:41.705226: Epoch 4911 +2024-11-22 13:52:41.705372: Current learning rate: 0.00425 +2024-11-22 13:53:01.180384: train_loss -0.7949 +2024-11-22 13:53:01.190037: val_loss -0.7622 +2024-11-22 13:53:01.190177: Pseudo dice [0.8443] +2024-11-22 13:53:01.190276: Epoch time: 19.48 s +2024-11-22 13:53:02.254188: +2024-11-22 13:53:02.254584: Epoch 4912 +2024-11-22 13:53:02.254715: Current learning rate: 0.00425 +2024-11-22 13:53:21.472320: train_loss -0.7924 +2024-11-22 13:53:21.476652: val_loss -0.7741 +2024-11-22 13:53:21.476763: Pseudo dice [0.8584] +2024-11-22 13:53:21.476846: Epoch time: 19.22 s +2024-11-22 13:53:22.336451: +2024-11-22 13:53:22.337521: Epoch 4913 +2024-11-22 13:53:22.337682: Current learning rate: 0.00424 +2024-11-22 13:53:40.757376: train_loss -0.7982 +2024-11-22 13:53:40.788926: val_loss -0.7727 +2024-11-22 13:53:40.789101: Pseudo dice [0.8456] +2024-11-22 13:53:40.789200: Epoch time: 18.42 s +2024-11-22 13:53:41.799103: +2024-11-22 13:53:41.799492: Epoch 4914 +2024-11-22 13:53:41.799624: Current learning rate: 0.00424 +2024-11-22 13:54:02.974578: train_loss -0.8008 +2024-11-22 13:54:02.980189: val_loss -0.7703 +2024-11-22 13:54:02.980308: Pseudo dice [0.8566] +2024-11-22 13:54:02.980397: Epoch time: 21.18 s +2024-11-22 13:54:04.464420: +2024-11-22 13:54:04.465770: Epoch 4915 +2024-11-22 13:54:04.465889: Current learning rate: 0.00424 +2024-11-22 13:54:24.841939: train_loss -0.7967 +2024-11-22 13:54:24.844463: val_loss -0.7872 +2024-11-22 13:54:24.844595: Pseudo dice [0.8487] +2024-11-22 13:54:24.844697: Epoch time: 20.38 s +2024-11-22 13:54:25.883101: +2024-11-22 13:54:25.884622: Epoch 4916 +2024-11-22 13:54:25.884754: Current learning rate: 0.00424 +2024-11-22 13:54:45.078180: train_loss -0.7874 +2024-11-22 13:54:45.085847: val_loss -0.7356 +2024-11-22 13:54:45.085985: Pseudo dice [0.8507] +2024-11-22 13:54:45.086098: Epoch time: 19.2 s +2024-11-22 13:54:45.989032: +2024-11-22 13:54:45.990248: Epoch 4917 +2024-11-22 13:54:45.990370: Current learning rate: 0.00424 +2024-11-22 13:55:05.208978: train_loss -0.7878 +2024-11-22 13:55:05.217844: val_loss -0.7874 +2024-11-22 13:55:05.218012: Pseudo dice [0.8505] +2024-11-22 13:55:05.218112: Epoch time: 19.22 s +2024-11-22 13:55:06.347357: +2024-11-22 13:55:06.348404: Epoch 4918 +2024-11-22 13:55:06.348521: Current learning rate: 0.00424 +2024-11-22 13:55:26.636398: train_loss -0.7935 +2024-11-22 13:55:26.643703: val_loss -0.7757 +2024-11-22 13:55:26.643832: Pseudo dice [0.8588] +2024-11-22 13:55:26.643931: Epoch time: 20.29 s +2024-11-22 13:55:27.622628: +2024-11-22 13:55:27.623801: Epoch 4919 +2024-11-22 13:55:27.623940: Current learning rate: 0.00424 +2024-11-22 13:55:46.624588: train_loss -0.8063 +2024-11-22 13:55:46.627858: val_loss -0.7777 +2024-11-22 13:55:46.627974: Pseudo dice [0.8633] +2024-11-22 13:55:46.628067: Epoch time: 19.0 s +2024-11-22 13:55:47.614723: +2024-11-22 13:55:47.615175: Epoch 4920 +2024-11-22 13:55:47.615291: Current learning rate: 0.00424 +2024-11-22 13:56:06.099376: train_loss -0.8058 +2024-11-22 13:56:06.109057: val_loss -0.7728 +2024-11-22 13:56:06.109213: Pseudo dice [0.8514] +2024-11-22 13:56:06.109316: Epoch time: 18.49 s +2024-11-22 13:56:07.182614: +2024-11-22 13:56:07.183022: Epoch 4921 +2024-11-22 13:56:07.183155: Current learning rate: 0.00423 +2024-11-22 13:56:25.590906: train_loss -0.7965 +2024-11-22 13:56:25.595680: val_loss -0.7604 +2024-11-22 13:56:25.595813: Pseudo dice [0.8434] +2024-11-22 13:56:25.595906: Epoch time: 18.41 s +2024-11-22 13:56:26.522988: +2024-11-22 13:56:26.523198: Epoch 4922 +2024-11-22 13:56:26.523314: Current learning rate: 0.00423 +2024-11-22 13:56:46.307672: train_loss -0.7963 +2024-11-22 13:56:46.314425: val_loss -0.7555 +2024-11-22 13:56:46.314592: Pseudo dice [0.8589] +2024-11-22 13:56:46.314697: Epoch time: 19.79 s +2024-11-22 13:56:47.189451: +2024-11-22 13:56:47.189649: Epoch 4923 +2024-11-22 13:56:47.189767: Current learning rate: 0.00423 +2024-11-22 13:57:07.162260: train_loss -0.789 +2024-11-22 13:57:07.175723: val_loss -0.7922 +2024-11-22 13:57:07.175877: Pseudo dice [0.8518] +2024-11-22 13:57:07.175987: Epoch time: 19.97 s +2024-11-22 13:57:08.231184: +2024-11-22 13:57:08.232978: Epoch 4924 +2024-11-22 13:57:08.233112: Current learning rate: 0.00423 +2024-11-22 13:57:27.571199: train_loss -0.7949 +2024-11-22 13:57:27.578140: val_loss -0.7797 +2024-11-22 13:57:27.578292: Pseudo dice [0.8563] +2024-11-22 13:57:27.578384: Epoch time: 19.34 s +2024-11-22 13:57:28.477252: +2024-11-22 13:57:28.478249: Epoch 4925 +2024-11-22 13:57:28.478369: Current learning rate: 0.00423 +2024-11-22 13:57:48.564975: train_loss -0.7877 +2024-11-22 13:57:48.573020: val_loss -0.7636 +2024-11-22 13:57:48.573170: Pseudo dice [0.8301] +2024-11-22 13:57:48.573279: Epoch time: 20.09 s +2024-11-22 13:57:49.464332: +2024-11-22 13:57:49.465715: Epoch 4926 +2024-11-22 13:57:49.465834: Current learning rate: 0.00423 +2024-11-22 13:58:08.320037: train_loss -0.8028 +2024-11-22 13:58:08.344944: val_loss -0.7903 +2024-11-22 13:58:08.345092: Pseudo dice [0.86] +2024-11-22 13:58:08.345186: Epoch time: 18.86 s +2024-11-22 13:58:09.685594: +2024-11-22 13:58:09.687623: Epoch 4927 +2024-11-22 13:58:09.687767: Current learning rate: 0.00423 +2024-11-22 13:58:28.876917: train_loss -0.7863 +2024-11-22 13:58:28.890485: val_loss -0.7627 +2024-11-22 13:58:28.890621: Pseudo dice [0.8269] +2024-11-22 13:58:28.890711: Epoch time: 19.19 s +2024-11-22 13:58:29.888191: +2024-11-22 13:58:29.888854: Epoch 4928 +2024-11-22 13:58:29.888989: Current learning rate: 0.00423 +2024-11-22 13:58:49.268185: train_loss -0.7951 +2024-11-22 13:58:49.270875: val_loss -0.7916 +2024-11-22 13:58:49.270985: Pseudo dice [0.8642] +2024-11-22 13:58:49.271085: Epoch time: 19.38 s +2024-11-22 13:58:50.312245: +2024-11-22 13:58:50.312659: Epoch 4929 +2024-11-22 13:58:50.312794: Current learning rate: 0.00422 +2024-11-22 13:59:08.633294: train_loss -0.7934 +2024-11-22 13:59:08.638867: val_loss -0.8009 +2024-11-22 13:59:08.638993: Pseudo dice [0.8609] +2024-11-22 13:59:08.639087: Epoch time: 18.32 s +2024-11-22 13:59:09.620020: +2024-11-22 13:59:09.620842: Epoch 4930 +2024-11-22 13:59:09.620986: Current learning rate: 0.00422 +2024-11-22 13:59:28.965813: train_loss -0.7935 +2024-11-22 13:59:28.970297: val_loss -0.7676 +2024-11-22 13:59:28.970424: Pseudo dice [0.8534] +2024-11-22 13:59:28.970504: Epoch time: 19.35 s +2024-11-22 13:59:29.830239: +2024-11-22 13:59:29.831157: Epoch 4931 +2024-11-22 13:59:29.831307: Current learning rate: 0.00422 +2024-11-22 13:59:49.381364: train_loss -0.7829 +2024-11-22 13:59:49.384027: val_loss -0.7704 +2024-11-22 13:59:49.384182: Pseudo dice [0.8569] +2024-11-22 13:59:49.384341: Epoch time: 19.55 s +2024-11-22 13:59:50.443204: +2024-11-22 13:59:50.444507: Epoch 4932 +2024-11-22 13:59:50.444659: Current learning rate: 0.00422 +2024-11-22 14:00:10.569106: train_loss -0.7751 +2024-11-22 14:00:10.589189: val_loss -0.7556 +2024-11-22 14:00:10.589355: Pseudo dice [0.8441] +2024-11-22 14:00:10.589442: Epoch time: 20.13 s +2024-11-22 14:00:11.503989: +2024-11-22 14:00:11.504383: Epoch 4933 +2024-11-22 14:00:11.504514: Current learning rate: 0.00422 +2024-11-22 14:00:30.946802: train_loss -0.7695 +2024-11-22 14:00:30.948811: val_loss -0.7665 +2024-11-22 14:00:30.948910: Pseudo dice [0.8463] +2024-11-22 14:00:30.949072: Epoch time: 19.44 s +2024-11-22 14:00:31.810396: +2024-11-22 14:00:31.811355: Epoch 4934 +2024-11-22 14:00:31.811500: Current learning rate: 0.00422 +2024-11-22 14:00:51.509418: train_loss -0.7744 +2024-11-22 14:00:51.513726: val_loss -0.7722 +2024-11-22 14:00:51.513868: Pseudo dice [0.8552] +2024-11-22 14:00:51.513993: Epoch time: 19.7 s +2024-11-22 14:00:52.445597: +2024-11-22 14:00:52.446933: Epoch 4935 +2024-11-22 14:00:52.447078: Current learning rate: 0.00422 +2024-11-22 14:01:11.318944: train_loss -0.79 +2024-11-22 14:01:11.325349: val_loss -0.7859 +2024-11-22 14:01:11.325499: Pseudo dice [0.8501] +2024-11-22 14:01:11.325592: Epoch time: 18.87 s +2024-11-22 14:01:12.310941: +2024-11-22 14:01:12.311622: Epoch 4936 +2024-11-22 14:01:12.311761: Current learning rate: 0.00422 +2024-11-22 14:01:32.032730: train_loss -0.7978 +2024-11-22 14:01:32.039285: val_loss -0.7883 +2024-11-22 14:01:32.039506: Pseudo dice [0.8641] +2024-11-22 14:01:32.039595: Epoch time: 19.72 s +2024-11-22 14:01:33.083108: +2024-11-22 14:01:33.085158: Epoch 4937 +2024-11-22 14:01:33.085316: Current learning rate: 0.00421 +2024-11-22 14:01:50.763967: train_loss -0.7971 +2024-11-22 14:01:50.769823: val_loss -0.7651 +2024-11-22 14:01:50.769948: Pseudo dice [0.8555] +2024-11-22 14:01:50.770041: Epoch time: 17.68 s +2024-11-22 14:01:52.082251: +2024-11-22 14:01:52.083218: Epoch 4938 +2024-11-22 14:01:52.083348: Current learning rate: 0.00421 +2024-11-22 14:02:11.455382: train_loss -0.7937 +2024-11-22 14:02:11.457000: val_loss -0.7815 +2024-11-22 14:02:11.457180: Pseudo dice [0.8692] +2024-11-22 14:02:11.457267: Epoch time: 19.37 s +2024-11-22 14:02:12.315448: +2024-11-22 14:02:12.315905: Epoch 4939 +2024-11-22 14:02:12.316029: Current learning rate: 0.00421 +2024-11-22 14:02:30.763047: train_loss -0.7882 +2024-11-22 14:02:30.768485: val_loss -0.7844 +2024-11-22 14:02:30.768624: Pseudo dice [0.8581] +2024-11-22 14:02:30.768735: Epoch time: 18.45 s +2024-11-22 14:02:31.640515: +2024-11-22 14:02:31.640734: Epoch 4940 +2024-11-22 14:02:31.640846: Current learning rate: 0.00421 +2024-11-22 14:02:49.702477: train_loss -0.7912 +2024-11-22 14:02:49.702693: val_loss -0.7848 +2024-11-22 14:02:49.702779: Pseudo dice [0.8536] +2024-11-22 14:02:49.702864: Epoch time: 18.06 s +2024-11-22 14:02:50.555892: +2024-11-22 14:02:50.556115: Epoch 4941 +2024-11-22 14:02:50.556240: Current learning rate: 0.00421 +2024-11-22 14:03:09.307541: train_loss -0.8002 +2024-11-22 14:03:09.308422: val_loss -0.7626 +2024-11-22 14:03:09.308530: Pseudo dice [0.8345] +2024-11-22 14:03:09.308624: Epoch time: 18.75 s +2024-11-22 14:03:10.210232: +2024-11-22 14:03:10.210467: Epoch 4942 +2024-11-22 14:03:10.210591: Current learning rate: 0.00421 +2024-11-22 14:03:28.565221: train_loss -0.7979 +2024-11-22 14:03:28.567981: val_loss -0.7731 +2024-11-22 14:03:28.568111: Pseudo dice [0.8641] +2024-11-22 14:03:28.568202: Epoch time: 18.36 s +2024-11-22 14:03:29.463885: +2024-11-22 14:03:29.464091: Epoch 4943 +2024-11-22 14:03:29.464201: Current learning rate: 0.00421 +2024-11-22 14:03:48.249408: train_loss -0.794 +2024-11-22 14:03:48.251214: val_loss -0.7742 +2024-11-22 14:03:48.251304: Pseudo dice [0.8522] +2024-11-22 14:03:48.251388: Epoch time: 18.79 s +2024-11-22 14:03:49.108021: +2024-11-22 14:03:49.108244: Epoch 4944 +2024-11-22 14:03:49.108369: Current learning rate: 0.00421 +2024-11-22 14:04:07.950603: train_loss -0.7988 +2024-11-22 14:04:07.953921: val_loss -0.7805 +2024-11-22 14:04:07.954048: Pseudo dice [0.8524] +2024-11-22 14:04:07.954142: Epoch time: 18.84 s +2024-11-22 14:04:08.833502: +2024-11-22 14:04:08.833711: Epoch 4945 +2024-11-22 14:04:08.833835: Current learning rate: 0.0042 +2024-11-22 14:04:26.324328: train_loss -0.8005 +2024-11-22 14:04:26.324582: val_loss -0.7928 +2024-11-22 14:04:26.324672: Pseudo dice [0.865] +2024-11-22 14:04:26.324776: Epoch time: 17.49 s +2024-11-22 14:04:27.373189: +2024-11-22 14:04:27.373383: Epoch 4946 +2024-11-22 14:04:27.373507: Current learning rate: 0.0042 +2024-11-22 14:04:46.802902: train_loss -0.7987 +2024-11-22 14:04:46.803426: val_loss -0.79 +2024-11-22 14:04:46.803523: Pseudo dice [0.8586] +2024-11-22 14:04:46.803607: Epoch time: 19.43 s +2024-11-22 14:04:47.667419: +2024-11-22 14:04:47.667621: Epoch 4947 +2024-11-22 14:04:47.667735: Current learning rate: 0.0042 +2024-11-22 14:05:05.901568: train_loss -0.8054 +2024-11-22 14:05:05.907235: val_loss -0.7855 +2024-11-22 14:05:05.925733: Pseudo dice [0.8632] +2024-11-22 14:05:05.925887: Epoch time: 18.23 s +2024-11-22 14:05:06.812973: +2024-11-22 14:05:06.813160: Epoch 4948 +2024-11-22 14:05:06.813281: Current learning rate: 0.0042 +2024-11-22 14:05:26.087957: train_loss -0.7906 +2024-11-22 14:05:26.091408: val_loss -0.7643 +2024-11-22 14:05:26.091533: Pseudo dice [0.8556] +2024-11-22 14:05:26.091630: Epoch time: 19.28 s +2024-11-22 14:05:26.955334: +2024-11-22 14:05:26.955725: Epoch 4949 +2024-11-22 14:05:26.955843: Current learning rate: 0.0042 +2024-11-22 14:05:45.050327: train_loss -0.7991 +2024-11-22 14:05:45.055666: val_loss -0.7664 +2024-11-22 14:05:45.055805: Pseudo dice [0.8493] +2024-11-22 14:05:45.055900: Epoch time: 18.1 s +2024-11-22 14:05:46.599431: +2024-11-22 14:05:46.600978: Epoch 4950 +2024-11-22 14:05:46.601133: Current learning rate: 0.0042 +2024-11-22 14:06:06.515660: train_loss -0.8068 +2024-11-22 14:06:06.518281: val_loss -0.7775 +2024-11-22 14:06:06.518439: Pseudo dice [0.8592] +2024-11-22 14:06:06.518534: Epoch time: 19.92 s +2024-11-22 14:06:07.380620: +2024-11-22 14:06:07.381389: Epoch 4951 +2024-11-22 14:06:07.381527: Current learning rate: 0.0042 +2024-11-22 14:06:26.898141: train_loss -0.7975 +2024-11-22 14:06:26.901413: val_loss -0.7653 +2024-11-22 14:06:26.901514: Pseudo dice [0.8516] +2024-11-22 14:06:26.901597: Epoch time: 19.52 s +2024-11-22 14:06:27.764518: +2024-11-22 14:06:27.765392: Epoch 4952 +2024-11-22 14:06:27.765529: Current learning rate: 0.0042 +2024-11-22 14:06:47.149905: train_loss -0.7987 +2024-11-22 14:06:47.157716: val_loss -0.7822 +2024-11-22 14:06:47.157862: Pseudo dice [0.8655] +2024-11-22 14:06:47.157959: Epoch time: 19.39 s +2024-11-22 14:06:48.085088: +2024-11-22 14:06:48.086277: Epoch 4953 +2024-11-22 14:06:48.086412: Current learning rate: 0.00419 +2024-11-22 14:07:07.450372: train_loss -0.7934 +2024-11-22 14:07:07.458842: val_loss -0.7713 +2024-11-22 14:07:07.466189: Pseudo dice [0.8592] +2024-11-22 14:07:07.466322: Epoch time: 19.37 s +2024-11-22 14:07:08.366279: +2024-11-22 14:07:08.367314: Epoch 4954 +2024-11-22 14:07:08.367454: Current learning rate: 0.00419 +2024-11-22 14:07:27.744875: train_loss -0.7814 +2024-11-22 14:07:27.759928: val_loss -0.777 +2024-11-22 14:07:27.760074: Pseudo dice [0.8607] +2024-11-22 14:07:27.760166: Epoch time: 19.38 s +2024-11-22 14:07:28.703934: +2024-11-22 14:07:28.704364: Epoch 4955 +2024-11-22 14:07:28.704508: Current learning rate: 0.00419 +2024-11-22 14:07:47.893075: train_loss -0.7976 +2024-11-22 14:07:47.906456: val_loss -0.7936 +2024-11-22 14:07:47.906604: Pseudo dice [0.8661] +2024-11-22 14:07:47.906697: Epoch time: 19.19 s +2024-11-22 14:07:47.906766: Yayy! New best EMA pseudo Dice: 0.8579 +2024-11-22 14:07:49.412521: +2024-11-22 14:07:49.413765: Epoch 4956 +2024-11-22 14:07:49.413918: Current learning rate: 0.00419 +2024-11-22 14:08:09.299769: train_loss -0.7951 +2024-11-22 14:08:09.305909: val_loss -0.783 +2024-11-22 14:08:09.306026: Pseudo dice [0.8562] +2024-11-22 14:08:09.306950: Epoch time: 19.89 s +2024-11-22 14:08:10.284237: +2024-11-22 14:08:10.284898: Epoch 4957 +2024-11-22 14:08:10.285069: Current learning rate: 0.00419 +2024-11-22 14:08:28.855709: train_loss -0.7957 +2024-11-22 14:08:28.876148: val_loss -0.7536 +2024-11-22 14:08:28.876323: Pseudo dice [0.8569] +2024-11-22 14:08:28.876425: Epoch time: 18.57 s +2024-11-22 14:08:29.759759: +2024-11-22 14:08:29.760159: Epoch 4958 +2024-11-22 14:08:29.760295: Current learning rate: 0.00419 +2024-11-22 14:08:49.283468: train_loss -0.8039 +2024-11-22 14:08:49.292067: val_loss -0.7717 +2024-11-22 14:08:49.292215: Pseudo dice [0.8559] +2024-11-22 14:08:49.292301: Epoch time: 19.52 s +2024-11-22 14:08:50.176216: +2024-11-22 14:08:50.177686: Epoch 4959 +2024-11-22 14:08:50.177826: Current learning rate: 0.00419 +2024-11-22 14:09:09.878396: train_loss -0.7987 +2024-11-22 14:09:09.905241: val_loss -0.7831 +2024-11-22 14:09:09.905375: Pseudo dice [0.8608] +2024-11-22 14:09:09.905476: Epoch time: 19.7 s +2024-11-22 14:09:11.248013: +2024-11-22 14:09:11.249725: Epoch 4960 +2024-11-22 14:09:11.250070: Current learning rate: 0.00419 +2024-11-22 14:09:31.594082: train_loss -0.7983 +2024-11-22 14:09:31.598928: val_loss -0.7857 +2024-11-22 14:09:31.599066: Pseudo dice [0.8608] +2024-11-22 14:09:31.599171: Epoch time: 20.35 s +2024-11-22 14:09:31.599251: Yayy! New best EMA pseudo Dice: 0.8581 +2024-11-22 14:09:32.843260: +2024-11-22 14:09:32.843949: Epoch 4961 +2024-11-22 14:09:32.844105: Current learning rate: 0.00418 +2024-11-22 14:09:51.929173: train_loss -0.8019 +2024-11-22 14:09:51.932906: val_loss -0.7748 +2024-11-22 14:09:51.933057: Pseudo dice [0.8458] +2024-11-22 14:09:51.933150: Epoch time: 19.09 s +2024-11-22 14:09:52.791332: +2024-11-22 14:09:52.791741: Epoch 4962 +2024-11-22 14:09:52.791872: Current learning rate: 0.00418 +2024-11-22 14:10:11.738540: train_loss -0.7951 +2024-11-22 14:10:11.746435: val_loss -0.79 +2024-11-22 14:10:11.746573: Pseudo dice [0.8593] +2024-11-22 14:10:11.746673: Epoch time: 18.95 s +2024-11-22 14:10:12.656981: +2024-11-22 14:10:12.657666: Epoch 4963 +2024-11-22 14:10:12.657831: Current learning rate: 0.00418 +2024-11-22 14:10:31.856246: train_loss -0.7975 +2024-11-22 14:10:31.864631: val_loss -0.789 +2024-11-22 14:10:31.864758: Pseudo dice [0.8545] +2024-11-22 14:10:31.864857: Epoch time: 19.2 s +2024-11-22 14:10:32.999461: +2024-11-22 14:10:32.999942: Epoch 4964 +2024-11-22 14:10:33.000090: Current learning rate: 0.00418 +2024-11-22 14:10:51.620787: train_loss -0.8023 +2024-11-22 14:10:51.624883: val_loss -0.7757 +2024-11-22 14:10:51.625012: Pseudo dice [0.8659] +2024-11-22 14:10:51.625142: Epoch time: 18.62 s +2024-11-22 14:10:52.492354: +2024-11-22 14:10:52.493389: Epoch 4965 +2024-11-22 14:10:52.493537: Current learning rate: 0.00418 +2024-11-22 14:11:11.807371: train_loss -0.7912 +2024-11-22 14:11:11.815871: val_loss -0.7688 +2024-11-22 14:11:11.816012: Pseudo dice [0.8538] +2024-11-22 14:11:11.816113: Epoch time: 19.32 s +2024-11-22 14:11:12.682226: +2024-11-22 14:11:12.683621: Epoch 4966 +2024-11-22 14:11:12.683767: Current learning rate: 0.00418 +2024-11-22 14:11:32.637933: train_loss -0.7984 +2024-11-22 14:11:32.649444: val_loss -0.772 +2024-11-22 14:11:32.649586: Pseudo dice [0.8592] +2024-11-22 14:11:32.649686: Epoch time: 19.96 s +2024-11-22 14:11:33.539017: +2024-11-22 14:11:33.540018: Epoch 4967 +2024-11-22 14:11:33.540168: Current learning rate: 0.00418 +2024-11-22 14:11:52.352211: train_loss -0.7883 +2024-11-22 14:11:52.367018: val_loss -0.7577 +2024-11-22 14:11:52.367162: Pseudo dice [0.8376] +2024-11-22 14:11:52.367254: Epoch time: 18.81 s +2024-11-22 14:11:53.391860: +2024-11-22 14:11:53.393874: Epoch 4968 +2024-11-22 14:11:53.394019: Current learning rate: 0.00418 +2024-11-22 14:12:13.248241: train_loss -0.7987 +2024-11-22 14:12:13.255581: val_loss -0.7671 +2024-11-22 14:12:13.255749: Pseudo dice [0.8548] +2024-11-22 14:12:13.255844: Epoch time: 19.86 s +2024-11-22 14:12:14.119425: +2024-11-22 14:12:14.121460: Epoch 4969 +2024-11-22 14:12:14.121596: Current learning rate: 0.00417 +2024-11-22 14:12:33.721561: train_loss -0.8018 +2024-11-22 14:12:33.727763: val_loss -0.7524 +2024-11-22 14:12:33.727908: Pseudo dice [0.8409] +2024-11-22 14:12:33.728005: Epoch time: 19.6 s +2024-11-22 14:12:34.607357: +2024-11-22 14:12:34.608116: Epoch 4970 +2024-11-22 14:12:34.608274: Current learning rate: 0.00417 +2024-11-22 14:12:53.112037: train_loss -0.7905 +2024-11-22 14:12:53.124045: val_loss -0.7825 +2024-11-22 14:12:53.124192: Pseudo dice [0.8501] +2024-11-22 14:12:53.124498: Epoch time: 18.51 s +2024-11-22 14:12:54.116727: +2024-11-22 14:12:54.117214: Epoch 4971 +2024-11-22 14:12:54.117343: Current learning rate: 0.00417 +2024-11-22 14:13:13.002927: train_loss -0.7834 +2024-11-22 14:13:13.024490: val_loss -0.7598 +2024-11-22 14:13:13.024637: Pseudo dice [0.8393] +2024-11-22 14:13:13.024743: Epoch time: 18.89 s +2024-11-22 14:13:14.259600: +2024-11-22 14:13:14.260322: Epoch 4972 +2024-11-22 14:13:14.260460: Current learning rate: 0.00417 +2024-11-22 14:13:34.039650: train_loss -0.7836 +2024-11-22 14:13:34.042036: val_loss -0.7598 +2024-11-22 14:13:34.042372: Pseudo dice [0.8461] +2024-11-22 14:13:34.042504: Epoch time: 19.78 s +2024-11-22 14:13:34.929444: +2024-11-22 14:13:34.929857: Epoch 4973 +2024-11-22 14:13:34.929985: Current learning rate: 0.00417 +2024-11-22 14:13:54.624392: train_loss -0.8002 +2024-11-22 14:13:54.631380: val_loss -0.7476 +2024-11-22 14:13:54.631528: Pseudo dice [0.845] +2024-11-22 14:13:54.631625: Epoch time: 19.7 s +2024-11-22 14:13:55.494913: +2024-11-22 14:13:55.495536: Epoch 4974 +2024-11-22 14:13:55.495678: Current learning rate: 0.00417 +2024-11-22 14:14:15.687153: train_loss -0.7937 +2024-11-22 14:14:15.692727: val_loss -0.7615 +2024-11-22 14:14:15.692838: Pseudo dice [0.8552] +2024-11-22 14:14:15.692917: Epoch time: 20.19 s +2024-11-22 14:14:16.570648: +2024-11-22 14:14:16.572257: Epoch 4975 +2024-11-22 14:14:16.572394: Current learning rate: 0.00417 +2024-11-22 14:14:36.100433: train_loss -0.8041 +2024-11-22 14:14:36.103390: val_loss -0.7717 +2024-11-22 14:14:36.103504: Pseudo dice [0.849] +2024-11-22 14:14:36.103595: Epoch time: 19.53 s +2024-11-22 14:14:36.978198: +2024-11-22 14:14:36.978648: Epoch 4976 +2024-11-22 14:14:36.978829: Current learning rate: 0.00417 +2024-11-22 14:14:55.725383: train_loss -0.7919 +2024-11-22 14:14:55.730548: val_loss -0.7705 +2024-11-22 14:14:55.730672: Pseudo dice [0.8496] +2024-11-22 14:14:55.730761: Epoch time: 18.75 s +2024-11-22 14:14:56.615628: +2024-11-22 14:14:56.616319: Epoch 4977 +2024-11-22 14:14:56.616475: Current learning rate: 0.00416 +2024-11-22 14:15:15.377711: train_loss -0.794 +2024-11-22 14:15:15.383366: val_loss -0.7762 +2024-11-22 14:15:15.383490: Pseudo dice [0.8581] +2024-11-22 14:15:15.383581: Epoch time: 18.76 s +2024-11-22 14:15:16.450152: +2024-11-22 14:15:16.450569: Epoch 4978 +2024-11-22 14:15:16.450701: Current learning rate: 0.00416 +2024-11-22 14:15:34.678159: train_loss -0.7983 +2024-11-22 14:15:34.683929: val_loss -0.7861 +2024-11-22 14:15:34.684049: Pseudo dice [0.8671] +2024-11-22 14:15:34.684182: Epoch time: 18.23 s +2024-11-22 14:15:35.650881: +2024-11-22 14:15:35.651531: Epoch 4979 +2024-11-22 14:15:35.651669: Current learning rate: 0.00416 +2024-11-22 14:15:54.852761: train_loss -0.7989 +2024-11-22 14:15:54.865828: val_loss -0.7815 +2024-11-22 14:15:54.865983: Pseudo dice [0.8426] +2024-11-22 14:15:54.866090: Epoch time: 19.2 s +2024-11-22 14:15:56.029401: +2024-11-22 14:15:56.030066: Epoch 4980 +2024-11-22 14:15:56.030219: Current learning rate: 0.00416 +2024-11-22 14:16:15.846980: train_loss -0.7952 +2024-11-22 14:16:15.853284: val_loss -0.7589 +2024-11-22 14:16:15.853481: Pseudo dice [0.8357] +2024-11-22 14:16:15.853564: Epoch time: 19.82 s +2024-11-22 14:16:16.699890: +2024-11-22 14:16:16.700291: Epoch 4981 +2024-11-22 14:16:16.700438: Current learning rate: 0.00416 +2024-11-22 14:16:36.432610: train_loss -0.7982 +2024-11-22 14:16:36.445378: val_loss -0.7476 +2024-11-22 14:16:36.445532: Pseudo dice [0.8543] +2024-11-22 14:16:36.447204: Epoch time: 19.73 s +2024-11-22 14:16:37.355021: +2024-11-22 14:16:37.355691: Epoch 4982 +2024-11-22 14:16:37.355841: Current learning rate: 0.00416 +2024-11-22 14:16:56.032930: train_loss -0.799 +2024-11-22 14:16:56.039245: val_loss -0.7639 +2024-11-22 14:16:56.039438: Pseudo dice [0.8354] +2024-11-22 14:16:56.039535: Epoch time: 18.68 s +2024-11-22 14:16:56.937459: +2024-11-22 14:16:56.938665: Epoch 4983 +2024-11-22 14:16:56.938783: Current learning rate: 0.00416 +2024-11-22 14:17:17.443863: train_loss -0.7914 +2024-11-22 14:17:17.451840: val_loss -0.787 +2024-11-22 14:17:17.451976: Pseudo dice [0.8577] +2024-11-22 14:17:17.452071: Epoch time: 20.51 s +2024-11-22 14:17:18.370197: +2024-11-22 14:17:18.370406: Epoch 4984 +2024-11-22 14:17:18.370521: Current learning rate: 0.00416 +2024-11-22 14:17:37.388485: train_loss -0.7865 +2024-11-22 14:17:37.393785: val_loss -0.7782 +2024-11-22 14:17:37.393925: Pseudo dice [0.8524] +2024-11-22 14:17:37.394017: Epoch time: 19.02 s +2024-11-22 14:17:38.279489: +2024-11-22 14:17:38.281462: Epoch 4985 +2024-11-22 14:17:38.281578: Current learning rate: 0.00416 +2024-11-22 14:17:56.938065: train_loss -0.793 +2024-11-22 14:17:56.940584: val_loss -0.7469 +2024-11-22 14:17:56.940705: Pseudo dice [0.8485] +2024-11-22 14:17:56.940793: Epoch time: 18.66 s +2024-11-22 14:17:57.815264: +2024-11-22 14:17:57.815884: Epoch 4986 +2024-11-22 14:17:57.815996: Current learning rate: 0.00415 +2024-11-22 14:18:16.107239: train_loss -0.7933 +2024-11-22 14:18:16.121144: val_loss -0.7777 +2024-11-22 14:18:16.121288: Pseudo dice [0.8475] +2024-11-22 14:18:16.121461: Epoch time: 18.29 s +2024-11-22 14:18:17.069071: +2024-11-22 14:18:17.069673: Epoch 4987 +2024-11-22 14:18:17.069792: Current learning rate: 0.00415 +2024-11-22 14:18:36.193699: train_loss -0.7833 +2024-11-22 14:18:36.202810: val_loss -0.7913 +2024-11-22 14:18:36.202952: Pseudo dice [0.8548] +2024-11-22 14:18:36.203144: Epoch time: 19.13 s +2024-11-22 14:18:37.262021: +2024-11-22 14:18:37.263495: Epoch 4988 +2024-11-22 14:18:37.263619: Current learning rate: 0.00415 +2024-11-22 14:18:56.847613: train_loss -0.7927 +2024-11-22 14:18:56.854481: val_loss -0.779 +2024-11-22 14:18:56.854671: Pseudo dice [0.8605] +2024-11-22 14:18:56.854767: Epoch time: 19.59 s +2024-11-22 14:18:57.749934: +2024-11-22 14:18:57.751039: Epoch 4989 +2024-11-22 14:18:57.751165: Current learning rate: 0.00415 +2024-11-22 14:19:15.967129: train_loss -0.7925 +2024-11-22 14:19:15.976638: val_loss -0.7735 +2024-11-22 14:19:15.976772: Pseudo dice [0.861] +2024-11-22 14:19:15.976876: Epoch time: 18.22 s +2024-11-22 14:19:17.212228: +2024-11-22 14:19:17.213573: Epoch 4990 +2024-11-22 14:19:17.213695: Current learning rate: 0.00415 +2024-11-22 14:19:36.051390: train_loss -0.7839 +2024-11-22 14:19:36.060846: val_loss -0.7711 +2024-11-22 14:19:36.060994: Pseudo dice [0.8526] +2024-11-22 14:19:36.061099: Epoch time: 18.84 s +2024-11-22 14:19:37.031290: +2024-11-22 14:19:37.032055: Epoch 4991 +2024-11-22 14:19:37.032187: Current learning rate: 0.00415 +2024-11-22 14:19:57.058843: train_loss -0.7936 +2024-11-22 14:19:57.071600: val_loss -0.7502 +2024-11-22 14:19:57.071726: Pseudo dice [0.8392] +2024-11-22 14:19:57.071823: Epoch time: 20.03 s +2024-11-22 14:19:58.041753: +2024-11-22 14:19:58.042966: Epoch 4992 +2024-11-22 14:19:58.043092: Current learning rate: 0.00415 +2024-11-22 14:20:17.824627: train_loss -0.7827 +2024-11-22 14:20:17.827729: val_loss -0.7666 +2024-11-22 14:20:17.827832: Pseudo dice [0.8473] +2024-11-22 14:20:17.827914: Epoch time: 19.78 s +2024-11-22 14:20:18.694846: +2024-11-22 14:20:18.695318: Epoch 4993 +2024-11-22 14:20:18.695472: Current learning rate: 0.00415 +2024-11-22 14:20:38.214407: train_loss -0.78 +2024-11-22 14:20:38.220017: val_loss -0.7734 +2024-11-22 14:20:38.220161: Pseudo dice [0.8592] +2024-11-22 14:20:38.220256: Epoch time: 19.52 s +2024-11-22 14:20:39.116353: +2024-11-22 14:20:39.117125: Epoch 4994 +2024-11-22 14:20:39.117242: Current learning rate: 0.00414 +2024-11-22 14:20:58.571748: train_loss -0.7957 +2024-11-22 14:20:58.574910: val_loss -0.7737 +2024-11-22 14:20:58.575012: Pseudo dice [0.8557] +2024-11-22 14:20:58.575137: Epoch time: 19.46 s +2024-11-22 14:20:59.436566: +2024-11-22 14:20:59.437662: Epoch 4995 +2024-11-22 14:20:59.437779: Current learning rate: 0.00414 +2024-11-22 14:21:18.806090: train_loss -0.8003 +2024-11-22 14:21:18.808728: val_loss -0.7771 +2024-11-22 14:21:18.808865: Pseudo dice [0.8562] +2024-11-22 14:21:18.808949: Epoch time: 19.37 s +2024-11-22 14:21:19.815437: +2024-11-22 14:21:19.816055: Epoch 4996 +2024-11-22 14:21:19.816173: Current learning rate: 0.00414 +2024-11-22 14:21:38.566978: train_loss -0.7956 +2024-11-22 14:21:38.575280: val_loss -0.7814 +2024-11-22 14:21:38.575420: Pseudo dice [0.857] +2024-11-22 14:21:38.575604: Epoch time: 18.75 s +2024-11-22 14:21:39.587061: +2024-11-22 14:21:39.587901: Epoch 4997 +2024-11-22 14:21:39.588038: Current learning rate: 0.00414 +2024-11-22 14:22:00.006384: train_loss -0.7952 +2024-11-22 14:22:00.014369: val_loss -0.7718 +2024-11-22 14:22:00.014523: Pseudo dice [0.8594] +2024-11-22 14:22:00.014616: Epoch time: 20.42 s +2024-11-22 14:22:01.120560: +2024-11-22 14:22:01.121995: Epoch 4998 +2024-11-22 14:22:01.122118: Current learning rate: 0.00414 +2024-11-22 14:22:20.293238: train_loss -0.7962 +2024-11-22 14:22:20.313990: val_loss -0.7627 +2024-11-22 14:22:20.314212: Pseudo dice [0.8607] +2024-11-22 14:22:20.314312: Epoch time: 19.17 s +2024-11-22 14:22:21.446341: +2024-11-22 14:22:21.447385: Epoch 4999 +2024-11-22 14:22:21.447520: Current learning rate: 0.00414 +2024-11-22 14:22:39.786969: train_loss -0.7912 +2024-11-22 14:22:39.793710: val_loss -0.7738 +2024-11-22 14:22:39.793826: Pseudo dice [0.854] +2024-11-22 14:22:39.793914: Epoch time: 18.34 s +2024-11-22 14:22:41.056776: +2024-11-22 14:22:41.057807: Epoch 5000 +2024-11-22 14:22:41.057938: Current learning rate: 0.00414 +2024-11-22 14:23:00.624629: train_loss -0.7832 +2024-11-22 14:23:00.631005: val_loss -0.7828 +2024-11-22 14:23:00.631140: Pseudo dice [0.8515] +2024-11-22 14:23:00.631224: Epoch time: 19.57 s +2024-11-22 14:23:01.509676: +2024-11-22 14:23:01.510864: Epoch 5001 +2024-11-22 14:23:01.510995: Current learning rate: 0.00414 +2024-11-22 14:23:19.882436: train_loss -0.7843 +2024-11-22 14:23:19.889509: val_loss -0.7809 +2024-11-22 14:23:19.889649: Pseudo dice [0.8465] +2024-11-22 14:23:19.889743: Epoch time: 18.37 s +2024-11-22 14:23:20.995671: +2024-11-22 14:23:20.998789: Epoch 5002 +2024-11-22 14:23:20.998927: Current learning rate: 0.00413 +2024-11-22 14:23:39.691130: train_loss -0.7875 +2024-11-22 14:23:39.703758: val_loss -0.7596 +2024-11-22 14:23:39.703892: Pseudo dice [0.8502] +2024-11-22 14:23:39.703995: Epoch time: 18.7 s +2024-11-22 14:23:40.713016: +2024-11-22 14:23:40.713488: Epoch 5003 +2024-11-22 14:23:40.713618: Current learning rate: 0.00413 +2024-11-22 14:24:00.136125: train_loss -0.8 +2024-11-22 14:24:00.143114: val_loss -0.7901 +2024-11-22 14:24:00.143262: Pseudo dice [0.8608] +2024-11-22 14:24:00.143364: Epoch time: 19.42 s +2024-11-22 14:24:01.435180: +2024-11-22 14:24:01.436945: Epoch 5004 +2024-11-22 14:24:01.437102: Current learning rate: 0.00413 +2024-11-22 14:24:19.860945: train_loss -0.786 +2024-11-22 14:24:19.879787: val_loss -0.7714 +2024-11-22 14:24:19.879939: Pseudo dice [0.8677] +2024-11-22 14:24:19.880035: Epoch time: 18.43 s +2024-11-22 14:24:20.778041: +2024-11-22 14:24:20.778832: Epoch 5005 +2024-11-22 14:24:20.778971: Current learning rate: 0.00413 +2024-11-22 14:24:40.657681: train_loss -0.794 +2024-11-22 14:24:40.680099: val_loss -0.7713 +2024-11-22 14:24:40.680232: Pseudo dice [0.85] +2024-11-22 14:24:40.680328: Epoch time: 19.88 s +2024-11-22 14:24:41.764906: +2024-11-22 14:24:41.766016: Epoch 5006 +2024-11-22 14:24:41.766166: Current learning rate: 0.00413 +2024-11-22 14:25:01.072370: train_loss -0.7815 +2024-11-22 14:25:01.077374: val_loss -0.7626 +2024-11-22 14:25:01.077485: Pseudo dice [0.832] +2024-11-22 14:25:01.077574: Epoch time: 19.31 s +2024-11-22 14:25:02.125531: +2024-11-22 14:25:02.126653: Epoch 5007 +2024-11-22 14:25:02.126797: Current learning rate: 0.00413 +2024-11-22 14:25:21.269426: train_loss -0.7948 +2024-11-22 14:25:21.288938: val_loss -0.7702 +2024-11-22 14:25:21.289074: Pseudo dice [0.8514] +2024-11-22 14:25:21.289174: Epoch time: 19.14 s +2024-11-22 14:25:22.338766: +2024-11-22 14:25:22.339770: Epoch 5008 +2024-11-22 14:25:22.339916: Current learning rate: 0.00413 +2024-11-22 14:25:41.136118: train_loss -0.7933 +2024-11-22 14:25:41.149905: val_loss -0.7871 +2024-11-22 14:25:41.150054: Pseudo dice [0.8605] +2024-11-22 14:25:41.150289: Epoch time: 18.8 s +2024-11-22 14:25:42.378048: +2024-11-22 14:25:42.380696: Epoch 5009 +2024-11-22 14:25:42.380851: Current learning rate: 0.00413 +2024-11-22 14:26:00.816240: train_loss -0.8007 +2024-11-22 14:26:00.818795: val_loss -0.7615 +2024-11-22 14:26:00.818909: Pseudo dice [0.8612] +2024-11-22 14:26:00.819004: Epoch time: 18.44 s +2024-11-22 14:26:01.681893: +2024-11-22 14:26:01.684026: Epoch 5010 +2024-11-22 14:26:01.684267: Current learning rate: 0.00412 +2024-11-22 14:26:20.536788: train_loss -0.7981 +2024-11-22 14:26:20.539886: val_loss -0.79 +2024-11-22 14:26:20.539988: Pseudo dice [0.8626] +2024-11-22 14:26:20.540255: Epoch time: 18.86 s +2024-11-22 14:26:21.407956: +2024-11-22 14:26:21.409487: Epoch 5011 +2024-11-22 14:26:21.409620: Current learning rate: 0.00412 +2024-11-22 14:26:40.126350: train_loss -0.8068 +2024-11-22 14:26:40.137212: val_loss -0.8065 +2024-11-22 14:26:40.137336: Pseudo dice [0.8681] +2024-11-22 14:26:40.137415: Epoch time: 18.72 s +2024-11-22 14:26:41.013288: +2024-11-22 14:26:41.014336: Epoch 5012 +2024-11-22 14:26:41.014464: Current learning rate: 0.00412 +2024-11-22 14:26:59.738138: train_loss -0.7945 +2024-11-22 14:26:59.749667: val_loss -0.7828 +2024-11-22 14:26:59.749808: Pseudo dice [0.8507] +2024-11-22 14:26:59.749908: Epoch time: 18.73 s +2024-11-22 14:27:00.633324: +2024-11-22 14:27:00.634427: Epoch 5013 +2024-11-22 14:27:00.634578: Current learning rate: 0.00412 +2024-11-22 14:27:20.130688: train_loss -0.7915 +2024-11-22 14:27:20.132977: val_loss -0.7512 +2024-11-22 14:27:20.133128: Pseudo dice [0.8526] +2024-11-22 14:27:20.133230: Epoch time: 19.5 s +2024-11-22 14:27:21.288322: +2024-11-22 14:27:21.288846: Epoch 5014 +2024-11-22 14:27:21.288969: Current learning rate: 0.00412 +2024-11-22 14:27:40.069077: train_loss -0.7803 +2024-11-22 14:27:40.071581: val_loss -0.7616 +2024-11-22 14:27:40.071701: Pseudo dice [0.8417] +2024-11-22 14:27:40.071800: Epoch time: 18.78 s +2024-11-22 14:27:41.135616: +2024-11-22 14:27:41.136953: Epoch 5015 +2024-11-22 14:27:41.137075: Current learning rate: 0.00412 +2024-11-22 14:28:00.477541: train_loss -0.7899 +2024-11-22 14:28:00.481413: val_loss -0.772 +2024-11-22 14:28:00.481518: Pseudo dice [0.8571] +2024-11-22 14:28:00.481603: Epoch time: 19.34 s +2024-11-22 14:28:01.852850: +2024-11-22 14:28:01.853062: Epoch 5016 +2024-11-22 14:28:01.853185: Current learning rate: 0.00412 +2024-11-22 14:28:20.795166: train_loss -0.7817 +2024-11-22 14:28:20.804154: val_loss -0.771 +2024-11-22 14:28:20.804293: Pseudo dice [0.8573] +2024-11-22 14:28:20.804389: Epoch time: 18.94 s +2024-11-22 14:28:21.675362: +2024-11-22 14:28:21.675561: Epoch 5017 +2024-11-22 14:28:21.675678: Current learning rate: 0.00412 +2024-11-22 14:28:40.494536: train_loss -0.7862 +2024-11-22 14:28:40.494784: val_loss -0.762 +2024-11-22 14:28:40.494868: Pseudo dice [0.8529] +2024-11-22 14:28:40.494962: Epoch time: 18.82 s +2024-11-22 14:28:41.417439: +2024-11-22 14:28:41.417667: Epoch 5018 +2024-11-22 14:28:41.417791: Current learning rate: 0.00411 +2024-11-22 14:28:59.923358: train_loss -0.7982 +2024-11-22 14:28:59.923854: val_loss -0.7595 +2024-11-22 14:28:59.923952: Pseudo dice [0.8429] +2024-11-22 14:28:59.924042: Epoch time: 18.51 s +2024-11-22 14:29:00.780871: +2024-11-22 14:29:00.781094: Epoch 5019 +2024-11-22 14:29:00.781213: Current learning rate: 0.00411 +2024-11-22 14:29:19.769682: train_loss -0.7988 +2024-11-22 14:29:19.770765: val_loss -0.7804 +2024-11-22 14:29:19.770875: Pseudo dice [0.8529] +2024-11-22 14:29:19.770966: Epoch time: 18.99 s +2024-11-22 14:29:20.635671: +2024-11-22 14:29:20.635906: Epoch 5020 +2024-11-22 14:29:20.636031: Current learning rate: 0.00411 +2024-11-22 14:29:40.832685: train_loss -0.7928 +2024-11-22 14:29:40.833212: val_loss -0.7671 +2024-11-22 14:29:40.833297: Pseudo dice [0.8462] +2024-11-22 14:29:40.833374: Epoch time: 20.2 s +2024-11-22 14:29:41.688253: +2024-11-22 14:29:41.688483: Epoch 5021 +2024-11-22 14:29:41.688597: Current learning rate: 0.00411 +2024-11-22 14:30:01.130820: train_loss -0.7942 +2024-11-22 14:30:01.131036: val_loss -0.7676 +2024-11-22 14:30:01.131137: Pseudo dice [0.8628] +2024-11-22 14:30:01.131233: Epoch time: 19.44 s +2024-11-22 14:30:01.992519: +2024-11-22 14:30:01.992706: Epoch 5022 +2024-11-22 14:30:01.992817: Current learning rate: 0.00411 +2024-11-22 14:30:19.720926: train_loss -0.7942 +2024-11-22 14:30:19.721491: val_loss -0.7784 +2024-11-22 14:30:19.721584: Pseudo dice [0.8504] +2024-11-22 14:30:19.721674: Epoch time: 17.73 s +2024-11-22 14:30:20.583904: +2024-11-22 14:30:20.584104: Epoch 5023 +2024-11-22 14:30:20.584221: Current learning rate: 0.00411 +2024-11-22 14:30:39.170830: train_loss -0.7884 +2024-11-22 14:30:39.190002: val_loss -0.7724 +2024-11-22 14:30:39.190121: Pseudo dice [0.8512] +2024-11-22 14:30:39.190213: Epoch time: 18.59 s +2024-11-22 14:30:40.045583: +2024-11-22 14:30:40.045778: Epoch 5024 +2024-11-22 14:30:40.045900: Current learning rate: 0.00411 +2024-11-22 14:30:58.205842: train_loss -0.7887 +2024-11-22 14:30:58.211904: val_loss -0.7622 +2024-11-22 14:30:58.212032: Pseudo dice [0.857] +2024-11-22 14:30:58.212133: Epoch time: 18.16 s +2024-11-22 14:30:59.179962: +2024-11-22 14:30:59.180906: Epoch 5025 +2024-11-22 14:30:59.181043: Current learning rate: 0.00411 +2024-11-22 14:31:18.719340: train_loss -0.7974 +2024-11-22 14:31:18.724738: val_loss -0.7701 +2024-11-22 14:31:18.724842: Pseudo dice [0.8559] +2024-11-22 14:31:18.724927: Epoch time: 19.54 s +2024-11-22 14:31:19.592132: +2024-11-22 14:31:19.592857: Epoch 5026 +2024-11-22 14:31:19.592974: Current learning rate: 0.0041 +2024-11-22 14:31:39.346411: train_loss -0.7924 +2024-11-22 14:31:39.354747: val_loss -0.7795 +2024-11-22 14:31:39.354857: Pseudo dice [0.8631] +2024-11-22 14:31:39.354950: Epoch time: 19.76 s +2024-11-22 14:31:40.310148: +2024-11-22 14:31:40.310674: Epoch 5027 +2024-11-22 14:31:40.310805: Current learning rate: 0.0041 +2024-11-22 14:32:01.024160: train_loss -0.7958 +2024-11-22 14:32:01.026815: val_loss -0.7938 +2024-11-22 14:32:01.026934: Pseudo dice [0.8518] +2024-11-22 14:32:01.027037: Epoch time: 20.71 s +2024-11-22 14:32:02.026505: +2024-11-22 14:32:02.027859: Epoch 5028 +2024-11-22 14:32:02.027996: Current learning rate: 0.0041 +2024-11-22 14:32:21.031978: train_loss -0.7893 +2024-11-22 14:32:21.037618: val_loss -0.7788 +2024-11-22 14:32:21.037762: Pseudo dice [0.8558] +2024-11-22 14:32:21.037908: Epoch time: 19.01 s +2024-11-22 14:32:22.023521: +2024-11-22 14:32:22.024474: Epoch 5029 +2024-11-22 14:32:22.024586: Current learning rate: 0.0041 +2024-11-22 14:32:42.563614: train_loss -0.7958 +2024-11-22 14:32:42.569958: val_loss -0.7818 +2024-11-22 14:32:42.570097: Pseudo dice [0.8507] +2024-11-22 14:32:42.570194: Epoch time: 20.54 s +2024-11-22 14:32:43.443234: +2024-11-22 14:32:43.443809: Epoch 5030 +2024-11-22 14:32:43.443934: Current learning rate: 0.0041 +2024-11-22 14:33:02.675986: train_loss -0.7972 +2024-11-22 14:33:02.679124: val_loss -0.7791 +2024-11-22 14:33:02.679240: Pseudo dice [0.8641] +2024-11-22 14:33:02.679330: Epoch time: 19.23 s +2024-11-22 14:33:03.548885: +2024-11-22 14:33:03.550000: Epoch 5031 +2024-11-22 14:33:03.550137: Current learning rate: 0.0041 +2024-11-22 14:33:22.534796: train_loss -0.792 +2024-11-22 14:33:22.545771: val_loss -0.7754 +2024-11-22 14:33:22.545917: Pseudo dice [0.8607] +2024-11-22 14:33:22.546018: Epoch time: 18.99 s +2024-11-22 14:33:23.639671: +2024-11-22 14:33:23.641777: Epoch 5032 +2024-11-22 14:33:23.641932: Current learning rate: 0.0041 +2024-11-22 14:33:42.769126: train_loss -0.796 +2024-11-22 14:33:42.777369: val_loss -0.741 +2024-11-22 14:33:42.777512: Pseudo dice [0.8525] +2024-11-22 14:33:42.777612: Epoch time: 19.13 s +2024-11-22 14:33:43.780186: +2024-11-22 14:33:43.781639: Epoch 5033 +2024-11-22 14:33:43.781765: Current learning rate: 0.0041 +2024-11-22 14:34:03.565140: train_loss -0.7827 +2024-11-22 14:34:03.567877: val_loss -0.7977 +2024-11-22 14:34:03.567991: Pseudo dice [0.8563] +2024-11-22 14:34:03.568083: Epoch time: 19.79 s +2024-11-22 14:34:04.522972: +2024-11-22 14:34:04.524397: Epoch 5034 +2024-11-22 14:34:04.524523: Current learning rate: 0.00409 +2024-11-22 14:34:25.811095: train_loss -0.7943 +2024-11-22 14:34:25.824929: val_loss -0.8042 +2024-11-22 14:34:25.825078: Pseudo dice [0.8568] +2024-11-22 14:34:25.825178: Epoch time: 21.29 s +2024-11-22 14:34:26.904465: +2024-11-22 14:34:26.906556: Epoch 5035 +2024-11-22 14:34:26.906765: Current learning rate: 0.00409 +2024-11-22 14:34:46.759018: train_loss -0.7851 +2024-11-22 14:34:46.778770: val_loss -0.765 +2024-11-22 14:34:46.778952: Pseudo dice [0.8479] +2024-11-22 14:34:46.779057: Epoch time: 19.86 s +2024-11-22 14:34:47.704784: +2024-11-22 14:34:47.705264: Epoch 5036 +2024-11-22 14:34:47.726909: Current learning rate: 0.00409 +2024-11-22 14:35:07.050529: train_loss -0.79 +2024-11-22 14:35:07.058162: val_loss -0.7549 +2024-11-22 14:35:07.058300: Pseudo dice [0.8597] +2024-11-22 14:35:07.058386: Epoch time: 19.35 s +2024-11-22 14:35:08.024210: +2024-11-22 14:35:08.025353: Epoch 5037 +2024-11-22 14:35:08.025496: Current learning rate: 0.00409 +2024-11-22 14:35:27.470141: train_loss -0.7873 +2024-11-22 14:35:27.477145: val_loss -0.7739 +2024-11-22 14:35:27.477290: Pseudo dice [0.8505] +2024-11-22 14:35:27.477383: Epoch time: 19.45 s +2024-11-22 14:35:28.857227: +2024-11-22 14:35:28.858690: Epoch 5038 +2024-11-22 14:35:28.858814: Current learning rate: 0.00409 +2024-11-22 14:35:48.581919: train_loss -0.7868 +2024-11-22 14:35:48.589378: val_loss -0.7528 +2024-11-22 14:35:48.589524: Pseudo dice [0.854] +2024-11-22 14:35:48.589615: Epoch time: 19.73 s +2024-11-22 14:35:49.469979: +2024-11-22 14:35:49.472270: Epoch 5039 +2024-11-22 14:35:49.472403: Current learning rate: 0.00409 +2024-11-22 14:36:08.717241: train_loss -0.8003 +2024-11-22 14:36:08.724414: val_loss -0.7724 +2024-11-22 14:36:08.724550: Pseudo dice [0.8516] +2024-11-22 14:36:08.724658: Epoch time: 19.25 s +2024-11-22 14:36:09.748581: +2024-11-22 14:36:09.750012: Epoch 5040 +2024-11-22 14:36:09.750149: Current learning rate: 0.00409 +2024-11-22 14:36:29.046185: train_loss -0.7972 +2024-11-22 14:36:29.055335: val_loss -0.7605 +2024-11-22 14:36:29.055510: Pseudo dice [0.8412] +2024-11-22 14:36:29.055602: Epoch time: 19.3 s +2024-11-22 14:36:30.053865: +2024-11-22 14:36:30.056450: Epoch 5041 +2024-11-22 14:36:30.056583: Current learning rate: 0.00409 +2024-11-22 14:36:50.407803: train_loss -0.7979 +2024-11-22 14:36:50.411734: val_loss -0.7904 +2024-11-22 14:36:50.411871: Pseudo dice [0.8473] +2024-11-22 14:36:50.411957: Epoch time: 20.35 s +2024-11-22 14:36:51.319520: +2024-11-22 14:36:51.320455: Epoch 5042 +2024-11-22 14:36:51.320576: Current learning rate: 0.00408 +2024-11-22 14:37:09.927899: train_loss -0.799 +2024-11-22 14:37:09.933475: val_loss -0.7877 +2024-11-22 14:37:09.933596: Pseudo dice [0.8542] +2024-11-22 14:37:09.933691: Epoch time: 18.61 s +2024-11-22 14:37:10.809045: +2024-11-22 14:37:10.809640: Epoch 5043 +2024-11-22 14:37:10.809759: Current learning rate: 0.00408 +2024-11-22 14:37:30.679875: train_loss -0.7936 +2024-11-22 14:37:30.687524: val_loss -0.7612 +2024-11-22 14:37:30.687696: Pseudo dice [0.8534] +2024-11-22 14:37:30.687791: Epoch time: 19.87 s +2024-11-22 14:37:31.601358: +2024-11-22 14:37:31.602266: Epoch 5044 +2024-11-22 14:37:31.602394: Current learning rate: 0.00408 +2024-11-22 14:37:51.603367: train_loss -0.7854 +2024-11-22 14:37:51.610272: val_loss -0.7717 +2024-11-22 14:37:51.610405: Pseudo dice [0.8565] +2024-11-22 14:37:51.610497: Epoch time: 20.0 s +2024-11-22 14:37:52.511396: +2024-11-22 14:37:52.513457: Epoch 5045 +2024-11-22 14:37:52.513634: Current learning rate: 0.00408 +2024-11-22 14:38:12.020781: train_loss -0.794 +2024-11-22 14:38:12.024136: val_loss -0.7767 +2024-11-22 14:38:12.024236: Pseudo dice [0.8614] +2024-11-22 14:38:12.024324: Epoch time: 19.51 s +2024-11-22 14:38:12.889044: +2024-11-22 14:38:12.890012: Epoch 5046 +2024-11-22 14:38:12.890155: Current learning rate: 0.00408 +2024-11-22 14:38:32.598140: train_loss -0.7984 +2024-11-22 14:38:32.603421: val_loss -0.7889 +2024-11-22 14:38:32.603633: Pseudo dice [0.8604] +2024-11-22 14:38:32.603740: Epoch time: 19.71 s +2024-11-22 14:38:33.472827: +2024-11-22 14:38:33.474271: Epoch 5047 +2024-11-22 14:38:33.474397: Current learning rate: 0.00408 +2024-11-22 14:38:52.872768: train_loss -0.7968 +2024-11-22 14:38:52.880444: val_loss -0.763 +2024-11-22 14:38:52.880572: Pseudo dice [0.8521] +2024-11-22 14:38:52.880659: Epoch time: 19.4 s +2024-11-22 14:38:53.784455: +2024-11-22 14:38:53.785562: Epoch 5048 +2024-11-22 14:38:53.785692: Current learning rate: 0.00408 +2024-11-22 14:39:12.249501: train_loss -0.7883 +2024-11-22 14:39:12.264468: val_loss -0.7786 +2024-11-22 14:39:12.264631: Pseudo dice [0.8603] +2024-11-22 14:39:12.264742: Epoch time: 18.47 s +2024-11-22 14:39:13.177170: +2024-11-22 14:39:13.230558: Epoch 5049 +2024-11-22 14:39:13.230716: Current learning rate: 0.00408 +2024-11-22 14:39:32.538064: train_loss -0.8007 +2024-11-22 14:39:32.544664: val_loss -0.7848 +2024-11-22 14:39:32.544784: Pseudo dice [0.8639] +2024-11-22 14:39:32.544886: Epoch time: 19.36 s +2024-11-22 14:39:34.138939: +2024-11-22 14:39:34.140070: Epoch 5050 +2024-11-22 14:39:34.140206: Current learning rate: 0.00407 +2024-11-22 14:39:53.102220: train_loss -0.8008 +2024-11-22 14:39:53.108659: val_loss -0.7492 +2024-11-22 14:39:53.108802: Pseudo dice [0.8402] +2024-11-22 14:39:53.108928: Epoch time: 18.96 s +2024-11-22 14:39:54.144526: +2024-11-22 14:39:54.145361: Epoch 5051 +2024-11-22 14:39:54.145501: Current learning rate: 0.00407 +2024-11-22 14:40:13.533881: train_loss -0.7964 +2024-11-22 14:40:13.539962: val_loss -0.7902 +2024-11-22 14:40:13.540098: Pseudo dice [0.8584] +2024-11-22 14:40:13.540191: Epoch time: 19.39 s +2024-11-22 14:40:14.450843: +2024-11-22 14:40:14.451973: Epoch 5052 +2024-11-22 14:40:14.452107: Current learning rate: 0.00407 +2024-11-22 14:40:33.010938: train_loss -0.8015 +2024-11-22 14:40:33.021719: val_loss -0.783 +2024-11-22 14:40:33.021867: Pseudo dice [0.858] +2024-11-22 14:40:33.021976: Epoch time: 18.56 s +2024-11-22 14:40:33.908162: +2024-11-22 14:40:33.908757: Epoch 5053 +2024-11-22 14:40:33.908881: Current learning rate: 0.00407 +2024-11-22 14:40:53.564197: train_loss -0.7957 +2024-11-22 14:40:53.570812: val_loss -0.7782 +2024-11-22 14:40:53.570943: Pseudo dice [0.8464] +2024-11-22 14:40:53.571116: Epoch time: 19.66 s +2024-11-22 14:40:54.569919: +2024-11-22 14:40:54.570713: Epoch 5054 +2024-11-22 14:40:54.570827: Current learning rate: 0.00407 +2024-11-22 14:41:12.503374: train_loss -0.7984 +2024-11-22 14:41:12.505925: val_loss -0.7915 +2024-11-22 14:41:12.506034: Pseudo dice [0.8556] +2024-11-22 14:41:12.506128: Epoch time: 17.93 s +2024-11-22 14:41:13.377110: +2024-11-22 14:41:13.377930: Epoch 5055 +2024-11-22 14:41:13.378065: Current learning rate: 0.00407 +2024-11-22 14:41:32.594947: train_loss -0.7906 +2024-11-22 14:41:32.598986: val_loss -0.7721 +2024-11-22 14:41:32.599105: Pseudo dice [0.8552] +2024-11-22 14:41:32.599197: Epoch time: 19.22 s +2024-11-22 14:41:33.564096: +2024-11-22 14:41:33.564883: Epoch 5056 +2024-11-22 14:41:33.565007: Current learning rate: 0.00407 +2024-11-22 14:41:53.235301: train_loss -0.7949 +2024-11-22 14:41:53.240210: val_loss -0.7994 +2024-11-22 14:41:53.240348: Pseudo dice [0.8518] +2024-11-22 14:41:53.240444: Epoch time: 19.67 s +2024-11-22 14:41:54.147843: +2024-11-22 14:41:54.148726: Epoch 5057 +2024-11-22 14:41:54.148866: Current learning rate: 0.00407 +2024-11-22 14:42:13.390012: train_loss -0.7953 +2024-11-22 14:42:13.397302: val_loss -0.7759 +2024-11-22 14:42:13.397428: Pseudo dice [0.8468] +2024-11-22 14:42:13.397523: Epoch time: 19.24 s +2024-11-22 14:42:14.320933: +2024-11-22 14:42:14.321560: Epoch 5058 +2024-11-22 14:42:14.321676: Current learning rate: 0.00406 +2024-11-22 14:42:33.889123: train_loss -0.8038 +2024-11-22 14:42:33.895042: val_loss -0.7589 +2024-11-22 14:42:33.895221: Pseudo dice [0.8486] +2024-11-22 14:42:33.895329: Epoch time: 19.57 s +2024-11-22 14:42:34.831537: +2024-11-22 14:42:34.833283: Epoch 5059 +2024-11-22 14:42:34.833428: Current learning rate: 0.00406 +2024-11-22 14:42:53.952354: train_loss -0.7864 +2024-11-22 14:42:53.960583: val_loss -0.7564 +2024-11-22 14:42:53.960727: Pseudo dice [0.8521] +2024-11-22 14:42:53.960827: Epoch time: 19.12 s +2024-11-22 14:42:54.898697: +2024-11-22 14:42:54.899995: Epoch 5060 +2024-11-22 14:42:54.900311: Current learning rate: 0.00406 +2024-11-22 14:43:14.063851: train_loss -0.7967 +2024-11-22 14:43:14.068949: val_loss -0.7837 +2024-11-22 14:43:14.069098: Pseudo dice [0.8587] +2024-11-22 14:43:14.069212: Epoch time: 19.17 s +2024-11-22 14:43:15.326199: +2024-11-22 14:43:15.328054: Epoch 5061 +2024-11-22 14:43:15.328189: Current learning rate: 0.00406 +2024-11-22 14:43:33.691250: train_loss -0.796 +2024-11-22 14:43:33.697231: val_loss -0.7598 +2024-11-22 14:43:33.697621: Pseudo dice [0.8499] +2024-11-22 14:43:33.697865: Epoch time: 18.37 s +2024-11-22 14:43:34.621624: +2024-11-22 14:43:34.622546: Epoch 5062 +2024-11-22 14:43:34.622687: Current learning rate: 0.00406 +2024-11-22 14:43:54.233192: train_loss -0.7856 +2024-11-22 14:43:54.238971: val_loss -0.7885 +2024-11-22 14:43:54.239105: Pseudo dice [0.8533] +2024-11-22 14:43:54.239211: Epoch time: 19.61 s +2024-11-22 14:43:55.118656: +2024-11-22 14:43:55.120174: Epoch 5063 +2024-11-22 14:43:55.120303: Current learning rate: 0.00406 +2024-11-22 14:44:13.799074: train_loss -0.801 +2024-11-22 14:44:13.821143: val_loss -0.7796 +2024-11-22 14:44:13.821291: Pseudo dice [0.8595] +2024-11-22 14:44:13.821393: Epoch time: 18.68 s +2024-11-22 14:44:14.710772: +2024-11-22 14:44:14.711696: Epoch 5064 +2024-11-22 14:44:14.711820: Current learning rate: 0.00406 +2024-11-22 14:44:34.428744: train_loss -0.7965 +2024-11-22 14:44:34.449573: val_loss -0.7688 +2024-11-22 14:44:34.449712: Pseudo dice [0.8539] +2024-11-22 14:44:34.449813: Epoch time: 19.72 s +2024-11-22 14:44:35.522481: +2024-11-22 14:44:35.523226: Epoch 5065 +2024-11-22 14:44:35.523361: Current learning rate: 0.00406 +2024-11-22 14:44:54.556409: train_loss -0.7972 +2024-11-22 14:44:54.562024: val_loss -0.788 +2024-11-22 14:44:54.562163: Pseudo dice [0.8563] +2024-11-22 14:44:54.562293: Epoch time: 19.03 s +2024-11-22 14:44:55.647683: +2024-11-22 14:44:55.648214: Epoch 5066 +2024-11-22 14:44:55.648355: Current learning rate: 0.00405 +2024-11-22 14:45:14.399341: train_loss -0.7967 +2024-11-22 14:45:14.403263: val_loss -0.7674 +2024-11-22 14:45:14.403385: Pseudo dice [0.8522] +2024-11-22 14:45:14.403496: Epoch time: 18.75 s +2024-11-22 14:45:15.412459: +2024-11-22 14:45:15.413756: Epoch 5067 +2024-11-22 14:45:15.413889: Current learning rate: 0.00405 +2024-11-22 14:45:34.198046: train_loss -0.7897 +2024-11-22 14:45:34.204498: val_loss -0.7573 +2024-11-22 14:45:34.204775: Pseudo dice [0.8544] +2024-11-22 14:45:34.204864: Epoch time: 18.79 s +2024-11-22 14:45:35.078447: +2024-11-22 14:45:35.079410: Epoch 5068 +2024-11-22 14:45:35.079553: Current learning rate: 0.00405 +2024-11-22 14:45:53.894035: train_loss -0.7856 +2024-11-22 14:45:53.910463: val_loss -0.751 +2024-11-22 14:45:53.910611: Pseudo dice [0.8316] +2024-11-22 14:45:53.910722: Epoch time: 18.82 s +2024-11-22 14:45:54.895303: +2024-11-22 14:45:54.896396: Epoch 5069 +2024-11-22 14:45:54.896518: Current learning rate: 0.00405 +2024-11-22 14:46:15.348114: train_loss -0.7947 +2024-11-22 14:46:15.354496: val_loss -0.7869 +2024-11-22 14:46:15.354656: Pseudo dice [0.8583] +2024-11-22 14:46:15.354768: Epoch time: 20.45 s +2024-11-22 14:46:16.239790: +2024-11-22 14:46:16.241262: Epoch 5070 +2024-11-22 14:46:16.241407: Current learning rate: 0.00405 +2024-11-22 14:46:35.173534: train_loss -0.7923 +2024-11-22 14:46:35.182287: val_loss -0.7797 +2024-11-22 14:46:35.182419: Pseudo dice [0.8517] +2024-11-22 14:46:35.182506: Epoch time: 18.93 s +2024-11-22 14:46:36.129432: +2024-11-22 14:46:36.130201: Epoch 5071 +2024-11-22 14:46:36.130336: Current learning rate: 0.00405 +2024-11-22 14:46:55.722941: train_loss -0.7959 +2024-11-22 14:46:55.729395: val_loss -0.7732 +2024-11-22 14:46:55.729544: Pseudo dice [0.844] +2024-11-22 14:46:55.729639: Epoch time: 19.59 s +2024-11-22 14:46:57.106272: +2024-11-22 14:46:57.107936: Epoch 5072 +2024-11-22 14:46:57.108072: Current learning rate: 0.00405 +2024-11-22 14:47:16.028684: train_loss -0.7861 +2024-11-22 14:47:16.034371: val_loss -0.7743 +2024-11-22 14:47:16.034499: Pseudo dice [0.8546] +2024-11-22 14:47:16.034661: Epoch time: 18.92 s +2024-11-22 14:47:16.981144: +2024-11-22 14:47:16.981891: Epoch 5073 +2024-11-22 14:47:16.982035: Current learning rate: 0.00405 +2024-11-22 14:47:35.466048: train_loss -0.8 +2024-11-22 14:47:35.473649: val_loss -0.7689 +2024-11-22 14:47:35.473804: Pseudo dice [0.8651] +2024-11-22 14:47:35.473894: Epoch time: 18.49 s +2024-11-22 14:47:36.463550: +2024-11-22 14:47:36.463771: Epoch 5074 +2024-11-22 14:47:36.463892: Current learning rate: 0.00404 +2024-11-22 14:47:55.317458: train_loss -0.7845 +2024-11-22 14:47:55.331208: val_loss -0.7654 +2024-11-22 14:47:55.331329: Pseudo dice [0.8479] +2024-11-22 14:47:55.331424: Epoch time: 18.85 s +2024-11-22 14:47:56.194317: +2024-11-22 14:47:56.195119: Epoch 5075 +2024-11-22 14:47:56.195248: Current learning rate: 0.00404 +2024-11-22 14:48:15.194704: train_loss -0.7937 +2024-11-22 14:48:15.198102: val_loss -0.7605 +2024-11-22 14:48:15.198218: Pseudo dice [0.8414] +2024-11-22 14:48:15.198331: Epoch time: 19.0 s +2024-11-22 14:48:16.066679: +2024-11-22 14:48:16.066886: Epoch 5076 +2024-11-22 14:48:16.067007: Current learning rate: 0.00404 +2024-11-22 14:48:35.699033: train_loss -0.7934 +2024-11-22 14:48:35.704310: val_loss -0.7655 +2024-11-22 14:48:35.704428: Pseudo dice [0.8614] +2024-11-22 14:48:35.704513: Epoch time: 19.63 s +2024-11-22 14:48:36.644965: +2024-11-22 14:48:36.645178: Epoch 5077 +2024-11-22 14:48:36.645294: Current learning rate: 0.00404 +2024-11-22 14:48:56.513232: train_loss -0.8013 +2024-11-22 14:48:56.519310: val_loss -0.7739 +2024-11-22 14:48:56.519430: Pseudo dice [0.862] +2024-11-22 14:48:56.519519: Epoch time: 19.87 s +2024-11-22 14:48:57.405484: +2024-11-22 14:48:57.406270: Epoch 5078 +2024-11-22 14:48:57.406391: Current learning rate: 0.00404 +2024-11-22 14:49:16.562129: train_loss -0.7913 +2024-11-22 14:49:16.569590: val_loss -0.7937 +2024-11-22 14:49:16.569717: Pseudo dice [0.8538] +2024-11-22 14:49:16.569812: Epoch time: 19.16 s +2024-11-22 14:49:17.541115: +2024-11-22 14:49:17.542134: Epoch 5079 +2024-11-22 14:49:17.542265: Current learning rate: 0.00404 +2024-11-22 14:49:36.270851: train_loss -0.789 +2024-11-22 14:49:36.284632: val_loss -0.7674 +2024-11-22 14:49:36.284760: Pseudo dice [0.8392] +2024-11-22 14:49:36.284896: Epoch time: 18.73 s +2024-11-22 14:49:37.423677: +2024-11-22 14:49:37.424447: Epoch 5080 +2024-11-22 14:49:37.424577: Current learning rate: 0.00404 +2024-11-22 14:49:56.499662: train_loss -0.8017 +2024-11-22 14:49:56.504308: val_loss -0.7857 +2024-11-22 14:49:56.504436: Pseudo dice [0.8568] +2024-11-22 14:49:56.504515: Epoch time: 19.08 s +2024-11-22 14:49:57.370680: +2024-11-22 14:49:57.371202: Epoch 5081 +2024-11-22 14:49:57.371323: Current learning rate: 0.00404 +2024-11-22 14:50:16.658676: train_loss -0.8007 +2024-11-22 14:50:16.669582: val_loss -0.7887 +2024-11-22 14:50:16.671819: Pseudo dice [0.8679] +2024-11-22 14:50:16.671939: Epoch time: 19.29 s +2024-11-22 14:50:17.628537: +2024-11-22 14:50:17.630537: Epoch 5082 +2024-11-22 14:50:17.630667: Current learning rate: 0.00403 +2024-11-22 14:50:36.440573: train_loss -0.7973 +2024-11-22 14:50:36.450979: val_loss -0.7706 +2024-11-22 14:50:36.451125: Pseudo dice [0.8557] +2024-11-22 14:50:36.451231: Epoch time: 18.81 s +2024-11-22 14:50:37.429135: +2024-11-22 14:50:37.429343: Epoch 5083 +2024-11-22 14:50:37.429474: Current learning rate: 0.00403 +2024-11-22 14:50:58.337847: train_loss -0.7991 +2024-11-22 14:50:58.342763: val_loss -0.7891 +2024-11-22 14:50:58.342921: Pseudo dice [0.8631] +2024-11-22 14:50:58.343078: Epoch time: 20.91 s +2024-11-22 14:50:59.671865: +2024-11-22 14:50:59.672530: Epoch 5084 +2024-11-22 14:50:59.672668: Current learning rate: 0.00403 +2024-11-22 14:51:18.665665: train_loss -0.7952 +2024-11-22 14:51:18.670829: val_loss -0.7647 +2024-11-22 14:51:18.670947: Pseudo dice [0.8465] +2024-11-22 14:51:18.671045: Epoch time: 18.99 s +2024-11-22 14:51:19.582577: +2024-11-22 14:51:19.583030: Epoch 5085 +2024-11-22 14:51:19.583192: Current learning rate: 0.00403 +2024-11-22 14:51:39.366392: train_loss -0.7925 +2024-11-22 14:51:39.372489: val_loss -0.7604 +2024-11-22 14:51:39.372643: Pseudo dice [0.8412] +2024-11-22 14:51:39.372735: Epoch time: 19.78 s +2024-11-22 14:51:40.259641: +2024-11-22 14:51:40.260067: Epoch 5086 +2024-11-22 14:51:40.260292: Current learning rate: 0.00403 +2024-11-22 14:51:59.809820: train_loss -0.8029 +2024-11-22 14:51:59.814372: val_loss -0.7794 +2024-11-22 14:51:59.814507: Pseudo dice [0.8524] +2024-11-22 14:51:59.814597: Epoch time: 19.55 s +2024-11-22 14:52:00.724302: +2024-11-22 14:52:00.725642: Epoch 5087 +2024-11-22 14:52:00.725796: Current learning rate: 0.00403 +2024-11-22 14:52:20.447762: train_loss -0.8028 +2024-11-22 14:52:20.453002: val_loss -0.7814 +2024-11-22 14:52:20.453167: Pseudo dice [0.8542] +2024-11-22 14:52:20.453259: Epoch time: 19.72 s +2024-11-22 14:52:21.420732: +2024-11-22 14:52:21.422600: Epoch 5088 +2024-11-22 14:52:21.422753: Current learning rate: 0.00403 +2024-11-22 14:52:40.717194: train_loss -0.7926 +2024-11-22 14:52:40.737126: val_loss -0.748 +2024-11-22 14:52:40.737275: Pseudo dice [0.8528] +2024-11-22 14:52:40.737380: Epoch time: 19.3 s +2024-11-22 14:52:41.723898: +2024-11-22 14:52:41.724604: Epoch 5089 +2024-11-22 14:52:41.724761: Current learning rate: 0.00403 +2024-11-22 14:53:00.669162: train_loss -0.7963 +2024-11-22 14:53:00.680813: val_loss -0.7612 +2024-11-22 14:53:00.680946: Pseudo dice [0.8526] +2024-11-22 14:53:00.681042: Epoch time: 18.95 s +2024-11-22 14:53:01.842101: +2024-11-22 14:53:01.844394: Epoch 5090 +2024-11-22 14:53:01.844552: Current learning rate: 0.00402 +2024-11-22 14:53:22.472651: train_loss -0.7963 +2024-11-22 14:53:22.481422: val_loss -0.7643 +2024-11-22 14:53:22.481620: Pseudo dice [0.8544] +2024-11-22 14:53:22.481725: Epoch time: 20.63 s +2024-11-22 14:53:23.357314: +2024-11-22 14:53:23.358347: Epoch 5091 +2024-11-22 14:53:23.358486: Current learning rate: 0.00402 +2024-11-22 14:53:43.136642: train_loss -0.7922 +2024-11-22 14:53:43.139839: val_loss -0.7701 +2024-11-22 14:53:43.139969: Pseudo dice [0.8456] +2024-11-22 14:53:43.140068: Epoch time: 19.78 s +2024-11-22 14:53:44.170027: +2024-11-22 14:53:44.170469: Epoch 5092 +2024-11-22 14:53:44.170598: Current learning rate: 0.00402 +2024-11-22 14:54:04.242448: train_loss -0.784 +2024-11-22 14:54:04.243619: val_loss -0.7663 +2024-11-22 14:54:04.243707: Pseudo dice [0.8507] +2024-11-22 14:54:04.243781: Epoch time: 20.07 s +2024-11-22 14:54:05.100070: +2024-11-22 14:54:05.100485: Epoch 5093 +2024-11-22 14:54:05.100628: Current learning rate: 0.00402 +2024-11-22 14:54:23.528515: train_loss -0.7863 +2024-11-22 14:54:23.531387: val_loss -0.7542 +2024-11-22 14:54:23.531512: Pseudo dice [0.8595] +2024-11-22 14:54:23.531612: Epoch time: 18.43 s +2024-11-22 14:54:24.422641: +2024-11-22 14:54:24.423097: Epoch 5094 +2024-11-22 14:54:24.423242: Current learning rate: 0.00402 +2024-11-22 14:54:43.579021: train_loss -0.7904 +2024-11-22 14:54:43.579286: val_loss -0.769 +2024-11-22 14:54:43.579402: Pseudo dice [0.8519] +2024-11-22 14:54:43.579496: Epoch time: 19.16 s +2024-11-22 14:54:44.809152: +2024-11-22 14:54:44.809352: Epoch 5095 +2024-11-22 14:54:44.809476: Current learning rate: 0.00402 +2024-11-22 14:55:04.431552: train_loss -0.7904 +2024-11-22 14:55:04.437064: val_loss -0.7775 +2024-11-22 14:55:04.437189: Pseudo dice [0.8559] +2024-11-22 14:55:04.437285: Epoch time: 19.62 s +2024-11-22 14:55:05.548607: +2024-11-22 14:55:05.548858: Epoch 5096 +2024-11-22 14:55:05.548984: Current learning rate: 0.00402 +2024-11-22 14:55:23.428736: train_loss -0.787 +2024-11-22 14:55:23.434001: val_loss -0.7741 +2024-11-22 14:55:23.434167: Pseudo dice [0.8442] +2024-11-22 14:55:23.434279: Epoch time: 17.88 s +2024-11-22 14:55:24.312516: +2024-11-22 14:55:24.312728: Epoch 5097 +2024-11-22 14:55:24.312881: Current learning rate: 0.00402 +2024-11-22 14:55:43.132205: train_loss -0.7833 +2024-11-22 14:55:43.132425: val_loss -0.7714 +2024-11-22 14:55:43.132511: Pseudo dice [0.8552] +2024-11-22 14:55:43.132591: Epoch time: 18.82 s +2024-11-22 14:55:43.999707: +2024-11-22 14:55:43.999923: Epoch 5098 +2024-11-22 14:55:44.000044: Current learning rate: 0.00401 +2024-11-22 14:56:03.334871: train_loss -0.7876 +2024-11-22 14:56:03.336170: val_loss -0.7625 +2024-11-22 14:56:03.336269: Pseudo dice [0.849] +2024-11-22 14:56:03.336368: Epoch time: 19.34 s +2024-11-22 14:56:04.197294: +2024-11-22 14:56:04.197518: Epoch 5099 +2024-11-22 14:56:04.197657: Current learning rate: 0.00401 +2024-11-22 14:56:24.068602: train_loss -0.7863 +2024-11-22 14:56:24.071288: val_loss -0.7413 +2024-11-22 14:56:24.073355: Pseudo dice [0.824] +2024-11-22 14:56:24.073487: Epoch time: 19.87 s +2024-11-22 14:56:25.395327: +2024-11-22 14:56:25.395533: Epoch 5100 +2024-11-22 14:56:25.395664: Current learning rate: 0.00401 +2024-11-22 14:56:45.434458: train_loss -0.7995 +2024-11-22 14:56:45.438287: val_loss -0.8111 +2024-11-22 14:56:45.438415: Pseudo dice [0.8656] +2024-11-22 14:56:45.438517: Epoch time: 20.04 s +2024-11-22 14:56:46.316388: +2024-11-22 14:56:46.316656: Epoch 5101 +2024-11-22 14:56:46.316793: Current learning rate: 0.00401 +2024-11-22 14:57:06.616698: train_loss -0.7972 +2024-11-22 14:57:06.619666: val_loss -0.7908 +2024-11-22 14:57:06.619784: Pseudo dice [0.8527] +2024-11-22 14:57:06.619893: Epoch time: 20.3 s +2024-11-22 14:57:07.482035: +2024-11-22 14:57:07.482737: Epoch 5102 +2024-11-22 14:57:07.482884: Current learning rate: 0.00401 +2024-11-22 14:57:26.276049: train_loss -0.8041 +2024-11-22 14:57:26.279830: val_loss -0.7798 +2024-11-22 14:57:26.279959: Pseudo dice [0.8645] +2024-11-22 14:57:26.280055: Epoch time: 18.79 s +2024-11-22 14:57:27.254886: +2024-11-22 14:57:27.255336: Epoch 5103 +2024-11-22 14:57:27.255481: Current learning rate: 0.00401 +2024-11-22 14:57:47.546219: train_loss -0.7887 +2024-11-22 14:57:47.552188: val_loss -0.7877 +2024-11-22 14:57:47.552338: Pseudo dice [0.8665] +2024-11-22 14:57:47.552431: Epoch time: 20.29 s +2024-11-22 14:57:48.436958: +2024-11-22 14:57:48.437382: Epoch 5104 +2024-11-22 14:57:48.437517: Current learning rate: 0.00401 +2024-11-22 14:58:07.456048: train_loss -0.7973 +2024-11-22 14:58:07.458599: val_loss -0.7633 +2024-11-22 14:58:07.458712: Pseudo dice [0.8498] +2024-11-22 14:58:07.458797: Epoch time: 19.02 s +2024-11-22 14:58:08.323153: +2024-11-22 14:58:08.323978: Epoch 5105 +2024-11-22 14:58:08.324115: Current learning rate: 0.00401 +2024-11-22 14:58:27.911395: train_loss -0.7983 +2024-11-22 14:58:27.927864: val_loss -0.762 +2024-11-22 14:58:27.928123: Pseudo dice [0.851] +2024-11-22 14:58:27.928239: Epoch time: 19.59 s +2024-11-22 14:58:28.793455: +2024-11-22 14:58:28.794136: Epoch 5106 +2024-11-22 14:58:28.794288: Current learning rate: 0.004 +2024-11-22 14:58:48.293581: train_loss -0.7977 +2024-11-22 14:58:48.299561: val_loss -0.7868 +2024-11-22 14:58:48.299702: Pseudo dice [0.8659] +2024-11-22 14:58:48.299796: Epoch time: 19.5 s +2024-11-22 14:58:49.217001: +2024-11-22 14:58:49.217449: Epoch 5107 +2024-11-22 14:58:49.217606: Current learning rate: 0.004 +2024-11-22 14:59:08.915034: train_loss -0.7882 +2024-11-22 14:59:08.923186: val_loss -0.764 +2024-11-22 14:59:08.923313: Pseudo dice [0.8533] +2024-11-22 14:59:08.923422: Epoch time: 19.7 s +2024-11-22 14:59:10.104542: +2024-11-22 14:59:10.105896: Epoch 5108 +2024-11-22 14:59:10.106036: Current learning rate: 0.004 +2024-11-22 14:59:29.410543: train_loss -0.7825 +2024-11-22 14:59:29.416992: val_loss -0.7713 +2024-11-22 14:59:29.417156: Pseudo dice [0.8575] +2024-11-22 14:59:29.417257: Epoch time: 19.31 s +2024-11-22 14:59:30.291763: +2024-11-22 14:59:30.292892: Epoch 5109 +2024-11-22 14:59:30.293020: Current learning rate: 0.004 +2024-11-22 14:59:50.630723: train_loss -0.7693 +2024-11-22 14:59:50.643696: val_loss -0.7639 +2024-11-22 14:59:50.643850: Pseudo dice [0.8434] +2024-11-22 14:59:50.643939: Epoch time: 20.34 s +2024-11-22 14:59:51.681525: +2024-11-22 14:59:51.683357: Epoch 5110 +2024-11-22 14:59:51.683531: Current learning rate: 0.004 +2024-11-22 15:00:11.361329: train_loss -0.7766 +2024-11-22 15:00:11.369903: val_loss -0.7434 +2024-11-22 15:00:11.370112: Pseudo dice [0.8416] +2024-11-22 15:00:11.370215: Epoch time: 19.68 s +2024-11-22 15:00:12.271138: +2024-11-22 15:00:12.272654: Epoch 5111 +2024-11-22 15:00:12.272775: Current learning rate: 0.004 +2024-11-22 15:00:30.966468: train_loss -0.7702 +2024-11-22 15:00:30.972834: val_loss -0.7632 +2024-11-22 15:00:30.972967: Pseudo dice [0.8456] +2024-11-22 15:00:30.973149: Epoch time: 18.7 s +2024-11-22 15:00:32.055249: +2024-11-22 15:00:32.056843: Epoch 5112 +2024-11-22 15:00:32.057191: Current learning rate: 0.004 +2024-11-22 15:00:51.506572: train_loss -0.7766 +2024-11-22 15:00:51.512239: val_loss -0.7724 +2024-11-22 15:00:51.518594: Pseudo dice [0.8515] +2024-11-22 15:00:51.518778: Epoch time: 19.45 s +2024-11-22 15:00:52.434968: +2024-11-22 15:00:52.436297: Epoch 5113 +2024-11-22 15:00:52.436448: Current learning rate: 0.004 +2024-11-22 15:01:10.933709: train_loss -0.7897 +2024-11-22 15:01:10.939624: val_loss -0.7419 +2024-11-22 15:01:10.939779: Pseudo dice [0.8492] +2024-11-22 15:01:10.939878: Epoch time: 18.5 s +2024-11-22 15:01:11.835852: +2024-11-22 15:01:11.837215: Epoch 5114 +2024-11-22 15:01:11.837347: Current learning rate: 0.00399 +2024-11-22 15:01:31.579196: train_loss -0.7866 +2024-11-22 15:01:31.586296: val_loss -0.7865 +2024-11-22 15:01:31.586425: Pseudo dice [0.8532] +2024-11-22 15:01:31.586539: Epoch time: 19.74 s +2024-11-22 15:01:32.495719: +2024-11-22 15:01:32.496451: Epoch 5115 +2024-11-22 15:01:32.496587: Current learning rate: 0.00399 +2024-11-22 15:01:51.873206: train_loss -0.7888 +2024-11-22 15:01:51.880408: val_loss -0.7503 +2024-11-22 15:01:51.880527: Pseudo dice [0.8572] +2024-11-22 15:01:51.880633: Epoch time: 19.38 s +2024-11-22 15:01:52.917542: +2024-11-22 15:01:52.918426: Epoch 5116 +2024-11-22 15:01:52.918544: Current learning rate: 0.00399 +2024-11-22 15:02:11.513712: train_loss -0.7896 +2024-11-22 15:02:11.519783: val_loss -0.7714 +2024-11-22 15:02:11.519930: Pseudo dice [0.8524] +2024-11-22 15:02:11.520039: Epoch time: 18.6 s +2024-11-22 15:02:12.394988: +2024-11-22 15:02:12.396443: Epoch 5117 +2024-11-22 15:02:12.396591: Current learning rate: 0.00399 +2024-11-22 15:02:32.812903: train_loss -0.7972 +2024-11-22 15:02:32.816087: val_loss -0.7646 +2024-11-22 15:02:32.816187: Pseudo dice [0.8531] +2024-11-22 15:02:32.816281: Epoch time: 20.42 s +2024-11-22 15:02:33.679002: +2024-11-22 15:02:33.680248: Epoch 5118 +2024-11-22 15:02:33.680377: Current learning rate: 0.00399 +2024-11-22 15:02:52.999646: train_loss -0.8015 +2024-11-22 15:02:53.006029: val_loss -0.7724 +2024-11-22 15:02:53.006159: Pseudo dice [0.861] +2024-11-22 15:02:53.006257: Epoch time: 19.32 s +2024-11-22 15:02:54.025861: +2024-11-22 15:02:54.027176: Epoch 5119 +2024-11-22 15:02:54.027312: Current learning rate: 0.00399 +2024-11-22 15:03:12.719434: train_loss -0.7932 +2024-11-22 15:03:12.724767: val_loss -0.7836 +2024-11-22 15:03:12.724907: Pseudo dice [0.8566] +2024-11-22 15:03:12.724995: Epoch time: 18.69 s +2024-11-22 15:03:13.617057: +2024-11-22 15:03:13.617286: Epoch 5120 +2024-11-22 15:03:13.617417: Current learning rate: 0.00399 +2024-11-22 15:03:33.042640: train_loss -0.7947 +2024-11-22 15:03:33.045315: val_loss -0.7682 +2024-11-22 15:03:33.045429: Pseudo dice [0.8579] +2024-11-22 15:03:33.045558: Epoch time: 19.43 s +2024-11-22 15:03:34.075726: +2024-11-22 15:03:34.077663: Epoch 5121 +2024-11-22 15:03:34.077808: Current learning rate: 0.00399 +2024-11-22 15:03:52.224975: train_loss -0.7992 +2024-11-22 15:03:52.230139: val_loss -0.7637 +2024-11-22 15:03:52.230299: Pseudo dice [0.8477] +2024-11-22 15:03:52.230399: Epoch time: 18.15 s +2024-11-22 15:03:53.095380: +2024-11-22 15:03:53.096197: Epoch 5122 +2024-11-22 15:03:53.096318: Current learning rate: 0.00398 +2024-11-22 15:04:13.427648: train_loss -0.8035 +2024-11-22 15:04:13.430663: val_loss -0.7656 +2024-11-22 15:04:13.430788: Pseudo dice [0.8621] +2024-11-22 15:04:13.430877: Epoch time: 20.33 s +2024-11-22 15:04:14.461148: +2024-11-22 15:04:14.462078: Epoch 5123 +2024-11-22 15:04:14.462202: Current learning rate: 0.00398 +2024-11-22 15:04:34.356378: train_loss -0.7961 +2024-11-22 15:04:34.361287: val_loss -0.7775 +2024-11-22 15:04:34.361432: Pseudo dice [0.8547] +2024-11-22 15:04:34.361529: Epoch time: 19.9 s +2024-11-22 15:04:35.265099: +2024-11-22 15:04:35.265303: Epoch 5124 +2024-11-22 15:04:35.265429: Current learning rate: 0.00398 +2024-11-22 15:04:54.871424: train_loss -0.805 +2024-11-22 15:04:54.884095: val_loss -0.7815 +2024-11-22 15:04:54.884268: Pseudo dice [0.8578] +2024-11-22 15:04:54.884366: Epoch time: 19.61 s +2024-11-22 15:04:56.022475: +2024-11-22 15:04:56.023962: Epoch 5125 +2024-11-22 15:04:56.024248: Current learning rate: 0.00398 +2024-11-22 15:05:15.167053: train_loss -0.804 +2024-11-22 15:05:15.169361: val_loss -0.7846 +2024-11-22 15:05:15.169502: Pseudo dice [0.8521] +2024-11-22 15:05:15.169596: Epoch time: 19.15 s +2024-11-22 15:05:16.167892: +2024-11-22 15:05:16.168347: Epoch 5126 +2024-11-22 15:05:16.168464: Current learning rate: 0.00398 +2024-11-22 15:05:34.506555: train_loss -0.804 +2024-11-22 15:05:34.517114: val_loss -0.7567 +2024-11-22 15:05:34.517267: Pseudo dice [0.8547] +2024-11-22 15:05:34.517373: Epoch time: 18.34 s +2024-11-22 15:05:35.424367: +2024-11-22 15:05:35.425899: Epoch 5127 +2024-11-22 15:05:35.426072: Current learning rate: 0.00398 +2024-11-22 15:05:55.351659: train_loss -0.796 +2024-11-22 15:05:55.384300: val_loss -0.7743 +2024-11-22 15:05:55.384449: Pseudo dice [0.8476] +2024-11-22 15:05:55.384542: Epoch time: 19.93 s +2024-11-22 15:05:56.724702: +2024-11-22 15:05:56.725152: Epoch 5128 +2024-11-22 15:05:56.725272: Current learning rate: 0.00398 +2024-11-22 15:06:17.307291: train_loss -0.8061 +2024-11-22 15:06:17.313864: val_loss -0.7773 +2024-11-22 15:06:17.313995: Pseudo dice [0.856] +2024-11-22 15:06:17.314157: Epoch time: 20.58 s +2024-11-22 15:06:18.281372: +2024-11-22 15:06:18.283427: Epoch 5129 +2024-11-22 15:06:18.283621: Current learning rate: 0.00398 +2024-11-22 15:06:37.613317: train_loss -0.798 +2024-11-22 15:06:37.620265: val_loss -0.7848 +2024-11-22 15:06:37.620400: Pseudo dice [0.8521] +2024-11-22 15:06:37.620580: Epoch time: 19.33 s +2024-11-22 15:06:38.579742: +2024-11-22 15:06:38.580591: Epoch 5130 +2024-11-22 15:06:38.580738: Current learning rate: 0.00397 +2024-11-22 15:06:58.268784: train_loss -0.798 +2024-11-22 15:06:58.274704: val_loss -0.7438 +2024-11-22 15:06:58.274837: Pseudo dice [0.837] +2024-11-22 15:06:58.274958: Epoch time: 19.69 s +2024-11-22 15:06:59.274311: +2024-11-22 15:06:59.276083: Epoch 5131 +2024-11-22 15:06:59.276222: Current learning rate: 0.00397 +2024-11-22 15:07:19.652556: train_loss -0.7986 +2024-11-22 15:07:19.660400: val_loss -0.7599 +2024-11-22 15:07:19.660518: Pseudo dice [0.8379] +2024-11-22 15:07:19.660616: Epoch time: 20.38 s +2024-11-22 15:07:20.545861: +2024-11-22 15:07:20.546680: Epoch 5132 +2024-11-22 15:07:20.546801: Current learning rate: 0.00397 +2024-11-22 15:07:39.123261: train_loss -0.7965 +2024-11-22 15:07:39.127005: val_loss -0.7617 +2024-11-22 15:07:39.127127: Pseudo dice [0.8467] +2024-11-22 15:07:39.127233: Epoch time: 18.58 s +2024-11-22 15:07:40.043756: +2024-11-22 15:07:40.044521: Epoch 5133 +2024-11-22 15:07:40.044649: Current learning rate: 0.00397 +2024-11-22 15:07:59.405043: train_loss -0.8078 +2024-11-22 15:07:59.419588: val_loss -0.779 +2024-11-22 15:07:59.419751: Pseudo dice [0.8545] +2024-11-22 15:07:59.419870: Epoch time: 19.36 s +2024-11-22 15:08:00.334140: +2024-11-22 15:08:00.334574: Epoch 5134 +2024-11-22 15:08:00.334713: Current learning rate: 0.00397 +2024-11-22 15:08:20.916579: train_loss -0.7953 +2024-11-22 15:08:20.923355: val_loss -0.7869 +2024-11-22 15:08:20.923503: Pseudo dice [0.8537] +2024-11-22 15:08:20.923607: Epoch time: 20.58 s +2024-11-22 15:08:21.844784: +2024-11-22 15:08:21.845221: Epoch 5135 +2024-11-22 15:08:21.845353: Current learning rate: 0.00397 +2024-11-22 15:08:41.038316: train_loss -0.7907 +2024-11-22 15:08:41.043901: val_loss -0.8017 +2024-11-22 15:08:41.044022: Pseudo dice [0.8555] +2024-11-22 15:08:41.044112: Epoch time: 19.19 s +2024-11-22 15:08:41.965956: +2024-11-22 15:08:41.967030: Epoch 5136 +2024-11-22 15:08:41.967161: Current learning rate: 0.00397 +2024-11-22 15:09:01.870275: train_loss -0.8032 +2024-11-22 15:09:01.874931: val_loss -0.7847 +2024-11-22 15:09:01.875072: Pseudo dice [0.845] +2024-11-22 15:09:01.875185: Epoch time: 19.91 s +2024-11-22 15:09:02.887161: +2024-11-22 15:09:02.888264: Epoch 5137 +2024-11-22 15:09:02.888388: Current learning rate: 0.00397 +2024-11-22 15:09:23.185366: train_loss -0.8023 +2024-11-22 15:09:23.188126: val_loss -0.7775 +2024-11-22 15:09:23.188264: Pseudo dice [0.8618] +2024-11-22 15:09:23.200464: Epoch time: 20.3 s +2024-11-22 15:09:24.150908: +2024-11-22 15:09:24.152076: Epoch 5138 +2024-11-22 15:09:24.152208: Current learning rate: 0.00396 +2024-11-22 15:09:43.459869: train_loss -0.7894 +2024-11-22 15:09:43.468718: val_loss -0.7676 +2024-11-22 15:09:43.468869: Pseudo dice [0.8539] +2024-11-22 15:09:43.468959: Epoch time: 19.31 s +2024-11-22 15:09:44.409930: +2024-11-22 15:09:44.410871: Epoch 5139 +2024-11-22 15:09:44.410989: Current learning rate: 0.00396 +2024-11-22 15:10:03.518802: train_loss -0.8046 +2024-11-22 15:10:03.525647: val_loss -0.7798 +2024-11-22 15:10:03.525772: Pseudo dice [0.8537] +2024-11-22 15:10:03.525869: Epoch time: 19.11 s +2024-11-22 15:10:05.063359: +2024-11-22 15:10:05.064768: Epoch 5140 +2024-11-22 15:10:05.064905: Current learning rate: 0.00396 +2024-11-22 15:10:24.862154: train_loss -0.7912 +2024-11-22 15:10:24.871237: val_loss -0.773 +2024-11-22 15:10:24.871373: Pseudo dice [0.861] +2024-11-22 15:10:24.871476: Epoch time: 19.8 s +2024-11-22 15:10:25.908471: +2024-11-22 15:10:25.910177: Epoch 5141 +2024-11-22 15:10:25.910323: Current learning rate: 0.00396 +2024-11-22 15:10:44.001388: train_loss -0.7931 +2024-11-22 15:10:44.007475: val_loss -0.7765 +2024-11-22 15:10:44.007610: Pseudo dice [0.8537] +2024-11-22 15:10:44.007700: Epoch time: 18.09 s +2024-11-22 15:10:44.897039: +2024-11-22 15:10:44.897803: Epoch 5142 +2024-11-22 15:10:44.897936: Current learning rate: 0.00396 +2024-11-22 15:11:04.372715: train_loss -0.7963 +2024-11-22 15:11:04.377302: val_loss -0.7612 +2024-11-22 15:11:04.377440: Pseudo dice [0.8532] +2024-11-22 15:11:04.377536: Epoch time: 19.47 s +2024-11-22 15:11:05.401504: +2024-11-22 15:11:05.402710: Epoch 5143 +2024-11-22 15:11:05.402831: Current learning rate: 0.00396 +2024-11-22 15:11:24.839086: train_loss -0.8043 +2024-11-22 15:11:24.844742: val_loss -0.7873 +2024-11-22 15:11:24.844863: Pseudo dice [0.8608] +2024-11-22 15:11:24.844966: Epoch time: 19.44 s +2024-11-22 15:11:25.727479: +2024-11-22 15:11:25.728897: Epoch 5144 +2024-11-22 15:11:25.729031: Current learning rate: 0.00396 +2024-11-22 15:11:44.838737: train_loss -0.7998 +2024-11-22 15:11:44.844811: val_loss -0.7644 +2024-11-22 15:11:44.844951: Pseudo dice [0.8447] +2024-11-22 15:11:44.845048: Epoch time: 19.11 s +2024-11-22 15:11:45.696991: +2024-11-22 15:11:45.698369: Epoch 5145 +2024-11-22 15:11:45.698511: Current learning rate: 0.00396 +2024-11-22 15:12:05.368293: train_loss -0.7984 +2024-11-22 15:12:05.377795: val_loss -0.7558 +2024-11-22 15:12:05.377944: Pseudo dice [0.851] +2024-11-22 15:12:05.378046: Epoch time: 19.67 s +2024-11-22 15:12:06.274194: +2024-11-22 15:12:06.276080: Epoch 5146 +2024-11-22 15:12:06.276225: Current learning rate: 0.00395 +2024-11-22 15:12:25.260851: train_loss -0.8011 +2024-11-22 15:12:25.262842: val_loss -0.7702 +2024-11-22 15:12:25.262960: Pseudo dice [0.8575] +2024-11-22 15:12:25.263075: Epoch time: 18.99 s +2024-11-22 15:12:26.124801: +2024-11-22 15:12:26.126570: Epoch 5147 +2024-11-22 15:12:26.126706: Current learning rate: 0.00395 +2024-11-22 15:12:45.147675: train_loss -0.7936 +2024-11-22 15:12:45.161531: val_loss -0.7698 +2024-11-22 15:12:45.161672: Pseudo dice [0.857] +2024-11-22 15:12:45.161795: Epoch time: 19.02 s +2024-11-22 15:12:46.126624: +2024-11-22 15:12:46.127426: Epoch 5148 +2024-11-22 15:12:46.127543: Current learning rate: 0.00395 +2024-11-22 15:13:05.639237: train_loss -0.7961 +2024-11-22 15:13:05.643017: val_loss -0.7514 +2024-11-22 15:13:05.643158: Pseudo dice [0.8627] +2024-11-22 15:13:05.643263: Epoch time: 19.51 s +2024-11-22 15:13:06.739447: +2024-11-22 15:13:06.740861: Epoch 5149 +2024-11-22 15:13:06.740997: Current learning rate: 0.00395 +2024-11-22 15:13:27.194613: train_loss -0.783 +2024-11-22 15:13:27.201858: val_loss -0.7699 +2024-11-22 15:13:27.201994: Pseudo dice [0.8464] +2024-11-22 15:13:27.202126: Epoch time: 20.46 s +2024-11-22 15:13:28.362836: +2024-11-22 15:13:28.364501: Epoch 5150 +2024-11-22 15:13:28.364634: Current learning rate: 0.00395 +2024-11-22 15:13:47.572399: train_loss -0.7877 +2024-11-22 15:13:47.624412: val_loss -0.7428 +2024-11-22 15:13:47.624582: Pseudo dice [0.8471] +2024-11-22 15:13:47.624675: Epoch time: 19.21 s +2024-11-22 15:13:48.894714: +2024-11-22 15:13:48.896539: Epoch 5151 +2024-11-22 15:13:48.896672: Current learning rate: 0.00395 +2024-11-22 15:14:07.603746: train_loss -0.794 +2024-11-22 15:14:07.610850: val_loss -0.7602 +2024-11-22 15:14:07.610994: Pseudo dice [0.8508] +2024-11-22 15:14:07.611113: Epoch time: 18.71 s +2024-11-22 15:14:08.511216: +2024-11-22 15:14:08.511447: Epoch 5152 +2024-11-22 15:14:08.511567: Current learning rate: 0.00395 +2024-11-22 15:14:28.476657: train_loss -0.7872 +2024-11-22 15:14:28.479109: val_loss -0.7663 +2024-11-22 15:14:28.479227: Pseudo dice [0.8587] +2024-11-22 15:14:28.479310: Epoch time: 19.97 s +2024-11-22 15:14:29.339881: +2024-11-22 15:14:29.340429: Epoch 5153 +2024-11-22 15:14:29.340548: Current learning rate: 0.00395 +2024-11-22 15:14:49.720750: train_loss -0.7891 +2024-11-22 15:14:49.726567: val_loss -0.7816 +2024-11-22 15:14:49.726687: Pseudo dice [0.8551] +2024-11-22 15:14:49.726794: Epoch time: 20.38 s +2024-11-22 15:14:50.609453: +2024-11-22 15:14:50.610310: Epoch 5154 +2024-11-22 15:14:50.610429: Current learning rate: 0.00394 +2024-11-22 15:15:09.607689: train_loss -0.803 +2024-11-22 15:15:09.613868: val_loss -0.7797 +2024-11-22 15:15:09.614016: Pseudo dice [0.8614] +2024-11-22 15:15:09.614119: Epoch time: 19.0 s +2024-11-22 15:15:10.498815: +2024-11-22 15:15:10.499906: Epoch 5155 +2024-11-22 15:15:10.500032: Current learning rate: 0.00394 +2024-11-22 15:15:30.586523: train_loss -0.7955 +2024-11-22 15:15:30.601938: val_loss -0.782 +2024-11-22 15:15:30.602166: Pseudo dice [0.858] +2024-11-22 15:15:30.602273: Epoch time: 20.09 s +2024-11-22 15:15:31.471413: +2024-11-22 15:15:31.472631: Epoch 5156 +2024-11-22 15:15:31.472747: Current learning rate: 0.00394 +2024-11-22 15:15:49.647806: train_loss -0.7668 +2024-11-22 15:15:49.654329: val_loss -0.7251 +2024-11-22 15:15:49.654461: Pseudo dice [0.8317] +2024-11-22 15:15:49.654561: Epoch time: 18.18 s +2024-11-22 15:15:50.582463: +2024-11-22 15:15:50.583337: Epoch 5157 +2024-11-22 15:15:50.583477: Current learning rate: 0.00394 +2024-11-22 15:16:09.637812: train_loss -0.7758 +2024-11-22 15:16:09.645827: val_loss -0.7741 +2024-11-22 15:16:09.646055: Pseudo dice [0.8565] +2024-11-22 15:16:09.646183: Epoch time: 19.06 s +2024-11-22 15:16:10.632547: +2024-11-22 15:16:10.633704: Epoch 5158 +2024-11-22 15:16:10.633835: Current learning rate: 0.00394 +2024-11-22 15:16:29.784860: train_loss -0.7786 +2024-11-22 15:16:29.792098: val_loss -0.7757 +2024-11-22 15:16:29.792228: Pseudo dice [0.855] +2024-11-22 15:16:29.792324: Epoch time: 19.15 s +2024-11-22 15:16:30.665228: +2024-11-22 15:16:30.665956: Epoch 5159 +2024-11-22 15:16:30.666109: Current learning rate: 0.00394 +2024-11-22 15:16:50.177178: train_loss -0.7882 +2024-11-22 15:16:50.180219: val_loss -0.7582 +2024-11-22 15:16:50.180336: Pseudo dice [0.8514] +2024-11-22 15:16:50.180452: Epoch time: 19.51 s +2024-11-22 15:16:51.039111: +2024-11-22 15:16:51.041968: Epoch 5160 +2024-11-22 15:16:51.042099: Current learning rate: 0.00394 +2024-11-22 15:17:09.600411: train_loss -0.8017 +2024-11-22 15:17:09.606520: val_loss -0.7954 +2024-11-22 15:17:09.606650: Pseudo dice [0.859] +2024-11-22 15:17:09.606742: Epoch time: 18.56 s +2024-11-22 15:17:10.646693: +2024-11-22 15:17:10.647227: Epoch 5161 +2024-11-22 15:17:10.647364: Current learning rate: 0.00394 +2024-11-22 15:17:30.088163: train_loss -0.7902 +2024-11-22 15:17:30.092414: val_loss -0.7612 +2024-11-22 15:17:30.092532: Pseudo dice [0.8479] +2024-11-22 15:17:30.092615: Epoch time: 19.44 s +2024-11-22 15:17:31.491029: +2024-11-22 15:17:31.492449: Epoch 5162 +2024-11-22 15:17:31.492584: Current learning rate: 0.00393 +2024-11-22 15:17:49.983645: train_loss -0.786 +2024-11-22 15:17:49.990326: val_loss -0.7609 +2024-11-22 15:17:49.990471: Pseudo dice [0.8491] +2024-11-22 15:17:49.990565: Epoch time: 18.49 s +2024-11-22 15:17:50.911728: +2024-11-22 15:17:50.912166: Epoch 5163 +2024-11-22 15:17:50.912296: Current learning rate: 0.00393 +2024-11-22 15:18:10.743012: train_loss -0.7752 +2024-11-22 15:18:10.745486: val_loss -0.7727 +2024-11-22 15:18:10.745605: Pseudo dice [0.8476] +2024-11-22 15:18:10.745708: Epoch time: 19.83 s +2024-11-22 15:18:11.611173: +2024-11-22 15:18:11.611731: Epoch 5164 +2024-11-22 15:18:11.611848: Current learning rate: 0.00393 +2024-11-22 15:18:30.776748: train_loss -0.7936 +2024-11-22 15:18:30.783289: val_loss -0.7754 +2024-11-22 15:18:30.783419: Pseudo dice [0.8467] +2024-11-22 15:18:30.783516: Epoch time: 19.17 s +2024-11-22 15:18:31.815187: +2024-11-22 15:18:31.816187: Epoch 5165 +2024-11-22 15:18:31.816318: Current learning rate: 0.00393 +2024-11-22 15:18:50.410544: train_loss -0.7913 +2024-11-22 15:18:50.424289: val_loss -0.7586 +2024-11-22 15:18:50.424435: Pseudo dice [0.8359] +2024-11-22 15:18:50.424545: Epoch time: 18.6 s +2024-11-22 15:18:51.393840: +2024-11-22 15:18:51.394103: Epoch 5166 +2024-11-22 15:18:51.394236: Current learning rate: 0.00393 +2024-11-22 15:19:09.988190: train_loss -0.7949 +2024-11-22 15:19:09.992757: val_loss -0.7862 +2024-11-22 15:19:09.992919: Pseudo dice [0.8559] +2024-11-22 15:19:09.993038: Epoch time: 18.6 s +2024-11-22 15:19:10.866816: +2024-11-22 15:19:10.867041: Epoch 5167 +2024-11-22 15:19:10.867171: Current learning rate: 0.00393 +2024-11-22 15:19:29.760518: train_loss -0.7912 +2024-11-22 15:19:29.761299: val_loss -0.7834 +2024-11-22 15:19:29.761418: Pseudo dice [0.8622] +2024-11-22 15:19:29.761527: Epoch time: 18.89 s +2024-11-22 15:19:30.669642: +2024-11-22 15:19:30.669861: Epoch 5168 +2024-11-22 15:19:30.669993: Current learning rate: 0.00393 +2024-11-22 15:19:49.543297: train_loss -0.7989 +2024-11-22 15:19:49.547109: val_loss -0.7982 +2024-11-22 15:19:49.547303: Pseudo dice [0.8615] +2024-11-22 15:19:49.547404: Epoch time: 18.87 s +2024-11-22 15:19:50.557522: +2024-11-22 15:19:50.557731: Epoch 5169 +2024-11-22 15:19:50.557862: Current learning rate: 0.00393 +2024-11-22 15:20:08.741871: train_loss -0.7994 +2024-11-22 15:20:08.742898: val_loss -0.7707 +2024-11-22 15:20:08.743037: Pseudo dice [0.8668] +2024-11-22 15:20:08.743189: Epoch time: 18.19 s +2024-11-22 15:20:09.718913: +2024-11-22 15:20:09.719122: Epoch 5170 +2024-11-22 15:20:09.719240: Current learning rate: 0.00392 +2024-11-22 15:20:28.305173: train_loss -0.8025 +2024-11-22 15:20:28.307063: val_loss -0.7719 +2024-11-22 15:20:28.307203: Pseudo dice [0.8492] +2024-11-22 15:20:28.307317: Epoch time: 18.59 s +2024-11-22 15:20:29.171472: +2024-11-22 15:20:29.171664: Epoch 5171 +2024-11-22 15:20:29.171781: Current learning rate: 0.00392 +2024-11-22 15:20:48.790050: train_loss -0.8016 +2024-11-22 15:20:48.796618: val_loss -0.7829 +2024-11-22 15:20:48.796777: Pseudo dice [0.8611] +2024-11-22 15:20:48.796881: Epoch time: 19.62 s +2024-11-22 15:20:49.675503: +2024-11-22 15:20:49.675748: Epoch 5172 +2024-11-22 15:20:49.675886: Current learning rate: 0.00392 +2024-11-22 15:21:08.504475: train_loss -0.792 +2024-11-22 15:21:08.510488: val_loss -0.7656 +2024-11-22 15:21:08.510652: Pseudo dice [0.853] +2024-11-22 15:21:08.512321: Epoch time: 18.83 s +2024-11-22 15:21:09.650744: +2024-11-22 15:21:09.650943: Epoch 5173 +2024-11-22 15:21:09.651078: Current learning rate: 0.00392 +2024-11-22 15:21:28.146474: train_loss -0.8054 +2024-11-22 15:21:28.147997: val_loss -0.7732 +2024-11-22 15:21:28.148139: Pseudo dice [0.8573] +2024-11-22 15:21:28.148233: Epoch time: 18.5 s +2024-11-22 15:21:29.489603: +2024-11-22 15:21:29.489839: Epoch 5174 +2024-11-22 15:21:29.489971: Current learning rate: 0.00392 +2024-11-22 15:21:47.918506: train_loss -0.8016 +2024-11-22 15:21:47.924502: val_loss -0.7803 +2024-11-22 15:21:47.924622: Pseudo dice [0.8599] +2024-11-22 15:21:47.924708: Epoch time: 18.43 s +2024-11-22 15:21:48.790738: +2024-11-22 15:21:48.791175: Epoch 5175 +2024-11-22 15:21:48.791301: Current learning rate: 0.00392 +2024-11-22 15:22:08.400372: train_loss -0.8005 +2024-11-22 15:22:08.408435: val_loss -0.7633 +2024-11-22 15:22:08.408553: Pseudo dice [0.8507] +2024-11-22 15:22:08.408664: Epoch time: 19.61 s +2024-11-22 15:22:09.282970: +2024-11-22 15:22:09.283633: Epoch 5176 +2024-11-22 15:22:09.283785: Current learning rate: 0.00392 +2024-11-22 15:22:29.299291: train_loss -0.7991 +2024-11-22 15:22:29.305570: val_loss -0.781 +2024-11-22 15:22:29.305705: Pseudo dice [0.8603] +2024-11-22 15:22:29.305825: Epoch time: 20.02 s +2024-11-22 15:22:30.203050: +2024-11-22 15:22:30.204211: Epoch 5177 +2024-11-22 15:22:30.204348: Current learning rate: 0.00392 +2024-11-22 15:22:49.706275: train_loss -0.7987 +2024-11-22 15:22:49.709589: val_loss -0.7484 +2024-11-22 15:22:49.709691: Pseudo dice [0.8573] +2024-11-22 15:22:49.709788: Epoch time: 19.5 s +2024-11-22 15:22:50.575742: +2024-11-22 15:22:50.576726: Epoch 5178 +2024-11-22 15:22:50.576859: Current learning rate: 0.00391 +2024-11-22 15:23:09.163460: train_loss -0.7961 +2024-11-22 15:23:09.173119: val_loss -0.7634 +2024-11-22 15:23:09.173267: Pseudo dice [0.8537] +2024-11-22 15:23:09.173356: Epoch time: 18.59 s +2024-11-22 15:23:10.049895: +2024-11-22 15:23:10.051204: Epoch 5179 +2024-11-22 15:23:10.051339: Current learning rate: 0.00391 +2024-11-22 15:23:29.860129: train_loss -0.7909 +2024-11-22 15:23:29.869186: val_loss -0.7719 +2024-11-22 15:23:29.869328: Pseudo dice [0.8589] +2024-11-22 15:23:29.869433: Epoch time: 19.81 s +2024-11-22 15:23:30.744979: +2024-11-22 15:23:30.746859: Epoch 5180 +2024-11-22 15:23:30.747000: Current learning rate: 0.00391 +2024-11-22 15:23:50.350634: train_loss -0.8 +2024-11-22 15:23:50.356324: val_loss -0.8078 +2024-11-22 15:23:50.356475: Pseudo dice [0.8678] +2024-11-22 15:23:50.356595: Epoch time: 19.61 s +2024-11-22 15:23:51.413848: +2024-11-22 15:23:51.415387: Epoch 5181 +2024-11-22 15:23:51.415510: Current learning rate: 0.00391 +2024-11-22 15:24:10.679157: train_loss -0.799 +2024-11-22 15:24:10.690540: val_loss -0.7982 +2024-11-22 15:24:10.690667: Pseudo dice [0.8624] +2024-11-22 15:24:10.690773: Epoch time: 19.27 s +2024-11-22 15:24:11.547902: +2024-11-22 15:24:11.549727: Epoch 5182 +2024-11-22 15:24:11.549857: Current learning rate: 0.00391 +2024-11-22 15:24:31.037087: train_loss -0.8012 +2024-11-22 15:24:31.043198: val_loss -0.7827 +2024-11-22 15:24:31.043330: Pseudo dice [0.866] +2024-11-22 15:24:31.043647: Epoch time: 19.49 s +2024-11-22 15:24:31.043845: Yayy! New best EMA pseudo Dice: 0.8582 +2024-11-22 15:24:32.329410: +2024-11-22 15:24:32.331163: Epoch 5183 +2024-11-22 15:24:32.331294: Current learning rate: 0.00391 +2024-11-22 15:24:52.529698: train_loss -0.7956 +2024-11-22 15:24:52.536170: val_loss -0.7514 +2024-11-22 15:24:52.536301: Pseudo dice [0.8512] +2024-11-22 15:24:52.536392: Epoch time: 20.2 s +2024-11-22 15:24:53.437673: +2024-11-22 15:24:53.439472: Epoch 5184 +2024-11-22 15:24:53.439597: Current learning rate: 0.00391 +2024-11-22 15:25:13.150139: train_loss -0.7944 +2024-11-22 15:25:13.158002: val_loss -0.7822 +2024-11-22 15:25:13.158151: Pseudo dice [0.8566] +2024-11-22 15:25:13.158265: Epoch time: 19.71 s +2024-11-22 15:25:14.527747: +2024-11-22 15:25:14.529493: Epoch 5185 +2024-11-22 15:25:14.529613: Current learning rate: 0.00391 +2024-11-22 15:25:33.333681: train_loss -0.7951 +2024-11-22 15:25:33.340467: val_loss -0.7853 +2024-11-22 15:25:33.340592: Pseudo dice [0.8483] +2024-11-22 15:25:33.340702: Epoch time: 18.81 s +2024-11-22 15:25:34.392940: +2024-11-22 15:25:34.394322: Epoch 5186 +2024-11-22 15:25:34.394447: Current learning rate: 0.0039 +2024-11-22 15:25:55.418419: train_loss -0.8027 +2024-11-22 15:25:55.427982: val_loss -0.7677 +2024-11-22 15:25:55.428114: Pseudo dice [0.845] +2024-11-22 15:25:55.428212: Epoch time: 21.03 s +2024-11-22 15:25:56.333578: +2024-11-22 15:25:56.334148: Epoch 5187 +2024-11-22 15:25:56.334273: Current learning rate: 0.0039 +2024-11-22 15:26:15.714715: train_loss -0.7892 +2024-11-22 15:26:15.727085: val_loss -0.7572 +2024-11-22 15:26:15.727208: Pseudo dice [0.8604] +2024-11-22 15:26:15.727296: Epoch time: 19.38 s +2024-11-22 15:26:16.788003: +2024-11-22 15:26:16.789906: Epoch 5188 +2024-11-22 15:26:16.790047: Current learning rate: 0.0039 +2024-11-22 15:26:36.111628: train_loss -0.7984 +2024-11-22 15:26:36.124770: val_loss -0.7876 +2024-11-22 15:26:36.124929: Pseudo dice [0.8589] +2024-11-22 15:26:36.125030: Epoch time: 19.32 s +2024-11-22 15:26:37.154930: +2024-11-22 15:26:37.155482: Epoch 5189 +2024-11-22 15:26:37.155601: Current learning rate: 0.0039 +2024-11-22 15:26:56.504406: train_loss -0.8033 +2024-11-22 15:26:56.514310: val_loss -0.7803 +2024-11-22 15:26:56.514432: Pseudo dice [0.847] +2024-11-22 15:26:56.514813: Epoch time: 19.35 s +2024-11-22 15:26:57.566372: +2024-11-22 15:26:57.567048: Epoch 5190 +2024-11-22 15:26:57.567167: Current learning rate: 0.0039 +2024-11-22 15:27:16.440751: train_loss -0.7966 +2024-11-22 15:27:16.454934: val_loss -0.7836 +2024-11-22 15:27:16.455180: Pseudo dice [0.8464] +2024-11-22 15:27:16.455280: Epoch time: 18.87 s +2024-11-22 15:27:17.433600: +2024-11-22 15:27:17.433815: Epoch 5191 +2024-11-22 15:27:17.433938: Current learning rate: 0.0039 +2024-11-22 15:27:36.008488: train_loss -0.7973 +2024-11-22 15:27:36.018027: val_loss -0.7521 +2024-11-22 15:27:36.018185: Pseudo dice [0.8582] +2024-11-22 15:27:36.018290: Epoch time: 18.58 s +2024-11-22 15:27:36.883956: +2024-11-22 15:27:36.886730: Epoch 5192 +2024-11-22 15:27:36.886878: Current learning rate: 0.0039 +2024-11-22 15:27:56.998776: train_loss -0.8081 +2024-11-22 15:27:57.001502: val_loss -0.776 +2024-11-22 15:27:57.001648: Pseudo dice [0.8437] +2024-11-22 15:27:57.001770: Epoch time: 20.12 s +2024-11-22 15:27:57.905076: +2024-11-22 15:27:57.905916: Epoch 5193 +2024-11-22 15:27:57.906053: Current learning rate: 0.0039 +2024-11-22 15:28:17.720371: train_loss -0.8017 +2024-11-22 15:28:17.743329: val_loss -0.7693 +2024-11-22 15:28:17.743503: Pseudo dice [0.8435] +2024-11-22 15:28:17.743601: Epoch time: 19.82 s +2024-11-22 15:28:18.829759: +2024-11-22 15:28:18.831526: Epoch 5194 +2024-11-22 15:28:18.831653: Current learning rate: 0.00389 +2024-11-22 15:28:37.688130: train_loss -0.8002 +2024-11-22 15:28:37.690662: val_loss -0.7816 +2024-11-22 15:28:37.690770: Pseudo dice [0.8465] +2024-11-22 15:28:37.690882: Epoch time: 18.86 s +2024-11-22 15:28:38.552427: +2024-11-22 15:28:38.553237: Epoch 5195 +2024-11-22 15:28:38.553366: Current learning rate: 0.00389 +2024-11-22 15:28:57.848726: train_loss -0.7989 +2024-11-22 15:28:57.854988: val_loss -0.7798 +2024-11-22 15:28:57.855145: Pseudo dice [0.8467] +2024-11-22 15:28:57.855241: Epoch time: 19.3 s +2024-11-22 15:28:59.270460: +2024-11-22 15:28:59.271843: Epoch 5196 +2024-11-22 15:28:59.271986: Current learning rate: 0.00389 +2024-11-22 15:29:18.489807: train_loss -0.793 +2024-11-22 15:29:18.498476: val_loss -0.7675 +2024-11-22 15:29:18.498618: Pseudo dice [0.852] +2024-11-22 15:29:18.498722: Epoch time: 19.22 s +2024-11-22 15:29:19.466409: +2024-11-22 15:29:19.467616: Epoch 5197 +2024-11-22 15:29:19.467741: Current learning rate: 0.00389 +2024-11-22 15:29:38.657755: train_loss -0.8031 +2024-11-22 15:29:38.664725: val_loss -0.7913 +2024-11-22 15:29:38.664866: Pseudo dice [0.8466] +2024-11-22 15:29:38.664958: Epoch time: 19.19 s +2024-11-22 15:29:39.628019: +2024-11-22 15:29:39.629937: Epoch 5198 +2024-11-22 15:29:39.630087: Current learning rate: 0.00389 +2024-11-22 15:29:59.236187: train_loss -0.7922 +2024-11-22 15:29:59.252771: val_loss -0.793 +2024-11-22 15:29:59.252909: Pseudo dice [0.8575] +2024-11-22 15:29:59.253001: Epoch time: 19.61 s +2024-11-22 15:30:00.267480: +2024-11-22 15:30:00.268082: Epoch 5199 +2024-11-22 15:30:00.268214: Current learning rate: 0.00389 +2024-11-22 15:30:20.065018: train_loss -0.7983 +2024-11-22 15:30:20.067993: val_loss -0.7804 +2024-11-22 15:30:20.068112: Pseudo dice [0.8621] +2024-11-22 15:30:20.068220: Epoch time: 19.8 s +2024-11-22 15:30:21.571719: +2024-11-22 15:30:21.573448: Epoch 5200 +2024-11-22 15:30:21.573582: Current learning rate: 0.00389 +2024-11-22 15:30:40.718833: train_loss -0.794 +2024-11-22 15:30:40.726177: val_loss -0.7626 +2024-11-22 15:30:40.726309: Pseudo dice [0.8481] +2024-11-22 15:30:40.726419: Epoch time: 19.15 s +2024-11-22 15:30:41.791443: +2024-11-22 15:30:41.791898: Epoch 5201 +2024-11-22 15:30:41.792252: Current learning rate: 0.00389 +2024-11-22 15:31:00.406908: train_loss -0.7858 +2024-11-22 15:31:00.411975: val_loss -0.7464 +2024-11-22 15:31:00.412105: Pseudo dice [0.8426] +2024-11-22 15:31:00.412210: Epoch time: 18.62 s +2024-11-22 15:31:01.520803: +2024-11-22 15:31:01.521049: Epoch 5202 +2024-11-22 15:31:01.521203: Current learning rate: 0.00388 +2024-11-22 15:31:21.273556: train_loss -0.8002 +2024-11-22 15:31:21.282711: val_loss -0.7669 +2024-11-22 15:31:21.282852: Pseudo dice [0.8413] +2024-11-22 15:31:21.282963: Epoch time: 19.75 s +2024-11-22 15:31:22.169794: +2024-11-22 15:31:22.170927: Epoch 5203 +2024-11-22 15:31:22.171077: Current learning rate: 0.00388 +2024-11-22 15:31:41.005730: train_loss -0.8041 +2024-11-22 15:31:41.021095: val_loss -0.792 +2024-11-22 15:31:41.021231: Pseudo dice [0.8594] +2024-11-22 15:31:41.021341: Epoch time: 18.84 s +2024-11-22 15:31:41.989267: +2024-11-22 15:31:41.991271: Epoch 5204 +2024-11-22 15:31:41.991391: Current learning rate: 0.00388 +2024-11-22 15:32:02.170710: train_loss -0.8016 +2024-11-22 15:32:02.186216: val_loss -0.7987 +2024-11-22 15:32:02.186337: Pseudo dice [0.8534] +2024-11-22 15:32:02.186426: Epoch time: 20.18 s +2024-11-22 15:32:03.223176: +2024-11-22 15:32:03.224769: Epoch 5205 +2024-11-22 15:32:03.224895: Current learning rate: 0.00388 +2024-11-22 15:32:22.174983: train_loss -0.7944 +2024-11-22 15:32:22.189595: val_loss -0.7611 +2024-11-22 15:32:22.189722: Pseudo dice [0.8444] +2024-11-22 15:32:22.189807: Epoch time: 18.95 s +2024-11-22 15:32:23.170380: +2024-11-22 15:32:23.171230: Epoch 5206 +2024-11-22 15:32:23.171355: Current learning rate: 0.00388 +2024-11-22 15:32:42.375332: train_loss -0.8009 +2024-11-22 15:32:42.379039: val_loss -0.761 +2024-11-22 15:32:42.379281: Pseudo dice [0.8526] +2024-11-22 15:32:42.379387: Epoch time: 19.21 s +2024-11-22 15:32:43.716285: +2024-11-22 15:32:43.718680: Epoch 5207 +2024-11-22 15:32:43.718825: Current learning rate: 0.00388 +2024-11-22 15:33:02.730253: train_loss -0.7831 +2024-11-22 15:33:02.737188: val_loss -0.7529 +2024-11-22 15:33:02.737331: Pseudo dice [0.8389] +2024-11-22 15:33:02.737434: Epoch time: 19.01 s +2024-11-22 15:33:03.627977: +2024-11-22 15:33:03.629416: Epoch 5208 +2024-11-22 15:33:03.629540: Current learning rate: 0.00388 +2024-11-22 15:33:23.129462: train_loss -0.7947 +2024-11-22 15:33:23.140644: val_loss -0.7858 +2024-11-22 15:33:23.140793: Pseudo dice [0.8519] +2024-11-22 15:33:23.140897: Epoch time: 19.5 s +2024-11-22 15:33:24.027734: +2024-11-22 15:33:24.028636: Epoch 5209 +2024-11-22 15:33:24.028770: Current learning rate: 0.00388 +2024-11-22 15:33:42.903075: train_loss -0.7922 +2024-11-22 15:33:42.907077: val_loss -0.7699 +2024-11-22 15:33:42.907221: Pseudo dice [0.8389] +2024-11-22 15:33:42.907316: Epoch time: 18.88 s +2024-11-22 15:33:43.828936: +2024-11-22 15:33:43.829869: Epoch 5210 +2024-11-22 15:33:43.829986: Current learning rate: 0.00387 +2024-11-22 15:34:03.832431: train_loss -0.7943 +2024-11-22 15:34:03.843893: val_loss -0.7802 +2024-11-22 15:34:03.844073: Pseudo dice [0.8515] +2024-11-22 15:34:03.844178: Epoch time: 20.0 s +2024-11-22 15:34:04.765697: +2024-11-22 15:34:04.769761: Epoch 5211 +2024-11-22 15:34:04.769890: Current learning rate: 0.00387 +2024-11-22 15:34:24.625997: train_loss -0.795 +2024-11-22 15:34:24.631251: val_loss -0.7928 +2024-11-22 15:34:24.631391: Pseudo dice [0.8432] +2024-11-22 15:34:24.631484: Epoch time: 19.86 s +2024-11-22 15:34:25.608349: +2024-11-22 15:34:25.609003: Epoch 5212 +2024-11-22 15:34:25.609137: Current learning rate: 0.00387 +2024-11-22 15:34:45.499937: train_loss -0.7921 +2024-11-22 15:34:45.506495: val_loss -0.7346 +2024-11-22 15:34:45.506642: Pseudo dice [0.8427] +2024-11-22 15:34:45.506737: Epoch time: 19.89 s +2024-11-22 15:34:46.512285: +2024-11-22 15:34:46.512747: Epoch 5213 +2024-11-22 15:34:46.512876: Current learning rate: 0.00387 +2024-11-22 15:35:05.871245: train_loss -0.7912 +2024-11-22 15:35:05.895052: val_loss -0.7702 +2024-11-22 15:35:05.895221: Pseudo dice [0.8488] +2024-11-22 15:35:05.895585: Epoch time: 19.36 s +2024-11-22 15:35:06.896568: +2024-11-22 15:35:06.897404: Epoch 5214 +2024-11-22 15:35:06.897543: Current learning rate: 0.00387 +2024-11-22 15:35:25.344589: train_loss -0.7886 +2024-11-22 15:35:25.351322: val_loss -0.7829 +2024-11-22 15:35:25.351527: Pseudo dice [0.848] +2024-11-22 15:35:25.351621: Epoch time: 18.45 s +2024-11-22 15:35:26.252185: +2024-11-22 15:35:26.252780: Epoch 5215 +2024-11-22 15:35:26.252912: Current learning rate: 0.00387 +2024-11-22 15:35:45.996816: train_loss -0.7941 +2024-11-22 15:35:46.009182: val_loss -0.7652 +2024-11-22 15:35:46.009622: Pseudo dice [0.8395] +2024-11-22 15:35:46.009749: Epoch time: 19.75 s +2024-11-22 15:35:46.918669: +2024-11-22 15:35:46.919949: Epoch 5216 +2024-11-22 15:35:46.920093: Current learning rate: 0.00387 +2024-11-22 15:36:06.745212: train_loss -0.7931 +2024-11-22 15:36:06.753775: val_loss -0.765 +2024-11-22 15:36:06.753921: Pseudo dice [0.8466] +2024-11-22 15:36:06.754017: Epoch time: 19.83 s +2024-11-22 15:36:07.667581: +2024-11-22 15:36:07.669670: Epoch 5217 +2024-11-22 15:36:07.669880: Current learning rate: 0.00387 +2024-11-22 15:36:28.697502: train_loss -0.7963 +2024-11-22 15:36:28.703745: val_loss -0.7896 +2024-11-22 15:36:28.703857: Pseudo dice [0.8653] +2024-11-22 15:36:28.703951: Epoch time: 21.03 s +2024-11-22 15:36:30.042172: +2024-11-22 15:36:30.043838: Epoch 5218 +2024-11-22 15:36:30.043967: Current learning rate: 0.00386 +2024-11-22 15:36:50.209788: train_loss -0.7864 +2024-11-22 15:36:50.215998: val_loss -0.7755 +2024-11-22 15:36:50.216129: Pseudo dice [0.8502] +2024-11-22 15:36:50.216227: Epoch time: 20.17 s +2024-11-22 15:36:51.131205: +2024-11-22 15:36:51.132148: Epoch 5219 +2024-11-22 15:36:51.132282: Current learning rate: 0.00386 +2024-11-22 15:37:10.982810: train_loss -0.7919 +2024-11-22 15:37:10.989390: val_loss -0.7762 +2024-11-22 15:37:10.989537: Pseudo dice [0.8606] +2024-11-22 15:37:10.989645: Epoch time: 19.85 s +2024-11-22 15:37:11.928950: +2024-11-22 15:37:11.929555: Epoch 5220 +2024-11-22 15:37:11.929694: Current learning rate: 0.00386 +2024-11-22 15:37:31.827086: train_loss -0.7949 +2024-11-22 15:37:31.833983: val_loss -0.7757 +2024-11-22 15:37:31.834122: Pseudo dice [0.8453] +2024-11-22 15:37:31.834215: Epoch time: 19.9 s +2024-11-22 15:37:32.979153: +2024-11-22 15:37:32.980689: Epoch 5221 +2024-11-22 15:37:32.980812: Current learning rate: 0.00386 +2024-11-22 15:37:52.740503: train_loss -0.8006 +2024-11-22 15:37:52.746573: val_loss -0.7636 +2024-11-22 15:37:52.746691: Pseudo dice [0.8561] +2024-11-22 15:37:52.746776: Epoch time: 19.76 s +2024-11-22 15:37:53.799891: +2024-11-22 15:37:53.801564: Epoch 5222 +2024-11-22 15:37:53.801689: Current learning rate: 0.00386 +2024-11-22 15:38:13.022301: train_loss -0.8017 +2024-11-22 15:38:13.030853: val_loss -0.7744 +2024-11-22 15:38:13.031073: Pseudo dice [0.8505] +2024-11-22 15:38:13.031181: Epoch time: 19.22 s +2024-11-22 15:38:13.907187: +2024-11-22 15:38:13.908782: Epoch 5223 +2024-11-22 15:38:13.908948: Current learning rate: 0.00386 +2024-11-22 15:38:34.249092: train_loss -0.7877 +2024-11-22 15:38:34.257136: val_loss -0.7983 +2024-11-22 15:38:34.257281: Pseudo dice [0.8581] +2024-11-22 15:38:34.257394: Epoch time: 20.34 s +2024-11-22 15:38:35.309769: +2024-11-22 15:38:35.310302: Epoch 5224 +2024-11-22 15:38:35.310422: Current learning rate: 0.00386 +2024-11-22 15:38:56.069877: train_loss -0.7879 +2024-11-22 15:38:56.078823: val_loss -0.7562 +2024-11-22 15:38:56.078941: Pseudo dice [0.8433] +2024-11-22 15:38:56.079044: Epoch time: 20.76 s +2024-11-22 15:38:57.026856: +2024-11-22 15:38:57.027693: Epoch 5225 +2024-11-22 15:38:57.027828: Current learning rate: 0.00386 +2024-11-22 15:39:17.056345: train_loss -0.7922 +2024-11-22 15:39:17.063205: val_loss -0.7708 +2024-11-22 15:39:17.063335: Pseudo dice [0.8458] +2024-11-22 15:39:17.063423: Epoch time: 20.03 s +2024-11-22 15:39:18.001034: +2024-11-22 15:39:18.002152: Epoch 5226 +2024-11-22 15:39:18.002272: Current learning rate: 0.00385 +2024-11-22 15:39:36.949935: train_loss -0.8024 +2024-11-22 15:39:36.957055: val_loss -0.7909 +2024-11-22 15:39:36.957185: Pseudo dice [0.8498] +2024-11-22 15:39:36.957278: Epoch time: 18.95 s +2024-11-22 15:39:37.931471: +2024-11-22 15:39:37.932998: Epoch 5227 +2024-11-22 15:39:37.933142: Current learning rate: 0.00385 +2024-11-22 15:39:57.677550: train_loss -0.7963 +2024-11-22 15:39:57.700778: val_loss -0.7686 +2024-11-22 15:39:57.700923: Pseudo dice [0.8516] +2024-11-22 15:39:57.701020: Epoch time: 19.75 s +2024-11-22 15:39:58.667800: +2024-11-22 15:39:58.670032: Epoch 5228 +2024-11-22 15:39:58.670163: Current learning rate: 0.00385 +2024-11-22 15:40:18.031711: train_loss -0.7922 +2024-11-22 15:40:18.035802: val_loss -0.7753 +2024-11-22 15:40:18.035928: Pseudo dice [0.8622] +2024-11-22 15:40:18.036030: Epoch time: 19.36 s +2024-11-22 15:40:18.910938: +2024-11-22 15:40:18.912530: Epoch 5229 +2024-11-22 15:40:18.912656: Current learning rate: 0.00385 +2024-11-22 15:40:38.412302: train_loss -0.799 +2024-11-22 15:40:38.416046: val_loss -0.7844 +2024-11-22 15:40:38.416190: Pseudo dice [0.8653] +2024-11-22 15:40:38.416282: Epoch time: 19.5 s +2024-11-22 15:40:39.758320: +2024-11-22 15:40:39.759960: Epoch 5230 +2024-11-22 15:40:39.760097: Current learning rate: 0.00385 +2024-11-22 15:40:59.578870: train_loss -0.8016 +2024-11-22 15:40:59.585912: val_loss -0.7602 +2024-11-22 15:40:59.586045: Pseudo dice [0.8513] +2024-11-22 15:40:59.586156: Epoch time: 19.82 s +2024-11-22 15:41:00.646743: +2024-11-22 15:41:00.647803: Epoch 5231 +2024-11-22 15:41:00.647943: Current learning rate: 0.00385 +2024-11-22 15:41:20.032096: train_loss -0.7969 +2024-11-22 15:41:20.038633: val_loss -0.7754 +2024-11-22 15:41:20.038841: Pseudo dice [0.8631] +2024-11-22 15:41:20.039006: Epoch time: 19.39 s +2024-11-22 15:41:20.963556: +2024-11-22 15:41:20.964121: Epoch 5232 +2024-11-22 15:41:20.964259: Current learning rate: 0.00385 +2024-11-22 15:41:40.273258: train_loss -0.7977 +2024-11-22 15:41:40.277189: val_loss -0.7854 +2024-11-22 15:41:40.277319: Pseudo dice [0.8622] +2024-11-22 15:41:40.277408: Epoch time: 19.31 s +2024-11-22 15:41:41.238791: +2024-11-22 15:41:41.239946: Epoch 5233 +2024-11-22 15:41:41.240088: Current learning rate: 0.00385 +2024-11-22 15:42:00.357064: train_loss -0.8032 +2024-11-22 15:42:00.368163: val_loss -0.7665 +2024-11-22 15:42:00.368386: Pseudo dice [0.845] +2024-11-22 15:42:00.368562: Epoch time: 19.12 s +2024-11-22 15:42:01.339687: +2024-11-22 15:42:01.340700: Epoch 5234 +2024-11-22 15:42:01.340821: Current learning rate: 0.00384 +2024-11-22 15:42:21.910191: train_loss -0.7951 +2024-11-22 15:42:21.913270: val_loss -0.793 +2024-11-22 15:42:21.913383: Pseudo dice [0.8485] +2024-11-22 15:42:21.913490: Epoch time: 20.57 s +2024-11-22 15:42:22.869076: +2024-11-22 15:42:22.870479: Epoch 5235 +2024-11-22 15:42:22.870604: Current learning rate: 0.00384 +2024-11-22 15:42:42.971564: train_loss -0.7979 +2024-11-22 15:42:42.978369: val_loss -0.7752 +2024-11-22 15:42:42.978553: Pseudo dice [0.851] +2024-11-22 15:42:42.978659: Epoch time: 20.1 s +2024-11-22 15:42:44.097137: +2024-11-22 15:42:44.097870: Epoch 5236 +2024-11-22 15:42:44.098005: Current learning rate: 0.00384 +2024-11-22 15:43:03.392583: train_loss -0.8043 +2024-11-22 15:43:03.400633: val_loss -0.7991 +2024-11-22 15:43:03.400747: Pseudo dice [0.8604] +2024-11-22 15:43:03.400841: Epoch time: 19.3 s +2024-11-22 15:43:04.296597: +2024-11-22 15:43:04.297520: Epoch 5237 +2024-11-22 15:43:04.297645: Current learning rate: 0.00384 +2024-11-22 15:43:22.571479: train_loss -0.8041 +2024-11-22 15:43:22.574541: val_loss -0.7584 +2024-11-22 15:43:22.574645: Pseudo dice [0.857] +2024-11-22 15:43:22.574743: Epoch time: 18.28 s +2024-11-22 15:43:23.440594: +2024-11-22 15:43:23.441354: Epoch 5238 +2024-11-22 15:43:23.441499: Current learning rate: 0.00384 +2024-11-22 15:43:43.011317: train_loss -0.7991 +2024-11-22 15:43:43.014222: val_loss -0.7708 +2024-11-22 15:43:43.014361: Pseudo dice [0.8539] +2024-11-22 15:43:43.014462: Epoch time: 19.57 s +2024-11-22 15:43:44.019068: +2024-11-22 15:43:44.020179: Epoch 5239 +2024-11-22 15:43:44.020322: Current learning rate: 0.00384 +2024-11-22 15:44:03.186073: train_loss -0.804 +2024-11-22 15:44:03.195518: val_loss -0.7619 +2024-11-22 15:44:03.195648: Pseudo dice [0.8465] +2024-11-22 15:44:03.195753: Epoch time: 19.17 s +2024-11-22 15:44:04.375085: +2024-11-22 15:44:04.375623: Epoch 5240 +2024-11-22 15:44:04.375743: Current learning rate: 0.00384 +2024-11-22 15:44:24.205229: train_loss -0.7817 +2024-11-22 15:44:24.212383: val_loss -0.7619 +2024-11-22 15:44:24.212545: Pseudo dice [0.8472] +2024-11-22 15:44:24.212655: Epoch time: 19.83 s +2024-11-22 15:44:25.500521: +2024-11-22 15:44:25.500735: Epoch 5241 +2024-11-22 15:44:25.500855: Current learning rate: 0.00384 +2024-11-22 15:44:44.587446: train_loss -0.7767 +2024-11-22 15:44:44.590209: val_loss -0.7693 +2024-11-22 15:44:44.590497: Pseudo dice [0.8581] +2024-11-22 15:44:44.590591: Epoch time: 19.09 s +2024-11-22 15:44:45.530491: +2024-11-22 15:44:45.530716: Epoch 5242 +2024-11-22 15:44:45.530828: Current learning rate: 0.00383 +2024-11-22 15:45:04.105888: train_loss -0.789 +2024-11-22 15:45:04.106399: val_loss -0.7705 +2024-11-22 15:45:04.106505: Pseudo dice [0.8595] +2024-11-22 15:45:04.106604: Epoch time: 18.58 s +2024-11-22 15:45:05.126949: +2024-11-22 15:45:05.127181: Epoch 5243 +2024-11-22 15:45:05.127311: Current learning rate: 0.00383 +2024-11-22 15:45:23.554677: train_loss -0.7781 +2024-11-22 15:45:23.556451: val_loss -0.7818 +2024-11-22 15:45:23.556598: Pseudo dice [0.8628] +2024-11-22 15:45:23.556709: Epoch time: 18.43 s +2024-11-22 15:45:24.535261: +2024-11-22 15:45:24.535470: Epoch 5244 +2024-11-22 15:45:24.535590: Current learning rate: 0.00383 +2024-11-22 15:45:43.438631: train_loss -0.7945 +2024-11-22 15:45:43.442366: val_loss -0.7802 +2024-11-22 15:45:43.442498: Pseudo dice [0.8525] +2024-11-22 15:45:43.442609: Epoch time: 18.9 s +2024-11-22 15:45:44.316052: +2024-11-22 15:45:44.316271: Epoch 5245 +2024-11-22 15:45:44.316395: Current learning rate: 0.00383 +2024-11-22 15:46:02.774283: train_loss -0.7919 +2024-11-22 15:46:02.775170: val_loss -0.7839 +2024-11-22 15:46:02.775277: Pseudo dice [0.8564] +2024-11-22 15:46:02.775403: Epoch time: 18.46 s +2024-11-22 15:46:03.632302: +2024-11-22 15:46:03.632509: Epoch 5246 +2024-11-22 15:46:03.632625: Current learning rate: 0.00383 +2024-11-22 15:46:22.653318: train_loss -0.8005 +2024-11-22 15:46:22.654840: val_loss -0.7806 +2024-11-22 15:46:22.654985: Pseudo dice [0.8486] +2024-11-22 15:46:22.655085: Epoch time: 19.02 s +2024-11-22 15:46:23.530389: +2024-11-22 15:46:23.530596: Epoch 5247 +2024-11-22 15:46:23.530724: Current learning rate: 0.00383 +2024-11-22 15:46:41.475022: train_loss -0.7894 +2024-11-22 15:46:41.478697: val_loss -0.767 +2024-11-22 15:46:41.478837: Pseudo dice [0.8551] +2024-11-22 15:46:41.478940: Epoch time: 17.95 s +2024-11-22 15:46:42.343596: +2024-11-22 15:46:42.343796: Epoch 5248 +2024-11-22 15:46:42.343921: Current learning rate: 0.00383 +2024-11-22 15:47:01.737381: train_loss -0.786 +2024-11-22 15:47:01.738499: val_loss -0.7626 +2024-11-22 15:47:01.738605: Pseudo dice [0.8507] +2024-11-22 15:47:01.738703: Epoch time: 19.39 s +2024-11-22 15:47:02.597453: +2024-11-22 15:47:02.597655: Epoch 5249 +2024-11-22 15:47:02.597772: Current learning rate: 0.00383 +2024-11-22 15:47:22.948078: train_loss -0.7944 +2024-11-22 15:47:22.963560: val_loss -0.7848 +2024-11-22 15:47:22.963693: Pseudo dice [0.8526] +2024-11-22 15:47:22.963794: Epoch time: 20.35 s +2024-11-22 15:47:24.127843: +2024-11-22 15:47:24.129676: Epoch 5250 +2024-11-22 15:47:24.129811: Current learning rate: 0.00382 +2024-11-22 15:47:44.109140: train_loss -0.7906 +2024-11-22 15:47:44.112199: val_loss -0.7589 +2024-11-22 15:47:44.112419: Pseudo dice [0.8546] +2024-11-22 15:47:44.112538: Epoch time: 19.98 s +2024-11-22 15:47:44.972326: +2024-11-22 15:47:44.973408: Epoch 5251 +2024-11-22 15:47:44.973547: Current learning rate: 0.00382 +2024-11-22 15:48:03.893930: train_loss -0.7933 +2024-11-22 15:48:03.913654: val_loss -0.7726 +2024-11-22 15:48:03.913776: Pseudo dice [0.8516] +2024-11-22 15:48:03.913889: Epoch time: 18.92 s +2024-11-22 15:48:04.956175: +2024-11-22 15:48:04.996682: Epoch 5252 +2024-11-22 15:48:04.997204: Current learning rate: 0.00382 +2024-11-22 15:48:24.674311: train_loss -0.7937 +2024-11-22 15:48:24.682988: val_loss -0.7875 +2024-11-22 15:48:24.683185: Pseudo dice [0.8509] +2024-11-22 15:48:24.683290: Epoch time: 19.72 s +2024-11-22 15:48:25.971286: +2024-11-22 15:48:25.972573: Epoch 5253 +2024-11-22 15:48:25.972705: Current learning rate: 0.00382 +2024-11-22 15:48:44.964115: train_loss -0.7918 +2024-11-22 15:48:44.969013: val_loss -0.7738 +2024-11-22 15:48:44.969137: Pseudo dice [0.8437] +2024-11-22 15:48:44.969227: Epoch time: 18.99 s +2024-11-22 15:48:45.832802: +2024-11-22 15:48:45.834254: Epoch 5254 +2024-11-22 15:48:45.834382: Current learning rate: 0.00382 +2024-11-22 15:49:04.850563: train_loss -0.7988 +2024-11-22 15:49:04.853248: val_loss -0.7756 +2024-11-22 15:49:04.853382: Pseudo dice [0.855] +2024-11-22 15:49:04.853478: Epoch time: 19.02 s +2024-11-22 15:49:05.835579: +2024-11-22 15:49:05.836855: Epoch 5255 +2024-11-22 15:49:05.836977: Current learning rate: 0.00382 +2024-11-22 15:49:25.115886: train_loss -0.7958 +2024-11-22 15:49:25.122821: val_loss -0.7818 +2024-11-22 15:49:25.122956: Pseudo dice [0.8604] +2024-11-22 15:49:25.123043: Epoch time: 19.28 s +2024-11-22 15:49:26.057964: +2024-11-22 15:49:26.059294: Epoch 5256 +2024-11-22 15:49:26.059416: Current learning rate: 0.00382 +2024-11-22 15:49:45.161459: train_loss -0.8048 +2024-11-22 15:49:45.164180: val_loss -0.7669 +2024-11-22 15:49:45.164285: Pseudo dice [0.8587] +2024-11-22 15:49:45.164371: Epoch time: 19.1 s +2024-11-22 15:49:46.023559: +2024-11-22 15:49:46.024970: Epoch 5257 +2024-11-22 15:49:46.025096: Current learning rate: 0.00382 +2024-11-22 15:50:05.880292: train_loss -0.804 +2024-11-22 15:50:05.887523: val_loss -0.7715 +2024-11-22 15:50:05.887656: Pseudo dice [0.862] +2024-11-22 15:50:05.887748: Epoch time: 19.86 s +2024-11-22 15:50:06.852407: +2024-11-22 15:50:06.852994: Epoch 5258 +2024-11-22 15:50:06.853136: Current learning rate: 0.00381 +2024-11-22 15:50:25.363518: train_loss -0.7918 +2024-11-22 15:50:25.371478: val_loss -0.7626 +2024-11-22 15:50:25.371595: Pseudo dice [0.845] +2024-11-22 15:50:25.371693: Epoch time: 18.51 s +2024-11-22 15:50:26.355064: +2024-11-22 15:50:26.356358: Epoch 5259 +2024-11-22 15:50:26.356498: Current learning rate: 0.00381 +2024-11-22 15:50:46.024748: train_loss -0.7901 +2024-11-22 15:50:46.031502: val_loss -0.7665 +2024-11-22 15:50:46.031623: Pseudo dice [0.8445] +2024-11-22 15:50:46.031728: Epoch time: 19.67 s +2024-11-22 15:50:47.122215: +2024-11-22 15:50:47.123846: Epoch 5260 +2024-11-22 15:50:47.123976: Current learning rate: 0.00381 +2024-11-22 15:51:07.102729: train_loss -0.8002 +2024-11-22 15:51:07.108994: val_loss -0.782 +2024-11-22 15:51:07.109143: Pseudo dice [0.8558] +2024-11-22 15:51:07.109251: Epoch time: 19.98 s +2024-11-22 15:51:08.161463: +2024-11-22 15:51:08.162321: Epoch 5261 +2024-11-22 15:51:08.162469: Current learning rate: 0.00381 +2024-11-22 15:51:27.804967: train_loss -0.7916 +2024-11-22 15:51:27.807152: val_loss -0.8048 +2024-11-22 15:51:27.807266: Pseudo dice [0.8591] +2024-11-22 15:51:27.807372: Epoch time: 19.64 s +2024-11-22 15:51:28.820239: +2024-11-22 15:51:28.821006: Epoch 5262 +2024-11-22 15:51:28.821130: Current learning rate: 0.00381 +2024-11-22 15:51:48.801254: train_loss -0.807 +2024-11-22 15:51:48.803490: val_loss -0.7872 +2024-11-22 15:51:48.803611: Pseudo dice [0.8581] +2024-11-22 15:51:48.803709: Epoch time: 19.98 s +2024-11-22 15:51:49.666932: +2024-11-22 15:51:49.668079: Epoch 5263 +2024-11-22 15:51:49.668212: Current learning rate: 0.00381 +2024-11-22 15:52:09.857770: train_loss -0.792 +2024-11-22 15:52:09.872798: val_loss -0.7762 +2024-11-22 15:52:09.872938: Pseudo dice [0.8613] +2024-11-22 15:52:09.873037: Epoch time: 20.19 s +2024-11-22 15:52:11.283639: +2024-11-22 15:52:11.285339: Epoch 5264 +2024-11-22 15:52:11.285502: Current learning rate: 0.00381 +2024-11-22 15:52:31.086734: train_loss -0.7844 +2024-11-22 15:52:31.093386: val_loss -0.7654 +2024-11-22 15:52:31.094030: Pseudo dice [0.8543] +2024-11-22 15:52:31.094169: Epoch time: 19.8 s +2024-11-22 15:52:31.964444: +2024-11-22 15:52:31.965371: Epoch 5265 +2024-11-22 15:52:31.965521: Current learning rate: 0.00381 +2024-11-22 15:52:51.474558: train_loss -0.781 +2024-11-22 15:52:51.483955: val_loss -0.7746 +2024-11-22 15:52:51.484110: Pseudo dice [0.8356] +2024-11-22 15:52:51.484226: Epoch time: 19.51 s +2024-11-22 15:52:52.488499: +2024-11-22 15:52:52.489836: Epoch 5266 +2024-11-22 15:52:52.489960: Current learning rate: 0.0038 +2024-11-22 15:53:12.132719: train_loss -0.7954 +2024-11-22 15:53:12.137884: val_loss -0.7679 +2024-11-22 15:53:12.138026: Pseudo dice [0.8479] +2024-11-22 15:53:12.138137: Epoch time: 19.65 s +2024-11-22 15:53:13.094708: +2024-11-22 15:53:13.097065: Epoch 5267 +2024-11-22 15:53:13.097197: Current learning rate: 0.0038 +2024-11-22 15:53:32.370326: train_loss -0.7976 +2024-11-22 15:53:32.375125: val_loss -0.7845 +2024-11-22 15:53:32.375257: Pseudo dice [0.851] +2024-11-22 15:53:32.375355: Epoch time: 19.28 s +2024-11-22 15:53:33.387339: +2024-11-22 15:53:33.387786: Epoch 5268 +2024-11-22 15:53:33.387923: Current learning rate: 0.0038 +2024-11-22 15:53:53.414824: train_loss -0.8024 +2024-11-22 15:53:53.421788: val_loss -0.7878 +2024-11-22 15:53:53.421941: Pseudo dice [0.8574] +2024-11-22 15:53:53.422077: Epoch time: 20.03 s +2024-11-22 15:53:54.329926: +2024-11-22 15:53:54.331037: Epoch 5269 +2024-11-22 15:53:54.331163: Current learning rate: 0.0038 +2024-11-22 15:54:13.340678: train_loss -0.8001 +2024-11-22 15:54:13.350040: val_loss -0.7848 +2024-11-22 15:54:13.350268: Pseudo dice [0.8563] +2024-11-22 15:54:13.350360: Epoch time: 19.01 s +2024-11-22 15:54:14.292967: +2024-11-22 15:54:14.293422: Epoch 5270 +2024-11-22 15:54:14.293543: Current learning rate: 0.0038 +2024-11-22 15:54:33.866802: train_loss -0.791 +2024-11-22 15:54:33.871726: val_loss -0.7772 +2024-11-22 15:54:33.871904: Pseudo dice [0.8652] +2024-11-22 15:54:33.872010: Epoch time: 19.57 s +2024-11-22 15:54:34.747543: +2024-11-22 15:54:34.749287: Epoch 5271 +2024-11-22 15:54:34.749412: Current learning rate: 0.0038 +2024-11-22 15:54:53.624907: train_loss -0.7867 +2024-11-22 15:54:53.631474: val_loss -0.7534 +2024-11-22 15:54:53.631635: Pseudo dice [0.8424] +2024-11-22 15:54:53.631736: Epoch time: 18.88 s +2024-11-22 15:54:54.733490: +2024-11-22 15:54:54.735013: Epoch 5272 +2024-11-22 15:54:54.735157: Current learning rate: 0.0038 +2024-11-22 15:55:13.873334: train_loss -0.7942 +2024-11-22 15:55:13.880134: val_loss -0.7481 +2024-11-22 15:55:13.880255: Pseudo dice [0.8376] +2024-11-22 15:55:13.880360: Epoch time: 19.14 s +2024-11-22 15:55:14.861118: +2024-11-22 15:55:14.861651: Epoch 5273 +2024-11-22 15:55:14.861792: Current learning rate: 0.0038 +2024-11-22 15:55:34.925776: train_loss -0.8008 +2024-11-22 15:55:34.931385: val_loss -0.7561 +2024-11-22 15:55:34.931521: Pseudo dice [0.8516] +2024-11-22 15:55:34.931622: Epoch time: 20.07 s +2024-11-22 15:55:35.814649: +2024-11-22 15:55:35.815754: Epoch 5274 +2024-11-22 15:55:35.815869: Current learning rate: 0.00379 +2024-11-22 15:55:55.544673: train_loss -0.7881 +2024-11-22 15:55:55.553024: val_loss -0.764 +2024-11-22 15:55:55.553161: Pseudo dice [0.8543] +2024-11-22 15:55:55.553248: Epoch time: 19.73 s +2024-11-22 15:55:56.491124: +2024-11-22 15:55:56.491327: Epoch 5275 +2024-11-22 15:55:56.491477: Current learning rate: 0.00379 +2024-11-22 15:56:14.513409: train_loss -0.7959 +2024-11-22 15:56:14.515017: val_loss -0.7746 +2024-11-22 15:56:14.515145: Pseudo dice [0.8548] +2024-11-22 15:56:14.515257: Epoch time: 18.02 s +2024-11-22 15:56:15.845832: +2024-11-22 15:56:15.847913: Epoch 5276 +2024-11-22 15:56:15.848132: Current learning rate: 0.00379 +2024-11-22 15:56:33.842891: train_loss -0.8026 +2024-11-22 15:56:33.857520: val_loss -0.7973 +2024-11-22 15:56:33.857686: Pseudo dice [0.8739] +2024-11-22 15:56:33.857793: Epoch time: 18.0 s +2024-11-22 15:56:34.799496: +2024-11-22 15:56:34.799719: Epoch 5277 +2024-11-22 15:56:34.799840: Current learning rate: 0.00379 +2024-11-22 15:56:54.513047: train_loss -0.7902 +2024-11-22 15:56:54.521215: val_loss -0.7605 +2024-11-22 15:56:54.521369: Pseudo dice [0.851] +2024-11-22 15:56:54.521472: Epoch time: 19.71 s +2024-11-22 15:56:55.410968: +2024-11-22 15:56:55.411430: Epoch 5278 +2024-11-22 15:56:55.411547: Current learning rate: 0.00379 +2024-11-22 15:57:14.965758: train_loss -0.798 +2024-11-22 15:57:14.971975: val_loss -0.7639 +2024-11-22 15:57:14.972141: Pseudo dice [0.8495] +2024-11-22 15:57:14.972233: Epoch time: 19.56 s +2024-11-22 15:57:15.888055: +2024-11-22 15:57:15.888715: Epoch 5279 +2024-11-22 15:57:15.888830: Current learning rate: 0.00379 +2024-11-22 15:57:34.893991: train_loss -0.8004 +2024-11-22 15:57:34.900877: val_loss -0.7575 +2024-11-22 15:57:34.901022: Pseudo dice [0.8375] +2024-11-22 15:57:34.901130: Epoch time: 19.01 s +2024-11-22 15:57:35.799752: +2024-11-22 15:57:35.803205: Epoch 5280 +2024-11-22 15:57:35.803340: Current learning rate: 0.00379 +2024-11-22 15:57:55.223921: train_loss -0.7831 +2024-11-22 15:57:55.232655: val_loss -0.7756 +2024-11-22 15:57:55.232798: Pseudo dice [0.8566] +2024-11-22 15:57:55.232901: Epoch time: 19.42 s +2024-11-22 15:57:56.232574: +2024-11-22 15:57:56.234210: Epoch 5281 +2024-11-22 15:57:56.234363: Current learning rate: 0.00379 +2024-11-22 15:58:16.646088: train_loss -0.8013 +2024-11-22 15:58:16.652475: val_loss -0.7763 +2024-11-22 15:58:16.652634: Pseudo dice [0.8526] +2024-11-22 15:58:16.652721: Epoch time: 20.41 s +2024-11-22 15:58:17.537694: +2024-11-22 15:58:17.538969: Epoch 5282 +2024-11-22 15:58:17.539127: Current learning rate: 0.00378 +2024-11-22 15:58:36.991418: train_loss -0.7961 +2024-11-22 15:58:36.996870: val_loss -0.7555 +2024-11-22 15:58:36.997014: Pseudo dice [0.8422] +2024-11-22 15:58:36.997128: Epoch time: 19.45 s +2024-11-22 15:58:37.867442: +2024-11-22 15:58:37.868934: Epoch 5283 +2024-11-22 15:58:37.869070: Current learning rate: 0.00378 +2024-11-22 15:58:57.152235: train_loss -0.7987 +2024-11-22 15:58:57.156800: val_loss -0.774 +2024-11-22 15:58:57.156954: Pseudo dice [0.8585] +2024-11-22 15:58:57.157093: Epoch time: 19.29 s +2024-11-22 15:58:58.199212: +2024-11-22 15:58:58.200559: Epoch 5284 +2024-11-22 15:58:58.200684: Current learning rate: 0.00378 +2024-11-22 15:59:16.676706: train_loss -0.7933 +2024-11-22 15:59:16.680915: val_loss -0.7792 +2024-11-22 15:59:16.681037: Pseudo dice [0.8642] +2024-11-22 15:59:16.681130: Epoch time: 18.48 s +2024-11-22 15:59:17.662918: +2024-11-22 15:59:17.663547: Epoch 5285 +2024-11-22 15:59:17.663678: Current learning rate: 0.00378 +2024-11-22 15:59:37.104043: train_loss -0.7901 +2024-11-22 15:59:37.114347: val_loss -0.7832 +2024-11-22 15:59:37.114474: Pseudo dice [0.8483] +2024-11-22 15:59:37.114570: Epoch time: 19.44 s +2024-11-22 15:59:38.120224: +2024-11-22 15:59:38.121304: Epoch 5286 +2024-11-22 15:59:38.121433: Current learning rate: 0.00378 +2024-11-22 15:59:57.207527: train_loss -0.7977 +2024-11-22 15:59:57.215420: val_loss -0.7735 +2024-11-22 15:59:57.215533: Pseudo dice [0.8542] +2024-11-22 15:59:57.215646: Epoch time: 19.09 s +2024-11-22 15:59:58.648218: +2024-11-22 15:59:58.649369: Epoch 5287 +2024-11-22 15:59:58.649526: Current learning rate: 0.00378 +2024-11-22 16:00:18.482162: train_loss -0.7862 +2024-11-22 16:00:18.494137: val_loss -0.7615 +2024-11-22 16:00:18.494267: Pseudo dice [0.8477] +2024-11-22 16:00:18.494392: Epoch time: 19.83 s +2024-11-22 16:00:19.402011: +2024-11-22 16:00:19.403122: Epoch 5288 +2024-11-22 16:00:19.403292: Current learning rate: 0.00378 +2024-11-22 16:00:39.187465: train_loss -0.7972 +2024-11-22 16:00:39.199672: val_loss -0.7702 +2024-11-22 16:00:39.199826: Pseudo dice [0.8386] +2024-11-22 16:00:39.199933: Epoch time: 19.79 s +2024-11-22 16:00:40.208336: +2024-11-22 16:00:40.210042: Epoch 5289 +2024-11-22 16:00:40.210179: Current learning rate: 0.00378 +2024-11-22 16:00:59.765926: train_loss -0.7986 +2024-11-22 16:00:59.770267: val_loss -0.7881 +2024-11-22 16:00:59.770407: Pseudo dice [0.8601] +2024-11-22 16:00:59.770510: Epoch time: 19.56 s +2024-11-22 16:01:00.665886: +2024-11-22 16:01:00.667933: Epoch 5290 +2024-11-22 16:01:00.668136: Current learning rate: 0.00377 +2024-11-22 16:01:18.547065: train_loss -0.7991 +2024-11-22 16:01:18.550170: val_loss -0.7839 +2024-11-22 16:01:18.550268: Pseudo dice [0.844] +2024-11-22 16:01:18.550356: Epoch time: 17.88 s +2024-11-22 16:01:19.417695: +2024-11-22 16:01:19.418403: Epoch 5291 +2024-11-22 16:01:19.418566: Current learning rate: 0.00377 +2024-11-22 16:01:38.065228: train_loss -0.7954 +2024-11-22 16:01:38.067397: val_loss -0.7628 +2024-11-22 16:01:38.067496: Pseudo dice [0.8459] +2024-11-22 16:01:38.067597: Epoch time: 18.65 s +2024-11-22 16:01:38.936212: +2024-11-22 16:01:38.937943: Epoch 5292 +2024-11-22 16:01:38.938101: Current learning rate: 0.00377 +2024-11-22 16:01:59.370990: train_loss -0.7993 +2024-11-22 16:01:59.379510: val_loss -0.7795 +2024-11-22 16:01:59.379647: Pseudo dice [0.8563] +2024-11-22 16:01:59.379793: Epoch time: 20.44 s +2024-11-22 16:02:00.319893: +2024-11-22 16:02:00.321175: Epoch 5293 +2024-11-22 16:02:00.321341: Current learning rate: 0.00377 +2024-11-22 16:02:21.017560: train_loss -0.7908 +2024-11-22 16:02:21.028627: val_loss -0.7792 +2024-11-22 16:02:21.028815: Pseudo dice [0.8633] +2024-11-22 16:02:21.028908: Epoch time: 20.7 s +2024-11-22 16:02:21.912455: +2024-11-22 16:02:21.913439: Epoch 5294 +2024-11-22 16:02:21.913595: Current learning rate: 0.00377 +2024-11-22 16:02:41.059976: train_loss -0.7982 +2024-11-22 16:02:41.067498: val_loss -0.78 +2024-11-22 16:02:41.067630: Pseudo dice [0.8664] +2024-11-22 16:02:41.067723: Epoch time: 19.15 s +2024-11-22 16:02:42.154384: +2024-11-22 16:02:42.156260: Epoch 5295 +2024-11-22 16:02:42.156415: Current learning rate: 0.00377 +2024-11-22 16:03:02.123286: train_loss -0.8006 +2024-11-22 16:03:02.129712: val_loss -0.7714 +2024-11-22 16:03:02.129855: Pseudo dice [0.8475] +2024-11-22 16:03:02.129948: Epoch time: 19.97 s +2024-11-22 16:03:02.998555: +2024-11-22 16:03:02.999532: Epoch 5296 +2024-11-22 16:03:02.999685: Current learning rate: 0.00377 +2024-11-22 16:03:22.730428: train_loss -0.7895 +2024-11-22 16:03:22.738773: val_loss -0.7591 +2024-11-22 16:03:22.738894: Pseudo dice [0.8452] +2024-11-22 16:03:22.738976: Epoch time: 19.73 s +2024-11-22 16:03:23.706757: +2024-11-22 16:03:23.709210: Epoch 5297 +2024-11-22 16:03:23.709364: Current learning rate: 0.00377 +2024-11-22 16:03:42.605350: train_loss -0.7987 +2024-11-22 16:03:42.613875: val_loss -0.7683 +2024-11-22 16:03:42.614014: Pseudo dice [0.8429] +2024-11-22 16:03:42.614130: Epoch time: 18.9 s +2024-11-22 16:03:43.525540: +2024-11-22 16:03:43.526101: Epoch 5298 +2024-11-22 16:03:43.526225: Current learning rate: 0.00376 +2024-11-22 16:04:02.396661: train_loss -0.7988 +2024-11-22 16:04:02.411483: val_loss -0.7807 +2024-11-22 16:04:02.411614: Pseudo dice [0.8532] +2024-11-22 16:04:02.411724: Epoch time: 18.87 s +2024-11-22 16:04:03.770009: +2024-11-22 16:04:03.771917: Epoch 5299 +2024-11-22 16:04:03.772047: Current learning rate: 0.00376 +2024-11-22 16:04:22.456935: train_loss -0.8008 +2024-11-22 16:04:22.467170: val_loss -0.79 +2024-11-22 16:04:22.467308: Pseudo dice [0.8509] +2024-11-22 16:04:22.467429: Epoch time: 18.69 s +2024-11-22 16:04:23.947809: +2024-11-22 16:04:23.949868: Epoch 5300 +2024-11-22 16:04:23.949991: Current learning rate: 0.00376 +2024-11-22 16:04:44.777315: train_loss -0.8046 +2024-11-22 16:04:44.782944: val_loss -0.758 +2024-11-22 16:04:44.783155: Pseudo dice [0.8469] +2024-11-22 16:04:44.783251: Epoch time: 20.83 s +2024-11-22 16:04:45.680635: +2024-11-22 16:04:45.681724: Epoch 5301 +2024-11-22 16:04:45.681854: Current learning rate: 0.00376 +2024-11-22 16:05:04.741522: train_loss -0.8063 +2024-11-22 16:05:04.748528: val_loss -0.771 +2024-11-22 16:05:04.748657: Pseudo dice [0.8554] +2024-11-22 16:05:04.748748: Epoch time: 19.06 s +2024-11-22 16:05:05.627118: +2024-11-22 16:05:05.629528: Epoch 5302 +2024-11-22 16:05:05.629662: Current learning rate: 0.00376 +2024-11-22 16:05:24.623014: train_loss -0.8043 +2024-11-22 16:05:24.632317: val_loss -0.7895 +2024-11-22 16:05:24.632464: Pseudo dice [0.8561] +2024-11-22 16:05:24.633705: Epoch time: 19.0 s +2024-11-22 16:05:25.518181: +2024-11-22 16:05:25.519854: Epoch 5303 +2024-11-22 16:05:25.520002: Current learning rate: 0.00376 +2024-11-22 16:05:44.649557: train_loss -0.7943 +2024-11-22 16:05:44.663230: val_loss -0.7652 +2024-11-22 16:05:44.663396: Pseudo dice [0.8453] +2024-11-22 16:05:44.663506: Epoch time: 19.13 s +2024-11-22 16:05:45.602763: +2024-11-22 16:05:45.604170: Epoch 5304 +2024-11-22 16:05:45.604301: Current learning rate: 0.00376 +2024-11-22 16:06:05.025368: train_loss -0.7944 +2024-11-22 16:06:05.034314: val_loss -0.7743 +2024-11-22 16:06:05.034452: Pseudo dice [0.8544] +2024-11-22 16:06:05.034570: Epoch time: 19.42 s +2024-11-22 16:06:06.087314: +2024-11-22 16:06:06.088989: Epoch 5305 +2024-11-22 16:06:06.089117: Current learning rate: 0.00376 +2024-11-22 16:06:25.819831: train_loss -0.7969 +2024-11-22 16:06:25.826195: val_loss -0.7684 +2024-11-22 16:06:25.826329: Pseudo dice [0.8579] +2024-11-22 16:06:25.826470: Epoch time: 19.73 s +2024-11-22 16:06:26.851694: +2024-11-22 16:06:26.854140: Epoch 5306 +2024-11-22 16:06:26.854268: Current learning rate: 0.00375 +2024-11-22 16:06:46.715409: train_loss -0.8014 +2024-11-22 16:06:46.720933: val_loss -0.7887 +2024-11-22 16:06:46.721089: Pseudo dice [0.8609] +2024-11-22 16:06:46.721207: Epoch time: 19.86 s +2024-11-22 16:06:47.592401: +2024-11-22 16:06:47.593824: Epoch 5307 +2024-11-22 16:06:47.593952: Current learning rate: 0.00375 +2024-11-22 16:07:07.276582: train_loss -0.7969 +2024-11-22 16:07:07.280945: val_loss -0.7863 +2024-11-22 16:07:07.281058: Pseudo dice [0.8532] +2024-11-22 16:07:07.281173: Epoch time: 19.69 s +2024-11-22 16:07:08.149598: +2024-11-22 16:07:08.151577: Epoch 5308 +2024-11-22 16:07:08.151705: Current learning rate: 0.00375 +2024-11-22 16:07:27.528511: train_loss -0.7989 +2024-11-22 16:07:27.534957: val_loss -0.7623 +2024-11-22 16:07:27.535107: Pseudo dice [0.8522] +2024-11-22 16:07:27.535201: Epoch time: 19.38 s +2024-11-22 16:07:28.414266: +2024-11-22 16:07:28.415380: Epoch 5309 +2024-11-22 16:07:28.415518: Current learning rate: 0.00375 +2024-11-22 16:07:48.373770: train_loss -0.8093 +2024-11-22 16:07:48.380380: val_loss -0.7838 +2024-11-22 16:07:48.380552: Pseudo dice [0.8531] +2024-11-22 16:07:48.380660: Epoch time: 19.96 s +2024-11-22 16:07:49.675215: +2024-11-22 16:07:49.675823: Epoch 5310 +2024-11-22 16:07:49.675956: Current learning rate: 0.00375 +2024-11-22 16:08:09.660637: train_loss -0.8026 +2024-11-22 16:08:09.665788: val_loss -0.7592 +2024-11-22 16:08:09.665914: Pseudo dice [0.8417] +2024-11-22 16:08:09.666035: Epoch time: 19.99 s +2024-11-22 16:08:10.572698: +2024-11-22 16:08:10.573488: Epoch 5311 +2024-11-22 16:08:10.573624: Current learning rate: 0.00375 +2024-11-22 16:08:29.705830: train_loss -0.7994 +2024-11-22 16:08:29.708495: val_loss -0.7829 +2024-11-22 16:08:29.708719: Pseudo dice [0.8545] +2024-11-22 16:08:29.708822: Epoch time: 19.13 s +2024-11-22 16:08:30.613603: +2024-11-22 16:08:30.614874: Epoch 5312 +2024-11-22 16:08:30.615020: Current learning rate: 0.00375 +2024-11-22 16:08:49.576205: train_loss -0.7979 +2024-11-22 16:08:49.590791: val_loss -0.7785 +2024-11-22 16:08:49.590940: Pseudo dice [0.8627] +2024-11-22 16:08:49.591045: Epoch time: 18.96 s +2024-11-22 16:08:50.475554: +2024-11-22 16:08:50.475799: Epoch 5313 +2024-11-22 16:08:50.475935: Current learning rate: 0.00375 +2024-11-22 16:09:09.419429: train_loss -0.804 +2024-11-22 16:09:09.421208: val_loss -0.7644 +2024-11-22 16:09:09.421317: Pseudo dice [0.8562] +2024-11-22 16:09:09.421412: Epoch time: 18.94 s +2024-11-22 16:09:10.278451: +2024-11-22 16:09:10.278647: Epoch 5314 +2024-11-22 16:09:10.278783: Current learning rate: 0.00374 +2024-11-22 16:09:28.000544: train_loss -0.801 +2024-11-22 16:09:28.001091: val_loss -0.7894 +2024-11-22 16:09:28.001236: Pseudo dice [0.8681] +2024-11-22 16:09:28.001334: Epoch time: 17.72 s +2024-11-22 16:09:28.869972: +2024-11-22 16:09:28.870169: Epoch 5315 +2024-11-22 16:09:28.870286: Current learning rate: 0.00374 +2024-11-22 16:09:48.628787: train_loss -0.8024 +2024-11-22 16:09:48.631741: val_loss -0.7391 +2024-11-22 16:09:48.631888: Pseudo dice [0.8539] +2024-11-22 16:09:48.631991: Epoch time: 19.76 s +2024-11-22 16:09:49.582651: +2024-11-22 16:09:49.582872: Epoch 5316 +2024-11-22 16:09:49.583003: Current learning rate: 0.00374 +2024-11-22 16:10:08.556499: train_loss -0.7933 +2024-11-22 16:10:08.556978: val_loss -0.7689 +2024-11-22 16:10:08.557097: Pseudo dice [0.8561] +2024-11-22 16:10:08.557192: Epoch time: 18.97 s +2024-11-22 16:10:09.514185: +2024-11-22 16:10:09.514404: Epoch 5317 +2024-11-22 16:10:09.514534: Current learning rate: 0.00374 +2024-11-22 16:10:28.501297: train_loss -0.7976 +2024-11-22 16:10:28.502915: val_loss -0.7535 +2024-11-22 16:10:28.503083: Pseudo dice [0.8438] +2024-11-22 16:10:28.503192: Epoch time: 18.99 s +2024-11-22 16:10:29.377749: +2024-11-22 16:10:29.377978: Epoch 5318 +2024-11-22 16:10:29.378128: Current learning rate: 0.00374 +2024-11-22 16:10:48.051688: train_loss -0.7969 +2024-11-22 16:10:48.056484: val_loss -0.77 +2024-11-22 16:10:48.056621: Pseudo dice [0.8507] +2024-11-22 16:10:48.056706: Epoch time: 18.67 s +2024-11-22 16:10:48.947649: +2024-11-22 16:10:48.947858: Epoch 5319 +2024-11-22 16:10:48.947980: Current learning rate: 0.00374 +2024-11-22 16:11:06.834242: train_loss -0.7992 +2024-11-22 16:11:06.839136: val_loss -0.7658 +2024-11-22 16:11:06.839284: Pseudo dice [0.8502] +2024-11-22 16:11:06.839386: Epoch time: 17.89 s +2024-11-22 16:11:07.762354: +2024-11-22 16:11:07.762577: Epoch 5320 +2024-11-22 16:11:07.762692: Current learning rate: 0.00374 +2024-11-22 16:11:26.884123: train_loss -0.7905 +2024-11-22 16:11:26.888848: val_loss -0.7721 +2024-11-22 16:11:26.888974: Pseudo dice [0.8636] +2024-11-22 16:11:26.889067: Epoch time: 19.12 s +2024-11-22 16:11:28.192130: +2024-11-22 16:11:28.192388: Epoch 5321 +2024-11-22 16:11:28.192502: Current learning rate: 0.00374 +2024-11-22 16:11:47.669530: train_loss -0.8034 +2024-11-22 16:11:47.674881: val_loss -0.7877 +2024-11-22 16:11:47.675044: Pseudo dice [0.8599] +2024-11-22 16:11:47.675143: Epoch time: 19.48 s +2024-11-22 16:11:48.571192: +2024-11-22 16:11:48.571400: Epoch 5322 +2024-11-22 16:11:48.571520: Current learning rate: 0.00373 +2024-11-22 16:12:08.664885: train_loss -0.7897 +2024-11-22 16:12:08.667179: val_loss -0.7665 +2024-11-22 16:12:08.667310: Pseudo dice [0.8409] +2024-11-22 16:12:08.667421: Epoch time: 20.09 s +2024-11-22 16:12:09.542330: +2024-11-22 16:12:09.543293: Epoch 5323 +2024-11-22 16:12:09.543427: Current learning rate: 0.00373 +2024-11-22 16:12:27.519699: train_loss -0.7973 +2024-11-22 16:12:27.535607: val_loss -0.775 +2024-11-22 16:12:27.535736: Pseudo dice [0.8625] +2024-11-22 16:12:27.535837: Epoch time: 17.98 s +2024-11-22 16:12:28.664771: +2024-11-22 16:12:28.666130: Epoch 5324 +2024-11-22 16:12:28.666247: Current learning rate: 0.00373 +2024-11-22 16:12:48.069856: train_loss -0.7952 +2024-11-22 16:12:48.072998: val_loss -0.7597 +2024-11-22 16:12:48.073106: Pseudo dice [0.8411] +2024-11-22 16:12:48.073215: Epoch time: 19.41 s +2024-11-22 16:12:48.944701: +2024-11-22 16:12:48.945462: Epoch 5325 +2024-11-22 16:12:48.945586: Current learning rate: 0.00373 +2024-11-22 16:13:08.759669: train_loss -0.8007 +2024-11-22 16:13:08.768192: val_loss -0.7701 +2024-11-22 16:13:08.768342: Pseudo dice [0.8535] +2024-11-22 16:13:08.768496: Epoch time: 19.82 s +2024-11-22 16:13:09.758531: +2024-11-22 16:13:09.760227: Epoch 5326 +2024-11-22 16:13:09.760357: Current learning rate: 0.00373 +2024-11-22 16:13:28.144591: train_loss -0.7972 +2024-11-22 16:13:28.147066: val_loss -0.7733 +2024-11-22 16:13:28.147188: Pseudo dice [0.8659] +2024-11-22 16:13:28.147286: Epoch time: 18.39 s +2024-11-22 16:13:29.016076: +2024-11-22 16:13:29.017740: Epoch 5327 +2024-11-22 16:13:29.017864: Current learning rate: 0.00373 +2024-11-22 16:13:48.829384: train_loss -0.794 +2024-11-22 16:13:48.838658: val_loss -0.7562 +2024-11-22 16:13:48.838795: Pseudo dice [0.8504] +2024-11-22 16:13:48.838893: Epoch time: 19.81 s +2024-11-22 16:13:49.722719: +2024-11-22 16:13:49.724098: Epoch 5328 +2024-11-22 16:13:49.724436: Current learning rate: 0.00373 +2024-11-22 16:14:09.187310: train_loss -0.7913 +2024-11-22 16:14:09.199118: val_loss -0.7614 +2024-11-22 16:14:09.199275: Pseudo dice [0.8469] +2024-11-22 16:14:09.199390: Epoch time: 19.47 s +2024-11-22 16:14:10.192564: +2024-11-22 16:14:10.193578: Epoch 5329 +2024-11-22 16:14:10.193709: Current learning rate: 0.00373 +2024-11-22 16:14:29.465561: train_loss -0.7883 +2024-11-22 16:14:29.471092: val_loss -0.7754 +2024-11-22 16:14:29.471215: Pseudo dice [0.8541] +2024-11-22 16:14:29.471316: Epoch time: 19.27 s +2024-11-22 16:14:30.553734: +2024-11-22 16:14:30.555079: Epoch 5330 +2024-11-22 16:14:30.555219: Current learning rate: 0.00372 +2024-11-22 16:14:50.409926: train_loss -0.7911 +2024-11-22 16:14:50.429377: val_loss -0.7753 +2024-11-22 16:14:50.429530: Pseudo dice [0.847] +2024-11-22 16:14:50.429635: Epoch time: 19.86 s +2024-11-22 16:14:51.385302: +2024-11-22 16:14:51.385760: Epoch 5331 +2024-11-22 16:14:51.385894: Current learning rate: 0.00372 +2024-11-22 16:15:10.810791: train_loss -0.8011 +2024-11-22 16:15:10.817039: val_loss -0.7913 +2024-11-22 16:15:10.817156: Pseudo dice [0.8556] +2024-11-22 16:15:10.817245: Epoch time: 19.43 s +2024-11-22 16:15:11.885142: +2024-11-22 16:15:11.885679: Epoch 5332 +2024-11-22 16:15:11.885806: Current learning rate: 0.00372 +2024-11-22 16:15:30.054598: train_loss -0.805 +2024-11-22 16:15:30.062811: val_loss -0.7604 +2024-11-22 16:15:30.062949: Pseudo dice [0.846] +2024-11-22 16:15:30.063051: Epoch time: 18.17 s +2024-11-22 16:15:31.446733: +2024-11-22 16:15:31.448600: Epoch 5333 +2024-11-22 16:15:31.448722: Current learning rate: 0.00372 +2024-11-22 16:15:51.393620: train_loss -0.8043 +2024-11-22 16:15:51.399326: val_loss -0.7876 +2024-11-22 16:15:51.399461: Pseudo dice [0.8488] +2024-11-22 16:15:51.399561: Epoch time: 19.95 s +2024-11-22 16:15:52.286963: +2024-11-22 16:15:52.287520: Epoch 5334 +2024-11-22 16:15:52.287655: Current learning rate: 0.00372 +2024-11-22 16:16:10.775363: train_loss -0.811 +2024-11-22 16:16:10.777475: val_loss -0.7665 +2024-11-22 16:16:10.777577: Pseudo dice [0.8472] +2024-11-22 16:16:10.777673: Epoch time: 18.49 s +2024-11-22 16:16:11.638332: +2024-11-22 16:16:11.639818: Epoch 5335 +2024-11-22 16:16:11.639960: Current learning rate: 0.00372 +2024-11-22 16:16:30.944758: train_loss -0.8015 +2024-11-22 16:16:30.954239: val_loss -0.7566 +2024-11-22 16:16:30.954370: Pseudo dice [0.8515] +2024-11-22 16:16:30.954481: Epoch time: 19.31 s +2024-11-22 16:16:32.014779: +2024-11-22 16:16:32.016088: Epoch 5336 +2024-11-22 16:16:32.016221: Current learning rate: 0.00372 +2024-11-22 16:16:50.569285: train_loss -0.7997 +2024-11-22 16:16:50.577233: val_loss -0.7775 +2024-11-22 16:16:50.577373: Pseudo dice [0.8599] +2024-11-22 16:16:50.577492: Epoch time: 18.56 s +2024-11-22 16:16:51.552758: +2024-11-22 16:16:51.553539: Epoch 5337 +2024-11-22 16:16:51.553663: Current learning rate: 0.00372 +2024-11-22 16:17:11.627170: train_loss -0.798 +2024-11-22 16:17:11.634915: val_loss -0.7892 +2024-11-22 16:17:11.635064: Pseudo dice [0.8624] +2024-11-22 16:17:11.635158: Epoch time: 20.08 s +2024-11-22 16:17:12.637324: +2024-11-22 16:17:12.638487: Epoch 5338 +2024-11-22 16:17:12.638611: Current learning rate: 0.00371 +2024-11-22 16:17:31.896673: train_loss -0.7843 +2024-11-22 16:17:31.914972: val_loss -0.7485 +2024-11-22 16:17:31.915114: Pseudo dice [0.8519] +2024-11-22 16:17:31.915228: Epoch time: 19.26 s +2024-11-22 16:17:32.930583: +2024-11-22 16:17:32.931105: Epoch 5339 +2024-11-22 16:17:32.931255: Current learning rate: 0.00371 +2024-11-22 16:17:52.963508: train_loss -0.8006 +2024-11-22 16:17:52.966071: val_loss -0.7847 +2024-11-22 16:17:52.966204: Pseudo dice [0.8504] +2024-11-22 16:17:52.966314: Epoch time: 20.03 s +2024-11-22 16:17:53.836543: +2024-11-22 16:17:53.837486: Epoch 5340 +2024-11-22 16:17:53.837610: Current learning rate: 0.00371 +2024-11-22 16:18:12.554833: train_loss -0.8061 +2024-11-22 16:18:12.561790: val_loss -0.7858 +2024-11-22 16:18:12.561947: Pseudo dice [0.8462] +2024-11-22 16:18:12.582352: Epoch time: 18.72 s +2024-11-22 16:18:13.456283: +2024-11-22 16:18:13.457303: Epoch 5341 +2024-11-22 16:18:13.457428: Current learning rate: 0.00371 +2024-11-22 16:18:33.456197: train_loss -0.7952 +2024-11-22 16:18:33.465194: val_loss -0.7957 +2024-11-22 16:18:33.465343: Pseudo dice [0.8627] +2024-11-22 16:18:33.465440: Epoch time: 20.0 s +2024-11-22 16:18:34.424047: +2024-11-22 16:18:34.425237: Epoch 5342 +2024-11-22 16:18:34.425364: Current learning rate: 0.00371 +2024-11-22 16:18:53.578362: train_loss -0.8003 +2024-11-22 16:18:53.586264: val_loss -0.7737 +2024-11-22 16:18:53.586408: Pseudo dice [0.8512] +2024-11-22 16:18:53.586516: Epoch time: 19.16 s +2024-11-22 16:18:54.648832: +2024-11-22 16:18:54.650257: Epoch 5343 +2024-11-22 16:18:54.650380: Current learning rate: 0.00371 +2024-11-22 16:19:15.347239: train_loss -0.7995 +2024-11-22 16:19:15.358619: val_loss -0.7353 +2024-11-22 16:19:15.358759: Pseudo dice [0.8267] +2024-11-22 16:19:15.358869: Epoch time: 20.7 s +2024-11-22 16:19:16.634753: +2024-11-22 16:19:16.635972: Epoch 5344 +2024-11-22 16:19:16.636116: Current learning rate: 0.00371 +2024-11-22 16:19:36.007019: train_loss -0.8 +2024-11-22 16:19:36.035827: val_loss -0.7749 +2024-11-22 16:19:36.035954: Pseudo dice [0.8551] +2024-11-22 16:19:36.036050: Epoch time: 19.37 s +2024-11-22 16:19:37.033700: +2024-11-22 16:19:37.034586: Epoch 5345 +2024-11-22 16:19:37.034713: Current learning rate: 0.00371 +2024-11-22 16:19:56.143817: train_loss -0.8021 +2024-11-22 16:19:56.154376: val_loss -0.7786 +2024-11-22 16:19:56.154520: Pseudo dice [0.8529] +2024-11-22 16:19:56.154731: Epoch time: 19.11 s +2024-11-22 16:19:57.035821: +2024-11-22 16:19:57.036385: Epoch 5346 +2024-11-22 16:19:57.036503: Current learning rate: 0.0037 +2024-11-22 16:20:15.682662: train_loss -0.8015 +2024-11-22 16:20:15.696424: val_loss -0.7892 +2024-11-22 16:20:15.696565: Pseudo dice [0.8512] +2024-11-22 16:20:15.696685: Epoch time: 18.65 s +2024-11-22 16:20:16.580714: +2024-11-22 16:20:16.581555: Epoch 5347 +2024-11-22 16:20:16.581714: Current learning rate: 0.0037 +2024-11-22 16:20:36.539142: train_loss -0.8046 +2024-11-22 16:20:36.556615: val_loss -0.765 +2024-11-22 16:20:36.556792: Pseudo dice [0.8453] +2024-11-22 16:20:36.556902: Epoch time: 19.96 s +2024-11-22 16:20:37.431169: +2024-11-22 16:20:37.432096: Epoch 5348 +2024-11-22 16:20:37.432228: Current learning rate: 0.0037 +2024-11-22 16:20:56.558335: train_loss -0.7997 +2024-11-22 16:20:56.565099: val_loss -0.7752 +2024-11-22 16:20:56.565236: Pseudo dice [0.8581] +2024-11-22 16:20:56.565323: Epoch time: 19.13 s +2024-11-22 16:20:57.647007: +2024-11-22 16:20:57.648175: Epoch 5349 +2024-11-22 16:20:57.648296: Current learning rate: 0.0037 +2024-11-22 16:21:16.032323: train_loss -0.7946 +2024-11-22 16:21:16.039854: val_loss -0.7835 +2024-11-22 16:21:16.039988: Pseudo dice [0.8626] +2024-11-22 16:21:16.040091: Epoch time: 18.39 s +2024-11-22 16:21:17.192936: +2024-11-22 16:21:17.194690: Epoch 5350 +2024-11-22 16:21:17.194826: Current learning rate: 0.0037 +2024-11-22 16:21:37.359898: train_loss -0.8001 +2024-11-22 16:21:37.363237: val_loss -0.7727 +2024-11-22 16:21:37.363378: Pseudo dice [0.8494] +2024-11-22 16:21:37.363505: Epoch time: 20.17 s +2024-11-22 16:21:38.332039: +2024-11-22 16:21:38.333423: Epoch 5351 +2024-11-22 16:21:38.333555: Current learning rate: 0.0037 +2024-11-22 16:21:57.587866: train_loss -0.8015 +2024-11-22 16:21:57.599800: val_loss -0.7688 +2024-11-22 16:21:57.599967: Pseudo dice [0.8624] +2024-11-22 16:21:57.600081: Epoch time: 19.26 s +2024-11-22 16:21:58.644606: +2024-11-22 16:21:58.645596: Epoch 5352 +2024-11-22 16:21:58.645747: Current learning rate: 0.0037 +2024-11-22 16:22:18.620629: train_loss -0.7917 +2024-11-22 16:22:18.628268: val_loss -0.7806 +2024-11-22 16:22:18.628397: Pseudo dice [0.8618] +2024-11-22 16:22:18.628496: Epoch time: 19.98 s +2024-11-22 16:22:19.663893: +2024-11-22 16:22:19.664690: Epoch 5353 +2024-11-22 16:22:19.664822: Current learning rate: 0.0037 +2024-11-22 16:22:38.324847: train_loss -0.7855 +2024-11-22 16:22:38.330966: val_loss -0.7746 +2024-11-22 16:22:38.349674: Pseudo dice [0.8551] +2024-11-22 16:22:38.349864: Epoch time: 18.66 s +2024-11-22 16:22:39.321808: +2024-11-22 16:22:39.323024: Epoch 5354 +2024-11-22 16:22:39.323158: Current learning rate: 0.00369 +2024-11-22 16:22:59.051203: train_loss -0.794 +2024-11-22 16:22:59.053928: val_loss -0.7862 +2024-11-22 16:22:59.054050: Pseudo dice [0.8528] +2024-11-22 16:22:59.054159: Epoch time: 19.73 s +2024-11-22 16:22:59.919972: +2024-11-22 16:22:59.921930: Epoch 5355 +2024-11-22 16:22:59.922056: Current learning rate: 0.00369 +2024-11-22 16:23:19.081991: train_loss -0.7932 +2024-11-22 16:23:19.087317: val_loss -0.7808 +2024-11-22 16:23:19.087448: Pseudo dice [0.8421] +2024-11-22 16:23:19.087550: Epoch time: 19.16 s +2024-11-22 16:23:20.374768: +2024-11-22 16:23:20.375805: Epoch 5356 +2024-11-22 16:23:20.375944: Current learning rate: 0.00369 +2024-11-22 16:23:39.677732: train_loss -0.7916 +2024-11-22 16:23:39.688276: val_loss -0.7866 +2024-11-22 16:23:39.688416: Pseudo dice [0.8576] +2024-11-22 16:23:39.688506: Epoch time: 19.3 s +2024-11-22 16:23:40.936054: +2024-11-22 16:23:40.938089: Epoch 5357 +2024-11-22 16:23:40.938214: Current learning rate: 0.00369 +2024-11-22 16:23:59.184915: train_loss -0.7923 +2024-11-22 16:23:59.202547: val_loss -0.7756 +2024-11-22 16:23:59.202671: Pseudo dice [0.8456] +2024-11-22 16:23:59.202757: Epoch time: 18.25 s +2024-11-22 16:24:00.107852: +2024-11-22 16:24:00.109531: Epoch 5358 +2024-11-22 16:24:00.109656: Current learning rate: 0.00369 +2024-11-22 16:24:19.095508: train_loss -0.7864 +2024-11-22 16:24:19.098294: val_loss -0.7671 +2024-11-22 16:24:19.098399: Pseudo dice [0.8441] +2024-11-22 16:24:19.098506: Epoch time: 18.99 s +2024-11-22 16:24:19.969759: +2024-11-22 16:24:19.970671: Epoch 5359 +2024-11-22 16:24:19.970796: Current learning rate: 0.00369 +2024-11-22 16:24:38.961375: train_loss -0.7924 +2024-11-22 16:24:38.968720: val_loss -0.7724 +2024-11-22 16:24:38.968863: Pseudo dice [0.8509] +2024-11-22 16:24:38.968967: Epoch time: 18.99 s +2024-11-22 16:24:39.884996: +2024-11-22 16:24:39.887474: Epoch 5360 +2024-11-22 16:24:39.887612: Current learning rate: 0.00369 +2024-11-22 16:24:58.867704: train_loss -0.7888 +2024-11-22 16:24:58.874661: val_loss -0.7756 +2024-11-22 16:24:58.874813: Pseudo dice [0.8348] +2024-11-22 16:24:58.874983: Epoch time: 18.98 s +2024-11-22 16:24:59.793057: +2024-11-22 16:24:59.793952: Epoch 5361 +2024-11-22 16:24:59.794078: Current learning rate: 0.00369 +2024-11-22 16:25:18.694182: train_loss -0.7872 +2024-11-22 16:25:18.708215: val_loss -0.7759 +2024-11-22 16:25:18.708376: Pseudo dice [0.8436] +2024-11-22 16:25:18.708466: Epoch time: 18.9 s +2024-11-22 16:25:19.659506: +2024-11-22 16:25:19.660849: Epoch 5362 +2024-11-22 16:25:19.660989: Current learning rate: 0.00368 +2024-11-22 16:25:38.871747: train_loss -0.7946 +2024-11-22 16:25:38.877634: val_loss -0.7717 +2024-11-22 16:25:38.877754: Pseudo dice [0.8552] +2024-11-22 16:25:38.877856: Epoch time: 19.21 s +2024-11-22 16:25:39.892348: +2024-11-22 16:25:39.893763: Epoch 5363 +2024-11-22 16:25:39.893902: Current learning rate: 0.00368 +2024-11-22 16:25:59.934262: train_loss -0.7872 +2024-11-22 16:25:59.942791: val_loss -0.7707 +2024-11-22 16:25:59.942945: Pseudo dice [0.8513] +2024-11-22 16:25:59.943046: Epoch time: 20.04 s +2024-11-22 16:26:01.105066: +2024-11-22 16:26:01.106853: Epoch 5364 +2024-11-22 16:26:01.106995: Current learning rate: 0.00368 +2024-11-22 16:26:20.012859: train_loss -0.7866 +2024-11-22 16:26:20.021240: val_loss -0.7775 +2024-11-22 16:26:20.021392: Pseudo dice [0.8654] +2024-11-22 16:26:20.021502: Epoch time: 18.91 s +2024-11-22 16:26:20.932259: +2024-11-22 16:26:20.933725: Epoch 5365 +2024-11-22 16:26:20.933862: Current learning rate: 0.00368 +2024-11-22 16:26:39.920577: train_loss -0.797 +2024-11-22 16:26:39.941855: val_loss -0.7676 +2024-11-22 16:26:39.942035: Pseudo dice [0.8437] +2024-11-22 16:26:39.942145: Epoch time: 18.99 s +2024-11-22 16:26:41.026474: +2024-11-22 16:26:41.027518: Epoch 5366 +2024-11-22 16:26:41.027643: Current learning rate: 0.00368 +2024-11-22 16:27:00.944476: train_loss -0.7959 +2024-11-22 16:27:00.964373: val_loss -0.7516 +2024-11-22 16:27:00.964516: Pseudo dice [0.8457] +2024-11-22 16:27:00.964667: Epoch time: 19.92 s +2024-11-22 16:27:02.358209: +2024-11-22 16:27:02.359063: Epoch 5367 +2024-11-22 16:27:02.359186: Current learning rate: 0.00368 +2024-11-22 16:27:21.646746: train_loss -0.7902 +2024-11-22 16:27:21.649332: val_loss -0.7583 +2024-11-22 16:27:21.649437: Pseudo dice [0.8482] +2024-11-22 16:27:21.649544: Epoch time: 19.29 s +2024-11-22 16:27:22.593728: +2024-11-22 16:27:22.595046: Epoch 5368 +2024-11-22 16:27:22.595184: Current learning rate: 0.00368 +2024-11-22 16:27:42.083658: train_loss -0.7906 +2024-11-22 16:27:42.090007: val_loss -0.7655 +2024-11-22 16:27:42.090208: Pseudo dice [0.8466] +2024-11-22 16:27:42.090294: Epoch time: 19.49 s +2024-11-22 16:27:42.976637: +2024-11-22 16:27:42.977442: Epoch 5369 +2024-11-22 16:27:42.977571: Current learning rate: 0.00368 +2024-11-22 16:28:02.114337: train_loss -0.8025 +2024-11-22 16:28:02.128742: val_loss -0.7674 +2024-11-22 16:28:02.128899: Pseudo dice [0.8504] +2024-11-22 16:28:02.128996: Epoch time: 19.14 s +2024-11-22 16:28:03.084585: +2024-11-22 16:28:03.086353: Epoch 5370 +2024-11-22 16:28:03.086517: Current learning rate: 0.00367 +2024-11-22 16:28:22.493051: train_loss -0.8045 +2024-11-22 16:28:22.499673: val_loss -0.7647 +2024-11-22 16:28:22.499801: Pseudo dice [0.8573] +2024-11-22 16:28:22.499890: Epoch time: 19.41 s +2024-11-22 16:28:23.393610: +2024-11-22 16:28:23.394898: Epoch 5371 +2024-11-22 16:28:23.395031: Current learning rate: 0.00367 +2024-11-22 16:28:41.608018: train_loss -0.7993 +2024-11-22 16:28:41.614313: val_loss -0.789 +2024-11-22 16:28:41.614426: Pseudo dice [0.8422] +2024-11-22 16:28:41.614527: Epoch time: 18.22 s +2024-11-22 16:28:42.663125: +2024-11-22 16:28:42.664356: Epoch 5372 +2024-11-22 16:28:42.664474: Current learning rate: 0.00367 +2024-11-22 16:29:02.589870: train_loss -0.8017 +2024-11-22 16:29:02.597248: val_loss -0.7841 +2024-11-22 16:29:02.597410: Pseudo dice [0.857] +2024-11-22 16:29:02.597513: Epoch time: 19.93 s +2024-11-22 16:29:03.540605: +2024-11-22 16:29:03.541997: Epoch 5373 +2024-11-22 16:29:03.542145: Current learning rate: 0.00367 +2024-11-22 16:29:23.267935: train_loss -0.8067 +2024-11-22 16:29:23.273793: val_loss -0.7783 +2024-11-22 16:29:23.273908: Pseudo dice [0.844] +2024-11-22 16:29:23.273992: Epoch time: 19.73 s +2024-11-22 16:29:24.236130: +2024-11-22 16:29:24.237953: Epoch 5374 +2024-11-22 16:29:24.238074: Current learning rate: 0.00367 +2024-11-22 16:29:42.474402: train_loss -0.8126 +2024-11-22 16:29:42.490244: val_loss -0.7808 +2024-11-22 16:29:42.490402: Pseudo dice [0.8453] +2024-11-22 16:29:42.490511: Epoch time: 18.24 s +2024-11-22 16:29:43.490171: +2024-11-22 16:29:43.491411: Epoch 5375 +2024-11-22 16:29:43.491546: Current learning rate: 0.00367 +2024-11-22 16:30:02.744120: train_loss -0.7969 +2024-11-22 16:30:02.751484: val_loss -0.7897 +2024-11-22 16:30:02.751636: Pseudo dice [0.8414] +2024-11-22 16:30:02.751724: Epoch time: 19.25 s +2024-11-22 16:30:03.725189: +2024-11-22 16:30:03.726836: Epoch 5376 +2024-11-22 16:30:03.726958: Current learning rate: 0.00367 +2024-11-22 16:30:24.629436: train_loss -0.7961 +2024-11-22 16:30:24.634433: val_loss -0.7712 +2024-11-22 16:30:24.634590: Pseudo dice [0.8516] +2024-11-22 16:30:24.634688: Epoch time: 20.91 s +2024-11-22 16:30:25.489099: +2024-11-22 16:30:25.489982: Epoch 5377 +2024-11-22 16:30:25.490116: Current learning rate: 0.00367 +2024-11-22 16:30:45.575492: train_loss -0.8094 +2024-11-22 16:30:45.580647: val_loss -0.7912 +2024-11-22 16:30:45.580780: Pseudo dice [0.8594] +2024-11-22 16:30:45.580873: Epoch time: 20.09 s +2024-11-22 16:30:46.597005: +2024-11-22 16:30:46.598934: Epoch 5378 +2024-11-22 16:30:46.599094: Current learning rate: 0.00366 +2024-11-22 16:31:06.353950: train_loss -0.7952 +2024-11-22 16:31:06.360367: val_loss -0.7756 +2024-11-22 16:31:06.360520: Pseudo dice [0.8561] +2024-11-22 16:31:06.360620: Epoch time: 19.76 s +2024-11-22 16:31:07.687342: +2024-11-22 16:31:07.687897: Epoch 5379 +2024-11-22 16:31:07.688032: Current learning rate: 0.00366 +2024-11-22 16:31:28.355028: train_loss -0.7987 +2024-11-22 16:31:28.356728: val_loss -0.7787 +2024-11-22 16:31:28.356829: Pseudo dice [0.8487] +2024-11-22 16:31:28.356913: Epoch time: 20.67 s +2024-11-22 16:31:29.224945: +2024-11-22 16:31:29.225705: Epoch 5380 +2024-11-22 16:31:29.225851: Current learning rate: 0.00366 +2024-11-22 16:31:49.408761: train_loss -0.8002 +2024-11-22 16:31:49.414578: val_loss -0.7615 +2024-11-22 16:31:49.414717: Pseudo dice [0.8544] +2024-11-22 16:31:49.414808: Epoch time: 20.18 s +2024-11-22 16:31:50.330855: +2024-11-22 16:31:50.331815: Epoch 5381 +2024-11-22 16:31:50.331960: Current learning rate: 0.00366 +2024-11-22 16:32:10.122405: train_loss -0.7942 +2024-11-22 16:32:10.131745: val_loss -0.7866 +2024-11-22 16:32:10.131926: Pseudo dice [0.8625] +2024-11-22 16:32:10.132026: Epoch time: 19.79 s +2024-11-22 16:32:10.997999: +2024-11-22 16:32:10.999985: Epoch 5382 +2024-11-22 16:32:11.000127: Current learning rate: 0.00366 +2024-11-22 16:32:30.174473: train_loss -0.7878 +2024-11-22 16:32:30.181290: val_loss -0.7859 +2024-11-22 16:32:30.181429: Pseudo dice [0.8534] +2024-11-22 16:32:30.181556: Epoch time: 19.18 s +2024-11-22 16:32:31.076559: +2024-11-22 16:32:31.077621: Epoch 5383 +2024-11-22 16:32:31.077768: Current learning rate: 0.00366 +2024-11-22 16:32:50.016784: train_loss -0.7959 +2024-11-22 16:32:50.023025: val_loss -0.7751 +2024-11-22 16:32:50.023154: Pseudo dice [0.8621] +2024-11-22 16:32:50.023236: Epoch time: 18.94 s +2024-11-22 16:32:50.991418: +2024-11-22 16:32:51.012221: Epoch 5384 +2024-11-22 16:32:51.012365: Current learning rate: 0.00366 +2024-11-22 16:33:09.955162: train_loss -0.7989 +2024-11-22 16:33:09.961473: val_loss -0.7921 +2024-11-22 16:33:09.961688: Pseudo dice [0.8542] +2024-11-22 16:33:09.961861: Epoch time: 18.96 s +2024-11-22 16:33:10.840413: +2024-11-22 16:33:10.841291: Epoch 5385 +2024-11-22 16:33:10.841423: Current learning rate: 0.00366 +2024-11-22 16:33:30.150568: train_loss -0.7998 +2024-11-22 16:33:30.167497: val_loss -0.7645 +2024-11-22 16:33:30.167643: Pseudo dice [0.8598] +2024-11-22 16:33:30.167740: Epoch time: 19.31 s +2024-11-22 16:33:31.130346: +2024-11-22 16:33:31.132371: Epoch 5386 +2024-11-22 16:33:31.132504: Current learning rate: 0.00365 +2024-11-22 16:33:52.030282: train_loss -0.8014 +2024-11-22 16:33:52.034666: val_loss -0.7841 +2024-11-22 16:33:52.034782: Pseudo dice [0.85] +2024-11-22 16:33:52.034883: Epoch time: 20.9 s +2024-11-22 16:33:52.899187: +2024-11-22 16:33:52.899381: Epoch 5387 +2024-11-22 16:33:52.899508: Current learning rate: 0.00365 +2024-11-22 16:34:12.340657: train_loss -0.8015 +2024-11-22 16:34:12.344243: val_loss -0.7619 +2024-11-22 16:34:12.344364: Pseudo dice [0.8444] +2024-11-22 16:34:12.344460: Epoch time: 19.44 s +2024-11-22 16:34:13.211128: +2024-11-22 16:34:13.211340: Epoch 5388 +2024-11-22 16:34:13.211482: Current learning rate: 0.00365 +2024-11-22 16:34:31.813871: train_loss -0.8074 +2024-11-22 16:34:31.814107: val_loss -0.7863 +2024-11-22 16:34:31.814214: Pseudo dice [0.8554] +2024-11-22 16:34:31.816515: Epoch time: 18.6 s +2024-11-22 16:34:32.902737: +2024-11-22 16:34:32.902935: Epoch 5389 +2024-11-22 16:34:32.903077: Current learning rate: 0.00365 +2024-11-22 16:34:51.802883: train_loss -0.8009 +2024-11-22 16:34:51.807709: val_loss -0.759 +2024-11-22 16:34:51.807853: Pseudo dice [0.8584] +2024-11-22 16:34:51.807946: Epoch time: 18.9 s +2024-11-22 16:34:52.788859: +2024-11-22 16:34:52.789085: Epoch 5390 +2024-11-22 16:34:52.789213: Current learning rate: 0.00365 +2024-11-22 16:35:11.314029: train_loss -0.8049 +2024-11-22 16:35:11.318635: val_loss -0.7898 +2024-11-22 16:35:11.318770: Pseudo dice [0.8414] +2024-11-22 16:35:11.318859: Epoch time: 18.53 s +2024-11-22 16:35:12.227197: +2024-11-22 16:35:12.227431: Epoch 5391 +2024-11-22 16:35:12.227568: Current learning rate: 0.00365 +2024-11-22 16:35:31.185264: train_loss -0.8008 +2024-11-22 16:35:31.185795: val_loss -0.7777 +2024-11-22 16:35:31.186103: Pseudo dice [0.8611] +2024-11-22 16:35:31.186202: Epoch time: 18.96 s +2024-11-22 16:35:32.050169: +2024-11-22 16:35:32.050392: Epoch 5392 +2024-11-22 16:35:32.050542: Current learning rate: 0.00365 +2024-11-22 16:35:51.581052: train_loss -0.7975 +2024-11-22 16:35:51.585921: val_loss -0.7805 +2024-11-22 16:35:51.586078: Pseudo dice [0.8582] +2024-11-22 16:35:51.586177: Epoch time: 19.53 s +2024-11-22 16:35:52.686866: +2024-11-22 16:35:52.687077: Epoch 5393 +2024-11-22 16:35:52.687209: Current learning rate: 0.00365 +2024-11-22 16:36:12.309260: train_loss -0.7836 +2024-11-22 16:36:12.313196: val_loss -0.7796 +2024-11-22 16:36:12.313353: Pseudo dice [0.846] +2024-11-22 16:36:12.313469: Epoch time: 19.62 s +2024-11-22 16:36:13.359300: +2024-11-22 16:36:13.359544: Epoch 5394 +2024-11-22 16:36:13.359671: Current learning rate: 0.00364 +2024-11-22 16:36:32.492009: train_loss -0.794 +2024-11-22 16:36:32.498809: val_loss -0.7551 +2024-11-22 16:36:32.498921: Pseudo dice [0.8511] +2024-11-22 16:36:32.499017: Epoch time: 19.13 s +2024-11-22 16:36:33.639108: +2024-11-22 16:36:33.639305: Epoch 5395 +2024-11-22 16:36:33.639417: Current learning rate: 0.00364 +2024-11-22 16:36:51.665872: train_loss -0.7926 +2024-11-22 16:36:51.666650: val_loss -0.7629 +2024-11-22 16:36:51.666742: Pseudo dice [0.8627] +2024-11-22 16:36:51.666832: Epoch time: 18.03 s +2024-11-22 16:36:52.523971: +2024-11-22 16:36:52.524178: Epoch 5396 +2024-11-22 16:36:52.524289: Current learning rate: 0.00364 +2024-11-22 16:37:11.360575: train_loss -0.8012 +2024-11-22 16:37:11.368032: val_loss -0.7827 +2024-11-22 16:37:11.368173: Pseudo dice [0.8465] +2024-11-22 16:37:11.368259: Epoch time: 18.84 s +2024-11-22 16:37:12.244885: +2024-11-22 16:37:12.245090: Epoch 5397 +2024-11-22 16:37:12.245401: Current learning rate: 0.00364 +2024-11-22 16:37:32.616696: train_loss -0.8051 +2024-11-22 16:37:32.620929: val_loss -0.7457 +2024-11-22 16:37:32.621082: Pseudo dice [0.8565] +2024-11-22 16:37:32.621178: Epoch time: 20.37 s +2024-11-22 16:37:33.490891: +2024-11-22 16:37:33.491127: Epoch 5398 +2024-11-22 16:37:33.491297: Current learning rate: 0.00364 +2024-11-22 16:37:52.740842: train_loss -0.8038 +2024-11-22 16:37:52.750214: val_loss -0.745 +2024-11-22 16:37:52.750730: Pseudo dice [0.8565] +2024-11-22 16:37:52.751053: Epoch time: 19.25 s +2024-11-22 16:37:53.635048: +2024-11-22 16:37:53.635697: Epoch 5399 +2024-11-22 16:37:53.635816: Current learning rate: 0.00364 +2024-11-22 16:38:12.839411: train_loss -0.8053 +2024-11-22 16:38:12.861778: val_loss -0.7656 +2024-11-22 16:38:12.861930: Pseudo dice [0.8529] +2024-11-22 16:38:12.862020: Epoch time: 19.21 s +2024-11-22 16:38:14.044429: +2024-11-22 16:38:14.044677: Epoch 5400 +2024-11-22 16:38:14.044814: Current learning rate: 0.00364 +2024-11-22 16:38:33.948731: train_loss -0.8015 +2024-11-22 16:38:33.957801: val_loss -0.7627 +2024-11-22 16:38:33.957951: Pseudo dice [0.841] +2024-11-22 16:38:33.958040: Epoch time: 19.91 s +2024-11-22 16:38:34.907628: +2024-11-22 16:38:34.907835: Epoch 5401 +2024-11-22 16:38:34.907964: Current learning rate: 0.00364 +2024-11-22 16:38:54.684220: train_loss -0.8076 +2024-11-22 16:38:54.687813: val_loss -0.7613 +2024-11-22 16:38:54.687955: Pseudo dice [0.8505] +2024-11-22 16:38:54.688080: Epoch time: 19.78 s +2024-11-22 16:38:55.626912: +2024-11-22 16:38:55.627728: Epoch 5402 +2024-11-22 16:38:55.627868: Current learning rate: 0.00363 +2024-11-22 16:39:14.485155: train_loss -0.8106 +2024-11-22 16:39:14.492352: val_loss -0.7831 +2024-11-22 16:39:14.492508: Pseudo dice [0.8528] +2024-11-22 16:39:14.492676: Epoch time: 18.86 s +2024-11-22 16:39:15.474324: +2024-11-22 16:39:15.474906: Epoch 5403 +2024-11-22 16:39:15.475043: Current learning rate: 0.00363 +2024-11-22 16:39:34.897554: train_loss -0.8052 +2024-11-22 16:39:34.901642: val_loss -0.7631 +2024-11-22 16:39:34.901753: Pseudo dice [0.8492] +2024-11-22 16:39:34.901853: Epoch time: 19.42 s +2024-11-22 16:39:35.769785: +2024-11-22 16:39:35.771261: Epoch 5404 +2024-11-22 16:39:35.771407: Current learning rate: 0.00363 +2024-11-22 16:39:55.771376: train_loss -0.7972 +2024-11-22 16:39:55.778342: val_loss -0.7729 +2024-11-22 16:39:55.778480: Pseudo dice [0.8585] +2024-11-22 16:39:55.778565: Epoch time: 20.0 s +2024-11-22 16:39:56.675011: +2024-11-22 16:39:56.676861: Epoch 5405 +2024-11-22 16:39:56.676995: Current learning rate: 0.00363 +2024-11-22 16:40:15.290998: train_loss -0.8026 +2024-11-22 16:40:15.299347: val_loss -0.7912 +2024-11-22 16:40:15.299505: Pseudo dice [0.8516] +2024-11-22 16:40:15.299701: Epoch time: 18.62 s +2024-11-22 16:40:16.265669: +2024-11-22 16:40:16.267652: Epoch 5406 +2024-11-22 16:40:16.267774: Current learning rate: 0.00363 +2024-11-22 16:40:35.754495: train_loss -0.8059 +2024-11-22 16:40:35.759206: val_loss -0.7606 +2024-11-22 16:40:35.759340: Pseudo dice [0.8471] +2024-11-22 16:40:35.759429: Epoch time: 19.49 s +2024-11-22 16:40:36.655778: +2024-11-22 16:40:36.657391: Epoch 5407 +2024-11-22 16:40:36.657511: Current learning rate: 0.00363 +2024-11-22 16:40:57.331703: train_loss -0.8028 +2024-11-22 16:40:57.338069: val_loss -0.7687 +2024-11-22 16:40:57.338205: Pseudo dice [0.8609] +2024-11-22 16:40:57.338298: Epoch time: 20.68 s +2024-11-22 16:40:58.350260: +2024-11-22 16:40:58.352098: Epoch 5408 +2024-11-22 16:40:58.352235: Current learning rate: 0.00363 +2024-11-22 16:41:18.810982: train_loss -0.8018 +2024-11-22 16:41:18.813772: val_loss -0.7773 +2024-11-22 16:41:18.813885: Pseudo dice [0.846] +2024-11-22 16:41:18.813970: Epoch time: 20.46 s +2024-11-22 16:41:19.705142: +2024-11-22 16:41:19.705575: Epoch 5409 +2024-11-22 16:41:19.705705: Current learning rate: 0.00363 +2024-11-22 16:41:39.063344: train_loss -0.8026 +2024-11-22 16:41:39.071113: val_loss -0.7693 +2024-11-22 16:41:39.071256: Pseudo dice [0.8535] +2024-11-22 16:41:39.071353: Epoch time: 19.36 s +2024-11-22 16:41:40.132679: +2024-11-22 16:41:40.133544: Epoch 5410 +2024-11-22 16:41:40.133665: Current learning rate: 0.00362 +2024-11-22 16:41:59.710173: train_loss -0.7897 +2024-11-22 16:41:59.717252: val_loss -0.7645 +2024-11-22 16:41:59.717507: Pseudo dice [0.8562] +2024-11-22 16:41:59.717678: Epoch time: 19.58 s +2024-11-22 16:42:00.720963: +2024-11-22 16:42:00.722383: Epoch 5411 +2024-11-22 16:42:00.722500: Current learning rate: 0.00362 +2024-11-22 16:42:20.607862: train_loss -0.7962 +2024-11-22 16:42:20.628440: val_loss -0.7822 +2024-11-22 16:42:20.628641: Pseudo dice [0.8547] +2024-11-22 16:42:20.628753: Epoch time: 19.89 s +2024-11-22 16:42:22.096615: +2024-11-22 16:42:22.098029: Epoch 5412 +2024-11-22 16:42:22.098166: Current learning rate: 0.00362 +2024-11-22 16:42:41.003517: train_loss -0.7877 +2024-11-22 16:42:41.011769: val_loss -0.7636 +2024-11-22 16:42:41.011919: Pseudo dice [0.8395] +2024-11-22 16:42:41.012021: Epoch time: 18.91 s +2024-11-22 16:42:42.053736: +2024-11-22 16:42:42.055190: Epoch 5413 +2024-11-22 16:42:42.055307: Current learning rate: 0.00362 +2024-11-22 16:43:02.760334: train_loss -0.7805 +2024-11-22 16:43:02.769640: val_loss -0.7638 +2024-11-22 16:43:02.769779: Pseudo dice [0.8421] +2024-11-22 16:43:02.769870: Epoch time: 20.71 s +2024-11-22 16:43:03.693913: +2024-11-22 16:43:03.694683: Epoch 5414 +2024-11-22 16:43:03.694823: Current learning rate: 0.00362 +2024-11-22 16:43:23.584945: train_loss -0.7744 +2024-11-22 16:43:23.591807: val_loss -0.7694 +2024-11-22 16:43:23.591952: Pseudo dice [0.8588] +2024-11-22 16:43:23.592075: Epoch time: 19.89 s +2024-11-22 16:43:24.463202: +2024-11-22 16:43:24.463649: Epoch 5415 +2024-11-22 16:43:24.463777: Current learning rate: 0.00362 +2024-11-22 16:43:43.201227: train_loss -0.7932 +2024-11-22 16:43:43.206916: val_loss -0.7656 +2024-11-22 16:43:43.207075: Pseudo dice [0.8581] +2024-11-22 16:43:43.207175: Epoch time: 18.74 s +2024-11-22 16:43:44.238136: +2024-11-22 16:43:44.239478: Epoch 5416 +2024-11-22 16:43:44.239604: Current learning rate: 0.00362 +2024-11-22 16:44:03.118457: train_loss -0.7869 +2024-11-22 16:44:03.123756: val_loss -0.7768 +2024-11-22 16:44:03.123886: Pseudo dice [0.8494] +2024-11-22 16:44:03.123981: Epoch time: 18.88 s +2024-11-22 16:44:04.124386: +2024-11-22 16:44:04.125565: Epoch 5417 +2024-11-22 16:44:04.125690: Current learning rate: 0.00362 +2024-11-22 16:44:23.769084: train_loss -0.8023 +2024-11-22 16:44:23.779864: val_loss -0.782 +2024-11-22 16:44:23.780009: Pseudo dice [0.8545] +2024-11-22 16:44:23.780111: Epoch time: 19.65 s +2024-11-22 16:44:24.733778: +2024-11-22 16:44:24.735771: Epoch 5418 +2024-11-22 16:44:24.735917: Current learning rate: 0.00361 +2024-11-22 16:44:44.676996: train_loss -0.7976 +2024-11-22 16:44:44.683637: val_loss -0.7571 +2024-11-22 16:44:44.683762: Pseudo dice [0.8588] +2024-11-22 16:44:44.683868: Epoch time: 19.94 s +2024-11-22 16:44:45.731951: +2024-11-22 16:44:45.733938: Epoch 5419 +2024-11-22 16:44:45.734061: Current learning rate: 0.00361 +2024-11-22 16:45:04.372867: train_loss -0.7992 +2024-11-22 16:45:04.391214: val_loss -0.7503 +2024-11-22 16:45:04.391358: Pseudo dice [0.838] +2024-11-22 16:45:04.391455: Epoch time: 18.64 s +2024-11-22 16:45:05.457411: +2024-11-22 16:45:05.458925: Epoch 5420 +2024-11-22 16:45:05.459046: Current learning rate: 0.00361 +2024-11-22 16:45:25.425117: train_loss -0.7952 +2024-11-22 16:45:25.429333: val_loss -0.7846 +2024-11-22 16:45:25.429460: Pseudo dice [0.8613] +2024-11-22 16:45:25.429550: Epoch time: 19.97 s +2024-11-22 16:45:26.334264: +2024-11-22 16:45:26.334913: Epoch 5421 +2024-11-22 16:45:26.335037: Current learning rate: 0.00361 +2024-11-22 16:45:45.939476: train_loss -0.8035 +2024-11-22 16:45:45.954015: val_loss -0.7802 +2024-11-22 16:45:45.954159: Pseudo dice [0.8428] +2024-11-22 16:45:45.954252: Epoch time: 19.61 s +2024-11-22 16:45:46.977728: +2024-11-22 16:45:46.978796: Epoch 5422 +2024-11-22 16:45:46.978918: Current learning rate: 0.00361 +2024-11-22 16:46:05.307353: train_loss -0.7958 +2024-11-22 16:46:05.309788: val_loss -0.8057 +2024-11-22 16:46:05.309900: Pseudo dice [0.8512] +2024-11-22 16:46:05.309989: Epoch time: 18.33 s +2024-11-22 16:46:06.177626: +2024-11-22 16:46:06.179517: Epoch 5423 +2024-11-22 16:46:06.179651: Current learning rate: 0.00361 +2024-11-22 16:46:26.303565: train_loss -0.7884 +2024-11-22 16:46:26.307263: val_loss -0.7661 +2024-11-22 16:46:26.307365: Pseudo dice [0.8511] +2024-11-22 16:46:26.307465: Epoch time: 20.13 s +2024-11-22 16:46:27.592309: +2024-11-22 16:46:27.593362: Epoch 5424 +2024-11-22 16:46:27.593485: Current learning rate: 0.00361 +2024-11-22 16:46:47.627682: train_loss -0.7725 +2024-11-22 16:46:47.631339: val_loss -0.7419 +2024-11-22 16:46:47.631478: Pseudo dice [0.8576] +2024-11-22 16:46:47.631563: Epoch time: 20.04 s +2024-11-22 16:46:48.666832: +2024-11-22 16:46:48.667794: Epoch 5425 +2024-11-22 16:46:48.667926: Current learning rate: 0.00361 +2024-11-22 16:47:08.285804: train_loss -0.7942 +2024-11-22 16:47:08.296690: val_loss -0.8018 +2024-11-22 16:47:08.296847: Pseudo dice [0.8554] +2024-11-22 16:47:08.296938: Epoch time: 19.62 s +2024-11-22 16:47:09.244458: +2024-11-22 16:47:09.245384: Epoch 5426 +2024-11-22 16:47:09.245518: Current learning rate: 0.0036 +2024-11-22 16:47:27.845555: train_loss -0.7997 +2024-11-22 16:47:27.849208: val_loss -0.7771 +2024-11-22 16:47:27.849405: Pseudo dice [0.8462] +2024-11-22 16:47:27.849515: Epoch time: 18.6 s +2024-11-22 16:47:28.918745: +2024-11-22 16:47:28.920147: Epoch 5427 +2024-11-22 16:47:28.920272: Current learning rate: 0.0036 +2024-11-22 16:47:49.191270: train_loss -0.7984 +2024-11-22 16:47:49.198716: val_loss -0.7718 +2024-11-22 16:47:49.198923: Pseudo dice [0.8549] +2024-11-22 16:47:49.199054: Epoch time: 20.27 s +2024-11-22 16:47:50.200887: +2024-11-22 16:47:50.202451: Epoch 5428 +2024-11-22 16:47:50.202597: Current learning rate: 0.0036 +2024-11-22 16:48:08.654347: train_loss -0.7958 +2024-11-22 16:48:08.658140: val_loss -0.7811 +2024-11-22 16:48:08.658254: Pseudo dice [0.8559] +2024-11-22 16:48:08.658336: Epoch time: 18.45 s +2024-11-22 16:48:09.633931: +2024-11-22 16:48:09.635250: Epoch 5429 +2024-11-22 16:48:09.635382: Current learning rate: 0.0036 +2024-11-22 16:48:29.794161: train_loss -0.8006 +2024-11-22 16:48:29.802165: val_loss -0.7934 +2024-11-22 16:48:29.802304: Pseudo dice [0.8578] +2024-11-22 16:48:29.802668: Epoch time: 20.16 s +2024-11-22 16:48:30.833886: +2024-11-22 16:48:30.835541: Epoch 5430 +2024-11-22 16:48:30.835664: Current learning rate: 0.0036 +2024-11-22 16:48:49.913918: train_loss -0.7967 +2024-11-22 16:48:49.918262: val_loss -0.754 +2024-11-22 16:48:49.918373: Pseudo dice [0.8401] +2024-11-22 16:48:49.918483: Epoch time: 19.08 s +2024-11-22 16:48:50.960976: +2024-11-22 16:48:50.961749: Epoch 5431 +2024-11-22 16:48:50.961866: Current learning rate: 0.0036 +2024-11-22 16:49:10.613857: train_loss -0.7999 +2024-11-22 16:49:10.621304: val_loss -0.7725 +2024-11-22 16:49:10.621450: Pseudo dice [0.8491] +2024-11-22 16:49:10.621570: Epoch time: 19.65 s +2024-11-22 16:49:11.496654: +2024-11-22 16:49:11.497261: Epoch 5432 +2024-11-22 16:49:11.497383: Current learning rate: 0.0036 +2024-11-22 16:49:31.056403: train_loss -0.8001 +2024-11-22 16:49:31.062211: val_loss -0.7652 +2024-11-22 16:49:31.062428: Pseudo dice [0.845] +2024-11-22 16:49:31.062528: Epoch time: 19.56 s +2024-11-22 16:49:31.940868: +2024-11-22 16:49:31.941346: Epoch 5433 +2024-11-22 16:49:31.941474: Current learning rate: 0.0036 +2024-11-22 16:49:51.736448: train_loss -0.8046 +2024-11-22 16:49:51.742266: val_loss -0.7694 +2024-11-22 16:49:51.742382: Pseudo dice [0.8552] +2024-11-22 16:49:51.742472: Epoch time: 19.8 s +2024-11-22 16:49:52.722873: +2024-11-22 16:49:52.723677: Epoch 5434 +2024-11-22 16:49:52.723793: Current learning rate: 0.00359 +2024-11-22 16:50:12.144531: train_loss -0.7865 +2024-11-22 16:50:12.169768: val_loss -0.7837 +2024-11-22 16:50:12.169929: Pseudo dice [0.8486] +2024-11-22 16:50:12.170030: Epoch time: 19.42 s +2024-11-22 16:50:13.524165: +2024-11-22 16:50:13.526022: Epoch 5435 +2024-11-22 16:50:13.526159: Current learning rate: 0.00359 +2024-11-22 16:50:32.868652: train_loss -0.7964 +2024-11-22 16:50:32.884445: val_loss -0.764 +2024-11-22 16:50:32.884574: Pseudo dice [0.845] +2024-11-22 16:50:32.884660: Epoch time: 19.35 s +2024-11-22 16:50:33.922175: +2024-11-22 16:50:33.923306: Epoch 5436 +2024-11-22 16:50:33.923458: Current learning rate: 0.00359 +2024-11-22 16:50:53.405794: train_loss -0.7911 +2024-11-22 16:50:53.414218: val_loss -0.7757 +2024-11-22 16:50:53.414333: Pseudo dice [0.8535] +2024-11-22 16:50:53.414477: Epoch time: 19.48 s +2024-11-22 16:50:54.394317: +2024-11-22 16:50:54.395092: Epoch 5437 +2024-11-22 16:50:54.395227: Current learning rate: 0.00359 +2024-11-22 16:51:14.102614: train_loss -0.7916 +2024-11-22 16:51:14.112190: val_loss -0.7557 +2024-11-22 16:51:14.112345: Pseudo dice [0.8443] +2024-11-22 16:51:14.112460: Epoch time: 19.71 s +2024-11-22 16:51:15.134568: +2024-11-22 16:51:15.135377: Epoch 5438 +2024-11-22 16:51:15.135506: Current learning rate: 0.00359 +2024-11-22 16:51:34.642473: train_loss -0.8113 +2024-11-22 16:51:34.649545: val_loss -0.7761 +2024-11-22 16:51:34.649681: Pseudo dice [0.8536] +2024-11-22 16:51:34.649795: Epoch time: 19.51 s +2024-11-22 16:51:35.658389: +2024-11-22 16:51:35.659746: Epoch 5439 +2024-11-22 16:51:35.659870: Current learning rate: 0.00359 +2024-11-22 16:51:56.369534: train_loss -0.8002 +2024-11-22 16:51:56.375092: val_loss -0.783 +2024-11-22 16:51:56.375223: Pseudo dice [0.8606] +2024-11-22 16:51:56.375315: Epoch time: 20.71 s +2024-11-22 16:51:57.335098: +2024-11-22 16:51:57.337296: Epoch 5440 +2024-11-22 16:51:57.337424: Current learning rate: 0.00359 +2024-11-22 16:52:16.969576: train_loss -0.8026 +2024-11-22 16:52:16.987095: val_loss -0.771 +2024-11-22 16:52:16.987230: Pseudo dice [0.855] +2024-11-22 16:52:16.987334: Epoch time: 19.64 s +2024-11-22 16:52:17.995032: +2024-11-22 16:52:17.996673: Epoch 5441 +2024-11-22 16:52:17.996802: Current learning rate: 0.00358 +2024-11-22 16:52:37.263160: train_loss -0.8018 +2024-11-22 16:52:37.277190: val_loss -0.7881 +2024-11-22 16:52:37.277323: Pseudo dice [0.8567] +2024-11-22 16:52:37.277415: Epoch time: 19.27 s +2024-11-22 16:52:38.187633: +2024-11-22 16:52:38.188620: Epoch 5442 +2024-11-22 16:52:38.188750: Current learning rate: 0.00358 +2024-11-22 16:52:58.194040: train_loss -0.7982 +2024-11-22 16:52:58.217185: val_loss -0.7693 +2024-11-22 16:52:58.217328: Pseudo dice [0.8526] +2024-11-22 16:52:58.217438: Epoch time: 20.01 s +2024-11-22 16:52:59.141681: +2024-11-22 16:52:59.143206: Epoch 5443 +2024-11-22 16:52:59.143342: Current learning rate: 0.00358 +2024-11-22 16:53:18.482173: train_loss -0.7992 +2024-11-22 16:53:18.486073: val_loss -0.7628 +2024-11-22 16:53:18.486210: Pseudo dice [0.8646] +2024-11-22 16:53:18.486315: Epoch time: 19.34 s +2024-11-22 16:53:19.358988: +2024-11-22 16:53:19.360051: Epoch 5444 +2024-11-22 16:53:19.360179: Current learning rate: 0.00358 +2024-11-22 16:53:38.946745: train_loss -0.8016 +2024-11-22 16:53:38.950661: val_loss -0.7513 +2024-11-22 16:53:38.950795: Pseudo dice [0.8454] +2024-11-22 16:53:38.950889: Epoch time: 19.59 s +2024-11-22 16:53:39.823842: +2024-11-22 16:53:39.825467: Epoch 5445 +2024-11-22 16:53:39.825590: Current learning rate: 0.00358 +2024-11-22 16:53:59.537098: train_loss -0.7932 +2024-11-22 16:53:59.539452: val_loss -0.7713 +2024-11-22 16:53:59.539594: Pseudo dice [0.8602] +2024-11-22 16:53:59.539685: Epoch time: 19.71 s +2024-11-22 16:54:00.408164: +2024-11-22 16:54:00.409544: Epoch 5446 +2024-11-22 16:54:00.409672: Current learning rate: 0.00358 +2024-11-22 16:54:20.525572: train_loss -0.7901 +2024-11-22 16:54:20.532184: val_loss -0.7694 +2024-11-22 16:54:20.532318: Pseudo dice [0.8573] +2024-11-22 16:54:20.532413: Epoch time: 20.12 s +2024-11-22 16:54:21.917639: +2024-11-22 16:54:21.919204: Epoch 5447 +2024-11-22 16:54:21.919333: Current learning rate: 0.00358 +2024-11-22 16:54:40.830965: train_loss -0.8001 +2024-11-22 16:54:40.846720: val_loss -0.7802 +2024-11-22 16:54:40.846913: Pseudo dice [0.8544] +2024-11-22 16:54:40.847013: Epoch time: 18.91 s +2024-11-22 16:54:41.780731: +2024-11-22 16:54:41.781972: Epoch 5448 +2024-11-22 16:54:41.782114: Current learning rate: 0.00358 +2024-11-22 16:55:01.450608: train_loss -0.7941 +2024-11-22 16:55:01.458688: val_loss -0.7617 +2024-11-22 16:55:01.458845: Pseudo dice [0.8566] +2024-11-22 16:55:01.458953: Epoch time: 19.67 s +2024-11-22 16:55:02.333626: +2024-11-22 16:55:02.334864: Epoch 5449 +2024-11-22 16:55:02.335007: Current learning rate: 0.00357 +2024-11-22 16:55:22.932621: train_loss -0.7782 +2024-11-22 16:55:22.936404: val_loss -0.7689 +2024-11-22 16:55:22.936541: Pseudo dice [0.8496] +2024-11-22 16:55:22.936633: Epoch time: 20.6 s +2024-11-22 16:55:24.240612: +2024-11-22 16:55:24.241910: Epoch 5450 +2024-11-22 16:55:24.242037: Current learning rate: 0.00357 +2024-11-22 16:55:43.582158: train_loss -0.7918 +2024-11-22 16:55:43.591162: val_loss -0.7721 +2024-11-22 16:55:43.591304: Pseudo dice [0.8508] +2024-11-22 16:55:43.591405: Epoch time: 19.34 s +2024-11-22 16:55:44.578436: +2024-11-22 16:55:44.580159: Epoch 5451 +2024-11-22 16:55:44.580284: Current learning rate: 0.00357 +2024-11-22 16:56:04.781949: train_loss -0.7919 +2024-11-22 16:56:04.789056: val_loss -0.7722 +2024-11-22 16:56:04.789330: Pseudo dice [0.8555] +2024-11-22 16:56:04.789537: Epoch time: 20.2 s +2024-11-22 16:56:05.767130: +2024-11-22 16:56:05.769233: Epoch 5452 +2024-11-22 16:56:05.769496: Current learning rate: 0.00357 +2024-11-22 16:56:25.582925: train_loss -0.7885 +2024-11-22 16:56:25.589005: val_loss -0.742 +2024-11-22 16:56:25.589158: Pseudo dice [0.8401] +2024-11-22 16:56:25.589243: Epoch time: 19.82 s +2024-11-22 16:56:26.581175: +2024-11-22 16:56:26.582343: Epoch 5453 +2024-11-22 16:56:26.582475: Current learning rate: 0.00357 +2024-11-22 16:56:46.726261: train_loss -0.7855 +2024-11-22 16:56:46.728696: val_loss -0.7735 +2024-11-22 16:56:46.728808: Pseudo dice [0.8506] +2024-11-22 16:56:46.728960: Epoch time: 20.15 s +2024-11-22 16:56:47.597947: +2024-11-22 16:56:47.599817: Epoch 5454 +2024-11-22 16:56:47.599960: Current learning rate: 0.00357 +2024-11-22 16:57:07.807499: train_loss -0.7968 +2024-11-22 16:57:07.812598: val_loss -0.7672 +2024-11-22 16:57:07.812736: Pseudo dice [0.8544] +2024-11-22 16:57:07.812850: Epoch time: 20.21 s +2024-11-22 16:57:08.722185: +2024-11-22 16:57:08.723730: Epoch 5455 +2024-11-22 16:57:08.744889: Current learning rate: 0.00357 +2024-11-22 16:57:27.657311: train_loss -0.7891 +2024-11-22 16:57:27.664764: val_loss -0.7824 +2024-11-22 16:57:27.664908: Pseudo dice [0.8505] +2024-11-22 16:57:27.665141: Epoch time: 18.94 s +2024-11-22 16:57:28.622780: +2024-11-22 16:57:28.624707: Epoch 5456 +2024-11-22 16:57:28.624830: Current learning rate: 0.00357 +2024-11-22 16:57:49.009759: train_loss -0.7984 +2024-11-22 16:57:49.020544: val_loss -0.7486 +2024-11-22 16:57:49.020714: Pseudo dice [0.8364] +2024-11-22 16:57:49.020817: Epoch time: 20.39 s +2024-11-22 16:57:50.048164: +2024-11-22 16:57:50.048738: Epoch 5457 +2024-11-22 16:57:50.048863: Current learning rate: 0.00356 +2024-11-22 16:58:10.666592: train_loss -0.8039 +2024-11-22 16:58:10.677694: val_loss -0.7633 +2024-11-22 16:58:10.677856: Pseudo dice [0.8526] +2024-11-22 16:58:10.679874: Epoch time: 20.62 s +2024-11-22 16:58:12.032014: +2024-11-22 16:58:12.033076: Epoch 5458 +2024-11-22 16:58:12.033216: Current learning rate: 0.00356 +2024-11-22 16:58:31.413407: train_loss -0.7939 +2024-11-22 16:58:31.415650: val_loss -0.7724 +2024-11-22 16:58:31.415762: Pseudo dice [0.8514] +2024-11-22 16:58:31.415863: Epoch time: 19.38 s +2024-11-22 16:58:32.447110: +2024-11-22 16:58:32.448714: Epoch 5459 +2024-11-22 16:58:32.448845: Current learning rate: 0.00356 +2024-11-22 16:58:51.783603: train_loss -0.7946 +2024-11-22 16:58:51.789377: val_loss -0.7406 +2024-11-22 16:58:51.789508: Pseudo dice [0.8543] +2024-11-22 16:58:51.789596: Epoch time: 19.34 s +2024-11-22 16:58:52.778343: +2024-11-22 16:58:52.802770: Epoch 5460 +2024-11-22 16:58:52.802910: Current learning rate: 0.00356 +2024-11-22 16:59:11.944912: train_loss -0.7901 +2024-11-22 16:59:11.948115: val_loss -0.7661 +2024-11-22 16:59:11.948251: Pseudo dice [0.8417] +2024-11-22 16:59:11.948345: Epoch time: 19.17 s +2024-11-22 16:59:12.823632: +2024-11-22 16:59:12.824946: Epoch 5461 +2024-11-22 16:59:12.825069: Current learning rate: 0.00356 +2024-11-22 16:59:31.778757: train_loss -0.7979 +2024-11-22 16:59:31.785835: val_loss -0.7897 +2024-11-22 16:59:31.785985: Pseudo dice [0.8524] +2024-11-22 16:59:31.786097: Epoch time: 18.96 s +2024-11-22 16:59:32.674755: +2024-11-22 16:59:32.675869: Epoch 5462 +2024-11-22 16:59:32.676090: Current learning rate: 0.00356 +2024-11-22 16:59:51.200941: train_loss -0.7946 +2024-11-22 16:59:51.205539: val_loss -0.7742 +2024-11-22 16:59:51.205670: Pseudo dice [0.8502] +2024-11-22 16:59:51.205767: Epoch time: 18.53 s +2024-11-22 16:59:52.084150: +2024-11-22 16:59:52.084360: Epoch 5463 +2024-11-22 16:59:52.084498: Current learning rate: 0.00356 +2024-11-22 17:00:11.140620: train_loss -0.798 +2024-11-22 17:00:11.143577: val_loss -0.7813 +2024-11-22 17:00:11.143719: Pseudo dice [0.8389] +2024-11-22 17:00:11.143811: Epoch time: 19.06 s +2024-11-22 17:00:12.039084: +2024-11-22 17:00:12.039297: Epoch 5464 +2024-11-22 17:00:12.039413: Current learning rate: 0.00356 +2024-11-22 17:00:30.901196: train_loss -0.8015 +2024-11-22 17:00:30.901700: val_loss -0.7574 +2024-11-22 17:00:30.901867: Pseudo dice [0.8541] +2024-11-22 17:00:30.901950: Epoch time: 18.86 s +2024-11-22 17:00:31.763889: +2024-11-22 17:00:31.764092: Epoch 5465 +2024-11-22 17:00:31.764220: Current learning rate: 0.00355 +2024-11-22 17:00:50.344643: train_loss -0.8033 +2024-11-22 17:00:50.348027: val_loss -0.7852 +2024-11-22 17:00:50.348163: Pseudo dice [0.8555] +2024-11-22 17:00:50.348254: Epoch time: 18.58 s +2024-11-22 17:00:51.292562: +2024-11-22 17:00:51.292807: Epoch 5466 +2024-11-22 17:00:51.292935: Current learning rate: 0.00355 +2024-11-22 17:01:10.913898: train_loss -0.7952 +2024-11-22 17:01:10.914465: val_loss -0.7815 +2024-11-22 17:01:10.914562: Pseudo dice [0.8496] +2024-11-22 17:01:10.914650: Epoch time: 19.62 s +2024-11-22 17:01:11.780257: +2024-11-22 17:01:11.780475: Epoch 5467 +2024-11-22 17:01:11.780591: Current learning rate: 0.00355 +2024-11-22 17:01:29.840220: train_loss -0.7954 +2024-11-22 17:01:29.842878: val_loss -0.7532 +2024-11-22 17:01:29.843032: Pseudo dice [0.8487] +2024-11-22 17:01:29.847172: Epoch time: 18.06 s +2024-11-22 17:01:30.742116: +2024-11-22 17:01:30.742333: Epoch 5468 +2024-11-22 17:01:30.742463: Current learning rate: 0.00355 +2024-11-22 17:01:49.865749: train_loss -0.7932 +2024-11-22 17:01:49.874183: val_loss -0.7961 +2024-11-22 17:01:49.874360: Pseudo dice [0.8593] +2024-11-22 17:01:49.874464: Epoch time: 19.12 s +2024-11-22 17:01:50.842068: +2024-11-22 17:01:50.842280: Epoch 5469 +2024-11-22 17:01:50.842407: Current learning rate: 0.00355 +2024-11-22 17:02:09.162220: train_loss -0.7922 +2024-11-22 17:02:09.171176: val_loss -0.7601 +2024-11-22 17:02:09.171335: Pseudo dice [0.8342] +2024-11-22 17:02:09.171441: Epoch time: 18.32 s +2024-11-22 17:02:10.196160: +2024-11-22 17:02:10.196369: Epoch 5470 +2024-11-22 17:02:10.196488: Current learning rate: 0.00355 +2024-11-22 17:02:29.833445: train_loss -0.7965 +2024-11-22 17:02:29.833957: val_loss -0.7811 +2024-11-22 17:02:29.834072: Pseudo dice [0.8525] +2024-11-22 17:02:29.834174: Epoch time: 19.64 s +2024-11-22 17:02:30.703594: +2024-11-22 17:02:30.703795: Epoch 5471 +2024-11-22 17:02:30.703917: Current learning rate: 0.00355 +2024-11-22 17:02:48.748553: train_loss -0.7971 +2024-11-22 17:02:48.766123: val_loss -0.784 +2024-11-22 17:02:48.766249: Pseudo dice [0.8482] +2024-11-22 17:02:48.766345: Epoch time: 18.05 s +2024-11-22 17:02:49.902904: +2024-11-22 17:02:49.903715: Epoch 5472 +2024-11-22 17:02:49.903848: Current learning rate: 0.00355 +2024-11-22 17:03:09.723106: train_loss -0.8097 +2024-11-22 17:03:09.729155: val_loss -0.7728 +2024-11-22 17:03:09.729274: Pseudo dice [0.8605] +2024-11-22 17:03:09.729366: Epoch time: 19.82 s +2024-11-22 17:03:10.620785: +2024-11-22 17:03:10.621989: Epoch 5473 +2024-11-22 17:03:10.622142: Current learning rate: 0.00354 +2024-11-22 17:03:30.506951: train_loss -0.8087 +2024-11-22 17:03:30.514052: val_loss -0.794 +2024-11-22 17:03:30.514193: Pseudo dice [0.8695] +2024-11-22 17:03:30.514285: Epoch time: 19.89 s +2024-11-22 17:03:31.750802: +2024-11-22 17:03:31.752046: Epoch 5474 +2024-11-22 17:03:31.752200: Current learning rate: 0.00354 +2024-11-22 17:03:52.093621: train_loss -0.8044 +2024-11-22 17:03:52.100239: val_loss -0.7579 +2024-11-22 17:03:52.100364: Pseudo dice [0.8577] +2024-11-22 17:03:52.100460: Epoch time: 20.34 s +2024-11-22 17:03:53.043883: +2024-11-22 17:03:53.044446: Epoch 5475 +2024-11-22 17:03:53.044569: Current learning rate: 0.00354 +2024-11-22 17:04:12.028006: train_loss -0.799 +2024-11-22 17:04:12.042987: val_loss -0.7911 +2024-11-22 17:04:12.043149: Pseudo dice [0.8594] +2024-11-22 17:04:12.043241: Epoch time: 18.98 s +2024-11-22 17:04:13.030859: +2024-11-22 17:04:13.032198: Epoch 5476 +2024-11-22 17:04:13.032335: Current learning rate: 0.00354 +2024-11-22 17:04:31.354267: train_loss -0.7966 +2024-11-22 17:04:31.356999: val_loss -0.7556 +2024-11-22 17:04:31.357123: Pseudo dice [0.8472] +2024-11-22 17:04:31.357228: Epoch time: 18.32 s +2024-11-22 17:04:32.255373: +2024-11-22 17:04:32.255906: Epoch 5477 +2024-11-22 17:04:32.256037: Current learning rate: 0.00354 +2024-11-22 17:04:52.185445: train_loss -0.7918 +2024-11-22 17:04:52.193331: val_loss -0.7466 +2024-11-22 17:04:52.193483: Pseudo dice [0.8452] +2024-11-22 17:04:52.193598: Epoch time: 19.93 s +2024-11-22 17:04:53.076494: +2024-11-22 17:04:53.078551: Epoch 5478 +2024-11-22 17:04:53.078679: Current learning rate: 0.00354 +2024-11-22 17:05:11.698762: train_loss -0.7947 +2024-11-22 17:05:11.713130: val_loss -0.7604 +2024-11-22 17:05:11.713267: Pseudo dice [0.8559] +2024-11-22 17:05:11.713353: Epoch time: 18.62 s +2024-11-22 17:05:12.706919: +2024-11-22 17:05:12.707815: Epoch 5479 +2024-11-22 17:05:12.707951: Current learning rate: 0.00354 +2024-11-22 17:05:31.322770: train_loss -0.7993 +2024-11-22 17:05:31.329218: val_loss -0.7761 +2024-11-22 17:05:31.329406: Pseudo dice [0.8581] +2024-11-22 17:05:31.329515: Epoch time: 18.62 s +2024-11-22 17:05:32.631813: +2024-11-22 17:05:32.633454: Epoch 5480 +2024-11-22 17:05:32.633587: Current learning rate: 0.00354 +2024-11-22 17:05:51.796662: train_loss -0.8099 +2024-11-22 17:05:51.805120: val_loss -0.7546 +2024-11-22 17:05:51.805265: Pseudo dice [0.8559] +2024-11-22 17:05:51.805372: Epoch time: 19.17 s +2024-11-22 17:05:52.727272: +2024-11-22 17:05:52.728423: Epoch 5481 +2024-11-22 17:05:52.728567: Current learning rate: 0.00353 +2024-11-22 17:06:12.081183: train_loss -0.8002 +2024-11-22 17:06:12.091794: val_loss -0.7683 +2024-11-22 17:06:12.091951: Pseudo dice [0.8455] +2024-11-22 17:06:12.092042: Epoch time: 19.35 s +2024-11-22 17:06:13.089069: +2024-11-22 17:06:13.089630: Epoch 5482 +2024-11-22 17:06:13.089749: Current learning rate: 0.00353 +2024-11-22 17:06:32.860337: train_loss -0.8074 +2024-11-22 17:06:32.875527: val_loss -0.7777 +2024-11-22 17:06:32.875677: Pseudo dice [0.8504] +2024-11-22 17:06:32.875861: Epoch time: 19.77 s +2024-11-22 17:06:33.800350: +2024-11-22 17:06:33.803085: Epoch 5483 +2024-11-22 17:06:33.803207: Current learning rate: 0.00353 +2024-11-22 17:06:53.070258: train_loss -0.812 +2024-11-22 17:06:53.076823: val_loss -0.7736 +2024-11-22 17:06:53.076955: Pseudo dice [0.8479] +2024-11-22 17:06:53.077049: Epoch time: 19.27 s +2024-11-22 17:06:54.116106: +2024-11-22 17:06:54.118468: Epoch 5484 +2024-11-22 17:06:54.118605: Current learning rate: 0.00353 +2024-11-22 17:07:13.431932: train_loss -0.7973 +2024-11-22 17:07:13.436616: val_loss -0.7819 +2024-11-22 17:07:13.436773: Pseudo dice [0.8454] +2024-11-22 17:07:13.436873: Epoch time: 19.32 s +2024-11-22 17:07:14.336910: +2024-11-22 17:07:14.337625: Epoch 5485 +2024-11-22 17:07:14.337755: Current learning rate: 0.00353 +2024-11-22 17:07:33.195073: train_loss -0.7982 +2024-11-22 17:07:33.205907: val_loss -0.784 +2024-11-22 17:07:33.206052: Pseudo dice [0.866] +2024-11-22 17:07:33.206152: Epoch time: 18.86 s +2024-11-22 17:07:34.291292: +2024-11-22 17:07:34.292588: Epoch 5486 +2024-11-22 17:07:34.292722: Current learning rate: 0.00353 +2024-11-22 17:07:53.453475: train_loss -0.8017 +2024-11-22 17:07:53.461542: val_loss -0.7338 +2024-11-22 17:07:53.461687: Pseudo dice [0.8525] +2024-11-22 17:07:53.461782: Epoch time: 19.16 s +2024-11-22 17:07:54.358531: +2024-11-22 17:07:54.359316: Epoch 5487 +2024-11-22 17:07:54.359434: Current learning rate: 0.00353 +2024-11-22 17:08:13.117122: train_loss -0.7941 +2024-11-22 17:08:13.146102: val_loss -0.7678 +2024-11-22 17:08:13.146252: Pseudo dice [0.8524] +2024-11-22 17:08:13.146355: Epoch time: 18.76 s +2024-11-22 17:08:14.035753: +2024-11-22 17:08:14.037435: Epoch 5488 +2024-11-22 17:08:14.037575: Current learning rate: 0.00353 +2024-11-22 17:08:32.745447: train_loss -0.8039 +2024-11-22 17:08:32.753570: val_loss -0.7763 +2024-11-22 17:08:32.753700: Pseudo dice [0.8518] +2024-11-22 17:08:32.753796: Epoch time: 18.71 s +2024-11-22 17:08:33.729922: +2024-11-22 17:08:33.731614: Epoch 5489 +2024-11-22 17:08:33.731748: Current learning rate: 0.00352 +2024-11-22 17:08:53.942641: train_loss -0.7995 +2024-11-22 17:08:53.953919: val_loss -0.7669 +2024-11-22 17:08:53.954067: Pseudo dice [0.8563] +2024-11-22 17:08:53.954170: Epoch time: 20.21 s +2024-11-22 17:08:54.829206: +2024-11-22 17:08:54.830512: Epoch 5490 +2024-11-22 17:08:54.830657: Current learning rate: 0.00352 +2024-11-22 17:09:14.143134: train_loss -0.7957 +2024-11-22 17:09:14.148490: val_loss -0.7775 +2024-11-22 17:09:14.148623: Pseudo dice [0.8532] +2024-11-22 17:09:14.148742: Epoch time: 19.31 s +2024-11-22 17:09:15.201204: +2024-11-22 17:09:15.203186: Epoch 5491 +2024-11-22 17:09:15.203334: Current learning rate: 0.00352 +2024-11-22 17:09:34.176087: train_loss -0.8011 +2024-11-22 17:09:34.181690: val_loss -0.7731 +2024-11-22 17:09:34.181862: Pseudo dice [0.8592] +2024-11-22 17:09:34.181983: Epoch time: 18.98 s +2024-11-22 17:09:35.549441: +2024-11-22 17:09:35.551134: Epoch 5492 +2024-11-22 17:09:35.551261: Current learning rate: 0.00352 +2024-11-22 17:09:55.937039: train_loss -0.7998 +2024-11-22 17:09:55.948681: val_loss -0.7662 +2024-11-22 17:09:55.948827: Pseudo dice [0.8471] +2024-11-22 17:09:55.948924: Epoch time: 20.39 s +2024-11-22 17:09:56.854734: +2024-11-22 17:09:56.854949: Epoch 5493 +2024-11-22 17:09:56.855276: Current learning rate: 0.00352 +2024-11-22 17:10:16.016494: train_loss -0.8006 +2024-11-22 17:10:16.027980: val_loss -0.7765 +2024-11-22 17:10:16.028123: Pseudo dice [0.8556] +2024-11-22 17:10:16.028231: Epoch time: 19.16 s +2024-11-22 17:10:17.037461: +2024-11-22 17:10:17.039291: Epoch 5494 +2024-11-22 17:10:17.039425: Current learning rate: 0.00352 +2024-11-22 17:10:35.731391: train_loss -0.792 +2024-11-22 17:10:35.744054: val_loss -0.7705 +2024-11-22 17:10:35.744212: Pseudo dice [0.8561] +2024-11-22 17:10:35.744308: Epoch time: 18.69 s +2024-11-22 17:10:36.844771: +2024-11-22 17:10:36.846111: Epoch 5495 +2024-11-22 17:10:36.846244: Current learning rate: 0.00352 +2024-11-22 17:10:55.862927: train_loss -0.8049 +2024-11-22 17:10:55.872864: val_loss -0.7944 +2024-11-22 17:10:55.873017: Pseudo dice [0.8724] +2024-11-22 17:10:55.873118: Epoch time: 19.02 s +2024-11-22 17:10:56.905409: +2024-11-22 17:10:56.907351: Epoch 5496 +2024-11-22 17:10:56.907492: Current learning rate: 0.00352 +2024-11-22 17:11:15.965308: train_loss -0.808 +2024-11-22 17:11:15.971617: val_loss -0.7843 +2024-11-22 17:11:15.971735: Pseudo dice [0.8574] +2024-11-22 17:11:15.971820: Epoch time: 19.06 s +2024-11-22 17:11:17.230711: +2024-11-22 17:11:17.232769: Epoch 5497 +2024-11-22 17:11:17.232908: Current learning rate: 0.00351 +2024-11-22 17:11:36.416143: train_loss -0.8016 +2024-11-22 17:11:36.431728: val_loss -0.7701 +2024-11-22 17:11:36.431882: Pseudo dice [0.853] +2024-11-22 17:11:36.431976: Epoch time: 19.19 s +2024-11-22 17:11:37.315551: +2024-11-22 17:11:37.316700: Epoch 5498 +2024-11-22 17:11:37.316828: Current learning rate: 0.00351 +2024-11-22 17:11:56.540480: train_loss -0.8138 +2024-11-22 17:11:56.552388: val_loss -0.7773 +2024-11-22 17:11:56.552543: Pseudo dice [0.8551] +2024-11-22 17:11:56.552637: Epoch time: 19.23 s +2024-11-22 17:11:57.607418: +2024-11-22 17:11:57.607881: Epoch 5499 +2024-11-22 17:11:57.607999: Current learning rate: 0.00351 +2024-11-22 17:12:17.544739: train_loss -0.8029 +2024-11-22 17:12:17.550573: val_loss -0.7709 +2024-11-22 17:12:17.550702: Pseudo dice [0.8544] +2024-11-22 17:12:17.550795: Epoch time: 19.94 s +2024-11-22 17:12:18.944919: +2024-11-22 17:12:18.946318: Epoch 5500 +2024-11-22 17:12:18.946444: Current learning rate: 0.00351 +2024-11-22 17:12:38.964859: train_loss -0.8085 +2024-11-22 17:12:38.969256: val_loss -0.767 +2024-11-22 17:12:38.969399: Pseudo dice [0.8432] +2024-11-22 17:12:38.969661: Epoch time: 20.02 s +2024-11-22 17:12:39.850473: +2024-11-22 17:12:39.851444: Epoch 5501 +2024-11-22 17:12:39.851571: Current learning rate: 0.00351 +2024-11-22 17:12:59.338352: train_loss -0.8103 +2024-11-22 17:12:59.344698: val_loss -0.7689 +2024-11-22 17:12:59.344846: Pseudo dice [0.8549] +2024-11-22 17:12:59.344955: Epoch time: 19.49 s +2024-11-22 17:13:00.246189: +2024-11-22 17:13:00.246807: Epoch 5502 +2024-11-22 17:13:00.246941: Current learning rate: 0.00351 +2024-11-22 17:13:20.510378: train_loss -0.801 +2024-11-22 17:13:20.541478: val_loss -0.7946 +2024-11-22 17:13:20.541631: Pseudo dice [0.8687] +2024-11-22 17:13:20.541759: Epoch time: 20.26 s +2024-11-22 17:13:21.944474: +2024-11-22 17:13:21.945477: Epoch 5503 +2024-11-22 17:13:21.945593: Current learning rate: 0.00351 +2024-11-22 17:13:41.035953: train_loss -0.7988 +2024-11-22 17:13:41.042647: val_loss -0.7962 +2024-11-22 17:13:41.042769: Pseudo dice [0.8594] +2024-11-22 17:13:41.042864: Epoch time: 19.09 s +2024-11-22 17:13:41.996144: +2024-11-22 17:13:41.996747: Epoch 5504 +2024-11-22 17:13:41.996869: Current learning rate: 0.00351 +2024-11-22 17:14:02.161008: train_loss -0.8076 +2024-11-22 17:14:02.169071: val_loss -0.7527 +2024-11-22 17:14:02.169218: Pseudo dice [0.8542] +2024-11-22 17:14:02.169335: Epoch time: 20.17 s +2024-11-22 17:14:03.161354: +2024-11-22 17:14:03.162142: Epoch 5505 +2024-11-22 17:14:03.162277: Current learning rate: 0.0035 +2024-11-22 17:14:22.107536: train_loss -0.8135 +2024-11-22 17:14:22.118197: val_loss -0.7927 +2024-11-22 17:14:22.118326: Pseudo dice [0.867] +2024-11-22 17:14:22.118428: Epoch time: 18.95 s +2024-11-22 17:14:23.058799: +2024-11-22 17:14:23.059742: Epoch 5506 +2024-11-22 17:14:23.059871: Current learning rate: 0.0035 +2024-11-22 17:14:43.595129: train_loss -0.8098 +2024-11-22 17:14:43.603374: val_loss -0.7766 +2024-11-22 17:14:43.603518: Pseudo dice [0.861] +2024-11-22 17:14:43.603619: Epoch time: 20.54 s +2024-11-22 17:14:44.497028: +2024-11-22 17:14:44.498505: Epoch 5507 +2024-11-22 17:14:44.498629: Current learning rate: 0.0035 +2024-11-22 17:15:02.241824: train_loss -0.8056 +2024-11-22 17:15:02.257771: val_loss -0.7967 +2024-11-22 17:15:02.257939: Pseudo dice [0.8654] +2024-11-22 17:15:02.258054: Epoch time: 17.75 s +2024-11-22 17:15:03.299848: +2024-11-22 17:15:03.300839: Epoch 5508 +2024-11-22 17:15:03.300969: Current learning rate: 0.0035 +2024-11-22 17:15:23.764020: train_loss -0.8135 +2024-11-22 17:15:23.770908: val_loss -0.7912 +2024-11-22 17:15:23.771066: Pseudo dice [0.8506] +2024-11-22 17:15:23.771182: Epoch time: 20.47 s +2024-11-22 17:15:24.708941: +2024-11-22 17:15:24.710240: Epoch 5509 +2024-11-22 17:15:24.710363: Current learning rate: 0.0035 +2024-11-22 17:15:43.445383: train_loss -0.7995 +2024-11-22 17:15:43.447981: val_loss -0.7742 +2024-11-22 17:15:43.448087: Pseudo dice [0.8475] +2024-11-22 17:15:43.448210: Epoch time: 18.74 s +2024-11-22 17:15:44.312229: +2024-11-22 17:15:44.313424: Epoch 5510 +2024-11-22 17:15:44.313556: Current learning rate: 0.0035 +2024-11-22 17:16:04.356209: train_loss -0.8059 +2024-11-22 17:16:04.363539: val_loss -0.7766 +2024-11-22 17:16:04.363682: Pseudo dice [0.8681] +2024-11-22 17:16:04.363776: Epoch time: 20.04 s +2024-11-22 17:16:05.278499: +2024-11-22 17:16:05.279235: Epoch 5511 +2024-11-22 17:16:05.279368: Current learning rate: 0.0035 +2024-11-22 17:16:24.732268: train_loss -0.8055 +2024-11-22 17:16:24.743447: val_loss -0.7736 +2024-11-22 17:16:24.743582: Pseudo dice [0.8599] +2024-11-22 17:16:24.743693: Epoch time: 19.45 s +2024-11-22 17:16:25.897867: +2024-11-22 17:16:25.898872: Epoch 5512 +2024-11-22 17:16:25.899010: Current learning rate: 0.0035 +2024-11-22 17:16:46.110346: train_loss -0.8116 +2024-11-22 17:16:46.114430: val_loss -0.7598 +2024-11-22 17:16:46.114576: Pseudo dice [0.8541] +2024-11-22 17:16:46.114677: Epoch time: 20.21 s +2024-11-22 17:16:47.074357: +2024-11-22 17:16:47.075020: Epoch 5513 +2024-11-22 17:16:47.075163: Current learning rate: 0.00349 +2024-11-22 17:17:06.113442: train_loss -0.805 +2024-11-22 17:17:06.119381: val_loss -0.7832 +2024-11-22 17:17:06.119527: Pseudo dice [0.8509] +2024-11-22 17:17:06.119613: Epoch time: 19.04 s +2024-11-22 17:17:07.450641: +2024-11-22 17:17:07.452044: Epoch 5514 +2024-11-22 17:17:07.452175: Current learning rate: 0.00349 +2024-11-22 17:17:26.776452: train_loss -0.7974 +2024-11-22 17:17:26.796237: val_loss -0.7806 +2024-11-22 17:17:26.796408: Pseudo dice [0.8455] +2024-11-22 17:17:26.796520: Epoch time: 19.33 s +2024-11-22 17:17:27.830643: +2024-11-22 17:17:27.832296: Epoch 5515 +2024-11-22 17:17:27.832433: Current learning rate: 0.00349 +2024-11-22 17:17:47.488350: train_loss -0.8003 +2024-11-22 17:17:47.495029: val_loss -0.7845 +2024-11-22 17:17:47.495162: Pseudo dice [0.86] +2024-11-22 17:17:47.495255: Epoch time: 19.66 s +2024-11-22 17:17:48.434217: +2024-11-22 17:17:48.435384: Epoch 5516 +2024-11-22 17:17:48.435526: Current learning rate: 0.00349 +2024-11-22 17:18:07.065701: train_loss -0.8142 +2024-11-22 17:18:07.071057: val_loss -0.7824 +2024-11-22 17:18:07.071176: Pseudo dice [0.8619] +2024-11-22 17:18:07.071270: Epoch time: 18.63 s +2024-11-22 17:18:08.098481: +2024-11-22 17:18:08.098961: Epoch 5517 +2024-11-22 17:18:08.099123: Current learning rate: 0.00349 +2024-11-22 17:18:27.824696: train_loss -0.8114 +2024-11-22 17:18:27.831406: val_loss -0.7858 +2024-11-22 17:18:27.831520: Pseudo dice [0.8571] +2024-11-22 17:18:27.831610: Epoch time: 19.73 s +2024-11-22 17:18:28.963683: +2024-11-22 17:18:28.964952: Epoch 5518 +2024-11-22 17:18:28.965094: Current learning rate: 0.00349 +2024-11-22 17:18:47.543800: train_loss -0.8011 +2024-11-22 17:18:47.549950: val_loss -0.7613 +2024-11-22 17:18:47.550267: Pseudo dice [0.8579] +2024-11-22 17:18:47.550374: Epoch time: 18.58 s +2024-11-22 17:18:48.714761: +2024-11-22 17:18:48.716434: Epoch 5519 +2024-11-22 17:18:48.716552: Current learning rate: 0.00349 +2024-11-22 17:19:06.934319: train_loss -0.8017 +2024-11-22 17:19:06.942425: val_loss -0.7755 +2024-11-22 17:19:06.942581: Pseudo dice [0.8458] +2024-11-22 17:19:06.942680: Epoch time: 18.22 s +2024-11-22 17:19:07.985917: +2024-11-22 17:19:07.987032: Epoch 5520 +2024-11-22 17:19:07.987170: Current learning rate: 0.00349 +2024-11-22 17:19:27.854196: train_loss -0.8096 +2024-11-22 17:19:27.863337: val_loss -0.7741 +2024-11-22 17:19:27.863477: Pseudo dice [0.8601] +2024-11-22 17:19:27.863570: Epoch time: 19.87 s +2024-11-22 17:19:28.851506: +2024-11-22 17:19:28.852066: Epoch 5521 +2024-11-22 17:19:28.852204: Current learning rate: 0.00348 +2024-11-22 17:19:48.171003: train_loss -0.8103 +2024-11-22 17:19:48.173363: val_loss -0.7755 +2024-11-22 17:19:48.173487: Pseudo dice [0.8604] +2024-11-22 17:19:48.173576: Epoch time: 19.32 s +2024-11-22 17:19:49.042411: +2024-11-22 17:19:49.042633: Epoch 5522 +2024-11-22 17:19:49.042760: Current learning rate: 0.00348 +2024-11-22 17:20:08.806147: train_loss -0.808 +2024-11-22 17:20:08.817283: val_loss -0.7706 +2024-11-22 17:20:08.817453: Pseudo dice [0.8587] +2024-11-22 17:20:08.817559: Epoch time: 19.76 s +2024-11-22 17:20:09.727895: +2024-11-22 17:20:09.728897: Epoch 5523 +2024-11-22 17:20:09.729040: Current learning rate: 0.00348 +2024-11-22 17:20:29.411617: train_loss -0.7954 +2024-11-22 17:20:29.413625: val_loss -0.7509 +2024-11-22 17:20:29.413769: Pseudo dice [0.8286] +2024-11-22 17:20:29.413861: Epoch time: 19.68 s +2024-11-22 17:20:30.274325: +2024-11-22 17:20:30.274740: Epoch 5524 +2024-11-22 17:20:30.274856: Current learning rate: 0.00348 +2024-11-22 17:20:50.583205: train_loss -0.7944 +2024-11-22 17:20:50.592044: val_loss -0.7759 +2024-11-22 17:20:50.592185: Pseudo dice [0.8526] +2024-11-22 17:20:50.592288: Epoch time: 20.31 s +2024-11-22 17:20:51.478870: +2024-11-22 17:20:51.479073: Epoch 5525 +2024-11-22 17:20:51.479198: Current learning rate: 0.00348 +2024-11-22 17:21:10.794195: train_loss -0.8063 +2024-11-22 17:21:10.814702: val_loss -0.7744 +2024-11-22 17:21:10.814873: Pseudo dice [0.8594] +2024-11-22 17:21:10.814990: Epoch time: 19.32 s +2024-11-22 17:21:12.253949: +2024-11-22 17:21:12.255892: Epoch 5526 +2024-11-22 17:21:12.256101: Current learning rate: 0.00348 +2024-11-22 17:21:31.037355: train_loss -0.8062 +2024-11-22 17:21:31.055860: val_loss -0.782 +2024-11-22 17:21:31.056016: Pseudo dice [0.8433] +2024-11-22 17:21:31.056280: Epoch time: 18.78 s +2024-11-22 17:21:32.005571: +2024-11-22 17:21:32.006214: Epoch 5527 +2024-11-22 17:21:32.006358: Current learning rate: 0.00348 +2024-11-22 17:21:52.008187: train_loss -0.8015 +2024-11-22 17:21:52.017568: val_loss -0.7884 +2024-11-22 17:21:52.017703: Pseudo dice [0.8544] +2024-11-22 17:21:52.017805: Epoch time: 20.0 s +2024-11-22 17:21:52.929184: +2024-11-22 17:21:52.929784: Epoch 5528 +2024-11-22 17:21:52.929912: Current learning rate: 0.00348 +2024-11-22 17:22:12.620783: train_loss -0.8029 +2024-11-22 17:22:12.626365: val_loss -0.7723 +2024-11-22 17:22:12.626511: Pseudo dice [0.8531] +2024-11-22 17:22:12.626617: Epoch time: 19.69 s +2024-11-22 17:22:13.521072: +2024-11-22 17:22:13.521642: Epoch 5529 +2024-11-22 17:22:13.521770: Current learning rate: 0.00347 +2024-11-22 17:22:32.345566: train_loss -0.8056 +2024-11-22 17:22:32.356145: val_loss -0.7692 +2024-11-22 17:22:32.356274: Pseudo dice [0.8521] +2024-11-22 17:22:32.356395: Epoch time: 18.83 s +2024-11-22 17:22:33.454998: +2024-11-22 17:22:33.457028: Epoch 5530 +2024-11-22 17:22:33.457167: Current learning rate: 0.00347 +2024-11-22 17:22:52.799700: train_loss -0.809 +2024-11-22 17:22:52.803117: val_loss -0.8001 +2024-11-22 17:22:52.803262: Pseudo dice [0.8554] +2024-11-22 17:22:52.803433: Epoch time: 19.35 s +2024-11-22 17:22:53.813549: +2024-11-22 17:22:53.814860: Epoch 5531 +2024-11-22 17:22:53.814988: Current learning rate: 0.00347 +2024-11-22 17:23:13.171764: train_loss -0.8011 +2024-11-22 17:23:13.187011: val_loss -0.7718 +2024-11-22 17:23:13.187166: Pseudo dice [0.8616] +2024-11-22 17:23:13.187259: Epoch time: 19.36 s +2024-11-22 17:23:14.285867: +2024-11-22 17:23:14.286317: Epoch 5532 +2024-11-22 17:23:14.286446: Current learning rate: 0.00347 +2024-11-22 17:23:34.329707: train_loss -0.7994 +2024-11-22 17:23:34.340944: val_loss -0.7745 +2024-11-22 17:23:34.341100: Pseudo dice [0.8626] +2024-11-22 17:23:34.341187: Epoch time: 20.04 s +2024-11-22 17:23:35.371095: +2024-11-22 17:23:35.372462: Epoch 5533 +2024-11-22 17:23:35.372593: Current learning rate: 0.00347 +2024-11-22 17:23:55.345095: train_loss -0.7978 +2024-11-22 17:23:55.353917: val_loss -0.7774 +2024-11-22 17:23:55.354065: Pseudo dice [0.844] +2024-11-22 17:23:55.354170: Epoch time: 19.97 s +2024-11-22 17:23:56.392003: +2024-11-22 17:23:56.393277: Epoch 5534 +2024-11-22 17:23:56.393399: Current learning rate: 0.00347 +2024-11-22 17:24:15.973737: train_loss -0.8042 +2024-11-22 17:24:15.985962: val_loss -0.7903 +2024-11-22 17:24:15.986133: Pseudo dice [0.8655] +2024-11-22 17:24:15.986223: Epoch time: 19.58 s +2024-11-22 17:24:17.007394: +2024-11-22 17:24:17.009064: Epoch 5535 +2024-11-22 17:24:17.009204: Current learning rate: 0.00347 +2024-11-22 17:24:36.153577: train_loss -0.7988 +2024-11-22 17:24:36.159215: val_loss -0.7729 +2024-11-22 17:24:36.159341: Pseudo dice [0.8629] +2024-11-22 17:24:36.159441: Epoch time: 19.15 s +2024-11-22 17:24:37.063250: +2024-11-22 17:24:37.063455: Epoch 5536 +2024-11-22 17:24:37.063575: Current learning rate: 0.00346 +2024-11-22 17:24:55.343724: train_loss -0.7993 +2024-11-22 17:24:55.344357: val_loss -0.7881 +2024-11-22 17:24:55.344483: Pseudo dice [0.861] +2024-11-22 17:24:55.344585: Epoch time: 18.28 s +2024-11-22 17:24:56.617998: +2024-11-22 17:24:56.618224: Epoch 5537 +2024-11-22 17:24:56.618356: Current learning rate: 0.00346 +2024-11-22 17:25:15.573790: train_loss -0.8086 +2024-11-22 17:25:15.574568: val_loss -0.7887 +2024-11-22 17:25:15.574669: Pseudo dice [0.8524] +2024-11-22 17:25:15.574749: Epoch time: 18.96 s +2024-11-22 17:25:16.445524: +2024-11-22 17:25:16.445738: Epoch 5538 +2024-11-22 17:25:16.445860: Current learning rate: 0.00346 +2024-11-22 17:25:34.341009: train_loss -0.808 +2024-11-22 17:25:34.341520: val_loss -0.7899 +2024-11-22 17:25:34.341619: Pseudo dice [0.8577] +2024-11-22 17:25:34.341712: Epoch time: 17.9 s +2024-11-22 17:25:35.237739: +2024-11-22 17:25:35.237937: Epoch 5539 +2024-11-22 17:25:35.238064: Current learning rate: 0.00346 +2024-11-22 17:25:54.173305: train_loss -0.8097 +2024-11-22 17:25:54.180043: val_loss -0.7443 +2024-11-22 17:25:54.180174: Pseudo dice [0.8505] +2024-11-22 17:25:54.180265: Epoch time: 18.94 s +2024-11-22 17:25:55.165292: +2024-11-22 17:25:55.165503: Epoch 5540 +2024-11-22 17:25:55.165639: Current learning rate: 0.00346 +2024-11-22 17:26:14.679074: train_loss -0.7985 +2024-11-22 17:26:14.679311: val_loss -0.7641 +2024-11-22 17:26:14.684563: Pseudo dice [0.8607] +2024-11-22 17:26:14.684756: Epoch time: 19.51 s +2024-11-22 17:26:15.658817: +2024-11-22 17:26:15.659022: Epoch 5541 +2024-11-22 17:26:15.659168: Current learning rate: 0.00346 +2024-11-22 17:26:35.099456: train_loss -0.8018 +2024-11-22 17:26:35.100013: val_loss -0.7699 +2024-11-22 17:26:35.100172: Pseudo dice [0.8427] +2024-11-22 17:26:35.100276: Epoch time: 19.44 s +2024-11-22 17:26:36.319714: +2024-11-22 17:26:36.319913: Epoch 5542 +2024-11-22 17:26:36.320047: Current learning rate: 0.00346 +2024-11-22 17:26:54.208092: train_loss -0.8026 +2024-11-22 17:26:54.214322: val_loss -0.7737 +2024-11-22 17:26:54.214479: Pseudo dice [0.8542] +2024-11-22 17:26:54.214591: Epoch time: 17.89 s +2024-11-22 17:26:55.116280: +2024-11-22 17:26:55.116500: Epoch 5543 +2024-11-22 17:26:55.116634: Current learning rate: 0.00346 +2024-11-22 17:27:13.226422: train_loss -0.8021 +2024-11-22 17:27:13.232940: val_loss -0.7628 +2024-11-22 17:27:13.233091: Pseudo dice [0.8427] +2024-11-22 17:27:13.233188: Epoch time: 18.11 s +2024-11-22 17:27:14.264677: +2024-11-22 17:27:14.284493: Epoch 5544 +2024-11-22 17:27:14.284666: Current learning rate: 0.00345 +2024-11-22 17:27:34.639993: train_loss -0.7904 +2024-11-22 17:27:34.646011: val_loss -0.7587 +2024-11-22 17:27:34.646151: Pseudo dice [0.8388] +2024-11-22 17:27:34.646253: Epoch time: 20.38 s +2024-11-22 17:27:35.611974: +2024-11-22 17:27:35.612668: Epoch 5545 +2024-11-22 17:27:35.612796: Current learning rate: 0.00345 +2024-11-22 17:27:54.362902: train_loss -0.8092 +2024-11-22 17:27:54.380326: val_loss -0.7792 +2024-11-22 17:27:54.380490: Pseudo dice [0.8589] +2024-11-22 17:27:54.380583: Epoch time: 18.75 s +2024-11-22 17:27:55.389668: +2024-11-22 17:27:55.389876: Epoch 5546 +2024-11-22 17:27:55.390010: Current learning rate: 0.00345 +2024-11-22 17:28:15.012537: train_loss -0.8086 +2024-11-22 17:28:15.027079: val_loss -0.7828 +2024-11-22 17:28:15.027227: Pseudo dice [0.8536] +2024-11-22 17:28:15.027333: Epoch time: 19.62 s +2024-11-22 17:28:15.962242: +2024-11-22 17:28:15.963024: Epoch 5547 +2024-11-22 17:28:15.963166: Current learning rate: 0.00345 +2024-11-22 17:28:35.143487: train_loss -0.8077 +2024-11-22 17:28:35.157477: val_loss -0.7746 +2024-11-22 17:28:35.157627: Pseudo dice [0.8555] +2024-11-22 17:28:35.157732: Epoch time: 19.18 s +2024-11-22 17:28:36.154004: +2024-11-22 17:28:36.154582: Epoch 5548 +2024-11-22 17:28:36.154749: Current learning rate: 0.00345 +2024-11-22 17:28:55.571373: train_loss -0.8082 +2024-11-22 17:28:55.573896: val_loss -0.7757 +2024-11-22 17:28:55.574032: Pseudo dice [0.862] +2024-11-22 17:28:55.574137: Epoch time: 19.42 s +2024-11-22 17:28:56.957404: +2024-11-22 17:28:56.958815: Epoch 5549 +2024-11-22 17:28:56.958944: Current learning rate: 0.00345 +2024-11-22 17:29:16.785315: train_loss -0.8023 +2024-11-22 17:29:16.786719: val_loss -0.7632 +2024-11-22 17:29:16.786822: Pseudo dice [0.8531] +2024-11-22 17:29:16.786911: Epoch time: 19.83 s +2024-11-22 17:29:17.958431: +2024-11-22 17:29:17.959421: Epoch 5550 +2024-11-22 17:29:17.959562: Current learning rate: 0.00345 +2024-11-22 17:29:38.187090: train_loss -0.8057 +2024-11-22 17:29:38.193136: val_loss -0.7872 +2024-11-22 17:29:38.193290: Pseudo dice [0.8595] +2024-11-22 17:29:38.193476: Epoch time: 20.23 s +2024-11-22 17:29:39.064355: +2024-11-22 17:29:39.065468: Epoch 5551 +2024-11-22 17:29:39.065588: Current learning rate: 0.00345 +2024-11-22 17:29:59.076706: train_loss -0.8072 +2024-11-22 17:29:59.083780: val_loss -0.7583 +2024-11-22 17:29:59.083916: Pseudo dice [0.8354] +2024-11-22 17:29:59.084020: Epoch time: 20.01 s +2024-11-22 17:30:00.059850: +2024-11-22 17:30:00.060805: Epoch 5552 +2024-11-22 17:30:00.060933: Current learning rate: 0.00344 +2024-11-22 17:30:20.627577: train_loss -0.8044 +2024-11-22 17:30:20.635769: val_loss -0.7797 +2024-11-22 17:30:20.636234: Pseudo dice [0.8539] +2024-11-22 17:30:20.636346: Epoch time: 20.57 s +2024-11-22 17:30:21.543307: +2024-11-22 17:30:21.544935: Epoch 5553 +2024-11-22 17:30:21.545053: Current learning rate: 0.00344 +2024-11-22 17:30:40.722216: train_loss -0.798 +2024-11-22 17:30:40.724779: val_loss -0.7782 +2024-11-22 17:30:40.724920: Pseudo dice [0.8586] +2024-11-22 17:30:40.725021: Epoch time: 19.18 s +2024-11-22 17:30:41.733136: +2024-11-22 17:30:41.734045: Epoch 5554 +2024-11-22 17:30:41.734185: Current learning rate: 0.00344 +2024-11-22 17:31:01.699336: train_loss -0.8032 +2024-11-22 17:31:01.704067: val_loss -0.7654 +2024-11-22 17:31:01.704179: Pseudo dice [0.843] +2024-11-22 17:31:01.704274: Epoch time: 19.97 s +2024-11-22 17:31:02.593860: +2024-11-22 17:31:02.594873: Epoch 5555 +2024-11-22 17:31:02.595011: Current learning rate: 0.00344 +2024-11-22 17:31:23.620103: train_loss -0.7981 +2024-11-22 17:31:23.639256: val_loss -0.7886 +2024-11-22 17:31:23.639386: Pseudo dice [0.8659] +2024-11-22 17:31:23.639492: Epoch time: 21.03 s +2024-11-22 17:31:24.586689: +2024-11-22 17:31:24.587854: Epoch 5556 +2024-11-22 17:31:24.588003: Current learning rate: 0.00344 +2024-11-22 17:31:45.473572: train_loss -0.7968 +2024-11-22 17:31:45.476134: val_loss -0.7688 +2024-11-22 17:31:45.476274: Pseudo dice [0.844] +2024-11-22 17:31:45.508342: Epoch time: 20.89 s +2024-11-22 17:31:46.374787: +2024-11-22 17:31:46.377161: Epoch 5557 +2024-11-22 17:31:46.377294: Current learning rate: 0.00344 +2024-11-22 17:32:07.178182: train_loss -0.8072 +2024-11-22 17:32:07.190461: val_loss -0.7748 +2024-11-22 17:32:07.190631: Pseudo dice [0.854] +2024-11-22 17:32:07.190750: Epoch time: 20.8 s +2024-11-22 17:32:08.250220: +2024-11-22 17:32:08.251418: Epoch 5558 +2024-11-22 17:32:08.251546: Current learning rate: 0.00344 +2024-11-22 17:32:27.981169: train_loss -0.7969 +2024-11-22 17:32:27.986182: val_loss -0.7717 +2024-11-22 17:32:27.986307: Pseudo dice [0.8459] +2024-11-22 17:32:27.986393: Epoch time: 19.73 s +2024-11-22 17:32:28.878550: +2024-11-22 17:32:28.879169: Epoch 5559 +2024-11-22 17:32:28.879300: Current learning rate: 0.00344 +2024-11-22 17:32:48.754782: train_loss -0.8022 +2024-11-22 17:32:48.763160: val_loss -0.7521 +2024-11-22 17:32:48.763381: Pseudo dice [0.8619] +2024-11-22 17:32:48.763488: Epoch time: 19.88 s +2024-11-22 17:32:50.063576: +2024-11-22 17:32:50.065470: Epoch 5560 +2024-11-22 17:32:50.065601: Current learning rate: 0.00343 +2024-11-22 17:33:09.232589: train_loss -0.7957 +2024-11-22 17:33:09.239039: val_loss -0.7751 +2024-11-22 17:33:09.239172: Pseudo dice [0.8532] +2024-11-22 17:33:09.239263: Epoch time: 19.17 s +2024-11-22 17:33:10.157482: +2024-11-22 17:33:10.158938: Epoch 5561 +2024-11-22 17:33:10.159089: Current learning rate: 0.00343 +2024-11-22 17:33:31.179598: train_loss -0.8092 +2024-11-22 17:33:31.186299: val_loss -0.7899 +2024-11-22 17:33:31.186485: Pseudo dice [0.8522] +2024-11-22 17:33:31.186597: Epoch time: 21.02 s +2024-11-22 17:33:32.242434: +2024-11-22 17:33:32.244339: Epoch 5562 +2024-11-22 17:33:32.244463: Current learning rate: 0.00343 +2024-11-22 17:33:52.250150: train_loss -0.8005 +2024-11-22 17:33:52.272015: val_loss -0.7631 +2024-11-22 17:33:52.272165: Pseudo dice [0.8405] +2024-11-22 17:33:52.272276: Epoch time: 20.01 s +2024-11-22 17:33:53.201109: +2024-11-22 17:33:53.202944: Epoch 5563 +2024-11-22 17:33:53.203081: Current learning rate: 0.00343 +2024-11-22 17:34:13.896629: train_loss -0.7985 +2024-11-22 17:34:13.901125: val_loss -0.7689 +2024-11-22 17:34:13.901258: Pseudo dice [0.8465] +2024-11-22 17:34:13.901363: Epoch time: 20.69 s +2024-11-22 17:34:14.954452: +2024-11-22 17:34:14.955724: Epoch 5564 +2024-11-22 17:34:14.955866: Current learning rate: 0.00343 +2024-11-22 17:34:34.278977: train_loss -0.7938 +2024-11-22 17:34:34.292233: val_loss -0.7705 +2024-11-22 17:34:34.292377: Pseudo dice [0.8378] +2024-11-22 17:34:34.292465: Epoch time: 19.33 s +2024-11-22 17:34:35.326664: +2024-11-22 17:34:35.328178: Epoch 5565 +2024-11-22 17:34:35.328315: Current learning rate: 0.00343 +2024-11-22 17:34:55.435359: train_loss -0.7908 +2024-11-22 17:34:55.441616: val_loss -0.7604 +2024-11-22 17:34:55.441767: Pseudo dice [0.8397] +2024-11-22 17:34:55.441899: Epoch time: 20.11 s +2024-11-22 17:34:56.469923: +2024-11-22 17:34:56.470720: Epoch 5566 +2024-11-22 17:34:56.470845: Current learning rate: 0.00343 +2024-11-22 17:35:16.149471: train_loss -0.791 +2024-11-22 17:35:16.160592: val_loss -0.788 +2024-11-22 17:35:16.160733: Pseudo dice [0.8625] +2024-11-22 17:35:16.160824: Epoch time: 19.68 s +2024-11-22 17:35:17.169065: +2024-11-22 17:35:17.170120: Epoch 5567 +2024-11-22 17:35:17.170257: Current learning rate: 0.00343 +2024-11-22 17:35:38.067498: train_loss -0.802 +2024-11-22 17:35:38.072042: val_loss -0.7467 +2024-11-22 17:35:38.072170: Pseudo dice [0.849] +2024-11-22 17:35:38.072270: Epoch time: 20.9 s +2024-11-22 17:35:38.947180: +2024-11-22 17:35:38.948870: Epoch 5568 +2024-11-22 17:35:38.949019: Current learning rate: 0.00342 +2024-11-22 17:35:58.484901: train_loss -0.7979 +2024-11-22 17:35:58.504423: val_loss -0.7754 +2024-11-22 17:35:58.504569: Pseudo dice [0.8492] +2024-11-22 17:35:58.504679: Epoch time: 19.54 s +2024-11-22 17:35:59.512870: +2024-11-22 17:35:59.514707: Epoch 5569 +2024-11-22 17:35:59.514845: Current learning rate: 0.00342 +2024-11-22 17:36:19.238269: train_loss -0.8069 +2024-11-22 17:36:19.245009: val_loss -0.7708 +2024-11-22 17:36:19.245147: Pseudo dice [0.8441] +2024-11-22 17:36:19.245311: Epoch time: 19.73 s +2024-11-22 17:36:20.124849: +2024-11-22 17:36:20.125665: Epoch 5570 +2024-11-22 17:36:20.125797: Current learning rate: 0.00342 +2024-11-22 17:36:39.842221: train_loss -0.7856 +2024-11-22 17:36:39.848857: val_loss -0.7539 +2024-11-22 17:36:39.848996: Pseudo dice [0.8421] +2024-11-22 17:36:39.849110: Epoch time: 19.72 s +2024-11-22 17:36:41.169111: +2024-11-22 17:36:41.170423: Epoch 5571 +2024-11-22 17:36:41.170546: Current learning rate: 0.00342 +2024-11-22 17:37:00.062850: train_loss -0.7914 +2024-11-22 17:37:00.075990: val_loss -0.7727 +2024-11-22 17:37:00.076130: Pseudo dice [0.8655] +2024-11-22 17:37:00.076222: Epoch time: 18.89 s +2024-11-22 17:37:00.973768: +2024-11-22 17:37:00.975527: Epoch 5572 +2024-11-22 17:37:00.975671: Current learning rate: 0.00342 +2024-11-22 17:37:21.710232: train_loss -0.7961 +2024-11-22 17:37:21.717397: val_loss -0.7821 +2024-11-22 17:37:21.717548: Pseudo dice [0.8633] +2024-11-22 17:37:21.717644: Epoch time: 20.74 s +2024-11-22 17:37:22.652953: +2024-11-22 17:37:22.654509: Epoch 5573 +2024-11-22 17:37:22.654655: Current learning rate: 0.00342 +2024-11-22 17:37:42.581368: train_loss -0.7987 +2024-11-22 17:37:42.588020: val_loss -0.7715 +2024-11-22 17:37:42.588168: Pseudo dice [0.8556] +2024-11-22 17:37:42.588255: Epoch time: 19.93 s +2024-11-22 17:37:43.524787: +2024-11-22 17:37:43.525556: Epoch 5574 +2024-11-22 17:37:43.525682: Current learning rate: 0.00342 +2024-11-22 17:38:03.361845: train_loss -0.7995 +2024-11-22 17:38:03.371247: val_loss -0.7715 +2024-11-22 17:38:03.371406: Pseudo dice [0.8526] +2024-11-22 17:38:03.371504: Epoch time: 19.84 s +2024-11-22 17:38:04.243439: +2024-11-22 17:38:04.244341: Epoch 5575 +2024-11-22 17:38:04.244464: Current learning rate: 0.00342 +2024-11-22 17:38:23.739464: train_loss -0.7946 +2024-11-22 17:38:23.743575: val_loss -0.7757 +2024-11-22 17:38:23.743727: Pseudo dice [0.8585] +2024-11-22 17:38:23.743823: Epoch time: 19.5 s +2024-11-22 17:38:24.743371: +2024-11-22 17:38:24.743900: Epoch 5576 +2024-11-22 17:38:24.744030: Current learning rate: 0.00341 +2024-11-22 17:38:43.525089: train_loss -0.7957 +2024-11-22 17:38:43.532172: val_loss -0.7783 +2024-11-22 17:38:43.532390: Pseudo dice [0.8502] +2024-11-22 17:38:43.532504: Epoch time: 18.78 s +2024-11-22 17:38:44.661983: +2024-11-22 17:38:44.662584: Epoch 5577 +2024-11-22 17:38:44.662710: Current learning rate: 0.00341 +2024-11-22 17:39:04.205238: train_loss -0.7929 +2024-11-22 17:39:04.213309: val_loss -0.7525 +2024-11-22 17:39:04.213460: Pseudo dice [0.8445] +2024-11-22 17:39:04.213555: Epoch time: 19.54 s +2024-11-22 17:39:05.220042: +2024-11-22 17:39:05.220934: Epoch 5578 +2024-11-22 17:39:05.221078: Current learning rate: 0.00341 +2024-11-22 17:39:24.666340: train_loss -0.792 +2024-11-22 17:39:24.674919: val_loss -0.756 +2024-11-22 17:39:24.675534: Pseudo dice [0.848] +2024-11-22 17:39:24.675655: Epoch time: 19.45 s +2024-11-22 17:39:25.661525: +2024-11-22 17:39:25.662399: Epoch 5579 +2024-11-22 17:39:25.662529: Current learning rate: 0.00341 +2024-11-22 17:39:45.301940: train_loss -0.7822 +2024-11-22 17:39:45.313545: val_loss -0.7901 +2024-11-22 17:39:45.313686: Pseudo dice [0.851] +2024-11-22 17:39:45.313776: Epoch time: 19.64 s +2024-11-22 17:39:46.273702: +2024-11-22 17:39:46.274486: Epoch 5580 +2024-11-22 17:39:46.274605: Current learning rate: 0.00341 +2024-11-22 17:40:07.178890: train_loss -0.7884 +2024-11-22 17:40:07.202166: val_loss -0.7958 +2024-11-22 17:40:07.202313: Pseudo dice [0.8654] +2024-11-22 17:40:07.202415: Epoch time: 20.91 s +2024-11-22 17:40:08.129465: +2024-11-22 17:40:08.130352: Epoch 5581 +2024-11-22 17:40:08.130470: Current learning rate: 0.00341 +2024-11-22 17:40:27.069280: train_loss -0.7986 +2024-11-22 17:40:27.087307: val_loss -0.767 +2024-11-22 17:40:27.087482: Pseudo dice [0.859] +2024-11-22 17:40:27.087592: Epoch time: 18.94 s +2024-11-22 17:40:27.951837: +2024-11-22 17:40:27.952707: Epoch 5582 +2024-11-22 17:40:27.953056: Current learning rate: 0.00341 +2024-11-22 17:40:47.648132: train_loss -0.7993 +2024-11-22 17:40:47.655243: val_loss -0.7735 +2024-11-22 17:40:47.655380: Pseudo dice [0.8548] +2024-11-22 17:40:47.655498: Epoch time: 19.7 s +2024-11-22 17:40:48.987814: +2024-11-22 17:40:48.989095: Epoch 5583 +2024-11-22 17:40:48.989214: Current learning rate: 0.00341 +2024-11-22 17:41:08.713235: train_loss -0.8042 +2024-11-22 17:41:08.718731: val_loss -0.7706 +2024-11-22 17:41:08.718876: Pseudo dice [0.8534] +2024-11-22 17:41:08.719054: Epoch time: 19.73 s +2024-11-22 17:41:09.901488: +2024-11-22 17:41:09.902941: Epoch 5584 +2024-11-22 17:41:09.903094: Current learning rate: 0.0034 +2024-11-22 17:41:28.610901: train_loss -0.8047 +2024-11-22 17:41:28.612903: val_loss -0.7805 +2024-11-22 17:41:28.613016: Pseudo dice [0.8552] +2024-11-22 17:41:28.613117: Epoch time: 18.71 s +2024-11-22 17:41:29.487044: +2024-11-22 17:41:29.488209: Epoch 5585 +2024-11-22 17:41:29.488352: Current learning rate: 0.0034 +2024-11-22 17:41:49.242842: train_loss -0.8005 +2024-11-22 17:41:49.255968: val_loss -0.7606 +2024-11-22 17:41:49.256167: Pseudo dice [0.8504] +2024-11-22 17:41:49.256266: Epoch time: 19.76 s +2024-11-22 17:41:50.309994: +2024-11-22 17:41:50.310858: Epoch 5586 +2024-11-22 17:41:50.310995: Current learning rate: 0.0034 +2024-11-22 17:42:10.218884: train_loss -0.7933 +2024-11-22 17:42:10.225771: val_loss -0.8054 +2024-11-22 17:42:10.225898: Pseudo dice [0.8715] +2024-11-22 17:42:10.225989: Epoch time: 19.91 s +2024-11-22 17:42:11.273038: +2024-11-22 17:42:11.275098: Epoch 5587 +2024-11-22 17:42:11.275278: Current learning rate: 0.0034 +2024-11-22 17:42:31.632225: train_loss -0.8069 +2024-11-22 17:42:31.639961: val_loss -0.7786 +2024-11-22 17:42:31.640111: Pseudo dice [0.8553] +2024-11-22 17:42:31.640203: Epoch time: 20.36 s +2024-11-22 17:42:32.533599: +2024-11-22 17:42:32.534136: Epoch 5588 +2024-11-22 17:42:32.534261: Current learning rate: 0.0034 +2024-11-22 17:42:51.944155: train_loss -0.7943 +2024-11-22 17:42:51.965690: val_loss -0.7846 +2024-11-22 17:42:51.965849: Pseudo dice [0.8526] +2024-11-22 17:42:51.965961: Epoch time: 19.41 s +2024-11-22 17:42:52.980594: +2024-11-22 17:42:52.982903: Epoch 5589 +2024-11-22 17:42:52.983030: Current learning rate: 0.0034 +2024-11-22 17:43:12.050176: train_loss -0.7956 +2024-11-22 17:43:12.064019: val_loss -0.7878 +2024-11-22 17:43:12.064163: Pseudo dice [0.8514] +2024-11-22 17:43:12.064367: Epoch time: 19.07 s +2024-11-22 17:43:13.115412: +2024-11-22 17:43:13.116773: Epoch 5590 +2024-11-22 17:43:13.116937: Current learning rate: 0.0034 +2024-11-22 17:43:32.619938: train_loss -0.7956 +2024-11-22 17:43:32.626541: val_loss -0.7754 +2024-11-22 17:43:32.626688: Pseudo dice [0.8533] +2024-11-22 17:43:32.626782: Epoch time: 19.51 s +2024-11-22 17:43:33.626333: +2024-11-22 17:43:33.628103: Epoch 5591 +2024-11-22 17:43:33.628241: Current learning rate: 0.0034 +2024-11-22 17:43:54.203096: train_loss -0.8007 +2024-11-22 17:43:54.210989: val_loss -0.7772 +2024-11-22 17:43:54.211156: Pseudo dice [0.8633] +2024-11-22 17:43:54.211249: Epoch time: 20.58 s +2024-11-22 17:43:55.099067: +2024-11-22 17:43:55.099938: Epoch 5592 +2024-11-22 17:43:55.100049: Current learning rate: 0.00339 +2024-11-22 17:44:14.232963: train_loss -0.7979 +2024-11-22 17:44:14.237533: val_loss -0.7605 +2024-11-22 17:44:14.239406: Pseudo dice [0.8438] +2024-11-22 17:44:14.239573: Epoch time: 19.13 s +2024-11-22 17:44:15.107075: +2024-11-22 17:44:15.107912: Epoch 5593 +2024-11-22 17:44:15.108043: Current learning rate: 0.00339 +2024-11-22 17:44:34.474186: train_loss -0.8069 +2024-11-22 17:44:34.480635: val_loss -0.7703 +2024-11-22 17:44:34.480763: Pseudo dice [0.8542] +2024-11-22 17:44:34.480865: Epoch time: 19.37 s +2024-11-22 17:44:35.767578: +2024-11-22 17:44:35.769389: Epoch 5594 +2024-11-22 17:44:35.769519: Current learning rate: 0.00339 +2024-11-22 17:44:53.976141: train_loss -0.802 +2024-11-22 17:44:53.988056: val_loss -0.7738 +2024-11-22 17:44:53.988199: Pseudo dice [0.8622] +2024-11-22 17:44:53.988476: Epoch time: 18.21 s +2024-11-22 17:44:54.861779: +2024-11-22 17:44:54.862763: Epoch 5595 +2024-11-22 17:44:54.862890: Current learning rate: 0.00339 +2024-11-22 17:45:12.604354: train_loss -0.8063 +2024-11-22 17:45:12.613088: val_loss -0.7908 +2024-11-22 17:45:12.613324: Pseudo dice [0.8521] +2024-11-22 17:45:12.613417: Epoch time: 17.74 s +2024-11-22 17:45:13.599200: +2024-11-22 17:45:13.600655: Epoch 5596 +2024-11-22 17:45:13.600788: Current learning rate: 0.00339 +2024-11-22 17:45:33.161899: train_loss -0.8031 +2024-11-22 17:45:33.170156: val_loss -0.7638 +2024-11-22 17:45:33.170288: Pseudo dice [0.8583] +2024-11-22 17:45:33.170398: Epoch time: 19.56 s +2024-11-22 17:45:34.045332: +2024-11-22 17:45:34.046989: Epoch 5597 +2024-11-22 17:45:34.047129: Current learning rate: 0.00339 +2024-11-22 17:45:52.864656: train_loss -0.796 +2024-11-22 17:45:52.880417: val_loss -0.7733 +2024-11-22 17:45:52.880554: Pseudo dice [0.8421] +2024-11-22 17:45:52.880658: Epoch time: 18.82 s +2024-11-22 17:45:53.846333: +2024-11-22 17:45:53.846983: Epoch 5598 +2024-11-22 17:45:53.847126: Current learning rate: 0.00339 +2024-11-22 17:46:13.551361: train_loss -0.7983 +2024-11-22 17:46:13.566239: val_loss -0.7936 +2024-11-22 17:46:13.566386: Pseudo dice [0.8565] +2024-11-22 17:46:13.566477: Epoch time: 19.71 s +2024-11-22 17:46:14.451892: +2024-11-22 17:46:14.453280: Epoch 5599 +2024-11-22 17:46:14.453407: Current learning rate: 0.00339 +2024-11-22 17:46:33.715972: train_loss -0.8011 +2024-11-22 17:46:33.718585: val_loss -0.7478 +2024-11-22 17:46:33.718709: Pseudo dice [0.8484] +2024-11-22 17:46:33.718799: Epoch time: 19.26 s +2024-11-22 17:46:34.998104: +2024-11-22 17:46:34.999410: Epoch 5600 +2024-11-22 17:46:34.999530: Current learning rate: 0.00338 +2024-11-22 17:46:55.338984: train_loss -0.8023 +2024-11-22 17:46:55.341369: val_loss -0.775 +2024-11-22 17:46:55.341522: Pseudo dice [0.8541] +2024-11-22 17:46:55.341634: Epoch time: 20.34 s +2024-11-22 17:46:56.324251: +2024-11-22 17:46:56.325940: Epoch 5601 +2024-11-22 17:46:56.326078: Current learning rate: 0.00338 +2024-11-22 17:47:15.818236: train_loss -0.7994 +2024-11-22 17:47:15.826749: val_loss -0.7704 +2024-11-22 17:47:15.826880: Pseudo dice [0.8472] +2024-11-22 17:47:15.826977: Epoch time: 19.49 s +2024-11-22 17:47:16.777747: +2024-11-22 17:47:16.779411: Epoch 5602 +2024-11-22 17:47:16.779535: Current learning rate: 0.00338 +2024-11-22 17:47:35.671522: train_loss -0.7997 +2024-11-22 17:47:35.679071: val_loss -0.7985 +2024-11-22 17:47:35.679214: Pseudo dice [0.8592] +2024-11-22 17:47:35.679318: Epoch time: 18.89 s +2024-11-22 17:47:36.735970: +2024-11-22 17:47:36.736684: Epoch 5603 +2024-11-22 17:47:36.736824: Current learning rate: 0.00338 +2024-11-22 17:47:56.432971: train_loss -0.8013 +2024-11-22 17:47:56.436768: val_loss -0.7797 +2024-11-22 17:47:56.436905: Pseudo dice [0.8575] +2024-11-22 17:47:56.437000: Epoch time: 19.7 s +2024-11-22 17:47:57.521042: +2024-11-22 17:47:57.522415: Epoch 5604 +2024-11-22 17:47:57.522538: Current learning rate: 0.00338 +2024-11-22 17:48:17.000121: train_loss -0.8043 +2024-11-22 17:48:17.008498: val_loss -0.7684 +2024-11-22 17:48:17.008734: Pseudo dice [0.8497] +2024-11-22 17:48:17.008830: Epoch time: 19.48 s +2024-11-22 17:48:18.027395: +2024-11-22 17:48:18.028188: Epoch 5605 +2024-11-22 17:48:18.028307: Current learning rate: 0.00338 +2024-11-22 17:48:38.716367: train_loss -0.8037 +2024-11-22 17:48:38.720771: val_loss -0.7702 +2024-11-22 17:48:38.720922: Pseudo dice [0.8544] +2024-11-22 17:48:38.721038: Epoch time: 20.69 s +2024-11-22 17:48:40.207558: +2024-11-22 17:48:40.209337: Epoch 5606 +2024-11-22 17:48:40.209481: Current learning rate: 0.00338 +2024-11-22 17:48:59.904121: train_loss -0.7932 +2024-11-22 17:48:59.910995: val_loss -0.779 +2024-11-22 17:48:59.911131: Pseudo dice [0.8452] +2024-11-22 17:48:59.911224: Epoch time: 19.7 s +2024-11-22 17:49:00.956626: +2024-11-22 17:49:00.956865: Epoch 5607 +2024-11-22 17:49:00.956995: Current learning rate: 0.00337 +2024-11-22 17:49:20.447939: train_loss -0.782 +2024-11-22 17:49:20.467745: val_loss -0.7703 +2024-11-22 17:49:20.467907: Pseudo dice [0.8482] +2024-11-22 17:49:20.468006: Epoch time: 19.49 s +2024-11-22 17:49:21.383837: +2024-11-22 17:49:21.384032: Epoch 5608 +2024-11-22 17:49:21.384150: Current learning rate: 0.00337 +2024-11-22 17:49:39.580235: train_loss -0.7979 +2024-11-22 17:49:39.584981: val_loss -0.7724 +2024-11-22 17:49:39.585166: Pseudo dice [0.8499] +2024-11-22 17:49:39.585263: Epoch time: 18.2 s +2024-11-22 17:49:40.460753: +2024-11-22 17:49:40.460989: Epoch 5609 +2024-11-22 17:49:40.461122: Current learning rate: 0.00337 +2024-11-22 17:49:58.656025: train_loss -0.7876 +2024-11-22 17:49:58.656279: val_loss -0.7882 +2024-11-22 17:49:58.656384: Pseudo dice [0.8426] +2024-11-22 17:49:58.656475: Epoch time: 18.2 s +2024-11-22 17:49:59.524526: +2024-11-22 17:49:59.524730: Epoch 5610 +2024-11-22 17:49:59.524844: Current learning rate: 0.00337 +2024-11-22 17:50:18.184492: train_loss -0.801 +2024-11-22 17:50:18.190033: val_loss -0.7753 +2024-11-22 17:50:18.190187: Pseudo dice [0.8547] +2024-11-22 17:50:18.190282: Epoch time: 18.66 s +2024-11-22 17:50:19.052958: +2024-11-22 17:50:19.053171: Epoch 5611 +2024-11-22 17:50:19.053290: Current learning rate: 0.00337 +2024-11-22 17:50:36.880990: train_loss -0.7901 +2024-11-22 17:50:36.883137: val_loss -0.7843 +2024-11-22 17:50:36.883251: Pseudo dice [0.8488] +2024-11-22 17:50:36.883352: Epoch time: 17.83 s +2024-11-22 17:50:37.881274: +2024-11-22 17:50:37.881461: Epoch 5612 +2024-11-22 17:50:37.881584: Current learning rate: 0.00337 +2024-11-22 17:50:57.399056: train_loss -0.8013 +2024-11-22 17:50:57.399300: val_loss -0.7744 +2024-11-22 17:50:57.399398: Pseudo dice [0.8472] +2024-11-22 17:50:57.399478: Epoch time: 19.52 s +2024-11-22 17:50:58.278411: +2024-11-22 17:50:58.278625: Epoch 5613 +2024-11-22 17:50:58.278747: Current learning rate: 0.00337 +2024-11-22 17:51:17.319188: train_loss -0.792 +2024-11-22 17:51:17.319956: val_loss -0.781 +2024-11-22 17:51:17.320055: Pseudo dice [0.843] +2024-11-22 17:51:17.320148: Epoch time: 19.04 s +2024-11-22 17:51:18.190354: +2024-11-22 17:51:18.190567: Epoch 5614 +2024-11-22 17:51:18.190693: Current learning rate: 0.00337 +2024-11-22 17:51:39.169391: train_loss -0.7984 +2024-11-22 17:51:39.193949: val_loss -0.769 +2024-11-22 17:51:39.194129: Pseudo dice [0.8579] +2024-11-22 17:51:39.194229: Epoch time: 20.98 s +2024-11-22 17:51:40.061875: +2024-11-22 17:51:40.062094: Epoch 5615 +2024-11-22 17:51:40.062217: Current learning rate: 0.00336 +2024-11-22 17:51:57.953788: train_loss -0.7842 +2024-11-22 17:51:57.957029: val_loss -0.76 +2024-11-22 17:51:57.957192: Pseudo dice [0.8408] +2024-11-22 17:51:57.957290: Epoch time: 17.89 s +2024-11-22 17:51:58.881866: +2024-11-22 17:51:58.882079: Epoch 5616 +2024-11-22 17:51:58.882199: Current learning rate: 0.00336 +2024-11-22 17:52:17.936980: train_loss -0.7878 +2024-11-22 17:52:17.942040: val_loss -0.7749 +2024-11-22 17:52:17.942185: Pseudo dice [0.8482] +2024-11-22 17:52:17.942293: Epoch time: 19.06 s +2024-11-22 17:52:19.326422: +2024-11-22 17:52:19.326632: Epoch 5617 +2024-11-22 17:52:19.326746: Current learning rate: 0.00336 +2024-11-22 17:52:37.363232: train_loss -0.7826 +2024-11-22 17:52:37.366807: val_loss -0.7726 +2024-11-22 17:52:37.366930: Pseudo dice [0.8488] +2024-11-22 17:52:37.367016: Epoch time: 18.04 s +2024-11-22 17:52:38.334181: +2024-11-22 17:52:38.334414: Epoch 5618 +2024-11-22 17:52:38.334532: Current learning rate: 0.00336 +2024-11-22 17:52:57.722961: train_loss -0.7868 +2024-11-22 17:52:57.754706: val_loss -0.77 +2024-11-22 17:52:57.754875: Pseudo dice [0.8405] +2024-11-22 17:52:57.754967: Epoch time: 19.39 s +2024-11-22 17:52:58.674738: +2024-11-22 17:52:58.674951: Epoch 5619 +2024-11-22 17:52:58.675070: Current learning rate: 0.00336 +2024-11-22 17:53:19.058161: train_loss -0.7898 +2024-11-22 17:53:19.106848: val_loss -0.7665 +2024-11-22 17:53:19.107008: Pseudo dice [0.8579] +2024-11-22 17:53:19.107103: Epoch time: 20.38 s +2024-11-22 17:53:19.978865: +2024-11-22 17:53:19.979070: Epoch 5620 +2024-11-22 17:53:19.979201: Current learning rate: 0.00336 +2024-11-22 17:53:39.098814: train_loss -0.785 +2024-11-22 17:53:39.117668: val_loss -0.7551 +2024-11-22 17:53:39.117829: Pseudo dice [0.8595] +2024-11-22 17:53:39.117927: Epoch time: 19.12 s +2024-11-22 17:53:40.146111: +2024-11-22 17:53:40.146311: Epoch 5621 +2024-11-22 17:53:40.146438: Current learning rate: 0.00336 +2024-11-22 17:54:00.192580: train_loss -0.796 +2024-11-22 17:54:00.211632: val_loss -0.7708 +2024-11-22 17:54:00.211792: Pseudo dice [0.854] +2024-11-22 17:54:00.211890: Epoch time: 20.05 s +2024-11-22 17:54:01.108084: +2024-11-22 17:54:01.108307: Epoch 5622 +2024-11-22 17:54:01.108419: Current learning rate: 0.00336 +2024-11-22 17:54:20.918665: train_loss -0.7808 +2024-11-22 17:54:20.925132: val_loss -0.7504 +2024-11-22 17:54:20.925286: Pseudo dice [0.8303] +2024-11-22 17:54:20.925373: Epoch time: 19.81 s +2024-11-22 17:54:21.831709: +2024-11-22 17:54:21.831932: Epoch 5623 +2024-11-22 17:54:21.832054: Current learning rate: 0.00335 +2024-11-22 17:54:40.244120: train_loss -0.7812 +2024-11-22 17:54:40.252312: val_loss -0.7666 +2024-11-22 17:54:40.252442: Pseudo dice [0.8595] +2024-11-22 17:54:40.252546: Epoch time: 18.41 s +2024-11-22 17:54:41.336629: +2024-11-22 17:54:41.336833: Epoch 5624 +2024-11-22 17:54:41.336951: Current learning rate: 0.00335 +2024-11-22 17:54:59.911596: train_loss -0.7958 +2024-11-22 17:54:59.936172: val_loss -0.7909 +2024-11-22 17:54:59.936337: Pseudo dice [0.8584] +2024-11-22 17:54:59.936438: Epoch time: 18.58 s +2024-11-22 17:55:00.921750: +2024-11-22 17:55:00.921941: Epoch 5625 +2024-11-22 17:55:00.922073: Current learning rate: 0.00335 +2024-11-22 17:55:19.804439: train_loss -0.792 +2024-11-22 17:55:19.814733: val_loss -0.751 +2024-11-22 17:55:19.814886: Pseudo dice [0.837] +2024-11-22 17:55:19.814995: Epoch time: 18.88 s +2024-11-22 17:55:20.794518: +2024-11-22 17:55:20.794744: Epoch 5626 +2024-11-22 17:55:20.794867: Current learning rate: 0.00335 +2024-11-22 17:55:39.644730: train_loss -0.7889 +2024-11-22 17:55:39.659742: val_loss -0.7742 +2024-11-22 17:55:39.659865: Pseudo dice [0.8654] +2024-11-22 17:55:39.659954: Epoch time: 18.85 s +2024-11-22 17:55:40.646688: +2024-11-22 17:55:40.646894: Epoch 5627 +2024-11-22 17:55:40.647006: Current learning rate: 0.00335 +2024-11-22 17:55:59.869178: train_loss -0.7998 +2024-11-22 17:55:59.888279: val_loss -0.7858 +2024-11-22 17:55:59.888418: Pseudo dice [0.8597] +2024-11-22 17:55:59.888510: Epoch time: 19.22 s +2024-11-22 17:56:00.789528: +2024-11-22 17:56:00.789733: Epoch 5628 +2024-11-22 17:56:00.789853: Current learning rate: 0.00335 +2024-11-22 17:56:18.576735: train_loss -0.795 +2024-11-22 17:56:18.605126: val_loss -0.7734 +2024-11-22 17:56:18.605298: Pseudo dice [0.8715] +2024-11-22 17:56:18.605396: Epoch time: 17.79 s +2024-11-22 17:56:19.861424: +2024-11-22 17:56:19.861705: Epoch 5629 +2024-11-22 17:56:19.861821: Current learning rate: 0.00335 +2024-11-22 17:56:39.591406: train_loss -0.7889 +2024-11-22 17:56:39.640771: val_loss -0.757 +2024-11-22 17:56:39.640948: Pseudo dice [0.8372] +2024-11-22 17:56:39.641050: Epoch time: 19.73 s +2024-11-22 17:56:40.621947: +2024-11-22 17:56:40.622157: Epoch 5630 +2024-11-22 17:56:40.622290: Current learning rate: 0.00335 +2024-11-22 17:57:00.575609: train_loss -0.794 +2024-11-22 17:57:00.634818: val_loss -0.7696 +2024-11-22 17:57:00.634994: Pseudo dice [0.8675] +2024-11-22 17:57:00.635102: Epoch time: 19.95 s +2024-11-22 17:57:01.640727: +2024-11-22 17:57:01.640946: Epoch 5631 +2024-11-22 17:57:01.641070: Current learning rate: 0.00334 +2024-11-22 17:57:20.020120: train_loss -0.8027 +2024-11-22 17:57:20.022782: val_loss -0.7714 +2024-11-22 17:57:20.022929: Pseudo dice [0.8617] +2024-11-22 17:57:20.023023: Epoch time: 18.38 s +2024-11-22 17:57:21.008906: +2024-11-22 17:57:21.009125: Epoch 5632 +2024-11-22 17:57:21.009242: Current learning rate: 0.00334 +2024-11-22 17:57:39.816105: train_loss -0.7922 +2024-11-22 17:57:39.840211: val_loss -0.7546 +2024-11-22 17:57:39.840385: Pseudo dice [0.8498] +2024-11-22 17:57:39.840482: Epoch time: 18.81 s +2024-11-22 17:57:40.731404: +2024-11-22 17:57:40.731618: Epoch 5633 +2024-11-22 17:57:40.731733: Current learning rate: 0.00334 +2024-11-22 17:57:59.111759: train_loss -0.7891 +2024-11-22 17:57:59.126214: val_loss -0.7694 +2024-11-22 17:57:59.126369: Pseudo dice [0.8498] +2024-11-22 17:57:59.126462: Epoch time: 18.38 s +2024-11-22 17:58:00.103033: +2024-11-22 17:58:00.103258: Epoch 5634 +2024-11-22 17:58:00.103399: Current learning rate: 0.00334 +2024-11-22 17:58:18.524389: train_loss -0.7981 +2024-11-22 17:58:18.537078: val_loss -0.7788 +2024-11-22 17:58:18.537223: Pseudo dice [0.8505] +2024-11-22 17:58:18.537372: Epoch time: 18.42 s +2024-11-22 17:58:19.513124: +2024-11-22 17:58:19.513332: Epoch 5635 +2024-11-22 17:58:19.513453: Current learning rate: 0.00334 +2024-11-22 17:58:37.671146: train_loss -0.8048 +2024-11-22 17:58:37.706829: val_loss -0.7814 +2024-11-22 17:58:37.706992: Pseudo dice [0.8387] +2024-11-22 17:58:37.707101: Epoch time: 18.16 s +2024-11-22 17:58:38.608952: +2024-11-22 17:58:38.609159: Epoch 5636 +2024-11-22 17:58:38.609272: Current learning rate: 0.00334 +2024-11-22 17:58:57.650029: train_loss -0.799 +2024-11-22 17:58:57.676043: val_loss -0.7851 +2024-11-22 17:58:57.676231: Pseudo dice [0.8592] +2024-11-22 17:58:57.676319: Epoch time: 19.04 s +2024-11-22 17:58:58.653946: +2024-11-22 17:58:58.654161: Epoch 5637 +2024-11-22 17:58:58.654292: Current learning rate: 0.00334 +2024-11-22 17:59:18.291684: train_loss -0.7981 +2024-11-22 17:59:18.303413: val_loss -0.7873 +2024-11-22 17:59:18.303568: Pseudo dice [0.8611] +2024-11-22 17:59:18.303661: Epoch time: 19.64 s +2024-11-22 17:59:19.173437: +2024-11-22 17:59:19.173647: Epoch 5638 +2024-11-22 17:59:19.173754: Current learning rate: 0.00334 +2024-11-22 17:59:38.590408: train_loss -0.8019 +2024-11-22 17:59:38.597221: val_loss -0.7575 +2024-11-22 17:59:38.597372: Pseudo dice [0.8492] +2024-11-22 17:59:38.597467: Epoch time: 19.42 s +2024-11-22 17:59:39.474733: +2024-11-22 17:59:39.474967: Epoch 5639 +2024-11-22 17:59:39.475151: Current learning rate: 0.00333 +2024-11-22 17:59:58.947240: train_loss -0.795 +2024-11-22 17:59:58.957753: val_loss -0.7824 +2024-11-22 17:59:58.957904: Pseudo dice [0.8505] +2024-11-22 17:59:58.957998: Epoch time: 19.47 s +2024-11-22 18:00:00.502339: +2024-11-22 18:00:00.502557: Epoch 5640 +2024-11-22 18:00:00.502685: Current learning rate: 0.00333 +2024-11-22 18:00:18.831259: train_loss -0.8 +2024-11-22 18:00:18.836900: val_loss -0.7685 +2024-11-22 18:00:18.837041: Pseudo dice [0.8595] +2024-11-22 18:00:18.837132: Epoch time: 18.33 s +2024-11-22 18:00:19.726492: +2024-11-22 18:00:19.726699: Epoch 5641 +2024-11-22 18:00:19.726822: Current learning rate: 0.00333 +2024-11-22 18:00:37.717404: train_loss -0.8057 +2024-11-22 18:00:37.723261: val_loss -0.7887 +2024-11-22 18:00:37.723392: Pseudo dice [0.8581] +2024-11-22 18:00:37.723505: Epoch time: 17.99 s +2024-11-22 18:00:38.629471: +2024-11-22 18:00:38.629675: Epoch 5642 +2024-11-22 18:00:38.629809: Current learning rate: 0.00333 +2024-11-22 18:00:57.570031: train_loss -0.8033 +2024-11-22 18:00:57.573601: val_loss -0.7953 +2024-11-22 18:00:57.573747: Pseudo dice [0.8637] +2024-11-22 18:00:57.573853: Epoch time: 18.94 s +2024-11-22 18:00:58.557852: +2024-11-22 18:00:58.558056: Epoch 5643 +2024-11-22 18:00:58.558185: Current learning rate: 0.00333 +2024-11-22 18:01:17.569802: train_loss -0.8012 +2024-11-22 18:01:17.576471: val_loss -0.7442 +2024-11-22 18:01:17.576608: Pseudo dice [0.8474] +2024-11-22 18:01:17.576709: Epoch time: 19.01 s +2024-11-22 18:01:18.508859: +2024-11-22 18:01:18.509081: Epoch 5644 +2024-11-22 18:01:18.509196: Current learning rate: 0.00333 +2024-11-22 18:01:37.534981: train_loss -0.8077 +2024-11-22 18:01:37.550919: val_loss -0.786 +2024-11-22 18:01:37.551066: Pseudo dice [0.8603] +2024-11-22 18:01:37.551152: Epoch time: 19.03 s +2024-11-22 18:01:38.641310: +2024-11-22 18:01:38.641504: Epoch 5645 +2024-11-22 18:01:38.641632: Current learning rate: 0.00333 +2024-11-22 18:01:59.070046: train_loss -0.8015 +2024-11-22 18:01:59.078720: val_loss -0.7979 +2024-11-22 18:01:59.125525: Pseudo dice [0.8608] +2024-11-22 18:01:59.125723: Epoch time: 20.43 s +2024-11-22 18:02:00.060907: +2024-11-22 18:02:00.061137: Epoch 5646 +2024-11-22 18:02:00.061289: Current learning rate: 0.00333 +2024-11-22 18:02:19.495324: train_loss -0.8043 +2024-11-22 18:02:19.504025: val_loss -0.7769 +2024-11-22 18:02:19.504211: Pseudo dice [0.8467] +2024-11-22 18:02:19.504315: Epoch time: 19.44 s +2024-11-22 18:02:20.471117: +2024-11-22 18:02:20.471323: Epoch 5647 +2024-11-22 18:02:20.471444: Current learning rate: 0.00332 +2024-11-22 18:02:40.440910: train_loss -0.8015 +2024-11-22 18:02:40.452836: val_loss -0.7634 +2024-11-22 18:02:40.452946: Pseudo dice [0.8598] +2024-11-22 18:02:40.453034: Epoch time: 19.97 s +2024-11-22 18:02:41.425831: +2024-11-22 18:02:41.426036: Epoch 5648 +2024-11-22 18:02:41.426176: Current learning rate: 0.00332 +2024-11-22 18:03:00.551009: train_loss -0.7969 +2024-11-22 18:03:00.558451: val_loss -0.7874 +2024-11-22 18:03:00.558577: Pseudo dice [0.8477] +2024-11-22 18:03:00.558697: Epoch time: 19.13 s +2024-11-22 18:03:01.583237: +2024-11-22 18:03:01.583445: Epoch 5649 +2024-11-22 18:03:01.583576: Current learning rate: 0.00332 +2024-11-22 18:03:21.322903: train_loss -0.8054 +2024-11-22 18:03:21.326747: val_loss -0.7849 +2024-11-22 18:03:21.326882: Pseudo dice [0.8476] +2024-11-22 18:03:21.326975: Epoch time: 19.74 s +2024-11-22 18:03:22.505804: +2024-11-22 18:03:22.506468: Epoch 5650 +2024-11-22 18:03:22.506596: Current learning rate: 0.00332 +2024-11-22 18:03:41.460243: train_loss -0.8015 +2024-11-22 18:03:41.481639: val_loss -0.7495 +2024-11-22 18:03:41.481781: Pseudo dice [0.8513] +2024-11-22 18:03:41.481875: Epoch time: 18.96 s +2024-11-22 18:03:42.350763: +2024-11-22 18:03:42.350965: Epoch 5651 +2024-11-22 18:03:42.351092: Current learning rate: 0.00332 +2024-11-22 18:04:01.458682: train_loss -0.8007 +2024-11-22 18:04:01.467648: val_loss -0.76 +2024-11-22 18:04:01.467788: Pseudo dice [0.852] +2024-11-22 18:04:01.467878: Epoch time: 19.11 s +2024-11-22 18:04:02.390469: +2024-11-22 18:04:02.390679: Epoch 5652 +2024-11-22 18:04:02.390812: Current learning rate: 0.00332 +2024-11-22 18:04:21.664250: train_loss -0.8096 +2024-11-22 18:04:21.666279: val_loss -0.7842 +2024-11-22 18:04:21.666396: Pseudo dice [0.8597] +2024-11-22 18:04:21.666525: Epoch time: 19.27 s +2024-11-22 18:04:22.541472: +2024-11-22 18:04:22.541688: Epoch 5653 +2024-11-22 18:04:22.541803: Current learning rate: 0.00332 +2024-11-22 18:04:42.816958: train_loss -0.8032 +2024-11-22 18:04:42.822289: val_loss -0.7687 +2024-11-22 18:04:42.822428: Pseudo dice [0.8487] +2024-11-22 18:04:42.822521: Epoch time: 20.28 s +2024-11-22 18:04:43.706587: +2024-11-22 18:04:43.706792: Epoch 5654 +2024-11-22 18:04:43.706908: Current learning rate: 0.00332 +2024-11-22 18:05:02.907670: train_loss -0.8008 +2024-11-22 18:05:02.915409: val_loss -0.7887 +2024-11-22 18:05:02.915532: Pseudo dice [0.8526] +2024-11-22 18:05:02.915624: Epoch time: 19.2 s +2024-11-22 18:05:03.926534: +2024-11-22 18:05:03.926985: Epoch 5655 +2024-11-22 18:05:03.927105: Current learning rate: 0.00331 +2024-11-22 18:05:22.753114: train_loss -0.8019 +2024-11-22 18:05:22.760643: val_loss -0.7707 +2024-11-22 18:05:22.760783: Pseudo dice [0.8514] +2024-11-22 18:05:22.760890: Epoch time: 18.83 s +2024-11-22 18:05:23.675122: +2024-11-22 18:05:23.675685: Epoch 5656 +2024-11-22 18:05:23.675798: Current learning rate: 0.00331 +2024-11-22 18:05:44.277447: train_loss -0.8054 +2024-11-22 18:05:44.283925: val_loss -0.743 +2024-11-22 18:05:44.284095: Pseudo dice [0.8646] +2024-11-22 18:05:44.284208: Epoch time: 20.6 s +2024-11-22 18:05:45.205978: +2024-11-22 18:05:45.206185: Epoch 5657 +2024-11-22 18:05:45.206323: Current learning rate: 0.00331 +2024-11-22 18:06:05.270100: train_loss -0.807 +2024-11-22 18:06:05.295045: val_loss -0.7877 +2024-11-22 18:06:05.295201: Pseudo dice [0.8679] +2024-11-22 18:06:05.295304: Epoch time: 20.06 s +2024-11-22 18:06:06.251195: +2024-11-22 18:06:06.251410: Epoch 5658 +2024-11-22 18:06:06.251541: Current learning rate: 0.00331 +2024-11-22 18:06:26.691903: train_loss -0.8035 +2024-11-22 18:06:26.694117: val_loss -0.759 +2024-11-22 18:06:26.694232: Pseudo dice [0.8492] +2024-11-22 18:06:26.694321: Epoch time: 20.44 s +2024-11-22 18:06:27.589486: +2024-11-22 18:06:27.589690: Epoch 5659 +2024-11-22 18:06:27.589822: Current learning rate: 0.00331 +2024-11-22 18:06:45.951342: train_loss -0.8031 +2024-11-22 18:06:45.956983: val_loss -0.7584 +2024-11-22 18:06:45.957113: Pseudo dice [0.8529] +2024-11-22 18:06:45.957216: Epoch time: 18.36 s +2024-11-22 18:06:46.820828: +2024-11-22 18:06:46.821037: Epoch 5660 +2024-11-22 18:06:46.821169: Current learning rate: 0.00331 +2024-11-22 18:07:05.709024: train_loss -0.8064 +2024-11-22 18:07:05.714874: val_loss -0.7838 +2024-11-22 18:07:05.715030: Pseudo dice [0.8571] +2024-11-22 18:07:05.715162: Epoch time: 18.89 s +2024-11-22 18:07:06.680697: +2024-11-22 18:07:06.681156: Epoch 5661 +2024-11-22 18:07:06.681275: Current learning rate: 0.00331 +2024-11-22 18:07:25.158919: train_loss -0.8085 +2024-11-22 18:07:25.173750: val_loss -0.7429 +2024-11-22 18:07:25.173878: Pseudo dice [0.8531] +2024-11-22 18:07:25.173979: Epoch time: 18.48 s +2024-11-22 18:07:26.777575: +2024-11-22 18:07:26.778594: Epoch 5662 +2024-11-22 18:07:26.778727: Current learning rate: 0.00331 +2024-11-22 18:07:46.103279: train_loss -0.8054 +2024-11-22 18:07:46.111718: val_loss -0.7874 +2024-11-22 18:07:46.118574: Pseudo dice [0.8599] +2024-11-22 18:07:46.118690: Epoch time: 19.33 s +2024-11-22 18:07:47.221747: +2024-11-22 18:07:47.222338: Epoch 5663 +2024-11-22 18:07:47.222456: Current learning rate: 0.0033 +2024-11-22 18:08:05.771827: train_loss -0.8046 +2024-11-22 18:08:05.783598: val_loss -0.7712 +2024-11-22 18:08:05.783740: Pseudo dice [0.8464] +2024-11-22 18:08:05.783834: Epoch time: 18.55 s +2024-11-22 18:08:06.832317: +2024-11-22 18:08:06.833288: Epoch 5664 +2024-11-22 18:08:06.833431: Current learning rate: 0.0033 +2024-11-22 18:08:27.547549: train_loss -0.8069 +2024-11-22 18:08:27.556438: val_loss -0.7886 +2024-11-22 18:08:27.556592: Pseudo dice [0.8599] +2024-11-22 18:08:27.556687: Epoch time: 20.72 s +2024-11-22 18:08:28.578232: +2024-11-22 18:08:28.579137: Epoch 5665 +2024-11-22 18:08:28.579277: Current learning rate: 0.0033 +2024-11-22 18:08:48.003983: train_loss -0.7972 +2024-11-22 18:08:48.008986: val_loss -0.7753 +2024-11-22 18:08:48.009124: Pseudo dice [0.8546] +2024-11-22 18:08:48.009230: Epoch time: 19.43 s +2024-11-22 18:08:48.917388: +2024-11-22 18:08:48.918411: Epoch 5666 +2024-11-22 18:08:48.918550: Current learning rate: 0.0033 +2024-11-22 18:09:08.020923: train_loss -0.7961 +2024-11-22 18:09:08.032826: val_loss -0.7533 +2024-11-22 18:09:08.032971: Pseudo dice [0.867] +2024-11-22 18:09:08.033072: Epoch time: 19.1 s +2024-11-22 18:09:09.001680: +2024-11-22 18:09:09.002529: Epoch 5667 +2024-11-22 18:09:09.002660: Current learning rate: 0.0033 +2024-11-22 18:09:28.920453: train_loss -0.7956 +2024-11-22 18:09:28.927387: val_loss -0.7919 +2024-11-22 18:09:28.927594: Pseudo dice [0.8659] +2024-11-22 18:09:28.927692: Epoch time: 19.92 s +2024-11-22 18:09:29.957721: +2024-11-22 18:09:29.958868: Epoch 5668 +2024-11-22 18:09:29.958991: Current learning rate: 0.0033 +2024-11-22 18:09:48.381232: train_loss -0.8023 +2024-11-22 18:09:48.384315: val_loss -0.7813 +2024-11-22 18:09:48.384427: Pseudo dice [0.8472] +2024-11-22 18:09:48.384547: Epoch time: 18.42 s +2024-11-22 18:09:49.260465: +2024-11-22 18:09:49.262222: Epoch 5669 +2024-11-22 18:09:49.262349: Current learning rate: 0.0033 +2024-11-22 18:10:09.622275: train_loss -0.8034 +2024-11-22 18:10:09.632005: val_loss -0.8019 +2024-11-22 18:10:09.632172: Pseudo dice [0.8621] +2024-11-22 18:10:09.632287: Epoch time: 20.36 s +2024-11-22 18:10:10.623837: +2024-11-22 18:10:10.625113: Epoch 5670 +2024-11-22 18:10:10.625232: Current learning rate: 0.00329 +2024-11-22 18:10:29.817436: train_loss -0.7917 +2024-11-22 18:10:29.827252: val_loss -0.7737 +2024-11-22 18:10:29.827382: Pseudo dice [0.8538] +2024-11-22 18:10:29.827469: Epoch time: 19.19 s +2024-11-22 18:10:30.787148: +2024-11-22 18:10:30.788031: Epoch 5671 +2024-11-22 18:10:30.788156: Current learning rate: 0.00329 +2024-11-22 18:10:50.635024: train_loss -0.8014 +2024-11-22 18:10:50.642294: val_loss -0.7683 +2024-11-22 18:10:50.642421: Pseudo dice [0.8539] +2024-11-22 18:10:50.642516: Epoch time: 19.85 s +2024-11-22 18:10:51.717023: +2024-11-22 18:10:51.717493: Epoch 5672 +2024-11-22 18:10:51.717615: Current learning rate: 0.00329 +2024-11-22 18:11:10.567340: train_loss -0.8022 +2024-11-22 18:11:10.576092: val_loss -0.786 +2024-11-22 18:11:10.576293: Pseudo dice [0.8489] +2024-11-22 18:11:10.576403: Epoch time: 18.85 s +2024-11-22 18:11:11.459648: +2024-11-22 18:11:11.459850: Epoch 5673 +2024-11-22 18:11:11.459984: Current learning rate: 0.00329 +2024-11-22 18:11:30.523027: train_loss -0.8002 +2024-11-22 18:11:30.532018: val_loss -0.7685 +2024-11-22 18:11:30.532178: Pseudo dice [0.855] +2024-11-22 18:11:30.532280: Epoch time: 19.06 s +2024-11-22 18:11:31.917123: +2024-11-22 18:11:31.918922: Epoch 5674 +2024-11-22 18:11:31.919046: Current learning rate: 0.00329 +2024-11-22 18:11:50.626954: train_loss -0.8027 +2024-11-22 18:11:50.634632: val_loss -0.7802 +2024-11-22 18:11:50.634761: Pseudo dice [0.8662] +2024-11-22 18:11:50.634849: Epoch time: 18.71 s +2024-11-22 18:11:51.546879: +2024-11-22 18:11:51.547104: Epoch 5675 +2024-11-22 18:11:51.547227: Current learning rate: 0.00329 +2024-11-22 18:12:11.174188: train_loss -0.8031 +2024-11-22 18:12:11.187593: val_loss -0.7605 +2024-11-22 18:12:11.187732: Pseudo dice [0.857] +2024-11-22 18:12:11.187832: Epoch time: 19.63 s +2024-11-22 18:12:12.180834: +2024-11-22 18:12:12.182191: Epoch 5676 +2024-11-22 18:12:12.182339: Current learning rate: 0.00329 +2024-11-22 18:12:32.535736: train_loss -0.802 +2024-11-22 18:12:32.543837: val_loss -0.7669 +2024-11-22 18:12:32.544001: Pseudo dice [0.8385] +2024-11-22 18:12:32.544117: Epoch time: 20.36 s +2024-11-22 18:12:33.485153: +2024-11-22 18:12:33.486474: Epoch 5677 +2024-11-22 18:12:33.486600: Current learning rate: 0.00329 +2024-11-22 18:12:52.894900: train_loss -0.8043 +2024-11-22 18:12:52.903254: val_loss -0.7679 +2024-11-22 18:12:52.903408: Pseudo dice [0.8653] +2024-11-22 18:12:52.903499: Epoch time: 19.41 s +2024-11-22 18:12:53.944320: +2024-11-22 18:12:53.946000: Epoch 5678 +2024-11-22 18:12:53.946137: Current learning rate: 0.00328 +2024-11-22 18:13:12.465240: train_loss -0.8044 +2024-11-22 18:13:12.468199: val_loss -0.771 +2024-11-22 18:13:12.468304: Pseudo dice [0.8486] +2024-11-22 18:13:12.468396: Epoch time: 18.52 s +2024-11-22 18:13:13.339044: +2024-11-22 18:13:13.339801: Epoch 5679 +2024-11-22 18:13:13.339925: Current learning rate: 0.00328 +2024-11-22 18:13:32.308182: train_loss -0.8108 +2024-11-22 18:13:32.312688: val_loss -0.7619 +2024-11-22 18:13:32.312836: Pseudo dice [0.8619] +2024-11-22 18:13:32.312941: Epoch time: 18.97 s +2024-11-22 18:13:33.438012: +2024-11-22 18:13:33.445737: Epoch 5680 +2024-11-22 18:13:33.445874: Current learning rate: 0.00328 +2024-11-22 18:13:52.364653: train_loss -0.7935 +2024-11-22 18:13:52.367110: val_loss -0.7714 +2024-11-22 18:13:52.367202: Pseudo dice [0.8443] +2024-11-22 18:13:52.367288: Epoch time: 18.93 s +2024-11-22 18:13:53.234456: +2024-11-22 18:13:53.235791: Epoch 5681 +2024-11-22 18:13:53.235918: Current learning rate: 0.00328 +2024-11-22 18:14:12.694870: train_loss -0.8038 +2024-11-22 18:14:12.702571: val_loss -0.7751 +2024-11-22 18:14:12.702712: Pseudo dice [0.8523] +2024-11-22 18:14:12.702802: Epoch time: 19.46 s +2024-11-22 18:14:13.649164: +2024-11-22 18:14:13.649980: Epoch 5682 +2024-11-22 18:14:13.650115: Current learning rate: 0.00328 +2024-11-22 18:14:32.508854: train_loss -0.803 +2024-11-22 18:14:32.511539: val_loss -0.7868 +2024-11-22 18:14:32.511655: Pseudo dice [0.8573] +2024-11-22 18:14:32.511757: Epoch time: 18.86 s +2024-11-22 18:14:33.491858: +2024-11-22 18:14:33.492279: Epoch 5683 +2024-11-22 18:14:33.492414: Current learning rate: 0.00328 +2024-11-22 18:14:52.903164: train_loss -0.7996 +2024-11-22 18:14:52.922832: val_loss -0.7726 +2024-11-22 18:14:52.922992: Pseudo dice [0.8635] +2024-11-22 18:14:52.923295: Epoch time: 19.41 s +2024-11-22 18:14:53.946260: +2024-11-22 18:14:53.947358: Epoch 5684 +2024-11-22 18:14:53.947488: Current learning rate: 0.00328 +2024-11-22 18:15:13.669935: train_loss -0.8104 +2024-11-22 18:15:13.689140: val_loss -0.78 +2024-11-22 18:15:13.689290: Pseudo dice [0.8596] +2024-11-22 18:15:13.689405: Epoch time: 19.72 s +2024-11-22 18:15:15.059938: +2024-11-22 18:15:15.060917: Epoch 5685 +2024-11-22 18:15:15.061042: Current learning rate: 0.00328 +2024-11-22 18:15:35.787862: train_loss -0.8048 +2024-11-22 18:15:35.792767: val_loss -0.7834 +2024-11-22 18:15:35.792900: Pseudo dice [0.8497] +2024-11-22 18:15:35.793018: Epoch time: 20.73 s +2024-11-22 18:15:36.775468: +2024-11-22 18:15:36.776877: Epoch 5686 +2024-11-22 18:15:36.776995: Current learning rate: 0.00327 +2024-11-22 18:15:55.613756: train_loss -0.8074 +2024-11-22 18:15:55.617637: val_loss -0.7803 +2024-11-22 18:15:55.617752: Pseudo dice [0.8595] +2024-11-22 18:15:55.617932: Epoch time: 18.84 s +2024-11-22 18:15:56.746845: +2024-11-22 18:15:56.747312: Epoch 5687 +2024-11-22 18:15:56.747447: Current learning rate: 0.00327 +2024-11-22 18:16:16.288697: train_loss -0.8091 +2024-11-22 18:16:16.296684: val_loss -0.8004 +2024-11-22 18:16:16.296830: Pseudo dice [0.8431] +2024-11-22 18:16:16.296929: Epoch time: 19.54 s +2024-11-22 18:16:17.244605: +2024-11-22 18:16:17.245439: Epoch 5688 +2024-11-22 18:16:17.245570: Current learning rate: 0.00327 +2024-11-22 18:16:35.955002: train_loss -0.7977 +2024-11-22 18:16:35.958111: val_loss -0.7836 +2024-11-22 18:16:35.958233: Pseudo dice [0.8499] +2024-11-22 18:16:35.958323: Epoch time: 18.71 s +2024-11-22 18:16:36.839962: +2024-11-22 18:16:36.840528: Epoch 5689 +2024-11-22 18:16:36.840654: Current learning rate: 0.00327 +2024-11-22 18:16:56.403382: train_loss -0.8043 +2024-11-22 18:16:56.410516: val_loss -0.7652 +2024-11-22 18:16:56.410666: Pseudo dice [0.8535] +2024-11-22 18:16:56.410761: Epoch time: 19.56 s +2024-11-22 18:16:57.396631: +2024-11-22 18:16:57.397451: Epoch 5690 +2024-11-22 18:16:57.397575: Current learning rate: 0.00327 +2024-11-22 18:17:16.734735: train_loss -0.8047 +2024-11-22 18:17:16.740634: val_loss -0.7605 +2024-11-22 18:17:16.740785: Pseudo dice [0.8615] +2024-11-22 18:17:16.740871: Epoch time: 19.34 s +2024-11-22 18:17:17.620470: +2024-11-22 18:17:17.621165: Epoch 5691 +2024-11-22 18:17:17.621283: Current learning rate: 0.00327 +2024-11-22 18:17:36.547366: train_loss -0.798 +2024-11-22 18:17:36.556073: val_loss -0.7879 +2024-11-22 18:17:36.556226: Pseudo dice [0.8642] +2024-11-22 18:17:36.556330: Epoch time: 18.93 s +2024-11-22 18:17:37.536105: +2024-11-22 18:17:37.536625: Epoch 5692 +2024-11-22 18:17:37.536748: Current learning rate: 0.00327 +2024-11-22 18:17:55.022901: train_loss -0.8022 +2024-11-22 18:17:55.027174: val_loss -0.7476 +2024-11-22 18:17:55.027330: Pseudo dice [0.8337] +2024-11-22 18:17:55.027455: Epoch time: 17.49 s +2024-11-22 18:17:55.907185: +2024-11-22 18:17:55.907383: Epoch 5693 +2024-11-22 18:17:55.907499: Current learning rate: 0.00327 +2024-11-22 18:18:15.847790: train_loss -0.8032 +2024-11-22 18:18:15.851733: val_loss -0.7909 +2024-11-22 18:18:15.851890: Pseudo dice [0.8407] +2024-11-22 18:18:15.851990: Epoch time: 19.94 s +2024-11-22 18:18:16.761806: +2024-11-22 18:18:16.762386: Epoch 5694 +2024-11-22 18:18:16.762511: Current learning rate: 0.00326 +2024-11-22 18:18:36.231446: train_loss -0.8012 +2024-11-22 18:18:36.249000: val_loss -0.7713 +2024-11-22 18:18:36.249147: Pseudo dice [0.8424] +2024-11-22 18:18:36.249369: Epoch time: 19.47 s +2024-11-22 18:18:37.196871: +2024-11-22 18:18:37.198045: Epoch 5695 +2024-11-22 18:18:37.198194: Current learning rate: 0.00326 +2024-11-22 18:18:57.088187: train_loss -0.797 +2024-11-22 18:18:57.117964: val_loss -0.7591 +2024-11-22 18:18:57.118156: Pseudo dice [0.8599] +2024-11-22 18:18:57.118259: Epoch time: 19.89 s +2024-11-22 18:18:58.116983: +2024-11-22 18:18:58.118003: Epoch 5696 +2024-11-22 18:18:58.118130: Current learning rate: 0.00326 +2024-11-22 18:19:16.609405: train_loss -0.799 +2024-11-22 18:19:16.614110: val_loss -0.7995 +2024-11-22 18:19:16.614267: Pseudo dice [0.8541] +2024-11-22 18:19:16.614376: Epoch time: 18.49 s +2024-11-22 18:19:17.998363: +2024-11-22 18:19:17.999776: Epoch 5697 +2024-11-22 18:19:17.999915: Current learning rate: 0.00326 +2024-11-22 18:19:37.807509: train_loss -0.7877 +2024-11-22 18:19:37.810346: val_loss -0.7778 +2024-11-22 18:19:37.810509: Pseudo dice [0.8467] +2024-11-22 18:19:37.810635: Epoch time: 19.81 s +2024-11-22 18:19:38.880620: +2024-11-22 18:19:38.882307: Epoch 5698 +2024-11-22 18:19:38.882432: Current learning rate: 0.00326 +2024-11-22 18:19:57.920052: train_loss -0.7988 +2024-11-22 18:19:57.927816: val_loss -0.7982 +2024-11-22 18:19:57.927937: Pseudo dice [0.8602] +2024-11-22 18:19:57.928028: Epoch time: 19.04 s +2024-11-22 18:19:58.905212: +2024-11-22 18:19:58.906004: Epoch 5699 +2024-11-22 18:19:58.906138: Current learning rate: 0.00326 +2024-11-22 18:20:18.926235: train_loss -0.7981 +2024-11-22 18:20:18.928476: val_loss -0.7832 +2024-11-22 18:20:18.928570: Pseudo dice [0.8642] +2024-11-22 18:20:18.928672: Epoch time: 20.02 s +2024-11-22 18:20:20.095101: +2024-11-22 18:20:20.096434: Epoch 5700 +2024-11-22 18:20:20.096586: Current learning rate: 0.00326 +2024-11-22 18:20:38.014450: train_loss -0.8053 +2024-11-22 18:20:38.025027: val_loss -0.771 +2024-11-22 18:20:38.025181: Pseudo dice [0.8589] +2024-11-22 18:20:38.025869: Epoch time: 17.92 s +2024-11-22 18:20:38.960687: +2024-11-22 18:20:38.962483: Epoch 5701 +2024-11-22 18:20:38.962625: Current learning rate: 0.00326 +2024-11-22 18:20:58.732130: train_loss -0.8058 +2024-11-22 18:20:58.746518: val_loss -0.7764 +2024-11-22 18:20:58.746645: Pseudo dice [0.8564] +2024-11-22 18:20:58.746756: Epoch time: 19.77 s +2024-11-22 18:20:59.782609: +2024-11-22 18:20:59.784755: Epoch 5702 +2024-11-22 18:20:59.784919: Current learning rate: 0.00325 +2024-11-22 18:21:18.877204: train_loss -0.8039 +2024-11-22 18:21:18.890959: val_loss -0.7555 +2024-11-22 18:21:18.891168: Pseudo dice [0.8465] +2024-11-22 18:21:18.891285: Epoch time: 19.1 s +2024-11-22 18:21:19.928590: +2024-11-22 18:21:19.929152: Epoch 5703 +2024-11-22 18:21:19.929271: Current learning rate: 0.00325 +2024-11-22 18:21:39.542075: train_loss -0.7994 +2024-11-22 18:21:39.549759: val_loss -0.7692 +2024-11-22 18:21:39.549897: Pseudo dice [0.8355] +2024-11-22 18:21:39.549988: Epoch time: 19.61 s +2024-11-22 18:21:40.518333: +2024-11-22 18:21:40.520547: Epoch 5704 +2024-11-22 18:21:40.520672: Current learning rate: 0.00325 +2024-11-22 18:22:00.118223: train_loss -0.8067 +2024-11-22 18:22:00.130318: val_loss -0.7704 +2024-11-22 18:22:00.130487: Pseudo dice [0.8614] +2024-11-22 18:22:00.130603: Epoch time: 19.6 s +2024-11-22 18:22:01.206284: +2024-11-22 18:22:01.206795: Epoch 5705 +2024-11-22 18:22:01.206916: Current learning rate: 0.00325 +2024-11-22 18:22:20.595211: train_loss -0.7895 +2024-11-22 18:22:20.602287: val_loss -0.7774 +2024-11-22 18:22:20.602419: Pseudo dice [0.8454] +2024-11-22 18:22:20.602506: Epoch time: 19.39 s +2024-11-22 18:22:21.522758: +2024-11-22 18:22:21.524207: Epoch 5706 +2024-11-22 18:22:21.524345: Current learning rate: 0.00325 +2024-11-22 18:22:40.610289: train_loss -0.8078 +2024-11-22 18:22:40.629037: val_loss -0.7662 +2024-11-22 18:22:40.629164: Pseudo dice [0.8545] +2024-11-22 18:22:40.629259: Epoch time: 19.09 s +2024-11-22 18:22:41.647097: +2024-11-22 18:22:41.648146: Epoch 5707 +2024-11-22 18:22:41.648278: Current learning rate: 0.00325 +2024-11-22 18:23:01.317622: train_loss -0.8071 +2024-11-22 18:23:01.323786: val_loss -0.7949 +2024-11-22 18:23:01.323931: Pseudo dice [0.8591] +2024-11-22 18:23:01.324038: Epoch time: 19.67 s +2024-11-22 18:23:02.636350: +2024-11-22 18:23:02.637874: Epoch 5708 +2024-11-22 18:23:02.638019: Current learning rate: 0.00325 +2024-11-22 18:23:21.946146: train_loss -0.7938 +2024-11-22 18:23:21.952539: val_loss -0.7708 +2024-11-22 18:23:21.952648: Pseudo dice [0.8446] +2024-11-22 18:23:21.952741: Epoch time: 19.31 s +2024-11-22 18:23:22.964223: +2024-11-22 18:23:22.965551: Epoch 5709 +2024-11-22 18:23:22.965889: Current learning rate: 0.00325 +2024-11-22 18:23:41.695711: train_loss -0.7995 +2024-11-22 18:23:41.710089: val_loss -0.7577 +2024-11-22 18:23:41.710238: Pseudo dice [0.8473] +2024-11-22 18:23:41.710388: Epoch time: 18.73 s +2024-11-22 18:23:42.762548: +2024-11-22 18:23:42.763871: Epoch 5710 +2024-11-22 18:23:42.763995: Current learning rate: 0.00324 +2024-11-22 18:24:02.802282: train_loss -0.8017 +2024-11-22 18:24:02.805432: val_loss -0.7735 +2024-11-22 18:24:02.805568: Pseudo dice [0.862] +2024-11-22 18:24:02.805661: Epoch time: 20.04 s +2024-11-22 18:24:03.703020: +2024-11-22 18:24:03.703570: Epoch 5711 +2024-11-22 18:24:03.703700: Current learning rate: 0.00324 +2024-11-22 18:24:23.434551: train_loss -0.8101 +2024-11-22 18:24:23.450277: val_loss -0.7922 +2024-11-22 18:24:23.450420: Pseudo dice [0.8665] +2024-11-22 18:24:23.450519: Epoch time: 19.73 s +2024-11-22 18:24:24.521340: +2024-11-22 18:24:24.521982: Epoch 5712 +2024-11-22 18:24:24.522126: Current learning rate: 0.00324 +2024-11-22 18:24:44.281042: train_loss -0.8101 +2024-11-22 18:24:44.291219: val_loss -0.79 +2024-11-22 18:24:44.291336: Pseudo dice [0.8515] +2024-11-22 18:24:44.291425: Epoch time: 19.76 s +2024-11-22 18:24:45.218472: +2024-11-22 18:24:45.219254: Epoch 5713 +2024-11-22 18:24:45.219380: Current learning rate: 0.00324 +2024-11-22 18:25:04.150127: train_loss -0.8029 +2024-11-22 18:25:04.156729: val_loss -0.7939 +2024-11-22 18:25:04.156893: Pseudo dice [0.8631] +2024-11-22 18:25:04.156985: Epoch time: 18.93 s +2024-11-22 18:25:05.082519: +2024-11-22 18:25:05.084751: Epoch 5714 +2024-11-22 18:25:05.084881: Current learning rate: 0.00324 +2024-11-22 18:25:24.121355: train_loss -0.8079 +2024-11-22 18:25:24.130850: val_loss -0.7799 +2024-11-22 18:25:24.130996: Pseudo dice [0.8587] +2024-11-22 18:25:24.131099: Epoch time: 19.04 s +2024-11-22 18:25:25.019767: +2024-11-22 18:25:25.021013: Epoch 5715 +2024-11-22 18:25:25.021156: Current learning rate: 0.00324 +2024-11-22 18:25:43.944025: train_loss -0.8118 +2024-11-22 18:25:43.949119: val_loss -0.7752 +2024-11-22 18:25:43.949231: Pseudo dice [0.865] +2024-11-22 18:25:43.949355: Epoch time: 18.93 s +2024-11-22 18:25:44.966967: +2024-11-22 18:25:44.967195: Epoch 5716 +2024-11-22 18:25:44.967327: Current learning rate: 0.00324 +2024-11-22 18:26:05.172445: train_loss -0.8083 +2024-11-22 18:26:05.174788: val_loss -0.7749 +2024-11-22 18:26:05.174924: Pseudo dice [0.8493] +2024-11-22 18:26:05.175025: Epoch time: 20.21 s +2024-11-22 18:26:06.257241: +2024-11-22 18:26:06.258763: Epoch 5717 +2024-11-22 18:26:06.258910: Current learning rate: 0.00324 +2024-11-22 18:26:26.172202: train_loss -0.8088 +2024-11-22 18:26:26.177167: val_loss -0.7721 +2024-11-22 18:26:26.177305: Pseudo dice [0.8596] +2024-11-22 18:26:26.177425: Epoch time: 19.92 s +2024-11-22 18:26:27.235726: +2024-11-22 18:26:27.237272: Epoch 5718 +2024-11-22 18:26:27.237407: Current learning rate: 0.00323 +2024-11-22 18:26:46.962034: train_loss -0.8099 +2024-11-22 18:26:46.968752: val_loss -0.7628 +2024-11-22 18:26:46.968884: Pseudo dice [0.8441] +2024-11-22 18:26:46.968972: Epoch time: 19.73 s +2024-11-22 18:26:48.330304: +2024-11-22 18:26:48.330531: Epoch 5719 +2024-11-22 18:26:48.330662: Current learning rate: 0.00323 +2024-11-22 18:27:06.775285: train_loss -0.8085 +2024-11-22 18:27:06.780297: val_loss -0.7714 +2024-11-22 18:27:06.780442: Pseudo dice [0.8633] +2024-11-22 18:27:06.780548: Epoch time: 18.45 s +2024-11-22 18:27:07.703079: +2024-11-22 18:27:07.703278: Epoch 5720 +2024-11-22 18:27:07.703394: Current learning rate: 0.00323 +2024-11-22 18:27:26.500592: train_loss -0.8037 +2024-11-22 18:27:26.517509: val_loss -0.7841 +2024-11-22 18:27:26.517712: Pseudo dice [0.8535] +2024-11-22 18:27:26.517806: Epoch time: 18.8 s +2024-11-22 18:27:27.477328: +2024-11-22 18:27:27.477531: Epoch 5721 +2024-11-22 18:27:27.477650: Current learning rate: 0.00323 +2024-11-22 18:27:46.168891: train_loss -0.8085 +2024-11-22 18:27:46.169370: val_loss -0.7669 +2024-11-22 18:27:46.169472: Pseudo dice [0.85] +2024-11-22 18:27:46.169568: Epoch time: 18.69 s +2024-11-22 18:27:47.037565: +2024-11-22 18:27:47.037778: Epoch 5722 +2024-11-22 18:27:47.037910: Current learning rate: 0.00323 +2024-11-22 18:28:06.411962: train_loss -0.7974 +2024-11-22 18:28:06.423693: val_loss -0.7923 +2024-11-22 18:28:06.423852: Pseudo dice [0.8483] +2024-11-22 18:28:06.423959: Epoch time: 19.38 s +2024-11-22 18:28:07.413404: +2024-11-22 18:28:07.413644: Epoch 5723 +2024-11-22 18:28:07.413773: Current learning rate: 0.00323 +2024-11-22 18:28:25.635285: train_loss -0.7998 +2024-11-22 18:28:25.639775: val_loss -0.7849 +2024-11-22 18:28:25.639892: Pseudo dice [0.8625] +2024-11-22 18:28:25.639978: Epoch time: 18.22 s +2024-11-22 18:28:26.554076: +2024-11-22 18:28:26.554280: Epoch 5724 +2024-11-22 18:28:26.554402: Current learning rate: 0.00323 +2024-11-22 18:28:46.179913: train_loss -0.7918 +2024-11-22 18:28:46.183717: val_loss -0.7605 +2024-11-22 18:28:46.183908: Pseudo dice [0.8521] +2024-11-22 18:28:46.183998: Epoch time: 19.63 s +2024-11-22 18:28:47.148767: +2024-11-22 18:28:47.148991: Epoch 5725 +2024-11-22 18:28:47.149121: Current learning rate: 0.00322 +2024-11-22 18:29:06.574240: train_loss -0.7961 +2024-11-22 18:29:06.575076: val_loss -0.7726 +2024-11-22 18:29:06.575182: Pseudo dice [0.8546] +2024-11-22 18:29:06.575278: Epoch time: 19.43 s +2024-11-22 18:29:07.454800: +2024-11-22 18:29:07.454990: Epoch 5726 +2024-11-22 18:29:07.455109: Current learning rate: 0.00322 +2024-11-22 18:29:26.853826: train_loss -0.7941 +2024-11-22 18:29:26.856277: val_loss -0.79 +2024-11-22 18:29:26.856457: Pseudo dice [0.8516] +2024-11-22 18:29:26.856565: Epoch time: 19.4 s +2024-11-22 18:29:27.784187: +2024-11-22 18:29:27.784379: Epoch 5727 +2024-11-22 18:29:27.784490: Current learning rate: 0.00322 +2024-11-22 18:29:46.230741: train_loss -0.8011 +2024-11-22 18:29:46.233618: val_loss -0.7725 +2024-11-22 18:29:46.233758: Pseudo dice [0.8582] +2024-11-22 18:29:46.233846: Epoch time: 18.45 s +2024-11-22 18:29:47.385850: +2024-11-22 18:29:47.386063: Epoch 5728 +2024-11-22 18:29:47.386198: Current learning rate: 0.00322 +2024-11-22 18:30:05.018041: train_loss -0.7977 +2024-11-22 18:30:05.039892: val_loss -0.7585 +2024-11-22 18:30:05.040047: Pseudo dice [0.8522] +2024-11-22 18:30:05.040141: Epoch time: 17.63 s +2024-11-22 18:30:06.001428: +2024-11-22 18:30:06.001653: Epoch 5729 +2024-11-22 18:30:06.001767: Current learning rate: 0.00322 +2024-11-22 18:30:24.806369: train_loss -0.797 +2024-11-22 18:30:24.812851: val_loss -0.7836 +2024-11-22 18:30:24.813000: Pseudo dice [0.8608] +2024-11-22 18:30:24.813112: Epoch time: 18.81 s +2024-11-22 18:30:25.998557: +2024-11-22 18:30:25.998754: Epoch 5730 +2024-11-22 18:30:25.998871: Current learning rate: 0.00322 +2024-11-22 18:30:45.658900: train_loss -0.799 +2024-11-22 18:30:45.666456: val_loss -0.759 +2024-11-22 18:30:45.666607: Pseudo dice [0.8479] +2024-11-22 18:30:45.666703: Epoch time: 19.66 s +2024-11-22 18:30:46.561775: +2024-11-22 18:30:46.561979: Epoch 5731 +2024-11-22 18:30:46.562096: Current learning rate: 0.00322 +2024-11-22 18:31:06.221631: train_loss -0.7976 +2024-11-22 18:31:06.246046: val_loss -0.7494 +2024-11-22 18:31:06.246221: Pseudo dice [0.8494] +2024-11-22 18:31:06.246318: Epoch time: 19.66 s +2024-11-22 18:31:07.127517: +2024-11-22 18:31:07.128139: Epoch 5732 +2024-11-22 18:31:07.128261: Current learning rate: 0.00322 +2024-11-22 18:31:26.832335: train_loss -0.8057 +2024-11-22 18:31:26.837996: val_loss -0.7479 +2024-11-22 18:31:26.838143: Pseudo dice [0.8446] +2024-11-22 18:31:26.838234: Epoch time: 19.71 s +2024-11-22 18:31:27.742587: +2024-11-22 18:31:27.742774: Epoch 5733 +2024-11-22 18:31:27.742894: Current learning rate: 0.00321 +2024-11-22 18:31:46.030667: train_loss -0.8093 +2024-11-22 18:31:46.039704: val_loss -0.7873 +2024-11-22 18:31:46.039831: Pseudo dice [0.8608] +2024-11-22 18:31:46.039929: Epoch time: 18.29 s +2024-11-22 18:31:47.016930: +2024-11-22 18:31:47.017137: Epoch 5734 +2024-11-22 18:31:47.017520: Current learning rate: 0.00321 +2024-11-22 18:32:05.438602: train_loss -0.8036 +2024-11-22 18:32:05.447866: val_loss -0.7815 +2024-11-22 18:32:05.448231: Pseudo dice [0.8669] +2024-11-22 18:32:05.448332: Epoch time: 18.42 s +2024-11-22 18:32:06.340346: +2024-11-22 18:32:06.340581: Epoch 5735 +2024-11-22 18:32:06.340704: Current learning rate: 0.00321 +2024-11-22 18:32:25.037711: train_loss -0.8058 +2024-11-22 18:32:25.053417: val_loss -0.7563 +2024-11-22 18:32:25.053557: Pseudo dice [0.844] +2024-11-22 18:32:25.053650: Epoch time: 18.7 s +2024-11-22 18:32:26.018879: +2024-11-22 18:32:26.019107: Epoch 5736 +2024-11-22 18:32:26.019239: Current learning rate: 0.00321 +2024-11-22 18:32:45.625428: train_loss -0.8029 +2024-11-22 18:32:45.634631: val_loss -0.7693 +2024-11-22 18:32:45.634770: Pseudo dice [0.8499] +2024-11-22 18:32:45.634874: Epoch time: 19.61 s +2024-11-22 18:32:46.547433: +2024-11-22 18:32:46.547633: Epoch 5737 +2024-11-22 18:32:46.547754: Current learning rate: 0.00321 +2024-11-22 18:33:05.975521: train_loss -0.8113 +2024-11-22 18:33:05.994308: val_loss -0.766 +2024-11-22 18:33:05.994445: Pseudo dice [0.8502] +2024-11-22 18:33:05.994551: Epoch time: 19.43 s +2024-11-22 18:33:06.871223: +2024-11-22 18:33:06.871436: Epoch 5738 +2024-11-22 18:33:06.871583: Current learning rate: 0.00321 +2024-11-22 18:33:26.251638: train_loss -0.7978 +2024-11-22 18:33:26.260967: val_loss -0.7563 +2024-11-22 18:33:26.261125: Pseudo dice [0.8316] +2024-11-22 18:33:26.261231: Epoch time: 19.38 s +2024-11-22 18:33:27.234083: +2024-11-22 18:33:27.234286: Epoch 5739 +2024-11-22 18:33:27.234405: Current learning rate: 0.00321 +2024-11-22 18:33:47.459021: train_loss -0.7856 +2024-11-22 18:33:47.462828: val_loss -0.7667 +2024-11-22 18:33:47.462966: Pseudo dice [0.8499] +2024-11-22 18:33:47.463069: Epoch time: 20.23 s +2024-11-22 18:33:48.484086: +2024-11-22 18:33:48.484286: Epoch 5740 +2024-11-22 18:33:48.484401: Current learning rate: 0.00321 +2024-11-22 18:34:07.162522: train_loss -0.8027 +2024-11-22 18:34:07.170291: val_loss -0.794 +2024-11-22 18:34:07.170425: Pseudo dice [0.8556] +2024-11-22 18:34:07.170517: Epoch time: 18.68 s +2024-11-22 18:34:08.614748: +2024-11-22 18:34:08.614959: Epoch 5741 +2024-11-22 18:34:08.615105: Current learning rate: 0.0032 +2024-11-22 18:34:27.834534: train_loss -0.8074 +2024-11-22 18:34:27.840140: val_loss -0.7716 +2024-11-22 18:34:27.840259: Pseudo dice [0.8577] +2024-11-22 18:34:27.840353: Epoch time: 19.22 s +2024-11-22 18:34:28.747581: +2024-11-22 18:34:28.747781: Epoch 5742 +2024-11-22 18:34:28.747899: Current learning rate: 0.0032 +2024-11-22 18:34:48.129847: train_loss -0.8014 +2024-11-22 18:34:48.133047: val_loss -0.7894 +2024-11-22 18:34:48.133248: Pseudo dice [0.8539] +2024-11-22 18:34:48.133351: Epoch time: 19.38 s +2024-11-22 18:34:49.020111: +2024-11-22 18:34:49.020359: Epoch 5743 +2024-11-22 18:34:49.020485: Current learning rate: 0.0032 +2024-11-22 18:35:08.747739: train_loss -0.7953 +2024-11-22 18:35:08.766646: val_loss -0.7839 +2024-11-22 18:35:08.766808: Pseudo dice [0.8574] +2024-11-22 18:35:08.766906: Epoch time: 19.73 s +2024-11-22 18:35:09.706774: +2024-11-22 18:35:09.706983: Epoch 5744 +2024-11-22 18:35:09.707105: Current learning rate: 0.0032 +2024-11-22 18:35:28.187444: train_loss -0.8054 +2024-11-22 18:35:28.195650: val_loss -0.7603 +2024-11-22 18:35:28.195795: Pseudo dice [0.8531] +2024-11-22 18:35:28.195894: Epoch time: 18.48 s +2024-11-22 18:35:29.348654: +2024-11-22 18:35:29.348919: Epoch 5745 +2024-11-22 18:35:29.349083: Current learning rate: 0.0032 +2024-11-22 18:35:48.745816: train_loss -0.8001 +2024-11-22 18:35:48.763259: val_loss -0.7786 +2024-11-22 18:35:48.763420: Pseudo dice [0.8683] +2024-11-22 18:35:48.763511: Epoch time: 19.4 s +2024-11-22 18:35:49.837643: +2024-11-22 18:35:49.837858: Epoch 5746 +2024-11-22 18:35:49.837984: Current learning rate: 0.0032 +2024-11-22 18:36:09.716812: train_loss -0.7965 +2024-11-22 18:36:09.725651: val_loss -0.7345 +2024-11-22 18:36:09.725794: Pseudo dice [0.823] +2024-11-22 18:36:09.725876: Epoch time: 19.88 s +2024-11-22 18:36:10.766365: +2024-11-22 18:36:10.766582: Epoch 5747 +2024-11-22 18:36:10.766724: Current learning rate: 0.0032 +2024-11-22 18:36:30.337814: train_loss -0.7819 +2024-11-22 18:36:30.367913: val_loss -0.7728 +2024-11-22 18:36:30.368070: Pseudo dice [0.8529] +2024-11-22 18:36:30.368157: Epoch time: 19.57 s +2024-11-22 18:36:31.331570: +2024-11-22 18:36:31.331778: Epoch 5748 +2024-11-22 18:36:31.331894: Current learning rate: 0.0032 +2024-11-22 18:36:50.152351: train_loss -0.7978 +2024-11-22 18:36:50.174261: val_loss -0.7736 +2024-11-22 18:36:50.174423: Pseudo dice [0.8436] +2024-11-22 18:36:50.174525: Epoch time: 18.82 s +2024-11-22 18:36:51.067264: +2024-11-22 18:36:51.067467: Epoch 5749 +2024-11-22 18:36:51.067604: Current learning rate: 0.00319 +2024-11-22 18:37:10.566464: train_loss -0.8008 +2024-11-22 18:37:10.570993: val_loss -0.7854 +2024-11-22 18:37:10.571152: Pseudo dice [0.8295] +2024-11-22 18:37:10.571248: Epoch time: 19.5 s +2024-11-22 18:37:11.748932: +2024-11-22 18:37:11.749533: Epoch 5750 +2024-11-22 18:37:11.749661: Current learning rate: 0.00319 +2024-11-22 18:37:31.162463: train_loss -0.801 +2024-11-22 18:37:31.175072: val_loss -0.7602 +2024-11-22 18:37:31.175226: Pseudo dice [0.857] +2024-11-22 18:37:31.175323: Epoch time: 19.41 s +2024-11-22 18:37:32.051870: +2024-11-22 18:37:32.052084: Epoch 5751 +2024-11-22 18:37:32.052204: Current learning rate: 0.00319 +2024-11-22 18:37:50.290033: train_loss -0.7894 +2024-11-22 18:37:50.297468: val_loss -0.7763 +2024-11-22 18:37:50.297609: Pseudo dice [0.8425] +2024-11-22 18:37:50.297710: Epoch time: 18.24 s +2024-11-22 18:37:51.712263: +2024-11-22 18:37:51.712471: Epoch 5752 +2024-11-22 18:37:51.712596: Current learning rate: 0.00319 +2024-11-22 18:38:10.174619: train_loss -0.7928 +2024-11-22 18:38:10.205298: val_loss -0.7814 +2024-11-22 18:38:10.205473: Pseudo dice [0.8636] +2024-11-22 18:38:10.205581: Epoch time: 18.46 s +2024-11-22 18:38:11.167555: +2024-11-22 18:38:11.167751: Epoch 5753 +2024-11-22 18:38:11.167866: Current learning rate: 0.00319 +2024-11-22 18:38:29.416203: train_loss -0.7993 +2024-11-22 18:38:29.433027: val_loss -0.78 +2024-11-22 18:38:29.433234: Pseudo dice [0.8573] +2024-11-22 18:38:29.433318: Epoch time: 18.25 s +2024-11-22 18:38:30.661898: +2024-11-22 18:38:30.662163: Epoch 5754 +2024-11-22 18:38:30.662287: Current learning rate: 0.00319 +2024-11-22 18:38:49.391799: train_loss -0.7885 +2024-11-22 18:38:49.418841: val_loss -0.7611 +2024-11-22 18:38:49.419001: Pseudo dice [0.8491] +2024-11-22 18:38:49.419093: Epoch time: 18.73 s +2024-11-22 18:38:50.308799: +2024-11-22 18:38:50.309019: Epoch 5755 +2024-11-22 18:38:50.309156: Current learning rate: 0.00319 +2024-11-22 18:39:10.094278: train_loss -0.7938 +2024-11-22 18:39:10.129454: val_loss -0.7798 +2024-11-22 18:39:10.129593: Pseudo dice [0.8534] +2024-11-22 18:39:10.129679: Epoch time: 19.79 s +2024-11-22 18:39:11.011047: +2024-11-22 18:39:11.011262: Epoch 5756 +2024-11-22 18:39:11.011386: Current learning rate: 0.00319 +2024-11-22 18:39:30.995457: train_loss -0.7989 +2024-11-22 18:39:31.039999: val_loss -0.7592 +2024-11-22 18:39:31.040170: Pseudo dice [0.8511] +2024-11-22 18:39:31.040273: Epoch time: 19.99 s +2024-11-22 18:39:32.026574: +2024-11-22 18:39:32.026774: Epoch 5757 +2024-11-22 18:39:32.026897: Current learning rate: 0.00318 +2024-11-22 18:39:51.856734: train_loss -0.7955 +2024-11-22 18:39:51.860699: val_loss -0.8 +2024-11-22 18:39:51.860826: Pseudo dice [0.8532] +2024-11-22 18:39:51.860919: Epoch time: 19.83 s +2024-11-22 18:39:52.785037: +2024-11-22 18:39:52.785297: Epoch 5758 +2024-11-22 18:39:52.785441: Current learning rate: 0.00318 +2024-11-22 18:40:12.501616: train_loss -0.7933 +2024-11-22 18:40:12.505985: val_loss -0.7532 +2024-11-22 18:40:12.506109: Pseudo dice [0.8631] +2024-11-22 18:40:12.506192: Epoch time: 19.72 s +2024-11-22 18:40:13.398739: +2024-11-22 18:40:13.398943: Epoch 5759 +2024-11-22 18:40:13.399078: Current learning rate: 0.00318 +2024-11-22 18:40:31.820621: train_loss -0.7962 +2024-11-22 18:40:31.827976: val_loss -0.7854 +2024-11-22 18:40:31.828107: Pseudo dice [0.8588] +2024-11-22 18:40:31.828200: Epoch time: 18.42 s +2024-11-22 18:40:32.995263: +2024-11-22 18:40:32.996015: Epoch 5760 +2024-11-22 18:40:32.996379: Current learning rate: 0.00318 +2024-11-22 18:40:52.795669: train_loss -0.7977 +2024-11-22 18:40:52.798535: val_loss -0.775 +2024-11-22 18:40:52.798713: Pseudo dice [0.8622] +2024-11-22 18:40:52.798815: Epoch time: 19.8 s +2024-11-22 18:40:53.709362: +2024-11-22 18:40:53.709578: Epoch 5761 +2024-11-22 18:40:53.709713: Current learning rate: 0.00318 +2024-11-22 18:41:12.963667: train_loss -0.7967 +2024-11-22 18:41:12.976656: val_loss -0.7891 +2024-11-22 18:41:12.976846: Pseudo dice [0.8587] +2024-11-22 18:41:12.976944: Epoch time: 19.26 s +2024-11-22 18:41:13.946216: +2024-11-22 18:41:13.946412: Epoch 5762 +2024-11-22 18:41:13.946530: Current learning rate: 0.00318 +2024-11-22 18:41:33.946480: train_loss -0.7979 +2024-11-22 18:41:33.962170: val_loss -0.7722 +2024-11-22 18:41:33.962350: Pseudo dice [0.8576] +2024-11-22 18:41:33.962459: Epoch time: 20.0 s +2024-11-22 18:41:35.318555: +2024-11-22 18:41:35.318759: Epoch 5763 +2024-11-22 18:41:35.318883: Current learning rate: 0.00318 +2024-11-22 18:41:53.862107: train_loss -0.8051 +2024-11-22 18:41:53.889709: val_loss -0.7556 +2024-11-22 18:41:53.889895: Pseudo dice [0.8606] +2024-11-22 18:41:53.889994: Epoch time: 18.54 s +2024-11-22 18:41:54.820268: +2024-11-22 18:41:54.820472: Epoch 5764 +2024-11-22 18:41:54.820601: Current learning rate: 0.00317 +2024-11-22 18:42:14.638240: train_loss -0.8094 +2024-11-22 18:42:14.645419: val_loss -0.7648 +2024-11-22 18:42:14.645542: Pseudo dice [0.8568] +2024-11-22 18:42:14.645622: Epoch time: 19.82 s +2024-11-22 18:42:15.521099: +2024-11-22 18:42:15.521287: Epoch 5765 +2024-11-22 18:42:15.521400: Current learning rate: 0.00317 +2024-11-22 18:42:34.749212: train_loss -0.8 +2024-11-22 18:42:34.769434: val_loss -0.8008 +2024-11-22 18:42:34.769579: Pseudo dice [0.8554] +2024-11-22 18:42:34.769662: Epoch time: 19.23 s +2024-11-22 18:42:35.653630: +2024-11-22 18:42:35.653868: Epoch 5766 +2024-11-22 18:42:35.653988: Current learning rate: 0.00317 +2024-11-22 18:42:54.582215: train_loss -0.8124 +2024-11-22 18:42:54.596970: val_loss -0.7712 +2024-11-22 18:42:54.597124: Pseudo dice [0.8537] +2024-11-22 18:42:54.597211: Epoch time: 18.93 s +2024-11-22 18:42:55.531475: +2024-11-22 18:42:55.531719: Epoch 5767 +2024-11-22 18:42:55.531842: Current learning rate: 0.00317 +2024-11-22 18:43:15.779757: train_loss -0.7896 +2024-11-22 18:43:15.789292: val_loss -0.7634 +2024-11-22 18:43:15.789453: Pseudo dice [0.8476] +2024-11-22 18:43:15.789570: Epoch time: 20.25 s +2024-11-22 18:43:16.761235: +2024-11-22 18:43:16.761450: Epoch 5768 +2024-11-22 18:43:16.761584: Current learning rate: 0.00317 +2024-11-22 18:43:36.541216: train_loss -0.8003 +2024-11-22 18:43:36.545350: val_loss -0.7574 +2024-11-22 18:43:36.545477: Pseudo dice [0.8514] +2024-11-22 18:43:36.545565: Epoch time: 19.78 s +2024-11-22 18:43:37.451437: +2024-11-22 18:43:37.451642: Epoch 5769 +2024-11-22 18:43:37.451764: Current learning rate: 0.00317 +2024-11-22 18:43:55.306658: train_loss -0.7972 +2024-11-22 18:43:55.312230: val_loss -0.7562 +2024-11-22 18:43:55.312343: Pseudo dice [0.8475] +2024-11-22 18:43:55.312430: Epoch time: 17.86 s +2024-11-22 18:43:56.210975: +2024-11-22 18:43:56.211184: Epoch 5770 +2024-11-22 18:43:56.211304: Current learning rate: 0.00317 +2024-11-22 18:44:16.143622: train_loss -0.7908 +2024-11-22 18:44:16.150959: val_loss -0.7769 +2024-11-22 18:44:16.151101: Pseudo dice [0.8543] +2024-11-22 18:44:16.151204: Epoch time: 19.93 s +2024-11-22 18:44:17.054869: +2024-11-22 18:44:17.055088: Epoch 5771 +2024-11-22 18:44:17.055215: Current learning rate: 0.00317 +2024-11-22 18:44:37.012463: train_loss -0.7941 +2024-11-22 18:44:37.050225: val_loss -0.7798 +2024-11-22 18:44:37.050380: Pseudo dice [0.8499] +2024-11-22 18:44:37.050474: Epoch time: 19.96 s +2024-11-22 18:44:37.948768: +2024-11-22 18:44:37.948976: Epoch 5772 +2024-11-22 18:44:37.949115: Current learning rate: 0.00316 +2024-11-22 18:44:57.398237: train_loss -0.8034 +2024-11-22 18:44:57.419259: val_loss -0.7601 +2024-11-22 18:44:57.419666: Pseudo dice [0.8506] +2024-11-22 18:44:57.419775: Epoch time: 19.45 s +2024-11-22 18:44:58.624660: +2024-11-22 18:44:58.624872: Epoch 5773 +2024-11-22 18:44:58.624995: Current learning rate: 0.00316 +2024-11-22 18:45:17.894341: train_loss -0.8005 +2024-11-22 18:45:17.903525: val_loss -0.7624 +2024-11-22 18:45:17.903656: Pseudo dice [0.8532] +2024-11-22 18:45:17.903744: Epoch time: 19.27 s +2024-11-22 18:45:19.218240: +2024-11-22 18:45:19.218438: Epoch 5774 +2024-11-22 18:45:19.218552: Current learning rate: 0.00316 +2024-11-22 18:45:38.218364: train_loss -0.8148 +2024-11-22 18:45:38.240699: val_loss -0.7665 +2024-11-22 18:45:38.240869: Pseudo dice [0.8618] +2024-11-22 18:45:38.240986: Epoch time: 19.0 s +2024-11-22 18:45:39.269229: +2024-11-22 18:45:39.269457: Epoch 5775 +2024-11-22 18:45:39.269596: Current learning rate: 0.00316 +2024-11-22 18:45:59.473407: train_loss -0.7941 +2024-11-22 18:45:59.479069: val_loss -0.7781 +2024-11-22 18:45:59.479205: Pseudo dice [0.8377] +2024-11-22 18:45:59.479291: Epoch time: 20.21 s +2024-11-22 18:46:00.394526: +2024-11-22 18:46:00.394740: Epoch 5776 +2024-11-22 18:46:00.394859: Current learning rate: 0.00316 +2024-11-22 18:46:19.458283: train_loss -0.8023 +2024-11-22 18:46:19.486905: val_loss -0.7656 +2024-11-22 18:46:19.487069: Pseudo dice [0.8525] +2024-11-22 18:46:19.487178: Epoch time: 19.06 s +2024-11-22 18:46:20.366735: +2024-11-22 18:46:20.366952: Epoch 5777 +2024-11-22 18:46:20.367081: Current learning rate: 0.00316 +2024-11-22 18:46:39.071353: train_loss -0.8028 +2024-11-22 18:46:39.077185: val_loss -0.757 +2024-11-22 18:46:39.077333: Pseudo dice [0.8478] +2024-11-22 18:46:39.077447: Epoch time: 18.71 s +2024-11-22 18:46:39.980053: +2024-11-22 18:46:39.980268: Epoch 5778 +2024-11-22 18:46:39.980398: Current learning rate: 0.00316 +2024-11-22 18:46:58.891553: train_loss -0.7994 +2024-11-22 18:46:58.895234: val_loss -0.7614 +2024-11-22 18:46:58.895325: Pseudo dice [0.8471] +2024-11-22 18:46:58.895410: Epoch time: 18.91 s +2024-11-22 18:46:59.779633: +2024-11-22 18:46:59.779842: Epoch 5779 +2024-11-22 18:46:59.779960: Current learning rate: 0.00316 +2024-11-22 18:47:18.992806: train_loss -0.7961 +2024-11-22 18:47:19.019539: val_loss -0.7911 +2024-11-22 18:47:19.019686: Pseudo dice [0.8599] +2024-11-22 18:47:19.019790: Epoch time: 19.21 s +2024-11-22 18:47:20.063776: +2024-11-22 18:47:20.063991: Epoch 5780 +2024-11-22 18:47:20.064135: Current learning rate: 0.00315 +2024-11-22 18:47:38.929246: train_loss -0.8041 +2024-11-22 18:47:38.942925: val_loss -0.7897 +2024-11-22 18:47:38.949144: Pseudo dice [0.8506] +2024-11-22 18:47:38.949257: Epoch time: 18.87 s +2024-11-22 18:47:40.025148: +2024-11-22 18:47:40.025373: Epoch 5781 +2024-11-22 18:47:40.025492: Current learning rate: 0.00315 +2024-11-22 18:47:58.658110: train_loss -0.8015 +2024-11-22 18:47:58.674582: val_loss -0.7924 +2024-11-22 18:47:58.674727: Pseudo dice [0.8487] +2024-11-22 18:47:58.674854: Epoch time: 18.63 s +2024-11-22 18:47:59.690881: +2024-11-22 18:47:59.691095: Epoch 5782 +2024-11-22 18:47:59.691219: Current learning rate: 0.00315 +2024-11-22 18:48:19.309803: train_loss -0.8044 +2024-11-22 18:48:19.326855: val_loss -0.7625 +2024-11-22 18:48:19.327013: Pseudo dice [0.8532] +2024-11-22 18:48:19.327104: Epoch time: 19.62 s +2024-11-22 18:48:20.299909: +2024-11-22 18:48:20.300122: Epoch 5783 +2024-11-22 18:48:20.300225: Current learning rate: 0.00315 +2024-11-22 18:48:41.079400: train_loss -0.8045 +2024-11-22 18:48:41.081377: val_loss -0.7593 +2024-11-22 18:48:41.081475: Pseudo dice [0.8682] +2024-11-22 18:48:41.081579: Epoch time: 20.78 s +2024-11-22 18:48:42.031274: +2024-11-22 18:48:42.039346: Epoch 5784 +2024-11-22 18:48:42.039496: Current learning rate: 0.00315 +2024-11-22 18:49:00.981004: train_loss -0.8052 +2024-11-22 18:49:00.996500: val_loss -0.7733 +2024-11-22 18:49:00.996643: Pseudo dice [0.8446] +2024-11-22 18:49:00.996733: Epoch time: 18.95 s +2024-11-22 18:49:02.387416: +2024-11-22 18:49:02.387636: Epoch 5785 +2024-11-22 18:49:02.387757: Current learning rate: 0.00315 +2024-11-22 18:49:21.420747: train_loss -0.8104 +2024-11-22 18:49:21.450321: val_loss -0.7689 +2024-11-22 18:49:21.450481: Pseudo dice [0.8586] +2024-11-22 18:49:21.450584: Epoch time: 19.03 s +2024-11-22 18:49:22.365138: +2024-11-22 18:49:22.365809: Epoch 5786 +2024-11-22 18:49:22.365998: Current learning rate: 0.00315 +2024-11-22 18:49:40.942855: train_loss -0.8068 +2024-11-22 18:49:40.945302: val_loss -0.786 +2024-11-22 18:49:40.945395: Pseudo dice [0.8679] +2024-11-22 18:49:40.945488: Epoch time: 18.58 s +2024-11-22 18:49:41.818682: +2024-11-22 18:49:41.818865: Epoch 5787 +2024-11-22 18:49:41.818981: Current learning rate: 0.00315 +2024-11-22 18:50:01.381626: train_loss -0.8039 +2024-11-22 18:50:01.411794: val_loss -0.769 +2024-11-22 18:50:01.412090: Pseudo dice [0.8484] +2024-11-22 18:50:01.412235: Epoch time: 19.56 s +2024-11-22 18:50:02.400807: +2024-11-22 18:50:02.401023: Epoch 5788 +2024-11-22 18:50:02.401146: Current learning rate: 0.00314 +2024-11-22 18:50:21.955773: train_loss -0.8038 +2024-11-22 18:50:21.967587: val_loss -0.7687 +2024-11-22 18:50:21.967753: Pseudo dice [0.8545] +2024-11-22 18:50:21.967864: Epoch time: 19.56 s +2024-11-22 18:50:23.101532: +2024-11-22 18:50:23.101738: Epoch 5789 +2024-11-22 18:50:23.101860: Current learning rate: 0.00314 +2024-11-22 18:50:42.698036: train_loss -0.8097 +2024-11-22 18:50:42.705517: val_loss -0.7806 +2024-11-22 18:50:42.705642: Pseudo dice [0.856] +2024-11-22 18:50:42.705739: Epoch time: 19.6 s +2024-11-22 18:50:43.617370: +2024-11-22 18:50:43.617566: Epoch 5790 +2024-11-22 18:50:43.617682: Current learning rate: 0.00314 +2024-11-22 18:51:03.393123: train_loss -0.7974 +2024-11-22 18:51:03.396029: val_loss -0.7517 +2024-11-22 18:51:03.396196: Pseudo dice [0.8494] +2024-11-22 18:51:03.396297: Epoch time: 19.78 s +2024-11-22 18:51:04.275288: +2024-11-22 18:51:04.275494: Epoch 5791 +2024-11-22 18:51:04.275619: Current learning rate: 0.00314 +2024-11-22 18:51:23.276674: train_loss -0.7939 +2024-11-22 18:51:23.279810: val_loss -0.7644 +2024-11-22 18:51:23.279934: Pseudo dice [0.854] +2024-11-22 18:51:23.280021: Epoch time: 19.0 s +2024-11-22 18:51:24.242152: +2024-11-22 18:51:24.242353: Epoch 5792 +2024-11-22 18:51:24.242483: Current learning rate: 0.00314 +2024-11-22 18:51:43.916439: train_loss -0.7909 +2024-11-22 18:51:43.946722: val_loss -0.7836 +2024-11-22 18:51:43.946866: Pseudo dice [0.8581] +2024-11-22 18:51:43.946971: Epoch time: 19.68 s +2024-11-22 18:51:44.831191: +2024-11-22 18:51:44.831393: Epoch 5793 +2024-11-22 18:51:44.831519: Current learning rate: 0.00314 +2024-11-22 18:52:04.008731: train_loss -0.7976 +2024-11-22 18:52:04.015365: val_loss -0.7974 +2024-11-22 18:52:04.015545: Pseudo dice [0.8577] +2024-11-22 18:52:04.015633: Epoch time: 19.18 s +2024-11-22 18:52:04.907524: +2024-11-22 18:52:04.907720: Epoch 5794 +2024-11-22 18:52:04.907829: Current learning rate: 0.00314 +2024-11-22 18:52:23.881735: train_loss -0.8061 +2024-11-22 18:52:23.921859: val_loss -0.7837 +2024-11-22 18:52:23.922037: Pseudo dice [0.8596] +2024-11-22 18:52:23.922156: Epoch time: 18.98 s +2024-11-22 18:52:24.915276: +2024-11-22 18:52:24.915494: Epoch 5795 +2024-11-22 18:52:24.915618: Current learning rate: 0.00314 +2024-11-22 18:52:43.862648: train_loss -0.8024 +2024-11-22 18:52:43.869267: val_loss -0.7774 +2024-11-22 18:52:43.869407: Pseudo dice [0.8618] +2024-11-22 18:52:43.869574: Epoch time: 18.95 s +2024-11-22 18:52:45.167645: +2024-11-22 18:52:45.168245: Epoch 5796 +2024-11-22 18:52:45.168362: Current learning rate: 0.00313 +2024-11-22 18:53:04.979501: train_loss -0.8027 +2024-11-22 18:53:04.986098: val_loss -0.7862 +2024-11-22 18:53:04.986228: Pseudo dice [0.856] +2024-11-22 18:53:04.986318: Epoch time: 19.81 s +2024-11-22 18:53:05.953469: +2024-11-22 18:53:05.953678: Epoch 5797 +2024-11-22 18:53:05.953810: Current learning rate: 0.00313 +2024-11-22 18:53:26.262212: train_loss -0.803 +2024-11-22 18:53:26.264952: val_loss -0.7861 +2024-11-22 18:53:26.265066: Pseudo dice [0.8674] +2024-11-22 18:53:26.265156: Epoch time: 20.31 s +2024-11-22 18:53:27.141739: +2024-11-22 18:53:27.142182: Epoch 5798 +2024-11-22 18:53:27.142304: Current learning rate: 0.00313 +2024-11-22 18:53:46.078925: train_loss -0.8081 +2024-11-22 18:53:46.086216: val_loss -0.7915 +2024-11-22 18:53:46.086446: Pseudo dice [0.8549] +2024-11-22 18:53:46.086542: Epoch time: 18.94 s +2024-11-22 18:53:47.090091: +2024-11-22 18:53:47.090312: Epoch 5799 +2024-11-22 18:53:47.090441: Current learning rate: 0.00313 +2024-11-22 18:54:05.999532: train_loss -0.8049 +2024-11-22 18:54:06.037585: val_loss -0.7421 +2024-11-22 18:54:06.037736: Pseudo dice [0.8441] +2024-11-22 18:54:06.037836: Epoch time: 18.91 s +2024-11-22 18:54:07.341945: +2024-11-22 18:54:07.342179: Epoch 5800 +2024-11-22 18:54:07.342296: Current learning rate: 0.00313 +2024-11-22 18:54:26.984814: train_loss -0.8044 +2024-11-22 18:54:26.987550: val_loss -0.7639 +2024-11-22 18:54:26.987659: Pseudo dice [0.8463] +2024-11-22 18:54:26.987751: Epoch time: 19.64 s +2024-11-22 18:54:27.892978: +2024-11-22 18:54:27.893196: Epoch 5801 +2024-11-22 18:54:27.893338: Current learning rate: 0.00313 +2024-11-22 18:54:48.120770: train_loss -0.8035 +2024-11-22 18:54:48.123213: val_loss -0.7831 +2024-11-22 18:54:48.123306: Pseudo dice [0.8572] +2024-11-22 18:54:48.123386: Epoch time: 20.23 s +2024-11-22 18:54:49.000410: +2024-11-22 18:54:49.000999: Epoch 5802 +2024-11-22 18:54:49.001129: Current learning rate: 0.00313 +2024-11-22 18:55:08.566703: train_loss -0.8038 +2024-11-22 18:55:08.573132: val_loss -0.7712 +2024-11-22 18:55:08.573263: Pseudo dice [0.8339] +2024-11-22 18:55:08.573433: Epoch time: 19.57 s +2024-11-22 18:55:09.644131: +2024-11-22 18:55:09.644359: Epoch 5803 +2024-11-22 18:55:09.644492: Current learning rate: 0.00313 +2024-11-22 18:55:28.211923: train_loss -0.8018 +2024-11-22 18:55:28.219778: val_loss -0.7787 +2024-11-22 18:55:28.219910: Pseudo dice [0.8616] +2024-11-22 18:55:28.220010: Epoch time: 18.57 s +2024-11-22 18:55:29.237563: +2024-11-22 18:55:29.238164: Epoch 5804 +2024-11-22 18:55:29.238287: Current learning rate: 0.00312 +2024-11-22 18:55:48.467460: train_loss -0.8058 +2024-11-22 18:55:48.472955: val_loss -0.779 +2024-11-22 18:55:48.473082: Pseudo dice [0.8561] +2024-11-22 18:55:48.473190: Epoch time: 19.23 s +2024-11-22 18:55:49.385966: +2024-11-22 18:55:49.387297: Epoch 5805 +2024-11-22 18:55:49.387445: Current learning rate: 0.00312 +2024-11-22 18:56:08.836609: train_loss -0.8062 +2024-11-22 18:56:08.845088: val_loss -0.7571 +2024-11-22 18:56:08.845286: Pseudo dice [0.8457] +2024-11-22 18:56:08.845395: Epoch time: 19.45 s +2024-11-22 18:56:09.732522: +2024-11-22 18:56:09.732734: Epoch 5806 +2024-11-22 18:56:09.732860: Current learning rate: 0.00312 +2024-11-22 18:56:28.937311: train_loss -0.7994 +2024-11-22 18:56:28.940984: val_loss -0.777 +2024-11-22 18:56:28.941111: Pseudo dice [0.8481] +2024-11-22 18:56:28.941216: Epoch time: 19.21 s +2024-11-22 18:56:30.434433: +2024-11-22 18:56:30.435941: Epoch 5807 +2024-11-22 18:56:30.436088: Current learning rate: 0.00312 +2024-11-22 18:56:50.535113: train_loss -0.7884 +2024-11-22 18:56:50.543354: val_loss -0.7824 +2024-11-22 18:56:50.543496: Pseudo dice [0.8552] +2024-11-22 18:56:50.543625: Epoch time: 20.1 s +2024-11-22 18:56:51.592025: +2024-11-22 18:56:51.593355: Epoch 5808 +2024-11-22 18:56:51.593496: Current learning rate: 0.00312 +2024-11-22 18:57:10.525620: train_loss -0.7909 +2024-11-22 18:57:10.527734: val_loss -0.7941 +2024-11-22 18:57:10.527873: Pseudo dice [0.8564] +2024-11-22 18:57:10.527968: Epoch time: 18.93 s +2024-11-22 18:57:11.411133: +2024-11-22 18:57:11.411751: Epoch 5809 +2024-11-22 18:57:11.411871: Current learning rate: 0.00312 +2024-11-22 18:57:31.141352: train_loss -0.7957 +2024-11-22 18:57:31.146309: val_loss -0.7815 +2024-11-22 18:57:31.146443: Pseudo dice [0.8572] +2024-11-22 18:57:31.146537: Epoch time: 19.73 s +2024-11-22 18:57:32.226449: +2024-11-22 18:57:32.226703: Epoch 5810 +2024-11-22 18:57:32.226829: Current learning rate: 0.00312 +2024-11-22 18:57:52.293639: train_loss -0.8053 +2024-11-22 18:57:52.307094: val_loss -0.7834 +2024-11-22 18:57:52.307824: Pseudo dice [0.8546] +2024-11-22 18:57:52.309010: Epoch time: 20.07 s +2024-11-22 18:57:53.247133: +2024-11-22 18:57:53.247866: Epoch 5811 +2024-11-22 18:57:53.247991: Current learning rate: 0.00311 +2024-11-22 18:58:12.514543: train_loss -0.8011 +2024-11-22 18:58:12.527705: val_loss -0.7886 +2024-11-22 18:58:12.527857: Pseudo dice [0.861] +2024-11-22 18:58:12.527945: Epoch time: 19.27 s +2024-11-22 18:58:13.574245: +2024-11-22 18:58:13.575037: Epoch 5812 +2024-11-22 18:58:13.575166: Current learning rate: 0.00311 +2024-11-22 18:58:33.711309: train_loss -0.7985 +2024-11-22 18:58:33.713781: val_loss -0.7823 +2024-11-22 18:58:33.713945: Pseudo dice [0.8609] +2024-11-22 18:58:33.714055: Epoch time: 20.14 s +2024-11-22 18:58:34.601416: +2024-11-22 18:58:34.601634: Epoch 5813 +2024-11-22 18:58:34.601765: Current learning rate: 0.00311 +2024-11-22 18:58:54.392621: train_loss -0.7989 +2024-11-22 18:58:54.424193: val_loss -0.7907 +2024-11-22 18:58:54.424376: Pseudo dice [0.8549] +2024-11-22 18:58:54.424491: Epoch time: 19.79 s +2024-11-22 18:58:55.498154: +2024-11-22 18:58:55.499410: Epoch 5814 +2024-11-22 18:58:55.499560: Current learning rate: 0.00311 +2024-11-22 18:59:14.884129: train_loss -0.7981 +2024-11-22 18:59:14.895329: val_loss -0.7672 +2024-11-22 18:59:14.895478: Pseudo dice [0.8644] +2024-11-22 18:59:14.895582: Epoch time: 19.39 s +2024-11-22 18:59:15.990082: +2024-11-22 18:59:15.991216: Epoch 5815 +2024-11-22 18:59:15.991340: Current learning rate: 0.00311 +2024-11-22 18:59:35.560146: train_loss -0.8026 +2024-11-22 18:59:35.567055: val_loss -0.792 +2024-11-22 18:59:35.567279: Pseudo dice [0.8524] +2024-11-22 18:59:35.567392: Epoch time: 19.57 s +2024-11-22 18:59:36.528973: +2024-11-22 18:59:36.529729: Epoch 5816 +2024-11-22 18:59:36.529860: Current learning rate: 0.00311 +2024-11-22 18:59:56.130010: train_loss -0.7916 +2024-11-22 18:59:56.161618: val_loss -0.7892 +2024-11-22 18:59:56.161759: Pseudo dice [0.8614] +2024-11-22 18:59:56.161863: Epoch time: 19.6 s +2024-11-22 18:59:57.062145: +2024-11-22 18:59:57.064337: Epoch 5817 +2024-11-22 18:59:57.064466: Current learning rate: 0.00311 +2024-11-22 19:00:16.095897: train_loss -0.7964 +2024-11-22 19:00:16.101450: val_loss -0.7892 +2024-11-22 19:00:16.101720: Pseudo dice [0.8561] +2024-11-22 19:00:16.101825: Epoch time: 19.03 s +2024-11-22 19:00:17.437440: +2024-11-22 19:00:17.439244: Epoch 5818 +2024-11-22 19:00:17.439369: Current learning rate: 0.00311 +2024-11-22 19:00:35.763135: train_loss -0.8054 +2024-11-22 19:00:35.777802: val_loss -0.7705 +2024-11-22 19:00:35.777961: Pseudo dice [0.849] +2024-11-22 19:00:35.778071: Epoch time: 18.33 s +2024-11-22 19:00:36.683095: +2024-11-22 19:00:36.683896: Epoch 5819 +2024-11-22 19:00:36.684029: Current learning rate: 0.0031 +2024-11-22 19:00:57.208816: train_loss -0.7968 +2024-11-22 19:00:57.217273: val_loss -0.7846 +2024-11-22 19:00:57.217413: Pseudo dice [0.8582] +2024-11-22 19:00:57.217504: Epoch time: 20.53 s +2024-11-22 19:00:58.398888: +2024-11-22 19:00:58.400128: Epoch 5820 +2024-11-22 19:00:58.400258: Current learning rate: 0.0031 +2024-11-22 19:01:17.914755: train_loss -0.7975 +2024-11-22 19:01:17.920134: val_loss -0.7571 +2024-11-22 19:01:17.920286: Pseudo dice [0.8524] +2024-11-22 19:01:17.920708: Epoch time: 19.52 s +2024-11-22 19:01:18.828226: +2024-11-22 19:01:18.829063: Epoch 5821 +2024-11-22 19:01:18.829198: Current learning rate: 0.0031 +2024-11-22 19:01:38.376790: train_loss -0.7976 +2024-11-22 19:01:38.379769: val_loss -0.7822 +2024-11-22 19:01:38.379916: Pseudo dice [0.8621] +2024-11-22 19:01:38.380026: Epoch time: 19.55 s +2024-11-22 19:01:39.423661: +2024-11-22 19:01:39.424861: Epoch 5822 +2024-11-22 19:01:39.424980: Current learning rate: 0.0031 +2024-11-22 19:01:59.399469: train_loss -0.7987 +2024-11-22 19:01:59.403038: val_loss -0.7993 +2024-11-22 19:01:59.403143: Pseudo dice [0.848] +2024-11-22 19:01:59.403238: Epoch time: 19.98 s +2024-11-22 19:02:00.280227: +2024-11-22 19:02:00.281346: Epoch 5823 +2024-11-22 19:02:00.281465: Current learning rate: 0.0031 +2024-11-22 19:02:18.753361: train_loss -0.8077 +2024-11-22 19:02:18.757447: val_loss -0.801 +2024-11-22 19:02:18.757552: Pseudo dice [0.8691] +2024-11-22 19:02:18.757647: Epoch time: 18.47 s +2024-11-22 19:02:19.644749: +2024-11-22 19:02:19.646363: Epoch 5824 +2024-11-22 19:02:19.646496: Current learning rate: 0.0031 +2024-11-22 19:02:39.835956: train_loss -0.805 +2024-11-22 19:02:39.848308: val_loss -0.7974 +2024-11-22 19:02:39.848429: Pseudo dice [0.8667] +2024-11-22 19:02:39.848515: Epoch time: 20.19 s +2024-11-22 19:02:40.881742: +2024-11-22 19:02:40.882974: Epoch 5825 +2024-11-22 19:02:40.883102: Current learning rate: 0.0031 +2024-11-22 19:03:01.118668: train_loss -0.8067 +2024-11-22 19:03:01.121913: val_loss -0.7969 +2024-11-22 19:03:01.122019: Pseudo dice [0.8673] +2024-11-22 19:03:01.122116: Epoch time: 20.24 s +2024-11-22 19:03:01.122208: Yayy! New best EMA pseudo Dice: 0.8586 +2024-11-22 19:03:02.313110: +2024-11-22 19:03:02.314166: Epoch 5826 +2024-11-22 19:03:02.314314: Current learning rate: 0.0031 +2024-11-22 19:03:22.949884: train_loss -0.8027 +2024-11-22 19:03:22.961829: val_loss -0.7751 +2024-11-22 19:03:22.961977: Pseudo dice [0.8536] +2024-11-22 19:03:22.962090: Epoch time: 20.64 s +2024-11-22 19:03:23.899633: +2024-11-22 19:03:23.900094: Epoch 5827 +2024-11-22 19:03:23.900226: Current learning rate: 0.00309 +2024-11-22 19:03:43.319341: train_loss -0.8093 +2024-11-22 19:03:43.321760: val_loss -0.7555 +2024-11-22 19:03:43.321900: Pseudo dice [0.8565] +2024-11-22 19:03:43.322000: Epoch time: 19.42 s +2024-11-22 19:03:44.447715: +2024-11-22 19:03:44.449062: Epoch 5828 +2024-11-22 19:03:44.449191: Current learning rate: 0.00309 +2024-11-22 19:04:03.459620: train_loss -0.8085 +2024-11-22 19:04:03.471497: val_loss -0.7959 +2024-11-22 19:04:03.471654: Pseudo dice [0.855] +2024-11-22 19:04:03.471792: Epoch time: 19.01 s +2024-11-22 19:04:04.884650: +2024-11-22 19:04:04.885462: Epoch 5829 +2024-11-22 19:04:04.885588: Current learning rate: 0.00309 +2024-11-22 19:04:23.942364: train_loss -0.8068 +2024-11-22 19:04:23.950966: val_loss -0.7694 +2024-11-22 19:04:23.951134: Pseudo dice [0.8554] +2024-11-22 19:04:23.951231: Epoch time: 19.06 s +2024-11-22 19:04:24.835637: +2024-11-22 19:04:24.836396: Epoch 5830 +2024-11-22 19:04:24.836530: Current learning rate: 0.00309 +2024-11-22 19:04:43.776768: train_loss -0.8105 +2024-11-22 19:04:43.782677: val_loss -0.7635 +2024-11-22 19:04:43.782894: Pseudo dice [0.8565] +2024-11-22 19:04:43.782994: Epoch time: 18.94 s +2024-11-22 19:04:44.684864: +2024-11-22 19:04:44.685112: Epoch 5831 +2024-11-22 19:04:44.685238: Current learning rate: 0.00309 +2024-11-22 19:05:03.771391: train_loss -0.8074 +2024-11-22 19:05:03.774451: val_loss -0.7688 +2024-11-22 19:05:03.774619: Pseudo dice [0.8569] +2024-11-22 19:05:03.774710: Epoch time: 19.09 s +2024-11-22 19:05:04.662191: +2024-11-22 19:05:04.663801: Epoch 5832 +2024-11-22 19:05:04.663951: Current learning rate: 0.00309 +2024-11-22 19:05:24.727230: train_loss -0.8089 +2024-11-22 19:05:24.733702: val_loss -0.7632 +2024-11-22 19:05:24.733872: Pseudo dice [0.8475] +2024-11-22 19:05:24.734008: Epoch time: 20.07 s +2024-11-22 19:05:25.619984: +2024-11-22 19:05:25.620989: Epoch 5833 +2024-11-22 19:05:25.621115: Current learning rate: 0.00309 +2024-11-22 19:05:44.420730: train_loss -0.7965 +2024-11-22 19:05:44.432272: val_loss -0.7795 +2024-11-22 19:05:44.432395: Pseudo dice [0.8521] +2024-11-22 19:05:44.432507: Epoch time: 18.8 s +2024-11-22 19:05:45.735721: +2024-11-22 19:05:45.737832: Epoch 5834 +2024-11-22 19:05:45.737973: Current learning rate: 0.00309 +2024-11-22 19:06:03.975209: train_loss -0.8008 +2024-11-22 19:06:03.985020: val_loss -0.774 +2024-11-22 19:06:03.985173: Pseudo dice [0.8475] +2024-11-22 19:06:03.985275: Epoch time: 18.24 s +2024-11-22 19:06:04.925216: +2024-11-22 19:06:04.927308: Epoch 5835 +2024-11-22 19:06:04.927463: Current learning rate: 0.00308 +2024-11-22 19:06:24.076318: train_loss -0.8044 +2024-11-22 19:06:24.091614: val_loss -0.7519 +2024-11-22 19:06:24.091753: Pseudo dice [0.8646] +2024-11-22 19:06:24.091858: Epoch time: 19.15 s +2024-11-22 19:06:25.122981: +2024-11-22 19:06:25.124529: Epoch 5836 +2024-11-22 19:06:25.124656: Current learning rate: 0.00308 +2024-11-22 19:06:44.563470: train_loss -0.8039 +2024-11-22 19:06:44.570602: val_loss -0.7723 +2024-11-22 19:06:44.570761: Pseudo dice [0.8539] +2024-11-22 19:06:44.570861: Epoch time: 19.44 s +2024-11-22 19:06:45.497379: +2024-11-22 19:06:45.498870: Epoch 5837 +2024-11-22 19:06:45.499014: Current learning rate: 0.00308 +2024-11-22 19:07:06.318636: train_loss -0.8059 +2024-11-22 19:07:06.338443: val_loss -0.7932 +2024-11-22 19:07:06.338603: Pseudo dice [0.8584] +2024-11-22 19:07:06.338931: Epoch time: 20.82 s +2024-11-22 19:07:07.428139: +2024-11-22 19:07:07.429499: Epoch 5838 +2024-11-22 19:07:07.429637: Current learning rate: 0.00308 +2024-11-22 19:07:27.248418: train_loss -0.8077 +2024-11-22 19:07:27.251366: val_loss -0.7843 +2024-11-22 19:07:27.251480: Pseudo dice [0.8508] +2024-11-22 19:07:27.251564: Epoch time: 19.82 s +2024-11-22 19:07:28.127380: +2024-11-22 19:07:28.127966: Epoch 5839 +2024-11-22 19:07:28.128094: Current learning rate: 0.00308 +2024-11-22 19:07:47.635496: train_loss -0.8092 +2024-11-22 19:07:47.659310: val_loss -0.7906 +2024-11-22 19:07:47.659439: Pseudo dice [0.8696] +2024-11-22 19:07:47.659546: Epoch time: 19.51 s +2024-11-22 19:07:49.121685: +2024-11-22 19:07:49.123094: Epoch 5840 +2024-11-22 19:07:49.123227: Current learning rate: 0.00308 +2024-11-22 19:08:07.520446: train_loss -0.8145 +2024-11-22 19:08:07.526597: val_loss -0.7618 +2024-11-22 19:08:07.526743: Pseudo dice [0.8624] +2024-11-22 19:08:07.526842: Epoch time: 18.4 s +2024-11-22 19:08:08.498188: +2024-11-22 19:08:08.498645: Epoch 5841 +2024-11-22 19:08:08.498783: Current learning rate: 0.00308 +2024-11-22 19:08:27.280981: train_loss -0.8132 +2024-11-22 19:08:27.288525: val_loss -0.7892 +2024-11-22 19:08:27.288650: Pseudo dice [0.8524] +2024-11-22 19:08:27.288751: Epoch time: 18.78 s +2024-11-22 19:08:28.243625: +2024-11-22 19:08:28.244895: Epoch 5842 +2024-11-22 19:08:28.245021: Current learning rate: 0.00308 +2024-11-22 19:08:47.216594: train_loss -0.804 +2024-11-22 19:08:47.219275: val_loss -0.7825 +2024-11-22 19:08:47.219392: Pseudo dice [0.8583] +2024-11-22 19:08:47.219504: Epoch time: 18.97 s +2024-11-22 19:08:48.101816: +2024-11-22 19:08:48.102008: Epoch 5843 +2024-11-22 19:08:48.102130: Current learning rate: 0.00307 +2024-11-22 19:09:06.757601: train_loss -0.809 +2024-11-22 19:09:06.765013: val_loss -0.7874 +2024-11-22 19:09:06.765146: Pseudo dice [0.8526] +2024-11-22 19:09:06.765245: Epoch time: 18.66 s +2024-11-22 19:09:07.783005: +2024-11-22 19:09:07.783485: Epoch 5844 +2024-11-22 19:09:07.783603: Current learning rate: 0.00307 +2024-11-22 19:09:27.902836: train_loss -0.8064 +2024-11-22 19:09:27.905605: val_loss -0.7862 +2024-11-22 19:09:27.905713: Pseudo dice [0.8563] +2024-11-22 19:09:27.905805: Epoch time: 20.12 s +2024-11-22 19:09:28.780778: +2024-11-22 19:09:28.781746: Epoch 5845 +2024-11-22 19:09:28.781878: Current learning rate: 0.00307 +2024-11-22 19:09:48.410896: train_loss -0.7922 +2024-11-22 19:09:48.418101: val_loss -0.7789 +2024-11-22 19:09:48.418244: Pseudo dice [0.8597] +2024-11-22 19:09:48.418337: Epoch time: 19.63 s +2024-11-22 19:09:49.284873: +2024-11-22 19:09:49.285666: Epoch 5846 +2024-11-22 19:09:49.285783: Current learning rate: 0.00307 +2024-11-22 19:10:08.342026: train_loss -0.7983 +2024-11-22 19:10:08.355416: val_loss -0.7786 +2024-11-22 19:10:08.355570: Pseudo dice [0.8452] +2024-11-22 19:10:08.355681: Epoch time: 19.06 s +2024-11-22 19:10:09.371629: +2024-11-22 19:10:09.372313: Epoch 5847 +2024-11-22 19:10:09.372446: Current learning rate: 0.00307 +2024-11-22 19:10:29.948469: train_loss -0.8012 +2024-11-22 19:10:29.950939: val_loss -0.7847 +2024-11-22 19:10:29.951085: Pseudo dice [0.8625] +2024-11-22 19:10:29.951173: Epoch time: 20.58 s +2024-11-22 19:10:30.962506: +2024-11-22 19:10:30.963234: Epoch 5848 +2024-11-22 19:10:30.963356: Current learning rate: 0.00307 +2024-11-22 19:10:50.672205: train_loss -0.7981 +2024-11-22 19:10:50.682463: val_loss -0.7909 +2024-11-22 19:10:50.697848: Pseudo dice [0.8619] +2024-11-22 19:10:50.698013: Epoch time: 19.71 s +2024-11-22 19:10:51.701402: +2024-11-22 19:10:51.701966: Epoch 5849 +2024-11-22 19:10:51.702097: Current learning rate: 0.00307 +2024-11-22 19:11:10.086004: train_loss -0.8015 +2024-11-22 19:11:10.092322: val_loss -0.771 +2024-11-22 19:11:10.092437: Pseudo dice [0.8623] +2024-11-22 19:11:10.092533: Epoch time: 18.39 s +2024-11-22 19:11:11.264656: +2024-11-22 19:11:11.264865: Epoch 5850 +2024-11-22 19:11:11.264982: Current learning rate: 0.00306 +2024-11-22 19:11:29.500560: train_loss -0.8086 +2024-11-22 19:11:29.516152: val_loss -0.7803 +2024-11-22 19:11:29.516299: Pseudo dice [0.8567] +2024-11-22 19:11:29.516406: Epoch time: 18.24 s +2024-11-22 19:11:31.108587: +2024-11-22 19:11:31.108782: Epoch 5851 +2024-11-22 19:11:31.108899: Current learning rate: 0.00306 +2024-11-22 19:11:49.811564: train_loss -0.8078 +2024-11-22 19:11:49.830599: val_loss -0.7813 +2024-11-22 19:11:49.830770: Pseudo dice [0.8618] +2024-11-22 19:11:49.830873: Epoch time: 18.7 s +2024-11-22 19:11:50.867587: +2024-11-22 19:11:50.867796: Epoch 5852 +2024-11-22 19:11:50.867920: Current learning rate: 0.00306 +2024-11-22 19:12:11.633255: train_loss -0.8058 +2024-11-22 19:12:11.635267: val_loss -0.7818 +2024-11-22 19:12:11.635363: Pseudo dice [0.857] +2024-11-22 19:12:11.635447: Epoch time: 20.77 s +2024-11-22 19:12:12.517945: +2024-11-22 19:12:12.518150: Epoch 5853 +2024-11-22 19:12:12.518267: Current learning rate: 0.00306 +2024-11-22 19:12:30.856596: train_loss -0.8068 +2024-11-22 19:12:30.860237: val_loss -0.7858 +2024-11-22 19:12:30.860437: Pseudo dice [0.8642] +2024-11-22 19:12:30.860523: Epoch time: 18.34 s +2024-11-22 19:12:31.764495: +2024-11-22 19:12:31.764725: Epoch 5854 +2024-11-22 19:12:31.764860: Current learning rate: 0.00306 +2024-11-22 19:12:50.139273: train_loss -0.8093 +2024-11-22 19:12:50.152436: val_loss -0.7679 +2024-11-22 19:12:50.152584: Pseudo dice [0.8554] +2024-11-22 19:12:50.152694: Epoch time: 18.38 s +2024-11-22 19:12:51.331716: +2024-11-22 19:12:51.331940: Epoch 5855 +2024-11-22 19:12:51.332092: Current learning rate: 0.00306 +2024-11-22 19:13:09.785308: train_loss -0.8026 +2024-11-22 19:13:09.788779: val_loss -0.7985 +2024-11-22 19:13:09.788908: Pseudo dice [0.8572] +2024-11-22 19:13:09.788990: Epoch time: 18.45 s +2024-11-22 19:13:10.959743: +2024-11-22 19:13:10.959950: Epoch 5856 +2024-11-22 19:13:10.960075: Current learning rate: 0.00306 +2024-11-22 19:13:29.222644: train_loss -0.8093 +2024-11-22 19:13:29.229370: val_loss -0.7629 +2024-11-22 19:13:29.229514: Pseudo dice [0.85] +2024-11-22 19:13:29.229616: Epoch time: 18.26 s +2024-11-22 19:13:30.181263: +2024-11-22 19:13:30.181448: Epoch 5857 +2024-11-22 19:13:30.181577: Current learning rate: 0.00306 +2024-11-22 19:13:47.837415: train_loss -0.815 +2024-11-22 19:13:47.840356: val_loss -0.803 +2024-11-22 19:13:47.840505: Pseudo dice [0.8543] +2024-11-22 19:13:47.840610: Epoch time: 17.66 s +2024-11-22 19:13:48.904032: +2024-11-22 19:13:48.904261: Epoch 5858 +2024-11-22 19:13:48.904410: Current learning rate: 0.00305 +2024-11-22 19:14:07.005486: train_loss -0.8067 +2024-11-22 19:14:07.016138: val_loss -0.787 +2024-11-22 19:14:07.016293: Pseudo dice [0.8572] +2024-11-22 19:14:07.016392: Epoch time: 18.1 s +2024-11-22 19:14:07.940080: +2024-11-22 19:14:07.940300: Epoch 5859 +2024-11-22 19:14:07.940441: Current learning rate: 0.00305 +2024-11-22 19:14:26.660223: train_loss -0.7975 +2024-11-22 19:14:26.664595: val_loss -0.7912 +2024-11-22 19:14:26.664775: Pseudo dice [0.8575] +2024-11-22 19:14:26.664876: Epoch time: 18.72 s +2024-11-22 19:14:27.741986: +2024-11-22 19:14:27.742193: Epoch 5860 +2024-11-22 19:14:27.742309: Current learning rate: 0.00305 +2024-11-22 19:14:45.749341: train_loss -0.8016 +2024-11-22 19:14:45.753215: val_loss -0.7601 +2024-11-22 19:14:45.753360: Pseudo dice [0.8397] +2024-11-22 19:14:45.753453: Epoch time: 18.01 s +2024-11-22 19:14:46.749111: +2024-11-22 19:14:46.749293: Epoch 5861 +2024-11-22 19:14:46.749412: Current learning rate: 0.00305 +2024-11-22 19:15:06.008767: train_loss -0.802 +2024-11-22 19:15:06.010028: val_loss -0.7786 +2024-11-22 19:15:06.010133: Pseudo dice [0.8384] +2024-11-22 19:15:06.010246: Epoch time: 19.26 s +2024-11-22 19:15:07.302119: +2024-11-22 19:15:07.302334: Epoch 5862 +2024-11-22 19:15:07.302446: Current learning rate: 0.00305 +2024-11-22 19:15:27.280556: train_loss -0.8016 +2024-11-22 19:15:27.282324: val_loss -0.7757 +2024-11-22 19:15:27.282429: Pseudo dice [0.8419] +2024-11-22 19:15:27.282509: Epoch time: 19.98 s +2024-11-22 19:15:28.151563: +2024-11-22 19:15:28.151764: Epoch 5863 +2024-11-22 19:15:28.151893: Current learning rate: 0.00305 +2024-11-22 19:15:47.171039: train_loss -0.8053 +2024-11-22 19:15:47.181782: val_loss -0.7813 +2024-11-22 19:15:47.182129: Pseudo dice [0.8531] +2024-11-22 19:15:47.182239: Epoch time: 19.02 s +2024-11-22 19:15:48.310445: +2024-11-22 19:15:48.310647: Epoch 5864 +2024-11-22 19:15:48.310761: Current learning rate: 0.00305 +2024-11-22 19:16:07.128277: train_loss -0.8049 +2024-11-22 19:16:07.135559: val_loss -0.7744 +2024-11-22 19:16:07.135715: Pseudo dice [0.8557] +2024-11-22 19:16:07.135805: Epoch time: 18.82 s +2024-11-22 19:16:08.202502: +2024-11-22 19:16:08.202721: Epoch 5865 +2024-11-22 19:16:08.202849: Current learning rate: 0.00305 +2024-11-22 19:16:27.360608: train_loss -0.8104 +2024-11-22 19:16:27.367353: val_loss -0.7819 +2024-11-22 19:16:27.367592: Pseudo dice [0.8558] +2024-11-22 19:16:27.367687: Epoch time: 19.16 s +2024-11-22 19:16:28.355849: +2024-11-22 19:16:28.356091: Epoch 5866 +2024-11-22 19:16:28.356213: Current learning rate: 0.00304 +2024-11-22 19:16:46.318820: train_loss -0.8116 +2024-11-22 19:16:46.328716: val_loss -0.7922 +2024-11-22 19:16:46.328854: Pseudo dice [0.8526] +2024-11-22 19:16:46.328951: Epoch time: 17.96 s +2024-11-22 19:16:47.417174: +2024-11-22 19:16:47.417390: Epoch 5867 +2024-11-22 19:16:47.417506: Current learning rate: 0.00304 +2024-11-22 19:17:07.301699: train_loss -0.8041 +2024-11-22 19:17:07.303943: val_loss -0.7941 +2024-11-22 19:17:07.304034: Pseudo dice [0.8588] +2024-11-22 19:17:07.304117: Epoch time: 19.89 s +2024-11-22 19:17:08.183418: +2024-11-22 19:17:08.183636: Epoch 5868 +2024-11-22 19:17:08.183753: Current learning rate: 0.00304 +2024-11-22 19:17:26.360344: train_loss -0.8138 +2024-11-22 19:17:26.363388: val_loss -0.7825 +2024-11-22 19:17:26.363498: Pseudo dice [0.8571] +2024-11-22 19:17:26.363598: Epoch time: 18.18 s +2024-11-22 19:17:27.247507: +2024-11-22 19:17:27.247715: Epoch 5869 +2024-11-22 19:17:27.247833: Current learning rate: 0.00304 +2024-11-22 19:17:46.651725: train_loss -0.8184 +2024-11-22 19:17:46.675747: val_loss -0.7846 +2024-11-22 19:17:46.675896: Pseudo dice [0.8532] +2024-11-22 19:17:46.675999: Epoch time: 19.4 s +2024-11-22 19:17:47.758779: +2024-11-22 19:17:47.758972: Epoch 5870 +2024-11-22 19:17:47.759110: Current learning rate: 0.00304 +2024-11-22 19:18:06.022534: train_loss -0.8091 +2024-11-22 19:18:06.026559: val_loss -0.7888 +2024-11-22 19:18:06.026767: Pseudo dice [0.85] +2024-11-22 19:18:06.026860: Epoch time: 18.26 s +2024-11-22 19:18:07.025159: +2024-11-22 19:18:07.025354: Epoch 5871 +2024-11-22 19:18:07.025467: Current learning rate: 0.00304 +2024-11-22 19:18:27.834094: train_loss -0.8039 +2024-11-22 19:18:27.845034: val_loss -0.7807 +2024-11-22 19:18:27.845161: Pseudo dice [0.8633] +2024-11-22 19:18:27.845248: Epoch time: 20.81 s +2024-11-22 19:18:28.769625: +2024-11-22 19:18:28.769831: Epoch 5872 +2024-11-22 19:18:28.769947: Current learning rate: 0.00304 +2024-11-22 19:18:48.798628: train_loss -0.7963 +2024-11-22 19:18:48.800884: val_loss -0.7808 +2024-11-22 19:18:48.801028: Pseudo dice [0.8496] +2024-11-22 19:18:48.801131: Epoch time: 20.03 s +2024-11-22 19:18:50.115285: +2024-11-22 19:18:50.115499: Epoch 5873 +2024-11-22 19:18:50.115613: Current learning rate: 0.00304 +2024-11-22 19:19:08.813392: train_loss -0.8063 +2024-11-22 19:19:08.817099: val_loss -0.7697 +2024-11-22 19:19:08.817250: Pseudo dice [0.8498] +2024-11-22 19:19:08.817365: Epoch time: 18.7 s +2024-11-22 19:19:09.724053: +2024-11-22 19:19:09.724517: Epoch 5874 +2024-11-22 19:19:09.724646: Current learning rate: 0.00303 +2024-11-22 19:19:29.065380: train_loss -0.8079 +2024-11-22 19:19:29.071006: val_loss -0.7861 +2024-11-22 19:19:29.071142: Pseudo dice [0.863] +2024-11-22 19:19:29.071230: Epoch time: 19.34 s +2024-11-22 19:19:30.163308: +2024-11-22 19:19:30.163497: Epoch 5875 +2024-11-22 19:19:30.163622: Current learning rate: 0.00303 +2024-11-22 19:19:48.997624: train_loss -0.8042 +2024-11-22 19:19:49.006703: val_loss -0.7792 +2024-11-22 19:19:49.006849: Pseudo dice [0.857] +2024-11-22 19:19:49.006948: Epoch time: 18.84 s +2024-11-22 19:19:49.937340: +2024-11-22 19:19:49.937550: Epoch 5876 +2024-11-22 19:19:49.937658: Current learning rate: 0.00303 +2024-11-22 19:20:08.026994: train_loss -0.8122 +2024-11-22 19:20:08.035455: val_loss -0.7604 +2024-11-22 19:20:08.035676: Pseudo dice [0.8602] +2024-11-22 19:20:08.035766: Epoch time: 18.09 s +2024-11-22 19:20:09.171530: +2024-11-22 19:20:09.171750: Epoch 5877 +2024-11-22 19:20:09.171881: Current learning rate: 0.00303 +2024-11-22 19:20:28.336047: train_loss -0.7997 +2024-11-22 19:20:28.347863: val_loss -0.777 +2024-11-22 19:20:28.348015: Pseudo dice [0.8548] +2024-11-22 19:20:28.348123: Epoch time: 19.17 s +2024-11-22 19:20:29.440775: +2024-11-22 19:20:29.440986: Epoch 5878 +2024-11-22 19:20:29.441106: Current learning rate: 0.00303 +2024-11-22 19:20:49.778970: train_loss -0.7976 +2024-11-22 19:20:49.786452: val_loss -0.7742 +2024-11-22 19:20:49.786581: Pseudo dice [0.8494] +2024-11-22 19:20:49.786689: Epoch time: 20.34 s +2024-11-22 19:20:50.719578: +2024-11-22 19:20:50.719798: Epoch 5879 +2024-11-22 19:20:50.719917: Current learning rate: 0.00303 +2024-11-22 19:21:08.877790: train_loss -0.8072 +2024-11-22 19:21:08.884265: val_loss -0.7587 +2024-11-22 19:21:08.884446: Pseudo dice [0.8634] +2024-11-22 19:21:08.884544: Epoch time: 18.16 s +2024-11-22 19:21:09.868845: +2024-11-22 19:21:09.869047: Epoch 5880 +2024-11-22 19:21:09.869170: Current learning rate: 0.00303 +2024-11-22 19:21:29.603244: train_loss -0.8039 +2024-11-22 19:21:29.609518: val_loss -0.7473 +2024-11-22 19:21:29.609666: Pseudo dice [0.8423] +2024-11-22 19:21:29.609761: Epoch time: 19.74 s +2024-11-22 19:21:30.504107: +2024-11-22 19:21:30.504532: Epoch 5881 +2024-11-22 19:21:30.504663: Current learning rate: 0.00303 +2024-11-22 19:21:51.121927: train_loss -0.7986 +2024-11-22 19:21:51.127981: val_loss -0.7591 +2024-11-22 19:21:51.128116: Pseudo dice [0.8657] +2024-11-22 19:21:51.128219: Epoch time: 20.62 s +2024-11-22 19:21:52.040090: +2024-11-22 19:21:52.041036: Epoch 5882 +2024-11-22 19:21:52.041167: Current learning rate: 0.00302 +2024-11-22 19:22:11.839256: train_loss -0.8083 +2024-11-22 19:22:11.843084: val_loss -0.7892 +2024-11-22 19:22:11.843241: Pseudo dice [0.8541] +2024-11-22 19:22:11.843360: Epoch time: 19.8 s +2024-11-22 19:22:12.772853: +2024-11-22 19:22:12.773713: Epoch 5883 +2024-11-22 19:22:12.773842: Current learning rate: 0.00302 +2024-11-22 19:22:32.637515: train_loss -0.8021 +2024-11-22 19:22:32.643496: val_loss -0.7965 +2024-11-22 19:22:32.643618: Pseudo dice [0.8666] +2024-11-22 19:22:32.643711: Epoch time: 19.87 s +2024-11-22 19:22:34.108500: +2024-11-22 19:22:34.109869: Epoch 5884 +2024-11-22 19:22:34.109980: Current learning rate: 0.00302 +2024-11-22 19:22:54.210476: train_loss -0.8007 +2024-11-22 19:22:54.221001: val_loss -0.794 +2024-11-22 19:22:54.221132: Pseudo dice [0.8439] +2024-11-22 19:22:54.221230: Epoch time: 20.1 s +2024-11-22 19:22:55.324198: +2024-11-22 19:22:55.324760: Epoch 5885 +2024-11-22 19:22:55.324884: Current learning rate: 0.00302 +2024-11-22 19:23:15.025458: train_loss -0.8 +2024-11-22 19:23:15.047272: val_loss -0.7615 +2024-11-22 19:23:15.047434: Pseudo dice [0.8391] +2024-11-22 19:23:15.047536: Epoch time: 19.7 s +2024-11-22 19:23:16.142595: +2024-11-22 19:23:16.144657: Epoch 5886 +2024-11-22 19:23:16.144781: Current learning rate: 0.00302 +2024-11-22 19:23:35.036456: train_loss -0.8075 +2024-11-22 19:23:35.039185: val_loss -0.7857 +2024-11-22 19:23:35.039335: Pseudo dice [0.867] +2024-11-22 19:23:35.039773: Epoch time: 18.89 s +2024-11-22 19:23:36.120538: +2024-11-22 19:23:36.121205: Epoch 5887 +2024-11-22 19:23:36.121340: Current learning rate: 0.00302 +2024-11-22 19:23:56.749862: train_loss -0.8012 +2024-11-22 19:23:56.752622: val_loss -0.7739 +2024-11-22 19:23:56.752741: Pseudo dice [0.8546] +2024-11-22 19:23:56.752843: Epoch time: 20.63 s +2024-11-22 19:23:57.689963: +2024-11-22 19:23:57.690390: Epoch 5888 +2024-11-22 19:23:57.690526: Current learning rate: 0.00302 +2024-11-22 19:24:16.921737: train_loss -0.8006 +2024-11-22 19:24:16.928986: val_loss -0.7545 +2024-11-22 19:24:16.929145: Pseudo dice [0.8609] +2024-11-22 19:24:16.929263: Epoch time: 19.23 s +2024-11-22 19:24:17.909201: +2024-11-22 19:24:17.910193: Epoch 5889 +2024-11-22 19:24:17.910311: Current learning rate: 0.00301 +2024-11-22 19:24:37.635567: train_loss -0.7975 +2024-11-22 19:24:37.643595: val_loss -0.7596 +2024-11-22 19:24:37.643970: Pseudo dice [0.8644] +2024-11-22 19:24:37.644090: Epoch time: 19.73 s +2024-11-22 19:24:38.525097: +2024-11-22 19:24:38.526574: Epoch 5890 +2024-11-22 19:24:38.526700: Current learning rate: 0.00301 +2024-11-22 19:24:57.861738: train_loss -0.8105 +2024-11-22 19:24:57.864742: val_loss -0.7778 +2024-11-22 19:24:57.864857: Pseudo dice [0.841] +2024-11-22 19:24:57.864950: Epoch time: 19.34 s +2024-11-22 19:24:58.747248: +2024-11-22 19:24:58.747954: Epoch 5891 +2024-11-22 19:24:58.748094: Current learning rate: 0.00301 +2024-11-22 19:25:19.029612: train_loss -0.8141 +2024-11-22 19:25:19.046097: val_loss -0.7809 +2024-11-22 19:25:19.046268: Pseudo dice [0.853] +2024-11-22 19:25:19.046369: Epoch time: 20.28 s +2024-11-22 19:25:19.949909: +2024-11-22 19:25:19.950110: Epoch 5892 +2024-11-22 19:25:19.950235: Current learning rate: 0.00301 +2024-11-22 19:25:39.260837: train_loss -0.806 +2024-11-22 19:25:39.267269: val_loss -0.7995 +2024-11-22 19:25:39.267403: Pseudo dice [0.8687] +2024-11-22 19:25:39.267500: Epoch time: 19.31 s +2024-11-22 19:25:40.279984: +2024-11-22 19:25:40.280186: Epoch 5893 +2024-11-22 19:25:40.280298: Current learning rate: 0.00301 +2024-11-22 19:25:58.695175: train_loss -0.7984 +2024-11-22 19:25:58.703594: val_loss -0.7784 +2024-11-22 19:25:58.703777: Pseudo dice [0.8539] +2024-11-22 19:25:58.703883: Epoch time: 18.42 s +2024-11-22 19:25:59.769553: +2024-11-22 19:25:59.770759: Epoch 5894 +2024-11-22 19:25:59.770885: Current learning rate: 0.00301 +2024-11-22 19:26:19.105659: train_loss -0.802 +2024-11-22 19:26:19.112983: val_loss -0.7677 +2024-11-22 19:26:19.113125: Pseudo dice [0.8459] +2024-11-22 19:26:19.113228: Epoch time: 19.34 s +2024-11-22 19:26:20.412584: +2024-11-22 19:26:20.413699: Epoch 5895 +2024-11-22 19:26:20.413816: Current learning rate: 0.00301 +2024-11-22 19:26:40.005116: train_loss -0.8079 +2024-11-22 19:26:40.011821: val_loss -0.7728 +2024-11-22 19:26:40.011993: Pseudo dice [0.8556] +2024-11-22 19:26:40.012105: Epoch time: 19.59 s +2024-11-22 19:26:40.879573: +2024-11-22 19:26:40.879775: Epoch 5896 +2024-11-22 19:26:40.879898: Current learning rate: 0.00301 +2024-11-22 19:27:00.242021: train_loss -0.8013 +2024-11-22 19:27:00.248336: val_loss -0.779 +2024-11-22 19:27:00.248510: Pseudo dice [0.8533] +2024-11-22 19:27:00.248601: Epoch time: 19.36 s +2024-11-22 19:27:01.185135: +2024-11-22 19:27:01.186555: Epoch 5897 +2024-11-22 19:27:01.186684: Current learning rate: 0.003 +2024-11-22 19:27:20.404422: train_loss -0.8064 +2024-11-22 19:27:20.416010: val_loss -0.7905 +2024-11-22 19:27:20.416160: Pseudo dice [0.8598] +2024-11-22 19:27:20.416263: Epoch time: 19.22 s +2024-11-22 19:27:21.333351: +2024-11-22 19:27:21.334018: Epoch 5898 +2024-11-22 19:27:21.334160: Current learning rate: 0.003 +2024-11-22 19:27:40.964478: train_loss -0.8029 +2024-11-22 19:27:40.981485: val_loss -0.7765 +2024-11-22 19:27:40.981642: Pseudo dice [0.8464] +2024-11-22 19:27:40.981744: Epoch time: 19.63 s +2024-11-22 19:27:41.866503: +2024-11-22 19:27:41.867768: Epoch 5899 +2024-11-22 19:27:41.867902: Current learning rate: 0.003 +2024-11-22 19:28:01.098014: train_loss -0.7833 +2024-11-22 19:28:01.104780: val_loss -0.7458 +2024-11-22 19:28:01.104923: Pseudo dice [0.8407] +2024-11-22 19:28:01.105033: Epoch time: 19.23 s +2024-11-22 19:28:02.353756: +2024-11-22 19:28:02.354578: Epoch 5900 +2024-11-22 19:28:02.354699: Current learning rate: 0.003 +2024-11-22 19:28:21.759244: train_loss -0.7849 +2024-11-22 19:28:21.769221: val_loss -0.7519 +2024-11-22 19:28:21.769361: Pseudo dice [0.85] +2024-11-22 19:28:21.769450: Epoch time: 19.41 s +2024-11-22 19:28:22.816431: +2024-11-22 19:28:22.816675: Epoch 5901 +2024-11-22 19:28:22.816802: Current learning rate: 0.003 +2024-11-22 19:28:41.261672: train_loss -0.7937 +2024-11-22 19:28:41.268773: val_loss -0.7733 +2024-11-22 19:28:41.268933: Pseudo dice [0.8515] +2024-11-22 19:28:41.269026: Epoch time: 18.45 s +2024-11-22 19:28:42.202178: +2024-11-22 19:28:42.202937: Epoch 5902 +2024-11-22 19:28:42.203083: Current learning rate: 0.003 +2024-11-22 19:29:00.836423: train_loss -0.7966 +2024-11-22 19:29:00.840008: val_loss -0.7773 +2024-11-22 19:29:00.840133: Pseudo dice [0.8588] +2024-11-22 19:29:00.840240: Epoch time: 18.64 s +2024-11-22 19:29:01.722517: +2024-11-22 19:29:01.723435: Epoch 5903 +2024-11-22 19:29:01.723561: Current learning rate: 0.003 +2024-11-22 19:29:22.018767: train_loss -0.8087 +2024-11-22 19:29:22.029546: val_loss -0.7781 +2024-11-22 19:29:22.029700: Pseudo dice [0.8553] +2024-11-22 19:29:22.029809: Epoch time: 20.3 s +2024-11-22 19:29:23.011167: +2024-11-22 19:29:23.011671: Epoch 5904 +2024-11-22 19:29:23.011787: Current learning rate: 0.003 +2024-11-22 19:29:42.570083: train_loss -0.8037 +2024-11-22 19:29:42.580997: val_loss -0.7646 +2024-11-22 19:29:42.581125: Pseudo dice [0.8478] +2024-11-22 19:29:42.581218: Epoch time: 19.56 s +2024-11-22 19:29:43.665108: +2024-11-22 19:29:43.666953: Epoch 5905 +2024-11-22 19:29:43.667090: Current learning rate: 0.00299 +2024-11-22 19:30:03.370887: train_loss -0.8087 +2024-11-22 19:30:03.391906: val_loss -0.7794 +2024-11-22 19:30:03.392071: Pseudo dice [0.8601] +2024-11-22 19:30:03.392271: Epoch time: 19.71 s +2024-11-22 19:30:04.701825: +2024-11-22 19:30:04.703007: Epoch 5906 +2024-11-22 19:30:04.703140: Current learning rate: 0.00299 +2024-11-22 19:30:24.921889: train_loss -0.7939 +2024-11-22 19:30:24.927781: val_loss -0.7699 +2024-11-22 19:30:24.927902: Pseudo dice [0.8515] +2024-11-22 19:30:24.927993: Epoch time: 20.22 s +2024-11-22 19:30:25.855267: +2024-11-22 19:30:25.856557: Epoch 5907 +2024-11-22 19:30:25.856702: Current learning rate: 0.00299 +2024-11-22 19:30:45.702771: train_loss -0.7982 +2024-11-22 19:30:45.708241: val_loss -0.7899 +2024-11-22 19:30:45.708345: Pseudo dice [0.8598] +2024-11-22 19:30:45.708430: Epoch time: 19.85 s +2024-11-22 19:30:46.868752: +2024-11-22 19:30:46.870233: Epoch 5908 +2024-11-22 19:30:46.870373: Current learning rate: 0.00299 +2024-11-22 19:31:07.375750: train_loss -0.8023 +2024-11-22 19:31:07.385768: val_loss -0.7647 +2024-11-22 19:31:07.385949: Pseudo dice [0.8459] +2024-11-22 19:31:07.386051: Epoch time: 20.51 s +2024-11-22 19:31:08.410393: +2024-11-22 19:31:08.412340: Epoch 5909 +2024-11-22 19:31:08.412469: Current learning rate: 0.00299 +2024-11-22 19:31:27.820478: train_loss -0.7994 +2024-11-22 19:31:27.831249: val_loss -0.786 +2024-11-22 19:31:27.831393: Pseudo dice [0.8641] +2024-11-22 19:31:27.831486: Epoch time: 19.41 s +2024-11-22 19:31:28.759854: +2024-11-22 19:31:28.760433: Epoch 5910 +2024-11-22 19:31:28.760562: Current learning rate: 0.00299 +2024-11-22 19:31:47.339985: train_loss -0.7996 +2024-11-22 19:31:47.345377: val_loss -0.7764 +2024-11-22 19:31:47.345492: Pseudo dice [0.8562] +2024-11-22 19:31:47.345608: Epoch time: 18.58 s +2024-11-22 19:31:48.250379: +2024-11-22 19:31:48.250810: Epoch 5911 +2024-11-22 19:31:48.250933: Current learning rate: 0.00299 +2024-11-22 19:32:07.076485: train_loss -0.8097 +2024-11-22 19:32:07.084078: val_loss -0.7498 +2024-11-22 19:32:07.084239: Pseudo dice [0.8621] +2024-11-22 19:32:07.084336: Epoch time: 18.83 s +2024-11-22 19:32:08.084371: +2024-11-22 19:32:08.085262: Epoch 5912 +2024-11-22 19:32:08.085395: Current learning rate: 0.00299 +2024-11-22 19:32:27.775968: train_loss -0.8063 +2024-11-22 19:32:27.782937: val_loss -0.7732 +2024-11-22 19:32:27.783038: Pseudo dice [0.8532] +2024-11-22 19:32:27.783135: Epoch time: 19.69 s +2024-11-22 19:32:28.669957: +2024-11-22 19:32:28.670164: Epoch 5913 +2024-11-22 19:32:28.670288: Current learning rate: 0.00298 +2024-11-22 19:32:47.877260: train_loss -0.8059 +2024-11-22 19:32:47.886562: val_loss -0.7786 +2024-11-22 19:32:47.886702: Pseudo dice [0.8503] +2024-11-22 19:32:47.886796: Epoch time: 19.21 s +2024-11-22 19:32:48.896343: +2024-11-22 19:32:48.897215: Epoch 5914 +2024-11-22 19:32:48.897370: Current learning rate: 0.00298 +2024-11-22 19:33:09.044229: train_loss -0.8017 +2024-11-22 19:33:09.052017: val_loss -0.7516 +2024-11-22 19:33:09.052156: Pseudo dice [0.844] +2024-11-22 19:33:09.052273: Epoch time: 20.15 s +2024-11-22 19:33:09.950691: +2024-11-22 19:33:09.952074: Epoch 5915 +2024-11-22 19:33:09.952193: Current learning rate: 0.00298 +2024-11-22 19:33:28.614639: train_loss -0.7963 +2024-11-22 19:33:28.636767: val_loss -0.7537 +2024-11-22 19:33:28.637179: Pseudo dice [0.8376] +2024-11-22 19:33:28.637286: Epoch time: 18.66 s +2024-11-22 19:33:29.562033: +2024-11-22 19:33:29.562811: Epoch 5916 +2024-11-22 19:33:29.562942: Current learning rate: 0.00298 +2024-11-22 19:33:48.885025: train_loss -0.8037 +2024-11-22 19:33:48.896911: val_loss -0.7975 +2024-11-22 19:33:48.899070: Pseudo dice [0.8675] +2024-11-22 19:33:48.899181: Epoch time: 19.32 s +2024-11-22 19:33:50.231348: +2024-11-22 19:33:50.233287: Epoch 5917 +2024-11-22 19:33:50.233427: Current learning rate: 0.00298 +2024-11-22 19:34:10.193732: train_loss -0.786 +2024-11-22 19:34:10.201272: val_loss -0.7254 +2024-11-22 19:34:10.201414: Pseudo dice [0.8556] +2024-11-22 19:34:10.201521: Epoch time: 19.96 s +2024-11-22 19:34:11.101072: +2024-11-22 19:34:11.101893: Epoch 5918 +2024-11-22 19:34:11.102037: Current learning rate: 0.00298 +2024-11-22 19:34:30.543075: train_loss -0.7983 +2024-11-22 19:34:30.548898: val_loss -0.7631 +2024-11-22 19:34:30.549117: Pseudo dice [0.8609] +2024-11-22 19:34:30.549214: Epoch time: 19.44 s +2024-11-22 19:34:31.453868: +2024-11-22 19:34:31.454993: Epoch 5919 +2024-11-22 19:34:31.455122: Current learning rate: 0.00298 +2024-11-22 19:34:51.198688: train_loss -0.7885 +2024-11-22 19:34:51.205092: val_loss -0.7819 +2024-11-22 19:34:51.205325: Pseudo dice [0.8572] +2024-11-22 19:34:51.205424: Epoch time: 19.75 s +2024-11-22 19:34:52.305249: +2024-11-22 19:34:52.307306: Epoch 5920 +2024-11-22 19:34:52.307433: Current learning rate: 0.00297 +2024-11-22 19:35:12.404417: train_loss -0.8007 +2024-11-22 19:35:12.411432: val_loss -0.7646 +2024-11-22 19:35:12.411572: Pseudo dice [0.8447] +2024-11-22 19:35:12.411670: Epoch time: 20.1 s +2024-11-22 19:35:13.320227: +2024-11-22 19:35:13.322039: Epoch 5921 +2024-11-22 19:35:13.322192: Current learning rate: 0.00297 +2024-11-22 19:35:32.556241: train_loss -0.7954 +2024-11-22 19:35:32.562845: val_loss -0.7866 +2024-11-22 19:35:32.563078: Pseudo dice [0.8543] +2024-11-22 19:35:32.563182: Epoch time: 19.24 s +2024-11-22 19:35:33.669145: +2024-11-22 19:35:33.670005: Epoch 5922 +2024-11-22 19:35:33.670130: Current learning rate: 0.00297 +2024-11-22 19:35:52.732515: train_loss -0.7998 +2024-11-22 19:35:52.739148: val_loss -0.7823 +2024-11-22 19:35:52.739280: Pseudo dice [0.8556] +2024-11-22 19:35:52.739365: Epoch time: 19.06 s +2024-11-22 19:35:53.647781: +2024-11-22 19:35:53.649512: Epoch 5923 +2024-11-22 19:35:53.649633: Current learning rate: 0.00297 +2024-11-22 19:36:12.796015: train_loss -0.8068 +2024-11-22 19:36:12.806460: val_loss -0.7905 +2024-11-22 19:36:12.806617: Pseudo dice [0.8576] +2024-11-22 19:36:12.806716: Epoch time: 19.15 s +2024-11-22 19:36:13.800750: +2024-11-22 19:36:13.801278: Epoch 5924 +2024-11-22 19:36:13.801394: Current learning rate: 0.00297 +2024-11-22 19:36:33.438630: train_loss -0.7933 +2024-11-22 19:36:33.444403: val_loss -0.7959 +2024-11-22 19:36:33.444579: Pseudo dice [0.8662] +2024-11-22 19:36:33.444679: Epoch time: 19.64 s +2024-11-22 19:36:34.370219: +2024-11-22 19:36:34.371690: Epoch 5925 +2024-11-22 19:36:34.371828: Current learning rate: 0.00297 +2024-11-22 19:36:53.042919: train_loss -0.8062 +2024-11-22 19:36:53.051742: val_loss -0.7525 +2024-11-22 19:36:53.051904: Pseudo dice [0.8546] +2024-11-22 19:36:53.052014: Epoch time: 18.67 s +2024-11-22 19:36:53.975069: +2024-11-22 19:36:53.976689: Epoch 5926 +2024-11-22 19:36:53.976831: Current learning rate: 0.00297 +2024-11-22 19:37:13.814091: train_loss -0.8067 +2024-11-22 19:37:13.822078: val_loss -0.7816 +2024-11-22 19:37:13.822209: Pseudo dice [0.8449] +2024-11-22 19:37:13.822309: Epoch time: 19.84 s +2024-11-22 19:37:14.827824: +2024-11-22 19:37:14.829952: Epoch 5927 +2024-11-22 19:37:14.830128: Current learning rate: 0.00297 +2024-11-22 19:37:33.821412: train_loss -0.8071 +2024-11-22 19:37:33.830970: val_loss -0.789 +2024-11-22 19:37:33.831107: Pseudo dice [0.8627] +2024-11-22 19:37:33.831198: Epoch time: 18.99 s +2024-11-22 19:37:35.264894: +2024-11-22 19:37:35.267557: Epoch 5928 +2024-11-22 19:37:35.267704: Current learning rate: 0.00296 +2024-11-22 19:37:54.240127: train_loss -0.8056 +2024-11-22 19:37:54.267156: val_loss -0.7576 +2024-11-22 19:37:54.267283: Pseudo dice [0.8725] +2024-11-22 19:37:54.267376: Epoch time: 18.98 s +2024-11-22 19:37:55.417861: +2024-11-22 19:37:55.419651: Epoch 5929 +2024-11-22 19:37:55.419811: Current learning rate: 0.00296 +2024-11-22 19:38:15.804019: train_loss -0.8073 +2024-11-22 19:38:15.807491: val_loss -0.7877 +2024-11-22 19:38:15.807623: Pseudo dice [0.8541] +2024-11-22 19:38:15.807725: Epoch time: 20.39 s +2024-11-22 19:38:16.837076: +2024-11-22 19:38:16.838394: Epoch 5930 +2024-11-22 19:38:16.838518: Current learning rate: 0.00296 +2024-11-22 19:38:36.519354: train_loss -0.7899 +2024-11-22 19:38:36.533852: val_loss -0.7686 +2024-11-22 19:38:36.533996: Pseudo dice [0.8635] +2024-11-22 19:38:36.534096: Epoch time: 19.68 s +2024-11-22 19:38:37.534494: +2024-11-22 19:38:37.535336: Epoch 5931 +2024-11-22 19:38:37.535458: Current learning rate: 0.00296 +2024-11-22 19:38:56.702180: train_loss -0.7951 +2024-11-22 19:38:56.705410: val_loss -0.7709 +2024-11-22 19:38:56.705543: Pseudo dice [0.8537] +2024-11-22 19:38:56.705648: Epoch time: 19.17 s +2024-11-22 19:38:57.597382: +2024-11-22 19:38:57.599192: Epoch 5932 +2024-11-22 19:38:57.599323: Current learning rate: 0.00296 +2024-11-22 19:39:16.897025: train_loss -0.8069 +2024-11-22 19:39:16.912909: val_loss -0.7559 +2024-11-22 19:39:16.913065: Pseudo dice [0.8584] +2024-11-22 19:39:16.913174: Epoch time: 19.3 s +2024-11-22 19:39:17.990672: +2024-11-22 19:39:17.991958: Epoch 5933 +2024-11-22 19:39:17.992101: Current learning rate: 0.00296 +2024-11-22 19:39:38.369574: train_loss -0.8054 +2024-11-22 19:39:38.379311: val_loss -0.7727 +2024-11-22 19:39:38.379438: Pseudo dice [0.8537] +2024-11-22 19:39:38.379534: Epoch time: 20.38 s +2024-11-22 19:39:39.371287: +2024-11-22 19:39:39.371505: Epoch 5934 +2024-11-22 19:39:39.371625: Current learning rate: 0.00296 +2024-11-22 19:39:59.176948: train_loss -0.8072 +2024-11-22 19:39:59.179468: val_loss -0.7806 +2024-11-22 19:39:59.179606: Pseudo dice [0.8585] +2024-11-22 19:39:59.179695: Epoch time: 19.81 s +2024-11-22 19:40:00.153121: +2024-11-22 19:40:00.154322: Epoch 5935 +2024-11-22 19:40:00.154445: Current learning rate: 0.00296 +2024-11-22 19:40:18.574469: train_loss -0.8016 +2024-11-22 19:40:18.581427: val_loss -0.7775 +2024-11-22 19:40:18.581574: Pseudo dice [0.8593] +2024-11-22 19:40:18.581686: Epoch time: 18.42 s +2024-11-22 19:40:19.552618: +2024-11-22 19:40:19.554240: Epoch 5936 +2024-11-22 19:40:19.554372: Current learning rate: 0.00295 +2024-11-22 19:40:39.669502: train_loss -0.8024 +2024-11-22 19:40:39.681267: val_loss -0.7878 +2024-11-22 19:40:39.681391: Pseudo dice [0.8573] +2024-11-22 19:40:39.681492: Epoch time: 20.12 s +2024-11-22 19:40:40.687242: +2024-11-22 19:40:40.687686: Epoch 5937 +2024-11-22 19:40:40.687819: Current learning rate: 0.00295 +2024-11-22 19:40:59.942109: train_loss -0.8096 +2024-11-22 19:40:59.948438: val_loss -0.7582 +2024-11-22 19:40:59.948819: Pseudo dice [0.8517] +2024-11-22 19:40:59.948936: Epoch time: 19.26 s +2024-11-22 19:41:00.940513: +2024-11-22 19:41:00.941814: Epoch 5938 +2024-11-22 19:41:00.941941: Current learning rate: 0.00295 +2024-11-22 19:41:20.045195: train_loss -0.7892 +2024-11-22 19:41:20.061791: val_loss -0.7911 +2024-11-22 19:41:20.061969: Pseudo dice [0.8591] +2024-11-22 19:41:20.062095: Epoch time: 19.11 s +2024-11-22 19:41:21.381103: +2024-11-22 19:41:21.382704: Epoch 5939 +2024-11-22 19:41:21.382845: Current learning rate: 0.00295 +2024-11-22 19:41:40.259005: train_loss -0.8045 +2024-11-22 19:41:40.261762: val_loss -0.7735 +2024-11-22 19:41:40.261874: Pseudo dice [0.8593] +2024-11-22 19:41:40.261979: Epoch time: 18.88 s +2024-11-22 19:41:41.147004: +2024-11-22 19:41:41.148463: Epoch 5940 +2024-11-22 19:41:41.148604: Current learning rate: 0.00295 +2024-11-22 19:42:01.042652: train_loss -0.808 +2024-11-22 19:42:01.047655: val_loss -0.8064 +2024-11-22 19:42:01.047788: Pseudo dice [0.8703] +2024-11-22 19:42:01.047882: Epoch time: 19.9 s +2024-11-22 19:42:02.037735: +2024-11-22 19:42:02.038702: Epoch 5941 +2024-11-22 19:42:02.038826: Current learning rate: 0.00295 +2024-11-22 19:42:21.975363: train_loss -0.8004 +2024-11-22 19:42:21.978426: val_loss -0.753 +2024-11-22 19:42:21.978562: Pseudo dice [0.8483] +2024-11-22 19:42:21.978652: Epoch time: 19.94 s +2024-11-22 19:42:22.867953: +2024-11-22 19:42:22.868167: Epoch 5942 +2024-11-22 19:42:22.868303: Current learning rate: 0.00295 +2024-11-22 19:42:40.180092: train_loss -0.8005 +2024-11-22 19:42:40.180634: val_loss -0.7775 +2024-11-22 19:42:40.180731: Pseudo dice [0.8671] +2024-11-22 19:42:40.180816: Epoch time: 17.31 s +2024-11-22 19:42:41.179104: +2024-11-22 19:42:41.179304: Epoch 5943 +2024-11-22 19:42:41.179415: Current learning rate: 0.00295 +2024-11-22 19:43:00.316076: train_loss -0.8029 +2024-11-22 19:43:00.316802: val_loss -0.7849 +2024-11-22 19:43:00.316893: Pseudo dice [0.8598] +2024-11-22 19:43:00.317044: Epoch time: 19.14 s +2024-11-22 19:43:01.201816: +2024-11-22 19:43:01.202021: Epoch 5944 +2024-11-22 19:43:01.202145: Current learning rate: 0.00294 +2024-11-22 19:43:20.156312: train_loss -0.8059 +2024-11-22 19:43:20.156927: val_loss -0.7855 +2024-11-22 19:43:20.157055: Pseudo dice [0.8565] +2024-11-22 19:43:20.157209: Epoch time: 18.96 s +2024-11-22 19:43:21.041318: +2024-11-22 19:43:21.041523: Epoch 5945 +2024-11-22 19:43:21.041650: Current learning rate: 0.00294 +2024-11-22 19:43:39.349635: train_loss -0.8126 +2024-11-22 19:43:39.354771: val_loss -0.7915 +2024-11-22 19:43:39.354904: Pseudo dice [0.8639] +2024-11-22 19:43:39.355008: Epoch time: 18.31 s +2024-11-22 19:43:39.355108: Yayy! New best EMA pseudo Dice: 0.8589 +2024-11-22 19:43:40.750735: +2024-11-22 19:43:40.750942: Epoch 5946 +2024-11-22 19:43:40.751078: Current learning rate: 0.00294 +2024-11-22 19:44:00.184566: train_loss -0.8049 +2024-11-22 19:44:00.185490: val_loss -0.7773 +2024-11-22 19:44:00.185601: Pseudo dice [0.8425] +2024-11-22 19:44:00.185699: Epoch time: 19.43 s +2024-11-22 19:44:01.058201: +2024-11-22 19:44:01.058401: Epoch 5947 +2024-11-22 19:44:01.058532: Current learning rate: 0.00294 +2024-11-22 19:44:19.005399: train_loss -0.8021 +2024-11-22 19:44:19.008267: val_loss -0.7854 +2024-11-22 19:44:19.008410: Pseudo dice [0.8526] +2024-11-22 19:44:19.008507: Epoch time: 17.95 s +2024-11-22 19:44:19.968849: +2024-11-22 19:44:19.969052: Epoch 5948 +2024-11-22 19:44:19.969198: Current learning rate: 0.00294 +2024-11-22 19:44:38.857135: train_loss -0.8064 +2024-11-22 19:44:38.861786: val_loss -0.7973 +2024-11-22 19:44:38.861910: Pseudo dice [0.8533] +2024-11-22 19:44:38.861997: Epoch time: 18.89 s +2024-11-22 19:44:39.794043: +2024-11-22 19:44:39.794260: Epoch 5949 +2024-11-22 19:44:39.794383: Current learning rate: 0.00294 +2024-11-22 19:44:59.419482: train_loss -0.7973 +2024-11-22 19:44:59.421145: val_loss -0.7603 +2024-11-22 19:44:59.421277: Pseudo dice [0.8597] +2024-11-22 19:44:59.421370: Epoch time: 19.63 s +2024-11-22 19:45:01.031941: +2024-11-22 19:45:01.041904: Epoch 5950 +2024-11-22 19:45:01.042035: Current learning rate: 0.00294 +2024-11-22 19:45:19.123237: train_loss -0.8041 +2024-11-22 19:45:19.129087: val_loss -0.758 +2024-11-22 19:45:19.129235: Pseudo dice [0.8462] +2024-11-22 19:45:19.129333: Epoch time: 18.09 s +2024-11-22 19:45:20.213143: +2024-11-22 19:45:20.213367: Epoch 5951 +2024-11-22 19:45:20.213489: Current learning rate: 0.00293 +2024-11-22 19:45:39.343712: train_loss -0.8058 +2024-11-22 19:45:39.346731: val_loss -0.7853 +2024-11-22 19:45:39.346844: Pseudo dice [0.855] +2024-11-22 19:45:39.346945: Epoch time: 19.13 s +2024-11-22 19:45:40.277692: +2024-11-22 19:45:40.277931: Epoch 5952 +2024-11-22 19:45:40.278043: Current learning rate: 0.00293 +2024-11-22 19:45:58.652428: train_loss -0.7987 +2024-11-22 19:45:58.662798: val_loss -0.7744 +2024-11-22 19:45:58.662987: Pseudo dice [0.8487] +2024-11-22 19:45:58.663086: Epoch time: 18.38 s +2024-11-22 19:45:59.612044: +2024-11-22 19:45:59.612598: Epoch 5953 +2024-11-22 19:45:59.612722: Current learning rate: 0.00293 +2024-11-22 19:46:19.619010: train_loss -0.8038 +2024-11-22 19:46:19.626469: val_loss -0.8037 +2024-11-22 19:46:19.626594: Pseudo dice [0.8636] +2024-11-22 19:46:19.626680: Epoch time: 20.01 s +2024-11-22 19:46:20.532710: +2024-11-22 19:46:20.533206: Epoch 5954 +2024-11-22 19:46:20.533335: Current learning rate: 0.00293 +2024-11-22 19:46:40.324010: train_loss -0.7892 +2024-11-22 19:46:40.329988: val_loss -0.7384 +2024-11-22 19:46:40.330130: Pseudo dice [0.851] +2024-11-22 19:46:40.330228: Epoch time: 19.79 s +2024-11-22 19:46:41.232769: +2024-11-22 19:46:41.233522: Epoch 5955 +2024-11-22 19:46:41.233651: Current learning rate: 0.00293 +2024-11-22 19:47:01.182848: train_loss -0.7907 +2024-11-22 19:47:01.191379: val_loss -0.776 +2024-11-22 19:47:01.191519: Pseudo dice [0.8608] +2024-11-22 19:47:01.191618: Epoch time: 19.95 s +2024-11-22 19:47:02.184081: +2024-11-22 19:47:02.185203: Epoch 5956 +2024-11-22 19:47:02.185327: Current learning rate: 0.00293 +2024-11-22 19:47:20.673230: train_loss -0.7949 +2024-11-22 19:47:20.692073: val_loss -0.7492 +2024-11-22 19:47:20.692214: Pseudo dice [0.8538] +2024-11-22 19:47:20.692316: Epoch time: 18.49 s +2024-11-22 19:47:21.807899: +2024-11-22 19:47:21.809359: Epoch 5957 +2024-11-22 19:47:21.809491: Current learning rate: 0.00293 +2024-11-22 19:47:41.638032: train_loss -0.8032 +2024-11-22 19:47:41.643854: val_loss -0.7696 +2024-11-22 19:47:41.643998: Pseudo dice [0.8442] +2024-11-22 19:47:41.644103: Epoch time: 19.83 s +2024-11-22 19:47:42.602254: +2024-11-22 19:47:42.603350: Epoch 5958 +2024-11-22 19:47:42.603489: Current learning rate: 0.00293 +2024-11-22 19:48:01.858309: train_loss -0.7882 +2024-11-22 19:48:01.875187: val_loss -0.783 +2024-11-22 19:48:01.875372: Pseudo dice [0.847] +2024-11-22 19:48:01.875470: Epoch time: 19.26 s +2024-11-22 19:48:02.902075: +2024-11-22 19:48:02.903553: Epoch 5959 +2024-11-22 19:48:02.903689: Current learning rate: 0.00292 +2024-11-22 19:48:23.656891: train_loss -0.8034 +2024-11-22 19:48:23.659992: val_loss -0.7839 +2024-11-22 19:48:23.660109: Pseudo dice [0.8533] +2024-11-22 19:48:23.660219: Epoch time: 20.76 s +2024-11-22 19:48:24.971964: +2024-11-22 19:48:24.974596: Epoch 5960 +2024-11-22 19:48:24.974721: Current learning rate: 0.00292 +2024-11-22 19:48:44.466357: train_loss -0.7935 +2024-11-22 19:48:44.472498: val_loss -0.7783 +2024-11-22 19:48:44.472631: Pseudo dice [0.8504] +2024-11-22 19:48:44.472731: Epoch time: 19.5 s +2024-11-22 19:48:45.366934: +2024-11-22 19:48:45.367554: Epoch 5961 +2024-11-22 19:48:45.367726: Current learning rate: 0.00292 +2024-11-22 19:49:04.890713: train_loss -0.7992 +2024-11-22 19:49:04.898690: val_loss -0.7945 +2024-11-22 19:49:04.898824: Pseudo dice [0.8639] +2024-11-22 19:49:04.898911: Epoch time: 19.52 s +2024-11-22 19:49:05.873441: +2024-11-22 19:49:05.874282: Epoch 5962 +2024-11-22 19:49:05.874429: Current learning rate: 0.00292 +2024-11-22 19:49:24.360981: train_loss -0.8011 +2024-11-22 19:49:24.367843: val_loss -0.7879 +2024-11-22 19:49:24.367979: Pseudo dice [0.854] +2024-11-22 19:49:24.389505: Epoch time: 18.49 s +2024-11-22 19:49:25.273972: +2024-11-22 19:49:25.294527: Epoch 5963 +2024-11-22 19:49:25.294677: Current learning rate: 0.00292 +2024-11-22 19:49:44.093695: train_loss -0.8023 +2024-11-22 19:49:44.101654: val_loss -0.7539 +2024-11-22 19:49:44.101827: Pseudo dice [0.8507] +2024-11-22 19:49:44.101934: Epoch time: 18.82 s +2024-11-22 19:49:45.188463: +2024-11-22 19:49:45.189755: Epoch 5964 +2024-11-22 19:49:45.189878: Current learning rate: 0.00292 +2024-11-22 19:50:04.139124: train_loss -0.8001 +2024-11-22 19:50:04.145920: val_loss -0.791 +2024-11-22 19:50:04.146052: Pseudo dice [0.855] +2024-11-22 19:50:04.146171: Epoch time: 18.95 s +2024-11-22 19:50:05.155031: +2024-11-22 19:50:05.157236: Epoch 5965 +2024-11-22 19:50:05.157362: Current learning rate: 0.00292 +2024-11-22 19:50:24.984649: train_loss -0.8104 +2024-11-22 19:50:24.991435: val_loss -0.7817 +2024-11-22 19:50:24.991616: Pseudo dice [0.8592] +2024-11-22 19:50:24.991711: Epoch time: 19.83 s +2024-11-22 19:50:25.929375: +2024-11-22 19:50:25.930271: Epoch 5966 +2024-11-22 19:50:25.930401: Current learning rate: 0.00292 +2024-11-22 19:50:46.739966: train_loss -0.8066 +2024-11-22 19:50:46.745836: val_loss -0.7796 +2024-11-22 19:50:46.745981: Pseudo dice [0.8529] +2024-11-22 19:50:46.746068: Epoch time: 20.81 s +2024-11-22 19:50:47.754908: +2024-11-22 19:50:47.756968: Epoch 5967 +2024-11-22 19:50:47.757170: Current learning rate: 0.00291 +2024-11-22 19:51:06.753662: train_loss -0.8044 +2024-11-22 19:51:06.759762: val_loss -0.7594 +2024-11-22 19:51:06.759932: Pseudo dice [0.8543] +2024-11-22 19:51:06.760045: Epoch time: 19.0 s +2024-11-22 19:51:07.744801: +2024-11-22 19:51:07.746283: Epoch 5968 +2024-11-22 19:51:07.746414: Current learning rate: 0.00291 +2024-11-22 19:51:26.010997: train_loss -0.816 +2024-11-22 19:51:26.021807: val_loss -0.7737 +2024-11-22 19:51:26.021942: Pseudo dice [0.8534] +2024-11-22 19:51:26.022044: Epoch time: 18.27 s +2024-11-22 19:51:26.995962: +2024-11-22 19:51:26.997623: Epoch 5969 +2024-11-22 19:51:26.997777: Current learning rate: 0.00291 +2024-11-22 19:51:46.317710: train_loss -0.812 +2024-11-22 19:51:46.322878: val_loss -0.7804 +2024-11-22 19:51:46.323015: Pseudo dice [0.8565] +2024-11-22 19:51:46.323121: Epoch time: 19.32 s +2024-11-22 19:51:47.215129: +2024-11-22 19:51:47.216784: Epoch 5970 +2024-11-22 19:51:47.216921: Current learning rate: 0.00291 +2024-11-22 19:52:08.153102: train_loss -0.8043 +2024-11-22 19:52:08.158160: val_loss -0.7674 +2024-11-22 19:52:08.158300: Pseudo dice [0.8514] +2024-11-22 19:52:08.158388: Epoch time: 20.94 s +2024-11-22 19:52:09.476122: +2024-11-22 19:52:09.478554: Epoch 5971 +2024-11-22 19:52:09.478699: Current learning rate: 0.00291 +2024-11-22 19:52:28.633619: train_loss -0.8074 +2024-11-22 19:52:28.639978: val_loss -0.7691 +2024-11-22 19:52:28.640159: Pseudo dice [0.8484] +2024-11-22 19:52:28.640367: Epoch time: 19.16 s +2024-11-22 19:52:29.781910: +2024-11-22 19:52:29.783857: Epoch 5972 +2024-11-22 19:52:29.783997: Current learning rate: 0.00291 +2024-11-22 19:52:48.594831: train_loss -0.8043 +2024-11-22 19:52:48.608625: val_loss -0.7756 +2024-11-22 19:52:48.608778: Pseudo dice [0.8578] +2024-11-22 19:52:48.608875: Epoch time: 18.81 s +2024-11-22 19:52:49.521385: +2024-11-22 19:52:49.522388: Epoch 5973 +2024-11-22 19:52:49.522520: Current learning rate: 0.00291 +2024-11-22 19:53:09.891163: train_loss -0.7964 +2024-11-22 19:53:09.899477: val_loss -0.7737 +2024-11-22 19:53:09.899596: Pseudo dice [0.8546] +2024-11-22 19:53:09.899687: Epoch time: 20.37 s +2024-11-22 19:53:10.912456: +2024-11-22 19:53:10.912894: Epoch 5974 +2024-11-22 19:53:10.913022: Current learning rate: 0.00291 +2024-11-22 19:53:29.352040: train_loss -0.8022 +2024-11-22 19:53:29.370251: val_loss -0.7994 +2024-11-22 19:53:29.370414: Pseudo dice [0.8555] +2024-11-22 19:53:29.370537: Epoch time: 18.44 s +2024-11-22 19:53:30.322160: +2024-11-22 19:53:30.323853: Epoch 5975 +2024-11-22 19:53:30.323988: Current learning rate: 0.0029 +2024-11-22 19:53:49.510239: train_loss -0.7947 +2024-11-22 19:53:49.515977: val_loss -0.7783 +2024-11-22 19:53:49.516117: Pseudo dice [0.858] +2024-11-22 19:53:49.516219: Epoch time: 19.19 s +2024-11-22 19:53:50.466726: +2024-11-22 19:53:50.467804: Epoch 5976 +2024-11-22 19:53:50.467932: Current learning rate: 0.0029 +2024-11-22 19:54:10.350038: train_loss -0.8101 +2024-11-22 19:54:10.353240: val_loss -0.7821 +2024-11-22 19:54:10.353350: Pseudo dice [0.8634] +2024-11-22 19:54:10.353465: Epoch time: 19.88 s +2024-11-22 19:54:11.235279: +2024-11-22 19:54:11.236216: Epoch 5977 +2024-11-22 19:54:11.236330: Current learning rate: 0.0029 +2024-11-22 19:54:30.149700: train_loss -0.8049 +2024-11-22 19:54:30.157211: val_loss -0.7751 +2024-11-22 19:54:30.157351: Pseudo dice [0.8512] +2024-11-22 19:54:30.157446: Epoch time: 18.92 s +2024-11-22 19:54:31.078202: +2024-11-22 19:54:31.078965: Epoch 5978 +2024-11-22 19:54:31.079086: Current learning rate: 0.0029 +2024-11-22 19:54:50.341085: train_loss -0.8014 +2024-11-22 19:54:50.345024: val_loss -0.7878 +2024-11-22 19:54:50.345158: Pseudo dice [0.8596] +2024-11-22 19:54:50.345263: Epoch time: 19.26 s +2024-11-22 19:54:51.383973: +2024-11-22 19:54:51.385622: Epoch 5979 +2024-11-22 19:54:51.385749: Current learning rate: 0.0029 +2024-11-22 19:55:11.296909: train_loss -0.7991 +2024-11-22 19:55:11.299293: val_loss -0.7699 +2024-11-22 19:55:11.299418: Pseudo dice [0.8528] +2024-11-22 19:55:11.299517: Epoch time: 19.91 s +2024-11-22 19:55:12.333131: +2024-11-22 19:55:12.334715: Epoch 5980 +2024-11-22 19:55:12.334840: Current learning rate: 0.0029 +2024-11-22 19:55:31.971927: train_loss -0.8055 +2024-11-22 19:55:31.975028: val_loss -0.7556 +2024-11-22 19:55:31.975253: Pseudo dice [0.8528] +2024-11-22 19:55:31.975350: Epoch time: 19.64 s +2024-11-22 19:55:32.915192: +2024-11-22 19:55:32.916268: Epoch 5981 +2024-11-22 19:55:32.916423: Current learning rate: 0.0029 +2024-11-22 19:55:52.584260: train_loss -0.8008 +2024-11-22 19:55:52.586598: val_loss -0.76 +2024-11-22 19:55:52.586720: Pseudo dice [0.8557] +2024-11-22 19:55:52.586806: Epoch time: 19.67 s +2024-11-22 19:55:53.943253: +2024-11-22 19:55:53.944636: Epoch 5982 +2024-11-22 19:55:53.944764: Current learning rate: 0.00289 +2024-11-22 19:56:14.525204: train_loss -0.8027 +2024-11-22 19:56:14.534628: val_loss -0.7821 +2024-11-22 19:56:14.534789: Pseudo dice [0.8507] +2024-11-22 19:56:14.534903: Epoch time: 20.58 s +2024-11-22 19:56:15.441329: +2024-11-22 19:56:15.441997: Epoch 5983 +2024-11-22 19:56:15.442126: Current learning rate: 0.00289 +2024-11-22 19:56:34.049973: train_loss -0.8091 +2024-11-22 19:56:34.056135: val_loss -0.7833 +2024-11-22 19:56:34.056303: Pseudo dice [0.8529] +2024-11-22 19:56:34.056414: Epoch time: 18.61 s +2024-11-22 19:56:35.132904: +2024-11-22 19:56:35.133975: Epoch 5984 +2024-11-22 19:56:35.134129: Current learning rate: 0.00289 +2024-11-22 19:56:54.470880: train_loss -0.8099 +2024-11-22 19:56:54.478225: val_loss -0.7689 +2024-11-22 19:56:54.478363: Pseudo dice [0.8617] +2024-11-22 19:56:54.478459: Epoch time: 19.34 s +2024-11-22 19:56:55.460955: +2024-11-22 19:56:55.462381: Epoch 5985 +2024-11-22 19:56:55.462514: Current learning rate: 0.00289 +2024-11-22 19:57:15.025202: train_loss -0.8156 +2024-11-22 19:57:15.040746: val_loss -0.7524 +2024-11-22 19:57:15.040926: Pseudo dice [0.8398] +2024-11-22 19:57:15.041026: Epoch time: 19.57 s +2024-11-22 19:57:16.017702: +2024-11-22 19:57:16.019299: Epoch 5986 +2024-11-22 19:57:16.019440: Current learning rate: 0.00289 +2024-11-22 19:57:35.528798: train_loss -0.8118 +2024-11-22 19:57:35.542084: val_loss -0.786 +2024-11-22 19:57:35.542236: Pseudo dice [0.8533] +2024-11-22 19:57:35.542341: Epoch time: 19.51 s +2024-11-22 19:57:36.437239: +2024-11-22 19:57:36.438987: Epoch 5987 +2024-11-22 19:57:36.439115: Current learning rate: 0.00289 +2024-11-22 19:57:57.356048: train_loss -0.8004 +2024-11-22 19:57:57.359139: val_loss -0.7759 +2024-11-22 19:57:57.359288: Pseudo dice [0.8559] +2024-11-22 19:57:57.359388: Epoch time: 20.92 s +2024-11-22 19:57:58.286728: +2024-11-22 19:57:58.288339: Epoch 5988 +2024-11-22 19:57:58.288691: Current learning rate: 0.00289 +2024-11-22 19:58:16.677595: train_loss -0.7983 +2024-11-22 19:58:16.680624: val_loss -0.7734 +2024-11-22 19:58:16.680748: Pseudo dice [0.855] +2024-11-22 19:58:16.680856: Epoch time: 18.39 s +2024-11-22 19:58:17.683537: +2024-11-22 19:58:17.684293: Epoch 5989 +2024-11-22 19:58:17.684422: Current learning rate: 0.00289 +2024-11-22 19:58:37.695394: train_loss -0.813 +2024-11-22 19:58:37.709470: val_loss -0.7801 +2024-11-22 19:58:37.709626: Pseudo dice [0.8458] +2024-11-22 19:58:37.709731: Epoch time: 20.01 s +2024-11-22 19:58:38.689199: +2024-11-22 19:58:38.691139: Epoch 5990 +2024-11-22 19:58:38.691278: Current learning rate: 0.00288 +2024-11-22 19:58:56.460629: train_loss -0.8152 +2024-11-22 19:58:56.465901: val_loss -0.7547 +2024-11-22 19:58:56.466034: Pseudo dice [0.8499] +2024-11-22 19:58:56.466152: Epoch time: 17.77 s +2024-11-22 19:58:57.359014: +2024-11-22 19:58:57.360432: Epoch 5991 +2024-11-22 19:58:57.360548: Current learning rate: 0.00288 +2024-11-22 19:59:16.175152: train_loss -0.8081 +2024-11-22 19:59:16.180707: val_loss -0.79 +2024-11-22 19:59:16.180845: Pseudo dice [0.8594] +2024-11-22 19:59:16.180940: Epoch time: 18.82 s +2024-11-22 19:59:17.181411: +2024-11-22 19:59:17.182997: Epoch 5992 +2024-11-22 19:59:17.183143: Current learning rate: 0.00288 +2024-11-22 19:59:37.156739: train_loss -0.8084 +2024-11-22 19:59:37.163349: val_loss -0.7686 +2024-11-22 19:59:37.163472: Pseudo dice [0.8548] +2024-11-22 19:59:37.163616: Epoch time: 19.98 s +2024-11-22 19:59:38.572850: +2024-11-22 19:59:38.574707: Epoch 5993 +2024-11-22 19:59:38.574901: Current learning rate: 0.00288 +2024-11-22 19:59:58.244357: train_loss -0.8097 +2024-11-22 19:59:58.250544: val_loss -0.7654 +2024-11-22 19:59:58.250665: Pseudo dice [0.8642] +2024-11-22 19:59:58.250792: Epoch time: 19.67 s +2024-11-22 19:59:59.205580: +2024-11-22 19:59:59.206725: Epoch 5994 +2024-11-22 19:59:59.206872: Current learning rate: 0.00288 +2024-11-22 20:00:19.277361: train_loss -0.8013 +2024-11-22 20:00:19.289627: val_loss -0.7689 +2024-11-22 20:00:19.289748: Pseudo dice [0.8595] +2024-11-22 20:00:19.289858: Epoch time: 20.07 s +2024-11-22 20:00:20.186836: +2024-11-22 20:00:20.188027: Epoch 5995 +2024-11-22 20:00:20.188162: Current learning rate: 0.00288 +2024-11-22 20:00:40.830547: train_loss -0.8072 +2024-11-22 20:00:40.846544: val_loss -0.7866 +2024-11-22 20:00:40.846695: Pseudo dice [0.8583] +2024-11-22 20:00:40.846799: Epoch time: 20.64 s +2024-11-22 20:00:41.736681: +2024-11-22 20:00:41.737921: Epoch 5996 +2024-11-22 20:00:41.738055: Current learning rate: 0.00288 +2024-11-22 20:01:01.624935: train_loss -0.8065 +2024-11-22 20:01:01.631362: val_loss -0.7841 +2024-11-22 20:01:01.631481: Pseudo dice [0.8502] +2024-11-22 20:01:01.631576: Epoch time: 19.89 s +2024-11-22 20:01:02.638831: +2024-11-22 20:01:02.640580: Epoch 5997 +2024-11-22 20:01:02.640711: Current learning rate: 0.00288 +2024-11-22 20:01:22.160055: train_loss -0.8087 +2024-11-22 20:01:22.176852: val_loss -0.7632 +2024-11-22 20:01:22.177022: Pseudo dice [0.8544] +2024-11-22 20:01:22.177147: Epoch time: 19.52 s +2024-11-22 20:01:23.158690: +2024-11-22 20:01:23.160451: Epoch 5998 +2024-11-22 20:01:23.160574: Current learning rate: 0.00287 +2024-11-22 20:01:42.091962: train_loss -0.8077 +2024-11-22 20:01:42.095156: val_loss -0.7561 +2024-11-22 20:01:42.095273: Pseudo dice [0.8454] +2024-11-22 20:01:42.095384: Epoch time: 18.93 s +2024-11-22 20:01:42.982373: +2024-11-22 20:01:42.982899: Epoch 5999 +2024-11-22 20:01:42.983021: Current learning rate: 0.00287 +2024-11-22 20:02:02.918086: train_loss -0.7981 +2024-11-22 20:02:02.920979: val_loss -0.7802 +2024-11-22 20:02:02.921128: Pseudo dice [0.8574] +2024-11-22 20:02:02.921306: Epoch time: 19.94 s +2024-11-22 20:02:04.242404: +2024-11-22 20:02:04.243690: Epoch 6000 +2024-11-22 20:02:04.243809: Current learning rate: 0.00287 +2024-11-22 20:02:23.202400: train_loss -0.811 +2024-11-22 20:02:23.208614: val_loss -0.7635 +2024-11-22 20:02:23.208741: Pseudo dice [0.8583] +2024-11-22 20:02:23.208854: Epoch time: 18.96 s +2024-11-22 20:02:24.179178: +2024-11-22 20:02:24.181475: Epoch 6001 +2024-11-22 20:02:24.181606: Current learning rate: 0.00287 +2024-11-22 20:02:43.200536: train_loss -0.8028 +2024-11-22 20:02:43.207439: val_loss -0.7839 +2024-11-22 20:02:43.207566: Pseudo dice [0.8514] +2024-11-22 20:02:43.207663: Epoch time: 19.02 s +2024-11-22 20:02:44.098943: +2024-11-22 20:02:44.099908: Epoch 6002 +2024-11-22 20:02:44.100049: Current learning rate: 0.00287 +2024-11-22 20:03:03.924622: train_loss -0.804 +2024-11-22 20:03:03.935223: val_loss -0.7698 +2024-11-22 20:03:03.935448: Pseudo dice [0.8549] +2024-11-22 20:03:03.935544: Epoch time: 19.83 s +2024-11-22 20:03:04.958248: +2024-11-22 20:03:04.960107: Epoch 6003 +2024-11-22 20:03:04.960248: Current learning rate: 0.00287 +2024-11-22 20:03:25.410652: train_loss -0.8077 +2024-11-22 20:03:25.414993: val_loss -0.7781 +2024-11-22 20:03:25.415137: Pseudo dice [0.8572] +2024-11-22 20:03:25.415240: Epoch time: 20.45 s +2024-11-22 20:03:26.734840: +2024-11-22 20:03:26.736144: Epoch 6004 +2024-11-22 20:03:26.736281: Current learning rate: 0.00287 +2024-11-22 20:03:45.691276: train_loss -0.8107 +2024-11-22 20:03:45.697472: val_loss -0.7627 +2024-11-22 20:03:45.697586: Pseudo dice [0.8522] +2024-11-22 20:03:45.697675: Epoch time: 18.96 s +2024-11-22 20:03:46.597344: +2024-11-22 20:03:46.599549: Epoch 6005 +2024-11-22 20:03:46.599691: Current learning rate: 0.00287 +2024-11-22 20:04:06.124556: train_loss -0.8008 +2024-11-22 20:04:06.132278: val_loss -0.7733 +2024-11-22 20:04:06.132401: Pseudo dice [0.8554] +2024-11-22 20:04:06.132507: Epoch time: 19.53 s +2024-11-22 20:04:07.159884: +2024-11-22 20:04:07.161342: Epoch 6006 +2024-11-22 20:04:07.161483: Current learning rate: 0.00286 +2024-11-22 20:04:26.576179: train_loss -0.8091 +2024-11-22 20:04:26.584817: val_loss -0.7558 +2024-11-22 20:04:26.585001: Pseudo dice [0.8593] +2024-11-22 20:04:26.585103: Epoch time: 19.42 s +2024-11-22 20:04:27.532679: +2024-11-22 20:04:27.533516: Epoch 6007 +2024-11-22 20:04:27.533637: Current learning rate: 0.00286 +2024-11-22 20:04:47.738036: train_loss -0.8036 +2024-11-22 20:04:47.745760: val_loss -0.7522 +2024-11-22 20:04:47.745886: Pseudo dice [0.8406] +2024-11-22 20:04:47.745996: Epoch time: 20.21 s +2024-11-22 20:04:48.746884: +2024-11-22 20:04:48.747770: Epoch 6008 +2024-11-22 20:04:48.747893: Current learning rate: 0.00286 +2024-11-22 20:05:08.797972: train_loss -0.8094 +2024-11-22 20:05:08.804114: val_loss -0.772 +2024-11-22 20:05:08.804245: Pseudo dice [0.8642] +2024-11-22 20:05:08.804340: Epoch time: 20.05 s +2024-11-22 20:05:09.726983: +2024-11-22 20:05:09.728700: Epoch 6009 +2024-11-22 20:05:09.728846: Current learning rate: 0.00286 +2024-11-22 20:05:29.201882: train_loss -0.8054 +2024-11-22 20:05:29.204816: val_loss -0.7752 +2024-11-22 20:05:29.204918: Pseudo dice [0.8586] +2024-11-22 20:05:29.205020: Epoch time: 19.48 s +2024-11-22 20:05:30.083910: +2024-11-22 20:05:30.084995: Epoch 6010 +2024-11-22 20:05:30.085124: Current learning rate: 0.00286 +2024-11-22 20:05:50.128598: train_loss -0.7981 +2024-11-22 20:05:50.138990: val_loss -0.7548 +2024-11-22 20:05:50.139166: Pseudo dice [0.8643] +2024-11-22 20:05:50.139257: Epoch time: 20.05 s +2024-11-22 20:05:51.085114: +2024-11-22 20:05:51.085918: Epoch 6011 +2024-11-22 20:05:51.086082: Current learning rate: 0.00286 +2024-11-22 20:06:10.742001: train_loss -0.8169 +2024-11-22 20:06:10.762927: val_loss -0.7896 +2024-11-22 20:06:10.763076: Pseudo dice [0.8629] +2024-11-22 20:06:10.763180: Epoch time: 19.66 s +2024-11-22 20:06:11.874482: +2024-11-22 20:06:11.876198: Epoch 6012 +2024-11-22 20:06:11.876328: Current learning rate: 0.00286 +2024-11-22 20:06:30.149555: train_loss -0.8096 +2024-11-22 20:06:30.157805: val_loss -0.7777 +2024-11-22 20:06:30.157987: Pseudo dice [0.8519] +2024-11-22 20:06:30.158143: Epoch time: 18.28 s +2024-11-22 20:06:31.091695: +2024-11-22 20:06:31.092710: Epoch 6013 +2024-11-22 20:06:31.092844: Current learning rate: 0.00285 +2024-11-22 20:06:49.389446: train_loss -0.805 +2024-11-22 20:06:49.414550: val_loss -0.7842 +2024-11-22 20:06:49.415725: Pseudo dice [0.85] +2024-11-22 20:06:49.415874: Epoch time: 18.3 s +2024-11-22 20:06:50.463011: +2024-11-22 20:06:50.465419: Epoch 6014 +2024-11-22 20:06:50.465569: Current learning rate: 0.00285 +2024-11-22 20:07:09.414057: train_loss -0.8101 +2024-11-22 20:07:09.417501: val_loss -0.7807 +2024-11-22 20:07:09.417638: Pseudo dice [0.8565] +2024-11-22 20:07:09.417826: Epoch time: 18.95 s +2024-11-22 20:07:10.849914: +2024-11-22 20:07:10.851228: Epoch 6015 +2024-11-22 20:07:10.851349: Current learning rate: 0.00285 +2024-11-22 20:07:30.122817: train_loss -0.8129 +2024-11-22 20:07:30.124899: val_loss -0.7749 +2024-11-22 20:07:30.125067: Pseudo dice [0.8509] +2024-11-22 20:07:30.125168: Epoch time: 19.27 s +2024-11-22 20:07:31.008146: +2024-11-22 20:07:31.008984: Epoch 6016 +2024-11-22 20:07:31.009120: Current learning rate: 0.00285 +2024-11-22 20:07:50.345567: train_loss -0.8158 +2024-11-22 20:07:50.351561: val_loss -0.7926 +2024-11-22 20:07:50.351703: Pseudo dice [0.8632] +2024-11-22 20:07:50.351798: Epoch time: 19.34 s +2024-11-22 20:07:51.237782: +2024-11-22 20:07:51.238034: Epoch 6017 +2024-11-22 20:07:51.238166: Current learning rate: 0.00285 +2024-11-22 20:08:09.698997: train_loss -0.8057 +2024-11-22 20:08:09.701826: val_loss -0.7843 +2024-11-22 20:08:09.701962: Pseudo dice [0.8504] +2024-11-22 20:08:09.702069: Epoch time: 18.46 s +2024-11-22 20:08:10.706878: +2024-11-22 20:08:10.707108: Epoch 6018 +2024-11-22 20:08:10.707236: Current learning rate: 0.00285 +2024-11-22 20:08:28.685114: train_loss -0.7973 +2024-11-22 20:08:28.687721: val_loss -0.779 +2024-11-22 20:08:28.687878: Pseudo dice [0.8557] +2024-11-22 20:08:28.687985: Epoch time: 17.98 s +2024-11-22 20:08:29.662055: +2024-11-22 20:08:29.662277: Epoch 6019 +2024-11-22 20:08:29.662644: Current learning rate: 0.00285 +2024-11-22 20:08:48.135559: train_loss -0.8107 +2024-11-22 20:08:48.139008: val_loss -0.7639 +2024-11-22 20:08:48.141110: Pseudo dice [0.8588] +2024-11-22 20:08:48.141226: Epoch time: 18.47 s +2024-11-22 20:08:49.297562: +2024-11-22 20:08:49.297776: Epoch 6020 +2024-11-22 20:08:49.297900: Current learning rate: 0.00285 +2024-11-22 20:09:08.593668: train_loss -0.8089 +2024-11-22 20:09:08.600108: val_loss -0.7863 +2024-11-22 20:09:08.600252: Pseudo dice [0.8651] +2024-11-22 20:09:08.600346: Epoch time: 19.3 s +2024-11-22 20:09:09.713297: +2024-11-22 20:09:09.713508: Epoch 6021 +2024-11-22 20:09:09.713641: Current learning rate: 0.00284 +2024-11-22 20:09:28.810491: train_loss -0.804 +2024-11-22 20:09:28.813240: val_loss -0.7603 +2024-11-22 20:09:28.813363: Pseudo dice [0.8502] +2024-11-22 20:09:28.813465: Epoch time: 19.1 s +2024-11-22 20:09:29.876971: +2024-11-22 20:09:29.877191: Epoch 6022 +2024-11-22 20:09:29.877331: Current learning rate: 0.00284 +2024-11-22 20:09:48.440753: train_loss -0.8084 +2024-11-22 20:09:48.442815: val_loss -0.769 +2024-11-22 20:09:48.442969: Pseudo dice [0.8497] +2024-11-22 20:09:48.443065: Epoch time: 18.56 s +2024-11-22 20:09:49.343562: +2024-11-22 20:09:49.343776: Epoch 6023 +2024-11-22 20:09:49.343900: Current learning rate: 0.00284 +2024-11-22 20:10:07.810769: train_loss -0.8002 +2024-11-22 20:10:07.814209: val_loss -0.7803 +2024-11-22 20:10:07.814352: Pseudo dice [0.8611] +2024-11-22 20:10:07.814438: Epoch time: 18.47 s +2024-11-22 20:10:08.695163: +2024-11-22 20:10:08.695395: Epoch 6024 +2024-11-22 20:10:08.695535: Current learning rate: 0.00284 +2024-11-22 20:10:27.984634: train_loss -0.7964 +2024-11-22 20:10:27.985656: val_loss -0.7765 +2024-11-22 20:10:27.985757: Pseudo dice [0.8604] +2024-11-22 20:10:27.985858: Epoch time: 19.29 s +2024-11-22 20:10:28.879321: +2024-11-22 20:10:28.879881: Epoch 6025 +2024-11-22 20:10:28.880009: Current learning rate: 0.00284 +2024-11-22 20:10:47.242078: train_loss -0.7975 +2024-11-22 20:10:47.255464: val_loss -0.7655 +2024-11-22 20:10:47.255610: Pseudo dice [0.8388] +2024-11-22 20:10:47.255702: Epoch time: 18.36 s +2024-11-22 20:10:48.712231: +2024-11-22 20:10:48.714098: Epoch 6026 +2024-11-22 20:10:48.714229: Current learning rate: 0.00284 +2024-11-22 20:11:07.710730: train_loss -0.7947 +2024-11-22 20:11:07.718962: val_loss -0.7823 +2024-11-22 20:11:07.719099: Pseudo dice [0.8532] +2024-11-22 20:11:07.719201: Epoch time: 19.0 s +2024-11-22 20:11:08.642601: +2024-11-22 20:11:08.643822: Epoch 6027 +2024-11-22 20:11:08.643962: Current learning rate: 0.00284 +2024-11-22 20:11:27.311044: train_loss -0.8053 +2024-11-22 20:11:27.319307: val_loss -0.7757 +2024-11-22 20:11:27.319446: Pseudo dice [0.8487] +2024-11-22 20:11:27.319558: Epoch time: 18.67 s +2024-11-22 20:11:28.262932: +2024-11-22 20:11:28.264307: Epoch 6028 +2024-11-22 20:11:28.264445: Current learning rate: 0.00284 +2024-11-22 20:11:46.468115: train_loss -0.7979 +2024-11-22 20:11:46.470383: val_loss -0.7577 +2024-11-22 20:11:46.470512: Pseudo dice [0.8455] +2024-11-22 20:11:46.470602: Epoch time: 18.21 s +2024-11-22 20:11:47.544193: +2024-11-22 20:11:47.545337: Epoch 6029 +2024-11-22 20:11:47.545461: Current learning rate: 0.00283 +2024-11-22 20:12:07.221099: train_loss -0.8055 +2024-11-22 20:12:07.230893: val_loss -0.7717 +2024-11-22 20:12:07.231021: Pseudo dice [0.8477] +2024-11-22 20:12:07.231148: Epoch time: 19.68 s +2024-11-22 20:12:08.276767: +2024-11-22 20:12:08.278640: Epoch 6030 +2024-11-22 20:12:08.278797: Current learning rate: 0.00283 +2024-11-22 20:12:27.696223: train_loss -0.7967 +2024-11-22 20:12:27.703780: val_loss -0.7603 +2024-11-22 20:12:27.703947: Pseudo dice [0.8637] +2024-11-22 20:12:27.704035: Epoch time: 19.42 s +2024-11-22 20:12:28.729599: +2024-11-22 20:12:28.731430: Epoch 6031 +2024-11-22 20:12:28.731557: Current learning rate: 0.00283 +2024-11-22 20:12:48.978289: train_loss -0.8022 +2024-11-22 20:12:48.984553: val_loss -0.7659 +2024-11-22 20:12:48.984684: Pseudo dice [0.8534] +2024-11-22 20:12:48.984797: Epoch time: 20.25 s +2024-11-22 20:12:49.920005: +2024-11-22 20:12:49.920697: Epoch 6032 +2024-11-22 20:12:49.920832: Current learning rate: 0.00283 +2024-11-22 20:13:08.983693: train_loss -0.8046 +2024-11-22 20:13:08.989183: val_loss -0.783 +2024-11-22 20:13:08.989312: Pseudo dice [0.8633] +2024-11-22 20:13:08.989402: Epoch time: 19.06 s +2024-11-22 20:13:10.039723: +2024-11-22 20:13:10.041500: Epoch 6033 +2024-11-22 20:13:10.041638: Current learning rate: 0.00283 +2024-11-22 20:13:29.434551: train_loss -0.8028 +2024-11-22 20:13:29.440282: val_loss -0.7864 +2024-11-22 20:13:29.440419: Pseudo dice [0.8567] +2024-11-22 20:13:29.440535: Epoch time: 19.4 s +2024-11-22 20:13:30.395815: +2024-11-22 20:13:30.396662: Epoch 6034 +2024-11-22 20:13:30.396789: Current learning rate: 0.00283 +2024-11-22 20:13:50.043780: train_loss -0.7988 +2024-11-22 20:13:50.046390: val_loss -0.7764 +2024-11-22 20:13:50.046526: Pseudo dice [0.8653] +2024-11-22 20:13:50.046606: Epoch time: 19.65 s +2024-11-22 20:13:51.125062: +2024-11-22 20:13:51.125998: Epoch 6035 +2024-11-22 20:13:51.126136: Current learning rate: 0.00283 +2024-11-22 20:14:09.935269: train_loss -0.7937 +2024-11-22 20:14:09.937261: val_loss -0.7773 +2024-11-22 20:14:09.937402: Pseudo dice [0.8548] +2024-11-22 20:14:09.937492: Epoch time: 18.81 s +2024-11-22 20:14:10.815768: +2024-11-22 20:14:10.816857: Epoch 6036 +2024-11-22 20:14:10.816990: Current learning rate: 0.00283 +2024-11-22 20:14:29.365661: train_loss -0.7937 +2024-11-22 20:14:29.373760: val_loss -0.7594 +2024-11-22 20:14:29.373888: Pseudo dice [0.8502] +2024-11-22 20:14:29.374006: Epoch time: 18.55 s +2024-11-22 20:14:30.358482: +2024-11-22 20:14:30.360550: Epoch 6037 +2024-11-22 20:14:30.360688: Current learning rate: 0.00282 +2024-11-22 20:14:49.044398: train_loss -0.8018 +2024-11-22 20:14:49.053174: val_loss -0.7738 +2024-11-22 20:14:49.053305: Pseudo dice [0.8547] +2024-11-22 20:14:49.053398: Epoch time: 18.69 s +2024-11-22 20:14:50.194638: +2024-11-22 20:14:50.196162: Epoch 6038 +2024-11-22 20:14:50.196285: Current learning rate: 0.00282 +2024-11-22 20:15:08.790354: train_loss -0.8043 +2024-11-22 20:15:08.799306: val_loss -0.7418 +2024-11-22 20:15:08.799460: Pseudo dice [0.8616] +2024-11-22 20:15:08.799566: Epoch time: 18.6 s +2024-11-22 20:15:09.718508: +2024-11-22 20:15:09.720363: Epoch 6039 +2024-11-22 20:15:09.720513: Current learning rate: 0.00282 +2024-11-22 20:15:29.408331: train_loss -0.8053 +2024-11-22 20:15:29.417090: val_loss -0.7772 +2024-11-22 20:15:29.417241: Pseudo dice [0.8452] +2024-11-22 20:15:29.417353: Epoch time: 19.69 s +2024-11-22 20:15:30.435163: +2024-11-22 20:15:30.436100: Epoch 6040 +2024-11-22 20:15:30.436250: Current learning rate: 0.00282 +2024-11-22 20:15:50.363003: train_loss -0.7926 +2024-11-22 20:15:50.376644: val_loss -0.7465 +2024-11-22 20:15:50.376784: Pseudo dice [0.847] +2024-11-22 20:15:50.376903: Epoch time: 19.93 s +2024-11-22 20:15:51.387997: +2024-11-22 20:15:51.390233: Epoch 6041 +2024-11-22 20:15:51.390363: Current learning rate: 0.00282 +2024-11-22 20:16:10.875183: train_loss -0.7871 +2024-11-22 20:16:10.890404: val_loss -0.7792 +2024-11-22 20:16:10.890568: Pseudo dice [0.8589] +2024-11-22 20:16:10.890661: Epoch time: 19.49 s +2024-11-22 20:16:11.813041: +2024-11-22 20:16:11.813263: Epoch 6042 +2024-11-22 20:16:11.813387: Current learning rate: 0.00282 +2024-11-22 20:16:31.478641: train_loss -0.7929 +2024-11-22 20:16:31.486773: val_loss -0.7781 +2024-11-22 20:16:31.486915: Pseudo dice [0.8494] +2024-11-22 20:16:31.487004: Epoch time: 19.67 s +2024-11-22 20:16:32.486138: +2024-11-22 20:16:32.487217: Epoch 6043 +2024-11-22 20:16:32.487355: Current learning rate: 0.00282 +2024-11-22 20:16:51.905191: train_loss -0.7987 +2024-11-22 20:16:51.913980: val_loss -0.7739 +2024-11-22 20:16:51.914183: Pseudo dice [0.8618] +2024-11-22 20:16:51.914288: Epoch time: 19.42 s +2024-11-22 20:16:52.839427: +2024-11-22 20:16:52.841082: Epoch 6044 +2024-11-22 20:16:52.841228: Current learning rate: 0.00281 +2024-11-22 20:17:13.285273: train_loss -0.7934 +2024-11-22 20:17:13.295138: val_loss -0.7678 +2024-11-22 20:17:13.295288: Pseudo dice [0.8544] +2024-11-22 20:17:13.295383: Epoch time: 20.45 s +2024-11-22 20:17:14.205012: +2024-11-22 20:17:14.207315: Epoch 6045 +2024-11-22 20:17:14.207494: Current learning rate: 0.00281 +2024-11-22 20:17:34.957000: train_loss -0.7942 +2024-11-22 20:17:34.959662: val_loss -0.7639 +2024-11-22 20:17:34.959784: Pseudo dice [0.8544] +2024-11-22 20:17:34.959880: Epoch time: 20.75 s +2024-11-22 20:17:35.852675: +2024-11-22 20:17:35.853197: Epoch 6046 +2024-11-22 20:17:35.853313: Current learning rate: 0.00281 +2024-11-22 20:17:53.947103: train_loss -0.8021 +2024-11-22 20:17:53.949224: val_loss -0.7762 +2024-11-22 20:17:53.949344: Pseudo dice [0.8601] +2024-11-22 20:17:53.949437: Epoch time: 18.1 s +2024-11-22 20:17:54.830141: +2024-11-22 20:17:54.830906: Epoch 6047 +2024-11-22 20:17:54.831034: Current learning rate: 0.00281 +2024-11-22 20:18:12.754336: train_loss -0.804 +2024-11-22 20:18:12.762480: val_loss -0.762 +2024-11-22 20:18:12.762612: Pseudo dice [0.8481] +2024-11-22 20:18:12.762711: Epoch time: 17.92 s +2024-11-22 20:18:14.154768: +2024-11-22 20:18:14.156483: Epoch 6048 +2024-11-22 20:18:14.156610: Current learning rate: 0.00281 +2024-11-22 20:18:32.813480: train_loss -0.7984 +2024-11-22 20:18:32.828014: val_loss -0.7715 +2024-11-22 20:18:32.828218: Pseudo dice [0.8598] +2024-11-22 20:18:32.828345: Epoch time: 18.66 s +2024-11-22 20:18:33.839472: +2024-11-22 20:18:33.841166: Epoch 6049 +2024-11-22 20:18:33.841287: Current learning rate: 0.00281 +2024-11-22 20:18:53.303019: train_loss -0.8013 +2024-11-22 20:18:53.313146: val_loss -0.7641 +2024-11-22 20:18:53.313303: Pseudo dice [0.8587] +2024-11-22 20:18:53.313411: Epoch time: 19.46 s +2024-11-22 20:18:54.540842: +2024-11-22 20:18:54.541957: Epoch 6050 +2024-11-22 20:18:54.542096: Current learning rate: 0.00281 +2024-11-22 20:19:14.122653: train_loss -0.798 +2024-11-22 20:19:14.128038: val_loss -0.7872 +2024-11-22 20:19:14.128180: Pseudo dice [0.8526] +2024-11-22 20:19:14.128273: Epoch time: 19.58 s +2024-11-22 20:19:15.054224: +2024-11-22 20:19:15.055674: Epoch 6051 +2024-11-22 20:19:15.055807: Current learning rate: 0.00281 +2024-11-22 20:19:34.818759: train_loss -0.7948 +2024-11-22 20:19:34.824693: val_loss -0.7889 +2024-11-22 20:19:34.839047: Pseudo dice [0.855] +2024-11-22 20:19:34.839220: Epoch time: 19.77 s +2024-11-22 20:19:35.729971: +2024-11-22 20:19:35.731301: Epoch 6052 +2024-11-22 20:19:35.731425: Current learning rate: 0.0028 +2024-11-22 20:19:55.141872: train_loss -0.7886 +2024-11-22 20:19:55.147611: val_loss -0.7613 +2024-11-22 20:19:55.147746: Pseudo dice [0.8522] +2024-11-22 20:19:55.147843: Epoch time: 19.41 s +2024-11-22 20:19:56.055997: +2024-11-22 20:19:56.057107: Epoch 6053 +2024-11-22 20:19:56.057231: Current learning rate: 0.0028 +2024-11-22 20:20:15.469340: train_loss -0.8085 +2024-11-22 20:20:15.472495: val_loss -0.7597 +2024-11-22 20:20:15.472669: Pseudo dice [0.8444] +2024-11-22 20:20:15.472762: Epoch time: 19.41 s +2024-11-22 20:20:16.565226: +2024-11-22 20:20:16.566894: Epoch 6054 +2024-11-22 20:20:16.567032: Current learning rate: 0.0028 +2024-11-22 20:20:36.426693: train_loss -0.8029 +2024-11-22 20:20:36.429016: val_loss -0.7781 +2024-11-22 20:20:36.429125: Pseudo dice [0.8586] +2024-11-22 20:20:36.429219: Epoch time: 19.86 s +2024-11-22 20:20:37.306578: +2024-11-22 20:20:37.308321: Epoch 6055 +2024-11-22 20:20:37.308448: Current learning rate: 0.0028 +2024-11-22 20:20:56.395274: train_loss -0.7992 +2024-11-22 20:20:56.401879: val_loss -0.7969 +2024-11-22 20:20:56.402018: Pseudo dice [0.8525] +2024-11-22 20:20:56.402213: Epoch time: 19.09 s +2024-11-22 20:20:57.557113: +2024-11-22 20:20:57.558773: Epoch 6056 +2024-11-22 20:20:57.558937: Current learning rate: 0.0028 +2024-11-22 20:21:16.246294: train_loss -0.8121 +2024-11-22 20:21:16.251689: val_loss -0.7779 +2024-11-22 20:21:16.251815: Pseudo dice [0.8508] +2024-11-22 20:21:16.251910: Epoch time: 18.69 s +2024-11-22 20:21:17.170220: +2024-11-22 20:21:17.171513: Epoch 6057 +2024-11-22 20:21:17.171634: Current learning rate: 0.0028 +2024-11-22 20:21:37.144463: train_loss -0.7954 +2024-11-22 20:21:37.153507: val_loss -0.7856 +2024-11-22 20:21:37.153641: Pseudo dice [0.8514] +2024-11-22 20:21:37.153732: Epoch time: 19.98 s +2024-11-22 20:21:38.037048: +2024-11-22 20:21:38.037622: Epoch 6058 +2024-11-22 20:21:38.037740: Current learning rate: 0.0028 +2024-11-22 20:21:58.203600: train_loss -0.7978 +2024-11-22 20:21:58.222115: val_loss -0.7907 +2024-11-22 20:21:58.222280: Pseudo dice [0.863] +2024-11-22 20:21:58.222376: Epoch time: 20.17 s +2024-11-22 20:21:59.673270: +2024-11-22 20:21:59.674834: Epoch 6059 +2024-11-22 20:21:59.674971: Current learning rate: 0.0028 +2024-11-22 20:22:18.738939: train_loss -0.8059 +2024-11-22 20:22:18.762330: val_loss -0.7682 +2024-11-22 20:22:18.762499: Pseudo dice [0.8553] +2024-11-22 20:22:18.762618: Epoch time: 19.07 s +2024-11-22 20:22:19.734848: +2024-11-22 20:22:19.736334: Epoch 6060 +2024-11-22 20:22:19.736522: Current learning rate: 0.00279 +2024-11-22 20:22:38.342706: train_loss -0.7974 +2024-11-22 20:22:38.345324: val_loss -0.7752 +2024-11-22 20:22:38.345443: Pseudo dice [0.8439] +2024-11-22 20:22:38.345549: Epoch time: 18.61 s +2024-11-22 20:22:39.229846: +2024-11-22 20:22:39.230769: Epoch 6061 +2024-11-22 20:22:39.230897: Current learning rate: 0.00279 +2024-11-22 20:23:00.002832: train_loss -0.791 +2024-11-22 20:23:00.008304: val_loss -0.7837 +2024-11-22 20:23:00.008505: Pseudo dice [0.8617] +2024-11-22 20:23:00.008616: Epoch time: 20.77 s +2024-11-22 20:23:00.925063: +2024-11-22 20:23:00.925848: Epoch 6062 +2024-11-22 20:23:00.925986: Current learning rate: 0.00279 +2024-11-22 20:23:19.798965: train_loss -0.8048 +2024-11-22 20:23:19.804533: val_loss -0.7923 +2024-11-22 20:23:19.804657: Pseudo dice [0.8556] +2024-11-22 20:23:19.804757: Epoch time: 18.87 s +2024-11-22 20:23:20.695032: +2024-11-22 20:23:20.695837: Epoch 6063 +2024-11-22 20:23:20.695982: Current learning rate: 0.00279 +2024-11-22 20:23:39.336093: train_loss -0.8115 +2024-11-22 20:23:39.342845: val_loss -0.793 +2024-11-22 20:23:39.342973: Pseudo dice [0.8526] +2024-11-22 20:23:39.343106: Epoch time: 18.64 s +2024-11-22 20:23:40.363918: +2024-11-22 20:23:40.364739: Epoch 6064 +2024-11-22 20:23:40.364865: Current learning rate: 0.00279 +2024-11-22 20:24:00.413363: train_loss -0.803 +2024-11-22 20:24:00.444736: val_loss -0.7613 +2024-11-22 20:24:00.444920: Pseudo dice [0.8383] +2024-11-22 20:24:00.445017: Epoch time: 20.05 s +2024-11-22 20:24:01.348714: +2024-11-22 20:24:01.349926: Epoch 6065 +2024-11-22 20:24:01.350062: Current learning rate: 0.00279 +2024-11-22 20:24:20.557869: train_loss -0.8059 +2024-11-22 20:24:20.578218: val_loss -0.7632 +2024-11-22 20:24:20.578411: Pseudo dice [0.8519] +2024-11-22 20:24:20.578529: Epoch time: 19.21 s +2024-11-22 20:24:21.634550: +2024-11-22 20:24:21.635487: Epoch 6066 +2024-11-22 20:24:21.635613: Current learning rate: 0.00279 +2024-11-22 20:24:41.087798: train_loss -0.7965 +2024-11-22 20:24:41.105780: val_loss -0.7682 +2024-11-22 20:24:41.105978: Pseudo dice [0.8448] +2024-11-22 20:24:41.106085: Epoch time: 19.45 s +2024-11-22 20:24:42.082372: +2024-11-22 20:24:42.083718: Epoch 6067 +2024-11-22 20:24:42.083856: Current learning rate: 0.00279 +2024-11-22 20:25:01.785937: train_loss -0.8003 +2024-11-22 20:25:01.790896: val_loss -0.7947 +2024-11-22 20:25:01.791046: Pseudo dice [0.8642] +2024-11-22 20:25:01.791204: Epoch time: 19.7 s +2024-11-22 20:25:02.675069: +2024-11-22 20:25:02.675623: Epoch 6068 +2024-11-22 20:25:02.675744: Current learning rate: 0.00278 +2024-11-22 20:25:22.185541: train_loss -0.8016 +2024-11-22 20:25:22.198857: val_loss -0.7713 +2024-11-22 20:25:22.199003: Pseudo dice [0.8646] +2024-11-22 20:25:22.199093: Epoch time: 19.51 s +2024-11-22 20:25:23.215700: +2024-11-22 20:25:23.216469: Epoch 6069 +2024-11-22 20:25:23.216606: Current learning rate: 0.00278 +2024-11-22 20:25:42.259437: train_loss -0.7996 +2024-11-22 20:25:42.266839: val_loss -0.7956 +2024-11-22 20:25:42.266970: Pseudo dice [0.8717] +2024-11-22 20:25:42.267079: Epoch time: 19.04 s +2024-11-22 20:25:43.798067: +2024-11-22 20:25:43.799758: Epoch 6070 +2024-11-22 20:25:43.799901: Current learning rate: 0.00278 +2024-11-22 20:26:02.325325: train_loss -0.8018 +2024-11-22 20:26:02.332780: val_loss -0.7745 +2024-11-22 20:26:02.332898: Pseudo dice [0.8557] +2024-11-22 20:26:02.333009: Epoch time: 18.53 s +2024-11-22 20:26:03.315850: +2024-11-22 20:26:03.317364: Epoch 6071 +2024-11-22 20:26:03.317515: Current learning rate: 0.00278 +2024-11-22 20:26:23.241385: train_loss -0.8029 +2024-11-22 20:26:23.244041: val_loss -0.7695 +2024-11-22 20:26:23.244141: Pseudo dice [0.8686] +2024-11-22 20:26:23.244225: Epoch time: 19.93 s +2024-11-22 20:26:24.128560: +2024-11-22 20:26:24.129211: Epoch 6072 +2024-11-22 20:26:24.129374: Current learning rate: 0.00278 +2024-11-22 20:26:43.040780: train_loss -0.7976 +2024-11-22 20:26:43.053683: val_loss -0.7848 +2024-11-22 20:26:43.053820: Pseudo dice [0.8349] +2024-11-22 20:26:43.053912: Epoch time: 18.91 s +2024-11-22 20:26:44.095027: +2024-11-22 20:26:44.098308: Epoch 6073 +2024-11-22 20:26:44.098477: Current learning rate: 0.00278 +2024-11-22 20:27:03.817416: train_loss -0.7988 +2024-11-22 20:27:03.823451: val_loss -0.7717 +2024-11-22 20:27:03.823599: Pseudo dice [0.8534] +2024-11-22 20:27:03.823701: Epoch time: 19.72 s +2024-11-22 20:27:04.773330: +2024-11-22 20:27:04.774726: Epoch 6074 +2024-11-22 20:27:04.774893: Current learning rate: 0.00278 +2024-11-22 20:27:23.370886: train_loss -0.8151 +2024-11-22 20:27:23.377110: val_loss -0.783 +2024-11-22 20:27:23.377258: Pseudo dice [0.868] +2024-11-22 20:27:23.377365: Epoch time: 18.6 s +2024-11-22 20:27:24.605782: +2024-11-22 20:27:24.607826: Epoch 6075 +2024-11-22 20:27:24.607974: Current learning rate: 0.00277 +2024-11-22 20:27:44.383435: train_loss -0.8088 +2024-11-22 20:27:44.387326: val_loss -0.7846 +2024-11-22 20:27:44.387501: Pseudo dice [0.8541] +2024-11-22 20:27:44.387606: Epoch time: 19.78 s +2024-11-22 20:27:45.344923: +2024-11-22 20:27:45.345906: Epoch 6076 +2024-11-22 20:27:45.346068: Current learning rate: 0.00277 +2024-11-22 20:28:05.205681: train_loss -0.7954 +2024-11-22 20:28:05.214447: val_loss -0.7673 +2024-11-22 20:28:05.214674: Pseudo dice [0.8512] +2024-11-22 20:28:05.214779: Epoch time: 19.86 s +2024-11-22 20:28:06.145736: +2024-11-22 20:28:06.147158: Epoch 6077 +2024-11-22 20:28:06.147490: Current learning rate: 0.00277 +2024-11-22 20:28:25.582648: train_loss -0.8001 +2024-11-22 20:28:25.609920: val_loss -0.7797 +2024-11-22 20:28:25.610093: Pseudo dice [0.8556] +2024-11-22 20:28:25.610188: Epoch time: 19.44 s +2024-11-22 20:28:26.518698: +2024-11-22 20:28:26.519750: Epoch 6078 +2024-11-22 20:28:26.519946: Current learning rate: 0.00277 +2024-11-22 20:28:46.648489: train_loss -0.8156 +2024-11-22 20:28:46.654442: val_loss -0.7961 +2024-11-22 20:28:46.654576: Pseudo dice [0.8591] +2024-11-22 20:28:46.654690: Epoch time: 20.13 s +2024-11-22 20:28:47.592800: +2024-11-22 20:28:47.594133: Epoch 6079 +2024-11-22 20:28:47.594282: Current learning rate: 0.00277 +2024-11-22 20:29:07.068471: train_loss -0.8104 +2024-11-22 20:29:07.074544: val_loss -0.7741 +2024-11-22 20:29:07.074657: Pseudo dice [0.8569] +2024-11-22 20:29:07.074750: Epoch time: 19.48 s +2024-11-22 20:29:08.016598: +2024-11-22 20:29:08.017390: Epoch 6080 +2024-11-22 20:29:08.017545: Current learning rate: 0.00277 +2024-11-22 20:29:28.303339: train_loss -0.8164 +2024-11-22 20:29:28.309564: val_loss -0.768 +2024-11-22 20:29:28.309711: Pseudo dice [0.8635] +2024-11-22 20:29:28.309802: Epoch time: 20.29 s +2024-11-22 20:29:29.595704: +2024-11-22 20:29:29.596987: Epoch 6081 +2024-11-22 20:29:29.597113: Current learning rate: 0.00277 +2024-11-22 20:29:48.624452: train_loss -0.8007 +2024-11-22 20:29:48.628265: val_loss -0.7618 +2024-11-22 20:29:48.628449: Pseudo dice [0.8588] +2024-11-22 20:29:48.628554: Epoch time: 19.03 s +2024-11-22 20:29:49.831903: +2024-11-22 20:29:49.833935: Epoch 6082 +2024-11-22 20:29:49.834074: Current learning rate: 0.00277 +2024-11-22 20:30:09.711942: train_loss -0.8107 +2024-11-22 20:30:09.719663: val_loss -0.7481 +2024-11-22 20:30:09.719799: Pseudo dice [0.8422] +2024-11-22 20:30:09.719901: Epoch time: 19.88 s +2024-11-22 20:30:10.875355: +2024-11-22 20:30:10.876737: Epoch 6083 +2024-11-22 20:30:10.876866: Current learning rate: 0.00276 +2024-11-22 20:30:28.714618: train_loss -0.811 +2024-11-22 20:30:28.718855: val_loss -0.7733 +2024-11-22 20:30:28.718972: Pseudo dice [0.8574] +2024-11-22 20:30:28.719065: Epoch time: 17.83 s +2024-11-22 20:30:29.715529: +2024-11-22 20:30:29.716049: Epoch 6084 +2024-11-22 20:30:29.716195: Current learning rate: 0.00276 +2024-11-22 20:30:48.400928: train_loss -0.8099 +2024-11-22 20:30:48.403696: val_loss -0.7675 +2024-11-22 20:30:48.403821: Pseudo dice [0.8544] +2024-11-22 20:30:48.403914: Epoch time: 18.69 s +2024-11-22 20:30:49.312243: +2024-11-22 20:30:49.313782: Epoch 6085 +2024-11-22 20:30:49.313912: Current learning rate: 0.00276 +2024-11-22 20:31:09.317474: train_loss -0.8182 +2024-11-22 20:31:09.323719: val_loss -0.793 +2024-11-22 20:31:09.323849: Pseudo dice [0.8616] +2024-11-22 20:31:09.323959: Epoch time: 20.01 s +2024-11-22 20:31:10.281604: +2024-11-22 20:31:10.283566: Epoch 6086 +2024-11-22 20:31:10.283698: Current learning rate: 0.00276 +2024-11-22 20:31:30.347501: train_loss -0.803 +2024-11-22 20:31:30.356701: val_loss -0.783 +2024-11-22 20:31:30.356845: Pseudo dice [0.8581] +2024-11-22 20:31:30.356946: Epoch time: 20.07 s +2024-11-22 20:31:31.251639: +2024-11-22 20:31:31.253211: Epoch 6087 +2024-11-22 20:31:31.253338: Current learning rate: 0.00276 +2024-11-22 20:31:50.444567: train_loss -0.8103 +2024-11-22 20:31:50.447321: val_loss -0.7803 +2024-11-22 20:31:50.447423: Pseudo dice [0.8671] +2024-11-22 20:31:50.447507: Epoch time: 19.19 s +2024-11-22 20:31:51.329941: +2024-11-22 20:31:51.330175: Epoch 6088 +2024-11-22 20:31:51.330300: Current learning rate: 0.00276 +2024-11-22 20:32:09.396134: train_loss -0.8041 +2024-11-22 20:32:09.401178: val_loss -0.7644 +2024-11-22 20:32:09.401297: Pseudo dice [0.8579] +2024-11-22 20:32:09.401391: Epoch time: 18.07 s +2024-11-22 20:32:10.283076: +2024-11-22 20:32:10.283291: Epoch 6089 +2024-11-22 20:32:10.283432: Current learning rate: 0.00276 +2024-11-22 20:32:29.444340: train_loss -0.8088 +2024-11-22 20:32:29.458654: val_loss -0.7836 +2024-11-22 20:32:29.458820: Pseudo dice [0.8606] +2024-11-22 20:32:29.459141: Epoch time: 19.16 s +2024-11-22 20:32:30.348479: +2024-11-22 20:32:30.348677: Epoch 6090 +2024-11-22 20:32:30.348788: Current learning rate: 0.00276 +2024-11-22 20:32:48.907110: train_loss -0.8001 +2024-11-22 20:32:48.913373: val_loss -0.7744 +2024-11-22 20:32:48.919904: Pseudo dice [0.8606] +2024-11-22 20:32:48.920046: Epoch time: 18.56 s +2024-11-22 20:32:49.937005: +2024-11-22 20:32:49.937245: Epoch 6091 +2024-11-22 20:32:49.937369: Current learning rate: 0.00275 +2024-11-22 20:33:08.873387: train_loss -0.7939 +2024-11-22 20:33:08.877698: val_loss -0.7765 +2024-11-22 20:33:08.877819: Pseudo dice [0.8482] +2024-11-22 20:33:08.877916: Epoch time: 18.94 s +2024-11-22 20:33:10.240392: +2024-11-22 20:33:10.240875: Epoch 6092 +2024-11-22 20:33:10.241017: Current learning rate: 0.00275 +2024-11-22 20:33:30.219163: train_loss -0.7942 +2024-11-22 20:33:30.219682: val_loss -0.7729 +2024-11-22 20:33:30.219771: Pseudo dice [0.8564] +2024-11-22 20:33:30.219855: Epoch time: 19.98 s +2024-11-22 20:33:31.101818: +2024-11-22 20:33:31.102251: Epoch 6093 +2024-11-22 20:33:31.102400: Current learning rate: 0.00275 +2024-11-22 20:33:49.956615: train_loss -0.809 +2024-11-22 20:33:49.961085: val_loss -0.7791 +2024-11-22 20:33:49.961220: Pseudo dice [0.8571] +2024-11-22 20:33:49.961300: Epoch time: 18.86 s +2024-11-22 20:33:50.922857: +2024-11-22 20:33:50.923278: Epoch 6094 +2024-11-22 20:33:50.923420: Current learning rate: 0.00275 +2024-11-22 20:34:08.425738: train_loss -0.8059 +2024-11-22 20:34:08.433220: val_loss -0.7645 +2024-11-22 20:34:08.433383: Pseudo dice [0.8371] +2024-11-22 20:34:08.433498: Epoch time: 17.5 s +2024-11-22 20:34:09.379011: +2024-11-22 20:34:09.379438: Epoch 6095 +2024-11-22 20:34:09.379593: Current learning rate: 0.00275 +2024-11-22 20:34:29.323274: train_loss -0.7841 +2024-11-22 20:34:29.328291: val_loss -0.7577 +2024-11-22 20:34:29.328450: Pseudo dice [0.854] +2024-11-22 20:34:29.328546: Epoch time: 19.95 s +2024-11-22 20:34:30.219646: +2024-11-22 20:34:30.220081: Epoch 6096 +2024-11-22 20:34:30.220229: Current learning rate: 0.00275 +2024-11-22 20:34:51.662398: train_loss -0.7959 +2024-11-22 20:34:51.664907: val_loss -0.7988 +2024-11-22 20:34:51.665008: Pseudo dice [0.8572] +2024-11-22 20:34:51.665101: Epoch time: 21.44 s +2024-11-22 20:34:52.534010: +2024-11-22 20:34:52.534417: Epoch 6097 +2024-11-22 20:34:52.534574: Current learning rate: 0.00275 +2024-11-22 20:35:12.223141: train_loss -0.7852 +2024-11-22 20:35:12.228697: val_loss -0.7703 +2024-11-22 20:35:12.228859: Pseudo dice [0.853] +2024-11-22 20:35:12.228950: Epoch time: 19.69 s +2024-11-22 20:35:13.132125: +2024-11-22 20:35:13.132921: Epoch 6098 +2024-11-22 20:35:13.133078: Current learning rate: 0.00274 +2024-11-22 20:35:32.480701: train_loss -0.801 +2024-11-22 20:35:32.487076: val_loss -0.7463 +2024-11-22 20:35:32.487221: Pseudo dice [0.8401] +2024-11-22 20:35:32.487315: Epoch time: 19.35 s +2024-11-22 20:35:33.499705: +2024-11-22 20:35:33.500695: Epoch 6099 +2024-11-22 20:35:33.500832: Current learning rate: 0.00274 +2024-11-22 20:35:53.869494: train_loss -0.8047 +2024-11-22 20:35:53.874917: val_loss -0.7551 +2024-11-22 20:35:53.875057: Pseudo dice [0.8561] +2024-11-22 20:35:53.875185: Epoch time: 20.37 s +2024-11-22 20:35:55.067456: +2024-11-22 20:35:55.068104: Epoch 6100 +2024-11-22 20:35:55.068243: Current learning rate: 0.00274 +2024-11-22 20:36:14.360626: train_loss -0.7992 +2024-11-22 20:36:14.362631: val_loss -0.772 +2024-11-22 20:36:14.362737: Pseudo dice [0.8513] +2024-11-22 20:36:14.362842: Epoch time: 19.29 s +2024-11-22 20:36:15.239591: +2024-11-22 20:36:15.240908: Epoch 6101 +2024-11-22 20:36:15.241064: Current learning rate: 0.00274 +2024-11-22 20:36:35.225967: train_loss -0.7959 +2024-11-22 20:36:35.231708: val_loss -0.7732 +2024-11-22 20:36:35.231835: Pseudo dice [0.8523] +2024-11-22 20:36:35.231920: Epoch time: 19.99 s +2024-11-22 20:36:36.165486: +2024-11-22 20:36:36.167044: Epoch 6102 +2024-11-22 20:36:36.167185: Current learning rate: 0.00274 +2024-11-22 20:36:55.021845: train_loss -0.8025 +2024-11-22 20:36:55.030768: val_loss -0.7727 +2024-11-22 20:36:55.030952: Pseudo dice [0.8546] +2024-11-22 20:36:55.031082: Epoch time: 18.86 s +2024-11-22 20:36:56.441431: +2024-11-22 20:36:56.442734: Epoch 6103 +2024-11-22 20:36:56.442863: Current learning rate: 0.00274 +2024-11-22 20:37:15.930833: train_loss -0.8107 +2024-11-22 20:37:15.944810: val_loss -0.7889 +2024-11-22 20:37:15.944969: Pseudo dice [0.8528] +2024-11-22 20:37:15.945103: Epoch time: 19.49 s +2024-11-22 20:37:16.860199: +2024-11-22 20:37:16.860618: Epoch 6104 +2024-11-22 20:37:16.860751: Current learning rate: 0.00274 +2024-11-22 20:37:35.628837: train_loss -0.8048 +2024-11-22 20:37:35.640082: val_loss -0.799 +2024-11-22 20:37:35.640241: Pseudo dice [0.8586] +2024-11-22 20:37:35.640347: Epoch time: 18.77 s +2024-11-22 20:37:36.543990: +2024-11-22 20:37:36.545514: Epoch 6105 +2024-11-22 20:37:36.545635: Current learning rate: 0.00274 +2024-11-22 20:37:55.988276: train_loss -0.8039 +2024-11-22 20:37:55.995786: val_loss -0.7858 +2024-11-22 20:37:55.995917: Pseudo dice [0.8424] +2024-11-22 20:37:55.996011: Epoch time: 19.45 s +2024-11-22 20:37:56.927729: +2024-11-22 20:37:56.928808: Epoch 6106 +2024-11-22 20:37:56.928947: Current learning rate: 0.00273 +2024-11-22 20:38:16.543339: train_loss -0.7981 +2024-11-22 20:38:16.550274: val_loss -0.78 +2024-11-22 20:38:16.550388: Pseudo dice [0.8578] +2024-11-22 20:38:16.550481: Epoch time: 19.62 s +2024-11-22 20:38:17.598802: +2024-11-22 20:38:17.600322: Epoch 6107 +2024-11-22 20:38:17.600455: Current learning rate: 0.00273 +2024-11-22 20:38:38.041905: train_loss -0.8046 +2024-11-22 20:38:38.050791: val_loss -0.7725 +2024-11-22 20:38:38.050970: Pseudo dice [0.8675] +2024-11-22 20:38:38.051088: Epoch time: 20.44 s +2024-11-22 20:38:39.056258: +2024-11-22 20:38:39.057506: Epoch 6108 +2024-11-22 20:38:39.057644: Current learning rate: 0.00273 +2024-11-22 20:38:57.687097: train_loss -0.8026 +2024-11-22 20:38:57.692332: val_loss -0.7562 +2024-11-22 20:38:57.692456: Pseudo dice [0.8577] +2024-11-22 20:38:57.692544: Epoch time: 18.63 s +2024-11-22 20:38:58.617396: +2024-11-22 20:38:58.618137: Epoch 6109 +2024-11-22 20:38:58.618257: Current learning rate: 0.00273 +2024-11-22 20:39:18.082279: train_loss -0.7983 +2024-11-22 20:39:18.088686: val_loss -0.7626 +2024-11-22 20:39:18.088875: Pseudo dice [0.842] +2024-11-22 20:39:18.088972: Epoch time: 19.47 s +2024-11-22 20:39:19.208753: +2024-11-22 20:39:19.210253: Epoch 6110 +2024-11-22 20:39:19.210393: Current learning rate: 0.00273 +2024-11-22 20:39:37.836681: train_loss -0.799 +2024-11-22 20:39:37.848683: val_loss -0.795 +2024-11-22 20:39:37.848813: Pseudo dice [0.8563] +2024-11-22 20:39:37.848906: Epoch time: 18.63 s +2024-11-22 20:39:38.821995: +2024-11-22 20:39:38.822828: Epoch 6111 +2024-11-22 20:39:38.822952: Current learning rate: 0.00273 +2024-11-22 20:39:58.684584: train_loss -0.7956 +2024-11-22 20:39:58.693082: val_loss -0.7913 +2024-11-22 20:39:58.693283: Pseudo dice [0.8528] +2024-11-22 20:39:58.693418: Epoch time: 19.86 s +2024-11-22 20:39:59.637507: +2024-11-22 20:39:59.638889: Epoch 6112 +2024-11-22 20:39:59.639026: Current learning rate: 0.00273 +2024-11-22 20:40:17.918610: train_loss -0.7998 +2024-11-22 20:40:17.945284: val_loss -0.7672 +2024-11-22 20:40:17.945452: Pseudo dice [0.861] +2024-11-22 20:40:17.945555: Epoch time: 18.28 s +2024-11-22 20:40:18.835576: +2024-11-22 20:40:18.837272: Epoch 6113 +2024-11-22 20:40:18.837408: Current learning rate: 0.00273 +2024-11-22 20:40:37.261376: train_loss -0.8042 +2024-11-22 20:40:37.281427: val_loss -0.7708 +2024-11-22 20:40:37.281564: Pseudo dice [0.8512] +2024-11-22 20:40:37.281667: Epoch time: 18.43 s +2024-11-22 20:40:38.281595: +2024-11-22 20:40:38.282835: Epoch 6114 +2024-11-22 20:40:38.282968: Current learning rate: 0.00272 +2024-11-22 20:40:57.601786: train_loss -0.8031 +2024-11-22 20:40:57.609655: val_loss -0.7653 +2024-11-22 20:40:57.609822: Pseudo dice [0.8529] +2024-11-22 20:40:57.609923: Epoch time: 19.32 s +2024-11-22 20:40:58.528348: +2024-11-22 20:40:58.529922: Epoch 6115 +2024-11-22 20:40:58.530239: Current learning rate: 0.00272 +2024-11-22 20:41:18.153163: train_loss -0.8084 +2024-11-22 20:41:18.160558: val_loss -0.7755 +2024-11-22 20:41:18.160662: Pseudo dice [0.8634] +2024-11-22 20:41:18.160780: Epoch time: 19.63 s +2024-11-22 20:41:19.055079: +2024-11-22 20:41:19.056725: Epoch 6116 +2024-11-22 20:41:19.056855: Current learning rate: 0.00272 +2024-11-22 20:41:38.781116: train_loss -0.8001 +2024-11-22 20:41:38.783370: val_loss -0.7831 +2024-11-22 20:41:38.783487: Pseudo dice [0.8547] +2024-11-22 20:41:38.783576: Epoch time: 19.73 s +2024-11-22 20:41:39.665180: +2024-11-22 20:41:39.666747: Epoch 6117 +2024-11-22 20:41:39.666873: Current learning rate: 0.00272 +2024-11-22 20:41:59.056415: train_loss -0.8079 +2024-11-22 20:41:59.083251: val_loss -0.7749 +2024-11-22 20:41:59.083436: Pseudo dice [0.8561] +2024-11-22 20:41:59.083549: Epoch time: 19.39 s +2024-11-22 20:42:00.095561: +2024-11-22 20:42:00.096601: Epoch 6118 +2024-11-22 20:42:00.096737: Current learning rate: 0.00272 +2024-11-22 20:42:20.091763: train_loss -0.794 +2024-11-22 20:42:20.098898: val_loss -0.7841 +2024-11-22 20:42:20.099027: Pseudo dice [0.8519] +2024-11-22 20:42:20.099136: Epoch time: 20.0 s +2024-11-22 20:42:21.084196: +2024-11-22 20:42:21.085656: Epoch 6119 +2024-11-22 20:42:21.085789: Current learning rate: 0.00272 +2024-11-22 20:42:40.228582: train_loss -0.7935 +2024-11-22 20:42:40.236722: val_loss -0.7783 +2024-11-22 20:42:40.236879: Pseudo dice [0.8453] +2024-11-22 20:42:40.236983: Epoch time: 19.15 s +2024-11-22 20:42:41.331464: +2024-11-22 20:42:41.333055: Epoch 6120 +2024-11-22 20:42:41.333200: Current learning rate: 0.00272 +2024-11-22 20:43:00.211237: train_loss -0.8039 +2024-11-22 20:43:00.213544: val_loss -0.7774 +2024-11-22 20:43:00.213734: Pseudo dice [0.8328] +2024-11-22 20:43:00.213829: Epoch time: 18.88 s +2024-11-22 20:43:01.234207: +2024-11-22 20:43:01.236103: Epoch 6121 +2024-11-22 20:43:01.236234: Current learning rate: 0.00271 +2024-11-22 20:43:23.557914: train_loss -0.7855 +2024-11-22 20:43:23.570051: val_loss -0.7651 +2024-11-22 20:43:23.570203: Pseudo dice [0.8439] +2024-11-22 20:43:23.570300: Epoch time: 22.32 s +2024-11-22 20:43:24.656558: +2024-11-22 20:43:24.656993: Epoch 6122 +2024-11-22 20:43:24.657132: Current learning rate: 0.00271 +2024-11-22 20:43:44.724562: train_loss -0.7907 +2024-11-22 20:43:44.740890: val_loss -0.796 +2024-11-22 20:43:44.741045: Pseudo dice [0.8569] +2024-11-22 20:43:44.741512: Epoch time: 20.07 s +2024-11-22 20:43:45.690468: +2024-11-22 20:43:45.691562: Epoch 6123 +2024-11-22 20:43:45.691697: Current learning rate: 0.00271 +2024-11-22 20:44:05.383404: train_loss -0.7916 +2024-11-22 20:44:05.388091: val_loss -0.768 +2024-11-22 20:44:05.388227: Pseudo dice [0.8536] +2024-11-22 20:44:05.388381: Epoch time: 19.69 s +2024-11-22 20:44:06.278604: +2024-11-22 20:44:06.280109: Epoch 6124 +2024-11-22 20:44:06.280241: Current learning rate: 0.00271 +2024-11-22 20:44:24.739077: train_loss -0.8004 +2024-11-22 20:44:24.746728: val_loss -0.765 +2024-11-22 20:44:24.746856: Pseudo dice [0.8508] +2024-11-22 20:44:24.746954: Epoch time: 18.46 s +2024-11-22 20:44:26.412403: +2024-11-22 20:44:26.413567: Epoch 6125 +2024-11-22 20:44:26.413705: Current learning rate: 0.00271 +2024-11-22 20:44:45.588935: train_loss -0.7975 +2024-11-22 20:44:45.595149: val_loss -0.7826 +2024-11-22 20:44:45.595316: Pseudo dice [0.8539] +2024-11-22 20:44:45.595429: Epoch time: 19.18 s +2024-11-22 20:44:46.585339: +2024-11-22 20:44:46.585752: Epoch 6126 +2024-11-22 20:44:46.585870: Current learning rate: 0.00271 +2024-11-22 20:45:05.760513: train_loss -0.7948 +2024-11-22 20:45:05.773827: val_loss -0.7773 +2024-11-22 20:45:05.773967: Pseudo dice [0.8531] +2024-11-22 20:45:05.774066: Epoch time: 19.18 s +2024-11-22 20:45:06.904684: +2024-11-22 20:45:06.905448: Epoch 6127 +2024-11-22 20:45:06.905585: Current learning rate: 0.00271 +2024-11-22 20:45:26.425085: train_loss -0.793 +2024-11-22 20:45:26.432599: val_loss -0.7741 +2024-11-22 20:45:26.432733: Pseudo dice [0.8511] +2024-11-22 20:45:26.432835: Epoch time: 19.52 s +2024-11-22 20:45:27.558925: +2024-11-22 20:45:27.560291: Epoch 6128 +2024-11-22 20:45:27.560416: Current learning rate: 0.00271 +2024-11-22 20:45:47.361737: train_loss -0.7903 +2024-11-22 20:45:47.367966: val_loss -0.7562 +2024-11-22 20:45:47.368124: Pseudo dice [0.8301] +2024-11-22 20:45:47.368234: Epoch time: 19.8 s +2024-11-22 20:45:48.244006: +2024-11-22 20:45:48.245710: Epoch 6129 +2024-11-22 20:45:48.245867: Current learning rate: 0.0027 +2024-11-22 20:46:06.973167: train_loss -0.7958 +2024-11-22 20:46:06.997473: val_loss -0.7823 +2024-11-22 20:46:06.997645: Pseudo dice [0.8602] +2024-11-22 20:46:06.997757: Epoch time: 18.73 s +2024-11-22 20:46:08.255560: +2024-11-22 20:46:08.256820: Epoch 6130 +2024-11-22 20:46:08.256941: Current learning rate: 0.0027 +2024-11-22 20:46:27.829051: train_loss -0.7937 +2024-11-22 20:46:27.843003: val_loss -0.7734 +2024-11-22 20:46:27.843159: Pseudo dice [0.8547] +2024-11-22 20:46:27.843247: Epoch time: 19.57 s +2024-11-22 20:46:28.836599: +2024-11-22 20:46:28.837932: Epoch 6131 +2024-11-22 20:46:28.838054: Current learning rate: 0.0027 +2024-11-22 20:46:47.174253: train_loss -0.7953 +2024-11-22 20:46:47.181421: val_loss -0.7821 +2024-11-22 20:46:47.188756: Pseudo dice [0.8508] +2024-11-22 20:46:47.188872: Epoch time: 18.34 s +2024-11-22 20:46:48.085502: +2024-11-22 20:46:48.086648: Epoch 6132 +2024-11-22 20:46:48.086783: Current learning rate: 0.0027 +2024-11-22 20:47:07.383487: train_loss -0.7956 +2024-11-22 20:47:07.390289: val_loss -0.7557 +2024-11-22 20:47:07.390426: Pseudo dice [0.8593] +2024-11-22 20:47:07.390538: Epoch time: 19.3 s +2024-11-22 20:47:08.363050: +2024-11-22 20:47:08.364324: Epoch 6133 +2024-11-22 20:47:08.364455: Current learning rate: 0.0027 +2024-11-22 20:47:27.117256: train_loss -0.8014 +2024-11-22 20:47:27.119538: val_loss -0.802 +2024-11-22 20:47:27.119648: Pseudo dice [0.8627] +2024-11-22 20:47:27.119754: Epoch time: 18.75 s +2024-11-22 20:47:28.339315: +2024-11-22 20:47:28.340282: Epoch 6134 +2024-11-22 20:47:28.340413: Current learning rate: 0.0027 +2024-11-22 20:47:47.194644: train_loss -0.7989 +2024-11-22 20:47:47.212480: val_loss -0.7699 +2024-11-22 20:47:47.212614: Pseudo dice [0.8454] +2024-11-22 20:47:47.212707: Epoch time: 18.86 s +2024-11-22 20:47:48.175145: +2024-11-22 20:47:48.176425: Epoch 6135 +2024-11-22 20:47:48.176566: Current learning rate: 0.0027 +2024-11-22 20:48:07.738541: train_loss -0.7975 +2024-11-22 20:48:07.743668: val_loss -0.7747 +2024-11-22 20:48:07.743801: Pseudo dice [0.8588] +2024-11-22 20:48:07.743889: Epoch time: 19.56 s +2024-11-22 20:48:09.297433: +2024-11-22 20:48:09.298893: Epoch 6136 +2024-11-22 20:48:09.299023: Current learning rate: 0.0027 +2024-11-22 20:48:28.200717: train_loss -0.8034 +2024-11-22 20:48:28.208814: val_loss -0.7852 +2024-11-22 20:48:28.208960: Pseudo dice [0.8678] +2024-11-22 20:48:28.209067: Epoch time: 18.9 s +2024-11-22 20:48:29.144880: +2024-11-22 20:48:29.146521: Epoch 6137 +2024-11-22 20:48:29.146647: Current learning rate: 0.00269 +2024-11-22 20:48:47.706084: train_loss -0.8012 +2024-11-22 20:48:47.712908: val_loss -0.7677 +2024-11-22 20:48:47.713046: Pseudo dice [0.8583] +2024-11-22 20:48:47.713158: Epoch time: 18.56 s +2024-11-22 20:48:48.679663: +2024-11-22 20:48:48.680449: Epoch 6138 +2024-11-22 20:48:48.680585: Current learning rate: 0.00269 +2024-11-22 20:49:07.925417: train_loss -0.8017 +2024-11-22 20:49:07.933273: val_loss -0.7726 +2024-11-22 20:49:07.933405: Pseudo dice [0.8384] +2024-11-22 20:49:07.933496: Epoch time: 19.25 s +2024-11-22 20:49:08.853823: +2024-11-22 20:49:08.855347: Epoch 6139 +2024-11-22 20:49:08.855488: Current learning rate: 0.00269 +2024-11-22 20:49:28.805818: train_loss -0.8015 +2024-11-22 20:49:28.810524: val_loss -0.7611 +2024-11-22 20:49:28.810640: Pseudo dice [0.8571] +2024-11-22 20:49:28.810730: Epoch time: 19.95 s +2024-11-22 20:49:29.700580: +2024-11-22 20:49:29.701441: Epoch 6140 +2024-11-22 20:49:29.701570: Current learning rate: 0.00269 +2024-11-22 20:49:49.236742: train_loss -0.8069 +2024-11-22 20:49:49.239458: val_loss -0.7826 +2024-11-22 20:49:49.239747: Pseudo dice [0.8533] +2024-11-22 20:49:49.239859: Epoch time: 19.54 s +2024-11-22 20:49:50.192833: +2024-11-22 20:49:50.193411: Epoch 6141 +2024-11-22 20:49:50.193527: Current learning rate: 0.00269 +2024-11-22 20:50:10.098183: train_loss -0.8073 +2024-11-22 20:50:10.109225: val_loss -0.7549 +2024-11-22 20:50:10.109366: Pseudo dice [0.861] +2024-11-22 20:50:10.109469: Epoch time: 19.91 s +2024-11-22 20:50:11.027315: +2024-11-22 20:50:11.028506: Epoch 6142 +2024-11-22 20:50:11.028633: Current learning rate: 0.00269 +2024-11-22 20:50:30.628505: train_loss -0.8113 +2024-11-22 20:50:30.644279: val_loss -0.7888 +2024-11-22 20:50:30.644418: Pseudo dice [0.8568] +2024-11-22 20:50:30.644515: Epoch time: 19.6 s +2024-11-22 20:50:31.649098: +2024-11-22 20:50:31.650428: Epoch 6143 +2024-11-22 20:50:31.650569: Current learning rate: 0.00269 +2024-11-22 20:50:52.569475: train_loss -0.7998 +2024-11-22 20:50:52.578343: val_loss -0.7964 +2024-11-22 20:50:52.578551: Pseudo dice [0.8563] +2024-11-22 20:50:52.578657: Epoch time: 20.92 s +2024-11-22 20:50:53.482076: +2024-11-22 20:50:53.482906: Epoch 6144 +2024-11-22 20:50:53.483033: Current learning rate: 0.00268 +2024-11-22 20:51:13.179821: train_loss -0.8065 +2024-11-22 20:51:13.189547: val_loss -0.7854 +2024-11-22 20:51:13.189691: Pseudo dice [0.848] +2024-11-22 20:51:13.189801: Epoch time: 19.7 s +2024-11-22 20:51:14.368990: +2024-11-22 20:51:14.370327: Epoch 6145 +2024-11-22 20:51:14.370476: Current learning rate: 0.00268 +2024-11-22 20:51:33.585231: train_loss -0.8035 +2024-11-22 20:51:33.587394: val_loss -0.7836 +2024-11-22 20:51:33.587502: Pseudo dice [0.8556] +2024-11-22 20:51:33.587603: Epoch time: 19.22 s +2024-11-22 20:51:34.465632: +2024-11-22 20:51:34.465843: Epoch 6146 +2024-11-22 20:51:34.465968: Current learning rate: 0.00268 +2024-11-22 20:51:53.705453: train_loss -0.7987 +2024-11-22 20:51:53.708114: val_loss -0.7441 +2024-11-22 20:51:53.708235: Pseudo dice [0.8633] +2024-11-22 20:51:53.708339: Epoch time: 19.24 s +2024-11-22 20:51:55.106336: +2024-11-22 20:51:55.108043: Epoch 6147 +2024-11-22 20:51:55.108170: Current learning rate: 0.00268 +2024-11-22 20:52:14.672797: train_loss -0.8002 +2024-11-22 20:52:14.678943: val_loss -0.7701 +2024-11-22 20:52:14.679091: Pseudo dice [0.8496] +2024-11-22 20:52:14.679185: Epoch time: 19.57 s +2024-11-22 20:52:15.722802: +2024-11-22 20:52:15.723639: Epoch 6148 +2024-11-22 20:52:15.723767: Current learning rate: 0.00268 +2024-11-22 20:52:35.563204: train_loss -0.8009 +2024-11-22 20:52:35.569433: val_loss -0.7659 +2024-11-22 20:52:35.569579: Pseudo dice [0.8476] +2024-11-22 20:52:35.569775: Epoch time: 19.84 s +2024-11-22 20:52:36.579815: +2024-11-22 20:52:36.581526: Epoch 6149 +2024-11-22 20:52:36.581651: Current learning rate: 0.00268 +2024-11-22 20:52:55.688450: train_loss -0.8081 +2024-11-22 20:52:55.692022: val_loss -0.7941 +2024-11-22 20:52:55.692162: Pseudo dice [0.8641] +2024-11-22 20:52:55.692320: Epoch time: 19.11 s +2024-11-22 20:52:56.963181: +2024-11-22 20:52:56.965035: Epoch 6150 +2024-11-22 20:52:56.965185: Current learning rate: 0.00268 +2024-11-22 20:53:16.170941: train_loss -0.807 +2024-11-22 20:53:16.189726: val_loss -0.7825 +2024-11-22 20:53:16.189861: Pseudo dice [0.8556] +2024-11-22 20:53:16.189956: Epoch time: 19.21 s +2024-11-22 20:53:17.092952: +2024-11-22 20:53:17.093675: Epoch 6151 +2024-11-22 20:53:17.093811: Current learning rate: 0.00268 +2024-11-22 20:53:37.117133: train_loss -0.8109 +2024-11-22 20:53:37.119633: val_loss -0.7669 +2024-11-22 20:53:37.119750: Pseudo dice [0.8642] +2024-11-22 20:53:37.119880: Epoch time: 20.03 s +2024-11-22 20:53:38.240683: +2024-11-22 20:53:38.241922: Epoch 6152 +2024-11-22 20:53:38.242043: Current learning rate: 0.00267 +2024-11-22 20:53:59.751726: train_loss -0.802 +2024-11-22 20:53:59.753729: val_loss -0.7755 +2024-11-22 20:53:59.753828: Pseudo dice [0.8583] +2024-11-22 20:53:59.753914: Epoch time: 21.51 s +2024-11-22 20:54:00.618228: +2024-11-22 20:54:00.618787: Epoch 6153 +2024-11-22 20:54:00.618915: Current learning rate: 0.00267 +2024-11-22 20:54:19.466359: train_loss -0.8075 +2024-11-22 20:54:19.473767: val_loss -0.7662 +2024-11-22 20:54:19.473922: Pseudo dice [0.8496] +2024-11-22 20:54:19.474014: Epoch time: 18.85 s +2024-11-22 20:54:20.497178: +2024-11-22 20:54:20.497723: Epoch 6154 +2024-11-22 20:54:20.497842: Current learning rate: 0.00267 +2024-11-22 20:54:39.773803: train_loss -0.7971 +2024-11-22 20:54:39.779349: val_loss -0.7612 +2024-11-22 20:54:39.779476: Pseudo dice [0.8575] +2024-11-22 20:54:39.779577: Epoch time: 19.28 s +2024-11-22 20:54:40.700932: +2024-11-22 20:54:40.701983: Epoch 6155 +2024-11-22 20:54:40.702123: Current learning rate: 0.00267 +2024-11-22 20:55:00.589331: train_loss -0.8027 +2024-11-22 20:55:00.596804: val_loss -0.7991 +2024-11-22 20:55:00.596935: Pseudo dice [0.869] +2024-11-22 20:55:00.597033: Epoch time: 19.89 s +2024-11-22 20:55:01.650250: +2024-11-22 20:55:01.651875: Epoch 6156 +2024-11-22 20:55:01.652006: Current learning rate: 0.00267 +2024-11-22 20:55:20.683254: train_loss -0.8051 +2024-11-22 20:55:20.691772: val_loss -0.7888 +2024-11-22 20:55:20.691925: Pseudo dice [0.8529] +2024-11-22 20:55:20.692034: Epoch time: 19.03 s +2024-11-22 20:55:21.585301: +2024-11-22 20:55:21.585511: Epoch 6157 +2024-11-22 20:55:21.585638: Current learning rate: 0.00267 +2024-11-22 20:55:40.844085: train_loss -0.8167 +2024-11-22 20:55:40.851270: val_loss -0.7767 +2024-11-22 20:55:40.851448: Pseudo dice [0.8689] +2024-11-22 20:55:40.851563: Epoch time: 19.26 s +2024-11-22 20:55:42.138142: +2024-11-22 20:55:42.139659: Epoch 6158 +2024-11-22 20:55:42.139782: Current learning rate: 0.00267 +2024-11-22 20:56:01.757771: train_loss -0.8057 +2024-11-22 20:56:01.771699: val_loss -0.7904 +2024-11-22 20:56:01.771821: Pseudo dice [0.8561] +2024-11-22 20:56:01.771916: Epoch time: 19.62 s +2024-11-22 20:56:02.655298: +2024-11-22 20:56:02.655493: Epoch 6159 +2024-11-22 20:56:02.655608: Current learning rate: 0.00267 +2024-11-22 20:56:21.849700: train_loss -0.8075 +2024-11-22 20:56:21.854778: val_loss -0.7863 +2024-11-22 20:56:21.854897: Pseudo dice [0.8527] +2024-11-22 20:56:21.854987: Epoch time: 19.2 s +2024-11-22 20:56:22.758010: +2024-11-22 20:56:22.758232: Epoch 6160 +2024-11-22 20:56:22.758349: Current learning rate: 0.00266 +2024-11-22 20:56:42.092533: train_loss -0.8077 +2024-11-22 20:56:42.095947: val_loss -0.7463 +2024-11-22 20:56:42.096083: Pseudo dice [0.8568] +2024-11-22 20:56:42.096166: Epoch time: 19.34 s +2024-11-22 20:56:43.024642: +2024-11-22 20:56:43.024867: Epoch 6161 +2024-11-22 20:56:43.025002: Current learning rate: 0.00266 +2024-11-22 20:57:01.746416: train_loss -0.8082 +2024-11-22 20:57:01.751116: val_loss -0.7832 +2024-11-22 20:57:01.751265: Pseudo dice [0.864] +2024-11-22 20:57:01.751365: Epoch time: 18.72 s +2024-11-22 20:57:02.651099: +2024-11-22 20:57:02.651330: Epoch 6162 +2024-11-22 20:57:02.651452: Current learning rate: 0.00266 +2024-11-22 20:57:21.961235: train_loss -0.7964 +2024-11-22 20:57:21.969226: val_loss -0.7509 +2024-11-22 20:57:21.969376: Pseudo dice [0.8614] +2024-11-22 20:57:21.969488: Epoch time: 19.31 s +2024-11-22 20:57:22.901643: +2024-11-22 20:57:22.901838: Epoch 6163 +2024-11-22 20:57:22.901950: Current learning rate: 0.00266 +2024-11-22 20:57:41.593757: train_loss -0.801 +2024-11-22 20:57:41.597339: val_loss -0.7801 +2024-11-22 20:57:41.597469: Pseudo dice [0.8632] +2024-11-22 20:57:41.597559: Epoch time: 18.69 s +2024-11-22 20:57:42.484696: +2024-11-22 20:57:42.484892: Epoch 6164 +2024-11-22 20:57:42.485021: Current learning rate: 0.00266 +2024-11-22 20:58:01.246088: train_loss -0.8074 +2024-11-22 20:58:01.246319: val_loss -0.7844 +2024-11-22 20:58:01.246409: Pseudo dice [0.8571] +2024-11-22 20:58:01.248683: Epoch time: 18.76 s +2024-11-22 20:58:02.182000: +2024-11-22 20:58:02.182230: Epoch 6165 +2024-11-22 20:58:02.182345: Current learning rate: 0.00266 +2024-11-22 20:58:20.579087: train_loss -0.8114 +2024-11-22 20:58:20.583561: val_loss -0.7781 +2024-11-22 20:58:20.596485: Pseudo dice [0.8508] +2024-11-22 20:58:20.596620: Epoch time: 18.4 s +2024-11-22 20:58:21.671178: +2024-11-22 20:58:21.691674: Epoch 6166 +2024-11-22 20:58:21.691811: Current learning rate: 0.00266 +2024-11-22 20:58:40.245533: train_loss -0.8133 +2024-11-22 20:58:40.246096: val_loss -0.7859 +2024-11-22 20:58:40.246219: Pseudo dice [0.8521] +2024-11-22 20:58:40.246319: Epoch time: 18.58 s +2024-11-22 20:58:41.122304: +2024-11-22 20:58:41.122511: Epoch 6167 +2024-11-22 20:58:41.122628: Current learning rate: 0.00266 +2024-11-22 20:59:00.130633: train_loss -0.8101 +2024-11-22 20:59:00.152333: val_loss -0.8022 +2024-11-22 20:59:00.152488: Pseudo dice [0.8572] +2024-11-22 20:59:00.152577: Epoch time: 19.01 s +2024-11-22 20:59:01.156841: +2024-11-22 20:59:01.158516: Epoch 6168 +2024-11-22 20:59:01.158652: Current learning rate: 0.00265 +2024-11-22 20:59:19.634362: train_loss -0.813 +2024-11-22 20:59:19.638343: val_loss -0.7624 +2024-11-22 20:59:19.638479: Pseudo dice [0.8663] +2024-11-22 20:59:19.638576: Epoch time: 18.48 s +2024-11-22 20:59:20.937386: +2024-11-22 20:59:20.937945: Epoch 6169 +2024-11-22 20:59:20.938080: Current learning rate: 0.00265 +2024-11-22 20:59:40.041594: train_loss -0.813 +2024-11-22 20:59:40.050142: val_loss -0.7868 +2024-11-22 20:59:40.050330: Pseudo dice [0.8659] +2024-11-22 20:59:40.050427: Epoch time: 19.1 s +2024-11-22 20:59:41.132069: +2024-11-22 20:59:41.133163: Epoch 6170 +2024-11-22 20:59:41.133284: Current learning rate: 0.00265 +2024-11-22 21:00:01.168516: train_loss -0.808 +2024-11-22 21:00:01.169922: val_loss -0.7659 +2024-11-22 21:00:01.170032: Pseudo dice [0.8521] +2024-11-22 21:00:01.170140: Epoch time: 20.04 s +2024-11-22 21:00:02.142980: +2024-11-22 21:00:02.143419: Epoch 6171 +2024-11-22 21:00:02.143543: Current learning rate: 0.00265 +2024-11-22 21:00:21.033586: train_loss -0.8116 +2024-11-22 21:00:21.043875: val_loss -0.7697 +2024-11-22 21:00:21.044017: Pseudo dice [0.8588] +2024-11-22 21:00:21.044131: Epoch time: 18.89 s +2024-11-22 21:00:21.966169: +2024-11-22 21:00:21.966621: Epoch 6172 +2024-11-22 21:00:21.966741: Current learning rate: 0.00265 +2024-11-22 21:00:41.939925: train_loss -0.8002 +2024-11-22 21:00:41.945360: val_loss -0.763 +2024-11-22 21:00:41.945470: Pseudo dice [0.8499] +2024-11-22 21:00:41.945561: Epoch time: 19.97 s +2024-11-22 21:00:42.923331: +2024-11-22 21:00:42.924182: Epoch 6173 +2024-11-22 21:00:42.924310: Current learning rate: 0.00265 +2024-11-22 21:01:01.932451: train_loss -0.7991 +2024-11-22 21:01:01.962657: val_loss -0.8046 +2024-11-22 21:01:01.962826: Pseudo dice [0.8613] +2024-11-22 21:01:01.962962: Epoch time: 19.01 s +2024-11-22 21:01:02.853869: +2024-11-22 21:01:02.855063: Epoch 6174 +2024-11-22 21:01:02.855194: Current learning rate: 0.00265 +2024-11-22 21:01:21.504666: train_loss -0.7971 +2024-11-22 21:01:21.511015: val_loss -0.7472 +2024-11-22 21:01:21.511494: Pseudo dice [0.8486] +2024-11-22 21:01:21.511600: Epoch time: 18.65 s +2024-11-22 21:01:22.468451: +2024-11-22 21:01:22.469203: Epoch 6175 +2024-11-22 21:01:22.469330: Current learning rate: 0.00264 +2024-11-22 21:01:41.287119: train_loss -0.8037 +2024-11-22 21:01:41.289199: val_loss -0.7866 +2024-11-22 21:01:41.289358: Pseudo dice [0.8613] +2024-11-22 21:01:41.289464: Epoch time: 18.82 s +2024-11-22 21:01:42.172511: +2024-11-22 21:01:42.174148: Epoch 6176 +2024-11-22 21:01:42.174284: Current learning rate: 0.00264 +2024-11-22 21:02:02.036008: train_loss -0.8037 +2024-11-22 21:02:02.055166: val_loss -0.7739 +2024-11-22 21:02:02.055374: Pseudo dice [0.8404] +2024-11-22 21:02:02.055475: Epoch time: 19.86 s +2024-11-22 21:02:02.942501: +2024-11-22 21:02:02.944300: Epoch 6177 +2024-11-22 21:02:02.944451: Current learning rate: 0.00264 +2024-11-22 21:02:22.382244: train_loss -0.8141 +2024-11-22 21:02:22.400346: val_loss -0.7845 +2024-11-22 21:02:22.400495: Pseudo dice [0.8631] +2024-11-22 21:02:22.400589: Epoch time: 19.44 s +2024-11-22 21:02:23.345121: +2024-11-22 21:02:23.345546: Epoch 6178 +2024-11-22 21:02:23.345675: Current learning rate: 0.00264 +2024-11-22 21:02:43.437932: train_loss -0.802 +2024-11-22 21:02:43.443192: val_loss -0.7954 +2024-11-22 21:02:43.443327: Pseudo dice [0.8659] +2024-11-22 21:02:43.443627: Epoch time: 20.09 s +2024-11-22 21:02:44.475920: +2024-11-22 21:02:44.476713: Epoch 6179 +2024-11-22 21:02:44.476852: Current learning rate: 0.00264 +2024-11-22 21:03:04.014491: train_loss -0.8003 +2024-11-22 21:03:04.023572: val_loss -0.7835 +2024-11-22 21:03:04.023712: Pseudo dice [0.8585] +2024-11-22 21:03:04.023813: Epoch time: 19.54 s +2024-11-22 21:03:05.446563: +2024-11-22 21:03:05.447926: Epoch 6180 +2024-11-22 21:03:05.448046: Current learning rate: 0.00264 +2024-11-22 21:03:24.831477: train_loss -0.8111 +2024-11-22 21:03:24.845126: val_loss -0.7668 +2024-11-22 21:03:24.845271: Pseudo dice [0.8649] +2024-11-22 21:03:24.845378: Epoch time: 19.39 s +2024-11-22 21:03:25.925376: +2024-11-22 21:03:25.927794: Epoch 6181 +2024-11-22 21:03:25.927957: Current learning rate: 0.00264 +2024-11-22 21:03:46.239748: train_loss -0.8044 +2024-11-22 21:03:46.247591: val_loss -0.7824 +2024-11-22 21:03:46.247712: Pseudo dice [0.8495] +2024-11-22 21:03:46.247807: Epoch time: 20.32 s +2024-11-22 21:03:47.166330: +2024-11-22 21:03:47.167173: Epoch 6182 +2024-11-22 21:03:47.167303: Current learning rate: 0.00264 +2024-11-22 21:04:07.124941: train_loss -0.8047 +2024-11-22 21:04:07.128210: val_loss -0.763 +2024-11-22 21:04:07.128346: Pseudo dice [0.8521] +2024-11-22 21:04:07.128443: Epoch time: 19.96 s +2024-11-22 21:04:08.112788: +2024-11-22 21:04:08.113827: Epoch 6183 +2024-11-22 21:04:08.113969: Current learning rate: 0.00263 +2024-11-22 21:04:27.282909: train_loss -0.8124 +2024-11-22 21:04:27.290891: val_loss -0.7764 +2024-11-22 21:04:27.291016: Pseudo dice [0.8436] +2024-11-22 21:04:27.291131: Epoch time: 19.17 s +2024-11-22 21:04:28.325307: +2024-11-22 21:04:28.326849: Epoch 6184 +2024-11-22 21:04:28.326981: Current learning rate: 0.00263 +2024-11-22 21:04:48.848614: train_loss -0.8073 +2024-11-22 21:04:48.856925: val_loss -0.7826 +2024-11-22 21:04:48.857075: Pseudo dice [0.8635] +2024-11-22 21:04:48.857173: Epoch time: 20.52 s +2024-11-22 21:04:49.801938: +2024-11-22 21:04:49.803057: Epoch 6185 +2024-11-22 21:04:49.803203: Current learning rate: 0.00263 +2024-11-22 21:05:09.729808: train_loss -0.812 +2024-11-22 21:05:09.734275: val_loss -0.7899 +2024-11-22 21:05:09.734422: Pseudo dice [0.8606] +2024-11-22 21:05:09.734522: Epoch time: 19.93 s +2024-11-22 21:05:10.708911: +2024-11-22 21:05:10.709537: Epoch 6186 +2024-11-22 21:05:10.709660: Current learning rate: 0.00263 +2024-11-22 21:05:30.561088: train_loss -0.8049 +2024-11-22 21:05:30.567862: val_loss -0.7942 +2024-11-22 21:05:30.567994: Pseudo dice [0.8636] +2024-11-22 21:05:30.568083: Epoch time: 19.85 s +2024-11-22 21:05:31.438751: +2024-11-22 21:05:31.439692: Epoch 6187 +2024-11-22 21:05:31.439832: Current learning rate: 0.00263 +2024-11-22 21:05:50.689725: train_loss -0.807 +2024-11-22 21:05:50.696251: val_loss -0.7663 +2024-11-22 21:05:50.696398: Pseudo dice [0.8443] +2024-11-22 21:05:50.696504: Epoch time: 19.25 s +2024-11-22 21:05:51.682826: +2024-11-22 21:05:51.684824: Epoch 6188 +2024-11-22 21:05:51.684952: Current learning rate: 0.00263 +2024-11-22 21:06:11.705723: train_loss -0.7966 +2024-11-22 21:06:11.729540: val_loss -0.7901 +2024-11-22 21:06:11.729697: Pseudo dice [0.8612] +2024-11-22 21:06:11.729796: Epoch time: 20.02 s +2024-11-22 21:06:12.777638: +2024-11-22 21:06:12.777863: Epoch 6189 +2024-11-22 21:06:12.777978: Current learning rate: 0.00263 +2024-11-22 21:06:31.490161: train_loss -0.8079 +2024-11-22 21:06:31.495729: val_loss -0.7554 +2024-11-22 21:06:31.495846: Pseudo dice [0.8514] +2024-11-22 21:06:31.495968: Epoch time: 18.71 s +2024-11-22 21:06:32.564898: +2024-11-22 21:06:32.566421: Epoch 6190 +2024-11-22 21:06:32.566565: Current learning rate: 0.00263 +2024-11-22 21:06:51.456544: train_loss -0.8154 +2024-11-22 21:06:51.464535: val_loss -0.7681 +2024-11-22 21:06:51.464674: Pseudo dice [0.846] +2024-11-22 21:06:51.464774: Epoch time: 18.89 s +2024-11-22 21:06:53.037627: +2024-11-22 21:06:53.038811: Epoch 6191 +2024-11-22 21:06:53.038947: Current learning rate: 0.00262 +2024-11-22 21:07:11.561801: train_loss -0.8141 +2024-11-22 21:07:11.568094: val_loss -0.7852 +2024-11-22 21:07:11.568312: Pseudo dice [0.8656] +2024-11-22 21:07:11.568424: Epoch time: 18.52 s +2024-11-22 21:07:12.514966: +2024-11-22 21:07:12.518081: Epoch 6192 +2024-11-22 21:07:12.518202: Current learning rate: 0.00262 +2024-11-22 21:07:32.360841: train_loss -0.8085 +2024-11-22 21:07:32.367761: val_loss -0.761 +2024-11-22 21:07:32.368003: Pseudo dice [0.849] +2024-11-22 21:07:32.368111: Epoch time: 19.85 s +2024-11-22 21:07:33.355114: +2024-11-22 21:07:33.355346: Epoch 6193 +2024-11-22 21:07:33.355483: Current learning rate: 0.00262 +2024-11-22 21:07:52.580973: train_loss -0.8126 +2024-11-22 21:07:52.591777: val_loss -0.7824 +2024-11-22 21:07:52.591913: Pseudo dice [0.8712] +2024-11-22 21:07:52.591998: Epoch time: 19.23 s +2024-11-22 21:07:53.615399: +2024-11-22 21:07:53.616279: Epoch 6194 +2024-11-22 21:07:53.616421: Current learning rate: 0.00262 +2024-11-22 21:08:13.514053: train_loss -0.8119 +2024-11-22 21:08:13.517091: val_loss -0.7882 +2024-11-22 21:08:13.517223: Pseudo dice [0.863] +2024-11-22 21:08:13.517316: Epoch time: 19.9 s +2024-11-22 21:08:14.579278: +2024-11-22 21:08:14.580341: Epoch 6195 +2024-11-22 21:08:14.580493: Current learning rate: 0.00262 +2024-11-22 21:08:33.529473: train_loss -0.8144 +2024-11-22 21:08:33.540101: val_loss -0.773 +2024-11-22 21:08:33.540263: Pseudo dice [0.8649] +2024-11-22 21:08:33.540361: Epoch time: 18.95 s +2024-11-22 21:08:34.444685: +2024-11-22 21:08:34.444889: Epoch 6196 +2024-11-22 21:08:34.445014: Current learning rate: 0.00262 +2024-11-22 21:08:55.475966: train_loss -0.8135 +2024-11-22 21:08:55.483164: val_loss -0.7762 +2024-11-22 21:08:55.483282: Pseudo dice [0.8444] +2024-11-22 21:08:55.483398: Epoch time: 21.03 s +2024-11-22 21:08:56.479789: +2024-11-22 21:08:56.480028: Epoch 6197 +2024-11-22 21:08:56.480176: Current learning rate: 0.00262 +2024-11-22 21:09:16.456349: train_loss -0.8064 +2024-11-22 21:09:16.468937: val_loss -0.7575 +2024-11-22 21:09:16.469086: Pseudo dice [0.8473] +2024-11-22 21:09:16.469184: Epoch time: 19.98 s +2024-11-22 21:09:17.364222: +2024-11-22 21:09:17.365269: Epoch 6198 +2024-11-22 21:09:17.365386: Current learning rate: 0.00261 +2024-11-22 21:09:36.212355: train_loss -0.8097 +2024-11-22 21:09:36.222399: val_loss -0.788 +2024-11-22 21:09:36.222550: Pseudo dice [0.8481] +2024-11-22 21:09:36.222651: Epoch time: 18.85 s +2024-11-22 21:09:37.173742: +2024-11-22 21:09:37.175445: Epoch 6199 +2024-11-22 21:09:37.175581: Current learning rate: 0.00261 +2024-11-22 21:09:56.498167: train_loss -0.8071 +2024-11-22 21:09:56.500242: val_loss -0.785 +2024-11-22 21:09:56.500351: Pseudo dice [0.8566] +2024-11-22 21:09:56.500490: Epoch time: 19.33 s +2024-11-22 21:09:57.702644: +2024-11-22 21:09:57.703323: Epoch 6200 +2024-11-22 21:09:57.703436: Current learning rate: 0.00261 +2024-11-22 21:10:17.308984: train_loss -0.8002 +2024-11-22 21:10:17.311915: val_loss -0.7764 +2024-11-22 21:10:17.312232: Pseudo dice [0.8421] +2024-11-22 21:10:17.312347: Epoch time: 19.61 s +2024-11-22 21:10:18.311506: +2024-11-22 21:10:18.311954: Epoch 6201 +2024-11-22 21:10:18.312084: Current learning rate: 0.00261 +2024-11-22 21:10:38.196541: train_loss -0.8053 +2024-11-22 21:10:38.207409: val_loss -0.7802 +2024-11-22 21:10:38.207533: Pseudo dice [0.8499] +2024-11-22 21:10:38.207626: Epoch time: 19.89 s +2024-11-22 21:10:39.601138: +2024-11-22 21:10:39.602391: Epoch 6202 +2024-11-22 21:10:39.602517: Current learning rate: 0.00261 +2024-11-22 21:10:59.067382: train_loss -0.7999 +2024-11-22 21:10:59.080946: val_loss -0.7662 +2024-11-22 21:10:59.081133: Pseudo dice [0.8556] +2024-11-22 21:10:59.081239: Epoch time: 19.47 s +2024-11-22 21:11:00.180273: +2024-11-22 21:11:00.181007: Epoch 6203 +2024-11-22 21:11:00.181146: Current learning rate: 0.00261 +2024-11-22 21:11:20.193699: train_loss -0.8026 +2024-11-22 21:11:20.203067: val_loss -0.7844 +2024-11-22 21:11:20.203215: Pseudo dice [0.8538] +2024-11-22 21:11:20.203310: Epoch time: 20.01 s +2024-11-22 21:11:21.104987: +2024-11-22 21:11:21.106024: Epoch 6204 +2024-11-22 21:11:21.106361: Current learning rate: 0.00261 +2024-11-22 21:11:40.635512: train_loss -0.8128 +2024-11-22 21:11:40.644252: val_loss -0.7575 +2024-11-22 21:11:40.644381: Pseudo dice [0.842] +2024-11-22 21:11:40.644478: Epoch time: 19.53 s +2024-11-22 21:11:41.758008: +2024-11-22 21:11:41.758723: Epoch 6205 +2024-11-22 21:11:41.758845: Current learning rate: 0.00261 +2024-11-22 21:12:01.436471: train_loss -0.8009 +2024-11-22 21:12:01.443840: val_loss -0.7879 +2024-11-22 21:12:01.443964: Pseudo dice [0.8502] +2024-11-22 21:12:01.444065: Epoch time: 19.68 s +2024-11-22 21:12:02.337176: +2024-11-22 21:12:02.337380: Epoch 6206 +2024-11-22 21:12:02.337501: Current learning rate: 0.0026 +2024-11-22 21:12:21.246181: train_loss -0.8119 +2024-11-22 21:12:21.250173: val_loss -0.7754 +2024-11-22 21:12:21.250305: Pseudo dice [0.8491] +2024-11-22 21:12:21.250429: Epoch time: 18.91 s +2024-11-22 21:12:22.174287: +2024-11-22 21:12:22.175374: Epoch 6207 +2024-11-22 21:12:22.175498: Current learning rate: 0.0026 +2024-11-22 21:12:41.617469: train_loss -0.8003 +2024-11-22 21:12:41.622289: val_loss -0.7801 +2024-11-22 21:12:41.622436: Pseudo dice [0.8441] +2024-11-22 21:12:41.622541: Epoch time: 19.44 s +2024-11-22 21:12:42.696841: +2024-11-22 21:12:42.699186: Epoch 6208 +2024-11-22 21:12:42.699331: Current learning rate: 0.0026 +2024-11-22 21:13:02.362098: train_loss -0.7707 +2024-11-22 21:13:02.366462: val_loss -0.7552 +2024-11-22 21:13:02.366605: Pseudo dice [0.856] +2024-11-22 21:13:02.366700: Epoch time: 19.67 s +2024-11-22 21:13:03.413181: +2024-11-22 21:13:03.414409: Epoch 6209 +2024-11-22 21:13:03.414533: Current learning rate: 0.0026 +2024-11-22 21:13:22.552359: train_loss -0.7928 +2024-11-22 21:13:22.565627: val_loss -0.7704 +2024-11-22 21:13:22.565776: Pseudo dice [0.8507] +2024-11-22 21:13:22.565882: Epoch time: 19.14 s +2024-11-22 21:13:23.681596: +2024-11-22 21:13:23.683773: Epoch 6210 +2024-11-22 21:13:23.683903: Current learning rate: 0.0026 +2024-11-22 21:13:43.390878: train_loss -0.8013 +2024-11-22 21:13:43.395848: val_loss -0.7769 +2024-11-22 21:13:43.395978: Pseudo dice [0.8482] +2024-11-22 21:13:43.396072: Epoch time: 19.71 s +2024-11-22 21:13:44.300523: +2024-11-22 21:13:44.300730: Epoch 6211 +2024-11-22 21:13:44.300855: Current learning rate: 0.0026 +2024-11-22 21:14:05.286494: train_loss -0.8003 +2024-11-22 21:14:05.295563: val_loss -0.7882 +2024-11-22 21:14:05.295705: Pseudo dice [0.8462] +2024-11-22 21:14:05.295806: Epoch time: 20.99 s +2024-11-22 21:14:06.305771: +2024-11-22 21:14:06.306836: Epoch 6212 +2024-11-22 21:14:06.306960: Current learning rate: 0.0026 +2024-11-22 21:14:26.602349: train_loss -0.8072 +2024-11-22 21:14:26.608199: val_loss -0.7396 +2024-11-22 21:14:26.608349: Pseudo dice [0.848] +2024-11-22 21:14:26.608464: Epoch time: 20.3 s +2024-11-22 21:14:27.506117: +2024-11-22 21:14:27.506971: Epoch 6213 +2024-11-22 21:14:27.507092: Current learning rate: 0.00259 +2024-11-22 21:14:46.407476: train_loss -0.8057 +2024-11-22 21:14:46.421358: val_loss -0.7839 +2024-11-22 21:14:46.421488: Pseudo dice [0.8538] +2024-11-22 21:14:46.421586: Epoch time: 18.9 s +2024-11-22 21:14:47.592305: +2024-11-22 21:14:47.601755: Epoch 6214 +2024-11-22 21:14:47.601895: Current learning rate: 0.00259 +2024-11-22 21:15:07.160929: train_loss -0.8041 +2024-11-22 21:15:07.168121: val_loss -0.7662 +2024-11-22 21:15:07.168273: Pseudo dice [0.8537] +2024-11-22 21:15:07.168368: Epoch time: 19.57 s +2024-11-22 21:15:08.202441: +2024-11-22 21:15:08.203781: Epoch 6215 +2024-11-22 21:15:08.203912: Current learning rate: 0.00259 +2024-11-22 21:15:27.678669: train_loss -0.8063 +2024-11-22 21:15:27.690190: val_loss -0.7797 +2024-11-22 21:15:27.690336: Pseudo dice [0.8623] +2024-11-22 21:15:27.690438: Epoch time: 19.48 s +2024-11-22 21:15:28.586814: +2024-11-22 21:15:28.587617: Epoch 6216 +2024-11-22 21:15:28.587783: Current learning rate: 0.00259 +2024-11-22 21:15:47.648833: train_loss -0.8099 +2024-11-22 21:15:47.655873: val_loss -0.7901 +2024-11-22 21:15:47.656006: Pseudo dice [0.8546] +2024-11-22 21:15:47.656343: Epoch time: 19.06 s +2024-11-22 21:15:48.625146: +2024-11-22 21:15:48.626055: Epoch 6217 +2024-11-22 21:15:48.626184: Current learning rate: 0.00259 +2024-11-22 21:16:08.103928: train_loss -0.8019 +2024-11-22 21:16:08.111010: val_loss -0.7843 +2024-11-22 21:16:08.111124: Pseudo dice [0.8481] +2024-11-22 21:16:08.111211: Epoch time: 19.48 s +2024-11-22 21:16:09.054016: +2024-11-22 21:16:09.055812: Epoch 6218 +2024-11-22 21:16:09.055938: Current learning rate: 0.00259 +2024-11-22 21:16:27.180424: train_loss -0.7956 +2024-11-22 21:16:27.193526: val_loss -0.7603 +2024-11-22 21:16:27.193642: Pseudo dice [0.8463] +2024-11-22 21:16:27.193735: Epoch time: 18.13 s +2024-11-22 21:16:28.111969: +2024-11-22 21:16:28.113148: Epoch 6219 +2024-11-22 21:16:28.113280: Current learning rate: 0.00259 +2024-11-22 21:16:46.807473: train_loss -0.794 +2024-11-22 21:16:46.815035: val_loss -0.7583 +2024-11-22 21:16:46.815191: Pseudo dice [0.8581] +2024-11-22 21:16:46.815286: Epoch time: 18.7 s +2024-11-22 21:16:47.808934: +2024-11-22 21:16:47.809834: Epoch 6220 +2024-11-22 21:16:47.809962: Current learning rate: 0.00259 +2024-11-22 21:17:06.836622: train_loss -0.8062 +2024-11-22 21:17:06.845959: val_loss -0.7719 +2024-11-22 21:17:06.846119: Pseudo dice [0.8582] +2024-11-22 21:17:06.846220: Epoch time: 19.03 s +2024-11-22 21:17:08.021195: +2024-11-22 21:17:08.021839: Epoch 6221 +2024-11-22 21:17:08.021975: Current learning rate: 0.00258 +2024-11-22 21:17:27.945559: train_loss -0.8036 +2024-11-22 21:17:27.953027: val_loss -0.7833 +2024-11-22 21:17:27.953196: Pseudo dice [0.857] +2024-11-22 21:17:27.953309: Epoch time: 19.93 s +2024-11-22 21:17:29.130467: +2024-11-22 21:17:29.131782: Epoch 6222 +2024-11-22 21:17:29.131922: Current learning rate: 0.00258 +2024-11-22 21:17:48.671451: train_loss -0.8041 +2024-11-22 21:17:48.673544: val_loss -0.7728 +2024-11-22 21:17:48.673648: Pseudo dice [0.8511] +2024-11-22 21:17:48.673779: Epoch time: 19.54 s +2024-11-22 21:17:49.565839: +2024-11-22 21:17:49.566864: Epoch 6223 +2024-11-22 21:17:49.566998: Current learning rate: 0.00258 +2024-11-22 21:18:10.550352: train_loss -0.803 +2024-11-22 21:18:10.572745: val_loss -0.7749 +2024-11-22 21:18:10.572917: Pseudo dice [0.8648] +2024-11-22 21:18:10.573006: Epoch time: 20.99 s +2024-11-22 21:18:11.877464: +2024-11-22 21:18:11.879043: Epoch 6224 +2024-11-22 21:18:11.879191: Current learning rate: 0.00258 +2024-11-22 21:18:30.770025: train_loss -0.8152 +2024-11-22 21:18:30.779823: val_loss -0.7873 +2024-11-22 21:18:30.779975: Pseudo dice [0.8572] +2024-11-22 21:18:30.780076: Epoch time: 18.89 s +2024-11-22 21:18:31.841368: +2024-11-22 21:18:31.842759: Epoch 6225 +2024-11-22 21:18:31.842893: Current learning rate: 0.00258 +2024-11-22 21:18:50.362612: train_loss -0.809 +2024-11-22 21:18:50.367460: val_loss -0.8011 +2024-11-22 21:18:50.367584: Pseudo dice [0.8658] +2024-11-22 21:18:50.367690: Epoch time: 18.52 s +2024-11-22 21:18:51.461600: +2024-11-22 21:18:51.463632: Epoch 6226 +2024-11-22 21:18:51.463763: Current learning rate: 0.00258 +2024-11-22 21:19:11.175791: train_loss -0.8103 +2024-11-22 21:19:11.183277: val_loss -0.7827 +2024-11-22 21:19:11.183436: Pseudo dice [0.8544] +2024-11-22 21:19:11.183537: Epoch time: 19.72 s +2024-11-22 21:19:12.098774: +2024-11-22 21:19:12.100804: Epoch 6227 +2024-11-22 21:19:12.100939: Current learning rate: 0.00258 +2024-11-22 21:19:31.956469: train_loss -0.8102 +2024-11-22 21:19:31.970317: val_loss -0.7856 +2024-11-22 21:19:31.970461: Pseudo dice [0.8504] +2024-11-22 21:19:31.970569: Epoch time: 19.86 s +2024-11-22 21:19:32.869198: +2024-11-22 21:19:32.870600: Epoch 6228 +2024-11-22 21:19:32.870744: Current learning rate: 0.00258 +2024-11-22 21:19:52.689844: train_loss -0.8082 +2024-11-22 21:19:52.698565: val_loss -0.775 +2024-11-22 21:19:52.705733: Pseudo dice [0.8627] +2024-11-22 21:19:52.705870: Epoch time: 19.82 s +2024-11-22 21:19:53.620632: +2024-11-22 21:19:53.622627: Epoch 6229 +2024-11-22 21:19:53.622778: Current learning rate: 0.00257 +2024-11-22 21:20:12.517383: train_loss -0.8182 +2024-11-22 21:20:12.525720: val_loss -0.7821 +2024-11-22 21:20:12.525875: Pseudo dice [0.848] +2024-11-22 21:20:12.525995: Epoch time: 18.9 s +2024-11-22 21:20:13.479372: +2024-11-22 21:20:13.479585: Epoch 6230 +2024-11-22 21:20:13.479726: Current learning rate: 0.00257 +2024-11-22 21:20:32.099880: train_loss -0.8122 +2024-11-22 21:20:32.100416: val_loss -0.7746 +2024-11-22 21:20:32.100498: Pseudo dice [0.8533] +2024-11-22 21:20:32.100593: Epoch time: 18.62 s +2024-11-22 21:20:33.042946: +2024-11-22 21:20:33.043159: Epoch 6231 +2024-11-22 21:20:33.043293: Current learning rate: 0.00257 +2024-11-22 21:20:52.234043: train_loss -0.8042 +2024-11-22 21:20:52.236624: val_loss -0.7713 +2024-11-22 21:20:52.236766: Pseudo dice [0.8497] +2024-11-22 21:20:52.236879: Epoch time: 19.19 s +2024-11-22 21:20:53.396195: +2024-11-22 21:20:53.396422: Epoch 6232 +2024-11-22 21:20:53.396551: Current learning rate: 0.00257 +2024-11-22 21:21:12.861590: train_loss -0.8049 +2024-11-22 21:21:12.864810: val_loss -0.7754 +2024-11-22 21:21:12.864952: Pseudo dice [0.8522] +2024-11-22 21:21:12.865046: Epoch time: 19.47 s +2024-11-22 21:21:14.230957: +2024-11-22 21:21:14.231235: Epoch 6233 +2024-11-22 21:21:14.231374: Current learning rate: 0.00257 +2024-11-22 21:21:32.781947: train_loss -0.8052 +2024-11-22 21:21:32.783370: val_loss -0.7574 +2024-11-22 21:21:32.783496: Pseudo dice [0.8426] +2024-11-22 21:21:32.783596: Epoch time: 18.55 s +2024-11-22 21:21:33.713722: +2024-11-22 21:21:33.713954: Epoch 6234 +2024-11-22 21:21:33.714086: Current learning rate: 0.00257 +2024-11-22 21:21:52.357839: train_loss -0.811 +2024-11-22 21:21:52.362766: val_loss -0.7854 +2024-11-22 21:21:52.362910: Pseudo dice [0.8597] +2024-11-22 21:21:52.363013: Epoch time: 18.64 s +2024-11-22 21:21:53.647834: +2024-11-22 21:21:53.648066: Epoch 6235 +2024-11-22 21:21:53.648188: Current learning rate: 0.00257 +2024-11-22 21:22:14.281582: train_loss -0.8065 +2024-11-22 21:22:14.282053: val_loss -0.7766 +2024-11-22 21:22:14.282144: Pseudo dice [0.855] +2024-11-22 21:22:14.282242: Epoch time: 20.63 s +2024-11-22 21:22:15.166304: +2024-11-22 21:22:15.166541: Epoch 6236 +2024-11-22 21:22:15.166661: Current learning rate: 0.00256 +2024-11-22 21:22:34.506942: train_loss -0.8019 +2024-11-22 21:22:34.508078: val_loss -0.7698 +2024-11-22 21:22:34.508211: Pseudo dice [0.851] +2024-11-22 21:22:34.508316: Epoch time: 19.34 s +2024-11-22 21:22:35.466208: +2024-11-22 21:22:35.466446: Epoch 6237 +2024-11-22 21:22:35.466561: Current learning rate: 0.00256 +2024-11-22 21:22:54.671308: train_loss -0.8067 +2024-11-22 21:22:54.675615: val_loss -0.7632 +2024-11-22 21:22:54.675745: Pseudo dice [0.8491] +2024-11-22 21:22:54.675833: Epoch time: 19.21 s +2024-11-22 21:22:55.697823: +2024-11-22 21:22:55.698030: Epoch 6238 +2024-11-22 21:22:55.698148: Current learning rate: 0.00256 +2024-11-22 21:23:13.781322: train_loss -0.8071 +2024-11-22 21:23:13.789005: val_loss -0.7634 +2024-11-22 21:23:13.789161: Pseudo dice [0.8426] +2024-11-22 21:23:13.789248: Epoch time: 18.08 s +2024-11-22 21:23:14.690987: +2024-11-22 21:23:14.692820: Epoch 6239 +2024-11-22 21:23:14.692953: Current learning rate: 0.00256 +2024-11-22 21:23:35.104374: train_loss -0.7938 +2024-11-22 21:23:35.112099: val_loss -0.7745 +2024-11-22 21:23:35.112287: Pseudo dice [0.8445] +2024-11-22 21:23:35.112392: Epoch time: 20.41 s +2024-11-22 21:23:35.996843: +2024-11-22 21:23:35.998572: Epoch 6240 +2024-11-22 21:23:35.998699: Current learning rate: 0.00256 +2024-11-22 21:23:54.288564: train_loss -0.8015 +2024-11-22 21:23:54.300998: val_loss -0.7805 +2024-11-22 21:23:54.301154: Pseudo dice [0.8542] +2024-11-22 21:23:54.301409: Epoch time: 18.29 s +2024-11-22 21:23:55.307951: +2024-11-22 21:23:55.308796: Epoch 6241 +2024-11-22 21:23:55.308935: Current learning rate: 0.00256 +2024-11-22 21:24:14.108629: train_loss -0.8029 +2024-11-22 21:24:14.117768: val_loss -0.7872 +2024-11-22 21:24:14.117898: Pseudo dice [0.8621] +2024-11-22 21:24:14.118148: Epoch time: 18.8 s +2024-11-22 21:24:15.197131: +2024-11-22 21:24:15.197628: Epoch 6242 +2024-11-22 21:24:15.197756: Current learning rate: 0.00256 +2024-11-22 21:24:33.634142: train_loss -0.8061 +2024-11-22 21:24:33.637873: val_loss -0.7829 +2024-11-22 21:24:33.638007: Pseudo dice [0.8464] +2024-11-22 21:24:33.638202: Epoch time: 18.44 s +2024-11-22 21:24:34.657224: +2024-11-22 21:24:34.658605: Epoch 6243 +2024-11-22 21:24:34.658741: Current learning rate: 0.00256 +2024-11-22 21:24:53.644229: train_loss -0.806 +2024-11-22 21:24:53.651223: val_loss -0.7643 +2024-11-22 21:24:53.651335: Pseudo dice [0.8434] +2024-11-22 21:24:53.651432: Epoch time: 18.99 s +2024-11-22 21:24:54.641718: +2024-11-22 21:24:54.642494: Epoch 6244 +2024-11-22 21:24:54.642630: Current learning rate: 0.00255 +2024-11-22 21:25:13.865375: train_loss -0.808 +2024-11-22 21:25:13.873986: val_loss -0.7917 +2024-11-22 21:25:13.874141: Pseudo dice [0.8705] +2024-11-22 21:25:13.874246: Epoch time: 19.22 s +2024-11-22 21:25:14.869974: +2024-11-22 21:25:14.871565: Epoch 6245 +2024-11-22 21:25:14.871697: Current learning rate: 0.00255 +2024-11-22 21:25:34.276074: train_loss -0.8094 +2024-11-22 21:25:34.294044: val_loss -0.7886 +2024-11-22 21:25:34.294198: Pseudo dice [0.8527] +2024-11-22 21:25:34.294302: Epoch time: 19.41 s +2024-11-22 21:25:35.185909: +2024-11-22 21:25:35.187405: Epoch 6246 +2024-11-22 21:25:35.187549: Current learning rate: 0.00255 +2024-11-22 21:25:54.660025: train_loss -0.8035 +2024-11-22 21:25:54.662626: val_loss -0.7831 +2024-11-22 21:25:54.662756: Pseudo dice [0.863] +2024-11-22 21:25:54.662850: Epoch time: 19.47 s +2024-11-22 21:25:55.542547: +2024-11-22 21:25:55.543138: Epoch 6247 +2024-11-22 21:25:55.543262: Current learning rate: 0.00255 +2024-11-22 21:26:15.219463: train_loss -0.8118 +2024-11-22 21:26:15.231973: val_loss -0.7582 +2024-11-22 21:26:15.232146: Pseudo dice [0.8517] +2024-11-22 21:26:15.232249: Epoch time: 19.68 s +2024-11-22 21:26:16.199631: +2024-11-22 21:26:16.202146: Epoch 6248 +2024-11-22 21:26:16.202266: Current learning rate: 0.00255 +2024-11-22 21:26:36.826240: train_loss -0.8067 +2024-11-22 21:26:36.833266: val_loss -0.7843 +2024-11-22 21:26:36.833488: Pseudo dice [0.8621] +2024-11-22 21:26:36.833600: Epoch time: 20.63 s +2024-11-22 21:26:37.725936: +2024-11-22 21:26:37.726738: Epoch 6249 +2024-11-22 21:26:37.726872: Current learning rate: 0.00255 +2024-11-22 21:26:57.324583: train_loss -0.8058 +2024-11-22 21:26:57.331800: val_loss -0.7697 +2024-11-22 21:26:57.331952: Pseudo dice [0.838] +2024-11-22 21:26:57.332056: Epoch time: 19.6 s +2024-11-22 21:26:58.552573: +2024-11-22 21:26:58.553886: Epoch 6250 +2024-11-22 21:26:58.554007: Current learning rate: 0.00255 +2024-11-22 21:27:17.233953: train_loss -0.8125 +2024-11-22 21:27:17.239359: val_loss -0.785 +2024-11-22 21:27:17.239490: Pseudo dice [0.8653] +2024-11-22 21:27:17.239660: Epoch time: 18.68 s +2024-11-22 21:27:18.511501: +2024-11-22 21:27:18.513115: Epoch 6251 +2024-11-22 21:27:18.513258: Current learning rate: 0.00255 +2024-11-22 21:27:38.000455: train_loss -0.8046 +2024-11-22 21:27:38.007468: val_loss -0.7923 +2024-11-22 21:27:38.007594: Pseudo dice [0.8551] +2024-11-22 21:27:38.007695: Epoch time: 19.49 s +2024-11-22 21:27:39.073495: +2024-11-22 21:27:39.074644: Epoch 6252 +2024-11-22 21:27:39.074789: Current learning rate: 0.00254 +2024-11-22 21:27:58.759277: train_loss -0.809 +2024-11-22 21:27:58.764023: val_loss -0.7743 +2024-11-22 21:27:58.764198: Pseudo dice [0.8493] +2024-11-22 21:27:58.764305: Epoch time: 19.69 s +2024-11-22 21:27:59.724995: +2024-11-22 21:27:59.727026: Epoch 6253 +2024-11-22 21:27:59.727156: Current learning rate: 0.00254 +2024-11-22 21:28:19.537331: train_loss -0.8056 +2024-11-22 21:28:19.539840: val_loss -0.7795 +2024-11-22 21:28:19.539961: Pseudo dice [0.8607] +2024-11-22 21:28:19.540051: Epoch time: 19.81 s +2024-11-22 21:28:20.424323: +2024-11-22 21:28:20.425385: Epoch 6254 +2024-11-22 21:28:20.425516: Current learning rate: 0.00254 +2024-11-22 21:28:39.003342: train_loss -0.8041 +2024-11-22 21:28:39.009834: val_loss -0.7972 +2024-11-22 21:28:39.009990: Pseudo dice [0.8599] +2024-11-22 21:28:39.010238: Epoch time: 18.58 s +2024-11-22 21:28:39.964498: +2024-11-22 21:28:39.965382: Epoch 6255 +2024-11-22 21:28:39.965508: Current learning rate: 0.00254 +2024-11-22 21:29:00.110888: train_loss -0.8046 +2024-11-22 21:29:00.116686: val_loss -0.7737 +2024-11-22 21:29:00.116853: Pseudo dice [0.8474] +2024-11-22 21:29:00.116970: Epoch time: 20.15 s +2024-11-22 21:29:00.995789: +2024-11-22 21:29:00.996887: Epoch 6256 +2024-11-22 21:29:00.997020: Current learning rate: 0.00254 +2024-11-22 21:29:21.310482: train_loss -0.8017 +2024-11-22 21:29:21.317103: val_loss -0.7803 +2024-11-22 21:29:21.317303: Pseudo dice [0.8583] +2024-11-22 21:29:21.317406: Epoch time: 20.32 s +2024-11-22 21:29:22.634433: +2024-11-22 21:29:22.635822: Epoch 6257 +2024-11-22 21:29:22.635972: Current learning rate: 0.00254 +2024-11-22 21:29:42.923642: train_loss -0.8073 +2024-11-22 21:29:42.928542: val_loss -0.7759 +2024-11-22 21:29:42.928685: Pseudo dice [0.8561] +2024-11-22 21:29:42.928787: Epoch time: 20.29 s +2024-11-22 21:29:43.819025: +2024-11-22 21:29:43.819573: Epoch 6258 +2024-11-22 21:29:43.819702: Current learning rate: 0.00254 +2024-11-22 21:30:02.998568: train_loss -0.7965 +2024-11-22 21:30:03.012237: val_loss -0.7917 +2024-11-22 21:30:03.012370: Pseudo dice [0.851] +2024-11-22 21:30:03.012484: Epoch time: 19.18 s +2024-11-22 21:30:04.137939: +2024-11-22 21:30:04.139090: Epoch 6259 +2024-11-22 21:30:04.139230: Current learning rate: 0.00253 +2024-11-22 21:30:24.151931: train_loss -0.799 +2024-11-22 21:30:24.157034: val_loss -0.7539 +2024-11-22 21:30:24.157162: Pseudo dice [0.8481] +2024-11-22 21:30:24.157257: Epoch time: 20.01 s +2024-11-22 21:30:25.054487: +2024-11-22 21:30:25.055269: Epoch 6260 +2024-11-22 21:30:25.055404: Current learning rate: 0.00253 +2024-11-22 21:30:43.957894: train_loss -0.8032 +2024-11-22 21:30:43.963092: val_loss -0.7601 +2024-11-22 21:30:43.963216: Pseudo dice [0.8597] +2024-11-22 21:30:43.963305: Epoch time: 18.9 s +2024-11-22 21:30:45.052378: +2024-11-22 21:30:45.052914: Epoch 6261 +2024-11-22 21:30:45.053044: Current learning rate: 0.00253 +2024-11-22 21:31:05.409805: train_loss -0.8035 +2024-11-22 21:31:05.413695: val_loss -0.757 +2024-11-22 21:31:05.413815: Pseudo dice [0.8427] +2024-11-22 21:31:05.413988: Epoch time: 20.36 s +2024-11-22 21:31:06.571784: +2024-11-22 21:31:06.573385: Epoch 6262 +2024-11-22 21:31:06.573530: Current learning rate: 0.00253 +2024-11-22 21:31:26.734815: train_loss -0.8109 +2024-11-22 21:31:26.743050: val_loss -0.7852 +2024-11-22 21:31:26.743202: Pseudo dice [0.8596] +2024-11-22 21:31:26.743298: Epoch time: 20.16 s +2024-11-22 21:31:27.682723: +2024-11-22 21:31:27.684385: Epoch 6263 +2024-11-22 21:31:27.684505: Current learning rate: 0.00253 +2024-11-22 21:31:46.223044: train_loss -0.8109 +2024-11-22 21:31:46.234646: val_loss -0.7933 +2024-11-22 21:31:46.234782: Pseudo dice [0.8645] +2024-11-22 21:31:46.234873: Epoch time: 18.54 s +2024-11-22 21:31:47.273946: +2024-11-22 21:31:47.275072: Epoch 6264 +2024-11-22 21:31:47.275191: Current learning rate: 0.00253 +2024-11-22 21:32:06.897692: train_loss -0.8134 +2024-11-22 21:32:06.903998: val_loss -0.7735 +2024-11-22 21:32:06.904137: Pseudo dice [0.855] +2024-11-22 21:32:06.904245: Epoch time: 19.62 s +2024-11-22 21:32:07.922274: +2024-11-22 21:32:07.924104: Epoch 6265 +2024-11-22 21:32:07.924243: Current learning rate: 0.00253 +2024-11-22 21:32:28.366017: train_loss -0.8033 +2024-11-22 21:32:28.368443: val_loss -0.7551 +2024-11-22 21:32:28.368555: Pseudo dice [0.8607] +2024-11-22 21:32:28.368664: Epoch time: 20.44 s +2024-11-22 21:32:29.249987: +2024-11-22 21:32:29.250830: Epoch 6266 +2024-11-22 21:32:29.250954: Current learning rate: 0.00253 +2024-11-22 21:32:49.760773: train_loss -0.8064 +2024-11-22 21:32:49.768893: val_loss -0.7943 +2024-11-22 21:32:49.769023: Pseudo dice [0.8591] +2024-11-22 21:32:49.769136: Epoch time: 20.51 s +2024-11-22 21:32:50.659224: +2024-11-22 21:32:50.661744: Epoch 6267 +2024-11-22 21:32:50.661876: Current learning rate: 0.00252 +2024-11-22 21:33:09.481295: train_loss -0.8083 +2024-11-22 21:33:09.490152: val_loss -0.7573 +2024-11-22 21:33:09.514619: Pseudo dice [0.8524] +2024-11-22 21:33:09.514805: Epoch time: 18.82 s +2024-11-22 21:33:10.817417: +2024-11-22 21:33:10.818356: Epoch 6268 +2024-11-22 21:33:10.818481: Current learning rate: 0.00252 +2024-11-22 21:33:30.041026: train_loss -0.8057 +2024-11-22 21:33:30.047651: val_loss -0.7649 +2024-11-22 21:33:30.047773: Pseudo dice [0.8558] +2024-11-22 21:33:30.047870: Epoch time: 19.22 s +2024-11-22 21:33:31.052799: +2024-11-22 21:33:31.054860: Epoch 6269 +2024-11-22 21:33:31.055022: Current learning rate: 0.00252 +2024-11-22 21:33:50.312322: train_loss -0.8094 +2024-11-22 21:33:50.318190: val_loss -0.7711 +2024-11-22 21:33:50.318352: Pseudo dice [0.8483] +2024-11-22 21:33:50.318462: Epoch time: 19.26 s +2024-11-22 21:33:51.255623: +2024-11-22 21:33:51.256592: Epoch 6270 +2024-11-22 21:33:51.256715: Current learning rate: 0.00252 +2024-11-22 21:34:10.747998: train_loss -0.81 +2024-11-22 21:34:10.761463: val_loss -0.7903 +2024-11-22 21:34:10.761588: Pseudo dice [0.8599] +2024-11-22 21:34:10.761683: Epoch time: 19.49 s +2024-11-22 21:34:11.767688: +2024-11-22 21:34:11.768210: Epoch 6271 +2024-11-22 21:34:11.768338: Current learning rate: 0.00252 +2024-11-22 21:34:31.241384: train_loss -0.8088 +2024-11-22 21:34:31.249998: val_loss -0.7653 +2024-11-22 21:34:31.250134: Pseudo dice [0.8401] +2024-11-22 21:34:31.250240: Epoch time: 19.47 s +2024-11-22 21:34:32.217604: +2024-11-22 21:34:32.218730: Epoch 6272 +2024-11-22 21:34:32.218882: Current learning rate: 0.00252 +2024-11-22 21:34:51.241866: train_loss -0.8037 +2024-11-22 21:34:51.249135: val_loss -0.7896 +2024-11-22 21:34:51.249251: Pseudo dice [0.8592] +2024-11-22 21:34:51.249349: Epoch time: 19.03 s +2024-11-22 21:34:52.193770: +2024-11-22 21:34:52.194505: Epoch 6273 +2024-11-22 21:34:52.194632: Current learning rate: 0.00252 +2024-11-22 21:35:10.101800: train_loss -0.8129 +2024-11-22 21:35:10.110309: val_loss -0.7798 +2024-11-22 21:35:10.110430: Pseudo dice [0.843] +2024-11-22 21:35:10.110528: Epoch time: 17.91 s +2024-11-22 21:35:11.135411: +2024-11-22 21:35:11.136500: Epoch 6274 +2024-11-22 21:35:11.136635: Current learning rate: 0.00252 +2024-11-22 21:35:31.034438: train_loss -0.8148 +2024-11-22 21:35:31.037051: val_loss -0.7632 +2024-11-22 21:35:31.037190: Pseudo dice [0.8468] +2024-11-22 21:35:31.037288: Epoch time: 19.9 s +2024-11-22 21:35:32.090216: +2024-11-22 21:35:32.091845: Epoch 6275 +2024-11-22 21:35:32.091998: Current learning rate: 0.00251 +2024-11-22 21:35:50.114980: train_loss -0.8073 +2024-11-22 21:35:50.117343: val_loss -0.769 +2024-11-22 21:35:50.117480: Pseudo dice [0.8646] +2024-11-22 21:35:50.117572: Epoch time: 18.03 s +2024-11-22 21:35:51.131613: +2024-11-22 21:35:51.132214: Epoch 6276 +2024-11-22 21:35:51.132361: Current learning rate: 0.00251 +2024-11-22 21:36:11.140732: train_loss -0.8031 +2024-11-22 21:36:11.153651: val_loss -0.7706 +2024-11-22 21:36:11.153780: Pseudo dice [0.8473] +2024-11-22 21:36:11.153884: Epoch time: 20.01 s +2024-11-22 21:36:12.050030: +2024-11-22 21:36:12.051153: Epoch 6277 +2024-11-22 21:36:12.051293: Current learning rate: 0.00251 +2024-11-22 21:36:32.120431: train_loss -0.8098 +2024-11-22 21:36:32.124649: val_loss -0.7644 +2024-11-22 21:36:32.124774: Pseudo dice [0.8504] +2024-11-22 21:36:32.124878: Epoch time: 20.07 s +2024-11-22 21:36:33.160235: +2024-11-22 21:36:33.161515: Epoch 6278 +2024-11-22 21:36:33.161644: Current learning rate: 0.00251 +2024-11-22 21:36:52.137940: train_loss -0.8131 +2024-11-22 21:36:52.144418: val_loss -0.7783 +2024-11-22 21:36:52.144585: Pseudo dice [0.8694] +2024-11-22 21:36:52.144689: Epoch time: 18.98 s +2024-11-22 21:36:53.150357: +2024-11-22 21:36:53.151261: Epoch 6279 +2024-11-22 21:36:53.151402: Current learning rate: 0.00251 +2024-11-22 21:37:11.866130: train_loss -0.8119 +2024-11-22 21:37:11.874626: val_loss -0.7774 +2024-11-22 21:37:11.874753: Pseudo dice [0.8595] +2024-11-22 21:37:11.874844: Epoch time: 18.72 s +2024-11-22 21:37:12.783201: +2024-11-22 21:37:12.784493: Epoch 6280 +2024-11-22 21:37:12.784636: Current learning rate: 0.00251 +2024-11-22 21:37:32.483035: train_loss -0.8081 +2024-11-22 21:37:32.485203: val_loss -0.7615 +2024-11-22 21:37:32.485310: Pseudo dice [0.8546] +2024-11-22 21:37:32.485401: Epoch time: 19.7 s +2024-11-22 21:37:33.366910: +2024-11-22 21:37:33.368497: Epoch 6281 +2024-11-22 21:37:33.368628: Current learning rate: 0.00251 +2024-11-22 21:37:52.883616: train_loss -0.8039 +2024-11-22 21:37:52.892052: val_loss -0.7811 +2024-11-22 21:37:52.892211: Pseudo dice [0.8519] +2024-11-22 21:37:52.892302: Epoch time: 19.52 s +2024-11-22 21:37:53.839511: +2024-11-22 21:37:53.840680: Epoch 6282 +2024-11-22 21:37:53.840805: Current learning rate: 0.0025 +2024-11-22 21:38:13.109856: train_loss -0.8132 +2024-11-22 21:38:13.127399: val_loss -0.7861 +2024-11-22 21:38:13.127519: Pseudo dice [0.8556] +2024-11-22 21:38:13.127622: Epoch time: 19.27 s +2024-11-22 21:38:14.141434: +2024-11-22 21:38:14.142804: Epoch 6283 +2024-11-22 21:38:14.142935: Current learning rate: 0.0025 +2024-11-22 21:38:32.931927: train_loss -0.812 +2024-11-22 21:38:32.934245: val_loss -0.7579 +2024-11-22 21:38:32.934373: Pseudo dice [0.8612] +2024-11-22 21:38:32.934469: Epoch time: 18.79 s +2024-11-22 21:38:33.928851: +2024-11-22 21:38:33.930191: Epoch 6284 +2024-11-22 21:38:33.930312: Current learning rate: 0.0025 +2024-11-22 21:38:53.722591: train_loss -0.7999 +2024-11-22 21:38:53.725082: val_loss -0.7492 +2024-11-22 21:38:53.725205: Pseudo dice [0.8454] +2024-11-22 21:38:53.725309: Epoch time: 19.79 s +2024-11-22 21:38:54.815744: +2024-11-22 21:38:54.818020: Epoch 6285 +2024-11-22 21:38:54.818171: Current learning rate: 0.0025 +2024-11-22 21:39:13.279804: train_loss -0.7958 +2024-11-22 21:39:13.286113: val_loss -0.7644 +2024-11-22 21:39:13.286297: Pseudo dice [0.847] +2024-11-22 21:39:13.286393: Epoch time: 18.46 s +2024-11-22 21:39:14.204647: +2024-11-22 21:39:14.206184: Epoch 6286 +2024-11-22 21:39:14.206337: Current learning rate: 0.0025 +2024-11-22 21:39:33.414601: train_loss -0.8156 +2024-11-22 21:39:33.421346: val_loss -0.7787 +2024-11-22 21:39:33.421578: Pseudo dice [0.8624] +2024-11-22 21:39:33.421678: Epoch time: 19.21 s +2024-11-22 21:39:34.551978: +2024-11-22 21:39:34.553062: Epoch 6287 +2024-11-22 21:39:34.553185: Current learning rate: 0.0025 +2024-11-22 21:39:55.474882: train_loss -0.8131 +2024-11-22 21:39:55.480272: val_loss -0.7744 +2024-11-22 21:39:55.480450: Pseudo dice [0.8373] +2024-11-22 21:39:55.480554: Epoch time: 20.92 s +2024-11-22 21:39:56.374617: +2024-11-22 21:39:56.376090: Epoch 6288 +2024-11-22 21:39:56.376215: Current learning rate: 0.0025 +2024-11-22 21:40:16.075410: train_loss -0.806 +2024-11-22 21:40:16.079767: val_loss -0.7628 +2024-11-22 21:40:16.079909: Pseudo dice [0.8468] +2024-11-22 21:40:16.080013: Epoch time: 19.7 s +2024-11-22 21:40:16.960516: +2024-11-22 21:40:16.962054: Epoch 6289 +2024-11-22 21:40:16.962196: Current learning rate: 0.0025 +2024-11-22 21:40:35.021275: train_loss -0.8187 +2024-11-22 21:40:35.023971: val_loss -0.7591 +2024-11-22 21:40:35.024103: Pseudo dice [0.8424] +2024-11-22 21:40:35.024187: Epoch time: 18.06 s +2024-11-22 21:40:36.337785: +2024-11-22 21:40:36.339623: Epoch 6290 +2024-11-22 21:40:36.339755: Current learning rate: 0.00249 +2024-11-22 21:40:55.769992: train_loss -0.8127 +2024-11-22 21:40:55.775951: val_loss -0.7955 +2024-11-22 21:40:55.776107: Pseudo dice [0.8635] +2024-11-22 21:40:55.776226: Epoch time: 19.43 s +2024-11-22 21:40:56.811364: +2024-11-22 21:40:56.813442: Epoch 6291 +2024-11-22 21:40:56.813671: Current learning rate: 0.00249 +2024-11-22 21:41:16.001759: train_loss -0.8094 +2024-11-22 21:41:16.013210: val_loss -0.7871 +2024-11-22 21:41:16.013364: Pseudo dice [0.8539] +2024-11-22 21:41:16.013470: Epoch time: 19.19 s +2024-11-22 21:41:16.932124: +2024-11-22 21:41:16.934048: Epoch 6292 +2024-11-22 21:41:16.934200: Current learning rate: 0.00249 +2024-11-22 21:41:36.863679: train_loss -0.8053 +2024-11-22 21:41:36.888139: val_loss -0.7799 +2024-11-22 21:41:36.888274: Pseudo dice [0.8605] +2024-11-22 21:41:36.888373: Epoch time: 19.93 s +2024-11-22 21:41:37.849445: +2024-11-22 21:41:37.850843: Epoch 6293 +2024-11-22 21:41:37.850962: Current learning rate: 0.00249 +2024-11-22 21:41:57.094329: train_loss -0.8137 +2024-11-22 21:41:57.100407: val_loss -0.7899 +2024-11-22 21:41:57.100523: Pseudo dice [0.8503] +2024-11-22 21:41:57.100604: Epoch time: 19.25 s +2024-11-22 21:41:58.253293: +2024-11-22 21:41:58.255522: Epoch 6294 +2024-11-22 21:41:58.255665: Current learning rate: 0.00249 +2024-11-22 21:42:17.819931: train_loss -0.8095 +2024-11-22 21:42:17.823896: val_loss -0.7637 +2024-11-22 21:42:17.824081: Pseudo dice [0.8669] +2024-11-22 21:42:17.824185: Epoch time: 19.57 s +2024-11-22 21:42:18.912964: +2024-11-22 21:42:18.914499: Epoch 6295 +2024-11-22 21:42:18.914627: Current learning rate: 0.00249 +2024-11-22 21:42:38.917872: train_loss -0.809 +2024-11-22 21:42:38.925359: val_loss -0.7818 +2024-11-22 21:42:38.925515: Pseudo dice [0.8469] +2024-11-22 21:42:38.925664: Epoch time: 20.01 s +2024-11-22 21:42:39.853576: +2024-11-22 21:42:39.855474: Epoch 6296 +2024-11-22 21:42:39.855596: Current learning rate: 0.00249 +2024-11-22 21:42:59.661305: train_loss -0.8107 +2024-11-22 21:42:59.666453: val_loss -0.7816 +2024-11-22 21:42:59.666573: Pseudo dice [0.8539] +2024-11-22 21:42:59.666663: Epoch time: 19.81 s +2024-11-22 21:43:00.577084: +2024-11-22 21:43:00.578623: Epoch 6297 +2024-11-22 21:43:00.578750: Current learning rate: 0.00248 +2024-11-22 21:43:19.673593: train_loss -0.8131 +2024-11-22 21:43:19.687556: val_loss -0.8014 +2024-11-22 21:43:19.687699: Pseudo dice [0.8652] +2024-11-22 21:43:19.687803: Epoch time: 19.1 s +2024-11-22 21:43:20.701316: +2024-11-22 21:43:20.702735: Epoch 6298 +2024-11-22 21:43:20.702869: Current learning rate: 0.00248 +2024-11-22 21:43:39.509881: train_loss -0.8104 +2024-11-22 21:43:39.514555: val_loss -0.7854 +2024-11-22 21:43:39.514678: Pseudo dice [0.8542] +2024-11-22 21:43:39.514776: Epoch time: 18.81 s +2024-11-22 21:43:40.607386: +2024-11-22 21:43:40.609118: Epoch 6299 +2024-11-22 21:43:40.609250: Current learning rate: 0.00248 +2024-11-22 21:43:59.322657: train_loss -0.7952 +2024-11-22 21:43:59.325469: val_loss -0.7851 +2024-11-22 21:43:59.325603: Pseudo dice [0.8661] +2024-11-22 21:43:59.325695: Epoch time: 18.72 s +2024-11-22 21:44:00.759408: +2024-11-22 21:44:00.759622: Epoch 6300 +2024-11-22 21:44:00.759749: Current learning rate: 0.00248 +2024-11-22 21:44:19.484841: train_loss -0.8114 +2024-11-22 21:44:19.485347: val_loss -0.7847 +2024-11-22 21:44:19.485430: Pseudo dice [0.8507] +2024-11-22 21:44:19.485533: Epoch time: 18.73 s +2024-11-22 21:44:20.361655: +2024-11-22 21:44:20.361875: Epoch 6301 +2024-11-22 21:44:20.361993: Current learning rate: 0.00248 +2024-11-22 21:44:38.924345: train_loss -0.8105 +2024-11-22 21:44:38.925406: val_loss -0.7767 +2024-11-22 21:44:38.925537: Pseudo dice [0.8546] +2024-11-22 21:44:38.925644: Epoch time: 18.56 s +2024-11-22 21:44:39.850777: +2024-11-22 21:44:39.850984: Epoch 6302 +2024-11-22 21:44:39.851105: Current learning rate: 0.00248 +2024-11-22 21:44:59.229878: train_loss -0.8122 +2024-11-22 21:44:59.232428: val_loss -0.7788 +2024-11-22 21:44:59.232556: Pseudo dice [0.8522] +2024-11-22 21:44:59.232657: Epoch time: 19.38 s +2024-11-22 21:45:00.124882: +2024-11-22 21:45:00.125113: Epoch 6303 +2024-11-22 21:45:00.125244: Current learning rate: 0.00248 +2024-11-22 21:45:18.887839: train_loss -0.795 +2024-11-22 21:45:18.892873: val_loss -0.7865 +2024-11-22 21:45:18.893023: Pseudo dice [0.8606] +2024-11-22 21:45:18.893122: Epoch time: 18.76 s +2024-11-22 21:45:19.777256: +2024-11-22 21:45:19.777470: Epoch 6304 +2024-11-22 21:45:19.777603: Current learning rate: 0.00248 +2024-11-22 21:45:38.957194: train_loss -0.8036 +2024-11-22 21:45:38.958447: val_loss -0.7422 +2024-11-22 21:45:38.958568: Pseudo dice [0.851] +2024-11-22 21:45:38.958652: Epoch time: 19.18 s +2024-11-22 21:45:39.955548: +2024-11-22 21:45:39.955743: Epoch 6305 +2024-11-22 21:45:39.955863: Current learning rate: 0.00247 +2024-11-22 21:45:58.737859: train_loss -0.8131 +2024-11-22 21:45:58.738958: val_loss -0.7633 +2024-11-22 21:45:58.739105: Pseudo dice [0.858] +2024-11-22 21:45:58.739424: Epoch time: 18.78 s +2024-11-22 21:45:59.798206: +2024-11-22 21:45:59.798401: Epoch 6306 +2024-11-22 21:45:59.798524: Current learning rate: 0.00247 +2024-11-22 21:46:18.418895: train_loss -0.8023 +2024-11-22 21:46:18.426029: val_loss -0.7654 +2024-11-22 21:46:18.426154: Pseudo dice [0.866] +2024-11-22 21:46:18.426260: Epoch time: 18.62 s +2024-11-22 21:46:19.381513: +2024-11-22 21:46:19.381741: Epoch 6307 +2024-11-22 21:46:19.381855: Current learning rate: 0.00247 +2024-11-22 21:46:39.135862: train_loss -0.8107 +2024-11-22 21:46:39.138786: val_loss -0.7867 +2024-11-22 21:46:39.138936: Pseudo dice [0.8617] +2024-11-22 21:46:39.139022: Epoch time: 19.76 s +2024-11-22 21:46:40.147615: +2024-11-22 21:46:40.147828: Epoch 6308 +2024-11-22 21:46:40.147967: Current learning rate: 0.00247 +2024-11-22 21:46:58.723794: train_loss -0.8105 +2024-11-22 21:46:58.743834: val_loss -0.7709 +2024-11-22 21:46:58.743989: Pseudo dice [0.8531] +2024-11-22 21:46:58.744092: Epoch time: 18.58 s +2024-11-22 21:46:59.719559: +2024-11-22 21:46:59.721147: Epoch 6309 +2024-11-22 21:46:59.721282: Current learning rate: 0.00247 +2024-11-22 21:47:19.386494: train_loss -0.8129 +2024-11-22 21:47:19.391407: val_loss -0.7725 +2024-11-22 21:47:19.391537: Pseudo dice [0.8498] +2024-11-22 21:47:19.391634: Epoch time: 19.67 s +2024-11-22 21:47:20.473604: +2024-11-22 21:47:20.474549: Epoch 6310 +2024-11-22 21:47:20.474686: Current learning rate: 0.00247 +2024-11-22 21:47:39.432673: train_loss -0.8106 +2024-11-22 21:47:39.440888: val_loss -0.7536 +2024-11-22 21:47:39.441087: Pseudo dice [0.8447] +2024-11-22 21:47:39.441177: Epoch time: 18.96 s +2024-11-22 21:47:40.514118: +2024-11-22 21:47:40.515557: Epoch 6311 +2024-11-22 21:47:40.515689: Current learning rate: 0.00247 +2024-11-22 21:48:00.242302: train_loss -0.804 +2024-11-22 21:48:00.248494: val_loss -0.7867 +2024-11-22 21:48:00.248665: Pseudo dice [0.8436] +2024-11-22 21:48:00.248763: Epoch time: 19.73 s +2024-11-22 21:48:01.671350: +2024-11-22 21:48:01.672875: Epoch 6312 +2024-11-22 21:48:01.673016: Current learning rate: 0.00247 +2024-11-22 21:48:21.641431: train_loss -0.8135 +2024-11-22 21:48:21.658463: val_loss -0.7824 +2024-11-22 21:48:21.658606: Pseudo dice [0.8609] +2024-11-22 21:48:21.658695: Epoch time: 19.97 s +2024-11-22 21:48:22.943885: +2024-11-22 21:48:22.945652: Epoch 6313 +2024-11-22 21:48:22.945783: Current learning rate: 0.00246 +2024-11-22 21:48:42.736400: train_loss -0.809 +2024-11-22 21:48:42.742722: val_loss -0.7901 +2024-11-22 21:48:42.742871: Pseudo dice [0.8591] +2024-11-22 21:48:42.742965: Epoch time: 19.79 s +2024-11-22 21:48:43.663965: +2024-11-22 21:48:43.664587: Epoch 6314 +2024-11-22 21:48:43.664723: Current learning rate: 0.00246 +2024-11-22 21:49:02.684661: train_loss -0.816 +2024-11-22 21:49:02.707549: val_loss -0.7687 +2024-11-22 21:49:02.707681: Pseudo dice [0.8446] +2024-11-22 21:49:02.707779: Epoch time: 19.02 s +2024-11-22 21:49:03.674434: +2024-11-22 21:49:03.675291: Epoch 6315 +2024-11-22 21:49:03.675408: Current learning rate: 0.00246 +2024-11-22 21:49:23.095554: train_loss -0.8166 +2024-11-22 21:49:23.101471: val_loss -0.7612 +2024-11-22 21:49:23.101602: Pseudo dice [0.8512] +2024-11-22 21:49:23.101716: Epoch time: 19.42 s +2024-11-22 21:49:24.091684: +2024-11-22 21:49:24.092506: Epoch 6316 +2024-11-22 21:49:24.092624: Current learning rate: 0.00246 +2024-11-22 21:49:43.445586: train_loss -0.8089 +2024-11-22 21:49:43.459547: val_loss -0.8005 +2024-11-22 21:49:43.459716: Pseudo dice [0.8572] +2024-11-22 21:49:43.459817: Epoch time: 19.35 s +2024-11-22 21:49:44.501826: +2024-11-22 21:49:44.502603: Epoch 6317 +2024-11-22 21:49:44.502743: Current learning rate: 0.00246 +2024-11-22 21:50:04.304874: train_loss -0.8119 +2024-11-22 21:50:04.308801: val_loss -0.7765 +2024-11-22 21:50:04.308934: Pseudo dice [0.8668] +2024-11-22 21:50:04.309021: Epoch time: 19.8 s +2024-11-22 21:50:05.272768: +2024-11-22 21:50:05.273624: Epoch 6318 +2024-11-22 21:50:05.273754: Current learning rate: 0.00246 +2024-11-22 21:50:24.454667: train_loss -0.8117 +2024-11-22 21:50:24.476181: val_loss -0.7717 +2024-11-22 21:50:24.476341: Pseudo dice [0.8511] +2024-11-22 21:50:24.476439: Epoch time: 19.18 s +2024-11-22 21:50:25.454563: +2024-11-22 21:50:25.455400: Epoch 6319 +2024-11-22 21:50:25.455530: Current learning rate: 0.00246 +2024-11-22 21:50:45.419616: train_loss -0.8151 +2024-11-22 21:50:45.428074: val_loss -0.7557 +2024-11-22 21:50:45.428295: Pseudo dice [0.8583] +2024-11-22 21:50:45.428388: Epoch time: 19.97 s +2024-11-22 21:50:46.320515: +2024-11-22 21:50:46.321167: Epoch 6320 +2024-11-22 21:50:46.321301: Current learning rate: 0.00245 +2024-11-22 21:51:06.513181: train_loss -0.801 +2024-11-22 21:51:06.521808: val_loss -0.7664 +2024-11-22 21:51:06.522031: Pseudo dice [0.8549] +2024-11-22 21:51:06.522144: Epoch time: 20.19 s +2024-11-22 21:51:07.564786: +2024-11-22 21:51:07.566597: Epoch 6321 +2024-11-22 21:51:07.566735: Current learning rate: 0.00245 +2024-11-22 21:51:26.395495: train_loss -0.8022 +2024-11-22 21:51:26.407838: val_loss -0.7734 +2024-11-22 21:51:26.407957: Pseudo dice [0.8623] +2024-11-22 21:51:26.408076: Epoch time: 18.83 s +2024-11-22 21:51:27.292709: +2024-11-22 21:51:27.293173: Epoch 6322 +2024-11-22 21:51:27.293311: Current learning rate: 0.00245 +2024-11-22 21:51:46.585812: train_loss -0.8109 +2024-11-22 21:51:46.590015: val_loss -0.7737 +2024-11-22 21:51:46.590246: Pseudo dice [0.8537] +2024-11-22 21:51:46.590337: Epoch time: 19.29 s +2024-11-22 21:51:47.652956: +2024-11-22 21:51:47.654065: Epoch 6323 +2024-11-22 21:51:47.654213: Current learning rate: 0.00245 +2024-11-22 21:52:07.850633: train_loss -0.808 +2024-11-22 21:52:07.859713: val_loss -0.7683 +2024-11-22 21:52:07.859844: Pseudo dice [0.8509] +2024-11-22 21:52:07.859946: Epoch time: 20.2 s +2024-11-22 21:52:08.930572: +2024-11-22 21:52:08.932164: Epoch 6324 +2024-11-22 21:52:08.932305: Current learning rate: 0.00245 +2024-11-22 21:52:28.844705: train_loss -0.8094 +2024-11-22 21:52:28.849941: val_loss -0.7674 +2024-11-22 21:52:28.850087: Pseudo dice [0.8521] +2024-11-22 21:52:28.850256: Epoch time: 19.91 s +2024-11-22 21:52:29.764200: +2024-11-22 21:52:29.767637: Epoch 6325 +2024-11-22 21:52:29.767782: Current learning rate: 0.00245 +2024-11-22 21:52:49.707855: train_loss -0.7991 +2024-11-22 21:52:49.710506: val_loss -0.7943 +2024-11-22 21:52:49.710629: Pseudo dice [0.8629] +2024-11-22 21:52:49.710731: Epoch time: 19.94 s +2024-11-22 21:52:50.598614: +2024-11-22 21:52:50.599428: Epoch 6326 +2024-11-22 21:52:50.599572: Current learning rate: 0.00245 +2024-11-22 21:53:10.318330: train_loss -0.8048 +2024-11-22 21:53:10.325129: val_loss -0.7989 +2024-11-22 21:53:10.325316: Pseudo dice [0.8554] +2024-11-22 21:53:10.325426: Epoch time: 19.72 s +2024-11-22 21:53:11.400857: +2024-11-22 21:53:11.402444: Epoch 6327 +2024-11-22 21:53:11.402572: Current learning rate: 0.00245 +2024-11-22 21:53:31.071864: train_loss -0.8149 +2024-11-22 21:53:31.081703: val_loss -0.7545 +2024-11-22 21:53:31.081832: Pseudo dice [0.8456] +2024-11-22 21:53:31.081938: Epoch time: 19.67 s +2024-11-22 21:53:32.038646: +2024-11-22 21:53:32.039479: Epoch 6328 +2024-11-22 21:53:32.039603: Current learning rate: 0.00244 +2024-11-22 21:53:51.848868: train_loss -0.8107 +2024-11-22 21:53:51.872896: val_loss -0.7799 +2024-11-22 21:53:51.873048: Pseudo dice [0.8559] +2024-11-22 21:53:51.873204: Epoch time: 19.81 s +2024-11-22 21:53:52.795215: +2024-11-22 21:53:52.795797: Epoch 6329 +2024-11-22 21:53:52.795920: Current learning rate: 0.00244 +2024-11-22 21:54:11.179616: train_loss -0.8129 +2024-11-22 21:54:11.183708: val_loss -0.7632 +2024-11-22 21:54:11.183871: Pseudo dice [0.8601] +2024-11-22 21:54:11.184072: Epoch time: 18.39 s +2024-11-22 21:54:12.230322: +2024-11-22 21:54:12.230742: Epoch 6330 +2024-11-22 21:54:12.230863: Current learning rate: 0.00244 +2024-11-22 21:54:31.157538: train_loss -0.8175 +2024-11-22 21:54:31.173066: val_loss -0.7845 +2024-11-22 21:54:31.173201: Pseudo dice [0.8589] +2024-11-22 21:54:31.173296: Epoch time: 18.93 s +2024-11-22 21:54:32.210697: +2024-11-22 21:54:32.212473: Epoch 6331 +2024-11-22 21:54:32.212811: Current learning rate: 0.00244 +2024-11-22 21:54:51.713389: train_loss -0.8124 +2024-11-22 21:54:51.718811: val_loss -0.7817 +2024-11-22 21:54:51.718969: Pseudo dice [0.8545] +2024-11-22 21:54:51.719108: Epoch time: 19.5 s +2024-11-22 21:54:52.618769: +2024-11-22 21:54:52.620200: Epoch 6332 +2024-11-22 21:54:52.620334: Current learning rate: 0.00244 +2024-11-22 21:55:12.027079: train_loss -0.8052 +2024-11-22 21:55:12.032279: val_loss -0.8107 +2024-11-22 21:55:12.032440: Pseudo dice [0.8685] +2024-11-22 21:55:12.032640: Epoch time: 19.41 s +2024-11-22 21:55:12.981334: +2024-11-22 21:55:12.981821: Epoch 6333 +2024-11-22 21:55:12.981959: Current learning rate: 0.00244 +2024-11-22 21:55:33.430288: train_loss -0.8105 +2024-11-22 21:55:33.432779: val_loss -0.7653 +2024-11-22 21:55:33.432876: Pseudo dice [0.8518] +2024-11-22 21:55:33.432981: Epoch time: 20.45 s +2024-11-22 21:55:34.704131: +2024-11-22 21:55:34.705968: Epoch 6334 +2024-11-22 21:55:34.706111: Current learning rate: 0.00244 +2024-11-22 21:55:53.218435: train_loss -0.8114 +2024-11-22 21:55:53.224738: val_loss -0.7688 +2024-11-22 21:55:53.224910: Pseudo dice [0.8397] +2024-11-22 21:55:53.225022: Epoch time: 18.52 s +2024-11-22 21:55:54.170110: +2024-11-22 21:55:54.170742: Epoch 6335 +2024-11-22 21:55:54.170861: Current learning rate: 0.00243 +2024-11-22 21:56:13.417112: train_loss -0.8089 +2024-11-22 21:56:13.423612: val_loss -0.7962 +2024-11-22 21:56:13.423757: Pseudo dice [0.8725] +2024-11-22 21:56:13.423863: Epoch time: 19.25 s +2024-11-22 21:56:14.339184: +2024-11-22 21:56:14.341228: Epoch 6336 +2024-11-22 21:56:14.341374: Current learning rate: 0.00243 +2024-11-22 21:56:33.855090: train_loss -0.813 +2024-11-22 21:56:33.861049: val_loss -0.7843 +2024-11-22 21:56:33.861183: Pseudo dice [0.8577] +2024-11-22 21:56:33.861277: Epoch time: 19.52 s +2024-11-22 21:56:34.932642: +2024-11-22 21:56:34.934231: Epoch 6337 +2024-11-22 21:56:34.934355: Current learning rate: 0.00243 +2024-11-22 21:56:53.977560: train_loss -0.8178 +2024-11-22 21:56:53.979866: val_loss -0.7798 +2024-11-22 21:56:53.979984: Pseudo dice [0.8576] +2024-11-22 21:56:53.980093: Epoch time: 19.05 s +2024-11-22 21:56:54.970220: +2024-11-22 21:56:54.971829: Epoch 6338 +2024-11-22 21:56:54.971951: Current learning rate: 0.00243 +2024-11-22 21:57:13.925258: train_loss -0.8126 +2024-11-22 21:57:13.929942: val_loss -0.7871 +2024-11-22 21:57:13.930081: Pseudo dice [0.8634] +2024-11-22 21:57:13.930193: Epoch time: 18.96 s +2024-11-22 21:57:14.812746: +2024-11-22 21:57:14.813169: Epoch 6339 +2024-11-22 21:57:14.813295: Current learning rate: 0.00243 +2024-11-22 21:57:33.427920: train_loss -0.8118 +2024-11-22 21:57:33.431191: val_loss -0.7759 +2024-11-22 21:57:33.431331: Pseudo dice [0.862] +2024-11-22 21:57:33.431422: Epoch time: 18.62 s +2024-11-22 21:57:34.440716: +2024-11-22 21:57:34.442307: Epoch 6340 +2024-11-22 21:57:34.442436: Current learning rate: 0.00243 +2024-11-22 21:57:54.328590: train_loss -0.8172 +2024-11-22 21:57:54.335113: val_loss -0.7775 +2024-11-22 21:57:54.335246: Pseudo dice [0.8436] +2024-11-22 21:57:54.335333: Epoch time: 19.89 s +2024-11-22 21:57:55.382675: +2024-11-22 21:57:55.384181: Epoch 6341 +2024-11-22 21:57:55.384303: Current learning rate: 0.00243 +2024-11-22 21:58:14.137773: train_loss -0.8193 +2024-11-22 21:58:14.147365: val_loss -0.7797 +2024-11-22 21:58:14.147523: Pseudo dice [0.8649] +2024-11-22 21:58:14.147625: Epoch time: 18.76 s +2024-11-22 21:58:15.039582: +2024-11-22 21:58:15.040626: Epoch 6342 +2024-11-22 21:58:15.040760: Current learning rate: 0.00243 +2024-11-22 21:58:34.087598: train_loss -0.8122 +2024-11-22 21:58:34.090560: val_loss -0.7668 +2024-11-22 21:58:34.090758: Pseudo dice [0.8565] +2024-11-22 21:58:34.090845: Epoch time: 19.05 s +2024-11-22 21:58:35.010638: +2024-11-22 21:58:35.011480: Epoch 6343 +2024-11-22 21:58:35.011617: Current learning rate: 0.00242 +2024-11-22 21:58:54.395103: train_loss -0.8101 +2024-11-22 21:58:54.408287: val_loss -0.8033 +2024-11-22 21:58:54.408458: Pseudo dice [0.867] +2024-11-22 21:58:54.408736: Epoch time: 19.39 s +2024-11-22 21:58:55.292497: +2024-11-22 21:58:55.293862: Epoch 6344 +2024-11-22 21:58:55.293991: Current learning rate: 0.00242 +2024-11-22 21:59:14.494198: train_loss -0.8058 +2024-11-22 21:59:14.503300: val_loss -0.7834 +2024-11-22 21:59:14.503453: Pseudo dice [0.8592] +2024-11-22 21:59:14.503541: Epoch time: 19.2 s +2024-11-22 21:59:15.463451: +2024-11-22 21:59:15.464541: Epoch 6345 +2024-11-22 21:59:15.464670: Current learning rate: 0.00242 +2024-11-22 21:59:35.929980: train_loss -0.8138 +2024-11-22 21:59:35.936537: val_loss -0.7573 +2024-11-22 21:59:35.936691: Pseudo dice [0.8509] +2024-11-22 21:59:35.936874: Epoch time: 20.47 s +2024-11-22 21:59:36.889392: +2024-11-22 21:59:36.890638: Epoch 6346 +2024-11-22 21:59:36.890776: Current learning rate: 0.00242 +2024-11-22 21:59:55.934797: train_loss -0.8101 +2024-11-22 21:59:55.941306: val_loss -0.792 +2024-11-22 21:59:55.941442: Pseudo dice [0.8609] +2024-11-22 21:59:55.941552: Epoch time: 19.05 s +2024-11-22 21:59:56.978994: +2024-11-22 21:59:56.980726: Epoch 6347 +2024-11-22 21:59:56.980851: Current learning rate: 0.00242 +2024-11-22 22:00:16.798927: train_loss -0.814 +2024-11-22 22:00:16.806424: val_loss -0.7904 +2024-11-22 22:00:16.806571: Pseudo dice [0.8662] +2024-11-22 22:00:16.806683: Epoch time: 19.82 s +2024-11-22 22:00:17.717516: +2024-11-22 22:00:17.718609: Epoch 6348 +2024-11-22 22:00:17.718727: Current learning rate: 0.00242 +2024-11-22 22:00:37.275663: train_loss -0.8112 +2024-11-22 22:00:37.285943: val_loss -0.7842 +2024-11-22 22:00:37.286080: Pseudo dice [0.8589] +2024-11-22 22:00:37.286162: Epoch time: 19.56 s +2024-11-22 22:00:38.432915: +2024-11-22 22:00:38.434745: Epoch 6349 +2024-11-22 22:00:38.434877: Current learning rate: 0.00242 +2024-11-22 22:00:58.344763: train_loss -0.808 +2024-11-22 22:00:58.351265: val_loss -0.782 +2024-11-22 22:00:58.351392: Pseudo dice [0.856] +2024-11-22 22:00:58.351501: Epoch time: 19.91 s +2024-11-22 22:00:59.707944: +2024-11-22 22:00:59.709430: Epoch 6350 +2024-11-22 22:00:59.709630: Current learning rate: 0.00242 +2024-11-22 22:01:20.601552: train_loss -0.8077 +2024-11-22 22:01:20.613141: val_loss -0.7885 +2024-11-22 22:01:20.613330: Pseudo dice [0.8581] +2024-11-22 22:01:20.613417: Epoch time: 20.89 s +2024-11-22 22:01:21.590995: +2024-11-22 22:01:21.592542: Epoch 6351 +2024-11-22 22:01:21.592674: Current learning rate: 0.00241 +2024-11-22 22:01:41.948489: train_loss -0.7985 +2024-11-22 22:01:41.956693: val_loss -0.7527 +2024-11-22 22:01:41.956835: Pseudo dice [0.8415] +2024-11-22 22:01:41.956928: Epoch time: 20.36 s +2024-11-22 22:01:42.873479: +2024-11-22 22:01:42.875162: Epoch 6352 +2024-11-22 22:01:42.875314: Current learning rate: 0.00241 +2024-11-22 22:02:03.373680: train_loss -0.7963 +2024-11-22 22:02:03.378659: val_loss -0.7613 +2024-11-22 22:02:03.379074: Pseudo dice [0.853] +2024-11-22 22:02:03.379187: Epoch time: 20.5 s +2024-11-22 22:02:04.385815: +2024-11-22 22:02:04.386496: Epoch 6353 +2024-11-22 22:02:04.386642: Current learning rate: 0.00241 +2024-11-22 22:02:23.785351: train_loss -0.8075 +2024-11-22 22:02:23.791915: val_loss -0.7804 +2024-11-22 22:02:23.792055: Pseudo dice [0.8519] +2024-11-22 22:02:23.792193: Epoch time: 19.4 s +2024-11-22 22:02:24.794001: +2024-11-22 22:02:24.794800: Epoch 6354 +2024-11-22 22:02:24.794928: Current learning rate: 0.00241 +2024-11-22 22:02:44.453341: train_loss -0.8037 +2024-11-22 22:02:44.464080: val_loss -0.7985 +2024-11-22 22:02:44.464250: Pseudo dice [0.8572] +2024-11-22 22:02:44.464351: Epoch time: 19.66 s +2024-11-22 22:02:45.346006: +2024-11-22 22:02:45.347083: Epoch 6355 +2024-11-22 22:02:45.347208: Current learning rate: 0.00241 +2024-11-22 22:03:04.567444: train_loss -0.8065 +2024-11-22 22:03:04.575254: val_loss -0.786 +2024-11-22 22:03:04.575410: Pseudo dice [0.855] +2024-11-22 22:03:04.575507: Epoch time: 19.22 s +2024-11-22 22:03:05.851941: +2024-11-22 22:03:05.853112: Epoch 6356 +2024-11-22 22:03:05.853329: Current learning rate: 0.00241 +2024-11-22 22:03:25.973634: train_loss -0.8117 +2024-11-22 22:03:26.005862: val_loss -0.788 +2024-11-22 22:03:26.006041: Pseudo dice [0.8544] +2024-11-22 22:03:26.006149: Epoch time: 20.12 s +2024-11-22 22:03:27.052271: +2024-11-22 22:03:27.053849: Epoch 6357 +2024-11-22 22:03:27.053990: Current learning rate: 0.00241 +2024-11-22 22:03:45.797818: train_loss -0.8036 +2024-11-22 22:03:45.804950: val_loss -0.7762 +2024-11-22 22:03:45.805114: Pseudo dice [0.8608] +2024-11-22 22:03:45.805228: Epoch time: 18.75 s +2024-11-22 22:03:46.768270: +2024-11-22 22:03:46.769608: Epoch 6358 +2024-11-22 22:03:46.769739: Current learning rate: 0.0024 +2024-11-22 22:04:08.256558: train_loss -0.8087 +2024-11-22 22:04:08.259536: val_loss -0.7542 +2024-11-22 22:04:08.259691: Pseudo dice [0.8645] +2024-11-22 22:04:08.259789: Epoch time: 21.49 s +2024-11-22 22:04:09.231584: +2024-11-22 22:04:09.233280: Epoch 6359 +2024-11-22 22:04:09.233412: Current learning rate: 0.0024 +2024-11-22 22:04:27.834049: train_loss -0.8132 +2024-11-22 22:04:27.839848: val_loss -0.7651 +2024-11-22 22:04:27.839993: Pseudo dice [0.8488] +2024-11-22 22:04:27.840097: Epoch time: 18.6 s +2024-11-22 22:04:29.052393: +2024-11-22 22:04:29.053500: Epoch 6360 +2024-11-22 22:04:29.053622: Current learning rate: 0.0024 +2024-11-22 22:04:47.948933: train_loss -0.8059 +2024-11-22 22:04:47.963454: val_loss -0.7673 +2024-11-22 22:04:47.963600: Pseudo dice [0.8582] +2024-11-22 22:04:47.963692: Epoch time: 18.9 s +2024-11-22 22:04:48.924542: +2024-11-22 22:04:48.925814: Epoch 6361 +2024-11-22 22:04:48.925945: Current learning rate: 0.0024 +2024-11-22 22:05:08.168167: train_loss -0.8058 +2024-11-22 22:05:08.176397: val_loss -0.7991 +2024-11-22 22:05:08.176540: Pseudo dice [0.8633] +2024-11-22 22:05:08.176643: Epoch time: 19.24 s +2024-11-22 22:05:09.115942: +2024-11-22 22:05:09.117277: Epoch 6362 +2024-11-22 22:05:09.117411: Current learning rate: 0.0024 +2024-11-22 22:05:27.830577: train_loss -0.8075 +2024-11-22 22:05:27.840751: val_loss -0.7963 +2024-11-22 22:05:27.840895: Pseudo dice [0.8583] +2024-11-22 22:05:27.840996: Epoch time: 18.72 s +2024-11-22 22:05:28.826469: +2024-11-22 22:05:28.827600: Epoch 6363 +2024-11-22 22:05:28.827746: Current learning rate: 0.0024 +2024-11-22 22:05:47.668523: train_loss -0.8168 +2024-11-22 22:05:47.680922: val_loss -0.7929 +2024-11-22 22:05:47.681073: Pseudo dice [0.8675] +2024-11-22 22:05:47.681186: Epoch time: 18.84 s +2024-11-22 22:05:48.681657: +2024-11-22 22:05:48.682698: Epoch 6364 +2024-11-22 22:05:48.682820: Current learning rate: 0.0024 +2024-11-22 22:06:08.382612: train_loss -0.8132 +2024-11-22 22:06:08.390164: val_loss -0.7978 +2024-11-22 22:06:08.390333: Pseudo dice [0.8653] +2024-11-22 22:06:08.390433: Epoch time: 19.7 s +2024-11-22 22:06:08.390507: Yayy! New best EMA pseudo Dice: 0.859 +2024-11-22 22:06:09.698521: +2024-11-22 22:06:09.699997: Epoch 6365 +2024-11-22 22:06:09.700149: Current learning rate: 0.0024 +2024-11-22 22:06:28.303975: train_loss -0.8187 +2024-11-22 22:06:28.308009: val_loss -0.7799 +2024-11-22 22:06:28.308135: Pseudo dice [0.8665] +2024-11-22 22:06:28.308251: Epoch time: 18.61 s +2024-11-22 22:06:28.308345: Yayy! New best EMA pseudo Dice: 0.8597 +2024-11-22 22:06:29.554365: +2024-11-22 22:06:29.556337: Epoch 6366 +2024-11-22 22:06:29.556469: Current learning rate: 0.00239 +2024-11-22 22:06:48.978876: train_loss -0.8138 +2024-11-22 22:06:48.987764: val_loss -0.7917 +2024-11-22 22:06:48.987920: Pseudo dice [0.859] +2024-11-22 22:06:48.988014: Epoch time: 19.43 s +2024-11-22 22:06:50.070517: +2024-11-22 22:06:50.074104: Epoch 6367 +2024-11-22 22:06:50.074263: Current learning rate: 0.00239 +2024-11-22 22:07:09.858989: train_loss -0.8069 +2024-11-22 22:07:09.861598: val_loss -0.7731 +2024-11-22 22:07:09.861740: Pseudo dice [0.8571] +2024-11-22 22:07:09.861846: Epoch time: 19.79 s +2024-11-22 22:07:10.883203: +2024-11-22 22:07:10.883957: Epoch 6368 +2024-11-22 22:07:10.884092: Current learning rate: 0.00239 +2024-11-22 22:07:30.851561: train_loss -0.8106 +2024-11-22 22:07:30.893644: val_loss -0.7827 +2024-11-22 22:07:30.893825: Pseudo dice [0.8587] +2024-11-22 22:07:30.921343: Epoch time: 19.97 s +2024-11-22 22:07:31.809205: +2024-11-22 22:07:31.810264: Epoch 6369 +2024-11-22 22:07:31.810403: Current learning rate: 0.00239 +2024-11-22 22:07:51.944227: train_loss -0.8081 +2024-11-22 22:07:51.950221: val_loss -0.7869 +2024-11-22 22:07:51.950345: Pseudo dice [0.8435] +2024-11-22 22:07:51.950448: Epoch time: 20.14 s +2024-11-22 22:07:53.032588: +2024-11-22 22:07:53.032802: Epoch 6370 +2024-11-22 22:07:53.032919: Current learning rate: 0.00239 +2024-11-22 22:08:12.191033: train_loss -0.8201 +2024-11-22 22:08:12.191556: val_loss -0.7766 +2024-11-22 22:08:12.191669: Pseudo dice [0.8648] +2024-11-22 22:08:12.191799: Epoch time: 19.16 s +2024-11-22 22:08:13.069446: +2024-11-22 22:08:13.069659: Epoch 6371 +2024-11-22 22:08:13.069782: Current learning rate: 0.00239 +2024-11-22 22:08:31.743987: train_loss -0.8105 +2024-11-22 22:08:31.744190: val_loss -0.7907 +2024-11-22 22:08:31.744276: Pseudo dice [0.857] +2024-11-22 22:08:31.744363: Epoch time: 18.68 s +2024-11-22 22:08:32.678511: +2024-11-22 22:08:32.678734: Epoch 6372 +2024-11-22 22:08:32.678858: Current learning rate: 0.00239 +2024-11-22 22:08:51.109948: train_loss -0.811 +2024-11-22 22:08:51.112764: val_loss -0.7727 +2024-11-22 22:08:51.112888: Pseudo dice [0.8445] +2024-11-22 22:08:51.112972: Epoch time: 18.43 s +2024-11-22 22:08:52.004168: +2024-11-22 22:08:52.004383: Epoch 6373 +2024-11-22 22:08:52.004521: Current learning rate: 0.00238 +2024-11-22 22:09:10.487210: train_loss -0.8207 +2024-11-22 22:09:10.492668: val_loss -0.7788 +2024-11-22 22:09:10.492871: Pseudo dice [0.8468] +2024-11-22 22:09:10.492974: Epoch time: 18.48 s +2024-11-22 22:09:11.391740: +2024-11-22 22:09:11.391954: Epoch 6374 +2024-11-22 22:09:11.392084: Current learning rate: 0.00238 +2024-11-22 22:09:29.773005: train_loss -0.794 +2024-11-22 22:09:29.773456: val_loss -0.7569 +2024-11-22 22:09:29.773545: Pseudo dice [0.8555] +2024-11-22 22:09:29.773644: Epoch time: 18.38 s +2024-11-22 22:09:30.902688: +2024-11-22 22:09:30.902904: Epoch 6375 +2024-11-22 22:09:30.903027: Current learning rate: 0.00238 +2024-11-22 22:09:49.589597: train_loss -0.8099 +2024-11-22 22:09:49.596607: val_loss -0.8032 +2024-11-22 22:09:49.596797: Pseudo dice [0.86] +2024-11-22 22:09:49.596890: Epoch time: 18.69 s +2024-11-22 22:09:50.686304: +2024-11-22 22:09:50.686516: Epoch 6376 +2024-11-22 22:09:50.686636: Current learning rate: 0.00238 +2024-11-22 22:10:09.626114: train_loss -0.8073 +2024-11-22 22:10:09.630583: val_loss -0.7611 +2024-11-22 22:10:09.630718: Pseudo dice [0.8428] +2024-11-22 22:10:09.630803: Epoch time: 18.94 s +2024-11-22 22:10:10.664240: +2024-11-22 22:10:10.664454: Epoch 6377 +2024-11-22 22:10:10.664591: Current learning rate: 0.00238 +2024-11-22 22:10:30.379549: train_loss -0.803 +2024-11-22 22:10:30.380285: val_loss -0.7736 +2024-11-22 22:10:30.380377: Pseudo dice [0.8501] +2024-11-22 22:10:30.380471: Epoch time: 19.72 s +2024-11-22 22:10:31.653412: +2024-11-22 22:10:31.653631: Epoch 6378 +2024-11-22 22:10:31.653767: Current learning rate: 0.00238 +2024-11-22 22:10:51.980628: train_loss -0.8121 +2024-11-22 22:10:51.984219: val_loss -0.7641 +2024-11-22 22:10:51.984323: Pseudo dice [0.8463] +2024-11-22 22:10:51.984414: Epoch time: 20.33 s +2024-11-22 22:10:52.869002: +2024-11-22 22:10:52.869544: Epoch 6379 +2024-11-22 22:10:52.869665: Current learning rate: 0.00238 +2024-11-22 22:11:11.409495: train_loss -0.816 +2024-11-22 22:11:11.415184: val_loss -0.7804 +2024-11-22 22:11:11.415342: Pseudo dice [0.8623] +2024-11-22 22:11:11.415753: Epoch time: 18.54 s +2024-11-22 22:11:12.428586: +2024-11-22 22:11:12.429867: Epoch 6380 +2024-11-22 22:11:12.429986: Current learning rate: 0.00238 +2024-11-22 22:11:31.611171: train_loss -0.814 +2024-11-22 22:11:31.617821: val_loss -0.7602 +2024-11-22 22:11:31.618012: Pseudo dice [0.8539] +2024-11-22 22:11:31.618123: Epoch time: 19.18 s +2024-11-22 22:11:32.639298: +2024-11-22 22:11:32.640456: Epoch 6381 +2024-11-22 22:11:32.640575: Current learning rate: 0.00237 +2024-11-22 22:11:52.665936: train_loss -0.8103 +2024-11-22 22:11:52.668226: val_loss -0.7832 +2024-11-22 22:11:52.668362: Pseudo dice [0.8619] +2024-11-22 22:11:52.668838: Epoch time: 20.03 s +2024-11-22 22:11:53.595162: +2024-11-22 22:11:53.596038: Epoch 6382 +2024-11-22 22:11:53.596159: Current learning rate: 0.00237 +2024-11-22 22:12:13.442377: train_loss -0.808 +2024-11-22 22:12:13.453970: val_loss -0.7693 +2024-11-22 22:12:13.454108: Pseudo dice [0.8594] +2024-11-22 22:12:13.454226: Epoch time: 19.85 s +2024-11-22 22:12:14.502836: +2024-11-22 22:12:14.504003: Epoch 6383 +2024-11-22 22:12:14.504141: Current learning rate: 0.00237 +2024-11-22 22:12:33.493895: train_loss -0.8081 +2024-11-22 22:12:33.496137: val_loss -0.7607 +2024-11-22 22:12:33.496266: Pseudo dice [0.853] +2024-11-22 22:12:33.496367: Epoch time: 18.99 s +2024-11-22 22:12:34.574540: +2024-11-22 22:12:34.575770: Epoch 6384 +2024-11-22 22:12:34.575912: Current learning rate: 0.00237 +2024-11-22 22:12:54.239793: train_loss -0.817 +2024-11-22 22:12:54.245891: val_loss -0.7737 +2024-11-22 22:12:54.246035: Pseudo dice [0.8566] +2024-11-22 22:12:54.246153: Epoch time: 19.67 s +2024-11-22 22:12:55.139004: +2024-11-22 22:12:55.140184: Epoch 6385 +2024-11-22 22:12:55.140328: Current learning rate: 0.00237 +2024-11-22 22:13:13.213774: train_loss -0.8145 +2024-11-22 22:13:13.215943: val_loss -0.7866 +2024-11-22 22:13:13.216049: Pseudo dice [0.8469] +2024-11-22 22:13:13.216154: Epoch time: 18.08 s +2024-11-22 22:13:14.097568: +2024-11-22 22:13:14.098637: Epoch 6386 +2024-11-22 22:13:14.098782: Current learning rate: 0.00237 +2024-11-22 22:13:34.014649: train_loss -0.8012 +2024-11-22 22:13:34.017111: val_loss -0.7715 +2024-11-22 22:13:34.017223: Pseudo dice [0.8562] +2024-11-22 22:13:34.017324: Epoch time: 19.92 s +2024-11-22 22:13:34.904670: +2024-11-22 22:13:34.905548: Epoch 6387 +2024-11-22 22:13:34.905675: Current learning rate: 0.00237 +2024-11-22 22:13:55.610385: train_loss -0.8039 +2024-11-22 22:13:55.612818: val_loss -0.7753 +2024-11-22 22:13:55.612957: Pseudo dice [0.85] +2024-11-22 22:13:55.613092: Epoch time: 20.71 s +2024-11-22 22:13:56.632131: +2024-11-22 22:13:56.633137: Epoch 6388 +2024-11-22 22:13:56.633265: Current learning rate: 0.00237 +2024-11-22 22:14:16.167173: train_loss -0.8134 +2024-11-22 22:14:16.171679: val_loss -0.7575 +2024-11-22 22:14:16.171807: Pseudo dice [0.8642] +2024-11-22 22:14:16.171923: Epoch time: 19.53 s +2024-11-22 22:14:17.645678: +2024-11-22 22:14:17.647299: Epoch 6389 +2024-11-22 22:14:17.647423: Current learning rate: 0.00236 +2024-11-22 22:14:37.328824: train_loss -0.8141 +2024-11-22 22:14:37.331180: val_loss -0.7725 +2024-11-22 22:14:37.331359: Pseudo dice [0.8632] +2024-11-22 22:14:37.331470: Epoch time: 19.68 s +2024-11-22 22:14:38.218247: +2024-11-22 22:14:38.219941: Epoch 6390 +2024-11-22 22:14:38.220082: Current learning rate: 0.00236 +2024-11-22 22:14:56.690042: train_loss -0.8116 +2024-11-22 22:14:56.696342: val_loss -0.7739 +2024-11-22 22:14:56.696511: Pseudo dice [0.8417] +2024-11-22 22:14:56.696619: Epoch time: 18.47 s +2024-11-22 22:14:57.656286: +2024-11-22 22:14:57.657585: Epoch 6391 +2024-11-22 22:14:57.657743: Current learning rate: 0.00236 +2024-11-22 22:15:18.265759: train_loss -0.8177 +2024-11-22 22:15:18.272362: val_loss -0.7711 +2024-11-22 22:15:18.272573: Pseudo dice [0.8473] +2024-11-22 22:15:18.272666: Epoch time: 20.61 s +2024-11-22 22:15:19.239493: +2024-11-22 22:15:19.241018: Epoch 6392 +2024-11-22 22:15:19.241152: Current learning rate: 0.00236 +2024-11-22 22:15:39.418214: train_loss -0.8011 +2024-11-22 22:15:39.424499: val_loss -0.7663 +2024-11-22 22:15:39.424659: Pseudo dice [0.8452] +2024-11-22 22:15:39.424763: Epoch time: 20.18 s +2024-11-22 22:15:40.492894: +2024-11-22 22:15:40.493946: Epoch 6393 +2024-11-22 22:15:40.494081: Current learning rate: 0.00236 +2024-11-22 22:16:00.128553: train_loss -0.8099 +2024-11-22 22:16:00.137832: val_loss -0.7822 +2024-11-22 22:16:00.137980: Pseudo dice [0.8667] +2024-11-22 22:16:00.138090: Epoch time: 19.64 s +2024-11-22 22:16:01.041692: +2024-11-22 22:16:01.043225: Epoch 6394 +2024-11-22 22:16:01.043365: Current learning rate: 0.00236 +2024-11-22 22:16:20.385680: train_loss -0.817 +2024-11-22 22:16:20.395328: val_loss -0.7773 +2024-11-22 22:16:20.395491: Pseudo dice [0.8584] +2024-11-22 22:16:20.395602: Epoch time: 19.34 s +2024-11-22 22:16:21.306180: +2024-11-22 22:16:21.307523: Epoch 6395 +2024-11-22 22:16:21.307648: Current learning rate: 0.00236 +2024-11-22 22:16:40.619285: train_loss -0.8183 +2024-11-22 22:16:40.632014: val_loss -0.7914 +2024-11-22 22:16:40.632230: Pseudo dice [0.8692] +2024-11-22 22:16:40.632386: Epoch time: 19.31 s +2024-11-22 22:16:41.599364: +2024-11-22 22:16:41.599828: Epoch 6396 +2024-11-22 22:16:41.599978: Current learning rate: 0.00235 +2024-11-22 22:17:01.672824: train_loss -0.8137 +2024-11-22 22:17:01.679599: val_loss -0.7667 +2024-11-22 22:17:01.679720: Pseudo dice [0.8594] +2024-11-22 22:17:01.679813: Epoch time: 20.07 s +2024-11-22 22:17:02.646531: +2024-11-22 22:17:02.647752: Epoch 6397 +2024-11-22 22:17:02.647875: Current learning rate: 0.00235 +2024-11-22 22:17:21.338144: train_loss -0.8201 +2024-11-22 22:17:21.343261: val_loss -0.7851 +2024-11-22 22:17:21.343404: Pseudo dice [0.8604] +2024-11-22 22:17:21.343522: Epoch time: 18.69 s +2024-11-22 22:17:22.480425: +2024-11-22 22:17:22.481315: Epoch 6398 +2024-11-22 22:17:22.481436: Current learning rate: 0.00235 +2024-11-22 22:17:41.017508: train_loss -0.8045 +2024-11-22 22:17:41.031857: val_loss -0.7893 +2024-11-22 22:17:41.032008: Pseudo dice [0.8582] +2024-11-22 22:17:41.032099: Epoch time: 18.54 s +2024-11-22 22:17:42.071848: +2024-11-22 22:17:42.073699: Epoch 6399 +2024-11-22 22:17:42.073844: Current learning rate: 0.00235 +2024-11-22 22:18:01.656500: train_loss -0.7994 +2024-11-22 22:18:01.663035: val_loss -0.7914 +2024-11-22 22:18:01.663154: Pseudo dice [0.8591] +2024-11-22 22:18:01.663254: Epoch time: 19.59 s +2024-11-22 22:18:03.275588: +2024-11-22 22:18:03.277126: Epoch 6400 +2024-11-22 22:18:03.277265: Current learning rate: 0.00235 +2024-11-22 22:18:23.748078: train_loss -0.8106 +2024-11-22 22:18:23.753957: val_loss -0.7693 +2024-11-22 22:18:23.754112: Pseudo dice [0.8487] +2024-11-22 22:18:23.754236: Epoch time: 20.47 s +2024-11-22 22:18:24.888490: +2024-11-22 22:18:24.889754: Epoch 6401 +2024-11-22 22:18:24.889880: Current learning rate: 0.00235 +2024-11-22 22:18:44.359846: train_loss -0.806 +2024-11-22 22:18:44.362680: val_loss -0.789 +2024-11-22 22:18:44.362814: Pseudo dice [0.8537] +2024-11-22 22:18:44.362917: Epoch time: 19.47 s +2024-11-22 22:18:45.252173: +2024-11-22 22:18:45.253052: Epoch 6402 +2024-11-22 22:18:45.253189: Current learning rate: 0.00235 +2024-11-22 22:19:04.340459: train_loss -0.8108 +2024-11-22 22:19:04.346700: val_loss -0.7768 +2024-11-22 22:19:04.346821: Pseudo dice [0.852] +2024-11-22 22:19:04.346918: Epoch time: 19.09 s +2024-11-22 22:19:05.233569: +2024-11-22 22:19:05.234316: Epoch 6403 +2024-11-22 22:19:05.234441: Current learning rate: 0.00235 +2024-11-22 22:19:25.216080: train_loss -0.8165 +2024-11-22 22:19:25.235783: val_loss -0.7687 +2024-11-22 22:19:25.235917: Pseudo dice [0.8507] +2024-11-22 22:19:25.236013: Epoch time: 19.98 s +2024-11-22 22:19:26.208632: +2024-11-22 22:19:26.210368: Epoch 6404 +2024-11-22 22:19:26.210501: Current learning rate: 0.00234 +2024-11-22 22:19:45.631163: train_loss -0.8027 +2024-11-22 22:19:45.656345: val_loss -0.743 +2024-11-22 22:19:45.656529: Pseudo dice [0.8434] +2024-11-22 22:19:45.656636: Epoch time: 19.42 s +2024-11-22 22:19:46.776203: +2024-11-22 22:19:46.777929: Epoch 6405 +2024-11-22 22:19:46.778067: Current learning rate: 0.00234 +2024-11-22 22:20:06.654280: train_loss -0.8107 +2024-11-22 22:20:06.663254: val_loss -0.7579 +2024-11-22 22:20:06.663394: Pseudo dice [0.864] +2024-11-22 22:20:06.663483: Epoch time: 19.88 s +2024-11-22 22:20:07.676050: +2024-11-22 22:20:07.677337: Epoch 6406 +2024-11-22 22:20:07.677470: Current learning rate: 0.00234 +2024-11-22 22:20:26.782390: train_loss -0.8147 +2024-11-22 22:20:26.788239: val_loss -0.7421 +2024-11-22 22:20:26.788411: Pseudo dice [0.8379] +2024-11-22 22:20:26.788508: Epoch time: 19.11 s +2024-11-22 22:20:27.676411: +2024-11-22 22:20:27.677032: Epoch 6407 +2024-11-22 22:20:27.677208: Current learning rate: 0.00234 +2024-11-22 22:20:45.998237: train_loss -0.822 +2024-11-22 22:20:46.017674: val_loss -0.7788 +2024-11-22 22:20:46.018029: Pseudo dice [0.8614] +2024-11-22 22:20:46.018140: Epoch time: 18.32 s +2024-11-22 22:20:46.970991: +2024-11-22 22:20:46.972034: Epoch 6408 +2024-11-22 22:20:46.972169: Current learning rate: 0.00234 +2024-11-22 22:21:06.137779: train_loss -0.8054 +2024-11-22 22:21:06.148156: val_loss -0.7788 +2024-11-22 22:21:06.148311: Pseudo dice [0.8541] +2024-11-22 22:21:06.148435: Epoch time: 19.17 s +2024-11-22 22:21:07.059196: +2024-11-22 22:21:07.060421: Epoch 6409 +2024-11-22 22:21:07.060546: Current learning rate: 0.00234 +2024-11-22 22:21:26.350040: train_loss -0.8126 +2024-11-22 22:21:26.363023: val_loss -0.7568 +2024-11-22 22:21:26.363182: Pseudo dice [0.8641] +2024-11-22 22:21:26.363269: Epoch time: 19.29 s +2024-11-22 22:21:27.346991: +2024-11-22 22:21:27.348609: Epoch 6410 +2024-11-22 22:21:27.348739: Current learning rate: 0.00234 +2024-11-22 22:21:46.347690: train_loss -0.8097 +2024-11-22 22:21:46.349864: val_loss -0.7711 +2024-11-22 22:21:46.349976: Pseudo dice [0.8622] +2024-11-22 22:21:46.350068: Epoch time: 19.0 s +2024-11-22 22:21:47.639171: +2024-11-22 22:21:47.640420: Epoch 6411 +2024-11-22 22:21:47.640539: Current learning rate: 0.00233 +2024-11-22 22:22:06.885563: train_loss -0.8122 +2024-11-22 22:22:06.892770: val_loss -0.7829 +2024-11-22 22:22:06.892916: Pseudo dice [0.8679] +2024-11-22 22:22:06.893007: Epoch time: 19.25 s +2024-11-22 22:22:07.964469: +2024-11-22 22:22:07.966619: Epoch 6412 +2024-11-22 22:22:07.966794: Current learning rate: 0.00233 +2024-11-22 22:22:27.227919: train_loss -0.8053 +2024-11-22 22:22:27.236244: val_loss -0.7749 +2024-11-22 22:22:27.236395: Pseudo dice [0.8637] +2024-11-22 22:22:27.236493: Epoch time: 19.26 s +2024-11-22 22:22:28.220753: +2024-11-22 22:22:28.221206: Epoch 6413 +2024-11-22 22:22:28.221336: Current learning rate: 0.00233 +2024-11-22 22:22:48.334938: train_loss -0.8096 +2024-11-22 22:22:48.340546: val_loss -0.7729 +2024-11-22 22:22:48.340661: Pseudo dice [0.8518] +2024-11-22 22:22:48.340766: Epoch time: 20.11 s +2024-11-22 22:22:49.229531: +2024-11-22 22:22:49.230367: Epoch 6414 +2024-11-22 22:22:49.230497: Current learning rate: 0.00233 +2024-11-22 22:23:08.004446: train_loss -0.8053 +2024-11-22 22:23:08.010299: val_loss -0.7855 +2024-11-22 22:23:08.010437: Pseudo dice [0.8642] +2024-11-22 22:23:08.010544: Epoch time: 18.78 s +2024-11-22 22:23:08.964447: +2024-11-22 22:23:08.966153: Epoch 6415 +2024-11-22 22:23:08.966275: Current learning rate: 0.00233 +2024-11-22 22:23:27.823169: train_loss -0.8178 +2024-11-22 22:23:27.828213: val_loss -0.7742 +2024-11-22 22:23:27.828360: Pseudo dice [0.8508] +2024-11-22 22:23:27.828457: Epoch time: 18.86 s +2024-11-22 22:23:28.822602: +2024-11-22 22:23:28.823917: Epoch 6416 +2024-11-22 22:23:28.824070: Current learning rate: 0.00233 +2024-11-22 22:23:48.142154: train_loss -0.8124 +2024-11-22 22:23:48.155855: val_loss -0.7507 +2024-11-22 22:23:48.155989: Pseudo dice [0.8542] +2024-11-22 22:23:48.156087: Epoch time: 19.32 s +2024-11-22 22:23:49.074296: +2024-11-22 22:23:49.075075: Epoch 6417 +2024-11-22 22:23:49.075197: Current learning rate: 0.00233 +2024-11-22 22:24:08.332505: train_loss -0.8126 +2024-11-22 22:24:08.340675: val_loss -0.7894 +2024-11-22 22:24:08.340833: Pseudo dice [0.8669] +2024-11-22 22:24:08.340938: Epoch time: 19.26 s +2024-11-22 22:24:09.231925: +2024-11-22 22:24:09.233104: Epoch 6418 +2024-11-22 22:24:09.233232: Current learning rate: 0.00233 +2024-11-22 22:24:28.208215: train_loss -0.8144 +2024-11-22 22:24:28.212579: val_loss -0.7672 +2024-11-22 22:24:28.212744: Pseudo dice [0.8515] +2024-11-22 22:24:28.212848: Epoch time: 18.98 s +2024-11-22 22:24:29.098554: +2024-11-22 22:24:29.099102: Epoch 6419 +2024-11-22 22:24:29.099234: Current learning rate: 0.00232 +2024-11-22 22:24:48.904959: train_loss -0.8093 +2024-11-22 22:24:48.912937: val_loss -0.7688 +2024-11-22 22:24:48.913386: Pseudo dice [0.859] +2024-11-22 22:24:48.913533: Epoch time: 19.81 s +2024-11-22 22:24:49.930073: +2024-11-22 22:24:49.931521: Epoch 6420 +2024-11-22 22:24:49.931653: Current learning rate: 0.00232 +2024-11-22 22:25:09.547701: train_loss -0.8071 +2024-11-22 22:25:09.553608: val_loss -0.7881 +2024-11-22 22:25:09.553727: Pseudo dice [0.8666] +2024-11-22 22:25:09.553814: Epoch time: 19.62 s +2024-11-22 22:25:10.450406: +2024-11-22 22:25:10.451744: Epoch 6421 +2024-11-22 22:25:10.451877: Current learning rate: 0.00232 +2024-11-22 22:25:29.098399: train_loss -0.8123 +2024-11-22 22:25:29.100476: val_loss -0.7792 +2024-11-22 22:25:29.100599: Pseudo dice [0.8522] +2024-11-22 22:25:29.100694: Epoch time: 18.65 s +2024-11-22 22:25:30.539189: +2024-11-22 22:25:30.540689: Epoch 6422 +2024-11-22 22:25:30.540827: Current learning rate: 0.00232 +2024-11-22 22:25:48.762967: train_loss -0.8075 +2024-11-22 22:25:48.772185: val_loss -0.7614 +2024-11-22 22:25:48.772387: Pseudo dice [0.843] +2024-11-22 22:25:48.772493: Epoch time: 18.22 s +2024-11-22 22:25:49.704191: +2024-11-22 22:25:49.705020: Epoch 6423 +2024-11-22 22:25:49.705156: Current learning rate: 0.00232 +2024-11-22 22:26:09.086615: train_loss -0.8087 +2024-11-22 22:26:09.093765: val_loss -0.7554 +2024-11-22 22:26:09.093918: Pseudo dice [0.847] +2024-11-22 22:26:09.094015: Epoch time: 19.38 s +2024-11-22 22:26:10.082533: +2024-11-22 22:26:10.083833: Epoch 6424 +2024-11-22 22:26:10.083956: Current learning rate: 0.00232 +2024-11-22 22:26:30.388631: train_loss -0.8114 +2024-11-22 22:26:30.396393: val_loss -0.7797 +2024-11-22 22:26:30.396541: Pseudo dice [0.8582] +2024-11-22 22:26:30.396646: Epoch time: 20.31 s +2024-11-22 22:26:31.484478: +2024-11-22 22:26:31.485396: Epoch 6425 +2024-11-22 22:26:31.485535: Current learning rate: 0.00232 +2024-11-22 22:26:50.698845: train_loss -0.818 +2024-11-22 22:26:50.712848: val_loss -0.7839 +2024-11-22 22:26:50.712985: Pseudo dice [0.8529] +2024-11-22 22:26:50.713097: Epoch time: 19.22 s +2024-11-22 22:26:51.691214: +2024-11-22 22:26:51.692353: Epoch 6426 +2024-11-22 22:26:51.692489: Current learning rate: 0.00231 +2024-11-22 22:27:10.677321: train_loss -0.8201 +2024-11-22 22:27:10.682737: val_loss -0.7749 +2024-11-22 22:27:10.682888: Pseudo dice [0.8352] +2024-11-22 22:27:10.682997: Epoch time: 18.99 s +2024-11-22 22:27:11.585288: +2024-11-22 22:27:11.586785: Epoch 6427 +2024-11-22 22:27:11.586904: Current learning rate: 0.00231 +2024-11-22 22:27:30.941647: train_loss -0.8098 +2024-11-22 22:27:30.947976: val_loss -0.7937 +2024-11-22 22:27:30.948138: Pseudo dice [0.8514] +2024-11-22 22:27:30.948546: Epoch time: 19.36 s +2024-11-22 22:27:31.901963: +2024-11-22 22:27:31.903481: Epoch 6428 +2024-11-22 22:27:31.903631: Current learning rate: 0.00231 +2024-11-22 22:27:50.960601: train_loss -0.8116 +2024-11-22 22:27:50.963621: val_loss -0.7792 +2024-11-22 22:27:50.963750: Pseudo dice [0.8609] +2024-11-22 22:27:50.963843: Epoch time: 19.06 s +2024-11-22 22:27:51.923306: +2024-11-22 22:27:51.924632: Epoch 6429 +2024-11-22 22:27:51.924754: Current learning rate: 0.00231 +2024-11-22 22:28:10.935807: train_loss -0.8088 +2024-11-22 22:28:10.940700: val_loss -0.762 +2024-11-22 22:28:10.940835: Pseudo dice [0.8466] +2024-11-22 22:28:10.940940: Epoch time: 19.01 s +2024-11-22 22:28:11.840315: +2024-11-22 22:28:11.842075: Epoch 6430 +2024-11-22 22:28:11.842203: Current learning rate: 0.00231 +2024-11-22 22:28:31.522462: train_loss -0.8156 +2024-11-22 22:28:31.534749: val_loss -0.7691 +2024-11-22 22:28:31.534879: Pseudo dice [0.8447] +2024-11-22 22:28:31.534988: Epoch time: 19.68 s +2024-11-22 22:28:32.485822: +2024-11-22 22:28:32.487147: Epoch 6431 +2024-11-22 22:28:32.487276: Current learning rate: 0.00231 +2024-11-22 22:28:51.384592: train_loss -0.8143 +2024-11-22 22:28:51.393097: val_loss -0.7867 +2024-11-22 22:28:51.393233: Pseudo dice [0.8607] +2024-11-22 22:28:51.393321: Epoch time: 18.9 s +2024-11-22 22:28:52.370131: +2024-11-22 22:28:52.372213: Epoch 6432 +2024-11-22 22:28:52.372448: Current learning rate: 0.00231 +2024-11-22 22:29:10.863158: train_loss -0.8135 +2024-11-22 22:29:10.890437: val_loss -0.7645 +2024-11-22 22:29:10.890638: Pseudo dice [0.8468] +2024-11-22 22:29:10.890750: Epoch time: 18.49 s +2024-11-22 22:29:12.266963: +2024-11-22 22:29:12.268729: Epoch 6433 +2024-11-22 22:29:12.268867: Current learning rate: 0.00231 +2024-11-22 22:29:30.749940: train_loss -0.8135 +2024-11-22 22:29:30.757774: val_loss -0.7753 +2024-11-22 22:29:30.758791: Pseudo dice [0.8596] +2024-11-22 22:29:30.758953: Epoch time: 18.48 s +2024-11-22 22:29:31.801420: +2024-11-22 22:29:31.801685: Epoch 6434 +2024-11-22 22:29:31.801812: Current learning rate: 0.0023 +2024-11-22 22:29:52.563046: train_loss -0.8005 +2024-11-22 22:29:52.570083: val_loss -0.7752 +2024-11-22 22:29:52.570240: Pseudo dice [0.8494] +2024-11-22 22:29:52.570342: Epoch time: 20.76 s +2024-11-22 22:29:53.844835: +2024-11-22 22:29:53.846851: Epoch 6435 +2024-11-22 22:29:53.846975: Current learning rate: 0.0023 +2024-11-22 22:30:13.294374: train_loss -0.8027 +2024-11-22 22:30:13.299740: val_loss -0.7822 +2024-11-22 22:30:13.299876: Pseudo dice [0.8627] +2024-11-22 22:30:13.299964: Epoch time: 19.45 s +2024-11-22 22:30:14.236732: +2024-11-22 22:30:14.238460: Epoch 6436 +2024-11-22 22:30:14.238581: Current learning rate: 0.0023 +2024-11-22 22:30:33.906341: train_loss -0.8137 +2024-11-22 22:30:33.909303: val_loss -0.7708 +2024-11-22 22:30:33.909441: Pseudo dice [0.859] +2024-11-22 22:30:33.909552: Epoch time: 19.67 s +2024-11-22 22:30:34.900245: +2024-11-22 22:30:34.901362: Epoch 6437 +2024-11-22 22:30:34.901502: Current learning rate: 0.0023 +2024-11-22 22:30:54.693993: train_loss -0.8127 +2024-11-22 22:30:54.700223: val_loss -0.7664 +2024-11-22 22:30:54.700355: Pseudo dice [0.8529] +2024-11-22 22:30:54.700469: Epoch time: 19.79 s +2024-11-22 22:30:55.727656: +2024-11-22 22:30:55.728185: Epoch 6438 +2024-11-22 22:30:55.728305: Current learning rate: 0.0023 +2024-11-22 22:31:15.812850: train_loss -0.8088 +2024-11-22 22:31:15.824856: val_loss -0.7712 +2024-11-22 22:31:15.825000: Pseudo dice [0.8615] +2024-11-22 22:31:15.825095: Epoch time: 20.09 s +2024-11-22 22:31:16.796741: +2024-11-22 22:31:16.798654: Epoch 6439 +2024-11-22 22:31:16.798779: Current learning rate: 0.0023 +2024-11-22 22:31:35.835318: train_loss -0.8086 +2024-11-22 22:31:35.841389: val_loss -0.7938 +2024-11-22 22:31:35.841523: Pseudo dice [0.8531] +2024-11-22 22:31:35.841614: Epoch time: 19.04 s +2024-11-22 22:31:36.813956: +2024-11-22 22:31:36.814169: Epoch 6440 +2024-11-22 22:31:36.814303: Current learning rate: 0.0023 +2024-11-22 22:31:56.294877: train_loss -0.8091 +2024-11-22 22:31:56.296392: val_loss -0.7968 +2024-11-22 22:31:56.296499: Pseudo dice [0.8578] +2024-11-22 22:31:56.296589: Epoch time: 19.48 s +2024-11-22 22:31:57.181731: +2024-11-22 22:31:57.181946: Epoch 6441 +2024-11-22 22:31:57.182078: Current learning rate: 0.00229 +2024-11-22 22:32:17.043070: train_loss -0.8095 +2024-11-22 22:32:17.043597: val_loss -0.7714 +2024-11-22 22:32:17.043684: Pseudo dice [0.8608] +2024-11-22 22:32:17.043776: Epoch time: 19.86 s +2024-11-22 22:32:17.931086: +2024-11-22 22:32:17.931294: Epoch 6442 +2024-11-22 22:32:17.931411: Current learning rate: 0.00229 +2024-11-22 22:32:36.588897: train_loss -0.8111 +2024-11-22 22:32:36.589162: val_loss -0.7826 +2024-11-22 22:32:36.592964: Pseudo dice [0.8583] +2024-11-22 22:32:36.598356: Epoch time: 18.66 s +2024-11-22 22:32:37.657314: +2024-11-22 22:32:37.657506: Epoch 6443 +2024-11-22 22:32:37.657658: Current learning rate: 0.00229 +2024-11-22 22:32:57.043419: train_loss -0.8134 +2024-11-22 22:32:57.047082: val_loss -0.7924 +2024-11-22 22:32:57.047260: Pseudo dice [0.8555] +2024-11-22 22:32:57.047400: Epoch time: 19.39 s +2024-11-22 22:32:58.390444: +2024-11-22 22:32:58.390657: Epoch 6444 +2024-11-22 22:32:58.390798: Current learning rate: 0.00229 +2024-11-22 22:33:16.602178: train_loss -0.8142 +2024-11-22 22:33:16.605101: val_loss -0.7726 +2024-11-22 22:33:16.605232: Pseudo dice [0.8543] +2024-11-22 22:33:16.605338: Epoch time: 18.21 s +2024-11-22 22:33:17.627330: +2024-11-22 22:33:17.627747: Epoch 6445 +2024-11-22 22:33:17.627859: Current learning rate: 0.00229 +2024-11-22 22:33:36.141416: train_loss -0.8118 +2024-11-22 22:33:36.147534: val_loss -0.776 +2024-11-22 22:33:36.147670: Pseudo dice [0.8529] +2024-11-22 22:33:36.147772: Epoch time: 18.51 s +2024-11-22 22:33:37.077183: +2024-11-22 22:33:37.077433: Epoch 6446 +2024-11-22 22:33:37.077557: Current learning rate: 0.00229 +2024-11-22 22:33:55.506402: train_loss -0.8151 +2024-11-22 22:33:55.510831: val_loss -0.7825 +2024-11-22 22:33:55.510972: Pseudo dice [0.8639] +2024-11-22 22:33:55.511093: Epoch time: 18.43 s +2024-11-22 22:33:56.405439: +2024-11-22 22:33:56.405662: Epoch 6447 +2024-11-22 22:33:56.405788: Current learning rate: 0.00229 +2024-11-22 22:34:14.900990: train_loss -0.8114 +2024-11-22 22:34:14.901547: val_loss -0.7883 +2024-11-22 22:34:14.901639: Pseudo dice [0.8576] +2024-11-22 22:34:14.901731: Epoch time: 18.5 s +2024-11-22 22:34:15.800014: +2024-11-22 22:34:15.800239: Epoch 6448 +2024-11-22 22:34:15.800378: Current learning rate: 0.00229 +2024-11-22 22:34:35.111154: train_loss -0.8152 +2024-11-22 22:34:35.111611: val_loss -0.7778 +2024-11-22 22:34:35.111696: Pseudo dice [0.8532] +2024-11-22 22:34:35.111784: Epoch time: 19.31 s +2024-11-22 22:34:36.001844: +2024-11-22 22:34:36.002038: Epoch 6449 +2024-11-22 22:34:36.002164: Current learning rate: 0.00228 +2024-11-22 22:34:55.834131: train_loss -0.8116 +2024-11-22 22:34:55.849777: val_loss -0.7659 +2024-11-22 22:34:55.849934: Pseudo dice [0.8457] +2024-11-22 22:34:55.850102: Epoch time: 19.83 s +2024-11-22 22:34:57.154324: +2024-11-22 22:34:57.154762: Epoch 6450 +2024-11-22 22:34:57.154905: Current learning rate: 0.00228 +2024-11-22 22:35:15.792541: train_loss -0.8141 +2024-11-22 22:35:15.800553: val_loss -0.7622 +2024-11-22 22:35:15.800715: Pseudo dice [0.8476] +2024-11-22 22:35:15.800816: Epoch time: 18.64 s +2024-11-22 22:35:16.984274: +2024-11-22 22:35:16.985188: Epoch 6451 +2024-11-22 22:35:16.985313: Current learning rate: 0.00228 +2024-11-22 22:35:36.362482: train_loss -0.8031 +2024-11-22 22:35:36.365024: val_loss -0.773 +2024-11-22 22:35:36.365159: Pseudo dice [0.8571] +2024-11-22 22:35:36.365260: Epoch time: 19.38 s +2024-11-22 22:35:37.397831: +2024-11-22 22:35:37.399173: Epoch 6452 +2024-11-22 22:35:37.399307: Current learning rate: 0.00228 +2024-11-22 22:35:57.041625: train_loss -0.807 +2024-11-22 22:35:57.045750: val_loss -0.7604 +2024-11-22 22:35:57.045863: Pseudo dice [0.8551] +2024-11-22 22:35:57.045979: Epoch time: 19.64 s +2024-11-22 22:35:57.942964: +2024-11-22 22:35:57.943743: Epoch 6453 +2024-11-22 22:35:57.943869: Current learning rate: 0.00228 +2024-11-22 22:36:16.232210: train_loss -0.8064 +2024-11-22 22:36:16.237029: val_loss -0.7634 +2024-11-22 22:36:16.237174: Pseudo dice [0.8605] +2024-11-22 22:36:16.237288: Epoch time: 18.29 s +2024-11-22 22:36:17.171357: +2024-11-22 22:36:17.171978: Epoch 6454 +2024-11-22 22:36:17.172103: Current learning rate: 0.00228 +2024-11-22 22:36:37.291244: train_loss -0.8078 +2024-11-22 22:36:37.296228: val_loss -0.7702 +2024-11-22 22:36:37.296360: Pseudo dice [0.8661] +2024-11-22 22:36:37.296475: Epoch time: 20.12 s +2024-11-22 22:36:38.693940: +2024-11-22 22:36:38.694920: Epoch 6455 +2024-11-22 22:36:38.695036: Current learning rate: 0.00228 +2024-11-22 22:36:58.446852: train_loss -0.8136 +2024-11-22 22:36:58.455364: val_loss -0.796 +2024-11-22 22:36:58.455496: Pseudo dice [0.8647] +2024-11-22 22:36:58.455584: Epoch time: 19.75 s +2024-11-22 22:36:59.467564: +2024-11-22 22:36:59.469072: Epoch 6456 +2024-11-22 22:36:59.469217: Current learning rate: 0.00228 +2024-11-22 22:37:18.593431: train_loss -0.8118 +2024-11-22 22:37:18.595697: val_loss -0.7813 +2024-11-22 22:37:18.595805: Pseudo dice [0.8478] +2024-11-22 22:37:18.595898: Epoch time: 19.13 s +2024-11-22 22:37:19.479845: +2024-11-22 22:37:19.481330: Epoch 6457 +2024-11-22 22:37:19.481459: Current learning rate: 0.00227 +2024-11-22 22:37:38.571010: train_loss -0.8167 +2024-11-22 22:37:38.577026: val_loss -0.7677 +2024-11-22 22:37:38.577151: Pseudo dice [0.849] +2024-11-22 22:37:38.591575: Epoch time: 19.09 s +2024-11-22 22:37:39.595081: +2024-11-22 22:37:39.596699: Epoch 6458 +2024-11-22 22:37:39.596848: Current learning rate: 0.00227 +2024-11-22 22:37:58.829451: train_loss -0.8128 +2024-11-22 22:37:58.835869: val_loss -0.7749 +2024-11-22 22:37:58.835999: Pseudo dice [0.863] +2024-11-22 22:37:58.836091: Epoch time: 19.24 s +2024-11-22 22:37:59.727984: +2024-11-22 22:37:59.728650: Epoch 6459 +2024-11-22 22:37:59.728783: Current learning rate: 0.00227 +2024-11-22 22:38:19.513070: train_loss -0.8118 +2024-11-22 22:38:19.515493: val_loss -0.7601 +2024-11-22 22:38:19.515613: Pseudo dice [0.8566] +2024-11-22 22:38:19.515712: Epoch time: 19.79 s +2024-11-22 22:38:20.404633: +2024-11-22 22:38:20.405920: Epoch 6460 +2024-11-22 22:38:20.406049: Current learning rate: 0.00227 +2024-11-22 22:38:39.170085: train_loss -0.8104 +2024-11-22 22:38:39.175357: val_loss -0.7687 +2024-11-22 22:38:39.175517: Pseudo dice [0.8436] +2024-11-22 22:38:39.175652: Epoch time: 18.77 s +2024-11-22 22:38:40.073225: +2024-11-22 22:38:40.074512: Epoch 6461 +2024-11-22 22:38:40.074650: Current learning rate: 0.00227 +2024-11-22 22:39:00.205349: train_loss -0.8066 +2024-11-22 22:39:00.212646: val_loss -0.8064 +2024-11-22 22:39:00.213076: Pseudo dice [0.8669] +2024-11-22 22:39:00.213183: Epoch time: 20.13 s +2024-11-22 22:39:01.275038: +2024-11-22 22:39:01.276843: Epoch 6462 +2024-11-22 22:39:01.276970: Current learning rate: 0.00227 +2024-11-22 22:39:21.383385: train_loss -0.8091 +2024-11-22 22:39:21.387373: val_loss -0.7674 +2024-11-22 22:39:21.387512: Pseudo dice [0.844] +2024-11-22 22:39:21.387602: Epoch time: 20.11 s +2024-11-22 22:39:22.319887: +2024-11-22 22:39:22.320970: Epoch 6463 +2024-11-22 22:39:22.321111: Current learning rate: 0.00227 +2024-11-22 22:39:41.773191: train_loss -0.8068 +2024-11-22 22:39:41.781144: val_loss -0.7863 +2024-11-22 22:39:41.781281: Pseudo dice [0.8591] +2024-11-22 22:39:41.781378: Epoch time: 19.45 s +2024-11-22 22:39:42.770221: +2024-11-22 22:39:42.771461: Epoch 6464 +2024-11-22 22:39:42.771583: Current learning rate: 0.00226 +2024-11-22 22:40:01.045398: train_loss -0.8028 +2024-11-22 22:40:01.047720: val_loss -0.7535 +2024-11-22 22:40:01.047843: Pseudo dice [0.8496] +2024-11-22 22:40:01.047939: Epoch time: 18.28 s +2024-11-22 22:40:01.932745: +2024-11-22 22:40:01.934557: Epoch 6465 +2024-11-22 22:40:01.934687: Current learning rate: 0.00226 +2024-11-22 22:40:22.215258: train_loss -0.7917 +2024-11-22 22:40:22.227908: val_loss -0.7576 +2024-11-22 22:40:22.228043: Pseudo dice [0.8471] +2024-11-22 22:40:22.228134: Epoch time: 20.28 s +2024-11-22 22:40:23.723652: +2024-11-22 22:40:23.724922: Epoch 6466 +2024-11-22 22:40:23.725082: Current learning rate: 0.00226 +2024-11-22 22:40:43.820993: train_loss -0.8041 +2024-11-22 22:40:43.832469: val_loss -0.7656 +2024-11-22 22:40:43.832586: Pseudo dice [0.8487] +2024-11-22 22:40:43.832684: Epoch time: 20.1 s +2024-11-22 22:40:44.788953: +2024-11-22 22:40:44.790244: Epoch 6467 +2024-11-22 22:40:44.790371: Current learning rate: 0.00226 +2024-11-22 22:41:04.470475: train_loss -0.8106 +2024-11-22 22:41:04.474818: val_loss -0.7846 +2024-11-22 22:41:04.474959: Pseudo dice [0.8597] +2024-11-22 22:41:04.475046: Epoch time: 19.68 s +2024-11-22 22:41:05.406461: +2024-11-22 22:41:05.407377: Epoch 6468 +2024-11-22 22:41:05.407506: Current learning rate: 0.00226 +2024-11-22 22:41:25.560029: train_loss -0.8064 +2024-11-22 22:41:25.567151: val_loss -0.7684 +2024-11-22 22:41:25.567286: Pseudo dice [0.8518] +2024-11-22 22:41:25.567392: Epoch time: 20.15 s +2024-11-22 22:41:26.675106: +2024-11-22 22:41:26.675910: Epoch 6469 +2024-11-22 22:41:26.676046: Current learning rate: 0.00226 +2024-11-22 22:41:45.718588: train_loss -0.8097 +2024-11-22 22:41:45.721188: val_loss -0.7602 +2024-11-22 22:41:45.721310: Pseudo dice [0.8558] +2024-11-22 22:41:45.721395: Epoch time: 19.04 s +2024-11-22 22:41:46.657376: +2024-11-22 22:41:46.658873: Epoch 6470 +2024-11-22 22:41:46.658995: Current learning rate: 0.00226 +2024-11-22 22:42:06.178725: train_loss -0.806 +2024-11-22 22:42:06.213307: val_loss -0.7969 +2024-11-22 22:42:06.213482: Pseudo dice [0.8534] +2024-11-22 22:42:06.213585: Epoch time: 19.52 s +2024-11-22 22:42:07.135703: +2024-11-22 22:42:07.136739: Epoch 6471 +2024-11-22 22:42:07.136873: Current learning rate: 0.00226 +2024-11-22 22:42:26.084980: train_loss -0.8049 +2024-11-22 22:42:26.095144: val_loss -0.7604 +2024-11-22 22:42:26.095277: Pseudo dice [0.844] +2024-11-22 22:42:26.095390: Epoch time: 18.95 s +2024-11-22 22:42:27.010606: +2024-11-22 22:42:27.011330: Epoch 6472 +2024-11-22 22:42:27.011454: Current learning rate: 0.00225 +2024-11-22 22:42:45.977328: train_loss -0.812 +2024-11-22 22:42:45.984745: val_loss -0.7556 +2024-11-22 22:42:45.984882: Pseudo dice [0.8511] +2024-11-22 22:42:45.984976: Epoch time: 18.97 s +2024-11-22 22:42:47.202890: +2024-11-22 22:42:47.203653: Epoch 6473 +2024-11-22 22:42:47.203789: Current learning rate: 0.00225 +2024-11-22 22:43:07.263862: train_loss -0.8104 +2024-11-22 22:43:07.268980: val_loss -0.7982 +2024-11-22 22:43:07.269130: Pseudo dice [0.8657] +2024-11-22 22:43:07.269226: Epoch time: 20.06 s +2024-11-22 22:43:08.201154: +2024-11-22 22:43:08.201669: Epoch 6474 +2024-11-22 22:43:08.201792: Current learning rate: 0.00225 +2024-11-22 22:43:26.579712: train_loss -0.8083 +2024-11-22 22:43:26.587187: val_loss -0.7862 +2024-11-22 22:43:26.587379: Pseudo dice [0.8662] +2024-11-22 22:43:26.587486: Epoch time: 18.38 s +2024-11-22 22:43:27.690581: +2024-11-22 22:43:27.692051: Epoch 6475 +2024-11-22 22:43:27.692190: Current learning rate: 0.00225 +2024-11-22 22:43:47.658951: train_loss -0.8053 +2024-11-22 22:43:47.662467: val_loss -0.7798 +2024-11-22 22:43:47.662591: Pseudo dice [0.8677] +2024-11-22 22:43:47.662760: Epoch time: 19.97 s +2024-11-22 22:43:48.747776: +2024-11-22 22:43:48.748500: Epoch 6476 +2024-11-22 22:43:48.748622: Current learning rate: 0.00225 +2024-11-22 22:44:07.959190: train_loss -0.807 +2024-11-22 22:44:07.973973: val_loss -0.7876 +2024-11-22 22:44:07.974125: Pseudo dice [0.8641] +2024-11-22 22:44:07.974241: Epoch time: 19.21 s +2024-11-22 22:44:09.456609: +2024-11-22 22:44:09.458131: Epoch 6477 +2024-11-22 22:44:09.458263: Current learning rate: 0.00225 +2024-11-22 22:44:28.996950: train_loss -0.8221 +2024-11-22 22:44:28.999271: val_loss -0.7733 +2024-11-22 22:44:28.999399: Pseudo dice [0.8458] +2024-11-22 22:44:28.999514: Epoch time: 19.54 s +2024-11-22 22:44:30.135123: +2024-11-22 22:44:30.136395: Epoch 6478 +2024-11-22 22:44:30.136526: Current learning rate: 0.00225 +2024-11-22 22:44:48.658992: train_loss -0.8136 +2024-11-22 22:44:48.680506: val_loss -0.7674 +2024-11-22 22:44:48.680657: Pseudo dice [0.8502] +2024-11-22 22:44:48.680753: Epoch time: 18.52 s +2024-11-22 22:44:49.751734: +2024-11-22 22:44:49.753749: Epoch 6479 +2024-11-22 22:44:49.753882: Current learning rate: 0.00224 +2024-11-22 22:45:08.525456: train_loss -0.8114 +2024-11-22 22:45:08.533810: val_loss -0.7823 +2024-11-22 22:45:08.533966: Pseudo dice [0.8557] +2024-11-22 22:45:08.534179: Epoch time: 18.77 s +2024-11-22 22:45:09.592917: +2024-11-22 22:45:09.594203: Epoch 6480 +2024-11-22 22:45:09.594341: Current learning rate: 0.00224 +2024-11-22 22:45:30.151262: train_loss -0.8051 +2024-11-22 22:45:30.171239: val_loss -0.7589 +2024-11-22 22:45:30.171393: Pseudo dice [0.8549] +2024-11-22 22:45:30.171506: Epoch time: 20.56 s +2024-11-22 22:45:31.101799: +2024-11-22 22:45:31.102350: Epoch 6481 +2024-11-22 22:45:31.102491: Current learning rate: 0.00224 +2024-11-22 22:45:50.917187: train_loss -0.8 +2024-11-22 22:45:50.947102: val_loss -0.7433 +2024-11-22 22:45:50.947257: Pseudo dice [0.8411] +2024-11-22 22:45:50.947356: Epoch time: 19.82 s +2024-11-22 22:45:51.941015: +2024-11-22 22:45:51.942555: Epoch 6482 +2024-11-22 22:45:51.942692: Current learning rate: 0.00224 +2024-11-22 22:46:11.514600: train_loss -0.8089 +2024-11-22 22:46:11.528081: val_loss -0.7636 +2024-11-22 22:46:11.528207: Pseudo dice [0.8588] +2024-11-22 22:46:11.528290: Epoch time: 19.57 s +2024-11-22 22:46:12.677050: +2024-11-22 22:46:12.677776: Epoch 6483 +2024-11-22 22:46:12.678080: Current learning rate: 0.00224 +2024-11-22 22:46:31.430821: train_loss -0.8055 +2024-11-22 22:46:31.432765: val_loss -0.7854 +2024-11-22 22:46:31.432873: Pseudo dice [0.852] +2024-11-22 22:46:31.432976: Epoch time: 18.75 s +2024-11-22 22:46:32.318279: +2024-11-22 22:46:32.319001: Epoch 6484 +2024-11-22 22:46:32.319123: Current learning rate: 0.00224 +2024-11-22 22:46:51.395782: train_loss -0.8039 +2024-11-22 22:46:51.400915: val_loss -0.7809 +2024-11-22 22:46:51.401065: Pseudo dice [0.86] +2024-11-22 22:46:51.401174: Epoch time: 19.08 s +2024-11-22 22:46:52.304828: +2024-11-22 22:46:52.306738: Epoch 6485 +2024-11-22 22:46:52.306884: Current learning rate: 0.00224 +2024-11-22 22:47:12.415049: train_loss -0.8096 +2024-11-22 22:47:12.422722: val_loss -0.7592 +2024-11-22 22:47:12.422851: Pseudo dice [0.8469] +2024-11-22 22:47:12.422964: Epoch time: 20.11 s +2024-11-22 22:47:13.461790: +2024-11-22 22:47:13.462990: Epoch 6486 +2024-11-22 22:47:13.463145: Current learning rate: 0.00224 +2024-11-22 22:47:33.327355: train_loss -0.8157 +2024-11-22 22:47:33.334129: val_loss -0.7811 +2024-11-22 22:47:33.334250: Pseudo dice [0.8577] +2024-11-22 22:47:33.334344: Epoch time: 19.87 s +2024-11-22 22:47:34.338195: +2024-11-22 22:47:34.339983: Epoch 6487 +2024-11-22 22:47:34.340134: Current learning rate: 0.00223 +2024-11-22 22:47:53.017261: train_loss -0.8124 +2024-11-22 22:47:53.028204: val_loss -0.7819 +2024-11-22 22:47:53.028382: Pseudo dice [0.8698] +2024-11-22 22:47:53.028490: Epoch time: 18.68 s +2024-11-22 22:47:54.421654: +2024-11-22 22:47:54.422559: Epoch 6488 +2024-11-22 22:47:54.422694: Current learning rate: 0.00223 +2024-11-22 22:48:12.640203: train_loss -0.8178 +2024-11-22 22:48:12.646457: val_loss -0.7888 +2024-11-22 22:48:12.646600: Pseudo dice [0.8547] +2024-11-22 22:48:12.646713: Epoch time: 18.22 s +2024-11-22 22:48:13.539656: +2024-11-22 22:48:13.540785: Epoch 6489 +2024-11-22 22:48:13.540916: Current learning rate: 0.00223 +2024-11-22 22:48:33.219933: train_loss -0.8138 +2024-11-22 22:48:33.222066: val_loss -0.7978 +2024-11-22 22:48:33.222176: Pseudo dice [0.8472] +2024-11-22 22:48:33.222271: Epoch time: 19.68 s +2024-11-22 22:48:34.114086: +2024-11-22 22:48:34.115133: Epoch 6490 +2024-11-22 22:48:34.115259: Current learning rate: 0.00223 +2024-11-22 22:48:53.978267: train_loss -0.8076 +2024-11-22 22:48:53.983246: val_loss -0.8034 +2024-11-22 22:48:53.983394: Pseudo dice [0.8488] +2024-11-22 22:48:53.983487: Epoch time: 19.86 s +2024-11-22 22:48:55.053122: +2024-11-22 22:48:55.054715: Epoch 6491 +2024-11-22 22:48:55.054842: Current learning rate: 0.00223 +2024-11-22 22:49:13.784170: train_loss -0.8169 +2024-11-22 22:49:13.792364: val_loss -0.785 +2024-11-22 22:49:13.792508: Pseudo dice [0.8615] +2024-11-22 22:49:13.792670: Epoch time: 18.73 s +2024-11-22 22:49:14.772354: +2024-11-22 22:49:14.773414: Epoch 6492 +2024-11-22 22:49:14.773546: Current learning rate: 0.00223 +2024-11-22 22:49:34.268636: train_loss -0.8103 +2024-11-22 22:49:34.283903: val_loss -0.7756 +2024-11-22 22:49:34.284037: Pseudo dice [0.8611] +2024-11-22 22:49:34.284142: Epoch time: 19.5 s +2024-11-22 22:49:35.193177: +2024-11-22 22:49:35.194082: Epoch 6493 +2024-11-22 22:49:35.194207: Current learning rate: 0.00223 +2024-11-22 22:49:54.066027: train_loss -0.8143 +2024-11-22 22:49:54.072381: val_loss -0.7944 +2024-11-22 22:49:54.072561: Pseudo dice [0.8585] +2024-11-22 22:49:54.072659: Epoch time: 18.87 s +2024-11-22 22:49:54.996051: +2024-11-22 22:49:54.997524: Epoch 6494 +2024-11-22 22:49:54.997649: Current learning rate: 0.00222 +2024-11-22 22:50:14.573830: train_loss -0.8123 +2024-11-22 22:50:14.589426: val_loss -0.7952 +2024-11-22 22:50:14.589597: Pseudo dice [0.8602] +2024-11-22 22:50:14.589695: Epoch time: 19.58 s +2024-11-22 22:50:15.531504: +2024-11-22 22:50:15.532786: Epoch 6495 +2024-11-22 22:50:15.532923: Current learning rate: 0.00222 +2024-11-22 22:50:35.532933: train_loss -0.8103 +2024-11-22 22:50:35.540513: val_loss -0.7772 +2024-11-22 22:50:35.540628: Pseudo dice [0.8533] +2024-11-22 22:50:35.540912: Epoch time: 20.0 s +2024-11-22 22:50:36.439265: +2024-11-22 22:50:36.440551: Epoch 6496 +2024-11-22 22:50:36.440690: Current learning rate: 0.00222 +2024-11-22 22:50:55.828229: train_loss -0.8077 +2024-11-22 22:50:55.833367: val_loss -0.8036 +2024-11-22 22:50:55.833479: Pseudo dice [0.8533] +2024-11-22 22:50:55.833577: Epoch time: 19.39 s +2024-11-22 22:50:56.883419: +2024-11-22 22:50:56.884445: Epoch 6497 +2024-11-22 22:50:56.884591: Current learning rate: 0.00222 +2024-11-22 22:51:16.497319: train_loss -0.8208 +2024-11-22 22:51:16.506252: val_loss -0.7927 +2024-11-22 22:51:16.506459: Pseudo dice [0.8525] +2024-11-22 22:51:16.506581: Epoch time: 19.61 s +2024-11-22 22:51:17.590406: +2024-11-22 22:51:17.591733: Epoch 6498 +2024-11-22 22:51:17.591863: Current learning rate: 0.00222 +2024-11-22 22:51:36.886278: train_loss -0.82 +2024-11-22 22:51:36.890080: val_loss -0.781 +2024-11-22 22:51:36.890218: Pseudo dice [0.8604] +2024-11-22 22:51:36.890305: Epoch time: 19.3 s +2024-11-22 22:51:38.225828: +2024-11-22 22:51:38.228159: Epoch 6499 +2024-11-22 22:51:38.228315: Current learning rate: 0.00222 +2024-11-22 22:51:58.242108: train_loss -0.8161 +2024-11-22 22:51:58.256753: val_loss -0.7592 +2024-11-22 22:51:58.256914: Pseudo dice [0.8587] +2024-11-22 22:51:58.257028: Epoch time: 20.02 s +2024-11-22 22:51:59.619117: +2024-11-22 22:51:59.620720: Epoch 6500 +2024-11-22 22:51:59.620867: Current learning rate: 0.00222 +2024-11-22 22:52:19.743682: train_loss -0.8156 +2024-11-22 22:52:19.747098: val_loss -0.7875 +2024-11-22 22:52:19.747213: Pseudo dice [0.8541] +2024-11-22 22:52:19.747333: Epoch time: 20.13 s +2024-11-22 22:52:20.885876: +2024-11-22 22:52:20.887203: Epoch 6501 +2024-11-22 22:52:20.887324: Current learning rate: 0.00222 +2024-11-22 22:52:41.258725: train_loss -0.7962 +2024-11-22 22:52:41.262560: val_loss -0.7718 +2024-11-22 22:52:41.262690: Pseudo dice [0.8583] +2024-11-22 22:52:41.262801: Epoch time: 20.37 s +2024-11-22 22:52:42.162057: +2024-11-22 22:52:42.162493: Epoch 6502 +2024-11-22 22:52:42.162632: Current learning rate: 0.00221 +2024-11-22 22:53:00.983226: train_loss -0.8044 +2024-11-22 22:53:00.997496: val_loss -0.784 +2024-11-22 22:53:00.997657: Pseudo dice [0.8478] +2024-11-22 22:53:00.997772: Epoch time: 18.82 s +2024-11-22 22:53:01.990002: +2024-11-22 22:53:01.991442: Epoch 6503 +2024-11-22 22:53:01.991583: Current learning rate: 0.00221 +2024-11-22 22:53:21.557260: train_loss -0.8077 +2024-11-22 22:53:21.573225: val_loss -0.7564 +2024-11-22 22:53:21.573382: Pseudo dice [0.8613] +2024-11-22 22:53:21.573534: Epoch time: 19.57 s +2024-11-22 22:53:22.546970: +2024-11-22 22:53:22.548462: Epoch 6504 +2024-11-22 22:53:22.548594: Current learning rate: 0.00221 +2024-11-22 22:53:40.909250: train_loss -0.8172 +2024-11-22 22:53:40.923998: val_loss -0.7851 +2024-11-22 22:53:40.924127: Pseudo dice [0.853] +2024-11-22 22:53:40.924258: Epoch time: 18.36 s +2024-11-22 22:53:41.961539: +2024-11-22 22:53:41.962744: Epoch 6505 +2024-11-22 22:53:41.962878: Current learning rate: 0.00221 +2024-11-22 22:54:00.664105: train_loss -0.8176 +2024-11-22 22:54:00.670046: val_loss -0.7795 +2024-11-22 22:54:00.670190: Pseudo dice [0.8476] +2024-11-22 22:54:00.670279: Epoch time: 18.7 s +2024-11-22 22:54:01.584937: +2024-11-22 22:54:01.585756: Epoch 6506 +2024-11-22 22:54:01.585887: Current learning rate: 0.00221 +2024-11-22 22:54:21.673981: train_loss -0.8103 +2024-11-22 22:54:21.689619: val_loss -0.7662 +2024-11-22 22:54:21.689768: Pseudo dice [0.8401] +2024-11-22 22:54:21.689874: Epoch time: 20.09 s +2024-11-22 22:54:22.664622: +2024-11-22 22:54:22.665500: Epoch 6507 +2024-11-22 22:54:22.665641: Current learning rate: 0.00221 +2024-11-22 22:54:41.391116: train_loss -0.8117 +2024-11-22 22:54:41.393395: val_loss -0.7639 +2024-11-22 22:54:41.393497: Pseudo dice [0.8416] +2024-11-22 22:54:41.393583: Epoch time: 18.73 s +2024-11-22 22:54:42.566581: +2024-11-22 22:54:42.568348: Epoch 6508 +2024-11-22 22:54:42.568482: Current learning rate: 0.00221 +2024-11-22 22:55:02.283578: train_loss -0.8086 +2024-11-22 22:55:02.300889: val_loss -0.7912 +2024-11-22 22:55:02.301049: Pseudo dice [0.8553] +2024-11-22 22:55:02.301146: Epoch time: 19.72 s +2024-11-22 22:55:03.272432: +2024-11-22 22:55:03.273122: Epoch 6509 +2024-11-22 22:55:03.273254: Current learning rate: 0.0022 +2024-11-22 22:55:23.452161: train_loss -0.8104 +2024-11-22 22:55:23.455209: val_loss -0.8019 +2024-11-22 22:55:23.455346: Pseudo dice [0.858] +2024-11-22 22:55:23.455451: Epoch time: 20.18 s +2024-11-22 22:55:24.784364: +2024-11-22 22:55:24.785505: Epoch 6510 +2024-11-22 22:55:24.785628: Current learning rate: 0.0022 +2024-11-22 22:55:42.981794: train_loss -0.8208 +2024-11-22 22:55:42.988693: val_loss -0.776 +2024-11-22 22:55:42.988891: Pseudo dice [0.8627] +2024-11-22 22:55:42.988979: Epoch time: 18.2 s +2024-11-22 22:55:44.062378: +2024-11-22 22:55:44.064132: Epoch 6511 +2024-11-22 22:55:44.064269: Current learning rate: 0.0022 +2024-11-22 22:56:04.203184: train_loss -0.8074 +2024-11-22 22:56:04.211836: val_loss -0.7774 +2024-11-22 22:56:04.211980: Pseudo dice [0.8714] +2024-11-22 22:56:04.212087: Epoch time: 20.14 s +2024-11-22 22:56:05.120477: +2024-11-22 22:56:05.121073: Epoch 6512 +2024-11-22 22:56:05.121197: Current learning rate: 0.0022 +2024-11-22 22:56:23.745177: train_loss -0.8165 +2024-11-22 22:56:23.747288: val_loss -0.7683 +2024-11-22 22:56:23.747424: Pseudo dice [0.8561] +2024-11-22 22:56:23.747524: Epoch time: 18.63 s +2024-11-22 22:56:24.896094: +2024-11-22 22:56:24.896325: Epoch 6513 +2024-11-22 22:56:24.896461: Current learning rate: 0.0022 +2024-11-22 22:56:43.937615: train_loss -0.8155 +2024-11-22 22:56:43.939826: val_loss -0.7503 +2024-11-22 22:56:43.940004: Pseudo dice [0.8529] +2024-11-22 22:56:43.940107: Epoch time: 19.04 s +2024-11-22 22:56:44.880917: +2024-11-22 22:56:44.881119: Epoch 6514 +2024-11-22 22:56:44.881233: Current learning rate: 0.0022 +2024-11-22 22:57:03.519772: train_loss -0.8016 +2024-11-22 22:57:03.527287: val_loss -0.7976 +2024-11-22 22:57:03.527402: Pseudo dice [0.8618] +2024-11-22 22:57:03.527524: Epoch time: 18.64 s +2024-11-22 22:57:04.541734: +2024-11-22 22:57:04.541950: Epoch 6515 +2024-11-22 22:57:04.542092: Current learning rate: 0.0022 +2024-11-22 22:57:24.238363: train_loss -0.8026 +2024-11-22 22:57:24.238909: val_loss -0.7765 +2024-11-22 22:57:24.239000: Pseudo dice [0.8549] +2024-11-22 22:57:24.239089: Epoch time: 19.7 s +2024-11-22 22:57:25.123591: +2024-11-22 22:57:25.123801: Epoch 6516 +2024-11-22 22:57:25.123925: Current learning rate: 0.0022 +2024-11-22 22:57:44.258384: train_loss -0.8195 +2024-11-22 22:57:44.262113: val_loss -0.7785 +2024-11-22 22:57:44.262261: Pseudo dice [0.855] +2024-11-22 22:57:44.262369: Epoch time: 19.14 s +2024-11-22 22:57:45.196537: +2024-11-22 22:57:45.196749: Epoch 6517 +2024-11-22 22:57:45.196890: Current learning rate: 0.00219 +2024-11-22 22:58:03.622818: train_loss -0.8122 +2024-11-22 22:58:03.628174: val_loss -0.7809 +2024-11-22 22:58:03.628308: Pseudo dice [0.8546] +2024-11-22 22:58:03.628396: Epoch time: 18.43 s +2024-11-22 22:58:04.641850: +2024-11-22 22:58:04.642057: Epoch 6518 +2024-11-22 22:58:04.642182: Current learning rate: 0.00219 +2024-11-22 22:58:23.790769: train_loss -0.8199 +2024-11-22 22:58:23.795135: val_loss -0.7792 +2024-11-22 22:58:23.795309: Pseudo dice [0.8564] +2024-11-22 22:58:23.795416: Epoch time: 19.15 s +2024-11-22 22:58:24.778572: +2024-11-22 22:58:24.778771: Epoch 6519 +2024-11-22 22:58:24.778890: Current learning rate: 0.00219 +2024-11-22 22:58:44.061652: train_loss -0.8051 +2024-11-22 22:58:44.062159: val_loss -0.8032 +2024-11-22 22:58:44.062264: Pseudo dice [0.8559] +2024-11-22 22:58:44.062346: Epoch time: 19.28 s +2024-11-22 22:58:45.141193: +2024-11-22 22:58:45.141407: Epoch 6520 +2024-11-22 22:58:45.141551: Current learning rate: 0.00219 +2024-11-22 22:59:04.148299: train_loss -0.8104 +2024-11-22 22:59:04.148872: val_loss -0.769 +2024-11-22 22:59:04.148998: Pseudo dice [0.8695] +2024-11-22 22:59:04.149139: Epoch time: 19.01 s +2024-11-22 22:59:05.471483: +2024-11-22 22:59:05.471696: Epoch 6521 +2024-11-22 22:59:05.471819: Current learning rate: 0.00219 +2024-11-22 22:59:25.034997: train_loss -0.8082 +2024-11-22 22:59:25.037002: val_loss -0.7752 +2024-11-22 22:59:25.037109: Pseudo dice [0.8616] +2024-11-22 22:59:25.037199: Epoch time: 19.56 s +2024-11-22 22:59:25.929978: +2024-11-22 22:59:25.930190: Epoch 6522 +2024-11-22 22:59:25.930313: Current learning rate: 0.00219 +2024-11-22 22:59:45.935792: train_loss -0.8133 +2024-11-22 22:59:45.938350: val_loss -0.7877 +2024-11-22 22:59:45.938576: Pseudo dice [0.8627] +2024-11-22 22:59:45.938704: Epoch time: 20.01 s +2024-11-22 22:59:46.848917: +2024-11-22 22:59:46.849143: Epoch 6523 +2024-11-22 22:59:46.849264: Current learning rate: 0.00219 +2024-11-22 23:00:07.447468: train_loss -0.8116 +2024-11-22 23:00:07.449638: val_loss -0.7784 +2024-11-22 23:00:07.449793: Pseudo dice [0.8551] +2024-11-22 23:00:07.449896: Epoch time: 20.6 s +2024-11-22 23:00:08.543047: +2024-11-22 23:00:08.543306: Epoch 6524 +2024-11-22 23:00:08.543449: Current learning rate: 0.00218 +2024-11-22 23:00:28.772444: train_loss -0.8061 +2024-11-22 23:00:28.779166: val_loss -0.7823 +2024-11-22 23:00:28.779304: Pseudo dice [0.8618] +2024-11-22 23:00:28.779409: Epoch time: 20.23 s +2024-11-22 23:00:29.690133: +2024-11-22 23:00:29.691037: Epoch 6525 +2024-11-22 23:00:29.691177: Current learning rate: 0.00218 +2024-11-22 23:00:48.626326: train_loss -0.8048 +2024-11-22 23:00:48.633833: val_loss -0.7872 +2024-11-22 23:00:48.633986: Pseudo dice [0.8627] +2024-11-22 23:00:48.634095: Epoch time: 18.94 s +2024-11-22 23:00:49.531011: +2024-11-22 23:00:49.531862: Epoch 6526 +2024-11-22 23:00:49.532001: Current learning rate: 0.00218 +2024-11-22 23:01:09.603595: train_loss -0.8138 +2024-11-22 23:01:09.610847: val_loss -0.7721 +2024-11-22 23:01:09.610995: Pseudo dice [0.8436] +2024-11-22 23:01:09.611121: Epoch time: 20.07 s +2024-11-22 23:01:10.566449: +2024-11-22 23:01:10.567046: Epoch 6527 +2024-11-22 23:01:10.567180: Current learning rate: 0.00218 +2024-11-22 23:01:30.237598: train_loss -0.8139 +2024-11-22 23:01:30.244233: val_loss -0.7741 +2024-11-22 23:01:30.244379: Pseudo dice [0.8495] +2024-11-22 23:01:30.244481: Epoch time: 19.67 s +2024-11-22 23:01:31.326220: +2024-11-22 23:01:31.327375: Epoch 6528 +2024-11-22 23:01:31.327583: Current learning rate: 0.00218 +2024-11-22 23:01:51.242405: train_loss -0.8033 +2024-11-22 23:01:51.256948: val_loss -0.793 +2024-11-22 23:01:51.257084: Pseudo dice [0.8597] +2024-11-22 23:01:51.257184: Epoch time: 19.92 s +2024-11-22 23:01:52.291899: +2024-11-22 23:01:52.293193: Epoch 6529 +2024-11-22 23:01:52.293339: Current learning rate: 0.00218 +2024-11-22 23:02:12.219346: train_loss -0.8197 +2024-11-22 23:02:12.235848: val_loss -0.7854 +2024-11-22 23:02:12.236011: Pseudo dice [0.8555] +2024-11-22 23:02:12.236127: Epoch time: 19.93 s +2024-11-22 23:02:13.140527: +2024-11-22 23:02:13.141772: Epoch 6530 +2024-11-22 23:02:13.141907: Current learning rate: 0.00218 +2024-11-22 23:02:31.997566: train_loss -0.8153 +2024-11-22 23:02:32.002974: val_loss -0.7826 +2024-11-22 23:02:32.003158: Pseudo dice [0.8582] +2024-11-22 23:02:32.003276: Epoch time: 18.86 s +2024-11-22 23:02:32.896179: +2024-11-22 23:02:32.897559: Epoch 6531 +2024-11-22 23:02:32.897698: Current learning rate: 0.00218 +2024-11-22 23:02:52.665473: train_loss -0.8079 +2024-11-22 23:02:52.673767: val_loss -0.7893 +2024-11-22 23:02:52.673895: Pseudo dice [0.8618] +2024-11-22 23:02:52.674002: Epoch time: 19.77 s +2024-11-22 23:02:53.982248: +2024-11-22 23:02:53.983047: Epoch 6532 +2024-11-22 23:02:53.983197: Current learning rate: 0.00217 +2024-11-22 23:03:13.288997: train_loss -0.8061 +2024-11-22 23:03:13.295792: val_loss -0.753 +2024-11-22 23:03:13.295980: Pseudo dice [0.8516] +2024-11-22 23:03:13.296138: Epoch time: 19.31 s +2024-11-22 23:03:14.304815: +2024-11-22 23:03:14.305648: Epoch 6533 +2024-11-22 23:03:14.305789: Current learning rate: 0.00217 +2024-11-22 23:03:35.004665: train_loss -0.7918 +2024-11-22 23:03:35.008974: val_loss -0.785 +2024-11-22 23:03:35.009133: Pseudo dice [0.8527] +2024-11-22 23:03:35.009228: Epoch time: 20.7 s +2024-11-22 23:03:36.109831: +2024-11-22 23:03:36.110376: Epoch 6534 +2024-11-22 23:03:36.110507: Current learning rate: 0.00217 +2024-11-22 23:03:56.392410: train_loss -0.7946 +2024-11-22 23:03:56.406682: val_loss -0.7549 +2024-11-22 23:03:56.406834: Pseudo dice [0.853] +2024-11-22 23:03:56.406936: Epoch time: 20.28 s +2024-11-22 23:03:57.437742: +2024-11-22 23:03:57.438795: Epoch 6535 +2024-11-22 23:03:57.438925: Current learning rate: 0.00217 +2024-11-22 23:04:17.199553: train_loss -0.8079 +2024-11-22 23:04:17.202380: val_loss -0.7825 +2024-11-22 23:04:17.202531: Pseudo dice [0.8534] +2024-11-22 23:04:17.202630: Epoch time: 19.76 s +2024-11-22 23:04:18.112026: +2024-11-22 23:04:18.112906: Epoch 6536 +2024-11-22 23:04:18.113037: Current learning rate: 0.00217 +2024-11-22 23:04:37.973269: train_loss -0.8066 +2024-11-22 23:04:37.974845: val_loss -0.7564 +2024-11-22 23:04:37.974976: Pseudo dice [0.8443] +2024-11-22 23:04:37.975073: Epoch time: 19.86 s +2024-11-22 23:04:38.913001: +2024-11-22 23:04:38.914375: Epoch 6537 +2024-11-22 23:04:38.914516: Current learning rate: 0.00217 +2024-11-22 23:04:58.142966: train_loss -0.8016 +2024-11-22 23:04:58.150045: val_loss -0.7803 +2024-11-22 23:04:58.150195: Pseudo dice [0.8542] +2024-11-22 23:04:58.150289: Epoch time: 19.23 s +2024-11-22 23:04:59.036796: +2024-11-22 23:04:59.037619: Epoch 6538 +2024-11-22 23:04:59.037745: Current learning rate: 0.00217 +2024-11-22 23:05:18.273055: train_loss -0.81 +2024-11-22 23:05:18.274813: val_loss -0.7658 +2024-11-22 23:05:18.274926: Pseudo dice [0.8583] +2024-11-22 23:05:18.275031: Epoch time: 19.24 s +2024-11-22 23:05:19.204596: +2024-11-22 23:05:19.205517: Epoch 6539 +2024-11-22 23:05:19.205650: Current learning rate: 0.00216 +2024-11-22 23:05:37.497721: train_loss -0.81 +2024-11-22 23:05:37.518646: val_loss -0.7814 +2024-11-22 23:05:37.518785: Pseudo dice [0.8526] +2024-11-22 23:05:37.518893: Epoch time: 18.29 s +2024-11-22 23:05:38.422776: +2024-11-22 23:05:38.423671: Epoch 6540 +2024-11-22 23:05:38.423807: Current learning rate: 0.00216 +2024-11-22 23:05:58.087132: train_loss -0.8028 +2024-11-22 23:05:58.094854: val_loss -0.803 +2024-11-22 23:05:58.094988: Pseudo dice [0.8698] +2024-11-22 23:05:58.095107: Epoch time: 19.67 s +2024-11-22 23:05:59.014668: +2024-11-22 23:05:59.015867: Epoch 6541 +2024-11-22 23:05:59.015997: Current learning rate: 0.00216 +2024-11-22 23:06:17.932755: train_loss -0.8172 +2024-11-22 23:06:17.941814: val_loss -0.7702 +2024-11-22 23:06:17.941941: Pseudo dice [0.8637] +2024-11-22 23:06:17.942032: Epoch time: 18.92 s +2024-11-22 23:06:18.834090: +2024-11-22 23:06:18.834735: Epoch 6542 +2024-11-22 23:06:18.834873: Current learning rate: 0.00216 +2024-11-22 23:06:37.692029: train_loss -0.8135 +2024-11-22 23:06:37.699290: val_loss -0.7668 +2024-11-22 23:06:37.699515: Pseudo dice [0.8559] +2024-11-22 23:06:37.699636: Epoch time: 18.86 s +2024-11-22 23:06:39.099642: +2024-11-22 23:06:39.101237: Epoch 6543 +2024-11-22 23:06:39.101372: Current learning rate: 0.00216 +2024-11-22 23:06:57.940940: train_loss -0.8187 +2024-11-22 23:06:57.949127: val_loss -0.7895 +2024-11-22 23:06:57.949250: Pseudo dice [0.8624] +2024-11-22 23:06:57.949352: Epoch time: 18.84 s +2024-11-22 23:06:59.079484: +2024-11-22 23:06:59.080576: Epoch 6544 +2024-11-22 23:06:59.080731: Current learning rate: 0.00216 +2024-11-22 23:07:18.592035: train_loss -0.8099 +2024-11-22 23:07:18.598346: val_loss -0.7586 +2024-11-22 23:07:18.598499: Pseudo dice [0.8562] +2024-11-22 23:07:18.598615: Epoch time: 19.51 s +2024-11-22 23:07:19.604042: +2024-11-22 23:07:19.604474: Epoch 6545 +2024-11-22 23:07:19.604598: Current learning rate: 0.00216 +2024-11-22 23:07:39.002688: train_loss -0.8077 +2024-11-22 23:07:39.009095: val_loss -0.788 +2024-11-22 23:07:39.009227: Pseudo dice [0.8624] +2024-11-22 23:07:39.009337: Epoch time: 19.4 s +2024-11-22 23:07:39.920863: +2024-11-22 23:07:39.922202: Epoch 6546 +2024-11-22 23:07:39.922334: Current learning rate: 0.00216 +2024-11-22 23:08:00.112267: train_loss -0.8039 +2024-11-22 23:08:00.115638: val_loss -0.7623 +2024-11-22 23:08:00.115937: Pseudo dice [0.8567] +2024-11-22 23:08:00.116037: Epoch time: 20.19 s +2024-11-22 23:08:01.034399: +2024-11-22 23:08:01.034618: Epoch 6547 +2024-11-22 23:08:01.034743: Current learning rate: 0.00215 +2024-11-22 23:08:20.420465: train_loss -0.8083 +2024-11-22 23:08:20.438919: val_loss -0.7725 +2024-11-22 23:08:20.439081: Pseudo dice [0.8545] +2024-11-22 23:08:20.439190: Epoch time: 19.39 s +2024-11-22 23:08:21.435199: +2024-11-22 23:08:21.436628: Epoch 6548 +2024-11-22 23:08:21.436772: Current learning rate: 0.00215 +2024-11-22 23:08:41.108747: train_loss -0.8104 +2024-11-22 23:08:41.115541: val_loss -0.7837 +2024-11-22 23:08:41.115767: Pseudo dice [0.8556] +2024-11-22 23:08:41.115858: Epoch time: 19.67 s +2024-11-22 23:08:42.131117: +2024-11-22 23:08:42.132412: Epoch 6549 +2024-11-22 23:08:42.132551: Current learning rate: 0.00215 +2024-11-22 23:09:01.821144: train_loss -0.8082 +2024-11-22 23:09:01.834965: val_loss -0.7929 +2024-11-22 23:09:01.835090: Pseudo dice [0.8623] +2024-11-22 23:09:01.835182: Epoch time: 19.69 s +2024-11-22 23:09:03.094169: +2024-11-22 23:09:03.095756: Epoch 6550 +2024-11-22 23:09:03.095891: Current learning rate: 0.00215 +2024-11-22 23:09:22.550564: train_loss -0.8107 +2024-11-22 23:09:22.564892: val_loss -0.7828 +2024-11-22 23:09:22.565038: Pseudo dice [0.8542] +2024-11-22 23:09:22.565141: Epoch time: 19.46 s +2024-11-22 23:09:23.748919: +2024-11-22 23:09:23.750437: Epoch 6551 +2024-11-22 23:09:23.750554: Current learning rate: 0.00215 +2024-11-22 23:09:43.545202: train_loss -0.8034 +2024-11-22 23:09:43.551450: val_loss -0.7564 +2024-11-22 23:09:43.551604: Pseudo dice [0.8634] +2024-11-22 23:09:43.551722: Epoch time: 19.8 s +2024-11-22 23:09:44.464482: +2024-11-22 23:09:44.465000: Epoch 6552 +2024-11-22 23:09:44.465125: Current learning rate: 0.00215 +2024-11-22 23:10:03.770735: train_loss -0.8121 +2024-11-22 23:10:03.778254: val_loss -0.7595 +2024-11-22 23:10:03.778431: Pseudo dice [0.8409] +2024-11-22 23:10:03.778523: Epoch time: 19.31 s +2024-11-22 23:10:04.697251: +2024-11-22 23:10:04.698292: Epoch 6553 +2024-11-22 23:10:04.698410: Current learning rate: 0.00215 +2024-11-22 23:10:25.153087: train_loss -0.8133 +2024-11-22 23:10:25.166914: val_loss -0.7681 +2024-11-22 23:10:25.167029: Pseudo dice [0.8597] +2024-11-22 23:10:25.167132: Epoch time: 20.46 s +2024-11-22 23:10:26.475603: +2024-11-22 23:10:26.476891: Epoch 6554 +2024-11-22 23:10:26.477034: Current learning rate: 0.00214 +2024-11-22 23:10:45.513965: train_loss -0.8118 +2024-11-22 23:10:45.522465: val_loss -0.7901 +2024-11-22 23:10:45.522613: Pseudo dice [0.8672] +2024-11-22 23:10:45.522710: Epoch time: 19.04 s +2024-11-22 23:10:46.549122: +2024-11-22 23:10:46.549923: Epoch 6555 +2024-11-22 23:10:46.550069: Current learning rate: 0.00214 +2024-11-22 23:11:05.580564: train_loss -0.8141 +2024-11-22 23:11:05.586067: val_loss -0.7872 +2024-11-22 23:11:05.586194: Pseudo dice [0.8464] +2024-11-22 23:11:05.586291: Epoch time: 19.03 s +2024-11-22 23:11:06.592827: +2024-11-22 23:11:06.593745: Epoch 6556 +2024-11-22 23:11:06.593871: Current learning rate: 0.00214 +2024-11-22 23:11:25.612260: train_loss -0.8064 +2024-11-22 23:11:25.617918: val_loss -0.7943 +2024-11-22 23:11:25.618071: Pseudo dice [0.864] +2024-11-22 23:11:25.618167: Epoch time: 19.02 s +2024-11-22 23:11:26.697200: +2024-11-22 23:11:26.698498: Epoch 6557 +2024-11-22 23:11:26.698637: Current learning rate: 0.00214 +2024-11-22 23:11:44.669341: train_loss -0.8157 +2024-11-22 23:11:44.675430: val_loss -0.7819 +2024-11-22 23:11:44.675547: Pseudo dice [0.8589] +2024-11-22 23:11:44.675647: Epoch time: 17.97 s +2024-11-22 23:11:45.744081: +2024-11-22 23:11:45.745348: Epoch 6558 +2024-11-22 23:11:45.745475: Current learning rate: 0.00214 +2024-11-22 23:12:06.590777: train_loss -0.8219 +2024-11-22 23:12:06.598921: val_loss -0.7757 +2024-11-22 23:12:06.599082: Pseudo dice [0.8579] +2024-11-22 23:12:06.599209: Epoch time: 20.85 s +2024-11-22 23:12:07.499953: +2024-11-22 23:12:07.500753: Epoch 6559 +2024-11-22 23:12:07.500889: Current learning rate: 0.00214 +2024-11-22 23:12:25.791807: train_loss -0.8076 +2024-11-22 23:12:25.809649: val_loss -0.7714 +2024-11-22 23:12:25.809820: Pseudo dice [0.8696] +2024-11-22 23:12:25.809941: Epoch time: 18.29 s +2024-11-22 23:12:26.724759: +2024-11-22 23:12:26.726250: Epoch 6560 +2024-11-22 23:12:26.726382: Current learning rate: 0.00214 +2024-11-22 23:12:46.381324: train_loss -0.8191 +2024-11-22 23:12:46.384140: val_loss -0.7687 +2024-11-22 23:12:46.384273: Pseudo dice [0.8617] +2024-11-22 23:12:46.384365: Epoch time: 19.65 s +2024-11-22 23:12:47.286764: +2024-11-22 23:12:47.287971: Epoch 6561 +2024-11-22 23:12:47.288104: Current learning rate: 0.00214 +2024-11-22 23:13:06.640414: train_loss -0.8171 +2024-11-22 23:13:06.643482: val_loss -0.7661 +2024-11-22 23:13:06.643580: Pseudo dice [0.8577] +2024-11-22 23:13:06.643667: Epoch time: 19.35 s +2024-11-22 23:13:07.526789: +2024-11-22 23:13:07.527538: Epoch 6562 +2024-11-22 23:13:07.527658: Current learning rate: 0.00213 +2024-11-22 23:13:27.455220: train_loss -0.814 +2024-11-22 23:13:27.465938: val_loss -0.7753 +2024-11-22 23:13:27.466183: Pseudo dice [0.855] +2024-11-22 23:13:27.466296: Epoch time: 19.93 s +2024-11-22 23:13:28.567620: +2024-11-22 23:13:28.568937: Epoch 6563 +2024-11-22 23:13:28.569283: Current learning rate: 0.00213 +2024-11-22 23:13:47.887277: train_loss -0.8098 +2024-11-22 23:13:47.894210: val_loss -0.7939 +2024-11-22 23:13:47.894348: Pseudo dice [0.86] +2024-11-22 23:13:47.894444: Epoch time: 19.32 s +2024-11-22 23:13:48.850996: +2024-11-22 23:13:48.851496: Epoch 6564 +2024-11-22 23:13:48.851616: Current learning rate: 0.00213 +2024-11-22 23:14:08.894882: train_loss -0.801 +2024-11-22 23:14:08.900956: val_loss -0.7711 +2024-11-22 23:14:08.901096: Pseudo dice [0.8631] +2024-11-22 23:14:08.901192: Epoch time: 20.04 s +2024-11-22 23:14:10.200625: +2024-11-22 23:14:10.202147: Epoch 6565 +2024-11-22 23:14:10.202284: Current learning rate: 0.00213 +2024-11-22 23:14:29.327196: train_loss -0.7988 +2024-11-22 23:14:29.343127: val_loss -0.799 +2024-11-22 23:14:29.343279: Pseudo dice [0.8526] +2024-11-22 23:14:29.343369: Epoch time: 19.13 s +2024-11-22 23:14:30.377753: +2024-11-22 23:14:30.378756: Epoch 6566 +2024-11-22 23:14:30.378885: Current learning rate: 0.00213 +2024-11-22 23:14:50.097411: train_loss -0.8103 +2024-11-22 23:14:50.103782: val_loss -0.7838 +2024-11-22 23:14:50.103920: Pseudo dice [0.8448] +2024-11-22 23:14:50.104017: Epoch time: 19.72 s +2024-11-22 23:14:51.070376: +2024-11-22 23:14:51.071608: Epoch 6567 +2024-11-22 23:14:51.071740: Current learning rate: 0.00213 +2024-11-22 23:15:10.650894: train_loss -0.8049 +2024-11-22 23:15:10.661464: val_loss -0.7696 +2024-11-22 23:15:10.661621: Pseudo dice [0.8529] +2024-11-22 23:15:10.661736: Epoch time: 19.58 s +2024-11-22 23:15:11.559926: +2024-11-22 23:15:11.560901: Epoch 6568 +2024-11-22 23:15:11.561034: Current learning rate: 0.00213 +2024-11-22 23:15:30.288632: train_loss -0.8049 +2024-11-22 23:15:30.291366: val_loss -0.7606 +2024-11-22 23:15:30.291478: Pseudo dice [0.8417] +2024-11-22 23:15:30.291569: Epoch time: 18.73 s +2024-11-22 23:15:31.181406: +2024-11-22 23:15:31.182962: Epoch 6569 +2024-11-22 23:15:31.183095: Current learning rate: 0.00212 +2024-11-22 23:15:50.378438: train_loss -0.8076 +2024-11-22 23:15:50.406749: val_loss -0.7895 +2024-11-22 23:15:50.406905: Pseudo dice [0.8563] +2024-11-22 23:15:50.407004: Epoch time: 19.2 s +2024-11-22 23:15:51.460816: +2024-11-22 23:15:51.461769: Epoch 6570 +2024-11-22 23:15:51.461901: Current learning rate: 0.00212 +2024-11-22 23:16:11.179913: train_loss -0.8119 +2024-11-22 23:16:11.188327: val_loss -0.7769 +2024-11-22 23:16:11.188478: Pseudo dice [0.8468] +2024-11-22 23:16:11.188586: Epoch time: 19.72 s +2024-11-22 23:16:12.206828: +2024-11-22 23:16:12.208384: Epoch 6571 +2024-11-22 23:16:12.208508: Current learning rate: 0.00212 +2024-11-22 23:16:32.162865: train_loss -0.8091 +2024-11-22 23:16:32.168037: val_loss -0.7761 +2024-11-22 23:16:32.168189: Pseudo dice [0.8519] +2024-11-22 23:16:32.168277: Epoch time: 19.96 s +2024-11-22 23:16:33.135372: +2024-11-22 23:16:33.160144: Epoch 6572 +2024-11-22 23:16:33.160306: Current learning rate: 0.00212 +2024-11-22 23:16:52.635623: train_loss -0.8151 +2024-11-22 23:16:52.641557: val_loss -0.766 +2024-11-22 23:16:52.641677: Pseudo dice [0.8474] +2024-11-22 23:16:52.641773: Epoch time: 19.5 s +2024-11-22 23:16:53.534972: +2024-11-22 23:16:53.536271: Epoch 6573 +2024-11-22 23:16:53.536393: Current learning rate: 0.00212 +2024-11-22 23:17:12.920439: train_loss -0.8108 +2024-11-22 23:17:12.933687: val_loss -0.7877 +2024-11-22 23:17:12.933823: Pseudo dice [0.8667] +2024-11-22 23:17:12.933921: Epoch time: 19.39 s +2024-11-22 23:17:14.085155: +2024-11-22 23:17:14.086869: Epoch 6574 +2024-11-22 23:17:14.087014: Current learning rate: 0.00212 +2024-11-22 23:17:32.857703: train_loss -0.818 +2024-11-22 23:17:32.861117: val_loss -0.7699 +2024-11-22 23:17:32.861258: Pseudo dice [0.858] +2024-11-22 23:17:32.861369: Epoch time: 18.77 s +2024-11-22 23:17:33.912234: +2024-11-22 23:17:33.913936: Epoch 6575 +2024-11-22 23:17:33.914073: Current learning rate: 0.00212 +2024-11-22 23:17:53.623418: train_loss -0.8143 +2024-11-22 23:17:53.630742: val_loss -0.7594 +2024-11-22 23:17:53.630875: Pseudo dice [0.8541] +2024-11-22 23:17:53.630972: Epoch time: 19.71 s +2024-11-22 23:17:54.982473: +2024-11-22 23:17:54.984004: Epoch 6576 +2024-11-22 23:17:54.984152: Current learning rate: 0.00212 +2024-11-22 23:18:14.244464: train_loss -0.813 +2024-11-22 23:18:14.259398: val_loss -0.7774 +2024-11-22 23:18:14.259548: Pseudo dice [0.8568] +2024-11-22 23:18:14.259675: Epoch time: 19.26 s +2024-11-22 23:18:15.270496: +2024-11-22 23:18:15.271198: Epoch 6577 +2024-11-22 23:18:15.271325: Current learning rate: 0.00211 +2024-11-22 23:18:34.015937: train_loss -0.8029 +2024-11-22 23:18:34.019151: val_loss -0.7787 +2024-11-22 23:18:34.019272: Pseudo dice [0.8566] +2024-11-22 23:18:34.019372: Epoch time: 18.75 s +2024-11-22 23:18:35.074716: +2024-11-22 23:18:35.076197: Epoch 6578 +2024-11-22 23:18:35.076338: Current learning rate: 0.00211 +2024-11-22 23:18:53.993971: train_loss -0.8121 +2024-11-22 23:18:53.998700: val_loss -0.7781 +2024-11-22 23:18:53.998822: Pseudo dice [0.8592] +2024-11-22 23:18:53.998921: Epoch time: 18.92 s +2024-11-22 23:18:54.887501: +2024-11-22 23:18:54.888364: Epoch 6579 +2024-11-22 23:18:54.888489: Current learning rate: 0.00211 +2024-11-22 23:19:15.405748: train_loss -0.806 +2024-11-22 23:19:15.412627: val_loss -0.7757 +2024-11-22 23:19:15.412788: Pseudo dice [0.859] +2024-11-22 23:19:15.412976: Epoch time: 20.52 s +2024-11-22 23:19:16.562508: +2024-11-22 23:19:16.563781: Epoch 6580 +2024-11-22 23:19:16.563922: Current learning rate: 0.00211 +2024-11-22 23:19:36.867239: train_loss -0.8027 +2024-11-22 23:19:36.874497: val_loss -0.7863 +2024-11-22 23:19:36.874645: Pseudo dice [0.8532] +2024-11-22 23:19:36.874748: Epoch time: 20.31 s +2024-11-22 23:19:37.796947: +2024-11-22 23:19:37.798154: Epoch 6581 +2024-11-22 23:19:37.798275: Current learning rate: 0.00211 +2024-11-22 23:19:56.828954: train_loss -0.8143 +2024-11-22 23:19:56.835395: val_loss -0.7717 +2024-11-22 23:19:56.835545: Pseudo dice [0.8623] +2024-11-22 23:19:56.835659: Epoch time: 19.03 s +2024-11-22 23:19:57.733014: +2024-11-22 23:19:57.734937: Epoch 6582 +2024-11-22 23:19:57.735076: Current learning rate: 0.00211 +2024-11-22 23:20:18.095733: train_loss -0.8169 +2024-11-22 23:20:18.112243: val_loss -0.779 +2024-11-22 23:20:18.112405: Pseudo dice [0.8522] +2024-11-22 23:20:18.112508: Epoch time: 20.36 s +2024-11-22 23:20:19.053278: +2024-11-22 23:20:19.054887: Epoch 6583 +2024-11-22 23:20:19.055015: Current learning rate: 0.00211 +2024-11-22 23:20:38.053773: train_loss -0.8207 +2024-11-22 23:20:38.059722: val_loss -0.7437 +2024-11-22 23:20:38.059842: Pseudo dice [0.8511] +2024-11-22 23:20:38.059941: Epoch time: 19.0 s +2024-11-22 23:20:38.956774: +2024-11-22 23:20:38.956994: Epoch 6584 +2024-11-22 23:20:38.957110: Current learning rate: 0.0021 +2024-11-22 23:20:57.921132: train_loss -0.8096 +2024-11-22 23:20:57.921367: val_loss -0.7881 +2024-11-22 23:20:57.921484: Pseudo dice [0.8679] +2024-11-22 23:20:57.925848: Epoch time: 18.97 s +2024-11-22 23:20:59.007860: +2024-11-22 23:20:59.008098: Epoch 6585 +2024-11-22 23:20:59.008217: Current learning rate: 0.0021 +2024-11-22 23:21:18.347195: train_loss -0.816 +2024-11-22 23:21:18.347803: val_loss -0.751 +2024-11-22 23:21:18.347912: Pseudo dice [0.8589] +2024-11-22 23:21:18.348015: Epoch time: 19.34 s +2024-11-22 23:21:19.236464: +2024-11-22 23:21:19.236656: Epoch 6586 +2024-11-22 23:21:19.236782: Current learning rate: 0.0021 +2024-11-22 23:21:37.775880: train_loss -0.8116 +2024-11-22 23:21:37.783038: val_loss -0.7663 +2024-11-22 23:21:37.783178: Pseudo dice [0.8663] +2024-11-22 23:21:37.783278: Epoch time: 18.54 s +2024-11-22 23:21:39.068125: +2024-11-22 23:21:39.068349: Epoch 6587 +2024-11-22 23:21:39.068486: Current learning rate: 0.0021 +2024-11-22 23:21:58.463368: train_loss -0.8161 +2024-11-22 23:21:58.465534: val_loss -0.7791 +2024-11-22 23:21:58.465673: Pseudo dice [0.8483] +2024-11-22 23:21:58.465766: Epoch time: 19.4 s +2024-11-22 23:21:59.379383: +2024-11-22 23:21:59.379598: Epoch 6588 +2024-11-22 23:21:59.379737: Current learning rate: 0.0021 +2024-11-22 23:22:18.824830: train_loss -0.8165 +2024-11-22 23:22:18.829748: val_loss -0.7618 +2024-11-22 23:22:18.829904: Pseudo dice [0.8624] +2024-11-22 23:22:18.829997: Epoch time: 19.45 s +2024-11-22 23:22:19.831716: +2024-11-22 23:22:19.831992: Epoch 6589 +2024-11-22 23:22:19.832118: Current learning rate: 0.0021 +2024-11-22 23:22:38.743200: train_loss -0.8074 +2024-11-22 23:22:38.743751: val_loss -0.7781 +2024-11-22 23:22:38.743850: Pseudo dice [0.8527] +2024-11-22 23:22:38.743959: Epoch time: 18.91 s +2024-11-22 23:22:39.638776: +2024-11-22 23:22:39.638999: Epoch 6590 +2024-11-22 23:22:39.639128: Current learning rate: 0.0021 +2024-11-22 23:22:58.150232: train_loss -0.8153 +2024-11-22 23:22:58.161769: val_loss -0.7581 +2024-11-22 23:22:58.161892: Pseudo dice [0.8584] +2024-11-22 23:22:58.161997: Epoch time: 18.51 s +2024-11-22 23:22:59.129217: +2024-11-22 23:22:59.129423: Epoch 6591 +2024-11-22 23:22:59.129561: Current learning rate: 0.0021 +2024-11-22 23:23:18.854952: train_loss -0.809 +2024-11-22 23:23:18.864349: val_loss -0.7792 +2024-11-22 23:23:18.864488: Pseudo dice [0.8685] +2024-11-22 23:23:18.864592: Epoch time: 19.73 s +2024-11-22 23:23:19.879745: +2024-11-22 23:23:19.879967: Epoch 6592 +2024-11-22 23:23:19.880088: Current learning rate: 0.00209 +2024-11-22 23:23:38.251138: train_loss -0.8187 +2024-11-22 23:23:38.251652: val_loss -0.7775 +2024-11-22 23:23:38.251746: Pseudo dice [0.8563] +2024-11-22 23:23:38.251844: Epoch time: 18.37 s +2024-11-22 23:23:39.189368: +2024-11-22 23:23:39.189571: Epoch 6593 +2024-11-22 23:23:39.189703: Current learning rate: 0.00209 +2024-11-22 23:23:58.518905: train_loss -0.8088 +2024-11-22 23:23:58.519798: val_loss -0.7721 +2024-11-22 23:23:58.519975: Pseudo dice [0.8391] +2024-11-22 23:23:58.520103: Epoch time: 19.33 s +2024-11-22 23:23:59.413243: +2024-11-22 23:23:59.413456: Epoch 6594 +2024-11-22 23:23:59.413589: Current learning rate: 0.00209 +2024-11-22 23:24:18.097431: train_loss -0.814 +2024-11-22 23:24:18.099866: val_loss -0.7937 +2024-11-22 23:24:18.100002: Pseudo dice [0.8608] +2024-11-22 23:24:18.100113: Epoch time: 18.69 s +2024-11-22 23:24:18.993325: +2024-11-22 23:24:18.993547: Epoch 6595 +2024-11-22 23:24:18.993669: Current learning rate: 0.00209 +2024-11-22 23:24:39.638427: train_loss -0.8107 +2024-11-22 23:24:39.641313: val_loss -0.7951 +2024-11-22 23:24:39.641504: Pseudo dice [0.8541] +2024-11-22 23:24:39.641599: Epoch time: 20.65 s +2024-11-22 23:24:40.667764: +2024-11-22 23:24:40.668004: Epoch 6596 +2024-11-22 23:24:40.668168: Current learning rate: 0.00209 +2024-11-22 23:24:59.110781: train_loss -0.8129 +2024-11-22 23:24:59.115499: val_loss -0.7858 +2024-11-22 23:24:59.115655: Pseudo dice [0.8621] +2024-11-22 23:24:59.115746: Epoch time: 18.44 s +2024-11-22 23:25:00.010169: +2024-11-22 23:25:00.020307: Epoch 6597 +2024-11-22 23:25:00.020581: Current learning rate: 0.00209 +2024-11-22 23:25:18.005964: train_loss -0.8105 +2024-11-22 23:25:18.011511: val_loss -0.773 +2024-11-22 23:25:18.011652: Pseudo dice [0.8546] +2024-11-22 23:25:18.011765: Epoch time: 18.0 s +2024-11-22 23:25:19.422820: +2024-11-22 23:25:19.423048: Epoch 6598 +2024-11-22 23:25:19.423182: Current learning rate: 0.00209 +2024-11-22 23:25:37.355828: train_loss -0.8082 +2024-11-22 23:25:37.359711: val_loss -0.7713 +2024-11-22 23:25:37.359863: Pseudo dice [0.8633] +2024-11-22 23:25:37.359968: Epoch time: 17.93 s +2024-11-22 23:25:38.321695: +2024-11-22 23:25:38.321923: Epoch 6599 +2024-11-22 23:25:38.322053: Current learning rate: 0.00208 +2024-11-22 23:25:57.379715: train_loss -0.8159 +2024-11-22 23:25:57.381959: val_loss -0.7939 +2024-11-22 23:25:57.382103: Pseudo dice [0.8649] +2024-11-22 23:25:57.382198: Epoch time: 19.06 s +2024-11-22 23:25:58.823959: +2024-11-22 23:25:58.824198: Epoch 6600 +2024-11-22 23:25:58.824316: Current learning rate: 0.00208 +2024-11-22 23:26:17.287100: train_loss -0.8077 +2024-11-22 23:26:17.287572: val_loss -0.7858 +2024-11-22 23:26:17.287664: Pseudo dice [0.8588] +2024-11-22 23:26:17.287745: Epoch time: 18.46 s +2024-11-22 23:26:18.172936: +2024-11-22 23:26:18.173151: Epoch 6601 +2024-11-22 23:26:18.173277: Current learning rate: 0.00208 +2024-11-22 23:26:37.619290: train_loss -0.7999 +2024-11-22 23:26:37.626880: val_loss -0.7758 +2024-11-22 23:26:37.627130: Pseudo dice [0.8551] +2024-11-22 23:26:37.627238: Epoch time: 19.45 s +2024-11-22 23:26:38.517852: +2024-11-22 23:26:38.518104: Epoch 6602 +2024-11-22 23:26:38.518224: Current learning rate: 0.00208 +2024-11-22 23:26:58.091511: train_loss -0.8094 +2024-11-22 23:26:58.092545: val_loss -0.7909 +2024-11-22 23:26:58.092644: Pseudo dice [0.8568] +2024-11-22 23:26:58.092725: Epoch time: 19.57 s +2024-11-22 23:26:58.980105: +2024-11-22 23:26:58.980315: Epoch 6603 +2024-11-22 23:26:58.980439: Current learning rate: 0.00208 +2024-11-22 23:27:17.773508: train_loss -0.8078 +2024-11-22 23:27:17.775116: val_loss -0.7969 +2024-11-22 23:27:17.775261: Pseudo dice [0.8758] +2024-11-22 23:27:17.775356: Epoch time: 18.79 s +2024-11-22 23:27:18.692497: +2024-11-22 23:27:18.692715: Epoch 6604 +2024-11-22 23:27:18.692832: Current learning rate: 0.00208 +2024-11-22 23:27:37.260136: train_loss -0.8113 +2024-11-22 23:27:37.260926: val_loss -0.7866 +2024-11-22 23:27:37.261036: Pseudo dice [0.8585] +2024-11-22 23:27:37.261152: Epoch time: 18.57 s +2024-11-22 23:27:38.154252: +2024-11-22 23:27:38.154470: Epoch 6605 +2024-11-22 23:27:38.154597: Current learning rate: 0.00208 +2024-11-22 23:27:57.342704: train_loss -0.8043 +2024-11-22 23:27:57.359877: val_loss -0.7907 +2024-11-22 23:27:57.360099: Pseudo dice [0.8487] +2024-11-22 23:27:57.360200: Epoch time: 19.19 s +2024-11-22 23:27:58.479775: +2024-11-22 23:27:58.479982: Epoch 6606 +2024-11-22 23:27:58.480128: Current learning rate: 0.00208 +2024-11-22 23:28:17.724709: train_loss -0.8002 +2024-11-22 23:28:17.725657: val_loss -0.7973 +2024-11-22 23:28:17.725745: Pseudo dice [0.8515] +2024-11-22 23:28:17.725826: Epoch time: 19.25 s +2024-11-22 23:28:18.610429: +2024-11-22 23:28:18.610633: Epoch 6607 +2024-11-22 23:28:18.610743: Current learning rate: 0.00207 +2024-11-22 23:28:37.238881: train_loss -0.8058 +2024-11-22 23:28:37.239101: val_loss -0.7625 +2024-11-22 23:28:37.239236: Pseudo dice [0.8475] +2024-11-22 23:28:37.239318: Epoch time: 18.63 s +2024-11-22 23:28:38.168954: +2024-11-22 23:28:38.169177: Epoch 6608 +2024-11-22 23:28:38.169286: Current learning rate: 0.00207 +2024-11-22 23:28:57.722091: train_loss -0.8167 +2024-11-22 23:28:57.722337: val_loss -0.777 +2024-11-22 23:28:57.722425: Pseudo dice [0.8592] +2024-11-22 23:28:57.724679: Epoch time: 19.55 s +2024-11-22 23:28:59.035205: +2024-11-22 23:28:59.035426: Epoch 6609 +2024-11-22 23:28:59.035545: Current learning rate: 0.00207 +2024-11-22 23:29:17.867426: train_loss -0.8034 +2024-11-22 23:29:17.867638: val_loss -0.7859 +2024-11-22 23:29:17.867726: Pseudo dice [0.8581] +2024-11-22 23:29:17.867805: Epoch time: 18.83 s +2024-11-22 23:29:18.749912: +2024-11-22 23:29:18.750155: Epoch 6610 +2024-11-22 23:29:18.766357: Current learning rate: 0.00207 +2024-11-22 23:29:37.333159: train_loss -0.8113 +2024-11-22 23:29:37.333416: val_loss -0.7671 +2024-11-22 23:29:37.333494: Pseudo dice [0.8512] +2024-11-22 23:29:37.333567: Epoch time: 18.58 s +2024-11-22 23:29:38.217595: +2024-11-22 23:29:38.217808: Epoch 6611 +2024-11-22 23:29:38.217927: Current learning rate: 0.00207 +2024-11-22 23:29:57.357031: train_loss -0.8148 +2024-11-22 23:29:57.357267: val_loss -0.7839 +2024-11-22 23:29:57.357349: Pseudo dice [0.857] +2024-11-22 23:29:57.357435: Epoch time: 19.14 s +2024-11-22 23:29:58.342627: +2024-11-22 23:29:58.342822: Epoch 6612 +2024-11-22 23:29:58.342936: Current learning rate: 0.00207 +2024-11-22 23:30:16.289155: train_loss -0.8202 +2024-11-22 23:30:16.289393: val_loss -0.7886 +2024-11-22 23:30:16.289475: Pseudo dice [0.8696] +2024-11-22 23:30:16.289571: Epoch time: 17.95 s +2024-11-22 23:30:17.190279: +2024-11-22 23:30:17.190490: Epoch 6613 +2024-11-22 23:30:17.190613: Current learning rate: 0.00207 +2024-11-22 23:30:35.632571: train_loss -0.8161 +2024-11-22 23:30:35.632787: val_loss -0.7596 +2024-11-22 23:30:35.632882: Pseudo dice [0.8615] +2024-11-22 23:30:35.632965: Epoch time: 18.44 s +2024-11-22 23:30:36.520656: +2024-11-22 23:30:36.520873: Epoch 6614 +2024-11-22 23:30:36.521000: Current learning rate: 0.00206 +2024-11-22 23:30:53.538651: train_loss -0.809 +2024-11-22 23:30:53.538863: val_loss -0.7914 +2024-11-22 23:30:53.538943: Pseudo dice [0.8597] +2024-11-22 23:30:53.539040: Epoch time: 17.02 s +2024-11-22 23:30:54.514584: +2024-11-22 23:30:54.515012: Epoch 6615 +2024-11-22 23:30:54.515142: Current learning rate: 0.00206 +2024-11-22 23:31:12.990350: train_loss -0.8116 +2024-11-22 23:31:12.990590: val_loss -0.7803 +2024-11-22 23:31:12.990667: Pseudo dice [0.856] +2024-11-22 23:31:12.990747: Epoch time: 18.48 s +2024-11-22 23:31:13.881541: +2024-11-22 23:31:13.881745: Epoch 6616 +2024-11-22 23:31:13.881863: Current learning rate: 0.00206 +2024-11-22 23:31:31.831365: train_loss -0.8182 +2024-11-22 23:31:31.831566: val_loss -0.7682 +2024-11-22 23:31:31.831642: Pseudo dice [0.8545] +2024-11-22 23:31:31.831731: Epoch time: 17.95 s +2024-11-22 23:31:32.716668: +2024-11-22 23:31:32.716876: Epoch 6617 +2024-11-22 23:31:32.716990: Current learning rate: 0.00206 +2024-11-22 23:31:50.612398: train_loss -0.8099 +2024-11-22 23:31:50.612620: val_loss -0.7862 +2024-11-22 23:31:50.612702: Pseudo dice [0.8439] +2024-11-22 23:31:50.612789: Epoch time: 17.9 s +2024-11-22 23:31:51.489562: +2024-11-22 23:31:51.489779: Epoch 6618 +2024-11-22 23:31:51.489893: Current learning rate: 0.00206 +2024-11-22 23:32:09.452489: train_loss -0.8146 +2024-11-22 23:32:09.452699: val_loss -0.7965 +2024-11-22 23:32:09.452799: Pseudo dice [0.8656] +2024-11-22 23:32:09.452879: Epoch time: 17.96 s +2024-11-22 23:32:10.326321: +2024-11-22 23:32:10.326532: Epoch 6619 +2024-11-22 23:32:10.326666: Current learning rate: 0.00206 +2024-11-22 23:32:28.003102: train_loss -0.7986 +2024-11-22 23:32:28.003412: val_loss -0.7471 +2024-11-22 23:32:28.003487: Pseudo dice [0.8575] +2024-11-22 23:32:28.003572: Epoch time: 17.68 s +2024-11-22 23:32:29.291252: +2024-11-22 23:32:29.291461: Epoch 6620 +2024-11-22 23:32:29.291589: Current learning rate: 0.00206 +2024-11-22 23:32:47.182165: train_loss -0.8122 +2024-11-22 23:32:47.182396: val_loss -0.7875 +2024-11-22 23:32:47.182490: Pseudo dice [0.8551] +2024-11-22 23:32:47.182582: Epoch time: 17.89 s +2024-11-22 23:32:48.196949: +2024-11-22 23:32:48.197161: Epoch 6621 +2024-11-22 23:32:48.197274: Current learning rate: 0.00206 +2024-11-22 23:33:06.944665: train_loss -0.8144 +2024-11-22 23:33:06.944893: val_loss -0.7684 +2024-11-22 23:33:06.944971: Pseudo dice [0.8653] +2024-11-22 23:33:06.945064: Epoch time: 18.75 s +2024-11-22 23:33:07.863242: +2024-11-22 23:33:07.863461: Epoch 6622 +2024-11-22 23:33:07.863568: Current learning rate: 0.00205 +2024-11-22 23:33:26.526219: train_loss -0.8089 +2024-11-22 23:33:26.526453: val_loss -0.7838 +2024-11-22 23:33:26.526531: Pseudo dice [0.8652] +2024-11-22 23:33:26.526624: Epoch time: 18.66 s +2024-11-22 23:33:27.447944: +2024-11-22 23:33:27.448162: Epoch 6623 +2024-11-22 23:33:27.448303: Current learning rate: 0.00205 +2024-11-22 23:33:46.696541: train_loss -0.8248 +2024-11-22 23:33:46.696767: val_loss -0.7551 +2024-11-22 23:33:46.696846: Pseudo dice [0.8617] +2024-11-22 23:33:46.696943: Epoch time: 19.25 s +2024-11-22 23:33:47.576605: +2024-11-22 23:33:47.576792: Epoch 6624 +2024-11-22 23:33:47.576908: Current learning rate: 0.00205 +2024-11-22 23:34:06.094200: train_loss -0.8095 +2024-11-22 23:34:06.094405: val_loss -0.7923 +2024-11-22 23:34:06.094489: Pseudo dice [0.8671] +2024-11-22 23:34:06.094562: Epoch time: 18.52 s +2024-11-22 23:34:06.094625: Yayy! New best EMA pseudo Dice: 0.8598 +2024-11-22 23:34:07.292050: +2024-11-22 23:34:07.292281: Epoch 6625 +2024-11-22 23:34:07.292392: Current learning rate: 0.00205 +2024-11-22 23:34:25.683250: train_loss -0.8121 +2024-11-22 23:34:25.683455: val_loss -0.782 +2024-11-22 23:34:25.683532: Pseudo dice [0.8566] +2024-11-22 23:34:25.683617: Epoch time: 18.39 s +2024-11-22 23:34:26.567284: +2024-11-22 23:34:26.567511: Epoch 6626 +2024-11-22 23:34:26.567626: Current learning rate: 0.00205 +2024-11-22 23:34:44.871347: train_loss -0.8086 +2024-11-22 23:34:44.871577: val_loss -0.7731 +2024-11-22 23:34:44.871656: Pseudo dice [0.8615] +2024-11-22 23:34:44.871739: Epoch time: 18.3 s +2024-11-22 23:34:45.764055: +2024-11-22 23:34:45.764328: Epoch 6627 +2024-11-22 23:34:45.764452: Current learning rate: 0.00205 +2024-11-22 23:35:04.578625: train_loss -0.8126 +2024-11-22 23:35:04.578847: val_loss -0.7851 +2024-11-22 23:35:04.578938: Pseudo dice [0.8459] +2024-11-22 23:35:04.579042: Epoch time: 18.82 s +2024-11-22 23:35:05.467387: +2024-11-22 23:35:05.467600: Epoch 6628 +2024-11-22 23:35:05.467731: Current learning rate: 0.00205 +2024-11-22 23:35:23.500172: train_loss -0.8134 +2024-11-22 23:35:23.500367: val_loss -0.7761 +2024-11-22 23:35:23.500444: Pseudo dice [0.865] +2024-11-22 23:35:23.500517: Epoch time: 18.03 s +2024-11-22 23:35:24.433094: +2024-11-22 23:35:24.433321: Epoch 6629 +2024-11-22 23:35:24.433433: Current learning rate: 0.00204 +2024-11-22 23:35:42.173164: train_loss -0.8127 +2024-11-22 23:35:42.173371: val_loss -0.7723 +2024-11-22 23:35:42.173451: Pseudo dice [0.8639] +2024-11-22 23:35:42.173531: Epoch time: 17.74 s +2024-11-22 23:35:43.096119: +2024-11-22 23:35:43.096324: Epoch 6630 +2024-11-22 23:35:43.096436: Current learning rate: 0.00204 +2024-11-22 23:36:01.788570: train_loss -0.8063 +2024-11-22 23:36:01.788805: val_loss -0.7852 +2024-11-22 23:36:01.788889: Pseudo dice [0.8631] +2024-11-22 23:36:01.789008: Epoch time: 18.69 s +2024-11-22 23:36:01.789080: Yayy! New best EMA pseudo Dice: 0.8598 +2024-11-22 23:36:03.370172: +2024-11-22 23:36:03.370381: Epoch 6631 +2024-11-22 23:36:03.370510: Current learning rate: 0.00204 +2024-11-22 23:36:22.936546: train_loss -0.8106 +2024-11-22 23:36:22.936756: val_loss -0.7863 +2024-11-22 23:36:22.936843: Pseudo dice [0.8707] +2024-11-22 23:36:22.936955: Epoch time: 19.57 s +2024-11-22 23:36:22.937023: Yayy! New best EMA pseudo Dice: 0.8609 +2024-11-22 23:36:24.145337: +2024-11-22 23:36:24.145573: Epoch 6632 +2024-11-22 23:36:24.145694: Current learning rate: 0.00204 +2024-11-22 23:36:42.444765: train_loss -0.8085 +2024-11-22 23:36:42.444974: val_loss -0.7713 +2024-11-22 23:36:42.445052: Pseudo dice [0.8493] +2024-11-22 23:36:42.445138: Epoch time: 18.3 s +2024-11-22 23:36:43.331843: +2024-11-22 23:36:43.332069: Epoch 6633 +2024-11-22 23:36:43.332196: Current learning rate: 0.00204 +2024-11-22 23:37:02.204245: train_loss -0.8144 +2024-11-22 23:37:02.204489: val_loss -0.7506 +2024-11-22 23:37:02.204577: Pseudo dice [0.856] +2024-11-22 23:37:02.204667: Epoch time: 18.87 s +2024-11-22 23:37:03.261484: +2024-11-22 23:37:03.261700: Epoch 6634 +2024-11-22 23:37:03.261831: Current learning rate: 0.00204 +2024-11-22 23:37:23.124747: train_loss -0.8147 +2024-11-22 23:37:23.125092: val_loss -0.7965 +2024-11-22 23:37:23.125173: Pseudo dice [0.8727] +2024-11-22 23:37:23.125258: Epoch time: 19.86 s +2024-11-22 23:37:24.025406: +2024-11-22 23:37:24.025616: Epoch 6635 +2024-11-22 23:37:24.025748: Current learning rate: 0.00204 +2024-11-22 23:37:42.178673: train_loss -0.8153 +2024-11-22 23:37:42.178892: val_loss -0.804 +2024-11-22 23:37:42.178974: Pseudo dice [0.8682] +2024-11-22 23:37:42.179070: Epoch time: 18.15 s +2024-11-22 23:37:42.179138: Yayy! New best EMA pseudo Dice: 0.8615 +2024-11-22 23:37:43.385472: +2024-11-22 23:37:43.385706: Epoch 6636 +2024-11-22 23:37:43.385833: Current learning rate: 0.00203 +2024-11-22 23:38:02.438155: train_loss -0.808 +2024-11-22 23:38:02.438458: val_loss -0.7959 +2024-11-22 23:38:02.438540: Pseudo dice [0.8615] +2024-11-22 23:38:02.438633: Epoch time: 19.05 s +2024-11-22 23:38:03.331317: +2024-11-22 23:38:03.331538: Epoch 6637 +2024-11-22 23:38:03.331658: Current learning rate: 0.00203 +2024-11-22 23:38:21.950752: train_loss -0.8121 +2024-11-22 23:38:21.951012: val_loss -0.7746 +2024-11-22 23:38:21.953295: Pseudo dice [0.8585] +2024-11-22 23:38:21.953426: Epoch time: 18.62 s +2024-11-22 23:38:22.861868: +2024-11-22 23:38:22.862072: Epoch 6638 +2024-11-22 23:38:22.862186: Current learning rate: 0.00203 +2024-11-22 23:38:41.046663: train_loss -0.8081 +2024-11-22 23:38:41.046879: val_loss -0.7841 +2024-11-22 23:38:41.046964: Pseudo dice [0.8573] +2024-11-22 23:38:41.047053: Epoch time: 18.19 s +2024-11-22 23:38:41.925495: +2024-11-22 23:38:41.925694: Epoch 6639 +2024-11-22 23:38:41.925822: Current learning rate: 0.00203 +2024-11-22 23:39:00.633921: train_loss -0.8183 +2024-11-22 23:39:00.634142: val_loss -0.7789 +2024-11-22 23:39:00.634219: Pseudo dice [0.8469] +2024-11-22 23:39:00.634302: Epoch time: 18.71 s +2024-11-22 23:39:01.555895: +2024-11-22 23:39:01.556093: Epoch 6640 +2024-11-22 23:39:01.556413: Current learning rate: 0.00203 +2024-11-22 23:39:20.717498: train_loss -0.8116 +2024-11-22 23:39:20.717776: val_loss -0.7631 +2024-11-22 23:39:20.717870: Pseudo dice [0.8422] +2024-11-22 23:39:20.717963: Epoch time: 19.16 s +2024-11-22 23:39:21.616495: +2024-11-22 23:39:21.616695: Epoch 6641 +2024-11-22 23:39:21.616806: Current learning rate: 0.00203 +2024-11-22 23:39:40.709509: train_loss -0.8161 +2024-11-22 23:39:40.709774: val_loss -0.7656 +2024-11-22 23:39:40.709871: Pseudo dice [0.8528] +2024-11-22 23:39:40.709952: Epoch time: 19.09 s +2024-11-22 23:39:42.001596: +2024-11-22 23:39:42.001807: Epoch 6642 +2024-11-22 23:39:42.001930: Current learning rate: 0.00203 +2024-11-22 23:40:00.622051: train_loss -0.8207 +2024-11-22 23:40:00.622283: val_loss -0.7926 +2024-11-22 23:40:00.622372: Pseudo dice [0.8587] +2024-11-22 23:40:00.622454: Epoch time: 18.62 s +2024-11-22 23:40:01.515596: +2024-11-22 23:40:01.515820: Epoch 6643 +2024-11-22 23:40:01.515932: Current learning rate: 0.00203 +2024-11-22 23:40:19.600429: train_loss -0.8205 +2024-11-22 23:40:19.600644: val_loss -0.7825 +2024-11-22 23:40:19.600721: Pseudo dice [0.8523] +2024-11-22 23:40:19.600810: Epoch time: 18.09 s +2024-11-22 23:40:20.483002: +2024-11-22 23:40:20.483217: Epoch 6644 +2024-11-22 23:40:20.483351: Current learning rate: 0.00202 +2024-11-22 23:40:38.971568: train_loss -0.8121 +2024-11-22 23:40:38.971803: val_loss -0.7749 +2024-11-22 23:40:38.971895: Pseudo dice [0.8594] +2024-11-22 23:40:38.971981: Epoch time: 18.49 s +2024-11-22 23:40:39.864968: +2024-11-22 23:40:39.865178: Epoch 6645 +2024-11-22 23:40:39.865296: Current learning rate: 0.00202 +2024-11-22 23:40:58.414383: train_loss -0.8161 +2024-11-22 23:40:58.414634: val_loss -0.7702 +2024-11-22 23:40:58.414715: Pseudo dice [0.8665] +2024-11-22 23:40:58.419981: Epoch time: 18.55 s +2024-11-22 23:40:59.333356: +2024-11-22 23:40:59.333578: Epoch 6646 +2024-11-22 23:40:59.333689: Current learning rate: 0.00202 +2024-11-22 23:41:17.543253: train_loss -0.8231 +2024-11-22 23:41:17.543456: val_loss -0.7816 +2024-11-22 23:41:17.543535: Pseudo dice [0.8565] +2024-11-22 23:41:17.543617: Epoch time: 18.21 s +2024-11-22 23:41:18.428166: +2024-11-22 23:41:18.428378: Epoch 6647 +2024-11-22 23:41:18.428506: Current learning rate: 0.00202 +2024-11-22 23:41:36.882073: train_loss -0.815 +2024-11-22 23:41:36.895295: val_loss -0.7956 +2024-11-22 23:41:36.895384: Pseudo dice [0.8602] +2024-11-22 23:41:36.895470: Epoch time: 18.45 s +2024-11-22 23:41:37.779736: +2024-11-22 23:41:37.779944: Epoch 6648 +2024-11-22 23:41:37.780054: Current learning rate: 0.00202 +2024-11-22 23:41:56.187832: train_loss -0.8137 +2024-11-22 23:41:56.188092: val_loss -0.7841 +2024-11-22 23:41:56.188177: Pseudo dice [0.8581] +2024-11-22 23:41:56.188270: Epoch time: 18.41 s +2024-11-22 23:41:57.084526: +2024-11-22 23:41:57.084716: Epoch 6649 +2024-11-22 23:41:57.084834: Current learning rate: 0.00202 +2024-11-22 23:42:15.337817: train_loss -0.8178 +2024-11-22 23:42:15.338041: val_loss -0.7786 +2024-11-22 23:42:15.338138: Pseudo dice [0.8455] +2024-11-22 23:42:15.338217: Epoch time: 18.25 s +2024-11-22 23:42:16.591974: +2024-11-22 23:42:16.592182: Epoch 6650 +2024-11-22 23:42:16.592294: Current learning rate: 0.00202 +2024-11-22 23:42:34.038254: train_loss -0.8199 +2024-11-22 23:42:34.038464: val_loss -0.7657 +2024-11-22 23:42:34.038538: Pseudo dice [0.8651] +2024-11-22 23:42:34.038618: Epoch time: 17.45 s +2024-11-22 23:42:34.981138: +2024-11-22 23:42:34.981325: Epoch 6651 +2024-11-22 23:42:34.981451: Current learning rate: 0.00201 +2024-11-22 23:42:53.349279: train_loss -0.8093 +2024-11-22 23:42:53.349520: val_loss -0.7682 +2024-11-22 23:42:53.349620: Pseudo dice [0.8489] +2024-11-22 23:42:53.349722: Epoch time: 18.37 s +2024-11-22 23:42:54.241303: +2024-11-22 23:42:54.241519: Epoch 6652 +2024-11-22 23:42:54.241659: Current learning rate: 0.00201 +2024-11-22 23:43:12.553195: train_loss -0.8145 +2024-11-22 23:43:12.553441: val_loss -0.7936 +2024-11-22 23:43:12.553520: Pseudo dice [0.8571] +2024-11-22 23:43:12.553609: Epoch time: 18.31 s +2024-11-22 23:43:13.855411: +2024-11-22 23:43:13.855640: Epoch 6653 +2024-11-22 23:43:13.855768: Current learning rate: 0.00201 +2024-11-22 23:43:32.518425: train_loss -0.8153 +2024-11-22 23:43:32.519131: val_loss -0.8008 +2024-11-22 23:43:32.519217: Pseudo dice [0.8614] +2024-11-22 23:43:32.519298: Epoch time: 18.66 s +2024-11-22 23:43:33.468496: +2024-11-22 23:43:33.468718: Epoch 6654 +2024-11-22 23:43:33.468842: Current learning rate: 0.00201 +2024-11-22 23:43:51.980325: train_loss -0.8171 +2024-11-22 23:43:51.980535: val_loss -0.7365 +2024-11-22 23:43:51.980615: Pseudo dice [0.8627] +2024-11-22 23:43:51.980690: Epoch time: 18.51 s +2024-11-22 23:43:52.979994: +2024-11-22 23:43:52.980206: Epoch 6655 +2024-11-22 23:43:52.980320: Current learning rate: 0.00201 +2024-11-22 23:44:10.978909: train_loss -0.8167 +2024-11-22 23:44:10.979199: val_loss -0.7738 +2024-11-22 23:44:10.979290: Pseudo dice [0.8596] +2024-11-22 23:44:10.979379: Epoch time: 18.0 s +2024-11-22 23:44:11.867962: +2024-11-22 23:44:11.868233: Epoch 6656 +2024-11-22 23:44:11.868371: Current learning rate: 0.00201 +2024-11-22 23:44:29.802243: train_loss -0.828 +2024-11-22 23:44:29.802483: val_loss -0.7585 +2024-11-22 23:44:29.802563: Pseudo dice [0.8534] +2024-11-22 23:44:29.802660: Epoch time: 17.94 s +2024-11-22 23:44:30.686489: +2024-11-22 23:44:30.686712: Epoch 6657 +2024-11-22 23:44:30.686821: Current learning rate: 0.00201 +2024-11-22 23:44:49.903664: train_loss -0.8193 +2024-11-22 23:44:49.903875: val_loss -0.7915 +2024-11-22 23:44:49.903957: Pseudo dice [0.8486] +2024-11-22 23:44:49.904043: Epoch time: 19.22 s +2024-11-22 23:44:50.853599: +2024-11-22 23:44:50.853827: Epoch 6658 +2024-11-22 23:44:50.853937: Current learning rate: 0.00201 +2024-11-22 23:45:09.425829: train_loss -0.8173 +2024-11-22 23:45:09.426041: val_loss -0.7711 +2024-11-22 23:45:09.426121: Pseudo dice [0.8515] +2024-11-22 23:45:09.426199: Epoch time: 18.57 s +2024-11-22 23:45:10.312757: +2024-11-22 23:45:10.312965: Epoch 6659 +2024-11-22 23:45:10.313102: Current learning rate: 0.002 +2024-11-22 23:45:28.855895: train_loss -0.8217 +2024-11-22 23:45:28.856153: val_loss -0.7864 +2024-11-22 23:45:28.856235: Pseudo dice [0.8585] +2024-11-22 23:45:28.856311: Epoch time: 18.54 s +2024-11-22 23:45:29.743866: +2024-11-22 23:45:29.744085: Epoch 6660 +2024-11-22 23:45:29.761796: Current learning rate: 0.002 +2024-11-22 23:45:48.621216: train_loss -0.8166 +2024-11-22 23:45:48.621453: val_loss -0.7882 +2024-11-22 23:45:48.621533: Pseudo dice [0.8661] +2024-11-22 23:45:48.621628: Epoch time: 18.88 s +2024-11-22 23:45:49.510872: +2024-11-22 23:45:49.511087: Epoch 6661 +2024-11-22 23:45:49.511222: Current learning rate: 0.002 +2024-11-22 23:46:08.100844: train_loss -0.8094 +2024-11-22 23:46:08.106221: val_loss -0.7953 +2024-11-22 23:46:08.106383: Pseudo dice [0.8595] +2024-11-22 23:46:08.106470: Epoch time: 18.59 s +2024-11-22 23:46:09.137811: +2024-11-22 23:46:09.138019: Epoch 6662 +2024-11-22 23:46:09.138150: Current learning rate: 0.002 +2024-11-22 23:46:27.618312: train_loss -0.8185 +2024-11-22 23:46:27.618541: val_loss -0.7906 +2024-11-22 23:46:27.618643: Pseudo dice [0.8639] +2024-11-22 23:46:27.618740: Epoch time: 18.48 s +2024-11-22 23:46:28.503436: +2024-11-22 23:46:28.503632: Epoch 6663 +2024-11-22 23:46:28.503761: Current learning rate: 0.002 +2024-11-22 23:46:46.740516: train_loss -0.8088 +2024-11-22 23:46:46.740746: val_loss -0.7754 +2024-11-22 23:46:46.740855: Pseudo dice [0.846] +2024-11-22 23:46:46.740949: Epoch time: 18.24 s +2024-11-22 23:46:48.020582: +2024-11-22 23:46:48.020803: Epoch 6664 +2024-11-22 23:46:48.020922: Current learning rate: 0.002 +2024-11-22 23:47:06.893211: train_loss -0.8127 +2024-11-22 23:47:06.893461: val_loss -0.7651 +2024-11-22 23:47:06.893551: Pseudo dice [0.838] +2024-11-22 23:47:06.893632: Epoch time: 18.87 s +2024-11-22 23:47:07.782590: +2024-11-22 23:47:07.782783: Epoch 6665 +2024-11-22 23:47:07.782892: Current learning rate: 0.002 +2024-11-22 23:47:25.952027: train_loss -0.8133 +2024-11-22 23:47:25.952295: val_loss -0.7689 +2024-11-22 23:47:25.952386: Pseudo dice [0.8509] +2024-11-22 23:47:25.952460: Epoch time: 18.17 s +2024-11-22 23:47:26.837578: +2024-11-22 23:47:26.837915: Epoch 6666 +2024-11-22 23:47:26.838057: Current learning rate: 0.00199 +2024-11-22 23:47:45.152246: train_loss -0.8116 +2024-11-22 23:47:45.152454: val_loss -0.785 +2024-11-22 23:47:45.152533: Pseudo dice [0.8574] +2024-11-22 23:47:45.152637: Epoch time: 18.32 s +2024-11-22 23:47:46.039514: +2024-11-22 23:47:46.039720: Epoch 6667 +2024-11-22 23:47:46.039832: Current learning rate: 0.00199 +2024-11-22 23:48:04.744586: train_loss -0.8114 +2024-11-22 23:48:04.744821: val_loss -0.7923 +2024-11-22 23:48:04.744907: Pseudo dice [0.8583] +2024-11-22 23:48:04.744985: Epoch time: 18.71 s +2024-11-22 23:48:05.639225: +2024-11-22 23:48:05.639467: Epoch 6668 +2024-11-22 23:48:05.639598: Current learning rate: 0.00199 +2024-11-22 23:48:24.895443: train_loss -0.823 +2024-11-22 23:48:24.895664: val_loss -0.7849 +2024-11-22 23:48:24.895789: Pseudo dice [0.8567] +2024-11-22 23:48:24.895885: Epoch time: 19.26 s +2024-11-22 23:48:25.792688: +2024-11-22 23:48:25.792907: Epoch 6669 +2024-11-22 23:48:25.793019: Current learning rate: 0.00199 +2024-11-22 23:48:43.837604: train_loss -0.8141 +2024-11-22 23:48:43.837834: val_loss -0.7639 +2024-11-22 23:48:43.837934: Pseudo dice [0.8588] +2024-11-22 23:48:43.838018: Epoch time: 18.05 s +2024-11-22 23:48:44.731985: +2024-11-22 23:48:44.732203: Epoch 6670 +2024-11-22 23:48:44.732318: Current learning rate: 0.00199 +2024-11-22 23:49:01.724834: train_loss -0.8181 +2024-11-22 23:49:01.725047: val_loss -0.758 +2024-11-22 23:49:01.725133: Pseudo dice [0.8436] +2024-11-22 23:49:01.725214: Epoch time: 16.99 s +2024-11-22 23:49:02.608923: +2024-11-22 23:49:02.609135: Epoch 6671 +2024-11-22 23:49:02.609272: Current learning rate: 0.00199 +2024-11-22 23:49:20.168069: train_loss -0.8078 +2024-11-22 23:49:20.168335: val_loss -0.7946 +2024-11-22 23:49:20.168432: Pseudo dice [0.8605] +2024-11-22 23:49:20.168518: Epoch time: 17.56 s +2024-11-22 23:49:21.059622: +2024-11-22 23:49:21.059836: Epoch 6672 +2024-11-22 23:49:21.059954: Current learning rate: 0.00199 +2024-11-22 23:49:38.870935: train_loss -0.8185 +2024-11-22 23:49:38.871193: val_loss -0.7493 +2024-11-22 23:49:38.871275: Pseudo dice [0.8465] +2024-11-22 23:49:38.906228: Epoch time: 17.81 s +2024-11-22 23:49:39.797716: +2024-11-22 23:49:39.797935: Epoch 6673 +2024-11-22 23:49:39.798050: Current learning rate: 0.00199 +2024-11-22 23:49:57.687490: train_loss -0.8118 +2024-11-22 23:49:57.687772: val_loss -0.793 +2024-11-22 23:49:57.687864: Pseudo dice [0.862] +2024-11-22 23:49:57.687942: Epoch time: 17.89 s +2024-11-22 23:49:58.577868: +2024-11-22 23:49:58.578085: Epoch 6674 +2024-11-22 23:49:58.578212: Current learning rate: 0.00198 +2024-11-22 23:50:17.230507: train_loss -0.8156 +2024-11-22 23:50:17.230716: val_loss -0.7407 +2024-11-22 23:50:17.230801: Pseudo dice [0.857] +2024-11-22 23:50:17.230884: Epoch time: 18.65 s +2024-11-22 23:50:18.563362: +2024-11-22 23:50:18.563562: Epoch 6675 +2024-11-22 23:50:18.563675: Current learning rate: 0.00198 +2024-11-22 23:50:37.010046: train_loss -0.7981 +2024-11-22 23:50:37.010274: val_loss -0.7776 +2024-11-22 23:50:37.010388: Pseudo dice [0.8521] +2024-11-22 23:50:37.010471: Epoch time: 18.45 s +2024-11-22 23:50:37.902148: +2024-11-22 23:50:37.902390: Epoch 6676 +2024-11-22 23:50:37.902504: Current learning rate: 0.00198 +2024-11-22 23:50:57.080836: train_loss -0.8012 +2024-11-22 23:50:57.081051: val_loss -0.7598 +2024-11-22 23:50:57.081137: Pseudo dice [0.852] +2024-11-22 23:50:57.081213: Epoch time: 19.18 s +2024-11-22 23:50:58.069525: +2024-11-22 23:50:58.069760: Epoch 6677 +2024-11-22 23:50:58.069877: Current learning rate: 0.00198 +2024-11-22 23:51:16.240177: train_loss -0.7891 +2024-11-22 23:51:16.240397: val_loss -0.76 +2024-11-22 23:51:16.240477: Pseudo dice [0.8662] +2024-11-22 23:51:16.240560: Epoch time: 18.17 s +2024-11-22 23:51:17.131900: +2024-11-22 23:51:17.132114: Epoch 6678 +2024-11-22 23:51:17.132227: Current learning rate: 0.00198 +2024-11-22 23:51:34.456255: train_loss -0.8029 +2024-11-22 23:51:34.456471: val_loss -0.7885 +2024-11-22 23:51:34.456559: Pseudo dice [0.8588] +2024-11-22 23:51:34.456655: Epoch time: 17.33 s +2024-11-22 23:51:35.512005: +2024-11-22 23:51:35.512220: Epoch 6679 +2024-11-22 23:51:35.512335: Current learning rate: 0.00198 +2024-11-22 23:51:53.359206: train_loss -0.802 +2024-11-22 23:51:53.359460: val_loss -0.8041 +2024-11-22 23:51:53.359594: Pseudo dice [0.8487] +2024-11-22 23:51:53.359677: Epoch time: 17.85 s +2024-11-22 23:51:54.324998: +2024-11-22 23:51:54.325204: Epoch 6680 +2024-11-22 23:51:54.325321: Current learning rate: 0.00198 +2024-11-22 23:52:12.483788: train_loss -0.8063 +2024-11-22 23:52:12.484069: val_loss -0.7595 +2024-11-22 23:52:12.484162: Pseudo dice [0.8426] +2024-11-22 23:52:12.484265: Epoch time: 18.16 s +2024-11-22 23:52:13.374331: +2024-11-22 23:52:13.374544: Epoch 6681 +2024-11-22 23:52:13.374661: Current learning rate: 0.00197 +2024-11-22 23:52:31.035617: train_loss -0.8015 +2024-11-22 23:52:31.035834: val_loss -0.7818 +2024-11-22 23:52:31.036000: Pseudo dice [0.8442] +2024-11-22 23:52:31.036104: Epoch time: 17.66 s +2024-11-22 23:52:31.929743: +2024-11-22 23:52:31.929931: Epoch 6682 +2024-11-22 23:52:31.930041: Current learning rate: 0.00197 +2024-11-22 23:52:50.987628: train_loss -0.8079 +2024-11-22 23:52:50.987841: val_loss -0.7788 +2024-11-22 23:52:50.987923: Pseudo dice [0.8468] +2024-11-22 23:52:50.988022: Epoch time: 19.06 s +2024-11-22 23:52:51.876599: +2024-11-22 23:52:51.876801: Epoch 6683 +2024-11-22 23:52:51.876921: Current learning rate: 0.00197 +2024-11-22 23:53:10.241433: train_loss -0.8153 +2024-11-22 23:53:10.241670: val_loss -0.7878 +2024-11-22 23:53:10.241805: Pseudo dice [0.849] +2024-11-22 23:53:10.241888: Epoch time: 18.37 s +2024-11-22 23:53:11.141296: +2024-11-22 23:53:11.141540: Epoch 6684 +2024-11-22 23:53:11.141655: Current learning rate: 0.00197 +2024-11-22 23:53:29.468987: train_loss -0.8087 +2024-11-22 23:53:29.469203: val_loss -0.7808 +2024-11-22 23:53:29.469291: Pseudo dice [0.8581] +2024-11-22 23:53:29.469371: Epoch time: 18.33 s +2024-11-22 23:53:30.362766: +2024-11-22 23:53:30.362967: Epoch 6685 +2024-11-22 23:53:30.363112: Current learning rate: 0.00197 +2024-11-22 23:53:48.525418: train_loss -0.8109 +2024-11-22 23:53:48.525645: val_loss -0.7602 +2024-11-22 23:53:48.525743: Pseudo dice [0.8428] +2024-11-22 23:53:48.525826: Epoch time: 18.16 s +2024-11-22 23:53:49.953822: +2024-11-22 23:53:49.954021: Epoch 6686 +2024-11-22 23:53:49.954132: Current learning rate: 0.00197 +2024-11-22 23:54:08.378220: train_loss -0.8123 +2024-11-22 23:54:08.378460: val_loss -0.7819 +2024-11-22 23:54:08.378539: Pseudo dice [0.873] +2024-11-22 23:54:08.378621: Epoch time: 18.43 s +2024-11-22 23:54:09.279284: +2024-11-22 23:54:09.279499: Epoch 6687 +2024-11-22 23:54:09.279611: Current learning rate: 0.00197 +2024-11-22 23:54:27.078163: train_loss -0.817 +2024-11-22 23:54:27.078416: val_loss -0.774 +2024-11-22 23:54:27.078528: Pseudo dice [0.8566] +2024-11-22 23:54:27.078610: Epoch time: 17.8 s +2024-11-22 23:54:27.966915: +2024-11-22 23:54:27.967160: Epoch 6688 +2024-11-22 23:54:27.967274: Current learning rate: 0.00196 +2024-11-22 23:54:46.823935: train_loss -0.8222 +2024-11-22 23:54:46.824161: val_loss -0.7748 +2024-11-22 23:54:46.824255: Pseudo dice [0.8591] +2024-11-22 23:54:46.824347: Epoch time: 18.86 s +2024-11-22 23:54:47.712407: +2024-11-22 23:54:47.712623: Epoch 6689 +2024-11-22 23:54:47.712739: Current learning rate: 0.00196 +2024-11-22 23:55:05.869290: train_loss -0.8157 +2024-11-22 23:55:05.869518: val_loss -0.7753 +2024-11-22 23:55:05.869599: Pseudo dice [0.847] +2024-11-22 23:55:05.869692: Epoch time: 18.16 s +2024-11-22 23:55:06.764090: +2024-11-22 23:55:06.764290: Epoch 6690 +2024-11-22 23:55:06.764407: Current learning rate: 0.00196 +2024-11-22 23:55:25.259207: train_loss -0.8181 +2024-11-22 23:55:25.259442: val_loss -0.7725 +2024-11-22 23:55:25.259530: Pseudo dice [0.8596] +2024-11-22 23:55:25.259623: Epoch time: 18.5 s +2024-11-22 23:55:26.162035: +2024-11-22 23:55:26.162238: Epoch 6691 +2024-11-22 23:55:26.162350: Current learning rate: 0.00196 +2024-11-22 23:55:44.385712: train_loss -0.8138 +2024-11-22 23:55:44.385909: val_loss -0.778 +2024-11-22 23:55:44.385986: Pseudo dice [0.8515] +2024-11-22 23:55:44.386067: Epoch time: 18.22 s +2024-11-22 23:55:45.274167: +2024-11-22 23:55:45.274383: Epoch 6692 +2024-11-22 23:55:45.274499: Current learning rate: 0.00196 +2024-11-22 23:56:02.644225: train_loss -0.823 +2024-11-22 23:56:02.644438: val_loss -0.7848 +2024-11-22 23:56:02.644542: Pseudo dice [0.8551] +2024-11-22 23:56:02.644620: Epoch time: 17.37 s +2024-11-22 23:56:03.622953: +2024-11-22 23:56:03.623193: Epoch 6693 +2024-11-22 23:56:03.623322: Current learning rate: 0.00196 +2024-11-22 23:56:22.686455: train_loss -0.8151 +2024-11-22 23:56:22.686664: val_loss -0.7813 +2024-11-22 23:56:22.686747: Pseudo dice [0.8662] +2024-11-22 23:56:22.686828: Epoch time: 19.06 s +2024-11-22 23:56:23.580159: +2024-11-22 23:56:23.580350: Epoch 6694 +2024-11-22 23:56:23.580472: Current learning rate: 0.00196 +2024-11-22 23:56:42.088573: train_loss -0.8163 +2024-11-22 23:56:42.088793: val_loss -0.7737 +2024-11-22 23:56:42.088875: Pseudo dice [0.8505] +2024-11-22 23:56:42.088960: Epoch time: 18.51 s +2024-11-22 23:56:43.007102: +2024-11-22 23:56:43.007316: Epoch 6695 +2024-11-22 23:56:43.007430: Current learning rate: 0.00196 +2024-11-22 23:57:01.480749: train_loss -0.8011 +2024-11-22 23:57:01.486138: val_loss -0.7805 +2024-11-22 23:57:01.486262: Pseudo dice [0.8399] +2024-11-22 23:57:01.486353: Epoch time: 18.47 s +2024-11-22 23:57:02.394081: +2024-11-22 23:57:02.394276: Epoch 6696 +2024-11-22 23:57:02.394393: Current learning rate: 0.00195 +2024-11-22 23:57:20.442462: train_loss -0.8031 +2024-11-22 23:57:20.442679: val_loss -0.7601 +2024-11-22 23:57:20.442764: Pseudo dice [0.8502] +2024-11-22 23:57:20.443898: Epoch time: 18.05 s +2024-11-22 23:57:21.770525: +2024-11-22 23:57:21.770719: Epoch 6697 +2024-11-22 23:57:21.770835: Current learning rate: 0.00195 +2024-11-22 23:57:39.901872: train_loss -0.8129 +2024-11-22 23:57:39.902133: val_loss -0.7763 +2024-11-22 23:57:39.902220: Pseudo dice [0.8688] +2024-11-22 23:57:39.902304: Epoch time: 18.13 s +2024-11-22 23:57:40.970803: +2024-11-22 23:57:40.971031: Epoch 6698 +2024-11-22 23:57:40.971148: Current learning rate: 0.00195 +2024-11-22 23:57:59.401490: train_loss -0.8106 +2024-11-22 23:57:59.401709: val_loss -0.7874 +2024-11-22 23:57:59.401788: Pseudo dice [0.8662] +2024-11-22 23:57:59.401870: Epoch time: 18.43 s +2024-11-22 23:58:00.300590: +2024-11-22 23:58:00.300810: Epoch 6699 +2024-11-22 23:58:00.300940: Current learning rate: 0.00195 +2024-11-22 23:58:17.894919: train_loss -0.8132 +2024-11-22 23:58:17.895148: val_loss -0.7899 +2024-11-22 23:58:17.895230: Pseudo dice [0.853] +2024-11-22 23:58:17.895334: Epoch time: 17.6 s +2024-11-22 23:58:19.128138: +2024-11-22 23:58:19.128342: Epoch 6700 +2024-11-22 23:58:19.128457: Current learning rate: 0.00195 +2024-11-22 23:58:36.526253: train_loss -0.8122 +2024-11-22 23:58:36.526486: val_loss -0.7862 +2024-11-22 23:58:36.526584: Pseudo dice [0.8571] +2024-11-22 23:58:36.528894: Epoch time: 17.4 s +2024-11-22 23:58:37.441602: +2024-11-22 23:58:37.441806: Epoch 6701 +2024-11-22 23:58:37.441920: Current learning rate: 0.00195 +2024-11-22 23:58:56.680336: train_loss -0.8136 +2024-11-22 23:58:56.680582: val_loss -0.7709 +2024-11-22 23:58:56.680662: Pseudo dice [0.8426] +2024-11-22 23:58:56.680742: Epoch time: 19.24 s +2024-11-22 23:58:57.684961: +2024-11-22 23:58:57.685177: Epoch 6702 +2024-11-22 23:58:57.685300: Current learning rate: 0.00195 +2024-11-22 23:59:15.542206: train_loss -0.8137 +2024-11-22 23:59:15.542465: val_loss -0.7954 +2024-11-22 23:59:15.542547: Pseudo dice [0.8629] +2024-11-22 23:59:15.542645: Epoch time: 17.86 s +2024-11-22 23:59:16.436502: +2024-11-22 23:59:16.436716: Epoch 6703 +2024-11-22 23:59:16.436828: Current learning rate: 0.00194 +2024-11-22 23:59:34.819107: train_loss -0.8142 +2024-11-22 23:59:34.819329: val_loss -0.7788 +2024-11-22 23:59:34.819435: Pseudo dice [0.8616] +2024-11-22 23:59:34.819523: Epoch time: 18.38 s +2024-11-22 23:59:35.713895: +2024-11-22 23:59:35.714136: Epoch 6704 +2024-11-22 23:59:35.714253: Current learning rate: 0.00194 +2024-11-22 23:59:52.989890: train_loss -0.8115 +2024-11-22 23:59:52.990188: val_loss -0.7737 +2024-11-22 23:59:52.990278: Pseudo dice [0.8584] +2024-11-22 23:59:52.990366: Epoch time: 17.28 s +2024-11-22 23:59:53.882237: +2024-11-22 23:59:53.882447: Epoch 6705 +2024-11-22 23:59:53.882580: Current learning rate: 0.00194 +2024-11-23 00:00:12.560659: train_loss -0.8187 +2024-11-23 00:00:12.560925: val_loss -0.7809 +2024-11-23 00:00:12.561008: Pseudo dice [0.8665] +2024-11-23 00:00:12.561096: Epoch time: 18.68 s +2024-11-23 00:00:13.448117: +2024-11-23 00:00:13.448306: Epoch 6706 +2024-11-23 00:00:13.448421: Current learning rate: 0.00194 +2024-11-23 00:00:32.055851: train_loss -0.82 +2024-11-23 00:00:32.056072: val_loss -0.778 +2024-11-23 00:00:32.056152: Pseudo dice [0.8453] +2024-11-23 00:00:32.056227: Epoch time: 18.61 s +2024-11-23 00:00:33.337912: +2024-11-23 00:00:33.338113: Epoch 6707 +2024-11-23 00:00:33.338238: Current learning rate: 0.00194 +2024-11-23 00:00:51.374525: train_loss -0.8194 +2024-11-23 00:00:51.374746: val_loss -0.7691 +2024-11-23 00:00:51.374830: Pseudo dice [0.849] +2024-11-23 00:00:51.374924: Epoch time: 18.04 s +2024-11-23 00:00:52.269027: +2024-11-23 00:00:52.269239: Epoch 6708 +2024-11-23 00:00:52.269365: Current learning rate: 0.00194 +2024-11-23 00:01:11.323253: train_loss -0.8092 +2024-11-23 00:01:11.323481: val_loss -0.7384 +2024-11-23 00:01:11.323561: Pseudo dice [0.8502] +2024-11-23 00:01:11.323637: Epoch time: 19.06 s +2024-11-23 00:01:12.323900: +2024-11-23 00:01:12.324106: Epoch 6709 +2024-11-23 00:01:12.324218: Current learning rate: 0.00194 +2024-11-23 00:01:29.526142: train_loss -0.8121 +2024-11-23 00:01:29.526353: val_loss -0.7627 +2024-11-23 00:01:29.530574: Pseudo dice [0.8559] +2024-11-23 00:01:29.532652: Epoch time: 17.2 s +2024-11-23 00:01:30.440420: +2024-11-23 00:01:30.440679: Epoch 6710 +2024-11-23 00:01:30.440804: Current learning rate: 0.00194 +2024-11-23 00:01:49.073279: train_loss -0.8173 +2024-11-23 00:01:49.073496: val_loss -0.7839 +2024-11-23 00:01:49.073595: Pseudo dice [0.8662] +2024-11-23 00:01:49.073674: Epoch time: 18.63 s +2024-11-23 00:01:49.967745: +2024-11-23 00:01:49.967943: Epoch 6711 +2024-11-23 00:01:49.968071: Current learning rate: 0.00193 +2024-11-23 00:02:07.980377: train_loss -0.8158 +2024-11-23 00:02:07.980663: val_loss -0.747 +2024-11-23 00:02:07.980779: Pseudo dice [0.8498] +2024-11-23 00:02:07.980869: Epoch time: 18.01 s +2024-11-23 00:02:08.887987: +2024-11-23 00:02:08.888177: Epoch 6712 +2024-11-23 00:02:08.888305: Current learning rate: 0.00193 +2024-11-23 00:02:27.906196: train_loss -0.8017 +2024-11-23 00:02:27.906415: val_loss -0.76 +2024-11-23 00:02:27.906498: Pseudo dice [0.8447] +2024-11-23 00:02:27.906575: Epoch time: 19.02 s +2024-11-23 00:02:28.799216: +2024-11-23 00:02:28.799431: Epoch 6713 +2024-11-23 00:02:28.799547: Current learning rate: 0.00193 +2024-11-23 00:02:47.487422: train_loss -0.8154 +2024-11-23 00:02:47.487647: val_loss -0.7953 +2024-11-23 00:02:47.499638: Pseudo dice [0.8657] +2024-11-23 00:02:47.499743: Epoch time: 18.69 s +2024-11-23 00:02:48.428579: +2024-11-23 00:02:48.428792: Epoch 6714 +2024-11-23 00:02:48.428908: Current learning rate: 0.00193 +2024-11-23 00:03:06.900287: train_loss -0.816 +2024-11-23 00:03:06.900521: val_loss -0.8041 +2024-11-23 00:03:06.900612: Pseudo dice [0.8646] +2024-11-23 00:03:06.900691: Epoch time: 18.47 s +2024-11-23 00:03:07.794917: +2024-11-23 00:03:07.795138: Epoch 6715 +2024-11-23 00:03:07.795251: Current learning rate: 0.00193 +2024-11-23 00:03:25.604304: train_loss -0.8165 +2024-11-23 00:03:25.604547: val_loss -0.787 +2024-11-23 00:03:25.604626: Pseudo dice [0.8554] +2024-11-23 00:03:25.604713: Epoch time: 17.81 s +2024-11-23 00:03:26.500583: +2024-11-23 00:03:26.500806: Epoch 6716 +2024-11-23 00:03:26.500947: Current learning rate: 0.00193 +2024-11-23 00:03:44.603624: train_loss -0.8186 +2024-11-23 00:03:44.603896: val_loss -0.7724 +2024-11-23 00:03:44.603971: Pseudo dice [0.8571] +2024-11-23 00:03:44.604050: Epoch time: 18.1 s +2024-11-23 00:03:45.493080: +2024-11-23 00:03:45.493304: Epoch 6717 +2024-11-23 00:03:45.493428: Current learning rate: 0.00193 +2024-11-23 00:04:03.719137: train_loss -0.8148 +2024-11-23 00:04:03.719360: val_loss -0.7865 +2024-11-23 00:04:03.719459: Pseudo dice [0.84] +2024-11-23 00:04:03.719555: Epoch time: 18.23 s +2024-11-23 00:04:04.993728: +2024-11-23 00:04:04.993945: Epoch 6718 +2024-11-23 00:04:04.994054: Current learning rate: 0.00192 +2024-11-23 00:04:24.613938: train_loss -0.8171 +2024-11-23 00:04:24.614184: val_loss -0.7758 +2024-11-23 00:04:24.614262: Pseudo dice [0.8554] +2024-11-23 00:04:24.614342: Epoch time: 19.62 s +2024-11-23 00:04:25.551964: +2024-11-23 00:04:25.552236: Epoch 6719 +2024-11-23 00:04:25.552394: Current learning rate: 0.00192 +2024-11-23 00:04:43.639362: train_loss -0.8195 +2024-11-23 00:04:43.639590: val_loss -0.7588 +2024-11-23 00:04:43.639673: Pseudo dice [0.8491] +2024-11-23 00:04:43.639768: Epoch time: 18.09 s +2024-11-23 00:04:44.529339: +2024-11-23 00:04:44.529560: Epoch 6720 +2024-11-23 00:04:44.529683: Current learning rate: 0.00192 +2024-11-23 00:05:02.240494: train_loss -0.8158 +2024-11-23 00:05:02.240712: val_loss -0.791 +2024-11-23 00:05:02.240802: Pseudo dice [0.8571] +2024-11-23 00:05:02.240879: Epoch time: 17.71 s +2024-11-23 00:05:03.135526: +2024-11-23 00:05:03.135745: Epoch 6721 +2024-11-23 00:05:03.135855: Current learning rate: 0.00192 +2024-11-23 00:05:22.056676: train_loss -0.8074 +2024-11-23 00:05:22.056887: val_loss -0.7837 +2024-11-23 00:05:22.056966: Pseudo dice [0.8554] +2024-11-23 00:05:22.057053: Epoch time: 18.92 s +2024-11-23 00:05:22.956118: +2024-11-23 00:05:22.956334: Epoch 6722 +2024-11-23 00:05:22.956450: Current learning rate: 0.00192 +2024-11-23 00:05:41.614774: train_loss -0.8036 +2024-11-23 00:05:41.615021: val_loss -0.7678 +2024-11-23 00:05:41.615111: Pseudo dice [0.864] +2024-11-23 00:05:41.615198: Epoch time: 18.66 s +2024-11-23 00:05:42.510727: +2024-11-23 00:05:42.510959: Epoch 6723 +2024-11-23 00:05:42.511083: Current learning rate: 0.00192 +2024-11-23 00:05:59.144951: train_loss -0.8177 +2024-11-23 00:05:59.145183: val_loss -0.7746 +2024-11-23 00:05:59.145260: Pseudo dice [0.8527] +2024-11-23 00:05:59.145341: Epoch time: 16.64 s +2024-11-23 00:06:00.038762: +2024-11-23 00:06:00.039000: Epoch 6724 +2024-11-23 00:06:00.039117: Current learning rate: 0.00192 +2024-11-23 00:06:18.404909: train_loss -0.8064 +2024-11-23 00:06:18.405180: val_loss -0.7765 +2024-11-23 00:06:18.405267: Pseudo dice [0.8538] +2024-11-23 00:06:18.405353: Epoch time: 18.37 s +2024-11-23 00:06:19.300015: +2024-11-23 00:06:19.300265: Epoch 6725 +2024-11-23 00:06:19.300377: Current learning rate: 0.00192 +2024-11-23 00:06:37.607844: train_loss -0.8096 +2024-11-23 00:06:37.608093: val_loss -0.7758 +2024-11-23 00:06:37.608195: Pseudo dice [0.8448] +2024-11-23 00:06:37.608366: Epoch time: 18.31 s +2024-11-23 00:06:38.504130: +2024-11-23 00:06:38.504368: Epoch 6726 +2024-11-23 00:06:38.504496: Current learning rate: 0.00191 +2024-11-23 00:06:56.718137: train_loss -0.8086 +2024-11-23 00:06:56.718381: val_loss -0.7771 +2024-11-23 00:06:56.718454: Pseudo dice [0.8591] +2024-11-23 00:06:56.718544: Epoch time: 18.21 s +2024-11-23 00:06:57.611531: +2024-11-23 00:06:57.611763: Epoch 6727 +2024-11-23 00:06:57.611883: Current learning rate: 0.00191 +2024-11-23 00:07:15.535438: train_loss -0.8201 +2024-11-23 00:07:15.535640: val_loss -0.7801 +2024-11-23 00:07:15.535763: Pseudo dice [0.8624] +2024-11-23 00:07:15.535845: Epoch time: 17.92 s +2024-11-23 00:07:16.424090: +2024-11-23 00:07:16.424299: Epoch 6728 +2024-11-23 00:07:16.424422: Current learning rate: 0.00191 +2024-11-23 00:07:34.286777: train_loss -0.8151 +2024-11-23 00:07:34.286990: val_loss -0.7951 +2024-11-23 00:07:34.287073: Pseudo dice [0.8547] +2024-11-23 00:07:34.287147: Epoch time: 17.86 s +2024-11-23 00:07:35.735679: +2024-11-23 00:07:35.735905: Epoch 6729 +2024-11-23 00:07:35.736032: Current learning rate: 0.00191 +2024-11-23 00:07:53.822455: train_loss -0.8168 +2024-11-23 00:07:53.822741: val_loss -0.7505 +2024-11-23 00:07:53.822820: Pseudo dice [0.8601] +2024-11-23 00:07:53.822913: Epoch time: 18.09 s +2024-11-23 00:07:54.716868: +2024-11-23 00:07:54.717104: Epoch 6730 +2024-11-23 00:07:54.717219: Current learning rate: 0.00191 +2024-11-23 00:08:12.410103: train_loss -0.8199 +2024-11-23 00:08:12.410324: val_loss -0.782 +2024-11-23 00:08:12.410409: Pseudo dice [0.8622] +2024-11-23 00:08:12.410500: Epoch time: 17.69 s +2024-11-23 00:08:13.341552: +2024-11-23 00:08:13.341777: Epoch 6731 +2024-11-23 00:08:13.341913: Current learning rate: 0.00191 +2024-11-23 00:08:31.334378: train_loss -0.8249 +2024-11-23 00:08:31.334584: val_loss -0.783 +2024-11-23 00:08:31.334666: Pseudo dice [0.859] +2024-11-23 00:08:31.334739: Epoch time: 17.99 s +2024-11-23 00:08:32.245953: +2024-11-23 00:08:32.246227: Epoch 6732 +2024-11-23 00:08:32.246342: Current learning rate: 0.00191 +2024-11-23 00:08:50.962508: train_loss -0.8171 +2024-11-23 00:08:50.962729: val_loss -0.7943 +2024-11-23 00:08:50.962813: Pseudo dice [0.8534] +2024-11-23 00:08:50.962912: Epoch time: 18.72 s +2024-11-23 00:08:52.017198: +2024-11-23 00:08:52.017425: Epoch 6733 +2024-11-23 00:08:52.017551: Current learning rate: 0.0019 +2024-11-23 00:09:10.734438: train_loss -0.8144 +2024-11-23 00:09:10.734664: val_loss -0.7414 +2024-11-23 00:09:10.734738: Pseudo dice [0.8476] +2024-11-23 00:09:10.734819: Epoch time: 18.72 s +2024-11-23 00:09:11.625637: +2024-11-23 00:09:11.625849: Epoch 6734 +2024-11-23 00:09:11.625960: Current learning rate: 0.0019 +2024-11-23 00:09:29.412020: train_loss -0.8226 +2024-11-23 00:09:29.412247: val_loss -0.7649 +2024-11-23 00:09:29.412325: Pseudo dice [0.8406] +2024-11-23 00:09:29.412400: Epoch time: 17.79 s +2024-11-23 00:09:30.300408: +2024-11-23 00:09:30.300646: Epoch 6735 +2024-11-23 00:09:30.300762: Current learning rate: 0.0019 +2024-11-23 00:09:48.642179: train_loss -0.8145 +2024-11-23 00:09:48.642393: val_loss -0.7906 +2024-11-23 00:09:48.642471: Pseudo dice [0.8438] +2024-11-23 00:09:48.642555: Epoch time: 18.34 s +2024-11-23 00:09:49.530667: +2024-11-23 00:09:49.530866: Epoch 6736 +2024-11-23 00:09:49.530974: Current learning rate: 0.0019 +2024-11-23 00:10:06.845710: train_loss -0.8145 +2024-11-23 00:10:06.845988: val_loss -0.7802 +2024-11-23 00:10:06.846079: Pseudo dice [0.8561] +2024-11-23 00:10:06.846156: Epoch time: 17.32 s +2024-11-23 00:10:07.826686: +2024-11-23 00:10:07.826905: Epoch 6737 +2024-11-23 00:10:07.827026: Current learning rate: 0.0019 +2024-11-23 00:10:25.089334: train_loss -0.8156 +2024-11-23 00:10:25.089613: val_loss -0.7845 +2024-11-23 00:10:25.089705: Pseudo dice [0.8562] +2024-11-23 00:10:25.089794: Epoch time: 17.26 s +2024-11-23 00:10:25.985381: +2024-11-23 00:10:25.985607: Epoch 6738 +2024-11-23 00:10:25.985746: Current learning rate: 0.0019 +2024-11-23 00:10:44.141864: train_loss -0.8106 +2024-11-23 00:10:44.142077: val_loss -0.7527 +2024-11-23 00:10:44.142154: Pseudo dice [0.8534] +2024-11-23 00:10:44.142228: Epoch time: 18.16 s +2024-11-23 00:10:45.034148: +2024-11-23 00:10:45.034360: Epoch 6739 +2024-11-23 00:10:45.034489: Current learning rate: 0.0019 +2024-11-23 00:11:03.958123: train_loss -0.8161 +2024-11-23 00:11:03.958329: val_loss -0.7703 +2024-11-23 00:11:03.958407: Pseudo dice [0.8524] +2024-11-23 00:11:03.958483: Epoch time: 18.92 s +2024-11-23 00:11:05.332085: +2024-11-23 00:11:05.332357: Epoch 6740 +2024-11-23 00:11:05.332471: Current learning rate: 0.00189 +2024-11-23 00:11:22.985190: train_loss -0.8115 +2024-11-23 00:11:22.985466: val_loss -0.7517 +2024-11-23 00:11:22.985556: Pseudo dice [0.841] +2024-11-23 00:11:22.985642: Epoch time: 17.65 s +2024-11-23 00:11:23.884075: +2024-11-23 00:11:23.884317: Epoch 6741 +2024-11-23 00:11:23.884446: Current learning rate: 0.00189 +2024-11-23 00:11:43.682910: train_loss -0.8156 +2024-11-23 00:11:43.683137: val_loss -0.7906 +2024-11-23 00:11:43.683215: Pseudo dice [0.8529] +2024-11-23 00:11:43.683290: Epoch time: 19.8 s +2024-11-23 00:11:44.568920: +2024-11-23 00:11:44.569139: Epoch 6742 +2024-11-23 00:11:44.569280: Current learning rate: 0.00189 +2024-11-23 00:12:03.203545: train_loss -0.8079 +2024-11-23 00:12:03.203789: val_loss -0.7803 +2024-11-23 00:12:03.203875: Pseudo dice [0.857] +2024-11-23 00:12:03.203949: Epoch time: 18.64 s +2024-11-23 00:12:04.098243: +2024-11-23 00:12:04.098457: Epoch 6743 +2024-11-23 00:12:04.098572: Current learning rate: 0.00189 +2024-11-23 00:12:21.772367: train_loss -0.8204 +2024-11-23 00:12:21.772630: val_loss -0.782 +2024-11-23 00:12:21.772818: Pseudo dice [0.8581] +2024-11-23 00:12:21.773375: Epoch time: 17.67 s +2024-11-23 00:12:22.789939: +2024-11-23 00:12:22.790171: Epoch 6744 +2024-11-23 00:12:22.790280: Current learning rate: 0.00189 +2024-11-23 00:12:41.128841: train_loss -0.8126 +2024-11-23 00:12:41.129094: val_loss -0.7845 +2024-11-23 00:12:41.129254: Pseudo dice [0.8512] +2024-11-23 00:12:41.129347: Epoch time: 18.34 s +2024-11-23 00:12:42.120808: +2024-11-23 00:12:42.121021: Epoch 6745 +2024-11-23 00:12:42.121145: Current learning rate: 0.00189 +2024-11-23 00:13:00.632152: train_loss -0.8187 +2024-11-23 00:13:00.632370: val_loss -0.7635 +2024-11-23 00:13:00.632460: Pseudo dice [0.8508] +2024-11-23 00:13:00.632544: Epoch time: 18.51 s +2024-11-23 00:13:01.521121: +2024-11-23 00:13:01.521322: Epoch 6746 +2024-11-23 00:13:01.521437: Current learning rate: 0.00189 +2024-11-23 00:13:21.116895: train_loss -0.8172 +2024-11-23 00:13:21.117244: val_loss -0.7753 +2024-11-23 00:13:21.117332: Pseudo dice [0.8658] +2024-11-23 00:13:21.117415: Epoch time: 19.6 s +2024-11-23 00:13:22.025470: +2024-11-23 00:13:22.025668: Epoch 6747 +2024-11-23 00:13:22.025782: Current learning rate: 0.00189 +2024-11-23 00:13:40.312336: train_loss -0.8215 +2024-11-23 00:13:40.312610: val_loss -0.7933 +2024-11-23 00:13:40.312702: Pseudo dice [0.8652] +2024-11-23 00:13:40.312786: Epoch time: 18.29 s +2024-11-23 00:13:41.248172: +2024-11-23 00:13:41.248395: Epoch 6748 +2024-11-23 00:13:41.248522: Current learning rate: 0.00188 +2024-11-23 00:13:59.960631: train_loss -0.8157 +2024-11-23 00:13:59.960864: val_loss -0.7726 +2024-11-23 00:13:59.960945: Pseudo dice [0.8553] +2024-11-23 00:13:59.961186: Epoch time: 18.71 s +2024-11-23 00:14:00.847497: +2024-11-23 00:14:00.847705: Epoch 6749 +2024-11-23 00:14:00.847818: Current learning rate: 0.00188 +2024-11-23 00:14:18.753797: train_loss -0.8168 +2024-11-23 00:14:18.754117: val_loss -0.7584 +2024-11-23 00:14:18.754207: Pseudo dice [0.8547] +2024-11-23 00:14:18.754300: Epoch time: 17.91 s +2024-11-23 00:14:19.969675: +2024-11-23 00:14:19.969897: Epoch 6750 +2024-11-23 00:14:19.970013: Current learning rate: 0.00188 +2024-11-23 00:14:37.941588: train_loss -0.8149 +2024-11-23 00:14:37.941799: val_loss -0.7932 +2024-11-23 00:14:37.941876: Pseudo dice [0.8597] +2024-11-23 00:14:37.941968: Epoch time: 17.97 s +2024-11-23 00:14:39.251358: +2024-11-23 00:14:39.251565: Epoch 6751 +2024-11-23 00:14:39.251682: Current learning rate: 0.00188 +2024-11-23 00:14:57.786439: train_loss -0.8046 +2024-11-23 00:14:57.786688: val_loss -0.7697 +2024-11-23 00:14:57.786789: Pseudo dice [0.8385] +2024-11-23 00:14:57.786881: Epoch time: 18.54 s +2024-11-23 00:14:58.670474: +2024-11-23 00:14:58.670666: Epoch 6752 +2024-11-23 00:14:58.670778: Current learning rate: 0.00188 +2024-11-23 00:15:16.126838: train_loss -0.8223 +2024-11-23 00:15:16.127082: val_loss -0.7655 +2024-11-23 00:15:16.127168: Pseudo dice [0.8637] +2024-11-23 00:15:16.127246: Epoch time: 17.46 s +2024-11-23 00:15:17.162207: +2024-11-23 00:15:17.162424: Epoch 6753 +2024-11-23 00:15:17.162542: Current learning rate: 0.00188 +2024-11-23 00:15:35.684949: train_loss -0.8151 +2024-11-23 00:15:35.685200: val_loss -0.783 +2024-11-23 00:15:35.685281: Pseudo dice [0.869] +2024-11-23 00:15:35.685360: Epoch time: 18.52 s +2024-11-23 00:15:36.714914: +2024-11-23 00:15:36.715140: Epoch 6754 +2024-11-23 00:15:36.715259: Current learning rate: 0.00188 +2024-11-23 00:15:56.600402: train_loss -0.8093 +2024-11-23 00:15:56.600631: val_loss -0.7629 +2024-11-23 00:15:56.600714: Pseudo dice [0.8469] +2024-11-23 00:15:56.600801: Epoch time: 19.89 s +2024-11-23 00:15:57.499794: +2024-11-23 00:15:57.500030: Epoch 6755 +2024-11-23 00:15:57.500190: Current learning rate: 0.00187 +2024-11-23 00:16:15.854933: train_loss -0.815 +2024-11-23 00:16:15.855165: val_loss -0.7915 +2024-11-23 00:16:15.855252: Pseudo dice [0.8512] +2024-11-23 00:16:15.855345: Epoch time: 18.36 s +2024-11-23 00:16:16.856487: +2024-11-23 00:16:16.856686: Epoch 6756 +2024-11-23 00:16:16.856797: Current learning rate: 0.00187 +2024-11-23 00:16:35.352624: train_loss -0.8096 +2024-11-23 00:16:35.352889: val_loss -0.7817 +2024-11-23 00:16:35.352971: Pseudo dice [0.8607] +2024-11-23 00:16:35.353051: Epoch time: 18.5 s +2024-11-23 00:16:36.267731: +2024-11-23 00:16:36.267987: Epoch 6757 +2024-11-23 00:16:36.268128: Current learning rate: 0.00187 +2024-11-23 00:16:54.960773: train_loss -0.8106 +2024-11-23 00:16:54.960989: val_loss -0.7892 +2024-11-23 00:16:54.961076: Pseudo dice [0.8642] +2024-11-23 00:16:54.961159: Epoch time: 18.69 s +2024-11-23 00:16:55.848996: +2024-11-23 00:16:55.849191: Epoch 6758 +2024-11-23 00:16:55.849302: Current learning rate: 0.00187 +2024-11-23 00:17:14.276548: train_loss -0.8233 +2024-11-23 00:17:14.276847: val_loss -0.7753 +2024-11-23 00:17:14.276924: Pseudo dice [0.8443] +2024-11-23 00:17:14.277008: Epoch time: 18.43 s +2024-11-23 00:17:15.172775: +2024-11-23 00:17:15.172971: Epoch 6759 +2024-11-23 00:17:15.173083: Current learning rate: 0.00187 +2024-11-23 00:17:33.863494: train_loss -0.8121 +2024-11-23 00:17:33.863715: val_loss -0.7848 +2024-11-23 00:17:33.865973: Pseudo dice [0.8508] +2024-11-23 00:17:33.866102: Epoch time: 18.69 s +2024-11-23 00:17:34.919648: +2024-11-23 00:17:34.919896: Epoch 6760 +2024-11-23 00:17:34.920014: Current learning rate: 0.00187 +2024-11-23 00:17:53.556967: train_loss -0.8147 +2024-11-23 00:17:53.557270: val_loss -0.7382 +2024-11-23 00:17:53.557352: Pseudo dice [0.8426] +2024-11-23 00:17:53.557433: Epoch time: 18.64 s +2024-11-23 00:17:54.448816: +2024-11-23 00:17:54.449043: Epoch 6761 +2024-11-23 00:17:54.449163: Current learning rate: 0.00187 +2024-11-23 00:18:13.124460: train_loss -0.8208 +2024-11-23 00:18:13.124715: val_loss -0.7831 +2024-11-23 00:18:13.127050: Pseudo dice [0.8538] +2024-11-23 00:18:13.127171: Epoch time: 18.68 s +2024-11-23 00:18:14.436719: +2024-11-23 00:18:14.436929: Epoch 6762 +2024-11-23 00:18:14.437067: Current learning rate: 0.00186 +2024-11-23 00:18:32.430575: train_loss -0.8197 +2024-11-23 00:18:32.430881: val_loss -0.7905 +2024-11-23 00:18:32.430963: Pseudo dice [0.8549] +2024-11-23 00:18:32.431064: Epoch time: 17.99 s +2024-11-23 00:18:33.318098: +2024-11-23 00:18:33.318312: Epoch 6763 +2024-11-23 00:18:33.318424: Current learning rate: 0.00186 +2024-11-23 00:18:52.432025: train_loss -0.8151 +2024-11-23 00:18:52.432288: val_loss -0.777 +2024-11-23 00:18:52.432373: Pseudo dice [0.8331] +2024-11-23 00:18:52.432463: Epoch time: 19.11 s +2024-11-23 00:18:53.376517: +2024-11-23 00:18:53.376727: Epoch 6764 +2024-11-23 00:18:53.376864: Current learning rate: 0.00186 +2024-11-23 00:19:11.229211: train_loss -0.8165 +2024-11-23 00:19:11.229437: val_loss -0.7923 +2024-11-23 00:19:11.229516: Pseudo dice [0.8592] +2024-11-23 00:19:11.229605: Epoch time: 17.85 s +2024-11-23 00:19:12.128778: +2024-11-23 00:19:12.129013: Epoch 6765 +2024-11-23 00:19:12.129135: Current learning rate: 0.00186 +2024-11-23 00:19:30.744771: train_loss -0.8168 +2024-11-23 00:19:30.745042: val_loss -0.7755 +2024-11-23 00:19:30.747409: Pseudo dice [0.8608] +2024-11-23 00:19:30.747537: Epoch time: 18.62 s +2024-11-23 00:19:31.685070: +2024-11-23 00:19:31.685273: Epoch 6766 +2024-11-23 00:19:31.685398: Current learning rate: 0.00186 +2024-11-23 00:19:49.114947: train_loss -0.815 +2024-11-23 00:19:49.115174: val_loss -0.7942 +2024-11-23 00:19:49.115258: Pseudo dice [0.8667] +2024-11-23 00:19:49.115348: Epoch time: 17.43 s +2024-11-23 00:19:50.014931: +2024-11-23 00:19:50.015141: Epoch 6767 +2024-11-23 00:19:50.015286: Current learning rate: 0.00186 +2024-11-23 00:20:09.236863: train_loss -0.8102 +2024-11-23 00:20:09.237091: val_loss -0.7801 +2024-11-23 00:20:09.237174: Pseudo dice [0.8602] +2024-11-23 00:20:09.237249: Epoch time: 19.22 s +2024-11-23 00:20:10.149119: +2024-11-23 00:20:10.149346: Epoch 6768 +2024-11-23 00:20:10.149461: Current learning rate: 0.00186 +2024-11-23 00:20:28.660418: train_loss -0.8183 +2024-11-23 00:20:28.660646: val_loss -0.7621 +2024-11-23 00:20:28.660739: Pseudo dice [0.8579] +2024-11-23 00:20:28.660820: Epoch time: 18.51 s +2024-11-23 00:20:29.554447: +2024-11-23 00:20:29.554681: Epoch 6769 +2024-11-23 00:20:29.554850: Current learning rate: 0.00186 +2024-11-23 00:20:48.486006: train_loss -0.815 +2024-11-23 00:20:48.486239: val_loss -0.7754 +2024-11-23 00:20:48.486327: Pseudo dice [0.8595] +2024-11-23 00:20:48.486670: Epoch time: 18.93 s +2024-11-23 00:20:49.378046: +2024-11-23 00:20:49.378266: Epoch 6770 +2024-11-23 00:20:49.378387: Current learning rate: 0.00185 +2024-11-23 00:21:07.209073: train_loss -0.8216 +2024-11-23 00:21:07.209300: val_loss -0.802 +2024-11-23 00:21:07.209395: Pseudo dice [0.862] +2024-11-23 00:21:07.209477: Epoch time: 17.83 s +2024-11-23 00:21:08.094342: +2024-11-23 00:21:08.094540: Epoch 6771 +2024-11-23 00:21:08.094661: Current learning rate: 0.00185 +2024-11-23 00:21:26.727578: train_loss -0.8179 +2024-11-23 00:21:26.727822: val_loss -0.7845 +2024-11-23 00:21:26.727911: Pseudo dice [0.8574] +2024-11-23 00:21:26.727991: Epoch time: 18.63 s +2024-11-23 00:21:27.879072: +2024-11-23 00:21:27.879282: Epoch 6772 +2024-11-23 00:21:27.879402: Current learning rate: 0.00185 +2024-11-23 00:21:46.108972: train_loss -0.8165 +2024-11-23 00:21:46.109272: val_loss -0.774 +2024-11-23 00:21:46.109354: Pseudo dice [0.853] +2024-11-23 00:21:46.109438: Epoch time: 18.23 s +2024-11-23 00:21:47.397992: +2024-11-23 00:21:47.398207: Epoch 6773 +2024-11-23 00:21:47.398338: Current learning rate: 0.00185 +2024-11-23 00:22:05.841210: train_loss -0.818 +2024-11-23 00:22:05.841463: val_loss -0.7777 +2024-11-23 00:22:05.841554: Pseudo dice [0.8509] +2024-11-23 00:22:05.841640: Epoch time: 18.44 s +2024-11-23 00:22:06.742660: +2024-11-23 00:22:06.742893: Epoch 6774 +2024-11-23 00:22:06.743006: Current learning rate: 0.00185 +2024-11-23 00:22:25.157598: train_loss -0.8144 +2024-11-23 00:22:25.162445: val_loss -0.7856 +2024-11-23 00:22:25.162640: Pseudo dice [0.8593] +2024-11-23 00:22:25.162733: Epoch time: 18.42 s +2024-11-23 00:22:26.066716: +2024-11-23 00:22:26.066931: Epoch 6775 +2024-11-23 00:22:26.067056: Current learning rate: 0.00185 +2024-11-23 00:22:44.829925: train_loss -0.8134 +2024-11-23 00:22:44.830181: val_loss -0.7794 +2024-11-23 00:22:44.830260: Pseudo dice [0.8586] +2024-11-23 00:22:44.830337: Epoch time: 18.76 s +2024-11-23 00:22:45.737021: +2024-11-23 00:22:45.737242: Epoch 6776 +2024-11-23 00:22:45.737370: Current learning rate: 0.00185 +2024-11-23 00:23:04.826315: train_loss -0.8096 +2024-11-23 00:23:04.826593: val_loss -0.7686 +2024-11-23 00:23:04.826733: Pseudo dice [0.8555] +2024-11-23 00:23:04.826831: Epoch time: 19.09 s +2024-11-23 00:23:05.722820: +2024-11-23 00:23:05.723032: Epoch 6777 +2024-11-23 00:23:05.723151: Current learning rate: 0.00184 +2024-11-23 00:23:24.741460: train_loss -0.8197 +2024-11-23 00:23:24.741683: val_loss -0.788 +2024-11-23 00:23:24.741785: Pseudo dice [0.8616] +2024-11-23 00:23:24.741883: Epoch time: 19.02 s +2024-11-23 00:23:25.637353: +2024-11-23 00:23:25.637571: Epoch 6778 +2024-11-23 00:23:25.637690: Current learning rate: 0.00184 +2024-11-23 00:23:45.146880: train_loss -0.8123 +2024-11-23 00:23:45.147129: val_loss -0.787 +2024-11-23 00:23:45.147218: Pseudo dice [0.8478] +2024-11-23 00:23:45.147377: Epoch time: 19.51 s +2024-11-23 00:23:46.035268: +2024-11-23 00:23:46.035463: Epoch 6779 +2024-11-23 00:23:46.035578: Current learning rate: 0.00184 +2024-11-23 00:24:04.532926: train_loss -0.8216 +2024-11-23 00:24:04.533168: val_loss -0.7974 +2024-11-23 00:24:04.533260: Pseudo dice [0.8606] +2024-11-23 00:24:04.533354: Epoch time: 18.5 s +2024-11-23 00:24:05.426384: +2024-11-23 00:24:05.426576: Epoch 6780 +2024-11-23 00:24:05.426695: Current learning rate: 0.00184 +2024-11-23 00:24:24.252799: train_loss -0.8163 +2024-11-23 00:24:24.253040: val_loss -0.793 +2024-11-23 00:24:24.253123: Pseudo dice [0.8512] +2024-11-23 00:24:24.253209: Epoch time: 18.83 s +2024-11-23 00:24:25.146107: +2024-11-23 00:24:25.146302: Epoch 6781 +2024-11-23 00:24:25.146430: Current learning rate: 0.00184 +2024-11-23 00:24:43.851263: train_loss -0.8067 +2024-11-23 00:24:43.851495: val_loss -0.772 +2024-11-23 00:24:43.851576: Pseudo dice [0.8479] +2024-11-23 00:24:43.851664: Epoch time: 18.71 s +2024-11-23 00:24:44.736766: +2024-11-23 00:24:44.737003: Epoch 6782 +2024-11-23 00:24:44.737126: Current learning rate: 0.00184 +2024-11-23 00:25:03.321619: train_loss -0.8175 +2024-11-23 00:25:03.321837: val_loss -0.8035 +2024-11-23 00:25:03.321914: Pseudo dice [0.8499] +2024-11-23 00:25:03.321990: Epoch time: 18.59 s +2024-11-23 00:25:04.219425: +2024-11-23 00:25:04.219626: Epoch 6783 +2024-11-23 00:25:04.219738: Current learning rate: 0.00184 +2024-11-23 00:25:22.653452: train_loss -0.8132 +2024-11-23 00:25:22.653670: val_loss -0.7575 +2024-11-23 00:25:22.653746: Pseudo dice [0.8674] +2024-11-23 00:25:22.653821: Epoch time: 18.43 s +2024-11-23 00:25:24.031613: +2024-11-23 00:25:24.031866: Epoch 6784 +2024-11-23 00:25:24.031986: Current learning rate: 0.00184 +2024-11-23 00:25:41.709123: train_loss -0.8185 +2024-11-23 00:25:41.709343: val_loss -0.793 +2024-11-23 00:25:41.709421: Pseudo dice [0.8528] +2024-11-23 00:25:41.711651: Epoch time: 17.68 s +2024-11-23 00:25:42.750943: +2024-11-23 00:25:42.751171: Epoch 6785 +2024-11-23 00:25:42.751291: Current learning rate: 0.00183 +2024-11-23 00:26:01.121575: train_loss -0.8134 +2024-11-23 00:26:01.121799: val_loss -0.7741 +2024-11-23 00:26:01.121877: Pseudo dice [0.8567] +2024-11-23 00:26:01.121975: Epoch time: 18.37 s +2024-11-23 00:26:02.006280: +2024-11-23 00:26:02.006530: Epoch 6786 +2024-11-23 00:26:02.006656: Current learning rate: 0.00183 +2024-11-23 00:26:20.184427: train_loss -0.8183 +2024-11-23 00:26:20.184643: val_loss -0.7812 +2024-11-23 00:26:20.184722: Pseudo dice [0.8592] +2024-11-23 00:26:20.184812: Epoch time: 18.18 s +2024-11-23 00:26:21.171279: +2024-11-23 00:26:21.171489: Epoch 6787 +2024-11-23 00:26:21.171616: Current learning rate: 0.00183 +2024-11-23 00:26:39.461975: train_loss -0.8098 +2024-11-23 00:26:39.462264: val_loss -0.7982 +2024-11-23 00:26:39.462351: Pseudo dice [0.8707] +2024-11-23 00:26:39.462442: Epoch time: 18.29 s +2024-11-23 00:26:40.361817: +2024-11-23 00:26:40.362020: Epoch 6788 +2024-11-23 00:26:40.362175: Current learning rate: 0.00183 +2024-11-23 00:26:58.820245: train_loss -0.8217 +2024-11-23 00:26:58.820503: val_loss -0.7921 +2024-11-23 00:26:58.820599: Pseudo dice [0.8603] +2024-11-23 00:26:58.820698: Epoch time: 18.46 s +2024-11-23 00:26:59.717443: +2024-11-23 00:26:59.717701: Epoch 6789 +2024-11-23 00:26:59.717840: Current learning rate: 0.00183 +2024-11-23 00:27:18.307412: train_loss -0.8116 +2024-11-23 00:27:18.307624: val_loss -0.784 +2024-11-23 00:27:18.307706: Pseudo dice [0.8615] +2024-11-23 00:27:18.307782: Epoch time: 18.59 s +2024-11-23 00:27:19.203159: +2024-11-23 00:27:19.203372: Epoch 6790 +2024-11-23 00:27:19.203486: Current learning rate: 0.00183 +2024-11-23 00:27:36.956107: train_loss -0.819 +2024-11-23 00:27:36.956404: val_loss -0.7812 +2024-11-23 00:27:36.956488: Pseudo dice [0.8618] +2024-11-23 00:27:36.956564: Epoch time: 17.75 s +2024-11-23 00:27:37.852633: +2024-11-23 00:27:37.852843: Epoch 6791 +2024-11-23 00:27:37.852975: Current learning rate: 0.00183 +2024-11-23 00:27:57.106971: train_loss -0.8148 +2024-11-23 00:27:57.107229: val_loss -0.8085 +2024-11-23 00:27:57.107320: Pseudo dice [0.8595] +2024-11-23 00:27:57.107408: Epoch time: 19.26 s +2024-11-23 00:27:58.001348: +2024-11-23 00:27:58.001554: Epoch 6792 +2024-11-23 00:27:58.001671: Current learning rate: 0.00182 +2024-11-23 00:28:17.042579: train_loss -0.8217 +2024-11-23 00:28:17.042786: val_loss -0.7817 +2024-11-23 00:28:17.042868: Pseudo dice [0.8686] +2024-11-23 00:28:17.042946: Epoch time: 19.04 s +2024-11-23 00:28:17.933715: +2024-11-23 00:28:17.933949: Epoch 6793 +2024-11-23 00:28:17.934074: Current learning rate: 0.00182 +2024-11-23 00:28:35.508647: train_loss -0.8128 +2024-11-23 00:28:35.508864: val_loss -0.7804 +2024-11-23 00:28:35.508942: Pseudo dice [0.866] +2024-11-23 00:28:35.509019: Epoch time: 17.58 s +2024-11-23 00:28:36.404066: +2024-11-23 00:28:36.404263: Epoch 6794 +2024-11-23 00:28:36.404385: Current learning rate: 0.00182 +2024-11-23 00:28:54.387275: train_loss -0.8168 +2024-11-23 00:28:54.387484: val_loss -0.7912 +2024-11-23 00:28:54.387570: Pseudo dice [0.8589] +2024-11-23 00:28:54.387663: Epoch time: 17.98 s +2024-11-23 00:28:55.659389: +2024-11-23 00:28:55.659591: Epoch 6795 +2024-11-23 00:28:55.659707: Current learning rate: 0.00182 +2024-11-23 00:29:13.299621: train_loss -0.8093 +2024-11-23 00:29:13.303164: val_loss -0.7775 +2024-11-23 00:29:13.303558: Pseudo dice [0.8629] +2024-11-23 00:29:13.303660: Epoch time: 17.64 s +2024-11-23 00:29:14.243378: +2024-11-23 00:29:14.243589: Epoch 6796 +2024-11-23 00:29:14.243716: Current learning rate: 0.00182 +2024-11-23 00:29:32.160359: train_loss -0.7959 +2024-11-23 00:29:32.160677: val_loss -0.7806 +2024-11-23 00:29:32.160770: Pseudo dice [0.8538] +2024-11-23 00:29:32.160851: Epoch time: 17.92 s +2024-11-23 00:29:33.051722: +2024-11-23 00:29:33.051940: Epoch 6797 +2024-11-23 00:29:33.052054: Current learning rate: 0.00182 +2024-11-23 00:29:52.327462: train_loss -0.822 +2024-11-23 00:29:52.327702: val_loss -0.7559 +2024-11-23 00:29:52.327796: Pseudo dice [0.8555] +2024-11-23 00:29:52.327894: Epoch time: 19.28 s +2024-11-23 00:29:53.218512: +2024-11-23 00:29:53.218717: Epoch 6798 +2024-11-23 00:29:53.218836: Current learning rate: 0.00182 +2024-11-23 00:30:11.228823: train_loss -0.814 +2024-11-23 00:30:11.229109: val_loss -0.7711 +2024-11-23 00:30:11.229192: Pseudo dice [0.8485] +2024-11-23 00:30:11.229279: Epoch time: 18.01 s +2024-11-23 00:30:12.118524: +2024-11-23 00:30:12.118727: Epoch 6799 +2024-11-23 00:30:12.118854: Current learning rate: 0.00181 +2024-11-23 00:30:30.258966: train_loss -0.8168 +2024-11-23 00:30:30.259236: val_loss -0.7973 +2024-11-23 00:30:30.259324: Pseudo dice [0.8556] +2024-11-23 00:30:30.259412: Epoch time: 18.14 s +2024-11-23 00:30:31.478367: +2024-11-23 00:30:31.478569: Epoch 6800 +2024-11-23 00:30:31.478689: Current learning rate: 0.00181 +2024-11-23 00:30:49.350448: train_loss -0.8132 +2024-11-23 00:30:49.350678: val_loss -0.774 +2024-11-23 00:30:49.350765: Pseudo dice [0.8551] +2024-11-23 00:30:49.350848: Epoch time: 17.87 s +2024-11-23 00:30:50.246107: +2024-11-23 00:30:50.246311: Epoch 6801 +2024-11-23 00:30:50.246428: Current learning rate: 0.00181 +2024-11-23 00:31:09.123473: train_loss -0.8157 +2024-11-23 00:31:09.123692: val_loss -0.7902 +2024-11-23 00:31:09.123775: Pseudo dice [0.8637] +2024-11-23 00:31:09.123852: Epoch time: 18.88 s +2024-11-23 00:31:10.008220: +2024-11-23 00:31:10.008423: Epoch 6802 +2024-11-23 00:31:10.008542: Current learning rate: 0.00181 +2024-11-23 00:31:26.739910: train_loss -0.8201 +2024-11-23 00:31:26.740157: val_loss -0.7874 +2024-11-23 00:31:26.740245: Pseudo dice [0.861] +2024-11-23 00:31:26.740334: Epoch time: 16.73 s +2024-11-23 00:31:27.644410: +2024-11-23 00:31:27.644621: Epoch 6803 +2024-11-23 00:31:27.644763: Current learning rate: 0.00181 +2024-11-23 00:31:46.597138: train_loss -0.8134 +2024-11-23 00:31:46.597366: val_loss -0.7985 +2024-11-23 00:31:46.597475: Pseudo dice [0.857] +2024-11-23 00:31:46.597558: Epoch time: 18.95 s +2024-11-23 00:31:47.482448: +2024-11-23 00:31:47.482684: Epoch 6804 +2024-11-23 00:31:47.482794: Current learning rate: 0.00181 +2024-11-23 00:32:06.137484: train_loss -0.8044 +2024-11-23 00:32:06.137720: val_loss -0.7754 +2024-11-23 00:32:06.137818: Pseudo dice [0.8694] +2024-11-23 00:32:06.137904: Epoch time: 18.66 s +2024-11-23 00:32:07.025395: +2024-11-23 00:32:07.025623: Epoch 6805 +2024-11-23 00:32:07.025739: Current learning rate: 0.00181 +2024-11-23 00:32:24.305974: train_loss -0.8149 +2024-11-23 00:32:24.306216: val_loss -0.778 +2024-11-23 00:32:24.306317: Pseudo dice [0.8668] +2024-11-23 00:32:24.306423: Epoch time: 17.28 s +2024-11-23 00:32:25.712095: +2024-11-23 00:32:25.712302: Epoch 6806 +2024-11-23 00:32:25.712431: Current learning rate: 0.00181 +2024-11-23 00:32:43.970644: train_loss -0.8153 +2024-11-23 00:32:43.970873: val_loss -0.7707 +2024-11-23 00:32:43.970950: Pseudo dice [0.8547] +2024-11-23 00:32:43.971029: Epoch time: 18.26 s +2024-11-23 00:32:44.856118: +2024-11-23 00:32:44.856325: Epoch 6807 +2024-11-23 00:32:44.856440: Current learning rate: 0.0018 +2024-11-23 00:33:02.883973: train_loss -0.8144 +2024-11-23 00:33:02.884181: val_loss -0.7585 +2024-11-23 00:33:02.884262: Pseudo dice [0.8488] +2024-11-23 00:33:02.884341: Epoch time: 18.03 s +2024-11-23 00:33:03.768834: +2024-11-23 00:33:03.769056: Epoch 6808 +2024-11-23 00:33:03.769173: Current learning rate: 0.0018 +2024-11-23 00:33:21.753910: train_loss -0.8096 +2024-11-23 00:33:21.754119: val_loss -0.7857 +2024-11-23 00:33:21.754202: Pseudo dice [0.8519] +2024-11-23 00:33:21.754292: Epoch time: 17.99 s +2024-11-23 00:33:22.629071: +2024-11-23 00:33:22.629274: Epoch 6809 +2024-11-23 00:33:22.629400: Current learning rate: 0.0018 +2024-11-23 00:33:40.453150: train_loss -0.8144 +2024-11-23 00:33:40.453394: val_loss -0.7759 +2024-11-23 00:33:40.453478: Pseudo dice [0.8593] +2024-11-23 00:33:40.453585: Epoch time: 17.82 s +2024-11-23 00:33:41.332899: +2024-11-23 00:33:41.333097: Epoch 6810 +2024-11-23 00:33:41.333247: Current learning rate: 0.0018 +2024-11-23 00:33:59.764756: train_loss -0.8136 +2024-11-23 00:33:59.764981: val_loss -0.7563 +2024-11-23 00:33:59.765068: Pseudo dice [0.8466] +2024-11-23 00:33:59.765151: Epoch time: 18.43 s +2024-11-23 00:34:00.664447: +2024-11-23 00:34:00.664665: Epoch 6811 +2024-11-23 00:34:00.664792: Current learning rate: 0.0018 +2024-11-23 00:34:19.303568: train_loss -0.809 +2024-11-23 00:34:19.303823: val_loss -0.7872 +2024-11-23 00:34:19.303922: Pseudo dice [0.8637] +2024-11-23 00:34:19.304005: Epoch time: 18.64 s +2024-11-23 00:34:20.189000: +2024-11-23 00:34:20.189224: Epoch 6812 +2024-11-23 00:34:20.189327: Current learning rate: 0.0018 +2024-11-23 00:34:38.707557: train_loss -0.8145 +2024-11-23 00:34:38.707767: val_loss -0.7791 +2024-11-23 00:34:38.707850: Pseudo dice [0.8602] +2024-11-23 00:34:38.707942: Epoch time: 18.52 s +2024-11-23 00:34:39.705156: +2024-11-23 00:34:39.705371: Epoch 6813 +2024-11-23 00:34:39.705486: Current learning rate: 0.0018 +2024-11-23 00:34:58.159043: train_loss -0.8127 +2024-11-23 00:34:58.159345: val_loss -0.7832 +2024-11-23 00:34:58.159425: Pseudo dice [0.8388] +2024-11-23 00:34:58.159504: Epoch time: 18.45 s +2024-11-23 00:34:59.030991: +2024-11-23 00:34:59.031200: Epoch 6814 +2024-11-23 00:34:59.031316: Current learning rate: 0.00179 +2024-11-23 00:35:16.770168: train_loss -0.8166 +2024-11-23 00:35:16.770374: val_loss -0.8186 +2024-11-23 00:35:16.770458: Pseudo dice [0.871] +2024-11-23 00:35:16.770619: Epoch time: 17.74 s +2024-11-23 00:35:17.639635: +2024-11-23 00:35:17.639848: Epoch 6815 +2024-11-23 00:35:17.639962: Current learning rate: 0.00179 +2024-11-23 00:35:35.591098: train_loss -0.8138 +2024-11-23 00:35:35.591330: val_loss -0.7845 +2024-11-23 00:35:35.591416: Pseudo dice [0.8552] +2024-11-23 00:35:35.591495: Epoch time: 17.95 s +2024-11-23 00:35:36.648892: +2024-11-23 00:35:36.649111: Epoch 6816 +2024-11-23 00:35:36.649231: Current learning rate: 0.00179 +2024-11-23 00:35:55.001414: train_loss -0.8093 +2024-11-23 00:35:55.001664: val_loss -0.7621 +2024-11-23 00:35:55.001744: Pseudo dice [0.8681] +2024-11-23 00:35:55.001833: Epoch time: 18.35 s +2024-11-23 00:35:56.337357: +2024-11-23 00:35:56.337558: Epoch 6817 +2024-11-23 00:35:56.337669: Current learning rate: 0.00179 +2024-11-23 00:36:14.353598: train_loss -0.8231 +2024-11-23 00:36:14.353844: val_loss -0.7695 +2024-11-23 00:36:14.353923: Pseudo dice [0.8576] +2024-11-23 00:36:14.354000: Epoch time: 18.02 s +2024-11-23 00:36:15.647529: +2024-11-23 00:36:15.647757: Epoch 6818 +2024-11-23 00:36:15.647877: Current learning rate: 0.00179 +2024-11-23 00:36:34.843327: train_loss -0.8184 +2024-11-23 00:36:34.843563: val_loss -0.7778 +2024-11-23 00:36:34.843640: Pseudo dice [0.8492] +2024-11-23 00:36:34.843717: Epoch time: 19.2 s +2024-11-23 00:36:35.955423: +2024-11-23 00:36:35.955648: Epoch 6819 +2024-11-23 00:36:35.955756: Current learning rate: 0.00179 +2024-11-23 00:36:56.118190: train_loss -0.8088 +2024-11-23 00:36:56.118421: val_loss -0.7741 +2024-11-23 00:36:56.118509: Pseudo dice [0.8631] +2024-11-23 00:36:56.118598: Epoch time: 20.16 s +2024-11-23 00:36:57.002557: +2024-11-23 00:36:57.002747: Epoch 6820 +2024-11-23 00:36:57.002860: Current learning rate: 0.00179 +2024-11-23 00:37:15.978154: train_loss -0.8177 +2024-11-23 00:37:15.978384: val_loss -0.7643 +2024-11-23 00:37:15.978461: Pseudo dice [0.856] +2024-11-23 00:37:15.978542: Epoch time: 18.98 s +2024-11-23 00:37:16.865798: +2024-11-23 00:37:16.866038: Epoch 6821 +2024-11-23 00:37:16.866153: Current learning rate: 0.00178 +2024-11-23 00:37:34.280243: train_loss -0.8188 +2024-11-23 00:37:34.280448: val_loss -0.7825 +2024-11-23 00:37:34.280764: Pseudo dice [0.8574] +2024-11-23 00:37:34.280863: Epoch time: 17.42 s +2024-11-23 00:37:35.178225: +2024-11-23 00:37:35.178424: Epoch 6822 +2024-11-23 00:37:35.178547: Current learning rate: 0.00178 +2024-11-23 00:37:52.037381: train_loss -0.8178 +2024-11-23 00:37:52.037612: val_loss -0.7891 +2024-11-23 00:37:52.037697: Pseudo dice [0.873] +2024-11-23 00:37:52.037777: Epoch time: 16.86 s +2024-11-23 00:37:52.929784: +2024-11-23 00:37:52.930008: Epoch 6823 +2024-11-23 00:37:52.930146: Current learning rate: 0.00178 +2024-11-23 00:38:10.695486: train_loss -0.8178 +2024-11-23 00:38:10.695708: val_loss -0.7876 +2024-11-23 00:38:10.695796: Pseudo dice [0.8544] +2024-11-23 00:38:10.695875: Epoch time: 17.77 s +2024-11-23 00:38:11.607188: +2024-11-23 00:38:11.607387: Epoch 6824 +2024-11-23 00:38:11.607502: Current learning rate: 0.00178 +2024-11-23 00:38:29.127593: train_loss -0.8244 +2024-11-23 00:38:29.127831: val_loss -0.8045 +2024-11-23 00:38:29.127909: Pseudo dice [0.8672] +2024-11-23 00:38:29.128001: Epoch time: 17.52 s +2024-11-23 00:38:30.010204: +2024-11-23 00:38:30.010388: Epoch 6825 +2024-11-23 00:38:30.010501: Current learning rate: 0.00178 +2024-11-23 00:38:49.815093: train_loss -0.8096 +2024-11-23 00:38:49.815321: val_loss -0.7597 +2024-11-23 00:38:49.815402: Pseudo dice [0.8481] +2024-11-23 00:38:49.815480: Epoch time: 19.81 s +2024-11-23 00:38:50.741481: +2024-11-23 00:38:50.741659: Epoch 6826 +2024-11-23 00:38:50.741772: Current learning rate: 0.00178 +2024-11-23 00:39:09.719723: train_loss -0.8154 +2024-11-23 00:39:09.719949: val_loss -0.7818 +2024-11-23 00:39:09.720036: Pseudo dice [0.8639] +2024-11-23 00:39:09.720122: Epoch time: 18.98 s +2024-11-23 00:39:10.603733: +2024-11-23 00:39:10.603929: Epoch 6827 +2024-11-23 00:39:10.604036: Current learning rate: 0.00178 +2024-11-23 00:39:28.950829: train_loss -0.8134 +2024-11-23 00:39:28.951045: val_loss -0.7428 +2024-11-23 00:39:28.951191: Pseudo dice [0.8437] +2024-11-23 00:39:28.951272: Epoch time: 18.35 s +2024-11-23 00:39:30.296985: +2024-11-23 00:39:30.297242: Epoch 6828 +2024-11-23 00:39:30.297402: Current learning rate: 0.00178 +2024-11-23 00:39:48.969490: train_loss -0.8143 +2024-11-23 00:39:48.969727: val_loss -0.7829 +2024-11-23 00:39:48.969817: Pseudo dice [0.8579] +2024-11-23 00:39:48.969908: Epoch time: 18.67 s +2024-11-23 00:39:49.902520: +2024-11-23 00:39:49.902725: Epoch 6829 +2024-11-23 00:39:49.902835: Current learning rate: 0.00177 +2024-11-23 00:40:08.498725: train_loss -0.8183 +2024-11-23 00:40:08.498958: val_loss -0.7891 +2024-11-23 00:40:08.499048: Pseudo dice [0.8429] +2024-11-23 00:40:08.499148: Epoch time: 18.6 s +2024-11-23 00:40:09.376777: +2024-11-23 00:40:09.376986: Epoch 6830 +2024-11-23 00:40:09.377122: Current learning rate: 0.00177 +2024-11-23 00:40:27.528543: train_loss -0.8203 +2024-11-23 00:40:27.539138: val_loss -0.7951 +2024-11-23 00:40:27.539277: Pseudo dice [0.866] +2024-11-23 00:40:27.539365: Epoch time: 18.15 s +2024-11-23 00:40:28.630810: +2024-11-23 00:40:28.631019: Epoch 6831 +2024-11-23 00:40:28.631140: Current learning rate: 0.00177 +2024-11-23 00:40:46.928718: train_loss -0.8104 +2024-11-23 00:40:46.928957: val_loss -0.7893 +2024-11-23 00:40:46.930511: Pseudo dice [0.8595] +2024-11-23 00:40:46.930757: Epoch time: 18.3 s +2024-11-23 00:40:47.849202: +2024-11-23 00:40:47.849440: Epoch 6832 +2024-11-23 00:40:47.849575: Current learning rate: 0.00177 +2024-11-23 00:41:07.527555: train_loss -0.8194 +2024-11-23 00:41:07.527763: val_loss -0.7759 +2024-11-23 00:41:07.527839: Pseudo dice [0.8603] +2024-11-23 00:41:07.527927: Epoch time: 19.68 s +2024-11-23 00:41:08.404488: +2024-11-23 00:41:08.404696: Epoch 6833 +2024-11-23 00:41:08.404814: Current learning rate: 0.00177 +2024-11-23 00:41:26.720086: train_loss -0.8259 +2024-11-23 00:41:26.720307: val_loss -0.777 +2024-11-23 00:41:26.720392: Pseudo dice [0.8525] +2024-11-23 00:41:26.720479: Epoch time: 18.32 s +2024-11-23 00:41:27.594442: +2024-11-23 00:41:27.594636: Epoch 6834 +2024-11-23 00:41:27.594744: Current learning rate: 0.00177 +2024-11-23 00:41:45.755121: train_loss -0.819 +2024-11-23 00:41:45.755376: val_loss -0.7919 +2024-11-23 00:41:45.755465: Pseudo dice [0.8539] +2024-11-23 00:41:45.755542: Epoch time: 18.16 s +2024-11-23 00:41:46.674703: +2024-11-23 00:41:46.674916: Epoch 6835 +2024-11-23 00:41:46.675039: Current learning rate: 0.00177 +2024-11-23 00:42:05.233123: train_loss -0.8263 +2024-11-23 00:42:05.233377: val_loss -0.7828 +2024-11-23 00:42:05.233460: Pseudo dice [0.8626] +2024-11-23 00:42:05.233546: Epoch time: 18.56 s +2024-11-23 00:42:06.124552: +2024-11-23 00:42:06.124752: Epoch 6836 +2024-11-23 00:42:06.124863: Current learning rate: 0.00176 +2024-11-23 00:42:24.843649: train_loss -0.824 +2024-11-23 00:42:24.843847: val_loss -0.7741 +2024-11-23 00:42:24.843934: Pseudo dice [0.8643] +2024-11-23 00:42:24.844011: Epoch time: 18.72 s +2024-11-23 00:42:25.740794: +2024-11-23 00:42:25.741049: Epoch 6837 +2024-11-23 00:42:25.741167: Current learning rate: 0.00176 +2024-11-23 00:42:44.188351: train_loss -0.8235 +2024-11-23 00:42:44.188574: val_loss -0.7944 +2024-11-23 00:42:44.190841: Pseudo dice [0.8602] +2024-11-23 00:42:44.190972: Epoch time: 18.45 s +2024-11-23 00:42:45.167791: +2024-11-23 00:42:45.167987: Epoch 6838 +2024-11-23 00:42:45.168102: Current learning rate: 0.00176 +2024-11-23 00:43:03.250362: train_loss -0.8166 +2024-11-23 00:43:03.250582: val_loss -0.7839 +2024-11-23 00:43:03.250670: Pseudo dice [0.8669] +2024-11-23 00:43:03.250761: Epoch time: 18.08 s +2024-11-23 00:43:04.536828: +2024-11-23 00:43:04.537034: Epoch 6839 +2024-11-23 00:43:04.537160: Current learning rate: 0.00176 +2024-11-23 00:43:23.368318: train_loss -0.817 +2024-11-23 00:43:23.368569: val_loss -0.8031 +2024-11-23 00:43:23.368659: Pseudo dice [0.8586] +2024-11-23 00:43:23.370979: Epoch time: 18.83 s +2024-11-23 00:43:24.369268: +2024-11-23 00:43:24.369474: Epoch 6840 +2024-11-23 00:43:24.369593: Current learning rate: 0.00176 +2024-11-23 00:43:43.478842: train_loss -0.8179 +2024-11-23 00:43:43.479084: val_loss -0.7855 +2024-11-23 00:43:43.479175: Pseudo dice [0.8552] +2024-11-23 00:43:43.479254: Epoch time: 19.11 s +2024-11-23 00:43:44.622368: +2024-11-23 00:43:44.622574: Epoch 6841 +2024-11-23 00:43:44.622684: Current learning rate: 0.00176 +2024-11-23 00:44:02.359970: train_loss -0.8185 +2024-11-23 00:44:02.360206: val_loss -0.8088 +2024-11-23 00:44:02.360286: Pseudo dice [0.8578] +2024-11-23 00:44:02.360374: Epoch time: 17.74 s +2024-11-23 00:44:03.267961: +2024-11-23 00:44:03.268189: Epoch 6842 +2024-11-23 00:44:03.268298: Current learning rate: 0.00176 +2024-11-23 00:44:20.932355: train_loss -0.8187 +2024-11-23 00:44:20.932594: val_loss -0.7861 +2024-11-23 00:44:20.932680: Pseudo dice [0.8542] +2024-11-23 00:44:20.932768: Epoch time: 17.67 s +2024-11-23 00:44:21.926662: +2024-11-23 00:44:21.926924: Epoch 6843 +2024-11-23 00:44:21.927092: Current learning rate: 0.00175 +2024-11-23 00:44:39.845206: train_loss -0.8234 +2024-11-23 00:44:39.845449: val_loss -0.7522 +2024-11-23 00:44:39.845540: Pseudo dice [0.8541] +2024-11-23 00:44:39.845625: Epoch time: 17.92 s +2024-11-23 00:44:40.767576: +2024-11-23 00:44:40.767810: Epoch 6844 +2024-11-23 00:44:40.767922: Current learning rate: 0.00175 +2024-11-23 00:44:58.960312: train_loss -0.8285 +2024-11-23 00:44:58.960556: val_loss -0.7696 +2024-11-23 00:44:58.960696: Pseudo dice [0.8547] +2024-11-23 00:44:58.960774: Epoch time: 18.19 s +2024-11-23 00:45:00.106316: +2024-11-23 00:45:00.106528: Epoch 6845 +2024-11-23 00:45:00.106639: Current learning rate: 0.00175 +2024-11-23 00:45:18.563861: train_loss -0.8187 +2024-11-23 00:45:18.564087: val_loss -0.7779 +2024-11-23 00:45:18.564170: Pseudo dice [0.8681] +2024-11-23 00:45:18.564257: Epoch time: 18.46 s +2024-11-23 00:45:19.454966: +2024-11-23 00:45:19.455240: Epoch 6846 +2024-11-23 00:45:19.455365: Current learning rate: 0.00175 +2024-11-23 00:45:38.195206: train_loss -0.8208 +2024-11-23 00:45:38.195455: val_loss -0.7834 +2024-11-23 00:45:38.195543: Pseudo dice [0.8632] +2024-11-23 00:45:38.195631: Epoch time: 18.74 s +2024-11-23 00:45:39.086618: +2024-11-23 00:45:39.086803: Epoch 6847 +2024-11-23 00:45:39.086920: Current learning rate: 0.00175 +2024-11-23 00:45:56.262848: train_loss -0.8205 +2024-11-23 00:45:56.263280: val_loss -0.7756 +2024-11-23 00:45:56.263376: Pseudo dice [0.8603] +2024-11-23 00:45:56.263451: Epoch time: 17.18 s +2024-11-23 00:45:57.148634: +2024-11-23 00:45:57.148841: Epoch 6848 +2024-11-23 00:45:57.148957: Current learning rate: 0.00175 +2024-11-23 00:46:16.757199: train_loss -0.8152 +2024-11-23 00:46:16.757412: val_loss -0.78 +2024-11-23 00:46:16.757508: Pseudo dice [0.8529] +2024-11-23 00:46:16.757625: Epoch time: 19.61 s +2024-11-23 00:46:17.642556: +2024-11-23 00:46:17.642760: Epoch 6849 +2024-11-23 00:46:17.642883: Current learning rate: 0.00175 +2024-11-23 00:46:35.690191: train_loss -0.8148 +2024-11-23 00:46:35.695634: val_loss -0.7639 +2024-11-23 00:46:35.695734: Pseudo dice [0.8376] +2024-11-23 00:46:35.695826: Epoch time: 18.05 s +2024-11-23 00:46:37.409468: +2024-11-23 00:46:37.409694: Epoch 6850 +2024-11-23 00:46:37.409817: Current learning rate: 0.00175 +2024-11-23 00:46:54.992255: train_loss -0.8183 +2024-11-23 00:46:54.992492: val_loss -0.7799 +2024-11-23 00:46:54.992599: Pseudo dice [0.8626] +2024-11-23 00:46:54.994883: Epoch time: 17.58 s +2024-11-23 00:46:55.889864: +2024-11-23 00:46:55.890069: Epoch 6851 +2024-11-23 00:46:55.890194: Current learning rate: 0.00174 +2024-11-23 00:47:14.398195: train_loss -0.8253 +2024-11-23 00:47:14.398441: val_loss -0.7627 +2024-11-23 00:47:14.398519: Pseudo dice [0.8544] +2024-11-23 00:47:14.398599: Epoch time: 18.51 s +2024-11-23 00:47:15.303995: +2024-11-23 00:47:15.304234: Epoch 6852 +2024-11-23 00:47:15.304348: Current learning rate: 0.00174 +2024-11-23 00:47:33.293313: train_loss -0.8221 +2024-11-23 00:47:33.293559: val_loss -0.7748 +2024-11-23 00:47:33.293662: Pseudo dice [0.8573] +2024-11-23 00:47:33.298043: Epoch time: 17.99 s +2024-11-23 00:47:34.204861: +2024-11-23 00:47:34.205073: Epoch 6853 +2024-11-23 00:47:34.205193: Current learning rate: 0.00174 +2024-11-23 00:47:52.876213: train_loss -0.8148 +2024-11-23 00:47:52.876467: val_loss -0.766 +2024-11-23 00:47:52.876553: Pseudo dice [0.8556] +2024-11-23 00:47:52.876637: Epoch time: 18.67 s +2024-11-23 00:47:53.766025: +2024-11-23 00:47:53.766222: Epoch 6854 +2024-11-23 00:47:53.766342: Current learning rate: 0.00174 +2024-11-23 00:48:12.574831: train_loss -0.8105 +2024-11-23 00:48:12.575042: val_loss -0.7747 +2024-11-23 00:48:12.575128: Pseudo dice [0.8419] +2024-11-23 00:48:12.575215: Epoch time: 18.81 s +2024-11-23 00:48:13.549742: +2024-11-23 00:48:13.549933: Epoch 6855 +2024-11-23 00:48:13.550045: Current learning rate: 0.00174 +2024-11-23 00:48:31.688311: train_loss -0.8188 +2024-11-23 00:48:31.688554: val_loss -0.7607 +2024-11-23 00:48:31.688635: Pseudo dice [0.8531] +2024-11-23 00:48:31.688726: Epoch time: 18.14 s +2024-11-23 00:48:32.614356: +2024-11-23 00:48:32.614567: Epoch 6856 +2024-11-23 00:48:32.614692: Current learning rate: 0.00174 +2024-11-23 00:48:50.802113: train_loss -0.819 +2024-11-23 00:48:50.802415: val_loss -0.7633 +2024-11-23 00:48:50.802500: Pseudo dice [0.8365] +2024-11-23 00:48:50.802588: Epoch time: 18.19 s +2024-11-23 00:48:51.793547: +2024-11-23 00:48:51.793746: Epoch 6857 +2024-11-23 00:48:51.793861: Current learning rate: 0.00174 +2024-11-23 00:49:10.028014: train_loss -0.8203 +2024-11-23 00:49:10.028277: val_loss -0.7697 +2024-11-23 00:49:10.028361: Pseudo dice [0.8579] +2024-11-23 00:49:10.028449: Epoch time: 18.24 s +2024-11-23 00:49:10.915190: +2024-11-23 00:49:10.915388: Epoch 6858 +2024-11-23 00:49:10.915503: Current learning rate: 0.00173 +2024-11-23 00:49:30.356441: train_loss -0.8203 +2024-11-23 00:49:30.356669: val_loss -0.8001 +2024-11-23 00:49:30.356753: Pseudo dice [0.8581] +2024-11-23 00:49:30.356847: Epoch time: 19.44 s +2024-11-23 00:49:31.237091: +2024-11-23 00:49:31.237296: Epoch 6859 +2024-11-23 00:49:31.237422: Current learning rate: 0.00173 +2024-11-23 00:49:49.759077: train_loss -0.8164 +2024-11-23 00:49:49.759299: val_loss -0.7612 +2024-11-23 00:49:49.759377: Pseudo dice [0.8663] +2024-11-23 00:49:49.759465: Epoch time: 18.52 s +2024-11-23 00:49:50.643712: +2024-11-23 00:49:50.643921: Epoch 6860 +2024-11-23 00:49:50.644039: Current learning rate: 0.00173 +2024-11-23 00:50:09.882919: train_loss -0.8138 +2024-11-23 00:50:09.883187: val_loss -0.7733 +2024-11-23 00:50:09.883364: Pseudo dice [0.8666] +2024-11-23 00:50:09.883474: Epoch time: 19.24 s +2024-11-23 00:50:11.262217: +2024-11-23 00:50:11.262409: Epoch 6861 +2024-11-23 00:50:11.262519: Current learning rate: 0.00173 +2024-11-23 00:50:30.425668: train_loss -0.815 +2024-11-23 00:50:30.425979: val_loss -0.7771 +2024-11-23 00:50:30.426071: Pseudo dice [0.8692] +2024-11-23 00:50:30.426150: Epoch time: 19.16 s +2024-11-23 00:50:31.381514: +2024-11-23 00:50:31.381723: Epoch 6862 +2024-11-23 00:50:31.381852: Current learning rate: 0.00173 +2024-11-23 00:50:50.866652: train_loss -0.8175 +2024-11-23 00:50:50.866956: val_loss -0.7962 +2024-11-23 00:50:50.867043: Pseudo dice [0.8534] +2024-11-23 00:50:50.867128: Epoch time: 19.49 s +2024-11-23 00:50:51.753967: +2024-11-23 00:50:51.754193: Epoch 6863 +2024-11-23 00:50:51.754327: Current learning rate: 0.00173 +2024-11-23 00:51:11.377024: train_loss -0.8127 +2024-11-23 00:51:11.377263: val_loss -0.8022 +2024-11-23 00:51:11.377349: Pseudo dice [0.8661] +2024-11-23 00:51:11.377429: Epoch time: 19.62 s +2024-11-23 00:51:12.291842: +2024-11-23 00:51:12.292060: Epoch 6864 +2024-11-23 00:51:12.292184: Current learning rate: 0.00173 +2024-11-23 00:51:31.552632: train_loss -0.8034 +2024-11-23 00:51:31.552867: val_loss -0.7662 +2024-11-23 00:51:31.552955: Pseudo dice [0.8457] +2024-11-23 00:51:31.553042: Epoch time: 19.26 s +2024-11-23 00:51:32.535859: +2024-11-23 00:51:32.536092: Epoch 6865 +2024-11-23 00:51:32.536202: Current learning rate: 0.00172 +2024-11-23 00:51:50.529918: train_loss -0.8094 +2024-11-23 00:51:50.530145: val_loss -0.7396 +2024-11-23 00:51:50.530221: Pseudo dice [0.8547] +2024-11-23 00:51:50.530299: Epoch time: 17.99 s +2024-11-23 00:51:51.473369: +2024-11-23 00:51:51.473563: Epoch 6866 +2024-11-23 00:51:51.473685: Current learning rate: 0.00172 +2024-11-23 00:52:10.811257: train_loss -0.8206 +2024-11-23 00:52:10.811492: val_loss -0.7972 +2024-11-23 00:52:10.811590: Pseudo dice [0.855] +2024-11-23 00:52:10.811667: Epoch time: 19.34 s +2024-11-23 00:52:11.693610: +2024-11-23 00:52:11.693817: Epoch 6867 +2024-11-23 00:52:11.693961: Current learning rate: 0.00172 +2024-11-23 00:52:30.356190: train_loss -0.8133 +2024-11-23 00:52:30.356448: val_loss -0.7709 +2024-11-23 00:52:30.356538: Pseudo dice [0.8693] +2024-11-23 00:52:30.356660: Epoch time: 18.66 s +2024-11-23 00:52:31.253556: +2024-11-23 00:52:31.253764: Epoch 6868 +2024-11-23 00:52:31.253891: Current learning rate: 0.00172 +2024-11-23 00:52:49.375706: train_loss -0.8169 +2024-11-23 00:52:49.375971: val_loss -0.7688 +2024-11-23 00:52:49.376065: Pseudo dice [0.8559] +2024-11-23 00:52:49.376142: Epoch time: 18.12 s +2024-11-23 00:52:50.258855: +2024-11-23 00:52:50.259061: Epoch 6869 +2024-11-23 00:52:50.259177: Current learning rate: 0.00172 +2024-11-23 00:53:08.246489: train_loss -0.8199 +2024-11-23 00:53:08.246691: val_loss -0.7827 +2024-11-23 00:53:08.246766: Pseudo dice [0.8548] +2024-11-23 00:53:08.246845: Epoch time: 17.99 s +2024-11-23 00:53:09.302601: +2024-11-23 00:53:09.302810: Epoch 6870 +2024-11-23 00:53:09.302930: Current learning rate: 0.00172 +2024-11-23 00:53:28.258115: train_loss -0.8251 +2024-11-23 00:53:28.258332: val_loss -0.7781 +2024-11-23 00:53:28.258410: Pseudo dice [0.8588] +2024-11-23 00:53:28.258497: Epoch time: 18.96 s +2024-11-23 00:53:29.151622: +2024-11-23 00:53:29.151832: Epoch 6871 +2024-11-23 00:53:29.151951: Current learning rate: 0.00172 +2024-11-23 00:53:48.238287: train_loss -0.8091 +2024-11-23 00:53:48.238512: val_loss -0.7963 +2024-11-23 00:53:48.238597: Pseudo dice [0.8647] +2024-11-23 00:53:48.238684: Epoch time: 19.09 s +2024-11-23 00:53:49.523160: +2024-11-23 00:53:49.523401: Epoch 6872 +2024-11-23 00:53:49.523514: Current learning rate: 0.00172 +2024-11-23 00:54:07.578034: train_loss -0.8147 +2024-11-23 00:54:07.578283: val_loss -0.7499 +2024-11-23 00:54:07.578381: Pseudo dice [0.8426] +2024-11-23 00:54:07.578477: Epoch time: 18.06 s +2024-11-23 00:54:08.465882: +2024-11-23 00:54:08.466094: Epoch 6873 +2024-11-23 00:54:08.466218: Current learning rate: 0.00171 +2024-11-23 00:54:26.108184: train_loss -0.8075 +2024-11-23 00:54:26.108535: val_loss -0.796 +2024-11-23 00:54:26.108625: Pseudo dice [0.8541] +2024-11-23 00:54:26.108703: Epoch time: 17.64 s +2024-11-23 00:54:26.989241: +2024-11-23 00:54:26.989468: Epoch 6874 +2024-11-23 00:54:26.989596: Current learning rate: 0.00171 +2024-11-23 00:54:45.309000: train_loss -0.8167 +2024-11-23 00:54:45.309240: val_loss -0.789 +2024-11-23 00:54:45.309317: Pseudo dice [0.8671] +2024-11-23 00:54:45.309399: Epoch time: 18.32 s +2024-11-23 00:54:46.195460: +2024-11-23 00:54:46.195702: Epoch 6875 +2024-11-23 00:54:46.195841: Current learning rate: 0.00171 +2024-11-23 00:55:04.459512: train_loss -0.8217 +2024-11-23 00:55:04.459743: val_loss -0.7612 +2024-11-23 00:55:04.459821: Pseudo dice [0.8601] +2024-11-23 00:55:04.465070: Epoch time: 18.26 s +2024-11-23 00:55:05.504259: +2024-11-23 00:55:05.505673: Epoch 6876 +2024-11-23 00:55:05.505838: Current learning rate: 0.00171 +2024-11-23 00:55:24.205220: train_loss -0.8169 +2024-11-23 00:55:24.205462: val_loss -0.7911 +2024-11-23 00:55:24.205547: Pseudo dice [0.8603] +2024-11-23 00:55:24.205628: Epoch time: 18.7 s +2024-11-23 00:55:25.096482: +2024-11-23 00:55:25.096685: Epoch 6877 +2024-11-23 00:55:25.096802: Current learning rate: 0.00171 +2024-11-23 00:55:43.288904: train_loss -0.8115 +2024-11-23 00:55:43.289150: val_loss -0.7984 +2024-11-23 00:55:43.289228: Pseudo dice [0.8538] +2024-11-23 00:55:43.289321: Epoch time: 18.19 s +2024-11-23 00:55:44.175899: +2024-11-23 00:55:44.176100: Epoch 6878 +2024-11-23 00:55:44.176232: Current learning rate: 0.00171 +2024-11-23 00:56:03.871451: train_loss -0.8069 +2024-11-23 00:56:03.871702: val_loss -0.7772 +2024-11-23 00:56:03.871778: Pseudo dice [0.8584] +2024-11-23 00:56:03.871852: Epoch time: 19.7 s +2024-11-23 00:56:04.760302: +2024-11-23 00:56:04.760566: Epoch 6879 +2024-11-23 00:56:04.760695: Current learning rate: 0.00171 +2024-11-23 00:56:22.761201: train_loss -0.8082 +2024-11-23 00:56:22.761453: val_loss -0.7912 +2024-11-23 00:56:22.761539: Pseudo dice [0.8628] +2024-11-23 00:56:22.766763: Epoch time: 18.0 s +2024-11-23 00:56:23.660690: +2024-11-23 00:56:23.660879: Epoch 6880 +2024-11-23 00:56:23.661013: Current learning rate: 0.0017 +2024-11-23 00:56:41.963775: train_loss -0.828 +2024-11-23 00:56:41.963995: val_loss -0.7993 +2024-11-23 00:56:41.964078: Pseudo dice [0.8651] +2024-11-23 00:56:41.964162: Epoch time: 18.3 s +2024-11-23 00:56:42.852521: +2024-11-23 00:56:42.852714: Epoch 6881 +2024-11-23 00:56:42.852853: Current learning rate: 0.0017 +2024-11-23 00:57:01.264649: train_loss -0.8217 +2024-11-23 00:57:01.264871: val_loss -0.7899 +2024-11-23 00:57:01.270140: Pseudo dice [0.8493] +2024-11-23 00:57:01.270258: Epoch time: 18.41 s +2024-11-23 00:57:02.362990: +2024-11-23 00:57:02.363241: Epoch 6882 +2024-11-23 00:57:02.363377: Current learning rate: 0.0017 +2024-11-23 00:57:20.079119: train_loss -0.8085 +2024-11-23 00:57:20.079358: val_loss -0.7882 +2024-11-23 00:57:20.079433: Pseudo dice [0.8567] +2024-11-23 00:57:20.079516: Epoch time: 17.72 s +2024-11-23 00:57:21.541049: +2024-11-23 00:57:21.541243: Epoch 6883 +2024-11-23 00:57:21.541360: Current learning rate: 0.0017 +2024-11-23 00:57:39.394554: train_loss -0.8068 +2024-11-23 00:57:39.394800: val_loss -0.7782 +2024-11-23 00:57:39.394883: Pseudo dice [0.855] +2024-11-23 00:57:39.394966: Epoch time: 17.85 s +2024-11-23 00:57:40.393587: +2024-11-23 00:57:40.393806: Epoch 6884 +2024-11-23 00:57:40.393933: Current learning rate: 0.0017 +2024-11-23 00:57:58.991809: train_loss -0.8179 +2024-11-23 00:57:58.992054: val_loss -0.814 +2024-11-23 00:57:58.992147: Pseudo dice [0.8635] +2024-11-23 00:57:58.992239: Epoch time: 18.6 s +2024-11-23 00:57:59.884859: +2024-11-23 00:57:59.885073: Epoch 6885 +2024-11-23 00:57:59.885183: Current learning rate: 0.0017 +2024-11-23 00:58:18.746576: train_loss -0.8151 +2024-11-23 00:58:18.746812: val_loss -0.7741 +2024-11-23 00:58:18.746895: Pseudo dice [0.8581] +2024-11-23 00:58:18.746972: Epoch time: 18.86 s +2024-11-23 00:58:19.628878: +2024-11-23 00:58:19.629099: Epoch 6886 +2024-11-23 00:58:19.629213: Current learning rate: 0.0017 +2024-11-23 00:58:38.158474: train_loss -0.8164 +2024-11-23 00:58:38.158742: val_loss -0.7947 +2024-11-23 00:58:38.163984: Pseudo dice [0.8677] +2024-11-23 00:58:38.164271: Epoch time: 18.53 s +2024-11-23 00:58:39.270602: +2024-11-23 00:58:39.270832: Epoch 6887 +2024-11-23 00:58:39.270955: Current learning rate: 0.00169 +2024-11-23 00:58:57.743044: train_loss -0.816 +2024-11-23 00:58:57.743278: val_loss -0.7763 +2024-11-23 00:58:57.743370: Pseudo dice [0.8511] +2024-11-23 00:58:57.743465: Epoch time: 18.47 s +2024-11-23 00:58:58.627882: +2024-11-23 00:58:58.628094: Epoch 6888 +2024-11-23 00:58:58.628216: Current learning rate: 0.00169 +2024-11-23 00:59:17.430615: train_loss -0.8133 +2024-11-23 00:59:17.430835: val_loss -0.7809 +2024-11-23 00:59:17.430917: Pseudo dice [0.857] +2024-11-23 00:59:17.431052: Epoch time: 18.8 s +2024-11-23 00:59:18.315379: +2024-11-23 00:59:18.315569: Epoch 6889 +2024-11-23 00:59:18.315684: Current learning rate: 0.00169 +2024-11-23 00:59:37.233350: train_loss -0.8162 +2024-11-23 00:59:37.233572: val_loss -0.7977 +2024-11-23 00:59:37.233660: Pseudo dice [0.8589] +2024-11-23 00:59:37.233738: Epoch time: 18.92 s +2024-11-23 00:59:38.157688: +2024-11-23 00:59:38.157903: Epoch 6890 +2024-11-23 00:59:38.158030: Current learning rate: 0.00169 +2024-11-23 00:59:56.275380: train_loss -0.8261 +2024-11-23 00:59:56.275636: val_loss -0.7884 +2024-11-23 00:59:56.275738: Pseudo dice [0.8539] +2024-11-23 00:59:56.275832: Epoch time: 18.12 s +2024-11-23 00:59:57.161651: +2024-11-23 00:59:57.161839: Epoch 6891 +2024-11-23 00:59:57.161952: Current learning rate: 0.00169 +2024-11-23 01:00:15.891614: train_loss -0.8173 +2024-11-23 01:00:15.891829: val_loss -0.7702 +2024-11-23 01:00:15.891923: Pseudo dice [0.8613] +2024-11-23 01:00:15.891999: Epoch time: 18.73 s +2024-11-23 01:00:16.785115: +2024-11-23 01:00:16.785304: Epoch 6892 +2024-11-23 01:00:16.785415: Current learning rate: 0.00169 +2024-11-23 01:00:34.584620: train_loss -0.8162 +2024-11-23 01:00:34.587041: val_loss -0.7788 +2024-11-23 01:00:34.587164: Pseudo dice [0.8639] +2024-11-23 01:00:34.587252: Epoch time: 17.8 s +2024-11-23 01:00:35.616537: +2024-11-23 01:00:35.616753: Epoch 6893 +2024-11-23 01:00:35.616871: Current learning rate: 0.00169 +2024-11-23 01:00:53.797154: train_loss -0.815 +2024-11-23 01:00:53.798070: val_loss -0.7953 +2024-11-23 01:00:53.798186: Pseudo dice [0.8632] +2024-11-23 01:00:53.798278: Epoch time: 18.18 s +2024-11-23 01:00:55.117646: +2024-11-23 01:00:55.117852: Epoch 6894 +2024-11-23 01:00:55.117991: Current learning rate: 0.00168 +2024-11-23 01:01:13.051813: train_loss -0.8122 +2024-11-23 01:01:13.052149: val_loss -0.7898 +2024-11-23 01:01:13.052237: Pseudo dice [0.8653] +2024-11-23 01:01:13.052327: Epoch time: 17.93 s +2024-11-23 01:01:13.937211: +2024-11-23 01:01:13.937458: Epoch 6895 +2024-11-23 01:01:13.937568: Current learning rate: 0.00168 +2024-11-23 01:01:32.218800: train_loss -0.8101 +2024-11-23 01:01:32.219030: val_loss -0.793 +2024-11-23 01:01:32.219132: Pseudo dice [0.8571] +2024-11-23 01:01:32.219210: Epoch time: 18.28 s +2024-11-23 01:01:33.099877: +2024-11-23 01:01:33.100116: Epoch 6896 +2024-11-23 01:01:33.100245: Current learning rate: 0.00168 +2024-11-23 01:01:50.347124: train_loss -0.8277 +2024-11-23 01:01:50.350729: val_loss -0.7792 +2024-11-23 01:01:50.350836: Pseudo dice [0.8412] +2024-11-23 01:01:50.350913: Epoch time: 17.25 s +2024-11-23 01:01:51.251111: +2024-11-23 01:01:51.251309: Epoch 6897 +2024-11-23 01:01:51.251435: Current learning rate: 0.00168 +2024-11-23 01:02:10.242131: train_loss -0.8148 +2024-11-23 01:02:10.242387: val_loss -0.7859 +2024-11-23 01:02:10.242469: Pseudo dice [0.8529] +2024-11-23 01:02:10.242563: Epoch time: 18.99 s +2024-11-23 01:02:11.135415: +2024-11-23 01:02:11.135610: Epoch 6898 +2024-11-23 01:02:11.135756: Current learning rate: 0.00168 +2024-11-23 01:02:29.428910: train_loss -0.8193 +2024-11-23 01:02:29.429135: val_loss -0.7846 +2024-11-23 01:02:29.429214: Pseudo dice [0.8625] +2024-11-23 01:02:29.429288: Epoch time: 18.29 s +2024-11-23 01:02:30.316210: +2024-11-23 01:02:30.316412: Epoch 6899 +2024-11-23 01:02:30.316527: Current learning rate: 0.00168 +2024-11-23 01:02:49.300908: train_loss -0.8188 +2024-11-23 01:02:49.301138: val_loss -0.7597 +2024-11-23 01:02:49.301233: Pseudo dice [0.8526] +2024-11-23 01:02:49.301310: Epoch time: 18.99 s +2024-11-23 01:02:50.518322: +2024-11-23 01:02:50.518528: Epoch 6900 +2024-11-23 01:02:50.518645: Current learning rate: 0.00168 +2024-11-23 01:03:09.330284: train_loss -0.8095 +2024-11-23 01:03:09.330515: val_loss -0.786 +2024-11-23 01:03:09.330605: Pseudo dice [0.8564] +2024-11-23 01:03:09.330688: Epoch time: 18.81 s +2024-11-23 01:03:10.223462: +2024-11-23 01:03:10.223671: Epoch 6901 +2024-11-23 01:03:10.223793: Current learning rate: 0.00168 +2024-11-23 01:03:28.022346: train_loss -0.8152 +2024-11-23 01:03:28.024779: val_loss -0.7654 +2024-11-23 01:03:28.024904: Pseudo dice [0.8503] +2024-11-23 01:03:28.025002: Epoch time: 17.8 s +2024-11-23 01:03:28.953973: +2024-11-23 01:03:28.954181: Epoch 6902 +2024-11-23 01:03:28.954308: Current learning rate: 0.00167 +2024-11-23 01:03:47.214135: train_loss -0.8209 +2024-11-23 01:03:47.214371: val_loss -0.7731 +2024-11-23 01:03:47.214450: Pseudo dice [0.8568] +2024-11-23 01:03:47.214534: Epoch time: 18.26 s +2024-11-23 01:03:48.107132: +2024-11-23 01:03:48.107351: Epoch 6903 +2024-11-23 01:03:48.107466: Current learning rate: 0.00167 +2024-11-23 01:04:06.350005: train_loss -0.8119 +2024-11-23 01:04:06.350232: val_loss -0.7889 +2024-11-23 01:04:06.350320: Pseudo dice [0.8637] +2024-11-23 01:04:06.350419: Epoch time: 18.24 s +2024-11-23 01:04:07.430537: +2024-11-23 01:04:07.430748: Epoch 6904 +2024-11-23 01:04:07.430861: Current learning rate: 0.00167 +2024-11-23 01:04:25.949599: train_loss -0.8117 +2024-11-23 01:04:25.949845: val_loss -0.76 +2024-11-23 01:04:25.949931: Pseudo dice [0.8506] +2024-11-23 01:04:25.950012: Epoch time: 18.52 s +2024-11-23 01:04:27.350274: +2024-11-23 01:04:27.350489: Epoch 6905 +2024-11-23 01:04:27.350603: Current learning rate: 0.00167 +2024-11-23 01:04:46.082732: train_loss -0.8212 +2024-11-23 01:04:46.082973: val_loss -0.772 +2024-11-23 01:04:46.083056: Pseudo dice [0.865] +2024-11-23 01:04:46.083143: Epoch time: 18.73 s +2024-11-23 01:04:46.965919: +2024-11-23 01:04:46.966156: Epoch 6906 +2024-11-23 01:04:46.966300: Current learning rate: 0.00167 +2024-11-23 01:05:05.358596: train_loss -0.8177 +2024-11-23 01:05:05.358827: val_loss -0.7894 +2024-11-23 01:05:05.358908: Pseudo dice [0.8591] +2024-11-23 01:05:05.358985: Epoch time: 18.39 s +2024-11-23 01:05:06.423703: +2024-11-23 01:05:06.423914: Epoch 6907 +2024-11-23 01:05:06.424031: Current learning rate: 0.00167 +2024-11-23 01:05:23.855175: train_loss -0.822 +2024-11-23 01:05:23.855424: val_loss -0.7937 +2024-11-23 01:05:23.855517: Pseudo dice [0.8635] +2024-11-23 01:05:23.855612: Epoch time: 17.43 s +2024-11-23 01:05:24.738140: +2024-11-23 01:05:24.738325: Epoch 6908 +2024-11-23 01:05:24.738434: Current learning rate: 0.00167 +2024-11-23 01:05:42.539183: train_loss -0.8218 +2024-11-23 01:05:42.539471: val_loss -0.7572 +2024-11-23 01:05:42.539554: Pseudo dice [0.8649] +2024-11-23 01:05:42.539634: Epoch time: 17.8 s +2024-11-23 01:05:43.427171: +2024-11-23 01:05:43.427391: Epoch 6909 +2024-11-23 01:05:43.427506: Current learning rate: 0.00166 +2024-11-23 01:06:02.731196: train_loss -0.8224 +2024-11-23 01:06:02.731425: val_loss -0.7919 +2024-11-23 01:06:02.731508: Pseudo dice [0.8567] +2024-11-23 01:06:02.731589: Epoch time: 19.3 s +2024-11-23 01:06:03.622547: +2024-11-23 01:06:03.622748: Epoch 6910 +2024-11-23 01:06:03.622864: Current learning rate: 0.00166 +2024-11-23 01:06:21.668809: train_loss -0.8185 +2024-11-23 01:06:21.669026: val_loss -0.7884 +2024-11-23 01:06:21.669114: Pseudo dice [0.8691] +2024-11-23 01:06:21.669189: Epoch time: 18.05 s +2024-11-23 01:06:22.549705: +2024-11-23 01:06:22.549921: Epoch 6911 +2024-11-23 01:06:22.550044: Current learning rate: 0.00166 +2024-11-23 01:06:40.463881: train_loss -0.8186 +2024-11-23 01:06:40.464146: val_loss -0.8026 +2024-11-23 01:06:40.464227: Pseudo dice [0.8638] +2024-11-23 01:06:40.464317: Epoch time: 17.91 s +2024-11-23 01:06:41.347229: +2024-11-23 01:06:41.347430: Epoch 6912 +2024-11-23 01:06:41.347542: Current learning rate: 0.00166 +2024-11-23 01:06:59.831817: train_loss -0.8205 +2024-11-23 01:06:59.832052: val_loss -0.7878 +2024-11-23 01:06:59.832140: Pseudo dice [0.8653] +2024-11-23 01:06:59.832229: Epoch time: 18.49 s +2024-11-23 01:07:00.720812: +2024-11-23 01:07:00.721062: Epoch 6913 +2024-11-23 01:07:00.721184: Current learning rate: 0.00166 +2024-11-23 01:07:19.507942: train_loss -0.8233 +2024-11-23 01:07:19.508172: val_loss -0.7784 +2024-11-23 01:07:19.508277: Pseudo dice [0.8492] +2024-11-23 01:07:19.508396: Epoch time: 18.79 s +2024-11-23 01:07:20.399124: +2024-11-23 01:07:20.399343: Epoch 6914 +2024-11-23 01:07:20.399456: Current learning rate: 0.00166 +2024-11-23 01:07:38.901682: train_loss -0.8247 +2024-11-23 01:07:38.901891: val_loss -0.7841 +2024-11-23 01:07:38.901976: Pseudo dice [0.8565] +2024-11-23 01:07:38.902080: Epoch time: 18.5 s +2024-11-23 01:07:39.797126: +2024-11-23 01:07:39.797349: Epoch 6915 +2024-11-23 01:07:39.797492: Current learning rate: 0.00166 +2024-11-23 01:07:57.284798: train_loss -0.82 +2024-11-23 01:07:57.285050: val_loss -0.7716 +2024-11-23 01:07:57.285138: Pseudo dice [0.8618] +2024-11-23 01:07:57.285294: Epoch time: 17.49 s +2024-11-23 01:07:58.595689: +2024-11-23 01:07:58.595890: Epoch 6916 +2024-11-23 01:07:58.596014: Current learning rate: 0.00165 +2024-11-23 01:08:16.814661: train_loss -0.8187 +2024-11-23 01:08:16.814892: val_loss -0.7599 +2024-11-23 01:08:16.814973: Pseudo dice [0.864] +2024-11-23 01:08:16.815052: Epoch time: 18.22 s +2024-11-23 01:08:17.724823: +2024-11-23 01:08:17.725036: Epoch 6917 +2024-11-23 01:08:17.725162: Current learning rate: 0.00165 +2024-11-23 01:08:36.117784: train_loss -0.8159 +2024-11-23 01:08:36.118019: val_loss -0.7781 +2024-11-23 01:08:36.118117: Pseudo dice [0.8443] +2024-11-23 01:08:36.118194: Epoch time: 18.39 s +2024-11-23 01:08:37.170146: +2024-11-23 01:08:37.170348: Epoch 6918 +2024-11-23 01:08:37.170481: Current learning rate: 0.00165 +2024-11-23 01:08:56.244204: train_loss -0.8129 +2024-11-23 01:08:56.244437: val_loss -0.794 +2024-11-23 01:08:56.244526: Pseudo dice [0.8666] +2024-11-23 01:08:56.244617: Epoch time: 19.07 s +2024-11-23 01:08:57.199486: +2024-11-23 01:08:57.199708: Epoch 6919 +2024-11-23 01:08:57.199859: Current learning rate: 0.00165 +2024-11-23 01:09:15.916363: train_loss -0.8101 +2024-11-23 01:09:15.916609: val_loss -0.7557 +2024-11-23 01:09:15.921835: Pseudo dice [0.8664] +2024-11-23 01:09:15.922008: Epoch time: 18.72 s +2024-11-23 01:09:17.106754: +2024-11-23 01:09:17.106960: Epoch 6920 +2024-11-23 01:09:17.107080: Current learning rate: 0.00165 +2024-11-23 01:09:34.547343: train_loss -0.8138 +2024-11-23 01:09:34.547580: val_loss -0.7726 +2024-11-23 01:09:34.547664: Pseudo dice [0.8535] +2024-11-23 01:09:34.547750: Epoch time: 17.44 s +2024-11-23 01:09:35.472968: +2024-11-23 01:09:35.473181: Epoch 6921 +2024-11-23 01:09:35.473296: Current learning rate: 0.00165 +2024-11-23 01:09:53.914328: train_loss -0.8207 +2024-11-23 01:09:53.914542: val_loss -0.771 +2024-11-23 01:09:53.914622: Pseudo dice [0.8672] +2024-11-23 01:09:53.914701: Epoch time: 18.44 s +2024-11-23 01:09:54.805454: +2024-11-23 01:09:54.805678: Epoch 6922 +2024-11-23 01:09:54.805802: Current learning rate: 0.00165 +2024-11-23 01:10:13.706150: train_loss -0.8273 +2024-11-23 01:10:13.706398: val_loss -0.7856 +2024-11-23 01:10:13.706488: Pseudo dice [0.8461] +2024-11-23 01:10:13.706573: Epoch time: 18.9 s +2024-11-23 01:10:14.604688: +2024-11-23 01:10:14.604892: Epoch 6923 +2024-11-23 01:10:14.605005: Current learning rate: 0.00165 +2024-11-23 01:10:33.109080: train_loss -0.8143 +2024-11-23 01:10:33.109298: val_loss -0.7826 +2024-11-23 01:10:33.109383: Pseudo dice [0.8525] +2024-11-23 01:10:33.109472: Epoch time: 18.51 s +2024-11-23 01:10:33.994168: +2024-11-23 01:10:33.994353: Epoch 6924 +2024-11-23 01:10:33.994460: Current learning rate: 0.00164 +2024-11-23 01:10:52.595899: train_loss -0.819 +2024-11-23 01:10:52.596118: val_loss -0.7908 +2024-11-23 01:10:52.596196: Pseudo dice [0.859] +2024-11-23 01:10:52.596275: Epoch time: 18.6 s +2024-11-23 01:10:53.487591: +2024-11-23 01:10:53.487786: Epoch 6925 +2024-11-23 01:10:53.487914: Current learning rate: 0.00164 +2024-11-23 01:11:11.904781: train_loss -0.8211 +2024-11-23 01:11:11.905019: val_loss -0.7712 +2024-11-23 01:11:11.905102: Pseudo dice [0.8537] +2024-11-23 01:11:11.905180: Epoch time: 18.42 s +2024-11-23 01:11:12.818121: +2024-11-23 01:11:12.818319: Epoch 6926 +2024-11-23 01:11:12.818435: Current learning rate: 0.00164 +2024-11-23 01:11:31.331491: train_loss -0.8205 +2024-11-23 01:11:31.331728: val_loss -0.7887 +2024-11-23 01:11:31.331802: Pseudo dice [0.8687] +2024-11-23 01:11:31.331886: Epoch time: 18.51 s +2024-11-23 01:11:32.607598: +2024-11-23 01:11:32.607809: Epoch 6927 +2024-11-23 01:11:32.607930: Current learning rate: 0.00164 +2024-11-23 01:11:51.320852: train_loss -0.8175 +2024-11-23 01:11:51.321094: val_loss -0.786 +2024-11-23 01:11:51.321176: Pseudo dice [0.8441] +2024-11-23 01:11:51.321254: Epoch time: 18.71 s +2024-11-23 01:11:52.430821: +2024-11-23 01:11:52.431038: Epoch 6928 +2024-11-23 01:11:52.431158: Current learning rate: 0.00164 +2024-11-23 01:12:11.148688: train_loss -0.8186 +2024-11-23 01:12:11.148921: val_loss -0.7908 +2024-11-23 01:12:11.148999: Pseudo dice [0.8593] +2024-11-23 01:12:11.149084: Epoch time: 18.72 s +2024-11-23 01:12:12.036721: +2024-11-23 01:12:12.036964: Epoch 6929 +2024-11-23 01:12:12.037104: Current learning rate: 0.00164 +2024-11-23 01:12:29.944760: train_loss -0.8165 +2024-11-23 01:12:29.944998: val_loss -0.764 +2024-11-23 01:12:29.945088: Pseudo dice [0.8511] +2024-11-23 01:12:29.945185: Epoch time: 17.91 s +2024-11-23 01:12:30.838078: +2024-11-23 01:12:30.838271: Epoch 6930 +2024-11-23 01:12:30.838383: Current learning rate: 0.00164 +2024-11-23 01:12:47.583807: train_loss -0.8205 +2024-11-23 01:12:47.584048: val_loss -0.7669 +2024-11-23 01:12:47.584136: Pseudo dice [0.8553] +2024-11-23 01:12:47.584246: Epoch time: 16.75 s +2024-11-23 01:12:48.488493: +2024-11-23 01:12:48.488691: Epoch 6931 +2024-11-23 01:12:48.488817: Current learning rate: 0.00163 +2024-11-23 01:13:07.575942: train_loss -0.8104 +2024-11-23 01:13:07.576171: val_loss -0.7875 +2024-11-23 01:13:07.576257: Pseudo dice [0.8571] +2024-11-23 01:13:07.576341: Epoch time: 19.09 s +2024-11-23 01:13:08.485729: +2024-11-23 01:13:08.485934: Epoch 6932 +2024-11-23 01:13:08.486071: Current learning rate: 0.00163 +2024-11-23 01:13:27.021739: train_loss -0.8189 +2024-11-23 01:13:27.021987: val_loss -0.8015 +2024-11-23 01:13:27.022078: Pseudo dice [0.8606] +2024-11-23 01:13:27.022166: Epoch time: 18.54 s +2024-11-23 01:13:27.911631: +2024-11-23 01:13:27.911832: Epoch 6933 +2024-11-23 01:13:27.911944: Current learning rate: 0.00163 +2024-11-23 01:13:46.366441: train_loss -0.8143 +2024-11-23 01:13:46.366730: val_loss -0.7733 +2024-11-23 01:13:46.366817: Pseudo dice [0.8593] +2024-11-23 01:13:46.366903: Epoch time: 18.46 s +2024-11-23 01:13:47.255984: +2024-11-23 01:13:47.256192: Epoch 6934 +2024-11-23 01:13:47.256312: Current learning rate: 0.00163 +2024-11-23 01:14:05.603909: train_loss -0.8173 +2024-11-23 01:14:05.606289: val_loss -0.7899 +2024-11-23 01:14:05.606390: Pseudo dice [0.854] +2024-11-23 01:14:05.606469: Epoch time: 18.35 s +2024-11-23 01:14:06.512912: +2024-11-23 01:14:06.513145: Epoch 6935 +2024-11-23 01:14:06.513267: Current learning rate: 0.00163 +2024-11-23 01:14:25.577154: train_loss -0.819 +2024-11-23 01:14:25.577428: val_loss -0.7637 +2024-11-23 01:14:25.577514: Pseudo dice [0.8581] +2024-11-23 01:14:25.577606: Epoch time: 19.07 s +2024-11-23 01:14:26.488484: +2024-11-23 01:14:26.488667: Epoch 6936 +2024-11-23 01:14:26.488783: Current learning rate: 0.00163 +2024-11-23 01:14:44.475364: train_loss -0.8139 +2024-11-23 01:14:44.475603: val_loss -0.7756 +2024-11-23 01:14:44.475736: Pseudo dice [0.8535] +2024-11-23 01:14:44.475814: Epoch time: 17.99 s +2024-11-23 01:14:45.366888: +2024-11-23 01:14:45.367137: Epoch 6937 +2024-11-23 01:14:45.367250: Current learning rate: 0.00163 +2024-11-23 01:15:04.462982: train_loss -0.8191 +2024-11-23 01:15:04.465351: val_loss -0.7667 +2024-11-23 01:15:04.465443: Pseudo dice [0.8544] +2024-11-23 01:15:04.465541: Epoch time: 19.1 s +2024-11-23 01:15:05.793093: +2024-11-23 01:15:05.793312: Epoch 6938 +2024-11-23 01:15:05.793434: Current learning rate: 0.00162 +2024-11-23 01:15:25.040648: train_loss -0.8221 +2024-11-23 01:15:25.040883: val_loss -0.7745 +2024-11-23 01:15:25.040959: Pseudo dice [0.8595] +2024-11-23 01:15:25.041038: Epoch time: 19.25 s +2024-11-23 01:15:25.930486: +2024-11-23 01:15:25.930717: Epoch 6939 +2024-11-23 01:15:25.930841: Current learning rate: 0.00162 +2024-11-23 01:15:43.734498: train_loss -0.8151 +2024-11-23 01:15:43.734737: val_loss -0.7649 +2024-11-23 01:15:43.734832: Pseudo dice [0.8583] +2024-11-23 01:15:43.734929: Epoch time: 17.8 s +2024-11-23 01:15:44.622670: +2024-11-23 01:15:44.622926: Epoch 6940 +2024-11-23 01:15:44.623067: Current learning rate: 0.00162 +2024-11-23 01:16:03.462039: train_loss -0.8056 +2024-11-23 01:16:03.462313: val_loss -0.7731 +2024-11-23 01:16:03.462399: Pseudo dice [0.853] +2024-11-23 01:16:03.462477: Epoch time: 18.84 s +2024-11-23 01:16:04.400365: +2024-11-23 01:16:04.400595: Epoch 6941 +2024-11-23 01:16:04.400712: Current learning rate: 0.00162 +2024-11-23 01:16:22.796379: train_loss -0.7992 +2024-11-23 01:16:22.796635: val_loss -0.763 +2024-11-23 01:16:22.796728: Pseudo dice [0.8556] +2024-11-23 01:16:22.796832: Epoch time: 18.4 s +2024-11-23 01:16:23.689525: +2024-11-23 01:16:23.689743: Epoch 6942 +2024-11-23 01:16:23.689857: Current learning rate: 0.00162 +2024-11-23 01:16:41.968649: train_loss -0.8131 +2024-11-23 01:16:41.968870: val_loss -0.7681 +2024-11-23 01:16:41.968953: Pseudo dice [0.8489] +2024-11-23 01:16:41.969038: Epoch time: 18.28 s +2024-11-23 01:16:42.878572: +2024-11-23 01:16:42.878779: Epoch 6943 +2024-11-23 01:16:42.878891: Current learning rate: 0.00162 +2024-11-23 01:17:00.769004: train_loss -0.8061 +2024-11-23 01:17:00.769229: val_loss -0.7992 +2024-11-23 01:17:00.769314: Pseudo dice [0.8561] +2024-11-23 01:17:00.769392: Epoch time: 17.89 s +2024-11-23 01:17:01.691328: +2024-11-23 01:17:01.691538: Epoch 6944 +2024-11-23 01:17:01.691650: Current learning rate: 0.00162 +2024-11-23 01:17:19.740450: train_loss -0.8147 +2024-11-23 01:17:19.740703: val_loss -0.7532 +2024-11-23 01:17:19.740800: Pseudo dice [0.8485] +2024-11-23 01:17:19.740883: Epoch time: 18.05 s +2024-11-23 01:17:20.630196: +2024-11-23 01:17:20.630399: Epoch 6945 +2024-11-23 01:17:20.630511: Current learning rate: 0.00161 +2024-11-23 01:17:38.601464: train_loss -0.8077 +2024-11-23 01:17:38.601684: val_loss -0.784 +2024-11-23 01:17:38.601760: Pseudo dice [0.8613] +2024-11-23 01:17:38.601844: Epoch time: 17.97 s +2024-11-23 01:17:39.484748: +2024-11-23 01:17:39.484921: Epoch 6946 +2024-11-23 01:17:39.485038: Current learning rate: 0.00161 +2024-11-23 01:17:57.599250: train_loss -0.8066 +2024-11-23 01:17:57.599469: val_loss -0.7802 +2024-11-23 01:17:57.599545: Pseudo dice [0.8602] +2024-11-23 01:17:57.599620: Epoch time: 18.12 s +2024-11-23 01:17:58.525022: +2024-11-23 01:17:58.525228: Epoch 6947 +2024-11-23 01:17:58.525347: Current learning rate: 0.00161 +2024-11-23 01:18:15.567119: train_loss -0.8067 +2024-11-23 01:18:15.567329: val_loss -0.7753 +2024-11-23 01:18:15.567426: Pseudo dice [0.8617] +2024-11-23 01:18:15.567575: Epoch time: 17.04 s +2024-11-23 01:18:16.452665: +2024-11-23 01:18:16.452868: Epoch 6948 +2024-11-23 01:18:16.452998: Current learning rate: 0.00161 +2024-11-23 01:18:36.508180: train_loss -0.813 +2024-11-23 01:18:36.508422: val_loss -0.7825 +2024-11-23 01:18:36.508504: Pseudo dice [0.8528] +2024-11-23 01:18:36.508591: Epoch time: 20.06 s +2024-11-23 01:18:37.869381: +2024-11-23 01:18:37.869603: Epoch 6949 +2024-11-23 01:18:37.869729: Current learning rate: 0.00161 +2024-11-23 01:18:56.912746: train_loss -0.8135 +2024-11-23 01:18:56.912995: val_loss -0.7818 +2024-11-23 01:18:56.913082: Pseudo dice [0.8628] +2024-11-23 01:18:56.913159: Epoch time: 19.04 s +2024-11-23 01:18:58.170451: +2024-11-23 01:18:58.170671: Epoch 6950 +2024-11-23 01:18:58.170789: Current learning rate: 0.00161 +2024-11-23 01:19:15.403187: train_loss -0.8192 +2024-11-23 01:19:15.403417: val_loss -0.7602 +2024-11-23 01:19:15.403494: Pseudo dice [0.8571] +2024-11-23 01:19:15.403577: Epoch time: 17.23 s +2024-11-23 01:19:16.288560: +2024-11-23 01:19:16.288762: Epoch 6951 +2024-11-23 01:19:16.288899: Current learning rate: 0.00161 +2024-11-23 01:19:35.202171: train_loss -0.8169 +2024-11-23 01:19:35.202413: val_loss -0.7763 +2024-11-23 01:19:35.202495: Pseudo dice [0.8628] +2024-11-23 01:19:35.202576: Epoch time: 18.91 s +2024-11-23 01:19:36.092698: +2024-11-23 01:19:36.092910: Epoch 6952 +2024-11-23 01:19:36.093037: Current learning rate: 0.00161 +2024-11-23 01:19:54.285909: train_loss -0.8148 +2024-11-23 01:19:54.286170: val_loss -0.7976 +2024-11-23 01:19:54.286258: Pseudo dice [0.8621] +2024-11-23 01:19:54.286350: Epoch time: 18.19 s +2024-11-23 01:19:55.198392: +2024-11-23 01:19:55.198587: Epoch 6953 +2024-11-23 01:19:55.198705: Current learning rate: 0.0016 +2024-11-23 01:20:13.366375: train_loss -0.8163 +2024-11-23 01:20:13.366600: val_loss -0.7804 +2024-11-23 01:20:13.366689: Pseudo dice [0.8621] +2024-11-23 01:20:13.366786: Epoch time: 18.17 s +2024-11-23 01:20:14.249802: +2024-11-23 01:20:14.250035: Epoch 6954 +2024-11-23 01:20:14.250152: Current learning rate: 0.0016 +2024-11-23 01:20:32.641105: train_loss -0.8179 +2024-11-23 01:20:32.641329: val_loss -0.7606 +2024-11-23 01:20:32.641411: Pseudo dice [0.853] +2024-11-23 01:20:32.641485: Epoch time: 18.39 s +2024-11-23 01:20:33.531074: +2024-11-23 01:20:33.531297: Epoch 6955 +2024-11-23 01:20:33.531418: Current learning rate: 0.0016 +2024-11-23 01:20:52.064487: train_loss -0.8159 +2024-11-23 01:20:52.064755: val_loss -0.7717 +2024-11-23 01:20:52.064839: Pseudo dice [0.8485] +2024-11-23 01:20:52.064930: Epoch time: 18.53 s +2024-11-23 01:20:52.956890: +2024-11-23 01:20:52.957096: Epoch 6956 +2024-11-23 01:20:52.957222: Current learning rate: 0.0016 +2024-11-23 01:21:11.675595: train_loss -0.8074 +2024-11-23 01:21:11.675813: val_loss -0.7607 +2024-11-23 01:21:11.675912: Pseudo dice [0.8644] +2024-11-23 01:21:11.676006: Epoch time: 18.72 s +2024-11-23 01:21:12.555228: +2024-11-23 01:21:12.555440: Epoch 6957 +2024-11-23 01:21:12.555555: Current learning rate: 0.0016 +2024-11-23 01:21:31.849373: train_loss -0.8159 +2024-11-23 01:21:31.849587: val_loss -0.7728 +2024-11-23 01:21:31.849681: Pseudo dice [0.853] +2024-11-23 01:21:31.849767: Epoch time: 19.29 s +2024-11-23 01:21:32.740178: +2024-11-23 01:21:32.740378: Epoch 6958 +2024-11-23 01:21:32.740494: Current learning rate: 0.0016 +2024-11-23 01:21:52.264692: train_loss -0.8237 +2024-11-23 01:21:52.264918: val_loss -0.7667 +2024-11-23 01:21:52.265001: Pseudo dice [0.8569] +2024-11-23 01:21:52.265098: Epoch time: 19.53 s +2024-11-23 01:21:53.153800: +2024-11-23 01:21:53.154009: Epoch 6959 +2024-11-23 01:21:53.154136: Current learning rate: 0.0016 +2024-11-23 01:22:11.706435: train_loss -0.817 +2024-11-23 01:22:11.706728: val_loss -0.7676 +2024-11-23 01:22:11.706810: Pseudo dice [0.8605] +2024-11-23 01:22:11.706891: Epoch time: 18.55 s +2024-11-23 01:22:12.991327: +2024-11-23 01:22:12.991555: Epoch 6960 +2024-11-23 01:22:12.991673: Current learning rate: 0.00159 +2024-11-23 01:22:31.459863: train_loss -0.823 +2024-11-23 01:22:31.460100: val_loss -0.7618 +2024-11-23 01:22:31.460206: Pseudo dice [0.8572] +2024-11-23 01:22:31.460288: Epoch time: 18.47 s +2024-11-23 01:22:32.348100: +2024-11-23 01:22:32.348349: Epoch 6961 +2024-11-23 01:22:32.348466: Current learning rate: 0.00159 +2024-11-23 01:22:50.524339: train_loss -0.8239 +2024-11-23 01:22:50.524570: val_loss -0.7531 +2024-11-23 01:22:50.524649: Pseudo dice [0.8517] +2024-11-23 01:22:50.524725: Epoch time: 18.18 s +2024-11-23 01:22:51.413445: +2024-11-23 01:22:51.413662: Epoch 6962 +2024-11-23 01:22:51.413777: Current learning rate: 0.00159 +2024-11-23 01:23:09.356244: train_loss -0.809 +2024-11-23 01:23:09.356472: val_loss -0.7689 +2024-11-23 01:23:09.356564: Pseudo dice [0.8391] +2024-11-23 01:23:09.356661: Epoch time: 17.94 s +2024-11-23 01:23:10.256443: +2024-11-23 01:23:10.256670: Epoch 6963 +2024-11-23 01:23:10.256780: Current learning rate: 0.00159 +2024-11-23 01:23:28.092350: train_loss -0.8094 +2024-11-23 01:23:28.092589: val_loss -0.7861 +2024-11-23 01:23:28.092670: Pseudo dice [0.8648] +2024-11-23 01:23:28.092758: Epoch time: 17.84 s +2024-11-23 01:23:28.984698: +2024-11-23 01:23:28.984923: Epoch 6964 +2024-11-23 01:23:28.985046: Current learning rate: 0.00159 +2024-11-23 01:23:48.053225: train_loss -0.8108 +2024-11-23 01:23:48.053467: val_loss -0.787 +2024-11-23 01:23:48.053552: Pseudo dice [0.8554] +2024-11-23 01:23:48.053633: Epoch time: 19.07 s +2024-11-23 01:23:49.139282: +2024-11-23 01:23:49.139502: Epoch 6965 +2024-11-23 01:23:49.139622: Current learning rate: 0.00159 +2024-11-23 01:24:07.401903: train_loss -0.8208 +2024-11-23 01:24:07.402141: val_loss -0.7742 +2024-11-23 01:24:07.402222: Pseudo dice [0.8552] +2024-11-23 01:24:07.402304: Epoch time: 18.26 s +2024-11-23 01:24:08.418715: +2024-11-23 01:24:08.418932: Epoch 6966 +2024-11-23 01:24:08.419047: Current learning rate: 0.00159 +2024-11-23 01:24:28.160881: train_loss -0.8222 +2024-11-23 01:24:28.163343: val_loss -0.7604 +2024-11-23 01:24:28.163456: Pseudo dice [0.8552] +2024-11-23 01:24:28.163568: Epoch time: 19.74 s +2024-11-23 01:24:29.070157: +2024-11-23 01:24:29.070365: Epoch 6967 +2024-11-23 01:24:29.070489: Current learning rate: 0.00158 +2024-11-23 01:24:46.626018: train_loss -0.8267 +2024-11-23 01:24:46.626244: val_loss -0.7556 +2024-11-23 01:24:46.626321: Pseudo dice [0.8494] +2024-11-23 01:24:46.626417: Epoch time: 17.56 s +2024-11-23 01:24:47.518397: +2024-11-23 01:24:47.518595: Epoch 6968 +2024-11-23 01:24:47.518716: Current learning rate: 0.00158 +2024-11-23 01:25:06.252835: train_loss -0.8147 +2024-11-23 01:25:06.253075: val_loss -0.7947 +2024-11-23 01:25:06.253179: Pseudo dice [0.8535] +2024-11-23 01:25:06.253253: Epoch time: 18.74 s +2024-11-23 01:25:07.139248: +2024-11-23 01:25:07.139426: Epoch 6969 +2024-11-23 01:25:07.139544: Current learning rate: 0.00158 +2024-11-23 01:25:25.328456: train_loss -0.824 +2024-11-23 01:25:25.328678: val_loss -0.7858 +2024-11-23 01:25:25.328761: Pseudo dice [0.8617] +2024-11-23 01:25:25.328840: Epoch time: 18.19 s +2024-11-23 01:25:26.215961: +2024-11-23 01:25:26.216168: Epoch 6970 +2024-11-23 01:25:26.216305: Current learning rate: 0.00158 +2024-11-23 01:25:44.491227: train_loss -0.8173 +2024-11-23 01:25:44.493257: val_loss -0.7534 +2024-11-23 01:25:44.493398: Pseudo dice [0.8443] +2024-11-23 01:25:44.493488: Epoch time: 18.28 s +2024-11-23 01:25:45.846054: +2024-11-23 01:25:45.846267: Epoch 6971 +2024-11-23 01:25:45.846380: Current learning rate: 0.00158 +2024-11-23 01:26:05.024055: train_loss -0.8176 +2024-11-23 01:26:05.024276: val_loss -0.7961 +2024-11-23 01:26:05.024354: Pseudo dice [0.8652] +2024-11-23 01:26:05.024435: Epoch time: 19.18 s +2024-11-23 01:26:05.906942: +2024-11-23 01:26:05.907195: Epoch 6972 +2024-11-23 01:26:05.907313: Current learning rate: 0.00158 +2024-11-23 01:26:23.760826: train_loss -0.8161 +2024-11-23 01:26:23.761057: val_loss -0.7626 +2024-11-23 01:26:23.761145: Pseudo dice [0.8483] +2024-11-23 01:26:23.761222: Epoch time: 17.85 s +2024-11-23 01:26:24.652935: +2024-11-23 01:26:24.653156: Epoch 6973 +2024-11-23 01:26:24.653276: Current learning rate: 0.00158 +2024-11-23 01:26:44.622264: train_loss -0.8192 +2024-11-23 01:26:44.622498: val_loss -0.7877 +2024-11-23 01:26:44.622581: Pseudo dice [0.8599] +2024-11-23 01:26:44.622671: Epoch time: 19.97 s +2024-11-23 01:26:45.512180: +2024-11-23 01:26:45.512373: Epoch 6974 +2024-11-23 01:26:45.512483: Current learning rate: 0.00157 +2024-11-23 01:27:03.420510: train_loss -0.8186 +2024-11-23 01:27:03.420774: val_loss -0.7923 +2024-11-23 01:27:03.420857: Pseudo dice [0.8557] +2024-11-23 01:27:03.420963: Epoch time: 17.91 s +2024-11-23 01:27:04.321934: +2024-11-23 01:27:04.322155: Epoch 6975 +2024-11-23 01:27:04.322271: Current learning rate: 0.00157 +2024-11-23 01:27:22.591158: train_loss -0.8227 +2024-11-23 01:27:22.591407: val_loss -0.7763 +2024-11-23 01:27:22.591496: Pseudo dice [0.8626] +2024-11-23 01:27:22.591580: Epoch time: 18.27 s +2024-11-23 01:27:23.503616: +2024-11-23 01:27:23.503826: Epoch 6976 +2024-11-23 01:27:23.503939: Current learning rate: 0.00157 +2024-11-23 01:27:42.017358: train_loss -0.818 +2024-11-23 01:27:42.017594: val_loss -0.7784 +2024-11-23 01:27:42.017673: Pseudo dice [0.8553] +2024-11-23 01:27:42.017750: Epoch time: 18.51 s +2024-11-23 01:27:43.097274: +2024-11-23 01:27:43.097468: Epoch 6977 +2024-11-23 01:27:43.097802: Current learning rate: 0.00157 +2024-11-23 01:28:01.364000: train_loss -0.8238 +2024-11-23 01:28:01.364250: val_loss -0.7896 +2024-11-23 01:28:01.364334: Pseudo dice [0.8631] +2024-11-23 01:28:01.365701: Epoch time: 18.27 s +2024-11-23 01:28:02.255081: +2024-11-23 01:28:02.255272: Epoch 6978 +2024-11-23 01:28:02.255397: Current learning rate: 0.00157 +2024-11-23 01:28:21.255408: train_loss -0.8198 +2024-11-23 01:28:21.255612: val_loss -0.795 +2024-11-23 01:28:21.255692: Pseudo dice [0.861] +2024-11-23 01:28:21.255764: Epoch time: 19.0 s +2024-11-23 01:28:22.141983: +2024-11-23 01:28:22.142185: Epoch 6979 +2024-11-23 01:28:22.142306: Current learning rate: 0.00157 +2024-11-23 01:28:41.516461: train_loss -0.8182 +2024-11-23 01:28:41.521832: val_loss -0.7784 +2024-11-23 01:28:41.522008: Pseudo dice [0.8579] +2024-11-23 01:28:41.522101: Epoch time: 19.38 s +2024-11-23 01:28:42.551376: +2024-11-23 01:28:42.551567: Epoch 6980 +2024-11-23 01:28:42.551685: Current learning rate: 0.00157 +2024-11-23 01:29:01.681386: train_loss -0.8153 +2024-11-23 01:29:01.681603: val_loss -0.7774 +2024-11-23 01:29:01.681679: Pseudo dice [0.8693] +2024-11-23 01:29:01.681753: Epoch time: 19.13 s +2024-11-23 01:29:02.563564: +2024-11-23 01:29:02.563780: Epoch 6981 +2024-11-23 01:29:02.563903: Current learning rate: 0.00157 +2024-11-23 01:29:21.278080: train_loss -0.8129 +2024-11-23 01:29:21.278327: val_loss -0.7738 +2024-11-23 01:29:21.278424: Pseudo dice [0.8555] +2024-11-23 01:29:21.278507: Epoch time: 18.72 s +2024-11-23 01:29:22.588881: +2024-11-23 01:29:22.589092: Epoch 6982 +2024-11-23 01:29:22.589209: Current learning rate: 0.00156 +2024-11-23 01:29:40.441595: train_loss -0.8132 +2024-11-23 01:29:40.441829: val_loss -0.7963 +2024-11-23 01:29:40.441911: Pseudo dice [0.8654] +2024-11-23 01:29:40.441991: Epoch time: 17.85 s +2024-11-23 01:29:41.326070: +2024-11-23 01:29:41.326315: Epoch 6983 +2024-11-23 01:29:41.326438: Current learning rate: 0.00156 +2024-11-23 01:30:00.017441: train_loss -0.8263 +2024-11-23 01:30:00.017680: val_loss -0.7724 +2024-11-23 01:30:00.017758: Pseudo dice [0.8529] +2024-11-23 01:30:00.017847: Epoch time: 18.69 s +2024-11-23 01:30:01.001928: +2024-11-23 01:30:01.002187: Epoch 6984 +2024-11-23 01:30:01.002327: Current learning rate: 0.00156 +2024-11-23 01:30:19.766758: train_loss -0.8173 +2024-11-23 01:30:19.766994: val_loss -0.7939 +2024-11-23 01:30:19.767085: Pseudo dice [0.8636] +2024-11-23 01:30:19.767162: Epoch time: 18.77 s +2024-11-23 01:30:20.655845: +2024-11-23 01:30:20.656063: Epoch 6985 +2024-11-23 01:30:20.656180: Current learning rate: 0.00156 +2024-11-23 01:30:38.980786: train_loss -0.8228 +2024-11-23 01:30:38.981074: val_loss -0.8024 +2024-11-23 01:30:38.981164: Pseudo dice [0.8675] +2024-11-23 01:30:38.981271: Epoch time: 18.33 s +2024-11-23 01:30:39.952939: +2024-11-23 01:30:39.953153: Epoch 6986 +2024-11-23 01:30:39.953272: Current learning rate: 0.00156 +2024-11-23 01:30:57.755577: train_loss -0.8194 +2024-11-23 01:30:57.755850: val_loss -0.7572 +2024-11-23 01:30:57.755935: Pseudo dice [0.8483] +2024-11-23 01:30:57.756026: Epoch time: 17.8 s +2024-11-23 01:30:58.655176: +2024-11-23 01:30:58.655391: Epoch 6987 +2024-11-23 01:30:58.655514: Current learning rate: 0.00156 +2024-11-23 01:31:17.646010: train_loss -0.8119 +2024-11-23 01:31:17.646244: val_loss -0.7707 +2024-11-23 01:31:17.646324: Pseudo dice [0.8559] +2024-11-23 01:31:17.646405: Epoch time: 18.99 s +2024-11-23 01:31:18.648045: +2024-11-23 01:31:18.648263: Epoch 6988 +2024-11-23 01:31:18.648393: Current learning rate: 0.00156 +2024-11-23 01:31:37.494429: train_loss -0.806 +2024-11-23 01:31:37.494650: val_loss -0.8141 +2024-11-23 01:31:37.494742: Pseudo dice [0.8689] +2024-11-23 01:31:37.494838: Epoch time: 18.85 s +2024-11-23 01:31:38.383177: +2024-11-23 01:31:38.383399: Epoch 6989 +2024-11-23 01:31:38.383516: Current learning rate: 0.00155 +2024-11-23 01:31:57.004467: train_loss -0.819 +2024-11-23 01:31:57.004707: val_loss -0.7768 +2024-11-23 01:31:57.004783: Pseudo dice [0.8578] +2024-11-23 01:31:57.004880: Epoch time: 18.62 s +2024-11-23 01:31:57.905021: +2024-11-23 01:31:57.905230: Epoch 6990 +2024-11-23 01:31:57.905350: Current learning rate: 0.00155 +2024-11-23 01:32:15.627455: train_loss -0.8187 +2024-11-23 01:32:15.627679: val_loss -0.7971 +2024-11-23 01:32:15.627761: Pseudo dice [0.8598] +2024-11-23 01:32:15.627843: Epoch time: 17.72 s +2024-11-23 01:32:16.591618: +2024-11-23 01:32:16.591808: Epoch 6991 +2024-11-23 01:32:16.591928: Current learning rate: 0.00155 +2024-11-23 01:32:35.414536: train_loss -0.8216 +2024-11-23 01:32:35.414761: val_loss -0.7941 +2024-11-23 01:32:35.414872: Pseudo dice [0.8532] +2024-11-23 01:32:35.414969: Epoch time: 18.82 s +2024-11-23 01:32:36.311438: +2024-11-23 01:32:36.311663: Epoch 6992 +2024-11-23 01:32:36.311797: Current learning rate: 0.00155 +2024-11-23 01:32:55.136101: train_loss -0.8205 +2024-11-23 01:32:55.136367: val_loss -0.789 +2024-11-23 01:32:55.136448: Pseudo dice [0.8589] +2024-11-23 01:32:55.136535: Epoch time: 18.83 s +2024-11-23 01:32:56.423477: +2024-11-23 01:32:56.423673: Epoch 6993 +2024-11-23 01:32:56.423796: Current learning rate: 0.00155 +2024-11-23 01:33:15.068437: train_loss -0.8239 +2024-11-23 01:33:15.068754: val_loss -0.767 +2024-11-23 01:33:15.068863: Pseudo dice [0.8526] +2024-11-23 01:33:15.068969: Epoch time: 18.65 s +2024-11-23 01:33:16.124869: +2024-11-23 01:33:16.125091: Epoch 6994 +2024-11-23 01:33:16.125204: Current learning rate: 0.00155 +2024-11-23 01:33:34.464028: train_loss -0.8203 +2024-11-23 01:33:34.464284: val_loss -0.7649 +2024-11-23 01:33:34.464379: Pseudo dice [0.8566] +2024-11-23 01:33:34.464461: Epoch time: 18.34 s +2024-11-23 01:33:35.351254: +2024-11-23 01:33:35.351454: Epoch 6995 +2024-11-23 01:33:35.351564: Current learning rate: 0.00155 +2024-11-23 01:33:54.716407: train_loss -0.819 +2024-11-23 01:33:54.716627: val_loss -0.7913 +2024-11-23 01:33:54.716703: Pseudo dice [0.8551] +2024-11-23 01:33:54.716781: Epoch time: 19.37 s +2024-11-23 01:33:55.608795: +2024-11-23 01:33:55.609008: Epoch 6996 +2024-11-23 01:33:55.609133: Current learning rate: 0.00154 +2024-11-23 01:34:12.958993: train_loss -0.8241 +2024-11-23 01:34:12.959256: val_loss -0.7985 +2024-11-23 01:34:12.959340: Pseudo dice [0.8636] +2024-11-23 01:34:12.959424: Epoch time: 17.35 s +2024-11-23 01:34:13.850531: +2024-11-23 01:34:13.850730: Epoch 6997 +2024-11-23 01:34:13.850852: Current learning rate: 0.00154 +2024-11-23 01:34:32.077610: train_loss -0.8179 +2024-11-23 01:34:32.077845: val_loss -0.7605 +2024-11-23 01:34:32.077944: Pseudo dice [0.8477] +2024-11-23 01:34:32.078021: Epoch time: 18.23 s +2024-11-23 01:34:32.961709: +2024-11-23 01:34:32.961919: Epoch 6998 +2024-11-23 01:34:32.962030: Current learning rate: 0.00154 +2024-11-23 01:34:50.918763: train_loss -0.8183 +2024-11-23 01:34:50.918992: val_loss -0.7901 +2024-11-23 01:34:50.919076: Pseudo dice [0.8581] +2024-11-23 01:34:50.919160: Epoch time: 17.96 s +2024-11-23 01:34:51.974731: +2024-11-23 01:34:51.974948: Epoch 6999 +2024-11-23 01:34:51.975082: Current learning rate: 0.00154 +2024-11-23 01:35:09.689713: train_loss -0.8213 +2024-11-23 01:35:09.692119: val_loss -0.7682 +2024-11-23 01:35:09.692232: Pseudo dice [0.8577] +2024-11-23 01:35:09.692323: Epoch time: 17.72 s +2024-11-23 01:35:11.160077: +2024-11-23 01:35:11.160316: Epoch 7000 +2024-11-23 01:35:11.160443: Current learning rate: 0.00154 +2024-11-23 01:35:29.693171: train_loss -0.8182 +2024-11-23 01:35:29.693398: val_loss -0.7735 +2024-11-23 01:35:29.693500: Pseudo dice [0.8625] +2024-11-23 01:35:29.693618: Epoch time: 18.53 s +2024-11-23 01:35:30.678736: +2024-11-23 01:35:30.678944: Epoch 7001 +2024-11-23 01:35:30.679056: Current learning rate: 0.00154 +2024-11-23 01:35:50.091055: train_loss -0.8234 +2024-11-23 01:35:50.091283: val_loss -0.7793 +2024-11-23 01:35:50.091366: Pseudo dice [0.8618] +2024-11-23 01:35:50.091469: Epoch time: 19.41 s +2024-11-23 01:35:50.978251: +2024-11-23 01:35:50.978499: Epoch 7002 +2024-11-23 01:35:50.978611: Current learning rate: 0.00154 +2024-11-23 01:36:10.269418: train_loss -0.8212 +2024-11-23 01:36:10.269670: val_loss -0.786 +2024-11-23 01:36:10.269755: Pseudo dice [0.8671] +2024-11-23 01:36:10.269830: Epoch time: 19.29 s +2024-11-23 01:36:11.185198: +2024-11-23 01:36:11.185402: Epoch 7003 +2024-11-23 01:36:11.185653: Current learning rate: 0.00153 +2024-11-23 01:36:29.273708: train_loss -0.818 +2024-11-23 01:36:29.273961: val_loss -0.753 +2024-11-23 01:36:29.274069: Pseudo dice [0.8351] +2024-11-23 01:36:29.274169: Epoch time: 18.09 s +2024-11-23 01:36:30.532715: +2024-11-23 01:36:30.532931: Epoch 7004 +2024-11-23 01:36:30.533081: Current learning rate: 0.00153 +2024-11-23 01:36:49.570392: train_loss -0.8232 +2024-11-23 01:36:49.570622: val_loss -0.7627 +2024-11-23 01:36:49.570706: Pseudo dice [0.8589] +2024-11-23 01:36:49.570786: Epoch time: 19.04 s +2024-11-23 01:36:50.512734: +2024-11-23 01:36:50.512963: Epoch 7005 +2024-11-23 01:36:50.513083: Current learning rate: 0.00153 +2024-11-23 01:37:08.584809: train_loss -0.8234 +2024-11-23 01:37:08.585066: val_loss -0.7978 +2024-11-23 01:37:08.585154: Pseudo dice [0.8572] +2024-11-23 01:37:08.585246: Epoch time: 18.07 s +2024-11-23 01:37:09.474802: +2024-11-23 01:37:09.475024: Epoch 7006 +2024-11-23 01:37:09.475152: Current learning rate: 0.00153 +2024-11-23 01:37:27.851812: train_loss -0.8222 +2024-11-23 01:37:27.852019: val_loss -0.7867 +2024-11-23 01:37:27.852099: Pseudo dice [0.8478] +2024-11-23 01:37:27.852278: Epoch time: 18.38 s +2024-11-23 01:37:28.729388: +2024-11-23 01:37:28.729634: Epoch 7007 +2024-11-23 01:37:28.729742: Current learning rate: 0.00153 +2024-11-23 01:37:47.874090: train_loss -0.8198 +2024-11-23 01:37:47.874362: val_loss -0.7914 +2024-11-23 01:37:47.874462: Pseudo dice [0.8584] +2024-11-23 01:37:47.874573: Epoch time: 19.15 s +2024-11-23 01:37:48.794008: +2024-11-23 01:37:48.794246: Epoch 7008 +2024-11-23 01:37:48.794366: Current learning rate: 0.00153 +2024-11-23 01:38:08.724950: train_loss -0.8227 +2024-11-23 01:38:08.725183: val_loss -0.7652 +2024-11-23 01:38:08.725264: Pseudo dice [0.8595] +2024-11-23 01:38:08.725935: Epoch time: 19.93 s +2024-11-23 01:38:09.793083: +2024-11-23 01:38:09.793282: Epoch 7009 +2024-11-23 01:38:09.793410: Current learning rate: 0.00153 +2024-11-23 01:38:28.703743: train_loss -0.8128 +2024-11-23 01:38:28.703969: val_loss -0.7882 +2024-11-23 01:38:28.704045: Pseudo dice [0.8516] +2024-11-23 01:38:28.704131: Epoch time: 18.91 s +2024-11-23 01:38:29.728607: +2024-11-23 01:38:29.728823: Epoch 7010 +2024-11-23 01:38:29.728956: Current learning rate: 0.00153 +2024-11-23 01:38:47.812635: train_loss -0.8158 +2024-11-23 01:38:47.812871: val_loss -0.7805 +2024-11-23 01:38:47.812971: Pseudo dice [0.855] +2024-11-23 01:38:47.813074: Epoch time: 18.08 s +2024-11-23 01:38:48.703847: +2024-11-23 01:38:48.704024: Epoch 7011 +2024-11-23 01:38:48.704147: Current learning rate: 0.00152 +2024-11-23 01:39:06.453825: train_loss -0.8 +2024-11-23 01:39:06.454141: val_loss -0.7702 +2024-11-23 01:39:06.454230: Pseudo dice [0.8486] +2024-11-23 01:39:06.454314: Epoch time: 17.75 s +2024-11-23 01:39:07.339235: +2024-11-23 01:39:07.339429: Epoch 7012 +2024-11-23 01:39:07.339549: Current learning rate: 0.00152 +2024-11-23 01:39:26.500444: train_loss -0.8077 +2024-11-23 01:39:26.500653: val_loss -0.7615 +2024-11-23 01:39:26.500729: Pseudo dice [0.8446] +2024-11-23 01:39:26.500805: Epoch time: 19.16 s +2024-11-23 01:39:27.391273: +2024-11-23 01:39:27.391502: Epoch 7013 +2024-11-23 01:39:27.391618: Current learning rate: 0.00152 +2024-11-23 01:39:45.804988: train_loss -0.8188 +2024-11-23 01:39:45.805210: val_loss -0.7696 +2024-11-23 01:39:45.805289: Pseudo dice [0.857] +2024-11-23 01:39:45.810532: Epoch time: 18.41 s +2024-11-23 01:39:46.725340: +2024-11-23 01:39:46.725548: Epoch 7014 +2024-11-23 01:39:46.725674: Current learning rate: 0.00152 +2024-11-23 01:40:05.877596: train_loss -0.8105 +2024-11-23 01:40:05.877817: val_loss -0.7727 +2024-11-23 01:40:05.877925: Pseudo dice [0.8523] +2024-11-23 01:40:05.878019: Epoch time: 19.15 s +2024-11-23 01:40:07.181524: +2024-11-23 01:40:07.181726: Epoch 7015 +2024-11-23 01:40:07.181837: Current learning rate: 0.00152 +2024-11-23 01:40:25.804498: train_loss -0.8052 +2024-11-23 01:40:25.804770: val_loss -0.7908 +2024-11-23 01:40:25.804850: Pseudo dice [0.8556] +2024-11-23 01:40:25.804935: Epoch time: 18.62 s +2024-11-23 01:40:26.815296: +2024-11-23 01:40:26.815538: Epoch 7016 +2024-11-23 01:40:26.815674: Current learning rate: 0.00152 +2024-11-23 01:40:44.819177: train_loss -0.8191 +2024-11-23 01:40:44.819411: val_loss -0.7824 +2024-11-23 01:40:44.819494: Pseudo dice [0.8609] +2024-11-23 01:40:44.819582: Epoch time: 18.0 s +2024-11-23 01:40:45.706471: +2024-11-23 01:40:45.706673: Epoch 7017 +2024-11-23 01:40:45.706795: Current learning rate: 0.00152 +2024-11-23 01:41:04.068493: train_loss -0.8122 +2024-11-23 01:41:04.068724: val_loss -0.7904 +2024-11-23 01:41:04.068817: Pseudo dice [0.8668] +2024-11-23 01:41:04.068907: Epoch time: 18.36 s +2024-11-23 01:41:04.968713: +2024-11-23 01:41:04.968919: Epoch 7018 +2024-11-23 01:41:04.969037: Current learning rate: 0.00151 +2024-11-23 01:41:22.244030: train_loss -0.8226 +2024-11-23 01:41:22.244298: val_loss -0.8049 +2024-11-23 01:41:22.244392: Pseudo dice [0.8576] +2024-11-23 01:41:22.244483: Epoch time: 17.28 s +2024-11-23 01:41:23.134895: +2024-11-23 01:41:23.135122: Epoch 7019 +2024-11-23 01:41:23.135264: Current learning rate: 0.00151 +2024-11-23 01:41:41.899127: train_loss -0.8202 +2024-11-23 01:41:41.899360: val_loss -0.7881 +2024-11-23 01:41:41.899437: Pseudo dice [0.8699] +2024-11-23 01:41:41.899516: Epoch time: 18.77 s +2024-11-23 01:41:43.017489: +2024-11-23 01:41:43.017711: Epoch 7020 +2024-11-23 01:41:43.017857: Current learning rate: 0.00151 +2024-11-23 01:42:01.652941: train_loss -0.8205 +2024-11-23 01:42:01.653189: val_loss -0.7929 +2024-11-23 01:42:01.653273: Pseudo dice [0.8631] +2024-11-23 01:42:01.653358: Epoch time: 18.64 s +2024-11-23 01:42:02.540395: +2024-11-23 01:42:02.540586: Epoch 7021 +2024-11-23 01:42:02.540707: Current learning rate: 0.00151 +2024-11-23 01:42:20.886341: train_loss -0.827 +2024-11-23 01:42:20.886566: val_loss -0.8108 +2024-11-23 01:42:20.888889: Pseudo dice [0.8619] +2024-11-23 01:42:20.889007: Epoch time: 18.35 s +2024-11-23 01:42:21.812317: +2024-11-23 01:42:21.812535: Epoch 7022 +2024-11-23 01:42:21.812650: Current learning rate: 0.00151 +2024-11-23 01:42:39.489276: train_loss -0.8212 +2024-11-23 01:42:39.491710: val_loss -0.7763 +2024-11-23 01:42:39.491865: Pseudo dice [0.8629] +2024-11-23 01:42:39.491955: Epoch time: 17.68 s +2024-11-23 01:42:40.487412: +2024-11-23 01:42:40.487613: Epoch 7023 +2024-11-23 01:42:40.487731: Current learning rate: 0.00151 +2024-11-23 01:42:58.853556: train_loss -0.8137 +2024-11-23 01:42:58.853782: val_loss -0.8016 +2024-11-23 01:42:58.853876: Pseudo dice [0.8642] +2024-11-23 01:42:58.853967: Epoch time: 18.37 s +2024-11-23 01:42:59.734798: +2024-11-23 01:42:59.735016: Epoch 7024 +2024-11-23 01:42:59.735149: Current learning rate: 0.00151 +2024-11-23 01:43:17.568410: train_loss -0.8145 +2024-11-23 01:43:17.568690: val_loss -0.7766 +2024-11-23 01:43:17.568771: Pseudo dice [0.8466] +2024-11-23 01:43:17.568862: Epoch time: 17.83 s +2024-11-23 01:43:18.455064: +2024-11-23 01:43:18.455257: Epoch 7025 +2024-11-23 01:43:18.455373: Current learning rate: 0.0015 +2024-11-23 01:43:36.314735: train_loss -0.818 +2024-11-23 01:43:36.314977: val_loss -0.7821 +2024-11-23 01:43:36.315054: Pseudo dice [0.8731] +2024-11-23 01:43:36.315153: Epoch time: 17.86 s +2024-11-23 01:43:37.695778: +2024-11-23 01:43:37.695981: Epoch 7026 +2024-11-23 01:43:37.696130: Current learning rate: 0.0015 +2024-11-23 01:43:56.207578: train_loss -0.8173 +2024-11-23 01:43:56.207897: val_loss -0.7759 +2024-11-23 01:43:56.207981: Pseudo dice [0.8669] +2024-11-23 01:43:56.208066: Epoch time: 18.51 s +2024-11-23 01:43:57.115829: +2024-11-23 01:43:57.116024: Epoch 7027 +2024-11-23 01:43:57.116141: Current learning rate: 0.0015 +2024-11-23 01:44:15.613837: train_loss -0.8179 +2024-11-23 01:44:15.614092: val_loss -0.7721 +2024-11-23 01:44:15.614182: Pseudo dice [0.8519] +2024-11-23 01:44:15.614282: Epoch time: 18.5 s +2024-11-23 01:44:16.502690: +2024-11-23 01:44:16.502934: Epoch 7028 +2024-11-23 01:44:16.503048: Current learning rate: 0.0015 +2024-11-23 01:44:34.968970: train_loss -0.8086 +2024-11-23 01:44:34.969210: val_loss -0.7785 +2024-11-23 01:44:34.969291: Pseudo dice [0.8535] +2024-11-23 01:44:34.969373: Epoch time: 18.47 s +2024-11-23 01:44:35.849488: +2024-11-23 01:44:35.849880: Epoch 7029 +2024-11-23 01:44:35.850016: Current learning rate: 0.0015 +2024-11-23 01:44:55.432781: train_loss -0.8118 +2024-11-23 01:44:55.433002: val_loss -0.7721 +2024-11-23 01:44:55.433086: Pseudo dice [0.846] +2024-11-23 01:44:55.435321: Epoch time: 19.58 s +2024-11-23 01:44:56.447305: +2024-11-23 01:44:56.447529: Epoch 7030 +2024-11-23 01:44:56.447655: Current learning rate: 0.0015 +2024-11-23 01:45:14.638238: train_loss -0.8255 +2024-11-23 01:45:14.638508: val_loss -0.7791 +2024-11-23 01:45:14.638597: Pseudo dice [0.8623] +2024-11-23 01:45:14.638690: Epoch time: 18.19 s +2024-11-23 01:45:15.683972: +2024-11-23 01:45:15.684180: Epoch 7031 +2024-11-23 01:45:15.684294: Current learning rate: 0.0015 +2024-11-23 01:45:34.419865: train_loss -0.819 +2024-11-23 01:45:34.420089: val_loss -0.7772 +2024-11-23 01:45:34.420166: Pseudo dice [0.8478] +2024-11-23 01:45:34.420243: Epoch time: 18.74 s +2024-11-23 01:45:35.304735: +2024-11-23 01:45:35.304949: Epoch 7032 +2024-11-23 01:45:35.305087: Current learning rate: 0.00149 +2024-11-23 01:45:54.317380: train_loss -0.8093 +2024-11-23 01:45:54.317606: val_loss -0.7849 +2024-11-23 01:45:54.317692: Pseudo dice [0.8663] +2024-11-23 01:45:54.317774: Epoch time: 19.01 s +2024-11-23 01:45:55.353437: +2024-11-23 01:45:55.353629: Epoch 7033 +2024-11-23 01:45:55.353740: Current learning rate: 0.00149 +2024-11-23 01:46:14.039242: train_loss -0.8181 +2024-11-23 01:46:14.039488: val_loss -0.7787 +2024-11-23 01:46:14.039588: Pseudo dice [0.8656] +2024-11-23 01:46:14.039673: Epoch time: 18.69 s +2024-11-23 01:46:14.933024: +2024-11-23 01:46:14.933238: Epoch 7034 +2024-11-23 01:46:14.933369: Current learning rate: 0.00149 +2024-11-23 01:46:32.690943: train_loss -0.8214 +2024-11-23 01:46:32.691236: val_loss -0.7776 +2024-11-23 01:46:32.691316: Pseudo dice [0.8653] +2024-11-23 01:46:32.691399: Epoch time: 17.76 s +2024-11-23 01:46:33.575827: +2024-11-23 01:46:33.576047: Epoch 7035 +2024-11-23 01:46:33.576182: Current learning rate: 0.00149 +2024-11-23 01:46:53.073121: train_loss -0.8274 +2024-11-23 01:46:53.073350: val_loss -0.809 +2024-11-23 01:46:53.073434: Pseudo dice [0.8654] +2024-11-23 01:46:53.073526: Epoch time: 19.5 s +2024-11-23 01:46:54.137478: +2024-11-23 01:46:54.137690: Epoch 7036 +2024-11-23 01:46:54.137819: Current learning rate: 0.00149 +2024-11-23 01:47:11.954508: train_loss -0.8174 +2024-11-23 01:47:11.954726: val_loss -0.795 +2024-11-23 01:47:11.954804: Pseudo dice [0.8632] +2024-11-23 01:47:11.954899: Epoch time: 17.82 s +2024-11-23 01:47:13.220709: +2024-11-23 01:47:13.220962: Epoch 7037 +2024-11-23 01:47:13.221080: Current learning rate: 0.00149 +2024-11-23 01:47:31.822386: train_loss -0.818 +2024-11-23 01:47:31.822654: val_loss -0.7906 +2024-11-23 01:47:31.822747: Pseudo dice [0.86] +2024-11-23 01:47:31.822846: Epoch time: 18.6 s +2024-11-23 01:47:32.712636: +2024-11-23 01:47:32.712845: Epoch 7038 +2024-11-23 01:47:32.712955: Current learning rate: 0.00149 +2024-11-23 01:47:50.517946: train_loss -0.8208 +2024-11-23 01:47:50.518189: val_loss -0.7808 +2024-11-23 01:47:50.523682: Pseudo dice [0.8676] +2024-11-23 01:47:50.523833: Epoch time: 17.81 s +2024-11-23 01:47:51.551238: +2024-11-23 01:47:51.551469: Epoch 7039 +2024-11-23 01:47:51.551591: Current learning rate: 0.00148 +2024-11-23 01:48:10.538214: train_loss -0.8209 +2024-11-23 01:48:10.538459: val_loss -0.8063 +2024-11-23 01:48:10.538541: Pseudo dice [0.8641] +2024-11-23 01:48:10.538663: Epoch time: 18.99 s +2024-11-23 01:48:11.427256: +2024-11-23 01:48:11.427506: Epoch 7040 +2024-11-23 01:48:11.427633: Current learning rate: 0.00148 +2024-11-23 01:48:30.406345: train_loss -0.825 +2024-11-23 01:48:30.406565: val_loss -0.758 +2024-11-23 01:48:30.406649: Pseudo dice [0.8541] +2024-11-23 01:48:30.406732: Epoch time: 18.98 s +2024-11-23 01:48:31.292227: +2024-11-23 01:48:31.292442: Epoch 7041 +2024-11-23 01:48:31.292553: Current learning rate: 0.00148 +2024-11-23 01:48:49.917433: train_loss -0.8311 +2024-11-23 01:48:49.917702: val_loss -0.7835 +2024-11-23 01:48:49.917803: Pseudo dice [0.8558] +2024-11-23 01:48:49.917893: Epoch time: 18.63 s +2024-11-23 01:48:50.807518: +2024-11-23 01:48:50.807717: Epoch 7042 +2024-11-23 01:48:50.807830: Current learning rate: 0.00148 +2024-11-23 01:49:09.829073: train_loss -0.8135 +2024-11-23 01:49:09.829286: val_loss -0.7761 +2024-11-23 01:49:09.829379: Pseudo dice [0.8652] +2024-11-23 01:49:09.829456: Epoch time: 19.02 s +2024-11-23 01:49:10.714040: +2024-11-23 01:49:10.714248: Epoch 7043 +2024-11-23 01:49:10.714364: Current learning rate: 0.00148 +2024-11-23 01:49:29.441925: train_loss -0.8265 +2024-11-23 01:49:29.442151: val_loss -0.7846 +2024-11-23 01:49:29.442232: Pseudo dice [0.8667] +2024-11-23 01:49:29.442333: Epoch time: 18.73 s +2024-11-23 01:49:30.336589: +2024-11-23 01:49:30.336799: Epoch 7044 +2024-11-23 01:49:30.336911: Current learning rate: 0.00148 +2024-11-23 01:49:47.275284: train_loss -0.8232 +2024-11-23 01:49:47.275542: val_loss -0.77 +2024-11-23 01:49:47.275621: Pseudo dice [0.8502] +2024-11-23 01:49:47.275707: Epoch time: 16.94 s +2024-11-23 01:49:48.173887: +2024-11-23 01:49:48.174110: Epoch 7045 +2024-11-23 01:49:48.174222: Current learning rate: 0.00148 +2024-11-23 01:50:07.000368: train_loss -0.8165 +2024-11-23 01:50:07.000584: val_loss -0.7762 +2024-11-23 01:50:07.000661: Pseudo dice [0.8593] +2024-11-23 01:50:07.000738: Epoch time: 18.83 s +2024-11-23 01:50:07.959499: +2024-11-23 01:50:07.959721: Epoch 7046 +2024-11-23 01:50:07.959836: Current learning rate: 0.00148 +2024-11-23 01:50:26.748105: train_loss -0.8107 +2024-11-23 01:50:26.748332: val_loss -0.7874 +2024-11-23 01:50:26.748410: Pseudo dice [0.8593] +2024-11-23 01:50:26.750740: Epoch time: 18.79 s +2024-11-23 01:50:27.655753: +2024-11-23 01:50:27.655985: Epoch 7047 +2024-11-23 01:50:27.656138: Current learning rate: 0.00147 +2024-11-23 01:50:46.827596: train_loss -0.8281 +2024-11-23 01:50:46.827809: val_loss -0.8074 +2024-11-23 01:50:46.827883: Pseudo dice [0.8645] +2024-11-23 01:50:46.827960: Epoch time: 19.17 s +2024-11-23 01:50:48.220343: +2024-11-23 01:50:48.220539: Epoch 7048 +2024-11-23 01:50:48.220645: Current learning rate: 0.00147 +2024-11-23 01:51:06.884272: train_loss -0.822 +2024-11-23 01:51:06.884515: val_loss -0.7863 +2024-11-23 01:51:06.884598: Pseudo dice [0.8532] +2024-11-23 01:51:06.884689: Epoch time: 18.66 s +2024-11-23 01:51:07.805019: +2024-11-23 01:51:07.805249: Epoch 7049 +2024-11-23 01:51:07.805380: Current learning rate: 0.00147 +2024-11-23 01:51:26.901965: train_loss -0.8206 +2024-11-23 01:51:26.902202: val_loss -0.7907 +2024-11-23 01:51:26.902279: Pseudo dice [0.8602] +2024-11-23 01:51:26.902356: Epoch time: 19.1 s +2024-11-23 01:51:28.120993: +2024-11-23 01:51:28.121211: Epoch 7050 +2024-11-23 01:51:28.121351: Current learning rate: 0.00147 +2024-11-23 01:51:47.439008: train_loss -0.8184 +2024-11-23 01:51:47.439236: val_loss -0.7702 +2024-11-23 01:51:47.439312: Pseudo dice [0.845] +2024-11-23 01:51:47.439391: Epoch time: 19.32 s +2024-11-23 01:51:48.335441: +2024-11-23 01:51:48.335649: Epoch 7051 +2024-11-23 01:51:48.335767: Current learning rate: 0.00147 +2024-11-23 01:52:06.336685: train_loss -0.8171 +2024-11-23 01:52:06.336958: val_loss -0.8019 +2024-11-23 01:52:06.337088: Pseudo dice [0.8671] +2024-11-23 01:52:06.337177: Epoch time: 18.0 s +2024-11-23 01:52:07.230066: +2024-11-23 01:52:07.230284: Epoch 7052 +2024-11-23 01:52:07.230397: Current learning rate: 0.00147 +2024-11-23 01:52:24.260619: train_loss -0.8202 +2024-11-23 01:52:24.260885: val_loss -0.792 +2024-11-23 01:52:24.260976: Pseudo dice [0.8516] +2024-11-23 01:52:24.261096: Epoch time: 17.03 s +2024-11-23 01:52:25.152200: +2024-11-23 01:52:25.152420: Epoch 7053 +2024-11-23 01:52:25.152556: Current learning rate: 0.00147 +2024-11-23 01:52:43.930576: train_loss -0.8191 +2024-11-23 01:52:43.930802: val_loss -0.7694 +2024-11-23 01:52:43.930884: Pseudo dice [0.8522] +2024-11-23 01:52:43.930972: Epoch time: 18.78 s +2024-11-23 01:52:44.821840: +2024-11-23 01:52:44.822029: Epoch 7054 +2024-11-23 01:52:44.822153: Current learning rate: 0.00146 +2024-11-23 01:53:03.567025: train_loss -0.8146 +2024-11-23 01:53:03.567253: val_loss -0.7973 +2024-11-23 01:53:03.572563: Pseudo dice [0.858] +2024-11-23 01:53:03.572713: Epoch time: 18.75 s +2024-11-23 01:53:04.476091: +2024-11-23 01:53:04.476336: Epoch 7055 +2024-11-23 01:53:04.476493: Current learning rate: 0.00146 +2024-11-23 01:53:22.823460: train_loss -0.8157 +2024-11-23 01:53:22.823706: val_loss -0.7765 +2024-11-23 01:53:22.823846: Pseudo dice [0.8453] +2024-11-23 01:53:22.823952: Epoch time: 18.35 s +2024-11-23 01:53:23.715754: +2024-11-23 01:53:23.715944: Epoch 7056 +2024-11-23 01:53:23.716062: Current learning rate: 0.00146 +2024-11-23 01:53:42.208678: train_loss -0.8164 +2024-11-23 01:53:42.208906: val_loss -0.7812 +2024-11-23 01:53:42.208984: Pseudo dice [0.8516] +2024-11-23 01:53:42.209070: Epoch time: 18.49 s +2024-11-23 01:53:43.094637: +2024-11-23 01:53:43.094820: Epoch 7057 +2024-11-23 01:53:43.094936: Current learning rate: 0.00146 +2024-11-23 01:54:02.336870: train_loss -0.8148 +2024-11-23 01:54:02.337101: val_loss -0.7605 +2024-11-23 01:54:02.337185: Pseudo dice [0.8424] +2024-11-23 01:54:02.337283: Epoch time: 19.24 s +2024-11-23 01:54:03.252589: +2024-11-23 01:54:03.252805: Epoch 7058 +2024-11-23 01:54:03.252926: Current learning rate: 0.00146 +2024-11-23 01:54:21.572866: train_loss -0.8165 +2024-11-23 01:54:21.573173: val_loss -0.7975 +2024-11-23 01:54:21.573251: Pseudo dice [0.8557] +2024-11-23 01:54:21.573338: Epoch time: 18.32 s +2024-11-23 01:54:22.851808: +2024-11-23 01:54:22.852044: Epoch 7059 +2024-11-23 01:54:22.852172: Current learning rate: 0.00146 +2024-11-23 01:54:41.632501: train_loss -0.8118 +2024-11-23 01:54:41.632746: val_loss -0.7771 +2024-11-23 01:54:41.632831: Pseudo dice [0.8609] +2024-11-23 01:54:41.632911: Epoch time: 18.78 s +2024-11-23 01:54:42.518317: +2024-11-23 01:54:42.518527: Epoch 7060 +2024-11-23 01:54:42.518649: Current learning rate: 0.00146 +2024-11-23 01:55:00.682013: train_loss -0.8163 +2024-11-23 01:55:00.682292: val_loss -0.7959 +2024-11-23 01:55:00.682373: Pseudo dice [0.8641] +2024-11-23 01:55:00.682459: Epoch time: 18.16 s +2024-11-23 01:55:01.576579: +2024-11-23 01:55:01.576796: Epoch 7061 +2024-11-23 01:55:01.576921: Current learning rate: 0.00145 +2024-11-23 01:55:19.873732: train_loss -0.8136 +2024-11-23 01:55:19.876106: val_loss -0.7949 +2024-11-23 01:55:19.876205: Pseudo dice [0.8651] +2024-11-23 01:55:19.876290: Epoch time: 18.3 s +2024-11-23 01:55:20.783000: +2024-11-23 01:55:20.783205: Epoch 7062 +2024-11-23 01:55:20.783318: Current learning rate: 0.00145 +2024-11-23 01:55:39.927546: train_loss -0.8218 +2024-11-23 01:55:39.927780: val_loss -0.7833 +2024-11-23 01:55:39.927864: Pseudo dice [0.8595] +2024-11-23 01:55:39.927961: Epoch time: 19.15 s +2024-11-23 01:55:40.813765: +2024-11-23 01:55:40.813965: Epoch 7063 +2024-11-23 01:55:40.814079: Current learning rate: 0.00145 +2024-11-23 01:55:58.177730: train_loss -0.8181 +2024-11-23 01:55:58.178049: val_loss -0.7625 +2024-11-23 01:55:58.178137: Pseudo dice [0.856] +2024-11-23 01:55:58.178216: Epoch time: 17.36 s +2024-11-23 01:55:59.072770: +2024-11-23 01:55:59.073047: Epoch 7064 +2024-11-23 01:55:59.073186: Current learning rate: 0.00145 +2024-11-23 01:56:17.065658: train_loss -0.8206 +2024-11-23 01:56:17.065875: val_loss -0.7741 +2024-11-23 01:56:17.065956: Pseudo dice [0.8705] +2024-11-23 01:56:17.066055: Epoch time: 17.99 s +2024-11-23 01:56:17.963142: +2024-11-23 01:56:17.963355: Epoch 7065 +2024-11-23 01:56:17.963469: Current learning rate: 0.00145 +2024-11-23 01:56:37.924905: train_loss -0.8102 +2024-11-23 01:56:37.925120: val_loss -0.7924 +2024-11-23 01:56:37.925198: Pseudo dice [0.8615] +2024-11-23 01:56:37.925281: Epoch time: 19.96 s +2024-11-23 01:56:38.811447: +2024-11-23 01:56:38.811661: Epoch 7066 +2024-11-23 01:56:38.811767: Current learning rate: 0.00145 +2024-11-23 01:56:56.595389: train_loss -0.8252 +2024-11-23 01:56:56.595665: val_loss -0.7963 +2024-11-23 01:56:56.595758: Pseudo dice [0.8614] +2024-11-23 01:56:56.595841: Epoch time: 17.78 s +2024-11-23 01:56:57.485022: +2024-11-23 01:56:57.485219: Epoch 7067 +2024-11-23 01:56:57.485337: Current learning rate: 0.00145 +2024-11-23 01:57:15.800693: train_loss -0.8167 +2024-11-23 01:57:15.800903: val_loss -0.7929 +2024-11-23 01:57:15.800983: Pseudo dice [0.8719] +2024-11-23 01:57:15.801083: Epoch time: 18.32 s +2024-11-23 01:57:16.683062: +2024-11-23 01:57:16.683278: Epoch 7068 +2024-11-23 01:57:16.683406: Current learning rate: 0.00144 +2024-11-23 01:57:34.624836: train_loss -0.8212 +2024-11-23 01:57:34.625085: val_loss -0.7795 +2024-11-23 01:57:34.625183: Pseudo dice [0.8653] +2024-11-23 01:57:34.625278: Epoch time: 17.94 s +2024-11-23 01:57:35.509802: +2024-11-23 01:57:35.510028: Epoch 7069 +2024-11-23 01:57:35.510145: Current learning rate: 0.00144 +2024-11-23 01:57:54.150963: train_loss -0.8242 +2024-11-23 01:57:54.151258: val_loss -0.7711 +2024-11-23 01:57:54.151338: Pseudo dice [0.8661] +2024-11-23 01:57:54.151424: Epoch time: 18.64 s +2024-11-23 01:57:55.484069: +2024-11-23 01:57:55.484271: Epoch 7070 +2024-11-23 01:57:55.484383: Current learning rate: 0.00144 +2024-11-23 01:58:13.664847: train_loss -0.8217 +2024-11-23 01:58:13.665093: val_loss -0.7973 +2024-11-23 01:58:13.665189: Pseudo dice [0.8548] +2024-11-23 01:58:13.665286: Epoch time: 18.18 s +2024-11-23 01:58:14.549472: +2024-11-23 01:58:14.549686: Epoch 7071 +2024-11-23 01:58:14.549800: Current learning rate: 0.00144 +2024-11-23 01:58:33.220519: train_loss -0.818 +2024-11-23 01:58:33.225875: val_loss -0.7455 +2024-11-23 01:58:33.226023: Pseudo dice [0.8671] +2024-11-23 01:58:33.226115: Epoch time: 18.67 s +2024-11-23 01:58:34.121044: +2024-11-23 01:58:34.121323: Epoch 7072 +2024-11-23 01:58:34.121449: Current learning rate: 0.00144 +2024-11-23 01:58:53.291352: train_loss -0.8196 +2024-11-23 01:58:53.291589: val_loss -0.7783 +2024-11-23 01:58:53.291687: Pseudo dice [0.8639] +2024-11-23 01:58:53.291775: Epoch time: 19.17 s +2024-11-23 01:58:53.291851: Yayy! New best EMA pseudo Dice: 0.8616 +2024-11-23 01:58:54.542109: +2024-11-23 01:58:54.542325: Epoch 7073 +2024-11-23 01:58:54.542443: Current learning rate: 0.00144 +2024-11-23 01:59:12.511752: train_loss -0.8234 +2024-11-23 01:59:12.514163: val_loss -0.7502 +2024-11-23 01:59:12.514257: Pseudo dice [0.8371] +2024-11-23 01:59:12.514338: Epoch time: 17.97 s +2024-11-23 01:59:13.548410: +2024-11-23 01:59:13.548601: Epoch 7074 +2024-11-23 01:59:13.548708: Current learning rate: 0.00144 +2024-11-23 01:59:31.380349: train_loss -0.8137 +2024-11-23 01:59:31.380577: val_loss -0.747 +2024-11-23 01:59:31.380667: Pseudo dice [0.854] +2024-11-23 01:59:31.380744: Epoch time: 17.83 s +2024-11-23 01:59:32.266346: +2024-11-23 01:59:32.266562: Epoch 7075 +2024-11-23 01:59:32.266675: Current learning rate: 0.00143 +2024-11-23 01:59:51.897455: train_loss -0.8146 +2024-11-23 01:59:51.897661: val_loss -0.794 +2024-11-23 01:59:51.897737: Pseudo dice [0.8615] +2024-11-23 01:59:51.897813: Epoch time: 19.63 s +2024-11-23 01:59:52.806891: +2024-11-23 01:59:52.807098: Epoch 7076 +2024-11-23 01:59:52.807217: Current learning rate: 0.00143 +2024-11-23 02:00:09.996243: train_loss -0.8249 +2024-11-23 02:00:09.996523: val_loss -0.7945 +2024-11-23 02:00:09.996602: Pseudo dice [0.8515] +2024-11-23 02:00:09.996688: Epoch time: 17.19 s +2024-11-23 02:00:10.887716: +2024-11-23 02:00:10.887926: Epoch 7077 +2024-11-23 02:00:10.888072: Current learning rate: 0.00143 +2024-11-23 02:00:29.567189: train_loss -0.8141 +2024-11-23 02:00:29.567408: val_loss -0.7623 +2024-11-23 02:00:29.567484: Pseudo dice [0.8521] +2024-11-23 02:00:29.567577: Epoch time: 18.68 s +2024-11-23 02:00:30.465793: +2024-11-23 02:00:30.466012: Epoch 7078 +2024-11-23 02:00:30.466141: Current learning rate: 0.00143 +2024-11-23 02:00:48.092215: train_loss -0.8144 +2024-11-23 02:00:48.092431: val_loss -0.7727 +2024-11-23 02:00:48.092515: Pseudo dice [0.8491] +2024-11-23 02:00:48.092603: Epoch time: 17.63 s +2024-11-23 02:00:48.976436: +2024-11-23 02:00:48.976708: Epoch 7079 +2024-11-23 02:00:48.978009: Current learning rate: 0.00143 +2024-11-23 02:01:07.264820: train_loss -0.8219 +2024-11-23 02:01:07.267191: val_loss -0.7739 +2024-11-23 02:01:07.267332: Pseudo dice [0.8598] +2024-11-23 02:01:07.267414: Epoch time: 18.29 s +2024-11-23 02:01:08.287907: +2024-11-23 02:01:08.288121: Epoch 7080 +2024-11-23 02:01:08.288230: Current learning rate: 0.00143 +2024-11-23 02:01:27.400292: train_loss -0.8145 +2024-11-23 02:01:27.400522: val_loss -0.788 +2024-11-23 02:01:27.400851: Pseudo dice [0.8696] +2024-11-23 02:01:27.400939: Epoch time: 19.11 s +2024-11-23 02:01:28.713308: +2024-11-23 02:01:28.713533: Epoch 7081 +2024-11-23 02:01:28.713666: Current learning rate: 0.00143 +2024-11-23 02:01:46.704432: train_loss -0.8248 +2024-11-23 02:01:46.704701: val_loss -0.7721 +2024-11-23 02:01:46.704780: Pseudo dice [0.861] +2024-11-23 02:01:46.704854: Epoch time: 17.99 s +2024-11-23 02:01:47.595578: +2024-11-23 02:01:47.595781: Epoch 7082 +2024-11-23 02:01:47.595900: Current learning rate: 0.00142 +2024-11-23 02:02:04.686601: train_loss -0.8181 +2024-11-23 02:02:04.686806: val_loss -0.7586 +2024-11-23 02:02:04.686885: Pseudo dice [0.8524] +2024-11-23 02:02:04.686974: Epoch time: 17.09 s +2024-11-23 02:02:05.845936: +2024-11-23 02:02:05.846146: Epoch 7083 +2024-11-23 02:02:05.846265: Current learning rate: 0.00142 +2024-11-23 02:02:23.742664: train_loss -0.8228 +2024-11-23 02:02:23.742878: val_loss -0.7816 +2024-11-23 02:02:23.742980: Pseudo dice [0.862] +2024-11-23 02:02:23.743085: Epoch time: 17.9 s +2024-11-23 02:02:24.629955: +2024-11-23 02:02:24.630203: Epoch 7084 +2024-11-23 02:02:24.630320: Current learning rate: 0.00142 +2024-11-23 02:02:42.587601: train_loss -0.8255 +2024-11-23 02:02:42.593027: val_loss -0.7781 +2024-11-23 02:02:42.593209: Pseudo dice [0.8598] +2024-11-23 02:02:42.593314: Epoch time: 17.96 s +2024-11-23 02:02:43.515222: +2024-11-23 02:02:43.515467: Epoch 7085 +2024-11-23 02:02:43.515580: Current learning rate: 0.00142 +2024-11-23 02:03:02.288689: train_loss -0.8186 +2024-11-23 02:03:02.288897: val_loss -0.7834 +2024-11-23 02:03:02.288976: Pseudo dice [0.8714] +2024-11-23 02:03:02.289090: Epoch time: 18.77 s +2024-11-23 02:03:03.174572: +2024-11-23 02:03:03.174781: Epoch 7086 +2024-11-23 02:03:03.174894: Current learning rate: 0.00142 +2024-11-23 02:03:20.897989: train_loss -0.8189 +2024-11-23 02:03:20.902642: val_loss -0.7823 +2024-11-23 02:03:20.902781: Pseudo dice [0.8539] +2024-11-23 02:03:20.902866: Epoch time: 17.72 s +2024-11-23 02:03:22.149994: +2024-11-23 02:03:22.150233: Epoch 7087 +2024-11-23 02:03:22.150363: Current learning rate: 0.00142 +2024-11-23 02:03:40.523449: train_loss -0.8131 +2024-11-23 02:03:40.523698: val_loss -0.7834 +2024-11-23 02:03:40.523840: Pseudo dice [0.8583] +2024-11-23 02:03:40.523957: Epoch time: 18.37 s +2024-11-23 02:03:41.418136: +2024-11-23 02:03:41.418345: Epoch 7088 +2024-11-23 02:03:41.418457: Current learning rate: 0.00142 +2024-11-23 02:04:00.018719: train_loss -0.8141 +2024-11-23 02:04:00.018946: val_loss -0.7964 +2024-11-23 02:04:00.019032: Pseudo dice [0.8681] +2024-11-23 02:04:00.019124: Epoch time: 18.6 s +2024-11-23 02:04:00.905461: +2024-11-23 02:04:00.905714: Epoch 7089 +2024-11-23 02:04:00.905827: Current learning rate: 0.00142 +2024-11-23 02:04:18.346910: train_loss -0.8228 +2024-11-23 02:04:18.347139: val_loss -0.7766 +2024-11-23 02:04:18.347220: Pseudo dice [0.8622] +2024-11-23 02:04:18.347318: Epoch time: 17.44 s +2024-11-23 02:04:19.240478: +2024-11-23 02:04:19.240708: Epoch 7090 +2024-11-23 02:04:19.240833: Current learning rate: 0.00141 +2024-11-23 02:04:37.413178: train_loss -0.8204 +2024-11-23 02:04:37.413413: val_loss -0.7726 +2024-11-23 02:04:37.413493: Pseudo dice [0.8531] +2024-11-23 02:04:37.413576: Epoch time: 18.17 s +2024-11-23 02:04:38.301920: +2024-11-23 02:04:38.302134: Epoch 7091 +2024-11-23 02:04:38.302249: Current learning rate: 0.00141 +2024-11-23 02:04:56.575211: train_loss -0.8193 +2024-11-23 02:04:56.575462: val_loss -0.7869 +2024-11-23 02:04:56.575561: Pseudo dice [0.858] +2024-11-23 02:04:56.575655: Epoch time: 18.27 s +2024-11-23 02:04:57.872878: +2024-11-23 02:04:57.873085: Epoch 7092 +2024-11-23 02:04:57.873199: Current learning rate: 0.00141 +2024-11-23 02:05:15.759003: train_loss -0.8186 +2024-11-23 02:05:15.759226: val_loss -0.7598 +2024-11-23 02:05:15.759309: Pseudo dice [0.8555] +2024-11-23 02:05:15.759384: Epoch time: 17.89 s +2024-11-23 02:05:16.755137: +2024-11-23 02:05:16.755360: Epoch 7093 +2024-11-23 02:05:16.755490: Current learning rate: 0.00141 +2024-11-23 02:05:35.520009: train_loss -0.8122 +2024-11-23 02:05:35.520236: val_loss -0.7824 +2024-11-23 02:05:35.520324: Pseudo dice [0.8653] +2024-11-23 02:05:35.520416: Epoch time: 18.77 s +2024-11-23 02:05:36.405528: +2024-11-23 02:05:36.405773: Epoch 7094 +2024-11-23 02:05:36.405893: Current learning rate: 0.00141 +2024-11-23 02:05:55.760030: train_loss -0.8129 +2024-11-23 02:05:55.760247: val_loss -0.7731 +2024-11-23 02:05:55.760331: Pseudo dice [0.8687] +2024-11-23 02:05:55.760412: Epoch time: 19.36 s +2024-11-23 02:05:56.651771: +2024-11-23 02:05:56.651998: Epoch 7095 +2024-11-23 02:05:56.652134: Current learning rate: 0.00141 +2024-11-23 02:06:14.642013: train_loss -0.8179 +2024-11-23 02:06:14.642262: val_loss -0.7764 +2024-11-23 02:06:14.642356: Pseudo dice [0.8554] +2024-11-23 02:06:14.642438: Epoch time: 17.99 s +2024-11-23 02:06:15.535292: +2024-11-23 02:06:15.535492: Epoch 7096 +2024-11-23 02:06:15.535607: Current learning rate: 0.00141 +2024-11-23 02:06:34.030832: train_loss -0.8113 +2024-11-23 02:06:34.033262: val_loss -0.7781 +2024-11-23 02:06:34.033379: Pseudo dice [0.8614] +2024-11-23 02:06:34.033460: Epoch time: 18.5 s +2024-11-23 02:06:35.042641: +2024-11-23 02:06:35.042863: Epoch 7097 +2024-11-23 02:06:35.042974: Current learning rate: 0.0014 +2024-11-23 02:06:53.837031: train_loss -0.8185 +2024-11-23 02:06:53.837340: val_loss -0.7911 +2024-11-23 02:06:53.837441: Pseudo dice [0.852] +2024-11-23 02:06:53.837538: Epoch time: 18.8 s +2024-11-23 02:06:54.728480: +2024-11-23 02:06:54.728691: Epoch 7098 +2024-11-23 02:06:54.728818: Current learning rate: 0.0014 +2024-11-23 02:07:12.559440: train_loss -0.8103 +2024-11-23 02:07:12.559748: val_loss -0.7645 +2024-11-23 02:07:12.559837: Pseudo dice [0.8637] +2024-11-23 02:07:12.559929: Epoch time: 17.83 s +2024-11-23 02:07:13.450365: +2024-11-23 02:07:13.450577: Epoch 7099 +2024-11-23 02:07:13.450713: Current learning rate: 0.0014 +2024-11-23 02:07:31.216262: train_loss -0.8228 +2024-11-23 02:07:31.216482: val_loss -0.7826 +2024-11-23 02:07:31.216577: Pseudo dice [0.8663] +2024-11-23 02:07:31.216656: Epoch time: 17.77 s +2024-11-23 02:07:32.537546: +2024-11-23 02:07:32.537745: Epoch 7100 +2024-11-23 02:07:32.537859: Current learning rate: 0.0014 +2024-11-23 02:07:51.350209: train_loss -0.8194 +2024-11-23 02:07:51.350423: val_loss -0.7978 +2024-11-23 02:07:51.350514: Pseudo dice [0.8685] +2024-11-23 02:07:51.350609: Epoch time: 18.81 s +2024-11-23 02:07:52.331593: +2024-11-23 02:07:52.331806: Epoch 7101 +2024-11-23 02:07:52.331919: Current learning rate: 0.0014 +2024-11-23 02:08:10.792259: train_loss -0.8202 +2024-11-23 02:08:10.792482: val_loss -0.7882 +2024-11-23 02:08:10.792564: Pseudo dice [0.8654] +2024-11-23 02:08:10.792639: Epoch time: 18.46 s +2024-11-23 02:08:10.792701: Yayy! New best EMA pseudo Dice: 0.8617 +2024-11-23 02:08:12.004262: +2024-11-23 02:08:12.004483: Epoch 7102 +2024-11-23 02:08:12.004619: Current learning rate: 0.0014 +2024-11-23 02:08:30.919029: train_loss -0.8172 +2024-11-23 02:08:30.919319: val_loss -0.7816 +2024-11-23 02:08:30.919402: Pseudo dice [0.8467] +2024-11-23 02:08:30.919516: Epoch time: 18.91 s +2024-11-23 02:08:32.415456: +2024-11-23 02:08:32.415668: Epoch 7103 +2024-11-23 02:08:32.415795: Current learning rate: 0.0014 +2024-11-23 02:08:50.021819: train_loss -0.8201 +2024-11-23 02:08:50.022082: val_loss -0.7904 +2024-11-23 02:08:50.022163: Pseudo dice [0.8534] +2024-11-23 02:08:50.022242: Epoch time: 17.61 s +2024-11-23 02:08:50.905367: +2024-11-23 02:08:50.905600: Epoch 7104 +2024-11-23 02:08:50.905715: Current learning rate: 0.00139 +2024-11-23 02:09:08.642945: train_loss -0.8248 +2024-11-23 02:09:08.643151: val_loss -0.7747 +2024-11-23 02:09:08.643227: Pseudo dice [0.8596] +2024-11-23 02:09:08.643306: Epoch time: 17.74 s +2024-11-23 02:09:09.732386: +2024-11-23 02:09:09.732603: Epoch 7105 +2024-11-23 02:09:09.732714: Current learning rate: 0.00139 +2024-11-23 02:09:26.906272: train_loss -0.8248 +2024-11-23 02:09:26.906479: val_loss -0.7774 +2024-11-23 02:09:26.906563: Pseudo dice [0.8695] +2024-11-23 02:09:26.906644: Epoch time: 17.17 s +2024-11-23 02:09:27.797143: +2024-11-23 02:09:27.797355: Epoch 7106 +2024-11-23 02:09:27.797465: Current learning rate: 0.00139 +2024-11-23 02:09:45.934723: train_loss -0.8244 +2024-11-23 02:09:45.935248: val_loss -0.751 +2024-11-23 02:09:45.935354: Pseudo dice [0.8435] +2024-11-23 02:09:45.935450: Epoch time: 18.14 s +2024-11-23 02:09:46.834185: +2024-11-23 02:09:46.834388: Epoch 7107 +2024-11-23 02:09:46.834514: Current learning rate: 0.00139 +2024-11-23 02:10:04.839092: train_loss -0.8213 +2024-11-23 02:10:04.839309: val_loss -0.7598 +2024-11-23 02:10:04.839386: Pseudo dice [0.8592] +2024-11-23 02:10:04.839466: Epoch time: 18.01 s +2024-11-23 02:10:05.728376: +2024-11-23 02:10:05.728593: Epoch 7108 +2024-11-23 02:10:05.728703: Current learning rate: 0.00139 +2024-11-23 02:10:23.993827: train_loss -0.8228 +2024-11-23 02:10:23.994046: val_loss -0.7609 +2024-11-23 02:10:23.994147: Pseudo dice [0.8576] +2024-11-23 02:10:23.994234: Epoch time: 18.27 s +2024-11-23 02:10:24.884797: +2024-11-23 02:10:24.885012: Epoch 7109 +2024-11-23 02:10:24.885149: Current learning rate: 0.00139 +2024-11-23 02:10:43.827201: train_loss -0.8219 +2024-11-23 02:10:43.829554: val_loss -0.7413 +2024-11-23 02:10:43.829764: Pseudo dice [0.8563] +2024-11-23 02:10:43.829853: Epoch time: 18.94 s +2024-11-23 02:10:44.736116: +2024-11-23 02:10:44.736325: Epoch 7110 +2024-11-23 02:10:44.736445: Current learning rate: 0.00139 +2024-11-23 02:11:03.687375: train_loss -0.8175 +2024-11-23 02:11:03.687598: val_loss -0.7968 +2024-11-23 02:11:03.687672: Pseudo dice [0.869] +2024-11-23 02:11:03.687754: Epoch time: 18.95 s +2024-11-23 02:11:04.592502: +2024-11-23 02:11:04.592718: Epoch 7111 +2024-11-23 02:11:04.592846: Current learning rate: 0.00138 +2024-11-23 02:11:22.745735: train_loss -0.8234 +2024-11-23 02:11:22.745953: val_loss -0.7858 +2024-11-23 02:11:22.746040: Pseudo dice [0.8696] +2024-11-23 02:11:22.746124: Epoch time: 18.15 s +2024-11-23 02:11:23.745846: +2024-11-23 02:11:23.746039: Epoch 7112 +2024-11-23 02:11:23.746155: Current learning rate: 0.00138 +2024-11-23 02:11:42.403250: train_loss -0.8149 +2024-11-23 02:11:42.403482: val_loss -0.7631 +2024-11-23 02:11:42.403559: Pseudo dice [0.8573] +2024-11-23 02:11:42.403652: Epoch time: 18.66 s +2024-11-23 02:11:43.289273: +2024-11-23 02:11:43.289486: Epoch 7113 +2024-11-23 02:11:43.289598: Current learning rate: 0.00138 +2024-11-23 02:12:02.308959: train_loss -0.8222 +2024-11-23 02:12:02.309829: val_loss -0.7934 +2024-11-23 02:12:02.309922: Pseudo dice [0.8633] +2024-11-23 02:12:02.310007: Epoch time: 19.02 s +2024-11-23 02:12:03.617817: +2024-11-23 02:12:03.618014: Epoch 7114 +2024-11-23 02:12:03.618131: Current learning rate: 0.00138 +2024-11-23 02:12:22.182783: train_loss -0.8238 +2024-11-23 02:12:22.183004: val_loss -0.7856 +2024-11-23 02:12:22.183096: Pseudo dice [0.8657] +2024-11-23 02:12:22.183177: Epoch time: 18.57 s +2024-11-23 02:12:23.070439: +2024-11-23 02:12:23.070637: Epoch 7115 +2024-11-23 02:12:23.070763: Current learning rate: 0.00138 +2024-11-23 02:12:40.120005: train_loss -0.8232 +2024-11-23 02:12:40.120275: val_loss -0.7757 +2024-11-23 02:12:40.120350: Pseudo dice [0.8557] +2024-11-23 02:12:40.120432: Epoch time: 17.05 s +2024-11-23 02:12:41.012078: +2024-11-23 02:12:41.012292: Epoch 7116 +2024-11-23 02:12:41.012403: Current learning rate: 0.00138 +2024-11-23 02:12:58.746389: train_loss -0.8214 +2024-11-23 02:12:58.746618: val_loss -0.7833 +2024-11-23 02:12:58.746699: Pseudo dice [0.8618] +2024-11-23 02:12:58.746782: Epoch time: 17.74 s +2024-11-23 02:12:59.644439: +2024-11-23 02:12:59.644633: Epoch 7117 +2024-11-23 02:12:59.644749: Current learning rate: 0.00138 +2024-11-23 02:13:18.800939: train_loss -0.8179 +2024-11-23 02:13:18.801172: val_loss -0.783 +2024-11-23 02:13:18.801262: Pseudo dice [0.8588] +2024-11-23 02:13:18.801356: Epoch time: 19.16 s +2024-11-23 02:13:19.692735: +2024-11-23 02:13:19.692948: Epoch 7118 +2024-11-23 02:13:19.693057: Current learning rate: 0.00137 +2024-11-23 02:13:37.414836: train_loss -0.8199 +2024-11-23 02:13:37.415054: val_loss -0.7982 +2024-11-23 02:13:37.415135: Pseudo dice [0.8627] +2024-11-23 02:13:37.415210: Epoch time: 17.72 s +2024-11-23 02:13:38.307208: +2024-11-23 02:13:38.307419: Epoch 7119 +2024-11-23 02:13:38.307541: Current learning rate: 0.00137 +2024-11-23 02:13:56.019091: train_loss -0.8219 +2024-11-23 02:13:56.019312: val_loss -0.7797 +2024-11-23 02:13:56.019392: Pseudo dice [0.8716] +2024-11-23 02:13:56.019490: Epoch time: 17.71 s +2024-11-23 02:13:56.019553: Yayy! New best EMA pseudo Dice: 0.8618 +2024-11-23 02:13:57.260201: +2024-11-23 02:13:57.260434: Epoch 7120 +2024-11-23 02:13:57.260550: Current learning rate: 0.00137 +2024-11-23 02:14:14.375890: train_loss -0.8229 +2024-11-23 02:14:14.378298: val_loss -0.7827 +2024-11-23 02:14:14.378415: Pseudo dice [0.8571] +2024-11-23 02:14:14.378509: Epoch time: 17.12 s +2024-11-23 02:14:15.307435: +2024-11-23 02:14:15.307655: Epoch 7121 +2024-11-23 02:14:15.307772: Current learning rate: 0.00137 +2024-11-23 02:14:34.975031: train_loss -0.82 +2024-11-23 02:14:34.975245: val_loss -0.7745 +2024-11-23 02:14:34.975322: Pseudo dice [0.868] +2024-11-23 02:14:34.975406: Epoch time: 19.67 s +2024-11-23 02:14:34.975483: Yayy! New best EMA pseudo Dice: 0.862 +2024-11-23 02:14:36.193158: +2024-11-23 02:14:36.193355: Epoch 7122 +2024-11-23 02:14:36.193463: Current learning rate: 0.00137 +2024-11-23 02:14:54.580491: train_loss -0.8216 +2024-11-23 02:14:54.580703: val_loss -0.7847 +2024-11-23 02:14:54.580777: Pseudo dice [0.8649] +2024-11-23 02:14:54.580863: Epoch time: 18.39 s +2024-11-23 02:14:54.580925: Yayy! New best EMA pseudo Dice: 0.8623 +2024-11-23 02:14:55.792910: +2024-11-23 02:14:55.793115: Epoch 7123 +2024-11-23 02:14:55.793241: Current learning rate: 0.00137 +2024-11-23 02:15:14.233859: train_loss -0.8214 +2024-11-23 02:15:14.234098: val_loss -0.7841 +2024-11-23 02:15:14.234175: Pseudo dice [0.8604] +2024-11-23 02:15:14.234251: Epoch time: 18.44 s +2024-11-23 02:15:15.231128: +2024-11-23 02:15:15.231341: Epoch 7124 +2024-11-23 02:15:15.231457: Current learning rate: 0.00137 +2024-11-23 02:15:34.261003: train_loss -0.8168 +2024-11-23 02:15:34.261508: val_loss -0.7664 +2024-11-23 02:15:34.261621: Pseudo dice [0.8584] +2024-11-23 02:15:34.261711: Epoch time: 19.03 s +2024-11-23 02:15:35.257546: +2024-11-23 02:15:35.257755: Epoch 7125 +2024-11-23 02:15:35.257869: Current learning rate: 0.00136 +2024-11-23 02:15:53.283757: train_loss -0.825 +2024-11-23 02:15:53.283961: val_loss -0.7905 +2024-11-23 02:15:53.284042: Pseudo dice [0.8634] +2024-11-23 02:15:53.284122: Epoch time: 18.03 s +2024-11-23 02:15:54.169923: +2024-11-23 02:15:54.170148: Epoch 7126 +2024-11-23 02:15:54.170273: Current learning rate: 0.00136 +2024-11-23 02:16:12.472394: train_loss -0.8291 +2024-11-23 02:16:12.472624: val_loss -0.8066 +2024-11-23 02:16:12.472717: Pseudo dice [0.8659] +2024-11-23 02:16:12.472797: Epoch time: 18.3 s +2024-11-23 02:16:12.472871: Yayy! New best EMA pseudo Dice: 0.8623 +2024-11-23 02:16:13.700109: +2024-11-23 02:16:13.700317: Epoch 7127 +2024-11-23 02:16:13.700435: Current learning rate: 0.00136 +2024-11-23 02:16:32.549027: train_loss -0.8251 +2024-11-23 02:16:32.549239: val_loss -0.7683 +2024-11-23 02:16:32.550729: Pseudo dice [0.8482] +2024-11-23 02:16:32.552480: Epoch time: 18.85 s +2024-11-23 02:16:33.589990: +2024-11-23 02:16:33.590201: Epoch 7128 +2024-11-23 02:16:33.590312: Current learning rate: 0.00136 +2024-11-23 02:16:51.656489: train_loss -0.8257 +2024-11-23 02:16:51.656738: val_loss -0.766 +2024-11-23 02:16:51.656818: Pseudo dice [0.8524] +2024-11-23 02:16:51.656913: Epoch time: 18.07 s +2024-11-23 02:16:52.559031: +2024-11-23 02:16:52.559247: Epoch 7129 +2024-11-23 02:16:52.559365: Current learning rate: 0.00136 +2024-11-23 02:17:11.570915: train_loss -0.8138 +2024-11-23 02:17:11.571132: val_loss -0.7861 +2024-11-23 02:17:11.571230: Pseudo dice [0.8608] +2024-11-23 02:17:11.571340: Epoch time: 19.01 s +2024-11-23 02:17:12.453959: +2024-11-23 02:17:12.454187: Epoch 7130 +2024-11-23 02:17:12.454312: Current learning rate: 0.00136 +2024-11-23 02:17:30.942091: train_loss -0.8229 +2024-11-23 02:17:30.942365: val_loss -0.7682 +2024-11-23 02:17:30.942463: Pseudo dice [0.8579] +2024-11-23 02:17:30.942558: Epoch time: 18.49 s +2024-11-23 02:17:31.838330: +2024-11-23 02:17:31.838523: Epoch 7131 +2024-11-23 02:17:31.838642: Current learning rate: 0.00136 +2024-11-23 02:17:50.793053: train_loss -0.8156 +2024-11-23 02:17:50.793580: val_loss -0.7757 +2024-11-23 02:17:50.793674: Pseudo dice [0.8541] +2024-11-23 02:17:50.793767: Epoch time: 18.96 s +2024-11-23 02:17:51.688686: +2024-11-23 02:17:51.688936: Epoch 7132 +2024-11-23 02:17:51.689069: Current learning rate: 0.00135 +2024-11-23 02:18:11.026541: train_loss -0.8115 +2024-11-23 02:18:11.026748: val_loss -0.7786 +2024-11-23 02:18:11.026842: Pseudo dice [0.8522] +2024-11-23 02:18:11.026922: Epoch time: 19.34 s +2024-11-23 02:18:11.920975: +2024-11-23 02:18:11.921197: Epoch 7133 +2024-11-23 02:18:11.921331: Current learning rate: 0.00135 +2024-11-23 02:18:30.479142: train_loss -0.8126 +2024-11-23 02:18:30.479348: val_loss -0.792 +2024-11-23 02:18:30.479434: Pseudo dice [0.8659] +2024-11-23 02:18:30.479509: Epoch time: 18.56 s +2024-11-23 02:18:31.476361: +2024-11-23 02:18:31.476576: Epoch 7134 +2024-11-23 02:18:31.476695: Current learning rate: 0.00135 +2024-11-23 02:18:49.265475: train_loss -0.8205 +2024-11-23 02:18:49.265677: val_loss -0.7783 +2024-11-23 02:18:49.265764: Pseudo dice [0.8534] +2024-11-23 02:18:49.265844: Epoch time: 17.79 s +2024-11-23 02:18:50.534486: +2024-11-23 02:18:50.534691: Epoch 7135 +2024-11-23 02:18:50.534816: Current learning rate: 0.00135 +2024-11-23 02:19:09.407711: train_loss -0.8229 +2024-11-23 02:19:09.408041: val_loss -0.7992 +2024-11-23 02:19:09.408137: Pseudo dice [0.85] +2024-11-23 02:19:09.408226: Epoch time: 18.87 s +2024-11-23 02:19:10.304424: +2024-11-23 02:19:10.304658: Epoch 7136 +2024-11-23 02:19:10.304769: Current learning rate: 0.00135 +2024-11-23 02:19:29.456111: train_loss -0.8135 +2024-11-23 02:19:29.456321: val_loss -0.7706 +2024-11-23 02:19:29.456401: Pseudo dice [0.8518] +2024-11-23 02:19:29.456481: Epoch time: 19.15 s +2024-11-23 02:19:30.344552: +2024-11-23 02:19:30.344765: Epoch 7137 +2024-11-23 02:19:30.344889: Current learning rate: 0.00135 +2024-11-23 02:19:48.876014: train_loss -0.815 +2024-11-23 02:19:48.876242: val_loss -0.7922 +2024-11-23 02:19:48.876334: Pseudo dice [0.8643] +2024-11-23 02:19:48.876415: Epoch time: 18.53 s +2024-11-23 02:19:49.778086: +2024-11-23 02:19:49.778288: Epoch 7138 +2024-11-23 02:19:49.778403: Current learning rate: 0.00135 +2024-11-23 02:20:08.033322: train_loss -0.8159 +2024-11-23 02:20:08.033528: val_loss -0.7715 +2024-11-23 02:20:08.033693: Pseudo dice [0.8398] +2024-11-23 02:20:08.033771: Epoch time: 18.26 s +2024-11-23 02:20:09.115753: +2024-11-23 02:20:09.115979: Epoch 7139 +2024-11-23 02:20:09.116113: Current learning rate: 0.00134 +2024-11-23 02:20:27.431253: train_loss -0.8222 +2024-11-23 02:20:27.431489: val_loss -0.7908 +2024-11-23 02:20:27.431574: Pseudo dice [0.8607] +2024-11-23 02:20:27.431658: Epoch time: 18.32 s +2024-11-23 02:20:28.321204: +2024-11-23 02:20:28.321402: Epoch 7140 +2024-11-23 02:20:28.321516: Current learning rate: 0.00134 +2024-11-23 02:20:46.060298: train_loss -0.8246 +2024-11-23 02:20:46.060509: val_loss -0.7948 +2024-11-23 02:20:46.060593: Pseudo dice [0.8589] +2024-11-23 02:20:46.060675: Epoch time: 17.74 s +2024-11-23 02:20:46.947666: +2024-11-23 02:20:46.947887: Epoch 7141 +2024-11-23 02:20:46.948016: Current learning rate: 0.00134 +2024-11-23 02:21:05.026645: train_loss -0.8236 +2024-11-23 02:21:05.026873: val_loss -0.7728 +2024-11-23 02:21:05.026953: Pseudo dice [0.8534] +2024-11-23 02:21:05.027035: Epoch time: 18.08 s +2024-11-23 02:21:05.913201: +2024-11-23 02:21:05.913429: Epoch 7142 +2024-11-23 02:21:05.913550: Current learning rate: 0.00134 +2024-11-23 02:21:23.979944: train_loss -0.8222 +2024-11-23 02:21:23.980160: val_loss -0.7827 +2024-11-23 02:21:23.980254: Pseudo dice [0.863] +2024-11-23 02:21:23.980358: Epoch time: 18.07 s +2024-11-23 02:21:24.873884: +2024-11-23 02:21:24.874094: Epoch 7143 +2024-11-23 02:21:24.874215: Current learning rate: 0.00134 +2024-11-23 02:21:43.236567: train_loss -0.8197 +2024-11-23 02:21:43.236814: val_loss -0.7918 +2024-11-23 02:21:43.236897: Pseudo dice [0.861] +2024-11-23 02:21:43.237010: Epoch time: 18.36 s +2024-11-23 02:21:44.124383: +2024-11-23 02:21:44.124592: Epoch 7144 +2024-11-23 02:21:44.124707: Current learning rate: 0.00134 +2024-11-23 02:22:02.709231: train_loss -0.8195 +2024-11-23 02:22:02.709450: val_loss -0.7715 +2024-11-23 02:22:02.709594: Pseudo dice [0.8608] +2024-11-23 02:22:02.709673: Epoch time: 18.59 s +2024-11-23 02:22:03.603511: +2024-11-23 02:22:03.603719: Epoch 7145 +2024-11-23 02:22:03.603853: Current learning rate: 0.00134 +2024-11-23 02:22:22.387266: train_loss -0.8212 +2024-11-23 02:22:22.387505: val_loss -0.7759 +2024-11-23 02:22:22.387593: Pseudo dice [0.8432] +2024-11-23 02:22:22.387682: Epoch time: 18.78 s +2024-11-23 02:22:23.663344: +2024-11-23 02:22:23.663630: Epoch 7146 +2024-11-23 02:22:23.663746: Current learning rate: 0.00134 +2024-11-23 02:22:42.390039: train_loss -0.819 +2024-11-23 02:22:42.395505: val_loss -0.7825 +2024-11-23 02:22:42.395602: Pseudo dice [0.8712] +2024-11-23 02:22:42.395705: Epoch time: 18.73 s +2024-11-23 02:22:43.286774: +2024-11-23 02:22:43.286981: Epoch 7147 +2024-11-23 02:22:43.287099: Current learning rate: 0.00133 +2024-11-23 02:23:01.960630: train_loss -0.819 +2024-11-23 02:23:01.960862: val_loss -0.7893 +2024-11-23 02:23:01.960947: Pseudo dice [0.8636] +2024-11-23 02:23:01.961034: Epoch time: 18.67 s +2024-11-23 02:23:02.853909: +2024-11-23 02:23:02.854117: Epoch 7148 +2024-11-23 02:23:02.854234: Current learning rate: 0.00133 +2024-11-23 02:23:22.104412: train_loss -0.8235 +2024-11-23 02:23:22.104621: val_loss -0.7452 +2024-11-23 02:23:22.104703: Pseudo dice [0.8562] +2024-11-23 02:23:22.104800: Epoch time: 19.25 s +2024-11-23 02:23:23.001479: +2024-11-23 02:23:23.001682: Epoch 7149 +2024-11-23 02:23:23.001796: Current learning rate: 0.00133 +2024-11-23 02:23:42.037213: train_loss -0.8234 +2024-11-23 02:23:42.039589: val_loss -0.7999 +2024-11-23 02:23:42.039676: Pseudo dice [0.8595] +2024-11-23 02:23:42.039751: Epoch time: 19.04 s +2024-11-23 02:23:43.413203: +2024-11-23 02:23:43.413409: Epoch 7150 +2024-11-23 02:23:43.413517: Current learning rate: 0.00133 +2024-11-23 02:24:01.071356: train_loss -0.8277 +2024-11-23 02:24:01.071600: val_loss -0.7805 +2024-11-23 02:24:01.071692: Pseudo dice [0.8549] +2024-11-23 02:24:01.071777: Epoch time: 17.66 s +2024-11-23 02:24:01.965697: +2024-11-23 02:24:01.965917: Epoch 7151 +2024-11-23 02:24:01.966031: Current learning rate: 0.00133 +2024-11-23 02:24:20.562550: train_loss -0.8266 +2024-11-23 02:24:20.562761: val_loss -0.8008 +2024-11-23 02:24:20.562838: Pseudo dice [0.8611] +2024-11-23 02:24:20.562912: Epoch time: 18.6 s +2024-11-23 02:24:21.452271: +2024-11-23 02:24:21.452478: Epoch 7152 +2024-11-23 02:24:21.452606: Current learning rate: 0.00133 +2024-11-23 02:24:40.867117: train_loss -0.8176 +2024-11-23 02:24:40.867333: val_loss -0.7971 +2024-11-23 02:24:40.867411: Pseudo dice [0.8674] +2024-11-23 02:24:40.867487: Epoch time: 19.42 s +2024-11-23 02:24:41.761778: +2024-11-23 02:24:41.761992: Epoch 7153 +2024-11-23 02:24:41.762115: Current learning rate: 0.00133 +2024-11-23 02:24:59.602223: train_loss -0.8273 +2024-11-23 02:24:59.602443: val_loss -0.7686 +2024-11-23 02:24:59.602526: Pseudo dice [0.8595] +2024-11-23 02:24:59.602622: Epoch time: 17.84 s +2024-11-23 02:25:00.595002: +2024-11-23 02:25:00.595216: Epoch 7154 +2024-11-23 02:25:00.595329: Current learning rate: 0.00132 +2024-11-23 02:25:19.878721: train_loss -0.8257 +2024-11-23 02:25:19.878966: val_loss -0.801 +2024-11-23 02:25:19.879047: Pseudo dice [0.8734] +2024-11-23 02:25:19.879134: Epoch time: 19.28 s +2024-11-23 02:25:20.765932: +2024-11-23 02:25:20.766145: Epoch 7155 +2024-11-23 02:25:20.766276: Current learning rate: 0.00132 +2024-11-23 02:25:39.478498: train_loss -0.8274 +2024-11-23 02:25:39.478713: val_loss -0.787 +2024-11-23 02:25:39.478788: Pseudo dice [0.8534] +2024-11-23 02:25:39.478866: Epoch time: 18.71 s +2024-11-23 02:25:40.392760: +2024-11-23 02:25:40.392966: Epoch 7156 +2024-11-23 02:25:40.393094: Current learning rate: 0.00132 +2024-11-23 02:25:58.613260: train_loss -0.8168 +2024-11-23 02:25:58.613481: val_loss -0.7624 +2024-11-23 02:25:58.615756: Pseudo dice [0.8622] +2024-11-23 02:25:58.615896: Epoch time: 18.22 s +2024-11-23 02:26:00.025491: +2024-11-23 02:26:00.025710: Epoch 7157 +2024-11-23 02:26:00.025825: Current learning rate: 0.00132 +2024-11-23 02:26:18.529584: train_loss -0.8284 +2024-11-23 02:26:18.530440: val_loss -0.7728 +2024-11-23 02:26:18.530561: Pseudo dice [0.8596] +2024-11-23 02:26:18.530662: Epoch time: 18.5 s +2024-11-23 02:26:19.436213: +2024-11-23 02:26:19.436444: Epoch 7158 +2024-11-23 02:26:19.436566: Current learning rate: 0.00132 +2024-11-23 02:26:36.958420: train_loss -0.8286 +2024-11-23 02:26:36.958680: val_loss -0.7796 +2024-11-23 02:26:36.958825: Pseudo dice [0.8671] +2024-11-23 02:26:36.958913: Epoch time: 17.52 s +2024-11-23 02:26:37.852964: +2024-11-23 02:26:37.853185: Epoch 7159 +2024-11-23 02:26:37.853317: Current learning rate: 0.00132 +2024-11-23 02:26:55.251405: train_loss -0.8259 +2024-11-23 02:26:55.256770: val_loss -0.7949 +2024-11-23 02:26:55.256948: Pseudo dice [0.8535] +2024-11-23 02:26:55.257047: Epoch time: 17.4 s +2024-11-23 02:26:56.172474: +2024-11-23 02:26:56.172688: Epoch 7160 +2024-11-23 02:26:56.172807: Current learning rate: 0.00132 +2024-11-23 02:27:15.292588: train_loss -0.8238 +2024-11-23 02:27:15.292879: val_loss -0.7791 +2024-11-23 02:27:15.292960: Pseudo dice [0.8557] +2024-11-23 02:27:15.293039: Epoch time: 19.12 s +2024-11-23 02:27:16.191109: +2024-11-23 02:27:16.191317: Epoch 7161 +2024-11-23 02:27:16.191432: Current learning rate: 0.00131 +2024-11-23 02:27:35.487676: train_loss -0.8225 +2024-11-23 02:27:35.487931: val_loss -0.7671 +2024-11-23 02:27:35.488010: Pseudo dice [0.8605] +2024-11-23 02:27:35.488096: Epoch time: 19.3 s +2024-11-23 02:27:36.392052: +2024-11-23 02:27:36.392291: Epoch 7162 +2024-11-23 02:27:36.392411: Current learning rate: 0.00131 +2024-11-23 02:27:53.274036: train_loss -0.8242 +2024-11-23 02:27:53.274252: val_loss -0.7733 +2024-11-23 02:27:53.274329: Pseudo dice [0.8626] +2024-11-23 02:27:53.274424: Epoch time: 16.88 s +2024-11-23 02:27:54.169038: +2024-11-23 02:27:54.169250: Epoch 7163 +2024-11-23 02:27:54.169370: Current learning rate: 0.00131 +2024-11-23 02:28:13.410553: train_loss -0.8221 +2024-11-23 02:28:13.410778: val_loss -0.7588 +2024-11-23 02:28:13.410853: Pseudo dice [0.8624] +2024-11-23 02:28:13.410930: Epoch time: 19.24 s +2024-11-23 02:28:14.302314: +2024-11-23 02:28:14.302519: Epoch 7164 +2024-11-23 02:28:14.302650: Current learning rate: 0.00131 +2024-11-23 02:28:32.849527: train_loss -0.8215 +2024-11-23 02:28:32.849744: val_loss -0.7767 +2024-11-23 02:28:32.849822: Pseudo dice [0.8524] +2024-11-23 02:28:32.849908: Epoch time: 18.55 s +2024-11-23 02:28:33.751691: +2024-11-23 02:28:33.751917: Epoch 7165 +2024-11-23 02:28:33.752025: Current learning rate: 0.00131 +2024-11-23 02:28:52.591958: train_loss -0.8328 +2024-11-23 02:28:52.592192: val_loss -0.7896 +2024-11-23 02:28:52.592287: Pseudo dice [0.8535] +2024-11-23 02:28:52.592381: Epoch time: 18.84 s +2024-11-23 02:28:53.473375: +2024-11-23 02:28:53.473582: Epoch 7166 +2024-11-23 02:28:53.473710: Current learning rate: 0.00131 +2024-11-23 02:29:12.049765: train_loss -0.8274 +2024-11-23 02:29:12.049975: val_loss -0.7913 +2024-11-23 02:29:12.050138: Pseudo dice [0.8534] +2024-11-23 02:29:12.050219: Epoch time: 18.58 s +2024-11-23 02:29:12.942300: +2024-11-23 02:29:12.942499: Epoch 7167 +2024-11-23 02:29:12.942614: Current learning rate: 0.00131 +2024-11-23 02:29:30.434831: train_loss -0.8267 +2024-11-23 02:29:30.435199: val_loss -0.7754 +2024-11-23 02:29:30.435282: Pseudo dice [0.8711] +2024-11-23 02:29:30.435364: Epoch time: 17.49 s +2024-11-23 02:29:31.320925: +2024-11-23 02:29:31.321129: Epoch 7168 +2024-11-23 02:29:31.321244: Current learning rate: 0.0013 +2024-11-23 02:29:49.466881: train_loss -0.8278 +2024-11-23 02:29:49.467373: val_loss -0.7871 +2024-11-23 02:29:49.467477: Pseudo dice [0.8519] +2024-11-23 02:29:49.467557: Epoch time: 18.15 s +2024-11-23 02:29:50.359576: +2024-11-23 02:29:50.359799: Epoch 7169 +2024-11-23 02:29:50.359915: Current learning rate: 0.0013 +2024-11-23 02:30:09.654739: train_loss -0.8235 +2024-11-23 02:30:09.654984: val_loss -0.7784 +2024-11-23 02:30:09.655068: Pseudo dice [0.8568] +2024-11-23 02:30:09.655145: Epoch time: 19.3 s +2024-11-23 02:30:10.537692: +2024-11-23 02:30:10.537925: Epoch 7170 +2024-11-23 02:30:10.538048: Current learning rate: 0.0013 +2024-11-23 02:30:28.657321: train_loss -0.8198 +2024-11-23 02:30:28.657570: val_loss -0.7921 +2024-11-23 02:30:28.662200: Pseudo dice [0.8627] +2024-11-23 02:30:28.662304: Epoch time: 18.12 s +2024-11-23 02:30:29.602320: +2024-11-23 02:30:29.602547: Epoch 7171 +2024-11-23 02:30:29.602665: Current learning rate: 0.0013 +2024-11-23 02:30:47.985409: train_loss -0.8171 +2024-11-23 02:30:47.985623: val_loss -0.7612 +2024-11-23 02:30:47.985703: Pseudo dice [0.8658] +2024-11-23 02:30:47.985791: Epoch time: 18.38 s +2024-11-23 02:30:48.881228: +2024-11-23 02:30:48.881447: Epoch 7172 +2024-11-23 02:30:48.881557: Current learning rate: 0.0013 +2024-11-23 02:31:07.457825: train_loss -0.8194 +2024-11-23 02:31:07.458089: val_loss -0.7781 +2024-11-23 02:31:07.458171: Pseudo dice [0.8529] +2024-11-23 02:31:07.458257: Epoch time: 18.58 s +2024-11-23 02:31:08.353424: +2024-11-23 02:31:08.353634: Epoch 7173 +2024-11-23 02:31:08.353768: Current learning rate: 0.0013 +2024-11-23 02:31:27.203382: train_loss -0.813 +2024-11-23 02:31:27.203621: val_loss -0.7528 +2024-11-23 02:31:27.203703: Pseudo dice [0.8529] +2024-11-23 02:31:27.203793: Epoch time: 18.85 s +2024-11-23 02:31:28.087810: +2024-11-23 02:31:28.088036: Epoch 7174 +2024-11-23 02:31:28.088156: Current learning rate: 0.0013 +2024-11-23 02:31:47.104094: train_loss -0.8199 +2024-11-23 02:31:47.104321: val_loss -0.7966 +2024-11-23 02:31:47.104405: Pseudo dice [0.8693] +2024-11-23 02:31:47.104498: Epoch time: 19.02 s +2024-11-23 02:31:47.998426: +2024-11-23 02:31:47.998656: Epoch 7175 +2024-11-23 02:31:47.998771: Current learning rate: 0.00129 +2024-11-23 02:32:07.415542: train_loss -0.8269 +2024-11-23 02:32:07.415762: val_loss -0.8035 +2024-11-23 02:32:07.415839: Pseudo dice [0.8568] +2024-11-23 02:32:07.415920: Epoch time: 19.42 s +2024-11-23 02:32:08.391584: +2024-11-23 02:32:08.391798: Epoch 7176 +2024-11-23 02:32:08.391910: Current learning rate: 0.00129 +2024-11-23 02:32:27.124288: train_loss -0.8242 +2024-11-23 02:32:27.124551: val_loss -0.8049 +2024-11-23 02:32:27.124647: Pseudo dice [0.8675] +2024-11-23 02:32:27.124752: Epoch time: 18.73 s +2024-11-23 02:32:28.015368: +2024-11-23 02:32:28.015561: Epoch 7177 +2024-11-23 02:32:28.015675: Current learning rate: 0.00129 +2024-11-23 02:32:46.643917: train_loss -0.825 +2024-11-23 02:32:46.644138: val_loss -0.7842 +2024-11-23 02:32:46.644219: Pseudo dice [0.8445] +2024-11-23 02:32:46.644294: Epoch time: 18.63 s +2024-11-23 02:32:47.537443: +2024-11-23 02:32:47.537635: Epoch 7178 +2024-11-23 02:32:47.537751: Current learning rate: 0.00129 +2024-11-23 02:33:06.284747: train_loss -0.8255 +2024-11-23 02:33:06.285008: val_loss -0.8037 +2024-11-23 02:33:06.285095: Pseudo dice [0.8567] +2024-11-23 02:33:06.285175: Epoch time: 18.75 s +2024-11-23 02:33:07.189548: +2024-11-23 02:33:07.189750: Epoch 7179 +2024-11-23 02:33:07.189864: Current learning rate: 0.00129 +2024-11-23 02:33:25.354475: train_loss -0.8199 +2024-11-23 02:33:25.354746: val_loss -0.7622 +2024-11-23 02:33:25.356075: Pseudo dice [0.854] +2024-11-23 02:33:25.356178: Epoch time: 18.17 s +2024-11-23 02:33:26.244710: +2024-11-23 02:33:26.244932: Epoch 7180 +2024-11-23 02:33:26.245052: Current learning rate: 0.00129 +2024-11-23 02:33:44.977294: train_loss -0.8182 +2024-11-23 02:33:44.977522: val_loss -0.7717 +2024-11-23 02:33:44.977599: Pseudo dice [0.8541] +2024-11-23 02:33:44.977678: Epoch time: 18.73 s +2024-11-23 02:33:45.865669: +2024-11-23 02:33:45.865877: Epoch 7181 +2024-11-23 02:33:45.865988: Current learning rate: 0.00129 +2024-11-23 02:34:04.168855: train_loss -0.8117 +2024-11-23 02:34:04.169094: val_loss -0.7867 +2024-11-23 02:34:04.169193: Pseudo dice [0.8584] +2024-11-23 02:34:04.169272: Epoch time: 18.3 s +2024-11-23 02:34:05.058866: +2024-11-23 02:34:05.059080: Epoch 7182 +2024-11-23 02:34:05.059201: Current learning rate: 0.00128 +2024-11-23 02:34:24.358097: train_loss -0.814 +2024-11-23 02:34:24.360997: val_loss -0.764 +2024-11-23 02:34:24.361150: Pseudo dice [0.8349] +2024-11-23 02:34:24.361233: Epoch time: 19.3 s +2024-11-23 02:34:25.268519: +2024-11-23 02:34:25.268725: Epoch 7183 +2024-11-23 02:34:25.268841: Current learning rate: 0.00128 +2024-11-23 02:34:43.475535: train_loss -0.8229 +2024-11-23 02:34:43.475768: val_loss -0.7935 +2024-11-23 02:34:43.475846: Pseudo dice [0.8652] +2024-11-23 02:34:43.475929: Epoch time: 18.21 s +2024-11-23 02:34:44.375144: +2024-11-23 02:34:44.375397: Epoch 7184 +2024-11-23 02:34:44.375548: Current learning rate: 0.00128 +2024-11-23 02:35:02.207097: train_loss -0.8289 +2024-11-23 02:35:02.207311: val_loss -0.7926 +2024-11-23 02:35:02.207392: Pseudo dice [0.8524] +2024-11-23 02:35:02.207470: Epoch time: 17.83 s +2024-11-23 02:35:03.093919: +2024-11-23 02:35:03.094121: Epoch 7185 +2024-11-23 02:35:03.094258: Current learning rate: 0.00128 +2024-11-23 02:35:21.497799: train_loss -0.8163 +2024-11-23 02:35:21.498028: val_loss -0.7933 +2024-11-23 02:35:21.498139: Pseudo dice [0.8524] +2024-11-23 02:35:21.498233: Epoch time: 18.4 s +2024-11-23 02:35:22.425576: +2024-11-23 02:35:22.425771: Epoch 7186 +2024-11-23 02:35:22.425959: Current learning rate: 0.00128 +2024-11-23 02:35:40.969441: train_loss -0.8224 +2024-11-23 02:35:40.969670: val_loss -0.7667 +2024-11-23 02:35:40.969751: Pseudo dice [0.8473] +2024-11-23 02:35:40.969836: Epoch time: 18.54 s +2024-11-23 02:35:41.860192: +2024-11-23 02:35:41.860398: Epoch 7187 +2024-11-23 02:35:41.860520: Current learning rate: 0.00128 +2024-11-23 02:36:00.056041: train_loss -0.8245 +2024-11-23 02:36:00.056344: val_loss -0.7976 +2024-11-23 02:36:00.056434: Pseudo dice [0.8625] +2024-11-23 02:36:00.056526: Epoch time: 18.2 s +2024-11-23 02:36:00.948091: +2024-11-23 02:36:00.948289: Epoch 7188 +2024-11-23 02:36:00.948399: Current learning rate: 0.00128 +2024-11-23 02:36:19.779150: train_loss -0.8261 +2024-11-23 02:36:19.779369: val_loss -0.7827 +2024-11-23 02:36:19.779471: Pseudo dice [0.8535] +2024-11-23 02:36:19.779563: Epoch time: 18.83 s +2024-11-23 02:36:20.683347: +2024-11-23 02:36:20.683546: Epoch 7189 +2024-11-23 02:36:20.683661: Current learning rate: 0.00127 +2024-11-23 02:36:39.258012: train_loss -0.82 +2024-11-23 02:36:39.258245: val_loss -0.7838 +2024-11-23 02:36:39.258342: Pseudo dice [0.8563] +2024-11-23 02:36:39.258435: Epoch time: 18.58 s +2024-11-23 02:36:40.514646: +2024-11-23 02:36:40.514877: Epoch 7190 +2024-11-23 02:36:40.514996: Current learning rate: 0.00127 +2024-11-23 02:36:58.010297: train_loss -0.8193 +2024-11-23 02:36:58.010514: val_loss -0.7639 +2024-11-23 02:36:58.010602: Pseudo dice [0.8587] +2024-11-23 02:36:58.010691: Epoch time: 17.5 s +2024-11-23 02:36:58.900308: +2024-11-23 02:36:58.900516: Epoch 7191 +2024-11-23 02:36:58.900643: Current learning rate: 0.00127 +2024-11-23 02:37:16.972627: train_loss -0.8188 +2024-11-23 02:37:16.972860: val_loss -0.8056 +2024-11-23 02:37:16.972938: Pseudo dice [0.8673] +2024-11-23 02:37:16.973014: Epoch time: 18.07 s +2024-11-23 02:37:17.862369: +2024-11-23 02:37:17.862602: Epoch 7192 +2024-11-23 02:37:17.862721: Current learning rate: 0.00127 +2024-11-23 02:37:35.628448: train_loss -0.8251 +2024-11-23 02:37:35.628657: val_loss -0.7607 +2024-11-23 02:37:35.628807: Pseudo dice [0.8606] +2024-11-23 02:37:35.628888: Epoch time: 17.77 s +2024-11-23 02:37:36.504394: +2024-11-23 02:37:36.504609: Epoch 7193 +2024-11-23 02:37:36.504738: Current learning rate: 0.00127 +2024-11-23 02:37:55.316369: train_loss -0.8221 +2024-11-23 02:37:55.316610: val_loss -0.776 +2024-11-23 02:37:55.316708: Pseudo dice [0.8562] +2024-11-23 02:37:55.316786: Epoch time: 18.81 s +2024-11-23 02:37:56.197278: +2024-11-23 02:37:56.197489: Epoch 7194 +2024-11-23 02:37:56.197600: Current learning rate: 0.00127 +2024-11-23 02:38:15.011908: train_loss -0.8236 +2024-11-23 02:38:15.012149: val_loss -0.7678 +2024-11-23 02:38:15.012230: Pseudo dice [0.8535] +2024-11-23 02:38:15.012315: Epoch time: 18.82 s +2024-11-23 02:38:15.895284: +2024-11-23 02:38:15.895493: Epoch 7195 +2024-11-23 02:38:15.895609: Current learning rate: 0.00127 +2024-11-23 02:38:34.319991: train_loss -0.8252 +2024-11-23 02:38:34.320200: val_loss -0.7797 +2024-11-23 02:38:34.320277: Pseudo dice [0.852] +2024-11-23 02:38:34.320359: Epoch time: 18.43 s +2024-11-23 02:38:35.213717: +2024-11-23 02:38:35.213926: Epoch 7196 +2024-11-23 02:38:35.214044: Current learning rate: 0.00126 +2024-11-23 02:38:53.959698: train_loss -0.8216 +2024-11-23 02:38:53.959913: val_loss -0.7822 +2024-11-23 02:38:53.960012: Pseudo dice [0.8665] +2024-11-23 02:38:53.960120: Epoch time: 18.75 s +2024-11-23 02:38:54.830066: +2024-11-23 02:38:54.830269: Epoch 7197 +2024-11-23 02:38:54.830382: Current learning rate: 0.00126 +2024-11-23 02:39:13.118585: train_loss -0.824 +2024-11-23 02:39:13.118790: val_loss -0.7912 +2024-11-23 02:39:13.118876: Pseudo dice [0.8612] +2024-11-23 02:39:13.118972: Epoch time: 18.29 s +2024-11-23 02:39:14.011699: +2024-11-23 02:39:14.011913: Epoch 7198 +2024-11-23 02:39:14.012023: Current learning rate: 0.00126 +2024-11-23 02:39:32.702483: train_loss -0.8266 +2024-11-23 02:39:32.702718: val_loss -0.7755 +2024-11-23 02:39:32.702798: Pseudo dice [0.8599] +2024-11-23 02:39:32.702880: Epoch time: 18.69 s +2024-11-23 02:39:33.630434: +2024-11-23 02:39:33.630642: Epoch 7199 +2024-11-23 02:39:33.630766: Current learning rate: 0.00126 +2024-11-23 02:39:51.185452: train_loss -0.8286 +2024-11-23 02:39:51.185668: val_loss -0.7973 +2024-11-23 02:39:51.185758: Pseudo dice [0.8711] +2024-11-23 02:39:51.185838: Epoch time: 17.56 s +2024-11-23 02:39:52.411446: +2024-11-23 02:39:52.411655: Epoch 7200 +2024-11-23 02:39:52.411764: Current learning rate: 0.00126 +2024-11-23 02:40:10.632416: train_loss -0.8267 +2024-11-23 02:40:10.632633: val_loss -0.7871 +2024-11-23 02:40:10.632712: Pseudo dice [0.8609] +2024-11-23 02:40:10.632803: Epoch time: 18.22 s +2024-11-23 02:40:11.843421: +2024-11-23 02:40:11.843616: Epoch 7201 +2024-11-23 02:40:11.843729: Current learning rate: 0.00126 +2024-11-23 02:40:31.672391: train_loss -0.8229 +2024-11-23 02:40:31.672985: val_loss -0.7883 +2024-11-23 02:40:31.673095: Pseudo dice [0.8552] +2024-11-23 02:40:31.673177: Epoch time: 19.83 s +2024-11-23 02:40:32.565010: +2024-11-23 02:40:32.565202: Epoch 7202 +2024-11-23 02:40:32.565311: Current learning rate: 0.00126 +2024-11-23 02:40:50.977734: train_loss -0.8295 +2024-11-23 02:40:50.977962: val_loss -0.7879 +2024-11-23 02:40:50.978062: Pseudo dice [0.8559] +2024-11-23 02:40:50.978150: Epoch time: 18.41 s +2024-11-23 02:40:51.917046: +2024-11-23 02:40:51.917265: Epoch 7203 +2024-11-23 02:40:51.917397: Current learning rate: 0.00125 +2024-11-23 02:41:10.292311: train_loss -0.828 +2024-11-23 02:41:10.292534: val_loss -0.7887 +2024-11-23 02:41:10.292612: Pseudo dice [0.85] +2024-11-23 02:41:10.297989: Epoch time: 18.38 s +2024-11-23 02:41:11.197606: +2024-11-23 02:41:11.197806: Epoch 7204 +2024-11-23 02:41:11.197924: Current learning rate: 0.00125 +2024-11-23 02:41:30.081302: train_loss -0.8222 +2024-11-23 02:41:30.081509: val_loss -0.7667 +2024-11-23 02:41:30.081589: Pseudo dice [0.8565] +2024-11-23 02:41:30.081666: Epoch time: 18.88 s +2024-11-23 02:41:30.962763: +2024-11-23 02:41:30.962971: Epoch 7205 +2024-11-23 02:41:30.963087: Current learning rate: 0.00125 +2024-11-23 02:41:49.377830: train_loss -0.8099 +2024-11-23 02:41:49.378079: val_loss -0.7724 +2024-11-23 02:41:49.378223: Pseudo dice [0.8484] +2024-11-23 02:41:49.378324: Epoch time: 18.42 s +2024-11-23 02:41:50.268486: +2024-11-23 02:41:50.268683: Epoch 7206 +2024-11-23 02:41:50.268813: Current learning rate: 0.00125 +2024-11-23 02:42:10.274080: train_loss -0.8259 +2024-11-23 02:42:10.274307: val_loss -0.7713 +2024-11-23 02:42:10.274404: Pseudo dice [0.8564] +2024-11-23 02:42:10.274490: Epoch time: 20.01 s +2024-11-23 02:42:11.159566: +2024-11-23 02:42:11.159764: Epoch 7207 +2024-11-23 02:42:11.159880: Current learning rate: 0.00125 +2024-11-23 02:42:30.102491: train_loss -0.8243 +2024-11-23 02:42:30.102710: val_loss -0.7511 +2024-11-23 02:42:30.104981: Pseudo dice [0.8626] +2024-11-23 02:42:30.105089: Epoch time: 18.94 s +2024-11-23 02:42:31.098186: +2024-11-23 02:42:31.098423: Epoch 7208 +2024-11-23 02:42:31.098557: Current learning rate: 0.00125 +2024-11-23 02:42:49.441987: train_loss -0.8158 +2024-11-23 02:42:49.442203: val_loss -0.7657 +2024-11-23 02:42:49.442298: Pseudo dice [0.8552] +2024-11-23 02:42:49.442378: Epoch time: 18.34 s +2024-11-23 02:42:50.332241: +2024-11-23 02:42:50.332439: Epoch 7209 +2024-11-23 02:42:50.332566: Current learning rate: 0.00125 +2024-11-23 02:43:08.205047: train_loss -0.8194 +2024-11-23 02:43:08.205278: val_loss -0.7857 +2024-11-23 02:43:08.205365: Pseudo dice [0.8552] +2024-11-23 02:43:08.205448: Epoch time: 17.87 s +2024-11-23 02:43:09.091410: +2024-11-23 02:43:09.091649: Epoch 7210 +2024-11-23 02:43:09.091763: Current learning rate: 0.00124 +2024-11-23 02:43:28.238733: train_loss -0.8221 +2024-11-23 02:43:28.239034: val_loss -0.7841 +2024-11-23 02:43:28.239118: Pseudo dice [0.8654] +2024-11-23 02:43:28.239203: Epoch time: 19.15 s +2024-11-23 02:43:29.142924: +2024-11-23 02:43:29.143147: Epoch 7211 +2024-11-23 02:43:29.143265: Current learning rate: 0.00124 +2024-11-23 02:43:48.521132: train_loss -0.8161 +2024-11-23 02:43:48.521370: val_loss -0.7835 +2024-11-23 02:43:48.521458: Pseudo dice [0.8639] +2024-11-23 02:43:48.521545: Epoch time: 19.38 s +2024-11-23 02:43:49.776768: +2024-11-23 02:43:49.776977: Epoch 7212 +2024-11-23 02:43:49.777105: Current learning rate: 0.00124 +2024-11-23 02:44:07.560934: train_loss -0.8204 +2024-11-23 02:44:07.561197: val_loss -0.791 +2024-11-23 02:44:07.561280: Pseudo dice [0.862] +2024-11-23 02:44:07.561364: Epoch time: 17.78 s +2024-11-23 02:44:08.445968: +2024-11-23 02:44:08.446182: Epoch 7213 +2024-11-23 02:44:08.446294: Current learning rate: 0.00124 +2024-11-23 02:44:26.757691: train_loss -0.8241 +2024-11-23 02:44:26.757890: val_loss -0.7802 +2024-11-23 02:44:26.757967: Pseudo dice [0.8667] +2024-11-23 02:44:26.758041: Epoch time: 18.31 s +2024-11-23 02:44:27.645075: +2024-11-23 02:44:27.645299: Epoch 7214 +2024-11-23 02:44:27.645408: Current learning rate: 0.00124 +2024-11-23 02:44:46.730009: train_loss -0.8206 +2024-11-23 02:44:46.730227: val_loss -0.7693 +2024-11-23 02:44:46.730311: Pseudo dice [0.8479] +2024-11-23 02:44:46.730392: Epoch time: 19.09 s +2024-11-23 02:44:47.727188: +2024-11-23 02:44:47.727398: Epoch 7215 +2024-11-23 02:44:47.727512: Current learning rate: 0.00124 +2024-11-23 02:45:05.889459: train_loss -0.8224 +2024-11-23 02:45:05.889674: val_loss -0.7868 +2024-11-23 02:45:05.889764: Pseudo dice [0.8664] +2024-11-23 02:45:05.889852: Epoch time: 18.16 s +2024-11-23 02:45:06.782822: +2024-11-23 02:45:06.783054: Epoch 7216 +2024-11-23 02:45:06.783191: Current learning rate: 0.00124 +2024-11-23 02:45:25.458667: train_loss -0.8222 +2024-11-23 02:45:25.458906: val_loss -0.7986 +2024-11-23 02:45:25.458988: Pseudo dice [0.8638] +2024-11-23 02:45:25.459077: Epoch time: 18.68 s +2024-11-23 02:45:26.345967: +2024-11-23 02:45:26.346196: Epoch 7217 +2024-11-23 02:45:26.346318: Current learning rate: 0.00123 +2024-11-23 02:45:44.334655: train_loss -0.8259 +2024-11-23 02:45:44.334862: val_loss -0.7627 +2024-11-23 02:45:44.334940: Pseudo dice [0.8604] +2024-11-23 02:45:44.335032: Epoch time: 17.99 s +2024-11-23 02:45:45.272382: +2024-11-23 02:45:45.272594: Epoch 7218 +2024-11-23 02:45:45.272716: Current learning rate: 0.00123 +2024-11-23 02:46:04.334492: train_loss -0.8223 +2024-11-23 02:46:04.334707: val_loss -0.7838 +2024-11-23 02:46:04.334788: Pseudo dice [0.8648] +2024-11-23 02:46:04.334865: Epoch time: 19.06 s +2024-11-23 02:46:05.220591: +2024-11-23 02:46:05.220803: Epoch 7219 +2024-11-23 02:46:05.220927: Current learning rate: 0.00123 +2024-11-23 02:46:24.256139: train_loss -0.8112 +2024-11-23 02:46:24.256373: val_loss -0.7874 +2024-11-23 02:46:24.256461: Pseudo dice [0.8561] +2024-11-23 02:46:24.256545: Epoch time: 19.04 s +2024-11-23 02:46:25.197750: +2024-11-23 02:46:25.197997: Epoch 7220 +2024-11-23 02:46:25.198152: Current learning rate: 0.00123 +2024-11-23 02:46:43.652449: train_loss -0.8181 +2024-11-23 02:46:43.652699: val_loss -0.7981 +2024-11-23 02:46:43.652790: Pseudo dice [0.8647] +2024-11-23 02:46:43.652882: Epoch time: 18.46 s +2024-11-23 02:46:44.545622: +2024-11-23 02:46:44.545818: Epoch 7221 +2024-11-23 02:46:44.545937: Current learning rate: 0.00123 +2024-11-23 02:47:03.606920: train_loss -0.8247 +2024-11-23 02:47:03.607194: val_loss -0.7731 +2024-11-23 02:47:03.607280: Pseudo dice [0.8518] +2024-11-23 02:47:03.607359: Epoch time: 19.06 s +2024-11-23 02:47:04.500794: +2024-11-23 02:47:04.501004: Epoch 7222 +2024-11-23 02:47:04.501123: Current learning rate: 0.00123 +2024-11-23 02:47:23.387633: train_loss -0.8228 +2024-11-23 02:47:23.387846: val_loss -0.774 +2024-11-23 02:47:23.387926: Pseudo dice [0.8582] +2024-11-23 02:47:23.388004: Epoch time: 18.89 s +2024-11-23 02:47:24.675270: +2024-11-23 02:47:24.675494: Epoch 7223 +2024-11-23 02:47:24.675612: Current learning rate: 0.00123 +2024-11-23 02:47:43.325071: train_loss -0.8229 +2024-11-23 02:47:43.325289: val_loss -0.7492 +2024-11-23 02:47:43.325378: Pseudo dice [0.8517] +2024-11-23 02:47:43.325459: Epoch time: 18.65 s +2024-11-23 02:47:44.220847: +2024-11-23 02:47:44.221052: Epoch 7224 +2024-11-23 02:47:44.221167: Current learning rate: 0.00122 +2024-11-23 02:48:03.333817: train_loss -0.8203 +2024-11-23 02:48:03.334069: val_loss -0.7614 +2024-11-23 02:48:03.334152: Pseudo dice [0.846] +2024-11-23 02:48:03.334238: Epoch time: 19.11 s +2024-11-23 02:48:04.229360: +2024-11-23 02:48:04.229601: Epoch 7225 +2024-11-23 02:48:04.229733: Current learning rate: 0.00122 +2024-11-23 02:48:22.946661: train_loss -0.8211 +2024-11-23 02:48:22.946895: val_loss -0.7501 +2024-11-23 02:48:22.946980: Pseudo dice [0.852] +2024-11-23 02:48:22.947073: Epoch time: 18.72 s +2024-11-23 02:48:23.847716: +2024-11-23 02:48:23.847942: Epoch 7226 +2024-11-23 02:48:23.848074: Current learning rate: 0.00122 +2024-11-23 02:48:41.071531: train_loss -0.828 +2024-11-23 02:48:41.071743: val_loss -0.7879 +2024-11-23 02:48:41.071828: Pseudo dice [0.8527] +2024-11-23 02:48:41.071909: Epoch time: 17.22 s +2024-11-23 02:48:41.964144: +2024-11-23 02:48:41.964375: Epoch 7227 +2024-11-23 02:48:41.964493: Current learning rate: 0.00122 +2024-11-23 02:49:00.189305: train_loss -0.8332 +2024-11-23 02:49:00.189549: val_loss -0.8012 +2024-11-23 02:49:00.189627: Pseudo dice [0.8553] +2024-11-23 02:49:00.189712: Epoch time: 18.23 s +2024-11-23 02:49:01.084759: +2024-11-23 02:49:01.084990: Epoch 7228 +2024-11-23 02:49:01.085107: Current learning rate: 0.00122 +2024-11-23 02:49:19.598307: train_loss -0.8177 +2024-11-23 02:49:19.598514: val_loss -0.7902 +2024-11-23 02:49:19.598590: Pseudo dice [0.8571] +2024-11-23 02:49:19.598721: Epoch time: 18.51 s +2024-11-23 02:49:20.487520: +2024-11-23 02:49:20.487746: Epoch 7229 +2024-11-23 02:49:20.487857: Current learning rate: 0.00122 +2024-11-23 02:49:38.818230: train_loss -0.8236 +2024-11-23 02:49:38.818443: val_loss -0.7868 +2024-11-23 02:49:38.818537: Pseudo dice [0.8699] +2024-11-23 02:49:38.818635: Epoch time: 18.33 s +2024-11-23 02:49:39.711565: +2024-11-23 02:49:39.711775: Epoch 7230 +2024-11-23 02:49:39.711890: Current learning rate: 0.00122 +2024-11-23 02:49:57.960568: train_loss -0.8143 +2024-11-23 02:49:57.960803: val_loss -0.7674 +2024-11-23 02:49:57.960892: Pseudo dice [0.8536] +2024-11-23 02:49:57.960977: Epoch time: 18.25 s +2024-11-23 02:49:58.851503: +2024-11-23 02:49:58.851718: Epoch 7231 +2024-11-23 02:49:58.851836: Current learning rate: 0.00121 +2024-11-23 02:50:17.516108: train_loss -0.825 +2024-11-23 02:50:17.519267: val_loss -0.7493 +2024-11-23 02:50:17.519393: Pseudo dice [0.8583] +2024-11-23 02:50:17.519479: Epoch time: 18.67 s +2024-11-23 02:50:18.592968: +2024-11-23 02:50:18.593187: Epoch 7232 +2024-11-23 02:50:18.593316: Current learning rate: 0.00121 +2024-11-23 02:50:38.210700: train_loss -0.8181 +2024-11-23 02:50:38.210912: val_loss -0.7798 +2024-11-23 02:50:38.210989: Pseudo dice [0.8576] +2024-11-23 02:50:38.211077: Epoch time: 19.62 s +2024-11-23 02:50:39.101741: +2024-11-23 02:50:39.101974: Epoch 7233 +2024-11-23 02:50:39.102095: Current learning rate: 0.00121 +2024-11-23 02:50:56.809753: train_loss -0.8154 +2024-11-23 02:50:56.809966: val_loss -0.8029 +2024-11-23 02:50:56.812235: Pseudo dice [0.8586] +2024-11-23 02:50:56.812320: Epoch time: 17.71 s +2024-11-23 02:50:57.809468: +2024-11-23 02:50:57.809688: Epoch 7234 +2024-11-23 02:50:57.809800: Current learning rate: 0.00121 +2024-11-23 02:51:16.122504: train_loss -0.8182 +2024-11-23 02:51:16.128255: val_loss -0.7856 +2024-11-23 02:51:16.128378: Pseudo dice [0.8595] +2024-11-23 02:51:16.128474: Epoch time: 18.31 s +2024-11-23 02:51:17.024328: +2024-11-23 02:51:17.024554: Epoch 7235 +2024-11-23 02:51:17.024990: Current learning rate: 0.00121 +2024-11-23 02:51:35.684527: train_loss -0.8223 +2024-11-23 02:51:35.685034: val_loss -0.7705 +2024-11-23 02:51:35.685178: Pseudo dice [0.8628] +2024-11-23 02:51:35.685272: Epoch time: 18.66 s +2024-11-23 02:51:36.574594: +2024-11-23 02:51:36.574803: Epoch 7236 +2024-11-23 02:51:36.574922: Current learning rate: 0.00121 +2024-11-23 02:51:54.286254: train_loss -0.8263 +2024-11-23 02:51:54.286471: val_loss -0.788 +2024-11-23 02:51:54.286557: Pseudo dice [0.8553] +2024-11-23 02:51:54.286633: Epoch time: 17.71 s +2024-11-23 02:51:55.242612: +2024-11-23 02:51:55.242821: Epoch 7237 +2024-11-23 02:51:55.242940: Current learning rate: 0.00121 +2024-11-23 02:52:15.191749: train_loss -0.8156 +2024-11-23 02:52:15.191973: val_loss -0.7632 +2024-11-23 02:52:15.192065: Pseudo dice [0.8535] +2024-11-23 02:52:15.192167: Epoch time: 19.95 s +2024-11-23 02:52:16.088017: +2024-11-23 02:52:16.088248: Epoch 7238 +2024-11-23 02:52:16.088363: Current learning rate: 0.0012 +2024-11-23 02:52:35.253234: train_loss -0.816 +2024-11-23 02:52:35.253476: val_loss -0.7723 +2024-11-23 02:52:35.253570: Pseudo dice [0.8496] +2024-11-23 02:52:35.253659: Epoch time: 19.17 s +2024-11-23 02:52:36.264509: +2024-11-23 02:52:36.264715: Epoch 7239 +2024-11-23 02:52:36.264828: Current learning rate: 0.0012 +2024-11-23 02:52:54.972516: train_loss -0.8252 +2024-11-23 02:52:54.972738: val_loss -0.7708 +2024-11-23 02:52:54.972818: Pseudo dice [0.8485] +2024-11-23 02:52:54.972894: Epoch time: 18.71 s +2024-11-23 02:52:55.863905: +2024-11-23 02:52:55.864123: Epoch 7240 +2024-11-23 02:52:55.864259: Current learning rate: 0.0012 +2024-11-23 02:53:14.240976: train_loss -0.8234 +2024-11-23 02:53:14.241194: val_loss -0.7798 +2024-11-23 02:53:14.241275: Pseudo dice [0.8626] +2024-11-23 02:53:14.241351: Epoch time: 18.38 s +2024-11-23 02:53:15.128365: +2024-11-23 02:53:15.128613: Epoch 7241 +2024-11-23 02:53:15.128752: Current learning rate: 0.0012 +2024-11-23 02:53:33.680682: train_loss -0.8219 +2024-11-23 02:53:33.680899: val_loss -0.7989 +2024-11-23 02:53:33.680986: Pseudo dice [0.8624] +2024-11-23 02:53:33.683266: Epoch time: 18.55 s +2024-11-23 02:53:34.583257: +2024-11-23 02:53:34.583479: Epoch 7242 +2024-11-23 02:53:34.583599: Current learning rate: 0.0012 +2024-11-23 02:53:53.776498: train_loss -0.8232 +2024-11-23 02:53:53.776744: val_loss -0.7893 +2024-11-23 02:53:53.776837: Pseudo dice [0.862] +2024-11-23 02:53:53.776918: Epoch time: 19.19 s +2024-11-23 02:53:54.668222: +2024-11-23 02:53:54.668445: Epoch 7243 +2024-11-23 02:53:54.668566: Current learning rate: 0.0012 +2024-11-23 02:54:13.501920: train_loss -0.8265 +2024-11-23 02:54:13.502136: val_loss -0.7748 +2024-11-23 02:54:13.502218: Pseudo dice [0.866] +2024-11-23 02:54:13.502294: Epoch time: 18.83 s +2024-11-23 02:54:14.386176: +2024-11-23 02:54:14.386386: Epoch 7244 +2024-11-23 02:54:14.386515: Current learning rate: 0.0012 +2024-11-23 02:54:32.870785: train_loss -0.8313 +2024-11-23 02:54:32.870988: val_loss -0.7991 +2024-11-23 02:54:32.871078: Pseudo dice [0.8657] +2024-11-23 02:54:32.871156: Epoch time: 18.49 s +2024-11-23 02:54:34.146310: +2024-11-23 02:54:34.146523: Epoch 7245 +2024-11-23 02:54:34.146635: Current learning rate: 0.0012 +2024-11-23 02:54:51.886161: train_loss -0.8187 +2024-11-23 02:54:51.886402: val_loss -0.7735 +2024-11-23 02:54:51.886487: Pseudo dice [0.8611] +2024-11-23 02:54:51.886567: Epoch time: 17.74 s +2024-11-23 02:54:52.780480: +2024-11-23 02:54:52.780690: Epoch 7246 +2024-11-23 02:54:52.780802: Current learning rate: 0.00119 +2024-11-23 02:55:10.680048: train_loss -0.8178 +2024-11-23 02:55:10.680283: val_loss -0.7827 +2024-11-23 02:55:10.680363: Pseudo dice [0.8636] +2024-11-23 02:55:10.680462: Epoch time: 17.9 s +2024-11-23 02:55:11.567429: +2024-11-23 02:55:11.567646: Epoch 7247 +2024-11-23 02:55:11.567773: Current learning rate: 0.00119 +2024-11-23 02:55:30.317886: train_loss -0.8188 +2024-11-23 02:55:30.320315: val_loss -0.7653 +2024-11-23 02:55:30.320436: Pseudo dice [0.848] +2024-11-23 02:55:30.320521: Epoch time: 18.75 s +2024-11-23 02:55:31.327468: +2024-11-23 02:55:31.327670: Epoch 7248 +2024-11-23 02:55:31.327786: Current learning rate: 0.00119 +2024-11-23 02:55:49.944606: train_loss -0.8205 +2024-11-23 02:55:49.944824: val_loss -0.7861 +2024-11-23 02:55:49.944901: Pseudo dice [0.8588] +2024-11-23 02:55:49.944978: Epoch time: 18.62 s +2024-11-23 02:55:50.871522: +2024-11-23 02:55:50.871742: Epoch 7249 +2024-11-23 02:55:50.871853: Current learning rate: 0.00119 +2024-11-23 02:56:09.251502: train_loss -0.8331 +2024-11-23 02:56:09.256947: val_loss -0.7618 +2024-11-23 02:56:09.257073: Pseudo dice [0.8449] +2024-11-23 02:56:09.257162: Epoch time: 18.38 s +2024-11-23 02:56:10.551726: +2024-11-23 02:56:10.551970: Epoch 7250 +2024-11-23 02:56:10.552091: Current learning rate: 0.00119 +2024-11-23 02:56:30.246651: train_loss -0.8221 +2024-11-23 02:56:30.246859: val_loss -0.7785 +2024-11-23 02:56:30.246949: Pseudo dice [0.8443] +2024-11-23 02:56:30.247027: Epoch time: 19.7 s +2024-11-23 02:56:31.135399: +2024-11-23 02:56:31.135613: Epoch 7251 +2024-11-23 02:56:31.135741: Current learning rate: 0.00119 +2024-11-23 02:56:49.769260: train_loss -0.8219 +2024-11-23 02:56:49.769491: val_loss -0.7979 +2024-11-23 02:56:49.769572: Pseudo dice [0.8648] +2024-11-23 02:56:49.769650: Epoch time: 18.63 s +2024-11-23 02:56:50.733223: +2024-11-23 02:56:50.733432: Epoch 7252 +2024-11-23 02:56:50.733544: Current learning rate: 0.00119 +2024-11-23 02:57:09.489211: train_loss -0.8263 +2024-11-23 02:57:09.489425: val_loss -0.7945 +2024-11-23 02:57:09.489501: Pseudo dice [0.861] +2024-11-23 02:57:09.489597: Epoch time: 18.76 s +2024-11-23 02:57:10.380667: +2024-11-23 02:57:10.380887: Epoch 7253 +2024-11-23 02:57:10.381015: Current learning rate: 0.00118 +2024-11-23 02:57:29.099289: train_loss -0.8343 +2024-11-23 02:57:29.099549: val_loss -0.7663 +2024-11-23 02:57:29.099646: Pseudo dice [0.8697] +2024-11-23 02:57:29.099777: Epoch time: 18.72 s +2024-11-23 02:57:29.989655: +2024-11-23 02:57:29.989863: Epoch 7254 +2024-11-23 02:57:29.989978: Current learning rate: 0.00118 +2024-11-23 02:57:48.151088: train_loss -0.819 +2024-11-23 02:57:48.151290: val_loss -0.7616 +2024-11-23 02:57:48.151374: Pseudo dice [0.8676] +2024-11-23 02:57:48.151475: Epoch time: 18.16 s +2024-11-23 02:57:49.038504: +2024-11-23 02:57:49.038722: Epoch 7255 +2024-11-23 02:57:49.038849: Current learning rate: 0.00118 +2024-11-23 02:58:07.223497: train_loss -0.8192 +2024-11-23 02:58:07.223716: val_loss -0.7819 +2024-11-23 02:58:07.223809: Pseudo dice [0.8567] +2024-11-23 02:58:07.223884: Epoch time: 18.19 s +2024-11-23 02:58:08.621847: +2024-11-23 02:58:08.622076: Epoch 7256 +2024-11-23 02:58:08.622190: Current learning rate: 0.00118 +2024-11-23 02:58:27.564082: train_loss -0.8166 +2024-11-23 02:58:27.564344: val_loss -0.7938 +2024-11-23 02:58:27.564423: Pseudo dice [0.8571] +2024-11-23 02:58:27.564509: Epoch time: 18.94 s +2024-11-23 02:58:28.483210: +2024-11-23 02:58:28.483427: Epoch 7257 +2024-11-23 02:58:28.483545: Current learning rate: 0.00118 +2024-11-23 02:58:46.740879: train_loss -0.8281 +2024-11-23 02:58:46.741118: val_loss -0.7608 +2024-11-23 02:58:46.741205: Pseudo dice [0.8449] +2024-11-23 02:58:46.741285: Epoch time: 18.26 s +2024-11-23 02:58:47.657293: +2024-11-23 02:58:47.657498: Epoch 7258 +2024-11-23 02:58:47.657611: Current learning rate: 0.00118 +2024-11-23 02:59:07.819138: train_loss -0.8246 +2024-11-23 02:59:07.819365: val_loss -0.7716 +2024-11-23 02:59:07.819445: Pseudo dice [0.8657] +2024-11-23 02:59:07.819523: Epoch time: 20.16 s +2024-11-23 02:59:08.711391: +2024-11-23 02:59:08.711588: Epoch 7259 +2024-11-23 02:59:08.711695: Current learning rate: 0.00118 +2024-11-23 02:59:27.591201: train_loss -0.8262 +2024-11-23 02:59:27.591420: val_loss -0.7965 +2024-11-23 02:59:27.591516: Pseudo dice [0.8585] +2024-11-23 02:59:27.591614: Epoch time: 18.88 s +2024-11-23 02:59:28.488379: +2024-11-23 02:59:28.488588: Epoch 7260 +2024-11-23 02:59:28.488703: Current learning rate: 0.00117 +2024-11-23 02:59:45.929739: train_loss -0.8216 +2024-11-23 02:59:45.929998: val_loss -0.7926 +2024-11-23 02:59:45.930088: Pseudo dice [0.8554] +2024-11-23 02:59:45.930183: Epoch time: 17.44 s +2024-11-23 02:59:46.930232: +2024-11-23 02:59:46.930700: Epoch 7261 +2024-11-23 02:59:46.930824: Current learning rate: 0.00117 +2024-11-23 03:00:05.083154: train_loss -0.8262 +2024-11-23 03:00:05.083391: val_loss -0.8141 +2024-11-23 03:00:05.083481: Pseudo dice [0.8644] +2024-11-23 03:00:05.083565: Epoch time: 18.15 s +2024-11-23 03:00:05.983006: +2024-11-23 03:00:05.983233: Epoch 7262 +2024-11-23 03:00:05.983349: Current learning rate: 0.00117 +2024-11-23 03:00:24.715690: train_loss -0.8252 +2024-11-23 03:00:24.715904: val_loss -0.7542 +2024-11-23 03:00:24.715989: Pseudo dice [0.8605] +2024-11-23 03:00:24.716081: Epoch time: 18.73 s +2024-11-23 03:00:25.626806: +2024-11-23 03:00:25.627052: Epoch 7263 +2024-11-23 03:00:25.627188: Current learning rate: 0.00117 +2024-11-23 03:00:43.611289: train_loss -0.8242 +2024-11-23 03:00:43.611516: val_loss -0.7496 +2024-11-23 03:00:43.611618: Pseudo dice [0.8513] +2024-11-23 03:00:43.611721: Epoch time: 17.99 s +2024-11-23 03:00:44.500850: +2024-11-23 03:00:44.501054: Epoch 7264 +2024-11-23 03:00:44.501180: Current learning rate: 0.00117 +2024-11-23 03:01:02.563428: train_loss -0.8281 +2024-11-23 03:01:02.563730: val_loss -0.7709 +2024-11-23 03:01:02.563808: Pseudo dice [0.8607] +2024-11-23 03:01:02.563898: Epoch time: 18.06 s +2024-11-23 03:01:03.458988: +2024-11-23 03:01:03.459243: Epoch 7265 +2024-11-23 03:01:03.459357: Current learning rate: 0.00117 +2024-11-23 03:01:22.339586: train_loss -0.8237 +2024-11-23 03:01:22.339807: val_loss -0.7555 +2024-11-23 03:01:22.339892: Pseudo dice [0.859] +2024-11-23 03:01:22.339992: Epoch time: 18.88 s +2024-11-23 03:01:23.231198: +2024-11-23 03:01:23.231418: Epoch 7266 +2024-11-23 03:01:23.231534: Current learning rate: 0.00117 +2024-11-23 03:01:41.478984: train_loss -0.8256 +2024-11-23 03:01:41.479207: val_loss -0.771 +2024-11-23 03:01:41.479286: Pseudo dice [0.8513] +2024-11-23 03:01:41.479364: Epoch time: 18.25 s +2024-11-23 03:01:42.777727: +2024-11-23 03:01:42.777942: Epoch 7267 +2024-11-23 03:01:42.778072: Current learning rate: 0.00116 +2024-11-23 03:02:02.233668: train_loss -0.8296 +2024-11-23 03:02:02.234009: val_loss -0.7684 +2024-11-23 03:02:02.234106: Pseudo dice [0.8552] +2024-11-23 03:02:02.234195: Epoch time: 19.46 s +2024-11-23 03:02:03.123077: +2024-11-23 03:02:03.123292: Epoch 7268 +2024-11-23 03:02:03.123406: Current learning rate: 0.00116 +2024-11-23 03:02:20.544366: train_loss -0.8263 +2024-11-23 03:02:20.544582: val_loss -0.7878 +2024-11-23 03:02:20.544663: Pseudo dice [0.8577] +2024-11-23 03:02:20.544742: Epoch time: 17.42 s +2024-11-23 03:02:21.437227: +2024-11-23 03:02:21.437441: Epoch 7269 +2024-11-23 03:02:21.437565: Current learning rate: 0.00116 +2024-11-23 03:02:39.809126: train_loss -0.8223 +2024-11-23 03:02:39.809361: val_loss -0.7607 +2024-11-23 03:02:39.809459: Pseudo dice [0.8507] +2024-11-23 03:02:39.809536: Epoch time: 18.37 s +2024-11-23 03:02:40.808988: +2024-11-23 03:02:40.809211: Epoch 7270 +2024-11-23 03:02:40.809325: Current learning rate: 0.00116 +2024-11-23 03:02:57.753115: train_loss -0.8277 +2024-11-23 03:02:57.753327: val_loss -0.7826 +2024-11-23 03:02:57.753405: Pseudo dice [0.8614] +2024-11-23 03:02:57.753497: Epoch time: 16.94 s +2024-11-23 03:02:58.747372: +2024-11-23 03:02:58.747578: Epoch 7271 +2024-11-23 03:02:58.747698: Current learning rate: 0.00116 +2024-11-23 03:03:17.452640: train_loss -0.8263 +2024-11-23 03:03:17.452870: val_loss -0.7798 +2024-11-23 03:03:17.452950: Pseudo dice [0.8571] +2024-11-23 03:03:17.453031: Epoch time: 18.71 s +2024-11-23 03:03:18.340416: +2024-11-23 03:03:18.340645: Epoch 7272 +2024-11-23 03:03:18.340760: Current learning rate: 0.00116 +2024-11-23 03:03:36.046755: train_loss -0.8274 +2024-11-23 03:03:36.046983: val_loss -0.8009 +2024-11-23 03:03:36.047075: Pseudo dice [0.8613] +2024-11-23 03:03:36.047154: Epoch time: 17.71 s +2024-11-23 03:03:36.934055: +2024-11-23 03:03:36.934281: Epoch 7273 +2024-11-23 03:03:36.934392: Current learning rate: 0.00116 +2024-11-23 03:03:55.243465: train_loss -0.828 +2024-11-23 03:03:55.243693: val_loss -0.7777 +2024-11-23 03:03:55.243773: Pseudo dice [0.8569] +2024-11-23 03:03:55.243859: Epoch time: 18.31 s +2024-11-23 03:03:56.138487: +2024-11-23 03:03:56.138700: Epoch 7274 +2024-11-23 03:03:56.138805: Current learning rate: 0.00115 +2024-11-23 03:04:14.627762: train_loss -0.8191 +2024-11-23 03:04:14.627982: val_loss -0.7887 +2024-11-23 03:04:14.628067: Pseudo dice [0.8638] +2024-11-23 03:04:14.628150: Epoch time: 18.49 s +2024-11-23 03:04:15.526173: +2024-11-23 03:04:15.526381: Epoch 7275 +2024-11-23 03:04:15.526504: Current learning rate: 0.00115 +2024-11-23 03:04:33.354869: train_loss -0.8295 +2024-11-23 03:04:33.355108: val_loss -0.7732 +2024-11-23 03:04:33.355196: Pseudo dice [0.8455] +2024-11-23 03:04:33.360468: Epoch time: 17.83 s +2024-11-23 03:04:34.313486: +2024-11-23 03:04:34.313698: Epoch 7276 +2024-11-23 03:04:34.313824: Current learning rate: 0.00115 +2024-11-23 03:04:52.092180: train_loss -0.8208 +2024-11-23 03:04:52.092401: val_loss -0.7676 +2024-11-23 03:04:52.092489: Pseudo dice [0.8545] +2024-11-23 03:04:52.092576: Epoch time: 17.78 s +2024-11-23 03:04:52.983905: +2024-11-23 03:04:52.984098: Epoch 7277 +2024-11-23 03:04:52.984211: Current learning rate: 0.00115 +2024-11-23 03:05:11.817841: train_loss -0.8335 +2024-11-23 03:05:11.818065: val_loss -0.7689 +2024-11-23 03:05:11.818145: Pseudo dice [0.8584] +2024-11-23 03:05:11.818229: Epoch time: 18.83 s +2024-11-23 03:05:13.231553: +2024-11-23 03:05:13.231771: Epoch 7278 +2024-11-23 03:05:13.231901: Current learning rate: 0.00115 +2024-11-23 03:05:32.255347: train_loss -0.8164 +2024-11-23 03:05:32.255592: val_loss -0.7847 +2024-11-23 03:05:32.255704: Pseudo dice [0.8651] +2024-11-23 03:05:32.255804: Epoch time: 19.02 s +2024-11-23 03:05:33.154571: +2024-11-23 03:05:33.154804: Epoch 7279 +2024-11-23 03:05:33.154916: Current learning rate: 0.00115 +2024-11-23 03:05:50.657268: train_loss -0.8251 +2024-11-23 03:05:50.657485: val_loss -0.7649 +2024-11-23 03:05:50.657564: Pseudo dice [0.8454] +2024-11-23 03:05:50.657641: Epoch time: 17.5 s +2024-11-23 03:05:51.549102: +2024-11-23 03:05:51.549312: Epoch 7280 +2024-11-23 03:05:51.549426: Current learning rate: 0.00115 +2024-11-23 03:06:09.323801: train_loss -0.8205 +2024-11-23 03:06:09.324012: val_loss -0.7897 +2024-11-23 03:06:09.326328: Pseudo dice [0.8556] +2024-11-23 03:06:09.326443: Epoch time: 17.78 s +2024-11-23 03:06:10.309924: +2024-11-23 03:06:10.310138: Epoch 7281 +2024-11-23 03:06:10.310268: Current learning rate: 0.00114 +2024-11-23 03:06:28.715611: train_loss -0.825 +2024-11-23 03:06:28.715832: val_loss -0.7899 +2024-11-23 03:06:28.715912: Pseudo dice [0.8703] +2024-11-23 03:06:28.716012: Epoch time: 18.41 s +2024-11-23 03:06:29.696393: +2024-11-23 03:06:29.696630: Epoch 7282 +2024-11-23 03:06:29.696745: Current learning rate: 0.00114 +2024-11-23 03:06:48.403871: train_loss -0.8207 +2024-11-23 03:06:48.404115: val_loss -0.7933 +2024-11-23 03:06:48.404200: Pseudo dice [0.8546] +2024-11-23 03:06:48.404280: Epoch time: 18.71 s +2024-11-23 03:06:49.296197: +2024-11-23 03:06:49.296419: Epoch 7283 +2024-11-23 03:06:49.296545: Current learning rate: 0.00114 +2024-11-23 03:07:08.362550: train_loss -0.8177 +2024-11-23 03:07:08.362849: val_loss -0.7766 +2024-11-23 03:07:08.362942: Pseudo dice [0.8668] +2024-11-23 03:07:08.363048: Epoch time: 19.07 s +2024-11-23 03:07:09.253652: +2024-11-23 03:07:09.253870: Epoch 7284 +2024-11-23 03:07:09.253987: Current learning rate: 0.00114 +2024-11-23 03:07:27.952456: train_loss -0.8248 +2024-11-23 03:07:27.952687: val_loss -0.7847 +2024-11-23 03:07:27.952764: Pseudo dice [0.8605] +2024-11-23 03:07:27.952840: Epoch time: 18.7 s +2024-11-23 03:07:28.844283: +2024-11-23 03:07:28.844497: Epoch 7285 +2024-11-23 03:07:28.844610: Current learning rate: 0.00114 +2024-11-23 03:07:47.396947: train_loss -0.8247 +2024-11-23 03:07:47.397182: val_loss -0.7654 +2024-11-23 03:07:47.397279: Pseudo dice [0.8607] +2024-11-23 03:07:47.397377: Epoch time: 18.55 s +2024-11-23 03:07:48.295281: +2024-11-23 03:07:48.295522: Epoch 7286 +2024-11-23 03:07:48.295649: Current learning rate: 0.00114 +2024-11-23 03:08:06.768577: train_loss -0.8255 +2024-11-23 03:08:06.768792: val_loss -0.7783 +2024-11-23 03:08:06.768878: Pseudo dice [0.8607] +2024-11-23 03:08:06.768952: Epoch time: 18.47 s +2024-11-23 03:08:07.654448: +2024-11-23 03:08:07.654663: Epoch 7287 +2024-11-23 03:08:07.654808: Current learning rate: 0.00114 +2024-11-23 03:08:26.160319: train_loss -0.8278 +2024-11-23 03:08:26.160608: val_loss -0.7538 +2024-11-23 03:08:26.160701: Pseudo dice [0.8552] +2024-11-23 03:08:26.160787: Epoch time: 18.51 s +2024-11-23 03:08:27.052236: +2024-11-23 03:08:27.052444: Epoch 7288 +2024-11-23 03:08:27.052581: Current learning rate: 0.00113 +2024-11-23 03:08:45.187194: train_loss -0.8286 +2024-11-23 03:08:45.187411: val_loss -0.7859 +2024-11-23 03:08:45.187494: Pseudo dice [0.8627] +2024-11-23 03:08:45.187584: Epoch time: 18.14 s +2024-11-23 03:08:46.081005: +2024-11-23 03:08:46.081204: Epoch 7289 +2024-11-23 03:08:46.081315: Current learning rate: 0.00113 +2024-11-23 03:09:03.200539: train_loss -0.8312 +2024-11-23 03:09:03.201156: val_loss -0.7954 +2024-11-23 03:09:03.201279: Pseudo dice [0.8595] +2024-11-23 03:09:03.201365: Epoch time: 17.12 s +2024-11-23 03:09:04.092747: +2024-11-23 03:09:04.092959: Epoch 7290 +2024-11-23 03:09:04.093079: Current learning rate: 0.00113 +2024-11-23 03:09:22.762687: train_loss -0.8248 +2024-11-23 03:09:22.762898: val_loss -0.7728 +2024-11-23 03:09:22.762975: Pseudo dice [0.8695] +2024-11-23 03:09:22.763067: Epoch time: 18.67 s +2024-11-23 03:09:23.656827: +2024-11-23 03:09:23.657052: Epoch 7291 +2024-11-23 03:09:23.657178: Current learning rate: 0.00113 +2024-11-23 03:09:42.509028: train_loss -0.826 +2024-11-23 03:09:42.509319: val_loss -0.7533 +2024-11-23 03:09:42.509404: Pseudo dice [0.8492] +2024-11-23 03:09:42.509501: Epoch time: 18.85 s +2024-11-23 03:09:43.658749: +2024-11-23 03:09:43.658983: Epoch 7292 +2024-11-23 03:09:43.659102: Current learning rate: 0.00113 +2024-11-23 03:10:02.372932: train_loss -0.8308 +2024-11-23 03:10:02.373218: val_loss -0.7644 +2024-11-23 03:10:02.373366: Pseudo dice [0.8553] +2024-11-23 03:10:02.373451: Epoch time: 18.71 s +2024-11-23 03:10:03.277092: +2024-11-23 03:10:03.277315: Epoch 7293 +2024-11-23 03:10:03.277445: Current learning rate: 0.00113 +2024-11-23 03:10:21.580324: train_loss -0.8324 +2024-11-23 03:10:21.580580: val_loss -0.7531 +2024-11-23 03:10:21.580659: Pseudo dice [0.8565] +2024-11-23 03:10:21.580739: Epoch time: 18.3 s +2024-11-23 03:10:22.526457: +2024-11-23 03:10:22.526664: Epoch 7294 +2024-11-23 03:10:22.526776: Current learning rate: 0.00112 +2024-11-23 03:10:40.443229: train_loss -0.8232 +2024-11-23 03:10:40.443455: val_loss -0.7931 +2024-11-23 03:10:40.443555: Pseudo dice [0.8651] +2024-11-23 03:10:40.443635: Epoch time: 17.92 s +2024-11-23 03:10:41.334999: +2024-11-23 03:10:41.335218: Epoch 7295 +2024-11-23 03:10:41.335329: Current learning rate: 0.00112 +2024-11-23 03:11:00.448090: train_loss -0.8264 +2024-11-23 03:11:00.448318: val_loss -0.7905 +2024-11-23 03:11:00.448410: Pseudo dice [0.8577] +2024-11-23 03:11:00.448487: Epoch time: 19.11 s +2024-11-23 03:11:01.342795: +2024-11-23 03:11:01.343020: Epoch 7296 +2024-11-23 03:11:01.343138: Current learning rate: 0.00112 +2024-11-23 03:11:19.877368: train_loss -0.8202 +2024-11-23 03:11:19.877620: val_loss -0.7684 +2024-11-23 03:11:19.877718: Pseudo dice [0.8593] +2024-11-23 03:11:19.877807: Epoch time: 18.54 s +2024-11-23 03:11:20.772824: +2024-11-23 03:11:20.773020: Epoch 7297 +2024-11-23 03:11:20.773136: Current learning rate: 0.00112 +2024-11-23 03:11:38.759018: train_loss -0.8261 +2024-11-23 03:11:38.759252: val_loss -0.7675 +2024-11-23 03:11:38.759356: Pseudo dice [0.8607] +2024-11-23 03:11:38.759436: Epoch time: 17.99 s +2024-11-23 03:11:39.667188: +2024-11-23 03:11:39.667400: Epoch 7298 +2024-11-23 03:11:39.667518: Current learning rate: 0.00112 +2024-11-23 03:11:57.707949: train_loss -0.8268 +2024-11-23 03:11:57.708185: val_loss -0.7911 +2024-11-23 03:11:57.708267: Pseudo dice [0.8601] +2024-11-23 03:11:57.708365: Epoch time: 18.04 s +2024-11-23 03:11:58.626866: +2024-11-23 03:11:58.627053: Epoch 7299 +2024-11-23 03:11:58.627179: Current learning rate: 0.00112 +2024-11-23 03:12:17.277476: train_loss -0.826 +2024-11-23 03:12:17.277699: val_loss -0.779 +2024-11-23 03:12:17.277789: Pseudo dice [0.8674] +2024-11-23 03:12:17.277863: Epoch time: 18.65 s +2024-11-23 03:12:18.911915: +2024-11-23 03:12:18.912130: Epoch 7300 +2024-11-23 03:12:18.912256: Current learning rate: 0.00112 +2024-11-23 03:12:37.941398: train_loss -0.8278 +2024-11-23 03:12:37.941723: val_loss -0.7951 +2024-11-23 03:12:37.941812: Pseudo dice [0.8535] +2024-11-23 03:12:37.941892: Epoch time: 19.03 s +2024-11-23 03:12:38.842113: +2024-11-23 03:12:38.842351: Epoch 7301 +2024-11-23 03:12:38.842485: Current learning rate: 0.00111 +2024-11-23 03:12:57.335809: train_loss -0.8268 +2024-11-23 03:12:57.336034: val_loss -0.7677 +2024-11-23 03:12:57.336119: Pseudo dice [0.8685] +2024-11-23 03:12:57.336200: Epoch time: 18.49 s +2024-11-23 03:12:58.435744: +2024-11-23 03:12:58.435946: Epoch 7302 +2024-11-23 03:12:58.436074: Current learning rate: 0.00111 +2024-11-23 03:13:15.603612: train_loss -0.8237 +2024-11-23 03:13:15.603837: val_loss -0.7888 +2024-11-23 03:13:15.603928: Pseudo dice [0.8545] +2024-11-23 03:13:15.604012: Epoch time: 17.17 s +2024-11-23 03:13:16.501072: +2024-11-23 03:13:16.501291: Epoch 7303 +2024-11-23 03:13:16.501410: Current learning rate: 0.00111 +2024-11-23 03:13:34.291644: train_loss -0.8296 +2024-11-23 03:13:34.291893: val_loss -0.7816 +2024-11-23 03:13:34.291972: Pseudo dice [0.8632] +2024-11-23 03:13:34.292052: Epoch time: 17.79 s +2024-11-23 03:13:35.185094: +2024-11-23 03:13:35.185313: Epoch 7304 +2024-11-23 03:13:35.185433: Current learning rate: 0.00111 +2024-11-23 03:13:53.592237: train_loss -0.824 +2024-11-23 03:13:53.592530: val_loss -0.7952 +2024-11-23 03:13:53.592618: Pseudo dice [0.8608] +2024-11-23 03:13:53.592702: Epoch time: 18.41 s +2024-11-23 03:13:54.528715: +2024-11-23 03:13:54.528905: Epoch 7305 +2024-11-23 03:13:54.529025: Current learning rate: 0.00111 +2024-11-23 03:14:12.338915: train_loss -0.8281 +2024-11-23 03:14:12.344316: val_loss -0.777 +2024-11-23 03:14:12.344438: Pseudo dice [0.8645] +2024-11-23 03:14:12.344538: Epoch time: 17.81 s +2024-11-23 03:14:13.262431: +2024-11-23 03:14:13.262643: Epoch 7306 +2024-11-23 03:14:13.262764: Current learning rate: 0.00111 +2024-11-23 03:14:31.670165: train_loss -0.827 +2024-11-23 03:14:31.670393: val_loss -0.7901 +2024-11-23 03:14:31.670473: Pseudo dice [0.8588] +2024-11-23 03:14:31.670563: Epoch time: 18.41 s +2024-11-23 03:14:32.560598: +2024-11-23 03:14:32.560846: Epoch 7307 +2024-11-23 03:14:32.560966: Current learning rate: 0.00111 +2024-11-23 03:14:51.320076: train_loss -0.8279 +2024-11-23 03:14:51.320287: val_loss -0.7905 +2024-11-23 03:14:51.320359: Pseudo dice [0.8571] +2024-11-23 03:14:51.320444: Epoch time: 18.76 s +2024-11-23 03:14:52.249705: +2024-11-23 03:14:52.249938: Epoch 7308 +2024-11-23 03:14:52.250052: Current learning rate: 0.0011 +2024-11-23 03:15:10.271160: train_loss -0.8186 +2024-11-23 03:15:10.271431: val_loss -0.792 +2024-11-23 03:15:10.271531: Pseudo dice [0.8519] +2024-11-23 03:15:10.271608: Epoch time: 18.02 s +2024-11-23 03:15:11.162977: +2024-11-23 03:15:11.163246: Epoch 7309 +2024-11-23 03:15:11.163356: Current learning rate: 0.0011 +2024-11-23 03:15:29.387616: train_loss -0.8307 +2024-11-23 03:15:29.387835: val_loss -0.784 +2024-11-23 03:15:29.387917: Pseudo dice [0.8545] +2024-11-23 03:15:29.388009: Epoch time: 18.23 s +2024-11-23 03:15:30.278878: +2024-11-23 03:15:30.279122: Epoch 7310 +2024-11-23 03:15:30.279242: Current learning rate: 0.0011 +2024-11-23 03:15:48.404305: train_loss -0.8259 +2024-11-23 03:15:48.404522: val_loss -0.7844 +2024-11-23 03:15:48.404603: Pseudo dice [0.8569] +2024-11-23 03:15:48.404700: Epoch time: 18.13 s +2024-11-23 03:15:49.292053: +2024-11-23 03:15:49.292247: Epoch 7311 +2024-11-23 03:15:49.292370: Current learning rate: 0.0011 +2024-11-23 03:16:08.404680: train_loss -0.8232 +2024-11-23 03:16:08.405191: val_loss -0.7852 +2024-11-23 03:16:08.405306: Pseudo dice [0.8609] +2024-11-23 03:16:08.405397: Epoch time: 19.11 s +2024-11-23 03:16:09.293453: +2024-11-23 03:16:09.293883: Epoch 7312 +2024-11-23 03:16:09.294032: Current learning rate: 0.0011 +2024-11-23 03:16:27.917243: train_loss -0.8208 +2024-11-23 03:16:27.917457: val_loss -0.776 +2024-11-23 03:16:27.917537: Pseudo dice [0.8524] +2024-11-23 03:16:27.917628: Epoch time: 18.62 s +2024-11-23 03:16:28.921865: +2024-11-23 03:16:28.922363: Epoch 7313 +2024-11-23 03:16:28.922509: Current learning rate: 0.0011 +2024-11-23 03:16:46.671433: train_loss -0.8217 +2024-11-23 03:16:46.671695: val_loss -0.8035 +2024-11-23 03:16:46.671794: Pseudo dice [0.8681] +2024-11-23 03:16:46.671880: Epoch time: 17.75 s +2024-11-23 03:16:47.759694: +2024-11-23 03:16:47.760137: Epoch 7314 +2024-11-23 03:16:47.760274: Current learning rate: 0.0011 +2024-11-23 03:17:06.336042: train_loss -0.8184 +2024-11-23 03:17:06.338454: val_loss -0.7754 +2024-11-23 03:17:06.338590: Pseudo dice [0.8606] +2024-11-23 03:17:06.338691: Epoch time: 18.58 s +2024-11-23 03:17:07.287289: +2024-11-23 03:17:07.287702: Epoch 7315 +2024-11-23 03:17:07.287843: Current learning rate: 0.00109 +2024-11-23 03:17:25.887950: train_loss -0.8208 +2024-11-23 03:17:25.888197: val_loss -0.7857 +2024-11-23 03:17:25.893470: Pseudo dice [0.8559] +2024-11-23 03:17:25.893649: Epoch time: 18.6 s +2024-11-23 03:17:26.875504: +2024-11-23 03:17:26.875920: Epoch 7316 +2024-11-23 03:17:26.876053: Current learning rate: 0.00109 +2024-11-23 03:17:44.755596: train_loss -0.8185 +2024-11-23 03:17:44.755814: val_loss -0.782 +2024-11-23 03:17:44.755893: Pseudo dice [0.8651] +2024-11-23 03:17:44.758204: Epoch time: 17.88 s +2024-11-23 03:17:45.667790: +2024-11-23 03:17:45.668226: Epoch 7317 +2024-11-23 03:17:45.668383: Current learning rate: 0.00109 +2024-11-23 03:18:03.719134: train_loss -0.8217 +2024-11-23 03:18:03.719346: val_loss -0.7733 +2024-11-23 03:18:03.719422: Pseudo dice [0.8584] +2024-11-23 03:18:03.719503: Epoch time: 18.05 s +2024-11-23 03:18:04.656789: +2024-11-23 03:18:04.657232: Epoch 7318 +2024-11-23 03:18:04.657369: Current learning rate: 0.00109 +2024-11-23 03:18:24.064608: train_loss -0.8235 +2024-11-23 03:18:24.064858: val_loss -0.7943 +2024-11-23 03:18:24.064945: Pseudo dice [0.8674] +2024-11-23 03:18:24.065044: Epoch time: 19.41 s +2024-11-23 03:18:24.964162: +2024-11-23 03:18:24.964587: Epoch 7319 +2024-11-23 03:18:24.964727: Current learning rate: 0.00109 +2024-11-23 03:18:45.354077: train_loss -0.8184 +2024-11-23 03:18:45.356476: val_loss -0.7795 +2024-11-23 03:18:45.356586: Pseudo dice [0.8662] +2024-11-23 03:18:45.356667: Epoch time: 20.39 s +2024-11-23 03:18:46.295650: +2024-11-23 03:18:46.296048: Epoch 7320 +2024-11-23 03:18:46.296196: Current learning rate: 0.00109 +2024-11-23 03:19:04.881848: train_loss -0.8137 +2024-11-23 03:19:04.882065: val_loss -0.7835 +2024-11-23 03:19:04.882141: Pseudo dice [0.872] +2024-11-23 03:19:04.882220: Epoch time: 18.59 s +2024-11-23 03:19:05.829462: +2024-11-23 03:19:05.829877: Epoch 7321 +2024-11-23 03:19:05.830015: Current learning rate: 0.00109 +2024-11-23 03:19:24.643722: train_loss -0.8241 +2024-11-23 03:19:24.643928: val_loss -0.7635 +2024-11-23 03:19:24.644017: Pseudo dice [0.8505] +2024-11-23 03:19:24.644098: Epoch time: 18.82 s +2024-11-23 03:19:25.812231: +2024-11-23 03:19:25.812658: Epoch 7322 +2024-11-23 03:19:25.812789: Current learning rate: 0.00108 +2024-11-23 03:19:43.999199: train_loss -0.8242 +2024-11-23 03:19:43.999471: val_loss -0.7836 +2024-11-23 03:19:43.999556: Pseudo dice [0.8417] +2024-11-23 03:19:43.999638: Epoch time: 18.19 s +2024-11-23 03:19:44.886946: +2024-11-23 03:19:44.887333: Epoch 7323 +2024-11-23 03:19:44.887458: Current learning rate: 0.00108 +2024-11-23 03:20:03.242799: train_loss -0.8181 +2024-11-23 03:20:03.243019: val_loss -0.7831 +2024-11-23 03:20:03.243126: Pseudo dice [0.8589] +2024-11-23 03:20:03.243210: Epoch time: 18.36 s +2024-11-23 03:20:04.130320: +2024-11-23 03:20:04.130737: Epoch 7324 +2024-11-23 03:20:04.130868: Current learning rate: 0.00108 +2024-11-23 03:20:22.870633: train_loss -0.8199 +2024-11-23 03:20:22.870832: val_loss -0.7643 +2024-11-23 03:20:22.870917: Pseudo dice [0.8585] +2024-11-23 03:20:22.870992: Epoch time: 18.74 s +2024-11-23 03:20:23.798124: +2024-11-23 03:20:23.798545: Epoch 7325 +2024-11-23 03:20:23.798678: Current learning rate: 0.00108 +2024-11-23 03:20:42.809768: train_loss -0.832 +2024-11-23 03:20:42.809972: val_loss -0.7935 +2024-11-23 03:20:42.810052: Pseudo dice [0.8696] +2024-11-23 03:20:42.810137: Epoch time: 19.01 s +2024-11-23 03:20:43.804753: +2024-11-23 03:20:43.805170: Epoch 7326 +2024-11-23 03:20:43.805307: Current learning rate: 0.00108 +2024-11-23 03:21:01.406692: train_loss -0.8238 +2024-11-23 03:21:01.406939: val_loss -0.7992 +2024-11-23 03:21:01.407019: Pseudo dice [0.8599] +2024-11-23 03:21:01.407105: Epoch time: 17.6 s +2024-11-23 03:21:02.297839: +2024-11-23 03:21:02.298249: Epoch 7327 +2024-11-23 03:21:02.298379: Current learning rate: 0.00108 +2024-11-23 03:21:19.874941: train_loss -0.827 +2024-11-23 03:21:19.875178: val_loss -0.7834 +2024-11-23 03:21:19.875329: Pseudo dice [0.8673] +2024-11-23 03:21:19.875406: Epoch time: 17.58 s +2024-11-23 03:21:20.799808: +2024-11-23 03:21:20.800226: Epoch 7328 +2024-11-23 03:21:20.800360: Current learning rate: 0.00108 +2024-11-23 03:21:38.590204: train_loss -0.8233 +2024-11-23 03:21:38.590447: val_loss -0.786 +2024-11-23 03:21:38.590539: Pseudo dice [0.8527] +2024-11-23 03:21:38.592844: Epoch time: 17.79 s +2024-11-23 03:21:39.488270: +2024-11-23 03:21:39.488679: Epoch 7329 +2024-11-23 03:21:39.488814: Current learning rate: 0.00107 +2024-11-23 03:21:57.543504: train_loss -0.8261 +2024-11-23 03:21:57.543735: val_loss -0.7859 +2024-11-23 03:21:57.543822: Pseudo dice [0.8531] +2024-11-23 03:21:57.543911: Epoch time: 18.06 s +2024-11-23 03:21:58.446618: +2024-11-23 03:21:58.447042: Epoch 7330 +2024-11-23 03:21:58.447187: Current learning rate: 0.00107 +2024-11-23 03:22:16.768900: train_loss -0.8372 +2024-11-23 03:22:16.769123: val_loss -0.7912 +2024-11-23 03:22:16.769206: Pseudo dice [0.8577] +2024-11-23 03:22:16.769290: Epoch time: 18.32 s +2024-11-23 03:22:17.660746: +2024-11-23 03:22:17.661191: Epoch 7331 +2024-11-23 03:22:17.661347: Current learning rate: 0.00107 +2024-11-23 03:22:36.432194: train_loss -0.8241 +2024-11-23 03:22:36.432417: val_loss -0.7878 +2024-11-23 03:22:36.432503: Pseudo dice [0.8531] +2024-11-23 03:22:36.432580: Epoch time: 18.77 s +2024-11-23 03:22:37.316792: +2024-11-23 03:22:37.317227: Epoch 7332 +2024-11-23 03:22:37.317372: Current learning rate: 0.00107 +2024-11-23 03:22:55.752732: train_loss -0.8164 +2024-11-23 03:22:55.752935: val_loss -0.7938 +2024-11-23 03:22:55.753015: Pseudo dice [0.8658] +2024-11-23 03:22:55.753104: Epoch time: 18.44 s +2024-11-23 03:22:57.033198: +2024-11-23 03:22:57.033428: Epoch 7333 +2024-11-23 03:22:57.033547: Current learning rate: 0.00107 +2024-11-23 03:23:15.770583: train_loss -0.8241 +2024-11-23 03:23:15.770810: val_loss -0.7812 +2024-11-23 03:23:15.770894: Pseudo dice [0.8509] +2024-11-23 03:23:15.770972: Epoch time: 18.74 s +2024-11-23 03:23:16.661067: +2024-11-23 03:23:16.661316: Epoch 7334 +2024-11-23 03:23:16.661439: Current learning rate: 0.00107 +2024-11-23 03:23:34.338372: train_loss -0.822 +2024-11-23 03:23:34.338591: val_loss -0.7749 +2024-11-23 03:23:34.338671: Pseudo dice [0.8486] +2024-11-23 03:23:34.338759: Epoch time: 17.68 s +2024-11-23 03:23:35.228206: +2024-11-23 03:23:35.228419: Epoch 7335 +2024-11-23 03:23:35.228543: Current learning rate: 0.00107 +2024-11-23 03:23:53.750979: train_loss -0.8234 +2024-11-23 03:23:53.751200: val_loss -0.7754 +2024-11-23 03:23:53.751276: Pseudo dice [0.8561] +2024-11-23 03:23:53.751351: Epoch time: 18.52 s +2024-11-23 03:23:54.644503: +2024-11-23 03:23:54.644703: Epoch 7336 +2024-11-23 03:23:54.644811: Current learning rate: 0.00106 +2024-11-23 03:24:13.275548: train_loss -0.8251 +2024-11-23 03:24:13.275760: val_loss -0.78 +2024-11-23 03:24:13.275836: Pseudo dice [0.8554] +2024-11-23 03:24:13.275916: Epoch time: 18.63 s +2024-11-23 03:24:14.294846: +2024-11-23 03:24:14.295166: Epoch 7337 +2024-11-23 03:24:14.295307: Current learning rate: 0.00106 +2024-11-23 03:24:34.362107: train_loss -0.8259 +2024-11-23 03:24:34.362408: val_loss -0.7877 +2024-11-23 03:24:34.362510: Pseudo dice [0.8701] +2024-11-23 03:24:34.362600: Epoch time: 20.07 s +2024-11-23 03:24:35.262219: +2024-11-23 03:24:35.262429: Epoch 7338 +2024-11-23 03:24:35.262546: Current learning rate: 0.00106 +2024-11-23 03:24:53.670412: train_loss -0.8288 +2024-11-23 03:24:53.670664: val_loss -0.7859 +2024-11-23 03:24:53.670746: Pseudo dice [0.8557] +2024-11-23 03:24:53.671122: Epoch time: 18.41 s +2024-11-23 03:24:54.560878: +2024-11-23 03:24:54.561093: Epoch 7339 +2024-11-23 03:24:54.561203: Current learning rate: 0.00106 +2024-11-23 03:25:13.149544: train_loss -0.819 +2024-11-23 03:25:13.149751: val_loss -0.7755 +2024-11-23 03:25:13.149825: Pseudo dice [0.8505] +2024-11-23 03:25:13.149906: Epoch time: 18.59 s +2024-11-23 03:25:14.043702: +2024-11-23 03:25:14.043943: Epoch 7340 +2024-11-23 03:25:14.044066: Current learning rate: 0.00106 +2024-11-23 03:25:32.416662: train_loss -0.8223 +2024-11-23 03:25:32.416878: val_loss -0.7815 +2024-11-23 03:25:32.416958: Pseudo dice [0.861] +2024-11-23 03:25:32.417054: Epoch time: 18.37 s +2024-11-23 03:25:33.311830: +2024-11-23 03:25:33.312052: Epoch 7341 +2024-11-23 03:25:33.312181: Current learning rate: 0.00106 +2024-11-23 03:25:52.094919: train_loss -0.8217 +2024-11-23 03:25:52.095160: val_loss -0.805 +2024-11-23 03:25:52.095236: Pseudo dice [0.8644] +2024-11-23 03:25:52.095318: Epoch time: 18.78 s +2024-11-23 03:25:52.986528: +2024-11-23 03:25:52.986725: Epoch 7342 +2024-11-23 03:25:52.986842: Current learning rate: 0.00106 +2024-11-23 03:26:10.902768: train_loss -0.8313 +2024-11-23 03:26:10.902977: val_loss -0.7766 +2024-11-23 03:26:10.903063: Pseudo dice [0.8645] +2024-11-23 03:26:10.903141: Epoch time: 17.92 s +2024-11-23 03:26:11.795052: +2024-11-23 03:26:11.795259: Epoch 7343 +2024-11-23 03:26:11.795373: Current learning rate: 0.00105 +2024-11-23 03:26:30.280396: train_loss -0.8319 +2024-11-23 03:26:30.280662: val_loss -0.7746 +2024-11-23 03:26:30.280739: Pseudo dice [0.8474] +2024-11-23 03:26:30.280819: Epoch time: 18.49 s +2024-11-23 03:26:31.167900: +2024-11-23 03:26:31.168120: Epoch 7344 +2024-11-23 03:26:31.168245: Current learning rate: 0.00105 +2024-11-23 03:26:48.993048: train_loss -0.8236 +2024-11-23 03:26:48.993542: val_loss -0.7811 +2024-11-23 03:26:48.993656: Pseudo dice [0.8658] +2024-11-23 03:26:48.993774: Epoch time: 17.83 s +2024-11-23 03:26:49.883782: +2024-11-23 03:26:49.884001: Epoch 7345 +2024-11-23 03:26:49.884122: Current learning rate: 0.00105 +2024-11-23 03:27:08.997628: train_loss -0.816 +2024-11-23 03:27:08.997841: val_loss -0.7861 +2024-11-23 03:27:08.997921: Pseudo dice [0.858] +2024-11-23 03:27:08.997998: Epoch time: 19.11 s +2024-11-23 03:27:09.887930: +2024-11-23 03:27:09.888140: Epoch 7346 +2024-11-23 03:27:09.888255: Current learning rate: 0.00105 +2024-11-23 03:27:28.914161: train_loss -0.8194 +2024-11-23 03:27:28.914380: val_loss -0.7791 +2024-11-23 03:27:28.914464: Pseudo dice [0.8588] +2024-11-23 03:27:28.914548: Epoch time: 19.03 s +2024-11-23 03:27:29.802356: +2024-11-23 03:27:29.802583: Epoch 7347 +2024-11-23 03:27:29.802700: Current learning rate: 0.00105 +2024-11-23 03:27:47.567136: train_loss -0.8237 +2024-11-23 03:27:47.567355: val_loss -0.7657 +2024-11-23 03:27:47.567450: Pseudo dice [0.8501] +2024-11-23 03:27:47.567541: Epoch time: 17.77 s +2024-11-23 03:27:48.453664: +2024-11-23 03:27:48.453902: Epoch 7348 +2024-11-23 03:27:48.454018: Current learning rate: 0.00105 +2024-11-23 03:28:07.200416: train_loss -0.8281 +2024-11-23 03:28:07.200664: val_loss -0.7873 +2024-11-23 03:28:07.200742: Pseudo dice [0.8627] +2024-11-23 03:28:07.200840: Epoch time: 18.75 s +2024-11-23 03:28:08.095777: +2024-11-23 03:28:08.095991: Epoch 7349 +2024-11-23 03:28:08.096123: Current learning rate: 0.00105 +2024-11-23 03:28:26.971785: train_loss -0.8257 +2024-11-23 03:28:26.972011: val_loss -0.7904 +2024-11-23 03:28:26.972136: Pseudo dice [0.8625] +2024-11-23 03:28:26.972212: Epoch time: 18.88 s +2024-11-23 03:28:28.272991: +2024-11-23 03:28:28.273216: Epoch 7350 +2024-11-23 03:28:28.273329: Current learning rate: 0.00104 +2024-11-23 03:28:46.497153: train_loss -0.8175 +2024-11-23 03:28:46.497360: val_loss -0.7865 +2024-11-23 03:28:46.497446: Pseudo dice [0.8589] +2024-11-23 03:28:46.497524: Epoch time: 18.22 s +2024-11-23 03:28:47.386043: +2024-11-23 03:28:47.386246: Epoch 7351 +2024-11-23 03:28:47.386365: Current learning rate: 0.00104 +2024-11-23 03:29:05.392228: train_loss -0.8204 +2024-11-23 03:29:05.392500: val_loss -0.7795 +2024-11-23 03:29:05.392587: Pseudo dice [0.8604] +2024-11-23 03:29:05.392665: Epoch time: 18.01 s +2024-11-23 03:29:06.316840: +2024-11-23 03:29:06.317070: Epoch 7352 +2024-11-23 03:29:06.317188: Current learning rate: 0.00104 +2024-11-23 03:29:24.424185: train_loss -0.8244 +2024-11-23 03:29:24.424429: val_loss -0.7803 +2024-11-23 03:29:24.424504: Pseudo dice [0.8571] +2024-11-23 03:29:24.424583: Epoch time: 18.11 s +2024-11-23 03:29:25.476597: +2024-11-23 03:29:25.476799: Epoch 7353 +2024-11-23 03:29:25.476915: Current learning rate: 0.00104 +2024-11-23 03:29:43.828859: train_loss -0.8325 +2024-11-23 03:29:43.829073: val_loss -0.7879 +2024-11-23 03:29:43.829160: Pseudo dice [0.8511] +2024-11-23 03:29:43.829253: Epoch time: 18.35 s +2024-11-23 03:29:44.717535: +2024-11-23 03:29:44.717759: Epoch 7354 +2024-11-23 03:29:44.717884: Current learning rate: 0.00104 +2024-11-23 03:30:03.371816: train_loss -0.8242 +2024-11-23 03:30:03.372033: val_loss -0.7925 +2024-11-23 03:30:03.372122: Pseudo dice [0.8629] +2024-11-23 03:30:03.372201: Epoch time: 18.66 s +2024-11-23 03:30:04.657948: +2024-11-23 03:30:04.658206: Epoch 7355 +2024-11-23 03:30:04.658322: Current learning rate: 0.00104 +2024-11-23 03:30:23.343571: train_loss -0.825 +2024-11-23 03:30:23.343831: val_loss -0.7681 +2024-11-23 03:30:23.343930: Pseudo dice [0.8571] +2024-11-23 03:30:23.344016: Epoch time: 18.69 s +2024-11-23 03:30:24.241617: +2024-11-23 03:30:24.241872: Epoch 7356 +2024-11-23 03:30:24.242011: Current learning rate: 0.00104 +2024-11-23 03:30:43.315081: train_loss -0.8248 +2024-11-23 03:30:43.315328: val_loss -0.7722 +2024-11-23 03:30:43.315419: Pseudo dice [0.8631] +2024-11-23 03:30:43.315508: Epoch time: 19.07 s +2024-11-23 03:30:44.208026: +2024-11-23 03:30:44.208266: Epoch 7357 +2024-11-23 03:30:44.208388: Current learning rate: 0.00103 +2024-11-23 03:31:01.545984: train_loss -0.833 +2024-11-23 03:31:01.546210: val_loss -0.7693 +2024-11-23 03:31:01.546293: Pseudo dice [0.853] +2024-11-23 03:31:01.546381: Epoch time: 17.34 s +2024-11-23 03:31:02.545800: +2024-11-23 03:31:02.546023: Epoch 7358 +2024-11-23 03:31:02.546144: Current learning rate: 0.00103 +2024-11-23 03:31:22.434560: train_loss -0.8232 +2024-11-23 03:31:22.434765: val_loss -0.7511 +2024-11-23 03:31:22.434848: Pseudo dice [0.8506] +2024-11-23 03:31:22.434942: Epoch time: 19.89 s +2024-11-23 03:31:23.336266: +2024-11-23 03:31:23.336505: Epoch 7359 +2024-11-23 03:31:23.336623: Current learning rate: 0.00103 +2024-11-23 03:31:41.453116: train_loss -0.8302 +2024-11-23 03:31:41.453390: val_loss -0.7792 +2024-11-23 03:31:41.453490: Pseudo dice [0.8525] +2024-11-23 03:31:41.453591: Epoch time: 18.1 s +2024-11-23 03:31:42.355416: +2024-11-23 03:31:42.355638: Epoch 7360 +2024-11-23 03:31:42.355748: Current learning rate: 0.00103 +2024-11-23 03:32:00.568567: train_loss -0.8183 +2024-11-23 03:32:00.568772: val_loss -0.7883 +2024-11-23 03:32:00.568853: Pseudo dice [0.8583] +2024-11-23 03:32:00.568929: Epoch time: 18.21 s +2024-11-23 03:32:01.460207: +2024-11-23 03:32:01.460425: Epoch 7361 +2024-11-23 03:32:01.460537: Current learning rate: 0.00103 +2024-11-23 03:32:20.423945: train_loss -0.8195 +2024-11-23 03:32:20.424163: val_loss -0.8173 +2024-11-23 03:32:20.424240: Pseudo dice [0.8733] +2024-11-23 03:32:20.424328: Epoch time: 18.96 s +2024-11-23 03:32:21.317629: +2024-11-23 03:32:21.317833: Epoch 7362 +2024-11-23 03:32:21.317943: Current learning rate: 0.00103 +2024-11-23 03:32:39.986890: train_loss -0.824 +2024-11-23 03:32:39.987118: val_loss -0.7758 +2024-11-23 03:32:39.987197: Pseudo dice [0.8539] +2024-11-23 03:32:39.992424: Epoch time: 18.67 s +2024-11-23 03:32:41.023889: +2024-11-23 03:32:41.024099: Epoch 7363 +2024-11-23 03:32:41.024215: Current learning rate: 0.00103 +2024-11-23 03:32:59.084248: train_loss -0.832 +2024-11-23 03:32:59.084485: val_loss -0.7697 +2024-11-23 03:32:59.084586: Pseudo dice [0.8618] +2024-11-23 03:32:59.084683: Epoch time: 18.06 s +2024-11-23 03:32:59.988593: +2024-11-23 03:32:59.988837: Epoch 7364 +2024-11-23 03:32:59.988966: Current learning rate: 0.00102 +2024-11-23 03:33:18.425079: train_loss -0.8273 +2024-11-23 03:33:18.425290: val_loss -0.7841 +2024-11-23 03:33:18.425369: Pseudo dice [0.8563] +2024-11-23 03:33:18.425651: Epoch time: 18.44 s +2024-11-23 03:33:19.313300: +2024-11-23 03:33:19.313504: Epoch 7365 +2024-11-23 03:33:19.313618: Current learning rate: 0.00102 +2024-11-23 03:33:36.342750: train_loss -0.8269 +2024-11-23 03:33:36.343003: val_loss -0.7783 +2024-11-23 03:33:36.343093: Pseudo dice [0.8643] +2024-11-23 03:33:36.343172: Epoch time: 17.03 s +2024-11-23 03:33:37.235828: +2024-11-23 03:33:37.236024: Epoch 7366 +2024-11-23 03:33:37.236140: Current learning rate: 0.00102 +2024-11-23 03:33:55.694050: train_loss -0.8269 +2024-11-23 03:33:55.694570: val_loss -0.7779 +2024-11-23 03:33:55.694740: Pseudo dice [0.8574] +2024-11-23 03:33:55.694841: Epoch time: 18.46 s +2024-11-23 03:33:56.590347: +2024-11-23 03:33:56.590547: Epoch 7367 +2024-11-23 03:33:56.590677: Current learning rate: 0.00102 +2024-11-23 03:34:15.294662: train_loss -0.8292 +2024-11-23 03:34:15.294924: val_loss -0.7906 +2024-11-23 03:34:15.295007: Pseudo dice [0.8531] +2024-11-23 03:34:15.295108: Epoch time: 18.71 s +2024-11-23 03:34:16.178505: +2024-11-23 03:34:16.178722: Epoch 7368 +2024-11-23 03:34:16.178837: Current learning rate: 0.00102 +2024-11-23 03:34:34.967266: train_loss -0.822 +2024-11-23 03:34:34.967492: val_loss -0.7637 +2024-11-23 03:34:34.967579: Pseudo dice [0.8507] +2024-11-23 03:34:34.967660: Epoch time: 18.79 s +2024-11-23 03:34:35.854713: +2024-11-23 03:34:35.854929: Epoch 7369 +2024-11-23 03:34:35.855043: Current learning rate: 0.00102 +2024-11-23 03:34:54.535874: train_loss -0.8224 +2024-11-23 03:34:54.536092: val_loss -0.7885 +2024-11-23 03:34:54.536169: Pseudo dice [0.853] +2024-11-23 03:34:54.536247: Epoch time: 18.68 s +2024-11-23 03:34:55.431938: +2024-11-23 03:34:55.432185: Epoch 7370 +2024-11-23 03:34:55.432315: Current learning rate: 0.00102 +2024-11-23 03:35:14.343534: train_loss -0.8229 +2024-11-23 03:35:14.343777: val_loss -0.7887 +2024-11-23 03:35:14.343870: Pseudo dice [0.8645] +2024-11-23 03:35:14.344023: Epoch time: 18.91 s +2024-11-23 03:35:15.241808: +2024-11-23 03:35:15.242010: Epoch 7371 +2024-11-23 03:35:15.242127: Current learning rate: 0.00101 +2024-11-23 03:35:33.714900: train_loss -0.8275 +2024-11-23 03:35:33.715138: val_loss -0.8014 +2024-11-23 03:35:33.715218: Pseudo dice [0.8573] +2024-11-23 03:35:33.715294: Epoch time: 18.47 s +2024-11-23 03:35:34.601766: +2024-11-23 03:35:34.601996: Epoch 7372 +2024-11-23 03:35:34.602125: Current learning rate: 0.00101 +2024-11-23 03:35:53.534032: train_loss -0.8294 +2024-11-23 03:35:53.534261: val_loss -0.7959 +2024-11-23 03:35:53.534353: Pseudo dice [0.8565] +2024-11-23 03:35:53.534437: Epoch time: 18.93 s +2024-11-23 03:35:54.434342: +2024-11-23 03:35:54.434582: Epoch 7373 +2024-11-23 03:35:54.434698: Current learning rate: 0.00101 +2024-11-23 03:36:12.843390: train_loss -0.8293 +2024-11-23 03:36:12.843597: val_loss -0.7923 +2024-11-23 03:36:12.843676: Pseudo dice [0.849] +2024-11-23 03:36:12.843759: Epoch time: 18.41 s +2024-11-23 03:36:13.734706: +2024-11-23 03:36:13.734978: Epoch 7374 +2024-11-23 03:36:13.735114: Current learning rate: 0.00101 +2024-11-23 03:36:32.108169: train_loss -0.8283 +2024-11-23 03:36:32.108379: val_loss -0.774 +2024-11-23 03:36:32.108567: Pseudo dice [0.8591] +2024-11-23 03:36:32.108649: Epoch time: 18.37 s +2024-11-23 03:36:33.002515: +2024-11-23 03:36:33.002762: Epoch 7375 +2024-11-23 03:36:33.002886: Current learning rate: 0.00101 +2024-11-23 03:36:50.701218: train_loss -0.8297 +2024-11-23 03:36:50.701432: val_loss -0.7948 +2024-11-23 03:36:50.701507: Pseudo dice [0.8587] +2024-11-23 03:36:50.701597: Epoch time: 17.7 s +2024-11-23 03:36:51.590303: +2024-11-23 03:36:51.590531: Epoch 7376 +2024-11-23 03:36:51.590661: Current learning rate: 0.00101 +2024-11-23 03:37:09.801039: train_loss -0.8185 +2024-11-23 03:37:09.801273: val_loss -0.7733 +2024-11-23 03:37:09.801350: Pseudo dice [0.8631] +2024-11-23 03:37:09.801430: Epoch time: 18.21 s +2024-11-23 03:37:11.070199: +2024-11-23 03:37:11.070413: Epoch 7377 +2024-11-23 03:37:11.070536: Current learning rate: 0.00101 +2024-11-23 03:37:29.752816: train_loss -0.8235 +2024-11-23 03:37:29.753079: val_loss -0.779 +2024-11-23 03:37:29.753159: Pseudo dice [0.8745] +2024-11-23 03:37:29.753245: Epoch time: 18.68 s +2024-11-23 03:37:30.649574: +2024-11-23 03:37:30.649788: Epoch 7378 +2024-11-23 03:37:30.649911: Current learning rate: 0.001 +2024-11-23 03:37:48.785016: train_loss -0.8244 +2024-11-23 03:37:48.785235: val_loss -0.7827 +2024-11-23 03:37:48.785311: Pseudo dice [0.868] +2024-11-23 03:37:48.785402: Epoch time: 18.14 s +2024-11-23 03:37:49.670015: +2024-11-23 03:37:49.670245: Epoch 7379 +2024-11-23 03:37:49.670365: Current learning rate: 0.001 +2024-11-23 03:38:07.164212: train_loss -0.8355 +2024-11-23 03:38:07.164428: val_loss -0.7836 +2024-11-23 03:38:07.164508: Pseudo dice [0.8595] +2024-11-23 03:38:07.164608: Epoch time: 17.49 s +2024-11-23 03:38:08.055947: +2024-11-23 03:38:08.056162: Epoch 7380 +2024-11-23 03:38:08.056275: Current learning rate: 0.001 +2024-11-23 03:38:27.204812: train_loss -0.8225 +2024-11-23 03:38:27.205038: val_loss -0.778 +2024-11-23 03:38:27.207304: Pseudo dice [0.8538] +2024-11-23 03:38:27.207391: Epoch time: 19.15 s +2024-11-23 03:38:28.176783: +2024-11-23 03:38:28.177001: Epoch 7381 +2024-11-23 03:38:28.177136: Current learning rate: 0.001 +2024-11-23 03:38:47.585999: train_loss -0.8244 +2024-11-23 03:38:47.586258: val_loss -0.7903 +2024-11-23 03:38:47.586360: Pseudo dice [0.8644] +2024-11-23 03:38:47.586464: Epoch time: 19.41 s +2024-11-23 03:38:48.482671: +2024-11-23 03:38:48.482892: Epoch 7382 +2024-11-23 03:38:48.483008: Current learning rate: 0.001 +2024-11-23 03:39:06.929641: train_loss -0.8221 +2024-11-23 03:39:06.929853: val_loss -0.7694 +2024-11-23 03:39:06.929927: Pseudo dice [0.8597] +2024-11-23 03:39:06.930006: Epoch time: 18.45 s +2024-11-23 03:39:07.817756: +2024-11-23 03:39:07.817957: Epoch 7383 +2024-11-23 03:39:07.818077: Current learning rate: 0.001 +2024-11-23 03:39:25.757469: train_loss -0.821 +2024-11-23 03:39:25.757689: val_loss -0.7862 +2024-11-23 03:39:25.757765: Pseudo dice [0.8666] +2024-11-23 03:39:25.757839: Epoch time: 17.94 s +2024-11-23 03:39:26.717666: +2024-11-23 03:39:26.717885: Epoch 7384 +2024-11-23 03:39:26.718002: Current learning rate: 0.001 +2024-11-23 03:39:44.685402: train_loss -0.8258 +2024-11-23 03:39:44.685683: val_loss -0.7751 +2024-11-23 03:39:44.685766: Pseudo dice [0.8633] +2024-11-23 03:39:44.685855: Epoch time: 17.97 s +2024-11-23 03:39:45.697384: +2024-11-23 03:39:45.697619: Epoch 7385 +2024-11-23 03:39:45.697747: Current learning rate: 0.00099 +2024-11-23 03:40:04.976611: train_loss -0.8243 +2024-11-23 03:40:04.976865: val_loss -0.7911 +2024-11-23 03:40:04.976957: Pseudo dice [0.8478] +2024-11-23 03:40:04.977049: Epoch time: 19.28 s +2024-11-23 03:40:05.865840: +2024-11-23 03:40:05.866048: Epoch 7386 +2024-11-23 03:40:05.866166: Current learning rate: 0.00099 +2024-11-23 03:40:24.756989: train_loss -0.8329 +2024-11-23 03:40:24.757227: val_loss -0.7804 +2024-11-23 03:40:24.757317: Pseudo dice [0.8587] +2024-11-23 03:40:24.757396: Epoch time: 18.89 s +2024-11-23 03:40:25.654083: +2024-11-23 03:40:25.654309: Epoch 7387 +2024-11-23 03:40:25.654425: Current learning rate: 0.00099 +2024-11-23 03:40:43.767165: train_loss -0.8239 +2024-11-23 03:40:43.767376: val_loss -0.7947 +2024-11-23 03:40:43.767458: Pseudo dice [0.8581] +2024-11-23 03:40:43.767540: Epoch time: 18.11 s +2024-11-23 03:40:44.693686: +2024-11-23 03:40:44.693890: Epoch 7388 +2024-11-23 03:40:44.694001: Current learning rate: 0.00099 +2024-11-23 03:41:03.225698: train_loss -0.8286 +2024-11-23 03:41:03.225915: val_loss -0.7927 +2024-11-23 03:41:03.225991: Pseudo dice [0.8577] +2024-11-23 03:41:03.226073: Epoch time: 18.53 s +2024-11-23 03:41:04.118603: +2024-11-23 03:41:04.118819: Epoch 7389 +2024-11-23 03:41:04.118930: Current learning rate: 0.00099 +2024-11-23 03:41:22.794236: train_loss -0.8265 +2024-11-23 03:41:22.794487: val_loss -0.7952 +2024-11-23 03:41:22.794593: Pseudo dice [0.8649] +2024-11-23 03:41:22.794673: Epoch time: 18.68 s +2024-11-23 03:41:23.702806: +2024-11-23 03:41:23.703055: Epoch 7390 +2024-11-23 03:41:23.703185: Current learning rate: 0.00099 +2024-11-23 03:41:42.361827: train_loss -0.8337 +2024-11-23 03:41:42.362041: val_loss -0.7757 +2024-11-23 03:41:42.362266: Pseudo dice [0.8602] +2024-11-23 03:41:42.362356: Epoch time: 18.66 s +2024-11-23 03:41:43.362230: +2024-11-23 03:41:43.362449: Epoch 7391 +2024-11-23 03:41:43.362566: Current learning rate: 0.00098 +2024-11-23 03:42:02.419026: train_loss -0.8216 +2024-11-23 03:42:02.419247: val_loss -0.7891 +2024-11-23 03:42:02.419339: Pseudo dice [0.8675] +2024-11-23 03:42:02.419437: Epoch time: 19.06 s +2024-11-23 03:42:03.311926: +2024-11-23 03:42:03.312140: Epoch 7392 +2024-11-23 03:42:03.312269: Current learning rate: 0.00098 +2024-11-23 03:42:21.082715: train_loss -0.8272 +2024-11-23 03:42:21.082966: val_loss -0.7618 +2024-11-23 03:42:21.083075: Pseudo dice [0.8647] +2024-11-23 03:42:21.083159: Epoch time: 17.77 s +2024-11-23 03:42:21.975842: +2024-11-23 03:42:21.976061: Epoch 7393 +2024-11-23 03:42:21.976182: Current learning rate: 0.00098 +2024-11-23 03:42:39.592902: train_loss -0.8302 +2024-11-23 03:42:39.593120: val_loss -0.7826 +2024-11-23 03:42:39.593202: Pseudo dice [0.8541] +2024-11-23 03:42:39.593295: Epoch time: 17.62 s +2024-11-23 03:42:40.580174: +2024-11-23 03:42:40.580396: Epoch 7394 +2024-11-23 03:42:40.580517: Current learning rate: 0.00098 +2024-11-23 03:42:59.803739: train_loss -0.8268 +2024-11-23 03:42:59.806155: val_loss -0.7961 +2024-11-23 03:42:59.806292: Pseudo dice [0.8454] +2024-11-23 03:42:59.806381: Epoch time: 19.22 s +2024-11-23 03:43:00.722596: +2024-11-23 03:43:00.722820: Epoch 7395 +2024-11-23 03:43:00.722953: Current learning rate: 0.00098 +2024-11-23 03:43:18.765852: train_loss -0.8332 +2024-11-23 03:43:18.768291: val_loss -0.7902 +2024-11-23 03:43:18.768378: Pseudo dice [0.8556] +2024-11-23 03:43:18.768467: Epoch time: 18.04 s +2024-11-23 03:43:19.798530: +2024-11-23 03:43:19.798746: Epoch 7396 +2024-11-23 03:43:19.798870: Current learning rate: 0.00098 +2024-11-23 03:43:39.413458: train_loss -0.83 +2024-11-23 03:43:39.418895: val_loss -0.7984 +2024-11-23 03:43:39.419011: Pseudo dice [0.859] +2024-11-23 03:43:39.419103: Epoch time: 19.62 s +2024-11-23 03:43:40.315577: +2024-11-23 03:43:40.315774: Epoch 7397 +2024-11-23 03:43:40.315904: Current learning rate: 0.00098 +2024-11-23 03:43:59.027525: train_loss -0.8244 +2024-11-23 03:43:59.027751: val_loss -0.773 +2024-11-23 03:43:59.027832: Pseudo dice [0.8539] +2024-11-23 03:43:59.027907: Epoch time: 18.71 s +2024-11-23 03:43:59.940068: +2024-11-23 03:43:59.940289: Epoch 7398 +2024-11-23 03:43:59.940405: Current learning rate: 0.00097 +2024-11-23 03:44:18.186030: train_loss -0.8297 +2024-11-23 03:44:18.186288: val_loss -0.7579 +2024-11-23 03:44:18.186384: Pseudo dice [0.8599] +2024-11-23 03:44:18.186476: Epoch time: 18.25 s +2024-11-23 03:44:19.472052: +2024-11-23 03:44:19.472505: Epoch 7399 +2024-11-23 03:44:19.472663: Current learning rate: 0.00097 +2024-11-23 03:44:37.732536: train_loss -0.827 +2024-11-23 03:44:37.732788: val_loss -0.784 +2024-11-23 03:44:37.732877: Pseudo dice [0.8524] +2024-11-23 03:44:37.732998: Epoch time: 18.26 s +2024-11-23 03:44:38.983211: +2024-11-23 03:44:38.983618: Epoch 7400 +2024-11-23 03:44:38.983763: Current learning rate: 0.00097 +2024-11-23 03:44:56.750516: train_loss -0.8307 +2024-11-23 03:44:56.750728: val_loss -0.7931 +2024-11-23 03:44:56.750805: Pseudo dice [0.8634] +2024-11-23 03:44:56.750883: Epoch time: 17.77 s +2024-11-23 03:44:57.682968: +2024-11-23 03:44:57.683466: Epoch 7401 +2024-11-23 03:44:57.683607: Current learning rate: 0.00097 +2024-11-23 03:45:15.460094: train_loss -0.8293 +2024-11-23 03:45:15.460317: val_loss -0.7956 +2024-11-23 03:45:15.460397: Pseudo dice [0.8508] +2024-11-23 03:45:15.460470: Epoch time: 17.78 s +2024-11-23 03:45:16.348011: +2024-11-23 03:45:16.348467: Epoch 7402 +2024-11-23 03:45:16.348607: Current learning rate: 0.00097 +2024-11-23 03:45:34.072542: train_loss -0.8234 +2024-11-23 03:45:34.072790: val_loss -0.8057 +2024-11-23 03:45:34.072896: Pseudo dice [0.8742] +2024-11-23 03:45:34.072989: Epoch time: 17.73 s +2024-11-23 03:45:34.964314: +2024-11-23 03:45:34.964757: Epoch 7403 +2024-11-23 03:45:34.964892: Current learning rate: 0.00097 +2024-11-23 03:45:52.686334: train_loss -0.8241 +2024-11-23 03:45:52.686611: val_loss -0.7634 +2024-11-23 03:45:52.686688: Pseudo dice [0.8421] +2024-11-23 03:45:52.686769: Epoch time: 17.72 s +2024-11-23 03:45:53.582648: +2024-11-23 03:45:53.583074: Epoch 7404 +2024-11-23 03:45:53.583225: Current learning rate: 0.00097 +2024-11-23 03:46:11.155194: train_loss -0.8168 +2024-11-23 03:46:11.155406: val_loss -0.7703 +2024-11-23 03:46:11.155495: Pseudo dice [0.8654] +2024-11-23 03:46:11.155583: Epoch time: 17.57 s +2024-11-23 03:46:12.045628: +2024-11-23 03:46:12.046020: Epoch 7405 +2024-11-23 03:46:12.046152: Current learning rate: 0.00096 +2024-11-23 03:46:29.860807: train_loss -0.8261 +2024-11-23 03:46:29.861026: val_loss -0.7902 +2024-11-23 03:46:29.861109: Pseudo dice [0.8583] +2024-11-23 03:46:29.861197: Epoch time: 17.82 s +2024-11-23 03:46:30.756638: +2024-11-23 03:46:30.757086: Epoch 7406 +2024-11-23 03:46:30.757225: Current learning rate: 0.00096 +2024-11-23 03:46:48.740955: train_loss -0.812 +2024-11-23 03:46:48.741180: val_loss -0.7948 +2024-11-23 03:46:48.741258: Pseudo dice [0.8605] +2024-11-23 03:46:48.741342: Epoch time: 17.99 s +2024-11-23 03:46:49.641824: +2024-11-23 03:46:49.642301: Epoch 7407 +2024-11-23 03:46:49.642442: Current learning rate: 0.00096 +2024-11-23 03:47:09.144377: train_loss -0.8164 +2024-11-23 03:47:09.144624: val_loss -0.7773 +2024-11-23 03:47:09.144750: Pseudo dice [0.8339] +2024-11-23 03:47:09.144847: Epoch time: 19.5 s +2024-11-23 03:47:10.029459: +2024-11-23 03:47:10.029882: Epoch 7408 +2024-11-23 03:47:10.030013: Current learning rate: 0.00096 +2024-11-23 03:47:28.278384: train_loss -0.8273 +2024-11-23 03:47:28.278589: val_loss -0.7814 +2024-11-23 03:47:28.278677: Pseudo dice [0.849] +2024-11-23 03:47:28.278754: Epoch time: 18.25 s +2024-11-23 03:47:29.196477: +2024-11-23 03:47:29.196666: Epoch 7409 +2024-11-23 03:47:29.196781: Current learning rate: 0.00096 +2024-11-23 03:47:46.729395: train_loss -0.8287 +2024-11-23 03:47:46.729628: val_loss -0.8031 +2024-11-23 03:47:46.729710: Pseudo dice [0.8703] +2024-11-23 03:47:46.729786: Epoch time: 17.53 s +2024-11-23 03:47:48.178450: +2024-11-23 03:47:48.178661: Epoch 7410 +2024-11-23 03:47:48.178779: Current learning rate: 0.00096 +2024-11-23 03:48:05.678237: train_loss -0.8226 +2024-11-23 03:48:05.678492: val_loss -0.7756 +2024-11-23 03:48:05.678582: Pseudo dice [0.8643] +2024-11-23 03:48:05.678668: Epoch time: 17.5 s +2024-11-23 03:48:06.581695: +2024-11-23 03:48:06.581954: Epoch 7411 +2024-11-23 03:48:06.582093: Current learning rate: 0.00096 +2024-11-23 03:48:25.274796: train_loss -0.8266 +2024-11-23 03:48:25.275028: val_loss -0.7843 +2024-11-23 03:48:25.275130: Pseudo dice [0.8452] +2024-11-23 03:48:25.275226: Epoch time: 18.69 s +2024-11-23 03:48:26.167579: +2024-11-23 03:48:26.167798: Epoch 7412 +2024-11-23 03:48:26.167927: Current learning rate: 0.00095 +2024-11-23 03:48:43.605031: train_loss -0.8302 +2024-11-23 03:48:43.605251: val_loss -0.7717 +2024-11-23 03:48:43.605338: Pseudo dice [0.8525] +2024-11-23 03:48:43.605418: Epoch time: 17.44 s +2024-11-23 03:48:44.765107: +2024-11-23 03:48:44.765340: Epoch 7413 +2024-11-23 03:48:44.765462: Current learning rate: 0.00095 +2024-11-23 03:49:04.536822: train_loss -0.8268 +2024-11-23 03:49:04.542180: val_loss -0.7841 +2024-11-23 03:49:04.542335: Pseudo dice [0.8614] +2024-11-23 03:49:04.542422: Epoch time: 19.77 s +2024-11-23 03:49:05.461004: +2024-11-23 03:49:05.461220: Epoch 7414 +2024-11-23 03:49:05.461343: Current learning rate: 0.00095 +2024-11-23 03:49:23.719380: train_loss -0.8287 +2024-11-23 03:49:23.719612: val_loss -0.7895 +2024-11-23 03:49:23.719687: Pseudo dice [0.8643] +2024-11-23 03:49:23.719767: Epoch time: 18.26 s +2024-11-23 03:49:24.610086: +2024-11-23 03:49:24.610302: Epoch 7415 +2024-11-23 03:49:24.610431: Current learning rate: 0.00095 +2024-11-23 03:49:43.641626: train_loss -0.8307 +2024-11-23 03:49:43.641843: val_loss -0.7876 +2024-11-23 03:49:43.641924: Pseudo dice [0.8605] +2024-11-23 03:49:43.642005: Epoch time: 19.03 s +2024-11-23 03:49:44.536743: +2024-11-23 03:49:44.536957: Epoch 7416 +2024-11-23 03:49:44.537091: Current learning rate: 0.00095 +2024-11-23 03:50:03.560642: train_loss -0.8286 +2024-11-23 03:50:03.560860: val_loss -0.7684 +2024-11-23 03:50:03.561151: Pseudo dice [0.8658] +2024-11-23 03:50:03.561241: Epoch time: 19.02 s +2024-11-23 03:50:04.455325: +2024-11-23 03:50:04.455561: Epoch 7417 +2024-11-23 03:50:04.455675: Current learning rate: 0.00095 +2024-11-23 03:50:22.883692: train_loss -0.827 +2024-11-23 03:50:22.883918: val_loss -0.7892 +2024-11-23 03:50:22.884000: Pseudo dice [0.8587] +2024-11-23 03:50:22.884086: Epoch time: 18.43 s +2024-11-23 03:50:23.802730: +2024-11-23 03:50:23.802952: Epoch 7418 +2024-11-23 03:50:23.803075: Current learning rate: 0.00095 +2024-11-23 03:50:42.673765: train_loss -0.8261 +2024-11-23 03:50:42.674067: val_loss -0.7657 +2024-11-23 03:50:42.674149: Pseudo dice [0.8563] +2024-11-23 03:50:42.674234: Epoch time: 18.87 s +2024-11-23 03:50:43.568729: +2024-11-23 03:50:43.568943: Epoch 7419 +2024-11-23 03:50:43.569072: Current learning rate: 0.00094 +2024-11-23 03:51:01.723787: train_loss -0.8221 +2024-11-23 03:51:01.723994: val_loss -0.792 +2024-11-23 03:51:01.724081: Pseudo dice [0.8603] +2024-11-23 03:51:01.724165: Epoch time: 18.16 s +2024-11-23 03:51:02.645541: +2024-11-23 03:51:02.645768: Epoch 7420 +2024-11-23 03:51:02.645886: Current learning rate: 0.00094 +2024-11-23 03:51:20.232983: train_loss -0.8274 +2024-11-23 03:51:20.233214: val_loss -0.7837 +2024-11-23 03:51:20.233303: Pseudo dice [0.864] +2024-11-23 03:51:20.233381: Epoch time: 17.59 s +2024-11-23 03:51:21.121851: +2024-11-23 03:51:21.122047: Epoch 7421 +2024-11-23 03:51:21.122175: Current learning rate: 0.00094 +2024-11-23 03:51:39.733204: train_loss -0.8292 +2024-11-23 03:51:39.733452: val_loss -0.8007 +2024-11-23 03:51:39.733540: Pseudo dice [0.8537] +2024-11-23 03:51:39.733627: Epoch time: 18.61 s +2024-11-23 03:51:40.621336: +2024-11-23 03:51:40.621552: Epoch 7422 +2024-11-23 03:51:40.621678: Current learning rate: 0.00094 +2024-11-23 03:51:59.166933: train_loss -0.8234 +2024-11-23 03:51:59.169353: val_loss -0.7898 +2024-11-23 03:51:59.169444: Pseudo dice [0.8529] +2024-11-23 03:51:59.169530: Epoch time: 18.55 s +2024-11-23 03:52:00.065119: +2024-11-23 03:52:00.065335: Epoch 7423 +2024-11-23 03:52:00.065448: Current learning rate: 0.00094 +2024-11-23 03:52:18.997523: train_loss -0.8268 +2024-11-23 03:52:18.997733: val_loss -0.754 +2024-11-23 03:52:18.997815: Pseudo dice [0.852] +2024-11-23 03:52:18.997906: Epoch time: 18.93 s +2024-11-23 03:52:19.892200: +2024-11-23 03:52:19.892428: Epoch 7424 +2024-11-23 03:52:19.892556: Current learning rate: 0.00094 +2024-11-23 03:52:38.817046: train_loss -0.8245 +2024-11-23 03:52:38.817271: val_loss -0.7516 +2024-11-23 03:52:38.817352: Pseudo dice [0.8605] +2024-11-23 03:52:38.817437: Epoch time: 18.93 s +2024-11-23 03:52:39.711189: +2024-11-23 03:52:39.711394: Epoch 7425 +2024-11-23 03:52:39.711518: Current learning rate: 0.00094 +2024-11-23 03:52:57.389338: train_loss -0.8285 +2024-11-23 03:52:57.389575: val_loss -0.7708 +2024-11-23 03:52:57.389668: Pseudo dice [0.853] +2024-11-23 03:52:57.389750: Epoch time: 17.68 s +2024-11-23 03:52:58.434175: +2024-11-23 03:52:58.434374: Epoch 7426 +2024-11-23 03:52:58.434484: Current learning rate: 0.00093 +2024-11-23 03:53:16.258493: train_loss -0.825 +2024-11-23 03:53:16.258704: val_loss -0.7871 +2024-11-23 03:53:16.258779: Pseudo dice [0.8663] +2024-11-23 03:53:16.258890: Epoch time: 17.83 s +2024-11-23 03:53:17.149464: +2024-11-23 03:53:17.149671: Epoch 7427 +2024-11-23 03:53:17.149793: Current learning rate: 0.00093 +2024-11-23 03:53:37.112658: train_loss -0.8332 +2024-11-23 03:53:37.112897: val_loss -0.7677 +2024-11-23 03:53:37.112987: Pseudo dice [0.8605] +2024-11-23 03:53:37.113074: Epoch time: 19.96 s +2024-11-23 03:53:38.059975: +2024-11-23 03:53:38.060188: Epoch 7428 +2024-11-23 03:53:38.060314: Current learning rate: 0.00093 +2024-11-23 03:53:56.526523: train_loss -0.823 +2024-11-23 03:53:56.526784: val_loss -0.787 +2024-11-23 03:53:56.526879: Pseudo dice [0.8466] +2024-11-23 03:53:56.526968: Epoch time: 18.47 s +2024-11-23 03:53:57.423429: +2024-11-23 03:53:57.423639: Epoch 7429 +2024-11-23 03:53:57.423753: Current learning rate: 0.00093 +2024-11-23 03:54:16.224216: train_loss -0.8266 +2024-11-23 03:54:16.224434: val_loss -0.7972 +2024-11-23 03:54:16.224534: Pseudo dice [0.8632] +2024-11-23 03:54:16.224607: Epoch time: 18.8 s +2024-11-23 03:54:17.111821: +2024-11-23 03:54:17.112040: Epoch 7430 +2024-11-23 03:54:17.112176: Current learning rate: 0.00093 +2024-11-23 03:54:35.442958: train_loss -0.8321 +2024-11-23 03:54:35.443179: val_loss -0.7859 +2024-11-23 03:54:35.443276: Pseudo dice [0.8581] +2024-11-23 03:54:35.443355: Epoch time: 18.33 s +2024-11-23 03:54:36.334831: +2024-11-23 03:54:36.335037: Epoch 7431 +2024-11-23 03:54:36.335153: Current learning rate: 0.00093 +2024-11-23 03:54:55.079001: train_loss -0.8278 +2024-11-23 03:54:55.079226: val_loss -0.7758 +2024-11-23 03:54:55.079304: Pseudo dice [0.8589] +2024-11-23 03:54:55.079388: Epoch time: 18.74 s +2024-11-23 03:54:56.376991: +2024-11-23 03:54:56.377413: Epoch 7432 +2024-11-23 03:54:56.377546: Current learning rate: 0.00092 +2024-11-23 03:55:14.506047: train_loss -0.8282 +2024-11-23 03:55:14.506294: val_loss -0.7822 +2024-11-23 03:55:14.506372: Pseudo dice [0.8672] +2024-11-23 03:55:14.506471: Epoch time: 18.13 s +2024-11-23 03:55:15.395496: +2024-11-23 03:55:15.395913: Epoch 7433 +2024-11-23 03:55:15.396052: Current learning rate: 0.00092 +2024-11-23 03:55:34.556620: train_loss -0.8237 +2024-11-23 03:55:34.556826: val_loss -0.777 +2024-11-23 03:55:34.556901: Pseudo dice [0.845] +2024-11-23 03:55:34.556977: Epoch time: 19.16 s +2024-11-23 03:55:35.452086: +2024-11-23 03:55:35.452506: Epoch 7434 +2024-11-23 03:55:35.452640: Current learning rate: 0.00092 +2024-11-23 03:55:54.747004: train_loss -0.8319 +2024-11-23 03:55:54.747242: val_loss -0.7467 +2024-11-23 03:55:54.747319: Pseudo dice [0.857] +2024-11-23 03:55:54.747398: Epoch time: 19.3 s +2024-11-23 03:55:55.636852: +2024-11-23 03:55:55.637283: Epoch 7435 +2024-11-23 03:55:55.637438: Current learning rate: 0.00092 +2024-11-23 03:56:14.118884: train_loss -0.8318 +2024-11-23 03:56:14.119107: val_loss -0.8076 +2024-11-23 03:56:14.119189: Pseudo dice [0.8674] +2024-11-23 03:56:14.119276: Epoch time: 18.48 s +2024-11-23 03:56:15.038890: +2024-11-23 03:56:15.039321: Epoch 7436 +2024-11-23 03:56:15.039458: Current learning rate: 0.00092 +2024-11-23 03:56:34.224854: train_loss -0.8292 +2024-11-23 03:56:34.225108: val_loss -0.7813 +2024-11-23 03:56:34.225186: Pseudo dice [0.8504] +2024-11-23 03:56:34.225269: Epoch time: 19.19 s +2024-11-23 03:56:35.347566: +2024-11-23 03:56:35.347988: Epoch 7437 +2024-11-23 03:56:35.348129: Current learning rate: 0.00092 +2024-11-23 03:56:54.220416: train_loss -0.8272 +2024-11-23 03:56:54.220634: val_loss -0.7843 +2024-11-23 03:56:54.220776: Pseudo dice [0.8657] +2024-11-23 03:56:54.220871: Epoch time: 18.87 s +2024-11-23 03:56:55.114224: +2024-11-23 03:56:55.114669: Epoch 7438 +2024-11-23 03:56:55.114813: Current learning rate: 0.00092 +2024-11-23 03:57:13.955681: train_loss -0.8359 +2024-11-23 03:57:13.955896: val_loss -0.8051 +2024-11-23 03:57:13.955986: Pseudo dice [0.8707] +2024-11-23 03:57:13.956081: Epoch time: 18.84 s +2024-11-23 03:57:14.908552: +2024-11-23 03:57:14.908959: Epoch 7439 +2024-11-23 03:57:14.909096: Current learning rate: 0.00091 +2024-11-23 03:57:33.859612: train_loss -0.8274 +2024-11-23 03:57:33.859827: val_loss -0.7633 +2024-11-23 03:57:33.859906: Pseudo dice [0.8491] +2024-11-23 03:57:33.860006: Epoch time: 18.95 s +2024-11-23 03:57:34.751633: +2024-11-23 03:57:34.752085: Epoch 7440 +2024-11-23 03:57:34.752237: Current learning rate: 0.00091 +2024-11-23 03:57:53.480479: train_loss -0.8278 +2024-11-23 03:57:53.480734: val_loss -0.788 +2024-11-23 03:57:53.480833: Pseudo dice [0.8613] +2024-11-23 03:57:53.480922: Epoch time: 18.73 s +2024-11-23 03:57:54.370225: +2024-11-23 03:57:54.370638: Epoch 7441 +2024-11-23 03:57:54.370774: Current learning rate: 0.00091 +2024-11-23 03:58:12.330893: train_loss -0.8315 +2024-11-23 03:58:12.331109: val_loss -0.774 +2024-11-23 03:58:12.331189: Pseudo dice [0.8728] +2024-11-23 03:58:12.331263: Epoch time: 17.96 s +2024-11-23 03:58:13.222903: +2024-11-23 03:58:13.223347: Epoch 7442 +2024-11-23 03:58:13.223492: Current learning rate: 0.00091 +2024-11-23 03:58:30.880482: train_loss -0.8301 +2024-11-23 03:58:30.880693: val_loss -0.7833 +2024-11-23 03:58:30.880921: Pseudo dice [0.8639] +2024-11-23 03:58:30.881021: Epoch time: 17.66 s +2024-11-23 03:58:31.784097: +2024-11-23 03:58:31.784301: Epoch 7443 +2024-11-23 03:58:31.784425: Current learning rate: 0.00091 +2024-11-23 03:58:49.885155: train_loss -0.8297 +2024-11-23 03:58:49.885383: val_loss -0.7979 +2024-11-23 03:58:49.885463: Pseudo dice [0.857] +2024-11-23 03:58:49.885558: Epoch time: 18.1 s +2024-11-23 03:58:50.782643: +2024-11-23 03:58:50.782846: Epoch 7444 +2024-11-23 03:58:50.782960: Current learning rate: 0.00091 +2024-11-23 03:59:09.392822: train_loss -0.83 +2024-11-23 03:59:09.393072: val_loss -0.773 +2024-11-23 03:59:09.393176: Pseudo dice [0.8554] +2024-11-23 03:59:09.393332: Epoch time: 18.61 s +2024-11-23 03:59:10.286845: +2024-11-23 03:59:10.287106: Epoch 7445 +2024-11-23 03:59:10.287220: Current learning rate: 0.00091 +2024-11-23 03:59:29.085926: train_loss -0.8245 +2024-11-23 03:59:29.086138: val_loss -0.7834 +2024-11-23 03:59:29.086223: Pseudo dice [0.8682] +2024-11-23 03:59:29.086301: Epoch time: 18.8 s +2024-11-23 03:59:29.977603: +2024-11-23 03:59:29.977835: Epoch 7446 +2024-11-23 03:59:29.977969: Current learning rate: 0.0009 +2024-11-23 03:59:47.232784: train_loss -0.8333 +2024-11-23 03:59:47.233000: val_loss -0.7932 +2024-11-23 03:59:47.233096: Pseudo dice [0.8635] +2024-11-23 03:59:47.233175: Epoch time: 17.26 s +2024-11-23 03:59:48.126081: +2024-11-23 03:59:48.126295: Epoch 7447 +2024-11-23 03:59:48.126422: Current learning rate: 0.0009 +2024-11-23 04:00:06.554728: train_loss -0.8257 +2024-11-23 04:00:06.554973: val_loss -0.8043 +2024-11-23 04:00:06.559701: Pseudo dice [0.8609] +2024-11-23 04:00:06.559946: Epoch time: 18.43 s +2024-11-23 04:00:07.663152: +2024-11-23 04:00:07.663365: Epoch 7448 +2024-11-23 04:00:07.663479: Current learning rate: 0.0009 +2024-11-23 04:00:26.526591: train_loss -0.8318 +2024-11-23 04:00:26.526821: val_loss -0.7673 +2024-11-23 04:00:26.526917: Pseudo dice [0.8487] +2024-11-23 04:00:26.526997: Epoch time: 18.86 s +2024-11-23 04:00:27.427667: +2024-11-23 04:00:27.427871: Epoch 7449 +2024-11-23 04:00:27.427983: Current learning rate: 0.0009 +2024-11-23 04:00:46.741432: train_loss -0.8303 +2024-11-23 04:00:46.741666: val_loss -0.7827 +2024-11-23 04:00:46.741758: Pseudo dice [0.8493] +2024-11-23 04:00:46.746978: Epoch time: 19.31 s +2024-11-23 04:00:47.989146: +2024-11-23 04:00:47.989352: Epoch 7450 +2024-11-23 04:00:47.989477: Current learning rate: 0.0009 +2024-11-23 04:01:04.935221: train_loss -0.8271 +2024-11-23 04:01:04.935485: val_loss -0.7575 +2024-11-23 04:01:04.935561: Pseudo dice [0.8463] +2024-11-23 04:01:04.935654: Epoch time: 16.95 s +2024-11-23 04:01:05.831321: +2024-11-23 04:01:05.831529: Epoch 7451 +2024-11-23 04:01:05.831646: Current learning rate: 0.0009 +2024-11-23 04:01:24.486705: train_loss -0.8201 +2024-11-23 04:01:24.486916: val_loss -0.7798 +2024-11-23 04:01:24.486991: Pseudo dice [0.861] +2024-11-23 04:01:24.487082: Epoch time: 18.66 s +2024-11-23 04:01:25.426696: +2024-11-23 04:01:25.426920: Epoch 7452 +2024-11-23 04:01:25.427042: Current learning rate: 0.0009 +2024-11-23 04:01:43.364774: train_loss -0.8284 +2024-11-23 04:01:43.364984: val_loss -0.7821 +2024-11-23 04:01:43.365066: Pseudo dice [0.862] +2024-11-23 04:01:43.365146: Epoch time: 17.94 s +2024-11-23 04:01:44.266168: +2024-11-23 04:01:44.266370: Epoch 7453 +2024-11-23 04:01:44.266481: Current learning rate: 0.00089 +2024-11-23 04:02:02.104476: train_loss -0.8154 +2024-11-23 04:02:02.104686: val_loss -0.7896 +2024-11-23 04:02:02.104765: Pseudo dice [0.8494] +2024-11-23 04:02:02.104849: Epoch time: 17.84 s +2024-11-23 04:02:03.314289: +2024-11-23 04:02:03.314495: Epoch 7454 +2024-11-23 04:02:03.314610: Current learning rate: 0.00089 +2024-11-23 04:02:22.192641: train_loss -0.8344 +2024-11-23 04:02:22.192877: val_loss -0.7938 +2024-11-23 04:02:22.192964: Pseudo dice [0.8629] +2024-11-23 04:02:22.193067: Epoch time: 18.88 s +2024-11-23 04:02:23.073344: +2024-11-23 04:02:23.073569: Epoch 7455 +2024-11-23 04:02:23.073687: Current learning rate: 0.00089 +2024-11-23 04:02:42.365277: train_loss -0.8235 +2024-11-23 04:02:42.365498: val_loss -0.8017 +2024-11-23 04:02:42.365579: Pseudo dice [0.8691] +2024-11-23 04:02:42.365661: Epoch time: 19.29 s +2024-11-23 04:02:43.261524: +2024-11-23 04:02:43.261744: Epoch 7456 +2024-11-23 04:02:43.261870: Current learning rate: 0.00089 +2024-11-23 04:03:01.375371: train_loss -0.8273 +2024-11-23 04:03:01.375581: val_loss -0.7735 +2024-11-23 04:03:01.375663: Pseudo dice [0.8642] +2024-11-23 04:03:01.375755: Epoch time: 18.11 s +2024-11-23 04:03:02.268303: +2024-11-23 04:03:02.268529: Epoch 7457 +2024-11-23 04:03:02.268641: Current learning rate: 0.00089 +2024-11-23 04:03:20.832902: train_loss -0.8299 +2024-11-23 04:03:20.833120: val_loss -0.7352 +2024-11-23 04:03:20.833197: Pseudo dice [0.8557] +2024-11-23 04:03:20.833294: Epoch time: 18.57 s +2024-11-23 04:03:21.781755: +2024-11-23 04:03:21.781983: Epoch 7458 +2024-11-23 04:03:21.782115: Current learning rate: 0.00089 +2024-11-23 04:03:39.784548: train_loss -0.8246 +2024-11-23 04:03:39.784784: val_loss -0.7763 +2024-11-23 04:03:39.784901: Pseudo dice [0.8574] +2024-11-23 04:03:39.784983: Epoch time: 18.0 s +2024-11-23 04:03:40.676207: +2024-11-23 04:03:40.676404: Epoch 7459 +2024-11-23 04:03:40.676519: Current learning rate: 0.00089 +2024-11-23 04:03:59.996896: train_loss -0.8255 +2024-11-23 04:03:59.997135: val_loss -0.7766 +2024-11-23 04:03:59.997211: Pseudo dice [0.857] +2024-11-23 04:03:59.997286: Epoch time: 19.32 s +2024-11-23 04:04:00.894312: +2024-11-23 04:04:00.894514: Epoch 7460 +2024-11-23 04:04:00.894648: Current learning rate: 0.00088 +2024-11-23 04:04:19.476800: train_loss -0.8302 +2024-11-23 04:04:19.477003: val_loss -0.7553 +2024-11-23 04:04:19.477095: Pseudo dice [0.8647] +2024-11-23 04:04:19.477179: Epoch time: 18.58 s +2024-11-23 04:04:20.415539: +2024-11-23 04:04:20.415755: Epoch 7461 +2024-11-23 04:04:20.415870: Current learning rate: 0.00088 +2024-11-23 04:04:38.816687: train_loss -0.8289 +2024-11-23 04:04:38.816905: val_loss -0.7744 +2024-11-23 04:04:38.816985: Pseudo dice [0.8479] +2024-11-23 04:04:38.817084: Epoch time: 18.4 s +2024-11-23 04:04:39.711448: +2024-11-23 04:04:39.711685: Epoch 7462 +2024-11-23 04:04:39.711838: Current learning rate: 0.00088 +2024-11-23 04:04:59.653569: train_loss -0.8213 +2024-11-23 04:04:59.653793: val_loss -0.7695 +2024-11-23 04:04:59.653872: Pseudo dice [0.8523] +2024-11-23 04:04:59.653954: Epoch time: 19.94 s +2024-11-23 04:05:00.566385: +2024-11-23 04:05:00.566598: Epoch 7463 +2024-11-23 04:05:00.566717: Current learning rate: 0.00088 +2024-11-23 04:05:18.084484: train_loss -0.8246 +2024-11-23 04:05:18.084707: val_loss -0.7863 +2024-11-23 04:05:18.084790: Pseudo dice [0.8607] +2024-11-23 04:05:18.084865: Epoch time: 17.52 s +2024-11-23 04:05:18.971481: +2024-11-23 04:05:18.971673: Epoch 7464 +2024-11-23 04:05:18.971792: Current learning rate: 0.00088 +2024-11-23 04:05:38.559236: train_loss -0.8233 +2024-11-23 04:05:38.559457: val_loss -0.7855 +2024-11-23 04:05:38.559596: Pseudo dice [0.8639] +2024-11-23 04:05:38.559677: Epoch time: 19.59 s +2024-11-23 04:05:39.836734: +2024-11-23 04:05:39.836952: Epoch 7465 +2024-11-23 04:05:39.837067: Current learning rate: 0.00088 +2024-11-23 04:05:59.071080: train_loss -0.8303 +2024-11-23 04:05:59.071335: val_loss -0.7702 +2024-11-23 04:05:59.071428: Pseudo dice [0.8536] +2024-11-23 04:05:59.071510: Epoch time: 19.24 s +2024-11-23 04:05:59.986099: +2024-11-23 04:05:59.986326: Epoch 7466 +2024-11-23 04:05:59.986441: Current learning rate: 0.00087 +2024-11-23 04:06:18.258688: train_loss -0.8248 +2024-11-23 04:06:18.258915: val_loss -0.7683 +2024-11-23 04:06:18.259015: Pseudo dice [0.8534] +2024-11-23 04:06:18.259118: Epoch time: 18.27 s +2024-11-23 04:06:19.281030: +2024-11-23 04:06:19.281261: Epoch 7467 +2024-11-23 04:06:19.281379: Current learning rate: 0.00087 +2024-11-23 04:06:37.784622: train_loss -0.8302 +2024-11-23 04:06:37.784832: val_loss -0.7849 +2024-11-23 04:06:37.784906: Pseudo dice [0.8547] +2024-11-23 04:06:37.784999: Epoch time: 18.5 s +2024-11-23 04:06:38.679454: +2024-11-23 04:06:38.679693: Epoch 7468 +2024-11-23 04:06:38.679830: Current learning rate: 0.00087 +2024-11-23 04:06:57.412980: train_loss -0.8234 +2024-11-23 04:06:57.418713: val_loss -0.7729 +2024-11-23 04:06:57.418868: Pseudo dice [0.8453] +2024-11-23 04:06:57.418970: Epoch time: 18.73 s +2024-11-23 04:06:58.352460: +2024-11-23 04:06:58.352655: Epoch 7469 +2024-11-23 04:06:58.352781: Current learning rate: 0.00087 +2024-11-23 04:07:16.525075: train_loss -0.834 +2024-11-23 04:07:16.525295: val_loss -0.7914 +2024-11-23 04:07:16.525373: Pseudo dice [0.8609] +2024-11-23 04:07:16.525457: Epoch time: 18.17 s +2024-11-23 04:07:17.419564: +2024-11-23 04:07:17.419786: Epoch 7470 +2024-11-23 04:07:17.419904: Current learning rate: 0.00087 +2024-11-23 04:07:35.155013: train_loss -0.8223 +2024-11-23 04:07:35.155235: val_loss -0.7897 +2024-11-23 04:07:35.155316: Pseudo dice [0.858] +2024-11-23 04:07:35.160532: Epoch time: 17.74 s +2024-11-23 04:07:36.348977: +2024-11-23 04:07:36.349200: Epoch 7471 +2024-11-23 04:07:36.349325: Current learning rate: 0.00087 +2024-11-23 04:07:54.581800: train_loss -0.8247 +2024-11-23 04:07:54.582014: val_loss -0.7812 +2024-11-23 04:07:54.582104: Pseudo dice [0.8703] +2024-11-23 04:07:54.582181: Epoch time: 18.23 s +2024-11-23 04:07:55.502696: +2024-11-23 04:07:55.502925: Epoch 7472 +2024-11-23 04:07:55.503047: Current learning rate: 0.00087 +2024-11-23 04:08:14.353258: train_loss -0.8258 +2024-11-23 04:08:14.353511: val_loss -0.7785 +2024-11-23 04:08:14.353591: Pseudo dice [0.8522] +2024-11-23 04:08:14.353681: Epoch time: 18.85 s +2024-11-23 04:08:15.374805: +2024-11-23 04:08:15.375023: Epoch 7473 +2024-11-23 04:08:15.375145: Current learning rate: 0.00086 +2024-11-23 04:08:33.628230: train_loss -0.8328 +2024-11-23 04:08:33.628880: val_loss -0.7854 +2024-11-23 04:08:33.628990: Pseudo dice [0.8583] +2024-11-23 04:08:33.629087: Epoch time: 18.25 s +2024-11-23 04:08:34.636872: +2024-11-23 04:08:34.637180: Epoch 7474 +2024-11-23 04:08:34.637314: Current learning rate: 0.00086 +2024-11-23 04:08:53.699234: train_loss -0.8291 +2024-11-23 04:08:53.699457: val_loss -0.7775 +2024-11-23 04:08:53.699543: Pseudo dice [0.8535] +2024-11-23 04:08:53.699634: Epoch time: 19.06 s +2024-11-23 04:08:54.590941: +2024-11-23 04:08:54.591166: Epoch 7475 +2024-11-23 04:08:54.591283: Current learning rate: 0.00086 +2024-11-23 04:09:13.483962: train_loss -0.8265 +2024-11-23 04:09:13.484188: val_loss -0.7843 +2024-11-23 04:09:13.484283: Pseudo dice [0.855] +2024-11-23 04:09:13.484372: Epoch time: 18.89 s +2024-11-23 04:09:14.790255: +2024-11-23 04:09:14.790476: Epoch 7476 +2024-11-23 04:09:14.790612: Current learning rate: 0.00086 +2024-11-23 04:09:32.974532: train_loss -0.8314 +2024-11-23 04:09:32.974801: val_loss -0.7847 +2024-11-23 04:09:32.974880: Pseudo dice [0.8531] +2024-11-23 04:09:32.974969: Epoch time: 18.19 s +2024-11-23 04:09:33.864884: +2024-11-23 04:09:33.865094: Epoch 7477 +2024-11-23 04:09:33.865222: Current learning rate: 0.00086 +2024-11-23 04:09:51.884220: train_loss -0.8304 +2024-11-23 04:09:51.884426: val_loss -0.7829 +2024-11-23 04:09:51.884516: Pseudo dice [0.8476] +2024-11-23 04:09:51.884593: Epoch time: 18.02 s +2024-11-23 04:09:52.769092: +2024-11-23 04:09:52.769310: Epoch 7478 +2024-11-23 04:09:52.769423: Current learning rate: 0.00086 +2024-11-23 04:10:11.254846: train_loss -0.8312 +2024-11-23 04:10:11.255071: val_loss -0.7917 +2024-11-23 04:10:11.255150: Pseudo dice [0.8525] +2024-11-23 04:10:11.255233: Epoch time: 18.49 s +2024-11-23 04:10:12.147086: +2024-11-23 04:10:12.147312: Epoch 7479 +2024-11-23 04:10:12.147438: Current learning rate: 0.00086 +2024-11-23 04:10:30.045538: train_loss -0.8378 +2024-11-23 04:10:30.045779: val_loss -0.7643 +2024-11-23 04:10:30.045921: Pseudo dice [0.862] +2024-11-23 04:10:30.046008: Epoch time: 17.9 s +2024-11-23 04:10:30.940906: +2024-11-23 04:10:30.941110: Epoch 7480 +2024-11-23 04:10:30.941228: Current learning rate: 0.00085 +2024-11-23 04:10:49.470103: train_loss -0.8238 +2024-11-23 04:10:49.470328: val_loss -0.7817 +2024-11-23 04:10:49.470415: Pseudo dice [0.8595] +2024-11-23 04:10:49.470500: Epoch time: 18.53 s +2024-11-23 04:10:50.379489: +2024-11-23 04:10:50.379705: Epoch 7481 +2024-11-23 04:10:50.379821: Current learning rate: 0.00085 +2024-11-23 04:11:08.811064: train_loss -0.8313 +2024-11-23 04:11:08.811277: val_loss -0.7772 +2024-11-23 04:11:08.811369: Pseudo dice [0.8608] +2024-11-23 04:11:08.811448: Epoch time: 18.43 s +2024-11-23 04:11:09.704493: +2024-11-23 04:11:09.704698: Epoch 7482 +2024-11-23 04:11:09.704808: Current learning rate: 0.00085 +2024-11-23 04:11:28.182012: train_loss -0.8313 +2024-11-23 04:11:28.182244: val_loss -0.7853 +2024-11-23 04:11:28.182329: Pseudo dice [0.8597] +2024-11-23 04:11:28.182424: Epoch time: 18.48 s +2024-11-23 04:11:29.074862: +2024-11-23 04:11:29.075096: Epoch 7483 +2024-11-23 04:11:29.075217: Current learning rate: 0.00085 +2024-11-23 04:11:48.253009: train_loss -0.8312 +2024-11-23 04:11:48.253252: val_loss -0.8031 +2024-11-23 04:11:48.253408: Pseudo dice [0.8703] +2024-11-23 04:11:48.253515: Epoch time: 19.18 s +2024-11-23 04:11:49.172489: +2024-11-23 04:11:49.172702: Epoch 7484 +2024-11-23 04:11:49.172820: Current learning rate: 0.00085 +2024-11-23 04:12:07.816917: train_loss -0.8285 +2024-11-23 04:12:07.818388: val_loss -0.7928 +2024-11-23 04:12:07.818472: Pseudo dice [0.858] +2024-11-23 04:12:07.818559: Epoch time: 18.65 s +2024-11-23 04:12:08.706477: +2024-11-23 04:12:08.706691: Epoch 7485 +2024-11-23 04:12:08.706816: Current learning rate: 0.00085 +2024-11-23 04:12:26.678275: train_loss -0.8254 +2024-11-23 04:12:26.678495: val_loss -0.767 +2024-11-23 04:12:26.678574: Pseudo dice [0.8605] +2024-11-23 04:12:26.678679: Epoch time: 17.97 s +2024-11-23 04:12:27.565284: +2024-11-23 04:12:27.565496: Epoch 7486 +2024-11-23 04:12:27.565622: Current learning rate: 0.00085 +2024-11-23 04:12:47.419657: train_loss -0.8247 +2024-11-23 04:12:47.419875: val_loss -0.7794 +2024-11-23 04:12:47.425150: Pseudo dice [0.8591] +2024-11-23 04:12:47.425355: Epoch time: 19.86 s +2024-11-23 04:12:48.704003: +2024-11-23 04:12:48.704214: Epoch 7487 +2024-11-23 04:12:48.704328: Current learning rate: 0.00084 +2024-11-23 04:13:06.808579: train_loss -0.8253 +2024-11-23 04:13:06.808832: val_loss -0.7789 +2024-11-23 04:13:06.808919: Pseudo dice [0.8508] +2024-11-23 04:13:06.809009: Epoch time: 18.11 s +2024-11-23 04:13:07.729846: +2024-11-23 04:13:07.730072: Epoch 7488 +2024-11-23 04:13:07.730187: Current learning rate: 0.00084 +2024-11-23 04:13:25.738912: train_loss -0.8313 +2024-11-23 04:13:25.739128: val_loss -0.789 +2024-11-23 04:13:25.739204: Pseudo dice [0.8703] +2024-11-23 04:13:25.739302: Epoch time: 18.01 s +2024-11-23 04:13:26.631571: +2024-11-23 04:13:26.631803: Epoch 7489 +2024-11-23 04:13:26.631937: Current learning rate: 0.00084 +2024-11-23 04:13:45.560197: train_loss -0.8327 +2024-11-23 04:13:45.560423: val_loss -0.7717 +2024-11-23 04:13:45.560517: Pseudo dice [0.8588] +2024-11-23 04:13:45.560604: Epoch time: 18.93 s +2024-11-23 04:13:46.449994: +2024-11-23 04:13:46.450228: Epoch 7490 +2024-11-23 04:13:46.450344: Current learning rate: 0.00084 +2024-11-23 04:14:04.687812: train_loss -0.8232 +2024-11-23 04:14:04.688145: val_loss -0.7904 +2024-11-23 04:14:04.688264: Pseudo dice [0.8589] +2024-11-23 04:14:04.688362: Epoch time: 18.24 s +2024-11-23 04:14:05.589096: +2024-11-23 04:14:05.589348: Epoch 7491 +2024-11-23 04:14:05.589463: Current learning rate: 0.00084 +2024-11-23 04:14:24.818776: train_loss -0.8251 +2024-11-23 04:14:24.819027: val_loss -0.7699 +2024-11-23 04:14:24.819128: Pseudo dice [0.8665] +2024-11-23 04:14:24.819233: Epoch time: 19.23 s +2024-11-23 04:14:25.715168: +2024-11-23 04:14:25.715394: Epoch 7492 +2024-11-23 04:14:25.715510: Current learning rate: 0.00084 +2024-11-23 04:14:44.004823: train_loss -0.8297 +2024-11-23 04:14:44.005033: val_loss -0.7741 +2024-11-23 04:14:44.005122: Pseudo dice [0.8633] +2024-11-23 04:14:44.005219: Epoch time: 18.29 s +2024-11-23 04:14:45.061653: +2024-11-23 04:14:45.061867: Epoch 7493 +2024-11-23 04:14:45.061987: Current learning rate: 0.00084 +2024-11-23 04:15:02.725147: train_loss -0.8304 +2024-11-23 04:15:02.725364: val_loss -0.7805 +2024-11-23 04:15:02.725454: Pseudo dice [0.8395] +2024-11-23 04:15:02.725533: Epoch time: 17.66 s +2024-11-23 04:15:03.618386: +2024-11-23 04:15:03.618610: Epoch 7494 +2024-11-23 04:15:03.618729: Current learning rate: 0.00083 +2024-11-23 04:15:21.834572: train_loss -0.8272 +2024-11-23 04:15:21.835174: val_loss -0.7993 +2024-11-23 04:15:21.835278: Pseudo dice [0.8659] +2024-11-23 04:15:21.835362: Epoch time: 18.22 s +2024-11-23 04:15:22.733840: +2024-11-23 04:15:22.734070: Epoch 7495 +2024-11-23 04:15:22.734191: Current learning rate: 0.00083 +2024-11-23 04:15:41.681576: train_loss -0.824 +2024-11-23 04:15:41.681797: val_loss -0.7891 +2024-11-23 04:15:41.681885: Pseudo dice [0.8645] +2024-11-23 04:15:41.681963: Epoch time: 18.95 s +2024-11-23 04:15:42.576572: +2024-11-23 04:15:42.576824: Epoch 7496 +2024-11-23 04:15:42.576945: Current learning rate: 0.00083 +2024-11-23 04:16:01.541530: train_loss -0.8297 +2024-11-23 04:16:01.541738: val_loss -0.8097 +2024-11-23 04:16:01.541822: Pseudo dice [0.8627] +2024-11-23 04:16:01.541896: Epoch time: 18.97 s +2024-11-23 04:16:02.440889: +2024-11-23 04:16:02.441116: Epoch 7497 +2024-11-23 04:16:02.441234: Current learning rate: 0.00083 +2024-11-23 04:16:20.965891: train_loss -0.829 +2024-11-23 04:16:20.966110: val_loss -0.7908 +2024-11-23 04:16:20.966196: Pseudo dice [0.8732] +2024-11-23 04:16:20.966285: Epoch time: 18.53 s +2024-11-23 04:16:22.251351: +2024-11-23 04:16:22.251564: Epoch 7498 +2024-11-23 04:16:22.251684: Current learning rate: 0.00083 +2024-11-23 04:16:40.710243: train_loss -0.8286 +2024-11-23 04:16:40.710505: val_loss -0.7915 +2024-11-23 04:16:40.710590: Pseudo dice [0.8648] +2024-11-23 04:16:40.710678: Epoch time: 18.46 s +2024-11-23 04:16:41.602377: +2024-11-23 04:16:41.602581: Epoch 7499 +2024-11-23 04:16:41.602697: Current learning rate: 0.00083 +2024-11-23 04:16:59.685717: train_loss -0.833 +2024-11-23 04:16:59.685948: val_loss -0.7963 +2024-11-23 04:16:59.686051: Pseudo dice [0.8508] +2024-11-23 04:16:59.686141: Epoch time: 18.08 s +2024-11-23 04:17:00.925094: +2024-11-23 04:17:00.925305: Epoch 7500 +2024-11-23 04:17:00.925418: Current learning rate: 0.00082 +2024-11-23 04:17:20.085758: train_loss -0.8265 +2024-11-23 04:17:20.085968: val_loss -0.7938 +2024-11-23 04:17:20.086053: Pseudo dice [0.8644] +2024-11-23 04:17:20.086152: Epoch time: 19.16 s +2024-11-23 04:17:20.975079: +2024-11-23 04:17:20.975284: Epoch 7501 +2024-11-23 04:17:20.975418: Current learning rate: 0.00082 +2024-11-23 04:17:39.051223: train_loss -0.8252 +2024-11-23 04:17:39.051447: val_loss -0.7901 +2024-11-23 04:17:39.051538: Pseudo dice [0.8602] +2024-11-23 04:17:39.051638: Epoch time: 18.08 s +2024-11-23 04:17:39.951390: +2024-11-23 04:17:39.951602: Epoch 7502 +2024-11-23 04:17:39.951727: Current learning rate: 0.00082 +2024-11-23 04:17:58.849680: train_loss -0.8304 +2024-11-23 04:17:58.849926: val_loss -0.7791 +2024-11-23 04:17:58.850009: Pseudo dice [0.8573] +2024-11-23 04:17:58.850096: Epoch time: 18.9 s +2024-11-23 04:17:59.749069: +2024-11-23 04:17:59.749273: Epoch 7503 +2024-11-23 04:17:59.749397: Current learning rate: 0.00082 +2024-11-23 04:18:18.495202: train_loss -0.8278 +2024-11-23 04:18:18.495416: val_loss -0.7811 +2024-11-23 04:18:18.495493: Pseudo dice [0.8563] +2024-11-23 04:18:18.495582: Epoch time: 18.75 s +2024-11-23 04:18:19.507448: +2024-11-23 04:18:19.507689: Epoch 7504 +2024-11-23 04:18:19.507817: Current learning rate: 0.00082 +2024-11-23 04:18:37.294639: train_loss -0.8342 +2024-11-23 04:18:37.294858: val_loss -0.7801 +2024-11-23 04:18:37.294936: Pseudo dice [0.8598] +2024-11-23 04:18:37.295015: Epoch time: 17.79 s +2024-11-23 04:18:38.184502: +2024-11-23 04:18:38.184706: Epoch 7505 +2024-11-23 04:18:38.184815: Current learning rate: 0.00082 +2024-11-23 04:18:56.911292: train_loss -0.8307 +2024-11-23 04:18:56.911521: val_loss -0.7763 +2024-11-23 04:18:56.911602: Pseudo dice [0.8529] +2024-11-23 04:18:56.911689: Epoch time: 18.73 s +2024-11-23 04:18:57.807528: +2024-11-23 04:18:57.807727: Epoch 7506 +2024-11-23 04:18:57.807845: Current learning rate: 0.00082 +2024-11-23 04:19:16.213532: train_loss -0.8238 +2024-11-23 04:19:16.213782: val_loss -0.798 +2024-11-23 04:19:16.213868: Pseudo dice [0.8679] +2024-11-23 04:19:16.213959: Epoch time: 18.41 s +2024-11-23 04:19:17.110740: +2024-11-23 04:19:17.110959: Epoch 7507 +2024-11-23 04:19:17.111088: Current learning rate: 0.00081 +2024-11-23 04:19:35.156569: train_loss -0.8263 +2024-11-23 04:19:35.156779: val_loss -0.7466 +2024-11-23 04:19:35.156854: Pseudo dice [0.859] +2024-11-23 04:19:35.156929: Epoch time: 18.05 s +2024-11-23 04:19:36.067492: +2024-11-23 04:19:36.067717: Epoch 7508 +2024-11-23 04:19:36.067836: Current learning rate: 0.00081 +2024-11-23 04:19:55.663070: train_loss -0.8221 +2024-11-23 04:19:55.663292: val_loss -0.7775 +2024-11-23 04:19:55.663372: Pseudo dice [0.8591] +2024-11-23 04:19:55.663471: Epoch time: 19.6 s +2024-11-23 04:19:56.961681: +2024-11-23 04:19:56.961899: Epoch 7509 +2024-11-23 04:19:56.962022: Current learning rate: 0.00081 +2024-11-23 04:20:15.753469: train_loss -0.8286 +2024-11-23 04:20:15.753702: val_loss -0.7862 +2024-11-23 04:20:15.753785: Pseudo dice [0.8523] +2024-11-23 04:20:15.753865: Epoch time: 18.79 s +2024-11-23 04:20:16.653748: +2024-11-23 04:20:16.653961: Epoch 7510 +2024-11-23 04:20:16.654072: Current learning rate: 0.00081 +2024-11-23 04:20:34.854875: train_loss -0.8348 +2024-11-23 04:20:34.855127: val_loss -0.7955 +2024-11-23 04:20:34.855201: Pseudo dice [0.8715] +2024-11-23 04:20:34.855279: Epoch time: 18.2 s +2024-11-23 04:20:35.845723: +2024-11-23 04:20:35.845932: Epoch 7511 +2024-11-23 04:20:35.846044: Current learning rate: 0.00081 +2024-11-23 04:20:53.842586: train_loss -0.8288 +2024-11-23 04:20:53.842807: val_loss -0.7935 +2024-11-23 04:20:53.842887: Pseudo dice [0.8634] +2024-11-23 04:20:53.842965: Epoch time: 18.0 s +2024-11-23 04:20:54.800049: +2024-11-23 04:20:54.800270: Epoch 7512 +2024-11-23 04:20:54.800397: Current learning rate: 0.00081 +2024-11-23 04:21:12.994089: train_loss -0.8229 +2024-11-23 04:21:12.996057: val_loss -0.7817 +2024-11-23 04:21:12.996186: Pseudo dice [0.858] +2024-11-23 04:21:12.996329: Epoch time: 18.19 s +2024-11-23 04:21:13.899978: +2024-11-23 04:21:13.900214: Epoch 7513 +2024-11-23 04:21:13.900348: Current learning rate: 0.00081 +2024-11-23 04:21:31.470391: train_loss -0.8286 +2024-11-23 04:21:31.470648: val_loss -0.7799 +2024-11-23 04:21:31.470728: Pseudo dice [0.8695] +2024-11-23 04:21:31.470811: Epoch time: 17.57 s +2024-11-23 04:21:32.508351: +2024-11-23 04:21:32.508547: Epoch 7514 +2024-11-23 04:21:32.508669: Current learning rate: 0.0008 +2024-11-23 04:21:50.501490: train_loss -0.8369 +2024-11-23 04:21:50.501700: val_loss -0.7818 +2024-11-23 04:21:50.501779: Pseudo dice [0.8637] +2024-11-23 04:21:50.501855: Epoch time: 17.99 s +2024-11-23 04:21:51.391983: +2024-11-23 04:21:51.392190: Epoch 7515 +2024-11-23 04:21:51.392303: Current learning rate: 0.0008 +2024-11-23 04:22:09.337322: train_loss -0.8329 +2024-11-23 04:22:09.337544: val_loss -0.7938 +2024-11-23 04:22:09.337623: Pseudo dice [0.8534] +2024-11-23 04:22:09.337703: Epoch time: 17.95 s +2024-11-23 04:22:10.296307: +2024-11-23 04:22:10.296519: Epoch 7516 +2024-11-23 04:22:10.296639: Current learning rate: 0.0008 +2024-11-23 04:22:28.834359: train_loss -0.8313 +2024-11-23 04:22:28.834644: val_loss -0.7935 +2024-11-23 04:22:28.834732: Pseudo dice [0.8729] +2024-11-23 04:22:28.834825: Epoch time: 18.54 s +2024-11-23 04:22:29.833221: +2024-11-23 04:22:29.833441: Epoch 7517 +2024-11-23 04:22:29.833549: Current learning rate: 0.0008 +2024-11-23 04:22:48.322760: train_loss -0.83 +2024-11-23 04:22:48.323007: val_loss -0.7825 +2024-11-23 04:22:48.323111: Pseudo dice [0.8688] +2024-11-23 04:22:48.323199: Epoch time: 18.49 s +2024-11-23 04:22:48.323262: Yayy! New best EMA pseudo Dice: 0.8626 +2024-11-23 04:22:49.552622: +2024-11-23 04:22:49.552847: Epoch 7518 +2024-11-23 04:22:49.552970: Current learning rate: 0.0008 +2024-11-23 04:23:08.022912: train_loss -0.8255 +2024-11-23 04:23:08.023132: val_loss -0.7663 +2024-11-23 04:23:08.023228: Pseudo dice [0.853] +2024-11-23 04:23:08.023321: Epoch time: 18.47 s +2024-11-23 04:23:08.913830: +2024-11-23 04:23:08.914040: Epoch 7519 +2024-11-23 04:23:08.914155: Current learning rate: 0.0008 +2024-11-23 04:23:27.624796: train_loss -0.8241 +2024-11-23 04:23:27.625018: val_loss -0.7806 +2024-11-23 04:23:27.625160: Pseudo dice [0.8531] +2024-11-23 04:23:27.625237: Epoch time: 18.71 s +2024-11-23 04:23:28.906298: +2024-11-23 04:23:28.906515: Epoch 7520 +2024-11-23 04:23:28.906706: Current learning rate: 0.00079 +2024-11-23 04:23:48.652815: train_loss -0.8246 +2024-11-23 04:23:48.653076: val_loss -0.7607 +2024-11-23 04:23:48.653171: Pseudo dice [0.8386] +2024-11-23 04:23:48.653263: Epoch time: 19.75 s +2024-11-23 04:23:49.551182: +2024-11-23 04:23:49.551399: Epoch 7521 +2024-11-23 04:23:49.551517: Current learning rate: 0.00079 +2024-11-23 04:24:08.099409: train_loss -0.8293 +2024-11-23 04:24:08.099641: val_loss -0.7896 +2024-11-23 04:24:08.099732: Pseudo dice [0.8631] +2024-11-23 04:24:08.102043: Epoch time: 18.55 s +2024-11-23 04:24:09.105307: +2024-11-23 04:24:09.105508: Epoch 7522 +2024-11-23 04:24:09.105636: Current learning rate: 0.00079 +2024-11-23 04:24:27.621431: train_loss -0.8313 +2024-11-23 04:24:27.621670: val_loss -0.7917 +2024-11-23 04:24:27.621760: Pseudo dice [0.8698] +2024-11-23 04:24:27.621838: Epoch time: 18.52 s +2024-11-23 04:24:28.520329: +2024-11-23 04:24:28.520557: Epoch 7523 +2024-11-23 04:24:28.520674: Current learning rate: 0.00079 +2024-11-23 04:24:45.975807: train_loss -0.826 +2024-11-23 04:24:45.976043: val_loss -0.774 +2024-11-23 04:24:45.976139: Pseudo dice [0.8447] +2024-11-23 04:24:45.976220: Epoch time: 17.46 s +2024-11-23 04:24:46.872871: +2024-11-23 04:24:46.873137: Epoch 7524 +2024-11-23 04:24:46.873256: Current learning rate: 0.00079 +2024-11-23 04:25:05.239981: train_loss -0.8323 +2024-11-23 04:25:05.240231: val_loss -0.795 +2024-11-23 04:25:05.240315: Pseudo dice [0.862] +2024-11-23 04:25:05.240393: Epoch time: 18.37 s +2024-11-23 04:25:06.138453: +2024-11-23 04:25:06.138674: Epoch 7525 +2024-11-23 04:25:06.138788: Current learning rate: 0.00079 +2024-11-23 04:25:25.365870: train_loss -0.833 +2024-11-23 04:25:25.366098: val_loss -0.7658 +2024-11-23 04:25:25.366185: Pseudo dice [0.8559] +2024-11-23 04:25:25.366269: Epoch time: 19.23 s +2024-11-23 04:25:26.336945: +2024-11-23 04:25:26.337186: Epoch 7526 +2024-11-23 04:25:26.337323: Current learning rate: 0.00079 +2024-11-23 04:25:44.186164: train_loss -0.8294 +2024-11-23 04:25:44.187471: val_loss -0.7687 +2024-11-23 04:25:44.187584: Pseudo dice [0.8638] +2024-11-23 04:25:44.187665: Epoch time: 17.85 s +2024-11-23 04:25:45.190106: +2024-11-23 04:25:45.190313: Epoch 7527 +2024-11-23 04:25:45.190425: Current learning rate: 0.00078 +2024-11-23 04:26:03.945400: train_loss -0.8234 +2024-11-23 04:26:03.945615: val_loss -0.7791 +2024-11-23 04:26:03.945708: Pseudo dice [0.8568] +2024-11-23 04:26:03.945787: Epoch time: 18.76 s +2024-11-23 04:26:04.949074: +2024-11-23 04:26:04.949295: Epoch 7528 +2024-11-23 04:26:04.949410: Current learning rate: 0.00078 +2024-11-23 04:26:23.472402: train_loss -0.824 +2024-11-23 04:26:23.472717: val_loss -0.764 +2024-11-23 04:26:23.472819: Pseudo dice [0.8526] +2024-11-23 04:26:23.472905: Epoch time: 18.52 s +2024-11-23 04:26:24.368712: +2024-11-23 04:26:24.368909: Epoch 7529 +2024-11-23 04:26:24.369035: Current learning rate: 0.00078 +2024-11-23 04:26:43.613865: train_loss -0.8256 +2024-11-23 04:26:43.614100: val_loss -0.7677 +2024-11-23 04:26:43.614183: Pseudo dice [0.8682] +2024-11-23 04:26:43.614266: Epoch time: 19.25 s +2024-11-23 04:26:44.509045: +2024-11-23 04:26:44.509296: Epoch 7530 +2024-11-23 04:26:44.509424: Current learning rate: 0.00078 +2024-11-23 04:27:02.815749: train_loss -0.8379 +2024-11-23 04:27:02.815962: val_loss -0.7878 +2024-11-23 04:27:02.816040: Pseudo dice [0.8672] +2024-11-23 04:27:02.816124: Epoch time: 18.31 s +2024-11-23 04:27:03.704808: +2024-11-23 04:27:03.705017: Epoch 7531 +2024-11-23 04:27:03.705136: Current learning rate: 0.00078 +2024-11-23 04:27:22.756735: train_loss -0.8359 +2024-11-23 04:27:22.757231: val_loss -0.7796 +2024-11-23 04:27:22.757327: Pseudo dice [0.8505] +2024-11-23 04:27:22.757406: Epoch time: 19.05 s +2024-11-23 04:27:23.652897: +2024-11-23 04:27:23.653105: Epoch 7532 +2024-11-23 04:27:23.653243: Current learning rate: 0.00078 +2024-11-23 04:27:42.629153: train_loss -0.8334 +2024-11-23 04:27:42.629415: val_loss -0.7792 +2024-11-23 04:27:42.629493: Pseudo dice [0.8622] +2024-11-23 04:27:42.629573: Epoch time: 18.98 s +2024-11-23 04:27:43.531608: +2024-11-23 04:27:43.531817: Epoch 7533 +2024-11-23 04:27:43.531943: Current learning rate: 0.00078 +2024-11-23 04:28:01.074897: train_loss -0.8333 +2024-11-23 04:28:01.075131: val_loss -0.7989 +2024-11-23 04:28:01.075222: Pseudo dice [0.8598] +2024-11-23 04:28:01.075314: Epoch time: 17.54 s +2024-11-23 04:28:01.972431: +2024-11-23 04:28:01.972665: Epoch 7534 +2024-11-23 04:28:01.972777: Current learning rate: 0.00077 +2024-11-23 04:28:21.141325: train_loss -0.8367 +2024-11-23 04:28:21.141531: val_loss -0.8 +2024-11-23 04:28:21.141613: Pseudo dice [0.8551] +2024-11-23 04:28:21.141688: Epoch time: 19.17 s +2024-11-23 04:28:22.036986: +2024-11-23 04:28:22.037220: Epoch 7535 +2024-11-23 04:28:22.037352: Current learning rate: 0.00077 +2024-11-23 04:28:40.189900: train_loss -0.8312 +2024-11-23 04:28:40.190155: val_loss -0.7748 +2024-11-23 04:28:40.190242: Pseudo dice [0.8493] +2024-11-23 04:28:40.190352: Epoch time: 18.15 s +2024-11-23 04:28:41.095524: +2024-11-23 04:28:41.095745: Epoch 7536 +2024-11-23 04:28:41.095862: Current learning rate: 0.00077 +2024-11-23 04:29:01.200891: train_loss -0.8214 +2024-11-23 04:29:01.201102: val_loss -0.7367 +2024-11-23 04:29:01.201177: Pseudo dice [0.854] +2024-11-23 04:29:01.201251: Epoch time: 20.11 s +2024-11-23 04:29:02.263824: +2024-11-23 04:29:02.264037: Epoch 7537 +2024-11-23 04:29:02.264155: Current learning rate: 0.00077 +2024-11-23 04:29:20.007893: train_loss -0.8347 +2024-11-23 04:29:20.008159: val_loss -0.79 +2024-11-23 04:29:20.008243: Pseudo dice [0.8616] +2024-11-23 04:29:20.008343: Epoch time: 17.74 s +2024-11-23 04:29:20.898108: +2024-11-23 04:29:20.898329: Epoch 7538 +2024-11-23 04:29:20.898452: Current learning rate: 0.00077 +2024-11-23 04:29:39.621732: train_loss -0.8322 +2024-11-23 04:29:39.621979: val_loss -0.7632 +2024-11-23 04:29:39.622065: Pseudo dice [0.8518] +2024-11-23 04:29:39.622145: Epoch time: 18.72 s +2024-11-23 04:29:40.518147: +2024-11-23 04:29:40.518390: Epoch 7539 +2024-11-23 04:29:40.518514: Current learning rate: 0.00077 +2024-11-23 04:29:59.030186: train_loss -0.8323 +2024-11-23 04:29:59.030394: val_loss -0.7724 +2024-11-23 04:29:59.030470: Pseudo dice [0.8478] +2024-11-23 04:29:59.030551: Epoch time: 18.51 s +2024-11-23 04:29:59.919851: +2024-11-23 04:29:59.920110: Epoch 7540 +2024-11-23 04:29:59.920252: Current learning rate: 0.00077 +2024-11-23 04:30:18.017005: train_loss -0.8244 +2024-11-23 04:30:18.017222: val_loss -0.7639 +2024-11-23 04:30:18.017304: Pseudo dice [0.8481] +2024-11-23 04:30:18.017501: Epoch time: 18.1 s +2024-11-23 04:30:18.909764: +2024-11-23 04:30:18.909993: Epoch 7541 +2024-11-23 04:30:18.910116: Current learning rate: 0.00076 +2024-11-23 04:30:37.674790: train_loss -0.8269 +2024-11-23 04:30:37.674997: val_loss -0.7913 +2024-11-23 04:30:37.675079: Pseudo dice [0.8579] +2024-11-23 04:30:37.675153: Epoch time: 18.77 s +2024-11-23 04:30:38.958478: +2024-11-23 04:30:38.958695: Epoch 7542 +2024-11-23 04:30:38.958812: Current learning rate: 0.00076 +2024-11-23 04:30:57.608231: train_loss -0.8326 +2024-11-23 04:30:57.608508: val_loss -0.8039 +2024-11-23 04:30:57.608593: Pseudo dice [0.8596] +2024-11-23 04:30:57.608678: Epoch time: 18.65 s +2024-11-23 04:30:58.509408: +2024-11-23 04:30:58.509618: Epoch 7543 +2024-11-23 04:30:58.509752: Current learning rate: 0.00076 +2024-11-23 04:31:16.969621: train_loss -0.8361 +2024-11-23 04:31:16.969837: val_loss -0.7887 +2024-11-23 04:31:16.969918: Pseudo dice [0.8637] +2024-11-23 04:31:16.970006: Epoch time: 18.46 s +2024-11-23 04:31:17.861669: +2024-11-23 04:31:17.861881: Epoch 7544 +2024-11-23 04:31:17.861992: Current learning rate: 0.00076 +2024-11-23 04:31:35.084138: train_loss -0.8356 +2024-11-23 04:31:35.084362: val_loss -0.7946 +2024-11-23 04:31:35.084452: Pseudo dice [0.8576] +2024-11-23 04:31:35.084543: Epoch time: 17.22 s +2024-11-23 04:31:35.981554: +2024-11-23 04:31:35.981762: Epoch 7545 +2024-11-23 04:31:35.981890: Current learning rate: 0.00076 +2024-11-23 04:31:54.253682: train_loss -0.8361 +2024-11-23 04:31:54.256081: val_loss -0.7831 +2024-11-23 04:31:54.256211: Pseudo dice [0.8532] +2024-11-23 04:31:54.256301: Epoch time: 18.27 s +2024-11-23 04:31:55.358381: +2024-11-23 04:31:55.358918: Epoch 7546 +2024-11-23 04:31:55.359046: Current learning rate: 0.00076 +2024-11-23 04:32:14.671215: train_loss -0.8311 +2024-11-23 04:32:14.671453: val_loss -0.7863 +2024-11-23 04:32:14.671542: Pseudo dice [0.8564] +2024-11-23 04:32:14.671629: Epoch time: 19.31 s +2024-11-23 04:32:15.562878: +2024-11-23 04:32:15.563138: Epoch 7547 +2024-11-23 04:32:15.563257: Current learning rate: 0.00075 +2024-11-23 04:32:33.534136: train_loss -0.8275 +2024-11-23 04:32:33.534354: val_loss -0.7992 +2024-11-23 04:32:33.534437: Pseudo dice [0.8596] +2024-11-23 04:32:33.534514: Epoch time: 17.97 s +2024-11-23 04:32:34.463593: +2024-11-23 04:32:34.463822: Epoch 7548 +2024-11-23 04:32:34.463941: Current learning rate: 0.00075 +2024-11-23 04:32:51.832718: train_loss -0.8255 +2024-11-23 04:32:51.832932: val_loss -0.7885 +2024-11-23 04:32:51.833010: Pseudo dice [0.8625] +2024-11-23 04:32:51.833096: Epoch time: 17.37 s +2024-11-23 04:32:52.723773: +2024-11-23 04:32:52.723991: Epoch 7549 +2024-11-23 04:32:52.724116: Current learning rate: 0.00075 +2024-11-23 04:33:11.355513: train_loss -0.8302 +2024-11-23 04:33:11.355728: val_loss -0.7792 +2024-11-23 04:33:11.355816: Pseudo dice [0.8571] +2024-11-23 04:33:11.355901: Epoch time: 18.63 s +2024-11-23 04:33:12.639813: +2024-11-23 04:33:12.640035: Epoch 7550 +2024-11-23 04:33:12.640155: Current learning rate: 0.00075 +2024-11-23 04:33:30.725301: train_loss -0.8365 +2024-11-23 04:33:30.725553: val_loss -0.794 +2024-11-23 04:33:30.725634: Pseudo dice [0.8476] +2024-11-23 04:33:30.725725: Epoch time: 18.09 s +2024-11-23 04:33:31.614260: +2024-11-23 04:33:31.614475: Epoch 7551 +2024-11-23 04:33:31.614592: Current learning rate: 0.00075 +2024-11-23 04:33:49.736465: train_loss -0.831 +2024-11-23 04:33:49.736688: val_loss -0.7786 +2024-11-23 04:33:49.736784: Pseudo dice [0.868] +2024-11-23 04:33:49.736862: Epoch time: 18.12 s +2024-11-23 04:33:50.636920: +2024-11-23 04:33:50.637117: Epoch 7552 +2024-11-23 04:33:50.637234: Current learning rate: 0.00075 +2024-11-23 04:34:10.192888: train_loss -0.829 +2024-11-23 04:34:10.193124: val_loss -0.7602 +2024-11-23 04:34:10.193204: Pseudo dice [0.8566] +2024-11-23 04:34:10.193306: Epoch time: 19.56 s +2024-11-23 04:34:11.481328: +2024-11-23 04:34:11.481544: Epoch 7553 +2024-11-23 04:34:11.481659: Current learning rate: 0.00075 +2024-11-23 04:34:30.162625: train_loss -0.8331 +2024-11-23 04:34:30.168070: val_loss -0.7665 +2024-11-23 04:34:30.168204: Pseudo dice [0.8506] +2024-11-23 04:34:30.168294: Epoch time: 18.68 s +2024-11-23 04:34:31.082317: +2024-11-23 04:34:31.082527: Epoch 7554 +2024-11-23 04:34:31.082638: Current learning rate: 0.00074 +2024-11-23 04:34:50.157333: train_loss -0.8284 +2024-11-23 04:34:50.157567: val_loss -0.7672 +2024-11-23 04:34:50.157671: Pseudo dice [0.8582] +2024-11-23 04:34:50.157748: Epoch time: 19.08 s +2024-11-23 04:34:51.050082: +2024-11-23 04:34:51.050290: Epoch 7555 +2024-11-23 04:34:51.050406: Current learning rate: 0.00074 +2024-11-23 04:35:09.466279: train_loss -0.8333 +2024-11-23 04:35:09.466490: val_loss -0.7834 +2024-11-23 04:35:09.466582: Pseudo dice [0.8597] +2024-11-23 04:35:09.466682: Epoch time: 18.42 s +2024-11-23 04:35:10.353351: +2024-11-23 04:35:10.353554: Epoch 7556 +2024-11-23 04:35:10.353680: Current learning rate: 0.00074 +2024-11-23 04:35:28.274611: train_loss -0.8319 +2024-11-23 04:35:28.274826: val_loss -0.8029 +2024-11-23 04:35:28.274907: Pseudo dice [0.8624] +2024-11-23 04:35:28.274995: Epoch time: 17.92 s +2024-11-23 04:35:29.174512: +2024-11-23 04:35:29.174736: Epoch 7557 +2024-11-23 04:35:29.174854: Current learning rate: 0.00074 +2024-11-23 04:35:47.167054: train_loss -0.8313 +2024-11-23 04:35:47.167304: val_loss -0.7648 +2024-11-23 04:35:47.167384: Pseudo dice [0.8589] +2024-11-23 04:35:47.167472: Epoch time: 17.99 s +2024-11-23 04:35:48.068504: +2024-11-23 04:35:48.068713: Epoch 7558 +2024-11-23 04:35:48.068827: Current learning rate: 0.00074 +2024-11-23 04:36:06.498426: train_loss -0.8293 +2024-11-23 04:36:06.498638: val_loss -0.775 +2024-11-23 04:36:06.498716: Pseudo dice [0.8537] +2024-11-23 04:36:06.498792: Epoch time: 18.43 s +2024-11-23 04:36:07.409560: +2024-11-23 04:36:07.409771: Epoch 7559 +2024-11-23 04:36:07.409883: Current learning rate: 0.00074 +2024-11-23 04:36:26.502357: train_loss -0.8337 +2024-11-23 04:36:26.502580: val_loss -0.7839 +2024-11-23 04:36:26.502658: Pseudo dice [0.8538] +2024-11-23 04:36:26.502741: Epoch time: 19.09 s +2024-11-23 04:36:27.398484: +2024-11-23 04:36:27.398702: Epoch 7560 +2024-11-23 04:36:27.398818: Current learning rate: 0.00074 +2024-11-23 04:36:45.906852: train_loss -0.8388 +2024-11-23 04:36:45.907069: val_loss -0.7796 +2024-11-23 04:36:45.907164: Pseudo dice [0.8666] +2024-11-23 04:36:45.907251: Epoch time: 18.51 s +2024-11-23 04:36:46.802772: +2024-11-23 04:36:46.802989: Epoch 7561 +2024-11-23 04:36:46.803119: Current learning rate: 0.00073 +2024-11-23 04:37:05.275801: train_loss -0.8275 +2024-11-23 04:37:05.276031: val_loss -0.767 +2024-11-23 04:37:05.276123: Pseudo dice [0.8708] +2024-11-23 04:37:05.276206: Epoch time: 18.47 s +2024-11-23 04:37:06.163814: +2024-11-23 04:37:06.164021: Epoch 7562 +2024-11-23 04:37:06.164152: Current learning rate: 0.00073 +2024-11-23 04:37:24.275128: train_loss -0.8374 +2024-11-23 04:37:24.275335: val_loss -0.7925 +2024-11-23 04:37:24.275414: Pseudo dice [0.8669] +2024-11-23 04:37:24.275497: Epoch time: 18.11 s +2024-11-23 04:37:25.163740: +2024-11-23 04:37:25.163958: Epoch 7563 +2024-11-23 04:37:25.164088: Current learning rate: 0.00073 +2024-11-23 04:37:43.774535: train_loss -0.8289 +2024-11-23 04:37:43.774747: val_loss -0.7721 +2024-11-23 04:37:43.774828: Pseudo dice [0.8633] +2024-11-23 04:37:43.774908: Epoch time: 18.61 s +2024-11-23 04:37:45.089393: +2024-11-23 04:37:45.089605: Epoch 7564 +2024-11-23 04:37:45.089733: Current learning rate: 0.00073 +2024-11-23 04:38:03.297764: train_loss -0.833 +2024-11-23 04:38:03.298038: val_loss -0.7706 +2024-11-23 04:38:03.298129: Pseudo dice [0.8666] +2024-11-23 04:38:03.298228: Epoch time: 18.21 s +2024-11-23 04:38:04.194735: +2024-11-23 04:38:04.194948: Epoch 7565 +2024-11-23 04:38:04.195081: Current learning rate: 0.00073 +2024-11-23 04:38:21.737695: train_loss -0.8329 +2024-11-23 04:38:21.737910: val_loss -0.7827 +2024-11-23 04:38:21.737994: Pseudo dice [0.8673] +2024-11-23 04:38:21.738095: Epoch time: 17.54 s +2024-11-23 04:38:22.631942: +2024-11-23 04:38:22.632190: Epoch 7566 +2024-11-23 04:38:22.632302: Current learning rate: 0.00073 +2024-11-23 04:38:42.323583: train_loss -0.8313 +2024-11-23 04:38:42.323808: val_loss -0.78 +2024-11-23 04:38:42.323887: Pseudo dice [0.8615] +2024-11-23 04:38:42.323992: Epoch time: 19.69 s +2024-11-23 04:38:43.214840: +2024-11-23 04:38:43.215050: Epoch 7567 +2024-11-23 04:38:43.215176: Current learning rate: 0.00072 +2024-11-23 04:39:01.667649: train_loss -0.8295 +2024-11-23 04:39:01.667873: val_loss -0.7863 +2024-11-23 04:39:01.667951: Pseudo dice [0.8679] +2024-11-23 04:39:01.668053: Epoch time: 18.45 s +2024-11-23 04:39:02.863494: +2024-11-23 04:39:02.863735: Epoch 7568 +2024-11-23 04:39:02.863861: Current learning rate: 0.00072 +2024-11-23 04:39:22.810842: train_loss -0.82 +2024-11-23 04:39:22.811086: val_loss -0.7652 +2024-11-23 04:39:22.811168: Pseudo dice [0.8552] +2024-11-23 04:39:22.811275: Epoch time: 19.95 s +2024-11-23 04:39:23.705374: +2024-11-23 04:39:23.705585: Epoch 7569 +2024-11-23 04:39:23.705707: Current learning rate: 0.00072 +2024-11-23 04:39:41.472039: train_loss -0.829 +2024-11-23 04:39:41.472259: val_loss -0.7873 +2024-11-23 04:39:41.472336: Pseudo dice [0.8607] +2024-11-23 04:39:41.472424: Epoch time: 17.77 s +2024-11-23 04:39:42.373089: +2024-11-23 04:39:42.373317: Epoch 7570 +2024-11-23 04:39:42.373437: Current learning rate: 0.00072 +2024-11-23 04:40:00.825572: train_loss -0.8219 +2024-11-23 04:40:00.825806: val_loss -0.7965 +2024-11-23 04:40:00.825903: Pseudo dice [0.8577] +2024-11-23 04:40:00.825982: Epoch time: 18.45 s +2024-11-23 04:40:01.726344: +2024-11-23 04:40:01.726562: Epoch 7571 +2024-11-23 04:40:01.726676: Current learning rate: 0.00072 +2024-11-23 04:40:20.731996: train_loss -0.83 +2024-11-23 04:40:20.732227: val_loss -0.7939 +2024-11-23 04:40:20.732306: Pseudo dice [0.8581] +2024-11-23 04:40:20.732383: Epoch time: 19.01 s +2024-11-23 04:40:21.663545: +2024-11-23 04:40:21.663753: Epoch 7572 +2024-11-23 04:40:21.663879: Current learning rate: 0.00072 +2024-11-23 04:40:40.610007: train_loss -0.8243 +2024-11-23 04:40:40.610254: val_loss -0.8096 +2024-11-23 04:40:40.610331: Pseudo dice [0.8749] +2024-11-23 04:40:40.610418: Epoch time: 18.95 s +2024-11-23 04:40:41.504915: +2024-11-23 04:40:41.505135: Epoch 7573 +2024-11-23 04:40:41.505258: Current learning rate: 0.00072 +2024-11-23 04:41:00.559652: train_loss -0.8383 +2024-11-23 04:41:00.559877: val_loss -0.7705 +2024-11-23 04:41:00.559961: Pseudo dice [0.8648] +2024-11-23 04:41:00.560053: Epoch time: 19.06 s +2024-11-23 04:41:01.451679: +2024-11-23 04:41:01.451903: Epoch 7574 +2024-11-23 04:41:01.452030: Current learning rate: 0.00071 +2024-11-23 04:41:18.279377: train_loss -0.8332 +2024-11-23 04:41:18.279586: val_loss -0.8038 +2024-11-23 04:41:18.279675: Pseudo dice [0.8715] +2024-11-23 04:41:18.279761: Epoch time: 16.83 s +2024-11-23 04:41:18.279825: Yayy! New best EMA pseudo Dice: 0.8634 +2024-11-23 04:41:19.913311: +2024-11-23 04:41:19.913577: Epoch 7575 +2024-11-23 04:41:19.913700: Current learning rate: 0.00071 +2024-11-23 04:41:38.830502: train_loss -0.8381 +2024-11-23 04:41:38.830787: val_loss -0.7809 +2024-11-23 04:41:38.830871: Pseudo dice [0.8641] +2024-11-23 04:41:38.830973: Epoch time: 18.92 s +2024-11-23 04:41:38.831036: Yayy! New best EMA pseudo Dice: 0.8634 +2024-11-23 04:41:40.126723: +2024-11-23 04:41:40.126943: Epoch 7576 +2024-11-23 04:41:40.127052: Current learning rate: 0.00071 +2024-11-23 04:41:58.370240: train_loss -0.8314 +2024-11-23 04:41:58.370706: val_loss -0.7837 +2024-11-23 04:41:58.370819: Pseudo dice [0.8673] +2024-11-23 04:41:58.370913: Epoch time: 18.24 s +2024-11-23 04:41:58.370984: Yayy! New best EMA pseudo Dice: 0.8638 +2024-11-23 04:41:59.597759: +2024-11-23 04:41:59.597964: Epoch 7577 +2024-11-23 04:41:59.598083: Current learning rate: 0.00071 +2024-11-23 04:42:17.202891: train_loss -0.8331 +2024-11-23 04:42:17.203127: val_loss -0.7944 +2024-11-23 04:42:17.203222: Pseudo dice [0.8582] +2024-11-23 04:42:17.203303: Epoch time: 17.61 s +2024-11-23 04:42:18.171748: +2024-11-23 04:42:18.171989: Epoch 7578 +2024-11-23 04:42:18.172120: Current learning rate: 0.00071 +2024-11-23 04:42:36.280457: train_loss -0.8316 +2024-11-23 04:42:36.280686: val_loss -0.7784 +2024-11-23 04:42:36.280767: Pseudo dice [0.8677] +2024-11-23 04:42:36.280851: Epoch time: 18.11 s +2024-11-23 04:42:37.185939: +2024-11-23 04:42:37.186177: Epoch 7579 +2024-11-23 04:42:37.186291: Current learning rate: 0.00071 +2024-11-23 04:42:55.986041: train_loss -0.8305 +2024-11-23 04:42:55.986282: val_loss -0.7932 +2024-11-23 04:42:55.986382: Pseudo dice [0.8599] +2024-11-23 04:42:55.986462: Epoch time: 18.8 s +2024-11-23 04:42:56.884568: +2024-11-23 04:42:56.884778: Epoch 7580 +2024-11-23 04:42:56.884891: Current learning rate: 0.0007 +2024-11-23 04:43:16.370455: train_loss -0.8301 +2024-11-23 04:43:16.370664: val_loss -0.7715 +2024-11-23 04:43:16.370759: Pseudo dice [0.8602] +2024-11-23 04:43:16.370834: Epoch time: 19.49 s +2024-11-23 04:43:17.494344: +2024-11-23 04:43:17.494570: Epoch 7581 +2024-11-23 04:43:17.494687: Current learning rate: 0.0007 +2024-11-23 04:43:35.881100: train_loss -0.8306 +2024-11-23 04:43:35.881318: val_loss -0.7685 +2024-11-23 04:43:35.881395: Pseudo dice [0.8518] +2024-11-23 04:43:35.881485: Epoch time: 18.39 s +2024-11-23 04:43:36.878253: +2024-11-23 04:43:36.878480: Epoch 7582 +2024-11-23 04:43:36.878621: Current learning rate: 0.0007 +2024-11-23 04:43:54.705432: train_loss -0.8304 +2024-11-23 04:43:54.705695: val_loss -0.8009 +2024-11-23 04:43:54.706609: Pseudo dice [0.861] +2024-11-23 04:43:54.706778: Epoch time: 17.83 s +2024-11-23 04:43:55.613729: +2024-11-23 04:43:55.613936: Epoch 7583 +2024-11-23 04:43:55.614052: Current learning rate: 0.0007 +2024-11-23 04:44:12.874759: train_loss -0.833 +2024-11-23 04:44:12.874982: val_loss -0.8005 +2024-11-23 04:44:12.875074: Pseudo dice [0.8521] +2024-11-23 04:44:12.875160: Epoch time: 17.26 s +2024-11-23 04:44:13.770711: +2024-11-23 04:44:13.770900: Epoch 7584 +2024-11-23 04:44:13.771014: Current learning rate: 0.0007 +2024-11-23 04:44:31.846726: train_loss -0.8346 +2024-11-23 04:44:31.846959: val_loss -0.7792 +2024-11-23 04:44:31.847037: Pseudo dice [0.8548] +2024-11-23 04:44:31.847136: Epoch time: 18.08 s +2024-11-23 04:44:32.738916: +2024-11-23 04:44:32.739140: Epoch 7585 +2024-11-23 04:44:32.739260: Current learning rate: 0.0007 +2024-11-23 04:44:50.874234: train_loss -0.8366 +2024-11-23 04:44:50.874478: val_loss -0.777 +2024-11-23 04:44:50.874579: Pseudo dice [0.8624] +2024-11-23 04:44:50.874675: Epoch time: 18.14 s +2024-11-23 04:44:52.199360: +2024-11-23 04:44:52.199574: Epoch 7586 +2024-11-23 04:44:52.199688: Current learning rate: 0.0007 +2024-11-23 04:45:11.006964: train_loss -0.8285 +2024-11-23 04:45:11.007230: val_loss -0.7842 +2024-11-23 04:45:11.007313: Pseudo dice [0.8655] +2024-11-23 04:45:11.007413: Epoch time: 18.81 s +2024-11-23 04:45:11.904361: +2024-11-23 04:45:11.904588: Epoch 7587 +2024-11-23 04:45:11.904722: Current learning rate: 0.00069 +2024-11-23 04:45:30.064636: train_loss -0.8308 +2024-11-23 04:45:30.067019: val_loss -0.778 +2024-11-23 04:45:30.067140: Pseudo dice [0.8656] +2024-11-23 04:45:30.067234: Epoch time: 18.16 s +2024-11-23 04:45:31.097597: +2024-11-23 04:45:31.097842: Epoch 7588 +2024-11-23 04:45:31.097980: Current learning rate: 0.00069 +2024-11-23 04:45:50.280956: train_loss -0.8331 +2024-11-23 04:45:50.281204: val_loss -0.7853 +2024-11-23 04:45:50.281373: Pseudo dice [0.8599] +2024-11-23 04:45:50.281477: Epoch time: 19.18 s +2024-11-23 04:45:51.186934: +2024-11-23 04:45:51.187165: Epoch 7589 +2024-11-23 04:45:51.187281: Current learning rate: 0.00069 +2024-11-23 04:46:09.142054: train_loss -0.8333 +2024-11-23 04:46:09.142299: val_loss -0.7545 +2024-11-23 04:46:09.142389: Pseudo dice [0.8606] +2024-11-23 04:46:09.142470: Epoch time: 17.96 s +2024-11-23 04:46:10.043898: +2024-11-23 04:46:10.044117: Epoch 7590 +2024-11-23 04:46:10.044228: Current learning rate: 0.00069 +2024-11-23 04:46:29.227565: train_loss -0.8255 +2024-11-23 04:46:29.227774: val_loss -0.7915 +2024-11-23 04:46:29.227853: Pseudo dice [0.8583] +2024-11-23 04:46:29.227939: Epoch time: 19.18 s +2024-11-23 04:46:30.126967: +2024-11-23 04:46:30.127177: Epoch 7591 +2024-11-23 04:46:30.127295: Current learning rate: 0.00069 +2024-11-23 04:46:48.318095: train_loss -0.8364 +2024-11-23 04:46:48.318315: val_loss -0.7655 +2024-11-23 04:46:48.318395: Pseudo dice [0.8551] +2024-11-23 04:46:48.318471: Epoch time: 18.19 s +2024-11-23 04:46:49.217273: +2024-11-23 04:46:49.217503: Epoch 7592 +2024-11-23 04:46:49.217629: Current learning rate: 0.00069 +2024-11-23 04:47:07.437101: train_loss -0.8302 +2024-11-23 04:47:07.437361: val_loss -0.7871 +2024-11-23 04:47:07.437451: Pseudo dice [0.8697] +2024-11-23 04:47:07.437533: Epoch time: 18.22 s +2024-11-23 04:47:08.334138: +2024-11-23 04:47:08.334351: Epoch 7593 +2024-11-23 04:47:08.334465: Current learning rate: 0.00069 +2024-11-23 04:47:27.177008: train_loss -0.8281 +2024-11-23 04:47:27.177239: val_loss -0.7866 +2024-11-23 04:47:27.177321: Pseudo dice [0.8542] +2024-11-23 04:47:27.177421: Epoch time: 18.84 s +2024-11-23 04:47:28.070018: +2024-11-23 04:47:28.070234: Epoch 7594 +2024-11-23 04:47:28.070405: Current learning rate: 0.00068 +2024-11-23 04:47:46.478087: train_loss -0.8204 +2024-11-23 04:47:46.478303: val_loss -0.7862 +2024-11-23 04:47:46.478384: Pseudo dice [0.8572] +2024-11-23 04:47:46.478488: Epoch time: 18.41 s +2024-11-23 04:47:47.366982: +2024-11-23 04:47:47.367204: Epoch 7595 +2024-11-23 04:47:47.367317: Current learning rate: 0.00068 +2024-11-23 04:48:05.014582: train_loss -0.8314 +2024-11-23 04:48:05.019971: val_loss -0.7719 +2024-11-23 04:48:05.020105: Pseudo dice [0.8591] +2024-11-23 04:48:05.020183: Epoch time: 17.65 s +2024-11-23 04:48:05.992146: +2024-11-23 04:48:05.992366: Epoch 7596 +2024-11-23 04:48:05.992487: Current learning rate: 0.00068 +2024-11-23 04:48:24.133323: train_loss -0.8383 +2024-11-23 04:48:24.133635: val_loss -0.7703 +2024-11-23 04:48:24.133720: Pseudo dice [0.8585] +2024-11-23 04:48:24.133804: Epoch time: 18.14 s +2024-11-23 04:48:25.510454: +2024-11-23 04:48:25.510676: Epoch 7597 +2024-11-23 04:48:25.510797: Current learning rate: 0.00068 +2024-11-23 04:48:44.560423: train_loss -0.8292 +2024-11-23 04:48:44.565860: val_loss -0.7821 +2024-11-23 04:48:44.565982: Pseudo dice [0.8461] +2024-11-23 04:48:44.566078: Epoch time: 19.05 s +2024-11-23 04:48:45.470770: +2024-11-23 04:48:45.470983: Epoch 7598 +2024-11-23 04:48:45.471099: Current learning rate: 0.00068 +2024-11-23 04:49:04.843797: train_loss -0.8309 +2024-11-23 04:49:04.844099: val_loss -0.7841 +2024-11-23 04:49:04.844185: Pseudo dice [0.8653] +2024-11-23 04:49:04.844264: Epoch time: 19.37 s +2024-11-23 04:49:05.743375: +2024-11-23 04:49:05.743576: Epoch 7599 +2024-11-23 04:49:05.743686: Current learning rate: 0.00068 +2024-11-23 04:49:24.072916: train_loss -0.8301 +2024-11-23 04:49:24.073157: val_loss -0.7895 +2024-11-23 04:49:24.073239: Pseudo dice [0.8492] +2024-11-23 04:49:24.073334: Epoch time: 18.33 s +2024-11-23 04:49:25.324491: +2024-11-23 04:49:25.324721: Epoch 7600 +2024-11-23 04:49:25.324841: Current learning rate: 0.00067 +2024-11-23 04:49:44.124892: train_loss -0.8317 +2024-11-23 04:49:44.125141: val_loss -0.7826 +2024-11-23 04:49:44.125221: Pseudo dice [0.86] +2024-11-23 04:49:44.125318: Epoch time: 18.8 s +2024-11-23 04:49:45.025028: +2024-11-23 04:49:45.025226: Epoch 7601 +2024-11-23 04:49:45.025348: Current learning rate: 0.00067 +2024-11-23 04:50:03.823694: train_loss -0.83 +2024-11-23 04:50:03.823966: val_loss -0.7809 +2024-11-23 04:50:03.824048: Pseudo dice [0.8617] +2024-11-23 04:50:03.824129: Epoch time: 18.8 s +2024-11-23 04:50:04.825549: +2024-11-23 04:50:04.825762: Epoch 7602 +2024-11-23 04:50:04.825871: Current learning rate: 0.00067 +2024-11-23 04:50:22.574353: train_loss -0.8321 +2024-11-23 04:50:22.574580: val_loss -0.7849 +2024-11-23 04:50:22.574680: Pseudo dice [0.8679] +2024-11-23 04:50:22.574769: Epoch time: 17.75 s +2024-11-23 04:50:23.469158: +2024-11-23 04:50:23.469379: Epoch 7603 +2024-11-23 04:50:23.469506: Current learning rate: 0.00067 +2024-11-23 04:50:41.979123: train_loss -0.8343 +2024-11-23 04:50:41.979369: val_loss -0.8033 +2024-11-23 04:50:41.979469: Pseudo dice [0.8714] +2024-11-23 04:50:41.979554: Epoch time: 18.51 s +2024-11-23 04:50:42.876011: +2024-11-23 04:50:42.876203: Epoch 7604 +2024-11-23 04:50:42.876324: Current learning rate: 0.00067 +2024-11-23 04:51:02.510587: train_loss -0.834 +2024-11-23 04:51:02.510803: val_loss -0.7826 +2024-11-23 04:51:02.510894: Pseudo dice [0.8604] +2024-11-23 04:51:02.510983: Epoch time: 19.64 s +2024-11-23 04:51:03.394048: +2024-11-23 04:51:03.394241: Epoch 7605 +2024-11-23 04:51:03.394350: Current learning rate: 0.00067 +2024-11-23 04:51:22.060588: train_loss -0.827 +2024-11-23 04:51:22.060804: val_loss -0.7828 +2024-11-23 04:51:22.060887: Pseudo dice [0.8502] +2024-11-23 04:51:22.060963: Epoch time: 18.67 s +2024-11-23 04:51:22.984888: +2024-11-23 04:51:22.985074: Epoch 7606 +2024-11-23 04:51:22.985186: Current learning rate: 0.00067 +2024-11-23 04:51:41.956070: train_loss -0.8307 +2024-11-23 04:51:41.956283: val_loss -0.7939 +2024-11-23 04:51:41.956365: Pseudo dice [0.8582] +2024-11-23 04:51:41.956447: Epoch time: 18.97 s +2024-11-23 04:51:42.851223: +2024-11-23 04:51:42.851452: Epoch 7607 +2024-11-23 04:51:42.851588: Current learning rate: 0.00066 +2024-11-23 04:52:00.977392: train_loss -0.8385 +2024-11-23 04:52:00.977636: val_loss -0.7917 +2024-11-23 04:52:00.977729: Pseudo dice [0.8653] +2024-11-23 04:52:00.977808: Epoch time: 18.13 s +2024-11-23 04:52:02.437116: +2024-11-23 04:52:02.437334: Epoch 7608 +2024-11-23 04:52:02.437456: Current learning rate: 0.00066 +2024-11-23 04:52:21.435555: train_loss -0.8396 +2024-11-23 04:52:21.435865: val_loss -0.7979 +2024-11-23 04:52:21.435955: Pseudo dice [0.852] +2024-11-23 04:52:21.436040: Epoch time: 19.0 s +2024-11-23 04:52:22.321676: +2024-11-23 04:52:22.321875: Epoch 7609 +2024-11-23 04:52:22.321991: Current learning rate: 0.00066 +2024-11-23 04:52:40.670811: train_loss -0.8255 +2024-11-23 04:52:40.671047: val_loss -0.7864 +2024-11-23 04:52:40.671143: Pseudo dice [0.8642] +2024-11-23 04:52:40.671222: Epoch time: 18.35 s +2024-11-23 04:52:41.563731: +2024-11-23 04:52:41.563919: Epoch 7610 +2024-11-23 04:52:41.564040: Current learning rate: 0.00066 +2024-11-23 04:53:00.214663: train_loss -0.8314 +2024-11-23 04:53:00.214885: val_loss -0.7774 +2024-11-23 04:53:00.214970: Pseudo dice [0.866] +2024-11-23 04:53:00.215054: Epoch time: 18.65 s +2024-11-23 04:53:01.105592: +2024-11-23 04:53:01.105807: Epoch 7611 +2024-11-23 04:53:01.105928: Current learning rate: 0.00066 +2024-11-23 04:53:20.261994: train_loss -0.8388 +2024-11-23 04:53:20.262236: val_loss -0.8054 +2024-11-23 04:53:20.262312: Pseudo dice [0.8666] +2024-11-23 04:53:20.262398: Epoch time: 19.16 s +2024-11-23 04:53:21.423345: +2024-11-23 04:53:21.423552: Epoch 7612 +2024-11-23 04:53:21.423674: Current learning rate: 0.00066 +2024-11-23 04:53:39.862348: train_loss -0.839 +2024-11-23 04:53:39.862575: val_loss -0.8069 +2024-11-23 04:53:39.862650: Pseudo dice [0.8738] +2024-11-23 04:53:39.862724: Epoch time: 18.44 s +2024-11-23 04:53:40.754434: +2024-11-23 04:53:40.754625: Epoch 7613 +2024-11-23 04:53:40.754736: Current learning rate: 0.00065 +2024-11-23 04:53:59.569324: train_loss -0.831 +2024-11-23 04:53:59.569535: val_loss -0.7825 +2024-11-23 04:53:59.569610: Pseudo dice [0.849] +2024-11-23 04:53:59.569690: Epoch time: 18.82 s +2024-11-23 04:54:00.639697: +2024-11-23 04:54:00.639929: Epoch 7614 +2024-11-23 04:54:00.640050: Current learning rate: 0.00065 +2024-11-23 04:54:18.772356: train_loss -0.8365 +2024-11-23 04:54:18.772594: val_loss -0.7875 +2024-11-23 04:54:18.772753: Pseudo dice [0.8656] +2024-11-23 04:54:18.772841: Epoch time: 18.13 s +2024-11-23 04:54:19.668820: +2024-11-23 04:54:19.669016: Epoch 7615 +2024-11-23 04:54:19.669129: Current learning rate: 0.00065 +2024-11-23 04:54:36.868837: train_loss -0.8309 +2024-11-23 04:54:36.869069: val_loss -0.751 +2024-11-23 04:54:36.869168: Pseudo dice [0.8426] +2024-11-23 04:54:36.869251: Epoch time: 17.2 s +2024-11-23 04:54:37.766078: +2024-11-23 04:54:37.766310: Epoch 7616 +2024-11-23 04:54:37.766425: Current learning rate: 0.00065 +2024-11-23 04:54:55.203245: train_loss -0.8275 +2024-11-23 04:54:55.203465: val_loss -0.7773 +2024-11-23 04:54:55.203544: Pseudo dice [0.8611] +2024-11-23 04:54:55.203620: Epoch time: 17.44 s +2024-11-23 04:54:56.099735: +2024-11-23 04:54:56.099927: Epoch 7617 +2024-11-23 04:54:56.100053: Current learning rate: 0.00065 +2024-11-23 04:55:14.666344: train_loss -0.833 +2024-11-23 04:55:14.666559: val_loss -0.7863 +2024-11-23 04:55:14.666652: Pseudo dice [0.8594] +2024-11-23 04:55:14.666726: Epoch time: 18.57 s +2024-11-23 04:55:15.556758: +2024-11-23 04:55:15.557007: Epoch 7618 +2024-11-23 04:55:15.557122: Current learning rate: 0.00065 +2024-11-23 04:55:33.591756: train_loss -0.8251 +2024-11-23 04:55:33.592056: val_loss -0.8064 +2024-11-23 04:55:33.592147: Pseudo dice [0.861] +2024-11-23 04:55:33.592227: Epoch time: 18.04 s +2024-11-23 04:55:34.920466: +2024-11-23 04:55:34.920685: Epoch 7619 +2024-11-23 04:55:34.920821: Current learning rate: 0.00065 +2024-11-23 04:55:53.950378: train_loss -0.8301 +2024-11-23 04:55:53.950634: val_loss -0.7887 +2024-11-23 04:55:53.950808: Pseudo dice [0.863] +2024-11-23 04:55:53.950912: Epoch time: 19.03 s +2024-11-23 04:55:54.942853: +2024-11-23 04:55:54.943079: Epoch 7620 +2024-11-23 04:55:54.943210: Current learning rate: 0.00064 +2024-11-23 04:56:13.242290: train_loss -0.8324 +2024-11-23 04:56:13.242503: val_loss -0.7936 +2024-11-23 04:56:13.244971: Pseudo dice [0.8645] +2024-11-23 04:56:13.245085: Epoch time: 18.3 s +2024-11-23 04:56:14.153902: +2024-11-23 04:56:14.154138: Epoch 7621 +2024-11-23 04:56:14.154253: Current learning rate: 0.00064 +2024-11-23 04:56:33.609540: train_loss -0.8329 +2024-11-23 04:56:33.614964: val_loss -0.7837 +2024-11-23 04:56:33.615096: Pseudo dice [0.8561] +2024-11-23 04:56:33.615184: Epoch time: 19.46 s +2024-11-23 04:56:34.550751: +2024-11-23 04:56:34.550976: Epoch 7622 +2024-11-23 04:56:34.551096: Current learning rate: 0.00064 +2024-11-23 04:56:52.764234: train_loss -0.8287 +2024-11-23 04:56:52.764544: val_loss -0.791 +2024-11-23 04:56:52.764627: Pseudo dice [0.8542] +2024-11-23 04:56:52.764721: Epoch time: 18.21 s +2024-11-23 04:56:53.735239: +2024-11-23 04:56:53.735461: Epoch 7623 +2024-11-23 04:56:53.735811: Current learning rate: 0.00064 +2024-11-23 04:57:11.725742: train_loss -0.8353 +2024-11-23 04:57:11.725971: val_loss -0.7705 +2024-11-23 04:57:11.726080: Pseudo dice [0.8539] +2024-11-23 04:57:11.726210: Epoch time: 17.99 s +2024-11-23 04:57:12.647113: +2024-11-23 04:57:12.647340: Epoch 7624 +2024-11-23 04:57:12.647455: Current learning rate: 0.00064 +2024-11-23 04:57:31.713760: train_loss -0.8334 +2024-11-23 04:57:31.713987: val_loss -0.765 +2024-11-23 04:57:31.714080: Pseudo dice [0.8619] +2024-11-23 04:57:31.714164: Epoch time: 19.07 s +2024-11-23 04:57:32.610529: +2024-11-23 04:57:32.610729: Epoch 7625 +2024-11-23 04:57:32.610838: Current learning rate: 0.00064 +2024-11-23 04:57:51.532792: train_loss -0.8376 +2024-11-23 04:57:51.533050: val_loss -0.7802 +2024-11-23 04:57:51.533134: Pseudo dice [0.8664] +2024-11-23 04:57:51.533218: Epoch time: 18.92 s +2024-11-23 04:57:52.455907: +2024-11-23 04:57:52.456107: Epoch 7626 +2024-11-23 04:57:52.456220: Current learning rate: 0.00064 +2024-11-23 04:58:12.270206: train_loss -0.828 +2024-11-23 04:58:12.270450: val_loss -0.7874 +2024-11-23 04:58:12.270545: Pseudo dice [0.8634] +2024-11-23 04:58:12.270622: Epoch time: 19.82 s +2024-11-23 04:58:13.189519: +2024-11-23 04:58:13.189757: Epoch 7627 +2024-11-23 04:58:13.189884: Current learning rate: 0.00063 +2024-11-23 04:58:31.983488: train_loss -0.8308 +2024-11-23 04:58:31.983735: val_loss -0.7862 +2024-11-23 04:58:31.983834: Pseudo dice [0.8637] +2024-11-23 04:58:31.983916: Epoch time: 18.79 s +2024-11-23 04:58:32.882793: +2024-11-23 04:58:32.883037: Epoch 7628 +2024-11-23 04:58:32.883160: Current learning rate: 0.00063 +2024-11-23 04:58:52.274477: train_loss -0.832 +2024-11-23 04:58:52.274726: val_loss -0.7859 +2024-11-23 04:58:52.274848: Pseudo dice [0.8615] +2024-11-23 04:58:52.274940: Epoch time: 19.39 s +2024-11-23 04:58:53.173948: +2024-11-23 04:58:53.174163: Epoch 7629 +2024-11-23 04:58:53.174275: Current learning rate: 0.00063 +2024-11-23 04:59:11.691574: train_loss -0.8226 +2024-11-23 04:59:11.691825: val_loss -0.7763 +2024-11-23 04:59:11.691906: Pseudo dice [0.8573] +2024-11-23 04:59:11.692009: Epoch time: 18.52 s +2024-11-23 04:59:13.009602: +2024-11-23 04:59:13.009825: Epoch 7630 +2024-11-23 04:59:13.009945: Current learning rate: 0.00063 +2024-11-23 04:59:31.341021: train_loss -0.8303 +2024-11-23 04:59:31.341251: val_loss -0.7967 +2024-11-23 04:59:31.343527: Pseudo dice [0.8657] +2024-11-23 04:59:31.343626: Epoch time: 18.33 s +2024-11-23 04:59:32.325511: +2024-11-23 04:59:32.325749: Epoch 7631 +2024-11-23 04:59:32.325869: Current learning rate: 0.00063 +2024-11-23 04:59:51.185994: train_loss -0.8388 +2024-11-23 04:59:51.186220: val_loss -0.7989 +2024-11-23 04:59:51.186303: Pseudo dice [0.871] +2024-11-23 04:59:51.191529: Epoch time: 18.86 s +2024-11-23 04:59:52.097335: +2024-11-23 04:59:52.097531: Epoch 7632 +2024-11-23 04:59:52.097645: Current learning rate: 0.00063 +2024-11-23 05:00:11.499303: train_loss -0.83 +2024-11-23 05:00:11.499570: val_loss -0.7955 +2024-11-23 05:00:11.499655: Pseudo dice [0.8625] +2024-11-23 05:00:11.499736: Epoch time: 19.4 s +2024-11-23 05:00:12.488663: +2024-11-23 05:00:12.488893: Epoch 7633 +2024-11-23 05:00:12.489051: Current learning rate: 0.00062 +2024-11-23 05:00:31.225015: train_loss -0.8326 +2024-11-23 05:00:31.225299: val_loss -0.7799 +2024-11-23 05:00:31.225390: Pseudo dice [0.8558] +2024-11-23 05:00:31.225479: Epoch time: 18.73 s +2024-11-23 05:00:32.260688: +2024-11-23 05:00:32.260937: Epoch 7634 +2024-11-23 05:00:32.261072: Current learning rate: 0.00062 +2024-11-23 05:00:49.741307: train_loss -0.8339 +2024-11-23 05:00:49.741518: val_loss -0.7695 +2024-11-23 05:00:49.741610: Pseudo dice [0.8726] +2024-11-23 05:00:49.741707: Epoch time: 17.48 s +2024-11-23 05:00:50.637440: +2024-11-23 05:00:50.637674: Epoch 7635 +2024-11-23 05:00:50.637784: Current learning rate: 0.00062 +2024-11-23 05:01:09.590808: train_loss -0.8347 +2024-11-23 05:01:09.591016: val_loss -0.7908 +2024-11-23 05:01:09.591107: Pseudo dice [0.8589] +2024-11-23 05:01:09.591196: Epoch time: 18.95 s +2024-11-23 05:01:10.487676: +2024-11-23 05:01:10.487919: Epoch 7636 +2024-11-23 05:01:10.488039: Current learning rate: 0.00062 +2024-11-23 05:01:29.389149: train_loss -0.8317 +2024-11-23 05:01:29.389373: val_loss -0.7626 +2024-11-23 05:01:29.389462: Pseudo dice [0.8468] +2024-11-23 05:01:29.389548: Epoch time: 18.9 s +2024-11-23 05:01:30.293040: +2024-11-23 05:01:30.293264: Epoch 7637 +2024-11-23 05:01:30.293378: Current learning rate: 0.00062 +2024-11-23 05:01:48.002507: train_loss -0.8318 +2024-11-23 05:01:48.002734: val_loss -0.7769 +2024-11-23 05:01:48.002829: Pseudo dice [0.8648] +2024-11-23 05:01:48.002906: Epoch time: 17.71 s +2024-11-23 05:01:49.073330: +2024-11-23 05:01:49.073582: Epoch 7638 +2024-11-23 05:01:49.073706: Current learning rate: 0.00062 +2024-11-23 05:02:07.863234: train_loss -0.8382 +2024-11-23 05:02:07.863459: val_loss -0.7833 +2024-11-23 05:02:07.863537: Pseudo dice [0.8483] +2024-11-23 05:02:07.863612: Epoch time: 18.79 s +2024-11-23 05:02:08.759953: +2024-11-23 05:02:08.760226: Epoch 7639 +2024-11-23 05:02:08.760356: Current learning rate: 0.00062 +2024-11-23 05:02:28.506062: train_loss -0.832 +2024-11-23 05:02:28.506286: val_loss -0.7798 +2024-11-23 05:02:28.506360: Pseudo dice [0.8438] +2024-11-23 05:02:28.506439: Epoch time: 19.75 s +2024-11-23 05:02:29.409567: +2024-11-23 05:02:29.409808: Epoch 7640 +2024-11-23 05:02:29.409920: Current learning rate: 0.00061 +2024-11-23 05:02:46.844995: train_loss -0.8357 +2024-11-23 05:02:46.851046: val_loss -0.7764 +2024-11-23 05:02:46.851183: Pseudo dice [0.8537] +2024-11-23 05:02:46.851288: Epoch time: 17.44 s +2024-11-23 05:02:48.141031: +2024-11-23 05:02:48.141267: Epoch 7641 +2024-11-23 05:02:48.141387: Current learning rate: 0.00061 +2024-11-23 05:03:05.679710: train_loss -0.8348 +2024-11-23 05:03:05.680001: val_loss -0.7695 +2024-11-23 05:03:05.680094: Pseudo dice [0.8609] +2024-11-23 05:03:05.680216: Epoch time: 17.54 s +2024-11-23 05:03:06.575746: +2024-11-23 05:03:06.575966: Epoch 7642 +2024-11-23 05:03:06.576087: Current learning rate: 0.00061 +2024-11-23 05:03:25.271086: train_loss -0.8356 +2024-11-23 05:03:25.271326: val_loss -0.7773 +2024-11-23 05:03:25.271407: Pseudo dice [0.8573] +2024-11-23 05:03:25.271505: Epoch time: 18.7 s +2024-11-23 05:03:26.171615: +2024-11-23 05:03:26.171835: Epoch 7643 +2024-11-23 05:03:26.171977: Current learning rate: 0.00061 +2024-11-23 05:03:44.082862: train_loss -0.8271 +2024-11-23 05:03:44.083114: val_loss -0.7898 +2024-11-23 05:03:44.083202: Pseudo dice [0.8709] +2024-11-23 05:03:44.083286: Epoch time: 17.91 s +2024-11-23 05:03:44.982471: +2024-11-23 05:03:44.982663: Epoch 7644 +2024-11-23 05:03:44.982791: Current learning rate: 0.00061 +2024-11-23 05:04:02.453889: train_loss -0.8361 +2024-11-23 05:04:02.454143: val_loss -0.7722 +2024-11-23 05:04:02.454226: Pseudo dice [0.865] +2024-11-23 05:04:02.454432: Epoch time: 17.47 s +2024-11-23 05:04:03.353743: +2024-11-23 05:04:03.353939: Epoch 7645 +2024-11-23 05:04:03.354055: Current learning rate: 0.00061 +2024-11-23 05:04:21.720378: train_loss -0.8334 +2024-11-23 05:04:21.723756: val_loss -0.7974 +2024-11-23 05:04:21.723917: Pseudo dice [0.8634] +2024-11-23 05:04:21.723999: Epoch time: 18.37 s +2024-11-23 05:04:22.667956: +2024-11-23 05:04:22.668164: Epoch 7646 +2024-11-23 05:04:22.668280: Current learning rate: 0.0006 +2024-11-23 05:04:39.787066: train_loss -0.8371 +2024-11-23 05:04:39.787341: val_loss -0.8019 +2024-11-23 05:04:39.787431: Pseudo dice [0.8662] +2024-11-23 05:04:39.787547: Epoch time: 17.12 s +2024-11-23 05:04:40.688416: +2024-11-23 05:04:40.688616: Epoch 7647 +2024-11-23 05:04:40.688730: Current learning rate: 0.0006 +2024-11-23 05:04:59.345064: train_loss -0.8332 +2024-11-23 05:04:59.345335: val_loss -0.7584 +2024-11-23 05:04:59.345417: Pseudo dice [0.8627] +2024-11-23 05:04:59.345551: Epoch time: 18.66 s +2024-11-23 05:05:00.350369: +2024-11-23 05:05:00.350586: Epoch 7648 +2024-11-23 05:05:00.350695: Current learning rate: 0.0006 +2024-11-23 05:05:18.743666: train_loss -0.8319 +2024-11-23 05:05:18.743896: val_loss -0.7807 +2024-11-23 05:05:18.744053: Pseudo dice [0.8555] +2024-11-23 05:05:18.744142: Epoch time: 18.39 s +2024-11-23 05:05:19.641726: +2024-11-23 05:05:19.641945: Epoch 7649 +2024-11-23 05:05:19.642272: Current learning rate: 0.0006 +2024-11-23 05:05:38.899462: train_loss -0.8372 +2024-11-23 05:05:38.899690: val_loss -0.7892 +2024-11-23 05:05:38.905270: Pseudo dice [0.8594] +2024-11-23 05:05:38.905420: Epoch time: 19.26 s +2024-11-23 05:05:40.142797: +2024-11-23 05:05:40.142991: Epoch 7650 +2024-11-23 05:05:40.143148: Current learning rate: 0.0006 +2024-11-23 05:05:59.306267: train_loss -0.8325 +2024-11-23 05:05:59.306520: val_loss -0.7747 +2024-11-23 05:05:59.306600: Pseudo dice [0.8577] +2024-11-23 05:05:59.306679: Epoch time: 19.16 s +2024-11-23 05:06:00.210446: +2024-11-23 05:06:00.210663: Epoch 7651 +2024-11-23 05:06:00.210775: Current learning rate: 0.0006 +2024-11-23 05:06:18.964521: train_loss -0.8388 +2024-11-23 05:06:18.964763: val_loss -0.7846 +2024-11-23 05:06:18.964860: Pseudo dice [0.8559] +2024-11-23 05:06:18.964956: Epoch time: 18.75 s +2024-11-23 05:06:20.338132: +2024-11-23 05:06:20.338346: Epoch 7652 +2024-11-23 05:06:20.338465: Current learning rate: 0.0006 +2024-11-23 05:06:38.771581: train_loss -0.8364 +2024-11-23 05:06:38.771837: val_loss -0.7862 +2024-11-23 05:06:38.771921: Pseudo dice [0.8542] +2024-11-23 05:06:38.772002: Epoch time: 18.43 s +2024-11-23 05:06:39.675123: +2024-11-23 05:06:39.675339: Epoch 7653 +2024-11-23 05:06:39.675456: Current learning rate: 0.00059 +2024-11-23 05:06:58.013335: train_loss -0.8294 +2024-11-23 05:06:58.013562: val_loss -0.7869 +2024-11-23 05:06:58.013649: Pseudo dice [0.8644] +2024-11-23 05:06:58.013740: Epoch time: 18.34 s +2024-11-23 05:06:58.909957: +2024-11-23 05:06:58.910178: Epoch 7654 +2024-11-23 05:06:58.910402: Current learning rate: 0.00059 +2024-11-23 05:07:17.978735: train_loss -0.8328 +2024-11-23 05:07:17.978979: val_loss -0.7919 +2024-11-23 05:07:17.979119: Pseudo dice [0.8632] +2024-11-23 05:07:17.979209: Epoch time: 19.07 s +2024-11-23 05:07:18.909508: +2024-11-23 05:07:18.909731: Epoch 7655 +2024-11-23 05:07:18.909881: Current learning rate: 0.00059 +2024-11-23 05:07:37.316111: train_loss -0.8374 +2024-11-23 05:07:37.316390: val_loss -0.7838 +2024-11-23 05:07:37.318169: Pseudo dice [0.865] +2024-11-23 05:07:37.318263: Epoch time: 18.41 s +2024-11-23 05:07:38.348973: +2024-11-23 05:07:38.349199: Epoch 7656 +2024-11-23 05:07:38.349323: Current learning rate: 0.00059 +2024-11-23 05:07:56.443829: train_loss -0.8404 +2024-11-23 05:07:56.444108: val_loss -0.7635 +2024-11-23 05:07:56.444198: Pseudo dice [0.8546] +2024-11-23 05:07:56.444292: Epoch time: 18.1 s +2024-11-23 05:07:57.352537: +2024-11-23 05:07:57.352756: Epoch 7657 +2024-11-23 05:07:57.352872: Current learning rate: 0.00059 +2024-11-23 05:08:15.926121: train_loss -0.8339 +2024-11-23 05:08:15.926345: val_loss -0.7554 +2024-11-23 05:08:15.926444: Pseudo dice [0.8645] +2024-11-23 05:08:15.926533: Epoch time: 18.57 s +2024-11-23 05:08:17.008631: +2024-11-23 05:08:17.008832: Epoch 7658 +2024-11-23 05:08:17.008969: Current learning rate: 0.00059 +2024-11-23 05:08:36.050436: train_loss -0.8286 +2024-11-23 05:08:36.050693: val_loss -0.7839 +2024-11-23 05:08:36.050790: Pseudo dice [0.8596] +2024-11-23 05:08:36.050901: Epoch time: 19.04 s +2024-11-23 05:08:36.954718: +2024-11-23 05:08:36.954915: Epoch 7659 +2024-11-23 05:08:36.955025: Current learning rate: 0.00058 +2024-11-23 05:08:56.515559: train_loss -0.8285 +2024-11-23 05:08:56.515890: val_loss -0.7887 +2024-11-23 05:08:56.515972: Pseudo dice [0.8479] +2024-11-23 05:08:56.516074: Epoch time: 19.56 s +2024-11-23 05:08:57.421177: +2024-11-23 05:08:57.421385: Epoch 7660 +2024-11-23 05:08:57.421508: Current learning rate: 0.00058 +2024-11-23 05:09:16.250028: train_loss -0.8284 +2024-11-23 05:09:16.250248: val_loss -0.7476 +2024-11-23 05:09:16.250328: Pseudo dice [0.854] +2024-11-23 05:09:16.250409: Epoch time: 18.83 s +2024-11-23 05:09:17.185783: +2024-11-23 05:09:17.185988: Epoch 7661 +2024-11-23 05:09:17.186103: Current learning rate: 0.00058 +2024-11-23 05:09:36.234910: train_loss -0.8296 +2024-11-23 05:09:36.235137: val_loss -0.7825 +2024-11-23 05:09:36.235219: Pseudo dice [0.8692] +2024-11-23 05:09:36.235294: Epoch time: 19.05 s +2024-11-23 05:09:37.179905: +2024-11-23 05:09:37.180106: Epoch 7662 +2024-11-23 05:09:37.180216: Current learning rate: 0.00058 +2024-11-23 05:09:55.851163: train_loss -0.8289 +2024-11-23 05:09:55.851481: val_loss -0.7803 +2024-11-23 05:09:55.851584: Pseudo dice [0.8657] +2024-11-23 05:09:55.851687: Epoch time: 18.67 s +2024-11-23 05:09:57.204460: +2024-11-23 05:09:57.204687: Epoch 7663 +2024-11-23 05:09:57.204804: Current learning rate: 0.00058 +2024-11-23 05:10:15.459802: train_loss -0.8296 +2024-11-23 05:10:15.460039: val_loss -0.7888 +2024-11-23 05:10:15.460133: Pseudo dice [0.8594] +2024-11-23 05:10:15.460254: Epoch time: 18.26 s +2024-11-23 05:10:16.357776: +2024-11-23 05:10:16.358014: Epoch 7664 +2024-11-23 05:10:16.358141: Current learning rate: 0.00058 +2024-11-23 05:10:36.035837: train_loss -0.8313 +2024-11-23 05:10:36.036094: val_loss -0.7601 +2024-11-23 05:10:36.036176: Pseudo dice [0.8511] +2024-11-23 05:10:36.036251: Epoch time: 19.68 s +2024-11-23 05:10:36.935857: +2024-11-23 05:10:36.936071: Epoch 7665 +2024-11-23 05:10:36.936183: Current learning rate: 0.00058 +2024-11-23 05:10:55.932309: train_loss -0.8325 +2024-11-23 05:10:55.932533: val_loss -0.7984 +2024-11-23 05:10:55.932612: Pseudo dice [0.8626] +2024-11-23 05:10:55.932706: Epoch time: 19.0 s +2024-11-23 05:10:56.835811: +2024-11-23 05:10:56.836002: Epoch 7666 +2024-11-23 05:10:56.836123: Current learning rate: 0.00057 +2024-11-23 05:11:16.165484: train_loss -0.8398 +2024-11-23 05:11:16.165733: val_loss -0.7862 +2024-11-23 05:11:16.165816: Pseudo dice [0.8689] +2024-11-23 05:11:16.165905: Epoch time: 19.33 s +2024-11-23 05:11:17.069888: +2024-11-23 05:11:17.070128: Epoch 7667 +2024-11-23 05:11:17.070268: Current learning rate: 0.00057 +2024-11-23 05:11:35.775795: train_loss -0.8335 +2024-11-23 05:11:35.776073: val_loss -0.775 +2024-11-23 05:11:35.776162: Pseudo dice [0.8537] +2024-11-23 05:11:35.776255: Epoch time: 18.71 s +2024-11-23 05:11:36.679834: +2024-11-23 05:11:36.680075: Epoch 7668 +2024-11-23 05:11:36.680210: Current learning rate: 0.00057 +2024-11-23 05:11:55.077843: train_loss -0.8267 +2024-11-23 05:11:55.078058: val_loss -0.7702 +2024-11-23 05:11:55.078142: Pseudo dice [0.8591] +2024-11-23 05:11:55.078217: Epoch time: 18.4 s +2024-11-23 05:11:55.976793: +2024-11-23 05:11:55.977129: Epoch 7669 +2024-11-23 05:11:55.977355: Current learning rate: 0.00057 +2024-11-23 05:12:15.068876: train_loss -0.8376 +2024-11-23 05:12:15.069135: val_loss -0.767 +2024-11-23 05:12:15.069227: Pseudo dice [0.8558] +2024-11-23 05:12:15.069374: Epoch time: 19.09 s +2024-11-23 05:12:16.021973: +2024-11-23 05:12:16.022207: Epoch 7670 +2024-11-23 05:12:16.022380: Current learning rate: 0.00057 +2024-11-23 05:12:34.726408: train_loss -0.8345 +2024-11-23 05:12:34.726643: val_loss -0.7959 +2024-11-23 05:12:34.726718: Pseudo dice [0.8707] +2024-11-23 05:12:34.726798: Epoch time: 18.71 s +2024-11-23 05:12:35.695112: +2024-11-23 05:12:35.695416: Epoch 7671 +2024-11-23 05:12:35.695548: Current learning rate: 0.00057 +2024-11-23 05:12:53.430064: train_loss -0.8367 +2024-11-23 05:12:53.430288: val_loss -0.7736 +2024-11-23 05:12:53.430378: Pseudo dice [0.8531] +2024-11-23 05:12:53.430455: Epoch time: 17.74 s +2024-11-23 05:12:54.330437: +2024-11-23 05:12:54.330631: Epoch 7672 +2024-11-23 05:12:54.330758: Current learning rate: 0.00056 +2024-11-23 05:13:12.619837: train_loss -0.8352 +2024-11-23 05:13:12.620039: val_loss -0.7919 +2024-11-23 05:13:12.620140: Pseudo dice [0.8653] +2024-11-23 05:13:12.620219: Epoch time: 18.29 s +2024-11-23 05:13:13.515226: +2024-11-23 05:13:13.515420: Epoch 7673 +2024-11-23 05:13:13.515543: Current learning rate: 0.00056 +2024-11-23 05:13:32.760769: train_loss -0.836 +2024-11-23 05:13:32.761005: val_loss -0.7915 +2024-11-23 05:13:32.761135: Pseudo dice [0.8525] +2024-11-23 05:13:32.761219: Epoch time: 19.25 s +2024-11-23 05:13:34.040157: +2024-11-23 05:13:34.040370: Epoch 7674 +2024-11-23 05:13:34.040487: Current learning rate: 0.00056 +2024-11-23 05:13:51.835343: train_loss -0.8335 +2024-11-23 05:13:51.835567: val_loss -0.7893 +2024-11-23 05:13:51.835649: Pseudo dice [0.852] +2024-11-23 05:13:51.835743: Epoch time: 17.8 s +2024-11-23 05:13:52.734361: +2024-11-23 05:13:52.734664: Epoch 7675 +2024-11-23 05:13:52.734788: Current learning rate: 0.00056 +2024-11-23 05:14:10.424545: train_loss -0.8355 +2024-11-23 05:14:10.424767: val_loss -0.7633 +2024-11-23 05:14:10.424843: Pseudo dice [0.8497] +2024-11-23 05:14:10.427120: Epoch time: 17.69 s +2024-11-23 05:14:11.417805: +2024-11-23 05:14:11.418010: Epoch 7676 +2024-11-23 05:14:11.418134: Current learning rate: 0.00056 +2024-11-23 05:14:30.149999: train_loss -0.8357 +2024-11-23 05:14:30.150263: val_loss -0.7706 +2024-11-23 05:14:30.150354: Pseudo dice [0.854] +2024-11-23 05:14:30.150436: Epoch time: 18.73 s +2024-11-23 05:14:31.069015: +2024-11-23 05:14:31.069253: Epoch 7677 +2024-11-23 05:14:31.069369: Current learning rate: 0.00056 +2024-11-23 05:14:49.904052: train_loss -0.8333 +2024-11-23 05:14:49.904294: val_loss -0.7948 +2024-11-23 05:14:49.904378: Pseudo dice [0.8595] +2024-11-23 05:14:49.904462: Epoch time: 18.84 s +2024-11-23 05:14:50.804605: +2024-11-23 05:14:50.804824: Epoch 7678 +2024-11-23 05:14:50.804945: Current learning rate: 0.00055 +2024-11-23 05:15:09.222403: train_loss -0.8378 +2024-11-23 05:15:09.222629: val_loss -0.7589 +2024-11-23 05:15:09.222709: Pseudo dice [0.8574] +2024-11-23 05:15:09.225034: Epoch time: 18.42 s +2024-11-23 05:15:10.143965: +2024-11-23 05:15:10.144239: Epoch 7679 +2024-11-23 05:15:10.144356: Current learning rate: 0.00055 +2024-11-23 05:15:28.665985: train_loss -0.8389 +2024-11-23 05:15:28.666220: val_loss -0.7777 +2024-11-23 05:15:28.666310: Pseudo dice [0.8783] +2024-11-23 05:15:28.666386: Epoch time: 18.52 s +2024-11-23 05:15:29.566089: +2024-11-23 05:15:29.566318: Epoch 7680 +2024-11-23 05:15:29.566435: Current learning rate: 0.00055 +2024-11-23 05:15:47.357656: train_loss -0.8394 +2024-11-23 05:15:47.357900: val_loss -0.7919 +2024-11-23 05:15:47.357982: Pseudo dice [0.8632] +2024-11-23 05:15:47.358072: Epoch time: 17.79 s +2024-11-23 05:15:48.262643: +2024-11-23 05:15:48.262851: Epoch 7681 +2024-11-23 05:15:48.262965: Current learning rate: 0.00055 +2024-11-23 05:16:07.393439: train_loss -0.8226 +2024-11-23 05:16:07.393652: val_loss -0.7855 +2024-11-23 05:16:07.393731: Pseudo dice [0.854] +2024-11-23 05:16:07.393812: Epoch time: 19.13 s +2024-11-23 05:16:08.296557: +2024-11-23 05:16:08.296747: Epoch 7682 +2024-11-23 05:16:08.296861: Current learning rate: 0.00055 +2024-11-23 05:16:26.456815: train_loss -0.8368 +2024-11-23 05:16:26.457044: val_loss -0.771 +2024-11-23 05:16:26.457150: Pseudo dice [0.8706] +2024-11-23 05:16:26.457240: Epoch time: 18.16 s +2024-11-23 05:16:27.492127: +2024-11-23 05:16:27.492331: Epoch 7683 +2024-11-23 05:16:27.492448: Current learning rate: 0.00055 +2024-11-23 05:16:45.596416: train_loss -0.8345 +2024-11-23 05:16:45.600118: val_loss -0.7605 +2024-11-23 05:16:45.600253: Pseudo dice [0.858] +2024-11-23 05:16:45.600347: Epoch time: 18.11 s +2024-11-23 05:16:46.504556: +2024-11-23 05:16:46.504766: Epoch 7684 +2024-11-23 05:16:46.504882: Current learning rate: 0.00055 +2024-11-23 05:17:06.196172: train_loss -0.8255 +2024-11-23 05:17:06.198752: val_loss -0.7765 +2024-11-23 05:17:06.198888: Pseudo dice [0.8544] +2024-11-23 05:17:06.199033: Epoch time: 19.69 s +2024-11-23 05:17:07.522622: +2024-11-23 05:17:07.522907: Epoch 7685 +2024-11-23 05:17:07.523085: Current learning rate: 0.00054 +2024-11-23 05:17:25.416279: train_loss -0.8295 +2024-11-23 05:17:25.416524: val_loss -0.7591 +2024-11-23 05:17:25.416619: Pseudo dice [0.8507] +2024-11-23 05:17:25.416696: Epoch time: 17.89 s +2024-11-23 05:17:26.311760: +2024-11-23 05:17:26.311979: Epoch 7686 +2024-11-23 05:17:26.312111: Current learning rate: 0.00054 +2024-11-23 05:17:45.074389: train_loss -0.8346 +2024-11-23 05:17:45.074620: val_loss -0.7511 +2024-11-23 05:17:45.074708: Pseudo dice [0.855] +2024-11-23 05:17:45.074802: Epoch time: 18.76 s +2024-11-23 05:17:45.979466: +2024-11-23 05:17:45.979800: Epoch 7687 +2024-11-23 05:17:45.980036: Current learning rate: 0.00054 +2024-11-23 05:18:04.706478: train_loss -0.8323 +2024-11-23 05:18:04.706692: val_loss -0.7903 +2024-11-23 05:18:04.706773: Pseudo dice [0.8641] +2024-11-23 05:18:04.706909: Epoch time: 18.73 s +2024-11-23 05:18:05.607879: +2024-11-23 05:18:05.608119: Epoch 7688 +2024-11-23 05:18:05.608278: Current learning rate: 0.00054 +2024-11-23 05:18:24.364966: train_loss -0.8296 +2024-11-23 05:18:24.370408: val_loss -0.7963 +2024-11-23 05:18:24.370538: Pseudo dice [0.8659] +2024-11-23 05:18:24.370638: Epoch time: 18.76 s +2024-11-23 05:18:25.287968: +2024-11-23 05:18:25.288197: Epoch 7689 +2024-11-23 05:18:25.288308: Current learning rate: 0.00054 +2024-11-23 05:18:44.108935: train_loss -0.8335 +2024-11-23 05:18:44.109153: val_loss -0.7577 +2024-11-23 05:18:44.109227: Pseudo dice [0.852] +2024-11-23 05:18:44.109301: Epoch time: 18.82 s +2024-11-23 05:18:45.011540: +2024-11-23 05:18:45.011754: Epoch 7690 +2024-11-23 05:18:45.011863: Current learning rate: 0.00054 +2024-11-23 05:19:03.935078: train_loss -0.8308 +2024-11-23 05:19:03.935343: val_loss -0.7757 +2024-11-23 05:19:03.935425: Pseudo dice [0.8606] +2024-11-23 05:19:03.935508: Epoch time: 18.92 s +2024-11-23 05:19:04.848954: +2024-11-23 05:19:04.849222: Epoch 7691 +2024-11-23 05:19:04.849348: Current learning rate: 0.00053 +2024-11-23 05:19:23.833287: train_loss -0.8329 +2024-11-23 05:19:23.833504: val_loss -0.7849 +2024-11-23 05:19:23.833590: Pseudo dice [0.8497] +2024-11-23 05:19:23.833699: Epoch time: 18.99 s +2024-11-23 05:19:24.735941: +2024-11-23 05:19:24.736198: Epoch 7692 +2024-11-23 05:19:24.736329: Current learning rate: 0.00053 +2024-11-23 05:19:42.427892: train_loss -0.8392 +2024-11-23 05:19:42.428154: val_loss -0.7688 +2024-11-23 05:19:42.428239: Pseudo dice [0.8669] +2024-11-23 05:19:42.428320: Epoch time: 17.69 s +2024-11-23 05:19:43.348121: +2024-11-23 05:19:43.348337: Epoch 7693 +2024-11-23 05:19:43.348452: Current learning rate: 0.00053 +2024-11-23 05:20:01.329193: train_loss -0.8323 +2024-11-23 05:20:01.329403: val_loss -0.7936 +2024-11-23 05:20:01.329491: Pseudo dice [0.8637] +2024-11-23 05:20:01.329568: Epoch time: 17.98 s +2024-11-23 05:20:02.229552: +2024-11-23 05:20:02.229790: Epoch 7694 +2024-11-23 05:20:02.229899: Current learning rate: 0.00053 +2024-11-23 05:20:20.757032: train_loss -0.8345 +2024-11-23 05:20:20.757250: val_loss -0.7723 +2024-11-23 05:20:20.757330: Pseudo dice [0.851] +2024-11-23 05:20:20.757414: Epoch time: 18.53 s +2024-11-23 05:20:21.656186: +2024-11-23 05:20:21.656428: Epoch 7695 +2024-11-23 05:20:21.656548: Current learning rate: 0.00053 +2024-11-23 05:20:40.656829: train_loss -0.8366 +2024-11-23 05:20:40.657083: val_loss -0.7568 +2024-11-23 05:20:40.657165: Pseudo dice [0.8618] +2024-11-23 05:20:40.657244: Epoch time: 19.0 s +2024-11-23 05:20:42.034933: +2024-11-23 05:20:42.035185: Epoch 7696 +2024-11-23 05:20:42.035316: Current learning rate: 0.00053 +2024-11-23 05:20:59.938865: train_loss -0.8329 +2024-11-23 05:20:59.939114: val_loss -0.7794 +2024-11-23 05:20:59.939220: Pseudo dice [0.8725] +2024-11-23 05:20:59.939319: Epoch time: 17.9 s +2024-11-23 05:21:00.837833: +2024-11-23 05:21:00.838176: Epoch 7697 +2024-11-23 05:21:00.838290: Current learning rate: 0.00053 +2024-11-23 05:21:19.490241: train_loss -0.832 +2024-11-23 05:21:19.490450: val_loss -0.7853 +2024-11-23 05:21:19.490587: Pseudo dice [0.867] +2024-11-23 05:21:19.490665: Epoch time: 18.65 s +2024-11-23 05:21:20.390711: +2024-11-23 05:21:20.390914: Epoch 7698 +2024-11-23 05:21:20.391048: Current learning rate: 0.00052 +2024-11-23 05:21:38.914481: train_loss -0.8384 +2024-11-23 05:21:38.914698: val_loss -0.803 +2024-11-23 05:21:38.914798: Pseudo dice [0.8585] +2024-11-23 05:21:38.914885: Epoch time: 18.52 s +2024-11-23 05:21:39.821270: +2024-11-23 05:21:39.821482: Epoch 7699 +2024-11-23 05:21:39.821593: Current learning rate: 0.00052 +2024-11-23 05:21:58.881127: train_loss -0.8292 +2024-11-23 05:21:58.881375: val_loss -0.7697 +2024-11-23 05:21:58.881453: Pseudo dice [0.8613] +2024-11-23 05:21:58.881536: Epoch time: 19.06 s +2024-11-23 05:22:00.150730: +2024-11-23 05:22:00.150941: Epoch 7700 +2024-11-23 05:22:00.151056: Current learning rate: 0.00052 +2024-11-23 05:22:18.343714: train_loss -0.8334 +2024-11-23 05:22:18.343929: val_loss -0.7951 +2024-11-23 05:22:18.344002: Pseudo dice [0.86] +2024-11-23 05:22:18.344085: Epoch time: 18.19 s +2024-11-23 05:22:19.243646: +2024-11-23 05:22:19.243858: Epoch 7701 +2024-11-23 05:22:19.243975: Current learning rate: 0.00052 +2024-11-23 05:22:38.121898: train_loss -0.8385 +2024-11-23 05:22:38.122132: val_loss -0.7784 +2024-11-23 05:22:38.122216: Pseudo dice [0.8584] +2024-11-23 05:22:38.122300: Epoch time: 18.88 s +2024-11-23 05:22:39.084141: +2024-11-23 05:22:39.084341: Epoch 7702 +2024-11-23 05:22:39.084456: Current learning rate: 0.00052 +2024-11-23 05:22:58.315540: train_loss -0.8292 +2024-11-23 05:22:58.315782: val_loss -0.7633 +2024-11-23 05:22:58.315865: Pseudo dice [0.8596] +2024-11-23 05:22:58.315951: Epoch time: 19.23 s +2024-11-23 05:22:59.217255: +2024-11-23 05:22:59.217472: Epoch 7703 +2024-11-23 05:22:59.217589: Current learning rate: 0.00052 +2024-11-23 05:23:17.054983: train_loss -0.8336 +2024-11-23 05:23:17.055243: val_loss -0.791 +2024-11-23 05:23:17.055396: Pseudo dice [0.8554] +2024-11-23 05:23:17.055482: Epoch time: 17.84 s +2024-11-23 05:23:18.047271: +2024-11-23 05:23:18.047470: Epoch 7704 +2024-11-23 05:23:18.047615: Current learning rate: 0.00051 +2024-11-23 05:23:36.535288: train_loss -0.8313 +2024-11-23 05:23:36.535560: val_loss -0.791 +2024-11-23 05:23:36.535652: Pseudo dice [0.869] +2024-11-23 05:23:36.535742: Epoch time: 18.49 s +2024-11-23 05:23:37.430965: +2024-11-23 05:23:37.431395: Epoch 7705 +2024-11-23 05:23:37.431515: Current learning rate: 0.00051 +2024-11-23 05:23:56.677765: train_loss -0.8424 +2024-11-23 05:23:56.682593: val_loss -0.7795 +2024-11-23 05:23:56.682695: Pseudo dice [0.8458] +2024-11-23 05:23:56.682784: Epoch time: 19.25 s +2024-11-23 05:23:57.582245: +2024-11-23 05:23:57.582463: Epoch 7706 +2024-11-23 05:23:57.582599: Current learning rate: 0.00051 +2024-11-23 05:24:16.066928: train_loss -0.8364 +2024-11-23 05:24:16.067196: val_loss -0.7621 +2024-11-23 05:24:16.067305: Pseudo dice [0.8608] +2024-11-23 05:24:16.067460: Epoch time: 18.49 s +2024-11-23 05:24:17.412739: +2024-11-23 05:24:17.412955: Epoch 7707 +2024-11-23 05:24:17.413072: Current learning rate: 0.00051 +2024-11-23 05:24:35.470862: train_loss -0.8353 +2024-11-23 05:24:35.471099: val_loss -0.794 +2024-11-23 05:24:35.471187: Pseudo dice [0.8527] +2024-11-23 05:24:35.471273: Epoch time: 18.06 s +2024-11-23 05:24:36.382259: +2024-11-23 05:24:36.382615: Epoch 7708 +2024-11-23 05:24:36.382730: Current learning rate: 0.00051 +2024-11-23 05:24:54.740404: train_loss -0.8313 +2024-11-23 05:24:54.740645: val_loss -0.7836 +2024-11-23 05:24:54.740739: Pseudo dice [0.8597] +2024-11-23 05:24:54.740824: Epoch time: 18.36 s +2024-11-23 05:24:56.012337: +2024-11-23 05:24:56.012576: Epoch 7709 +2024-11-23 05:24:56.012693: Current learning rate: 0.00051 +2024-11-23 05:25:13.435436: train_loss -0.838 +2024-11-23 05:25:13.435695: val_loss -0.7871 +2024-11-23 05:25:13.435797: Pseudo dice [0.8658] +2024-11-23 05:25:13.435880: Epoch time: 17.42 s +2024-11-23 05:25:14.332594: +2024-11-23 05:25:14.332980: Epoch 7710 +2024-11-23 05:25:14.333183: Current learning rate: 0.00051 +2024-11-23 05:25:32.143643: train_loss -0.8358 +2024-11-23 05:25:32.143912: val_loss -0.7708 +2024-11-23 05:25:32.143999: Pseudo dice [0.8687] +2024-11-23 05:25:32.144085: Epoch time: 17.81 s +2024-11-23 05:25:33.045556: +2024-11-23 05:25:33.045803: Epoch 7711 +2024-11-23 05:25:33.045912: Current learning rate: 0.0005 +2024-11-23 05:25:51.563664: train_loss -0.841 +2024-11-23 05:25:51.563890: val_loss -0.7896 +2024-11-23 05:25:51.563973: Pseudo dice [0.8646] +2024-11-23 05:25:51.564055: Epoch time: 18.52 s +2024-11-23 05:25:52.462923: +2024-11-23 05:25:52.463127: Epoch 7712 +2024-11-23 05:25:52.463241: Current learning rate: 0.0005 +2024-11-23 05:26:10.029886: train_loss -0.8401 +2024-11-23 05:26:10.030113: val_loss -0.7737 +2024-11-23 05:26:10.030203: Pseudo dice [0.8696] +2024-11-23 05:26:10.030282: Epoch time: 17.57 s +2024-11-23 05:26:11.002424: +2024-11-23 05:26:11.002616: Epoch 7713 +2024-11-23 05:26:11.002728: Current learning rate: 0.0005 +2024-11-23 05:26:29.310931: train_loss -0.832 +2024-11-23 05:26:29.313341: val_loss -0.7963 +2024-11-23 05:26:29.313468: Pseudo dice [0.867] +2024-11-23 05:26:29.313555: Epoch time: 18.31 s +2024-11-23 05:26:30.264912: +2024-11-23 05:26:30.265148: Epoch 7714 +2024-11-23 05:26:30.265270: Current learning rate: 0.0005 +2024-11-23 05:26:48.615877: train_loss -0.8327 +2024-11-23 05:26:48.616134: val_loss -0.7746 +2024-11-23 05:26:48.616236: Pseudo dice [0.8551] +2024-11-23 05:26:48.616319: Epoch time: 18.35 s +2024-11-23 05:26:49.522311: +2024-11-23 05:26:49.522504: Epoch 7715 +2024-11-23 05:26:49.522680: Current learning rate: 0.0005 +2024-11-23 05:27:07.913483: train_loss -0.8298 +2024-11-23 05:27:07.913692: val_loss -0.7886 +2024-11-23 05:27:07.913770: Pseudo dice [0.8575] +2024-11-23 05:27:07.913859: Epoch time: 18.39 s +2024-11-23 05:27:08.813248: +2024-11-23 05:27:08.813446: Epoch 7716 +2024-11-23 05:27:08.813556: Current learning rate: 0.0005 +2024-11-23 05:27:27.211715: train_loss -0.8337 +2024-11-23 05:27:27.211948: val_loss -0.7727 +2024-11-23 05:27:27.212035: Pseudo dice [0.844] +2024-11-23 05:27:27.212128: Epoch time: 18.4 s +2024-11-23 05:27:28.112664: +2024-11-23 05:27:28.112856: Epoch 7717 +2024-11-23 05:27:28.112980: Current learning rate: 0.00049 +2024-11-23 05:27:46.012063: train_loss -0.838 +2024-11-23 05:27:46.012303: val_loss -0.7968 +2024-11-23 05:27:46.012386: Pseudo dice [0.8778] +2024-11-23 05:27:46.012493: Epoch time: 17.9 s +2024-11-23 05:27:47.334952: +2024-11-23 05:27:47.335159: Epoch 7718 +2024-11-23 05:27:47.335270: Current learning rate: 0.00049 +2024-11-23 05:28:06.616135: train_loss -0.8273 +2024-11-23 05:28:06.616421: val_loss -0.7841 +2024-11-23 05:28:06.616514: Pseudo dice [0.862] +2024-11-23 05:28:06.616603: Epoch time: 19.28 s +2024-11-23 05:28:07.515031: +2024-11-23 05:28:07.515249: Epoch 7719 +2024-11-23 05:28:07.515379: Current learning rate: 0.00049 +2024-11-23 05:28:26.703011: train_loss -0.8411 +2024-11-23 05:28:26.703310: val_loss -0.7959 +2024-11-23 05:28:26.703398: Pseudo dice [0.8678] +2024-11-23 05:28:26.703485: Epoch time: 19.19 s +2024-11-23 05:28:27.607538: +2024-11-23 05:28:27.607744: Epoch 7720 +2024-11-23 05:28:27.607870: Current learning rate: 0.00049 +2024-11-23 05:28:46.135560: train_loss -0.8383 +2024-11-23 05:28:46.135785: val_loss -0.8005 +2024-11-23 05:28:46.135862: Pseudo dice [0.8681] +2024-11-23 05:28:46.135965: Epoch time: 18.53 s +2024-11-23 05:28:47.048462: +2024-11-23 05:28:47.048661: Epoch 7721 +2024-11-23 05:28:47.048775: Current learning rate: 0.00049 +2024-11-23 05:29:05.461393: train_loss -0.8397 +2024-11-23 05:29:05.461642: val_loss -0.7887 +2024-11-23 05:29:05.461724: Pseudo dice [0.8595] +2024-11-23 05:29:05.461809: Epoch time: 18.41 s +2024-11-23 05:29:06.368092: +2024-11-23 05:29:06.368313: Epoch 7722 +2024-11-23 05:29:06.368428: Current learning rate: 0.00049 +2024-11-23 05:29:24.599273: train_loss -0.8354 +2024-11-23 05:29:24.599534: val_loss -0.7826 +2024-11-23 05:29:24.599633: Pseudo dice [0.8532] +2024-11-23 05:29:24.599711: Epoch time: 18.23 s +2024-11-23 05:29:25.559443: +2024-11-23 05:29:25.559641: Epoch 7723 +2024-11-23 05:29:25.559757: Current learning rate: 0.00048 +2024-11-23 05:29:43.171642: train_loss -0.8358 +2024-11-23 05:29:43.171853: val_loss -0.7856 +2024-11-23 05:29:43.171940: Pseudo dice [0.8616] +2024-11-23 05:29:43.172016: Epoch time: 17.61 s +2024-11-23 05:29:44.065518: +2024-11-23 05:29:44.065724: Epoch 7724 +2024-11-23 05:29:44.065849: Current learning rate: 0.00048 +2024-11-23 05:30:01.341373: train_loss -0.8445 +2024-11-23 05:30:01.341630: val_loss -0.7997 +2024-11-23 05:30:01.341711: Pseudo dice [0.8639] +2024-11-23 05:30:01.341795: Epoch time: 17.28 s +2024-11-23 05:30:02.245152: +2024-11-23 05:30:02.245365: Epoch 7725 +2024-11-23 05:30:02.245475: Current learning rate: 0.00048 +2024-11-23 05:30:20.304513: train_loss -0.8407 +2024-11-23 05:30:20.304732: val_loss -0.7896 +2024-11-23 05:30:20.304812: Pseudo dice [0.8553] +2024-11-23 05:30:20.304890: Epoch time: 18.06 s +2024-11-23 05:30:21.214788: +2024-11-23 05:30:21.214990: Epoch 7726 +2024-11-23 05:30:21.215110: Current learning rate: 0.00048 +2024-11-23 05:30:39.238451: train_loss -0.83 +2024-11-23 05:30:39.238667: val_loss -0.7877 +2024-11-23 05:30:39.238764: Pseudo dice [0.8665] +2024-11-23 05:30:39.238872: Epoch time: 18.02 s +2024-11-23 05:30:40.135002: +2024-11-23 05:30:40.135220: Epoch 7727 +2024-11-23 05:30:40.135332: Current learning rate: 0.00048 +2024-11-23 05:30:58.681767: train_loss -0.8364 +2024-11-23 05:30:58.681989: val_loss -0.7871 +2024-11-23 05:30:58.682082: Pseudo dice [0.8661] +2024-11-23 05:30:58.682165: Epoch time: 18.55 s +2024-11-23 05:30:59.581223: +2024-11-23 05:30:59.581429: Epoch 7728 +2024-11-23 05:30:59.581548: Current learning rate: 0.00048 +2024-11-23 05:31:18.765547: train_loss -0.8304 +2024-11-23 05:31:18.765785: val_loss -0.7832 +2024-11-23 05:31:18.770961: Pseudo dice [0.8616] +2024-11-23 05:31:18.771121: Epoch time: 19.19 s +2024-11-23 05:31:20.339329: +2024-11-23 05:31:20.339555: Epoch 7729 +2024-11-23 05:31:20.339674: Current learning rate: 0.00048 +2024-11-23 05:31:39.006541: train_loss -0.8326 +2024-11-23 05:31:39.006785: val_loss -0.7932 +2024-11-23 05:31:39.006863: Pseudo dice [0.845] +2024-11-23 05:31:39.006941: Epoch time: 18.67 s +2024-11-23 05:31:39.912318: +2024-11-23 05:31:39.912559: Epoch 7730 +2024-11-23 05:31:39.912689: Current learning rate: 0.00047 +2024-11-23 05:31:58.034165: train_loss -0.8355 +2024-11-23 05:31:58.034399: val_loss -0.7808 +2024-11-23 05:31:58.034566: Pseudo dice [0.8559] +2024-11-23 05:31:58.034649: Epoch time: 18.12 s +2024-11-23 05:31:58.975500: +2024-11-23 05:31:58.975720: Epoch 7731 +2024-11-23 05:31:58.975841: Current learning rate: 0.00047 +2024-11-23 05:32:17.373075: train_loss -0.8377 +2024-11-23 05:32:17.373300: val_loss -0.7783 +2024-11-23 05:32:17.373379: Pseudo dice [0.8561] +2024-11-23 05:32:17.373666: Epoch time: 18.4 s +2024-11-23 05:32:18.276149: +2024-11-23 05:32:18.276399: Epoch 7732 +2024-11-23 05:32:18.276547: Current learning rate: 0.00047 +2024-11-23 05:32:36.802275: train_loss -0.8417 +2024-11-23 05:32:36.802529: val_loss -0.7757 +2024-11-23 05:32:36.802616: Pseudo dice [0.8572] +2024-11-23 05:32:36.802704: Epoch time: 18.53 s +2024-11-23 05:32:37.709765: +2024-11-23 05:32:37.709965: Epoch 7733 +2024-11-23 05:32:37.710116: Current learning rate: 0.00047 +2024-11-23 05:32:56.848230: train_loss -0.8394 +2024-11-23 05:32:56.848451: val_loss -0.7864 +2024-11-23 05:32:56.848581: Pseudo dice [0.852] +2024-11-23 05:32:56.848688: Epoch time: 19.14 s +2024-11-23 05:32:57.748238: +2024-11-23 05:32:57.748469: Epoch 7734 +2024-11-23 05:32:57.748584: Current learning rate: 0.00047 +2024-11-23 05:33:15.646317: train_loss -0.8415 +2024-11-23 05:33:15.646535: val_loss -0.7888 +2024-11-23 05:33:15.648824: Pseudo dice [0.8703] +2024-11-23 05:33:15.648937: Epoch time: 17.9 s +2024-11-23 05:33:16.610352: +2024-11-23 05:33:16.610562: Epoch 7735 +2024-11-23 05:33:16.610676: Current learning rate: 0.00047 +2024-11-23 05:33:34.996642: train_loss -0.8406 +2024-11-23 05:33:34.996888: val_loss -0.793 +2024-11-23 05:33:34.996970: Pseudo dice [0.8579] +2024-11-23 05:33:34.997078: Epoch time: 18.39 s +2024-11-23 05:33:35.938223: +2024-11-23 05:33:35.938426: Epoch 7736 +2024-11-23 05:33:35.938534: Current learning rate: 0.00046 +2024-11-23 05:33:54.649727: train_loss -0.8359 +2024-11-23 05:33:54.649967: val_loss -0.7729 +2024-11-23 05:33:54.650050: Pseudo dice [0.8605] +2024-11-23 05:33:54.650139: Epoch time: 18.71 s +2024-11-23 05:33:55.554851: +2024-11-23 05:33:55.555095: Epoch 7737 +2024-11-23 05:33:55.555217: Current learning rate: 0.00046 +2024-11-23 05:34:13.514510: train_loss -0.8371 +2024-11-23 05:34:13.514744: val_loss -0.7877 +2024-11-23 05:34:13.514821: Pseudo dice [0.8513] +2024-11-23 05:34:13.514896: Epoch time: 17.96 s +2024-11-23 05:34:14.415639: +2024-11-23 05:34:14.415848: Epoch 7738 +2024-11-23 05:34:14.415970: Current learning rate: 0.00046 +2024-11-23 05:34:33.032453: train_loss -0.842 +2024-11-23 05:34:33.034901: val_loss -0.7676 +2024-11-23 05:34:33.035017: Pseudo dice [0.8703] +2024-11-23 05:34:33.035114: Epoch time: 18.62 s +2024-11-23 05:34:34.140025: +2024-11-23 05:34:34.140255: Epoch 7739 +2024-11-23 05:34:34.140369: Current learning rate: 0.00046 +2024-11-23 05:34:52.519378: train_loss -0.8356 +2024-11-23 05:34:52.519626: val_loss -0.804 +2024-11-23 05:34:52.519722: Pseudo dice [0.8631] +2024-11-23 05:34:52.519813: Epoch time: 18.38 s +2024-11-23 05:34:53.823834: +2024-11-23 05:34:53.824047: Epoch 7740 +2024-11-23 05:34:53.824170: Current learning rate: 0.00046 +2024-11-23 05:35:12.076690: train_loss -0.8412 +2024-11-23 05:35:12.076944: val_loss -0.7905 +2024-11-23 05:35:12.077157: Pseudo dice [0.8533] +2024-11-23 05:35:12.077236: Epoch time: 18.25 s +2024-11-23 05:35:12.975084: +2024-11-23 05:35:12.975304: Epoch 7741 +2024-11-23 05:35:12.975435: Current learning rate: 0.00046 +2024-11-23 05:35:30.279279: train_loss -0.841 +2024-11-23 05:35:30.279520: val_loss -0.7978 +2024-11-23 05:35:30.279604: Pseudo dice [0.8694] +2024-11-23 05:35:30.286387: Epoch time: 17.3 s +2024-11-23 05:35:31.231473: +2024-11-23 05:35:31.231750: Epoch 7742 +2024-11-23 05:35:31.231961: Current learning rate: 0.00045 +2024-11-23 05:35:50.176220: train_loss -0.8317 +2024-11-23 05:35:50.176465: val_loss -0.7946 +2024-11-23 05:35:50.176564: Pseudo dice [0.874] +2024-11-23 05:35:50.176649: Epoch time: 18.95 s +2024-11-23 05:35:51.083597: +2024-11-23 05:35:51.083790: Epoch 7743 +2024-11-23 05:35:51.083900: Current learning rate: 0.00045 +2024-11-23 05:36:09.792370: train_loss -0.8379 +2024-11-23 05:36:09.792597: val_loss -0.7941 +2024-11-23 05:36:09.792674: Pseudo dice [0.8626] +2024-11-23 05:36:09.792790: Epoch time: 18.71 s +2024-11-23 05:36:10.696112: +2024-11-23 05:36:10.696310: Epoch 7744 +2024-11-23 05:36:10.696440: Current learning rate: 0.00045 +2024-11-23 05:36:31.720305: train_loss -0.8296 +2024-11-23 05:36:31.720608: val_loss -0.8053 +2024-11-23 05:36:31.720690: Pseudo dice [0.8698] +2024-11-23 05:36:31.720763: Epoch time: 21.02 s +2024-11-23 05:36:32.628868: +2024-11-23 05:36:32.629088: Epoch 7745 +2024-11-23 05:36:32.629208: Current learning rate: 0.00045 +2024-11-23 05:36:52.379225: train_loss -0.8345 +2024-11-23 05:36:52.379463: val_loss -0.7801 +2024-11-23 05:36:52.379544: Pseudo dice [0.8581] +2024-11-23 05:36:52.379631: Epoch time: 19.75 s +2024-11-23 05:36:53.284099: +2024-11-23 05:36:53.284305: Epoch 7746 +2024-11-23 05:36:53.284421: Current learning rate: 0.00045 +2024-11-23 05:37:11.212734: train_loss -0.8348 +2024-11-23 05:37:11.212970: val_loss -0.7792 +2024-11-23 05:37:11.213051: Pseudo dice [0.8479] +2024-11-23 05:37:11.213142: Epoch time: 17.93 s +2024-11-23 05:37:12.124359: +2024-11-23 05:37:12.124817: Epoch 7747 +2024-11-23 05:37:12.124995: Current learning rate: 0.00045 +2024-11-23 05:37:30.331036: train_loss -0.8265 +2024-11-23 05:37:30.331494: val_loss -0.7857 +2024-11-23 05:37:30.331588: Pseudo dice [0.8568] +2024-11-23 05:37:30.331687: Epoch time: 18.21 s +2024-11-23 05:37:31.234027: +2024-11-23 05:37:31.234227: Epoch 7748 +2024-11-23 05:37:31.234335: Current learning rate: 0.00045 +2024-11-23 05:37:49.846571: train_loss -0.8364 +2024-11-23 05:37:49.846797: val_loss -0.7731 +2024-11-23 05:37:49.846880: Pseudo dice [0.8549] +2024-11-23 05:37:49.847314: Epoch time: 18.61 s +2024-11-23 05:37:50.747475: +2024-11-23 05:37:50.747686: Epoch 7749 +2024-11-23 05:37:50.747800: Current learning rate: 0.00044 +2024-11-23 05:38:08.123490: train_loss -0.8379 +2024-11-23 05:38:08.129253: val_loss -0.788 +2024-11-23 05:38:08.129351: Pseudo dice [0.8654] +2024-11-23 05:38:08.129440: Epoch time: 17.38 s +2024-11-23 05:38:09.455858: +2024-11-23 05:38:09.456071: Epoch 7750 +2024-11-23 05:38:09.456180: Current learning rate: 0.00044 +2024-11-23 05:38:28.729686: train_loss -0.8354 +2024-11-23 05:38:28.729924: val_loss -0.7801 +2024-11-23 05:38:28.730003: Pseudo dice [0.856] +2024-11-23 05:38:28.735994: Epoch time: 19.27 s +2024-11-23 05:38:29.791836: +2024-11-23 05:38:29.792068: Epoch 7751 +2024-11-23 05:38:29.792196: Current learning rate: 0.00044 +2024-11-23 05:38:48.722417: train_loss -0.835 +2024-11-23 05:38:48.722642: val_loss -0.7736 +2024-11-23 05:38:48.722721: Pseudo dice [0.866] +2024-11-23 05:38:48.727963: Epoch time: 18.93 s +2024-11-23 05:38:49.743802: +2024-11-23 05:38:49.744041: Epoch 7752 +2024-11-23 05:38:49.744158: Current learning rate: 0.00044 +2024-11-23 05:39:08.401796: train_loss -0.836 +2024-11-23 05:39:08.402033: val_loss -0.7947 +2024-11-23 05:39:08.402162: Pseudo dice [0.8609] +2024-11-23 05:39:08.402322: Epoch time: 18.66 s +2024-11-23 05:39:09.302578: +2024-11-23 05:39:09.302792: Epoch 7753 +2024-11-23 05:39:09.302913: Current learning rate: 0.00044 +2024-11-23 05:39:28.458300: train_loss -0.8371 +2024-11-23 05:39:28.458528: val_loss -0.7581 +2024-11-23 05:39:28.458612: Pseudo dice [0.8454] +2024-11-23 05:39:28.458696: Epoch time: 19.16 s +2024-11-23 05:39:29.365925: +2024-11-23 05:39:29.366128: Epoch 7754 +2024-11-23 05:39:29.366242: Current learning rate: 0.00044 +2024-11-23 05:39:47.138346: train_loss -0.839 +2024-11-23 05:39:47.145477: val_loss -0.7881 +2024-11-23 05:39:47.145584: Pseudo dice [0.8601] +2024-11-23 05:39:47.145671: Epoch time: 17.77 s +2024-11-23 05:39:48.241978: +2024-11-23 05:39:48.242201: Epoch 7755 +2024-11-23 05:39:48.242316: Current learning rate: 0.00043 +2024-11-23 05:40:06.225378: train_loss -0.8381 +2024-11-23 05:40:06.225614: val_loss -0.7725 +2024-11-23 05:40:06.225707: Pseudo dice [0.8557] +2024-11-23 05:40:06.225795: Epoch time: 17.98 s +2024-11-23 05:40:07.125298: +2024-11-23 05:40:07.125511: Epoch 7756 +2024-11-23 05:40:07.125629: Current learning rate: 0.00043 +2024-11-23 05:40:25.587753: train_loss -0.8417 +2024-11-23 05:40:25.587972: val_loss -0.7846 +2024-11-23 05:40:25.588049: Pseudo dice [0.8523] +2024-11-23 05:40:25.588146: Epoch time: 18.46 s +2024-11-23 05:40:26.549176: +2024-11-23 05:40:26.549388: Epoch 7757 +2024-11-23 05:40:26.549505: Current learning rate: 0.00043 +2024-11-23 05:40:44.471738: train_loss -0.8368 +2024-11-23 05:40:44.472015: val_loss -0.798 +2024-11-23 05:40:44.472120: Pseudo dice [0.8693] +2024-11-23 05:40:44.472222: Epoch time: 17.92 s +2024-11-23 05:40:45.405456: +2024-11-23 05:40:45.405656: Epoch 7758 +2024-11-23 05:40:45.405796: Current learning rate: 0.00043 +2024-11-23 05:41:03.745833: train_loss -0.841 +2024-11-23 05:41:03.746052: val_loss -0.7858 +2024-11-23 05:41:03.746136: Pseudo dice [0.854] +2024-11-23 05:41:03.746219: Epoch time: 18.34 s +2024-11-23 05:41:04.646339: +2024-11-23 05:41:04.646586: Epoch 7759 +2024-11-23 05:41:04.646701: Current learning rate: 0.00043 +2024-11-23 05:41:23.033147: train_loss -0.8362 +2024-11-23 05:41:23.033382: val_loss -0.7835 +2024-11-23 05:41:23.033473: Pseudo dice [0.8654] +2024-11-23 05:41:23.033557: Epoch time: 18.39 s +2024-11-23 05:41:23.938316: +2024-11-23 05:41:23.938547: Epoch 7760 +2024-11-23 05:41:23.938688: Current learning rate: 0.00043 +2024-11-23 05:41:42.036830: train_loss -0.8405 +2024-11-23 05:41:42.037099: val_loss -0.7758 +2024-11-23 05:41:42.037191: Pseudo dice [0.8615] +2024-11-23 05:41:42.037275: Epoch time: 18.1 s +2024-11-23 05:41:43.325493: +2024-11-23 05:41:43.325681: Epoch 7761 +2024-11-23 05:41:43.325821: Current learning rate: 0.00042 +2024-11-23 05:42:01.914786: train_loss -0.8396 +2024-11-23 05:42:01.915121: val_loss -0.7746 +2024-11-23 05:42:01.915203: Pseudo dice [0.862] +2024-11-23 05:42:01.915286: Epoch time: 18.59 s +2024-11-23 05:42:02.823124: +2024-11-23 05:42:02.823335: Epoch 7762 +2024-11-23 05:42:02.823452: Current learning rate: 0.00042 +2024-11-23 05:42:20.608299: train_loss -0.8342 +2024-11-23 05:42:20.608526: val_loss -0.7785 +2024-11-23 05:42:20.608606: Pseudo dice [0.8641] +2024-11-23 05:42:20.608679: Epoch time: 17.79 s +2024-11-23 05:42:21.490843: +2024-11-23 05:42:21.491054: Epoch 7763 +2024-11-23 05:42:21.491178: Current learning rate: 0.00042 +2024-11-23 05:42:40.345795: train_loss -0.8383 +2024-11-23 05:42:40.346011: val_loss -0.7721 +2024-11-23 05:42:40.346096: Pseudo dice [0.8681] +2024-11-23 05:42:40.346186: Epoch time: 18.86 s +2024-11-23 05:42:41.248643: +2024-11-23 05:42:41.248884: Epoch 7764 +2024-11-23 05:42:41.249017: Current learning rate: 0.00042 +2024-11-23 05:42:58.728767: train_loss -0.8437 +2024-11-23 05:42:58.729008: val_loss -0.7895 +2024-11-23 05:42:58.729104: Pseudo dice [0.863] +2024-11-23 05:42:58.729189: Epoch time: 17.48 s +2024-11-23 05:42:59.642734: +2024-11-23 05:42:59.642953: Epoch 7765 +2024-11-23 05:42:59.643066: Current learning rate: 0.00042 +2024-11-23 05:43:17.219328: train_loss -0.8323 +2024-11-23 05:43:17.219573: val_loss -0.7894 +2024-11-23 05:43:17.219651: Pseudo dice [0.8573] +2024-11-23 05:43:17.219732: Epoch time: 17.58 s +2024-11-23 05:43:18.130520: +2024-11-23 05:43:18.130718: Epoch 7766 +2024-11-23 05:43:18.130834: Current learning rate: 0.00042 +2024-11-23 05:43:36.298045: train_loss -0.8312 +2024-11-23 05:43:36.298282: val_loss -0.7974 +2024-11-23 05:43:36.298366: Pseudo dice [0.872] +2024-11-23 05:43:36.298446: Epoch time: 18.17 s +2024-11-23 05:43:37.209702: +2024-11-23 05:43:37.209894: Epoch 7767 +2024-11-23 05:43:37.210013: Current learning rate: 0.00041 +2024-11-23 05:43:56.607036: train_loss -0.8426 +2024-11-23 05:43:56.607254: val_loss -0.7719 +2024-11-23 05:43:56.607333: Pseudo dice [0.8507] +2024-11-23 05:43:56.607448: Epoch time: 19.4 s +2024-11-23 05:43:57.517161: +2024-11-23 05:43:57.517360: Epoch 7768 +2024-11-23 05:43:57.517470: Current learning rate: 0.00041 +2024-11-23 05:44:17.277118: train_loss -0.8387 +2024-11-23 05:44:17.277331: val_loss -0.7757 +2024-11-23 05:44:17.277409: Pseudo dice [0.8621] +2024-11-23 05:44:17.277492: Epoch time: 19.76 s +2024-11-23 05:44:18.177750: +2024-11-23 05:44:18.177962: Epoch 7769 +2024-11-23 05:44:18.178091: Current learning rate: 0.00041 +2024-11-23 05:44:37.042670: train_loss -0.8431 +2024-11-23 05:44:37.042914: val_loss -0.7743 +2024-11-23 05:44:37.042993: Pseudo dice [0.8625] +2024-11-23 05:44:37.043083: Epoch time: 18.87 s +2024-11-23 05:44:38.017518: +2024-11-23 05:44:38.017729: Epoch 7770 +2024-11-23 05:44:38.017863: Current learning rate: 0.00041 +2024-11-23 05:44:56.471365: train_loss -0.8314 +2024-11-23 05:44:56.471576: val_loss -0.7686 +2024-11-23 05:44:56.471658: Pseudo dice [0.854] +2024-11-23 05:44:56.471733: Epoch time: 18.45 s +2024-11-23 05:44:57.370601: +2024-11-23 05:44:57.370792: Epoch 7771 +2024-11-23 05:44:57.370914: Current learning rate: 0.00041 +2024-11-23 05:45:15.676671: train_loss -0.8389 +2024-11-23 05:45:15.676895: val_loss -0.7849 +2024-11-23 05:45:15.677018: Pseudo dice [0.8715] +2024-11-23 05:45:15.677117: Epoch time: 18.31 s +2024-11-23 05:45:16.980435: +2024-11-23 05:45:16.980636: Epoch 7772 +2024-11-23 05:45:16.980763: Current learning rate: 0.00041 +2024-11-23 05:45:35.738106: train_loss -0.8357 +2024-11-23 05:45:35.738365: val_loss -0.7919 +2024-11-23 05:45:35.738449: Pseudo dice [0.8502] +2024-11-23 05:45:35.738551: Epoch time: 18.76 s +2024-11-23 05:45:36.690447: +2024-11-23 05:45:36.690655: Epoch 7773 +2024-11-23 05:45:36.690763: Current learning rate: 0.00041 +2024-11-23 05:45:55.127142: train_loss -0.8392 +2024-11-23 05:45:55.127348: val_loss -0.7847 +2024-11-23 05:45:55.127430: Pseudo dice [0.8631] +2024-11-23 05:45:55.127509: Epoch time: 18.44 s +2024-11-23 05:45:56.143011: +2024-11-23 05:45:56.143231: Epoch 7774 +2024-11-23 05:45:56.143341: Current learning rate: 0.0004 +2024-11-23 05:46:15.008252: train_loss -0.8311 +2024-11-23 05:46:15.008453: val_loss -0.7854 +2024-11-23 05:46:15.008528: Pseudo dice [0.8618] +2024-11-23 05:46:15.008603: Epoch time: 18.87 s +2024-11-23 05:46:15.906096: +2024-11-23 05:46:15.906309: Epoch 7775 +2024-11-23 05:46:15.906432: Current learning rate: 0.0004 +2024-11-23 05:46:34.715902: train_loss -0.8363 +2024-11-23 05:46:34.716133: val_loss -0.7957 +2024-11-23 05:46:34.716215: Pseudo dice [0.8668] +2024-11-23 05:46:34.716352: Epoch time: 18.81 s +2024-11-23 05:46:35.625452: +2024-11-23 05:46:35.625671: Epoch 7776 +2024-11-23 05:46:35.625793: Current learning rate: 0.0004 +2024-11-23 05:46:53.697853: train_loss -0.8398 +2024-11-23 05:46:53.698155: val_loss -0.795 +2024-11-23 05:46:53.698241: Pseudo dice [0.8693] +2024-11-23 05:46:53.698326: Epoch time: 18.07 s +2024-11-23 05:46:54.636290: +2024-11-23 05:46:54.636504: Epoch 7777 +2024-11-23 05:46:54.636614: Current learning rate: 0.0004 +2024-11-23 05:47:13.003268: train_loss -0.838 +2024-11-23 05:47:13.003469: val_loss -0.7743 +2024-11-23 05:47:13.003551: Pseudo dice [0.8597] +2024-11-23 05:47:13.003631: Epoch time: 18.37 s +2024-11-23 05:47:13.905813: +2024-11-23 05:47:13.906018: Epoch 7778 +2024-11-23 05:47:13.906145: Current learning rate: 0.0004 +2024-11-23 05:47:31.338377: train_loss -0.8386 +2024-11-23 05:47:31.338602: val_loss -0.8171 +2024-11-23 05:47:31.338679: Pseudo dice [0.8692] +2024-11-23 05:47:31.339201: Epoch time: 17.43 s +2024-11-23 05:47:32.369513: +2024-11-23 05:47:32.369728: Epoch 7779 +2024-11-23 05:47:32.369859: Current learning rate: 0.0004 +2024-11-23 05:47:51.809270: train_loss -0.8356 +2024-11-23 05:47:51.809496: val_loss -0.7533 +2024-11-23 05:47:51.809593: Pseudo dice [0.8556] +2024-11-23 05:47:51.809729: Epoch time: 19.44 s +2024-11-23 05:47:52.710812: +2024-11-23 05:47:52.711040: Epoch 7780 +2024-11-23 05:47:52.711164: Current learning rate: 0.00039 +2024-11-23 05:48:12.527267: train_loss -0.8247 +2024-11-23 05:48:12.527504: val_loss -0.7996 +2024-11-23 05:48:12.527591: Pseudo dice [0.8617] +2024-11-23 05:48:12.527691: Epoch time: 19.82 s +2024-11-23 05:48:13.431190: +2024-11-23 05:48:13.431396: Epoch 7781 +2024-11-23 05:48:13.431512: Current learning rate: 0.00039 +2024-11-23 05:48:32.547186: train_loss -0.8418 +2024-11-23 05:48:32.547403: val_loss -0.7548 +2024-11-23 05:48:32.547482: Pseudo dice [0.8549] +2024-11-23 05:48:32.547557: Epoch time: 19.12 s +2024-11-23 05:48:33.460732: +2024-11-23 05:48:33.460940: Epoch 7782 +2024-11-23 05:48:33.461086: Current learning rate: 0.00039 +2024-11-23 05:48:51.426653: train_loss -0.8398 +2024-11-23 05:48:51.426867: val_loss -0.7989 +2024-11-23 05:48:51.426949: Pseudo dice [0.8584] +2024-11-23 05:48:51.427038: Epoch time: 17.97 s +2024-11-23 05:48:52.734212: +2024-11-23 05:48:52.734417: Epoch 7783 +2024-11-23 05:48:52.734537: Current learning rate: 0.00039 +2024-11-23 05:49:10.552475: train_loss -0.8337 +2024-11-23 05:49:10.552729: val_loss -0.7851 +2024-11-23 05:49:10.552813: Pseudo dice [0.8637] +2024-11-23 05:49:10.552907: Epoch time: 17.82 s +2024-11-23 05:49:11.454234: +2024-11-23 05:49:11.454451: Epoch 7784 +2024-11-23 05:49:11.454572: Current learning rate: 0.00039 +2024-11-23 05:49:29.055875: train_loss -0.8347 +2024-11-23 05:49:29.056082: val_loss -0.797 +2024-11-23 05:49:29.056168: Pseudo dice [0.8599] +2024-11-23 05:49:29.056348: Epoch time: 17.6 s +2024-11-23 05:49:29.964941: +2024-11-23 05:49:29.965163: Epoch 7785 +2024-11-23 05:49:29.965281: Current learning rate: 0.00039 +2024-11-23 05:49:47.715591: train_loss -0.8406 +2024-11-23 05:49:47.715789: val_loss -0.7674 +2024-11-23 05:49:47.715870: Pseudo dice [0.8565] +2024-11-23 05:49:47.715945: Epoch time: 17.75 s +2024-11-23 05:49:48.612097: +2024-11-23 05:49:48.612302: Epoch 7786 +2024-11-23 05:49:48.612416: Current learning rate: 0.00038 +2024-11-23 05:50:08.161475: train_loss -0.8413 +2024-11-23 05:50:08.161692: val_loss -0.7805 +2024-11-23 05:50:08.161795: Pseudo dice [0.8588] +2024-11-23 05:50:08.161876: Epoch time: 19.55 s +2024-11-23 05:50:09.070692: +2024-11-23 05:50:09.070908: Epoch 7787 +2024-11-23 05:50:09.071020: Current learning rate: 0.00038 +2024-11-23 05:50:27.966706: train_loss -0.8364 +2024-11-23 05:50:27.967033: val_loss -0.7748 +2024-11-23 05:50:27.967132: Pseudo dice [0.8673] +2024-11-23 05:50:27.967226: Epoch time: 18.9 s +2024-11-23 05:50:28.884807: +2024-11-23 05:50:28.885021: Epoch 7788 +2024-11-23 05:50:28.885136: Current learning rate: 0.00038 +2024-11-23 05:50:48.062529: train_loss -0.8317 +2024-11-23 05:50:48.062819: val_loss -0.7881 +2024-11-23 05:50:48.064120: Pseudo dice [0.863] +2024-11-23 05:50:48.064213: Epoch time: 19.18 s +2024-11-23 05:50:48.973637: +2024-11-23 05:50:48.973858: Epoch 7789 +2024-11-23 05:50:48.973973: Current learning rate: 0.00038 +2024-11-23 05:51:06.250138: train_loss -0.8406 +2024-11-23 05:51:06.250351: val_loss -0.7758 +2024-11-23 05:51:06.250429: Pseudo dice [0.8641] +2024-11-23 05:51:06.250509: Epoch time: 17.28 s +2024-11-23 05:51:07.150037: +2024-11-23 05:51:07.150254: Epoch 7790 +2024-11-23 05:51:07.150373: Current learning rate: 0.00038 +2024-11-23 05:51:25.852212: train_loss -0.835 +2024-11-23 05:51:25.852511: val_loss -0.791 +2024-11-23 05:51:25.852606: Pseudo dice [0.8673] +2024-11-23 05:51:25.852704: Epoch time: 18.7 s +2024-11-23 05:51:26.761646: +2024-11-23 05:51:26.761863: Epoch 7791 +2024-11-23 05:51:26.761976: Current learning rate: 0.00038 +2024-11-23 05:51:45.743393: train_loss -0.8415 +2024-11-23 05:51:45.743596: val_loss -0.7722 +2024-11-23 05:51:45.743672: Pseudo dice [0.8627] +2024-11-23 05:51:45.743775: Epoch time: 18.98 s +2024-11-23 05:51:46.649735: +2024-11-23 05:51:46.649953: Epoch 7792 +2024-11-23 05:51:46.650072: Current learning rate: 0.00037 +2024-11-23 05:52:05.614377: train_loss -0.8386 +2024-11-23 05:52:05.614624: val_loss -0.7996 +2024-11-23 05:52:05.614697: Pseudo dice [0.873] +2024-11-23 05:52:05.614771: Epoch time: 18.97 s +2024-11-23 05:52:06.562725: +2024-11-23 05:52:06.562920: Epoch 7793 +2024-11-23 05:52:06.563031: Current learning rate: 0.00037 +2024-11-23 05:52:25.310955: train_loss -0.8404 +2024-11-23 05:52:25.311167: val_loss -0.7736 +2024-11-23 05:52:25.311255: Pseudo dice [0.8628] +2024-11-23 05:52:25.311334: Epoch time: 18.75 s +2024-11-23 05:52:26.598801: +2024-11-23 05:52:26.599009: Epoch 7794 +2024-11-23 05:52:26.599126: Current learning rate: 0.00037 +2024-11-23 05:52:45.044434: train_loss -0.8346 +2024-11-23 05:52:45.044664: val_loss -0.7941 +2024-11-23 05:52:45.044742: Pseudo dice [0.8609] +2024-11-23 05:52:45.044842: Epoch time: 18.45 s +2024-11-23 05:52:45.980213: +2024-11-23 05:52:45.980462: Epoch 7795 +2024-11-23 05:52:45.980611: Current learning rate: 0.00037 +2024-11-23 05:53:05.623580: train_loss -0.8462 +2024-11-23 05:53:05.625532: val_loss -0.8002 +2024-11-23 05:53:05.625643: Pseudo dice [0.8604] +2024-11-23 05:53:05.625721: Epoch time: 19.64 s +2024-11-23 05:53:06.568543: +2024-11-23 05:53:06.568798: Epoch 7796 +2024-11-23 05:53:06.568927: Current learning rate: 0.00037 +2024-11-23 05:53:25.771373: train_loss -0.8353 +2024-11-23 05:53:25.771587: val_loss -0.7776 +2024-11-23 05:53:25.771679: Pseudo dice [0.8591] +2024-11-23 05:53:25.771754: Epoch time: 19.2 s +2024-11-23 05:53:26.677532: +2024-11-23 05:53:26.677754: Epoch 7797 +2024-11-23 05:53:26.677869: Current learning rate: 0.00037 +2024-11-23 05:53:44.691024: train_loss -0.8435 +2024-11-23 05:53:44.691244: val_loss -0.7802 +2024-11-23 05:53:44.691326: Pseudo dice [0.8555] +2024-11-23 05:53:44.691416: Epoch time: 18.01 s +2024-11-23 05:53:45.600734: +2024-11-23 05:53:45.600991: Epoch 7798 +2024-11-23 05:53:45.601119: Current learning rate: 0.00036 +2024-11-23 05:54:04.036695: train_loss -0.8377 +2024-11-23 05:54:04.036956: val_loss -0.7764 +2024-11-23 05:54:04.037040: Pseudo dice [0.8694] +2024-11-23 05:54:04.037142: Epoch time: 18.44 s +2024-11-23 05:54:05.232308: +2024-11-23 05:54:05.232518: Epoch 7799 +2024-11-23 05:54:05.232645: Current learning rate: 0.00036 +2024-11-23 05:54:24.572250: train_loss -0.8367 +2024-11-23 05:54:24.572470: val_loss -0.7895 +2024-11-23 05:54:24.572553: Pseudo dice [0.8556] +2024-11-23 05:54:24.572647: Epoch time: 19.34 s +2024-11-23 05:54:25.836065: +2024-11-23 05:54:25.836291: Epoch 7800 +2024-11-23 05:54:25.836419: Current learning rate: 0.00036 +2024-11-23 05:54:43.517216: train_loss -0.8358 +2024-11-23 05:54:43.517558: val_loss -0.7834 +2024-11-23 05:54:43.517655: Pseudo dice [0.8577] +2024-11-23 05:54:43.517734: Epoch time: 17.68 s +2024-11-23 05:54:44.565382: +2024-11-23 05:54:44.565628: Epoch 7801 +2024-11-23 05:54:44.565763: Current learning rate: 0.00036 +2024-11-23 05:55:02.557306: train_loss -0.8294 +2024-11-23 05:55:02.557525: val_loss -0.7963 +2024-11-23 05:55:02.559801: Pseudo dice [0.8575] +2024-11-23 05:55:02.559917: Epoch time: 17.99 s +2024-11-23 05:55:03.508497: +2024-11-23 05:55:03.508746: Epoch 7802 +2024-11-23 05:55:03.508899: Current learning rate: 0.00036 +2024-11-23 05:55:21.274505: train_loss -0.8423 +2024-11-23 05:55:21.274754: val_loss -0.7986 +2024-11-23 05:55:21.274842: Pseudo dice [0.8735] +2024-11-23 05:55:21.274923: Epoch time: 17.77 s +2024-11-23 05:55:22.244915: +2024-11-23 05:55:22.245102: Epoch 7803 +2024-11-23 05:55:22.245214: Current learning rate: 0.00036 +2024-11-23 05:55:41.154212: train_loss -0.8388 +2024-11-23 05:55:41.154421: val_loss -0.7962 +2024-11-23 05:55:41.154504: Pseudo dice [0.8668] +2024-11-23 05:55:41.154583: Epoch time: 18.91 s +2024-11-23 05:55:42.055718: +2024-11-23 05:55:42.055917: Epoch 7804 +2024-11-23 05:55:42.056054: Current learning rate: 0.00036 +2024-11-23 05:56:01.009892: train_loss -0.8339 +2024-11-23 05:56:01.010104: val_loss -0.7855 +2024-11-23 05:56:01.010181: Pseudo dice [0.8606] +2024-11-23 05:56:01.010432: Epoch time: 18.95 s +2024-11-23 05:56:02.310578: +2024-11-23 05:56:02.310794: Epoch 7805 +2024-11-23 05:56:02.310926: Current learning rate: 0.00035 +2024-11-23 05:56:19.400209: train_loss -0.8399 +2024-11-23 05:56:19.400470: val_loss -0.7814 +2024-11-23 05:56:19.400560: Pseudo dice [0.861] +2024-11-23 05:56:19.400648: Epoch time: 17.09 s +2024-11-23 05:56:20.305783: +2024-11-23 05:56:20.305996: Epoch 7806 +2024-11-23 05:56:20.306113: Current learning rate: 0.00035 +2024-11-23 05:56:38.822583: train_loss -0.8389 +2024-11-23 05:56:38.822792: val_loss -0.7798 +2024-11-23 05:56:38.822873: Pseudo dice [0.8476] +2024-11-23 05:56:38.822953: Epoch time: 18.52 s +2024-11-23 05:56:39.728887: +2024-11-23 05:56:39.729122: Epoch 7807 +2024-11-23 05:56:39.729238: Current learning rate: 0.00035 +2024-11-23 05:56:57.358783: train_loss -0.835 +2024-11-23 05:56:57.358998: val_loss -0.7916 +2024-11-23 05:56:57.359080: Pseudo dice [0.8679] +2024-11-23 05:56:57.359163: Epoch time: 17.63 s +2024-11-23 05:56:58.264934: +2024-11-23 05:56:58.265168: Epoch 7808 +2024-11-23 05:56:58.265286: Current learning rate: 0.00035 +2024-11-23 05:57:17.428519: train_loss -0.8401 +2024-11-23 05:57:17.428737: val_loss -0.7991 +2024-11-23 05:57:17.428820: Pseudo dice [0.859] +2024-11-23 05:57:17.428908: Epoch time: 19.16 s +2024-11-23 05:57:18.336629: +2024-11-23 05:57:18.336850: Epoch 7809 +2024-11-23 05:57:18.336968: Current learning rate: 0.00035 +2024-11-23 05:57:35.550148: train_loss -0.8381 +2024-11-23 05:57:35.550382: val_loss -0.8092 +2024-11-23 05:57:35.550484: Pseudo dice [0.8702] +2024-11-23 05:57:35.550580: Epoch time: 17.21 s +2024-11-23 05:57:36.496131: +2024-11-23 05:57:36.496364: Epoch 7810 +2024-11-23 05:57:36.496474: Current learning rate: 0.00035 +2024-11-23 05:57:56.483541: train_loss -0.8334 +2024-11-23 05:57:56.483754: val_loss -0.7854 +2024-11-23 05:57:56.483843: Pseudo dice [0.8661] +2024-11-23 05:57:56.483923: Epoch time: 19.99 s +2024-11-23 05:57:57.404077: +2024-11-23 05:57:57.404306: Epoch 7811 +2024-11-23 05:57:57.404419: Current learning rate: 0.00034 +2024-11-23 05:58:16.734356: train_loss -0.8323 +2024-11-23 05:58:16.734578: val_loss -0.8055 +2024-11-23 05:58:16.734661: Pseudo dice [0.8686] +2024-11-23 05:58:16.734736: Epoch time: 19.33 s +2024-11-23 05:58:17.635360: +2024-11-23 05:58:17.635575: Epoch 7812 +2024-11-23 05:58:17.635706: Current learning rate: 0.00034 +2024-11-23 05:58:36.948196: train_loss -0.8297 +2024-11-23 05:58:36.948456: val_loss -0.7996 +2024-11-23 05:58:36.948535: Pseudo dice [0.8716] +2024-11-23 05:58:36.953900: Epoch time: 19.31 s +2024-11-23 05:58:36.954002: Yayy! New best EMA pseudo Dice: 0.864 +2024-11-23 05:58:38.514399: +2024-11-23 05:58:38.514616: Epoch 7813 +2024-11-23 05:58:38.514727: Current learning rate: 0.00034 +2024-11-23 05:58:57.154093: train_loss -0.8345 +2024-11-23 05:58:57.154305: val_loss -0.7806 +2024-11-23 05:58:57.154391: Pseudo dice [0.8549] +2024-11-23 05:58:57.154466: Epoch time: 18.64 s +2024-11-23 05:58:58.057750: +2024-11-23 05:58:58.057974: Epoch 7814 +2024-11-23 05:58:58.058099: Current learning rate: 0.00034 +2024-11-23 05:59:16.644817: train_loss -0.8374 +2024-11-23 05:59:16.645052: val_loss -0.7297 +2024-11-23 05:59:16.645155: Pseudo dice [0.865] +2024-11-23 05:59:16.645245: Epoch time: 18.59 s +2024-11-23 05:59:17.545525: +2024-11-23 05:59:17.545758: Epoch 7815 +2024-11-23 05:59:17.545882: Current learning rate: 0.00034 +2024-11-23 05:59:37.057751: train_loss -0.8397 +2024-11-23 05:59:37.057989: val_loss -0.7949 +2024-11-23 05:59:37.058072: Pseudo dice [0.8584] +2024-11-23 05:59:37.058146: Epoch time: 19.51 s +2024-11-23 05:59:38.395849: +2024-11-23 05:59:38.396051: Epoch 7816 +2024-11-23 05:59:38.396179: Current learning rate: 0.00034 +2024-11-23 05:59:57.461708: train_loss -0.8398 +2024-11-23 05:59:57.461962: val_loss -0.7945 +2024-11-23 05:59:57.467251: Pseudo dice [0.854] +2024-11-23 05:59:57.467402: Epoch time: 19.07 s +2024-11-23 05:59:58.414016: +2024-11-23 05:59:58.414258: Epoch 7817 +2024-11-23 05:59:58.414380: Current learning rate: 0.00033 +2024-11-23 06:00:16.003381: train_loss -0.838 +2024-11-23 06:00:16.003595: val_loss -0.8047 +2024-11-23 06:00:16.003679: Pseudo dice [0.8622] +2024-11-23 06:00:16.003759: Epoch time: 17.59 s +2024-11-23 06:00:17.025609: +2024-11-23 06:00:17.025807: Epoch 7818 +2024-11-23 06:00:17.025932: Current learning rate: 0.00033 +2024-11-23 06:00:35.301969: train_loss -0.8441 +2024-11-23 06:00:35.302190: val_loss -0.7952 +2024-11-23 06:00:35.302266: Pseudo dice [0.8665] +2024-11-23 06:00:35.302366: Epoch time: 18.28 s +2024-11-23 06:00:36.203862: +2024-11-23 06:00:36.204085: Epoch 7819 +2024-11-23 06:00:36.204213: Current learning rate: 0.00033 +2024-11-23 06:00:54.754799: train_loss -0.8368 +2024-11-23 06:00:54.757230: val_loss -0.8107 +2024-11-23 06:00:54.757328: Pseudo dice [0.8613] +2024-11-23 06:00:54.757430: Epoch time: 18.55 s +2024-11-23 06:00:55.766385: +2024-11-23 06:00:55.766629: Epoch 7820 +2024-11-23 06:00:55.766743: Current learning rate: 0.00033 +2024-11-23 06:01:13.695221: train_loss -0.8378 +2024-11-23 06:01:13.695445: val_loss -0.7918 +2024-11-23 06:01:13.695599: Pseudo dice [0.8656] +2024-11-23 06:01:13.695686: Epoch time: 17.93 s +2024-11-23 06:01:14.660089: +2024-11-23 06:01:14.660299: Epoch 7821 +2024-11-23 06:01:14.660409: Current learning rate: 0.00033 +2024-11-23 06:01:33.172987: train_loss -0.8426 +2024-11-23 06:01:33.173232: val_loss -0.7764 +2024-11-23 06:01:33.175504: Pseudo dice [0.8475] +2024-11-23 06:01:33.175621: Epoch time: 18.51 s +2024-11-23 06:01:34.090616: +2024-11-23 06:01:34.090823: Epoch 7822 +2024-11-23 06:01:34.090937: Current learning rate: 0.00033 +2024-11-23 06:01:51.652610: train_loss -0.8394 +2024-11-23 06:01:51.652810: val_loss -0.7953 +2024-11-23 06:01:51.652885: Pseudo dice [0.8482] +2024-11-23 06:01:51.652961: Epoch time: 17.56 s +2024-11-23 06:01:52.552694: +2024-11-23 06:01:52.552888: Epoch 7823 +2024-11-23 06:01:52.552997: Current learning rate: 0.00032 +2024-11-23 06:02:09.612195: train_loss -0.841 +2024-11-23 06:02:09.612449: val_loss -0.8057 +2024-11-23 06:02:09.612530: Pseudo dice [0.8652] +2024-11-23 06:02:09.612618: Epoch time: 17.06 s +2024-11-23 06:02:10.517286: +2024-11-23 06:02:10.517494: Epoch 7824 +2024-11-23 06:02:10.517610: Current learning rate: 0.00032 +2024-11-23 06:02:28.537024: train_loss -0.842 +2024-11-23 06:02:28.537278: val_loss -0.765 +2024-11-23 06:02:28.537358: Pseudo dice [0.8512] +2024-11-23 06:02:28.537445: Epoch time: 18.02 s +2024-11-23 06:02:29.441448: +2024-11-23 06:02:29.441654: Epoch 7825 +2024-11-23 06:02:29.441770: Current learning rate: 0.00032 +2024-11-23 06:02:48.186586: train_loss -0.8421 +2024-11-23 06:02:48.186808: val_loss -0.7837 +2024-11-23 06:02:48.186891: Pseudo dice [0.8656] +2024-11-23 06:02:48.186972: Epoch time: 18.75 s +2024-11-23 06:02:49.091229: +2024-11-23 06:02:49.091454: Epoch 7826 +2024-11-23 06:02:49.091569: Current learning rate: 0.00032 +2024-11-23 06:03:07.453667: train_loss -0.8384 +2024-11-23 06:03:07.453900: val_loss -0.7901 +2024-11-23 06:03:07.453979: Pseudo dice [0.8616] +2024-11-23 06:03:07.454056: Epoch time: 18.36 s +2024-11-23 06:03:08.787761: +2024-11-23 06:03:08.787973: Epoch 7827 +2024-11-23 06:03:08.788098: Current learning rate: 0.00032 +2024-11-23 06:03:26.211577: train_loss -0.8376 +2024-11-23 06:03:26.214437: val_loss -0.7945 +2024-11-23 06:03:26.214595: Pseudo dice [0.8621] +2024-11-23 06:03:26.214687: Epoch time: 17.42 s +2024-11-23 06:03:27.204350: +2024-11-23 06:03:27.204601: Epoch 7828 +2024-11-23 06:03:27.204714: Current learning rate: 0.00032 +2024-11-23 06:03:47.521135: train_loss -0.8283 +2024-11-23 06:03:47.521361: val_loss -0.7821 +2024-11-23 06:03:47.521448: Pseudo dice [0.8643] +2024-11-23 06:03:47.521526: Epoch time: 20.32 s +2024-11-23 06:03:48.427428: +2024-11-23 06:03:48.427655: Epoch 7829 +2024-11-23 06:03:48.427768: Current learning rate: 0.00031 +2024-11-23 06:04:07.782502: train_loss -0.8385 +2024-11-23 06:04:07.782724: val_loss -0.8017 +2024-11-23 06:04:07.782802: Pseudo dice [0.8614] +2024-11-23 06:04:07.782883: Epoch time: 19.36 s +2024-11-23 06:04:08.691487: +2024-11-23 06:04:08.691704: Epoch 7830 +2024-11-23 06:04:08.691822: Current learning rate: 0.00031 +2024-11-23 06:04:27.460034: train_loss -0.8458 +2024-11-23 06:04:27.460601: val_loss -0.7849 +2024-11-23 06:04:27.460701: Pseudo dice [0.8549] +2024-11-23 06:04:27.460779: Epoch time: 18.77 s +2024-11-23 06:04:28.372630: +2024-11-23 06:04:28.372849: Epoch 7831 +2024-11-23 06:04:28.372960: Current learning rate: 0.00031 +2024-11-23 06:04:46.999893: train_loss -0.8349 +2024-11-23 06:04:47.000141: val_loss -0.7832 +2024-11-23 06:04:47.000234: Pseudo dice [0.8596] +2024-11-23 06:04:47.000319: Epoch time: 18.63 s +2024-11-23 06:04:47.913277: +2024-11-23 06:04:47.913479: Epoch 7832 +2024-11-23 06:04:47.913607: Current learning rate: 0.00031 +2024-11-23 06:05:06.259097: train_loss -0.8352 +2024-11-23 06:05:06.259330: val_loss -0.7728 +2024-11-23 06:05:06.259412: Pseudo dice [0.8648] +2024-11-23 06:05:06.259488: Epoch time: 18.35 s +2024-11-23 06:05:07.180132: +2024-11-23 06:05:07.180369: Epoch 7833 +2024-11-23 06:05:07.180484: Current learning rate: 0.00031 +2024-11-23 06:05:25.339561: train_loss -0.8382 +2024-11-23 06:05:25.339782: val_loss -0.7442 +2024-11-23 06:05:25.339874: Pseudo dice [0.8522] +2024-11-23 06:05:25.339964: Epoch time: 18.16 s +2024-11-23 06:05:26.243803: +2024-11-23 06:05:26.244023: Epoch 7834 +2024-11-23 06:05:26.244151: Current learning rate: 0.00031 +2024-11-23 06:05:44.698384: train_loss -0.8449 +2024-11-23 06:05:44.698649: val_loss -0.7855 +2024-11-23 06:05:44.698740: Pseudo dice [0.8654] +2024-11-23 06:05:44.698843: Epoch time: 18.46 s +2024-11-23 06:05:45.622534: +2024-11-23 06:05:45.622776: Epoch 7835 +2024-11-23 06:05:45.622896: Current learning rate: 0.0003 +2024-11-23 06:06:04.426283: train_loss -0.8405 +2024-11-23 06:06:04.426508: val_loss -0.7542 +2024-11-23 06:06:04.426595: Pseudo dice [0.8465] +2024-11-23 06:06:04.426702: Epoch time: 18.8 s +2024-11-23 06:06:05.328566: +2024-11-23 06:06:05.328772: Epoch 7836 +2024-11-23 06:06:05.328905: Current learning rate: 0.0003 +2024-11-23 06:06:24.079309: train_loss -0.839 +2024-11-23 06:06:24.079525: val_loss -0.7937 +2024-11-23 06:06:24.079609: Pseudo dice [0.8595] +2024-11-23 06:06:24.079701: Epoch time: 18.75 s +2024-11-23 06:06:24.989679: +2024-11-23 06:06:24.989894: Epoch 7837 +2024-11-23 06:06:24.990007: Current learning rate: 0.0003 +2024-11-23 06:06:42.635663: train_loss -0.8414 +2024-11-23 06:06:42.635890: val_loss -0.7678 +2024-11-23 06:06:42.635985: Pseudo dice [0.8665] +2024-11-23 06:06:42.636073: Epoch time: 17.65 s +2024-11-23 06:06:43.898429: +2024-11-23 06:06:43.898645: Epoch 7838 +2024-11-23 06:06:43.898763: Current learning rate: 0.0003 +2024-11-23 06:07:02.986771: train_loss -0.8393 +2024-11-23 06:07:02.987079: val_loss -0.7935 +2024-11-23 06:07:02.987173: Pseudo dice [0.8668] +2024-11-23 06:07:02.987260: Epoch time: 19.09 s +2024-11-23 06:07:03.901988: +2024-11-23 06:07:03.902192: Epoch 7839 +2024-11-23 06:07:03.902302: Current learning rate: 0.0003 +2024-11-23 06:07:22.595554: train_loss -0.8423 +2024-11-23 06:07:22.595771: val_loss -0.7911 +2024-11-23 06:07:22.595879: Pseudo dice [0.862] +2024-11-23 06:07:22.596017: Epoch time: 18.69 s +2024-11-23 06:07:23.502578: +2024-11-23 06:07:23.502798: Epoch 7840 +2024-11-23 06:07:23.502918: Current learning rate: 0.0003 +2024-11-23 06:07:42.083968: train_loss -0.8324 +2024-11-23 06:07:42.084310: val_loss -0.7981 +2024-11-23 06:07:42.084398: Pseudo dice [0.8776] +2024-11-23 06:07:42.084478: Epoch time: 18.58 s +2024-11-23 06:07:42.999442: +2024-11-23 06:07:42.999683: Epoch 7841 +2024-11-23 06:07:42.999793: Current learning rate: 0.00029 +2024-11-23 06:08:01.136806: train_loss -0.8438 +2024-11-23 06:08:01.137023: val_loss -0.7858 +2024-11-23 06:08:01.137117: Pseudo dice [0.8708] +2024-11-23 06:08:01.137200: Epoch time: 18.14 s +2024-11-23 06:08:02.046208: +2024-11-23 06:08:02.046414: Epoch 7842 +2024-11-23 06:08:02.046525: Current learning rate: 0.00029 +2024-11-23 06:08:21.284026: train_loss -0.8417 +2024-11-23 06:08:21.284285: val_loss -0.7824 +2024-11-23 06:08:21.284426: Pseudo dice [0.8602] +2024-11-23 06:08:21.284516: Epoch time: 19.24 s +2024-11-23 06:08:22.191811: +2024-11-23 06:08:22.192033: Epoch 7843 +2024-11-23 06:08:22.192148: Current learning rate: 0.00029 +2024-11-23 06:08:41.088832: train_loss -0.844 +2024-11-23 06:08:41.089046: val_loss -0.764 +2024-11-23 06:08:41.089133: Pseudo dice [0.865] +2024-11-23 06:08:41.091363: Epoch time: 18.9 s +2024-11-23 06:08:42.066602: +2024-11-23 06:08:42.066836: Epoch 7844 +2024-11-23 06:08:42.066966: Current learning rate: 0.00029 +2024-11-23 06:09:00.533723: train_loss -0.8439 +2024-11-23 06:09:00.533943: val_loss -0.7805 +2024-11-23 06:09:00.534021: Pseudo dice [0.8491] +2024-11-23 06:09:00.534150: Epoch time: 18.47 s +2024-11-23 06:09:01.420647: +2024-11-23 06:09:01.420861: Epoch 7845 +2024-11-23 06:09:01.420974: Current learning rate: 0.00029 +2024-11-23 06:09:19.892460: train_loss -0.8372 +2024-11-23 06:09:19.892669: val_loss -0.7611 +2024-11-23 06:09:19.892757: Pseudo dice [0.8637] +2024-11-23 06:09:19.892840: Epoch time: 18.47 s +2024-11-23 06:09:20.792267: +2024-11-23 06:09:20.792514: Epoch 7846 +2024-11-23 06:09:20.792632: Current learning rate: 0.00029 +2024-11-23 06:09:39.665479: train_loss -0.8407 +2024-11-23 06:09:39.665697: val_loss -0.8091 +2024-11-23 06:09:39.665776: Pseudo dice [0.8745] +2024-11-23 06:09:39.668164: Epoch time: 18.87 s +2024-11-23 06:09:40.576331: +2024-11-23 06:09:40.576533: Epoch 7847 +2024-11-23 06:09:40.576640: Current learning rate: 0.00028 +2024-11-23 06:09:59.472996: train_loss -0.8422 +2024-11-23 06:09:59.475355: val_loss -0.7757 +2024-11-23 06:09:59.475455: Pseudo dice [0.8628] +2024-11-23 06:09:59.475536: Epoch time: 18.9 s +2024-11-23 06:10:00.525814: +2024-11-23 06:10:00.526015: Epoch 7848 +2024-11-23 06:10:00.526146: Current learning rate: 0.00028 +2024-11-23 06:10:18.475675: train_loss -0.8404 +2024-11-23 06:10:18.475895: val_loss -0.7913 +2024-11-23 06:10:18.475973: Pseudo dice [0.8591] +2024-11-23 06:10:18.476048: Epoch time: 17.95 s +2024-11-23 06:10:19.725129: +2024-11-23 06:10:19.725356: Epoch 7849 +2024-11-23 06:10:19.725485: Current learning rate: 0.00028 +2024-11-23 06:10:37.519546: train_loss -0.8351 +2024-11-23 06:10:37.525021: val_loss -0.7862 +2024-11-23 06:10:37.525155: Pseudo dice [0.8704] +2024-11-23 06:10:37.525244: Epoch time: 17.8 s +2024-11-23 06:10:38.844982: +2024-11-23 06:10:38.845228: Epoch 7850 +2024-11-23 06:10:38.845365: Current learning rate: 0.00028 +2024-11-23 06:10:58.560548: train_loss -0.8396 +2024-11-23 06:10:58.560754: val_loss -0.8038 +2024-11-23 06:10:58.560853: Pseudo dice [0.8656] +2024-11-23 06:10:58.560931: Epoch time: 19.72 s +2024-11-23 06:10:59.458767: +2024-11-23 06:10:59.459054: Epoch 7851 +2024-11-23 06:10:59.459173: Current learning rate: 0.00028 +2024-11-23 06:11:18.562234: train_loss -0.8382 +2024-11-23 06:11:18.562436: val_loss -0.7865 +2024-11-23 06:11:18.562516: Pseudo dice [0.8617] +2024-11-23 06:11:18.562595: Epoch time: 19.1 s +2024-11-23 06:11:19.467036: +2024-11-23 06:11:19.467269: Epoch 7852 +2024-11-23 06:11:19.467381: Current learning rate: 0.00028 +2024-11-23 06:11:38.031507: train_loss -0.8403 +2024-11-23 06:11:38.031717: val_loss -0.7753 +2024-11-23 06:11:38.031794: Pseudo dice [0.8554] +2024-11-23 06:11:38.034115: Epoch time: 18.57 s +2024-11-23 06:11:39.004673: +2024-11-23 06:11:39.004888: Epoch 7853 +2024-11-23 06:11:39.005017: Current learning rate: 0.00027 +2024-11-23 06:11:57.424490: train_loss -0.8489 +2024-11-23 06:11:57.424714: val_loss -0.7864 +2024-11-23 06:11:57.424789: Pseudo dice [0.8505] +2024-11-23 06:11:57.424870: Epoch time: 18.42 s +2024-11-23 06:11:58.328217: +2024-11-23 06:11:58.328432: Epoch 7854 +2024-11-23 06:11:58.328559: Current learning rate: 0.00027 +2024-11-23 06:12:18.488216: train_loss -0.8344 +2024-11-23 06:12:18.488451: val_loss -0.7756 +2024-11-23 06:12:18.488530: Pseudo dice [0.8569] +2024-11-23 06:12:18.488613: Epoch time: 20.16 s +2024-11-23 06:12:19.401440: +2024-11-23 06:12:19.401648: Epoch 7855 +2024-11-23 06:12:19.401768: Current learning rate: 0.00027 +2024-11-23 06:12:38.266306: train_loss -0.8339 +2024-11-23 06:12:38.266523: val_loss -0.783 +2024-11-23 06:12:38.266644: Pseudo dice [0.8671] +2024-11-23 06:12:38.266724: Epoch time: 18.87 s +2024-11-23 06:12:39.167873: +2024-11-23 06:12:39.168091: Epoch 7856 +2024-11-23 06:12:39.168205: Current learning rate: 0.00027 +2024-11-23 06:12:58.122280: train_loss -0.8415 +2024-11-23 06:12:58.122527: val_loss -0.7787 +2024-11-23 06:12:58.122614: Pseudo dice [0.8645] +2024-11-23 06:12:58.122733: Epoch time: 18.96 s +2024-11-23 06:12:59.056748: +2024-11-23 06:12:59.056963: Epoch 7857 +2024-11-23 06:12:59.057088: Current learning rate: 0.00027 +2024-11-23 06:13:17.049422: train_loss -0.8457 +2024-11-23 06:13:17.051833: val_loss -0.7644 +2024-11-23 06:13:17.051980: Pseudo dice [0.8639] +2024-11-23 06:13:17.052070: Epoch time: 17.99 s +2024-11-23 06:13:18.040040: +2024-11-23 06:13:18.040261: Epoch 7858 +2024-11-23 06:13:18.040390: Current learning rate: 0.00027 +2024-11-23 06:13:37.419443: train_loss -0.835 +2024-11-23 06:13:37.419665: val_loss -0.7868 +2024-11-23 06:13:37.419766: Pseudo dice [0.8572] +2024-11-23 06:13:37.422052: Epoch time: 19.38 s +2024-11-23 06:13:38.685201: +2024-11-23 06:13:38.685416: Epoch 7859 +2024-11-23 06:13:38.685527: Current learning rate: 0.00026 +2024-11-23 06:13:58.168370: train_loss -0.8247 +2024-11-23 06:13:58.168580: val_loss -0.7894 +2024-11-23 06:13:58.168654: Pseudo dice [0.8731] +2024-11-23 06:13:58.168735: Epoch time: 19.48 s +2024-11-23 06:13:59.487756: +2024-11-23 06:13:59.487955: Epoch 7860 +2024-11-23 06:13:59.488075: Current learning rate: 0.00026 +2024-11-23 06:14:19.084588: train_loss -0.8334 +2024-11-23 06:14:19.084823: val_loss -0.7848 +2024-11-23 06:14:19.084913: Pseudo dice [0.8549] +2024-11-23 06:14:19.085004: Epoch time: 19.6 s +2024-11-23 06:14:19.995904: +2024-11-23 06:14:19.996150: Epoch 7861 +2024-11-23 06:14:19.996268: Current learning rate: 0.00026 +2024-11-23 06:14:37.724846: train_loss -0.8412 +2024-11-23 06:14:37.725057: val_loss -0.7832 +2024-11-23 06:14:37.725140: Pseudo dice [0.8639] +2024-11-23 06:14:37.725215: Epoch time: 17.73 s +2024-11-23 06:14:38.627888: +2024-11-23 06:14:38.628131: Epoch 7862 +2024-11-23 06:14:38.628257: Current learning rate: 0.00026 +2024-11-23 06:14:57.139481: train_loss -0.841 +2024-11-23 06:14:57.139696: val_loss -0.7813 +2024-11-23 06:14:57.139778: Pseudo dice [0.8659] +2024-11-23 06:14:57.139856: Epoch time: 18.51 s +2024-11-23 06:14:58.045834: +2024-11-23 06:14:58.046052: Epoch 7863 +2024-11-23 06:14:58.046182: Current learning rate: 0.00026 +2024-11-23 06:15:15.681553: train_loss -0.8415 +2024-11-23 06:15:15.681793: val_loss -0.7854 +2024-11-23 06:15:15.681873: Pseudo dice [0.8561] +2024-11-23 06:15:15.681949: Epoch time: 17.64 s +2024-11-23 06:15:16.638674: +2024-11-23 06:15:16.638878: Epoch 7864 +2024-11-23 06:15:16.638990: Current learning rate: 0.00026 +2024-11-23 06:15:34.568123: train_loss -0.8404 +2024-11-23 06:15:34.568345: val_loss -0.7809 +2024-11-23 06:15:34.568417: Pseudo dice [0.8592] +2024-11-23 06:15:34.568497: Epoch time: 17.93 s +2024-11-23 06:15:35.493367: +2024-11-23 06:15:35.493594: Epoch 7865 +2024-11-23 06:15:35.493716: Current learning rate: 0.00025 +2024-11-23 06:15:53.847614: train_loss -0.8447 +2024-11-23 06:15:53.847851: val_loss -0.7866 +2024-11-23 06:15:53.847930: Pseudo dice [0.8632] +2024-11-23 06:15:53.848019: Epoch time: 18.36 s +2024-11-23 06:15:54.753328: +2024-11-23 06:15:54.753536: Epoch 7866 +2024-11-23 06:15:54.753644: Current learning rate: 0.00025 +2024-11-23 06:16:13.205137: train_loss -0.8335 +2024-11-23 06:16:13.205360: val_loss -0.7993 +2024-11-23 06:16:13.205455: Pseudo dice [0.8712] +2024-11-23 06:16:13.205531: Epoch time: 18.45 s +2024-11-23 06:16:14.113715: +2024-11-23 06:16:14.113925: Epoch 7867 +2024-11-23 06:16:14.114040: Current learning rate: 0.00025 +2024-11-23 06:16:32.720150: train_loss -0.8409 +2024-11-23 06:16:32.720418: val_loss -0.7741 +2024-11-23 06:16:32.720515: Pseudo dice [0.8626] +2024-11-23 06:16:32.720644: Epoch time: 18.61 s +2024-11-23 06:16:33.625132: +2024-11-23 06:16:33.625379: Epoch 7868 +2024-11-23 06:16:33.625510: Current learning rate: 0.00025 +2024-11-23 06:16:51.228050: train_loss -0.8421 +2024-11-23 06:16:51.228303: val_loss -0.7734 +2024-11-23 06:16:51.228403: Pseudo dice [0.8677] +2024-11-23 06:16:51.228494: Epoch time: 17.6 s +2024-11-23 06:16:52.256762: +2024-11-23 06:16:52.256969: Epoch 7869 +2024-11-23 06:16:52.257094: Current learning rate: 0.00025 +2024-11-23 06:17:11.939485: train_loss -0.8379 +2024-11-23 06:17:11.939691: val_loss -0.7708 +2024-11-23 06:17:11.939770: Pseudo dice [0.8684] +2024-11-23 06:17:11.939861: Epoch time: 19.68 s +2024-11-23 06:17:12.840997: +2024-11-23 06:17:12.841209: Epoch 7870 +2024-11-23 06:17:12.841342: Current learning rate: 0.00025 +2024-11-23 06:17:31.669732: train_loss -0.8447 +2024-11-23 06:17:31.669939: val_loss -0.7929 +2024-11-23 06:17:31.670022: Pseudo dice [0.8494] +2024-11-23 06:17:31.670101: Epoch time: 18.83 s +2024-11-23 06:17:32.998020: +2024-11-23 06:17:32.998234: Epoch 7871 +2024-11-23 06:17:32.998351: Current learning rate: 0.00024 +2024-11-23 06:17:52.454488: train_loss -0.8381 +2024-11-23 06:17:52.454748: val_loss -0.7989 +2024-11-23 06:17:52.454836: Pseudo dice [0.854] +2024-11-23 06:17:52.454937: Epoch time: 19.46 s +2024-11-23 06:17:53.363193: +2024-11-23 06:17:53.363396: Epoch 7872 +2024-11-23 06:17:53.363509: Current learning rate: 0.00024 +2024-11-23 06:18:12.169999: train_loss -0.8385 +2024-11-23 06:18:12.174747: val_loss -0.8011 +2024-11-23 06:18:12.174956: Pseudo dice [0.8623] +2024-11-23 06:18:12.175075: Epoch time: 18.81 s +2024-11-23 06:18:13.214869: +2024-11-23 06:18:13.215096: Epoch 7873 +2024-11-23 06:18:13.215224: Current learning rate: 0.00024 +2024-11-23 06:18:30.380399: train_loss -0.8371 +2024-11-23 06:18:30.385404: val_loss -0.764 +2024-11-23 06:18:30.385505: Pseudo dice [0.8544] +2024-11-23 06:18:30.385598: Epoch time: 17.17 s +2024-11-23 06:18:31.491315: +2024-11-23 06:18:31.491542: Epoch 7874 +2024-11-23 06:18:31.491654: Current learning rate: 0.00024 +2024-11-23 06:18:49.911867: train_loss -0.8419 +2024-11-23 06:18:49.912092: val_loss -0.7789 +2024-11-23 06:18:49.912175: Pseudo dice [0.8661] +2024-11-23 06:18:49.917463: Epoch time: 18.42 s +2024-11-23 06:18:50.985348: +2024-11-23 06:18:50.985585: Epoch 7875 +2024-11-23 06:18:50.985712: Current learning rate: 0.00024 +2024-11-23 06:19:09.001837: train_loss -0.8433 +2024-11-23 06:19:09.002083: val_loss -0.7587 +2024-11-23 06:19:09.002180: Pseudo dice [0.8598] +2024-11-23 06:19:09.002264: Epoch time: 18.02 s +2024-11-23 06:19:09.906518: +2024-11-23 06:19:09.906739: Epoch 7876 +2024-11-23 06:19:09.906852: Current learning rate: 0.00024 +2024-11-23 06:19:28.292070: train_loss -0.8388 +2024-11-23 06:19:28.292368: val_loss -0.7695 +2024-11-23 06:19:28.292453: Pseudo dice [0.8664] +2024-11-23 06:19:28.292531: Epoch time: 18.39 s +2024-11-23 06:19:29.193041: +2024-11-23 06:19:29.193341: Epoch 7877 +2024-11-23 06:19:29.193473: Current learning rate: 0.00023 +2024-11-23 06:19:47.082451: train_loss -0.8383 +2024-11-23 06:19:47.082671: val_loss -0.7745 +2024-11-23 06:19:47.082744: Pseudo dice [0.854] +2024-11-23 06:19:47.082832: Epoch time: 17.89 s +2024-11-23 06:19:48.148644: +2024-11-23 06:19:48.148859: Epoch 7878 +2024-11-23 06:19:48.148973: Current learning rate: 0.00023 +2024-11-23 06:20:07.265854: train_loss -0.8425 +2024-11-23 06:20:07.266087: val_loss -0.7747 +2024-11-23 06:20:07.266172: Pseudo dice [0.8506] +2024-11-23 06:20:07.266256: Epoch time: 19.12 s +2024-11-23 06:20:08.172820: +2024-11-23 06:20:08.173114: Epoch 7879 +2024-11-23 06:20:08.173239: Current learning rate: 0.00023 +2024-11-23 06:20:26.938203: train_loss -0.8494 +2024-11-23 06:20:26.938421: val_loss -0.7957 +2024-11-23 06:20:26.938501: Pseudo dice [0.8736] +2024-11-23 06:20:26.938582: Epoch time: 18.77 s +2024-11-23 06:20:27.841615: +2024-11-23 06:20:27.841819: Epoch 7880 +2024-11-23 06:20:27.841931: Current learning rate: 0.00023 +2024-11-23 06:20:47.276103: train_loss -0.839 +2024-11-23 06:20:47.276316: val_loss -0.7751 +2024-11-23 06:20:47.276415: Pseudo dice [0.8613] +2024-11-23 06:20:47.276516: Epoch time: 19.44 s +2024-11-23 06:20:48.183257: +2024-11-23 06:20:48.183459: Epoch 7881 +2024-11-23 06:20:48.183583: Current learning rate: 0.00023 +2024-11-23 06:21:07.912378: train_loss -0.8397 +2024-11-23 06:21:07.912587: val_loss -0.8074 +2024-11-23 06:21:07.912667: Pseudo dice [0.8654] +2024-11-23 06:21:07.912745: Epoch time: 19.73 s +2024-11-23 06:21:09.211649: +2024-11-23 06:21:09.211865: Epoch 7882 +2024-11-23 06:21:09.211990: Current learning rate: 0.00022 +2024-11-23 06:21:27.778185: train_loss -0.8451 +2024-11-23 06:21:27.778434: val_loss -0.7977 +2024-11-23 06:21:27.778531: Pseudo dice [0.8654] +2024-11-23 06:21:27.778615: Epoch time: 18.57 s +2024-11-23 06:21:28.681731: +2024-11-23 06:21:28.681963: Epoch 7883 +2024-11-23 06:21:28.682086: Current learning rate: 0.00022 +2024-11-23 06:21:46.577212: train_loss -0.8395 +2024-11-23 06:21:46.577430: val_loss -0.7896 +2024-11-23 06:21:46.577505: Pseudo dice [0.859] +2024-11-23 06:21:46.577579: Epoch time: 17.9 s +2024-11-23 06:21:47.481237: +2024-11-23 06:21:47.481465: Epoch 7884 +2024-11-23 06:21:47.481577: Current learning rate: 0.00022 +2024-11-23 06:22:06.948459: train_loss -0.8383 +2024-11-23 06:22:06.948680: val_loss -0.7667 +2024-11-23 06:22:06.948783: Pseudo dice [0.8552] +2024-11-23 06:22:06.948860: Epoch time: 19.47 s +2024-11-23 06:22:07.852139: +2024-11-23 06:22:07.852350: Epoch 7885 +2024-11-23 06:22:07.852463: Current learning rate: 0.00022 +2024-11-23 06:22:27.187076: train_loss -0.8384 +2024-11-23 06:22:27.187322: val_loss -0.793 +2024-11-23 06:22:27.187418: Pseudo dice [0.8649] +2024-11-23 06:22:27.187505: Epoch time: 19.34 s +2024-11-23 06:22:28.100178: +2024-11-23 06:22:28.100408: Epoch 7886 +2024-11-23 06:22:28.100535: Current learning rate: 0.00022 +2024-11-23 06:22:47.612003: train_loss -0.8382 +2024-11-23 06:22:47.612246: val_loss -0.7702 +2024-11-23 06:22:47.612328: Pseudo dice [0.8491] +2024-11-23 06:22:47.612410: Epoch time: 19.51 s +2024-11-23 06:22:48.588132: +2024-11-23 06:22:48.588341: Epoch 7887 +2024-11-23 06:22:48.588453: Current learning rate: 0.00022 +2024-11-23 06:23:07.071041: train_loss -0.8446 +2024-11-23 06:23:07.071343: val_loss -0.7822 +2024-11-23 06:23:07.071424: Pseudo dice [0.8663] +2024-11-23 06:23:07.071508: Epoch time: 18.48 s +2024-11-23 06:23:07.978475: +2024-11-23 06:23:07.978701: Epoch 7888 +2024-11-23 06:23:07.978817: Current learning rate: 0.00021 +2024-11-23 06:23:26.259715: train_loss -0.8429 +2024-11-23 06:23:26.259935: val_loss -0.7768 +2024-11-23 06:23:26.260011: Pseudo dice [0.8569] +2024-11-23 06:23:26.260109: Epoch time: 18.28 s +2024-11-23 06:23:27.276419: +2024-11-23 06:23:27.276622: Epoch 7889 +2024-11-23 06:23:27.276736: Current learning rate: 0.00021 +2024-11-23 06:23:45.943096: train_loss -0.8434 +2024-11-23 06:23:45.943330: val_loss -0.783 +2024-11-23 06:23:45.943416: Pseudo dice [0.8484] +2024-11-23 06:23:45.943498: Epoch time: 18.67 s +2024-11-23 06:23:46.850716: +2024-11-23 06:23:46.850929: Epoch 7890 +2024-11-23 06:23:46.851043: Current learning rate: 0.00021 +2024-11-23 06:24:06.401854: train_loss -0.8417 +2024-11-23 06:24:06.402112: val_loss -0.7811 +2024-11-23 06:24:06.402189: Pseudo dice [0.8593] +2024-11-23 06:24:06.402269: Epoch time: 19.55 s +2024-11-23 06:24:07.311871: +2024-11-23 06:24:07.312118: Epoch 7891 +2024-11-23 06:24:07.312254: Current learning rate: 0.00021 +2024-11-23 06:24:25.056592: train_loss -0.84 +2024-11-23 06:24:25.056823: val_loss -0.7951 +2024-11-23 06:24:25.056901: Pseudo dice [0.8607] +2024-11-23 06:24:25.056995: Epoch time: 17.75 s +2024-11-23 06:24:25.961007: +2024-11-23 06:24:25.961228: Epoch 7892 +2024-11-23 06:24:25.961340: Current learning rate: 0.00021 +2024-11-23 06:24:44.759445: train_loss -0.842 +2024-11-23 06:24:44.759660: val_loss -0.7968 +2024-11-23 06:24:44.759744: Pseudo dice [0.8593] +2024-11-23 06:24:44.759824: Epoch time: 18.8 s +2024-11-23 06:24:46.095313: +2024-11-23 06:24:46.095544: Epoch 7893 +2024-11-23 06:24:46.095666: Current learning rate: 0.00021 +2024-11-23 06:25:05.505702: train_loss -0.8326 +2024-11-23 06:25:05.508144: val_loss -0.7835 +2024-11-23 06:25:05.508296: Pseudo dice [0.8542] +2024-11-23 06:25:05.508404: Epoch time: 19.41 s +2024-11-23 06:25:06.619641: +2024-11-23 06:25:06.619871: Epoch 7894 +2024-11-23 06:25:06.619989: Current learning rate: 0.0002 +2024-11-23 06:25:24.893170: train_loss -0.8444 +2024-11-23 06:25:24.898602: val_loss -0.8127 +2024-11-23 06:25:24.898757: Pseudo dice [0.8568] +2024-11-23 06:25:24.898848: Epoch time: 18.27 s +2024-11-23 06:25:25.995327: +2024-11-23 06:25:25.995559: Epoch 7895 +2024-11-23 06:25:25.995669: Current learning rate: 0.0002 +2024-11-23 06:25:45.069932: train_loss -0.8359 +2024-11-23 06:25:45.070156: val_loss -0.8019 +2024-11-23 06:25:45.070245: Pseudo dice [0.8634] +2024-11-23 06:25:45.070324: Epoch time: 19.08 s +2024-11-23 06:25:46.023927: +2024-11-23 06:25:46.024162: Epoch 7896 +2024-11-23 06:25:46.024293: Current learning rate: 0.0002 +2024-11-23 06:26:04.432330: train_loss -0.8362 +2024-11-23 06:26:04.432567: val_loss -0.807 +2024-11-23 06:26:04.432656: Pseudo dice [0.855] +2024-11-23 06:26:04.432740: Epoch time: 18.41 s +2024-11-23 06:26:05.351233: +2024-11-23 06:26:05.351475: Epoch 7897 +2024-11-23 06:26:05.351635: Current learning rate: 0.0002 +2024-11-23 06:26:23.409335: train_loss -0.8473 +2024-11-23 06:26:23.409552: val_loss -0.781 +2024-11-23 06:26:23.409637: Pseudo dice [0.8493] +2024-11-23 06:26:23.409716: Epoch time: 18.06 s +2024-11-23 06:26:24.309089: +2024-11-23 06:26:24.309295: Epoch 7898 +2024-11-23 06:26:24.309409: Current learning rate: 0.0002 +2024-11-23 06:26:43.333583: train_loss -0.8427 +2024-11-23 06:26:43.333807: val_loss -0.7828 +2024-11-23 06:26:43.333913: Pseudo dice [0.8626] +2024-11-23 06:26:43.334002: Epoch time: 19.03 s +2024-11-23 06:26:44.239339: +2024-11-23 06:26:44.239556: Epoch 7899 +2024-11-23 06:26:44.239668: Current learning rate: 0.0002 +2024-11-23 06:27:02.565091: train_loss -0.8454 +2024-11-23 06:27:02.565323: val_loss -0.8 +2024-11-23 06:27:02.565410: Pseudo dice [0.8602] +2024-11-23 06:27:02.565502: Epoch time: 18.33 s +2024-11-23 06:27:03.819828: +2024-11-23 06:27:03.820041: Epoch 7900 +2024-11-23 06:27:03.820167: Current learning rate: 0.00019 +2024-11-23 06:27:23.827354: train_loss -0.8415 +2024-11-23 06:27:23.827582: val_loss -0.7885 +2024-11-23 06:27:23.827663: Pseudo dice [0.8586] +2024-11-23 06:27:23.827763: Epoch time: 20.01 s +2024-11-23 06:27:24.742705: +2024-11-23 06:27:24.742927: Epoch 7901 +2024-11-23 06:27:24.743049: Current learning rate: 0.00019 +2024-11-23 06:27:42.676520: train_loss -0.8464 +2024-11-23 06:27:42.676796: val_loss -0.7516 +2024-11-23 06:27:42.676876: Pseudo dice [0.8459] +2024-11-23 06:27:42.676955: Epoch time: 17.93 s +2024-11-23 06:27:43.600204: +2024-11-23 06:27:43.600422: Epoch 7902 +2024-11-23 06:27:43.600544: Current learning rate: 0.00019 +2024-11-23 06:28:01.591990: train_loss -0.8385 +2024-11-23 06:28:01.592207: val_loss -0.782 +2024-11-23 06:28:01.592282: Pseudo dice [0.8665] +2024-11-23 06:28:01.592359: Epoch time: 17.99 s +2024-11-23 06:28:02.536598: +2024-11-23 06:28:02.536803: Epoch 7903 +2024-11-23 06:28:02.536946: Current learning rate: 0.00019 +2024-11-23 06:28:20.875308: train_loss -0.838 +2024-11-23 06:28:20.875553: val_loss -0.7731 +2024-11-23 06:28:20.875632: Pseudo dice [0.8557] +2024-11-23 06:28:20.875717: Epoch time: 18.34 s +2024-11-23 06:28:21.785710: +2024-11-23 06:28:21.785914: Epoch 7904 +2024-11-23 06:28:21.786025: Current learning rate: 0.00019 +2024-11-23 06:28:40.023465: train_loss -0.8401 +2024-11-23 06:28:40.023723: val_loss -0.7792 +2024-11-23 06:28:40.023808: Pseudo dice [0.8337] +2024-11-23 06:28:40.023893: Epoch time: 18.24 s +2024-11-23 06:28:40.932254: +2024-11-23 06:28:40.932463: Epoch 7905 +2024-11-23 06:28:40.932591: Current learning rate: 0.00018 +2024-11-23 06:28:59.204267: train_loss -0.8423 +2024-11-23 06:28:59.204509: val_loss -0.7896 +2024-11-23 06:28:59.204592: Pseudo dice [0.8595] +2024-11-23 06:28:59.204678: Epoch time: 18.27 s +2024-11-23 06:29:00.232325: +2024-11-23 06:29:00.232556: Epoch 7906 +2024-11-23 06:29:00.232675: Current learning rate: 0.00018 +2024-11-23 06:29:18.358678: train_loss -0.8473 +2024-11-23 06:29:18.358912: val_loss -0.7742 +2024-11-23 06:29:18.358997: Pseudo dice [0.8687] +2024-11-23 06:29:18.359082: Epoch time: 18.13 s +2024-11-23 06:29:19.263052: +2024-11-23 06:29:19.263271: Epoch 7907 +2024-11-23 06:29:19.263386: Current learning rate: 0.00018 +2024-11-23 06:29:38.772179: train_loss -0.8413 +2024-11-23 06:29:38.772445: val_loss -0.8039 +2024-11-23 06:29:38.772589: Pseudo dice [0.8667] +2024-11-23 06:29:38.772683: Epoch time: 19.51 s +2024-11-23 06:29:39.685743: +2024-11-23 06:29:39.685968: Epoch 7908 +2024-11-23 06:29:39.686329: Current learning rate: 0.00018 +2024-11-23 06:29:57.389084: train_loss -0.8414 +2024-11-23 06:29:57.389319: val_loss -0.7755 +2024-11-23 06:29:57.389404: Pseudo dice [0.8534] +2024-11-23 06:29:57.389481: Epoch time: 17.7 s +2024-11-23 06:29:58.479798: +2024-11-23 06:29:58.480007: Epoch 7909 +2024-11-23 06:29:58.480140: Current learning rate: 0.00018 +2024-11-23 06:30:17.726371: train_loss -0.8398 +2024-11-23 06:30:17.726588: val_loss -0.7864 +2024-11-23 06:30:17.726672: Pseudo dice [0.8663] +2024-11-23 06:30:17.726757: Epoch time: 19.25 s +2024-11-23 06:30:18.630645: +2024-11-23 06:30:18.630837: Epoch 7910 +2024-11-23 06:30:18.630948: Current learning rate: 0.00018 +2024-11-23 06:30:37.269255: train_loss -0.8446 +2024-11-23 06:30:37.269468: val_loss -0.7815 +2024-11-23 06:30:37.269551: Pseudo dice [0.8454] +2024-11-23 06:30:37.269631: Epoch time: 18.64 s +2024-11-23 06:30:38.174892: +2024-11-23 06:30:38.175095: Epoch 7911 +2024-11-23 06:30:38.175228: Current learning rate: 0.00017 +2024-11-23 06:30:57.086842: train_loss -0.8404 +2024-11-23 06:30:57.087107: val_loss -0.7771 +2024-11-23 06:30:57.087189: Pseudo dice [0.873] +2024-11-23 06:30:57.087273: Epoch time: 18.91 s +2024-11-23 06:30:57.993228: +2024-11-23 06:30:57.993413: Epoch 7912 +2024-11-23 06:30:57.993530: Current learning rate: 0.00017 +2024-11-23 06:31:16.114916: train_loss -0.8439 +2024-11-23 06:31:16.115151: val_loss -0.7939 +2024-11-23 06:31:16.115235: Pseudo dice [0.8587] +2024-11-23 06:31:16.115309: Epoch time: 18.12 s +2024-11-23 06:31:17.015244: +2024-11-23 06:31:17.015490: Epoch 7913 +2024-11-23 06:31:17.015610: Current learning rate: 0.00017 +2024-11-23 06:31:35.160700: train_loss -0.8406 +2024-11-23 06:31:35.160907: val_loss -0.7881 +2024-11-23 06:31:35.160989: Pseudo dice [0.8689] +2024-11-23 06:31:35.161089: Epoch time: 18.15 s +2024-11-23 06:31:36.477778: +2024-11-23 06:31:36.478002: Epoch 7914 +2024-11-23 06:31:36.478127: Current learning rate: 0.00017 +2024-11-23 06:31:55.148184: train_loss -0.8371 +2024-11-23 06:31:55.148434: val_loss -0.798 +2024-11-23 06:31:55.148516: Pseudo dice [0.8615] +2024-11-23 06:31:55.148662: Epoch time: 18.67 s +2024-11-23 06:31:56.159981: +2024-11-23 06:31:56.160202: Epoch 7915 +2024-11-23 06:31:56.160335: Current learning rate: 0.00017 +2024-11-23 06:32:14.519323: train_loss -0.8308 +2024-11-23 06:32:14.519580: val_loss -0.791 +2024-11-23 06:32:14.519659: Pseudo dice [0.8565] +2024-11-23 06:32:14.519739: Epoch time: 18.36 s +2024-11-23 06:32:15.424834: +2024-11-23 06:32:15.425040: Epoch 7916 +2024-11-23 06:32:15.425167: Current learning rate: 0.00017 +2024-11-23 06:32:34.367335: train_loss -0.8448 +2024-11-23 06:32:34.367578: val_loss -0.7747 +2024-11-23 06:32:34.367659: Pseudo dice [0.8507] +2024-11-23 06:32:34.367757: Epoch time: 18.94 s +2024-11-23 06:32:35.284271: +2024-11-23 06:32:35.284514: Epoch 7917 +2024-11-23 06:32:35.284635: Current learning rate: 0.00016 +2024-11-23 06:32:55.336001: train_loss -0.8383 +2024-11-23 06:32:55.336233: val_loss -0.7818 +2024-11-23 06:32:55.336315: Pseudo dice [0.859] +2024-11-23 06:32:55.336391: Epoch time: 20.05 s +2024-11-23 06:32:56.290716: +2024-11-23 06:32:56.290929: Epoch 7918 +2024-11-23 06:32:56.291047: Current learning rate: 0.00016 +2024-11-23 06:33:16.754169: train_loss -0.838 +2024-11-23 06:33:16.754411: val_loss -0.7966 +2024-11-23 06:33:16.754519: Pseudo dice [0.8625] +2024-11-23 06:33:16.754682: Epoch time: 20.46 s +2024-11-23 06:33:17.667667: +2024-11-23 06:33:17.667884: Epoch 7919 +2024-11-23 06:33:17.668011: Current learning rate: 0.00016 +2024-11-23 06:33:36.205553: train_loss -0.8412 +2024-11-23 06:33:36.205774: val_loss -0.7964 +2024-11-23 06:33:36.205857: Pseudo dice [0.8668] +2024-11-23 06:33:36.205939: Epoch time: 18.54 s +2024-11-23 06:33:37.106266: +2024-11-23 06:33:37.106485: Epoch 7920 +2024-11-23 06:33:37.106598: Current learning rate: 0.00016 +2024-11-23 06:33:56.033329: train_loss -0.8378 +2024-11-23 06:33:56.033544: val_loss -0.7951 +2024-11-23 06:33:56.033619: Pseudo dice [0.8577] +2024-11-23 06:33:56.033695: Epoch time: 18.93 s +2024-11-23 06:33:56.937217: +2024-11-23 06:33:56.937432: Epoch 7921 +2024-11-23 06:33:56.937541: Current learning rate: 0.00016 +2024-11-23 06:34:15.086104: train_loss -0.8372 +2024-11-23 06:34:15.086372: val_loss -0.7916 +2024-11-23 06:34:15.086458: Pseudo dice [0.8644] +2024-11-23 06:34:15.086542: Epoch time: 18.15 s +2024-11-23 06:34:15.992631: +2024-11-23 06:34:15.992851: Epoch 7922 +2024-11-23 06:34:15.992977: Current learning rate: 0.00015 +2024-11-23 06:34:33.601924: train_loss -0.8422 +2024-11-23 06:34:33.602146: val_loss -0.7848 +2024-11-23 06:34:33.602229: Pseudo dice [0.8623] +2024-11-23 06:34:33.607487: Epoch time: 17.61 s +2024-11-23 06:34:34.764160: +2024-11-23 06:34:34.764370: Epoch 7923 +2024-11-23 06:34:34.764485: Current learning rate: 0.00015 +2024-11-23 06:34:52.487184: train_loss -0.8452 +2024-11-23 06:34:52.487401: val_loss -0.8105 +2024-11-23 06:34:52.487478: Pseudo dice [0.8715] +2024-11-23 06:34:52.487551: Epoch time: 17.72 s +2024-11-23 06:34:53.393073: +2024-11-23 06:34:53.393292: Epoch 7924 +2024-11-23 06:34:53.393411: Current learning rate: 0.00015 +2024-11-23 06:35:11.072823: train_loss -0.8387 +2024-11-23 06:35:11.078211: val_loss -0.7912 +2024-11-23 06:35:11.078303: Pseudo dice [0.8639] +2024-11-23 06:35:11.078393: Epoch time: 17.68 s +2024-11-23 06:35:12.438740: +2024-11-23 06:35:12.438975: Epoch 7925 +2024-11-23 06:35:12.439106: Current learning rate: 0.00015 +2024-11-23 06:35:31.521350: train_loss -0.8438 +2024-11-23 06:35:31.521603: val_loss -0.7796 +2024-11-23 06:35:31.521684: Pseudo dice [0.8571] +2024-11-23 06:35:31.521774: Epoch time: 19.08 s +2024-11-23 06:35:32.427734: +2024-11-23 06:35:32.427944: Epoch 7926 +2024-11-23 06:35:32.428069: Current learning rate: 0.00015 +2024-11-23 06:35:50.724215: train_loss -0.8406 +2024-11-23 06:35:50.724438: val_loss -0.7647 +2024-11-23 06:35:50.724532: Pseudo dice [0.8604] +2024-11-23 06:35:50.729773: Epoch time: 18.3 s +2024-11-23 06:35:51.669145: +2024-11-23 06:35:51.669385: Epoch 7927 +2024-11-23 06:35:51.669522: Current learning rate: 0.00015 +2024-11-23 06:36:10.785415: train_loss -0.8439 +2024-11-23 06:36:10.785640: val_loss -0.8041 +2024-11-23 06:36:10.785736: Pseudo dice [0.8537] +2024-11-23 06:36:10.785815: Epoch time: 19.12 s +2024-11-23 06:36:11.706736: +2024-11-23 06:36:11.706947: Epoch 7928 +2024-11-23 06:36:11.707069: Current learning rate: 0.00014 +2024-11-23 06:36:31.182796: train_loss -0.8399 +2024-11-23 06:36:31.183031: val_loss -0.7878 +2024-11-23 06:36:31.185345: Pseudo dice [0.8711] +2024-11-23 06:36:31.185472: Epoch time: 19.48 s +2024-11-23 06:36:32.116162: +2024-11-23 06:36:32.116377: Epoch 7929 +2024-11-23 06:36:32.116489: Current learning rate: 0.00014 +2024-11-23 06:36:49.743242: train_loss -0.8499 +2024-11-23 06:36:49.743541: val_loss -0.7926 +2024-11-23 06:36:49.743625: Pseudo dice [0.8605] +2024-11-23 06:36:49.743708: Epoch time: 17.63 s +2024-11-23 06:36:50.654081: +2024-11-23 06:36:50.654286: Epoch 7930 +2024-11-23 06:36:50.654402: Current learning rate: 0.00014 +2024-11-23 06:37:08.751952: train_loss -0.8439 +2024-11-23 06:37:08.752179: val_loss -0.7965 +2024-11-23 06:37:08.752270: Pseudo dice [0.8663] +2024-11-23 06:37:08.752366: Epoch time: 18.1 s +2024-11-23 06:37:09.989852: +2024-11-23 06:37:09.990078: Epoch 7931 +2024-11-23 06:37:09.990189: Current learning rate: 0.00014 +2024-11-23 06:37:29.080420: train_loss -0.8473 +2024-11-23 06:37:29.080642: val_loss -0.7976 +2024-11-23 06:37:29.080720: Pseudo dice [0.8714] +2024-11-23 06:37:29.080813: Epoch time: 19.09 s +2024-11-23 06:37:30.104645: +2024-11-23 06:37:30.104859: Epoch 7932 +2024-11-23 06:37:30.104993: Current learning rate: 0.00014 +2024-11-23 06:37:48.774109: train_loss -0.8365 +2024-11-23 06:37:48.774373: val_loss -0.8054 +2024-11-23 06:37:48.774472: Pseudo dice [0.8672] +2024-11-23 06:37:48.774573: Epoch time: 18.67 s +2024-11-23 06:37:49.714102: +2024-11-23 06:37:49.714320: Epoch 7933 +2024-11-23 06:37:49.714442: Current learning rate: 0.00014 +2024-11-23 06:38:07.391677: train_loss -0.8425 +2024-11-23 06:38:07.391930: val_loss -0.7773 +2024-11-23 06:38:07.392041: Pseudo dice [0.8673] +2024-11-23 06:38:07.392133: Epoch time: 17.68 s +2024-11-23 06:38:08.293979: +2024-11-23 06:38:08.294174: Epoch 7934 +2024-11-23 06:38:08.294508: Current learning rate: 0.00013 +2024-11-23 06:38:26.894427: train_loss -0.8423 +2024-11-23 06:38:26.894714: val_loss -0.7998 +2024-11-23 06:38:26.894799: Pseudo dice [0.8757] +2024-11-23 06:38:26.894877: Epoch time: 18.6 s +2024-11-23 06:38:26.894946: Yayy! New best EMA pseudo Dice: 0.8649 +2024-11-23 06:38:28.147982: +2024-11-23 06:38:28.148221: Epoch 7935 +2024-11-23 06:38:28.148343: Current learning rate: 0.00013 +2024-11-23 06:38:46.641909: train_loss -0.8414 +2024-11-23 06:38:46.642130: val_loss -0.813 +2024-11-23 06:38:46.642220: Pseudo dice [0.8621] +2024-11-23 06:38:46.642317: Epoch time: 18.49 s +2024-11-23 06:38:47.968291: +2024-11-23 06:38:47.968515: Epoch 7936 +2024-11-23 06:38:47.968636: Current learning rate: 0.00013 +2024-11-23 06:39:06.329794: train_loss -0.8412 +2024-11-23 06:39:06.330029: val_loss -0.7869 +2024-11-23 06:39:06.330114: Pseudo dice [0.8585] +2024-11-23 06:39:06.330212: Epoch time: 18.36 s +2024-11-23 06:39:07.233647: +2024-11-23 06:39:07.233892: Epoch 7937 +2024-11-23 06:39:07.234023: Current learning rate: 0.00013 +2024-11-23 06:39:27.160774: train_loss -0.8432 +2024-11-23 06:39:27.161055: val_loss -0.781 +2024-11-23 06:39:27.161142: Pseudo dice [0.8624] +2024-11-23 06:39:27.161248: Epoch time: 19.93 s +2024-11-23 06:39:28.073918: +2024-11-23 06:39:28.074128: Epoch 7938 +2024-11-23 06:39:28.074239: Current learning rate: 0.00013 +2024-11-23 06:39:46.560292: train_loss -0.8559 +2024-11-23 06:39:46.560548: val_loss -0.7924 +2024-11-23 06:39:46.560633: Pseudo dice [0.8658] +2024-11-23 06:39:46.560709: Epoch time: 18.49 s +2024-11-23 06:39:47.559099: +2024-11-23 06:39:47.559311: Epoch 7939 +2024-11-23 06:39:47.559429: Current learning rate: 0.00012 +2024-11-23 06:40:06.407122: train_loss -0.8415 +2024-11-23 06:40:06.412530: val_loss -0.7884 +2024-11-23 06:40:06.412716: Pseudo dice [0.8615] +2024-11-23 06:40:06.412821: Epoch time: 18.85 s +2024-11-23 06:40:07.487719: +2024-11-23 06:40:07.487933: Epoch 7940 +2024-11-23 06:40:07.488066: Current learning rate: 0.00012 +2024-11-23 06:40:25.855859: train_loss -0.8363 +2024-11-23 06:40:25.856108: val_loss -0.788 +2024-11-23 06:40:25.856187: Pseudo dice [0.8566] +2024-11-23 06:40:25.861506: Epoch time: 18.37 s +2024-11-23 06:40:26.770802: +2024-11-23 06:40:26.771029: Epoch 7941 +2024-11-23 06:40:26.771168: Current learning rate: 0.00012 +2024-11-23 06:40:45.058575: train_loss -0.8378 +2024-11-23 06:40:45.058788: val_loss -0.7858 +2024-11-23 06:40:45.058868: Pseudo dice [0.87] +2024-11-23 06:40:45.058957: Epoch time: 18.29 s +2024-11-23 06:40:45.961868: +2024-11-23 06:40:45.962087: Epoch 7942 +2024-11-23 06:40:45.962221: Current learning rate: 0.00012 +2024-11-23 06:41:04.632156: train_loss -0.8465 +2024-11-23 06:41:04.632379: val_loss -0.787 +2024-11-23 06:41:04.632456: Pseudo dice [0.8631] +2024-11-23 06:41:04.632546: Epoch time: 18.67 s +2024-11-23 06:41:05.535134: +2024-11-23 06:41:05.535344: Epoch 7943 +2024-11-23 06:41:05.535481: Current learning rate: 0.00012 +2024-11-23 06:41:24.561291: train_loss -0.8463 +2024-11-23 06:41:24.561534: val_loss -0.7797 +2024-11-23 06:41:24.561620: Pseudo dice [0.8534] +2024-11-23 06:41:24.561711: Epoch time: 19.03 s +2024-11-23 06:41:25.565881: +2024-11-23 06:41:25.566087: Epoch 7944 +2024-11-23 06:41:25.566209: Current learning rate: 0.00011 +2024-11-23 06:41:44.928479: train_loss -0.8405 +2024-11-23 06:41:44.928713: val_loss -0.7887 +2024-11-23 06:41:44.928792: Pseudo dice [0.8542] +2024-11-23 06:41:44.928876: Epoch time: 19.36 s +2024-11-23 06:41:45.832664: +2024-11-23 06:41:45.832898: Epoch 7945 +2024-11-23 06:41:45.833020: Current learning rate: 0.00011 +2024-11-23 06:42:04.096961: train_loss -0.8469 +2024-11-23 06:42:04.097189: val_loss -0.7857 +2024-11-23 06:42:04.097280: Pseudo dice [0.8555] +2024-11-23 06:42:04.097366: Epoch time: 18.27 s +2024-11-23 06:42:05.000024: +2024-11-23 06:42:05.000236: Epoch 7946 +2024-11-23 06:42:05.000367: Current learning rate: 0.00011 +2024-11-23 06:42:23.856947: train_loss -0.8444 +2024-11-23 06:42:23.857174: val_loss -0.7926 +2024-11-23 06:42:23.857252: Pseudo dice [0.8703] +2024-11-23 06:42:23.857329: Epoch time: 18.86 s +2024-11-23 06:42:25.169575: +2024-11-23 06:42:25.169782: Epoch 7947 +2024-11-23 06:42:25.169913: Current learning rate: 0.00011 +2024-11-23 06:42:43.440861: train_loss -0.8411 +2024-11-23 06:42:43.441132: val_loss -0.7774 +2024-11-23 06:42:43.441217: Pseudo dice [0.8605] +2024-11-23 06:42:43.441306: Epoch time: 18.27 s +2024-11-23 06:42:44.383781: +2024-11-23 06:42:44.384006: Epoch 7948 +2024-11-23 06:42:44.384122: Current learning rate: 0.00011 +2024-11-23 06:43:02.148882: train_loss -0.8441 +2024-11-23 06:43:02.149115: val_loss -0.7809 +2024-11-23 06:43:02.149198: Pseudo dice [0.8622] +2024-11-23 06:43:02.149278: Epoch time: 17.77 s +2024-11-23 06:43:03.046275: +2024-11-23 06:43:03.046499: Epoch 7949 +2024-11-23 06:43:03.046616: Current learning rate: 0.00011 +2024-11-23 06:43:22.613724: train_loss -0.8447 +2024-11-23 06:43:22.613959: val_loss -0.7771 +2024-11-23 06:43:22.614067: Pseudo dice [0.8586] +2024-11-23 06:43:22.614143: Epoch time: 19.57 s +2024-11-23 06:43:23.900540: +2024-11-23 06:43:23.900768: Epoch 7950 +2024-11-23 06:43:23.900896: Current learning rate: 0.0001 +2024-11-23 06:43:41.530078: train_loss -0.8474 +2024-11-23 06:43:41.530307: val_loss -0.775 +2024-11-23 06:43:41.530389: Pseudo dice [0.8646] +2024-11-23 06:43:41.530469: Epoch time: 17.63 s +2024-11-23 06:43:42.442552: +2024-11-23 06:43:42.442803: Epoch 7951 +2024-11-23 06:43:42.442921: Current learning rate: 0.0001 +2024-11-23 06:44:01.303468: train_loss -0.8471 +2024-11-23 06:44:01.303717: val_loss -0.7805 +2024-11-23 06:44:01.303797: Pseudo dice [0.8678] +2024-11-23 06:44:01.303891: Epoch time: 18.86 s +2024-11-23 06:44:02.206523: +2024-11-23 06:44:02.206752: Epoch 7952 +2024-11-23 06:44:02.206867: Current learning rate: 0.0001 +2024-11-23 06:44:21.241610: train_loss -0.8437 +2024-11-23 06:44:21.241835: val_loss -0.7796 +2024-11-23 06:44:21.241913: Pseudo dice [0.8564] +2024-11-23 06:44:21.242125: Epoch time: 19.04 s +2024-11-23 06:44:22.138672: +2024-11-23 06:44:22.138880: Epoch 7953 +2024-11-23 06:44:22.138992: Current learning rate: 0.0001 +2024-11-23 06:44:39.924343: train_loss -0.8481 +2024-11-23 06:44:39.924546: val_loss -0.783 +2024-11-23 06:44:39.924623: Pseudo dice [0.8532] +2024-11-23 06:44:39.924695: Epoch time: 17.79 s +2024-11-23 06:44:40.826470: +2024-11-23 06:44:40.826687: Epoch 7954 +2024-11-23 06:44:40.826803: Current learning rate: 0.0001 +2024-11-23 06:44:59.950921: train_loss -0.8379 +2024-11-23 06:44:59.951207: val_loss -0.8051 +2024-11-23 06:44:59.951288: Pseudo dice [0.8695] +2024-11-23 06:44:59.951378: Epoch time: 19.13 s +2024-11-23 06:45:00.861304: +2024-11-23 06:45:00.861500: Epoch 7955 +2024-11-23 06:45:00.861615: Current learning rate: 9e-05 +2024-11-23 06:45:18.422765: train_loss -0.8454 +2024-11-23 06:45:18.423000: val_loss -0.7874 +2024-11-23 06:45:18.423085: Pseudo dice [0.8673] +2024-11-23 06:45:18.423193: Epoch time: 17.56 s +2024-11-23 06:45:19.325562: +2024-11-23 06:45:19.325785: Epoch 7956 +2024-11-23 06:45:19.325898: Current learning rate: 9e-05 +2024-11-23 06:45:37.368015: train_loss -0.8482 +2024-11-23 06:45:37.368246: val_loss -0.7553 +2024-11-23 06:45:37.368381: Pseudo dice [0.8677] +2024-11-23 06:45:37.368472: Epoch time: 18.04 s +2024-11-23 06:45:38.270462: +2024-11-23 06:45:38.270686: Epoch 7957 +2024-11-23 06:45:38.270809: Current learning rate: 9e-05 +2024-11-23 06:45:56.539488: train_loss -0.8394 +2024-11-23 06:45:56.539718: val_loss -0.7767 +2024-11-23 06:45:56.539800: Pseudo dice [0.8484] +2024-11-23 06:45:56.539880: Epoch time: 18.27 s +2024-11-23 06:45:57.444947: +2024-11-23 06:45:57.445178: Epoch 7958 +2024-11-23 06:45:57.445328: Current learning rate: 9e-05 +2024-11-23 06:46:16.126400: train_loss -0.8508 +2024-11-23 06:46:16.126704: val_loss -0.8068 +2024-11-23 06:46:16.126803: Pseudo dice [0.8744] +2024-11-23 06:46:16.126904: Epoch time: 18.68 s +2024-11-23 06:46:17.109413: +2024-11-23 06:46:17.109631: Epoch 7959 +2024-11-23 06:46:17.109744: Current learning rate: 9e-05 +2024-11-23 06:46:35.904739: train_loss -0.8404 +2024-11-23 06:46:35.904970: val_loss -0.8007 +2024-11-23 06:46:35.905050: Pseudo dice [0.8712] +2024-11-23 06:46:35.905145: Epoch time: 18.8 s +2024-11-23 06:46:36.809696: +2024-11-23 06:46:36.809924: Epoch 7960 +2024-11-23 06:46:36.810069: Current learning rate: 8e-05 +2024-11-23 06:46:56.333562: train_loss -0.8423 +2024-11-23 06:46:56.333787: val_loss -0.7851 +2024-11-23 06:46:56.333867: Pseudo dice [0.8571] +2024-11-23 06:46:56.333947: Epoch time: 19.52 s +2024-11-23 06:46:57.236527: +2024-11-23 06:46:57.236737: Epoch 7961 +2024-11-23 06:46:57.236850: Current learning rate: 8e-05 +2024-11-23 06:47:15.660507: train_loss -0.8484 +2024-11-23 06:47:15.660750: val_loss -0.8007 +2024-11-23 06:47:15.660830: Pseudo dice [0.8647] +2024-11-23 06:47:15.660919: Epoch time: 18.42 s +2024-11-23 06:47:16.581736: +2024-11-23 06:47:16.581936: Epoch 7962 +2024-11-23 06:47:16.582051: Current learning rate: 8e-05 +2024-11-23 06:47:35.369917: train_loss -0.8419 +2024-11-23 06:47:35.370139: val_loss -0.7916 +2024-11-23 06:47:35.370218: Pseudo dice [0.8611] +2024-11-23 06:47:35.370302: Epoch time: 18.79 s +2024-11-23 06:47:36.273629: +2024-11-23 06:47:36.273833: Epoch 7963 +2024-11-23 06:47:36.273962: Current learning rate: 8e-05 +2024-11-23 06:47:54.212833: train_loss -0.8299 +2024-11-23 06:47:54.218223: val_loss -0.7891 +2024-11-23 06:47:54.218404: Pseudo dice [0.8528] +2024-11-23 06:47:54.218487: Epoch time: 17.94 s +2024-11-23 06:47:55.179008: +2024-11-23 06:47:55.179225: Epoch 7964 +2024-11-23 06:47:55.179347: Current learning rate: 8e-05 +2024-11-23 06:48:12.694556: train_loss -0.8389 +2024-11-23 06:48:12.696967: val_loss -0.7812 +2024-11-23 06:48:12.697120: Pseudo dice [0.8557] +2024-11-23 06:48:12.697221: Epoch time: 17.52 s +2024-11-23 06:48:13.838905: +2024-11-23 06:48:13.839127: Epoch 7965 +2024-11-23 06:48:13.839246: Current learning rate: 8e-05 +2024-11-23 06:48:32.400153: train_loss -0.8368 +2024-11-23 06:48:32.400392: val_loss -0.766 +2024-11-23 06:48:32.400476: Pseudo dice [0.853] +2024-11-23 06:48:32.400563: Epoch time: 18.56 s +2024-11-23 06:48:33.304528: +2024-11-23 06:48:33.304731: Epoch 7966 +2024-11-23 06:48:33.304853: Current learning rate: 7e-05 +2024-11-23 06:48:52.007020: train_loss -0.8434 +2024-11-23 06:48:52.007245: val_loss -0.7701 +2024-11-23 06:48:52.007335: Pseudo dice [0.8617] +2024-11-23 06:48:52.007433: Epoch time: 18.7 s +2024-11-23 06:48:52.909197: +2024-11-23 06:48:52.909379: Epoch 7967 +2024-11-23 06:48:52.909492: Current learning rate: 7e-05 +2024-11-23 06:49:11.351031: train_loss -0.8399 +2024-11-23 06:49:11.351262: val_loss -0.7752 +2024-11-23 06:49:11.351351: Pseudo dice [0.8665] +2024-11-23 06:49:11.351428: Epoch time: 18.44 s +2024-11-23 06:49:12.768723: +2024-11-23 06:49:12.768930: Epoch 7968 +2024-11-23 06:49:12.769049: Current learning rate: 7e-05 +2024-11-23 06:49:31.656080: train_loss -0.8356 +2024-11-23 06:49:31.656343: val_loss -0.7816 +2024-11-23 06:49:31.658134: Pseudo dice [0.8559] +2024-11-23 06:49:31.658338: Epoch time: 18.89 s +2024-11-23 06:49:32.583143: +2024-11-23 06:49:32.583358: Epoch 7969 +2024-11-23 06:49:32.583475: Current learning rate: 7e-05 +2024-11-23 06:49:51.451323: train_loss -0.8444 +2024-11-23 06:49:51.451537: val_loss -0.7795 +2024-11-23 06:49:51.451613: Pseudo dice [0.8584] +2024-11-23 06:49:51.451700: Epoch time: 18.87 s +2024-11-23 06:49:52.357364: +2024-11-23 06:49:52.357563: Epoch 7970 +2024-11-23 06:49:52.357675: Current learning rate: 7e-05 +2024-11-23 06:50:11.488881: train_loss -0.8402 +2024-11-23 06:50:11.489117: val_loss -0.7737 +2024-11-23 06:50:11.489218: Pseudo dice [0.8482] +2024-11-23 06:50:11.489297: Epoch time: 19.13 s +2024-11-23 06:50:12.549397: +2024-11-23 06:50:12.549626: Epoch 7971 +2024-11-23 06:50:12.549751: Current learning rate: 6e-05 +2024-11-23 06:50:31.399565: train_loss -0.8412 +2024-11-23 06:50:31.399781: val_loss -0.791 +2024-11-23 06:50:31.399864: Pseudo dice [0.8476] +2024-11-23 06:50:31.399939: Epoch time: 18.85 s +2024-11-23 06:50:32.314539: +2024-11-23 06:50:32.314752: Epoch 7972 +2024-11-23 06:50:32.314862: Current learning rate: 6e-05 +2024-11-23 06:50:50.854622: train_loss -0.8409 +2024-11-23 06:50:50.854865: val_loss -0.7856 +2024-11-23 06:50:50.854947: Pseudo dice [0.8607] +2024-11-23 06:50:50.855030: Epoch time: 18.54 s +2024-11-23 06:50:51.763809: +2024-11-23 06:50:51.764025: Epoch 7973 +2024-11-23 06:50:51.764149: Current learning rate: 6e-05 +2024-11-23 06:51:10.468887: train_loss -0.84 +2024-11-23 06:51:10.469140: val_loss -0.786 +2024-11-23 06:51:10.469220: Pseudo dice [0.8614] +2024-11-23 06:51:10.469296: Epoch time: 18.71 s +2024-11-23 06:51:11.381706: +2024-11-23 06:51:11.381917: Epoch 7974 +2024-11-23 06:51:11.382037: Current learning rate: 6e-05 +2024-11-23 06:51:30.400525: train_loss -0.8406 +2024-11-23 06:51:30.400762: val_loss -0.7774 +2024-11-23 06:51:30.400842: Pseudo dice [0.8701] +2024-11-23 06:51:30.400935: Epoch time: 19.02 s +2024-11-23 06:51:31.305641: +2024-11-23 06:51:31.305849: Epoch 7975 +2024-11-23 06:51:31.305976: Current learning rate: 6e-05 +2024-11-23 06:51:49.506112: train_loss -0.8511 +2024-11-23 06:51:49.506326: val_loss -0.7513 +2024-11-23 06:51:49.506409: Pseudo dice [0.8579] +2024-11-23 06:51:49.506484: Epoch time: 18.2 s +2024-11-23 06:51:50.531183: +2024-11-23 06:51:50.531424: Epoch 7976 +2024-11-23 06:51:50.531543: Current learning rate: 5e-05 +2024-11-23 06:52:08.954323: train_loss -0.8417 +2024-11-23 06:52:08.954577: val_loss -0.7976 +2024-11-23 06:52:08.954677: Pseudo dice [0.8657] +2024-11-23 06:52:08.954757: Epoch time: 18.42 s +2024-11-23 06:52:09.859194: +2024-11-23 06:52:09.859423: Epoch 7977 +2024-11-23 06:52:09.859538: Current learning rate: 5e-05 +2024-11-23 06:52:28.061195: train_loss -0.8396 +2024-11-23 06:52:28.061402: val_loss -0.7877 +2024-11-23 06:52:28.061486: Pseudo dice [0.8549] +2024-11-23 06:52:28.061568: Epoch time: 18.2 s +2024-11-23 06:52:28.969360: +2024-11-23 06:52:28.969562: Epoch 7978 +2024-11-23 06:52:28.969679: Current learning rate: 5e-05 +2024-11-23 06:52:46.822395: train_loss -0.8463 +2024-11-23 06:52:46.822600: val_loss -0.7825 +2024-11-23 06:52:46.822676: Pseudo dice [0.8535] +2024-11-23 06:52:46.822754: Epoch time: 17.85 s +2024-11-23 06:52:48.337422: +2024-11-23 06:52:48.337660: Epoch 7979 +2024-11-23 06:52:48.337778: Current learning rate: 5e-05 +2024-11-23 06:53:06.541465: train_loss -0.8479 +2024-11-23 06:53:06.541685: val_loss -0.7751 +2024-11-23 06:53:06.541780: Pseudo dice [0.8558] +2024-11-23 06:53:06.541889: Epoch time: 18.2 s +2024-11-23 06:53:07.442315: +2024-11-23 06:53:07.442542: Epoch 7980 +2024-11-23 06:53:07.442661: Current learning rate: 5e-05 +2024-11-23 06:53:26.499522: train_loss -0.8461 +2024-11-23 06:53:26.499732: val_loss -0.7838 +2024-11-23 06:53:26.499816: Pseudo dice [0.8613] +2024-11-23 06:53:26.499892: Epoch time: 19.06 s +2024-11-23 06:53:27.400848: +2024-11-23 06:53:27.401071: Epoch 7981 +2024-11-23 06:53:27.401185: Current learning rate: 4e-05 +2024-11-23 06:53:44.631016: train_loss -0.8478 +2024-11-23 06:53:44.631261: val_loss -0.7821 +2024-11-23 06:53:44.631374: Pseudo dice [0.8523] +2024-11-23 06:53:44.631483: Epoch time: 17.23 s +2024-11-23 06:53:45.537445: +2024-11-23 06:53:45.537667: Epoch 7982 +2024-11-23 06:53:45.537781: Current learning rate: 4e-05 +2024-11-23 06:54:03.888933: train_loss -0.8459 +2024-11-23 06:54:03.889167: val_loss -0.7695 +2024-11-23 06:54:03.891417: Pseudo dice [0.853] +2024-11-23 06:54:03.891548: Epoch time: 18.35 s +2024-11-23 06:54:04.852528: +2024-11-23 06:54:04.852738: Epoch 7983 +2024-11-23 06:54:04.852849: Current learning rate: 4e-05 +2024-11-23 06:54:24.089610: train_loss -0.8417 +2024-11-23 06:54:24.089869: val_loss -0.8026 +2024-11-23 06:54:24.089950: Pseudo dice [0.8667] +2024-11-23 06:54:24.090036: Epoch time: 19.24 s +2024-11-23 06:54:24.993469: +2024-11-23 06:54:24.993687: Epoch 7984 +2024-11-23 06:54:24.993803: Current learning rate: 4e-05 +2024-11-23 06:54:43.682804: train_loss -0.8389 +2024-11-23 06:54:43.683015: val_loss -0.8082 +2024-11-23 06:54:43.683115: Pseudo dice [0.863] +2024-11-23 06:54:43.683192: Epoch time: 18.69 s +2024-11-23 06:54:44.569532: +2024-11-23 06:54:44.569755: Epoch 7985 +2024-11-23 06:54:44.569879: Current learning rate: 4e-05 +2024-11-23 06:55:02.813055: train_loss -0.8407 +2024-11-23 06:55:02.813270: val_loss -0.7753 +2024-11-23 06:55:02.813347: Pseudo dice [0.8547] +2024-11-23 06:55:02.813421: Epoch time: 18.24 s +2024-11-23 06:55:03.821280: +2024-11-23 06:55:03.821501: Epoch 7986 +2024-11-23 06:55:03.821629: Current learning rate: 3e-05 +2024-11-23 06:55:23.026254: train_loss -0.8449 +2024-11-23 06:55:23.026509: val_loss -0.7876 +2024-11-23 06:55:23.026613: Pseudo dice [0.8701] +2024-11-23 06:55:23.028869: Epoch time: 19.21 s +2024-11-23 06:55:24.120889: +2024-11-23 06:55:24.121105: Epoch 7987 +2024-11-23 06:55:24.121222: Current learning rate: 3e-05 +2024-11-23 06:55:43.022673: train_loss -0.8406 +2024-11-23 06:55:43.022897: val_loss -0.7911 +2024-11-23 06:55:43.022989: Pseudo dice [0.8524] +2024-11-23 06:55:43.023071: Epoch time: 18.9 s +2024-11-23 06:55:43.923968: +2024-11-23 06:55:43.924189: Epoch 7988 +2024-11-23 06:55:43.924307: Current learning rate: 3e-05 +2024-11-23 06:56:01.780713: train_loss -0.8447 +2024-11-23 06:56:01.780920: val_loss -0.7912 +2024-11-23 06:56:01.781004: Pseudo dice [0.8614] +2024-11-23 06:56:01.781084: Epoch time: 17.86 s +2024-11-23 06:56:02.672140: +2024-11-23 06:56:02.672352: Epoch 7989 +2024-11-23 06:56:02.672475: Current learning rate: 3e-05 +2024-11-23 06:56:21.481720: train_loss -0.8379 +2024-11-23 06:56:21.481945: val_loss -0.8025 +2024-11-23 06:56:21.482026: Pseudo dice [0.8716] +2024-11-23 06:56:21.482125: Epoch time: 18.81 s +2024-11-23 06:56:22.848446: +2024-11-23 06:56:22.848883: Epoch 7990 +2024-11-23 06:56:22.849020: Current learning rate: 2e-05 +2024-11-23 06:56:41.958092: train_loss -0.8387 +2024-11-23 06:56:41.958359: val_loss -0.778 +2024-11-23 06:56:41.958478: Pseudo dice [0.8636] +2024-11-23 06:56:41.958623: Epoch time: 19.11 s +2024-11-23 06:56:42.872599: +2024-11-23 06:56:42.873041: Epoch 7991 +2024-11-23 06:56:42.873194: Current learning rate: 2e-05 +2024-11-23 06:57:01.513008: train_loss -0.8467 +2024-11-23 06:57:01.513227: val_loss -0.786 +2024-11-23 06:57:01.514540: Pseudo dice [0.8546] +2024-11-23 06:57:01.514638: Epoch time: 18.64 s +2024-11-23 06:57:02.415314: +2024-11-23 06:57:02.415723: Epoch 7992 +2024-11-23 06:57:02.415862: Current learning rate: 2e-05 +2024-11-23 06:57:20.433598: train_loss -0.838 +2024-11-23 06:57:20.433805: val_loss -0.7778 +2024-11-23 06:57:20.433881: Pseudo dice [0.8588] +2024-11-23 06:57:20.433961: Epoch time: 18.02 s +2024-11-23 06:57:21.345618: +2024-11-23 06:57:21.346066: Epoch 7993 +2024-11-23 06:57:21.346205: Current learning rate: 2e-05 +2024-11-23 06:57:39.754687: train_loss -0.8411 +2024-11-23 06:57:39.754975: val_loss -0.7809 +2024-11-23 06:57:39.755070: Pseudo dice [0.8561] +2024-11-23 06:57:39.755178: Epoch time: 18.41 s +2024-11-23 06:57:40.682162: +2024-11-23 06:57:40.682634: Epoch 7994 +2024-11-23 06:57:40.682774: Current learning rate: 2e-05 +2024-11-23 06:57:58.494476: train_loss -0.8426 +2024-11-23 06:57:58.494768: val_loss -0.781 +2024-11-23 06:57:58.494849: Pseudo dice [0.8715] +2024-11-23 06:57:58.494935: Epoch time: 17.81 s +2024-11-23 06:57:59.405489: +2024-11-23 06:57:59.405942: Epoch 7995 +2024-11-23 06:57:59.406097: Current learning rate: 1e-05 +2024-11-23 06:58:17.800231: train_loss -0.8422 +2024-11-23 06:58:17.800457: val_loss -0.8016 +2024-11-23 06:58:17.800634: Pseudo dice [0.8706] +2024-11-23 06:58:17.800717: Epoch time: 18.4 s +2024-11-23 06:58:18.703490: +2024-11-23 06:58:18.703939: Epoch 7996 +2024-11-23 06:58:18.704088: Current learning rate: 1e-05 +2024-11-23 06:58:37.006774: train_loss -0.8378 +2024-11-23 06:58:37.006991: val_loss -0.7878 +2024-11-23 06:58:37.007076: Pseudo dice [0.8566] +2024-11-23 06:58:37.007154: Epoch time: 18.3 s +2024-11-23 06:58:37.914990: +2024-11-23 06:58:37.915416: Epoch 7997 +2024-11-23 06:58:37.915555: Current learning rate: 1e-05 +2024-11-23 06:58:57.464160: train_loss -0.8381 +2024-11-23 06:58:57.464374: val_loss -0.8072 +2024-11-23 06:58:57.464454: Pseudo dice [0.864] +2024-11-23 06:58:57.464541: Epoch time: 19.55 s +2024-11-23 06:58:58.367945: +2024-11-23 06:58:58.368401: Epoch 7998 +2024-11-23 06:58:58.368557: Current learning rate: 1e-05 +2024-11-23 06:59:17.624304: train_loss -0.8341 +2024-11-23 06:59:17.624545: val_loss -0.7813 +2024-11-23 06:59:17.624624: Pseudo dice [0.8549] +2024-11-23 06:59:17.624726: Epoch time: 19.26 s +2024-11-23 06:59:18.527200: +2024-11-23 06:59:18.527610: Epoch 7999 +2024-11-23 06:59:18.527751: Current learning rate: 0.0 +2024-11-23 06:59:36.834114: train_loss -0.8428 +2024-11-23 06:59:36.834339: val_loss -0.7882 +2024-11-23 06:59:36.834442: Pseudo dice [0.8663] +2024-11-23 06:59:36.834518: Epoch time: 18.31 s +2024-11-23 06:59:38.193276: Training done. +2024-11-23 06:59:38.207134: Using splits from existing split file: /sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/splits_final.json +2024-11-23 06:59:38.223072: The split file contains 5 splits. +2024-11-23 06:59:38.223197: Desired fold for training: 4 +2024-11-23 06:59:38.223254: This split has 535 training and 133 validation cases. +2024-11-23 06:59:38.224226: predicting FLAIR_006 +2024-11-23 06:59:38.232875: FLAIR_006, shape torch.Size([1, 135, 137, 192]), rank 0 +2024-11-23 06:59:50.213866: predicting FLAIR_024 +2024-11-23 06:59:50.230803: FLAIR_024, shape torch.Size([1, 123, 139, 187]), rank 0 +2024-11-23 06:59:50.809322: predicting FLAIR_030 +2024-11-23 06:59:50.855242: FLAIR_030, shape torch.Size([1, 144, 152, 202]), rank 0 +2024-11-23 06:59:51.437519: predicting FLAIR_033 +2024-11-23 06:59:51.457748: FLAIR_033, shape torch.Size([1, 135, 154, 190]), rank 0 +2024-11-23 06:59:52.038650: predicting FLAIR_035 +2024-11-23 06:59:52.053758: FLAIR_035, shape torch.Size([1, 134, 143, 188]), rank 0 +2024-11-23 06:59:52.633765: predicting FLAIR_037 +2024-11-23 06:59:52.649104: FLAIR_037, shape torch.Size([1, 132, 144, 187]), rank 0 +2024-11-23 06:59:53.229815: predicting FLAIR_044 +2024-11-23 06:59:53.239620: FLAIR_044, shape torch.Size([1, 133, 153, 199]), rank 0 +2024-11-23 06:59:53.810809: predicting FLAIR_059 +2024-11-23 06:59:53.827320: FLAIR_059, shape torch.Size([1, 135, 148, 199]), rank 0 +2024-11-23 06:59:54.407483: predicting FLAIR_060 +2024-11-23 06:59:54.423414: FLAIR_060, shape torch.Size([1, 137, 147, 197]), rank 0 +2024-11-23 06:59:55.003472: predicting FLAIR_064 +2024-11-23 06:59:55.019400: FLAIR_064, shape torch.Size([1, 140, 148, 198]), rank 0 +2024-11-23 07:00:05.747154: predicting FLAIR_070 +2024-11-23 07:00:05.755849: FLAIR_070, shape torch.Size([1, 139, 156, 178]), rank 0 +2024-11-23 07:00:06.345607: predicting FLAIR_073 +2024-11-23 07:00:06.370455: FLAIR_073, shape torch.Size([1, 128, 152, 162]), rank 0 +2024-11-23 07:00:06.974271: predicting FLAIR_077 +2024-11-23 07:00:06.986830: FLAIR_077, shape torch.Size([1, 130, 150, 187]), rank 0 +2024-11-23 07:00:07.573183: predicting FLAIR_078 +2024-11-23 07:00:07.592965: FLAIR_078, shape torch.Size([1, 136, 156, 181]), rank 0 +2024-11-23 07:00:08.205132: predicting FLAIR_079 +2024-11-23 07:00:08.244736: FLAIR_079, shape torch.Size([1, 137, 162, 183]), rank 0 +2024-11-23 07:00:08.863192: predicting FLAIR_082 +2024-11-23 07:00:08.879603: FLAIR_082, shape torch.Size([1, 129, 155, 200]), rank 0 +2024-11-23 07:00:09.462111: predicting FLAIR_084 +2024-11-23 07:00:09.469974: FLAIR_084, shape torch.Size([1, 148, 158, 188]), rank 0 +2024-11-23 07:00:10.041930: predicting FLAIR_087 +2024-11-23 07:00:10.049623: FLAIR_087, shape torch.Size([1, 134, 140, 171]), rank 0 +2024-11-23 07:00:10.640138: predicting FLAIR_092 +2024-11-23 07:00:10.660125: FLAIR_092, shape torch.Size([1, 138, 133, 179]), rank 0 +2024-11-23 07:00:11.248893: predicting FLAIR_095 +2024-11-23 07:00:11.288332: FLAIR_095, shape torch.Size([1, 137, 148, 183]), rank 0 +2024-11-23 07:00:11.901110: predicting FLAIR_097 +2024-11-23 07:00:11.908152: FLAIR_097, shape torch.Size([1, 133, 141, 181]), rank 0 +2024-11-23 07:00:12.482396: predicting FLAIR_106 +2024-11-23 07:00:12.489579: FLAIR_106, shape torch.Size([1, 126, 148, 197]), rank 0 +2024-11-23 07:00:13.079141: predicting FLAIR_108 +2024-11-23 07:00:13.110592: FLAIR_108, shape torch.Size([1, 134, 152, 184]), rank 0 +2024-11-23 07:00:13.712772: predicting FLAIR_109 +2024-11-23 07:00:13.732134: FLAIR_109, shape torch.Size([1, 129, 140, 185]), rank 0 +2024-11-23 07:00:14.363746: predicting FLAIR_117 +2024-11-23 07:00:14.383598: FLAIR_117, shape torch.Size([1, 135, 152, 179]), rank 0 +2024-11-23 07:00:15.026751: predicting FLAIR_119 +2024-11-23 07:00:15.045152: FLAIR_119, shape torch.Size([1, 125, 147, 187]), rank 0 +2024-11-23 07:00:15.678952: predicting FLAIR_122 +2024-11-23 07:00:15.685852: FLAIR_122, shape torch.Size([1, 136, 160, 174]), rank 0 +2024-11-23 07:00:16.678927: predicting FLAIR_125 +2024-11-23 07:00:16.686968: FLAIR_125, shape torch.Size([1, 135, 157, 194]), rank 0 +2024-11-23 07:00:17.302621: predicting FLAIR_126 +2024-11-23 07:00:17.344826: FLAIR_126, shape torch.Size([1, 137, 162, 188]), rank 0 +2024-11-23 07:00:17.996130: predicting FLAIR_127 +2024-11-23 07:00:18.024337: FLAIR_127, shape torch.Size([1, 137, 160, 196]), rank 0 +2024-11-23 07:00:18.751480: predicting FLAIR_130 +2024-11-23 07:00:18.763867: FLAIR_130, shape torch.Size([1, 134, 144, 174]), rank 0 +2024-11-23 07:00:19.393151: predicting FLAIR_144 +2024-11-23 07:00:19.405914: FLAIR_144, shape torch.Size([1, 140, 155, 186]), rank 0 +2024-11-23 07:00:20.013715: predicting FLAIR_147 +2024-11-23 07:00:20.020993: FLAIR_147, shape torch.Size([1, 138, 154, 183]), rank 0 +2024-11-23 07:00:21.209328: predicting FLAIR_156 +2024-11-23 07:00:21.215904: FLAIR_156, shape torch.Size([1, 129, 140, 185]), rank 0 +2024-11-23 07:00:21.805176: predicting FLAIR_167 +2024-11-23 07:00:21.882596: FLAIR_167, shape torch.Size([1, 132, 151, 184]), rank 0 +2024-11-23 07:00:22.558858: predicting FLAIR_168 +2024-11-23 07:00:22.591921: FLAIR_168, shape torch.Size([1, 140, 149, 194]), rank 0 +2024-11-23 07:00:23.182185: predicting FLAIR_173 +2024-11-23 07:00:23.212730: FLAIR_173, shape torch.Size([1, 130, 164, 187]), rank 0 +2024-11-23 07:00:23.824908: predicting FLAIR_177 +2024-11-23 07:00:23.848036: FLAIR_177, shape torch.Size([1, 127, 149, 184]), rank 0 +2024-11-23 07:00:24.449760: predicting FLAIR_186 +2024-11-23 07:00:24.473930: FLAIR_186, shape torch.Size([1, 133, 192, 152]), rank 0 +2024-11-23 07:00:24.817461: predicting FLAIR_209 +2024-11-23 07:00:24.917373: FLAIR_209, shape torch.Size([1, 137, 180, 153]), rank 0 +2024-11-23 07:00:25.246614: predicting FLAIR_213 +2024-11-23 07:00:25.253721: FLAIR_213, shape torch.Size([1, 129, 186, 148]), rank 0 +2024-11-23 07:00:25.574263: predicting FLAIR_215 +2024-11-23 07:00:25.604946: FLAIR_215, shape torch.Size([1, 136, 211, 162]), rank 0 +2024-11-23 07:00:26.461373: predicting FLAIR_225 +2024-11-23 07:00:26.467403: FLAIR_225, shape torch.Size([1, 126, 183, 137]), rank 0 +2024-11-23 07:00:26.761832: predicting FLAIR_227 +2024-11-23 07:00:26.769796: FLAIR_227, shape torch.Size([1, 134, 208, 161]), rank 0 +2024-11-23 07:00:27.622426: predicting FLAIR_228 +2024-11-23 07:00:27.630752: FLAIR_228, shape torch.Size([1, 134, 212, 153]), rank 0 +2024-11-23 07:00:28.067933: predicting FLAIR_229 +2024-11-23 07:00:28.088167: FLAIR_229, shape torch.Size([1, 126, 198, 159]), rank 0 +2024-11-23 07:00:28.537457: predicting FLAIR_232 +2024-11-23 07:00:28.551361: FLAIR_232, shape torch.Size([1, 126, 190, 151]), rank 0 +2024-11-23 07:00:28.875535: predicting FLAIR_233 +2024-11-23 07:00:28.914400: FLAIR_233, shape torch.Size([1, 123, 190, 149]), rank 0 +2024-11-23 07:00:29.289167: predicting FLAIR_237 +2024-11-23 07:00:29.307568: FLAIR_237, shape torch.Size([1, 128, 182, 138]), rank 0 +2024-11-23 07:00:29.614512: predicting FLAIR_243 +2024-11-23 07:00:29.621200: FLAIR_243, shape torch.Size([1, 127, 176, 150]), rank 0 +2024-11-23 07:00:29.943170: predicting FLAIR_246 +2024-11-23 07:00:29.958584: FLAIR_246, shape torch.Size([1, 133, 148, 188]), rank 0 +2024-11-23 07:00:30.541442: predicting FLAIR_252 +2024-11-23 07:00:30.548241: FLAIR_252, shape torch.Size([1, 129, 177, 148]), rank 0 +2024-11-23 07:00:30.848014: predicting FLAIR_260 +2024-11-23 07:00:30.854523: FLAIR_260, shape torch.Size([1, 127, 193, 152]), rank 0 +2024-11-23 07:00:31.308162: predicting FLAIR_262 +2024-11-23 07:00:31.329306: FLAIR_262, shape torch.Size([1, 147, 186, 146]), rank 0 +2024-11-23 07:00:31.638440: predicting FLAIR_264 +2024-11-23 07:00:31.651207: FLAIR_264, shape torch.Size([1, 125, 192, 153]), rank 0 +2024-11-23 07:00:31.954098: predicting FLAIR_265 +2024-11-23 07:00:31.976417: FLAIR_265, shape torch.Size([1, 129, 181, 148]), rank 0 +2024-11-23 07:00:32.283416: predicting FLAIR_268 +2024-11-23 07:00:32.316298: FLAIR_268, shape torch.Size([1, 136, 198, 159]), rank 0 +2024-11-23 07:00:32.777766: predicting FLAIR_270 +2024-11-23 07:00:32.798421: FLAIR_270, shape torch.Size([1, 135, 210, 161]), rank 0 +2024-11-23 07:00:33.665559: predicting FLAIR_280 +2024-11-23 07:00:33.673150: FLAIR_280, shape torch.Size([1, 133, 193, 149]), rank 0 +2024-11-23 07:00:34.109149: predicting FLAIR_286 +2024-11-23 07:00:34.117661: FLAIR_286, shape torch.Size([1, 141, 202, 159]), rank 0 +2024-11-23 07:00:34.553631: predicting FLAIR_288 +2024-11-23 07:00:34.561514: FLAIR_288, shape torch.Size([1, 131, 158, 194]), rank 0 +2024-11-23 07:00:35.140992: predicting FLAIR_289 +2024-11-23 07:00:35.173081: FLAIR_289, shape torch.Size([1, 122, 183, 143]), rank 0 +2024-11-23 07:00:35.479904: predicting FLAIR_294 +2024-11-23 07:00:35.492023: FLAIR_294, shape torch.Size([1, 124, 184, 146]), rank 0 +2024-11-23 07:00:35.813175: predicting FLAIR_295 +2024-11-23 07:00:35.845845: FLAIR_295, shape torch.Size([1, 130, 177, 153]), rank 0 +2024-11-23 07:00:36.181013: predicting FLAIR_298 +2024-11-23 07:00:36.188478: FLAIR_298, shape torch.Size([1, 135, 193, 157]), rank 0 +2024-11-23 07:00:36.653183: predicting FLAIR_302 +2024-11-23 07:00:36.671404: FLAIR_302, shape torch.Size([1, 139, 187, 158]), rank 0 +2024-11-23 07:00:36.980812: predicting FLAIR_303 +2024-11-23 07:00:37.016772: FLAIR_303, shape torch.Size([1, 134, 188, 150]), rank 0 +2024-11-23 07:00:37.348207: predicting FLAIR_308 +2024-11-23 07:00:37.359394: FLAIR_308, shape torch.Size([1, 125, 184, 147]), rank 0 +2024-11-23 07:00:37.707096: predicting FLAIR_310 +2024-11-23 07:00:37.726210: FLAIR_310, shape torch.Size([1, 136, 156, 192]), rank 0 +2024-11-23 07:00:38.308635: predicting FLAIR_316 +2024-11-23 07:00:38.314789: FLAIR_316, shape torch.Size([1, 120, 179, 142]), rank 0 +2024-11-23 07:00:38.608316: predicting FLAIR_319 +2024-11-23 07:00:38.615077: FLAIR_319, shape torch.Size([1, 139, 183, 149]), rank 0 +2024-11-23 07:00:38.927170: predicting FLAIR_322 +2024-11-23 07:00:38.956629: FLAIR_322, shape torch.Size([1, 129, 198, 156]), rank 0 +2024-11-23 07:00:39.405754: predicting FLAIR_334 +2024-11-23 07:00:39.423250: FLAIR_334, shape torch.Size([1, 123, 149, 188]), rank 0 +2024-11-23 07:00:39.998644: predicting FLAIR_338 +2024-11-23 07:00:40.012116: FLAIR_338, shape torch.Size([1, 127, 184, 147]), rank 0 +2024-11-23 07:00:40.339617: predicting FLAIR_341 +2024-11-23 07:00:40.347035: FLAIR_341, shape torch.Size([1, 131, 198, 160]), rank 0 +2024-11-23 07:00:40.787608: predicting FLAIR_345 +2024-11-23 07:00:40.807658: FLAIR_345, shape torch.Size([1, 130, 153, 189]), rank 0 +2024-11-23 07:00:41.393370: predicting FLAIR_354 +2024-11-23 07:00:41.440608: FLAIR_354, shape torch.Size([1, 136, 158, 191]), rank 0 +2024-11-23 07:00:42.030573: predicting FLAIR_358 +2024-11-23 07:00:42.037598: FLAIR_358, shape torch.Size([1, 138, 156, 185]), rank 0 +2024-11-23 07:00:42.609362: predicting FLAIR_370 +2024-11-23 07:00:42.616699: FLAIR_370, shape torch.Size([1, 126, 148, 178]), rank 0 +2024-11-23 07:00:43.193281: predicting FLAIR_372 +2024-11-23 07:00:43.199201: FLAIR_372, shape torch.Size([1, 125, 140, 175]), rank 0 +2024-11-23 07:00:43.772220: predicting FLAIR_375 +2024-11-23 07:00:43.779361: FLAIR_375, shape torch.Size([1, 138, 147, 187]), rank 0 +2024-11-23 07:00:44.370616: predicting FLAIR_383 +2024-11-23 07:00:44.377589: FLAIR_383, shape torch.Size([1, 130, 148, 189]), rank 0 +2024-11-23 07:00:44.954539: predicting FLAIR_388 +2024-11-23 07:00:44.961727: FLAIR_388, shape torch.Size([1, 128, 148, 184]), rank 0 +2024-11-23 07:00:45.541243: predicting FLAIR_390 +2024-11-23 07:00:45.561318: FLAIR_390, shape torch.Size([1, 131, 151, 187]), rank 0 +2024-11-23 07:00:46.150192: predicting FLAIR_393 +2024-11-23 07:00:46.157367: FLAIR_393, shape torch.Size([1, 138, 158, 166]), rank 0 +2024-11-23 07:00:46.729023: predicting FLAIR_394 +2024-11-23 07:00:46.734801: FLAIR_394, shape torch.Size([1, 122, 147, 170]), rank 0 +2024-11-23 07:00:47.335273: predicting FLAIR_399 +2024-11-23 07:00:47.352933: FLAIR_399, shape torch.Size([1, 137, 154, 172]), rank 0 +2024-11-23 07:00:47.961194: predicting FLAIR_403 +2024-11-23 07:00:47.981418: FLAIR_403, shape torch.Size([1, 137, 198, 161]), rank 0 +2024-11-23 07:00:48.853718: predicting FLAIR_406 +2024-11-23 07:00:48.874751: FLAIR_406, shape torch.Size([1, 130, 187, 149]), rank 0 +2024-11-23 07:00:49.190406: predicting FLAIR_410 +2024-11-23 07:00:49.211520: FLAIR_410, shape torch.Size([1, 140, 190, 150]), rank 0 +2024-11-23 07:00:49.528619: predicting FLAIR_411 +2024-11-23 07:00:49.536245: FLAIR_411, shape torch.Size([1, 142, 192, 154]), rank 0 +2024-11-23 07:00:49.867041: predicting FLAIR_420 +2024-11-23 07:00:49.874931: FLAIR_420, shape torch.Size([1, 133, 190, 166]), rank 0 +2024-11-23 07:00:50.477199: predicting FLAIR_421 +2024-11-23 07:00:50.493616: FLAIR_421, shape torch.Size([1, 142, 198, 147]), rank 0 +2024-11-23 07:00:50.949283: predicting FLAIR_426 +2024-11-23 07:00:50.993606: FLAIR_426, shape torch.Size([1, 141, 163, 197]), rank 0 +2024-11-23 07:00:51.591172: predicting FLAIR_440 +2024-11-23 07:00:51.599321: FLAIR_440, shape torch.Size([1, 138, 174, 150]), rank 0 +2024-11-23 07:00:51.893815: predicting FLAIR_442 +2024-11-23 07:00:51.901505: FLAIR_442, shape torch.Size([1, 137, 193, 156]), rank 0 +2024-11-23 07:00:52.366205: predicting FLAIR_449 +2024-11-23 07:00:52.382808: FLAIR_449, shape torch.Size([1, 139, 203, 163]), rank 0 +2024-11-23 07:00:53.246101: predicting FLAIR_457 +2024-11-23 07:00:53.253160: FLAIR_457, shape torch.Size([1, 127, 184, 152]), rank 0 +2024-11-23 07:00:53.548352: predicting FLAIR_460 +2024-11-23 07:00:53.555955: FLAIR_460, shape torch.Size([1, 134, 193, 154]), rank 0 +2024-11-23 07:00:54.001183: predicting FLAIR_473 +2024-11-23 07:00:54.007946: FLAIR_473, shape torch.Size([1, 137, 147, 182]), rank 0 +2024-11-23 07:00:54.588455: predicting FLAIR_483 +2024-11-23 07:00:54.596144: FLAIR_483, shape torch.Size([1, 130, 158, 195]), rank 0 +2024-11-23 07:00:55.167651: predicting FLAIR_486 +2024-11-23 07:00:55.175851: FLAIR_486, shape torch.Size([1, 141, 162, 196]), rank 0 +2024-11-23 07:00:55.747735: predicting FLAIR_493 +2024-11-23 07:00:55.758709: FLAIR_493, shape torch.Size([1, 133, 146, 183]), rank 0 +2024-11-23 07:00:56.337718: predicting FLAIR_498 +2024-11-23 07:00:56.358107: FLAIR_498, shape torch.Size([1, 141, 157, 182]), rank 0 +2024-11-23 07:00:56.961343: predicting FLAIR_513 +2024-11-23 07:00:56.969231: FLAIR_513, shape torch.Size([1, 139, 152, 192]), rank 0 +2024-11-23 07:00:57.575188: predicting FLAIR_515 +2024-11-23 07:00:57.598644: FLAIR_515, shape torch.Size([1, 132, 145, 189]), rank 0 +2024-11-23 07:00:58.216219: predicting FLAIR_519 +2024-11-23 07:00:58.235546: FLAIR_519, shape torch.Size([1, 118, 139, 173]), rank 0 +2024-11-23 07:00:58.861205: predicting FLAIR_525 +2024-11-23 07:00:58.886385: FLAIR_525, shape torch.Size([1, 131, 148, 189]), rank 0 +2024-11-23 07:00:59.498203: predicting FLAIR_537 +2024-11-23 07:00:59.525676: FLAIR_537, shape torch.Size([1, 136, 147, 194]), rank 0 +2024-11-23 07:01:00.345055: predicting FLAIR_542 +2024-11-23 07:01:00.351395: FLAIR_542, shape torch.Size([1, 130, 152, 179]), rank 0 +2024-11-23 07:01:00.942857: predicting FLAIR_547 +2024-11-23 07:01:00.948968: FLAIR_547, shape torch.Size([1, 122, 146, 191]), rank 0 +2024-11-23 07:01:01.836966: predicting FLAIR_556 +2024-11-23 07:01:01.845035: FLAIR_556, shape torch.Size([1, 133, 164, 203]), rank 0 +2024-11-23 07:01:03.636131: predicting FLAIR_561 +2024-11-23 07:01:03.643971: FLAIR_561, shape torch.Size([1, 136, 152, 194]), rank 0 +2024-11-23 07:01:05.937451: predicting FLAIR_575 +2024-11-23 07:01:05.949621: FLAIR_575, shape torch.Size([1, 144, 155, 192]), rank 0 +2024-11-23 07:01:06.566825: predicting FLAIR_577 +2024-11-23 07:01:06.598596: FLAIR_577, shape torch.Size([1, 143, 155, 183]), rank 0 +2024-11-23 07:01:07.207152: predicting FLAIR_578 +2024-11-23 07:01:07.214575: FLAIR_578, shape torch.Size([1, 135, 160, 202]), rank 0 +2024-11-23 07:01:07.794219: predicting FLAIR_579 +2024-11-23 07:01:07.801193: FLAIR_579, shape torch.Size([1, 137, 154, 182]), rank 0 +2024-11-23 07:01:08.379734: predicting FLAIR_581 +2024-11-23 07:01:08.399615: FLAIR_581, shape torch.Size([1, 132, 152, 180]), rank 0 +2024-11-23 07:01:08.979735: predicting FLAIR_587 +2024-11-23 07:01:08.987338: FLAIR_587, shape torch.Size([1, 137, 157, 204]), rank 0 +2024-11-23 07:01:10.476517: predicting FLAIR_593 +2024-11-23 07:01:10.483107: FLAIR_593, shape torch.Size([1, 136, 150, 195]), rank 0 +2024-11-23 07:01:12.205538: predicting FLAIR_595 +2024-11-23 07:01:12.213943: FLAIR_595, shape torch.Size([1, 143, 155, 213]), rank 0 +2024-11-23 07:01:13.942182: predicting FLAIR_606 +2024-11-23 07:01:13.949430: FLAIR_606, shape torch.Size([1, 136, 155, 199]), rank 0 +2024-11-23 07:01:14.770649: predicting FLAIR_612 +2024-11-23 07:01:14.777933: FLAIR_612, shape torch.Size([1, 130, 147, 186]), rank 0 +2024-11-23 07:01:15.374048: predicting FLAIR_617 +2024-11-23 07:01:15.380567: FLAIR_617, shape torch.Size([1, 133, 151, 191]), rank 0 +2024-11-23 07:01:15.984531: predicting FLAIR_618 +2024-11-23 07:01:16.000531: FLAIR_618, shape torch.Size([1, 136, 151, 202]), rank 0 +2024-11-23 07:01:16.589386: predicting FLAIR_619 +2024-11-23 07:01:16.609084: FLAIR_619, shape torch.Size([1, 132, 152, 191]), rank 0 +2024-11-23 07:01:17.705447: predicting FLAIR_621 +2024-11-23 07:01:17.711856: FLAIR_621, shape torch.Size([1, 130, 137, 173]), rank 0 +2024-11-23 07:01:18.302691: predicting FLAIR_622 +2024-11-23 07:01:18.325331: FLAIR_622, shape torch.Size([1, 125, 151, 194]), rank 0 +2024-11-23 07:01:20.138965: predicting FLAIR_624 +2024-11-23 07:01:20.146369: FLAIR_624, shape torch.Size([1, 131, 151, 201]), rank 0 +2024-11-23 07:01:21.752702: predicting FLAIR_629 +2024-11-23 07:01:21.759288: FLAIR_629, shape torch.Size([1, 128, 155, 196]), rank 0 +2024-11-23 07:01:23.060199: predicting FLAIR_632 +2024-11-23 07:01:23.067801: FLAIR_632, shape torch.Size([1, 137, 163, 208]), rank 0 +2024-11-23 07:01:23.670449: predicting FLAIR_633 +2024-11-23 07:01:23.690987: FLAIR_633, shape torch.Size([1, 128, 135, 189]), rank 0 +2024-11-23 07:01:24.303487: predicting FLAIR_655 +2024-11-23 07:01:24.329526: FLAIR_655, shape torch.Size([1, 131, 145, 196]), rank 0 +2024-11-23 07:01:52.824974: Validation complete +2024-11-23 07:01:52.825863: Mean Validation Dice: 0.7939505654800686 diff --git a/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/plans.json b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/plans.json new file mode 100644 index 0000000000000000000000000000000000000000..b073e86c8e6c7284ceb79ee9cd5cd3699c119911 --- /dev/null +++ b/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/plans.json @@ -0,0 +1,345 @@ +{ + "dataset_name": "Dataset004_WML", + "plans_name": "nnUNetPlans", + "original_median_spacing_after_transp": [ + 1.0, + 0.9000000059604645, + 0.9000000059604645 + ], + "original_median_shape_after_transp": [ + 144, + 177, + 190 + ], + "image_reader_writer": "SimpleITKIO", + "transpose_forward": [ + 2, + 0, + 1 + ], + "transpose_backward": [ + 1, + 2, + 0 + ], + "configurations": { + "2d": { + "data_identifier": "nnUNetPlans_2d", + "preprocessor_name": "DefaultPreprocessor", + "batch_size": 106, + "patch_size": [ + 160, + 192 + ], + "median_image_size_in_voxels": [ + 154.0, + 185.0 + ], + "spacing": [ + 0.9000000059604645, + 0.9000000059604645 + ], + "normalization_schemes": [ + "ZScoreNormalization" + ], + "use_mask_for_norm": [ + true + ], + "resampling_fn_data": "resample_data_or_seg_to_shape", + "resampling_fn_seg": "resample_data_or_seg_to_shape", + "resampling_fn_data_kwargs": { + "is_seg": false, + "order": 3, + "order_z": 0, + "force_separate_z": null + }, + "resampling_fn_seg_kwargs": { + "is_seg": true, + "order": 1, + "order_z": 0, + 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